integrating faces and fingerprints for personal identification. an automatic personal identification system based solely on fingerprints or faces is often not able to meet the system performance requirements. face recognition is fast but not extremely reliable, while fingerprint verification is reliable but inefficient in database retrieval. we have developed a prototype biometric system which integrates faces and fingerprints. the system overcomes the limitations of face recognition systems as well as fingerprint verification systems. the integrated prototype system operates in the identification mode with an admissible response time. the identity established by the system is more reliable than the identity established by a face recognition system. in addition, the proposed decision fusion scheme enables performance improvement by integrating multiple cues with different confidence measures. experimental results demonstrate that our system performs very well. it meets the response time as well as the accuracy requirements.
optimising the complete image feature extraction chain. the hypothesis verification stage of the traditional image processing approach, consisting of low, medium, and high level processing, will suffer if the set of low level features extracted are of poor quality. we investigate the optimisation of the feature extraction chain by using genetic algorithms. the fitness function is a performance measure which reflects the quality of an extracted set of features. we will present some results and compare them with a hill-climbing approach.
3d shape recovery of smooth surfaces: dropping the fixed viewpoint assumption. we present a new method for recovering the 3d shape of a featureless smooth surface from three or more calibrated images illuminated by different light sources (three of them are independent). this method is unique in its ability to handle images taken from unconstrained perspective viewpoints and unconstrained illumination directions. the correspondence between such images is hard to compute and no other known method can handle this problem locally from a small number of images. our method combines geometric and photometric information in order to recover dense correspondence between the images and accurately computes the 3d shape. only a single pass starting at one point and local computation are used. this is in contrast to methods that use the occluding contours recovered from many images to initialize and constrain an optimization process. the output of our method can be used to initialize such processes. in the special case of fixed viewpoint, the proposed method becomes a new perspective photometric stereo algorithm. nevertheless, the introduction of the multiview setup, self-occlusions, and regions close to the occluding boundaries are better handled, and the method is more robust to noise than photometric stereo. experimental results are presented for simulated and real images.
a real-time large disparity range stereo-system using fpgas. in this paper, we discuss the design and implementation of a field-programmable gate array (fpga) based stereo depth measurement system that is capable of handling a very large disparity range. the system performs rectification of the input video stream and a left-right consistency check to improve the accuracy of the results and generates subpixel disparities at 30 frames/second on 480 × 640 images. the system is based on the local weighted phase- correlation algorithm [9] which estimates disparity using a multi-scale and multi-orientation approach. though fpgas are ideal devices to exploit the inherent parallelism in many computer vision algorithms, they have a finite resource capacity which poses a challenge when adapting a system to deal with large image sizes or disparity ranges. in this work, we take advantage of the temporal information available in a video sequence to design a novel architecture for the correlation unit to achieve correlation over a large range while keeping the resource utilisation very low as compared to a naive approach of designing a correlation unit in hardware.
a linear algorithm for motion from three weak perspective images using euler angles. in this paper, we describe a new simple linear algorithm for motion and structure from three weak perspective projections using euler angles. we first determine the epipolar equation between each pair of images, which determines the first and third euler angles for the rotation between that pair of images, leaving only the second euler angle undetermined. in the next step, combining the three rotations results in a very simple linear algorithm to determine the second euler angles, up to a necker reversal. experimental results on synthetic and real images are presented. the degenerate cases are discussed. the program can be ftped from http://www.cv.cs.ritsumei.ac.jp/noriko/motion.html.
viewpoint determination of image by interpolation over sparse samples. we address the problem of determining the viewpoint of an image without referencing to or estimating explicitly the 3-d structure pictured in the image. used for reference are instead a number of sample snapshots of the scene, each supplied with the associated viewpoint. by viewing image and its associated viewpoint as the input and output of a function, and the reference snapshot-viewpoint pairs as input-output samples of that function, we have a natural formulation of the problem as an interpolation one. the interpolation formulation allows imaging details like camera intrinsic parameters to be unknown, and the specification of the desired viewpoint to be not necessarily in metric terms. we describe an interpolation-based mechanism that determines the viewpoint of any given input image, which has the property that it fits all the given input-output reference samples exactly. experimental results on benchmarking image datasets show that the mechanism is effective in reaching quality viewpoint solution even with only a few reference snapshots.
an integrated model for evaluating the amount of data required for reliable recognition. many recognition procedures rely on the consistency of a subset of data features with a hypothesis as the sufficient evidence to the presence of the corresponding object. we analyze here the performance of such procedures, using a probabilistic model, and provide expressions for the sufficient size of such data subsets, that, if consistent, guarantee the validity of the hypotheses with arbitrary confidence. we focus on 2d objects and the affine transformation class, and provide, for the first time, an integrated model which takes into account the shape of the objects involved, the accuracy of the data collected, the clutter present in the scene, the class of the transformations involved, the accuracy of the localization, and the confidence we would like to have in our hypotheses. interestingly, it turns out that most of these factors can be quantified cumulatively by one parameter, denoted "effective similarity," which largely determines the sufficient subset size. the analysis is based on representing the class of instances corresponding to a model object and a group of transformations, as members of a metric space, and quantifying the variation of the instances by a metric cover.
script and language identification from document images. in this paper we present a detailed review of current script and language identification techniques. the main criticism of the existing techniques is that most of them rely on character segmentation. we go on to present a new method based on texture analysis for script identification which does not require character segmentation. a uniform text block on which texture analysis can be performed is produced from a document image via simple processing. multiple channel (gabor) filters and grey level co-occurrence matrices are used in independent experiments in order to extract texture features. classification of test documents is made based on the features of training documents using the k-nn classifier. initial results of over 95% accuracy on the classification of 105 test documents from 7 languages are very promising. the method shows robustness with respect to noise, the presence of foreign characters or numerals, and can be applied to very small amounts of text.
similarity matching. with complex multimedia data, wesee the emergence of database systems in which the fundamental operation is similarity assessment. before database issues can be addressed, it is necessary to give a definition of similarity as an operation. in this paper, we develop a similarity measure, based on fuzzy logic, that exhibits several features that match experimental findings in humans. the model is dubbed fuzzy feature contrast (ffc) and is an extension to a more general domain of the feature contrast model due to tversky. we show how the ffc model can be used to model similarity assessment from fuzzy judgment of properties, and we address the use of fuzzy measures to deal with dependencies among the properties.
online updating appearance generative mixture model for meanshift tracking. this paper proposes an appearance generative mixture model based on key frames for meanshift tracking. meanshift tracking algorithm tracks an object by maximizing the similarity between the histogram in tracking window and a static histogram acquired at the beginning of tracking. the tracking therefore could fail if the appearance of the object varies substantially. in this paper, we assume the key appearances of the object can be acquired before tracking and the manifold of the object appearance can be approximated by piece-wise linear combination of these key appearances in histogram space. the generative process is described by a bayesian graphical model. an online em algorithm is proposed to estimate the model parameters from the observed histogram in the tracking window and to update the appearance histogram. we applied this approach to track human head motion and to infer the head pose simultaneously in videos. experiments verify that our online histogram generative model constrained by key appearance histograms alleviates the drifting problem often encountered in tracking with online updating, that the enhanced meanshift algorithm is capable of tracking object of varying appearances more robustly and accurately, and that our tracking algorithm can infer additional information such as the object poses.
3d shape and motion analysis from image blur and smear: a unified approach. this paper addresses 3d shape recovery and motion estimation using a realistic camera model with an aperture and a shutter. the spatial blur and temporal smear effects induced by the camera's finite aperture and shutter speed are used for inferring both the shape and motion of the imaged objects.
histogram features-based fisher linear discriminant for face detection. the face pattern is described by pairs of template-based histogram and fisher projection orientation under the framework of adaboost learning in this paper. we assume that a set of templates are available first. to avoid making strong assumptions about distributional structure while still retaining good properties for estimation, the classical statistical model, histogram, is used to summarize the response of each template. by introducing a novel “integral histogram image”, we can compute histogram rapidly. then, we turn to fisher linear discriminant for each template to project histogram from d-dimensional subspace to one-dimensional subspace. best features, used to describe face pattern, are selected by adaboost learning. the results of experiments demonstrate that the selected features are much more powerful to represent the face pattern than the simple rectangle features used by viola and jones and some variants.
eye correction using correlation information. this paper proposes a novel eye detection method using the mct-based pattern correlation. the proposed method detects the face by the mct-based adaboost face detector over the input image and then detects two eyes by the mct-based adaboost eye detector over the eye regions. sometimes, we have some incorrectly detected eyes due to the limited detection capability of the eye detector. to reduce the falsely detected eyes, we propose a novel eye verification method that employs the mct-based pattern correlation map. we verify whether the detected eye patch is eye or non-eye depending on the existence of a noticeable peak. when one eye is correctly detected and the other eye is falsely detected, we can correct the falsely detected eye using the peak position of the correlation map of the correctly detected eye. experimental results show that the eye detection rate of the proposed method is 98.7% and 98.8% on the bern images and ar-564 images.
probability hypothesis density approach for multi-camera multi-object tracking. object tracking with multiple cameras is more efficient than tracking with one camera. in this paper, we propose a multiple-camera multiple-object tracking system that can track 3d object locations even when objects are occluded at cameras. our system tracks objects and fuses data from multiple cameras by using the probability hypothesis density filter. this method avoids data association between observations and states of objects, and tracks multiple objects in single-object state space. hence, it has lower computation than methods using joint state space. moreover, our system can track varying number of objects. the results demonstrate that our method has a high reliability when tracking 3d locations of objects.
adaptive multiple object tracking using colour and segmentation cues. we consider the problem of reliably tracking multiple objects in video, such as people moving through a shopping mall or airport. in order to mitigate difficulties arising as a result of object occlusions, mergers and changes in appearance, we adopt an integrative approach in which multiple cues are exploited. object tracking is formulated as a bayesian parameter estimation problem. the object model used in computing the likelihood function is incrementally updated. key to the approach is the use of a background subtraction process to deliver foreground segmentations. this enables the object colour model to be constructed using weights derived from a distance transform operating over foreground regions. results from foreground segmentation are also used to gain improved localisation of the object within a particle filter framework. we demonstrate the effectiveness of the approach by tracking multiple objects through videos obtained from the caviar dataset.
gender classification based on fusion of multi-view gait sequences. in this paper, we present a new method for gender classification based on fusion of multi-view gait sequences. for each silhouette of gait sequences, we first use a simple method to divide the silhouette into 7 (for 90 degree, i.e. fronto-parallel view) or 5 (for 0 and 180 degree, i.e. front view and back view) parts, and then fit ellipses to each of the regions. next, the features are extracted from each sequence by computing the ellipse parameters. for each view angle, every subject's features are normalized and combined as a feature vector. the combination of feature vector contains enough information to perform well on gender recognition. sum rule and svm are applied to fuse the similarity measures from 0°, 90°, and 180°. we carried our experiments on casia gait database, one of the largest gait databases as we know, and achieved the classification accuracy of 89.5%.
synthesis of exaggerative caricature with inter and intra correlations. we developed a novel system consisting of two modules, statistics-based synthesis and non-photorealistic rendering (npr), to synthesize caricatures of exaggerated facial features and other particular characteristics, such as beards or nevus. the statistics-based synthesis module can exaggerate shapes and positions of facial features based on non-linear exaggerative rates determined automatically. instead of comparing only the inter relationship between features of different subjects at the existing methods, our synthesis module applies both inter and intra (i.e. comparisons between facial features of the same subject) relationships to make the synthesized exaggerative shape more contrastive. subsequently, the npr module generates a line-drawing sketch of original face, and then the sketch is warped to an exaggerative style with synthesized shape points. the experimental results demonstrate that this system can automatically, and effectively, exaggerate facial features, thereby generating corresponding facial caricatures.
combined object detection and segmentation by using space-time patches. this paper presents a method for classifying the direction of movement and for segmenting objects simultaneously using features of space-time patches. our approach uses vector quantization to classify the direction of movement of an object and to estimate its centroid by referring to a codebook of the space-time patch feature, which is generated from multiple learning samples. we segmented the objects' regions based on the probability calculated from the mask images of the learning samples by using the estimated centroid of the object. even though occlusions occur when multiple objects overlap in different directions of movement, our method detects objects individually because their direction of movement is classified. experimental results show that object detection is more accurate with our method than with the conventional method, which is only based on appearance features.
image assimilation for motion estimation of atmospheric layers with shallow-water model. the complexity of dynamical laws governing 3d atmospheric flows associated to incomplete and noisy observations makes very difficult the recovery of atmospheric dynamics from satellite images sequences. in this paper, we face the challenging problem of joint estimation of time-consistent horizontal motion fields and pressure maps at various atmospheric depths. based on a vertical decomposition of the atmosphere, we propose a dense motion estimator relying on a multi-layer dynamical model. noisy and incomplete pressure maps obtained from satellite images are reconstructed according to shallow-water model on each cloud layer using a framework derived from data assimilation. while reconstructing dense pressure maps, this variational process estimates time-consistent horizontal motion fields related to the multi-layer model. the proposed approach is validated on a synthetic example and applied to a real world meteorological satellite image sequence.
an fpga-based smart camera for gesture recognition in hci applications. smart camera is a camera that can not only see but also think and act. a smart camera is an embedded vision system which captures and processes image to extract application-specific information in real time. the brain of a smart camera is a special processing module that performs application specific information processing. the design of a smart camera as an embedded system is challenging because video processing has insatiable demand for performance and power, but at the same time embedded systems place considerable constraints on the design. we present our work to develop gesturecam, an fpga-based smart camera built from scratch that can recognize simple hand gestures. the first completed version of gesturecam has shown promising real-time performance and is being tested in several desktop hci (human computer interface) applications.
real-time and marker-free 3d motion capture for home entertainment oriented applications. we present an automated system for real-time marker-free motion capture from two calibrated webcams. for fast 3d shape and skin reconstructions, we extend shape-from-silhouette algorithms. the motion capture system is based on simple and fast heuristics to increase the efficiency. multi-modal scheme using both shape and skin-parts analysis, temporal coherence, and human anthropometric constraints are adopted to increase the robustness. thanks to fast algorithms, low-cost cameras and the fact that the system runs on a single computer, our system is perfectly suitable for home entertainment device. results on real video sequences demonstrate our approach efficiency.
an efficient method for text detection in video based on stroke width similarity. text appearing in video provides semantic knowledge and significant information for video indexing and retrieval system. this paper proposes an effective method for text detection in video based on the similarity in stroke width of text (which is defined as the distance between two edges of a stroke). from the observation that text regions can be characterized by a dominant fixed stroke width, edge detection with local adaptive thresholds is first devised to keep text- while reducing background-regions. second, morphological dilation operator with adaptive structuring element size determined by stroke width value is exploited to roughly localize text regions. finally, to reduce false alarm and refine text location, a new multi-frame refinement method is applied. experimental results show that the proposed method is not only robust to different levels of background complexity, but also effective to different fonts (size, color) and languages of text.
user-guided shape from shading to reconstruct fine details from a single photograph. many real objects, such as faces, sculptures, or low-reliefs are composed of many detailed parts that can not be easily modeled by an artist nor by 3d scanning. in this paper, we propose a new shape from shading (sfs) approach to rapidly model details of these objects such as wrinkles and reliefs of surfaces from one photograph. the method first determines the surface's flat areas in the photograph. then, it constructs a graph of relative altitudes between each of these flat areas. we circumvent the ill-posed problem of shape from shading by having the user set if some of these flat areas are a local maximum or a local minimum; additional points can be added by the user (e.g. at discontinuous creases) - this is the only user input. we use an intuitive mass-spring based minimization to determine the final position of these flat areas and a fast-marching method to generate the surface. this process can be iterated until the user is satisfied with the resulting surface. we illustrate our approach on real faces and low-relief photographs.
unsupervised identification of multiple objects of interest from multiple images: discover. given a collection of images of offices, what would we say we see in the images? the objects of interest are likely to be monitors, keyboards, phones, etc. such identification of the foreground in a scene is important to avoid distractions caused by background clutter and facilitates better understanding of the scene. it is crucial for such an identification to be unsupervised to avoid extensive human labeling as well as biases induced by human intervention.most interesting scenes contain multiple objects of interest. hence, it would be useful to separate the foreground into the multiple objects it contains. we propose discover, an unsupervised approach to identifying the multiple objects of interest in a scene from a collection of images. in order to achieve this, it exploits the consistency in foreground objects - in terms of occurrence and geometry - across the multiple images of the scene.
privacy preserving: hiding a face in a face. this paper proposes a detailed framework of privacy preserving techniques in real-time video surveillance systems. in the proposed system, the protected video data can be released in such a way that the identity of any individual contained in video cannot be recognized while the surveillance data remains practically useful, and if the original privacy information is demanded, it can be recoverable with a secrete key. the proposed system attempts to hide a face (real face, privacy information) in a face (new generated face for anonymity). to deal with the huge payload problem of privacy information hiding, an active appearance model (aam) based privacy information extraction and recovering is proposed in our system. a quantized index modulation based data hiding scheme is used to hide the privacy information. experimental results have shown that the proposed system can embed the privacy information into video without affecting its visual quality and keep its practical usefulness, at the same time, allows the privacy information to be revealed in a secure and reliable way.
initial pose estimation for 3d model tracking using learned objective functions. tracking 3d models in image sequences essentially requires determining their initial position and orientation. our previous work [14] identifies the objective function as a crucial component for fitting 2d models to images. we state preferable properties of these functions and we propose to learn such a function from annotated example images. this paper extends this approach by making it appropriate to also fit 3d models to images. the correctly fitted model represents the initial pose for model tracking. however, this extension induces nontrivial challenges such as out-of-plane rotations and self occlusion, which cause large variation to the model's surface visible in the image. we solve this issue by connecting the input features of the objective function directly to the model. furthermore, sequentially executing objective functions specifically learned for different displacements from the correct positions yields highly accurate objective values.
shape reconstruction from cast shadows using coplanarities and metric constraints. to date, various techniques of shape reconstruction using cast shadows have been proposed. the techniques have the advantage that they can be applied to various scenes including outdoor scenes without using special devices. previously proposed techniques usually require calibration of camera parameters and light source positions, and such calibration processes make the application ranges limited. if a shape can be reconstructed even when these values are unknown, the technique can be used to wider range of applications. in this paper, we propose a method to realize such a technique by constructing simultaneous equations from coplanarities and metric constraints, which are observed by cast shadows of straight edges and visible planes in the scenes, and solving them. we conducted experiments using simulated and real images to verify the technique.
on the critical point of gradient vector flow snake. in this paper, the so-called critical point problem of gradient vector flow (gvf) snake is studied in two respects: influencing factors and detection of the critical points. one influencing factor that particular attention should be paid to is the iteration number in the diffusion process, too large amount of diffusion would flood the object boundaries while too small amount would preserve excessive noise. here, the optimal iteration number is chosen by minimizing the correlation between the signal and noise in the filtered vector field. on the other hand, we single out all the critical points by quantizing the gvf vector field. after the critical points are singled out, the initial contour can be located properly to avoid the nuisance arising from critical points. several experiments are also presented to demonstrate the effectiveness of the proposed strategies.
super resolution of images of 3d scenecs. we address the problem of super resolved generation of novel views of a 3d scene with the reference images obtained from cameras in general positions; a problem which has not been tackled before in the context of super resolution and is also of importance to the field of image based rendering. we formulate the problem as one of estimation of the color at each pixel in the high resolution novel view without explicit and accurate depth recovery. we employ a reconstruction based approach using mrf-map formalism and solve using graph cut optimization. we also give an effective method to handle occlusion. we present compelling results on real images.
feature subset selection for multi-class svm based image classification. multi-class image classification can benefit much from feature subset selection. this paper extends an error bound of binary svms to a feature subset selection criterion for the multi-class svms. by minimizing this criterion, the scale factors assigned to each feature in a kernel function are optimized to identify the important features. this minimization problem can be efficiently solved by gradient-based search techniques, even if hundreds of features are involved. also, considering that image classification is often a small sample problem, the regularization issue is investigated for this criterion, showing its robustness in this situation. experimental study on multiple benchmark image data sets demonstrates the effectiveness of the proposed approach.
generative estimation of 3d human pose using shape contexts matching. we present a method for 3d pose estimation of human motion in generative framework. for the generalization of application scenario, the observation information we utilized comes from monocular silhouettes. we distill prior information of human motion by performing conventional pca on single motion capture data sequence. in doing so, the aims for both reducing dimensionality and extracting the prior knowledge of human motion are achieved simultaneously. we adopt the shape contexts descriptor to construct the matching function, by which the validity and the robustness of the matching between image features and synthesized model features can be ensured. to explore the solution space efficiently, we design the annealed genetic algorithm (aga) and hierarchical annealed genetic algorithm (haga) that searches the optimal solutions effectively by utilizing the characteristics of state space. results of pose estimation on different motion sequences demonstrate that the novel generative method can achieves viewpoint invariant 3d pose estimation.
view planning for cityscape archiving and visualization. this work explores full registration of scenes in a large area purely based images for city indexing and visualization. ground-based images including route panoramas, scene tunnels, panoramic views, and spherical views are acquired in the area and are associated with geospatial information. in this paper, we plan distributed locations and paths in the urban area based on the visibility, image properties, image coverage, and scene importance for image acquisition. the criterion is to use a small number of images to cover as large scenes as possible. lidar data are used in this view evaluation and real data are acquired accordingly. the extended images realize a compact and complete visual data archiving, which will enhance the perception of spatial relations of scenes.
markov random field modeled level sets method for object tracking with moving cameras. object tracking using active contours has attracted increasing interest in recent years due to acquisition of effective shape descriptions. in this paper, an object tracking method based on level sets using moving cameras is proposed. we develop an automatic contour initialization method based on optical flow detection. a markov random field (mrf)-like model measuring the correlations between neighboring pixels is added to improve the general region-based level sets speed model. the experimental results on several real video sequences show that our method successfully tracks objects despite object scale changes, motion blur, background disturbance, and gets smoother and more accurate results than the current region-based method.
constrained optimization for human pose estimation from depth sequences. a new 2-step method is presented for human upper-body pose estimation from depth sequences, in which coarse human part labeling takes place first, followed by more precise joint position estimation as the second phase. in the first step, a number of constraints are extracted from notable image features such as the head and torso. the problem of pose estimation is cast as that of label assignment with these constraints. major parts of the human upper body are labeled by this process. the second step estimates joint positions optimally based on kinematic constraints using dense correspondences between depth profile and human model parts. the proposed framework is shown to overcome some issues of existing approaches for human pose tracking using similar types of data streams. performance comparison with motion capture data is presented to demonstrate the accuracy of our approach.
shape from contour for the digitization of curved documents. we are aiming at extending the basic digital camera functionalities to the ability to simulate the flattening of a document, by virtually acting like a flatbed scanner. typically, the document is the warped page of an opened book. the problem is stated as a computer vision problem, whose resolution involves, in particular, a 3d reconstruction technique, namely shape from contour. assuming that a photograph is taken by a camera in arbitrary position or orientation, and that the model of the document surface is a generalized cylinder, we show how the corrections of its geometric distortions, including perspective distortion, can be achieved from a single view of the document. the performances of the proposed technique are assessed and illustrated through experiments on real images.
evaluating multi-class multiple-instance learning for image categorization. automatic image categorization is a challenging computer vision problem, to which multiple-instance learning (mil) has emerged as a promising approach. typical current mil schemes rely on binary one-versus-all classification, even for inherently multi-class problems. there are a few drawbacks with binary mil when applied to a multi-class classification problem. this paper describes multi-class multiple-instance learning (mcmil). to image categorization that bypasses the necessity of constructing a series of binary classifiers. we analyze mcmil in depth to show why it is advantageous over binary mil when strong target concept overlaps exist among the classes. we systematically valuate mcmil using two challenging image databases, and compare it with state-of-the-art binary mil approaches. the mcmil achieves competitive classification accuracy, robustness to labeling noise, and effectiveness in capturing the target concepts using smaller amount of training data. we show that the learned target concepts from mcmil conform to human interpretation of the images.
action recognition for surveillance applications using optic flow and svm. low quality images taken by surveillance cameras pose a great challenge to human action recognition algorithms. this is because they are usually noisy, of low resolution and of low frame rate. in this paper we propose an action recognition algorithm to overcome the above challenges. we use optic flow to construct motion descriptors and apply a svm to classify them. having powerful discriminative features, we significantly reduce the size of the feature set required. this algorithm can be applied to videos with low frame rate without scarifying efficiency or accuracy, and is robust to scale and view point changes. to evaluate our method, we used a database consisting of walking, running, jogging, hand clapping, hand waving and boxing actions. this grayscale database has images of low resolution and poor quality. this image database resembles images taken by surveillance cameras. the proposed method outperforms competing algorithms evaluated on the same database.
depth from stationary blur with adaptive filtering. this work achieves an efficient acquisition of scenes and their depths along long streets. a camera is mounted on a vehicle moving along a path and a sampling line properly set in the camera frame scans the 1d scene continuously to form a 2d route panorama. this paper extends a method to estimate depth from the camera path by analyzing the stationary blur in the route panorama. the temporal stationary blur is a perspective effect in parallel projection yielded from the sampling slit with a physical width. the degree of blur is related to the scene depth from the camera path. this paper analyzes the behavior of the stationary blur with respect to camera parameters and uses adaptive filtering to improve the depth estimation. it avoids feature matching or tracking for complex street scenes and facilitates real time sensing. the method also stores much less data than a structure from motion approach does so that it can extend the sensing area significantly.
an occupancy-depth generative model of multi-view images. this paper presents an occupancy based generative model of stereo and multi-view stereo images. in this model, the space is divided into empty and occupied regions. the depth of a pixel is naturally determined from the occupancy as the depth of the first occupied point in its viewing ray. the color of a pixel corresponds to the color of this 3d point. this model has two theoretical advantages. first, unlike other occupancy based models, it explicitly models the deterministic relationship between occupancy and depth and, thus, it correctly handles occlusions. second, unlike depth based approaches, determining depth from the occupancy automatically ensures the coherence of the resulting depth maps. experimental results computing the map of the model using message passing techniques are presented to show the applicability of the model.
highest accuracy fundamental matrix computation. we compare algorithms for fundamental matrix computation, which we classify into "a posteriori correction", "internal access", and "external access". doing experimental comparison, we show that the 7-parameter levenberg-marquardt (lm) search and the extended fns (efns) exhibit the best performance and that additional bundle adjustment does not increase the accuracy to any noticeable degree.
determining relative geometry of cameras from normal flows. determining the relative geometry of cameras is important in active binocular head or multi-camera system. most of the existing works rely upon the establishment of either motion correspondences or binocular correspondences. this paper presents a first solution method that requires no recovery of full optical flow in either camera, nor overlap in the cameras' visual fields and in turn the presence of binocular correspondences. the method is based upon observations that are directly available in the respective image stream - the monocular normal flow. experimental results on synthetic data and real image data are shown to illustrate the potential of the method.
detecting, tracking and recognizing license plates. this paper introduces a novel real-time framework which enables detection, tracking and recognition of license plates from video sequences. an efficient algorithm based on analysis of maximally stable extremal region (mser) detection results allows localization of international license plates in single images without the need of any learning scheme. after a one-time detection of a plate it is robustly tracked through the sequence by applying a modified version of the mser tracking framework which provides accurate localization results and additionally segmentations of the individual characters. therefore, tracking and character segmentation is handled simultaneously. finally, support vector machines are used to recognize the characters on the plate. an experimental evaluation shows the high accuracy and efficiency of the detection and tracking algorithm. furthermore, promising results on a challenging data set are presented and the significant improvement of the recognition rate due to the robust tracking scheme is proved.
dense 3d reconstruction of specular and transparent objects using stereo cameras and phase-shift method. in this paper, we first describe our approach to measuring the surface shape of specular objects and then we extend the method to measuring the surface shape of transparent objects by using stereo cameras and a display. we show that two viewpoints can uniquely determine the surface shape and surface normal by investigating the light path for each surface point. we can determine the light origin for each surface point by showing two-dimensional phase shifts on the display. we obtained dense and accurate results for both planar surfaces and curved surfaces.
fast optimal three view triangulation. we consider the problem of l2-optimal triangulation from three separate views. triangulation is an important part of numerous computer vision systems. under gaussian noise, minimizing the l2 norm of the reprojection error gives a statistically optimal estimate. this has been solved for two views. however, for three or more views, it is not clear how this should be done. a previously proposed, but computationally impractical, method draws on gröbner basis techniques to solve for the complete set of stationary points of the cost function. we show how this method can be modified to become significantly more stable and hence given a fast implementation in standard ieee double precision. we evaluate the precision and speed of the new method on both synthetic and real data. the algorithm has been implemented in a freely available software package which can be downloaded from the internet.
recognition of digital images of the human face at ultra low resolution via illumination spaces. recent work has established that digital images of a human face, collected under various illumination conditions, contain discriminatory information that can be used in classification. in this paper we demonstrate that sufficient discriminatory information persists at ultralow resolution to enable a computer to recognize specific human faces in settings beyond human capabilities. for instance, we utilized the haar wavelet to modify a collection of images to emulate pictures from a 25- pixel camera. from these modified images, a low-resolution illumination space was constructed for each individual in the cmu-pie database. each illumination space was then interpreted as a point on a grassmann manifold. classification that exploited the geometry on this manifold yielded error-free classification rates for this data set. this suggests the general utility of a low-resolution illumination camera for set-based image recognition problems.
an adaptive nonparametric discriminant analysis method and its application to face recognition. linear discriminant analysis (lda) is frequently used for dimension reduction and has been successfully utilized in many applications, especially face recognition. in classical lda, however, the definition of the between-class scatter matrix can cause large overlaps between neighboring classes, because lda assumes that all classes obey a gaussian distribution with the same covariance. we therefore, propose an adaptive nonparametric discriminant analysis (anda) algorithm that maximizes the distance between neighboring samples belonging to different classes, thus improving the discriminating power of the samples near the classification borders. to evaluate its performance thoroughly, we have compared our anda algorithm with traditional pca+lda, orthogonal lda (olda) and nonparametric discriminant analysis (nda) on the feret and orl face databases. experimental results show that the proposed algorithm outperforms the others.
sports classification using cross-ratio histograms. the paper proposes a novel approach for classification of sports images based on the geometric information encoded in the image of a sport's field. the proposed approach uses invariant nature of a crossratio under projective transformation to develop a robust classifier. for a given image, cross-ratios are computed for the points obtained from the intersection of lines detected using hough transform. these cross-ratios are represented by a histogram which forms a feature vector for the image. an svm classifier trained on aprior model histograms of crossratios for sports fields is used to decide the most likely sport's field in the image. experimental validation shows robust classification using the proposed approach for images of tennis, football, badminton, basketball taken from dissimilar view points.
multiplexed illumination for measuring brdf using an ellipsoidal mirror and a projector. measuring a bidirectional reflectance distribution function (brdf) requires long time because a target object must be illuminated from all incident angles and the reflected light must be measured from all reflected angles. a high-speed method is presented to measure brdfs using an ellipsoidal mirror and a projector. the method can change incident angles without a mechanical drive. moreover, it is shown that the dynamic range of the measured brdf can be significantly increased by multiplexed illumination based on the hadamard matrix.
image segmentation using iterated graph cuts based on multi-scale smoothing. we present a novel approach to image segmentation using iterated graph cuts based on multi-scale smoothing. we compute the prior probability obtained by the likelihood from a color histogram and a distance transform using the segmentation results from graph cuts in the previous process, and set the probability as the t-link of the graph for the next process. the proposed method can segment the regions of an object with a stepwise process from global to local segmentation by iterating the graph-cuts process with gaussian smoothing using different values for the standard deviation. we demonstrate that we can obtain 4.7% better segmentation than that with the conventional approach.
person-similarity weighted feature for expression recognition. in this paper, a new method to extract person-independent expression feature based on hosvd (higher-order singular value decomposition) is proposed for facial expression recognition. with the assumption that similar persons have similar facial expression appearance and shape, person-similarity weighted expression feature is used to estimate the expression feature of the test person. as a result, the estimated expression feature can reduce the influence of individual caused by insufficient training data and becomes less person-dependent, and can be more robust to new persons. the proposed method has been tested on cohn-kanade facial expression database and japanese female facial expression (jaffe) database. person-independent experimental results show the efficiency of the proposed method.
co-segmentation of image pairs with quadratic global constraint in mrfs. this paper provides a novel method for co-segmentation, namely simultaneously segmenting multiple images with same foreground and distinct backgrounds. our contribution primarily lies in four-folds. first, image pairs are typically captured under different imaging conditions, which makes the color distribution of desired object shift greatly, hence it brings challenges to color-based co-segmentation. here we propose a robust regression method to minimize color variances between corresponding image regions. secondly, although having been intensively discussed, the exact meaning of the term "co-segmentation" is rather vague and importance of image background is previously neglected, this motivate us to provide a novel, clear and comprehensive definition for co-segmentation. thirdly, it is an involved issue that specific regions tend to be categorized as foreground, so we introduce "risk term" to differentiate colors, which has not been discussed before in the literatures to our best knowledge. lastly and most importantly, unlike conventional linear global terms in mrfs, we propose a sum-of-squared-difference (ssd) based global constraint and deduce its equivalent quadratic form which takes into account the pairwise relations in feature space. reasonable assumptions are made and global optimal could be efficiently obtained via alternating graph cuts.
microscopic surface shape estimation of a transparent plate using a complex image. this paper proposes a method to estimate the surface shape of a transparent plate using a reflection image on the plate. the reflection image on a transparent plate is a complex image that consists of a reflection on the surface and on the rear surface of the plate. a displacement between the two reflection images holds the range information to the object, which can be extracted from a single complex image. the displacement in the complex image depends not only on the object range but also on the normal vectors of the plate surfaces, plate thickness, relative refraction index, and the plate position. these parameters can be estimated using multiple planar targets with random texture at known distances. experimental results show that the proposed method can detect microscopic surface shape differences between two different commercially available transparent acrylic plates.
pose estimation from circle or parallel lines in a single image. the paper is focused on the problem of pose estimation from a single view in minimum conditions that can be obtained from images. under the assumption of known intrinsic parameters, we propose and prove that the pose of the camera can be recovered uniquely in three situations: (a) the image of one circle with discriminable center; (b) the image of one circle with preassigned world frame; (c) the image of any two pairs of parallel lines. compared with previous techniques, the proposed method does not need any 3d measurement of the circle or lines, thus the required conditions are easily satisfied in many scenarios. extensive experiments are carried out to validate the proposed method.
discriminant clustering embedding for face recognition with image sets. in this paper, a novel local discriminant embedding method, discriminant clustering embedding (dce), is proposed for face recognition with image sets. dce combines the effectiveness of submanifolds, which are extracted by clustering for each subject's image set, characterizing the inherent structure of face appearance manifold and the discriminant property of discriminant embedding. the low-dimensional embedding is learned via preserving the neighbor information within each submanifold, and separating the neighbor submanifolds belonging to different subjects from each other. compared with previous work, the proposed method could not only discover the most powerful discriminative information embedded in the local structure of face appearance manifolds more sufficiently but also preserve it more efficiently. extensive experiments on real world data demonstrate that dce is efficient and robust for face recognition with image sets.
learning-based super-resolution system using single facial image and multi-resolution wavelet synthesis. a learning-based super-resolution system consisting of training and synthesis processes is presented. in the proposed system, a multiresolution wavelet approach is applied to carry out the robust synthesis of both the global geometric structure and the local high-frequency detailed features of a facial image. in the training process, the input image is transformed into a series of images of increasingly lower resolution using the haar discrete wavelet transform (dwt). the images at each resolution level are divided into patches, which are then projected onto an eigenspace to derive the corresponding projection weight vectors. in the synthesis process, a low-resolution input image is divided into patches, which are then projected onto the same eigenspace as that used in the training process. modeling the resulting projection weight vectors as a markov network, the maximum a posteriori (map) estimation approach is then applied to identity the best-matching patches with which to reconstruct the image at a higher level of resolution. the experimental results demonstrate that the proposed reconstruction system yields better results than the bi-cubic spline interpolation method.
content-based matching of videos using local spatio-temporal fingerprints. fingerprinting is the process of mapping content or fragments of it, into unique, discriminative hashes called fingerprints. in this paper, we propose an automated video identification algorithm that employs fingerprinting for storing videos inside its database. when queried using a degraded short video segment, the objective of the system is to retrieve the original video to which it corresponds to, both accurately and in real-time. we present an algorithm that first, extracts key frames for temporal alignment of the query and its actual database video, and then computes spatio-temporal fingerprints locally within such frames, to indicate a content-match. all stages of the algorithm have been shown to be highly stable and reproducible even when strong distortions are applied to the query.
a new framework for grayscale and colour non-lambertian shape-from-shading. in this paper we show how arbitrary surface reflectance properties can be incorporated into a shape-from-shading scheme, by using a riemannian minimisation scheme to minimise the brightness error. we show that for face images an additional regularising constraint on the surface height function is all that is required to recover accurate face shape from single images, the only assumption being of a single light source of known direction. the method extends naturally to colour images, which add additional constraints to the problem. for our experimental evaluation we incorporate the torrance and sparrow surface reflectance model into our scheme and show how to solve for its parameters in conjunction with recovering a face shape estimate. we demonstrate that the method provides a realistic route to non-lambertian shape-from-shading for both grayscale and colour face images.
comparative studies on multispectral palm image fusion for biometrics. hand biometrics, including fingerprint, palmprint, hand geometry and hand vein pattern, have obtained extensive attention in recent years. physiologically, skin is a complex multi-layered tissue consisting of various types of components. optical research suggests that different components appear when the skin is illuminated with light sources of different wavelengths. this motivates us to extend the capability of camera by integrating information from multispectral palm images to a composite representation that conveys richer and denser pattern for recognition. besides, usability and security of the whole system might be boosted at the same time. in this paper, comparative study of several pixel level multispectral palm image fusion approaches is conducted and several well-established criteria are utilized as objective fusion quality evaluation measure. among others, curvelet transform is found to perform best in preserving discriminative patterns from multispectral palm images.
improved space carving method for merging and interpolating multiple range images using information of light sources of active stereo. to merge multiple range data obtained by range scanners, filling holes caused by unmeasured regions, the space carving method is a simple and effective method. however, this method often fails if the number of the input range images is small, because unseen voxels that are not carved out remains in the volume area. in this paper, we propose an improved algorithm of the space carving method that produces stable results. in the proposed method, a discriminant function defined on volume space is used to estimate whether each voxel is inside or outside the objects. also, in particular case that the range images are obtained by active stereo method, the information of the positions of the light sources can be used to improve the accuracy of the results.
image and video matting with membership propagation. two techniques are devised for a natural image matting method using semi-supervised object extraction. one is a guiding scheme for placement of user strokes specifying object or background regions and the other is a scheme of adjustment of object colors for conforming to composited background colors. we draw strokes at inhomogeneous color regions disclosed with an unsupervised cluster extraction method from which the semi-supervised algorithm is derived. objects are composited with a new background after their color adjustment using a color transfer method with eigencolor mapping. this image matting method is then extended to videos. strokes are drawn only in the first frame from which memberships are propagated to successive frames to extract objects in every frame. performance of the proposed method is examined with images and videos experimented with existing matting methods.
high capacity watermarking in nonedge texture under statistical distortion constraint. high-capacity image watermarking scheme aims at maximize bit rate of hiding information, neither eliciting perceptible image distortion nor facilitating special watermark attack. texture, in preattentive vision, delivers itself by concise high-order statistics, and holds high capacity for watermark. however, traditional distortion constraint, e.g. just-noticeable-distortion (jnd), cannot evaluate texture distortion in visual perception and thus imposes too strict constraint. inspired by recent work of image representation [9], which suggests texture extraction and mix probability principal component analysis for learning texture feature, we propose a distortion measure in the subspace spanned by texture principal components, and an adaptive distortion constraint depending on image local roughness. the proposed spread-spectrum watermarking scheme generates watermarked images with larger snr than jnd-based schemes at the same distortion level allowed, and its watermark has a power spectrum approximately directly proportional to the host image's and thereby more robust against wiener filtering attack.
localized content-based image retrieval using semi-supervised multiple instance learning. in this paper, we propose a semi-supervised multiple-instance learning (ssmil) algorithm, and apply it to localized content-based image retrieval (lcbir), where the goal is to rank all the images in the database, according to the object that users want to retrieve. ssmil treats lcbir as a semi-supervised problem and utilize the unlabeled pictures to help improve the retrieval performance. the comparison result of ssmil with several state-of-art algorithms is promising.
where's the weet-bix? this paper proposes a new retrieval problem and conducts the initial study. this problem aims at finding the location of an item in a supermarket by means of visual retrieval. it is modelled as object-based retrieval and approached using the local invariant features. two existing retrieval methods are investigated and their similarity measures are modified to better fit this new problem. more importantly, through the study this new retrieval problem proves itself to be a challenging task. an instant application of it is to help the customer find what they want without physically wandering around the shelves but a wide range of potential applications could be expected.
evolving measurement regions for depth from defocus. depth from defocus (dfd) is a 3d recovery method based on estimating the amount of defocus induced by finite lens apertures. given two images with different camera settings, the problem is to measure the resulting differences in defocus across the image, and to estimate a depth based on these blur differences. most methods assume that the scene depth map is locally smooth, and this leads to inaccurate depth estimates near discontinuities. in this paper, we propose a novel dfd method that avoids smoothing over discontinuities by iteratively modifying an elliptical image region over which defocus is estimated. our method can be used to complement any depth from defocus method based on spatial domain measurements. in particular, this method improves the dfd accuracy near discontinuities in depth or surface orientation.
face recognition by using elongated local binary patterns with average maximum distance gradient magnitude. in this paper, we propose a new face recognition approach based on local binary patterns (lbp). the proposed approach has the following novel contributions. (i) as compared with the conventional lbp, anisotropic structures of the facial images can be captured effectively by the proposed approach using elongated neighborhood distribution, which is called the elongated lbp (elbp). (ii) a new feature, called average maximum distance gradient magnitude (amdgm), is proposed. amdgm embeds the gray level difference information between the reference pixel and neighboring pixels in each elbp pattern. (iii) it is found that the elbp and amdgm features are well complement with each other. the proposed method is evaluated by performing facial expression recognition experiments on two databases: orl and feret. the proposed method is compared with two widely used face recognition approaches. furthermore, to test the robustness of the proposed method under the condition that the resolution level of the input images is low, we also conduct additional face recognition experiments on the two databases by reducing the resolution of the input facial images. the experimental results show that the proposed method gives the highest recognition accuracy in both normal environment and low image resolution conditions.
a convex programming approach to the trace quotient problem. the trace quotient problem arises in many applications in pattern classification and computer vision, e.g., manifold learning, low-dimension embedding, etc. the task is to solve a optimization problem involving maximizing the ratio of two traces, i.e., maxw tr(f(w))/tr(h(w)). this optimization problem itself is non-convex in general, hence it is hard to solve it directly. conventionally, the trace quotient objective function is replaced by a much simpler quotient trace formula, i.e., maxw tr (h(w)-1f(w)), which accommodates a much simpler solution. however, the result is no longer optimal for the original problem setting, and some desirable properties of the original problem are lost. in this paper we proposed a new formulation for solving the trace quotient problem directly. we reformulate the original non-convex problem such that it can be solved by efficiently solving a sequence of semidefinite feasibility problems. the solution is therefore globally optimal. besides global optimality, our algorithm naturally generates orthonormal projection matrix. moreover it relaxes the restriction of linear discriminant analysis that the projection matrix's rank can only be at most c - 1, where c is the number of classes. our approach is more flexible. experiments show the advantages of the proposed algorithm.
kernel discriminant analysis based on canonical differences for face recognition in image sets. a novel kernel discriminant transformation (kdt) algorithm based on the concept of canonical differences is presented for automatic face recognition applications. for each individual, the face recognition system compiles a multi-view facial image set comprising images with different facial expressions, poses and illumination conditions. since the multi-view facial images are non-linearly distributed, each image set is mapped into a highdimensional feature space using a nonlinear mapping function. the corresponding linear subspace, i.e. the kernel subspace, is then constructed via a process of kernel principal component analysis (kpca). the similarity of two kernel subspaces is assessed by evaluating the canonical difference between them based on the angle between their respective canonical vectors. utilizing the kernel fisher discriminant (kfd), a kdt algorithm is derived to establish the correlation between kernel subspaces based on the ratio of the canonical differences of the between-classes to those of the within-classes. the experimental results demonstrate that the proposed classification system outperforms existing subspace comparison schemes and has a promising potential for use in automatic face recognition applications.
visual odometry for non-overlapping views using second-order cone programming. we present a solution for motion estimation for a set of cameras which are firmly mounted on a head unit and do not have overlapping views in each image. this problem relates to ego-motion estimation of multiple cameras, or visual odometry. we reduce motion estimation to solving a triangulation problem, which finds a point in space from multiple views. the optimal solution of the triangulation problem in linfinity norm is found using socp (second-order cone programming) consequently, with the help of the optimal solution for the triangulation, we can solve visual odometry by using socp as well.
stereo vision enabling precise border localization within a scanline optimization framework. a novel algorithm for obtaining accurate dense disparity measurements and precise border localization from stereo pairs is proposed. the algorithm embodies a very effective variable support approach based on segmentation within a scanline optimization framework. the use of a variable support allows for precisely retrieving depth discontinuities while smooth surfaces are well recovered thanks to the minimization of a global function along multiple scanlines. border localization is further enhanced by symmetrically enforcing the geometry of the scene along depth discontinuities. experimental results show a significant accuracy improvement with respect to comparable stereo matching approaches.
a fast and noise-tolerant method for positioning centers of spiraling and circulating vector fields. identification of centers of circulating and spiraling vector fields are important in many applications. tropical cyclone tracking, rotating object identification, analysis of motion video and movement of fluids are but some examples. in this paper, we introduce a fast and noise tolerant method for finding centers of circulating and spiraling vector field pattern. the method can be implemented using integer operations only. it is 1.4 to 4.5 times faster than traditional methods, and the speedup can be further boosted up to 96.6 by the incorporation of search algorithms. we show the soundness of the algorithm using experiments on synthetic vector fields and demonstrate its practicality using application examples in the field of multimedia and weather forecasting.
discriminating 3d faces by statistics of depth differences. in this paper, we propose an efficient 3d face recognition method based on statistics of range image differences. each pixel value of range image represents normalized depth value of corresponding point on facial surface, and so depth differences between two range images' pixels of the same position on face can straightforwardly describe the differences between two faces' structures. here, we propose to use histogram proportion of depth differences to discriminate intra and inter personal differences for 3d face recognition. depth differences are computed from a neighbor district instead of direct subtraction to avoid the impact of non-precise registration. furthermore, three schemes are proposed to combine the local rigid region(nose) and holistic face to overcome expression variation for robust recognition. promising experimental results are achieved on the 3d dataset of frgc2.0, which is the most challenging 3d database so far.
color-stripe structured light robust to surface color and discontinuity. multiple color stripes have been employed for structured light-based rapid range imaging to increase the number of uniquely identifiable stripes. the use of multiple color stripes poses two problems: (1) object surface color may disturb the stripe color and (2) the number of adjacent stripes required for identifying a stripe may not be maintained near surface discontinuities such as occluding boundaries. in this paper, we present methods to alleviate those problems. log-gradient filters are employed to reduce the influence of object colors, and color stripes in two and three directions are used to increase the chance of identifying correct stripes near surface discontinuities. experimental results demonstrate the effectiveness of our methods.
viewpoint insensitive action recognition using envelop shape. action recognition is a popular and important research topic in computer vision. however, it is challenging when facing viewpoint variance. so far, most researches in action recognition remain rooted in view-dependent representations. some view invariance approaches have been proposed, but most of them suffer from some weaknesses, such as lack of abundant information for recognition, dependency on robust meaningful feature detection or point correspondence. to perform viewpoint and subject independent action recognition, we propose a representation named "envelop shape" which is viewpoint insensitive. "envelop shape" is easy to acquire from silhouettes using two orthogonal cameras. it makes full use of two cameras' silhouettes to dispel influence caused by human body's vertical rotation, which is often the primary viewpoint variance. with the help of "envelop shape", we obtained inspiring results on action recognition independent of subject and viewpoint. results indicate that "envelop shape" representation contains enough discriminating features for action recognition.
shape recovery from turntable image sequence. this paper makes use of both feature points and silhouettes to deliver fast 3d shape recovery from a turntable image sequence. the algorithm exploits object silhouettes in two views to establish a 3d rim curve, which is defined with respect to the two frontier points arising from two views. the images of this 3d rim curve in the two views are matched using cross correlation technique with silhouette constraint incorporated. a 3d planar rim curve is then reconstructed using point-based reconstruction method. a set of rims enclosing the object can be obtained from an image sequence captured under circular motion. the proposed method solves the problem of reconstruction of concave object surface, which is usually left unresolved in general silhouette-based reconstruction methods. in addition, the property of the organized reconstructed rim curves allows fast surface extraction. experimental results with real data are presented.
fast 3-d interpretation from monocular image sequences on large motion fields. this paper proposes a fast method for dense 3-d interpretation to directly estimate a dense map of relative depth and motion from a monocular sequence of images on large motion fields. the nagel-enkelmann technique is employed in the variational formulation of the problem. diffusion-reaction equations are derived from the formulation so as to approximate the dense map on large motion fields and realize an anisotropic diffusion to preserve the discontinuities of the map. by combining the ideas of implicit schemes and multigrid methods, we present a new implicit multigrid block gauss-seidel relaxation scheme, which dramatically reduces the computation time for solving the largescale linear system of diffusion-reaction equations. using our method, we perform fast 3-d interpretation of image sequences with large motion fields. the efficiency and effectiveness of our method are experimentally verified with synthetic and real image sequences.
a regularized approach to feature selection for face detection. in this paper we present a trainable method for selecting features from an overcomplete dictionary of measurements. the starting point is a thresholded version of the landweber algorithm for providing a sparse solution to a linear system of equations. we consider the problem of face detection and adopt rectangular features as an initial representation for allowing straightforward comparisons with existing techniques. for computational efficiency and memory requirements, instead of implementing the full optimization scheme on tenths of thousands of features, we propose to first solve a number of smaller size optimization problems obtained by randomly sub-sampling the feature vector, and then recombining the selected features. the obtained set is still highly redundant, so we further apply feature selection. the final feature selection system is an efficient two-stages architecture. experimental results of an optimized version of the method on face images and image sequences indicate that this method is a serious competitor of other feature selection schemes recently popularized in computer vision for dealing with problems of real time object detection.
adaptively determining degrees of implicit polynomial curves and surfaces. fitting an implicit polynomial (ip) to a data set usually suffers from the difficulty of determining a moderate polynomial degree. an over-low degree leads to inaccuracy than one expects, whereas an overhigh degree leads to global instability. we propose a method based on automatically determining the moderate degree in an incremental fitting process through using qr decomposition. this incremental process is computationally efficient, since by reusing the calculation result from the previous step, the burden of calculation is dramatically reduced at the next step. simultaneously, the fitting instabilities can be easily checked out by judging the eigenvalues of an upper triangular matrix from qr decomposition, since its diagonal elements are equal to the eigenvalues. based on this beneficial property and combining it with tasdizen's ridge regression method, a new technique is also proposed for improving fitting stability.
iris tracking and regeneration for improving nonverbal interface. in this study, we discuss the quality of teleconference with respect to especially to the "eye-contact". recently, video conference system can be used easily even in the mobile phone environment with camera, and many people use it in daily life. since human is likely to look at the face of his partner on monitor not at camera, he will usually fail to send his own eye-contacted facial images to him, and vice versa. we pay attention to the disagreement of the eye-contact in teleconference caused by the separation between the input camera and output monitor devices. then we propose the eye-contact camera system for generating eye-contacted motion images to the receiver. in this system, iris contour is extracted after the face region extraction, the vertical and horizontal directions of the glance are calculated based on the relation among positions of the monitor, camera and receiver, and finally the iris center coordinates are shifted in the image so that the partner looks just looking at him, and vice versa. we implemented the system on note pc with web-camera for evaluating the usability.
multiple view geometry for non-rigid motions viewed from translational cameras. this paper introduces multiple view geometry under projective projections from four-dimensional space to two-dimensional space which can represent multiple view geometry under the projection of space with time. we show the multifocal tensors defined under space-time projective projections can be derived from non-rigid object motions viewed from multiple cameras with arbitrary translational motions, and they are practical for generating images of non-rigid object motions viewed from cameras with arbitrary translational motions. the method is tested in real image sequences.
shape representation and classification using boundary radius function. in this paper, a new method for the problem of shape representation and classification is proposed. in this method, we define a radius function on the contour of the shape which captures for each point of the boundary, attributes of its related internal part of the shape. we call these attributes as "depth" of the point. depths of boundary points generate a descriptor sequence which represents the shape. matching of sequences is performed using dynamic programming method and a distance measure is acquired. at last, different classes of shapes are classified using a hierarchical clustering method and the distance measure. the proposed method can analyze features of each part of the shape locally which this leads to the ability of part analysis and insensitivity to local deformations such as articulation, occlusion and missing parts. we show high efficiency of the proposed method by evaluating it for shape matching and classification of standard shape datasets.
efficient graph cuts for multiclass interactive image segmentation. interactive image segmentation has attracted much attention in the vision and graphics community recently. a typical application for interactive image segmentation is foreground/background segmentation based on user specified brush labellings. the problem can be formulated within the binary markov random field (mrf) framework which can be solved efficiently via graph cut [1]. however, no attempt has yet been made to handle segmentation of multiple regions using graph cuts. in this paper, we propose a multiclass interactive image segmentation algorithm based on the potts mrf model. following [2], this can be converted to a multiway cut problem first proposed in [2] and solved by expansion-move algorithms for approximate inference [2]. a faster algorithm is proposed in this paper for efficient solution of the multiway cut problem based on partial optimal labeling. to achieve this, we combine the one-vs-all classifier fusion framework with the expansion-move algorithm for label inference over large images. we justify our approach with both theoretical analysis and experimental validation.
motion observability analysis of the simplified color correlogram for visual tracking. compared with the color histogram, where the position information of each pixel is ignored, a simplified color correlogram (scc) representation encodes the spatial information explicitly and enables an estimation algorithm to recover the object orientation. this paper analyzes the capability of the scc (in a kernel based framework) in detecting and estimating object motion and presents a principled way to obtain motion observable sccs as object representations to achieve more reliable tracking. extensive experimental results demonstrate the reliability of the tracking procedure using the proposed algorithm.
simultaneous plane extraction and 2d homography estimation using local feature transformations. in this paper, we use local feature transformations estimated in the matching process as initial seeds for 2d homography estimation. the number of testing hypotheses is equal to the number of matches, naturally enabling a full search over the hypothesis space. using this property, we develop an iterative algorithm that clusters the matches under the common 2d homography into one group, i.e., features on a common plane. our clustering algorithm is less affected by the proportion of inliers and as few as two features on the common plane can be clustered together; thus, the algorithm robustly detects multiple dominant scene planes. the knowledge of the dominant planes is used for robust fundamental matrix computation in the presence of quasi-degenerate data.
identifying foreground from multiple images. in this paper, we present a novel foreground extraction method that automatically identifies image regions corresponding to a common space region seen from multiple cameras. we assume that background regions present some color coherence in each image and we exploit the spatial consistency constraint that several image projections of the same space region must satisfy. integrating both color and spatial consistency constraints allows to fully automatically segment foreground and background regions in multiple images. in contrast to standard background subtraction approaches, the proposed approach does not require any a priori knowledge on the background nor user interactions. we demonstrate the effectiveness of the method for multiple camera setups with experimental results on standard real data sets.
a novel multi-stage classifier for face recognition. a novel face recognition scheme based on multi-stages classifier, which includes methods of support vector machine (svm), eigenface, and random sample consensus (ransac), is proposed in this paper. the whole decision process is conducted cascade coarse-to-fine stages. the first stage adopts one-against-one-svm (oao-svm) method to choose two possible classes best similar to the testing image. in the second stage, "eigenface" method was employed to select one prototype image with the minimum distance to the testing image in each of the two classes chosen. finally, the real class is determined by comparing the geometric similarity, as done by "ransac" method, between these prototype images and the testing images. this multi-stage face recognition system has been tested on olivetti research laboratory (orl) face databases, and its experimental results give evidence that the proposed approach outperforms the other approaches either based on the single classifier or multi-parallel classifier, it can even obtain a nearly 100 percent recognition accuracy.
conic fitting using the geometric distance. we consider the problem of fitting a conic to a set of 2d points. it is commonly agreed that minimizing geometrical error, i.e. the sum of squared distances between the points and the conic, is better than using an algebraic error measure. however, most existing methods rely on algebraic error measures. this is usually motivated by the fact that pointto-conic distances are difficult to compute and the belief that non-linear optimization of conics is computationally very expensive. in this paper, we describe a parameterization for the conic fitting problem that allows to circumvent the difficulty of computing point-to-conic distances, and we show how to perform the non-linear optimization process efficiently.
statistical framework for shot segmentation and classification in sports video. in this paper, a novel statistical framework is proposed for shot segmentation and classification. the proposed framework segments and classifies shots simultaneously using same difference features based on statistical inference. the task of shot segmentation and classification is taken as finding the most possible shot sequence given feature sequences, and it can be formulated by a conditional probability which can be divided into a shot sequence probability and a feature sequence probability. shot sequence probability is derived from relations between adjacent shots by bi-gram, and feature sequence probability is dependent on inherent character of shot modeled by hmm. thus, the proposed framework segments shot considering the character of intra-shot to classify shot, while classifies shot considering character of inter-shot to segment shot, which obtain more accurate results. experimental results on soccer and badminton videos are promising, and demonstrate the effectiveness of the proposed framework.
temporal priors for novel video synthesis. in this paper we propose a method to construct a virtual sequence for a camera moving through a static environment given an input sequence from a different camera trajectory. existing image-based rendering techniques can generate photorealistic images given a set of input views, though the output images almost unavoidably contain small regions where the colour has been incorrectly chosen. in a single image these artifacts are often hard to spot, but become more obvious when viewing a real image with its virtual stereo pair, and even more so when when a sequence of novel views is generated, since the artifacts are rarely temporally consistent. to address this problem of consistency, we propose a new spatiotemporal approach to novel video synthesis. the pixels in the output video sequence are modelled as nodes of a 3-d graph. we define an mrf on the graph which encodes photoconsistency of pixels as well as texture priors in both space and time. unlike methods based on scene geometry which yield highly connected graphs, our approach results in a graph whose degree is independent of scene structure. the mrf energy is therefore tractable and we solve it for the whole sequence using a stateof-the-art message passing optimisation algorithm. we demonstrate the effectiveness of our approach in reducing temporal artifacts.
face mis-alignment analysis by multiple-instance subspace. in this paper, we systematically study the effect of poorly registered faces on the training and inferring stages of traditional face recognition algorithms. we then propose a novel multiple-instance based subspace learning scheme for face recognition. in this approach, we iteratively update the subspace training instances according to diverse densities, using class-balanced supervised clustering. we test our multiple instance subspace learning algorithm with fisherface for the application of face recognition. experimental results show that the proposed learning algorithm can improve the robustness of current methods with poorly aligned training and testing data.
backward segmentation and region fitting for geometrical visibility range estimation. we present a new application of computer vision: continuous measurement of the geometrical visibility range on inter-urban roads, solely based on a monocular image acquisition system. to tackle this problem, we propose first a road segmentation scheme based on a parzen-windowing of a color feature space with an original update that allows us to cope with heterogeneously paved-roads, shadows and reflections, observed under various and changing lighting conditions. second, we address the under-constrained problem of retrieving the depth information along the road based on the flat word assumption. this is performed by a new region-fitting iterative least squares algorithm, derived from half-quadratic theory, able to cope with vanishing-point estimation, and allowing us to estimate the geometrical visibility range.
image correspondence from motion subspace constraint and epipolar constraint. in this paper, we propose a novel method for inferring image correspondences on the pair of synchronized image sequences. in the proposed method, after tracking the feature points in each image sequence over several frames, we solve the image corresponding problem from two types of geometrical constraints: (1) the motion subspace obtained from the tracked feature points of a target sequence, and (2) the epipolar constraints between the two cameras. dissimilarly to the conventional correspondence estimation based on image matching using pixel values, the proposed approach enables us to obtain the correspondences even though the feature points, that can be seen from one camera view, but can not be seen (occluded or outside of the view) from the other camera. the validity of our method is demonstrated through the experiments using synthetic and real images.
analyzing facial expression by fusing manifolds. feature representation and classification are two major issues in facial expression analysis. in the past, most methods used either holistic or local representation for analysis. in essence, local information mainly focuses on the subtle variations of expressions and holistic representation stresses on global diversities. to take the advantages of both, a hybrid representation is suggested in this paper and manifold learning is applied to characterize global and local information discriminatively. unlike some methods using unsupervised manifold learning approaches, embedded manifolds of the hybrid representation are learned by adopting a supervised manifold learning technique. to integrate these manifolds effectively, a fusion classifier is introduced, which can help to employ suitable combination weights of facial components to identify an expression. comprehensive comparisons on facial expression recognition are included to demonstrate the effectiveness of our algorithm.
content-based image retrieval by indexing random subwindows with randomized trees. we propose a new method for content-based image retrieval which exploits the similarity measure and indexing structure of totally randomized tree ensembles induced from a set of subwindows randomly extracted from a sample of images. we also present the possibility of updating the model as new images come in, and the capability of comparing new images using a model previously constructed from a different set of images. the approach is quantitatively evaluated on various types of images with state-of-the-art results despite its conceptual simplicity and computational efficiency.
palmprint recognition under unconstrained scenes. this paper presents a novel real-time palmprint recognition system for cooperative user applications. this system is the first one achieving noncontact capturing and recognizing palmprint images under unconstrained scenes. its novelties can be described in two aspects. the first is a novel design of image capturing device. the hardware can reduce influences of background objects and segment out hand regions efficiently. the second is a process of automatic hand detection and fast palmprint alignment, which aims to obtain normalized palmprint images for subsequent feature extraction. the palmprint recognition algorithm used in the system is based on accurate ordinal palmprint representation. by integrating power of the novel imaging device, the palmprint preprocessing approach and the palmprint recognition engine, the proposed system provides a friendly user interface and achieves a good performance under unconstrained scenes simultaneously.
stereo matching using population-based mcmc. in this paper, we propose a new stereo matching method using the population-based markov chain monte carlo (pop-mcmc). pop-mcmc belongs to the sampling-based methods. since previous mcmc methods produce only one sample at a time, only local moves are available. however, since pop-mcmc uses multiple chains and produces multiple samples at a time, it enables global moves by exchanging information between samples, and in turn leads to faster mixing rate. in the view of optimization, it means that we can reach a state with the lower energy. the experimental results on real stereo images demonstrate that the performance of proposed algorithm is superior to those of previous algorithms.
accelerating pattern matching or how much can you slide? this paper describes a method that accelerates pattern matching. the distance between a pattern and a window is usually close to the distance of the pattern to the adjacement windows due to image smoothness. we show how to exploit this fact to reduce the running time of pattern matching by adaptively sliding the window often by more than one pixel. the decision how much we can slide is based on a novel rank we define for each feature in the pattern. implemented on a pentium 4 3ghz processor, detection of a pattern with 7569 pixels in a 640 × 480 pixel image requires only 3.4ms.
learning gabor magnitude features for palmprint recognition. palmprint recognition, as a new branch of biometric technology, has attracted much attention in recent years. various palmprint representations have been proposed for recognition. gabor feature has been recognized as one of the most effective representations for palmprint recognition, where gabor phase and orientation feature representations are extensively studied. in this paper, we explore a novel gabor magnitude feature-based method for palmprint recognition. the novelties are as follows: first, we propose an illumination normalization method for palmprint images to decrease the influence of illumination variations caused by different sensors and lighting conditions. second, we propose to use gabor magnitude features for palmprint representation. third, we utilize adaboost learning to extract most effective features and apply local discriminant analysis (lda) to reduce the dimension further for palmprint recognition. experimental results on three large palmprint databases demonstrate the effectiveness of proposed method. compared with state-of-the-art gabor-based methods, our method achieves higher accuracy.
total absolute gaussian curvature for stereo prior. in spite of the great progress in stereo matching algorithms, the prior models they use, i.e., the assumptions about the probability to see each possible surface, have not changed much in three decades. here, we introduce a novel prior model motivated by psychophysical experiments. it is based on minimizing the total sum of the absolute value of the gaussian curvature over the disparity surface. intuitively, it is similar to rolling and bending a flexible paper to fit to the stereo surface, whereas the conventional prior is more akin to spanning a soap film. through controlled experiments, we show that the new prior outperforms the conventional models, when compared in the equal setting.
a bayesian network for foreground segmentation in region level. this paper presents a probabilistic approach for automatically segmenting foreground objects from a video sequence. in order to save computation time and be robust to noise effect, a region detection algorithm incorporating edge information is first proposed to identify the regions of interest. next, we consider the motion of the foreground objects, and hence utilize the temporal coherence property on the regions detected. thus, foreground segmentation problem is formulated as follows. given two consecutive image frames and the segmentation result obtained priorly, we simultaneously estimate the motion vector field and the foreground segmentation mask in a mutually supporting manner. to represent the conditional joint probability density function in a compact form, a bayesian network is adopted, which is derived to model the interdependency of these two elements. experimental results for several video sequences are provided to demonstrate the effectiveness of our proposed approach.
information fusion for multi-camera and multi-body structure and motion. information fusion algorithms have been successful in many vision tasks such as stereo, motion estimation, registration and robot localization. stereo and motion image analysis are intimately connected and can provide complementary information to obtain robust estimates of scene structure and motion. we present an information fusion based approach for multi-camera and multi-body structure and motion that combines bottom-up and top-down knowledge on scene structure and motion. the only assumption we make is that all scene motion consists of rigid motion. we present experimental results on synthetic and nonsynthetic data sets, demonstrating excellent performance compared to binocular based state-of-the-art approaches for structure and motion.
a basin morphology approach to colour image segmentation by region merging. the problem of colour image segmentation is investigated in the context of mathematical morphology. morphological operators are extended to colour images by means of a lexicographical ordering in a polar colour space, which are then employed in the preprocessing stage. the actual segmentation is based on the use of the watershed transformation, followed by region merging, with the procedure being formalized as a basin morphology, where regions are "eroded" in order to form greater catchment basins. the result is a fully automated processing chain, with multiple levels of parametrisation and flexibility, the application of which is illustrated by means of the berkeley segmentation dataset.
embedding a region merging prior in level set vector-valued image segmentation. in the scope of level set image segmentation, the number of regions is fixed beforehand. this number occurs as a constant in the objective functional and its optimization. in this study, we propose a region merging prior which optimizes the objective functional implicitly with respect to the number of regions. a statistical interpretation of the functional and learning over a set of relevant images and segmentation examples allow setting the weight of this prior to obtain the correct number of regions. this method is investigated and validated with color images and motion maps.
continuously tracking objects across multiple widely separated cameras. in this paper, we present a new solution to the problem of multi-camera tracking with non-overlapping fields of view. the identities of moving objects are maintained when they are traveling from one camera to another. appearance information and spatio-temporal information are explored and combined in a maximum a posteriori (map) framework. in computing appearance probability, a two-layered histogram representation is proposed to incorporate spatial information of objects. diffusion distance is employed to histogram matching to compensate for illumination changes and camera distortions. in deriving spatio-temporal probability, transition time distribution between each pair of entry zone and exit zone is modeled as a mixture of gaussian distributions. experimental results demonstrate the effectiveness of the proposed method.
spatiotemporal oriented energy features for visual tracking. this paper presents a novel feature set for visual tracking that is derived from "oriented energies". more specifically, energy measures are used to capture a target's multiscale orientation structure across both space and time, yielding a rich description of its spatiotemporal characteristics. to illustrate utility with respect to a particular tracking mechanism, we show how to instantiate oriented energy features efficiently within the mean shift estimator. empirical evaluations of the resulting algorithm illustrate that it excels in certain important situations, such as tracking in clutter with multiple similarly colored objects and environments with changing illumination. many trackers fail when presented with these types of challenging video sequences.
a cascade of feed-forward classifiers for fast pedestrian detection. we develop a method that can detect humans in a single image based on a new cascaded structure. in our approach, both the rectangle features and 1-d edge-orientation features are employed in the feature pool for weak-learner selection, which can be computed via the integral-image and the integral-histogram techniques, respectively. to make the weak learner more discriminative, real adaboost is used for feature selection and learning the stage classifiers from the training images. instead of the standard boosted cascade, a novel cascaded structure that exploits both the stage-wise classification information and the interstage cross-reference information is proposed. experimental results show that our approach can detect people with both efficiency and accuracy.
synchronized ego-motion recovery of two face-to-face cameras. a movie captured by a wearable camera affixed to an actor's body gives audiences the sense of "immerse in the movie". the raw movie captured by wearable camera needs stabilization with jitters due to ego-motion. however, conventional approaches often fail in accurate ego-motion estimation when there are moving objects in the image and no sufficient feature pairs provided by background region. to address this problem, we proposed a new approach that utilizes an additional synchronized video captured by the camera attached on the foreground object (another actor). formally we configure above sensor system as two face-to-face moving cameras. then we derived the relations between four views including two consecutive views from each camera. the proposed solution has two steps. firstly we calibrate the extrinsic relationship of two cameras with an ax=xb formulation, and secondly estimate the motion using calibration matrix. experiments verify that this approach can recover from failures of conventional approach and provide acceptable stabilization results for real data.
multiperspective distortion correction using collineations. we present a new framework for correcting multiperspective distortions using collineations. a collineation describes the transformation between the images of a camera due to changes in sampling and image plane selection. we show that image distortions in many previous models of cameras can be effectively reduced via proper collineations. to correct distortions in a specific multiperspective camera, we develop an interactive system that allows users to select feature rays from the camera and position them at the desirable pixels. our system then computes the optimal collineation to match the projections of these rays with the corresponding pixels. experiments demonstrate that our system robustly corrects complex distortions without acquiring the scene geometry, and the resulting images appear nearly undistorted.
multi-camera people tracking by collaborative particle filters and principal axis-based integration. this paper presents a novel approach to tracking people in multiple cameras. a target is tracked not only in each camera but also in the ground plane by individual particle filters. these particle filters collaborate in two different ways. first, the particle filters in each camera pass messages to those in the ground plane where the multicamera information is integrated by intersecting the targets' principal axes. this largely relaxes the dependence on precise foot positions when mapping targets from images to the ground plane using homographies. secondly, the fusion results in the ground plane are then incorporated by each camera as boosted proposal functions. a mixture proposal function is composed for each tracker in a camera by combining an independent transition kernel and the boosted proposal function. experiments show that our approach achieves more reliable results using less computational resources than conventional methods.
machine vision in early days: japan's pioneering contributions. the history of machine vision started in the mid-1960s by the efforts of japanese industry researchers. a variety of prominent vision-based systems was made possible by creating and evolving real-time image processing techniques, and was applied to factory automation, office automation, and even to social automation during the 1970-2000 period. in this article, these historical attempts are briefly explained to promote understanding of the pioneering efforts that opened the door and formed the bases of today's computer vision research.
how marginal likelihood inference unifies entropy, correlation and snr-based stopping in nonlinear diffusion scale-spaces. iterative smoothing algorithms are frequently applied in image restoration tasks. the result depends crucially on the optimal stopping (scale selection) criteria. an attempt is made towards the unification of the two frequently applied model selection ideas: (i) the earliest time when the 'entropy of the signal' reaches its steady state, suggested by j. sporring and j. weickert (1999), and (ii) the time of the minimal 'correlation' between the diffusion outcome and the noise estimate, investigated by p. mrázek and m. navara (2003). it is shown that both ideas are particular cases of the marginal likelihood inference. better entropy measures are discovered and their connection to the generalized signal-to-noise ratio is emphasized.
pedestrian detection using global-local motion patterns. we propose a novel learning strategy called global-local motion pattern classification (glmpc) to localize pedestrian-like motion patterns in videos. instead of modeling such patterns as a single class that alone can lead to high intra-class variability, three meaningful partitions are considered - left, right and frontal motion. an adaboost classifier based on the most discriminative eigenflow weak classifiers is learnt for each of these subsets separately. furthermore, a linear three-class svm classifier is trained to estimate the global motion direction. to detect pedestrians in a given image sequence, the candidate optical flow sub-windows are tested by estimating the global motion direction followed by feeding to the matched adaboost classifier. the comparison with two baseline algorithms including the degenerate case of a single motion class shows an improvement of 37% in false positive rate.
flea, do you remember me? the ability to detect and recognize individuals is essential for an autonomous robot interacting with humans even if computational resources are usually rather limited. in general a small user group can be assumed for interaction. the robot has to distinguish between multiple users and further on between known and unknown persons. for solving this problem we propose an approach which integrates detection, recognition and tracking by formulating all tasks as binary classification problems. because of its efficiency it is well suited for robots or other systems with limited resources but nevertheless demonstrates robustness and comparable results to state-of-the-art approaches. we use a common over-complete representation which is shared by the different modules. by means of the integral data structure an efficient feature computation is performed enabling the usage of this system for real-time applications such as for our autonomous robot flea.
optimal algorithms in multiview geometry. this is a survey paper summarizing recent research aimed at finding guaranteed optimal algorithms for solving problems in multiview geometry. many of the traditional problems in multiview geometry now have optimal solutions in terms of minimizing residual imageplane error. success has been achieved in minimizing l2 (least-squares) or l∞ (smallest maximum error) norm. the main methods involve second order cone programming, or quasi-convex optimization, and branch-andbound. the paper gives an overview of the subject while avoiding as far as possible the mathematical details, which can be found in the original papers.
coarse-to-fine statistical shape model by bayesian inference. in this paper, we take a predefined geometry shape as a constraint for accurate shape alignment. a shape model is divided in two parts: fixed shape and active shape. the fixed shape is a user-predefined simple shape with only a few landmarks which can be easily and accurately located by machine or human. the active one is composed of many landmarks with complex shape contour. when searching an active shape, pose parameter is calculated by the fixed shape. bayesian inference is introduced to make the whole shape more robust to local noise generated by the active shape, which leads to a compensation factor and a smooth factor for a coarse-to-fine shape search. this method provides a simple and stable means for online and offline shape analysis. experiments on cheek and face contour demonstrate the effectiveness of our proposed approach.
finding camera overlap in large surveillance networks. recent research on video surveillance across multiple cameras has typically focused on camera networks of the order of 10 cameras. in this paper we argue that existing systems do not scale to a network of hundreds, or thousands, of cameras. we describe the design and deployment of an algorithm called exclusion that is specifically aimed at finding correspondence between regions in cameras for large camera networks. the information recovered by exclusion can be used as the basis for other surveillance tasks such as tracking people through the network, or as an aid to human inspection. we have run this algorithm on a campus network of over 100 cameras, and report on its performance and accuracy over this network.
multiview pedestrian detection based on vector boosting. in this paper, a multiview pedestrian detection method based on vector boosting algorithm is presented. the extended histograms of oriented gradients (ehog) features are formed via dominant orientations in which gradient orientations are quantified into several angle scales that divide gradient orientation space into a number of dominant orientations. blocks of combined rectangles with their dominant orientations constitute the feature pool. the vector boosting algorithm is used to learn a tree-structure detector for multiview pedestrian detection based on ehog features. further a detector pyramid framework over several pedestrian scales is proposed for better performance. experimental results are reported to show its high performance.
a noise-insensitive object tracking algorithm. in this paper, we brought out a noise-insensitive pixel-wise object tracking algorithm whose kernel is a new reliable data grouping algorithm that introduces the reliability evaluation into the existing k-means clustering (called as rk-means clustering). the rk-means clustering concentrates on two problems of the existing k-mean clustering algorithm: 1) the unreliable clustering result when the noise data exists; 2) the bad/wrong clustering result caused by the incorrectly assumed number of clusters. the first problem is solved by evaluating the reliability of classifying an unknown data vector according to the triangular relationship among it and its two nearest cluster centers. noise data will be ignored by being assigned low reliability. the second problem is solved by introducing a new group merging method that can delete pairs of "too near" data groups by checking their variance and average reliability, and then combining them together. we developed a video-rate object tracking system (called as rk-means tracker) with the proposed algorithm. the extensive experiments of tracking various objects in cluttered environments confirmed its effectiveness and advantages.
calibrating pan-tilt cameras with telephoto lenses. pan-tilt cameras are widely used in surveillance networks. these cameras are often equipped with telephoto lenses to capture objects at a distance. such a camera makes full-metric calibration more difficult since the projection with a telephoto lens is close to orthographic. this paper discusses the problems caused by pan-tilt cameras with long focal length and presents a method to improve the calibration accuracy. experiments show that our method reduces the re-projection errors by an order of magnitude compared to popular homography-based approaches.
camera calibration from silhouettes under incomplete circular motion with a constant interval angle. in this paper, we propose an algorithm for camera calibration from silhouettes under circular motion with an unknown constant interval angle. unlike previous silhouette-based methods based on surface of revolution, the proposed algorithm can be applied to sparse and incomplete image sequences. under the assumption of circular motion with a constant interval angle, epipoles of successive image pairs remain constant and can be determined from silhouettes. a pair of epipoles formed by a certain interval angle can provide a constraint on the angle and focal length. with more pairs of epipoles recovered, the focal length can be determined from the one that most satisfies the constraints and determine the interval angle concurrently. the rest of camera parameters can be recovered from image invariants. finally, the estimated parameters are optimized by minimizing the epipolar tangency constraints. experimental results on both synthetic and real images are shown to demonstrate its performance.
hand posture estimation in complex backgrounds by considering mis-match of model. this paper proposes a novel method of estimating 3-d hand posture from images observed in complex backgrounds. conventional methods often cause mistakes by mis-matches of local image features. our method considers possibility of the mis-match between each posture model appearance and the other model appearances in a baysian stochastic estimation form by introducing a novel likelihood concept "mistakenly matching likelihood (mml)". the correct posture model is discriminated from mis-matches by mml-based posture candidate evaluation. the method is applied to hand tracking problem in complex backgrounds and its effectiveness is shown.
learning generative models for monocular body pose estimation. we consider the problem of monocular 3d body pose tracking from video sequences. this task is inherently ambiguous. we propose to learn a generative model of the relationship of body pose and image appearance using a sparse kernel regressor. within a particle filtering framework, the potentially multimodal posterior probability distributions can then be inferred. the 2d bounding box location of the person in the image is estimated along with its body pose. body poses are modelled on a low-dimensional manifold, obtained by lle dimensionality reduction. in addition to the appearance model, we learn a prior model of likely body poses and a nonlinear dynamical model, making both pose and bounding box estimation more robust. the approach is evaluated on a number of challenging video sequences, showing the ability of the approach to deal with low-resolution images and noise.
a theoretical approach to construct highly discriminative features with application in adaboost. adaboost is a practical method of real-time face detection, but abides by a crucial problem of overfitting for the big number of features used in a trained classifier due to the weak discriminative abilities of these features. this paper proposes a theoretical approach to construct highly discriminative features, which is named composed features, from haar-like features. both of the composed and haar-like features are employed to train a multi-view face detector. the primary experiments show promising results in reducing the number of features used in a classifier, which leads to the increase of the generalization ability of the classifier.
3d intrusion detection system with uncalibrated multiple cameras. in this paper, we propose a practical intrusion detection system using uncalibrated multiple cameras. our algorithm combines the contour based multi-planar visual hull method and a projective reconstruction method. to set up the detection system, no advance knowledge or calibration is necessary. a user can specify points in the scene directly with a simple colored marker, and the system automatically generates a restricted area as the convex hull of all specified points. to detect an intrusion, the system computes intersections of an object and each sensitive plane, which is the boundary of the restricted area, by projecting an object silhouette from each image to the sensitive plane using 2d homography. when an object exceeds one sensitive plane, the projected silhouettes from all cameras must have some common regions. therefore, the system can detect intrusion by any object with an arbitrary shape without reconstruction of the 3d shape of the object.
optical flow-driven motion model with automatic variance adjustment for adaptive tracking. we propose a statistical motion model for sequential bayesian tracking, called the optical flow-driven motion model, and show an adaptive particle filter algorithm with the motion model. it predicts the current state with the help of optical flows, i.e., it explores the state space with information based on the current and previous images of an image sequence. in addition, we introduce an automatic method for adjusting the variance of the motion model, which parameter is manually determined in most particle filters. in experiments with synthetic and real image sequences, we compare the proposed motion model with a random walk model, which is a widely used model for tracking, and show the proposed model outperform the random walk model in terms of accuracy even though their execution times are almost the same.
gesture recognition under small sample size. this paper addresses gesture recognition under small sample size, where direct use of traditional classifiers is difficult due to high dimensionality of input space.we propose a pairwise feature extraction method of video volumes for classification. the method of canonical correlation analysis is combined with the discriminant functions and scale-invariant-feature-transform (sift) for the discriminative spatiotemporal features for robust gesture recognition. the proposed method is practically favorable as it works well with a small amount of training samples, involves few parameters, and is computationally efficient. in the experiments using 900 videos of 9 hand gesture classes, the proposed method notably outperformed the classifiers such as support vector machine/relevance vector machine, achieving 85% accuracy.
robust foreground extraction technique using gaussian family model and multiple thresholds. we propose a robust method to extract silhouettes of foreground objects from color video sequences. to cope with various changes in the background, the background is modeled as generalized gaussian family of distributions and updated by the selective running average and static pixel observation. all pixels in the input video image are classified into four initial regions using background subtraction with multiple thresholds, after which shadow regions are eliminated using color components. the final foreground silhouette is extracted by refining the initial region using morphological processes. we have verified that the proposed algorithm works very well in various background and foreground situations through experiments.
detecting and segmenting un-occluded items by actively casting shadows. we present a simple and practical approach for segmenting unoccluded items in a scene by actively casting shadows. by 'items', we refer to objects (or part of objects) enclosed by depth edges. our approach utilizes the fact that under varying illumination, un-occluded items will cast shadows on occluded items or background, but will not be shadowed themselves. we employ an active illumination approach by taking multiple images under different illumination directions, with illumination source close to the camera. our approach ignores the texture edges in the scene and uses only the shadow and silhouette information to determine the occlusions. we show that such a segmentation does not require the estimation of a depth map or 3d information, which can be cumbersome, expensive and often fails due to the lack of texture and presence of specular objects in the scene. our approach can handle complex scenes with self-shadows and specularities. results on several real scenes along with the analysis of failure cases are presented.
qualitative and quantitative behaviour of geometrical pdes in image processing. we analyse a series of approaches to evolve images. it is motivated by combining gaussian blurring, the mean curvature motion (used for denoising and edge-preserving), and maximal blurring (used for inpainting). we investigate the generalised method using the combination of second order derivatives in terms of gauge coordinates. for the qualitative behaviour, we derive a solution of the pde series and mention its properties briefly. relations with general diffusion equations are discussed. quantitative results are obtained by a novel implementation whose stability and convergence is analysed. the practical results are visualised on a real-life image, showing the expected qualitative behaviour. when a constraint is added that penalises the distance of the results to the input image, one can vary the desired amount of blurring and denoising.
pose-invariant facial expression recognition using variable-intensity templates. in this paper, we propose a method for pose-invariant facial expression recognition from monocular video sequences. the advantage of our method is that, unlike existing methods, our method uses a simple model, called the variable-intensity template, for describing different facial expressions. this makes it possible to prepare a model for each person with very little time and effort. variable-intensity templates describe how the intensities of multiple points, defined in the vicinity of facial parts, vary with different facial expressions. by using this model in the framework of a particle filter, our method is capable of estimating facial poses and expressions simultaneously. experiments demonstrate the effectiveness of our method. a recognition rate of over 90% is achieved for all facial orientations, horizontal, vertical, and in-plane, in the range of ±40 degrees, ±20 degrees, and ±40 degrees from the frontal view, respectively.
efficient search in document image collections. this paper presents an efficient indexing and retrieval scheme for searching in document image databases. in many non-european languages, optical character recognizers are not very accurate. word spotting - word image matching - may instead be used to retrieve word images in response to a word image query. the approaches used for word spotting so far, dynamic time warping and/or nearest neighbor search, tend to be slow. here indexing is done using locality sensitive hashing (lsh) - a technique which computes multiple hashes - using word image features computed at word level. efficiency and scalability is achieved by content-sensitive hashing implemented through approximate nearest neighbor computation. we demonstrate that the technique achieves high precision and recall (in the 90% range), using a large image corpus consisting of seven kalidasa's (a well known indian poet of antiquity) books in the telugu language. the accuracy is comparable to using dynamic time warping and nearest neighbor search while the speed is orders of magnitude better - 20000 word images can be searched in milliseconds.
texture-independent feature-point matching (tifm) from motion coherence. this paper proposes a novel and efficient feature-point matching algorithm for finding point correspondences between two uncalibrated images. the striking feature of the proposed algorithm is that the algorithm is based on the motion coherence/smoothness constraint only, which states that neighboring features in an image tend to move coherently. in the algorithm, the correspondences of feature points in a neighborhood are collectively determined in a way such that the smoothness of the local motion field is maximized. the smoothness constraint does not rely on any image feature, and is self-contained in the motion field. it is robust to the camera motion, scene structure, illumination, etc. this makes the proposed algorithm texture-independent and robust. experimental results show that the proposed method outperforms existing methods for feature-point tracking in image sequences.
mapaco-training: a novel online learning algorithm of behavior models. the traditional co-training algorithm, which needs a great number of unlabeled examples in advance and then trains classifiers by iterative learning approach, is not suitable for online learning of classifiers. to overcome this barrier, we propose a novel semi-supervised learning algorithm, called mapaco-training, by combining the cotraining with the principle of maximum a posteriori adaptation. this mapaco-training algorithm is an online multi-class learning algorithm, and has been successfully applied to online learning of behaviors modeled by hidden markov model. the proposed algorithm is tested with the li's database as well as schuldt's dataset.
cardiac motion estimation from tagged mri using 3d-harp and nurbs volumetric model. concerning analysis of tagged cardiac mr images, harmonic phase (harp) is a promising technique with the largest potential for clinical use in terms of rapidity and automation without tags detection and tracking. however, it is usually applied to 2d images and only provides "apparent motion" information. in this paper, harp is integrated with a nonuniform rational b-spline (nurbs) volumetric model to densely reconstruct 3d motion of left ventricle (lv). the nurbs model represents anatomy of lv compactly, and displacement information that harp provides within short-axis and long-axis images drives the model to deform. after estimating the motion at each phase, we smooth the nurbs models temporally to achieve a 4d continuous time-varying representation of lv motion. experimental results on in vivo data show that the proposed strategy could estimate 3d motion of lv rapidly and effectively benefiting from both harp and nurbs model.
task scheduling in large camera networks. camera networks are increasingly being deployed for security. in most of these camera networks, video sequences are captured, transmitted and archived continuously from all cameras, creating enormous stress on available transmission bandwidth, storage space and computing facilities. we describe an intelligent control system for scheduling pan-tilt-zoom cameras to capture video only when task-specific requirements can be satisfied. these videos are collected in real time during predicted temporal "windows of opportunity". we present a scalable algorithm that constructs schedules in which multiple tasks can possibly be satisfied simultaneously by a given camera. we describe two scheduling algorithms: a greedy algorithm and another based on dynamic programming (dp). we analyze their approximation factors and present simulations that show that the dp method is advantageous for large camera networks in terms of task coverage. results from a prototype real time active camera system however reveal that the greedy algorithm performs faster than the dp algorithm, making it more suitable for a real time system. the prototype system, built using existing low-level vision algorithms, also illustrates the applicability of our algorithms.
a local probabilistic prior-based active contour model for brain mr image segmentation. this paper proposes a probabilistic prior-based active contour model for segmenting human brain mr images. our model is formulated with the maximum a posterior (map) principle and implemented under the level set framework. probabilistic atlas for the structure of interest, e.g., cortical gray matter or caudate nucleus, can be seamlessly integrate into the level set evolution procedure to provide crucial guidance in accurately capturing the target. unlike other region-based active contour models, our solution uses locally varying gaussians to account for intensity inhomogeneity and local variations existing in many mr images are better handled. experiments conducted on whole brain as well as caudate segmentation demonstrate the improvement made by our model.
an active multi-camera motion capture for face, fingers and whole body. this paper explores a novel endeavor of deploying only four active-tracking cameras and fundamental vision-based technologies for 3d motion capture of a full human body figure, which includes facial expression, motion of fingers of both hands and a whole body. the proposed methods suggest alternatives to extract motion parameters of the mentioned body parts from four single-view image sequences. the proposed ellipsoidal model- and flow-based facial expression motion capture solution tackles both 3d head pose and non-rigid facial motion effectively and we observe that a set of 22 self-defined feature points suffice the expression representation. the body figure and fingers motion capture is solved with a combination of articulated model and flow-based methods.
exploiting inter-frame correlation for fast video to reference image alignment. strong temporal correlation between adjacent frames of a video signal has been successfully exploited in standard video compression algorithms. in this work, we show that the temporal correlation in a video signal can also be used for fast video to reference image alignment. to this end, we first divide the input video sequence into groups of pictures (gops). then for each gop, only one frame is completely correlated with the reference image, while for the remaining frames, upper and lower bounds on the correlation coefficient (ρ) are calculated. these newly proposed bounds are significantly tighter than the existing cauchy-schwartz inequality based bounds on ρ. these bounds are used to eliminate majority of the search locations and thus resulting in significant speedup, without effecting the value or location of the global maxima. in our experiments, up to 80% search locations are found to be eliminated and the speedup is up to five times the fft based implementation and up to seven times the spatial domain techniques.
a family of quadratic snakes for road extraction. the geographic information system industry would benefit from flexible automated systems capable of extracting linear structures from satellite imagery. quadratic snakes allow global interactions between points along a contour, and are well suited to segmentation of linear structures such as roads. however, a single quadratic snake is unable to extract disconnected road networks and enclosed regions. we propose to use a family of cooperating snakes, which are able to split, merge, and disappear as necessary. we also propose a preprocessing method based on oriented filtering, thresholding, canny edge detection, and gradient vector flow (gvf) energy. we evaluate the performance of the method in terms of precision and recall in comparison to ground truth data. the family of cooperating snakes consistently outperforms a single snake in a variety of road extraction tasks, and our method for obtaining the gvf is more suitable for road extraction tasks than standard methods.
automated removal of partial occlusion blur. this paper presents a novel, automated method to remove partial occlusion from a single image. in particular, we are concerned with occlusions resulting from objects that fall on or near the lens during exposure. for each such foreground object, we segment the completely occluded region using a geometric flow. we then look outward from the region of complete occlusion at the segmentation boundary to estimate the width of the partially occluded region. once the area of complete occlusion and width of the partially occluded region are known, the contribution of the foreground object can be removed. we present experimental results which demonstrate the ability of this method to remove partial occlusion with minimal user interaction. the result is an image with improved visibility in partially occluded regions, which may convey important information or simply improve the image's aesthetics.
hierarchical learning of dominant constellations for object class recognition. the importance of spatial configuration information for object class recognition is widely recognized. single isolated local appearance codes are often ambiguous. on the other hand, object classes are often characterized by groups of local features appearing in a specific spatial structure. learning these structures can provide additional discriminant cues and boost recognition performance. however, the problem of learning such features automatically from raw images remains largely uninvestigated. in contrast to previous approaches which require accurate localization and segmentation of objects to learn spatial information, we propose learning by hierarchical voting to identify frequently occurring spatial relationships among local features directly from raw images. the method is resistant to common geometric perturbations in both the training and test data. we describe a novel representation developed to this end and present experimental results that validate its efficacy by demonstrating the improvement in class recognition results realized by including the additional learned information.
multistrategical approach in visual learning. in this paper, we propose a novel visual learning framework to develop flexible and accurate object recognition methods. currently, most of visual learning based recognition methods adopt the monostrategy learning framework using a single feature. however, the real-world objects are so complex that it is quite difficult for monostrategy method to correctly classify them. thus, utilizing a wide variety of features is required to precisely distinguish them. in order to utilize various features, we propose multistrategical visual learning by integrating multiple visual learners. in our method, multiple visual learners are collaboratively trained. specifically, a visual learner l intensively learns the examples misclassified by the other visual learners. instead, the other visual learners learn the examples misclassified by l. as a result, a powerful object recognition method can be developed by integrating various visual learners even if they have mediocre recognition performance.
attention monitoring for music contents based on analysis of signal-behavior structures. in this paper, we propose a method to estimate user attention to displayed content signals with temporal analysis of their exhibited behavior. detecting user attention and controlling contents are key issues in our "networked interaction therapy system" that effectively attracts the attention of memory-impaired people. in our proposed method, user behavior, including body motions (beat actions), is detected with auditory/vision-based methods. this design is based on our observations of the behavior of memory-impaired people under video watching conditions. user attention to the displayed content is then estimated based on body motions synchronized to auditorial signals. estimated attention levels can be used for content control to attract deeper attention of viewers to the display system. experimental results suggest that the proposed method effectively extracts user attention to musical signals.
eye-gaze detection from monocular camera image using parametric template matching. in the coming ubiquitous-computing society, an eyegaze interface will be one of the key technologies as an input device. most of the conventional eyegaze tracking algorithms require specific light sources, equipments, devices, etc. in a previous work, the authors developed a simple eye-gaze detection system using a monocular video camera. this paper proposes a fast eye-gaze detection algorithm using the parametric template matching. in our algorithm, the iris extraction by the parametric template matching is applied to the eye-gaze detection based on physiological eyeball model. the parametric template matching can carry out an accurate sub-pixel matching by interpolating a few template images of a user's eye captured in the calibration process for personal error. so, a fast calculation can be realized with keeping the detection accuracy. we construct an eye-gaze communication interface using the proposed algorithm, and verified the performance through key typing experiments using visual keyboard on display.
improved background mixture models for video surveillance applications. background subtraction is a method commonly used to segment objects of interest in image sequences. by comparing new frames to a background model, regions of interest can be found. to cope with highly dynamic and complex environments, a mixture of several models has been proposed. this paper proposes an update of the popular mixture of gaussian models technique. experimental analysis shows a lack of this technique to cope with quick illumination changes. a different matching mechanism is proposed to improve the general robustness and a comparison with related work is given. finally, experimental results are presented to show the gain of the updated technique, according to the standard scheme and the related techniques.
fragments based parametric tracking. the paper proposes a parametric approach for color based tracking. the method fragments a multimodal color object into multiple homogeneous, unimodal, fragments. the fragmentation process consists of multi level thresholding of the object color space followed by an assembling. each homogeneous region is then modelled using a single parametric distribution and the tracking is achieved by fusing the results of the multiple parametric distributions. the advantage of the method lies in tracking complex objects with partial occlusions and various deformations like non-rigid, orientation and scale changes. we evaluate the performance of the proposed approach on standard and challenging real world datasets.
less is more: coded computational photography. computational photography combines plentiful computing, digital sensors, modern optics, actuators, and smart lights to escape the limitations of traditional cameras, enables novel imaging applications and simplifies many computer vision tasks. however, a majority of current computational photography methods involve taking multiple sequential photos by changing scene parameters and fusing the photos to create a richer representation. the goal of coded computational photography is to modify the optics, illumination or sensors at the time of capture so that the scene properties are encoded in a single (or a few) photographs. we describe several applications of coding exposure, aperture, illumination and sensing and describe emerging techniques to recover scene parameters from coded photographs.
tracking and classifying of human motions with gaussian process annealed particle filter. this paper presents a framework for 3d articulated human body tracking and action classification. the method is based on nonlinear dimensionality reduction of high dimensional data space to low dimensional latent space. motion of human body is described by concatenation of low dimensional manifolds which characterize different motion types. we introduce a body pose tracker, which uses the learned mapping function from low dimensional latent space to high dimensional body pose space. the trajectories in the latent space provide low dimensional representations of body poses performed during motion. they are used to classify human actions. the approach was checked on humaneva dataset as well as on our own one. the results and the comparison to other methods are presented.
mirror localization for catadioptric imaging system by observing parallel light pairs. this paper describes a method of mirror localization to calibrate a catadioptric imaging system. while the calibration of a catadioptric system includes the estimation of various parameters, we focus on the localization of the mirror. the proposed method estimates the position of the mirror by observing pairs of parallel lights, which are projected from various directions. although some earlier methods for calibrating catadioptric systems assume that the system is single viewpoint, which is a strong restriction on the position and shape of the mirror, our method does not restrict the position and shape of the mirror. since the constraint used by the proposed method is that the relative angle of two parallel lights is constant with respect to the rigid transformation of the imaging system, we can omit both the translation and rotation between the camera and calibration objects from the parameters to be estimated. therefore, the estimation of the mirror position by the proposed method is independent of the extrinsic parameters of a camera. we compute the error between the model of the mirror and the measurements, and then estimate the position of the mirror by minimizing this error. we test our method using both simulation and real experiments, and evaluate the accuracy thereof.
automated billboard insertion in video. the paper proposes an approach to superimpose virtual contents for advertising in an existing image sequence with no or minimal user interaction. our approach automatically recognizes planar surfaces in the scene over which a billboard can be inserted for seamless display to the viewers. the planar surfaces are segmented in the image frame using a homography dependent scheme. in each of the segmented planar regions, a rectangle with the largest area is located to superimpose a billboard into the original image sequence. it can also provide a viewing index based on the occupancy of the virtual real estate for charging the advertiser.
gait identification based on multi-view observations using omnidirectional camera. we propose a method of gait identification based on multiview gait images using an omnidirectional camera. we first transform omnidirectional silhouette images into panoramic ones and obtain a spatio-temporal gait silhouette volume (gsv). next, we extract frequency-domain features by fourier analysis based on gait periods estimated by autocorrelation of the gsvs. because the omnidirectional camera makes it possible to observe a straight-walking person from various views, multiview features can be extracted from the gsvs composed of multi-view images. in an identification phase, distance between a probe and a gallery feature of the same view is calculated, and then these for all views are integrated for matching. experiments of gait identification including 15 subjects from 5 views demonstrate the effectiveness of the proposed method.
high dynamic range scene realization using two complementary images. many existing tone reproduction schemes are based on the use of a single high dynamic range (hdr) image and are therefore unable to accurately recover the local details and colors of the scene due to the limited information available. accordingly, the current study develops a novel tone reproduction system which utilizes two images with different exposures to capture both the local details and color information of the low- and high-luminance regions of a scene. by computing the local region of each pixel, whose radius is determined via an iterative morphological erosion process, the proposed system implements a pixel-wise local tone mapping module which compresses the luminance range and enhances the local contrast in the low-exposure image. and a local color mapping module is applied to capture the precise color information from the high-exposure image. subsequently, a fusion process is then performed to fuse the local tone mapping and color mapping results to generate highly realistic reproductions of hdr scenes.
human pose estimation from volume data and topological graph database. this paper proposes a novel volume-based motion capture method using a bottom-up analysis of volume data and an example topology database of the human body. by using a two-step graph matching algorithm with many example topological graphs corresponding to postures that a human body can take, the proposed method does not require any initial parameters or iterative convergence processes, and it can solve the changing topology problem of the human body. first, three-dimensional curved lines (skeleton) are extracted from the captured volume data using the thinning process. the skeleton is then converted into an attributed graph. by using a graph matching algorithm with a large amount of example data, we can identify the body parts from each curved line in the skeleton. the proposed method is evaluated using several video sequences of a single person and multiple people, and we can confirm the validity of our approach.
non-parametric background and shadow modeling for object detection. we propose a fast algorithm to estimate background models using parzen density estimation in non-stationary scenes. each pixel has a probability density which approximates pixel values observed in a video sequence. it is important to estimate a probability density function fast and accurately. in our approach, the probability density function is partially updated within the range of the window function based on the observed pixel value. the model adapts quickly to changes in the scene and foreground objects can be robustly detected. in addition, applying our approach to cast-shadow modeling, we can detect moving cast shadows. several experiments show the effectiveness of our approach.
on-line ensemble svm for robust object tracking. in this paper, we present a novel visual object tracking algorithm based on ensemble of linear svm classifiers. there are two main contributions in this paper. first of all, we propose a simple yet effective way for on-line updating linear svm classifier, where useful "key frames" of target are automatically selected as support vectors. secondly, we propose an on-line ensemble svm tracker, which can effectively handle target appearance variation. the proposed algorithm makes better usage of history information, which leads to better discrimination of target and the surrounding background. the proposed algorithm is tested on many video clips including some public available ones. experimental results show the robustness of our proposed algorithm, especially under large appearance change during tracking.
road sign detection using eigen color. this paper presents a novel color-based method to detect road signs directly from videos. a road sign usually has specific colors and high contrast to its background. traditional color-based approaches need to train different color detectors for detecting road signs if their colors are different. this paper presents a novel color model derived from karhunen-loeve (kl) transform to detect road sign color pixels from the background. the proposed color transform model is invariant to different perspective effects and occlusions. furthermore, only one color model is needed to detect various road signs. after transformation into the proposed color space, a rbf (radial basis function) network is trained for finding all possible road sign candidates. then, a verification process is applied to these candidates according to their edge maps. due to the filtering effect and discriminative ability of the proposed color model, different road signs can be very efficiently detected from videos. experiment results have proved that the proposed method is robust, accurate, and powerful in road sign detection.
logical dp matching for detecting similar subsequence. a logical dynamic programming (dp) matching algorithm is proposed for extracting similar subpatterns from two sequential patterns. in the proposed algorithm, local similarity between two patterns is measured by a logical function, called support. the dp matching with the support can extract all similar subpatterns simultaneously while compensating nonlinear fluctuation. the performance of the proposed algorithm was evaluated qualitatively and quantitatively via an experiment of extracting motion primitives, i.e., common subpatterns in gesture patterns of different classes.
multi-view gymnastic activity recognition with fused hmm. more and more researchers focus their studies on multiview activity recognition, because a fixed view could not provide enough information for recognition. in this paper, we use multi-view features to recognize six kinds of gymnastic activities. firstly, shape-based features are extracted from two orthogonal cameras in the form of r transform. then a multi-view approach based on fused hmm is proposed to combine different features for similar gymnastic activity recognition. compared with other activity models, our method achieves better performance even in the case of frame loss.
adaboost learning for human detection based on histograms of oriented gradients. we developed a novel learning-based human detection system, which can detect people having different sizes and orientations, under a wide variety of backgrounds or even with crowds. to overcome the affects of geometric and rotational variations, the system automatically assigns the dominant orientations of each block-based feature encoding by using the rectangular- and circular-type histograms of orientated gradients (hog), which are insensitive to various lightings and noises at the outdoor environment. moreover, this work demonstrated that gaussian weight and tri-linear interpolation for hog feature construction can increase detection performance. particularly, a powerful feature selection algorithm, adaboost, is performed to automatically select a small set of discriminative hog features with orientation information in order to achieve robust detection results. the overall computational time is further reduced significantly without any performance loss by using the cascade-ofrejecter structure, whose hyperplanes and weights of each stage are estimated by using the adaboost approach.
object detection combining recognition and segmentation. we develop an object detection method combining top-down recognition with bottom-up image segmentation. there are two main steps in this method: a hypothesis generation step and a verification step. in the top-down hypothesis generation step, we design an improved shape context feature, which is more robust to object deformation and background clutter. the improved shape context is used to generate a set of hypotheses of object locations and figure-ground masks, which have high recall and low precision rate. in the verification step, we first compute a set of feasible segmentations that are consistent with top-down object hypotheses, then we propose a false positive pruning (fpp) procedure to prune out false positives. we exploit the fact that false positive regions typically do not align with any feasible image segmentation. experiments show that this simple framework is capable of achieving both high recall and high precision with only a few positive training examples and that this method can be generalized to many object classes.
discriminative mean shift tracking with auxiliary particles. we present a new approach towards efficient and robust tracking by incorporating the efficiency of the mean shift algorithm with the robustness of the particle filtering. the mean shift tracking algorithm is robust and effective when the representation of a target is sufficiently discriminative, the target does not jump beyond the bandwidth, and no serious distractions exist. in case of sudden motion, the particle filtering outperforms the mean shift algorithm at the expense of using a large particle set. in our approach, the mean shift algorithm is used as long as it provides reasonable performance. auxiliary particles are introduced to conquer the distraction and sudden motion problems when such threats are detected. moreover, discriminative features are selected according to the separation of the foreground and background distributions. we demonstrate the performance of our approach by comparing it with other trackers on challenging image sequences.
efficient normalized cross correlation based on adaptive multilevel successive elimination. in this paper we propose an efficient normalized cross correlation (ncc) algorithm for pattern matching based on adaptive multilevel successive elimination. this successive elimination scheme is applied in conjunction with an upper bound for the cross correlation derived from cauchy-schwarz inequality. to apply the successive elimination, we partition the summation of cross correlation into different levels with the partition order determined by the gradient energies of the partitioned regions in the template. thus, this adaptive multi-level successive elimination scheme can be employed to early reject most candidates to reduce the computational cost. experimental results show the proposed algorithm is very efficient for pattern matching under different lighting conditions.
efficient texture representation using multi-scale regions. this paper introduces an efficient way of representing textures using connected regions which are formed by coherent multi-scale over-segmentations. we show that the recently introduced covariance-based similarity measure, initially applied on rectangular windows, can be used with our newly devised, irregular structure-coherent patches; increasing the discriminative power and consistency of the texture representation. furthermore, by treating texture in multiple scales, we allow for an implicit encoding of the spatial and statistical texture properties which are persistent across scale. the meaningfulness and efficiency of the covariance based texture representation is verified utilizing a simple binary segmentation method based on min-cut. our experiments show that the proposed method, despite the low dimensional representation in use, is able to effectively discriminate textures and that its performance compares favorably with the state of the art.
tracking iris contour with a 3d eye-model for gaze estimation. this paper describes a sophisticated method to track iris contour and to estimate eye gaze for blinking eyes with a monocular camera. a 3d eye-model that consists of eyeballs, iris contours and eyelids is designed that describes the geometrical properties and the movements of eyes. both the iris contours and the eyelid contours are tracked by using this eye-model and a particle filter. this algorithm is able to detect "pure" iris contours because it can distinguish iris contours from eyelids contours. the eye gaze is described by the movement parameters of the 3d eye model, which are estimated by the particle filter during tracking. other distinctive features of this algorithm are: 1) it does not require any special light sources (e.g. an infrared illuminator) and 2) it can operate at video rate. through extensive experiments on real video sequences we confirmed the robustness and the effectiveness of our method.
feature management for efficient camera tracking. in dynamic scenes with occluding objects many features need to be tracked for a robust real-time camera pose estimation. an open problem is that tracking too many features has a negative effect on the real-time capability of a tracking approach. this paper proposes a method for the feature management which performs a statistical analysis of the ability to track a feature and then uses only those features which are very likely to be tracked from a current camera position. thereby a large set of features in different scales is created, where every feature holds a probability distribution of camera positions from which the feature can be tracked successfully. as only the feature points with the highest probability are used in the tracking step, the method can handle a large amount of features in different scale without losing the ability of real time performance. both the statistical analysis and the reconstruction of the features' 3d coordinates are performed online during the tracking and no preprocessing step is needed.
multi-posture human detection in video frames by motion contour matching. in the paper, we proposed a method for moving human detection in video frames by motion contour matching. firstly, temporal and spatial difference of frames is calculated and contour pixels are extracted by global thresholding as the basic features. then, skeleton templates with multiple representative postures are built on these features to represent multiposture human contours. in the detection procedure, a dynamic programming algorithm is adopted to find best global match between the built templates and with extracted contour features. finally a thresholding method is used to classify a matching result into moving human or negatives. and in the matching process scale problem and interpersonal contour difference are considered. experiments on real video data prove the effectiveness of the proposed method.
measurement of reflection properties in ancient japanese drawing ukiyo-e. ukiyo-e is one famous traditional woodblock type japanese drawing. some pattern printed by special print techniques can only be seen from some special direction. this phenomenon relate to the reflection properties on the surface of ukiyo-e. in this paper, we propose a method to measure these reflection properties of ukiyo-e. fitstly, the normal on the surface and the direction of the fiber in japanese paper are computed from photos which are taken by a measuring machine named ogm. then, fit the reflection model to the measured data and the reflection properties of ukiyo-e can be obtained. based on these parameters, the the appearance of ukiyo-e can be rendered on real-time.
camera calibration using principal-axes aligned conics. the projective geometric properties of two principal-axes aligned (paa) conics in a model plane are investigated in this paper by utilized the generalized eigenvalue decomposition (ged). we demonstrate that one constraint on the image of the absolute conic (iac) can be obtained from a single image of two paa conics even if their parameters are unknown. and if the eccentricity of one of the two conics is given, two constraints on the iac can be obtained. an important merit of the algorithm using paa is that it can be employed to avoid the ambiguities when estimating extrinsic parameters in the calibration algorithms using concentric circles. we evaluate the characteristics and robustness of the proposed algorithm in experiments with synthetic and real data.
color constancy via convex kernel optimization. this paper introduces a novel convex kernel based method for color constancy computation with explicit illuminant parameter estimation. a simple linear render model is adopted and the illuminants in a new scene that contains some of the color surfaces seen in the training image are sequentially estimated in a global optimization framework. the proposed method is fully data-driven and initialization invariant. nonlinear color constancy can also be approximately solved in this kernel optimization framework with piecewise linear assumption. extensive experiments on real-scene images validate the practical performance of our method.
kernel-bayesian framework for object tracking. this paper proposes a general kernel-bayesian framework for object tracking. in this framework, the kernel based method--mean shift algorithm is embedded into the bayesian framework seamlessly to provide a heuristic prior information to the state transition model, aiming at effectively alleviating the heavy computational load and avoiding sample degeneracy suffered by the conventional bayesian trackers. moreover, the tracked object is characterized by a spatial-constraint mog (mixture of gaussians) based appearance model, which is shown more discriminative than the traditional mog based appearance model. meantime, a novel selective updating technique for the appearance model is developed to accommodate the changes in both appearance and illumination. experimental results demonstrate that, compared with bayesian and kernel based tracking frameworks, the proposed algorithm is more efficient and effective.
optimal learning high-order markov random fields priors of colour image. in this paper, we present an optimised learning algorithm for learning the parametric prior models for high-order markov random fields (mrf) of colour images. compared to the priors used by conventional low-order mrfs, the learned priors have richer expressive power and can capture the statistics of natural scenes. our proposed optimal learning algorithm is achieved by simplifying the estimation of partition function without compromising the accuracy of the learned model. the parameters in mrf colour image priors are learned alternatively and iteratively in an em-like fashion by maximising their likelihood. we demonstrate the capability of the proposed learning algorithm of high-order mrf colour image priors with the application of colour image denoising. experimental results show the superior performance of our algorithm compared to the state-of-the-art of colour image priors in [1], although we use a much smaller training image set.
near-optimal mosaic selection for rotating and zooming video cameras. applying graph-theoretic concepts to solve computer vision problems makes it not only trivial to analyze the complexity of the problem at hand, but also existing algorithms from the graph-theory literature can be used to find a solution. we consider the challenging tasks of frame selection for use in mosaicing, and feature selection from computer vision, andmachine learning, respectively, and demonstrate that we can map these problems into the existing graph theory problem of finding the maximum independent set. for frame selection, we represent the temporal and spatial connectivity of the images in a video sequence by a graph, and demonstrate that the optimal subset of images to be used in mosaicing can be determined by finding the maximum independent set of the graph. this process of determining the maximum independent set, not only reduces the overhead of using all the images, which may not be significantly contributing in building the mosaic, but also implicitly solves the "camera loop-back" problem. for feature selection, we conclude that we can apply a similar mapping to the maximum independent set problem to obtain a solution. finally, to demonstrate the efficacy of our frame selection method, we build a system for mosaicing, which uses our method of frame selection.
efficient registration of aerial image sequences without camera priors. we present an efficient approach for finding homographies between sequences of aerial images. we propose a two-step approach: a) initially solving for image-plane rotation and scale parameters without using correspondence (under affine assumption), and b) using these parameters to constrain the full homography search, and c) extending the results to full perspective projection. no flight meta-data, camera priors, or any other user defined information is used for the task. based on the perspective parameters estimated, the aerial images are stitched with the best matching image based on a probabilistic model, to compose a high resolution aerial image mosaic. while retaining the improved asymptotic worst-case complexity of [6], we demonstrate significant performance improvements in practice.
three dimensional position measurement for maxillofacial surgery by stereo x-ray images. this paper describes a method whereby a three dimensional position inside a human body can be measured using a simple x-ray stereo image pair. because the geometry of x-ray imaging is similar to that of ordinary photography, a standard stereo vision technique can be used. however, one problem is that the x-ray source position is unknown and should be computed from the x-ray image. in addition, a reference coordinate on which the measurement is based needs to be determined. the proposed method solves these two problems using a cubic wire frame called the reference object. although three dimensional positioning for a human body is possible by computer tomography (ct), it requires expensive equipment. in contrast, the proposed method only requires ordinary x-ray photography equipment, which is inexpensive and widely available even in developing countries.
the kernel orthogonal mutual subspace method and its application to 3d object recognition. this paper proposes the kernel orthogonal mutual subspace method (komsm) for 3d object recognition. komsm is a kernel-based method for classifying sets of patterns such as video frames or multiview images. it classifies objects based on the canonical angles between the nonlinear subspaces, which are generated from the image patterns of each object class by kernel pca. this methodology has been introduced in the kernel mutual subspace method (kmsm). however, komsm is different from kmsm in that nonlinear class subspaces are orthogonalized based on the framework proposed by fukunaga and koontz before calculating the canonical angles. this orthogonalization provides a powerful feature extraction method for improving the performance of kmsm. the validity of komsm is demonstrated through experiments using face images and images from a public database.
video mosaicing based on structure from motion for distortion-free document digitization. this paper presents a novel video mosaicing method capable of generating a geometric distortion-free mosaic image using a hand-held camera. for a document composed of curved pages, mosaic images of virtually flattened pages are generated. the process of our method is composed of two stages : real-time stage and off-line stage. in the realtime stage, image features are automatically tracked on the input images, and the viewpoint of each image as well as the 3-d position of each image feature are estimated by a structure-from-motion technique. in the offline stage, the estimated viewpoint and 3-d position of each feature are refined and utilized to generate a geometric distortion-free mosaic image. we demonstrate our prototype system on curved documents to show the feasibility of our approach.
image segmentation using co-em strategy. inspired by the idea of multi-view, we proposed an image segmentation algorithm using co-em strategy in this paper. image data are modeled using gaussian mixture model (gmm), and two sets of features, i.e. two views, are employed using co-em strategy instead of conventional single view based em to estimate the parameters of gmm. compared with the single view based gmm-em methods, there are several advantages with the proposed segmentation method using co-em strategy. first, imperfectness of single view can be compensated by the other view in the co-em. second, employing two views, co-em strategy can offer more reliability to the segmentation results. third, the drawback of local optimality for single view based em can be overcome to some extent. fourth, the convergence rate is improved. the average time is far less than single view based methods. we test the proposed method on large number of images with no specified contents. the experimental results verify the above advantages, and outperform the single view based gmm-em segmentation methods.
efficiently solving the fractional trust region problem. normalized cuts has successfully been applied to a wide range of tasks in computer vision, it is indisputably one of the most popular segmentation algorithms in use today. a number of extensions to this approach have also been proposed, ones that can deal with multiple classes or that can incorporate a priori information in the form of grouping constraints. it was recently shown how a general linearly constrained normalized cut problem can be solved. this was done by proving that strong duality holds for the lagrangian relaxation of such problems. this provides a principled way to perform multi-class partitioning while enforcing any linear constraints exactly. the lagrangian relaxation requires the maximization of the algebraically smallest eigenvalue over a one-dimensional matrix sub-space. this is an unconstrained, piece-wise differentiable and concave problem. in this paper we show how to solve this optimization efficiently even for very large-scale problems. the method has been tested on real data with convincing results.
sequential l norm minimization for triangulation. it has been shown that various geometric vision problems such as triangulation and pose estimation can be solved optimally by minimizing l∞ error norm. this paper proposes a novel algorithm for sequential estimation. when a measurement is given at a time instance, applying the original batch bi-section algorithm is very much inefficient because the number of seocnd order constraints increases as time goes on and hence the computational cost increases accordingly. this paper shows that, the upper and lower bounds, which are two input parameters of the bi-section method, can be updated through the time sequence so that the gap between the two bounds is kept as small as possible. furthermore, we may use only a subset of all the given measurements for the l∞ estimation. this reduces the number of constraints drastically. finally, we do not have to reestimate the parameter when the reprojection error of the measurement is smaller than the estimation error. these three provide a very fast l∞ estimation through the sequence; our method is suitable for real-time or on-line sequential processing under l∞ optimality. this paper particularly focuses on the triangulation problem, but the algorithm is general enough to be applied to any l∞ problems.
transformesh : a topology-adaptive mesh-based approach to surface evolution. most of the algorithms dealing with image based 3-d reconstruction involve the evolution of a surface based on a minimization criterion. the mesh parametrization, while allowing for an accurate surface representation, suffers from the inherent problems of not being able to reliably deal with selfintersections and topology changes. as a consequence, an important number of methods choose implicit representations of surfaces, e.g. level set methods, that naturally handle topology changes and intersections. nevertheless, these methods rely on space discretizations, which introduce an unwanted precision-complexity trade-off. in this paper we explore a new mesh-based solution that robustly handles topology changes and removes self intersections, therefore overcoming the traditional limitations of this type of approaches. to demonstrate its efficiency, we present results on 3-d surface reconstruction from multiple images and compare them with state-of-the art results.
analyzing the influences of camera warm-up effects on image acquisition. this article presents an investigation of the impact of camera warmup on the image acquisition process and therefore on the accuracy of segmented image features. based on an experimental study we show that the camera image is shifted to an extent of some tenth of a pixel after camera start-up. the drift correlates with the temperature of the sensor board and stops when the camera reaches its thermal equilibrium. a further study of the observed image flow shows that it originates from a slight displacement of the image sensor due to thermal expansion of the mechanical components of the camera. this sensor displacement can be modeled using standard methods of projective geometry in addition with bi-exponential decay terms to model the temporal dependence. the parameters of the proposed model can be calibrated and then used to compensate warmup effects. further experimental studies show that our method is applicable to different types of cameras and that the warm-up behaviour is characteristic for a specific camera.
converting thermal infrared face images into normal gray-level images. in this paper, we address the problem of producing visible spectrum facial images as we normally see by using thermal infrared images. we apply canonical correlation analysis (cca) to extract the features, converting a many-to-many mapping between infrared and visible images into a one-to-one mapping approximately. then we learn the relationship between two feature spaces in which the visible features are inferred from the corresponding infrared features using locally-linear regression (llr) or, what is called, sophisticated lle, and a locally linear embedding (lle) method is used to recover a visible image from the inferred features, recovering some information lost in the infrared image. experiments demonstrate that our method maintains the global facial structure and infers many local facial details from the thermal infrared images.
face mosaicing for pose robust video-based recognition. this paper proposes a novel face mosaicing approach to modeling human facial appearance and geometry in a unified framework. the human head geometry is approximated with a 3d ellipsoid model. multi-view face images are back projected onto the surface of the ellipsoid, and the surface texture map is decomposed into an array of local patches, which are allowed to move locally in order to achieve better correspondences among multiple views. finally the corresponding patches are trained to model facial appearance. and a deviation model obtained from patch movements is used to model the face geometry. our approach is applied to pose robust face recognition. using the cmu pie database, we show experimentally that the proposed algorithm provides better performance than the baseline algorithms. we also extend our approach to video-based face recognition and test it on the face in action database.
simultaneous appearance modeling and segmentation for matching people under occlusion. we describe an approach to segmenting foreground regions corresponding to a group of people into individual humans. given background subtraction and ground plane homography, hierarchical parttemplate matching is employed to determine a reliable set of human detection hypotheses, and progressive greedy optimization is performed to estimate the best configuration of humans under a bayesian map framework. then, appearance models and segmentations are simultaneously estimated in an iterative sampling-expectation paradigm. each human appearance is represented by a nonparametric kernel density estimator in a joint spatial-color space and a recursive probability update scheme is employed for soft segmentation at each iteration. additionally, an automatic occlusion reasoning method is used to determine the layered occlusion status between humans. the approach is evaluated on a number of images and videos, and also applied to human appearance matching using a symmetric distance measure derived from the kullback-leiber divergence.
crystal vision-applications of point groups in computer vision. methods from the representation theory of finite groups are used to construct efficient processing methods for the special geometries related to the finite subgroups of the rotation group. we motivate the use of these subgroups in computer vision, summarize the necessary facts from the representation theory and develop the basics of fourier theory for these geometries. we illustrate its usage for data compression in applications where the processes are (on average) symmetrical with respect to these groups. we use the icosahedral group as an example since it is the largest finite subgroup of the 3d rotation group. other subgroups with fewer group elements can be studied in exactly the same way.
three-stage motion deblurring from a video. in this paper, a novel approach is proposed to remove the motion blur from a video, which is degraded and distorted by fast camera motion. our approach is based on the image statistics rather than the traditional motion estimation. the image statistics has been successfully applied for blind motion deblurring for a single image by fergus et al [3] and levin [10]. here a three-stage method is used to deal with the video. first, the "unblurred" frames in the video can be found based on the image statistics. then the blur functions can be obtained by comparing the blurred frames with the unblurred ones. finally a standard deconvolution algorithm is used to reconstruct the video. our experiments show that our algorithms are efficient.
interpolation between eigenspaces using rotation in multiple dimensions. we propose a method for interpolation between eigenspaces. techniques that represent observed patterns as multivariate normal distribution have actively been developed to make it robust over observation noises. in the recognition of images that vary based on continuous parameters such as camera angles, one cause that degrades performance is training images that are observed discretely while the parameters are varied continuously. the proposed method interpolates between eigenspaces by analogy from rotation of a hyper-ellipsoid in high dimensional space. experiments using face images captured in various illumination conditions demonstrate the validity and effectiveness of the proposed interpolation method.
sign recognition using constrained optimization. sign recognition has been one of the challenging problems in computer vision for years. for many sign languages, signs formed by two overlapping hands are a part of the vocabulary. in this work, an algorithm for recognizing such signs with overlapping hands is presented. two formulations are proposed for the problem. for both approaches, the input blob is converted to a graph representing the finger and palm structure which is essential for sign understanding. the first approach uses a graph subdivision as the basic framework, while the second one casts the problem to a label assignment problem and integer programming is applied for finding an optimal solution. experimental results are shown to illustrate the feasibility of our approaches.
automatic range image registration using mixed integer linear programming. a coarse registration method using mixed integer linear programming (milp) is described that finds global optimal registration parameter values that are independent of the values of invariant features. we formulate the range image registration problem using milp. our algorithm using milp formulation finds the best balanced optimal registration for robustly aligning two range images with the best balanced accuracy. it adjusts the error tolerance automatically in accordance with the accuracy of the given range image data. experimental results show that this method of coarse registration is highly effective.
an all-subtrees approach to unsupervised parsing. we investigate generalizations of the all-subtrees "dop" approach to unsupervised parsing. unsupervised dop models assign all possible binary trees to a set of sentences and next use (a large random subset of) all subtrees from these binary trees to compute the most probable parse trees. we will test both a relative frequency estimator for unsupervised dop and a maximum likelihood estimator which is known to be statistically consistent. we report state-of-the-art results on english (wsj), german (negra) and chinese (ctb) data. to the best of our knowledge this is the first paper which tests a maximum likelihood estimator for dop on the wall street journal, leading to the surprising result that an unsupervised parsing model beats a widely used supervised model (a treebank pcfg).
spoken dialogue interpretation with the dop model. we show how the dop model can be used for fast and robust processing of spoken input in a practical spoken dialogue system called ovis. ovis, openbaar vervoer informatie systeem ("public transport information system"), is a dutch spoken language information system which operates over ordinary telephone lines. the prototype system is the immediate goal of the nwo1 priority programme "language and speech technology". in this paper, we extend the original dop model to context-sensitive interpretation of spoken input. the system we describe uses the ovis corpus (10,000 trees enriched with compositional semantics) to compute from an input word-graph the best utterance together with its meaning. dialogue context is taken into account by dividing up the ovis corpus into context-dependent subcorpora. each system question triggers a subcorpus by which the user answer is analyzed and interpreted. our experiments indicate that the context-sensitive dop model obtains better accuracy than the original model, allowing for fast and robust processing of spoken input.
a bootstrapping approach to unsupervised detection of cue phrase variants. we investigate the unsupervised detection of semi-fixed cue phrases such as "this paper proposes a novel approach...1" from unseen text, on the basis of only a handful of seed cue phrases with the desired semantics. the problem, in contrast to bootstrapping approaches for question answering and information extraction, is that it is hard to find a constraining context for occurrences of semi-fixed cue phrases. our method uses components of the cue phrase itself, rather than external context, to bootstrap. it successfully excludes phrases which are different from the target semantics, but which look superficially similar. the method achieves 88% accuracy, outperforming standard bootstrapping approaches.
a probabilistic corpus-driven model for lexical-functional analysis. we develop a data-oriented parsing (dop) model based on the syntactic representations of lexical-functional grammar (lfg). we start by summarizing the original dop model for tree representations and then show how it can be extended with corresponding functional structures. the resulting lfg-dop model triggers a new, corpus-based notion of grammaticality, and its probability models exhibit interesting behavior with respect to specificity and the interpretation of ill-formed strings.
polynominal learnability and locality of formal grammars. we apply a complexity theoretic notion of feasible learnability called "polynomial learnability" to the evaluation of grammatical formalisms for linguistic description. we show that a novel, nontrivial constraint on the degree of "locality" of grammars allows not only context free languages but also a rich class of mildy context sensitive languages to be polynomially learnable. we discuss possible implications of this result to the theory of natural language acquisition.
lexical and syntactic rules in a tree adjoining grammar. taking examples from english and french idioms, this paper shows that not only constituent structures rules but also most syntactic rules (such as topicalization, wh-question, pronominalization ...) are subject to lexical constraints (on top of syntactic, and possibly semantic, ones). we show that such puzzling phenomena are naturally handled in a 'lexicalized' formalism such as tree adjoining grammar. the extended domain of locality of tags also allows one to 'jexicalize' syntactic rules while defining them at the level of constituent structures.
japanese dependency parsing using co-occurrence information and a combination of case elements. in this paper, we present a method that improves japanese dependency parsing by using large-scale statistical information. it takes into account two kinds of information not considered in previous statistical (machine learning based) parsing methods: information about dependency relations among the case elements of a verb, and information about co-occurrence relations between a verb and its case element. this information can be collected from the results of automatic dependency parsing of large-scale corpora. the results of an experiment in which our method was used to rerank the results obtained using an existing machine learning based parsing method showed that our method can improve the accuracy of the results obtained using the existing method.
construct algebra: analytical dialog management. in this paper we describe a systematic approach for creating a dialog management system based on a construct algebra, a collection of relations and operations on a task representation. these relations and operations are analytical components for building higher level abstractions called dialog motivators. the dialog manager, consisting of a collection of dialog motivators, is entirely built using the construct algebra.
scaling to very very large corpora for natural language disambiguation. the amount of readily available on-line text has reached hundreds of billions of words and continues to grow. yet for most core natural language tasks, algorithms continue to be optimized, tested and compared after training on corpora consisting of only one million words or less. in this paper, we evaluate the performance of different learning methods on a prototypical natural language disambiguation task, confusion set disambiguation, when trained on orders of magnitude more labeled data than has previously been used. we are fortunate that for this particular application, correctly labeled training data is free. since this will often not be the case, we examine methods for effectively exploiting very large corpora when labeled data comes at a cost.
bootstrapping. this paper refines the analysis of co-training, defines and evaluates a new co-training algorithm that has theoretical justification, gives a theoretical justification for the yarowsky algorithm, and shows that co-training and the yarowsky algorithm are based on different independence assumptions.
headline generation based on statistical translation. extractive summarization techniques cannot generate document summaries shorter than a single sentence, something that is often required. an ideal summarization system would understand each document and generate an appropriate summary directly from the results of that understanding. a more practical approach to this problem results in the use of an approximation: viewing summarization as a problem analogous to statistical machine translation. the issue then becomes one of generating a target document in a more concise language from a source document in a more verbose language. this paper presents results on experiments using this approach, in which statistical models of the term selection and term ordering are jointly applied to produce summaries in a style learned from a training corpus.
relating probabilistic grammars and automata. both probabilistic context-free grammars (pcfgs) and shift-reduce probabilistic pushdown automata (ppdas) have been used for language modeling and maximum likelihood parsing. we investigate the precise relationship between these two formalisms, showing that, while they define the same classes of probabilistic languages, they appear to impose different inductive biases.
paraphrasing with bilingual parallel corpora. previous work has used monolingual parallel corpora to extract and generate paraphrases. we show that this task can be done using bilingual parallel corpora, a much more commonly available resource. using alignment techniques from phrase-based statistical machine translation, we show how paraphrases in one language can be identified using a phrase in another language as a pivot. we define a paraphrase probability that allows paraphrases extracted from a bilingual parallel corpus to be ranked using translation probabilities, and show how it can be refined to take contextual information into account. we evaluate our paraphrase extraction and ranking methods using a set of manual word alignments, and contrast the quality with paraphrases extracted from automatic alignments.
an unsupervised morpheme-based hmm for hebrew morphological disambiguation. morphological disambiguation is the process of assigning one set of morphological features to each individual word in a text. when the word is ambiguous (there are several possible analyses for the word), a disambiguation procedure based on the word context must be applied. this paper deals with morphological disambiguation of the hebrew language, which combines morphemes into a word in both agglutinative and fusional ways. we present an un-supervised stochastic model - the only resource we use is a morphological analyzer-which deals with the data sparseness problem caused by the affixational morphology of the hebrew language.we present a text encoding method for languages with affixational morphology in which the knowledge of word formation rules (which are quite restricted in hebrew) helps in the disambiguation. we adapt hmm algorithms for learning and searching this text representation, in such a way that segmentation and tagging can be learned in parallel in one step. results on a large scale evaluation indicate that this learning improves disambiguation for complex tag sets. our method is applicable to other languages with affix morphology.
evaluation tool for rule-based anaphora resolution methods. in this paper we argue that comparative evaluation in anaphora resolution has to be performed using the same pre-processing tools and on the same set of data. the paper proposes an evaluation environment for comparing anaphora resolution algorithms which is illustrated by presenting the results of the comparative evaluation of three methods on the basis of several evaluation measures.
evaluation of semantic clusters. semantic clusters of a domain form an important feature that can be useful for performing syntactic and semantic disambiguation. several attempts have been made to extract the semantic clusters of a domain by probabilistic or taxonomic techniques. however, not much progress has been made in evaluating the obtained semantic clusters. this paper focuses on an evaluation mechanism that can be used to evaluate semantic clusters produced by a system against those provided by human experts.
processing unknown words in hpsg. the lexical acquisition system presented in this paper incrementally updates linguistic properties of unknown words inferred from their surrounding context by parsing sentences with an hpsg grammar for german. we employ a gradual, information-based concept of "unknownness" providing a uniform treatment for the range of completely known to maximally unknown lexical entries. "unknown" information is viewed as revisable information, which is either generalizable or specializable. updating takes place after parsing, which only requires a modified lexical lookup. revisable pieces of information are identified by grammar-specified declarations which provide access paths into the parse feature structure. the updating mechanism revises the corresponding places in the lexical feature structures iff the context actually provides new information. for revising generalizable information, type union is required. a worked-out example demonstrates the inferential capacity of our implemented system.
a simple but useful approach to conjunct identification. this paper presents an approach to identifying conjuncts of coordinate conjunctions appearing in text which has been labelled with syntactic and semantic tags. the overall project of which this research is a part is also briefly discussed. the program was tested on a 10,000 word chapter of the merck veterinary manual. the algorithm is deterministic and domain independent and it performs relatively well on a large real-life domain. constructs not handled by the simple algorithm are also described in some detail.
semi-automatic recognition of noun modifier relationships. semantic relationships among words and phrases are often marked by explicit syntactic or lexical clues that help recognize such relationships in texts. within complex nominals, however, few overt clues are available. systems that analyze such nominals must compensate for the lack of surface clues with other information. one way is to load the system with lexical semantics for nouns or adjectives. this merely shifts the problem elsewhere: how do we define the lexical semantics and build large semantic lexicons? another way is to find constructions similar to a given complex nominal, for which the relationships are already known. this is the way we chose, but it too has drawbacks. similarity is not easily assessed, similar analyzed constructions may not exist, and if they do exist, their analysis may not be appropriate for the current nominal.we present a semi-automatic system that identifies semantic relationships in noun phrases without using precoded noun or adjective semantics. instead, partial matching on previously analyzed noun phrases leads to a tentative interpretation of a new input. processing can start without prior analyses, but the early stage requires user interaction. as more noun phrases are analyzed, the system learns to find better interpretations and reduces its reliance on the user. in experiments on english technical texts the system correctly identified 60--70% of relationships automatically.
towards a single proposal in spelling correction. the study presented here relies on the integrated use of different kinds of knowledge in order to improve first-guess accuracy in non-word context-sensitive correction for general unrestricted text. state of the art spelling correction systems, e.g. ispell, apart from detecting spelling errors, also assist the user by offering a set of candidate corrections that are close to the misspelled word. based on the correction proposals of ispell, we built several guessers, which were combined in different ways. firstly, we evaluated all possibilities and selected the best ones in a corpus with artificially generated typing errors. secondly, the best combinations were tested on texts with genuine spelling errors. the results for the latter suggest that we can expect automatic non-word correction for all the errors in a free running text with 80% precision and a single proposal 98% of the times (1.02 proposals on average).
redundancy: helping semantic disambiguation. redundancy is a good thing, at least in a learning process. to be a good teacher you must say what you are going to say, say it, then say what you have just said. well, three times is better than one. to acquire and learn knowledge from text for building a lexical knowledge base, we need to find a source of information that states facts, and repeats them a few times using slightly different sentence structures. a technique is needed for gathering information from that source and identify the redundant information. the extraction of the commonality is an active learning of the knowledge expressed. the proposed research is based on a clustering method developed by barrière and popowich (1996) which performs a gathering of related information about a particular topic. individual pieces of information are represented via the conceptual graph (cg) formalism and the result of the clustering is a large cg embedding all individual graphs. in the present paper, we suggest that the identification of the redundant information within the resulting graph is very useful for disambiguation of the original information at the semantic level.
a tool kit for lexicon building. this paper describes a set of interactive routines that can be used to create, maintain, and update a computer lexicon. the routines are available to the user as a set of commands resembling a simple operating system. the lexicon produced by this system is based on lexical-semantic relations, but is compatible with a variety of other models of lexicon structure. the lexicon builder is suitable for the generation of moderate-sized vocabularies and has been used to construct a lexicon for a small medical expert system. a future version of the lexicon builder will create a much larger lexicon by parsing definitions from machine-readable dictionaries.
guided parsing of range concatenation languages. the theoretical study of the range concatenation grammar [rcg] formalism has revealed many attractive properties which may be used in nlp. in particular, range concatenation languages [rcl] can be parsed in polynomial time and many classical grammatical formalisms can be translated into equivalent rcgs without increasing their worst-case parsing time complexity. for example, after translation into an equivalent rcg, any tree adjoining grammar can be parsed in o(n6) time. in this paper, we study a parsing technique whose purpose is to improve the practical efficiency of rcl parsers. the non-deterministic parsing choices of the main parser for a language l are directed by a guide which uses the shared derivation forest output by a prior rcl parser for a suitable superset of l. the results of a practical evaluation of this method on a wide coverage english grammar are given.
parsing vs. text processing in the analysis of dictionary definitions. we have analyzed definitions from webster's seventh new collegiate dictionary using sager's linguistic string parser and again using basic unix text processing utilities such as grep and awk. this paper evaluates both procedures, compares their results, and discusses possible future lines of research exploiting and combining their respective strengths.
a simple hybrid aligner for generating lexical correspondences in parallel texts. we present an algorithm for bilingual word alignment that extends previous work by treating multi-word candidates on a par with single words, and combining some simple assumptions about the translation process to capture alignments for low frequency words. as most other alignment algorithms it uses cooccurrence statistics as a basis, but differs in the assumptions it makes about the translation process. the algorithm has been implemented in a modular system that allows the user to experiment with different combinations and variants of these assumptions. we give performance results from two evaluations, which compare will with results reported in the literature.
modeling local coherence: an entity-based approach. this article proposes a novel framework for representing and measuring local coherence. central to this approach is the entity-grid representation of discourse, which captures patterns of entity distribution in a text. the algorithm introduced in the article automatically abstracts a text into a set of entity transition sequences and records distributional, syntactic, and referential information about discourse entities. we re-conceptualize coherence assessment as a learning task and show that our entity-based representation is well-suited for ranking-based generation and text classification tasks. using the proposed representation, we achieve good performance on text ordering, summary coherence evaluation, and readability assessment.
extracting paraphrases from a parallel corpus. while paraphrasing is critical both for interpretation and generation of natural language, current systems use manual or semi-automatic methods to collect paraphrases. we present an unsupervised learning algorithm for identification of paraphrases from a corpus of multiple english translations of the same source text. our approach yields phrasal and single word lexical paraphrases as well as syntactic paraphrases.
analysis of source identified text corpora: exploring the statistics of the reused text and authorship. this paper aims at providing a view of text recycled, within a short time, by the authors themselves. we first present a simple and general method for extracting reused term sequences, and then analyze several author-identified text collections to compare the statistical quantities. the ratio of recycling is also measured for each collection. finally, related research topics are introduced together with some discussion of future research directions.
information fusion in the context of multi-document summarization. we present a method to automatically generate a concise summary by identifying and synthesizing similar elements across related text from a set of multiple documents. our approach is unique in its usage of language generation to reformulate the wording of the summary.
resolving anaphors in embedded sentences. we propose an algorithm to resolve anaphors, tackling mainly the problem of intrasentential antecedents. we base our methodology on the fact that such antecedents are likely to occur in embedded sentences. sidner's focusing mechanism is used as the basic algorithm in a more complete approach. the proposed algorithm has been tested and implemented as a part of a conceptual analyser, mainly to process pronouns. details of an evaluation are given.
generalized chart algorithm: an efficient procedure for cost-based abduction. we present an efficient procedure for cost-based abduction, which is based on the idea of using chart parsers as proof procedures. we discuss in detail three features of our algorithm --- goal-driven bottom-up derivation, tabulation of the partial results, and agenda control mechanism --- and report the results of the preliminary experiments, which show how these features improve the computational efficiency of cost-based abduction.
a flexible example-based parser based on the sstc. in this paper we sketch an approach for natural language parsing. our approach is an example-based approach, which relies mainly on examples that already parsed to their representation structure, and on the knowledge that we can get from these examples the required information to parse a new input sentence. in our approach, examples are annotated with the structured string tree correspondence (sstc) annotation schema where each sstc describes a sentence, a representation tree as well as the correspondence between substrings in the sentence and subtrees in the representation tree. in the process of parsing, we first try to build subtrees for phrases in the input sentence which have been successfully found in the example-base - a bottom up approach. these subtrees will then be combined together to form a single rooted representation tree based on an example with similar representation structure - a top down approach.
aspects of clause politeness in japanese: an extended inquiry semantics treatment. the inquiry semantics approach of the nigel computational systemic grammar of english has proved capable of revealing distinctions within propositional content that the text planning process needs to control in order for adequate text to be generated. an extension to the chooser and inquiry framework motivated by a japanese clause generator capable of expressing levels of politeness makes this facility available for revealing the distinctions necessary among interpersonal, social meanings also. this paper shows why the previous inquiry framework was incapable of the kind of semantic control japanese politeness requires and how the implemented extension achieves that control. an example is given of the generation of a sentence that is appropriately polite for its context of use and some implications for future work are suggested.
translating named entities using monolingual and bilingual resources. named entity phrases are some of the most difficult phrases to translate because new phrases can appear from nowhere, and because many are domain specific, not to be found in bilingual dictionaries. we present a novel algorithm for translating named entity phrases using easily obtainable monolingual and bilingual resources. we report on the application and evaluation of this algorithm in translating arabic named entities to english. we also compare our results with the results obtained from human translations and a commercial system for the same task.
using aggregation for selecting content when generating referring expressions. previous algorithms for the generation of referring expressions have been developed specifically for this purpose. here we introduce an alternative approach based on a fully generic aggregation method also motivated for other generation tasks. we argue that the alternative contributes to a more integrated and uniform approach to content determination in the context of complete noun phrase generation.
distortion models for statistical machine translation. in this paper, we argue that n-gram language models are not sufficient to address word reordering required for machine translation. we propose a new distortion model that can be used with existing phrase-based smt decoders to address those n-gram language model limitations. we present empirical results in arabic to english machine translation that show statistically significant improvements when our proposed model is used. we also propose a novel metric to measure word order similarity (or difference) between any pair of languages based on word alignments.
features and agreement. this paper compares the consistency-based account of agreement phenomena in 'unification-based' grammars with an implication-based account based on a simple feature extension to lambek categorial grammar (lcg). we show that the lcg treatment accounts for constructions that have been recognized as problematic for 'unification-based' treatments.
using machine learning techniques to build a comma checker for basque. in this paper, we describe the research using machine learning techniques to build a comma checker to be integrated in a grammar checker for basque. after several experiments, and trained with a little corpus of 100,000 words, the system guesses correctly not placing commas with a precision of 96% and a recall of 98%. it also gets a precision of 70% and a recall of 49% in the task of placing commas. finally, we have shown that these results can be improved using a bigger and a more homogeneous corpus to train, that is, a bigger corpus written by one unique author.
grammatical analysis by computer of the lancaster-oslo/bergen (lob) corpus of british english texts. research has been under way at the unit for computer research on the english language at the university of lancaster, england, to develop a suite of computer programs which provide a detailed grammatical analysis of the lob corpus, a collection of about 1 million words of british english texts available in machine readable form.the first phrase of the project, completed in september 1983, produced a grammatically annotated version of the corpus giving a tag showing the word class of each word token. over 93 per cent of the word tags were correctly selected by using a matrix of tag pair probabilities and this figure was upgraded by a further 3 per cent by retagging problematic strings of words prior to disambiguation and by altering the probability weightings for sequences of three tags. the remaining 3 to 4 per cent were corrected by a human post-editor.the system was originally designed to run in batch mode over the corpus but we have recently modified procedures to run interactively for sample sentences typed in by a user at a terminal. we are currently extending the word tag set and improving the word tagging procedures to further reduce manual intervention. a similar probabilistic system is being developed for phrase and clause tagging.
an unsupervised system for identifying english inclusions in german text. we present an unsupervised system that exploits linguistic knowledge resources, namely english and german lexical databases and the world wide web, to identify english inclusions in german text. we describe experiments with this system and the corpus which was developed for this task. we report the classification results of our system and compare them to the performance of a trained machine learner in a series of in- and cross-domain experiments.
corpus-based lexical choice in natural language generation. choosing the best lexeme to realize a meaning in natural language generation is a hard task. we investigate different tree-based stochastic models for lexical choice. because of the difficulty of obtaining a sense-tagged corpus, we generalize the notion of synonymy. we show that a tree-based model can achieve a word-bag based accuracy of 90%, representing an improvement over the baseline.
jointly labeling multiple sequences: a factorial hmm approach. we present new statistical models for jointly labeling multiple sequences and apply them to the combined task of part-of-speech tagging and noun phrase chunking. the model is based on the factorial hidden markov model (fhmm) with distributed hidden states representing part-of-speech and noun phrase sequences. we demonstrate that this joint labeling approach, by enabling information sharing between tagging/chunking subtasks, out-performs the traditional method of tagging and chunking in succession. further, we extend this into a novel model, switching fhmm, to allow for explicit modeling of cross-sequence dependencies based on linguistic knowledge. we report tagging/chunking accuracies for varying dataset sizes and show that our approach is relatively robust to data sparsity.
a rote extractor with edit distance-based generalisation and multi-corpora precision calculation. in this paper, we describe a rote extractor that learns patterns for finding semantic relationships in unrestricted text, with new procedures for pattern generalization and scoring. these include the use of part-of-speech tags to guide the generalization, named entity categories inside the patterns, an edit-distance-based pattern generalization algorithm, and a pattern accuracy calculation procedure based on evaluating the patterns on several test corpora. in an evaluation with 14 entities, the system attains a precision higher than 50% for half of the relationships considered.
lexicon and grammar in probabilistic tagging of written english. the paper describes the development of software for automatic grammatical analysis of unrestricted, unedited english text at the unit for computer research on the english language (ucrel) at the university of lancaster. the work is currently funded by ibm and carried out in collaboration with colleagues at ibm uk (winchester) and ibm yorktown heights. the paper will focus on the lexicon component of the word tagging system, the ucrel grammar, the databanks of parsed sentences, and the tools that have been written to support development of these components. this work has applications to speech technology, spelling correction, and other areas of natural language processing. currently, our goal is to provide a language model using transition statistics to disambiguate alternative parses for a speech recognition device.
generalized algorithms for constructing statistical language models. recent text and speech processing applications such as speech mining raise new and more general problems related to the construction of language models. we present and describe in detail several new and efficient algorithms to address these more general problems and report experimental results demonstrating their usefulness. we give an algorithm for computing efficiently the expected counts of any sequence in a word lattice output by a speech recognizer or any arbitrary weighted automaton; describe a new technique for creating exact representations of n-gram language models by weighted automata whose size is practical for offline use even for a vocabulary size of about 500,000 words and an n-gram order n = 6; and present a simple and more general technique for constructing class-based language models that allows each class to represent an arbitrary weighted automaton. an efficient implementation of our algorithms and techniques has been incorporated in a general software library for language modeling, the grm library, that includes many other text and grammar processing functionalities.
corpus-based identification of non-anaphoric noun phrases. coreference resolution involves finding antecedents for anaphoric discourse entities, such as definite noun phrases. but many definite noun phrases are not anaphoric because their meaning can be understood from general world knowledge (e.g., "the white house" or "the news media"). we have developed a corpus-based algorithm for automatically identifying definite noun phrases that are non-anaphoric, which has the potential to improve the efficiency and accuracy of coreference resolution systems. our algorithm generates lists of non-anaphoric noun phrases and noun phrase patterns from a training corpus and uses them to recognize non-anaphoric noun phrases in new texts. using 1600 muc-4 terrorism news articles as the training corpus, our approach achieved 78% recall and 87% precision at identifying such noun phrases in 50 text documents.
toward a computational theory of speech perception. in recent years, a great deal of evidence has been collected which gives substantially increased insight into the nature of human speech perception. it is the author's belief that such data can be effectively used to infer much of the structure of a practical speech recognition system. this paper details a new view of the role of structural constraints within the several structural domains (e. g. articulation, phonetics, phonology, syntax, semantics) that must be utilized to infer the desired percept.
integrating multiple knowledge sources for detection and correction of repairs in human-computer dialog. we have analyzed 607 sentences of spontaneous human-computer speech data containing repairs, drawn from a total corpus of 10,718 sentences. we present here criteria and techniques for automatically detecting the presence of a repair, its location, and making the appropriate correction. the criteria involve integration of knowledge from several sources: pattern matching, syntactic and semantic analysis, and acoustics.
evaluating a focus-based approach to anaphora resolution. we present an approach to anaphora resolution based on a focusing algorithm, and implemented within an existing muc (message understanding conference) information extraction system, allowing quantitative evaluation against a substantial corpus of annotated real-world texts. extensions to the basic focusing mechanism can be easily tested, resulting in refinements to the mechanism and resolution rules. results show that the focusing algorithm is highly sensitive to the quality of syntactic-semantic analyses, when compared to a simpler heuristic-based approach.
dependency-based statistical machine translation. we present a czech-english statistical machine translation system which performs tree-to-tree translation of dependency structures. the only bilingual resource required is a sentence-aligned parallel corpus. all other resources are monolingual. we also refer to an evaluation method and plan to compare our system's output with a benchmark system.
two diverse systems built using generic components for spoken dialogue (recent progress on trips). this paper describes recent progress on the trips architecture for developing spoken-language dialogue systems. the interactive poster session will include demonstrations of two systems built using trips: a computer purchasing assistant, and an object placement (and manipulation) task.
prosody, syntax and parsing. we describe the modification of a grammar to take advantage of prosodic information provided by a speech recognition system. this initial study is limited to the use of relative duration of phonetic segments in the assignment of syntactic structure, specifically in ruling out alternative parses in otherwise ambiguous sentences. taking advantage of prosodic information in parsing can make a spoken language system more accurate and more efficient, if prosodic-syntactic mismatches, or unlikely matches, can be pruned. we know of no other work that has succeeded in automatically extracting speech information and using it in a parser to rule out extraneous parses.
a robust system for natural spoken dialogue. this paper describes a system that leads us to believe in the feasibility of constructing natural spoken dialogue systems in task-oriented domains. it specifically addresses the issue of robust interpretation of speech in the presence of recognition errors. robustness is achieved by a combination of statistical error post-correction, syntactically- and semantically-driven robust parsing, and extensive use of the dialogue context. we present an evaluation of the system using time-to-completion and the quality of the final solution that suggests that most native speakers of english can use the system successfully with virtually no training.
k-valued non-associative lambek categorial grammars are not learnable from strings. this paper is concerned with learning categorial grammars in gold's model. in contrast to k-valued classical categorial grammars, k-valued lambek grammars are not learnable from strings. this result was shown for several variants but the question was left open for the weakest one, the non-associative variant nl.we show that the class of rigid and k-valued nl grammars is unlearnable from strings, for each k; this result is obtained by a specific construction of a limit point in the considered class, that does not use product operator.another interest of our construction is that it provides limit points for the whole hierarchy of lambek grammars, including the recent pregroup grammars.such a result aims at clarifying the possible directions for future learning algorithms: it expresses the difficulty of learning categorial grammars from strings and the need for an adequate structure on examples.
head automata and bilingual tiling: translation with minimal representations. we present a language model consisting of a collection of costed bidirectional finite state automata associated with the head words of phrases. the model is suitable for incremental application of lexical associations in a dynamic programming search for optimal dependency tree derivations. we also present a model and algorithm for machine translation involving optimal "tiling" of a dependency tree with entries of a costed bilingual lexicon. experimental results are reported comparing methods for assigning cost functions to these models. we conclude with a discussion of the adequacy of annotated linguistic strings as representations for machine translation.
tagging unknown proper names using decision trees. this paper describes a supervised learning method to automatically select from a set of noun phrases, embedding proper names of different semantic classes, their most distinctive features. the result of the learning process is a decision tree which classifies an unknown proper name on the basis of its context of occurrence. this classifier is used to estimate the probability distribution of an out of vocabulary proper name over a tagset. this probability distribution is itself used to estimate the parameters of a stochastic part of speech tagger.
automatic acquisition of hierarchical transduction models for machine translation. we describe a method for the fully automatic learning of hierarchical finite state translation models. the input to the method is transcribed speech utterances and their corresponding human translations, and the output is a set of head transducers, i.e. statistical lexical head-outward transducers. a word-alignment function and a head-ranking function are first obtained, and then counts are generated for hypothesized state transitions of head transducers whose lexical translations and word order changes are consistent with the alignment. the method has been applied to create an english-spanish translation model for a speech translation application, with word accuracy of over 75% as measured by a string-distance comparison to three reference translations.
an efficient kernel for multilingual generation in speech-to-speech dialogue translation. we present core aspects of a fully implemented generation component in a multilingual speech-to-speech dialogue translation system. its design was particularly influenced by the necessity of real-time processing and usability for multiple languages and domains. we developed a general kernel system comprising a microplanning and a syntactic realizer module. the microplanner performs lexical and syntactic choice, based on constraint-satisfaction techniques. the syntactic realizer processes hpsg grammars reflecting the latest developments of the underlying linguistic theory, utilizing their pre-processing into the tag formalism. the declarative nature of the knowledge bases, i.e., the microplanning constraints and the hpsg grammars allowed an easy adaption to new domains and languages. the successful integration of our component into the translation system verbmobil proved the fulfillment of the specific real-time constraints.
a comparison of head transducers and transfer for a limited domain translation application. we compare the effectiveness of two related machine translation models applied to the same limited-domain task. one is a transfer model with monolingual head automata for analysis and generation; the other is a direct transduction model based on bilingual head transducers. we conclude that the head transducer model is more effective according to measures of accuracy, computational requirements, model size, and development effort.
the sammie system: multimodal in-car dialogue. the sammie system is an in-car multi-modal dialogue system for an mp3 application. it is used as a testing environment for our research in natural, intuitive mixed-initiative interaction, with particular emphasis on multimodal output planning and realization aimed to produce output adapted to the context, including the driver's attention state w.r.t. the primary driving task.
monotonic semantic interpretation. aspects of semantic interpretation, such as quantifier scoping and reference resolution, are often realised computationally by non-monotonic operations involving loss of information and destructive manipulation of semantic representations. the paper describes how monotonic reference resolution and scoping can be carried out using a revised quasi logical form (qlf) representation. semantics for qlf are presented in which the denotations of formulas are extended monotonically as qlf expressions are resolved.
the rhythm of lexical stress in prose. "prose rhythm" is a widely observed but scarcely quantified phenomenon. we describe an information-theoretic model for measuring the regularity of lexical stress in english texts, and use it in combination with trigram language models to demonstrate a relationship between the probability of word sequences in english and the amount of rhythm present in them. we find that the stream of lexical stress in text from the wall street journal has an entropy rate of less than 0.75 bits per syllable for common sentences. we observe that the average number of syllables per word is greater for rarer word sequences, and to normalize for this effect we run control experiments to show that the choice of word order contributes significantly to stress regularity, and increasingly with lexical probability.
a model of lexical attraction and repulsion. this paper introduces new methods based on exponential families for modeling the correlations between words in text and speech. while previous work assumed the effects of word co-occurrence statistics to be constant over a window of several hundred words, we show that their influence is nonstationary on a much smaller time scale. empirical data drawn from english and japanese text, as well as conversational speech, reveals that the "attraction" between words decays exponentially, while stylistic and syntactic contraints create a "repulsion" between words that discourages close co-occurrence. we show that these characteristics are well described by simple mixture models based on two-stage exponential distributions which can be trained using the em algorithm. the resulting distance distributions can then be incorporated as penalizing features in an exponential language model.
logical forms in the core language engine. this paper describes a 'logical form' target language for representing the literal meaning of english sentences, and an intermediate level of representation ('quasi logical form') which engenders a natural separation between the compositional semantics and the processes of scoping and reference resolution. the approach has been implemented in the sri core language engine which handles the english constructions discussed in the paper.
consonant spreading in arabic stems. this paper examines the phenomenon of consonant spreading in arabic stems. each spreading involves a local surface copying of an underlying consonant, and, in certain phonological contexts, spreading alternates productively with consonant lengthening (or gemination). the morphophonemic triggers of spreading lie in the patterns or even in the roots themselves, and the combination of a spreading root and a spreading pattern causes a consonant to be copied multiple times. the interdigitation of arabic stems and the realization of consonant spreading are formalized using finite-state morphotactics and variation rules, and this approach has been successfully implemented in a large-scale arabic morphological analyzer which is available for testing on the internet.
computing locally coherent discourses. we present the first algorithm that computes optimal orderings of sentences into a locally coherent discourse. the algorithm runs very efficiently on a variety of coherence measures from the literature. we also show that the discourse ordering problem is np-complete and cannot be approximated.
finite-state non-concatenative morphotactics. we describe a new technique for constructing finite-state transducers that involves reapplying the regular-expression compiler to its own output. implemented in an algorithm called compile-replace, this technique has proved useful for handling non-concatenative phenomena; and we demonstrate it on malay full-stem reduplication and arabic stem interdigitation.
the selection of the most probable dependency structure in japanese using mutual information. we use a statistical method to select the most probable structure or parse for a given sentence. it takes as input the dependency structures generated for the sentence by a dependency grammar, finds all triple of modifier, particle and modificant relations, calculates mutual information of each relation and chooses the structure for which the product of the mutual information of its relations is the highest.
inside-outside estimation of a lexicalized pcfg for german. the paper describes an extensive experiment in inside-outside estimation of a lexicalized probabilistic context free grammar for german verb-final clauses. grammar and formalism features which make the experiment feasible are described. successive models are evaluated on precision and recall of phrase markup.
improvement of a whole sentence maximum entropy language model using grammatical features. in this paper, we propose adding long-term grammatical information in a whole sentence maximun entropy language model (wsme) in order to improve the performance of the model. the grammatical information was added to the wsme model as features and were obtained from a stochastic context-free grammar. finally, experiments using a part of the penn treebank corpus were carried out and significant improvements were acheived.
the sentimental factor: improving review classification via human-provided information. sentiment classification is the task of labeling a review document according to the polarity of its prevailing opinion (favorable or unfavorable). in approaching this problem, a model builder often has three sources of information available: a small collection of labeled documents, a large collection of unlabeled documents, and human understanding of language. ideally, a learning method will utilize all three sources. to accomplish this goal, we generalize an existing procedure that uses the latter two.we extend this procedure by re-interpreting it as a naive bayes model for document sentiment. viewed as such, it can also be seen to extract a pair of derived features that are linearly combined to predict sentiment. this perspective allows us to improve upon previous methods, primarily through two strategies: incorporating additional derived features into the model and, where possible, using labeled data to estimate their relative influence.
mt evaluation: human-like vs. human acceptable. we present a comparative study on machine translation evaluation according to two different criteria: human likeness and human acceptability. we provide empirical evidence that there is a relationship between these two kinds of evaluation: human likeness implies human acceptability but the reverse is not true. from the point of view of automatic evaluation this implies that metrics based on human likeness are more reliable for system tuning. our results also show that current evaluation metrics are not always able to distinguish between automatic and human translations. in order to improve the descriptive power of current metrics we propose the use of additional syntax-based metrics, and metric combinations inside the qarla framework.
an empirical study of information synthesis task. this paper describes an empirical study of the "information synthesis" task, defined as the process of (given a complex information need) extracting, organizing and inter-relating the pieces of information contained in a set of relevant documents, in order to obtain a comprehensive, non redundant report that satisfies the information need.two main results are presented: a) the creation of an information synthesis testbed with 72 reports manually generated by nine subjects for eight complex topics with 100 relevant documents each; and b) an empirical comparison of similarity metrics between reports, under the hypothesis that the best metric is the one that best distinguishes between manual and automatically generated reports. a metric based on key concepts overlap gives better results than metrics based on n-gram overlap (such as rouge) or sentence overlap.
qarla: a framework for the evaluation of text summarization systems. this paper presents a probabilistic framework, qarla, for the evaluation of text summarisation systems. the input of the framework is a set of manual (reference) summaries, a set of baseline (automatic) summaries and a set of similarity metrics between summaries. it provides i) a measure to evaluate the quality of any set of similarity metrics, ii) a measure to evaluate the quality of a summary using an optimal set of similarity metrics, and iii) a measure to evaluate whether the set of baseline summaries is reliable or may produce biased results.compared to previous approaches, our framework is able to combine different metrics and evaluate the quality of a set of metrics without any a-priori weighting of their relative importance. we provide quantitative evidence about the effectiveness of the approach to improve the automatic evaluation of text summarisation systems by combining several similarity metrics.
discovering phonotactic finite-state automata by generic search. this paper presents a genetic algorithm based approach to the automatic discovery of finite-state automata (fsas) from positive data. fsas are commonly used in computational phonology, but-given the limited learnability of fsas from arbitrary language subsets-are usually constructed manually. the approach presented here offers a practical automatic method that helps reduce the cost of manual fsa construction.
tense and connective constraints on the expression of causality. starting from descriptions of french connectives (in particular "donc"---therefore), on the one hand, and aspectual properties of french tenses passé simple and imparfait on the other hand, we study in this paper how the two interact with respect to the expression of causality. it turns out that their interaction is not free. some combinations are not acceptable, and we propose an explanation for them. these results apply straightforwardly to natural language generation: given as input two events related by a cause relation, we can choose among various ways of presentation (the parameters being (i) the order, (ii) the connective, (iii) the tense) so that we are sure to express a cause relation, without generating either an incorrect discourse or an ambiguous one.
query-relevant summarization using faqs. this paper introduces a statistical model for query-relevant summarization: succinctly characterizing the relevance of a document to a query. learning parameter values for the proposed model requires a large collection of summarized documents, which we do not have, but as a proxy, we use a collection of faq (frequently-asked question) documents. taking a learning approach enables a principled, quantitative evaluation of the proposed system, and the results of some initial experiments---on a collection of usenet faqs and on a faq-like set of customer-submitted questions to several large retail companies---suggest the plausibility of learning for summarization.
time mapping with hypergraphs. word graphs are able to represent a large number of different utterance hypotheses in a very compact manner. however, usually they contain a huge amount of redundancy in terms of word hypotheses that cover almost identical intervals in time. we address this problem by introducing hypergraphs for speech processing. hypergraphs can be classified as an extension to word graphs and charts, their edges possibly having several start and end vertices. by converting ordinary word graphs to hypergraphs one can reduce the number of edges considerably. we define hypergraphs formally, present an algorithm to convert word graphs into hypergraphs and state consistency properties for edges and their combination. finally, we present some empirical results concerning graph size and parsing effciency.
bootstrapping path-based pronoun resolution. we present an approach to pronoun resolution based on syntactic paths. through a simple bootstrapping procedure, we learn the likelihood of coreference between a pronoun and a candidate noun based on the path in the parse tree between the two entities. this path information enables us to handle previously challenging resolution instances, and also robustly addresses traditional syntactic coreference constraints. highly coreferent paths also allow mining of precise probabilistic gender/number information. we combine statistical knowledge with well known features in a support vector machine pronoun resolution classifier. significant gains in performance are observed on several datasets.
a high-performance semi-supervised learning method for text chunking. in machine learning, whether one can build a more accurate classifier by using unlabeled data (semi-supervised learning) is an important issue. although a number of semi-supervised methods have been proposed, their effectiveness on nlp tasks is not always clear. this paper presents a novel semi-supervised method that employs a learning paradigm which we call structural learning. the idea is to find "what good classifiers are like" by learning from thousands of automatically generated auxiliary classification problems on unlabeled data. by doing so, the common predictive structure shared by the multiple classification problems can be discovered, which can then be used to improve performance on the target problem. the method produces performance higher than the previous best results on conll'00 syntactic chunking and conll'03 named entity chunking (english and german).
finding parts in very large corpora. we present a method for extracting parts of objects from wholes (e.g. "speedometer" from "car"). given a very large corpus our method finds part words with 55% accuracy for the top 50 words as ranked by the system. the part list could be scanned by an end-user and added to an existing ontology (such as wordnet), or used as a part of a rough semantic lexicon.
resolution of collective-distributive ambiguity using model-based reasoning. i present a semantic analysis of collective-distributive ambiguity, and resolution of such ambiguity by model-based reasoning. this approach goes beyond scha and stallard [17], whose reasoning capability was limited to checking semantic types. my semantic analysis is based on link [14, 13] and roberts [15], where distributivity comes uniformly from a quantificational operator, either explicit (e.g. each) or implicit (e.g. the d operator). i view the semantics module of the natural language system as a hypothesis generator and the reasoner in the pragmatics module as a hypothesis filter (cf. simmons and davis [18]). the reasoner utilizes a model consisting of domain-dependent constraints and domain-independent axioms for disambiguation. there are two kinds of constraints, type constraints and numerical constraints, and they are associated with predicates in the knowledge base. whenever additional information is derived from the model, the contradiction checker is invoked to detect any contradiction in a hypothesis using simple mathematical knowledge. cdcl (collective-distributive constraint language) is used to represent hypotheses, constraints, and axioms in a way isomorphic to diagram representations of collective-distributive ambiguity.
evaluating automated and manual acquisition of anaphora resolution strategies. we describe one approach to build an automatically trainable anaphora resolution system. in this approach, we use japanese newspaper articles tagged with discourse information as training examples for a machine learning algorithm which employs the c4.5 decision tree algorithm by quinlan (quinlan, 1993). then, we evaluate and compare the results of several variants of the machine learning-based approach with those of our existing anaphora resolution system which uses manually-designed knowledge sources. finally, we compare our algorithms with existing theories of anaphora, in particular, japanese zero pronouns.
a language-independent anaphora resolution system for understanding multilingual texts. this paper describes a new discourse module within our multilingual nlp system. because of its unique data-driven architecture, the discourse module is language-independent. moreover, the use of hierarchically organized multiple knowledge sources makes the module robust and trainable using discourse-tagged corpora. separating discourse phenomena from knowledge sources makes the discourse module easily extensible to additional phenomena.
trainable, scalable summarization using robust nlp and machine learning. we describe a trainable and scalable summarization system which utilizes features derived from information retrieval, information extraction, and nlp techniques and on-line resources. the system combines these features using a trainable feature combiner learned from summary examples through a machine learning algorithm. we demonstrate system scalability by reporting results on the best combination of summarization features for different document sources. we also present preliminary results from a task-based evaluation on summarization output usability.
parsing free word order languages in the paninian framework. there is a need to develop a suitable computational grammar formalism for free word order languages for two reasons: first, a suitably designed formalism is likely to be more efficient. second, such a formalism is also likely to be linguistically more elegant and satisfying. in this paper, we describe such a formalism, called the paninian framework, that has been successfully applied to indian languages.this paper shows that the paninian framework applied to modern indian languages gives an elegant account of the relation between surface form (vibhakti) and semantic (karaka) roles. the mapping is elegant and compact. the same basic account also explains active-passives and complex sentences. this suggests that the solution is not just adhoc but has a deeper underlying unity.a constraint based parser is described for the framework. the constraints problem reduces to bipartite graph matching problem because of the nature of constraints. efficient solutions are known for these problems.it is interesting to observe that such a parser (designed for free word order languages) compares well in asymptotic time complexity with the parser for context free grammars (cfgs) which are basically designed for positional languages.
zero morphemes in unification-based combinatory categorial grammar. in this paper, we report on our use of zero morphemes in unification-based combinatory categorial grammar. after illustrating the benefits of this approach with several examples, we describe the algorithm for compiling zero morphemes into unary rules, which allows us to use zero morphemes more efficiently in natural language processing. then, we discuss the question of equivalence of a grammar with these unary rules to the original grammar. lastly, we compare our approach to zero morphemes with possible alternatives.
unsupervised sense disambiguation using bilingual probabilistic models. we describe two probabilistic models for unsupervised word-sense disambiguation using parallel corpora. the first model, which we call the sense model, builds on the work of diab and resnik (2002) that uses both parallel text and a sense inventory for the target language, and recasts their approach in a probabilistic framework. the second model, which we call the concept model, is a hierarchical model that uses a concept latent variable to relate different language specific sense labels. we show that both models improve performance on the word sense disambiguation task over previous unsupervised approaches, with the concept model showing the largest improvement. furthermore, in learning the concept model, as a by-product, we learn a sense inventory for the parallel language.
problem solving applied to language generation. this research was supported at sri international by the defense advanced research projects agency under contract n00039--79--c--0118 with the naval electronic systems command. the views and conclusions contained in this document are those of the author and should not be interpreted as representative of the official policies either expressed or implied of the defense advanced research projects agency, or the u. s. government. the author is grateful to barbara grosz, gary hendrix and terry winograd for comments on an earlier draft of this paper.
unsupervised part-of-speech tagging employing efficient graph clustering. an unsupervised part-of-speech (pos) tagging system that relies on graph clustering methods is described. unlike in current state-of-the-art approaches, the kind and number of different tags is generated by the method itself. we compute and merge two partitionings of word graphs: one based on context similarity of high frequency words, another on log-likelihood statistics for words of lower frequencies. using the resulting word clusters as a lexicon, a viterbi pos tagger is trained, which is refined by a morphological component. the approach is evaluated on three different languages by measuring agreement with existing taggers.
alternative phrases and natural languages information retrieval. this paper presents a formal analysis for a large class of words called alternative markers, which includes other(than), such(as), and besides. these words appear frequently enough in dialog to warrant serious attention, yet present natural language search engines perform poorly on queries containing them. i show that the performance of a search engine can be improved dramatically by incorporating an approximation of the formal analysis that is compatible with the search engine's operational semantics. the value of this approach is that as the operational semantics of natural language applications improve, even larger improvements are possible.
a practical nonmonotonic theory for reasoning about speech acts. a prerequisite to a theory of the way agents understand speech acts is a theory of how their beliefs and intentions are revised as a consequence of events. this process of attitude revision is an interesting domain for the application of nonmonotonic reasoning because speech acts have a conventional aspect that is readily represented by defaults, but that interacts with an agent's beliefs and intentions in many complex ways that may override the defaults. perrault has developed a theory of speech acts, based on rieter's default logic, that captures the conventional aspect; it does not, however, adequately account for certain easily observed facts about attitude revision resulting from speech acts. a natural theory of attitude revision seems to require a method of stating preferences among competing defaults. we present here a speech act theory, formalized in hierarchic autoepistemic logic (a refinement of moore's autoepistemic logic), in which revision of both the speaker's and hearer's attitudes can be adequately described. as a collateral benefit, efficient automatic reasoning methods for the formalism exist. the theory has been implemented and is now being employed by an utterance-planning system.
the structure of shared forests in ambiguous parsing. the context-free backbone of some natural language analyzers produces all possible cf parses as some kind of shared forest, from which a single tree is to be chosen by a disambiguation process that may be based on the finer features of the language. we study the structure of these forests with respect to optimality of sharing, and in relation with the parsing schema used to produce them. in addition to a theoretical and experimental framework for studying these issues, the main results presented are:- sophistication in chart parsing schemata (e.g. use of look-ahed) may reduce time and space efficiency instead of improving it,- there is a shared forest structure with at most cubic size for any cf grammar,- when o(n3) complexity is required, the shape of a shared forest is dependent on the parsing schema used.though analyzed on cf grammars for simplicity, these results extend to more complex formalisms such as unification based grammars.
a flexible approach to cooperative response generation in information-seeking dialogues. this paper presents a cooperative consultation system on a restricted domain. the system builds hypotheses on the user's plan and avoids misunderstandings (with consequent repair dialogues) through clarification dialogues in case of ambiguity. the role played by constraints in the generation of the answer is characterized in order to limit the cases of ambiguities requiring a clarification dialogue. the answers of the system are generated at different levels of detail, according to the user's competence in the domain.
nltk: the natural language toolkit. the natural language toolkit is a suite of program modules, data sets and tutorials supporting research and teaching in computational linguistics and natural language processing. nltk is written in python and distributed under the gpl open source license. over the past year the toolkit has been rewritten, simplifying many linguistic data structures and taking advantage of recent enhancements in the python language. this paper reports on the simplified toolkit and explains how it is used in teaching nlp.
a memory-based approach to learning shallow natural language patterns. recognizing shallow linguistic patterns, such as basic syntactic relationships between words, is a common task in applied natural language and text processing. the common practice for approaching this task is by tedious manual definition of possible pattern structures, often in the form of regular expressions or finite automata. this paper presents a novel memory-based learning method that recognizes shallow patterns in new text based on a bracketed training corpus. the training data are stored as-is, in efficient suffix-tree data structures. generalization is performed on-line at recognition time by comparing subsequences of the new text to positive and negative evidence in the corpus. this way, no information in the training is lost, as can happen in other learning systems that construct a single generalized model at the time of training. the paper presents experimental results for recognizing noun phrase, subject-verb and verb-object patterns in english. since the learning approach enables easy porting to new domains, we plan to apply it to syntactic patterns in other languages and to sub-language patterns for information extraction.
a flexible approach to natural language generation for disabled children. natural language generation (nlg) is a way to automatically realize a correct expression in response to a communicative goal. this technology is mainly explored in the fields of machine translation, report generation, dialog system etc. in this paper we have explored the nlg technique for another novel application-assisting disabled children to take part in conversation. the limited physical ability and mental maturity of our intended users made the nlg approach different from others. we have taken a flexible approach where main emphasis is given on flexibility and usability of the system. the evaluation results show this technique can increase the communication rate of users during a conversation.
lexicalization in crosslinguistic probabilistic parsing: the case of french. this paper presents the first probabilistic parsing results for french, using the recently released french treebank. we start with an unlexicalized pcfg as a baseline model, which is enriched to the level of collins' model 2 by adding lexicalization and subcategorization. the lexicalized sister-head model and a bigram model are also tested, to deal with the flatness of the french treebank. the bigram model achieves the best performance: 81% constituency f-score and 84% dependency accuracy. all lexicalized models outperform the unlexicalized baseline, consistent with probabilistic parsing results for english, but contrary to results for german, where lexicalization has only a limited effect on parsing performance.
parsing ambiguous structures using controlled disjunctions and unary quasi-trees. the problem of parsing ambiguous structures concerns (i) their representation and (ii) the specification of mechanisms allowing to delay and control their evaluation. we first propose to use a particular kind of disjunctions called controlled disjunctions: these formulae allows the representation and the implementation of specific constraints that can occur between ambiguous values. but an efficient control of ambiguous structures also has to take into account lexical as well as syntactic information concerning this object. we then propose the use of unary quasi-trees specifying constraints at these different levels. the two devices allow an efficient implementation of the control of the ambiguity. moreover, they are independent from a particular formalism and can be used whatever the linguistic theory.
intentions and indormation in discourse. this paper is about the flow of inference between communicative intentions, discourse structure and the domain during discourse processing. we augment a theory of discourse interpretation with a theory of distinct mental attitudes and reasoning about them, in order to provide an account of how the attitudes interact with reasoning about discourse structure.
acceptability prediction by means of grammaticality quantification. we propose in this paper a method for quantifying sentence grammaticality. the approach based on property grammars, a constraint-based syntactic formalism, makes it possible to evaluate a grammaticality index for any kind of sentence, including ill-formed ones. we compare on a sample of sentences the grammaticality indices obtained from pg formalism and the acceptability judgements measured by means of a psycholinguistic analysis. the results show that the derived grammaticality index is a fairly good tracer of acceptability scores.
knowledge acquisition from texts: using an automatic clustering method based on noun-modifier relationship. we describe the early stage of our methodology of knowledge acquisition from technical texts. first, a partial morpho-syntactic analysis is performed to extract "candidate terms". then, the knowledge engineer, assisted by an automatic clustering tool, builds the "conceptual fields" of the domain. we focus on this conceptual analysis stage, describe the data prepared from the results of the morpho-syntactic analysis and show the results of the clustering module and their interpretation. we found that syntactic links represent good descriptors for candidate terms clustering since the clusters are often easily interpreted as "conceptual fields".
trigger-pair predictors in parsing and tagging. in this article, we apply to natural language parsing and tagging the device of trigger-pair predictors, previously employed exclusively within the field of language modelling for speech recognition. given the task of predicting the correct rule to associate with a parse-tree node, or the correct tag to associate with a word of text, and assuming a particular class of parsing or tagging model, we quantify the information gain realized by taking account of rule or tag trigger-pair predictors, i.e. pairs consisting of a "triggering" rule or tag which has already occurred in the document being processed, together with a specific "triggered" rule or tag whose probability of occurrence within the current sentence we wish to estimate. this information gain is shown to be substantial. further, by utilizing trigger pairs taken from the same general sort of document as is being processed (e.g. same subject matter or same discourse type)---as opposed to predictors derived from a comprehensive general set of english texts---we can significantly increase this information gain.
the effect of corpus size in combining supervised and unsupervised training for disambiguation. we investigate the effect of corpus size in combining supervised and unsupervised learning for two types of attachment decisions: relative clause attachment and prepositional phrase attachment. the supervised component is collins' parser, trained on the wall street journal. the unsupervised component gathers lexical statistics from an unannotated corpus of newswire text. we find that the combined system only improves the performance of the parser for small training sets. surprisingly, the size of the unannotated corpus has little effect due to the noisiness of the lexical statistics acquired by unsupervised learning.
towards history-based grammars: using richer models for probabilistic parsing. we describe a generative probabilistic model of natural language, which we call hbg, that takes advantage of detailed linguistic information to resolve ambiguity. hbg incorporates lexical, syntactic, semantic, and structural information from the parse tree into the disambiguation process in a novel way. we use a corpus of bracketed sentences, called a treebank, in combination with decision tree building to tease out the relevant aspects of a parse tree that will determine the correct parse of a sentence. this stands in contrast to the usual approach of further grammar tailoring via the usual linguistic introspection in the hope of generating the correct parse. in head-to-head tests against one of the best existing robust probabilistic parsing models, which we call p-cfg, the hbg model significantly outperforms p-cfg, increasing the parsing accuracy rate from 60% to 75%, a 37% reduction in error.
a phrase-based statistical model for sms text normalization. short messaging service (sms) texts behave quite differently from normal written texts and have some very special phenomena. to translate sms texts, traditional approaches model such irregularities directly in machine translation (mt). however, such approaches suffer from customization problem as tremendous effort is required to adapt the language model of the existing translation system to handle sms text style. we offer an alternative approach to resolve such irregularities by normalizing sms texts before mt. in this paper, we view the task of sms normalization as a translation problem from the sms language to the english language and we propose to adapt a phrase-based statistical mt model for the task. evaluation by 5-fold cross validation on a parallel sms normalized corpus of 5000 sentences shows that our method can achieve 0.80702 in bleu score against the baseline bleu score 0.6958. another experiment of translating sms texts from english to chinese on a separate sms text corpus shows that, using sms normalization as mt preprocessing can largely boost sms translation performance from 0.1926 to 0.3770 in bleu score.
development and evaluation of a broad-coverage probabilistic grammar of english-language computer manuals. we present an approach to grammar development where the task is decomposed into two separate subtasks. the first tasks linguistic, with the goal of producing a set of rules that have a large coverage (in the sense that the correct parse is among the proposed parses) on a blind test set of sentences. the second task is statistical, with the goal of developing a model of the grammar which assigns maximum probability for the correct parse. we give parsing results on text from computer manuals.
going beyond aer: an extensive analysis of word alignments and their impact on mt. this paper presents an extensive evaluation of five different alignments and investigates their impact on the corresponding mt system output. we introduce new measures for intrinsic evaluations and examine the distribution of phrases and untranslated words during decoding to identify which characteristics of different alignments affect translation. we show that precision-oriented alignments yield better mt output (translating more words and using longer phrases) than recall-oriented alignments.
automatic compensation for parser figure-of-merit flaws. best-first chart parsing utilises a figure of merit (fom) to efficiently guide a parse by first attending to those edges judged better. in the past it has usually been static; this paper will show that with some extra information, a parser can compensate for fom flaws which otherwise slow it down. our results are faster than the prior best by a factor of 2.5; and the speedup is won with no significant decrease in parser accuracy.
discourse entities in janus. this paper addresses issues that arose in applying the model for discourse entity (de) generation in b. webber's work (1978, 1983) to an interactive multimodal interface. her treatment was extended in 4 areas: (1) the notion of context dependence of des was formalized in an intensional logic, (2) the treatment of des for indefinite nps was modified to use skolem functions, (3) the treatment of dependent quantifiers was generalized, and (4) des originating from non-linguistic sources, such as pointing actions, were taken into account. the discourse entities are used in intra- and extra-sentential pronoun resolution in bbn janus.
on the decidability of functional uncertainty. we show that feature logic extended by functional uncertainty is decidable, even if one admits cyclic descriptions. we present an algorithm, which solves feature descriptions containing functional uncertainty in two phases, both phases using a set of deterministic and non-deterministic rewrite rules. we then compare our algorithm with the one of kaplan and maxwell, that does not cover cyclic feature descriptions.
a comparison of document, sentence, and term event spaces. the trend in information retrieval systems is from document to sub-document retrieval, such as sentences in a summarization system and words or phrases in question-answering system. despite this trend, systems continue to model language at a document level using the inverse document frequency (idf). in this paper, we compare and contrast idf with inverse sentence frequency (isf) and inverse term frequency (itf). a direct comparison reveals that all language models are highly correlated; however, the average isf and itf values are 5.5 and 10.4 higher than idf. all language models appeared to follow a power law distribution with a slope coefficient of 1.6 for documents and 1.7 for sentences and terms. we conclude with an analysis of idf stability with respect to random, journal, and section partitions of the 100,830 full-text scientific articles in our experimental corpus.
a complete and recursive feature theory. various feature descriptions are being employed in constrained-based grammar formalisms. the common notational primitive of these descriptions are functional attributes called features. the descriptions considered in this paper are the possibly quantified first-order formulae obtained from a signature of features and sorts. we establish a complete first-order theory ft by means of three axiom schemes and construct three elementarily equivalent models.one of the models consists of so-called feature graphs, a data structure common in computational linguistics. the other two models consist of so-called feature trees, a record-like data structure generalizing the trees corresponding to first-order terms.our completeness proof exhibits a terminating simplification system deciding validity and satisfiability of possibly quantified feature descriptions.
outilex, a linguistic platform for text processing. we present outilex, a generalist linguistic platform for text processing. the platform includes several modules implementing the main operations for text processing and is designed to use large-coverage language resources. these resources (dictionaries, grammars, annotated texts) are formatted into xml, in accordance with current standards. evaluations on efficiency are given.
entity-based cross-document coreferencing using the vector space model. cross-document coreference occurs when the same person, place, event, or concept is discussed in more than one text source. computer recognition of this phenomenon is important because it helps break "the document boundary" by allowing a user to examine information about a particular entity from multiple text sources at the same time. in this paper we describe a cross-document coreference resolution algorithm which uses the vector space model to resolve ambiguities between people having the same name. in addition, we also describe a scoring algorithm for evaluating the cross-document coreference chains produced by our system and we compare our algorithm to the scoring algorithm used in the muc-6 (within document) coreference task.
towards an optimal lexicalization in a natural-sounding portable natural language generator for dialog systems. in contrast to the latest progress in speech recognition, the state-of-the-art in natural language generation for spoken language dialog systems is lagging behind. the core dialog managers are now more sophisticated; and natural-sounding and flexible output is expected, but not achieved with current simple techniques such as template-based systems. portability of systems across subject domains and languages is another increasingly important requirement in dialog systems. this paper presents an outline of legend, a system that is both portable and generates natural-sounding output. this goal is achieved through the novel use of existing lexical resources such as framenet and wordnet.
the berkeley framenet project. framenet is a three-year nsf-supported project in corpus-based computational lexicography, now in its second year (nsf iri-9618838, "tools for lexicon building"). the project's key features are (a) a commitment to corpus evidence for semantic and syntactic generalizations, and (b) the representation of the valences of its target words (mostly nouns, adjectives, and verbs) in which the semantic portion makes use of frame semantics. the resulting database will contain (a) descriptions of the semantic frames underlying the meanings of the words described, and (b) the valence representation (semantic and syntactic) of several thousand words and phrases, each accompanied by (c) a representative collection of annotated corpus attestations, which jointly exemplify the observed linkings between "frame elements" and their syntactic realizations (e.g. grammatical function, phrase type, and other syntactic traits). this report will present the project's goals and workflow, and information about the computational tools that have been adapted or created in-house for this work.
on representing governed prepositions and handling "incorrect" and novel prepositions. nlp systems, in order to be robust, must handle novel and ill-formed input. one common type of error involves the use of non-standard prepositions to mark arguments. in this paper, we argue that such errors can be handled in a systematic fashion, and that a system designed to handle them offers other advantages. we offer a classification scheme for preposition usage errors. further, we show how the knowledge representation employed in the sra nlp system facilitates handling these data.
coupling ccg and hybrid logic dependency semantics. categorial grammar has traditionally used the λ-calculus to represent meaning. we present an alternative, dependency-based perspective on linguistic meaning and situate it in the computational setting. this perspective is formalized in terms of hybrid logic and has a rich yet perspicuous propositional ontology that enables a wide variety of semantic phenomena to be represented in a single meaning formalism. finally, we show how we can couple this formalization to combinatory categorial grammar to produce interpretations compositionally.
low-cost, high-performance translation retrieval: dumber is better. in this paper, we compare the relative effects of segment order, segmentation and segment contiguity on the retrieval performance of a translation memory system. we take a selection of both bag-of-words and segment order-sensitive string comparison methods, and run each over both character and word-segmented data, in combination with a range of local segment contiguity models (in the form of n-grams). over two distinct datasets, we find that indexing according to simple character bigrams produces a retrieval accuracy superior to any of the tested word n-gram models. further, in their optimum configuration, bag-of-words methods are shown to be equivalent to segment order-sensitive methods in terms of retrieval accuracy, but much faster. we also provide evidence that our findings are scalable.
discriminative word alignment with conditional random fields. in this paper we present a novel approach for inducing word alignments from sentence aligned data. we use a conditional random field (crf), a discriminative model, which is estimated on a small supervised training set. the crf is conditioned on both the source and target texts, and thus allows for the use of arbitrary and overlapping features over these data. moreover, the crf has efficient training and decoding processes which both find globally optimal solutions.we apply this alignment model to both french-english and romanian-english language pairs. we show how a large number of highly predictive features can be easily incorporated into the crf, and demonstrate that even with only a few hundred word-aligned training sentences, our model improves over the current state-of-the-art with alignment error rates of 5.29 and 25.8 for the two tasks respectively.
learning the countability of english nouns from corpus data. this paper describes a method for learning the countability preferences of english nouns from raw text corpora. the method maps the corpus-attested lexico-syntactic properties of each noun onto a feature vector, and uses a suite of memory-based classifiers to predict membership in 4 countability classes. we were able to assign countability to english nouns with a precision of 94.6%.
multiple underlying systems: translating user requests into programs to produce answers. a user may typically need to combine the strengths of more than one system in order to perform a task. in this paper, we describe a component of the janus natural language interface that translates intensional logic expressions representing the meaning of a request into executable code for each application program, chooses which combination of application systems to use, and designs the transfer of data among them in order to provide an answer. the complete janus natural language system has been ported to two large command and control decision support aids.
an improved parser for data-oriented lexical-functional analysis. we present an lfg-dop parser which uses fragments from lfg-annotated sentences to parse new sentences. experiments with the verbmobil and homecentre corpora show that (1) viterbi n best search performs about 100 times faster than monte carlo search while both achieve the same accuracy; (2) the dop hypothesis which states that parse accuracy increases with increasing fragment size is confirmed for lfg-dop; (3) lfg-dop's relative frequency estimator performs worse than a discounted frequency estimator; and (4) lfg-dop significantly outperforms tree-dop if evaluated on tree structures only.
negative polarity licensing at the syntax-semantics interface. recent work on the syntax-semantics interface (see e.g. (dalrymple et al., 1994)) uses a fragment of linear logic as a 'glue language' for assembling meanings compositionally. this paper presents a glue language account of how negative polarity items (e.g. ever, any) get licensed within the scope of negative or downward-entailing contexts (ladusaw, 1979), e.g. nobody ever left. this treatment of licensing operates precisely at the syntax-semantics interface, since it is carried out entirely within the interface glue language (linear logic). in addition to the account of negative polarity licensing, we show in detail how linear-logic proof nets (girard, 1987; gallier, 1992) can be used for efficient meaning deduction within this 'glue language' framework.
a general computational treatment of comparatives for natural language question answering. we discuss the techniques we have developed and implemented for the cross-categorial treatment of comparatives in teli, a natural language question-answering system that's transportable among both application domains and types of backend retrieval systems. for purposes of illustration, we shall consider the example sentences "list the cars at least 20 inches more than twice as long as the century is wide" and "have any us companies made at least 3 more large cars than buick?" issues to be considered include comparative inflections, left recursion and other forms of nesting, extraposition of comparative complements, ellipsis, the wh element "how", and the translation of normalized parse trees into logical form.
what is the minimal set of fragments that achieves maximal parse accuracy? we aim at finding the minimal set of fragments which achieves maximal parse accuracy in data oriented parsing. experiments with the penn wall street journal treebank show that counts of almost arbitrary fragments within parse trees are important, leading to improved parse accuracy over previous models tested on this treebank (a precision of 90.8% and a recall of 90.6%). we isolate some dependency relations which previous models neglect but which contribute to higher parse accuracy.
integrating word boundary identification with sentence understanding. chinese sentences are written with no special delimiters such as space to indicate word boundaries. existing chinese nlp systems therefore employ preprocessors to segment sentences into words. contrary to the conventional wisdom of separating this issue from the task of sentence understanding, we propose an integrated model that performs word boundary identification in lockstep with sentence understanding. in this approach, there is no distinction between rules for word boundary identification and rules for sentence understanding. these two functions are combined. word boundary ambiguities are detected, especially the fallacious ones, when they block the primary task of discovering the inter-relationships among the various constituents of a sentence, which essentially is the essence of the understanding process. in this approach, statistical information is also incorporated, providing the system a quick and fairly reliable starting ground to carry out the primary task of relationship-building.
learning the structure of task-driven human-human dialogs. data-driven techniques have been used for many computational linguistics tasks. models derived from data are generally more robust than hand-crafted systems since they better reflect the distribution of the phenomena being modeled. with the availability of large corpora of spoken dialog, dialog management is now reaping the benefits of data-driven techniques. in this paper, we compare two approaches to modeling subtask structure in dialog: a chunk-based model of subdialog sequences, and a parse-based, or hierarchical, model. we evaluate these models using customer agent dialogs from a catalog service domain.
responding to user queries in a collaborative environment. we propose a plan-based approach for responding to user queries in a collaborative environment. we argue that in such an environment, the system should not accept the user's query automatically, but should consider it a proposal open for negotiation. in this paper we concentrate on cases in which the system and user disagree, and discuss how this disagreement can be detected, negotiated, and how final modifications should be made to the existing plan.
a bottom-up approach to sentence ordering for multi-document summarization. ordering information is a difficult but important task for applications generating natural language texts such as multi-document summarization, question answering, and concept-to-text generation. in multi-document summarization, information is selected from a set of source documents. however, improper ordering of information in a summary can confuse the reader and deteriorate the readability of the summary. therefore, it is vital to properly order the information in multi-document summarization. we present a bottom-up approach to arrange sentences extracted for multi-document summarization. to capture the association and order of two textual segments (e.g. sentences), we define four criteria: chronology, topical-closeness, precedence, and succession. these criteria are integrated into a criterion by a supervised learning approach. we repeatedly concatenate two textual segments into one segment based on the criterion, until we obtain the overall segment with all sentences arranged. we evaluate the sentence orderings produced by the proposed method and numerous baselines using subjective gradings as well as automatic evaluation measures. we introduce the average continuity, an automatic evaluation measure of sentence ordering in a summary, and investigate its appropriateness for this task.
anchoring floating quantifiers in japanese-to-english machine transltion. in this paper we present an algorithm to anchor floating quantifiers in japanese, a language in which quantificational nouns and numeral-classifier combinations can appear separated from the noun phrase they quantify. the algorithm differentiates degree and event modifiers from nouns that quantify noun phrases. it then finds a suitable anchor for such floating quantifiers. to do this, the algorithm considers the part of speech of the quantifier and the target, the semantic relation between them, the case marker of the antecedent and the meaning of the verb that governs the two constituents. the algorithm has been implemented and tested in a rule-based japanese-to-english machine translation system, with an accuracy of 76% and a recall of 97%.
a dop model for semantic interpretation. in data-oriented language processing, an annotated language corpus is used as a stochastic grammar. the most probable analysis of a new sentence is constructed by combining fragments from the corpus in the most probable way. this approach has been successfully used for syntactic analysis, using corpora with syntactic annotations such as the penn tree-bank. if a corpus with semantically annotated sentences is used, the same approach can also generate the most probable semantic interpretation of an input sentence. the present paper explains this semantic interpretation method. a data-oriented semantic interpretation algorithm was tested on two semantically annotated corpora: the english atis corpus and the dutch ovis corpus. experiments show an increase in semantic accuracy if larger corpus-fragments are taken into consideration.
managing information at linguistic interfaces. a large spoken dialogue translation system imposes both engineering and linguistic constraints on the way in which linguistic information is communicated between modules. we describe the design and use of interface terms, whose formal, functional and communicative role has been tested in a sequence of integrated systems and which have proven adequate to these constraints.
shallow parsing on the basis of words only: a case study. we describe a case study in which a memory-based learning algorithm is trained to simultaneously chunk sentences and assign grammatical function tags to these chunks. we compare the algorithm's performance on this parsing task with varying training set sizes (yielding learning curves) and different input representations. in particular we compare input consisting of words only, a variant that includes word form information for low-frequency words, gold-standard pos only, and combinations of these. the word-based shallow parser displays an apparently log-linear increase in performance, and surpasses the flatter pos-based curve at about 50,000 sentences of training data. the low-frequency variant performs even better, and the combinations is best. comparative experiments with a real pos tagger produce lower results. we argue that we might not need an explicit intermediate pos-tagging step for parsing when a sufficient amount of training material is available and word form information is used for low-frequency words.
memory-based morphological analysis. we present a general architecture for efficient and deterministic morphological analysis based on memory-based learning, and apply it to morphological analysis of dutch. the system makes direct mappings from letters in context to rich categories that encode morphological boundaries, syntactic class labels, and spelling changes. both precision and recall of labeled morphemes are over 84% on held-out dictionary test words and estimated to be over 93% in free text.
detecting problematic turns in human-machine interactions: rule-induction versus memory-based learning approaches. we address the issue of on-line detection of communication problems in spoken dialogue systems. the usefulness is investigated of the sequence of system question types and the word graphs corresponding to the respective user utterances. by applying both rule-induction and memory-based learning techniques to data obtained with a dutch train time-table information system, the current paper demonstrates that the aforementioned features indeed lead to a method for problem detection that performs significantly above baseline. the results are interesting from a dialogue perspective since they employ features that are present in the majority of spoken dialogue systems and can be obtained with little or no computational overhead. the results are interesting from a machine learning perspective, since they show that the rule-based method performs significantly better than the memory-based method, because the former is better capable of representing interactions between features.
simulating children's null subjects: an early language generation model. this paper reports work in progress on a sentence generation model which attempts to emulate certain language output patterns of children between the ages of one and one-half and three years. in particular, the model addresses the issue of why missing or phonetically "null" subjects appear as often as they do in the speech of young english-speaking children. it will also be used to examine why other patterns of output appear in the speech of children learning languages such as italian and chinese. initial findings are that an output generator successfully approximates the null-subject output patterns found in english-speaking children by using a 'processing overload' metric alone; however, reference to several parameters related to discourse orientation and agreement morphology is necessary in order to account for the differing patterns of null arguments appearing cross-linguistically. based on these findings, it is argued that the 'null-subject phenomenon' is due to the combined effects of limited processing capacity and early, accurate parameter setting.
a quantitative analysis of lexical differences between genders in telephone conversations. in this work, we provide an empirical analysis of differences in word use between genders in telephone conversations, which complements the considerable body of work in sociolinguistics concerned with gender linguistic differences. experiments are performed on a large speech corpus of roughly 12000 conversations. we employ machine learning techniques to automatically categorize the gender of each speaker given only the transcript of his/her speech, achieving 92% accuracy. an analysis of the most characteristic words for each gender is also presented. experiments reveal that the gender of one conversation side influences lexical use of the other side. a surprising result is that we were able to classify male-only vs. female-only conversations with almost perfect accuracy.
another facet of lig parsing. in this paper we present a new parsing algorithm for linear indexed grammars (ligs) in the same spirit as the one described in (vijay-shanker and weir, 1993) for tree adjoining grammars. for a lig l and an input string x of length n, we build a non ambiguous context-free grammar whose sentences are all (and exclusively) valid derivation sequences in l which lead to x. we show that this grammar can be built in o(n6) time and that individual parses can be extracted in linear time with the size of the extracted parse tree. though this o(n6) upper bound does not improve over previous results, the average case behaves much better. moreover, practical parsing times can be decreased by some statically performed computations.
defaults in unification grammar. incorporation of defaults in grammar formalisms is important for reasons of linguistic adequacy and grammar organization. in this paper we present an algorithm for handling default information in unification grammar. the algorithm specifies a logical operation on feature structures, merging with the non-default structure only those parts of the default feature structure which are not constrained by the non-default structure. we present various linguistic applications of default unification.
constraint-based categorical grammar. we propose a generalization of categorial grammar in which lexical categories are defined by means of recursive constraints. in particular, the introduction of relational constraints allows one to capture the effects of (recursive) lexical rules in a computationally attractive manner. we illustrate the linguistic merits of the new approach by showing how it accounts for the syntax of dutch cross-serial dependencies and the position and scope of adjuncts in such constructions. delayed evaluation is used to process grammars containing recursive constraints.
a morphographemic model for error correction in nonconcatenative strings. this paper introduces a spelling correction system which integrates seamlessly with morphological analysis using a multi-tape formalism. handling of various semitic error problems is illustrated, with reference to arabic and syriac examples. the model handles errors vocalisation, diacritics, phonetic syncopation and morphographemic idiosyncrasies, in addition to damerau errors. a complementary correction strategy for morphologically sound but morphosyntactically ill-formed words is outlined.
deriving the predicate-argument structure for a free word order language. in relatively free word order languages, grammatical functions are intricately related to case marking. assuming an ordered representation of the predicate-argument structure, this work proposes a combinatory categorial grammar formulation of relating surface case cues to categories and types for correctly placing the arguments in the predicate-argument structure. this is achieved by treating case markers as type shifters. unlike other cg formulations, type shifting does not proliferate or cause spurious ambiguity. categories of all argument-encoding grammatical functions follow from the same principle of category assignment. normal order evaluation of the combinatory form reveals the predicate-argument structure. the application of the method to turkish is shown.
the logical structure of binding. a logical recasting of binding theory is performed as an enhancing step for the purpose of its full and lean declarative implementation. a new insight on sentential anaphoric processes is presented which may suggestively be captured by the slogan binding conditions are the effect of phase quantification on the universe of discourse referents.
tagset reduction without information loss. a technique for reducing a tagset used for n-gram part-of-speech disambiguation is introduced and evaluated in an experiment. the technique ensures that all information that is provided by the original tagset can be restored from the reduced one. this is crucial, since we are interested in the linguistically motivated tags for part-of-speech disambiguation. the reduced tagset needs fewer parameters for its statistical model and allows more accurate parameter estimation. additionally, there is a slight but not significant improvement of tagging accuracy.
a simplified theory of tense representations and constraints on their composition. this paper proposes a set of representations for tenses and a set of constraints on how they can be combined in adjunct clauses. the semantics we propose explains the possible meanings of tenses in a variety of sentential contexts. it also supports an elegant constraint on tense combination in adjunct clauses. these semantic representations provide insights into the interpretations of tenses, and the constraints provide a source of syntactic disambiguation that has not previously been demonstrated. we demonstrate an implemented disambiguator for a certain class of three-clause sentences based on our theory.
automatic acquisition of subcategorization frames from untagged text. this paper describes an implemented program that takes a raw, untagged text corpus as its only input (no open-class dictionary) and generates a partial list of verbs occurring in the text and the subcategorization frames (sfs) in which they occur. verbs are detected by a novel technique based on the case filter of rouvret and vergnaud (1980). the completeness of the output list increases monotonically with the total number of occurrences of each verb in the corpus. false positive rates are one to three percent of observations. five sfs are currently detected and more are planned. ultimately, i expect to provide a large sf dictionary to the nlp community and to train dictionaries for specific corpora.
chinese text segmentation with mbdp-1: making the most of training corpora. this paper describes a system for segmenting chinese text into words using the mbdp-1 algorithm. mbdp-1 is a knowledge-free segmentation algorithm that bootstraps its own lexicon, which starts out empty. experiments on chinese and english corpora show that mbdp-1 reliably outperforms the best previous algorithm when the available hand-segmented training corpus is small. as the size of the hand-segmented training corpus grows, the performance of mbdp-1 converges toward that of the best previous algorithm. the fact that mbdp-1 can be used with a small corpus is expected to be useful not only for the rare event of adapting to a new language, but also for the common event of adapting to a new genre within the same language.
automatic grammar induction and parsing free text: a transformation-based approach. in this paper we describe a new technique for parsing free text: a transformational grammar1 is automatically learned that is capable of accurately parsing text into binary-branching syntactic trees with nonterminals unlabelled. the algorithm works by beginning in a very naive state of knowledge about phrase structure. by repeatedly comparing the results of bracketing in the current state to proper bracketing provided in the training corpus, the system learns a set of simple structural transformations that can be applied to reduce error. after describing the algorithm, we present results and compare these results to other recent results in automatic grammar induction.
beyond n-grams: can linguistic sophistication improve language modeling? it seems obvious that a successful model of natural language would incorporate a great deal of both linguistic and world knowledge. interestingly, state of the art language models for speech recognition are based on a very crude linguistic model, namely conditioning the probability of a word on a small fixed number of preceding words. despite many attempts to incorporate more sophisticated information into the models, the n-gram model remains the state of the art, used in virtually all speech recognition systems. in this paper we address the question of whether there is hope in improving language modeling by incorporating more sophisticated linguistic and world knowledge, or whether the n-grams are already capturing the majority of the information that can be employed.
an improved error model for noisy channel spelling correction. the noisy channel model has been applied to a wide range of problems, including spelling correction. these models consist of two components: a source model and a channel model. very little research has gone into improving the channel model for spelling correction. this paper describes a new channel model for spelling correction, based on generic string to string edits. using this model gives significant performance improvements compared to previously proposed models.
man* vs. machine: a case study in base noun phrase learning. a great deal of work has been done demonstrating the ability of machine learning algorithms to automatically extract linguistic knowledge from annotated corpora. very little work has gone into quantifying the difference in ability at this task between a person and a machine. this paper is a first step in that direction.
classifier combination for improved lexical disambiguation. one of the most exciting recent directions in machine learning is the discovery that the combination of multiple classifiers often results in significantly better performance than what can be achieved with a single classifier. in this paper, we first show that the errors made from three different state of the art part of speech taggers are strongly complementary. next, we show how this complementatry behavior can be used to our advantage. by using contextual cues to guide tagger combination, we are able to derive a new tagger that achieves performance significantly greater than any of the individual taggers.
lexical access in connected speech recognition. this paper addresses two issues concerning lexical access in connected speech recognition: 1) the nature of the pre-lexical representation used to initiate lexical lookup 2) the points at which lexical look-up is triggered off this representation. the results of an experiment are reported which was designed to evaluate a number of access strategies proposed in the literature in conjunction with several plausible pre-lexical representations of the speech input. the experiment also extends previous work by utilising a dictionary database containing a realistic rather than illustrative english vocabulary.
co-evolution of language and of the language acquisition device. a new account of parameter setting during grammatical acquisition is presented in terms of generalized categorial grammar embedded in a default inheritance hierarchy, providing a natural partial ordering on the setting of parameters. experiments show that several expermentally effective learners can be defined in this framework. evolutionary simulations suggest that a learner with default initial settings for parameters will emerge, provided that learning is memory limited and the environment of linguistic adaptation contains an appropriate language.
evaluating the accuracy of an unlexicalized statistical parser on the parc depbank. we evaluate the accuracy of an unlexicalized statistical parser, trained on 4k treebanked sentences from balanced data and tested on the parc depbank. we demonstrate that a parser which is competitive in accuracy (without sacrificing processing speed) can be quickly tuned without reliance on large in-domain manually-constructed treebanks. this makes it more practical to use statistical parsers in applications that need access to aspects of predicate-argument structure. the comparison of systems using depbank is not straightforward, so we extend and validate depbank and highlight a number of representation and scoring issues for relational evaluation schemes.
the second release of the rasp system. we describe the new release of the rasp (robust accurate statistical parsing) system, designed for syntactic annotation of free text. the new version includes a revised and more semantically-motivated output representation, an enhanced grammar and part-of-speech tagger lexicon, and a more flexible and semi-supervised training method for the structural parse ranking model. we evaluate the released version on the wsj using a relational evaluation scheme, and describe how the new release allows users to enhance performance using (in-domain) lexical information.
correcting esl errors using phrasal smt techniques. this paper presents a pilot study of the use of phrasal statistical machine translation (smt) techniques to identify and correct writing errors made by learners of english as a second language (esl). using examples of mass noun errors found in the chinese learner error corpus (clec) to guide creation of an engineered training set, we show that application of the smt paradigm can capture errors not well addressed by widely-used proofing tools designed for native speakers. our system was able to correct 61.81% of mistakes in a set of naturally-occurring examples of mass noun errors found on the world wide web, suggesting that efforts to collect alignable corpora of pre- and post-editing esl writing samples offer can enable the development of smt-based writing assistance tools capable of repairing many of the complex syntactic and lexical problems found in the writing of esl learners.
ensemble methods for unsupervised wsd. combination methods are an effective way of improving system performance. this paper examines the benefits of system combination for unsupervised wsd. we investigate several voting- and arbiter-based combination strategies over a diverse pool of unsupervised wsd systems. our combination methods rely on predominant senses which are derived automatically from raw text. experiments using the semcor and senseval-3 data sets demonstrate that our ensembles yield significantly better results when compared with state-of-the-art.
separating surface order and syntactic relations in a dependency grammar. this paper proposes decoupling the dependency tree from word order, such that surface ordering is not determined by traversing the dependency tree. we develop the notion of a word order domain structure, which is linked but structurally dissimilar to the syntactic dependency tree. the proposal results in a lexicalized, declarative, and formally precise description of word order; features which lack previous proposals for dependency grammars. contrary to other lexicalized approaches to word order, our proposal does not require lexical ambiguities for ordering alternatives.
aligning sentences in parallel corpora. in this paper we describe a statistical technique for aligning sentences with their translations in two parallel corpora. in addition to certain anchor points that are available in our data, the only information about the sentences that we use for calculating alignments is the number of tokens that they contain. because we make no use of the lexical details of the sentence, the alignment computation is fast and therefore practical for application to very large collections of text. we have used this technique to align several million sentences in the english-french hansard corpora and have achieved an accuracy in excess of 99% in a random selected set of 1000 sentence pairs that we checked by hand. we show that even without the benefit of anchor points the correlation between the lengths of aligned sentences is strong enough that we should expect to achieve an accuracy of between 96% and 97%. thus, the technique may be applicable to a wider variety of texts than we have yet tried.
word-sense disambiguation using statistical methods. we describe a statistical technique for assigning senses to words. an instance of a word is assigned a sense by asking a question about the context in which the word appears. the question is constructed to have high mutual information with the translation of that instance in another language. when we incorporated this method of assigning senses into our statistical machine translation system, the error rate of the system decreased by thirteen percent.
word-sense disambiguation using decomposable models. most probabilistic classifiers used for word-sense disambiguation have either been based on only one contextual feature or have used a model that is simply assumed to characterize the interdependencies among multiple contextual features. in this paper, a different approach to formulating a probabilistic model is presented along with a case study of the performance of models produced in this manner for the disambiguation of the noun interest. we describe a method for formulating probabilistic models that use multiple contextual features for word-sense disambiguation, without requiring untested assumptions regarding the form of the model. using this approach, the joint distribution of all variables is described by only the most systematic variable interactions, thereby limiting the number of parameters to be estimated, supporting computational efficiency, and providing an understanding of the data.
the interpretation of relational nouns. this paper decribes a computational treatment of the semantics of relational nouns. it covers relational nouns such as "sister" and "commander", and focuses especially on a particular subcategory of them, called function nouns ("speed", "distance", "rating"). relational nouns are usually viewed as either requiring non-compositional semantic interpretation, or causing an undesirable proliferation of syntactic rules. in contrast to this, we present a treatment which is both syntactically uniform and semantically compositional. the core ideas of this treatment are: (1) the recognition of different levels of semantic analysis; in particular, the distinction between an english-oriented and a domain-oriented level of meaning representation. (2) the analysis of relational nouns as denoting relation-extensions.the paper shows how this approach handles a variety of linguistic constructions involving relational nouns. the treatment presented here has been implemented in bbn's spoken language system, an experimental spoken language interface to a database/graphics system.
terminology finite-state preprocessing for computational lfg. this paper presents a technique to deal with multiword nominal terminology in a computational lexical functional grammar. this method treats multiword terms as single tokens by modifying the preprocessing stage of the grammar (tokenization and morphological analysis), which consists of a cascade of two-level finite-state automata (transducers). we present here how we build the transducers to take terminology into account. we tested the method by parsing a small corpus with the without this treatment of multiword terms. the number of parses and parsing time decrease without affecting the relevance of the results. moreover, the method improves the perspicuity of the analyses.
collective information extraction with relational markov networks. most information extraction (ie) systems treat separate potential extractions as independent. however, in many cases, considering influences between different potential extractions could improve overall accuracy. statistical methods based on undirected graphical models, such as conditional random fields (crfs), have been shown to be an effective approach to learning accurate ie systems. we present a new ie method that employs relational markov networks (a generalization of crfs), which can represent arbitrary dependencies between extractions. this allows for "collective information extraction" that exploits the mutual influence between possible extractions. experiments on learning to extract protein names from biomedical text demonstrate the advantages of this approach.
named entity scoring for speech input. this paper describes a new scoring algorithm that supports comparison of linguistically annotated data from noisy sources. the new algorithm generalizes the message understanding conference (muc) named entity scoring algorithm, using a comparison based on explicit alignment of the underlying texts, followed by a scoring phase. the scoring procedure maps corresponding tagged regions and compares these according to tag type and tag extent, allowing us to reproduce the muc named entity scoring for identical underlying texts. in addition, the new algorithm scores for content (transcription correctness) of the tagged region, a useful distinction when dealing with noisy data that may differ from a reference transcription (e.g., speech recognizer output). to illustrate the algorithm, we have prepared a small test data set consisting of a careful transcription of speech data and manual insertion of sgml named entity annotation. we report results for this small test corpus on a variety of experiments involving automatic speech recognition and named entity tagging.
automated scoring using a hybrid feature identification technique. this study exploits statistical redundancy inherent in natural language to automatically predict scores for essays. we use a hybrid feature identification method, including syntactic structure analysis, rhetorical structure analysis, and topical analysis, to score essay responses from test-takers of the graduate management admissions test (gmat) and the test of written english (twe). for each essay question, a stepwise linear regression analysis is run on a training set (sample of human scored essay responses) to extract a weighted set of predictive features for each test question. score prediction for cross-validation sets is calculated from the set of predictive features. exact or adjacent agreement between the electronic essay rater (e-rater) score predictions and human rater scores ranged from 87% to 94% across the 15 test questions.
towards automatic classification of discourse elements in essays. educators are interested in essay evaluation systems that include feedback about writing features that can facilitate the essay revision process. for instance, if the thesis statement of a student's essay could be automatically identified, the student could then use this information to reflect on the thesis statement with regard to its quality, and its relationship to other discourse elements in the essay. using a relatively small corpus of manually annotated data, we use bayesian classification to identify thesis statements. this method yields results that are much closer to human performance than the results produced by two baseline systems.
using an on-line dictionary to find rhyming words and pronunciations for unknown words. humans know a great deal about relationships among words. this paper discusses relationships among word pronunciations. we describe a computer system which models human judgement of rhyme by assigning specific roles to the location of primary stress, the similarity of phonetic segments, and other factors. by using the model as an experimental tool, we expect to improve our understanding of rhyme. a related computer model will attempt to generate pronunciations for unknown words by analogy with those for known words. the analogical processes involve techniques for segmenting and matching word spellings, and for mapping spelling to sound in known words. as in the case of rhyme, the computer model will be an important tool for improving our understanding of these processes. both models serve as the basis for functions in the wordsmith automated dictionary system.
adapting an english morphological analyzer for french. a word-based morphological analyzer and a dictionary for recognizing inflected forms of french words have been built by adapting the udict system. we describe the adaptations, emphasizing mechanisms developed to handle french verbs. this work lays the groundwork for doing french derivational morphology and morphology for other languages.
resolving pronominal reference to abstract entities. this paper describes phora, a technique for resolving pronominal reference to either individual or abstract entities. it defines processes for evoking abstract referents from discourse and for resolving both demonstrative and personal pronouns. it successfully interprets 72% of test pronouns, compared to 37% for a leading technique without these features.
a preliminary model of centering in dialog. the centering framework explains local coherence by relating local focus and the form of referring expressions. it has proven useful in monolog, but its utility for multi-party discourse has not been shown, and a variety of issues must be tackled to adapt the model for dialog. this paper reports our application of three naive models of centering theory for dialog. these results will be used as baselines for evaluating future models.
long-distance dependency resolution in automatically acquired wide-coverage pcfg-based lfg approximations. this paper shows how finite approximations of long distance dependency (ldd) resolution can be obtained automatically for wide-coverage, robust, probabilistic lexical-functional grammar (lfg) resources acquired from treebanks. we extract lfg subcategorisation frames and paths linking ldd reentrancies from f-structures generated automatically for the penn-ii treebank trees and use them in an ldd resolution algorithm to parse new text. unlike (collins, 1999; johnson, 2000), in our approach resolution of ldds is done at f-structure (attribute-value structure representations of basic predicate-argument or dependency structure) without empty productions, traces and coindexation in cfg parse trees. currently our best automatically induced grammars achieve 80.97% f-score for f-structures parsing section 23 of the wsj part of the penn-ii treebank and evaluating against the dcu 1051 and 80.24% against the parc 700 dependency bank (king et al., 2003), performing at the same or a slightly better level than state-of-the-art hand-crafted grammars (kaplan et al., 2004).
from rags to riches: exploiting the potential of a flexible generation architecture. the rags proposals for generic specification of nlg systems includes a detailed account of data representation, but only an outline view of processing aspects. in this paper we introduce a modular processing architecture with a concrete implementation which aims to meet the rags goals of transparency and reusability. we illustrate the model with the riches system -- a generation system built from simple linguistically-motivated modules.
robust pcfg-based generation using automatically acquired lfg approximations. we present a novel pcfg-based architecture for robust probabilistic generation based on wide-coverage lfg approximations (cahill et al., 2004) automatically extracted from treebanks, maximising the probability of a tree given an f-structure. we evaluate our approach using string-based evaluation. we currently achieve coverage of 95.26%, a bleu score of 0.7227 and string accuracy of 0.7476 on the penn-ii wsj section 23 sentences of length ≤20.
the effect of pitch accenting on pronoun referent resolution. by strictest interpretation, theories of both centering and intonational meaning fail to predict the existence of pitch accented pronominals. yet they occur felicitously in spoken discourse. to explain this, i emphasize the dual functions served by pitch accents, as markers of both propositional (semantic/pragmatic) and attentional salience. this distinction underlies my proposals about the attentional consequences of pitch accents when applied to pronominals, in particular, that while most pitch accents may weaken or reinforce a cospecifier's status as the center of attention, a contrastively stressed pronominal may force a shift, even when contraindicated by textual features.
integrating discourse markers into a pipelined natural language generation architecture. pipelined natural language generation (nlg) systems have grown increasingly complex as architectural modules were added to support language functionalities such as referring expressions, lexical choice, and revision. this has given rise to discussions about the relative placement of these new modules in the overall architecture. recent work on another aspect of multi-paragraph text, discourse markers, indicates it is time to consider where a discourse marker insertion algorithm fits in. we present examples which suggest that in a pipelined nlg architecture, the best approach is to strongly tie it to a revision component. finally, we evaluate the approach in a working multi-page system.
pronominalization in generated discourse and dialogue. previous approaches to pronominalization have largely been theoretical rather than applied in nature. frequently, such methods are based on centering theory, which deals with the resolution of anaphoric pronouns. but it is not clear that complex theoretical mechanisms, while having satisfying explanatory power, are necessary for the actual generation of pronouns. we first illustrate examples of pronouns from various domains, describe a simple method for generating pronouns in an implemented multi-page generation system, and present an evaluation of its performance.
scaling phrase-based statistical machine translation to larger corpora and longer phrases. in this paper we describe a novel data structure for phrase-based statistical machine translation which allows for the retrieval of arbitrarily long phrases while simultaneously using less memory than is required by current decoder implementations. we detail the computational complexity and average retrieval times for looking up phrase translations in our suffix array-based data structure. we show how sampling can be used to reduce the retrieval time by orders of magnitude with no loss in translation quality.
statistical machine translation with word- and sentence-aligned parallel corpora. the parameters of statistical translation models are typically estimated from sentence-aligned parallel corpora. we show that significant improvements in the alignment and translation quality of such models can be achieved by additionally including word-aligned data during training. incorporating word-level alignments into the parameter estimation of the ibm models reduces alignment error rate and increases the bleu score when compared to training the same models only on sentence-aligned data. on the verbmobil data set, we attain a 38% reduction in the alignment error rate and a higher bleu score with half as many training examples. we discuss how varying the ratio of word-aligned to sentence-aligned data affects the expected performance gain.
using linguistic principles to recover empty categories. this paper describes an algorithm for detecting empty nodes in the penn treebank (marcus et al., 1993), finding their antecedents, and assigning them function tags, without access to lexical information such as valency. unlike previous approaches to this task, the current method is not corpus-based, but rather makes use of the principles of early government-binding theory (chomsky, 1981), the syntactic theory that underlies the annotation. using the evaluation metric proposed by johnson (2002), this approach outperforms previously published approaches on both detection of empty categories and antecedent identification, given either annotated input stripped of empty categories or the output of a parser. some problems with this evaluation metric are noted and an alternative is proposed along with the results. the paper considers the reasons a principle-based approach to this problem should outperform corpus-based approaches, and speculates on the possibility of a hybrid approach.
generating an ltag out of a principle-based hierarchical representation. lexicalized tree adjoining grammars have proved useful for nlp. however, numerous redundancy problems face ltags developers, as highlighted by vijay-shanker and schabes (92).we present and a tool that automatically generates the tree families of an ltag. it starts from a compact hierarchical organization of syntactic descriptions that is linguistically motivated and carries out all the relevant combinations of linguistic phenomena.
building parallel ltag for french and italian. in this paper we view lexicalized tree adjoining grammars as the compilation of a more abstract and modular layer of linguistic description: the metagrammar (mg). mg provides a hierarchical representation of lexico-syntactic descriptions and principles that capture the well-formedness of lexicalized structures, expressed using syntactic functions. this makes it possible for a tool to compile an instance of mg into an ltag, automatically performing the relevant combinations of linguistic phenomena. we then describe the instantiation of an mg for italian and french. the work for french was performed starting with an existing ltag, which has been augmented as a result. the work for italian was performed by systematic contrast with the french mg. the automatic compilation gives two parallel ltag, compatible for multilingual nlp applications.
uncertainty reduction in collaborative bootstrapping: measure and algorithm. this paper proposes the use of uncertainty reduction in machine learning methods such as co-training and bilingual boot-strapping, which are referred to, in a general term, as 'collaborative bootstrapping'. the paper indicates that uncertainty reduction is an important factor for enhancing the performance of collaborative bootstrapping. it proposes a new measure for representing the degree of uncertainty correlation of the two classifiers in collaborative bootstrapping and uses the measure in analysis of collaborative bootstrapping. furthermore, it proposes a new algorithm of collaborative bootstrapping on the basis of uncertainty reduction. experimental results have verified the correctness of the analysis and have demonstrated the significance of the new algorithm.
automatic construction of a hypernym-labeled noun hierarchy from text. previous work has shown that automatic methods can be used in building semantic lexicons. this work goes a step further by automatically creating not just clusters of related words, but a hierarchy of nouns and their hypernyms, akin to the hand-built hierarchy in wordnet.
a pragmatics-based approach to understanding intersentential ellipsis. intersentential elliptical utterances occur frequently in information-seeking dialogues. this paper presents a pragmatics-based framework for interpreting such utterances, including identification of the speaker's discourse goal in employing the fragment. we claim that the advantage of this approach is its reliance upon pragmatic information, including discourse content and conversational goals, rather than upon precise representations of the preceding utterance alone.
metapher - a key to extensible semantic analysis. interpreting metaphors is an integral and inescapable process in human understanding of natural language. this paper discusses a method of analyzing metaphors based on the existence of a small number of generalized metaphor mappings. each generalized metaphor contains a recognition network, a basic mapping, additional transfer mappings, and an implicit intention component. it is argued that the method reduces metaphor interpretation from a reconstruction to a recognition task. implications towards automating certain aspects of language learning are also discussed.
corpus-based acquisition of relative pronoun disambiguation heuristics. this paper presents a corpus-based approach for deriving heuristics to locate the antecedents of relative pronouns. the technique duplicates the performance of hand-coded rules and requires human intervention only during the training phase. because the training instances are built on parser output rather than word cooccurrences, the technique requires a small number of training examples and can be used on small to medium-sized corpora. our initial results suggest that the approach may provide a general method for the automated acquisition of a variety of disambiguation heuristics for natural language systems, especially for problems that require the assimilation of syntactic and semantic knowledge.
error-driven pruning of treebank grammars for base noun phrase identification. finding simple, non-recursive, base noun phrases is an important subtask for many natural language processing applications. while previous empirical methods for base np identification have been rather complex, this paper instead proposes a very simple algorithm that is tailored to the relative simplicity of the task. in particular, we present a corpus-based approach for finding base nps by matching part-of-speech tag sequences. the training phase of the algorithm is based on two successful techniques: first the base np grammar is read from a "treebank" corpus; then the grammar is improved by selecting rules with high "benefit" scores. using this simple algorithm with a naive heuristic for matching rules, we achieve surprising accuracy in an evaluation on the penn treebank wall street journal.
an empirical study of the influence of argument conciseness on argument effectiveness. we have developed a system that generates evaluative arguments that are tailored to the user, properly arranged and concise. we have also developed an evaluation framework in which the effectiveness of evaluative arguments can be measured with real users. this paper presents the results of a formal experiment we have performed in our framework to verify the influence of argument conciseness on argument effectiveness
paralanguage in computer mediated communication. this paper reports on some of the components of person to person communication mediated by computer conferenceing systems. transcripts from two systems were analysed: the electronic information and exchange system (eies), based at the new jersey institute of technology; and planet, based at infomedia inc. in palo alto, california. the research focused upon the ways in which expressive communication is encoded by users of the medium
inclusion, disjointness and choice: the logic of linguistic classification. we investigate the logical structure of concepts generated by conjunction and disjunction over a monotonic multiple inheritance network where concept nodes represent linguistic categories and links indicate basic inclusion (isa) and disjointness (isnota) relations. we model the distinction between primitive and defined concepts as well as between closed-and open-world reasoning. we apply our logical analysis to the sort inheritance and unification system of hpsg and also to classification in systemic choice systems.
word sense disambiguation vs. statistical machine translation. we directly investigate a subject of much recent debate: do word sense disambiguation models help statistical machine translation quality? we present empirical results casting doubt on this common, but unproved, assumption. using a state-of-the-art chinese word sense disambiguation model to choose translation candidates for a typical ibm statistical mt system, we find that word sense disambiguation does not yield significantly better translation quality than the statistical machine translation system alone. error analysis suggests several key factors behind this surprising finding, including inherent limitations of current statistical mt architectures.
relating complexity to practical performance in parsing with wide-coverage unification grammars. the paper demonstrates that exponential complexities with respect to grammar size and input length have little impact on the performance of three unification-based parsing algorithms, using a wide-coverage grammar. the results imply that the study and optimisation of unification-based parsing must rely on empirical data until complexity theory can more accurately predict the practical behaviour of such parsers1.
lattice-based word identification in clare. i argue that because of spelling and typing errors and other properties of typed text, the identification of words and word boundaries in general requires syntactic and semantic knowledge. a lattice representation is therefore appropriate for lexical analysis. i show how the use of such a representation in the clare system allows different kinds of hypothesis about word identity to be integrated in a uniform framework. i then describe a quantitative evaluation of clare's performance on a set of sentences into which typographic errors have been introduced. the results show that syntax and semantics can be applied as powerful sources of constraint on the possible corrections for misspelled words.
n semantic classes are harder than two. we show that we can automatically classify semantically related phrases into 10 classes. classification robustness is improved by training with multiple sources of evidence, including within-document cooccurrence, html markup, syntactic relationships in sentences, substitutability in query logs, and string similarity. our work provides a benchmark for automatic n-way classification into wordnet's semantic classes, both on a trec news corpus and on a corpus of substitutable search query phrases.
non-verbal cues for discourse structure. this paper addresses the issue of designing embodied conversational agents that exhibit appropriate posture shifts during dialogues with human users. previous research has noted the importance of hand gestures, eye gaze and head nods in conversations between embodied agents and humans. we present an analysis of human monologues and dialogues that suggests that postural shifts can be predicted as a function of discourse state in monologues, and discourse and conversation state in dialogues. on the basis of these findings, we have implemented an embodied conversational agent that uses collagen in such a way as to generate postural shifts.
computational lexical semantics, incrementality, and the so-called punctuality of events. the distinction between <i>achievements and accomplishments</i> is known to be an empirically important but subtle one. it is argued here to depend on the <i>atomicity</i> (rather than punctuality) of events, and to be strongly related to <i>incrementality</i> (i.e., to event-object mapping functions). a computational treatment of incrementality and atomicity is discussed in the paper, and a number or related empirical problems considered, notably lexical polysemy in verb-argument relationships.
optimization in multimodal interpretation. in a multimodal conversation, the way users communicate with a system depends on the available interaction channels and the situated context (e.g., conversation focus, visual feedback). these dependencies form a rich set of constraints from various perspectives such as temporal alignments between different modalities, coherence of conversation, and the domain semantics. there is strong evidence that competition and ranking of these constraints is important to achieve an optimal interpretation. thus, we have developed an optimization approach for multimodal interpretation, particularly for interpreting multimodal references. a preliminary evaluation indicates the effectiveness of this approach, especially for complex user inputs that involve multiple referring expressions in a speech utterance and multiple gestures.
towards conversational qa: automatic identification of problematic situations and user intent. to enable conversational qa, it is important to examine key issues addressed in conversational systems in the context of question answering. in conversational systems, understanding user intent is critical to the success of interaction. recent studies have also shown that the capability to automatically identify problematic situations during interaction can significantly improve the system performance. therefore, this paper investigates the new implications of user intent and problematic situations in the context of question answering. our studies indicate that, in basic interactive qa, there are different types of user intent that are tied to different kinds of system performance (e.g., problematic/error free situations). once users are motivated to find specific information related to their information goals, the interaction context can provide useful cues for the system to automatically identify problematic situations and user intent.
sense disambiguation using semantic relations and adjacency information. this paper describes a heuristic-based approach to word-sense disambiguation. the heuristics that are applied to disambiguate a word depend on its part of speech, and on its relationship to neighboring salient words in the text. parts of speech are found through a tagger, and related neighboring words are identified by a phrase extractor operating on the tagged text. to suggest possible senses, each heuristic draws on semantic relations extracted from a webster's dictionary and the semantic thesaurus wordnet. for a given word, all applicable heuristics are tried, and those senses that are rejected by all heuristics are discarded. in all, the disambiguator uses 39 heuristics based on 12 relationships.
estimating class priors in domain adaptation for word sense disambiguation. instances of a word drawn from different domains may have different sense priors (the proportions of the different senses of a word). this in turn affects the accuracy of word sense disambiguation (wsd) systems trained and applied on different domains. this paper presents a method to estimate the sense priors of words drawn from a new domain, and highlights the importance of using well calibrated probabilities when performing these estimations. by using well calibrated probabilities, we are able to estimate the sense priors effectively to achieve significant improvements in wsd accuracy.
an alignment method for noisy parallel corpora based on image processing techniques. this paper presents a new approach to bitext correspondence problem (bcp) of noisy bilingual corpora based on image processing (ip) techniques. by using one of several ways of estimating the lexical translation probability (ltp) between pairs of source and target words, we can turn a bitext into a discrete gray-level image. we contend that the bcp, when seen in the light, bears a striking resemblance to the line detection problem in ip. therefore, bcps, including sentence and word alignment, can benefit from a wealth of effective, well established ip techniques, including convolution-based filters, texture analysis and hough transform. this paper describes a new program, plotalign that produces a word-level bitext map for noisy or non-literal bitext, based on these techniques.
a pipeline framework for dependency parsing. pipeline computation, in which a task is decomposed into several stages that are solved sequentially, is a common computational strategy in natural language processing. the key problem of this model is that it results in error accumulation and suffers from its inability to correct mistakes in previous stages. we develop a framework for decisions made via in pipeline models, which addresses these difficulties, and presents and evaluates it in the context of bottom up dependency parsing for english. we show improvements in the accuracy of the inferred trees relative to existing models. interestingly, the proposed algorithm shines especially when evaluated globally, at a sentence level, where our results are significantly better than those of existing approaches.
gpsm: a generalized probabilistic semantic model for ambiguity resolution. in natural language processing, ambiguity resolution is a central issue, and can be regarded as a preference assignment problem. in this paper, a generalized probabilistic semantic model (gpsm) is proposed for preference computation. an effective semantic tagging procedure is proposed for tagging semantic features. a semantic score function is derived based on a score function, which integrates lexical, syntactic and semantic preference under a uniform formulation. the semantic score measure shows substantial improvement in structural disambiguation over a syntax-based approach.
immediate-head parsing for language models. we present two language models based upon an "immediate-head" parser --- our name for a parser that conditions all events below a constituent c upon the head of c. while all of the most accurate statistical parsers are of the immediate-head variety, no previous grammatical language model uses this technology. the perplexity for both of these models significantly improve upon the trigram model base-line as well as the best previous grammar-based language model. for the better of our two models these improvements are 24% and 14% respectively. we also suggest that improvement of the underlying parser should significantly improve the model's perplexity and that even in the near term there is a lot of potential for improvement in immediate-head language models.
a logic for semantic interpretation. we propose that logic (enhanced to encode probability information) is a good way of characterizing semantic interpretation. in support of this we give a fragment of an axiomatization for word-sense disambiguation, nounphrase (and verb) reference, and case disambiguation. we describe an inference engine (frail3) which actually takes this axiomatization and uses it to drive the semantic interpretation process. we claim three benefits from this scheme. first, the interface between semantic interpretation and pragmatics has always been problematic, since all of the above tasks in general require pragmatic inference. now the interface is trival, since both semantic interpretation and pragmatics use the same vocabulary and inference engine. the second benefit, related to the first, is that semantic guidance of syntax is a side effect of the interpretation. the third benefit is the elegance of the semantic interpretation theory. a few simple rules capture a remarkable diversity of semantic phenomena.
coarse-to-fine n-best parsing and maxent discriminative reranking. discriminative reranking is one method for constructing high-performance statistical parsers (collins, 2000). a discriminative reranker requires a source of candidate parses for each sentence. this paper describes a simple yet novel method for constructing sets of 50-best parses based on a coarse-to-fine generative parser (charniak, 2000). this method generates 50-best lists that are of substantially higher quality than previously obtainable. we used these parses as the input to a maxent reranker (johnson et al., 1999; riezler et al., 2002) that selects the best parse from the set of parses for each sentence, obtaining an f-score of 91.0% on sentences of length 100 or less.
word alignment in english-hindi parallel corpus using recency-vector approach: some studies. word alignment using recency-vector based approach has recently become popular. one major advantage of these techniques is that unlike other approaches they perform well even if the size of the parallel corpora is small. this makes these algorithms worth-studying for languages where resources are scarce. in this work we studied the performance of two very popular recency-vector based approaches, proposed in (fung and mckeown, 1994) and (somers, 1998), respectively, for word alignment in english-hindi parallel corpus. but performance of the above algorithms was not found to be satisfactory. however, subsequent addition of some new constraints improved the performance of the recency-vector based alignment technique significantly for the said corpus. the present paper discusses the new version of the algorithm and its performance in detail.
a hybrid convolution tree kernel for semantic role labeling. a hybrid convolution tree kernel is proposed in this paper to effectively model syntactic structures for semantic role labeling (srl). the hybrid kernel consists of two individual convolution kernels: a path kernel, which captures predicate-argument link features, and a constituent structure kernel, which captures the syntactic structure features of arguments. evaluation on the datasets of conll-2005 srl shared task shows that the novel hybrid convolution tree kernel out-performs the previous tree kernels. we also combine our new hybrid tree kernel based method with the standard rich flat feature based method. the experimental results show that the combinational method can get better performance than each of them individually.
a structured language model. the paper presents a language model that develops syntatic structure and uses it to extract meaningful information from the word history, thus enabling the use of long distance dependencies. the model assigns probability to every joint sequence of words-binary-parse-structure with headword annotation. the model, its probabilistic parametrization, and a set of experiments meant to evaluate its predictive power are presented.
position specific posterior lattices for indexing speech. the paper presents the position specific posterior lattice, a novel representation of automatic speech recognition lattices that naturally lends itself to efficient indexing of position information and subsequent relevance ranking of spoken documents using proximity.in experiments performed on a collection of lecture recordings --- mit icampus data --- the spoken document ranking accuracy was improved by 20% relative over the commonly used baseline of indexing the 1-best output from an automatic speech recognizer. the mean average precision (map) increased from 0.53 when using 1-best output to 0.62 when using the new lattice representation. the reference used for evaluation is the output of a standard retrieval engine working on the manual transcription of the speech collection.albeit lossy, the pspl lattice is also much more compact than the asr 3-gram lattice from which it is computed --- which translates in reduced inverted index size as well --- at virtually no degradation in word-error-rate performance. since new paths are introduced in the lattice, the oracle accuracy increases over the original asr lattice.
speech ogle: indexing uncertainty for spoken document search. the paper presents the position specific posterior lattice (pspl), a novel lossy representation of automatic speech recognition lattices that naturally lends itself to efficient indexing and subsequent relevance ranking of spoken documents.in experiments performed on a collection of lecture recordings --- mit icampus data --- the spoken document ranking accuracy was improved by 20% relative over the commonly used baseline of indexing the 1-best output from an automatic speech recognizer.the inverted index built from pspl lattices is compact --- about 20% of the size of 3-gram asr lattices and 3% of the size of the uncompressed speech --- and it allows for extremely fast retrieval. furthermore, little degradation in performance is observed when pruning pspl lattices, resulting in even smaller indexes --- 5% of the size of 3-gram asr lattices.
exploiting syntactic structure for language modeling. the paper presents a language model that develops syntactic structure and uses it to extract meaningful information from the word history, thus enabling the use of long distance dependencies. the model assigns probability to every joint sequence of words-binary-parse-structure with headword annotation and operates in a left-to-right manner --- therefore usable for automatic speech recognition. the model, its probabilistic parameterization, and a set of experiments meant to evaluate its predictive power are presented; an improvement over standard trigram modeling is achieved.
aligning sentences in bilingual corpora using lexical information. in this paper, we describe a fast algorithm for aligning sentences with their translations in a bilingual corpus. existing efficient algorithms ignore word identities and only consider sentence length (brown et al., 1991b; gale and church, 1991). our algorithm constructs a simple statistical word-to-word translation model on the fly during alignment. we find the alignment that maximizes the probability of generating the corpus with this translation model. we have achieved an error rate of approximately 0.4% on canadian hansard data, which is a significant improvement over previous results. the algorithm is language independent.
bayesian grammar induction for language modeling. we describe a corpus-based induction algorithm for probabilistic context-free grammars. the algorithm employs a greedy heuristic search within a bayesian framework, and a post-pass using the inside-outside algorithm. we compare the performance of our algorithm to n-gram models and the inside-outside algorithm in three language modeling tasks. in two of the tasks, the training data is generated by a probabilistic context-free grammar and in both tasks our algorithm outperforms the other techniques. the third task involves naturally-occurring data, and in this task our algorithm does not perform as well as n-gram models but vastly outperforms the inside-outside algorithm.
resolving translation ambiguity and target polysemy in cross-language information retrieval. this paper deals with translation ambiguity and target polysemy problems together. two monolingual balanced corpora are employed to learn word co-occurrence for translation ambiguity resolution, and augmented translation restrictions for target polysemy resolution. experiments show that the model achieves 62.92% of monolingual information retrieval, and is 40.80% addition to the select-all model. combining the target polysemy resolution, the retrieval performance is about 10.11% increase to the model resolving translation ambiguity only.
a high-accurate chinese-english ne backward translation system combining both lexical information and web statistics. named entity translation is indispensable in cross language information retrieval nowadays. we propose an approach of combining lexical information, web statistics, and inverse search based on google to backward translate a chinese named entity (ne) into english. our system achieves a high top-1 accuracy of 87.6%, which is a relatively good performance reported in this area until present.
extracting noun phrases from large-scale texts: a hybrid approach and its automatic evaluation. to acquire noun phrases from running texts is useful for many applications, such as word grouping, terminology indexing, etc. the reported literatures adopt pure probabilistic approach, or pure rule-based noun phrases grammar to tackle this problem. in this paper, we apply a probabilistic chunker to deciding the implicit boundaries of constituents and utilize the linguistic knowledge to extract the noun phrases by a finite state mechanism. the test texts are susanne corpus and the results are evaluated by comparing the parse field of susanne corpus automatically. the results of this preliminary experiment are encouraging.
a concept-based adaptive approach to word sense disambiguation. word sense disambiguation for unrestricted text is one of the most difficult tasks in the fields of computational linguistics. the crux of the problem is to discover a model that relates the intended sense of a word with its context. this paper describes a general framework for adaptive conceptual word sense disambiguation. central to this wsd framework is the sense division and semantic relations based on topical analysis of dictionary sense definitions. the process begins with an initial disambiguation step using an mrd-derived knowledge base. an adaptation step follows to combine the initial knowledge base with knowledge gleaned from the partial disambiguated text. once the knowledge base is adjusted to suit the text at hand, it is then applied to the text again to finalize the disambiguation result. definitions and example sentences from ldoce are employed as training materials for wsd, while passages from the brown corpus and wall street journal are used for testing. we report on several experiments illustrating effectiveness of the adaptive approach.
an empirical study of smoothing techniques for language modeling. we present an extensive empirical comparison of several smoothing techniques in the domain of language modeling, including those described by jelinek and mercer (1980), katz (1987), and church and gale (1991). we investigate for the first time how factors such as training data size, corpus (e.g., brown versus wall street journal), and n-gram order (bigram versus trigram) affect the relative performance of these methods, which we measure through the cross-entropy of test data. in addition, we introduce two novel smoothing techniques, one a variation of jelinek-mercer smoothing and one a very simple linear interpolation technique, both of which outperform existing methods.
proper name translation in cross-language information retrieval. recently, language barrier becomes the major problem for people to search, retrieve, and understand www documents in different languages. this paper deals with query translation issue in cross-language information retrieval, proper names in particular. models for name identification, name translation and name searching are presented. the recall rates and the precision rates for the identification of chinese organization names, person names and location names under met data are (76.67%, 79.33%), (87.33%, 82.33%) and (77.00%, 82.00%), respectively. in name translation, only 0.79% and 1.11% of candidates for english person names and location names, respectively, have to be proposed. the name searching facility is implemented on an mt sever for information retrieval on the www. under this system, user can issue queries and read documents with his familiar language.
relation extraction using label propagation based semi-supervised learning. shortage of manually labeled data is an obstacle to supervised relation extraction methods. in this paper we investigate a graph based semi-supervised learning algorithm, a label propagation (lp) algorithm, for relation extraction. it represents labeled and unlabeled examples and their distances as the nodes and the weights of edges of a graph, and tries to obtain a labeling function to satisfy two constraints: 1) it should be fixed on the labeled nodes, 2) it should be smooth on the whole graph. experiment results on the ace corpus showed that this lp algorithm achieves better performance than svm when only very few labeled examples are available, and it also performs better than bootstrapping for the relation extraction task.
unsupervised relation disambiguation using spectral clustering. this paper presents an unsupervised learning approach to disambiguate various relations between name entities by use of various lexical and syntactic features from the contexts. it works by calculating eigen-vectors of an adjacency graph's laplacian to recover a submanifold of data from a high dimensionality space and then performing cluster number estimation on the eigenvectors. experiment results on ace corpora show that this spectral clustering based approach outperforms the other clustering methods.
a new statistical approach to chinese pinyin input. chinese input is one of the key challenges for chinese pc users. this paper proposes a statistical approach to pinyin-based chinese input. this approach uses a trigram-based language model and a statistically based segmentation. also, to deal with real input, it also includes a typing model which enables spelling correction in sentence-based pinyin input, and a spelling model for english which enables modeless pinyin input.
fast - an automatic generation system for grammar tests. this paper introduces a method for the semi-automatic generation of grammar test items by applying natural language processing (nlp) techniques. based on manually-designed patterns, sentences gathered from the web are transformed into tests on grammaticality. the method involves representing test writing knowledge as test patterns, acquiring authentic sentences on the web, and applying generation strategies to transform sentences into items. at runtime, sentences are converted into two types of toefl-style question: multiple-choice and error detection. we also describe a prototype system fast (free assessment of structural tests). evaluation on a set of generated questions indicates that the proposed method performs satisfactory quality. our methodology provides a promising approach and offers significant potential for computer assisted language learning and assessment.
novel association measures using web search with double checking. a web search with double checking model is proposed to explore the web as a live corpus. five association measures including variants of dice, overlap ratio, jaccard, and cosine, as well as co-occurrence double check (codc), are presented. in the experiments on rubenstein-goodenough's benchmark data set, the codc measure achieves correlation coefficient 0.8492, which competes with the performance (0.8914) of the model using wordnet. the experiments on link detection of named entities using the strategies of direct association, association matrix and scalar association matrix verify that the double-check frequencies are reliable. further study on named entity clustering shows that the five measures are quite useful. in particular, codc measure is very stable on word-word and name-name experiments. the application of codc measure to expand community chains for personal name disambiguation achieves 9.65% and 14.22% increase compared to the system without community expansion. all the experiments illustrate that the novel model of web search with double checking is feasible for mining associations from the web.
chinese verb sense discrimination using an em clustering model with rich linguistic features. this paper discusses the application of the expectation-maximization (em) clustering algorithm to the task of chinese verb sense discrimination. the model utilized rich linguistic features that capture predicate-argument structure information of the target verbs. a semantic taxonomy for chinese nouns, which was built semi-automatically based on two electronic chinese semantic dictionaries, was used to provide semantic features for the model. purity and normalized mutual information were used to evaluate the clustering performance on 12 chinese verbs. the experimental results show that the em clustering model can learn sense or sense group distinctions for most of the verbs successfully. we further enhanced the model with certain fine-grained semantic categories called lexical sets. our results indicate that these lexical sets improve the model's performance for the three most challenging verbs chosen from the first set of experiments.
pat-trees with the deletion function as the learning device for linguistic patterns. in this study, a learning device based on the pat-tree data structures was developed. the original pat-trees were enhanced with the deletion function to emulate human learning competence. the learning process worked as follows. the linguistic patterns from the text corpus are inserted into the pat-tree one by one. since the memory was limited, hopefully, the important and new patterns would be retained in the pat-tree and the old and unimportant patterns would be released from the tree automatically. the proposed pat-trees with the deletion function have the following advantages. 1) they are easy to construct and maintain. 2) any prefix substring and its frequency count through pat-tree can be searched very quickly. 3) the space requirement for a pat-tree is linear with respect to the size of the input text. 4) the insertion of a new element can be carried out at any time without being blocked by the memory constraints because the free space is released through the deletion of unimportant elements.experiments on learning high frequency bigrams were carried out under different memory size constraints. high recall rates were achieved. the results show that the proposed pat-trees can be used as on-line learning devices.
an empirical study of chinese chunking. in this paper, we describe an empirical study of chinese chunking on a corpus, which is extracted from upenn chinese treebank-4 (ctb4). first, we compare the performance of the state-of-the-art machine learning models. then we propose two approaches in order to improve the performance of chinese chunking. 1) we propose an approach to resolve the special problems of chinese chunking. this approach extends the chunk tags for every problem by a tag-extension function. 2) we propose two novel voting methods based on the characteristics of chunking task. compared with traditional voting methods, the proposed voting methods consider long distance information. the experimental results show that the svms model outperforms the other models and that our proposed approaches can improve performance significantly.
reranking answers for definitional qa using language modeling. statistical ranking methods based on centroid vector (profile) extracted from external knowledge have become widely adopted in the top definitional qa systems in trec 2003 and 2004. in these approaches, terms in the centroid vector are treated as a bag of words based on the independent assumption. to relax this assumption, this paper proposes a novel language model-based answer reranking method to improve the existing bag-of-words model approach by considering the dependence of the words in the centroid vector. experiments have been conducted to evaluate the different dependence models. the results on the trec 2003 test set show that the reranking approach with biterm language model, significantly outperforms the one with the bag-of-words model and unigram language model by 14.9% and 12.5% respectively in f-measure(5).
embedding new information into referring expressions. this paper focuses on generating referring expressions capable of serving multiple communicative goals. the components of a referring expression are divided into a referring part and a non-referring part. two rules for the content determination and construction of the non-referring part are given, which are realised in an embedding algorithm. the significant aspect of our approach is that it intends to generate the non-referring part given the restrictions imposed by the referring part, whose realisation is, on the other hand, affected by the non-referring part.
a probability model to improve word alignment. word alignment plays a crucial role in statistical machine translation. word-aligned corpora have been found to be an excellent source of translation-related knowledge. we present a statistical model for computing the probability of an alignment given a sentence pair. this model allows easy integration of context-specific features. our experiments show that this model can be an effective tool for improving an existing word alignment.
soft syntactic constraints for word alignment through discriminative training. word alignment methods can gain valuable guidance by ensuring that their alignments maintain cohesion with respect to the phrases specified by a monolingual dependency tree. however, this hard constraint can also rule out correct alignments, and its utility decreases as alignment models become more complex. we use a publicly available structured output svm to create a max-margin syntactic aligner with a soft cohesion constraint. the resulting aligner is the first, to our knowledge, to use a discriminative learning method to train an itg bitext parser.
statistical parsing with an automatically-extracted tree adjoining grammar. we discuss the advantages of lexicalized tree-adjoining grammar as an alternative to lexicalized pcfg for statistical parsing, describing the induction of a probabilistic ltag model from the penn treebank and evaluating its parsing performance. we find that this induction method is an improvement over the em-based method of (hwa, 1998), and that the induced model yields results comparable to lexicalized pcfg.
constraints on strong generative power. we consider the question "how much strong generative power can be squeezed out of a formal system without increasing its weak generative power?" and propose some theoretical and practical constraints on this problem. we then introduce a formalism which, under these constraints, maximally squeezes strong generative power out of context-free grammar. finally, we generalize this result to formalisms beyond cfg.
a hierarchical phrase-based model for statistical machine translation. we present a statistical phrase-based translation model that uses hierarchical phrases---phrases that contain subphrases. the model is formally a synchronous context-free grammar but is learned from a bitext without any syntactic information. thus it can be seen as a shift to the formal machinery of syntax-based translation systems without any linguistic commitment. in our experiments using bleu as a metric, the hierarchical phrase-based model achieves a relative improvement of 7.5% over pharaoh, a state-of-the-art phrase-based system.
a preference-first language processor integrating the unification grammar and markov language model for speech recognition applications. a language processor is to find out a most promising sentence hypothesis for a given word lattice obtained from acoustic signal recognition. in this paper a new language processor is proposed, in which unification grammar and markov language model are integrated in a word lattice parsing algorithm based on an augmented chart, and the island-driven parsing concept is combined with various preference-first parsing strategies defined by different construction principles and decision rules. test results show that significant improvements in both correct rate of recognition and computation speed can be achieved.
teaching a weaker classifier: named entity recognition on upper case text. this paper describes how a machine-learning named entity recognizer (ner) on upper case text can be improved by using a mixed case ner and some unlabeled text. the mixed case ner can be used to tag some unlabeled mixed case text, which are then used as additional training material for the upper case ner. we show that this approach reduces the performance gap between the mixed case ner and the upper case ner substantially, by 39% for muc-6 and 22% for muc-7 named entity test data. our method is thus useful in improving the accuracy of ners on upper case text, such as transcribed text from automatic speech recognizers where case information is missing.
closing the gap: learning-based information extraction rivaling knowledge-engineering methods. in this paper, we present a learning approach to the scenario template task of information extraction, where information filling one template could come from multiple sentences. when tested on the muc-4 task, our learning approach achieves accuracy competitive to the best of the muc-4 systems, which were all built with manually engineered rules. our analysis reveals that our use of full parsing and state-of-the-art learning algorithms have contributed to the good performance. to our knowledge, this is the first research to have demonstrated that a learning approach to the full-scale information extraction task could achieve performance rivaling that of the knowledge engineering approach.
an account for compound prepositions in farsi. there are some sorts of 'preposition + noun' combinations in farsi that apparently a prepositional phrase almost behaves as compound prepositions. as they are not completely behaving as compounds, it is doubtful that the process of word formation is a morphological one. the analysis put forward by this paper proposes "incorporation" by which an n&deg; is incorporated to a p&deg; constructing a compound preposition. in this way tagging prepositions and parsing texts in natural language processing is defined in a proper manner.
extracting semantic hierarchies from a large on-line dictionary. dictionaries are rich sources of detailed semantic information, but in order to use the information for natural language processing, it must be organized systematically. this paper describes automatic and semi-automatic procedures for extracting and organizing semantic feature information implicit in dictionary definitions. two head-finding heuristics are described for locating the genus terms in noun and verb definitions. the assumption is that the genus term represents inherent features of the word it defines. the two heuristics have been used to process definitions of 40,000 nouns and 8,000 verbs, producing indexes in which each genus term is associated with the words it defined. the sprout program interactively grows a taxonomic "tree" from any specified root feature by consulting the genus index. its output is a tree in which all of the nodes have the root feature for at least one of their senses. the filter program uses an inverted form of the genus index. filtering begins with an initial filter file consisting of words that have a given feature (e.g. [+human]) in all of their senses. the program then locates, in the index, words whose genus terms all appear in the filter file. the output is a list of new words that have the given feature in all of their senses.
a flexible distributed architecture for nlp system development and use. we describe a distributed, modular architecture for platform independent natural language systems. it features automatic interface generation and self-organization. adaptive (and non-adaptive) voting mechanisms are used for integrating discrete modules. the architecture is suitable for rapid prototyping and product delivery.
analysis system of speech acts and discourse structures using maximum entropy model. we propose a statistical dialogue analysis model to determine discourse structures as well as speech acts using maximum entropy model. the model can automatically acquire probabilistic discourse knowledge from a discourse tagged corpus to resolve ambiguities. we propose the idea of tagging discourse segment boundaries to represent the structural information of discourse. using this representation we can effectively combine speech act analysis and discourse structure analysis in one framework.
hybrid approaches to improvement of translation quality in web-based english-korean machine translation. the previous english-korean mt system that was the transfer-based mt system and applied to only written text enumerated a following brief list of the problems that had not seemed to be easy to solve in the near future: 1) processing of non-continuous idiomatic expressions 2) reduction of too many ambiguities in english syntactic analysis 3) robust processing for failed or illformed sentences 4) selecting correct word correspondence between several alternatives 5) generation of korean sentence style. the problems can be considered as factors that have influence on the translation quality of machine translation system. this paper describes the symbolic and statistical hybrid approaches to solutions of problems of the previous english-to-korean machine translation system in terms of the improvement of translation quality. the solutions are now successfully applied to the web-based english-korean machine translation system "fromto/ek" which has been developed from 1997.
techniques to incorporate the benefits of a hierarchy in a modified hidden markov model. this paper explores techniques to take advantage of the fundamental difference in structure between hidden markov models (hmm) and hierarchical hidden markov models (hhmm). the hhmm structure allows repeated parts of the model to be merged together. a merged model takes advantage of the recurring patterns within the hierarchy, and the clusters that exist in some sequences of observations, in order to increase the extraction accuracy. this paper also presents a new technique for reconstructing grammar rules automatically. this work builds on the idea of combining a phrase extraction method with hhmm to expose patterns within english text. the reconstruction is then used to simplify the complex structure of an hhmm the models discussed here are evaluated by applying them to natural language tasks based on conll-2004 and a sub-corpus of the lancaster treebank
analysis and synthesis of the distribution of consonants over languages: a complex network approach. cross-linguistic similarities are reflected by the speech sound systems of languages all over the world. in this work we try to model such similarities observed in the consonant inventories, through a complex bipartite network. we present a systematic study of some of the appealing features of these inventories with the help of the bipartite network. an important observation is that the occurrence of consonants follows a two regime power law distribution. we find that the consonant inventory size distribution together with the principle of preferential attachment are the main reasons behind the emergence of such a two regime behavior. in order to further support our explanation we present a synthesis model for this network based on the general theory of preferential attachment.
using machine-learning to assign function labels to parser output for spanish. data-driven grammatical function tag assignment has been studied for english using the penn-ii treebank data. in this paper we address the question of whether such methods can be applied successfully to other languages and treebank resources. in addition to tag assignment accuracy and f-scores we also present results of a task-based evaluation. we use three machine-learning methods to assign cast3lb function tags to sentences parsed with bikel's parser trained on the cast3lb treebank. the best performing method, svm, achieves an f-score of 86.87% on gold-standard trees and 66.67% on parser output - a statistically significant improvement of 6.74% over the baseline. in a task-based evaluation we generate lfg functional-structures from the function-tag-enriched trees. on this task we achive an f-score of 75.67%, a statistically significant 3.4% improvement over the baseline.
tracking initiative in collaborative dialogue interactions. in this paper, we argue for the need to distinguish between task and dialogue initiatives, and present a model for tracking shifts in both types of initiatives in dialogue interactions. our model predicts the initiative holders in the next dialogue turn based on the current initiative holders and the effect that observed cues have on changing them. our evaluation across various corpora shows that the use of cues consistently improves the accuracy in the system's prediction of task and dialogue initiative holders by 2-4 and 8-13 percentage points, respectively, thus illustrating the generality of our model.
response generation in collaborative negotiation. in collaborative planning activities, since the agents are autonomous and heterogenous, it is inevitable that conflicts arise in their beliefs during the planning process. in cases where such conflicts are relevant to the task at hand, the agents should engage in collaborative negotiation as an attempt to square away the discrepancies in their beliefs. this paper presents a computational strategy for detecting conflicts regarding proposed beliefs and for engaging in collaborative negotiation to resolve the conflicts that warrant resolution. our model is capable of selecting the most effective aspect to address in its pursuit of conflict resolution in cases where multiple conflicts arise, and of selecting appropriate evidence to justify the need for such modification. furthermore, by capturing the negotiation process in a recursive propose-evaluate-modify cycle of actions, our model can successfully handle embedded negotiation subdialogues.
dialogue management in vector-based call routing. this paper describes a domain independent, automatically trained call router which directs customer calls based on their response to an open-ended "how may i direct your call?" query. routing behavior is trained from a corpus of transcribed and hand-routed calls and then carried out using vector-based information retrieval techniques. based on the statistical discriminating power of the n-gram terms extracted from the caller's request, the caller is 1) routed to the appropriate destination, 2) transferred to a human operator, or 3) asked a disambiguation question. in the last case, the system dynamically generates queries tailored to the caller's request and the destinations with which it is consistent. our approach is domain independent and the training process is fully automatic. evaluations over a financial services call center handling hundreds of activities with dozens of destinations demonstrate a substantial improvement on existing systems by correctly routing 93.8% of the calls after punting 10.2% of the calls to a human operator.
constraint-based sentence compression: an integer programming approach. the ability to compress sentences while preserving their grammaticality and most of their meaning has recently received much attention. our work views sentence compression as an optimisation problem. we develop an integer programming formulation and infer globally optimal compressions in the face of linguistically motivated constraints. we show that such a formulation allows for relatively simple and knowledge-lean compression models that do not require parallel corpora or large-scale resources. the proposed approach yields results comparable and in some cases superior to state-of-the-art.
developing a flexible spoken dialog system using simulation. in this paper, we describe a new methodology to develop mixed-initiative spoken dialog systems, which is based on the extensive use of simulations to accelerate the development process. with the help of simulations, a system providing information about a database of nearly 1000 restaurants in the boston area has been developed. the simulator can produce thousands of unique dialogs which benefit not only dialog development but also provide data to train the speech recognizer and understanding components, in preparation for real user interactions. also described is a strategy for creating cooperative responses to user queries, incorporating an intelligent language generation capability that produces content-dependent verbal descriptions of listed items.
generating parallel multilingual lfg-tag grammars from a metagrammar. we introduce a metagrammar, which allows us to automatically generate, from a single and compact metagrammar hierarchy, parallel lexical functional grammars (lfg) and tree-adjoining grammars (tag) for french and for english: the grammar writer specifies in compact manner syntactic properties that are potentially framework-, and to some extent language-independent (such as subcategorization, valency alternations and realization of syntactic functions), from which grammars for several frameworks and languages are automatically generated offline.
on parsing strategies and closure. this paper proposes a welcom hypothesis: a computationally simple deviceis sufficient for processing natural language. traditionally it has been argued that processing natural language syntax requires very powerful machinery. many engineers have come to this rather grim conclusion; almost all working parsers are actually turing machines (tm). for example, woods believed that a parser should have tm complexity and specifically designed his augmented transition networks (atns) to be turing equivalent.(1) "it is well known (cf. [chomsky64]) that the strict context-free grammar model is not an adequate mechanism for characterizing the subtleties of natural languages." [woods70]if the problem is really as hard as it appears, then the only solution is to grin and bear it. our own position is that parsing acceptable sentences is simpler because there are constraints on human performance that drastically reduce the computational complexity. although woods correctly observes that <u>competence</u> models are very complex, this observation may not apply directly to a <u>performance</u> problem such as parsing.the claim is that performance limitations actually <u>reduce</u> parsing complexity. this suggests two interesting questions: (a) how is the performance model constrained so as to reduce its complexity, and (b) how can the constrained performance model naturally approximate competence idealizations?
stress assignment in letter to sound rules for speech synthesis. this paper will discuss how to determine word stress from spelling. stress assignment is a well-established weak point for many speech synthesizers because stress dependencies cannot be determined locally. it is impossible to determine the stress of a word by looking through a five or six character window, as many speech synthesizers do. well-known examples such as degr&aacute;de / d&egrave;grad&aacute;tion and t&eacute;legraph / tel&eacute;graphy demonstrate that stress dependencies can span over two and three syllables. this paper will present a principled framework for dealing with these long distance dependencies. stress assignment will be formulated in terms of waltz' style constraint propagation with four sources of constraints: (1) syllable weight, (2) part of speech, (3) morphology and (4) etymology. syllable weight is perhaps the most interesting, and will be the main focus of this paper. most of what follows has been implemented.
char_align: a program for aligning parallel texts at the character level. there have been a number of recent papers on aligning parallel texts at the sentence level, e.g., brown et al (1991), gale and church (to appear), isabelle (1992), kay and r&ouml;senschein (to appear), simard et al (1992), warwick-armstrong and russell (1990). on clean inputs, such as the canadian hansards, these methods have been very successful (at least 96% correct by sentence). unfortunately, if the input is noisy (due to ocr and/or unknown markup conventions), then these methods tend to break down because the noise can make it difficult to find paragraph boundaries, let alone sentences. this paper describes a new program, char_align, that aligns texts at the character level rather than at the sentence/paragraph level, based on the cognate approach proposed by simard et al.
word association norms, mutual information and lexicography. the term word association is used in a very particular sense in the psycholinguistic literature. (generally speaking, subjects respond quicker than normal to the word "nurse" if it follows a highly associated word such as "doctor.") we will extend the term to provide the basis for a statistical description of a variety of interesting linguistic phenomena, ranging from semantic relations of the doctor/nurse type (content word/content word) to lexico-syntactic co-occurrence constraints between verbs and prepositions (content word/function word). this paper will propose a new objective measure based on the information theoretic notion of mutual information, for estimating word association norms from computer readable corpora. (the standard method of obtaining word association norms, testing a few thousand subjects on a few hundred words, is both costly and unreliable.) the proposed measure, the association ratio, estimates word association norms directly from computer readable corpora, making it possible to estimate norms for tens of thousands of words.
partially specified signatures: a vehicle for grammar modularity. this work provides the essential foundations for modular construction of (typed) unification grammars for natural languages. much of the information in such grammars is encoded in the signature, and hence the key is facilitating a modularized development of type signatures. we introduce a definition of signature modules and show how two modules combine. our definitions are motivated by the actual needs of grammar developers obtained through a careful examination of large scale grammars. we show that our definitions meet these needs by conforming to a detailed set of desiderata.
the wild thing. suppose you are on a mobile device with no keyboard (e.g., a cell or pda). how can you enter text quickly? t9? graffiti? this demo will show how language modeling can be used to speed up data entry, both in the mobile context, as well as the desk-top. the wild thing encourages users to use wildcards (*). a language model finds the k-best expansions. users quickly figure out when they can get away with wildcards. general purpose trigram language models are effective for the general case (unrestricted text), but there are important special cases like searching over popular web queries, where more restricted language models are even more effective.
natural language input to a computer-based glaucoma consultation system. a "front end" for a computer-based glaucoma consultation system is described. the system views a case as a description of a particular instance of a class of concepts called "structured objects" and builds up a representation of the instance from the sentences in the case. the information required by the consultation system is then extracted and passed on to the consultation system in the appropriately coded form. a core of syntactic, semantic and contextual rules which are applicable to all structured objects is being developed together with a representation of the structured object glaucoma-patient. there is also a facility for adding domain dependent syntax, abbreviations and defaults.
speech acts and rationality. this paper derives the basis of a theory of communication from a formal theory of rational interaction. the major result is a demonstration that illocutionary acts need not be primitive, and need not be recognized. as a test case. we derive searle's conditions on requesting from principles of rationality coupled with a gricean theory of imperatives. the theory is shown to distinguish insincere or nonserious imperatives from true requests. extensions to indirect speech acts, and ramifications for natural language systems are also briefly discussed.
memory-based learning of morphology with stochastic transducers. this paper discusses the supervised learning of morphology using stochastic transducers, trained using the expectation-maximization (em) algorithm. two approaches are presented: first, using the transducers directly to model the process, and secondly using them to define a similarity measure, related to the fisher kernel method (jaakkola and haussler, 1998), and then using a memory-based learning (mbl) technique. these are evaluated and compared on data sets from english, german, slovene and arabic.
performatives in a rationally based speech act theory. a crucially important adequacy test of any theory of speech acts is its ability to handle performatives. this paper provides a theory of performatives as a test case for our rationally based theory of illocutionary acts. we show why "i request you..." is a request, and "i lie to you that p" is self-defeating. the analysis supports and extends earlier work of theorists such as bach and harnish [1] and takes issue with recent claims by searle [10] that such performative-as-declarative analyses are doomed to failure.
parsing the wsj using ccg and log-linear models. this paper describes and evaluates log-linear parsing models for combinatory categorial grammar (ccg). a parallel implementation of the l-bfgs optimisation algorithm is described, which runs on a beowulf cluster allowing the complete penn treebank to be used for estimation. we also develop a new efficient parsing algorithm for ccg which maximises expected recall of dependencies. we compare models which use all ccg derivations, including non-standard derivations, with normal-form models. the performances of the two models are comparable and the results are competitive with existing wide-coverage ccg parsers.
scaling conditional random fields using error-correcting codes. conditional random fields (crfs) have been applied with considerable success to a number of natural language processing tasks. however, these tasks have mostly involved very small label sets. when deployed on tasks with larger label sets, the requirements for computational resources mean that training becomes intractable.this paper describes a method for training crfs on such tasks, using error correcting output codes (ecoc). a number of crfs are independently trained on the separate binary labelling tasks of distinguishing between a subset of the labels and its complement. during decoding, these models are combined to produce a predicted label sequence which is resilient to errors by individual models.error-correcting crf training is much less resource intensive and has a much faster training time than a standardly formulated crf, while decoding performance remains quite comparable. this allows us to scale crfs to previously impossible tasks, as demonstrated by our experiments with large label sets.
machine translation versus dictionary term translation - a comparison for english-japanese news article alignment. bilingual news article alignment methods based on multi-lingual information retrieval have been shown to be successful for the automatic production of so-called noisy-parallel corpora. in this paper we compare the use of machine translation (mt) to the commonly used dictionary term lookup (dtl) method for reuter news article alignment in english and japanese. the results show the trade-off between improved lexical disambiguation provided by machine translation and extended synonym choice provided by dictionary term lookup and indicate that mt is superior to dtl only at medium and low recall levels. at high recall levels dtl has superior precision.
models for sentence compression: a comparison across domains, training requirements and evaluation measures. sentence compression is the task of producing a summary at the sentence level. this paper focuses on three aspects of this task which have not received detailed treatment in the literature: training requirements, scalability, and automatic evaluation. we provide a novel comparison between a supervised constituent-based and an weakly supervised word-based compression algorithm and examine how these models port to different domains (written vs. spoken text). to achieve this, a human-authored compression corpus has been created and our study highlights potential problems with the automatically gathered compression corpora currently used. finally, we assess whether automatic evaluation measures can be used to determine compression quality.
the distributional inclusion hypotheses and lexical entailment. this paper suggests refinements for the distributional similarity hypothesis. our proposed hypotheses relate the distributional behavior of pairs of words to lexical entailment -- a tighter notion of semantic similarity that is required by many nlp applications. to automatically explore the validity of the defined hypotheses we developed an inclusion testing algorithm for characteristic features of two words, which incorporates corpus and web-based feature sampling to overcome data sparseness. the degree of hypotheses validity was then empirically tested and manually analyzed with respect to the word sense level. in addition, the above testing algorithm was exploited to improve lexical entailment acquisition.
an experiment in hybrid dictionary and statistical sentence alignment. the task of aligning sentences in parallel corpora of two languages has been well studied using pure statistical or linguistic models. we developed a linguistic method based on lexical matching with a bilingual dictionary and two statistical methods based on sentence length ratios and sentence offset probabilities. this paper seeks to further our knowledge of the alignment task by comparing the performance of the alignment models when used separately and together, i.e. as a hybrid system. our results show that for our english-japanese corpus of newspaper articles, the hybrid system using lexical matching and sentence length ratios outperforms the pure methods.
ranking algorithms for named entity extraction: boosting and the voted perceptron. this paper describes algorithms which rerank the top n hypotheses from a maximum-entropy tagger, the application being the recovery of named-entity boundaries in a corpus of web data. the first approach uses a boosting algorithm for ranking problems. the second approach uses the voted perceptron algorithm. both algorithms give comparable, significant improvements over the maximum-entropy baseline. the voted perceptron algorithm can be considerably more efficient to train, at some cost in computation on test examples.
a new statistical parser based on bigram lexical dependencies. this paper describes a new statistical parser which is based on probabilities of dependencies between head-words in the parse tree. standard bigram probability estimation techniques are extended to calculate probabilities of dependencies between pairs of words. tests using wall street journal data show that the method performs at least as well as spatter (magerman 95; jelinek et al. 94), which has the best published results for a statistical parser on this task. the simplicity of the approach means the model trains on 40,000 sentences in under 15 minutes. with a beam search strategy parsing speed can be improved to over 200 sentences a minute with negligible loss in accuracy.
three generative, lexicalised models for statistical parsing. in this paper we first propose a new statistical parsing model, which is a generative model of lexicalised context-free grammar. we then extend the model to include a probabilistic treatment of both subcategorisation and wh-movement. results on wall street journal text show that the parser performs at 88.1/87.5% constituent precision/recall, an average improvement of 2.3% over (collins 96).
head-driven parsing for word lattices. we present the first application of the head-driven statistical parsing model of collins (1999) as a simultaneous language model and parser for large-vocabulary speech recognition. the model is adapted to an online left to right chart-parser for word lattices, integrating acoustic, n-gram, and parser probabilities. the parser uses structural and lexical dependencies not considered by n-gram models, conditioning recognition on more linguistically-grounded relationships. experiments on the wall street journal treebank and lattice corpora show word error rates competitive with the standard n-gram language model while extracting additional structural information useful for speech understanding.
new ranking algorithms for parsing and tagging: kernels over discrete structures, and the voted perceptron. this paper introduces new learning algorithms for natural language processing based on the perceptron algorithm. we show how the algorithms can be efficiently applied to exponential sized representations of parse trees, such as the "all subtrees" (dop) representation described by (bod 1998), or a representation tracking all sub-fragments of a tagged sentence. we give experimental results showing significant improvements on two tasks: parsing wall street journal text, and named-entity extraction from web data.
clause restructuring for statistical machine translation. we describe a method for incorporating syntactic information in statistical machine translation systems. the first step of the method is to parse the source language string that is being translated. the second step is to apply a series of transformations to the parse tree, effectively reordering the surface string on the source language side of the translation system. the goal of this step is to recover an underlying word order that is closer to the target language word-order than the original string. the reordering approach is applied as a pre-processing step in both the training and decoding phases of a phrase-based statistical mt system. we describe experiments on translation from german to english, showing an improvement from 25.2% bleu score for a baseline system to 26.8% bleu score for the system with reordering, a statistically significant improvement.
incremental parsing with the perceptron algorithm. this paper describes an incremental parsing approach where parameters are estimated using a variant of the perceptron algorithm. a beam-search algorithm is used during both training and decoding phases of the method. the perceptron approach was implemented with the same feature set as that of an existing generative model (roark, 2001a), and experimental results show that it gives competitive performance to the generative model on parsing the penn treebank. we demonstrate that training a perceptron model to combine with the generative model during search provides a 2.1 percent f-measure improvement over the generative model alone, to 88.8 percent.
discriminative syntactic language modeling for speech recognition. we describe a method for discriminative training of a language model that makes use of syntactic features. we follow a reranking approach, where a baseline recogniser is used to produce 1000-best output for each acoustic input, and a second "reranking" model is then used to choose an utterance from these 1000-best lists. the reranking model makes use of syntactic features together with a parameter estimation method that is based on the perception algorithm. we describe experiments on the switchboard speech recognition task. the syntactic features provide an additional 0.3% reduction in test-set error rate beyond the model of (roark et al., 2004a; roark et al., 2004b) (significant at p < 0.001), which makes use of a discriminatively trained n-gram model, giving a total reduction of 1.2% over the baseline switchboard system.
measuring conformity to discourse routines in decision-making interactions. in an effort to develop measures of discourse level management strategies, this study examines a measure of the degree to which decision-making interactions consist of sequences of utterance functions that are linked in a decision-making routine. the measure is applied to 100 dyadic interactions elicited in both face-to-face and computer-mediated environments with systematic variation of task complexity and message-window size. every utterance in the interactions is coded according to a system that identifies decision-making functions and other routine functions of utterances. markov analyses of the coded utterances make it possible to measure the relative frequencies with which sequences of 2 and 3 utterances trace a path in a markov model of the decision routine. these proportions suggest that interactions in all conditions adhere to the model, although we find greater conformity in the computer-mediated environments, which is probably due to increased processing and attentional demands for greater efficiency. the results suggest that measures based on markov analyses of coded interactions can provide useful measures for comparing discourse level properties, for correlating discourse features with other textual features, and for analyses of discourse management strategies.
topic-focused multi-document summarization using an approximate oracle score. we consider the problem of producing a multi-document summary given a collection of documents. since most successful methods of multi-document summarization are still largely extractive, in this paper, we explore just how well an extractive method can perform. we introduce an "oracle" score, based on the probability distribution of unigrams in human summaries. we then demonstrate that with the oracle score, we can generate extracts which score, on average, better than the human summaries, when evaluated with rouge. in addition, we introduce an approximation to the oracle score which produces a system with the best known performance for the 2005 document understanding conference (duc) evaluation.
integrating symbolic and statistical representations: the lexicon pragmatics interface. we describe a formal framework for interpretation of words and compounds in a discourse context which integrates a symbolic lexicon/grammar, word-sense probabilities, and a pragmatic component. the approach is motivated by the need to handle productive word use. in this paper, we concentrate on compound nominals. we discuss the inadequacies of approaches which consider compund interpretation as either wholly lexico-grammatical or wholly pragmatic, and provide an alternative integrated account.
an algebra for semantic construction in constraint-based grammars. we develop a framework for formalizing semantic construction within grammars expressed in typed feature structure logics, including hpsg. the approach provides an alternative to the lambda calculus; it maintains much of the desirable flexibility of unification-based approaches to composition, while constraining the allowable operations in order to capture basic generalizations and improve maintainability.
a pylonic decision-tree language model- with optimal question selection. this paper discusses a decision-tree approach to the problem of assigning probabilities to words following a given text. in contrast with previous decision-tree language model attempts, an algorithm for selecting nearly optimal questions is considered. the model is to be tested on a standard task, <i>the wall street journal</i>, allowing a fair comparison with the well-known trigram model.
using parsed corpora for structural disambiguation in the trains domain. this paper describes a prototype disambiguation module, kankei, which was tested on two corpora of the trains project. in ambiguous verb phrases of form v ... np pp or v ... np adverb(s), the two corpora have very different pp and adverb attachment patterns; in the first, the correct attachment is to the vp 88.7% of the time, while in the second, the correct attachment is to the np 73.5% of the time. kankei uses various n-gram patterns of the phrase heads around these ambiguities, and assigns parse trees (with these ambiguities) a score based on a linear combination of the frequencies with which these patterns appear with np and vp attachments in the trains corpora. unlike previous statistical disambiguation systems, this technique thus combines evidence from bigrams, trigrams, and the 4-gram around an ambiguous attachment. in the current experiments, equal weights are used for simplicity but results are still good on the trains corpora (92.2% and 92.4% accuracy). despite the large statistical differences in attachment preferences in the two corpora, training on the first corpus and testing on the second gives an accuracy of 90.9%.
a syntactic framework for speech repairs and other disruptions. this paper presents a grammatical and processing framework for handling the repairs, hesitations, and other interruptions in natural human dialog. the proposed framework has proved adequate for a collection of human-human task-oriented dialogs, both in a full manual examination of the corpus, and in tests with a parser capable of parsing some of that corpus. this parser can also correct a pre-parser speech repair identifier resulting in a 4.8% increase in recall.
on determining the consistency of partial descriptions of trees. we examine the consistency problem for descriptions of trees based on remote dominance, and present a consistency-checking algorithm which is polynomial in the number of nodes in the description, despite disjunctions inherent in the theory of trees. the resulting algorithm allows for descriptions which go beyond sets of atomic formulas to allow certain types of disjunction and negation.
less is more: eliminating index terms from subordinate clauses. we perform a linguistic analysis of documents during indexing for information retrieval. by eliminating index terms that occur only in subordinate clauses, index size is reduced by approximately 30% without adversely affecting precision or recall. these results hold for two corpora: a sample of the world wide web and an electronic encyclopedia.
a machine learning approach to the automatic evaluation of machine translation. we present a machine learning approach to evaluating the well-formedness of output of a machine translation system, using classifiers that learn to distinguish human reference translations from machine translations. this approach can be used to evaluate an mt system, tracking improvements over time; to aid in the kind of failure analysis that can help guide system development; and to select among alternative output strings. the method presented is fully automated and independent of source language, target language and domain.
using wordnet to automatically deduce relations between words in noun-noun compounds. we present an algorithm for automatically disambiguating noun-noun compounds by deducing the correct semantic relation between their constituent words. this algorithm uses a corpus of 2,500 compounds annotated with wordnet senses and covering 139 different semantic relations (we make this corpus available online for researchers interested in the semantics of noun-noun compounds). the algorithm takes as input the wordnet senses for the nouns in a compound, finds all parent senses (hypernyms) of those senses, and searches the corpus for other compounds containing any pair of those senses. the relation with the highest proportional co-occurrence with any sense pair is returned as the correct relation for the compound. this algorithm was tested using a 'leave-one-out' procedure on the corpus of compounds. the algorithm identified the correct relations for compounds with high precision: in 92% of cases where a relation was found with a proportional co-occurrence of 1.0, it was the correct relation for the compound being disambiguated.
alignment of multiple languages for historical comparison. an essential step in comparative reconstruction is to align corresponding phonological segments in the words being compared. to do this, one must search among huge numbers of potential alignments to find those that give a good phonetic fit. this is a hard computational problem, and it becomes exponentially more difficult when more than two strings are being aligned. in this paper i extend the guided-search alignment algorithm of covington (computational linguistics, 1996) to handle more than two strings. the resulting algorithm has been implemented in prolog and gives reasonable results when tested on data from several languages.
reference to locations. we propose a semantics for locative expressions such as near jones or west of denver, an important subsystem for nlp applications. locative expressions denote regions of space, and serve as arguments to predicates, locating objects and events spatially. since simple locatives occupy argument positions, they do not participate in scope ambiguities---pace one common view, which sees locatives as logical operators. our proposal justifies common representational practice in computational linguistics, accounting for how locative expressions function anaphorically, and explaining a wide range of inference involving locatives. we further demonstrate how the argument analysis may accommodate multiple locative arguments in a single predicate. the analysis is implemented for use in a database query application.
a computational semantics for natural language. in the new head-driven phrase structure grammar (hpsg) language processing system that is currently under development at hewlett-packard laboratories, the montagovian semantics of the earlier gpsg system (see [gawron et al. 1982]) is replaced by a radically different approach with a number of distinct advantages. in place of the lambda calculus and standard first-order logic, our medium of conceptual representation is a new logical formalism called nflt (neo-fregean language of thought); compositional semantics is effected, not by schematic lambda expressions, but by lisp procedures that operate on nflt expressions to produce new expressions. nflt has a number of features that make it well-suited for natural language translations, including predicates of variable arity in which explicitly marked situational roles supercede order-coded argument positions, sortally restricted quantification, a compositional (but nonextensional) semantics that handles causal contexts, and a principled conceptual raising mechanism that we expect to lead to a computationally tractable account of propositional attitudes. the use of semantically compositional lisp procedures in place of lambda-schemas allows us to produce fully reduced translations on the fly, with no need for post-processing. this approach should simplify the task of using semantic information (such as sortal incompatibilities) to eliminate bad parse paths.
automatically extracting nominal mentions of events with a bootstrapped probabilistic classifier. most approaches to event extraction focus on mentions anchored in verbs. however, many mentions of events surface as noun phrases. detecting them can increase the recall of event extraction and provide the foundation for detecting relations between events. this paper describes a weakly-supervised method for detecting nominal event mentions that combines techniques from word sense disambiguation (wsd) and lexical acquisition to create a classifier that labels noun phrases as denoting events or non-events. the classifier uses boot-strapped probabilistic generative models of the contexts of events and non-events. the contexts are the lexically-anchored semantic dependency relations that the nps appear in. our method dramatically improves with bootstrapping, and comfortably outperforms lexical lookup methods which are based on very much larger hand-crafted resources.
unsupervised segmentation of words using prior distributions of morph length and frequency. we present a language-independent and unsupervised algorithm for the segmentation of words into morphs. the algorithm is based on a new generative probabilistic model, which makes use of relevant prior information on the length and frequency distributions of morphs in a language. our algorithm is shown to outperform two competing algorithms, when evaluated on data from a language with agglutinative morphology (finnish), and to perform well also on english data.
veins theory: a model of global discourse cohesion and coherence. in this paper, we propose a generalization of centering theory (ct) (grosz, joshi, weinstein (1995)) called veins theory (vt), which extends the applicability of centering rules from local to global discourse. a key facet of the theory involves the identification of &laquo;veins&raquo; over discourse structure trees such as those defined in rst, which delimit domains of referential accessibility for each unit in a discourse. once identified, reference chains can be extended across segment boundaries, thus enabling the application of ct over the entire discourse. we describe the processes by which veins are defined over discourse structure trees and how ct can be applied to global discourse by using these chains. we also define a discourse &laquo;smoothness&raquo; index which can be used to compare different discourse structures and interpretations, and show how vt can be used to abstract a span of text in the context of the whole discourse. finally, we validate our theory by analyzing examples from corpora of english, french, and romanian.
expectations in incremental discourse processing. the way in which discourse features express connections back to the previous discourse has been described in the literature in terms of adjoining at the right frontier of discourse structure. but this does not allow for discourse features that express expectations about what is to come in the subsequent discourse. after characterizing these expectations and their distribution in text, we show how an approach that makes use of substitution as well as adjoining on a suitably defined right frontier, can be used to both process expectations and constrain discouse processing in general.
sub-sentential alignment using substring co-occurrence counts. in this paper, we will present an efficient method to compute the co-occurrence counts of any pair of substring in a parallel corpus, and an algorithm that make use of these counts to create sub-sentential alignments on such a corpus. this algorithm has the advantage of being as general as possible regarding the segmentation of text.
constraint-based event recognition for information extraction. we present a program for segmenting texts according to the separate events they describe. a modular architecture is described that allows us to examine the contributions made by particular aspects of natural language to event structuring. this is applied in the context of terrorist news articles, and a technique is suggested for evaluating the resulting segmentations. we also examine the usefulness of various heuristics in forming these segmentations.
an integrated archictecture for shallow and deep processing. we present an architecture for the integration of shallow and deep nlp components which is aimed at flexible combination of different language technologies for a range of practical current and future applications. in particular, we describe the integration of a high-level hpsg parsing system with different high-performance shallow components, ranging from named entity recognition to chunk parsing and shallow clause recognition. the nlp components enrich a representation of natural language text with layers of new xml meta-information using a single shared data structure, called the text chart. we describe details of the integration methods, and show how information extraction and language checking applications for realworld german text benefit from a deep grammatical analysis.
automatic semantic tagging of unknown proper names. implemented methods for proper names recognition rely on large gazetteers of common proper nouns and a set of heuristic rules (e.g. mr. as an indicator of a person entity type). though the performance of current pn recognizers is very high (over 90%), it is important to note that this problem is by no means a "solved problem". existing systems perform extremely well on newswire corpora by virtue of the availability of large gazetteers and rule bases designed for specific tasks (e.g. recognition of organization and person entity types as specified in recent message understanding conferences muc).however, large gazetteers are not available for most languages and applications other than newswire texts and, in any case, proper nouns are an open class.in this paper we describe a context-based method to assign an entity type to unknown proper names (pns). like many others, our system relies on a gazetteer and a set of context-dependent heuristics to classify proper nouns. however, due to the unavailability of large gazetteers in italian, over 20% detected pns cannot be semantically tagged.the algorithm that we propose assigns an entity type to an unknown pn based on the analysis of syntactically and semantically similar contexts already seen in the application corpus.the performance of the algorithm is evaluated not only in terms of precision, following the tradition of muc conferences, but also in terms of information gain, an information theoretic measure that takes into account the complexity of the classification task.
language independent, minimally supervised induction of lexical probabilities. a central problem in part-of-speech tagging, especially for new languages for which limited annotated resources are available, is estimating the distribution of lexical probabilities for unknown words. this paper introduces a new paradigmatic similarity measure and presents a minimally supervised learning approach combining effective selection and weighting methods based on paradigmatic and contextual similarity measures populated from large quantities of inexpensive raw text data. this approach is highly language independent and requires no modification to the algorithm or implementation to shift between languages such as french and english.
dependency tree kernels for relation extraction. we extend previous work on tree kernels to estimate the similarity between the dependency trees of sentences. using this kernel within a support vector machine, we detect and classify relations between entities in the automatic content extraction (ace) corpus of news articles. we examine the utility of different features such as wordnet hypernyms, parts of speech, and entity types, and find that the dependency tree kernel achieves a 20% f1 improvement over a "bag-of-words" kernel.
supersense tagging of unknown nouns using semantic similarity. the limited coverage of lexical-semantic resources is a significant problem for nlp systems which can be alleviated by automatically classifying the unknown words. supersense tagging assigns unknown nouns one of 26 broad semantic categories used by lexicographers to organise their manual insertion into wordnet. ciaramita and johnson (2003) present a tagger which uses synonym set glosses as annotated training examples. we describe an unsupervised approach, based on vector-space similarity, which does not require annotated examples but significantly outperforms their tagger. we also demonstrate the use of an extremely large shallow-parsed corpus for calculating vector-space semantic similarity.
multi-tagging for lexicalized-grammar parsing. with performance above 97% accuracy for newspaper text, part of speech (pos) tagging might be considered a solved problem. previous studies have shown that allowing the parser to resolve pos tag ambiguity does not improve performance. however, for grammar formalisms which use more fine-grained grammatical categories, for example tag and ccg, tagging accuracy is much lower. in fact, for these formalisms, premature ambiguity resolution makes parsing infeasible.we describe a multi-tagging approach which maintains a suitable level of lexical category ambiguity for accurate and efficient ccg parsing. we extend this multi-tagging approach to the pos level to overcome errors introduced by automatically assigned pos tags. although pos tagging accuracy seems high, maintaining some pos tag ambiguity in the language processing pipeline results in more accurate ccg supertagging.
scaling context space. context is used in many nlp systems as an indicator of a term's syntactic and semantic function. the accuracy of the system is dependent on the quality and quantity of contextual information available to describe each term. however, the quantity variable is no longer fixed by limited corpus resources. given fixed training time and computational resources, it makes sense for systems to invest time in extracting high quality contextual information from a fixed corpus. however, with an effectively limitless quantity of text available, extraction rate and representation size need to be considered. we use thesaurus extraction with a range of context extracting tools to demonstrate the interaction between context quantity, time and size on a corpus of 300 million words.
lexical disambiguation: sources of information and their statistical realization. lexical disambiguation can be achieved using different sources of information. aiming at high performance of automatic disambiguation it is important to know the relative importance and applicability of the various sources. in this paper we classify several sources of information and show how some of them can be achieved using statistical data. first evaluations indicate the extreme importance of local information, which mainly represents lexical associations and selectional restrictions for syntactically related words.
direct word sense matching for lexical substitution. this paper investigates conceptually and empirically the novel sense matching task, which requires to recognize whether the senses of two synonymous words match in context. we suggest direct approaches to the problem, which avoid the intermediate step of explicit word sense disambiguation, and demonstrate their appealing advantages and stimulating potential for future research.
two languages are more informative than one. this paper presents a new approach for resolving lexical ambiguities in one language using statistical data on lexical relations in another language. this approach exploits the differences between mappings of words to senses in different languages. we concentrate on the problem of target word selection in machine translation, for which the approach is directly applicable, and employ a statistical model for the selection mechanism. the model was evaluated using two sets of hebrew and german examples and was found to be very useful for disambiguation.
similarity-based methods for word sense disambiguation. we compare four similarity-based estimation methods against back-off and maximum-likelihood estimation methods on a pseudo-word sense disambiguation task in which we controlled for both unigram and bigram frequency. the similarity-based methods perform up to 40% better on this particular task. we also conclude that events that occur only once in the training set have major impact on similarity-based estimates.
contextual word similarity and estimation from sparse data. in recent years there is much interest in word cooccurrence relations, such as n-grams, verb-object combinations, or cooccurrence within a limited context. this paper discusses how to estimate the probability of cooccurrences that do not occur in the training data. we present a method that makes local analogies between each specific unobserved cooccurrence and other cooccurrences that contain similar words, as determined by an appropriate word similarity metric. our evaluation suggests that this method performs better than existing smoothing methods, and may provide an alternative to class based models.
similarity-based estimation of word cooccurrence probabilities. in many applications of natural language processing it is necessary to determine the likelihood of a given word combination. for example, a speech recognizer may need to determine which of the two word combinations "eat a peach" and "eat a beach" is more likely. statistical nlp methods determine the likelihood of a word combination according to its frequency in a training corpus. however, the nature of language is such that many word combinations are infrequent and do not occur in a given corpus. in this work we propose a method for estimating the probability of such previously unseen word combinations using available information on "most similar" words.we describe a probabilistic word association model based on distributional word similarity, and apply it to improving probability estimates for unseen word bigrams in a variant of katz's back-off model. the similarity-based method yields a 20% perplexity improvement in the prediction of unseen bigrams and statistically significant reductions in speech-recognition error.
cooking up referring expressions. this paper describes the referring expression generation mechanisms used in epicure, a computer program which produces natural language descriptions of cookery recipes. major features of the system include: an underlying ontology which permits the representation of non-singular entities; a notion of discriminatory power, to determine what properties should be used in a description; and a patr-like unification grammar to produce surface linguistic strings.
the interpretation of tense and aspect in english. an analysis of english tense and aspect is presented that specifies temporal precedence relations within a sentence. the relevant reference points for interpretation are taken to be the initial and terminal points of events in the world, as well as two "hypothetical" times: the perfect time (when a sentence contains perfect aspect) and the progressive or during time. a method for providing temporal interpretation for nontensed elements in the sentence is also described.
investigating regular sense extensions based on intersective levin classes. in this paper we specifically address questions of polysemy with respect to verbs, and how regular extensions of meaning can be achieved through the adjunction of particular syntactic phrases. we see verb classes as the key to making generalizations about regular extensions of meaning. current approaches to english classification, levin classes and wordnet, have limitations in their applicability that impede their utility as general classification schemes. we present a refinement of levin classes, intersective sets, which are a more fine-grained classification and have more coherent sets of syntactic frames and associated semantic components. we have preliminary indications that the membership of our intersective sets will be more compatible with wordnet than the original levin classes. we also have begun to examine related classes in portuguese, and find that these verbs demonstrate similarly coherent syntactic and semantic properties.
the role of semantic roles in disambiguating verb senses. we describe an automatic word sense disambiguation (wsd) system that disambiguates verb senses using syntactic and semantic features that encode information about predicate arguments and semantic classes. our system performs at the best published accuracy on the english verbs of senseval-2. we also experiment with using the gold-standard predicate-argument labels from propbank for disambiguating fine-grained wordnet senses and course-grained propbank framesets, and show that disambiguation of verb senses can be further improved with better extraction of semantic roles.
mapping wordnets using structural information. we present a robust approach for linking already existing lexical/semantic hierarchies. we used a constraint satisfaction algorithm (relaxation labeling) to select - among a set of candidates- the node in a target taxonomy that bests matches each node in a source taxonomy. in particular, we use it to map the nominal part of wordnet 1.5 onto wordnet 1.6, with a very high precision and a very low remaining ambiguity.
a noisy-channel model for document compression. we present a document compression system that uses a hierarchical noisy-channel model of text production. our compression system first automatically derives the syntactic structure of each sentence and the overall discourse structure of the text given as input. the system then uses a statistical hierarchical model of text production in order to drop non-important syntactic and discourse constituents so as to generate coherent, grammatical document compressions of arbitrary length. the system outperforms both a baseline and a sentence-based compression system that operates by simplifying sequentially all sentences in a text. our results support the claim that discourse knowledge plays an important role in document summarization.
bayesian query-focused summarization. we present bayesum (for "bayesian summarization"), a model for sentence extraction in query-focused summarization. bayesum leverages the common case in which multiple documents are relevant to a single query. using these documents as reinforcement for query terms, bayesum is not afflicted by the paucity of information in short queries. we show that approximate inference in bayesum is possible on large data sets and results in a state-of-the-art summarization system. furthermore, we show how bayesum can be understood as a justified query expansion technique in the language modeling for ir framework.
efficient unsupervised discovery of word categories using symmetric patterns and high frequency words. we present a novel approach for discovering word categories, sets of words sharing a significant aspect of their meaning. we utilize meta-patterns of high-frequency words and content words in order to discover pattern candidates. symmetric patterns are then identified using graph-based measures, and word categories are created based on graph clique sets. our method is the first pattern-based method that requires no corpus annotation or manually provided seed patterns or words. we evaluate our algorithm on very large corpora in two languages, using both human judgments and wordnet-based evaluation. our fully unsupervised results are superior to previous work that used a pos tagged corpus, and computation time for huge corpora are orders of magnitude faster than previously reported.
assigning intonational features in synthesized spoken directions. speakers convey much of the information hearers use to interpret discourse by varying prosodic features such as phrasing, pitch accent placement, tune, and pitch range. the ability to emulate such variation is crucial to effective (synthetic) speech generation. while text-to-speech synthesis must rely primarily upon structural information to determine appropriate intonational features, speech synthesized from an abstract representation of the message to be conveyed may employ much richer sources. the implementation of an intonation assignment component for direction assistance, a program which generates spoken directions, provides a first approximation of how recent models of discourse structure can be used to control intonational variation in ways that build upon recent research in intonational meaning. the implementation further suggests ways in which these discourse models might be augmented to permit the assignment of appropriate intonational features.
a three-valued interpretation of negation in feature structure descriptions. feature structures are informational elements that have been used in several linguistic theories and in computational systems for natural-language processing. a logical calculus has been developed and used as a description language for feature structures. in the present work, a framework in three-valued logic is suggested for defining the semantics of a feature structure description language, allowing for a more complete set of logical operators. in particular, the semantics of the negation and implication operators are examined. various proposed interpretations of negation and implication are compared within the suggested framework. one particular interpretation of the description language with a negation operator is described and its computational aspects studied.
interactively exploring a machine translation model. this paper describes a method of interactively visualizing and directing the process of translating a sentence. the method allows a user to explore a model of syntax-based statistical machine translation (mt), to understand the model's strengths and weaknesses, and to compare it to other mt systems. using this visualization method, we can find and address conceptual and practical problems in an mt system. in our demonstration at acl, new users of our tool will drive a syntax-based decoder for themselves.
an information-state approach to collaborative reference. we describe a dialogue system that works with its interlocutor to identify objects. our contributions include a concise, modular architecture with reversible processes of understanding and generation, an information-state model of reference, and flexible links between semantics and collaborative problem solving.
a nonparametric method for extraction of candidate phrasal terms. this paper introduces a new method for identifying candidate phrasal terms (also known as multiword units) which applies a nonparametric, rank-based heuristic measure. evaluation of this measure, the mutual rank ratio metric, shows that it produces better results than standard statistical measures when applied to this task.
the use of syntactic clues in discourse processing. the desirability of a syntactic parsing component in natural language understanding systems has been the subject of debate for the past several years. this paper describes an approach to automatic text processing which is entirely based on syntactic form. a program is described which processes one genre of discourse, that of newspaper reports. the program creates summaries of reports by relying on an expanded concept of text grounding: certain syntactic structures and tense/aspect pairs indicate the most important events in a news story. supportive, background material is also highly coded syntactically. certain types of information are routinely expressed with distinct syntactic forms. where more than one episode occurs in a single report, a change of episode will also be marked syntactically in a reliable way.
learning a syntagmatic and paradigmatic structure from language data with a bi-multigram model. in this paper, we present a stochastic language modeling tool which aims at retrieving variable-length phrases (multigrams), assuming bigram dependencies between them. the phrase retrieval can be intermixed with a phrase clustering procedure, so that the language data are iteratively structured at both a paradigmatic and a syntagmatic level in a fully integrated way. perplexity results on atr travel arrangement data with a bi-multigram model (assuming bigram correlations between the phrases) come very close to the trigram scores with a reduced number of entries in the language model. also the ability of the class version of the model to merge semantically related phrases into a common class is illustrated.
experiments with learning parsing heuristics. any large language processing software relies in its operation on heuristic decisions concerning the strategy of processing. these decisions are usually "hard-wired" into the software in the form of hand-crafted heuristic rules, independent of the nature of the processed texts. we propose an alternative, adaptive approach in which machine learning techniques learn the rules from examples of sentences in each class. we have experimented with a variety of learning techniques on a representative instance of this problem within the realm of parsing. our approach lead to the discovery of new heuristics that perform significantly better than the current hand-crafted heuristic. we discuss the entire cycle of application of machine learning and suggest a methodology for the use of machine learning as a technique for the adaptive optimisation of language-processing software.
answer extraction, semantic clustering, and extractive summarization for clinical question answering. this paper presents a hybrid approach to question answering in the clinical domain that combines techniques from summarization and information retrieval. we tackle a frequently-occurring class of questions that takes the form "what is the best drug treatment for x?" starting from an initial set of medline citations, our system first identifies the drugs under study. abstracts are then clustered using semantic classes from the umls ontology. finally, a short extractive summary is generated for each abstract to populate the clusters. two evaluations---a manual one focused on short answers and an automatic one focused on the supporting abstract---demonstrate that our system compares favorably to pubmed, the search system most widely used by physicians today.
relieving the data acquisition bottleneck in word sense disambiguation. supervised learning methods for wsd yield better performance than unsupervised methods. yet the availability of clean training data for the former is still a severe challenge. in this paper, we present an unsupervised bootstrapping approach for wsd which exploits huge amounts of automatically generated noisy data for training within a supervised learning framework. the method is evaluated using the 29 nouns in the english lexical sample task of senseval 2. our algorithm does as well as supervised algorithms on 31% of this test set, which is an improvement of 11% (absolute) over state-of-the-art bootstrapping wsd algorithms. we identify seven different factors that impact the performance of our system.
an unsupervised method for word sense tagging using parallel corpora. we present an unsupervised method for word sense disambiguation that exploits translation correspondences in parallel corpora. the technique takes advantage of the fact that cross-language lexicalizations of the same concept tend to be consistent, preserving some core element of its semantics, and yet also variable, reflecting differing translator preferences and the influence of context. working with parallel corpora introduces an extra complication for evaluation, since it is difficult to find a corpus that is both sense tagged and parallel with another language; therefore we use pseudo-translations, created by machine translation systems, in order to make possible the evaluation of the approach against a standard test set. the results demonstrate that word-level translation correspondences are a valuable source of information for sense disambiguation.
detecting errors in discontinuous structural annotation. consistency of corpus annotation is an essential property for the many uses of annotated corpora in computational and theoretical linguistics. while some research addresses the detection of inconsistencies in positional annotation (e.g., part-of-speech) and continuous structural annotation (e.g., syntactic constituency), no approach has yet been developed for automatically detecting annotation errors in discontinuous structural annotation. this is significant since the annotation of potentially discontinuous stretches of material is increasingly relevant, from tree-banks for free-word order languages to semantic and discourse annotation.in this paper we discuss how the variation n-gram error detection approach (dickinson and meurers, 2003a) can be extended to discontinuous structural annotation. we exemplify the approach by showing how it successfully detects errors in the syntactic annotation of the german tiger corpus (brants et al., 2002).
a corpus-based approach to topic in danish dialog. we report on an investigation of the pragmatic category of topic in danish dialog and its correlation to surface features of nps. using a corpus of 444 utterances, we trained a decision tree system on 16 features. the system achieved near-human performance with success rates of 84--89% and f1-scores of 0.63--0.72 in 10-fold cross validation tests (human performance: 89% and 0.78). the most important features turned out to be preverbal position, definiteness, pronominalisation, and non-subordination. we discovered that nps in epistemic matrix clauses (e.g. "i think ...") were seldom topics and we suspect that this holds for other interpersonal matrix clauses as well.
deep syntactic processing by combining shallow methods. we present a novel approach for finding discontinuities that outperforms previously published results on this task. rather than using a deeper grammar formalism, our system combines a simple unlexicalized pcfg parser with a shallow pre-processor. this pre-processor, which we call a trace tagger, does surprisingly well on detecting where discontinuities can occur without using phase structure information.
grammars for local and long dependencies. polarized dependency (pd-) grammars are proposed as a means of efficient treatment of discontinuous constructions. pd-grammars describe two kinds of dependencies: local, explicitly derived by the rules, and long, implicitly specified by negative and positive valencies of words. if in a pd-grammar the number of non-saturated valencies in derived structures is bounded by a constant, then it is weakly equivalent to a cf-grammar and has a o(n3)-time parsing algorithm. it happens that such bounded pd-grammars are strong enough to express such phenomena as unbounded raising, extraction and extraposition.
multext-east: parallel and comparable corpora and lexicons for six central and eastern european languages. the eu copernicus project multext-east has created a multi-lingual corpus of text and speech data, covering the six languages of the project: bulgarian, czech, estonian, hungarian, romanian, and slovene. in addition, wordform lexicons for each of the languages were developed. the corpus includes a parallel component consisting of orwell's nineteen eighty-four, with versions in all six languages tagged for part-of-speech and aligned to english (also tagged for pos). we describe the encoding format and data architecture designed especially for this corpus, which is generally usable for encoding linguistic corpora. we also describe the methodology for the development of a harmonized set of morphosyntactic descriptions (msds), which builds upon the scheme for western european languages developed within the eagles project. we discuss the special concerns for handling the six project languages, which cover three distinct language families.
machine translation using probabilistic synchronous dependency insertion grammars. syntax-based statistical machine translation (mt) aims at applying statistical models to structured data. in this paper, we present a syntax-based statistical machine translation system based on a probabilistic synchronous dependency insertion grammar. synchronous dependency insertion grammars are a version of synchronous grammars defined on dependency trees. we first introduce our approach to inducing such a grammar from parallel corpora. second, we describe the graphical model for the machine translation task, which can also be viewed as a stochastic tree-to-tree transducer. we introduce a polynomial time decoding algorithm for the model. we evaluate the outputs of our mt system using the nist and bleu automatic mt evaluation software. the result shows that our system outperforms the baseline system based on the ibm models in both translation speed and quality.
error driven word sense disambiguation. in this paper we describe a method for performing word sense disambiguation (wsd). the method relies on unsupervised learning and exploits functional relations among words as produced by a shallow parser. by exploiting an error driven rule learning algorithm (brill 1997), the system is able to produce rules for wsd, which can be optionally edited by humans in order to increase the performance of the system.
a text input front-end processor as an information access platform. this paper presents a practical foreign language writing support tool which makes it much easier to utilize dictionary and example sentence resources. like a kana-kanji conversion front-end processor used to input japanese language text, this tool is also implemented as a front-end processor and can be combined with a wide variety of applications. a morphological analyzer automatically extracts key words from text as it is being input into the tool, and these words are used to locate information relevant to the input text. this information is then automatically displayed to the user. with this tool, users can concentrate better on their writing because much less interruption of their work is required for the consulting of dictionaries or for the retrieval of reference sentences. retrieval and display may be conducted in any three ways: 1) relevant information is retrieved and displayed automatically; 2) information is retrieved automatically but displayed only on user command; 3) information is both retrieved and displayed only on user command. the extent to which the retrieval and display of information proceeds automatically depends on the type of information being referenced; this element of the design adds to system efficiency. further, by combining this tool with a stepped-level interactive machine translation function, we have created a pc support tool to help japanese people write in english.
subdeletion in verb phrase ellipsis. this paper stems from an ongoing research project on verb phrase ellipsis. the project's goals are to implement a verb phrase ellipsis resolution algorithm, automatically test the algorithm on corpus data, then automatically evaluate the algorithm against human-generated answers. the paper will establish the current status of the algorithm based on this automatic evaluation, categorizing current problem situations. an algorithm to handle one of these problems, the case of subdeletion, will be described and evaluated. the algorithm attempts to detect and solve subdeletion by locating adjuncts of similar types in a verb phrase ellipsis and corresponding antecedent.
syntactic and semantic transfer with f-structures. we present two approaches for syntactic and semantic transfer based on lfg f-structures and compare the results with existing co-description and restriction operator based approaches, focusing on aspects of ambiguity preserving transfer, complex cases of syntactic structural mismatches as well as on modularity and reusability. the two transfer approaches are interfaced with an existing, implemented transfer component (verbmobil), by translating f-structures into a term language, and by interfacing f-structure representations with an existing semantic based transfer approach, respectively.
solving thematic divergences in machine translation. though most translation systems have some mechanism for translating certain types of divergent predicate-argument structures, they do not provide a general procedure that takes advantage of the relationship between lexical-semantic structure and syntactic structure. a divergent predicate-argument structure is one in which the predicate (e.g., the main verb) or its arguments (e.g., the subject and object) do not have the same syntactic ordering properties for both the source and target language. to account for such ordering differences, a machine translator must consider language-specific syntactic idiosyncrasies that distinguish a target language from a source language, while making use of lexical-semantic uniformities that tie the two languages together. this paper describes the mechanisms used by the unitran machine translation system for mapping an underlying lexical-conceptual structure to a syntactic structure (and vice versa), and it shows how these mechanisms coupled with a set of general linking routines solve the problem of thematic divergence in machine translation.
a parameterized approach to integrating aspect with lexical-semanics for machine translation. this paper discusses how a two-level knowledge representation model for machine translation integrates aspectual information with lexical-semantic information by means of parameterization. the integration of aspect with lexical-semantics is especially critical in machine translation because of the lexical selection and aspectual realization processes that operate during the production of the target-language sentence: there are often a large number of lexical and aspectual possibilities to choose from in the production of a sentence from a lexical semantic representation. aspectual information from the source-language sentence constrains the choice of target-language terms. in turn, the target-language terms limit the possibilities for generation of aspect. thus, there is a two-way communication channel between the two processes. this paper will show that the selection/realization processes may be parameterized so that they operate uniformly across more than one language and it will describe how the parameter-based approach is currently being used as the basis for extraction of aspectual information from corpora.
deriving verbal and compositional lexical aspect for nlp applications. verbal and compositional lexical aspect provide the underlying temporal structure of events. knowledge of lexical aspect, e.g., (a)telicity, is therefore required for interpreting event sequences in discourse (dowty, 1986; moens and steedman, 1988; passoneau, 1988), interfacing to temporal databases (androutsopoulos, 1996), processing temporal modifiers (antonisse, 1994), describing allowable alternations and their semantic effects (resnik, 1996; tenny, 1994), and selecting tense and lexical items for natural language generation ((dorr and olsen, 1996; klavans and chodorow, 1992), cf. (slobin and bocaz, 1988)). we show that it is possible to represent lexical aspect---both verbal and compositional---on a large scale, using lexical conceptual structure (lcs) representations of verbs in the classes cataloged by levin (1993). we show how proper consideration of these universal pieces of verb meaning may be used to refine lexical representations and derive a range of meanings from combinations of lcs representations. a single algorithm may therefore be used to determine lexical aspect classes and features at both verbal and sentence levels. finally, we illustrate how knowledge of lexical aspect facilitates the interpretation of events in nlp applications.
feature logic with weak subsumption constraints. in the general framework of a constraint-based grammar formalism often some sort of feature logic serves as the constraint language to describe linguistic objects. we investigate the extension of basic feature logic with subsumption (or matching) constraints, based on a weak notion of subsumption. this mechanism of one-way information flow is generally deemed to be necessary to give linguistically satisfactory descriptions of coordination phenomena in such formalisms. we show that the problem whether a set of constraints is satisfiable in this logic is decidable in polynomial time and give a solution algorithm.
parsing for semidirectional lambek grammar is np-complete. we study the computational complexity of the parsing problem of a variant of lambek categorial grammar that we call semidirectional. in semidirectional lambek calculus sdl there is an additional nondirectional abstraction rule allowing the formula abstracted over to appear anywhere in the premise sequent's left-hand side, thus permitting non-peripheral extraction. sdl grammars are able to generate each context-free language and more than that. we show that the parsing problem for semidirectional lambek grammar is np-complete by a reduction of the 3-partition problem.
efficient construction of underspecified semantics under massive ambiguity. we investigate the problem of determining a compact underspecified semantical representation for sentences that may be highly ambiguous. due to combinatorial explosion, the naive method of building semantics for the different syntactic readings independently is prohibitive. we present a method that takes as input a syntactic parse forest with associated constraint-based semantic construction rules and directly builds a packed semantic structure. the algorithm is fully implemented and runs in o(n4log(n)) in sentence length, if the grammar meets some reasonable 'normality' restrictions.
gemini: a natural language system for spoken-language understanding. gemini is a natural language understanding system developed for spoken language applications. this paper describes the details of the system, and includes relevant measurements of size, efficiency, and performance of each of its sub-components in detail.
practical issues in compiling typed unification grammars for speech recognition. current alternatives for language modeling are statistical techniques based on large amounts of training data, and hand-crafted context-free or finite-state grammars that are difficult to build and maintain. one way to address the problems of the grammar-based approach is to compile recognition grammars from grammars written in a more expressive formalism. while theoretically straight-forward, the compilation process can exceed memory and time bounds, and might not always result in accurate and efficient speech recognition. we will describe and evaluate two approaches to this compilation problem. we will also describe and evaluate additional techniques to reduce the structural ambiguity of the language model.
interleaving syntax and semantics in an effecient bottom-up parser. we describe an efficient bottom-up parser that interleaves syntactic and semantic structure building. two techniques are presented for reducing search by reducing local ambiguity: limited left context constraints are used to reduce local syntactic ambiguity, and deferred sortal-constraint application is used to reduce local semantic ambiguity. we experimentally evaluate these techniques, and show dramatic reductions in both number of chart edges and total parsing time. the robust processing capabilities of the parser are demonstrated in its use in improving the accuracy of a speech recognizer.
representing paraphrases using synchronous tags. this paper looks at representing paraphrases using the formalism of synchronous tags; it looks particularly at comparisons with machine translation and the modifications it is necessary to make to synchronous tags for paraphrasing. a more detailed version is in dras (1997a).
a meta-level grammar: redefining synchronous tag for translation and paraphrase. in applications such as translation and paraphrase, operations are carried out on grammars at the meta level. this paper shows how a meta-grammar, defining structure at the meta level, is useful in the case of such operations; in particular, how it solves problems in the current definition of synchronous tag (shieber, 1994) caused by ignoring such structure in mapping between grammars, for applications such as translation. moreover, essential properties of the formalism remain unchanged.
a bio-inspired approach for multi-word expression extraction. this paper proposes a new approach for multi-word expression (mwe)extraction on the motivation of gene sequence alignment because textual sequence is similar to gene sequence in pattern analysis. theory of longest common subsequence (lcs) originates from computer science and has been established as affine gap model in bioinformatics. we perform this developed lcs technique combined with linguistic criteria in mwe extraction. in comparison with traditional n-gram method, which is the major technique for mwe extraction, lcs approach is applied with great efficiency and performance guarantee. experimental results show that lcs-based approach achieves better results than n-gram.
what to do when lexicalization fails: parsing german with suffix analysis and smoothing. in this paper, we present an unlexicalized parser for german which employs smoothing and suffix analysis to achieve a labelled bracket f-score of 76.2, higher than previously reported results on the negra corpus. in addition to the high accuracy of the model, the use of smoothing in an unlexicalized parser allows us to better examine the interplay between smoothing and parsing results.
probabilistic parsing for german using sister-head dependencies. we present a probabilistic parsing model for german trained on the negra treebank. we observe that existing lexicalized parsing models using head-head dependencies, while successful for english, fail to outperform an unlexicalized baseline model for german. learning curves show that this effect is not due to lack of training data. we propose an alternative model that uses sister-head dependencies instead of head-head dependencies. this model out-performs the baseline, achieving a labeled precision and recall of up to 74%. this indicates that sister-head dependencies are more appropriate for treebanks with very flat structures such as negra.
integrating syntactic priming into an incremental probabilistic parser, with an application to psycholinguistic modeling. the psycholinguistic literature provides evidence for syntactic priming, i.e., the tendency to repeat structures. this paper describes a method for incorporating priming into an incremental probabilistic parser. three models are compared, which involve priming of rules between sentences, within sentences, and within coordinate structures. these models simulate the reading time advantage for parallel structures found in human data, and also yield a small increase in overall parsing accuracy.
empirically estimating order constraints for content planning in generation. in a language generation system, a content planner embodies one or more "plans" that are usually hand--crafted, sometimes through manual analysis of target text. in this paper, we present a system that we developed to automatically learn elements of a plan and the ordering constraints among them. as training data, we use semantically annotated transcripts of domain experts performing the task our system is designed to mimic. given the large degree of variation in the spoken language of the transcripts, we developed a novel algorithm to find parallels between transcripts based on techniques used in computational genomics. our proposed methodology was evaluated two--fold: the learning and generalization capabilities were quantitatively evaluated using cross validation obtaining a level of accuracy of 89%. a qualitative evaluation is also provided.
topological dependency trees: a constraint-based account of linear precedence. we describe a new framework for dependency grammar, with a modular decomposition of immediate dependency and linear precedence. our approach distinguishes two orthogonal yet mutually constraining structures: a syntactic dependency tree and a topological dependency tree. the syntax tree is nonprojective and even non-ordered, while the topological tree is projective and partially ordered.
interpreting the human genome sequence, using stochastic grammars. the 3 billion base pair sequence of the human genome is now available, and attention is focusing on annotating it to extract biological meaning. i will discuss what we have obtained, and the methods that are being used to analyse biological sequences. in particular i will discuss approaches using stochastic grammars analogous to those used in computational linguistics, both for gene finding and protein family classification.
a noisy-channel approach to question answering. we introduce a probabilistic noisy-channel model for question answering and we show how it can be exploited in the context of an end-to-end qa system. our noisy-channel system outperforms a state-of-the-art rule-based qa system that uses similar resources. we also show that the model we propose is flexible enough to accommodate within one mathematical framework many qa-specific resources and techniques, which range from the exploitation of wordnet, structured, and semi-structured databases to reasoning, and paraphrasing.
towards a modular data model for multi-layer annotated corpora. in this paper we discuss the current methods in the representation of corpora annotated at multiple levels of linguistic organization (so-called multi-level or multi-layer corpora). taking five approaches which are representative of the current practice in this area, we discuss the commonalities and differences between them focusing on the underlying data models. the goal of the paper is to identify the common concerns in multi-layer corpus representation and processing so as to lay a foundation for a unifying, modular data model.
choosing the word most typical in context using a lexical co-occurrence network. this paper presents a partial solution to a component of the problem of lexical choice: choosing the synonym most typical, or expected, in context. we apply a new statistical approach to representing the context of a word through lexical co-occurrence networks. the implementation was trained and evaluated on a large corpus, and results show that the inclusion of second-order co-occurrence relations improves the performance of our implemented lexical choice program.
constraints over lambda-structures in semantic underspecification. we introduce a first-order language for semantic underspecification that we call constraint language for lambda-structures (clls). a &lambda;-structure can be considered as a &lambda;-term up to consistent renaming of bound variables (&lambda;-equality); a constraint of clls is an underspecified description of a &lambda;-structure. clls solves a capturing problem omnipresent in underspecified scope representations. clls features constraints for dominance, lambda binding, parallelism, and anaphoric links. based on clls we present a simple, integrated, and underspecified treatment of scope, parallelism, and anaphora.
unification of disjunctive feature descriptions. the paper describes a new implementation of feature structures containing disjunctive values, which can be characterized by the following main points: local representation of embedded disjunctions, avoidance of expansion to disjunctive normal form and of repeated test-unifications for checking consistence. the method is based on a modification of kasper and rounds' calculus of feature descriptions and its correctness therefore is easy to see. it can handle cyclic structures and has been incorporated successfully into an environment for grammar development.
parameter estimation for probabilistic finite-state transducers. weighted finite-state transducers suffer from the lack of a training algorithm. training is even harder for transducers that have been assembled via finite-state operations such as composition, minimization, union, concatenation, and closure, as this yields tricky parameter tying. we formulate a "parameterized fst" paradigm and give training algorithms for it, including a general bookkeeping trick ("expectation semirings") that cleanly and efficiently computes expectations and gradients.
efficient normal-form parsing for combinatory categorial grammar. under categorial grammars that have powerful rules like composition, a simple n-word sentence can have exponentially many parses. generating all parses is inefficient and obscures whatever true semantic ambiguities are in the input. this paper addresses the problem for a fairly general form of combinatory categorial grammar, by means of an efficient, correct, and easy to implement normal-form parsing technique. the parser is proved to find exactly one parse in each semantic equivalence class of allowable parses; that is, spurious ambiguity (as carefully defined) is shown to be both safely and completely eliminated.
efficient generation in primitive optimality theory. this paper introduces primitive optimality theory (otp), a linguistically motivated formalization of ot. otp specifies the class of autosegmental representations, the universal generator gen, and the two simple families of permissible constraints. in contrast to less restricted theories using generalized alignment, otp's optimal surface forms can be generated with finite-state methods adapted from (ellison, 1994). unfortunately these methods take time exponential on the size of the grammar. indeed the generation problem is shown np-complete in this sense. however, techniques are discussed for making ellison's approach fast in the typical case, including a simple trick that alone provides a 100-fold speedup on a grammar fragment of moderate size. one avenue for future improvements is a new finite-state notion, "factored automata," where regular languages are represented compactly via formal intersections &cap;ki=1ai of fsas.
efficient parsing for bilexical context-free grammars and head automaton grammars. several recent stochastic parsers use <i>bilexical</i> grammars, where each word type idiosyncratically prefers particular complements with particular head words. we present <i>o(n</i><sup>4</sup>) parsing algorithms for two bilexical formalisms, improving the prior upper bounds of <i>o(n</i><sup>5</sup>). for a common special case that was known to allow <i>o(n</i><sup>3</sup>) parsing (eisner, 1997), we present an <i>o(n</i><sup>3</sup>) algorithm with an improved grammar constant.
a modified joint source-channel model for transliteration. most machine transliteration systems transliterate out of vocabulary (oov) words through intermediate phonemic mapping. a framework has been presented that allows direct orthographical mapping between two languages that are of different origins employing different alphabet sets. a modified joint source-channel model along with a number of alternatives have been proposed. aligned transliteration units along with their context are automatically derived from a bilingual training corpus to generate the collocational statistics. the transliteration units in bengali words take the pattern c+m where c represents a vowel or a consonant or a conjunct and m represents the vowel modifier or matra. the english transliteration units are of the form c*v* where c represents a consonant and v represents a vowel. a bengali-english machine transliteration system has been developed based on the proposed models. the system has been trained to transliterate person names from bengali to english. it uses the linguistic knowledge of possible conjuncts and diphthongs in bengali and their equivalents in english. the system has been evaluated and it has been observed that the modified joint source-channel model performs best with a word agreement ratio of 69.3% and a transliteration unit agreement ratio of 89.8%.
types in functional unification grammars. functional unification grammars (fugs) are popular for natural language applications because the formalism uses very few primitives and is uniform and expressive. in our work on text generation, we have found that it also has annoying limitations: it is not suited for the expression of simple, yet very common, taxonomic relations and it does not allow the specification of completeness conditions. we have implemented an extension of traditional functional unification. this extension addresses these limitations while preserving the desirable properties of fugs. it is based on the notions of typed features and typed constituents. we show the advantages of this extension in the context of a grammar used for text generation.
measuring language divergence by intra-lexical comparison. this paper presents a method for building genetic language taxonomies based on a new approach to comparing lexical forms. instead of comparing forms cross-linguistically, a matrix of language-internal similarities between forms is calculated. these matrices are then compared to give distances between languages. we argue that this coheres better with current thinking in linguistics and psycholinguistics. an implementation of this approach, called philologicon, is described, along with its application to dyen et al.'s (1992) ninety-five wordlists from indo-european languages.
spelling correction using context. this paper describes a spelling correction system that functions as part of an intelligent tutor that carries on a natural language dialogue with its users. the process that searches the lexicon is adaptive as is the system filter, to speed up the process. the basis of our approach is the interaction between the parser and the spelling corrector. alternative correction targets are fed back to the parser, which does a series of syntactic and semantic checks, based on the dialogue context, the sentence context, and the phrase context.
exploring and exploiting the limited utility of captions in recognizing intention in information graphics. this paper presents a corpus study that explores the extent to which captions contribute to recognizing the intended message of an information graphic. it then presents an implemented graphic interpretation system that takes into account a variety of communicative signals, and an evaluation study showing that evidence obtained from shallow processing of the graphic's caption has a significant impact on the system's success. this work is part of a larger project whose goal is to provide sight-impaired users with effective access to information graphics.
unification with lazy non-redundant copying. this paper presents a unification procedure which eliminates the redundant copying of structures by using a lazy incremental copying approach to achieve structure sharing. copying of structures accounts for a considerable amount of the total processing time. several methods have been proposed to minimize the amount of necessary copying. lazy incremental copying (lic) is presented as a new solution to the copying problem. it synthesizes ideas of lazy copying with the notion of chronological dereferencing for achieving a high amount of structure sharing.
ambiguity preserving machine translation using packed representations. in this paper we present an ambiguity preserving translation approach which transfers ambiguous lfg f-structure representatios. it is based on packed f-structure representations which are the result of potentially ambiguous utterances. if the ambiguities between source and target language can be preserved, no unpacking during transfer is necessary and the generator may produce utterances which maximally cover the underlying ambiguities. we convert the packed f-structure descriptions into a flat set of prolog terms which consist of predicates, their predicate argument structure and additional attribute-value information. ambiguity is expressed via local disjunctions. the flat representations facilitate the application of a shake-and-bake like transfer approach extended to deal with packed ambiguites.
handling linear precedence constraints by unification. linear precedence (lp) rules are widley used for stating word order principles. they have been adopted as constraints by hpsg but no encoding in the formalism has been provided. since they only order siblings, they are not quite adequate, at least not for german. we propose a notion of lp constraints that applies to linguistically motivated branching domains such as head domains. we show a type-based encoding in an hpsg-style formalism that supports processing. the encoding can be achieved by a compilation step.
minimizing manual annotation cost in supervised training from corpora. corpus-based methods for natural language processing often use supervised training, requiring expensive manual annotation of training corpora. this paper investigates methods for reducing annotation cost by sample selection. in this approach, during training the learning program examines many unlabeled examples and selects for labeling (annotation) only those that are most informative at each stage. this avoids redundantly annotating examples that contribute little new information. this paper extends our previous work on committee-based sample selection for probabilistic classifiers. we describe a family of methods for committee-based sample selection, and report experimental results for the task of stochastic part-of-speech tagging. we find that all variants achieve a significant reduction in annotation cost, though their computational efficiency differs. in particular, the simplest method, which has no parameters to tune, gives excellent results. we also show that sample selection yields a significant reduction in the size of the model used by the tagger.
towards a resource for lexical semantics: a large german corpus with extensive semantic annotation. we describe the ongoing construction of a large, semantically annotated corpus resource as reliable basis for the large-scale acquisition of word-semantic information, e.g. the construction of domain-independent lexica. the backbone of the annotation are semantic roles in the frame semantics paradigm. we report experiences and evaluate the annotated data from the first project stage. on this basis, we discuss the problems of vagueness and ambiguity in semantic annotation.
understanding natural language instructions: the case of purpose clauses. this paper presents an analysis of purpose clauses in the context of instruction understanding. such analysis shows that goals affect the interpretation and / or execution of actions, lends support to the proposal of using generation and enablement to model relations between actions, and sheds light on some inference processes necessary to interpret purpose clauses.
aggregation improves learning: experiments in natural language generation for intelligent tutoring systems. to improve the interaction between students and an intelligent tutoring system, we developed two natural language generators, that we systematically evaluated in a three way comparison that included the original system as well. we found that the generator which intuitively produces the best language does engender the most learning. specifically, it appears that functional aggregation is responsible for the improvement.
an empirical investigation of proposals in collaborative dialogues. we describe a corpus-based investigation of proposals in dialogue. first, we describe our dri compliant coding scheme and report our inter-coder reliability results. next, we test several hypotheses about what constitutes a well-formed proposal.
learning features that predict cue usage. our goal is to identify the features that predict the occurrence and placement of discourse cues in tutorial explanations in order to aid in the automatic generation of explanations. previous attempts to devise rules for text generation were based on intuition or small numbers of constructed examples. we apply a machine learning program, c4.5, to induce decision trees for cue occurrence and placement from a corpus of data coded for a variety of features previously thought to affect cue usage. our experiments enable us to identify the features with most predictive power, and show that machine learning can be used to induce decision trees useful for text generation.
approximating context-free grammars with a finite-state calculus. although adequate models of human language for syntactic analysis and semantic interpretation are of at least context-free complexity, for applications such as speech processing in which speed is important finite-state models are often preferred. these requirements may be reconciled by using the more complex grammar to automatically derive a finite-state approximation which can then be used as a filter to guide speech recognition or to reject many hypotheses at an early stage of processing. a method is presented here for calculating such finite-state approximations from context-free grammars. it is essentially different from the algorithm introduced by pereira and wright (1991; 1996), is faster in some cases, and has the advantage of being open-ended and adaptable.
encoding lexicalized tree adjoining grammars with a nonmonotonic inheritance hierachy. this paper shows how datr, a widely used formal language for lexical knowledge representation, can be used to define an ltag lexicon as an inheritance hierarchy with internal lexical rules. a bottom-up featural encoding is used for ltag trees and this allows lexical rules to be implemented as covariation constraints within feature structures. such an approach eliminates the considerable redundancy otherwise associated with an ltag lexicon.
a structure-sharing parser for lexicalized grammars. in wide-coverage lexicalized grammars many of the elementary structures have substructures in common. this means that in conventional parsing algorithms some of the computation associated with different structures is duplicated. in this paper we describe a precompilation technique for such grammars which allows some of this computation to be shared. in our approach the elementary structures of the grammar are transformed into finite state automata which can be merged and minimised using standard algorithms, and then parsed using an automaton-based parser. we present algorithms for constructing automata from elementary structures, merging and minimising them, and string recognition and parse recovery with the resulting grammar.
noun-phrase analysis in unrestricted text for information retrieval. information retrieval is an important application area of natural-language processing where one encounters the genuine challenge of processing large quantities of unrestricted natural-language text. this paper reports on the application of a few simple, yet robust and efficient noun-phrase analysis techniques to create better indexing phrases for information retrieval. in particular, we describe an hybrid approach to the extraction of meaningful (continuous or discontinuous) subcompounds from complex noun phrases using both corpus statistics and linguistic heuristics. results of experiments show that indexing based on such extracted subcompound improves both recall and precision in an information retrieval system. the noun-phrase analysis techniques are also potentially useful for book indexing and automatic thesaurus extraction.
methods for the qualitative evaluation of lexical association measures. this paper presents methods for a qualitative, unbiased comparison of lexical association measures and the results we have obtained for adjective-noun pairs and preposition-noun-verb triples extracted from german corpora. in our approach, we compare the entire list of candidates, sorted according to the particular measures, to a reference set of manually identified "true positives". we also show how estimates for the very large number of hapaxlegomena and double occurrences can be inferred from random samples.
combining stochastic and rule-based methods for disambiguation in agglutinative languages. in this paper we present the results of the combination of stochastic and rule-based disambiguation methods applied to basque language1. the methods we have used in disambiguation are constraint grammar formalism and an hmm based tagger developed within the multext project. as basque is an agglutinative language, a morphological analyser is needed to attach all possible readings to each word. then, cg rules are applied using all the morphological features and this process decreases morphological ambiguity of texts. finally, we use the multext project tools to select just one from the possible remaining tags.using only the stochastic method the error rate is about 14%, but the accuracy may be increased by about 2% enriching the lexicon with the unknown words. when both methods are combined, the error rate of the whole process is 3.5%. considering that the training corpus is quite small, that the hmm model is a first order one and that constraint grammar of basque language is still in progress, we think that this combined method can achieve good results, and it would be appropriate for other agglutinative languages.
chinese-english term translation mining based on semantic prediction. using abundant web resources to mine chinese term translations can be applied in many fields such as reading/writing assistant, machine translation and cross-language information retrieval. in mining english translations of chinese terms, how to obtain effective web pages and evaluate translation candidates are two challenging issues. in this paper, the approach based on semantic prediction is first proposed to obtain effective web pages. the proposed method predicts possible english meanings according to each constituent unit of chinese term, and expands these english items using semantically relevant knowledge for searching. the refined related terms are extracted from top retrieved documents through feedback learning to construct a new query expansion for acquiring more effective web pages. for obtaining a correct translation list, a translation evaluation method in the weighted sum of multi-features is presented to rank these candidates estimated from effective web pages. experimental results demonstrate that the proposed method has good performance in chinese-english term translation acquisition, and achieves 82.9% accuracy.
optimizing story link detection is not equivalent to optimizing new event detection. link detection has been regarded as a core technology for the topic detection and tracking tasks of new event detection. in this paper we formulate story link detection and new event detection as information retrieval task and hypothesize on the impact of precision and recall on both systems. motivated by these arguments, we introduce a number of new performance enhancing techniques including part of speech tagging, new similarity measures and expanded stop lists. experimental results validate our hypothesis.
highly constrained unification grammars. unification grammars are widely accepted as an expressive means for describing the structure of natural languages. in general, the recognition problem is undecidable for unification grammars. even with restricted variants of the formalism, off-line parsable grammars, the problem is computationally hard. we present two natural constraints on unification grammars which limit their expressivity and allow for efficient processing. we first show that non-reentrant unification grammars generate exactly the class of context-free languages. we then relax the constraint and show that one-reentrant unification grammars generate exactly the class of mildly context-sensitive languages. we thus relate the commonly used and linguistically motivated formalism of unification grammars to more restricted, computationally tractable classes of languages.
anaphor resolution in unrestricted texts with partial parsing. in this paper we deal with several kinds of anaphora in unrestricted texts. these kinds of anaphora are pronominal references, surfacecount anaphora and one-anaphora. in order to solve these anaphors we work on the output of a part-of-speech tagger, on which we automatically apply a partial parsing from the formalism: slot unification grammar, which has been implemented in prolog. we only use the following kinds of information: lexical (the lemma of each word), morphologic (person, number, gender) and syntactic. finally we show the experimental results, and the restrictions and preferences that we have used for anaphor resolution with partial parsing.
using textual clues to improve metaphor processing. in this paper, we propose a textual clue approach to help metaphor detection, in order to improve the semantic processing of this figure. the previous works in the domain studied the semantic regularities only, overlooking an obvious set of regularities. a corpus-based analysis shows the existence of surface regularities related to metaphors. these clues can be characterized by syntactic structures and lexical markers. we present an object oriented model for representing the textual clues that were found. this representation is designed to help the choice of a semantic processing, in terms of possible non-literal meanings. a prototype implementing this model is currently under development, within an incremental approach allowing step-by-step evaluations.
how to thematically segemt texts by using lexical cohesion? this article outlines a quantitative method for segmenting texts into thematically coherent units. this method relies on a network of lexical collocations to compute the thematic coherence of the different parts of a text from the lexical cohesiveness of their words. we also present the results of an experiment about locating boundaries between a series of concatened texts.
thematic segmentation of texts: two methods for two kinds of text. to segment texts in thematic units, we present here how a basic principle relying on word distribution can be applied on different kind of texts. we start from an existing method well adapted for scientific texts, and we propose its adaptation to other kinds of texts by using semantic links between words. these relations are found in a lexical network, automatically built from a large corpus. we will compare their results and give criteria to choose the more suitable method according to text characteristics.
enhancing electronic dictionaries with an index based on associations. a good dictionary contains not only many entries and a lot of information concerning each one of them, but also adequate means to reveal the stored information. information access depends crucially on the quality of the index. we will present here some ideas of how a dictionary could be enhanced to support a speaker/writer to find the word s/he is looking for. to this end we suggest to add to an existing electronic resource an index based on the notion of association. we will also present preliminary work of how a subset of such associations, for example, topical associations, can be acquired by filtering a network of lexical co-occurrences extracted from a corpus.
a dynamic bayesian framework to model context and memory in edit distance learning: an application to pronunciation classification. sitting at the intersection between statistics and machine learning, dynamic bayesian networks have been applied with much success in many domains, such as speech recognition, vision, and computational biology. while natural language processing increasingly relies on statistical methods, we think they have yet to use graphical models to their full potential. in this paper, we report on experiments in learning edit distance costs using dynamic bayesian networks and present results on a pronunciation classification task. by exploiting the ability within the dbn framework to rapidly explore a large model space, we obtain a 40% reduction in error rate compared to a previous transducer-based method of learning edit distance.
automatic creation of domain templates. recently, many natural language processing (nlp) applications have improved the quality of their output by using various machine learning techniques to mine information extraction (ie) patterns for capturing information from the input text. currently, to mine ie patterns one should know in advance the type of the information that should be captured by these patterns. in this work we propose a novel methodology for corpus analysis based on cross-examination of several document collections representing different instances of the same domain. we show that this methodology can be used for automatic domain template creation. as the problem of automatic domain template creation is rather new, there is no well-defined procedure for the evaluation of the domain template quality. thus, we propose a methodology for identifying what information should be present in the template. using this information we evaluate the automatically created domain templates through the text snippets retrieved according to the created templates.
using lexical dependency and ontological knowledge to improve a detailed syntactic and semantic tagger of english. this paper presents a detailed study of the integration of knowledge from both dependency parses and hierarchical word ontologies into a maximum-entropy-based tagging model that simultaneously labels words with both syntax and semantics. our findings show that information from both these sources can lead to strong improvements in overall system accuracy: dependency knowledge improved performance over all classes of word, and knowledge of the position of a word in an on-tological hierarchy increased accuracy for words not seen in the training data. the resulting tagger offers the highest reported tagging accuracy on this tagset to date.
incorporating non-local information into information extraction systems by gibbs sampling. most current statistical natural language processing models use only local features so as to permit dynamic programming in inference, but this makes them unable to fully account for the long distance structure that is prevalent in language use. we show how to solve this dilemma with gibbs sampling, a simple monte carlo method used to perform approximate inference in factored probabilistic models. by using simulated annealing in place of viterbi decoding in sequence models such as hmms, cmms, and crfs, it is possible to incorporate non-local structure while preserving tractable inference. we use this technique to augment an existing crf-based information extraction system with long-distance dependency models, enforcing label consistency and extraction template consistency constraints. this technique results in an error reduction of up to 9% over state-of-the-art systems on two established information extraction tasks.
a layered approach to nlp-based information retrieval. a layered approach to information retrieval permits the inclusion of multiple search engines as well as multiple databases, with a natural language layer to convert english queries for use by the various search engines. the nlp layer incorporates morphological analysis, noun phrase syntax, and semantic expansion based on word-net.
offline strategies for online question answering: answering questions before they are asked. recent work in question answering has focused on web-based systems that extract answers using simple lexico-syntactic patterns. we present an alternative strategy in which patterns are used to extract highly precise relational information offline, creating a data repository that is used to efficiently answer questions. we evaluate our strategy on a challenging subset of questions, i.e. "who is ..." questions, against a state of the art web-based question answering system. results indicate that the extracted relations answer 25% more questions correctly and do so three orders of magnitude faster than the state of the art system.
structure-sharing in lexical representation. the lexicon now plays a central role in our implementation of a head-driven phrase structure grammar (hpsg), given the massive relocation into the lexicon of linguistic information that was carried by the phrase structure rules in the old gpsg system. hpsg's grammar contains fewer than twenty (very general) rules; its predecessor required over 350 to achieve roughly the same coverage. this simplification of the grammar is made possible by an enrichment of the structure and content of lexical entries, using both inheritance mechanisms and lexical rules to represent the linguistic information in a general and efficient form. we will argue that our mechanisms for structure-sharing not only provide the ability to express important linguistic generalization about the lexicon, but also make possible an efficient, readily modifiable implementation that we find quite adequate for continuing development of a large natural language system.
factorizing complex models: a case study in mention detection. as natural language understanding research advances towards deeper knowledge modeling, the tasks become more and more complex: we are interested in more nuanced word characteristics, more linguistic properties, deeper semantic and syntactic features. one such example, explored in this article, is the mention detection and recognition task in the automatic content extraction project, with the goal of identifying named, nominal or pronominal references to real-world entities---mentions---and labeling them with three types of information: entity type, entity subtype and mention type. in this article, we investigate three methods of assigning these related tags and compare them on several data sets. a system based on the methods presented in this article participated and ranked very competitively in the ace'04 evaluation.
dynamic nonlocal language modeling via hierarchical topic-based adaptation. this paper presents a novel method of generating and applying hierarchical, dynamic topic-based language models. it proposes and evaluates new cluster generation, hierarchical smoothing and adaptive topic-probability estimation techniques. these combined models help capture long-distance lexical dependencies. experiments on the broadcast news corpus show significant improvement in perplexity (10.5% overall and 33.5% on target vocabulary).
free indexation: combinatorial analysis and a compositional algorithm. the principle known as 'free indexation' plays an important role in the determination of the referential properties of noun phrases in the principle-and-parameters language framework. first, by investigating the combinatorics of free indexation, we show that the problem of enumerating all possible indexings requires exponential time. secondly, we exhibit a provably optimal free indexation algorithm.
on reversing the generation process in optimality theory. optimality theory, a constraint-based phonology and morphology paradigm, has allowed linguists to make elegant analyses of many phenomena, including infixation and reduplication. in this work-in-progress, we build on the work of ellison (1994) to investigate the possibility of using ot as a parsing tool that derives underlying forms from surface forms.
a maximum entropy/minimum divergence translation model. i present empirical comparisons between a linear combination of standard statistical language and translation models and an equivalent maximum entropy/minimum divergence (memd) model, using several different methods for automatic feature selection. the memd model significantly outperforms the standard model in test corpus perplexity, even though it has far fewer parameters.
multimodal generation in the comic dialogue system. we describe how context-sensitive, user-tailored output is specified and produced in the comic multimodal dialogue system. at the conference, we will demonstrate the user-adapted features of the dialogue manager and text planner.
guiding a constraint dependency parser with supertags. we investigate the utility of supertag information for guiding an existing dependency parser of german. using weighted constraints to integrate the additionally available information, the decision process of the parser is influenced by changing its preferences, without excluding alternative structural interpretations from being considered. the paper reports on a series of experiments using varying models of supertags that significantly increase the parsing accuracy. in addition, an upper bound on the accuracy that can be achieved with perfect supertags is estimated.
hybrid parsing: using probabilistic models as predictors for a symbolic parser. in this paper we investigate the benefit of stochastic predictor components for the parsing quality which can be obtained with a rule-based dependency grammar. by including a chunker, a supertagger, a pp attacher, and a fast probabilistic parser we were able to improve upon the baseline by 3.2%, bringing the overall labelled accuracy to 91.1% on the german negra corpus. we attribute the successful integration to the ability of the underlying grammar model to combine uncertain evidence in a soft manner, thus avoiding the problem of error propagation.
the benefit of stochastic pp attachment to a rule-based parser. to study pp attachment disambiguation as a benchmark for empirical methods in natural language processing it has often been reduced to a binary decision problem (between verb or noun attachment) in a particular syntactic configuration. a parser, however, must solve the more general task of deciding between more than two alternatives in many different contexts. we combine the attachment predictions made by a simple model of lexical attraction with a full-fledged parser of german to determine the actual benefit of the subtask to parsing. we show that the combination of data-driven and rule-based components can reduce the number of all parsing errors by 14% and raise the attachment accuracy for dependency parsing of german to an unprecedented 92%.
from route descriptions to sketches: a model for a text-to-image translator. this paper deals with the automatic translation of route descriptions into graphic sketches. we discuss some general problems implied by such inter-mode transcription. we propose a model for an automatic text-to-image translator with a two-stage intermediate representation in which the linguistic representation of a route description precedes the creation of its conceptual representation.
learning more effective dialogue strategies using limited dialogue move features. we explore the use of restricted dialogue contexts in reinforcement learning (rl) of effective dialogue strategies for information seeking spoken dialogue systems (e.g. communicator (walker et al., 2001)). the contexts we use are richer than previous research in this area, e.g. (levin and pieraccini, 1997; scheffler and young, 2001; singh et al., 2002; pietquin, 2004), which use only slot-based information, but are much less complex than the full dialogue "information states" explored in (henderson et al., 2005), for which tractabe learning is an issue. we explore how incrementally adding richer features allows learning of more effective dialogue strategies. we use 2 user simulations learned from communicator data (walker et al., 2001; georgila et al., 2005b) to explore the effects of different features on learned dialogue strategies. our results show that adding the dialogue moves of the last system and user turns increases the average reward of the automatically learned strategies by 65.9% over the original (hand-coded) communicator systems, and by 7.8% over a baseline rl policy that uses only slot-status features. we show that the learned strategies exhibit an emergent "focus switching" strategy and effective use of the 'give help' action.
licensing and tree adjoining grammar in government binding parsing. this paper presents an implemented, psychologically plausible parsing model for government binding theory grammars. i make use of two main ideas: (1) a generalization of the licensing relations of [abney, 1986] allows for the direct encoding of certain principles of grammar (e.g. theta criterion, case filter) which drive structure building; (2) the working space of the parser is constrained to the domain determined by a tree adjoining grammar elementary tree. all dependencies and constraints are localized within this bounded structure. the resultant parser operates in linear time and allows for incremental semantic interpretation and determination of grammaticality.
integrated shallow and deep parsing: topp meets hpsg. we present a novel, data-driven method for integrated shallow and deep parsing. mediated by an xml-based multi-layer annotation architecture, we interleave a robust, but accurate stochastic topological field parser of german with a constraint-based hpsg parser. our annotation-based method for dovetailing shallow and deep phrasal constraints is highly flexible, allowing targeted and fine-grained guidance of constraint-based parsing. we conduct systematic experiments that demonstrate substantial performance gains.
incorporating context information for the extraction of terms. the information used for the extraction of terms can be considered as rather 'internal', i.e. coming from the candidate string itself. this paper presents the incorporation of 'external' information derived from the context of the candidate string. it is embedded to the c-value approach for automatic term recognition (atr), in the form of weights constructed from statistical characteristics of the context words of the candidate string.
independence assumptions considered harmful. many current approaches to statistical language modeling rely on independence assumptions between the different explanatory variables. this results in models which are computationally simple, but which only model the main effects of the explanatory variables on the response variable. this paper presents an argument in favor of a statistical approach that also models the interactions between the explanatory variables. the argument rests on empirical evidence from two series of experimetns concerning automatic ambiguity resolution.
semi-supervised training for statistical word alignment. we introduce a semi-supervised approach to training for statistical machine translation that alternates the traditional expectation maximization step that is applied on a large training corpus with a discriminative step aimed at increasing word-alignment quality on a small, manually word-aligned sub-corpus. we show that our algorithm leads not only to improved alignments but also to machine translation outputs of higher quality.
toward general-purpose learning for information extraction. two trends are evident in the recent evolution of the field of information extraction: a preference for simple, often corpus-driven techniques over linguistically sophisticated ones; and a broadening of the central problem definition to include many non-traditional text domains. this development calls for information extraction systems which are as retargetable and general as possible. here, we describe srv, a learning architecture for information extraction which is designed for maximum generality and flexibility. srv can exploit domain-specific information, including linguistic syntax and lexical information, in the form of features provided to the system explicitly as input for training. this process is illustrated using a domain created from reuters corporate acquisitions articles. features are derived from two general-purpose nlp systems, sleator and temperly's link grammar parser and wordnet. experiments compare the learner's performance with and without such linguistic information. surprisingly, in many cases, the system performs as well without this information as with it.
a general computational treatment of the comparative. we present a general treatment of the comparative that is based on more basic linguistic elements so that the underlying system can be effectively utilized: in the syntactic analysis phase, the comparative is treated the same as similar structures; in the syntactic regularization phase, the comparative is transformed into a standard form so that subsequent processing is basically unaffected by it. the scope of quantifiers under the comparative is also integrated into the system in a general way.
semi-supervised learning of partial cognates using bilingual bootstrapping. partial cognates are pairs of words in two languages that have the same meaning in some, but not all contexts. detecting the actual meaning of a partial cognate in context can be useful for machine translation tools and for computer-assisted language learning tools. in this paper we propose a supervised and a semi-supervised method to disambiguate partial cognates between two languages: french and english. the methods use only automatically-labeled data; therefore they can be applied for other pairs of languages as well. we also show that our methods perform well when using corpora from different domains.
japanese morphological analyzer using word co-occurence -jtag. we developed a japanese morphological analyzer that uses the co-occurrence of words to select the correct sequence of words in an unsegmented japanese sentence. the co-occurrence information can be obtained from cases where the system incorrectly analyzes sentences. as the amount of information increases, the accuracy of the system increases with a small risk of degradation. experimental results show that the proposed system assigns the correct phonological representations to unsegmented japanese sentences more precisely than do other popular systems.
minimal recursion semantics as dominance constraints: translation, evaluation, and analysis. we show that a practical translation of mrs descriptions into normal dominance constraints is feasible. we start from a recent theoretical translation and verify its assumptions on the outputs of the english resource grammar (erg) on the redwoods corpus. the main assumption of the translation---that all relevant underspecified descriptions are nets---is validated for a large majority of cases; all non-nets computed by the erg seem to be systematically incomplete.
utilizing the world wide web as an encyclopedia: extracting term descriptions from semi-structured texts. in this paper, we propose a method to extract descriptions of technical terms from web pages in order to utilize the world wide web as an encyclopedia. we use linguistic patterns and html text structures to extract text fragments containing term descriptions. we also use a language model to discard extraneous descriptions, and a clustering method to summarize resultant descriptions. we show the effectiveness of our method by way of experiments.
oganizing encyclopedic knowledge based on the web and its application to question answering. we propose a method to generate large-scale encyclopedic knowledge, which is valuable for much nlp research, based on the web. we first search the web for pages containing a term in question. then we use linguistic patterns and html structures to extract text fragments describing the term. finally, we organize extracted term descriptions based on word senses and domains. in addition, we apply an automatically generated encyclopedia to a question answering system targeting the japanese information-technology engineers examination.
an implemented description of japanese: the lexeed dictionary and the hinoki treebank. in this paper we describe the current state of a new japanese lexical resource: the hinoki treebank. the treebank is built from dictionary definition sentences, and uses an hpsg based japanese grammar to encode both syntactic and semantic information. it is combined with an ontology based on the definition sentences to give a detailed sense level description of the most familiar 28,000 words of japanese.
using bilingual comparable corpora and semi-supervised clustering for topic tracking. we address the problem dealing with skewed data, and propose a method for estimating effective training stories for the topic tracking task. for a small number of labelled positive stories, we extract story pairs which consist of positive and its associated stories from bilingual comparable corpora. to overcome the problem of a large number of labelled negative stories, we classify them into some clusters. this is done by using k-means with em. the results on the tdt corpora show the effectiveness of the method.
a hardware algorithm for high speed morpheme extraction and its implementation. this paper describes a new hardware algorithm for morpheme extraction and its implementation on a specific machine (mex-i), as the first step toward achieving natural language parsing accelerators. it also shows the machine's performance, 100--1,000 times faster than a personal computer. this machine can extract morphemes from 10,000 character japanese text by searching an 80,000 morpheme dictionary in 1 second. it can treat multiple text streams, which are composed of character candidates, as well as one text stream. the algorithm is implemented on the machine in linear time for the number of candidates, while conventional sequential algorithms are implemented in combinational time.
a pattern matching method for finding noun and proper noun translations from noisy parallel corpora. we present a pattern matching method for compiling a bilingual lexicon of nouns and proper nouns from unaligned, noisy parallel texts of asian/indo-european language pairs. tagging information of one language is used. word frequency and position information for high and low frequency words are represented in two different vector forms for pattern matching. new anchor point finding and noise elimination techniques are introduced. we obtained a 73.1% precision. we also show how the results can be used in the compilation of domain-specific noun phrases.
robust word sense translation by em learning of frame semantics. we propose a robust method of automatically constructing a bilingual word sense dictionary from readily available monolingual ontologies by using estimation-maximization, without any annotated training data or manual tuning. we demonstrate our method on the english framenet and chinese hownet structures. owing to the robustness of em iterations in improving translation likelihoods, our word sense translation accuracies are very high, at 82% on average, for the 11 most ambiguous words in the english framenet with 5 senses or more. we also carried out a pilot study on using this automatically generated bilingual word sense dictionary to choose the best translation candidates and show the first significant evidence that frame semantics are useful for translation disambiguation. translation disambiguation accuracy using frame semantics is 75%, compared to 15% by using dictionary glossing only. these results demonstrate the great potential for future application of bilingual frame semantics to machine translation tasks.
automatic speech recognition and its application to information extraction. this paper describes recent progress and the author's perspectives of speech recognition technology. applications of speech recognition technology can be classified into two main areas, dictation and human-computer dialogue systems. in the dictation domain, the automatic broadcast news transcription is now actively investigated, especially under the darpa project. the broadcast news dictation technology has recently been integrated with information extraction and retrieval technology and many application systems, such as automatic voice document indexing and retrieval systems, are under development. in the human-computer interaction domain, a variety of experimental systems for information retrieval through spoken dialogue are being investigated. in spite of the remarkable recent progress, we are still behind our ultimate goal of understanding free conversational speech uttered by any speaker under any environment. this paper also describes the most important research issues that we should attack in order to advance to our ultimate goal of fluent speech recognition.
splitting long or ill-formed input for robust spoken-language translation. this paper proposes an input-splitting method for translating spoken-language which includes many long or ill-formed expressions. the proposed method splits input into well-balanced translation units based on a semantic distance calculation. the splitting is performed during left-to-right parsing, and does not degrade translation efficiency. the complete translation result is formed by concatenating the partial translation results of each split unit. the proposed method can be incorporated into frameworks like tdmt, which utilize left-to-right parsing and a score for a substructure. experimental results show that the proposed method gives tdmt the following advantages: (1) elimination of null outputs, (2) splitting of utterances into sentences, and (3) robust translation of erroneous speech recognition results.
combining acoustic and pragmatic features to predict recognition performance in spoken dialogue systems. we use machine learners trained on a combination of acoustic confidence and pragmatic plausibility features computed from dialogue context to predict the accuracy of incoming n-best recognition hypotheses to a spoken dialogue system. our best results show a 25% weighted f-score improvement over a baseline system that implements a "grammar-switching" approach to context-sensitive speech recognition.
automatic extraction of subcorpora based on subcategorization frames from a part-of-speech tagged corpus. this paper presents a method for extracting subcorpora documenting different subcategorization frames for verbs, nouns, and adjectives in the 100 mio. word british national corpus. the extraction tool consists of a set of batch files for use with the corpus query processor (cqp), which is part of the ims corpus workbench (cf. christ 1994a, b). a macroprocessor has been developed that allows the user to specify in a simple input file which subcorpora are to be created for a given lemma.the resulting subcorpora can be used (1) to provide evidence for the subcategorization properties of a given lemma, and to facilitate the selection of corpus lines for lexicographic research, and (2) to determine the frequencies of different syntactic contexts of each lemma.
a program for aligning sentences in bilingual corpora. researchers in both machine translation (e.g., brown et al. 1990) and bilingual lexicography (e.g., klavans and tzoukermann 1990) have recently become interested in studying bilingual corpora, bodies of text such as the canadian hansards (parliamentary proceedings), which are available in multiple languages (such as french and english). one useful step is to align the sentences, that is, to identify correspondences between sentences in one language and sentences in the other language.this paper will describe a method and a program (align) for aligning sentences based on a simple statistical model of character lengths. the program uses the fact that longer sentences in one language tend to be translated into longer sentences in the other language, and that shorter sentences tend to be translated into shorter sentences. a probabilistic score is assigned to each proposed correspondence of sentences, based on the scaled difference of lengths of the two sentences (in characters) and the variance of this difference. this probabilistic score is used in a dynamic programming framework to find the maximum likelihood alignment of sentences.it is remarkable that such a simple approach works as well as it does. an evaluation was performed based on a trilingual corpus of economic reports issued by the union bank of switzerland (ubs) in english, french, and german. the method correctly aligned all but 4% of the sentences. moreover, it is possible to extract a large subcorpus that has a much smaller error rate. by selecting the best-scoring 80% of the alignments, the error rate is reduced from 4% to 0.7%. there were more errors on the english-french subcorpus than on the english-german subcorpus, showing that error rates will depend on the corpus considered; however, both were small enough to hope that the method will be useful for many language pairs.to further research on bilingual corpora, a much larger sample of canadian hansards (approximately 90 million words, half in english and and half in french) has been aligned with the align program and will be available through the data collection initiative of the association for computational linguistics (acl/dci). in addition, in order to facilitate replication of the align program, an appendix is provided with detailed c-code of the more difficult core of the align program.
estimating upper and lower bounds on the performance of word-sense disambiguation programs. we have recently reported on two new word-sense disambiguation systems, one trained on bilingual material (the canadian hansards) and the other trained on monolingual material (roget's thesaurus and grolier's encyclopedia). after using both the monolingual and bilingual classifiers for a few months, we have convinced ourselves that the performance is remarkably good. nevertheless, we would really like to be able to make a stronger statement, and therefore, we decided to try to develop some more objective evaluation measures. although there has been a fair amount of literature on sense-disambiguation, the literature does not offer much guidance in how we might establish the success or failure of a proposed solution such as the two systems mentioned in the previous paragraph. many papers avoid quantitative evaluations altogether, because it is so difficult to come up with credible estimates of performance.this paper will attempt to establish upper and lower bounds on the level of performance that can be expected in an evaluation. an estimate of the lower bound of 75% (averaged over ambiguous types) is obtained by measuring the performance produced by a baseline system that ignores context and simply assigns the most likely sense in all cases. an estimate of the upper bound is obtained by assuming that our ability to measure performance is largely limited by our ability obtain reliable judgments from human informants. not surprisingly, the upper bound is very dependent on the instructions given to the judges. jorgensen, for example, suspected that lexicographers tend to depend too much on judgments by a single informant and found considerable variation over judgments (only 68% agreement), as she had suspected. in our own experiments, we have set out to find word-sense disambiguation tasks where the judges can agree often enough so that we could show that they were outperforming the baseline system. under quite different conditions, we have found 96.8% agreement over judges.
scalable inference and training of context-rich syntactic translation models. statistical mt has made great progress in the last few years, but current translation models are weak on re-ordering and target language fluency. syntactic approaches seek to remedy these problems. in this paper, we take the framework for acquiring multi-level syntactic translation rules of (galley et al., 2004) from aligned tree-string pairs, and present two main extensions of their approach: first, instead of merely computing a single derivation that minimally explains a sentence pair, we construct a large number of derivations that include contextually richer rules, and account for multiple interpretations of unaligned words. second, we propose probability estimates and a training procedure for weighting these rules. we contrast different approaches on real examples, show that our estimates based on multiple derivations favor phrasal re-orderings that are linguistically better motivated, and establish that our larger rules provide a 3.63 bleu point increase over minimal rules.
discourse segmentation of multi-party conversation. we present a domain-independent topic segmentation algorithm for multi-party speech. our feature-based algorithm combines knowledge about content using a text-based algorithm as a feature and about form using linguistic and acoustic cues about topic shifts extracted from speech. this segmentation algorithm uses automatically induced decision rules to combine the different features. the embedded text-based algorithm builds on lexical cohesion and has performance comparable to state-of-the-art algorithms based on lexical information. a significant error reduction is obtained by combining the two knowledge sources.
identifying agreement and disagreement in conversational speech: use of bayesian networks to model pragmatic dependencies. we describe a statistical approach for modeling agreements and disagreements in conversational interaction. our approach first identifies adjacency pairs using maximum entropy ranking based on a set of lexical, durational, and structural features that look both forward and backward in the discourse. we then classify utterances as agreement or disagreement using these adjacency pairs and features that represent various pragmatic influences of previous agreement or disagreement on the current utterance. our approach achieves 86.9% accuracy, a 4.9% increase over previous work.
a synopsis of learning to recognize names across languages. the development of natural language processing (nlp) systems that perform machine translation (mt) and information retrieval (ir) has highlighted the need for the automatic recognition of proper names. while various name recognizers have been developed, they suffer from being too limited; some only recognize one name class, and all are language specific. this work develops an approach to multilingual name recognition that uses machine learning and a portable framework to simplify the porting task by maximizing reuse and automation.
semantic-head based resolution of scopal ambiguities. we introduce an algorithm for scope resolution in underspecified semantic representations. scope preferences are suggested on the basis of semantic argument structure. the major novelty of this approach is that, while maintaining an (scopally) underspecified semantic representation, we at the same time suggest a resolution possibility. the algorithm has been implemented and tested in a large-scale system and fared quite well: 28% of the utterances were ambiguous, 80% of these were correctly interpreted, leaving errors in only 5.7% of the utterance set.
machine-learned contexts for linguistic operations in german sentence realization. we show that it is possible to learn the contexts for linguistic operations which map a semantic representation to a surface syntactic tree in sentence realization with high accuracy. we cast the problem of learning the contexts for the linguistic operations as classification tasks, and apply straightforward machine learning techniques, such as decision tree learning. the training data consist of linguistic features extracted from syntactic and semantic representations produced by a linguistic analysis system. the target features are extracted from links to surface syntax trees. our evidence consists of four examples from the german sentence realization system code-named amalgam: case assignment, assignment of verb position features, extraposition, and syntactic aggregation.
exploring asymmetric clustering for statistical language modeling. the n-gram model is a stochastic model, which predicts the next word (predicted word) given the previous words (conditional words) in a word sequence. the cluster n-gram model is a variant of the n-gram model in which similar words are classified in the same cluster. it has been demonstrated that using different clusters for predicted and conditional words leads to cluster models that are superior to classical cluster models which use the same clusters for both words. this is the basis of the asymmetric cluster model (acm) discussed in our study. in this paper, we first present a formal definition of the acm. we then describe in detail the methodology of constructing the acm. the effectiveness of the acm is evaluated on a realistic application, namely japanese kana-kanji conversion. experimental results show substantial improvements of the acm in comparison with classical cluster models and word n-gram models at the same model size. our analysis shows that the high-performance of the acm lies in the asymmetry of the model.
distribution-based pruning of backoff language models. we propose a distribution-based pruning of n-gram backoff language models. instead of the conventional approach of pruning n-grams that are infrequent in training data, we prune n-grams that are likely to be infrequent in a new document. our method is based on the n-gram distribution i.e. the probability that an n-gram occurs in a new document. experimental results show that our method performed 7--9% (word perplexity reduction) better than conventional cutoff methods.
improved source-channel models for chinese word segmentation. this paper presents a chinese word segmentation system that uses improved source-channel models of chinese sentence generation. chinese words are defined as one of the following four types: lexicon words, morphologically derived words, factoids, and named entities. our system provides a unified approach to the four fundamental features of word-level chinese language processing: (1) word segmentation, (2) morphological analysis, (3) factoid detection, and (4) named entity recognition. the performance of the system is evaluated on a manually annotated test set, and is also compared with several state-of-the-art systems, taking into account the fact that the definition of chinese words often varies from system to system.
unsupervised learning of dependency structure for language modeling. this paper presents a dependency language model (dlm) that captures linguistic constraints via a dependency structure, i.e., a set of probabilistic dependencies that express the relations between headwords of each phrase in a sentence by an acyclic, planar, undirected graph. our contributions are three-fold. first, we incorporate the dependency structure into an n-gram language model to capture long distance word dependency. second, we present an unsupervised learning method that discovers the dependency structure of a sentence using a bootstrapping procedure. finally, we evaluate the proposed models on a realistic application (japanese kana-kanji conversion). experiments show that the best dlm achieves an 11.3% error rate reduction over the word trigram model.
approximation lasso methods for language modeling. lasso is a regularization method for parameter estimation in linear models. it optimizes the model parameters with respect to a loss function subject to model complexities. this paper explores the use of lasso for statistical language modeling for text input. owing to the very large number of parameters, directly optimizing the penalized lasso loss function is impossible. therefore, we investigate two approximation methods, the boosted lasso (blasso) and the forward stagewise linear regression (fslr). both methods, when used with the exponential loss function, bear strong resemblance to the boosting algorithm which has been used as a discriminative training method for language modeling. evaluations on the task of japanese text input show that blasso is able to produce the best approximation to the lasso solution, and leads to a significant improvement, in terms of character error rate, over boosting and the traditional maximum likelihood estimation.
improving language model size reduction using better pruning criteria. reducing language model (lm) size is a critical issue when applying a lm to realistic applications which have memory constraints. in this paper, three measures are studied for the purpose of lm pruning. they are probability, rank, and entropy. we evaluated the performance of the three pruning criteria in a real application of chinese text input in terms of character error rate (cer). we first present an empirical comparison, showing that rank performs the best in most cases. we also show that the high-performance of rank lies in its strong correlation with error rate. we then present a novel method of combining two criteria in model pruning. experimental results show that the combined criterion consistently leads to smaller models than the models pruned using either of the criteria separately, at the same cer.
towards a self-extending parser. this paper discusses an approach to incremental learning in natural language processing. the technique of projecting and integrating semantic constraints to learn word definitions is analyzed as implemented in the politics system. extensions and improvements of this technique are developed. the problem of generalizing existing word meanings and understanding metaphorical uses of words is addressed in terms of semantic constraint integration.
refined lexikon models for statistical machine translation using a maximum entropy approach. typically, the lexicon models used in statistical machine translation systems do not include any kind of linguistic or contextual information, which often leads to problems in performing a correct word sense disambiguation. one way to deal with this problem within the statistical framework is to use maximum entropy methods. in this paper, we present how to use this type of information within a statistical machine translation system. we show that it is possible to significantly decrease training and test corpus perplexity of the translation models. in addition, we perform a rescoring of n-best lists using our maximum entropy model and thereby yield an improvement in translation quality. experimental results are presented on the so-called "verbmobil task".
unifying parallels. i show that the equational treatment of ellipsis proposed in (dalrymple et al., 1991) can further be viewed as modeling the effect of parallelism on semantic interpretation. i illustrate this claim by showing that the account straightforwardly extends to a general treatment of sloppy identity on the one hand, and to deaccented foci on the other. i also briefly discuss the results obtained in a prototype implementation.
generating minimal definite descriptions. the incremental algorithm introduced in (dale and reiter, 1995) for producing distinguishing descriptions does not always generate a minimal description. in this paper, i show that when generalised to sets of individuals and disjunctive properties, this approach might generate unnecessarily long and ambiguous and/or epistemically redundant descriptions. i then present an alternative, constraint-based algorithm and show that it builds on existing related algorithms in that (i) it produces minimal descriptions for sets of individuals using positive, negative and disjunctive properties, (ii) it straightforwardly generalises to n-ary relations and (iii) it is integrated with surface realisation.
efficient parsing for french. parsing with categorial grammars often leads to problems such as proliferating lexical ambiguity, spurious parses and overgeneration. this paper presents a parser for french developed on an unification based categorial grammar (fg) which avoids these problems. this parser is a bottom-up chart parser augmented with a heuristic eliminating spurious parses. the unicity and completeness of parsing are proved.
higher-order coloured unification and natural language semantics. in this paper, we show that higher-order coloured unification - a form of unification developed for automated theorem proving - provides a general theory for modeling the interface between the interpretation process and other sources of linguistic, non semantic information. in particular, it provides the general theory for the primary occurrence restriction which (dalrymple et al., 1991)'s analysis called for.
coreference handling in xmg. we claim that existing specification languages for tree based grammars fail to adequately support identifier managment. we then show that xmg (extensible meta-grammar) provides a sophisticated treatment of identifiers which is effective in supporting a linguist-friendly grammar design.
generating with a grammar based on tree descriptions: a constraint-based approach. while the generative view of language processing builds bigger units out of smaller ones by means of rewriting steps, the axiomatic view eliminates invalid linguistic structures out of a set of possible structures by means of well formedness principles. we present a generator based on the axiomatic view and argue that when combined with a tag-like grammar and a flat semantics, this axiomatic view permits avoiding drawbacks known to hold either of top-down or of bottom-up generators.
acquiring receptive morphology: a connectionist model. this paper describes a modular connectionist model of the acquisition of receptive inflectional morphology. the model takes inputs in the form of phones one at a time and outputs the associated roots and inflections. simulations using artificial language stimuli demonstrate the capacity of the model to learn suffixation, prefixation, infixation, circumfixation, mutation, template, and deletion rules. separate network modules responsible for syllables enable to the network to learn simple reduplication rules as well. the model also embodies constraints against association-line crossing.
conceptual coherence in the generation of referring expressions. one of the challenges in the automatic generation of referring expressions is to identify a set of domain entities coherently, that is, from the same conceptual perspective. we describe and evaluate an algorithm that generates a conceptually coherent description of a target set. the design of the algorithm is motivated by the results of psycholinguistic experiments.
a geometric view on bilingual lexicon extraction from comparable corpora. we present a geometric view on bilingual lexicon extraction from comparable corpora, which allows to re-interpret the methods proposed so far and identify unresolved problems. this motivates three new methods that aim at solving these problems. empirical evaluation shows the strengths and weaknesses of these methods, as well as a significant gain in the accuracy of extracted lexicons.
processing broadcast audio for information access. this paper addresses recent progress in speaker-independent, large vocabulary, continuous speech recognition, which has opened up a wide range of near and mid-term applications. one rapidly expanding application area is the processing of broadcast audio for information access. at limsi, broadcast news transcription systems have been developed for english, french, german, mandarin and portuguese, and systems for other languages are under development. audio indexation must take into account the specificities of audio data, such as needing to deal with the continuous data stream and an imperfect word transcription. some near-term applications areas are audio data mining, selective dissemination of information and media monitoring.
growing semantic grammars. a critical path in the development of natural language understanding (nlu) modules lies in the difficulty of defining a mapping from words to semantics: usually it takes in the order of years of highly-skilled labor to develop a semantic mapping, e.g., in the form of a semantic grammar, that is comprehensive enough for a given domain. yet, due to the very nature of human language, such mapping invariably fail to achieve full coverage on unseen data. acknowledging the impossibility of stating a priori all the surface forms by which a concept can be expressed, we present gsg: an empathic computer system for the rapid deployment of nlu front-ends and their dynamic customization by non-expert end-users. given a new domain for which an nlu front-end is to be developed, two stages are involved. in the authoring stage, gsg aids the developer in the construction of a simple domain model and a kernel analysis grammar. then, in the run-time stage, gsg provides the end-user with an interactive environment in which the kernel grammar is dynamically extended. three learning methods are employed in the acquisition of semantic mappings from unseen data: (i) parser predictions, (ii) hidden understanding model, and (iii) end-user paraphrases. a baseline version of gsg has been implemented and preliminary experiments show promising results.
priority union and generalization in discourse grammars. we describe an implementation in carpenter's typed feature formalism, ale, of a discourse grammar of the kind proposed by scha, polanyi, et al. we examine their method for resolving parallelism-dependent anaphora and show that there is a coherent feature-structural rendition of this type of grammar which uses the operations of priority union and generalization. we describe an augmentation of the ale system to encompass these operations and we show that an appropriate choice of definition for priority union gives the desired multiple output for examples of vp-ellipsis which exhibit a strict/sloppy ambiguity.
dynamic programming for parsing and estimation of stochastic unification-based grammars. stochastic unification-based grammars (subgs) define exponential distributions over the parses generated by a unification-based grammar (ubg). existing algorithms for parsing and estimation require the enumeration of all of the parses of a string in order to determine the most likely one, or in order to calculate the statistics needed to estimate a grammar from a training corpus. this paper describes a graph-based dynamic programming algorithm for calculating these statistics from the packed ubg parse representations of maxwell and kaplan (1995) which does not require enumerating all parses. like many graphical algorithms, the dynamic programming algorithm's complexity is worst-case exponential, but is often polynomial. the key observation is that by using maxwell and kaplan packed representations, the required statistics can be rewritten as either the max or the sum of a product of functions. this is exactly the kind of problem which can be solved by dynamic programming over graphical models.
xml-based data preparation for robust deep parsing. we describe the use of xml tokenisation, tagging and mark-up tools to prepare a corpus for parsing. our techniques are generally applicable but here we focus on parsing medline abstracts with the anlt wide-coverage grammar. hand-crafted grammars inevitably lack coverage but many coverage failures are due to inadequacies of their lexicons. we describe a method of gaining a degree of robustness by interfacing pos tag information with the existing lexicon. we also show that xml tools provide a sophisticated approach to pre-processing, helping to ameliorate the 'messiness' in real language data and improve parse performance.
on interpreting f-structures as udrss. we describe a method for interpreting abstract flat syntactic representations, lfg f-structures, as underspecified semantic representations, here underspecified discourse representation structures (udrss). the method establishes a one-to-one correspondence between subsets of the lfg and udrs formalisms. it provides a model theoretic interpretation and an inferential component which operates directly on underspecified representations for f-structures through the translation images of f-structures as udrss.
segment-based hidden markov models for information extraction. hidden markov models (hmms) are powerful statistical models that have found successful applications in information extraction (ie). in current approaches to applying hmms to ie, an hmm is used to model text at the document level. this modelling might cause undesired redundancy in extraction in the sense that more than one filler is identified and extracted. we propose to use hmms to model text at the segment level, in which the extraction process consists of two steps: a segment retrieval step followed by an extraction step. in order to retrieve extraction-relevant segments from documents, we introduce a method to use hmms to model and retrieve segments. our experimental results show that the resulting segment hmm ie system not only achieves near zero extraction redundancy, but also has better overall extraction performance than traditional document hmm ie systems.
an empirical evaluation of probabilistic lexicalized tree insertion grammars. we present an empirical study of the applicability of probabilistic lexicalized tree insertion grammars (pltig), a lexicalized counterpart to probabilistic context-free grammars (pcfg), to problems in stochastic natural-language processing. comparing the performance of pltigs, with non-hierarchical n-gram models and pcfgs, we show that pltig combines the best aspects of both, with language modeling capability comparable to n-gram models and pcfgs, we show that pltig combines the best aspects of both, with language modeling capability comparable to n-grams, and improved parsing performance over its nonlexicalized counterpart. furthermore, training of pltigs displays faster convergence than pcfgs.
entropy rate constancy in text. we present a constancy rate principle governing language generation. we show that this principle implies that local measures of entropy (ignoring context) should increase with the sentence number. we demonstrate that this is indeed the case by measuring entropy in three different ways. we also show that this effect has both lexical (which words are used) and non-lexical (how the words are used) causes.
anaphora resolution: short-term memory and focusing. anaphora resolution is the process of determining the referent of anaphors, such as definite noun phrases and pronouns, in a discourse. computational linguists, in modeling the process of anaphora resolution. have proposed the notion of focusing. focusing is the process, engaged in by a reader of selecting a subset of the discourse items and making them highly available for further computations. this paper provides a cognitive basis for anaphora resolution and focusing. human memory is divided into a short-term, an operating, and a long-term memory. short-term memory can only contain a small number of meaning units and its retrieval time is fast. short-term memory is divided into a cache and a buffer. the cache contains a subset of meaning units expressed in the previous sentences and the buffer holds a representation of the incoming sentence. focusing is realized in the cache that contains a subset of the most topical units and a subset of the most recent units in the text. the information stored in the cache is used to integrate the incoming sentence with the preceding discourse. pronouns should be used to refer to units in focus. operating memory contains a very large number of units but its retrieval time is slow. it contains the previous text units that are not in the cache. it comprises the text units not in focus. definite noun phrases should be used to refer to units not in focus. two empirical studies are described that demonstrate the cognitive basis for focusing, the use of definite noun pphrases to refer to antecedents not in focus. and the use of pronouns to refer to antecedents in focus.
word order in german: a formal dependency grammar using a topological hierarchy. this paper proposes a description of german word order including phenomena considered as complex, such as scrambling, (partial) vp fronting and verbal pied piping. our description relates a syntactic dependency structure directly to a topological hierarchy without resorting to movement or similar mechanisms.
mechanisms for mixed-initiative human-computer collaborative discourse. in this paper, we examine mechanisms for automatic dialogue initiative setting. we show how to incorporate initiative changing in a task-oriented human-computer dialogue system, and we evaluate the effects of initiative both analytically and via computer-computer dialogue simulation.
a polynomial parsing algorithm for the topological model: synchronizing constituent and dependency grammars, illustrated by german word order phenomena. this paper describes a minimal topology driven parsing algorithm for topological grammars that synchronizes a rewriting grammar and a dependency grammar, obtaining two linguistically motivated syntactic structures. the use of non-local slash and visitor features can be restricted to obtain a cky type analysis in polynomial time. german long distance phenomena illustrate the algorithm, bringing to the fore the procedural needs of the analyses of syntax-topology mismatches in constraint based approaches like for example hpsg.
one tokenization per source. we report in this paper the observation of one tokenization per source. that is, the same critical fragment in different sentences from the same source almost always realize one and the same of its many possible tokenizations. this observation is demonstrated very helpful in sentence tokenization practice, and is argued to be with far-reaching implications in natural language processing.
supervised grammar induction using training data with limited constituent information. corpus-based grammar induction generally relies on hand-parsed training data to learn the structure of the language. unfortunately, the cost of building large annotated corpora is prohibitively expensive. this work aims to improve the induction strategy when there are few labels in the training data. we show that the most informative linguistic constituents are the higher nodes in the parse trees, typically denoting complex noun phrases and sentential clauses. they account for only 20% of all constituents. for inducing grammars from sparsely labeled training data (e.g., only higher-level constituent labels), we propose an <i>adaptation</i> strategy, which produces grammars that parse almost as well as grammars induced from fully labeled corpora. our results suggest that for a partial parser to replace human annotators, it must be able to automatically extract higher-level constituents rather than base noun phrases.
fast decoding and optimal decoding for machine translation. a good decoding algorithm is critical to the success of any statistical machine translation system. the decoder's job is to find the translation that is most likely according to set of previously learned parameters (and a formula for combining them). since the space of possible translations is extremely large, typical decoding algorithms are only able to examine a portion of it, thus risking to miss good solutions. in this paper, we compare the speed and output quality of a traditional stack-based decoding algorithm with two new decoders: a fast greedy decoder and a slow but optimal decoder that treats decoding as an integer-programming optimization problem.
memory capacity and sentence processing. the limited capacity of working memory is intrinsic to human sentence processing, and therefore must be addressed by any theory of human sentence processing. this paper gives a theory of garden-path effects and processing overload that is based on simple assumptions about human short term memory capacity.
accessing germanet data and computing semantic relatedness. we present an api developed to access germanet, a lexical semantic database for german represented in xml. the api provides a set of software functions for parsing and retrieving information from germanet. then, we present a case study which builds upon the germanet api and implements an application for computing semantic relatedness according to five different metrics. the package can, again, serve as a software library to be deployed in natural language processing applications. a graphical user interface allows to interactively experiment with the system.
grammar viewed as a functional part of a cognitive system. how can grammar be viewed as a functional part of a cognitive system? given a neural basis for the processing control paradigm of language performance, what roles does "grammar" play? is there evidence to suggest that grammatical processing can be independent from other aspects of language processing?this paper will focus on these issues and suggest answers within the context of one computational solution. the example model of sentence comprehension, hope, is intended to demonstrate both representational considerations for a grammar within such a system as well as to illustrate that by interpreting a grammar as a feedback control mechanism of a "neural-like" process, additional insights into language processing can be obtained.
subject-dependent co-occurence and word sense disambiguation. we describe a method for obtaining subject-dependent word sets relative to some (subject) domain. using the subject classifications given in the machine-redable version of longman's dictionary of contemporary english, we established subject-dependent co-occurrence links between words of the defining vocabulary to construct these "neighborhoods". here, we describe the application of these neighborhoods to information retrieval, and present a method of word sense disambiguation based on these co-occurrences, an extension of previous work.
would i lie to you? modelling misrepresentation and context in dialogue. in this paper we discuss a mechanism for modifying context in a tutorial dialogue. the context mechanism imposes a pedagogically motivated misrepresentation (pmm) on a dialogue to achieve instructional goals. in the paper, we outline several types of pmms and detail a particular pmm in a sample dialogue situation. while the notion of pmms are specifically oriented towards tutorial dialogue, misrepresentation has interesting implications for context in dialogue situations generally, and also suggests that grice's maxim of quality needs to be modified.
loosely tree-based alignment for machine translation. we augment a model of translation based on re-ordering nodes in syntactic trees in order to allow alignments not conforming to the original tree structure, while keeping computational complexity polynomial in the sentence length. this is done by adding a new subtree cloning operation to either tree-to-string or tree-to-tree alignment algorithms.
reduced n-gram models for english and chinese corpora. statistical language models should improve as the size of the n-grams increases from 3 to 5 or higher. however, the number of parameters and calculations, and the storage requirement increase very rapidly if we attempt to store all possible combinations of n-grams. to avoid these problems, the reduced n-grams' approach previously developed by o'boyle (1993) can be applied. a reduced n-gram language model can store an entire corpus's phrase-history length within feasible storage limits. another theoretical advantage of reduced n-grams is that they are closer to being semantically complete than traditional models, which include all n-grams. in our experiments, the reduced n-gram zipf curves are first presented, and compared with previously obtained conventional n-grams for both english and chinese. the reduced n-gram model is then applied to large english and chinese corpora. for english, we can reduce the model sizes, compared to 7-gram traditional model sizes, with factors of 14.6 for a 40-million-word corpus and 11.0 for a 500-million-word corpus while obtaining 5.8% and 4.2% improvements in perplexities. for chinese, we gain a 16.9% perplexity reductions and we reduce the model size by a factor larger than 11.2. this paper is a step towards the modeling of english and chinese using semantically complete phrases in an n-gram model.
automatic labeling of semantic roles. we present a system for identifying the semantic relationships, or semantic roles, filled by constituents of a sentence within a semantic frame. various lexical and syntactic features are derived from parse trees and used to derive statistical classifiers from hand-annotated training data.
a generalization of the offline parsable grammars. the offline parsable grammars apparently have enough formal power to describe human language, yet the parsing problem for these grammars is solvable. unfortunately they exclude grammars that use x-bar theory - and these grammars have strong linguistic justification. we define a more general class of unification grammars, which admits x-bar grammars while preserving the desirable properties of offline parsable grammars.
automatic induction of finite state transducers for simple phonological rules. this paper presents a method for learning phonological rules from sample pairs of underlying and surface forms, without negative evidence. the learned rules are represented as finite state transducers that accept underlying forms as input and generate surface forms as output. the algorithm for learning them is an extension of the ostia algorithm for learning general subsequential finite state transducers. although ostia is capable of learning arbitrary s.f.s.t's in the limit, large dictionaries of actual english pronunciations did not give enough samples to correctly induce phonological rules. we then augmented ostia with two kinds of knowledge specific to natural language phonology, biases from "universal grammar". one bias is that underlying phones are often realized as phonetically similar or identical surface phones. the other biases phonological rules to apply across natural phonological classes. the additions helped in learning more compact, accurate, and general transducers than the unmodified ostia algorithm. an implementation of the algorithm successfully learns a number of english postlexical rules.
arabic tokenization, part-of-speech tagging and morphological disambiguation in one fell swoop. we present an approach to using a morphological analyzer for tokenizing and morphologically tagging (including part-of-speech tagging) arabic words in one process. we learn classifiers for individual morphological features, as well as ways of using these classifiers to choose among entries from the output of the analyzer. we obtain accuracy rates on all tasks in the high nineties.
the necessity of parsing for predicate argument recognition. broad-coverage corpora annotated with semantic role, or argument structure, information are becoming available for the first time. statistical systems have been trained to automatically label semantic roles from the output of statistical parsers on unannotated text. in this paper, we quantify the effect of parser accuracy on these systems' performance, and examine the question of whether a flatter "chunked" representation of the input can be as effective for the purposes of semantic role identification.
magead: a morphological analyzer and generator for the arabic dialects. we present magead, a morphological analyzer and generator for the arabic language family. our work is novel in that it explicitly addresses the need for processing the morphology of the dialects. magead performs an on-line analysis to or generation from a root+pattern+features representation, it has separate phonological and orthographic representations, and it allows for combining morphemes from different dialects. we present a detailed evaluation of magead.
factoring synchronous grammars by sorting. synchronous context-free grammars (scfgs) have been successfully exploited as translation models in machine translation applications. when parsing with an scfg, computational complexity grows exponentially with the length of the rules, in the worst case. in this paper we examine the problem of factorizing each rule of an input scfg to a generatively equivalent set of rules, each having the smallest possible length. our algorithm works in time o(n log n), for each rule of length n. this improves upon previous results and solves an open problem about recognizing permutations that can be factored.
separable verbs in a reusable morphological dictionary for german. separable verbs are verbs with prefixes which, depending on the syntactic context, can occur as one word written together or discontinuously. they occur in languages such as german and dutch and constitute a problem for nlp because they are lexemes whose forms cannot always be recognized by dictionary lookup on the basis of a text word. conventional solutions take a mixed lexical and syntactic approach. in this paper, we propose the solution offered by word manager, consisting of string-based recognition by means of rules of types also required for periphrastic inflection and clitics. in this way, separable verbs are dealth with as part of the domain of reusable lexical resources. we show how this solution compares favourably with conventional approaches.
low-cost enrichment of spanish wordnet with automatically translated glosses: combining general and specialized models. this paper studies the enrichment of spanish wordnet with synset glosses automatically obtained from the english word-net glosses using a phrase-based statistical machine translation system. we construct the english-spanish translation system from a parallel corpus of proceedings of the european parliament, and study how to adapt statistical models to the domain of dictionary definitions. we build specialized language and translation models from a small set of parallel definitions and experiment with robust manners to combine them. a statistically significant increase in performance is obtained. the best system is finally used to generate a definition for all spanish synsets, which are currently ready for a manual revision. as a complementary issue, we analyze the impact of the amount of in-domain data needed to improve a system trained entirely on out-of-domain data.
semantics of temporal queries and temporal data. this paper analyzes the requirements for adding a temporal reasoning component to a natural language database query system, and proposes a computational model that satisfies those requirements. a preliminary implementation in prolog is used to generate examples of the model's capabilities.
resolving ellipsis in clarification. we offer a computational analysis of the resolution of ellipsis in certain cases of dialogue clarification. we show that this goes beyond standard techniques used in anaphora and ellipsis resolution and requires operations on highly structured, linguistically heterogeneous representations. we characterize these operations and the representations on which they operate. we offer an analysis couched in a version of head-driven phrase structure grammar combined with a theory of information states (is) in dialogue. we sketch an algorithm for the process of utterance integration in iss which leads to grounding or clarification.
prototype-driven grammar induction. we investigate prototype-driven learning for primarily unsupervised grammar induction. prior knowledge is specified declaratively, by providing a few canonical examples of each target phrase type. this sparse prototype information is then propagated across a corpus using distributional similarity features, which augment an otherwise standard pcfg model. we show that distributional features are effective at distinguishing bracket labels, but not determining bracket locations. to improve the quality of the induced trees, we combine our pcfg induction with the ccm model of klein and manning (2002), which has complementary stengths: it identifies brackets but does not label them. using only a handful of prototypes, we show substantial improvements over naive pcfg induction for english and chinese grammar induction.
scaling up from dialogue to multilogue: some principles and benchmarks. the paper considers how to scale up dialogue protocols to multilogue, settings with multiple conversationalists. we extract two benchmarks to evaluate scaled up protocols based on the long distance resolution possibilities of non-sentential utterances in dialogue and multilogue in the british national corpus. in light of these benchmarks, we then consider three possible transformations to dialogue protocols, formulated within an issue-based approach to dialogue management. we show that one such transformation yields protocols for querying and assertion that fulfill these benchmarks.
selection of effective contextual information for automatic synonym acquisition. various methods have been proposed for automatic synonym acquisition, as synonyms are one of the most fundamental lexical knowledge. whereas many methods are based on contextual clues of words, little attention has been paid to what kind of categories of contextual information are useful for the purpose. this study has experimentally investigated the impact of contextual information selection, by extracting three kinds of word relationships from corpora: dependency, sentence co-occurrence, and proximity. the evaluation result shows that while dependency and proximity perform relatively well by themselves, combination of two or more kinds of contextual information gives more stable performance. we've further investigated useful selection of dependency relations and modification categories, and it is found that modification has the greatest contribution, even greater than the widely adopted subject-object combination.
phrase linguistic classification and generalization for improving statistical machine translation. in this paper a method to incorporate linguistic information regarding single-word and compound verbs is proposed, as a first step towards an smt model based on linguistically-classified phrases. by substituting these verb structures by the base form of the head verb, we achieve a better statistical word alignment performance, and are able to better estimate the translation model and generalize to unseen verb forms during translation. preliminary experiments for the english - spanish language pair are performed, and future research lines are detailed.
centering in-the-large: computing referential discourse segments. we specify an algorithm that builds up a hierarchy of referential discourse segments from local centering data. the spatial extension and nesting of these discourse segments constrain the reachability of potential antecedents of an anaphoric expression beyond the local level of adjacent center pairs. thus, the centering model is scaled up to the level of the global referential structure of discourse. an empirical evaluation of the algorithm is supplied.
semantic role labeling via framenet, verbnet and propbank. this article describes a robust semantic parser that uses a broad knowledge base created by interconnecting three major resources: framenet, verbnet and propbank. the framenet corpus contains the examples annotated with semantic roles whereas the verbnet lexicon provides the knowledge about the syntactic behavior of the verbs. we connect verbnet and framenet by mapping the framenet frames to the verbnet intersective levin classes. the propbank corpus, which is tightly connected to the verbnet lexicon, is used to increase the verb coverage and also to test the effectiveness of our approach. the results indicate that our model is an interesting step towards the design of more robust semantic parsers.
a text understander that learns. we introduce an approach to the automatic acquisition of new concepts from natural language texts which is tightly integrated with the underlying text understanding process. the learning model is centered around the 'quality' of different forms of linguistic and conceptual evidence which underlies the incremental generation and refinement of alternative concept hypotheses, each one capturing a different conceptual reading for an unknown lexical item.
speeding up full syntactic parsing by leveraging partial parsing decisions. parsing is a computationally intensive task due to the combinatorial explosion seen in chart parsing algorithms that explore possible parse trees. in this paper, we propose a method to limit the combinatorial explosion by restricting the cyk chart parsing algorithm based on the output of a chunk parser. when tested on the three parsers presented in (collins, 1999), we observed an approximate three-fold speedup with only an average decrease of 0.17% in both precision and recall.
project april: a progress report. parsing techniques based on rules defining grammaticality are difficult to use with authentic inputs, which are often grammatically messy. instead, the april system seeks a labelled tree structure which maximizes a numerical measure of conformity to statistical norms derived from a sample of parsed text. no distinction between legal and illegal trees arises: any labelled tree has a value. because the search space is large and has an irregular geometry, april seeks the best tree using simulated annealing, a stochastic optimization technique. beginning with an arbitrary tree, many randomly-generated local modifications are considered and adopted or rejected according to their effect on tree-value: acceptance decisions are made probabilistically, subject to a bias against adverse moves which is very weak at the outset but is made to increase as the random walk through the search space continues. this enables the system to converge on the global optimum without getting trapped in local optima. performance of an early version of the april system on authentic inputs is yielding analyses with a mean accuracy of 75.3% using a schedule which increases processing linearly with sentence-length; modifications currently being implemented should eliminate a high proportion of the remaining errors.
domain kernels for word sense disambiguation. in this paper we present a supervised word sense disambiguation methodology, that exploits kernel methods to model sense distinctions. in particular a combination of kernel functions is adopted to estimate independently both syntagmatic and domain similarity. we defined a kernel function, namely the domain kernel, that allowed us to plug "external knowledge" into the supervised learning process. external knowledge is acquired from unlabeled data in a totally unsupervised way, and it is represented by means of domain models. we evaluated our methodology on several lexical sample tasks in different languages, outperforming significantly the state-of-the-art for each of them, while reducing the amount of labeled training data required for learning.
exploiting comparable corpora and bilingual dictionaries for cross-language text categorization. cross-language text categorization is the task of assigning semantic classes to documents written in a target language (e.g. english) while the system is trained using labeled documents in a source language (e.g. italian).in this work we present many solutions according to the availability of bilingual resources, and we show that it is possible to deal with the problem even when no such resources are accessible. the core technique relies on the automatic acquisition of multilingual domain models from comparable corpora.experiments show the effectiveness of our approach, providing a low cost solution for the cross language text categorization task. in particular, when bilingual dictionaries are available the performance of the categorization gets close to that of monolingual text categorization.
serial combination of rules and statistics: a case study in czech tagging. a hybrid system is described which combines the strength of manual rule-writing and statistical learning, obtaining results superior to both methods if applied separately. the combination of a rule-based system and a statistical one is not parallel but serial: the rule-based system performing partial disambiguation with recall close to 100% is applied first, and a trigram hmm tagger runs on its results. an experiment in czech tagging has been performed with encouraging results.
a computational framework for composition in multiple linguistic domains. we describe a computational framework for a grammar architecture in which different linguistic domains such as morphology, syntax, and semantics are treated not as separate components but compositional domains. the framework is based on combinatory categorial grammars and it uses the morpheme as the basic building block of the categorial lexicon.
topic-focus and salience. most of the current work on corpus annotation is concentrated on morphemics, lexical semantics and sentence structure. however, it becomes more and more obvious that attention should and can be also paid to phenomena that reflect the links between a sentence and its context, i.e. the discourse anchoring of utterances. if conceived in this way, an annotated corpus can be used as a resource for linguistic research not only within the limits of the sentence, but also with regard to discourse patterns. thus, the applications of the research to issues of information retrieval and extraction may be made more effective; also applications in new domains become feasible, be it to serve for inner linguistic (and literary) aims, such as text segmentation, specification of topics of parts of a discourse, or for other disciplines.
lazy unification. unification-based nl parsers that copy argument graphs to prevent their destruction suffer from inefficiency. copying is the most expensive operation in such parsers, and several methods to reduce copying have been devised with varying degrees of success. lazy unification is presented here as a new, conceptually elegant solution that reduces copying by nearly an order of magnitude. lazy unification requires no new slots in the structure of nodes, and only nominal revisions to the unification algorithm.
pcfgs with syntactic and prosodic indicators of speech repairs. a grammatical method of combining two kinds of speech repair cues is presented. one cue, prosodic disjuncture, is detected by a decision tree-based ensemble classifier that uses acoustic cues to identify where normal prosody seems to be interrupted (lickley, 1996). the other cue, syntactic parallelism, codifies the expectation that repairs continue a syntactic category that was left unfinished in the reparandum (levelt, 1983). the two cues are combined in a treebank pcfg whose states are split using a few simple tree transformations. parsing performance on the switchboard and fisher corpora suggests that these two cues help to locate speech repairs in a synergistic way.
an unsupervised model for statistically determining coordinate phrase attachment. this paper examines the use of an unsupervised statistical model for determining the attachment of ambiguous coordinate phrases (cp) of the form <i>n</i>1 <i>p n</i>2 <i>cc n</i>3. the model presented here is based on [ar98], an unsupervised model for determining prepositional phrase attachment. after training on unannotated 1988 wall street journal text, the model performs at 72% accuracy on a development set from sections 14 through 19 of the wsj treebank [msm93].
attention shifting for parsing speech. we present a technique that improves the efficiency of word-lattice parsing as used in speech recognition language modeling. our technique applies a probabilistic parser iteratively where on each iteration it focuses on a different subset of the word-lattice. the parser's attention is shifted towards word-lattice subsets for which there are few or no syntactic analyses posited. this attention-shifting technique provides a six-times increase in speed (measured as the number of parser analyses evaluated) while performing equivalently when used as the first-stage of a multi-stage parsing-based language model.
noun phrase chunking in hebrew: influence of lexical and morphological features. we present a method for noun phrase chunking in hebrew. we show that the traditional definition of base-nps as non-recursive noun phrases does not apply in hebrew, and propose an alternative definition of simple nps. we review syntactic properties of hebrew related to noun phrases, which indicate that the task of hebrew simplenp chunking is harder than base-np chunking in english. as a confirmation, we apply methods known to work well for english to hebrew data. these methods give low results (f from 76 to 86) in hebrew. we then discuss our method, which applies svm induction over lexical and morphological features. morphological features improve the average precision by ~0.5%, recall by ~1%, and f-measure by ~0.75, resulting in a system with average performance of 93% precision, 93.4% recall and 93.2 f-measure.
discriminative classifiers for deterministic dependency parsing. deterministic parsing guided by treebank-induced classifiers has emerged as a simple and efficient alternative to more complex models for data-driven parsing. we present a systematic comparison of memory-based learning (mbl) and support vector machines (svm) for inducing classifiers for deterministic dependency parsing, using data from chinese, english and swedish, together with a variety of different feature models. the comparison shows that svm gives higher accuracy for richly articulated feature models across all languages, albeit with considerably longer training times. the results also confirm that classifier-based deterministic parsing can achieve parsing accuracy very close to the best results reported for more complex parsing models.
combining trigram-based and feature-based methods for context-sensitive spelling correction. this paper addresses the problem of correcting spelling errors that result in valid, though unintended words (such as peace and piece, or quiet and quite) and also the problem of correcting particular word usage errors (such as amount and number, or among and between). such corrections require contextual information and are not handled by conventional spelling programs such as unix spell. first, we introduce a method called trigrams that uses part-of-speech trigrams to encode the context. this method uses a small number of parameters compared to previous methods based on word trigrams. however, it is effectively unable to distinguish among words that have the same part of speech. for this case, an alternative feature-based method called bayes performs better; but bayes is less effective than trigrams when the distinction among words depends on syntactic constraints. a hybrid method called tribayes is then introduced that combines the best of the previous two methods. the improvement in performance of tribayes over its components is verified experimentally. tribayes is also compared with the grammar checker in microsoft word, and is found to have substantially higher performance.
event extraction in a plot advice agent. in this paper we present how the automatic extraction of events from text can be used to both classify narrative texts according to plot quality and produce advice in an interactive learning environment intended to help students with story writing. we focus on the story rewriting task, in which an exemplar story is read to the students and the students rewrite the story in their own words. the system automatically extracts events from the raw text, formalized as a sequence of temporally ordered predicate-arguments. these events are given to a machine-learner that produces a coarse-grained rating of the story. the results of the machine-learner and the extracted events are then used to generate fine-grained advice for the students.
contextual dependencies in unsupervised word segmentation. developing better methods for segmenting continuous text into words is important for improving the processing of asian languages, and may shed light on how humans learn to segment speech. we propose two new bayesian word segmentation methods that assume unigram and bigram models of word dependencies respectively. the bigram model greatly outperforms the unigram model (and previous probabilistic models), demonstrating the importance of such dependencies for word segmentation. we also show that previous probabilistic models rely crucially on sub-optimal search procedures.
linguistic profiling for authorship recognition and verification. a new technique is introduced, linguistic profiling, in which large numbers of counts of linguistic features are used as a text profile, which can then be compared to average profiles for groups of texts. the technique proves to be quite effective for authorship verification and recognition. the best parameter settings yield a false accept rate of 8.1% at a false reject rate equal to zero for the verification task on a test corpus of student essays, and a 99.4% 2-way recognition accuracy on the same corpus.
building verb predicates: a computational view. a method for the definition of verb predicates is proposed. the definition of the predicates is essentially tied to a semantic interpretation algorithm that determines the predicate for the verb, its semantic roles and adjuncts. as predicate definitions are complete, they can be tested by running the algorithm on some sentences and verifying the resolution of the predicate, semantic roles and adjuncts in those sentences. the predicates are defined semiautomatically with the help of a software environment that uses several sections of a corpus to provide feedback for the definition of the predicates, and then for the subsequent testing and refining of the definitions. the method is very flexible in adding a new predicate to a list of already defined predicates for a given verb. the method builds on an existing approach that defines predicates for wordnet verb classes, and that plans to define predicates for every english verb. the definitions of the predicates and the semantic interpretation algorithm are being used to automatically create a corpus of annotated verb predicates, semantic roles and adjuncts.
improving data driven wordclass tagging by system combination. in this paper we examine how the differences in modelling between different data driven systems performing the same nlp task can be exploited to yield a higher accuracy than the best individual system. we do this by means of an experiment involving the task of morpho-syntactic wordclass tagging. four well-known tagger generator (hidden markov model, memory-based, transformation rules and maximum entropy) are trained on the same corpus data. after comparison, their outputs are combined using several voting strategies and second stage classifiers. all combination taggers outperform their best component, with the best combination showing a 19.1% lower error rate than the best indvidual tagger.
detection of quotations and inserted clauses and its application to dependency structure analysis in spontaneous japanese. japanese dependency structure is usually represented by relationships between phrasal units called bunsetsus. one of the biggest problems with dependency structure analysis in spontaneous speech is that clause boundaries are ambiguous. this paper describes a method for detecting the boundaries of quotations and inserted clauses and that for improving the dependency accuracy by applying the detected boundaries to dependency structure analysis. the quotations and inserted clauses are determined by using an svm-based text chunking method that considers information on morphemes, pauses, fillers, etc. the information on automatically analyzed dependency structure is also used to detect the beginning of the clauses. our evaluation experiment using corpus of spontaneous japanese (csj) showed that the automatically estimated boundaries of quotations and inserted clauses helped to improve the accuracy of dependency structure analysis.
sequential conditional generalized iterative scaling. we describe a speedup for training conditional maximum entropy models. the algorithm is a simple variation on generalized iterative scaling, but converges roughly an order of magnitude faster, depending on the number of constraints, and the way speed is measured. rather than attempting to train all model parameters simultaneously, the algorithm trains them sequentially. the algorithm is easy to implement, typically uses only slightly more memory, and will lead to improvements for most maximum entropy problems.
a step towards the detection of semantic variants of terms in technical documents. this paper reports the results of a preliminary experiment on the detection of semantic variants of terms in a french technical document. the general goal of our work is to help the structuration of terminologies. two kinds of semantic variants can be found in traditional terminologies: strict synonymy links and fuzzier relations like see-also. we have designed three rules which exploit general dictionary information to infer synonymy relations between complex candidate terms. the results have been examined by a human terminologist. the expert has judged that half of the overall pairs of terms are relevant for the semantic variation. he validated an important part of the detected links as synonymy. moreover, it appeared that numerous errors are due to few mis-interpreted links: they could be eliminated by few exception rules.
repairing reference identification failures by relaxation. the goal of this work is the enrichment of human-machine interactions in a natural language environment. we want to provide a framework less restrictive than earlier ones by allowing a speaker leeway in forming an utterance about a task and in determining the conversational vehicle to deliver it. a speaker and listener cannot be assured to have the same beliefs, contexts, backgrounds or goals at each point in a conversation. as a result, difficulties and mistakes arise when a listener interprets a speaker's utterance. these mistakes can lead to various kinds of misunderstandings between speaker and listener, including reference failures or failure to understand the speaker's intention. we call these misunderstandings miscommunication. such mistakes constitute a kind of "ill-formed" input that can slow down and possibly break down communication. our goal is to recognize and isolate such miscommunications and circumvent them. this paper will highlight a particular class of miscommunication - reference problems - by describing a case study, including techniques for avoiding failures of reference.
improving english subcategorization acquisition with diathesis alternations as heuristic information. automatically acquired lexicons with subcategorization information have already proved accurate and useful enough for some purposes but their accuracy still shows room for improvement. by means of diathesis alternation, this paper proposes a new filtering method, which improved the performance of korhonen's acquisition system remarkably, with the precision increased to 91.18% and recall unchanged, making the acquired lexicon much more practical for further manual proofreading and other nlp uses.
parsing algorithms and metrics. many different metrics exist for evaluating parsing results, including viterbi, crossing brackets rate, zero crossing brackets rate, and several others. however, most parsing algorithms, including the viterbi algorithm, attempt to optimize the same metric, namely the probability of getting the correct labelled tree. by choosing a parsing algorithm appropriate for the evaluation metric, better performance can be achieved. we present two new algorithms: the "labelled recall algorithm," which maximizes the expected labelled recall rate, and the "bracketed recall algorithm," which maximizes the bracketed recall rate. experimental results are given, showing that the two new algorithms have improved performance over the viterbi algorithm on many criteria, especially the ones that they optimize.
an application of wordnet to prepositional attachment. this paper presents a method for word sense disambiguation and coherence understanding of prepositional relations. the method relies on information provided by wordnet 1.5. we first classify prepositional attachments according to semantic equivalence of phrase heads and then apply inferential heuristics for understanding the validity of prepositional structures.
recognizing expressions of commonsense psychology in english text. many applications of natural language processing technologies involve analyzing texts that concern the psychological states and processes of people, including their beliefs, goals, predictions, explanations, and plans. in this paper, we describe our efforts to create a robust, large-scale lexical-semantic resource for the recognition and classification of expressions of commonsense psychology in english text. we achieve high levels of precision and recall by hand-authoring sets of local grammars for commonsense psychology concepts, and show that this approach can achieve classification performance greater than that obtained by using machine learning techniques. we demonstrate the utility of this resource for large-scale corpus analysis by identifying references to adversarial and competitive goals in political speeches throughout u.s. history.
methods for using textual entailment in open-domain question answering. work on the semantics of questions has argued that the relation between a question and its answer(s) can be cast in terms of logical entailment. in this paper, we demonstrate how computational systems designed to recognize textual entailment can be used to enhance the accuracy of current open-domain automatic question answering (q/a) systems. in our experiments, we show that when textual entailment information is used to either filter or rank answers returned by a q/a system, accuracy can be increased by as much as 20% overall.
scaling distributional similarity to large corpora. accurately representing synonymy using distributional similarity requires large volumes of data to reliably represent infrequent words. however, the na&iuml;ve nearest-neighbour approach to comparing context vectors extracted from large corpora scales poorly (o(n2) in the vocabulary size).in this paper, we compare several existing approaches to approximating the nearest-neighbour search for distributional similarity. we investigate the trade-off between efficiency and accuracy, and find that sash (houle and sakuma, 2005) provides the best balance.
experiments with interactive question-answering. this paper describes a novel framework for interactive question-answering (q/a) based on predictive questioning. generated off-line from topic representations of complex scenarios, predictive questions represent requests for information that capture the most salient (and diverse) aspects of a topic. we present experimental results from large user studies (featuring a fully-implemented interactive q/a system named ferret) that demonstrates that surprising performance is achieved by integrating predictive questions into the context of a q/a dialogue.
the role of lexico-semantic feedback in open-domain textual question-answering. this paper presents an open-domain textual question-answering system that uses several feedback loops to enhance its performance. these feedback loops combine in a new way statistical results with syntactic, semantic or pragmatic information derived from texts and lexical databases. the paper presents the contribution of each feedback loop to the overall performance of 76% human-assessed precise answers.
interleaving universal principles and relational constraints over typed feature logic. we introduce a typed feature logic system providing both universal implicational principles as well as definite clauses over feature terms. we show that such an architecture supports a modular encoding of linguistic theories and allows for a compact representation using underspecification. the system is fully implemented and has been used as a workbench to develop and test large hpsg grammars. the techniques described in this paper are not restricted to a specific implementation, but could be added to many current feature-based grammar development systems.
an efficient parsing algorithm for tree adjoining grammars. in the literature, tree adjoining grammars (tags) are propagated to be adequate for natural language description --- analysis as well as generation. in this paper we concentrate on the direction of analysis. especially important for an implementation of that task is how efficiently this can be done, i.e., how readily the word problem can be solved for tags. up to now, a parser with o(n6) steps in the worst case was known where n is the length of the input string. in this paper, the result is improved to o(n4 log n) as a new lowest upper bound. the paper demonstrates how local interpretion of tag trees allows this reduction.
aligning words using matrix factorisation. aligning words from sentences which are mutual translations is an important problem in different settings, such as bilingual terminology extraction, machine translation, or projection of linguistic features. here, we view word alignment as matrix factorisation. in order to produce proper alignments, we show that factors must satisfy a number of constraints such as orthogonality. we then propose an algorithm for orthogonal non-negative matrix factorisation, based on a probabilistic model of the alignment data, and apply it to word alignment. this is illustrated on a french-english alignment task from the hansard.
an algorithm for vp ellipsis. an algorithm is proposed to determine antecedents for vp ellipsis. the algorithm eliminates impossible antecedents, and then imposes a preference ordering on possible antecedents. the algorithm performs with 94% accuracy on a set of 304 examples of vp ellipsis collected from the brown corpus. the problem of determining antecedents for vp ellipsis has received little attention in the literature, and it is shown that the current proposal is a significant improvement over alternative approaches.
parsing aligned parallel corpus by projecting syntactic relations from annotated source corpus. example-based parsing has already been proposed in literature. in particular, attempts are being made to develop techniques for language pairs where the source and target languages are different, e.g. direct projection algorithm (hwa et al., 2005). this enables one to develop parsed corpus for target languages having fewer linguistic tools with the help of a resource-rich source language. the dpa algorithm works on the assumption of direct correspondence which simply means that the relation between two words of the source language sentence can be projected directly between the corresponding words of the parallel target language sentence. however, we find that this assumption does not hold good all the time. this leads to wrong parsed structure of the target language sentence. as a solution we propose an algorithm called pseudo dpa (pdpa) that can work even if direct correspondence assumption is not guaranteed. the proposed algorithm works in a recursive manner by considering the embedded phrase structures from outermost level to the innermost. the present work discusses the pdpa algorithm, and illustrates it with respect to english-hindi language pair. link grammar based parsing has been considered as the underlying parsing scheme for this work.
polyphony and argumentative semantics. we extract from sentences a superstructure made of argumentative operators and connectives applying to the remaining set of terminal sub-sentences. we found the argumentative interpretation of utterances on a semantics defined at the linguistic level. we describe the computation of this particular semantics, based on the constraints that the superstructure impels to the argumentative power of terminal subsentences.
generation of vp ellipsis: a corpus-based approach. we present conditions under which verb phrases are elided based on a corpus of positive and negative examples. factor that affect verb phrase ellipsis include: the distance between antecedent and ellipsis site, the syntactic relation between antecedent and ellipsis site, and the presence or absence of adjuncts. building on these results, we examine where in the generation architecture a trainable algorithm for vp ellipsis should be located. we show that the best performance is achieved when the trainable module is located after the realizer and has access to surface-oriented features (error rate of 7.5%).
normal state implicature. in the right situation, a speaker can use an unqualified indefinite description without being misunderstood. this use of language, normal state implicature, is a kind of conversational implicature, i.e. a non-truth-functional context-dependent inference based upon language users' awareness of principles of cooperative conversation. i present a convention for identifying normal state implicatures which is based upon mutual beliefs of the speaker and hearer about certain properties of the speaker's plan. a key property is the precondition that an entity playing a role in the plan must be in a normal state with respect to the plan.
data-driven strategies for an automated dialogue system. we present a prototype natural-language problem-solving application for a financial services call center, developed as part of the amiti&eacute;s multilingual human-computer dialogue project. our automated dialogue system, based on empirical evidence from real call-center conversations, features a data-driven approach that allows for mixed system/customer initiative and spontaneous conversation. preliminary evaluation results indicate efficient dialogues and high user satisfaction, with performance comparable to or better than that of current conversational travel information systems.
local constraints on sentence markers and focus in somali. we present a computationally tractable account of the interactions between sentence markers and focus marking in somali. somali, as a cushitic language, has a basic pattern wherein a small 'core' clause is preceded, and in some cases followed by, a set of 'topics', which provide scene-seting information against which the core is interpreted. some topics appear to carry a 'focus marker', indicating that they are particularly salient. we will outline a computationally tractable grammar for somali in which focus marking emerges naturally from a consideration of the use of a range of sentence markers.
conversational implicatures in indirect replies. in this paper we present algorithms for the interpretation and generation of a kind of particularized conversational implicature occurring in certain indirect replies. our algorithms make use of discourse expectations, discourse plans, and discourse relations. the algorithms calculate implicatures of discourse units of one or more sentences. our approach has several advantages. first, by taking discourse relations into account, it can capture a variety of implicatures not handled before. second, by treating implicatures of discourse units which may consist of more than one sentence, it avoids the limitations of a sentence-at-a-time approach. third, by making use of properties of discourse which have been used in models of other discourse phenomena, our approach can be integrated with those models. also, our model permits the same information to be used both in interpretation and generation.
designer definites in logical form. in this paper, we represent singular definite noun phrases as functions in logical form. this representation is designed to model the behaviors of both anaphoric and non-anaphoric, distributive definites. it is also designed to obey the computational constraints suggested in harper [har88]. our initial representation of a definite places an upper bound on its behavior given its structure and location in a sentence. later, when ambiguity is resolved, the precise behavior of the definite is pinpointed.
a hybrid reasoning model for indirect answers. this paper presents our implemented computational model for interpreting and generating indirect answers to yes-no questions. its main features are 1) a discourse-plan-based approach to implicature, 2) a reversible architecture for generation and interpretation, 3) a hybrid reasoning model that employs both plan inference and logical inference, and 4) use of stimulus conditions to model a speaker's motivation for providing appropriate, unrequested information. the model handles a wider range of types of indirect answers than previous computational models and has several significant advantages.
inducing frame semantic verb classes from wordnet and ldoce. this paper presents semframe, a system that induces frame semantic verb classes from wordnet and ldoce. semantic frames are thought to have significant potential in resolving the paraphrase problem challenging many language-based applications.when compared to the handcrafted framenet, semframe achieves its best recall-precision balance with 83.2% recall (based on semframe's coverage of framenet frames) and 73.8% precision (based on semframe verbs' semantic relatedness to frame-evoking verbs). the next best performing semantic verb classes achieve 56.9% recall and 55.0% precision.
mapping lexical entries in a verbs database to wordnet senses. this paper describes automatic techniques for mapping 9611 entries in a database of english verbs to wordnet senses. the verbs were initially grouped into 491 classes based on syntactic features. mapping these verbs into wordnet senses provides a resource that supports disambiguation in multilingual applications such as machine translation and cross-language information retrieval. our techniques make use of (1) a training set of 1791 disambiguated entries, representing 1442 verb entries from 167 classes; (2) word sense probabilities, from frequency counts in a tagged corpus; (3) semantic similarity of wordnet senses for verbs within the same class; (4) probabilistic correlations between wordnet data and attributes of the verb classes. the best results achieved 72% precision and 58% recall, versus a lower bound of 62% precision and 38% recall for assigning the most frequently occurring wordnet sense, and an upper bound of 87% precision and 75% recall for human judgment.
semi-supervised conditional random fields for improved sequence segmentation and labeling. we present a new semi-supervised training procedure for conditional random fields (crfs) that can be used to train sequence segmentors and labelers from a combination of labeled and unlabeled training data. our approach is based on extending the minimum entropy regularization framework to the structured prediction case, yielding a training objective that combines unlabeled conditional entropy with labeled conditional likelihood. although the training objective is no longer concave, it can still be used to improve an initial model (e.g. obtained from supervised training) by iterative ascent. we apply our new training algorithm to the problem of identifying gene and protein mentions in biological texts, and show that incorporating unlabeled data improves the performance of the supervised crf in this case.
analysis and repair of name tagger errors. name tagging is a critical early stage in many natural language processing pipelines. in this paper we analyze the types of errors produced by a tagger, distinguishing name classification and various types of name identification errors. we present a joint inference model to improve chinese name tagging by incorporating feedback from subsequent stages in an information extraction pipeline: name structure parsing, cross-document coreference, semantic relation extraction and event extraction. we show through examples and performance measurement how different stages can correct different types of errors. the resulting accuracy approaches that of individual human annotators.
sextant: exploring unexplored contexts for semantic extraction from syntactic analysis. for a very long time, it has been considered that the only way of automatically extracting similar groups of words from a text collection for which no semantic information exists is to use document co-occurrence data. but, with robust syntactic parsers that are becoming more frequently available, syntactically recognizable phenomena about word usage can be confidently noted in large collections of texts. we present here a new system called sextant which uses these parsers and the finer-grained contexts they produce to judge word similarity.
a collaborative framework for collecting thai unknown words from the web. we propose a collaborative framework for collecting thai unknown words found on web pages over the internet. our main goal is to design and construct a web-based system which allows a group of interested users to participate in constructing a thai unknown-word open dictionary. the proposed framework provides supporting algorithms and tools for automatically identifying and extracting unknown words from web pages of given urls. the system yields the result of unknown-word candidates which are presented to the users for verification. the approved unknown words could be combined with the set of existing words in the lexicon to improve the performance of many nlp tasks such as word segmentation, information retrieval and machine translation. our framework includes word segmentation and morphological analysis modules for handling the non-segmenting characteristic of thai written language. to take advantage of large available text resource on the web, our unknown-word boundary identification approach is based on the statistical string pattern-matching algorithm.
using conditional random fields to predict pitch accents in conversational speech. the detection of prosodic characteristics is an important aspect of both speech synthesis and speech recognition. correct placement of pitch accents aids in more natural sounding speech, while automatic detection of accents can contribute to better word-level recognition and better textual understanding. in this paper we investigate probabilistic, contextual, and phonological factors that influence pitch accent placement in natural, conversational speech in a sequence labeling setting. we introduce conditional random fields (crfs) to pitch accent prediction task in order to incorporate these factors efficiently in a sequence model. we demonstrate the usefulness and the incremental effect of these factors in a sequence model by performing experiments on hand labeled data from the switchboard corpus. our model outperforms the baseline and previous models of pitch accent prediction on the switch-board corpus.
mistake-driven mixture of hierarchical tag context trees. this paper proposes a mistake-driven mixture method for learning a tag model. the method iteratively performs two procedures: 1. constructing a tag model based on the current data distribution and 2. updating the distribution by focusing on data that are not well predicted by the constructed model. the final tag model is constructed by mixing all the models according to their performance. to well reflect the data distribution, we represent each tag model as a hierarchical tag (i.e., ntt <proper noun <noun) context tree. by using the hierarchical tag context tree, the constituents of sequential tag models gradually change from broad coverage tags (e.g., noun) to specific exceptional words that cannot be captured by general tags. in other words, the method incorporates not only frequent connetions but also infrequent ones that are often considered to be collocational. we evaluate several tag models by implementing japanese part-of-speech taggers that share all other conditions (i.e., dictionary and word model) other than their tag models. the experimental results show the proposed method significantly outperforms both hand-crafted and conventional statistical methods.
unsupervised learning of field segmentation models for information extraction. the applicability of many current information extraction techniques is severely limited by the need for supervised training data. we demonstrate that for certain field structured extraction tasks, such as classified advertisements and bibliographic citations, small amounts of prior knowledge can be used to learn effective models in a primarily unsupervised fashion. although hidden markov models (hmms) provide a suitable generative model for field structured text, general unsupervised hmm learning fails to learn useful structure in either of our domains. however, one can dramatically improve the quality of the learned structure by exploiting simple prior knowledge of the desired solutions. in both domains, we found that unsupervised methods can attain accuracies with 400 unlabeled examples comparable to those attained by supervised methods on 50 labeled examples, and that semi-supervised methods can make good use of small amounts of labeled data.
using decision trees to construct a practical parser. this paper describes novel and practical japanese parsers that uses decision trees. first, we construct a single decision tree to estimate modification probabilities; how one phrase tends to modify another. next, we introduce a boosting algorithm in which several decision trees are constructed and then combined for probability estimation. the two constructed parsers are evaluated by using the edr japanese annotated corpus. the single-tree method outperforms the conventional japanese stochastic methods by 4%. moreover, the boosting version is shown to have significant advantages; 1) better parsing accuracy than its single-tree counterpart for any amount of training data and 2) no over-fitting to data for various iterations.
high-performance bilingual text alignment using statistical and dictionary information. this paper describes an accurate and robust text alignment system for structurally different languages. among structurally different languages such as japanese and english, there is a limitation on the amount of word correspondences that can be statistically acquired. the main reason for this is the systems of functional (closed) words are quite different in the two languages. the proposed method makes use of two kinds of word correspondences in aligning bilingual texts. one is a bilingual dictionary of general use. the other is the word correspondences that are statistically acquired in the alignment process. our method gradually determines sentence pairs (anchors) that correspond to each other by relaxing parameters. the method, by combining two kinds of word correspondences, achieves adequate word correspondences for complete alignment. as a result, texts of various length and of various genres in structurally different languages can be aligned with high precision. experimental results show our system outperforms conventional methods for various kinds of japanese&ndash;english texts.
learning strategies for open-domain natural language question answering. this work presents a model for learning inference procedures for story comprehension through inductive generalization and reinforcement learning, based on classified examples. the learned inference procedures (or strategies) are represented as of sequences of transformation rules. the approach is compared to three prior systems, and experimental results are presented demonstrating the efficacy of the model.
integrating text plans for conciseness and coherence. our experience with a critiquing system shows that when the system detects problems with the user's performance, multiple critiques are often produced. analysis of a corpus of actual critiques revealed that even though each individual critique is concise and coherent, the set of critiques as a whole may exhibit several problems that detract from conciseness and coherence, and consequently assimilation. thus a text planner was needed that could integrated the text plans for individual communicative goals to produce an overall text plan representing a concise, coherent message.this paper presents our general rule-based system for accomplishing this task. the system takes as input a set of individual text plans represented as rst-style trees, and produces a smaller set of more complex trees representing integrated messages that still achieve the multiple communicative goals of the individual text plans. domain-independent rules are used to capture strategies across domains, while the facility for addition of domain-dependent rules enables the system to be tuned to the requirements of a particular domain. the system has been tested on a corpus of critiques in the domain of trauma care.
towards abstract categorial grammars. we introduce a new categorial formalism based on intuitionistic linear logic. this formalism, which derives from current type-logical grammars, is abstract in the sense that both syntax and semantics are handled by the same set of primitives. as a consequence, the formalism is reversible and provides different computational paradigms that may be freely composed together.
improving name tagging by reference resolution and relation detection. information extraction systems incorporate multiple stages of linguistic analysis. although errors are typically compounded from stage to stage, it is possible to reduce the errors in one stage by harnessing the results of the other stages. we demonstrate this by using the results of coreference analysis and relation extraction to reduce the errors produced by a chinese name tagger. we use an n-best approach to generate multiple hypotheses and have them re-ranked by subsequent stages of processing. we obtained thereby a reduction of 24% in spurious and incorrect name tags, and a reduction of 14% in missed tags.
discovering relations among named entities from large corpora. discovering the significant relations embedded in documents would be very useful not only for information retrieval but also for question answering and summarization. prior methods for relation discovery, however, needed large annotated corpora which cost a great deal of time and effort. we propose an unsupervised method for relation discovery from large corpora. the key idea is clustering pairs of named entities according to the similarity of context words intervening between the named entities. our experiments using one year of newspapers reveals not only that the relations among named entities could be detected with high recall and precision, but also that appropriate labels could be automatically provided for the relations.
japanese idiom recognition: drawing a line between literal and idiomatic meanings. recognizing idioms in a sentence is important to sentence understanding. this paper discusses the lexical knowledge of idioms for idiom recognition. the challenges are that idioms can be ambiguous between literal and idiomatic meanings, and that they can be "transformed" when expressed in a sentence. however, there has been little research on japanese idiom recognition with its ambiguity and transformations taken into account. we propose a set of lexical knowledge for idiom recognition. we evaluated the knowledge by measuring the performance of an idiom recognizer that exploits the knowledge. as a result, more than 90% of the idioms in a corpus are recognized with 90% accuracy.
towards the automatic identification of adjectival scales: clustering adjectives according to meaning. in this paper we present a method to group adjectives according to their meaning, as a first step towards the automatic identification of adjectival scales. we discuss the properties of adjectival scales and of groups of semantically related adjectives and how they imply sources of linguistic knowledge in text corpora. we describe how our system exploits this linguistic knowledge to compute a measure of similarity between two adjectives, using statistical techniques and without having access to any semantic information about the adjectives. we also show how a clustering algorithm can use these similarities to produce the groups of adjectives, and we present results produced by our system for a sample set of adjectives. we conclude by presenting evaluation methods for the task at hand, and analyzing the significance of the results obtained.
a quantitative evaluation of linguistic tests for the automatic prediction of semantic markedness. we present a corpus-based study of methods that have been proposed in the linguistics literature for selecting the semantically unmarked term out of a pair of antonymous adjectives. solutions to this problem are applicable to the more general task of selecting the positive term from the pair. using automatically collected data, the accuracy and applicability of each method is quantified, and a statistical analysis of the significance of the results is performed. we show that some simple methods are indeed good indicators for the answer to the problem while other proposed methods fail to perform better than would be attributable to chance. in addition, one of the simplest methods, text frequency, dominates all others. we also apply two generic statistical learning methods for combining the indications of the individual methods, and compare their performance to the simple methods. the most sophisticated complex learning method offers a small, but statistically significant, improvement over the original tests.
predicting the semantic orientation of adjectives. we identify and validate from a large corpus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. a log-linear regression model uses these constraints to predict whether conjoined adjectives are of same or different orientations, achieving 82% accuracy in this task when each conjunction is considered independently. combining the constraints across many adjectives, a clustering algorithm separates the adjectives into groups of different orientations, and finally, adjectives are labeled positive or negative. evaluations on real data and simulation experiments indicate high levels of performance: classification precision is more than 90% for adjectives that occur in a modest number of conjunctions in the corpus.
expanding the horizons of natural language interfaces. current natural language interfaces have concentrated largely on determining the literal "meaning" of input from their users. while such decoding is an essential underpinning, much recent work suggests that natural language interfaces will never appear cooperative or graceful unless they also incorporate numerous non-literal aspects of communication, such as robust communication procedures.this paper defends that view. but claims that direct imitation of human performance is not the best way to implement many of these non-literal aspects of communication; that the new technology of powerful personal computers with integral graphics displays offers techniques superior to those of humans for these aspects, while still satisfying human communication needs. the paper proposes interfaces based on a judicious mixture of these techniques and the still valuable methods of more traditional natural language interfaces.
flexible parsing. when people use natural language in natural settings, they often use it ungrammatically, leaving out or repeating words, breaking off and restarting, speaking in fragments, etc. their human listeners are usually able to cope with these deviations with little difficulty. if a computer system is to accept natural language input from its users on a routine basis, it should be similarly robust. in this paper, we outline a set of parsing flexibilities that such a system should provide. we go on to describe flexp, a bottom-up pattern matching parser that we have designed and implemented to provide many of these flexibilities for restricted natural language input to a limited-domain computer system.
metaphoric generalization through sort coercion. this paper presents a method for interpreting metaphoric language in the context of a portable natural language inferface. the method licenses metaphoric uses via coercions between incompatible ontological sorts. the machinery allows both previously-known and unexpected metaphoric uses ot be correctly interpreted and evaluated with respect to the backend expert system.
multi-paragraph segmentation of expository text. this paper describes texttiling, an algorithm for partitioning expository texts into coherent multi-paragraph discourse units which reflect the subtopic structure of the texts. the algorithm uses domain-independent lexical frequency and distribution information to recognize the interactions of multiple simultaneous themes. two fully-implemented versions of the algorithm are described and shown to produce segmentation that corresponds well to human judgments of the major subtopic boundaries of thirteen lengthy texts.
untangling text data mining. the possibilities for data mining from large text collections are virtually untapped. text expresses a vast, rich range of information, but encodes this information in a form that is difficult to decipher automatically. perhaps for this reason, there has been little work in text data mining to date, and most people who have talked about it have either conflated it with information access or have not made use of text directly to discover heretofore unknown information. in this paper i will first define data mining, information access, and corpus-based computational linguistics, and then discuss the relationship of these to text data mining. the intent behind these contrasts is to draw attention to exciting new kinds of problems for computational linguists. i describe examples of what i consider to be real text data mining efforts and briefly outline recent ideas about how to pursue exploratory data analysis over text.
collaborating on referring expressions. this paper presents a computational model of how conversational participants collaborate in making referring expressions. the model is based on the planning paradigm. it employs plans for constructing and recognizing referring expressions and meta-plans for constructing and recognizing clarifications. this allows the model to account for the generation and understanding both of referring expressions and of their clarifications in a uniform framework using a single knowledge base.
deyecting and correcting speech repairs. interactive spoken dialog provides many new challenges for spoken language systems. one of the most critical is the prevalence of speech repairs. this paper presents an algorithm that detects and corrects speech repairs based on finding the repair pattern. the repair pattern is built by finding word matches and word replacements, and identifying fragments and editing terms. rather than using a set of prebuilt templates, we build the pattern on the fly. in a the fair test, our method, when combined with a statistical model to filter possible repairs, was successful at detecting and correcting 80% of the repairs, without using prosodic information or a parser.
intonational boundaries, speech repairs and discourse markers: modeling spoken dialog. to understand a speaker's turn of a conversation, one needs to segment it into intonational phrases, clean up any speech repairs that might have occurred, and identify discourse markers. in this paper, we argue that these problems must be resolved together, and that they must be resolved early in the processing stream. we put forward a statistical language model that resolves these problem, does pos tagging, and can be used as the language model of a speech recognizer. we find that by accounting for the interactions between these tasks that the performance on each task improves, as does pos tagging and perplexity.
definiteness predictions for japanese noun phrases. one of the major problems when translating from japanese into a eurpoean language such as german or english is to determine definiteness of noun phrases in order to choose the correct determiner in the target language. even though in japanese, noun phrase reference is said to depend in large parts on the discourse context, we show that in many cases there also exist linguistic markers for definiteness. we use these to build a rule hierarchy that predicts 79,5% of the articles with an accuracy of 98,9% from syntactic-semantic properties alone, yielding an efficient pre-processing tool for the computationally expensive context checking.
eliminative parsing with graded constraints. natural language parsing is conceived to be a procedure of disambiguation, which successively reduces an initially totally ambiguous structural representation towards a single interpretation. graded constraints are used as means to express well-formedness conditions of different strength and to decide which partial structures are locally least preferred and, hence, can be deleted. this approach facilitates a higher degree of robustness of the analysis, allows to introduce resource adaptivity into the parsing procedure, and exhibits a high potential for parallelization of the computation.
optimal multi-paragraph text segmentation by dynamic programming. there exist several methods of calculating a similarity curve, or a sequence of similarity values, representing the lexical cohesion of successive text constituents, e.g., paragraphs. methods for deciding the locations of fragment boundaries are, however, scarce. we propose a fragmentation method based on dynamic programming. the method is theoretically sound and guaranteed to provide an optimal splitting on the basis of a similarity curve, a preferred fragment length, and a cost function defined. the method is especially useful when control on fragment size is of importance.
discriminative training of a neural network statistical parser. discriminative methods have shown significant improvements over traditional generative methods in many machine learning applications, but there has been difficulty in extending them to natural language parsing. one problem is that much of the work on discriminative methods conflates changes to the learning method with changes to the parameterization of the problem. we show how a parser can be trained with a discriminative learning method while still parameterizing the problem according to a generative probability model. we present three methods for training a neural network to estimate the probabilities for a statistical parser, one generative, one discriminative, and one where the probability model is generative but the training criteria is discriminative. the latter model outperforms the previous two, achieving state-of-the-art levels of performance (90.1% f-measure on constituents).
a connectionist parser for structure unification grammar. this paper presents a connectionist syntactic parser which uses structure unification grammar as its grammatical framework. the parser is implemented in a connectionist architecture which stores and dynamically manipulates symbolic representations, but which can't represent arbitrary disjunction and has bounded memory. these problems can be overcome with structure unification grammar's extensive use of partial descriptions.
a connectionist architecture for learning to parse. we present a connectionist architecture and demonstrate that it can learn syntactic parsing from a corpus of parsed text. the architecture can represent syntactic constituents, and can learn generalizations over syntactic constituents, thereby addressing the sparse data problems of previous connectionist architectures. we apply these simple synchrony networks to mapping sequences of word tags to parse trees. after training on parsed samples of the brown corpus, the networks achieve precision and recall on constituents that approaches that of statistical methods for this task.
data-defined kernels for parse reranking derived from probabilistic models. previous research applying kernel methods to natural language parsing have focussed on proposing kernels over parse trees, which are hand-crafted based on domain knowledge and computational considerations. in this paper we propose a method for defining kernels in terms of a probabilistic model of parsing. this model is then trained, so that the parameters of the probabilistic model reflect the generalizations in the training data. the method we propose then uses these trained parameters to define a kernel for reranking parse trees. in experiments, we use a neural network based statistical parser as the probabilistic model, and use the resulting kernel with the voted perceptron algorithm to rerank the top 20 parses from the probabilistic model. this method achieves a significant improvement over the accuracy of the probabilistic model.
independence and commitment: assumptions for rapid training and execution of rule-based pos taggers. this paper addresses the rule-based pos tagging method of brill, and questions the importance of rule interactions to its performance. adopting two assumptions that serve to exclude rule interactions during tagging and training, we arrive at some variants of brill's approach that are instances of decision list models. these models allow for both rapid training on large data sets and rapid tagger execution, giving tagging accuracy that is comparable to, or better than the brill method.
efficient incremental processing with categorial grammar. some problems are discussed that arise for incremental processing using certain flexible categorial grammars, which involve either undesirable parsing properties or failure to allow combinations useful to incrementality. we suggest a new calculus which, though 'designed' in relation to categorial interpretations of some notions of dependency grammar, seems to provide a degree of flexibility that is highly appropriate for incremental interpretation. we demonstrate how this grammar may be used for efficient incremental parsing, by employing normalisation techniques.
maximal incrementality in linear categorial deduction. recent work has seen the emergence of a common framework for parsing categorial grammar (cg) formalisms that fall within the 'type-logical' tradition (such as the lambek calculus and related systems), whereby some method of linear logic theorem proving is used in combination with a system of labelling that ensures only deductions appropriate to the relevant grammatical logic are allowed. the approaches realising this framework, however, have not so far addressed the task of incremental parsing --- a key issue in earlier work with 'flexible' categorial grammars. in this paper, the approach of (hepple, 1996) is modified to yield a linear deduction system that does allow flexible deduction and hence incremental processing, but that hence also suffers the problem of 'spurious ambiguity'. this problem is avoided via normalisation.
memoisation for glue language deduction and categorial parsing. the multiplicative fragment of linear logic has found a number of applications in computational linguistics: in the "glue language" approach to lfg semantics, and in the formulation and parsing of various categorial grammars. these applications call for efficient deduction methods. although a number of deduction methods for multiplicative linear logic are known, none of them are tabular methods, which bring a substantial efficiency gain by avoiding redundant computation (c.f. chart methods in cfg parsing): this paper presents such a method, and discusses its use in relation to the above applications.
an earley-style predictive chart parsing method for lambek grammars. we present a new chart parsing method for lambek grammars, inspired by a method for d-tree grammar parsing. the formulae of a lambek sequent are firstly converted into rules of an indexed grammar formalism, which are used in an earley-style predictive chart algorithm. the method is non-polynomial, but performs well for practical purposes---much better than previous chart methods for lambek grammars.
learning parse and translation decisions from examples with rich context. we present a knowledge and context-based system for parsing and translating natural language and evaluate it on sentences from the wall street journal. applying machine learning techniques, the system uses parse action examples acquired under supervision to generate a deterministic shift-reduce parser in the form of a decision structure. it relies heavily on context, as encoded in features which describe the morphological, syntactic, semantic and other aspects of a given parse state.
on the spatial uses of prepositions. at first glance, the spatial uses of prepositions seem to constitute a good semantic domain for a computational approach. one expects such uses will refer more or less strictly to a closed, explicit, and precise chunk of world knowledge. such an attitude is expressed in the following statement:"given descriptions of the shape of two objects, given their location (for example, by means or coordinates in some system of reference), and, in some cases, the location of an observer, one can select an appropriate preposition."this paper shows the fallacy of this claim. it addresses the problem of interpreting and generating "locative predications" (expressions made up of two noun-phrases governed by a preposition used spatially). it identifies and describes a number of object characteristics beyond shape (section 1) and contextual factors (section 2) which bear on these processes. drawing on these descriptions, the third section proposes core meanings for two categories of prepositions, and describes some of the transformations these core meanings are subject to in context. the last section outlines the main directions of inquiry suggested by the examples and observations in the paper.
ferret: interactive question-answering for real-world environments. this paper describes ferret, an interactive question-answering (q/a) system designed to address the challenges of integrating automatic q/a applications into real-world environments. ferret utilizes a novel approach to q/a - known as predictive questioning - which attempts to identify the questions (and answers) that users need by analyzing how a user interacts with a system while gathering information related to a particular scenario.
corpus-based discourse understanding in spoken dialogue systems. this paper concerns the discourse understanding process in spoken dialogue systems. this process enables the system to understand user utterances based on the context of a dialogue. since multiple candidates for the understanding result can be obtained for a user utterance due to the ambiguity of speech understanding, it is not appropriate to decide on a single understanding result after each user utterance. by holding multiple candidates for understanding results and resolving the ambiguity as the dialogue progresses, the discourse understanding accuracy can be improved. this paper proposes a method for resolving this ambiguity based on statistical information obtained from dialogue corpora. unlike conventional methods that use hand-crafted rules, the proposed method enables easy design of the discourse understanding process. experiment results have shown that a system that exploits the proposed method performs sufficiently and that holding multiple candidates for understanding results is effective.
learning to generate naturalistic utterances using reviews in spoken dialogue systems. spoken language generation for dialogue systems requires a dictionary of mappings between semantic representations of concepts the system wants to express and realizations of those concepts. dictionary creation is a costly process; it is currently done by hand for each dialogue domain. we propose a novel unsupervised method for learning such mappings from user reviews in the target domain, and test it on restaurant reviews. we test the hypothesis that user reviews that provide individual ratings for distinguished attributes of the domain entity make it possible to map review sentences to their semantic representation with high precision. experimental analyses show that the mappings learned cover most of the domain ontology, and provide good linguistic variation. a subjective user evaluation shows that the consistency between the semantic representations and the learned realizations is high and that the naturalness of the realizations is higher than a hand-crafted baseline.
parsing parallel grammatical representation. traditional accounts of quantifier scope employ qualitative constraints or rules to account for scoping preferences. this paper outlines a feature-based parsing algorithm for a grammar with multiple simultaneous levels of representation, one of which corresponds to a partial ordering among quantifiers according to scope. the optimal such ordering (as well as the ranking of other orderings) is determined in this grammar not by absolute constraints, but by stochastic heuristics based on the degree of alignment among the representational levels. a prolog implementation is described and its accuracy is compared with that of other accounts.
acquiring disambiguation rules from text. an effective procedure for automatically acquiring a new set of disambiguation rules for an existing deterministic parser on the basis of tagged text is presented. performance of the automatically acquired rules is much better than the existing hand-written disambiguation rules. the success of the acquired rules depends on using the linguistic information encoded in the parser; enhancements to various components of the parser improves the acquired rule set. this work suggests a path toward more robust and comprehensive syntactic analyzers.
noun classification from predicate-argument structures. a method of determining the similarity of nouns on the basis of a metric derived from the distribution of subject, verb and object in a large text corpus is described. the resulting quasi-semantic classification of nouns demonstrates the plausibility of the distributional hypothesis, and has potential application to a variety of tasks, including automatic indexing, resolving nominal compounds, and determining the scope of modification.
structural ambiguity and lexical relations. we propose that many ambiguous prepositional phrase attachments can be resolved on the basis of the relative strength of association of the preposition with verbal and nominal heads, estimated on the basis of distribution in an automatically parsed corpus. this suggests that a distributional approach can provide an approximate solution to parsing problems that, in the worst case, call for complex reasoning.
two constraints on speech act ambiguity. existing plan-based theories of speech act interpretation do not account for the conventional aspect of speech acts. we use patterns of linguistic features (e.g. mood, verb form, sentence adverbials, thematic roles) to suggest a range of speech act interpretations for the utterance. these are filtered using plan-based conversational implicatures to eliminate inappropriate ones. extended plan reasoning is available but not necessary for familiar forms. taking speech act ambiguity seriously, with these two constraints, explains how "can you pass the salt?" is a typical indirect request while "are you able to pass the salt?" is not.
graph branch algorithm: an optimum tree search method for scored dependency graph with arc co-occurrence constraints. various kinds of scored dependency graphs are proposed as packed shared data structures in combination with optimum dependency tree search algorithms. this paper classifies the scored dependency graphs and discusses the specific features of the "dependency forest" (df) which is the packed shared data structure adopted in the "preference dependency grammar" (pdg), and proposes the "graph branch algorithm" for computing the optimum dependency tree from a df. this paper also reports the experiment showing the computational amount and behavior of the graph branch algorithm.
a prosodic analysis of discourse segments in direction-giving monologues. this paper reports on corpus-based research into the relationship between intonational variation and discourse structure. we examine the effects of speaking style (read versus spontaneous) and of discourse segmentation method (text-alone versus text-and-speech) on the nature of this relationship. we also compare the acoustic-prosodic features of initial, medial, and final utterances in a discourse segment.
deep read: a reading comprehension system. this paper describes initial work on <b>deep read</b>, an automated reading comprehension system that accepts arbitrary text input (a story) and answers questions about it. we have acquired a corpus of 60 development and 60 test stories of 3<sup>rd</sup> to 6<sup>th</sup> grade material; each story is followed by short-answer questions (an answer key was also provided). we used these to construct and evaluate a baseline system that uses pattern matching (bag-of-words) techniques augmented with additional automated linguistic processing (stemming, name identification, semantic class identification, and pronoun resolution). this simple system retrieves the sentence containing the answer 30--40% of the time.
long distance pronominalisation and global focus. our corpus of descriptive text contains a significant number of long-distance pronominal references (8.4% of the total). in order to account for how these pronouns are intepreted, we re-examine grosz and sidner's theory of the attentional state, and in particular the use of the global focus to supplement centering theory. our corpus evidence concerning these long-distance pronominal references, as well as studies of the use of descriptions, proper names and ambiguous uses of pronouns, lead us to conclude that a discourse focus stack mechanism of the type proposed by sidner is essential to account for the use of these referring expressions. we suggest revising the grosz & sidner framework by allowing for the possibility that an entity in a focus space may have special status.
ontological promiscuity. to facilitate work in discourse interpretation, the logical form of english sentences should be both close to english and syntactically simple. in this paper i propose a logical notation which is first-order and nonintensional, and for which semantic translation can be naively compositional. the key move is to expand what kinds of entities one allows in one's ontology, rather than complicating the logical notation, the logical form of sentences, or the semantic translation process. three classical problems - opaque adverbials, the distinction between de re and de dicto belief reports, and the problem of identity in intensional contexts - are examined for the difficulties they pose for this logical notation, and it is shown that the difficulties can be overcome. the paper closes with a statement about the view of semantics that is presupposed by this approach.
a theory of parallelism and the case of vp ellipsis. we provide a general account of parallelism in discourse, and apply it to the special case of resolving possible readings for instances of vp ellipsis. we show how several problematic examples are accounted for in a natural and straightforward fashion. the generality of the approach makes it directly applicable to a variety of other types of ellipsis and reference.
interpretation as abduction. an approach to abductive inference developed in the tacitus project has resulted in a dramatic simplification of how the problem of interpreting texts is conceptualized. its use in solving the local pragmatics problems of reference, compound nominals, syntactic ambiguity, and metonymy is described and illustrated. it also suggests an elegant and thorough integration of syntax, semantics, and pragmatics.
parsing with generative models of predicate-argument structure. the model used by the ccg parser of hockenmaier and steedman (2002b) would fail to capture the correct bilexical dependencies in a language with freer word order, such as dutch. this paper argues that probabilistic parsers should therefore model the dependencies in the predicate-argument structure, as in the model of clark et al. (2002), and defines a generative model for ccg derivations that captures these dependencies, including bounded and unbounded long-range dependencies.
creating a ccgbank and a wide-coverage ccg lexicon for german. we present an algorithm which creates a german ccgbank by translating the syntax graphs in the german tiger corpus into ccg derivation trees. the resulting corpus contains 46,628 derivations, covering 95% of all complete sentences in tiger. lexicons extracted from this corpus contain correct lexical entries for 94% of all known tokens in unseen text.
generative models for statistical parsing with combinatory categorial grammar. this paper compares a number of generative probability models for a wide-coverage combinatory categorial grammar (ccg) parser. these models are trained and tested on a corpus obtained by translating the penn treebank trees into ccg normal-form derivations. according to an evaluation of unlabeled word-word dependencies, our best model achieves a performance of 89.9%, comparable to the figures given by collins (1999) for a linguistically less expressive grammar. in contrast to gildea (2001), we find a significant improvement from modeling word-word dependencies.
the formal consequences of using variables in ccg categories. combinatory categorial grammars, ccgs, (steedman 1985) have been shown by weir and joshi (1988) to generate the same class of languages as tree-adjoining grammars (tag), head grammars (hg), and linear indexed grammars (lig). in this paper, i will discuss the effect of using variables in lexical category assignments in ccgs. it will be shown that using variables in lexical categories can increase the weak generative capacity of ccgs beyond the class of grammars listed above.
a semantically-derived subset of english for hardware verification. to verify hardware designs by model checking, circuit specifications are commonly expressed in the temporal logic ctl. automatic conversion of english to ctl requires the definition of an appropriately restricted subset of english. we show how the limited semantic expressibility of ctl can be exploited to derive a <i>hierarchy</i> of subsets. our strategy avoids potential difficulties with approaches that take existing computational semantic analyses of english as their starting point---such as the need to ensure that all sentences in the subset possess a ctl translation.
integration of visual inter-word constraints and linguistic knowledge in degraded text recognition. degraded text recognition is a difficult task. given a noisy text image, a word recognizer can be applied to generate several candidates for each word image. high-level knowledge sources can then be used to select a decision from the candidate set for each word image. in this paper, we propose that visual inter-word constraints can be used to facilitate candidate selection. visual inter-word constraints provide a way to link word images inside the text page, and to interpret them systematically.
exploring the potential of intractable parsers. we revisit the idea of history-based parsing, and present a history-based parsing framework that strives to be simple, general, and flexible. we also provide a decoder for this probability model that is linear-space, optimal, and anytime. a parser based on this framework, when evaluated on section 23 of the penn tree-bank, compares favorably with other state-of-the-art approaches, in terms of both accuracy and speed.
an algorithm for generating referential descriptions with flexible interfaces. most algorithms dedicated to the generation of referential descriptions widely suffer from a fundamental problem: they make too strong assumptions about adjacent processing components, resulting in a limited coordination with their perceptive and linguistics data, that is, the provider for object descriptors and the lexical expression by which the chosen descriptors is ultimately realized. motivated by this deficit, we present a new algorithm that (1) allows for a widely unconstrained, incremental, and goal-driven selection of descriptors, (2) integrates linguistic constraints to ensure the expressibility of the chosen descriptors, and (3) provides means to control the appearance of the created referring expression. hence, the main achievement of our approach lies in providing a core algorithm that makes few assumptions about other processing components and improves the flow of control between modules.
transformation-based interpretation of implicit parallel structures: reconstructing the meaning of "vice versa" and similar linguistic operators. successful participation in dialogue as well as understanding written text requires, among others, interpretation of specifications implicitly conveyed through parallel structures. while those whose reconstruction requires insertion of a missing element, such as gapping and ellipsis, have been addressed to a certain extent by computational approaches, there is virtually no work addressing parallel structures headed by vice versa-like operators, whose reconstruction requires transformation. in this paper, we address the meaning reconstruction of such constructs by an informed reasoning process. the applied techniques include building deep semantic representations, application of categories of patterns underlying a formal reconstruction, and using pragmatically-motivated and empirically justified preferences. we present an evaluation of our algorithm conducted on a uniform collection of texts containing the phrases in question.
planning coherent multisentential text. though most text generators are capable of simply stringing together more than one sentence, they cannot determine which order will ensure a coherent paragraph. a paragraph is coherent when the information in successive sentences follows some pattern of inference or of knowledge with which the hearer is familiar. to signal such inferences, speakers usually use relations that link successive sentences in fixed ways. a set of 20 relations that span most of what people usually say in english is proposed in the rhetorical structure theory of mann and thompson. this paper describes the formalization of these relations and their use in a prototype text planner that structures input elements into coherent paragraphs.
two types of planning in language generation. as our understanding of natural language generation has increased, a number of tasks have been separated from realization and put together under the heading "text planning". so far, however, no-one has enumerated the kinds of tasks a text planner should be able to do. this paper describes the principal lesson learned in combining a number of planning tasks in a planner-realizer: planning and realization should be interleaved, in a limited-commitment planning paradigm, to perform two types of planning: prescriptive and restrictive. limited-commitment planning consists of both prescriptive (hierarchical expansion) planning and of restrictive planning (selecting from options with reference to the status of active goals). at present, existing text planners use prescriptive plans exclusively. however, a large class of planner tasks, especially those concerned with the pragmatic (non-literal) content of text such as style and slant, is most easily performed under restrictive planning. the kinds of tasks suited to each planning style are listed, and a program that uses both styles is described.
when conset meets synset: a preliminary survey of an ontological lexical resource based on chinese characters. this paper describes an on-going project concerning with an ontological lexical resource based on the abundant conceptual information grounded on chinese characters. the ultimate goal of this project is set to construct a cognitively sound and computationally effective character-grounded machine-understandable resource. philosophically, chinese ideogram has its ontological status, but its applicability to the nlp task has not been expressed explicitly in terms of language resource. we thus propose the first attempt to locate chinese characters within the context of ontology. having the primary success in applying it to some nlp tasks, we believe that the construction of this knowledge resource will shed new light on theoretical setting as well as the construction of chinese lexical semantic resources.
planning reference choices for argumentative texts. this paper deals with the reference choices involved in the generation of argumentative text. since a natual segmentation of discourse into attentional spaces is needed to carry out this task, this paper first proposes an architecture for natural language generation that combines hierarchical planning and focus-guided navigation, a work in its own right. while hierarchical planning spans out an attentional hierarchy of the discourse produced, local navigation fills details into the primitive discourse spaces. the usefulness of this architecure actually goes beyond the particular domain of application for which it is developed.a piece of argumentative text such as the proof of a mathematical theorem conveys a sequence of derivations. for each step of derivation, the premises derived in the previous context and the inference method (such as the application of a particular theorem or definition) must be made clear. although not restricted to nominal phrases, our reference decisions are similar to those concerning nominal subsequent referring expressions. based on the work of reichmann, this paper presents a discourse theory that handles reference choices by taking into account both textual distance as well as the attentional hierarchy.
chinese-korean word alignment based on linguistic comparison. word alignment problem between parallel corpora is based on the similar characteristics of two aligned words in two languages. we investigate linguistic-knowledge-based word similarity measures while other previous works heavily rely on statistical information, and their limits will be discussed. linguistic knowledge is acquired from linguistic comparison of all layers between two languages, for chinese and korean in this paper.
information extraction from voicemail. in this paper we address the problem of extracting key pieces of information from voicemail messages, such as the identity and phone number of the caller. this task differs from the named entity task in that the information we are interested in is a subset of the named entities in the message, and consequently, the need to pick the correct subset makes the problem more difficult. also, the caller's identity may include information that is not typically associated with a named entity. in this work, we present three information extraction methods, one based on hand-crafted rules, one based on maximum entropy tagging, and one based on probabilistic transducer induction. we evaluate their performance on both manually transcribed messages and on the output of a speech recognition system.
american sign language generation: multimodal nlg with multiple linguistic channels. software to translate english text into american sign language (asl) animation can improve information accessibility for the majority of deaf adults with limited english literacy. asl natural language generation (nlg) is a special form of multimodal nlg that uses multiple linguistic output channels. asl nlg technology has applications for the generation of gesture animation and other communication signals that are not easily encoded as text strings.
a study on automatically extracted keywords in text categorization. this paper presents a study on if and how automatically extracted keywords can be used to improve text categorization. in summary we show that a higher performance --- as measured by micro-averaged f-measure on a standard text categorization collection --- is achieved when the full-text representation is combined with the automatically extracted keywords. the combination is obtained by giving higher weights to words in the full-texts that are also extracted as keywords. we also present results for experiments in which the keywords are the only input to the categorizer, either represented as unigrams or intact. of these two experiments, the unigrams have the best performance, although neither performs as well as headlines only.
raisins, sultanas, and currants: lexical classification and abstraction via context priming. in this paper we discuss the results of experiments which use a context, essentially an ordered set of lexical items, as the seed from which to build a network representing statistically important relationships among lexical items in some corpus. a metric is then applied to the nodes in the network in order to discover those pairs of items related by high indices of similarity. the goal of this research is to instantiate a class of items corresponding to each item in the priming context. we believe that this instantiation process is ultimately a special case of abstraction over the entire network; in this abstraction, similar nodes are collapsed into metanodes which may then function as if they were single lexical items.
acquiring the meaning of discourse markers. this paper applies machine learning techniques to acquiring aspects of the meaning of discourse markers. three subtasks of acquiring the meaning of a discourse marker are considered: learning its polarity, veridicality, and type (i.e. causal, temporal or additive). accuracy of over 90% is achieved for all three tasks, well above the baselines.
modelling the substitutability of discourse connectives. processing discourse connectives is important for tasks such as discourse parsing and generation. for these tasks, it is useful to know which connectives can signal the same coherence relations. this paper presents experiments into modelling the substitutability of discourse connectives. it shows that substitutability effects distributional similarity. a novel variance-based function for comparing probability distributions is found to assist in predicting substitutability.
spontaneous speech understanding for robust multi-modal human-robot communication. this paper presents a speech understanding component for enabling robust situated human-robot communication. the aim is to gain semantic interpretations of utterances that serve as a basis for multi-modal dialog management also in cases where the recognized word-stream is not grammatically correct. for the understanding process, we designed semantic processable units, which are adapted to the domain of situated communication. our framework supports the specific characteristics of spontaneous speech used in combination with gestures in a real world scenario. it also provides information about the dialog acts. finally, we present a processing mechanism using these concept structures to generate the most likely semantic interpretation of the utterances and to evaluate the interpretation with respect to semantic coherence.
evaluating translational correspondence using annotation projection. recently, statistical machine translation models have begun to take advantage of higher level linguistic structures such as syntactic dependencies. underlying these models is an assumption about the directness of translational correspondence between sentences in the two languages; however, the extent to which this assumption is valid and useful is not well understood. in this paper, we present an empirical study that quantifies the degree to which syntactic dependencies are preserved when parses are projected directly from english to chinese. our results show that although the direct correspondence assumption is often too restrictive, a small set of principled, elementary linguistic transformations can boost the quality of the projected chinese parses by 76% relative to the unimproved baseline.
context-dependent smt model using bilingual verb-noun collocation. in this paper, we propose a new context-dependent smt model that is tightly coupled with a language model. it is designed to decrease the translation ambiguities and efficiently search for an optimal hypothesis by reducing the hypothesis search space. it works through reciprocal incorporation between source and target context: a source word is determined by the context of previous and corresponding target words and the next target word is predicted by the pair consisting of the previous target word and its corresponding source word. in order to alleviate the data sparseness in chunk-based translation, we take a stepwise back-off translation strategy. moreover, in order to obtain more semantically plausible translation results, we use bilingual verb-noun collocations; these are automatically extracted by using chunk alignment and a monolingual dependency parser. as a case study, we experimented on the language pair of japanese and korean. as a result, we could not only reduce the search space but also improve the performance.
tense trees as the "fine structure" of discourse. we present a new compositional tense-aspect deindexing mechanism that makes use of tense trees as components of discourse contexts. the mechanism allows reference episodes to be correctly identified even for embedded clauses and for discourse that involves shifts in temporal perspective, and permits deindexed logical forms to be automatically computed with a small number of deindexing rules.
terminological variation, a means of identifying research topics from texts. after extracting terms from a corpus of titles and abstracts in english, syntactic variation relations are identified amongst them in order to detect research topics. three types of syntactic variations were studied: permutation, expansion and substitution. these syntactic variations yield other relations of formal and conceptual nature. basing on a distinction of the variation relations according to the grammatical function affected in a term - head or modifier - term variants are first clustered into connected components which are in turn clustered into classes. these classes relate two or more components through variations involving a change of head word, thus of topic. the graph obtained reveals the global organisation of research topics in the corpus. a clustering method has been built to compute such classes of research topics.
a hierarchical account of referential accessibility. in this paper, we outline a theory of referential accessibility called veins theory (vt). we show how vt addresses the problem of "left satellites", currently a problem for stack-based models, and show that vt can be used to significantly reduce the search space for antecedents. we also show that vt provides a better model for determining domains of referential accessibility, and discuss how vt can be used to address various issues of structural ambiguity.
a common framework for syntactic annotation. it is widely recognized that the proliferation of annotation schemes runs counter to the need to re-use language resources, and that standards for linguistic annotation are becoming increasingly mandatory. to answer this need, we have developed a representation framework comprised of an abstract model for a variety of different annotation types (e.g., morpho-syntactic tagging, syntactic annotation, co-reference annotation, etc.), which can be instantiated in different ways depending on the annotator s approach and goals. in this paper we provide an overview of our representation framework and demonstrate its applicability to syntactic annotation. we show how the framework can contribute to comparative evaluation and merging of parser output and diverse syntactic annotation schemes.
exploiting syntactic patterns as clues in zero-anaphora resolution. we approach the zero-anaphora resolution problem by decomposing it into intra-sentential and inter-sentential zero-anaphora resolution. for the former problem, syntactic patterns of the appearance of zero-pronouns and their antecedents are useful clues. taking japanese as a target language, we empirically demonstrate that incorporating rich syntactic pattern features in a state-of-the-art learning-based anaphora resolution model dramatically improves the accuracy of intra-sentential zero-anaphora, which consequently improves the overall performance of zero-anaphora resolution.
information classification and navigation based on 5w1h of the target information. this paper proposes a method by which 5w1h (who, when, where, what, why, how, and predicate) information is used to classify and navigate japanese-language texts. 5w1h information, extracted from text data, has an access platform with three functions: episodic retrieval, multi-dimensional classification, and overall classification. in a six-month trial, the platform was used by 50 people to access 6400 newspaper articles. the three functions proved to be effective for office documentation work and the precision of extraction was approximately 82%.
feedback cleaning of machine translation rules using automatic evaluation. when rules of transfer-based machine translation (mt) are automatically acquired from bilingual corpora, incorrect/redundant rules are generated due to acquisition errors or translation variety in the corpora. as a new countermeasure to this problem, we propose a feedback cleaning method using automatic evaluation of mt quality, which removes incorrect/redundant rules as a way to increase the evaluation score. bleu is utilized for the automatic evaluation. the hill-climbing algorithm, which involves features of this task, is applied to searching for the optimal combination of rules. our experiments show that the mt quality improves by 10% in test sentences according to a subjective evaluation. this is considerable improvement over previous methods.
a concurrent approach to the automatic extraction of subsegmental primes and phonological constituents from speech. we demonstrate the feasibility of using unary primes in speech-driven language processing. proponents of government phonology (one of several phonological frameworks in which speech segments are represented as combinations of relatively few subsegmental primes) claim that primes are acoustically realisable. this claim is examined critically searching out signatures for primes in multispeaker speech signal data. in response to a wide variation in the ease of detection of primes, it is proposed that the computational approach to phonology-based, speech-driven software should be organised in stages. after each stage, computational processes like segmentation and lexical access can be launched to run <u>concurrently</u> with later stages of prime detection.
the limits of unification. current complex-feature based grammars use a single procedure---unification---for a multitude of purposes, among them, enforcing formal agreement between purely syntactic features. this paper presents evidence from several natural languages that unification---variable-matching combined with variable substitution---is the wrong mechanism for effecting agreement. the view of grammar developed here is one in which unification is used for semantic interpretation, while purely formal agreement involves only a check for non-distinctness---i.e. variable-matching without variable substitution.
a computational mechanism for pronominal reference. this paper describes an implemented mechanism for handling bound anaphora, disjoint reference, and pronominal reference. the algorith maps over every node in a parse tree in a left-to-right, depth first manner. forward and backwards coreference, and disjoint reference are assigned during this tree walk. a semantic interpretation procedure is used to deal with multiple antecedents.
automatic noun classification by using japanese-english word pairs. this paper describes a method of classifying semantically similar nouns. the approach is based on the "distributional hypothesis". our approach is characterized by distinguishing among senses of the same word in order to resolve the "polysemy" issue. the classification result demonstrates that our approach is successful.
lexical semantics to disambiguate polysemous phenomena of japanese adnominal constituents. we exploit and extend the generative lexicon theory to develop a formal description of adnominal constituents in a lexicon which can deal with linguistic phenomena found in japanese adnominal constituents. we classify the problematic behavior into "static disambiguation" and "dynamic disambiguation" tasks. static disambiguation can be done using lexical information in a dictionary, whereas dynamic disambiguation requires inferences at the knowledge representation level.
automated japanese essay scoring system based on articles written by experts. we have developed an automated japanese essay scoring system called jess. the system needs expert writings rather than expert raters to build the evaluation model. by detecting statistical outliers of predetermined aimed essay features compared with many professional writings for each prompt, our system can evaluate essays. the following three features are examined: (1) rhetoric --- syntactic variety, or the use of various structures in the arrangement of phases, clauses, and sentences, (2) organization --- characteristics associated with the orderly presentation of ideas, such as rhetorical features and linguistic cues, and (3) content --- vocabulary related to the topic, such as relevant information and precise or specialized vocabulary. the final evaluation score is calculated by deducting from a perfect score assigned by a learning process using editorials and columns from the mainichi daily news newspaper. a diagnosis for the essay is also given.
exploring the characteristics of multi-party dialogues. this paper describes novel results on the characteristics of three-party dialogues by quantitatively comparing them with those of two-party. in previous dialogue research, two-party dialogues are mainly focussed because data collection of multi-party dialogues is difficult and there are very few theories handling them, although research on multi-party dialogues is expected to be of much use in building computer supported collaborative work environments and computer assisted instruction systems. in this paper, firstly we describe our data collection method of multi-party dialogues using a meeting scheduling task, which enables us to compare three-party dialogues with those of two party. then we quantitively compare these two kinds of dialogues such as the number of characters and turns and patterns of information exchanges. lastly we show that patterns of information exchanges in speaker alternation and initiative-taking can be used to characterise three-party dialogues.
japanese named entity recognition based on a simple rule generator and decision tree learning. named entity (ne) recognition is a task in which proper nouns and numerical information in a document are detected and classified into categories such as person, organization, location, and date. ne recognition plays an essential role in information extraction systems and question answering systems. it is well known that hand-crafted systems with a large set of heuristic rules are difficult to maintain, and corpus-based statistical approaches are expected to be more robust and require less human intervention. several statistical approaches have been reported in the literature. in a recent japanese ne workshop, a maximum entropy (me) system outperformed decision tree systems and most hand-crafted systems. here, we propose an alternative method based on a simple rule generator and decision tree learning. our experiments show that its performance is comparable to the me approach. we also found that it can be trained more efficiently with a large set of training data and that it improves readability.
dialogue act tagging for instant messaging chat sessions. instant messaging chat sessions are real-time text-based conversations which can be analyzed using dialogue-act models. we describe a statistical approach for modelling and detecting dialogue acts in instant messaging dialogue. this involved the collection of a small set of task-based dialogues and annotating them with a revised tag set. we then dealt with segmentation and synchronisation issues which do not arise in spoken dialogue. the model we developed combines naive bayes and dialogue-act n-grams to obtain better than 80% accuracy in our tagging experiment.
towards the orwellian nightmare: separation of business and personal emails. this paper describes the largest scale annotation project involving the enron email corpus to date. over 12,500 emails were classified, by humans, into the categories "business" and "personal", and then sub-categorised by type within these categories. the paper quantifies how well humans perform on this task (evaluated by inter-annotator agreement). it presents the problems experienced with the separation of these language types. as a final section, the paper presents preliminary results using a machine to perform this classification task.
optimizing the computational lexicalization of large grammars. the computational lexicalization of a grammar is the optimization of the links between lexicalized rules and lexical items in order to improve the quality of the bottom-up filtering during parsing. this problem is np-complete and untractable on large grammars. an approximation algorithm is presented. the quality of the suboptimal solution is evaluated on real-world grammars as well as on randomly generated ones.
improving automatic indexing through concept combination and term enrichment. although indexes may overlap, the output of an automatic indexer is generally presented as a flat and unstructured list of terms. our purpose is to exploit term overlap and embedding so as to yield a substantial qualitative and quantitative improvement in automatic indexing through concept combination. the increase in the volume of indexing is 10.5% for free indexing and 52.3% for controlled indexing. the resulting structure of the indexed corpus is a partial conceptual analysis.
syntagmatic and paradigmatic representations of term variation. a two-tier model for the description of morphological, syntactic and semantic variations of multi-word terms is presented. it is applied to term normalization of french and english corpora in the medical and agricultural domains. five differenct sources of morphological and semantic knowledge are exploited (multext, celex, agrovoc, wordnet1.6, and microsoft word97 thesaurus).
expansion of multi-word terms for indexing and retrieval using morphology and syntax. a system for the automatic production of controlled index terms is presented using linguistically-motivated techniques. this includes a finite-state part of speech tagger, a derivational morphological processor for analysis and generation, and a unification-based shallow-level parser using transformational rules over syntactic patterns. the contribution of this research is the successful combination of parsing over a seed term list coupled with derivational morphology to achieve greater coverage of multi-word terms for indexing and retrieval. final results are evaluated for precision and recall, and implications for indexing and retrieval are discussed.
using mutual information to resolve query translation ambiguities and query term weighting. an easy way of translating queries in one language to the other for cross-language information retrieval (ir) is to use a simple bilingual dictionary. because of the general-purpose nature of such dictionaries, however, this simple method yields a severe translation ambiguity problem. this paper describes the degree to which this problem arises in korean-english cross-language ir and suggests a relatively simple yet effective method for disambiguation using mutual information statistics obtained only from the target document collection. in this method, mutual information is used not only to select the best candidate but also to assign a weight to query terms in the target language. our experimental results based on the trec-6 collection shows that this method can achieve up to 85% of the monolingual retrieval case and 96% of the manual disambiguation case.
parametric models of linguistic count data. it is well known that occurrence counts of words in documents are often modeled poorly by standard distributions like the binomial or poisson. observed counts vary more than simple models predict, prompting the use of overdispersed models like gamma-poisson or beta-binomial mixtures as robust alternatives. another deficiency of standard models is due to the fact that most words never occur in a given document, resulting in large amounts of zero counts. we propose using zero-inflated models for dealing with this, and evaluate competing models on a naive bayes text classification task. simple zero-inflated models can account for practically relevant variation, and can be easier to work with than overdispersed models.
a system for translating locative prepositions from english into french. machine translation of locative prepositions is not straightforward, even between closely related languages. this paper discusses a system of translation of locative prepositions between english and french. the system is based on the premises that english and french do not always conceptualize objects in the same way, and that this accounts for the major differences in the ways that locative prepositions are used in these languages. this paper introduces knowledge representations of conceptualizations of objects, and a method for translating prepositions based on these conceptual representations.
multi-engine machine translation guided by explicit word matching. we describe a new approach for synthetically combining the output of several different machine translation (mt) engines operating on the same input. the goal is to produce a synthetic combination that surpasses all of the original systems in translation quality. our approach uses the individual mt engines as "black boxes" and does not require any explicit cooperation from the original mt systems. a decoding algorithm uses explicit word matches, in conjunction with confidence estimates for the various engines and a trigram language model in order to score and rank a collection of sentence hypotheses that are synthetic combinations of words from the various original engines. the highest scoring sentence hypothesis is selected as the final output of our system. experiments, using several arabic-to-english systems of similar quality, show a substantial improvement in the quality of the translation output.
exploiting non-local features for spoken language understanding. in this paper, we exploit non-local features as an estimate of long-distance dependencies to improve performance on the statistical spoken language understanding (slu) problem. the statistical natural language parsers trained on text perform unreliably to encode non-local information on spoken language. an alternative method we propose is to use trigger pairs that are automatically extracted by a feature induction algorithm. we describe a light version of the inducer in which a simple modification is efficient and successful. we evaluate our method on an slu task and show an error reduction of up to 27% over the base local model.
parasession on topics in interactive discourse influence of the problem context. my comments are organized within the framework suggested by the panel chair, barbara grosz, which i find very appropriate. all of my comments pertain to the various issues raised by her; however, wherever possible i will discuss these issues more in the context of the "information seeking" interaction and the data base domain.the primary question is how the purpose of the interaction or "the problem context" affects what is said and how it is interpreted. the two separate aspects of this question that must be considered are the <u>function</u> and the <u>domain</u> of the discourse.
enriching the output of a parser using memory-based learning. we describe a method for enriching the output of a parser with information available in a corpus. the method is based on graph rewriting using memory-based learning, applied to dependency structures. this general framework allows us to accurately recover both grammatical and semantic information as well as non-local dependencies. it also facilitates dependency-based evaluation of phrase structure parsers. our method is largely independent of the choice of parser and corpus, and shows state of the art performance.
unsupervised segmentation of chinese text by use of branching entropy. we propose an unsupervised segmentation method based on an assumption about language data: that the increasing point of entropy of successive characters is the location of a word boundary. a large-scale experiment was conducted by using 200 mb of unsegmented training data and 1 mb of test data, and precision of 90% was attained with recall being around 80%. moreover, we found that the precision was stable at around 90% independently of the learning data size.
phrase structure trees bear more fruit than you would have thought. in this paper we will present several results concerning phrase structure trees. these results show that phrase structure trees, when viewed in certain ways, have much more descriptive power than one would have thought. we have given a brief account of local constraints on structural descriptions and an intuitive proof of a theorem about local constraints. we have compared the local constraints approach to some aspects of gazdar's framework and that of peters and ritchie and of karttunen. we have also presented some results on skeletons (phrase structure trees without labels) which show that phrase structure trees, even when deprived of the labels, retain in a certain sense all the structural information. this result has implications for grammatical inference procedures.
combining multiple, large-scale resources in a reusable lexicon for natural language generation. a lexicon is an essential component in a generation system but few efforts have been made to build a rich, large-scale lexicon and make it reusable for different generation applications. in this paper, we describe our work to build such a lexicon by combining multiple, heterogeneous linguistic resources which have been developed for other purposes. novel transformation and integration of resources is required to reuse them for generation. we also applied the lexicon to the lexical choice and realization component of a practical generation application by using a multi-level feedback architecture. the integration of the lexicon and the architecture is able to effectively improve the system paraphrasing power, minimize the chance of grammatical errors, and simplify the development process substantially.
text segmentation using reiteration and collocation. a method is presented for segmenting text into subtopic areas. the proportion of related pairwise words is calculated between adjacent windows of text to determine their lexical similarity. the lexical cohesion relations of reiteration and collocation are used to identify related words. these relations are automatically located using a combination of three linguistic features: word repetition, collocation and relation weights. this method is shown to successfully detect known subject changes in text and corresponds well to the segmentations placed by test subjects.
treatment of long distance dependencies in lfg and tag: functional uncertainty in lfg is a corollary in tag. in this paper the functional uncertainty machinery in lfg is compared with the treatment of long distance dependencies in tag. it is shown that the functional uncertainty machinery is redundant in tag, i.e., what functional uncertainty accomplishes for lfg follows from the tag formalism itself and some aspects of the linguistic theory instantiated in tag. it is also shown that the analyses provided by the functional uncertainty machinery can be obtained without requiring power beyond mildly context-sensitive grammars. some linguistic and computational aspects of these results have been briefly discussed also.
a framenet-based semantic role labeler for swedish. we present a framenet-based semantic role labeling system for swedish text. as training data for the system, we used an annotated corpus that we produced by transferring framenet annotation from the english side to the swedish side in a parallel corpus. in addition, we describe two frame element bracketing algorithms that are suitable when no robust constituent parsers are available. we evaluated the system on a part of the framenet example corpus that we translated manually, and obtained an accuracy score of 0.75 on the classification of presegmented frame elements, and precision and recall scores of 0.67 and 0.47 for the complete task.
questionbank: creating a corpus of parse-annotated questions. this paper describes the development of questionbank, a corpus of 4000 parse-annotated questions for (i) use in training parsers employed in qa, and (ii) evaluation of question parsing. we present a series of experiments to investigate the effectiveness of questionbank as both an exclusive and supplementary training resource for a state-of-the-art parser in parsing both question and non-question test sets. we introduce a new method for recovering empty nodes and their antecedents (capturing long distance dependencies) from parser output in cfg trees using lfg f-structure reentrancies. our main findings are (i) using questionbank training data improves parser performance to 89.75% labelled bracketing f-score, an increase of almost 11% over the baseline; (ii) back-testing experiments on non-question data (penn-ii wsj section 23) shows that the retrained parser does not suffer a performance drop on non-question material; (iii) ablation experiments show that the size of training material provided by questionbank is sufficient to achieve optimal results; (iv) our method for recovering empty nodes captures long distance dependencies in questions from the atis corpus with high precision (96.82%) and low recall (39.38%). in summary, questionbank provides a useful new resource in parser-based qa research.
joint and conditional estimation of tagging and parsing models. this paper compares two different ways of estimating statistical language models. many statistical nlp tagging and parsing models are estimated by maximizing the (joint) likelihood of the fully-observed training data. however, since these applications only require the conditional probability distributions, these distributions can in principle be learnt by maximizing the conditional likelihood of the training data. perhaps somewhat surprisingly, models estimated by maximizing the joint were superior to models estimated by maximizing the conditional, even though some of the latter models intuitively had access to "more information".
a simple pattern-matching algorithm for recovering empty nodes and their antecedents. this paper describes a simple pattern-matching algorithm for recovering empty nodes and identifying their co-indexed antecedents in phrase structure trees that do not contain this information. the patterns are minimal connected tree fragments containing an empty node and all other nodes co-indexed with it. this paper also proposes an evaluation procedure for empty node recovery procedures which is independent of most of the details of phrase structure, which makes it possible to compare the performance of empty node recovery on parser output with the empty node annotations in a gold-standard corpus. evaluating the algorithm on the output of charniak's parser (charniak, 2000) and the penn treebank (marcus et al., 1993) shows that the pattern-matching algorithm does surprisingly well on the most frequently occuring types of empty nodes given its simplicity.
obfuscating document stylometry to preserve author anonymity. this paper explores techniques for reducing the effectiveness of standard authorship attribution techniques so that an author a can preserve anonymity for a particular document d. we discuss feature selection and adjustment and show how this information can be fed back to the author to create a new document d' for which the calculated attribution moves away from a. since it can be labor intensive to adjust the document in this fashion, we attempt to quantify the amount of effort required to produce the anonymized document and introduce two levels of anonymization: shallow and deep. in our test set, we show that shallow anonymization can be achieved by making 14 changes per 1000 words to reduce the likelihood of identifying a as the author by an average of more than 83%. for deep anonymization, we adapt the unmasking work of koppel and schler to provide feedback that allows the author to choose the level of anonymization.
parsing with discontinuous constituents. by generalizing the notion of location of a constituent to allow discontinuous loctaions, one can describe the discontinuous constituents of non-configurational languages. these discontinuous constituents can be described by a variant of definite clause grammars, and these grammars can be used in conjunction with a proof procedure to create a parser for non-configurational languages.
a statistical analysis of morphemes in japanese terminology. in this paper i will report the result of a quantitative analysis of the dynamics of the constituent elements of japanese terminology. in japanese technical terms, the linguistic contribution of morphemes greatly differ according to their types of origin. to analyse this aspect, a quantitative method is applied, which can properly characterise the dynamic nature of morphemes in terminology on the basis of a small sample.
deductive parsing with multiple levels of representation. this paper discusses a sequence of deductive parsers, called pad1 -- pad5, that utilize an axiomatization of the principles and parameters of gb theory, including a restricted transformational component (move-&alpha;). pad2 uses an inference control strategy based on the 'freeze' predicate of prolog-ii, while pad3 -- 5 utilize the unfold-fold transformation to transform the original axiomatization into a form that functions as a recursive descent prolog parser for the fragment.
polarized unification grammars. this paper proposes a generic mathematical formalism for the combination of various structures: strings, trees, dags, graphs and products of them. the polarization of the objects of the elementary structures controls the saturation of the final structure. this formalism is both elementary and powerful enough to strongly simulate many grammar formalisms, such as rewriting systems, dependency grammars, tag, hpsg and lfg.
expressing disjunctive and negative feature constraints with classical first-order logic. in contrast to the "designer logic" approach, this paper shows how the attribute-value feature structures of unification grammar and constraints on them can be axiomatized in classical first-order logic, which can express disjunctive and negative constraints. because only quantifier-free formulae are used in the axiomatization, the satisfiability problem is np-complete.
finite-state approximation of constraint-based grammars using left-corner grammar transforms. this paper describes how to construct a finite-state machine (fsm) approximating a 'unification-based' grammar using a left-corner grammar transform. the approximation is presented as a series of grammar transforms, and is exact for left-linear and right-linear cfgs, and for trees up to a user-specified depth of center-embedding.
robust, finite-state parsing for spoken language understanding. human understanding of spoken language appears to integrate the use of contextual expectations with acoustic level perception in a tightly-coupled, sequential fashion. yet computer speech understanding systems typically pass the transcript produced by a speech recognizer into a natural language parser with no integration of acoustic and grammatical constraints. one reason for this is the complexity of implementing that integration. to address this issue we have created a robust, semantic parser as a single finite-state machine (fsm). as such, its run-time action is less complex than other robust parsers that are based on either chart or generalized left-right (glr) architectures. therefore, we believe it is ultimately more amenable to direct integration with a speech decoder.
a tag-based noisy-channel model of speech repairs. this paper describes a noisy channel model of speech repairs, which can identify and correct repairs in speech transcripts. a syntactic parser is used as the source model, and a novel type of tag-based transducer is the channel model. the use of tag is motivated by the intuition that the reparandum is a "rough copy" of the repair. the model is trained and tested on the switchboard disfluency-annotated corpus.
automatic construction of polarity-tagged corpus from html documents. this paper proposes a novel method of building polarity-tagged corpus from html documents. the characteristics of this method is that it is fully automatic and can be applied to arbitrary html documents. the idea behind our method is to utilize certain layout structures and linguistic pattern. by using them, we can automatically extract such sentences that express opinion. in our experiment, the method could construct a corpus consisting of 126,610 sentences.
memoization of coroutined constraints. some linguistic constraints cannot be effectively resolved during parsing at the location in which they are most naturally introduced. this paper shows how constraints can be propagated in a memoizing parser (such as a chart parser) in much the same way that variable bindings are, providing a general treatment of constraint coroutining in memoization. prolog code for a simple application of our technique to bouma and van noord's (1994) categorial grammar analysis of dutch is provided.
verb paraphrase based on case frame alignment. this paper describes a method of translating a predicate-argument structure of a verb into that of an equivalent verb, which is a core component of the dictionary-based paraphrasing. our method grasps several usages of a headword and those of the def-heads as a form of their case frames and aligns those case frames, which means the acquisition of word sense disambiguation rules and the detection of the appropriate equivalent and case marker transformation.
estimators for stochastic "unification-based" grammars. log-linear models provide a statistically sound framework for stochastic "unification-based" grammars (subgs) and stochastic versions of other kinds of grammars. we describe two computationally-tractable ways of estimating the parameters of such grammars from a training corpus of syntactic analyses, and apply these to estimate a stochastic version of lexical-functional grammar.
diagnostic processing of japanese for computer-assisted second language learning. as an application of nlp to computer-assisted language learning(call), we propose a diagnostic processing of japanese being able to detect errors and inappropriateness of sentences composed by the students in the given situation and the context of the exercise texts. using ltag(lexicalized tree adjoining grammar) formalism, we have implemented a prototype of such a diagnostic parser as a component of a call system being developed.
a unification-based parser for relational grammar. we present an implemented unification-based parser for relational grammars developed within the stratified feature grammar (sfg) framework, which generalizes kasper-rounds logic to handle relational grammar analyses. we first introduce the key aspects of sfg and a lexicalized, graph-based variant of the framework suitable for implementing relational grammars. we then describe a head-driven chart parser for lexicalized sfg. the basic parsing operation is essentially ordinary feature-structure unification augmented with an operation of label unification to build the stratified features characteristic of sfg.
a method for correcting errors in speech recognition using the statistical features of character co-occurence. it is important to correct the errors in the results of speech recognition to increase the performance of a speech translation system. this paper proposes a method for correcting errors using the statistical features of character co-occurrence, and evaluates the method.the proposed method comprises two successive correcting processes. the first process uses pairs of strings: the first string is an erroneous substring of the utterance predicted by speech recognition, the second string is the corresponding section of the actual utterance. errors are detected and corrected according to the database learned from erroneous-correct utterance pairs. the remaining errors are passed to the posterior process which uses a string in the corpus that is similar to the string including recognition errors.the results of our evaluation show that the use of our proposed method as a post-processor for speech recognition is likely to make a significant contribution to the performance of speech translation systems.
unification-based multimodal parsing. in order to realize their full potential, multimodal systems need to support not just input from multiple modes, but also synchronized integration of modes. johnston et al (1997) model this integration using a unification operation over typed feature structures. this is an effective solution for a broad class of systems, but limits multimodal utterances to combinations of a single spoken phrase with a single gesture. we show how the unification-based approach can be scaled up to provide a full multimodal grammar formalism. in conjunction with a multidimensional chart parser, this approach supports integration of multiple elements distributed across the spatial, temporal, and acoustic dimensions of multimodal interaction. integration strategies are stated in a high level unification-based rule formalism supporting rapid prototyping and iterative development of multimodal systems.
learning attribute selections for non-pronominal expressions. a fundamental function of any task-oriented dialogue system is the ability to generate nominal expressions that describe objects in the task domain. in this paper, we report results from using machine learning to train and test a nominal-expression generator on a set of 393 nominal descriptions from the coconut corpus of task-oriented design dialogues. results show that we can achieve a 50% match to human performance as opposed to a 16% baseline for just guessing the most frequent type of nominal expression in the coconut corpus. to our surprise our results indicate that many of the central features of previously proposed selection models did not improve the performance of the learned nominal-expression generator.
match: an architecture for multimodal dialogue systems. mobile interfaces need to allow the user and system to adapt their choice of communication modes according to user preferences, the task at hand, and the physical and social environment. we describe a multimodal application architecture which combines finite-state multimodal language processing, a speech-act based multimodal dialogue manager, dynamic multimodal output generation, and user-tailored text planning to enable rapid prototyping of multimodal interfaces with flexible input and adaptive output. our testbed application match (multimodal access to city help) provides a mobile multimodal speech-pen interface to restaurant and sub-way information for new york city.
chart generation. charts constitute a natural uniform architecture for parsing and generation provided string position is replaced by a notion more appropriate to logical forms and that measures are taken to curtail generation paths containing semantically incomplete phrases.
unification-based multimodal integration. recent empirical research has shown conclusive advantages of multimodal interaction over speech-only interaction for map-based tasks. this paper describes a multimodal language processing architecture which supports interfaces allowing simultaneous input from speech and gesture recognition. integration of spoken and gestural input is driven by unification of typed feature structures representing the semantic contributions of the different modes. this integration method allows the component modalities to mutually compensate for each others' errors. it is implemented in quick-set, a multimodal (pen/voice) system that enables users to set up and control distributed interactive simulations.
minority vote: at-least-n voting improves recall for extracting relations. several nlp tasks are characterized by asymmetric data where one class label none, signifying the absence of any structure (named entity, coreference, relation, etc.) dominates all other classes. classifiers built on such data typically have a higher precision and a lower recall and tend to overproduce the none class. we present a novel scheme for voting among a committee of classifiers that can significantly boost the recall in such situations. we demonstrate results showing up to a 16% relative improvement in ace value for the 2004 ace relation extraction task for english, arabic and chinese.
user expertise modeling and adaptivity in a speech-based e-mail system. this paper describes the user expertise model in athosmail, a mobile, speech-based e-mail system. the model encodes the system's assumptions about the user expertise, and gives recommendations on how the system should respond depending on the assumed competence levels of the user. the recommendations are realized as three types of explicitness in the system responses. the system monitors the user's competence with the help of parameters that describe e.g. the success of the user's interaction with the system. the model consists of an online and an offline version, the former taking care of the expertise level changes during the same session, the latter modelling the overall user expertise as a function of time and repeated interactions.
metonymy: reassessment, survey of acceptability, and its treatment in a machine translation system. in this article we outline a basic approach to treating metonymy properly in a multilingual machine translation system. this is the first attempt at treating metonymy in an machine translation environment. the approach is guided by the differences of acceptability of metonymy which were obtained by our comparative survey among three languages, english, chinese, and japanese. the characteristics of the approach are as follows:(1)influences of the context, individuals, and familiality with metonymy are not used.(2) an actual acceptability of each metonymic expression is not realized directly.(3) grouping metonymic examples into patterns is determined by the acceptability judgement of the speakers surveyed as well as the analysts' intuition.(4) the analysis and generation components treat metonymy differently using the patterns.(5) the analysis component accepts a wider range of metonymy than the actual results of the survey, and the generation component treats metonymy more strictly than the actual results.we think that the approach is a starting point for more sophisticated approaches to translation in a multilingual machine translation environment.
atomization in grammar sharing. we describe a prototype shared grammar for the syntax of simple nominal expressions in arabic, english, french, german, and japanese implemented at mcc. in this grammar, a complex inheritance lattice of shared grammatical templates provides parts that each language can put together to form language-specific grammatical templates. we conclude that grammar sharing is not only possible but also desirable. it forces us to reveal crosslinguistically invariant grammatical primitives that may otherwise remain conflated with other primitives if we deal only with a single language or language type. we call this the process of grammatical atomization. the specific implementation reported here uses categorial unification grammar. the topics include the mono-level nominal category n, the functional distinction between argument and non-argument of nominals, grammatical agreement, and word order types.
resolving translation mismatches with information flow. languages differ in the concepts and real-world entities for which they have words and grammatical constructs. therefore translation must sometimes be a matter of approximating the meaning of a source language text rather than finding an exact counterpart in the target language. we propose a translation framework based on situation theory. the basic ingredients are an information lattice, a representation scheme for utterances embedded in contexts, and a mismatch resolution scheme defined in terms of information flow. we motivate our approach with examples of translation between english and japanese.
towards testing the syntax of punctuation. little work has been done in nlp on the subject of punctuation, owing mainly to a lack of a good theory on which computational treatments could be based. this paper described early work in progress to try to construct such a theory. two approaches to finding the syntactic function of punctuation marks are discussed, and procedures are described by which the results from these approaches can be tested and evaluated both against each other as well as against other work. suggestions are made for the use of these results, and for future work.
temporal centering. we present a semantic and pragmatic account of the anaphoric properties of past and perfect that improves on previous work by integrating discourse structure, aspectual type, surface structure and commonsense knowledge. a novel aspect of our account is that we distinguish between two kinds of temporal intervals in the interpretation of temporal operators --- discourse reference intervals and event intervals. this distinction makes it possible to develop an analogy between centering and temporal centering, which operates on discourse reference intervals. our temporal property-sharing principle is a defeasible inference rule on the logical form. along with lexical and causal reasoning, it plays a role in incrementally resolving underspecified aspects of the event structure representation of an utterance against the current context.
movement in active production networks. we describe how movement is handled in a class of computational devices called active production networks (apns). the apn model is a parallel, activation-based framework that has been applied to other aspects of natural language processing. the model is briefly defined, the notation and mechanism for movement is explained, and then several examples are given which illustrate how various conditions on movement can naturally be explained in terms of limitations of the apn device.
fsa: an efficient and flexible c++ toolkit for finite state automata using on-demand computation. in this paper we present the rwth fsa toolkit --- an efficient implementation of algorithms for creating and manipulating weighted finite-state automata. the toolkit has been designed using the principle of on-demand computation and offers a large range of widely used algorithms. to prove the superior efficiency of the toolkit, we compare the implementation to that of other publically available toolkits. we also show that on-demand computations help to reduce memory requirements significantly without any loss in speed. to increase its flexibility, the rwth fsa toolkit supports high-level interfaces to the programming language python as well as a command-line tool for interactive manipulation of fsas. furthermore, we show how to utilize the toolkit to rapidly build a fast and accurate statistical machine translation system. future extensibility of the toolkit is ensured as it will be publically available as open source software.
robust interaction through partial interpretation and dialogue management. in this paper we present results on developing robust natural language interfaces by combining shallow and partial interpretation with dialogue management. the key issue is to reduce the effort needed to adapt the knowledge sources for parsing and interpretation to a necessary minimum. in the paper we identify different types of information and present corresponding computational models. the approach utilizes an automatically generated lexicon which is updated with information from a corpus of simulated dialogues. the grammar is developed manually from the same knowledge sources. we also present results from evaluations that support the approach.
can nominal expressions achieve multiple goals? an empirical study. while previous work suggests that multiple goals can be addressed by a nominal expression, there is no systematic work describing what goals in addition to identification might be relevant and how speakers can use nominal expressions to achieve them. in this paper, we first hypothesize a number of communicative goals that could be addressed by nominal expressions in task-oriented dialogues. we then describe the intentional influences model for nominal expression generation that attempts to simultaneously address the identification goal and these additional goals with a single nominal expression. our evaluation results show that the intentional influences model fits the nominal expressions in the coconut corpus as well as previous accounts that focus solely on the identification goal.
defining the semantics of verbal modifiers in the domain of cooking tasks. seafact (semantic analysis for the animation of cooking tasks) is a natural language interface to a computer-generated animation system operating in the domain of cooking tasks. seafact allows the user to specify cooking tasks using a small subset of english. the system analyzes english input and produces a representation of the task which can drive motion synthesis procedures. this paper describes the semantic analysis of verbal modifiers on which the seafact implementation is based.
using terminological knowledge representation languages to manage linguistic resources. i examine how terminological languages can be used to manage linguistic data during nl research and development. in particular, i consider the lexical semantics task of characterizing semantic verb classes and show how the language can be extended to flag inconsistencies in verb class definitions, identify the need for new verb classes, and identify appropriate linguistic hypotheses for a new verb's behavior.
use of mutual information based character clusters in dictionary-less morphological analysis of japanese. for languages whose character set is very large and whose orthography does not require spacing between words, such as japanese, tokenizing and part-of-speech tagging are often the difficult parts of any morphological analysis. for practical systems to tackle this problem, uncontrolled heuristics are primarily used. the use of information on character sorts, however, mitigates this difficulty. this paper presents our method of incorporating character clustering based on mutual information into decision-tree dictionary-less morphological analysis. by using natural classes, we have confirmed that our morphological analyzer has been significantly improved in both tokenizing and tagging japanese text.
the replace operator. this paper introduces to the calculus of regular expressions a replace operator and defines a set of replacement expressions that concisely encode alternate variations of the operation. replace expressions denote regular relations, defined in terms of other regular expression operators. the basic case is unconditional obligatory replacement. we develop several versions of conditional replacement that allow the operation to be constrained by context.
directed replacement. this paper introduces to the finite-state calculus a family of directed replace operators. in contrast to the simple replace expression, upper &larr; lower, defined in karttunen (1995), the new directed version, upper @&larr; lower, yields an unambiguous transducer if the lower language consists of a single string. it transduces the input string from left to right, making only the longest possible replacement at each point.a new type of replacement expression, upper @&larr; prefix ... suffix, yields a transducer that inserts text around strings that are instances of upper. the symbol ... denotes the matching part of the input which itself remains unchanged. prefix and suffix are regular expressions describing the insertions.expressions of the type upper @&larr; prefix ... suffix may be used to compose a deterministic parser for a "local grammar" in the sense of gross (1989). other useful applications of directed replacement include tokenization and filtering of text streams.
fast methods for kernel-based text analysis. kernel-based learning (e.g., support vector machines) has been successfully applied to many hard problems in natural language processing (nlp). in nlp, although feature combinations are crucial to improving performance, they are heuristically selected. kernel methods change this situation. the merit of the kernel methods is that effective feature combination is implicitly expanded without loss of generality and increasing the computational costs. kernel-based text analysis shows an excellent performance in terms in accuracy; however, these methods are usually too slow to apply to large-scale text analysis. in this paper, we extend a basket mining algorithm to convert a kernel-based classifier into a simple and fast linear classifier. experimental results on english basenp chunking, japanese word segmentation and japanese dependency parsing show that our new classifiers are about 30 to 300 times faster than the standard kernel-based classifiers.
conditional descriptions in functional unification grammar. a grammatical description often applies to a linguistic object only when that object has certain features. such conditional descriptions can be indirectly modeled in kay's functional unification grammar (fug) using functional descriptions that are embedded within disjunctive alternatives. an extension to fug is proposed that allows for a direct representation of conditional descriptions. this extension has been used to model the input conditions on the systems of systemic grammar. conditional descriptions are formally defined in terms of logical implication and negation. this formal definition enables the use of conditional descriptions as a general notational extension to any of the unification-based grammar representation systems currently used in computational linguistics.
homonymy and polysemy in information retrieval. this paper discusses research on distinguishing word meanings in the context of information retrieval systems. we conducted experiments with three sources of evidence for making these distinctions: morphology, part-of-speech, and phrases. we have focused on the distinction between homonymy and polysemy (unrelated vs. related meanings). our results support the need to distinguish homonymy and polysemy. we found: 1) grouping morphological variants makes a significant improvement in retrieval performance, 2) that more than half of all words in a dictionary that differ in part-of-speech are related in meaning, and 3) that it is crucial to assign credit to the component words of a phrase. these experiments provide better understanding of word-based methods, and suggest where natural language processing can provide further improvements in retrieval performance.
know when to hold 'em: shuffling deterministically in a parser for nonconcatenative grammars. nonconcatenative constraints, such as the shuffle relation, are frequently employed in grammatical analyses of languages that have more flexible ordering of constituents than english. we show how it is possible to avoid searching the large space of permutations that results from a nondeterministic application of shuffle constraints. the results of our implementation demonstrate that deterministic application of shuffle constraints yields a dramatic improvement in the overall performance of a head-corner parser for german using an hpsg-style grammar.
incorporating compositional evidence in memory-based partial parsing. in this paper, a memory-based parsing method is extended for handling compositional structures. the method is oriented for learning to parse any selected subset of target syntactic structures. it is local, yet can handle also compositional structures. parts of speech as well as embedded instances are being used simultaneously. the output is a partial parse in which instances of the target structures are marked.
charting the depths of robust speech parsing. we describe a novel method for coping with ungrammatical input based on the use of chart-like data structures, which permit anytime processing. priority is given to deep syntactic analysis. should this fail, the best partial analyses are selected, according to a shortest-paths algorithm, and assembled in a robust processing phase. the method has been applied in a speech translation project with large hpsg grammars.
from chunks to function-argument structure: a similarity-based approach. chunk parsing has focused on the recognition of partial constituent structures at the level of individual chunks. little attention has been paid to the question of how such partial analyses can be combined into larger structures for complete utterances. such larger structures are not only desirable for a deeper syntactic analysis. they also constitute a necessary prerequisite for assigning function-argument structure.the present paper offers a similarity-based algorithm for assigning functional labels such as subject, object, head, complement, etc. to complete syntactic structures on the basis of prechunked input.the evaluation of the algorithm has concentrated on measuring the quality of functional labels. it was performed on a german and an english treebank using two different annotation schemes at the level of function-argument structure. the results of 89.73 % correct functional labels for german and 90.40 % for english validate the general approach.
compilation of hpsg to tag. we present an implemented compilation algorithm that translates hpsg into lexicalized feature-based tag, relating concepts of the two theories. while hpsg has a more elaborated principle-based theory of possible phrase structures, tag provides the means to represent lexicalized structures more explicitly. our objectives are met by giving clear definitions that determine the projection of structures from the lexicon, and identify "maximal" projections, auxiliary trees and foot nodes.
boosting-based parse reranking with subtree features. this paper introduces a new application of boosting for parse reranking. several parsers have been proposed that utilize the all-subtrees representation (e.g., tree kernel and data oriented parsing). this paper argues that such an all-subtrees representation is extremely redundant and a comparable accuracy can be achieved using just a small set of subtrees. we show how the boosting algorithm can be applied to the all-subtrees representation and how it selects a small and relevant feature set efficiently. two experiments on parse reranking show that our method achieves comparable or even better performance than kernel methods and also improves the testing efficiency.
using string-kernels for learning semantic parsers. we present a new approach for mapping natural language sentences to their formal meaning representations using string-kernel-based classifiers. our system learns these classifiers for every production in the formal language grammar. meaning representations for novel natural language sentences are obtained by finding the most probable semantic parse using these string classifiers. our experiments on two real-world data sets show that this approach compares favorably to other existing systems and is particularly robust to noise.
mildly non-projective dependency structures. syntactic parsing requires a fine balance between expressivity and complexity, so that naturally occurring structures can be accurately parsed without compromising efficiency. in dependency-based parsing, several constraints have been proposed that restrict the class of permissible structures, such as projectivity, planarity, multi-planarity, well-nestedness, gap degree, and edge degree. while projectivity is generally taken to be too restrictive for natural language syntax, it is not clear which of the other proposals strikes the best balance between expressivity and complexity. in this paper, we review and compare the different constraints theoretically, and provide an experimental evaluation using data from two treebanks, investigating how large a proportion of the structures found in the treebanks are permitted under different constraints. the results indicate that a combination of the well-nestedness constraint and a parametric constraint on discontinuity gives a very good fit with the linguistic data.
extraposition via complex domain formation. we propose a novel approach to extraposition in german within an alternative conception of syntax in which syntactic structure and linear order are mediated not via encodings of hierarchical relations but instead via order domains. at the heart of our proposal is a new kind of domain formation which affords analyses of extraposition constructions that are linguistically more adequate than those previously suggested in the literature.
processing optimality-theoretic syntax by interleaved chart parsing and generation. the earley deduction algorithm is extended for the processing of ot syntax based on feature grammars. due to faithfulness violations, infinitely many candidates must be compared. with the (reasonable) assumptions (i) that ot constraints are descriptions denoting bounded structures and (ii) that every rule recursion in the base grammar incurs some constraint violation, a chart algorithm can be devised. interleaving parsing and generation permits the application of generation-based optimization even in the parsing task, i.e., for a string input.
cohesion and collocation: using context vectors in text segmentation. collocational word similarity is considered a source of text cohesion that is hard to measure and quantify. the work presented here explores the use of information from a training corpus in measuring word similarity and evaluates the method in the text segmentation task. an implementation, the <b>vectile</b> system, produces similarity curves over texts using pre-compiled vector representations of the contextual behavior of words. the performance of this system is shown to improve over that of the purely string-based <b>texttiling algorithm</b> (hearst, 1997).
ot syntax - decidability of generation-based optimization. in optimality-theoretic syntax, optimization with unrestricted expressive power on the side of the ot constraints is undecidable. this paper provides a proof for the decidability of optimization based on constraints expressed with reference to local subtrees (which is in the spirit of ot theory). the proof builds on kaplan and wedekind's (2000) construction showing that lfg generation produces context-free languages.
transitivity and foregrounding in news articles: experiments in information retrieval and automatic summarising. this paper describes an on-going study which applies the concept of transitivity to news discourse for text processing tasks. the complex notion of transitivity is defined and the relatioship between transitivity and information foregrounding is explained. a sample corpus of news articles has been coded for transitivity. the corpus is being used in two text processing experiments.
compounding and derivational morphology in a finite-state setting. this paper proposes the application of finite-state approximation techniques on a unification-based grammar of word formation for a language like german. a refinement of an rtn-based approximation algorithm is proposed, which extends the state space of the automaton by selectively adding distinctions based on the parsing history at the point of entering a context-free rule. the selection of history items exploits the specific linguistic nature of word formation. as experiments show, this algorithm avoids an explosion of the size of the automaton in the approximation construction.
experiments in parallel-text based grammar induction. this paper discusses the use of statistical word alignment over multiple parallel texts for the identification of string spans that cannot be constituents in one of the languages. this information is exploited in monolingual pcfg grammar induction for that language, within an augmented version of the inside-outside algorithm. besides the aligned corpus, no other resources are required. we discuss an implemented system and present experimental results with an evaluation against the penn tree-bank.
the effect of establishing coherence in ellipsis and anaphora resolution. this paper presents a new model of anaphoric processing that utilizes the establishment of coherence relations between clauses in a discourse. we survey data that comprises a currently stalemated argument over whether vp-ellipsis is an inherently syntactic or inherently semantic phenomenon, and show that the data can be handled within a uniform discourse processing architecture. this architecture, which revises the dichotomy between ellipsis vs. model interpretive anaphora given by sag and hankamer (1984), is also able to accommodate divergent theories and data for pronominal reference resolution. the resulting architecture serves as a baseline system for modeling the role of cohesive devices in natural language.
common topics and coherent situations: interpreting ellipsis in the context of discourse inference. it is claimed that a variety of facts concerning ellipsis, event reference, and interclausal coherence can be explained by two features of the linguistic form in question: (1) whether the form leaves behind an empty constituent in the syntax, and (2) whether the form is anaphoric in the semantics. it is proposed that these features interact with one of two types of discourse inference, namely common topic inference and coherent situation inference. the differing ways in which these types of inference utilize syntactic and semantic representations predicts phenomena for which it is otherwise difficult to account.
using higher-order logic programming for semantic interpretation of coordinate constructs. many theories of semantic interpretation use &lambda;-term manipulation to compositionally compute the meaning of a sentence. these theories are usually implemented in a language such as prolog that can simulate &lambda;-term operations with first-order unification. however, for some interesting cases, such as a combinatory categorial grammar account of coordination constructs, this can only be done by obscuring the underlying linguistic theory with the "tricks" needed for implementation. this paper shows how the use of abstract syntax permitted by higher-order logic programming allows an elegant implementation of the semantics of combinatory categorial grammar, including its handling of coordination constructs.
temporal relations reference or discourse coherence? the temporal relations that hold between events described by successive utterances are often left implicit or underspecified. we address the role of two phenomena with respect to the recovery of these relations: (1) the referential properties of tense, and (2) the role of temporal constraints imposed by coherence relations. we account for several facets of the identification of temporal relations through an integration of these.
unsupervised discrimination and labeling of ambiguous names. this paper describes adaptations of unsupervised word sense discrimination techniques to the problem of name discrimination. these methods cluster the contexts containing an ambiguous name, such that each cluster refers to a unique underlying person or place. we also present new techniques to assign meaningful labels to the discovered clusters.
atn grammar modeling in applied linguistics. augmented transition network grammars have significant areas of unexplored application as a simulation tool for grammar designers. the intent of this paper is to discuss some current efforts in developing a grammar testing tool for the specialist in linguistics. the scope of the system under discussion is to display structures based on the modeled grammar. full language definition with facilitation of semantic interpretation is not within the scope of the systems described in this paper. application of grammar testing to an applied linguistics research enviroment is emphasized. extensions to the teaching of linguistics principles and to refinement of the primitive atn functions are also considered.
senseclusters: unsupervised clustering and labeling of similar contexts. senseclusters is a freely available system that identifies similar contexts in text. it relies on lexical features to build first and second order representations of contexts, which are then clustered using unsupervised methods. it was originally developed to discriminate among contexts centered around a given target word, but can now be applied more generally. it also supports methods that create descriptive and discriminating labels for the discovered clusters.
incremental generation of spatial referring expressions in situated dialog. this paper presents an approach to incrementally generating locative expressions. it addresses the issue of combinatorial explosion inherent in the construction of relational context models by: (a) contextually defining the set of objects in the context that may function as a landmark, and (b) sequencing the order in which spatial relations are considered using a cognitively motivated hierarchy of relations, and visual and discourse salience.
learning transliteration lexicons from the web. this paper presents an adaptive learning framework for phonetic similarity modeling (psm) that supports the automatic construction of transliteration lexicons. the learning algorithm starts with minimum prior knowledge about machine transliteration, and acquires knowledge iteratively from the web. we study the active learning and the unsupervised learning strategies that minimize human supervision in terms of data labeling. the learning process refines the psm and constructs a transliteration lexicon at the same time. we evaluate the proposed psm and its learning algorithm through a series of systematic experiments, which show that the proposed framework is reliably effective on two independent databases.
proximity in context: an empirically grounded computational model of proximity for processing topological spatial expressions. the paper presents a new model for context dependent interpretation of linguistic expressions about spatial proximity between objects in a natural scene. the paper discusses novel psycholinguistic experimental data that tests and verifies the model. the model has been implemented, and enables a conversational robot to identify objects in a scene through topological spatial relations (e.g. "x near y"). the model can help motivate the choice between topological and projective prepositions.
an algorithm for finding noun phrase correspondences in bilingual corpora. the paper describes an algorithm that employs english and french text taggers to associate noun phrases in an aligned bilingual corpus. the taggers provide part-of-speech categories which are used by finite-state recognizers to extract simple noun phrases for both languages. noun phrases are then mapped to each other using an iterative re-estimation algorithm that bears similarities to the baum-welch algorithm which is used for training the taggers. the algorithm provides an alternative to other approaches for finding word correspondences, with the advantage that linguistic structure is incorporated. improvements to the basic algorithm are described, which enable context to be accounted for when constructing the noun phrase mappings.
datr theories and datr models. evans and gazdar (evans and gazdar, 1989a; evans and gazdar, 1989b) introduced datr as a simple, non-monotonic language for representing natural language lexicons. although a number of implementations of datr exist, the full language has until now lacked an explicit, declarative semantics. this paper rectifies the situation by providing a mathematical semantics for datr. we present a view of datr as a language for defining certain kins of partial functions by cases. the formal model provides a transparent treatment of datr's notion of global context. it is shown that datr's default mechanism can be accounted for by interpreting value descriptors as families of values indexed by paths.
semantic analysis of japanese noun phrases - a new approach to dictionary-based understanding. this paper presents a new method of analyzing japanese noun phrases of the form <i>n</i><sub>1</sub> no n<sub>2</sub>. the japanese postposition <i>no</i> roughly corresponds to <i>of</i>, but it has much broader usage. the method exploits a definition of <i>n<sub>2</sub></i> in a dictionary. for example, <i>rugby no coach</i> can be interpreted as <i>a person who teaches technique in rugby</i>. we illustrate the effectiveness of the method by the analysis of 300 test noun phrases.
finite state transducers approximating hidden markov models. this paper describes the conversion of a hidden markov model into a sequential transducer that closely approximates the behavior of the stochastic model. this transformation is especially advantageous for part-of-speech tagging because the resulting transducer can be composed with other transducers that encode correction rules for the most frequent tagging errors. the speed of tagging is also improved. the described methods have been implemented and successfully tested on six languages.
automatic detection of text genre. as the text databases available to users become larger and more heterogeneous, genre becomes increasingly important for computational linguistics as a complement to topical and structural principles of classification. we propose a theory of genres as bundles of facets, which correlate with various surface cues, and argue that genre detection based on surface cues is as successful as detection based on deeper structural properties.
bridging the gap between dictionary and thesaurus. this paper presents an algorithm to integrate different lexical resources, through which we hope to overcome the individual inadequacy of the resources, and thus obtain some enriched lexical semantic information for applications such as word sense disambiguation. we used wordnet as a mediator between a conventional dictionary and a thesaurus. preliminary results support our hypothesised structural relationship, which enables the integration, of the resources. these results also suggest that we can combine the resources to achieve an overall balanced degree of sense discrimination.
integration of speech to computer-assisted translation using finite-state automata. state-of-the-art computer-assisted translation engines are based on a statistical prediction engine, which interactively provides completions to what a human translator types. the integration of human speech into a computer-assisted system is also a challenging area and is the aim of this paper. so far, only a few methods for integrating statistical machine translation (mt) models with automatic speech recognition (asr) models have been studied. they were mainly based on n-best rescoring approach. n-best rescoring is not an appropriate search method for building a real-time prediction engine. in this paper, we study the incorporation of mt models and asr models using finite-state automata. we also propose some transducers based on mt models for rescoring the asr word graphs.
extracting loanwords from mongolian corpora and producing a japanese-mongolian bilingual dictionary. this paper proposes methods for extracting loanwords from cyrillic mongolian corpora and producing a japanese-mongolian bilingual dictionary. we extract loanwords from mongolian corpora using our own handcrafted rules. to complement the rule-based extraction, we also extract words in mongolian corpora that are phonetically similar to japanese katakana words as loanwords. in addition, we correspond the extracted loanwords to japanese words and produce a bilingual dictionary. we propose a stemming method for mongolian to extract loanwords correctly. we verify the effectiveness of our methods experimentally.
gf parallel resource grammars and russian. a resource grammar is a standard library for the gf grammar formalism. it raises the abstraction level of writing domain-specific grammars by taking care of the general grammatical rules of a language. gf resource grammars have been built in parallel for eleven languages and share a common interface, which simplifies multilingual applications. we reflect on our experience with the russian resource grammar trying to answer the questions: how well russian fits into the common interface and where the line between language-independent and language-specific should be drawn.
a tripartite plan-based model of dialogue. this paper presents a tripartite model of dialogue in which three different kinds of actions are modeled: domain actions, problem-solving actions, and discourse or communicative actions. we contend that our process model provides a more finely differentiated representation of user intentions than previous models; enables the incremental recognition of communicative actions that cannot be recognized from a single utterance alone; and accounts for implicit acceptance of a communicated proposition.
extracting causal knowledge from a medical database using graphical patterns. this paper reports the first part of a project that aims to develop a knowledge extraction and knowledge discovery system that extracts causal knowledge from textual databases. in this initial study, we develop a method to identify and extract cause-effect information that is explicitly expressed in medical abstracts in the medline database. a set of graphical patterns were constructed that indicate the presence of a causal relation in sentences, and which part of the sentence represents the cause and which part represents the effect. the patterns are matched with the syntactic parse trees of sentences, and the parts of the parse tree that match with the slots in the patterns are extracted as the cause or the effect.
modeling negotiation subdialogues. this paper presents a plan-based model that handles negotiation subdialogues by inferring both the communicative actions that people pursue when speaking and the beliefs underlying these actions. we contend that recognizing the complex discourse actions pursued in negotiation subdialogues (e.g., expressing doubt) requires both a multistrength belief model and a process model that combines different knowledge sources in a unified framework. we show how our model identifies the structure of negotiation subdialogues, including recognizing expressions of doubt, implicit acceptance of communicated propositions, and negotiation subdialogues embedded within other negotiation subdialogues.
a bag of useful techniques for efficient and robust parsing. this paper describes new and improved techniques which help a unification-based parser to process input efficiently and robustly. in combination these methods result in a speed-up in parsing time of more than an order of magnitude. the methods are correct in the sense that none of them rule out legal rule applications.
the grapho-phonological system of written french: statistical analysis and empirical validation. the processes through which readers evoke mental representations of phonological forms from print constitute a hotly debated and controversial issue in current psycholinguistics. in this paper we present a computational analysis of the grapho-phonological system of written french, and an empirical validation of some of the obtained descriptive statistics. the results provide direct evidence demonstrating that both grapheme frequency and grapheme entropy influence performance on pseudoword naming. we discuss the implications of those findings for current models of phonological coding in visual word recognition.
term-list translation using mono-lingual word co-occurence vectors. a term-list is a list of content words that characterize a consistent text or a concept. this paper presents a new method for translating a term-list by using a corpus in the target language. the method first retrieves alternative translations for each input word from a bilingual dictionary. it then determines the most 'coherent' combination of alternative translations, where the coherence of a set of words is defined as the proximity among multi-dimensional vectors produced from the words on the basis of co-occurrence statistics. the method was applied to term-lists extracted from newspaper articles and achieved 81% translation accuracy for ambiguous words (i.e., words with multiple translations).
document classification using a finite mixture model. we propose a new method of classifying documents into categories. we define for each category a finite mixture model based on soft clustering of words. we treat the problem of classifying documents as that of conducting statistical hypothesis testing over finite mixture models, and employ the em algorithm to efficiently estimate parameters in a finite mixture model. experimental results indicate that our method outperforms existing methods.
graded unification: a framework for interactive processing. an extension to classical unification, called graded unification is presented. it is capable of combining contradictory information. an interactive processing paradigm and parser based on this new operator are also presented.
generation that exploits corpus-based statistical knowledge. we describe novel aspects of a new natural language generator called nitrogen. this generator has a highly flexible input representation that allows a spectrum of input from syntactic to semantic depth, and shifts the burden of many linguistic decisions to the statistical post-processor. the generation algorithm is compositional, making it efficient, yet it also handles non-compositional aspects of language. nitrogen's design makes it robust and scalable, operating with lexicons and knowledge bases of one hundred thousand entities.
interpreting semantic relations in noun compounds via verb semantics. we propose a novel method for automatically interpreting compound nouns based on a predefined set of semantic relations. first we map verb tokens in sentential contexts to a fixed set of seed verbs using wordnet::similarity and moby's thesaurus. we then match the sentences with semantic relations based on the semantics of the seed verbs and grammatical roles of the head noun and modifier. based on the semantics of the matched sentences, we then build a classifier using timbl. the performance of our final system at interpreting ncs is 52.6%.
methods and practical issues in evaluating alignment techniques. this paper describes the work achieved in the first half of a 4-year cooperative research project (arcade), financed by aupelf-uref. the project is devoted to the evaluation of parallel text alignment techniques. in its first period arcade ran a competition between six systems on a sentence-to-sentence alignment task which yielded two main types of results. first, a large reference bilingual corpus comprising of texts of different genres was created, each presenting various degrees of difficulty with respect to the alignment task.second, significant methodological progress was made both on the evaluation protocols and metrics, and the algorithms used by the different systems. for the second phase, which is now underway, arcade has been opened to a larger number of teams who will tackle the problem of word-level alignment.
dimension-reduced estimation of word co-occurrence probability. we investigate a novel approach to solve the problem of sparse data through dimension reduction. linear algebraic technique called lsa/svd is used to find co-relationships of sparse words. three variant estimation methods are suggested and they are evaluated for estimating unseen noun-verb co-occurrence probability. the model shows possibility to be alternative probability smoothing method.
probabilistic text structuring: experiments with sentence ordering. ordering information is a critical task for natural language generation applications. in this paper we propose an approach to information ordering that is particularly suited for text-to-text generation. we describe a model that learns constraints on sentence order from a corpus of domain-specific texts and an algorithm that yields the most likely order among several alternatives. we evaluate the automatically generated orderings against authored texts from our corpus and against human subjects that are asked to mimic the model's task. we also assess the appropriateness of such a model for multidocument summarization.
phrase-pattern-based korean to english machine translation using two level translation pattern selection. pattern-based machine translation is one of the machine translation methods which performs syntactic analysis and structure transfer at the same time using bilingual patterns. pbmt is used to expand the length of patterns up to sentence-length in order to reduce ambiguities in translation, but it brought out the problem of rapidly increased patterns. we propose a model which shortens the length of patterns to phrase-length and reduces ambiguities in translation by using two level translation pattern selection method. in the first level, the proper translation patterns are selected by using a hybrid method of exact example matching and semantic constraint by thesaurus. in the second level, the most natural translation pattern for the verb phrase is selected among the selected translation pattern categories by using statistic information of the target language. by using this proposed model, we could shorten the length of patterns without raising the ambiguities in translation.
acquiring lexical generalizations from corpora: a case study for diathesis alternations. this paper examines the extent to which verb diathesis alternations are empirically attested in corpus data. we automatically acquire alternating verbs from large balanced corpora by using partialparsing methods and taxonomic information, and discuss how corpus data can be used to quantify linguistic generalizations. we estimate the productivity of an alternation and the typicality of its members using type and token frequencies.
automatic identification of pro and con reasons in online reviews. in this paper, we present a system that automatically extracts the pros and cons from online reviews. although many approaches have been developed for extracting opinions from text, our focus here is on extracting the reasons of the opinions, which may themselves be in the form of either fact or opinion. leveraging online review sites with author-generated pros and cons, we propose a system for aligning the pros and cons to their sentences in review texts. a maximum entropy model is then trained on the resulting labeled set to subsequently extract pros and cons from online review sites that do not explicitly provide them. our experimental results show that our resulting system identifies pros and cons with 66% precision and 76% recall.
evaluating smoothing algorithms against plausibility judgements. previous research has shown that the plausibility of an adjective-noun combination is correlated with its corpus co-occurrence frequency. in this paper, we estimate the co-occurrence frequencies of adjective-noun pairs that fail to occur in a 100 million word corpus using smoothing techniques and compare them to human plausibility ratings. both class-based smoothing and distance-weighted averaging yield frequency estimates that are significant predictors of rated plausibility, which provides independent evidence for the validity of these smoothing techniques.
unlimited vocabulary grapheme to phoneme conversion for korean tts. this paper describes a grapheme-to-phoneme conversion method using phoneme connectivity and ccv conversion rules. the method consists of mainly four modules including morpheme normalization, phrase-break detection, morpheme to phoneme conversion and phoneme connectivity check.the morpheme normalization is to replace non-korean symbols into standard korean graphemes. the phrase-break detector assigns phrase breaks using part-of-speech (pos) information. in the morpheme-to-phoneme conversion module, each morpheme in the phrase is converted into phonetic patterns by looking up the morpheme phonetic pattern dictionary which contains candidate phonological changes in boundaries of the morphemes. graphemes within a morpheme are grouped into ccv patterns and converted into phonemes by the ccv conversion rules. the phoneme connectivity table supports grammaticality checking of the adjacent two phonetic morphemes.in the experiments with a corpus of 4,973 sentences, we achieved 99.9% of the grapheme-to-phoneme conversion performance. the full korean tts system is now being implemented using this conversion method.
a syntactic filter on pronomial anaphora for slot grammar. we propose a syntactic filter for identifying non-coreferential pronoun-np pairs within a sentence. the filter applies to the output of a slot grammar parser and is formulated in terms of the head-argument structures which the parser generates. it handles control and unbounded dependency constructions without empty categories or binding chains, by virtue of the unificational nature of the parser. the filter provides constraints for a discourse semantics system, reducing the search domain to which the inference rules of the system's anaphora resolution component apply.
self-organizing markov models and their application to part-of-speech tagging. this paper presents a method to develop a class of variable memory markov models that have higher memory capacity than traditional (uniform memory) markov models. the structure of the variable memory models is induced from a manually annotated corpus through a decision tree learning algorithm. a series of comparative experiments show the resulting models outperform uniform memory markov models in a part-of-speech tagging task.
discourse relations and defeasible knowledge. this paper presents a formal account of the temporal interpretation of text. the distinct natural interpretations of texts with similar syntax are explained in terms of defeasible rules characterising causal laws and gricean-style pragmatic maxims. intuitively compelling patterns of defeasible entailment that are supported by the logic in which the theory is expressed are shown to underly temporal interpretation.
conceptional association for compound noun analysis. this paper describes research toward the automatic interpretation of compound nouns using corpus statistics. an initial study aimed at syntactic disambiguation is presented. the approach presented bases associations upon thesaurus categories. association data is gathered from unambiguous cases extracted from a corpus and is then applied to the analysis of ambiguous compound nouns. while the work presented is still in progress, a first attempt to syntactically analyse a test set of 244 examples shows 75% correctness. future work is aimed at improving this accuracy and extending the technique to assign semantic role information, thus producing a complete interpretation.
a language-independent shallow-parser compiler. we present a rule--based shallow--parser compiler, which allows to generate a robust shallow-parser for any language, even in the absence of training data, by resorting to a very limited number of rules which aim at identifying constituent boundaries. we contrast our approach to other approaches used for shallow--parsing (i.e. finite-state and probabilistic methods). we present an evaluation of our tool for english (penn treebank) and for french (newspaper corpus "lemonde") for several tasks (np-chunking & "deeper" parsing).
interferring discourse relations in context. we investigate various contextual effects on text interpretation, and account for them by providing contextual constraints in a logical theory of text interpretation. on the basis of the way these constraints interact with the other knowledge sources, we draw some general conclusions about the role of domain-specific information, top-down and bottom-up discourse information flow, and the usefulness of formalisation in discourse theory.
parsing preferences with lexicalized trey adjoining grammars exploiting the derivation tree. since kimball (73) parsing preference principles such as "right association" (ra) and "minimal attachment" (ma) are often formulated with respect to constituent trees. we present 3 preference principles based on "derivation trees" within the framework of ltags. we argue they remedy some shortcomings of the former approaches and account for widely accepted heuristics (e.g. argument/modifier, idioms...).
connection relations and quantifier scope. a formalism will be presented in this paper which makes it possible to realise the idea of assigning only one scope-ambiguous representation to a sentence that is ambiguous with regard to quantifier scope. the scope determination results in extending this representation with additional context and world knowledge conditions. if there is no scope determining information, the formalism can work further with this scope-ambiguous representation. thus scope information does not have to be completely determined.
semhe: a generalised two-level system. this paper presents a generalised two-level implementation which can handle linear and non-linear morphological operations. an algorithm for the interpretation of multi-tape two-level rules is described. in addition, a number of issues which arise when developing non-linear grammars are discussed with examples from syriac.
corpus statistics meet the noun compound: some empirical results. a variety of statistical methods for noun compound analysis are implemented and compared. the results support two main conclusions. first, the use of conceptual association not only enables a broad coverage, but also improves the accuracy. second, an analysis model based on dependency grammar is substantially more accurate than one based on deepest constituents, even though the latter is more prevalent in the literature.
compiling regular formalisms with rule features into finite-state automata. this paper presents an algorithm for the compilation of regular formalisms with rule features into finite-state automata. rule features are incorporated into the right context of rules. this general notion can also be applied to other algorithms which compile regular rewrite rules into automata.
an integrated heuristic scheme for partial parse evaluation. glr is a recently developed robust version of the generalized lr parser [tomita, 1986], that can parse almost any input sentence by ignoring unrecognizable parts of the sentence. on a given input sentence, the parser returns a collection of parses that correspond to maximal, or close to maximal, parsable subjsets of the original input. this paper describes recent work on developing an integrated heuristic scheme for selecting the parse that is deemed "best" from such a collection. we describe the heuristic measures used and their combination scheme. preliminary results from experiments conducted on parsing speech recognized spontaneous speech are also reported.
toward a plan-based understanding model for mixed-initiative dialogues. this paper presents an enhanced model of plan-based dialogue understanding. most plan-based dialogue understanding models derived from [litman and allen, 1987] assume that the dialogue speakers have access to the same domain plan library, and that the active domain plans are shared by the two speakers. we call these features shared domain plan constraints. these assumptions, however, ae too strict to account for mixed-initiative dialogues where each speaker has a different set of domain plans that are housed in his or her own plan library, and where an individual speaker's domain plans may be activated at any point in the dialogue. we propose an extension to the litman and allen model by relaxing the shared domain plan constraints. our extension improves (1) the ability to track the currently active plan, (2) the ability to explain the planning behind speaker utterances, and (3) the ability to track which speaker controls the conversational initiative in the dialogue.
a framework for customizable generation of hypertext presentations. in this paper, we present a framework, presentor, for the development and customization of hypertext presentation generators. presentor offers intuitive and powerful declarative languages specifying the presentation at different levels: macro-planning, micro-planning, realization, and formatting. pressentor is implemented and is portable cross-platform and cross-domain. it has been used with success in several application domains including weather forecasting, object modeling, system description and requirements summarization.
role of verbs in document analysis. we present results of two methods for assessing the event profile of news articles as a function of verb type. the unique contribution of this research is the focus on the role of verbs, rather than nouns. two algorithms are presented and evaluated, one of which is shown to accurately discriminate documents by type and semantic properties, i.e. the event profile. the initial method, using wordnet (miller et al. 1990), produced multiple cross-classification of articles, primarily due to the bushy nature of the verb tree coupled with the sense disambiguation problem. our second approach using english verb classes and alternations (evca) levin (1993) showed that monosemous categorization of the frequent verbs in wsj made it possible to usefully discriminate documents. for example, our results show that articles in which communication verbs predominate tend to be opinion pieces, whereas articles with a high percentage of agreement verbs tend to be about mergers or legal cases. an evaluation is performed on the results using kendall's &tau;. we present convincing evidence for using verb semantic classes as a discriminant in document classification.
using readers to identify lexical cohesive structures in texts. this paper describes a reader-based experiment on lexical cohesion, detailing the task given to readers and the analysis of the experimental data. we conclude with discussion of the usefulness of the data in future research on lexical cohesion.
extending lambek grammars: a logical account of minimalist grammars. we provide a logical definition of minimalist grammars, that are stabler's formalization of chomsky's minimalist program. our logical definition leads to a neat relation to categorial grammar, (yielding a treatment of montague semantics), a parsing-as-deduction in a resource sensitive logic, and a learning algorithm from structured data (based on a typing-algorithm and type-unification). here we emphasize the connection to montague semantics which can be viewed as a formal computation of the logical form.
a constraint-based approach to english prosodic constituents. the paper develops a constraint-based theory of prosodic phrasing and prominence, based on an hpsg framework, with an implementation in ale. prominence and juncture are represented by n-ary branching metrical trees. the general aim is to define prosodic structures recursively, in parallel with the definition of syntactic structures. we address a number of prima facie problems arising from the discrepancy between syntactic and prosodic structure
fast context-free parsing requires fast boolean matrix multiplication. valiant showed that boolean matrix multiplication (bmm) can be used for cfg parsing. we prove a dual result: cfg parsers running in time o(|g||w|3-e) on a grammar g and a string w can be used to multiply m x m boolean matrices in tmie o(m3-e/3). in the process we also provide a formal definition of parsing motivated by an informal notion due to lang. our result establishes one of the first limitations on general cfg parsing: a fast, practical cfg parser would yield a fast, practical bmm algorithm, which is not believed to exist.
learning stochastic ot grammars: a bayesian approach using data augmentation and gibbs sampling. stochastic optimality theory (boersma, 1997) is a widely-used model in linguistics that did not have a theoretically sound learning method previously. in this paper, a markov chain monte-carlo method is proposed for learning stochastic ot grammars. following a bayesian framework, the goal is finding the posterior distribution of the grammar given the relative frequencies of input-output pairs. the data augmentation algorithm allows one to simulate a joint posterior distribution by iterating two conditional sampling steps. this gibbs sampler constructs a markov chain that converges to the joint distribution, and the target posterior can be derived as its marginal distribution.
parsing with treebank grammars: empirical bounds, theoretical models, and the structure of the penn treebank. this paper presents empirical studies and closely corresponding theoretical models of the performance of a chart parser exhaustively parsing the penn treebank with the treebank's own cfg grammar. we show how performance is dramatically affected by rule representation and tree transformations, but little by top-down vs. bottom-up strategies. we discuss grammatical saturation, including analysis of the strongly connected components of the phrasal nonterminals in the treebank, and model how, as sentence length increases, the effective grammar rule size increases as regions of the grammar are unlocked, yielding super-cubic observed time behavior in some configurations.
measures of distributional similarity. we study distributional similarity measures for the purpose of improving probability estimation for unseen cooccurrences. our contributions are three-fold: an empirical comparison of a broad range of measures; a classification of similarity functions based on the information that they incorporate; and the introduction of a novel function that is superior at evaluating potential proxy distributions.
the role of information retrieval in answering complex questions. this paper explores the role of information retrieval in answering "relationship" questions, a new class complex information needs formally introduced in trec 2005. since information retrieval is often an integral component of many question answering strategies, it is important to understand the impact of different term-based techniques. within a framework of sentence retrieval, we examine three factors that contribute to question answering performance: the use of different retrieval engines, relevance (both at the document and sentence level), and redundancy. results point out the limitations of purely term-based methods to this challenging task. nevertheless, ir-based techniques provide a strong baseline on top of which more sophisticated language processing techniques can be deployed.
a generative constituent-context model for improved grammar induction. we present a generative distributional model for the unsupervised induction of natural language syntax which explicitly models constituent yields and contexts. parameter search with em produces higher quality analyses than previously exhibited by unsupervised systems, giving the best published un-supervised parsing results on the atis corpus. experiments on penn treebank sentences of comparable length show an even higher f1 of 71% on non-trivial brackets. we compare distributionally induced and actual part-of-speech tags as input data, and examine extensions to the basic model. we discuss errors made by the system, compare the system to previous models, and discuss upper bounds, lower bounds, and stability for this task.
accurate unlexicalized parsing. we demonstrate that an unlexicalized pcfg can parse much more accurately than previously shown, by making use of simple, linguistically motivated state splits, which break down false independence assumptions latent in a vanilla treebank grammar. indeed, its performance of 86.36% (lp/lr f1) is better than that of early lexicalized pcfg models, and surprisingly close to the current state-of-the-art. this result has potential uses beyond establishing a strong lower bound on the maximum possible accuracy of unlexicalized models: an unlexicalized pcfg is much more compact, easier to replicate, and easier to interpret than more complex lexical models, and the parsing algorithms are simpler, more widely understood, of lower asymptotic complexity, and easier to optimize.
automatic acquisition of language model based on head-dependent relation between words. language modeling is to associate a sequence of words with a priori probability, which is a key part of many natural language applications such as speech recognition and statistical machine translation. in this paper, we present a language modeling based on a kind of simple dependency grammar. the grammar consists of head-dependent relations between words and can be learned automatically from a raw corpus using the reestimation algorithm which is also introduced in this paper. our experiments show that the proposed model performs better than n-gram models at 11% to 11.5% reductions in test corpus entropy.
corpus-based induction of syntactic structure: models of dependency and constituency. we present a generative model for the unsupervised learning of dependency structures. we also describe the multiplicative combination of this dependency model with a model of linear constituency. the product model outperforms both components on their respective evaluation metrics, giving the best published figures for unsupervised dependency parsing and unsupervised constituency parsing. we also demonstrate that the combined model works and is robust cross-linguistically, being able to exploit either attachment or distributional regularities that are salient in the data.
weakly supervised named entity transliteration and discovery from multilingual comparable corpora. named entity recognition (ner) is an important part of many natural language processing tasks. current approaches often employ machine learning techniques and require supervised data. however, many languages lack such resources. this paper presents an (almost) unsupervised learning algorithm for automatic discovery of named entities (nes) in a resource free language, given a bilingual corpora in which it is weakly temporally aligned with a resource rich language. nes have similar time distributions across such corpora, and often some of the tokens in a multi-word ne are transliterated. we develop an algorithm that exploits both observations iteratively. the algorithm makes use of a new, frequency based, metric for time distributions and a resource free discriminative approach to transliteration. seeded with a small number of transliteration pairs, our algorithm discovers multi-word nes, and takes advantage of a dictionary (if one exists) to account for translated or partially translated nes. we evaluate the algorithm on an english-russian corpus, and show high level of nes discovery in russian.
language model based arabic word segmentation. we approximate arabic's rich morphology by a model that a word consists of a sequence of morphemes in the pattern prefix*-stem-suffix* (* denotes zero or more occurrences of a morpheme). our method is seeded by a small manually segmented arabic corpus and uses it to bootstrap an unsupervised algorithm to build the arabic word segmenter from a large unsegmented arabic corpus. the algorithm uses a trigram language model to determine the most probable morpheme sequence for a given input. the language model is initially estimated from a small manually segmented corpus of about 110,000 words. to improve the segmentation accuracy, we use an unsupervised algorithm for automatically acquiring new stems from a 155 million word unsegmented corpus, and re-estimate the model parameters with the expanded vocabulary and training corpus. the resulting arabic word segmentation system achieves around 97% exact match accuracy on a test corpus containing 28,449 word tokens. we believe this is a state-of-the-art performance and the algorithm can be used for many highly inflected languages provided that one can create a small manually segmented corpus of the language of interest.
machine transliteration. it is challenging to translate names and technical terms across languages with different alphabets and sound inventories. these items are commonly trnasliterated, i.e., replaced with approximate phonetic equivalents. for example, "computer" in english comes out as "konpyuutaa" in japanese. translating such items from japanese back to english is even more challenging, and of practical interest, as transliterated items make up the bulk of text phrases not found in bilingual dictionaries. we describe and evaluate a method for performing backwards transliterations by machine. this method uses a generative model, incorporating several distinct stages in the transliteration process.
a syllable based word recognition model for korean noun extraction. noun extraction is very important for many nlp applications such as information retrieval, automatic text classification, and information extraction. most of the previous korean noun extraction systems use a morphological analyzer or a part-of-speech (pos) tagger. therefore, they require much of the linguistic knowledge such as morpheme dictionaries and rules (e.g. morphosyntactic rules and morphological rules).this paper proposes a new noun extraction method that uses the syllable based word recognition model. it finds the most probable syllable-tag sequence of the input sentence by using automatically acquired statistical information from the pos tagged corpus and extracts nouns by detecting word boundaries. furthermore, it does not require any labor for constructing and maintaining linguistic knowledge. we have performed various experiments with a wide range of variables influencing the performance. the experimental results show that without morphological analysis or pos tagging, the proposed method achieves comparable performance with the previous methods.
two-level, many-path generation. large-scale natural language generation requires the integration of vast amounts of knowledge: lexical, grammatical, and conceptual. a robust generator must be able to operate well even when pieces of knowledge are missing. it must also be robust against incomplete or inaccurate inputs. to attack these problems, we have built a hybrid generator, in which gaps in symbolic knowledge are filled by statistical methods. we describe algorithms and show experimental results. we also discuss how the hybrid generation model can be used to simplify current generators and enhance their portability, even when perfect knowledge is in principle obtainable.
part-of-speech tagging based on hidden markov model assuming joint independence. in this paper we present part-of-speech taggers based on hidden markov models, which adopt a less strict markov assumption to consider rich contexts. in models whose parameters are very specific like lexicalized ones, sparse-data problem is very serious and also conditional probabilities tend to be estimated unreliably. to overcome data-sparseness, a simplified version of the well-known back-off smoothing method is used. to mitigate unreliable estimation problem, our models assume joint independence instead of conditional independence because joint probabilities have the same degree of estimation reliability. in experiments for the brown corpus, models with rich contexts achieve relatively high accuracy and some models assuming joint independence show better results than the corresponding hmms.
unsupervised analysis for decipherment problems. we study a number of natural language decipherment problems using unsupervised learning. these include letter substitution ciphers, character code conversion, phonetic decipherment, and word-based ciphers with relevance to machine translation. straightforward unsupervised learning techniques most often fail on the first try, so we describe techniques for understanding errors and significantly increasing performance.
an expert lexicon approach to identifying english phrasal verbs. phrasal verbs are an important feature of the english language. properly identifying them provides the basis for an english parser to decode the related structures. phrasal verbs have been a challenge to natural language processing (nlp) because they sit at the borderline between lexicon and syntax. traditional nlp frameworks that separate the lexicon module from the parser make it difficult to handle this problem properly. this paper presents a finite state approach that integrates a phrasal verb expert lexicon between shallow parsing and deep parsing to handle morpho-syntactic interaction. with precision/recall combined performance benchmarked consistently at 95.8%-97.5%, the phrasal verb identification problem has basically been solved with the presented method.
hidden markov model-based korean part-of-speech tagging considering high agglutinativity, word-spacing, and lexical correlativity. in this paper we present hidden markov models for korean part-of-speech tagging, which consider korean characteristics such as high agglutinativity, word-spacing, and high lexical correlativity. in order ot consider rich information in contexts, the models adopt a less strict markov assumption. in the models, sparse-data problem is very serious and their parameters tend to be estimated unreliably because they have a large number of parameters. to overcome sparse-data problem, our model uses a simplified version of the well-known back-off smoothing method. to mitigate unreliable estimation problem, our models assume joint independence instead of conditional independence because joint probabilities have the same degree of estimation reliability. experimental results show that models with rich contexts perform even better than standard hmms and that joint independent assumption is effective in some models.
feature-rich statistical translation of noun phrases. we define noun phrase translation as a subtask of machine translation. this enables us to build a dedicated noun phrase translation subsystem that improves over the currently best general statistical machine translation methods by incorporating special modeling and special features. we achieved 65.5% translation accuracy in a german-english translation task vs. 53.2% with ibm model 4.
ambiguity resolution for machine translation of telegraphic messages. telegraphic messages with numerous instances of omission pose a new challenge to parsing in that a sentence with omission causes a higher degree of ambiguity than a sentence without omission. misparsing induced by omissions has a far-reaching consequence in machine translation. namely, a misparse of the input often leads to a translation into the target language which has incoherent meaning in the given context. this is more frequently the case if the structures of the source and target languages are quite different, as in english and korean. thus, the question of how we parse telegraphic messages accurately and efficiently becomes a critical issue in machine translation. in this paper we describe a technical solution for the issue, and present the performance evaluation of a machine translation system on telegraphic messages before and after adopting the proposed solution. the solution lies in a grammar design in which lexicalized grammar rules defined in terms of semantic categories and syntactic rules defined in terms of part-of-speech are utilized together. the proposed grammar achieves a higher parsing coverage without increasing the amount of ambiguity/misparsing when compared with a purely lexicalized semantic grammar, and achieves a lower degree of ambiguity/misparses without decreasing the parsing coverage when compared with a purely syntactic grammar.
learning semantic classes for word sense disambiguation. word sense disambiguation suffers from a long-standing problem of knowledge acquisition bottleneck. although state of the art supervised systems report good accuracies for selected words, they have not been shown to be promising in terms of scalability. in this paper, we present an approach for learning coarser and more general set of concepts from a sense tagged corpus, in order to alleviate the knowledge acquisition bottleneck. we show that these general concepts can be transformed to fine grained word senses using simple heuristics, and applying the technique for recent senseval data sets shows that our approach can yield state of the art performance.
how to cover a grammar. a novel formalism is presented for earley-like parsers. it accommodates the simulation of non-deterministic pushdown automata. in particular, the theory is applied to non-deterministic lr-parsers for rtn grammars.
solving analogies on words: an algorithm. to introduce the algorithm presented in this paper, we take a path that is inverse to the historical development of the idea of analogy (see (hoffman 95)). this is necessary, because a certain incomprehension is faced when speaking about linguistic analogy, i.e., it is generally given a broader and more psychological definition. also, with our proposal being computational, it is impossible to ignore works about analogy in computer science, which has come to mean artificial intelligence.
a polynomial-time fragment of dominance constraints. dominance constraints are logical descriptions of trees that are widely used in computational linguistics. their general satisfiability problem is known to be np-complete. here we identify the natural fragment of normal dominance constraints and show that its satisfiability problem is in deterministic polynomial time.
analysis of conjunctions in a rule-based parser. the aim of the present paper is to show how a rule-based parser for the italian language has been extended to analyze sentences involving conjunctions. the most noticeable fact is the ease with which the required modifications fit in the previous parser structure. in particular, the rules written for analyzing simple sentences (without conjunctions) needed only small changes. on the contrary, more substantial changes were made to the exception-handling rules (called "natural changes") that are used to restructure the tree in case of failure of a syntactic hypothesis. the parser described in the present work constitutes the syntactic component of the fido system (a flexible interface for database operations), an interface allowing an end-user to access a relational database in natural language (italian).
generation as dependency parsing. natural-language generation from flat semantics is an np-complete problem. this makes it necessary to develop algorithms that run with reasonable efficiency in practice despite the high worst-case complexity. we show how to convert tag generation problems into dependency parsing problems, which is useful because optimizations in recent dependency parsers based on constraint programming tackle exactly the combinatorics that make generation hard. indeed, initial experiments display promising runtimes.
the structure and process of talking about doing. people talk about what they do, often at the same time as they are doing. this reporting has an important function in coordinating action between people working together on real everyday problems. it is also an important source of data for social scientists studying people's behavior. in this paper, we report on some studies we are doing on report dialogues. we describe two kinds of phenomena we have identified, outline a preliminary process model that integrates the report generation with the processes that are generating the actions being reported upon, and specify a systematic methodology for extracting relevant evidence bearing on these phenomena from text transcripts of talk about doing to use in evaluating the model.
efficient solving and exploration of scope ambiguities. we present the currently most efficient solver for scope underspecification; it also converts between different underspecification formalisms and counts readings. our tool makes the practical use of large-scale grammars with (underspecified) semantic output more feasible, and can be used in grammar debugging.
characterizing and recognizing spoken corrections in human-computer dialogue. miscommunication in speech recognition systems is unavoidable, but a detailed characterization of user corrections will enable speech systems to identify when a correction is taking place and to more accurately recognize the content of correction utterances. in this paper we investigate the adaptations of users when they encounter recognition errors in interactions with a voice-in/voice-out spoken language system. in analyzing more than 300 pairs of original and repeat correction utterances, matched on speaker and lexical content, we found overall increases in both utterance and pause duration from original to correction. interestingly, corrections of misrecognition erros (cme) exhibited significantly heightened pitch variability, while corrections of rejection errors (cre) showed only a small but significant decrease in pitch minimum. cme's demonstrated much greater increases in measures of duration and pitch variability than cre's. these contrasts allow the development of decision trees which distinguish cme's from cre's and from original inputs at 70--75% accuracy based on duration, pitch, and amplitude features.
an improved redundancy elimination algorithm for underspecified representations. we present an efficient algorithm for the redundancy elimination problem: given an underspecified semantic representation (usr) of a scope ambiguity, compute an usr with fewer mutually equivalent readings. the algorithm operates on underspecified chart representations which are derived from dominance graphs; it can be applied to the usrs computed by large-scale grammars. we evaluate the algorithm on a corpus, and show that it reduces the degree of ambiguity significantly while taking negligible runtime.
is it harder to parse chinese, or the chinese treebank? we present a detailed investigation of the challenges posed when applying parsing models developed against english corpora to chinese. we develop a factored-model statistical parser for the penn chinese treebank, showing the implications of gross statistical differences between wsj and chinese tree-banks for the most general methods of parser adaptation. we then provide a detailed analysis of the major sources of statistical parse errors for this corpus, showing their causes and relative frequencies, and show that while some types of errors are due to difficult ambiguities inherent in chinese grammar, others arise due to treebank annotation practices. we show how each type of error can be addressed with simple, targeted changes to the independence assumptions of the maximum likelihood-estimated pcfg factor of the parsing model, which raises our f1 from 80.7% to 82.6% on our development set, and achieves parse accuracy close to the best published figures for chinese parsing.
generative power of ccgs with generalized type-raised categories. this paper shows that a class of combinatory categorial grammars (ccgs) augmented with a linguistically-motivated form of type raising involving variables is weakly equivalent to the standard ccgs not involving variables. the proof is based on the idea that any instance of such a grammar can be simulated by a standard ccg.
deep dependencies from context-free statistical parsers: correcting the surface dependency approximation. we present a linguistically-motivated algorithm for reconstructing nonlocal dependency in broad-coverage context-free parse trees derived from treebanks. we use an algorithm based on loglinear classifiers to augment and reshape context-free trees so as to reintroduce underlying nonlocal dependencies lost in the context-free approximation. we find that our algorithm compares favorably with prior work on english using an existing evaluation metric, and also introduce and argue for a new dependency-based evaluation metric. by this new evaluation metric our algorithm achieves 60% error reduction on gold-standard input trees and 5% error reduction on state-of-the-art machine-parsed input trees, when compared with the best previous work. we also present the first results on non-local dependency reconstruction for a language other than english, comparing performance on english and german. our new evaluation metric quantitatively corroborates the intuition that in a language with freer word order, the surface dependencies in context-free parse trees are a poorer approximation to underlying dependency structure.
flexible guidance generation using user model in spoken dialogue systems. we address appropriate user modeling in order to generate cooperative responses to each user in spoken dialogue systems. unlike previous studies that focus on user's knowledge or typical kinds of users, the user model we propose is more comprehensive. specifically, we set up three dimensions of user models: skill level to the system, knowledge level on the target domain and the degree of hastiness. moreover, the models are automatically derived by decision tree learning using real dialogue data collected by the system. we obtained reasonable classification accuracy for all dimensions. dialogue strategies based on the user modeling are implemented in kyoto city bus information system that has been developed at our laboratory. experimental evaluation shows that the cooperative responses adaptive to individual users serve as good guidance for novice users without increasing the dialogue duration for skilled users.
neural network recognition of spelling errors. one area in which artificial neural networks (anns) may strengthen nlp systems is in the identification of words under noisy conditions. in order to achieve this benefit when spelling errors or spelling variants are present, variable-length strings of symbols must be converted to ann input/output form---fixed-length arrays of numbers. a common view in the neural network community has been that different forms of input/output representations have negligible effect on ann performance. this paper, however, shows that input/output representations can in fact affect the performance of anns in the case of natural language words. minimum properties for an adequate word representation are proposed, as well as new methods of word representation.to test the hypothesis that word representations significantly affect ann performance, traditional and new word representations are evaluated for their ability to recognize words in the presence of four types of typographical noise: substitutions, insertions, deletions and reversals of letters. the results indicate that word representations have a significant effect on ann performance. additionally, different types of word representation are shown to perform better on different types of error.
parsing as natural deduction. the logic behind parsers for categorial grammars can be formalized in several different ways. lambek calculus (lc) constitutes an example for a natural deduction1 style parsing method.in natural language processing, the task of a parser usually consists in finding derivations for all different readings of a sentence. the original lambek calculus, when it is used as a parser/theorem prover, has the undesirable property of allowing for the derivation of more than one proof for a reading of a sentence, in the general case.in order to overcome this inconvenience and to turn lambek calculus into a reasonable parsing method, we show the existence of "relative" normal form proof trees and make use of their properties to constrain the proof procedure in the desired way.
a freely available morphological analyzer, disambiguator and context sensitive lemmatizer for german. in this paper we present morphy, an integrated tool for german morphology, part-of-speech tagging and context-sensitive lemmatization. its large lexicon of more than 320, 000 word forms plus its ability to process german compound nouns guarantee a wide morphological coverage. syntactic ambiguities can be resolved with a standard statistical part-of-speech tagger. by using the output of the tagger, the lemmatizer can determine the correct root even for ambiguous word forms. the complete package is freely available and can be downloaded from the world wide web.
parsing and subcategorization data. in this paper, we compare the performance of a state-of-the-art statistical parser (bikel, 2004) in parsing written and spoken language and in generating subcategorization cues from written and spoken language. although bikel's parser achieves a higher accuracy for parsing written language, it achieves a higher accuracy when extracting subcategorization cues from spoken language. additionally, we explore the utility of punctuation in helping parsing and extraction of subcategorization cues. our experiments show that punctuation is of little help in parsing spoken language and extracting subcategorization cues from spoken language. this indicates that there is no need to add punctuation in transcribing spoken corpora simply in order to help parsers.
principle-based parsing without overgeneration. overgeneration is the main source of computational complexity in previous principle-based parsers. this paper presents a message passing algorithm for principle-based parsing that avoids the overgeneration problem. this algorithm has been implemented in c++ and successfully tested with example sentences from (van riemsdijk and williams, 1986).
automatic classification of verbs in biomedical texts. lexical classes, when tailored to the application and domain in question, can provide an effective means to deal with a number of natural language processing (nlp) tasks. while manual construction of such classes is difficult, recent research shows that it is possible to automatically induce verb classes from cross-domain corpora with promising accuracy. we report a novel experiment where similar technology is applied to the important, challenging domain of biomedicine. we show that the resulting classification, acquired from a corpus of biomedical journal articles, is highly accurate and strongly domain-specific. it can be used to aid bio-nlp directly or as useful material for investigating the syntax and semantics of verbs in biomedical texts.
word clustering and disambiguation based on co-occurence data. we address the problem of clustering words (or constructing a thesaurus) based on co-occurrence data, and using the acquired word classes to improve the accuracy of syntactic disambiguation. we view this problem as that of estimating a joint probability distribution specifying the joint probabilities of word pairs, such as noun verb pairs. we propose an efficient algorithm based on the minimum description length (mdl) principle for estimating such a probability distribution. our method is a natural extension of those proposed in (brown et al., 1992) and (li and abe, 1996), and overcomes their drawbacks while retaining their advantages. we then combined this clustering method with the disambiguation method of (li and abe, 1995) to derive a disambiguation method that makes use of both automatically constructed thesauruses and a hand-made thesaurus. the overall disambiguation accuracy achieved by our method is 85.2%, which compares favorably against the accuracy (82.4%) obtained by the state-of-the-art disambiguation method of (brill and resnik, 1994).
knowledge-based automatic topic identification. as the first step in an automated text summarization algorithm, this work presents a new method for automatically identifying the central ideas in a text based on a knowledge-based concept counting paradigm. to represent and generalize concepts, we use the hierarchical concept taxonomy wordnet. by setting appropriate cutoff values for such parameters as concept generality and child-to-parent frequency ratio, we control the amount and level of generality of concepts extracted from the text.
clustering polysemic subcategorization frame distributions semantically. previous research has demonstrated the utility of clustering in inducing semantic verb classes from undisambiguated corpus data. we describe a new approach which involves clustering subcategorization frame (scf) distributions using the information bottleneck and nearest neighbour methods. in contrast to previous work, we particularly focus on clustering polysemic verbs. a novel evaluation scheme is proposed which accounts for the effect of polysemy on the clusters, offering us a good insight into the potential and limitations of semantically classifying undisambiguated scf data.
parsing and subcategorization data. in this paper, we compare the performance of a state-of-the-art statistical parser (bikel, 2004) in parsing written and spoken language and in generating subcategorization cues from written and spoken language. although bikel's parser achieves a higher accuracy for parsing written language, it achieves a higher accuracy when extracting subcategorization cues from spoken language. our experiments also show that current technology for extracting subcategorization frames initially designed for written texts works equally well for spoken language. additionally, we explore the utility of punctuation in helping parsing and extraction of subcategorization cues. our experiments show that punctuation is of little help in parsing spoken language and extracting subcategorization cues from spoken language. this indicates that there is no need to add punctuation in transcribing spoken corpora simply in order to help parsers.
using syntactic dependency as local context to resolve word sense ambiguity. most previous corpus-based algorithms disambiguate a word with a classifier trained from previous usages of the same word. separate classifiers have to be trained for different words. we present an algorithm that uses the same knowledge sources to disambiguate different words. the algorithm does not require a sense-tagged corpus and exploits the fact that two different words are likely to have similar meanings if they occur in identical local contexts.
improving subcategorization acquisition using word sense disambiguation. we investigate the change in performance of automatic subcategorization acquisition when a word sense disambiguation (wsd) system is employed to guide the acquisition process. as a subgoal, this involves creating a probabilistic wsd system, which we evaluate on the senseval-2 english all-words task data. we carry out an evaluation of the enriched subcategorization acquisition system using 29 'difficult' english verbs which shows that wsd helps to improve the acquisition performance.
a test environment for natural language understanding systems. the natural language understanding engine test environment (ete) is a gui software tool that aids in the development and maintenance of large, modular, natural language understanding (nlu) systems. natural language understanding systems are composed of modules (such as part-of-speech taggers, parsers and semantic analyzers) which are difficult to test individually because of the complexity of their output data structures. not only are the output data structures of the internal modules complex, but also many thousands of test items (messages or sentences) are required to provide a reasonable sample of the linguistic structures of a single human language, even if the language is restricted to a particular domain. the ete assists in the management and analysis of the thousands of complex data structures created during natural language processing of a large corpus using relational database technology in a network environment.
on the intonation of mono- and di-syllabic words within the discourse framework of conversational games. recent studies on the analysis of intonational function examine a range of materials from cue phrases in monologue (litman and hirschberg, 1990) and dialogue (hirschberg and litman, 1987; hockey, 1991) to longer utterances in both monologue and dialogue (mclemore, 1991). results match specific intonational tunes to certain discourse functions which are more or less well defined. although these results make a convincing case that intonation does signal a change in discourse structure, the specification of discourse function remains vague. a suitable taxonomy is needed to fine-tune the relationship between intonation and discourse function. a recent analysis of dialogue (kowtko et al., 1991) provides a framework of conversational games which allows more fine-grained examination of prosodic function. the current paper introduces an intonational analysis of mono-and di-syllabic words based upon such a framework and compares results in progress with previous work on intonation.
word translation disambiguation using bilingual bootstrapping. this paper proposes a new method for word translation disambiguation using a machine learning technique called 'bilingual bootstrapping'. bilingual bootstrapping makes use of in learning, a small number of classified data and a large number of unclassified data in the source and the target languages in translation. it constructs classifiers in the two languages in parallel and repeatedly boosts the performances of the classifiers by further classifying data in each of the two languages and by exchanging between the two languages information regarding the classified data. experimental results indicate that word translation disambiguation based on bilingual bootstrapping consistently and significantly outperforms the existing methods based on 'monolingual bootstrapping'.
automatic retrieval and clustering of similar words. bootstrapping semantics from text is one of the greatest challenges in natural language learning. we first define a word similarity measure based on the distributional pattern of words. the similarity measure allows us to construct a thesaurus using a parsed corpus. we then present a new evaluation methodology for the automatically constructed thesaurus. the evaluation results show that the thesaurus is significantly closer to wordnet than roget thesaurus is.
large scale collocation data and their application to japanese word processor technology. word processors or computers used in japan employ japanese input method through keyboard stroke combined with kana (phonetic) character to kanji (ideographic, chinese) character conversion technology. the key factor of kana-to-kanji conversion technology is how to raise the accuracy of the conversion through the homophone processing, since we have so many homophonic kanjis. in this paper, we report the results of our kana-to-kanji conversion experiments which embody the homophone processing based on large scale collocation data. it is shown that approximately 135,000 collocations yield 9.1 % raise of the conversion accuracy compared with the prototype system which has no collocation data.
identifying syntactic role of antecedent in korean relative clause using corpus and thesaurus information. this paper describes an approach to identifying the syntactic role of an antecedent in a korean relative clause, which is essential to structural disambiguation and semantic analysis. in a learning phase, linguistic knowledge such as conceptual co-occurrence patterns and syntactic role distribution of antecedents is extracted from a large-scale corpus. then, in an application phase, the extracted knowledge is applied in determining the correct syntactic role of an antecedent in relative clauses. unlike previous research based on co-occurrence patterns at the lexical level, we represent co-occurrence patterns with concept types in a thesaurus. in an experiment, the proposed method showed a high accuracy rate of 90.4% in resolving ambiguities of syntactic role determination of antecedents.
text segmentation based on similarity between words. this paper proposes a new indicator of text structure, called the lexical cohesion profile (lcp), which locates segment boundaries in a text. a text segment is a coherent scene; the words in a segment are linked together via lexical cohesion relations. lcp records mutual similarity of words in a sequence of text. the similarity of words, which represents their cohesiveness, is computed using a semantic network. comparison with the text segments marked by a number of subjects shows that lcp closely correlates with the human judgments. lcp may provide valuable information for resolving anaphora and ellipsis.
a phonotactic language model for spoken language identification. we have established a phonotactic language model as the solution to spoken language identification (lid). in this framework, we define a single set of acoustic tokens to represent the acoustic activities in the world's spoken languages. a voice tokenizer converts a spoken document into a text-like document of acoustic tokens. thus a spoken document can be represented by a count vector of acoustic tokens and token n-grams in the vector space. we apply latent semantic analysis to the vectors, in the same way that it is applied in information retrieval, in order to capture salient phonotactics present in spoken documents. the vector space modeling of spoken utterances constitutes a paradigm shift in lid technology and has proven to be very successful. it presents a 12.4% error rate reduction over one of the best reported results on the 1996 nist language recognition evaluation database.
automatic identification of non-compositional phrases. non-compositional expressions present a special challenge to nlp applications. we present a method for automatic identification of non-compositional expressions using their statistical properties in a text corpus. our method is based on the hypothesis that when a phrase is non-composition, its mutual information differs significantly from the mutual informations of phrases obtained by substituting one of the word in the phrase with a similar word.
feature-based allomorphy. morphotactics and allomorphy are usually modeled in different components, leading to interface problems. to describe both uniformly, we define finite automata (fa) for allomorphy in the same feature description language used for morphotactics. nonphonologically conditioned allomorphy is problematic in fa models but submits readily to treatment in a uniform formalism.
concept unification of terms in different languages for ir. due to the historical and cultural reasons, english phases, especially the proper nouns and new words, frequently appear in web pages written primarily in asian languages such as chinese and korean. although these english terms and their equivalences in the asian languages refer to the same concept, they are erroneously treated as independent index units in traditional information retrieval (ir). this paper describes the degree to which the problem arises in ir and suggests a novel technique to solve it. our method firstly extracts an english phrase from asian language web pages, and then unifies the extracted phrase and its equivalence(s) in the language as one index unit. experimental results show that the high precision of our conceptual unification approach greatly improves the ir performance.
quantifying lexical influence: giving direction to context. the relevance of context in disambiguating natural language input has been widely acknowledged in the literature. however, most attempts at formalising the intuitive notion of context tend to treat the word and its context symmetrically. we demonstrate here that traditional measures such as mutual information score are likely to overlook a significant fraction of all co-occurrence phenomena in natural language. we also propose metrics for measuring directed lexical influence and compare performances.
a comparison and semi-quantitative analysis of words and character-bigrams as features in chinese text categorization. words and character-bigrams are both used as features in chinese text processing tasks, but no systematic comparison or analysis of their values as features for chinese text categorization has been reported heretofore. we carry out here a full performance comparison between them by experiments on various document collections (including a manually word-segmented corpus as a golden standard), and a semi-quantitative analysis to elucidate the characteristics of their behavior; and try to provide some preliminary clue for feature term choice (in most cases, character-bigrams are better than words) and dimensionality setting in text categorization systems.
an effective two-stage model for exploiting non-local dependencies in named entity recognition. this paper shows that a simple two-stage approach to handle non-local dependencies in named entity recognition (ner) can outperform existing approaches that handle non-local dependencies, while being much more computationally efficient. ner systems typically use sequence models for tractable inference, but this makes them unable to capture the long distance structure present in text. we use a conditional random field (crf) based ner system using local features to make predictions and then train another crf which uses both local information and features extracted from the output of the first crf. using features capturing non-local dependencies from the same document, our approach yields a 12.6% relative error reduction on the f1 score, over state-of-the-art ner systems using local-information alone, when compared to the 9.3% relative error reduction offered by the best systems that exploit non-local information. our approach also makes it easy to incorporate non-local information from other documents in the test corpus, and this gives us a 13.3% error reduction over ner systems using local-information alone. additionally, our running time for inference is just the inference time of two sequential crfs, which is much less than that directly model the dependencies and do approximate inference.
applying machine learning to chinese temporal relation resolution. temporal relation resolution involves extraction of temporal information explicitly or implicitly embedded in a language. this information is often inferred from a variety of interactive grammatical and lexical cues, especially in chinese. for this purpose, inter-clause relations (temporal or otherwise) in a multiple-clause sentence play an important role. in this paper, a computational model based on machine learning and heterogeneous collaborative bootstrapping is proposed for analyzing temporal relations in a chinese multiple-clause sentence. the model makes use of the fact that events are represented in different temporal structures. it takes into account the effects of linguistic features such as tense/aspect, temporal connectives, and discourse structures. a set of experiments has been conducted to investigate how linguistic features could affect temporal relation resolution.
conversationally relevant descriptions. conversationally relevant descriptions are definite descriptions that are not merely tools for the identification of a referent, but are also crucial to the discourse in other respects. i analyse the uses of such descriptions in assertions as conveying a particular type of conversational implicatures. such implicatures can be represented within the framework of possible world semantics. the analysis is extended to non-assertive illocutionary acts on the one hand, and to indefinite descriptions on the other.
extractive summarization using inter- and intra- event relevance. event-based summarization attempts to select and organize the sentences in a summary with respect to the events or the sub-events that the sentences describe. each event has its own internal structure, and meanwhile often relates to other events semantically, temporally, spatially, causally or conditionally. in this paper, we define an event as one or more event terms along with the named entities associated, and present a novel approach to derive intra- and inter- event relevance using the information of internal association, semantic relatedness, distributional similarity and named entity clustering. we then apply pagerank ranking algorithm to estimate the significance of an event for inclusion in a summary from the event relevance derived. experiments on the duc 2001 test data shows that the relevance of the named entities involved in events achieves better result when their relevance is derived from the event terms they associate. it also reveals that the topic-specific relevance from documents themselves outperforms the semantic relevance from a general purpose knowledge base like word-net.
compacting the penn treebank grammar. treebanks, such as the penn treebank (ptb), offer a simple approach to obtaining a broad coverage grammar: one can simply read the grammar off the parse trees in the treebank. while such a grammar is easy to obtain, a square-root rate of growth of the rule set with corpus size suggests that the derived grammar is far from complete and that much more treebanked text would be required to obtain a complete grammar, if one exists at some limit. however, we offer an alternative explanation in terms of the underspecification of structures within the treebank. this hypothesis is explored by applying an algorithm to compact the derived grammar by eliminating redundant rules - rules whose right hand sides can be parsed by other rules. the size of the resulting compacted grammar, which is significantly less than that of the full treebank grammar, is shown to approach a limit. however, such a compacted grammar does not yield very good performance figures. a version of the compaction algorithm taking rule probabilities into account is proposed, which is argued to be more linguistically motivated. combined with simple thresholding, this method can be used to give a 58% reduction in grammar size without significant change in parsing performance, and can produce a 69% reduction with some gain in recall, but a loss in precision.
discriminative pruning of language models for chinese word segmentation. this paper presents a discriminative pruning method of n-gram language model for chinese word segmentation. to reduce the size of the language model that is used in a chinese word segmentation system, importance of each bigram is computed in terms of discriminative pruning criterion that is related to the performance loss caused by pruning the bigram. then we propose a step-by-step growing algorithm to build the language model of desired size. experimental results show that the discriminative pruning method leads to a much smaller model compared with the model pruned using the state-of-the-art method. at the same chinese word segmentation f-measure, the number of bigrams in the model can be reduced by up to 90%. correlation between language model perplexity and word segmentation performance is also discussed.
sense-linking in a machine readable dictionary. dictionaries contain a rich set of relationships between their senses, but often these relationships are only implicit. we report on our experiments to automatically identify links between the senses in a machine-readable dictionary. in particular, we automatically identify instances of zero-affix morphology, and use that information to find specific linkages between senses. this work has provided insight into the performance of a stochastic tagger.
sentence fragments regular structures. this paper describes an analysis of telegraphic fragments as regular structures (not errors) handled by minimal extensions to a system designed for processing the standard language. the modular approach which has been implemented in the unisys natural language processing system pundit is based on a division of labor in which syntax regulates the occurrence and distribution of elided elements, and semantics and pragmatics use the system's standard mechanisms to interpret them.
an end-to-end discriminative approach to machine translation. we present a perceptron-style discriminative approach to machine translation in which large feature sets can be exploited. unlike discriminative reranking approaches, our system can take advantage of learned features in all stages of decoding. we first discuss several challenges to error-driven discriminative approaches. in particular, we explore different ways of updating parameters given a training example. we find that making frequent but smaller updates is preferable to making fewer but larger updates. then, we discuss an array of features and show both how they quantitatively increase bleu score and how they qualitatively interact on specific examples. one particular feature we investigate is a novel way to introduce learning into the initial phrase extraction process, which has previously been entirely heuristic.
morphological cues for lexical semantics. most natural language processing tasks require lexical semantic information. automated acquisition of this information would thus increase the robustness and portability of nlp systems. this paper describes an acquisition method which makes use of fixed correspondences between derivational affixes and lexical semantic information. one advantage of this method, and of other methods that rely only on surface characteristics of language, is that the necessary input is currently available.
are these documents written from different perspectives? a test of different perspectives based on statistical distribution divergence. in this paper we investigate how to automatically determine if two document collections are written from different perspectives. by perspectives we mean a point of view, for example, from the perspective of democrats or republicans. we propose a test of different perspectives based on distribution divergence between the statistical models of two collections. experimental results show that the test can successfully distinguish document collections of different perspectives from other types of collections.
automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics. in this paper we describe two new objective automatic evaluation methods for machine translation. the first method is based on longest common subsequence between a candidate translation and a set of reference translations. longest common subsequence takes into account sentence level structure similarity naturally and identifies longest co-occurring in-sequence n-grams automatically. the second method relaxes strict n-gram matching to skip-bigram matching. skip-bigram is any pair of words in their sentence order. skip-bigram cooccurrence statistics measure the overlap of skip-bigrams between a candidate translation and a set of reference translations. the empirical results show that both methods correlate with human judgments very well in both adequacy and fluency.
learning constraint grammar-style disambiguation rules using inductive logic programming. this paper reports a pilot study, in which constraint grammar inspired rules were learnt using the progol machine-learning system. rules discarding faulty readings of ambiguously tagged words were learnt for the part of speech tags of the stockholm-ume&aring; corpus. several thousand disambiguation rules were induced. when tested on unseen data, 98% of the words retained the correct reading after tagging. however, there were ambiguities pending after tagging, on an average 1.13 tags per word. the results suggest that the progol system can be useful for learning tagging rules of good quality.
generating precondition expressions in instructional text. this study employs a knowledge intensive corpus analysis to identify the elements of the communicative context which can be used to determine the appropriate lexical and grammatical form of instructional texts. imagene, an instructional text generation system based on this analysis, is presented, particularly with reference to its expression of precondition relations.
algorithms for generation in lambek theorem proving. we discuss algorithms for generation within the lambek theorem proving framework. efficient algorithms for generation in this framework take a semantics-driven strategy. this strategy can be modeled by means of rules in the calculus that are geared to generation, or by means of an algorithm for the theorem prover. the latter possibility enables processing of a bidirectional calculus. therefore lambek theorem proving is a natural candidate for a 'uniform' architecture for natural language parsing and generation.
modeling adjectives in computational relational lexica. in this paper we propose a small set of lexical conceptual relations which allow to encode adjectives in computational relational lexica in a principled and integrated way. our main motivation comes from the fact that adjectives and certain classes of verbs, related in a way or another with adjectives, do not have a satisfactory representation in this kind of lexica. this is due to a great extent to the heterogeneity of their semantic and syntactic properties. we sustain that such properties are mostly derived from the relations holding between adjectives and other pos. accordingly, our proposal is mainly concerned with the specification of appropriate cross-pos relations to encode adjectives in lexica of the type considered here.
examining the content load of part of speech blocks for information retrieval. we investigate the connection between part of speech (pos) distribution and content in language. we define pos blocks to be groups of parts of speech. we hypothesise that there exists a directly proportional relation between the frequency of pos blocks and their content salience. we also hypothesise that the class membership of the parts of speech within such blocks reflects the content load of the blocks, on the basis that open class parts of speech are more content-bearing than closed class parts of speech. we test these hypotheses in the context of information retrieval, by syntactically representing queries, and removing from them content-poor blocks, in line with the aforementioned hypotheses. for our first hypothesis, we induce pos distribution information from a corpus, and approximate the probability of occurrence of pos blocks as per two statistical estimators separately. for our second hypothesis, we use simple heuristics to estimate the content load within pos blocks. we use the text retrieval conference (trec) queries of 1999 and 2000 to retrieve documents from the wt2g and wt10g test collections, with five different retrieval strategies. experimental outcomes confirm that our hypotheses hold in the context of information retrieval.
learning to predict pitch accents and prosodic boundaries in dutch. we train a decision tree inducer (cart) and a memory-based classifier (mbl) on predicting prosodic pitch accents and breaks in dutch text, on the basis of shallow, easy-to-compute features. we train the algorithms on both tasks individually and on the two tasks simultaneously. the parameters of both algorithms and the selection of features are optimized per task with iterative deepening, an efficient wrapper procedure that uses progressive sampling of training data. results show a consistent significant advantage of mbl over cart, and also indicate that task combination can be done at the cost of little generalization score loss. tests on cross-validated data and on held-out data yield f-scores of mbl on accent placement of 84 and 87, respectively, and on breaks of 88 and 91, respectively. accent placement is shown to outperform an informed baseline rule; reliably predicting breaks other than those already indicated by intra-sentential punctuation, however, appears to be more challenging.
truecasing. truecasing is the process of restoring case information to badly-cased or non-cased text. this paper explores truecasing issues and proposes a statistical, language modeling based truecaser which achieves an accuracy of ~98% on news articles. task based evaluation shows a 26% f-measure improvement in named entity recognition when using truecasing. in the context of automatic content extraction, mention detection on automatic speech recognition text is also improved by a factor of 8. truecasing also enhances machine translation output legibility and yields a bleu score improvement of 80.2%. this paper argues for the use of truecasing as a valuable component in text processing applications.
cl research's knowledge management system. cl research began experimenting with massive xml tagging of texts to answer questions in trec 2002. in duc 2003, the experiments were extended into text summarization. based on these experiments, the knowledge management system (kms) was developed to combine these two capabilities and to serve as a unified basis for other types of document exploration. kms has been extended to include web question answering, both general and topic-based summarization, information extraction, and document exploration. the document exploration functionality includes identification of semantically similar concepts and dynamic ontology creation. as development of kms has continued, user modeling has become a key research issue: how will different users want to use the information they identify.
comparing two grammar-based generation algorithms: a case study. in this paper we compare two grammar-based generation algorithms: the semantic-head-driven generation algorithm (shdga), and the essential arguments algorithm (eaa). both algorithms have successfully addressed several outstanding problems in grammar-based generation, including dealing with non-monotonic compositionality of representation, left-recursion, deadlock-prone rules, and nondeterminism. we concentrate here on the comparison of selected properties: generality, efficiency, and determinism. we show that eaa's traversals of the analysis tree for a given language construct, include also the one taken on by shdga. we also demonstrate specific and common situations in which shdga will invariably run into serious inefficiency and nondeterminism, and which eaa will handle in an efficient and deterministic manner. we also point out that only eaa allows to treat the underlying grammar in a truly multi-directional manner.
predicting student emotions in computer-human tutoring dialogues. we examine the utility of speech and lexical features for predicting student emotions in computer-human spoken tutoring dialogues. we first annotate student turns for negative, neutral, positive and mixed emotions. we then extract acoustic-prosodic features from the speech signal, and lexical items from the transcribed or recognized speech. we compare the results of machine learning experiments using these features alone or in combination to predict various categorizations of the annotated student emotions. our best results yield a 19-36% relative improvement in error reduction over a baseline. finally, we compare our results with emotion prediction in human-human tutoring dialogues.
bitext correspondences through rich mark-up. rich mark-up can considerably benefit the process of establishing bitext correspondences, that is, the task of providing correct identification and alignment methods for text segments that are translation equivalences of each other in a parallel corpus. we present a sentence alignment algorithm that, by taking advantage of previously annotated texts, obtains accuracy rates close to 100%. the algorithm evaluates the similarity of the linguistic and extralinguistic mark-up in both sides of a bitext. given that annotations are neutral with respect to typological, grammatical and orthographical differences between languages, rich mark-up becomes an optimal foundation to support bitext correspondences. the main originality of this approach is that it makes maximal use of annotations, which is a very sensible and efficient method for the exploitation of parallel corpora when annotations exist.
predicting user reactions to system error. this paper focuses on the analysis and prediction of so-called aware sites, defined as turns where a user of a spoken dialogue system first becomes aware that the system has made a speech recognition error. we describe statistical comparisons of features of these aware sites in a train timetable spoken dialogue corpus, which reveal significant prosodic differences between such turns, compared with turns that 'correct' speech recognition errors as well as with 'normal' turns that are neither aware sites nor corrections. we then present machine learning results in which we show how prosodic features in combination with other automatically available features can predict whether or not a user turn was a normal turn, a correction, and/or an aware site.
structural disambiguation with constraint propagation. we present a new grammatical formalism called constraint dependency grammar (cdg) in which every grammatical rule is given as a constraint on word-to-word modifications. cdg parsing is formalized as a constraint satisfaction problem over a finite domain so that efficient constraint-propagation algorithms can be employed to reduce structural ambiguity without generating individual parse trees. the weak generative capacity and the computational complexity of cdg parsing are also discussed.
combining multiple knowledge sources for discourse segmentation. we predict discourse segment boundaries from linguistic features of utterances, using a corpus of spoken narratives as data. we present two methods for developing segmentation algorithms from training data: hand tuning and machine learning. when multiple types of features are used, results approach human performance on an independent test set (both methods), and using cross-validation (machine learning).
probabilistic cfg with latent annotations. this paper defines a generative probabilistic model of parse trees, which we call pcfg-la. this model is an extension of pcfg in which non-terminal symbols are augmented with latent variables. fine-grained cfg rules are automatically induced from a parsed corpus by training a pcfg-la model using an em-algorithm. because exact parsing with a pcfg-la is np-hard, several approximations are described and empirically compared. in experiments using the penn wsj corpus, our automatically trained model gave a performance of 86.6% (f1, sentences &le; 40 words), which is comparable to that of an unlexicalized pcfg parser created using extensive manual feature selection.
evaluating response strategies in a web-based spoken dialogue agent. while the notion of a cooperative response has been the focus of considerable research in natural language dialogue systems, there has been little empirical work demonstrating how such responses lead to more efficient, natural, or successful dialogues. this paper presents an experimental evaluation of two alternative response strategies in toot, a spoken dialogue agent that allows users to access train schedules stored on the web via a telephone conversation. we compare the performance of two versions of toot (literal and cooperative), by having users carry out a set of tasks with each version. by using hypothesis testing methods, we show that a combination of response strategy, application task, and task/strategy interactions account for various types of performance differences. by using the paradise evaluation framework to estimate an overall performance function, we identify interdependencies that exist between speech recognition and response strategy. our results elaborate the conditions under which toot's cooperative rather than literal strategy contributes to greater performance.
are: instance splitting strategies for dependency relation-based information extraction. information extraction (ie) is a fundamental technology for nlp. previous methods for ie were relying on co-occurrence relations, soft patterns and properties of the target (for example, syntactic role), which result in problems of handling paraphrasing and alignment of instances. our system are (anchor and relation) is based on the dependency relation model and tackles these problems by unifying entities according to their dependency relations, which we found to provide more invariant relations between entities in many cases. in order to exploit the complexity and characteristics of relation paths, we further classify the relation paths into the categories of 'easy', 'average' and 'hard', and utilize different extraction strategies based on the characteristics of those categories. our extraction method leads to improvement in performance by 3% and 6% for muc4 and muc6 respectively as compared to the state-of-art ie systems.
automatic detection of poor speech recognition at the dialogue level. the dialogue strategies used by a spoken dialogue system strongly influence performance and user satisfaction. an ideal system would not use a single fixed strategy, but would <i>adapt</i> to the circumstances at hand. to do so, a system must be able to identify dialogue properties that suggest adaptation. this paper focuses on identifying situations where the speech recognizer is performing poorly. we adopt a machine learning approach to learn rules from a dialogue corpus for identifying these situations. our results show a significant improvement over the baseline and illustrate that both lower-level acoustic features and higher-level dialogue features can affect the performance of the learning algorithm.
sructural matching of parallel texts. this paper describes a method for finding structural matching between parallel sentences of two languages, (such as japanese and english). parallel sentences are analyzed based on unification grammars, and structural matching is performed by making use of a similarity measure of word pairs in the two languages. syntactic ambiguities are resolved simultaneously in the matching process. the results serve as a useful source for extracting linguistic and lexical knowledge.
building semantic perceptron net for topic spotting. this paper presents an approach to automatically build a semantic perceptron net (spn) for topic spotting. it uses context at the lower layer to select the exact meaning of key words, and employs a combination of context, co-occurrence statistics and thesaurus to group the distributed but semantically related words within a topic to form basic semantic nodes. the semantic nodes are then used to infer the topic within an input document. experiments on reuters 21578 data set demonstrate that spn is able to capture the semantics of topics, and it performs well on topic spotting task.
discourse cues for broadcast news segmentation. this paper describes the design and application of time-enhanced, finite state models of discourse cues to the automated segmentation of broadcast news, we describe our analysis of a broadcast news corpus, the design of a discourse cue based story segmentor that builds upon information extraction techniques, and finally its computational implementation and evaluation in the broadcast news navigator (bnn) to support video news browsing, retrieval, and summarization.
stochastic iterative alignment for machine translation evaluation. a number of metrics for automatic evaluation of machine translation have been proposed in recent years, with some metrics focusing on measuring the adequacy of mt output, and other metrics focusing on fluency. adequacy-oriented metrics such as bleu measure &eta;-gram overlap of mt outputs and their references, but do not represent sentence-level information. in contrast, fluency-oriented metrics such as rouge-w compute longest common subsequences, but ignore words not aligned by the lcs. we propose a metric based on stochastic iterative string alignment (sia), which aims to combine the strengths of both approaches. we compare sia with existing metrics, and find that it outperforms them in overall evaluation, and works specially well in fluency evaluation.
an intermediate representation for the interpretation of temporal expressions. the interpretation of temporal expressions in text is an important constituent task for many practical natural language processing tasks, including question-answering, information extraction and text summarisation. although temporal expressions have long been studied in the research literature, it is only more recently, with the impetus provided by exercises like the ace program, that attention has been directed to broad-coverage, implemented systems. in this paper, we describe our approach to intermediate semantic representations in the interpretation of temporal expressions.
dynamically generating a protein entity dictionary using online resources. with the overwhelming amount of biological knowledge stored in free text, natural language processing (nlp) has received much attention recently to make the task of managing information recorded in free text more feasible. one requirement for most nlp systems is the ability to accurately recognize biological entity terms in free text and the ability to map these terms to corresponding records in databases. such task is called biological named entity tagging. in this paper, we present a system that automatically constructs a protein entity dictionary, which contains gene or protein names associated with uniprot identifiers using online resources. the system can run periodically to always keep up-to-date with these online resources. using online resources that were available on dec. 25, 2004, we obtained 4,046,733 terms for 1,640,082 entities. the dictionary can be accessed from the following website: http://biocreative.ifsm.umbc.edu/biothesaurus/.
should we translate the documents or the queries in cross-language information retrieval? previous comparisons of document and query translation suffered difficulty due to differing quality of machine translation in these two opposite directions. we avoid this difficulty by training identical statistical translation models for both translation directions using the same training data. we investigate information retrieval between english and french, incorporating both translations directions into both document translation and query translation-based information retrieval, as well as into hybrid systems. we find that hybrids of document and query translation-based systems out-perform query translation systems, even human-quality query translation systems.
log-linear models for word alignment. we present a framework for word alignment based on log-linear models. all knowledge sources are treated as feature functions, which depend on the source language sentence, the target language sentence and possible additional variables. log-linear models allow statistical alignment models to be easily extended by incorporating syntactic information. in this paper, we use ibm model 3 alignment probabilities, pos correspondence, and bilingual dictionary coverage as features. our experiments show that log-linear models significantly outperform ibm translation models.
detecting verbal participation in diathesis alternations. we present a method for automatically identifying verbal participation in diathesis alternations. automatically acquired subcategorization frames are compared to a hand-crafted classification for selecting candidate verbs. the minimum description length principle is then used to produce a model and cost for storing the head noun instances from a training corpus at the relevant argument slots. alternating subcategorization frames are identified where the data from corresponding argument slots in the respective frames can be combined to produce a cheaper model than that produced if the data is encoded separately.
tree-to-string alignment template for statistical machine translation. we present a novel translation model based on tree-to-string alignment template (tat) which describes the alignment between a source parse tree and a target string. a tat is capable of generating both terminals and non-terminals and performing reordering at both low and high levels. the model is linguistically syntax-based because tats are extracted automatically from word-aligned, source side parsed parallel texts. to translate a source sentence, we first employ a parser to produce a source parse tree and then apply tats to transform the tree into a target string. our experiments show that the tat-based model significantly outperforms pharaoh, a state-of-the-art decoder for phrase-based models.
finding predominant word senses in untagged text. in word sense disambiguation (wsd), the heuristic of choosing the most common sense is extremely powerful because the distribution of the senses of a word is often skewed. the problem with using the predominant, or first sense heuristic, aside from the fact that it does not take surrounding context into account, is that it assumes some quantity of hand-tagged data. whilst there are a few hand-tagged corpora available for some languages, one would expect the frequency distribution of the senses of words, particularly topical words, to depend on the genre and domain of the text under consideration. we present work on the use of a thesaurus acquired from raw textual corpora and the wordnet similarity package to find predominant noun senses automatically. the acquired predominant senses give a precision of 64% on the nouns of the senseval-2 english all-words task. this is a very promising result given that our method does not require any hand-tagged text, such as semcor. furthermore, we demonstrate that our method discovers appropriate predominant senses for words from two domain-specific corpora.
an empirical study on thematic knowledge acquisition based on syntactic clues and heuristics. thematic knowledge is a basis of semantic interpretation. in this paper, we propose an acquisition method to acquire thematic knowledge by exploiting syntactic clues from training sentences. the syntactic clues, which may be easily collected by most existing syntactic processors, reduce the hypothesis space of the thematic roles. the ambiguities may be further resolved by the evidences either from a trainer or from a large corpus. a set of heuristics based on linguistic constraints is employed to guide the ambiguity resolution process. when a trainer is available, the system generates new sentences whose thematic validities can be justified by the trainer. when a large corpus is available, the thematic validity may be justified by observing the sentences in the corpus. using this way, a syntactic processor may become a thematic recognizer by simply deriving its thematic knowledge from its own syntactic knowledge.
reranking and self-training for parser adaptation. statistical parsers trained and tested on the penn wall street journal (wsj) treebank have shown vast improvements over the last 10 years. much of this improvement, however, is based upon an ever-increasing number of features to be trained on (typically) the wsj treebank data. this has led to concern that such parsers may be too finely tuned to this corpus at the expense of portability to other genres. such worries have merit. the standard "charniak parser" checks in at a labeled precision-recall f-measure of 89.7% on the penn wsj test set, but only 82.9% on the test set from the brown treebank corpus.this paper should allay these fears. in particular, we show that the reranking parser described in charniak and johnson (2005) improves performance of the parser on brown to 85.2%. furthermore, use of the self-training techniques described in (mcclosky et al., 2006) raise this to 87.8% (an error reduction of 28%) again without any use of labeled brown data. this is remarkable since training the parser and reranker on labeled brown data achieves only 88.4%.
using conditional random fields for sentence boundary detection in speech. sentence boundary detection in speech is important for enriching speech recognition output, making it easier for humans to read and downstream modules to process. in previous work, we have developed hidden markov model (hmm) and maximum entropy (maxent) classifiers that integrate textual and prosodic knowledge sources for detecting sentence boundaries. in this paper, we evaluate the use of a conditional random field (crf) for this task and relate results with this model to our prior work. we evaluate across two corpora (conversational telephone speech and broadcast news speech) on both human transcriptions and speech recognition output. in general, our crf model yields a lower error rate than the hmm and maxent models on the nist sentence boundary detection task in speech, although it is interesting to note that the best results are achieved by three-way voting among the classifiers. this probably occurs because each model has different strengths and weaknesses for modeling the knowledge sources.
modular logic grammars. this report describes a logic grammar formalism, modular logic grammars, exhibiting a high degree of modularity between syntax and semantics. there is a syntax rule compiler (compiling into prolog) which takes care of the building of analysis structures and the interface to a clearly separated semantic interpretation component dealing with scoping and the construction of logical forms. the whole system can work in either a one-pass mode or a two-pass mode. in the one-pass mode, logical forms are built directly during parsing through interleaved calls to semantics, added automatically by the rule compiler. in the two-pass mode, syntactic analysis trees are built automatically in the first pass, and then given to the (one-pass) semantic component. the grammar formalism includes two devices which cause the automatically built syntactic structures to differ from derivation trees in two ways: (1) there is a shift operator, for dealing with left-embedding constructions such as english possessive noun phrases while using right-recursive rules (which are appropriate for prolog parsing). (2) there is a distinction in the syntactic formalism between strong non-terminals and weak non-terminals, which is important for distinguishing major levels of grammar.
pens: a machine-aided english writing system for chinese users. writing english is a big barrier for most chinese users. to build a computer-aided system that helps chinese users not only on spelling checking and grammar checking but also on writing in the way of native-english is a challenging task. although machine translation is widely used for this purpose, how to find an efficient way in which human collaborates with computers remains an open issue. in this paper, based on the comprehensive study of chinese users requirements, we propose an approach to machine aided english writing system, which consists of two components: 1) a statistical approach to word spelling help, and 2) an information retrieval based approach to intelligent recommendation by providing suggestive example sentences. both components work together in a unified way, and highly improve the productivity of english writing. we also developed a pilot system, namely pens (perfect english system). preliminary experiments show very promising results.
a functional approach to generation with tag. it has been hypothesized that tree adjoining grammar (tag) is particularly well suited for sentence generation. it is unclear, however, how a sentence generation system based on tag should choose among the syntactic possibilities made available in the grammar. in this paper we consider the question of what needs to be done to generate with tags and explain a generation system that provides the necessary features. this approach is compared with other tag-based generation systems. particular attention is given to mumble-86 which, like our system, makes syntactic choice on sophisticated functional grounds.
an algorithm for plan recognition in collaborative discourse. a model of plan recognition in discourse must be based on intended recognition, distinguish each agent's beliefs and intentions from the other's, and avoid assumptions about the correctness or completeness of the agents' beliefs. in this paper, we present an algorithm for plan recognition that is based on the shared-plan model of collaboration (grosz and sidner, 1990; lochbaum et al., 1990) and that satisfies these constraints.
discriminating image senses by clustering with multimodal features. we discuss image sense discrimination (isd), and apply a method based on spectral clustering, using multimodal features from the image and text of the embedding web page. we evaluate our method on a new data set of annotated web images, retrieved with ambiguous query terms. experiments investigate different levels of sense granularity, as well as the impact of text and image features, and global versus local text features.
target word selection as proximity in semantic space. lexical selection is a significant problem for wide-coverage machine translation: depending on the context, a given source language word can often be translated into different target language words. in this paper i propose a method for target word selection that assumes the appropriate translation is more similar to the translated context than are the alternatives. similarity of a word to a context is estimated using a proximity measure in corpus-derived "semantic space". the method is evaluated using an english-spanish parallel corpus of colloquial dialogue.
memory-efficient and thread-safe quasi-destructive graph unification. in terms of both speed and memory consumption, graph unification remains the most expensive component of unification-based grammar parsing. we present a technique to reduce the memory usage of unification algorithms considerably, without increasing execution times. also, the proposed algorithm is thread-safe, providing an efficient algorithm for parallel processing as well.
a distributional model of semantic context effects in lexical processing. one of the most robust findings of experimental psycholinguistics is that the context in which a word is presented influences the effort involved in processing that word. we present a computational model of contextual facilitation based on word co-occurrence vectors, and empirically validate the model through simulation of three representative types of context manipulation: single word priming, multiple-priming and contextual constraint. the aim of our study is to find out whether special-purpose mechanisms are necessary in order to capture the pattern of the experimental results.
a generic approach to parallel chart parsing with an application to lingo. multi-processor systems are becoming more commonplace and affordable. based on analyses of actual parsings, we argue that to exploit the capabilities of such machines, unification-based grammar parsers should distribute work at the level of individual unification operations. we present a generic approach to parallel chart parsing that meets this requirement, and show that an implementation of this technique for lingo achieves considerable speedups.
online large-margin training of dependency parsers. we present an effective training algorithm for linearly-scored dependency parsers that implements online large-margin multi-class training (crammer and singer, 2003; crammer et al., 2003) on top of efficient parsing techniques for dependency trees (eisner, 1996). the trained parsers achieve a competitive dependency accuracy for both english and czech with no language specific enhancements.
incremental dependency parsing. the paper introduces a dependency-based grammar and the associated parser and focusses on the problem of determinism in parsing and recovery from errors. first, it is shown how dependency-based parsing can be afforded, by taking into account the suggestions coming from other approaches, and the preference criteria for parsing are breifly addressed. second, the issues of the interconnection between the syntactic analysis and the semantic interpretation in incremental processing are discussed and the adoption of a tms for the recovery of the processing errors is suggested.
tags as a grammatical formalism for generation. tree adjoining grammars, or "tag's", (joshi, levy & takahashi 1975; joshi 1983; kroch & joshi 1985) were developed as an alternative to the standard syntactic formalisms that are used in theoretical analyses of language. they are attractive because they may provide just the aspects of context sensitive expressive power that actually appear in human languages while otherwise remaining context free.this paper describes how we have applied the theory of tree adjoining grammars to natural language generation. we have been attracted to tag's because their central operation---the extension of an "initial" phrase structure tree through the inclusion, at very specifically constrained locations, of one or more "auxiliary" trees---corresponds directly to certain central operations of our own, performance-oriented theory.we begin by briefly describing tag's as a formalism for phrase structure in a competence theory, and summarize the points in the theory of tag's that are germaine to our own theory. we then consider generally the position of a grammar within the generation process, introducing our use of tag's through a contrast with how others have used systemic grammars. this takes us to the core results of our paper: using examples from our research with weil-written texts from newspapers, we walk through our tag inspired treatments of raising and wh-movement, and show the correspondence of the tag "adjunction" operation and our "attachment" process.in the final section we discuss extensions to the theory, motivated by the way we use the operation corresponding to tag's adjunction in performance. this suggests that the competence theory of tag's can be profitably projected to structures at the morphological level as well as the present syntactic level.
formal aspects and parsing issues of dependency theory. the paper investigates the problem of providing a formal device for the dependency approach to syntax, and to link it with a parsing model. after reviewing the basic tenets of the paradigm and the few existing mathematical results, we describe a dependency formalism which is able to deal with long-distance dependencies. finally, we present an earley-style parser for the formalism and discuss the (polynomial) complexity results.
babel: a testbed for research in origins of language. we believe that language is a complex adaptive system that emerges from adaptive interactions between language users and continues to evolve and adapt through repeated interactions. our research looks at the mechanisms and processes involved in such emergence and adaptation. to provide a basis for our computer simulations, we have implemented an open-ended, extensible testbed called babel which allows rapid construction of experiments and flexible visualization of results.
re-usable tools for precision machine translation. the logon mt demonstrator assembles independently valuable general-purpose nlp components into a machine translation pipeline that capitalizes on output quality. the demonstrator embodies an interesting combination of hand-built, symbolic resources and stochastic processes.
simple algorithms for complex relation extraction with applications to biomedical ie. a complex relation is any n-ary relation in which some of the arguments may be be unspecified. we present here a simple two-stage method for extracting complex relations between named entities in text. the first stage creates a graph from pairs of entities that are likely to be related, and the second stage scores maximal cliques in that graph as potential complex relation instances. we evaluate the new method against a standard baseline for extracting genomic variation relations from biomedical text.
on2l - a framework for incremental ontology learning in spoken dialog systems. an open-domain spoken dialog system has to deal with the challenge of lacking lexical as well as conceptual knowledge. as the real world is constantly changing, it is not possible to store all necessary knowledge beforehand. therefore, this knowledge has to be acquired during the run time of the system, with the help of the out-of-vocabulary information of a speech recognizer. as every word can have various meanings depending on the context in which it is uttered, additional context information is taken into account, when searching for the meaning of such a word. in this paper, i will present the incremental ontology learning framework on2l. the defined tasks for the framework are: the hypernym extraction from internet texts for unknown terms delivered by the speech recognizer; the mapping of those and their hypernyms into ontological concepts and instances; and the following integration of them into the system's ontology.
confirmation in multimodal systems. systems that attempt to understand natural human input make mistakes, even humans. however, humans avoid misunderstandings by confirming doubtful input. multimodal systems---those that combine simultaneous input from more than one modality, for example speech and gesture-have historically been designed so that they either request confirmation of speech, their primary modality, or not at all. instead, we experimented with delaying confirmation until after the speech and gesture were combined into a complete multimodal command. in controlled experiments, subjects achieved more commands per minute at a lower error rate when the system delayed confirmation, than compared to when subjects confirmed only speech. in addition, this style of late confirmation meets the user's expectation that confirmed commands should be executable.
alternative approaches for generating bodies of grammar rules. we compare two approaches for describing and generating bodies of rules used for natural language parsing. in today's parsers rule bodies do not exist a priori but are generated on the fly, usually with methods based on n-grams, which are one particular way of inducing probabilistic regular languages. we compare two approaches for inducing such languages. one is based on n-grams, the other on minimization of the kullback-leibler divergence. the inferred regular languages are used for generating bodies of rules inside a parsing procedure. we compare the two approaches along two dimensions: the quality of the probabilistic regular language they produce, and the performance of the parser they were used to build. the second approach outperforms the first one along both dimensions.
probabilistic disambiguation models for wide-coverage hpsg parsing. this paper reports the development of log-linear models for the disambiguation in wide-coverage hpsg parsing. the estimation of log-linear models requires high computational cost, especially with wide-coverage grammars. using techniques to reduce the estimation cost, we trained the models using 20 sections of penn tree-bank. a series of experiments empirically evaluated the estimation techniques, and also examined the performance of the disambiguation models on the parsing of real-world sentences.
hybrid methods for pos guessing of chinese unknown words. this paper describes a hybrid model that combines a rule-based model with two statistical models for the task of pos guessing of chinese unknown words. the rule-based model is sensitive to the type, length, and internal structure of unknown words, and the two statistical models utilize contextual information and the likelihood for a character to appear in a particular position of words of a particular length and pos category. by combining models that use different sources of information, the hybrid model achieves a precision of 89%, a significant improvement over the best result reported in previous studies, which was 69%.
paraphrasing using given and new information in a question-answer system. the design and implementation of a paraphrase component for a natural language question-answer system (co-op) is presented. a major point made is the role of given and new information in formulating a paraphrase that differs in a meaningful way from the user's question. a description is also given of the transformational grammar used by the paraphraser to generate questions.
an equivalent pseudoword solution to chinese word sense disambiguation. this paper presents a new approach based on equivalent pseudowords (eps) to tackle word sense disambiguation (wsd) in chinese language. eps are particular artificial ambiguous words, which can be used to realize unsupervised wsd. a bayesian classifier is implemented to test the efficacy of the ep solution on senseval-3 chinese test set. the performance is better than state-of-the-art results with an average f-measure of 0.80. the experiment verifies the value of ep for unsupervised wsd.
collocation translation acquisition using monolingual corpora. collocation translation is important for machine translation and many other nlp tasks. unlike previous methods using bilingual parallel corpora, this paper presents a new method for acquiring collocation translations by making use of monolingual corpora and linguistic knowledge. first, dependency triples are extracted from chinese and english corpora with dependency parsers. then, a dependency triple translation model is estimated using the em algorithm based on a dependency correspondence assumption. the generated triple translation model is used to extract collocation translations from two monolingual corpora. experiments show that our approach outperforms the existing monolingual corpus based methods in dependency triple translation and achieves promising results in collocation translation extraction.
using language resources in an intelligent tutoring system for french. this paper presents a project that investigates to what extent computational linguistic methods and tools used at geta for machine translation can be used to implement novel functionalities in intelligent computer assisted language learning. our intelligent tutoring system project is still in its early phases. the learner module is based on an empirical study of french as used by acadian elementary students living in new-brunswick, canada. additionally, we are studying the state of the art of systems using artificial intelligence techniques as well as nlp resources and/or methodologies for teaching language, especially for bilingual and minority groups.
statistical sense disambiguation with relatively small corpora using dictionary definitions. corpus-based sense disambiguation methods, like most other statistical nlp approaches, suffer from the problem of data sparseness. in this paper, we describe an approach which overcomes this problem using dictionary definitions. using the definition-based conceptual co-occurrence data collected from the relatively small brown corpus, our sense disambiguation system achieves an average accuracy comparable to human performance given the same contextual information.
tailoring lexical choice to the user's vocabulary in multimedia explanation generation. in this paper, we discuss the different strategies used in comet (coordinated multimedia explanation testbed) for selecting words with which the user is familiar. when pictures cannot be used to disambiguate a word or phrase, comet has four strategies for avoiding unknown words. we give examples for each of these strategies and show how they are implemented in comet.
a mention-synchronous coreference resolution algorithm based on the bell tree. this paper proposes a new approach for coreference resolution which uses the bell tree to represent the search space and casts the coreference resolution problem as finding the best path from the root of the bell tree to the leaf nodes. a maximum entropy model is used to rank these paths. the coreference performance on the 2002 and 2003 automatic content extraction (ace) data will be reported. we also train a coreference system using the muc6 data and competitive results are obtained.
combining trigram and winnow in thai ocr error correction. for languages that have no explicit word boundary such as thai, chinese and japanese, correcting words in text is harder than in english because of additional ambiguities in locating error words. the traditional method handles this by hypothesizing that every substrings in the input sentence could be error words and trying to correct all of them. in this paper, we propose the idea of reducing the scope of spelling correction by focusing only on dubious areas in the input sentence. boundaries of these dubious areas could be obtained approximately by applying word segmentation algorithm and finding word sequences with low probability. to generate the candidate correction words, we used a modified edit distance which reflects the characteristic of thai ocr errors. finally, a part-of-speech trigram model and winnow algorithm are combined to determine the most probable correction.
an iterative algorithm to build chinese language models. we present an iterative procedure to build a chinese language model (lm). we segment chinese text into words based on a word-based chinese language model. however, the construction of a chinese lm itself requires word boundaries. to get out of the chicken-and-egg problem, we propose an iterative procedure that alternates two operations: segmenting text into words and building an lm. starting with an initial segmented corpus and an lm based upon it, we use a viterbi-liek algorithm to segment another set of data. then, we build an lm based on the second set and use the resulting lm to segment again the first corpus. the alternating procedure provides a self-organized way for the segmenter to detect automatically unseen words and correct segmentation errors. our preliminary experiment shows that the alternating procedure not only improves the accuracy of our segmentation, but discovers unseen words suprisingly well. the resulting word-based lm has a perplexity of 188 for a general chinese corpus.
coordination as a direct process. we propose a treatment of coordination based on the concepts of functor, argument and subcategorization. its formalization comprises two parts which are conceptually independent. on one hand, we have extended the feature structure unification to disjunctive and set values in order to check the compatibility and the satisfiability of subcategorization requirements by structured complements. on the other hand, we have considered the conjunction et (and) as the head of the coordinate structure, so that coordinate structures stem simply from the subcategorization specifications of et and the general schemata of a head saturation. both parts have been encoded within hpsg using the same resource that is the subcategorization and its principle which we have just extended.
the representation of multimodal user interface dialogues using discourse pegs. the three-tiered discourse representation defined in (luperfoy, 1991) is applied to multimodal human-computer interface (hci) dialogues. in the applied system the three tiers are (1) a linguistic analysis (morphological, syntactic, sentential semantic) of input and output communicative events including keyboard-entered command language atoms, nl strings, mouse clicks, output text strings, and output graphical events; (2) a discourse model representation containing one discourse object, called a peg, for each construct (each guise of an individual) under discussion; and (3) the knowledge base (kb) representation of the computer agent's 'belief' system which is used to support its interpretation procedures. i present evidence to justify the added complexity of this three-tiered system over standard two-tiered representations, based on (a) cognitive processes that must be supported for any non-idealized dialogue environment (e.g., the agents can discuss constructs not present in their current belief systems), including information decay, and the need for a distinction between understanding a discourse and believing the information content of a discourse; (b) linguistic phenomena, in particular, context-dependent nps, which can be partially or totally anaphoric; and (c) observed requirements of three implemented hci dialogue systems that have employed this three-tiered discourse representation.
segmented and unsegmented dialogue-act annotation with statistical dialogue models. dialogue systems are one of the most challenging applications of natural language processing. in recent years, some statistical dialogue models have been proposed to cope with the dialogue problem. the evaluation of these models is usually performed by using them as annotation models. many of the works on annotation use information such as the complete sequence of dialogue turns or the correct segmentation of the dialogue. this information is not usually available for dialogue systems. in this work, we propose a statistical model that uses only the information that is usually available and performs the segmentation and annotation at the same time. the results of this model reveal the great influence that the availability of a correct segmentation has in obtaining an accurate annotation of the dialogues.
an architecture for dialogue management, context tracking, and pragmatic adaptation in spoken dialogue systems. this paper details a software architecture for discourse processing in spoken dialogue systems, where the three component tasks of discourse processing are (1) dialogue management, (2) context tracking, and (3) pragmatic adaptation. we define these three component tasks and describe their roles in a complex, near-future scenario in which multiple humans interact with each other and with computers in multiple, simultaneous dialogue exchanges. this paper reports on the software modules that accomplish the three component tasks of discourse processing, and an architecture for the interaction among these modules and with other modules of the spoken dialogue system. a motivation of this work is reusable discourse processing software for integration with non-discourse modules in spoken dialogue systems. we document the use of this architecture and its components in several prototypes, and also discuss its potential application to spoken dialogue systems defined in the near-future scenario.
statistical machine translation by parsing. in an ordinary syntactic parser, the input is a string, and the grammar ranges over strings. this paper explores generalizations of ordinary parsing algorithms that allow the input to consist of string tuples and/or the grammar to range over string tuples. such algorithms can infer the synchronous structures hidden in parallel texts. it turns out that these generalized parsers can do most of the work required to train and apply a syntax-aware statistical machine translation system.
a portable algorithm for mapping bitext correspondence. the first step in most empirical work in multilingual nlp is to construct maps of the correspondence between texts and their translations (bitext maps). the smooth injective map recognizer (simr) algorithm presented here is a generic pattern recognition algorithm that is particularly well-suited to mapping bitext correspondence. simr is faster and significantly more accurate than other algorithms in the literature. the algorithm is robust enough to use on noisy texts, such as those resulting from ocr input, and on translations that are not very literal. simr encapsulates its language-specific heuristics, so that it can be ported to any language pair with a minimal effort.
an iterative implicit feedback approach to personalized search. general information retrieval systems are designed to serve all users without considering individual needs. in this paper, we propose a novel approach to personalized search. it can, in a unified way, exploit and utilize implicit feedback information, such as query logs and immediately viewed documents. moreover, our approach can implement result re-ranking and query expansion simultaneously and collaboratively. based on this approach, we develop a client-side personalized web search agent pair (personalized assistant for information retrieval), which supports both english and chinese. our experiments on trec and htrdp collections clearly show that the new approach is both effective and efficient.
a word-to-word model of translational equivalence. many multilingual nlp applications need to translate words between different languages, but cannot afford the computational expenses of inducing or applying a full translation model. for theses applications, we have designed a fast algorithm for estimating a partial translation model, which accounts for translational equivalence only at the word level. the model's precision/recall trade-off can be directly controlled via one threshold parameter. this feature makes the model more suitable for applications that are not fully statistical. the model's hidden parameters can be easily conditioned on information extrinsic to the model, providing an easy way to integrate pre-existing knowledge such as part-of-speech, dictionaries, word order, etc., our model can link word tokens in parallel texts as well as other translation models in the literature. unlike other translation models, it can automatically produce dictionary-sized translation lexicons, and it can do so with over 99% accuracy.
a compositional semantics for focusing subjuncts. a compositional semantics for focusing subjuncts---words such as only, even, and also---is developed from rooth's theory of association with focus. by adapting the theory so that it can be expressed in terms of a frame-based semantic formalism, a semantics that is more computationally practical is arrived at. this semantics captures pragmatic subtleties by incorporating a two-part representation, and recognizes the contribution of intonation to meaning.
syntax-based semi-supervised named entity tagging. we report an empirical study on the role of syntactic features in building a semi-supervised named entity (ne) tagger. our study addresses two questions: what types of syntactic features are suitable for extracting potential nes to train a classifier in a semi-supervised setting? how good is the resulting ne classifier on testing instances dissimilar from its training data? our study shows that constituency and dependency parsing constraints are both suitable features to extract nes and train the classifier. moreover, the classifier showed significant accuracy improvement when constituency features are combined with new dependency feature. furthermore, the degradation in accuracy on unfamiliar test cases is low, suggesting that the trained classifier generalizes well.
a multi-neuro tagger using variable lenghts of contexts. this paper presents a multi-neuro tagger that uses variable lengths of contexts and weighted inputs (with information gains) for part of speech tagging. computer experiments show that it has a correct rate of over 94% for tagging ambiguous words when a small thai corpus with 22,311 ambiguous words is used for training. this result is better than any of the results obtained using the single-neuro taggers with fixed but different lengths of contexts, which indicates that the multi-neuro tagger can dynamically find a suitable length of contexts in tagging.
generalized multitext grammars. generalized multitext grammar (gmtg) is a synchronous grammar formalism that is weakly equivalent to linear context-free rewriting systems (lcfrs), but retains much of the notational and intuitive simplicity of context-free grammar (cfg). gmtg allows both synchronous and independent rewriting. such flexibility facilitates more perspicuous modeling of parallel text than what is possible with other synchronous formalisms. this paper investigates the generative capacity of gmtg, proves that each component grammar of a gmtg retains its generative power, and proposes a generalization of chomsky normal form, which is necessary for synchronous cky-style parsing.
parsing japanese honorifics in unification-based grammar. this paper presents a unification-based approach to japanese honorifics based on a version of hpsg (head-driven phrase structure grammar). utterance parsing is based on lexical specifications of each lexical item, including honorifics, and a few general psg rules using a parser capable of unifying cyclic feature structures. it is shown that the possible word orders of japanese honorific predicate constituents can be automatically deduced in the proposed framework without independently specifying them. discourse information change rules (dicrs) that allow resolving a class of anaphors in honorific contexts are also formulated.
some chart-based techniques for parsing ill-formed input. we argue for the usefulness of an active chart as the basis of a system that searches for the globally most plausible explanation of failure to syntactically parse a given input. we suggest semantics-free, grammar-independent techniques for parsing inputs displaying simple kinds of ill-formedness and discuss the search issues involved.
statistical decision-tree models for parsing. syntactic natural language parsers have shown themselves to be inadequate for processing highly-ambiguous large-vocabulary text, as is evidenced by their poor performance on domains like the wall street journal, and by the movement away from parsing-based approaches to text-processing in general. in this paper, i describe spatter, a statistical parser based on decision-tree learning techniques which constructs a complete parse for every sentence and achieves accuracy rates far better than any published result. this work is based on the following premises: (1) grammars are too complex and detailed to develop manually for most interesting domains; (2) parsing models must rely heavily on lexical and contextual information to analyze sentences accurately; and (3) existing n-gram modeling techniques are inadequate for parsing models. in experiments comparing spatter with ibm's computer manuals parser, spatter significantly outperforms the grammar-based parser. evaluating spatter against the penn treebank wall street journal corpus using the parseval measures, spatter achieves 86% precision, 86% recall, and 1.3 crossing brackets per sentence for sentences of 40 words or less, and 91% precision, 90% recall, and 0.5 crossing brackets for sentences between 10 and 20 words in length.
efficiency, robustness and accuracy in picky chart parsing. this paper describes picky, a probabilistic agenda-based chart parsing algorithm which uses a technique called probabilistic prediction to predict which grammar rules are likely to lead to an acceptable parse of the input. using a suboptimal search method, picky significantly reduces the number of edges produced by cky-like chart parsing algorithms, while maintaining the robustness of pure bottom-up parsers and the accuracy of existing probabilistic parsers. experiments using picky demonstrate how probabilistic modelling can impact upon the efficiency, robustness and accuracy of a parser.
an lr category-neutral parser with left corner prediction. in this paper we present a new parsing model of linguistic and computational interest. linguistically, the relation between the parser and the theory of grammar adopted (government and binding (gb) theory as presented in chomsky (1981, 1986a, b) is clearly specified. computationally, this model adopts a mixed parsing procedure, by using left corner prediction in a modified lr parser.
is it the right answer? exploiting web redundancy for answer validation. answer validation is an emerging topic in question answering, where open domain systems are often required to rank huge amounts of candidate answers. we present a novel approach to answer validation based on the intuition that the amount of implicit knowledge which connects an answer to a question can be quantitatively estimated by exploiting the redundancy of web information. experiments carried out on the trec-2001 judged-answer collection show that the approach achieves a high level of performance (i.e. 81% success rate). the simplicity and the efficiency of this approach make it suitable to be used as a module in question answering systems.
a multilingual paradigm for automatic verb classification. we demonstrate the benefits of a multilingual approach to automatic lexical semantic verb classification based on statistical analysis of corpora in multiple languages. our research incorporates two interrelated threads. in one, we exploit the similarities in the crosslinguistic classification of verbs, to extend work on english verb classification to a new language (italian), and to new classes within that language, achieving an accuracy of 86.4% (baseline 33.9%). our second strand of research exploits the differences across languages in the syntactic expression of semantic properties, to show that complementary information about english verbs can be extracted from their translations in a second language (chinese). the use of multilingual features improves classification performance of the english verbs, achieving an accuracy of 83.5% (baseline 33.3%).
reaping the benefits of interactive syntax and semantics. semantic feedback is an important source of information that a parser could use to deal with local ambiguities in syntax. however, it is difficult to devise a systematic communication mechanism for interactive syntax and semantics. in this article, i propose a variant of left-corner parsing to define the points at which syntax and semantics should interact, an account of grammatical relations and thematic roles to define the content of the communication, and a conflict resolution strategy based on independent preferences from syntax and semantics. the resulting interactive model has been implemented in a program called compere and shown to account for a wide variety of psycholinguistic data on structural and lexical ambiguities.
annotation schemes and their influence on parsing results. most of the work on treebank-based statistical parsing exclusively uses the wall-street-journal part of the penn treebank for evaluation purposes. due to the presence of this quasi-standard, the question of to which degree parsing results depend on the properties of treebanks was often ignored. in this paper, we use two similar german treebanks, t&uuml;ba-d/z and negra, and investigate the role that different annotation decisions play for parsing. for these purposes, we approximate the two treebanks by gradually taking out or inserting the corresponding annotation components and test the performance of a standard pcfg parser on all treebank versions. our results give an indication of which structures are favorable for parsing and which ones are not.
error profiling: toward a model of english acquisition for deaf learners. in this paper we discuss our approach toward establishing a model of the acquisition of english grammatical structures by users of our english language tutoring system, which has been designed for deaf users of american sign language. we explore the correlation between a corpus of error-tagged texts and their holistic proficiency scores assigned by experts in order to draw initial conclusions about what language errors typically occur at different levels of proficiency in this population. since errors made at lower levels (and not at higher levels) presumably represent constructions acquired before those on which errors are found only at higher levels, this should provide insight into the order of acquisition of english grammatical forms.
language independent extractive summarization. textrank is a system for unsupervised extractive summarization that relies on an innovative application of iterative graph-based ranking algorithms to graphs encoding the cohesive structure of texts. an important characteristic of the system is that it does not rely on any language-specific knowledge resources or any manually constructed training data, and thus it is highly portable to new languages or domains.
punjabi machine transliteration. machine transliteration is to transcribe a word written in a script with approximate phonetic equivalence in another language. it is useful for machine translation, cross-lingual information retrieval, multilingual text and speech processing. punjabi machine transliteration (pmt) is a special case of machine transliteration and is a process of converting a word from shahmukhi (based on arabic script) to gurmukhi (derivation of landa, shardha and takri, old scripts of indian subcontinent), two scripts of punjabi, irrespective of the type of word.the punjabi machine transliteration system uses transliteration rules (character mappings and dependency rules) for transliteration of shahmukhi words into gurmukhi. the pmt system can transliterate every word written in shahmukhi.
senselearner: word sense disambiguation for all words in unrestricted text. this paper describes senselearner --- a minimally supervised word sense disambiguation system that attempts to disambiguate all content words in a text using wordnet senses. we evaluate the accuracy of senselearner on several standard sense-annotated data sets, and show that it compares favorably with the best results reported during the recent senseval evaluations.
minimum cut model for spoken lecture segmentation. we consider the task of unsupervised lecture segmentation. we formalize segmentation as a graph-partitioning task that optimizes the normalized cut criterion. our approach moves beyond localized comparisons and takes into account long-range cohesion dependencies. our results demonstrate that global analysis improves the segmentation accuracy and is robust in the presence of speech recognition errors.
a method for word sense disambiguation of unrestricted text. selecting the most appropriate sense for an ambiguous word in a sentence is a central problem in natural language processing. in this paper, we present a method that attempts to disambiguate all the nouns, verbs, adverbs and adjectives in a text, using the senses provided in wordnet. the senses are ranked using two sources of information: (1) the internet for gathering statistics for word-word cooccurrences and (2) wordnet for measuring the semantic density for a pair of words. we report an average accuracy of 80% for the first ranked sense, and 91% for the first two ranked senses. extensions of this method for larger windows of more than two words are considered.
universality and individuality: the interaction of noun phrase determiners in corpular clauses. this paper presents an implemented theory for quantifying noun phrases in clauses containing copular verbs (e.g., 'be' and 'become'). proceeding from recent theoretical work by jackendoff [1983], this computational theory recognizes the dependence of the quantification decision on the definiteness, indefiniteness, or classness of both the subject and object of copular verbs in english. jackendoffs intuition about the quantificational interdependence of subject and object has been imported from his broader cognitive theory and reformulated within a constraint propagation framework. extensions reported here include the addition of more active determiners, the expansion of determiner categories, and the treatment of displaced objects. a further finding is that quantificational constraints may propagate across some clausal boundaries. the algorithm is used by the relatus natural language understanding system during a phase of analysis that posts constraints to produce a 'constraint tree.' this phase comes after creation of syntactic deep structure and before sentential reference in a semantic-network model. incorporation of the quantification algorithm in a larger system that parses sentences and builds semantic models from them makes relatus able to acquire taxonomic and identity information from text.
experiences with an on-line translating dialogue system. an english-japanese bi-directional machine translation system was connected to a keyboard conversation function on a workstation, and tested via a satellite link with users in japan and switzerland. the set-up is described, and some informal observations on the nature of the bilingual dialogues reported.
the order of prenominal adjectives in natural language generation. the order of prenominal adjectival modifiers in english is governed by complex and difficult to describe constraints which straddle the boundary between competence and performance. this paper describes and compares a number of statistical and machine learning techniques for ordering sequences of adjectives in the context of a natural language generation system.
unsupervised learning of word-category guessing rules. words unknown to the lexicon present a substantial problem to part-of-speech tagging. in this paper we present a technique for fully unsupervised statistical acquisition of rules which guess possible parts-of-speech for unknown words. three complementary sets of word-guessing rules are induced from the lexicon and a raw corpus: prefix morphological rules, suffix morphological rules and ending-guessing rules. the learning was performed on the brown corpus data and rule-sets, with a highly competitive performance, were produced and compared with the state-of-the-art.
an attributive logic of set descriptions and set operations. this paper provides a model theoretic semantics to feature terms augmented with set descriptions. we provide constraints to specify hpsg style set descriptions, fixed cardinality set descriptions, set-membership constraints, restricted universal role quantifications, set union, intersection, subset and disjointness. a sound, complete and terminating consistency checking procedure is provided to determine the consistency of any given term in the logic. it is shown that determining consistency of terms is a np-complete problem.
feature lattices for maximum entropy modelling. maximum entropy framework proved to be expressive and powerful for the statistical language modelling, but it suffers from the computational expensiveness of the model building. the iterative scaling algorithm that is used for the parameter estimation is computationally expensive while the feature selection process might require to estimate parameters for many candidate features many times. in this paper we present a novel approach for building maximum entropy models. our approach uses the feature collocation lattice and builds complex candidate features without resorting to iterative scaling.
improving summaries by revising them. this paper describes a program which revises a draft text by aggregating together descriptions of discourse entities, in addition to deleting extraneous information. in contrast to knowledge-rich sentence aggregation approaches explored in the past, this approach exploits statistical parsing and robust coreference detection. in an evaluation involving revision of topic-related summaries using informativeness measures from the tipster summac evaluation, the results show gains in informativeness without compromising readability.
a knowledge-free method for capitalized word disambiguation. in this paper we present an approach to the disambiguation of capitalized words when they are used in the positions where capitalization is expected, such as the first word in a sentence or after a period, quotes, etc.. such words can act as proper names or can be just capitalized variants of common words. the main feature of our approach is that it uses a minimum of prebuilt resources and tires to dynamically infer the disambiguation clues from the entire document. the approach was thoroughly tested and achieved about 98.5% accuracy on unseen texts from the new york times 1996 corpus.
dictionaries of the mind. how lexical information should be formulated, and how it is organized in computer memory for rapid retrieval, are central questions for computational linguists who want to create systems for language understanding. how lexical knowledge is acquired, and how it is organized in human memory for rapid retrieval during language use, are also central questions for cognitive psychologists. some examples of psycholinguistic research on the lexical component of language are reviewed with special attention to their implications for the computational problem.
machine learning of temporal relations. this paper investigates a machine learning approach for temporally ordering and anchoring events in natural language texts. to address data sparseness, we used temporal reasoning as an over-sampling method to dramatically expand the amount of training data, resulting in predictive accuracy on link labeling as high as 93% using a maximum entropy classifier on human annotated data. this method compared favorably against a series of increasingly sophisticated baselines involving expansion of rules derived from human intuitions.
the lexical component of natural language processing. of the various problems that natural language processing has revealed, polysemy is probably the most frustrating. people deal with polysemy so easily that potential abiguities are overlooked, whereas computers must work hard to do far less well. a linguistic approach generally involves a parser, a lexicon, and some ad hoc rules for using linguistic context to identify the context-appropriate sense. a statistical approach generally involves the use of word co-occurrence statistics to create a semantic hyperspace where each word, regardless of its polysemy, is represented as a single vector. each approach has strengths and limitations; some combination is often proposed. various possibilities will be discussed in terms of their psychological plausibility. computational linguistics is generally considered to be the branch of engineering that uses computers to do useful things with linguistic signals, but it can also be viewed as an extended test of computational theories of human cognition; it is this latter perspective that psychologists find most interesting. language provides a critical test for the hypothesis that physical symbol systems are adequate to perform all human cognitive functions. as yet, no adequate system for natural language processing has approached human levels of performance.
hidden understanding models of natural language. we describe and evaluate hidden understanding models, a statistical learning approach to natural language understanding. given a string of words, hidden understanding models determine the most likely meaning for the string. we discuss 1) the problem of representing meaning in this framework, 2) the structure of the statistical model, 3) the process of training the model, and 4) the process of understanding using the model. finally, we give experimental results, including results on an arpa evaluation.
a fully statistical approach to natural language interfaces. we present a natural language interface system which is based entirely on trained statistical models. the system consists of three stages of processing: parsing, semantic interpretation, and discourse. each of these stages is modeled as a statistical process. the models are fully integrated, resulting in an end-to-end system that maps input utterances into meaning representation frames.
multi-field information extraction and cross-document fusion. in this paper, we examine the task of extracting a set of biographic facts about target individuals from a collection of web pages. we automatically annotate training text with positive and negative examples of fact extractions and train rote, na&iuml;ve bayes, and conditional random field extraction models for fact extraction from individual web pages. we then propose and evaluate methods for fusing the extracted information across documents to return a consensus answer. a novel cross-field bootstrapping method leverages data interdependencies to yield improved performance.
the role of centering theory's rough-shift in the teaching and evaluation of writing skills. existing software systems for automated essay scoring can provide nlp researchers with opportunities to test certain theoretical hypotheses, including some derived from centering theory. in this study we employ ets's e-rater essay scoring system to examine whether local discourse coherence, as defined by a measure of rough-shift transitions, might be a significant contributor to the evaluation of essays. our positive results indicate that rough-shifts do indeed capture a source of incoherence, one that has not been closely examined in the centering literature. these results not only justify rough-shifts as a valid transition type, but they also support the original formulation of centering as a measure of discourse continuity even in pronominal-free text.
automatic acquisition of a large subcategorization dictionary from corpora. this paper presents a new method for producing a dictionary of subcategorization frames from unlabelled text corpora. it is shown that statistical filtering of the results of a finite state parser running on the output of a stochastic tagger produces high quality results, despite the error rates of the tagger and the parser. further, it is argued that this method can be used to learn all subcategorization frames, whereas previous methods are not extensible to a general solution to the problem.
distributing representation for robust interpretation of dialogue utterances. a syntax tree or standard semantic representation can be represented as a set of indexed constraints. this paper describes how this idea can be used in task oriented dialogue systems to provide interpretation rules which incorporate structural and contextual constraints where available, and degrade gracefully on ungrammatical input.
chinese work segmentation without using lexicon and hand-crafted training data. chinese word segmentation is the first step in any chinese nlp system. this paper presents a new algorithm for segmenting chinese texts without making use of any lexicon and hand-crafted linguistic resource. the statistical data required by the algorithm, that is, mutual information and the difference of t-score between characters, is derived automatically from raw chinese corpora. the preliminary experiment shows that the segmentation accuracy of our algorithm is acceptable. we hope the gaining of this approach will be beneficial to improving the performance (especially in ability to cope with unknown words and ability to adapt to various domains) of the existing segmenters, though the algorithm itself can also be utilized as a stand-alone segmenter in some nlp applications.
mima search: a structuring knowledge system towards innovation for engineering education. the main aim of the mima (mining information for management and acquisition) search system is to achieve 'structuring knowledge' to accelerate knowledge exploitation in the domains of science and technology. this system integrates natural language processing including ontology development, information retrieval, visualization, and database technology. the 'structuring knowledge' that we define indicates 1) knowledge storage, 2) (hierarchical) classification of knowledge, 3) analysis of knowledge, 4) visualization of knowledge. we aim at integrating different types of databases (papers and patents, technologies and innovations) and knowledge domains, and simultaneously retrieving different types of knowledge. applications for the several targets such as syllabus structuring will also be mentioned.
parsing the lob corpus. this paper presents a rapid and robust parsing system currently used to learn from large bodies of unedited text. the system contains a multivalued part-of-speech disambiguator and a novel parser employing bottom-up recognition to find the constituent phrases of larger structures that might be too difficult to analyze. the results of applying the disambiguator and parser to large sections of the lancaster/oslo-bergen corpus are presented.
simultaneous interpretation utilizing example-based incremental transfer. this paper describes a practical method of automatic simultaneous interpretation utilizing an example-based incremental transfer mechanism. we primarily show how incremental translation is achieved in the context of an example-based framework. we then examine the type of translation examples required for a simultaneous interpretation to create naturally communicative dialogs. finally, we propose a scheme for automatic simultaneous interpretation exploiting this example-based incremental translation mechanism. preliminary experimentation analyzing the performance of our example-based incremental translation mechanism leads us to believe that the proposed scheme can be utilized to achieve a practical simultaneous interpretation system.
acquiring a lexicon from unsegmented speech. we present work-in-progress on the machine acquisition of a lexicon from sentences that are each an unsegmented phone sequence paired with a primitive representation of meaning. a simple exploratory algorithm is described, along with the direction of current work and a discussion of the relevance of the problem for child language acquisition and computer speech recognition.
integrated control of chart items for error repair. this paper describes a system that performs hierarchical error repair for ill-formed sentences, with heterarchical control of chart items produced at the lexical, syntactic, and semantic levels. the system uses an augmented context-free grammar and employs a bidirectional chart parsing algorithm. the system is composed of four subsystems: for lexical, syntactic, surface case, and semantic processing. the subsystems are controlled by an integrated-agenda system. the system employs a parser for well-formed sentences and a second parser for repairing single error sentences. the system ranks possible repairs by penalty scores which are based on both grammar-independent factors (e.g. the significance of the repaired constituent in a local tree) and grammar-independent factors (e.g. error types). this paper focuses on the heterarchical processing of integrated-agenda items (i.e. chart items) at three levels, in the context of single error recovery.
linguistic structure as composition and perturbation. this paper discusses the problem of learning language from unprocessed text and speech signals, concentrating on the problem of learning a lexicon. in particular, it argues for a representation of language in which linguistic parameters like words are built by perturbing a composition of existing parameters. the power of the representation is demonstrated by several examples in text segmentation and compression, acquisition of a lexicon from raw speech, and the acquisition of mappings between text and artificial representations of meaning.
magic for filter optimization in dynamic bottom-up processing. off-line compilation of logic grammars using magic allows an incorporation of filtering into the logic underlying the grammar. the explicit definite clause characterization of filtering resulting from magic compilation allows processor independent and logically clean optimizations of dynamic bottom-up processing with respect to goal-directedness. two filter optimizations based on the program transformation technique of unfolding are discussed which are of practical and theoretical interest.
towards a unified approach to memory- and statistical-based machine translation. we present a set of algorithms that enable us to translate natural language sentences by exploiting both a translation memory and a statistical-based translation model. our results show that an automatically derived translation memory can be used within a statistical framework to often find translations of higher probability than those found using solely a statistical model. the translations produced using both the translation memory and the statistical model are significantly better than translations produced by two commercial systems: our hybrid system translated perfectly 58% of the 505 sentences in a test collection, while the commercial systems translated perfectly only 40-42% of them.
integrating pattern-based and distributional similarity methods for lexical entailment acquisition. this paper addresses the problem of acquiring lexical semantic relationships, applied to the lexical entailment relation. our main contribution is a novel conceptual integration between the two distinct acquisition paradigms for lexical relations - the pattern-based and the distributional similarity approaches. the integrated method exploits mutual complementary information of the two approaches to obtain candidate relations and informative characterizing features. then, a small size training set is used to construct a more accurate supervised classifier, showing significant increase in both recall and precision over the original approaches.
the rhetorical parsing of natural language texts. we derive the rhetorical structures of texts by means of two new, surface-form-based algorithms: one that identifies discourse usages of cue phrases and breaks sentences into clauses, and one that produces valid rhetorical structure trees for unrestricted natural languages texts. the algorithms use information that was derived from a corpus analysis of cue phrases.
robust pronoun resolution with limited knowledge. most traditional approaches to anaphora resolution rely heavily on linguistic and domain knowledge. one of the disadvantages of developing a knowledge-based system, however, is that it is a very labour-intensive and time-consuming task. this paper presents a robust, knowledge-poor approach to resolving pronouns in technical manuals, which operates on texts pre-processed by a part-of-speech tagger. input is checked against agreement and for a number of antecedent indicators. candidates are assigned scores by each indicator and the candidate with the highest score is returned as the antecedent. evaluation reports a success rate of 89.7% which is better than the success rates of the approaches selected for comparison and tested on the same data. in addition, preliminary experiments show that the approach can be successfully adapted for other languages with minimum modifications.
a decision-based approach to rhetorical parsing. we present a shift-reduce rhetorical parsing algorithm that learns to construct rhetorical structures of texts from a corpus of discourse-parse action sequences. the algorithm exploits robust lexical, syntactic, and semantic knowledge sources.
an unsupervised approach to recognizing discourse relations. we present an unsupervised approach to recognizing discourse relations of contrast, explanation-evidence, condition and elaboration that hold between arbitrary spans of texts. we show that discourse relation classifiers trained on examples that are automatically extracted from massive amounts of text can be used to distinguish between some of these relations with accuracies as high as 93%, even when the relations are not explicitly marked by cue phrases.
elaboration in object descriptions through examples. examples are often used along with textual descriptions to help convey particular ideas - especially in instructional or explanatory contexts. these accompanying examples reflect information in the surrounding text, and in turn, also influence the text. sometimes, examples replace possible (textual) elaborations in the description. it is thus clear that if object descriptions are to be generated, the system must incorporate strategies to handle examples. in this work, we shall investigate some of these issues in the generation of object descriptions.
a uniform treatment of pragmatic inferences in simple and complex utterances and sequences of utterances. drawing appropriate defeasible inferences has been proven to be one of the most pervasive puzzles of natural language processing and a recurrent problem in pragmatics. this paper provides a theoretical framework, called stratified logic, that can accommodate defeasible pragmatic inferences. the framework yields an algorithm that computes the conversational, conventional, scalar, clausal, and normal state implicatures; and the presuppositions that are associated with utterances. the algorithm applies equally to simple and complex utterances and sequences of utterances.
packing of feature structures for efficient unification of disjunctive feature structures. this paper proposes a method for packing feature structures, which automatically collapses equivalent parts of lexical/phrasal feature structures of hpsg into a single <i>packed feature structure</i>. this method avoids redundant repetition of unification of those parts. preliminary experiments show that this method can significantly improve a unification speed in parsing.
bottom-up parsing extending context-freeness in a process grammar processor. a new approach to bottom-up parsing that extends augmented context-free grammar to a process grammar is formally presented. a processor grammar (pg) defines a set of rules suited for bottom-up parsing and conceived as processes that are applied by a pg processor. the matching phase is a crucial step for process application, and a parsing structure for efficient matching is also presented. the pg processor is composed of a process scheduler that allows immediate constituent analysis of structures, and behaves in a non-deterministic fashion. on the other side, the pg offers means for implementing specific parsing strategies improving the lack of determinism innate in the processor.
semantic retrieval for the accurate identification of relational concepts in massive textbases. this paper introduces a novel framework for the accurate retrieval of relational concepts from huge texts. prior to retrieval, all sentences are annotated with predicate argument structures and ontological identifiers by applying a deep parser and a term recognizer. during the run time, user requests are converted into queries of region algebra on these annotations. structural matching with pre-computed semantic annotations establishes the accurate and efficient retrieval of relational concepts. this framework was applied to a text retrieval system for medline. experiments on the retrieval of biomedical correlations revealed that the cost is sufficiently small for real-time applications and that the retrieval precision is significantly improved.
a flexible pos tagger using an automatically acquired language model. we present an algorithm that automatically learns context constraints using statistical decision trees. we then use the acquired constraints in a flexible pos tagger. the tagger is able to use information of any degree: n-grams, automatically learned context constraints, linguistically motivated manually written constraints, etc. the sources and kinds of constraints are unrestricted, and the language model can be easily extended, improving the results. the tagger has been tested and evaluated on the wsj corpus.
the structure and performance of an open-domain question answering system. this paper presents the architecture, operation and results obtained with the lasso question answering system developed in the natural language processing laboratory at smu. to find answers, the system relies on a combination of syntactic and semantic techniques. the search for the answer is based on a novel form of indexing called paragraph indexing. a score of 55.5% for short answers and 64.5% for long answers was achieved at the trec-8 competition.
compact representations by finite-state transducers. finite-state transducers give efficient representations of many natural language phenomena. they allow to account for complex lexicon restrictions encountered, without involving the use of a large set of complex rules difficult to analyze. we here show that these representations can be made very compact, indicate how to perform the corresponding minimization, and point out interesting linguistic side-effects of this operation.
dynamic compilation of weighted context-free grammars. weighted context-free grammars are a convenient formalism for representing grammatical constructions and their likelihoods in a variety of language-processing applications. in particular, speech understanding applications require appropriate grammars both to constrain speech recognition and to help extract the meaning of utterances. in many of those applications, the actual languages described are regular, but context-free representations are much more concise and easier to create. we describe an efficient algorithm for compiling into weighted finite automata an interesting class of weighted context-free grammars that represent regular languages. the resulting automata can then be combined with other speech recognition components. our method allows the recognizer to dynamically activate or deactivate grammar rules and substitute a new regular language for some terminal symbols, depending on previously recognized inputs, all without recompilation. we also report experimental results showing the practicality of the approach.
an efficient compiler for weighted rewrite rules. context-dependent rewrite rules are used in many areas of natural language and speech processing. work in computational phonology has demonstrated that, given certain conditions, such rewrite rules can be represented as finite-state transducers (fsts). we describe a new algorithm for compiling rewrite rules into fsts. we show the algorithm to be simpler and more efficient than existing algorithms. further, many of our applications demand the ability to compile weighted rules into weighted fsts, transducers generalized by providing transitions with weights. we have extended the algorithm to allow for this.
applying explanation-based learning to control and speeding-up natural language generation. this paper presents a method for the automatic extraction of subgrammars to control and speeding-up natural language generation nlg. the method is based on explanation-based learning ebl. the main advantage for the proposed new method for nlg is that the complexity of the grammatical decision making process during nlg can be vastly reduced, because the ebl method supports the adaption of a nlg system to a particular use of a language.
performance issues and error analysis in an open-domain question answering system. this paper presents an in-depth analysis of a state-of-the-art question answering system. several scenarios are examined: (1) the performance of each module in a serial baseline system, (2) the impact of feedbacks and the insertion of a logic prover, and (3) the impact of various lexical resources. the main conclusion is that the overall performance depends on the depth of natural language processing resources and the tools used for answer finding.
examining the role of linguistic knowledge sources in the automatic identification and classification of reviews. this paper examines two problems in document-level sentiment analysis: (1) determining whether a given document is a review or not, and (2) classifying the polarity of a review as positive or negative. we first demonstrate that review identification can be performed with high accuracy using only unigrams as features. we then examine the role of four types of simple linguistic knowledge sources in a polarity classification system.
logic form transformation of wordnet and its applicability to question answering. wordnet is a rich source of world knowledge from which formal axioms can be derived. in this paper we present a method for transforming the wordnet glosses into logic forms and further into axioms. the transformation of wordnet glosses into logic forms is useful for theorem proving and other applications. the paper demonstrates the utility of the wordnet axioms in a question answering system to rank and extract answers.
machine learning for coreference resolution: from local classification to global ranking. in this paper, we view coreference resolution as a problem of ranking candidate partitions generated by different coreference systems. we propose a set of partition-based features to learn a ranking model for distinguishing good and bad partitions. our approach compares favorably to two state-of-the-art coreference systems when evaluated on three standard coreference data sets.
finding ideographic representations of japanese names written in latin script via language identification and corpus validation. multilingual applications frequently involve dealing with proper names, but names are often missing in bilingual lexicons. this problem is exacerbated for applications involving translation between latin-scripted languages and asian languages such as chinese, japanese and korean (cjk) where simple string copying is not a solution. we present a novel approach for generating the ideographic representations of a cjk name written in a latin script. the proposed approach involves first identifying the origin of the name, and then back-transliterating the name to all possible chinese characters using language-specific mappings. to reduce the massive number of possibilities for computation, we apply a three-tier filtering process by filtering first through a set of attested bigrams, then through a set of attested terms, and lastly through the www for a final validation. we illustrate the approach with english-to-japanese back-transliteration. against test sets of japanese given names and surnames, we have achieved average precisions of 73% and 90%, respectively.
multilingual document clustering: an heuristic approach based on cognate named entities. this paper presents an approach for multilingual document clustering in comparable corpora. the algorithm is of heuristic nature and it uses as unique evidence for clustering the identification of cognate named entities between both sides of the comparable corpora. one of the main advantages of this approach is that it does not depend on bilingual or multilingual resources. however, it depends on the possibility of identifying cognate named entities between the languages used in the corpus. an additional advantage of the approach is that it does not need any information about the right number of clusters; the algorithm calculates it. we have tested this approach with a comparable corpus of news written in english and spanish. in addition, we have compared the results with a system which translates selected document features. the obtained results are encouraging.
a hierarchical bayesian language model based on pitman-yor processes. we propose a new hierarchical bayesian n-gram model of natural languages. our model makes use of a generalization of the commonly used dirichlet distributions called pitman-yor processes which produce power-law distributions more closely resembling those in natural languages. we show that an approximation to the hierarchical pitman-yor language model recovers the exact formulation of interpolated kneser-ney, one of the best smoothing methods for n-gram language models. experiments verify that our model gives cross entropy results superior to interpolated kneser-ney and comparable to modified kneser-ney.
is it correct? - towards web-based evaluation of automatic natural language phrase generation. this paper describes a novel approach for the automatic generation and evaluation of a trivial dialogue phrases database. a trivial dialogue phrase is defined as an expression used by a chatbot program as the answer of a user input. a transfer-like genetic algorithm (ga) method is used to generating the trivial dialogue phrases for the creation of a natural language generation (nlg) knowledge base. the automatic evaluation of a generated phrase is performed by producing n-grams and retrieving their frequencies from the world wide web (www). preliminary experiments show very positive results.
integrating multiple knowledge sources to disambiguate word sense: an exemplar-based approach. in this paper, we present a new approach for word sense disambiguation (wsd) using an exemplar-based learning algorithm. this approach integrates a diverse set of knowledge sources to disambiguate word sense, including part of speech of neighboring words, morphological form, the unordered set of surrounding words, local collocations, and verb-object syntactic relation. we tested our wsd program, named lexas, on both a common data set used in previous work, as well as on a large sense-tagged corpus that we separately constructed. lexas achieves a higher accuracy on the common data set, and performs better than the most frequent heuristic on the highly ambiguous words in the large corpus tagged with the refined senses of wordnet.
investigations on event-based summarization. we investigate independent and relevant event-based extractive mutli-document summarization approaches. in this paper, events are defined as event terms and associated event elements. with independent approach, we identify important contents by frequency of events. with relevant approach, we identify important contents by pagerank algorithm on the event map constructed from documents. experimental results are encouraging.
learning to recognize tables in free text. many real-world texts contain tables. in order to process these texts correctly and extract the information contained within the tables, it is important to identify the presence and structure of tables. in this paper, we present a new approach that learns to recognize tables in free text, including the boundary, rows and columns of tables. when tested on wall street journal news documents, our learning approach outperforms a deterministic table recognition algorithm that identifies table recognition algorithm that identifies tables based on a fixed set of conditions. our learning approach is also more flexible and easily adaptable to texts in different domains with different table characteristics.
improving ibm word alignment model 1. we investigate a number of simple methods for improving the word-alignment accuracy of ibm model 1. we demonstrate reduction in alignment error rate of approximately 30% resulting from (1) giving extra weight to the probability of alignment to the null word, (2) smoothing probability estimates for rare words, and (3) using a simple heuristic estimation method to initialize, or replace, em training of model parameters.
exploiting parallel texts for word sense disambiguation: an empirical study. a central problem of word sense disambiguation (wsd) is the lack of manually sense-tagged data required for supervised learning. in this paper, we evaluate an approach to automatically acquire sense-tagged training data from english-chinese parallel corpora, which are then used for disambiguating the nouns in the senseval-2 english lexical sample task. our investigation reveals that this method of acquiring sense-tagged data is promising. on a subset of the most difficult senseval-2 nouns, the accuracy difference between the two approaches is only 14.0%, and the difference could narrow further to 6.5% if we disregard the advantage that manually sense-tagged data have in their sense coverage. our analysis also highlights the importance of the issue of domain dependence in evaluating wsd programs.
unification-based semantic interpretation. we show how unification can be used to specify the semantic interpretation of natural-language expressions, including problematical constructions involving long-distance dependencies. we also sketch a theoretical foundation for unification-based semantic interpretation, and compare the unification-based approach with more conventional techniques based on the lambda calculus.
rule writing or annotation: cost-efficient resource usage for base noun phrase chunking. this paper presents a comprehensive empirical comparison between two approaches for developing a base noun phrase chunker: human rule writing and active learning using interactive real-time human annotation. several novel variations on active learning are investigated, and underlying cost models for cross-modal machine learning comparison are presented and explored. results show that it is more efficient and more successful by several measures to train a system using active learning annotation rather than hand-crafted rule writing at a comparable level of human labor investment.
semantic parsing with structured svm ensemble classification models. we present a learning framework for structured support vector models in which boosting and bagging methods are used to construct ensemble models. we also propose a selection method which is based on a switching model among a set of outputs of individual classifiers when dealing with natural language parsing problems. the switching model uses subtrees mined from the corpus and a boosting-based algorithm to select the most appropriate output. the application of the proposed framework on the domain of semantic parsing shows advantages in comparison with the original large margin methods.
planning text for advisory dialogues. explanation is an interactive process requiring a dialogue between advice-giver and advice-seeker. in this paper, we argue that in order to participate in a dialogue with its users, a generation system must be capable of reasoning about its own utterances and therefore must maintain a rich representation of the responses it produces. we present a text planner that constructs a detailed text plan, containing the intentional, attentional, and rhetorical structures of the text it generates.
word alignment and cross-lingual resource acquisition. annotated corpora are valuable resources for developing natural language processing applications. this work focuses on acquiring annotated data for multilingual processing applications. we present an annotation environment that supports a web-based user-interface for acquiring word alignments between english and chinese as well as a visualization tool for researchers to explore the annotated data.
improved discriminative bilingual word alignment. for many years, statistical machine translation relied on generative models to provide bilingual word alignments. in 2005, several independent efforts showed that discriminative models could be used to enhance or replace the standard generative approach. building on this work, we demonstrate substantial improvement in word-alignment accuracy, partly though improved training methods, but predominantly through selection of more and better features. our best model produces the lowest alignment error rate yet reported on canadian hansards bilingual data.
a uniform approach to underspecification and parallelism. we propose a unified framework in which to treat semantic underspecification and parallelism phenomena in discourse. the framework employs a constraint language that can express equality and subtree relations between finite trees. in addition, our constraint language can express the equality up-to relation over trees which captures parallelism between them. the constraints are solved by context unification. we demonstrate the use of our framework at the examples of quantifier scope, ellipsis, and their interaction.
quantifier scoping in the sri core language engine. an algorithm for generating the possible quantifier scopings for a sentence, in order of preference, is outlined. the scoping assigned to a quantifier is determined by its interactions with other quantifiers, modals, negation, and certain syntactic-constituent boundaries. when a potential scoping is logically equivalent to another, the less preferred one is discarded.the relative scoping preferences of the individual quantifiers are not embedded in the algorithm, but are specified by a set of rules. many of the rules presented here have appeared in the linguistics literature and have been used in various natural language processing systems. however, the co-ordination of these rules and the resulting coverage represents a significant contribution. because experimental data on human quantifier-scoping preferences are still fragmentary, we chose to design a system in which the set of preference rules could be easily modified and expanded.the algorithm described has been implemented in prolog as part of a larger natural language processing system. extensions of this algorithm are in progress.
bridging the gap between underspecification formalisms: minimal recursion semantics as dominance constraints. minimal recursion semantics (mrs) is the standard formalism used in large-scale hpsg grammars to model underspecified semantics. we present the first provably efficient algorithm to enumerate the readings of mrs structures, by translating them into normal dominance constraints.
representing constraints with automata. in this paper we describe an approach to constraint based syntactic theories in terms of finite tree automata. the solutions to constraints expressed in weak monadic second order (mso) logic are represented by tree automata recognizing the assignments which make the formulas true. we show that this allows an efficient representation of knowledge about the content of constraints which can be used as a practical tool for grammatical theory verification. we achieve this by using the intertranslatability of formulae of mso logic and tree automata and the embedding of mso logic into a constraint logic programming scheme. the usefulness of the approach is discussed with examples from the realm of principles-and-parameters based parsing.
a dp based search algorithm for statistical machine translation. we introduce a novel search algorithm for statistical machine translation based on dynamic programming (dp). during the search process two statistical knowledge sources are combined: a translation model and a bigram language model. this search algorithm expands hypotheses along the positions of the target string while guaranteeing progressive coverage of the words in the source string. we present experimental results on the verbmobil task.
a stochastic language model using dependency and its improvement by word clustering. in this paper, we present a stochastic language model for japanese using dependency. the prediction unit in this model is an attribute of "bunsetsu". this is represented by the product of the head of content words and that of function words. the relation between the attributes of "bunsetsu" is ruled by a context-free grammar. the word sequences are predicted from the attribute using word n-gram model. the spell of unknow word is predicted using character n-gram model. this model is robust in that it can compute the probability of an arbitrary string and is complete in that it models from unknown word to dependency at the same time.
graph transformations in data-driven dependency parsing. transforming syntactic representations in order to improve parsing accuracy has been exploited successfully in statistical parsing systems using constituency-based representations. in this paper, we show that similar transformations can give substantial improvements also in data-driven dependency parsing. experiments on the prague dependency treebank show that systematic transformations of coordinate structures and verb groups result in a 10% error reduction for a deterministic data-driven dependency parser. combining these transformations with previously proposed techniques for recovering non-projective dependencies leads to state-of-the-art accuracy for the given data set.
phoneme-to-text transcription system with an infinite vocabulary. the noisy channel model approach is successfully applied to various natural language processing tasks. currently the main research focus of this approach is adaptation methods, how to capture characteristics of words and expressions in a target domain given example sentences in that domain. as a solution we describe a method enlarging the vocabulary of a language model to an almost infinite size and capturing their context information. especially the new method is suitable for languages in which words are not delimited by whitespace. we applied our method to a phoneme-to-text transcription task in japanese and reduced about 10% of the errors in the results of an existing method.
coreference for nlp applications. this paper presents several techniques for performing automatic coreference annotation and performance results for each of them. to demonstrate that they can be applied to real-world data, we have built a simple question-answering system which uses the techniques. a system using coreference is compared to a baseline system with the result that the addition of the coreference annotation improves performance.
syntactic features and word similarity for supervised metonymy resolution. we present a supervised machine learning algorithm for metonymy resolution, which exploits the similarity between examples of conventional metonymy. we show that syntactic head-modifier relations are a high precision feature for metonymy recognition but suffer from data sparseness. we partially overcome this problem by integrating a thesaurus and introducing simpler grammatical features, thereby preserving precision and increasing recall. our algorithm generalises over two levels of contextual similarity. resulting inferences exceed the complexity of inferences undertaken in word sense disambiguation. we also compare automatic and manual methods for syntactic feature extraction.
a study on convolution kernels for shallow statistic parsing. in this paper we have designed and experimented novel convolution kernels for automatic classification of predicate arguments. their main property is the ability to process structured representations. support vector machines (svms), using a combination of such kernels and the flat feature kernel, classify prop-bank predicate arguments with accuracy higher than the current argument classification state-of-the-art.additionally, experiments on framenet data have shown that svms are appealing for the classification of semantic roles even if the proposed kernels do not produce any improvement.
learning word sense with feature selection and order identification capabilities. this paper presents an unsupervised word sense learning algorithm, which induces senses of target word by grouping its occurrences into a "natural" number of clusters based on the similarity of their contexts. for removing noisy words in feature set, feature selection is conducted by optimizing a cluster validation criterion subject to some constraint in an unsupervised manner. gaussian mixture model and minimum description length criterion are used to estimate cluster structure and cluster number. experimental results show that our algorithm can find important feature subset, estimate model order (cluster number) and achieve better performance than another algorithm which requires cluster number to be provided.
investigating cue selection and placement in tutorial discourse. our goal is to identify the features that predict cue selection and placement in order to devise strategies for automatic text generation. much previous work in this area has relied on ad hoc methods. our coding scheme for the exhaustive analysis of discourse allows a systematic evaluation and refinement of hypotheses concerning cues. we report two results based on this analysis: a comparison of the distribution of since and because in our corpus, and the impact of embeddedness on cue selection.
word sense disambiguation using label propagation based semi-supervised learning. shortage of manually sense-tagged data is an obstacle to supervised word sense disambiguation methods. in this paper we investigate a label propagation based semi-supervised learning algorithm for wsd, which combines labeled and unlabeled data in learning process to fully realize a global consistency assumption: similar examples should have similar labels. our experimental results on benchmark corpora indicate that it consistently outperforms svm when only very few labeled examples are available, and its performance is also better than monolingual bootstrapping, and comparable to bilingual bootstrapping.
semantic information preprocessing for natural language interfaces to databases. an approach is described for supplying selectional restrictions to parsers in natural language interfaces (nlis) to databases by extracting the selectional restrictions from semantic descriptions of those nlis. automating the process of finding selectional restrictions reduces nli development time and may avoid errors introduced by hand-coding selectional restrictions.
a bootstrapping approach to named entity classification using successive learners. this paper presents a new bootstrapping approach to named entity (ne) classification. this approach only requires a few common noun/pronoun seeds that correspond to the concept for the target ne type, e.g. he/she/man/woman for person ne. the entire bootstrapping procedure is implemented as training two successive learners: (i) a decision list is used to learn the parsing-based high precision ne rules; (ii) a hidden markov model is then trained to learn string sequence-based ne patterns. the second learner uses the training corpus automatically tagged by the first learner. the resulting ne system approaches supervised ne performance for some ne types. the system also demonstrates intuitive support for tagging user-defined ne types. the differences of this approach from the co-training-based ne bootstrapping are also discussed.
dealing with distinguishing descriptions in a guided composition system. the goal of this paper is to provide computable account for some definite descriptions. to this end, we define in terms of inclusion the notion of distinguishing description and of distinguishable entities introduced by [dale 89]. these definitions allow us to give conditions of wellformedness for incomplete distinguishing descriptions. we also extend the notion of distinguishing description to take into account cases of synonymy and hyponymy.we describe a real application of a guided composition system where this sort of expressions arise.
weakly supervised learning for cross-document person name disambiguation supported by information extraction. it is fairly common that different people are associated with the same name. in tracking person entities in a large document pool, it is important to determine whether multiple mentions of the same name across documents refer to the same entity or not. previous approach to this problem involves measuring context similarity only based on co-occurring words. this paper presents a new algorithm using information extraction support in addition to co-occurring words. a learning scheme with minimal supervision is developed within the bayesian framework. maximum entropy modeling is then used to represent the probability distribution of context similarities based on heterogeneous features. statistical annealing is applied to derive the final entity coreference chains by globally fitting the pairwise context similarities. benchmarking shows that our new approach significantly outperforms the existing algorithm by 25 percentage points in overall f-measure.
applying co-training to reference resolution. in this paper, we investigate the practical applicability of co-training for the task of building a classifier for reference resolution. we are concerned with the question if co-training can significantly reduce the amount of manual labeling work and still produce a classifier with an acceptable performance.
right association revisited. consideration of when right association works and when it fails lead to a restatement of this parsing principle in terms of the notion of heaviness. a computational investigation of a syntactically annotated corpus provides evidence for this proposal and suggest circumstances when ra is likely to make correct attachment predictions.
aligning a parallel english-chinese corpus statistically with lexical criteria. we describe our experience with automatic alignment of sentences in parallel english-chinese texts. our report concerns three related topics: (1) progress on the hkust english-chinese parallel bilingual corpus; (2) experiments addressing the applicability of gale & church's (1991) length-based statistical method to the task of alignment involving a non-indo-european language; and (3) an improved statistical method that also incorporates domain-specific lexical cues.
automatic detection of syllable boundaries combining the advantages of treebank and bracketed corpora training. an approach to automatic detection of syllable boundaries is presented. we demonstrate the use of several manually constructed grammars trained with a novel algorithm combining the advantages of treebank and bracketed corpora training. we investigate the effect of the training corpus size on the performance of our system. the evaluation shows that a hand-written grammar performs better on finding syllable boundaries than does a treebank grammar.
a psycholinguistically motivated parser for ccg. considering the speed in which humans resolve syntactic ambiguity, and the overwhelming evidence that syntactic ambiguity is resolved through selection of the analysis whose interpretation is the most 'sensible', one comes to the conclusion that interpretation, hence parsing take place incrementally, just about every word. considerations of parsimony in the theory of the syntactic processor lead one to explore the simplest of parsers: one which represents only analyses as defined by the grammar and no other information.toward this aim of a simple, incremental parser i explore the proposal that the competence grammar is a combinatory categorial grammar (ccg). i address the problem of the proliferating analyses that stem from ccg's associativity of derivation. my solution involves maintaining only the maximally incremental analysis and, when necessary, computing the maximally right-branching analysis. i use results from the study of rewrite systems to show that this computation is efficient.
an algorithm for simultaneously bracketing parallel texts by aligning words. we describe a grammarless method for simultaneously bracketing both halves of a parallel text and giving word alignments, assuming only a translation lexicon for the language pair. we introduce inversion-invariant transduction grammars which serve as generative models for parallel bilingual sentences with weak order constraints. focusing on transduction grammars for bracketing, we formulate a normal form, and a stochastic version amenable to a maximum-likelihood bracketing algorithm. several extensions and experiments are discussed.
a flexible stand-off data model with query language for multi-level annotation. we present an implemented xml data model and a new, simplified query language for multi-level annotated corpora. the new query language involves automatic conversion of queries into the underlying, more complicated mmaxql query language. it supports queries for sequential and hierarchical, but also associative (e.g. coreferential) relations. the simplified query language has been designed with non-expert users in mind.
pseudo-projective dependency parsing. in order to realize the full potential of dependency-based syntactic parsing, it is desirable to allow non-projective dependency structures. we show how a data-driven deterministic dependency parser, in itself restricted to projective structures, can be combined with graph transformation techniques to produce non-projective structures. experiments using data from the prague dependency treebank show that the combined system can handle non-projective constructions with a precision sufficient to yield a significant improvement in overall parsing accuracy. this leads to the best reported performance for robust non-projective parsing of czech.
inducing probabilistic syllable classes using multivariate clustering. an approach to automatic detection of syllable structure is presented. we demonstrate a novel application of em-based clustering to multivariate data, exemplified by the induction of 3- and 5-dimensional probabilistic syllable classes. the qualitative evaluation shows that the method yields phonologically meaningful syllable classes. we then propose a novel approach to grapheme-to-phoneme conversion and show that syllable structure represents valuable information for pronunciation systems.
a markov language learning model for finite parameter spaces. this paper shows how to formally characterize language learning in a finite parameter space as a markov structure. important new language learning results follow directly: explicitly calculated sample complexity learning times under different input distribution assumptions (inclding childes database language input) and learning regimes. we also briefly describe a new way to formally model (rapid) diachronic syntax change.
extracting parallel sub-sentential fragments from non-parallel corpora. we present a novel method for extracting parallel sub-sentential fragments from comparable, non-parallel bilingual corpora. by analyzing potentially similar sentence pairs using a signal processing-inspired approach, we detect which segments of the source sentence are translated into segments in the target sentence, and which are not. this method enables us to extract useful machine translation training data even from very non-parallel corpora, which contain no parallel sentence pairs. we evaluate the quality of the extracted data by showing that it improves the performance of a state-of-the-art statistical machine translation system.
difficulty indices for the named entity task in japanese. we propose indices to measure the difficulty of the named entity (ne) task by looking at test corpora, based on expressions inside and outside the nes. these indices are intended to estimate the difficulty of each task without actually using an ne system and to be unbiased towards a specific system. the values of the indices are compared with the systems' performance in japanese documents. we also discuss the difference between ne classes with the indices and show useful clues which will make it easier to recognize nes.
optimizing typed feature structure grammar parsing through non-statistical indexing. this paper introduces an indexing method based on static analysis of grammar rules and type signatures for typed feature structure grammars (tfsgs). the static analysis tries to predict at compile-time which feature paths will cause unification failure during parsing at run-time. to support the static analysis, we introduce a new classification of the instances of variables used in tfsgs, based on what type of structure sharing they create. the indexing actions that can be performed during parsing are also enumerated. non-statistical indexing has the advantage of not requiring training, and, as the evaluation using large-scale hpsgs demonstrates, the improvements are comparable with those of statistical optimizations. such statistical optimizations rely on data collected during training, and their performance does not always compensate for the training costs.
multi-engine machine translation with voted language model. the paper describes a particular approach to multiengine machine translation (memt), where we make use of voted language models to selectively combine translation outputs from multiple off-the-shelf mt systems. experiments are done using large corpora from three distinct domains. the study found that the use of voted language models leads to an improved performance of memt systems.
an estimate of referent of noun phrases in japanese sentences. in machine translation and man-machine dialogue, it is important to clarify referents of noun phrases. we present a method for determining the referents of noun phrases in japanese sentences by using the referential properties, modifiers, and possessors of noun phrases. since the japanese language has no articles, it is difficult to decide whether a noun phrase has an antecedent or not. we had previously estimated the referential properties of noun phrases that correspond to articles by using clue words in the sentences (murata and nagao 1993). by using these referential properties, our system determined the referents of noun phrases in japanese sentences. furthermore we used the modifiers and possessors of noun phrases in determining the referents of noun phrases. as a result, on training sentences we obtained a precision rate of 82% and a recall rate of 85% in the determination of the referents of noun phrases that have antecedents. on test sentences, we obtained a precision rate of 79% and a recall rate of 77%.
supervised ranking in open-domain text summarization. the paper proposes and empirically motivates an integration of supervised learning with unsupervised learning to deal with human biases in summarization. in particular, we explore the use of probabilistic decision tree within the clustering framework to account for the variation as well as regularity in human created summaries. the corpus of human created extracts is created from a newspaper corpus and used as a test set. we build probabilistic decision trees of different flavors and integrate each of them with the clustering framework. experiments with the corpus demonstrate that the mixture of the two paradigms generally gives a significant boost in performance compared to cases where either of the two is considered alone.
leveraging reusability: cost-effective lexical acquisition for large-scale ontology translation. thesauri and ontologies provide important value in facilitating access to digital archives by representing underlying principles of organization. translation of such resources into multiple languages is an important component for providing multilingual access. however, the specificity of vocabulary terms in most ontologies precludes fully-automated machine translation using general-domain lexical resources. in this paper, we present an efficient process for leveraging human translations when constructing domain-specific lexical resources. we evaluate the effectiveness of this process by producing a probabilistic phrase dictionary and translating a thesaurus of 56,000 concepts used to catalogue a large archive of oral histories. our experiments demonstrate a cost-effective technique for accurate machine translation of large ontologies.
error mining for wide-coverage grammar engineering. parsing systems which rely on hand-coded linguistic descriptions can only perform adequately in as far as these descriptions are correct and complete.the paper describes an error mining technique to discover problems in hand-coded linguistic descriptions for parsing such as grammars and lexicons. by analysing parse results for very large unannotated corpora, the technique discovers missing, incorrect or incomplete linguistic descriptions.the technique uses the frequency of n-grams of words for arbitrary values of n. it is shown how a new combination of suffix arrays and perfect hash finite automata allows an efficient implementation.
automatic text summarization based on the global document annotation. the gda (global document annotation) project proposes a tag set which allows machines to automatically infer the underlying semantic/pragmatic structure of documents. its objectives are to promote development and spread of nlp/ai applications to render gda-tagged documents versatile and intelligent contents, which should motivate www (world wide web) users to tag their documents as part of content authoring. this paper discusses automatic text summarization based on gda. its main features are a domain/style-free algorithm and personalization on summarization which reflects readers' interests and preferences. in order to calculate the importance score of a text element, the algorithm uses spreading activation on an intradocument network which connects text elements via thematic, rhetorical, and coreferential relations. the proposed method is flexible enough to dynamically generate summaries of various sizes. a summary browser supporting personalization is reported as well.
head corner parsing for discontinuous constituency. i describe a head-driven parser for a class of grammars that handle discontinuous constituency by a richer notion of string combination than ordinary concatenation. the parser is a generalization of the left-corner parser (matsumoto et al., 1983) and can be used for grammars written in powerful formalisms such as non-concatenative versions of hpsg (pollard, 1984; reape, 1989).
speech dialogue with facial displays: multimodal human-computer conversation. human face-to-face conversation is an ideal model for human-computer dialogue. one of the major features of face-to-face communication is its multiplicity of communication channels that act on multiple modalities. to realize a natural multimodal dialogue, it is necessary to study how humans perceive information and determine the information to which humans are sensitive. a face is an independent communication channel that conveys emotional and conversational signals, encoded as facial expressions. we have developed an experimental system that integrates speech dialogue and facial animation, to investigate the effect of introducing communicative facial expressions as a new modality in human-computer conversation. our experiments have showen that facial expressions are helpful, especially upon first contact with the system. we have also discovered that featuring facial expressions at an early stage improves subsequent interaction.
the intersection of finite state automata and definite clause grammars. bernard lang defines parsing as the calculation of the intersection of a fsa (the input) and a cfg. viewing the input for parsing as a fsa rather than as a string combines well with some approaches in speech understanding systems, in which parsing takes a word lattice as input (rather than a word string). furthermore, certain techniques for robust parsing can be modelled as finite state transducers.in this paper we investigate how we can generalize this approach for unification grammars. in particular we will concentrate on how we might the calculation of the intersection of a fsa and a dcg. it is shown that existing parsing algorithms can be easily extended for fsa inputs. however, we also show that the termination properties change drastically: we show that it is undecidable whether the intersection of a fsa and a dcg is empty (even if the dcg is off-line parsable).furthermore we discuss approaches to cope with the problem.
synchronous morphological analysis of grapheme and phoneme for japanese ocr. we developed a novel language model for japanese based on grapheme-phoneme tuples, which is one order of magnitude smaller than word-based models. we also developed an alignment algorithm of graphemes and phonemes for both ordinary text and ocr output. we show, by experiment, that the combination of the grapheme-phoneme tuple ngram model and the grapheme-phoneme alignment algorithm significantly improve character recognition accuracy if both grapheme and phoneme representations are given.
time period identification of events in text. this study aims at identifying when an event written in text occurs. in particular, we classify a sentence for an event into four time-slots; morning, daytime, evening, and night. to realize our goal, we focus on expressions associated with time-slot (time-associated words). however, listing up all the time-associated words is impractical, because there are numerous time-associated expressions. we therefore use a semi-supervised learning method, the na&iuml;ve bayes classifier backed up with the expectation maximization algorithm, in order to iteratively extract time-associated words while improving the classifier. we also propose to use support vector machines to filter out noisy instances that indicates no specific time period. as a result of experiments, the proposed method achieved 0.864 of accuracy and outperformed other methods.
japanese ocr error correction using character shape similarity and statistical language model. we present a novel ocr error correction method for languages without word delimiters that have a large character set, such as japanese and chinese. it consists of a statistical ocr model, an approximate word matching method using character shape similarity, and a word segmentation algorithm using a statistical language model. by using a statistical ocr model and character shape similarity, the proposed error corrector outperforms the previously published method. when the baseline character recognition accuracy is 90%, it achieves 97.4% character recognition accuracy.
integration of large-scale linguistic resources in a natural language understanding system. knowledge acquisition is a serious bottleneck for natural language understanding systems. for this reason, large-scale linguistic resources have been compiled and made available by organizations such as the linguistic data consortium (comlex) and princeton university (wordnet). systems making use of these resources can greatly accelerate the development process by avoiding the need for the developer to re-create this information.in this paper we describe how we integrated these large scale linguistic resources into our natural language understanding system. client-server architecture was used to make a large volume of lexical information and a large knowledge base available to the system at development and/or run time. we discuss issues of achieving compatibility between these disparate resources.
a part of speech estimation method for japanese unknown words using a statistical model of morphology and context. we present a statistical model of japanese unknown words consisting of a set of length and spelling models classified by the character types that constitute a word. the point is quite simple: different character sets should be treated differently and the changes between character types are very important because japanese script has both ideograms like chinese <i>(kanji)</i> and phonograms like english <i>(katakana)</i>. both word segmentation accuracy and part of speech tagging accuracy are improved by the proposed model. the model can achieve 96.6% tagging accuracy if unknown words are correctly segmented.
an empirical model of acknowledgement for spoken-language systems. we refine and extend prior views of the description, purposes, and contexts-of-use of acknowledgment acts through empirical examination of the use of acknowledgments in task-based conversation. we distinguish three broad classes of acknowledgments (other&larr;ackn, self&larr;other&larr;ackn, and self+ackn) and present a catalogue of 13 patterns within these classes that account for the specific uses of acknowledgment in the corpus.
question answering with lexical chains propagating verb arguments. this paper describes an algorithm for propagating verb arguments along lexical chains consisting of wordnet relations. the algorithm creates verb argument structures using verbnet syntactic patterns. in order to increase the coverage, a larger set of verb senses were automatically associated with the existing patterns from verbnet. the algorithm is used in an in-house question answering system for re-ranking the set of candidate answers. tests on factoid questions from trec 2004 indicate that the algorithm improved the system performance by 2.4%.
a clustered global phrase reordering model for statistical machine translation. in this paper, we present a novel global reordering model that can be incorporated into standard phrase-based statistical machine translation. unlike previous local reordering models that emphasize the reordering of adjacent phrase pairs (till-mann and zhang, 2005), our model explicitly models the reordering of long distances by directly estimating the parameters from the phrase alignments of bilingual training sentences. in principle, the global phrase reordering model is conditioned on the source and target phrases that are currently being translated, and the previously translated source and target phrases. to cope with sparseness, we use n-best phrase alignments and bilingual phrase clustering, and investigate a variety of combinations of conditioning factors. through experiments, we show, that the global reordering model significantly improves the translation accuracy of a standard japanese-english translation task.
classification of modality function and its application to japanese language analysis. this paper proposes an analysis method for japanese modality. in this purpose, meaning of japanese modality is classified into four semantic categories and the role of it is formalized into five modality functions. based on these formalizations, information and constraints to be applied to the modality analysis procedure are specified. then by combining these investigations with case analysis, the analysis method is proposed. this analysis method has been applied to japanese analysis for machine translation.
temporal inferences in medical texts. the objectives of this paper are twofold, whereby the computer program is meant to be a particular implementation of a general natural language [nl] processing system [nlps] which could be used for different domains. the first objective is to provide a theory for processing temporal information contained in a well-structured, technical text. the second objective is to argue for a knowledge-based approach to nlp in which the parsing procedure is driven by extra linguistic knowledge.the resulting computer program incorporates enough domain-specific and general knowledge so that the parsing procedure can be driven by the knowledge base of the program, while at the same time employing a descriptively adequate theory of syntactic processing, i.e., x-bar syntax. my parsing algorithm not only supports the prevalent theories of knowledge-based parsing put forth in ai, but also uses a sound linguistic theory for the necessary syntactic information processing.
revision learning and its application to part-of-speech tagging. this paper presents a revision learning method that achieves high performance with small computational cost by combining a model with high generalization capacity and a model with small computational cost. this method uses a high capacity model to revise the output of a small cost model. we apply this method to english part-of-speech tagging and japanese morphological analysis, and show that the method performs well.
large-scale induction and evaluation of lexical resources from the penn-ii treebank. in this paper we present a methodology for extracting subcategorisation frames based on an automatic lfg f-structure annotation algorithm for the penn-ii treebank. we extract abstract syntactic function-based subcategorisation frames (lfg semantic forms), traditional cfg category-based subcategorisation frames as well as mixed function/category-based frames, with or without preposition information for obliques and particle information for particle verbs. our approach does not predefine frames, associates probabilities with frames conditional on the lemma, distinguishes between active and passive frames, and fully reflects the effects of long-distance dependencies in the source data structures. we extract 3586 verb lemmas, 14348 semantic form types (an average of 4 per lemma) with 577 frame types. we present a large-scale evaluation of the complete set of forms extracted against the full comlex resource.
guessing parts-of-speech of unknown words using global information. in this paper, we present a method for guessing pos tags of unknown words using local and global information. although many existing methods use only local information (i.e. limited window size or intra-sentential features), global information (extra-sentential features) provides valuable clues for predicting pos tags of unknown words. we propose a probabilistic model for pos guessing of unknown words using global information as well as local information, and estimate its parameters using gibbs sampling. we also attempt to apply the model to semi-supervised learning, and conduct experiments on multiple corpora.
whose thumb is it anyway? classifying author personality from weblog text. we report initial results on the relatively novel task of automatic classification of author personality. using a corpus of personal weblogs, or 'blogs', we investigate the accuracy that can be achieved when classifying authors on four important personality traits. we explore both binary and multiple classification, using differing sets of n-gram features. results are promising for all four traits examined.
hypertext authoring for linking relevant segments of related instruction manuals. recently manuals of industrial products become large and often consist of separated volumes. in reading such individual but related manuals, we must consider the relation among segments, which contain explanations of sequences of operation. in this paper, we propose methods for linking relevant segments in hypertext authoring of a set of related manuals. our method is based on the similarity calculation between two segments. our experimental results show that the proposed method improves both recall and precision comparing with the conventional tf.idf based method.
minimum error rate training in statistical machine translation. often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. a general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. in this paper, we analyze various training criteria which directly optimize translation quality. these training criteria make use of recently proposed automatic evaluation metrics. we describe a new algorithm for efficient training an unsmoothed error count. we show that significantly better results can often be obtained if the final evaluation criterion is taken directly into account as part of the training procedure.
a polynomial-time algorithm for statistical machine translation. we introduce a polynomial-time algorithm for statistical machine translation. this algorithm can be used in place of the expensive, slow best-first search strategies in current statistical translation architectures. the approach employs the stochastic bracketing transduction grammar (sbtg) model we recently introduced to replace earlier word alignment channel models, while retaining a bigram language model. the new algorithm in our experience yields major speed improvement with no significant loss of accuracy.
improved statistical alignment models. in this paper, we present and compare various single-word based alignment models for statistical machine translation. we discuss the five ibm alignment models, the hidden-markov alignment model, smoothing techniques and various modifications. we present different methods to combine alignments. as evaluation criterion we use the quality of the resulting viterbi alignment compared to a manually produced reference alignment. we show that models with a first-order dependence and a fertility model lead to significantly better results than the simple models ibm-1 or ibm-2, which are not able to go beyond zero-order dependencies.
constraint projection: an efficient treatment of disjunctive feature descriptions. unification of disjunctive feature descriptions is important for efficient unification-based parsing. this paper presents constraint projection, a new method for unification of disjunctive feature structures represented by logical constraints. constraint projection is a generalization of constraint unification, and is more efficient because constraint projection has a mechanism for abandoning information irrelevant to a goal specified by a list of variables.
discriminative training and maximum entropy models for statistical machine translation. we present a framework for statistical machine translation of natural languages based on direct maximum entropy models, which contains the widely used source-channel approach as a special case. all knowledge sources are treated as feature functions, which depend on the source language sentence, the target language sentence and possible hidden variables. this approach allows a baseline machine translation system to be extended easily by adding new feature functions. we show that a baseline statistical machine translation system is significantly improved using this approach.
understanding unsegmented user utterances in real-time spoken dialogue systems. this paper proposes a method for incrementally understanding user utterances whose semantic boundaries are not known and responding in real time even before boundaries are determined. it is an integrated parsing and discourse processing method that updates the partial result of understanding word by word, enabling responses based on the partial result. this method incrementally finds plausible sequences of utterances that play crucial roles in the task execution of dialogues, and utilizes beam search to deal with the ambiguity of boundaries as well as syntactic and semantic ambiguities. the results of a preliminary experiment demonstrate that this method understands user utterances better than an understanding method that assumes pauses to be semantic boundaries.
improving statistical natural language translation with categories and rules. this paper describes an all level approach on statistical natural language translation (snlt). without any predefined knowledge the system learns a statistical translation lexicon (stl), word classes (wcs) and translation rules (trs) from a parallel corpus thereby producing a generalized form of a word alignment (wa). the translation process itself is realized as a beam search. in our method example-based techniques enter an overall statistical approach leading to about 50 percent correctly translated sentences applied to the very difficult english-german verbmobil spontaneous speech corpus.
towards a model of face-to-face grounding. we investigate the verbal and nonverbal means for grounding, and propose a design for embodied conversational agents that relies on both kinds of signals to establish common ground in human-computer interaction. we analyzed eye gaze, head nods and attentional focus in the context of a direction-giving task. the distribution of nonverbal behaviors differed depending on the type of dialogue move being grounded, and the overall pattern reflected a monitoring of lack of negative feedback. based on these results, we present an eca that uses verbal and nonverbal grounding acts to update dialogue state.
dependency parsing with an extended finite state approach. this article presents a dependency parsing scheme using an extended finite-state approach. the parser augments input representation with "channels" so that links representing syntactic dependency relations among words can be accommodated and iterates on the input a number of times to arrive at a fixed point. intermediate configurations violating various constraints of projective dependency representations such as no crossing links and no independent items except sentential head are filtered via finite-state filters. we have applied the parser to dependency parsing of turkish.
translating a unification grammar with disjunctions into logical constraints. this paper proposes a method for generating a logical constraint-based internal representation from a unification grammar formalism with disjunctive information. unification grammar formalisms based on path equations and lists of pairs of labels and values are better than those based on first-order terms in that the former is easier to describe and to understand. parsing with term-based internal representations is more efficient than parsing with graph-based representations. therefore, it is effective to translate unification grammar formalism based on path equations and lists of pairs of labels and values into a term-based internal representation. previous translation methods cannot deal with disjunctive feature descriptions, which reduce redundancies in the grammar and make parsing efficient. since the proposed method translates a formalism without expanding disjunctions, parsing with the resulting representation is efficient.
morphological disambiguation by voting constraints. we present a constraint-based morphological disambiguation system in which individual constraints vote on matching morphological parses, and disambiguation of all the tokens in a sentence is performed at the end by selecting parses that receive the highest votes. this constraint application paradigm makes the outcome of the disambiguation independent of the rule sequence, and hence relieves the rule developer from worrying about potentially conflicting rule sequencing. our results for disambiguating turkish indicate that using about 500 constraint rules and some additional simple statistics, we can attain a recall of 95--96% and a precision of 94--95% with about 1.01 parses per token. our system is implemented in prolog and we are currently investigating an efficient implementation based on finite state transducers.
an algorithm for one-page summarization of a long text based on thematic hierarchy detection. this paper presents an algorithm for text summarization using the thematic hierarchy of a text. the algorithm is intended to generate a one-page summary for the user, thereby enabling the user to skim large volumes of an electronic book on a computer display. the algorithm first detects the thematic hierarchy of a source text with lexical cohesion measured by term repetitions. then, it identifies boundary sentences at which a topic of appropriate grading probably starts. finally, it generates a structured summary indicating the outline of the thematic hierarchy. this paper mainly describes and evaluates the part for boundary sentence identification in the algorithm, and then briefly discusses the readability of one-page summaries.
term recognition using technical dictionary hierarchy. in recent years, statistical approaches on atr (automatic term recognition) have achieved good results. however, there are scopes to improve the performance in extracting terms still further. for example, domain dictionaries can improve the performance in atr. this paper focuses on a method for extracting terms using a dictionary hierarchy. our method produces relatively good results for this task.
dependency parsing of japanese spoken monologue based on clause boundaries. spoken monologues feature greater sentence length and structural complexity than do spoken dialogues. to achieve high parsing performance for spoken monologues, it could prove effective to simplify the structure by dividing a sentence into suitable language units. this paper proposes a method for dependency parsing of japanese monologues based on sentence segmentation. in this method, the dependency parsing is executed in two stages: at the clause level and the sentence level. first, the dependencies within a clause are identified by dividing a sentence into clauses and executing stochastic dependency parsing for each clause. next, the dependencies over clause boundaries are identified stochastically, and the dependency structure of the entire sentence is thus completed. an experiment using a spoken monologue corpus shows this method to be effective for efficient dependency parsing of japanese monologue sentences.
constituent-based accent prediction. near-perfect automatic accent assignment is attainable for citation-style speech, but better computational models are needed to predict accent in extended, spontaneous discourses. this paper presents an empirically motivated theory of the discourse focusing nature of accent in spontaneous speech. hypotheses based on this theory lead to a new approach to accent prediction, in which patterns of deviation from citation form accentuation, defined at the constituent or noun phrase level, are automatically learned from an annotated corpus. machine learning experiments on 1031 noun phrases from eighteen spontaneous direction-giving monologues show that accent assignment can be significantly improved by up to 4%-6% relative to a hypothetical baseline system that would produce only citation-form accentuation, giving error rate reductions of 11%-25%.
automatic extraction of aspectual information from a monolingual corpus. this paper describes an approach to extract the aspectual information of japanese verb phrases from a monoligual corpus. we classify verbs into six categories by means of the aspectual features which are defined on the basis of the possibility of co-occurrence with aspectual forms and adverbs. a unique category could be identified for 96% of the target verbs. to evaluate the result of the experiment, we examined the meaning of -teiru which is one of the most fundamental aspectual markers in japanese, and obtained the correct recognition score of 71% for the 200 sentences.
a speech-first model for repair detection and correction. interpreting fully natural speech is an important goal for spoken language understanding systems. however, while corpus studies have shown that about 10% of spontaneous utterances contain self-corrections, or repairs, little is known about the extent to which cues in the speech signal may facilitate repair processing. we identify several cues based on acoustic and prosodic analysis of repairs in a corpus of spontaneous speech, and propose methods for exploiting these cues to detect and correct repairs. we test our acoustic-prosodic cues with other lexical cues to repair identification and find that precision rates of 89--93% and recall of 78--83% can be achieved, depending upon the cues employed, from a prosodically labeled corpus.
learning to say it well: reranking realizations by predicted synthesis quality. this paper presents a method for adapting a language generator to the strengths and weaknesses of a synthetic voice, thereby improving the naturalness of synthetic speech in a spoken language dialogue system. the method trains a discriminative reranker to select paraphrases that are predicted to sound natural when synthesized. the ranker is trained on realizer and synthesizer features in supervised fashion, using human judgements of synthetic voice quality on a sample of the paraphrases representative of the generator's capability. results from a cross-validation study indicate that discriminative paraphrase reranking can achieve substantial improvements in naturalness on average, ameliorating the problem of highly variable synthesis quality typically encountered with today's unit selection synthesizers.
analysis of selective strategies to build a dependency-analyzed corpus. this paper discusses sampling strategies for building a dependency-analyzed corpus and analyzes them with different kinds of corpora. we used the kyoto text corpus, a dependency-analyzed corpus of newspaper articles, and prepared the ipal corpus, a dependency-analyzed corpus of example sentences in dictionaries, as a new and different kind of corpus. the experimental results revealed that the length of the test set controlled the accuracy and that the longest-first strategy was good for an expanding corpus, but this was not the case when constructing a corpus from scratch.
supporting annotation layers for natural language processing. we demonstrate a system for flexible querying against text that has been annotated with the results of nlp processing. the system supports self-overlapping and parallel layers, integration of syntactic and ontological hierarchies, flexibility in the format of returned results, and tight integration with sql. we present a query language and its use on examples taken from the nlp literature.
recognition of the coherence relation between te-linked clauses. this paper describes a method for recognizing coherence relations between clauses which are linked by te in japanese-a translational equivalent of english and. we consider that the coherence relations are categories each of which has a prototype structure as well as the relationships among them. by utilizing this organization of the relations, we can infer an appropriate relation from the semantic structures of the clauses between which that relation holds. we carried out an experiment and obtained the correct recognition ratio of 82% for the 280 sentences.
an automatic method for summary evaluation using multiple evaluation results by a manual method. to solve a problem of how to evaluate computer-produced summaries, a number of automatic and manual methods have been proposed. manual methods evaluate summaries correctly, because humans evaluate them, but are costly. on the other hand, automatic methods, which use evaluation tools or programs, are low cost, although these methods cannot evaluate summaries as accurately as manual methods. in this paper, we investigate an automatic evaluation method that can reduce the errors of traditional automatic methods by using several evaluation results obtained manually. we conducted some experiments using the data of the text summarization challenge 2 (tsc-2). a comparison with conventional automatic methods shows that our method outperforms other methods usually used.
the lexical semantics of comparative expressions in a multi-level semantic processor. comparative expressions (ces) such as "bigger than" and "more oranges than" are highly ambiguous, and their meaning is context dependent. thus, they pose problems for the semantic interpretation algorithms typically used in natural language database interfaces. we focus on the comparison attribute ambiguities that occur with ces. to resolve these ambiguities our natural language interface interacts with the user, finding out which of the possible interpretations was intended. our multi-level semantic processor facilitates this interaction by recognizing the occurrence of comparison attribute ambiguity and then calculating and presenting a list of candidate comparison attributes from which the user may choose.
focus to emphasize tone structures for prosodic analysis in spoken language generation. we analyze the concept of focus in speech and the relationship between focus and speech acts for prosodic generation. we determine how the speaker's utterances are influenced by speaker's intention. the relationship between speech acts and focus information is used to define which parts of the sentence serve as the focus parts. we propose the focus to emphasize tones (fet) structure to analyze the focus components. we also design the fet grammar to analyze the intonation patterns and produce tone marks as a result of our analysis. we present a proof-of-the-concept working example to validate our proposal. more comprehensive evaluations are part of our current work.
improving the scalability of semi-markov conditional random fields for named entity recognition. this paper presents techniques to apply semi-crfs to named entity recognition tasks with a tractable computational cost. our framework can handle an ner task that has long named entities and many labels which increase the computational cost. to reduce the computational cost, we propose two techniques: the first is the use of feature forests, which enables us to pack feature-equivalent states, and the second is the introduction of a filtering process which significantly reduces the number of candidate states. this framework allows us to use a rich set of features extracted from the chunk-based representation that can capture informative characteristics of entities. we also introduce a simple trick to transfer information about distant entities by embedding label information into non-entity labels. experimental results show that our model achieves an f-score of 71.48% on the jnlpba 2004 shared task without using any external resources or post-processing techniques.
robust parsing based on discourse information: completing partial parses of ill-formed sentences on the basis of discourse information. in a consistent text, many words and phrases are repeatedly used in more than one sentence. when an identical phrase (a set of consecutive words) is repeated in different sentences, the constituent words of those sentences tend to be associated in identical modification patterns with identical parts of speech and identical modifiee-modifier relationships. thus, when a syntactic parser cannot parse a sentence as a unified structure, parts of speech and modifiee-modifier relationships among morphologically identical words in complete parses of other sentences within the same text provide useful information for obtaining partial parses of the sentence.in this paper, we describe a method for completing partial parses by maintaining consistency among morphologically identical words within the same text as regards their part of speech and their modifiee-modifier relationship. the experimental results obtained by using this method with technical documents offer good prospects for improving the accuracy of sentence analysis in a broad-coverage natural language processing system such as a machine translation system.
a term recognition approach to acronym recognition. we present a term recognition approach to extract acronyms and their definitions from a large text collection. parenthetical expressions appearing in a text collection are identified as potential acronyms. assuming terms appearing frequently in the proximity of an acronym to be the expanded forms (definitions) of the acronyms, we apply a term recognition method to enumerate such candidates and to measure the likelihood scores of the expanded forms. based on the list of the expanded forms and their likelihood scores, the proposed algorithm determines the final acronym-definition pairs. the proposed method combined with a letter matching algorithm achieved 78% precision and 85% recall on an evaluation corpus with 4,212 acronym-definition pairs.
meaningful clustering of senses helps boost word sense disambiguation performance. fine-grained sense distinctions are one of the major obstacles to successful word sense disambiguation. in this paper, we present a method for reducing the granularity of the wordnet sense inventory based on the mapping to a manually crafted dictionary encoding sense hierarchies, namely the oxford dictionary of english. we assess the quality of the mapping and the induced clustering, and evaluate the performance of coarse wsd systems in the senseval-3 english all-words task.
a computational view of the cognitive semantics of spatial prepostions. this paper outlines the linguistic semantic commitments underlying an application which automatically constructs depictions of verbal spatial descriptions. our approach draws on the ideational view of linguistic semantics developed by ronald langacker in his theory of cognitive grammar, and the conceptual representation of physical objects from the two-level semantics of bierwisch and lang. in particular the dimensions of the process of conventional imagery are used as a metric for the design of our own conceptual representation.
valido: a visual tool for validating sense annotations. in this paper we present valido, a tool that supports the difficult task of validating sense choices produced by a set of annotators. the validator can analyse the semantic graphs resulting from each sense choice and decide which sense is more coherent with respect to the structure of the adopted lexicon. we describe the interface and report an evaluation of the tool in the validation of manual sense annotations.
the effects of interaction on spoken discourse. near-term spoken language systems will likely be limited in their interactive capabilities. to design them, we shall need to model how the presence or absence of speaker interaction influences spoken discourse patterns in different types of tasks. in this research, a comprehensive examination is provided of the discourse structure and performance efficiency of both interactive and noninteractive spontaneous speech in a seriated assembly task. more specifically, telephone dialogues and audiotape monologues are compared, which represent opposites in terms of the opportunity for confirmation feedback and clarification subdialogues. keyboard communication patterns, upon which most natural language heuristics and algorithms have been based, also are contrasted with patterns observed in the two speech modalities. finally, implications are discussed for the design of near-term limited-interaction spoken language systems.
using bilingual dependencies to align words in english/french parallel corpora. this paper describes a word and phrase alignment approach based on a dependency analysis of french/english parallel corpora, referred to as alignment by "syntax-based propagation." both corpora are analysed with a deep and robust dependency parser. starting with an anchor pair consisting of two words that are translations of one another within aligned sentences, the alignment link is propagated to syntactically connected words.
an optimal tabular parsing algorithm. in this paper we relate a number of parsing algorithms which have been developed in very different areas of parsing theory, and which include deterministic algorithms, tabular algorithms, and a parallel algorithm. we show that these algorithms are based on the same underlying ideas.by relating existing ideas, we hope to provide an opportunity to improve some algorithms based on features of others. a second purpose of this paper is to answer a question which has come up in the area of tabular parsing, namely how to obtain a parsing algorithm with the property that the table will contain as little entries as possible, but without the possibility that two entries represent the same subderivation.
constructing semantic space models from parsed corpora. traditional vector-based models use word co-occurrence counts from large corpora to represent lexical meaning. in this paper we present a novel approach for constructing semantic spaces that takes syntactic relations into account. we introduce a formalisation for this class of models and evaluate their adequacy on two modelling tasks: semantic priming and automatic discrimination of lexical relations.
an alternative lr algorithm for tags. we present a new lr algorithm for tree-adjoining grammars. it is an alternative to an existing algorithm that is shown to be incorrect. furthermore, the new algorithm is much simpler, being very close to traditional lr parsing for context-free grammars. the construction of derived trees and the computation of features also become straightforward.
optimal constituent alignment with edge covers for semantic projection. given a parallel corpus, semantic projection attempts to transfer semantic role annotations from one language to another, typically by exploiting word alignments. in this paper, we present an improved method for obtaining constituent alignments between parallel sentences to guide the role projection task. our extensions are twofold: (a) we model constituent alignment as minimum weight edge covers in a bipartite graph, which allows us to find a globally optimal solution efficiently; (b) we propose tree pruning as a promising strategy for reducing alignment noise. experimental results on an english-german parallel corpus demonstrate improvements over state-of-the-art models.
on the evaluation and comparison of taggers: the effect of noise in testing corpora. this paper addresses the issue of pos tagger evaluation. such evaluation is usually performed by comparing the tagger output with a reference test corpus, which is assumed to be error-free. currently used corpora contain noise which causes the obtained performance to be a distortion of the real value. we analyze to what extent this distortion may invalidate the comparison between taggers or the measure of the improvement given by a new system. the main conclusion is that a more rigorous testing experimentation setting/designing is needed to reliably evaluate and compare tagger accuracies.
probabilistic parsing strategies. we present new results on the relation between context-free parsing strategies and their probabilistic counter-parts. we provide a necessary condition and a sufficient condition for the probabilistic extension of parsing strategies. these results generalize existing results in the literature that were obtained by considering parsing strategies in isolation.
empirically-based control of natural language generation. in this paper we present a new approach to controlling the behaviour of a natural language generation system by correlating internal decisions taken during free generation of a wide range of texts with the surface stylistic characteristics of the resulting outputs, and using the correlation to control the generator. this contrasts with the generate-and-test architecture adopted by most previous empirically-based generation approaches, offering a more efficient, generic and holistic method of generator control. we illustrate the approach by describing a system in which stylistic variation (in the sense of biber (1988)) can be effectively controlled during the generation of short medical information texts.
an alternative method of training probabilistic lr parsers. we discuss existing approaches to train lr parsers, which have been used for statistical resolution of structural ambiguity. these approaches are nonoptimal, in the sense that a collection of probability distributions cannot be obtained. in particular, some probability distributions expressible in terms of a context-free grammar cannot be expressed in terms of the lr parser constructed from that grammar, under the restrictions of the existing approaches to training of lr parsers. we present an alternative way of training that is provably optimal, and that allows all probability distributions expressible in the context-free grammar to be carried over to the lr parser. we also demonstrate empirically that this kind of training can be effectively applied on a large treebank.
semi-supervised maximum entropy based approach to acronym and abbreviation normalization in medical texts. text normalization is an important aspect of successful information retrieval from medical documents such as clinical notes, radiology reports and discharge summaries. in the medical domain, a significant part of the general problem of text normalization is abbreviation and acronym disambiguation. numerous abbreviations are used routinely throughout such texts and knowing their meaning is critical to data retrieval from the document. in this paper i will demonstrate a method of automatically generating training data for maximum entropy (me) modeling of abbreviations and acronyms and will show that using me modeling is a promising technique for abbreviation and acronym normalization. i report on the results of an experiment involving training a number of me models used to normalize abbreviations and acronyms on a sample of 10,000 rheumatology notes with ~89% accuracy.
an extended theory of head-driven parsing. we show that more head-driven parsing algorithms can be formulated than those occurring in the existing literature. these algorithms are inspired by a family of left-to-right parsing algorithms from a recent publication. we further introduce a more advanced notion of "head-driven parsing" which allows more detailed specification of the processing order of non-head elements in the right-hand side. we develop a parsing algorithm for this strategy, based on lr parsing techniques.
modeling filled pauses in medical dictations. filled pauses are characteristic of spontaneous speech and can present considerable problems for speech recognition by being often recognized as short words. an <i>um</i> can be recognized as <i>thumb</i> or <i>arm</i> if the recognizer's language model does not adequately represent fp's. recognition of quasi-spontaneous speech (medical dictation) is subject to this problem as well. results from medical dictations by 21 family practice physicians show that using an fp model trained on the corpus populated with fp's produces overall better result than a model trained on a corpus that excluded fp's or a corpus that had random fp's.
efficient tabular lr parsing. we give a new treatment of tabular lr parsing, which is an alternative to tomita's generalized lr algorithm. the advantage is twofold. firstly, our treatment is conceptually more attractive because it uses simpler concepts, such as grammar transformations and standard tabulation techniques also know as chart parsing. secondly, the static and dynamic complexity of parsing, both in space and time, is significantly reduced.
high throughput modularized nlp system for clinical text. this paper presents the results of the development of a high throughput, real time modularized text analysis and information retrieval system that identifies clinically relevant entities in clinical notes, maps the entities to several standardized nomenclatures and makes them available for subsequent information retrieval and data mining. the performance of the system was validated on a small collection of 351 documents partitioned into 4 query topics and manually examined by 3 physicians and 3 nurse abstractors for relevance to the query topics. we find that simple key phrase searching results in 73% recall and 77% precision. a combination of nlp approaches to indexing improve the recall to 92%, while lowering the precision to 67%.
prefix probabilities from stochastic tree adjoining grammars. language models for speech recognition typically use a probability model of the form pr(an/a1, a2, .... an-1 stochastic grammars, on the other hand, are typically used to assign structure to utterances. a language model of the above form is constructed from such grammars by computing the prefix probability &sum;wε&sigma;* pr(a1 ...anw), where w represents all possible terminations of the prefix a1 ... an. the main result in this paper is an algorithm to compute such prefix probabilities given a stochastic tree adjoining grammar (tag). the algorithm achieves the required computation in o(n 6) time. the probability of sub-derivations that do not derive any words in the prefix, but contribute structurally to its derivation, are precomputed to achieve termination. this algorithm enables existing corpus-based estimation techniques for stochastic tags to be used for language modelling.
a trainable rule-based algorithm for word segmentation. this paper presents a trainable rule-based algorithm for performing word segmentation. the algorithm provides a simple, language-independent alternative to large-scale lexical-based segmenters requiring large amounts of knowledge engineering. as a stand-alone segmenter, we show our algorithm to produce high performance chinese segmentation. in addition, we show the transformation-based algorithm to be effective in improving the output of several existing word segmentation algorithms in three different languages.
dictionaries, dictionary grammars and dictionary entry parsing. we identify two complementary processes in the conversion of machine-readable dictionaries into lexical databases: recovery of the dictionary stucture from the typographical markings which persist on the dictionary distribution tapes and embody the publishers' notational conventions; followed by making explicit all of the codified and ellided information packed into individual entries. we discuss notational conventions and tape formats, outline structural properties of dictionaries, observe a range of representational phenomena particularly relevant to dictionary parsing, and derive a set of minimal requirements for a dictionary grammar formalism. we present a general purpose dictionary entry parser which uses a formal notation designed to describe the structure of entries and performs a mapping from the flat character stream on the tape to a highly structured and fully instantiated representation of the dictionary. we demonstrate the power of the formalism by drawing examples from a range of dictionary sources which have been processed and converted into lexical databases.
modeling local context for pitch accent prediction. pitch accent placement is a major topic in intonational phonology research and its application to speech synthesis. what factors influence whether or not a word is made intonationally prominent or not is an open question. in this paper, we investigate how one aspect of a word's local context --- its collocation with neighboring words --- influences whether it is accented or not. results of experiments on two transcribed speech corpora in a medical domain show that such collocation information is a useful predictor of pitch accent placement.
learning intonation rules for concept to speech generation. in this paper, we report on an effort to provide a general-purpose spoken language generation tool for concept-to-speech (cts) applications by extending a widely used text generation package, fuf/surge, with an intonation generation component. as a first step, we applied machine learning and statistical models to learn intonation rules based on the semantic and syntactic information typically represented in fuf/surge at the sentence level. the results of this study are a set of intonation rules learned automatically which can be directly implemented in our intonation generation component. through 5-fold cross-validation, we show that the learned rules achieve around 90% accuracy for break index, boundary tone and phrase accent and 80% accuracy for pitch accent. our study is unique in its use of features produced by language generation to control intonation. the methodology adopted here can be employed directly when more discourse/pragmatic information is to be considered in the future.
bilingual hebrew-english generation of possessives and partitives: raising the input abstraction level. we present a contrastive analysis of the syntactic realizations of possessives and partitives in hebrew and english and conclude by presenting an input specification for complex nps which is slightly more abstract than the one used in surge. we define two main features - <i>possessor</i> and <i>ref-set</i> and discuss how the grammar handles complex syntactic co-occurrence phenomena based on this input. we conclude by evaluating how the resulting input specification language is appropriate for both languages. syntactic realization grammars have traditionally attempted to accept inputs with the highest possible level of abstraction, in order to facilitate the work of the components (sentence planner) preparing the input. recently, the search for higher abstraction has been, however, challenged (elhadad and robin, 1996) (lavoie and rambow, 1997) (busemann and horacek, 1998). in this paper, we contribute to the issue of selecting the "ideal" abstraction level in the input to syntactic realization grammar by considering the case of partitives and possessives in a bilingual hebrew-english generation grammar. in the case of bilingual generation, the ultimate goal is to provide a single input structure, where only the openclass lexical entries are specific to the language. in that case, the minimal abstraction required must cover the different syntactic constraints of the two languages.
automatic alignment in parallel corpora. this paper addresses the alignment issue in the framework of exploitation of large bimultilingual corpora for translation purposes. a generic alignment scheme is proposed that can meet varying requirements of different applications. depending on the level at which alignment is sought, appropriate surface linguistic information is invoked coupled with information about possible unit delimiters. each text unit (sentence, clause or phrase) is represented by the sum of its content tags. the results are then fed into a dynamic programming framework that computes the optimum alignment of units. the proposed scheme has been tested at sentence level on parallel corpora of the celex database. the success rate exceeded 99%. the next steps of the work concern the testing of the scheme's efficiency at lower levels endowed with necessary bilingual information about potential delimiters.
the complexity of recognition of linguistically adequate dependency grammars. results of computational complexity exist for a wide range of phrase structure-based grammar formalisms, while there is an apparent lack of such results for dependency-based formalisms. we here adapt a result on the complexity of id/lp-grammars to the dependency framework. contrary to previous studies on heavily restricted dependency grammars, we prove that recognition (and thus, parsing) of linguistically adequate dependency grammars is np-complete.
learning event durations from event descriptions. we have constructed a corpus of news articles in which events are annotated for estimated bounds on their duration. here we describe a method for measuring inter-annotator agreement for these event duration distributions. we then show that machine learning techniques applied to this data yield coarse-grained event duration information, considerably outperforming a baseline and approaching human performance.
learning noun phrase anaphoricity to improve conference resolution: issues in representation and optimization. knowledge of the anaphoricity of a noun phrase might be profitably exploited by a coreference system to bypass the resolution of non-anaphoric noun phrases. perhaps surprisingly, recent attempts to incorporate automatically acquired anaphoricity information into coreference systems, however, have led to the degradation in resolution performance. this paper examines several key issues in computing and using anaphoricity information to improve learning-based coreference systems. in particular, we present a new corpus-based approach to anaphoricity determination. experiments on three standard coreference data sets demonstrate the effectiveness of our approach.
instance-based sentence boundary determination by optimization for natural language generation. this paper describes a novel instance-based sentence boundary determination method for natural language generation that optimizes a set of criteria based on examples in a corpus. compared to existing sentence boundary determination approaches, our work offers three significant contributions. first, our approach provides a general domain independent framework that effectively addresses sentence boundary determination by balancing a comprehensive set of sentence complexity and quality related constraints. second, our approach can simulate the characteristics and the style of naturally occurring sentences in an application domain since our solutions are optimized based on their similarities to examples in a corpus. third, our approach can adapt easily to suit a natural language generation system's capability by balancing the strengths and weaknesses of its subcomponents (e.g. its aggregation and referring expression generation capability). our final evaluation shows that the proposed method results in significantly better sentence generation outcomes than a widely adopted approach.
a sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts. sentiment analysis seeks to identify the viewpoint(s) underlying a text span; an example application is classifying a movie review as "thumbs up" or "thumbs down". to determine this sentiment polarity, we propose a novel machine-learning method that applies text-categorization techniques to just the subjective portions of the document. extracting these portions can be implemented using efficient techniques for finding minimum cuts in graphs; this greatly facilitates incorporation of cross-sentence contextual constraints.
seeing stars: exploiting class relationships for sentiment categorization with respect to rating scales. we address the rating-inference problem, wherein rather than simply decide whether a review is "thumbs up" or "thumbs down", as in previous sentiment analysis work, one must determine an author's evaluation with respect to a multi-point scale (e.g., one to five "stars"). this task represents an interesting twist on standard multi-class text categorization because there are several different degrees of similarity between class labels; for example, "three stars" is intuitively closer to "four stars" than to "one star".we first evaluate human performance at the task. then, we apply a meta-algorithm, based on a metric labeling formulation of the problem, that alters a given n-ary classifier's output in an explicit attempt to ensure that similar items receive similar labels. we show that the meta-algorithm can provide significant improvements over both multi-class and regression versions of svms when we employ a novel similarity measure appropriate to the problem.
inducing ontological co-occurrence vectors. in this paper, we present an unsupervised methodology for propagating lexical cooccurrence vectors into an ontology such as wordnet. we evaluate the framework on the task of automatically attaching new concepts into the ontology. experimental results show 73.9% attachment accuracy in the first position and 81.3% accuracy in the top-5 positions. this framework could potentially serve as a foundation for ontologizing lexical-semantic resources and assist the development of other largescale and internally consistent collections of semantic information.
an unsupervised approach to prepositional phrase attachment using contextually similar words. prepositional phrase attachment is a common source of ambiguity in natural language processing. we present an unsupervised corpus-based approach to prepositional phrase attachment that achieves similar performance to supervised methods. unlike previous unsupervised approaches in which training data is obtained by heuristic extraction of unambiguous examples from a corpus, we use an iterative process to extract training data from an automatically parsed corpus. attachment decisions are made using a linear combination of features and low frequency events are approximated using contextually similar words.
espresso: leveraging generic patterns for automatically harvesting semantic relations. in this paper, we present espresso, a weakly-supervised, general-purpose, and accurate algorithm for harvesting semantic relations. the main contributions are: i) a method for exploiting generic patterns by filtering incorrect instances using the web; and ii) a principled measure of pattern and instance reliability enabling the filtering algorithm. we present an empirical comparison of espresso with various state of the art systems, on different size and genre corpora, on extracting various general and specific relations. experimental results show that our exploitation of generic patterns substantially increases system recall with small effect on overall precision.
bleu: a method for automatic evaluation of machine translation. human evaluations of machine translation are extensive but expensive. human evaluations can take months to finish and involve human labor that can not be reused. we propose a method of automatic machine translation evaluation that is quick, inexpensive, and language-independent, that correlates highly with human evaluation, and that has little marginal cost per run. we present this method as an automated understudy to skilled human judges which substitutes for them when there is need for quick or frequent evaluations.
possissive pronominal anaphor resolution in portuguese written texts. this paper describes a proposal for portuguese possessive pronominal anaphor (ppa) resolution, a problem little considered so far. particularly, we address the problem of portuguese 3rd person intrasentential ppas seu/sua/seus/suas (his/her/their/its, for human and non-human subjects in english), which constitute 30% of pronominal occurrences in our corpus (brazilian laws about environment protection). considering some differences between ppas and other kinds of anaphors, such as personal or demonstrative pronouns, we define three knowledge sources (kss) for ppa resolution: surface patterns (taking in account factors such as syntactic parallelism), possessive relationship rules and sentence centering. these knowledge sources are organized in a blackboard architecture for ppa resolution, which provides both knowledge and procedure distribution among autonomous entities (reflexive agents), each of them specialized in a particular aspect of the problem solving. the proposal has been implemented and its results are discussed at the end of the work.
multiset-valued linear index grammars: imposing dominance constraints on derivations. this paper defines multiset-valued linear index grammar and unordered vector grammar with dominance links. the former models certain uses of multiset-valued feature structures in unification-based formalisms, while the latter is motivated by word order variation and by "quasi-trees", a generalization of trees. the two formalisms are weakly equivalent, and an important subset is at most context-sensitive and polynomially parsable.
a definite clause version of categorial grammar. we introduce a first-order version of categorial grammar, based on the idea of encoding syntactic types as definite clauses. thus, we drop all explicit requirements of adjacency between combinable constituents, and we capture word-order constraints simply by allowing subformulae of complex types to share variables ranging over string positions. we are in this way able to account for constructions involving discontinuous constituents. such constructions involving discontinuous constituents. such constructions are difficult to handle in the more traditional version of categorial grammar, which is based on propositional types and on the requirement of strict string adjacency between combinable constituents.we show then how, for this formalism, parsing can be efficiently implemented as theorem proving. our approach to encoding types as definite clauses presupposes a modification of standard horn logic syntax to allow internal implications in definite clauses. this modification is needed to account for the types of higher-order functions and, as a consequence, standard prolog-like horn logic theorem proving is not powerful enough. we tackle this problem by adopting an intuitionistic treatment of implication, which has already been proposed elsewhere as an extension of prolog for implementing hypothetical reasoning and modular logic programming.
evaluating a trainable sentence planner for a spoken dialogue system. techniques for automatically training modules of a natural language generator have recently been proposed, but a fundamental concern is whether the quality of utterances produced with trainable components can compete with hand-crafted template-based or rule-based approaches. in this paper we experimentally evaluate a trainable sentence planner for a spoken dialogue system by eliciting subjective human judgments. in order to perform an exhaustive comparison, we also evaluate a hand-crafted template-based generation component, two rule-based sentence planners, and two baseline sentence planners. we show that the trainable sentence planner performs better than the rule-based systems and the baselines, and as well as the hand-crafted system.
synchronous models of language. in synchronous rewriting, the productions of two rewriting systems are paired and applied synchronously in the derivation of a pair of strings. we present a new synchronous rewriting system and argue that it can handle certain phenomena that are not covered by existing synchronous systems. we also prove some interesting formal/computational properties of our system.
modeling human sentence processing data with a statistical parts-of-speech tagger. it has previously been assumed in the psycholinguistic literature that finite-state models of language are crucially limited in their explanatory power by the locality of the probability distribution and the narrow scope of information used by the model. we show that a simple computational model (a bigram part-of-speech tagger based on the design used by corley and crocker (2000)) makes correct predictions on processing difficulty observed in a wide range of empirical sentence processing data. we use two modes of evaluation: one that relies on comparison with a control sentence, paralleling practice in human studies; another that measures probability drop in the disambiguating region of the sentence. both are surprisingly good indicators of the processing difficulty of garden-path sentences. the sentences tested are drawn from published sources and systematically explore five different types of ambiguity: previous studies have been narrower in scope and smaller in scale. we do not deny the limitations of finite-state models, but argue that our results show that their usefulness has been underestimated.
d-tree grammars. dtg are designed to share some of the advantages of tag while overcoming some of its limitations. dtg involve two composition operations called subsertion and sister-adjunction. the most distinctive feature of dtg is that, unlike tag, there is complete uniformity in the way that the two dtg operations relate lexical items: subsertion always corresponds to complementation and sister-adjunction to modification. furthermore, dtg, unlike tag, can provide a uniform analysis for wh-movement in english and kashmiri, despite the fact that the wh element in kashmiri appears in sentence-second position, and not sentence-initial position as in english.
extraction of tree adjoining grammars from a treebank for korean. we present the implementation of a system which extracts not only lexicalized grammars but also feature-based lexicalized grammars from korean sejong treebank. we report on some practical experiments where we extract tag grammars and tree schemata. above all, full-scale syntactic tags and well-formed morphological analysis in sejong treebank allow us to extract syntactic features. in addition, we modify treebank for extracting lexicalized grammars and convert lexicalized grammars into tree schemata to resolve limited lexical coverage problem of extracted lexicalized grammars.
a three-level model for plan exploration. in modeling the structure of task-related discourse using plans, it is important to distinguish between plans that the agent has adopted and is pursuing and those that are only being considered and explored, since the kinds of utterances arising from a particular domain plan and the patterns of reference to domain plans and movement within the plan tree are quite different in the two cases. this paper presents a three-level discourse model that uses separate domain and exploration layers, in addition to a layer of discourse metaplans, allowing these distinct behavior patterns and the plan adoption and reconsideration moves they imply to be recognized and modeled.
a unification-based semantic interpretation for coordinate constructs. this paper shows that a first-order unification-based semantic interpretation for various coordinate constructs is possible without an explicit use of lambda expressions if we slightly modify the standard montagovian semantics of coordination. this modification, along with partial execution, completely eliminates the lambda reduction steps during semantic interpretation.
meinongian semantics for propositional semantic networks. this paper surveys several approaches to semantic-network semantics that have not previously been treated in the al or computational linguistics literature, though there is a large philosophical literature investigating them in some detail. in particular, propositional semantic networks (exemplihed by sneps) are discussed. it is argued that only a fully intensional ("meinongran") semantics is appropriate for them, and several meinongran systems are presented.
quantifier scope and constituency. traditional approaches to quantifier scope typically need stipulation to exclude readings that are unavailable to human understanders. this paper shows that quantifier scope phenomena can be precisely characterized by a semantic representation constrained by surface constituency, if the distinction between referential and quantificational nps is properly observed. a ccg implementation is described and compared to other approaches.
a practical solution to the problem of automatic part-of-speech induction from text. the problem of part-of-speech induction from text involves two aspects: firstly, a set of word classes is to be derived automatically. secondly, each word of a vocabulary is to be assigned to one or several of these word classes. in this paper we present a method that solves both problems with good accuracy. our approach adopts a mixture of statistical methods that have been successfully applied in word sense induction. its main advantage over previous attempts is that it reduces the syntactic space to only the most important dimensions, thereby almost eliminating the otherwise omnipresent problem of data sparseness.
mapping scrambled korean senteces into english using synchronous tags. synchronous tree adjoining grammars can be used for machine translation. however, translating a free order language such as korean to english is complicated. i present a mechanism to translate scrambled korean sentences into english by combining the concepts of multi-component tags (mc-tags) and synchronous tags (stags).
identifying word translation in non_parallel texts. common algorithms for sentence and word-alignment allow the automatic identification of word translations from parallel texts. this study suggests that the identification of word translations should also be possible with non-parallel and even unrelated texts. the method proposed is based on the assumption that there is a correlation between the patterns of word co-occurrences in texts of different languages.
a finite-state model of human sentence processing. it has previously been assumed in the psycholinguistic literature that finite-state models of language are crucially limited in their explanatory power by the locality of the probability distribution and the narrow scope of information used by the model. we show that a simple computational model (a bigram part-of-speech tagger based on the design used by corley and crocker (2000)) makes correct predictions on processing difficulty observed in a wide range of empirical sentence processing data. we use two modes of evaluation: one that relies on comparison with a control sentence, paralleling practice in human studies; another that measures probability drop in the disambiguating region of the sentence. both are surprisingly good indicators of the processing difficulty of garden-path sentences. the sentences tested are drawn from published sources and systematically explore five different types of ambiguity: previous studies have been narrower in scope and smaller in scale, we do not deny the limitations of finite-state models, but argue that our results show that their usefulness has been underestimated.
automatic identification of word translations from unrelated english and german corpora. algorithms for the alignment of words in translated texts are well established. however, only recently new approaches have been proposed to identify word translations from non-parallel or even unrelated texts. this task is more difficult, because most statistical clues useful in the processing of parallel texts cannot be applied to non-parallel texts. whereas for parallel texts in some studies up to 99% of the word alignments have been shown to be correct, the accuracy for non-parallel texts has been around 30% up to now. the current study, which is based on the assumption that there is a correlation between the patterns of word co-occurrences in corpora of different languages, makes a significant improvement to about 72% of word translations identified correctly.
machine aided error-correction environment for korean morphological analysis and part-of-speech tagging. statistical methods require very large corpus with high quality. but building large and faultless annotated corpus is a very difficult job. this paper proposes an efficient method to construct part-of-speech tagged corpus. a rule-based error correction method is proposed to find and correct errors semi-automatically by user-defined rules. we also make use of user's correction log to reflect feedback. experiments were carried out to show the efficiency of error correction process of this workbench. the result shows that about 63.2 % of tagging errors can be corrected.
statistical models for unsupervised prepositional phrase attachement. we present several unsupervised statistical models for the prepositional phrase attachment task that approach the accuracy of the best supervised methods for this task. our unsupervised approach uses a heuristic based on attachment proximity and trains from raw text that is annotated with only part-of-speech tags and morphological base forms, as opposed to attachment information. it is therefore less resource-intensive and more portable than previous corpus-based algorithm proposed for this task. we present results for prepositional phrase attachment in both english and spanish.
text chunking by combining hand-crafted rules and memory-based learning. this paper proposes a hybrid of hand-crafted rules and a machine learning method for chunking korean. in the partially free word-order languages such as korean and japanese, a small number of rules dominate the performance due to their well-developed postpositions and endings. thus, the proposed method is primarily based on the rules, and then the residual errors are corrected by adopting a memory-based machine learning method. since the memory-based learning is an efficient method to handle exceptions in natural language processing, it is good at checking whether the estimates are exceptional cases of the rules and revising them. an evaluation of the method yields the improvement in f-score over the rules or various machine learning methods alone.
learning surface text patterns for a question answering system. in this paper we explore the power of surface text patterns for open-domain question answering systems. in order to obtain an optimal set of patterns, we have developed a method for learning such patterns automatically. a tagged corpus is built from the internet in a bootstrapping process by providing a few hand-crafted examples of each question type to altavista. patterns are then automatically extracted from the returned documents and standardized. we calculate the precision of each pattern, and the average precision for each question type. these patterns are then applied to find answers to new questions. using the trec-10 question set, we report results for two cases: answers determined from the trec-10 corpus and from the web.
word sense disambiguation by learning from unlabeled data. most corpus-based approaches to natural language processing suffer from lack of training data. this is because acquiring a large number of labeled data is expensive. this paper describes a learning method that exploits unlabeled data to tackle data sparseness problem. the method uses committee learning to predict the labels of unlabeled data that augment the existing training data. our experiments on word sense disambiguation show that predictive accuracy is significantly improved by using additional unlabeled data.
randomized algorithms and nlp: using locality sensitive hash functions for high speed noun clustering. in this paper, we explore the power of randomized algorithm to address the challenge of working with very large amounts of data. we apply these algorithms to generate noun similarity lists from 70 million pages. we reduce the running time from quadratic to practically linear in the number of elements to be computed.
disambiguating and interpreting verb definitions. to achieve our goal of building a comprehensive lexical database out of various on-line resources, it is necessary to interpret and disambiguate the information found in these resources. in this paper we describe a disambiguation module which analyzes the content of dictionary definitions, in particular, definitions of the form "to verb with np". we discuss the semantic relations holding between the head and the prepositional phrase in such structures, as well as our heuristics for identifying these relations and for disambiguating the senses of the words involved. we present some results obtained by the disambiguation module and evaluate its rate of success as compared with results obtained from human judgments.
parsing and interpreting comparatives. we describe a fairly comprehensive handling of the syntax and semantics of comparative constructions. the analysis is largely based on the theory developed by pinkham, but we advance arguments to support a different handling of phrasal comparatives - in particular, we use direct interpretation instead of c-ellipsis. we explain the reasons for dividing comparative sentences into different categories, and for each category we give an example of the corresponding montague semantics. the ideas have all been implemented within a large-scale grammar for swedish.
names and similarities on the web: fact extraction in the fast lane. in a new approach to large-scale extraction of facts from unstructured text, distributional similarities become an integral part of both the iterative acquisition of high-coverage contextual extraction patterns, and the validation and ranking of candidate facts. the evaluation measures the quality and coverage of facts extracted from one hundred million web documents, starting from ten seed facts and using no additional knowledge, lexicons or complex tools.
fast parsing using pruning and grammar specialization. we show how a general grammar may be automatically adapted for fast parsing of utterances from a specific domain by means of constituent pruning and grammar specialization based on explanation-based learning. these methods together give an order of magnitude increase in speed, and the coverage loss entailed by grammar specialization is reduced to approximately half that reported in previous work. experiments described here suggest that the loss of coverage has been reduced to the point where it no longer causes significant performance degradation in the context of a real application.
getting at discourse referents. i examine how discourse anaphoric uses of the definite pronoun it contrast with similar uses of the demonstrative pronoun that. their distinct contexts of use are characterized in terms of two contextual features---persistence of grammatical subject and persistence of grammatical form---which together demonstrate very clearly the interrelation among lexical choice, grammatical choices and the dimension of time in signalling the dynamic attentional state of a discourse.
a voice enabled procedure browser for the international space station. clarissa, an experimental voice enabled procedure browser that has recently been deployed on the international space station (iss), is to the best of our knowledge the first spoken dialog system in space. this paper gives background on the system and the iss procedures, then discusses the research developed to address three key problems: grammar-based speech recognition using the regulus toolkit; svm based methods for open microphone speech recognition; and robust side-effect free dialogue management for handling undos, corrections and confirmations.
some facts about centers, indexicals, and demonstratives. certain pronoun contexts are argued to establish a local center (lc), i.e., a conventionalized indexical similar to 1st/2nd pers. pronouns. demonstrative pronouns, also indexicals, are shown to access entities that are not lcs because they lack discourse relevance or because they are not yet in the universe of discourse.
using emoticons to reduce dependency in machine learning techniques for sentiment classification. sentiment classification seeks to identify a piece of text according to its author's general feeling toward their subject, be it positive or negative. traditional machine learning techniques have been applied to this problem with reasonable success, but they have been shown to work well only when there is a good match between the training and test data with respect to topic. this paper demonstrates that match with respect to domain and time is also important, and presents preliminary experiments with training data labeled with emoticons, which has the potential of being independent of domain, topic and time.
intention-based segmentation: human reliability and correlation with linguistic cues. certain spans of utterances in a discourse, referred to here as segments, are widely assumed to form coherent units. further, the segmental structure of discourse has been claimed to constrain and be constrained by many phenomena. however, there is weak consensus on the nature of segments and the criteria for recognizing or generating them. we present quantitative results of a two part study using a corpus of spontaneous, narrative monologues. the first part evaluates the statistical reliability of human segmentation of our corpus, where speaker intention is the segmentation criterion. we then use the subjects' segmentations to evaluate the correlation of discourse segmentation with three linguistic cues (referential noun phrases, cue words, and pauses), using information retrieval metrics.
jabot: a multilingual java-based intelligent agent for web sites. this paper presents a novel type of intelligent agent with a multilingual natural language interface, which retrieves information from within a web site. this agent, named jabot after the fact that it is a bot which has been programmed in java, has been designed and developed by the authors in an attempt to solve common web site problems related to information retrieval. jabot runs quickly and efficiently, and rather than running directly on the web site pages, it is connected to a lexical semantic map. this map is based upon the contents of the web site in question together with other associated linguistic knowledge.
a computational model of social perlocutions. the view that communication is a form of action serving a variety of specific functions has had a tremendous impact on the philosophy of language and on computational linguistics. yet, this mode of analysis has been applied to only a narrow range of exchanges (e.g. those whose primary purpose is transferring information or coordinating tasks) while exchanges meant to manage interpersonal relationships, maintain "face", or simply to convey thanks, sympathy, and so on have been largely ignored. we present a model of such "social perlocutions" that integrates previous work in natural language generation, social psychology, and communication studies. this model has been implemented in a system that generates socially appropriate e-mail in response to user-specified communicative goals.
generating the structure of argument. this paper demonstrates that generating arguments in natural language requires planning at an abstract level, and that the appropriate abstraction cannot be captured by approaches based solely upon coherence relations. an abstraction based planning system is presented which employs operators motivated by empirical study and rhetorical maxims. these operators include a subset of traditional deductive rules of inference, argumentation theoretic rules of refutation, and inductive reasoning patterns. the paper presents a unified system in which the various argument forms are employed in generating rich, complex structures for persuasive text.
an extensive empirical study of collocation extraction methods. this paper presents a status quo of an ongoing research study of collocations -- an essential linguistic phenomenon having a wide spectrum of applications in the field of natural language processing. the core of the work is an empirical evaluation of a comprehensive list of automatic collocation extraction methods using precision-recall measures and a proposal of a new approach integrating multiple basic methods and statistical classification. we demonstrate that combining multiple independent techniques leads to a significant performance improvement in comparison with individual basic methods.
learning perceptually-grounded semantics in the l project. a method is presented for acquiring perceptually-grounded semantics for spatial terms in a simple visual domain, as a part of the l0 miniature language acquisition project. two central problems in this learning task are (a) ensuring that the terms learned generalize well, so that they can be accurately applied to new scenes, and (b) learning in the absence of explicit negative evidence. solutions to these two problems are presented, and the results discussed.
combining association measures for collocation extraction. we introduce the possibility of combining lexical association measures and present empirical results of several methods employed in automatic collocation extraction. first, we present a comprehensive summary overview of association measures and their performance on manually annotated data evaluated by precision-recall graphs and mean average precision. second, we describe several classification methods for combining association measures, followed by their evaluation and comparison with individual measures. finally, we propose a feature selection algorithm significantly reducing the number of combined measures with only a small performance degradation.
the computational complexity of avoiding conversational implicatures. referring expressions and other object descriptions should be maximal under the local brevity, no unnecessary components, and lexical preference preference rules; otherwise, they may lead hearers to infer unwanted conversational implicatures. these preference rules can be incorporated into a polynomial time generation algorithm, while some alternative formalizations of conversational implicature make the generation task np-hard.
mining metalinguistic activity in corpora to create lexical resources using information extraction techniques: the mop system. this paper describes and evaluates mop, an ie system for automatic extraction of metalinguistic information from technical and scientific documents. we claim that such a system can create special databases to bootstrap compilation and facilitate update of the huge and dynamically changing glossaries, knowledge bases and ontologies that are vital to modern-day research.
using classification to generate text. the idas natural-language generation system uses a kl-one type classifier to perform content determination, surface realisation, and part of text planning. generation-by-classification allows idas to use a single representation and reasoning component for both domain and linguistic knowledge, which is difficult for systems based on unification or systemic generation techniques.
tractability and structural closures in attribute logic type signatures. this paper considers three assumptions conventionally made about signatures in typed feature logic that are in potential disagreement with current practice among grammar developers and linguists working within feature-based frameworks such as hpsg: meet-semi-latticehood, unique feature introduction, and the absence of subtype covering. it also discusses the conditions under which each of these can be tractably restored in realistic grammar signatures where they do not already exist.
using a randomised controlled clinical trial to evaluate an nlg system. the stop system, which generates personalised smoking-cessation letters, was evaluated by a randomised controlled clinical trial. we believe this is the largest and perhaps most rigorous task effectiveness evaluation ever performed on an nlg system. the detailed results of the clinical trial have been presented elsewhere, in the medical literature. in this paper we discuss the clinical trial itself: its structure and cost, what we did and did not learn from it (especially considering that the trial showed that stop was not effective), and how it compares to other nlg evaluation techniques.
generalized encoding of description spaces and its application to typed feature structures. this paper presents a new formalization of a unification- or join-preserving encoding of partially ordered sets that more essentially captures what it means for an encoding to preserve joins, generalizing the standard definition in ai research. it then shows that every statically typable ontology in the logic of typed feature structures can be encoded in a data structure of fixed size without the need for resizing or additional union-find operations. this is important for any grammar implementation or development system based on typed feature structures, as it significantly reduces the overhead of memory management and reference-pointer-chasing during unification.
summarizing multilingual spoken negotiation dialogues. we present the multilingual summarization functionality for verb-mobil, a speech translation system. we reuse resources of the system to create a summary. after content extraction, we interpret the results in the dialog context. a summary generator provides the input to generation. a first evaluation indicates the feasibility of the approach.
balancing clarity and efficiency in typed feature logic through delaying. the purpose of this paper is to re-examine the balance between clarity and efficiency in hpsg design, with particular reference to the design decisions made in the english resource grammar (lingo, 1999, erg). it is argued that a simple generalization of the conventional delay statements used in logic programming is sufficient to restore much of the functionality and concomitant benefit that the erg elected to forego, with an acceptable although still perceptible computational cost.
utilizing statistical dialogue act processing in verbmobil. in this paper, we present a statistical approach for dialogue act processing in the dialogue component of the speech-to-speech translation system verbmobil. statistics in dialogue processing is used to predict follow-up dialogue acts. as an application example we show how it supports repair when unexpected dialogue states occur.
parametric types for typed attribute-value logic. parametric polymorphism has been combined with inclusional polymorphism to provide natural type systems for prolog (dh88), hilog (yfs92), and constraint resolution languages (smo89), and, in linguistics, by hpsg-like grammars to classify lists and sets of linguistic objects (ps94), and by phonologists in representations of hierarchical structure (kle91). this paper summarizes the incorporation of parametric types into the typed attribute-value logic of (car92), thus providing a natural extension to the type system for ale (cp96). following (car92), the concern here is not with models of feature terms themselves, but with how to compute with parametric types, and what diferent kinds of information one can represent relative to a signature with parametric types, than relative to a signature without them. this enquiry has yielded a more flexible interpretation of parametric types with several specific properties necessary to conform to their current usage by linguists and implementors who work with feature-based formalisms.
a tabulation-based parsing method that reduces copying. this paper presents a new bottom-up chart parsing algorithm for prolog along with a compilation procedure that reduces the amount of copying at run-time to a constant number (2) per edge. it has applications to unification-based grammars with very large partially ordered categories, in which copying is expensive, and can facilitate the use of more sophisticated indexing strategies for retrieving such categories that may otherwise be overwhelmed by the cost of such copying. it also provides a new perspective on "quick-checking" and related heuristics, which seems to confirm that forcing an early failure (as opposed to seeking an early guarantee of success) is in fact the best approach to use. a preliminary empirical evaluation of its performance is also provided.
ontologizing semantic relations. many algorithms have been developed to harvest lexical semantic resources, however few have linked the mined knowledge into formal knowledge repositories. in this paper, we propose two algorithms for automatically ontologizing (attaching) semantic relations into wordnet. we present an empirical evaluation on the task of attaching part-of and causation relations, showing an improvement on f-score over a baseline model.
mining the web for bilingual text. strand (resnik, 1998) is a language-independent system for automatic discovery of text in parallel translation on the world wide web. this paper extends the preliminary strand results by adding automatic language identification, scaling up by orders of magnitude, and formally evaluating performance. the most recent end-product is an automatically acquired parallel corpus comprising 2491 english-french document pairs, approximately 1.5 million words per language.
a structure-sharing representation for unification-based grammar formalisms. this paper describes a structure-sharing method for the representation of complex phrase types in a parser for patr-ii, a unification-based grammar formalism.in parsers for unification-based grammar formalisms, complex phrase types are derived by incremental refinement of the phrase types defined in grammar rules and lexical entries. in a na&iuml;ve implementation, a new phrase type is built by copying older ones and then combining the copies according to the constraints stated in a grammar rule. the structure-sharing method was designed to eliminate most such copying; indeed, practical tests suggest that the use of this technique reduces parsing time by as much as 60%.the present work is inspired by the structure-sharing method for theorem proving introduced by boyer and moore and on the variant of it that is used in some prolog implementations.
the linguist's search engine: an overview. the linguist's search engine (lse) was designed to provide an intuitive, easy-to-use interface that enables language researchers to seek linguistically interesting examples on the web, based on syntactic and lexical criteria. we briefly describe its user interface and architecture, as well as recent developments that include lse search capabilities for chinese.
a calculus for semantic composition and scoping. certain restrictions on possible scopings of quantified noun phrases in natural language are usually expressed in terms of formal constraints on binding at a level of logical form. such reliance on the form rather than the content of semantic interpretations goes against the spirit of compositionality. i will show that those scoping restrictions follow from simple and fundamental facts about functional application and abstraction, and can be expressed as constraints on the derivation of possible meanings for sentences rather than constraints of the alleged forms of those meanings.
inside-outside reestimation from partially bracketed corpora. the inside-outside algorithm for inferring the parameters of a stochastic context-free grammar is extended to take advantage of constituent information (constituent bracketing) in a partially parsed corpus. experiments on formal and natural language parsed corpora show that the new algorithm can achieve faster convergence and better modeling of hierarchical structure than the original one. in particular, over 90% test set bracketing accuracy was achieved for grammars inferred by our algorithm from a training set of handparsed part-of-speech strings for sentences in the air travel information system spoken language corpus. finally, the new algorithm has better time complexity than the original one when sufficient bracketing is provided.
an automatic method of finding topic boundaries. this article outlines a new method of locating discourse boundaries based on lexical cohesion and a graphical technique called dotplotting. the application of dotplotting to discourse segmentation can be performed either manually, by examining a graph, or automatically, using an optimization algorithm. the results of two experiments involving automatically locating boundaries between a series of concatenated documents are presented. areas of application and future directions for this work are also outlined.
distributional clustering of english words. we describe and evaluate experimentally a method for clustering words according to their distribution in particular syntactic contexts. words are represented by the relative frequency distributions of contexts in which they appear, and relative entropy between those distributions is used as the similarity measure for clustering. clusters are represented by average context distributions derived from the given words according to their probabilities of cluster membership. in many cases, the clusters can be thought of as encoding coarse sense distinctions. deterministic annealing is used to find lowest distortion sets of clusters: as the annealing parameter increases, existing clusters become unstable and subdivide, yielding a hierarchical "soft" clustering of the data. clusters are used as the basis for class models of word coocurrence, and the models evaluated with respect to held-out test data.
statistical models for topic segmentation. most documents are about more than one subject, but many nlp and ir techniques implicitly assume documents have just one topic. we describe new clues that mark shifts to new topics, novel algorithms for identifying topic boundaries and the uses of such boundaries once identified. we report topic segmentation performance on several corpora as well as improvement on an ir task that benefits from good segmentation.
finite-state approximation of phrase structure grammars. phrase-structure grammars are an effective representation for important syntactic and semantic aspects of natural languages, but are computationally too demanding for use as language models in real-time speech recognition. an algorithm is described that computes finite-state approximations for context-free grammars and equivalent augmented phrase-structure grammar formalisms. the approximation is exact for certain context-free grammars generating regular languages, including all left-linear and right-linear context-free grammars. the algorithm has been used to construct finite-state language models for limited-domain speech recognition tasks.
using confidence bands for parallel texts alignment. this paper describes a language independent method for alignment of parallel texts that makes use of homograph tokens for each pair of languages. in order to filter out tokens that may cause misalignment, we use confidence bands of linear regression lines instead of heuristics which are not theoretically supported. this method was originally inspired on work done by pascale fung and kathleen mckeown, and melamed, providing the statistical support those authors could not claim.
a procedure for multi-class discrimination and some linguistic applications. the paper describes a novel computational tool for multiple concept learning. unlike previous approaches, whose major goal is prediction on unseen instances rather than the legibility of the output, our mpd (maximally parsimonious discrimination) program emphasizes the conciseness and intelligibility of the resultant class descriptions, using three intuitive simplicity criteria to this end. we illustrate mpd with applications in componential analysis (in lexicology and phonology), language typology, and speech pathology.
mindnet: acquiring and structuring semantic information from text. as a lexical knowledge base constructed automatically from the definitions and example sentences in two machine-readable dictionaries (mrds), mindnet embodies several features that distinguish it from prior work with mrds. it is, however, more than this static resource alone. mindnet represents a general methodology for acquiring, structuring, accessing, and exploiting semantic information from natural language text. this paper provides an overview of the distinguishing characteristics of mindnet, the steps involved in its creation, and its extension beyond dictionary text.
lr recursive transition networks for earley and tomita parsing. efficient syntactic and semantic parsing for ambiguous context-free languages are generally characterized as complex, specialized, highly formal algorithms. in fact, they are readily constructed from straightforward recursive transition networks (rtns). in this paper, we introduce lr-rtns, and then computationally motivate a uniform progression from basic lr parsing, to earley's (chart) parsing, concluding with tomita's parser. these apparently disparate algorithms are unified into a single implementation, which was used to automatically generate all the figures in this paper.
dependency treelet translation: syntactically informed phrasal smt. we describe a novel approach to statistical machine translation that combines syntactic information in the source language with recent advances in phrasal translation. this method requires a source-language dependency parser, target language word segmentation and an unsupervised word alignment component. we align a parallel corpus, project the source dependency parse onto the target sentence, extract dependency treelet translation pairs, and train a tree-based ordering model. we describe an efficient decoder and show that using these tree-based models in combination with conventional smt models provides a promising approach that incorporates the power of phrasal smt with the linguistic generality available in a parser.
from prosodic trees to syntactic trees. this paper describes an ongoing effort to parse the hebrew bible. the parser consults the bracketing information extracted from the cantillation marks of the masoetic text. we first constructed a cantillation treebank which encodes the prosodic structures of the text. it was found that many of the prosodic boundaries in the cantillation trees correspond, directly or indirectly, to the phrase boundaries of the syntactic trees we are trying to build. all the useful boundary information was then extracted to help the parser make syntactic decisions, either serving as hard constraints in rule application or used probabilistically in tree ranking. this has greatly improved the accuracy and efficiency of the parser and reduced the amount of manual work in building a hebrew treebank.
using machine learning to maintain rule-based named-entity recognition and classification systems. this paper presents a method that assists in maintaining a rule-based named-entity recognition and classification system. the underlying idea is to use a separate system, constructed with the use of machine learning, to monitor the performance of the rule-based system. the training data for the second system is generated with the use of the rule-based system, thus avoiding the need for manual tagging. the disagreement of the two systems acts as a signal for updating the rule-based system. the generality of the approach is illustrated by applying it to large corpora in two different languages: greek and french. the results are very encouraging, showing that this alternative use of machine learning can assist significantly in the maintenance of rule-based systems.
using machine learning to explore human multimodal clarification strategies. we investigate the use of machine learning in combination with feature engineering techniques to explore human multimodal clarification strategies and the use of those strategies for dialogue systems. we learn from data collected in a wizard-of-oz study where different wizards could decide whether to ask a clarification request in a multimodal manner or else use speech alone. we show that there is a uniform strategy across wizards which is based on multiple features in the context. these are generic runtime features which can be implemented in dialogue systems. our prediction models achieve a weighted f-score of 85.3% (which is a 25.5% improvement over a one-rule baseline). to assess the effects of models, feature discretisation, and selection, we also conduct a regression analysis. we then interpret and discuss the use of the learnt strategy for dialogue systems. throughout the investigation we discuss the issues arising from using small initial wizard-of-oz data sets, and we show that feature engineering is an essential step when learning from such limited data.
learning accurate, compact, and interpretable tree annotation. we present an automatic approach to tree annotation in which basic nonterminal symbols are alternately split and merged to maximize the likelihood of a training treebank. starting with a simple x-bar grammar, we learn a new grammar whose nonterminals are subsymbols of the original nonterminals. in contrast with previous work, we are able to split various terminals to different degrees, as appropriate to the actual complexity in the data. our grammars automatically learn the kinds of linguistic distinctions exhibited in previous work on manual tree annotation. on the other hand, our grammars are much more compact and substantially more accurate than previous work on automatic annotation. despite its simplicity, our best grammar achieves an f1 of 90.2% on the penn treebank, higher than fully lexicalized systems.
implications for generating clarification requests in task-oriented dialogues. clarification requests (crs) in conversation ensure and maintain mutual understanding and thus play a crucial role in robust dialogue interaction. in this paper, we describe a corpus study of crs in task-oriented dialogue and compare our findings to those reported in two prior studies. we find that cr behavior in task-oriented dialogue differs significantly from that in everyday conversation in a number of ways. moreover, the dialogue type, the modality and the channel quality all influence the decision of when to clarify and at which level of the grounding process. finally we identify form-function correlations which can inform the generation of crs.
learning correlations between linguistic indicators and semantic constraints: reuse of context-dependent decsriptions of entities. this paper presents the results of a study on the semantic constraints imposed on lexical choice by certain contextual indicators. we show how such indicators are computed and how correlations between them and the choice of a noun phrase description of a named entity can be automatically established using supervised learning. based on this correlation, we have developed a technique for automatic lexical choice of descriptions of entities in text generation. we discuss the underlying relationship between the pragmatics of choosing an appropriate description that serves a specific purpose in the automatically generated text and the semantics of the description itself. we present our work in the framework of the more general concept of reuse of linguistic structures that are automatically extracted from large corpora. we present a formal evaluation of our approach and we conclude with some thoughts on potential applications of our method.
verb semantics and lexical selection. this paper will focus on the semantic representation of verbs in computer systems and its impact on lexical selection problems in machine translation (mt). two groups of english and chinese verbs are examined to show that lexical selection must be based on interpretation of the sentences as well as selection restrictions placed on the verb arguments. a novel representation scheme is suggested, and is compared to representations with selection restrictions used in transfer-based mt. we see our approach as closely aligned with knowledge-based mt approaches (kbmt), and as a separate component that could be incorporated into existing systems. examples and experimental results will show that, using this scheme, inexact matches can achieve correct lexical selection.
an eclectic approach to building natural languages interfaces. inka is a natural language interface to facilitate knowledge acquisition during expert system development for electronic instrument trouble-shooting. the expert system design methodology develops a domain definition, called glib, in the form of a semantic grammar. this grammar format enables glib to be used with the inglish interface, which constrains users to create statements within a subset of english. incremental parsing in inglish allows immediate remedial information to be generated if a user deviates from the sublanguage. sentences are translated into production rules using the methodology of lexical-functional grammar. the system is written in smalltalk and, in inka, produces rules for a prolog inference engine.
parsing the wall street journal using a lexical-functional grammar and discriminative estimation techniques. we present a stochastic parsing system consisting of a lexical-functional grammar (lfg), a constraint-based parser and a stochastic disambiguation model. we report on the results of applying this system to parsing the upenn wall street journal (wsj) treebank. the model combines full and partial parsing techniques to reach full grammar coverage on unseen data. the treebank annotations are used to provide partially labeled data for discriminative statistical estimation using exponential models. disambiguation performance is evaluated by measuring matches of predicate-argument relations on two distinct test sets. on a gold standard of manually annotated f-structures for a subset of the wsj treebank, this evaluation reaches 79% f-score. an evaluation on a gold standard of dependency relations for brown corpus data achieves 76% f-score.
factorization of language constraints in speech recognition. integration of language constraints into a large vocabulary speech recognition system often leads to prohibitive complexity. we propose to factor the constraints into two components. the first is characterized by a covering grammar which is small and easily integrated into existing speech recognizers. the recognized string is then decoded by means of an efficient language post-processor in which the full set of constraints is imposed to correct possible errors introduced by the speech recognizer.
fertility models for statistical natural language understanding. several recent efforts in statistical natural language understanding (nlu) have focused on generating clumps of english words from semantic meaning concepts (miller et al., 1995; levin and pieracini, 1995; epstein et al., 1996; epstein, 1996). this paper extends the ibm machine translation group's concept of fertility (brown et al., 1993) to the generation of clumps for natural language understanding. the basic underlying intuition is that a single concept may be expressed in english as many disjoint clump of words. we present two fertility models which attempt to capture this phenomenon. the first is a poisson model which leads to appealing computational simplicity. the second is a general nonparametric fertility model. the general model's parameters are boot-strapped from the poisson model and updated by the em algorithm. these fertility models can be used to impose clump fertility structure on top of preexisting clump generation models. here, we present results for adding fertility structure to unigram, bigram, and headword clump generation models on arpa's air travel information service (atis) domain.
reversible automata and induction of the english auxiliary system. in this paper we apply some recent work of angluin (1982) to the induction of the english auxiliary verb system. in general, the induction of finite automata is computationally intractable. however, angluin shows that restricted finite automata, the k-reversible automata, can be learned by efficient (polynomial time) algoriths. can be learned by efficient (polynomial time) algorithms. we present an explicit computer model demonstrating that the english auxiliary verb system can in fact be learned as a l-reversible automaton, and hence in a computationally feasible amount of time. the entire system can be acquired by looking at only half the possible auxiliary verb sequences, and the pattern of generalization seems compatible with what is known about human acquisition of auxiliaries. we conclude that certain linguistic subsystems may well be learnable by inductive inference methods of this kind, and suggest an extension to context-free languages.
combining unsupervised lexical knowledge methods for word sense disambiguation. this paper presents a method to combine a set of unsupervised algorithms that can accurately disambiguate word senses in a large, completely untagged corpus. although most of the techniques for word sense resolution have been presented as stand-alone, it is our belief that full-fledged lexical ambiguity resolution should combine several information sources and techniques. the set of techniques have been applied in a combined way to disambiguate the genus terms of two machine-readable dictionaries (mrd), enabling us to construct complete taxonomies for spanish and french. texted accuracy is above 80% overall and 95% for two-way ambiguous genus terms, showing that texonomy building is not limited to structured dictionaries such as ldoce.
feature logic for dotted types: a formalism for complex word meanings. in this paper we revisit pustejovsky's proposal to treat ontologically complex word meaning by so-called dotted pairs. we use a higher-order feature logic based on ohori's record &lambda;-calculus to model the semantics of words like book and library, in particular their behavior in the context of quantification and cardinality statements.
transforming syntactic graphs into semantic graphs. in this paper, we present a computational method for transforming a syntactic graph, which represents all syntactic interpretations of a sentence, into a semantic graph which filters out certain interpretations, but also incorporates any remaining ambiguities. we argue that the resulting ambiguous graph, supported by an exclusion matrix, is a useful data structure for question answering and other semantic processing. our research is based on the principle that ambiguity is an inherent aspect of natural language communication.
from information structure to intonation: a phonological interface for concept-to-speech. the paper describes an interface between generator and synthesizer of the german language concept-to-speech system viectos. it discusses phenomena in german intonation that depend on the interaction between grammatical dependencies (projection of information structure into syntax) and prosodic context (performance-related modifications to intonation patterns).phonological processing in our system comprises segmental as well as suprasegmental dimensions such as syllabification, modification of word stress positions, and a symbolic encoding of intonation. phonological phenomena often touch upon more than one of these dimensions, so that mutual accessibility of the data structures on each dimension had to be ensured.we present a linear representation of the multidimensional phonological data based on a straightforward linearization convention, which suffices to bring this conceptually multilinear data set under the scope of the well-known processing techniques for two-level morphology.
computational structure of generative phonology and its relation to language comprehension. we analyze the computational complexity of phonological models as they have developed over the past twenty years. the major results are that generation and recognition are undecidable for segmental models, and that recognition is np-hard for that portion of segmental phonology subsumed by modern autosegmental models. formal restrictions are evaluated.
finding synonyms using automatic word alignment and measures of distributional similarity. there have been many proposals to extract semantically related words using measures of distributional similarity, but these typically are not able to distinguish between synonyms and other types of semantically related words such as antonyms, (co)hyponyms and hypernyms. we present a method based on automatic word alignment of parallel corpora consisting of documents translated into multiple languages and compare our method with a monolingual syntax-based method. the approach that uses aligned multilingual data to extract synonyms shows much higher precision and recall scores for the task of synonym extraction than the monolingual syntax-based approach.
new techniques for context modeling. we introduce three new techniques for statistical language models: extension modeling, nonmonotonic contexts, and the divergence heuristic. together these techniques result in language models that have few states, even fewer parameters, and low message entropies.
speech recognition of czech-inclusion of rare words helps. large vocabulary continuous speech recognition of inflective languages, such as czech, russian or serbo-croatian, is heavily deteriorated by excessive out of vocabulary rate. in this paper, we tackle the problem of vocabulary selection, language modeling and pruning for inflective languages. we show that by explicit reduction of out of vocabulary rate we can achieve significant improvements in recognition accuracy while almost preserving the model size. reported results are on czech speech corpora.
hierarchical non-emitting markov models. we describe a simple variant of the interpolated markov model with non-emitting state transitions and prove that it is strictly more powerful than any markov model. empirical results demonstrate that the non-emitting model outperforms the interpolated model on the brown corpus and on the wall street journal under a wide range of experimental conditions. the non-emitting model is also much less prone to overtraining.
assigning a semantic scope to operations. i propose that the characteristics of the scope disambiguation process observed in the literature can be explained in terms of the way in which the model of the situation described by a sentence is built. the model construction procedure i present builds an event structure by identifying the situations associated with the operators in the sentence and their mutual dependency relations, as well as the relations between these situations and other situations in the context. the procedure takes into account lexical semantics and the result of various discourse interpretation procedures such as definite description interpretation, and does not require a complete disambiguation to take place.
markov parsing: lattice rescoring with a statistical parser. we present a generalization of an incremental statistical parsing algorithm that allows for the re-scoring of lattices of word hypotheses, for use by a speech recognizer. this approach contrasts with other lattice parsing algorithms, which either do not provide scores for strings in the lattice (i.e. they just produce parse trees) or use search techniques (e.g. a-star) to find the best paths through the lattice, without re-scoring every arc. we show that a very large efficiency gain can be had in processing 1000-best lists without reducing word accuracy when the lists are encoded in lattices instead of trees. further, this allows for processing arbitrary lattices without n-best extraction. this can lead to more interesting methods of combination with other models, both acoustic and language, through, for example, adaptation or confusion matrices.
specifying the parameters of centering theory: a corpus-based evaluation using text from application-oriented domains. the definitions of the basic concepts, rules, and constraints of centering theory involve underspecified notions such as 'previous utterance', 'realization', and 'ranking'. we attempted to find the best way of defining each such notion among those that can be annotated reliably, and using a corpus of texts in two domains of practical interest. our main result is that trying to reduce the number of utterances without a backward-looking center (cb) results in an increased number of cases in which some discourse entity, but not the cb, gets pronominalized, and viceversa.
learning to resolve bridging references. we use machine learning techniques to find the best combination of local focus and lexical distance features for identifying the anchor of mereological bridging references. we find that using first mention, utterance distance, and lexical distance computed using either google or wordnet results in an accuracy significantly higher than obtained in previous experiments.
efficient probabilistic top-down and left-corner parsing. this paper examines efficient predictive broad, coverage parsing without dynamic programming. in contrast to bottom-up methods, depth-first top-down parsing produces partial parses that are fully connected trees spanning the entire left context, from which any kind of non-local dependency or partial semantic interpretation can in principle be read. we contrast two predictive parsing approaches, top-down and left-corner parsing, and find both to be viable. in addition, we find that enhancement with non-local information not only improves parser accuracy, but also substantially improves the search efficiency.
an integrated framework for semantic and pragmatic interpretation. we report on a mechanism for semantic and pragmatic interpretation that has been designed to take advantage of the generally compositional nature of semantic analysis, without unduly constraining the order in which pragmatic decisions are made. to achieve this goal, we introduce the idea of a conditional interpretation: one that depends upon a set of assumptions about subsequent pragmatic processing. conditional interpretations are constructed compositionally according to a set of declaratively specified interpretation rules. the mechanism can handle a wide range of pragmatic phenomena and their interactions.
lexnet: a graphical environment for graph-based nlp. this interactive presentation describes lexnet, a graphical environment for graph-based nlp developed at the university of michigan. lexnet includes lexrank (for text summarization), biased lexrank (for passage retrieval), and tumbl (for binary classification). all tools in the collection are based on random walks on lexical graphs, that is graphs where different nlp objects (e.g., sentences or phrases) are represented as nodes linked by edges proportional to the lexical similarity between the two nodes. we will demonstrate these tools on a variety of nlp tasks including summarization, question answering, and prepositional phrase attachment.
utilizing co-occurrence of answers in question answering. in this paper, we discuss how to utilize the co-occurrence of answers in building and automatic question answering system that answers a series of questions on a specific topic in a batch mode. experiments show that the answers to the many of the questions in the series usually have a high degree of co-occurrence in relevant document passages. this feature sometimes can't be easily utilized in an automatic qa system which processes questions independently. however it can be utilized in a qa system that processes questions in a batch mode. we have used our pervious trec qa system as baseline and augmented it with new answer clustering and co-occurrence maximization components to build the batch qa system. the experiment results show that the qa system running under the batch mode get significant performance improvement over our baseline trec qa system.
reference resolution beyond coreference: a conceptual frame and its application. a model for reference use in communication is proposed, from a representationist point of view. both the sender and the receiver of a message handle representations of their common environment, including mental representations of objects. reference resolution by a computer is viewed as the construction of object representations using referring expressions from the discourse, whereas often only coreference links between such expressions are looked for. differences between these two approaches are discussed.the model has been implemented with elementary rules, and tested on complex narrative texts (hundreds to thousands of referring expressions). the results support the mental representations paradigm.
discriminative language modeling with conditional random fields and the perceptron algorithm. this paper describes discriminative language modeling for a large vocabulary speech recognition task. we contrast two parameter estimation methods: the perceptron algorithm, and a method based on conditional random fields (crfs). the models are encoded as deterministic weighted finite state automata, and are applied by intersecting the automata with word-lattices that are the output from a baseline recognizer. the perceptron algorithm has the benefit of automatically selecting a relatively small feature set in just a couple of passes over the training data. however, using the feature set output from the perceptron algorithm (initialized with their weights), crf training provides an additional 0.5% reduction in word error rate, for a total 1.8% absolute reduction from the baseline of 39.2%.
tree unification grammar. tree unification grammar is a declarative unification-based linguistic framework. the basic grammar structures of this framework are partial descriptions of trees, and the framework requires only a single grammar rule to combine these partial descriptions. using this framework, constraints associated with various linguistic phenomena (reflexivisation in particular) can be stated succinctly in the lexicon.
learning meronyms from biomedical text. the part-whole relation is of special importance in biomedicine: structure and process are organised along partitive axes. anatomy, for example, is rich in part-whole relations. this paper reports preliminary experiments on part-whole extraction from a corpus of anatomy definitions, using a fully automatic iterative algorithm to learn simple lexico-syntactic patterns from multiword terms. the experiments show that meronyms can be extracted using these patterns. a failure analysis points out factors that could contribute to improvements in both precision and recall, including pattern generalisation, pattern pruning, and term matching. the analysis gives insights into the relationship between domain terminology and lexical relations, and into evaluation strategies for relation learning.
learning information structure in the prague treebank. this paper investigates the automatic identification of aspects of information structure (is) in texts. the experiments use the prague dependency treebank which is annotated with is following the praguian approach of topic focus articulation. we automatically detect t(opic) and f(ocus), using node attributes from the treebank as basic features and derived features inspired by the annotation guidelines. we show the performance of c4.5, bagging, and ripper classifiers on several classes of instances such as nouns and pronouns, only nouns, only pronouns. a baseline system assigning always f(ocus) has an f-score of 42.5%. our best system obtains 82.04%.
evaluating the portability of revision rules for incremental summary generation. this paper presents a quantitative evaluation of the portability to the stock market domain of the revision rule hierarchy used by the system streak to incrementally generate newswire sports summaries. the evaluation consists of searching a test corpus of stock market reports for sentence pairs whose (semantic and syntactic) structures respectively match the triggering condition and application result of each revision rule. the results show that at least 59% of all rule classes are fully portable, with at least another 7% partially portable.
multilingual authoring using feedback texts. there are obvious reasons for trying to automate the production of multilingual documentation, especially for routine subject-matter in restricted domains (e.g. technical instructions). two approaches have been adopted: machine translation (mt) of a source text, and multilingual natural language generation (m-nlg) from a knowledge base. for mt, information extraction is a major difficulty, since the meaning must be derived by analysis of the source text; m-nlg avoids this difficulty but seems at first sight to require an expensive phase of knowledge engineering in order to encode the meaning. we introduce here a new technique which employs m-nlg during the phase of knowledge editing. a 'feedback text', generated from a possibly incomplete knowledge base, describes in natural language the knowledge encoded so far, and the options for extending it. this method allows anyone speaking one of the supported languages to produce texts in all of them, requiring from the author only expertise in the subject-matter, not expertise in knowledge engineering.
an efficient generation algorithm for lexicalist mt. the lexicalist approach to machine translation offers significant advantages in the development of linguistic descriptions. however, the shake-and-bake generation algorithm of (whitelock, 1992) is np-complete. we present a polynomial time algorithm for lexicalist mt generation provided that sufficient information can be transferred to ensure more determinism.
evaluation challenges in large-scale document summarization. we present a large-scale meta evaluation of eight evaluation measures for both single-document and multi-document summarizers. to this end we built a corpus consisting of (a) 100 million automatic summaries using six summarizers and baselines at ten summary lengths in both english and chinese, (b) more than 10,000 manual abstracts and extracts, and (c) 200 million automatic document and summary retrievals using 20 queries. we present both qualitative and quantitative results showing the strengths and draw-backs of all evaluation methods and how they rank the different summarizers.
practical glossing by prioritised tining. we present the design of a practical context-sensitive glosser, incorporating current techniques for lightweight linguistic analysis based on large-scale lexical resources. we outline a general model for ranking the possible translations of the words and expressions that make up a text. this information can be used by a simple resource-bounded algorithm, of complexity o(n log n) in sentence length, that determines a consistent gloss of best translations. we then describe how the results of the general ranking model may be approximated using a simple heuristic prioritisation scheme. finally we present a preliminary evaluation of the glosser's performance.
semantic role labeling using different syntactic views. semantic role labeling is the process of annotating the predicate-argument structure in text with semantic labels. in this paper we present a state-of-the-art baseline semantic role labeling system based on support vector machine classifiers. we show improvements on this system by: i) adding new features including features extracted from dependency parses, ii) performing feature selection and calibration and iii) combining parses obtained from semantic parsers trained using different syntactic views. error analysis of the baseline system showed that approximately half of the argument identification errors resulted from parse errors in which there was no syntactic constituent that aligned with the correct argument. in order to address this problem, we combined semantic parses from a minipar syntactic parse and from a chunked syntactic representation with our original baseline system which was based on charniak parses. all of the reported techniques resulted in performance improvements.
question answering using constraint satisfaction: qa-by-dossier-with-contraints. qa-by-dossier-with-constraints is a new approach to question answering whereby candidate answers' confidences are adjusted by asking auxiliary questions whose answers constrain the original answers. these constraints emerge naturally from the domain of interest, and enable application of real-world knowledge to qa. we show that our approach significantly improves system performance (75% relative improvement in f-measure on select question types) and can create a "dossier" of information about the subject matter in the original question.
a morphologically sensitive clustering algorithm for identifying arabic roots. we present a clustering algorithm for arabic words sharing the same root. root based clusters can substitute dictionaries in indexing for ir. modifying adamson and boreham (1974), our two-stage algorithm applies light stemming before calculating word pair similarity coefficients using techniques sensitive to arabic morphology. tests show a successful treatment of infixes and accurate clustering to up to 94.06% for unedited arabic text samples, without the use of dictionaries.
improving qa accuracy by question inversion. this paper demonstrates a conceptually simple but effective method of increasing the accuracy of qa systems on factoid-style questions. we define the notion of an inverted question, and show that by requiring that the answers to the original and inverted questions be mutually consistent, incorrect answers get demoted in confidence and correct ones promoted. additionally, we show that lack of validation can be used to assert no-answer (nil) conditions. we demonstrate increases of performance on trec and other question-sets, and discuss the kinds of future activities that can be particularly beneficial to approaches such as ours.
unsupervised learning of arabic stemming using a parallel corpus. this paper presents an unsupervised learning approach to building a non-english (arabic) stemmer. the stemming model is based on statistical machine translation and it uses an english stemmer and a small (10 k sentences) parallel corpus as its sole training resources. no parallel text is needed after the training phase. monolingual, unannotated text can be used to further improve the stemmer by allowing it to adapt to a desired domain or genre. examples and results will be given for arabic, but the approach is applicable to any language that needs affix removal. our resource-frugal approach results in 87.5% agreement with a state of the art, proprietary arabic stemmer built using rules, affix lists, and human annotated text, in addition to an unsupervised component. task-based evaluation using arabic information retrieval indicates an improvement of 22-38% in average precision over unstemmed text, and 96% of the performance of the proprietary stemmer above.
an information structural approach to spoken language generation. this paper presents an architecture for the generation of spoken monologues with contextually appropriate intonation. a two-tiered information structure representation is used in the high-level content planning and sentence planning stages of generation to produce efficient, coherent speech that makes certain discourse relationships, such as explicit contrasts, appropriately salient. the system is able to produce appropriate intonational patterns that cannot be generated by other systems which rely solely on word class and given/new distinctions.
wrapping of trees. we explore the descriptive power, in terms of syntactic phenomena, of a formalism that extends tree-adjoining grammar (tag) by adding a fourth level of hierarchical decomposition to the three levels tag already employs. while extending the descriptive power minimally, the additional level of decomposition allows us to obtain a uniform account of a range of phenomena that has heretofore been difficult to encompass, an account that employs unitary elementary structures and eschews synchronized derivation operations, and which is, in many respects, closer to the spirit of the intuitions underlying tag-based linguistic theory than previously considered extensions to tag.
capturing cfls with tree adjoining grammars. we define a decidable class of tags that is strongly equivalent to cfgs and is cubic-time parsable. this class serves to lexicalize cfgs in the same manner as the lcfgs of schabes and waters but with considerably less restriction on the form of the grammars. the class provides a normal form for tags that generate local sets in much the same way that regular grammars provide a normal form for cfgs that generate regular sets.
an intelligent multi-dictionary environment. an open, extendible multi-dictionary system is introduced in the paper. it supports the translator in accessing adequate entries of various bi- and monolingual dictionaries and translation examples from parallel corpora. simultaneously an unlimited number of dictionaries can be held open, thus by a single interrogation step, all the dictionaries (translations, explanations, synonyms, etc.) can be surveyed. the implemented system (called mobidic) knows morphological rules of the dictionaries' languages. thus, never the actual (inflected) words, but always their lemmas-that is, the right dictionary entries-are looked up. mobidic has an open, multimedial architecture, thus it is suitable for handling not only textual, but speaking or picture dictionaries, as well. the same system is also able to find words and expressions in corpora, dynamically providing the translators with examples from their earlier translations or other translators' works. mobidic has been designed for translator workgroups, where the translators' own glossaries (built also with the help of the system) may also be disseminated among the members of the group, with different access rights, if needed. the system has a tcp/ip-based client-server implementation for various platforms and available with a gradually increasing number of dictionaries for numerous language pairs.
a model-theoretic framework for theories of syntax. a natural next step in the evolution of constraint-based grammar formalisms from rewriting formalisms is to abstract fully away from the details of the grammar mechanism---to express syntactic theories purely in terms of the properties of the class of structures they license. by focusing on the structural properties of languages rather than on mechanisms for generating or checking structures that exhibit those properties, this model-theoretic approach can offer simpler and significantly clearer expression of theories and can potentially provide a uniform formalization, allowing disparate theories to be compared on the basis of those properties. we discuss l2k, p, a monadic second-order logical framework for such an approach to syntax that has the distinctive virtue of being superficially expressive---supporting direct statement of most linguistically significant syntactic properties---but having well-defined strong generative capacity---languages are definable in l2k, p iff they are strongly context-free. we draw examples from the realms of gpsg and gb.
a unification-based approach to morpho-syntactic parsing of agglutinative and other (highly) inflectional languages. this paper introduces a new approach to morpho-syntactic analysis through humor 99 (<u>h</u>igh-speed <u>u</u>nification <u>mor</u>phology), a reversible and unification-based morphological analyzer which has already been integrated with a variety of industrial applications. humor 99 successfully copes with problems of agglutinative (e.g. hungarian, turkish, estonian) and other (highly) inflectional languages (e.g. polish, czech, german) very effectively. the authors conclude the paper by arguing that the approach used in humor 99 is general enough to be well suitable for a wide range of languages, and can serve as basis for higher-level linguistic operations such as shallow parsing.
a descriptive characterization of tree-adjoining languages (project note). since the early sixties and seventies it has been known that the regular and context-free languages are characterized by definability in the monadic second-order theory of certain structures. more recently, these descriptive characterizations have been used to obtain complexity results for constraint- and principle-based theories of syntax and to provide a uniform model-theoretic framework for exploring the relationship between theories expressed in disparate formal terms. these results have been limited, to an extent, by the lack of descriptive characterizations of language classes beyond the context-free. recently, we have shown that tree-adjoining languages (in a mildly generalized form) can be characterized by recognition by automata operating on three-dimensional tree manifolds, a three-dimensional analog of trees. in this paper, we exploit these automata-theoretic results to obtain a characterization of the tree-adjoining languages by definability in the monadic second-order theory of these three-dimensional tree manifolds. this not only opens the way to extending the tools of model-theoretic syntax to the level of tals, but provides a highly flexible mechanism for defining tags in terms of logical constraints.
parsing head-driven phrase structure grammar. the head-driven phrase structure grammar project (hpsg) is an english language database query system under development at hewlett-packard laboratories. unlike other product-oriented efforts in the natural language understanding field, the hpsg system was designed and implemented by linguists on the basis of recent theoretical developments. but, unlike other implementations of linguistic theories, this system is not a toy, as it deals with a variety of practical problems not covered in the theoretical literature. we believe that this makes the hpsg system unique in its combination of linguistic theory and practical application.the hpsg system differs from its predecessor gpsg, reported on at the 1982 acl meeting (gawron et al. ([1982]), in four significant respects: syntax, lexical representation, parsing, and semantics. the paper focuses on parsing issues, but also gives a synopsis of the underlying syntactic formalism.
reasoning with descriptions of trees. in this paper we introduce a logic for describing trees which allows us to reason about both the parent and domination relationship. the use of domination has found a number of applications, such as in deterministic parsers based on description theory (marcus, hindle & fleck, 1983), in a compact organization of the basic structures of tree-adjoining grammars (vijay-shanker & schabes, 1992), and in a new characterization of the adjoining operation that allows a clean integration of tags into the unification-based framework (vijay-shanker, 1992) our logic serves to formalize the reasoning on which these applications are based.
a generative lexicon perspective for adjectival modification. this paper presents a semantic interpretation of adjectival modification in terms of the generative lexicon. it highlights the elements which can be borrowed from the gl and develops limitations and extensions. we show how elements of the qualia structure can be incorporated into semantic composition rules to make explicit the semantics of the combination adjective + noun.
how verb subcategorization frequencies are affected by corpus choice. the probabilistic relation between verbs and their arguments plays an important role in modern statistical parsers and supertaggers, and in psychological theories of language processing. but these probabilities are computed in very different ways by the two sets of researchers. computational linguists compute verb subcategorization probabilities from large corpora while psycholinguists compute them from psychological studies (sentence production and completion tasks). recent studies have found differences between corpus frequencies and psycholinguistic measures. we analyze subcategorization frequencies from four different corpora: psychological sentence production data (connine et al. 1984), written text (brown and wsj), and telephone conversation data (switchboard). we find two different sources for the differences. discourse influence is a result of how verb use is affected by different discourse types such as narrative, connected discourse, and single sentence productions. semantic influence is a result of different corpora using different senses of verbs, which have different subcategorization frequencies. we conclude that verb sense and discourse type play an important role in the frequencies observed in different experimental and corpus based sources of verb subcategorization frequencies.
classifying semantic relations in bioscience texts. a crucial step toward the goal of automatic extraction of propositional information from natural language text is the identification of semantic relations between constituents in sentences. we examine the problem of distinguishing among seven relation types that can occur between the entities "treatment" and "disease" in bioscience text, and the problem of identifying such entities. we compare five generative graphical models and a neural network, using lexical, syntactic, and semantic features, finding that the latter help achieve high classification accuracy.
the descent of hierarchy, and selection in relational semantics. in many types of technical texts, meaning is embedded in noun compounds. a language understanding program needs to be able to interpret these in order to ascertain sentence meaning. we explore the possibility of using an existing lexical hierarchy for the purpose of placing words from a noun compound into categories, and then using this category membership to determine the relation that holds between the nouns. in this paper we present the results of an analysis of this method on two-word noun compounds from the biomedical domain, obtaining classification accuracy of approximately 90%. since lexical hierarchies are not necessarily ideally suited for this task, we also pose the question: how far down the hierarchy must the algorithm descend before all the terms within the subhierarchy behave uniformly with respect to the semantic relation in question? we find that the topmost levels of the hierarchy yield an accurate classification, thus providing an economic way of assigning relations to noun compounds.
discourse processing of dialogues with multiple threads. in this paper we will present our ongoing work on a plan-based discourse processor developed in the context of the enthusiast spanish to english translation system as part of the janus multi-lingual speech-to-speech translation system. we will demonstrate that theories of discourse which postulate a strict tree structure of discourse on either the intentional or attentional level are not totally adequate for handling spontaneous dialogues. we will present our extension to this approach along with its implementation in our plan-based discourse processor. we will demonstrate that the implementation of our approach outperforms an implementation based on the strict tree structure approach.
an interactive domain independent approach to robust dialogue interpretation. we discuss an interactive approach to robust interpretation in a large scale speech-to-speech translation system. where other interactive approaches to robust interpretation have depended upon domain dependent repair rules, the approach described here operates efficiently without any such hand-coded repair knowledge and yields a 37% reduction in error rate over a corpus of noisy sentences.
identifying relevant prior explanations. when human tutors engage in dialogue, they freely exploit all aspects of the mutually known context, including the previous discourse. utterances that do not draw on previous discourse seem awkward, unnatural, or even incoherent. previous discourse must be taken into account in order to relate new information effectively to recently conveyed material, and to avoid repeating old material that would distract the student from what is new.producing a system that displays such behavior involves finding an efficient way to identify which previous explanations (if any) are relevant to the current explanation task. thus, we are implementing a system that uses a case-based reasoning approach to identify previous situations and explanations that could potentially affect the explanation being constructed. we have identified heuristics for constructing explanations that exploit this information in ways similar to what we have observed in human-human tutorial dialogues.
ures : an unsupervised web relation extraction system. most information extraction systems either use hand written extraction patterns or use a machine learning algorithm that is trained on a manually annotated corpus. both of these approaches require massive human effort and hence prevent information extraction from becoming more widely applicable. in this paper we present ures (unsupervised relation extraction system), which extracts relations from the web in a totally unsupervised way. it takes as input the descriptions of the target relations, which include the names of the predicates, the types of their attributes, and several seed instances of the relations. then the system downloads from the web a large collection of pages that are likely to contain instances of the target relations. from those pages, utilizing the known seed instances, the system learns the relation patterns, which are then used for extraction. we present several experiments in which we learn patterns and extract instances of a set of several common ie relations, comparing several pattern learning and filtering setups. we demonstrate that using simple noun phrase tagger is sufficient as a base for accurate patterns. however, having a named entity recognizer, which is able to recognize the types of the relation attributes significantly, enhances the extraction performance. we also compare our approach with knowitall's fixed generic patterns.
dependencies between student state and speech recognition problems in spoken tutoring dialogues. speech recognition problems are a reality in current spoken dialogue systems. in order to better understand these phenomena, we study dependencies between speech recognition problems and several higher level dialogue factors that define our notion of student state: frustration/anger, certainty and correctness. we apply chi square (x2) analysis to a corpus of speech-based computer tutoring dialogues to discover these dependencies both within and across turns. significant dependencies are combined to produce interesting insights regarding speech recognition problems and to propose new strategies for handling these problems. we also find that tutoring, as a new domain for speech applications, exhibits interesting tradeoffs and new factors to consider for spoken dialogue design.
part of speech tagging using a network of linear separators. we present an architecture and an on-line learning algorithm and apply it to the problem of part-of-speech tagging. the architecture presented, snow, is a network of linear separators in the feature space, utilizing the winnow update algorithm.multiplicative weight-update algorithms such as winnow have been shown to have exceptionally good behavior when applied to very high dimensional problems, and especially when the target concepts depend on only a small subset of the features in the feature space. in this paper we describe an architecture that utilizes this mistake-driven algorithm for multi-class prediction-selecting the part of speech of a word. the experimental analysis presented here provides more evidence to that these algorithms are suitable for natural language problems.the algorithm used is an on-line algorithm: every example is used by the algorithm only once, and is then discarded. this has significance in terms of efficiency, as well as quick adaptation to new contexts.we present an extensive experimental study of our algorithm under various conditions; in particular, it is shown that the algorithm performs comparably to the best known algorithms for pos.
prosodic aids to syntactic and semantic analysis of spoken english. prosody can be useful in resolving certain lexical and structural ambiguities in spoken english. in this paper we present some results of employing two types of prosodic information, namely pitch and pause, to assist syntactic and semantic analysis during parsing.
spoken dialogue management using probabilistic reasoning. spoken dialogue managers have benefited from using stochastic planners such as markov decision processes (mdps). however, so far, mdps do not handle well noisy and ambiguous speech utterances. we use a partially observable markov decision process (pomdp)-style approach to generate dialogue strategies by inverting the notion of dialogue state; the state represents the user's intentions, rather than the system state. we demonstrate that under the same noisy conditions, a pomdp dialogue manager makes fewer mistakes than an mdp dialogue manager. furthermore, as the quality of speech recognition degrades, the pomdp dialogue manager automatically adjusts the policy.
automatic generation of domain models for call-centers from noisy transcriptions. call centers handle customer queries from various domains such as computer sales and support, mobile phones, car rental, etc. each such domain generally has a domain model which is essential to handle customer complaints. these models contain common problem categories, typical customer issues and their solutions, greeting styles. currently these models are manually created over time. towards this, we propose an unsupervised technique to generate domain models automatically from call transcriptions. we use a state of the art automatic speech recognition system to transcribe the calls between agents and customers, which still results in high word error rates (40%) and show that even from these noisy transcriptions of calls we can automatically build a domain model. the domain model is comprised of primarily a topic taxonomy where every node is characterized by topic(s), typical questions-answers (q&as), typical actions and call statistics. we show how such a domain model can be used for topic identification of unseen calls. we also propose applications for aiding agents while handling calls and for agent monitoring based on the domain model.
argumentative feedback: a linguistically-motivated term expansion for information retrieval. we report on the development of a new automatic feedback model to improve information retrieval in digital libraries. our hypothesis is that some particular sentences, selected based on argumentative criteria, can be more useful than others to perform well-known feedback information retrieval tasks. the argumentative model we explore is based on four disjunct classes, which has been very regularly observed in scientific reports: purpose, methods, results, conclusion. to test this hypothesis, we use the rocchio algorithm as baseline. while rocchio selects the features to be added to the original query based on statistical evidence, we propose to base our feature selection also on argumentative criteria. thus, we restrict the expansion on features appearing only in sentences classified into one of our argumentative categories. our results, obtained on the ohsumed collection, show a significant improvement when expansion is based on purpose (mean average precision = +23%) and conclusion (mean average precision = +41%) contents rather than on other argumentative contents. these results suggest that argumentation is an important linguistic dimension that could benefit information retrieval.
clavius: bi-directional parsing for generic multimodal interaction. we introduce a new multi-threaded parsing algorithm on unification grammars designed specifically for multimodal interaction and noisy environments. by lifting some traditional constraints, namely those related to the ordering of constituents, we overcome several difficulties of other systems in this domain. we also present several criteria used in this model to constrain the search process using dynamically loadable scoring functions. some early analyses of our implementation are discussed.
a domain-specific statistical surface realizer. we present a search-based approach to automatic surface realization given a corpus of domain sentences. using heuristic search based on a statistical language model and a structure we introduce called an inheritance table we overgenerate a set of complete syntactic-semantic trees that are consistent with the given semantic structure and have high likelihood relative to the language model. these trees are then lexicalized, linearized, scored, and ranked. this model is being developed to generate real-time navigation instructions.
multipe default inheritance in a unification-based lexicon. a formalism is presented for lexical specification in unification-based grammars which exploits defeasible multiple inheritance to express regularity, sub-regularity, and exceptions in classifying the properties of words. such systems are in the general case intractable; the present proposal represents an attempt to reduce complexity while retaining sufficient expressive power for the task at hand. illustrative examples are given of morphological analyses from english and german.
asymmetry in parsing and generating with unification grammars: case studies from elu. recent developments in generation algorithms have enabled work in unification-based computational linguistics to approach more closely the ideal of grammars as declarative statements of linguistic facts, neutral between analysis and synthesis. from this perspective, however, the situation is still far from perfect; all known methods of generation impose constraints on the grammars they assume.we briefly consider a number of proposals for generation, outlining their consequences for the form of grammars, and then report on experience arising from the addition of a generator to an existing unification environment. the algorithm in question (based on that of shieber et al. (1989)), though among the most permissive currently available, excludes certain classes of parsable analyses.
simultaneous english-japanese spoken language translation based on incremental dependency parsing and transfer. this paper proposes a method for incrementally translating english spoken language into japanese. to realize simultaneous translation between languages with different word order, such as english and japanese, our method utilizes the feature that the word order of a target language is flexible. to resolve the problem of generating a grammatically incorrect sentence, our method uses dependency structures and japanese dependency constraints to determine the word order of a translation. moreover, by considering the fact that the inversion of predicate expressions occurs more frequently in japanese spoken language, our method takes advantage of a predicate inversion to resolve the problem that japanese has the predicate at the end of a sentence. furthermore, our method includes the function of canceling an inversion by restating a predicate when the translation is incomprehensible due to the inversion. we implement a prototype translation system and conduct an experiment with all 578 sentences in the atis corpus. the results indicate improvements in comparison to two other methods.
towards a cognitively plausible model for quantification. the purpose of this paper is to suggest that quantifiers in natural languages do not have a fixed truth functional meaning as has long been held in logical semantics. instead we suggest that quantifiers can best be modeled as complex inference procedures that are highly dynamic and sensitive to the linguistic context, as well as time and memory constraints.
combination of arabic preprocessing schemes for statistical machine translation. statistical machine translation is quite robust when it comes to the choice of input representation. it only requires consistency between training and testing. as a result, there is a wide range of possible preprocessing choices for data used in statistical machine translation. this is even more so for morphologically rich languages such as arabic. in this paper, we study the effect of different word-level preprocessing schemes for arabic on the quality of phrase-based statistical machine translation. we also present and evaluate different methods for combining preprocessing schemes resulting in improved translation quality.
a best-first probabilistic shift-reduce parser. recently proposed deterministic classifier-based parsers (nivre and scholz, 2004; sagae and lavie, 2005; yamada and mat-sumoto, 2003) offer attractive alternatives to generative statistical parsers. deterministic parsers are fast, efficient, and simple to implement, but generally less accurate than optimal (or nearly optimal) statistical parsers. we present a statistical shift-reduce parser that bridges the gap between deterministic and probabilistic parsers. the parsing model is essentially the same as one previously used for deterministic parsing, but the parser performs a best-first search instead of a greedy search. using the standard sections of the wsj corpus of the penn treebank for training and testing, our parser has 88.1% precision and 87.8% recall (using automatically assigned part-of-speech tags). perhaps more interestingly, the parsing model is significantly different from the generative models used by other well-known accurate parsers, allowing for a simple combination that produces precision and recall of 90.9% and 90.7%, respectively.
automatic measurement of syntactic development in child language. to facilitate the use of syntactic information in the study of child language acquisition, a coding scheme for grammatical relations (grs) in transcripts of parent-child dialogs has been proposed by sagae, macwhinney and lavie (2004). we discuss the use of current nlp techniques to produce the grs in this annotation scheme. by using a statistical parser (charniak, 2000) and memory-based learning tools for classification (daelemans et al., 2004), we obtain high precision and recall of several grs. we demonstrate the usefulness of this approach by performing automatic measurements of syntactic development with the index of productive syntax (scarborough, 1990) at similar levels to what child language researchers compute manually.
using linguistic knowledge in automatic abstracting. we present work on the automatic generation of short indicative-informative abstracts of scientific and technical articles. the indicative part of the abstract identifies the topics of the document while the informative part of the abstract elaborate some topics according to the reader's interest by motivating the topics, describing entities and defining concepts. we have defined our method of automatic abstracting by studying a corpus professional abstracts. the method also considers the reader's interest as essential in the process of abstracting.
how do we count? the problem of tagging phrasal verbs in parts. this paper examines the current performance of the stochastic tagger parts (church 88) in handling phrasal verbs, describes a problem that arises from the statistical model used, and suggests a way to improve the tagger's performance. the solution involves a change in the definition of what counts as a word for the purpose of tagging phrasal verbs.
a word-order database for testing computational models of language acquisition. an investment of effort over the last two years has begun to produce a wealth of data concerning computational psycholinguistic models of syntax acquisition. the data is generated by running simulations on a recently completed database of word order patterns from over 3,000 abstract languages. this article presents the design of the database which contains sentence patterns, grammars and derivations that can be used to test acquisition models from widely divergent paradigms. the domain is generated from grammars that are linguistically motivated by current syntactic theory and the sentence patterns have been validated as psychologically/developmentally plausible by checking their frequency of occurrence in corpora of child-directed speech. a small case-study simulation is also presented.
syntactic approaches to automatic book indexing. automatic book indexing systems are based on the generation of phrase structures capable of reflecting text content. some approaches are given for the automatic construction of back-of-book indexes using a syntactic analysis of the available texts, followed by the identification of nominal constructions, the assignment of importance weights to the term phrases, and the choice of phrases as indexing units.
generalized augmented transition network grammars for generation from semantic networks. the augmented transition network (atn) is a formalism for writing parsing grammars that has been much used in artificial intelligence and computational linguistics. a few researchers have also used atns for writing grammars for generating sentences. previously, however, either generation atns did not have the same semantics as parsing atns, or they required an auxiliary mechanism to determine the syntactic structure of the sentence to be generated. this paper reports a generalization of the atn formalism that allows atn grammars to be written to parse labelled directed graphs. specifically, an atn grammar can be written to parse a semantic network and generate a surface string as its analysis. an example is given of a combined parsing-generating grammar that parses surface sentences, builds and queries a semantic network knowledge representation, and generates surface sentences in response.
on the existence of primitive meaning units. knowledge representation schemes are either based on a set of primitives or not. the decision of whether or not to have a primitive-based scheme is crucial since it affects the knowledge that is stored and how that knowledge may be processed. we suggest that a knowledge representation scheme may not initially have primitives, but may evolve into a primitive-based scheme by inferring a set of primitive meaning units based on previous experience. we describe a program that infers its own primitive set and discuss how the inferred primitives may affect the organization of existing information and the subsequent incorporation of new information.
using comparable corpora to solve problems difficult for human translators. in this paper we present a tool that uses comparable corpora to find appropriate translation equivalents for expressions that are considered by translators as difficult. for a phrase in the source language the tool identifies a range of possible expressions used in similar contexts in target language corpora and presents them to the translator as a list of suggestions. in the paper we discuss the method and present results of human evaluation of the performance of the tool, which highlight its usefulness when dictionary solutions are lacking.
dialogue act tagging with transformation-based learning. for the task of recognizing dialogue acts, we are applying the transformation-based learning (tbl) machine learning algorithm. to circumvent a sparse data problem, we extract values of well-motivated features of utterances, such as speaker direction, punctuation marks, and a new feature, called dialogue act cues, which we find to be more effective than cue phrases and word n-grams in practice. we present strategies for constructing a set of dialogue act cues automatically by minimizing the entropy of the distribution of dialogue acts in a training corpus, filtering out irrelevant dialogue act cues, and clustering semantically-related words. in addition, to address limitations of tbl, we introduce a monte carlo strategy for training efficiently and a committee method for computing confidence measures. these ideas are combined in our working implementation, which labels held-out data as accurately as any other reported system for the dialogue act tagging task.
grammar specialization through entropy thresholds. explanation-based generalization is used to extract a specialized grammar from the original one using a training corpus of parse trees. this allows very much faster parsing and gives a lower error rate, at the price of a small loss in coverage. previously, it has been necessary to specify the tree-cutting criteria (or operationality criteria) manually; here they are derived automatically from the training set and the desired coverage of the specialized grammar. this is done by assigning an entropy value to each node in the parse trees and cutting in the nodes with sufficiently high entropy values.
conciseness through aggregation in text generation. aggregating different pieces of similar information is necessary to generate concise and easy to understand reports in technical domains. this paper presents a general algorithm that combines similar messages in order to generate one or more coherent sentences for them. the process is not as trivial as might be expected. problems encountered are briefly described.
comparing a linguistic and a stochastic tagger. concerning different approaches to automatic pos tagging: engcg-2, a constraint-based morphological tagger, is compared in a double-blind test with a state-of-the-art statistical tagger on a common disambiguation task using a common tag set. the experiments show that for the same amount of remaining ambiguity, the error rate of the statistical tagger is one order of magnitude greater than that of the rule-based one. the two related issues of priming effects compromising the results and disagreement between human annotators are also addressed.
segregatory coordination and ellipsis in text generation. in this paper, we provide an account of how to generate sentences with coordination constructions from clause-sized semantic representations. an algorithm is developed and various examples from linguistic literature will be used to demonstrate that the algorithm does its job well.
ranking text units according to textual saliency, connectivity and topic aptness. an efficient use of lexical cohesion is described for ranking text units according to their contribution in defining the meaning of a text (textual saliency), their ability to form a cohesive subtext (textual connectivity) and the extent and effectiveness to which they address the different topics which characterize the subject matter of the text (topic aptness). a specific application is also discussed where the method described is employed to build the indexing component of a summarization system to provide both generic and query-based indicative summaries.
ordering among premodifiers. we present a corpus-based study of the sequential ordering among premodifiers in noun phrases. this information is important for the fluency of generated text in practical applications. we propose and evaluate three approaches to identify sequential order among premodifiers: direct evidence, transitive closure, and clustering. our implemented system can make over 94% of such ordering decisions correctly, as evaluated on a large, previously unseen test corpus.
on the automatic transformation of class membership criteria. this paper addresses a problem that may arise in classification tasks: the design of procedures for matching an instance with a set of criteria for class membership in such a way as to permit the intelligent handling of inexact, as well as exact matches. an inexact match is a comparison between an instance and a set of criteria (or a second instance) which has the result that some, but not all, of the criteria described (or exemplified) in the second are found to be satisfied in the first. an exact match is such a comparison for which all of the criteria of the second are found to be satisfied in the first. the approach presented in this paper is to transform the set of criteria for class membership into an exemplary instance of a member of the class, which exhibits a set of characteristics whose presence is necessary and sufficient for membership in that class. use of this exemplary instance during the matching process appears to permit important functions associated with inexact matching to be easily performed, and also to have a beneficial effect on the overall efficiency of the matching process.
a snow based supertagger with application to np chunking. supertagging is the tagging process of assigning the correct elementary tree of ltag, or the correct supertag, to each word of an input sentence. in this paper we propose to use supertags to expose syntactic dependencies which are unavailable with pos tags. we first propose a novel method of applying sparse network of winnow (snow) to sequential models. then we use it to construct a supertagger that uses long distance syntactical dependencies, and the supertagger achieves an accuracy of 92.41%. we apply the supertagger to np chunking. the use of supertags in np chunking gives rise to almost 1% absolute increase (from 92.03% to 92.95%) in f-score under transformation based learning(tbl) frame. the surpertagger described here provides an effective and efficient way to exploit syntactic information.
the production of code-mixed discourse. we propose a comprehensive theory of code-mixed discourse, encompassing equivalencepoint and insertional code-switching, palindromic constructions and lexical borrowing. the starting point is a production model of code-switching acconting for empirical observations about switch-point distribution (the equivalence constraint), well-formedness of monolingual fragments, conservation of constituent structure and lack of constraint between successive switch points, without invoking any "code-switching grammar". code-switched sentence production makes alternate reference to two virtual monolingual sentences, one in each language, and is based on conservative conditions on language labeling of constituents, together with a constraint against real-time "look-ahead" from one code-switch to the next. selective weakening of model conditions can produce (i) the type of palindromic (or portmanteau) construction occasionally occurring e.g., in switches between prepositional and postpositional languages, (ii) the switching by "insertion" of very specific kinds of constituent reported e.g., for french noun phrases in switching with arabic and, most important, (iii) lexical borrowing. borrowing can create ambiguity as to language membership of sentence items, but the model predicts where this can be resolved, and the confirmation of these predictions, based on empirical studies of inflectional morphology, validates key aspects of the model.
exploring correlation of dependency relation paths for answer extraction. in this paper, we explore correlation of dependency relation paths to rank candidate answers in answer extraction. using the correlation measure, we compare dependency relations of a candidate answer and mapped question phrases in sentence with the corresponding relations in question. different from previous studies, we propose an approximate phrase mapping algorithm and incorporate the mapping score into the correlation measure. the correlations are further incorporated into a maximum entropy-based ranking model which estimates path weights from training. experimental results show that our method significantly outperforms state-of-the-art syntactic relation-based methods by up to 20% in mrr.
implementing a characterization of genre for automatic genre identification of web pages. in this paper, we propose an implementable characterization of genre suitable for automatic genre identification of web pages. this characterization is implemented as an inferential model based on a modified version of bayes' theorem. such a model can deal with genre hybridism and individualization, two important forces behind genre evolution. results show that this approach is effective and is worth further research.
adding syntax to dynamic programming for aligning comparable texts for the generation of paraphrases. multiple sequence alignment techniques have recently gained popularity in the natural language community, especially for tasks such as machine translation, text generation, and paraphrase identification. prior work falls into two categories, depending on the type of input used: (a) parallel corpora (e.g., multiple translations of the same text) or (b) comparable texts (non-parallel but on the same topic). so far, only techniques based on parallel texts have successfully used syntactic information to guide alignments. in this paper, we describe an algorithm for incorporating syntactic features in the alignment process for non-parallel texts with the goal of generating novel paraphrases of existing texts. our method uses dynamic programming with alignment decision based on the local syntactic similarity between two sentences. our results show that syntactic alignment outrivals syntax-free methods by 20% in both grammaticality and fidelity when computed over the novel sentences generated by alignment-induced finite state automata.
multi-criteria-based active learning for named entity recognition. in this paper, we propose a multi-criteria-based active learning approach and effectively apply it to named entity recognition. active learning targets to minimize the human annotation efforts by selecting examples for labeling. to maximize the contribution of the selected examples, we consider the multiple criteria: informativeness, representativeness and diversity and propose measures to quantify them. more comprehensively, we incorporate all the criteria using two selection strategies, both of which result in less labeling cost than single-criterion-based method. the results of the named entity recognition in both muc-6 and genia show that the labeling cost can be reduced by at least 80% without degrading the performance.
splitting complex temporal questions for question answering systems. this paper presents a multi-layered question answering (q.a.) architecture suitable for enhancing current q.a. capabilities with the possibility of processing complex questions. that is, questions whose answer needs to be gathered from pieces of factual information scattered in different documents. specifically, we have designed a layer oriented to process the different types of temporal questions. complex temporal questions are first decomposed into simpler ones, according to the temporal relationships expressed in the original question.in the same way, the answers of each simple question are re-composed, fulfilling the temporal restrictions of the original complex question.using this architecture, a temporal q.a. system has been developed.in this paper, we focus on explaining the first part of the process: the decomposition of the complex questions. furthermore, it has been evaluated with the terqas question corpus of 112 temporal questions. for the task of question splitting our system has performed, in terms of precision and recall, 85% and 71%, respectively.
a dom tree alignment model for mining parallel data from the web. this paper presents a new web mining scheme for parallel data acquisition. based on the document object model (dom), a web page is represented as a dom tree. then a dom tree alignment model is proposed to identify the translationally equivalent texts and hyperlinks between two parallel dom trees. by tracing the identified parallel hyperlinks, parallel web documents are recursively mined. compared with previous mining schemes, the benchmarks show that this new mining scheme improves the mining coverage, reduces mining bandwidth, and enhances the quality of mined parallel sentences.
unsupervised topic identification by integrating linguistic and visual information based on hidden markov models. this paper presents an unsupervised topic identification method integrating linguistic and visual information based on hidden markov models (hmms). we employ hmms for topic identification, wherein a state corresponds to a topic and various features including linguistic, visual and audio information are observed. our experiments on two kinds of cooking tv programs show the effectiveness of our proposed method.
extending kimmo's two-level model of morphology. this paper describes the problems faced while using kimmo's two-level model to describe certain indian languages such as tamil and hindi. the two-level model is shown to be descriptively inadequate to address these problems. a simple extension to the basic two-level model is introduced which allows conflicting phonological rules to coexist. the computational complexity of the extension is the same as kimmo's two-level model.
using restriction to extend parsing algorithms for complex-feature-based formalisms. grammar formalisms based on the encoding of grammatical information in complex-valued feature systems enjoy some currency both in linguistics and natural-language-processing research. such formalisms can be thought of by analogy to context-free grammars as generalizing the notion of nonterminal symbol from a finite domain of atomic elements to a possibly infinite domain of directed graph structures of a certain sort. unfortunately, in moving to an infinite nonterminal domain, standard methods of parsing may no longer be applicable to the formalism. typically, the problem manifests itself as gross inefficiency or even nontermination of the algorithms. in this paper, we discuss a solution to the problem of extending parsing algorithms to formalisms with possibly infinite nonterminal domains, a solution based on a general technique we call restriction. as a particular example of such an extension, we present a complete, correct, terminating extension of earley's algorithm that uses restriction to perform top-down filtering. our implementation of this algorithm demonstrates the drastic elimination of chart edges that can be achieved by this technique. finally, we describe further uses for the technique---including parsing other grammar formalisms, including definite-clause grammars; extending other parsing algorithms, including lr methods and syntactic preference modeling algorithms; and efficient indexing.
incremental parser generation for tree adjoining grammars. this paper describes the incremental generation of parse tables for the lr-type parsing of tree adjoining languages (tals). the algorithm presented handles modifications to the input grammar by updating the parser generated so far. in this paper, a lazy generation of lr-type parsers for tals is defined in which parse tables are created by need while parsing. we then describe an incremental parser generator for tals which responds to modification of the input grammar by updating parse tables built so far.
a semantic-head-driven generation algorithm for unification-based formalisms. we present an algorithm for generating strings from logical form encodings that improves upon previous algorithms in that it places fewer restrictions on the class of grammars to which it is applicable. in particular, unlike an earley deduction generator (shieber, 1988), it allows use of semantically nonmonotonic grammars, yet unlike topdown methods, it also permits left-recursion. the enabling design feature of the algorithm is its implicit traversal of the analysis tree for the string being generated in a semantic-head-driven fashion.
conditions on consistency of probabilistic tree adjoining grammars. much of the power of probabilistic methods in modelling language comes from their ability to compare several derivations for the same string in the language. an important starting point for the study of such cross-derivational properties is the notion of consistency. the probability model defined by a probabilistic grammar is said to be consistent if the probabilities assigned to all the strings in the language sum to one. from the literature on probabilistic context-free grammars (cfgs), we know precisely the conditions which ensure that consistency is true for a given cfg. this paper derives the conditions under which a given probabilistic tree adjoining grammar (tag) can be shown to be consistent. it gives a simple algorithm for checking consistency and gives the formal justification for its correctness. the conditions derived here can be used to ensure that probability models that use tags can be checked for deficiency (i.e. whether any probability mass is assigned to strings that cannot be generated).
semantic discourse segmentation and labeling for route instructions. in order to build a simulated robot that accepts instructions in unconstrained natural language, a corpus of 427 route instructions was collected from human subjects in the office navigation domain. the instructions were segmented by the steps in the actual route and labeled with the action taken in each step. this flat formulation reduced the problem to an ie/segmentation task, to which we applied conditional random fields. we compared the performance of crfs with a set of hand-written rules. the result showed that crfs perform better with a 73.7% success rate.
question answering as question-biased term extraction: a new approach toward multilingual qa. this paper regards question answering (qa) as question-biased term extraction (qbte). this new qbte approach liberates qa systems from the heavy burden imposed by question types (or answer types). in conventional approaches, a qa system analyzes a given question and determines the question type, and then it selects answers from among answer candidates that match the question type. consequently, the output of a qa system is restricted by the design of the question types. the qbte directly extracts answers as terms biased by the question. to confirm the feasibility of our qbte approach, we conducted experiments on the crl qa data based on 10-fold cross validation, using maximum entropy models (mems) as an ml technique. experimental results showed that the trained system achieved 0.36 in mrr and 0.47 in top5 accuracy.
exact decoding for jointly labeling and chunking sequences. there are two decoding algorithms essential to the area of natural language processing. one is the viterbi algorithm for linear-chain models, such as hmms or crfs. the other is the cky algorithm for probabilistic context free grammars. however, tasks such as noun phrase chunking and relation extraction seem to fall between the two, neither of them being the best fit. ideally we would like to model entities and relations, with two layers of labels. we present a tractable algorithm for exact inference over two layers of labels and chunks with time complexity o(n2), and provide empirical results comparing our model with linear-chain models.
an empirical study of active learning with support vector machines for japanese word segmentation. we explore how active learning with support vector machines works well for a non-trivial task in natural language processing. we use japanese word segmentation as a test case. in particular, we discuss how the size of a pool affects the learning curve. it is found that in the early stage of training with a larger pool, more labeled examples are required to achieve a given level of accuracy than those with a smaller pool. in addition, we propose a novel technique to use a large number of unlabeled examples effectively by adding them gradually to a pool. the experimental results show that our technique requires less labeled examples than those with the technique in previous research. to achieve 97.0% accuracy, the proposed technique needs 59.3% of labeled examples that are required when using the previous technique and only 17.4% of labeled examples with random sampling.
retrieving collocations by co-occurrences and word order constraints. in this paper, we describe a method for automatically retrieving collocations from large text corpora. this method retrieve collocations in the following stages: 1) extracting strings of characters as units of collocations 2) extracting recurrent combinations of strings in accordance with their word order in a corpus as collocations. through the method, various range of collocations, especially domain specific collocations, are retrieved. the method is practical because it uses plain texts without any information dependent on a language such as lexical knowledge and parts of speech.
translating hpsg-style outputs of a robust parser into typed dynamic logic. the present paper proposes a method by which to translate outputs of a robust hpsg parser into semantic representations of typed dynamic logic (tdl), a dynamic plural semantics defined in typed lambda calculus. with its higher-order representations of contexts, tdl analyzes and describes the inherently inter-sentential nature of quantification and anaphora in a strictly lexicalized and compositional manner. the present study shows that the proposed translation method successfully combines robustness and descriptive adequacy of contemporary semantics. the present implementation achieves high coverage, approximately 90%, for the real text of the penn treebank corpus.
compiling a lexicon of cooking actions for animation generation. this paper describes a system which generates animations for cooking actions in recipes, to help people understand recipes written in japanese. the major goal of this research is to increase the scalability of the system, i.e., to develop a system which can handle various kinds of cooking actions. we designed and compiled the lexicon of cooking actions required for the animation generation system. the lexicon includes the action plan used for animation generation, and the information about ingredients upon which the cooking action is taken. preliminary evaluation shows that our lexicon contains most of the cooking actions that appear in japanese recipes. we also discuss how to handle linguistic expressions in recipes, which are not included in the lexicon, in order to generate animations for them.
maximum entropy model learning of the translation rules. this paper proposes a learning method of translation rules from parallel corpora. this method applies the maximum entropy principle to a probabilistic model of translation rules. first, we define feature functions which express statistical properties of this model. next, in order to optimize the model, the system iterates following steps: (1) selects a feature function which maximizes loglikelihood, and (2) adds this function to the model incrementally. as computational cost associated with this model is too expensive, we propose several methods to suppress the overhead in order to realize the system. the result shows that it attained 69.54% recall rate.
natural vs. precise concise languages for human operation of computers: research issues and experimental approaches. this paper raises concerns that natural language front ends for computer systems can limit a researcher's scope of thinking, yield inappropriately complex systems, and exaggerate public fear of computers. alternative modes of computer use are suggested and the role of psychologically oriented controlled experimentation is emphasized. research methods and recent experimental results are briefly reviewed.
recognition of linear context-free rewriting systems. the class of linear context-free rewriting systems has been introduced as a generalization of a class of grammar formalisms known as mildly context-sensitive. the recognition problem for linear context-free rewriting languages is studied at length here, presenting evidence that, even in some restricted cases, it cannot be solved efficiently. this entails the existence of a gap between, for example, tree adjoining languages and the subclass of linear context-free rewriting languages that generalizes the former class; such a gap is attributed to "crossing configurations". a few other interesting consequences of the main result are discussed, that concern the recognition problem for linear context-free rewriting languages.
generating referring expressions in open domains. we present an algorithm for generating referring expressions in open domains. existing algorithms work at the semantic level and assume the availability of a classification for attributes, which is only feasible for restricted domains. our alternative works at the realisation level, relies on word-net synonym and antonym sets, and gives equivalent results on the examples cited in the literature and improved results for examples that prior approaches cannot handle. we believe that ours is also the first algorithm that allows for the incremental incorporation of relations. we present a novel corpus-evaluation using referring expressions from the penn wall street journal treebank.
efficient transformation-based parsing. in transformation-based parsing, a finite sequence of tree rewriting rules are checked for application to an input structure. since in practice only a small percentage of rules are applied to any particular structure, the naive parsing algorithm is rather inefficient. we exploit this sparseness in rule applications to derive an algorithm two to three orders of magnitude faster than the standard parsing algorithm.
string transformation learning. string transformation systems have been introduced in (brill, 1995) and have several applications in natural language processing. in this work we consider the computational problem of automatically learning from a given corpus the set of transformations presenting the best evidence. we introduce an original data structure and efficient algorithms that learn some families of transformations that are relevant for part-of-speech tagging and phonological rule systems. we also show that the same learning problem becomes np-hard in cases of an unbounded use of don't care symbols in a transformation.
corpus-based linguistic indicators for aspectual classification. fourteen indicators that measure the frequency of lexico-syntactic phenomena linguistically related to aspectual class are applied to aspectual classification. this group of indicators is shown to improve classification performance for two aspectual distinctions, stativity and completedness (i.e., telicity), over unrestricted sets of verbs from two corpora. several of these indicators have not previously been discovered to correlate with aspect.
restrictions on tree adjoining languages. several methods are known for parsing languages generated by tree adjoining grammars (tags) in o(n6) worst case running time. in this paper we investigate which restrictions on tags and tag derivations are needed in order to lower this o(n6) time complexity, without introducing large runtime constants, and without losing any of the generative power needed to capture the syntactic constructions in natural language that can be handled by unrestricted tags. in particular, we describe an algorithm for parsing a strict subcalss of tag in o(n5), and attempt to show that this subclass retains enough generative power to make it useful in the general case.
an application of automated language understanding techniques to the generation of data base elements. this paper defines a methodology for automatically analyzing textual reports of events and synthesizing event data elements from the reports for automated input to a data base. the long-term goal of the work described is to develop a support technology for specific analytical functions related to the evaluation of daily message traffic in a military environment. the approach taken leans heavily on theoretical advances in several disciplines, including linguistics, computational linguistics, artificial intelligence, and cognitive psychology. the aim is to model the cognitive activities of the human analyst as he reads and understands message text, distilling its contents into information items of interest to him, and building a conceptual model of the information conveyed by the message. this methodology, although developed on the basis of a restricted subject domain, is presumed to be general, and extensible to other domains.our approach is centered around the notion of "event", and utilizes two major knowledge sources: (1) a model of the sublanguage for event reporting which characterizes the message traffic, and (2), a model of the analyst-user's conceptualization of the world (i.e., a model of the entities and relations characteristic of his world).
minimalist parsing of subjects displaced from embedded clauses in free word order languages. in sayeed and szpakowicz (2004), we proposed a parser inspired by some aspects of the minimalist program. this incremental parser was designed specifically to handle discontinuous constituency phenomena for nps in latin. we take a look at the application of this parser to a specific kind of apparent island violation in latin involving the extraction of constituents, including subjects, from tensed embedded clauses. we make use of ideas about the left periphery from rizzi (1997) to modify our parser in order to handle apparently violated subject islands and similar phenomena.
tree-gram parsing: lexical dependencies and structural relations. this paper explores the kinds of probabilistic relations that are important in syntactic disambiguation. it proposes that two widely used kinds of relations, lexical dependencies and structural relations, have complementary disambiguation capabilities. it presents a new model based on structural relations, the tree-gram model, and reports experiments showing that structural relations should benefit from enrichment by lexical dependencies.
multi-level plurals and distributivity. we present a computational treatment of the semantics of plural noun phrases which extends an earlier approach presented by scha [7] to be able to deal with multiple-level plurals ("the boys and the girls", "the juries and the committees", etc.), we argue that the arbitrary depth to which such plural structures can be nested creates a correspondingly arbitrary ambiguity in the possibilities for the distribution of verbs over such nps. we present a recursive translation rule scheme which accounts for this ambiguity, and in particular show how it allows for the option of "partial distributivity" that collective verbs have when applied to such plural noun phrases.
polynomial time and space shift-reduce parsing of arbitrary context-free grammars. we introduce an algorithm for designing a predictive left to right shift-reduce non-determinisic push-down machine corresponding to an arbitrary unrestricted context-free grammar and an algorithm for efficiently driving this machine in pseudo-parallel. the performance of the resulting parser is formally proven to be superior to earley's parser (1970).the technique employed consists in constructing before run-time a parsing table that encodes a non-deterministic machine in the which the predictive behavior has been compiled out. at run time, the machine is driven in pseudo-parallel with the help of a chart.the recognizer behaves in the worst case in o(|g|2n3)-time and o(|g|n2)-space. however in practice it is always superior to earley's parser since the prediction steps have been compiled before run-time.finally, we explain how other more efficient variants of the basic parser can be obtained by determinizing portions of the basic non-deterministic push-down machine while still using the same pseudo-parallel driver.
the acquisition and application of context sensitive grammar for english. a system is described for acquiring a context-sensitive, phrase structure grammar which is applied by a best-path, bottom-up, deterministic parser. the grammar was based on english news stories and a high degree of success in parsing in reported. overall, this research concludes that csg is a computationally and conceptually tractable approach to the construction of phrase structure grammar for news story text.
an earley-type parsing algorithm for tree adjoining grammars. we will describe an earley-type parser for tree adjoining grammars (tags). although a cky-type parser for tags has been developed earlier (vijay-shanker and joshi, 1985), this is the first practical parser for tags because as is well known for cfgs, the average behavior of earley-type parsers is superior to that of cky-type parsers. the core of the algorithm is described. then we discuss modifications of the parsing algorithm that can parse extensions of tags such as constraints on adjunction, substitution, and feature structures for tags. we show how with the use of substitution in tags the system is able to parse directly cfgs and tags. the system parses unification formalisms that have a cfg skeleton and also those with a tag skeleton. thus it also allows us to embed the essential aspects of patr-ii.
an alternative conception of tree-adjoining derivation. the precise formulation of derivation for tree-adjoining grammars has important ramifications for a wide variety of uses of the formalism, from syntactic analysis to semantic interpretation and statistical language modeling. we argue that the definition of tree-adjoining derivation must be reformulated in order to manifest the proper linguistic dependencies in derivations. the particular proposal is both precisely characterizable, through a compilation to linear indexed grammars, and computationally operational, by virtue of an efficient algorithm for recognition and parsing.
morphological richness offsets resource demand - experiences in constructing a pos tagger for hindi. in this paper we report our work on building a pos tagger for a morphologically rich language- hindi. the theme of the research is to vindicate the stand that- if morphology is strong and harnessable, then lack of training corpora is not debilitating. we establish a methodology of pos tagging which the resource disadvantaged (lacking annotated corpora) languages can make use of. the methodology makes use of locally annotated modestly-sized corpora (15,562 words), exhaustive morpohological analysis backed by high-coverage lexicon and a decision tree based learning algorithm (cn2). the evaluation of the system was done with 4-fold cross validation of the corpora in the news domain (www.bbc.co.uk/hindi). the current accuracy of pos tagging is 93.45% and can be further improved.
deterministic left to right parsing of tree adjoining languages. we define a set of deterministic bottom-up left to right parsers which analyze a subset of tree adjoining languages. the lr parsing strategy for context free grammars is extended to tree adjoining grammars (tags). we use a machine, called bottom-up embedded push down automation (bepda), that recognizes in a bottom-up fashion the set of tree adjoining languages (and exactly this set). each parser consists of a finite state control that drives the moves of a bottom-up embedded pushdown automaton. the parsers handle deterministically some context-sensitive tree adjoining languages. in this paper, we informally describe the bepda then given a parsing table, we explain the lr parsing algorithm. we then show how to construct an lr(0) parsing table (no lookahead). an example of a context-sensitive language recognized deterministically is given. then, we explain informally the construction of slr(1) parsing tables for bepda. we conclude with a discussion of our parsing method and current work.
acquiring core meanings of words, represented as jackendoff-style conceptual structures, from correlated streams of linguistic and non-linguistic input. this paper describes an operational system which can acquire the core meanings of words without any prior knowledge of either the category or meaning of any words it encounters. the system is given as input, a description of sequences of scenes along with sentences which describe the [events] taking place as those scenes unfold, and produces as output, a lexicon consisting of the category and meaning of each word in the input, that allows the sentences to describe the [events]. it is argued, that each of the three main components of the system, the parser, the linker and the inference component, make only linguistically and cognitively plausible assumptions about the innate knowledge needed to support tractable learning. the paper discusses the theory underlying the system, the representations and algorithms used in the implementation, the semantic constraints which support the heuristics necessary to achieve tractable learning, the limitations of the current theory and the implications of this work for language acquisition research.
lexicalized context-free grammars. lexicalized context-free grammar(lcfg) is an attractive compromise between the parsing efficiency of context-free grammar (cfg) and the elegance and lexical sensitivity of lexicalized tree adjoining grammar (ltag). lcfg is a restricted form of ltag that can only generate context-free languages and can be parsed in cubic time. however, lcfg supports much of the elegance of ltag's analysis of english and shares with ltag the ability to lexicalize cfgs without changing the trees generated.
guiding an hpsg parser using semantic and pragmatic expectations. efficient natural language generation has been successfully demonstrated using highly compiled knowledge about speech acts and their related social actions. a design and prototype implementation of a parser which utilizes this same pragmatic knowledge to efficiently guide parsing is presented. such guidance is shown to prune the search space and thus avoid needless processing of pragmatically unlikely constituent structures.
metaphor comprehension - a special mode of language processing? the paper addresses the question of whether a complete language understanding system requires special procedures in order to comprehend metaphorical language. to answer this question it is necessary to delineate the processes involved in metaphor comprehension and to determine the uniqueness of such processes in the context of existing language understanding systems.
ellipsis resolution with underspecified scope. the paper presents an approach to ellipsis resolution in a framework of scope underspecification (underspecified discourse representation theory). it is argued that the approach improves on previous proposals to integrate ellipsis resolution and scope underspecification (crouch, 1995; egg et al., 2001) in that application processes like anaphora resolution do not require full disambiguation but can work directly on the underspecified representation. furthermore it is shown that the approach presented can cope with the examples discussed by dalrymple et al. (1991) as well as a problem noted recently by erk and koller (2001).
combining deep and shallow approaches in parsing german. the paper describes two parsing schemes: a shallow approach based on machine learning and a cascaded finite-state parser with a hand-crafted grammar. it discusses several ways to combine them and presents evaluation results for the two individual approaches and their combination. an underspecification scheme for the output of the finite-state parser is introduced and shown to improve performance.
learning tense translation from bilingual corpora. this paper studies and evaluates disambiguation strategies for the translation of tense between german and english, using a bilingual corpus of appointment scheduling dialogues. it describes a scheme to detect complex verb predicates based on verb form subcategorization and grammatical knowledge. the extracted verb and tense information is presented and the role of different context factors is discussed.
from n-grams to collocations: an evaluation of xtract. in previous papers we presented methods for retrieving collocations from large samples of texts. we described a tool, xtract, that implements these methods and able to retrieve a wide range of collocations in a two stage process. these methods as well as other related methods however have some limitations. mainly, the produced collocations do not include any kind of functional information and many of them are invalid. in this paper we introduce methods that address these issues. these methods are implemented in an added third stage to xtract that examines the set of collocations retrieved during the previous two stages to both filter out a number of invalid collocations and add useful syntactic information to the retained ones. by combining parsing and statistical techniques the addition of this third stage has raised the overall precision level of xtract from 40% to 80% with a precision of 94%. in the paper we describe the methods and the evaluation experiments.
producing biographical summaries: combining linguistic knowledge with corpus statistics. we describe a biographical multi-document summarizer that summarizes information about people described in the news. the summarizer uses corpus statistics along with linguistic knowledge to select and merge descriptions of people from a document collection, removing redundant descriptions. the summarization components have been extensively evaluated for coherence, accuracy, and non-redundancy of the descriptions produced.
automatically extracting and representing collocations for language generation. collocational knowledge is necessary for language generation. the problem is that collocations come in a large variety of forms. they can involve two, three or more words, these words can be of different syntactic categories and they can be involved in more or less rigid ways. this leads to two main difficulties: collocational knowledge has to be acquired and it must be represented flexibly so that it can be used for language generation. we address both problems in this paper, focusing on the acquisition problem. we describe a program, xtract, that automatically acquires a range of collocations from large textual corpora and we describe how they can be represented in a flexible lexicon using a unification based formalism.
aspect and discourse structure: is a neutral viewpoint required? we apply smith's theory of aspect (1991) to german - a language without any aspectual markers. in particular, we try to shed more light on the effects aspect can have on discourse structure and show how english and german behave differently in this respect. we furthermore describe how smith's notion of a neutral viewpoint can be helpful for the analysis of discourse in german. it turned out that proposals claiming that the german preterite covers the progressive as well as the simple aspect can not sufficiently explain the data presented in this paper (b&auml;uerle, 1988). finally we give a situation-theoretic approach to formalize smith's intuitions following glasbey (1994) incorporating allen's interval-calculus (allen, 1984).
word expert parsing. this paper describes an approach to conceptual analysis and understanding of natural language in which linguistic knowledge centers on individual words, and the analysis mechanisms consist of interactions among distributed procedural experts representing that knowledge. each word expert models the process of diagnosing the intended usage of a particular word in context. the word expert parser performs conceptual analysis through the interactions of the individual experts, which ask questions and exchange information in converging on a single mutually acceptable sentence meaning. the word expert theory is advanced as a better cognitive model of natural language understanding than the traditional rule-based approaches. the word expert parser models parts of the theory, and the important issues of control and representation that arise in developing such a model from the basis of the technical discussion. an example from the prototype lisp implementation helps explain the theoretical results presented.
a cognitive model of coherence-driven story comprehension. current models of story comprehension have three major deficiencies: (1) lack of experimental support for the inference processes they involve (e.g. reliance on prediction); (2) indifference to 'kinds' of coherence (e.g. local and global); and (3) inability to find interpretations at variable depths. i propose that comprehension is driven by the need to find a representation that reaches a 'coherence threshold'. variable inference processes are a reflection of different thresholds, and the skepticism of an individual inference process determines how thresholds are reached.
towards finding and fixing fragments-using ml to identify non-sentential utterances and their antecedents in multi-party dialogue. non-sentential utterances (e.g., short-answers as in "who came to the party?"--- "peter.") are pervasive in dialogue. as with other forms of ellipsis, the elided material is typically present in the context (e.g., the question that a short answer answers). we present a machine learning approach to the novel task of identifying fragments and their antecedents in multiparty dialogue. we compare the performance of several learning algorithms, using a mixture of structural and lexical features, and show that the task of identifying antecedents given a fragment can be learnt successfully (f(0.5) = .76); we discuss why the task of identifying fragments is harder (f(0.5) = .41) and finally report on a combined task (f(0.5) = .38).
logarithmic opinion pools for conditional random fields. recent work on conditional random fields (crfs) has demonstrated the need for regularisation to counter the tendency of these models to overfit. the standard approach to regularising crfs involves a prior distribution over the model parameters, typically requiring search over a hyperparameter space. in this paper we address the overfitting problem from a different perspective, by factoring the crf distribution into a weighted product of individual "expert" crf distributions. we call this model a logarithmic opinion pool (lop) of crfs (lop-crfs). we apply the lop-crf to two sequencing tasks. our results show that unregularised expert crfs with an unregularised crf under a lop can outperform the unregularised crf, and attain a performance level close to the regularised crf. lop-crfs therefore provide a viable alternative to crf regularisation without the need for hyperparameter search.
trace prediction and recovery with unlexicalized pcfgs and slash features. this paper describes a parser which generates parse trees with empty elements in which traces and fillers are co-indexed. the parser is an unlexicalized pcfg parser which is guaranteed to return the most probable parse. the grammar is extracted from a version of the penn treebank which was automatically annotated with features in the style of klein and manning (2003). the annotation includes gpsg-style slash features which link traces and fillers, and other features which improve the general parsing accuracy. in an evaluation on the penn treebank (marcus et al., 1993), the parser outperformed other unlexicalized pcfg parsers in terms of labeled bracketing f-score. its results for the empty category prediction task and the trace-filler co-indexation task exceed all previously reported results with 84.1% and 77.4% f-score, respectively.
annealing techniques for unsupervised statistical language learning. exploiting unannotated natural language data is hard largely because unsupervised parameter estimation is hard. we describe deterministic annealing (rose et al., 1990) as an appealing alternative to the expectation-maximization algorithm (dempster et al., 1977). seeking to avoid search error, da begins by globally maximizing an easy concave function and maintains a local maximum as it gradually morphs the function into the desired non-concave likelihood function. applying da to parsing and tagging models is shown to be straightforward; significant improvements over em are shown on a part-of-speech tagging task. we describe a variant, skewed da, which can incorporate a good initializer when it is available, and show significant improvements over em on a grammar induction task.
parse forest computation of expected governors. in a headed tree, each terminal word can be uniquely labeled with a governing word and grammatical relation. this labeling is a summary of a syntactic analysis which eliminates detail, reflects aspects of semantics, and for some grammatical relations (such as subject of finite verb) is nearly uncontroversial. we define a notion of expected governor markup, which sums vectors indexed by governors and scaled by probabilistic tree weights. the quantity is computed in a parse forest representation of the set of tree analyses for a given sentence, using vector sums and scaling by inside probability and flow.
incremental construction of compact acyclic nfas. this paper presents and analyzes an incremental algorithm for the construction of acyclic non-deterministic finite-state automata (nfa). automata of this type are quite useful in computational linguistics, especially for storing lexicons. the proposed algorithm produces compact nfas, i.e. nfas that do not contain equivalent states. unlike deterministic finite-state automata (dfa), this property is not sufficient to ensure minimality, but still the resulting nfas are considerably smaller than the minimal dfas for the same languages.
synonymous collocation extraction using translation information. automatically acquiring synonymous collocation pairs such as <turn on, obj, light> and <switch on, obj, light> from corpora is a challenging task. for this task, we can, in general, have a large monolingual corpus and/or a very limited bilingual corpus. methods that use monolingual corpora alone or use bilingual corpora alone are apparently inadequate because of low precision or low coverage. in this paper, we propose a method that uses both these resources to get an optimal compromise of precision and coverage. this method first gets candidates of synonymous collocation pairs based on a monolingual corpus and a word thesaurus, and then selects the appropriate pairs from the candidates using their translations in a second language. the translations of the candidates are obtained with a statistical translation model which is trained with a small bilingual corpus and a large monolingual corpus. the translation information is proved as effective to select synonymous collocation pairs. experimental results indicate that the average precision and recall of our approach are 74% and 64% respectively, which outperform those methods that only use monolingual corpora and those that only use bilingual corpora.
natural language access to software applications. this paper reports on the esprit project melissa (methods and tools for natural-language interfacing with standard software applications)1. melissa aims at developing the technology and tools enabling end users to interface with computer applications, using natural-language (nl), and to obtain a precompetitive product validated in selected enduser applications. this paper gives an overview of the approach to solving (nl) interfacing problem and outlines some of the methods and software components developed in the project.
contrastive estimation: training log-linear models on unlabeled data. conditional random fields (lafferty et al., 2001) are quite effective at sequence labeling tasks like shallow parsing (sha and pereira, 2003) and named-entity extraction (mccallum and li, 2003). crfs are log-linear, allowing the incorporation of arbitrary features into the model. to train on unlabeled data, we require unsupervised estimation methods for log-linear models; few exist. we describe a novel approach, contrastive estimation. we show that the new technique can be intuitively understood as exploiting implicit negative evidence and is computationally efficient. applied to a sequence labeling problem---pos tagging given a tagging dictionary and unlabeled text---contrastive estimation outperforms em (with the same feature set), is more robust to degradations of the dictionary, and can largely recover by modeling additional features.
recognizing syntactic errors in the writing of second language learners. this paper reports on the recognition component of an intelligent tutoring system that is designed to help foreign language speakers learn standard english. the system models the grammar of the learner, with this instantiation of the system tailored to signers of american sign language (asl). we discuss the theoretical motivations for the system, various difficulties that have been encountered in the implementation, as well as the methods we have used to overcome these problems. our method of capturing ungrammaticalities involves using mal-rules (also called 'error productions'). however, the straightforward addition of some mal-rules causes significant performance problems with the parser. for instance, the asl population has a strong tendency to drop pronouns and the auxiliary verb 'to be'. being able to account for these as sentences results in an explosion in the number of possible parses for each sentence. this explosion, left unchecked, greatly hampers the performance of the system. we discuss how this is handled by taking into account expectations from the specific population (some of which are captured in our unique user model). the different representations of lexical items at various points in the acquisition process are modeled by using mal-rules, which obviates the need for multiple lexicons. the grammar is evaluated on its ability to correctly diagnose agreement problems in actual sentences produced by asl native speakers.
annealing structural bias in multilingual weighted grammar induction. we first show how a structural locality bias can improve the accuracy of state-of-the-art dependency grammar induction models trained by em from unannotated examples (klein and manning, 2004). next, by annealing the free parameter that controls this bias, we achieve further improvements. we then describe an alternative kind of structural bias, toward "broken" hypotheses consisting of partial structures over segmented sentences, and show a similar pattern of improvement. we relate this approach to contrastive estimation (smith and eisner, 2005a), apply the latter to grammar induction in six languages, and show that our new approach improves accuracy by 1-17% (absolute) over ce (and 8-30% over em), achieving to our knowledge the best results on this task to date. our method, structural annealing, is a general technique with broad applicability to hidden-structure discovery problems.
atlas - a new text alignment architecture. we are presenting a new, hybrid alignment architecture for aligning bilingual, linguistically annotated parallel corpora. it is able to align simultaneously at paragraph, sentence, phrase and word level, using statistical and heuristic cues, along with linguistics-based rules. the system currently aligns english and german texts, and the linguistic annotation used covers pos-tags, lemmas and syntactic constitutents. however, as the system is highly modular, we can easily adapt it to new language pairs and other types of annotation. the hybrid nature of the system allows experiments with a variety of alignment cues to find solutions to word alignment problems like the correct alignment of rare words and multiwords, or how to align despite syntactic differences between two languages. first performance tests are promising, and we are setting up a gold standard for a thorough evaluation of the system.
minimum risk annealing for training log-linear models. when training the parameters for a natural language system, one would prefer to minimize 1-best loss (error) on an evaluation set. since the error surface for many natural language problems is piecewise constant and riddled with local minima, many systems instead optimize log-likelihood, which is conveniently differentiable and convex. we propose training instead to minimize the expected loss, or risk. we define this expectation using a probability distribution over hypotheses that we gradually sharpen (anneal) to focus on the 1-best hypothesis. besides the linear loss functions used in previous work, we also describe techniques for optimizing nonlinear functions such as precision or the bleu metric. we present experiments training log-linear combinations of models for dependency parsing and for machine translation. in machine translation, annealed minimum risk training achieves significant improvements in bleu over standard minimum error training. we also show improvements in labeled dependency parsing.
computational properties of environment-based disambiguation. the standard pipeline approach to semantic processing, in which sentences are morphologically and syntactically resolved to a single tree before they are interpreted, is a poor fit for applications such as natural language interfaces. this is because the environment information, in the form of the objects and events in the application's runtime environment, cannot be used to inform parsing decisions unless the input sentence is semantically analyzed, but this does not occur until after parsing in the single-tree semantic architecture. this paper describes the computational properties of an alternative architecture, in which semantic analysis is performed on all possible interpretations during parsing, in polynomial time.
using model-theoretic semantic interpretation to guide statistical parsing and word recognition in a spoken language interface. this paper describes an extension of the semantic grammars used in conventional statistical spoken language interfaces to allow the probabilities of derived analyses to be conditioned on the meanings or denotations of input utterances in the context of an interface's underlying application environment or world model. since these denotations will be used to guide disambiguation in interactive applications, they must be efficiently shared among the many possible analyses that may be assigned to an input utterance. this paper therefore presents a formal restriction on the scope of variables in a semantic grammar which guarantees that the denotations of all possible analyses of an input utterance can be calculated in polynomial time, without undue constraints on the expressivity of the derived semantics. empirical tests show that this model-theoretic interpretation yields a statistically significant improvement on standard measures of parsing accuracy over a baseline grammar not conditioned on denotations.
unsupervised induction of modern standard arabic verb classes using syntactic frames and lsa. we exploit the resources in the arabic treebank (atb) and arabic gigaword (ag) to determine the best features for the novel task of automatically creating lexical semantic verb classes for modern standard arabic (msa). the verbs are classified into groups that share semantic elements of meaning as they exhibit similar syntactic behavior. the results of the clustering experiments are compared with a gold standard set of classes, which is approximated by using the noisy english translations provided in the atb to create levin-like classes for msa. the quality of the clusters is found to be sensitive to the inclusion of syntactic frames, lsa vectors, morphological pattern, and subject animacy. the best set of parameters yields an f&beta;=1 score of 0.456, compared to a random baseline of an f&beta;=1 score of 0.205.
preserving semantic dependencies in synchronous tree adjoining grammar. rambow, wier and vijay-shanker (rambow et al., 1995) point out the differences between tag derivation structures and semantic or predicate-argument dependencies, and joshi and vijay-shanker (joshi and vijay-shanker, 1999) describe a monotonic compositional semantics based on attachment order that represents the desired dependencies of a derivation without underspecifying predicate-argument relationships at any stage. in this paper, we apply the joshi and vijay-shanker conception of compositional semantics to the problem of preserving semantic dependencies in synchronous tag translation (shieber and schabes, 1990; abeill&eacute; et al., 1990). in particular, we describe an algorithm to obtain the semantic dependencies on a tag parse forest and construct a target derivation forest with isomorphic or locally non-isomorphic dependencies in <i>o (n<sup>7</sup>)</i> time.
a bayesian model for morpheme and paradigm identification. this paper describes a system for unsupervised learning of morphological affixes from texts or word lists. the system is composed of a generative probability model and a search algorithm. experiments on the wall street journal and the hansard corpus (french and english) demonstrate the effectiveness of this approach. the results suggest that more integrated systems for learning both affixes and morphographemic adjustment rules may be feasible. in addition, several definitions and a theorem are developed so that our search algorithm can be formalized in terms of the lattice formed by subsets of suffixes under inclusion. this formalism is expected to be useful for investigating alternative search strategies over the same morphological hypothesis space.
multi-component tag and notions of formal power. this paper presents a restricted version of set-local multi-component tags (weir, 1988) which retains the strong generative capacity of tree-local multi-component tag (i.e. produces the same derived structures) but has a greater derivational generative capacity (i.e. can derive those structures in more ways). this formalism is then applied as a framework for integrating dependency and constituency based linguistic representations.
semantic taxonomy induction from heterogenous evidence. we propose a novel algorithm for inducing semantic taxonomies. previous algorithms for taxonomy induction have typically focused on independent classifiers for discovering new single relationships based on hand-constructed or automatically discovered textual patterns. by contrast, our algorithm flexibly incorporates evidence from multiple classifiers over heterogenous relationships to optimize the entire structure of the taxonomy, using knowledge of a word's coordinate terms to help in determining its hypernyms, and vice versa. we apply our algorithm on the problem of sense-disambiguated noun hyponym acquisition, where we combine the predictions of hypernym and coordinate term classifiers with the knowledge in a preexisting semantic taxonomy (wordnet 2.1). we add 10,000 novel synsets to wordnet 2.1 at 84% precision, a relative error reduction of 70% over a non-joint algorithm using the same component classifiers. finally, we show that a taxonomy built using our algorithm shows a 23% relative f-score improvement over wordnet 2.1 on an independent testset of hypernym pairs.
exploiting named entity taggers in a second language. in this work we present a method for named entity recognition (ner). our method does not rely on complex linguistic resources, and apart from a hand coded system, we do not use any language-dependent tools. the only information we use is automatically extracted from the documents, without human intervention. moreover, the method performs well even without the use of the hand coded system. the experimental results are very encouraging. our approach even outperformed the hand coded system on ner in spanish, and it achieved high accuracies in portuguese.
part-of-speech induction from scratch. this paper presents a method for inducing the parts of speech of a language and part-of-speech labels for individual words from a large text corpus. vector representations for the part-of-speech of a word are formed from entries of its near lexical neighbors. a dimensionality reduction creates a space representing the syntactic categories of unambiguous words. a neural net trained on these spatial representations classifies individual contexts of occurrence of ambiguous words. the method classifies both ambiguous and unambiguous words correctly with high accuracy.
part-of-speech tagging using a variable memory markov model. we present a new approach to disambiguating syntactically ambiguous words in context, based on variable memory markov (vmm) models. in contrast to fixed-length markov models, which predict based on fixed-lenth histories, variable memory markov models dynamically adapt their history length based on the training data, and hence may use fewer parameters. in a test of a vmm based tagger on the brown corpus, 95.81% of tokens are correctly classified.
k-qard: a practical korean question answering framework for restricted domain. we present a korean question answering framework for restricted domains, called k-qard. k-qard is developed to achieve domain portability and robustness, and the framework is successfully applied to build question answering systems for several domains.
reading level assessment using support vector machines and statistical language models. reading proficiency is a fundamental component of language competency. however, finding topical texts at an appropriate reading level for foreign and second language learners is a challenge for teachers. this task can be addressed with natural language processing technology to assess reading level. existing measures of reading level are not well suited to this task, but previous work and our own pilot experiments have shown the benefit of using statistical language models. in this paper, we also use support vector machines to combine features from traditional reading level measures, statistical language models, and other language processing tools to produce a better method of assessing reading level.
a connectionist approach to propositional phrase attachment for real world texts. in this paper we describe a neural network-based approach to prepositional phrase attachment disam biguation for real world texts. although the use of semantic classes in this task seems intuitively to be adequate, methods employed to date have not used them very effectively. causes of their poor results are discussed. our model, which uses only classes, scores appreciably better than the other class-based methods which have been tested on the wall street journal corpus. to date, the best result obtained using only classes was a score of 79.1%; we obtained an accuracy score of 86.8%. this score is among the best reported in the literature using this corpus.
continuous space language models for statistical machine translation. statistical machine translation systems are based on one or more translation models and a language model of the target language. while many different translation models and phrase extraction algorithms have been proposed, a standard word n-gram back-off language model is used in most systems. in this work, we propose to use a new statistical language model that is based on a continuous representation of the words in the vocabulary. a neural network is used to perform the projection and the probability estimation. we consider the translation of european parliament speeches. this task is part of an international evaluation organized by the tc-star project in 2006. the proposed method achieves consistent improvements in the bleu score on the development and test data. we also present algorithms to improve the estimation of the language model probabilities when splitting long sentences into shorter chunks.
towards developing generation algorithms for text-to-text applications. we describe a new sentence realization framework for text-to-text applications. this framework uses idl-expressions as a representation formalism, and a generation mechanism based on algorithms for intersecting idl-expressions with probabilistic language models. we present both theoretical and empirical results concerning the correctness and efficiency of these algorithms.
parallel multiple context-free grammars, finite-state translation systems, and polynomial-time recognizable subclasses of lexical-functional grammars. a number of grammatical formalisms were introduced to define the syntax of natural languages. among them are parallel multiple context-free grammars (pmcfg's) and lexical-functional grammars (lfg's). pmcfg's and their subclass called multiple context-free grammars (mcfg's) are natural extensions of cfg's, and pmcfg's are known to be recognizable in polynomial time. some subclasses of lfg's have been proposed, but they were shown to generate an np-complete language. finite state translation systems (fts') were introduced as a computational model of transformational grammars. in this paper, three subclasses of lfg's called nc-lfg's, dc-lfg's and fc-lfg's are introduced and the generative capacities of the above mentioned grammatical formalisms are investigated. first, we show that the generative capacity of fts' is equal to that of nc-lfg's. as relations among subclasses of those formalisms, it is shown that the generative capacities of deterministic fts', dc-lfg's, and pmcfg's are equal to each other, and the generative capacity of fc-lfg's is equal to that of mcfg's. it is also shown that at least one np-complete language is generated by fts'. consequently, deterministic fts', dc-lfg's and fc-lfg's can be recognized in polynomial time. however, fts' (and nc-lfg's) cannot, if p &ne; np.
stochastic language generation using widl-expressions and its application in machine translation and summarization. we propose widl-expressions as a flexible formalism that facilitates the integration of a generic sentence realization system within end-to-end language processing applications. widl-expressions represent compactly probability distributions over finite sets of candidate realizations, and have optimal algorithms for realization via interpolation with language model probability distributions. we show the effectiveness of a widl-based nlg system in two sentence realization tasks: automatic translation and headline generation.
on-demand information extraction. at present, adapting an information extraction system to new topics is an expensive and slow process, requiring some knowledge engineering for each new topic. we propose a new paradigm of information extraction which operates 'on demand' in response to a user's query. on-demand information extraction (odie) aims to completely eliminate the customization effort. given a user's query, the system will automatically create patterns to extract salient relations in the text of the topic, and build tables from the extracted information using paraphrase discovery technology. it relies on recent advances in pattern discovery, paraphrase discovery, and extended named entity tagging. we report on experimental results in which the system created useful tables for many topics, demonstrating the feasibility of this approach.
discourse generation using utility-trained coherence models. we describe a generic framework for integrating various stochastic models of discourse coherence in a manner that takes advantage of their individual strengths. an integral part of this framework are algorithms for searching and training these stochastic coherence models. we evaluate the performance of our models and algorithms and show empirically that utility-trained log-linear coherence models outperform each of the individual coherence models considered.
transforming lattices into non-deterministic automata with optional null arcs. the problem of transforming a lattice into a non-deterministic finite state automaton is non-trivial. we present a transformation algorithm which tracks, for each node of an automaton under construction, the larcs which it reflects and the lattice nodes at their origins and extremities. an extension of the algorithm permits the inclusion of null, or epsilon, arcs in the output automaton. the algorithm has been successfully applied to lattices derived from dictionaries, i.e. very large corpora of strings.
semantics of conceptual graphs. conceptual graphs are both a language for representing knowledge and patterns for constructing models. they form models in the ai sense of structures that approximate some actual or possible system in the real world. they also form models in the logical sense of structures for which some set of axioms are true. when combined with recent developments in nonstandard logic and semantics, conceptual graphs can form a bridge between heuristic techniques of ai and formal techniques of model theory.
locating noun phrases with finite state transducers. we present a method for constructing, maintaining and consulting a database of proper nouns. we describe noun phrases composed of a proper noun and/or a description of a human occupation. they are formalized by finite state transducers (fst) and large coverage dictionaries and are applied to a corpus of newspapers. we take into account synonymy and hyperonymy. this first stage of our parsing procedure has a high degree of accuracy. we show how we can handle requests such as: 'find all newspaper articles in a general corpus mentioning the french prime minister', or 'how is mr. x referred to in the corpus; what have been his different occupations through out the period over which our corpus extends?' in the first case, non trivial occurrences of noun phrases are located, that is phrases not containing words present in the request, but either synonyms, or proper nouns relevant to request. the results of the search is far better than than those obtained by a key-word based engine. most answers are correct: except some cases of homonymy (where a human reader would also fail without more context). also, the treatment of people having several different occupations is not fully resolved. we have built for french, a library of about one thousand such fsts, and english fsts are under construction. the same method can be used to locate and propose new proper nouns, simply by replacing given proper names in the same fsts by variables.
a hybrid relational approach for wsd - first results. we present a novel hybrid approach for word sense disambiguation (wsd) which makes use of a relational formalism to represent instances and background knowledge. it is built using inductive logic programming techniques to combine evidence coming from both sources during the learning process, producing a rule-based wsd model. we experimented with this approach to disambiguate 7 highly ambiguous verbs in english-portuguese translation. results showed that the approach is promising, achieving an average accuracy of 75%, which outperforms the other machine learning techniques investigated (66%).
flsa: extending latent semantic analysis with features for dialogue act classification. we discuss feature latent semantic analysis (flsa), an extension to latent semantic analysis (lsa). lsa is a statistical method that is ordinarily trained on words only; flsa adds to lsa the richness of the many other linguistic features that a corpus may be labeled with. we applied flsa to dialogue act classification with excellent results. we report results on three corpora: callhome spanish, maptask, and our own corpus of tutoring dialogues.
compilation of weighted finite-state transducers from decision trees. we report on a method for compiling decision trees into weighted finite-state transducers. the key assumptions are that the tree predictions specify how to rewrite symbols from an input string, and the decision at each tree node is stateable in terms of regular expressions on the input string. each leaf node can then be treated as a separate rule where the left and right contexts are constructable from the decisions made traversing the tree from the root to the leaf. these rules are compiled into transducers using the weighted rewite-rule rule-compilation algorithm described in (mohri and sproat, 1996).
multilingual legal terminology on the jibiki platform: the lexalp project. this paper presents the particular use of "jibiki" (papillon's web server development platform) for the lexalp1 project. lexalp's goal is to harmonise the terminology on spatial planning and sustainable development used within the alpine convention2, so that the member states are able to cooperate and communicate efficiently in the four official languages (french, german, italian and slovene). to this purpose, lexalp uses the jibiki platform to build a term bank for the contrastive analysis of the specialised terminology used in six different national legal systems and four different languages. in this paper we present how a generic platform like jibiki can cope with a new kind of dictionary.
a stochastic finite-state word-segmentation algorithm for chinese. we present a stochastic finite-state model for segmenting chinese text into dictionary entries and productively derived words, and providing pronunciations for these words; the method incorporates a class-based model in its treatment of personal names. we also evaluate the system's performance, taking into account the fact that people often do not agree on a single segmentation.
accurate collocation extraction using a multilingual parser. this paper focuses on the use of advanced techniques of text analysis as support for collocation extraction. a hybrid system is presented that combines statistical methods and multilingual parsing for detecting accurate collocational information from english, french, spanish and italian corpora. the advantage of relying on full parsing over using a traditional window method (which ignores the syntactic information) is first theoretically motivated, then empirically validated by a comparative evaluation experiment.
named entity transliteration with comparable corpora. in this paper we investigate chinese-english name transliteration using comparable corpora, corpora where texts in the two languages deal in some of the same topics --- and therefore share references to named entities --- but are not translations of each other. we present two distinct methods for transliteration, one approach using phonetic transliteration, and the second using the temporal distribution of candidate pairs. each of these approaches works quite well, but by combining the approaches one can achieve even better results. we then propose a novel score propagation method that utilizes the co-occurrence of transliteration pairs within document pairs. this propagation method achieves further improvement over the best results from the previous step.
two kinds of metonymy. we propose a distinction between two kinds of metonymy: "referential" metonymy, in which the referent of an np is shifted, and "predicative" metonymy, in which the referent of the np is unchanged and the argument place of the predicate is shifted instead. examples are, respectively, "the hamburger is waiting for his check" and "which airlines fly from boston to denver". we also show that complications arise for both types of metonymy when multiple coercing predicates are considered. finally, we present implemented algorithms handling these complexities that generate both types of metonymic reading, as well as criteria for choosing one type of metonymic reading over another.
dimlex: a lexicon of discorse markers for text generation and understanding. discourse markers ('cue words') are lexical items that signal the kind of coherence relation holding between adjacent text spans; for example, because, since, and for this reason are different markers for causal relations. discourse markers are a syntactically quite heterogeneous group of words, many of which are traditionally treated as function words belonging to the realm of grammar rather than to the lexicon. but for a single discourse relation there is often a set of similar markers, allowing for a range of paraphrases for expressing the relation. to capture the similarities and differences between these, and to represent them adequately, we are developing dimlex, a lexicon of discourse markers. after describing our methodology and the kind of information to be represented in dimlex, we briefly discuss its potential applications in both text generation and understanding.
structure and intonation in spoken language undestanding. the structure imposed upon spoken sentences by intonation seems frequently to be orthogonal to their traditional surface-syntactic structure. however, the notion of "intonational structure" as formulated by pierrehumbert, selkirk, and others, can be subsumed under a rather different notion of syntactic surface structure that emerges from a theory of grammar based on a "combinatory" extension to categorial grammar. interpretations of constituents at this level are in turn directly related to "information structure", or discourse-related notions of "theme", "rheme", "focus" and "presupposition". some simplifications appear to follow for the problem of integrating syntax and other high-level modules in spoken language systems.
type-raising and directionality in combinatory grammar. the form of rules in combinatory categorial grammars (ccg) is constrained by three principles, called "adjacency", "consistency" and "inheritance". these principles have been claimed elsewhere to constrain the combinatory rules of composition and type raising in such a way as to make certain linguistic universals concerning word order under coordination follow immediately. the present paper shows that the three principles have a natural expression in a unification-based interpretation of ccg in which directional information is an attribute of the arguments of functions grounded in string position. the universals can thereby be derived as consequences of elementary assumptions. some desirable results for grammars and parsers follow, concerning type-raising rules.
alternating quantifier scope in ccg. the paper shows that movement or equivalent computational structure-changing operations of any kind at the level of logical form can be dispensed with entirely in capturing quantifier scope ambiguity. it offers a new semantics whereby the effects of quantifier scope alternation can be obtained by an entirely monotonic derivation, without type-changing rules. the paper follows fodor (1982), fodor and sag (1982), and park (1995, 1996) in viewing many apparent scope ambiguities as arising from referential categories rather than true generalized quantifiers.
constructivist development of grounded construction grammar. the paper reports on progress in building computational models of a constructivist approach to language development. it introduces a formalism for construction grammars and learning strategies based on invention, abduction, and induction. examples are drawn from experiments exercising the model in situated language games played by embodied artificial agents.
spontaneous lexicon change. the paper argues that language change can be explained through the stochasticity observed in real-world natural language use. this thesis is demonstrated by modeling language use through language games played in an evolving population of agents. we show that the artificial languages which the agents spontaneously develop based on self-organisation, do not evolve even if the population is changing. then we introduce stochasticity in language use and show that this leads to a constant innovation (new forms and new form-meaning associations) and a maintenance of variation in the population, if the agents are tolerant to variation. some of these variations overtake existing linguistic conventions, particularly in changing populations, thus explaining lexicon change.
trainable sentence planning for complex information presentations in spoken dialog systems. a challenging problem for spoken dialog systems is the design of utterance generation modules that are fast, flexible and general, yet produce high quality output in particular domains. a promising approach is trainable generation, which uses general-purpose linguistic knowledge automatically adapted to the application domain. this paper presents a trainable sentence planner for the match dialog system. we show that trainable sentence planning can produce output comparable to that of match's template-based generator even for quite complex information presentations.
a competition-based explanation of syntactic attachment preferences and garden path phenomena. this paper presents a massively parallel parser that predicts critical attachment behaviors of the human sentence processor, without the use of explicit preference heuristics or revision strategies. the processing of a syntactic ambiguity is modeled as an active, distributed competition among the potential attachments for a phrase. computationally motivated constraints on the competitive mechanism provide a principled and uniform account of a range of human attachment preferences and garden path phenomena.
a semantic approach to ie pattern induction. this paper presents a novel algorithm for the acquisition of information extraction patterns. the approach makes the assumption that useful patterns will have similar meanings to those already identified as relevant. patterns are compared using a variation of the standard vector space model in which information from an ontology is used to capture semantic similarity. evaluation shows this algorithm performs well when compared with a previously reported document-centric approach.
hahacronym: a computational humor system. computational humor will be needed in interfaces, no less than other cognitive capabilities. there are many practical settings where computational humor will add value. among them there are: business world applications (such as advertisement, e-commerce, etc.), general computer-mediated communication and human-computer interaction, increase in the friendliness of natural language interfaces, educational and edutainment systems. in particular in the educational field it is an important resource for getting selective attention, help in memorizing names and situations etc. and we all know how well it works with children.automated humor production in general is a very difficult task but we wanted to prove that some results can be achieved even in short time. we have worked at a concrete limited problem, as the core of the european project hahacronym. the main goal of hahacronym has been the realization of an acronym ironic re-analyzer and generator as a proof of concept in a focalized but non restricted context. to implement this system some general tools have been adapted, or developed for the humorous context. systems output has been submitted to evaluation by human subjects, with a very positive result.
precise n-gram probabilities from stochastic context-free grammars. we present an algorithm for computing n-gram probabilities from stochastic context-free grammars, a procedure that can alleviate some of the standard problems associated with n-grams (estimation from sparse data, lack of linguistic structure, among others). the method operates via the computation of substring expectations, which in turn is accomplished by solving systems of linear equations derived from the grammar. the procedure is fully implemented and has proved viable and useful in practice.
sentence planning as description using tree adjoining grammar. we present an algorithm for simultaneously constructing both the syntax and semantics of a sentence using a lexicalized tree adjoining grammar (ltag). this approach captures naturally and elegantly the interaction between pragmatic and syntactic constraints on descriptions in a sentence, and the inferential interactions between multiple descriptions in a sentence. at the same time, it exploits linguistically motivated, declarative specifications of the discourse functions of syntactic constructions to make contextually appropriate syntactic choices.
user-defined nonmonotonicity in unification-based formalisms. a common feature of recent unification-based grammar formalisms is that they give the user the ability to define his own structures. however, this possibility is mostly limited and does not include nonmonotonic operations. in this paper we show how nonmonotonic operations can also be user-defined by applying default logic (reiter, 1980) and generalizing previous results on nonmonotonic sorts (young and rounds, 1993).
processing complex sentences in the centering framework. we extend the centering model for the resolution of intra-sentential anaphora and specify how to handle complex sentences. an empirical evaluation indicates that the functional information structure guides the search for an antecedent within the sentence.
never look back: an alternative to centering. i propose a model for determining the hearer's attentional state which depends solely on a list of salient discourse entities (s-list). the ordering among the elements of the s-list covers also the function of the backward-looking center in the centering model. the ranking criteria for the s-list are based on the distinction between hearer-old and hearer-new discourse entities and incorporate preferences for inter- and intra-sentential anaphora. the model is the basis for an algorithm which operates incrementally, word by word.
functional centering. based on empirical evidence from a free word order language (german) we propose a fundamental revision of the principles guiding the ordering of discourse entities in the forward-looking centers within the centering model. we claim that grammatical role criteria should be replaced by indicators of the functional information structure of the utterances, i.e., the distinction between context-bound and unbound discourse elements. this claim is backed up by an empirical evaluation of functional centering.
a machine learning approach to pronoun resolution in spoken dialogue. we apply a decision tree based approach to pronoun resolution in spoken dialogue. our system deals with pronouns with np-and non-np-antecedents. we present a set of features designed for pronoun resolution in spoken dialogue and determine the most promising features. we evaluate the system on twenty switchboard dialogues and show that it compares well to byron's (2002) manually tuned system.
automated inversion of logic grammars for generation. we describe a system of reversible grammar in which, given a logic-grammar specification of a natural language, two efficient prolog programs are derived by an off-line compilation process: a parser and a generator for this language. the centerpiece of the system is the inversion algorithm designed to compute the generator code from the parser's prolog code, using the collection of minimal sets of essential arguments (msea) for predicates. the system has been implemented to work with definite clause grammars (dcg) and is a part of an english-japanese machine translation project currently under development at nyu's courant institute.
information retrieval using robust natural language processing. we developed a prototype information retrieval system which uses advanced natural language processing techniques to enhance the effectiveness of traditional key-word based document retrieval. the backbone of our system is a statistical retrieval engine which performs automated indexing of documents, then search and ranking in response to user queries. this core architecture is augmented with advanced natural language processing tools which are both robust and efficient. in early experiments, the augmented system has displayed capabilities that appear to make it superior to the purely statistical base.
summarization-based query expansion in information retrieval. we discuss a semi-interactive approach to information retrieval which consists of two tasks performed in a sequence. first, the system assists the searcher in building a comprehensive statement of information need, using automatically generated topical summaries of sample documents. second, the detailed statement of information need is automatically processed by a series of natural language processing routines in order to derive an optimal search query for a statistical information retrieval system. in this paper, we investigate the role of automated document summarization in building effective search statements. we also discuss the results of latest evaluation of our system at the annual text retrieval conference (trec).
a corpus-based approach to automatic compound extraction. an automatic compound retrieval method is proposed to extract compounds within a text message. it uses n-gram mutual information, relative frequency count and parts of speech as the features for compound extraction. the problem is modeled as a two-class classification problem based on the distributional characteristics of n-gram tokens in the compound and the non-compound clusters. the recall and precision using the proposed approach are 96.2% and 48.2% for bigram compounds and 96.6% and 39.6% for trigram compounds for a testing corpus of 49,314 words. a significant cutdown in processing time has been observed.
an improved extraction pattern representation model for automatic ie pattern acquisition. several approaches have been described for the automatic unsupervised acquisition of patterns for information extraction. each approach is based on a particular model for the patterns to be acquired, such as a predicate-argument structure or a dependency chain. the effect of these alternative models has not been previously studied. in this paper, we compare the prior models and introduce a new model, the subtree model, based on arbitrary subtrees of dependency trees. we describe a discovery procedure for this model and demonstrate experimentally an improvement in recall using subtree patterns.
incorporating speech recognition confidence into discriminative named entity recognition of speech data. this paper proposes a named entity recognition (ner) method for speech recognition results that uses confidence on automatic speech recognition (asr) as a feature. the asr confidence feature indicates whether each word has been correctly recognized. the ner model is trained using asr results with named entity (ne) labels as well as the corresponding transcriptions with ne labels. in experiments using support vector machines (svms) and speech data from japanese newspaper articles, the proposed method outperformed a simple application of text-based ner to asr results in ner f-measure by improving precision. these results show that the proposed method is effective in ner for noisy inputs.
lexical transfer using a vector-space model. building a bilingual dictionary for transfer in a machine translation system is conventionally done by hand and is very time-consuming. in order to overcome this bottleneck, we propose a new mechanism for lexical transfer, which is simple and suitable for learning from bilingual corpora. it exploits a vector-space model developed in information retrieval research. we present a preliminary result from our computational experiment.
experiments and prospects of example-based machine translation. ebmt (example-based machine translation) is proposed. ebmt retrieves similar examples (pairs of source phrases, sentences, or texts and their translations) from a database of examples, adapting the examples to translate a new input. ebmt has the following features: (1) it is easily upgraded simply by inputting appropriate examples to the database; (2) it assigns a reliability factor to the translation result; (3) it is accelerated effectively by both indexing and parallel computing; (4) it is robust because of best-match reasoning; and (5) it well utilizes translator expertise. a prototype system has been implemented to deal with a difficult translation problem for conventional rule-based machine translation (rbmt), i.e., translating japanese noun phrases of the form "n1 no n2" into english. the system has achieved about a 78% success rate on average. this paper explains the basic idea of ebmt, illustrates the experiment in detail, explains the broad applicability of ebmt to several difficult translation problems for rbmt and discusses the advantages of integrating ebmt with rbmt.
using predicate-argument structures for information extraction. in this paper we present a novel, customizable ie paradigm that takes advantage of predicate-argument structures. we also introduce a new way of automatically identifying predicate argument structures, which is central to our ie paradigm. it is based on: (1) an extended set of features; and (2) inductive decision tree learning. the experimental results prove our claim that accurate predicate-argument structures enable high quality ie results.
keyword extraction using term-domain interdependence for dictation of radio news. in this paper, we propose keyword extraction method for dictation of radio news which consists of several domains. in our method, newspaper articles which are automatically classified into suitable domains are used in order to calculate feature vectors. the feature vectors shows term-domain interdependence and are used for selecting a suitable domain of each part of radio news. keywords are extracted by using the selected domain. the results of keyword extraction experiments showed that our methods are robust and effective for dictation of radio news.
hierarchical directed acyclic graph kernel: methods for structured natural language data. this paper proposes the "hierarchical directed acyclic graph (hdag) kernel" for structured natural language data. the hdag kernel directly accepts several levels of both chunks and their relations, and then efficiently computes the weighed sum of the number of common attribute sequences of the hdags. we applied the proposed method to question classification and sentence alignment tasks to evaluate its performance as a similarity measure and a kernel function. the results of the experiments demonstrate that the hdag kernel is superior to other kernel functions and baseline methods.
convolution kernels with feature selection for natural language processing tasks. convolution kernels, such as sequence and tree kernels, are advantageous for both the concept and accuracy of many natural language processing (nlp) tasks. experiments have, however, shown that the over-fitting problem often arises when these kernels are used in nlp tasks. this paper discusses this issue of convolution kernels, and then proposes a new approach based on statistical feature selection that avoids this issue. to enable the proposed method to be executed efficiently, it is embedded into an original kernel calculation process by using sub-structure mining algorithms. experiments are undertaken on real nlp tasks to confirm the problem with a conventional method and to compare its performance with that of the proposed method.
training conditional random fields with multivariate evaluation measures. this paper proposes a framework for training conditional random fields (crfs) to optimize multivariate evaluation measures, including non-linear measures such as f-score. our proposed framework is derived from an error minimization approach that provides a simple solution for directly optimizing any evaluation measure. specifically focusing on sequential segmentation tasks, i.e. text chunking and named entity recognition, we introduce a loss function that closely reflects the target evaluation measure for these tasks, namely, segmentation f-score. our experiments show that our method performs better than standard crf training.
learning to predict case markers in japanese. japanese case markers, which indicate the grammatical relation of the complement np to the predicate, often pose challenges to the generation of japanese text, be it done by a foreign language learner, or by a machine translation (mt) system. in this paper, we describe the task of predicting japanese case markers and propose machine learning methods for solving it in two settings: (i) monolingual, when given information only from the japanese sentence; and (ii) bilingual, when also given information from a corresponding english source sentence in an mt context. we formulate the task after the well-studied task of english semantic role labelling, and explore features from a syntactic dependency structure of the sentence. for the monolingual task, we evaluated our models on the kyoto corpus and achieved over 84% accuracy in assigning correct case markers for each phrase. for the bilingual task, we achieved an accuracy of 92% per phrase using a bilingual dataset from a technical domain. we show that in both settings, features that exploit dependency information, whether derived from gold-standard annotations or automatically assigned, contribute significantly to the prediction of case markers.
a comparison of alternative parse tree paths for labeling semantic roles. the integration of sophisticated inference-based techniques into natural language processing applications first requires a reliable method of encoding the predicate-argument structure of the propositional content of text. recent statistical approaches to automated predicate-argument annotation have utilized parse tree paths as predictive features, which encode the path between a verb predicate and a node in the parse tree that governs its argument. in this paper, we explore a number of alternatives for how these parse tree paths are encoded, focusing on the difference between automatically generated constituency parses and dependency parses. after describing five alternatives for encoding parse tree paths, we investigate how well each can be aligned with the argument substrings in annotated text corpora, their relative precision and recall performance, and their comparative learning curves. results indicate that constituency parsers produce parse tree paths that can more easily be aligned to argument substrings, perform better in precision and recall, and have more favorable learning curves than those produced by a dependency parser.
improving translation through contextual information. this paper proposes a two-layered model of dialogue structure for task-oriented dialogues that processes contextual information and disambiguates speech acts. the final goal is to improve translation quality in a speech-to-speech translation system.
learning phonological rule probabilities from speech corpora with exploratory computational phonology. this paper presents an algorithm for learning the probabilities of optional phonological rules from corpora. the algorithm is based on using a speech recognition system to discover the surface pronunciations of words in speech corpora; using an automatic system obviates expensive phonetic labeling by hand. we describe the details of our algorithm and show the probabilities the system has learned for ten common phonological rules which model reductions and coarticulation effects. these probabilities were derived from a corpus of 7203 sentences of read speech from the wall street journal, and are shown to be a reasonably close match to probabilities from phonetically hand-transcribed data (timit). finally, we analyze the probability differences between rule use in male versus female speech, and suggest that the differences are caused by differing average rates of speech.
extracting semantic orientations of words using spin model. we propose a method for extracting semantic orientations of words: desirable or undesirable. regarding semantic orientations as spins of electrons, we use the mean field approximation to compute the approximate probability function of the system instead of the intractable actual probability function. we also propose a criterion for parameter selection on the basis of magnetization. given only a small number of seed words, the proposed method extracts semantic orientations with high accuracy in the experiments on english lexicon. the result is comparable to the best value ever reported.
tricolor dags for machine translation. machine translation (mt) has recently been formulated in terms of constraint-based knowledge representation and unification theories, but it is becoming more and more evident that it is not possible to design a practical mt system without an adequate method of handling mismatches between semantic representations in the source and target languages. in this paper, we introduce the idea of "information-based" mt, which is considerably more flexible than interlingual mt or the conventional transfer-based mt.
pattern-based context-free grammars for machine translation. this paper proposes the use of "patternbased" context-free grammars as a basis for building machine translation (mt) systems, which are now being adopted as personal tools by a broad range of users in the cyberspace society. we discuss major requirements for such tools, including easy customization for diverse domains, the efficiency of the translation algorithm, and scalability (incremental improvement in translation quality through user interaction), and describe how our approach meets these requirements.
modelling lexical redundancy for machine translation. certain distinctions made in the lexicon of one language may be redundant when translating into another language. we quantify redundancy among source types by the similarity of their distributions over target types. we propose a language-independent framework for minimising lexical redundancy that can be optimised directly from parallel text. optimisation of the source lexicon for a given target language is viewed as model selection over a set of cluster-based translation models.redundant distinctions between types may exhibit monolingual regularities, for example, inflexion patterns. we define a prior over model structure using a markov random field and learn features over sets of monolingual types that are predictive of bilingual redundancy. the prior makes model selection more robust without the need for language-specific assumptions regarding redundancy. using these models in a phrase-based smt system, we show significant improvements in translation quality for certain language pairs.
multi-agent explanation strategies in real-time domains. we examine the benefits of using multiple agents to produce explanations. in particular, we identify the ability to construct prior plans as a key issue constraining the effectiveness of a single-agent approach. we describe an implemented system that uses multiple agents to tackle a problem for which prior planning is particularly impractical: real-time soccer commentary. our commentary system demonstrates a number of the advantages of decomposing an explanation task among several agents. most notably, it shows how individual agents can benefit from following different discourse strategies. further, it illustrates that discourse issues such as controlling interruption, abbreviation, and maintaining consistency can also be decomposed: rather than considering them at the single level of one linear explanation they can also be tackled separately within each individual agent. we evaluate our system's output, and show that it closely compares to the speaking patterns of a human commentary team.
reactive content selection in the generation of real-time soccer commentary. mike is an automatic commentary system that generates a commentary of a simulated soccer game in english, french, or japanese.one of the major technical challenges involved in live sports commentary is the reactive selection of content to describe complex, rapidly unfolding situation. to address this challenge, mike employs importance scores that intuitively capture the amount of information communicated to the audience. we describe how a principle of maximizing the total gain of importance scores during a game can be used to incorporate content selection into the surface generation module, thus accounting for issues such as interruption and abbreviation.sample commentaries produced by mike are presented and used to evaluate different methods for content selection and generation in terms of efficiency of communication.
acquiring vocabulary for predictive text entry through dynamic reuse of a small user corpus. as mobile computing and communications have become popular, predictive text entry systems have become an increasingly important technology. existing methods still need refinement, though, with respect to personalization, especially how to acquire vocabulary not pre-registered in the system dictionary. in this paper, we report on an automatic method that dynamically obtains a user specific vocabulary from the user's unanalyzed documents. when a user makes an entry, the system dynamically extracts the corresponding chunks from the user text and suggests them along with words suggested by the dictionary. with our method, texts in a particular style or concerning a specific domain can be entered using a predictive text entry system. we verified that a large amount of words not registered in the dictionary can be entered using our method.
high precision treebanking-blazing useful trees using pos information. in this paper we present a quantitative and qualitative analysis of annotation in the hinoki treebank of japanese, and investigate a method of speeding annotation by using part-of-speech tags. the hinoki treebank is a redwoods-style treebank of japanese dictionary definition sentences. 5,000 sentences are annotated by three different annotators and the agreement evaluated. an average agreement of 65.4% was found using strict agreement, and 83.5% using labeled precision. exploiting pos tags allowed the annotators to choose the best parse with 19.5% fewer decisions.
an efficient statistical speech act type tagging system for speech translation systems. this paper describes a new efficient speech act type tagging system. this system covers the tasks of (1) segmenting a turn into the optimal number of speech act units (sa units), and (2) assigning a speech act type tag (sa tag) to each sa unit. our method is based on a theoretically clear statistical model that integrates linguistic, acoustic and situational information. we report tagging experiments on japanese and english dialogue corpora manually labeled with sa tags. we then discuss the performance difference between the two languages. we also report on some translation experiments on positive response expressions using sa tags.
active learning for statistical natural language parsing. it is necessary to have a (large) annotated corpus to build a statistical parser. acquisition of such a corpus is costly and time-consuming. this paper presents a method to reduce this demand using active learning, which selects what samples to annotate, instead of annotating blindly the whole training corpus.sample selection for annotation is based upon "representativeness" and "usefulness". a model-based distance is proposed to measure the difference of two sentences and their most likely parse trees. based on this distance, the active learning process analyzes the sample distribution by clustering and calculates the density of each sample to quantify its representativeness. further more, a sentence is deemed as useful if the existing model is highly uncertain about its parses, where uncertainty is measured by various entropy-based scores.experiments are carried out in the shallow semantic parser of an air travel dialog system. our result shows that for about the same parsing accuracy, we only need to annotate a third of the samples as compared to the usual random selection method.
the parameters of conversational style. there are several dimensions along which verbalization responds to context, resulting in individual and social differences in conversational style. style, as i use the term, is not something extra added on, like decoration. anything that is said must be said in some way; co-occurrence expectations of that "way" constitute style. the dimensions of style i will discuss are:1. fixity vs. novelty2. cohesiveness vs. expressiveness3. focus on content vs. interpersonal involvement.
coherence in spoken discourse. this paper explores the possibilities and limits of a discourse grammar applied to spontaneous speech. most discourse grammars (e.g. sdrt, asher, 1993; rst, mann & thompson, 1988) tend to be descriptive theories of written discourse which presuppose a coherent structure. this structure is the outcome of a goal directed planning process on the part of the producer. in order to obtain a better understanding of the planning process we analyse spoken discourse elicited in an experimental setting. subjects describe the pixel-per-pixel development of sketch-maps on a computer screen. this forces the speakers to conceptualise the perceived state of affairs, plan their discourse, and produce a description of the drawing at the same time. thus we find evidence for the planning process in the recorded data and can show that the discourse structures are less globally coherent than those underlying written text. in our paper we discuss to what extent a flexible discourse grammar based on a tree description grammar (tdg) (schilder, 1997) can handle such data.
automatic discovery of intentions in text and its application to question answering. semantic relations between text concepts denote the core elements of lexical semantics. this paper presents a model for the automatic detection of intention semantic relation. our approach first identifies the syntactic patterns that encode intentions, then we select syntactic and semantic features for a svm learning classifier. in conclusion, we discuss the application of intention relations to q&a.
a logic-based semantic approach to recognizing textual entailment. this paper proposes a knowledge representation model and a logic proving setting with axioms on demand successfully used for recognizing textual entailments. it also details a lexical inference system which boosts the performance of the deep semantic oriented approach on the rte data. the linear combination of two slightly different logical systems with the third lexical inference system achieves 73.75% accuracy on the rte 2006 data.
computing optimal descriptions for optimality theory grammars with context-free position structures. this paper describes an algorithm for computing optimal structural descriptions for optimality theory grammars with context-free position structures. this algorithm extends tesar's dynamic programming approach (tesar, 1994) (tesar, 1995a) to computing optimal structural descriptions from regular to context-free structures. the generalization to context-free structures creates several complications, all of which are overcome without compromising the core dynamic programming approach. the resulting algorithm has a time complexity cubic in the length of the input, and is applicable to grammars with universal constraints that exhibit context-free locality.
lexflow: a system for cross-fertilization of computational lexicons. this demo presents lexflow, a work-flow management system for cross-fertilization of computational lexicons. borrowing from techniques used in the domain of document workflows, we model the activity of lexicon management as a set of workflow types, where lexical entries move across agents in the process of being dynamically updated. a prototype of lexflow has been implemented with extensive use of xml technologies (xslt, xpath, xforms, svg) and open-source tools (cocoon, tomcat, mysql). lexflow is a web-based application that enables the cooperative and distributed management of computational lexicons.
analysis of syntax-based pronoun resolution methods. this paper presents a pronoun resolution algorithm that adheres to the constraints and rules of centering theory (grosz et al., 1995) and is an alternative to brennan et al.'s 1987 algorithm. the advantages of this new model, the left-right centering algorithm (lrc), lie in its incremental processing of utterances and in its low computational overhead. the algorithm is compared with three other pronoun resolution methods: hobbs' syntax-based algorithm, strube's s-list approach, and the bfp centering algorithm. all four methods were implemented in a system and tested on an annotated subset of the treebank corpus consisting of 2026 pronouns. the noteworthy results were that hobbs and lrc performed the best.
understanding the thematic structure of the qur'an: an exploratory multivariate approach. in this paper, we develop a methodology for discovering the thematic structure of the qur'an based on a fundamental idea in data mining and related disciplines: that, with respect to some collection of texts, the lexical frequency profiles of the individual texts are a good indicator of their conceptual content, and thus provide a reliable criterion for their classification relative to one another. this idea is applied to the discovery of thematic interrelationships among the suras (chapters) of the qur'an by abstracting lexical frequency data from them and then applying hierarchical cluster analysis to that data. the results reported here indicate that the proposed methodology yields usable results in understanding the qur'an on the basis of its lexical semantics.
predicting part-of-speech information about unknown words using statistical methods. this paper examines the feasibility of using statistical methods to train a part-of-speech predictor for unknown words. by using statistical methods, without incorporating hand-crafted linguistic information, the predictor could be used with any language for which there is a large tagged training corpus. encouraging results have been obtained by testing the predictor on unknown words from the brown corpus. the relative value of information sources such as affixes and context is discussed. this part-of-speech predictor will be used in a part-of-speech tagger to handle out-of-lexicon words.
a second-order hidden markov model for part-of-speech tagging. this paper describes an extension to the hidden markov model for part-of-speech tagging using second-order approximations for both contextual and lexical probabilities. this model increases the accuracy of the tagger to state of the art levels. these approximations make use of more contextual information than standard statistical systems. new methods of smoothing the estimated probabilities are also introduced to address the sparse data problem.
contrastive accent in a data-to-speech system. being able to predict the placement of contrastive accent is essential for the assignment of correct accentuation patterns in spoken language generation. i discuss two approaches to the generation of contrastive accent and propose and alternative method that is feasible and computationally attractive in data-to-speech systems.
real reading behavior. the most obvious observable activities that accompany reading are the eye fixations on various parts of the text. our laboratory has now developed the technology for automatically measuring and recording the sequence and duration of eye fixations that readers make in a fairly natural reading situation. this paper reports on research in progress to use our observations of this real reading behavior to construct computational models of the cognitive processes involved in natural reading.in the first part of this paper we consider some constraints placed on models of human language comprehension imposed by the eye fixation data. in the second part we propose a particular model whose processing time on each word of the text is proportional to human readers' fixation durations.
designing a task-based evaluation methodology for a spoken machine translation system. in this paper, i discuss issues pertinent to the design of a task-based evaluation methodology for a spoken machine translation (mt) system processing human to human communication rather than human to machine communication. i claim that system mediated human to human communication requires new evaluation criteria and metrics based on goal complexity and the speaker's prioritization of goals.
acquisition of a lexicon from semantic representations of sentences. a system, wolfie, that acquires a mapping of words to their semantic representation is presented and a preliminary evaluation is performed. tree least general generalizations (tlggs) of the representations of input sentences are performed to assist in determining the representations of individual words in the sentences. the best guess for a meaning of a word is the tlgg which overlaps with the highest percentage of sentence representations in which that word appears. some promising experimental results on a non-artificial data set are presented.
compose-reduce parsing. two new parsing algorithms for context-free phrase structure grammars are presented which perform a bounded amount of processing per word per analysis path, independently of sentence length. they are thus capable of parsing in real-time in a parallel implementation which forks processors in response to non-deterministic choice points.
a dp based search using monotone alignments in statistical translation. in this paper, we describe a dynamic programming (dp) based search algorithm for statistical translation and present experimental results. the statistical translation uses two sources of information: a translation model and a language model. the language model used is a standard bigram model. for the translation model, the alignment probabilities are made dependent on the differences in the alignment positions rather than on the absolute positions. thus, the approach amounts to a first-order hidden markov model (hmm) as they are used successfully in speech recognition for the time alignment problem. under the assumption that the alignment is monotone with respect to the word order in both languages, an efficient search strategy for translation can be formulated. the details of the search algorithm are described. experiments on the eutrans corpus produced a word error rate of 5.1%.
a localized prediction model for statistical machine translation. in this paper, we present a novel training method for a localized phrase-based prediction model for statistical machine translation (smt). the model predicts blocks with orientation to handle local phrase re-ordering. we use a maximum likelihood criterion to train a log-linear block bigram model which uses real-valued features (e.g. a language model score) as well as binary features based on the block identities themselves, e.g. block bigram features. our training algorithm can easily handle millions of features. the best system obtains a 18.6% improvement over the baseline on a standard arabic-english translation task.
a discriminative global training algorithm for statistical mt. this paper presents a novel training algorithm for a linearly-scored block sequence translation model. the key component is a new procedure to directly optimize the global scoring function used by a smt decoder. no translation, language, or distortion model probabilities are used as in earlier work on smt. therefore our method, which employs less domain specific knowledge, is both simpler and more extensible than previous approaches. moreover, the training procedure treats the decoder as a black-box, and thus can be used to optimize any decoding scheme. the training algorithm is evaluated on a standard arabic-english translation task.
quasi-destructive graph unification. graph unification is the most expensive part of unification-based grammar parsing. it often takes over 90% of the total parsing time of a sentence. we focus on two speed-up elements in the design of unification algorithms: 1) elimination of excessive copying by only copying successful unifications, 2) finding unification failures as soon as possible. we have developed a scheme to attain these two elements without expensive overhead through temporarily modifying graphs during unification to eliminate copying during unification. we found that parsing relatively long sentences (requiring about 500 top-level unifications during a parse) using our algorithm is approximately twice as fast as parsing the same sentences using wroblewski's algorithm.
statistical phrase-based models for interactive computer-assisted translation. obtaining high-quality machine translations is still a long way off. a post-editing phase is required to improve the output of a machine translation system. an alternative is the so called computer-assisted translation. in this framework, a human translator interacts with the system in order to obtain high-quality translations. a statistical phrase-based approach to computer-assisted translation is described in this article. a new decoder algorithm for interactive search is also presented, that combines monotone and non-monotone search. the system has been assessed in the trans type-2 project for the translation of several printer manuals, from (to) english to (from) spanish, german and french.
graph-structured stack and natural language parsing. a general device for handling nondeterminism in stack operations is described. the device, called a graph-structured stack, can eliminate duplication of operations throughout the nondeterministic processes. this paper then applies the graph-structured stack to various natural language parsing methods, including atn, lr parsing, categorial grammar and principle-based parsing. the relationship between the graph-structured stack and a chart in chart parsing is also discussed.
maximizing top-down constraints for unification-based systems. a left-corner parsing algorithm with topdown filtering has been reported to show very efficient performance for unification-based systems. however, due to the nontermination of parsing with left-recursive grammars, top-down constraints must be weakened. in this paper, a general method of maximizng top-down constraints is proposed. the method provides a procedure to dynamically compute restrictor, a minimum set of features involved in an infinite loop for every propagation path; thus top-down constraints are maximally propagated.
joint learning improves semantic role labeling. despite much recent progress on accurate semantic role labeling, previous work has largely used independent classifiers, possibly combined with separate label sequence models via viterbi decoding. this stands in stark contrast to the linguistic observation that a core argument frame is a joint structure, with strong dependencies between arguments. we show how to build a joint model of argument frames, incorporating novel features that model these interactions into discriminative log-linear models. this system achieves an error reduction of 22% on all arguments and 32% on core arguments over a state-of-the art independent classifier for gold-standard parse trees on propbank.
pronunciation modeling for improved spelling correction. this paper presents a method for incorporating word pronunciation information in a noisy channel model for spelling correction. the proposed method builds an explicit error model for word pronunciations. by modeling pronunciation similarities between words we achieve a substantial performance improvement over the previous best performing models for spelling correction.
discourse obligations in dialogue processing. we show that in modeling social interaction, particularly dialogue, the attitude of obligation can be a useful adjunct to the popularly considered attitudes of belief, goal, and intention and their mutual and shared counterparts. in particular, we show how discourse obligations can be used to account in a natural manner for the connection between a question and its answer in dialogue and how obligations can be used along with other parts of the discourse context to extend the coverage of a dialogue system.
spatial lexicalization in the translation of prepositional phrases. a pattern in the translation of locative prepositional phrases between english and spanish is presented. a way of exploiting this pattern is proposed in the context of a multilingual machine translation system under development.
using word support model to improve chinese input system. this paper presents a word support model (wsm). the wsm can effectively perform homophone selection and syllable-word segmentation to improve chinese input systems. the experimental results show that: (1) the wsm is able to achieve tonal (syllables input with four tones) and toneless (syllables input without four tones) syllable-to-word (stw) accuracies of 99% and 92%, respectively, among the converted words; and (2) while applying the wsm as an adaptation processing, together with the microsoft input method editor 2003 (msime) and an optimized bigram model, the average tonal and toneless stw improvements are 37% and 35%, respectively.
integrated morphological and syntactic disambiguation for modern hebrew. current parsing models are not immediately applicable for languages that exhibit strong interaction between morphology and syntax, e.g., modern hebrew (mh), arabic and other semitic languages. this work represents a first attempt at modeling morphological-syntactic interaction in a generative probabilistic framework to allow for mh parsing. we show that morphological information selected in tandem with syntactic categories is instrumental for parsing semitic languages. we further show that redundant morphological information helps syntactic disambiguation.
tagging english by path voting constraints. we describe a constraint-based tagging approach where individual constraint rules vote on sequences of matching tokens and tags. disambiguation of all tokens in a sentence is performed at the very end by selecting tags that appear on the path that receives the highest vote. this constraint application paradigm makes the outcome of the disambiguation independent of the rule sequence, and hence relieves the rule developer from worrying about potentially conflicting rule sequencing. the approach can also combine statistically and manually obtained constraints, and incorporate negative constraint rules to rule out certain patterns. we have applied this approach to tagging english text from the wall street journal and the brown corpora. our results from the wall street journal corpus indicate that with 400 statistically derived constraint rules and about 800 hand-crafted constraint rules, we can attain an average accuracy of 97.89% on the training corpus and an average accuracy of 97.50% on the testing corpus. we can also relax the single tag per token limitation and allow ambiguous tagging which lets us trade recall and precision.
automatically creating bilingual lexicons for machine translation from bilingual text. a method is presented for automatically augmenting the bilingual lexicon of an existing machine translation system, by extracting bilingual entries from aligned bilingual text. the proposed method only relies on the resources already available in the mt system itself. it is based on the use of bilingual lexical templates to match the terminal symbols in the parses of the aligned sentences.
advances in discriminative parsing. the present work advances the accuracy and training speed of discriminative parsing. our discriminative parsing method has no generative component, yet surpasses a generative baseline on constituent parsing, and does so with minimal linguistic cleverness. our model can incorporate arbitrary features of the input and parse state, and performs feature selection incrementally over an exponential feature space during training. we demonstrate the flexibility of our approach by testing it with several parsing strategies and various feature sets. our implementation is freely available at: http://nlp.cs.nyu.edu/parser/.
supervised and unsupervised learning for sentence compression. in statistics-based summarization - step one: sentence compression, knight and marcu (knight and marcu, 2000) (k&m) present a noisy-channel model for sentence compression. the main difficulty in using this method is the lack of data; knight and marcu use a corpus of 1035 training sentences. more data is not easily available, so in addition to improving the original k&m noisy-channel model, we create unsupervised and semi-supervised models of the task. finally, we point out problems with modeling the task in this way. they suggest areas for future research.
thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews. this paper presents a simple unsupervised learning algorithm for classifying reviews as recommended (thumbs up) or not recommended (thumbs down). the classification of a review is predicted by the average semantic orientation of the phrases in the review that contain adjectives or adverbs. a phrase has a positive semantic orientation when it has good associations (e.g., "subtle nuances") and a negative semantic orientation when it has bad associations (e.g., "very cavalier"). in this paper, the semantic orientation of a phrase is calculated as the mutual information between the given phrase and the word "excellent" minus the mutual information between the given phrase and the word "poor". a review is classified as recommended if the average semantic orientation of its phrases is positive. the algorithm achieves an average accuracy of 74% when evaluated on 410 reviews from epinions, sampled from four different domains (reviews of automobiles, banks, movies, and travel destinations). the accuracy ranges from 84% for automobile reviews to 66% for movie reviews.
expressing implicit semantic relations without supervision. we present an unsupervised learning algorithm that mines large text corpora for patterns that express implicit semantic relations. for a given input word pair x:y with some unspecified semantic relations, the corresponding output list of patterns (p1,..., pm) is ranked according to how well each pattern pi expresses the relations between x and y. for example, given x = ostrich and y = bird, the two highest ranking output patterns are "x is the largest y" and "y such as the x". the output patterns are intended to be useful for finding further pairs with the same relations, to support the construction of lexicons, ontologies, and semantic networks. the patterns are sorted by pertinence, where the pertinence of a pattern pi for a word pair x:y is the expected relational similarity between the given pair and typical pairs for pi. the algorithm is empirically evaluated on two tasks, solving multiple-choice sat word analogy questions and classifying semantic relations in noun-modifier pairs. on both tasks, the algorithm achieves state-of-the-art results, performing significantly better than several alternative pattern ranking algorithms, based on tf-idf.
named entity extraction based on a maximum entropy model and transformation rules. this paper describes named entity (ne) extraction based on a maximum entropy (m. e.) model and transformation rules. there are two types of named entities when focusing on the relationship between morphemes and nes as defined in the ne task of the irex competition held in 1999. each ne consists of one or more morphemes, or includes a substring of a morpheme. we extract the former type of ne by using the m. e. model. we then extract the latter type of ne by applying transformation rules to the text.
morphological analysis of a large spontaneous speech corpus in japanese. this paper describes two methods for detecting word segments and their morphological information in a japanese spontaneous speech corpus, and describes how to tag a large spontaneous speech corpus accurately by using the two methods. the first method is used to detect any type of word segments. the second method is used when there are several definitions for word segments and their pos categories, and when one type of word segments includes another type of word segments. in this paper, we show that by using semi-automatic analysis we achieve a precision of better than 99% for detecting and tagging short words and 97% for long words; the two types of words that comprise the corpus. we also show that better accuracy is achieved by using both methods than by using only the first.
trimming cfg parse trees for sentence compression using machine learning approaches. sentence compression is a task of creating a short grammatical sentence by removing extraneous words or phrases from an original sentence while preserving its meaning. existing methods learn statistics on trimming context-free grammar (cfg) rules. however, these methods sometimes eliminate the original meaning by incorrectly removing important parts of sentences, because trimming probabilities only depend on parents' and daughters' non-terminals in applied cfg rules. we apply a maximum entropy model to the above method. our method can easily include various features, for example, other parts of a parse tree or words the sentences contain. we evaluated the method using manually compressed sentences and human judgments. we found that our method produced more grammatical and informative compressed sentences than other methods.
a method for relating multiple newspaper articles by using graphs, and its application to webcasting. this paper describes methods for relating (threading) multiple newspaper articles, and for visualizing various characteristics of them by using a directed graph. a set of articles is represented by a set of word vectors, and the similarity between the vectors is then calculated. the graph is constructed from the similarity matrix. by applying some constraints on the chronological ordering of articles, an efficient threading algorithm that runs in o(n) time (where n is the number of articles) is obtained. the constructed graph is visualized with words that represent the topics of the threads, and words that represent new information in each article. the threading technique is suitable for webcasting (push) applications. a threading server determines relationships among articles from various news sources, and creates files containing their threading information. this information is represented in extended markup language (xml), and can be visualized on most web browsers. the xml-based representation and a current prototype are described in this paper.
strategies for adding control information to declarative grammars. strategies are proposed for combining different kinds of constraints in declarative grammars with a detachable layer of control information. the added control information is the basis for parametrized dynamically controlled linguistic deduction, a form of linguistic processing that permits the implementation of plausible linguistic performance models without giving up the declarative formulation of linguistic competence. the information can be used by the linguistic processor for ordering the sequence in which conjuncts and disjuncts are processed, for mixing depth-first and breadth-first search, for cutting off undesired derivations, and for constraint-relaxation.
a statistical model for domain-independent text segmentation. we propose a statistical method that finds the maximum-probability segmentation of a given text. this method does not require training data because it estimates probabilities from the given text. therefore, it can be applied to any text in any domain. an experiment showed that the method is more accurate than or at least as accurate as a state-of-the-art text segmentation system.
reliable measures for aligning japanese-english news articles and sentences. we have aligned japanese and english news articles and sentences to make a large parallel corpus. we first used a method based on cross-language information retrieval (clir) to align the japanese and english articles and then used a method based on dynamic programming (dp) matching to align the japanese and english sentences in these articles. however, the results included many incorrect alignments. to remove these, we propose two measures (scores) that evaluate the validity of alignments. the measure for article alignment uses similarities in sentences aligned by dp matching and that for sentence alignment uses similarities in articles aligned by clir. they enhance each other to improve the accuracy of alignment. using these measures, we have successfully constructed a large-scale article and sentence alignment corpus available to the public.
organizing english reading materials for vocabulary learning. we propose a method of organizing reading materials for vocabulary learning. it enables us to select a concise set of reading texts (from a target corpus) that contains all the target vocabulary to be learned. we used a specialized vocabulary for an english certification test as the target vocabulary and used english wikipedia, a free-content encyclopedia, as the target corpus. the organized reading materials would enable learners not only to study the target vocabulary efficiently but also to gain a variety of knowledge through reading. the reading materials are available on our web site.
word vectors and two kinds of similarity. this paper examines what kind of similarity between words can be represented by what kind of word vectors in the vector space model. through two experiments, three methods for constructing word vectors, i.e., lsa-based, cooccurrence-based and dictionary-based methods, were compared in terms of the ability to represent two kinds of similarity, i.e., taxonomic similarity and associative similarity. the result of the comparison was that the dictionary-based word vectors better reflect taxonomic similarity, while the lsa-based and the cooccurrence-based word vectors better reflect associative similarity.
general-to-specific model selection for subcategorization preference. this paper proposes a novel method for learning probability models of subcategorization preference of verbs. we consider the issues of case dependencies and noun class generalization in a uniform way by employing the maximum entropy modeling method. we also propose a new model selection algorithm which starts from the most general model and gradually examines more specific models. in the experimental evaluation, it is shown that both of the case dependencies and specific sense restriction selected by the proposed method contribute to improving the performance in subcategorization preference resolution.
a minimalist head-corner parser. in the minimalist program (chomsky, 1992) it is assumed that there are different types of projections (lexical and functional) and therefore different types of heads. this paper explains why functional heads are not treated as head-corners by the minimalist head-corner parser described here.
computer aided interpretation of lexical coocurrences. this paper addresses the problem of developing a large semantic lexicon for natural language processing. the increasing availability of machine readable documents offers an opportunity to the field of lexical semantics, by providing experimental evidence of word uses (on-line texts) and word definitions (on-line dictionaries).the system presented hereafter, petrarca, detects word cooccurrences from a large sample of press agency releases on finance and economics, and uses these associations to build a case-based semantic lexicon. synt&aacute;ctically valid cooccurences including a new word w are detected by a high-coverage morphosyntactic analyzer. syntactic relations are interpreted e.g. replaced by case relations, using a a catalogue of patterns/interpretation pairs, a concept type hierarchy, and a set of selectional restriction rules on semantic interpretation types.
effective phrase translation extraction from alignment models. phrase level translation models are effective in improving translation quality by addressing the problem of local re-ordering across language boundaries. methods that attempt to fundamentally modify the traditional ibm translation model to incorporate phrases typically do so at a prohibitive computational cost. we present a technique that begins with improved ibm models to create phrase level knowledge sources that effectively represent local as well as global phrasal context. our method is robust to noisy alignments at both the sentence and corpus level, delivering high quality phrase level translation pairs that contribute to significant improvements in translation quality (as measured by the bleu metric) over word based lexica as well as a competing alignment based method.
multilingual computational semantic lexicons in action: the wysinnwyg approach to nlp. much effort has been put into computational lexicons over the years, and most systems give much room to (lexical) semantic data. however, in these systems, the effort put on the study and representation of lexical items to express the underlying continuum existing in 1) language vagueness and polysemy, and 2) language gaps and mismatches, has remained embryonic. a sense enumeration approach fails from a theoretical point of view to capture the core meaning of words, let alone relate word meanings to one another, and complicates the task of nlp by multiplying ambiguities in analysis and choices in generation. in this paper, i study computational semantic lexicon representation from a multilingual point of view, reconciling different approaches to lexicon representation: i) vagueness for lexemes which have a more or less finer grained semantics with respect to other languages; ii) underspecification for lexemes which have multiple related facets; and, iii) lexical rules to relate systematic polysemy to systematic ambiguity. i build on a what you see is not necessarily what you get (wysinnwyg) approach to provide the nlp system with the "right" lexical data already tuned towards a particular task. in order to do so, i argue for a lexical semantic approach to lexicon representation. i exemplify my study through a cross-linguistic investigation on spatially-based expressions.
the computational lexical semantics of syntagmatic relations. in this paper, we address the issue of syntagmatic expressions from a computational lexical semantic perspective. from a representational viewpoint, we argue for a hybrid approach combining linguistic and conceptual paradigms, in order to account for the continuum we find in natural languages from free combining words to frozen expressions. in particular, we focus on the place of lexical and semantic restricted co-occurrences. from a processing viewpoint, we show how to generate/analyze syntagmatic expressions by using an efficient constraintbased processor, well fitted for a knowledge-driven approach.
from submit to submitted via submission: on lexical rules in large-scale lexicon acquisition. this paper deals with the discovery, representation, and use of lexical rules (lrs) during large-scale semi-automatic computational lexicon acquisition. the analysis is based on a set of lrs implemented and tested on the basis of spanish and english business- and finance-related corpora. we show that, though the use of lrs is justified, they do not come cost-free. semi-automatic output checking is required, even with blocking and preemtion procedures built in. nevertheless, large-scope lrs are justified because they facilitate the unavoidable process of large-scale semi-automatic lexical acquisition. we also argue that the place of lrs in the computational process is a complex issue.
towards resolution of bridging descriptions. we present preliminary results concerning robust techniques for resolving bridging definite descriptions. we report our analysis of a collection of 20 wall street journal articles from the penn treebank corpus and our experiments with wordnet to identify relations between bridging descriptions and their antecedents.
polynomial time parsing of combinatory categorial grammars. in this paper we present a polynomial time parsing algorithm for combinatory categorial grammar. the recognition phase extends the cky algorithm for cfg. the process of generating a representation of the parse trees has two phases. initially, a shared forest is build that encodes the set of all derivation trees for the input string. this shared forest is then pruned to remove all spurious ambiguity.
information states as first class citizens. the information state of an agent is changed when a text (in natural language) is processed. the meaning of a text can be taken to be this information state change potential. the inference of a consequence make explicit something already implicit in the premises --- i.e. that no information state change occurs if the (assumed) consequence text is processed after the (given) premise texts have been processed. elementary logic (i.e. first-order logic) can be used as a logical representation language for texts, but the notion of a information state (a set of possibilities --- namely first-order models) is not available from the object language (belongs to the meta language). this means that texts with other texts as parts (e.g. propositional attitudes with embedded sentences) cannot be treated directly. traditional intensional logics (i.e. modal logic) allow (via modal operators) access to the information states from the object language, but the access is limited and interference with (extensional) notions like (standard) identity, variables etc. is introduced. this does not mean that the ideas present in intensional logics will not work (possibly improved by adding a notion of partiality), but rather that often a formalisation in the simple type theory (with sorts for entities and indices making information states first class citizens --- like individuals) is more comprehensible, flexible and logically well-behaved.
translation with cascaded finite state transducers. in this paper we discuss the use of cascaded finite state transducers for machine translation. a number of small, dedicated transducers is applied to convert sentence pairs from a bilingual corpus into generalized translation patterns. these patterns, together with the transducers are then used as a hierarchical translation memory for fully automatic translation. results on the german--english verbmobil corpus are given.
probing the lexicon in evaluating commercial mt systems. in the past the evaluation of machine translation systems has focused on single system evaluations because there were only few systems available. but now there are several commercial systems for the same language pair. this requires new methods of comparative evaluation. in the paper we propose a black-box method for comparing the lexical coverage of mt systems. the method is based on lists of words from different frequency classes. it is shown how these word lists can be compiled and used for testing. we also present the results of using our method on 6 mt systems that translate between english and german.
inducing german semantic verb classes from purely syntactic subcategorisation information. the paper describes the application of k-means, a standard clustering technique, to the task of inducing semantic classes for german verbs. using probability distributions over verb subcategorisation frames, we obtained an intuitively plausible clustering of 57 verbs into 14 classes. the automatic clustering was evaluated against independently motivated, hand-constructed semantic verb classes. a series of post-hoc cluster analyses explored the influence of specific frames and frame groups on the coherence of the verb classes, and supported the tight connection between the syntactic behaviour of the verbs and their lexical meaning components.
evaluating discourse processing algorithms. in order to take steps towards establishing a methodology for evaluating natural language systems, we conducted a case study. we attempt to evaluate two different approaches to anaphoric processing in discourse by comparing the accuracy and coverage of two published algorithms for finding the co-specifiers of pronouns in naturally occurring texts and dialogues. we present the quantitative results of hand-simulating these algorithms, but this analysis naturally gives rise to both a qualititive evaluation and recommendations for performing such evaluations in general. we illustrate the general difficulties encountered with quantitative evaluation. these are problems with: (a) allowing for underlying assumptions, (b) determining how to handle underspecifications, and (c) evaluating the contribution of false positives and error chaining.
learning optimal dialogue strategies: a case study of a spoken dialogue agent for email. this paper describes a novel method by which a dialogue agent can learn to choose an optimal dialogue strategy. while it is widely agreed that dialogue strategies should be formulated in terms of communicative intentions, there has been little work on automatically optimizing an agent's choices when there are multiple ways to realize a communicative intention. our method is based on a combination of learning algorithms and empirical evaluation techniques. the learning component of our method is based on algorithms for reinforcement learning, such as dynamic programming and q-learning. the empirical component uses the paradise evaluation framework (walker et al., 1997) to identify the important performance factors and to provide the performance function needed by the learning algorithm. we illustrate our method with a dialogue agent named elvis (email voice interactive system), that supports access to email over the phone. we show how elvis can learn to choose among alternate strategies for agent initiative, for reading messages, and for summarizing email folders.
paradise: a framework for evaluating spoken dialogue agents. this paper presents paradise (paradigm for dialogue system evaluation), a general framework for evaluating spoken dialogue agents. the framework decouples task requirements from an agent's dialogue behaviors, supports comparisons among dialogue strategies, enables the calculation of performance over subdialogues and whole dialogues, specifies the relative contribution of various factors to performance, and makes it possible to compare agents performing different tasks by normalizing for task complexity.
quantitative and qualitative evaluation of darpa communicator spoken dialogue systems. this paper describes the application of the paradise evaluation framework to the corpus of 662 human-computer dialogues collected in the june 2000 darpa communicator data collection. we describe results based on the standard logfile metrics as well as results based on additional qualitative metrics derived using the date dialogue act tagging scheme. we show that performance models derived via using the standard metrics can account for 37% of the variance in user satisfaction, and that the addition of date metrics improved the models by an absolute 5%.
mixed initiative in dialogue: an investigation into discourse segmentation. conversation between two people is usually of mixed-initiative, with control over the conversation being transferred from one person to another. we apply a set of rules for the transfer of control to 4 sets of dialogues consisting of a total of 1862 turns. the application of the control rules lets us derive domain-independent discourse structures. the derived structures indicate that initiative plays a role in the structuring of discourse. in order to explore the relationship of control and initiative to discourse processes like centering, we analyze the distribution of four different classes of anaphora for two data sets. this distribution indicates that some control segments are hierarchically related to others. the analysis suggests that discourse participants often mutually agree to a change of topic. we also compared initiative in task oriented and advice giving dialogues and found that both allocation of control and the manner in which control is transferred is radically different for the two dialogue types. these differences can be explained in terms of collaborative planning principles.
understanding scene descriptions as event simulations. the language of scene descriptions must allow a hearer to build structures of schemas similar (to some level of detail) to those the speaker has built via perceptual processes. the understanding process in general requires a hearer to create and run <u>"event simulations"</u> to check the consistency and plausibility of a "picture" constructed from a speaker's description. a speaker must also run similar event simulations on his own descriptions in order to be able to judge when the hearer has been given sufficient information to construct an appropriate "picture", and to be able to respond appropriately to the hearer's questions about or responses to the scene description.in this paper i explore some simple scene description examples in which a hearer must make judgements involving reasoning about scenes, space, common-sense physics, cause-effect relationships, etc. while i propose some mechanisms for dealing with such scene descriptions, my primary concern at this time is to flesh out our understanding of just what the mechanisms must accomplish: what information will be available to them and what information must be found or generated to account for the inferences we know are actually made.
automatic english-chinese name transliteration for development of multilingual resources. in this paper, we describe issues in the translation of proper names from english to chinese which we have faced in constructing a system for multilingual text generation supporting both languages. we introduce an algorithm for mapping from english names to chinese characters based on (1) heuristics about relationships between english spelling and pronunciation, and (2) consistent relationships between english phonemes and chinese characters.
dual-coding theory and connectionist lexical selection. we introduce the bilingual dual-coding theory as a model for bilingual mental representation. based on this model, lexical selection neural networks are implemented for a connectionist transfer project in machine translation.
combining statistical and knowledge-based spoken language understanding in conditional models. spoken language understanding (slu) addresses the problem of extracting semantic meaning conveyed in an utterance. the traditional knowledge-based approach to this problem is very expensive --- it requires joint expertise in natural language processing and speech recognition, and best practices in language engineering for every new domain. on the other hand, a statistical learning approach needs a large amount of annotated data for model training, which is seldom available in practical applications outside of large research labs. a generative hmm/cfg composite model, which integrates easy-to-obtain domain knowledge into a data-driven statistical learning framework, has previously been introduced to reduce data requirement. the major contribution of this paper is the investigation of integrating prior knowledge and statistical learning in a conditional model framework. we also study and compare conditional random fields (crfs) with perceptron learning for slu. experimental results show that the conditional models achieve more than 20% relative reduction in slot error rate over the hmm/cfg model, which had already achieved an slu accuracy at the same level as the best results reported on the atis data.
an automatic treebank conversion algorithm for corpus sharing. an automatic treebank conversion method is proposed in this paper to convert a treebank into another treebank. a new treebank associated with a different grammar can be generated automatically from the old one such that the information in the original treebank can be transformed to the new one and be shared among different research communities. the simple algorithm achieves conversion accuracy of 96.4% when tested on 8,867 sentences between two major grammar revisions of a large mt system.
extracting key semantic terms from chinese speech query for web searches. this paper discusses the challenges and proposes a solution to performing information retrieval on the web using chinese natural language speech query. the main contribution of this research is in devising a divide-and-conquer strategy to alleviate the speech recognition errors. it uses the query model to facilitate the extraction of main core semantic string (css) from the chinese natural language speech query. it then breaks the css into basic components corresponding to phrases, and uses a multi-tier strategy to map the basic components to known phrases in order to further eliminate the errors. the resulting system has been found to be effective.
predicting intonational phrasing from text. determining the relationship between the intonational characteristics of an utterance and other features inferable from its text is important both for speech recognition and for speech synthesis. this work investigates the use of text analysis in predicting the location of intonational phrase boundaries in natural speech, through analyzing 298 utterances from the darpa air travel information service database. for statistical modeling, we employ classification and regression tree (cart) techniques. we achieve success rates of just over 90%, representing a major improvement over other attempts at boundary prediction from unrestricted text.
a fast, accurate deterministic parser for chinese. we present a novel classifier-based deterministic parser for chinese constituency parsing. our parser computes parse trees from bottom up in one pass, and uses classifiers to make shift-reduce decisions. trained and evaluated on the standard training and test sets, our best model (using stacked classifiers) runs in linear time and has labeled precision and recall above 88% using gold-standard part-of-speech tags, surpassing the best published results. our svm parser is 2-13 times faster than state-of-the-art parsers, while producing more accurate results. our maxent and dtree parsers run at speeds 40-270 times faster than state-of-the-art parsers, but with 5-6% losses in accuracy.
decoding algorithm in statistical machine translation. decoding algorithm is a crucial part in statistical machine translation. we describe a stack decoding algorithm in this paper. we present the hypothesis scoring method and the heuristics used in our algorithm. we report several techniques deployed to improve the performance of the decoder. we also introduce a simplified model to moderate the sparse data problem and to speed up the decoding process. we evaluate and compare these techniques/models in our statistical machine translation system.
modeling with structures in statistical machine translation. most statistical machine translation systems employ a word-based alignment model. in this paper we demonstrate that word-based alignment is a major cause of translation errors. we propose a new alignment model based on shallow phrase structures, and the structures can be automatically acquired from parallel corpus. this new model achieved over 10% error reduction for our spoken language translation task.
word alignment for languages with scarce resources using bilingual corpora of other language pairs. this paper proposes an approach to improve word alignment for languages with scarce resources using bilingual corpora of other language pairs. to perform word alignment between languages l1 and l2, we introduce a third language l3. although only small amounts of bilingual data are available for the desired language pair l1-l2, large-scale bilingual corpora in l1-l3 and l2-l3 are available. based on these two additional corpora and with l3 as the pivot language, we build a word alignment model for l1 and l2. this approach can build a word alignment model for two languages even if no bilingual corpus is available in this language pair. in addition, we build another word alignment model for l1 and l2 using the small l1-l2 bilingual corpus. then we interpolate the above two models to further improve word alignment between l1 and l2. experimental results indicate a relative error rate reduction of 21.30% as compared with the method only using the small bilingual corpus in l1 and l2.
sinhala grapheme-to-phoneme conversion and rules for schwa epenthesis. this paper describes an architecture to convert sinhala unicode text into phonemic specification of pronunciation. the study was mainly focused on disambiguating /schwa/ and /a/ vowel epenthesis for consonants, which is one of the significant problems found in sinhala. this problem has been addressed by formulating a set of rules. the proposed set of rules was tested using 30,000 distinct words obtained from a corpus and compared with the same words manually transcribed to phonemes by an expert. the grapheme-to-phoneme (g2p) conversion model achieves 98% accuracy.
using leading text for news summaries: evaluation results and implications for commercial summarization applications. leading text extracts created to support some online boolean retrieval goals are evaluated for their acceptability as news document summaries. results are presented and discussed from the perspective of commercial summarization technology needs.
aligning articles in tv newscasts and newspapers. it is important to use pattern information (e.g. tv newscasts) and textual information (e.g. newspapers) together. for this purpose, we describe a method for aligning articles in tv newscasts and newspapers. in order to align articles, the alignment system uses words extracted from telops in tv newscasts. the recall and the precision of the alignment process are 97% and 89%, respectively. in addition, using the results of the alignment process, we develop a browsing and retrieval system for articles in tv newscasts and newspapers.
chunk-based statistical translation. this paper describes an alternative translation model based on a text chunk under the framework of statistical machine translation. the translation model suggested here first performs chunking. then, each word in a chunk is translated. finally, translated chunks are reordered. under this scenario of translation modeling, we have experimented on a broad-coverage japanese-english traveling corpus and achieved improved performance.
a pattern-based machine translation system extended by example-based processing. in this paper, we describe a machine translation system called palmtree which uses the "pattern based" approach as a fundamental framework. the pure pattern-based translation framework has several issues. one is the performance due to using many rules in the parsing stage, and the other is inefficiency of usage of translation patterns due to the exact-matching. to overcome these problems, we describe several methods; pruning techniques for the former, and introduction of example-based processing for the latter.
left-to-right target generation for hierarchical phrase-based translation. we present a hierarchical phrase-based statistical machine translation in which a target sentence is efficiently generated in left-to-right order. the model is a class of synchronous-cfg with a greibach normal form-like structure for the projected production rule: the paired target-side of a production rule takes a phrase prefixed form. the decoder for the target-normalized form is based on an early-style top down parser on the source side. the target-normalized form coupled with our top down parser implies a left-to-right generation of translations which enables us a straightforward integration with ngram language models. our model was experimented on a japanese-to-english newswire translation task, and showed statistically significant performance improvements against a phrase-based translation system.
discourse deixis: reference to discourse segments. computational approaches to discourse understanding have a two-part goal: (1) to identify those aspects of discourse understanding that require process-based accounts, and (2) to characterize the processes and data structures they involve. to date, in the area of reference, process-based accounts have been developed for subsequent reference via anaphoric pronouns and reference via definite descriptors. in this paper, i propose and argue for a process-based account of subsequent reference via deictic expressions. a significant feature of this account is that it attributes distinct mental reality to units of text often called discourse segments, a reality that is distinct from that of the entities described therein.
accommodating context change. two independent mechanisms of context change have been discussed separately in the literature - context change by entity introduction and context change by event simulation. here we discuss their integration. the effectiveness of the integration depends in part on a representation of events that captures people's uncertainty about their outcome - in particular, people's incomplete expectations about the changes effected by events. we propose such a representation and a process of accommodation that makes use of it, and discuss our initial implementation of these ideas.
discourse relations: a structural and presuppositional account using lexicalised tag. we show that discourse structure need not bear the full burden of conveying discourse relations by showing that many of them can be explained <i>nonstructurally</i> in terms of the grounding of <i>anaphoric presuppositions</i> (van der sandt, 1992). this simplifies discourse structure, while still allowing the realisation of a full range of discourse relations. this is achieved using the same semantic machinery used in deriving clause-level semantics.
prospects for computer-assisted dialect adaption. this paper describes a project which has explored the feasibility of using a computer to perform a significant portion of the changes required to adapt text from one dialect to several others. this ongoing experiment has examined adaptation between various dialects of quechua, finding that a computer program may be an important tool for adaptation. an experimental computer program was written and applied to text, and its output was field tested in five target dialects. preliminary results indicate that preprocessing text with a computer may 1) enable informants who are not bi-dialectical (in the source and target dialects) to produce adequate adaptations without much coaching from the linguist/translator; 2) improve the quality of the resulting text; and 3) reduce time and effortm-both in adaptation and in manuscript preparation.
automatic acquisition of the lexical semantics of verbs from sentence frames. this paper presents a computational model of verb acquisition which uses what we will call the principle of structured overcommitment to eliminate the need for negative evidence. the learner escapes from the need to be told that certain possibilities cannot occur (i.e., are "ungrammatical") by one simple expedient: it assumes that all properties it has observed are either obligatory or forbidden until it sees otherwise, at which point it decides that what it thought was either obligatory or forbidden is merely optional. this model is built upon a classification of verbs based upon a simple three-valued set of features which represents key aspects of a verb's syntactic structure, its predicate/argument structure, and the mapping between them.
twicpen: hand-held scanner and translation software for non-native readers. twicpen is a terminology-assistance system for readers of printed (ie. off-line) material in foreign languages. it consists of a hand-held scanner and sophisticated parsing and translation software to provide readers a limited number of translations selected on the basis of a linguistic analysis of the whole scanned text fragment (a phrase, part of the sentence, etc.). the use of a morphological and syntactic parser makes it possible (i) to disambiguate to a large extent the word selected by the user (and hence to drastically reduce the noise in the response), and (ii) to handle expressions (compounds, collocations, idioms), often a major source of difficulty for non-native readers. the system exists for the following language-pairs: english-french, french-english, german-french and italian-french.
translating idioms. this paper discusses the treatment of fixed word expressions developed for our its-2 frenc-english translation system. this treatment makes a clear distinction between compounds-i.e. multiword expressions of x0-level in which the chunks are adjacent-and idiomatic phrases-i.e. multiword expressions of phrasal categories, where the chunks are not necessarily adjacent. in our system, compounds are handled during the lexical analysis, while idioms are treated in the syntax, where they are treated as "specialized lexemes". once recognized, an idiom can be transfered according to the specifications of the bilingual dictionary. we will show several cases of transfer to corresponding idioms in the target language, or to simple lexemes. the complete system, including several hundreds of compounds and idioms can be consulted on the internet (http://latl.unige.ch/itsweb.html).
linear context-free rewriting systems and deterministic tree-walking transducers. we show that the class of string languages generated by linear context-free rewriting systems is equal to the class of output languages of deterministic tree-walking transducers. from equivalences that have previously been established we know that this class of languages is also equal to the string languages generated by context-free hypergraph grammars, multicomponent tree-adjoining grammars, and multiple context-free grammars and to the class of yields of images of the regular tree languages under finite-copying top-down tree transducers.
combinatory categorial grammars: generative power and relationship to linear context-free rewriting systems. recent results have established that there is a family of languages that is exactly the class of languages generated by three independently developed grammar formalisms: tree adjoining grammars, head grammars, and linear indexed grammars. in this paper we show that combinatory categorial grammars also generates the same class of languages. we discuss the structural descriptions produced by combinatory categorial grammars and compare them to those of grammar formalisms in the class of linear context-free rewriting systems. we also discuss certain extensions of combinatory categorial grammars and their effect on the weak generative capacity.
a hybrid approach to representation in the janus natural language processor. in bbn's natural language understanding and generation system (janus), we have used a hybrid approach to representation, employing an intensional logic for the representation of the semantics of utterances and a taxonomic language with formal semantics for specification of descriptive constants and axioms relating them. remarkably, 99.9% of 7,000 vocabulary items in our natural language applications could be adequately axiomatized in the taxonomic language.
empirical lower bounds on the complexity of translational equivalence. this paper describes a study of the patterns of translational equivalence exhibited by a variety of bitexts. the study found that the complexity of these patterns in every bitext was higher than suggested in the literature. these findings shed new light on why "syntactic" constraints have not helped to improve statistical translation models, including finite-state phrase-based models, tree-to-string models, and tree-to-tree models. the paper also presents evidence that inversion transduction grammars cannot generate some translational equivalence relations, even in relatively simple real bitexts in syntactically similar languages with rigid word order. instructions for replicating our experiments are at http://nip.cs.nyu.edu/genpar/acl06
you can't beat frequency (unless you use linguistic knowledge) - a qualitative evaluation of association measures for collocation and term extraction. in the past years, a number of lexical association measures have been studied to help extract new scientific terminology or general-language collocations. the implicit assumption of this research was that newly designed term measures involving more sophisticated statistical criteria would outperform simple counts of co-occurrence frequencies. we here explicitly test this assumption. by way of four qualitative criteria, we show that purely statistics-based measures reveal virtually no difference compared with frequency of occurrence counts, while linguistically more informed metrics do reveal such a marked difference.
the imperfective paradox and trajectory-of-motion events. in the first part of the paper, i present a new treatment of the imperfective paradox (dowty 1979) for the restricted case of trajectory-of-motion events. this treatment extends and refines those of moens and steedman (1988) and jackendoff (1991). in the second part, i describe an implemented algorithm based on this treatment which determines whether a specified sequence of such events is or is not possible under certain situationally supplied constraints and restrictive assumptions.
cues and control in expert-client dialogues. we conducted an empirical analysis into the relation between control and discourse structure. we applied control criteria to four dialogues and identified 3 levels of discourse structure. we investigated the mechanism for changing control between these structures and found that utterance type and not cue words predicted shifts of control. participants used certain types of signals when discourse goals were proceeding successfully but resorted to interruptions when they were not.
empirical study of predictive powers od simple attachment schemes for post-modifier prepositional phrases. this empirical study attempts to find answers to the question of how a natural language (henceforth nl) system could resolve attachment of prepositional phrases (henceforth pps) by examining naturally occurring pp attachments in typed dialogue. examination includes testing predictive powers of existing attachment theories against the data. the result of this effort will be an algorithm for interpreting pp attachment.
event-building through role-filling and anaphora resolution. in this study we map out a way to build event representations incrementally, using information which may be widely distributed across a discourse. an enhanced discourse representation (kamp, 1981) provides the vehicle both for carrying open event roles through the discourse until they can be instantiated by nps, and for resolving the reference of these otherwise problematic nps by binding them to the event roles.
orthogonal negation in vector spaces for modelling word-meanings and document retrieval. standard ir systems can process queries such as "web not internet", enabling users who are interested in arachnids to avoid documents about computing. the documents retrieved for such a query should be irrelevant to the negated query term. most systems implement this by reprocessing results after retrieval to remove documents containing the unwanted string of letters.this paper describes and evaluates a theoretically motivated method for removing unwanted meanings directly from the original query in vector models, with the same vector negation operator as used in quantum logic. irrelevance in vector spaces is modelled using orthogonality, so query vectors are made orthogonal to the negated term or terms.as well as removing unwanted terms, this form of vector negation reduces the occurrence of synonyms and neighbours of the negated terms by as much as 76% compared with standard boolean methods. by altering the query vector itself, vector negation removes not only unwanted strings but unwanted meanings.
development and use of a gold-standard data set for subjectivity classifications. this paper presents a case study of analyzing and improving intercoder reliability in discourse tagging using statistical techniques. bias-corrected tags are formulated and successfully used to guide a revision of the coding manual and develop an automatic classifier.
word sense and subjectivity. subjectivity and meaning are both important properties of language. this paper explores their interaction, and brings empirical evidence in support of the hypotheses that (1) subjectivity is a property that can be associated with word senses, and (2) word sense disambiguation can directly benefit from subjectivity annotations.
a computational theory of perspective and reference in narrative. narrative passages told from a character's perspective convey the character's thoughts and perceptions. we present a discourse process that recognizes characters' thoughts and perceptions in third-person narrative. an effect of perspective on reference in narrative is addressed: references in passages told from the perspective of a character reflect the character's beliefs. an algorithm that uses the results of our discourse process to understand references with respect to an appropriate set of beliefs is presented.
head-driven generation with hpsg. as hpsg is head-driven, with clear semantic heads, semantic head-driven generation should be simple. we adapt van noord's prolog generator for use with an hpsg grammar in profit. however, quantifiers and context factors are difficult to include in head-driven generation. we must adopt recent theoretical proposals for lexicalized scoping and context. with these revisions, head-driven generation with hpsg is not so simple, but it is possible.
phran - a knowledge-base natural language understander. we have developed an approach to natural language processing in which the natural language processor is viewed as a knowledge-based system whose knowledge is about the meanings of the utterances of its language. the approach is oriented around the phrase rather than the word as the basic unit. we believe that this paradigm for language processing not only extends the capabilities of other natural language systems, but handles those tasks that previous systems could perform in a more systematic and extensible manner.we have constructed a natural language analysis program called phran (phrasal analyzer) based in this approach. this model has a number of advantages over existing systems, including the ability to understand a wider variety of language utterances, increased processing speed in some cases, a clear separation of control structure from data structure, a knowledge base that could be shared by a language production mechanism, greater ease of extensibility, and the ability to store some useful forms of knowledge that cannot readily be added to other systems.
word sense disambiguation using optimised combinations of knowledge sources. word sense disambiguation algorithms, with few exceptions, have made use of only one lexical knowledge source. we describe a system which performs word sense disambiguation on all content words in free text by combining different knowledge sources: semantic preferences, dictionary definitions and subject/domain codes along with part-of-speech tags, optimised by means of a learning algorithm. we also describe the creation of a new sense tagged corpus by combining existing resources. tested accuracy of our approach on this corpus exceeds 92%, demonstrating the viability of all-word disambiguation rather than restricting oneself to a small sample.
two accounts of scope availability and semantic underspecification. we propose a formal system for representing the available readings of sentences displaying quantifier scope ambiguity, in which <i>partial</i> scopes may be expressed. we show that using a theory of scope availability based upon the function-argument structure of a sentence allows a deterministic, polynomial time test for the availability of a reading, while solving the same problem within theories based on the well-formedness of sentences in the meaning language has been shown to be np-hard.
compositional semantics for linguistic formalisms. in what sense is a grammar the union of its rules? this paper adapts the notion of <i>composition</i>, well developed in the context of programming languages, to the domain of linguistic formalisms. we study alternative definitions for the semantics of such formalisms, suggesting a denotational semantics that we show to be compositional and fully-abstract. this facilitates a clear, mathematically sound way for defining grammar modularity.
using bracketed parses to evaluate a grammar checking application. we describe a method for evaluating a grammar checking application with hand-bracketed parses. a randomly-selected set of sentences was submitted to a grammar checker in both bracketed and unbracketed formats. a comparison of the resulting error reports illuminates the relationship between the underlying performance of the parser-grammar system and the error critiques presented to the user.
paragraph-, word-, and coherence-based approaches to sentence ranking: a comparison of algorithm and human performance. sentence ranking is a crucial part of generating text summaries. we compared human sentence rankings obtained in a psycholinguistic experiment to three different approaches to sentence ranking: a simple paragraph-based approach intended as a baseline, two word-based approaches, and two coherence-based approaches. in the paragraph-based approach, sentences in the beginning of paragraphs received higher importance ratings than other sentences. the word-based approaches determined sentence rankings based on relative word frequencies (luhn (1958); salton & buckley (1988)). coherence-based approaches determined sentence rankings based on some property of the coherence structure of a text (marcu (2000); page et al. (1998)). our results suggest poor performance for the simple paragraph-based approach, whereas word-based approaches perform remarkably well. the best performance was achieved by a coherence-based approach where coherence structures are represented in a non-tree structure. most approaches also outperformed the commercially available msword summarizer.
compositional semantics of german prefix verbs. a compositional account of the semantics of german prefix verbs in hpsg is outlined. we consider only those verbs that are formed by productive synchronic rules. rules are fully productive if they apply to all base verbs which satisfy a common description. prefixes can be polysemous and have separate, highly underspecified lexical entries. adequate bases are determined via selection restrictions.
a model for robust processing of spontaneous speech by integrating viable fragments. we describe the design and function of a robust processing component which is being developed for the verbmobil speech translation system. its task consists of collecting partial analyses of an input utterance produced by three parsers and attempting to combine them into more meaningful, larger units. it is used as a fallback mechanism in cases where no complete analysis spanning the whole input can be achieved, owing to spontaneous speech phenomena or speech recognition errors.
computational analysis of move structures in academic abstracts. this paper introduces a method for computational analysis of move structures in abstracts of research articles. in our approach, sentences in a given abstract are analyzed and labeled with a specific move in light of various rhetorical functions. the method involves automatically gathering a large number of abstracts from the web and building a language model of abstract moves. we also present a prototype concordancer, care, which exploits the move-tagged abstracts for digital learning. this system provides a promising approach to web-based computer-assisted academic writing.
a grammatical approach to understanding textual tables using two-dimensional scfgs. we present an elegant and extensible model that is capable of providing semantic interpretations for an unusually wide range of textual tables in documents. unlike the few existing table analysis models, which largely rely on relatively ad hoc heuristics, our linguistically-oriented approach is systematic and grammar based, which allows our model (1) to be concise and yet (2) recognize a wider range of data models than others, and (3) disambiguate to a significantly finer extent the underlying semantic interpretation of the table in terms of data models drawn from relation database theory. to accomplish this, the model introduces viterbi parsing under two-dimensional stochastic cfgs. the cleaner grammatical approach facilitates not only greater coverage, but also grammar extension and maintenance, as well as a more direct and declarative link to semantic interpretation, for which we also introduce a new, cleaner data model. in disambiguation experiments on recognizing relevant data models of unseen web tables from different domains, a blind evaluation of the model showed 60% precision and 80% recall.
learning source-target surface patterns for web-based terminology translation. this paper introduces a method for learning to find translation of a given source term on the web. in the approach, the source term is used as query and part of patterns to retrieve and extract translations in web pages. the method involves using a bilingual term list to learn source-target surface patterns. at runtime, the given term is submitted to a search engine then the candidate translations are extracted from the returned summaries and subsequently ranked based on the surface patterns, occurrence counts, and transliteration knowledge. we present a prototype called termmine that applies the method to translate terms. evaluation on a set of encyclopedia terms shows that the method significantly outperforms the state-of-the-art online machine translation systems.
a kernel pca method for superior word sense disambiguation. we introduce a new method for disambiguating word senses that exploits a nonlinear kernel principal component analysis (kpca) technique to achieve accuracy superior to the best published individual models. we present empirical results demonstrating significantly better accuracy compared to the state-of-the-art achieved by either na&iuml;ve bayes or maximum entropy models, on senseval-2 data. we also contrast against another type of kernel method, the support vector machine (svm) model, and show that our kpca-based model outperforms the svm-based model. it is hoped that these highly encouraging first results on kpca for natural language processing tasks will inspire further development of these directions.
using machine learning techniques to interpret wh-questions. we describe a set of supervised machine learning experiments centering on the construction of statistical models of wh-questions. these models, which are built from shallow linguistic features of questions, are employed to predict target variables which represent a user's informational goals. we report on different aspects of the predictive performance of our models, including the influence of various training and testing factors on predictive performance, and examine the relationships among the target variables.
boosting statistical word alignment using labeled and unlabeled data. this paper proposes a semi-supervised boosting approach to improve statistical word alignment with limited labeled data and large amounts of unlabeled data. the proposed approach modifies the supervised boosting algorithm to a semi-supervised learning algorithm by incorporating the unlabeled data. in this algorithm, we build a word aligner by using both the labeled data and the unlabeled data. then we build a pseudo reference set for the unlabeled data, and calculate the error rate of each word aligner using only the labeled data. based on this semi-supervised boosting algorithm, we investigate two boosting methods for word alignment. in addition, we improve the word alignment results by combining the results of the two semi-supervised boosting methods. experimental results on word alignment indicate that semi-supervised boosting achieves relative error reductions of 28.29% and 19.52% as compared with supervised boosting and unsupervised boosting, respectively.
machine translation between turkic languages. we present an approach to mt between turkic languages and present results from an implementation of a mt system from turkmen to turkish. our approach relies on ambiguous lexical and morphological transfer augmented with target side rule-based repairs and rescoring with statistical language models.
a phonetic-based approach to chinese chat text normalization. chatting is a popular communication media on the internet via icq, chat rooms, etc. chat language is different from natural language due to its anomalous and dynamic natures, which renders conventional nlp tools inapplicable. the dynamic problem is enormously troublesome because it makes static chat language corpus outdated quickly in representing contemporary chat language. to address the dynamic problem, we propose the phonetic mapping models to present mappings between chat terms and standard words via phonetic transcription, i.e. chinese pinyin in our case. different from character mappings, the phonetic mappings can be constructed from available standard chinese corpus. to perform the task of dynamic chat language term normalization, we extend the source channel model by incorporating the phonetic mapping models. experimental results show that this method is effective and stable in normalizing dynamic chat language terms.
centrality measures in text mining: prediction of noun phrases that appear in abstracts. in this paper, we study different centrality measures being used in predicting noun phrases appearing in the abstracts of scientific articles. our experimental results show that centrality measures improve the accuracy of the prediction in terms of both precision and recall. we also found that the method of constructing noun phrase network significantly influences the accuracy when using the centrality heuristics itself, but is negligible when it is used together with other text features in decision trees.
maximum entropy based phrase reordering model for statistical machine translation. we propose a novel reordering model for phrase-based statistical machine translation (smt) that uses a maximum entropy (maxent) model to predicate reorderings of neighbor blocks (phrase pairs). the model provides content-dependent, hierarchical phrasal reordering with generalization based on features automatically learned from a real-world bitext. we present an algorithm to extract all reordering events of neighbor blocks from bilingual data. in our experiments on chinese-to-english translation, this maxent-based reordering model obtains significant improvements in bleu score on the nist mt-05 and iwslt-04 tasks.
a study on richer syntactic dependencies for structured language modeling. we study the impact of richer syntactic dependencies on the performance of the structured language model (slm) along three dimensions: parsing accuracy (lp/lr), perplexity (ppl) and word-error-rate (wer, n-best re-scoring). we show that our models achieve an improvement in lp/lr, ppl and/or wer over the reported baseline results using the slm on the upenn treebank and wall street journal (wsj) corpora, respectively. analysis of parsing performance shows correlation between the quality of the parser (as measured by precision/recall) and the language model performance (ppl and wer). a remarkable fact is that the enriched slm outperforms the baseline 3-gram model in terms of wer by 10% when used in isolation as a second pass (n-best re-scoring) language model.
aligning features with sense distinction dimensions. in this paper we present word sense disambiguation (wsd) experiments on ten highly polysemous verbs in chinese, where significant performance improvements are achieved using rich linguistic features. our system performs significantly better, and in some cases substantially better, than the baseline on all ten verbs. our results also demonstrate that features extracted from the output of an automatic chinese semantic role labeling system in general benefited the wsd system, even though the amount of improvement was not consistent across the verbs. for a few verbs, semantic role information actually hurt wsd performance. the inconsistency of feature performance is a general characteristic of the wsd task, as has been observed by others. we argue that this result can be explained by the fact that word senses are partitioned along different dimensions for different verbs and the features therefore need to be tailored to particular verbs in order to achieve adequate accuracy on verb sense disambiguation.
a unified statistical model for the identification of english basenp. this paper presents a novel statistical model for automatic identification of english basenp. it uses two steps: the n-best part-of-speech (pos) tagging and basenp identification given the n-best pos-sequences. unlike the other approaches where the two steps are separated, we integrate them into a unified statistical framework. our model also integrates lexical information. finally, viterbi algorithm is applied to make global search in the entire sentence, allowing us to obtain linear complexity for the entire process. compared with other methods using the same testing set, our approach achieves 92.3% in precision and 93.2% in recall. the result is comparable with or better than the previously reported results.
clustering hungarian verbs on the basis of complementation patterns. our paper reports an attempt to apply an unsupervised clustering algorithm to a hungarian treebank in order to obtain semantic verb classes. starting from the hypothesis that semantic metapredicates underlie verbs' syntactic realization, we investigate how one can obtain semantically motivated verb classes by automatic means. the 150 most frequent hungarian verbs were clustered on the basis of their complementation patterns, yielding a set of basic classes and hints about the features that determine verbal subcategorization. the resulting classes serve as a basis for the subsequent analysis of their alternation behavior.
automatic acquisition of adjectival subcategorization from corpora. this paper describes a novel system for acquiring adjectival subcategorization frames (scfs) and associated frequency information from english corpus data. the system incorporates a decision-tree classifier for 30 scf types which tests for the presence of grammatical relations (grs) in the output of a robust statistical parser. it uses a powerful pattern-matching language to classify grs into frames hierarchically in a way that mirrors inheritance-based lexica. the experiments show that the system is able to detect scf types with 70% precision and 66% recall rate. a new tool for linguistic annotation of scfs in corpus data is also introduced which can considerably alleviate the process of obtaining training and test data for subcategorization acquisition.
wordnet-based semantic relatedness measures in automatic speech recognition for meetings. this paper presents the application of wordnet-based semantic relatedness measures to automatic speech recognition (asr) in multi-party meetings. different word-utterance context relatedness measures and utterance-coherence measures are defined and applied to the rescoring of n-best lists. no significant improvements in terms of word-error-rate (wer) are achieved compared to a large word-based n-gram baseline model. we discuss our results and the relation to other work that achieved an improvement with such models for simpler tasks.
a syntax-based statistical translation model. we present a syntax-based statistical translation model. our model transforms a source-language parse tree into a target-language string by applying stochastic operations at each node. these operations capture linguistic differences such as word order and case marking. model parameters are estimated in polynomial time using an em algorithm. the model produces word alignments that are better than those produced by ibm model 5.
multimedia blog creation system using dialogue with intelligent robot. a multimedia blog creation system is described that uses japanese dialogue with an intelligent robot. although multimedia blogs are increasing in popularity, creating blogs is not easy for users who lack high-level information literacy skills. even skilled users have to waste time creating and assigning text descriptions to their blogs and searching related multimedia such as images, music, and illustrations. to enable effortless and enjoyable creation of multimedia blogs, we developed the system on a prototype robot called papero. video messages are recorded and converted into text descriptions by papero using continuous speech recognition. papero then searches for suitable multimedia contents on the internet and databases, and then, based on the search results, chooses appropriate sympathetic comments by using natural language text retrieval. the retrieved contents, papero's comments, and the video recording on the user's blog is automatically uploaded and edited. the system was evaluated by 10 users for creating travel blogs and proved to be helpful for both inexperienced and experienced users. the system enabled easy multimedia-rich blog creation and even provided users the pleasure of chatting with papero.
a decoder for syntax-based statistical mt. this paper describes a decoding algorithm for a syntax-based translation model (yamada and knight, 2001). the model has been extended to incorporate phrasal translations as presented here. in contrast to a conventional word-to-word statistical model, a decoder for the syntax-based model builds up an english parse tree given a sentence in a foreign language. as the model size becomes huge in a practical setting, and the decoder considers multiple syntactic structures for each word alignment, several pruning techniques are necessary. we tested our decoder in a chinese-to-english translation system, and obtained better results than ibm model 4. we also discuss issues concerning the relation between this decoder and a language model.
system demonstration of on-demand information extraction. in this paper, we will describe odie, the on-demand information extraction system. given a user's query, the system will produce tables of the salient information about the topic in structured form. it produces the tables in less than one minute without any knowledge engineering by hand, i.e. pattern creation or paraphrase knowledge creation, which was the largest obstacle in traditional ie. this demonstration is based on the idea and technologies reported in (sekine 06). a substantial speed-up over the previous system (which required about 15 minutes to analyze one year of newspaper) was achieved through a new approach to handling pattern candidates; now less than one minute is required when using 11 years of newspaper corpus. in addition, functionality was added to facilitate investigation of the extracted information.
combination of an automatic and an interactive disambiguation method. in natural language processing, many methods have been proposed to solve the ambiguity problems. in this paper, we propose a technique to combine a method of interactive disambiguation and automatic one for ambiguous words. the characteristic of our method is that the accuracy of the interactive disambiguation is considered. the method solves the two following problems when combining those disambiguation methods: (1) when should the interactive disambiguation be executed? (2) which ambiguous word should be disambiguated when more than one ambiguous words exist in a sentence? our method defines the condition of executing the interaction with users and the order of disambiguation based on the strategy where the accuracy of the result is maximized, considering the accuracy of the interactive disambiguation and automatic one. using this method, user interaction can be controlled while holding the accuracy of results.
multi-class composite n-gram language model for spoken language processing using multiple word clusters. in this paper, a new language model, the multi-class composite n-gram, is proposed to avoid a data sparseness problem for spoken language in that it is difficult to collect training data. the multi-class composite n-gram maintains an accurate word prediction capability and reliability for sparse data with a compact model size based on multiple word clusters, called multi-classes. in the multi-class, the statistical connectivity at each position of the n-grams is regarded as word attributes, and one word cluster each is created to represent the positional attributes. furthermore, by introducing higher order word n-grams through the grouping of frequent word successions, multi-class n-grams are extended to multi-class composite n-grams. in experiments, the multi-class composite n-grams result in 9.5% lower perplexity and a 16% lower word error rate in speech recognition with a 40% smaller parameter size than conventional word 3-grams.
kinds of features for chinese opinionated information retrieval. this paper presents the results of experiments in which we tested different kinds of features for retrieval of chinese opinionated texts. we assume that the task of retrieval of opinionated texts (oir) can be regarded as a subtask of general ir, but with some distinct features. the experiments showed that the best results were obtained from the combination of character-based processing, dictionary look up (maximum matching) and a negation check.
automatic part-of-speech tagging for bengali: an approach for morphologically rich languages in a poor resource scenario. this paper describes our work on building part-of-speech (pos) tagger for bengali. we have use hidden markov model (hmm) and maximum entropy (me) based stochastic taggers. bengali is a morphologically rich language and our taggers make use of morphological and contextual information of the words. since only a small labeled training set is available (45,000 words), simple stochastic approach does not yield very good results. in this work, we have studied the effect of using a morphological analyzer to improve the performance of the tagger. we find that the use of morphology helps improve the accuracy of the tagger especially when less amount of tagged corpora are available.
a selectionist theory of language acquisition. this paper argues that developmental patterns in child language be taken seriously in computational models of language acquisition, and proposes a formal theory that meets this criterion. we first present developmental facts that are problematic for statistical learning approaches which assume no prior knowledge of grammar, and for traditional learnability models which assume the learner moves from one ug-defined grammar to another. in contrast, we view language acquisition as a population of grammars associated with "weights", that compete in a darwinian selectionist process. selection is made possible by the <i>variational</i> properties of individual grammars; specifically, their differential compatibility with the primary linguistic data in the environment. in addition to a convergence proof, we present empirical evidence in child language development, that a learner is best modeled as multiple grammars in co-existence and competition.
on the formalization of invariant mappings for metaphor interpretation. in this paper we provide a formalization of a set of default rules that we claim are required for the transfer of information such as causation, event rate and duration in the interpretation of metaphor. such rules are domain-independent and are identified as invariant adjuncts to any conceptual metaphor. we also show a way of embedding the invariant mappings in a semantic framework.
word sense disambiguation using lexical cohesion in the context. this paper designs a novel lexical hub to disambiguate word sense, using both syntagmatic and paradigmatic relations of words. it only employs the semantic network of wordnet to calculate word similarity, and the edinburgh association thesaurus (eat) to transform contextual space for computing syntagmatic and other domain relations with the target word. without any back-off policy the result on the english lexical sample of senseval-21 shows that lexical cohesion based on edge-counting techniques is a good way of unsupervisedly disambiguating senses.
improving pronoun resolution using statistics-based semantic compatibility information. in this paper we focus on how to improve pronoun resolution using the statistics-based semantic compatibility information. we investigate two unexplored issues that influence the effectiveness of such information: statistics source and learning framework. specifically, we for the first time propose to utilize the web and the twin-candidate model, in addition to the previous combination of the corpus and the single-candidate model, to compute and apply the semantic information. our study shows that the semantic compatibility obtained from the web can be effectively incorporated in the twin-candidate learning model and significantly improve the resolution of neutral pronouns.
kernel-based pronoun resolution with structured syntactic knowledge. syntactic knowledge is important for pronoun resolution. traditionally, the syntactic information for pronoun resolution is represented in terms of features that have to be selected and defined heuristically. in the paper, we propose a kernel-based method that can automatically mine the syntactic information from the parse trees for pronoun resolution. specifically, we utilize the parse trees directly as a structured feature and apply kernel functions to this feature, as well as other normal features, to learn the resolution classifier. in this way, our approach avoids the efforts of decoding the parse trees into the set of flat syntactic features. the experimental results show that our approach can bring significant performance improvement and is reliably effective for the pronoun resolution task.
improving pronoun resolution by incorporating coreferential information of candidates. coreferential information of a candidate, such as the properties of its antecedents, is important for pronoun resolution because it reflects the salience of the candidate in the local discourse. such information, however, is usually ignored in previous learning-based systems. in this paper we present a trainable model which incorporates coreferential information of candidates into pronoun resolution. preliminary experiments show that our model will boost the resolution performance given the right antecedents of the candidates. we further discuss how to apply our model in real resolution where the antecedents of the candidate are found by a separate noun phrase resolution module. the experimental results show that our model still achieves better performance than the baseline.
coreference resolution using competition learning approach. in this paper we propose a competition learning approach to coreference resolution. traditionally, supervised machine learning approaches adopt the single-candidate model. nevertheless the preference relationship between the antecedent candidates cannot be determined accurately in this model. by contrast, our approach adopts a twin-candidate learning model. such a model can present the competition criterion for antecedent candidates reliably, and ensure that the most preferred candidate is selected. furthermore, our approach applies a candidate filter to reduce the computational cost and data noises during training and resolution. the experimental results on muc-6 and muc-7 data set show that our approach can outperform those based on the single-candidate model.
limitations of current grammar induction algorithms. i review a number of grammar induction algorithms (abl, emile, adios), and test them on the eindhoven corpus, resulting in disappointing results, compared to the usually tested corpora (atis, ovis). also, i show that using neither pos-tags induced from biemann's unsupervised pos-tagging algorithm nor hand-corrected pos-tags as input improves this situation. last, i argue for the development of entirely incremental grammar induction algorithms instead of the approaches of the systems discussed before.
counter-training in discovery of semantic patterns. this paper presents a method for unsupervised discovery of semantic patterns. semantic patterns are useful for a variety of text understanding tasks, in particular for locating events in text for information extraction. the method builds upon previously described approaches to iterative unsupervised pattern acquisition. one common characteristic of prior approaches is that the output of the algorithm is a continuous stream of patterns, with gradually degrading precision.our method differs from the previous pattern acquisition algorithms in that it introduces competition among several scenarios simultaneously. this provides natural stopping criteria for the unsupervised learners, while maintaining good precision levels at termination. we discuss the results of experiments with several scenarios, and examine different aspects of the new procedure.
chinese named entity and relation identification system. in this interactive presentation, a chinese named entity and relation identification system is demonstrated. the domain-specific system has a three-stage pipeline architecture which includes word segmentation and part-of-speech (pos) tagging, named entity recognition, and named entity relation identitfication. the experimental results have shown that the average f-measure for word segmentation and pos tagging after correcting errors achieves 92.86 and 90.01 separately. moreover, the overall average f-measure for 6 kinds of name entities and 14 kinds of named entity relations is 83.08% and 70.46% respectively.
minimum bayes risk decoding for bleu. we present a minimum bayes risk (mbr) decoder for statistical machine translation. the approach aims to minimize the expected loss of translation errors with regard to the bleu score. we show that mbr decoding on n-best lists leads to an improvement of translation quality. we report the performance of the mbr decoder on four different tasks: the tc-star epps spanish-english task 2006, the nist chinese-english task 2005 and the gale arabic-english and chinese-english task 2006. the absolute improvement of the bleu score is between 0.2% for the tc-star task and 1.1% for the gale chinese-english task.
decision lists for lexical ambiguity resolution: application to accent restoration in spanish and french. this paper presents a statistical decision procedure for lexical ambiguity resolution. the algorithm exploits both local syntactic patterns and more distant collocational evidence, generating an efficient, effective, and highly perspicuous recipe for resolving a given ambiguity. by identifying and utilizing only the single best disambiguating evidence in a target context, the algorithm avoids the problematic complex modeling of statistical dependencies. although directly applicable to a wide class of ambiguities, the algorithm is described and evaluated in a realistic case study, the problem of restoring missing accents in spanish and french text. current accuracy exceeds 99% on the full task, and typically is over 90% for even the most difficult ambiguities.
semantic enrichment of journal articles using chemical named entity recognition. we describe the semantic enrichment of journal articles with chemical structures and biomedical ontology terms using oscar, a program for chemical named entity recognition (ner). we describe how oscar works and how it can been adapted for general ner. we discuss its implementation in a real publishing workflow and possible applications for enriched articles.
unsupervised word sense disambiguation rivaling supervised methods. this paper presents an unsupervised learning algorithm for sense disambiguation that, when trained on unannotated english text, rivals the performance of supervised techniques that require time-consuming hand annotations. the algorithm is based on two powerful constraints---that words tend to have one sense per discourse and one sense per collocation---exploited in an iterative bootstrapping procedure. tested accuracy exceeds 96%.
pivot language approach for phrase-based statistical machine translation. this paper proposes a novel method for phrase-based statistical machine translation based on the use of a pivot language. to translate between languages l s and l t with limited bilingual resources, we bring in a third language, l p , called the pivot language. for the language pairs l s ¿ l p and l p ¿ l t , there exist large bilingual corpora. using only l s ¿ l p and l p ¿ l t bilingual corpora, we can build a translation model for l s ¿ l t . the advantage of this method lies in the fact that we can perform translation between l s and l t even if there is no bilingual corpus available for this language pair. using bleu as a metric, our pivot language approach significantly outperforms the standard model trained on a small bilingual corpus. moreover, with a small l s ¿ l t bilingual corpus available, our method can further improve translation quality by using the additional l s ¿ l p and l p ¿ l t bilingual corpora.
minimally supervised morphological analysis by multimodal alignment. this paper presents a corpus-based algorithm capable of inducing inflectional morphological analyses of both regular and highly irregular forms (such as brought&rarr;bring) from distributional patterns in large monolingual text with no direct supervision. the algorithm combines four original alignment models based on relative corpus frequency, contextual similarity, weighted string similarity and incrementally retrained inflectional transduction probabilities. starting with no paired <inflection,root> examples for training and no prior seeding of legal morphological transformations, accuracy of the induced analyses of 3888 past-tense test cases in english exceeds 99.2% for the set, with currently over 80% accuracy on the most highly irregular forms and 99.7% accuracy on forms exhibiting non-concatenative suffixation.
extracting word sets with non-taxonomical relation. at least two kinds of relations exist among related words: taxonomical relations and thematic relations. both relations identify related words useful to language understanding and generation, information retrieval, and so on. however, although words with taxonomical relations are easy to identify from linguistic resources such as dictionaries and thesauri, words with thematic relations are difficult to identify because they are rarely maintained in linguistic resources. in this paper, we sought to extract thematically (non-taxonomically) related word sets among words in documents by employing case-marking particles derived from syntactic analysis. we then verified the usefulness of word sets with non-taxonomical relation that seems to be a thematic relation for information retrieval.
using existing systems to supplement small amounts of annotated grammatical relations training data. grammatical relationships (grs) form an important level of natural language processing, but different sets of grs are useful for different purposes. therefore, one may often only have time to obtain a small training corpus with the desired gr annotations. to boost the performance from using such a small training corpus on a transformation rule learner, we use existing systems that find related types of annotations.
some properties of preposition and subordinate conjunction attachments. determining the attachments of prepositions and subordinate conjunctions is a key problem in parsing natural language. this paper presents a trainable approach to making these attachments through transformation sequences and error-driven learning. our approach is broad coverage, and accounts for roughly three times the attachment cases that have previously been handled by corpus-based techniques. in addition, our approach is based on a simplified model of syntax that is more consistent with the practice in current state-of-the-art language processing systems. this paper sketches syntactic and algorithmic details, and presents experimental results on data sets derived from the penn treebank. we obtain an attachment accuracy of 75.4% for the general case, the first such corpus-based result to be reported. for the restricted cases previously studied with corpusbased methods, our approach yields an accuracy comparable to current work (83.1%).
moses: open source toolkit for statistical machine translation. we describe an open-source toolkit for statistical machine translation whose novel contributions are (a) support for linguistically motivated factors, (b) confusion network decoding, and (c) efficient data formats for translation models and language models. in addition to the smt decoder, the toolkit also includes a wide variety of tools for training, tuning and applying the system to many translation tasks.
stochastic discourse modeling in spoken dialogue systems using semantic dependency graphs. this investigation proposes an approach to modeling the discourse of spoken dialogue using semantic dependency graphs. by characterizing the discourse as a sequence of speech acts, discourse modeling becomes the identification of the speech act sequence. a statistical approach is adopted to model the relations between words in the user's utterance using the semantic dependency graphs. dependency relation between the headword and other words in a sentence is detected using the semantic dependency grammar. in order to evaluate the proposed method, a dialogue system for medical service is developed. experimental results show that the rates for speech act detection and task-completion are 95.6% and 85.24%, respectively, and the average number of turns of each dialogue is 8.3. compared with the bayes' classifier and the partial-pattern tree based approaches, we obtain 14.9% and 12.47% improvements in accuracy for speech act identification, respectively.
tense, aspect and the cognitive representation of time. this paper explores the relationships between a computational theory of temporal representation (as developed by james allen) and a formal linguistic theory of tense (as developed by norbert hornstein) and aspect. it aims to provide explicit answers to four fundamental questions: (1) what is the computational justification for the primitives of a linguistic theory; (2) what is the computational explanation of the formal grammatical constraints: (3) what are the processing constraints imposed on the learnability and markedness of these theoretical constructs: and (4) what are the constraints that a linguistic theory imposes on. representations. we show that one can effectively exploit the interface between the language faculty and the cognitive faculties by using linguistic constraints to determine restructions on the cognitive representations and vice versa.three main results are obtained: (1) we derive an explanation of an observed grammatical constraint on tense .. the linear order constraint .. from the information monotonicity property of the constraint propagation algorithm of allen's temporal system: (2) we formulate a principle of markedness for the basic tense structures based on the computational efficiency of the temporal representations: and (3) we show allen's interval-based temporal system is not arbitrary. but it can be used to explair, independently motivated linguistic constraints on tense and aspect interpretations.we also claim that the methodology of research developed in this study .. "cross-level" investigation of independently motivated formal grammatical theory and computational models .. is a powerful paradigm with which to attack representational problems in basic cognitive domains, e.g., space. time, causality, etc.
automatic discovery of named entity variants: grammar-driven approaches to non-alphabetical transliterations. identification of transliterated names is a particularly difficult task of named entity recognition (ner), especially in the chinese context. of all possible variations of transliterated named entities, the difference between prc and taiwan is the most prevalent and most challenging. in this paper, we introduce a novel approach to the automatic extraction of diverging transliterations of foreign named entities by bootstrapping co-occurrence statistics from tagged and segmented chinese corpus. preliminary experiment yields promising results and shows its potential in nlp applications.
corpus-oriented development of japanese hpsg parsers. this paper reports the corpus-oriented development of a wide-coverage japanese hpsg parser. we first created an hpsg treebank from the edr corpus by using heuristic conversion rules, and then extracted lexical entries from the treebank. the grammar developed using this method attained wide coverage that could hardly be obtained by conventional manual development. we also trained a statistical parser for the grammar on the treebank, and evaluated the parser in terms of the accuracy of semantic-role identification and dependency analysis.
reformatting web documents via header trees. we propose a new method for reformatting web documents by extracting semantic structures from web pages. our approach is to extract trees that describe hierarchical relations in documents. we developed an algorithm for this task by employing the em algorithm and clustering techniques. preliminary experiments showed that our approach was more effective than baseline methods.
evaluation of importance of sentences based on connectivity to title. this paper proposes a method of selecting important sentences from a text based on the evaluation of the connectivity between sentences by using surface information. we assume that the title of a text is the most concise statement which expresses the most essential information of the text, and that the closer a sentence relates to an important sentence, the more important this sentence is. the importance of a sentence is defined as the connectivity between the sentence and the title. the connectivity between two sentences is measured based on correference between a pronoun and a preceding (pro)noun, and on lexical cohesion of lexical items. in an experiment with 80 english texts, which consist of an average of 29.0 sentences, the proposed method has marked recall of 78.2% and precision of 57.7%, with the selection ratio being 25%. the recall and precision values surpass those achieved by conventional methods, which means that our method is more effective in abridging relatively short texts.
annotating and learning compound noun semantics. there is little consensus on a standard experimental design for the compound interpretation task. this paper introduces well-motivated general desiderata for semantic annotation schemes, and describes such a scheme for in-context compound annotation accompanied by detailed publicly available guidelines. classification experiments on an open-text dataset compare favourably with previously reported results and provide a solid baseline for future research.
resume information extraction with cascaded hybrid model. this paper presents an effective approach for resume information extraction to support automatic resume management and routing. a cascaded information extraction (ie) framework is designed. in the first pass, a resume is segmented into a consecutive blocks attached with labels indicating the information types. then in the second pass, the detailed information, such as name and address, are identified in certain blocks (e.g. blocks labelled with personal information), instead of searching globally in the entire resume. the most appropriate model is selected through experiments for each ie task in different passes. the experimental results show that this cascaded hybrid model achieves better f-score than flat models that do not apply the hierarchical structure of resumes. it also shows that applying different ie models in different passes according to the contextual structure is effective.
hal-based cascaded model for variable-length semantic pattern induction from psychiatry web resources. negative life events play an important role in triggering depressive episodes. developing psychiatric services that can automatically identify such events is beneficial for mental health care and prevention. before these services can be provided, some meaningful semantic patterns, such as <lost, parents>, have to be extracted. in this work, we present a text mining framework capable of inducing variable-length semantic patterns from unannotated psychiatry web resources. this framework integrates a cognitive motivated model, hyperspace analog to language (hal), to represent words as well as combinations of words. then, a cascaded induction process (cip) bootstraps with a small set of seed patterns and incorporates relevance feedback to iteratively induce more relevant patterns. the experimental results show that by combining the hal model and relevance feedback, the cip can induce semantic patterns from the unannotated web corpora so as to reduce the reliance on annotated corpora.
boosting statistical machine translation by lemmatization and linear interpolation. data sparseness is one of the factors that degrade statistical machine translation (smt). existing work has shown that using morpho-syntactic information is an effective solution to data sparseness. however, fewer efforts have been made for chinese-to-english smt with using english morpho-syntactic analysis. we found that while english is a language with less inflection, using english lemmas in training can significantly improve the quality of word alignment that leads to yield better translation performance. we carried out comprehensive experiments on multiple training data of varied sizes to prove this. we also proposed a new effective linear interpolation method to integrate multiple homologous features of translation models.
paradigmatic cascades: a linguistically sound model of pronunciation by analogy. we present and experimentally evaluate a new model of prounciation by analogy: the paradigmatic cascades model. given a pronunciation lexicon, this algorithm first extracts the most productive paradigmatic mappings in the graphemic domain, and pairs them statistically with their correlate(s) in the phonemic domain. these mappings are used to search and retrieve in the lexical database the most promising analog of unseen words. we finally apply to the analogs pronunciation the correlated series of mappings in the phonemic domain to get the desired pronunciation.
a transfer model using a typed feature structure rewriting system with inheritance. we propose a model for transfer in machine translation which uses a rewriting system for typed feature structures. the grammar definitions describe transfer relations which are applied on the input structure (a typed feature structure) by the interpreter to produce all possible transfer pairs. the formalism is based on the semantics of typed feature structures as described in [a&iuml;t-kaci 84].
automatic learning of textual entailments with cross-pair similarities. in this paper we define a novel similarity measure between examples of textual entailments and we use it as a kernel function in support vector machines (svms). this allows us to automatically learn the rewrite rules that describe a non trivial set of entailment cases. the experiments with the data sets of the rte 2005 challenge show an improvement of 4.4% over the state-of-the-art methods.
discovering asymmetric entailment relations between verbs using selectional preferences. in this paper we investigate a novel method to detect asymmetric entailment relations between verbs. our starting point is the idea that some point-wise verb selectional preferences carry relevant semantic information. experiments using word-net as a gold standard show promising results. where applicable, our method, used in combination with other approaches, significantly increases the performance of entailment detection. a combined approach including our model improves the aroc of 5% absolute points with respect to standard models.
memory-based learning: using similarity for smoothing. this paper analyses the relation between the use of similarity in memory-based learning and the notion of backed-off smoothing in statistical language modeling. we show that the two approaches are closely related, and we argue that feature weighting methods in the memory-based paradigm can offer the advantage of automatically specifying a suitable domain-specific hierarchy between most specific and most general conditioning information without the need for a large number of parameters. we report two applications of this approach: pp-attachment and pos-tagging. our method achieves state-of-the-art performance in both domains, and allows the easy integration of diverse information sources, such as rich lexical representations.
automatic construction of frame representations for spontaneous speech in unrestricted domains. this paper presents a system which automatically generates shallow semantic frame structures for conversational speech in unrestricted domains.we argue that such shallow semantic representations can indeed be generated with a minimum amount of linguistic knowledge engineering and without having to explicitly construct a semantic knowledge base. the system is designed to be robust to deal with the problems of speech dysfluencies, ungrammaticalities, and imperfect speech recognition.initial results on speech transcripts are promising in that correct mappings could be identified in 21% of the clauses of a test set (resp. 44% of this test set where ungrammatical or verb-less clauses were removed).
an implementation of combined partial parser and morphosyntactic disambiguator. the aim of this paper is to present a simple yet efficient implementation of a tool for simultaneous rule-based morphosyntactic tagging and partial parsing formalism. the parser is currently used for creating a tree-bank of partial parses in a valency acquisition project over the ipi pan corpus of polish.
using chunk based partial parsing of spontaneous speech in unrestricted domains for reducing word error rate in speech recognition. in this paper, we present a chunk based partial parsing system for spontaneous, conversational speech in unrestricted domains. we show that the chunk parses produced by this parsing system can be usefully applied to the task of reranking nbest lists from a speech recognizer, using a combination of chunk-based n-gram model scores and chunk coverage scores.the input for the system is nbest lists generated from speech recognizer lattices. the hypotheses from the nbest lists are tagged for part of speech, "cleaned up" by a preprocessing pipe, parsed by a part of speech based chunk parser, and rescored using a backpropagation neural net trained on the chunk based scores. finally, the reranked nbest lists are generated.the results of a system evaluation are promising in that a chunk accuracy of 87.4% is achieved and the best performance on a randomly selected test set is a decrease in world error rate of 0.3 percent (absolute), measured on the new first hypotheses in the reranked nbest lists.
a comparative study on reordering constraints in statistical machine translation. in statistical machine translation, the generation of a translation hypothesis is computationally expensive. if arbitrary word-reorderings are permitted, the search problem is np-hard. on the other hand, if we restrict the possible word-reorderings in an appropriate way, we obtain a polynomial-time search algorithm.in this paper, we compare two different reordering constraints, namely the itg constraints and the ibm constraints. this comparison includes a theoretical discussion on the permitted number of reorderings for each of these constraints. we show a connection between the itg constraints and the since 1870 known schr&ouml;der numbers.we evaluate these constraints on two tasks: the verbmobil task and the canadian hansards task. the evaluation consists of two parts: first, we check how many of the viterbi alignments of the training corpus satisfy each of these constraints. second, we restrict the search to each of these constraints and compare the resulting translation hypotheses.the experiments will show that the baseline itg constraints are not sufficient on the canadian hansards task. therefore, we present an extension to the itg constraints. these extended itg constraints increase the alignment coverage from about 87% to 96%.
towards a self-extending lexicon. the problem of manually modifying the lexicon appears with any natural language processing program. ideally, a program should be able to acquire new lexical entries from context, the way people learn. we address the problem of acquiring entire phrases, specifically figurative phrases, through augmenting a phrasal lexicon. facilitating such a self-extending lexicon involves (a) disambiguation---selection of the intended phrase from a set of matching phrases, (b) robust parsing---comprehension of partially-matching phrases, and (c) error analysis---use of errors in forming hypotheses about new phrases. we have designed and implemented a program called rina which uses demons to implement functional-grammar principles. rina receives new figurative phrases in context and through the application of a sequence of failure-driven rules, creates and refines both the patterns and the concepts which hold syntactic and semantic information about phrases.
towards a computational treatment of superlatives. i propose a computational treatment of superlatives, starting with superlative constructions and the main challenges in automatically recognising and extracting their components. initial experimental evidence is provided for the value of the proposed work for question answering. i also briefly discuss its potential value for sentiment detection and opinion extraction.
dialect mt: a case study between cantonese and mandarin. machine translation (mt) need not be confined to inter-language activities. in this paper, we discuss inter-dialect mt in general and cantonese-mandarin mt in particular. mandarin and cantonese are two most important dialects of chinese. the former is the national lingua franca and the latter is the most influential dialect in south china, hong kong and overseas. the difference in between is such that mutual intelligibility is impossible. this paper presents, from a computational point of view, a comparative study of mandarin and cantonese at the three aspects of sound systems, grammar rules and vocabulary contents, followed by a discussion of the design and implementation of a dialect mt system between them.
real-time correction of closed-captions. live closed-captions for deaf and hard of hearing audiences are currently produced by stenographers, or by voice writers using speech recognition. both techniques can produce captions with errors. we are currently developing a correction module that allows a user to intercept the real-time caption stream and correct it before it is broadcast. we report results of preliminary experiments on correction rate and actual user performance using a prototype correction module connected to the output of a speech recognition captioning system.
text chunking using regularized winnow. many machine learning methods have recently been applied to natural language processing tasks. among them, the winnow algorithm has been argued to be particularly suitable for nlp problems, due to its robustness to irrelevant features. however in theory, winnow may not converge for non-separable data. to remedy this problem, a modification called regularized winnow has been proposed. in this paper, we apply this new method to text chunking. we show that this method achieves state of the art performance with significantly less computation than previous approaches.
stochastic lexicalized inversion transduction grammar for alignment. we present a version of inversion transduction grammar where rule probabilities are lexicalized throughout the synchronous parse tree, along with pruning techniques for efficient training. alignment results improve over unlexicalized itg on short sentences for which full em is feasible, but pruning seems to have a negative impact on longer sentences.
inducing word alignments with bilexical synchronous trees. this paper compares different bilexical tree-based models for bilingual alignment. em training for the new model benefits from the dynamic programming "hook trick". the model produces improved dependency structure for both languages.
subword-based tagging for confidence-dependent chinese word segmentation. we proposed a subword-based tagging for chinese word segmentation to improve the existing character-based tagging. the subword-based tagging was implemented using the maximum entropy (maxent) and the conditional random fields (crf) methods. we found that the proposed subword-based tagging outperformed the character-based tagging in all comparative experiments. in addition, we proposed a confidence measure approach to combine the results of a dictionary-based and a subword-tagging-based segmentation. this approach can produce an ideal tradeoff between the in-vocaulary rate and out-of-vocabulary rate. our techniques were evaluated using the test data from sighan bakeoff 2005. we achieved higher f-scores than the best results in three of the four corpora: pku(0.951), cityu(0.950) and msr(0.971).
a progressive feature selection algorithm for ultra large feature spaces. recent developments in statistical modeling of various linguistic phenomena have shown that additional features give consistent performance improvements. quite often, improvements are limited by the number of features a system is able to explore. this paper describes a novel progressive training algorithm that selects features from virtually unlimited feature spaces for conditional maximum entropy (cme) modeling. experimental results in edit region identification demonstrate the benefits of the progressive feature selection (pfs) algorithm: the pfs algorithm maintains the same accuracy performance as previous cme feature selection algorithms (e.g., zhou et al., 2003) when the same feature spaces are used. when additional features and their combinations are used, the pfs gives 17.66% relative improvement over the previously reported best result in edit region identification on switchboard corpus (kahn et al., 2005), which leads to a 20% relative error reduction in parsing the switchboard corpus when gold edits are used as the upper bound.
detecting semantic relations between named entities in text using contextual features. this paper proposes a supervised learning method for detecting a semantic relation between a given pair of named entities, which may be located in different sentences. the method employs newly introduced contextual features based on centering theory as well as conventional syntactic and word-based features. these features are organized as a tree structure and are fed into a boosting-based classification algorithm. experimental results show the proposed method outperformed prior methods, and increased precision and recall by 4.4% and 6.7%.
a composite kernel to extract relations between entities with both flat and structured features. this paper proposes a novel composite kernel for relation extraction. the composite kernel consists of two individual kernels: an entity kernel that allows for entity-related features and a convolution parse tree kernel that models syntactic information of relation examples. the motivation of our method is to fully utilize the nice properties of kernel methods to explore diverse knowledge for relation extraction. our study illustrates that the composite kernel can effectively capture both flat and structured features without the need for extensive feature engineering, and can also easily scale to include more features. evaluation on the ace corpus shows that our method outperforms the previous best-reported methods and significantly out-performs previous two dependency tree kernels for relation extraction.
extracting relations with integrated information using kernel methods. entity relation detection is a form of information extraction that finds predefined relations between pairs of entities in text. this paper describes a relation detection approach that combines clues from different levels of syntactic processing using kernel methods. information from three different levels of processing is considered: tokenization, sentence parsing and deep dependency analysis. each source of information is represented by kernel functions. then composite kernels are developed to integrate and extend individual kernels so that processing errors occurring at one level can be overcome by information from other levels. we present an evaluation of these methods on the 2004 ace relation detection task, using support vector machines, and show that each level of syntactic processing contributes useful information for this task. when evaluated on the official test data, our approach produced very competitive ace value scores. we also compare the svm with knn on different kernels.
bitam: bilingual topic admixture models for word alignment. we propose a novel bilingual topical admixture (bitam) formalism for word alignment in statistical machine translation. under this formalism, the parallel sentence-pairs within a document-pair are assumed to constitute a mixture of hidden topics; each word-pair follows a topic-specific bilingual translation model. three bitam models are proposed to capture topic sharing at different levels of linguistic granularity (i.e., at the sentence or word levels). these models enable word-alignment process to leverage topical contents of document-pairs. efficient variational approximation algorithms are designed for inference and parameter estimation. with the inferred latent topics, bitam models facilitate coherent pairing of bilingual linguistic entities that share common topical aspects. our preliminary experiments show that the proposed models improve word alignment accuracy, and lead to better translation quality.
digesting virtual "geek" culture: the summarization of technical internet relay chats. this paper describes a summarization system for technical chats and emails on the linux kernel. to reflect the complexity and sophistication of the discussions, they are clustered according to subtopic structure on the sub-message level, and immediate responding pairs are identified through machine learning methods. a resulting summary consists of one or more mini-summaries, each on a subtopic from the discussion.
word association and mi-trigger-based language modeling. there exists strong word association in natural language. based on mutual information, this paper proposes a new mi-trigger-based modeling approach to capture the preferred relationships between words over a short or long distance. both the distance-independent(di) and distance-dependent(dd) mi-trigger-based models are constructed within a window. it is found that proper mi-trigger modeling is superior to word bigram model and the dd mi-trigger models have better performance than the di mi-trigger models for the same window size. it is also found that the number of the trigger pairs in an mi-trigger model can be kept to a reasonable size without losing too much of its modeling power. finally, it is concluded that the preferred relationships between words are useful to language disambiguation and can be modeled efficiently by the mi-trigger-based modeling approach.
automatically assessing the post quality in online discussions on software. assessing the quality of user generated content is an important problem for many web forums. while quality is currently assessed manually, we propose an algorithm to assess the quality of forum posts automatically and test it on data provided by nabble.com. we use state-of-the-art classification techniques and experiment with five feature classes: surface, lexical, syntactic, forum specific and similarity features. we achieve an accuracy of 89% on the task of automatically assessing post quality in the software domain using forum specific features. without forum specific features, we achieve an accuracy of 82%.
named entity recognition using an hmm-based chunk tagger. this paper proposes a hidden markov model (hmm) and an hmm-based chunk tagger, from which a named entity (ne) recognition (ner) system is built to recognize and classify names, times and numerical quantities. through the hmm, our system is able to apply and integrate four types of internal and external evidences: 1) simple deterministic internal feature of the words, such as capitalization and digitalization; 2) internal semantic feature of important triggers; 3) internal gazetteer feature; 4) external macro context feature. in this way, the ner problem can be resolved effectively. evaluation of our system on muc-6 and muc-7 english ne tasks achieves f-measures of 96.6% and 94.1% respectively. it shows that the performance is significantly better than reported by any other machine-learning system. moreover, the performance is even consistently better than those based on handcrafted rules.
generating usable formats for metadata and annotations in a large meeting corpus. the ami meeting corpus is now publicly available, including manual annotation files generated in the nxt xml format, but lacking explicit metadata for the 171 meetings of the corpus. to increase the usability of this important resource, a representation format based on relational databases is proposed, which maximizes informativeness, simplicity and reusability of the metadata and annotations. the annotation files are converted to a tabular format using an easily adaptable xslt-based mechanism, and their consistency is verified in the process. metadata files are generated directly in the imdi xml format from implicit information, and converted to tabular format using a similar procedure. the results and tools will be freely available with the ami corpus. sharing the metadata using the open archives network will contribute to increase the visibility of the ami corpus.
a hybrid approach to word segmentation and pos tagging. in this paper, we present a hybrid method for word segmentation and pos tagging. the target languages are those in which word boundaries are ambiguous, such as chinese and japanese. in the method, word-based and character-based processing is combined, and word segmentation and pos tagging are conducted simultaneously. experimental results on multiple corpora show that the integrated method has high accuracy.
an hmm-based approach to automatic phrasing for mandarin text-to-speech synthesis. automatic phrasing is essential to mandarin text-to-speech synthesis. we select word format as target linguistic feature and propose an hmm-based approach to this issue. then we define four states of prosodic positions for each word when employing a discrete hidden markov model. the approach achieves high accuracy of roughly 82%, which is very close to that from manual labeling. our experimental results also demonstrate that this approach has advantages over those part-of-speech-based ones.
an approximate approach for training polynomial kernel svms in linear time. kernel methods such as support vector machines (svms) have attracted a great deal of popularity in the machine learning and natural language processing (nlp) communities. polynomial kernel svms showed very competitive accuracy in many nlp problems, like part-of-speech tagging and chunking. however, these methods are usually too inefficient to be applied to large dataset and real time purpose. in this paper, we propose an approximate method to analogy polynomial kernel with efficient data mining approaches. to prevent exponential-scaled testing time complexity, we also present a new method for speeding up svm classifying which does independent to the polynomial degree d. the experimental results showed that our method is 16.94 and 450 times faster than traditional polynomial kernel in terms of training and testing respectively.
the effect of translation quality in mt-based cross-language information retrieval. this paper explores the relationship between the translation quality and the retrieval effectiveness in machine translation (mt) based cross-language information retrieval (clir). to obtain mt systems of different translation quality, we degrade a rule-based mt system by decreasing the size of the rule base and the size of the dictionary. we use the degraded mt systems to translate queries and submit the translated queries of varying quality to the ir system. retrieval effectiveness is found to correlate highly with the translation quality of the queries. we further analyze the factors that affect the retrieval effectiveness. title queries are found to be preferred in mt-based clir. in addition, dictionary-based degradation is shown to have stronger impact than rule-based degradation in mt-based clir.
maximum entropy based restoration of arabic diacritics. short vowels and other diacritics are not part of written arabic scripts. exceptions are made for important political and religious texts and in scripts for beginning students of arabic. script without diacritics have considerable ambiguity because many words with different diacritic patterns appear identical in a diacritic-less setting. we propose in this paper a maximum entropy approach for restoring diacritics in a document. the approach can easily integrate and make effective use of diverse types of information; the model we propose integrates a wide array of lexical, segment-based and part-of-speech tag features. the combination of these feature types leads to a state-of-the-art diacritization model. using a publicly available corpus (ldc's arabic treebank part 3), we achieve a diacritic error rate of 5.1%, a segment error rate 8.5%, and a word error rate of 17.3%. in case-ending-less setting, we obtain a diacritic error rate of 2.2%, a segment error rate 4.0%, and a word error rate of 7.2%.
a practical classification of multiword expressions. the paper proposes a methodology for dealing with multiword expressions in natural language processing applications. it provides a practically justified taxonomy of such units, and suggests the ways in which the individual classes can be processed computationally. while the study is currently limited to polish and english, we believe our findings can be successfully employed in the processing of other languages, with emphasis on inflectional ones.
rethinking chinese word segmentation: tokenization, character classification, or wordbreak identification. this paper addresses two remaining challenges in chinese word segmentation. the challenge in hlt is to find a robust segmentation method that requires no prior lexical knowledge and no extensive training to adapt to new types of data. the challenge in modelling human cognition and acquisition it to segment words efficiently without using knowledge of wordhood. we propose a radical method of word segmentation to meet both challenges. the most critical concept that we introduce is that chinese word segmentation is the classification of a string of character-boundaries (cb's) into either word-boundaries (wb's) and non-word-boundaries. in chinese, cb's are delimited and distributed in between two characters. hence we can use the distributional properties of cb among the background character strings to predict which cb's are wb's.
mapping concrete entities from parole-simple-clips to italwordnet: methodology and results. this paper describes a work in progress aiming at linking the two largest italian lexical-semantic databases italwordnet and parole-simple-clips. the adopted linking methodology, the software tool devised and implemented for this purpose and the results of the first mapping phase regarding 1storderentities are illustrated here.
construction of domain dictionary for fundamental vocabulary. for natural language understanding, it is essential to reveal semantic relations between words. to date, only the is-a relation has been publicly available. toward deeper natural language understanding, we semi-automatically constructed the domain dictionary that represents the domain relation between japanese fundamental words. this is the first japanese domain resource that is fully available. besides, our method does not require a document collection, which is indispensable for keyword extraction techniques but is hard to obtain. as a task-based evaluation, we performed blog categorization. also, we developed a technique for estimating the domain of unknown words.
exploration of term dependence in sentence retrieval. this paper focuses on the exploration of term dependence in the application of sentence retrieval. the adjacent terms appearing in query are assumed to be related with each other. these assumed dependences among query terms will be further validated for each sentence and sentences, which present strong syntactic relationship among query terms, are considered more relevant. experimental results have fully demonstrated the promising of the proposed models in improving sentence retrieval effectiveness.
deriving an ambiguous word's part-of-speech distribution from unannotated text. a distributional method for part-of-speech induction is presented which, in contrast to most previous work, determines the part-of-speech distribution of syntactically ambiguous words without explicitly tagging the underlying text corpus. this is achieved by assuming that the word pair consisting of the left and right neighbor of a particular token is characteristic of the part of speech at this position, and by clustering the neighbor pairs on the basis of their middle words as observed in a large corpus. the results obtained in this way are evaluated by comparing them to the part-of-speech distributions as found in the manually tagged brown corpus.
multilingual ontological analysis of european directives. this paper describes the main features of our tool called "legal taxonomy syllabus". the system is an ontology based tool designed to annotate and recover multi-lingua legal information and build conceptual dictionaries on european directives.
a translation aid system with a stratified lookup interface. we are currently developing a translation aid system specially designed for english-to-japanese volunteer translators working mainly online. in this paper we introduce the stratified reference lookup interface that has been incorporated into the source text area of the system, which distinguishes three user awareness levels depending on the type and nature of the reference unit. the different awareness levels are assigned to reference units from a variety of reference sources, according to the criteria of "composition", "difficulty", "speciality" and "resource type".
an api for measuring the relatedness of words in wikipedia. we present an api for computing the semantic relatedness of words in wikipedia.
a linguistic service ontology for language infrastructures. this paper introduces conceptual framework of an ontology for describing linguistic services on network-based language infrastructures. the ontology defines a taxonomy of processing resources and the associated static language resources. it also develops a sub-ontology for abstract linguistic objects such as expression, meaning, and description; these help define functionalities of a linguistic service. the proposed ontology is expected to serve as a solid basis for the interoperability of technical elements in language infrastructures.
an owl ontology for hpsg. the paper presents an owl ontology for hpsg. the hpsg ontology is integrated with an existing owl ontology, gold, as a community of practice extension. the basic ideas are illustrated by visualizations of type hierarchies for parts of speech.
measuring importance and query relevance in topic-focused multi-document summarization. the increasing complexity of summarization systems makes it difficult to analyze exactly which modules make a difference in performance. we carried out a principled comparison between the two most commonly used schemes for assigning importance to words in the context of query focused multi-document summarization: raw frequency (word probability) and log-likelihood ratio. we demonstrate that the advantages of log-likelihood ratio come from its known distributional properties which allow for the identification of a set of words that in its entirety defines the aboutness of the input. we also find that llr is more suitable for query-focused summarization since, unlike raw frequency, it is more sensitive to the integration of the information need defined by the user.
empirical measurements of lexical similarity in noun phrase conjuncts. the ability to detect similarity in conjunct heads is potentially a useful tool in helping to disambiguate coordination structures - a difficult task for parsers. we propose a distributional measure of similarity designed for such a task. we then compare several different measures of word similarity by testing whether they can empirically detect similarity in the head nouns of noun phrase conjuncts in the wall street journal (wsj) treebank. we demonstrate that several measures of word similarity can successfully detect conjunct head similarity and suggest that the measure proposed in this paper is the most appropriate for this task.
measuring syntactic difference in british english. recent work by nerbonne and wiersma (2006) has provided a foundation for measuring syntactic differences between corpora. it uses part-of-speech trigrams as an approximation to syntactic structure, comparing the trigrams of two corpora for statistically significant differences. this paper extends the method and its application. it extends the method by using leaf-path ancestors of sampson (2000) instead of trigrams, which capture internal syntactic structure---every leaf in a parse tree records the path back to the root. the corpus used for testing is the international corpus of english, great britain (nelson et al., 2002), which contains syntactically annotated speech of great britain. the speakers are grouped into geographical regions based on place of birth. this is different in both nature and number than previous experiments, which found differences between two groups of norwegian l2 learners of english. we show that dialectal variation in eleven british regions from the ice-gb is detectable by our algorithm, using both leaf-ancestor paths and trigrams.
exploiting structure for event discovery using the mdi algorithm. effectively identifying events in unstructured text is a very difficult task. this is largely due to the fact that an individual event can be expressed by several sentences. in this paper, we investigate the use of clustering methods for the task of grouping the text spans in a news article that refer to the same event. the key idea is to cluster the sentences, using a novel distance metric that exploits regularities in the sequential structure of events within a document. when this approach is compared to a simple bag of words baseline, a statistically significant increase in performance is observed.
shallow dependency labeling. we present a formalization of dependency labeling with integer linear programming. we focus on the integration of subcategorization into the decision making process, where the various subcategorization frames of a verb compete with each other. a maximum entropy model provides the weights for ilp optimization.
extracting hypernym pairs from the web. we apply pattern-based methods for collecting hypernym relations from the web. we compare our approach with hypernym extraction from morphological clues and from large text corpora. we show that the abundance of available data on the web enables obtaining good results with relatively unsophisticated techniques.
poliqarp: an open source corpus indexer and search engine with syntactic extensions. this paper presents recent extensions to poliqarp, an open source tool for indexing and searching morphosyntactically annotated corpora, which turn it into a tool for indexing and searching certain kinds of treebanks, complementary to existing treebank search engines. in particular, the paper discusses the motivation for such a new tool, the extended query syntax of poliqarp and implementation and efficiency issues.
semtag: a platform for specifying tree adjoining grammars and performing tag-based semantic construction. in this paper, we introduce semtag, a free and open software architecture for the development of tree adjoining grammars integrating a compositional semantics. semtag differs from xtag in two main ways. first, it provides an expressive grammar formalism and compiler for factorising and specifying tags. second, it supports semantic construction.
automatic prediction of cognate orthography using support vector machines. this paper describes an algorithm to automatically generate a list of cognates in a target language by means of support vector machines. while levenshtein distance was used to align the training file, no knowledge repository other than an initial list of cognates used for training purposes was input into the algorithm. evaluation was set up in a cognate production scenario which mimed a real-life situation where no word lists were available in the target language, delivering the ideal environment to test the feasibility of a more ambitious project that will involve language portability. an overall improvement of 50.58% over the baseline showed promising horizons.
extending marie: an n-gram-based smt decoder. in this paper we present several extensions of marie, a freely available n-gram-based statistical machine translation (smt) decoder. the extensions mainly consist of the ability to accept and generate word graphs and the introduction of two new n-gram models in the loglinear combination of feature functions the decoder implements. additionally, the decoder is enhanced with a caching strategy that reduces the number of n-gram calls improving the overall search efficiency. experiments are carried out over the eurpoean parliament spanish-english translation task.
an efficient algorithm for building a distributional thesaurus (and other sketch engine developments). gorman and curran (2006) argue that thesaurus generation for billion+-word corpora is problematic as the full computation takes many days. we present an algorithm with which the computation takes under two hours. we have created, and made publicly available, thesauruses based on large corpora for (at time of writing) seven major world languages. the development is implemented in the sketch engine (kilgarriff et al., 2004). another innovative development in the same tool is the presentation of the grammatical behaviour of a word against the background of how all other words of the same word class behave. thus, the english noun constraint occurs 75% in the plural. is this a salient lexical fact? to form a judgement, we need to know the distribution for all nouns. we use histograms to present the distribution in a way that is easy to grasp.
building emotion lexicon from weblog corpora. an emotion lexicon is an indispensable resource for emotion analysis. this paper aims to mine the relationships between words and emotions using weblog corpora. a collocation model is proposed to learn emotion lexicons from weblog articles. emotion classification at sentence level is experimented by using the mined lexicons to demonstrate their usefulness.
computing lexical chains with graph clustering. this paper describes a new method for computing lexical chains. these are sequences of semantically related words that reflect a text's cohesive structure. in contrast to previous methods, we are able to select chains based on their cohesive strength. this is achieved by analyzing the connectivity in graphs representing the lexical chains. we show that the generated chains significantly improve performance of automatic text summarization and keyphrase indexing.
identifying linguistic structure in a quantitative analysis of dialect pronunciation. the aim of this paper is to present a new method for identifying linguistic structure in the aggregate analysis of the language variation. the method consists of extracting the most frequent sound correspondences from the aligned transcriptions of words. based on the extracted correspondences every site is compared to all other sites, and a correspondence index is calculated for each site. this method enables us to identify sound alternations responsible for dialect divisions and to measure the extent to which each alternation is responsible for the divisions obtained by the aggregate analysis.
japanese dependency parsing using sequential labeling for semi-spoken language. the amount of documents directly published by end users is increasing along with the growth of web 2.0. such documents often contain spoken-style expressions, which are difficult to analyze using conventional parsers. this paper presents dependency parsing whose goal is to analyze japanese semi-spoken expressions. one characteristic of our method is that it can parse self-dependent (independent) segments using sequential labeling.
semantic classification of noun phrases using web counts and learning algorithms. this paper investigates the use of machine learning algorithms to label modifier-noun compounds with a semantic relation. the attributes used as input to the learning algorithms are the web frequencies for phrases containing the modifier, noun, and a prepositional joining term. we compare and evaluate different algorithms and different joining phrases on nastase and szpakowicz's (2003) dataset of 600 modifier-noun compounds. we find that by using a support vector machine classifier we can obtain better performance on this dataset than a current state-of-the-art system; even with a relatively small set of prepositional joining terms.
extractive summarization based on event term clustering. event-based summarization extracts and organizes summary sentences in terms of the events that the sentences describe. in this work, we focus on semantic relations among event terms. by connecting terms with relations, we build up event term graph, upon which relevant terms are grouped into clusters. we assume that each cluster represents a topic of documents. then two summarization strategies are investigated, i.e. selecting one term as the representative of each topic so as to cover all the topics, or selecting all terms in one most significant topic so as to highlight the relevant information related to this topic. the selected terms are then responsible to pick out the most appropriate sentences describing them. the evaluation of clustering-based summarization on duc 2001 document sets shows encouraging improvement over the well-known pagerank-based summarization.
nict-atr speech-to-speech translation system. this paper describes the latest version of speech-to-speech translation systems developed by the team of nict-atr for over twenty years. the system is now ready to be deployed for the travel domain. a new noise-suppression technique notably improves speech recognition performance. corpus-based approaches of recognition, translation, and synthesis enable coverage of a wide variety of topics and portability to other languages.
ensemble document clustering using weighted hypergraph generated by nmf. in this paper, we propose a new ensemble document clustering method. the novelty of our method is the use of non-negative matrix factorization (nmf) in the generation phase and a weighted hypergraph in the integration phase. in our experiment, we compared our method with some clustering methods. our method achieved the best results.
inducing combinatory categorial grammars with genetic algorithms. this paper proposes a novel approach to the induction of combinatory categorial grammars (ccgs) by their potential affinity with the genetic algorithms (gas). specifically, ccgs utilize a rich yet compact notation for lexical categories, which combine with relatively few grammatical rules, presumed universal. thus, the search for a ccg consists in large part in a search for the appropriate categories for the data-set's lexical items. we present and evaluates a system utilizing a simple ga to successively search and improve on such assignments. the fitness of categorial-assignments is approximated by the coverage of the resulting grammar on the data-set itself, and candidate solutions are updated via the standard ga techniques of reproduction, crossover and mutation.
adaptive string distance measures for bilingual dialect lexicon induction. this paper compares different measures of graphemic similarity applied to the task of bilingual lexicon induction between a swiss german dialect and standard german. the measures have been adapted to this particular language pair by training stochastic transducers with the expectation-maximisation algorithm or by using handmade transduction rules. these adaptive metrics show up to 11% f-measure improvement over a static metric like levenshtein distance.
logistic online learning methods and their application to incremental dependency parsing. we investigate a family of update methods for online machine learning algorithms for cost-sensitive multiclass and structured classification problems. the update rules are based on multinomial logistic models. the most interesting question for such an approach is how to integrate the cost function into the learning paradigm. we propose a number of solutions to this problem. to demonstrate the applicability of the algorithms, we evaluated them on a number of classification tasks related to incremental dependency parsing. these tasks were conventional multiclass classification, hiearchical classification, and a structured classification task: complete labeled dependency tree prediction. the performance figures of the logistic algorithms range from slightly lower to slightly higher than margin-based online algorithms.
using error-correcting output codes with model-refinement to boost centroid text classifier. in this work, we investigate the use of error-correcting output codes (ecoc) for boosting centroid text classifier. the implementation framework is to decompose one multi-class problem into multiple binary problems and then learn the individual binary classification problems by centroid classifier. however, this kind of decomposition incurs considerable bias for centroid classifier, which results in noticeable degradation of performance for centroid classifier. in order to address this issue, we use model-refinement to adjust this so-called bias. the basic idea is to take advantage of misclassified examples in the training data to iteratively refine and adjust the centroids of text data. the experimental results reveal that model-refinement can dramatically decrease the bias introduced by ecoc, and the combined classifier is comparable to or even better than svm classifier in performance.
mimus: a multimodal and multilingual dialogue system for the home domain. this paper describes mimus, a multimodal and multilingual dialogue system for the in--home scenario, which allows users to control some home devices by voice and/or clicks. its design relies on wizard of oz experiments and is targeted at disabled users. mimus follows the information state update approach to dialogue management, and supports english, german and spanish, with the possibility of changing language on--the--fly. mimus includes a gestures--enabled talking head which endows the system with a human--like personality.
test collection selection and gold standard generation for a multiply-annotated opinion corpus. opinion analysis is an important research topic in recent years. however, there are no common methods to create evaluation corpora. this paper introduces a method for developing opinion corpora involving multiple annotators. the characteristics of the created corpus are discussed, and the methodologies to select more consistent testing collections and their corresponding gold standards are proposed. under the gold standards, an opinion extraction system is evaluated. the experiment results show some interesting phenomena.
classifying temporal relations between events. this paper describes a fully automatic two-stage machine learning architecture that learns temporal relations between pairs of events. the first stage learns the temporal attributes of single event descriptions, such as tense, grammatical aspect, and aspectual class. these imperfect guesses, combined with other linguistic features, are then used in a second stage to classify the temporal relationship between two events. we present both an analysis of our new features and results on the timebank corpus that is 3% higher than previous work that used perfect human tagged features.
learning to rank definitions to generate quizzes for interactive information presentation. this paper proposes the idea of ranking definitions of a person (a set of biographical facts) to automatically generate "who is this?" quizzes. the definitions are ordered according to how difficult they make it to name the person. such ranking would enable users to interactively learn about a person through dialogue with a system with improved understanding and lasting motivation, which is useful for educational systems. in our approach, we train a ranker that learns from data the appropriate ranking of definitions based on features that encode the importance of keywords in a definition as well as its content. experimental results show that our approach is significantly better in ranking definitions than baselines that use conventional information retrieval measures such as tf*idf and pointwise mutual information (pmi).
expanding indonesian-japanese small translation dictionary using a pivot language. we propose a novel method to expand a small existing translation dictionary to a large translation dictionary using a pivot language. our method depends on the assumption that it is possible to find a pivot language for a given language pair on condition that there are both a large translation dictionary from the source language to the pivot language, and a large translation dictionary from the pivot language to the destination language. experiments that expands the indonesian-japanese dictionary using the english language as a pivot language shows that the proposed method can improve performance of a real clir system.
minimally lexicalized dependency parsing. dependency structures do not have the information of phrase categories in phrase structure grammar. thus, dependency parsing relies heavily on the lexical information of words. this paper discusses our investigation into the effectiveness of lexicalization in dependency parsing. specifically, by restricting the degree of lexicalization in the training phase of a parser, we examine the change in the accuracy of dependency relations. experimental results indicate that minimal or low lexicalization is sufficient for parsing accuracy.
support vector machines for query-focused summarization trained and evaluated on pyramid data. this paper presents the use of support vector machines (svm) to detect relevant information to be included in a query-focused summary. several svms are trained using information from pyramids of summary content units. their performance is compared with the best performing systems in duc-2005, using both rouge and autopan, an automatic scoring method for pyramid evaluation.
a joint statistical model for simultaneous word spacing and spelling error correction for korean. this paper presents noisy-channel based korean preprocessor system, which corrects word spacing and typographical errors. the proposed algorithm corrects both errors simultaneously. using eojeol transition pattern dictionary and statistical data such as eumjeol n-gram and jaso transition probabilities, the algorithm minimizes the usage of huge word dictionaries.
disambiguating between generic and referential "you" in dialog. we describe an algorithm for a novel task: disambiguating the pronoun you in conversation. you can be generic or referential; finding referential you is important for tasks such as addressee identification or extracting 'owners' of action items. our classifier achieves 84% accuracy in two-person conversations; an initial study shows promising performance even on more complex multi-party meetings.
a feature based approach to leveraging context for classifying newsgroup style discussion segments. on a multi-dimensional text categorization task, we compare the effectiveness of a feature based approach with the use of a state-of-the-art sequential learning technique that has proven successful for tasks such as "email act classification". our evaluation demonstrates for the three separate dimensions of a well established annotation scheme that novel thread based features have a greater and more consistent impact on classification performance.
constraint reasoning in deep biomedical models. objective:: deep biomedical models are often expressed by means of differential equations. despite their expressive power, they are difficult to reason about and make decisions, given their non-linearity and the important effects that the uncertainty on data may cause. the objective of this work is to propose a constraint reasoning framework to support safe decisions based on deep biomedical models. method:: the methods used in our approach include the generic constraint propagation techniques for reducing the bounds of uncertainty of the numerical variables complemented with new constraint reasoning techniques that we developed to handle differential equations. results:: the results of our approach are illustrated in biomedical models for the diagnosis of diabetes, tuning of drug design and epidemiology where it was a valuable decision-supporting tool notwithstanding the uncertainty on data. conclusion:: the main conclusion that follows from the results is that, in biomedical decision support, constraint reasoning may be a worthwhile alternative to traditional simulation methods, especially when safe decisions are required.
content collection for the labelling of health-related web content. as the number of health-related web sites in various languages increases, so does the need for control mechanisms that give the users adequate guarantee on whether the web resources they are visiting meet a minimum level of quality standards. based upon state-of-the-art technology in the areas of semantic web, content analysis and quality labelling, the medieq project, integrates existing technologies and tests them in a novel application: the automation of the labelling process in health-related web content. medieq provides tools that crawl the web to locate unlabelled health web resources, to label them according to pre-defined labelling criteria, as well as to monitor them. this paper focuses on content collection and discusses our experiments in the english language.
an application of machine learning in the diagnosis of ischaemic heart disease. ischaemic heart disease is one of the world's most important causes of mortality, so improvements and rationalization of diagnostic procedures would be very useful. the four diagnostic levels consist of evaluation of signs and symptoms of the disease and ecg (electrocardiogram) at rest, sequential ecg testing during the controlled exercise, myocardial scintigraphy and finally coronary angiography. the diagnostic process is stepwise and the results are interpreted hierarchically, i.e, the next step is necessary only if the results of the former are inconclusive. because suggestibility is possible, the results of each step are interpreted individually and only the results of the highest step are valid. on the other hand, machine learning methods may be capable of objective interpretation of all available results for the same patient and in this way increase the diagnostic accuracy, sensitivity and specificity of each step. in the usual setting, the machine learning algorithms are tuned to maximize classification accuracy. in our case, the sensitivity and specificity were much more important, so we generalized the algorithms to take in account the variable misclassification costs. the costs can be tuned in order to bias the algorithms towards higher sensitivity or specificity. we conducted many experiments with four learning algorithms and different variations of our dataset (327 patients with completed diagnostic procedures). our results show that improvements using machine learning techniques are reasonable and might find good use in practice.
extending temporal databases to deal with telic/atelic medical data. objective: in this paper, we aim at defining a general-purpose data model and query language coping with both ''telic'' and ''atelic'' medical data. background: in the area of medical informatics, there is an increasing realization that temporal information plays a crucial role, so that suitable database models and query languages are needed to store and support it. however, despite the wide range of approaches in the area, in this paper we show that a relevant class of medical data cannot be properly dealt with. methodology: we first show that data models based on the ''point-based'' semantics, which is (implicitly or explicitly) assumed by the totality of temporal database approaches, have several limitations when dealing with ''telic'' data. we then propose a new model (based on the ''interval-based'' semantics) to cope with such data, and extend the query language accordingly. results: we propose a new three-sorted model and a query language to properly deal with both ''telic'' and ''atelic'' medical data (as well as non-temporal data). our query language is flexible, since it allows one to switch from ''atelic'' to ''telic'' data, and vice versa. conclusion: in this paper, we demostrate the feasibilty of a database approach copying with both telic and atelic data as needed in several (medical) applications.
credal classification for dementia screening. dementia is a very serious personal, medical and social problem. early and accurate diagnoses seem to be the key to effectively cope with it. this paper presents a diagnostic tool that couples the most widely used computerized system of cognitive tests in dementia research, the cognitive drug research system, with the naive credal classifier. although the classifier is trained on an incomplete database, it provides unmatched predictive performance and reliability. the tool also proves to be very effective in discriminating between alzheimer''s disease and dementia with lewy bodies, which is a problem on the frontier of research on dementia.
bayesian network decomposition for modeling breast cancer detection. the automated differentiation between benign and malignant abnormalities is a difficult problem in the breast cancer domain. while previous studies consider a single bayesian network approach, in this paper we propose a novel perspective based on bayesian network decomposition. we consider three methods that allow for different (levels of) network topological or structural decomposition. through examples, we demonstrate some advantages of bayesian network decomposition for the problem at hand: (i) natural and more intuitive representation of breast abnormalities and their features (ii) compact representation and efficient manipulation of large conditional probability tables, and (iii) a possible improvement in the knowledge acquisition and representation processes.
adaptive optimization of hospital resource calendars. as demand for health care increases, a high efficiency on limited resources is necessary for affordable high patient service levels. here, we present an adaptive approach to efficient resource usage by automatic optimization of resource calendars. we describe a precise model based on a case study at the radiology department of the academic medical center amsterdam (amc). we model the properties of the different groups of patients, with additional differentiating urgency levels. based on this model, we develop a detailed simulation that is able to replicate the known scheduling problems. in particular, the simulation shows that due to fluctuations in demand, the allocations in the resource calendar must be flexible in order to make efficient use of the resources. we develop adaptive algorithms to automate iterative adjustments to the resource calendar. to test the effectiveness of our approach, we evaluate the algorithms using the simulation. our adaptive optimization approach is able to maintain overall target performance levels while the resource is used at high efficiency.
inference in the promedas medical expert system. in the current paper, the promedas model for internal medicine, developed by our team, is introduced. the model is based on up-to-date medical knowledge and consists of approximately 2000 diagnoses, 1000 findings and 8600 connections between diagnoses and findings, covering a large part of internal medicine. we show that belief propagation (bp) can be successfully applied as approximate inference algorithm in the promedas network. in some cases, however, we find errors that are too large for this application. we apply a recently developed method that improves the bp results by means of a loop expansion scheme. this method, termed loop corrected (lc) bp, is able to improve the marginal probabilities significantly, leaving a remaining error which is acceptable for the purpose of medical diagnosis.
an experiment in automatic classification of pathological reports. medical reports are predominantly written in natural language; as such they are not computer-accessible. a common way to make medical narrative accessible to automated systems is by assigning `computer-understandable' keywords from a controlled vocabulary. experts usually perform this task by hand. in this paper, we investigate methods to support or automate this type of medical classification. we report on experiments using the palga data set, a collection of 14 million pathological reports, each of which has been classified by a domain expert. we describe methods for automatically categorizing the documents in this data set in an accurate way. in order to evaluate the proposed automatic classification approaches, we compare their output with that of two additional human annotators. while the automatic system performs well in comparison with humans, the inconsistencies within the annotated data constrain the maximum attainable performance.
temporal data mining with temporal constraints. nowadays, methods for discovering temporal knowledge try to extract more complete and representative patterns. the use of qualitative temporal constraints can be helpful in that aim, but its use should also involve methods for reasoning with them (instead of using them just as a high level representation) when a pattern consists of a constraint network instead of an isolated constraint.in this paper, we put forward a method for mining temporal patterns that makes use of a formal model for representing and reasoning with qualitative temporal constraints. three steps should be accomplished in the method: 1) the selection of a model that allows a trade off between efficiency and representation; 2) a preprocessing step for adapting the input to the model; 3) a data mining algorithm able to deal with the properties provided by the model for generating a representative output.in order to implement this method we propose the use of the fuzzy temporal constraint network (ftcn) formalism and of a temporal abstraction method for preprocessing. finally, the ideas of the classic methods for data mining inspire an algorithm that can generate ftcns as output.along this paper, we focus our attention on the data mining algorithm.
using temporal context-specific independence information in the exploratory analysis of disease processes. disease processes in patients are temporal in nature and involve uncertainty. it is necessary to gain insight into these processes when aiming at improving the diagnosis, treatment and prognosis of disease in patients. one way to achieve these aims is by explicitly modelling disease processes; several researchers have advocated the use of dynamic bayesian networks for this purpose because of the versatility and expressiveness of this time-oriented probabilistic formalism. in the research described in this paper, we investigate the role of context-specific independence information in modelling the evolution of disease. the hypothesis tested was that within similar populations of patients differences in the learnt structure of a dynamic bayesian network may result, depending on whether or not patients have a particular disease. this is an example of temporal context-specific independence information. we have tested and confirmed this hypothesis using a constraint-based bayesian network structure learning algorithm which supports incorporating background knowledge into the learning process. clinical data of mechanically-ventilated icu patients, some of whom developed ventilator-associated pneumonia, were used for that purpose.
the role of model checking in critiquing based on clinical guidelines. medical critiquing systems criticise clinical actions performed by a physician. in order to provide useful feedback, an important task is to find differences between the actual actions and a set of `ideal' actions as described by a clinical guideline. in case differences exist, insight to which extent they are compatible is provided by the critiquing system. we propose a methodology for such critiquing, where the ideal actions are given by a formal model of a clinical guideline, and where the actual actions are derived from real world patient data. we employ model checking to investigate whether a part of the actual treatment is consistent with the guideline. furthermore, it is shown how critiquing can be cast in terms of temporal logic, and what can be achieved by using model checking. the methodology has been applied to a clinical guideline of breast cancer in conjunction with breast cancer patient data.
procarsur: a system for dynamic prognostic reasoning in cardiac surgery. we present the procarsur system for prognostic reasoning in the domain of cardiac surgery. the system has a three-tiered architecture consisting of a bayesian network, a task layer, and a graphical user interface. in contrast to traditional prognostic tools, that are usually based on logistic regression, procarsur implements a dynamic, process-oriented view on prognosis. the system distinguishes between the various phases of peri-surgical care, explicates the scenarios that lead to different clinical outcomes, and can be used to update predictions when new information becomes available. to support users in their interaction with the bayesian network, a set of predefined prognostic reasoning tasks is implemented in the task layer. the user communicates with the system through an interface that hides the underlying bayesian network and aggregates the results of probabilistic inferences.
segmentation techniques for automatic region extraction: an application to aphasia rehabilitation. we describe a system that facilitates speech therapists to administer cognitive rehabilitation exercises and to evaluate treatment outcomes. we started by augmenting a commercial tool with a more user-friendly interface, meeting the needs of the healthcare professionals involved. then we integrated, into the same tool, a new type of exercise, that is particularly patient-tailored, being based on the recognition of familiar images within a picture (such as a relative, a domestic animal, a home object, etc). segmentation techniques are used to elaborate an input picture and individuate areas including interesting objects, that will be semi-automatically linked to text and sound. the picture and associated information are then stored in the system database and may be subsequently used as objects for the new exercise. any number of images may be elaborated, personalised and stored for each patient. the performance has been tested on voluntary subjects with good results.
nasopharyngeal carcinoma data analysis with a novel bayesian network skeleton learning algorithm. in this paper, we discuss efforts to apply a novel bayesian network (bn) structure learning algorithm to a real world epidemiological problem, namely the nasopharyngeal carcinoma (npc). our specific aims are : (1) to provide a statistical profile of the recruited population, (2) to help indentify the important environmental risk factors involved in npc, and (3) to gain insight on the applicability and limitations of bn methods on small epidemiological data sets obtained from questionnaires. we discuss first the novel bn structure learning algorithm called max-min parents and children skeleton (mmpc) developped by tsamardinos et al. in 2005. mmpc was proved by extensive empirical simulations to be an excellent trade-off between time and quality of reconstruction compared to most constraint based algorithms, especially for the smaller sample sizes. unfortunately, mmpc is unable to deal with datasets containing approximate functional dependencies between variables. in this work, we overcome this problem and apply the new version of mmpc on nasopharyngeal carcinoma data in order to shed some light into the statistical profile of the population under study.
induction of partial orders to predict patient evolutions in medicine. in medicine, prognosis is the task of predicting the probable course and outcome of a disease. questions like, is a patient going to improve?, what is his/her chance of recovery?, and how likely a relapse is? are common and they rely on the concept of state. the feasible states of a disease define a partial order structure with extreme states those of 'cure' and 'death'; improving, recovering, and survival meaning particular transitions between states of the partial order. in spite of this, it is not usual in medicine to find an explicit representation either of the states or of the states partial order for many diseases. on the contrary, the variables (e.g. signs and symptoms) related to a disease and their normality and abnormality values are broadly agreed. here, an inductive algorithm is introduced that generates partial orders from a data matrix containing information about the patient-professional encounters, and the normality functions of each one of these disease variables.
machine learning techniques for decision support in anesthesia. the growing availability of measurement devices in the operating room enables the collection of a huge amount of data about the state of the patient and the doctors' practice during a surgical operation. this paper explores the possibilities of generating, from these data, decision support rules in order to support the daily anesthesia procedures. in particular, we focus on machine learning techniques to design a decision support tool. the preliminary tests in a simulation setting are promising and show the role of computational intelligence techniques in extracting useful information for anesthesiologists.
a novel way of incorporating large-scale knowledge into mrf prior model. based on markov random fields (mrf) theory, bayesian methods have been accepted as an effective solution to overcome the ill-posed problems of image restoration and reconstruction. traditionally, the knowledge in most of prior models is from a simply weighted differences between the pixel intensities within a small local neighborhood, so it can only provide limited prior information for regularization. exploring the ways of incorporating more large-scale knowledge into prior model, this paper proposes an effective approach to incorporate large-scale image knowledge into mrf prior model. and a novel nonlocal prior is put forward. relevant experiments in emission tomography prove that the proposed mrf nonlocal prior is capable of imposing more effective regularization on original reconstructions.
testing careflow process execution conformance by translating a graphical language to computational logic. careflow systems implement workflow concepts in the clinical domain in order to administer, support and monitor the execution of health care services performed by different health care professionals and structures. in this work we focus on the monitoring aspects and propose a solution for the conformance verification of careflow process executions.given a careflow model, we have defined an algorithm capable of translating it to a formal language based on computational logic and abductive logic programming in particular. the main advantage of this formalism lies in its operational proof-theoretic counterpart, which is able to verify the conformance of a given careflow process execution (in the form of an event log) w.r.t. the model.the feasibility of the approach has been tested on a case study related to the careflow process described in the cervical cancer screening protocol.
querying clinical workflows by temporal similarity. the degree of fulfillment of clinical guidelines is considered a key factor when evaluating the quality of a clinical service. guidelines can be seen as processes describing the sequence of activities to be done. consequently, workflow formalisms seem to be a valid approach to model the flow of actions in the guideline and their temporal aspects. the application of a guideline to a specific patient (guideline instance) can be modeled by means of a workflow case. the best (worst) application of a guideline, represented as a reference workflow case, can be used to evaluate the quality of the service, by comparing the optimal case with specific patient instances. on the other hand, the correct application of a guideline to a patient involves the fulfillment of the guideline temporal constraints. thus, the evaluation of the temporal similarity degree between different workflow cases is a key aspect in evaluating health care quality. in this work, we represent a portion of the stroke guideline using a temporal workflow schema and we propose a method to evaluate the temporal similarity between workflow cases. our proposal, based on temporal constraint networks, consists of a linear combination of functions to differentiate intra-task and inter-task temporal distances.
metacode: a lightweight umls mapping tool. in the course of our current research on automatic information extraction from medical electronic literature, we have been facing the need to map big corpora onto the concepts of the umls metathesaurus, both in french and in english. in order to meet our specific needs in terms of processing speed, we have developed a lightweight umls tagger, metacode, that processes large text collections at an acceptable speed, but at the cost of the sophistication of the treatments. in this paper, we describe metacode and evaluate its quality, allowing potential users to balance the gain in speed against the loss in quality.
extracting specific medical data using semantic structures. in this paper, we discuss the architecture, functionality and performance of a medical information extraction system. the system is based on an approach to automatic generation of semantic structures for free-text. using a multiaxial nomenclature (wingert nomenclature) and existing language-engineering technologies, a conceptual graph-like representation is produced for each sentence of a text. these semantic structures are then exploited to extract information. the components that might be adopted for processing texts in another language than german are identified. results of first evaluations of the system's performance in an information extraction (ie) subtask in the medical domain are presented: the filling of selected template slots obtained values of 81- 95% precision and 83-97% recall.
unsupervised documents categorization using new threshold-sensitive weighting technique. as the number of published documents increase quickly, there is a crucial need for fast and sensitive categorization methods to manage the produced information. in this paper, we focused on the categorization of biomedical documents with concepts of the gene ontology, an ontology dedicated to gene description. our approach discovers associations between the predefined concepts and the documents using string matching techniques. the assignations are ranked according to a score computed given several strategies. the effects of these different scoring strategies on the categorization effectiveness are evaluated. more especially a new weighting technique based on term frequency is presented. this new weighting technique improves the categorization effectiveness on most of the experiment performed. this paper shows that a cleaver use of the frequency can bring substantial benefits when performing automatic categorization on large collection of documents.
supporting factors in descriptive analysis of brain ischaemia. this paper analyzes two different approaches to the detection of supporting factors used in descriptive induction. the first is based on the statistical comparison of the pattern properties relative to the properties of the entire negative and the entire positive example sets. the other approach uses artificially generated random examples that are added into the original training set. the methodology is illustrated in the analysis of patients suffering from brain ischaemia.
automatic retrieval of web pages with standards of ethics and trustworthiness within a medical portal: what a page name tells us. the ever-increasing volume of health online information, coupled with the uneven reliability and quality, may have considerable implications for the citizen. in order to address this issue, we propose to use, within a general or specialised search engine, standards for identifying the reliability of online documents. standards used are those related to the ethics as well as trustworthiness of websites. in this research, they are detected through the url names of web pages by applying machine learning algorithms. according to algorithms used and to principles, our straightforward approach shows up to 93% precision and 91% recall. but a few principles remain difficult to recognize.
integrating document-based and knowledge-based models for clinical guidelines analysis. research in the computerization of clinical guidelines (cg) has often opposed document-based approaches to knowledge-based ones. in this paper, we suggest that both approaches can be used simultaneously to assess the contents of textual clinical guidelines. in this first experiment, we investigate the mapping between a document model, which has been marked-up to structure its recommendations, and a knowledge structure representing the management of specific disease. this knowledge representation is based on planning formalisms, more specifically hierarchical task networks (htn). our system operates by first automatically encoding the textual guideline through the identification of specific expressions with surface natural language processing, as described in previous work. in a subsequent step, the htn, constructed manually and independently, and represented as an explicit and/or graph, is searched for a solution sub-graph using an algorithm derived from ao*. whilst the htn is being traversed, corresponding information is accessed in the encoded textual cg, to guide the solution extraction process. we illustrate this through a case study developed around french guidelines for the management of hypertension. recommendations included in the textual guideline provide complementary information for the instantiation of an htn on specific patient data. the mapping takes place at different levels, from the pre-condition of operators to the rules playing a role as selection heuristics when extracting a solution sub-graph. such a process, which explores the textual document from the prospective of a task model, can help analyzing the overall structure of clinical guidelines and ultimately improving its applicability.
predictive modeling of fmri brain states using functional canonical correlation analysis. we present a novel method for predictive modeling of human brain states from functional neuroimaging (fmri) data. extending the traditional canonical correlation analysis of discrete data to the domain of stochastic functional measurements, the method explores the functional canonical correlation between stimuli and fmri training data. via an incrementally steered pattern searching technique, subspaces of voxel time courses are explored to arrive at (spatially distributed) voxel clusters that optimize the relationship between stimuli and fmri in terms of redundancy. application of the method for prediction of naturalistic stimuli from unknown fmri data shows that the method finds highly predictive brain areas, i.e. brain areas relevant in processing the stimuli.
application of cross-language criteria for the automatic distinction of expert and non expert online health documents. distinction between expert and non expert documents is an important issue in the medical area, for instance in the context of information retrieval. in our work we address this issue through stylistic corpus analysis and application of machine learning algorithms. our hypothesis is that this distinction can be observed on the basis of a little number of criteria and that such criteria can be language and domain independent. the used criteria have been acquired in source corpus (russian) and then tested on source and target (french) corpora. the method shows up to 90% precision and 93% recall, and 85% precision and 74% recall in source and target corpora.
variable selection for optimal decision making. this paper discusses variable selection for medical decision making; in particular decisions regarding which treatment to provide a patient. current variable selection methods were designed for use in prediction applications. these techniques often leave behind small but important interaction variables that are critical when the goal is decision making rather than prediction. this paper presents a new method designed to find variables that aid in decision making and demonstrates the method on data from a clinical trial for treatment of depression.
a human-machine cooperative approach for time series data interpretation. this paper deals with the interpretation of biomedical multivariate time series for extracting typical scenarios. this task is known to be difficult, due to the temporal nature of the data at hand, and to the context-sensitive aspect of data interpretation, which hamper the formulation of a priori knowledge about the kind of patterns to detect and their interrelations. a new way to tackle this problem is proposed, based on a collaborative approach between a human and a machine by means of specific annotations. two grounding principles, namely autonomy and knowledge discovery, support the co-construction of successive abstraction levels for data interpretation. a multi-agent system is proposed to implement effectively these two principles. respiratory time series data (flow, paw) have been explored with our system for patient/ventilator asynchronies characterization studies.
semantic web framework for knowledge-centric clinical decision support systems. lately, there have been considerable efforts to computerize clinical practice guidelines (cpg) so that they can be executed via clinical decision support systems (cdss) at the point of care. we present a semantic web framework to both model and execute the knowledge within a cpg to develop knowledge-centric cdss. our approach entails knowledge modeling through a synergy between multiple ontologies---i.e. a domain ontology, cpg ontology and patient ontology. we develop decision-rules based on the ontologies, and execute them with a proof engine to derive cpg-based patient specific recommendations. we present a prototype of our cpg-based cdss to execute the cpg for follow-up after treatment for breast cancer.
an ontology-driven agent-based clinical guideline execution engine. one of the hardest tasks in any healthcare application is the management of knowledge. organisational information as well as medical concepts should be represented in an appropriate way in order to improve interoperability among existing systems, to allow the implementation of knowledge-based intelligent systems, or to provide high level support to healthcare professionals. this paper proposes the inclusion of an especially designed ontology into an agent-based medical platform called hecase2. the ontology has been constructed as an external resource, allowing agents to coordinate complex activities defined in any clinical guideline.
formalizing 'living guidelines' using lassie: a multi-step information extraction method. living guidelines are documents presenting up-to-date and state-of-the-art knowledge to practitioners. to have guidelines implemented by computer-support they firstly have to be formalized in a computer-interpretable form. due to the complexity of such formats the formalization process is challenging, but burdensome and time-consuming.the lassie methodology supports this task by formalizing guidelines in several steps from the textual form to the guideline representation language asbru using a document-centric approach. lassie uses information extraction technique to semi-automatically accomplish these steps.we apply lassie to support the implementation of living guidelines. based on a living guideline published by the scottish intercollegiate guidelines network (sign) we show that adaptations of previously formalized guidelines can be accomplished easily and fast. by using this new approach only new and changed text parts have to be modeled. furthermore, models can be inherited from previously modeled guideline versions that were added by domain experts.
multi-level clustering in sarcoidosis: a preliminary study. sarcoidosis is a multisystem disorder that is characterized by the formation of granulomas in certain organs of the body. the exact cause of sarcoidosis is unknown but evidence exists that sarcoidosis results from exposure of genetically susceptible hosts to specific environmental agents. the wide degree of clinical heterogeneity might indicate that sarcoidosis is not a single polymorphic disease but a collection of genetically complex diseases. as a first step to identify the hypothesized subcategories, large amounts of multidimensional data are collected that are divided into distinct levels. we investigated how clustering techniques can be applied to support the interpretation of sarcoidosis and subsequently to reveal categories of sarcoidosis data. an attempt is made to relate multiple clusters between the different data levels based on validation criteria.
anonymisation of swedish clinical data. there is a constantly growing demand for exchanging clinical and health-related information electronically. in the era of the electronic health record the release of individual data for research, health care statistics, monitoring of new diagnostic tests and tracking disease outbreak alerts are some of the areas in which the protection of (patient) privacy has become an important concern. in this paper we present a system for automatic anonymisation of swedish clinical free text, in the form of discharge letters, by applying generic named entity recognition technology.
contrast set mining for distinguishing between similar diseases. the task addressed and the method proposed in this paper aim at improved understanding of differences between similar diseases. in particular we address the problem of distinguishing between thrombolic brain stroke and embolic brain stroke as an application of our approach of contrast set mining through subgroup discovery. we describe methodological lessons learned in the analysis of brain ischaemia data and a practical implementation of the approach within an open source data mining toolbox.
multi-resolution image parametrization in stepwise diagnostics of coronary artery disease. coronary artery disease is one of the world's most important causes of early mortality, so any improvements of diagnostic procedures are highly appreciated. in the clinical setting, coronary artery disease diagnostics is typically performed in a sequential manner. the four diagnostic levels consist of evaluation of (1) signs and symptoms of the disease and ecg (electrocardiogram) at rest, (2) ecg testing during a controlled exercise, (3) myocardial perfusion scintigraphy, and (4) finally coronary angiography (which is considered as the "gold standard" reference method). in our study we focus on improving diagnostic performance of the third diagnostic level (myocardial perfusion scintigraphy). this diagnostic level consists of series of medical images that are easily obtained and the imaging procedure represents only a minor threat to patients' health. in clinical practice, these images are manually described (parameterized) and subsequently evaluated by expert physicians. in our paper we present an innovative alternative to manual image evaluation --- an automatic image parametrization on multiple resolutions, based on texture description with specialized association rules, and image evaluation with machine learning methods. our results show that multi-resolution image parameterizations equals the physicians in terms of quality of image parameters. however, by using both manual and automatic image description parameters at the same time, diagnostic performance can be significantly improved with respect to the results of clinical practice.
interacting agents for the risk assessment of allergies in newborn babies. allergic diseases are increasing all over the world. therefore, the risk assessment of allergy in newborns is a key issue for prevention purposes. the risk can be assessed at the birth by combining information about familiarity with results of blood examination. then, the individual must be monitored, particularly in the fist months of life, in order to better define the type of allergy and the risk. the monitoring is carried on by different professionals (agents), therefore the communication and collaboration between these agents must be supported in order to obtain the best treatment strategy for the baby. this paper presents a new project which allows the cooperation between the agents involved in the risk assessment of allergy in newborn babies, and presents the main technologies which will be used to develop it.
novel features for automated lung function diagnosis in spontaneously breathing infants. a comparative analysis of 14 classic and 23 novel mathematical features for diagnosing lung function in infants is presented. the data set comprises tidal breathing flow volume loops of 195 spontaneously breathing infants aged 3 to 24 months, with 9 known breathing problems (diseases). the data set is sparse. diagnostic power was evaluated using support vector machines featuring both polynomial and gaussian kernels in a rigorous experimental setting (100 runs for random splits of data into the training set (90% of data) and test set (10% of data)). novel features achieve lower error rates than the old ones.
a mixed data clustering algorithm to identify population patterns of cancer mortality in hijuelas-chile. the cancer disease in hijuelas-chile represents the 45% of the population deaths in the last decade. this high mortality rate have concerned the sanitary authority that lacks of information to identify the risk groups and the factors that influence in the disease.in this work we propose a clustering algorithm for mixed numerical, categorical and multi-valued attributes. we apply our proposed algorithm to identify and to characterize the common patterns in people who died of cancer in the population of hijuelas between 1994 and 2006. as a consequence of this research, we were able to characterize the people who died of cancer in hijuelas-chile.
a causal modeling framework for generating clinical practice guidelines from data. the practice of medicine is becoming increasingly evidence-based and clinical practice guidelines (cpgs) are necessary for advancing evidence-based medicine (ebm). we hypothesize that machine learning methods can play an important role in learning cpgs automatically from data . automatically induced cpgs can then be used for further manual refinement and deployment, for automated guideline compliance checking, for better understanding of disease processes, and for improved physician education. we discuss why learning cpgs is a special form of computational causal discovery and why simply predictive (i.e., non-causal) methods may not be appropriate for this task.
knowledge-based modeling and simulation of diseases with highly differentiated clinical manifestations. this paper presents the cognitive model of gastroesophageal reflux disease (gerd) developed for the maryland virtual patient simulation and mentoring environment. gerd represents a class of diseases that have a large number of clinical manifestations. our model at once manages that complexity while offering robust automatic function in response to open-ended user actions. this ontologically grounded model is largely based on script-oriented representations of causal chains reflecting the actual physiological processes in virtual patients. a detailed description of the gerd model is presented along with a high-level description of the environment for which it was developed.
a methodology for automated extraction of the optimal pathways from influence diagrams. the influence diagram (id) is a powerful tool for modelling medical decision-making processes, like the optimal application of diagnostic imaging. in this area, where safety and efficacy are determined by a number of aspects varying in nature and importance, it is difficult for humans to relate all available pieces of evidence and consequences of choices. ids are well suited to provide evidence-based diagnostic pathways. however, medical specialists cannot be expected to be familiar with ids and their output can be difficult to interpret. to overcome these shortcomings, a methodology is developed to automatically extract the optimal pathways from an id and represent these in a tree shaped flow diagram. it imposes a few general rules on the structure of the model, which determine the relation between decisions to perform imaging and the availability of test results. extracting the optimal pathways requires post-processing the results of an id, leaving out the sub optimal choices and irrelevant scenarios. predictive value of tests are vital information in medical protocols, they are at hand in the id for each relevant scenario. the methodology is illustrated by the problem of diagnosing acute chest pain. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
a pattern recognition approach to diagnose foot plant pathologies: from segmentation to classification. some foot plant diseases such as flat foot and cave foot are usually diagnosed by a human expert. in this paper we propose an original method to diagnose these diseases by using optical color foot plant images. a number of modern image processing and pattern recognition techniques have been employed to configure a system that can dramatically decrease the time in which such analysis are performed, besides delivering robust and reliable results to complement efficiently the specialist's task. our results demonstrate the feasibility of building such automatic diagnosis systems that can be used as massive first screening methods for detecting foot plant pathologies.
co-operative agents in analysis and interpretation of intracerebral eeg activity: application to epilepsy. the paper presents a distributed approach for the interpretation of epileptic signals based on a dynamical vectorial analysis method. the approach associates signal processing methods into a situated, reactive, cooperative and decentralized implementation. the objective is to identify and locate the various interictal and ictal epileptiform events (pathological and/or normal) contained in intracerebral eeg signals (one hundred recording channels in general) recorded in patients suffering from partial temporal lobe epilepsy. this approach associates some signal processing methods (spectral analysis, causality measurements, detection, classification) in a multi-agent system.
an integrated it system for phenotypic and genotypic data mining and management. this paper describes the application of an information technology infrastructure aimed at supporting translational bioinformatics studies which need the joint management of phenotypic and genotypic data. the system provides an integrated and easy to use software environment, based on data warehouse and data mining tools, to discover the most frequent complex phenotypes and search their penetrance and heritability by mapping them on the population pedigree. we first use a logical formalization to define phenotypes of interest in order to retrieve individuals having that phenotype from the electronic medical record. we then use an open-source web-based data warehouse application for analyzing phenotypic data and presenting the results in a multidimensional format. relationships between the selected individuals are automatically visualized by integrating in the system an ad-hoc developed pedigree visualization tool. finally, the application of the system to support a genetic study of an isolated population, the val borbera project, is presented.
using semantic web technologies for knowledge-driven querying of biomedical data. software applications that work with biomedical data have significant knowledge-management requirements. formal knowledge models and knowledge-based methods can be very useful in meeting these requirements. however, most biomedical data are stored in relational databases, a practice that will continue for the foreseeable future. using these data in knowledge-driven applications requires approaches that can form a bridge between relational models and knowledge models. accomplishing this task efficiently is a research challenge. to address this problem, we have developed an end-to-end knowledge-based system based on semantic web technologies. it permits formal design-time specification of the data requirements of a system and uses those requirements to drive knowledge-driven queries on operational relational data in a deployed system. we have implemented a dynamic owl-to-relational mapping method and used swrl, the semantic web rule language, as a high-level query language that uses these mappings. we have used these methods to support the development of a participant tracking application for clinical trials and in the development of a test bed for evaluating biosurveillance methods.
computerised guidelines implementation: obtaining feedback for revision of guidelines, clinical data model and data flow. in this paper we describe a module that allows to collect (a) motivations for non-compliance to guidelines, (b) motivations for poor data entry into the electronic patient record, and (c) comments on medical aspects of guideline recommendations, on their formalisation into computerised rules, and on the guideline integration into the computerised clinical chart. we organised a well-structured taxonomy of non-compliance motivations in such a way that the main hierarchical levels correspond to different medical or technical roles suitable for feedback managing. we analysed about 400 consecutive cases of patients with ischemic stroke. about 40 non-compliances, as well as several incomplete data forms have been identified and motivated.
analyzing differences in operational disease definitions using ontological modeling. in medicine, there are many diseases which cannot be precisely characterized but are considered as natural kinds. in the communication between health care professionals, this is generally not problematic. in biomedical research, however, crisp definitions are required to unambiguously distinguish patients with and without the disease. in practice, this results in different operational definitions being in use for a single disease. this paper presents an approach to compare different operational definitions of a single disease using ontological modeling. the approach is illustrated with a case-study in the area of severe sepsis.
learning decision tree for selecting qrs detectors for cardiac monitoring. the qrs complex is the main wave of the ecg. it is widely used for diagnosing many cardiac diseases. automatic qrs detection is an essential task of cardiac monitoring and many detection algorithms have been proposed in the literature. although most of the algorithms perform satisfactorily in normal situations, there are contexts, in the presence of noise or a specific pathology, where one algorithm performs better than the others. we propose a combination method that selects, on line, the detector that is the most adapted to the current context. the selection is done by a decision tree that has been learnt from the performance measures of 7 algorithms in various instances of 130 combinations of arrhythmias and noises. the decision tree is compared to expert rules tested in the framework of the cardiac monitoring system ip-calicot.
automatic generation of textual summaries from neonatal intensive care data. intensive care is becoming increasingly complex. if mistakes are to be avoided, there is a need for the large amount of clinical data to be presented effectively to the medical staff. although the most common approach is to present the data graphically, it has been shown that textual summarisation can lead to improved decision making. as the first step in the babytalk project, a prototype is being developed which will generate a textual summary of 45 minutes of continuous physiological signals and discrete events (e.g.: equipment settings and drug administration). its architecture brings together techniques from the different areas of signal analysis, medical reasoning, and natural language generation. although the current system is still being improved, it is powerful enough to generate meaningful texts containing the most relevant information. this prototype will be extended to summarize several hours of data and to include clinical interpretation.
a nearest neighbor approach to predicting survival time with an application in chronic respiratory disease. the care for patients with chronic and progressive diseases often requires that reliable estimates of their remaining lifetime are made. the predominant method for obtaining such individual prognoses is to analyze historical data using cox regression, and apply the resulting model to data from new patients. however, the black-box nature of the cox regression model makes it unattractive for clinical practice. instead most physicians prefer to relate a new patient to the histories of similar, individual patients that were treated before. this paper presents a prognostic inference method that combines the k-nearest neighbor paradigm with cox regression. it yields survival predictions for individual patients, based on small sets of similar patients from the past, and can be used to implement a prognostic case-retrieval system. to evaluate the method, it was applied to data from patients with idiopathic interstitial pneumonia, a progressive and lethal lung disease. experiments pointed out that the method competes well with cox regression. the best predictive performance was obtained with a neighborhood size of 20.
monitoring human resources of a public health-care system through intelligent data analysis and visualization. a public health-care system (hcs) is a complex system that requires permanent monitoring. this paper focuses on the slovenian national hcs sub-system consisting of a network of health-care professionals at the primary care level. the challenge addressed in this paper is the development and application of intelligent data analysis, decision support and visualization methods aimed to improve the monitoring of human resources of this network. the main outcome is a set of proposed performance indicators and the developed model for monitoring the network of primary health-care professionals of slovenia. the model enables improved planning and management through data analysis and visualization modules developed for the monitoring of physicians' qualification, age, workload and dispersion.
mrf agent based segmentation: application to mri brain scans. the markov random field (mrf) probabilistic framework is classically introduced for a robust segmentation of magnetic resonance imaging (mri) brain scans. most mrf approaches handle tissues segmentation via global model estimation. structure segmentation is then carried out as a separate task. we propose in this paper to consider mrf segmentation of tissues and structures as two local and cooperative procedures immersed in a multiagent framework. tissue segmentation is performed by partitionning the volume in subvolumes where agents estimate local mrf models in cooperation with their neighbours to ensure consistency of local models. these models better reflect local intensity distributions. structure segmentation is performed via dynamically localized agents that integrate anatomical spatial constraints provided by an apriori fuzzy description of brain anatomy. structure segmentation is not reduced to a postprocessing step: rather, structure agents cooperate with tissue agents to render models gradually more accurate. we report several experiments that illustrate the working of our multiagent framework. the evaluation was performed using both phantoms and real 3t brain scans and showed a robustness to nonuniformity and noise together with a low computational time. this mrf agent based approach appears as a very promising new tool for complex image segmentation.
on the behaviour of information measures for test selection. in diagnostic decision-support systems, a test-selection facility serves to select tests that are expected to yield the largest decrease in the uncertainty about a patient's diagnosis. for capturing diagnostic uncertainty, often an information measure is used. in this paper, we study the shannon entropy, the gini index, and the misclassification error for this purpose. we argue that for a large range of values, the first derivative of the gini index can be regarded as an approximation of the first derivative of the shannon entropy. we also argue that the differences between the derivative functions outside this range can explain different test sequences in practice. we further argue that the misclassification error is less suited for test-selection purposes as it is likely to show a tendency to select tests arbitrarily. experimental results from using the measures with a real-life probabilistic network in oncology support our observations.
enhancing automated test selection in probabilistic networks. most test-selection algorithms currently in use with probabilistic networks select variables myopically, that is, test variables are selected sequentially, on a one-by-one basis, based upon expected information gain. while myopic test selection is not realistic for many medical applications, non-myopic test selection, in which information gain would be computed for all combinations of variables, would be too demanding. we present three new test-selection algorithms for probabilistic networks, which all employ knowledge-based clusterings of variables; these are a myopic algorithm, a non-myopic algorithm and a semi-myopic algorithm. in a preliminary evaluation study, the semi-myopic algorithm proved to generate a satisfactory test strategy, with little computational burden.
computer-aided assessment of drug-induced lung disease plausibility. drug-induced lung disease (dild), often suspected in pneumology, is still a diagnostic challenge because of the ever increasing number of pneumotoxic drugs and the large diversity of observed clinical patterns. as a result, dild can only be evoked as a plausible diagnosis after the exclusion of all other possible causes. pneumodoc is a computer-based decision support that formalises the evaluation process of the drug-imputability of a lung disease. the knowledge base has been structured as a two-level decision tree. patient-specific chronological and semiological criteria are first examined leading to the assessment of a qualitative intrinsic dild plausibility score. then literature-based data including the frequency of dild with a given drug and the frequency of the observed clinical situation among the clinical patterns reported with the same drug are evaluated to compute a qualitative extrinsic dild plausibility score. based on a simple multimodal qualitative model, extrinsic and intrinsic scores are combined to yield an overall dild plausibility score.
maintaining formal models of living guidelines efficiently. translating clinical guidelines into formal models is beneficial in many ways, but expensive. the progress in medical knowledge requires clinical guidelines to be updated at relatively short intervals, leading to the term living guideline. this causes potentially expensive, frequent updates of the corresponding formal models.when performing these updates, there are two goals: the modelling effort must be minimised and the links between the original document and the formal model must be maintained. in this paper, we describe our solution, using tools and techniques developed during the protocure ii project.
categorical representation of evolving structure of an ontology for clinical fungus. with increasing popularity of using ontologies, many industrial and clinical applications have employed ontologies as their conceptual backbone. ontologies try to capture knowledge from a domain of interest and when the knowledge changes, the definitions will be altered. we study change management in the fungalweb ontology, which is the result of integrating numerous biological databases and web accessible textual resources. the fungal taxonomy is currently unstable and evolves over time. this evolution can be seen in both nomenclature and the taxonomic structure. in an experiment we have focused on changes in medical species of fungus which can potentially alter the related disease name and description in an integrated clinical system. in order to address certain aspects of representation of changes in an ontology driven clinical application we propose a methodology based on category theory as a mathematical notation, which is independent of a specific choice of ontology language and any particular implementation.
classifying alarms in intensive care - analogy to hypothesis testing. monitoring devices in intensive care units observe a patient's health status and trigger an alarm in critical situations. the alarm rules in commercially available monitoring systems are usually based on simple thresholds set by the clinical staff. though there are some more advanced alarm rules integrated in modern monitoring devices, even for those, the false alarm rate is very high. decision trees have proven suitable for alarm classification and false alarm reduction. random forests which are ensembles of trees can improve the accuracy compared to single trees in many situations. in intensive care, the probability of misclassifying a situation in which an alarm is needed has to be controlled. subject to this constraint the probability of misclassifying a situation in which no alarm should be given has to be minimized - an analogy to a hypothesis test for testing "situation is alarm relevant" vs. "situation is non alarm relevant" based on an ensemble of trees. this yields a classification rule for any given significance level, which is the probability of misclassifying alarm relevant situations. we apply this procedure to annotated physiological data recorded at an intensive care unit and generate rules for false alarm reduction.
an intelligent aide for interpreting a patient's dialysis data set. many machines used in the modern hospital settings offer real time physiological monitoring. haemodialysis machines combine a therapeutic treatment system integrated with sophisticated monitoring equipment. a large array of parameters can be collected including cardiovascular measures such as heart rate and blood pressure together with treatment related data including relative blood volume, ultrafiltration rate and small molecule clearance. a small subset of this information is used by clinicians to monitor treatment and plan therapeutic strategies but it is not usually analysed in any detail. the focus of this paper is the analysis of data collected over a number of treatment sessions with a view to predicting patient physiological behaviour whilst on dialysis and correlating this with clinical characteristics of individual patients.one of the commonest complications experienced by patients on dialysis is symptomatic hypotension. we have taken real time treatment data and outline a program of work which attempts to predict when hypotension is likely to occur, and which patients might be particularly prone to haemodynamic instability. this initial study has investigated: the rate of change of blood pressure versus rate of change of heart rate, rate of fluid removal, and rate of uraemic toxin clearance. we have used a variety of machine learning techniques (including hierarchical clustering, and bayesian network analysis algorithms). we have been able to detect from this dataset, 3 distinct groups which appear to be clinically meaningful. furthermore we have investigated whether it is possible to predict changes in blood pressure in terms of other parameters with some encouraging results that merit further study.
knowledge acquisition from a medical corpus: use and return on experiences. the present work aims at refining and expanding user's queries thanks to association rules. we adapted the a-close algorithm to a medical corpus indexed by mesh descriptors. the originality of our approach lies in the use of the association rules in the information retrieval process and the exploitation of the structure of the domain knowledge to evaluate the association rules. the results show the usefulness of this query expansion approach. based on observations, new knowledge is modelled as expert rules.
building an ontology of hypertension management. the analysis of customized decisions during hypertension management in a specialized unit requires a detailed representation of clinical cases. we are building a specific ontology to code medical records and process them with computerized tools. relevant concepts to describe and justify medical decisions are extracted from three sources: (i) clinical guidelines; (ii) items of the semi-structured medical record form used in the clinical unit; (iii) free-text answers from 5,000 completed record forms. combining terminological sources is mandatory to cover the whole spectrum of possible justifications for clinical decisions, including contextual specificities and patients' particulars.
replacing sep-triplets in snomed ct using tractable description logic operators. reification of parthood relations according to the sep-triplet encoding pattern has been employed in the clinical terminology snomed ct to simulate transitivity of the part-of relation via transitivity of the is-a relation and to inherit properties along part-of links. in this paper we argue that using a more expressive representation language, which allows for a direct representation of the relevant properties of the part-of relation, makes modelling less error prone while having no adverse effect on the efficiency of reasoning.
discovery and integration of organ-failure episodes in mortality prediction. current predictive models in the intensive care rely on summaries of data collected at patient admission. it has been shown recently that temporal patterns of the daily sequential organ failure assessment (sofa) scores can improve predictions. however, the derangement of the six individual organ systems underlying the calculation of a sofa score were not taken into account, thus impeding the understanding of their prognostic merits. in this paper we propose a method for model induction that integrates in a novel way the individual organ failure scores with sofa scores. the integration of these two correlated components is achieved by summarizing the historic sofa information and at the same time by capturing the evolution of individual organ system failure status. the method also explicitly avoids the collinearity problem among organ failure episodes. we report on the application of our method to a large dataset and demonstrate its added value. the ubiquity of severity scores and sub-scores in medicine renders our approach relevant to a wide range of medical domains.
interpreting gene expression data by searching for enriched gene sets. this paper presents a novel method integrating gene-gene interaction information and gene ontology (go) for the construction of new gene sets that are potentially enriched. enrichment of a gene set is determined by gene set enrichment analysis. the experimental results show that the introduced method improves over existing methods, i.e. that it is capable to find new descriptions of the biology governing the experiments, not detectable by the traditional methods of evaluating the enrichment of predefined gene sets, defined by a single go term.
document-oriented views of guideline knowledge bases. a computer-interpretable guideline knowledge base can be a very large network whose information content is difficult for developers and clinicians to comprehend and review. we created a method to annotate a guideline model and use the annotations to export the guideline knowledge base in an xml format that can be transformed into a readable document. we applied this method to knowledge bases developed in three different guideline modeling projects to analyze uses and limitations of this approach. we demonstrate the promise of creating such document-oriented views, but conclude that guideline models and knowledge bases should be constructed with the goal of creating such human-comprehensible views from the beginning.
literature mining: towards better understanding of autism. in this article we present a literature mining method rajolink that upgrades swanson's abc model approach to uncovering hidden relations from a set of articles in a given domain. when these relations are interesting from medical point of view and can be verified by medical experts, they represent new pieces of knowledge and can contribute to better understanding of diseases. in our study we analyzed biomedical literature about autism, which is a very complex and not yet sufficiently understood domain. on the basis of word frequency statistics several rare terms were identified with the aim of generating potentially new explanations for the impairments that are observed in the affected population. calcineurin was discovered as a joint term in the intersection of their corresponding literature. similarly, nf-kappab was recognized as a joint term. pairs of documents that point to potential relations between the identified joint terms and autism were also automatically detected. expert evaluation confirmed the relevance of these relations.
hierarchical latent class models and statistical foundation for traditional chinese medicine. the theories of traditional chinese medicine (tcm) originated from experiences doctors had with patients in ancient times. we ask the question whether aspects of tcm theories can be reconstructed through modern day data analysis. we have recently analyzed a tcm data set using a machine learning method and found that the resulting statistical model matches the relevant tcm theory well. this is an exciting discovery because it shows that, contrary to common perception, there are scientific truths in tcm theories. it also suggests the possibility of laying a statistical foundation for tcm through data analysis and thereby turning it into a modern science.
r-cast-med: applying intelligent agents to support emergency medical decision-making teams. decision-making is a crucial aspect of emergency response during mass casualty incidents (mcis). mcis require rapid decisions to be taken by geographically-dispersed teams in an environment characterized by insufficient information, ineffective collaboration and inadequate resources. despite the increasing adoption of decision support systems in healthcare, there is limited evidence of their value in large-scale disasters. we conducted focus groups with emergency medical services and emergency department personnel who revealed that one of the main challenges in emergency response during mcis is information management. therefore, to alleviate the issues arising from ineffective information management, we propose r-cast-med, an intelligent agent architecture built on recognition-primed decision-making (rpd) and shared mental models (smms). a simulation of r-cast-med showed that this tool enabled efficient information management by identifying relevant information, inferring missing information and sharing information with other agents, which led to effective collaboration and coordination of tasks across teams.
an ultra low-power processor for sensor networks. we present a novel processor architecture designed specifically for use in low-power wireless sensor-network nodes. our sensor network asynchronous processor (snap/le) is based on an asynchronous data-driven 16-bit risc core with an extremely low-power idle state, and a wakeup response latency on the order of tens of nanoseconds. the processor instruction set is optimized for sensor-network applications, with support for event scheduling, pseudo-random number generation, bitfield operations, and radio/sensor interfaces. snap/le has a hardware event queue and event coprocessors, which allow the processor to avoid the overhead of operating system software (such as task schedulers and external interrupt servicing), while still providing a straightforward programming interface to the designer. the processor can meet performance levels required for data monitoring applications while executing instructions with tens of picojoules of energy.we evaluate the energy consumption of snap/le with several applications representative of the workload found in data-gathering wireless sensor networks. we compare our architecture and software against existing platforms for sensor networks, quantifying both the software and hardware benefits of our approach.
active disks: programming model, algorithms and evaluation. several application and technology trends indicate that it might be both profitable and feasible to move computation closer to the data that it processes. in this paper, we evaluate active disk architectures which integrate significant processing power and memory into a disk drive and allow application-specific code to be downloaded and executed on the data that is being read from (written to) disk. the key idea is to offload bulk of the processing to the diskresident processors and to use the host processor primarily for coordination, scheduling and combination of results from individual disks. to program active disks, we propose a stream-based programming model which allows disklets to be executed efficiently and safely. simulation results for a suite of six algorithms from three application domains (commercial data warehouses, image processing and satellite data processing) indicate that for these algorithms, active disks outperform conventional-disk architectures.
dcg: an efficient, retargetable dynamic code generation system. dynamic code generation allows aggressive optimization through the use of runtime information. previous systems typically relied on ad hoc code generators that were not designed for retargetability, and did not shield the client from machine-specific details. we present a system, dcg, that allows clients to specify dynamically generated code in a machine-independent manner. our one-pass code generator is easily retargeted and extremely efficient (code generation costs approximately 350 instructions per generated instruction). experiments show that dynamic code generation increases some application speeds by over an order of magnitude.
softflash: analyzing the performance of clustered distributed virtual shared memory. one potentially attractive way to build large-scale shared-memory machines is to use small-scale to medium-scale shared-memory machines as clusters that are interconnected with an off-the-shelf network. to create a shared-memory programming environment across the clusters, it is possible to use a virtual shared-memory software layer. because of the low latency and high bandwidth of the interconnect available within each cluster, there are clear advantages in making the clusters as large as possible. the critical question then becomes whether the latency and bandwidth of the top-level network and the software system are sufficient to support the communication demands generated by the clusters.to explore these questions, we have built an aggressive kernel implementation of a virtual shared-memory system using sgi multiprocessors and 100mbyte/sec hippi interconnects. the system obtains speedups on 32 processors (four nodes, eight processors per node plus additional reserved protocol processors) that range from 6.9 on the communication-intensive fft program to 21.6 on ocean (both from the splash 2 suite). in general, clustering is effective in reducing internode miss rates, but as the cluster size increases, increases in the remote latency, mostly due to increased tlb synchronization cost, offset the advantages. for communication-intensive applications, such as fft, the overhead of sending out network requests, the limited network bandwidth, and the long network latency prevent the achievement of good performance. overall, this approach still appears promising, but our results indicate that large low latency networks may be needed to make cluster-based virtual shared-memory machines broadly useful as large-scale shared-memory multiprocessors.
a multi-microprocessor architecture with hardware support for communication and scheduling. we describe a multiprocessor system that attempts to enhance the system performance by incorporating into its architecture a number of key operating system concepts. in particular: &mdash; the scheduling and synchronization of concurrent activities are built in at the hardware level, &mdash; the interprocess communication functions are performed in hardware, and, &mdash; a coupling between the scheduling and communication functions is provided which allows efficient implementation of parallel systems that is precluded when the scheduling and communication functions are realized in software.
high speed switch scheduling for local area networks. current technology trends make it possible to build communication networks that can support high-performance distributed computing. this paper describes issues in the design of a prototype switch for an arbitrary topology point-to-point network with link speeds of up to 1 gbit/s. the switch deals in fixed-length atm-style cells, which it can process at a rate of 37 million cells per second. it provides high bandwidth and low latency for datagram traffic. in addition, it supports real-time traffic by providing bandwidth reservations with guaranteed latency bounds. the key to the switch's operation is a technique called parallel iterative matching, which can quickly identify a set of conflict-free cells for transmission in a time slot. bandwidth reservations are accommodated in the switch by building a fixed schedule for transporting cells from reserved flows across the switch; parallel iterative matching can fill unused slots with datagram traffic. finally, we note that parallel iterative matching may not allocate bandwidth fairly among flows of datagram traffic. we describe a technique called statistical matching, which can be used to ensure fairness at the switch and to support applications with rapidly changing needs for guaranteed bandwidth.
thread level parallelism and interactive performance of desktop applications. multiprocessing is already prevalent in servers where multiple clients present an obvious source of thread-level parallelism. however, the case for multiprocessing is less clear for desktop applications. nevertheless, architects are designing processors that count on the availability of thread-level parallelism. unlike server workloads, the primary requirement of interactive applications is to respond to user events under human perception bounds rather than to maximize end-to-end throughput. in this paper we report on the thread-level parallelism and interactive response time of a variety of desktop applications. by tracking the communication between tasks, we can focus our measurements on the portions of the benchmark's execution that have the greatest impact on the user. we find that running our benchmarks on a dual-processor machine improves response time of mouse-click events by as much as 36%, and 22% on average---out of a maximum possible 50%. the benefits of multiprocessing are even more apparent when background tasks are considered. in our experiments, running a simple mp3 playback program in the background increases response time by 14% on a uniprocessor while it only increases the response time on a dual processor by 4%. when response times are fast enough for further improvements to be imperceptible, the increased idle time after interactive episodes could be exploited to build systems that are more power efficient.
adapting to network and client variability via on-demand dynamic distillation. the explosive growth of the internet and the proliferation of smart cellular phones and handheld wireless devices is widening an already large gap between internet clients. clients vary in their hardware resources, software sophistication, and quality of connectivity, yet server support for client variation ranges from relatively poor to none at all. in this paper we introduce some design principles that we believe are fundamental to providing "meaningful" internet access for the entire range of clients. in particular, we show how to perform on-demand datatype-specific lossy compression on semantically typed data, tailoring content to the specific constraints of the client. we instantiate our design principles in a proxy architecture that further exploits typed data to enable application-level management of scarce network resources. our proxy architecture generalizes previous work addressing all three aspects of client variation by applying well-understood techniques in a novel way, resulting in quantitatively better end-to-end performance, higher quality display output, and new capabilities for low-end clients.
efficient debugging primitives for multiprocessors. existing kernel-level debugging primitives are inappropriate for instrumenting complex sequential or parallel programs. these functions incur a heavy overhead in their use of system calls and process switches. context switches are used to alternately invoke the debugger and the target programs. system calls are used to communicate data between the target and debugger. none of this is necessary in shared-memory multiprocessors. multiple processors concurrently run both the debugger and the target. shared-memory is used to implement efficient communication. the target's state is accessed by running both the target and the debugger in the same address space. finally, instrumentation points, which have largely been implemented as traps to the system, are reimplemented as simple branches to routines of arbitrary complexity maintained by the debugger. not only are primitives such as conditional breakpoints thus generalized, but their efficiency is improved by several orders of magnitude. in the process, much of the traditional system's kernel support for debugging is reimplemented at user-level. this paper describes the implementation of debugging primitives in parasight, a parallel programming environment. parasight has been used to implement conditional breakpoints, an important primitive for both high-level and parallel debugging. preliminary measurements indicate that parasight breakpoints are 1000 times faster than the breakpoints in parallel &ldquo;cdb&rdquo;, a conventional unix debugger. light-weight conditional breakpoints open up new opportunities for debugging and profiling both parallel and sequential programs.
value speculation scheduling for high performance processors. recent research in value prediction shows a surprising amount of predictability for the values produced by register-writing instructions. several hardware based value predictor designs have been proposed to exploit this predictability by eliminating flow dependencies for highly predictable values. this paper proposed a hardware and software based scheme for value speculation scheduling (vss). static vliw scheduling techniques are used to speculate value dependent instructions by scheduling them above the instructions whose results they are dependent on. prediction hardware is used to provide value predictions for allowing the execution of speculated instructions to continue. in the case of miss-predicted values, control flow is redirected to patch-up code so that execution can proceed with the correct results. in this paper, experiments in vss for load operations in the specint95 benchmarks are performed. speedup of up to 17% has been shown for using vss. empirical results on the value predictability of loads, based on value profiling data, are also provided.
a technique for monitoring run-time dynamics of an operating system and a microprocessor executing user applications. in this paper, we present a non-invasive and efficient technique for simulating applications complete with their operating system interaction. the technique involves booting and initiating an application on a hardware development system, capturing the entire state of the application and the microprocessor at a well defined point in execution and then simulating the application on microprocessor simulators. extensive statistics generated from the simulators on run-time dynamics of the application, the operating system as well as the microprocessor enabled us to tune the operating system and the microprocessor architecture and implementation. the results also enabled us to optimize system level design choices by anticipating/predicting the performance of the target system. lastly, the results were used to adjust and refocus the evolution of the architecture of both the operating system and the microprocessor.
an experiment to improve operand addressing. mcode is a high-level language, stack machine designed to support strongly-typed, pascal-based languages with a variety of data types in a modular programming environment. the instruction set, constructed for efficiency and extensibility, is based on an analysis of 120,000 lines of pascal programs. the design was compared for efficiency with the instruction sets of the digital equipment pdp-11 and vax by examining the generated code from the same compiler for all three machines. in addition, the original design choices were tested by analyzing the generated code from 19,000 lines of starmod programs. as a result of this iterative experiment, we have summarized our observations in an efficient reorganization of the vax's addressing modes.
an out-of-order execution technique for runtime binary translators. a dynamic translator emulates an instruction set architccturc by translating source instructions to native code during execution. on statically-scheduled hardware, higher performance can potentially be achieved by reordering the translated instructions; however, this is a challenging transformation if the source architecture supports precise exception semantics, and the user-level program is allowed to register exception handlers. this paper presents a software technique which allows a translator to achieve the out-of-order execution of user-level programs, while preserving all sequential semantics. the design combines a translator, an interpreter, and a set of operating system services. using the proposed techniques, a dynamic translator can optimistically reorder instructions and speculate them across branch boundaries. if a mispeculated operation causes an exception, the recovery algorithm reverts the application state to a safe point, then retranslates the faulty code without reordering to disable further exceptions.
compiler chip: a hardware implementation of compiler. in this paper we discuss about another approch: compiler chip, which is a vlsi implementation of a compiler. constructing a compiler by a few vlsi chip, the computer manufacturer can deliver compilers by sets of vlsi chips, and these chips are installed in a intelligent terminal in order to remove the compilation from the tasks which are processed in the mainframe.
cool-mem: combining statically speculative memory accessing with selective address translation for energy efficiency. this paper presents cool-mem, a family of memory system architectures that integrate conventional memory system mechanisms, energy-aware address translation, and compiler-enabled cache disambiguation techniques, to reduce energy consumption in general purpose architectures. it combines statically speculative cache access modes, a dynamic cam based tag-cache used as backup for statically mispredicted accesses, various conventional multi-level associative cache organizations, embedded protection checking along all cache access mechanisms, as well as architectural organizations to reduce the power consumed by address translation in virtual memory. because it is based on speculative static information, the approach removes the burden of provable correctness in compiler analysis passes that extract static information. this makes cool-mem applicable for large and complex applications, without having any limitations due to complexity issues in the compiler passes or the presence of precompiled static libraries. based on extensive evaluation, for both spec2000 and mediabench applications, 12% to 20% total energy savings are obtained in the processor, with performance ranging from 1.2% degradation to 8% improvement, for the applications studied.
dynamic memory disambiguation using the memory conflict buffer. to exploit instruction level parallelism, compilers for vliw and superscalar processors often employ static code scheduling. however, the available code reordering may be severely restricted due to ambiguous dependences between memory instructions. this paper introduces a simple hardware mechanism, referred to as the memory conflict buffer, which facilitates static code scheduling in the presence of memory store/load dependences. correct program execution is ensured by the memory conflict buffer and repair code provided by the compiler. with this addition, significant speedup over an aggressive code scheduling model can be achieved for both non-numerical and numerical programs.
the dragon processor. the xerox parc dragon is a vlsi research computer that uses several techniques to achieve dense code and fast procedure calls in a system that can support multiple processors on a central high bandwidth memory bus.
an experimental coprocessor for implementing persistant objects on an ibm 4381. in this paper we describe an experimental coprocessor for an ibm 4381 that is designed to facilitate the exploration of persistent objects.
architecture and design of alphaserver gs320. this paper describes the architecture and implementation of the alphaserver gs320, a cache-coherent non-uniform memory access multiprocessor developed at compaq. the alphaserver gs320 architecture is specifically targeted at medium-scale multiprocessing with 32 to 64 processors. each node in the design consists of four alpha 21264 processors, up to 32gb of coherent memory, and an aggressive io subsystem. the current implementation supports up to 8 such nodes for a total of 32 processors. while snoopy-based designs have been stretched to medium-scale multiprocessors by some vendors, providing sufficient snoop bandwidth remains a major challenge especially in systems with aggressive processors. at the same time, directory protocols targeted at larger scale designs lead to a number of inherent inefficiencies relative to snoopy designs. a key goal of the alphaserver gs320 architecture has been to achieve the best-of-both-worlds, partly by exploiting the bounded scale of the target systems.this paper focuses on the unique design features used in the alphaserver gs320 to efficiently implement coherence and consistency. the guiding principle for our directory-based protocol is to address correctness issues related to rare protocol races without burdening the common transaction flows. our protocol exhibits lower occupancy and lower message counts compared to previous designs, and provides more efficient handling of 3-hop transactions. furthermore, our design naturally lends itself to elegant solutions for deadlock, livelock, starvation, and fairness. the alphaserver gs320 architecture also incorporates a couple of innovative techniques that extend previous approaches for efficiently implementing memory consistency models. these techniques allow us to generate commit events (which are used for ordering purposes) well in advance of formulating the reply to a transaction. furthermore, the separation of the commit event allows time-critical replies to bypass inbound requests without violating ordering properties. even though our design specifically targets medium-scale servers, many of the same techniques can be applied to larger-scale directory-based and smaller-scale snoopy-based designs. finally, we evaluate the performance impact of some of the above optimizations and present a few competitive benchmark results.
vlsi assist for a multiprocessor. multiprocessors have long been of interest to computer community. they provide the potential for accelerating applications through parallelism and increased throughput for large multi-user system. three factors have limited the commercial success of multiprocessor systems; entry cost, range of performance, and ease of application. advances in very large scale integration (vlsi) and in computer aided design (cad) have removed these limitations, making possible a new class of multiprocessor systems based on vlsi components. a set of requirements for building an efficient shared multiprocessor system are discussed, including: low-level mutual exclusion, interrupt distribution, inter-processor signaling, process dispatching, caching, and system configuration. a system that meets these requirements is described and evaluated.
precise miss analysis for program transformations with caches of arbitrary associativity. analyzing and optimizing program memory performance is a pressing problem in high-performance computer architectures. currently, software solutions addressing the processor-memory performance gap include compiler-or programmer-applied optimizations like data structure padding, matrix blocking, and other program transformations. compiler optimization can be effective, but the lack of precise analysis and optimization frameworks makes it impossible to confidently make optimal, rather than heuristic-based, program transformations. imprecision is most problematic in situations where hard-to-predict cache conflicts foil heuristic approaches. furthermore, the lack of a general framework for compiler memory performance analysis makes it impossible to understand the combined effects of several program transformations.the cache miss equation (cme) framework discussed in this paper addresses these issues. we express memory reference and cache conflict behavior in terms of sets of equations. the mathematical precision of cmes allows us to find true optimal solutions for transformations like blocking or padding. the generality of cmes also allows us to reason about interactions between transformations applied in concert. unlike our prior work, this framework applies to caches of arbitrary associativity. this paper also demonstrates the utility of cmes by presenting precise algorithms for intra-variable padding, inter-variable padding, and selecting tile sizes. our experiences with cmes implemented in the suif system show that they are a unifying mathematical framework offering the generality and precision imperative for compiler optimizations on current high-performance architectures.
the operating system and language support features of the bellmac-32 microprocessor. the bellmac-32 microprocessor is a 32-bit microprocessor, implemented with cmos technology, designed to support operating system functions and high level languages efficiently. the architecture was designed with the following objectives in mind: &bull; high performance. &bull; enhanced operating system support capabilities. &bull; high level language support. &bull; high reliability, availability and maintainability.
hoard: a scalable memory allocator for multithreaded applications. parallel, multithreaded programs such as web servers, database managers, news servers, and scientific applications are becoming increasingly prevalent. for these c and c++ applications, the memory allocator is often a bottleneck that severely limits program performance and scalability on multiprocessor systems. previous allocators suffer from problems that include poor performance and scalability, and heap organizations that introduce false sharing. worse, many allocators exhibit a "blowup" in memory consumption when confronted with a producer-consumer pattern of object allocation and freeing. this blowup can increase memory consumption by a factor of p (the number of processors) or lead to unbounded memory consumption. such pathological behavior can cause premature program termination by exhausting all available swap space. this paper introduces hoard, a fast, highly scalable allocator that avoids false sharing and blowup. hoard is the first allocator to simultaneously solve the above problems. hoard combines one global heap and p per-processor heaps with a novel discipline that provably bounds blowup and has near zero synchronization costs in the common case. our results on eleven programs demonstrate that hoard yields low average fragmentation and improves overall program performance over the standard solaris allocator by up to a factor of 60 on 14 processors, and up to a factor of 18 over the next best allocator we tested.
a cost-effective, high-bandwidth storage architecture. this paper describes the network-attached secure disk (nasd) storage architecture, prototype implementations oj nasd drives, array management for our architecture, and three, filesystems built on our prototype. nasd provides scalable storage bandwidth without the cost of servers used primarily, for transferring data from peripheral networks (e.g. scsi) to client networks (e.g. ethernet). increasing datuset sizes, new attachment technologies, the convergence of peripheral and interprocessor switched networks, and the increased availability of on-drive transistors motivate and enable this new architecture. nasd is based on four main principles: direct transfer to clients, secure interfaces via cryptographic support, asynchronous non-critical-path oversight, and variably-sized data objects. measurements of our prototype system show that these services can be cost-effectively integrated into a next generation disk drive ask. end-to-end measurements of our prototype drive andfilesysterns suggest that nasd cun support conventional distributed filesystems without performance degradation. more importantly, we show scaluble bandwidth for nasd-specialized filesystems. using a parallel data mining application, nasd drives deliver u linear scaling of 6.2 mb/s per clientdrive pair, tested with up to eight pairs in our lab.
avoiding conflict misses dynamically in large direct-mapped caches. this paper describes a method for improving the performance of a large direct-mapped cache by reducing the number of conflict misses. our solution consists of two components: an inexpensive hardware device called a cache miss lookaside (cml) buffer that detects conflicts by recording and summarizing a history of cache misses, and a software policy within the operating system's virtual memory system that removes conflicts by dynamically remapping pages whenever large numbers of conflict misses are detected. using trace-driven simulation of applications and the operating system, we show that a cml buffer enables a large direct-mapped cache to perform nearly as well as a two-way set associative cache of equivalent size and speed, although with lower hardware cost and complexity.
heat-and-run: leveraging smt and cmp to manage power density through the operating system. power density in high-performance processors continues to increase with technology generations as scaling of current, clock speed, and device density outpaces the downscaling of supply voltage and thermal ability of packages to dissipate heat. power density is characterized by localized chip hot spots that can reach critical temperatures and cause failure. previous architectural approaches to power density have used global clock gating, fetch toggling, dynamic frequency scaling, or resource duplication to either prevent heating or relieve overheated resources in a superscalar processor. previous approaches also evaluate design technologies where power density is not a major problem and most applications do not overheat the processor. future processors, however, are likely to be chip multiprocessors (cmps) with simultaneously-multithreaded (smt) cores. smt cmps pose unique challenges and opportunities for power density. smt and cmp increase throughput and thus on-chip heat, but also provide natural granularities for managing power-density. this paper is the first work to leverage smt and cmp to address power density. we propose heat-and-run smt thread assignment to increase processor-resource utilization before cooling becomes necessary by co-scheduling threads that use complimentary resources. we propose heat-and-run cmp thread migration to migrate threads away from overheated cores and assign them to free smt contexts on alternate cores, leveraging availability of smt contexts on alternate cmp cores to maintain throughput while allowing overheated cores to cool. we show that our proposal has an average of 9% and up to 34% higher throughput than a previous superscalar technique running the same number of threads.
fast mutual exclusion for uniprocessors. in this paper we describe restartable atomic sequences, an optimistic mechanism for implementing simple atomic operations (such as test-and-set) on a uniprocessor. a thread that is suspended within a restartable atomic sequence is resumed by the operating system at the beginning of the sequence, rather than at the point of suspension. this guarantees that the thread eventually executes the sequence atomically. a restartable atomic sequence has significantly less overhead than other software-based synchronization mechanisms, such as kernel emulation or software reservation. consequently, it is an attractive alternative for use on uniprocessors that do no support atomic operations. even on processors that do support atomic operations in hardware, restartable atomic sequences can have lower overhead. we describe different implementations of restartable atomic sequences for the mach 3.0 and taos operating systems. these systems' thread management packages rely on atomic operations to implement higher-level mutual exclusion facilities. we show that improving the performance of low-level atomic operations, and therefore mutual exclusion mechanisms, improves application performance.
coherency for multiprocessor virtual address caches. a multiprocessor cache memory system is described that supplies data to the processor based on virtual addresses, but maintains consistency in the main memory, both across caches and across virtual address spaces. pages in the same or different address spaces may be mapped to share a single physical page. the same hardware is used for maintaining consistency both among caches and among virtual addresses. three different notions of a cache "block" are defined: (1) the unit for transferring data to/from main storage, (2) the unit over which tag information is maintained, and (3) the unit over which consistency is maintained. the relation among these block sizes is explored, and it is shown that they can be optimized independently. it is shown that the use of large address blocks results in low overhead for the virtual address cache.
access normalization: loop restructuring for numa compilers. in scalable parallel machines, processors can make local memory accesses much faster than they can make remote memory accesses. in addition, when a number of remote accesses must be made, it is usually more efficient to use block transfers of data rather than to use many small messages. to run well on such machines, software must exploit these features. we believe it is too onerous for a programmer to do this by hand, so we have been exploring the use of restructuring compiler tecnology for this purpose. in this paper, we start with a language like fortran-d with user-specified data distribution and develop a systematic loop transformation strategy called access normalization that restructures loop nests to exploit locality and block transfers. we demonstrate the power of our techniques using routines from the blas (basic linear algebra subprograms) library. an important feature of our approach is that we model loop transformations using invertible matrices and integer lattice theory, thereby generalizing banerjee's framework of unimodular matrices [5].
evaluating design alternatives for reliable communication on high-speed networks. we systematically evaluate the performance of five implementations of a single, user-level communication interface. each implementation makes different architectural assumptions about the reliability of the network hardware and the capabilities of the network interface. the implementations differ accordingly in their division of protocol tasks between host software, network-interface firmware, and network hardware. using microbenchmarks, parallel-programming systems, and parallel applications, we assess the performance impact of different protocol decompositions. we show how moving protocol tasks to a relatively slow network interface yields both performance advantages and disadvantages, depending on the characteristics of the application and the underlying parallel-programming system. in particular, we show that a communication system that assumes highly reliable network hardware and that uses network-interface support to process multicast traffic performs best for all applications.
a stateless, content-directed data prefetching mechanism. although central processor speeds continues to improve, improvements in overall system performance are increasingly hampered by memory latency, especially for pointer-intensive applications. to counter this loss of performance, numerous data and instruction prefetch mechanisms have been proposed. recently, several proposals have posited a memory-side prefetcher; typically, these prefetchers involve a distinct processor that executes a program slice that would effectively prefetch data needed by the primary program. alternative designs embody large state tables that learn the miss reference behavior of the processor and attempt to prefetch likely misses.this paper proposes content-directed data prefetching, a data prefetching architecture that exploits the memory allocation used by operating systems and runtime systems to improve the performance of pointer-intensive applications constructed using modern language systems. this technique is modeled after conservative garbage collection, and prefetches "likely" virtual addresses observed in memory references. this prefetching mechanism uses the underlying data of the application, and provides an 11.3% speedup using no additional processor state. by adding less than &frac12;% space overhead to the second level cache, performance can be further increased to 12.6% across a range of "real world" applications.
envy: a non-volatile, main memory storage system. this paper describes the architecture of envy, a large non-volatile main memory storage system built primarily with flash memory. envy presents its storage space as a linear, memory mapped array rather than as an emulated disk in order to provide an efficient and easy to use software interface.flash memories provide persistent storage with solid-state memory access times at a lower cost than other solid-state technologies. however, they have a number of drawbacks. flash chips are write-once, bulk-erase devices whose contents cannot be updated in-place. they also suffer from slow program times and a limit on the number of program/erase cycles. envy uses a copy-on-write scheme, page remapping, a small amount of battery backed sram, and high bandwidth parallel data transfers to provide low latency, in-place update semantics. a cleaning algorithm optimized for large flash arrays is used to reclaim space. the algorithm is designed to evenly wear the array, thereby extending its lifetime.software simulations of a 2 gigabyte envy system show that it can support i/o rates corresponding to approximately 30,000 transactions per second on the tpc-a database benchmark. despite the added work done to overcome the deficiencies associated with flash memories, average latencies to the storage system are as low as 180ns for reads and 200ns for writes. the estimated lifetime of this type of storage system is in the 10 year range when exposed to a workload of 10,000 transactions per second.
hiding communication latency and coherence overhead in software dsms. in this paper we propose the use of a pci-based programmable protocol controller for hiding communication and coherence overheads in software dsms. our protocol controller provides three different types of overhead tolerance: a) moving basic communication and coherence tasks away from computation processors; b) prefetching of diffs; and c) generating and applying diffs with hardware assistance. we evaluate the isolated and combined impact of these features on the performance of treadmarks. we also compare performance against two versions of the shrimp-based aurc protocol. using detailed execution-driven simulations of a 16-node network of workstations, we show that the greatest performance benefits provided by our protocol controller come from our hardware-supported diffs. reducing the burden of communication and coherence transactions on the computation processor is also beneficial but to a smaller extent. prefetching is not always profitable. our results show that our protocol controller can improve running time performance by up to 50% for treadmarks, which means that it can double the treadmarks speedups. the overlapping implementation of treadmarks performs as well or better than aurc for 5 of our 6 applications. we conclude that the simple hardware support we propose allows for the implementation of high-performance software dsms at low cost. based on this conclusion, we are building the ncp2 parallel system at coppe/ufrj.
efficent synchronization primitives for large-scale cache-coherent multiprocessors. this paper proposes a set of efficient primitives for process synchronization in multiprocessors. the only assumptions made in developing the set of primitives are that hardware combining is not implemented in the inter-connect, and (in one case) that the interconnect supports broadcast. the primitives make use of synchronization bits (syncbits) to provide a simple mechanism for mutual exclusion. the proposed implementation of the primitives includes efficient (i.e. local) busy-waiting for syncbits. in addition, a hardware-supported mechanism for maintaining a first-come first-serve queue of requests for a syncbit is proposed. this queueing mechanism allows for a very efficient implementation of, as well as fair access to, binary semaphores. we also propose to implement fetch and add with combining in software rather than hardware. this allows an architecture to scale to a large number of processors while avoiding the cost of hardware combining. scenarios for common synchronization events such as work queues and barriers are presented to demonstrate the generality and ease of use of the proposed primitives. the efficient implementation of the primitives is simpler if the multiprocessor has a hardware cache-consistency protocol. to illustrate this point, we outline how the primitives would be implemented in the multicube multiprocessor [gowo88].
architectural support for multilanguage parallel programming on heterogeneous systems. we have designed and implemented a software facility, called agora, that supports the development of parallel applications written in multiple languages. at the core of agora there is a mechanism that allows concurrent computations to share data structures independently of the computer architecture they are executed on. concurrent computations exchange control information by using a pattern-directed technique. this paper describes the agora shared memory and its software implementation on both tightly and loosely-coupled architectures.
a stream compiler for communication-exposed architectures. with the increasing miniaturization of transistors, wire delays are becoming a dominant factor in microprocessor performance. to address this issue, a number of emerging architectures contain replicated processing units with software-exposed communication between one unit and another (e.g., raw, smartmemories, trips). however, for their use to be widespread, it will be necessary to develop compiler technology that enables a portable, high-level language to execute efficiently across a range of wire-exposed architectures.in this paper, we describe our compiler for streamit: a high-level, architecture-independent language for streaming applications. we focus on our backend for the raw processor. though streamit exposes the parallelism and communication patterns of stream programs, some analysis is needed to adapt a stream program to a software-exposed processor. we describe a partitioning algorithm that employs fission and fusion transformations to adjust the granularity of a stream graph, a layout algorithm that maps a stream graph to a given network topology, and a scheduling strategy that generates a fine-grained static communication pattern for each computational element.we have implemented a fully functional compiler that parallelizes streamit applications for raw, including several load-balancing transformations. using the cycle-accurate raw simulator, we demonstrate that the streamit compiler can automatically map a high-level stream abstraction to raw without losing performance. we consider this work to be a first step towards a portable programming model for communication-exposed architectures.
whole-program optimization for time and space efficient threads. modern languages and operating systems often encourage programmers to use threads, or independent control streams, to mask the overhead of some operations and simplify program structure. multitasking operating systems use threads to mask communication latency, either with hardwares devices or users. client-server applications typically use threads to simplify the complex control-flow that arises when multiple clients are used. recently, the scientific computing community has started using threads to mask network communication latency in massively parallel architectures, allowing computation and communication to be overlapped. lastly, some architectures implement threads in hardware, using those threads to tolerate memory latency.in general, it would be desirable if threaded programs could be written to expose the largest degree of parallelism possible, or to simplify the program design. however, threads incur time and space overheads, and programmers often compromise simple designs for performance. in this paper, we show how to reduce time and space thread overhead using control flow and register liveness information inferred after compilation. our techniques work on binaries, are not specific to a particular compiler or thread library and reduce the the overall execution time of fine-grain threaded programs by &asymp; 15-30%. we use execution-driven analysis and an instrumented operating system to show why the execution time is reduced and to indicate areas for future work.
software profiling for hot path prediction: less is more. recently, there has been a growing interest in exploiting profile information in adaptive systems such as just-in-time compilers, dynamic optimizers and, binary translators. in this paper, we show that sophisticated software profiling schemes that provide highly accurate information in an offline setting are ill-suited for these dynamic code generation systems. we experimentally demonstrate that hot path predictions must be made early in order to control the rising cost of missed opportunity that result from the prediction delay. we also show that existing sophisticated path profiling schemes, if used in an online setting, offer no prediction advantages over simpler schemes that exhibit much lower runtime overheads.based on these observation we developed a new low-overhead software profiling scheme for hot path prediction. using an abstract metric we compare our scheme to path profile based prediction and show that our scheme achieves comparable prediction quality. in our second set of experiments we include runtime overhead and evaluate the performance of our scheme in a realistic application: dynamo, a dynamic optimization system. the results show that our prediction scheme clearly outperforms path profile based prediction and thus confirm that less profiling as exhibited in our scheme will actually lead to more effective hot path prediction.
riscs versus ciscs for prolog: a case study. this paper compares the performance of executing compiled prolog code on two different architectures under development at u. c. berkeley. the first is the plm, a special-purpose cisc architecture intended as a coprocessor for a host machine. the second is spur, a general-purpose risc architecture that supports tagged data. fourteen standard benchmark programs were run on both the plm and spur simulators. the compiled code for spur was obtained by simple macro-expansion of plm code generated by the plm prolog compiler. the two implementations are compared with regard to static and dynamic program size, execution speed, and memory system performance. on average, the macrocoded spur implementation has a static code size 14 times larger than the plm, executes 16 times more instructions, yet requires only 2.3 times the number of machine cycles (or has the performance of 0.43 plms). when memory system performance is taken into account, spur is equivalent to 0.29 plms. optimizations of the macro-expanded code and minor architectural changes to spur would increase this ratio to 0.53, or 0.60 for the largest benchmarks. thus a tagged risc architecture can execute prolog at least half as fast as a special-purpose cisc architecture for prolog.
the fuzzy barrier: a mechanism for high speed synchronization of processors. parallel programs are commonly written using barriers to synchronize parallel processes. upon reaching a barrier, a processor must stall until all participating processors reach the barrier. a software implementation of the barrier mechanism using shared variables has two major drawbacks. firstly, the execution of the barrier may be slow as it may not only require execution of several instructions and but also result in hot-spot accesses. secondly, processors that are stalled waiting for other processors to reach the barrier are essentially idling and cannot do any useful work. in this paper, the notion of the fuzzy barrier is presented, that avoids the above drawbacks. the first problem is avoided by implementing the mechanism in hardware. the second problem is solved by extending the barrier concept to include a region of statements that can be executed by a processor while it awaits synchronization. the barrier regions are constructed by a compiler and consist of several instructions such that a processor is ready to synchronize upon reaching the first instruction in this region and must synchronize before exiting the region. when synchronization does occur, the processors could be executing at any point in their respective barrier regions. the larger the barrier region, the more likely it is that none of the processors will have to stall. preliminary investigations show that barrier regions can be large and the use of program transformations can significantly increase their size. examples of situations where such a mechanism can result in improved performance are presented. results based on a software implementation of the fuzzy barrier on the encore multiprocessor indicate that the synchronization overhead can be greatly reduced using the mechanism.
compiler-controlled memory. optimizations aimed at reducing the impact of memory operations on execution speed have long concentrated on improving cache performance. these efforts achieve a. reasonable level of success. the primary limit on the compiler's ability to improve memory behavior is its imperfect knowledge about the run-time behavior of the program. the compiler cannot completely predict runtime access patterns.there is an exception to this rule. during the register allocation phase, the compiler often must insert substantial amounts of spill code; that is, instructions that move values from registers to memory and back again. because the compiler itself inserts these memory instructions, it has more knowledge about them than other memory operations in the program.spill-code operations are disjoint from the memory manipulations required by the semantics of the program being compiled, and, indeed, the two can interfere in the cache. this paper proposes a hardware solution to the problem of increased spill costs---a small compiler-controlled memory (ccm) to hold spilled values. this small random-access memory can (and should) be placed in a distinct address space from the main memory hierarchy. the compiler can target spill instructions to use the ccm, moving most compiler-inserted memory traffic out of the pathway to main memory and eliminating any impact that those spill instructions would have on the state of the main memory hierarchy. such memories already exist on some dsp microprocessors. our techniques can be applied directly on those chips.this paper presents two compiler-based methods to exploit such a memory, along with experimental results showing that speedups from using ccm may be sizable. it shows that using the register allocation's coloring paradigm to assign spilled values to memory can greatly reduce the amount of memory required by a program.
application-level checkpointing for shared memory programs. trends in high-performance computing are making it necessary for long-running applications to tolerate hardware faults. the most commonly used approach is checkpoint and restart (cpr) - the state of the computation is saved periodically on disk, and when a failure occurs, the computation is restarted from the last saved state. at present, it is the responsibility of the programmer to instrument applications for cpr.our group is investigating the use of compiler technology to instrument codes to make them self-checkpointing and self-restarting, thereby providing an automatic solution to the problem of making long-running scientific applications resilient to hardware faults. our previous work focused on message-passing programs.in this paper, we describe such a system for shared-memory programs running on symmetric multiprocessors. this system has two components: (i) a pre-compiler for source-to-source modification of applications, and (ii) a runtime system that implements a protocol for coordinating cpr among the threads of the parallel application. for the sake of concreteness, we focus on a non-trivial subset of openmp that includes barriers and locks.one of the advantages of this approach is that the ability to tolerate faults becomes embedded within the application itself, so applications become self-checkpointing and self-restarting on any platform. we demonstrate this by showing that our transformed benchmarks can checkpoint and restart on three different platforms (windows/x86, linux/x86, and tru64/alpha). our experiments show that the overhead introduced by this approach is usually quite small; they also suggest ways in which the current implementation can be tuned to reduced overheads further.
spatial computation. this paper describes a computer architecture, spatial computation (sc), which is based on the translation of high-level language programs directly into hardware structures. sc program implementations are completely distributed, with no centralized control. sc circuits are optimized for wires at the expense of computation units.in this paper we investigate a particular implementation of sc: ash (application-specific hardware). under the assumption that computation is cheaper than communication, ash replicates computation units to simplify interconnect, building a system which uses very simple, completely dedicated communication channels. as a consequence, communication on the datapath never requires arbitration; the only arbitration required is for accessing memory. ash relies on very simple hardware primitives, using no associative structures, no multiported register files, no scheduling logic, no broadcast, and no clocks. as a consequence, ash hardware is fast and extremely power efficient.in this work we demonstrate three features of ash: (1) that such architectures can be built by automatic compilation of c programs; (2) that distributed computation is in some respects fundamentally different from monolithic superscalar processors; and (3) that asic implementations of ash use three orders of magnitude less energy compared to high-end superscalar processors, while being on average only 33% slower in performance (3.5x worst-case).
programming with transactional coherence and consistency (tcc). transactional coherence and consistency (tcc) offers a way to simplify parallel programming by executing all code within transactions. in tcc systems, transactions serve as the fundamental unit of parallel work, communication and coherence. as each transaction completes, it writes all of its newly produced state to shared memory atomically, while restarting other processors that have speculatively read stale data. with this mechanism, a tcc-based system automatically handles data synchronization correctly, without programmer intervention. to gain the benefits of tcc, programs must be decomposed into transactions. we describe two basic programming language constructs for decomposing programs into transactions, a loop conversion syntax and a general transaction-forking mechanism. with these constructs, writing correct parallel programs requires only small, incremental changes to correct sequential programs. the performance of these programs may then easily be optimized, based on feedback from real program execution, using a few simple techniques.
compiler-directed page coloring for multiprocessors. this paper presents a new technique, compiler-directed page coloring, that eliminates conflict misses in multiprocessor applications. it enables applications to make better use of the increased aggregate cache size available in a multiprocessor. this technique uses the compiler's knowledge of the access patterns of the parallelized applications to direct the operating system's virtual memory page mapping strategy. we demonstrate that this technique can lead to significant performance improvements over two commonly used page mapping strategies for machines with either direct-mapped or two-way set-associative caches. we also show that it is complementary to latency-hiding techniques such as prefetching.we implemented compiler-directed page coloring in the suif parallelizing compiler and on two commercial operating systems. we applied the technique to the spec95fp benchmark suite, a representative set of numeric programs. we used the simos machine simulator to analyze the applications and isolate their performance bottlenecks. we also validated these results on a real machine, an eight-processor 350mhz digital alphaserver. compiler-directed page coloring leads to significant performance improvements for several applications. overall, our technique improves the spec95fp rating for eight processors by 8% over digital unix's page mapping policy and by 20% over a page coloring, a standard page mapping policy. the suif compiler achieves a spec95fp ratio of 57.4, the highest ratio to date.
data speculation support for a chip multiprocessor. thread-level speculation is a technique that enables parallel execution of sequential applications on a multiprocessor. this paper describes the complete implementation of the support for threadlevel speculation on the hydra chip multiprocessor (cmp). the support consists of a number of software speculation control handlers and modifications to the shared secondary cache memory system of the cmp this support is evaluated using five representative integer applications. our results show that the speculative support is only able to improve performance when there is a substantial amount of medium--grained loop-level parallelism in the application. when the granularity of parallelism is too small or there is little inherent parallelism in the application, the overhead of the software handlers overwhelms any potential performance benefits from speculative-thread parallelism. overall, thread-level speculation still appears to be a promising approach for expanding the class of applications that can be automatically parallelized, but more hardware intensive implementations for managing speculation control are required to achieve performance improvements on a wide class of integer applications.
architectural support for fast symmetric-key cryptography. the emergence of the internet as a trusted medium for commerce and communication has made cryptography an essential component of modern information systems. cryptography provides the mechanisms necessary to implement accountability, accuracy, and confidentiality in communication. as demands for secure communication bandwidth grow, efficient cryptographic processing will become increasingly vital to good system performance.in this paper, we explore techinques to improve the performance of symmetric key cipher algorithms. eight popular strong encryption algorithms are examined in detail. analysis reveals the algorithms are computaionally complex and contain little parallelism. overall throughput on high-end microprocessor is quite poor, a 600 mhz processor is incapable of saturation a t3 communication line with 3des (triple des) encrypted data.we introduce new instructions taht improve the efficiency of the analyzed algorithms. our approach adds instruction set support for fast substitutions, general permutations, rotates, and modular arithmetic. performance analysis of the optimized ciphers shows an overall speedup of 59% over a baseline machine with rotate instructions and 74% speedup over a baseline without rotates. even higher speedups are demonstrated with optimized subtitutions (sboxes) and additional functional unit resources. our analyses of the original and optimized algorithms suggest future directions for the design of high-performance programmable cryptographic processors.
an architectural alternative to optimizing compilers. programming languages are designed to make programming productive. computer architectures are designed to make program execution efficient. although architectures should be designed with programming languages in mind, it may be as inappropriate to make the computer execute the programming language directly it is to make the programmer use machine language. it is the compiler's job to match the programming language and the computer architectures, and therefore making compiler's efficient and easy to write are important design goals of a complete hardware/software system. this paper summerizes research completed in 1980 [5] on a computer architecture, tm, that takes over some of the more burdensome tasks of optimizing compilers for high-level-languages (hll's), performing these tasks dynamically during the execution of the object program. this is a different approach to making compilers efficient than is commonly taken; more common approaches include devising more efficient optimization algorithms[i], being clever about when to do optimizations [4], and building the compilers semiautomatically [6].
architectural support for synchronous task communication. this paper describes the motivation for a set of intertask communication primitives, the hardware support of these primitives, the architecture used in the sylvan project which studies these issues, and the experience gained from various experiments conducted in this area. we start by describing how these facilities have been implemented in a multiprocessor configuration that utilizes a shared backplane. this configuration represents a single node in the system. the latter part of the paper discusses a distributed multiple node system and the extension of the primitives that are used in this expanded environment. this research is funded by a strategic grant from the natural sciences and engineering research council of canada (grant no. g1581).
an integrated compile-time/run-time software distributed shared memory system. on a distributed memory machine, hand-coded message passing leads to the most efficient execution, but it is difficult to use. parallelizing compilers can approach the performance of hand-coded message passing by translating data-parallel programs into message passing programs, but efficient execution is limited to those programs for which precise analysis can be carried out. shared memory is easier to program than message passing and its domain is not constrained by the limitations of parallelizing compilers, but it lags in performance. our goal is to close that performance gap while retaining the benefits of shared memory. in other words, our goal is (1) to make shared memory as efficient as message passing, whether hand-coded or compiler-generated, (2) to retain its ease of programming, and (3) to retain the broader class of applications it supports.to this end we have designed and implemented an integrated compile-time and run-time software dsm system. the programming model remains identical to the original pure run-time dsm system. no user intervention is required to obtain the benefits of our system. the compiler computes data access patterns for the individual processors. it then performs a source-to-source transformation, inserting in the program calls to inform the run-time system of the computed data access patterns. the run-time system uses this information to aggregate communication, to aggregate data and synchronization into a single message, to eliminate consistency overhead, and to replace global synchronization with point-to-point synchronization wherever possible.we extended the parascope programming environment to perform the required analysis, and we augmented the treadmarks run-time dsm library to take advantage of the analysis. we used six fortran programs to assess the performance benefits: jacobi, 3d-fft, integer sort, shallow, gauss, and modified gramm-schmidt, each with two different data set sizes. the experiments were run on an 8-node ibm sp/2 using user-space communication. compiler optimization in conjunction with the augmented run-time system achieves substantial execution time improvements in comparison to the base treadmarks, ranging from 4% to 59% on 8 processors. relative to message passing implementations of the same applications, the compile-time run-time system is 0-29% slower than message passing, while the base run-time system is 5-212% slower. for the five programs that xhpf could parallelize (all except is), the execution times achieved by the compiler optimized shared memory programs are within 9% of xhpf.
efficient and flexible value sampling. this paper presents novel sampling-based techniques for collecting statistical profiles of register contents, data values, and other information associated with instructions, such as memory latencies. values of interest are sampled in response to periodic interrupts. the resulting value profiles can be analyzed by programmers and optimizers to improve the performance of production uniprocessor and multiprocessor systems.our value sampling system extends the dcpi continuous profiling infrastructure, and inherits many of its desirable properties: our value profiler has low overhead (approximately 10% slowdown); it profiles all the code in the system, including the operating system kernel; and it operates transparently, without requiring any modifications to the profiled code.
application-controlled physical memory using external page-cache management. next generation computer systems will have gigabytes of physical memory and processors in the 100 mips range or higher. contrary to some conjectures, this trend requires more sophisticated memory management support for memory-bound computations such as scientific simulations and systems such as large-scale database systems, even though memory management for most programs will be less of a concern. we describe the design, implementation and evaluation of a virtual memory system that provides application control of physical memory using external page-cache management. in this approach, a sophisticated application is able to monitor and control the amount of physical memory it has available for execution, the exact contents of this memory, and the scheduling and nature of page-in and page-out using the abstraction of a physical page cache provided by the kernel. we claim that this approach can significantly improve performance for many memory-bound applications while reducing kernel complexity, yet does not complicate other applications or reduce their performance.
low-overhead memory leak detection using adaptive statistical profiling. sampling has been successfully used to identify performance optimization opportunities. we would like to apply similar techniques to check program correctness. unfortunately, sampling provides poor coverage of infrequently executed code, where bugs often lurk. we describe an adaptive profiling scheme that addresses this by sampling executions of code segments at a rate inversely proportional to their execution frequency. to validate our ideas, we have implemented swat, a novel memory leak detection tool. swat traces program allocations/ frees to construct a heap model and uses our adaptive profiling infrastructure to monitor loads/stores to these objects with low overhead. swat reports 'stale' objects that have not been accessed for a 'long' time as leaks. this allows it to find all leaks that manifest during the current program execution. since swat has low runtime overhead (‹5%), and low space overhead (‹10% in most cases and often less than 5%), it can be used to track leaks in production code that take days to manifest. in addition to identifying the allocations that leak memory, swat exposes where the program last accessed the leaked data, which facilitates debugging and fixing the leak. swat has been used by several product groups at microsoft for the past 18 months and has proved effective at detecting leaks with a low false positive rate (‹10%).
compiling smalltalk-80 to a risc. the smalltalk on a risc project at u. c. berkeley proves that a high-level object-oriented language can attain high performance on a modified reduced instruction set architecture. the single most important optimization is the removal of a layer of interpretation, compiling the bytecoded virtual machine instructions into low-level, register-based, hardware instructions. this paper describes the compiler and how it was affected by soar architectural features. the compiler generates code of reasonable density and speed. because of smalltalk-80's semantics, relatively few optimizations are possible, but hardware and software mechanisms at runtime offset these limitations. register allocation for an architecture with register windows comprises the major task of the compiler. performance analysis suggests that soar is not simple enough; several hardware features could be efficiently replaced by instruction sequences constructed by the compiler.
ap1000+: architectural support of put/get interface for parallelizing compiler. the scalability of distributed-memory parallel computers makes them attractive candidates for solving large-scale problems. new languages, such as hpf, fortrand, and vpp fortran, have been developed to enable existing software to be easily ported to such machines. many distributed-memory parallel computers have been built, but none of them support the mechanisms required by such languages. we studied the mechanisms required by parallelizing compilers and proposed a new architecture to support them. based on this proposed architecture, we developed a new distributed-memory parallel computer, the ap1000+, which is an enhanced version of the ap1000. using scientific applications in vpp fortran and c, such as nas parallel benchmarks, we simulated the performance of the ap1000+.
dynamic dead-instruction detection and elimination. we observe a non-negligible fraction--3 to 16% in our benchmarks--of dynamically dead instructions, dynamic instruction instances that generate unused results. the majority of these instructions arise from static instructions that also produce useful results. we find that compiler optimization (specifically instruction scheduling) creates a significant portion of these partially dead static instructions. we show that most of the dynamically instructions arise from a small set of static instructions that produce dead values most of the time.we leverage this locality by proposing a dead instruction predictor and presenting a scheme to avoid the execution of predicted-dead instructions. our predictor achieves an accuracy of 93% while identifying over 91% of the dead instructions using less than 5 kb of state. we achieve such high accuracies by leveraging future control flow information (i.e., branch predictions) to distinguish between useless and useful instances of the same static instruction.we then present a mechanism to avoid the register allocation, instruction scheduling, and execution of predicted dead instructions. we measure reductions in resource utilization averaging over 5% and sometimes exceeding 10%, covering physical register management (allocation and freeing), register file read and write traffic, and data cache accesses. performance improves by an average of 3.6% on an architecture exhibiting resource contention. additionally, our scheme frees future compilers from the need to consider the costs of dead instructions, enabling more aggressive code motion and optimization. simultaneously, it mitigates the need for good path profiling information in making inter-block code motion decisions.
an architecture for the direct execution of the forth programming language. we have developed a simple direct execution architecture for a 32 bit forth microprocessor. the processor can directly access a linear address space of over 4 gigawords. two instruction types are defined; a subroutine call, and a user defined microcode instruction. on-chip stack caches allow most forth primitives to execute in a single cycle.
reducing branch costs via branch alignment. several researchers have proposed algorithms for basic block reordering. we call these branch alignment algorithms. the primary emphasis of these algorithms has been on improving instruction cache locality, and the few studies concerned with branch prediction reported small or minimal improvements. as wide-issue architectures become increasingly popular the importance of reducing branch costs will increase, and branch alignment is one mechanism which can effectively reduce these costs.in this paper, we propose an improved branch alignment algorithm that takes into consideration the architectural cost model and the branch prediction architecture when performing the basic block reordering. we show that branch alignment algorithms can improve a broad range of static and dynamic branch prediction architectures. we also show that a program performance can be improved by approximately 5% even when using recently proposed, highly accurate branch prediction architectures. the programs are compiled by any existing compiler and then transformed via binary transformations. when implementing these algorithms on a alpha axp 21604 up to a 16% reduction in total execution time is achieved.
integration of message passing and shared memory in the stanford flash multiprocessor. the advantages of using message passing over shared memory for certain types of communication and synchronization have provided an incentive to integrate both models within a single architecture. a key goal of the flash (flexible architecture for shared memory) project at stanford is to achieve this integration while maintaining a simple and efficient design. this paper presents the hardware and software mechanisms in flash to support various message passing protocols. we achieve low overhead message passing by delegating protocol functionality to the programmable node controllers in flash and by providing direct user-level access to this messaging subsystem. in contrast to most earlier work, we provide an integrated solution that handles the interaction of the messaging protocols with virtual memory, protected multiprogramming, and cache coherence. detailed simulation studies indicate that this system can sustain message-transfers rates of several hundred megabytes per second, effectively utilizing projected network bandwidths for next generation multiprocessors.
cache-conscious data placement. as the gap between memory and processor speeds continues to widen, cache eficiency is an increasingly important component of processor performance. compiler techniques have been used to improve instruction cache pet$ormance by mapping code with temporal locality to different cache blocks in the virtual address space eliminating cache conflicts. these code placement techniques can be applied directly to the problem of placing data for improved data cache pedormance.in this paper we present a general framework for cache conscious data placement. this is a compiler directed approach that creates an address placement for the stack (local variables), global variables, heap objects, and constants in order to reduce data cache misses. the placement of data objects is guided by a temporal relationship graph between objects generated via profiling. our results show that profile driven data placement significantly reduces the data miss rate by 24% on average.
hardware/software tradeoffs for increased performance. most new computer architectures are concerned with maximizing performance by providing suitable instruction sets for compiled code and providing support for systems functions. we argue that the most effective design methodology must make simultaneous tradeoffs across all three areas: hardware, software support, and systems support. recent trends lean towards extensive hardware support for both the compiler and operating systems software. however, consideration of all possible design tradeoffs may often lead to less hardware support. several examples of this approach are presented, including: omission of condition codes, word-addressed machines, and imposing pipeline interlocks in software. the specifics and performance of these approaches are examined with respect to the mips processor.
cheap hardware support for software debugging and profiling. we wish to determine the effectiveness of some simple hardware for debugging and profiling compiled programs on a conventional processor. the hardware cost is small -- a counter decremented on each instruction that raises an exception when its value becomes zero. with the counter a debugger can provide data watchpoints and reverse execution: a profiler can measure the total instruction cost of a code segment and sample the program counter accurately. such a counter has been included on a single-board mc68020 workstation, for which system software is currently being written. we will report our progress at the symposium.
compiler optimizations for improving data locality. in the past decade, processor speed has become significantly faster than memory speed. small, fast cache memories are designed to overcome this discrepancy, but they are only effective when programs exhibit data locality. in this paper, we present compiler optimizations to improve data locality based on a simple yet accurate cost model. the model computes both temporal and spatial reuse of cache lines to find desirable loop organizations. the cost model drives the application of compound transformations consisting of loop permutation, loop fusion, loop distribution, and loop reversal. we demonstrate that these program transformations are useful for optimizing many programs.to validate our optimization strategy, we implemented our algorithms and ran experiments on a large collection of scientific programs and kernels. experiments with kernels illustrate that our model and algorithm can select and achieve the best performance. for over thirty complete applications, we executed the original and transformed versions and simulated cache hit rates. we collected statistics about the inherent characteristics of these programs and our ability to improve their data locality. to our knowledge, these studies are the first of such breadth and depth. we found performance improvements were difficult to achieve because benchmark programs typically have high hit rates even for small data caches; however, our optimizations significantly improved several programs.
system architecture directions for networked sensors. technological progress in integrated, low-power, cmos communication devices and sensors makes a rich design space of networked sensors viable. they can be deeply embedded in the physical world and spread throughout our environment like smart dust. the missing elements are an overall system architecture and a methodology for systematic advance. to this end, we identify key requirements, develop a small device that is representative of the class, design a tiny event-driven operating system, and show that it provides support for efficient modularity and concurrency-intensive operation. our operating system fits in 178 bytes of memory, propagates events in the time it takes to copy 1.25 bytes of memory, context switches in the time it takes to copy 6 bytes of memory and supports two level scheduling. the analysis lays a groundwork for future architectural advances.
hardware support for fast capability-based addressing. traditional methods of providing protection in memory systems do so at the cost of increased context switch time and/or increased storage to record access permissions for processes. with the advent of computers that supported cycle-by-cycle multithreading, protection schemes that increase the time to perform a context switch are unacceptable, but protecting unrelated processes from each other is still necessary if such machines are to be used in non-trusting environments.this paper examines guarded pointers, a hardware technique which uses tagged 64-bit pointer objects to implement capability-based addressing. guarded pointers encode a segment descriptor into the upper bits of every pointer, eliminating the indirection and related performance penalties associated with traditional implementations of capabilities. all processes share a single 54-bit virtual address space, and access is limited to the data that can be referenced through the pointers that a process has been issued. only one level of address translation is required to perform a memory reference. sharing data between processes is efficient, and protection states are defined to allow fast protected subsystem calls and create unforgeable data keys.
reference history, page size, and migration daemons in local/remote architectures. we address the problem of paged main memory management in the local/remote architecture subclass of shared memory multiprocessors. we consider the case where the operating system has primary responsibility and uses page migration as its main tool. we identify some of the key issues with respect to architectural support (reference history maintenance, and page size), and operating system mechanism (duration between daemon passes, and number of migration daemons). the experiments were conducted using software implemented page tables on 32-node bbn butterfly plus&trade;. several numeral programs with both synthetic and real data were used as the workload. the primary conclusion is that for the cases considered migration was at best marginally effective. on the other hand, practical migration mechanisms were robust and never significantly degraded performance. the specific results include: 1) referenced bits with aging can closely approximate usage fields, 2) larger page sizes are beneficial except when the page is large enough to include locality sets of two processes, and 3) multiple migration daemons can be useful. only small regions of the space of architectural, system, and workload parameters were explored. further investigation of other parameter combinations is clearly warranted.
limitless directories: a scalable cache coherence scheme. caches enhance the performance of multiprocessors by reducing network traffic and average memory access latency. however, cache-based systems must address the problem of cache coherence. we propose the limitless directory protocol to solve this problem. the limitless scheme uses a combination of hardware and software techniques to realize the performance of a full-map directory with the memory overhead of a limited directory. this protocol is supported by alewife, a large-scale multiprocessor. we describe the architectural interfaces needed to implement the limitless directory, and evaluate its performance through simulations of the alewife machine.
the intrinsic bandwidth requirements of ordinary programs. while there has been an abundance of recent papers on hardware and software approaches to improving the performance of memory accesses, few papers have addressed the problem from the program's point of view. there is a general notion that certain programs have larger working sets than others. however, there is no quantitative method for evaluating and comparing the memory requirements of programs.this paper introduces the bandwidth spectrum for characterizing the memory requirements of a program's instruction and data stream. the bandwidth spectrum measures the average bandwidth requirement of a program as a function of available local memory. these measurements are performed under the most idealized conditions of perfect knowledge and perfect memory management. as such, they represent the lower bounds on the memory requirements of programs. we present the bandwidth spectrums for a set of 22 benchmarks and show how they can be used in the comparison of memory requirements and i/o requirement. the bandwidth spectrums also offer a convenient method to weigh the trade-off amongst instruction issue rate, local memory capacity and bandwidth into local memory.using the bandwidth spectrum, we show that at issue rates of four or less, bandwidth usually scales linearly with the issue rate. at higher issue rates, bandwidth can often scale superlinearly with respect to issue rate. finally, we also investigate the effects of varying the input sets on the bandwidth spectrums.
scheduling and page migration for multiprocessor compute servers. several cache-coherent shared-memory multiprocessors have been developed that are scalable and offer a very tight coupling between the processing resources. they are therefore quite attractive for use as compute servers for multiprogramming and parallel application workloads. process scheduling and memory management, however, remain challenging due to the distributed main memory found on such machines. this paper examines the effects of os scheduling and page migration policies on the performance of such compute servers. our experiments are done on the stanford dash, a distributed-memory cache-coherent multiprocessor. we show that for our multiprogramming workloads consisting of sequential jobs, the traditional unix scheduling policy does very poorly. in contrast, a policy incorporating cluster and cache affinity along with a simple page-migration algorithm offers up to two-fold performance improvement. for our workloads consisting of multiple parallel applications, we compare space-sharing policies that divide the processors among the applications to time-slicing policies such as standard unix or gang scheduling. we show that space-sharing policies can achieve better processor utilization due to the operating point effect, but time-slicing policies benefit strongly from user-level data distribution. our initial experience with automatic page migration suggests that policies based only on tlb miss information can be quite effective, and useful for addressing the data distribution problems of space-sharing schedulers.
coherence decoupling: making use of incoherence. this paper explores a new technique called coherence decoupling, which breaks a traditional cache coherence protocol into two protocols: a speculative cache lookup (scl) protocol and a safe, backing coherence protocol. the scl protocol produces a speculative load value, typically from an invalid cache line, permitting the processor to compute with incoherent data. in parallel, the coherence protocol obtains the necessary coherence permissions and the correct value. eventually, the speculative use of the incoherent data can be verified against the coherent data. thus, coherence decoupling can greatly reduce --- if not eliminate --- the effects of false sharing. furthermore, coherence decoupling can also reduce latencies incurred by true sharing. scl protocols reduce those latencies by speculatively writing updates into invalid lines, thereby increasing the accuracy of speculation, without complicating the simple, underlying coherence protocol that guarantees correctness.the performance benefits of coherence decoupling are evaluated using a full-system simulator and a mix of commercial and scientific benchmarks. our results show that 40% to 90% of all coherence misses can be speculated correctly, and therefore their latencies partially or fully hidden. this capability results in performance improvements ranging from 3% to over 16%, in most cases where the latencies of coherence misses have an effect on performance.
where is time spent in message-passing and shared-memory programs? message passing and shared memory are two techniques parallel programs use for coordination and communication. this paper studies the strengths and weaknesses of these two mechanisms by comparing equivalent, well-written message-passing and shared-memory programs running on similar hardware. to ensure that our measurements are comparable, we produced two carefully tuned versions of each program and measured them on closely-related simulators of a message-passing and a shared-memory machine, both of which are based on same underlying hardware assumptions.we examined the behavior and performance of each program carefully. although the cost of computation in each pair of programs was similar, synchronization and communication differed greatly. we found that message-passing's advantage over shared-memory is not clear-cut. three of the four shared-memory programs ran at roughly the same speed as their message-passing equivalent, even though their communication patterns were different.
a look at several memory management units, tlb-refill mechanisms, and page table organizations. virtual memory is a staple in modem systems, though there is little agreement on how its functionality is to be implemented on either the hardware or software side of the interface. the myriad of design choices and incompatible hardware mechanisms suggests potential performance problems, especially since increasing numbers of systems (even embedded systems) are using memory management. a comparative study of the implementation choices in virtual memory should therefore aid system-level designers.this paper compares several virtual memory designs, including combinations of hierarchical and inverted page tables on hardware-managed and software-managed translation lookaside buffers (tlbs). the simulations show that systems are fairly sensitive to tlb size; that interrupts already account for a large portion of memory-management overhead and can become a significant factor as processors execute more concurrent instructions; and that if one includes the cache misses inflicted on applications by the vm system, the total vm overhead is roughly twice what was thought (10--20% rather than 5--10%).
reducing network latency using subpages in a global memory environment. new high-speed networks greatly encourage the use of network memory as a cache for virtual memory and file pages, thereby reducing the need for disk access. because pages are the fundamental transfer and access units in remote memory systems, page size is a key performance factor. recently, page sizes of modern processors have been increasing in order to provide more tlb coverage and amortize disk access costs. unfortunately, for high-speed networks, small transfers are needed to provide low latency. this trend in page size is thus at odds with the use of network memory on high-speed networks.this paper studies the use of subpages as a means of reducing transfer size and latency in a remote-memory environment. using trace-driven simulation, we show how and why subpages reduce latency and improve performance of programs using network memory. our results show that memory-intensive applications execute up to 1.8 times faster when executing with 1k-byte subpages, when compared to the same applications using full 8k-byte pages in the global memory system. those same applications using 1k-byte subpages execute up to 4 times faster than they would using the disk for backing store. using a prototype implementation on the dec alpha and an2 network, we demonstrate how subpages can reduce remote-memory fault time; e.g., our prototype is able to satisfy a fault on a 1k subpage stored in remote memory in 0.5 milliseconds, one third the time of a full page.
utlb: a mechanism for address translation on network interfaces. an important aspect of a high-speed network system is the ability to transfer data directly between the network interface and application buffers. such a direct data path requires the network interface to "know" the virtual-to-physical address translation of a user buffer, i.e., the physical memory location of the buffer. this paper presents an efficient address translation architecture, user-managed tlb (utlb), which eliminates system calls and device interrupts from the common communication path. utlb also supports application-specific policies to pin and unpin application memory. we report micro-benchmark results for an implementation on myrinet pc clusters. a trace-driven analysis is used to compare the utlb approach with the interrupt-based approach. it is also used to study the effects of utlb cache size, associativity, and prefetching. our results show that the utlb approach delivers robust performance with relatively small translation cache sizes.
some requirements for architectural support of software debugging. architectural support of high-level, symbolic debugging is described at three levels of abstraction: the user's view of desired debugging functionality, the debugger implementor's view of architectural requirements that support the functionality, and the computer architect's view of architectural features or attributes that implement the requirements. references are made where possible to computing systems that meet the requirements. the paper is written from the viewpoint of debugger implementors, and is addressed primarily to computer architects.
analysis of branch prediction via data compression. branch prediction is an important mechanism in modern microprocessor design. the focus of research in this area has been on designing new branch prediction schemes. in contrast, very few studies address the theoretical basis behind these prediction schemes. knowing this theoretical basis helps us to evaluate how good a prediction scheme is and how much we can expect to improve its accuracy.in this paper, we apply techniques from data compression to establish a theoretical basis for branch prediction, and to illustrate alternatives for further improvement. to establish a theoretical basis, we first introduce a conceptual model to characterize each component in a branch prediction process. then we show that current "two-level" or correlation based predictors are, in fact, simplifications of an optimal predictor in data compression, prediction by partial matching (ppm).if the information provided to the predictor remains the same, it is unlikely that significant improvements can be expected (asymptotically) from two-level predictors, since ppm is optimal. however, there are a rich set of predictors available from data compression, several of which can still yield some improvement in cases where resources are limited. to illustrate this, we conduct trace-driven simulation running the instruction benchmark suite and the spec cint95 benchmarks. the results show that ppm can outperform a two-level predictor for modest sized branch target buffers.
the rio file cache: surviving operating system crashes. one of the fundamental limits to high-performance, high-reliability file systems is memory's vulnerability to system crashes. because memory is viewed as unsafe, systems periodically write data back to disk. the extra disk traffic lowers performance, and the delay period before data is safe lowers reliability. the goal of the rio (ram i/o) file cache is to make ordinary main memory safe for persistent storage by enabling memory to survive operating system crashes. reliable memory enables a system to achieve the best of both worlds: reliability equivalent to a write-through file cache, where every write is instantly safe, and performance equivalent to a pure write-back cache, with no reliability-induced writes to disk. to achieve reliability, we protect memory during a crash and restore it during a reboot (a "warm" reboot). extensive crash tests show that even without protection, warm reboot enables memory to achieve reliability close to that of a write-through file system. adding protection makes memory even safer than a write-through file system while adding essentially no overhead. by eliminating reliability-induced disk writes, rio performs 4-22 times as fast as a write-through file system, 2-14 times as fast as a standard unix file system, and 1-3 times as fast as an optimized system that risks losing 30 seconds of data and metadata.
an overview of the mesa processor architecture. this paper provides an overview of the architecture of the mesa processor, an architecture which was designed to support the mesa programming system [4]. mesa is a high level systems programming language and associated tools designed to support the development of large information processing applications (on the order of one million source lines). since the start of development in 1971, the processor architecture, the programming language, and the operating system have been designed as a unit, so that proper tradeoffs among these components could be made.
software prefetching for mark-sweep garbage collection: hardware analysis and software redesign. tracing garbage collectors traverse references from live program variables, transitively tracing out the closure of live objects. memory accesses incurred during tracing are essentially random: a given object may contain references to any other object. since application heaps are typically much larger than hardware caches, tracing results in many cache misses. technology trends will make cache misses more important, so tracing is a prime target for prefetching.simulation of java benchmarks running with the boehm-de-mers-weiser mark-sweep garbage collector for a projected hardware platform reveal high tracing overhead (up to 65% of elapsed time), and that cache misses are a problem. applying boehm's default prefetching strategy yields improvements in execution time (16% on average with incremental/generational collection for gc-intensive benchmarks), but analysis shows that his strategy suffers from significant timing problems: prefetches that occur too early or too late relative to their matching loads. this analysis drives development of a new prefetching strategy that yields up to three times the performance improvement of boehm's strategy for gc-intensive benchmark (27% average speedup), and achieves performance close to that of perfect timing ie, few misses for tracing accesses) on some benchmarks. validating these simulation results with live runs on current hardware produces average speedup of 6% for the new strategy on gc-intensive benchmarks with a gc configuration that tightly controls heap growth. in contrast, boehm's default prefetching strategy is ineffective on this platform.
systematic protection mechanism design. this work describes an attempt to systematically design a hardware resource protection mechanism when given the requirements of a particular language as a target. the design process is formalized as a structured walk through the multidimensional computer design space towards a hypothetical class of optimal machines. each step in this walk involves a change in the distribution of work between the compiler and run-time system but no change in the source language semantics. the starting point for this walk is the result of a semantic analysis of the language to be implemented; typically, this produces a very high level machine where the compiler, if any, is trivial. the walk ends when no changes result in a net improvement. this does not guarantee that the result is even locally optimal, since the changes tried depend on the ingenuity and persistence of the designer. this design approach has been used to arrive at a practical, general purpose protection mechanism oriented towards the needs of the ada language (preliminary version). this architecture was evaluated by comparing it with the pdp-11/45. for the purpose of this comparison, the protection mechanism was incorporated into a partially specified pdp-11 like instruction set. the number of bits making up the processor state and the number of operations involved in address computation were evaluated. on this basis, the result appears to be competitive and worth further investigation.
a unified vector/scalar floating-point architecture. in this paper we present a unified approach to vector and scalar computation, using a single register file for both scalar operands and vector elements. the goal of this architecture is to yield improved scalar performance while broadening the range of vectorizable applications. for example, reduction operations and recurrences can be expressed in vector form in this architecture. this approach results in greater overall performance for most applications than does the approach of emphasizing peak vector performance. the hardware required to support the enhanced vector capability is insignificant, but allows the execution of two operations per cycle for vectorized code. moreover, the size of the unified vector/scalar register file required for peak performance is an order of magnitude smaller than traditional vector register files, allowing efficient on-chip vlsi implementation. the results of simulations of the livermore loops and linpack using this architecture are presented.
using meta-level compilation to check flash protocol code. building systems such as os kernels and embedded software is difficult. an important source of this difficulty is the numerous rules they must obey: interrupts cannot be disabled for "too long," global variables must be protected by locks, user pointers passed to os code must be checked for safety before use, etc. a single violation can crash the system, yet typically these invariants are unchecked, existing only on paper or in the implementor's mind.this paper is a case study in how system implementors can use a new programming methodology, metalevel compilation (mc), to easily check such invariants. it focuses on using mc to check for errors in the code used to manage cache coherence on the flash shared memory multiprocessor. the only real practical method known for verifying such code is testing and simulation. we show that simple, system-specific checkers can dramatically improve this situation by statically pinpointing errors in the program source. these checkers can be written by implementors themselves and, by exploiting the system-specific information this allows, can detect errors unreachable with other methods. the checkers in this paper found 34 bugs in flash code despite the care used in building it and the years of testing it has undergone. many of these errors fall in the worst category of systems bugs: those that show up sporadically only after days of continuous use. the case study is interesting because it shows that the mc approach finds serious errors in well-tested, non-toy systems code. further, the code to find such bugs is usually 10-100 lines long, written in a few hours, and exactly locates errors that, if discovered during testing, would require several days of investigation by an experienced implementor.the paper presents 8 checkers we wrote, their application to five different protocol implementations, and a discussion of the errors that we found.
available instruction-level parallelism for superscalar and superpipelined machines. superscalar machines can issue several instructions per cycle. superpipelined machines can issue only one instruction per cycle, but they have cycle times shorter than the latency of any functional unit. in this paper these two techniques are shown to be roughly equivalent ways of exploiting instruction-level parallelism. a parameterizable code reorganization and simulation system was developed and used to measure instruction-level parallelism for a series of benchmarks. results of these simulations in the presence of various compiler optimizations are presented. the average degree of superpipelining metric is introduced. our simulations suggest that this metric is already high for many machines. these machines already exploit all of the instruction-level parallelism available in many non-numeric applications, even without parallel instruction issue or higher degrees of pipelining.
how many addressing modes are enough? programs naturally require a variety of memory-addressing modes. it isn't necessary to provide them in hardware, however, if a compiler can synthesize them from a few primitive modes. this not only simplifies the hardware, but also permits the compiler to use its understanding of the program to economize on the modes which it uses. we present some compilation techniques that allow the compiler to deal effectively with a single addressing mode in a target risc processor. we also give measurements to show the benefits of such techniques, and to support our assertion that a single addressing mode is adequate for a general purpose processor, provided that mode incorporates both a pointer and an offset.
energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with zebranet. over the past decade, mobile computing and wireless communication have become increasingly important drivers of many new computing applications. the field of wireless sensor networks particularly focuses on applications involving autonomous use of compute, sensing, and wireless communication devices for both scientific and commercial purposes. this paper examines the research decisions and design tradeoffs that arise when applying wireless peer-to-peer networking techniques in a mobile sensor network designed to support wildlife tracking for biology research.the zebranet system includes custom tracking collars (nodes) carried by animals under study across a large, wild area; the collars operate as a peer-to-peer network to deliver logged data back to researchers. the collars include global positioning system (gps), flash memory, wireless transceivers, and a small cpu; essentially each node is a small, wireless computing device. since there is no cellular service or broadcast communication covering the region where animals are studied, ad hoc, peer-to-peer routing is needed. although numerous ad hoc protocols exist, additional challenges arise because the researchers themselves are mobile and thus there is no fixed base station towards which to aim data. overall, our goal is to use the least energy, storage, and other resources necessary to maintain a reliable system with a very high `data homing' success rate. we plan to deploy a 30-node zebranet system at the mpala research centre in central kenya. more broadly, we believe that the domain-centric protocols and energy tradeoffs presented here for zebranet will have general applicability in other wireless and sensor applications.
accelerating multi-media processing by implementing memoing in multiplication and division units. this paper proposes a technique that enables performing multi-cycle (multiplication, division, square-root &hellip;) computations in a single cycle. the technique is based on the notion of memoing: saving the input and output of previous calculations and using the output if the input is encountered again. this technique is especially suitable for multi-media (mm) processing. in mm applications the local entropy of the data tends to be low which results in repeated operations on the same datum.the inputs and outputs of assembly level operations are stored in cache-like lookup tables and accessed in parallel to the conventional computation. a successful lookup gives the result of a multi-cycle computation in a single cycle, and a failed lookup doesn't necessitate a penalty in computation time.results of simulations have shown that on the average, for a modestly sized memo-table, about 40% of the floating point multiplications and 50% of the floating point divisions, in multi-media applications, can be avoided by using the values within the memo-table, leading to an average computational speedup of more than 20%.
heart: an operating system nucleus machine implemented by firmware. this paper discusses the role of microprogramming in operating system design and shows several things: (1) advantages of the efficiency which may be gained from microcoded operating system primitives, (2) selecting the most appropriste primitives for implementation, and (3) an analysis of the tradeoffs among software, firmware, and hardware. the authors propose a practical approach of enhancing computer architecture level, from a view point of functional hierarchy of operating systems. in order to prove the advantages of this approach, we have designed and implemented an experimental abstract machine for an operating system nucleus. this research is an experimental design, and evaluation on its operating system nucleus machine,called heart. heart is a set of primitive and universal functions, and works as a nucleus of a multiprogrammed operating system. the research results of our approach are the followings: first, to clarify the properties of operating system nucleus, taking functional hierarchy of operating system into consideration. second, to show the design of operating system nucleus based on novel concepts. third, to confirm the possibility of implimenting operating system nucleus machine. finally, we give a performance evaluation on microcoded heart and the effectiveness of enhancing computer architecture level based on the properties of operating systems.
pipelining and performance in the vax 8800 processor. the vax 8800 family (models 8800, 8700, 8550), currently the fastest computers in the vax product line, achieve their speed through a combination of fast cycle time and deep pipelining. rather than pipeline highly variable vax instructions as such, the 8800 design pipelines uniform microinstructions whose addresses are generated by instruction unit hardware. this design approach helps achieve a fast cycle time, which is the prime determinan of performance. some preliminary measurements of cycles per average instruction are reported.
software overhead in messaging layers: where does the time go? despite improvements in network interfaces and software messaging layers, software communication overhead still dominates the hardware routing cost in most systems. in this study, we identify the sources of this overhead by analyzing software costs of typical communication protocols built atop the active messages layer on the cm-5. we show that up to 50&ndash;70% of the software messaging costs are a direct consequence of the gap between specific network features such as arbitrary delivery order, finite buffering, and limited fault-handling, and the user communication requirements of in-order delivery, end-to-end flow control, and reliable transmission. however, virtually all of these costs can be eliminated if routing networks provide higher-level services such as in-order delivery, end-to-end flow control, and packet-level fault-tolerance. we conclude that significant cost reductions require changing the constraints on messaging layers: we propose designing networks and network interfaces which simplify or replace software for implementing user communication requirements.
using registers to optimize cross-domain call performance. this paper describes a new technique to improve the performance of cross-domain calls and returns in a capability-based computer system. using register optimization information obtained from the compiler, a trusted linker can minimize the number of registers that must be saved, restored, or cleared when changing from one protection domain to another. the size of the performance gain depends on the level of trust between the calling and called protection domains. the paper presents alternate implementations for an extended vax architecture and for a risc architecture and reports performance measurements done on a re-microprogrammed vax-11/730 processor.
a vliw architecture for a trace scheduling compiler. very long instruction word (vliw) architectures were promised to deliver far more than the factor of two or three that current architectures achieve from overlapped execution. using a new type of compiler which compacts ordinary sequential code into long instruction words, a vliw machine was expected to provide from ten to thirty times the performance of a more conventional machine built of the same implementation technology.multiflow computer, inc., has now built a vliw called the tracetm along with its companion trace schedulingtm compacting compiler. this new machine has fulfilled the performance promises that were made. using many fast functional units in parallel, this machine extends some of the basic reduced-instruction-set precepts: the architecture is load/store, the microarchitecture is exposed to the compiler, there is no microcode, and there is almost no hardware devoted to synchronization, arbitration, or interlocking of any kind (the compiler has sole responsibility for runtime resource usage).this paper discusses the design of this machine and presents some initial performance results.
effective null pointer check elimination utilizing hardware trap. we present a new algorithm for eliminating null pointer checks from programs written in java&trade;. our new algorithm is split into two phases. in the first phase, it moves null checks backward, and it is iterated for a few times with other optimizations to eliminate redundant null checks and maximize the effectiveness of other optimizations. in the second phase, it moves null checks forward and converts many null checks to hardware traps in order to minimize the execution cost of the remaining null checks. as a result, it eliminates many null checks effectively and exploits the maximum use of hardware traps. this algorithm has been implemented in the ibm cross-platform java just-in-time (jit) compiler. our experimental results show that our approach improves performance by up to 71% for jbytemark and up to 10% for specjvm98 over the previously known best algorithm. they also show that it increases jit compilation time by only 2.3%. although we implemented our algorithm for java, it is also applicable for other languages requiring null checking.
micro-optimization of floating point operations. this paper describes micro-optimization, a technique for reducing the operation count and time required to perform floating-point calculations. micro-optimization involves breaking floating-point operations into their constituent micro-operations and optimizing the resulting code. exposing micro-operations to the compiler creates many opportunities for optimization. redundant normalization operations can be eliminated or combined. also, scheduling micro-operations separately allows dependent operations to be partially overlapped. a prototype expression compiler has been written to evaluate a number of micro-optimizations. on a set of benchmark expressions operation count is reduced by 33% and execution time is reduced by 40%.
the effect of instruction set complexity on program size and memory performance. one potential disadvantage of a machine with a reduced instruction set is that object programs may be substantially larger than those for a machine with a richer, more complex instruction set. the main reason is that a small instruction set will require more instructions to implement the same function. in addition, the tendency of risc machines to use fixed length instructions with a few instruction formats also increases object program size. it has been conjectured that the resulting larger programs could adversely affect memory performance and bus traffic. in this paper we report the results of a set of experiments to isolate and determine the effect of instruction set complexity on cache memory performance and bus traffic. three high-level language compilers were constructed for machines with instruction sets of varying degrees of complexity. using a set of benchmark programs, we evaluated the effect of instruction set complexity had on program size. five of the programs were used to perform a set of trace-driven simulations to study each machine's cache and bus performance. while we found that the miss ratio is affected by object program size, it appears that this can be corrected by simplying increasing the size of the cache. our measurements of bus traffic, however, show that even with large caches, machines with simple instruction sets can expect substantially more main memory reads than machines with dense object programs.
a risc architecture for symbolic computation. the g-machine is a language-directed processor architecture designed to support graph reduction as a model of computation. it can carry out lazy evaluation of functional language programs and can evaluate programs in which logical variables are used. to support these language features, the abstract machine requires tagged memory and executes some rather complex instructions, such as to evaluate a function application.this paper explores an implementation of the g-machine as a high performance risc architecture. complex instructions can be represented by risc code without experiencing a large expansion of code volume. the instruction pipeline is discussed in some detail. the processor is intended to be integrated into a standard, 32-bit memory architecture. tagged memory is supported by aggregating data with tags in a cache.
overlapped loop support in the cydra 5. the cydratm 5 architecture adds unique support for overlapping successive iterations of a loop to a very long instruction word (vliw) base. this architecture allows highly parallel loop execution for a much larger class of loops than can be vectorized, without requiring the unrolling of loops usually used by compilers for vliw machines. this paper discusses the cydra 5 loop scheduling model, the special architectural features which support it, and the loop compilation techniques used to take full advantage of the architecture.
the effect of sharing on the cache and bus performance of parallel programs. bus bandwidth ultimately limits the performance, and therefore the scale, of bus-based, shared memory multiprocessors. previous studies have extrapolated from uniprocessor measurements and simulations to estimate the performance of these machines. in this study, we use traces of parallel programs to evaluate the cache and bus performance of shared memory multiprocessors, in which coherency is maintained by a write-invalidate protocol. in particular, we analyze the effect of sharing overhead on cache miss ratio and bus utilization. our studies show that parallel programs incur substantially higher miss ratios and bus utilization than comparable uniprocessor programs. the sharing component of these metrics proportionally increases with both cache and block size, and for some cache configurations determines both their magnitude and trend. the amount of overhead depends on the memory reference pattern to the shared data. programs that exhibit good per-processor-locality perform better than those with fine-grain-sharing. this suggests that parallel software writers and better compiler technology can improve program performance through better memory organization of shared data.
a message driven or-parallel machine. a message driven architecture for the execution of or-parallel logic languages is proposed. the computational model is based on well known compilation techniques for logic languages. we present first the multiple binding mechanism for the or-parallel prolog architecture and the corresponding or-parallel abstract machine is described. a scheduling algorithm which does not rely upon the availability of global data structures to direct the search for work is discussed. the message driven processor, the processing node of the parallel machine, is designed to interact with a shared global address space and to efficiently process messages from other processing nodes. we discuss some of the results obtained from a high level functional simulator of the message driven machine.
an adaptive, non-uniform cache structure for wire-delay dominated on-chip caches. growing wire delays will force substantive changes in the designs of large caches. traditional cache architectures assume that each level in the cache hierarchy has a single, uniform access time. increases in on-chip communication delays will make the hit time of large on-chip caches a function of a line's physical location within the cache. consequently, cache access times will become a continuum of latencies rather than a single discrete latency. this non-uniformity can be exploited to provide faster access to cache lines in the portions of the cache that reside closer to the processor. in this paper, we evaluate a series of cache designs that provides fast hits to multi-megabyte cache memories. we first propose physical designs for these non-uniform cache architectures (nucas). we extend these physical designs with logical policies that allow important data to migrate toward the processor within the same level of the cache. we show that, for multi-megabyte level-two caches, an adaptive, dynamic nuca design achieves 1.5 times the ipc of a uniform cache architecture of any size, outperforms the best static nuca scheme by 11%, outperforms the best three-level hierarchy--while using less silicon area--by 13%, and comes within 13% of an ideal minimal hit latency solution.
deconstructing storage arrays. we introduce shear, a user-level software tool that characterizes raid storage arrays. shear employs a set of controlled algorithms combined with statistical techniques to automatically determine the important properties of a raid system, including the number of disks, chunk size, level of redundancy, and layout scheme. we illustrate the correctness of shear by running it upon numerous simulated configurations, and then verify its real-world applicability by running shear on both software-based and hardware-based raid systems. finally, we demonstrate the utility of shear through three case studies. first, we show how shear can be used in a storage management environment to verify raid construction and detect failures. second, we demonstrate how shear can be used to extract detailed characteristics about the individual disks within an array. third, we show how an operating system can use shear to automatically tune its storage subsystems to specific raid configurations.
increasing web server throughput with network interface data caching. this paper introduces network interface data caching, a new technique to reduce local interconnect traffic on networking servers by caching frequently-requested content on a programmable network interface. the operating system on the host cpu determines which data to store in the cache and for which packets it should use data from the cache. to facilitate data reuse across multiple packets and connections, the cache only stores application-level response content (such as http data), with application-level and networking headers generated by the host cpu. network interface data caching can reduce pci traffic by up to 57% on a prototype implementation of a uniprocessor web server. this traffic reduction results in up to 31% performance improvement, leading to a peak server throughput of 1571 mb/s.
scalable selective re-execution for edge architectures. pipeline flushes are becoming increasingly expensive in modern microprocessors with large instruction windows and deep pipelines. selective re-execution is a technique that can reduce the penalty of mis-speculations by re-executing only instructions affected by the mis-speculation, instead of all instructions. in this paper we introduce a new selective re-execution mechanism that exploits the properties of a dataflow-like explicit data graph execution (edge) architecture to support efficient mis-speculation recovery, while scaling to window sizes of thousands of instructions with high performance. this distributed selective re-execution (dsre) protocol permits multiple speculative waves of computation to be traversing a dataflow graph simultaneously, with a commit wave propagating behind them to ensure correct execution. we evaluate one application of this protocol to provide efficient recovery for load-store dependence speculation. unlike traditional dataflow architectures which resorted to single-assignment memory semantics, the dsre protocol combines dataflow execution with speculation to enable high performance and conventional sequential memory semantics. our experiments show that the dsre protocol results in an average 17% speedup over the best dependence predictor proposed to date, and obtains 82% of the performance possible with a perfect oracle directing the issue of loads.
design and evaluation of compiler algorithms for pre-execution. pre-execution is a promising latency tolerance technique that uses one or more helper threads running in spare hardware contexts ahead of the main computation to trigger long-latency memory operations early, hence absorbing their latency on behalf of the main computation. this paper investigates a source-to-source c compiler for extracting pre-execution thread code automatically, thus relieving the programmer or hardware from this onerous task. at the heart of our compiler are three algorithms. first, program slicing removes non-critical code for computing cache-missing memory references, reducing pre-execution overhead. second, prefetch conversion replaces blocking memory references with non-blocking prefetch instructions to minimize pre-execution thread stalls. finally, threading scheme selection chooses the best scheme for initiating pre-execution threads, speculatively parallelizing loops to generate thread-level parallelism when necessary for latency tolerance. we prototyped our algorithms using the stanford university intermediate format (suif) framework and a publicly available program slicer, called unravel [13], and we evaluated our compiler on a detailed architectural simulator of an smt processor. our results show compiler-based pre-execution improves the performance of 9 out of 13 applications, reducing execution time by 22.7%. across all 13 applications, our technique delivers an average speedup of 17.0%. these performance gains are achieved fully automatically on conventional smt hardware, with only minimal modifications to support pre-execution threads.
register allocation for free: the c machine stack cache. the bell labs c machine project is investigating computer architectures to support the c programming language.1 one of the goals is to match an efficient architecture to the language and the compiler technology available. measurements of different c programs show that roughly one out of every twenty instructions executed is either a procedure call or return.2 procedure call overhead is therefore a very important consideration in the overall machine design. a second and related area of primary concern in overall machine efficiency is the register allocation strategy. while use of additional registers can offer considerable improvement in execution times, adding registers usually has the adverse effects of increasing the procedure call overhead due to register saving and creating an undue burden on the compiler. in this paper we describe a piece of the c machine architecture which effectively eliminates the register allocation problem, and improves procedure calling by drastically reducing storage references required by traditional register saving. the technique can be generalized for other languages and architectures, though we will only directly address those issues involving the c language.
enabling trusted software integrity. preventing execution of unauthorized software on a given computer plays a pivotal role in system security. the key problem is that although a program at the beginning of its execution can be verified as authentic, while running, its execution flow can be redirected to externally injected malicious code using, for example, a buffer overflow exploit. existing techniques address this problem by trying to detect the intrusion at run-time or by formally verifying that the software is not prone to a particular attack.we take a radically different approach to this problem. we aim at intrusion prevention as the core technology for enabling secure computing systems. intrusion prevention systems force an adversary to solve a computationally hard task in order to create a binary that can be executed on a given machine. in this paper, we present an exemplary system--spef--a combination of architectural and compilation techniques that ensure software integrity at run-time. spef embeds encrypted, processor-specific constraints into each block of instructions at software installation time and then verifies their existence at run-time. thus, the processor can execute only properly installed programs, which makes installation the only system gate that needs to be protected. we have designed a spef prototype based on the arm instruction set and validated its impact on security and performance using the mediabench suite of applications.
evaluation of architectural support for global address-based communication in large-scale parallel machines. large-scale parallel machines are incorporating increasingly sophisticated architectural support for user-level messaging and global memory access. we provide a systematic evaluation of a broad spectrum of current design alternatives based on our implementations of a global address language on the thinking machines cm-5, intel paragon, meiko cs-2, cray t3d, and berkeley now. this evaluation includes a range of compilation strategies that make varying use of the network processor; each is optimized for the target architecture and the particular strategy. we analyze a family of interacting issues that determine the performance trade-offs in each implementation, quantify the resulting latency, overhead, and bandwidth of the global access operations, and demonstrate the effects on application performance.
programming language optimizations for modular router configurations. networking systems such as ensemble, the x-kernel, scout, and click achieve flexibility by building routers and other packet processors from modular components. unfortunately, component designs are often slower than purpose-built code, and routers in particular have stringent efficiency requirements. this paper addresses the efficiency problems of one component-based router, click, through optimization tools inspired in part by compiler optimization passes. this pragmatic approach can result in significant performance improvements; for example, the combination of three optimizations reduces the amount of cpu time click requires to process a packet in a simple ip router by 34%. we present several optimization tools, describe how those tools affected the design of click itself, and present detailed evaluations of click's performance with and without optimization.
the performance impact of flexibility in the stanford flash multiprocessor. a flexible communication mechanism is a desirable feature in multiprocessors because it allows support for multiple communication protocols, expands performance monitoring capabilities, and leads to a simpler design and debug process. in the stanford flash multiprocessor, flexibility is obtained by requiring all transactions in a node to pass through a programmable node controller, called magic. in this paper, we evaluate the performance costs of flexibility by comparing the performance of flash to that of an idealized hardwired machine on representative parallel applications and a multiprogramming workload. to measure the performance of flash, we use a detailed simulator of the flash and magic designs, together with the code sequences that implement the cache-coherence protocol. we find that for a range of optimized parallel applications the performance differences between the idealized machine and flash are small. for these programs, either the miss rates are small or the latency of the programmable protocol can be hidden behind the memory access time. for applications that incur a large number of remote misses or exhibit substantial hot-spotting, performance is poor for both machines, though the increased remote access latencies or the occupancy of magic lead to lower performance for the flexible design. in most cases, however, flash is only 2%&ndash;12% slower than the idealized machine.
overlapping execution with transfer using non-strict execution for mobile programs. in order to execute a program on a remote computer, it mustfirst be transferred over a network. this transmission incurs the over-head of network latency before execution can begin. this latency can vary greatly depending upon the size of the program., where it is located (e.g., on a local network or across the internet), and the bandwidth available to retrieve the program. existing technologies, like java, require that a jle be filly transferred before it can start executing. for large files and low bandwidth lines, this delay can be significant.in this paper we propose and evaluate a non-strict form of mobile program execution. a mobile program is any program that is transferred to a different machine and executed. the goal of nonstrict execution is to overlap execution with transfer; allowing the program to start executing as soon as possible. non-strict execution allows a procedure in the program to start executing as soon as its code and data have transferred. to enable this technology, we examine several techniques for rearranging procedures and reorganizing the data inside java classjles. our results show that nonstrict execution decreases the initial transfer delay between 31% and 56% on average, with an average reduction in overall execution time between 25% and 40%.
on a general property of memory mapping tables. the paper shows that memory mapping tables can be used to implement the display registers used in providing architectural support for block-structured languages such as algol 60. this allows full lexical level addressing to be implemented on so-called von-neuman machines. the problems of fragmentation of the paged address space are explored, and machines with memory mapping schemes capable of supporting the proposals identified. attention is drawn to the similarity between segmented and paged schemes, and it is suggested that the latter may be used to support the former.
formal online methods for voltage/frequency control in multiple clock domain microprocessors. multiple clock domain (mcd) processors are a promising future alternative to today's fully synchronous designs. dynamic voltage and frequency scaling (dvfs) in an mcd processor has the extra flexibility to adjust the voltage and frequency in each domain independently. most existing dvfs approaches are profile-based offline schemes which are mainly suitable for applications whose execution char-acteristics are constrained and repeatable. while some work has been published about online dvfs schemes, the prior approaches are typically heuristic-based. in this paper, we present an effective online dvfs scheme for an mcd processor which takes a formal analytic approach, is driven by dynamic workloads, and is suitable for all applications. in our approach, we model an mcd processor as a queue-domain network and the online dvfs as a feedback control problem with issue queue occupancies as feedback signals. a dynamic stochastic queuing model is first proposed and linearized through an accu-rate linearization technique. a controller is then designed and verified by stability analysis. finally we evaluate our dvfs scheme through a cycle-accurate simulation with a broad set of applications selected from mediabench and spec2000 benchmark suites. compared to the best-known prior approach, which is heuristic-based, the proposed online dvfs scheme is substantially more effective due to its automatic regulation ability. for example, we have achieved a 2-3 fold increase in efficiency in terms of energy-delay product improvement. in addition, our control theoretic technique is more resilient, requires less tuning effort, and has better scalability as compared to prior online dvfs schemes.we believe that the techniques and methodology described in this paper can be generalized for energy control in processors other than mcd, such as tiled stream processors.
oceanstore: an architecture for global-scale persistent storage. oceanstore is a utility infrastructure designed to span the globe and provide continuous access to persistent information. since this infrastructure is comprised of untrusted servers, data is protected through redundancy and cryptographic techniques. to improve performance, data is allowed to be cached anywhere, anytime. additionally, monitoring of usage patterns allows adaptation to regional outages and denial of service attacks; monitoring also enhances performance through pro-active movement of data. a prototype implementation is currently under development.
the structure and performance of interpreters. interpreted languages have become increasingly popular due to demands for rapid program development, ease of use, portability, and safety. beyond the general impression that they are "slow," however, little has been documented about the performance of interpreters as a class of applications.this paper examines interpreter performance by measuring and analyzing interpreters from both software and hardware perspectives. as examples, we measure the mipsi, java, perl, and tcl interpreters running an array of micro and macro benchmarks on a dec alpha platform. our measurements of these interpreters relate performance to the complexity of the interpreter's virtual machine and demonstrate that native runtime libraries can play a key role in providing good performance. from an architectural perspective, we show that interpreter performance is primarily a function of the interpreter itself and is relatively independent of the application being interpreted. we also demonstrate that high-level interpreters' demands on processor resources are comparable to those of other complex compiled programs, such as gcc. we conclude that interpreters, as a class of applications, do not currently motivate special hardware support for increased performance.
closing the window of vulnerability in multiphase memory transactions. multiprocessor architects have begun to explore several mechanisms such as prefetching, context-switching and software-assisted dynamic cache-coherence, which transform single-phase memory transactions in conventional memory systems into multiphase operations. multiphase operations introduce a window of vulnerability in which data can be invalidated before it is used. losing data due to invalidations introduces damaging livelock situations. this paper discusses the origins of the window of vulnerability and proposes an architectural framework that closes it. the framework is implemented in alewife, a large-scale multi-processor being built at mit.
fast out-of-order processor simulation using memoization. our new out-of-order processor simulatol; fastsim, uses two innovations to speed up simulation 8--15 times (vs. wisconsin simplescalar) with no loss in simulation accuracy. first, fastsim uses speculative direct-execution to accelerate the functional emulation of speculatively executed program code. second, it uses a variation on memoization---a well-known technique in programming language implementation---to cache microarchitecture states and the resulting simulator actions, and then "fast forwards" the simulation the next time a cached state is reached. fast-forwarding accelerates simulation by an order of magnitude, while producing exactly the same, cycle-accurate result as conventional simulation.
fine-grain access control for distributed shared memory. this paper discusses implementations of fine-grain memory access control, which selectively restricts reads and writes to cache-block-sized memory regions. fine-grain access control forms the basis of efficient cache-coherent shared memory. this paper focuses on low-cost implementations that require little or no additional hardware. these techniques permit efficient implementation of shared memory on a wide range of parallel systems, thereby providing shared-memory codes with a portability previously limited to message passing.this paper categorizes techniques based on where access control is enforced and where access conflicts are handled. we incorporated three techniques that require no additional hardware into blizzard, a system that supports distributed shared memory on the cm-5. the first adds a software lookup before each shared-memory reference by modifying the program's executable. the second uses the memory's error correcting code (ecc) as cache-block valid bits. the third is a hybrid. the software technique ranged from slightly faster to two times slower than the ecc approach. blizzard's performance is roughly comparable to a hardware shared-memory machine. these results argue that clusters of workstations or personal computers with networks comparable to the cm-5's will be able to support the same shared-memory interfaces as supercomputers.
fast procedure calls. a mechanism for control transfers should handle a variety of applications (e.g., procedure calls and returns, coroutine transfers, exceptions, process switches) in a uniform way. it should also allow an implementation in which the common cases of procedure call and return are extremely fast, preferably as fast as unconditional jumps in the normal case. this paper describes such a mechanism and methods for its efficient implementation.
synchronization and communication in the t3e multiprocessor. this paper describes the synchronization and communication primitives of the cray t3e multiprocessor, a shared memory system scalable to 2048 processors. we discuss what we have learned from the t3d project (the predecessor to the t3e) and the rationale behind changes made for the t3e. we include performance measurements for various aspects of communication and synchronization.the t3e augments the memory interface of the dec 21164 microprocessor with a large set of explicitly-managed, external registers (e-registers). e-registers are used as the source or target for all remote communication. they provide a highly pipelined interface to global memory that allows dozens of requests per processor to be outstanding. through e-registers, the t3e provides a rich set of atomic memory operations and a flexible, user-level messaging facility. the t3e also provides a set of virtual hardware barrier/eureka networks that can be arbitrarily embedded into the 3d torus interconnect.
lcm: memory system support for parallel language implementation. higher-level parallel programming languages can be difficult to implement efficiently on parallel machines. this paper shows how a flexible, compiler-controlled memory system can help achieve good performance for language constructs that previously appeared too costly to be practical.our compiler-controlled memory system is called loosely coherent memory (lcm). it is an example of a larger class of reconcilable shared memory (rsm) systems, which generalize the replication and merge policies of cache-coherent shared-memory. rsm protocols differ in the action taken by a processor in response to a request for a location and the way in which a processor reconciles multiple outstanding copies of a location. lcm memory becomes temporarily inconsistent to implement the semantics of c** parallel functions efficiently. rsm provides a compiler with control over memory-system policies, which it can use to implement a language's semantics, improve performance, or detect errors. we illustrate the first two points with lcm and our compiler for the data-parallel language c**.
segregating heap objects by reference behavior and lifetime. dynamic storage allocation has become increasingly important in many applications, in part due to the use of the object-oriented paradigm. at the same time, processor speeds are increasing faster than memory speeds and programs are increasing in size faster than memories. in this paper, we investigate efforts to predict heap object reference and lifetime behavior at the time objects are allocated. our approach uses profile-based optimization, and considers a variety of different information sources present at the time of object allocation to predict the object's reference frequency and lifetime. our results, based on measurements of six allocation intensive programs, show that program references to heap objects are highly predictable and that our prediction methods can successfully predict the behavior of these heap objects. we show that our methods can decrease the page fault rate of the programs measured, sometimes dramatically, in cases where the physical memory available to the program is constrained.
interleaving: a multithreading technique targeting multiprocessors and workstations. there is an increasing trend to use commodity microprocessors as the compute engines in large-scale multiprocessors. however, given that the majority of the microprocessors are sold in the workstation market, not in the multiprocessor market, it is only natural that architectural features that benefit only multiprocessors are less likely to be adopted in commodity microprocessors. in this paper, we explore multiple-context processors, an architectural technique proposed to hide the large memory latency in multiprocessors. we show that while current multiple-context designs work reasonably well for multiprocessors, they are ineffective in hiding the much shorter uniprocessor latencies using the limited parallelism found in workstation environments. we propose an alternative design that combines the best features of two existing approaches, and present simulation results that show it yields better performance for both multiprogrammed workloads on a workstation and parallel applications on a multiprocessor. by addressing the needs of the workstation environment, our proposal makes multiple contexts more attractive for commodity microprocessors.
multiple-block ahead branch predictors. a basic rule in computer architecture is that a processor cannot execute an application faster than it fetches its instructions. this paper presents a novel cost-effective mechanism called the two-block ahead branch predictor. information from the current instruction block is not used for predicting the address of the next instruction block, but rather for predicting the block following the next instruction block.this approach overcomes the instruction fetch bottle-neck exhibited by wide-dispatch "brainiac" processors by enabling them to efficiently predict addresses of two instruction blocks in a single cycle. furthermore, pipelining the branch prediction process can also be done by means of our predictor for "speed demon" processors to achieve higher clock rate or to improve the prediction accuracy by means of bigger prediction structures.moreover, and unlike the previously-proposed multiple predictor schemes, multiple-block ahead branch predictors can use any of the branch prediction schemes to perform the very accurate predictions required to achieve high-performance on superscalar processors.
power aware page allocation. one of the major challenges of post-pc computing is the need to reduce energy consumption, thereby extending the lifetime of the batteries that power these mobile devices. memory is a particularly important target for efforts to improve energy efficiency. memory technology is becoming available that offers power management features such as the ability to put individual chips in any one of several different power modes. in this paper we explore the interaction of page placement with static and dynamic hardware policies to exploit these emerging hardware features. in particular, we consider page allocation policies that can be employed by an informed operating system to complement the hardware power management strategies. we perform experiments using two complementary simulation environments: a trace-driven simulator with workload traces that are representative of mobile computing and an execution-driven simulator with a detailed processor/memory model and a more memory-intensive set of benchmarks (spec2000). our results make a compelling case for a cooperative hardware/software approach for exploiting power-aware memory, with down to as little as 45% of the energy&bull; delay for the best static policy and 1% to 20% of the energy&bull; delay for a traditional full-power memory.
locality phase prediction. as computer memory hierarchy becomes adaptive, its performance increasingly depends on forecasting the dynamic program locality. this paper presents a method that predicts the locality phases of a program by a combination of locality profiling and run-time prediction. by profiling a training input, it identifies locality phases by sifting through all accesses to all data elements using variable-distance sampling, wavelet filtering, and optimal phase partitioning. it then constructs a phase hierarchy through grammar compression. finally, it inserts phase markers into the program using binary rewriting. when the instrumented program runs, it uses the first few executions of a phase to predict all its later executions.compared with existing methods based on program code and execution intervals, locality phase prediction is unique because it uses locality profiles, and it marks phase boundaries in program code. the second half of the paper presents a comprehensive evaluation. it measures the accuracy and the coverage of the new technique and compares it with best known run-time methods. it measures its benefit in adaptive cache resizing and memory remapping. finally, it compares the automatic analysis with manual phase marking. the results show that locality phase prediction is well suited for identifying large, recurring phases in complex programs.
space-time scheduling of instruction-level parallelism on a raw machine. increasing demand for both greater parallelism and faster clocks dictate that future generation architectures will need to decentralize their resources and eliminate primitives that require single cycle global communication. a raw microprocessor distributes all of its resources, including instruction streams, register files, memory ports, and alus, over a pipelined two-dimensional mesh interconnect, and exposes them fully to the compiler. because communication in raw machines is distributed, compiling for instruction-level parallelism (ilp) requires both spatial instruction partitioning as well as traditional temporal instruction scheduling. in addition, the compiler must explicitly manage all communication through the interconnect, including the global synchronization required at branch points. this paper describes rawcc, the compiler we have developed for compiling general-purpose sequential programs to the distributed raw architecture. we present performance results that demonstrate that although raw machines provide no mechanisms for global communication the raw compiler can schedule to achieve speedups that scale with the number of available functional units.
automatically characterizing large scale program behavior. understanding program behavior is at the foundation of computer architecture and program optimization. many programs have wildly different behavior on even the very largest of scales (over the complete execution of the program). this realization has ramifications for many architectural and compiler techniques, from thread scheduling, to feedback directed optimizations, to the way programs are simulated. however, in order to take advantage of time-varying behavior, we must first develop the analytical tools necessary to automatically and efficiently analyze program behavior over large sections of execution.our goal is to develop automatic techniques that are capable of finding and exploiting the large scale behavior of programs (behavior seen over billions of instructions). the first step towards this goal is the development of a hardware independent metric that can concisely summarize the behavior of an arbitrary section of execution in a program. to this end we examine the use of basic block vectors. we quantify the effectiveness of basic block vectors in capturing program behavior across several different architectural metrics, explore the large scale behavior of several programs, and develop a set of algorithms based on clustering capable of analyzing this behavior. we then demonstrate an application of this technology to automatically determine where to simulate for a program to help guide computer architecture research.
evolving rpc for active storage. we introduce scriptable rpc (srpc), an rpc-based framework that enables distributed system services to take advantage of active components. technology trends point to a world where each component in a system (whether disk, network interface, or memory) has substantial computational capabilities; however, traditional methods of building distributed services are not designed to take advantage of these new architectures, mandating wholesale change of the software base to exploit more powerful hardware. in contrast, srpc provides a direct and simple migration path for traditional services into the active environment.we demonstrate the power and flexibility of the srpc framework through a series of case studies, with a focus on active storage servers. specifically, we find three advantages to our approach. first, srpc improves the performance of distributed file servers, reducing latency by combining the execution of operations at the file server. second, srpc enables the ready addition of new functionality; for example, more powerful cache consistency models can be realized on top of a server that exports a simple nfs-like interface. third, srpc simplifies the construction of distributed services; operations that are difficult to coordinate across client and server can now be co-executed at the server, thus avoiding costly agreement and crash-recovery protocols.
simple compiler algorithms to reduce ownership operhead in cache coherence protocols. we study in this paper the design and efficiency of compiler algorithms that remove ownership overhead in shared-memory multiprocessors with write-invalidate protocols. these algorithms detect loads followed by stores to the same address. such loads are marked and constitute a hint to the cache to obtain an exclusive copy of the block. we consider three algorithms where the first one focuses on load-store sequences within each basic block of code and the other two analyse the existence of load-store sequences across basic blocks at the intra-procedural level. since the dataflow analysis we adopt is a trivial variation of live-variable analysis, the algorithms are easily incorporated into a compiler.through detailed simulations of a cache-coherent numa architecture using five scientific parallel benchmark programs, we find that the algorithms are capable of removing over 95% of the separate ownership acquisitions. moreover, we also find that even the simplest algorithm is comparable in efficiency with previously proposed hardware-based adaptive cache coherence protocols to attack the same problem.
petal: distributed virtual disks. the ideal storage system is globally accessible, always available, provides unlimited performance and capacity for a large number of clients, and requires no management. this paper describes the design, implementation, and performance of petal, a system that attempts to approximate this ideal in practice through a novel combination of features. petal consists of a collection of network-connected servers that cooperatively manage a pool of physical disks. to a petal client, this collection appears as a highly available block-level storage system that provides large abstract containers called virtual disks. a virtual disk is globally accessible to all petal clients on the network. a client can create a virtual disk on demand to tap the entire capacity and performance of the underlying physical resources. furthermore, additional resources, such as servers and disks, can be automatically incorporated into petal.we have an initial petal prototype consisting of four 225 mhz dec 3000/700 workstations running digital unix and connected by a 155 mbit/s atm network. the prototype provides clients with virtual disks that tolerate and recover from disk, server, and network failures. latency is comparable to a locally attached disk, and throughput scales with the number of servers. the prototype can achieve i/o rates of up to 3150 requests/sec and bandwidth up to 43.1 mbytes/sec.
temporally silent stores. recent work has shown that silent stores--stores which write a value matching the one already stored at the memory location--occur quite frequently and can be exploited to reduce memory traffic and improve performance. this paper extends the definition of silent stores to encompass sets of stores that change the value stored at a memory location, but only temporarily, and subsequently return a previous value of interest to the memory location. the stores that cause the value to revert are called temporally silent stores. we redefine multiprocessor sharing to account for temporal silence and show that in the limit, up to 45% of communication misses in scientific and commercial applications can be eliminated by exploiting values that change only temporarily. we describe a practical mechanism that detects temporally silent stores and removes the coherence traffic they cause in conventional multiprocessors. we find that up to 42% of communication misses can be eliminated with a simple extension to the mesi protocol. further, we examine application and operating system code to provide insight into the temporal silence phenomenon and characterize temporal silence by examining value frequencies and dynamic instruction distances between temporally silent pairs. these studies indicate that the operating system is involved heavily in temporal silence, in both commercial and scientific workloads, and that while detectable synchronization primitives provide substantial contributions, significant opportunity exists outside these references.
parallel computers for graphics applications. specialized computer architectures can provide better price/performance for executing image processing and graphics applications than general purpose designs. two processors are presented that use parallel simd data paths to support common graphics data structures as primitive operands in arithmetic expressions. a variant of the c language has been implemented to allow high level language coding of user applications on these processors. high level programming support is designed into the processor architecture that implements parallel object data typing and parallel conditional evaluation in hardware.
efficient superscalar performance through boosting. the foremost goal of superscalar processor design is to increase performance through the exploitation of instruction-level parallelism (ilp). previous studies have shown that speculative execution is required for high instruction per cycle (ipc) rates in non-numerical applications. the general trend has been toward supporting speculative execution in complicated, dynamically-scheduled processors. performance, though, is more than just a high ipc rate; it also depends upon instruction count and cycle time. boosting is an architectural technique that supports general speculative execution in simpler, statically-scheduled processors. boosting labels speculative instructions with their control dependence information. this labelling eliminates control dependence constraints on instruction scheduling while still providng full dependence information to the hardware. we have incorporated boosting into a trace-based, global scheduling algorithm that exploits ilp without adversely affecting the instruction count of a program. we use this algorithm and estimates of the boosting hardware involved to evaluate how much speculative execution support is really necessary to achieve good performance. we find that a statically-scheduled superscalar processor using a minimal implementation of boosting can easily reach the performance of a much more complex dynamically-scheduled superscalar processor.
limits on multiple instruction issue. this paper investigates the limitations on designing a processor which can sustain an execution rate of greater than one instruction per cycle on highly-optimized, non-scientific applications. we have used trace-driven simulations to determine that these applications contain enough instruction independence to sustain an instruction rate of about two instructions per cycle. in a straightforward implementation, cost considerations argue strongly against decoding more than two instructions in one cycle. given this constraint, the efficiency in instruction fetching rather than the complexity of the execution hardware limits the concurrency attainable at the instruction level.
understanding and improving operating system effects in control flow prediction. many modern applications result in a significant operating system (os) component. the os component has several implications including affecting the control flow transfer in the execution environment. this paper focuses on understanding the operating system effects on control flow transfer and prediction, and designing architectural support to alleviate the bottlenecks. we characterize the control flow transfer of several emerging applications on a commercial operating system. we find that the exception-driven, intermittent invocation of os code and the user/os branch history interference increase the misprediction in both user and kernel code.we propose two simple os-aware control flow prediction techniques to alleviate the destructive impact of user/os branch interference. the first one consists of capturing separate branch correlation information for user and kernel code. the second one involves using separate branch prediction tables for user and kernel code. we study the improvement contributed by the os-aware prediction to various branch predictors ranging from simple gshare to more elegant agree, multi-hybrid and bi-mode predictors. on 32k entries predictors, incorporating os-aware techniques yields up to 34%, 23%, 27% and 9% prediction accuracy improvement in gshare, multi-hybrid, agree and bi-mode predictors, resulting in up to 8% execution speedup.
fingerprinting: bounding soft-error detection latency and bandwidth. fingerprinting summarizes the history of internal processor state updates into a cryptographic signature. the processors in a dual modular redundant pair periodically exchange and compare fingerprints to corroborate each other's correctness. relative to other techniques, fingerprinting offers superior error coverage and significantly reduces the error-detection latency and bandwidth.
performance directed energy management for main memory and disks. much research has been conducted on energy management for memory and disks. most studies use control algorithms that dynamically transition devices to low power modes after they are idle for a certain threshold period of time. the control algorithms used in the past have two major limitations. first, they require painstaking, application-dependent manual tuning of their thresholds to achieve energy savings without significantly degrading performance. second, they do not provide performance guarantees. in one case, they slowed down an application by 835.this paper addresses these two limitations for both memory and disks, making memory/disk energy-saving schemes practical enough to use in real systems. specifically, we make three contributions: (1) we propose a technique that provides a performance guarantee for control algorithms. we show that our method works well for all tested cases, even with previously proposed algorithms that are not performance-aware. (2) we propose a new control algorithm, performance-directed dynamic (pd), that dynamically adjusts its thresholds periodically, based on available slack and recent workload characteristics. for memory, pd consumes the least energy, when compared to previous hand-tuned algorithms combined with a performance guarantee. however, for disks, pd is too complex and its self-tuning is unable to beat previous hand-tuned algorithms. (3) to improve on pd, we propose a simple, optimization-based, threshold-free control algorithm, performance-directed static (ps). ps periodically assigns a static configuration by solving an optimization problem that incorporates information about the available slack and recent traffic variability to different chips/disks. we find that ps is the best or close to the best across all performanceguaranteed disk algorithms, including hand-tuned versions.
symbiotic jobscheduling for a simultaneous multithreading processor. simultaneous multithreading machines fetch and execute instructions from multiple instruction streams to increase system utilization and speedup the execution of jobs. when there are more jobs in the system than there is hardware to support simultaneous execution, the operating system scheduler must choose the set of jobs to coschedulethis paper demonstrates that performance on a hardware multithreaded processor is sensitive to the set of jobs that are coscheduled by the operating system jobscheduler. thus, the full benefits of smt hardware can only be achieved if the scheduler is aware of thread interactions. here, a mechanism is presented that allows the scheduler to significantly raise the performance of smt architectures. this is done without any advance knowledge of a workload's characteristics, using sampling to identify jobs which run well together.we demonstrate an smt jobscheduler called sos. sos combines an overhead-free sample phase which collects information about various possible schedules, and a symbiosis phase which uses that information to predict which schedule will provide the best performance. we show that a small sample of the possible schedules is sufficient to identify a good schedule quickly. on a system with random job arrivals and departures, response time is improved as much as 17% over a schedule which does not incorporate symbiosis.
architectural support for copy and tamper resistant software. although there have been attempts to develop code transformations that yield tamper-resistant software, no reliable software-only methods are known. this paper studies the hardware implementation of a form of execute-only memory (xom) that allows instructions stored in memory to be executed but not otherwise manipulated. to support xom code we use a machine that supports internal compartments---a process in one compartment cannot read data from another compartment. all data that leaves the machine is encrypted, since we assume external memory is not secure. the design of this machine poses some interesting trade-offs between security, efficiency, and flexibility. we explore some of the potential security issues as one pushes the machine to become more efficient and flexible. although security carries a performance penalty, our analysis indicates that it is possible to create a normal multi-tasking machine where nearly all applications can be run in xom mode. while a virtual xom machine is possible, the underlying hardware needs to support a unique private key, private memory, and traps on cache misses. for efficient operation, hardware assist to provide fast symmetric ciphers is also required.
an empirical analysis of instruction repetition. we study the phenomenon of instruction repetition, where the inputs and outputs of multiple dynamic instances of a static instruction are repeated. we observe that over 80% of the dynamic instructions executed in several programs are repeated and most of the repetition is due to a small number of static instructions. we attempt understand the source of this repetitive behavior by categorizing dynamic program instructions into dynamic program slices at both a global level and a local (within function) level. we observe that repeatability is more an artifact of how computation is expressed, and less of program inputs. function-level analysis suggests that many functions are called with repeated arguments, though almost all of them have side effects. we provide commentary on exploiting the observed phenomenon and its sources in both software and hardware.
reactive synchronization algorithms for multiprocessors. synchronization algorithms that are efficient across a wide range of applications and operating conditions are hard to design because their performance depends on unpredictable run-time factors. the designer of a synchronization algorithm has a choice of protocols to use for implementing the synchronization operation. for example, candidate protocols for locks include test-and-set protocols and queueing protocols. frequently, the best choice of protocols depends on the level of contention: previous research has shown that test-and-set protocols for locks outperform queueing protocols at low contention, while the opposite is true at high contention.this paper investigates reactive synchronization algorithms that dynamically choose protocols in response to the level of contention. we describe reactive algorithms for spin locks and fetch-and-op that choose among several shared-memory and message-passing protocols. dynamically choosing protocols presents a challenge: a reactive algorithm needs to select and change protocols efficiently, and has to allow for the possibility that multiple processes may be executing different protocols at the same time. we describe the notion of consensus objects that the reactive algorithms use to preserve correctness in the face of dynamic protocol changes.experimental measurements demonstrate that reactive algorithms perform close to the best static choice of protocols at all levels of contention. furthermore, with mixed levels of contention, reactive algorithms outperform passive algorithms with fixed protocols, provided that contention levels do not change too frequently. measurements of several parallel applications show that reactive algorithms result in modest performance gains for spin locks and significant gains for fetch-and-op.
value locality and load value prediction. since the introduction of virtual memory demand-paging and cache memories, computer systems have been exploiting spatial and temporal locality to reduce the average latency of a memory reference. in this paper, we introduce the notion of value locality, a third facet of locality that is frequently present in real-world programs, and describe how to effectively capture and exploit it in order to perform load value prediction. temporal and spatial locality are attributes of storage locations, and describe the future likelihood of references to those locations or their close neighbors. in a similar vein, value locality describes the likelihood of the recurrence of a previously-seen value within a storage location. modern processors already exploit value locality in a very restricted sense through the use of control speculation (i.e. branch prediction), which seeks to predict the future value of a single condition bit based on previously-seen values. our work extends this to predict entire 32- and 64-bit register values based on previously-seen values. we find that, just as condition bits are fairly predictable on a per-static-branch basis, full register values being loaded from memory are frequently predictable as well. furthermore, we show that simple microarchitectural enhancements to two modern microprocessor implementations (based on the powerpc 620 and alpha 21164) that enable load value prediction can effectively exploit value locality to collapse true dependencies, reduce average memory latency and bandwidth requirements, and provide measurable performance gains.
tradeoffs in instruction format design for horizontal architectures. with recent improvements in software techniques and the enhanced level of fine grain parallelism made available by such techniques, there has been an increased interest in horizontal architectures and large instruction words that are capable of issuing more that one operation per instruction. this paper investigates some issues in the design of such instruction formats. we study how the choice of an instruction format is influenced by factors such as the degree of pipelining and the instruction's view of the register file. our results suggest that very large instruction words capable of issuing one operation to each functional unit resource in a horizontal architecture may be overkill. restricted instruction formats with limited operation issuing capabilities are capable of providing similar performance (measured by the total number of time steps) with significantly less hardware in many cases.
devirtualizable virtual machines enabling general, single-node, online maintenance. maintenance is the dominant source of downtime at high availability sites. unfortunately, the dominant mechanism for reducing this downtime, cluster rolling upgrade, has two shortcomings that have prevented its broad acceptance. first, cluster-style maintenance over many nodes is typically performed a few nodes at a time, mak-ing maintenance slow and often impractical. second, cluster-style maintenance does not work on single-node systems, despite the fact that their unavailability during maintenance can be painful for organizations. in this paper, we propose a novel technique for online maintenance that uses virtual machines to provide maintenance on single nodes, allowing parallel maintenance over multiple nodes, and online maintenance for standalone servers. we present the microvisor, our prototype virtual machine system that is custom tailored to the needs of online maintenance. unlike general purpose virtual machine environments that induce continual 10-20% over-head, the microvisor virtualizes the hardware only during periods of active maintenance, letting the guest os run at full speed most of the time. unlike past attempts at virtual machine optimization, we do not compromise os transparency. we instead give up generality and tailor our virtual machine system to the minimum needs of online maintenance, eschewing features, such as i/o and memory virtualization, that it does not strictly require. the result is a very thin virtual machine system that induces only 5.6% cpu overhead when virtualizing the hardware, and zero cpu overhead when devirtualized. using the microvisor, we demonstrate an online os upgrade on a live, single-node web server, reducing downtime from one hour to less than one minute.
continual flow pipelines. increased integration in the form of multiple processor cores on a single die, relatively constant die sizes, shrinking power envelopes, and emerging applications create a new challenge for processor architects. how to build a processor that provides high single-thread performance and enables multiple of these to be placed on the same die for high throughput while dynamically adapting for future applications? conventional approaches for high single-thread performance rely on large and complex cores to sustain a large instruction window for memory tolerance, making them unsuitable for multi-core chips. we present continual flow pipelines (cfp) as a new non-blocking processor pipeline architecture that achieves the performance of a large instruction window without requiring cycle-critical structures such as the scheduler and register file to be large. we show that to achieve benefits of a large instruction window, inefficiencies in management of both the scheduler and register file must be addressed, and we propose a unified solution. the non-blocking property of cfp keeps key processor structures affecting cycle time and power (scheduler, register file), and die size (second level cache) small. the memory latency-tolerant cfp core allows multiple cores on a single die while outperforming current processor cores for single-thread applications.
compiler-based prefetching for recursive data structures. software-controlled data prefetching offers the potential for bridging the ever-increasing speed gap between the memory subsystem and today's high-performance processors. while prefetching has enjoyed considerable success in array-based numeric codes, its potential in pointer-based applications has remained largely unexplored. this paper investigates compiler-based prefetching for pointer-based applications---in particular, those containing recursive data structures. we identify the fundamental problem in prefetching pointer-based data structures and propose a guideline for devising successful prefetching schemes. based on this guideline, we design three prefetching schemes, we automate the most widely applicable scheme (greedy prefetching) in an optimizing research compiler, and we evaluate the performance of all three schemes on a modern superscalar processor similar to the mips r10000. our results demonstrate that compiler-inserted prefetching can significantly improve the execution speed of pointer-based codes---as much as 45% for the applications we study. in addition, the more sophisticated algorithms (which we currently perform by hand, but which might be implemented in future compilers) can improve performance by as much as twofold. compared with the only other compiler-based pointer prefetching scheme in the literature, our algorithms offer substantially better performance by avoiding unnecessary overhead and hiding more latency.
sheaved memory: architectural support for state saving and restoration in paged systems. the concept of read-one/write-many paged memory is introduced and given the name sheaved memory. it is shown that sheaved memory is useful for efficiently maintaining checkpoints in main memory and for providing state saving and state restoration for software that includes recovery blocks or similar control structures. the organization of sheaved memory is described in detail, and a design is presented for a prototype sheaved-memory module that can be built easily from inexpensive, off-the-shelf components. the module can be incorporated within many available computers without altering the computers' hardware design. the concept of sheaved memory is simple and appealing, and its potential for use in a number of software contexts is foreseen.
d-sptf: decentralized request distribution in brick-based storage systems. distributed shortest-positioning time first (d-sptf) is a request distribution protocol for decentralized systems of storage servers. d-sptf exploits high-speed interconnects to dynamically select which server, among those with a replica, should service each read request. in doing so, it simultaneously balances load, exploits the aggregate cache capacity, and reduces positioning times for cache misses. for network latencies expected in storage clusters (e.g., 10--200μs), d-sptf performs as well as would a hypothetical centralized system with the same collection of cpu, cache, and disk resources. compared to popular decentralized approaches, d-sptf achieves up to 65% higher throughput and adapts more cleanly to heterogenous server capabilities.
variable length path branch prediction. accurate branch prediction is required to achieve high performance in deeply pipelined, wide-issue processors. recent studies have shown that conditional and indirect (or computed) branch targets can be accuratelypredicted by recording the path, which consists of the target addresses of recent branches, leading up to the branch. in current path based branch predictors, the n most recent target addresses are hashed together to form an index into a table, where n is some fixed integer. the indexed table entry isused to make a prediction for the current branch.this paper introduces a new branch predictor in which the value of n is allowed to vary. by constructing the index into the table using the last n target addresses, and using profiling information to select the proper value of n for each branch, extremely accurate branch prediction is achieved. for the specint95 gee benchmark, this new predictor has a conditional branch misprediction rate of 4.3% given a 4k byte hardware budget. for comparison, the gshare predictor, a predictor known for its high accuracy, has a conditional branch misprediction rate of 8.8% given the same hardware budget. for the indirect branches in gee, the new predictor achieves a misprediction rate of 27.7% when given a hardware budget of 512 bytes, whereas the best competingpredictor achieves a misprediction rate of 44.2% when given the same hardware budget.
hardware-software trade-offs in a direct rambus implementation of the rampage memory hierarchy. the rampage memory hierarchy is an alternative to the traditional division between cache and main memory: main memory is moved up a level and dram is used as a paging device. the idea behind rampage is to reduce hardware complexity, if at the cost of software complexity, with a view to allowing more flexible memory system design. this paper investigates some issues in choosing between rampage and a conventionalcache architecture, with a view to illustrating trade-offs which can be made in choosing whether to place complexity in the memory system in hardware or in software. performance results in this paper are based on a simple rambus implementation of dram, with performance characteristics of direct rambus, which should be available in 1999. this paper explores the conditions under which it becomes feasible to perform a context switch on a miss in the rampage model, and the conditions under which rampage is a win over a conventional cache architecture: as the cpu-dram speed gap grows, rampage becomes more viable.
tags and type checking in lisp: hardware and software approaches. one of the major factors that distinguishes lisp from many other languages (pascal, c, fortran, etc.) is the need for run-time type checking. run-time type checking is implemented by adding to each data object a tag that encodes type information. tags must be compared for type compatibility, removed when using the data, and inserted when new data items are created. this tag manipulation, together with other work related to dynamic type checking and generic operations, constitutes a significant component of the execution time of lisp programs. this has led both to the development of lisp machines that support tag checking in hardware and to the avoidance of type checking by users running on stock hardware. to understand the role and necessity of special-purpose hardware for tag handling, we first measure the cost of type checking operations for a group of lisp programs. we then examine hardware and software implementations of tag operations and estimate the cost of tag handling with the different tag implementation schemes. the data shows that minimal levels of support provide most of the benefits, and that tag operations can be relatively inexpensive, even when no special hardware support is present.
firmware structure and architectural support for monitors, vertical migration and user microprogramming. this paper describes firmware and hardware support necessary for constructing easy-to-understand and high performance operating systems including language translators and interpreters. basic principles are one-to-one correspondence between logical hierarchy and physical hierarchy, and vertical migration. implementation of monitors in firmware and architectural support for it are discussed, and a sample system is shown. architectural support for user microprogramming is then discussed and an example is shown. after a total system firmware structure is discussed, an experiment of vertical migration is described. it is shown that a proper selection of modules for migration is extremely important. it is suggested that the direction shown in this paper is one of future directions of computer systems.
a real-time support processor for ada tasking. task synchronization in ada causes excessive run-time overhead due to the complex semantics of the rendezvous. to demonstrate that the speed can be increased by two orders of magnitude by using special purpose hardware, a single chip vlsi support processor has been designed. by providing predictable and uniformly low overhead for the entire semantics of a rendezvous, the powerful real-time constructs of ada can be used freely without performance degradation. the key to high performance is the set of primitive operations implemented in hardware. each operation is complex enough to replace a considerable amount of code was designed to execute with a minimum of communication overhead. task control blocks are stored on-chip as well as headers for entry, delay and ready queues. all necessary scheduling is integrated in the operations. delays are handled completely on-chip using an internal real-time clock. a multilevel design strategy, based on silicon compilation, made it possible to run actual ada programs on a functional emulator of the chip and use the results to verify the detailed design. a high degree of parallelism and pipelining together with an elaborate internal addressing scheme has reduced the number of clock cycles needed to perform each operation. using 2 &mgr;m cmos, the processor can run at 20 mhz. a complex rendezvous, including the calling sequence and all necessary scheduling, can be performed in less than 15 &mgr;s.
integer multiplication and division on the hp precision architecture. in recent years, many architectural design efforts have focused on maximizing performance for frequently executed, simple instructions. the authors describe how a small set of primitive instructions combined with what is considered careful frequency analysis and clever programming allows the hewlett-packard (hp) precision architecture integer multiplication and division implementation to provide adequate performance at little or no hardware cost.
schedule-independent storage mapping for loops. this paper studies the relationship between storage requirements and performance. storage-related dependences inhibit optimizations for locality and parallelism. techniques such as renaming and array expansion can eliminate all storage-related dependences, but do so at the expense of increased storage. this paper introduces the universal occupancy vector (uov) for loops with a regular stencil of dependences. the uov provides a schedule-independent storage reuse pattern that introduces no further dependences (other than those implied by true flow dependences). ov-mapped code requires less storage than full array expansion and only slightly more storage than schedule-dependent minimal storage.we show that determine if a vector is a uov is npcomplete. however, an easily constructed but possibly nonminimal uov can be used. we also present a branch and bound algorithm which finds the minimal uov, while still maintaining a legal uov at all times.our experimental results show that the use of ov-mapped storage, coupled with tiling for locality, achieves better performance than tiling after array expansion, and accommodates larger problem sizes than untilable, storage-optimized code. f'urthermore, storage mapping based on the uov introduces negligible runtime overhead.
sentinel scheduling for vliw and superscalar processors. speculative execution is an important source of parallelism for vliw and superscalar processors. a serious challenge with compiler-controlled speculative execution is to accurately detect and report all program execution errors at the time of occurrence. in this paper, a set of architectural features and compile-time scheduling support referred to as sentinel scheduling is introduced. sentinel scheduling provides an effective framework for compiler-controlled speculative execution that accurately detects and reports all exceptions. sentinel scheduling also supports speculative execution of store instructions by providing a store buffer which allows probationary entries. experimental results show that sentinel scheduling is highly effective for a wide range of vliw and superscalar processors.
dependance based prefetching for linked data structures. we introduce a dynamic scheme that captures the accesspat-terns of linked data structures and can be used to predict future accesses with high accuracy. our technique exploits the dependence relationships that exist between loads that produce addresses and loads that consume these addresses. by identzj+ing producer-consumer pairs, we construct a compact internal representation for the associated structure and its traversal. to achieve a prefetching eflect, a small prefetch engine speculatively traverses this representation ahead of the executing program. dependence-based prefetching achieves speedups of up to 25% on a suite of pointer-intensive programs.
coding guidelines for pipelined processors. this paper is a tutorial for assembly language programmers of pipelined processors. it describes the general characteristics of pipelined processors and presents a collection of coding guidelines for them. these guidelines are particularly significant to compiler developers who determine object code patterns.
timestamp snooping: an approach for extending smps. symmetric multiprocessor (smp) servers provide superior performance for the commercial workloads that dominate the internet. our simulation results show that over one-third of cache misses by these applications result in cache-to-cache transfers, where the data is found in another processor's cache rather than in memory. smps are optimized for this case by using snooping protocols that broadcast address transactions to all processors. conversely, directory-based shared-memory systems must indirectly locate the owner and sharers through a directory, resulting in larger average miss latencies.this paper proposes timestamp snooping, a technique that allows smps to i) utilize high-speed switched interconnection networks and ii) exploit physical locality by delivering address transactions to processors and memories without regard to order. traditional snooping requires physical ordering of transactions. timestamp snooping works by processing address transactions in a logical order. logical time is maintained by adding a few bits per address transaction and having network switches perform a handshake to ensure on-time delivery. processors and memories then reorder transactions based on their timestamps to establish a total order.we evaluate timestamp snooping with commercial workloads on a 16-processor sparc system using the simics full-system simulator. we simulate both an indirect (butterfly) and a direct (torus) network design. for oltp, dss, web serving, web searching, and one scientific application, timestamp snooping with the butterfly network runs 6-28% faster than directories, at a cost of 13-43% more link traffic. similarly, with the torus network, timestamp snooping runs 6-29% faster for 17-37% more link traffic. thus, timestamp snooping is worth considering when buying more interconnect bandwidth is easier than reducing interconnect latency.
secure program execution via dynamic information flow tracking. we present a simple architectural mechanism called dynamic information flow tracking that can significantly improve the security of computing systems with negligible performance overhead. dynamic information flow tracking protects programs against malicious software attacks by identifying spurious information flows from untrusted i/o and restricting the usage of the spurious information.every security attack to take control of a program needs to transfer the program's control to malevolent code. in our approach, the operating system identifies a set of input channels as spurious, and the processor tracks all information flows from those inputs. a broad range of attacks are effectively defeated by checking the use of the spurious values as instructions and pointers.our protection is transparent to users or application programmers; the executables can be used without any modification. also, our scheme only incurs, on average, a memory overhead of 1.4% and a performance overhead of 1.1%.
speculative synchronization: applying thread-level speculation to explicitly parallel applications. barriers, locks, and flags are synchronizing operations widely used programmers and parallelizing compilers to produce race-free parallel programs. often times, these operations are placed suboptimally, either because of conservative assumptions about the program, or merely for code simplicity.we propose speculative synchronization, which applies the philosophy behind thread-level speculation (tls) to explicitly parallel applications. speculative threads execute past active barriers, busy locks, and unset flags instead of waiting. the proposed hardware checks for conflicting accesses and, if a violation is detected, offending speculative thread is rolled back to the synchronization point and restarted on the fly. tls's principle of always keeping a safe thread is key to our proposal: in any speculative barrier, lock, or flag, the existence of one or more safe threads at all times guarantees forward progress, even in the presence of access conflicts or speculative buffer overflow. our proposal requires simple hardware and no programming effort. furthermore, it can coexist with conventional synchronization at run time.we use simulations to evaluate 5 compiler- and hand-parallelized applications. our results show a reduction in the time lost to synchronization of 34% on average, and a reduction in overall program execution time of 7.4% on average.
slipstream processors: improving both performance and fault tolerance. processors execute the full dynamic instruction stream to arrive at the final output of a program, yet there exist shorter instruction streams that produce the same overall effect. we propose creating a shorter but otherwise equivalent version of the original program by removing ineffectual computation and computation related to highly-predictable control flow. the shortened program is run concurrently with the full program on a chip multiprocessor simultaneous multithreaded processor, with two key advantages:1) improved single-program performance. the shorter program speculatively runs ahead of the full program and supplies the full program with control and data flow outcomes. the full program executes efficiently due to the communicated outcomes, at the same time validating the speculative, shorter program. the two programs combined run faster than the original program alone. detailed simulations of an example implementation show an average improvement of 7% for the spec95 integer benchmarks.2) fault tolerance. the shorter program is a subset of the full program and this partial-redundancy is transparently leveraged for detecting and recovering from transient hardware faults.
superoptimizer - a look at the smallest program. given an instruction set, the superoptimizer finds the shortest program to compute a function. startling programs have been generated, many of them engaging in convoluted bit-fiddling bearing little resemblance to the source programs which defined the functions. the key idea in the superoptimizer is a probabilistic test that makes exhaustive searches practical for programs of useful size. the search space is defined by the processor's instruction set, which may include the whole set, but it is typically restricted to a subset. by constraining the instructions and observing the effect on the output program, one can gain insight into the design of instruction sets. in addition, superoptimized programs may be used by peephole optimizers to improve the quality of generated code, or by assembly language programmers to improve manually written code.
empirical analysis of the mesa instruction set. this paper describes recent work to refine the instruction set of the mesa processor. mesa [8] is a high level systems implementation language developed at xerox parc during the middle 1970's. typical systems written in mesa are large collections of programs running on single-user machines. for this reason, a major design goal of the project has been to generate compact object programs. the computers that execute mesa programs are implementations of a stack architecture [5]. the instructions of an object program are organized into a stream of eight bit bytes. the exact complement into of instructions in the architecture has changed as the language and machine micro architecture have evolved. in sections 3 and 4, we give a short history of the mesa instruction set and discuss the motivation for our most recent analysis of it. in section 5, we discuss the tools and techniques used in this analysis. section 6 shows the results of this analysis as applied to a large sample of approximately 2.5 million instruction bytes. sections 7 and 8 give advice to others who might be contemplating similar analyses.
communication scheduling. the high arithmetic rates of media processing applications require architectures with tens to hundreds of functional units, multiple register files, and explicit interconnect between functional units and register files. communication scheduling enables scheduling to these emerging architectures, including those that use shared buses and register file ports. scheduling to these shared interconnect architectures is difficult because it requires simultaneously allocating functional units to operations and buses and register file ports to the communications between operations. prior vliw scheduling algorithms are limited to clustered register file architectures with no shared buses or register file ports. communication scheduling extends the range of target architectures by making each communication explicit and decomposing it into three components: a write stub, zero or more copy operations, and a read stub. communication scheduling allows media processing kernels to achieve 98% of the performance of a central register file architecture on a distributed register file architecture with only 9% of the area, 6% of the power consumption, and 37% of the access delay, and 120% of the performance of a clustered register file architecture on a distributed register file architecture with 56% of the area and 50% of the power consumption.
performance and architectural evaluation of the psi machine. we evaluated a prolog machine psi (personal sequential inference machine) for the purpose of improving and redesigning it. in this evaluation, we measured the execution speed and the dynamic characteristics of cache memory, register file, and branching hardware introduced for high-speed execution of prolog programs.execution speed of the psi firmware interpreter was found to be comparable to that of the dec-10 prolog compiled code on the dec-2060. it was also found that psi was faster than dec for executing programs containing much unification and backtracking that require runtime processing.with the cache memory, the hit ratio for application programs was found higher than 96%; this demonstrates that the prolog execution has much memory access locality. the memory access frequency and the appearance ratio between read and write command were also investigated.concerning the register file, use rate of each dedicated access mode was measured and effect of each mode was discussed. in the branching function we confirmed a high appearance rate of conditional branches and multi-way branches based on tag values.
contrasting characteristics and cache performance of technical and multi-user commercial workloads. experience has shown that many widely used benchmarks are poor predictors of the performance of systems running commercial applications. research into this anomaly has long been hampered by a lack of address traces from representative multi-user commercial workloads. this paper presents research, using traces of industry-standard commercial benchmarks, which examines the characteristic differences between technical and commercial workloads and illustrates how those differences affect cache performance.commercial and technical environments differ in their respective branch behavior, operating system activity, i/o, and dispatching characteristics. a wide range of uniprocessor instruction and data cache geometries were studied. the instruction cache results for commercial workloads demonstrate that instruction cache performance can no longer be neglected because these workloads have much larger code working sets than technical applications. for database workloads, a breakdown of kernel and user behavior reveals that the application component can exhibit behavior similar to the operating system and therefore, can experience miss rates equally high. this paper also indicates that &ldquo;dispatching&rdquo; or process switching characteristics must be considered when designing level-two caches. the data presented shows that increasing the associativity of second-level caches can reduce miss rates significantly. overall, the results of this research should help system designers choose a cache configuration that will perform well in commercial markets.
surpassing the tlb performance of superpages with less operating system support. many commercial microprocessor architectures have added translation lookaside buffer (tlb) support for superpages. superpages differ from segments because their size must be a power of two multiple of the base page size and they must be aligned in both virtual and physical address spaces. very large superpages (e.g., 1mb) are clearly useful for mapping special structures, such as kernel data or frame buffers. this paper considers the architectural and operating system support required to exploit medium-sized superpages (e.g., 64kb, i.e., sixteen times a 4kb base page size). first, we show that superpages improve tlb performance only after invasive operating system modifications that introduce considerable overhead.we then propose two subblock tlb designs as alternate ways to improve tlb performance. analogous to a subblock cache, a complete-subblock tlb associates a tag with a superpage-sized region but has valid bits, physical page number, attributes, etc., for each possible base page mapping. a partial-subblock tlb entry is much smaller than a complete-subblock tlb entry, because it shares physical page number and attribute fields across base page mappings. a drawback of a partial-subblock tlb is that base page mappings can share a tlb entry only if they map to consecutive physical pages and have the same attributes. we propose a physical memory allocation algorithm, page reservation, that makes this sharing more likely. when page reservation is used, experimental results show partial-subblock tlbs perform better than superpage tlbs, while requiring simpler operating system changes. if operating system changes are inappropriate, however, complete-subblock tlbs perform best.
an analysis of a mesa instruction set using dynamic instruction frequencies. the mesa architecture is implemented on a variety of processors, and dynamic instruction frequency data for two programs is used to analyze the architecture in an implementation independent fashion. the mesa compiler allocates variables in an order based upon their static frequency of use, and measurements are provided that show that these static predictions predict run time usage as well. we provide an evaluation of the advantages and costs of mesa's compact byte encoding, its reliance upon an evaluation stack, and its use of memory. the mesa language has evolved over time in a hardware environment oriented around 16-bit quantities with growing use of and accommodations to 32-bit quantities. the cost of emulating 32-bit data paths on a 16-bit machine is identified for a program that heavily exploits longer values. several potential areas for improving the execution speed of a mesa processor with special purpose hardware are identified.
investigating optimal local memory performance. recent work has demonstrated that, cache space is often poorly utilized. however, no previous work has yet demonstrated upper bounds on what a cache or local memory could achieve when exploiting both spatial and temporal locality. belady's min algorithm does yield an upper bound, but exploits only temporal locality. in this article, we present an optimal replacement algorithm for local memory that exploits temporal locality and spatial locality simultaneously. this algorithm is an extension of belady's algorithm. we prove the optimality of this new algorithm with respect to minimizing misses, and we show experimentally that the algorithm produces nearly minimum memory traffic on the spec95 benchmarks. like belady's algorithm, our algorithm requires the entire program trace. it selects replacement victims and the number of words it fetches at once based on future accesses. many different spatial locality strategies can be implemented with this algorithm. with an optimal strategy, the algorithm yields an upper bound that enables us to evaluate alternative implementations to today's caches. we further demonstrate the utility of this algorithm as an analysis tool by evaluating several intermediate strategies between cache and optimal to highlight the limitations of the cache line paradigm using the spec95 benchmarks.
program optimization for instruction caches. this paper presents an optimization algorithm for reducing instruction cache misses. the algorithm uses profile information to reposition programs in memory so that a direct-mapped cache behaves much like an optimal cache with full associativity and full knowledge of the future. for best results, the cache should have a mechanism for excluding certain instructions designated by the compiler. this paper first presents a reduced form of the algorithm. this form is shown to produce an optimal miss rate for programs without conditionals and with a tree call graph, assuming basic blocks can be reordered at will. if conditionals are allowed, but there are no loops within conditionals, the algorithm does as well as an optimal cache for the worst case execution of the program consistent with the profile information. next, the algorithm is extended with heuristics for general programs. the effectiveness of these heuristics are demonstrated with empirical results for a set of 10 programs for various cache sizes. the improvement depends on cache size. for a 512 word cache, miss rates for a direct-mapped instruction cache are halved. for an 8k word cache, miss rates fall by over 75%. over a wide range of cache sizes the algorithm is as effective as increasing the cache size by a factor of 3 times. for 512 words, the algorithm generates only 32% more misses than an optimal cache. optimized programs on a direct-mapped cache have lower miss rates than unoptimized programs on set-associative caches of the same size.
firefly: a multiprocessor workstation. firefly is a shared-memory multiprocessor workstation that contains from one to seven microvax 78032 processors, each with a floating point unit and a sixteen kilobyte cache. the caches are coherent, so that all processors see a consistent view of main memory. a system may contain from four to sixteen megabytes of storage. input-output is done via a standard dec qbus. input-output devices are an ethernet controller, fixed disks, and a monochrome 1024 x 768 display with keyboard and mouse. optional hardware includes a high resolution color display and a controller for high capacity disks. figure 1 is a system block diagram.the firefly runs a software system that emulates the ultrix system call interface. it also supports medium- and coarse-grained multiprocessing through multiple threads of control in a single address space. communications are implemented uniformly through the use of remote procedure calls.this paper describes the goals, architecture, implementation and performance analysis of the firefly. it then presents some measurements of hardware performance, and discusses the degree to which src has been successful in producing software to take advantage of multiprocessing.
a quantitative analysis of loop nest locality. this paper analyzes and quantifies the locality characteristics of numerical loop nests in order to suggest future directions for architecture and software cache optimizations. since most programs spend the majority of their time in nests, the vast majority of cache optimization techniques target loop nests. in contrast, the locality characteristics that drive these optimizations are usually collected across the entire application rather than the nest level. indeed, researchers have studied numerical codes for so long that a number of commonly held assertions have emerged on their locality characteristics. in light of these assertions, we use the perfect benchmarks to take a new look at measuring locality on numerical codes based on references, loop nests, and program locality properties. our results show that several popular assertions are at best overstatements. for example, we find that temporal and spatial reuse have balanced roles within a loop nest and most reuse across nests and the entire program is temporal. these results are consistent with high hit rates, but go against the commonly held assumption that spatial reuse dominates. another result contrary to popular assumption is that misses within a nest are overwhelmingly conflict misses rather than capacity misses. capacity misses are a significant source of misses for the entire program, but mostly correspond to potential reuse between different loop nests. our locality measurements reveal important differences between loop nests and programs; refute some popular assertions; and provide new insights for the compiler writer and the architect.
the effectiveness of multiple hardware contexts. multithreaded processors are used to tolerate long memory latencies. by executing threads loaded in multiple hardware contexts, an otherwise idle processor can keep busy, thus increasing its utilization. however, the larger size of a multi-thread working set can have a negative effect on cache conflict misses. in this paper we evaluate the two phenomena together, examining their combined effect on execution time.the usefulness of multiple hardware contexts depends on: program data locality, cache organization and degree of multiprocessing. multiple hardware contexts are most effective on programs that have been optimized for data locality. for these programs, execution time dropped with increasing contexts, over widely varying architectures. with unoptimized applications, multiple contexts had limited value. the best performance was seen with only two contexts, and only on uniprocessors and small multiprocessors. the behavior of the unoptimized applications changed more noticeably with variations in cache associativity and cache hierarchy, unlike the optimized programs.as a mechanism for exploiting program parallelism, an additional processor is clearly better than another context. however, there were many configurations for which the addition of a few hardware contexts brought as much or greater performance than a larger multiprocessor with fewer than the optimal number of contexts.
guidelines for creating a debuggable processor. hardware without software is of little use. systems that ease the task of debugging software reduce cost and speed development. this paper presents guidelines for designing processors that ease debugging for real-time computer systems. special hardware can aid the debugging process by tracing execution and accesses to memory. such hardware requires access to signals that may not be readily available. other, less exotic hardware provides an interface to the programmer and other processors. the hardware and software of the debugging system should not alter the real-time characteristics of the system under test and should be able to operate on a field-grade processor. it is undesirable to require special versions of processor hardware and software for the debugging system.
exploiting dual data-memory banks in digital signal processors. over the past decade, digital signal processors (dsps) have emerged as the processors of choice for implementing embedded applications in high-volume consumer products. through their use of specialized hardware features and small chip areas, dsps provide the high performance necessary for embedded applications at the low costs demanded by the high-volume consumer market. one feature commonly found in dsps is the use of dual data-memory banks to double the memory system's bandwidth. when coupled with high-order data interleaving, dual memory banks provide the same bandwidth as more costly memory organizations such as a dual-ported memory. however, making effective use of dual memory banks remains difficult, especially for high-level language (hll) dsp compilers.in this paper, we describe two algorithms --- compaction-based (cb) data partitioning and partial data duplication --- that we developed as part of our research into the effective exploitation of dual data-memory banks in hll dsp compilers. we show that cb partitioning is an effective technique for exploiting dual data-memory banks, and that partial data duplication can augment cb partitioning in improving execution performance. our results show that cb partitioning improves the performance of our kernel benchmarks by 13%-40% and the performance of our application benchmarks by 3%-15%. for one of the application benchmarks, partial data duplication boosts performance from 3% to 34%.
a software instruction counter. although several recent papers have proposed architectural support for program debugging and profiling, most processors do not yet provide even basic facilities, such as an instruction counter. as a result, system developers have been forced to invent software solutions. this paper describes our implementation of a software instruction counter for program debugging. we show that an instruction counter can be reasonably implemented in software, often with less than 10% execution overhead. our experience suggests that a hardware instruction counter is not necessary for a practical implementation of watch-points and reverse execution, however it will make program instrumentation much easier for the system developer.
fab: building distributed enterprise disk arrays from commodity components. this paper describes the design, implementation, and evaluation of a federated array of bricks (fab), a distributed disk array that provides the reliability of traditional enterprise arrays with lower cost and better scalability. fab is built from a collection of bricks, small storage appliances containing commodity disks, cpu, nvram, and network interface cards. fab deploys a new majority-voting-based algorithm to replicate or erasure-code logical blocks across bricks and a reconfiguration algorithm to move data in the background when bricks are added or decommissioned. we argue that voting is practical and necessary for reliable, high-throughput storage systems such as fab. we have implemented a fab prototype on a 22-node linux cluster. this prototype sustains 85mb/second of throughput for a database workload, and 270mb/second for a bulk-read workload. in addition, it can outperform traditional master-slave replication through performance decoupling and can handle brick failures and recoveries smoothly without disturbing client requests.
hardware and software support for efficient exception handling. program-synchronous exceptions, for example, breakpoints, watchpoints, illegal opcodes, and memory access violations, provide information about exceptional conditions, interrupting the program and vectoring to an operating system handler. over the last decade, however, programs and run-time systems have increasingly employed these mechanisms as a performance optimization to detect normal and expected conditions. unfortunately, current architecture and operating system structures are designed for exceptional or erroneous conditions, where performance is of secondary importance, rather than normal conditions. consequently, this has limited the practicality of such hardware-based detection mechanisms.we propose both hardware and software structures that permit efficient handling of synchronous exceptions by user-level code. we demonstrate a software implementation that reduces exception-delivery cost by an order-of-magnitude on current risc processors, and show the performance benefits of that mechanism for several example applications.
visa: netstation's virtual internet scsi adapter. in this paper we describe the implementation of visa, our virtual internet scsi adapter. visa was built to evaluate the performance impact on the host operating system of using ip to communicate with peripherals, especially storage devices. we have built and benchmarked file systems on visa-attached emulated disk drives using udp/ip. by using ip, we expect to take advantage of its scaling characteristics and support for heterogeneous media to build large, long-lived systems. detailed file system and network cpu utilization and performance data indicate that it is possible for udp/ip to reach more than 80% of scsi's maximum throughput without the use of network coprocessors. we conclude that ip is a viable alternative to special-purpose storage network protocols, and presents numerous advantages.
separating data and control transfer in distributed operating systems. advances in processor architecture and technology have resulted in workstations in the 100+ mips range. as well, newer local-area networks such as atm promise a ten- to hundred-fold increase in throughput, much reduced latency, greater scalability, and greatly increased reliability, when compared to current lans such as ethernet.we believe that these new network and processor technologies will permit tighter coupling of distributed systems at the hardware level, and that distributed systems software should be designed to benefit from that tighter coupling. in this paper, we propose an alternative way of structuring distributed systems that takes advantage of a communication model based on remote network access (reads and writes) to protected memory segments.a key feature of the new structure, directly supported by the communication model, is the separation of data transfer and control transfer. this is in contrast to the structure of traditional distributed systems, which are typically organized using message passing or remote procedure call (rpc). in rpc-style systems, data and control are inextricably linked&mdash;all rpcs must transfer both data and control, even if the control transfer is unnecessary.we have implemented our model on decstation hardware connected by an atm network. we demonstrate how separating data transfer and control transfer can eliminate unnecessary control transfers and facilitate tighter coupling of the client and server. this has the potential to increase performance and reduce server load, which supports scaling in the face of an increasing number of clients. for example, for a small set of file server operations, our analysis shows a 50% decrease in server load when we switched from a communications mechanism requiring both control transfer and data transfer, to an alternative structure based on pure data transfer.
the effect of the pdp-11 architecture on code generation for chill. this paper outlines the implementation of the ccitt*) high level programming language chill on pdp-11 computers in the chill compiler constructed at the dr. neher laboratories. the characteristics and structure of the compiler are briefly described. the relationship between the pdp-11 architecture and the implementation of chill is outlined in more detail.
trap-driven simulation with tapeworm ii. tapeworm ii is a software-based simulation tool that evaluates the cache and tlb performance of multiple-task and operating system intensive workloads. tapeworm resides in an os kernel and causes a host machine's hardware to drive simulations with kernel traps instead of with address traces, as is conventionally done. this allows tapeworm to quickly and accurately capture complete memory referencing behavior with a limited degradation in overall system performance. this paper compares trap-driven simulation, as implemented in tapeworm, with the more common technique of trace-driven memory simulation with respect to speed, accuracy, portability and flexibility.
resource allocation in a high clock rate microprocessor. this paper discusses the design of a high clock rate (300mhz) processor. the architecture is described, and the goals for the design are explained. the performance of three processor models is evaluated using trace-driven simulation. a cost model is used to estimate the resources required to build processors with varying sizes of on-chip memories, in both single and dual issue models. recommendations are then made to increase the effectiveness of each of the models.
direct execution of lisp on a list-directed architecture. we have defined a direct-execution model dedicated to non-numerical processing which is based upon an internal representation of source programs derived from lisp. this model provides good support for both sophisticated editing (syntactical parsing, tree manipulation, pretty-printing, ...) of conventional languages and artificial intelligence languages. a high level microprogramming language (lem) was designed to write the interpreters and the editors. a hardware processor was built and a lisp interpreter, microprogrammed in lem, has been operational since september 1980. first, the influence of lisp on the lem language and the architecture is discussed. at the lem level, we will see that lisp has prompted the control constructs and the access functions to the tree-structured internal form. as for the architecture, we present the hardware implementation of a special garbage collector based upon reference counters. in turn, the machine has influenced the implementation of lisp. we present here the structure of our lisp interpreter and we give evaluation measures dealing with size, development effort, speed; they prove that programming in lem is easy, short to debug and very concise. moreover, the speed of our lisp interpreter confirms that the architecture is very efficient for symbolic processing.
a comparative study of arbitration algorithms for the alpha 21364 pipelined router. interconnection networks usually consist of a fabric of interconnected routers, which receive packets arriving at their input ports and forward them to appropriate output ports. unfortunately, network packets moving through these routers are often delayed due to conflicting demand for resources, such as output ports or buffer space. hence, routers typically employ arbiters that resolve conflicting resource demands to maximize the number of matches between packets waiting at input ports and free output ports. efficient design and implementation of the algorithm running on these arbiters is critical to maximize network performance.this paper proposes a new arbitration algorithm called spaa (simple pipelined arbitration algorithm), which is implemented in the alpha 21364 processor's on-chip router pipeline. simulation results show that spaa significantly outperforms two earlier well-known arbitration algorithms: pim (parallel iterative matching) and wfa (wave-front arbiter) implemented in the sgi spider switch. spaa outperforms pim and wfa because spaa exhibits matching capabilities similar to pim and wfa under realistic conditions when many output ports are busy, incurs fewer clock cycles to perform the arbitration, and can be pipelined effectively. additionally, we propose a new prioritization policy called the rotary rule, which prevents the network's adverse performance degradation from saturation at high network loads by prioritizing packets already in the network over new packets generated by caches or memory.
a performance evaluation of optimal hybrid cache coherency protocols. the caches within a multiprocessor typically use either a write-invalidate protocol or a write-update protocol to maintain consistency. the recently introduced mips r4000 processor allows operating system software to select, on a per-page basis, which multiprocessor cache coherence protocol (write-invalidate versus write-update) the hardware will use. the availability of the r4000 and the prospect of even more flexible hardware motivated us to examine the potential performance advantages of allowing user-level control over the choice of coherence protocol on a per-page basis and to ask whether more powerful hybrid protocols provide substantially more benefit. we examine the potential benefits of three classes of hybrid protocols: (1) hybrid protocols that choose statically, at the beginning of the program, between write-invalidate (wi) or write-update (wu) on a per-page basis, (2) hybrid protocols that choose statically between wi or wu for each cache block, and (3) dynamic hybrid protocols that can choose between wi or wu at each write. in order to determine how much potential benefit could be obtained by each of these protocol classes, we used trace-driven simulations to evaluate the optimal off-line protocol for each class. we found that the use of a hybrid protocol can substantially reduce the cost of memory references for most of the programs studied. a few programs can also realize large additional benefits from a per-block static hybrid protocol compared to a per-page static hybrid protocol. none of the programs, however, receive a significant additional benefit from using a dynamic hybrid protocol compared to the per-block static hybrid protocol, unless cache block sizes are larger than 16 words (64 bytes).
data buffering: run-time versus compile-time support. data-dependency, branch, and memory-access penalties are main constraints on the performance of high-speed microprocessors. the memory-access penalties concern both penalties imposed by external memory (e.g. cache) or by under utilization of the local processor memory (e.g. registers). this paper focuses solely on methods of increasing the utilization of data memory, local to the processor (registers or register-oriented buffers). a utilization increase of local processor memory is possible by means of compile-time software, run-time hardware, or a combination of both. this paper looks at data buffers which perform solely because of the compile-time software (single register sets); those which operate mainly through hardware but with possible software assistance (multiple register sets); and those intended to operate transparently with main memory implying no software assistance whatsoever (stack buffers). this paper shows that hardware buffering schemes cannot replace compile-time effort, but at most can reduce the complexity of this effort. it shows the utility increase of applying register allocation for multiple register sets. the paper also shows a potential utility decrease inherent to stack buffers. the observation that a single register set, allocated by means of interprocedural allocation, performs competitively with both multiple register set and stack buffer emphasizes the significance of the conclusion
memories: a programmable, real-time hardware emulation tool for multiprocessor server design. modern system design often requires multiple levels of simulation for design validation and performance debugging. however, while machines have gotten faster, and simulators have become more detailed, simulation speeds have not tracked machine speeds. as a result, it is difficult to simulate realistic problem sizes and hardware configurations for a target machine. instead, researchers have focussed on developing scaling methodologies and running smaller problem sizes and configurations that attempt to represent the behavior of the real problem. given the increasing size of problems today, it is unclear whether such an approach yields accurate results. moreover, although commercial workloads are prevalent and important in today's marketplace, many simulation tools are unable to adequately profile such applications, let alone for realistic sizes.in this paper we present a hardware-based emulation tool that can be used to aid memory system designers. our focus is on the memory system because the ever-widening gap between processor and memory speeds means that optimizing the memory subsystem is critical for performance. we present the design of the memory instrumentation and emulation system (memories). memories is a programmable tool designed using fpgas and sdrams. it plugs into an smp bus to perform on-line emulation of several cache configurations, structures and protocols while the system is running real-life workloads in real-time, without any slowdown in application execution speed. we demonstrate its usefulness in several case studies, and find several important results. first, using traces to perform system evaluation can lead to incorrect results (off by 100% or more in some cases) if the trace size is not sufficiently large. second, memories is able to detect performance problems by profiling miss behavior over the entire course of a run, rather than relying on a small interval of time. finally, we observe that previous studies of splash2 applications using scaled application sizes can result in optimistic miss rates relative to real sizes on real machines, providing potentially misleading data when used for design evaluation.
operating system support for improving data locality on cc-numa compute servers. the dominant architecture for the next generation of shared-memory multiprocessors is cc-numa (cache-coherent non-uniform memory architecture). these machines are attractive as compute servers because they provide transparent access to local and remote memory. however, the access latency to remote memory is 3 to 5 times the latency to local memory. cc-now machines provide the benefits of cache coherence to networks of workstations, at the cost of even higher remote access latency. given the large remote access latencies of these architectures, data locality is potentially the most important performance issue. using realistic workloads, we study the performance improvements provided by os supported dynamic page migration and replication. analyzing our kernel-based implementation, we provide a detailed breakdown of the costs. we show that sampling of cache misses can be used to reduce cost without compromising performance, and that tlb misses may not be a consistent approximation for cache misses. finally, our experiments show that dynamic page migration and replication can substantially increase application performance, as much as 30%, and reduce contention for resources in the numa memory system.
bytecode fetch optimization for a java interpreter. interpreters play an important role in many languages, and their performance is critical particularly for the popular language java. the performance of the interpreter is important even for high-performance virtual machines that employ just-in-time compiler technology, because there are advantages in delaying the start of compilation and in reducing the number of the target methods to be compiled. many techniques have been proposed to improve the performance of various interpreters, but none of them has fully addressed the issues of minimizing redundant memory accesses and the overhead of indirect branches inherent to interpreters running on superscalar processors. these issues are especially serious for java because each bytecode is typically one or a few bytes long and the execution routine for each bytecode is also short due to the low-level, stack-based semantics of java bytecode. in this paper, we describe three novel techniques of our java bytecode interpreter, write-through top-of-stack caching (wt), position-based handler customization (phc), and position-based speculative decoding (psd), which ameliorate these problems for the powerpc processors. we show how each technique contributes to improving the overall performance of the interpreter for major java benchmark programs on an ibm power3 processor. among three, phc is the most effective one. we also show that the main source of memory accesses is due to bytecode fetches and that phc successfully eliminates the majority of them, while it keeps the instruction cache miss ratios small.
joint local and global hardware adaptations for energy. this work concerns algorithms to control energy-driven architecture adaptations for multimedia applications, without and with dynamic voltage scaling (dvs). we identify a broad design space for adaptation control algorithms based on two attributes: (1) when to adapt or temporal granularity and (2) what structures to adapt or spatial granularity. for each attribute, adaptation may be global or local. our previous work developed a temporally and spatially global algorithm. it invokes adaptation at the granularity of a full frame of a multimedia application (temporally global) and considers the entire hardware configuration at a time (spatially global). it exploits inter-frame execution time variability, slowing computation just enough to eliminate idle time before the real-time deadline.this paper explores temporally and spatially local algorithms and their integration with the previous global algorithm. the local algorithms invoke architectural adaptation within an application frame to exploit intra-frame execution variability, and attempt to save energy without affecting execution time. we consider local algorithms previously studied for non-real-time applications as well as propose new algorithms. we find that, for systems without and with dvs, the local algorithms are effective in saving energy for multimedia applications, but the new integrated global and local algorithm is best for the systems and applications studied.
the case for a single-chip multiprocessor. advances in ic processing allow for more microprocessor design options. the increasing gate density and cost of wires in advanced integrated circuit technologies require that we look for new ways to use their capabilities effectively. this paper shows that in advanced technologies it is possible to implement a single-chip multiprocessor in the same area as a wide issue superscalar processor. we find that for applications with little parallelism the performance of the two microarchitectures is comparable. for applications with large amounts of parallelism at both the fine and coarse grained levels, the multiprocessor microarchitecture outperforms the superscalar architecture by a significant margin. single-chip multiprocessor architectures have the advantage in that they offer localized implementation of a high-clock rate processor for inherently sequential applications and low latency interprocessor communication for parallel applications.
performance isolation: sharing and isolation in shared-memory multiprocessors. shared-memory multiprocessors (smps) are being extensively used as general-purpose servers. the tight coupling of multiple processors, memory, and i/o provides enormous computing power in a single system, and enables the efficient sharing of these resources.the operating systems for these machines (unix or windows nt) provide very few controls for sharing the resources of the system among the active tasks or users. this unconstrained sharing model is a serious limitation for a server because the load placed by one user can adversely affect other users' performance in an unpredictable manner. we show that this lack of isolation is caused by the resource allocation scheme (or lack thereof) carried over from singleuser workstations. multi-user multiprocessor systems require more sophisticated resource management, and we show how the proposed "performance isolation" scheme can address the current weaknesses of these systems. we have implemented performance isolation in the silicon graphics irix operating system for three important system resources: cpu time, memory, and disk bandwidth. running a number of workloads we show that our proposed scheme is successful at providing workstation-like isolation under heavy load, smp-like latency under light load, and smp-like throughput in all cases.
enhancing software reliability with speculative threads. this paper advocates the use of a monitor-and-recover programming paradigm to enhance the reliability of software, and proposes an architectural design that allows software and hardware to cooperate in making this paradigm more efficient and easier to program.we propose that programmers write monitoring functions assuming simple sequential execution semantics. our architecture speeds up the computation by executing the monitoring functions speculatively in parallel with the main computation. for recovery, programmers can define fine-grain transactions whose side effects, including all register modifications and memory writes, can either be committed or aborted under program control. transactions are implemented efficiently by treating them as speculative threads.our experimental results suggest that monitored execution is more amenable to parallelization than regular program execution. code monitoring is sped up by a factor of 1.5 by exploiting single-thread instruction-level parallelism, and by an additional factor of 1.6 using thread-level speculation. this results in an overall improvement of 2.5 times and a sustained 5.4 instructions-per-cycle performance. a monitored execution that used to be 2.5 times slower executes with a degradation of only 12% when compared to the performance on the baseline machine. we also show that the concept of fine-grain transactional programming is useful in catching buffer overrun errors through a number of real-life examples.
evaluating the performance of software cache coherence. in a shared-memory multiprocessor with private caches, cached copies of a data item must be kept consistent. this is called cache coherence. both hardware and software coherence schemes have been proposed. software techniques are attractive because they avoid hardware complexity and can be used with any processor-memory interconnection. this paper presents an analytical model of the performance of two software coherence schemes and, for comparison, snoopy-cache hardware. the model is validated against address traces from a bus-based multiprocessor. the behavior of the coherence schemes under various workloads is compared, and their sensitivity to variations in workload parameters is assessed. the analysis shows that the performance of software schemes is critically determined by certain parameters of the workload: the proportion of data accesses, the fraction of shared references, and the number of times a shared block is accessed before it is purged from the cache. snoopy caches are more resilient to variations in these parameters. thus when evaluating a software scheme as a design alternative, it is essential to consider the characteristics of the expected workload. the performance of the two software schemes with a multistage interconnection network is also evaluated, and it is determined that both scale well.
locality-aware request distribution in cluster-based network servers. we consider cluster-based network servers in which a front-end directs incoming requests to one of a number of back-ends. specifically, we consider content-based request distribution: the front-end uses the content requested, in addition to information about the load on the back-end nodes, to choose which back-end will handle this request. content-based request distribution can improve locality in the back-ends' main memory caches, increase secondary storage scalability by partitioning the server's database, and provide the ability to employ back-end nodes that are specialized for certain types of requests.as a specific policy for content-based request distribution, we introduce a simple, practical strategy for locality-aware request distribution (lard). with lard, the front-end distributes incoming requests in a manner that achieves high locality in the back-ends' main memory caches as well as load balancing. locality is increased by dynamically subdividing the server's working set over the back-ends. trace-based simulation results and measurements on a prototype implementation demonstrate substantial performance improvements over state-of-the-art approaches that use only load information to distribute requests. on workloads with working sets that do not fit in a single server node's main memory cache, the achieved throughput exceeds that of the state-of-the-art approach by a factor of two to four.with content-based distribution, incoming requests must be handed off to a back-end in a manner transparent to the client, after the front-end has inspected the content of the request. to this end, we introduce an efficient tcp handoflprotocol that can hand off an established tcp connection in a client-transparent manner.
the mahler experience: using and intermediate language as the machine description. division of a compiler into a front end and a back end that communicate via an intermediate language is a well-known technique. we go farther and use the intermediate language as the official description of a family of machines with simple instruction sets and addressing capabilities, hiding some of the inconvenient details of the real machine from the users and the front end compilers.to do this credibly, we have had to hide not only the existence of the details but also the performance consequences of hiding them. the back end that compiles and links the intermediate language tries to produce code that does not suffer a performance penalty because of the details that were hidden from the front end compiler. to accomplish this, we have used a number of link-time optimizations, including instruction scheduling and interprocedural register allocation, to hide the existence of such idiosyncracies as delayed branches and non-infinite register sets. for the most part we have been sucessful.
an evaluation of memory consistency models for shared-memory systems with ilp processors. relaxed consistency models have been shown to significantly outperform sequential consistency for single-issue, statically scheduled processors with blocking reads. however, current microprocessors aggressively exploit instruction-level parallelism (ilp) using methods such as multiple issue, dynamic scheduling, and non-blocking reads. researchers have conjectured that two techniques, hardware-controlled non-binding prefetching and speculative loads, have the potential to equalize the hardware performance of memory consistency models on such processors.this paper performs the first detailed quantitative comparison of several implementations of sequential consistency and release consistency optimized for aggressive ilp processors. our results indicate that hardware prefetching and speculative loads dramatically improve the performance of sequential consistency. however, the gap between sequential consistency and release consistency depends on the cache write policy and the complexity of the cache-coherence protocol implementation. in most cases, release consistency significantly outperforms sequential consistency, but for two applications, the use of a write-back primary cache and a more complex cache-coherence protocol nearly equalizes the performance of the two models.we also observe that the existing techniques, which require on-chip hardware modifications, enhance the performance of release consistency only to a small extent. we propose two new software techniques --- fuzzy acquires and selective acquires --- to achieve more overlap than allowed by the previous implementations of release consistency. to enhance methods for overlapping acquires, we also propose a technique to eliminate control dependences caused by an acquire loop, using a small amount of off-chip hardware called the synchronization buffer.
helper threads via virtual multithreading on an experimental itanium 2 processor-based platform. helper threading is a technology to accelerate a program by exploiting a processor's multithreading capability to run ``assist'' threads. previous experiments on hyper-threaded processors have demonstrated significant speedups by using helper threads to prefetch hard-to-predict delinquent data accesses. in order to apply this technique to processors that do not have built-in hardware support for multithreading, we introduce virtual multithreading (vmt), a novel form of switch-on-event user-level multithreading, capable of fly-weight multiplexing of event-driven thread executions on a single processor without additional operating system support. the compiler plays a key role in minimizing synchronization cost by judiciously partitioning register usage among the user-level threads. the vmt approach makes it possible to launch dynamic helper thread instances in response to long-latency cache miss events, and to run helper threads in the shadow of cache misses when the main thread would be otherwise stalled.the concept of vmt is prototyped on an itanium ® 2 processor using features provided by the processor abstraction layer (pal) firmware mechanism already present in currently shipping processors. on a 4-way mp physical system equipped with vmt-enabled itanium 2 processors, helper threading via the vmt mechanism can achieve significant performance gains for a diverse set of real-world workloads, ranging from single-threaded workstation benchmarks to heavily multithreaded large scale decision support systems (dss) using the ibm db2 universal database. we measure a wall-clock speedup of 5.8% to 38.5% for the workstation benchmarks, and 5.0% to 12.7% on various queries in the dss workload.
analysis of cache invalidation patterns in multiprocessors. to make shared-memory multiprocessors scalable, researchers are now exploring cache coherence protocols that do not rely on broadcast, but instead send invalidation messages to individual caches that contain stale data. the feasibility of such directory-based protocols is highly sensitive to the cache invalidation patterns that parallel programs exhibit. in this paper, we analyze the cache invalidation patterns caused by several parallel applications and investigate the effect of these patterns on a directory-based protocol. our results are based on multiprocessor traces with 4, 8 and 16 processors. to gain insight into what the invalidation patterns would look like beyond 16 processors, we propose a classification scheme for data objects found in parallel applications and link the invalidation traffic patterns observed in the traces back to these high-level objects. our results show that synchronization objects have very different invalidation patterns from those of other data objects. a write reference to a synchronization object usually causes invalidations in many more caches. we point out situations where restructuring the application seems appropriate to reduce the invalidation traffic, and others where hardware support is more appropriate. our results also show that it should be possible to scale &ldquo;well-written&rdquo; parallel programs to a large number of processors without an explosion in invalidation traffic.
improving cache performance with balanced tag and data paths. there are two concurrent paths in a typical cache access --- one through the data array and the other through the tag array. the path through the data array drives the selected set out of the array. the path through the tag array determines cache hit/miss and, for set-associative caches, selects the appropriate line from within the selected set. in both direct-mapped and set-associative caches, the path through the tag array is significantly longer than that through the data array. in this paper, we propose a path balancing technique help match the delays of the tag and data paths. the basic idea behind this technique is to employ a separate subset of the tag array to decouple the one-to-one relationship between address tags and cache lines so as to achieve a design that provides higher performance. performance evaluation using both tpc-c and spec92 benchmarks shows that this path balancing technique offers impressive improvements in overall system performance over conventional cache designs. for tpc-c, improvements in the range of 6% to 28% are possible.
a study of scalar compilation techniques for pipelined supercomputers. this paper studies two compilation techniques for enhancing scalar performance in high-speed scientific processors: software pipelining and loop unrolling. we study the impact of the architecture (size of the register file) and of the hardware (size of instruction buffer) on the efficiency of loop unrolling. we also develop a methodology for classifying software pipelining techniques. for loop unrolling, a straightforward scheduling algorithm is shown to produce near-optimal results when not inhibited by recurrences or memory hazards. our study indicates that the performance produced with a modified cray-1s scalar architecture and a code scheduler utilizing loop unrolling is comparable to the performance achieved by the cray-1s with a vector unit and the cft vectorizing compiler. finally, we show that the combination of loop unrolling and dynamic software pipelining, as implemented by a decoupled computer, substantially outperforms the vector cray-1s.
capturing dynamic memory reference behavior with adaptive cache topology. memory references exhibit locality and are therefore not uniformly distributed across the sets of a cache. this skew reduces the effectiveness of a cache because it results in the caching of a considerable number of less-recently-used lines which are less likely to be re-referenced before they are replaced. in this paper, we describe a technique that dynamically identifies these less-recently-used lines and effectively utilizes the cache frames they occupy to more accurately approximate the global least-recently-used replacement policy while maintaining the fast access time of a direct-mapped cache. we also explore the idea of using these underutilized cache frames to reduce cache misses through data prefetching. in the proposed design, the possible locations that a line can reside in is not predetermined. instead, the cache is dynamically partitioned into groups of cache lines. because both the total number of groups and the individual group associativity adapt to the dynamic reference pattern, we call this design the adaptive group-associative cache. performance evaluation using trace-driven simulations of the tpc-c benchmark and selected programs from the spec95 benchmark suite shows that the group-associative cache is able to achieve a hit ratio that is consistently better than that of a 4-way set-associative cache. for some of the workloads, the hit ratio approaches that of a fully-associative cache.
performance counters and state sharing annotations: a unified approach to thread locality. this paper describes a combined approach for improving thread locality that uses the bardware performance monitors of modem processors and program-centric code annotations to guide thread scheduling on smps. the approach relies on a shared state cache model to compute expected thread footprints in the cache on-line. the accuracy of the model has been analyzed by simmations involving a set of parallel applications. we demonstrate how the cache model can be used to implement several practical locality-based thread scheduling policies with little overhead. active threads, a portable, high-performance thread system, has been built and used to investigate the performance impact of locality scheduling for several applications.
thread scheduling for cache locality. this paper describes a method to improve the cache locality of sequential programs by scheduling fine-grained threads. the algorithm relies upon hints provided at the time of thread creation to determine a thread execution order likely to reduce cache misses. this technique may be particularly valuable when compiler-directed tiling is not feasible. experiments with several application programs, on two systems with different cache structures, show that our thread scheduling method can improve program performance by reducing second-level cache misses.
shasta: a low overhead, software-only approach for supporting fine-grain shared memory. this paper describes shasta, a system that supports a shared address space in software on clusters of computers with physically distributed memory. a unique aspect of shasta compared to most other software distributed shared memory systems is that shared data can be kept coherent at a fine granularity. in addition, the system allows the coherence granularity to vary across different shared data structures in a single application. shasta implements the shared address space by transparently rewriting the application executable to intercept loads and stores. for each shared load or store, the inserted code checks to see if the data is available locally and communicates with other processors if necessary. the system uses numerous techniques to reduce the run-time overhead of these checks. since shasta is implemented entirely in software, it also provides tremendous flexibility in supporting different types of cache coherence protocols. we have implemented an efficient cache coherence protocol that incorporates a number of optimizations, including support for multiple communication granularities and use of relaxed memory models. this system is fully functional and runs on a cluster of alpha workstations.the primary focus of this paper is to describe the techniques used in shasta to reduce the checking overhead for supporting fine granularity sharing in software. these techniques include careful layout of the shared address space, scheduling the checking code for efficient execution on modern processors, using a simple method that checks loads using only the value loaded, reducing the extra cache misses caused by the checking code, and combining the checks for multiple loads and stores. to characterize the effect of these techniques, we present detailed performance results for the splash-2 applications running on an alpha processor. without our optimizations, the checking overheads are excessively high, exceeding 100% for several applications. however, our techniques are effective in reducing these overheads to a range of 5% to 35% for almost all of the applications. we also describe our coherence protocol and present some preliminary results on the parallel performance of several applications running on our workstation cluster. our experience so far indicates that once the cost of checking memory accesses is reduced using our techniques, the shasta approach is an attractive software solution for supporting a shared address space with fine-grain access to data.
supporting ada memory management in the iapx-432. in this paper, we describe how the memory management mechanisms of the intel iapx-432 are used to implement the visibility rules of ada. at any point in the execution of an ada&reg; program on the 432, the program has a protected address space that corresponds exactly to the program's accessibility at the corresponding point in the program's source. this close match of architecture and language did not occur because the 432 was designed to execute ada&mdash;it was not. rather, both ada and the 432 are the result of very similar design goals. to illustrate this point, we compare, in their support for ada, the memory management mechanisms of the 432 to those of traditional computers. the most notable differences occur in heap-space management and multitasking. with respect to the former, we describe a degree of hardware/software cooperation that is not typical of other systems. in the latter area, we show how ada's view of sharing is the same as the 432, but differs totally from the sharing permitted by traditional systems. a description of these differences provide some insight into the problems of implementing an ada compiler for a traditional architecture.
consistency management for virtually indexed caches. a virtually indexed cache can improve performance by allowing cache lookup and address translation to occur in parallel, thus reducing processor cycle time. unlike physically indexed caches, virtually indexed caches create consistency problems because a physical address may be represented in more than one cache line when it has been accessed through more than one virtual address. write-back virtually indexed caches create additional inconsistencies because memory may become stale with respect to the cache. in this paper we examine the problem of consistency management for a virtually indexed write-back cache. we assume that the hardware does not support intra-cache consistency. we present a model and software implementation strategy for maintaining consistency with virtually indexed caches. we present measurements from an implementation of this model on the hp in the context of the mach operating system. our measurements show that a virtually indexed cache can be managed with nearly the same cost as that required to manage a physically indexed one, even when used by a virtual memory system that encourages and exploits sharing.
compiler orchestrated prefetching via speculation and predication. this paper introduces a compiler orchestrated prefetching system as a unified framework geared toward ameliorating the gap between processing speeds and memory access latencies. we focus the scope of the optimization on specific subsets of the program dependence graph that succinctly characterize the memory access pattern of both regular array-based applications and irregular pointer-intensive programs. we illustrate how program embedded precomputation via speculative execution can accurately predict and effectively prefetch future memory references with negligible overhead. the proposed techniques reduce the total running time of seven spec benchmarks and two olden benchmarks by 27% on an itanium 2 processor. the improvements are in addition to several state-of-the-art optimizations including software pipelining and data prefetching. in addition, we use cycle-accurate simulations to identify important and lightweight architectural innovations that further mitigate the memory system bottleneck. in particular, we focus on the notoriously challenging class of pointer-chasing applications, and demonstrate how they may benefit from a novel scheme of it sentineled prefetching. our results for twelve spec benchmarks demonstrate that 45% of the processor stalls that are caused by the memory system are avoidable. the techniques in this paper can effectively mask long memory latencies with little instruction overhead, and can readily contribute to the performance of processors today.
a case study of vax-11 instruction set usage for compiler execution. analysis of an instruction set as large and varied as the one specified for the vax-11 architecture is important for aiding processor design evaluation. this paper looks at dynamic vax-11 instruction set usage by one class of programs, and discusses the methodology and tools which have been developed to provide that information. six vax/vms native mode compilers from digital equipment corporation were used: basic, bliss, cobol, fortran, pascal, and pl/i. a summary of results generated by analyzing executions of these six compilers is presented. information is included for instruction and class frequency, general instruction features, operand specifiers, the memory data stream, register utilization, instruction sequencing, and branch displacements.
the 801 minicomputer. this paper provides an overview of an experimental system developed at the ibm thomas j. watson research center. it consists of a running hardware prototype, a control program, and an optimizing compiler. the basic concepts underlying the system are discussed, as are the performance characteristics of the prototype. in particular, three principles are examined: (1) system orientation towards the pervasive use of high-level language programming and a sophisticated compiler, (2) a primitive instruction set which can be completely hard-wired, and (3) storage hierarchy and i/o organization to enable the cpu to execute an instruction at almost every cycle.
hardware support for memory protection: capability implementations. this paper is intended to stimulate discussion on the present state of hardware supported capability systems. interest in such systems grew up in the mid-1960's and since that time information has been published on several different versions. in the opinion of some observers, the software complexity of these systems outweighs the advantage gained. the paper surveys the situation, and endeavors to set out the general features that a hardware supported capability system should possess. an attempt is made to identify the causes of the complexity and to make recommendations for removing them. the arguments for and against the tagging of capabilities are discussed and attention is drawn to a system of semi-tagging previously proposed by the author.
transactional lock-free execution of lock-based programs. this paper is motivated by the difficulty in writing correct high-performance programs. writing shared-memory multi-threaded programs imposes a complex trade-off between programming ease and performance, largely due to subtleties in coordinating access to shared data. to ensure correctness programmers often rely on conservative locking at the expense of performance. the resulting serialization of threads is a performance bottleneck. locks also interact poorly with thread scheduling and faults, resulting in poor system performance.we seek to improve multithreaded programming trade-offs by providing architectural support for optimistic lock-free execution. in a lock-free execution, shared objects are never locked when accessed by various threads. we propose transactional lock removal (tlr) and show how a program that uses lock-based synchronization can be executed by the hardware in a lock-free manner, even in the presence of conflicts, without programmer support or software changes. tlr uses timestamps for conflict resolution, modest hardware, and features already present in many modern computer systems.tlr's benefits include improved programmability, stability, and performance. programmers can obtain benefits of lock-free data structures, such as non-blocking behavior and wait-freedom, while using lock-protected critical sections for writing programs.
performance of a hardware-assisted real-time garbage collector. hardware-assisted real-time garbage collection offers high throughput and small worst-case bounds on the times required to allocate dynamic objects and to access the memory contained within previously allocated objects. whether the proposed technology is cost effective depends on various choices between configuration alternatives. this paper reports the performance of several different configurations of the hardware-assisted real-time garbage collection system subjected to several different workloads. reported measurements demonstrate that hardware-assisted real-time garbage collection is a viable alternative to traditional explicit memory management techniques, even for low-level languages like c++.
an empirical study of decentralized ilp execution models. recent fascination for dynamic scheduling as a means for exploiting instruction-level parallelism has introduced significant interest in the scalability aspects of dynamic scheduling hardware. in order to overcome the scalability problems of centralized hardware schedulers, many decentralized execution models are being proposed and investigated recently. the crux of all these models is to split the instruction window across multiple processing elements (pes) that do independent, scheduling of instructions. the decentralized execution models proposed so far can be grouped under 3 categories, based on the criterion used for assigning an instruction to a particular pe. they are: (i) execution unit dependence based decentralization (edd), (ii) control dependence based decentralization (cdd), and (iii) data dependence based decentralization (ddd). this paper investigates the performance aspects of these three decentralization approaches. using a suite of important benchmarks and realistic system parameters, we examine performance differences resulting from the type of partitioning as well as from specific implementation issues such as the type of pe interconnect.we found that with a ring-type pe interconnect, the ddd approach performs the best when the number of pes is moderate, and that the cdd approach performs best when the number of pes is large. the currently used approach---edd---does not perform well for any configuration. with a realistic crossbar, performance does not increase with the number of pes for any of the partitioning approaches. the results give insight into the best way to use the transistor budget available for implementing the instruction window.
designing computer systems with mems-based storage. for decades the ram-to-disk memory hierarchy gap has plagued computer architects. an exciting new storage technology based on microelectromechanical systems (mems) is poised to fill a large portion of this performance gap, significantly reduce system power consumption, and enable many new applications. this paper explores the system-level implications of integrating mems-based storage into the memory hierarchy. results show that standalone mems-based storage reduces i/o stall times by 4-74x over disks and improves overall application runtimes by 1.9-4.4x. when used as on-board caches for disks, mems-based storage improves i/o response time by up to 3.5x. further, the energy consumption of mems-based storage is 10-54x less than that of state-of-the-art low-power disk drives. the combination of the high-level physical characteristics of mems-based storage (small footprints, high shock tolerance) and the ability to directly integrate mems-based storage with processing leads to such new applications as portable gigabit storage systems and ubiquitous active storage nodes.
performance of database workloads on shared-memory systems with out-of-order processors. database applications such as online transaction processing (oltp) and decision support systems (dss) constitute the largest and fastest-growing segment of the market for multiprocessor servers. however, most current system designs have been optimized to perform well on scientific and engineering workloads. given the radically different behavior of database workloads (especially oltp), it is important to re-evaluate key system design decisions in the context of this important class of applications.this paper examines the behavior of database workloads on shared-memory multiprocessors with aggressive out-of-order processors, and considers simple optimizations that can provide further performance improvements. our study is based on detailed simulations of the oracle commercial database engine. the results show that the combination of out-of-order execution and multiple instruction issue is indeed effective in improving performance of database workloads, providing gains of 1.5 and 2.6 times over an in-order single-issue processor for oltp and dss, respectively. in addition, speculative techniques enable optimized implementations of memory consistency models that significantly improve the performance of stricter consistency models, bringing the performance to within 10--15% of the performance of more relaxed models.the second part of our study focuses on the more challenging oltp workload. we show that an instruction stream buffer is effective in reducing the remaining instruction stalls in oltp, providing a 17% reduction in execution time (approaching a perfect instruction cache to within 15%). furthermore, our characterization shows that a large fraction of the data communication misses in oltp exhibit migratory behavior; our preliminary results show that software prefetch and writeback/flush hints can be used for this data to further reduce execution time by 12%.
comprehensively and efficiently protecting the heap. the goal of this paper is to propose a scheme that provides comprehensive security protection for the heap. heap vulnerabilities are increasingly being exploited for attacks on computer programs. in most implementations, the heap management library keeps the heap meta-data (heap structure information) and the application's heap data in an interleaved fashion and does not protect them against each other. such implementations are inherently unsafe: vulnerabilities in the application can cause the heap library to perform unintended actions to achieve control-flow and non-control attacks.unfortunately, current heap protection techniques are limited in that they use too many assumptions on how the attacks will be performed, require new hardware support, or require too many changes to the software developers' toolchain. we propose heap server, a new solution that does not have such drawbacks. through existing virtual memory and inter-process protection mechanisms, heap server prevents the heap meta-data from being illegally overwritten, and heap data from being meaningfully overwritten. we show that through aggressive optimizations and parallelism, heap server protects the heap with nearly-negligible performance overheads even on heap-intensive applications. we also verify the protection against several real-world exploits and attack kernels.
machine-independent virtual memory management for paged uniprocessor and multiprocessor architectures. this paper describes the design and implementation of virtual memory management within the cmu mach operating system and the experiences gained by the mach kernel group in porting that system to a variety of architectures. as of this writing, mach runs on more than half a dozen uniprocessors and multiprocessors including the vax family of uniprocessors and multiprocessors, the ibm rt pc, the sun 3, the encore multimax, the sequent balance 21000 and several experimental computers. although these systems vary considerably in the kind of hardware support for memory management they provide, the machine-dependent portion of mach virtual memory consists of a single code module and its related header file. this separation of software memory management from hardware support has been accomplished without sacrificing system performance. in addition to improving portability, it makes possible a relatively unbiased examination of the pros and cons of various hardware memory management schemes, especially as they apply to the support of multiprocessors.
hardware architectures for programming languages and programming languages for hardware architectures. programming languages and operating systems introduce abstractions which allow the programmer to ignore details of an implementation. support of an abstraction must not only concentrate on promoting the efficiency of an implementation, but also on providing the necessary guards against violations of the abstractions. in the frantic drive for efficiency the second goal has been neglected. there are indications that recent designs which are claimed to be both simple and powerful, achieve efficiency by shifting the complex issues of code generation and of appropriate guards onto compilers.complexity has become the common hallmark of software as well as hardware designs. it cannot be mastered by the common practices of testing and simulation. hardware design may profit from developments in programming methodology by adopting proof techniques similar to those used in programming.
hardware/software cooperation in the iapx-423. the intel iapx-432 is an object-based microcomputer system with a unified approach to the design and use of its architecture, operating system, and primary programming language. the concrete architecture of the 432 incorporates hardware support for data abstraction, small protection domains, and language-oriented run-time environments. it also uses its object-orientation to provide hardware support for dynamic heap storage management, interprocess communication, and processor dispatching. we begin with an overview of the 432 architecture so readers unfamiliar with its basic concepts will be able to follow the succeeding discussion without the need to consult the references. following that, we introduce the various forms of hardware/software cooperation and the criteria by which a function or service is selected for migration. this is followed by several of the more interesting examples of hardware/software cooperation in the 432. a comparison of cooperation in the 432 with several contemporary machines and discussions of development issues, past and future, complete the paper.
mondrian memory protection. mondrian memory protection (mmp) is a fine-grained protection scheme that allows multiple protection domains to flexibly share memory and export protected services. in contrast to earlier page-based systems, mmp allows arbitrary permissions control at the granularity of individual words. we use a compressed permissions table to reduce space overheads and employ two levels of permissions caching to reduce run-time overheads. the protection tables in our implementation add less than 9% overhead to the memory space used by the application. accessing the protection tables adds than 8% additional memory references to the accesses made by the application. although it can be layered on top of demand-paged virtual memory, mmp is also well-suited to embedded systems with a single physical address space. we extend mmp to support segment translation which allows a memory segment to appear at another location in the address space. we use this translation to implement zero-copy networking underneath the standard read system call interface, where packet payload fragments are connected together by the translation system to avoid data copying. this saves 52% of the memory references used by a traditional copying network stack.
architectural support for the efficient generation of code for horizontal architectures. horizontal architectures, such as the cdc advanced flexible processor [i] and the fps api20-b [2}, consist of a number of resources that can operate in parallel, each of which is controlled by a field in the wide instruction word. such architectures have been developed to perform high speed scientific computations at a modest cost: figure 1 displays those characteristics of horizontal architectures that are germane to the issues discussed in this paper. the simultaneous requirements of high performance and low cost lead to an architecture consisting of multiple pipelined processing elements (pes) such as adders and multipliers, a memory (which for scheduling purposes may be viewed as yet another pe with two operations: a read and a write), and an interconnect which ties them all together. the interconnect allows the result of one operation to be directly routed to another pe as one of the inputs for an operation that is to be performed there. the required memory bandwidth is reduced since temporary values need not be written to and read from the memory. the final aspect of horizontal processors that is of interest is that their program memories emit wide instructions which synchronously specify the actions of the multiple and possibly dissimilar pes. the program memory is sequenced by a conventional sequencer that assumes sequential flow of control unless a branch is explicitly specified. as a consequence of the simplicity of such an architecture, it is inexpensive relative to the potential performance of the multiple pipelined pes. however, if this potential performance is to be realized, the multiple resources of a horizontal processor must be scheduled effectively. the scheduling task for conventional horizontal processors is quite complex and the construction of highly optimizing compilers for them is a difficult and expensiw3 project. the polycyclic architecture [3- 6] is a horizontal architecture with architectural support for the scheduling task. the cause of the complexity involved in scheduling conventional horizontal processors and the manner in which the polycyclic architecture addresses this issue are outlined in this paper.
an analysis of operating system behavior on a simultaneous multithreaded architecture. this paper presents the first analysis of operating system execution on a simultaneous multithreaded (smt) processor. while smt has been studied extensively over the past 6 years, previous research has focused entirely on user-mode execution. however, many of the applications most amenable to multithreading technologies spend a significant fraction of their time in kernel code. a full understanding of the behavior of such workloads therefore requires execution and measurement of the operating system, as well as the application itself.to carry out this study, we (1) modified the digital unix 4.0d operating system to run on an smt cpu, and (2) integrated our smt alpha instruction set simulator into the simos simulator to provide an execution environment. for an os-intensive workload, we ran the multithreaded apache web server on an 8-context smt. we compared apache's user- and kernel-mode behavior to a standard multiprogrammed specint workload, and compared the smt processor to an out-of-order superscalar running both workloads. overall, our results demonstrate the microarchitectural impact of an os-intensive workload on an smt processor and provide insight into the os demands of the apache web server. the synergy between the smt processor and web and os software produced a greater throughput gain over superscalar execution than seen on any previously examined workloads, including commercial databases and explicitly parallel programs.
the performance advantages of integrating block data trabsfer in cache-coherent multiprocessors. integrating support for block data transfer has become an important emphasis in recent cache-coherent shared address space multiprocessors. this paper examines the potential performance benefits of adding this support. a set of ambitious hardware mechanisms is used to study performance gains in five important scientific computations that appear to be good candidates for using block transfer. our conclusion is that the benefits of block transfer are not substantial for hardware cache-coherent multiprocessors. the main reasons for this are (i) the relatively modest fraction of time applications spend in communication amenable to block transfer, (ii) the difficulty of finding enough independent computation to overlap with the communication latency that remains after block transfer, and (iii) long cache lines often capture many of the benefits of block transfer in efficient cache-coherent machines. in the cases where block transfer improves performance, prefetching can often provide comparable, if not superior, performance benefits. we also examine the impact of varying important communication parameters and processor speed on the effectiveness of block transfer, and comment on useful features that a block transfer facility should support for real applications.
hoist: a system for automatically deriving static analyzers for embedded systems. embedded software must meet conflicting requirements such as be-ing highly reliable, running on resource-constrained platforms, and being developed rapidly. static program analysis can help meet all of these goals. people developing analyzers for embedded object code face a difficult problem: writing an abstract version of each instruction in the target architecture(s). this is currently done by hand, resulting in abstract operations that are both buggy and im-precise. we have developed hoist: a novel system that solves these problems by automatically constructing abstract operations using a microprocessor (or simulator) as its own specification. with almost no input from a human, hoist generates a collection of c func-tions that are ready to be linked into an abstract interpreter. we demonstrate that hoist generates abstract operations that are cor-rect, having been extensively tested, sufficiently fast, and substan-tially more precise than manually written abstract operations. hoist is currently limited to eight-bit machines due to costs exponential in the word size of the target architecture. it is essential to be able to analyze software running on these small processors: they are important and ubiquitous, with many embedded and safety-critical systems being based on them.
improving the accuracy of static branch prediction using branch correlation. recent work in history-based branch prediction uses novel hardware structures to capture branch correlation and increase branch prediction accuracy. we present a profile-based code transformation that exploits branch correlation to improve the accuracy of static branch prediction schemes. our general method encodes branch history information in the program counter through the duplication and placement of program basic blocks. for correlation histories of eight branches, our experimental results achieve up to a 14.7% improvement in prediction accuracy over conventional profile-based prediction without any increase in the dynamic instruction count of our benchmark applications. in the majority of these applications, code duplication increases code size by less than 30%. for the few applications with code segments that exhibit exponential branching paths and no branch correlation, simple compile-time heuristics can eliminate these branches as code-transformation candidates.
os and compiler considerations in the design of the ia-64 architecture. increasing demands for processor performance have outstripped the pace of process and frequency improvements, pushing designers to find ways of increasing the amount of work that can be processed in parallel. traditional risc architectures use hardware approaches to obtain more instruction-level parallelism, with the compiler and the operating system (os) having only indirect visibility into the mechanisms used.the ia-64 architecture [14] was specifically designed to enable systems which create and exploit high levels of instruction-level parallelism by explicitly encoding a program's parallelism in the instruction set [25]. this paper provides a qualitative summary of the ia-64 architecture features that support control and data speculation, and register stacking. the paper focusses on the functional synergy between these architectural elements (rather than their individual performance merits), and emphasizes how they were designed for cooperation between processor hardware, compilers and the os.
ecosystem: managing energy as a first class operating system resource. energy consumption has recently been widely recognized as a major challenge of computer systems design. this paper explores how to support energy as a first-class operating system resource. energy, because of its global system nature, presents challenges beyond those of conventional resource management. to meet these challenges we propose the currentcy model that unifies energy accounting over diverse hardware components and enables fair allocation of available energy among applications. our particular goal is to extend battery lifetime by limiting the average discharge rate and to share this limited resource among competing task according to user preferences. to demonstrate how our framework supports explicit control over the battery resource we implemented ecosystem, a modified linux, that incorporates our currentcy model. experimental results show that ecosystem accurately accounts for the energy consumed by asynchronous device operation, can achieve a target battery lifetime, and proportionally shares the limited energy resource among competing tasks.
compiler optimization of scalar value communication between speculative threads. while there have been many recent proposals for hardware that supports thread-level speculation (tls), there has been relatively little work on compiler optimizations to fully exploit this potential for parallelizing programs optimistically. in this paper, we focus on one important limitation of program performance under tls, which is stalls due to forwarding scalar values between threads that would otherwise cause frequent data dependences. we present and evaluate dataflow algorithms for three increasingly-aggressive instruction scheduling techniques that reduce the critical forwarding path introduced by the synchronization associated with this data forwarding. in addition, we contrast our compiler techniques with related hardware-only approaches. with our most aggressive compiler and hardware techniques, we improve performance under tls by 6.2-28.5% for 6 of 14 applications, and by at least 2.7% for half of the other applications.
frequent value locality and value-centric data cache design. by studying the behavior of programs in the specint95 suite we observed that six out of eight programs exhibit a new kind of value locality, the frequent value locality, according to which a few values appear very frequently in memory locations and are therefore involved in a large fraction of memory accesses. in these six programs ten distinct values occupy over 50% of all memory locations and on an average account for nearly 50% of all memory accesses during program execution. this observation holds for smaller blocks of consecutive memory locations and the set of frequent values remains quite stable over the execution of the program.in the six benchmarks with frequent value locality, on an average 50% of all cache misses occur during the reading or writing of the ten most frequently accessed values. we propose a new data cache structure, the frequent value cache (fvc), which employs a value-centric approach to caching data locations for exploiting the frequent value locality phenomenon. fvc is a small direct-mapped cache which is dedicated to holding only frequently occurring values. the value-centric nature of fvc enables us to store data in a compressed form where the compression is achieved by encoding the frequent values using a few bits. moreover this simple compression scheme preserves the random access to data values in a cache line.our experiments demonstrate that by augmenting a direct mapped cache (dmc) with a direct mapped fvc of size no more than 3 kbytes we can obtain reductions in miss rates ranging from 1% to 68%. in fact we observed that higher reductions in miss rates can be achieved by augmenting a dmc with a small fvc as opposed to doubling the size of dmc for the 124.m88ksim and 134.perl benchmarks.
dynamic tracking of page miss ratio curve for memory management. memory can be efficiently utilized if the dynamic memory demands of applications can be determined and analyzed at run-time. the page miss ratio curve(mrc), i.e. page miss rate vs. memory size curve, is a good performance-directed metric to serve this purpose. however, dynamically tracking mrc at run time is challenging in systems with virtual memory because not every memory reference passes through the operating system (os).this paper proposes two methods to dynamically track mrc of applications at run time. the first method is using a hardware mrc monitor that can track mrc at fine time granularity. our simulation results show that this monitor has negligible performance and energy overheads. the second method is an os-only implementation that can track mrc at coarse time granularity. our implementation results on linux show that it adds only 7--10% overhead.we have also used the dynamic mrc to guide both memory allocation for multiprogramming systems and memory energy management. our real system experiments on linux with applications including apache web server show that the mrc-directed memory allocation can speed up the applications' execution/response time by up to a factor of 5.86 and reduce the number of page faults by up to 63.1%. our execution-driven simulation results with spec2000 benchmarks show that the mrc-directed memory energy management can improve the energy * delay metric by 27--58% over previously proposed static and dynamic schemes.
hide: an infrastructure for efficiently protecting information leakage on the address bus. xom-based secure processor has recently been introduced as a mechanism to provide copy and tamper resistant execution. xom provides support for encryption/decryption and integrity checking. however, neither xom nor any other current approach adequately addresses the problem of information leakage via the address bus. this paper shows that without address bus protection, the xom model is severely crippled. two realistic attacks are shown and experiments show that 70% of the code might be cracked and sensitive data might be exposed leading to serious security breaches.although the problem of address bus leakage has been widely acknowledged both in industry and academia, no practical solution has ever been proposed that can provide an adequate security guarantee. the main reason is that the problem is very difficult to solve in practice due to severe performance degradation which accompanies most of the solutions. this paper presents an infrastructure called hide (hardware-support for leakage-immune dynamic execution) which provides a solution consisting of chunk-level protection with hardware support and a flexible interface which can be orchestrated through the proposed compiler optimization and user specifications that allow utilizing underlying hardware solution more efficiently to provide better security guarantees.our results show that protecting both data and code with a high level of security guarantee is possible with negligible performance penalty (1.3% slowdown).
a regulated transitive reduction (rtr) for longer memory race recording. now at vmware. multithreaded deterministic replay has important applications in cyclic debugging, fault tolerance and intrusion analysis. memory race recording is a key technology for multithreaded deterministic replay. in this paper, we considerably improve our previous always-on flight data recorder (fdr) in four ways: •longer recording by reducing the log size growth rate to approximately one byte per thousand dynamic instructions. •lower hardware cost by reducing the cost to 24 kb per processor core. •simpler design by modifying only the cache coherence protocol, but not the cache. •broader applicability by supporting both sequential consistency (sc) and total store order (tso) memory consistency models (existing recorders support only sc).these improvements stem from several ideas: (1) a regulated transitive reduction (rtr) recording algorithm that creates stricter and vectorizable dependencies to reduce the log growth rate; (2) a set/lru timestamp approximation method that better approximates timestamps of uncached memory locations to reduce the hardware cost; (3) an order-value-hybrid recording methodthat explicitly logs the value of potential sc-violating load instructions to support multiprocessor systems with tso.
hardbound: architectural support for spatial safety of the c programming language. the c programming language is at least as well known for its absence of spatial memory safety guarantees (i.e., lack of bounds checking) as it is for its high performance. c's unchecked pointer arithmetic and array indexing allow simple programming mistakes to lead to erroneous executions, silent data corruption, and security vulnerabilities. many prior proposals have tackled enforcing spatial safety in c programs by checking pointer and array accesses. however, existing software-only proposals have significant drawbacks that may prevent wide adoption, including: unacceptably high run-time overheads, lack of completeness, incompatible pointer representations, or need for non-trivial changes to existing c source code and compiler infrastructure. inspired by the promise of these software-only approaches, this paper proposes a hardware bounded pointer architectural primitive that supports cooperative hardware/software enforcement of spatial memory safety for c programs. this bounded pointer is a new hardware primitive datatype for pointers that leaves the standard c pointer representation intact, but augments it with bounds information maintained separately and invisibly by the hardware. the bounds are initialized by the software, and they are then propagated and enforced transparently by the hardware, which automatically checks a pointer's bounds before it is dereferenced. one mode of use requires instrumenting only malloc, which enables enforcement of perallocation spatial safety for heap-allocated objects for existing binaries. when combined with simple intraprocedural compiler instrumentation, hardware bounded pointers enable a low-overhead approach for enforcing complete spatial memory safety in unmodified c programs.
understanding the propagation of hard errors to software and implications for resilient system design. with continued cmos scaling, future shipped hardware will be increasingly vulnerable to in-the-field faults. to be broadly deployable, the hardware reliability solution must incur low overheads, precluding use of expensive redundancy. we explore a cooperative hardware-software solution that watches for anomalous software behavior to indicate the presence of hardware faults. fundamental to such a solution is a characterization of how hardware faults indifferent microarchitectural structures of a modern processor propagate through the application and os. this paper aims to provide such a characterization, resulting in identifying low-cost detection methods and providing guidelines for implementation of the recovery and diagnosis components of such a reliability solution. we focus on hard faults because they are increasingly important and have different system implications than the much studied transients. we achieve our goals through fault injection experiments with a microarchitecture-level full system timing simulator. our main results are: (1) we are able to detect 95% of the unmasked faults in 7 out of 8 studied microarchitectural structures with simple detectors that incur zero to little hardware overhead; (2) over 86% of these detections are within latencies that existing hardware checkpointing schemes can handle, while others require software checkpointing; and (3) a surprisingly large fraction of the detected faults corrupt os state, but almost all of these are detected with latencies short enough to use hardware checkpointing, thereby enabling os recovery in virtually all such cases.
the mapping collector: virtual memory support for generational, parallel, and concurrent compaction. parallel and concurrent garbage collectors are increasingly employed by managed runtime environments (mres) to maintain scalability, as multi-core architectures and multi-threaded applications become pervasive. moreover, state-of-the-art mres commonly implement compaction to eliminate heap fragmentation and enable fast linear object allocation. our empirical analysis of object demographics reveals that unreachable objects in the heap tend to form clusters large enough to be effectively managed at the granularity of virtual memory pages. even though processes can manipulate the mapping of the virtual address space through the standard operating system (os) interface on most platforms, extant parallel/concurrent compactors do not do so to exploit this clustering behavior and instead achieve compaction by performing, relatively expensive, object moving and pointer adjustment. we introduce the mapping collector (mc), which leverages virtual memory operations to reclaim and consolidate free space without moving objects and updating pointers. mc is a nearly-single-phase compactor that is simpler and more efficient than previously reported compactors that comprise two to four phases. through effective mre-os coordination, mc maintains the simplicity of a non-moving collector while providing efficient parallel and concurrent compaction. we implement both stop-the-world and concurrent mc in a generational garbage collection framework within the open-source hotspot java virtual machine. our experimental evaluation using a multiprocessor indicates that mc significantly increases throughput and scalability as well as reduces pause times, relative to state-of-the-art, parallel and concurrent compactors.
temporal search: detecting hidden malware timebombs with virtual machines. worms, viruses, and other malware can be ticking bombs counting down to a specific time, when they might, for example, delete files or download new instructions from a public web server. we propose a novel virtual-machine-based analysis technique to automatically discover the timetable of a piece of malware, or when events will be triggered, so that other types of analysis can discern what those events are. this information can be invaluable for responding to rapid malware, and automating its discovery can provide more accurate information with less delay than careful human analysis.developing an automated system that produces the timetable of a piece of malware is a challenging research problem. in this paper, we describe our implementation of a key component of such a system: the discovery of timers without making assumptions about the integrity of the infected system's kernel. our technique runs a virtual machine at slightly different rates of perceived time (time as seen by the virtual machine), and identifies time counters by correlating memory write frequency to timer interrupt frequency.we also analyze real malware to assess the feasibility of using full-system, machine-level symbolic execution on these timers to discover predicates. because of the intricacies of the gregorian calendar (leap years, different number of days in each month, etc.) these predicates will not be direct expressions on the timer but instead an annotated trace; so we formalize the calculation of a timetable as a weakest precondition calculation. our analysis of six real worms sheds light on two challenges for future work: 1) time-dependent malware behavior often does not follow a linear timetable; and 2) that an attacker with knowledge of the analysis technique can evade analysis. our current results are promising in that with simple symbolic execution we are able to discover predicates on the day of the month for four real worms. then through more traditional manual analysis we conclude that a more control-flow-sensitive symbolic execution implementation would discover all predicates for the malware we analyzed.
optimistic parallelism benefits from data partitioning. recent studies of irregular applications such as finite-element mesh generators and data-clustering codes have shown that these applications have a generalized data parallelism arising from the use of iterative algorithms that perform computations on elements of worklists. in some irregular applications, the computations on different elements are independent. in other applications, there may be complex patterns of dependences between these computations. the galois system was designed to exploit this kind of irregular data parallelism on multicore processors. its main features are (i) two kinds of set iterators for expressing worklist-based data parallelism, and (ii) a runtime system that performs optimistic parallelization of these iterators, detecting conflicts and rolling back computations as needed. detection of conflicts and rolling back iterations requires information from class implementors. in this paper, we introduce mechanisms to improve the execution efficiency of galois programs: data partitioning, data-centric work assignment, lock coarsening, and over-decomposition. these mechanisms can be used to exploit locality of reference, reduce mis-speculation, and lower synchronization overhead. we also argue that the design of the galois system permits these mechanisms to be used with relatively little modification to the user code. finally, we present experimental results that demonstrate the utility of these mechanisms.
xoc, an extension-oriented compiler for systems programming. today's system programmers go to great lengths to extend the languages in which they program. for instance, system-specific compilers find errors in linux and other systems, and add support for specialized control flow to qt and event-based programs. these compilers are difficult to build and cannot always understand each other's language changes. however, they can greatly improve code understandability and correctness, advantages that should be accessible to all programmers. we describe an extension-oriented compiler for c called xoc. an extension-oriented compiler, unlike a conventional extensible compiler, implements new features via many small extensions that are loaded together as needed. xoc gives extension writers full control over program syntax and semantics while hiding many compiler internals. xoc programmers concisely define powerful compiler extensions that, by construction, can be combined; even some parts of the base compiler, such as gnu c compatibility, are structured as extensions. xoc is based on two key interfaces. syntax patterns allow extension writers to manipulate language fragments using concrete syntax. lazy computation of attributes allows extension writers to use the results of analyses by other extensions or the core without needing to worry about pass scheduling. extensions built using xoc include xsparse, a 345-line extension that mimics sparse, linux's c front end, and xlambda, a 170-line extension that adds function expressions to c. an evaluation of xoc using these and 13 other extensions shows that xoc extensions are typically more concise than equivalent extensions written for conventional extensible compilers and that it is possible to compose extensions.
accelerating two-dimensional page walks for virtualized systems. nested paging is a hardware solution for alleviating the software memory management overhead imposed by system virtualization. nested paging complements existing page walk hardware to form a two-dimensional (2d) page walk, which reduces the need for hypervisor intervention in guest page table management. however, the extra dimension also increases the maximum number of architecturally-required page table references. this paper presents an in-depth examination of the 2d page table walk overhead and options for decreasing it. these options include using the amd opteron processor's page walk cache to exploit the strong reuse of page entry references. for a mix of server and spec benchmarks, the presented results show a 15%-38% improvement in guest performance by extending the existing page walk cache to also store the nested dimension of the 2d page walk. caching nested page table translations and skipping multiple page entry references produce an additional 3%-7% improvement. much of the remaining 2d page walk overhead is due to low-locality nested page entry references, which result in additional memory hierarchy misses. by using large pages, the hypervisor can eliminate many of these long-latency accesses and further improve the guest performance by 3%-22%.
archipelago: trading address space for reliability and security. memory errors are a notorious source of security vulnerabilities that can lead to service interruptions, information leakage and unauthorized access. because such errors are also difficult to debug, the absence of timely patches can leave users vulnerable to attack for long periods of time. a variety of approaches have been introduced to combat these errors, but these often incur large runtime overheads and generally abort on errors, threatening availability. this paper presents archipelago, a runtime system that takes advantage of available address space to substantially reduce the likelihood that a memory error will affect program execution. archipelago randomly allocates heap objects far apart in virtual address space, effectively isolating each object from buffer overflows. archipelago also protects against dangling pointer errors by preserving the contents of freed objects after they are freed. archipelago thus trades virtual address space---a plentiful resource on 64-bit systems---for significantly improved program reliability and security, while limiting physical memory consumption by tracking the working set of an application and compacting cold objects. we show that archipelago allows applications to continue to run correctly in the face of thousands of memory errors. across a suite of server applications, archipelago's performance overhead is 6% on average (between -7% and 22%), making it especially suitable to protect servers that have known security vulnerabilities due to heap memory errors.
understanding and visualizing full systems with data flow tomography. it is not uncommon for modern systems to be composed of a variety of interacting services, running across multiple machines in such a way that most developers do not really understand the whole system. as abstraction is layered atop abstraction, developers gain the ability to compose systems of extraordinary complexity with relative ease. however, many software properties, especially those that cut across abstraction layers, become very difficult to understand in such compositions. the communication patterns involved, the privacy of critical data, and the provenance of information, can be difficult to find and understand, even with access to all of the source code. the goal of data flow tomography is to use the inherent information flow of such systems to help visualize the interactions between complex and interwoven components across multiple layers of abstraction. in the same way that the injection of short-lived radioactive isotopes help doctors trace problems in the cardiovascular system, the use of "data tagging" can help developers slice through the extraneous layers of software and pin-point those portions of the system interacting with the data of interest. to demonstrate the feasibility of this approach we have developed a prototype system in which tags are tracked both through the machine and in between machines over the network, and from which novel visualizations of the whole system can be derived. we describe the system-level challenges in creating a working system tomography tool and we qualitatively evaluate our system by examining several example real world scenarios.
softsig: software-exposed hardware signatures for code analysis and optimization. many code analysis techniques for optimization, debugging, or parallelization need to perform runtime disambiguation of sets of addresses. such operations can be supported efficiently and with low complexity with hardware signatures. to enable flexible use of signatures, this paper proposes to expose a signature register file to the software through a rich isa. the software has great flexibility to decide, for each signature,which addresses to collect and which addresses to disambiguate against. we call this architecture softsig. in addition, as an example of softsig use, we show how to detect redundant function calls efficiently and eliminate them dynamically. we call this algorithm memoise. on average for five popular applications, memoise reduces the number of dynamic instructions by 9.3%, thereby reducing the execution time of the applications by 9%.
learning from mistakes: a comprehensive study on real world concurrency bug characteristics. the reality of multi-core hardware has made concurrent programs pervasive. unfortunately, writing correct concurrent programs is difficult. addressing this challenge requires advances in multiple directions, including concurrency bug detection, concurrent program testing, concurrent programming model design, etc. designing effective techniques in all these directions will significantly benefit from a deep understanding of real world concurrency bug characteristics. this paper provides the first (to the best of our knowledge) comprehensive real world concurrency bug characteristic study. specifically, we have carefully examined concurrency bug patterns, manifestation, and fix strategies of 105 randomly selected real world concurrency bugs from 4 representative server and client open-source applications (mysql, apache, mozilla and openoffice). our study reveals several interesting findings and provides useful guidance for concurrency bug detection, testing, and concurrent programming language design. some of our findings are as follows: (1) around one third of the examined non-deadlock concurrency bugs are caused by violation to programmers' order intentions, which may not be easily expressed via synchronization primitives like locks and transactional memories; (2) around 34% of the examined non-deadlock concurrency bugs involve multiple variables, which are not well addressed by existing bug detection tools; (3) about 92% of the examined concurrency bugs canbe reliably triggered by enforcing certain orders among no more than 4 memory accesses. this indicates that testing concurrent programs can target at exploring possible orders among every small groups of memory accesses, instead of among all memory accesses; (4) about 73% of the examinednon-deadlock concurrency bugs were not fixed by simply adding or changing locks, and many of the fixes were not correct at the first try, indicating the difficulty of reasoning concurrent execution by programmers.
streamware: programming general-purpose multicore processors using streams. recently, the number of cores on general-purpose processors has been increasing rapidly. using conventional programming models, it is challenging to effectively exploit these cores for maximal performance. an interesting alternative candidate for programming multiple cores is the stream programming model, which provides a framework for writing programs in a sequential-style while greatly simplifying the task of automatic parallelization. it has been shown that not only traditional media/image applications but also more general-purpose data-intensive applications can be expressed in the stream programming style. in this paper, we investigate the potential to use the stream programming model to efficiently utilize commodity multicore general-purpose processors (e.g., intel/amd). although several stream languages and stream compilers have recently been developed, they typically target special-purpose stream processors. in contrast, we propose a flexible software system, streamware, which automatically maps stream programs onto a wide variety of general-purpose multicore processor configurations. we leverage existing compilation framework for stream processors and design a runtime environment which takes as input the output of these stream compilers in the form of machine-independent stream virtual machine code. the runtime environment assigns work to processor cores considering processor/cache configurations and adapts to workload variations. we evaluate this approach for a few general-purpose scientific applications on real hardware and a cycle-level simulator set-up to showcase scaling and contention issues. the results show that the stream programming model is a good choice for efficiently exploiting modern and future multicore cpus for an important class of applications.
communication optimizations for global multi-threaded instruction scheduling. the recent shift in the industry towards chip multiprocessor (cmp) designs has brought the need for multi-threaded applications to mainstream computing. as observed in several limit studies, most of the parallelization opportunities require looking for parallelism beyond local regions of code. to exploit these opportunities, especially for sequential applications, researchers have recently proposed global multi-threaded instruction scheduling techniques, including dswp and gremio. these techniques simultaneously schedule instructions from large regions of code, such as arbitrary loop nests or whole procedures, and have been shown to be effective at extracting threads for many applications. a key enabler of these global instruction scheduling techniques is the multi-threaded code generation (mtcg) algorithm proposed in [16], which generates multi-threaded code for any partition of the instructions into threads. this algorithm inserts communication and synchronization instructions in order to satisfy all inter-thread dependences. in this paper, we present a general compiler framework, coco, to optimize the communication and synchronization instructions inserted by the mtcg algorithm. this framework, based on thread-aware data-flow analyses and graph min-cut algorithms, appropriately models andoptimizes all kinds of inter-thread dependences, including register, memory, and control dependences. our experiments, using a fully automatic compiler implementation of these techniques, demonstrate significant reductions (about 30% on average) in the number of dynamic communication instructions in code parallelized with dswp and gremio. this reduction in communication translates to performance gains of up to 40%.
better bug reporting with better privacy. software vendors collect bug reports from customers to improve the quality of their software. these reports should include the inputs that make the software fail, to enable vendors to reproduce the bug. however, vendors rarely include these inputs in reports because they may contain private user data. we describe a solution to this problem that provides software vendors with new input values that satisfy the conditions required to make the software follow the same execution path until it fails, but are otherwise unrelated with the original inputs. these new inputs allow vendors to reproduce the bug while revealing less private information than existing approaches. additionally, we provide a mechanism to measure the amount of information revealed in an error report. this mechanism allows users to perform informed decisions on whether or not to submit reports. we implemented a prototype of our solution and evaluated it with real errors in real programs. the results show that we can produce error reports that allow software vendors to reproduce bugs while revealing almost no private information.
improving the performance of object-oriented languages with dynamic predication of indirect jumps. indirect jump instructions are used to implement increasingly-common programming constructs such as virtual function calls, switch-case statements, jump tables, and interface calls. the performance impact of indirect jumps is likely to increase because indirect jumps with multiple targets are difficult to predict even with specialized hardware. this paper proposes a new way of handling hard-to-predict indirect jumps: dynamically predicating them. the compiler (static or dynamic) identifies indirect jumps that are suitable for predication along with their control-flow merge (cfm) points. the hardware predicates theinstructions between different targets of the jump and its cfm point if the jump turns out to be hard-to-predict at run time. if the jump would actually have been mispredicted, its dynamic predication eliminates a pipeline flush, thereby improving performance. our evaluations show that dynamic indirect jump predication (dip) improves the performance of a set of object-oriented applications including the java dacapo benchmark suite by 37.8% compared to a commonly-used branch target buffer based predictor, while also reducing energy consumption by 24.8%. we compare dip to three previously proposed indirect jump predictors and find that it provides the best performance and energy-efficiency.
a comparison of software and hardware techniques for x86 virtualization. until recently, the x86 architecture has not permitted classical trap-and-emulate virtualization. virtual machine monitors for x86, such as vmware ® workstation and virtual pc, have instead used binary translation of the guest kernel code. however, both intel and amd have now introduced architectural extensions to support classical virtualization.we compare an existing software vmm with a new vmm designed for the emerging hardware support. surprisingly, the hardware vmm often suffers lower performance than the pure software vmm. to determine why, we study architecture-level events such as page table updates, context switches and i/o, and find their costs vastly different among native, software vmm and hardware vmm execution.we find that the hardware support fails to provide an unambiguous performance advantage for two primary reasons: first, it offers no support for mmu virtualization; second, it fails to co-exist with existing software techniques for mmu virtualization. we look ahead to emerging techniques for addressing this mmu virtualization problem in the context of hardware-assisted virtualization.
automatic generation of peephole superoptimizers. peephole optimizers are typically constructed using human-written pattern matching rules, an approach that requires expertise and time, as well as being less than systematic at exploiting all opportunities for optimization. we explore fully automatic construction of peephole optimizers using brute force superoptimization. while the optimizations discovered by our automatic system may be less general than human-written counterparts, our approach has the potential to automatically learn a database of thousands to millions of optimizations, in contrast to the hundreds found in current peephole optimizers. we show experimentally that our optimizer is able to exploit performance opportunities not found by existing compilers; in particular, we show speedups from 1.7 to a factor of 10 on some compute intensive kernels over a conventional optimizing compiler.
integrated network interfaces for high-bandwidth tcp/ip. this paper proposes new network interface controller (nic) designs that take advantage of integration with the host cpu to provide increased flexibility for operating system kernel-based performance optimization.we believe that this approach is more likely to meet the needs of current and future high-bandwidth tcp/ip networking on end hosts than the current trend of putting more complexity in the nic, while avoiding the need to modify applications and protocols. this paper presents two such nics. the first, the simple integrated nic (sinic), is a minimally complex design that moves the responsibility for managing the network fifos from the nic to the kernel. despite this closer interaction between the kernel and the nic, sinic provides performance equivalent to a conventional dma-based nic without increasing cpu overhead. the second design, v-sinic, adds virtual per-packet registers to sinic, enabling parallel packet processing while maintaining a fifo model. v-sinic allows the kernel to decouple examining a packet's header from copying its payload to memory. we exploit this capability to implement a true zero-copy receive optimization in the linux 2.6 kernel, providing bandwidth improvements of over 50% on unmodified sockets-based receive-intensive benchmarks.
bell: bit-encoding online memory leak detection. memory leaks compromise availability and security by crippling performance and crashing programs. leaks are difficult to diagnose because they have no immediate symptoms. online leak detection tools benefit from storing and reporting per-object sites (e.g., allocation sites) for potentially leaking objects. in programs with many small objects, per-object sites add high space overhead, limiting their use in production environments.this paper introduces bit-encoding leak location (bell), a statistical approach that encodes per-object sites to a single bit per object. a bit loses information about a site, but given sufficient objects that use the site and a known, finite set of possible sites, bell uses brute-force decoding to recover the site with high accuracy.we use this approach to encode object allocation and last-use sites in sleigh, a new leak detection tool. sleigh detects stale objects (objects unused for a long time) and uses bell decoding to report their allocation and last-use sites. our implementation steals four unused bits in the object header and thus incurs no per-object space overhead. sleigh's instrumentation adds 29% execution time overhead, which adaptive profiling reduces to 11%. sleigh's output is directly useful for finding and fixing leaks in spec jbb2000 and eclipse, although sufficiently many objects must leak before bell decoding can report sites with confidence. bell is suitable for other leak detection approaches that store per-object sites, and for other problems amenable to statistical per-object metadata.
stealth prefetching. prefetching in shared-memory multiprocessor systems is an increasingly difficult problem. as system designs grow to incorporate larger numbers of faster processors, memory latency and interconnect traffic increase. while aggressive prefetching techniques can mitigate the increasing memory latency, they can harm performance by wasting precious interconnect bandwidth and prematurely accessing shared data, causing state downgrades at remote nodes that force later upgrades.this paper investigates stealth prefetching, a new technique that utilizes information from coarse-grain coherence tracking (cgct) for prefetching data aggressively, stealthily, and efficiently in a broadcast-based shared-memory multiprocessor system. stealth prefetching utilizes cgct to identify regions of memory that are not shared by other processors, aggressively fetches these lines from dram in open-page mode, and moves them close to the processor in anticipation of future references. our analysis with commercial, scientific, and multiprogrammed workloads show that stealth prefetching provides an average speedup of 20% over an aggressive baseline system with conventional prefetching.
computation spreading: employing hardware migration to specialize cmp cores on-the-fly. in canonical parallel processing, the operating system (os) assigns a processing core to a single thread from a multithreaded server application. since different threads from the same application often carry out similar computation, albeit at different times, we observe extensive code reuse among different processors, causing redundancy (e.g., in our server workloads, 45-65% of all instruction blocks are accessed by all processors). moreover, largely independent fragments of computation compete for the same private resources causing destructive interference. together, this redundancy and interference lead to poor utilization of private microarchitecture resources such as caches and branch predictors.we present computation spreading (csp), which employs hardware migration to distribute a thread's dissimilar fragments of computation across the multiple processing cores of a chip multiprocessor (cmp), while grouping similar computation fragments from different threads together. this paper focuses on a specific example of csp for os intensive server applications: separating application level (user) computation from the os calls it makes.when performing csp, each core becomes temporally specialized to execute certain computation fragments, and the same core is repeatedly used for such fragments. we examine two specific thread assignment policies for csp, and show that these policies, across four server workloads, are able to reduce instruction misses in private l2 caches by 27-58%, private l2 load misses by 0-19%, and branch mispredictions by 9-25%.
heapmd: identifying heap-based bugs using anomaly detection. we present the design, implementation, and evaluation of heapmd, a dynamic analysis tool that finds heap-based bugs using anomaly detection. heapmd is based upon the observation that, in spite of the evolving nature of the heap, several of its properties remain stable. heapmd uses this observation in a novel way: periodically, during the execution of the program, it computes a suite of metrics which are sensitive to the state of the heap. these metrics track heap behavior, and the stability of the heap reflects quantitatively in the values of these metrics. the "normal" ranges of stable metrics, obtained by running a program on multiple inputs, are then treated as indicators of correct behaviour, and are used in conjunction with an anomaly detector to find heap-based bugs. using heapmd, we were able to find 40 heap-based bugs, 31 of them previously unknown, in 5 large, commercial applications.
kendo: efficient deterministic multithreading in software. although chip-multiprocessors have become the industry standard, developing parallel applications that target them remains a daunting task. non-determinism, inherent in threaded applications, causes significant challenges for parallel programmers by hindering their ability to create parallel applications with repeatable results. as a consequence, parallel applications are significantly harder to debug, test, and maintain than sequential programs. this paper introduces kendo: a new software-only system that provides deterministic multithreading of parallel applications. kendo enforces a deterministic interleaving of lock acquisitions and specially declared non-protected reads through a novel dynamically load-balanced deterministic scheduling algorithm. the algorithm tracks the progress of each thread using performance counters to construct a deterministic logical time that is used to compute an interleaving of shared data accesses that is both deterministic and provides good load balancing. kendo can run on today's commodity hardware while incurring only a modest performance cost. experimental results on the splash-2 applications yield a geometric mean overhead of only 16% when running on 4 processors. this low overhead makes it possible to benefit from kendo even after an application is deployed. programmers can start using kendo today to program parallel applications that are easier to develop, debug, and test.
unbounded page-based transactional memory. exploiting thread level parallelism is paramount in the multicore era. transactions enable programmers to expose such parallelism by greatly simplifying the multi-threaded programming model. virtualized transactions (unbounded in space and time) are desirable, as they can increase the scope of transactions' use, and thereby further simplify a programmer's job. however, hardware support is essential to support efficient execution of unbounded transactions. in this paper, we introduce page-based transactional memory to support unbounded transactions. we combine transaction bookkeeping with the virtual memory system to support fast transaction conflict detection, commit, abort, and to maintain transactions' speculative data.
anomaly-based bug prediction, isolation, and validation: an automated approach for software debugging. software defects, commonly known as bugs, present a serious challenge for system reliability and dependability. once a program failure is observed, the debugging activities to locate the defects are typically nontrivial and time consuming. in this paper, we propose a novel automated approach to pin-point the root-causes of software failures. our proposed approach consists of three steps. the first step is bug prediction, which leverages the existing work on anomaly-based bug detection as exceptional behavior during program execution has been shown to frequently point to the root cause of a software failure. the second step is bug isolation, which eliminates false-positive bug predictions by checking whether the dynamic forward slices of bug predictions lead to the observed program failure. the last step is bug validation, in which the isolated anomalies are validated by dynamically nullifying their effects and observing if the program still fails. the whole bug prediction, isolation and validation process is fully automated and can be implemented with efficient architectural support. our experiments with 6 programs and 7 bugs, including a real bug in the gcc 2.95.2 compiler, show that our approach is highly effective at isolating only the relevant anomalies. compared to state-of-art debugging techniques, our proposed approach pinpoints the defect locations more accurately and presents the user with a much smaller code set to analyze.
tradeoffs in transactional memory virtualization. for transactional memory (tm) to achieve widespread acceptance, transactions should not be limited to the physical resources of any specific hardware implementation. tm systems should guarantee correct execution even when transactions exceed scheduling quanta, overflow the capacity of hardware caches and physical memory, or include more independent nesting levels than what is supported in hardware. existing proposals for tm virtualization are either incomplete or rely on complex hardware implementations, which are an overkill if virtualization is invoked infrequently in the common case.we present extended transactional memory (xtm), the first tm virtualization system that virtualizes all aspects of transactional execution (time, space, and nesting depth). xtm is implemented in software using virtual memory support. it operates at page granularity, using private copies of overflowed pages to buffer memory updates until the transaction commits and snapshots of pages to detect interference between transactions. we also describe two enhancements to xtm that use limited hardware support to address key performance bottlenecks.we compare xtm to hardwarebased virtualization using both real applications and synthetic microbenchmarks. we show that despite being software-based, xtm and its enhancements are competitive with hardware-based alternatives. overall, we demonstrate that xtm provides a complete, flexible, and low-cost mechanism for practical tm virtualization.
efficient online validation with delta execution. software systems are constantly changing. patches to fix bugs and patches to add features are all too common. every change risks breaking a previously working system. hence administrators loathe change, and are willing to delay even critical security patches until after fully validating their correctness. compared to off-line validation, on-line validation has clear advantages since it tests against real life workloads. yet unfortunately it imposes restrictive overheads as it requires running the old and new versions side-by-side. moreover, due to spurious differences (e.g. event timing, random number generation, and thread interleavings), it is difficult to compare the two for validation. to allow more effective on-line patch validation, we propose a new mechanism, called delta execution, that is based on the observation that most patches are small. delta execution merges the two side-by-side executions for most of the time and splits only when necessary, such as when they access different data or execute different code. this allows us to perform on-line validation not only with lower overhead but also with greatly reduced spurious differences, allowing us to effectively validate changes. we first validate the feasibility of our idea by studying the characteristics of 240 patches from 4 server programs; our examination shows that 77% of the changes should not be expected to cause large changes and are thereby feasible for delta execution. we then implemented delta execution using dynamic instrumentation. using real world patches from 7 server applications and 3 other programs, we compared our implementation of delta execution against a traditional side-by-side on-line validation. delta execution outperformed traditional validation by up to 128%; further, for 3 of the changes, spurious differences caused the traditional validation to fail completely while delta execution succeeded. this demonstrates that delta execution can allow administrators to use on-line validation to confidently ensure the correctness of the changes they apply.
a spatial path scheduling algorithm for edge architectures. growing on-chip wire delays are motivating architectural features that expose on-chip communication to the compiler. edge architectures are one example of communication-exposed microarchitectures in which the compiler forms dataflow graphs that specify how the microarchitecture maps instructions onto a distributed execution substrate. this paper describes a compiler scheduling algorithm called spatial path scheduling that factors in previously fixed locations - called anchor points - for each placement. this algorithm extends easily to different spatial topologies. we augment this basic algorithm with three heuristics: (1) local and global alu and network link contention modeling, (2) global critical path estimates, and (3) dependence chain path reservation. we use simulated annealing to explore possible performance improvements and to motivate the augmented heuristics and their weighting functions. we show that the spatial path scheduling algorithm augmented with these three heuristics achieves a 21% average performance improvement over the best prior algorithm and comes within an average of 5% of the annealed performance for our benchmarks.
dispersing proprietary applications as benchmarks through code mutation. industry vendors hesitate to disseminate proprietary applications to academia and third party vendors. by consequence, the benchmarking process is typically driven by standardized, open-source benchmarks which may be very different from and likely not representative of the real-life applications of interest. this paper proposes code mutation, a novel technique that mutates a proprietary application to complicate reverse engineering so that it can be distributed as a benchmark. the benchmark mutant then serves as a proxy for the proprietary application. the key idea in the proposed code mutation approach is to preserve the proprietary application's dynamic memory access and/or control flow behavior in the benchmark mutant while mutating the rest of the application code. to this end, we compute program slices for memory access operations and/or control flow operationstrimmed through constant value and branch profiles; and subsequently mutate the instructions not appearing in these slices through binary rewriting. our experimental results using spec cpu2000 and mibench benchmarks show that code mutation is a promising technique that mutates up to 90% of the static binary, up to 50% of the dynamically executed instructions, and up to 35% of the at run time exposed inter-operation data dependencies. the performance characteristics of the mutant are very similar to those of the proprietary application across a wide range of microarchitectures and hardware implementations.
no "power" struggles: coordinated multi-level power management for the data center. power delivery, electricity consumption, and heat management are becoming key challenges in data center environments. several past solutions have individually evaluated different techniques to address separate aspects of this problem, in hardware and software, and at local and global levels. unfortunately, there has been no corresponding work on coordinating all these solutions. in the absence of such coordination, these solutions are likely to interfere with one another, in unpredictable (and potentially dangerous) ways. this paper seeks to address this problem. we make two key contributions. first, we propose and validate a power management solution that coordinates different individual approaches. using simulations based on 180 server traces from nine different real-world enterprises, we demonstrate the correctness, stability, and efficiency advantages of our solution. second, using our unified architecture as the base, we perform a detailed quantitative sensitivity analysis and draw conclusions about the impact of different architectures, implementations, workloads, and system design choices.
hardware counter driven on-the-fly request signatures. today's processors provide a rich source of statistical informationon application execution through hardware counters. in this paper, we explore the utilization of these statistics as request signaturesin server applications for identifying requests and inferring high-level request properties (e.g., cpu and i/o resource needs). our key finding is that effective request signatures may be constructed using a small amount of hardware statistics while the request is still in an early stage of its execution. such on-the-fly request identification and property inference allow guided operating system adaptation at request granularity (e.g., resource-aware request scheduling and on-the-fly request classification). we address the challenges of selecting hardware counter metrics for signature construction and providing necessary operating system support for per-request statistics management. our implementation in the linux 2.6.10 kernel suggests that our approach requires low overhead suitable for runtime deployment. our on-the-fly request resource consumption inference (averaging 7%, 3%, 20%, and 41% prediction errors for four server workloads, tpc-c, tpc-h, j2ee-based rubis, and a trace-driven index search, respectively) is much more accurate than the online running-average based prediction (73-82% errors). its use for resource-aware request scheduling results in a 15-70% response time reduction for three cpu-bound applications. its use for on-the-fly request classification and anomaly detection exhibits high accuracy for the tpc-h workload with synthetically generated anomalous requests following a typical sql-injection attack pattern.
hybrid transactional memory. transactional memory (tm) promises to substantially reduce the difficulty of writing correct, efficient, and scalable concurrent programs. but "bounded" and "best-effort" hardware tm proposals impose unreasonable constraints on programmers, while more flexible software tm implementations are considered too slow. proposals for supporting "unbounded" transactions in hardware entail significantly higher complexity and risk than best-effort designs.we introduce hybrid transactional memory (hytm), an approach to implementing tmin software so that it can use best effort hardware tm (htm) to boost performance but does not depend on htm. thus programmers can develop and test transactional programs in existing systems today, and can enjoy the performance benefits of htm support when it becomes available.we describe our prototype hytm system, comprising a compiler and a library. the compiler allows a transaction to be attempted using best-effort htm, and retried using the software library if it fails. we have used our prototype to "transactify" part of the berkeley db system, as well as several benchmarks. by disabling the optional use of htm, we can run all of these tests on existing systems. furthermore, by using a simulated multiprocessor with htm support, we demonstrate the viability of the hytm approach: it can provide performance and scalability approaching that of an unbounded htm implementation, without the need to support all transactions with complicated htm support.
maximum benefit from a minimal htm. a minimal, bounded hardware transactional memory implementation significantly improves synchronization performance when used in an operating system kernel. we add htm to linux 2.4, a kernel with a simple, coarse-grained synchronization structure. the transactional linux 2.4 kernel can improve performance of user programs by as much as 40% over the non-transactional 2.4 kernel. it closes 68% of the performance gap with the linux 2.6 kernel, which has had significant engineering effort applied to improve scalability. we then extend our minimal htm to a fast, unbounded transactional memory with a novel technique for coordinating hardware transactions and software synchronization. overflowed transactions run in software, with only a minimal coupling between hardware and software systems. there is no performance penalty for overflow rates of less than 1%. in one instance, at 16 processors and an overflow rate of 4%, performance degrades from an ideal 4.3x to 3.6x.
a performance counter architecture for computing accurate cpi components. a common way of representing processor performance is to use cycles per instruction (cpi) `stacks' which break performance into a baseline cpi plus a number of individual miss event cpi components. cpi stacks can be very helpful in gaining insight into the behavior of an application on a given microprocessor; consequently, they are widely used by software application developers and computer architects. however, computing cpi stacks on superscalar out-of-order processors is challenging because of various overlaps among execution and miss events (cache misses, tlb misses, and branch mispredictions).this paper shows that meaningful and accurate cpi stacks can be computed for superscalar out-of-order processors. using interval analysis, a novel method for analyzing out-of-order processor performance, we gain understanding into the performance impact of the various miss events. based on this understanding, we propose a novel way of architecting hardware performance counters for building accurate cpi stacks. the additional hardware for implementing these counters is limited and comparable to existing hardware performance counter architectures while being significantly more accurate than previous approaches.
twindrivers: semi-automatic derivation of fast and safe hypervisor network drivers from guest os drivers. in a virtualized environment, device drivers are often run inside a virtual machine (vm) rather than in the hypervisor, for reasons of safety and reduction in software engineering effort. unfortunately, this approach results in poor performance for i/o-intensive devices such as network cards. the alternative approach of running device drivers directly in the hypervisor yields better performance, but results in the loss of safety guarantees for the hypervisor and incurs additional software engineering costs. in this paper we present twindrivers, a framework which allows us to semi-automatically create safe and efficient hypervisor drivers from guest os drivers. the hypervisor driver runs directly in the hypervisor, but its data resides completely in the driver vm address space. a software virtual memory mechanism allows the driver to access its vm data efficiently from the hypervisor running in any guest context, and also protects the hypervisor from invalid memory accesses from the driver. an upcall mechanism allows the hypervisor to largely reuse the driver support infrastructure present in the vm. the twindriver system thus combines most of the performance benefits of hypervisor-based driver approaches with the safety and software engineering benefits of vm-based driver approaches. using the twindrivers hypervisor driver, we are able to improve the guest domain networking throughput in xen by a factor of 2.4 for transmit workloads, and 2.1 for receive workloads, both in cpu-scaled units, and achieve close to 64-67 of native linux throughput.
exploiting coarse-grained task, data, and pipeline parallelism in stream programs. as multicore architectures enter the mainstream, there is a pressing demand for high-level programming models that can effectively map to them. stream programming offers an attractive way to expose coarse-grained parallelism, as streaming applications (image, video, dsp, etc.) are naturally represented by independent filters that communicate over explicit data channels.in this paper, we demonstrate an end-to-end stream compiler that attains robust multicore performance in the face of varying application characteristics. as benchmarks exhibit different amounts of task, data, and pipeline parallelism, we exploit all types of parallelism in a unified manner in order to achieve this generality. our compiler, which maps from the streamit language to the 16-core raw architecture, attains a 11.2x mean speedup over a single-core baseline, and a 1.84x speedup over our previous work.
leak pruning. managed languages improve programmer productivity with type safety and garbage collection, which eliminate memory errors such as dangling pointers, double frees, and buffer overflows. however, because garbage collection uses reachability to over-approximate live objects, programs may still leak memory if programmers forget to eliminate the last reference to an object that will not be used again. leaks slow programs by increasing collector workload and frequency. growing leaks eventually crash programs. this paper introduces leak pruning, which keeps programs running by predicting and reclaiming leaked objects at run time. it predicts dead objects and reclaims them based on observing data structure usage patterns. leak pruning preserves semantics because it waits for heap exhaustion before reclaiming objects and poisons references to objects it reclaims. if the program later tries to access a poisoned reference, the virtual machine (vm) throws an error. we show leak pruning has low overhead in a java vm and evaluate it on 10 leaking programs. leak pruning does not help two programs, executes five substantial programs 1.6-81x longer, and executes three programs, including a leak in eclipse, for at least 24 hours. in the worst case, leak pruning defers fatal errors. in the best case, it keeps leaky programs running with preserved semantics and consistent throughput.
gordon: using flash memory to build fast, power-efficient clusters for data-intensive applications. as our society becomes more information-driven, we have begun to amass data at an astounding and accelerating rate. at the same time, power concerns have made it difficult to bring the necessary processing power to bear on querying, processing, and understanding this data. we describe gordon, a system architecture for data-centric applications that combines low-power processors, flash memory, and data-centric programming systems to improve performance for data-centric applications while reducing power consumption. the paper presents an exhaustive analysis of the design space of gordon systems, focusing on the trade-offs between power, energy, and performance that gordon must make. it analyzes the impact of flash-storage and the gordon architecture on the performance and power efficiency of data-centric applications. it also describes a novel flash translation layer tailored to data intensive workloads and large flash storage arrays. our data show that, using technologies available in the near future, gordon systems can out-perform disk-based clusters by 1.5× and deliver up to 2.5× more performance per watt.
efficiently exploring architectural design spaces via predictive modeling. architects use cycle-by-cycle simulation to evaluate design choices and understand tradeoffs and interactions among design parameters. efficiently exploring exponential-size design spaces with many interacting parameters remains an open problem: the sheer number of experiments renders detailed simulation intractable. we attack this problem via an automated approach that builds accurate, confident predictive design-space models. we simulate sampled points, using the results to teach our models the function describing relationships among design parameters. the models produce highly accurate performance estimates for other points in the space, can be queried to predict performance impacts of architectural changes, and are very fast compared to simulation, enabling efficient discovery of tradeoffs among parameters in different regions. we validate our approach via sensitivity studies on memory hierarchy and cpu design spaces: our models generally predict ipc with only 1-2% error and reduce required simulation by two orders of magnitude. we also show the efficacy of our technique for exploring chip multiprocessor (cmp) design spaces: when trained on a 1% sample drawn from a cmp design space with 250k points and up to 55x performance swings among different system configurations, our models predict performance with only 4-5% error on average. our approach combines with techniques to reduce time per simulation, achieving net time savings of three-four orders of magnitude.
complete information flow tracking from the gates up. for many mission-critical tasks, tight guarantees on the flow of information are desirable, for example, when handling important cryptographic keys or sensitive financial data. we present a novel architecture capable of tracking all information flow within the machine, including all explicit data transfers and all implicit flows (those subtly devious flows caused by not performing conditional operations). while the problem is impossible to solve in the general case, we have created a machine that avoids the general-purpose programmability that leads to this impossibility result, yet is still programmable enough to handle a variety of critical operations such as public-key encryption and authentication. through the application of our novel gate-level information flow tracking method, we show how all flows of information can be precisely tracked. from this foundation, we then describe how a class of architectures can be constructed, from the gates up, to completely capture all information flows and we measure the impact of doing so on the hardware implementation, the isa, and the programmer.
geiger: monitoring the buffer cache in a virtual machine environment. virtualization is increasingly being used to address server management and administration issues like flexible resource allocation, service isolation and workload migration. in a virtualized environment, the virtual machine monitor (vmm) is the primary resource manager and is an attractive target for implementing system features like scheduling, caching, and monitoring. however, the lackof runtime information within the vmm about guest operating systems, sometimes called the semantic gap, is a significant obstacle to efficiently implementing some kinds of services.in this paper we explore techniques that can be used by a vmm to passively infer useful information about a guest operating system's unified buffer cache and virtual memory system. we have created a prototype implementation of these techniques inside the xen vmm called geiger and show that it can accurately infer when pages are inserted into and evicted from a system's buffer cache. we explore several nuances involved in passively implementing eviction detection that have not previously been addressed, such as the importance of tracking disk block liveness, the effect of file system journaling, and the importance of accounting for the unified caches found in modern operating systems.using case studies we show that the information provided by geiger enables a vmm to implement useful vmm-level services. we implement a novel working set size estimator which allows the vmm to make more informed memory allocation decisions. we also show that a vmm can be used to drastically improve the hit rate in remote storage caches by using eviction-based cache placement without modifying the application or operating system storage interface. both case studies hint at a future where inference techniques enable a broad new class of vmm-level functionality.
dmp: deterministic shared memory multiprocessing. current shared memory multicore and multiprocessor systems are nondeterministic. each time these systems execute a multithreaded application, even if supplied with the same input, they can produce a different output. this frustrates debugging and limits the ability to properly test multithreaded code, becoming a major stumbling block to the much-needed widespread adoption of parallel programming. in this paper we make the case for fully deterministic shared memory multiprocessing (dmp). the behavior of an arbitrary multithreaded program on a dmp system is only a function of its inputs. the core idea is to make inter-thread communication fully deterministic. previous approaches to coping with nondeterminism in multithreaded programs have focused on replay, a technique useful only for debugging. in contrast, while dmp systems are directly useful for debugging by offering repeatability by default, we argue that parallel programs should execute deterministically in the field as well. this has the potential to make testing more assuring and increase the reliability of deployed multithreaded software. we propose a range of approaches to enforcing determinism and discuss their implementation trade-offs. we show that determinism can be provided with little performance cost using our architecture proposals on future hardware, and that software-only approaches can be utilized on existing systems.
a new idiom recognition framework for exploiting hardware-assist instructions. modern processors support hardware-assist instructions (such as trt and trot instructions on ibm zseries) to accelerate certain functions such as delimiter search and character conversion. such special instructions have often been used in high performance libraries, but they have not been exploited well in optimizing compilers except for some limited cases. we propose a new idiom recognition technique derived from a topological embedding algorithm [4] to detect idiom patterns in the input program more aggressively than in previous approaches. our approach can detect a pattern even if the code segment does not exactly match the idiom. for example, we can detect a code segment that includes additional code within the idiom pattern. we implemented our new idiom recognition approach based on the java just-in-time (jit) compiler that is part of the j9 java virtual machine, and we supported several important idioms for special hardware-assist instructions on the ibm zseries and on some models of the ibm pseries. to demonstrate the effectiveness of our technique, we performed two experiments. the first one is to see how many more patterns we can detect compared to the previous approach. the second one is to see how much performance improvement we can achieve over the previous approach. for the first experiment, we used the java compatibility kit (jck) api tests. for the second one we used ibm xml parser, specjvm98, and spcjbb2000. in summary, relative to a baseline implementation using exact pattern matching, our algorithm converted 75% more loops in jck tests. we also observed significant performance improvement of the xml parser by 64%, of specjvm98 by 1%, and of specjbb2000 by 2% on average on a z990. finally, we observed the jit compilation time increases by only 0.32% to 0.44%.
adapting to intermittent faults in multicore systems. future multicore processors will be more susceptible to a variety of hardware failures. in particular, intermittent faults, caused in part by manufacturing, thermal, and voltage variations, can cause bursts of frequent faults that last from several cycles to several seconds or more. due to practical limitations of circuit techniques, cost-effective reliability will likely require the ability to temporarily suspend execution on a core during periods of intermittent faults. we investigate three of the most obvious techniques for adapting to the dynamically changing resource availability caused by intermittent faults, and demonstrate their different system-level implications. we show that system software reconfiguration has very high overhead, that temporarily pausing execution on a faulty core can lead to cascading livelock, and that using spare cores has high fault-free cost. to remedy these and other drawbacks of the three baseline techniques, we propose using a thin hardware/firmware layer to manage an overcommitted system -- one where the os is configured to use more virtual processors than the number of currently available physical cores. we show that this proposed technique can gracefully degrade performance during intermittent faults of various duration with low overhead, without involving system software, and without requiring spare cores.
predictor virtualization. many hardware optimizations rely on collecting information about program behavior at runtime. this information is stored in lookup tables. to be accurate and effective, these optimizations usually require large dedicated on-chip tables. although technology advances offer an increased amount of on-chip resources, these resources are allocated to increase the size of on-chip conventional cache hierarchies. this work proposes predictor virtualization, a technique that uses the existing memory hierarchy to emulate large predictor tables. we demonstrate the benefits of this technique by virtualizing a state-of-the-art data prefetcher. full-system, cycle-accurate simulations demonstrate that the virtualized prefetcher preserves the performance benefits of the original design, while reducing the on-chip storage dedicated to the predictor table from 60kb down to less than one kilobyte.
merge: a programming model for heterogeneous multi-core systems. in this paper we propose the merge framework, a general purpose programming model for heterogeneous multi-core systems. the merge framework replaces current ad hoc approaches to parallel programming on heterogeneous platforms with a rigorous, library-based methodology that can automatically distribute computation across heterogeneous cores to achieve increased energy and performance efficiency. the merge framework provides (1) a predicate dispatch-based library system for managing and invoking function variants for multiple architectures; (2) a high-level, library-oriented parallel language based on map-reduce; and (3) a compiler and runtime which implement the map-reduce language pattern by dynamically selecting the best available function implementations for a given input and machine configuration. using a generic sequencer architecture interface for heterogeneous accelerators, the merge framework can integrate function variants for specialized accelerators, offering the potential for to-the-metal performance for a wide range of heterogeneous architectures, all transparent to the user. the merge framework has been prototyped on a heterogeneous platform consisting of an intel core 2 duo cpu and an 8-core 32-thread intel graphics and media accelerator x3000, and a homogeneous 32-way unisys smp system with intel xeon processors. we implemented a set of benchmarks using the merge framework and enhanced the library with x3000 specific implementations, achieving speedups of 3.6x -- 8.5x using the x3000 and 5.2x -- 22x using the 32-way system relative to the straight c reference implementation on a single ia32 core.
accurate and efficient regression modeling for microarchitectural performance and power prediction. we propose regression modeling as an efficient approach for accurately predicting performance and power for various applications executing on any microprocessor configuration in a large microarchitectural design space. this paper addresses fundamental challenges in microarchitectural simulation cost by reducing the number of required simulations and using simulated results more effectively via statistical modeling and inference.specifically, we derive and validate regression models for performance and power. such models enable computationally efficient statistical inference, requiring the simulation of only 1 in 5 million points of a joint microarchitecture-application design space while achieving median error rates as low as 4.1 percent for performance and 4.3 percent for power. although both models achieve similar accuracy, the sources of accuracy are strikingly different. we present optimizations for a baseline regression model to obtain (1) application-specific models to maximize accuracy in performance prediction and (2) regional power models leveraging only the most relevant samples from the microarchitectural design space to maximize accuracy in power prediction. assessing sensitivity to the number of samples simulated for model formulation, we find fewer than 4,000 samples from a design space of approximately 22 billion points are sufficient. collectively, our results suggest significant potential in accurate and efficient statistical inference for microarchitectural design space exploration via regression models.
rapidmrc: approximating l2 miss rate curves on commodity systems for online optimizations. miss rate curves (mrcs) are useful in a number of contexts. in our research, online l2 cache mrcs enable us to dynamically identify optimal cache sizes when cache-partitioning a shared-cache multicore processor. obtaining l2 mrcs has generally been assumed to be expensive when done in software and consequently, their usage for online optimizations has been limited. to address these problems and opportunities, we have developed a low-overhead software technique to obtain l2 mrcs online on current processors, exploiting features available in their performance monitoring units so that no changes to the application source code or binaries are required. our technique, called rapidmrc, requires a single probing period of roughly 221 million processor cycles (147 ms), and subsequently 124 million cycles (83 ms) to process the data. we demonstrate its accuracy by comparing the obtained mrcs to the actual l2 mrcs of 30 applications taken from speccpu2006, speccpu2000, and specjbb2000. we show that rapidmrc can be applied to sizing cache partitions, helping to achieve performance improvements of up to 27%.
mapping esterel onto a multi-threaded embedded processor. the synchronous language esterel is well-suited for programming control-dominated reactive systems at the system level. it provides non-traditional control structures, in particular concurrency and various forms of preemption, which allow to concisely express reactive behavior. as these control structures cannot be mapped easily onto traditional, sequential processors, an alternative approach that has emerged recently makes use of special-purpose reactive processors. however, the designs proposed so far have limitations regarding completeness of the language support, and did not really take advantage of compile-time knowledge to optimize resource usage.this paper presents a reactive processor, the kiel esterel processor 3a (kep3a), and its compiler. the kep3a improves on earlier designs in several areas; most notable are the support for exception handling and the provision of context-dependent preemption handling instructions. the kep3a compiler presented here is to our knowledge the first for multi-threaded reactive processors. the translation of esterel's preemption constructs onto kep3a assembler is straightforward; however, a challenge is the correct and efficient representation of esterel's concurrency. the compiler generates code that respects data and control dependencies using the kep3a priority-based scheduling mechanism. we present a priority assignment approach that makes use of a novel concurrent control flow graph and has a complexity that in practice tends to be linear in the size of the program. unlike earlier esterel compilation schemes, this approach avoids unnecessary context switches by considering each thread's actual execution state at run time. furthermore, it avoids code replication present in other approaches.
powernap: eliminating server idle power. data center power consumption is growing to unprecedented levels: the epa estimates u.s. data centers will consume 100 billion kilowatt hours annually by 2011. much of this energy is wasted in idle systems: in typical deployments, server utilization is below 30%, but idle servers still consume 60% of their peak power draw. typical idle periods though frequent--last seconds or less, confounding simple energy-conservation approaches. in this paper, we propose powernap, an energy-conservation approach where the entire system transitions rapidly between a high-performance active state and a near-zero-power idle state in response to instantaneous load. rather than requiring fine-grained power-performance states and complex load-proportional operation from each system component, powernap instead calls for minimizing idle power and transition time, which are simpler optimization goals. based on the powernap concept, we develop requirements and outline mechanisms to eliminate idle power waste in enterprise blade servers. because powernap operates in low-efficiency regions of current blade center power supplies, we introduce the redundant array for inexpensive load sharing (rails), a power provisioning approach that provides high conversion efficiency across the entire range of powernap's power demands. using utilization traces collected from enterprise-scale commercial deployments, we demonstrate that, together, powernap and rails reduce average server power consumption by 74%.
avio: detecting atomicity violations via access interleaving invariants. this article proposes an innovative concurrent-program invariant that captures programmers' atomicity assumptions. it describes a tool with two implementations, one in software and the other using hardware support, that can automatically extract such invariants and detect atomicity bugs.
dftl: a flash translation layer employing demand-based selective caching of page-level address mappings. recent technological advances in the development of flash-memory based devices have consolidated their leadership position as the preferred storage media in the embedded systems market and opened new vistas for deployment in enterprise-scale storage systems. unlike hard disks, flash devices are free from any mechanical moving parts, have no seek or rotational delays and consume lower power. however, the internal idiosyncrasies of flash technology make its performance highly dependent on workload characteristics. the poor performance of random writes has been a cause of major concern, which needs to be addressed to better utilize the potential of flash in enterprise-scale environments. we examine one of the important causes of this poor performance: the design of the flash translation layer (ftl), which performs the virtual-to-physical address translations and hides the erase-before-write characteristics of flash. we propose a complete paradigm shift in the design of the core ftl engine from the existing techniques with our demand-based flash translation layer (dftl), which selectively caches page-level address mappings. we develop a flash simulation framework called flashsim. our experimental evaluation with realistic enterprise-scale workloads endorses the utility of dftl in enterprise-scale storage systems by demonstrating: (i) improved performance, (ii) reduced garbage collection overhead and (iii) better overload behavior compared to state-of-the-art ftl schemes. for example, a predominantly random-write dominant i/o trace from an oltp application running at a large financial institution shows a 78% improvement in average response time (due to a 3-fold reduction in operations of the garbage collector), compared to a state-of-the-art ftl scheme. even for the well-known read-dominant tpc-h benchmark, for which dftl introduces additional overheads, we improve system response time by 56%.
instruction scheduling for a tiled dataflow architecture. this paper explores hierarchical instruction scheduling for a tiled processor. our results show that at the top level of the hierarchy, a simple profile-driven algorithm effectively minimizes operand latency. after this schedule has been partitioned into large sections, the bottom-level algorithm must more carefully analyze program structure when producing the final schedule.our analysis reveals that at this bottom level, good scheduling depends upon carefully balancing instruction contention for processing elements and operand latency between producer and consumer instructions. we develop a parameterizable instruction scheduler that more effectively optimizes this trade-off. we use this scheduler to determine the contention-latency sweet spot that generates the best instruction schedule for each application. to avoid this application-specific tuning, we also determine the parameters that produce the best performance across all applications. the result is a contention-latency setting that generates instruction schedules for all applications in our workload that come within 17% of the best schedule for each.
mixed-mode multicore reliability. future processors are expected to observe increasing rates of hardware faults. using dual-modular redundancy (dmr), two cores of a multicore can be loosely coupled to redundantly execute a single software thread, providing very high coverage from many difference sources of faults. this reliability, however, comes at a high price in terms of per-thread ipc and overall system throughput. we make the observation that a user may want to run both applications requiring high reliability, such as financial software, and more fault tolerant applications requiring high performance, such as media or web software, on the same machine at the same time. yet a traditional dmr system must fully operate in redundant mode whenever any application requires high reliability. this paper proposes a mixed-mode multicore (mmm), which enables most applications, including the system software, to run with high reliability in dmr mode, while applications that need high performance can avoid the penalty of dmr. though conceptually simple, two key challenges arise: 1) care must be taken to protect reliable applications from any faults occurring to applications running in high performance mode, and 2) the desire to execute additional independent software threads for a performance application complicates the scheduling of computation to cores. after solving these issues, an mmm is shown to improve overall system performance, compared to a traditional dmr system, by approximately 2x when one reliable and one performance application are concurrently executing.
software-based instruction caching for embedded processors. while hardware instruction caches are present in virtually all general-purpose and high-performance microprocessors today, many embedded processors use sram or scratchpad memories instead. these are simple array memory structures that are directly addressed and explicitly managed by software. compared to hardware caches of the same data capacity, they are smaller, have shorter access times and consume less energy per access. access times are also easier to predict with simple memories since there is no possibility of a "miss." on the other hand, they are more difficult for the programmer to use since they are not automatically managed.in this paper, we present a software system that allows all or part of an sram or scratchpad memory to be automatically managed as a cache. this system provides the programming convenience of a cache for processors that lack dedicated caching hardware. it has been implemented for an actual processor and runs on real hardware. our results show that a software-based instruction cache can be built that provides performance within 10% of a traditional hardware cache on many benchmarks while using a cheaper, simpler, sram memory. on these same benchmarks, energy consumption is up to 3% lower than it would be using a hardware cache.
accelerating critical section execution with asymmetric multi-core architectures. to improve the performance of a single application on chip multiprocessors (cmps), the application must be split into threads which execute concurrently on multiple cores. in multi-threaded applications, critical sections are used to ensure that only one thread accesses shared data at any given time. critical sections can serialize the execution of threads, which significantly reduces performance and scalability. this paper proposes accelerated critical sections (acs), a technique that leverages the high-performance core(s) of an asymmetric chip multiprocessor (acmp) to accelerate the execution of critical sections. in acs, selected critical sections are executed by a high-performance core, which can execute the critical section faster than the other, smaller cores. as a result, acs reduces serialization: it lowers the likelihood of threads waiting for a critical section to finish. our evaluation on a set of 12 critical-section-intensive workloads shows that acs reduces the average execution time by 34% compared to an equal-area 32t-core symmetric cmp and by 23% compared to an equal-area acmp. moreover, for 7 out of the 12 workloads, acs improves scalability by increasing the number of threads at which performance saturates.
tartan: evaluating spatial computation for whole program execution. spatial computing (sc) has been shown to be an energy-efficient model for implementing program kernels. in this paper we explore the feasibility of using sc for more than small kernels. to this end, we evaluate the performance and energy efficiency of entire applications on tartan, a general-purpose architecture which integrates a reconfigurable fabric (rf) with a superscalar core. our compiler automatically partitions and compiles an application into an instruction stream for the core and a configuration for the rf. we use a detailed simulator to capture both timing and energy numbers for all parts of the system.our results indicate that a hierarchical rf architecture, designed around a scalable interconnect, is instrumental in harnessing the benefits of spatial computation. the interconnect uses static configuration and routing at the lower levels and a packet-switched, dynamically-routed network at the top level. tartan is most energyefficient when almost all of the application is mapped to the rf, indicating the need for the rf to support most general-purpose programming constructs. our initial investigation reveals that such a system can provide, on average, an order of magnitude improvement in energy-delay compared to an aggressive superscalar core on single-threaded workloads.
producing wrong data without doing anything obviously wrong! this paper presents a surprising result: changing a seemingly innocuous aspect of an experimental setup can cause a systems researcher to draw wrong conclusions from an experiment. what appears to be an innocuous aspect in the experimental setup may in fact introduce a significant bias in an evaluation. this phenomenon is called measurement bias in the natural and social sciences. our results demonstrate that measurement bias is significant and commonplace in computer system evaluation. by significant we mean that measurement bias can lead to a performance analysis that either over-states an effect or even yields an incorrect conclusion. by commonplace we mean that measurement bias occurs in all architectures that we tried (pentium 4, core 2, and m5 o3cpu), both compilers that we tried (gcc and intel's c compiler), and most of the spec cpu2006 c programs. thus, we cannot ignore measurement bias. nevertheless, in a literature survey of 133 recent papers from asplos, pact, pldi, and cgo, we determined that none of the papers with experimental results adequately consider measurement bias. inspired by similar problems and their solutions in other sciences, we describe and demonstrate two methods, one for detecting (causal analysis) and one for avoiding (setup randomization) measurement bias.
supporting nested transactional memory in logtm. nested transactional memory (tm) facilitates software composition by letting one module invoke another without either knowing whether the other uses transactions. closed nested transactions extend isolation of an inner transaction until the toplevel transaction commits. implementations may flatten nested transactions into the top-level one, resulting in a complete abort on conflict, or allow partial abort of inner transactions. open nested transactions allow a committing inner transaction to immediately release isolation, which increases parallelism and expressiveness at the cost of both software and hardware complexity.this paper extends the recently-proposed flat log-based transactional memory (logtm) with nested transactions. flat logtm saves pre-transaction values in a log, detects conflicts with read (r) and write (w) bits per cache block, and, on abort, invokes a software handler to unroll the log. nested logtm supports nesting by segmenting the log into a stack of activation records and modestly replicating r/w bits. to facilitate composition with nontransactional code, such as language runtime and operating system services, we propose escape actions that allow trusted code to run outside the confines of the transactional memory system.
dynamic prediction of collection yield for managed runtimes. the growth in complexity of modern systems makes it increasingly difficult to extract high-performance. the software stacks for such systems typically consist of multiple layers and include managed runtime environments (mres). in this paper, we investigate techniques to improve cooperation between these layers and the hardware to increase the efficacy of automatic memory management in mres. general-purpose mres commonly implement parallel and/or concurrent garbage collection and employ compaction to eliminate heap fragmentation. moreover, most systems trigger collection based on the amount of heap a program uses. our analysis shows that in many cases this strategy leads to ineffective collections that are unable to reclaim sufficient space to justify the incurred cost. to avoid such collections, we exploit the observation that dead objects tend to cluster together and form large, never-referenced, regions in the address space that correlate well with virtual pages that have not recently been referenced by the application. we leverage this correlation to design a new, simple and light-weight, yield predictor that estimates the amount of reclaimable space in the heap using hardware page reference bits. our predictor allows mres to avoid low-yield collections and thereby improve resource management. we integrate this predictor into three state-of-the-art parallel compactors, implemented in the hotspot jvm, that represent distinct canonical heap layouts. our empirical evaluation, based on standard java benchmarks and open-source applications, indicates that inexpensive and accurate yield prediction can improve performance significantly.
introspective 3d chips. while the number of transistors on a chip increases exponentially over time, the productivity that can be realized from these systems has not kept pace. to deal with the complexity of modern systems, software developers are increasingly dependent on specialized development tools such as security profilers, memory leak identifiers, data flight recorders, and dynamic type analysis. many of these tools require full-system data which covers multiple interacting threads, processes, and processors. reducing the performance penalty and complexity of these software tools is critical to those developing next generation applications, and many researchers have proposed adding specialized hardware to assist in profiling and introspection. unfortunately, while this additional hardware would be incredibly beneficial to developers, the cost of this hardware must be paid on every single die that is manufactured.in this paper, we argue that a new way to attack this problem is with the addition of specialized analysis hardware built on separate active layers stacked vertically on the processor die using 3d ic technology. this provides a modular "snap-on" functionality that could be included with developer systems, and omitted from consumer systems to keep the cost impact to a minimum. in this paper we describe the advantage of using inter-die vias for introspection and we quantify the impact they can have in terms of the area, power, temperature, and routability of the resulting systems. we show that hardware stubs could be inserted into commodity processors at design time that would allow analysis layers to be bonded to development chips, and that these stubs would increase area and power by no more than 0.021mm2 and 0.9% respectively.
per-thread cycle accounting in smt processors. this paper proposes a cycle accounting architecture for simultaneous multithreading (smt) processors that estimates the execution times for each of the threads had they been executed alone, while they are running simultaneously on the smt processor. this is done by accounting each cycle to either a base, miss event or waiting cycle component during multi-threaded execution. single-threaded alone execution time is then estimated as the sum of the base and miss event components; the waiting cycle component represents the lost cycle count due to smt execution. the cycle accounting architecture incurs reasonable hardware cost (around 1kb of storage) and estimates single-threaded performance with average prediction errors around 7.2% for two-program workloads and 11.7% for four-program workloads. the cycle accounting architecture has several important applications to system software and its interaction with smt hardware. for one, the estimated single-thread alone execution time provides an accurate picture to system software of the actually consumed processor cycles per thread. the alone execution time instead of the total execution time (timeslice) may make system software scheduling policies more effective. second, a new class of thread-progress aware smt fetch policies based on per-thread progress indicators enable system software level priorities to be enforced at the hardware level.
recording shared memory dependencies using strata. significant time is spent by companies trying to reproduce and fix bugs. bugnet and fdr are recent architecture proposals that provide architecture support for deterministic replay debugging. they focus on continuously recording information about the program's execution, which can be communicated back to the developer. using that information, the developer can deterministically replay the program's execution to reproduce and fix the bugs.in this paper, we propose using strata to efficiently capture the shared memory dependencies. a stratum creates a time layer across all the logs for the running threads, which separates all the memory operations executed before and after the stratum. a strata log allows us to determine all the shared memory dependencies during replay and thereby supports deterministic replay debugging for multi-threaded programs.
an evaluation of the trips computer system. the trips system employs a new instruction set architecture (isa) called explicit data graph execution (edge) that renegotiates the boundary between hardware and software to expose and exploit concurrency. edge isas use a block-atomic execution model in which blocks are composed of dataflow instructions. the goal of the trips design is to mine concurrency for high performance while tolerating emerging technology scaling challenges, such as increasing wire delays and power consumption. this paper evaluates how well trips meets this goal through a detailed isa and performance analysis. we compare performance, using cycles counts, to commercial processors. on spec cpu2000, the intel core 2 outperforms compiled trips code in most cases, although trips matches a pentium 4. on simple benchmarks, compiled trips code outperforms the core 2 by 10% and hand-optimized trips code outperforms it by factor of 3. compared to conventional isas, the block-atomic model provides a larger instruction window, increases concurrency at a cost of more instructions executed, and replaces register and memory accesses with more efficient direct instruction-to-instruction communication. our analysis suggests isa, microarchitecture, and compiler enhancements for addressing weaknesses in trips and indicates that edge architectures have the potential to exploit greater concurrency in future technologies.
slick: slice-based locality exploitation for efficient redundant multithreading. transient faults are expected a be a major design consideration in future microprocessors. recent proposals for transient fault detection in processor cores have revolved around the idea of redundant threading, which involves redundant execution of a program across multiple execution contexts. this paper presents a new approach to redundant threading by bringing together the concepts of slice-level execution and value and control-flow locality into a novel partial redundant threading mechanism called slick.the purpose of redundant execution is to check the integrity of the outputs propagating out of the core (typically through stores). slick implements redundancy at the granularity of backward-slices of these output instructions and exploits value and control-flow locality to avoid redundantly executing slices that lead to predictable outputs, thereby avoiding redundant execution of a significant fraction of instructions while maintaining extremely low vulnerabilities for critical processor structures.we propose the microarchitecture of a backward-slice extractor called sliceem that is able to identify backward slices without interrupting the instruction flow, and show how this extractor and a set of predictors can be integrated into a redundant threading mechanism to form slick. detailed simulations with spec cpu2000 benchmarks show that slick can provide around 10.2% performance improvement over a well known redundant threading mechanism, buying back over 50% of the loss suffered due to redundant execution. slick can keep the architectural vulnerability factors of processor structures to typically 0%-2%. more importantly, slick's slice-based mechanisms provide future opportunities for exploring interesting points in the performance-reliability design space based on market segment needs.
phantom-btb: a virtualized branch target buffer design. modern processors use branch target buffers (btbs) to predict the target address of branches such that they can fetch ahead in the instruction stream increasing concurrency and performance. ideally, btbs would be sufficiently large to capture the entire working set of the application and sufficiently small for fast access and practical on-chip dedicated storage. depending on the application, these requirements are at odds. this work introduces a btb design that accommodates large instruction footprints without dedicating expensive onchip resources. in the proposed phantom-btb (pbtb) design, a conventional btb is augmented with a virtual table that collects branch target information as the application runs. the virtual table does not have fixed dedicated storage. instead, it is transparently allocated, on demand, in the on-chip caches, at cache line granularity. the entries in the virtual table are proactively prefetched and installed in the dedicated conventional btb, thus, increasing its perceived capacity. experimental results with commercial workloads under full-system simulation demonstrate that pbtb improves ipc performance over a 1k-entry btb by 6.9% on average and up to 12.7%, with a storage overhead of only 8%. overall, the virtualized design performs within 1% of a conventional 4k-entry, single-cycle access btb, while the dedicated storage is 3.6 times smaller.
a defect tolerant self-organizing nanoscale simd architecture. the continual decrease in transistor size (through either scaled cmos or emerging nano-technologies) promises to usher in an era of tera to peta-scale integration. however, this decrease in size is also likely to increase defect densities, contributing to the exponentially increasing cost of top-down lithography. bottom-up manufacturing techniques, like self assembly, may provide a viable lower-cost alternative to top-down lithography, but may also be prone to higher defects. therefore, regardless of fabrication methodology, defect tolerant architectures are necessary to exploit the full potential of future increased device densities.this paper explores a defect tolerant simd architecture. a key feature of our design is the ability of a large number of limited capability nodes with high defect rates (up to 30%) to self-organize into a set of simd processing elements. despite node simplicity and high defect rates, we show that by supporting the familiar data parallel programming model the architecture can execute a variety of programs. the architecture efficiently exploits a large number of nodes and higher device densities to keep device switching speeds and power density low. on a medium sized system (~1cm2 area), the performance of the proposed architecture on our data parallel programs matches or exceeds the performance of an aggressively scaled out-of-order processor (128-wide, 8k reorder buffer, perfect memory system). for larger systems (>1cm2), the proposed architecture can match the performance of a chip multiprocessor with 16 aggressively scaled out-of-order cores.
recovery domains: an organizing principle for recoverable operating systems. we describe a strategy for enabling existing commodity operating systems to recover from unexpected run-time errors in nearly any part of the kernel, including core kernel components. our approach is dynamic and request-oriented; it isolates the effects of a fault to the requests that caused the fault rather than to static kernel components. this approach is based on a notion of "recovery domains," an organizing principle to enable rollback of state affected by a request in a multithreaded system with minimal impact on other requests or threads. we have applied this approach on v2.4.22 and v2.6.27 of the linux kernel and it required 132 lines of changed or new code: the other changes are all performed by a simple instrumentation pass of a compiler. our experiments show that the approach is able to recover from otherwise fatal faults with minimal collateral impact during a recovery event.
understanding prediction-based partial redundant threading for low-overhead, high- coverage fault tolerance. redundant threading architectures duplicate all instructions to detect and possibly recover from transient faults. several lighter weight partial redundant threading (prt) architectures have been proposed recently. (i) opportunistic fault tolerance duplicates instructions only during periods of poor single-thread performance. (ii) restore does not explicitly duplicate instructions and instead exploits mispredictions among highly confident branch predictions as symptoms of faults. (iii) slipstream creates a reduced alternate thread by replacing many instructions with highly confident predictions. we explore prt as a possible direction for achieving the fault tolerance of full duplication with the performance of single-thread execution. opportunistic and restore yield partial coverage since they are restricted to using only partial duplication or only confident predictions, respectively. previous analysis of slipstream fault tolerance was cursory and concluded that only duplicated instructions are covered. in this paper, we attempt to better understand slipstream's fault tolerance, conjecturing that the mixture of partial duplication and confident predictions actually closely approximates the coverage of full duplication. a thorough dissection of prediction scenarios confirms that faults in nearly 100% of instructions are detectable. fewer than 0.1% of faulty instructions are not detectable due to coincident faults and mispredictions. next we show that the current recovery implementation fails to leverage excellent detection capability, since recovery sometimes initiates belatedly, after already retiring a detected faulty instruction. we propose and evaluate a suite of simple microarchitectural alterations to recovery and checking. using the best alterations, slipstream can recover from faults in 99% of instructions, compared to only 78% of instructions without alterations. both results are much higher than predicted by past research, which claims coverage for only duplicated instructions, or 65% of instructions. on an 8-issue smt processor, slipstream performs within 1.3% of single-thread execution whereas full duplication slows performance by 14%.a key byproduct of this paper is a novel analysis framework in which every dynamic instruction is considered to be hypothetically faulty, thus not requiring explicit fault injection. fault coverage is measured in terms of the fraction of candidate faulty instructions that are directly or indirectly detectable before.
commutativity analysis for software parallelization: letting program transformations see the big picture. extracting performance from many-core architectures requires software engineers to create multi-threaded applications, which significantly complicates the already daunting task of software development. one solution to this problem is automatic compile-time parallelization, which can ease the burden on software developers in many situations. clearly, automatic parallelization in its present form is not suitable for many application domains and new compiler analyses are needed address its shortcomings. in this paper, we present one such analysis: a new approach for detecting commutative functions. commutative functions are sections of code that can be executed in any order without affecting the outcome of the application, e.g., inserting elements into a set. previous research on this topic had one significant limitation, in that the results of a commutative functions must produce identical memory layouts. this prevented previous techniques from detecting functions like malloc, which may return different pointers depending on the order in which it is called, but these differing results do not affect the overall output of the application. our new commutativity analysis correctly identify these situations to better facilitate automatic parallelization. we demonstrate that this analysis can automatically extract significant amounts of parallelism from many applications, and where it is ineffective it can provide software developers a useful list of functions that may be commutative provided semantic program changes that are not automatable.
impact of virtualization on computer architecture and operating systems. abstract this talk describes how virtualization is changing the way computing is done in the industry today and how it is causing users to rethink how they view hardware, operating systems, and application programs. the talk will describe this new view on computing and the benefits driving users to adopt it. the changing roles for hardware and operating systems will be discussed along with what changes will be needed to efficiently and simply support this new computing model. i will conclude with a discussion of areas where industry could use input from the asplos research community.
assure: automatic software self-healing using rescue points. software failures in server applications are a significant problem for preserving system availability. we present assure, a system that introduces rescue points that recover software from unknown faults while maintaining both system integrity and availability, by mimicking system behavior under known error conditions. rescue points are locations in existing application code for handling a given set of programmer-anticipated failures, which are automatically repurposed and tested for safely enabling fault recovery from a larger class of (unanticipated) faults. when a fault occurs at an arbitrary location in the program, assure restores execution to an appropriate rescue point and induces the program to recover execution by virtualizing the program's existing error-handling facilities. rescue points are identified using fuzzing, implemented using a fast coordinated checkpoint-restart mechanism that handles multi-process and multi-threaded applications, and, after testing, are injected into production code using binary patching. we have implemented an assure linux prototype that operates without application source code and without base operating system kernel changes. our experimental results on a set of real-world server applications and bugs show that assure enabled recovery for all of the bugs tested with fast recovery times, has modest performance overhead, and provides automatic self-healing orders of magnitude faster than current human-driven patch deployment methods.
a program transformation and architecture support for quantum uncomputation. quantum computing's power comes from new algorithms that exploit quantum mechanical phenomena for computation. quantum algorithms are different from their classical counterparts in that quantum algorithms rely on algorithmic structures that are simply not present in classical computing. just as classical program transformations and architectures have been designed for common classical algorithm structures, quantum program transformations and quantum architectures should be designed with quantum algorithms in mind. because quantum algorithms come with these new algorithmic structures, resultant quantum program transformations and architectures may look very different from their classical counterparts.this paper focuses on uncomputation, a critical and prevalent structure in quantum algorithms, and considers how program transformations, and architecture support should be designed to accommodate uncomputation. in this paper,we show a simple quantum program transformation that exposes independence between uncomputation and later computation. we then propose a multicore architecture tailored to this exposed parallelism and propose a scheduling policy that efficiently maps such parallelism to the multicore architecture. our policy achieves parallelism between uncomputation and later computation while reducing cumulative communication distance. our scheduling and architecture allows significant speedup of quantum programs (between 1.8x and 2.8x speedup in shor's factoring algorithm), while reducing cumulative communication distance 26%.
streamray: a stream filtering architecture for coherent ray tracing. the wide availability of commodity graphics processors has made real-time graphics an intrinsic component of the human/computer interface. these graphics cores accelerate the z-buffer algorithm and provide a highly interactive experience at a relatively low cost. however, many applications in entertainment, science, and industry require high quality lighting effects such as accurate shadows, reflection, and refraction. these effects can be difficult to achieve with z-buffer algorithms but are straightforward to implement using ray tracing. although ray tracing is computationally more complex, the algorithm exhibits excellent scaling and parallelism properties. nevertheless, ray tracing memory access patterns are difficult to predict and the parallelism speedup promise is therefore hard to achieve. this paper highlights a novel approach to ray tracing based on stream filtering and presents streamray, a multicore wide simd microarchitecture that delivers interactive frame rates of 15-32 frames/second for scenes of high geometric complexity and exhibits high utilization for simd widths ranging from eight to 16 elements. streamray consists of two main components: the ray engine, which is responsible for stream assembly and employs address generation units that generate addresses to form large simd vectors, and the filter engine, which implements the ray tracing operations with programmable accelerators. results demonstrate that separating address and data processing reduces data movement and resource contention. performance improves by 56% while simultaneously providing 11.63% power savings per accelerator core compared to a design which does not use separate resources for address and data computations.
ultra low-cost defect protection for microprocessor pipelines. the sustained push toward smaller and smaller technology sizes has reached a point where device reliability has moved to the forefront of concerns for next-generation designs. silicon failure mechanisms, such as transistor wearout and manufacturing defects, are a growing challenge that threatens the yield and product lifetime of future systems. in this paper we introduce the bulletproof pipeline, the first ultra low-cost mechanism to protect a microprocessor pipeline and on-chip memory system from silicon defects. to achieve this goal we combine area-frugal on-line testing techniques and system-level checkpointing to provide the same guarantees of reliability found in traditional solutions, but at much lower cost. our approach utilizes a microarchitectural checkpointing mechanism which creates coarse-grained epochs of execution, during which distributed on-line built in self-test (bist) mechanisms validate the integrity of the underlying hardware. in case a failure is detected, we rely on the natural redundancy of instructionlevel parallel processors to repair the system so that it can still operate in a degraded performance mode. using detailed circuit-level and architectural simulation, we find that our approach provides very high coverage of silicon defects (89%) with little area cost (5.8%). in addition, when a defect occurs, the subsequent degraded mode of operation was found to have only moderate performance impacts, (from 4% to 18% slowdown).
ctrigger: exposing atomicity violation bugs from their hiding places. multicore hardware is making concurrent programs pervasive. unfortunately, concurrent programs are prone to bugs. among different types of concurrency bugs, atomicity violation bugs are common and important. existing techniques to detect atomicity violation bugs suffer from one limitation: requiring bugs to manifest during monitored runs, which is an open problem in concurrent program testing. this paper makes two contributions. first, it studies the interleaving characteristics of the common practice in concurrent program testing (i.e., running a program over and over) to understand why atomicity violation bugs are hard to expose. second, it proposes ctrigger to effectively and efficiently expose atomicity violation bugs in large programs. ctrigger focuses on a special type of interleavings (i.e., unserializable interleavings) that are inherently correlated to atomicity violation bugs, and uses trace analysis to systematically identify (likely) feasible unserializable interleavings with low occurrence-probability. ctrigger then uses minimum execution perturbation to exercise low-probability interleavings and expose difficult-to-catch atomicity violation. we evaluate ctrigger with real-world atomicity violation bugs from four sever/desktop applications (apache, mysql, mozilla, and pbzip2) and three splash2 applications on 8-core machines. ctrigger efficiently exposes the tested bugs within 1--235 seconds, two to four orders of magnitude faster than stress testing. without ctrigger, some of these bugs do not manifest even after 7 full days of stress testing. in addition, without deterministic replay support, once a bug is exposed, ctrigger can help programmers reliably reproduce it for diagnosis. our tested bugs are reproduced by ctrigger mostly within 5 seconds, 300 to over 60000 times faster than stress testing.
a probabilistic pointer analysis for speculative optimizations. pointer analysis is a critical compiler analysis used to disambiguate the indirect memory references that result from the use of pointers and pointer-based data structures. a conventional pointer analysis deduces for every pair of pointers, at any program point, whether a points-to relation between them (i) definitely exists, (ii) definitely does not exist, or (iii) maybe exists. many compiler optimizations rely on accurate pointer analysis, and to ensure correctness cannot optimize in the maybe case. in contrast, recently-proposed speculative optimizations can aggressively exploit the maybe case, especially if the likelihood that two pointers alias can be quantified. this paper proposes a probabilistic pointer analysis (ppa) algorithm that statically predicts the probability of each points-to relation at every program point. building on simple control-flow edge profiling, our analysis is both one-level context and flow sensitive-yet can still scale to large programs including the spec 2000 integer benchmark suite. the key to our approach is to compute points-to probabilities through the use of linear transfer functions that are efficiently encoded as sparse matrices.we demonstrate that our analysis can provide accurate probabilities, even without edge-profile information. we also find that-even without considering probability information-our analysis provides an accurate approach to performing pointer analysis.
early experience with a commercial hardware transactional memory implementation. we report on our experience with the hardware transactional memory (htm) feature of two pre-production revisions of a new commercial multicore processor. our experience includes a number of promising results using htm to improve performance in a variety of contexts, and also identifies some ways in which the feature could be improved to make it even better. we give detailed accounts of our experiences, sharing techniques we used to achieve the results we have, as well as describing challenges we faced in doing so.
combinatorial sketching for finite programs. sketching is a software synthesis approach where the programmer develops a partial implementation - a sketch - and a separate specification of the desired functionality. the synthesizer then completes the sketch to behave like the specification. the correctness of the synthesized implementation is guaranteed by the compiler, which allows, among other benefits, rapid development of highly tuned implementations without the fear of introducing bugs.we develop sketch, a language for finite programs with linguistic support for sketching. finite programs include many highperformance kernels, including cryptocodes. in contrast to prior synthesizers, which had to be equipped with domain-specific rules, sketch completes sketches by means of a combinatorial search based on generalized boolean satisfiability. consequently, our combinatorial synthesizer is complete for the class of finite programs: it is guaranteed to complete any sketch in theory, and in practice has scaled to realistic programming problems.freed from domain rules, we can now write sketches as simpleto-understand partial programs, which are regular programs in which difficult code fragments are replaced with holes to be filled by the synthesizer. holes may stand for index expressions, lookup tables, or bitmasks, but the programmer can easily define new kinds of holes using a single versatile synthesis operator.we have used sketch to synthesize an efficient implementation of the aes cipher standard. the synthesizer produces the most complex part of the implementation and runs in about an hour.
isolator: dynamically ensuring isolation in comcurrent programs. in this paper, we focus on concurrent programs that use locks to achieve isolation of data accessed by critical sections of code. we present isolator, an algorithm that guarantees isolation for well-behaved threads of a program that obey a locking discipline even in the presence of ill-behaved threads that disobey the locking discipline. isolator uses code instrumentation, data replication, and virtual memory protection to detect isolation violations and delays ill-behaved threads to ensure isolation. our instrumentation scheme requires access only to the code of well-behaved threads. we have evaluated isolator on several benchmark programs and found that isolator can ensure isolation with reasonable runtime overheads. in addition, we present three general desiderata - safety, isolation, and permissiveness - for any scheme that attempts to ensure isolation, and formally prove that isolator satisfies all of these desiderata.
accelerator: using data parallelism to program gpus for general-purpose uses. gpus are difficult to program for general-purpose uses. programmers can either learn graphics apis and convert their applications to use graphics pipeline operations or they can use stream programming abstractions of gpus. we describe accelerator, a system that uses data parallelism to program gpus for general-purpose uses instead. programmers use a conventional imperative programming language and a library that provides only high-level data-parallel operations. no aspects of gpus are exposed to programmers. the library implementation compiles the data-parallel operations on the fly to optimized gpu pixel shader code and api calls.we describe the compilation techniques used to do this. we evaluate the effectiveness of using data parallelism to program gpus by providing results for a set of compute-intensive benchmarks. we compare the performance of accelerator versions of the benchmarks against hand-written pixel shaders. the speeds of the accelerator versions are typically within 50% of the speeds of hand-written pixel shader code. some benchmarks significantly outperform c versions on a cpu: they are up to 18 times faster than c code running on a cpu.
adaptive set pinning: managing shared caches in chip multiprocessors. as part of the trend towards chip multiprocessors (cmps) for the next leap in computing performance, many architectures have explored sharing the last level of cache among different processors for better performance-cost ratio and improved resource allocation. shared cache management is a crucial cmp design aspect for the performance of the system. this paper first presents a new classification of cache misses - cii: compulsory, inter-processor and intra-processor misses - for cmps with shared caches to provide a better understanding of the interactions between memory transactions of different processors at the level of shared cache in a cmp. we then propose a novel approach, called set pinning, for eliminating inter-processor misses and reducing intra-processor misses in a shared cache. furthermore, we show that an adaptive set pinning scheme improves over the benefits obtained by the set pinning scheme by significantly reducing the number of off-chip accesses. extensive analysis of these approaches with specomp 2001 benchmarks is performed using a full system simulator. our experiments indicate that the set pinning scheme achieves an average improvement of 22.18% in the l2 miss rate while the adaptive set pinning scheme reduces the miss rates by an average of 47.94% as compared to the traditional shared cache scheme. they also improve the performance by 7.24% and 17.88% respectively.
overshadow: a virtualization-based approach to retrofitting protection in commodity operating systems. commodity operating systems entrusted with securing sensitive data are remarkably large and complex, and consequently, frequently prone to compromise. to address this limitation, we introduce a virtual-machine-based system called overshadow that protects the privacy and integrity of application data, even in the event of a total oscompromise. overshadow presents an application with a normal view of its resources, but the os with an encrypted view. this allows the operating system to carry out the complex task of managing an application's resources, without allowing it to read or modify them. thus, overshadow offers a last line of defense for application data. overshadow builds on multi-shadowing, a novel mechanism that presents different views of "physical" memory, depending on the context performing the access. this primitive offers an additional dimension of protection beyond the hierarchical protection domains implemented by traditional operating systems and processor architectures. we present the design and implementation of overshadow and show how its new protection semantics can be integrated with existing systems. our design has been fully implemented and used to protect a wide range of unmodified legacy applications running on an unmodified linux operating system. we evaluate the performance of our implementation, demonstrating that this approach is practical.
efficiency trends and limits from comprehensive microarchitectural adaptivity. increasing demand for power-efficient, high-performance computing requires tuning applications and/or the underlying hardware to improve the mapping between workload heterogeneity and computational resources. to assess the potential benefits of hardware tuning, we propose a framework that leverages synergistic interactions between recent advances in (a) sampling, (b) predictive modeling, and (c) optimization heuristics. this framework enables qualitatively new capabilities in analyzing the performance and power characteristics of adaptive microarchitectures. for the first time, we are able to simultaneously consider high temporal and comprehensive spatial adaptivity. in particular, we optimize efficiency for many, short adaptive intervals and identify the best configuration of 15 parameters, which define a space of 240b point. with frequent sub-application reconfiguration and a fully reconfigurable hardware substrate, adaptive microarchitectures achieve bips3/w efficiency gains of up to 5.3x (median 2.4x) relative to their static counterparts already optimized for a given application. this 5.3x efficiency gain is derived from a 1.6x performance gain and 0.8x power reduction. although several applications achieve a significant fraction of their potential efficiency with as few as three adaptive parameters, the three most significant parameters differ across applications. these differences motivate a hardware substrate capable of comprehensive adaptivity to meet these diverse application requirements.
architectural support for swar text processing with parallel bit streams: the inductive doubling principle. parallel bit stream algorithms exploit the swar (simd within a register) capabilities of commodity processors in high-performance text processing applications such as utf-8 to utf-16 transcoding, xml parsing, string search and regular expression matching. direct architectural support for these algorithms in future swar instruction sets could further increase performance as well as simplifying the programming task. a set of simple swar instruction set extensions are proposed for this purpose based on the principle of systematic support for inductive doubling as an algorithmic technique. these extensions are shown to significantly reduce instruction count in core parallel bit stream algorithms, often providing a 3x or better improvement. the extensions are also shown to be useful for swar programming in other application areas, including providing a systematic treatment for horizontal operations. an implementation model for these extensions involves relatively simple circuitry added to the operand fetch components in a pipelined processor.
capo: a software-hardware interface for practical deterministic multiprocessor replay. while deterministic replay of parallel programs is a powerful technique, current proposals have shortcomings. specifically, software-based replay systems have high overheads on multiprocessors, while hardware-based proposals focus only on basic hardware-level mechanisms, ignoring the overall replay system. to be practical, hardware-based replay systems need to support an environment with multiple parallel jobs running concurrently -- some being recorded, others being replayed and even others running without recording or replay. moreover, they need to manage limited-size log buffers. this paper addresses these shortcomings by introducing, for the first time, a set of abstractions and a software-hardware interface for practical hardware-assisted replay of multiprocessor systems. the approach, called capo, introduces the novel abstraction of the replay sphere to separate the responsibilities of the hardware and software components of the replay system. in this paper, we also design and build capoone, a prototype of a deterministic multiprocessor replay system that implements capo using linux and simulated delorean hardware. our evaluation of 4-processor executions shows that capoone largely records with the efficiency of hardware-based schemes and the flexibility of software-based schemes.
picsel: measuring user-perceived performance to control dynamic frequency scaling. the ultimate goal of a computer system is to satisfy its users. the success of architectural or system-level optimizations depends largely on having accurate metrics for user satisfaction. we propose to derive such metrics from information that is "close to flesh" and apparent to the user rather than from information that is "close to metal" and hidden from the user. we describe and evaluate picsel, a dynamic voltage and frequency scaling (dvfs) technique that uses measurements of variations in the rate of change of a computer's video output to estimate user-perceived performance. our adaptive algorithms, one conservative and one aggressive, use these estimates to dramatically reduce operating frequencies and voltages for graphically-intensive applications while maintaining performance at a satisfactory level for the user. we evaluate picsel through user studies conducted on a pentium m laptop running windows xp. experiments performed with 20 users executing three applications indicate that the measured laptop power can be reduced by up to 12.1%, averaged across all of our users and applications, compared to the default windows xp dvfs policy. user studies revealed that the difference in overall user satisfaction between the more aggressive version of picsel and windows dvfs were statistically insignificant, whereas the conservative version of picsel actually improved user satisfaction when compared to windows dvfs.
how low can you go?: recommendations for hardware-supported minimal tcb code execution. we explore the extent to which newly available cpu-based security technology can reduce the trusted computing base (tcb) for security-sensitive applications. we find that although this new technology represents a step in the right direction, significant performance issues remain. we offer several suggestions that leverage existing processor technology, retain security, and improve performance. implementing these recommendations will finally allow application developers to focus exclusively on the security of their own code, enabling it to execute in isolation from the numerous vulnerabilities in the underlying layers of legacy code.
parallelizing security checks on commodity hardware. speck (speculative parallel check) is a system thataccelerates powerful security checks on commodity hardware by executing them in parallel on multiple cores. speck provides an infrastructure that allows sequential invocations of a particular security check to run in parallel without sacrificing the safety of the system. speck creates parallelism in two ways. first, speck decouples a security check from an application by continuing the application, using speculative execution, while the security check executes in parallel on another core. second, speck creates parallelism between sequential invocations of a security check by running later checks in parallel with earlier ones. speck provides a process-level replay system to deterministically and efficiently synchronize state between a security check and the original process.we use speck to parallelize three security checks: sensitive data analysis, on-access virus scanning, and taint propagation. running on a 4-core and an 8-core computer, speck improves performance 4x and 7.5x for the sensitive data analysis check, 3.3x and 2.8x for theon-access virus scanning check, and 1.6x and 2x for the taint propagation check.
the design and implementation of microdrivers. device drivers commonly execute in the kernel to achieve high performance and easy access to kernel services. however, this comes at the price of decreased reliability and increased programming difficulty. driver programmers are unable to use user-mode development tools and must instead use cumbersome kernel tools. faults in kernel drivers can cause the entire operating system to crash. user-mode drivers have long been seen as a solution to this problem, but suffer from either poor performance or new interfaces that require a rewrite of existing drivers. this paper introduces the microdrivers architecture that achieves high performance and compatibility by leaving critical path code in the kernel and moving the rest of the driver code to a user-mode process. this allows data-handling operations critical to i/o performance to run at full speed, while management operations such as initialization and configuration run at reduced speed in user-level. to achieve compatibility, we present driverslicer, a tool that splits existing kernel drivers into a kernel-level component and a user-level component using a small number of programmer annotations. experiments show that as much as 65% of driver code can be removed from the kernel without affecting common-case performance, and that only 1-6 percent of the code requires annotations.
feedback-driven threading: power-efficient and high-performance execution of multi-threaded workloads on cmps. extracting high-performance from the emerging chip multiprocessors (cmps) requires that the application be divided into multiple threads. each thread executes on a separate core thereby increasing concurrency and improving performance. as the number of cores on a cmp continues to increase, the performance of some multi-threaded applications will benefit from the increased number of threads, whereas, the performance of other multi-threaded applications will become limited by data-synchronization and off-chip bandwidth. for applications that get limited by data-synchronization, increasing the number of threads significantly degrades performance and increases on-chip power. similarly, for applications that get limited by off-chip bandwidth, increasing the number of threads increases on-chip power without providing any performance improvement. furthermore, whether an application gets limited by data-synchronization, or bandwidth, or neither depends not only on the application but also on the input set and the machine configuration. therefore, controlling the number of threads based on the run-time behavior of the application can significantly improve performance and reduce power. this paper proposes feedback-driven threading (fdt), a framework to dynamically control the number of threads using run-time information. fdt can be used to implement synchronization-aware threading (sat), which predicts the optimal number of threads depending on the amount of data-synchronization. our evaluation shows that sat can reduce both execution time and power by up to 66% and 78% respectively. similarly, fdt can be used to implement bandwidth-aware threading (bat), which predicts the minimum number of threads required to saturate the off-chip bus. our evaluation shows that bat reduces on-chip power by up to 78%. when sat and bat are combined, the average execution time reduces by 17% and power reduces by 59%. the proposed techniques leverage existing performance counters and require minimal support from the threading library.
exploiting access semantics and program behavior to reduce snoop power in chip multiprocessors. integrating more processor cores on-die has become the unanimous trend in the microprocessor industry. most of the current research thrusts using chip multiprocessors (cmps) as the baseline to analyze problems in various domains. one of the main design issues facing cmp systems is the growing number of snoops required to maintain cache coherency and to support self/cross-modifying code that leads to power and performance limitations. in this paper, we analyze the internal and external snoop behavior in a cmp system and relax the snoopy cache coherence protocol based on the program semantics and properties of the shared variables for saving power. based on the observations and analyses, we propose two novel techniques: selective snoop probe (ssp) and essential snoop probe (esp) to reduce power without compromising performance. our simulation results show that using the ssptechnique, 5% to 65% data cache energy savings per core for different processor configurations can be achieved with 1% to 2% performance improvement. we also show that 5% to 82% of data cache energy per core is spent on the non-essential snoop probes that can be saved using the esp technique.
picoserver: using 3d stacking technology to enable a compact energy efficient chip multiprocessor. in this paper, we show how 3d stacking technology can be used to implement a simple, low-power, high-performance chip multiprocessor suitable for throughput processing. our proposed architecture, picoserver, employs 3d technology to bond one die containing several simple slow processing cores to multiple dram dies sufficient for a primary memory. the 3d technology also enables wide low-latency buses between processors and memory. these remove the need for an l2 cache allowing its area to be re-allocated to additional simple cores. the additional cores allow the clock frequency to be lowered without impairing throughput. lower clock frequency in turn reduces power and means that thermal constraints, a concern with 3d stacking, are easily satisfied.the picoserver architecture specifically targets tier 1 server applications, which exhibit a high degree of thread level parallelism. an architecture targeted to efficient throughput is ideal for this application domain. we find for a similar logic die area, a 12 cpu system with 3d stacking and no l2 cache outperforms an 8 cpu system with a large on-chip l2 cache by about 14% while consuming 55% less power. in addition, we show that a picoserver performs comparably to a pentium 4-like class machine while consuming only about 1/10 of the power, even when conservative assumptions are made about the power consumption of the picoserver.
accurate branch prediction for short threads. multi-core processors, with low communication costs and high availability of execution cores, will increase the use of execution and compilation models that use short threads to expose parallelism. current branch predictors seek to incorporate large amounts of control flow history to maximize accuracy. however, when that history is absent the predictor fails to work as intended. thus, modern predictors are almost useless for threads below a certain length. using a speculative multithreaded (spmt) architecture as an example of a system which generates shorter threads, this work examines techniques to improve branch prediction accuracy when a new thread begins to execute on a different core. this paper proposes a minor change to the branch predictor that gives virtually the same performance on short threads as an idealized predictor that incorporates unknowable pre-history of a spawned speculative thread. at the same time, strong performance on long threads is preserved. the proposed technique sets the global history register of the spawned thread to the initial value of the program counter. this novel and simple design reduces branch mispredicts by 29% and provides as much as a 13% ipc improvement on selected spec2000 benchmarks.
tapping into the fountain of cpus: on operating system support for programmable devices. the constant race for faster and more powerful cpus is drawing to a close. no longer is it feasible to significantly increase the speed of the cpu without paying a crushing penalty in power consumption and production costs. instead of increasing single thread performance, the industry is turning to multiple cpu threads or cores (such as smt and cmp) and heterogeneous cpu architectures (such as the cell broadband engine). while this is a step in the right direction, in every modern pc there is a wealth of untapped compute resources. the nic has a cpu; the disk controller is programmable; some high-end graphics adaptersare already more powerful than host cpus. some of these cpus can perform some functions more efficiently than the host cpus. our operating systems and programming abstractions should be expanded to let applications tap into these computational resources and make the best use of them. therefore, we propose the hydra framework, which lets application developers use the combined power of every compute resource in a coherent way. hydra is a programming model and a runtime support layer which enables utilization of host processors as well as various programmable peripheral devices' processors. we present the frameworkand its application for a demonstrative use-case, as well as provide a thorough evaluation of its capabilities. using hydra we were able to cut down the development cost of a system that uses multiple heterogenous compute resources significantly.
toward molecular programming with dna. biological organisms are beautiful examples of programming. the program and data are stored in biological molecules such as dna, rna, and proteins; the algorithms are carried out by molecular and biochemical processes; and the end result is the creation and function of an organism. if we understood how to program molecular systems, what could we create? lifelike technologies whose basic operations are chemical reactions? the fields of chemistry, physics, biology, and computer science are converging as we begin to synthesize molecules, molecular machines, and molecular systems of ever increasing complexity, leading to subdisciplines such as dna nanotechnology, dna computing, and synthetic biology. having demonstrated simple devices and systems -- self-assembled structures, molecular motors, chemical logic gates -- researchers are now turning to the question of how to create large-scale integrated systems. to do so, we must learn how to manage complexity: how to efficiently specify the structure and behavior of intricate molecular systems, how to compile such specifications down to the design of molecules to be synthesized in the lab, and how to ensure that such systems function robustly. these issues will be illustrated for chemical logic circuits based on cascades of dna hybridization reactions. bio erik winfree is an associate professor in computer science, computation & neural systems, and bioengineering at caltech. winfree is the recipient of the feynman prize for nanotechnology (2006), the nsf pecase/career award (2001), the onr young investigators award (2001), a macarthur fellowship (2000), and mit technology review's first tr100 list of "top young innovators" (1999). prior to joining the faculty at caltech in 2000, winfree was a lewis thomas postdoctoral fellow in molecular biology at princeton, and a visiting scientist at the mit ai lab. winfree received a b.s. in mathematics w/ computer science from the university of chicago in 1991, and a ph.d. in computation & neural systems from caltech in 1998. his website is http://dna.caltech.edu/~winfree/.
combining head tracking and mouse input for a gui on multiple monitors. the use of multiple lcd monitors is becoming popular as prices are reduced, but this creates problems for window management and switching between applications. for a single monitor, eye tracking can be combined with the mouse to reduce the amount of mouse movement, but with several monitors the head is moved through a large range of positions and angles which makes eye tracking difficult. we thus use head tracking to switch the mouse pointer between monitors and use the mouse to move within each monitor. in our experiment users required significantly less mouse movement with the tracking system, and preferred using it, although task time actually increased. a graphical prompt (flashing star) prevented the user losing the pointer when switching monitors. we present discussions on our results and ideas for further developments.
an approach to evaluation of software visualization. this paper briefly describes the work presented by the authors in the 1997 chi development consortium. this work focuses on several aspects of software visualization (sv), including the evaluation of sv systems and the application of sv in the domain of parallel computation.
the affective connection: how and when users communicate emotion. affective computer systems which recognize human emotions or use emotion in their displays have potential to enhance human-computer interaction (hci). wizard-of-oz (woz) methods and experimental design have enabled recording, analysis and comparison of emotional interaction of participants with an apparently 'emotional' machine and a standard 'non-emotional' version. early results suggest participants use subtle emotional displays during hci, for example through posture, body movement, sounds and facial expression. further analysis will confirm if they show more emotion when they believe the system recognises their emotions, or when the system varies its behaviour in response to their emotional expression. this will contribute to hci knowledge of affective computing by emphasizing the user's perspective, demonstrating the usefulness of woz techniques, and raising questions about future directions of affective computing.
e-motional advantage: performance and satisfaction gains with affective computing. emotions are now recognized as complex human control systems, crucial to decision making, creativity, playing and learning. affective technologies may offer improved interaction and commercial promise. in the past, research has focused on technical development work, leaving many questions about user preferences unanswered. for this user-centered study, 60 participants played a simple 'word ladder' game under different controlled conditions. using 2 x 2 factorial design, and a wizard of oz scenario, half the participants interacted with a system that adapted on the basis of the user's emotional expression and half were told the system could react to their emotional expressions. we established that when using an apparently affective system, users perform significantly better and report themselves as feeling significantly happier. we also discuss behavioral responses to the different conditions. these results are relevant to the design of future affective systems.
shownpass: an easy access control with a displayed password. access control is one of the most important issue with ubiquitous networking environment. traditional access control methods are mainly considering authentication of registered user or device. therefore, it is troublesome to allow a visitor to use a networked resource in an office, without accessiblity to other resources. we propose a new access control method using frequently changing passwords displayed beside a resource. this method can be implemented without any special hardware like a sensor.
fitster: social fitness information visualizer. we present fitster, a social visualization interface that supports fitness motivation among busy people struggling to exercise. among our pilot group of busy graduate students, we found that a popular time-saving strategy is to recast exercise in terms of everyday, informal activities. fitster employs pedometer data to support activity tracking, goal setting, and motivation through virtual competitions and teamwork. it contributes to the human-computer interaction (hci) and health domains by identifying a new facet of exercise behavior and by offering a lightweight social interface to promote fitness motivation and enjoyment.
auraorb: social notification appliance. one of the problems with notification appliances is that they can be distracting when providing information not of immediate interest to the user. in this paper, we present auraorb, an ambient notification appliance that deploys progressive turn taking techniques to minimize notification disruptions. auraorb uses eye contact sensing to detect user interest in an initially ambient light notification. once detected, it displays a text message with a notification heading visible from 360 degrees. touching the orb causes the associated message to be displayed on the user's computer screen.we performed an initial evaluation of auraorb's functionality using a set of heuristics tailored to ambient displays. results of our evaluation suggest that progressive turn taking techniques allowed auraorb users to access notification headings with minimal impact on their focus task.
introducing human-centered research to game design: designing game concepts for and with senior citizens. this paper introduces a human-centered methodology for innovating gameplay, based on ethnographic principles and participatory design. this methodology was applied in a project for designing game concepts for and with senior citizens. the research started off by observing and probing senior citizens in their 'natural habitat', researching what positive experiences occur in their daily life. these observed passions then became the input for brainstorm sessions. seniors and researchers generated game-ideas and, consequently, co-designed the selected ideas into game concepts.the results of this methodology are inspiring game concepts, directly grafted on the passions and desires of the senior. but more important than the actual game concepts, we conceived a model of passions in elderly life. this model provides game designers with an understanding of the ingredients that are fundamental to 'meaningful play' in elderly life.
using music as a communication medium. music is a rich communication medium, and there are some similarities between the job of a music composer and that of an hci designer (although their objectives may be different). whilst sound has been used in interfaces, its use has mainly been at a primitive level, often involving real-world sound. since music offers a highly structured set of mechanisms for communicating, it is surprising that there have been so few attempts at exploring its possibilities. our current activity involves investigations into the use of music in algorithmic audiolisation and program debugging.
cellular phone manuals: users' benefit from spatial maps. manuals of technical devices are often not very helpful to the user. this study investigates the influence of spatial instructions versus conventional linear step-by-step manuals on inexperienced users' performance handling cellular phones. results show a significant interaction between user age and manual. middle aged users profit more from the spatial information given in the manual that contains the phone's menu tree than from the step-by-step instruction, whereas subjects older than 50 show no improvement. it is concluded that manufacturers should consider the inclusion of spatial information on the cellular phones' menu structure in their manuals, as the majority of users would benefit.
a new approach of a context-adaptive search agent for automotive environments. the progress in electronic devices and therefore the growing amount of information in cars implicates the development of new strategies to cope with this amount of information for drivers. an intelligent search agent can help with navigation in deep hierarchies and in huge databases, and consequently has a high potential to increase the concentration on the primary driving task. the evaluation shows that a search agent concept reached a high user acceptance and the objective data proved observably acceleration in handling compared to deep hierarchical menu navigation.
ivo: interactive voting for the olympics. this paper describes the creation of an interactive audience voting system, ivo. the device is intended for diving and gymnastics events during the 2004 summer olympics in athens, greece. ivo is adaptable and can be incorporated into a wider range of sports and events. industrial design and interaction design methodologies were combined allowing us to create an iterative process which guided us through the project. this unique mixture of techniques allowed us to explore both the interface and usability, as well as form and ergonomics of this device. through the application of this methodology, we created an interactive voting system that is innovative and realistic for implementation during the 2004 olympics.
a tool-based interactive drawing environment. graphical user interfaces rely heavily on the tool metaphor. in most drawing systems, for example, functions are organized as they might be on a workbench; buttons associated with drawing modes for lines or rectangles are called line-drawing or rectangle-drawing tools; etc. despite the similarities, however, there remain many differences between software tools and physical tools. this paper gives a concise account of tool use in general, and describes a drawing application, called habilisdraw, that relies on a detailed correspondence to physical tool behavior.
ubiquitous computing: the impact on future interaction paradigms and hci research. as we look to the future of computing, and particularly to the future of hci research, the vision of ubiquitous computing emerges as a principal theme. the focus of this workshop is applications-centered research in ubiquitous computing. we define ubiquitous computing as the attempt to break the pattern of traditional relationships between users and computational services by extending the computational interface into the user's environment. over the past few years researchers in wireless networking and distributed systems have worked to build infrastructures supporting mobile and ubiquitous computing. infrastructure research is, of course, necessary for the advancement of ubiquitous computing, but we must also examine higher-level issues such as the kinds of tasks and interaction patterns that emerge as the user is allowed to break away from the desktop.
mobile advice: an accessible device for visually impaired capability enhancement. the visually impaired have limited access to the world of mobile devices. our goal was to design a handheld mobile device to overcome limitations such as reliance on visual display and lack of audio and tactile feedback. we built a prototype handheld device using a combination of tactile feedback and auditory display based on preliminary research and testing. our hypothesis was that this device would provide users with an interface with which they would be able to access advanced functions of a mobile device. this prototype was evaluated by both blind and sighted users. based on both quantitative and qualitative measures, the results suggest that such a device can enhance the capabilities of visually impaired users of handheld mobile devices.
how people use www bookmarks. in this detailed empirical study of www browsing and bookmarks we define a personal information space as having five basic properties paralleling those of a larger complex information space. we describe user behavior on the web and show how a user's bookmark archive is a personal web information space.
criteria for effective groupware 2. the audience of a panel at chi'96 in vancouver submitted 61 forms suggesting criteria for the design of effective groupware. the suggestions made were analysed for common themes that are summarised here. the poster also presents an opportunity for participants at chi'97 to contribute to this discussion.
the sound of one hand: a wrist-mounted bio-acoustic fingertip gesture interface. two hundred and fifty years ago the japanese zen master hakuin asked the question, "what is the sound of the single hand?" this koan has long served as an aid to meditation but it also describes our new interaction techinique. we discovered that gentle fingertip gestures such as tapping, rubbing, and flicking make quiet sounds that travel by bone conduction throughout the hand. a small wristband-mounted contact microphone can reliably and inexpensively sense these sounds. we harnessed this "sound in the hand" phenomenon to build a wristband-mounted bio-acoustic fingertip gesture interface. the bio-acoustic interface recognizes some common gestures that state-of-the-art glove and image-processing techniques capture but in a smaller, mobile package.
photoarcs: a tool for creating and sharing photo-narratives. the photoarcs interface aims to enable easy and fun creation and manipulation of photo-narratives to encourage sharing and interaction. photoarcs leverages the benefits of existing sharing habits both online and face-to-face. we describe our design of the photoarcs interface, report on the results of an exploratory low-fidelity usability study with five participants, and outline future directions.
3d and sequential representations of spatial relationships among photos. this paper proposes automatic representations of spatial relationships among photos for structure analysis and review of a photographic subject. based on camera tracking, photos are shown in a 3d virtual reality space to represent global spatial relationships. at the same time, the spatial relationships between two of the photos are represented in slide show sequences. this proposal allows people to organize photos quickly in spatial representations with qualitative meaning.
'ensemble': playing with sensors and sound. this paper presents a set of sensor driven sonic prototypes and the workshops in which they are played with by children in games of dressing up. seven garments are fitted with wireless sensors that control sound samples and their modifiers in real time. the aim of the project is to capture the children's emerging understanding of the sensors as they explore and play and in the longer term inform the use of analog sensing in touchable interfaces. the system is described and observations from the first workshops are reported. the paper concludes with a short discussion and conclusions regarding both the system itself and the methods used.
in the mixxx: novel digital dj interfaces. we present an interactive system, mixxx, for live dj'ing using digital sound files. the design of the system is approached from two directions: through contextual design using contextual interviews and video recordings and open source development where feedback and ideas are generated by developers and users from the open source community. our contextual interviews show that djs use a significant amount of their time on tracking and synchronizing songs using the traditional setup with turntables or cd players. by making beat information an integrated part of our dj software mixxx, synchronization is done automatically and djs can use more time to attend other parts of the mix. we provide an intuitive interface for mixing with beat information that allows the same level of flexibility as with the traditional setup but facilitates new creative ways of mixing.
a simple movement time model for scrolling. a model for movement time for scrolling is developed and verified experimentally. it is hypothesized that the maximum scroll speed is a constant at which the target can be perceived when scrolling over the screen. in an experiment where distance to target and target width were varied, it was found that movement time did not follow fitts' law. rather, it was linearly dependent on the distance to the target, suggesting a constant maximum scrolling speed. we hypothesize that the same relationship between movement time and target distance apply to other computer interaction tasks where the position of the target is not known ahead of time, and the data in which the target is sought is not ordered.
meeting the needs of the "user experience" professional. in the business of "user experience" (ux), collaboration across multiple disciplines is considered to be critical to achieving success. but the increasing number of professional associations and events of relevance to ux practitioners rely much less on collaboration with others in their pursuit of success. this panel reports on obstacles to and opportunities for increasing collaboration among professional organizations, and the effects increased collaboration can have on the service and support provided to the rapidly growing, multidisciplinary ux profession.
interaction patterns with a classroom feedback system: making time for feedback. in this paper, we describe two novel patterns of interaction that arose in a study of a computer-mediated feedback system for the university classroom. in both patterns, students gave feedback through the system that they would not have given aloud for lack of an appropriate moment-either because the feedback would be premature or tardy. we describe the patterns themselves and how awareness of the patterns can inform pedagogy and system-building.
putting personas to work. personas for use in interaction and interface design have generated a great deal of interest, but the method is still relatively new. this panel brings together professionals who have used personas to solve real business problems. the panelists will describe the methods they have developed to put personas to work in their organizations and how the use of personas has impacted their products and their organizations.
designing tangible interfaces for children's collaboration. this paper presents the development of a design concept for an interactive play system and learning tool for children. the concept was illustrated with ely the explorer, an accessible and robust multi-user unit, set of tangible tools, and software application, designed for the school environment. this work examines the design of interfaces for co-present collaboration from an interaction design perspective. this paper also presents results from the concept evaluation in a school environment. the results showed that the system supported collaboration and interactivity and that the children enjoyed, and were engaged in the play. this indicates to us that the concept can make a positive contribution to the existing array of learning tools.
knowledge-based support for visual exploration of spatial data. the knowledge-based system iris is designed to help users in analysis of spatially referenced statistical data. for this purpose the system provides the user with automatically built thematic maps presenting the data visually. the process of map design is governed by the domain-independent visualisation knowledge base. the user receives the opportunity to concentrate on data exploration instead of the process of planning and building data presentations. implementation of the interface part of the system in java language allows to run the system in the world wide web (www).
research issues in intelligent data visualisation for exploration and communication. efficiency and quality of solving problems by people are greatly affected by the way in that relevant information is arranged and presented. there is a need for intelligent software assisting humans by automatic generation of adequate presentations. we focus on graphical and especially cartographic data presentations and distinguish two problem classes where these presentations have high potential: data exploration and communication. it is argued that graphics design principles should be different for these two classes. data communication is treated in a wider sense than merely report making: it is proposed to consider a "visual message" being built with respect to author's pragmatic goals, beliefs, attitudes, etc., as well as the image of the addressee. we outline the necessary research directions and reason about the role that could be played in such a research by the prototype knowledge-based system iris we have developed earlier.
mpath: facilitating human interaction. as the "baby-boomer" generation approaches retirement, the united states will enjoy a significant increase in the number of senior citizens. issues involving seniors are likely to rise to the forefront of national consciousness. a primary concern for this population is the loss of companionship, which can contribute to isolation, depression, and decreased socialization [9]. a concept for a data management service - mpath - is proposed to combat isolation among seniors. mpath works with administrators of assisted-living facilities to oversee an ad-hoc volunteer network. interacting with residents, these volunteers assess social relationships and emotional reactions, quantifying for the computer their qualitative observations. the system examines accumulated data over time to reveal anomalies, highlight trends and anticipate future responses. administrators may choose to act upon that information. the overall effect is to increase the social well being of seniors in an unobtrusive manner.
misuse and abuse of interactive technologies. the goal of this workshop is to address the darker side of hci by examining how computers sometimes bring about the expression of negative emotions. in particular, we are interested in the phenomenon of human beings abusing computers. such behavior can take many forms, ranging from the verbal abuse of conversational agents to physical attacks on the hardware. in some cases, particularly in the case of embodied conversational agents, there are questions about how the machine should respond to verbal assaults. this workshop is also interested in understanding the psychological underpinnings of negative behavior involving computers. in this regard, we are interested in exploring how hci factors influence human-to-human abuse in computer-mediated communication. the overarching objective of this workshop is to sketch a research agenda on the topic of the misuse and abuse of interactive technologies that will lead to design solutions capable of protecting users and restraining disinhibited behaviors.
ethnographic interviews guide design of ford vehicles website. this case study describes ethnographic interviews with vehicle buyers to learn how they make purchase decisions. the research was conducted for j. walter thompson (jwt), the digital design agency of the ford division of the ford motor company; the authors faced challenges of tight schedule, limited budget, and difficulties in finding suitable participants. we nevertheless obtained valuable data that helped jwt refine the ford vehicles website.
evaluation of multimodal input for entering mathematical equations on the computer. current standard interfaces for entering mathematical equations on computers are arguably limited and cumbersome. mathematics notations have evolved to aid visual thinking and yet text-based interfaces relying on keyboard-and-mouse input do not take advantage of the natural two-dimensional aspects of math. due to its similarities to paper-based mathematics, pen-based handwriting input may be faster, more efficient, and more preferable for entering mathematics on computers. this paper presents an empirical study that tests this hypothesis. we also explored a multimodal input method combining handwriting and speech because we hypothesize that it may enhance computer recognition and aid user cognition. novice users were indeed faster, more efficient and enjoyed the handwriting modality more than a standard keyboard-and-mouse mathematics interface, especially as equation length and complexity increased. the multimodal handwriting-plus-speech method was faster and better liked than the keyboard-and-mouse method and was not much worse than handwriting alone.
child-user abstractions. interactive technologies are becoming ubiquitous in many children's lives. this work-in-progress paper briefly describes and illustrates a new approach for creating user abstractions of children. the technique is based on a theoretically and empirically grounded framework for creating child-personas. it is expected to reduce designer's assumptions about children. a preliminary assessment of this claim based on engagement, complexity and realism concludes this work in progress.
discovering design drivers for mobile media solutions. we conducted user studies in 2000 and 2004 into digital media use, and discovered a number of constant findings even though the studies were separate both in geographically and chronologically. these constant findings, which we call design drivers, represent high level user benefits and constraints which are not likely to change quickly. we feel that knowledge of these constant drivers is beneficial in designing key features of mobile media devices. on the other hand, findings specific to a particular environment, variable design drivers, help to identify potential enablers and obstacles of product adoption.
the effect of miscommunication rate on user response preferences. we report results from a small wizard-of-oz study investigating user responses to miscommunications in speech dialogue systems. we explore the separate and joint effects of miscommunication rate and system response to miscommunications on the likelihood that users choose to resort to direct manipulation, to repeat, or to rephrase. while we predicted that users would be more likely to resort to direct manipulation as miscommunication rate increased, our surprising finding was that users were most likely to resort to direct manipulation where communication success was least predictable, i.e., in the middle of the range, rather than at either extreme.
be a judge!: wearable wireless motion sensors for audience participation. in recent years the olympic games have undergone vast criticism due to perceived subjective scoring in judged events, as for example figure skating and gymnastics. judges' scores may be influenced by favoritism, human error, or possibly corruption. audience participation in scoring represents a promising approach to meet these problems. in this paper we present an audience voting system that utilizes the natural behavior of sports spectators: clapping and cheering. the system consists of wireless motion sensors and microphones that enable spectators to cast their vote in real time. the sensors are worn by audience members and determine the clapping frequency of each participant. this facilitates continuous influence on the score throughout an athlete's performance. the audience score is presented on wall-sized stadium displays and might be contrasted with the judges' scores to encourage audience engagement.
wizard of oz for participatory design: inventing a gestural interface for 3d selection of neural pathway estimates. this paper describes a participatory design process employed to invent an interface for 3d selection of neural pathways estimated from mri imaging of human brains. existing pathway selection interfaces are frustratingly difficult to use, since they require the 3d placement of regions-of-interest within the brain data using only a mouse and keyboard. the proposed system addresses these usability problems by providing an interface that is potentially more intuitive and powerful: converting 2d mouse gestures into 3d path selections. the contributions of this work are twofold: 1) we introduce a participatory design process in which users invent and test their own gestural selection interfaces using a wizard of oz prototype, and 2) this process has helped to yield the design of an interface for 3d pathway selection, a problem that is known to be difficult. aspects of both the design process and the interface may generalize to other interface design problems.
eyevox: a collaborative scoring process. this paper describes an audience response process and its supporting systems for use in judged sporting events at the 2004 athens olympic games. it consists of a wireless score-input system and an inclusive, transparent scoring procedure that leverages group knowledge to optimize collective voting. by educating spectators prior to and during the audience voting process, the \b^eyevox\n^ system not only provides sophisticated spectator feedback, it leads spectators to more informed understanding, and thus better appreciation of the sport and the olympics.
biasing response in fitts' law tasks. fitts' law, relating the time to acquire a target to the target size and the distance from the target, is an effective and widely used predictor of performance in feedback controlled human motor targeting tasks. beyond target size, however, movement time also varies according to a subject controlled mental trade-off between speed and accuracy for a given task. to adjust for this trade-off, researchers often use the "effective target width", the target width normalized for variations in movement speed, as a predictor of movement time. in this paper, we describe on-going work on analyzing factors affecting the speed-accuracy tradeoff for fitts' tasks in subjects, exploring both incentives and penalties to manipulate subject accuracy. we also describe our work on measurable parameters of motion that correlate with the speed-accuracy trade-off.
using task models to generate multi-platform user interfaces while ensuring usability. the widespread emergence of new computing devices and associated interaction metaphors has necessitated new ways of building user interfaces (uis) for these devices. in this paper, we describe our approach of using a task model in conjunction with the user interface markup language (uiml) to drive generation of multi-platform user interfaces. we also discuss briefly how current usability engineering practices have to be modified to accommodate the development of multi-platform uis.
the stakeholder forest: designing an expenses application for the enterprise. this paper discusses the redesign of peoplesoft's enterprise expenses product from a product that was notorious for it's complexity into a product that was both usable and one of peoplesoft's best selling products. the process used was a combination of best practices from user-centered design, business and marketing to deliver a usable application on a pure-html "no-code on the client" platform. the design effort was also a collaboration of design, usability engineers, business strategy, functional analysts and developers (and of course our customers!) at the same time, the process needed to track the competing interests of various stakeholders: clients, their end users, their business processes, our technical requirements, our limited resources and our internal stakeholders. the designed solution had to work within a framework that could not be re-written. a poorly working metaphor was redefined into a concept that would work better with the end-users.
direct manipulation interface for architectural design tools. the early architectural design stage is a typical example where traditional design tools such as sketching on paper still dominate over computer-assisted tools. augmented reality is presented as a promising approach towards developing interaction techniques that preserve the naturalness of the traditional way of designing, while at the same time providing access to new media. based on the analysis of user requirements and requirements for a natural user interface, a working prototype of a new interaction platform for architectural design was created.
physiological computing. applications involving the measurement of human physiological responses to environment are becoming increasingly popular in hci. this is due in part to the increasing availability of low-cost, high-specification sensing technologies. areas such hci evaluation, affective computing and biofeedback-based brain-computer interaction are all benefiting from the rich data source physiological sensing technologies make available. however, guidelines on the gathering and analysis of these measurements are virtually non-existent, which makes it difficult for new researchers to practise in this area. this timely workshop will bring together both practising and potential researchers using this method to gather knowledge on the techniques, technologies and applications of physiological computing.
carcoach: a polite and effective driving coach. this paper describes the design and evaluation on the road of a context aware driving advisor designed to promote better driving behavior. carcoach takes the information gathered from various sensors in the car and identifies common driving mistakes to appropriately commenting on driving behavior. the system presents scheduled feedback controlled in terms of quantity of total feedback and feedback with regards to a specific stimulus, and driver current state. its goal is to reduce driver's stress while maximizing the effectiveness of the feedback presented.
usability tool for analysis of web designs using mouse tracks. this paper presents mousetrack as a web logging system that tracks mouse movements on websites. the system includes a visualization tool that displays the mouse cursor path followed by website visitors. it helps web site administrators run usability tests and analyze the collected data. practitioners can track any existing webpage by simply entering its url. this paper includes a design case that shows the tool's value for teaching interaction design concepts.
musiccube: making digital music tangible. to some extent listening to digital music via storage devices has led to a loss of part of the physical experience associated with earlier media formats such as cds and lps. for example, one could consider the role of album covers in music appreciation. previous efforts at making music interaction more tangible have focused mainly on access issues. a case study is presented in which several content attributes of mp3 formatted music as well as control access are made more visible and tangible. play lists, music rhythm, volume, and navigational feedback were communicated via multicolored light displayed in a tangible interface. users were able to physically interact with music collections via the musiccube, a wireless cube-like object, using gestures to shuffle music and a rotary dial with a button for song navigation and volume control. speech and non-speech feedback were given to communicate current mode and song title. the working prototype was compared to an apple ipod, along the dimensions of trust, engagement, ergonomic and hedonic qualities, and appeal. subjects rated the musiccube higher on scales associated with hedonic qualities, while the ipod was preferred for ergonomic qualities. results on trust measures were found to correlate with ergonomic qualities, while sense of engagement related to hedonic aspects. subjects generally valued the expressive and tangible interaction with music collections. next design steps will focus on increasing ergonomic aspects of the musiccube while maintaining a high hedonic rating.
developing a car gesture interface for use as a secondary task. existing gesture-interface research has centered on controlling the user's primary task. this paper explores the use of gestures to control secondary tasks while the user is focused on driving. through contextual inquiry, ten iterative prototypes, and a wizard of oz experiment, we show that a gesture interface is a viable alternative for completing secondary tasks in the car.
experimental evaluation of user errors at the skill-based level in an automative environment. concentrating on the lowest performance level of reason's error model, in this work we evaluated the potential of user errors in an automative environment. thereby the test subjects had to operate various in-car devices while primarily fulfilling a simulated 3d driving task. the study clearly showed that special error types are related to special distraction effects and that most of the operation errors are not critical and can be resolved by the user himself.
active cybercode: a directly controllable 2d code. many augmented reality (ar) applications which overlay computer graphics on a real image have been developed. one of the limitations of such applications is that a user has to control cg objects, invoked by a realworld condition, using a traditional input device like a keyboard or mouse. we developed a directly controllable 2d code called active cybercode. a user can give commands by putting his/her finger on a printed button beside the code. the code has fixed and variable parts, and the variable part is recognized as the same as the fixed part. it allows a computer to recognize commands without the need for expensive methods like finger recognition.
a fisheye calendar interface for pdas: providing overviews for small displays. datelens is a novel calendar interface for pdas. it supports users in performing planning and analysis tasks by using a fisheye representation of dates coupled with compact overviews, user control over the visible time period, and integrated search. this enables users to see overviews and to easily navigate the calendar structure, and to discover patterns and outliers.
making memories: applying user input logs to interface design and evaluation. in this paper, we describe our approach to designing interface components that automate the logging of user input. these recorded logs of user-system interactions can serve as a basis for usability assessment, and we present here the usability measures that can be automatically derived from this logged data. making user logs an integral component of the system data model extends their usefulness beyond providing information on user behavior. in our prototype, logs are used for creating a more collaborative interface by increasing the system's contextual awareness of user interactions.
displayless interface access to spatial data: effects on speaker prosodics. displayless interface technology must address challenges similar to those presented by the problem of providing gui access to visually impaired users. both must address the issue of providing nonvisual access to spatial data. this research examines the hypothesis that such access places a cognitive burden on the user, which in turn will impact the prosodics, i.e. nonverbal aspects, of the user's speech.
usability and learning in a speech-enabled reading tutor: a field study. in this paper we discuss outcomes of a field study conducted to evaluate usability and learning associated with a speech-enabled reading tutor application for adults. the evaluation compared learning outcomes and usability measures between two versions of the software, as well as with traditional classroom instruction. findings indicate small usability improvements and no significant difference in learning between versions, and equivalent learning levels between the groups who used the software exclusively and those that had a teacher cover the material instead. we discuss these results and how challenges associated with the field evaluation may have impacted the findings.
workshop on sigchi public policy. in this paper we describe the goals of a one-day workshop to be held at chi 2006 whose goal is to form an action plan for the sigchi u.s. public policy committee for the next year.
effects of display blurring on the behavior of novices and experts during program debugging. the restricted focus viewer (rfv) relates a small part of an otherwise blurred display to the focus of visual attention. a user controls which part of the screen is in focus by using a computer mouse. the rfv tool records these movements. recently, some studies used the rfv to investigate the cognitive behavior of users and some others have even enhanced the tool for research of usability issues.we report on an eye-tracking study where the effects of rfv's display blurring on the visual attention allocation of 18 novice and expert programmers were investigated. we replicated a previous rfv-based study and analyzed attention switching and fixation durations reported by an eye tracker. our results indicate that the blurring interferes with the strategies possessed by experts and has an effect on fixation duration: however, we found that debugging performance was preserved. we discuss possible reasons and implications.
mobile blogging: experiences of technologically inspired design. we discuss the details of the architecture, design, and acceptability of a system created to support mobile blogging, called smartblog. the process of blogging is often an instant-response mode of writing that provides its own challenges for systems that aim to support it.smartblog was developed from a technologically inspired design approach towards creating new artifacts, which we outline.
user performance and haptic design issues for a force-feedback sound editing interface. this paper describes current work on the design and development of haptic interfaces for use with digital sound editing software. current systems rely on computer keyboards, mice, and sometimes passive knobs for user input and graphics and audio for feedback. the addition of haptic feedback will improve the user experience because of the additional mode of feedback received through touch. this work is focused on using a design methodology, including need finding, user observations, prototyping, and user testing to develop haptic sensations effective for manipulating sound.
enhancing interactivity in webcasts with voip. this interactivity demonstration presents a novel coupling of webcasting (streaming) with audioconferencing in which voice over internet protocol (voip) communication is used in webcasts to enhance interactivity, engagement, and the sense of presence among viewers and presenters.
augmented reading: presenting additional information without penalty. we present a new interaction technique for computer-based reading tasks. our technique leverages users' peripheral vision as a channel for information transfer by using a video projector along with a computer monitor. in our experiment, users of our system acquired significantly more information than did users in the control group. the results indicate that our technique conveys extra information to users nearly "for free," without adversely affecting their comprehension or reading times.
evaluating interactive information retrieval systems: opportunities and challenges. information retrieval or search plays an important role in a wide range of information management and electronic commerce tasks. in spite of the importance of information retrieval, search systems are often poorly designed from a human computer interaction perspective. the goal of this sig is to articulate some of the opportunities and challenges in designing and evaluating highly interactive information retrieval systems.
the impact of structure and medium on choice and recall in profile assessment. electronic expert-finder systems routinely store expert information in profile format. a user can view these profiles to choose the expert he/she wants to work with. in this paper we examine how profile attributes affect a user's choice of an expert. we report the results of an exploratory study in which we manipulated the structure of profiles and the medium of presentation, and measured participant behavior in an it-helpdesk recruitment task. we found that the presence of structure in profiles decreases, while the electronic medium (compared to paper) increases the probability of choosing the most qualified candidate.
designing culturally situated technologies for the home. as digital technologies proliferate in the home, the human computer interaction (hci) community has turned its attention from the workplace and productivity tools towards domestic design environments and non-utilitarian activities. in the workplace, applications tend to focus on productivity and efficiency and involve relatively well-understood requirements and methodologies, but in domestic design environments we are faced with the need to support new classes of activities. while usability is still central to the field, hci is beginning to address considerations such as pleasure, fun, emotional effect, aesthetics, the experience of use, and the social and cultural impacts of new technologies. these considerations are particularly relevant to the home, where technologies are situated or embedded within an ecology that is rich with meaning and nuance.the aim of this workshop is to explore ways of designing domestic technology by incorporating an awareness of cultural context, accrued social meanings, and user experience.
designing the user interface of a data collection instrument for the consumer price index. the bureau of labor statistics (bls) collects data for a variety of economic indicators. to make data collection more efficient, bls has been developing computer-assisted data collection (cadc) instruments for many of these indicators. we recently deployed a cadc instrument for the consumer price index (cpi). the cpi is the most widely used measure of inflation and a leading economic indicator in the u.s. this paper describes the development process we used and how we overcame the challenges we faced.
lessons learned using ubiquitous sensors for data collection in real homes. interface design for the home requires a realistic understanding of the complexity and richness of the human activities that go on there; it is our goal to develop tools that enable hci investigation in actual home environments. we have developed a kit of ubiquitous sensing devices and over the past year have conducted a series of studies installing a large number of sensors, of diverse types, in multiple homes of participants not affiliated with the research team. as we deployed our portable kit outside the laboratory, we encountered unanticipated study design and technology requirements that will affect the continued development of the kit itself. we offer practical tips we have learned from our experience and describe how we are applying them to the design of our next generation of sensors.
gender hci issues in problem-solving software. thus far, researchers have not investigated gender hci issues in the context of end-user problem-solving software. designers' ignorance of gender differences is particularly evident in studies showing software is unintentionally designed for males. we are investigating gender hci issues using quantitative and qualitative empirical methods, using formative work to consider gender-conscious design features, implementing these features in our research prototype, and following up with summative work to evaluate effectiveness.
effects of alphanumerical display formatting on search time among chinese and american users. in this paper, we examine whether a design guideline derived from studies with american users can be generalized to chinese users. the effects of alphanumerical display formatting on search time among chinese and american college student were measured. users searched for a target word among a list of words in alphabetical order. the list was either displayed horizontally in rows or vertically in columns. the formatting of the list on the screen affected american users significantly with the vertical display leading to faster response. the formatting of the list on the screen had no significant effect on the response time among chinese users. the significance of this founding in terms of cross-cultural usability was discussed.
in search of end-users. learning from end-users is essential to participatory design, but before we can learn from them we must first find them. this search can be the hardest part of a project, however. what pro-active steps can be taken? in this paper we describe our search for end-users to work with on one particular design project. we reflect on why we were often unsuccessful, and how in the end we found end-users who were eager to collaborate with us to design a risk and compliance visualization.
effects of tiled high-resolution display on basic visualization and navigation tasks. large high-resolution screens are becoming increasingly available and less expensive. this creates potential advantages for data visualization in that more dense data and fine details are viewable at once. also, less navigation may be needed to see more data. however, little work has been done to determine the effectiveness of large high-resolution displays, especially for basic low-level data visualization and navigation tasks. this paper describes an exploratory study on the effects of a large tiled display with a resolution of 3840x3072 as compared to two smaller displays (1560x2048 and 1280x1024). we conclude that, with finely detailed data, higher resolution displays that use physical navigation significantly outperform smaller displays that use pan and zoom navigation. qualitatively, we also conclude that use of the larger display is less stressful and creates a better sense of confidence than the smaller displays.
sweep and point and shoot: phonecam-based interactions for large public displays. this paper focuses on enabling interactions with large public displays using the most ubiquitous personal computing device, the mobile phone. two new interaction techniques are introduced that use the embedded camera on mobile phones as an enabling technology. the "point & shoot" technique allows users to select objects using visual codes to set up an absolute coordinate system on the display surface instead of tagging individual objects on the screen. the "sweep" technique enables users to use the phone like an optical mouse with multiple degrees of freedom and allows interaction without having to point the camera at the display. prototypes of these interactions have been implemented and evaluated using modern mobile phone technologies. this proof of concept provides a performance baseline and gives valuable insights to guide future research and development. these techniques are intended to inspire and enable new classes of large public display applications.
pygmybrowse: a small screen tree browser. we present pygmybrowse, a browser that allows users to navigate a tree data structure in a limited amount of display space. a pilot evaluation of pygmybrowse was conducted, and results suggest that it reduces task completion times and increases user satisfaction over two alternative node-link tree browsers.
enhancement of communicative presence in desktop video conferencing systems. communicative presence (cp) has been defined as "... the capacity of a system to transfer mutual communicative signals of interlocutors." [2]. the main objective of my research is to define communicative presence more precisely and improve it in desktop video conferencing systems (dvcss). an initial experiment has suggested that the modality of all available channels should be consistent.
multi-monitor mouse. multiple-monitor computer configurations significantly increase the distances that users must traverse with the mouse when interacting with existing applications, resulting in increased time and effort. we introduce the multi-monitor mouse (m3) technique, which virtually simulates having one mouse pointer per monitor when using a single physical mouse device. m3 allows for conventional control of the mouse within each monitor's screen, while permitting immediate warping across monitors when desired to increase mouse traversal speed. we report the results of a user study in which we compared three implementations of m3 and two cursor placement strategies. our results suggest that using m3 significantly increases interaction speed in a multi-monitor environment. all eight study participants strongly preferred m3 to the regular mouse behavior.
system administrators are users, too: designing workspaces for managing internet-scale systems. the people who run large-scale computer systems deserve the attention of the hci community. these professionals work with increasingly diverse and complex hardware and software, large systems often characterized as "unknowable" by a single person. relying on relatively crude tools, these professionals keep the technological world running. by improving the system administration work environment, the cost of computing and risk of downtime will be decreased while the deployment of complex, beneficial systems will increase.this one-day workshop will focus on the hci problems of system administrators, specifically management of scale and diversity, problem solving, and system monitoring and notification. our goal is to bring together (1) hci researchers, (2) middleware user interface software developers, and (3) real-world system administrators to form a cross-disciplinary community around this topic.
the effect touching a projection augmented model has on perception and object-presence. this paper outlines the phd thesis entitled 'the effect touching a projection augmented model has on perception and object-presence'.
reality testing: hci challenges in non-traditional environments. non-traditional environments often change rapidly without forewarning, are difficult or impossible to control, and have other environmental and operational constraints that cannot easily be modeled in a laboratory, partly because the necessary level of ecological validity is almost impossible to achieve in the artificial lab environment. current in situ field study evaluation techniques are insufficient in these environments. furthermore, it is often difficult or impossible to ascertain which behavioral data are needed to answer questions about user requirements, interface design, and user acceptance. in this workshop, we will use case studies to create and explore frameworks for future non-traditional field study evaluations.
roombugs: simulating insect infestations in elementary classrooms. this paper presents research on a collaborative learning environment in an urban elementary science classroom. the application, called roombugs, simulates a dynamic ecosystem of insects within the physical space of a classroom. using table-mounted tablet computers as "sand traps" that capture the foot-prints of virtual bugs walking across the screen, participants take on the role of scientists attempting to track and control the imagined insects that exist within their classroom walls. the simulation is designed to create authentic phenomenon without requiring heavy instrumentation.
experimental study of cockpit displays of traffic information for pilot self-spacing in congested airspace. an experimental study examined cockpit displays of traffic information for pilot self-spacing in congested airspace. results demonstrate that pilots have the capability to benefit from additional traffic information and take over some additional control responsibility. additionally, this experiment shows that pilots benefit from the presentation of velocity and closure rate, and from range spacing arcs.
professional usability in open source projects: gnome, openoffice.org, netbeans. working as a usability professional in the open source arena is a challenging task. the decentralized and engineering-driven approach of open source projects can be at odds with corporate processes and usability engineering methodologies. nonetheless, there is great potential for large corporations to contribute to open source projects. providing usability know-how that leads to usable and useful products is a win-win situation for developers, the corporations, and -- most importantly -- the users.
research issues in wearable computers. wearable computers are becoming more common. a recent workshop on wearable computing in seattle attracted more than 200 attendees. for the most part, however, wearable computers are being treated as small computers with attempts to provide the same range of input and output devices as on a desktop and to utilize the same applications. we believe, however, that wearable computing is a new paradigm introducing new issues. it is not just mobile desktop computing. the purpose of this workshop is to discuss this position and to identify those research issues that are specific to wearable computers. the goal of the workshop is to produce a white paper identifying research issues in wearable computing and we expect this white paper to be seminal in the oncoming era of wearable computing.
preferences for unfavorable external representations in interaction with atms and multimedia. security codes accompany almost every new multimedia device. the codes are commonly represented in the form of symbolic numbers. the relative usefulness of symbolic and visuo-spatial representations of codes was investigated, using atm-codes as an enlightening example. visuo-spatial representations lead to higher performance on an immediate recall test. this suggests that explicit visuo-spatial representations in multimedia design may enhance usability. in spite of these results people showed preferences for the more frequently used numerical representations.
a model-based tool for interactive prototyping of highly interactive applications. we present a model-based case tool dedicated to the prototyping of highly interactive (also called post-wimp) applications. such applications are challenging to model and to prototype, since they require the use of non-standard widgets and interaction techniques and exhibit a complex dynamic behavior. the tool, called petshop, embodies the results of several years of research about the formal modeling of interactive systems, and its main application domain is safety-critical interactive applications such air-traffic control or military command and control systems. petshop stands apart from most formal-based tools since it supports and promotes an iterative and user-centered design process, and also stands apart from most model-based tools since it goes beyond wimp interfaces and does not sacrifice the formal validation of models.
personal information management. personal information management (pim) is the management of information (e.g. files, emails, and bookmarks) by an individual in support of his/her roles and tasks. although pim is practiced daily by millions of people, a research community has never been established. this sig aims to provide an opportunity for researchers, students and designers who share an interest in the field to meet and discuss key issues. we hope the sig will lay the foundation for an ongoing pim research community.
communicating more than nothing. strong social connections permeate one's daily life. with the numerous means available, these connections can easily dominate one's communications, though one only wants to convey and have a sense of presence in each other's lives. portal frame fosters this feeling of connection between individuals while keeping the amount of active communication that must take place to a minimum. individuals are provided a means to glimpse the lives of intimate friends through a well known and established physical medium, the picture frame.
co-experience: the social user experience. this paper presents a critical view of existing models of user experience. these models view experience as the subjective response in the individual's mind. while designers and developers have to try to provide a satisfying user experience, the means to do so remain limited. this paper presents a missing aspect of user experience. experience can be seen as an individual's reaction, but also as something constructed in social interaction. designed artifacts, especially personal communication and digital media products, environments and systems can facilitate this kind of use. "co-experience" is the experience that users themselves create together in social interaction.
browsing through an information visualization design space. ilog discovery is an information visualization editor, which allows browsing the visualization design space of data sets. this editor relies on the definition of data-linear visualizations, which are a very large class of visualizations that are defined from a relatively small number of parameters. visualizations that can be produced by the editor encompass histograms, parallel coordinates, treemaps, as well as mixes of those representation types, such as a parallel histogram embedded in a treemap, all with one single unified model.
video visions of the future: a critical review. this panel explores the impact video and film visions of the future have had on user centered design, with a focus on the role of corporate vision pieces from recent decades.two vision video veterans join us: hugh dubberly, co-creator of apple's "knowledge navigator" and bruce tognazzini, creator of sun microsystem's "starfire". we consider how well the chi community has anticipated or created the future. are we better off having created these visions, or are they costly exercises with little or no reward? lastly, we view excerpts from several hollywood films to ask if they teach us something about envisioning the future.
workshop: teaching interaction design. a full day workshop focused on the practice and philoso-phies involved with teaching interaction design to students and professionals. the format involved teachers expressing their approaches to the challenges of design education, and group discussion and sharing of ideas and stories from their experiences.
mouse ether: accelerating the acquisition of targets across multi-monitor displays. when acquiring a target located on a different screen, multi-monitor users face a challenge: differences in resolution and vertical and horizontal offsets between screens cause the mouse pointer to get warped, making the attempt to acquire the target difficult. mouse ether eliminates warping effects by applying appropriate transformations to all mouse move events. in our user study, mouse ether improved participants' performance on a target acquisition task across two screens running at different resolutions by up to 28%. 7 of the 8 participants also strongly preferred using mouse ether to the control.
discovery point: enhancing the museum experience with technology. the discovery point prototype allows art museum visitors to hear stories about a work of art without burdening them with lengthy commentary. it is simple and compact; it has only four buttons and can be worn around the neck. it is a nearly invisible addition to the museum experience, but one that fills the need to deliver the right amount of information to visitors. to develop this concept, we observed and interviewed visitors, constructed a prototype, and then evaluated that prototype through two rounds of user tests at the museum.
focus plus context screens: displays for users working with large visual documents. users working with documents that are too large and detailed to fit the user's screen (e.g. chip designs) have the choice of zooming or applying appropriate visualization techniques. in this demonstration, we will present focus plus context screens-wall-size low-resolution displays with an embedded high-resolution display region. they allow users to view details of a document up close, while simultaneously seeing peripheral parts of the document in lower resolution. unlike overview plus detail, focus plus context screens do not require users to visually switch between multiple views. unlike fisheye views, focus plus context screens do not introduce distortion.
ovid: object view and interaction design. several methods are already available for object oriented program design. these methods do not deal with user interface design. the tutorial teaches ovid, a systematic method for designing object user interfaces for use by product design teams. ovid is a major step in changing user interface design from art to science. it emphasizes the production of a complete, accurate model that can be used as input to program design methodologies.
personal information geographies. we need increasingly better tools to help us manage today's flood of information. this research explores the use of visual maps as workspaces which help us both to organize new material and to relocate past resources. in particular, visual workspaces can facilitate the process of sensemaking, the gradual evolution of an inquiry through our repeated interaction with information. this interaction can serve as an organizing structure for personally meaningful information geographies: map-like workspaces which accumulate 'trails' of our activity, which evolve over time but remain stable enough to provide the same fluency that we have with maps of physical places.
evaluating the effect of technology on note-taking and learning. current note-taking applications have been shown to affect the way students take notes. the impact on learning has not been studied. in this paper, we describe a project aimed at addressing how specific features of note-taking tools impact both behavior and performance. we describe our initial results evaluating copy-paste functionality, their implication for design, and future studies. we believe this work has relevance not only for the design of note-taking tools, but for a broader chi audience.
teresa: a transformation-based environment for designing and developing multi-device interfaces. the ever-increasing availability of new types of devices raises a number of issues for user interface designers and interactive software developers. we have designed and developed a model-based authoring environment (teresa), which provides support when designing and developing interfaces accessible through various device types in web-based environment.
fridgets: digital refrigerator magnets. the senior population is a broad, diverse demographic that it is often overlooked by traditional markets, particularly in the united states. in addition, seniors commonly experience feelings of isolation, abandonment and loneliness. this paper seeks to examine the sources of depression in the elderly and to explore human-centered technological solutions. we then propose a system of refrigerator-based technologies designed to foster self-reliance and connectedness among seniors.
memory-rich clothing. this paper describes a series of reactive body-worn artifacts that display their history of use and communicate physical (or embodied) memory. these electronically enhanced garments strive to promote touch, physical proximity, and human-to-human interaction. we explored distinct input, mapping, and output methodologies that deal with different models of autonomy, memory, and interruption granularity.the pieces described are part of a larger research project called memory rich clothing. by concentrating on garments that reflect more subtle, playful, or poetic aspects of our identity and history, our enquiry attempts to redefine some of the assumptions that technology designers traditionally make under financial and cultural constraints about how people interact and communicate with each other.
smoks: the memory suits. this paper describes smoks, a pair of electronically enhanced suits that acts as an experimental platform for constructing individual and collective memories, for creating and nurturing social networks, and for personal communication and intimacy.the suits combine and overlay different interaction methodologies explored in our larger research project called memory rich clothing. moreover, rather than deploying a single social electronic artifact, we created garments in pairs, balancing the interaction affordances between users and creating conditions for the emergence of playful social networks surrounding the body.by capturing physical memories, representing traces of human touch, recording and playing sounds, and by providing hiding places for physical mementoes, the smoks use fashion and our interactions through clothing to accumulate and display traces of physical memory in personal and playful ways.
somo: an automatic sound & motion sensitive audience voting system. continuous controversy surrounding the judging of events during the olympic games incites the need for a system of audience participation in scoring. in this way the audience votes could theoretically be considered by the judges. in this pilot proposal the audience vote will initially be offered purely as a form of entertainment and a means to increase audience participation. judging, be it by a professional or an amateur prospector seems to suffer from idiosyncrasies (bias). in the design of a new flexible and highly usable system for collecting spectators' scores, this problem is embraced instead of denied. without harming the spontaneous reaction and appreciation of the international audience for an athlete, the designed sound & motion (somo) system takes the normal response (clapping, cheering, and waving) of an audience and translates this into a vote.
interface agents as social models: the impact of appearance on females' attitude toward engineering. this experimental study investigated the impact of interface agent appearance (age, gender, "coolness") on enhancing undergraduate females' attitudes toward engineering. results revealed that participants reported more positive stereotypes of engineers after interacting with a female agent. in contrast, participants interacting with a male agent reported that engineering was more useful and engaging. an interaction of "coolness" and age indicated that agents who were young and "cool" (i.e., peer-like; similar to participants) and agents who were old and "uncool" (stereotypical engineers) were both most effective on enhancing self-efficacy toward engineering.
creating a ux profession. current aspirations to coordinate the ux community should be complemented by a coordinated series of professional initiatives to raise the status of the ux profession so that it can take its rightful role at the heart of the development process.
health view: a simple and subtle approach to monitoring nutrition. young adults today often lack the knowledge and skills necessary to manage a nutritious eating pattern. monitoring nutritional intake can provide the stimulus to change unhealthy patterns. to this end we introduce health view, a web-based nutrition monitoring system that subtly integrates with the current habits of today's young adults. health view leverages already-existing grocery store savings card accounts to pull the necessary data into the system automatically. by managing grocery lists and providing a repository for recipes, health view enables the conditions for monitoring the nutrition of users while they go about their usual tasks. when the current nutrition status is known, health view can then make simple suggestions for improving the consumption habits of the users.
video and image-based reflective learning tools for professional training environments. i am interested in the learning processes that go on in hands-on professional training domains, and how to design digital technology to help people acquire professional skills. in my dissertation research, i am conducting a multi-year ethnography-for-design project at a local dental hygiene training program looking at how new students develop expertise in instrumentation skills during hands-on training in a clinical laboratory. i have helped the school design a new clinical training laboratory, equipped with a variety of digital media technology, such as embedded monitors and overhead cameras. i am investigating how digital imaging and video technology affect how novices develop the complex skill set (perceptual, manual and conceptual) required of expert dental hygienists. in order to create successful technology for teaching expert skills, it is important to understand the learning effects of certain kinds of representations, media, and instructional strategies. research methods are informed by ethnography-for-design and contextual design [11], situated in a framework provided by distributed cognition theory [12].
a framework for locomotional design: toward a generative design theory. generative design theories are needed to bridge the gaps between pure scientific knowledge, individual ("point") designs and systematic generation of viable design alternatives. this papers suggests a framework for locomotional design that uses knowledge of navigation and spatial cognition to inform design. examples of the implications of two such pieces of knowledge are sketched out, suggesting how this framework might lead to a generative design theory.
predictive targeted movement in electronic spaces. the lodestones and leylines interaction technique simplifies navigation in electronic spaces by coordinating physical and conceptual movement-gently constraining motion to follow automatically computed paths to predicted destinations. this approach simplifies physical movement, ensures that movement leads to interesting locations and supports navigation to locations not visible from the current location. it is illustrated in a spatial multiscale environment where pilot data show reliable performance improvements.
the "magic number 5": is it enough for web testing? common practice holds that 80% of usability findings are discovered after five participants. recent findings from web testing indicate that a much larger number of participants is required to get results and that independent teams testing the same web-based product do not replicate results. how many users are enough for web testing?
webgazeanalyzer: a system for capturing and analyzing web reading behavior using eye gaze. capturing and analyzing the detailed eye movements of a user while reading a web page can reveal much about the ways in which web reading occurs. the webgazeanalyzer system described here is a remote-camera system, requiring no invasive head-mounted apparatus, giving test subjects a normal web use experience when performing web-based tasks. while many such systems have been used in the past to collect eye gaze data, webgazeanalyzer brings together several techniques for efficiently collecting, analyzing and re-analyzing eye gaze data. we briefly describe techniques for overcoming the inherent inaccuracies of such apparatus, illustrating how we capture and analyze eye gaze data for commercial web design problems. techniques developed here include methods to group fixations along lines of text, and reading analysis to measure reading speed, regressions, and coverage of web page text.
domain-specific search strategies for the effective retrieval of healthcare and shopping information. an increasing number of users are performing searches on the web in unfamiliar domains such as healthcare. however, because many users lack domain-specific search knowledge, their searches are often ineffective. an important remedy is to make domain-specific search knowledge in these new domains explicit and available. towards that goal, healthcare and online shopping experts were observed while they performed search tasks within and outside their domains of expertise. the study: (1) identified domain-specific search strategies in each domain; (2) demonstrated that such knowledge is not automatically acquired from using general-purpose search engines. these results suggest that users should benefit from strategy portals that provide domain-specific knowledge to perform searches in unfamiliar domains.
measuring visual appeal of web pages. much research in human-computer interaction (hci) has focused on usability. an equally important yet often overlooked component of hci is the subjective visual appeal of an interface [3]. the present paper redresses this shortcoming by comparing two approaches to measuring the subjective visual appeal of web pages.
sig: the role of human-computer interaction in next-generation control rooms. the purpose of this chi special interest group (sig) is to facilitate the convergence between human-computer interaction (hci) and control room design. hci researchers and practitioners actively need to infuse state-of-the-art interface technology into control rooms to meet usability, safety, and regulatory requirements. this sig outlines potential hci contributions to instrumentation and control (i&c) and automation in control rooms as well as to general control room design.
exploring the distribution of online healthcare information. motivated by the importance of retrieving comprehensive healthcare information, we analyzed how information about 12 concepts related to a widely available healthcare topic is distributed across 145 high-quality webpages. the analysis reveals that the distribution of the concepts follows a power law where a few pages contain many concepts, while the majority contains less than half the concepts. the analysis also reveals the existence of general, specialized, and sparse pages, in addition to the large number of pages that users must visit before they have access to all the concepts. these results provide insights into expert search procedures, and motivate the design of future search systems that guide users in the retrieval of comprehensive information.
helping users determine video quality of service settings. in this paper, we present a method to assist users in selecting quality parameters for streaming video. constrained scaling, a method for calibrating users' subjective judgements to a naturalistic scale is introduced. an experiment in which participants judged the fluidity of sample videos across different frame rates demonstrates the effectiveness of constrained scaling.
towards the design of multimodal interfaces for handheld conversational characters. this paper presents a study of individuals having conversations with animated characters on pdas, and characterizes their use of natural nonverbal behavior compared to behavior exhibited in similar conversations with another person. the study finds that most people use the same nonverbal behavior in conversation handheld characters that they use in conversations with people, although the frequency is somewhat lower in the handheld case. these results can inform the design of new pda input modalities which leverage the natural nonverbal behavior observed.
traveling blues: the effect of relocation on partially distributed teams. this experimental study looks at how relocation affected the collaboration patterns of partially-distributed work groups. partially distributed teams have part of their membership together in one location and part joining at a distance. these teams have some characteristics of collocated teams, some of distributed (virtual) teams, and some dynamics that are unique. previous experiments have shown that these teams are vulnerable to in-groups forming between the collocated and distributed members. in this study we switched the locations of some of the members about halfway through the experiment to see what effect it would have on these ingroups. people who changed from being isolated 'telecommuters' to collocators very quickly formed new collaborative relationships. people who were moved out of a collocated room had more trouble adjusting, and tried unsuccessfully to maintain previous ties. overall, collocation was a more powerful determiner of collaboration patterns than previous relationships. implications and future research are discussed.
acceptance and usability of a relational agent interface by urban older adults. this study examines the acceptance and usability of an animated conversational agent designed to establish long-term relationships with older, mostly minority adult users living in urban neighborhoods. the agent plays the role of an exercise advisor who interacts with subjects daily for two months on a touch-screen computer installed in their homes for the study. survey results indicate the eight subjects who completed the pilot study (aged 62-82) found the agent very easy to interact with, even though most of them had little or no previous experience using computers. most subjects also indicated strong liking for and trust in the agent, felt that their relationship with the agent was more similar to a close friend than a stranger, and expressed a strong desire to continue working with the agent at the end of the study. these results were also confirmed through qualitative analysis of post-experiment debrief transcripts.
modalities for building relationships with handheld computer agents. in this paper we describe the design of a relational agent interface for handheld computers and the results of a study exploring the effectiveness of different user-agent interaction modalities. four different agent output modalities-text only, static image plus text, animated, and animated plus nonverbal speech-are compared and their impact on the ability of the agent to establish a social bond with the user, the perceived credibility of information delivered, and user acceptance is evaluated. subjects ranked the two animated versions of the system higher on all measures.
towards caring machines. the perception of feeling cared for has beneficial consequences in education, psychotherapy, and medicine. results from a longitudinal study of simulated caring by a computer are presented, in which 60 subjects interacted with a computer agent daily for a month, half with a "caring" agent and half with an agent that did not use behaviors to demonstrate caring. the perception of caring by subjects in the "caring" condition was significantly higher after four weeks, and was also reflected in qualitative interviews with them, and in a significantly higher reported willingness to continue working with the "caring" agent. this paper presents the techniques that contributed to the increased perception of caring, and presents some of the implications of this new technology.
using an adaptive display for the treatment of emotional disorders: a preliminary analysis of effectiveness. a preliminary study on the use of an adaptive display for treating emotional disorders is presented. this adaptive display (named emma) varies the contents that are presented depending on the emotions of the user at each moment. the application has been designed to help in the treatment of post-traumatic stress disorder (ptsd) and adjustment disorder (ad). the specific objective of the present work is to test the effectiveness of this adaptive display, specifically the acceptance of the treatment by patients. emma's tools are compared with the standard of care for ptsd and ad. results showed differences only for the variable aversiveness. participants in the emma condition evaluated the treatment less unpleasant at post treatment, compared to participants in the traditional condition.
the comforting presence of relational agents. in this paper we describe an on-going experiment on the calming effects of a relational agent on users following a social bonding interaction. applications to a range of health care problems are discussed.
icare: a component-based approach for the design and development of multimodal interfaces. multimodal interactive systems support multiple interaction techniques such as the synergistic use of speech, gesture and eye gaze tracking. the flexibility they offer results in an increased complexity that current software development tools do not address appropriately. in this paper we describe a component-based approach, called icare, for specifying and developing multimodal interfaces. our approach relies on two types of components: (i) elementary components that describe pure modalities and (ii) composition components (complementarity, redundancy and equivalence) that enable the designer to specify combined usage of modalities. the designer graphically assembles the icare components and the code of the multimodal user interface is automatically generated. although the icare platform is not fully developed, we illustrate the applicability of the approach with the implementation of two multimodal systems: memo a geonote system and mid, a multimodal identification interface.
djogger: a mobile dynamic music device. maintaining motivation during exercise can be difficult for people engaged in individual workout routines. a common method for maintaining pace and staying motivated is the introduction of a musical soundtrack. the pace of the music and selection of songs influences the workout by suggesting how one should adjust their effort, or help with the timing of a precise regimen. to explore the impact of music on pace and motivation in exercise, we present our work so far on djogger. djogger builds a model of a runner's pace and uses this information along with a workout plan to dynamically adjust the musical soundtrack. djogger contributes a compelling application of hci to fitness, and explores methods for real world wearable evaluation.
technology: a means for enhancing the independence and connectivity of older people. the focus of this panel will be on aging and technology. the intent is to demonstrate how technology can be used to help older adults remain independent, productive and connected to family, friends, resources and services. actual examples, using a variety of formats, of the types of difficulties older people encounter when they confront technical systems will be provided. interview data from older people regarding their experiences with technology will also be presented. finally, suggestions for needed research and design solutions will be discussed. the overall intent of the panel is to energize the hci community to focus on issues relevant to aging and technology.
multiscale pointing: facilitating pan-zoom coordination. in a laboratory experiment on multiscale pointing, we compared one-handed vs. two-handed input for two zoom-control devices, a wheel vs. a mini-joystick with an all or none response. using a recent method of quantifying multiple degree-of-freedom (dof) input coordination to evaluate pan-zoom parallelism, we confirm previous work [1] showing that multiscale pointing performance strongly depends on the degree of pan-zoom parallelism. the new finding is that two-handed input and a constant zoom speed allow more input parallelism, thereby increasing performance speed.
a comparative study of map use. we present a study comparing the handling of three kinds of maps, each on a physical device: a paper map, a tablet-pc based map, and a cellular phone based one. six groups of users were asked to locate eight landmarks, looking out a window, and using a particular map. we have begun analyzing video recordings of the situations, and this paper will give examples of the handling of the three kinds of physical devices.
phases of use: a means to identify factors that influence product utilization. in usability research and design much emphasis is placed on creating products that are easy to learn and efficient to use. this does not guarantee however that the product is actually being used in an optimal way. this article describes utilization of a new product as a process with different phases. a product will only be optimally used if all these phases are successfully gone through. based on the experience of the authors in product development, a model is created that helps product development, sales, marketing and support to develop a product that is not only easy to use, but also creates awareness, motivates people to use it and helps people to imbed the product in their daily lives.
entity quick click: rapid text copying based on automatic entity extraction. retyping text phrases can be time consuming. as a result, techniques for copying text from one software application to another, such as copy-and-paste and drag-and-drop are now commonplace. however, even these techniques can be too slow in situations where many phrases need to be copied. in the special case where the phrases to be copied represent syntactically identifiable entities, such as person names, company names, telephone numbers, or street addresses, much faster phrase copying is possible. we describe entity quick click, an approach that reduces both the amount of cursor travel and the number of button presses needed to copy a phrase.
sparrow web: group-writable information on structured web pages. sparrow web is a server-based software tool that supports the creation and customization of group-writable web pages. templates in each page define the data schema and layout of that page's group-editable data items. using different templates, page authors produce web pages that support many tasks, including task lists, co-authored documents, bibliographies, home pages, faculty directories, and project lists. while lacking the rich ui of dedicated information-sharing applications, it is successful at supporting a variety of groups and tasks because it integrates information-sharing into web pages, leveraging the affordances of the web for supporting group work.
a different kind of information appliance: fridge companion. a prototype device is described that allows a user to understand and contemplate the inner workings of a common home applicance, the refrigerator. the device monitors select physical properties of its host and displays scheduled graphic presentations on the host's principles of operation. fridge companion is a device designed to make domestic life not easier but deeper.
"this is a lot easier!": constrained movement speeds navigation. this paper reports on an experiment comparing constrained and unconstrained movement in a 2d zooming environment. results showed a significant reduction in time on task when movement was constrained, accompanied by considerable decreases in mouse movement activity. detailed analysis suggests that subjects were calmer, more confident in their actions and experienced less spatial disorientation, indicating that judiciously constrained movement can reduce both mechanical and cognitive demands of navigation.
exploring web browser history comparisons. this work explores how comparing web navigation histories between two people and presenting the results to them might allow them to gain insight about each other. we developed a prototype that presents web matches sorted according to frequency, recency, and web site. interviews with users of the prototype suggest that common interests and preferences can be inferred from these comparisons.
speech user interface design challenges. there have been dramatic improvements during the last decade in the performance of both automatic speech recognition (asr) systems and the computers on which they run. speaker independent recognition with an active vocabulary of over 1,000 items is now possible even under the difficult conditions imposed by the public switched telephone network. the impressive raw recognition power of commercial recognizers has led to the development of a wide range of complex information, call management, and transaction services that rely on asr. despite this progress, it has become clear that recognition performance in the lab is not a good predictor of success in the field, and that extensive work on dialogue design and human factors "tuning" is required before most services can be used successfully by the general population. since recognizer capabilities strongly influence user-interface design, and since these capabilities have been changing rapidly over the past decade, there is no clear body of knowledge that a designer can turn to when developing new services that rely on speech.
factors affecting the utility of technology-mediated collaboration in science and engineering. there is significant interest in scientific and industrial collaboration and the cscw technologies to support it. what is missing, however, is a means for systematic assessment of prospective users, in order to determine what tools are needed and how organizational factors encourage or discourage collaboration. this study proposes development and deployment of a survey instrument measuring social and organizational factors that will likely affect the utility of collaboration for scientists in 3 fields. results will drive the design of other types of tools for assessing group needs, and specific recommendations about tools likely to be useful under different conditions.
smart sinks: real-world opportunities for context-aware interaction. can implicit interaction with a computer easily drive useful interface improvements in physical world settings? this paper presents a case study presenting multiple such context-aware interaction improvements in a sink. we have identified opportunities where automated interfaces at the sink have positive consequences for safety, hygiene and ecology. the danger of scalding oneself with hot water is confronted by transforming the water into a graphical user interface and using image understanding to dispense the proper temperature of water. audio-visual feedback at the sink can motivate users to conserve water. used in combination with an rfid reader, the sink can serve as an effective means of verifying hand-washing compliance for clean environments. finally, automatic actuation of the sink's height based on the user and task can prevent burns and ergonomic injuries. this project demonstrates that the integration of digital interaction in a hostile environment can facilitate and improve our daily rituals.
friendster and publicly articulated social networking. this paper presents ethnographic fieldwork on friendster, an online dating site utilizing social networks to encourage friend-of-friend connections. i discuss how friendster applies social theory, how users react to the site, and the tensions that emerge between creator and users when the latter fails to conform to the expectations of the former. by offering this ethnographic piece as an example, i suggest how the hci community should consider the co-evolution of the social community and the underlying technology.
does immersion make a virtual environment more usable? usability tests comparing three different virtual environment (ve) interface designs indicate that an immersive ve is more usable than two non-immersive ves for a task with search and navigation components. three interface designs were tried in a counterbalanced within-subjects procedure with ten randomly-ordered trials for each interface design. one of the interface designs used a head-tracked, stereoscopic head-mounted display. the other two interface designs used hand-tracking and were non-immersive---the visual display appeared on a desktop monitor. results for sixty participants doing the same task with each interface design show faster task completion times with the immersive design.
attention-based design of augmented reality interfaces. the objects and surfaces of a task-based environment can be layered with digital interfaces to make them easier and safer to use. once information can be projected anywhere in the space, it becomes crucial to design the information to make optimal use of users' attention. we have prototyped and evaluated a real-world augmented reality kitchen where user-centered interfaces and displays can be projected anywhere in the space to improve its usability. the augmented environment is designed to support the activities of a variety of people in diverse kitchen environments.this paper presents five intelligent kitchen systems that layer useful interfaces onto the refrigerator, range, cabinets, countertops and sink. the interface design is driven by human factors, especially attention theory and user evaluations. by projecting interfaces where they require the least cognitive load, we hope to improve the performance and confidence of users. the design employs cueing and search principles from attention theory. we present the results of pilot studies and future directions for our work.
about interaction group. this paper gives an overview of the hci group i belong to. research domain and focus, history and mission, research activities, published outcomes and current issue are described.
playpals: tangible interfaces for remote communication and play. playpals are a set of wireless figurines with their electronic accessories that provide children with a playful way to communicate between remote locations. playpals is designed for children aged 5-8 to share multimedia experiences and virtual co-presence. we learned from our pilot study that embedding digital communication into existing play pattern enhances both remote play and communication.
task difficulty as a predictor and indicator of web searching interaction. this study explored how the perception of task difficulty affects information searching interaction. we analyzed how the relationship between perceived task difficulty and information searching interaction varies by different types of tasks. these types were factual task, interpretive task, and exploratory task. the implications of the results are twofold. in the first place, we can illuminate some general agreement about the relationship between task difficulty and actual searching behavior. considering the statistical significance of differences in task difficulty and searching behavior measures enables this. we can also explain the disagreement of relationship, if any, by analyzing factors identified as underlying the difficulty of a task.
tangible interface for collaborative information retrieval. most information retrieval (ir) interfaces are designed for a single user working with a dedicated interface. we present a system in which the ir interface has been fully integrated into a collaborative context of discussion or debate relating to the query topic. by using a tangible user interface, we support multiple users interacting simultaneously to refine the query. integration with more powerful back-end query processing is still in progress, but we have already been able to evaluate the prototype interface in a real context of use, and confirmed that it can improve relevance rankings compared to single-user dedicated search engines such as google.
hands on cooking: towards an attentive kitchen. to make human computer interaction more transparent, different modes of communication need to be explored. we present eyecook, a multimodal attentive cookbook to help a non-expert computer user cook a meal. the user communicates using eye-gaze and speech commands, and eyecook responds visually and/or verbally, promoting communication through natural human input channels without physically encumbering the user. our goal is to improve productivity and user satisfaction without creating additional requirements for user attention. we describe how the user interacts with the eyecook prototype and the role of this system in an attentive kitchen.
extended abstract a field computer for animal trackers. the field computer system has been developed to gather complex data on amimal behaviour that is observed by expert animal trackers. the system is location aware using the satellite global positioning sytem. the system has been designed to empower semi-literate trackers. user testing showed that trackers were easily able to master the interface. they benefit from greater recognition, while the wider community gains from access to the knowledge of the trackers on animal behaviour.
single-handed interaction techniques for multiple pressure-sensitive strips. we present a set of interaction techniques that make novel use of a small pressure-sensitive pad to allow one-handed direct control of a large number of parameters. the surface of the pressure-sensitive pad is logically divided into four linear strips which simulate traditional interaction metaphors and the functions of which may be modified dynamically under software control. no homing of the hand or fingers in needed once the fingers are placed above their corresponding strips. we show how the number of strips on the pad can be virtually extended from four to fourteen by detecting contact pressure differences and dual-finger motions. due to the compact size of the device and the method of interaction, which does not rely on on-screen widgets or the 2d navigation of a cursor, the versatile input system may be used in applications, where it is advantageous to minimize the amount of visual feedback required for interaction.
emotional interaction. this paper discusses the association of emotions as an underlying component of everyday human-computer interaction. it presents the ongoing work in the design of an experiment to help understand the role that cognitive or appraisal theory of emotions might have in shaping the human-computer dialogue.
faces of emotion in human-computer interaction. the study of users' emotional behavior in the human-computer interaction (hci) field has received increasing attention during the last few years. our work in this area focuses on the relationship between user emotions and perceived usability problems. specifically, we propose to observe users' spontaneous facial expressions as a method to identify adverse-event occurrences at the user interface level.this paper reports on the results of an experiment designed to investigate the association between adverse-event occurrences during a word processing task and users' facial expressions monitored using electromyogram (emg) sensor devices. the results suggest that an increase of task difficulty is related to an increase in specific facial muscle activity, thus creating a baseline for future developments using camera-based monitoring of facial activities.
designing interactivity for the specific context of designerly collaborations. we report on one of several exploratory, formulative studies that we conducted to help inform the thoughtful use of mixed physical and digital interactivity in a wiki-based system targeted at design collaborations. this study had two parts, both involving bar-coded cards, a bar-code scanner, and a projector. one part emphasized a creative, synthesis-oriented design activity. the other part emphasized a decision-making design activity.we learned that our method of designing the physical cards and the variance in the types of information we included on the cards significantly affected the collaborative behaviors. we also learned that the extension of interactivity from the digital to the physical world and back again successfully scaffolded both creative and decision-making activities in our context, although with some very notable differences in interactive behaviors between the specific activities. this latter point notwithstanding, we learned that allowing high-resolution, small size physical cards to be arrayed and manipulated on a shared surface matters much more for the purposes of scaffolding the collaborative activities than the ability to scan and project large-size, low-resolution facsimiles of the same information, in specific contexts of collaborative story-creation and decision making.
corporate re-orgs: poison or catalyst to hci? are you facing a corporate re-org? re-orgs can create exciting opportunities for hci groups, or good people's careers can be set back. this panel of hci managers will consult on corporate reorganizations described by audience members. first, panelists with different perspectives discuss the roles of hci resources during re-orgs. then the panel will address audience questions on how to be proactive about organizational changes. (send your questions to stephanie@teced.com by march 15th.) this panel will be of special interest to the industry segment of the chi community-and also to academics who are educating future practitioners.
computerized self-administered questionnaires on touchscreen kiosks: do they tell the truth? a computerized self-administered questionnaire (csaq) was implemented on a touchscreen-based information kiosk. because of the voluntary nature thereof and uncontrolled circumstances in which respondents could complete the survey, it was essential to determine whether the feedback could be regarded as representing the true feelings of kiosk users. respondents were categorized according to the number of items completed and the internal consistency of responses within each category was examined. results from the csaq were compared with those from a paper-based survey. it was found that results of a csaq can be trusted if they are analyzed correctly.
intouch: a medium for haptic interpersonal communication. in this paper, we introduce a new approach for applying haptic feedback technology to interpersonal communication. we present the design of our prototype intouch system which provides a physical link between users separated by distance.
a theory of personalized recommendations. 35 internet users were assigned to one of seven discussion groups where they expressed views on interacting with a recommendation system (rs). grounded theory analysis of the data yielded a theory that highlights factors affecting an individual's decision to use personalized predictions.
service innovation and design. this panel introduces the chi community to a growing area of innovation and business development that leverages new technology platforms, namely service design. this topic is explored through a series of case studies of service design in a diverse set of industries and contexts from healthcare delivery to internet -based services.
strategic usability: introducing usability into organisations. usability may now be practised by a large number of software developers, but has yet to gain wide acceptance. communicating the value of usability must happen across multiple levels of an organisation, and requires speaking several "languages". this practical, hands-on tutorial will cover techniques for convincing management or potential clients of the value of usability, in terms each group understands. it will examine what is required to develop a usability strategy for a whole organisation to finding data to convince stakeholders of a single usability activity.
taptap: a haptic wearable for asynchronous distributed touch therapy. taptap is a wearable haptic system that allows nurturing human touch to be recorded, broadcast and played back for emotional therapy. haptic input/output modules in a convenient modular scarf provide affectionate touch that can be personalized. we present a working prototype informed by a pilot study.
an automated approach and virtual environment for generating maintenance instructions. maintenance of complex machinery such as aircraft engines requires reliable and accurate documentation, including illustrated parts catalogs (ipcs), exploded views, and technical manuals describing how to remove, inspect, repair and install parts. for new designs, there are often time constraints for getting a new engine to the field, and the available documentation must go with it. authoring technical manuals is a complex process involving technical writers, engineers, as well as domain experts (mechanics and designers). often, several revisions are required before a manual has correct ipc figures and maintenance instructions. compounding this problem is that technical writers often perform tasks better suited for computers, leading to increased costs and error.in this demonstration, we describe a new framework to generate maintenance instructions from solid models (computer aided design/cad data) and then validate these instructions in a haptics-enabled virtual environment. our approach utilizes natural language processing techniques to generate a presentation-independent logical form, which can be transformed for display within the virtual environment. during the development of the system, task analyses, human models, usability studies, and domain experts were used to gain insights. the end result is a more integrated and human-centered process for developing technical manuals, providing higher quality documents with less cost.
leave the office, bring your colleagues: design solutions for mobile teamworkers. one of the keys to successful deployment of mobile multimedia technology among professionals lies in identifying inherently distributed teams working under real-time constraints in dynamic field environments where the need to increase the efficiency of co-ordination, communication and collaboration is apparent. we report on some findings from investigating such non-office/out-of-office user-groups, and discuss the design of a portable environment for supporting the virtual reinforcement of teams, with special emphasis on co-worker status monitoring with respect to process phase, availability, geographical position etc.
broken expectations in the digital home. as part of an ongoing effort to understand ease of use of digital home technologies, we undertook an exploratory study of people who use their home networks for more than just broadband internet access. in particular, we wanted to understand the overhead, or problem-time, people spent with their home network devices. as expected, we saw issues of broken hardware and broken software. we also found that problems are often caused by broken expectations, a mismatch between what a person expects to be able to do and specific device capabilities. in this paper we explore broken expectations in the digital home with examples from our study. these observations suggest further research into the ways user expectations and activities shape the digital home experience.
technology biogarphies: field study techinques for home use product development. the technology biography combines and adapts a number of qualitative data collection techniques to focus on past, present and possible future domestic technologies. processes, concerns and problems of domestic life are identified in order to develop illustrative product suggestions to inspire or provoke designers.
sexual interactions: why we should talk about sex in hci. within the chi community there is growing interest in moving beyond cognition and expanding into the social, emotional, and bodily aspects of the human-computer experience. sexuality sex lies at the intersection of these concerns, and indeed outside of hci, has become a central topic for anthropology, behavioral sciences, and other areas of intellectual inquiry. examining sex and themes related to it has benefited these disciplines and we intend to understand how it can contribute to hci.there is a tendency to desexualize technology, despite the presence of sex and sexuality in a variety of interactions, including the use of the internet for viewing pornography, building online communities, and facilitating intimacy. by rendering these interactions sexless, we risk gaining only a marginal understanding of technology's role in day-to-day life.
tele-biographies: data collection techniques to capture the ways people interact with digital tv. this paper describes data collection techniques that capture the ways people use digital television. it reports preliminary findings and examples of the resulting conceptual designs.
non-visual information display using tactons. this paper describes a novel form of display using tactile output. tactons, or tactile icons, are structured tactile messages that can be used to communicate message to users non visually. a range of different parameters can be used to construct tactons, e.g.: frequency, amplitude, waveform and duration of a tactile pulse, plus body location. tactons have the potential to improve interaction in a range of different areas, particularly where the visual display is overloaded, limited in size or not available, such as interfaces for blind people or on mobile and wearable devices.
theory and method for experience centered design. there is currently much interest in notions of experience-centered design in human-computer interaction (hci). a great deal of the research and practice in this area is at the boundaries of arts, design and sciences. however, there has not been enough critical discussion of how these disciplines can work together. in this one-day workshop we will bring together practitioners and researchers to explore the state of the art in the theory and practice of experience-centered design.
no im please, : we're testing. this paper discusses the use of instant messaging (im) as a communication tool during usability studies - primarily between the interview and observation rooms. the benefits and challenges associated with providing an im link are discussed, based on feedback from a survey of study moderators and observers. observers were much more positive about the use of im than the moderators. a key concern to moderators was the potential distraction to themselves, participants and observers. in contrast, observers greatly welcomed the opportunity to ask questions and help deal with buggy prototypes. guidelines are outlined for the effective use of im within a usability context, and contexts outlined when an im link is most appropriate.
support for cooperatively controlled objects in multimedia applications. this paper presents a class of objects that facilitate building software for "close collaboration." a definition is given for "cooperatively controlled objects" and three example activities are described.
kinetic typography-based instant messaging. kinetic typography, text whose appearance changes over time, is emerging as a new form of expression due to its ability to add emotional content to text. we explored the potential for kinetic typography to improve the way people communicate over the internet using instant messaging (im). our kinetic instant messenger (kim) builds upon applications for rendering and editing kinetic typography effects and addresses several design issues that spring from integrating kinetic typography and im.
a contextual inquiry of expert programmers in an event-based programming environment. event-based programming has been studied little, yet recent work suggests that language paradigm can predict programming strategies and performance. a contextual inquiry of four expert programmers using the alice 3d programming environment was performed in order to discover how event-based programming strategies might be supported in programming environments. various programming, testing, and debugging breakdowns were extracted from observations and possible programming environment tools are suggested as aids to avoid these breakdowns. future analyses and studies are described.
the next revolution: vehicle user-interfaces and the global rider/driver experience. the driver/rider experience is a major development in mobile user-interface (ui) design worldwide, similar in scale to the first introduction of personal computers to the desktop. most automobile manufacturers seeking to develop smart cars have relatively little experience with advanced software-based uis and information visualization (iv). this panel introduces essential issues of vehicle ui design to the chi community and offers competing views about the most important issues affecting usability, safety, appeal, functionality, information, and entertainment.
imprints of place: creative expressions of the museum experience. personalization and social awareness, important aspects in the definition of a place, are traditionally overlooked in the design of technology for museums. we describe imprints, a system to enhance the role of visitor participation beyond information receiver to active creator of sense of place. overall response to the imprints system is explored through interviews and log analysis of use. despite some usability issues, response to the system was positive, and it was appropriated for both personalization and awareness of others. the results suggest an opportunity to introduce technology that plays with the dynamic between private expression and public presence in the traditional environment of the art museum.
designing to support communication on the move. we investigated what mobile workers do when they are mobile to achieve their communication goals, using contextual interviews and ethnographically inspired observations in a variety of settings. implications for the design of mobile technology were extracted from the raw data collected in the fieldwork using such novel design techniques as 'day in the life' vignettes, affinity diagrams, and consolidated artefact models from contextual design. our findings are being using to generate software prototypes for supporting mobile activities.
interfaces, autonomy, & interactions in automobile driving. issues surrounding human computer interaction apply to all domains where humans interact with a software or a hardware system through a computer controlled interface. it is important that an interface presents a consistent system that matches the operator's goals and understanding, and this importance grows when rapid decisions and actions are required to maintain a desired level of productivity and/or safety. driving is a domain where split second responses are the norm; this implies that interfaces which require high-level cognitive responses are often undesirable because such responses are often much too slow. in the design of driver support systems, safety is always the primary constraint that permeates all design decisions independent of whether the goal is to improve driving performance, enhance comfort, reduce fatigue, or free up attentional resources to better manage and enjoy telematics services. in the panel discussion at chi2004, a panel of experts from varied backgrounds is challenged to design joystick control for a passenger car in order to expose the chi community to the multi-facetted structure of issues that arise when technological and human constraints define the boundary of design possibilities.
an evaluation of the integrated use of a multimedia storytelling system within a psychotherapy intervention for adolescents. this paper describes a study currently being conducted with adolescents attending the child and adolescent mental health service (camhs) at the mater hospital dublin, ireland measuring the effectiveness of a therapeutic groupwork intervention for adolescents experiencing depression, anxiety and other mental health issues. the intervention is essentially a cognitive behavioural therapy (cbt) programme that uses an animated story building system in combination with a series of short movie vignettes to help clients develop their own coping skills, express their experiences creatively and increase their ability to communicate their emotions effectively.
fingerprint: supporting social awareness in a translucent sensor-mediated cue-based environment. we report on a pilot study that is part of an ongoing project which investigates social awareness support for project groups made of students who may choose to work at the university, at home or at part-time job offices. the study involved the design and early evaluation of a prototype which augments a cooperative application with various sensorial and computational cues about co-worker presence. the sensing devices were installed and annotated by the users themselves. based on this experience and inspired by "technomethodology", we suggest implications for design of awareness support and context-enabled devices.
crystal ball: predicting end-user experience with a digital media adapter. computers are moving out of the home office and into other areas of the home. the problem today is not whether the technology that enables this transition is available, but whether people can use the technology as it is presented today. unfortunately, for the average user, the initial experience of setting up and using some of the newest and most interesting digital home devices is challenging, at best, and impossible for many. this paper describes a unique research technique that has been used to create tools that predict the end-users' experience when setting up and using a variety of products (lind & michalak, 2001; lind & michalak, 2002). most recently, we applied this approach to a new category of products called "digital media adapters" (dmas). as with its predecessors, this tool not only allows the prediction of an end-users' experience but provides guidance on how to improve their experience.
webcard = email + news + www. this video shows webcard, a system that provides integrated and uniform access to email, news, and the web. webcard's user interface is based on folders, which can contain mail messages, news articles, and also web pages. the obvious use of folders is for organizing material, as is done in conventional mail and news readers using folders, and in web browsers using bookmarks or hotlists. in webcard, however, folders can contain an arbitrary mix of mail messages, news articles, and web pages. webcard also uses folders to present the mail messages, news articles, and web pages returned by commands such as "search" and "auto surf."
social interaction in 'there'. persistent online environments, such as multi-player games, exhibit a complex social organisation. these environments often feature large social groupings and elaborate cooperative behaviours. this paper discusses 'there', one such environment, focusing on how users interact online. resources such as overlapping chat and emotional gestures create a compelling social experience, although not one without its problems. we draw three lessons from there for the design of games and virtual environments: that text chat can be better integrated into the virtual environment, that gestures are valuable as communication topics as well as resources, and that social interactions can improve the social presence felt in virtual environments.
tactile crescendos and sforzandos: applying musical techniques to tactile icon design. tactile icons (tactons) are structured vibrotactile messages which can be used for non visual information display. information is encoded in tactons by manipulating vibrotactile parameters. this research investigates the possibilities of applying musical techniques to tactile icon design in order to define such parameters. tactile versions of musical dynamics were created by manipulating the amplitude of vibrations to create increasing, decreasing, and level stimuli and an experiment was carried out to test perception of these stimuli. identification rates of 92%-100% indicate that these tactile dynamics can be identified and distinguished from each other, and that tactile dynamics could be used in tacton design.
a grounded investigation of game immersion. the term immersion is widely used to describe games but it is not clear what immersion is or indeed if people are using the same word consistently. this paper describes work done to define immersion based on the experiences of gamers. grounded theory is used to construct a robust division of immersion into the three levels: engagement, engrossment and total immersion. this division alone suggests new lines for investigating immersion and transferring it into software domains other than games.
reflecting on health: a system for students to monitor diet and exercise. using an iterative design process, we designed and evaluated a system for college students to encourage the development and maintenance of healthy diet and exercise habits. the system has three components: a camera phone application to support photographic diet and exercise journaling, an automatic workout tracking application for exercise machines in the gym, and a visualization application to support users as they reflect on their diet and exercise activities.
feel who's talking: using tactons for mobile phone alerts. while the sense of touch is capable of processing complex stimuli, the vibration feedback used in mobile phones is generally very simple. using more complex vibrotactile messages would enable the communication of more information through phone alerts, however it has been suggested that phone vibration motors are not capable of presenting complex messages. this paper reports a study investigating the use of tactons (tactile icons), presented using a standard mobile phone vibration motor, to represent mobile phone alerts. the recognition rate of 72% achieved for tactons encoding two pieces of information is comparable to results achieved in a previous experiment with a high specification transducer, indicating that it is possible to communicate multi-dimensional information in mobile phone alerts. these results will help designers to understand the possibilities offered by standard phone vibration motors for communicating complex information.
distributed applets. this video shows several examples of distributed active web content, that is, applets that can communicate with other applets running on different machines.
explorations in an activity-centric collaboration environment. this demonstration presents a new hybrid collaboration technology that partakes of selected qualities of informal, ad hoc, easy-to-initiate collaborative tools, and more formal, structured, and disciplined collaborative applications. our approach focuses on the support of lightweight, informally structured, opportunistic activities featuring heterogeneous threads of shared objects with dynamic membership as well as blended synchronous and asynchronous collaboration. we will introduce the system, and then invite audience members to use it in several exercises.
a new perspective on "community" and its implications for computer-mediated communication systems. scholars have long argued about the nature of "community," and the growth of internet-based communication and "online communities" has intensified this debate. this paper argues that a new perspective on the concept "community" can shed light on the subject. ideas from cognitive science, particularly category theory, can help. i suggest that community can be viewed as a prototype-based category. prototype-based categories are defined not by simple rules of inclusion and exclusion, but instead by their prototypical members--a robin is a better example of a bird than an emu or a penguin. items in a category are better or worse examples of the category depending on their degree of similarity to the prototypical members. i will argue that these theoretical insights can help resolve debates about the nature of community, and also can help guide designers of computer-mediated communication (cmc) systems.
managing deviant behavior in online communities. wherever groups of people gather, norms for appropriate behavior emerge, and some people chose to violate those norms. what is an exercise of free speech to one person, to another is disruptive, harassing, racist, or worse. for groups that communicate online, a range of technical and social mechanisms are available to help create a climate conducive to meeting the group's stated mission. how do designers of online systems decide what kind of conduct is acceptable? how are these expectations communicated to members? how can designers help prevent and manage deviant behavior? what are the implications of corporate control of content for ideals of free expression? this panel brings together experts from media theory, computer-supported collaborative learning (cscl), computer-supported cooperative work (cscw), and online entertainment to explore current issues in this complex research area.
how to trust robots further than we can throw them. panelists from defense, entertainment, industry, transportation and energy sectors will discuss the challenges of human-robot interaction in terms of operator trust trust affects a broad range of mobile robot applications including everything from helpful robots such as automated wheelchairs and robot wedding photographers to robots used in critical environments such as urban search and rescue, countermine operations and bomb disposal. panelists will discuss experiments and case studies that highlight the importance of operator trust. each panelist provides a unique perspective on the role of trust in mobile robot applications and offers insight on how we can help build trust for a future generation of mobile robots. the panel will discuss cases where humans were too willing to place trust in robot systems and others where humans have been unwilling or unable to trust robot behavior. in each instance, panelists will point to current shortcomings (i.e., interfaces, communications, robot intelligence) and plans to address these limitations in the future.
meeteetse: social well-being through place attachment. this paper introduces meeteetse, a set of technologies designed to facilitate social well-being through place attachment. meeteetse builds a connection between individual homes and a local community center, a connection that is designed to encourage active involvement in community events and create a support network for those who might otherwise be isolated by the effects of old age. the design consists of several parts that work together to build this connection. a location-aware digital camera and a large public display are integrated into the community center to strengthen shared identity. a touch-screen scheduling device and a digital picture frame create a tangible community presence in seniors' homes. together, these components enhance social well-being and lower the barrier for participation in the community.
backseat gaming: expolaration of mobile properties for fun. this paper presents a prototype developed as part of the backseat gaming project. the aim of the project is to explore how to make use of moblie properties for developing compelling and fun game experiences. the prototype is developed for use in a highly mobile situation, that of a car passenger and is realized by the use of mobile devices and the users physical location during speed to merge the virtual content and surrounding road context into an augmented reality game.
annotating digital documents: anchoring, educational use, and notification. annotating is a very common activity. people often highlight and make notes while reading. increasingly documents exist primarily in digital form. supporting annotation of digital documents both for personal use and for asynchronous collaboration has many challenges.by building software prototypes and deploying them in laboratory and field studies, this work investigates three issues: robustly anchoring annotations on modified documents to meet user expectations, using annotations in an educational setting to enhance interaction outside of class, and providing appropriate notification mechanisms to support asynchronous collaboration around documents. although the primary focus of this research is digital document annotation many of the findings may generalize to other media types including images and video.
a comparison of synchronous remote and local usability studies for an expert interface. synchronous remote usability studies can be a convenient and cost-effective alternative to conventional local usability studies. although they are common in the field, there has been little research comparing synchronous remote usability studies with local studies. in our comparison of remote and local studies of an expert interface, the primary differences were in the participant's and facilitator's qualitative experience. the remote and local studies agreed closely (with no significant differences) in terms of the number of usability issues found, their type, and their severity. while our comparison focuses on an expert interface and more work is needed to understand remote studies in general, our experience suggests that evaluators of expert interfaces will have comparable success identifying usability issues with either remote or local studies.
'today' messages: lightweight group awareness via email. 'today' messages are short daily status emails sent by members of a project team to each other. their original purpose was to take the place of status updates at meetings. however, they had the unexpected additional effect of increasing group task awareness at very low cost. we present the results of a small study of 'today' messages and their effect on group dynamics.
designs for home life. in this special interest group (sig) we intend to consider the increasingly popular area of interactive systems design for the home. aiming to incorporate a wide range of perspectives, the sig's participants will map out the growing number of research and development programs in the area. particular emphasis will be given to how home life has been characterized in various programmatic visions and how the chi community might best capitalize on these characterizations. the importance of an understanding of home life to inform design and future directions in this area will also be reflected on. this sig is intended to appeal to a broad cross section of the chi community, ranging from practitioners and developers to computer and social scientists.
automatic generation of high coverage usability tests. software systems are often complex in the number of features that are available through the user interface and consequently, the number of interactions that can occur. such systems are prone to errors when interactions do not work as anticipated. this research introduces a combinatorial method for setting up task-based usability tests. the method bridges contributions from mathematics, design of experiments, software test, and algorithms for application to usability testing.
the design of a tangible interaction device to alleviate anxiety and pain in paediatric burns patients. this paper presents a case study on the design of a unique tangible media device to alleviate anxiety and pain in paediatric burns patients. the multidisciplinary interaction design approach used throughout the study is presented together with the hardware and content design solution. results of an initial study are presented which qualify the use of the device within a clinical trial. the paper concludes with a reflection on the process undertaken leading to suggestions for undertaking successful collaborative projects which span medical science, computer science and design disciplines.
children's and adults' multimodal interaction with 2d conversational agents. few systems combine both embodied conversational agents (ecas) and multimodal input. this research aims at modeling the behavior of adults and children during their multimodal interaction with ecas. a wizard-of-oz setup was used and users were video-recorded while interacting with 2d ecas in a game scenario with speech and pen as input modes. we found that frequent social cues and natural human-human syntax condition the verbal interaction of both groups with ecas. multimodality accounted for 21% of inputs: it was used for integrating conversational and social aspects (by speech) into task-oriented actions (by pen). we closely examined temporal and semantic integration of modalities: most of the time, speech and gesture overlapped and produced complementary or redundant messages; children also tended to produce concurrent multimodal inputs, as a way of doing several things at the same time. design implications of our results for multimodal bidirectional ecas and game systems are discussed.
analyzing usage of location based services. friendzone, a suit of mobile location-based community services has been launched. friendzone's social services include instant messenger and locator (im&l), location-based chat, and anonymous im, with supporting privacy management. we describe the findings of a 16 months usage survey of 40,000 users, most of them young adults.the results indicate that anonymous im is the most popular service, more than im&l, with lower use of location-based chat that was introduced last.
banner ads hinder visual search and are forgotten. banner ads persist on the internet in spite of evidence against their efficacy. many ads include animation in an attempt to increase their attentional capture. an experiment was conducted to examine how various banner ads affect the visual search of news headlines on the web, and whether participants could recall the ads they saw. the results both support and contradict the notion of "banner blindness," the idea that people ignore banner ads. participants could not recall the ads that they saw, but those ads did distract the users and significantly increased search times. the most surprising result is that recall was especially bad for animated banners. this paper examines issues of attentional capture in an applied domain and provides guidance for web designers.
access for all: hephaistos - a personal home assistant. in this paper, we describe a demonstrator which was developed in the course of the european project tide 1004: hephaistos (home environment private help assistant for elderly and disabled). the demonstrator constitutes a hand held personal home assistant capable to control a selected range of electronic home devices. its multimodal user interface is based on a coloured high resolution touch screen extended with speech input/output. the development process focused on taking into account requirements of elderly people and people with special needs. the usability of the personal assistant was evaluated in a series of user tests with subjects from this particular demographic groups.
hci and usability in russia. this paper presents the "bird's-eye-view" of the development and growth of hci and usability within academia and industry in russia. the paper also highlights the challenges facing russian hci and usability community.
the next step: from end-user programming to end-user software engineering. is it possible to bring the benefits of rigorous software engineering methodologies to end users? end users create software when they use spreadsheet systems, web authoring tools and graphical languages, when they write educational simulations, spreadsheets, and dynamic e-business web applications. unfortunately, however, errors are pervasive in end-user software, and the resulting impact is sometimes enormous. a growing number of researchers and developers are working on ways to make the software created by end users more reliable. this workshop brings together researchers who are addressing this topic with industry representatives who are deploying end-user programming applications, to facilitate sharing of real-world problems and solutions.
vaca: a tool for qualitative video analysis. in experimental research the job of analyzing data is an extremely slow and laborious process. in particular, video and audio data of human behavior are particularly difficult to analyze, as this type of information does not lend itself to automation. here we present vaca, an open source tool for qualitative video analysis. vaca presents video annotations on a timeline interface and integrates external sensor data to improve the rate at which analysis can be performed. a comparative study is run against traditional video analysis tools, and results are reported.
extending ubiquitous computing to vineyards. in this paper, we describe how an ethnographic approach led to novel interface and system designs for vineyard management and discuss the lessons learned from it.
clearpen: improving the legibility of handwriting. we describe the application of a pen model, and sub-pixel addressing (clearpen), to render handwriting on an lcd display. this technique is shown to improve the legibility of handwriting. clearpen can increase the viability of working with handwriting on a computer. this has direct significance to tabletpc applications such as note taking or annotating documents.
habilisdraw dt: a bimanual tool-based direct manipulation drawing environment. in this paper, we present a two-handed tool-based drawing environment based on the principles originally incorporated into the habilisdraw interactive drawing system. these principles include persistent tools that embody intuitive aspects of their physical counterparts and an approach to interface learnability that capitalizes on the user's inherent ability to use tools both separately and in conjunction with other tools. in addition to these principles, the diamondtouch variation of habilisdraw (habilisdraw dt) extends the physical-virtual tool correlation with bimanual input via the merl diamondtouch input device and a close adherence to the direct manipulation interaction model. this paper presents the habilisdraw interface, explores the benefits of a desktop metaphor that closely mimics the behavior of two-dimensional tools and objects in a drawing environment, and argues for the applicability of the system's fundamental principles for improving interface usability in the future.
human-computer interaction: introduction and overview. the objective of this special introductory seminar is to provide newcomers to human-computer interaction (hci) with an introduction and overview of the field. the material will begin with a brief history of the field, followed by presentation and discussion of how good application development methods pull on the interdisciplinary technologies of hci. the topics will include the psychology of human-computer interaction, psychologically-based design methods and tools, user interface media and tools, and introduction to user interface architecture.
tangible uis for media control: probes into the design space. in a student project over the summer of 2004 teams of computer science and product design students worked together to develop new forms of interfaces for media control in living room contexts. in this paper we describe the design process from collecting first ideas of design choices and iteratively evolving (low- fidelity) prototypes to fully functional products, partially even meeting mass production requirements. we discuss how the interdisciplinary collaboration influenced the creative process in such a way, that the solutions were more realistic than purely design- informed solutions and more inspired than purely technology- informed ones. we experienced that the combination of skills lead to a much more focused design process, which produced fully functional prototypes in a short time. the resulting designs include one interface installed in the room, two autonomous interaction objects which can be freely moved around, and a two- handed inter- face. while these are only small spotlights into a large design space, they nicely show the possible diversity. we also learned that fully functional and aesthetically pleasing prototypes can be developed with technologically relatively simple means.
interaction at lincoln laboratory in the 1960's: looking forward -- looking back. the activity centered around the tx-2 computer at lincoln laboratory in the 1960's laid the foundation for much of hci. through the use of archival film footage, and live presentations by some of the key protagonists, this panel is intended to contribute to a more general awareness of this work, its historical importance to hci, and its relevance to research today.
students at chi. the students at chi sig provides an open session where all students attending chi'97 can meet and discuss graduate student issues. the sig is intended for graduate students (beginning through senior), recent graduates, undergraduates, and friends.
providing elegant peripheral awareness. in a one-day workshop, we strive to build community in this emerging research area, specifically targeting interfaces that are designed to provide awareness in a peripheral and elegant manner. we focus on improving consensus of basic and fundamental issues and developing a structural framework--critical parameters, design themes, and evaluation procedures--for research on these types of user interfaces.
comparison of display methods in online help. this poster describes a study conducted by the human interface design department at fidelity investments systems company. the purpose of this study was to obtain performance and preference data about various methods of displaying data definitions in online help. the four methods studied were an alphabetical list of data elements with pop-up definitions, a window-ordered list with pop-up definitions, a screen shot of the window with pop-up definitions, and a table listing all data elements and their definitions. performance and preference data indicated that the alphabetical list was the best.
navigational blocks: tangible navigation of digital information. navigational blocks provide a tangible user interface for applications such as information kiosks. orientation, movement, and relative position of electronically and microprocessor augmented physical blocks support visitor querying, retrieving, understanding, navigation and exploration of an historical information database.
does spelling matter in instant messaging?: answers from measuring error correction frequency. although instant messaging (im) is widely perceived as a communication mode with relaxed spelling and grammar rules, three measures show that people still perceive errors and often correct them. in two usability studies with different tasks, participants on average corrected 89 and 95 percent of their typographical and grammatical errors that they identified. however, their self-correction rates were substantially lower and more variable when compared to all errors found by independent proofreaders. the results from the second measurement showed that participants were aware of their own errors. they judged their own error rate to be significantly higher than the other person's even when that was not true. using the third measure, correction rates in im were found to be lower than "normal" typing. the self-sensitivity to errors prompts further investigation of techniques for error detection and correction appropriate for im's rapid pace and relaxed linguistic register.
supporting notable information in office work. this paper reports a study examining how current electronic technology (e.g., pdas, e-mail, laptops, cellphones) and classic paper-based tools (e.g., post-its, notepads, scrap paper) are used to manage to-do lists, appointments, and other types of notable information. many of the users interviewed report that notes need to be temporary, viewable, mobile, postable, transferable, short, easy to create and destroy. paper-based tools are clearly preferred over electronic for managing notable information, and are used much more often. pdas are almost never used for notable information because they lack high-resolution screens, are bulky, and require too much time to enter new information. e-mail is the most used electronic tool and is commonly given dedicated screen space so that it was always visible. design recommendations for electronic office technology are presented.
instant messaging comprehension with non-keyboard composition. a comparison of the accuracy of comprehension of instant messaging (im) messages composed using a keyboard, handwriting recognition and speech recognition was performed. the participants in the study were shown text messages either containing no errors or having errors caused by typing, handwriting or speech recognition. they demonstrated their understanding of the messages by correcting the errors as they retyped the messages. the time to correct typographical errors was not significantly different from the time to type messages without errors. speech and handwriting recognition errors in the text took significantly longer to correct than typographical errors, and the results were significantly less accurate. interestingly, participants expressed slightly higher confidence in their understanding of messages containing speech recognition errors than handwriting, but the accuracy results from those two categories were not significantly different.
designing visual notification cues for mobile devices. mobile and wearable devices place enormous constraints on input and display form factors as well as on user attention. the key to designing micro-displays is knowing what sizes and configurations are viable for keeping users informed, what flexibility different micro-displays provide for different types of messages, and the learning requirements on the user. an experiment was performed to measure user learning and comprehension of increasing amounts of information on a simulated three-light visual display. users were required to learn five sets of messages of increasing information and complexity using the small display. results show that micro-displays can transmit detailed, information-rich messages up to 6.75 bits with minimal training (i.e., few trials and short time frames).
konekt: connecting the audience through judging at the olympic games. konekt is an interactive voting system that allows audience members that are physically present at the 2004 athens summer olympics to judge and score the athletes during the gymnastics and diving competitions. the goal of the system is to connect audience members to each other through judging to facilitate human-to-human interactions. a handheld device allows all members of the audience to score athletes performances without competing with the technical scorings done by the olympic judges. we explain how the team gained a holistic understanding of different issues that needed to be addressed by conducting interviews with experts in the sports, attending sporting events, and various other methods of immersing ourselves in the problem. two key findings included difficulty by audience members to notice nuances in the performance and how to seamlessly integrate this system for this particular olympics. we explain how we generated multiple iterations of possible solutions to this problem and then consolidated those concepts into our final solution. the final design is a screen based hand held device that has an animated character derived from the existing mascot for the athens olympics. it guides the user through the judging process and introduces them to a giant screen in the stadium that displays the results. when the device is carried throughout the stadium it allows people to connect to other people who had similar voting patterns.
evaluation of alternative presentation control techniques. although slideshow presentation applications, such as powerpoint™ have been popular for years, the techniques commercially available to control them rely on mouse and keyboard, which can be restrictive for the presenters. we evaluated two representative alternative designs of presentation control techniques - bare hand and laser pointer, through a wizard-of-oz user study. the result showed that bare hand was better than laser pointer and standard (mouse/keyboard) control in terms of acceptance and preference from both presenters and audience. we also proposed design directions based on user feedback.
remember when: development of an interactive reminiscence device. the use of technology has become increasingly widespread across the globe. findings from a feasibility study for the proposed device suggests that a population of 45-65 year olds are experienced using technology. therefore this experience will be carried through to old age facilitating the use of emerging technologies, such as a technology driven reminiscence device. furthermore a case study revealed that stimulation may aid communication amongst elderly people. a technology based reminiscence device is proposed as a means of facilitating communication creating bonds among elderly people. this reminiscence device in turn should alleviate loneliness by initiating conversation between elderly people. the proposed device is targeted at elderly people living in a nursing home, elderly people living alone and as a tool for care workers.
3book: a scalable 3d virtual book. this paper describes the 3book, a 3d interactive visualization of a codex book as a component for digital library and information-intensive applications. the 3book is able to represent books of almost unlimited length, allows users to read large format books, and has features to enhance reading and sensemaking.
real hci: what it takes to do hci engineering for disasters, driving, disruption, and distributed work. the current dependence of hci practice on feature-level design and defect-oriented usability evaluation is hindering it from addressing persistent societal problems such as disaster search and rescue, driver distraction and communication failures. hci has much to offer here in helping apply information technologies in effective, usable ways. but a fundamental issue in solving these persistent problems is ensuring that steady progress is made, and hci can play a role here too, by characterizing the task, helping define the metrics for progress, providing the interfaces on which progress hinges, and assessing the likely effect of design choices. these cases can benefit from taking an engineering approach and from using hci as a part of that activity. speakers will present cases that involve variations on this theme. their presentations will provide a basis for a lively discussion of hci's potential to make an impact on social problems in the future and the methods effective in realizing this potential.
learning about user-centered design: a multimedia case study tutorial. this multimedia tutrial provides a learning support system for continuing education in hci. the system includes an authentic case study of a design project, a guide to user-centred design concepts, active role-playing activities and links to the larger professional community.
the collaboratory: a virtual, collaborative learning environment. the collaboratory is the result of a future-oriented project in learning, in which the process of human-centered design was applied to the observed problems and opportunities in learning in high schools [1]. it is a shared virtual space which teaches and facilitates collaboration and project work. this video describes the collaboratory project and demonstrates the environment and interface as a product of the users and design process which helped develop it.
magazines and electronic information web channels - the reader's point of view. one magazine and one electronic information web channel are compared with respect to the reader's attitude. integrity, personal touch, character and ease of access are found to be the important factors in forming a strong relationship between the reader and the magazine, whether paper-based or electronic.
the neighborhood viewer: a paradigm for exploring image databases. the brain neighborhood viewer is a tool developed to help neuroscientists explore massive databases of brain images. the viewer implements an interface paradigm based on stacks of 2d images that are "yoked together" to provide a common coordinate system. when a user navigates in an image stack, all yoked stacks are updated to display the same location, which we call a brain neighborhood. experience with the neighborhood suggests that this interface is useful for neuroscience research.
maps: creating socio-technical environments in support of distributed cognition for people with cognitive impairments and their caregivers. individuals with cognitive disabilities are often unable to live independently due to their inability to perform daily tasks. by providing socio-technical environments to increase their independence, they can have richer, fuller lives. maps (memory aiding prompting system), provides a simple effective prompting system with an interface for caregivers designed to affect high rates of integration into daily life. maps contributes the base upon which a distributed support system can provide mobile, context-aware error detection and repair. the process of designing and evaluation of the maps system utilizes and extends hci frameworks, such as distributed cognition, situated action and end-user programming.
end user programming and context responsiveness in handheld prompting systems for persons with cognitive disabilities and caregivers. providing instructions via handheld prompters holds much promise for supporting independence for persons with cognitive disabilities. because users of these tools are paired - caregivers who make scripts and a person with cognitive disabilities who uses them - designing such a system presents unique meta-design problems. the problems of changing content and configuration on a handheld computer, as needs and abilities change of the users with cognitive disabilities, produce a critical need for end-user programming tools. this paper describes the design and testing of the maps (memory aiding prompting system) system, consisting of a handheld prompter and a multimedia editing tool for script creation, storage, and modification. the unique meta-design challenges of supporting end-user programming of context-responsive systems, and its broader implications, are presented.
institutionalizing hci: what do i-schools offer? i-schools (schools of information, of informatics, of information studies, and of information sciences) have emerged as a new academic home for university programs in hci. this panel will discuss the significance of i-schools in us universities, related international university-level education movements and trends, the role and possible trajectory of hci within i-schools, and how the sigchi community can play a role in contributing to this development.
scenarios in practice. this one-day workshop focuses on how scenarios are being used in industrial projects effectively and efficiently. the scope includes the overlapping concerns of: (1) deployment (2) method integration (3) craft and quality, and (4) tailing to various project contexts.
communication by neural control. people who are completely paralyzed are able to control a computer using technology which harnesses brain signals. this paper describes research in developing a system to allow such a person to communicate. we gathered and analyzed data on the communicative needs of our users, finding that style and content of interactions vary according to the role of the person with whom the user is communicating.
the role of the author in topical blogs. web logs, or blogs, challenge the notion of authorship. seemingly, rather than a model in which the author's writings are themselves a contribution, the blog author weaves a tapestry of links, quotations, and references amongst generated content. in this paper, i present a study of the role of the author plays in the construction of topical blogs, in particular focusing on how blog authors make decisions about what to post and how they judge the quality of posts. to this end, i analyzed the blogs and blogging habits of eight participants using a quantitative analysis tool that i developed, a diary study, and interviews with each participant. results suggest that authors of topical blogs often do not create new content but strive to, often follow journalistic conventions, use the content of their blogs as a reference tool for other work practices, and are connected as a community by a set of source documents. results also show that instant messaging is useful as an interview medium when questions center around online content.
digital graffiti: public annotation of multimedia content. our physical environment is increasingly filled with multimedia content on situated, community public displays. we are designing methods for people to post and acquire digital information to and from public digital displays, and to modify and annotate previously posted content to create publicly observable threads. we support in-the-moment and on-site "person-to-place-to-people-to-persons" content interaction, annotation, augmentation and publication. we draw design inspiration from field work observations of how people remove, modify and mark up paper postings. we present our initial designs in this arena, and some initial user reactions.
rubber shark as user interface. this paper presents a simple means to tag real world physical objects with digital information and functions. the system is low-cost and easily distributable to allow the general public outside the laboratory and academic environments to explore and experiment with physical-digital object couplings as an interface. the system is a tool to test out conceptual physical-digital mapping and metaphor and to prototype elements of tangible user interface. it can simply enhance the graphical user interface experience.
notes on a pattern language for interactive usability. this paper explores a way of applying the emerging idea of pattern based design to creation of usable interactive systems. it defines patterns based on traditional usability attributes. it describes examples of three pattern types: simple (one attribute), intrinsic (attribute combinations), and circumstantial (external constraints involved).
simplifying video editing with silver. digital video is becoming more ubiquitous. unfortunately, editing videos remains difficult for several reasons. it has dual tracks of audio and video and may require working at the smallest level of detail. silver is an authoring tool that uses video metadata to overcome these problems. it provides mulitiple views with different content types and at different levels of abstraction. this paper focuses on silver's smart selection and editing operations, which work at a high semantic level and handle different boundaries in audio and video. our research suggests several ways in which video editing tools can assist users in the composition and reuse of video.
smart laser-scanner for 3d human-machine interface. the problem of tracking hands and fingers on natural scenes has received much attention using passive acquisition vision systems and computationally intense image processing. we are currently studying a simple active tracking system using a laser diode, steering mirrors, and a single non-imaging detector, which is capable of acquiring three dimensional coordinates in real time without the need of any image processing at all. essentially, it is a smart rangefinder scanner that instead of continuously scanning over the full field of view restricts its scanning area, on the basis of a real-time analysis of the backscattered signal, to a very narrow window precisely the size of the target. the complexity of the whole setup is equivalent to that of a portable laser-based barcode reader, making the system compatible with wearable computers.
interacting with the big screen: pointers to ponder. in large screen projection environments, inexpensive wireless input devices can not match the performance of standard desktop interactive devices. we added buttons and a radio transmitter to a standard laser pointer to match the functionality of a standard mouse. user testing revealed that the device performed as well as a standard mouse and significantly better than standard presentation input devices. devices that used visible laser light performed significantly better than those with invisible near-infrared lasers.
older adults and web usability: is web experience the same as web expertise? level of web experience is often a factor for which researchers attempt to control while conducting experimental studies on web usability. it is typically measured by some means of self-assessment that often includes questions regarding long-term usage, frequency of use, and the types of activities performed while using the web. a common assumption is that web experience is the same as web expertise (high experience = high expertise). in our research studies primarily focused on web usability and older adults, we found that even when web experience is controlled, older adults still demonstrated less web expertise than younger adults. our research has supported the hypothesis that web expertise is significantly influenced by how users learned the web - or their cumulative time spent in collaborative learning environments (learning from and with others) - rather than just how long or how often they have used it. preliminary results in our labs demonstrate a positive correlation between opportunities for collaborative learning and web expertise, as well as a negative correlation between opportunities for collaborative learning and age. these results support the need to reassess how best to measure web expertise and how we might improve web interaction for older adults.
jadoo: a paper user interface for users unfamiliar with computers. in this paper we look at how socialization in a community can be used to help computer illiterate users start using computers and internet in a few minutes. we describe a prototype system, jadoo, which can be used by computer literates to create and distribute paper user interfaces. this paper interface can then be used by computer illiterates to access online information. we tested jadoo with our target audience, people living in rural india, and iterated the design to fit their needs.
balance pass: service design for a healthy college lifestyle. this paper describes the design of a service that provides nutritional feedback to female college freshmen. a variety of background research methods--food journals, competitive product analyses, and ethnographic interviews--led to the design of a service that integrates into existing university systems with little effort.
multimodal theater: extending low fidelity paper prototyping to multimodal applications. low-fidelity paper prototyping has proven to be a useful technique for designing graphical user interfaces [1]. wizard of oz prototyping for other input modalities, such as speech, also has a long history [2]. yet to surface are guidelines for low-fidelity prototyping of multimodal applications, those that use multiple and sometimes simultaneous combination of different input types. this paper describes our recent research in low fidelity, multimodal, paper prototyping and suggest guidelines to be used by future designers of multimodal applications.
weinteract: a pervasive audience participation system. greece has given the world two great gifts: the olympics, and democracy. this paper introduces "weinteract" (win) - a pervasive audience participation system that strives to connect these two great traditions. the "win" system introduces a method for capturing and quantifying the audience's natural performance - approval activities such as clapping and waving as a measure of their score to the athletes. through the use of the proposed technology, we predict that there will be a significant increase in audience engagement, and a greater appreciation of the olympic judging process.
designing systems that direct human action. in this paper we present a user-centered design process for active capture systems. these systems bring together techniques from human-human direction practice, multimedia signal processing, and human-computer interaction to form computational systems that automatically analyze and direct human action. the interdependence between the design of multimedia signal parsers and the user interaction script presents a unique challenge in the design process. we have developed an iterative user-centered design process for active capture systems that incorporates bodystorming, wizard-of-oz user studies, iterative parser design, and traditional user studies, based on our experience designing a portrait camera system that works with the user to record her name and take her picture. based on our experiences, we lay out a set of recommendations for future tools to support such a design process.
engaging the city: public interfaces as civic intermediary. this two-day workshop will advance discussion on the role of public interfaces in engaging citizens within the urban context. the aim is to determine how technology can help to develop cities that address the needs and reflect the desires of its inhabitants. the challenge for the hci community is to design more effective public interfaces that provide citizens with more active access, authorship, and agency. the workshop's field research component will involve visiting the city of portland as a case study for processing and refining these theoretical considerations.
audio-haptic feedback in mobile phones. a new breed of mobile phones has been designed to enable concurrent vibration and audio stimulation, or audio-haptics. this paper aims to share techniques for creating and optimizing audio-haptic effects to enhance the user interface.the authors present audio manipulation techniques specific to the multifunction transducer (mft) technology. in particular two techniques, the haptic inheritance and synthesis and matching methods are discussed. these two methods of haptic media generation allow simple creation of vibration content, and also allow for compatibility with non-haptic mobile devices.the authors present preliminary results of an evaluation of 42 participants comparing audio-based haptic user interface (ui) feedback with audio-only feedback. the results show that users were receptive to audio-haptic ui feedback. the results also suggest that audio-haptics seems to enhance the perception of audio quality.
user interface guidelines for enhancing usability of airline travel agency e-commerce web sites. specific user interface guidelines are described to increase the usability of airline travel e-commerce web sites. although previous guidelines address the usability issue from the perspective of the sale of tangible products that can be described and depicted, less attention has been given to the usability issues for the sale of services. service industries have different requirements for communicating with customers, specifically regarding their product offerings. this is prominent in the air travel industy, where web site usability is known to be poor. we examine how the current guidelines are inadequate for web sites providing air travel information. we propose specific guidelines for those sites that will enhance their usability.
applying user testing data to uem performance metrics. the lack of standard assessment criteria for reliably comparing usability evaluation methods (uems) is an important gap in hci knowledge. recently, metrics for assessing thoroughness, validity, and effectiveness of uems, based on user data, have been proposed to bridge this gap. this paper reports our findings of applying these proposed metrics in a study that compared heuristic evaluation (he) to he-plus (an extended version of he). our experiment showed better overlap among the he-plus evaluators than the he evaluators, demonstrating greater reliability of the method. when evaluation data, from testing the usability of the same website, was used in calculating the uem performance metrics, he-plus was found to be a superior method to he in all assessment criteria with a 17%, 39%, and 67% improvement in the aspects of thoroughness, validity, and effectiveness, respectively. the paper concludes with a discussion concerning the limitations of the effectiveness of the uem from which the real users' data was obtained.
in-visible: perceiving invisible urban information through ambient media. in this paper, we introduce in-visible, an urban system that enhances the contact between people and the subway. in-visible was conceived as a two-way system that brings users of the subway closer to the "exterior" urban environment and, through ambient media, provides walkers-by with knowledge about the subway, such as timings, motion, etc.the intention is to reflect upon how, using ambient media, structural urban elements can have an adequate impact on the urban space and make that meaningful for potential users.we propose one way of implementing this idea in the surroundings of one specific subway station and discuss ways in which the system may be generalized so as to serve other stations, trains and cities.
integrating isometric joysticks into mobile phones for text entry. we are investigating a new gestural text entry method for mobile phones that uses an isometric joystick and therefore consumes very little physical space. we have created a high-fidelity mobile phone prototype with two embedded isometric joysticks, one on the front for use with the thumb, and another on the back for use with the index finger. the joysticks can be used to enter text using a special version of the edgewrite text entry method. in our proposed studies, we would like to investigate the performance of using the joysticks as text input devices in stationary and mobile situations. with our prototype, the authors were able to write at ~12 wpm with the front joystick, and ~7 wpm with the back joystick. these numbers are sure to improve as further refinements are made.
context-aware collaborative filtering system: predicting the user's preferences in ubiquitous computing. in this paper i propose a context-aware collaborative filtering system that can predict a user's preference in different context situations based on past user-experiences. the system uses what other like-minded users have done in similar context to predict a user's preference towards an item in the current context.
facilitating mobile communication with multimodal access to email messages on a cell phone. this paper reports on a user trial (n=17) that compares the use of two systems for accessing email messages on a telephone handset. the first system uses graphic output and telephone keypad input, while the second system has both graphic and speech output, with keypad and speech as input. to our knowledge, this trial represents the first evaluation of a fully functioning multimodal system that uses natural language understanding on a phone, and was dependent on the 3g network currently available in australia. participants saw significantly greater value in the multimodal interaction, and rated their experience with the multimodal system significantly more positively than the unimodal system. they were also significantly more inclined to use and recommend the multimodal system over the current unimodal product offering. while we expected to see some mixed usage of modalities in the multimodal system, participants used speech predominantly, falling back to gui selection only after encountering multiple speech recognition failures in a row.
visualization in law enforcement. visualization techniques have proven to be invaluable in crime analysis. by interviewing and observing criminal intelligence officers (cio) and civilian crime analysts at the tucson police department (tpd), we identified two crime analysis tasks that can especially benefit from visualization: crime pattern recognition and criminal association discovery. as part of an extension to the coplink project [1], we have developed two systems to provide automatic visual assistance for these tasks. the spatial-temporal visualization (stv) system assists in identifying crime patterns by integrating a synchronized view of three visualization techniques: a gis view, a timeline view and a periodic pattern view. the criminal activities network (can) system extracts, visualizes and analyzes criminal relationships using spring-embedded and blockmodeling algorithms. we present the functionalities of the stv and can systems in the demonstration section.
games in asia project. the new technologies associated with computer games have more than an entertainment component; they also bring tremendous changes in human life at both the individual and societal level. since asia is the largest market for game consumption around the globe, this project seeks to understand the social, cultural, psychological, economic and educational implications of game playing in different asian regions. besides investigating the social impacts of gaming in respective countries, comparison among different countries is also of interest.
comslipper: an expressive design to support awareness and availability. in our increasingly decentralized world, demands to maintain relationships over long distances continue to increase. it is more and more difficult to maintain a sense of connection with others, to communicate with others in an emotionally rich way, and to know whether one is available for initiating a conversation in an appropriate context.this paper describes the design process and our solution to this challenge. the comslipper is a lightweight yet expressive sensible slipper that enhances the quality of computer-mediated relationships. the comslipper was developed using a human-centered design approach to better understand user behaviors and needs. the comslipper empowers the wearer to create a sense of connection to others. the wearer uses body gesture and tactile manipulation to feel and express emotions and availability to distant loved ones. the comslipper provides a natural and intimate way of communicating, and facilitates the development of intimate relationships.
sharecomp: sharing for companionship. we describe our process, findings, and resulting solution for the chi2005 student competition. the design problem was the issue of well-being of persons above the age of 65 years. loss of a companion can be a primary cause of depression, and decline of social well-being and health for the elderly, so the challenge is to design for "artificial" companionship to support the elderly. we met this challenge by employing extensive research in geriatric psychology, empirical and analytical human-computer interaction methods, interaction design techniques, and technologies currently available or in development. our solution is a wearable and stationary device that will allow the user to 1) record events through pictures and audio for sharing, 2) gather artifacts of their past such as photographs into a multimedia slideshow format for sharing with others, and 3) allow friends and family to be aware of the user's location for safety purposes.
using mental load for managing interruptions in physiologically attentive user interfaces. today's user is surrounded by mobile appliances that continuously disrupt activities through instant message, email and phone call notifications. in this paper, we present a system that regulates notifications by such devices dynamically on the basis of direct measures of the user's mental load. we discuss a prototype physiologically attentive user interface (paui) that measures mental load using heart rate variability (hrv) signals, and motor activity using electroencephalogram (eeg) analysis. the paui uses this information to distinguish between 4 attentional states of the user: at rest, moving, thinking and busy. we discuss an example paui application in the automated regulation of notifications in a mobile cell phone appliance.
behaviour, realism and immersion in games. immersion is recognised as an important element of good games. however, it is not always clear what is meant by immersion. earlier work has identified possible barriers to immersion including a lack of coherence between different aspects of the game. building on this work, we designed an experiment to examine people's expectations of how a game should behave and what would happen if that behaviour was deliberately made to be incoherent. the idea then is to understand immersion through seeing how immersion can be broken. the main manipulation was to alter the behaviour and realism of the graphics in the course of a simple game situation. surprisingly, results indicated that participants could be so immersed within a simple environment such that even significant changes in behaviour had little effect on the level of immersion. in some cases, the attempted disruptions went completely unnoticed. these results suggest that immersion within an application can overcome effects which are completely against user expectations.
human pacman: a wide area socio-physical interactive entertainment system in mixed reality. human pacman is a novel mixed reality interactive entertainment system that ventures to embed the natural physical world seamlessly with a fantasy virtual playground by capitalizing on infrastructure provided by wearable computer, mixed reality, and ubiquitous computing research. we have progressed from the old days of 2d arcade pacman on screens, with incremental development, to the popular 3d game home console pacman, and the recent mobile online pacman. finally with our research system human pacman, we have a physical role-playing computer fantasy together with real human-social and mobile-gaming that emphasizes on collaboration and competition between players in a wide outdoor area that allows natural wide-area human-physical movements. pacmen and ghosts are now human players in the real world experiencing computer graphics fantasy-reality by using the wearable computers on them. virtual cookies and actual tangible physical objects are incorporated into the game play to provide unique experiences of seamless transitions between real and virtual worlds. we believe human pacman is pioneering a new form of gaming that anchors on physicality, mobility, social interaction,and ubiquitous computing.
virtualcase: a tool for online collaborative learning. in this paper we describe the design and use of a web-based tool that enables teachers to create integrated online workspaces for collaborative case-based and problem-based learning. we discuss how this tool has been used in a variety of ways other than those originally intended by the designers. we discuss our classroom-based studies of two of these uses, and describe how these studies are influencing the redesign of the tool.
learners on the back-end: students contributing to web-based information systems. what happens when students, instead of merely drawing from online information resources, organize and populate such resources? in this paper we discuss how collaboratively creating web-based information resources might contribute to learning. we are currently studying two communities that are creating such resources using a prototype system we've designed.
sparks. in this paper we introduce sparks, an ambient social networking and communication facilitation interface. we developed the sparks system as a physical alternative to existing connectedness mediator systems. while several systems are under investigation, they are limited by their confinement to the traditional display. we address this issue, in part, by collocating the visualization and the user within the physical environment of the scenario. we describe the specific aspects of the system that capitalize on both foreground and peripheral attention to facilitate communication throughout a conversation. we discuss our ongoing research where architectural surfaces are used to provide interactive layers of information related to elements present in the space, and conclude with a discussion of the benefits of the system in combining the immediacy of the physical environment with the dynamic data handling characteristics of a digital system.
ebooks with indexes that reorganize conceptually. subject indexes were an important step forward for books because they enabled the comparison and correlations of information without extensive reading, re-reading and memorization. in this short paper, we focus on the user interaction and usage scenario of a new system called scentindex that enhances the subject index of an ebook by conceptually reorganizing it to suit particular information needs. users first enter information needs via keywords describing the concepts they are trying to retrieve and comprehend. scentindex then computes what index entries are conceptually related, and reorganizes and displays these index entries on a single page.
a spatially-aware tangible interface for computer-aided design. this paper presents a computer-aided design (cad) platform for designers to navigate and construct 3d model intuitively through tangible user interfaces (tuis). we suggest that 3d geometry can be inspected and modified in real-time through manipulating physical tokens on horizontal and vertical projected referential planes. a semi-transparent tablet as vertical display can be dynamically placed on the horizontal projected plane that triggers displaying spatially-contiguous 3d section images of the 3d cad model. our approach explores the spatially-aware tangible interface that couples the fragmented viewpoints with physical constraints to enhance the visual and spatial qualities of 3d representation to cad designers.
matching user and business goals. got constraints? we did. not only were we concerned with schedule and costs - the usual constraints - but also a company organization unused to cooperating among business units and a vendor "solution" that met business requirements but missed usability requirements. to cope on our portal redesign project, we matched the needs of the business and the needs of our key user group by innovating user-centered design practices and negotiating priorities with the project's sponsors. our user experience research took both the user experience and the company's needs into account, creating a set of needs and constraints that made it more likely to produce a successful site for both the users and the business. this case describes our process, the design evolution, and the result.
the digital set-top box as a virtual channel provider. this research is based on the realization that the desktop computing paradigm is not appropriate for television, because it is adapted to fundamentally different user aspirations and activities. instead, the virtual channel is a model that aids the organization and dynamic presentation of digital television programming from a combination of live broadcasts, prerecorded content and internet resources at each set-top box. the goal is to design the respective framework of user interface patterns that consider the affective nature of television usability and facilitate the diversity of viewing situations.
reality instant messaging: injecting a dose of reality into online chat. online chat technologies such as instant messaging and sms have become extremely popular. online chat environments, however, are missing a key ingredient that we take for granted in physical world chat - reality. when we socialize in the physical world we are surrounded by colorful and interesting events, e.g. a sporting event, a music concert, or an interesting drama on television. these events become conversational devices that play a crucial role in driving and facilitating social interaction. the reality instant messaging project injects these reality events back into online chat. in this way we enhance the reality streams by tying them to a social context, and at the same time we enhance the social environment by giving people something to talk about.
designing sound canvas: the role of expectation and discrimination. in this paper, expectation and discrimination are identified as two important constructs to be considered in ecological sound design to achieve a sense of presence in virtual enviroments. research to investigate the extent of this is described and the results obtained are discussed. future avenues for research, on the basis of these results, are indicated.
topic spotting common sense translation assistant. our translation assistant applies common sense logic to the problem of translating speech in real time from one language to another. using speech recognition combined with a software translator to do word-by-word translation is not feasible because speech recognition is notorious for poor results. word-by-word translation requires grammatically correct input to translate accurately. therefore, translation of speech that is potentially already fraught with errors is not expected to be good. our translation assistant works around these problems by using the context of the conversation as a basis for translation. it takes the location and the speaker as input to establish the circumstances. then it uses a common sense knowledge network to do topic-spotting using key words from the conversation. it only translates the most likely topics of conversation into the target language. this system does not require perfect speech recognition, yet enables end-users to have a sense of the conversation.
lover's cups: drinking interfaces as new communication channels. this paper shows how computer interfaces can enhance common activities and use them as communication method between people. in this paper, the act of drinking is used as an input of remote communication with the support of computer interfaces. we present lover's cups which enable people to share the time of drinking with someone they care about in different places. using a wireless connection, an otherwise ordinary pair of cups becomes a communication device, amplifying the social aspect of drinking behavior.
a user-centered approach to designing home network interfaces. this case study describes our approach to enhancing the way family members may interact with each other - and their homes - in the near future. samsung electronics and american institutes for research worked together to show how the user-centered design of network technology in the home could best enhance a family's ability to com-municate, play, and live harmoniously. we conducted user research in south korea and in the u.s., held fast-paced collaborative design sessions, and created interaction design guidelines to inform the development of an innovative line of home networked products. the final user interface was prototyped on samsung's home network control pda and showcased at the 2002 consumer electronics show.
the affective remixer: personalized music arranging. this paper describes a real-time music-arranging system that reacts to immediate affective cues from a listener. data was collected on the potential of certain musical dimensions to elicit change in a listener's affective state using sound files created explicitly for the experiment through composition/production, segmentation, and re-assembly of music along these dimensions. based on listener data, a probabilistic state transition model was developed to infer the listener's current affective state. a second model was made that would select music segments and re-arrange ('re-mix') them to induce a target affective state. we propose that this approach provides a new perspective for characterizing musical preference.
monitoring and managing presence in incoming and outgoing communication. the increase in channels and formats of personal communication such as email, instant messaging, and mobile phones, has generated new problems both with selecting the appropriate method to contact someone and communicating a preference for incoming communication. some applications, such as instant messaging have partially addressed this problem with status and away messages, but this approach offers limited communication options and only works for this communication channel. following a user-centered design approach, we explored the needs of users to manage their communication channels. using diaries, observations, and directed story-telling interviews we generated a set of observed needs. we then generated concept scenarios that capture these needs and performed a concept validation with a focus group looking for an overlap between our observed needs and the focus groups perceived needs. this paper documents our findings and offers implications for designers addressing these communication needs.
tangibly simple, architecturally complex: evaluating a tangible presentation aid. in this paper, we describe an evaluation of the palette, a presentation tool that was reported at chi '99. the palette allows presenters to quickly access digital presentations using physical cards that have unique barcodes printed on them. the palette has been in use in our lab for over three years, and has been released as a product in japan. our evaluation consists of an analysis of usage logs, an expert walkthrough review, and observations and interviews with users, non-users and the system administrator. the findings reveal benefits and drawbacks of the technology, and offers design ideas for further work on tangible tools of this kind.
café life in the digital age: augmenting information flow in a café-work-entertainment space. in this report we detail our experience of designing and installing a large-screen public, interactive community board, the eyecanvas, in a neighbourhood café and art gallery in san francisco. features of the community board include the ability to display content related to the café, including menus, nightly events and artists' work; the possibility of signing up for the cafe's email newsletter; and a touch-screen, "finger scribble" application that allows comments to be left. we describe the café, the eyecanvas interactive display, the contents that are posted to the display comment on the adoption, use and impact of the eyecanvas display.
entertainment is a human factor: game design and hci. every year, hundreds of thousands of people spend money from their own discretionary entertainment budgets just for the opportunity to experience the user interfaces of software applications sold as games. much of this experience involves difficult problem solving as well as tactical and strategic reasoning and performance, that often exceeds the demands of typical tasks at work. yet, games are fun and work often is not. why?
an empirical study of typing rates on mini-qwerty keyboards. we present a longitudinal study of mini-qwerty keyboard use, examining the learning rates of novice mini-qwerty users. the study consists of 20 twenty-minute typing sessions using two different-sized keyboard models. subjects average over 31 words per minute (wpm) for the first session and increase to an average of 60 wpm by the twentieth. individual subjects also exceed the upper bound of 60.74 wpm suggested by mackenzie and soukoreff's model of two-thumb text entry [5]. we discuss our results in the context of this model.
an educational digital library for human-centered computing. digital libraries have great potential to improve the educational experience. as a result, there are a wide variety of such repositories, especially those that focus specifically on education. but relatively few focus on topics as specific as human-computer interaction (hci) or human-centered computing (hcc). in addition, support for browsing behavior, with a few exceptions, is both weak and not suitable for user needs. this paper presents our work to create a repository of educational materials for a relatively narrowly-targeted field (hcc/hci), including our requirements gathering methods and results. finally, we discuss the hcc education digital library (hcc edl) as a platform for investigating broader digital library research questions, such as exploring alternative designs for content browsing mechanisms.
from quality in use to value in the world. this paper argues that a focus on quality in use limits the potential of hci. it summarizes how novel approaches such as grounded design can let us go beyond usability to reveal the fit between designs and expected contexts of use. this however is still not enough. it cannot resolve dilemmas about what is and is not a usability problem, or when fit is or is not essential. such dilemmas can only be resolved by an understanding of the value that artifacts aim to deliver in the world. hci must move beyond contextual description to prescriptive approaches to value in the world.
a development framework for value-centred design. hci's focus has shifted from the system, via the user, to the context of use. all are necessary but not sufficient for effective interactive systems design, which requires a 'fourth' value-centred focus. system-, user- and context-centred hci must be co?ordinated within a value?centred framework with four main processes: opportunity identification, design, evaluation and iteration. the latter two are separate, since iteration requires skills and knowledge beyond those typically available to evaluators. value-centred development adds new activities and artifacts to existing development methodologies. opportunity identification has the goal of stating the intended value for a digital product or service. value delivery scenarios refocus design on value in the world, as does value impact analysis for evaluation. the co?ordination of existing and new hci activities within a value-centred framework is outlined using examples from an ongoing design project.
reconditioned merchandise: extended structured report formats in usability inspection. structured problem report formats have been key to improving the assessment of usability methods. once extended to record analysts' rationales, they not only reveal analyst behaviour but also change it. we report on two versions of an extended structured report format for usability problems, briefly noting their impact on analyst behaviour, but more extensively presenting insights into decision making during usability inspection, thus validating and refining a model of evaluation performance.
a closed-loop tactor frequency control system for vibrotactile feedback. in this paper, we address the problem of maintaining a precise frequency in vibrating motors for use as vibrotactile cueing devices. our solution utilizes a piezoelectric film sensor that measures the motor frequency and uses a feedback-loop circuit to dynamically adjust the motor power to maintain the target frequency. we confirmed the accuracy of the film with a laser sensor and tested the ability of the feedback system to match a target frequency by changing the physical load placed on the motor. a user study showed that subjects perceived a difference in vibration intensity under loaded conditions with and without our compensation system, indicating the usefulness of such a feedback system on influencing perception. the results can help designers create better interfaces when vibrotactile cues are employed.
designing interactive life story multimedia for a family affected by alzheimer's disease: a case study. in this paper we present a design project involving primary end users who have declining cognitive abilities such as memory, communication, and problem solving. we are designing interactive multimedia with personalized life stories for individuals with alzheimer's disease. we conducted a case study to discover and address the design challenges for this project. a particular challenge is a limited ability to communicate with the primary end users. in this paper, we present design methods that take this challenge into consideration. our goal is to contribute insight into designing for users with cognitive disabilities, and to present methodologies that are useful for designers who have a limited ability to interact or communicate with end users.
improving interface designs to help users choose better passwords. conventional wisdom seems to have concluded that traditional passwords are inherently insecure. the argument is usually that users choose bad passwords and cannot be expected to remember strong passwords. we feel that these conclusions are premature and that this argument is flawed. at present most password selection mechanisms are not designed according to basic hci principles and we believe that this is highly responsible for the above conclusions. our current research is reexamining the problem of password selection and memorability through the exploration of password selection mechanisms with novel interface designs. the goal of this research is develop both principles and designs that help users to choose passwords that are both memorable and secure.
impact of progress feedback on task completion: first impressions matter. designers routinely provide feedback about task progress in order to persuade users not to abort the task (break off). however little is known about the effectiveness of such "progress indicators." two experiments are presented that evaluate progress indicators in web surveys. in the first, progress is displayed at different speeds. when the early feedback is slow, break-off rates are higher and users' subjective experience more negative than when early feedback is fast. in the second experiment, intermittent presentation seems to minimize the costs while preserving the benefits of feedback. overall, progress indicators can increase completion rates. however, not using them should be as deliberate a decision as using them.
evaluating an ambient display for the home. we present our experiences with evaluating an ambient display for the home using two different evaluation techniques: the recently proposed 'heuristic evaluation of ambient displays' and an in situ, 3-week long, wizard of oz evaluation. we compare the list of usability violations found in the heuristic evaluation to the set of problems that were discovered in the in situ evaluation. overall, the 'heuristic evaluation of ambient displays' was effective - 75% of known usability problems were found by eight evaluators (39-55% were found by 3-5 evaluators). however, the most severe usability problem found in the in situ evaluation was not identified in the heuristic evaluation. because the problem directly violated one of the heuristics, we believe that the problem is not with the heuristics, but rather that evaluators have minimal experience with ambient displays for the home.
board-based collaboration in cross-cultural pairs. this work in progress reports a study of cross-cultural collaboration mediated by board-based collaborative systems. american-chinese and american-american pairs performed collaborative design tasks either face-to-face or remotely. survey data, video recording, and design products were collected to examine the impact of culture (american-american vs. american-chinese), medium (face-to-face vs. remote), and system (mimiotm vs. smart boardtm) on the process and outcomes of collaboration. results from the survey showed significant effects of these variables on several reliable measures of common ground, cognitive consensus building, perceived performance, and satisfaction. the effects on perceived performance were robust. american-chinese pairs reported a significantly lower level of consensus when using a system that supports uni-directional (mimio™) rather than bi-directional interaction on the board.
from the flashing 12: 00 to a usable machine: applying ubicomp to the vcr. the hype of intelligent appliances and "smart homes" has so far failed to produce consumer electronics technology of mass appeal. it is our contention that common frustration with overly complex user interfaces has been the foremost obstacle preventing society from reaping the benefits promised by such technology. in order to replace the remote controls and command consoles that litter both our work and home environments, we suggest that existing technologies can be combined to enable more appropriate human-computer interaction, and thus, produce truly usable machines.
experiences from the design of a ubiquitous computing system for the blind. this paper presents the user interface experiences we had while developing an assistive system for the blind and visually impaired based on ubiquitous computing technology, the chatty environment. after introducing the system, it describes several issues encountered during user interface design and the chosen solutions. it then shortly presents the results of a conducted user survey.
olympic voting system proposal. in an effort to address the contentious issue of judged olympic events, the olympic committee has proposed a pilot audience participation system to score the gymnastics and diving competitions in the upcoming 2004 athens summer games. the system would allow the spectators who are physically present at the event to cast their vote in real time. the spectator vote will have no effect on an athlete's official score and will be purely for entertainment purposes. enabling audience members to voice their opinions electronically creates an emotionally exciting new form of spectator involvement within the olympics. our system relies on the principle of judging the judges, allowing spectators to agree or disagree with a score given to an athlete by the olympic panel of judges. the spectator participates in the unique experience of being able to voice their opinion on a larger scale. after the event, the spectator has a keepsake that they can treasure for years after the athens games.
a logic block enabling logic configuration by non-experts in sensor networks. recent years have seen the evolution of networks of tiny low power computing blocks, known as sensor networks. in one class of sensor networks, a non-expert user, who has little or no experience with electronics or programming, selects, connects and/or configures one or more blocks such that the blocks compute a particular boolean logic function of sensor values. we describe a series of experiments showing that non-expert users have much difficulty with a block based on boolean logic truth tables, and that a logic block having a sentence-like structure with some configurable switches yields a better success rate. we also show that a particular use of color with a truth table improves results over a traditional truth table.
incorporating physical co-presence at events into digital social networking. as mobile devices become location-aware, it will become possible to know when people are physically co-located and to incorporate this information into social software. is this valuable? a prototype social networking system based on physical co-presence was created and tested wizard-of-oz-style at four different physical social events by providing event attendees a digital link back to others at the event. usage of the system was higher than expected, suggesting a meaningful role for incorporating shared physical events into social networking software. usage and questionnaire analyses suggest some guidelines for design of such systems.
mobile social software: realizing potential, managing risks. given recent hardware, platform development, and internet connectivity gains, mobile devices are quickly becoming key outlets for social software. bringing social software into the physical social world raises a number of critical research questions, including issues of changes to the ways people socialize, the potentially sweeping impact of location services, how physical world context should be captured and incorporated, and a host of privacy concerns. this workshop seeks to address these and other key issues around the proliferation of social software on mobile devices. additionally, the workshop focuses on research tools and approaches for studying these questions, projected future directions for social software on mobile devices, and the role of related technologies, such as hardware and communication protocols.
gaze- vs. hand-based pointing in virtual environments. this paper contributes to the nascent body of literature on pointing performance in virtual environments (ves), comparing gaze- and hand-based pointing. contrary to previous findings, preliminary results indicate that gaze-based pointing is slower than hand-based pointing for distant objects.
an animated direct-manipulation interface to digital library services. the digital library integrated task environment (dlite) is a novel user interface concept for distributed document collections and services. it is an interaction prototype, not a polished graphical user interface, and is a front end to an evolving variety of distributed document services. dlite is part of the stanford university digital libraries research project. this videotape explains the principles of the dlite design and shows the current implementation in action.
kids as data: using tangible interaction in a science exhibit. this paper describes the design and implementation of a science exhibit aimed at giving children an understanding of the different factors that can affect the speed of a computer. the exhibit uses tangible interaction engaging visitors in a way that would not be possible using standard interaction techniques such as a keyboard and mouse. an informal evaluation of the initial prototype has indicated that the exhibit is successful at informing the users of the concepts being presented.
two-handed navigation in a haptic virtual environment. this paper describes the initial results from a study looking at a two-handed interaction paradigm for tactile navigation for blind and visually impaired users. participants were set the task of navigating a virtual maze environment using their dominant hand to move the cursor, while receiving contextual information in the form of tactile cues presented to their non-dominant hand. results suggest that most participants were comfortable with the two-handed style of interaction even with little training. two sets of contextual cues were examined with information presented through static patterns or tactile flow of raised pins. the initial results of this study suggest that while both sets of cues were usable, participants performed significantly better and faster with the static cues.
gait phase effects in mobile interaction. one problem evaluating mobile and wearable devices is that they are used in mobile settings, making it hard to collect usability data. we present a study of tap-based selection of on-screen targets whilst walking and sitting, using a pocketpc instrumented with an accelerometer to collect information about user activity at the time of each tap. from these data the user's gait can be derived, and this is then used to investigate preferred tapping behaviour relative to gait phase, and associated tap accuracy. results showed that users were more accurate sitting than walking. when walking there were phase regions with significantly increased tap likelihood, and these regions had significantly lower error rates, and lower error variability. this work represents an example of accelerometer-instrumented mobile usability analysis, and the results give a quantitative understanding of the detailed interactions taking place when on the move, allowing us to develop better mobile interfaces.
interface design for metadata creation. the rapid growth of the web has increased the importance of decentralized metadata creation. resource authors must create their own metadata to enable enhanced information seeking and retrieval, and they need effective interfaces to support their work. this paper reports a baseline study of author interactions with a metadata system and draws implications for the design of future interfaces.
methods for assessing web design through the internet. web design guidelines are often derived from best practices, conventional wisdom, or small-scale usability studies conducted in labs. we contend that if web design guidelines are to inform the design of web sites serving varied audiences with varied needs, the guidelines must be derived from empirical research that assesses users in their native environments as they interact with real web sites. while we believe that the delivery of a remote web-based experiment has many potential benefits, we acknowledge that it can be difficult to exercise experimental control so as to acquire reliable data, capture user behavior unobtrusively, extract meaningful information from server logs, and collect valid survey data. therefore, we report on how we addressed some of the challenges of conducting remote empirical studies of the effect of navigational cues on web browsing behavior.
advanced technology for streamlining the creation of eportfolio resources and dynamically-indexing digital library assets: a case study from the digital chemistry project. the goal of the digital chemistry project at uc berkeley is to create a model for how technology can be used to (a) introduce interactivity into large lecture classes, (b) offer customized, web-based learning materials to students outside of the classroom, and (c) provide immediate feedback on students' understanding of targeted instructional concepts. two products, prism and lotis, and their interrelated design processes are described in this paper. prism (presentation and interaction with streaming media) automates the creation of online learning materials by integrating streaming digital video, wireless concept testing, an annotation system, and face-to-face peer interaction. lotis (the learning object tagging and information system) catalogues and packages instructional resources using a combination of intelligent agents and customized metadata templates. the result is a model for dynamic content creation that lays the foundation for design improvements based on students' access to and interaction with instructional materials.
large display research overview. as large displays become more affordable, researchers are investigating their effects on productivity, and techniques for making the large display user experience more effective. recent work has demonstrated significant productivity benefits, but has also identified numerous usability issues with current software design not scaling well. studies show that larger displays enable users to create and manage many more windows, as well as to engage in more complex multitasking behavior. in this overview, various usability issues, including problems around accessing windows and icons at a distance, window management, and task management, will be discussedseveral novel interaction techniques that address these issues and make users more productive across multiple sizes of displays will be explored.
evaluating technology for coordinating communication. the goal of this work is two-fold: (1) propose a model of communication initiation and response, and (2) evaluate the utility of a set of technology interventions based on that model for coordinating communication. the contribution to the field of hci will be useful recommendations for the design of electronic communication systems.
administrative assistants as interruption mediators. when designing automated systems that make decisions about when to allow or deny interruptions, the methods of professional interruption mediators are an important source of information. administrative assistants are, by the nature of their jobs, expert interruption mediators. they make decisions every day about whether to allow interruptions to the person they support. we have conducted a series of interviews with administrative assistants whose ability has been publicly recognized. based on their responses, we present a production-rule model of the decision process they use when deciding whether to deliver interruptions to the person they support.
coordinating communication: awareness displays and interruption. in this paper, we describe a laboratory experiment to determine whether peripheral awareness information about a remote collaborator's workload aids in timing interruptive communication. our results indicate that a display with an abstract representation of a collaborator's workload is best in that it leads to better timing of interruptions without overwhelming the interrupter.
marked for deletion: an analysis of email data. what characteristics of an email message make it more likely to be discarded? statistical analyses of a set of deleted and non-deleted messages revealed several factors that were important in predicting the fate of a message. after controlling for the owner of the particular message, four factors turned out to be most important: history of communication with the sender (messages sent to and messages received from), intra-organizational vs. external sender, and size of the recipient group.
timezoom: a flexible detail and context timeline. in this paper we present timezoom, an interactive timeline widget to be combined with a tabular display of data in calendar, e-mail, project planning, or other applications. different time levels are vertically stacked and can be smoothly zoomed, permitting arbitrary granularity of time units. in addition, single or multiple focus regions with various levels of detail can be defined to allow the display and comparison of time-dependent data, while preserving the overall context.
why use memo for all?: restructuring mobile applications to support informal note taking. informal note taking is an essential activity in personal information management (pim). most mobile devices support this via a suite of applications, employing both highly structured (e.g., calendar, task list, contacts) and loosely structured (e.g., memos) data formats. contextual interviews and artifact inspections with expert pim-on-pda (personal digital assistant) users explored task-to-application mapping. structured tools were routinely avoided for informal note taking in favor of unstructured ones, even though this made managing the information more difficult. improved support lies somewhere in between, suggesting the design of an integrated architecture, which links data across all pim tools and provides a persistent, universal organizational system.
system for audience participation in event scoring at the 2004 olympic games. in this paper we describe a system for audience participation in gymnastics and diving events scoring at the 2004 olympics in athens, greece. the proposed system has six primary design goals: ease-of-use, scalability, low cost, scoring accuracy, portability and resistance to tampering. the system provides a simple and portable system that can be used for any sporting event where judge scores are reviewed by an audience. the supporting database design provides for statistical analysis and portability as well by providing a generalized database structure that can be easily adapted to any event as necessary. by using off-the-shelf technologies and open-source software, the solution provides for simple implementation, inexpensive hardware requirements, and easy software development.
demonstrations and guided tours of virtual worlds on the internet. multi-user virtual worlds are proliferating on the internet. these are two and three dimensional graphical environments inhabited by users represented as digital actors called "avatars". through this medium, a wide variety of internet users are participating in a large scale social experiment and collaborating on a variety of projects. the inhabited virtual world is an exciting new medium for hci professionals including interaction and graphic designers, and educators and researchers focused on distance learning and teleworking. it also appeals to children and ordinary users of the internet as a vast new digital playground and a venue for personal expression. this demonstration will introduce participants to a variety of inhabited virtual worlds and give them hands-on experience in collaboratively building and interacting with other users in the worlds.
interacting and designing in virtual worlds on the internet. multi-user virtual worlds are proliferating on the internet. these are two and three dimensional graphical environments inhabited by users represented as digital actors called "avatars". through this medium, a wide variety of internet users are participating in a large scale social experiment and collaborating on a variety of projects. the inhabited virtual world is an exciting new medium for hci professionals including interaction and graphic designers, and educators and researchers focused on distance learning and teleworking. it also appeals to children and ordinary users of the internet as a vast new digital playground and a venue for personal expression. this tutorial will introduce participants to a variety of inhabited virtual worlds and give them hands-on experience in collaboratively building and interacting with other users in the worlds.
mitap for real users, real data, real problems. the mitap system was developed as an experimental prototype using human language technologies for monitoring disease outbreaks. the system provides timely, multi-lingual, global information access to analysts, medical experts and individuals involved in humanitarian assistance. thousands of articles from electronic information sources spanning multiple languages are automatically captured, translated, tagged, summarized, and presented to users in a variety of ways. real users access mitap daily to solve real problems. the successful adoption of mitap is attributed to its user-focused design that accommodates the imperfect component technologies and allows users to interact with the system in familiar ways. we will discuss the problem, design process, and implementation from the perspective of services provided and how these services support system capabilities that satisfy user requirements.
pollen: promoting the exchange of meaningful objects. one of the most trying aspects of growing old is the loss of loved ones. older people often experience depression as a result of this reality. without regular contact from friends and family to amend this loneliness, a gap may exist in the individual's social welfare.through a unique combination of industrial design and interaction design methods, we have formed a process that allows us to explore the contextual background of a problem as well as a physical product solution. by using this process, we were able to create pollen, an affordable product that provides companionship through the exchange of meaningful artifacts. this paper describes both the process taken to create this unique product as well as the product itself.
managers' email: beyond tasks and to-dos. in this paper, we describe preliminary findings that indicate that managers and non-mangers think about their email differently. we asked three research managers and three research non-managers to sort about 250 of their own email messages into categories that "would help them to manage their work." our analyses indicate that managers create more categories and a more differentiated category structure than non-managers. our data also suggest that managers create "relationship-oriented" categories more often than non-managers. these results are relevant to research on "email overload" that has highlighted the use of email for activities beyond communication. in particular, our findings suggest that too strong a focus on task management may be incomplete, and that a user's organizational role has an impact on their conceptualization and likely use of email.
effects of fisheye on visualizing connections between nodes. it is important for analysts to realize the connection between two distant nodes in a graph, which is not readily supported by existing space-filling techniques. we developed an experimental prototype, focustree, which displays graphs in two view modes: fisheye or tree. in fisheye view, selected nodes and the nodes connecting them remained full-sized while the other nodes were reduced in size. in tree view, all nodes remained the same size, regardless of selection state. we conducted a study to compare the speed of participants using the fisheye view to the tree view when determining the number of links between two nodes. there were two states for the degree of separation in the tasks: simple (four links) and complex (eight links). results showed a main effect for view type with fisheye view being significantly faster than tree view for determining the connection between two nodes.
the book as user interface: lowering the entry cost to email for elders. substantial stumbling blocks confront computer-illiterate elders. we introduce a novel user interface technology to lower these start up costs: the book as user interface, or bui. book pages contain both step-by-step instructions and tangible controls, turning a complex interaction into a walk-up-and-use scenario. the system expands support past the technical artifact to a go-to relationship. eldermail users designate an internet-savvy trusted friend or relative to help with complex tasks. in this paper, we conduct a preliminary evaluation of a bui-based email system, and report our findings. while research has augmented paper artifacts to provide alternate access into the digital world, we find that elders use the bui as a way to circumvent the digital world.
household indicators: design to inform and engage citizens. urban simulation systems can be a powerful tool for helping to understand the complex, long-term consequences of urban planning decisions. simulation results are summarized and reported using indicators, aggregate measures such as population density or total minutes of vehicle delay. to citizens, these indicators may seem abstract and unfamiliar. this extended abstract presents design work in progress on household indicators, a new form of indicator designed especially for citizens. accessed through a web-based interface, household indicators are intended to inform citizens by relating simulation results to citizens' life experiences, and to engage citizens by addressing the question, "how will this decision affect me?.
decreasing online 'bad' behavior. 'bad' behavior is a serious problem in many online social situations, such as chat rooms. one potential reason is that social norms for 'proper' interpersonal behavior are not invoked in these situations as they are in face-to-face interactions. we describe a game we developed to explore good and bad behavior in computer-mediated situations. we found that increasing the 'social' nature of the interaction through voice communication between game partners decreased aversive behavior, but having profile information about the other person had little impact.
mmm2: mobile media metadata for media sharing. cameraphones are rapidly becoming a global platform for everyday digital imaging especially for networked sharing of media from mobile devices. however, their constrained user interfaces and the current network and application infrastructure encumber the basic tasks of transferring, finding, and sharing captured media. we have deployed a prototype context-aware cameraphone application for mobile media sharing (mmm2) that aims to overcome these difficulties. mmm2 leverages the point of capture and of sharing to gather metadata, and uses metadata to support sharing. based on the early results of the first 6 weeks of a six-month trial involving 60 users, indications are that with mmm2 users are actively capturing and sharing photos. the ability to automatically upload photos from a cameraphone to a web-based photo management application and to automatically suggest sharing recipients at the time of capture based on bluetooth-sensed co-presence and sharing frequency promise to reduce the current difficulty of mobile media sharing.
evaluating web lectures: a case study from hci. we present research using web lectures to enhance the classroom learning experience in an introductory hci course. by using web lectures to present lecture material before class, more in-class time can be spent engaging students with hands-on learning activities. a quasi-experiment was conducted over a 15-week semester with 46 students in two sections of the same course: one section using web lectures and one using traditional lectures. many control measures were in place, including each section being taught by the same instructor and blind grading. the web lecture section's grades were significantly higher than the traditional lecture section, and web lecture students reported increasingly strong positive attitudes about the intervention. our twofold contribution is a novel use of existing technology to improve learning, and a longitudinal study of its use within the context of hci education.
evaluating pattern languages in participatory design. we present an evaluaion of pattern languages as tools for participatory design, based on three criteria, derived from the work of christopher alexander: empowering users, generative design and life-enhancing outcomes. our results suggest that pattern languages can be used to enable users to participate in design, but that the role of facilitator and the form and physical presentaton of the pattern language are factors in success.
effect of location-awareness on rendezvous behaviour. this paper presents an exploratory field study investigating the behavioral effects of mobile location-aware computing on rendezvousing. participants took part in one of three mobile device conditions (a mobile phone, a location-aware handheld or both a mobile phone and a location-aware handheld) and completed different rendezvousing scenarios. we present one of the scenarios in depth and discuss the effect of location-awareness on rendezvous behaviour.
using perceptual grouping for object group selection. modern graphical user interfaces support the direct manipulation of objects and efficient selection of objects is an integral part of this user interface paradigm. for the selection of object groups most systems implement only rectangle selection and shift-clicking. this paper presents an approach to group selection that is based on the way human perception naturally groups objects, also known as the "gestalt" phenomenon. based on known results from perception research, we present a new approach to group objects by the gestalt principles of proximity, curve-linearity, and closure. we demonstrate the results with several examples.
shared text input for note taking on handheld devices. shared text input is a technique we implemented into a note taking system for facilitating text entry on small devices. instead of writing out words on the tedious text entry interfaces found on handheld computers, users can quickly reuse words and phrases already entered by others. sharing notes during a meeting also increases awareness among note takers. we found that filtering the text to share was appropriate to deal with a variety of design issues such as screen real estate, scalability, privacy, reciprocity, and predictability of text location.
shared freeform input for note taking across devices. shared freeform input is a technique for facilitating note taking across devices during a meeting. laptop users enter text with a keyboard, whereas pda and tablet pc users input freeform ink with their stylus. users can quickly reuse text and freeform ink already entered by others. we show how a new technique, freeform pasting, allowed us to deal with a variety of design issues such as quick and informal ink sharing, screen real estate, privacy and mixing ink-based and textual material.
attractive windows: dynamic windows for digital bulletin boards. in this paper we describe attractive windows, a novel interface for presenting live, interactive, multimedia content on a network of public, digital, bulletin boards. implementing a paper flyer metaphor, attractive windows are paper-like in appearance and are attached to a virtual corkboard by virtual pushpins. windows can therefore appear in different orientations, creating an attractive, informal look. attractive windows can also have autonomous behaviors that are consistent with the corkboard metaphor, like fluttering in the wind. we describe the attractive windows prototype, and offer the results of an initial evaluative user study.
voicecode: an innovative speech interface for programming-by-voice. in this paper we describe voicecode, a system for programming-by-voice. with voicecode, programmers can dictate code in an easy to pronounce syntax, which the system translates to native syntax in the current programming language. we illustrate how this approach addresses most of the usability issues for programming-by-voice.
using heuristics to evaluate the playability of games. heuristics have become an accepted and widely used adjunct method of usability evaluation in internet and software development. this report introduces heuristic evaluation for playability (hep), a comprehensive set of heuristics for playability, based on the literature on productivity and playtesting heuristics that were specifically tailored to evaluate video, computer, and board games. these heuristics were tested on an evolving game design to assess their face validity and evaluation effectiveness compared to more standard user testing methodologies. the results suggest that hep identified qualitative similarities and differences with user testing and that hep is best suited for evaluating general issues in the early development phases with a prototype or mock-up. combined with user studies, hep offers a new method for the hci game community that can result in a more usable and playable game.
designing interfaces that influence group processes. the goal of this research is to build and evaluate collaborative tools that persuade behavior change over a group of individuals. preliminary work in this area is presented and future directions are discussed.
using visualizations to review a group's interaction dynamics. we present a visualization system for reviewing the turn-taking patterns in a face-to-face meeting. without the need to directly observe a group, a user can use the system to gain insight into the interaction dynamics of a meeting. we evaluated the visualizations by asking outside observers to make qualitative judgments about the individuals represented visually, and then compared their assessments to our own, made from direct observation of the meetings.
eye contact sensing glasses for attention-sensitive wearable video blogging. we present ecsglasses: eye contact sensing glasses that report when people look at their wearer. when eye contact is detected, the glasses stream this information to appliances to inform these about the wearer's engagement. we present one example of such an appliance, eyeblog, a conversational video blogging system. the system uses eye contact information to decide when to record video from the glasses'; camera.
supporting collaboration through passing informal notes to peripheral displays. dropnotes is a note-passing system for informal sharing of information within a small group or for posting notes to oneself. its goal is to improve collaboration by increasing awareness through peripheral displays. dropnotes typically appear on peripheral displays placed in the work environment, such as a door panel, a peripheral display near the phone, a group board in a break room or a pda. the design of dropnotes focuses both on making note creation easy and on minimizing interruptions. as such, dropnotes supports informal information sharing and peripheral awareness rather than messaging.
scalability in system management guis: a designer's nightmare. as information technology (it) advances, traditional concerns over performance are being overtaken by concerns over manageability and scalability in system management interfaces [1]. designing effective interactions and representations of large complex systems with intricate relationships among components is a formidable challenge. in this paper we describe the design of a topology viewer application for enterprise-scale storage systems. a key issue in this design effort was to create a graphical topology viewer that would scale to the complexity of typical storage environments and support administrators effectively in various activities. our approach to address these issues was to use semantic zooming and progressive information disclosure techniques extensively; thus essentially shifting the scalability challenge from purely visual design to mostly interaction design.
multi-channel consumer behavior: online and offline travel preparations. elaborating on the first stage in the user-centered design (ucd) process, understanding the user, this study questions whether it is sufficient to look at the use of interactive systems in isolation. starting from the assumption that consumers often use the internet in combination with other channels (telephone, high street, mail order), this paper discusses a study on how consumers move between online and offline channels during the preparations for leisure travel. the theoretical framework was informed by literature from the fields of hci, marketing and social sciences. the results of the first stage of this work-in-progress indicate that multi-channel use is a day-to-day reality for many consumers.
the bed: a medium for intimate communication. in this paper, i present "the bed", an environment providing a new form of abstracted presence for intimate, non-verbal inter-personal communication. this secure and familiar environment is explored for its ability to become a shared virtual space for bridging the distance between two remotely located individuals through aural, visual, and tactile manifestations of subtle emotional qualities. as an example, i describe the application of these tangible interfaces and ambient media into a working prototype.
shake it! this paper presents our design process and resulting solution for the chi 2004 student design competition. the design challenge posed was to pilot audience participation as a way to reduce the controversy caused by judging at the olympics in sports such as diving and gymnastics. we faced this challenge by applying both empirical and analytical human-computer interaction methods, as well as extensive research into the olympics and available technologies. our findings led us to suggest the "shake it!" system for athens 2004: each spectator will have a shaker that divides into two parts, each part having a different color and producing a different sound. audience members use the shaker to express agreement or disagreement with the judge's scores. a computer vision system will be used to process the input, and audience member votes will be represented on a large screen in the venue.
limestick: designing for performer-audience connection in laptop based computer music. this paper describes a design argument and a prototype for a performance interface for laptop musicians geared towards improving audience interaction and engagement with the performer. limestick, the prototype interface presented in this paper, is an attempt to address and improve characteristics of current conventional laptop performance that are negative to audience enjoyment.
echoes: encouraging companionship, home organization, and entertainment in seniors. the echoes project (encouraging companionship, home organization, and entertainment in seniors), is focused on understanding and improving aspects of companionship in senior populations aged sixty-five years and older. individuals in this age range commonly experience the loss of close friends and life partners. furthermore, they are at risk of suffering from feelings of loneliness and depression. the project team consulted with several experts on aging in order to better understand the target population. the team followed an iterative design process which included focus groups and field studies. potential design possibilities were identified and a final design prototype was chosen after several rounds of usability testing. the proposed system includes "teletable," an interactive table-based device that offers intuitive means of arranging and organizing digital media. the teletable also functions in a communicative capacity, encouraging individuals to interact with each other by playing simple games, conversing verbally, and exchanging digital photos with each other. this system also includes the "pitara," a portable device enabling the association of physical mementos and keepsakes to digital media which adds a mobility, lifetime sharing and storytelling aspect to the teletable.
dove: digital olympic voting environment. this paper describes the design process and solution for a voting system to be used in the 2004 olympics. it focuses on the initial design ideas that were brainstormed, user testing, and the final design of the system. taking into account the different cultural groups and technology literacy levels, we determined that the voting device should be "tangible". we developed several different prototypes and user tested them to determine which design would be most effective. the resulting design was then developed along with a feedback component which utilizes a jumbotron.
barriers to inclusive design in the uk. this research combines a systematic approach to engineering design and technical communication to address industry barriers to inclusive design. the barriers were investigated from design consultancies, manufacturers and retailers, using a variety of methods such as interview, observation, survey and case studies. three different types of barriers were identified, namely: perception barriers, technical barriers and organizational barriers. a toolkit has been developed to address the barriers identified and is undergoing industry testing. the initial test results have demonstrated the effectiveness of the toolkit as a technical communication vehicle for inclusive design.
window navigation with and without animation: a comparison of scroll bars, zoom, and fisheye view. each of three window navigation techniques --- scroll bars, zoom, and fisheye view --- were implemented in two versions: with animation (a gradual transition from one state to another was provided) and without animation. a highly significant effect of navigation technique, but not of animation, was found in the experiment reported in the paper.
the korean twiddler: one-handed chording text entry for korean mobile phones. we present a text entry method using the twiddler one-handed chording keyboard to input hangul, the korean alphabet, on mobile phones. after estimating keystrokes of various text entry methods, we found that our twiddler 3 bul keymap has the fewest keystrokes needed among the methods evaluated.
wizard of oz interfaces for mixed reality applications. one important tool for developing complex interactive applications is "wizard of oz "(woz)simulation.woz simulation allows design concepts,content and partially completed applications to be tested on users without the need to first create a completely working system.in this paper we discuss the integration of wizard interface tools into a mixed reality (mr)design environment and show how easier creation and evolution of wizard interfaces can lead to an expanded role for woz-based testing during the design evolution of mr experiences.we share our experiences designing an audio experience in an historic site,and illustrate the evolution of the wizard interfaces alongside the user experience
global garden: a vision of the universal scoring device. recent controversies surrounding the judging of olympic events, has created the need for an audience participatory judging system. the stage for this participation will be the diving and gymnastics events at the 2004 summer olympic games in athens. we researched the olympic audience and studied collaborative group interaction. this process made us realize that a traditional, quantitative scoring system would not adequately address the needs of an international olympic audience. our solution is the global garden, a wearable interface that defies the conventional process of entering a "score" and displaying it. it consists of a set of interactive devices worn on the hand that glow green when a user claps, and changes colors based on different hand gestures that follow. by using applause, the intuitive and international sign of appreciation, the audience itself becomes an interface. people provide the input and output of a universal "score," heightening everyone's desires to participate and eliminating the need for excessive infrastructure. we achieved our goals to design a novel, intuitive (instruction-less) interaction that connects members of the audience to the events they watch and to each other.
structured observation: practical methods for understanding users and their work context. this tutorial will focus why and how to do observations of users in their own worksite. it will introduce practitioners how to use ethnographic tools, and how to apply what they find to design.
is roi an effective approach for persuading decision-makers of the value of user-centered design? this panel examines the utility and effectiveness of various ways of making the business case for user-centered design (ucd). most of the discussion in our field has assumed that measuring and demonstrating roi for usability is the key to this effort. however, experience shows that the most brilliant roi analysis may not win the day in the real world of business. our panelists range from people who claim that roi is an important persuasive tool as long as the communication about roi is happening within a healthy business relationship, to people who claim that a focus on roi can actually be destructive. we also explore the idea that there are important business contexts where roi simply does not fit. through the presentations by the panelists and through discussion of a business case scenario, we explore some alternatives to roi in making the business case for user-centered design.
the hci educator's open house: exchanging resources, delivery formats, learning strategies and future concerns. in previous chi pre-conference workshops, hci educators and industrial professionals have met to address pertinent hci education issues. workshop themes have ranged from hci knowledge and skills needed for effective hci professsional practice (chi '92), to designs for teaching hci (chi '94), and to increasing collaboration between academia and industry (chi '95 and chi '96).
sound intensity gradients in an ambient intelligence audio display. this paper describes the prototype of a real-time responsive audio display for an ambient intelligent game named socio-ec(h)o. the audio display relies on a gradient response to represent and anticipate player action. we describe the audio display schema, and discuss results of our current experimentation in guiding player actions through types of audio feedback, for creating sound recognition, perceptions of change and sound intensity.
the world of wireless and kids. in this panel, we will explore the impact that emerging new wireless technologies have on the way children learn, communicate and play. the challenge of interface design for children's wireless technologies will be discussed along with the opportunities these new technologies afford for social learning experiences. panelists will discuss a range of issues based on their diverse perspectives as ethnographers, researchers, and product developers. panelists will be asked questions not only from the audience, but also from a diverse group of discussants: three chikids (ages 7--11), one k-12 teacher and one parent of a child who uses wireless technologies.
the world of wireless and kids. in this panel, we will explore the impact that emerging new wireless technologies have on the way children learn, communicate and play. the challenge of interface design for children's wireless technologies will be discussed along with the opportunities these new technologies afford for social learning experiences. panelists will discuss a range of issues based on their diverse perspectives as ethnographers, researchers, and product developers. panelists will be asked questions not only from the audience, but also from a diverse group of discussants: three chikids (ages 7--11), one k-12 teacher and one parent of a child who uses wireless technologies.
design guidelines for improved human-robot interaction. this poster highlights one of our analysis frameworks for human-robot interaction (hri) and a sample of our results. we developed a fine-grained definition of hri awareness based on research from computer-supported cooperative work (cscw). results consist of initial design guidelines for hri that we are incorporating in next-generation robots and interfaces under development at umass lowell.
the orbital browser: composing ubicomp services using only rotation and selection. most ubiquitous computing environments are designed as collections of highly distributed and heterogeneous services. in this paper we describe a user interface, the orbital browser, which reduces the complexity of ubicomp service composition to two simple end-user operations: rotation and selection. we discuss the design requirements imposed by service composition and how we addressed them with our system.
user strategies for handling information tasks in webcasts. webcast systems support real-time webcasting, and may also support access to the stored webcasts. yet, research rarely examines issues concerning the interface to webcast systems, another form of multimedia system. this paper focuses specifically on how stored webcasts are re-used. sixteen participants performed three typical information tasks using epresence, a webcasting system that handles both live and stored video, and contains several tools: a video window, a timeline of the webcast, slides used by the presenter, and a moderator-generated table of contents, that facilitate user access to the intellectual content of a stored video. use takes place at the level of the webcast, and our analysis assessed user interactivity. the results showed that different types of tasks need different strategies and tools.
how much do we understand when skim reading? the world wide web and other technological advances have meant rapid reading or "skimming" of text is increasingly common in our information-rich time-limited society. this study investigates the effectiveness of skimming as a strategy for understanding a text. a replication and extension of masson's (1982) work found that recognition of important, unimportant and inferable information declined equally when readers were required to skim rather than read text normally. this indicates that readers struggle to focus on important information when skimming. moreover, a response bias suggests skimmers are more likely to over-interpret complicated information as consistent with the text. thus, designers including large amounts of text should be aware that skimming is a limited strategy for achieving understanding.
spinner, using non sequential and contextual functions for early learners. spinner is a media collection, interaction and sharing device for early learners that promotes play and exploration using a novel set of interactive techniques and designs based around a non sequential, contextual physical interface [2] and a graphical user interface (gui).
the pillow: artist-designers in the digital age. the pillow is a treated lcd screen which shows changing patterns in response to ambient electromagnetic radiation, challenging viewers to consider our constant invasion by electronic information. it is proposed as a product for mass-production, one that people would purchase for home use. in this paper, we describe how this admittedly impractical value fiction illustrates some of the ways that designers can pursue research.
netraker suite: a demonstration. this demonstration will show the application of a unique approach to collecting and analyzing usability data from the users of web sites and software applications. the netraker suite supports researchers in conducting usability research remotely, collecting both quantitative and qualitative data, reducing administration overhead and project cost. it provides several different types of interaction with test participants, including email invitations and web page intercepts. researchers can also participate in real-time screen sharing sessions with test participants, and view streaming videos of previous screen sharing sessions. the suite of tools offers an easy-to-use web-based interface that supports the entire team collaborating on a web site design. its built-in research templates and online analysis tools makes the task of starting a new research project, as well as collecting and analyzing the resulting data, something that can be accomplished in hours rather than days or weeks.
groupspace: a 3d workspace supporting user awareness. real-time distributed groupware must support awareness of other users if collaborators are to work together effectively. several techniques have been developed for enhancing awareness in two-dimensional shared workspaces, but less is known about how to support awareness in 3d workspaces. the groupspace system incorporates several types of awareness techniques (embodiment enhancements, participant list enhancements, and the grand tour) to help users maintain awareness of others' locations and perspectives, even when they are distant or out of view.
transference of dance knowledge through interface design. this research is for a doctoral project to develop labanassist as a prototype application. when completed this application will provide dancers, choreographers, artistic directors, choreologists, students and educators with a tool designed to make labanotation more accessible to the dance community and as a result enhance dance literacy. the research considers the characteristics of various styles of interactions, the function they serve in structuring information and the design of the interface to facilitate the accurate documentation of dance notation.
nemesys: neural emotion eliciting system. this paper describes the development of a new model of agent emotion elicitation called nemesys. it enhances interfaces with emotional and social information. nemesys is based on an artificial neural network and is able to learn six basic emotional states. the elicitation of emotions is based on models drawn from the state of the art in modeling emotions in the field of psychology. further the described framework includes the five-factor model of personality to represent different agent personalities.nemesys (called after nemesis, the greek goddess of righteous anger) is designed to perform in various types of interfaces. the usage of nemesys is presented with an application scenario employing a commercial 3d game-engine. additionally a critical review of the current elicitation behavior of nemesys is presented and discussed.
interactive systems for supporting the emergence of concepts and ideas. current computer application systems are best at dealing with well-defined materials rather than in helping users create new concepts. for example, it is easier to use computers to draft precise drawings than to quickly sketch new configurations; it is easier to craft polished documents than to jot ideas and play with them. a body of research is beginning to accumulate that explores systems, such as pen-based sketching applications, to support the user in dealing with ill-defined concepts and materials. the key idea is that a person needs be able to easily create a visual representation, even for abstract and verbal ideas, and then respond to it perceptually to discover new arrangements and shapes representing new ideas. the new concepts emerge from the concrete materials of the visual representation. (this basic idea is expressed by the sociologist donald sch&ouml;n in the reflective practitioner.)
drawing on the right side of the brain. drawing on the right side of the brain is one of the most effective teaching methods for drawing ever developed. in this tutorial, the participant will be introduced to the underlying theory behind the method. the bulk of the session will involve practical hands-on exercises, which demonstrate the participants' ability to learn to draw, and to learn to "see things more clearly."in this tutorial you will learn basic strategies for accessing the visual, perceptual mode of thinking. this type of thinking is learned through the acquisition of very basic drawing skills and the acquisition of an understanding of the nature of drawing.
representation without taxation: what makes gui good. in the proposed work, research in cognitive science and display-based hci is synthesized and brought to bear on the question of "what makes gui good?". a two-phase approach is outlined. the empirical phase will build upon a foundation laid by display-based hci research. the computational modeling phase will be informed by the empirical phase and previous modeling efforts. the primary goal is to be able to explicate conditions under which a user will rely on external display components vs. internal knowledge structures to control task performance.
what should it do?: key isssues in navigation interface design for small screen devices. one important application area for location-aware mobile devices is offering navigational support. this paper summarizes the results of preliminary user tests with different navigation interfaces designed for small screens. we focus on the effectiveness vs. likeability of the interface and explore how these two aspects can be combined to support the navigational task of the user. our research shows, that offering rich contextual information can support the navigational task by providing the user with a feeling of familiarity and perceived credibility. at the same time it can be a source of distraction, and cause misinterpretations. we propose the use of a rotating route-model to provide the user with a navigational guidance system both effective and likeable.
intelligent lighting for a better gaming experience. lighting assumes many aesthetic and communicative functions in game environments that affect attention, immersion, visibility, and emotions. game environments are dynamic and highly unpredictable; lighting such experiences to achieve desired visual goals is a very challenging problem. current lighting methods rely on static manual techniques, which require designers to anticipate and account for all possible situations and user actions. alternatively, we have developed ele (expressive lighting engine) -- an intelligent lighting system that automatically sets and adjusts scene lighting in real-time to achieve desired aesthetic and communicative goals. in this paper, we discuss ele and its utility in dynamically manipulating the lighting in a scene to direct attention, stimulate tension, and maintain visual continuity. ele has been integrated within unreal tournament 2003. the videos shown at [14] shows a demonstration of a first person shooter game developed using the unreal 2.0 engine, where ele was configured to dynamically stimulate tension, while maintaining other visual goals.
personalsoundtrack: context-aware playlists that adapt to user pace. this paper describes a mobile music player, personalsoundtrack, that makes real-time choices of music based on user pace. standard playlists are non-interactive streams of previously chosen music, insensitive to user context and requiring explicit user input to find suitable songs. the context-aware mobile music player described here works with its owner's library to select music in real-time based on a taxonomy of attributes and contextual information derived from an accelerometer connected wirelessly to a laptop carried under the arm. we are in the process of evaluating this prototype with 25 users who will compare the system's context-sensitive playlist to random shuffle. on the basis of user feedback and analysis, a hand-held device will be implemented for testing in less constrained mobile scenarios. personalsoundtrack allows users to experience their music with both mind and body, providing a unique embodied experience of their personal music library. in mobile environments where attention is a limited resource, users can spend less time deciding what music to enjoy and more time enjoying it.
the sampling lens: making sense of saturated visualisations. information visualisation systems frequently have to deal with large amounts of data and this often leads to saturated areas in the display with considerable overplotting. this paper introduces the sampling lens, a novel tool that utilises random sampling to reduce the clutter within a moveable region, thus allowing the user to uncover any potentially interesting patterns and trends in the data while still being able to view the sample in context. we demonstrate the versatility of the tool by adding sampling lenses to scatter and parallel co-ordinate visualisations. we also consider some implementation issues and present initial user evaluation results.
social visualization in software development. most software development tools focus on supporting the primary technical work -- writing code, managing requirements, filing bugs, etc. yet with large teams, managing the social aspects of a project can be as complex as managing code. here, we discuss the iterative design of a visualization that helps developers better understand the social aspects of their work.
using treemaps to visualize threaded discussion forums on pdas. this paper describes a new way of visualizing threaded discussion forums on compact displays. the technique uses squarified treemaps to render the threads in discussion forums as colored rectangles, thereby using 100% of the limited screen space. we conducted a preliminary user study, which compared the treemap version and a traditional text based tree interface. this showed that the contents of the discussion forum were easily grasped when using a treemap, even though there were in excess of one hundred threads. in particular our technique showed a significant improvement in time for finding the largest and most active threads. overall, it was shown that the benefits derived from using treemaps on desktop computers are still valid for small screens.
hierarchical faceted metadata in site search interfaces. one of the most pressing usability issues in the design of large web sites is that of the organization of search results. a previous study on a moderate-sized web site indicated that users understood and preferred dynamically organized faceted metadata over standard search. we are now examining how to scale this approach to very large collections, since it is difficult to present hierarchical faceted metadata in a manner appealing and understandable to general users. we have iteratively designed and tested interfaces that address these design challenges; the most recent version is receiving enthusiastic responses in ongoing usability studies.
feedback management in the pronunciation training system artur. this extended abstract discusses the development of a computer-assisted pronunciation training system that gives articulatory feedback, and in particular the management of feedback given to the user.
a study of hand shape use in tabletop gesture interaction. although manual gesture has long been suggested as an intuitive method of input for horizontal human-computer systems, little research has been conducted into observing user preferences for tabletop gesture interaction. this is particularly the case for computer vision-based gesture input, where the recognition of different hand shapes opens up a new vocabulary of interaction. in this paper, results from an observational study of manual gesture input for a tabletop display are discussed. implications for tabletop gesture interaction design include suggestions for the use of different hands shapes for input, the desirability of combined touch screen and computer vision gesture input, and possibilities for flexible two-handed interaction.
hci at trilogy: bringing the design stance to a startup. a successful startup in the arena of enterprise software, trilogy development group began experimenting with hci as a means for improving user reactions to their products. two years have passed since the first experiments; in that time an entire hci group was created and has subsequently become a respected and critical component of trilogy's development process, as well as taking some responsibility for providing a vision for trilogy's future. this paper chronicles our experiences in bringing the "design stance" to trilogy.
designing visualizations of social activity: six claims. in this paper, we describe a set of claims that have evolved from our work in designing visual representations of groups in online environments. we argue that these claims can serve as a good starting point for design work, and can drive critical discussions amongst design stakeholders.
discourse architectures: designing and visualizing computer mediated conversation. the goal of this workshop is to examine the issue of coherence in computer-mediated (text-based) conversation (cmc), and how it can be visualized graphically. the premise underlying the workshop is that the understandings of coherence developed by designers and researchers can usefully inform one another. analytical representations based on discourse research and/or theory might, suitably modified, serve as interface designs, and the interplay between graphical user interfaces and the achievement of coherence by users might advance research understandings.
putting it all together: pattern languages for interaction design. interaction design is becoming increasingly complex and diverse. complexity increases because existing technologies are becoming smaller and cheaper and thus more ubiquitous, even as new i/o devices are invented. this complexity is increased by the task of integrating technologies into workplaces which we are recognizing as filled with existing customs and practices. simultaneously, interaction design is becoming more diverse. within chi, it is well accepted that anthropologists, psychologists, and visual designers, as well as engineers and computer scientists, have roles to play in systems design. and as new technologies and application domains appear on the scene, the need for disciplines such as industrial and product design, architecture, interior design, music and film becomes evident. another factor driving diversity is customization. as systems become increasingly customizable, more design is done in-house by mis departments, outside consultants, or the end users. in many cases, these participants lack the time, resources, training or inclination to engage in research on the needs and practices of their users.
derive: a distributed platform for mixed reality interaction. this article describes a concept for and the realization of a distributed mixed reality platform. it allows to freely connect real and virtual components which can be located all over the world, integrating them into a homogenous environment. in the project derive, this is applied to techinical training. within this scope, the components of interest are electro-pneumatic parts like valves and cylinders, being connected by tubes and wires. using the idea of swapping/merging real and virtual elements, the concept is supposed to support new demands for the training of multi-skilled technicians.
gaze behavior of talking faces makes a difference. we present the results of an experiment investigating the effects of a talking head's gaze behavior on the user's quality assessment of the interface. we compared a version that used life-like rules for gazing with a version that would keep its eyes fixed on the visitor most of the time, and a random version. we found significant differences between these gaze algorithms in terms of ease of use, efficiency and other quality factors.
usability from the cio's perspective. there is significant frustration among business leaders and cios concerning the success of their systems in the field. there is an equal frustration among hci professionals at the marginalized role that usability often plays in systems development efforts. these frustrations are, to a large extent, two sides of the same coin. this panel will consider how cios manage the apparently competing challenges of faster/better/cheaper systems and the time and money required for developing highly usable systems. they will discuss the strategies and techniques that they use to integrate usability into systems design and development.
modal spaces: spatial multiplexing to mediate direct-touch input on large displays. we present a new interaction technique for large direct-touch displays called modal spaces. modal interfaces require the user to keep track of the state of the system. the modal spaces technique adds screen location as an additional parameter of the interaction. each modal region on the display supports a particular set of input actions and the visual background indicates the space's use. this "workbench approach" exploits the larger form factor of display. our spatial multiplexing of the display supports a document-centric paradigm (as opposed to application-centric), enabling input gesture reuse, while complementing and enhancing the current existing practices of modal interfaces. we present a proof-of-concept system and discuss potential applications, design issues, and future research directions.
cross-cultural applicability of user evaluation methods: a case study amongst japanese, north-american, english and dutch users. this paper describes the findings for an international user study investigating cultural applicability of user evaluation methods. the case study evaluates cultural differences in understanding of a virtual campus website across four culturally different user groups by using the same methods for each group. findings suggest that some user evaluation methods are less applicable than others are for a culturally diverse user base.
amigo - wireless image based instant messaging for handheld computers. we introduce amigo - an instant messaging (im) client for handheld computers. amigo allows free-form images as well as handwriting to be sent between people, taking advantage of the touch sensitive display of mobile devices. amigo differs from other im clients in that the text written by the user never has to be translated into ascii data. twenty students used amigo for two weeks. preliminary use results show that amigo functions well as an im client for handheld computers, and also introduces new ways for people to interact using im: mixed text/image sessions, collaborative drawings and instant gaming.
what is a place?: allowing users to name and define places. from working with location-based information systems we know that positioning is problematic. a different approach was tested, where users themselves were allowed to name and define the places they wanted to use. the question was if they would do so, and if they would understand the notion of "place". in a user study, 78 users created 84 place labels. the user study also gave us some unexpected input to the users' perception of place: not only physical, but also virtual places were created.
a discourse model for interaction design based on theories of human communication. most current models of interaction design build on scenarios and task analysis. we think that interaction design should be more along the lines of communication between humans. with this motivation, our paper presents a new approach to modeling interaction design based on insights from theories of human communication. from such discourse models, we aim for automated generation of user interfaces.
the penguin: using the web as a database for descriptive and dynamic grammar and spell checking. in consequence of emergent limitations of traditional spell and grammar checkers, the penguin prototype system has been designed to be a descriptive and dynamic tool for computer based writing. rather than relying on a static dictionary, the web is used as a database to handle language artifacts out of the ordinary, such as idioms, colloquialisms, names, and slang expressions; a common source of concern especially for second language speakers.
managing icon abundance on ebay. icons play an important role in ebay's global interface by quickly communicating features, actions, or status while reinforcing the ebay brand. connecting our users with concepts in a graphical manner, icons cross cultural and language barriers. with ebay's expansion into international countries and the growing complexity of the site, requests for icon creation have increased exponentially. to address the challenge of maintaining consistency in the face of an abundance of icons and the many purposes that they serve, we conducted a series of studies. how does one present the variety of icons and accommodate all their different functions, and still maintain simplicity and consistency? recognizing the need to create a consistent icon experience, ebay conducted two usability studies to research icon usage. we sought to answer the following 2 questions: 1) how does an icon's design affect its affordance and comprehension? 2) how many icons can we present before reaching a saturation point?
avatar proxies: configurable informants of collaborative activities. in the physical world, every user exists at one and only one place, but in a collaborative virtual environment (cve), other paradigms are achievable such as a user existing at more than one place at a time. in a collaborative environment, a user is typically engaged with one primary activity at a time. as the number of collaborative activities increases, users are unable to maintain focal attention on all activities, and must offload some cognitive effort to a peripheral attention sphere. this delegation of attention-the movement of primary activities as focal attention to secondary activities as non-focal attention-requires that users remember certain parameters of context switching, such as what the secondary activities are, and more importantly, when to switch their focal attention to these activities. keeping track of these context-switching parameters is itself a cognitive load that often degenerates focal attention on primary activities.our goal is to augment users' cognition by delegating the work of remembering context-switching parameters to other entities in a collaborative environment. we call these entities avatar proxies because our implementation is in a cve in which users are iconified as avatars, but the techniques and results are general to a broader range of collaborative environments. avatar proxies notify users when they are required to switch their focal attention to secondary activities.
relescope: an experiment in accelerating relationships. busy academics and professionals are being called upon to manage more and more relationships. many details of collaboration are accessible in digital libraries and other repositories. with relationship-oriented computing, we posit that network information embedded in these repositories can be leveraged to improve the human need to manage and form the most productive relationships. to explore this idea, we developed a relationship-network application, called relescope, and deployed it at the acm cscw 2004 conference. it provided a personalized report to attendees based on publication and citation information. the report was intended to provide concrete insights into the relationship-network that could be acted upon. results of a survey showed that 52% of responders used their report to recognize and talk to others or plan which talks to attend. people with fewer collaborators were more inclined to use relescope than the people with the most collaborators. lessons learned and future work are discussed.
enabling rich human-agent interaction for a calendar scheduling agent. the rhaical system provides novel visualizations and interaction techniques for interacting with an intelligent agent, with an emphasis on calendar scheduling. after an agent interprets natural language containing meeting information, a user can easily correct mistakes using rhaical's clarification dialogs, which provide the agent with feedback to improve its performance. when an agent proposes actions to take on the user's behalf, it can ask the user to confirm them. rhaical uses novel visualizations to present the proposal to the user and allow them to modify the proposal, and informs the agent of the user's actions in a manner that supports long-term learning of the user's preferences. we have designed a high-level xml-based language that allows an agent to express its questions and proposed actions without mentioning user interface details, and that enables rhaical to generate high-quality user interfaces.
availability bars for calendar scheduling. calendar scheduling is a difficult task for people who have overbooked calendars with many constraints. currently, calendar applications do not allow users to specify scheduling constraints such as how preferable a free time is for scheduling a new meeting or to what extent an existing meeting can be rescheduled. this paper introduces the "availability bar," an interaction and visualization technique for complex calendar scheduling constraints. availability bars, embedded in calendar applications, can help users who manually schedule meetings. availability bars can also mediate communication with calendar scheduling agents that gather availability constraints, search for times that satisfy the constraints, and negotiate with invitees when no satisfactory time is found for the constraints.
a tenant interface for energy and maintenance systems. we describe the design of a user interface for energy and maintenance systems in commercial buildings. the user interface is for use by occupants (tenants) of commercial buildings. our hypothesis is that by allowing tenants access to information from the energy and maintenance systems and by giving them some control over these systems, energy and maintenance performance can be improved. we used interviews with potential users and existing energy and maintenance databases to guide the design.
giveaway wireless sensors for large-group interaction. we have developed a small, handheld or wearable, wireless motion sensor that sends out a short rf pulse whenever it is jerked. the hardware is minimal, as it mainly includes only a piezoelectric foil accelerometer, a cmos timer, and a single-transistor 300 mhz rf transmitter. as such, the onboard battery should last for many years, and the cost is low enough (well under us $1. in large quantity) to be given away with a ticket to an event, enabling it to be used to allow individuals to contribute to a large-group, real-time interaction. we discuss results from experiments using this device to explore collaborative music control, and touch on other applications.
visibabble for pre-speech feedback. the visibabble system processes infant vocalizations in real-time. it responds to the infant's syllable-like productions with brightly colored animations and auditory feedback. it saves an audio recording and its acoustic-phonetic analysis. the system reinforces the production of syllabic utterances that are associated with later language and cognitive development. we are developing both a toy and a clinical/research tool.
american sign language of the web. the development of non-western character encodings has empowered linguistic communities all over the world to create their own on-line webs. however, in the case of sign languages, which convey meaning by gestures moving in time and space, the static and textual nature of the www medium has, until now, continued to prevent the development of on-line webs by signing linguistic communities. the challenge then is to enable web designers to create on-line, linked webs based on moving gestures and signs without the need to use static image or text-based equivalents. we have developed a mechanism, signlinks, that facilitates the development of such webs, without requiring any degree of bilingualism with a written language for the user. signlinks use a special form of hyperlinking within video material to enable web browsing without written language.
improving speech-based navigation during dictation. this research focuses on understanding the failures of speech-based navigation as it exists in state-of-the-art speech recognition software. a detailed analysis of failure rates, reasons commands fail, and consequences of these failures in the allowed for the identification of three specific improvements to spech-based navigation. results from a follow-up study are reported, indicating that each of the three improvements reduced failure rates.
modeling command selection for speech-based applications. command selection is an important problem in human computer interaction. we are applying a decision-making approach to model the process by which users select commands when multiple alternatives exist. our initial focus is on speech-based systems, but the underlying approach is applicable to a wide range of interaction styles. two empirical studies that provide a foundation for this research are complete and an initial decision model is proposed which specifies the factors that influence the command selection decisions and the relationships between those factors. empirical studies are planned to investigate users' perceptions of individual model components and to validate the complete model.
interpersonal trust and empathy online: a fragile relationship. an empirical study was conducted focusing on the effect of empathic accuracy and response type on online interpersonal trust in textual im. the results suggest both empathic accuracy and response type have significant influence on online interpersonal trust. however, the interaction between empathic accuracy and response type is the dominant factor on interpersonal trust. the results also imply an interesting relationship between general trust attitude and online interpersonal trust.
the founding of the netscape user experience group. netscape communications is a company that has grown faster than any other software company in history. although the design effort at netscape has evolved greatly, the initial experience of bringing design into an organization in hypergrowth provided some valuable lessons in the creation of a successful design organization.
applying hci to music-related hardware. the application of usability techniques to the development of music-related hardware is rarely discussed in the hci literature. this is in spite of the fact that such devices could potentially be improved by employing usability methods during their development. this paper documents a case study of an existing electric guitar pre-amplifier. the ease of use of its user interface was investigated using the traditional hci methods of heuristic evaluation and usability testing. the user interface was susequently modified, and a follow-up usability test confirmed improvements to ease of use. these findings demonstrate that hci methods can and should be used to enhance the usability of music-related hardware.
the palm zire 71 camera interface. in late summer of 2002, the palm human interface (hi) team was given four months to design a digital camera interface for the palm zire 71 handheld computer. the project required an unusual amount of coordination between hi, product management, engineering, and hardware industrial design (id) to find ways to extend digital photography conventions into the context of the palm os and the not very camera-like form factor of the typical palm device. this case study shows the evolution of the camera interface over the entire development period, placing design decisions in context with larger product developments. discovery was minimal, user testing nonexistent, and there are no published results. in other words, this case study describes how an elegant human interface design gets created under real (i.e. unreasonable) deadlines and with typical (i.e. nonexistent) resources.
perspectives on hci patterns: concepts and tools. this workshop will explore a diversity of perspectives on patterns and patterns languages for hci as well as the requirements for software tools needed to improve the effectiveness of both pattern creation and pattern use. through discussion of conceptual and methodological issues of why (and how) patterns are identified and in what circumstances they are useful in the design process we hope to map out the conceptual landscape of hci patterns. by moving closer and examining pattern-related behavior and experiences we hope to identify the requirements for tools to make progress through that landscape.
providing a tailored overview of program source code. one very important aspect of computer programming is reading source code. even relatively small programs can consist of thousands of lines of code, and navigating through all this information can be time consuming and difficult. whilst this can be considered a minor nuisance for sighted persons, for blind computer programmers the problem is more severe.the main aim of this research is to improve access to programming for any user unable or unwilling to use a visual system. the hypothesis is that providing a glance at the source code using a tailored, auditory overview will improve the reader's understanding of the program. it is hoped that these findings could also facilitate code reading and comprehension for all users.
online personals: an overview. online personal advertisements have recently become an easy, socially acceptable way to meet partners for dates or relationships. because popular personals systems not only reflect but also have the potential to reshape how people attract one another, date, and fall in love, the design of these systems merits careful consideration. we present a survey of current styles of online personals, including searchable profile listings, personality matching, and social network systems. finally, we encourage the community to study this booming phenomenon.
homophily in online dating: when do you like someone like yourself? psychologists have found that actual and perceived similarity between potential romantic partners in demographics, attitudes, values, and attractiveness correlate positively with attraction and, later, relationship satisfaction. online dating systems provide a new way for users to identify and communicate with potential partners, but the information they provide differs dramatically from what a person might glean from face-to-face interaction. an analysis of dyadic interactions of approximately 65,000 heterosexual users of an online dating system in the u.s. showed that, despite these differences, users of the system sought people like them much more often than chance would predict, just as in the offline world. the users' preferences were most strongly same-seeking for attributes related to the life course, like marital history and whether one wants children, but they also demonstrated significant homophily in self-reported physical build, physical attractiveness, and smoking habits.
a gui paradigm using tablets, two-hands and transparency. an experimental gui paradigm is presented which is based on the design goals of maximizing the amount of screen used for application data, reducing the amount that the ui diverts visual attentions from the application data, and increasing the quality of input. in pursuit of these goals, we integrated the non-standard ui technologies of multi-sensor tablets, toolglass [1], transparent ui components [4], and marking menus [6]. while our prototypes and efforts focus within the domain of creating digital art, we believe the concepts and lessons learned are generalizable to other domains. the video shows three main segments: (1) motivation by showing an artist using traditional paper-based interactions, (2) a prototype system called t3 and (3) integration of the concepts into studiopaint, a high end commercial paint application.
breakingstory: visualizing change in online news. breakingstory is an interactive system for visualizing change in online news. the system regularly collects the text from the front pages of international daily news web sites. it allows users to search over the collection and view the frequency of occurrence of keywords in graphic, tabular, and full text formats. results from the system are shown over time, and can be filtered geographically. the system was developed using a user-centered design process that included rapid prototyping and informal user testing. it provides a new way of viewing the news that incorporates a sense of history.
an environment that integrates flying and fish tank metaphors. fledermaus vr is a system that combines the flying and fish tank metaphors for viewpoint control. a key component of the system is the continuous scaling of the scene so that it always appears just behind the screen. this scaling is done even when flying over a virtual landscape. because the scene is scaled, it is always in the right position for fish tank vr viewing. in addition, the scaling removes some of the problems that commonly occur with stereoscopic displays, it puts objects in the appropriate place for manipulation, and it can be used to modulate the flight velocity. the system is demonstrated with a cable laying application.
foundations of a pattern language based on gestalt principles. traditionally, human-computer interaction (hci) is a highly interdisciplinary field bridging the research between psychological research and computer science. this paper places great emphasis on a new pattern language based on gestalt principles, among which prägnanz is regarded as the fundamental one. psychological findings, pattern methodology and linguistic categories consequently form the basis of our work. the proposed pattern language, not yet finished, is intended to support visual design [11] in a user-centered way by providing comprehensive information about gestalt principles.
prominence-interpretation theory: explaining how people assess credibility online. four years of research has led to a theory that describes how people assess the credibility of web sites. this theory proposes that users notice and interpret various web site elements to arrive at an overall credibility assessment. although preliminary, this theory explains previous research results and suggests directions for future studies.
captology: the study of computers as persuasive technologies. "captology" is a newly coined word that describes the study of computers as persuasive technologies (see figure 1).
how users reciprocate to computers: an experiment that demonstrates behavior change. we conducted an experiment to investigate if computers could motivate users to change their behavior. by leveraging a social dynamic called the "rule of reciprocity," this experiment demonstrated that users provided more helping behavior to a computer that had helped them previously than to a different computer. users also worked longer, performed higher quality work, and felt happier. conversely, the data provide evidence of a retaliation effect.
chi education community sig. the purpose of this sig is to ask "what can the chi education community do for you at chi conferences?" and to discuss criteria for chi education experience reports.
sig visual interaction design: designing the quality experience. the visual interaction design sig has been active in the chi community for several years by hosting a column in the sigchi bulletin, with strong representation in interactions and several previous and successful sig meetings at chi. this year we continue this tradition with a meeting on the theme of "designing thequality experience."
kinetic typography: issues in time-based presentation of text. this paper introduces research in kinetic typography, a new method of displaying text that takes advantage of the dynamic nature of digital media. we suggest a preliminary set of design issues by which kinetic typography may be understood and used.
the influences of communication media and decision-making technique on team decision outcomes: a critical assessment of the stepladder approach. the stepladder technique is a method for improving face-to-face (ftf) team problem solving. the purpose of this study was to determine whether or not the stepladder technique benefits computer-mediated (cm) teams of individuals. hypotheses addressed the effects of communication media and decision making technique on team decision quality, decision variability, time to make a decision, and team member satisfaction. eighty 4-person team worked on a decision making task using one of the following group structures: ftf conventional, ftf stepladder, cm conventional, or cm stepladder. the results revealed fundamental differences between ftf and cm teams of decision makers.
techniques for researching and designing global products in an unstable world: a case study. the value of ethnographic field work for guiding and inspiring product design is indisputable, especially for development teams working on products for other cultures. however, global instability can make it difficult or impossible for researchers and product designers to travel to foreign countries to conduct field work, leaving them ill equipped to guide culturally-appropriate product design. in this paper, we present a series of ethnographically-inspired techniques that allow researchers and development teams to gather a range of culturally relevant information for product design without visiting the countries for which they are designing. these techniques are not intended to substitute for on-the-ground ethnographic fieldwork, rather, they are intended to serve as a surrogate until further in-situ research can be conducted.
outsourcing & offshoring: impact on the user experience. in a june 2003 survey, the management consulting firm mckinsey & company reported that 51 percent of software executives surveyed have indicated that their offshore development strategy is already underway. furthermore, another 20 percent of those surveyed indicated that they would move some portion of their product development offshore within the next 12 months.while offshore development has distinct advantages from the cost of labor perspective, it raises a significant number of challenges as well as opportunities for hci practitioners and companies that wish to develop well designed, usable products. offshoring is already changing the practice of hci in industry, and will continue to impact practitioners more significantly over time.
users' conceptions of web security: a comparative study. this study characterizes users' conceptions of web security. seventy-two individuals, 24 each from a rural community in maine, a suburban professional community in new jersey, and a high-technology community in california, participated in an extensive (2-hour) semi-structured interview (including a drawing task) about web security. the results show that many users across the three diverse communities mistakently evaluated whether a connection is secure or not secure. empirically-derived typologies are provided for (1) conceptions of security based on users' verbal reasoning, (2) the types of evidence users depend upon in evaluating whether a connection is secure, and (3) conceptions of security as portrayed in users' drawings. design implications are discussed.
users' conceptions of risks and harms on the web: a comparative study. in this study, we analyzed web users concerns about potential risks and harms from web use to themselves and to society at large. in addition, we assessed how strongly users felt something should be done to address their concerns. seventy-two individuals, 24 each from a rural community in maine, a suburban professional community in new jersey, and a high-technology community in california, participated in an extensive (2-hour) semistructured interview about web security. results show that web users were primarily concerned about risks to information, and secondarily about risks to people and technology. different sets of concerns were identified among the rural, suburban, and high-technology communities. our discussion focuses on implications for interface design and information policy.
looking back at plan ahead™: exercising user- centered design in emergency management. plan ahead™- all hazard exercise development and administration is a usability test development tool designed for emergency management agencies focused on disaster preparedness. several user- centered design principles employed to develop plan ahead are discussed including ethnographic research, rapid prototyping and iterative design. specific design decisions that rely on these approaches are highlighted. alternative design approaches that failed to meet user requirements are included. plan ahead™ incorporated design elements that were novel to the emergency exercise development domain. in part because of the intensive user- centered design approaches, plan ahead continues to be used by emergency managers worldwide; even with the approaches described, the application can benefit from several usability improvements.
getting to know you: open source development meets usability. this workshop seeks to increase the likelihood that usabil-ity will become a core value in open source software de-velopment by creating a meeting ground of people with direct experience of both perspectives. anticipated out-comes include tangible and immediate production of arti-cles and posters, as well as intangible and longer term re-search agenda, outreach efforts to increase the number of people with usability and interaction design expertise in-volved in all open source projects.
non-speech sound and paralinguistic parameters in mobile speech applications. this paper describes the background, research questions and methodology of user studies on the integration of non-speech sound and paralinguistic parameters in speech-enabled applications. preliminary results are summarized and future directions are discussed.
dealing with system response times in interactive speech applications. in this user study, we address several open issues in the design of waiting cues for system response time (srt) in interactive telephony speech applications. user observations and structured preference tests indicate that silent waiting times should not be longer than 4 -- 8 seconds. already at short durations, music combined with speech was favored to silence. a preference test regarding several non-speech waiting cues proposed in literature suggests that music is preferred to more simple synthetic sounds and to natural sounds. the continuous indication of the remaining waiting time by speech was rated as much more pleasant and appropriate than a non-speech audio progress meter. commercial announcements and navigational advice during waiting times were not accepted by the subjects. empirically based guidelines for a maximum waiting duration in voice services is given. implications for the design of auditory waiting cues for srt are discussed.
the hti lab @ ftw: user research for telecom systems. this paper presents the human-telecom systems interaction laboratory (hti lab) at the telecommunications research center vienna (ftw). the current setup of the hti lab and its contributions to related application-oriented projects at ftw are described.
cooperative usability testing: complementing usability tests with user-supported interpretation sessions. recent criticism of think-aloud testing (ta) discusses discrepancies between theory and practice, the artificiality of the test situation, and inconsistencies in the evaluators' interpretation of the process. rather than enforcing a more strict ta procedure, we describe cooperative usability testing (cut), where test users and evaluators join expertise to understand the usability problems of the application evaluated. cut consists of two sessions. in the interaction session, the test user tries out the application to uncover potential usability problems while the evaluators mainly observe, e.g. as in ta or contextual inquiry. in the interpretation session, evaluators and test users discuss what they consider the most important usability problems, supported by a video of the interaction session. in an exploratory study comparing cut to ta, seven evaluators find that interpretation sessions contribute important usability information compared to ta. also test users found participation in the interpretation session interesting.
visualizing health practice to treat diabetes. this research is about how to help diabetics reflect upon and improve their own health practice by collecting and visualizing health related information. we introduced a new type of data collection to diabetics, photography, to complement the data they usually collect, blood sugar levels. diabetics shoot pictures of meals, exercise, work, play and anything else they feel impacts health. we combine the quantitative glucose measurements with qualitative portraits of action into unified data visualizations. in doing so, we hope to make the relationship between physiology and behavior an object for discussion and reflection. more so, we hope that diabetics who viewed these data will begin to develop new interpretations of their lifestyles that will ultimately lead to healthier activities.
tangible search for stacked objects. the goal of tangible search is to more effectively support the user in physically locating one of a number of stacked objects. it consists of two operations - automatic logging of stacked objects and direct annotation; image processing is used to determine the heights of the stack and of the user's finger. tangible search offers stable and accurate 3d analysis since it uses our previously proposed method. it employs a single camera with a compound half-mirror; this configuration also allows the top and side views of the stack to be captured simultaneously. our approach is to make it easier for the user to handle stacks of items; it will enhance the tabletop metaphor for intuitive interaction in real-world environments where stacks are very common.
incompatible block: wonders accompanied interface. for interface design, improving user curiosity is important, as is intuitiveness and intelligibility. we think the wonder of 2d property input becoming 3d, as expected by the user, in the range of matching will be effective for enhancing not only curiosity but also availability. in this study, we developed the 3d modeling software "incompatible block" with an interface of such wonders. this paper describes the four wonders of the interface of incompatible block, introduces the mechanism, and discusses the usefulness of a wonders-accompanied interface from user evaluations.
it's a global economy out there: usability innovation for global marketplaces. we describe a workshop for usability researchers to share information about international and intercultural research methods.
proposing new metrics to evaluate web usability for the blind. accessibility-related regulations and guidelines are contributing to the steady improvement of web accessibility. there are various accessibility evaluation tools, and they also help web authors make their pages compliant with guidelines. as a result, an increasing number of web pages are compliant with the evaluation tools. these days, however, blind people face the serious problem that reading web pages is quite difficult. improvements in information density by using visual effects such as two-dimensional layouts are making it difficult for blind people to understand the page structure. also, inappropriate alternative texts mislead or confuse blind users.in this paper, to evaluate these kinds of usability problems, we introduce two metrics: navigability and listenability. navigability evaluates how well structured the web content is by using headings, intra-page links, labels, etc. listenability denotes how appropriate the alternative texts are. by using these metrics, we summarize the historical transition of web usability for blind people.
why do tagging systems work? the panel will explore the relevance of the emerging tagging systems (flickr, del.icio.us, rawsugar and more). why do they seem to work? what kinds of incentives are required for users to participate? will tagging survive and scale to mass adoption? what are the behavioral, economic, and social models that underlie each tagging system? what are the dynamics of those systems, and how are they derived from the specific application's design and affordances?.we will demand answers to these questions and others from some of the pioneering practitioners and academics in the field. bring your wireless laptop to participate in a live tagging experiment! the experiment results will be shown and discussed at the end of the panel. to add to the fun, parts of the discussion will be motivated by short video segments.
relationships among speech, vision, and action in collaborative physical tasks. this workshop focuses on the relationships among speech, gaze and action in collaborative physical tasks. we address three key challenges: characterizing the nature of collaborative physical tasks, understanding how people coordinate their activities during collaborative physical tasks, and designing technology to support these tasks.
where do helpers look?: gaze targets during collaborative physical tasks. this study used eye-tracking technology to assess where helpers look as they are providing assistance to a worker during collaborative physical tasks. gaze direction was coded into one of six categories: partner's head, partner's hands, task parts and tools, the completed task, and instruction manual. results indicated that helpers rarely gazed at their partners' faces, but distributed gaze fairly evenly across the other targets. the results have implications for the design of video systems to support collaborative physical tasks.
assessing the value of a cursor pointing device for remote collaboration on physical tasks. this study assessed the value of a cursor pointer that allows remote collaborators to point to locations in a partner's workspace via a shared video feed. we compared performance with the cursor pointer with that in video-only and side-by-side conditions. results indicated that participants found the cursor pointer of value for referring to objects and locations in the work environment, but that the pointer did not improve performance time over video-only. we conclude that cursor pointing is valuable for collaboration on physical tasks, but that additional gestural support will be required to make performance using video systems as good as performance working side-by-side.
annotation in the wild: benefits of linking paper to digital media. this work presents the design of alt, a prototype system that supports learning activities on the move by enabling users to annotate and sketch on paper in collaboration with a remote peer. initial observations of learners interacting with alt during an informal learning event show that paper annotation combined with synchronous communication technology shifts learners to use annotation as a basis for discussion and more personal interpretation of the information available.
metamuse: a novel control metaphor for granular synthesis. traditional musical intruments have a direct connection between the way they are played or controlled and the properties of the sound produced. this connectedness has, in general, been lacking in computer-based musical instruments. we present a prop-based synthesis controller that uses a metaphor to create a connection between the control and the sound. specific to granular synthesis, the metaphor is one of falling particles striking a surface to create a sound. the concept is extensible to other metaphors and other synthesis techniques.
production of pace as collaborative activity. in this paper we investigate the concept of pace development and management among groups of people. we explore and compare groups visiting museums, and groups virtually co-located in a mixed reality system for a museum. in considering pace, and how to design to support it, we have to consider more than the speed or location of information display. we have to also take into consideration the social formation of pace through features such as the visitors' awareness of each other's location and attention. by considering aspects of collaboratively produced pace such as presenting engagement and disengagement, we offer suggestions as to how social handling of pace might be better supported by technology.
ais sighci position paper. the upcoming acm sigchi development consortium is aimed at meeting the needs of multidisciplinary professionals that must choose among a variety of professional associations and their events. the position of ais' (association for information systems) sighci is that the main problem lies in the deep chasms that separate the literatures of the related disciplines, and the solution is to provide an umbrella organization that enables a more organized federation of disciplines, groups, and associations. problems identified include differences in terminology, competition for scarce resources, differences in how publications in various outlets are valued, and confusion about where should be the "home" for hci/chi majors. suggestions include developing a framework for a federation, negotiating shared understandings about publication outlets, and coordinating information about meetings and other events.
supporting the collaborative meeting place. the combination of an interactive large screen display and wireless handheld devices in a meeting room setting can augment and enhance collaborative activities. this work examines the issues in developing applications to support such a collaborative meeting place.
exploring design through wearable computing art(ifacts). usability is taken into account in design, however analysis of underlying technological values (such as trust, privacy, security) might become overlooked. in this paper, we illustrate how performance art can be used to elicit information about device design and usage. wearable computing devices or art(ifacts) were used to spark behavior and debate. it was found that the degree of acceptability of the design was related to the perceived control the wearer had over the device. we suggest that what is learned from performance art can be incorporated into future design.
building website credibility: a prospective solution to e-commerce in poland. the paper presents main problems concerning e-commerce development in poland and other countries in eastern europe, in particular links between consumer's trust and cultural background in the region. the paper presents also a model proposal, describing relations and factors affecting creation of consumer's trust toward an on-line supplier.
embracing agile development of usable software systems. the interdisciplinary nature of system design can lead to communication problems between developers in different fields. this is becoming evident in the emerging field of agile software development which has largely ignored or been unable to address usability. this work presents a development process and toolset that draws on extreme programming--an agile software development process, and scenario-based design--a usability engineering process. this approach will allow developers in both fields to better communicate and work together to efficiently design usable systems.
the drift table: designing for ludic engagement. the drift table is an electronic coffee table that displays slowly moving aerial photography controlled by the distribution of weight on its surface. it was designed to investigate our ideas about how technologies for the home could support ludic activities-that is, activities motivated by curiosity, exploration, and reflection rather than externally-defined tasks. the many design choices we made, for example to block or disguise utilitarian functionality, helped to articulate our emerging understanding of ludic design. observations of the drift table being used in volunteers' homes over several weeks gave greater insight into how playful exploration is practically achieved and the issues involved in designing for ludic engagement.
a flexible 3d sound system for interactive applications. we have developed a 3d sound system for headphones that allows real-time sound source and user displacement in a virtual acoustic environment. because of a flexible design that uses different sets of pre-selected, physically modeled filters, the complexity level of simulation can be chosen, making the system adaptable both to available cpu power and to application requirements. no extensive signal processing knowledge is required in order to select the appropriate simulation complexity. a preliminary evaluation involving 4 users showed that the system provides a satisfying localization of sounds and users (even with limited memory and cpu power) while also giving access to low-level control over simulation complexity.
bashocam: collective photographic sequencing in wireless p2p networks. wireless peer-to-peer network technology enables new types of collaborative practices among people in public space and across multiple locations. bashocam is an on-going project that designs for a collective aesthetic practice across wireless peer-to-peer social networks. it aims at enabling users connected by a social network to create collaborative narratives by juxtaposing rhythmic sequences of photographs taken on the spot. these narratives evolve as they spread throughout the network. we describe the concept of bashocam, the user interaction and our current implementation.
video browsing interfaces for the open video project. the open video project is an on-going effort to develop an open source digital video collection that can be used by the research community and ultimately serve an even broader audience. the initial collection contains video or metadata for more than 1600 digitized video segments comprising nearly half a terabyte of content. our primary goals for this project are to provide free digital video content to people doing a wide variety of research, to develop a collaborative research environment for people interested in digital video, and to provide a testbed for our own video browsing interface work. each of these goals fit within a broader mission to understand how people think about, seek, and use digital video. this demonstration summarizes the current status of the project through a brief tour of the open video web site, describes our current work in developing surrogates to preview video segments, and shows an innovative video browsing interface we are developing.
the value of shared visual space for collaborative physical tasks. the goal of this research is to elucidate the ways shared visual space supports group communication and performance. this work involves three stages: a series of empirical studies that decompose the features of shared visual space and task, a methodology for assessing the sequential structure of how visible actions serve to augment discourse, and the development of a computational model of discourse to further our theoretical understanding of the ways in which shared visual information serves communication in collaborative physical tasks.
information visualization tutorial. visual representation of information requires merging of data visualization methods, computer graphics, design, and imagination. this course describes the emerging field of information visualization including visualizing retrieved information from large document collections (e.g., digital libraries), the world wide web, and databases. the course highlights the process of producing effective visualizations, making sense of information, taking users' needs into account, and illustrating good practical visualization procedures in specific case studies.
corporate pioneers part ii - lessons learned: introducing and promoting usability testing in a corporate environment. customers today demand to receive a quality, usable product. companies are finding that their products will not sell unless they have the reputation for being usable. one way that companies can ensure usable products is through usability evaluations, user involvement, and testing. a direct result of the need for user-centered design and testing is the challenge of establishing and evolving usability methodology as an integral part of the development process within the corporate environment.
collaborating on ethnography & design research: center for ethnography & contextual innovation at hfi. human factors international inc. (hfi) is a 100 people, $13 million user-centered systems integration company, with a mission to improve the interactions that people have with computers and other digital systems. hfi offers end-to-end solutions for web/intranet and internet-based applications, software applications, ivr systems, handheld devices, telemetric, public service networks, medical and automation equipments and help make our clients' existing offerings more user centric, optimized and efficient. in the wake of the recent interest of research and development for business innovations for the emerging markets and products & services for new markets, we are in the process of establishing ethnography and design research as a service area along with the existing areas of activities & services. hfi's interest in this area is reflected through a few successful collaborations with research initiatives launched by global corporate as well as academic institutions, e.g. hp labs, nokia research, ncr, media lab asia [6] etc.in this extended abstract we will elaborate on some key issues regarding successful research collaborations. we will also discuss the lessons learnt about carrying out such collaborations and jointly leading a multidisciplinary research team with early participation in the overall project planning.
design considerations for a financial management system for rural, semi-literate users. in this paper, we describe the design process, results, and general observations obtained in designing a user interface for managing community-based micro-finance institutions in rural india. the primary users studied were semi-literate village women. we discuss our contextual study observations and conclude by presenting a grounded design approach that best leverages the existing learning patterns of the users.
indo-european partnership to promote hci and usability issues in the indian it industry and academia. the indo european systems usability partnership (iesup) is a european commission funded project under asia it & c initiative, jointly supported by british computer society / british hci group, computer society of india and other european academic institutions, to facilitate collaboration between european and indian academics and industry practitioners interested in the disciplines of usability and human-computer interaction (hci). iesup enables europe and india to collaborate in issues relating to the design of usable interactive it systems that support people in their everyday and working lives through activities that include seminars / workshops in india, visits from india to europe, building virtual communities and other methods of larger scale communication and networking.
lifesource: two cvs visualizations. we present lifesource, two visualizations of cvs code repositories, one file-centric and one author-centric. codeconnections, the file-centric visualization, pulls out the overall structure of a large body of interacting code and authors. codeconnections scales well and reveals large trends in the code base at a glance. codesaw, the author-centric visualization, compares authors' code and project mail contributions over the course of one year. codesaw reveals trends in authors' lives, exposing peaks and valleys of productivity. both visualizations uncover deep details about the life of a code project to developers and onlookers.
digital storytelling and computer game design. this workshop uses a combination of short lecture and hands on practice to introduce digital storytelling and computer game design and the multitude of skills needed to successfully design digital stories and computer games. working examples are taken from two current projects at indiana university: lost highways and rock-paper-scissors in lizard land.
chi design community sig. while most of the hci literature can be seen as part of an engineering-science practice (with an emphasis on the acquisition and interpretation of 'facts'), the chi2006 design community focuses on how arts and engineering come together in the construction, study and interpretation of created objects (maybe more like the study of literature and criticism).
snif: social networking in fur. we present snif: social networking in fur, a system that allows pet owners to interact through their pets' social networks. snif comprises inexpensive hardware that can be unobtrusively and transparently affixed to pet collars and paraphernalia in order to augment pet-to-pet, pet-to-owner, and owner-to-owner interactions. snif devices aggregate pertinent environmental, social, and individual information that can be broadcast or addressed to other participating community members.
interactive search in large video collections. we present a search interface for large video collections with time-aligned text transcripts. the system is designed for users such as intelligence analysts that need to quickly find video clips relevant to a topic expressed in text and images. a key component of the system is a powerful and flexible user interface that incorporates dynamic visualizations of the underlying multimedia objects. the interface displays search results in ranked sets of story keyframe collages, and lets users explore the shots in a story. by adapting the keyframe collages based on query relevance and indicating which portions of the video have already been explored, we enable users to quickly find relevant sections. we tested our system as part of the nist trecvid interactive search evaluation, and found that our user interface enabled users to find more relevant results within the allotted time than those of many systems employing more sophisticated analysis techniques.
innovative design within the lines: an expert critique of the xbox 360 design process. this panel session is a real-world critique of the design process and the results of a large design project. a team of outside experts from academia and industry will openly critique and discuss with the audience the lessons that can be learned and theories that can be applied to their own work. the primary example will be the xbox 360, whose team will be describing and showing the intimate details of their work.the goal is to provide audience members a behind-the-scenes look into the actual process used to solve design problems behind the xbox 360, to hear expert critique of the process and results, and to engage in an open and entertaining question & answer session.
rosebud: technological toys for storytelling. rosebud is a user-interface prototype which elicits storytelling by child users though interaction with a computationally-augmented physical artifact. in particular, rosebud links children's stories to their toys, such that toy and computer augment one another. the toy engages children in a familiar mode of interaction, while the computer makes a previously passive object active. the children are able to write, edit, collaborate, and share their stories, activities which have particular attraction for female users.
prespe: participatory requirements elicitation using scenarios and photo essays. we describe our ongoing investigation of the prespe (participatory requirements elicitation using scenarios and photo essays) method. prespe enables participants to reflect upon their personal experiences when using systems and create photo-essays based on this reflection. the participants can then analyze these experiences by forming design concepts, envision scenarios by imagining contexts of use, and create artifacts by sketching these scenarios. our case study showed that prespe enabled participants, even those with no prior design education, to create novel ideas regarding system development.
what the best usability specialists are made of. many usability specialists practicing today have not had the benefit of formal education in the field, instead bringing unique value from their various backgrounds. this panel will address how (if at all) individuals' backgrounds contribute to their approach to usability. the panel will also investigate potential career paths and connections between a usability practitioner's background and his or her self-defined successes in usability groups positioned in different organizational structures.
aviva: a health and fitness monitor for young women. in this paper we describe aviva, a prototype health and fitness monitor for young women. the device helps and encourages the user to balance the many aspects of attaining good health, including nutrition, exercise, and the social aspects of health. we describe the process used in developing the aviva monitor as well as our final design.
the future of signs: interactive information, inexpensively! we present an inexpensive, interactive ubiquitous computing system that supports information presentation on demand using a novel "card reading" interaction style. we've deployed this system in our office as a means of supporting wayfinding, sales presentations, project context sharing, and notification (e.g., is there any free food in the kitchen?). however, since the system is essentially an information appliance embedded in our physical space, it also enables people to navigate through our information space-a much more challenging and exciting.
cooperation with a robotic assistant. robotic assistants soon will serve many assistive roles in our everyday lives. it is important to understand how these robots can interact with users, not just as tools, but also as social agents. in a controlled laboratory experiment, we examined cooperation in an effortful task with a robot that displayed one of two personalities. we found that a serious, caring robot induced more compliance than a playful, ejoybale robot on this task. we propose possible explanations and further research.
doodling our way to better authentication. password security often fails in practice because users select predictable passwords. we conducted a study to explore the use of hand-drawn doodle password ("passdoodle"). our findings show that users could recall all visual elements of the doodle as well as they could recall alphanumeric passwords, but most could not perfectly redraw their selected doodles. users perceive passdoodles as easier to remember than alphanumeric passwords; however, they prefer whichever authentication method they perceive to be more secure.
telling stories to computers for document retrieval. the documents users must handle are growing both in number and diversity. however, the ways of organizing and retrieving them remain largely unchanged. given the innate human ability to tell stories, the use of narratives can be a natural and effective way to retrieve documents. to better understand how narratives can be used in this context, a thorough characterization of their contents and structure was obtained from several interviews. then, the results were validated by the evaluation of low fidelity prototypes for story-capture interfaces, allowing us to verify that stories are valid as document-retrieval tools, and the shape those interfaces should take (structured text entry).
quill: a narrative-based interface for personal document retrieval. the ways to manage and retrieve documents have changed little in recent years. browsing is increasingly unpractical and search still is fairly simple, relying mostly on keywords. the wide range of autobiographic information that users remember about their documents cannot be used. we present a new interaction paradigm, narrative-based interfaces, especially well suited for document retrieval. stories make remembering information easier since it appears contextualized in a coherent whole. we describe the quill system, a narrative-based query-formulation interface for personal document retrieval, explaining the user studies and results that led to its design in a sound and effective way. its evaluation confirms that stories can be told naturally, containing the desired information about documents.
an enhanced multitap text entry method with predictive next-letter highlighting. full keyboards are difficult to implement on small mobile devices, and are sometimes replaced by keypads, with multiple characters assigned to each key. the multitap method is often used for text entry on devices with keypads. while conceptually simple, multitap requires one or more key presses to enter each desired letter, and is relatively inefficient from the standpoint of the number of keystrokes required to enter each word. it also requires a significant amount of visual searching to find a needed letter on a key. fortunately, newer methods based on multitap (such as letterwise) have been shown to increase users' text entry efficiency. this paper presents an enhanced multitap method that uses predictive next-letter highlighting to aid visual searching. testing shows that this method, when compared to letterwise, offers increased text entry speeds, fewer errors, and greater novice user satisfaction.
staying in the flow with zoomable user interfaces. this research aims to investigate a collection of interactions in 2d workspaces with the goal of helping users stay in the flow of their activity. these interactions will be explored in the context of two software tools designed to support information work. the first tool, niagara, addresses the early phases of this work that involve organization and synthesis. counterpoint, the second tool, targets the later stages of this work that concern the authoring, delivery, and understanding of presentations.
automatic text reduction for changing size constraints. this paper introduces a technique for viewing text objects under changing size constraints in 2d environments. our approach automatically combines font size reduction and content reduction to preserve legibility of key words. unlike traditional semantic zooming, our approach creates intermediate representations and transitions automatically. the main benefit is that it provides more meaningful views for different object sizes without additional authoring effort.
a user-centered approach to visualizing network traffic for intrusion detection. intrusion detection (id) analysts are charged with ensuring the safety and integrity of today's high-speed computer networks. their work includes the complex task of searching for indications of attacks and misuse in vast amounts of network data. although there are several information visualization tools to support id, few are grounded in a thorough understanding of the work id analysts perform or include any empirical evaluation. we present a user-centered visualization based on our understanding of the work of id and the needs of analysts derived from the first significant user study of id. the tool presents analysts with both 'at a glance' understanding of network activity, and low-level network link details. results from preliminary usability testing show that users performed better and found easier those tasks dealing with network state in comparison to network link tasks.
end-user computing. end-user computing and user programming refer to environments where non-programmers produce complete working computer applications[1]. well-known examples include spreadsheets, the logo "turtle language" for children, and labview virtual instruments for laboratory automation.
seeing fit: visualizing physical activity in context. this paper describes the results of a three month study of physical fitness in the united states. using a literature review, blog readings, interviews, and diary studies, the authors identify key challenges and opportunities for technology to support fitness behaviors. results focus on implications for the design and implementation of personal health visualization software.
multiagents based modelling in graphical user interfaces. a graphical environment that experiments visual programming techniques based on autonomous agents is presented. the model consists of active entities called agents, and passive entities such as behaviours, trajectories, actions, and conditions. the agents have rule based behaviours defined as spatial and temporal volutions. a consistent set of agent structures, actions and rule types is highlighted to support a general oriented visual programming. the model concerns on the notion of trajectory and topological information used in a cooperative evolution to control applications based on real time, processes synchronization, data flow diagrams, graphical animation, metaphorical user interface, artificial intelligence techniques.
usability error classification: qualitative data analysis for ux practitioners. usability evaluations generate large amounts of poorly structured qualitative data, but traditional methods of analysis are often impractical for use by industry practitioners. to address this, we developed a classification of usability issues covering cause, effect, task impact and business impact. in a design project, this has several applications, such as a) enabling practitioners to analyze qualitative data quickly and reliably; b) ensuring that findings can be systematically compared across studies; c) presenting results to clients in terms of potential business impact and its causes; and d) offering recommendations to designers in terms of design errors and their cost. we continue refining the model as we test it in our projects.
managing international usability projects: cooperative strategy. multi-national projects face many challenges, such as finding and coordinating resources, managing logistics in different countries, defining research methodology, controlling project cost, and dealing with cross-cultural issues. project managers can choose among different approaches to such ventures: centralized, decentralized and cooperative. we discuss our experience in managing international usability teams using the cooperative strategy. with four participating countries and three languages used for conducting user studies, bringing the project together becomes both a challenge and a valuable lesson. the report details the strategy applied and specifically addresses the setup and data analysis stages. we reflect on our experience from two viewpoints: of the global project manager and of a local coordinator. for others to draw on our learning, we summarize both positive and negative project lessons.
a tangible architecture for creating modular, subsumption-based robot control systems. we present a new modular, reconfigurable architecture for building and interacting with subsumption-based robot controllers. a set of modules - with embedded sensing, communication and processing capabilities - divide up the subsumption architecture into self-contained behavioral layers that subsume each other according to the way the modules are physically stacked. on-board indicators of the internal state of each module help in programming and understanding the behavior of the robot in real-time. this offers novices, in particular children, a new environment to learn about a powerful metaphor for programming robots and other interactive systems in a hands-on and exploratory manner. we will also discuss a prototype implementation of this architecture and the results of a preliminary user study using the prototype with a group of children.
peddo: steps to a healthy lifestyle. studies show that 14-to-40 year olds are spending more time at the computer and less time exercising. using contextual design, our group tackled the challenge of motivating people in that demographic group to exercise more. the result is the "peddo" (latin ped: foot, persian do: two) - a device which encourages physical activity of its users in an entertaining way and reinforces positive exercise habits.
culture issues and mobile ui design. culture anthropologists have identified fundamental dimensions of world cultures. uis designers have identified basic components of uis. mobile devices must map these dimensions to components to cope with global product and service development. ultimately, tools may emerge to facilitate tuning designs per culture.
international usability evaluation sig: issues and strategies. applications, interfaces, and devices are increasingly customized to appeal to users with vastly different needs, desires, and values. in the past, products were built on the basis of technical proficiency, education, and age; now, product designers are embracing culture.how can human factors professionals support this work? this sig will examine issues and strategies to be considered when evaluating product interfaces in two or more countries or cultures.a panel of practitioners will review some of the problems they faced in selecting and customizing methods for international usability design. sig participants will then be invited to brainstorm and contribute their own "war stories" and experiences.it is expected that this sig will generate 1) a range of case studies and 2) a reference list of people working in different countries and cultures who can help one another do international usability evaluation.
designing a multimedia conversation aid for reminiscence therapy in dementia care environments. as world populations grow older the incidence of alzheimer's disease (ad) and other dementia related illnesses increases (approximately 18 million sufferers worldwide). one particularly devastating effect of ad is the loss of short-term memory, which radically impairs the sufferer's ability to communicate. people with dementia, however, often retain a facility for long-term memory that can function strongly given appropriate stimulation.project circa (computer interactive reminiscence and conversation aid), utilizes interactive multimedia (including audio, video, animation and quicktime vr environments) to stimulate long-term memory to prompt verbal and non-verbal communication. we will demonstrate how - through good design practice, interdisciplinary collaboration and a user-centred approach to design - we can invest reminiscence therapy with technology-led solutions to assist our participating test groups (30+ people with dementia and 40 carers) in conversational settings. we will demonstrate how this adaptable, expansive, immediate and engaging tool can contribute significantly to 'quality of life' in dementia care environments.
meeting the challenge of measuring return on investment for user centered development. to demonstrate return on investment (roi), usability organizations must measure their impact on business-wide metrics such as quality, innovation, cost, and customer satisfaction. although much work has focused on calculating costs and benefits of specific projects, demonstrating roi of a usability program remains a difficult task. to build a successful measurement program for roi, a framework is needed in which value can be explored, measured, and analyzed from different perspectives. sig attendees will explore the foundations of such a framework by exchanging information on the challenges they face as they demonstrate roi, suggesting possible solutions and measures, and identifying important business-wide goals.
managing the information technology infrastructure: hci design for network and system management applications. all too often the people responsible for the care and feeding of the information technology infrastructure are poorly supported by the very technology they must manage, even as the popularity and use of networks (such as for the world wide web) grows. corporate mis staffs spend billions of dollars just on managing their computing infrastructures, and still they must continually cope with ineffectual products that do not support them in their work. moving a single user within a corporate network is estimated to cost an average of $2000.00. recent outages in america online service are examples of how failures in network management can affect thousands of end users. this special interest group (sig) will provide an opportunity for hci practitioners and researchers in the domain of network and system management to share information about the problems faced by operators, system managers, administrators, and end users, and to explore new techniques in user interface design that might provide better support in the future.
sharing the big apple: a survey study of people, place and locatability. with the advancement in technologies to locate individuals, there has been an emergence of information systems that link people-to-people-to-geographical-places, labeled p3-systems. while various p3-system services have been proposed and deployed, there is limited knowledge on people's desires and attitudes towards such services. we used the p3-systems framework to guide a survey study of the impact of 'place' on people's social information needs and willingness to share personal location data. at fourteen different place types (restaurant, post office, etc.) in manhattan, new york, we surveyed 509 individuals over 3 weeks. the vast majority of respondents expressed a desire for and willing to share their personal location data. e.g., 77% of respondents were willing to reveal their current location to others (17% with complete strangers).
profile before optimizing: a cognitive metrics approach to workload analysis. the intelligence analyst (ia) community will soon be the designated users of many new software tools. in the multitasking world of the ia, any one tool cannot be permitted to greedily consume cognitive resources. this situation requires a new approach to usability assessment; one that profiles the moment-by-moment demands placed on embodied cognition by a given software tool during task performance. the approach we have taken relies on families of cognitive models that interleave cognition, perception, and action at the 1/3 to 3 sec timescale. this is the level of analysis where embodied cognition forms interactive routines that adapt to the cost-benefit structure of the software tool. our proof-of-concept is a model that performs a task that the ias find challenging. from the trace of the model, we derive a cognitive metrics profile that pinpoints dynamic changes in workload demands on human cognitive, perceptual, or action systems.
perceptions of proximity in video conferencing. proximity is used as a non-verbal signal in face-to-face interaction. it is unknown whether similar information may exist during desktop video conferencing and if so what factors may regulate it. an experiment was conducted to compare the relative impact of image size and the scope of the image on users' impressions of proximity. the results demonstrate that participants felt that changing the focal length (zoom) of the camera could make the remote person appear closer or further away. participants appeared to use the image size of the remote person per se to determine their apparent proximity, rather than the proportion of the image taken by their face.
a reduced qwerty keyboard for mobile text entry. in this paper we describe a specialized keyboard for text entry that maps four rows of a standard keyboard onto the home row, with different characters encoded via modifier keys and multi-tap input. use of the keyboard also relies on lexicon-based disambiguation. this design has two motivations: limiting physical space requirements and capitalizing on user knowledge of the standard qwerty keyboard layout. the resulting "stick" keyboard is between 15% and 25% of the size of a standard keyboard. in a preliminary empirical study, users reached half of their normal typing speed using lexicon-based disambiguation (22.5 wpm) and a reasonable but lower speed with multi-tap input (10.4 wpm) with only a few minutes of practice.
camping in the digital wilderness: tents and flashlights as interfaces to virtual worlds. a projection screen in the shape of a tent provides children with a shared immersive experience of a virtual world based on the metaphor of camping. rfid aerials at its entrances sense tagged children and objects as they enter and leave. video tracking allows multiple flashlights to be used as pointing devices. the tent is an example of a traversable interface, designed for deployment in public spaces such as museums, galleries and classrooms.
three robot-rooms: the awe project. we describe innovative new work in the development of an "animated architecture." specifically, we describe our early research aimed at the creation of intelligent, programmable, physical spaces supporting working life. our research takes advantage of recent developments in hci and continuum robotics to enable humans to exploit emerging technologies and adaptively alter both the ambience and functionality of their environments.
dynamic dimensional feedback: an interface aid to business rule creation. we examined the efficacy of providing dimensional feedback in the user interface as people construct business rules. business rules often involve objects that have dimensions (e.g., area, cost, weight) and may entail complex calculations on these objects. such mathematical expressions are error prone. we designed and tested a novel interface utilizing dimensional analysis to provide advice on expected dimensions, and error feedback on incorrect usage of dimensional objects. experimental studies were carried out in which subjects used the interface to create rules based on word problems. in a balanced design, rule creation with dimensional feedback was compared to rule creation without such feedback. we found evidence for the usefulness of such feedback. in addition we observed the need to support higher level 'proxy variables' and stepwise definition of complex rules. the findings have implications beyond business rules tools and may be applied to any system requiring mathematical expressions with dimensional objects.
ears and hair: what headsets will people wear? many different audio headsets are commercially available. to choose a headset for a short-term use environment, we conducted a pilot study to elicit end-user criteria for headsets. we discovered a number of severe end-user issues with less traditional designs, and concluded that a minor variant of a traditional design is more appropriate for our application than many of the more exotic options that have recently become available.
increasing transaction processing efficiency by automating an asynchronous processor. moving simple yet highly repetitive manual tasks to an asynchronous automated validation process increased data processing productivity. contextual analysis of manual processing actions revealed opportunities for timesaving.
awarenessmaps: visualizing awareness in shared workspaces. in cooperative activity users require information about their cooperative environment. awarenessmaps provide the members of shared workspaces with an overview of users and shared documents: the peoplemap shows an array of pictures of active users fading out over time; and the documentmap provides a schematic overview of the structure of a shared workspace and indicates recent changes.
leaders leading? a shift in technology adoption. in the past, most early hands-on users of interactive software in organizations were individual contributors. managers as early adopters is a new trend with significant implications for design and use. although managers and executives have always been involved in acquisition decisions, they generally delegated use to support staff. only later if at all did they become hands-on users. this is changing as new generations of managers and technology come to the fore. examples and implications are presented.
why chi fragmented. i have been active in sigchi since 1983, serving on the executive committee and many conference and program committees. after editing acm tochi for six years, i explored the history of chi and related fields. the "conference-centered" model unique to u.s. computer science, wherein little published research reaches journals, and uncertainty regarding hci's academic niche have created an unusual situation. i propose some paths forward.
human computer interfaces for autism: assessing the influence of task assignment and output modalities. several experimental studies have shown the usefulness of computers for autism, but software design remains poorly documented. our multidisciplinary research focuses on educational hci for autism. we compared two domains of learning: social dialogue understanding and spatial planning, our hypothesis being that people with autism will be less skilful in the first than in the second domain. two sets of exercises were designed for each domain: one for training purposes and the other for performance assessment before and after training. we also tested the influence of the following output modalities: text, images, speech synthesis, visual and auditory feedback. each exercise produced log files informing on duration, number of trials and successes. so far, eight teenagers with autism have completed a 13 week training program with one session a week. first analysis of log files suggests a significant progression in dialogic understanding but not in spatial planning; nor was significant influence of output modalities found.
individual differences in internet search outcomes and processes. a study was conducted, with 180 participants, to evaluate whether individual differences in basic cognitive abilities (i.e., spatial and verbal ability), attitudes towards computers, and prior experience with computers influence peoples' ability to search for and find information on the internet. spatial and verbal ability, as well as attitudes towards computers, influenced the accuracy and speed of internet search. current analyses are focusing on whether cognitive abilities and attitudes influence component search processes, as well as overall accuracy and speed.
a reference model for multimodal input interpretation. this paper proposes a reference model for multimodal input interpretation to understand multimodal input in multimodal interactive systems. the paper gives details of the functionality of each of the layers within the model and suggests its validity through development of multiple multimodal systems with same architecture.
jamspace: a networked real-time collaborative music environment. the motivation, design, implementation and analysis of a networked environment for real-time music collaboration are presented. jamspace provides a simple hardware and software interface that allows novices to play music together anonymously from isolated locations connected by a local network. the low-latency conditions of a local network allow for real-time rhythmic collaboration. this in turn facilitates satisfaction of the design requirements of accessibility to novices as well as privacy and anonymity.
from the personal to the profound: understanding the blog life cycle. this ongoing research project investigates the changes that occur to weblogs (blogs) throughout their lifespan. it examines both the markers that indicate a particular phase of its existence in our emerging life cycle model and the drivers that move the community through those cycles. emphasis is placed on identifying likely causes for abandonment at each phase. implications of this research are both social, promoting the health of the blogosphere in general, and technical, appropriately mapping tools to correct life cycle stages.
the power-aware cord: energy awareness through ambient information display. in order to support increased consumer awareness regarding energy consumption, we have been developing new ways of representing and interacting with energy in electric products intended for domestic environments. the 'power-aware cord' is a re-design of a common electrical power strip that displays the amount of energy passing through it at any given moment. this is done by dynamic glowing patterns produced by electroluminescent wires molded into the transparent electrical cord. using this fully functional prototype, we have been investigating how such ambient displays can be used to increase energy awareness. an initial user study indicates that the power-aware cord is a very accessible and intuitive mean for better understanding energy consumption. future work includes further development of the mapping between load and visual pattern and in-depth studies of user perception and learning over time.
accounting for individual differences through games: guided adaptive multimedia editing system. multimedia communication is influenced by increasing complexity and reach of information and by a rapidly growing user population. due to these developments average authors of electronically published media have little expert knowledge in multimedia presentations. they are also confronted with considerable individual differences of recipients in culture, social life, education, psychology and physiology. in order to compensate for these shortcomings it is necessary to integrate interpretation and interaction abilities of individual users into future presentation and editing systems. we are developing a chart editing system which generates critics by user request. these critics are based on a user model, on expert knowledge in chart editing and on the currently edited chart. the system helps the author to avoid commonly made mistakes. it empowers recipients to adjust certain parameters (e.g.: colors) to their individual abilities and needs.
eewww!!: tangible interfaces for navigating into the human body. tangible interfaces have the potential to support learning for non-expert users, ease 3d navigation, and foster collaboration. we developed two physical devices aimed at school children for navigating a 3d virtual model of the human body. results from a 40-subject user study suggest that these devices can encourage collaboration and improve the learnability of a navigational interface.
exploring the design and use of peripheral displays of awareness information. peripheral displays allow users to monitor an information source while focusing on a separate primary task. in this paper, we present our work investigating what form peripheral displays of awareness information from instant messaging programs may take and the role these displays could have in existing communication practices. we describe several prototypes of tangible, aesthetic displays of awareness information. a focus group involving users of instant messaging software revealed that the awareness information component of the software (such as sounds or flashing windows) is often used to trigger communication through more heavyweight means such as telephone or face-to-face conversation.
reinventing the inbox: supporting the management of pending tasks in email. email was originally designed as a tool for asynchronous communication. however, its current usage goes far beyond that. one of the most commonly performed activities in email is the management of pending tasks. this research focuses on how to support this activity in email and explores alternative solutions that use different external representations of messages and associated tasks.
email task management styles: the cleaners and the keepers. email has become overloaded as users make use of email tools for performing a wide range of activities. previous studies have demonstrated the different strategies employed by email users to manage messages. however, we have little information regarding how to explain those differences between users.the research described in this paper seeks to gain understanding of individual differences in email behaviour. we present results from a questionnaire-based study, which focused on how email users dealt with messages that relate to future tasks or events. we identified two types of user, defined by how they dealt with such messages: the cleaners and the keepers. the difference between these two groups can be attributed to differences in email experience and requirements for flexibility of closure. the ultimate goal of such research is to be able to predict differences in email use and to inform email user interface design and we discuss possible ways in which this could be done.
indirect assessment of web navigation success. despite much research on hypertext and web navigation, relatively little is known about the relationship between web navigation strategies and success. we present two exploratory studies designed to explore the relationships between several web navigation metrics that are based on similarity to an optimal path to predict task success. the data suggest that the relationships between these measures depend on the particular web navigation task.
an examination of user perception and misconception of internet cookies. proper cookie management methods have long been the source of frustration to consumers and researchers alike. a primary reason for this challenge is the ability for cookies to be both beneficial and malicious. because of this duality, a subjective component is required to appropriately deal with cookies. in this paper, we present results from focus group sessions we conducted to explore problems of cookie management. based on some of our observations from this work, we discuss social and technical considerations and conclude that an increase in awareness is the best partial solution to privacy problems associated with cookies.
swordfish: user tailored workspaces in multi-display environments. this paper presents a novel interaction metaphor for multiple display environments (mdes) called lightweight personal bindings. this approach enables users to easily bind edges from one display to another and move seamlessly between displays. the goal of this work is to support collocated collaboration in a dynamic multi-display environment while accommodating users' personal preferences. with lightweight personal bindings, each user can choose their own display connections and create a personalized mde. this approach also helps manage changes in the environment as devices enter, move, or leave.
my mde: configuring virtual workspaces in multi-display environments. a low fidelity study was conducted to investigate how users envision configuring their virtual workspace in a multiple display environment (mde). the results of a low-fidelity prototyping study revealed two primary virtual workspace organisation patterns: environment-centric and user-centric workspaces. these depict different ways in which users conceived they would configure multiple displays into a single cohesive virtual workspace. the paper then discusses future design implications, specifically the need for the support of multiple user preferences in collaborative mdes.
an automatic method for arranging symbols and widgets to reflect their internal relations. the two data visualization techniques cluster analysis and voronoi tessellation are combined to automatically arrange objects, e.g. the widgets of an interface, so that their positions within a given area reflect their internal relations. the method is illustrated as it arranges three sets of objects.
what's in a barcode? informed consent and machine scannable driver licenses. drawing on theory and methods of value sensitive design [2] we investigated the social and value implications of the addition of barcodes to machine scannable driver licenses. in particular, we focused on the value of informed consent, user knowledge, and understanding. twelve washington state driver license holders were interviewed. results indicate that participants in this study were largely unaware of the nature of the information in the barcode, and the potential uses of such information. moreover, with increasing knowledge, participants developed a sense of concern regarding the potential misuse of information. in our discussion, we focus on the importance of informed consent and design suggestions for machine scannable driver licenses.
snapshots from a study of context photography. we developed context photography to provide an alternative photographic experience. sensors gather real-time context information which visually affects a photograph as it is taken. in an exploratory study, we investigated how people would experience, use and understand a context camera and how it differs from regular digital photography. we here present an extract of the study, where one participant experienced context photography as being "more real" than post-hoc image manipulation and that it added a new dimension to picture taking.
including accessibility as a component of web-related research: ensuring that the fruits of your work will be usable by all. great strides have been made in improving the accessibility of the web to persons with disabilities. this has been largely possible through the efforts of the world wide web consortium's (w3c) web accessibility initiative (wai) and the development of web standards and guidelines that promote the creation of content, authoring tools and user agents that are accessible. given that the web and related technologies are a dynamic proving ground for user interface research, ensuring that these new developments are usable to the widest possible audience can be a challenge, to both the research community and the end-user. the w3c wai research and development interest group (rdig) was chartered to examine emerging, web related technologies, still in the research stage and, through a series of virtual workshops, explore how accessibility can be incorporated at an early stage to ensure all users can benefit from promising developments, (e.g., technologies coming from the area of ubiquitous computing or multimodality).this sig will examine the progress of rdig and encourage discussion by interested chi researchers on the role of accessibility in their work.
does it matter if you don't know who's talking?: multiplayer gaming with voiceover ip. voiceover ip (voip) now makes it possible for people in distributed online multiplayer games to talk to each other. this might not only influence game performance, but also social interaction. however, using voip in multiplayer games can often make it hard to know who is talking, an issue that other researchers have found to be problematic. in a 10-week study of a fixed group of adult gamers, we found that not knowing who is talking affects game performance differently according to the type of game. in team-based war games, it can have a negative effect both on learning and coordination, but in race games, where individual rather than teams compete, it appears generally not to matter. in contrast, the impact of not knowing who is talking on social interaction is the same regardless of game type: while the social experience can be highly enjoyable, it is difficult for gamers to get to know each other. we consider the design implications for enhancing both game performance and social interaction.
teaching and learning ubiquitous chi (uchi) design: suggestions from the bauhaus model. we describe a design pedagogy under development. it is a) interdisciplinary, b) inspired by success in teaching architectural design, c) motivated by the rapid maturation of chi design and computing, d) directly connected to what we call ubiquitous-computer-human interaction or uchi, and e) based on larning design by building. we have brainstormed about how we might merge significant aspects of our disciplines (architecture and hci) into a joint design course; we both agree that gropius' 1922 [3,4] pedagogical model for the bauhaus applies to learning architecture and uchi design. we invite feedback, ideas, and collaboration from the hci community on this work in progress.
communities of design practice in electronic government. as we move towards more online governmental services-electronic government or e-government-our information technology (it) and human-computer interaction (hci) designs must both broaden and deepen. in georgia, we have fostered communities of design practice (cdps) that focus on it and hci design at the statewide enterprise level through the georgia digital academy (gda). in this study, we utilized observational methods and a participatory analysis of the cdp formation in the gda. our findings and conclusions converge with the growing body of knowledge on hci communities of practice. we report our results and recommendations on how cdps might be utilized to build effective e-government.
integrating models of human-computer visual interaction. predicting visual search behavior in human-computer interaction is a challenging problem. it is important for predictive modeling of human-computer interaction to integrate the visual search strategies identified in individual models in order to predict users' visual interaction with a variety of complex, real-world layouts. individual research efforts have done well in developing models that predict users' visual search behavior for a single well-defined task. considering the large variety of visual layouts users can encounter, many visual search strategies can come into play during visual search. this dissertation investigates principles for integrating strategies of visual search. these principles will be used to integrate four models of visual search from hci literature.
link colors guide a search. while much basic research exists on the effects of various visual properties on visual search, the application of such research to real-world tasks is lacking. the purpose of this research is to address the lack of empirical validation for design guidelines that affect visual search. one common design element used in web interface design is link color. the general research question asked is how text color affects visual search. this research demonstrates, with reaction time and eye movement analysis, the dramatic but imperfect control a designer has on guiding the attention of users with text color. experimental support for the differentiation of visited link colors is presented, along with analyses of the advantages provided by differentiating link colors.
human-robot speech interface understanding inexplicit utterances using vision. speech interfaces should have a capability of dealing with inexplicit utterances including such as ellipsis and deixis since they are common phenomena in our daily conversation. their resolution using context and a priori knowledge has been investigated in the fields of natural language and speech understanding. however, there are utterances that cannot be understood by such symbol processing alone. in this paper, we consider inexplicit utterances caused from the fact that humans have vision. if we are certain that the listeners share some visual information, we often omit or mention ambiguously things about it in our utterances. we propose a method of understanding speech with such ambiguities using computer vision. it tracks the human's gaze direction, detecting objects in the direction. it also recognizes the human's actions. based on these bits of visual information, it understands the human's inexplicit utterances. experimental results show that the method helps to realize human-friendly speech interfaces.
knowledge sharing, maintenance, and use in online support communities. widespread adoption of collaborative authoring tools (such as wikis) by online communities has fostered new ways of storing, sharing, maintaining, and using community knowledge. my dissertation research examines the effect and potential use of these shared knowledge repositories within online technical and medical support communities using short-term ethnography (including content analysis and interviews), surveys, and quantitative analysis of behavior traces. i characterize the key technological mechanisms, and the processes and social norms at play. i then use this knowledge to propose best practices and novel social and technical designs.
mixed interaction space: designing for camera based interaction with mobile devices. in mobile devices, such as mobile phones and pdas, an integrated camera can be used to interact with the device in new ways. in this paper we introduce the term mixed interaction space and argue that the possibility of using mixed interaction spaces is what distinguishes camera-based interaction from other types of sensor-based interaction on mobile devices. we present our implemented applications, and related work that use mixed interaction spaces. based on this we address how mixed interaction spaces can have different identities, be mapped to applications, and how it can be visualized.
use your head: exploring face tracking for mobile interaction. in this paper we present how face tracking can be implemented on mobile devices. our main contribution is to present how face tracking on mobile systems can be used as a multi-dimensional input technique and to demonstrate how this can be used in different mobile applications. we present at set of different applications based on the tracking, and discuss current and future advantages, challenges and problems with face tracking as input device for mobile systems.
nutristat: tracking young child nutrition. our childhood eating patterns strongly affect our lifelong health. recently, type ii diabetes emerged as a national health crisis in america that can be prevented almost entirely by improving the quality of child nutrition. in this paper, we describe the scenario-based design process used to build nutristat, a system for tracking young child nutrition for children with multiple caregivers. nutristat empowers parents to collaboratively monitor a young child's diet and consequently provide more well-rounded nutrition.
visual, attractive, and luminous: learning japanese hand alphabets for elementary school pupils. in this interactive poster, we will demonstrate how the visual interface of practice: yubimuji aiueo (pya) works in a practical classroom and/or homework environment. pya aims to let ordinary elementary school pupils learn the essence of the japanese hand language system with visual, attractive, and luminous manner. yubimoji and aiueo respectively stand for japanese words of "hand language" and 'alphabets.'
object-oriented models in user interface design. objects have been used as the informal basis for the conceptual design of interactive systems for at least a decade. given recent advances in the development of object-oriented modeling languages and methodologies, it is now timely to re-evaluate the role of object-modeling during the process of user interface design.
the unless switch: adding conditional logic to concept mapping for middle school students. qualitative concept maps are useful for sharing the structure of a domain and for assessing students' understanding. while concept maps made from links and nodes depict static causal relationships between concepts quite well, they provide little support for displaying conditional logic and thresholds for causation. in this paper, we describe the process of incorporating a representation for conditional reasoning into betty, a computer agent students teach via concept maps. betty helps students formalize their knowledge of a domain by acting as a novice learner. students use betty to construct and assess their knowledge of science topics.we tested several prototypes combining conditional logic with concept maps and found that people had difficulty keeping conditional states and conceptual nodes separate. in the end, the "unless switch" provided the closest semantic parallel to the type of reasoning we wanted students to learn and generated the least amount of confusion.
assessing the attractiveness of interactive systems. qualities beyond usefulness and traditional usability are increasingly being recognised as important in hci. a common understanding of which factors affect the overall user experience and how they interrelate is still to be established. in a theory-led approach, users' perceptions of qualities that together contribute to the overall 'attractiveness' of a system are investigated. an empirical study with three live websites from stanford university demonstrates a halo effect of aesthetics on perceptions of usability and content. however, the perception and impact of aesthetics are significantly affected by users' backgrounds and tasks.
a responsive and persuasive audio device to stimulate exercise and fitness in children. designing to stimulate health and fitness in children proposes particular challenges because children lack direct control over their environment. additionally, children respond more to activities emphasizing recreation over education. this paper details the design and development process for children, highlighting design choices with research from industry, parents and children. the end product is a responsive and persuasive audio player that controls and varies music tempo based on measured activity level. this device makes use of music's natural ability to fuel activity, and it gives children a way to directly control some portion of their environment. additionally, it delivers increased exercise under the disguise of fun and recreation. this paper contributes to the hci design process for children by showing how to develop persuasive technologies to implicitly succeed a specific goal without explicitly addressing an existing problem.
alice sat here. in this paper, we describe alice sat here, a telerobotic installation in which participants in physical space and cyberspace are afforded extended means of interaction. using live video served to the world wide web, telerobotic camera control (pan and tilt controlled remotely over the web), and a wheeled electric throne driven by gallery visitors, alice sat here becomes an interface at the intersection of physical space and cyberspace. by designing an installation as a physical metaphor for the web, we hope to sensitize the public to the dynamics at work on the web (surveillance, control), and to challenge the collective imagination of the kinds of experiences the web can offer.
from mental effort to perceived usability: transforming experiences into summary assessments. in many cases, practitioners and researchers of human-computer interaction and usability engineering rely on users' subjective product quality assessments. such an assessment of, for example, perceived usability is believed to summarize previous experiences made with the according software. the present study shows that such summary assessments of perceived usability do not reflect a whole experiential episode, but rather its most recent incidents. additional measurement strategies, such as repeated measurements of perceived usability throughout the experiential episode, are explored.
ineractive 3d presentations and buyer behavior. this paper shows preliminary results on how interactive 3d product presentations affect buyer behavior in e-commerce applications over the internet. we conducted two experiments involving simulated online shopping trips, in which subjects saw some products with 3d presentations and made product choices. the results show that the availability of interactive 3d product presentations instead of still images may affect some important aspects of buyer behavior, including the amount of time spent examining products and purchase likelihood.
artificial intelligence techniques in the interface to a digital video library. for the huge amounts of audio and video material that could usefully be included in digital libraries, the cost of producing human-generated annotations and meta-data is prohibitive. in the informedia digital video library, the production of meta-data supporting the library interface is automated using techniques from artificial intelligence (ai). by applying speech recognition, natural language processing and image analysis, the interface helps users locate the information they want and navigate or browse the digital video library more effectively. specific ai-based interface components include automatic titles, filmstrips, video skims, word location marking and representative frames for shots.
privacy gradients: exploring ways to manage incidental information during co-located collaboration. this research introduces privacy issues related to the viewing of incidental information during co-located collaboration. web browsers were the representative application used in this research as they have several convenience features that record and display traces of previous web page visits. a one-week field study examined how individuals perceive privacy needs relating to the later incidental viewing of traces of their browsing activity. participants used a 4-tier privacy gradient to classify the privacy of their actual web browsing. the results revealed per window patterns of privacy during browsing with streaks at given privacy levels and relatively few transitions between levels. management of incidental information is a complex problem due to multiple viewing contexts, individual differences, and the large volume of information. these privacy patterns suggest that a semi-automated approach to privacy management may be feasible.
web browsing today: the impact of changing contexts on user activity. although web browsing behaviour was studied in detail in the mid-to-late 1990s, few recent results have been reported. the nature of web browsing has changed significantly since these early studies, both in the profile of the typical web user and in the context of their browsing (e.g. location, connection speed, web browser features). this paper reports on per-session and per-browser window usage, such as the number of pages visited and the speed of browsing. some of our findings differ from previously published results that continue to motivate research in this area. our research indicates that changes in user behaviour, such as the magnitude of web browsing activity, may place restrictions on web-browser related applications.
from cookies to puppies to athletes: designing a visual audience voting system. we describe the design process taken and prototype developed for a system supporting audience voting at the summer olympics. in our examination of issues related to the expression and capture of audience votes, we utilized informal focus groups, interviews with experts, and user studies comparing voting formats. our proposed solution involves displaying results on large screens. this provides the context for visual audience interaction through the use of ranking booklets. the audience input is determined through image analysis of the audience.
documenting and understanding everyday activities through the selective archiving of live experiences. the goal of this research is to build upon the work of capturing data in structured and planned settings to develop socially appropriate ways to archive important life experiences during unexpected, unstructured, and sometimes informal situations. this work involves three significant phases: formative studies to understand the data capture needs of particular populations of users in these situations; design and development of a technical architecture for capture and access in these settings coupled with design and development of applications for two specific domain problems; and evaluation of this solution as it pertains to these domain problems.
practices for capturing short important thoughts. in this paper we describe a user study designed to understand current practices for recording and utilizing information in everyday life. we describe a subset of the results that suggest that improving on current practices will require physical and digital artifacts, flexibility, multi-modality, and ubiquity.
experience buffers: a socially appropriate, selective archiving tool for evidence-based care. diagnosis, treatment, and monitoring of interventions for children with autism can profit most when caregivers have substantial amounts of data they can easily record and review as evidence of specific observed behaviors over time. through our work with one prototype system and interviews with caregivers, we have recognized the importance of socially appropriate ways to add rich data to the information recorded by caregivers. analysts must be able to view incidents as they occurred without unnecessarily burdening caregivers and other children with always-on recording of data about them. in this paper, we introduce experience buffers, a collection of capture services embedded in an environment that, though always on and available, require explicit user action to store an experience.. this creates a way to balance the social, technical, and practical concerns of capture applications.
measurement of user frustration: a biologic approach. this paper describes the use of facial emg to provide a continuous measure of the user's emotional state. facial emg was recorded while female users performed five tasks to one of two web sites. frustration index scores were developed from the corrugator emg data by calculating a percentage score of a pre-task baseline. as predicted, the frustration index was greater for (1) novices as compared to experienced users, (2) incorrect as compared to correct answered tasks, and (3) for the web site that was rated more difficult. the frustration index was able to provide important information on web page performance.
searching and browsing text collections with large category hierarchies. a new user interface has been developed that allows users to make use of large category hierarchies for search and browsing of retrieval results for information access. the key insight is the separation of the representation of category labels from documents, which allows the display of multiple categories per document.
efficient user interest estimation in fisheye views. we present a new technique for efficiently computing degree-of-interest distributions to inform the visualization of graph-structured data. the technique is independent of the interest distribution used and enables fluid interaction with very large data sets (over 100,000 nodes).
acm siggraph user experience initiatives. there has been a substantial growth in the number of educational and networking opportunities for professionals in the computer graphics and related fields in the last three years. one of the fastest areas of growth is in the field of computer user experience and the development of cultural communities through the advent of portal technologies, blogs, and wikis.
how do people organize their desktops? knowledge workers today have a lot of digital documents to manage, and most employ some sort of organizational system or scheme to help them. most commonly used software provides the ability to create a hierarchical organization, but the appropriateness of this structure for personal digital document management has not been established. this research aims to understand how people currently organize their documents, identify the strengths and weaknesses of current systems and explore the usefulness of other information structures. this should provide insight into how personal digital document management systems can be made more usable.
the route to the sea for user value. hci managers with experience in delivering user value in shipping products that make good businesses will discuss the hazards that the product development process holds, and what it takes for hci managers to ensure that user value remains in the products throughout that process. (see also the companion panel: "building user value into the business case.").
building user value into the business case. concepts that are of great value to users are an important part of making great products. however, unless the concepts make sense for businesses, they will never become products, no matter how good they might be for users. this panel looks at this harsh reality from the point of view of product managers. it addresses the question of what makes business sense and how user value plays in making that case. product managers with experience in making such cases will discuss the practical realities of making effective business cases, the role of user value, and what hci professionals can do to help managers in making a mutually satisfying case. (see also the companion panel: "the route to the sea.".
the chi management community. this sig will provide those interested in the interplay between management and hci the opportunity to explore this subject and the ongoing development of the management community at the chi conferences.
dating example for information architecture. this paper provides the documented explanations of our submitted poster to chi 2003 about the process of information architecture (ia). the general theme of chi 2003 was to deliver an innovative way of presenting ia in order to better the ia community through a given theme or use of a metaphor. our poster, ia dating example for information architecture, explains how ia is related to everyone's daily lives. in this document, we describe the similarities of ia in the web field and in dating in each step of the ia process.
evaluating paper prototypes on the street. the evaluation of paper prototypes is normally conducted in controlled settings such as a usability lab. this paper, in contrast, reports on a study where evaluations of a paper prototype were performed on the street with young adults. we discuss the merits of this approach and how it impacted the design process. a key finding is that the street location can enfranchise people who may otherwise be under-represented in design. we conclude that evaluating paper prototypes in public, street settings is feasible and informative.
creating organization-specific usability guidelines. working with a large information technology organization in industry, we have been investigating how a repository of organization-specific usability guidelines can be created and used to produce high quality end-user applications. our approach is to create tools and methods in which software development organizations can develop and evolve usability guidelines based on the kinds of applications they develop. this information can then be used to match customer requirements to specific interface techniques that have proven effective for similar users and application domains. this is supported through a case-based system that attaches experience cases to guidelines to help find, explain, specialize, and extend usabiltiy guidelines.
interactive web usage mining with the navigation visualizer. web usage mining, the analysis of user navigation paths through web sites, is a common technique for evaluating site designs or adaptive hypermedia techniques. however, often it is hard to relate aggregated clusters or measures to actual user navigation behavior. by contrast, basic graph-based visualizations of user navigation paths are easier to interpret, but it is difficult to find effective views that convey all the required information. in this paper we present the navigation visualizer, a web usage analysis tool that combines the two approaches. the navigation visualizer makes use of the rich data set that is collected by the scone proxy-based web enhancement framework and facilitates dynamic selection of the data and interactive exploration with various layout mechanisms, color codings and markers. several aggregated measures can be calculated and exported to statistical and data mining packages.
a process for creating the business case for user experience projects. the ebay user experience & design (ued) group has had significant success sponsoring successful user experience (ue) projects, in large part by creating and communicating the business case for these projects. this paper presents the process the ebay ued group uses to get projects approved and how these projects are evaluated for success. this paper also refers to specific projects as examples that followed this process.
usability inspections by groups of specialists: perceived agreement in spite of disparate observations. evaluators who examine the same system using the same usability evaluation method tend to report substantially different sets of problems. this so-called evaluator effect means that different evaluations point to considerably different revisions of the evaluated system. the first step in coping with the evaluator effect is to acknowledge its existence. in this study 11 usability specialists individually inspected a website and then met in four groups to combine their findings into group outputs. although the overlap in reported problems between any two evaluators averaged only 9%, the 11 evaluators felt that they were largely in agreement. the evaluators perceived their disparate observations as mulitiple sources of evidence in support of the same issues, not as disagreements. thus, the group work increased the evaluators' confidence in their individual inspections, rather than alerted them to the evaluator effect.
designing an on-line map tool for dutch farmers. this paper describes our real life experience in designing an on-line map user interface for the dutch farmers. the project challenge was to design a simple user interface for advanced mapping technology in a critical schedule. the domain involved understanding of several technical and legal constraints. we studied the context of use, designed the user interface concept, evaluated a prototype and provided the developers with detailed specifications during a four week period.
time design. the goal of this workshop is to explore and support the design of temporal aspects of interactive systems. time design is an emerging research and development domain that emphasizes the functional, causal role of time in human-device interaction. it draws on a diverse literature on time in cognitive psychology, psychophysics, sociology, computer science, engineering, human factors and hci. contributions from each of these disciplines are invited so that preliminary design recommendations can be distilled and an interdisciplinary research agenda can be defined. the discussion will be centered around several scenarios that highlight the temporal characteristics and requirements of different application domains.
activity rhythm detection and modeling. we present an algorithm for detecting and modeling rhythmic temporal patterns in the record of an individual's computer activity, or online "presence." the model is both predictive and descriptive of temporal features and is constructed with minimal a priori knowledge.
asynchronous learning networks: priorities for software development. asynchronous learning networks (alns), a form of elearning, use computer-mediated communication to sup-port the delivery of courses in which anytime, anywhere access to interactions among the students and between the instructor/facilitator and the students are key ele-ments. what constitutes an aln software platform that supports and enhances collaborative learning? how can existing learning theories and small group interaction models guide the design of effective environments for alns? what kinds of new software tools would best im-prove support for "teacher immediacy" behaviors and active, collaborative learning by students? what are the most important interface issues to accommodate multi-cultural and multinational faculty and student groups using aln platforms.
reassessing current cell phone designs: using thumb input effectively. the physical form of cell phones has changed little from conventional landline phones. however, added features such as text input capabilities make cell phone usage very different from that of conventional phones. this paper reviews the emergence of text input on current cell phones. then a new design optimized for text input is proposed.
txtmob: text messaging for protest swarms. this paper describes cell phone text messaging during the 2004 us democratic and republican national conventions by protesters using txtmob -- a text-message broadcast system developed by the authors. drawing upon analysis of txtmob messages, user interviews, self-reporting, and news media accounts, we describe the ways that activists used text messaging to share information and coordinate actions during decentralized protests. we argue that text messaging supports new forms of distributed participation in mass mobilizations.
altarnation: interface design for meditative communities. altarnation allows physically isolated individuals to participate in communities of meditation and tailor thier own meditative practices. by lighting candles, users enter a shared virtual community of users represented by a field of stars, each associated with a sound sample of a prayer, song, joy, or concern of another user. existing practices of individual meditation and candlelight vigils inform this work. this paper describes implementation and design approaches of the altarnation system.
interactive querying of time series data. identification of patterns in time series data sets is a task that arises in a wide variety of application domains [4]. this paper presents a user interface for the timebox query model of rectangular regions that specify constraints over time series data sets. a prototype application based on timeboxes is presented. collaborations with potential users will guide the design of enhanced functionality. usability tests and controlled experiments will be conducted to evaluate the timebox query model.
a dynamic query interface for finding patterns in time series data. identification of patterns in time series data sets is a task that arises in a wide variety of application domains. this demonstration presents the timebox model of rectangular regions that specify constraints for dynamic queries over time series data sets, and the timesearcher application, which uses timeboxes as the basis of an interactive query tool.
simple tutors for hard problems: understanding the role of pseudo-tutors. the construction of cognitive tutors is often focused on tightly constrained domains. this is because the creation of a cognitive tutor is a time-intensive process. pseudo-tutors allow us to model a small number of problems in a relatively short time. there is no need to program a general cognitive model if we can demonstrate this model by example. the creation of a relatively small set of examples can have real cognitive benefit to the student.the lsat analytic logic tutor demonstrates that this is possible. this tutor was designed for teaching strategies for solving analytic logic games. although such a task would be difficult to model in general, three rich problems produced enough of an impact to significantly improve student performance. this is an interesting example where a small suite of well-designed pseudo tutors are significantly more useful than a full cognitive tutor.
a sense of spatial semantics. this paper describes an approach to the semantic analysis of location information. the system gathers verified natural language input and uses a ranking system to produce semantically meaningful tags. these associations are tied to precise spatial locations allowing a viewer to get the sense of a space.
crossmodal icons for information display. this paper describes a novel form of display using crossmodal output. a crossmodal icon is an abstract icon that can be instantiated in one of two equivalent forms (auditory or tactile). these can be used in interfaces as a means of non-visual output. this paper discusses how crossmodal icons can be constructed and the potential benefits they bring to mobile human computer interfaces.
sigchi project: user centered design of a program alleviating loneliness (pal). this paper illustrates the creation of an interactive entertainment system; pal (program alleviating loneliness.) the purpose of pal is to provide artificial companionship to support the social well-being of elderly homebound persons living alone above the age of 65 years. pal also provides a fully reliable source of emergency contact. pal is intended for the elderly homebound persons of today with its simplistic design. in order to create pal methodologies and techniques for designing user centred products or devices were considered. suggestions from the elderly persons and district nurses were also taken into consideration when designing pal. through the application of the above methodology we created an interactive entertainment system that is emotionally engaging, entertaining, cost effective, and supports at least one non-entertainment function for the owner.
fly: an organic presentation tool. in this paper, we present fly, a prototype presentation system that adds a visual structure to presentations. current presentation software, like powerpoint, structure slides in a linear sequence. the fly design introduces a spatial organization that is based on mind maps. using colour associations, spatial relations, and fluid movement, we show how presentation software can structure a meaningful overview of the underlying content.
attentive display: paintings as attentive user interfaces. in this paper we present ecs display, a large plasma screen that tracks the user's point of gaze from a distance, without any calibration. we discuss how we applied ecs display in the design of attentive art. artworks displayed on the ecs display respond directly to user interest by visually highlighting areas of the artwork that receive attention, and by darkening areas that receive little interest. this results in an increasingly abstract artwork that provides guidance to subsequent viewers. we believe such attentive information visualization may be applied more generally to large screen display interactions. the filtering of information on the basis of user interest allows cognitive load associated with large display visualizations to be managed dynamically.
learning for usability: an explorative study of qualities in use. efforts for creating usable systems which fulfill the purpose of being efficient and effective tools in an enterprise have been focused on the software itself. the study proposed here turns to the user, and to what the user contributes with for that use. the study explores the concepts of usability and qualities of software in use, and their relationship to end-users learning to use the software, in a case study approach. the understanding developed during this study will be used in an intervention study, which aims at proposing a way for formal training to contribute to usability and quality in use.
user-driven innovation in the future applications lab. user-driven innovation regards users as a resource in the innovation process. taking prototypes of novel technology as a starting point, a dialogue with users becomes a springboard to generate new ideas. the user group is often highly specialized, and not necessarily the intended end users of the technology. the future applications lab has successfully used this approach in several recent projects. in pin&play, we pushed the development of novel surface-based networking in collaboration with the staff of a film festival. in context photography we engaged a group of photographers with a unique outlook on the process of picture taking.
evaluating the comprehension of ambient displays. we introduce an evaluation framework for ambient displays, with three levels of comprehension: that data is visualized; what is visualized; and how it is visualized.
focus+context visualization with flip zooming and the zoom browser. flip zooming is a novel focus+context technique for visualizing large data sets. it offers an overview of the data, and gives users instant access to any part. originally developed for visualizing large documents, the method might be adapted for different types of information, including web pages, image collections and as a general windowing interface. a first practical demonstration of flip zooming is the zoom browser, a world wide web-browser that uses flip zooming to present web-pages.
total recall: in-place viewing of captured whiteboard annotations. total recall introduces a new way to view captured whiteboard annotations. to digitize drawings we used a modified commercial system. however, instead of displaying the annotations on a separate computer screen, total recall shows the annotations at the place on the board where they were actually made. the user holds a hand-held computer to the board and moves it to reveal the desirable portion of the captured annotations. by using ultra-sonic positioning and optimized graphics, we achieve a high frame-rate (30 fps), allowing for very smooth panning and interaction. we argue that this way of viewing captured whiteboard annotations is more natural and intuitive than current desktop-based systems.
a tool supporting capture and analysis of field research data using the contextual design methodology. field research techniques generate large amounts of unstructured data about users: their work practice, attitudes, strategies, motivations, and so forth. managing, organizing, communicating, and making sense of this complex and rich data is an ongoing problem for hci researchers. incontext performs field research and design for its clients, so we have experienced these problems in our business. this presentation demonstrates the software tools we built to manage our own research and design projects, showing how such tools can support a heavily team-based process, and how they can enhance the human thought process inherent in research and design.
making customer-centered design work in the real world of organizations. the goal of this sig is to provide a discussion area for those interested in overcoming the challenges of introducing-and then successfully establishing-customer-centered design techniques in organizations. sig participants will share the challenges they've faced in trying to initiate customer-centered design and share possible solutions to the challenges. after the sig, the discussion will be moved to chiplace, where the conversation can continue.
sig on contextual techniques: seeing design implications in data. contextual techniques are used to collect in-depth information on how people work. through these techniques engineering teams collect the knowledge they need to design products that fit their users well. however, going from customer data to design is not trivial; designers have to know how to look at the data and how to see implications for design out of it. the difference between a small tweak to an existing system and the invention of a whole new approach to a problem domain often lies in how good the designers were at recognizing what their customer data was telling them.
getting started on a contextual project. field data gathering techniques such as contextual inquiry enable a design team to collect the detailed customer data they need for their projects. but when a team wants to apply contextual techniques to their own situation, they are faced with a host of problems. what project should they start with? is it better to introduce them early or late in the process? given all the different possible techniques, which will work best for the specific project chosen? how should the customers be chosen and how should visits to them be set up? who should be on the project? it's no wonder people find it hard to get started with these new techniques in their own organizations.this tutorial gets participants over the roadblocks in the way of using contextual techniques in their projects. we walk through the different aspects of a contextual project, describing the issues that need to be resolved, the different approaches that can work, and the principles which guide making a choice. we use exercises to give participants the chance to plan aspects of their own projects, so they can do the thinking process themselves and raise any questions raised by their own situations.this tutorial is appropriate to anyone wishing to use field methods to gather customer data for their projects. some familiarity with these methods is assumed.
contextual design: using customer work models to drive systems design. field data gathering techniques such as contextual inquiry enable a design team to gather the detailed data they need. these techniques produce enormous amounts of information on how the customers of a system work. this creates a new problem---how to represent all this detail in a coherent, comprehensible form, which can be a suitable basis for design. an affinity diagram effectively shows the scope of the customer problem, but is less effective at capturing and coherently representing the details of how people work. design teams need a way to organize this detail so they can use it in their own development process.in this tutorial we present our latest methods for representing detailed information about work practice and using these representations to drive system design. these methods have been adopted over the last few years by major product development and information systems organizations. we show how to represent the work of individual users in models, how to generalize these to describe a whole market or department, and how to use these to drive innovative design. we present the process by which we build and use the models and practice key steps. we show how these methods fit into the overall design process, and summarize contextual design, which gathers field data and uses it to drive design through a well-defined series of steps.the tutorial is appropriate for those who have used field techniques, especially contextual inquiry, and would like to put more structure on the process of using field data.we use shopping as our example of work practice throughout this tutorial, since shopping is simple and understood by everyone. we encourage participants to go grocery shopping shortly before the tutorial, and bring any shopping list they may have used, their store receipt, and a drawing of the store layout and their movement through it.
rapid user centered design techniques: challenges and solutions. this sig provides a forum for discussing how user-centered methods, including methods like contextual design that include field data gathering, can be modified to support short development time frames and organizations using rapid development methodologies. we share ideas for how to get field data into the fast-paced development process, discuss the tradeoffs that can reasonably be made, and talk about techniques for working closely with developers so they value the influx of customer field data. we start by sharing our experiences, and then lead participants through discussions of their key challenges to generate solutions. we record our collective knowledge for the chi community.
techniques for designing mobile applications with customer data. this sig provides a forum for discussing how customer-centered techniques can best be used to gather requirements for mobile applications, especially considering the possibilities that new technologies offer. we will discuss when and how to modify customer-centered design for initial requirements gathering and during paper mock-up interviews. we will also share ideas for involving end users in visioning new possibilities for mobile platforms and key principles for designing applications for mobile devices. we start by sharing our experiences and then lead participants through discussions of their experience and challenges recording our collective knowledge for the chi community.
the context fabric: an infrastructure for context-aware computing. despite many sensor, hardware, networking, and software advances, it is still quite difficult to build effective and reliable context-aware applications. we propose to build a context infrastructure that provides three things to simplify the task of building context-aware applications: a context data store for modeling, storing, and distributing context data; a context specification language for declaratively stating and processing context needs; and protection mechanisms for safeguarding privacy needs.
annotating 3d electronic books. the importance of annotations, as a by-product of the reading activity, cannot be overstated. annotations help users in the process of analyzing, re-reading, and recalling detailed facts such as prior analyses and relations to other works. as elec-tronic reading become pervasive, digital annotations will become part of the essential records of the reading activity. but creating and rendering annotations on a 3d book and other objects in a 3d workspace is non-trivial. in this paper, we present our exploration of how to use 3d graphics techniques to create realistic annotations with acceptable frame rates. we discuss the pros and cons of several techniques and detail our hybrid solution.
gustbowl: technology supporting affective communication through routine ritual interactions. the gustbowl enables parents and out-of-house children to bring back the feeling of coming home and allow for low-threshold, uncomplicated communication through using an aesthetically pleasing product. technology is used to reconnect mother and grown-up son, by anchoring communication in routine daily actions. prototypes were tested over longer periods of time to develop and evaluate both the intended routine use and improvised focused use of the bowl.
fantasya and sentoy. fantasya is a role-playing game where emotions are part of the game logic. sentoy is a tangible interface device [2], used to influence emotional behaviour in fantasya. players in the game fantasya have to master sentoy and exhibit a particular set of emotions and perform a set of actions in order to evolve in the game [3]. a study was undertaken to gauge the success of the overall gaming experience, as well as the individual components, the fantasya game with its emotional content and the sentoy control device with its gestural input.
webquests: changing the way we teach online. this paper introduces webquests as potential teaching tools for hci and software design educators. based on our daylong observations of a high-school class, we believe that webquests can be adapted for use in online as well as classroom-based education and for use with adults as well as children. the webquest model offers three advantages for hci educators. one is that the students construct their own knowledge and meaning, and thereby learn the material more thoroughly. another is that a webquest, if done correctly, takes advantage of more learning styles. we observed aural, kinesthetic, and visual learning styles, for example. the third advantage is that, since webquests are team projects, students learn to work in teams.
location learning in chinese versus english menu selection. the orthography of chinese is remarkably different from that of english. does it have implications for human-computer interaction? this paper presents an empirical study in which location learning of chinese menu items and location learning of english menu items were compared. participants using a chinese menu learned the locations of menu items to a less extent, compared with participants using an equivalent english menu.
tangible programming in the classroom: a practical approach. this paper introduces quetzal, a tangible programming language for children to use in educational settings. quetzal features inexpensive, durable parts with no embedded electronics or power supplies. children create programs in offline settings--on their desks or on the floor--and carry their programs to a scanning station when they are ready to compile. we argue that a language like quetzal could offer an appealing and practical alternative to conventional languages for introducing programming concepts in the classroom. this paper discusses the motivations for the quetzal project and describes the design and implementation of the language. we also outline several key questions that are guiding our research with quetzal.
the effects of spatial and temporal video distortion on lie detection performance. in various types of interactions, individuals may attempt to determine whether their communication partners are being honest or deceptive. judgments of honesty rely, in part, on assessments of nonverbal behavior. with the increased use of videoconferencing technology, many traditionally face-to-face interactions now take place over sub-optimal video connections. in these connections, reduced spatial and temporal video quality may affect the ability to detect whether others are lying or telling the truth. in the current study we examined the effects of varying levels of temporal and spacial distortion on lie detection performance. consistent with earlier work, we found that a slight distortion of video signal impaired lie detection performance. surprisingly, performance improved when the video was severely spatially degraded.
eyedraw: a system for drawing pictures with the eyes. this paper describes the development of eyedraw, a software system that enables children with severe motor impairments to draw pictures by just moving their eyes. eyedraw will help these children to have creative and developmental experiences currently missing from their lives. the project demonstrates how task analysis integrated at various levels of detail, including that of the unit task as well as that of visual-perceptual and oculomotor processing, can improve eye tracking for real-time input. the project introduces refined techniques for controlling a computer with the eyes. the paper discusses the motivation for the project, previous research on eye-control of computers, how eyedraw works, and the results of user observation studies that are currently in progress.
designing icons and visual symbols. problems with icons are common---especially on web pages and guis designed by amateurs. most of these problems can be solved with more attention to detail, more input from various viewpoints, and more testing. this checklist will help you with those tasks.
conference state estimation by biosignal processing: observation of heart rate resonance. this paper discusses a conference state estimation method that uses only biosignal processing; linguistic understanding is avoided. in conventional dialogue communication research, the physiological characteristic of "entrainment" between the participants has been already reported. we extend "entrainment" to introduce the concept of "resonance" to grasp the relationship between attendees. we then propose a method which estimates the conference state from "resonance". first, using a multimedia conference system, we record conference data including time-series records of the participants' heart rates. by observing and analyzing the conference data, we assess the "resonance" phenomenon among the talkers. using the "resonance correlation matrix", a newly proposed index based on the correlation of the heart rate data, conference participative state can be successfully estimated.
"girls don't waste time": pre-adolescent attitudes toward ict. relying on naturalistic observation, via video self-documentaries, contextual interviews, and focus groups, we explored gender differences in the information and communication technology (ict) perception and use of united states middle school students. our study revealed four key dimensions which foreground the significant gender differences in how students of this age approach and interact with technology. these differences should be considered when developing age appropriate technology and education programs. our later research will explore the relationship among ict use, self-efficacy, and career choices through a large-scale survey.
tap or touch?: pen-based selection accuracy for the young and old. the effect of the decline in cognitive, perceptive, and motor abilities on older adults' performance with input devices has been well documented in several experiments. none of these experiments, however, have provided information on the challenges faced by older adults when using pens to interact with handheld computers. to address this need, we conducted a study to learn about the performance of older adults in simple pen-based tasks with handheld computers. the study compared the performance of twenty 18-22 year olds, twenty 50-64 year olds, and twenty 65-84 year olds. we found that for the most part, older adults were able to complete tasks accurately. an exception occurred with the low accuracy rates achieved by 65-84 year old participants when tapping on targets of the same size as the standard radio buttons, checkboxes, and icons on the pocketpc. an alternative selection technique we refer to as "touch" enabled 65-84 year olds to select targets more accurately. this technique did not negatively affect the performance of the other participants. if tapping to select, making standard-sized targets 50 percent larger provided 65-84 year olds with similar advantages to switching to "touch" interactions. the results suggest that "touch" interactions need to be further explored to understand whether they will work in more realistic situations.
preschool children's use of mouse buttons. we have observed numerous times how young children find it difficult to use software that provides different functionality with each mouse button. to better learn how young children use mice, we conducted a study with 4 year-olds, 5 year-olds, and adults. the study's participants played a game that responded equally regardless of the button used to click. the results showed that while adults and most 5 year-olds consistently clicked on the left mouse button, 4 year-olds did not. these results suggest that 4 year-olds are better served by user interfaces that provide the same functionality to all mouse buttons.
kidpad: collaborative storytelling for children. collaborative storytelling occurs frequently when children play, but few efforts have been made to support it with computers. this demonstration presents kidpad, a collaborative storytelling tool that supports children creating hyperlinked stories in a large two-dimensional zoomable space. through the use of local tools, kidpad provides children with advanced interaction techniques in a collaborative environment.
searchkids: a digital library interface for young children. as more information resources become accessible using computers, our digital interfaces to those resources need to be appropriate for all people. however, digital library interfaces have typically been designed for older children or adults. in this demonstration, we present searchkids, a digital library interface developmentally appropriate for young children (age 5-10 years old). searchkids offers a graphical interface for querying, browsing and reviewing search results.
designing public government web sites. public government web sites offer a promise of quick, convenient, and easy access to information and services. this has led many governments to push for an unprecedented move of publications, forms, and other information and services to this medium. there are many design challenges in developing public government web sites. in this sig we aim to identify these challenges and discuss lessons learned. we will concentrate in two areas: supporting safety and communities, and user-centered design. in our discussion, we plan to touch on issues such as trust, information transparency, information relevance, community support, user-centered design techniques, stakeholders, legal requirements, and universal access. we expect attendees will be either involved in the design of government web sites or interested in a discussion of these issues. the sig's activities will be organized to maximize input from all attendees.
interview viz: visualization-assisted photo elicitation. this paper describes a novel variation on an established social science research method, photo elicitation. we developed two visualizations of large numbers of cameraphone images, by time and sharing partner. the result was much richer and more detailed interviews than would have been possible otherwise. this method may be appropriate for other user studies where photo diaries are useful, and can be implemented using available photo organizing applications.
the uses of personal networked digital imaging: an empirical study of cameraphone photos and sharing. developments in networked digital imaging promise to substantially affect the near-universal experience of personal photography. designing technology for image capture and sharing requires an understanding of how people use photos as well as how they adapt emerging technology to their photographic practices, and vice versa. in this paper, we report on an empirical study of the uses made of a prototype context-aware cameraphone application for mobile media sharing, and relate them to prior work on photographic practices. by reducing many of the barriers to cameraphone use and image sharing (including increasing image quality, easing the sharing process, and removing cost barriers), we find that users quickly develop new uses for imaging. their innovative communicative uses of imaging are understandable in terms of the social uses identified from prior photographic activity; new functional uses are developing as well.
not just intuitive: examining the basic manipulation of tangible user interfaces. tangible user interfaces have received increasing attention in recent years. people often describe tangible user interfaces as "more intuitive" interfaces because we have learned how to manipulate physical objects throughout our lifetime. however, after almost 10 years of prototype development and numerous conference papers, tangible user interfaces have had minimal impact on everyday use of computers. is there anything that prevents tangible user interfaces from becoming more widely used? in order to investigate the effect of tangible user interfaces, we designed a spatial task to compare a paper tangible user interface with a mouse-controlled graphical user interface. using a within-subjects design, data were collected from 12 subjects who used both interfaces. results indicated that subjects exhibited better performance (center displacement error and reproduction time) with the paper tangible user interface.
design and analysis of groupware for large displays. despite the proliferation of large-scale displays in the workplace, creating groupware applications that take advantage of their potential for collaboration and communication remains challenging. interactions with large displays yield user experiences that are different from interaction with conventional desktop groupware. thus, unique hurdles exist for designing large display groupware applications (ldgas) that are integrated into actual work practice. our research addresses these challenges through experimental design based on studies of workgroup practices, the formation of a framework of heuristics for ldga adoption, and its application to the design and analysis of ldgas.
camera angle affects dominance in video-mediated communication. physical proximity and appearance guide people to interact with each other in different ways [1,6]. however, in video-mediated communications (vmc), these are distorted in various ways. monitors and camera zooms make people look close or far, monitors and camera angles can be high or low making people look tall or short, volume can be loud or soft, making people sound assertive or submissive, --all independent of the true physical characteristics or intentions of the participants. here we test the apparent height of a person on how dominant they are in a group decision-making task. we found that the artificially tall people had more influence in the group decision than the artifically short people.
promoting awareness of work activities through peripheral displays. the globalization of the workforce, growing prevalence of dynamic project-oriented teams, increasing flexibility in work times and places is beneficial to companies and workers. however, they contribute to the fragmentation of the workforce, reducing awareness of colleagues' activities. these awareness "gaps" result in missed opportunities for collaboration and sharing of relevant knowledge, as well as a diminished sense of community. we have conducted a user study to better understand these gaps in one particular workgroup, and designed a system to promote stronger awareness of workplace activities using peripheral displays.
3d object recognition with motion. this extended abstract presents preliminary results of an experiment that explores the effects of stereoscopic and monoscopic viewing, and controlled and uncontrolled motion, on the accuracy and speed of visually comparing and matching solid and wire frame cube- and sphere-based objects presented on a computer screen.
integrating tools into the classroom. smile, a learning environment for collaboration and design, is based on our experience with synchronous and asynchronous collaboration tools in the classroom and sound principles of software and interface design. smile provides a more holistic approach to supporting student reasoning and activities rather than the more reductionist tool-based approach we had started with. this more holistic approach focuses on the cognitive processes involved in doing design and learning from that experience, rather than focusing on activities that students are carrying out. this new emphasis has also allowed us to identify ways of integrating scaffolding for metacognitive and reflective reasoning that were not naturally integratable into the previous framework.
bridging the gap: fluidly connecting paper notecards with digital representations for story/task-based planning. programmers use both paper and digital artifacts to aid in the process of software planning. this paper presents a prototype of a system that uses digital pen technology to integrate paper notecards and digital task plan representations, allowing programmers to utilize the affordances provided by both techniques. through an ethnography of programmers who practice planning using both physical and digital artifacts, we discovered common actions performed by the programmers included card creation, card augmentation, card combining, and scheduling of card for completion. we designed interaction techniques to facilitate these actions and conducted a usability study (n=10) to evaluate the techniques. through the study, we discovered that the initial prototype provided both positive and negative experiences for the user, providing insightful design implications for the future.
the sense lounger: establishing a ubicomp beachhead in elders' homes. in this paper we describe the sense lounger, a method for simply and cheaply turning a lounge chair into an initial "ubicomp" device in a home; providing a beachhead for transforming the home into a rich ubicomp environment. the sense lounger employs fabric sensors sewn into a chair's slipcover and force sensors on each leg to detect both an occupant and their activity. drawing insights from user needs, we developed the sense lounger to (i) fit into the home and lifestyle of elders, (ii) assist and add value to the lives of elders, (iii) provide a platform for expanding assistive devices within the home environment. the current sense lounger prototype can be used to detect signs of life, patterns of use, posture, and sitting duration.
quickspace: new operations for the desktop metaphor. the explosion of information available to everyday users has resulted in numerous applications that allow users to access this information. fundamental desktop operations fail to assist the user efficiently display all of the information available in these applications. we propose a number of new window and space management techniques that attempt to solve this problem.
mudibo: multiple dialog boxes for multiple monitors. a general problem identified in recent research on multiple monitor systems is the placement of small windows such as dialog boxes and toolbars. these small windows could be placed on top of the application window or on a monitor next to the application window; different situations call for different placements. we present mudibo, a component of the window manager that alleviates this problem by initially placing a window in multiple locations simultaneously and subsequently allowing the user to easily interact with the window in a desired location. additional important contributions of mudibo are that as a general technique it can be applied to a number of situations and windows beyond simple dialog boxes, exploits the additional screen space that multiple monitors provide to solve a specific problem with dialog box interaction, and is among the first research prototype uis that explicitly account for multiple-monitor users.
time quilt: scaling up zoomable photo browsers for large, unstructured photo collections. in the absence of manual organization of large digital photo collections, the photos ' visual content and creation dates can help support time-based visual search tasks. current zoomable photo browsers are designed to support visual searches by maximizing screenspace usage. however, their space-filling layouts fail to convey temporal order effectively. we propose a novel layout called time quilt that trades off screenss-pace usage for better presentation of temporal order. in an experimental comparison of space-filling, linear timeline, and time quilt layouts, participants carried out the task of finding photos in their personal photo collections averaging 4,000 items. they performed 45% faster on time quilt.furthermore, while current zoomable photo browsers are designed for visual searches,this support does not scale to thousands of photos: individual thumbnails become less informative as they grow smaller. we found a subjective preference for the use of representative photos to provide an overview for visual searches in place of the diminishing thumbnails.
exploring user experience in "blended reality": moving interactions out of the screen. video game players often learn to map their physical actions (e.g., pressing buttons) onto their on-screen avatars' actions (e.g., wielding swords) in order to play. we explored the experience resulted from eliminating this mapping by modeling the screen as a "window" through which virtual objects enter the player's physical space, and the player interacts with them directly without the mediation of an avatar. we define this interaction as "blended reality" (br). we designed, developed, and evaluated a br game prototype called "apple yard" in which the player was to use a wand to hit apples flying out of the screen. a camera was used to track the positions of the player's eyes and wand, and the 3d game scene was rendered accordingly to create the illusion of looking through a window. a user tests experiment conducted on this prototypes indicated br's potential in camera-based entertainment.
a study of cursor trajectories of motion-impaired users. this paper describes a study of the cursor trajectories of motion-impaired users in "point and click" interactions. a characteristic of cursor movement is proposed that aims to capture the spatial distribution of cursor movement about a target. this characteristic indicates that users often exhibit increased cursor movement in the vicinity of the target, have more difficulty performing the "clicking" part of the interaction as compared to the navigation part, and tend to navigate directly toward the target during the middle portion of the cursor trajectory. the implications of these characteristic behaviours on interface design are discussed.
partitioning cursor movements in "point and click" tasks. studies of cursor trajectories can help explain performance differences in "point and click" tasks. as users can have different difficulties with moving the cursor to a point on the screen, as compared with pressing a button to select an object, it is helpful to study the two stages of the interaction separately. this paper proposes a method of partitioning a cursor trajectory into a travel and a select phase. the movements of motion-impaired users are studied to show that, by analyzing the two phases separately, it is possible to capture aspects of movement that may otherwise be lost.
qwerty-like 3x4 keypad layouts for mobile phone. most computer users are accustomed to the qwerty keyboard layout. this study was started from the hypothesis that a user's skill in a qwerty keyboard may be transferred to a 3x4 keypad environment. in order to test the hypothesis, we designed an experiment where users are instructed to type a series of sentences on a "blank" keypad after they were informed that the underlying layout is either qwerty-like or abc-type (alphabetical). we observed a more localized layout of typed characters over keys in the qwerty-like case than in the abc case. encouraged by the results, we carried out a series of experiments in order to compare a qwerty-like layout and an abc-type layout, and obtained consistently better learning curves and better final typing speeds with a qwerty-like keypad. as an effort to explain the results, we carried out an eye-gaze analysis for the two cases, and the results are presented.
feeltip: tactile input device for small wearable information appliances. the ever decreasing size of information devices these days does not allow even the space for small input devices such as a touchpad or a 3x4 keypad. we introduce here an input device, feeltip, as a solution for very small information devices. the main idea is to exchange the usual roles of a finger and a surface in a touchpad; a device has a tip and a finger now provides a surface. the result is an input device requiring minimal space but is potentially more efficient than a touchpad due to the tactile feedback of a tip on a finger. our first prototype consists of a transparent tip and a small cmos image sensor that tracks the movement of a finger on a tip. in a series of experiments, it outperformed a small analog joystick in free pointing tasks, and was comparable with a 3x4 keypad in text entry tasks.
interface with pre-typing visual feedback for touch-sensitive keyboard. in this paper, a method is described that detects and displays what key a user has touched with his fingertip before the key is pressed. the proposed method is based on the use of a touch-sensitive cover on a pushbutton key set. the identity of the touched key is displayed exactly at the point where the i-beam pointer indicates at the inputting string, so that correct data entry will be made simpler without looking at the keyboard or needing training.
user experience: an umbrella topic. this position paper represents my views on how we address the multi-disciplinary needs of the user experience industry. while each profession struggles to deepen its core skills and membership offerings, it also needs to branch out beyond its traditional borders to serve its members' needs within a broader industry. "user experience" should be the topic that unites all of various professional organizations under an umbrella. because each organization has its special contribution to the network (some at the core, some as specialists and others as interested parties), and each person will have different needs, a personalized portal should be built for the ux topic to help individuals cross over existing boundaries.
eliciting user preferences using image-based experience sampling and reflection. determining requirements for any design project involves identifying and ranking user needs and preferences. user needs are typically elicited via personal or focus group interviews, site visits, and photographic and video analysis. often, however, users know more than they say in a single or even several interviews [1]. we propose a methodology for assisting a user who is interested in learning about his or her own preferences using a process we call image-based experience sampling and reflection. we describe the methodology using a storyboard example from the domain of architectural redesign of home environments.
a living laboratory for the design and evaluation of ubiquitous computing technologies. we introduce the placelab, a new "living laboratory" for the study of ubiquitous technologies in home settings. the placelab is a tool for researchers developing context-aware and ubiquitous interaction technologies. it complements more traditional data gathering instruments and methods, such as home ethnography and laboratory studies. we describe the data collection capabilities of the laboratory and current examples of its use.
a context-aware experience sampling tool. a new software tool for user-interface development and assessment of ubiquitous computing applications is available for chi researchers. the software permits researchers to use common pda mobile computing devices for experience sampling studies. the basic tool offers options not currently available in any other open-source sampling package. however, the tool also has new functionality: context-aware experience sampling. this feature permits researchers to acquire feedback from users in particular situations that are detected by sensors connected to a mobile computing device.
investigating the effectiveness of mental workload as a predictor of opportune moments for interruption. this work investigates the use of workload-aligned task models for predicting opportune moments for interruption. from models for several tasks, we selected boundaries with the lowest (best) and highest (worst) mental workload. we compared effects of interrupting primary tasks at these and random moments on resumption lag, annoyance, and social attribution. results show that interrupting at the best moments consistently caused less resumption lag and annoyance, and fostered more social attribution. results demonstrate that use of workload-aligned models offers a systematic method for predicting opportune moments.
task-evoked pupillary response to mental workload in human-computer interaction. accurate assessment of a user's mental workload will be critical for developing systems that manage user attention (interruptions) in the user interface. empirical evidence suggests that an interruption is much less disruptive when it occurs during a period of lower mental workload. to provide a measure of mental workload for interactive tasks, we investigated the use of task-evoked pupillary response. results show that a more difficult task demands longer processing time, induces higher subjective ratings of mental workload, and reliably evokes greater pupillary response at salient subtasks. we discuss the findings and their implications for the design of an attention manager.
interviewing customers: discovering what they can't tell you. product designers typically talk to customers in an effort to better understand their needs. however, without interviewing skills and an understanding of the types of information people can provide about themselves, interviewers may collect little useful information or even misleading information. this tutorial provides a practical approach to interviewing customers. it focuses on three areas: (a) the types of information you should (and should not) expect to learn from interviews, (b) good interviewing techniques, and (c) methods for analyzing the large volumes of information collected in interviews. the tutorial makes heavy use of demonstrations and exercises to give the participants hands-on experience with preparing and conducting interviews as well as analyzing information collected.
characterizing instant messaging from recorded logs. most studies about instant messaging (im) are based on self-report data. we logged thousands of real im conversations and examined them to find characteristic patterns of im use in the workplace. frequent imers have longer, faster-paced interactions than do infrequent users, with shorter turns, more threading, and more multitasking. pairs who im with each other often have longer interactions with more threading than do rare partners. in contrast to previous characterizations, im is used only occasionally to set up interactions in other media.
evaluating affective interfaces: innovative approaches. this paper presents the broad outlines of the context and goals for a one-day workshop concerning the evaluation of affective interfaces.
on natural living room communication with "comadapter": adapting to the differences in room structure. aiming at rich and useful communication in our daily home life, we propose a novel communication concept, "comadapter", in which people can mutually share their intention and emotion by exchanging their spontaneous behavior. comadapter can create shared space communication that allow us to communicate with another party in a remote location as though other party has entered our room. to achieve this, comadapter offsets the differences in the configurations of the rooms. in a simple preliminary system, body motions are successfully adapted and transmitted between two rooms with different layout. the success of the experiment confirms the validity and potential of comadapter.
combined model for text entry rate development. we combine the power law of learning and theoretical upper limit predictions to describe the development of text entry rates from users' first contact to asymptotic expert usage. the combined model makes comparing text entry methods easier. we present the rationale for the model and two candidate implementations. the first is a simple regression model with a reasonable fit to the data. the second fits measured data better, but is more complicated.
cyarm: an alternative aid device for blind persons. with the concept of 'human-machine interface', designed especially for visually impaired persons, we have developed an electric aid device for use in guiding orientation and locomotion. the device, which we call cyarm, measures the distance between a person and an object with an ultrasonic sensor and transmits the distance information to the user's haptic sense. in this report, we will: (1) outline the concept of cyarm, (2) describe its mechanism, and (3) demonstrate three preliminary experiments that verify the usability of cyarm. we conducted the experiments in terms of detection of objects, detection of space, and tracking object movement. as a result of these experiments, we have concluded that cyarm is potentially effective for visually impaired persons. our study will encourage the related studies of user interfaces, particularly focusing on electric aid devices that guide visually impaired persons in detecting their environment.
communication service design by interhuman interaction approach. this paper describes a new communication service that supports all communication environments for healthy elderly people. this service was designed based on the interhuman interaction approach, and the acceptability of this system was verified by a field test.
'tsunagari' communication: fostering a feeling of connection between family members. families in japan increasingly have one or more members living outside of the family household, but many people don't want to lose the bond between family members when they live apart. we have developed a concept called 'tsunagari' communication aimed at fostering a feeling of connection between people and maintaining their social relationships. a system based on this concept, called the family planter system, was also developed for family use. we have field tested this system with family members living apart, and our interviews of users have shown that the users' family relationships tend to be slightly improved by use of this system.
search result exploration: a preliminary study of blind and sighted users' decision making and performance. we conducted a preliminary study to examine sighted and blind users' decision-making behavior and performance during the search process. we manipulated the search result's relevance to a task, the search result presentation, and the effort required to process the corresponding web page. we found that users leveraged page features to gauge the amount of effort that is required to explore search pages and made exploration decisions accordingly. users' desire to know additional page details varied based on their visual ability and the results' relevance. we quantified the cost/benefit tradeoff of additional page features and suggest ways to better support diverse web searchers.
towards computer-supported face-to-face knowledge sharing. although a lot of systems provide co-located collaboration support, few existing technologies provide support for fluid knowledge sharing. to fluidly share our knowledge in co-located environments, each person's digital experience should be merged and presented on a collaborative display device such as a face-to-face tabletop display. for capturing concrete requirements for such face-to-face fluid knowledge sharing, we built a prototype system that presents merged multi-users' web browsing histories on a tabletop display. we experimented with our prototype in an exhibition and collected over 100 filled questionnaires and informal observations.
hci group of the department of ergonomics and psychology at the budapest university of technology and economics. our hci group developed mutually useful relationships with industrial partners, like matáv hungarian telecom, paks nuclear power plant, graphisoft, nokia, eurocontrol, etc., successfully accomplishing various r&d projects in very different fields.we apply a variety of evaluation methods, including a complex methodology called interface developed by us. this system is based on the continuous and simultaneous recording of heart period variability, time data of keystroke and mouse events, video images of users' behaviour and screen content.
establishing remote conversations through eye contact with physical awareness proxies. we present a mechanism for initiating mediated conversations through eye contact. an eyephone is a physical proxy of a remote individual that senses and conveys attention using an eye tracking device and a pair of actuated eyeballs. users may initiate calls by jointly looking at each other's eyephone. we discuss how this allows participants to implement some of the basic social rules of face-to-face conversations in mediated conversations.
reach: dynamic textile patterns for communication and social expression. in the research project 'reach', we investigate the potential for new forms of communication and expression to be incorporated dynamically and interactively into the things to be worn everyday. through a series of iterative prototypes, we have explored both dynamic textile materials and the interactive behaviours of clothing and accessories, which change pattern through direct physical interaction as well as through sensing context. we have developed a series of working prototypes, where dynamic textile patterns are incorporated into wearable items to reflect and make visible social and contextual behaviours, such as person-to-person communication, proximity and local weather conditions. ultimately, we aim to develop a new dynamic language of wearable expression integrating aesthetics, pattern and computation into everyday artifacts with increased personal and cultural meaning.
using a tree view metaphor to visualize hardware simulation for testing. this papers suggests the use of a tree view metaphor as a suitable way of visualizing simulated hardware elements in a graphical user interface (gui) for testing purposes. the prospective users declared a few comprehensive demands regarding the desired application - such as maximal availability of desktop space and ease of configuring and reconfiguring the hardware simulations. an application was prototyped and evaluated through interviews and an accompanying usability test. preliminary evaluation shows that using the new gui with the tree metaphore makes the task of configuration faster and saves desktop space.
breakaway: an ambient display designed to change human behavior. we present breakaway, an ambient display that encourages people, whose job requires them to sit for long periods of time, to take breaks more frequently. breakaway uses the information from sensors placed on an office chair to communicate in a non-obtrusive manner how long the user has been sitting. breakaway is a small sculpture placed on the desk. its design is inspired by animation arts and theater, which rely heavily on body language to express emotions. its shape and movement reflect the form of the human body; an upright position reflecting the body's refreshed pose, and a slouching position reflecting the body's pose after sitting for a long time. an initial evaluation shows a correlation between the movement of the sculpture and when participants took breaks, suggesting that ambient displays that make use of aesthetic and lifelike form might be promising for making positive changes in human behavior.
the effectiveness of social agents in reducing user frustration. a study was conducted to evaluate the effectiveness of social agents in reducing user frustration. the particular type of agent studied reacted to users' facial expressions while they browsed through a shopping website. while highly frustrated users reported that the agent often increased their frustration, those experiencing a moderate level of frustration stated that it somewhat reduced their frustrations.
getting real about speech: overdue or overhyped? speech has recently made headway towards becoming a more mainstream interface modality. for example, there is an increasing number of call center applications, especially in the airline and banking industries. however, speech still has many properties that cause its use to be problematic, such as its inappropriateness in both very quiet and very noisy environments, and the tendency of speech to increase cognitive load. concerns about such problems are valid; however, they do not explain why the use of speech is so controversial in the hci community. this panel would like to address the issues underlying the controversy around speech, by discussing the current state of the art, the reasons it is so difficult to build a good speech interface, and how hci research can contribute to the development of speech interfaces.
the impact of automated assistance on the information retrieval process. advanced information retrieval systems providing automated assistance offer the opportunity to greatly enhance the effectiveness of the information retrieval process. one issue in designing such systems is determining the effect that the automated assistance has on the tasks and sequence of tasks within this process. using verbal protocol data and transaction log analysis, we present a taxonomy of tasks when utilizing information retrieval systems with automated assistance, along with a temporal analysis of when interaction with the automated assistance occurs. results indicate that there is a predictable pattern of user interaction with automated assistance with implications for the design of information retrieval systems.
eyeview: focus+context views for large group video conferences. in this paper, we describe the design of eyeview, a video conferencing system that uses participant looking behavior to determine the size of online video conferencing windows. the system uses an elastic windowing algorithm that enlarges the image of the person most looked at by others, while maintaining a contextual view of other remote participants. eyeview measures interest by gauging whom participants look at using an eye tracker embedded in the display. users can enter side conversations by looking at each other, and pressing the space bar. cocktail-party filtering is aided by attenuating audio sources outside the social network constituted by glances between participants. by allocating both screen and audio real estate according to the joint attention of participants, eyeview supports smooth allocation of focus on the speaker, while maintaining awareness of the group.
about face interface: creative engagement in the new media arts and hci. by promoting divergent thinking and creative visions, new media art practices present hci research with a platform that emphasizes creative engagement as a locus for innovative design and evaluation methods. the workshop goal is to identify attributes of a conceptual framework that positions creative engagement as a hub for future transdisciplinary research and incorporates practices and theories from the new media arts, hci, and computer science research.
design communication. why is design communication so hard? we've all been in the situation: a room full of people, a usability test with clear problems and obvious outcomes. yet the team can't agree on a design solution. why does this happen? how can intelligent people disagree so strongly when looking at the same data?.this panel approaches a problem that has not been discussed much at chi: the social interaction of the design process.each of the four panelists, who have broad industry experience in consulting, in-house design centers, and academics, will each take a different position on this problem. is this simply a matter of vocabulary, process, experience, or competence?.this panel will start off with brief statements by each panel member and then spend the majority of the session debating each panelists position. the last third of the session will be opened up to audience questions.
the advantages of a cross-session web workspace. conducting research using the web is often an iterative process of collecting, comparing and contrasting information. not surprisingly, web-based research tasks habitually span multiple web sessions and involve considerable web page revisitation. such tasks are not only carried out by researchers, but also by casual web users who, for example, plan vacations and large purchases. despite the prominence of this activity among web users, existing tools support it poorly. we propose an alternative approach, whereby web-based research tasks are facilitated by a web workspace which represents collected urls with web page thumbnails. a prototype of our design was developed and studied in an evaluation with 12 participants. each of the participants adopted the workspace approach instinctively: the workspace was used for web page revisitation, web page comparison, collection overview, cross-session task continuation, and continuous task focus.
do we need eye trackers to tell where people look? we investigated the validity of two low-cost alternatives to state-of-the-art eye tracking technology: 1) prompting users to report from memory on their own eye movements, and 2) asking experienced web designers to predict the eye movements of a typical user. users could reliably remember 70 % of the web elements they had actually seen. web designers could only predict 46 % of the elements typically seen. users were not particularly good at remembering the order of their fixations. we discuss how to further improve the validity of self-reported gaze patterns and suggest new areas that it may be used in.
the engineering community sig. the engineering community may be the least populated and the least understood of the new communities at chi, perhaps because so many definitions of engineering exist (as evidenced by the quotes in the margins). this sig will provide a forum for people interested in bringing the best of the field of engineering to the field of hci.
universal access to the net: requirements and social impact. this talk will address the following questions: what does "universal access" mean with respect to computer-based network services? is it desirable? where do we stand today with respect to achieving it? what is required (particularly in the hci realm) to achieve it? what are some of the consequences and side-effects -- positive and negative -- for society?
convergent usability evaluation: a case study from the eirs project. two non-profit organizations developed a web application to help monitor u.s. elections: the election incident reporting system (eirs). the mostly-volunteer team had only four months to develop a workable system. the aggressive schedule, limited budget, and distributed team-structure challenged us to find creative ways to evaluate and improve eirs' usability. we used an approach that combined expert ui review with opportunistic exploitation of venues for gathering data on eirs' usability. this approach, which we call convergent usability evaluation, had, in the non-profit environment, advantages over the more formal methods typically used for commercial projects. in this paper we describe the usability evaluation methods we used for the eirs project and discuss how they converged to provide a more complete picture than we would have obtained by conventional methods.
designing user interfaces from analyses of users' tasks. this tutorial provides a detailed introduction to task analysis and task-based design. the focus of task analysis is the description of work tasks, while the focus of task-based design is designing interactive systems from the perspective of users' work. techniques from psychology, ethnomethodology and sociology are used to analyse and describe users' current work tasks. a framework for modelling work tasks (task knowledge structures) is used to represent relevant task information. guidelines are provided to help the design team envision and reason about how current tasks might be changed and improved through the design of interactive systems. the envisioned task descriptions provide the focus for the design and development of interactive systems that will support the users' work.
usability and cmmi: does a higher maturity level in product development mean better usability? the new process improvement model, capability maturity model integration (cmmi) is analytically examined from the point of view of usability. the results show that a development organization even at the high levels of maturity may produce products with usability problems. the challenge for the field of hci is to develop universal usability measures for the high maturity levels of cmmi.
cognition and collaboration: analyzing distributed community practices for design. this extended abstract describes the workshop cognition and collaboration - analyzing distributed community practices for design, the third international workshop on analyzing collaborative activity.
i-vote: an audience voting system. in this paper, we describe the i-vote system for audience response voting at the olympic games. the audience members vote by using a $2 handheld device that they can keep as a souvenir. the devices are simple to use, come in multiple designs, and are tradable. these devices do not hold any personal information so privacy is never an issue. the vote results are presented on a large public display, which is loaded with information in the form of graphs that are quickly understood. people can retrieve their personal votes later on the internet. the system was designed through a process involving brainstorming, creating scenarios, searching for information, doing cognitive walkthroughs, developing prototypes, and revising and refining ideas.
"it's about the information stupid!": why we need a separate field of human-information interaction. the past few years have seen increasing discussion of the need for, even the inevitability of, a field of human-information interaction (hii) - as either a major sub-branch of human-computer interaction (hci) or as a separate field altogether. the "i" in hii implies a focus on information and not computing technology. but what does this mean? is there any way to focus on information without also considering the supporting tools, applications, and gadgets that are enabled by computing technology? the panel will explore both the pros and cons in favor of a separate field of hii. panelists provide a diversity of perspectives from several disciplines and research traditions including cognitive modeling and the study of human cognition, information science, information architecture, personal information management, ethnography and anthropology.
don't take my folders away!: organizing personal information to get ghings done. a study explores the way people organize information in support of projects ("teach a course", "plan a wedding", etc.). the folder structures to organize project information - especially electronic documents and other files - frequently resembled a "divide and conquer" problem decomposition with subfolders corresponding to major components (subprojects) of the project. folders were clearly more than simply a means to one end: organizing for later retrieval. folders were information in their own right - representing, for example, a person's evolving understanding of a project and its components. unfortunately, folders are often "overloaded" with information. for example, folders sometimes included leading characters to force an ordering ("aa", "zz"). and folder hierarchies frequently reflected a tension between organizing information for current use vs. repeated re-use.
how can rhetoric and argumentation help us make the case for ucd? when making the case for user-centered design (ucd), the hci field tends to rely on an objective approach, such as cost justification, to speak for itself. however, this approach may not be enough to garner support for decisions ranging from implementing a certain design to adhering to a ucd process. promising sources for enhancements to an objective approach are rhetoric and argumentation. one purpose of this sig is to explore how rhetoric and argumentation can help advance the case for ucd on organizational and project levels in various contexts and organizations. as a catalyst for discussion among sig attendees, this abstract describes examples of using rhetoric and argumentation in three contexts: boutique consultancy, in-house consultancy for large corporation, and research-oriented federal agencies. another purpose of this sig is to establish a community of people interested in using rhetoric and argumentation to augment their communication approach when making the case for ucd.
don't blame me i am only the driver: impact of blame attribution on attitudes and attention to driving task. key concerns of automobile interface designers are driving performance and safety. as cars include voices for telematics, command and control, warning messages, etc., these voices become an opportunity to affect drivers and their performance. in this experimental study, participants (n=36) spent 20 minutes in a driving simulator. the car presented randomly interspersed warnings about the driver's performance while they were driving. there were three conditions: driver blame (e.g., "you are driving too fast"), driver and car blame ("we are driving too fast"), or environment blame ("the road is easy to handle at low speeds"). results indicate that warnings associated with the environment works best. drivers felt most at-ease, they liked the system, they rated the quality of the car higher, and their measured attention to the road was better than the other conditions. implications for in-car interaction systems are discussed.
thank you, i did not see that: in-car speech based information systems for older adults. older adult drivers have more difficulty than the general driving public in attending to driving tasks especially in complex traffic situations. this study examines whether a speech based in-car information system can positively influence driver attitudes, driving performance and safety. eighteen participants between the ages of 55 and 73 used a driving simulator for approximately thirty minutes in one of three conditions: in-car information system with a young voice informing the driver of upcoming hazards, in-car information system with an older adult voice, and no in-car system. there was a clear positive effect of driving with the in-car information system; drivers felt more confident driving, they completed the driving course in less time (without exceeding the speed limit), and had fewer accidents. there was also a clear positive effect of using a young adult voice for the in-car information system.
interaction design in india: past, present and future. in many parts of the world, human-computer interaction (hci) emerged as an interdisciplinary activity between the fields of computer science, cognitive psychology and / or human factors. elsewhere, the field of information sciences gave birth to the discipline now recognized as information architecture (ia). in india however, it emerged as interaction design, largely based in the field of design. in this paper, i talk about this experience, give a summary of current status in industry and research and suggest an agenda for the future, particularly for interaction design education.
keylekh: a keyboard for text entry in indic scripts. typing in an indian language is currently not an easy task. significant training is required before one can achieve an acceptable speed and only professional typists make the investment. part of the complexity arises due to the structure of indic scripts and large number of characters in each script. solutions to input text in indic languages have been around for a while, but none of these are usable enough to emerge as the de-facto standard. here we describe the design of a new keyboard based on the structure of the indic alphabet. the project went through cycles of design, prototyping and user evaluation. the evaluation was done by multiple techniques - usability tests, informal demonstrations, road shows and a typing competition. we particularly found the road shows and the competition useful for gathering feedback for this type of products.
trading design spaces: exchanging ideas on physical design environments. physical design environments are places that support people engaged in the spatial, physical, tangible act of creation. it is now possible to augment workspaces with an amazing array of technologies to assist users in their creative endeavors. however, the integration of computing technologies into physical environments involves a new set of tools, technologies, principles and practices. in this panel, researchers working on the challenges of physical design support present their work through a walkthrough of their prototype work environments. each environment will then be "remodeled" by a fellow researcher using his or her own approach, tools, and design philosophy. the goal of this session will be to explore the large variety of potential applications, tools, technologies, interfaces, and processes used by those working to augment the creative physical world.
influence of colearner agent gehavior on learner performance and attitudes. this study examines the effect of colearner agent performance and social behavior on learner performance and subjective satisfaction in an interactive learning environment. in this 2 (high- or low-performing colearner) by 2 (socially supportive or competitive colearner) experiment (n=44), participants learned morse code alongside an agent colearner. participants with high-scoring colearner agents performed significantly better than participants with low-scoring colearners. participants liked and felt liked by socially supportive agents more than they did socially competitive agent participants. implications for developing educational software are discussed.
synchronized retrieval of recorded multimedia data. this paper describes techniques for the retrieval of recorded multimedia data for supervisory control systems. currently these systems operators can only retrieve recorded data individually. we developed new techniques to access all recorded data is synchronization. the techniques enable users to retrieve multimedia data such as sensor data and videos simultaneously, and also enable users to obtain the desired related data, including objects in videos, by "drag and drop" operation. all these techniques allow operators to exactly and quickly analyze phenomena in the systems based on the recorded multimedia data.
basic research symposium. the basic research symposium is a special event with a five-year history at chi. it is a hybrid between a mini-conference and a workshop that presents an opportunity for researchers from different disciplines to share their visions through exchanging new developments and insights from their own fields. the goal of the symposium is to provide an interactive forum to promote and enhance scientific discussions of developing research issues. it is designed to advance understanding and dialogue among fellow researchers as well as to encourage asking of questions and reflection on methods and results. it is a unique opportunity to learn about the variety of perspectives present in the international hci research community and to apply the often radically different criteria associated with those perspectives to one's own work.
i just clicked to say i love you: rich evaluations of minimal communication. virtual intimate objects are low bandwidth devices for communicating intimacy for couples in long-distance relationships. vios were designed to express intimacy in a rich manner over a low bandwidth connection. vios were evaluated using a logbook which included open-ended questions designed to understand the context within which the vio was used. users constructed a complex, dynamically-changing understanding of the meaning of each interaction, based on an understanding of their and their partner's context of use. the results show that users had rich and complex interpretations of this seemingly simple communication, which suggests the necessity of exploring context of use to understand the situated nature of the interactions as an intrinsic part of an evaluation process for such technologies.
sketching annotations in a 3d web environment. collaborative design review is an important part of architectural design work. the space pen system supports annotation and drawing on (and inside) 3d vrml/java models using a regular web browser to exchange text and sketched annotations for review.
communicating intimacy one bit at a time. in this paper, we present a study of 'minimal intimate objects': low bandwidth devices for communicating intimacy for couples in long-distance relationships. we describe a user study of a software intimate object built to communicate a single bit at a time. the results from both log data and journal entries suggest that even a one-bit communication device is seen by users as a valuable and rich channel for communicating intimacy, despite the availability of wider channels of communication such as email, instant messaging, and telephone. we suggest the constrained nature of the communication affords active reinterpretation by its users, and discuss the results in the context of the study of intimacy in human-computer interaction.
tailoring virtual reality technology for stroke rehabilitation: a human factors design. in this paper we introduce an interdisciplinary project to develop a virtual reality enhanced stroke rehabilitation system (vrsrs). in particular, we propose a human factors design in developing a vrsrs for improving the functional recovery rate of stroke patients' upper extremities.
understanding how to improve the accessibility of computers through cursor control studies. people with motion-impairments often find it difficult to perform many of the actions required to interact with a computer. this paper presents the results of an on-going series of experiments designed to understand how using force feedback affects interaction for motion-impaired users. point and click tasks were analyzed using new cursor control measures. the results showed significant improvement in throughput for all users with force-feedback and the cursor control measures were effective in capturing the differences between the conditions.
the untapped world of video games. due to fierce industry competition and demand for novelty, games are a fertile research setting for studying interface design, input devices, graphics, social communication and development processes. this sig proposes to bring together researchers with a wide set of interests, to showcase and discuss their common research platform: video and computer games. we hope to educate both games researchers and interested attendees from the general chi community. small group discussions around game play stations will expose participants to the breadth of game genres that are being used by chi researchers as a research platform as well as popular game genres that are currently untapped.
symbolic objects in a networked gestural sound interface. signalplay is a sensor-based interactive sound environment in which familiar objects encourage exploration and discovery of sound interfaces through the process of play. embedded wireless sensors form a network that detects gestural motion as well as environmental factors such as light and magnetic field. human interactions with the sensors and with each other cause both immediate and systemic changes in a spatialized soundscape. our investigation highlights the interplay between expected object-behavior associations and new modes of interaction with everyday objects. here we present observations on embodied network interaction and suggest opportunities for further investigation in this field.
an examination of user behaviour during web information tasks. since the inception of electronic environments, researchers have been interested in how to provide better support for the tasks users perform in these environments. the research presented in this thesis is the result of three successive studies conducted to examine user behaviour within the web browser in the context of task. an exploratory field study was first conducted to examine how users interact with their web browsers during information seeking tasks on the web. based on the study findings a characterization of web information tasks was developed, which includes: fact finding, information gathering, browsing, communications, transactions, and maintenance. the study also found significant differences in how users interacted with their web browsers to complete these tasks. the findings from the field study also highlighted the fact that little is known about the monitoring activities of web users, which occur when users return to previously visited web pages to view new or updated information. as a next step, a series of semi-structured interviews were conducted to concentrate on the role of web-based monitoring in the context of web information tasks. the results from this study suggested that monitoring is an activity that occurs, to varying degrees, within all web information tasks. this implies that information monitoring activities require different types of web browser support, depending on the underlying web information task. based on the study results, a series of recommendations for the design of task-specific tools to support web-based monitoring were developed. a laboratory study was then conducted to evaluate three task-specific web browser monitoring tools, which were developed based on the recommendations resulting from the semi-structured interviews. the results of this third study reinforced the notion that different monitoring activities require different types of support and also yielded several potential improvements to the tools. the findings from these three studies provide new understanding of (1) the tasks users engage in on the web; (2) how users interact with their web browsers to complete these tasks; and (3) how web browsers can better support users during these tasks.
it's a jungle out there: practical considerations for evaluation in the city. an essential aspect of mobile and ubiquitous computing research is evaluation within the expected usage context, including environment. when that environment is an urban center, it can be dynamic, expansive, and unpredictable. methodologies that focus on genuine use in the environment can uncover valuable insights, although they may also limit measurement and control. in this paper, we present our experiences applying traditional experimental techniques for field research in two separate projects set in urban environments. we argue that although traditional methods may be difficult to apply in cities, the challenges are surmountable, and this kind of field research can be a crucial component of evaluation.
"i care about him as a pal": conceptions of robotic pets in online aibo discussion forums. in this study, we analyzed people's conceptions of aibo, a robotic pet, through thier spontaneous postings in online aibo discussion forums. results showed that aibo psychologically engaged this group of participants, particularly by drawing forth conceptions of essences (79%), agency (60%), and social standing (59%). however, participants seldom attributed moral standing to aibo (e.g., that aibo deserves respect, has rights, or can be held morally accountable for action). our discussion focuses on the societal implications of these results.
robotic pets in the lives of preschool children. this study examined preschool children's reasoning about and behavioral interactions with one of the most advanced robotic pets currently on the retail market, sony's robotic dog aibo. eighty children, equally divided between two age groups, 34-50 months and 58-74 months, participated in individual sessions that included play with and an interview about two artifacts: aibo and a stuffed dog. results showed similarities in children's reasoning about the two artifacts, but differences in their behavioral interactions. discussion focuses on how robotic pets, as representative of an emerging technological genre in hci, may be (a) blurring foundational ontological categories, and (b) impacting children's social and moral development. more broadly, results inform on our understanding of the human-robotic relationship.
augmented conceptual analysis of the web. in the history of computing, there has been nothing comparable to the world wide web. no one predicted the web or its unprecedented growth, which continues almost unabated today. the purpose of this workshop is to gain some perspective on the rapidly changing landscape of the web by driving up the level of abstraction in considering significant web phenomena. we seek to create conceptual leverage to augment our understanding of what the web is, and what it will become in the future.
reciprocal eye contact as an interaction technique. modeled on how humans use eye contact to engage one another, the interaction technique presented here enables users to effectively engage devices in ubiquitous computing contexts. equipping devices to reciprocate eye contact enables users to effectively address devices, infer device attention, and target control actions.
optimizing the number of search result categories. automatically generated web search result categories were found to be beneficial in our previous study. in that study, we used 15 result categories and left the optimal number of categories issue deliberately untouched. to address this matter, we conducted a new experiment with 27 participants to compare search user interfaces with 10, 20, and 40 automatically generated categories. the results show that users prefer fewer categories. the use of fewer categories results in a slightly more accurate performance in result selection. in addition, the observed speed differences between the conditions were small. although reading longer category lists requires more time, the users benefited from the increased descriptiveness, causing the overall speed to be almost equal. according to our results, the optimal number of categories is between 10 and 20.
sketch-based rapid prototyping platform for hardware-software integrated interactive products. this paper presents a platform in which interaction designers can effectively and rapidly develop tangible interactive prototypes by sketching. the study aims to build a platform that plays the role of sketching in the hardware-software integrated interactive product design process. the platform consists of three components: a sketch based interactive concept exploration software application called stctools, a set of physical user interface(pui) widgets with a key converter and a video projection based augmented reality desk (ardesk). for prototyping, a designer creates hardware and software sketches with pen based computers using stctools. sketches of hardware and software are drawn in a client device and composed in an electronic whiteboard, which is the server device. pui widgets can be physically attached on a foam mockup or on a screen of the client device. the hardware-software integrated simulations are conducted on ardesk. the sketch simulation is captured and projected onto a paper marker created with invisible infra-red ink.
geospatial intelligence analysis via semantic lensing. geospatial displays typically contain many data layers ranging in type and level of detail that often result in dense, occluded, and cluttered map displays. we investigated a localized, "detail on-demand" filtering strategy called semantic lensing that in certain situations provides a more efficient and desirable approach than global filtering for mitigating clutter and occlusion.an initial formal user study with these semantic lenses has shown their significant value, expediency, and desirability in aiding decision making during real-world tasks. completion times of geospatial analyses are significantly faster when using lenses and workloads are significantly lower. the research suggests that using lenses may also improve analysts' accuracy when completing complex time-critical geospatial intelligence analyses. continued work will evaluate additional features and task-specific applicability. successful evaluation will propose the distribution of such a lens tool to geospatial intelligence analysts.
user centered technologies research institute. in this paper we describe the user centered technologies research institute at university of applied sciences vorarlberg. we illustrate the perspectives on hci efforts concerning analogous communication in multi-modal hci as well as our research and development services for enterprises in order to support user centered design. we also describe current research and development activities of user centered technologies research institute, the policies, and organizational background. the mission of this research institute aims to advance the level of usability of human computer interfaces within ec fp6 idea of european research area.
the effects of background music on using a pocket computer in a cafeteria: immersion, emotional responses, and social richness of medium. the focus of the present paper was to examine the effects of background music on using a pocket computer (i.e., reading entertainment news and making notes) in a noisy cafeteria environment. music listening, as compared to using pda without listening to music, prompted higher overall user satisfaction and immersion in media use, less boredom and more pleasure, and higher perceived social richness of the medium in terms of personality, liveliness, and emotionality. it was also found that pda user experience and personality (i.e., impulsive-sensation seeking [impss]) moderated some of these responses. the results are of importance given that the modern technology make it possible (1) to use computers in various everyday environments (e.g., in cafeterias and on business trips), and (2) to adapt the information and/or interfaces to fit the individual characteristics of the user.
collagemachine: temporality and indeterminacy in media browsing via interface ecology. collagemachine synthesizes artistic and computational practices in order to represent media from the world wide web (www). it functions as a process-based art work, and as a special browser which can be useful for searching. media elements are pulled from web pages and composed into a collage which evolves over time. the evolving art work / browsing session can be shaped by the user. the temporal composition of the collage develops with relation to its visual composition and semantic content. the collagemachine engine combines structured randomness and the user's expression of preferences and interests with design rules and semantic rules to make decisions about the collage's layout, and about which media to retrieve. my approach in blending music composition strategies, visual art aesthetics, and computer science techniques into this interactive environment arises through application of the theory of interface ecology.
collagemachine: temporality and indeterminacy in media browsing via interface ecology. collagemachine synthesizes artistic and computational practices in order to represent media from the world wide web (www). it functions as a process-based art work, and as a special browser which can be useful for searching. media elements are pulled from web pages and composed into a collage which evolves over time. the evolving art work / browsing session can be shaped by the user. the temporal composition of the collage develops with relation to its visual composition and semantic content. the collagemachine engine combines structured randomness and the user's expression of preferences and interests with design rules and semantic rules to make decisions about the collage's layout, and about which media to retrieve. my approach in blending music composition strategies, visual art aesthetics, and computer science techniques into this interactive environment arises through application of the theory of interface ecology.
constructing moving pictures eyes-free: an animation tool for the blind. visually impaired people constantly interpret moving phenomena in the real world; they do not lack the skills to understand the meaning of what is portrayed in an animation. however, today there is no method that allows them to create computer-based animation. we have extended ic2d, a drawing tool for the blind, to allow users to construct animation based on their drawings by defining rotation, swing, and path motions.
evaluating navigational surrogate formats with divergent browsing tasks. navigational surrogates are representations that stand for information resources within search engine result sets, e?commerce sites, and digital libraries. they also form the basis of personal collections of media, such as web pages. our hypothesis is that the formats of individual surrogates and collections play an important role in how people use collections. we are particularly interested in processes of information discovery, in which ideas are iteratively reformulated in the context of working with information.to investigate how the representation of navigational surrogates affects how people work with information, we have created a collection of undergraduate psychology curriculum resources in 3 alternative formats: a linear list of textual elements, a spatialized set of textual elements, and a spatialized set of labeled images that have been composited. to evaluate navigation with these surrogate formats during information discovery, we designed divergent browsing tasks, that is, tasks that require assembling information from multiple diverse sources. a within-subjects evaluation indicates that users prefer the spatial labeled images format, and navigate more effectively with it.
growing bloom: design of a visualization of project evolution. in this paper we describe the design behind the bloom diagram, a tool to visualize the evolution of individual participants' code and comment contributions to open source software projects. the design blends techniques such as concentric pie charts, animation, motion trails, and social proxies to produce a compact presentation of the large scale dynamics around software development. we also briefly present some preliminary findings using data gathered from sourceforge, a popular open source project hosting site, and discuss future directions for this work.
minimedia surfer: browsing video segments on small displays. it is challenging to browse multimedia on mobile devices with small displays. we present minimedia surfer, a prototype application for interactively searching a multimedia collection for video segments of interest. transparent layers are used to support browsing subtasks: keyword query, exploration of results through keyframes, and playback of video. this layered interface smoothly blends the key tasks of the browsing process and deals with the small screen size. during exploration, the user can adjust the transparency levels of the layers using pen gestures. details of the video segments are displayed in an expandable timeline that supports gestural interaction.
designing remail: reinventing the email client through innovation and integration. the remail design team defined a specification for an innovative and integrated email client. this design-lead effort tackled three key problems that email researchers have discovered: lack of context, co-opting of email, and keeping track of too many things. based on earlier design and research explorations, we conceived of a client from the ground up that attacked these problems in an integrated fashion. our solutions were based on three constructs: showing message context, marking email, and selective display. a small team of programmers implemented much of the design in a functional prototype. this experimental client continues to allow researchers to expand and explore these concepts.
introducing usability at london life insurance company: a process perspective. this presentation describes how and why usability engineering is being introduced at london life. it describes the unique set of circumstances that were present allowing us to integrate usability engineering from day one in a project. it will cover our approach to learning about and institutionalizing the usability process into a well established internal systems development area. our future plans will also be discussed.
personal media exploration with semantic regions. computer users deal with large amount of personal media data and they often face problems in managing and exploring them. the paper presents an innovative approach, semantic regions that are rectangular regions directly drawn on 2d space with semantics so that their layout can form users' various mental models toward the personal media data. a prototype personal media exploring application, mediafinder, based on the concept of semantic regions is presented. usability tests will be conducted to evaluate the semantic regions as a personal media management model including organization, search, navigation, indexing, meaning extraction, and distribution.
mediafinder: an interface for dynamic personal media management with semantic regions. computer users deal with large amounts of personal media often face problems in managing and exploring it. this paper presents semantic regions, rectangular regions that enable users to specify their semantics or mental models, and the mediafinder application, which uses semantic regions as the basis of a personal media management tool.
castaway: a context-aware task management system. this paper describes the development of castaway, a context-aware task management system. specifically, we describe a three-week field study with thirty-five participants, the results of which illuminate the nature of people's recorded tasks. we further describe in detail iterations made to our task management interface, including a map-based view, and the insights gained that will inform future design and development.
toward wearable social networking with iband. the iband is a wearable bracelet-like device that exchanges information about its users and their relationships. this exchange happens during the common gesture of the handshake, which is detected by the device. as such, iband seeks to explore potential applications at the intersection of social networking and ubiquitous computing. in this paper, we discuss the iband technology and feedback from an initial study in which 11 devices were used at two different social networking events. the results suggest that control over personal information is an ongoing issue, but they also highlight the possibility for wearable devices to enable the creation of a set of invented techno-gestures with different affordances and constraints that might be more appropriate for certain social interaction applications.
dancealong: supporting positive social exchange and exercise for the elderly through dance. the elderly face serious social, environmental, and physical constraints that impact their well-being. some of the most serious of these are shrinking social connections, limitations in building new relationships, and diminished health. to address these issues, we have designed an augmented dancing environment that allows elders to select dance sequences from well-known movies and dance along with them. the goal of dancealong is twofold: (1) to provide entertainment and exercise for each individual user and (2) to promote social engagement within the group. we deployed dancealong in a cultural celebration at a senior community center and conducted evaluations. in this paper, we present the design process of dancealong, evaluations of dancealong, and design guidelines for creating similar interactive systems for the elderly.
web tool for health insurance design by small groups: usability study. this experience report describes the challenges of evaluating the usability of a web-based collaborative health insurance benefits planning application. the application was created by researchers at the national institutes of health and the university of michigan.
how peer photos influence member participation in online communities. online communities (olcs) are gatherings of like-minded people, brought together in cyberspace by shared interests. creating such communities is not a big challenge; sustaining members' participation is. in this paper, we describe a technique for presenting members' photos and evaluate how it affects member participation in the community. we compare three different policies for presenting peer photos on the home page of the web site. our results show that explicit requests in the form of simple and short messages on the home page of a community can induce participation. we show that we were able to motivate members to (a) log into the system to see photos of fellow members, and (b) upload their personal photos.
developing user interface guidelines for dvd menus. watching dvds can be a frustrating experience, because dvd menus often miss out on usability and are complex and difficult to navigate through. similar to the early years of web development, there is a lack of design standards. in this paper, we show the development of user interface guidelines for dvd menus. these guidelines can be used to design and evaluate dvd menus. we built a prototype according to the guidelines, conducted usability tests with the prototype and evaluated other movie dvds using the guidelines to show the applicability, utility and usability of the guidelines.
a sensemaking-supporting information gathering system. this paper introduces a sensemaking-supporting information gathering system (ssigs), which provides a workspace with features that not only facilitate information search but also the representation search and representation shift which are crucial for sensemaking tasks.
transient visual cues for scrolling: an empirical study. the paper reports an empirical study, in which regular scrolling was compared with a novel scrolling technique featuring transient visual cues (tvc), that is, visual cues temporarily presented on a page to help the user locate new contents. an advantage of scrolling supported with tvc over traditional scrolling was found.
mental models of robotic assistants. if robotic assistants are to be successful, people will need appropriate mental models of what these robots can do and how they operate. we are developing techniques for measuring people's mental models of interactive robots and social agents. we aim to measure the content of these models--if they are anthropomorphic or mechanistic--and the richness of these models (how elaborate or sparse they are; how much confidence people have in them). we report progress here.
activity theory: basic concepts and applications. this tutorial introduces participants to activity theory, a conceptual approach that provides a broad framework for describing the structure, development, and context of computer-supported activities. the tutorial will consist of lectures, discussion and small group exercises. a web community will be established so attendees will be able to continue to learn about and use activity theory.
sources of structure in sensemaking. a critical aspect of sensemaking is finding appropriate representations for information important to a task. as background for the design of future systems to help people in finding such representations, this paper reports a study of where people currently get aspects of structure for their representations results show that representation construction and information seeking are closely coupled, as people get aspects of structure top down deducing from their previous knowledge, bottom up inducing from facts they find, and by borrowing from previous sensemaking efforts of others. the findings suggest important revisions of previous sensemaking theories and new opportunities for system design.
post-cognitivist hci: second-wave theories. historically, the dominant paradigm in hci, when it appeared as a field in early 80s, was information processing ("cognitivist") psychology. in recent decades, as the focus of research moved beyond information processing to include how the use of technology emerges in social, cultural and organizational contexts, a variety of conceptual frameworks have been proposed as candidate theoretical foundations for "second-wave" hci and cscw. the purpose of this panel is to articulate similarities and differences between some of the leading "post-cognitivist" theoretical perspectives: language/ action, activity theory, and distributed cognition.
non-visual overviews of complex data sets. this paper describes the design and preliminary testing of an interface to obtain overview information from complex numerical data tables non-visually, which is something that cannot be done with currently available accessibility tools for the blind and visually impaired users. a sonification technique that hides detail in the data and highlights its main features without doing any computations to the data, is combined with a graphics tablet for focus+context interactive navigation, in an interface called tablevis. results from its evaluation suggest that this technique can deliver better scores than speech in time to answer overview questions, correctness of the answers and subjective workload.
chit chat club: bridging virtual and physical space for social interaction. in this work, we create an audio-video link via an interactive sculpture to facilitate casual, sociable communication between two remote spaces. this communication installation was designed to blend the benefits of online interaction such as low risk interaction, lower barriers to entry, and minimized geographical constraints with the ease and the affordances of interacting and signalling in physical space. we describe the creation and the iterative design process for creating a social virtual-physical hybrid space-interface we call the chit chat club. in describing our design decisions, we note the advantages and disadvantages of two chit chat club installations and their effect on interaction.
social visualization: exploring text, audio, and video interaction. in this workshop, we address the importance and uses of social visualizations. in particular, we explore visualizations of text, audio, and visual interaction data to uncover social connections and interaction patterns in online and physical spaces. we stress the need to move beyond typical visualizations to date and explore new design approaches for creating social visualizations. finally, we address the need for comparing and evaluating the effectiveness of social visualizations and the approaches used to create them.
mypyramid: increasing nutritional awareness. a major challenge that new college students face is the establishment of healthy habits that will affect their long-term health. focusing on this difficult task is mypyramid: a dining hall service to support the development of healthy eating habits for busy and impressionable students. it offers an integrated student environment that builds basic nutrition and cooking skills in a fun and social manner while addressing unique student needs. in the mypyramid dining hall, students customize and cook meals that are tailored with the advice and recommendations of an "intelligent shopping basket". this intelligent basket offers personalized advice based on the usda dietary guidelines to ensure proper nutrition based on students' eating history. by teaching students basic cooking skills and educating them about how foods affect their dietary balance, mypyramid empowers students with knowledge and skills to establish long-term healthy nutritional habits [10].
a study on the use of semaphoric gestures to support secondary task interactions. we present results of a study that considers (a) gestures outside the context of a specific implementation and (b) their use in supporting secondary, rather than primary tasks in a multitasking environment. the results show semaphoric gestures offer significant benefits over function keys in such interactions, and how our findings can be used to extend models of design and evaluation for ubiquitous computing environments that support multitasking.
understanding users in consumer electronics experience design. designing a user experience is a multi-disciplinary field. while different points of view and diverse approaches are recommended due to the variety of its nature, understanding a user is important in ensuring quality outcomes in all approaches. in this paper, we describe practical user research approaches that we applied in our user experience design process for consumer electronics, approaches that can be performed with limited time and resources. these techniques have been applied in major user experience design stages including understanding user requirements, establishing design strategy, and conducting usability evaluations.
designing personalized user experiences for ecommerce: theory, methods, and research. the present workshop aims to form a community of individuals interested in exploring the user implications of personalized ecommerce applications. people working in industry, academia, and government are welcomed to participate. the aim of the two-day workshop is to access the current state of theory, methods, and research in this area and to create a theoretical framework on personalization of the user experience in ecommerce to help identify critical questions and guide future research.
emotional usability of customer interfaces - focusing on cyber banking system interfaces. emotions play a major role in the social interaction process with electronic commerce systems. this paper describes our attempts to design customer interfaces that can induce target emotions for cyber banking systems. four experiments were conducted to identify the important emotive factors and design factors, and to establish and verify causal relations between the factors. results indicate that it is possible to design customer interfaces that will elicit target emotions for the systems(e.g., trustworthiness).
cherish: smart digital photo frames for sharing social narratives at home. the introduction and rapid acceptance of digital cameras has fundamentally changed the way people take and share images. when displaying and interacting with images in the home, people still print out the photos as if they had been taken on a film camera. although sharing occurs on computer monitors or even on tv, the digital photo hasn't made complete circle in being represented digitally in a home environment. this research explores the display and social interaction with digital photos in the home.to find design opportunities we used a user-centered approach and studied how people currently display and interact with photos at home. observed needs were used to generate concept scenarios that were validated with representative users during a concept validation session. out of this has emerged the design of cherish, a system for organizing and displaying photos in the home.
cookieflavors: easy building blocks for wireless tangible input. we present cookieflavors, a tui prototyping tool that provides a set of physical input primitives realized by coin-size bluetooth wireless sensors named cookie. developers can attach cookieflavors on any physical objects and examine the suitability of tangible input in a tui prototype phase. we have built a map viewer application and projected it in an experimental room that contains various physical objects and several cookieflavors. we asked the focus group to manipulate the map viewer application by augmenting cookieflavors into physical objects. in this paper we present the interesting result of their perception and activities regarding this intuitive tui, cookieflavors.
haystack: a user interface for creating, browsing, and organizing arbitrary semistructured information. much past hci research has examined the usability concerns of information management software for specific domains such as object-oriented software design, e-mail, and the web. we believe that many of the results uncovered by these studies are applicable across multiple domains but that more broadly-scoped experiments require a system that can integrate multiple data sources. haystack is a general-purpose information management environment designed to attack this very problem. haystack's user interface, which incorporates capabilities from previous research such as context-specific visualization paradigms and attribute-based categorization, is built upon a highly expressive semistructured data model and data integration capabilities. in our demonstration we show how combination of a direct-manipulation-based ui paradigm and an expressive, federated data model can begin to address many of the information management problems plaguing general desktop computing today and can serve as a basis for further, yet unexplored, crossover information interaction experiments.
i saw this and thought of you: some social uses of camera phones. this paper presents aspects of a study into how and why people use camera phones. the study examined people's intentions at the time of image capture and subsequent patterns of use. motivated by current interest in "picture messaging", we focus on images taken to communicate with absent people and look at how they were actually used. we consider the timeliness of communication and the role of common ground to derive implications for design.
collections: flexible, essential tools for information management. while collections-aggregation mechanisms such as folders, buddy lists, photo albums, etc.-clearly play a central role in information management, the potential benefits of true first class support for collections are masked by disparate implementations that force users to pay attention to technological distinctions such as application, format, and protocol. we argue that systems should expose a single unified concept of collection and that concepts such as portals, cross-application projects, customized menus, and e-mail-task unification come about naturally as a result of our abstraction. in addition, uniform support for collections brings about a new set of capabilities for supporting creative processes. we discuss a prototype implementation of this abstraction in our haystack system, give several examples of why we believe our abstraction is useful in everyday information management, and present some preliminary results from user studies that support our hypotheses.
desktop aksi: virtual workspace concept integrating personal social communication and task management. a virtual workspace assists users to organize information on the desktop better. with such an intention, a virtual workspace concept named desktop aksi is proposed which accommodates three important aspects of desktop management i.e., finding and reminding, task-switching and spatial proximity to personal social communication. on realization of this workspace, users will be able to bring meaning and context to their task at hand. with the help of focus+context technique based on hyperbolic geometry users can navigate the information space.
user-centered eservice design and redesign. as telecom service providers struggle under the financial pressures associated with the continuing sluggish economy, plans to trim operational expenses and grow margins have been fundamental parts of their business models. key among these expense-cutting efforts has been the redirection of cost-intensive customer services communications to significantly less-costly web site portal interactions, such as online bill presentment and payment web services. however, the telecom industry survey results showed that expense savings and competitive differentiation should not be the only reason for developing these web services in order to ensure high use rate of these eservices [1]. these web services should be developed to enhance customer experience with these services. this paper presents how the user experience engineering techniques and usability test results were applied to redesign online bill presentment application to ensure the high rate of positive customer experience, and high percentage of use and adoption of these eservices. the online bill presentment application, one of eservices, has been developed for at&t's business customers.
testing for power usability. usability studies are usually conducted in a compressed time scale (measured in hours) compared with a user's eventual experience with a product (often measured in years). for this reason, typical usability evaluations focus on success during initial interactions with a product (sea for example dumas & redish, 1994 and nielsen & mack, 1994). success on initial use is often driven by familiarity. are what we call "intuitive" user interfaces really just familiar user interfaces? this "familiarity effect" can often swamp the usability differences between design alternatives. if usability evaluations continue to emphasize initial success with a product we may inhibit innovation in user interface design. there is a tension between initial usability (measured by success at first encounter) and efficiency of skilled performance. initial learning of a product's user interface often results in quite rapid increases in efficiency of use. a narrow focus on initial usability elevates learnability above efficiency once "up the learning curve". while this approach is appropriate for some products targeted primarily for casual / occasional users, it fails to capture the usability issues associated with power users (those with significant experience, training, or a professional orientation to their interaction with the product).
routeplanner. this paper discusses the routeplanner, a portable personal training and motivational aide, which displays real-time statistical and locational data. we focus on the iterative design techniques associated with developing requirements and functionality, while looking at the role user testing and feedback played in the refinement of our design.
modelling cyclic interaction: an account of feedback. this paper reports an empirical study of the effectiveness of different kinds of feedback to signal that a goal has been successfully completed. participants had to make setting changes to a simulated cell phone while at the same time dealing with incoming messages. one group had only implicit feedback that the setting had been changed so that success had to be inferred from the lack of an error message. the other groups had explicit feedback for a set period of 1, 2 or 5 seconds. the implicit feedback group were significantly less likely to complete the task than the explicit feedback groups. there is also evidence that the one second timed explicit feedback condition was less effective in inducing participants to eliminate their current subgoal than the two and five second explicit feedback conditions. a notation is introduced to explain these findings.
flexible timeline user interface using constraints. authoring tools routinely include a timeline representation to allow the author to specify the sequence of animations and interactions. however, traditional static timelines are best suited for static, linear sequences (such midi sequencers) and do not lend themselves to interactive content. this forces authors to supplement their timelines with scripted actions which are not represented. timelines also force frame-accuracy on the author, which interferes with rapid exploration of different designs. we present a redesign of the timeline in which users can specify the relative ordering and causality of events without specifying exact times or durations. this effectively enables users to "work rough" in time. we then implement a prototype and perform a user study to investigate its efficiency.
a study of the use of mobile phones by older persons. this paper reports on issues related to the use of mobile phones by older people. this study uses triangulation, a mixed method of qualitative (focus group discussions) and quantitative (online questionnaire) approaches. usage patterns, problems, perceived benefits and desired and unwanted features were covered in this study.
licai+: a comprehension-based model of learning for display-based human-computer interaction. this paper describes a model of comprehension-based learning, licai+, an extension to the comprehension-based model of display-based hci, licai [5], that simulates a user who performs tasks given as instructions. licai+ models users' learning of task performance by incorporating a process for encoding events during the task performance. a simulation of encoding and recalling events is described.
low-fi prototyping for mobile devices. this paper introduces a set of concepts for user-centered design methodologies that apply to mobile and multi-device applications. it ranges from initial data gathering and specification processes to the creation of low-fidelity prototypes and their evaluation. the focus is given to usability issues of ubiquitous, context and ambient intelligent applications. the paper's main contributions are (1) the description of our findings on how to engage on the early stage prototyping process, involving mobility; (2) a set of details that need to be taken into consideration so that the design and prototyping process is successful; (3) a set of guidelines on how to evaluate mobile applications on their context of use at an early design stage and (4) a rapid prototyping framework which allows designers to quickly move from their hand-drawn sketches to semi-functional software prototypes, particularly for pdas and smart phones.
measuring the effective parameters of steering motions. the steering law model describes pointing device motion through constrained paths. previous uses of the model are deficient because they are built using only error-free responses, ignoring altogether the path of the cursor. we correct this by proposing and validating a technique to include spatial variability, including errors. the technique is a variant of the well-known "effective target width" used in fitts' law models. an experiment designed to test our technique demonstrates the improvement: correlations are consistently higher when spatial variability is included in building the model. suggestions to aid further development of the steering law model are included.
a lost cause: the ever-improving developer's map. in this paper we describe our work in the danfoss user centred design group on the design for a frequency converter, a device which controls the speed of an electric motor. a significant part of this project lies in getting to know often unfamiliar users and use contexts. we feel that developers often look at the user's problems through developers eyes rather than through the user's eyes. having researched and actively used ethnographic field methods over the past few years, we argue that it is necessary to create an awareness of this perspective issue, its consequences for how we interpret field sessions and its influence on product development. we present a collection of existing methods that can be applied to challenge our perspective as developers and to shift our view to that of the users. to illustrate how these methods may lead to a deeper understanding we start with a portrait of one of our informants. we present two provotypes to show how we try to incorporate the users' perspective in our design solutions. finally, we reflect on the interaction language which products speak and argue that usability studies without awareness of the perspective issue make products more clear for the developers only.
benefits of animated scrolling. we examined the benefits of animated scrolling using four speeds and three different document types in terms of task speed, accuracy and user preference. we considered reading tasks involving unformatted and formatted text documents, as well as counting tasks involving abstract symbol documents. we found that, compared with non-animated scrolling, animated scrolling significantly improves average task time, by up to 5.3% using 300 millisecond animations for reading documents and by up to 24% at 500 milliseconds for symbol documents. animated scrolling also significantly decreases error rates for reading tasks by up to 54%, as well as improving satisfaction.
connecting with the absent presence: pervasive technology use and effects on community. this research investigates how the pervasive use of technology by an individual in the physical presence of group members affects community level. when technology use occurs, the individual can become an absent presence to the group-removing themselves from the context of shared group behaviors to become involved in a virtual world that is not available to those around them. depending on group norms, this individual use of technology signals a particular social message and has implications for how the group interacts. community is used as the measure of interest because of its relationship with other variables such as social trust, decision-making ability, and learning.
bridging physical and electronic media for distributed design collaboration. research on distributed collaboration has predominantly focused on shared electronic media. we have found, as other researchers have, that users often have good reason to want to work with physical media. yet they would still like to collaborate with each other. a fundamental tension exists in the design of systems to support remote collaboration when the interaction primitives are physical: physical objects live in one place. we have designed and implemented a remote collaboration system where users can still use physical objects. we introduce an interaction paradigm where objects that are physical in one space are electronic in the other space, and vice versa. our distributed system is designed for two groups, with multiple users at each end. our tangible approach is the first system to enable simultaneous, multi-input across locations. we have implemented this system as an extension to the designers' outpost[5].
user-centered design in the context of large and distributed projects. user-centered design (ucd) is a research and product development orientation that utilizes end user or customer information for making better (efficient, usable, enjoyable etc.) and thus commercially successful products. in practice, this is achieved by involving the end user early on, and maintaining this orientation throughout the developmental project.this paper presents lessons learned in eu ist project mobilife about the management of user-centered design. we reflect best practices of ucd in a setting consisting of complex technological problems being solved by large coalition of geographically distributed partners.
local ambassadors: local action/global impact. this position paper for the chi2005 development consortium introduces the local ambassadors initiative of the user experience network (uxnet), a collaborative international vision that unites user experience professionals with a variety of skills and backgrounds in a shared effort to develop a productive user experience community.
preliminary evaluation of the interactive drama . there is growing interest in technologies that support user experiences emphasizing aesthetic satisfaction and enjoyment rather than task accomplishment. evaluating such experiences remains an open research problem. here we describe a methodology for evaluating the interactive drama façade, and present the first experimental results. interactive dramas are "pure" hedonic experiences, forcing a focus on experience quality rather than efficiency and ease of use. through the coding of retroactive protocols, we reveal play patterns whereby interaction failures are leveraged into new player goals, thus supporting players in maintaining positive interest in the experience even in the face of interaction failures.
compensating for low frame rates. experiments were conducted to investigate the interdependency of frame rates (30, 15, 10 fps) and audio-visual skew (from +163 to -233 ms1). noised nonsense words like 'abagava' were presented to 20 participants who were asked to identify the middle consonant. at low frame rates (10 fps) consonant perception was impaired when audio ran ahead of video content (skew of ?113 to ?233ms). when audio lagged video, performance improved monotonically to a maximum at +167ms, where performance equaled 30fps in synch. the results suggest that frame rate and skew are not orthogonal parameters but must both be taken into consideration for av-delivery. the findings do not support the current notion that 10 fps videos do not adequately capture visual content for speech perception. participants were able to integrate the given bi-modal information as well as the 30 fps condition if the audio channel was subjected to an additional 167ms delay.
design requirements for more flexible structured editors from a study of programmers' text editing. a detailed study of java programmers' text editing found that the full flexibility of unstructured text was not utilized for the vast majority of programmers' character-level edits. rather, programmers used a small set of editing patterns to achieve their modifications, which accounted for all of the edits observed in the study. about two-thirds of the edits were of name and list structures and most edits preserved structure except for temporary omissions of delimiters. these findings inform the design of a new class of more flexible structured program editors that may avoid well-known usability problems of traditional structured editors, while providing more sophisticated support such as more universal code completion and smarter copy and paste.
targeted steering motions. in this paper we investigate targeted steering motions. fitts' law is a very successful model to explain human targeting behavior, while the steering law has been used to model steering motions. dennerlein et al. combined these two models to explain targeted steering motions, but this combination introduces additional parameters. in this paper, we present a new, simpler, model that can be used to predict targeted steering motions.
cultural usability: a localization study of mobile text messaging use. the success of mobile text messaging poses many questions for usability studies. considering the inherent usability weaknesses of mobile phones such as the small display, poor input methods, the moving environment, and noisy surroundings, this success is hard to explain with traditional usability theories that ignore the social-cultural context. a new model -- cultural usability -- is proposed for studying the intriguing processes of how cultural factors and contextual issues affect the consumption of mobile text messaging in contexts of use.
work coordination, workflow, and workarounds in a medical context. in this paper we report an ethnographic study of workarounds-informal temporary practices for handling exceptions to normal workflow-in a hospital environment. workarounds are a common technique for dealing with the inherent uncertainty of dynamic work environments. workarounds can help coordinate work, especially under conditions of high time pressure, but they may result in information or work protocols that are unstable, unavailable, or unreliable. we investigated workarounds and their effects through observation and interviews in a major teaching medical center. our results suggest 4 key features of workarounds that technologies might help address: (a) workarounds differ as a function of people's role; (b) workarounds draw on tacit knowledge of others' abilities and willingness to help; (c) workarounds can have a cascading effect, causing other workarounds down the line; (d) workarounds often rely on principles of fairness and who owes whom a favor. we provide recommendations for designing systems to better support workarounds in dynamic environments.
a tangible interface for ip network simulation. we present the ip network design workbench which supports collaborative network design and simulation by a group of experts and customers. this system is based on a tangible user interface platform called "sensetable," which can wirelessly detect the location and orientation of physical pucks. using this system, users can directly manipulate network topologies, control parameters of nodes and links using physical pucks on the sensing table, and simultaneously see the simulation results projected onto the table in real-time.
dynamic speedometer: dashboard redesign to discourage drivers from speeding. we apply hci design principles to redesign the dashboard of the automobile to address the problem of speeding. we prototyped and evaluated a new speedometer designed with the explicit intention of changing drivers' speeding behavior. our user-tests show that displaying the current speed limit as part of the speedometer visualization (i.e. the dynamic speedometer) results in safer driving behavior. designing with the intent to achieve a particular behavior can be an effective approach for increasing the safety of mission-critical systems. this is an area in which hci designers can have a significant impact.
genres as a tool for understanding and analyzing user experience in games. hci has profoundly changed the way people work with computers, it also has the potential to help shape the way people entertain in the digital age. as a popular entertainment form, games are poised to become the next frontier for hci research. however, the broader hci community only has limited knowledge of games. the intent of this demo is to paint a broad picture of today's games. we employ genre theory, which has been widely used in film study, as a framework to introduce a variety of games, analyze different interface metaphors and user experiences of games, and present innovative interaction techniques and devices used in games.
collaborative simulation interface for planning disaster measures. we introduce a disaster simulation system that supports collaborative planning of disaster measures. while several simulation tools are available for examination and evaluation of disaster prevention plans, they are limited to use on traditional computers and displays, and rarely used in collaborative planning sessions. to address this issue, we have designed and prototyped a tabletop tangible user interface for disaster simulation. this paper describes the design and implementation of our prototype and reports our preliminary user observations and their feedback. the results show that our system can effectively support collaborative emergency planning tasks by a group of users and that users can easily learn how to use our system.
privacy-enhanced personalization. consumer surveys show that online users value personalized content [5]. at the same time, providing personalization on websites seems quite profitable for web vendors [2, 6-8]. this win-win situation is however marred by privacy concerns since personalizing people's interaction entails gathering considerable amounts of data about them. as numerous recent surveys have consistently demonstrated, computer users are very concerned about their privacy on the internet. moreover, the collection of personal data is also subject to legal regulations in many countries and states. both user concerns and privacy regulations impact frequently-used personalization methods. this workshop will explore the potential of research on "privacy-enhanced personalization," which aims at reconciling the goals and methods of user modeling and personalization with privacy constraints imposed by individual preferences, conventions and laws.
will it be upper-case or will it be lower-case: can a prompt for text be a mode signal? the new forms of interaction being devised for small mobile devices have required designers to re-visit basic principles for user interface design. one of these is the notion of mode. for example, when a key is pressed how will the user know whether the letter displayed will be in upper- or lower-case. an experiment is described in which users have to learn to use a new device where this is an issue. results show that users are influenced by the case of letters in the prompt.
interaction techniques and applications for peephole displays. this demonstration presents several interaction techniques enabled by peephole displays, an interface metaphor based on situating information in physical space and providing a movable window on the space. using a peephole display, it is possible to browse a large map using one hand, to draw objects larger than the screen, and to perform drag-and-drop in 3-d. example applications that exploit these techniques are shown.
computer aided creativity and multicriteria optimization in design. establishing that machines cannot automate creative design and that it is a difficult task for humans, i propose a computational model based on the human and machine complementarity and collaboration.
seascape and volcano: visualizing online discussions using timeless motion. motion is the strongest visual appeal to attention [2], yet it is rarely used in the visualization of large-scale quantitative information. motion is complex; it can vary across numerous dimensions, each of which is potentially an information-bearing element in the visualization. which dimensions are used and how the data is mapped onto them are the key questions in using motion effectively. in this paper we present two interfaces that use motion as the primary visual element for representing data. these interfaces, seascape and volcano, use periodic animation loops to represent key social interaction features in online discussions. we propose that motion may be particularly well suited for representing data about behavior and actions, creating visualizations that intuitively depict different levels and types of activity. in this paper we describe the interfaces we have built and present the results of preliminary user studies.
mediators: guides through online tv services. the mediator prototype which is demonstrated is the result of exploratory research into domestic online entertainment services. mediators are anthropomorphic guides who aid users in selection and navigation to content in interactive television services. the project goals include developing prototype services and navigation tools and carrying out extensive user tests. the main focus of the work is to develop models of interaction, functionality and system behaviour.
two-handed drawing on augmented desk. this paper describes a two-handed drawing tool on enhanced desk. through the experiments, our tool showed better performance when drawing simple figures than traditional drawing tools. the subjects also reported that it was easier to learn the usage of the tool.
common sense investing: bridging the gap between expert and novice. in this paper, we describe common sense investing (csi), an interactive investment tool that uses a knowledge base of common sense statements in conjunction with domain knowledge to assist personal investors with their financial decisions, primarily asset-allocation. in interfaces that provide expert advice, one key problem is elicitation - how to ask questions that enable the expert model to make decisions, and at the same time, are understandable to the novice. the second problem is explanation - how to explain rationale behind expert decisions in terms that the user can understand. many programs already encode expert models, but few have good models of novice knowledge, especially where broad knowledge of everyday life might bear on the subject. omcsnet, a semantic network representation of the openmind common sense knowledge base, is the source of a wide range of facts about day-to-day life. csi maps the user's goals, expressed in concepts from omcsnet, to the expert's goals, expressed in technical financial terms. instead of asking "what is your tolerance for risk?" where the user might not understand the concept of risk tolerance, we can ask, "do you usually have a lot of credit card debt?" aligning the expert's questions and decisions with common sense knowledge pertinent to the user increases the user's confidence in the ability of the system to meet their needs.
two-handed interaction on a tablet display. a touchscreen can be overlaid on a tablet computer to support asymmetric two-handed interaction in which the preferred hand uses a stylus and the non-preferred hand operates the touchscreen. the result is a portable device that allows both hands to interact directly with the display, easily constructed from commonly available hardware. the method for tracking the independent motions of both hands is described. a wide variety of existing two-handed interaction techniques can be used on this platform, as well as some new ones that exploit the reconfigurability of touchscreen interfaces. informal tests show that, when the non-preferred hand performs simple actions, users find direct manipulation on the display with both hands to be comfortable, natural, and efficient.
comparing the immediate usability of graffiti 2 and virtual keyboard. this paper presents the results of an empirical study on the input system of the most frequent pda operating system, palmos from palm inc. in an experiment with novice users we compared the stroke based alphabet graffiti 2 with the virtual keyboard and the predictive add-on wordcomplete from cic software for graffiti 2. we found that although text input with graffiti 2 was significantly slower and generated a higher error rate (9 wpm; 19%) than text input with the virtual keyboard (13 wpm; 4%), there was no significant difference in usability and task load rating. wordcomplete for graffiti 2 had no significant impact on performance but enhanced user comfort.
vrmath: knowledge construction of 3d geometry in virtual reality microworlds. because of the complexity of 3d geometry (e.g., 3d transformations) and the constraints in our real environments (e.g., body movement and manipulation of objects), most young children have difficulty in learning 3d geometry concepts and processes. therefore, in order to address this issue, a prototype virtual reality learning environment (vrle) named vrmath that set out to enable children to move in, manipulate objects, and construct programs to create objects in a 3d environment was designed and evaluated. the design of the hci components of vrmath was influenced by educational semiotics [2, 5], which connect mathematical meanings with multiple semiotic resources. the evaluation, which involved six children, focused on both the design of vrmath and the learning within vrmath. many new ways about thinking and doing 3d geometry and issues about the usability of vrmath were identified during the evaluation. these have implications for learning within and design of vrles.
implications for designing the user experience of dvd menus. dvd menus often miss out on usability and are complex and difficult to navigate through. one of the main problems is the lack of design standards. by conducting an expert walkthrough we identified typical usability issues of dvd menus and verified them with usability testing and a user survey. our research goal is to develop a set of specific solutions for designing usable dvd menus to improve the overall user experience. as a first step towards this goal we present an initial set of usability issues that are specifically relevant for dvd menu design.
using an intergenerational communications system as a 'light-weight' technology probe. a problem with the technology probe [1] approach is the substantial time required to gain results. for prototype technological systems, a further problem is the requirement that systems are deployed into non- technical end-user's homes, where they are comparatively hard to maintain. even a robust system may be vulnerable to unavoidable problems in these kinds of environment (for example, bandwidth outages in a communications device). we introduce a light-weight procedure that sacrifices some of the realism associated with technology probes in favor of ease of deployment and speed of information gathering.we apply our methods to the "keep in touch" (kit) intergenerational communications system, and describe some preliminary results that we have obtained.
world wide web as usability tester, collector, recruiter. the usability team at wildfire communications inc. conducted a usability test using the world wide web (www) as a method to advertise the test, recruit participants and gather data --- all automatically.the test was conducted over the course of only 2 days during which we collected useful information from 96 people.the usability test was for a speech system using participants recruited by internet newsgroups, e-mail lists and the www. using these resources helped us to get a large population to test the system in a short period of time.
focus+context sketching on a pocket pc. current personal digital assistants (pdas) such as pocket pcs provide little support for sketching. this is due, no doubt, to the limited screen size and relatively poor resolution of these devices. to support sketching on these devices, we describe a focus+context technique using fisheye views integrated into a sketching application on pocket pcs. our technique creates a distorted display view of a canvas that is larger than a pocket pc screen. users draw in a high resolution focus area that is smoothly embedded into the distorted context. we have conducted a modest user trial that validates user preference for this drawing technique over a traditional scroll-bar based interface.
directions in hci education, research, and practice in southern africa. this paper focuses on the current status and directions of human-computer interaction (hci) education, research, and practice in southern africa.
challenges in teaching user interface design for telephones and cell phones. participants in this sig will identify issues and suggest solutions for teaching user interface design for telephones and cell phones. specifically, speech user interface development environments, implementation languages, unique problems of speech interfaces, and additional resources will be examined. participants will include educators who teach web development, and web developers interested in developing speech applications.
when design is not the problem: better usability through non-design means. when it comes to shipping quality software, design is not the hard part. methods and techniques to study users, best practices for creating iterative designs, and tools to validate them are all very well documented. unfortunately, in chaotic and complex ecosystems very few of the designs actually end up making it through the user-centered design (ucd) process. interaction designers' input is either ignored or interpreted through a development/business lens and considerable fidelity is lost. as a result, designers too often throw up their hands and blame the technology or the organizations. these barriers can be overcome if designers broaden their roles and better understand other stakeholders' charters. successful collaboration with other disciplines that make up the software development lifecycle is the key to success. practical case studies will be discussed where usability, attractiveness, and good design were achieved through non-design means. poor information architecture, screen layout, and task flows were not the barriers to usability. design impact was made instead through overcoming barriers in technology, organizational structure, legal, marketing, documentation / quality assurance (qa), and development tools.
principles for mujltimodal user inteface desgin. the goal of this workshop is to identify ten guiding principles for designing multimodal user interfaces. researchers will use these principles to identify topics requiring further research. practitioners will use these principles to generate guidelines for designing multimodal user interfaces.
use of research-based guidelines in the development of websites. the communication technologies branch at the national cancer institute has been working for the past two years to identify research related to web design and usability and to translate that research into web design guidelines. this effort has resulted in a set of approximately 200 guidelines that have strength of evidence and relative importance ratings. panel members vary in their opinions on how and when to make the best use of guidelines in the development of websites. they will discuss issues related to translating research to guidelines, validation of guidelines, usability of guidelines themselves, and how to handle conflicting research.
automatic capture, representation, and analysis of user behavior. the goal of this workshop is to explore the implications of automated capture and analysis of user behaviors on hci and ue research.
text analysis as a tool for analyzing conversation in online support groups. in this paper we describe a software tool that allows investigators to make comparisons across different online forums and media by analyzing word counts in user-specified categories. using a large sample of messages from a bipolar support chatroom, we demonstrate how this tool can be used to characterize the nature of the discourse and compare it to other media, to analyze relationships among different word categories, and to characterize changes in visitors' discourse over time. future plans for adding functionality to the software and using external data for additional validation are also discussed.
cost294-mause: a pan european usability research community. cost294-mause is a usability research community. its ultimate goal is to bring more science to bear on usability evaluation and being realized through scientific activities of four working groups. the community's hitherto achievements and future working plans are described.
homie: an artificial companion for elderly people. in this paper we present "homie" an artificial companion for elderly people. our approach emphasizes amusement and benefit - amusement in form of entertainment and benefit in terms of medical care. the key to awake elderly people's emotional engagement in an artificial companion is its emotional behavior. therefore, we propose a companion that does not look technical, which is mostly associated with the words cold and impersonal. furthermore it features facial expression and gesture. an important design aspect was that it is no additional burden for elderly people. engaging with it is free and fun.
robotic method of taking the initiative in eye contact. eye contact is an effective means of controlling human communication, such as in starting communication. it seems that we can make eye contact if we simply look at each other. however, this alone does not establish eye contact. both parties also need to be aware of being watched by the other. we proposed an eye-contact method between humans and robots satisfying these two conditions. in our previous work, however, we mainly consider eye contact from humans to robots. in this paper, we consider the reversal case. we deal with cases where a robot wants to start communication with a particular person. in such cases, the robot needs to make the person aware of its gaze. the robot should make the person feel clearly that it is none other than him/her who the robot is looking at. we show through experiments that the body action of the robot is effective for this.
physical-digital ensembles for mobile interaction. we describe ensemble interactions, which bridge the gap between the physical and digital worlds, enabling users to leverage paper tools and computers in tandem. our projects (e.g., see figure 1) serve as test beds for these interactions. this research will inform mobile and tangible computing, where integrated paper-electronic interfaces will have great impact.
breaking the laws of action in the user interface. fitts' law, steering law and law of crossing, collectively known as the laws of action, model the speed-accuracy trade-offs in common hci tasks. these laws impose a certain speed ceiling on precise actions in a user interface. my hypothesis is that for some interfaces, the constraints of these laws can be relaxed by using context information of the task. to support this thesis, i present two systems i have developed for pen-based text input on stylus keyboards. these systems break either fitts' law or the law of crossing by taking advantage of high-resolution information from the pen, and the fact that words can be seen as patterns traced on the keyboard. using these systems users can potentially gain higher text entry speed than on a regular stylus keyboard that is limited by the laws of action. i conclude by discussing planned future research, primarily improved visual feedback and empirical evaluation.
robotic wheelchair looking at all people. although several robotic/intelligent wheelchairs have been proposed recently,they consider friendliness only to their users. machines like wheelchairs interact various people other than their users. they must consider friendliness to all these people. this paper presents a robotic wheelchair that cares for all relevant people: users, pedestrians, and caregivers, by looking at these people. it looks at the user's face, observing its direction. the user can turn it by looking in his/her desired direction. it looks at pedestrians and changes the way of avoidance against them depending on whether or not their noticing it. in addition, it looks at the caregiver when he/she is with it and keeps moving with him/her.
visualizing a computer mediated communication (cmc) process to facilitate knowledge management. the archive of a computer-mediated communication (cmc) process contains knowledge shared and implicit information about participants' behavior patterns during discussion. however, most cmc systems focus only on organizing the content of discussions. on the other hand, the social visualization research has developed techniques to depict human behaviors during a process of cmc but has not been integrated in any organizational memory system yet. in addition, the impacts of the graphical representations created by social visualization techniques have seldom been studied. the dissertation thus proposes a two-phase research to address those issues. the first phase proposes a prototype system that integrates a social visualization technique with various information analysis technologies to graphically summarize both the content and behavior of a cmc process. the second phase proposes to adopt the "de-featuring" approach used by previous interface evaluation studies to evaluate how the graphical interface developed affects users' information acquisition and evaluation process.
isometric pointer interfaces for wearable 3d visualization. 3d visualizations will soon be important wearable computer applications. however, 3d interaction can be problematic, especially in a wearable computing environment. we evaluated four 3d interaction methods using isometric joysticks common to wearable computing. subjective and objective results favor a two-handed, aircraft-like interface mapping.
new issues in teaching hci: pinning a tail on a moving donkey. as technology changes, so does the area of human-computer interaction. hci education must continuously change to meet the new challenges to user interaction. the world wide web and other distributed networks, hand-held devices, and embedded computing all present new challenges for user-centered design methods, usability testing, and other forms of evaluation. in addition, as more people use technology, the diversity of users increases, requiring increased attention to concepts such as accessibility and universal usability. this panel will address the challenges of keeping hci education up-to-date and offer approaches that have been successfully used. the four major topics addressed by the panel will be 1) the challenge of rapidly changing technology, 2) new methods for user-centered design, 3) student involvement with users, and 4) balancing hci theory and hci practice.
what's my method?: a game show on games. what's my method? is the game show that asks the question, "how do you user-test games?" the goal of this session is to highlight important differences between user research methods for games and productivity software in an instructive and engaging format. emotion measurement scenarios are presented to the contestants and audience as questions in a fictional game show. three games researchers "compete" to propose the best methodology to research thorny questions from real games. the audience acts as the judge, deciding how many points to award contestants for their answers.
all together now: visualizing local and remote actors of localized activity. we present all together now (atn), a tool for visualizing localized activities involving both local and remote actors. atn presents each user with a webpage containing a common view of a shared virtual space modeled after the physical locus of the activity. actors signal socially meaningful behavior by manipulating the spatial positions of their representations in this space. local actors' positions are acquired automatically using computer vision. remote actors indicate their positions with a mouse. actors are not expressly identified. atn exploits people's culturally established notions of spatial position to help them convey contextually relevant social cues to each other. conveying just enough spatial and identity information helps optimize-without needlessly eliminating-the awareness asymmetries intrinsic to localized distance work
who wants to know what when? privacy preference determinants in ubiquitous computing. we conducted a questionnaire-based study of the relative importance of two factors, inquirer and situation, in determining the preferred accuracy of personal information disclosed through a ubiquitous computing system. we found that privacy preferences varied by inquirer more than by situation. that is, individuals were more likely to apply the same privacy preferences to the same inquirer in different situations than to apply the same privacy preferences to different inquirers in the same situation. we are applying these results to the design of a user interface for managing everyday privacy in ubiquitous computing.
understanding research trends in conferences using paperlens. paperlens is a novel visualization that reveals trends, connections, and activity throughout a conference community. it tightly couples views across papers, authors, and references. paperlens was developed to visualize 8 years (1995-2002) of infovis conference proceedings and was then extended to visualize 23 years (1982-2004) of the chi conference proceedings. this paper describes how we analyzed the data and designed paperlens. we also describe a user study to focus our redesign efforts along with the design changes we made to address usability issues. we summarize lessons learned in the process of design and scaling up to the larger set of chi conference papers.
developing collaborative applications using the world wide web "shell". the world wide web is often viewed as the latest and most user friendly way of providing information over the internet (i.e., server of documents). it is not customarily viewed as a platform for developing and deploying applications. in this tutorial, we introduce and demonstrate how web technologies can be used in combination with web browsers to design, create, distribute and execute collaborative applications. we discuss how html in combination with cgi scripts, javascript, and java can be used to develop interactive and collaborative applications. we discuss recent extensions and additions that support sophisticated application development as well as the constraints with the www 'shell' approach. the term world wide web 'shell' is used in a manner analogous to the use of the term expert system shell. specifically, the components of the www provide basic functionality and services for developing application in much the same way as an expert system shell provides components for developing expert system applications.
a gesture-based american sign language game for deaf children. we present a system designed to facilitate language development in deaf children. the children interact with a computer game using american sign language (asl). the system consists of three parts: an asl (gesture) recognition engine; an interactive, game-based interface; and an evaluation system. using interactive, user-centered design and the results of two wizard-of-oz studies at atlanta area school for the deaf, we present some unique insights into the spatial organization of interfaces for deaf children.
attention meter: a vision-based input toolkit for interaction designers. this paper shows how a software toolkit can allow graphic designers to make camera-based interactive environments in a short period of time without experience in user interface design or machine vision. the attention meter, a vision-based input toolkit, gives users an analysis of faces found in a given image stream, including facial expression, body motion, and attentive activities. this data is fed to a text file that can be easily understood by humans and programs alike. a four day workshop demonstrated that some flash-savvy architecture students could construct interactive spaces (e.g. taiker-ktv and screammarket) based on body and head motions.
: an adaptive interactive orchestral conducting system for digital audio and video streams. we present isymphony, an interactive orchestral conducting system for digital audio and video that adaptively adjusts to the user's conducting style. using a digital baton, users may control the tempo, volume, and instrument emphasis of a digital audio and video recording of an orchestra. the system adaptively recognizes three gesture profiles: the four-beat neutral-legato pattern, an up-down pattern, and random gestures. the system uses an audio time-stretching algorithm we developed that allows the playback speed of a digital audio recording to be arbitrarily adjusted without changing its pitch. isymphony is an example of how computers can enable more people to experience an interaction style normally limited to a few people (conductors), and is installed as part of the it's artastic! exhibit at the betty brinn children's museum in milwaukee, usa.
more than just fun and games: assessing the value of educational video games in the classroom. the objective of this preliminary study is to investigate whether educational video games can be integrated into a classroom with positive effects for the teacher and students. the challenges faced when introducing a video game into a classroom are twofold: overcoming the notion that a "toy" does not belong in the school and developing software that has real educational value while stimulating the learner. we conducted an initial pilot study with 39 second grade students using our mathematic drill software skills arena. early data from the pilot suggests that not only do teachers and students enjoy using skills arena, students have exceeded our expectations by doing three times more math problems in 19 days than they would have using traditional worksheets. based on this encouraging qualitative study, future work that focuses on quantitative benefits should likely uncover additional positive results.
nodding in conversations with a robot. in this demo we describe our ongoing efforts to build a robot that can collaborate with a person in hosting activities. we illustrate our current robot's conversations, which include gestures of various types, and report on extensions to the robot's existing gestural abilities to be able to recognize nodding in conversations.
sensing activity in video images. video-based awareness tools increase familiarity among remote group members and provide pre-communication information, low-cost iconic indicators provide less but more succinct information than video images while preserving privacy. observations of and feedback from users of our video awareness tool suggest that an activity sensing feature along with a variety of privacy options combines advantages of both the video images and iconic indicator approaches. we introduced the activity sensing feature in response to user requests. it derives activity information from video images and provides options to control privacy and improves the usability of video-based awareness tools.
creating and managing user partnership programs. in this workshop, we will discuss our experiences and share best practices in creating and utilizing a user partnership program (upp) to help overcome the challenges of collecting customer feedback in environments characterized with diverse users and business processes, complex technology infrastructures, and large scale enterprise software deployments.
pmeb: a mobile phone application for monitoring caloric balance. in this paper, we present pmeb, an application for mobile phones that allows users to monitor their caloric balance as a part of weight management. pmeb allows users to track their caloric balance by recording food intake and physical activity on their mobile phones. daily reminder messages are sent via sms messages to encourage compliance. collected data is sent automatically every 24 hours to a central server where it can be analyzed in detail. pmeb was designed as a tool for both users to self-monitor and manage their food consumption and physical activity and primary health care providers to study behavioral patterns in overweight patients. formative evaluation with seven health-intervention experts and a week-long user study with six clinically overweight, non-expert participants have shown pmeb to have promising potential for improving self-efficacy in dietary and exercise behavior.
two methods for auto-organizing personal web history. two methods for automatically organizing personal web history were developed and evaluated, and compared to the internet explorer history. one method grouped visited web pages based on similarity of root url and time co-occurrence. the second method started with the similarity ratings and further associated or dissociated web pages using an associative learning rule. in a preliminary experiment, participants reported that both methods organized their web history significantly more like their own mental organization of their web history than did ie history. participants were also faster to revisit web pages using both organizations than when using ie history.
supporting engagement in asynchronous education. a key challenge for software that supports asynchronous distance education is to engage and guide students who are not interacting in real-time. we describe a first study of two approaches to adding interactive exercises to the viewing of videotaped lectures. we found individual differences, but a surprising tendency to prefer more intrusive exercises. we conclude with possible next steps.
unifying the cisco intranet through hierarchical navigation. cisco web-enabled numerous processes during a period of rapid growth, resulting in a number of disconnected sites and tools. although this innovation cut costs, employees could not easily find information and had to learn new models of navigation and interaction. this paper describes how the intranet strategy team responded by designing a hierarchical navigation system that met user and business requirements, connected numerous isolated sites, and encouraged standardization and governance of the intranet. the team leveraged prior work on navigation for cisco's public web site, created and tested a series of prototypes, and integrated the final design with an innovative template framework. the result was better navigation, increased relevancy, and reduced costs.
cubik: a bi-directional tangible modeling interface. we present cubik, a bi-directional tangible modeling interface used to aid architects and designers in the process of creating and manipulating 3d models with the computer. cubik consists of a wire frame cube structure and an interactive virtual cube as its user interfaces. when activated users can manipulate a 3d model from either interface physically or virtually. any one interface can change its configuration according to manipulations from the other interface, enabling designers to directly assemble and manipulate tangible objects as an aid in designing 3d models. this can improve the interaction between designers and computer-aided design systems.
understanding how bloggers feel: recognizing affect in blog posts. one of the goals of affective computing is to recognize human emotions. we present a system that learns to recognize emotions based on textual resources and test it on a large number of blog entries tagged with moods by their authors. we show how a machine-learning approach can be used to gain insight into the way writers convey and interpret their own emotions, and provide nuanced mood associations for a large wordlist.
"when i'm sixty-four...": are there real strategies for providing universal accessibility for the elderly. in this panel we will present four strategies for providing computing for the elderly. we hope to generate discussion and ideas of the plusses and minuses of these strategies.
usability testing of world wide web sites. world wide web (web) site usability - for better or worse - affects millions of users on a daily basis. as the capabilities of the web continue to expand through html extensions, vrml, java, and activex, site designers are becoming overwhelmed by a proliferation of viable interaction techniques. just because a technology is possible, however, does not mean it is desirable, nor that it is being incorporated in a productive manner. many web sites, both those connected to the internet and those available through an institutional intranet, have become cluttered with useless and confusing, albeit cool, new features.
dynamic query sliders vs. brushing histograms. dynamic queries facilitate exploration of information through real-time visual display of both query formulation and results. dynamic query sliders are linked to the main visualization to filter data. a common alternative to dynamic queries is to link several simple visualizations, such as histograms, to the main visualization with a brushing interaction. selecting data in the histograms highlights that data in the main visualization. we compare these two approaches in an empirical experiment on dynamaps, a geographic data visualization tool. dynamic query sliders resulted in better performance for simple range tasks, while brushing histograms was better for complex comparison, tradeoff, and pattern tasks. participants preferred brushing histograms for understanding relationships between attributes.
ifq: a visual query interface for object-based image retrieval. there are two major directions for image retrieval interface development. one direction is manipulation through query languages, which is more precise to computers but not user friendly since users need to know database schema and query languages. another disadvantage is that query languages do not visualize queries so that users can match the query representation with their mental models. approaches include keyword-based interfaces and sql-like query languages.
out of many, one: reliable results from unreliable recognition. recognition technologies such as speech recognition and optical recognition are still, by themselves, not reliable enough for many practical uses in user interfaces. however, by combining input from several sources, each of which may be unreliable by itself, and with knowledge of a specific task and context that the user is engaged in, we might achieve enough recognition to provide useful results. we describe a preliminary experiment to assist the user in giving directions for urban navigation by combining partial results from unreliable speech recognition and unreliable visual recognition.
perspectives on end user development. the goal of the workshop is to bring about a coherent research agenda in the field of end user development. we seek contributors concerned with: adaptability, adaptivity, tailoring of system functionality and user interfaces, the use of annotations for individuals and user groups, and use of effective visual and multimedia representations.
the role of the interaction designer in an agile software development process. in this paper we describe observations of a contrast in thinking styles between a user-interface design team and a software engineering team developing a new software product. presented in case study form, it is a first hand account by the interaction designers of work-in-progress. it concludes by identifying some key roles for the interaction designer working in an agile software development environment .
the role of context in question answering systems. despite recent advances in natural language question an-swering technology, the problem of designing effective user interfaces has been largely unexplored. we conducted a user study to investigate the problem and discovered that overall, users prefer a paragraph-sized chunk of text over just an exact phrase as the answer to their questions. fur-thermore, users generally prefer answers embedded in con-text, regardless of the perceived reliability of the source documents. when users research a topic, increasing the amount of text returned to users significantly decreases the number of queries that they pose to the system, suggesting that users utilize supporting text to answer related ques-tions. we believe that these results can serve to guide future developments in question answering user interfaces.
graphics matter: a case study of mobile phone keypad design for chinese input. developing more effective and efficient chinese character input methods has the potential to help chinese mobile phone users (currently 320 millions) input text messages. itap(r) supports input based on the writing structure of chinese characters. current keypad graphics include three items: digits (0-9), letters (a-z), and symbols that represent the minimum writing units of chinese characters (strokes). our study revealed the difficulties of mapping these strokes to individual keys using the current symbols. we present a case study illustrating the user-centered redesign of these symbols. the new symbols allow for faster entry speeds and lower error rates as compared to the current commercial solution. results with our solution were also favorable when compared to pinyin, a popular cross-cultural solution relying on the roman alphabet. the new design is in the process of being integrated into commercial mobile phones for users who would prefer native input methods for chinese.
designing interfaces to afford enjoyable social interactions by collocated groups. the main aim of this research is to understand how domestic technologies for collocated groups can be designed to afford enjoyable social interactions. a secondary aim is to devise process measures to assess the nature of these interactions. this study presents a number of process measures and uses them to evaluate differences in groups' social behaviour when sharing photos as prints compared to when photos are presented using a television. differences in gesturing behaviour towards the photos were evident across the two conditions. however, aspects of verbal behaviour that were measured, which were taken to be indicative of enjoyable social interactions, were not found to vary.
designing appropriate affordances for electronic photo sharing media. in contrast to printed photos, practices for sharing digital photos are yet to become well established. consequently, they have received relatively little attention in the literature. six individuals from four households were interviewed to understand how the co-present use of different digital media might affect people's perceptions and enjoyment of photo sharing. a number of observations made by the participants were identified that have implications for design and for further work. primarily, new display technologies need to: (i) allow people to interact facing one another in comfortable surroundings, and (ii) afford easy control of the presentation by both photographer and audience.
affective diary: designing for bodily expressiveness and self-reflection. a diary provides a useful means to express inner thoughts and record experiences of past events. in re-readings, it also provides a resource for reflection, allowing us to re-experience, brood over or even shed the thoughts and feelings we've associated with events or people. to expand on the ways in which we creatively engage in diary-keeping, we have designed an affective diary that captures some of the physical, bodily aspects of experiences and emotions--what we refer to as "affective body memorabilia". the affective diary assembles sensor data, captured from the user and uploaded via their mobile phone, to form an ambiguous, abstract colourful body shape. with a range of other materials from the mobile phone, such as text and mms messages, photographs, etc., these shapes are made available to the user. combining these materials, the diary is designed to invite reflection and to allow the user to piece together their own stories.
combining multiple gaming interfaces in epidemic menace. this paper presents the multiple gaming interfaces of the crossmedia game epidemic menace, including a game board station, a mobile assistant and a mobile augmented reality (ar) system. each gaming interface offers different functionality within the game play. we explain the interfaces and describe early results of an ethnographic observation showing how the different gaming interfaces were used by the players to observe, collaborate and interact within the game.
streaming format software for usability testing. audio and video capture for qualitative usability testing requires multiple video sources to be synchronized for subsequent playback along with any required test data. windows media player 9 is limited to playing only single video streams. this paper describes the architecture of a software system that has been developed to overcome the single stream of video and allow multiple synchronized audio, video and data streams suitable for usability testing. post processing and the practical application of using multi-stream software tool in usability testing are then discussed with example qualitative testing situations.
attitudes towards technology use in public zones: the influence of external factors on atm use. this study used a grounded theory approach to find factors that influence current and future use of technological systems in public zones. fifteen participants who were either frequent or non-frequent automated teller machine (atm) users were interviewed. they were asked their opinions, views, feelings and any other issues that they felt were important to them when using an atm and that effected their use. from the themes and concepts that emerged from the data a conceptual model of atm use was constructed. the model builds on ideas from the technology acceptance model but additionally postulates that external factors such as perception of privacy exert an effect on attitude to use.
paper or interactive?: a study of prototyping techniques for ubiquitous computing environments. we studied the effects of varying the fidelity and automation levels of a ubicomp application prototype. our results show that the interactive prototype captured the same usability issues that the paper prototype studies did and more. we found that paper prototyping is insufficient for supporting unique ubicomp requirements, such as scalability, but a prototype with higher fidelity and automation levels can enhance the quality of interaction data available for evaluation.
programmatic semantics for natural language interfaces. an important way of making interfaces usable by non-expert users is to enable the use of natural language input, as in natural language query interfaces to databases, or muds and moos. when the subject matter is about procedures, however, we have discovered that interfaces can take advantage of what we call programmatic semantics, procedural relations that can be inferred from the linguistic structure. roughly, nouns can be interpreted as data structures; verbs are functions; adjectives are properties. some linguistic forms imply conditionals, loops, and recursive structures.we illustrate the principles of programmatic semantics with a description of metafor, a "brainstorming" editor for programs, analogous to an outlining tool for prose writing. metafor interactively converts english sentences to partially specified program code, to be used as "scaffolding" for a more detailed program. a user study showed that metafor is capable of capturing enough programmatic semantics to facilitate non-programming users and beginners' conceptualization of programming problems.
visualizing the affective structure of a text document. this paper introduces an approach for graphically visualizing the affective structure of a text document. a document is first affectively analyzed using a unique textual affect sensing engine, which leverages commonsense knowledge to classify text more reliably and comprehensively than can be achieved with keyword spotting methods alone. using this engine, sentences are annotated using six basic ekman emotions. colors used to represent each of these emotions are sequenced into a color bar, which represents the progression of affect through a text document. smoothing techniques allow the user to vary the granularity of the affective structure being displayed on the color bar. the bar is hyperlinked in a way such that it can be used to easily navigate the document. a user evaluation demonstrates that the proposed method for visualizing and navigating a document's affective structure facilitates a user's within-document information foraging activity.
context photography: modifying the digital camera into a new creative tool. context photography consists of capturing context when taking a picture, by sensing physical input in addition to light and representing it visually in real time. by developing this concept, we explore alternative potentials of digital cameras as everyday creative tools. we have developed two prototypes and tested them in user workshops. based on the results of this process, we present implications of such modifications of underlying characteristics of a still camera.
are designers ready for ubiquitous computing?: a formative study. ubiquitous computing is increasingly becoming reality, even for people outside of research. a group that will have to face the challenges of this new technology is product and industrial designers. to get a designer's view of ubiquitous computing, we demonstrated the smart-its ubiquitous computing prototyping platform to 16 product designers and collected their impressions during a workshop. our results show that the way designers approach technology differs from that of researchers, which indicates the need for more comprehensive workshops.
lafcam: leveraging affective feedback camcorder. if a video camera recognizes and records affective data from the camera operator, this data can help determine which sequences will be interesting to the camera operator at a later time. in the case of home videos, the camera operator is likely to also be the editor and narrator of the final video. lafcam is a system for recording and editing home video. we facilitate the process of browsing and provide automatic editing features by indexing where the camera operator laughed and visualizing the skin conductivity and facial expressions in the editing session.
mr.web: an automated interactive webmaster. this paper describes a system, mr.web, designed to interact with users over email to create and update web pages. our goal is that users interact with mr.web as if it were a human webmaster. we collected 325 examples of people writing email requests to a webmaster, and used this to generate the semantics of mr.web's email parser. the results of the survey indicate that the limited context of a webmaster gives us a reasonable subset of the natural language processing (nlp) problem. this paper explains the system design, user study results, and plans for future work.
creating an educational digital library: grow a national civil engineering education resource library. the grow (geotechnical, rock and water engineering) project (http://www.grow.arizona.edu) is the first iteration of a national civil engineering education resource library (ncerl). this educational digital library uses precise coding and metadata to integrate fully with the national sciences digital library (nsdl) and to meet the learning, teaching, and research needs of audience groups consisting of k-12, higher education, engineering professionals, and the community at large. grow is a portal to reviewed civil engineering resources throughout the world wide web and interactive, multimedia learning objects created by grow team members. through this project we demonstrate how to create an educational digital library that is flexible enough to meet the needs of a diverse audience and innovative enough to provide interactive self-contained learning objects.
silver: simplifying video editing with metadata. digital video is becoming increasingly ubiquitous. however, editing video remains difficult for several reasons: it is a time-based medium, it has dual tracks of audio and video, and current tools force users to work at the smallest level of detail. based on interviews with professional video editors, we developed a video editor, called silver, that uses metadata to make digital video editing more accessible to novices. to help users visualize video, silver provides multiple views with different semantic content and at different levels of abstraction, including storyboard, editable transcript, and timeline views. silver offers smart editing operations that help users resolve the inconsistencies that arise because of the different boundaries in audio and video.
dealing with mobile conversations in public places: some implications for the design of socially intrusive technologies. in this paper we describe the results of a study investigating the behaviour and views of bystanders in response to a proximal mobile telephone conversation by a third party. analysis of the data revealed that despite varied expressed views on embarrassment, discomfort and rudeness, patterns of behaviour were remarkably similar. mechanisms of disengagement were employed by all of the participants so that they were demonstrably not attending; yet all of them were able to report on the precise content of the overheard calls. other social mechanisms were used by the bystanders to diffuse the perceived intrusiveness of the call and to grant "permissions" for these intrusions. implications are drawn from the study for the design of mobile and ubiquitous computing applications.
resizing beyond widgets: object resizing techniques for immersive virtual environments. the most common technique for resizing 3d objects in virtual environments is the use of 3d widgets. however, such techniques often exhibit usability problems due to difficulties in selecting and manipulating the widgets. we have developed two novel interaction techniques for resizing objects in immersive ves. our two techniques, the pointer orientation-based resize technique (port) and the gaze-hand resize technique, take advantage of the user's proprioceptive sense and their spatial knowledge of the environment. we designed these techniques as an alternative to 3d widgets and performed a usability study to compare the effectiveness of all three techniques. our results show that participants were able to perform tasks significantly faster with the two new techniques than with the existing 3d widgets technique.
scaffolding in the small: designing educational supports for concept mapping on handheld computers. handheld computers offer the flexibility and mobility to be "ready at hand" tools that can facilitate learning anytime, anywhere. applying the principles of learner centered design [2], we have developed pocket picomap to support students engaged in complex concept mapping activities using handheld computers. pocket picomap uses scaffolds to address specific student needs; for instance, a color scaffold was provided to address students' difficulty organizing and understanding information displayed on small screens. pocket picomap was piloted for six weeks with 33 eighth grade students in mid-michigan classrooms, and our preliminary results suggest that scaffolds are both useful and viable for handheld educational software.
sharing everyday places i go while preserving privacy. several new location-based information applications reveal sets of places that an individual frequently visits. this practice gives rise to related privacy questions and new interface needs. for example, while electronic system users want to be in control of private data and know how those who have it will employ it [10], there are no design guidelines for garnering informed consent for using place-based information. in addition, the set of places a person frequents may reveal information such as: 1) when they are likely to go to a place, or 2) within close proximity, where they live. if a user considers this information private, they may still inadvertently disclose it: humans have difficulty comprehending aggregate effects of their actions [1]. a system could therefore deliver benefit by identifying notable risks and informing the user. this research plan will address these key issues and will ultimately inform privacy interface design.
measuring gaze point on handheld mobile devices. this work describes a prototype system, which enables the measurement of gaze point on the screen surface of a handheld mobile device, without constraining the user's natural movements. the method is software based, and integrates a commercial eye tracking device with a magnetic positional tracking device. the evaluation of the system shows that it is capable of producing valid data with adequate accuracy.
the human factors and ergonomics society perspective. we first describe the human factors and ergonomics society (hfes), then our challenges with respect to meeting the needs of multidisciplinary professionals. we discuss how hfes has tried, as a professional organization, to meet the needs of its diverse members.
home technologies to keep elders connected. this one-day workshop examines the current state of research in computing to support elders in maintaining health and well-being. a particular area of interest is in designing technologies to facilitate connectedness - staying connected with friends and family, staying connected with past, present, and future, staying connected with elders' identifying pastimes, and staying connected with the status of their health. we then identify key areas for future research, and discuss ways to foster more effective research in these areas.
predicting task execution time on handheld devices using the keystroke-level model. the keystroke-level model (klm) has been shown to predict skilled use of desktop systems, but has not been validated on a handheld device that uses a stylus instead of a keyboard. this paper investigates the accuracy of klm predictions for user interface tasks running on a palm os based handheld device. the models were produced using a recently developed tool for klm construction, cogtool, and were compared to data obtained from a user study of 10 participants. our results have shown that the klm can accurately predict task execution time on handheld user interfaces with less than 8% prediction error.
informal communication in collaboratories. recent years have seen an increasing use of collaboratories in distributed scientific work. this study examines the role of collaboratories in informal scientific communication. hypotheses relating to potential opportunities for informal communication afforded by collaboratories are tested with data from in-depth interviews.
spoken dialogue interfaces. this introductory tutorial overviews recent advancement and current efforts in the integration of speech processing with other components of spoken-dialogue systems. it examines important results in designing, constructing, and evaluating complete conversational systems that integrate speech recognition and synthesis with other enabling technologies. among the disciplines contributing material for the course are, therefore, speech recognition and synthesis, but also natural language processing, user-interface design, machine translation, planning and plan recognition, gesture analysis, computational discourse, and usability evaluation. the full-day course is comprised of four sessions including an introduction to the state of the art, review of existing spoken interface systems, the integration of speech processing with other interaction modalities, and a closing session on evaluation methods, tools for developing spoken dialogue systems, and other issues affecting the spoken interface community.
telebuddies: social stitching with interactive television. in this paper we report on our work to enable "laid-back" social interactions using television as a primary interaction medium. by integrating semantic web techniques with interactive television we were able to create smart applications that can run as extensions of television shows and stimulate groups of users to communicate. groups are based on the shared characteristics that can be found for subsets of spectators. communication between spectators is brought about at two levels: direct communication like instant messaging and indirect communication like cooperating in a team to win a quiz. our system does not necessarily require a new television format, but is able to reuse existing television shows and to "socialize" them so they can be re-broadcasted with support for group interaction.
hci and the face. the workshop aims at a general assessment of facial information processing in hci. we will discuss why certain areas of face-based hci, such as facial expression recognition and robotic facial display, have lagged others, such as eye gaze tracking, facial identity recognition, and conversational characters. our goal is to collectively identify research strategies to bring the more slowly developing areas up to speed.
mouthtype: text entry by hand and mouth. in this paper we describe a novel text entry method which uses coordinated motor action of hand and mouth. a vision based algorithm is used to gauge shape parameters of the cavity of the open mouth. these are mapped to a discrete set of input states which are combined with keypad input in a factorial manner to allow unambiguous input of a large number of symbols. the method is implemented and tested for an alphabetic writing system (the roman alphabet) and a syllabic writing system (japanese hiragana). we report the results of preliminary experiments to measure text entry speed and error rate.
preliminary evaluation of a synchronous co-located educational simulation framework. we designed the mushi (multi-user simulation with handheld integration) framework to address two educational needs: (1) to help students learn about complex, multi-scalar systems, and (2) to help students collaborate with one another in small groups. the mushi system provides each student with a handheld computer that is wirelessly synchronized with a simulation running on a tablet pc computer. a group of students can interact with small-scale elements of the simulation via their personal handhelds, and can observe large-scale elements on the shared computer. because this is a novel combination of devices, we conducted use trials with middle school students to explore issues surrounding multi-device representations, small-group collaboration, and equitable computing.
believability in multi-agent computer games: revisiting the turing test. although the turing test has fallen out of favor as a scientific test for machine intelligence, it maintains its usefulness in research with less grand intentions. in some situations 'true' intelligence may be less important than simply portraying a believable human. one such environment, multi-player computer games will be discussed and data on the believability of three different algorithms presented.
the gateway: a navigation technique for migrating to small screens. displaying and navigating information on a large screen can be a challenge and has resulted in a variety of techniques such as text summarization and fisheye. an additional challenge is how to organize information on small screens in a format that can be understood in its context and facilitates navigation within the inherent constraints of these devices. we introduce a navigation model, the gateway, to decrease transitional volatility introduced by migration of web pages to the smaller screen.
an evaluation of landmarks for re-finding information on the web. re-finding information on the web is a common yet often time consuming and challenging task. even with the use of traditional bookmarks, which allow users to return to a previously visited page, it can be hard to re-find facts within that page. furthermore, it is not uncommon for users to have long and unmanageable lists of bookmarks, making it difficult to identify the purpose of individual bookmarks. in this paper, we present an extension to traditional bookmarks called landmarks, a user-directed technique that aids users in returning to specific content within a previously visited web page. we investigate the efficiency of landmarks for re-finding information on web pages and present the findings of a study in which participants were first primed on two web pages and returned at a later date to re-find the information using both traditional bookmarks and landmarks.
the tactile touchpad. a prototype touchpad with embedded tactile feedback is described. tactile feedback allows the touchpad to mimic the operation of a mouse for basic transactions such as clicking, double-clicking, and dragging. a button click is achieved by increasing the finger pressure applied to the touchpad, instead of using a lift-and-tap strategy or by pressing separate buttons. the result is more natural and less error prone. pressure thresholds for the button-down and button-up actions are under software control and include hysteresis to minimise inadvertent selections.
phrase sets for evaluating text entry techniques. in evaluations of text entry methods, participants enter phrases of text using a technique of interest while performance data are collected. this paper describes and publishes (via the internet) a collection of 500 phrases for such evaluations. utility programs are also provided to compute statistical properties of the phrase set, or any other phrase set. the merits of using a pre-defined phrase set are described as are methodological considerations, such as attaining results that are generalizable and the possible addition of punctuation and other characters.
card, english, and burr (1978): 25 years later. we revisit the fitts? law model published 25 years ago by card, english, and burr. their research was important because it was the first comparative evaluation of the mouse, and also the first use of fitts? law in hci. for the mouse, they reported mt = 1.03 + 0.096 id, with throughput reported as the slope reciprocal: tp = 1 / 0.96 = 10.3 bps. we re-analyse their data in view of iso9241-9, the new standard for evaluating pointing devices. the reanalysis yields a throughput of 2.65 bps, or 4.32 bps including a nominal adjustment for the time for the hand to adjust its grip on the mouse. these values are closer to recently published iso-conforming values for the mouse.
a two-ball mouse affords three degrees of freedom. we describe a prototype two-ball mouse containing the electronics and mechanics of two mice in a single chassis. unlike a conventional mouse, which senses x-axis and y-axis displacement only, our mouse also senses z-axis angular motion. this is accomplished through simple calculations on the two sets of x-y displacement data. our mouse looks and feels like a standard mouse, however certain primitive operations are performed with much greater ease. the rotate tool -- common in most drawing programs -- becomes redundant as objects are easily moved with three degrees of freedom. mechanisms to engage the added degree of freedom and different interaction techniques are discussed.
the ncr human interface technology center. the ncr human interface technology center (hitc) exists to meet its customers' business needs through the application of new human-interface technologies. the hitc designs and develops these user-interface solutions through a user-centered design (ucd) process, in which user needs and expectations guide all design and development decisions. the hitc consists of about 90 engineers and scientists with expertise in such areas as cognitive engineering, graphic design, image understanding, artificial intelligence, intelligent tutoring, database mining, and new i/o technologies. established in 1988, the hitc is funded by work performed for its customers.
a focus on conferences. conferences are still valuable for established attendees and potential new audiences, and the overall audience for events can be increased, helping alleviate competition between professional organisations.in addition professional organisations need to avoid conferences being run-of-the-mill, and taking their audience for granted. they need to widen their primary and secondary audiences by helping potential attendees and presenters find out about events, evaluate those they might attend, and benefit in other ways from participating in; professionalising presentation and documentation; facilitating more controversial discussion; improving media relations (including with informal commentators).some of the solutions involved re-designing and re-programming events, greater inter-organisational cooperation, technical developments, and greater intelligence when thinking about audiences and stakeholders.
managing international user research. the desire to extend product development success internationally and understand users in the countries in which a product will be marketed has extended user methods overseas. while the practice of international research has become common, approaches have been varied depending on the needs of the project as well as corporate constraints. many corporate researchers spend a great deal of their time traveling the globe to meet and study consumers, while others look to partner with other researchers or outsource the work entirely. each of these approaches has its own advantages and disadvantages. this panel will explore these diverse approaches, how and why choices are made, the issues and challenges faced, and lessons learned based on past experiences.
wideband displays: mitigating multiple monitor seams. wideband displays fill our field of view, creating new opportunities to develop effective visual interfaces. although multiple monitors are becoming an affordable way to create wideband displays, the resulting seams create gaps in words and divide diagonal lines into nonaligned segments. we present several novel user interface techniques for creating seam-aware applications, showing that vendors need not wait for affordable seamless displays to exploit the potential of wideband displays.
factors influencing the experience of website usage. the present study examines the role of subjectively preceived factors of the experience of website usage in forming an intention to use a website. an integrative research model is presented and tested empirically. it includes the following four aspects of experience: perceived usefulness, ease of use, hedonic quality and visual attractiveness. the two main research questions are: (1) are these aspects four subjectively independently preceived aspects of website interaction? and (2) is the intention to use formed by combining and weighting these four experience aspects and if so, which weights are assigned to the respective aspects.the results suggest that all four aspects of experience can be independently perceived by the user and contribute all with different weights to the intention to use the website.
measuring multiple components of emotions in interactive contexts. the study of users' emotional behavior in hci has been receiving increasing attention for the last few years. this paper focuses on emotions as an important part of a user's overall experience when interacting with a system. based on the multi-component approach to emotions proposed by scherer [15], different aspects of emotions in an interactive context were investigated: subjective feelings, physiological activation, motor expression, cognitive appraisals, and behavioral tendencies. to induce different emotional states, two versions of an interactive system were employed which differed with respect to quality of use. the results suggest that systems of high usability lead to more positive emotions than systems with usability flaws. differences were detected for a number of emotional components by using a variety of methods: rating scales for subjective feelings, emg for facial muscles, heart rate, eda, performance data and questionnaires on cognitive appraisals. we suggest that this combination provides a comprehensive basis for analyzing emotions in hci.
what's in your wallet?: implications for global e-wallet design. as part of a comparative ethnographic study of everyday life of young professionals in london, los angeles, and tokyo, we conducted a detailed survey of wallets and their contents, through photographs, interviews, diary studies, and observation. despite prominent differences in culture and lifestyle, there were remarkable similarities across all three sites in terms of what wallets contained and how they were used. individuals arrived at similar (if imperfect) solutions to common problems of temptation management and access control, identity management and partitioning, and collecting tokens of affiliation and history. our findings suggest that future electronic wallets (e-wallets), whether physical devices or distributed functionalities, will be able to capitalize on these existing patterns, solve some of the existing problems, and encounter new challenges. furthermore, they frame the potential value of e-wallets in a broader context than traditional concerns over privacy, security, and efficiency.
auditory and visual feedback during eye typing. we describe a study on how auditory and visual feedback affects eye typing. results show that the feedback method influences both text entry speed and error rate. in addition, a proper feedback mode facilitates eye typing by reducing the user's need to switch her gaze between the on-screen keyboard and the typed text field.
technology for design education: a case study. we present results of the first longitudinal study of physical and digital technology hybrids for design education. through deployment in an introductory hci class, we have instrumented and analyzed traditional design practices with newer technological components. in particular, we show that hybrid idea logs that maintain the flexibility of paper notebooks can successfully implement the fluidity needed between teammates in design projects, and between the digital and physical world. our preliminary analysis of questionnaires, performance data, and student design notebooks support our hypothesis that this hybrid of technologies may effectively address the needs of this domain, and suggest that basic digital affordances such as export and sharing of design content can improve the educational experience.
an ethnographic study of an online, mutual-aid health community: group dynamics, roles, and relationships. the research project will examine a fairly well studied, long established, and thriving online health bulletin board through a multi level, in-depth analysis. ethnographic research methods will be used in combination with social network analysis and an examination of issues related to usability. the purpose of the research is to document the role the online community plays in the lives of its members; define the patterns of interaction within the group; compare group dynamics in the online community to those in face to face mutual aid groups, and examine the impact of usability issues on group process.
hci and homecare: connecting families and clinicians. the proposed workshop aims to form a community of individuals interested in using computing technology to promote healthcare and support wellness in the context of homecare. we strive to connect and engage researchers from several distinct fields of scientific inquiry and practice: people with clinical experience, developers of enabling technologies and hci researchers interested in home healthcare and issues such as aging in place. the focus of this one-day workshop is on establishing common ground in vocabulary, research methods and research framework; understanding the shared needs of people with health challenges, their families and clinicians, and developing a joint framework for future research.
careview: analyzing nursing narratives for temporal trends. in a study of home-healthcare practitioners, we found that temporal trends contained in patients' clinical records form one of the most critical pieces of information when selecting and administering appropriate treatment. however, these records are comprised of quantitative and qualitative data, and recorded as a narrative. this format makes the extraction of historical trends difficult and time-consuming. to address this limitation, we introduce careview, a system that utilizes a set of visualization techniques to increase the visibility of temporal trends in clinical narratives. specifically, our system focuses on integrated temporal visualizations of numeric and qualitative records; a visualization to facilitate rapid comparison of a patient's condition against previously established care goals; and the ability to immediately visualize data as it is entered. two experiments comparing the market-leading tabular interface with careview revealed a significant reduction in the time required to identify trends in patients' conditions. however, interviews with nurses highlighted the importance of preserving the integrity of the holistic narrative and suggested extending the design space.
full-time wearable headphone-type gaze detector. a headphone-type gaze detector for a full-time wearable interface is proposed. it uses a kalman filter to analyze multiple channels of eog signals measured at the locations of headphone cushions to estimate gaze direction. evaluations show that the average estimation error is 4.4® (horizontal) and 8.3® (vertical), and that the drift is suppressed to the same level as in ordinary eog. the method is especially robust against signal anomalies. selecting a real object from among many surrounding ones is one possible application of this headphone gaze detector.
"unvoiced speech recognition using emg - mime speech recognition". we propose unvoiced speech recognition, "mime speech recognition". it recognizes speech by observing the muscles associated with speech. it is not based on voice signals but electromyography (emg). it will realize unvoiced communication, which is a new communication style. because voice signals are not used, it can be applied in noisy environments; it also supports people without vocal-cords and aphasics. in preliminary experiments, we try to recognize the 5 japanese vowels. emg signals from the 3 muscles that contribute greatly to the utterance of japanese vowels are input to a neural network. the recognition accuracy is over 90% for the three subjects tested.
in-car cell phone use: mitigating risk by signaling remote callers. research has linked in-car cell phone use with automobile accidents. we explore a signaling method that could mitigate that risk. we show in a first experiment how remote cell phone callers were induced to speak less during critical driving periods, and, in a second experiment, how driving performance in a simulator improved when callers reduced conversation levels during critical driving periods.
using intimacy, chronology and zooming to visualize rhythms in email experience. experiences of intimacy and connectedness through social networks are vital to human sense of well-being. we live in an electronic habitat. electronic mail functions as a medium of interpersonal exchange. as it accumulates, email data becomes more than a collection of reminders. it is a diary we didn't know we were keeping, and a potential source of valuable insight into the structure and dynamics of one's social network. current interfaces do little to help users see patterns of social interaction within email data.we introduce a multiscale email interface that utilizes computed intimacy measures and chronology as parameters for information visualization. rhythms of intimacy in email experience are made visible as patterns of color and shapes in a zoomable chronological grid. qualitative user experience data indicates that such an email visualization can provide striking insights into the experience of social connectedness over time. these insights potentially enable users to better manage how they invest time and energy into personal and work relationships, and thus to improve overall sense of well-being.
objectively evaluating entertainment technology. emerging technologies offer new ways of using entertainment technology to foster interactions between players and connect people. evaluating entertainment technology is challenging because success isn't defined in terms of productivity and performance, but in terms of enjoyment and interaction. current subjective methods of evaluating entertainment technology aren't robust. this research uses previous literature and empirical results to create a methodology for objective evaluation of entertainment technology. by gathering physiological data in the context of game play, we intend to correlate physiological responses with subjective reports and with game events. this framework would be a powerful tool used by designers, developers, and researchers to inform their design and evaluate their decisions.
false prophets: exploring hybrid board/video games. in order to develop technology that promotes social interaction rather than isolation, we are exploring the space between board games and video games. we created a hybrid game that leverages the advantages of both physical and digital media. a custom sensor interface promotes physical interaction around the shared public display while the un-oriented tabletop display encourages players to focus on each other rather than on the interface to the game. the ensuing social interactions define the course that the game takes, while the computer enhances the gaming experience by completing the menial tasks and providing dynamic, exciting environments. our hybrid board/video game has the potential to enhance natural and enjoyable recreational interaction between friends.
sticky widgets: pseudo-haptic widget enhancements for multi-monitor displays. people use multiple monitors to increase their display surface and to facilitate multitasking. however, if windows are maximized to fill one screen, users may have difficulties accessing widgets and tools on the borders of the displays, accidentally crossing over to the other display. to assist users of multi monitor displays, we developed a pseudo-haptic approach to enhance boundary widgets. we compared our sticky widget to a standard widget for two multi monitor display configurations: two identical side-by-side monitors, and two separated monitors of different sizes. our enhancement improved performance by significantly reducing errors for accessing a boundary widget, reducing the number of accidental crossovers to the wrong display and consequently decreasing selection time.
practical service learning issues in hci. we explore the practical difficulties of adding service learning to a regularly taught undergraduate hci course. we explore ways to minimize instructor workload, particularly with regard to recruiting partner organizations. none of these approaches we describe was entirely satisfactory, however overall, student recruitment of organizations seemed to proceed most smoothly and have more positive outcomes for students, and required the least instructor workload. we also address issues pertinent to managing partner expectations in the absence of fully working interfaces.
metaphor design in user interfaces: how to manage expectation, surprise, comprehension, and delight effectively. user interface design requires designing metaphors, the essential terms, concepts, and images representing data, functions, tasks, roles, organizations, and people. advanced user interfaces require consideration of new metaphors and repurposing of older ones. awareness of semiotics principles, in particular the use of metaphors, can assist researchers and developers in achieving more efficient, effective ways to communicate to more diverse user communities.
effects of reproduction equipment on interaction with a spatial audio interface. spatial audio displays have been criticized because the use of headphones may isolate users from their real world audio environment. in this paper we study the effects of three types of audio reproduction equipment (standard headphones, bone-conductance headphones and monaural presentation using a single earphone) on time and accuracy during interaction with a deictic spatial audio display. participants selected a target sound emitting from one of four different locations in the presence of distracters whilst wearing the different types of headphones. target locations were marked with audio feedback. no significant differences were found for time and accuracy ratings between bone conductance and standard headphones. monaural reproduction significantly slowed interaction. the results show that alternative reproduction equipment can be used to overcome user isolation from the natural audio environment.
are there benefits in seeing double?: a study of collaborative information visualization. we conducted an empirical study to better understand colla-borative information visualization. we found that a system that offered fewer options for visualizations yielded more correct responses faster. groups were more accurate but slower in solving problems than individuals. we identified different stages in visual discovery and found that collaboration benefits are from validating results and not from planning and system use. tools to help translate and confirm the visualization would be of great benefit.
supporting articulation with the reconciler. a problem in distributed collaboration is the difficulty in resolving different perspectives. we conducted an experiment to test the reconciler, a system designed to aid communicating partners in developing and using negotiated meanings of terms in text-based online communication. we found that with the system, groups used fewer clarifications and explanations for technical terms, which suggests that the system aided the memory of negotiated meanings. the results suggest that technology use can benefit articulation.
keeping in touch with the family: home and away with the astra awareness system. this paper describes research in supporting close family members living apart to keep in touch with each other. we introduce an awareness system for supporting lightweight social communication between mobile individuals and people at home. communication is based on pictures, short messages and reachability information. a field test has provided empirical evidence that affective benefits, to this point only hypothesized by researchers in awareness systems, are indeed experienced by users of our system.
safe & sound: a wireless leash. safe & sound uses location-aware mobile phones to create a "virtual leash"; a secure zone beyond which a child may not travel. if the child leaves this zone, both child and parent receive audible alerts, and the parent can communicate with the child by voice over the phone. the peer-to-peer transmission of location, and the accepted role of responsibility by care-givers, reduce the privacy concerns which often arise with location-aware systems.
possibilities for the digital baton as a general-purpose gestural interface. this paper describes issues and results from the design and use of the digital baton, a new interface for real-time gestural control. its construction was originally motivated by the need for a new instrument on which to perform computer music, and it was designed to replicate as closely as possible the feel of a traditional conducting baton. however, it has unexpectedly become a model for the design of new interfaces and digital objects, and is currently being used to record data for analysis in gesture-recognition research. some preliminary results and future research areas are discussed at the end.
small screen access to digital libraries. this paper looks at the possibilities of taking existing digital library technology and using it for educating those who do not normally have access to the internet. we have built a system which allows wap devices to access an html based digital libary. whilst building such a system is technically possible, our work has shown that there are a wide range of usability issues which need to be tackled. we investigate these problems, suggest improvements and outline where future research needs to take place.
using digital technology to access and store african art. in this paper, we describe the challenges in creating, and providing access to, a database of african culutural artifacts. the submission is targeted at the setion 2 int he consortium - how hci research is being used to support the african renaissance.
automating the detection of breaks in continuous user experience with computer games. this paper describes an approach towards automating the identification of design problems with three-dimensional mediated or gaming environments through the capture and query of user-player behavior represented as a data schema that we have termed "immersidata". analysis of data from a study of an educational computer game that we are developing shows that this approach is an effective way to pinpoint potential usability or design problems occurring in unfolding situational and episodic events that can interrupt or break user experience. as well as informing redesign, a key advantage of this cost-effective approach is that it considerably reduces the time evaluators spend analyzing hours of videoed study material.
from personal to shared annotations. preliminary results obtained by comparing personal annotations on paper with shared annotations made on-line show that only a small fraction of personal annotations are used in initiating and responding to related on-line discussions. the personal annotations that are shared tended to correspond to explicit marginalia; much effort is still put into rendering both the content and anchors of thse annotations intelligible to others.
giving the caller the finger: collaborative responsibility for cellphone interruptions. we present a system in which a cell phone decides whether to ring by accepting votes from the others in a conversation with the called party. when a call comes in, the phone first determines who is in the conversation by using a decentralized network of autonomous body-worn sensor nodes. it then vibrates all participants' wireless finger rings. although the alerted people do not know if it is their own cellphones that are about to interrupt, each of them has the possibility to veto the call anonymously by touching his/her finger ring. if no one vetoes, the phone rings. a user study showed significantly more vetoes during a collaborative group-focused setting than during a less group oriented setting. our system is a component of a larger research project in context-aware computer-mediated call control.
engaging with a situated display via picture messaging. we outline initial investigations into how choices of spatial configuration, input devices and display technologies influence action and interaction in hybrid electronic and physical spaces. joe blogg is a socially situated public display for receiving mms and sms messages and we describe our first installation of this system, giving an account of the rationale of the design concept, the installation and observations on the outcome.
development of an olympic audience judging system. in this paper we describe the development of a system to facilitate audience participation in judging olympic events for the chi 2004, student design contest. this development process utilized domain analysis and human factors principles in combination with user-centered design techniques and usability testing.application of these techniques resulted in the creation of the olympic audience judging system (oajs), a solid-state device that uses a hard-control system of buttons and dials in combination with icons and color grouping to convey functionality information to the user. in addition, the system guides the user through the judging process by means of luminance changes designed to draw attention to necessary parts of the interface.the resulting design focuses on simplicity of function. no previous knowledge of the olympics or of the sports events is necessary to use the system. the oajs allows for users from various backgrounds to judge olympic performances.
prototyping supermarket designs using virtual reality. an experiment is described to compare the protyping of store designs using three different media. the first medium is the traditional use of architectural drawings, the second medium is a representation of store designs made using a virtual reality software package, the third is the evaluation of real existing stores. the preliminary results indicate that prototyping with virtual reality improves the spatial/logistics, but not yet the commercial characteristics of the store designs.
neurophysiologically driven image triage: a pilot study. effective analysis of complex imagery is a vital aspect of important domains such as intelligence image analysis. as technological developments lower the cost of gathering and storing imagery, the cost of searching through large image sets for important information has been growing substantially. this paper demonstrates the feasibility of using neurophysiological signals associated with early perceptual processing to identify critical information within large image sets efficiently. brain signals called evoked response potentials, detected in conjunction with rapid serial presentation of images, show promise as a human computer interaction modality for screening high volumes of imagery accurately and efficiently.
using the environment as an interactive interface to motivate positive behavior change in a subway station. this paper examines the use of incremental persuasion techniques to motivate behavior change using the environment. it also describes three design schemes to motivate positive behavior change through the modification of architectural elements and integration of interactive interfaces into the environment of a subway station.
z-agon: mobile multi-display browser cube. z-agon is a multimedia computer with six cubic multi-displays. this device operated by physical movements of the cube to change channels of contents. this device is used as a network-based multimedia player. users browse many kinds of contents such as blogs, web news, movies, music videos and so on. this concept of z-agon has been envisioned by design studies.now product design requires knowledge from many fields such as hardware, software, infrastructures, social networks and revenue models. sometimes technologies have not entered the stage to satisfy user needs. however, envisioning the concept based on design adequacy is an important attitude to break an innovation into a product. in this paper, an integrated design of z-agon is introduced.
design of a role-playing game to study the trajectories of health care workers in an operating room. drawing on an ethnographic study of hospital work in an operating room, we present the design and implementation of a web-based role-playing application of a master schedule. we show how we simulate the coordination mechanisms and trajectories of hospital personnel as they move patients in and out of or. experiments are proposed to show how active and passive notification systems (interruptions) are expected to affect trajectory management and performance over time.
managing the design of the user interface. the purpose of this tutorial is to provide an overview of practical methods and techniques for managing the process of designing good user interfaces. the tutorial is organized around a typical, modern project life cycle, and presents usability methods which can be applied at different points in the development process. methods and techniques presented include not only information gathering, design and evaluation techniques, but also organizational and managerial strategies.
you're in control: a urinary user interface. the you're in control system uses computation to enhance the act of urination. sensors in the back of a urinal detect the position of impact of a stream of urine, enabling the user to play interactive games on a screen mounted above the urinal.
learner articulation in an immersive visualization environment. learner articulation, described variously in the literature on cognition and instruction as self-explanation or self-directed generative summarization, contributes to new learning through the process of combining ideas in the course of expressing them. in this observational study, we examined movement, gesture and verbal explanation as 14 undergraduate engineering students explored in an immersive visualization display to understand concepts in basic fluid dynamics. data from user videos, interviews, and a 3-d graphical tracking tool were analyzed. approach, observational, and perspectival 'moves' were in evidence to support articulation. students' dietic, iconic and metaphoric gestures combined with their verbalizations to achieve generative articulations regarding the content. accuracy of articulations and system features remains an open question.
measuring presence in virtual environments. this demonstration presents findings from two studies on presence that use a new technology for developing photo-realistic virtual environments. our studies have used a combination of qualitative and quantitative measures, and in doing so have pointed to the importance of exploring place as part of presence. the demonstration explores issues of presence in such environments and the range of data capture methods we used and methodological issues found..
digital backchannels in shared physical spaces: experiences at an academic conference. there are a variety of digital tools for enabling people who are physically separated by time and space to communicate and collaborate. widespread use of some of these tools, such as instant messaging and group chat, coupled with the increasingly availability of wireless internet access, have created new opportunities for using these collaboration tools by people sharing physical spaces in real time. such 'digital backchannels' affect interactions and experiences in a variety of ways, depending on the spaces, the participants, and the relationships among them. we focus on the space of an academic conference, a physical space designed for voluntary participation by people with shared interests, seeking to share knowledge and connect with others. we present and analyze system logs and interview data from a recent conference, highlight some of the advantages and disadvantages experienced both by those who used the tools and by those who did not, and discuss implications and considerations for future use and research.
'user experience' design a new form of design practice takes shape. this paper outlines my professional background and interests in the 'user-experience' field. i summarise my current relevant responsibilities related to my employment as a specialist in 'user experience' design and my sigchi activities. i also summarise some observations on the emergence of 'user experience' as a focus for the professional practice of interactive system design and observations on some directions for the future.
harnessing mobile ubiquitous video. realityflythrough is a telepresence/tele-reality system that works in the dynamic, uncalibrated environments typically associated with ubiquitous computing. by opportunistically harnessing networked mobile video cameras, it allows a user to remotely and immersively explore a physical space. live 2d video feeds are situated in a 3d representation of the world. rather than try to achieve photorealism at every point in space, we instead focus on providing the user with a sense of how the video streams relate to one another spatially. by providing cues in the form of dynamic transitions, we can approximate photorealistic telepresence while harnessing cameras "in the wild." this paper shows that transitions between situated 2d images are sensible and provide a compelling telepresence experience.
awareness in collaborative systems. the provision of awareness is an important aspect of developing useful and usable collaborative systems. this workshop will bring together researchers from around the world to discuss their approaches and to develop a coherent research strategy. the end result of this workshop will be a comprehensive research program for determining what type of awareness information is appropriate to particular situations, a set of proposed solutions, and a strategy to evaluate these solutions in the laboratory and in real world situations.
it@home: unraveling complexities of networked devices in the home. the home is becoming a complex and hard to manage collection of computers and digital lifestyle devices. the work to setup and maintain a network of digital living devices in the home is similar to the work of it professionals. indeed the growing complexity of interconnected digital devices results in more and more time spent solving problems with those devices and their configurations, an important part of computer use that we call "it@home". this workshop explores the complexity of framing the right problems, methods for studying those problems, and designing to support users' it@home.
a new technique for adjusting distraction moments in multitasking non-field usability tests. evaluating errors that result from user interactions with in-car applications, it has to be considered that the user is permanently involved with driving the car. reproducing this driving workload in non-field usability tests, it showed that the driving simulation demanded each test subject in a different way because of individual precognitions and properties. to ensure an identical driving workload for each test subject, it becomes necessary to individually adapt the degree of difficulty (dod) of the driving task. we present a new technique in which, concerning the driving performance, each test participant is pre-classified in a baseline investigation before the main trial. in this context, a special measurement for objectively validating the driving performance of the subjects is being introduced.
multivis: improving access to visualisations for visually impaired people. this paper illustrates work undertaken on the multivis project to allow visually impaired users both to construct and browse mathematical graphs effectively. we start by discussing the need for such work, before discussing some of the problems of current technology. we then discuss graph builder, a novel tool to allow interactive graph construction, and sound bar which provides quick overview access to bar graphs.
wizards, coaches, advisors, and more: a performance support primer. today's business environment is complicated. downsizing means fewer people doing more. the staff has less time to learn new systems. and while there are more "mission-critical" systems in the workplace, there are fewer training dollars available to ensure proper operation. the result is a "performance gap"---users may not have the skills they need to take full advantage of the systems they must use. in this tutorial we present a definition and objectives of performance support and illustrate how performance support can yield roi. next, we review each component and discuss development methodology and design issues. finally, we address hurdles to successful projects.
designing technology for people with cognitive impairments. cognitive impairments, assistive technologies, design and evaluation methodologies, accessibility, inclusive design, universal usability.
seismospin: a physical instrument for digital data. seismospin is a novel interactive instrument that uses a disc-jockey-mixer analogy to give seismologists a quick and powerful way to explore northern california earthquake data. the custom-built interface and display maps earthquake data to responsive, user-determined windows of time and geographical areas. testers (seismologists) found that seismospin provided a greater control and understanding of the dataset than current tools.
being accurate is not enough: how accuracy metrics have hurt recommender systems. recommender systems have shown great potential to help users find interesting and relevant items from within a large information space. most research up to this point has focused on improving the accuracy of recommender systems. we believe that not only has this narrow focus been misguided, but has even been detrimental to the field. the recommendations that are most accurate according to the standard metrics are sometimes not the recommendations that are most useful to users. in this paper, we propose informal arguments that the recommender community should move beyond the conventional accuracy metrics and their associated experimental methodologies. we propose new user-centric directions for evaluating recommender systems.
making recommendations better: an analytic model for human-recommender interaction. recommender systems do not always generate good recommendations for users. in order to improve recommender quality, we argue that recommenders need a deeper understanding of users and their information seeking tasks. human-recommender interaction (hri) provides a framework and a methodology for understanding users, their tasks, and recommender algorithms using a common language. further, by using an analytic process model, hri becomes not only descriptive, but also constructive. it can help with the design and structure of a recommender system, and it can act as a bridge between user information seeking tasks and recommender algorithms.
subjeqt: controlling an equalizer through subjective terms. equalizing is one of the most important tasks in audio engineering. it also is a task that requires technical and auditory training to achieve the desired results. we propose to simplify the use of an equalizer by providing a visual arrangement of subjective terms such as 'warm', 'present', 'boomy' instead of the standard controls that closely correspond to the underlying technology.
supporting professional readers of online documents. reading online documents for professional purposes such as formulating a piece of advice is the subject of a 4 year phd project. a first study in this project indicated that readers who had to write a piece of advice based on electronic sources had a superficial task conception. interacting with the online environment (note-taking, and the retrieval of information) played an important role during reading. readers frequently copied citations from the source documents. these citations were evaluated only during advice writing. based on these observations, we set up a second study that addresses note-taking in a writing-from-sources task. we compare the benefits of an advanced annotation tool with the benefits of a basic annotation tool. the preliminary results of this study will be available at the time of the conference. in the future we will evaluate the benefits of navigational tools.
robots as dogs?: children's interactions with the robotic dog aibo and a live australian shepherd. this study investigated the interactions of 72 children (ages 7 to 15) with sony's robotic dog aibo in comparison to a live australian shepherd dog. results showed that more children conceptualized the live dog, as compared to aibo, as having physical essences, mental states, sociality, and moral standing. based on behavioral analyses, children also spent more time touching and within arms distance of the live dog, as compared to aibo. that said, a surprising majority of children conceptualized and interacted with aibo in ways that were like a live dog. discussion focuses on two questions. first, is it possible that a new technological genre is emerging in hci that challenges traditional ontological categories (e.g., between animate and inanimate)? second, are pervasive interactions with a wide array of "robotic others" -- increasingly sophisticated personified computational artifacts that mimic biological forms and pull psychologically in mental, social, and moral ways -- a good thing for human beings.
from tools to tasks: discoverability and adobe acrobat 6.0. the adobe acrobat 6.0 user interface represents the outcome of a research and design effort to make the most important functionality in the product discoverable, easier to learn, and easier to use. one of the challenges facing the acrobat 6.0 team was the legacy of the existing acrobat 5.0 product, which had presented users with many tools and little context to explain when or how to use them. the review and comment feature area was a business priority for acrobat 6.0, and a usability study on 5.0 revealed discoverability problems with the commenting tool.acrobat 6.0 introduced task buttons that provide access to tools and instructional text relevant to accomplishing common tasks. the review and comment solution leverages the task button framework and proactively presents ui elements to reviewers when they need them. iterative user feedback sessions were invaluable for identifying and resolving usability issues early in the product cycle.
user recalled occurrences of usability errors: implications on the user experience. usability testing determines what problems thwart goal attainment, but what problems shape the user experience? this study gathered users recalled instances of frustration from using various technologies and categorized those frustrating incidents with the user action framework, an adaptation of norman's seven stages of action for classifying usability problems. we found that many of the recalled frustrating incidents occurred while the user was in the outcome phase and that most of those incidents were intrusive in the user's cognitive flow.
multimedia visual interface design. over the past few years, as graphics and imagery have come to dominate our popular modes of communication, interactive multimedia and www developers and users have become keenly aware of the interplay between these visual elements and the cognitive functioning of the interface. this tutorial explores the various facets of this relationship. as a result, participants of this tutorial will gain a better understanding and a working knowledge of how the components of visual interface design work in concert with the cognitive demands of an interface. they will be able to design or direct the design of functional and visually appropriate interfaces for multimedia, websites, course ware and/or training modules.
age group differences in world wide web navigation. in this study, we examined the effects of age and training on efficiency and preferences in a world wide web search activity. older participants were able to complete most of the tasks, but took more steps to find the information than did younger adults. factors in this inefficiency were patterns of returning to the home page and revisiting pages that had been seen before during a search. interactive training improved efficiency and altered preferences. we discuss implications for training and design.
dance your work away: exploring step user interfaces. while applications are typically optimized for traditional desktop interfaces using a keyboard and mouse, there are a variety of compelling reasons to consider alternative input mechanisms that require more physical exertion, including promoting fitness, preventing repetitive strain injuries, and encouraging fun. we chose to explore physical interfaces based on foot motion and have built two applications with step user interfaces: stepmail and stepphoto. both support working with email and photos using the dance pad made popular by the dance dance revolution (ddr) game. results of a formative evaluation with ten participants suggest that the interactions are intuitive to learn, somewhat enjoyable, and cause participants to increase their level of exertion over sitting at a desk. our evaluation also revealed design considerations for step user interfaces, including balancing effort across the body, avoiding needless exertion, and choosing target applications with care.
chi2006: design research abstract. this paper will outline the design methodology for a random pattern derivation based on phenomenology and choice of movement and its subsequent application to computer assisted weaving.
haptic chameleon: a new concept of shape-changing user interface controls with force feedback. in this paper, we introduce the concept of shape-changing, user interface control devices called "haptic chameleon", which refers to computer-controlled user interface devices that convey information to and from the user by altering their shape and feel. the user decides what a haptic chameleon control will do by changing its shape, and can immediately recognize the capabilities of the newly shaped device through haptic and tactile channels. by combining the benefits of tangible and haptic user interfaces, this new user interface paradigm has the potential to vastly improve the learning and efficiency of interaction in a wide range of applications. it also represents an appealing alternative to current control devices. we report on our experience with early prototypes based on this concept, discuss open issues, and propose possible directions for future work.
an interactive braille-recognition system for the visually impaired based on a portable camera. we develop an interactive braille-recognition system using a portable camera for visually impaired persons who cannot read braille. our system helps them to find and then push a desired button, as is necessary when using an elevator or a ticket vending machine, for example. it is natural to think that the information provided, in braille, with specific buttons is sufficient for successful operation in using an elevator or a ticket vending machine. most visually impaired persons, however, cannot read braille. to push a desired button, the user needs to hear only the word or letter associated with the specific braille character so that s/he can correctly relate the buttons to braille characters. if the user is informed of all the braille characters in front of her/him, s/he will be unable to relate the buttons to braille characters. in our system, the user interactively specifies the location of a particular braille character to be read by using hand gestures. the system recognizes the user's gestures and reads the desired braille aloud. in our preliminary experiment, six blindfolded subjects were all able to interact with our system, and recognized the meaning of the buttons that s/he identified.
identity disclosure and the creation of social capital. in this paper, we describe the identity policy decisions for a community network outside of boston, massachusetts. to promote trust and accountability, a member's online identity is their real-world identity; there is no anonymity. we conclude, based on analysis of the online interaction that this identity policy: bridged and enriched online and face-to-face interactions, promoted accountability in support of local commerce, and fostered a social norm of polite conversation.
mind maps and causal models: using graphical representations of field research data. we recently completed a series of field visits to understand how workers use the internet in their daily work activities. at each site, the team used traditional field research methods such as work observations, artifact walk-throughs, and contextual inquiry. an innovative debrief process was developed to understand, summarize and document each visit. in addition to a structured debrief questionnaire, the team created graphical summary notes using "mind maps." these mind maps efficiently captured a nonlinear, graphical clustering of key ideas. a "causal loop diagram" was also developed to document the team's understanding of the internal and external driving forces for each organization. taken together, the debrief questionnaire, the mind maps, and the causal loop diagrams provided a rich multimedia representation of the field data.
effects of structure and label ambiguity on information navigation. we present experimental results showing that search for target items in a three-tiered categorization structure (approximately 8 links per page) is faster than a comparable two-tiered structure provided that the category labels are clear and unambiguous. for items in ambiguous categories, search is faster in the two-tiered structure.
software agents tutorial. "agents" and "agent technology" have become the new buzzwords in computer software. much of this 'buzz' is pure hype similar to the ai hype of the 80's. the software agents tutorial is intended to provide the attendee an overview of the software and user interface technologies being applied to autonomous software modules known as "agents". this overview should allow the student to separate the "wheat from the chaff" and provide pointers for the student's further research into the technology.
eye gaze interaction with expanding targets. recent evidence on the performance benefits of expanding targets during manual pointing raises a provocative question: can a similar effect be expected for eye gaze interaction? we present two experiments to examine the benefits of target expansion during an eye-controlled selection task. the second experiment also tested the efficiency of a "grab-and-hold algorithm" to counteract inherent eye jitter. results confirm the benefits of target expansion both in pointing speed and accuracy. additionally, the grab-and-hold algorithm affords a dramatic 57% reduction in error rates overall. the reduction is as much as 68% for targets subtending 0.35 degrees of visual angle. however, there is a cost which surfaces as a slight increase in movement time (10%). these findings indicate that target expansion coupled with additional measures to accommodate eye jitter has the potential to make eye gaze a more suitable input modality.
evaluating e-commerce environments: approaches to cross-disciplinary investigation. in our on-going e?commerce research programme, we are employing techniques from hci, cognitive psychology, social psychology, and marketing and adapting them to investigate customer behaviour with e?commerce environments. our aim is to investigate the influencing factors beyond the usability of the website that shape the customer's expectations and subsequent experience with e?commerce. in this paper, we propose an empirically-grounded model of customer's purchase and consumption behaviour (derived as a part of our research) that supports systematic choice of techniques for the customer-centred design and evaluation of e?commerce environments. our aim is not to provide a handbook of techniques but to share experiences of applying complementary techniques for investigating different facets of customer behaviour with e?commerce. this paper is meant to serve as a resource for researchers and practitioners who are involved in research, design and evaluation of e?commerce environments.
supporting children's rhythm learning using vibration devices. in this paper, a rhythm instruction tool for school children using vibration devices is discussed. the proposed system called t-rhythm is for supporting individual children in playing musical instruments or singing, in solo or ensemble situations. t-rhythm provides each child with rhythm patterns of musical pieces through tactile senses, and supports her so that she can recognize her own rhythm without being confused by other children's performances or singing voices. the rhythm of the music given to individual children is determined based on a performance by an accompanist and transmitted to their own vibration devices via a wireless communication. we have evaluated t-rhythm in a music class in a japanese elementary school and gained initial feedback from children and their teacher.
intuitive manipulation techniques for projected displays of mobile devices. mobile devices (cellular phone, pda, etc.) used by many people in their daily lives have so far been personal tools. due to their multi-functionality, however, the devices have begun to be used by multiple people in co-located situations. this paper discusses near future technologies: a mobile device with a projector and intuitive manipulation techniques by using a video camera mounted on the device. it is difficult to realize a mobile device with a small and light projector that still retains the feature of mobility, so we have developed a system to project displays of mobile devices by tracking their three-dimensional positions and orientations. the proposed system called hotaru (a firefly, in english) allows users to annotate, rotate or transfer files between multiple devices by touching their projected displays with fingers.
active eye contact for human-robot communication. eye contact is an effective means of controlling communication for humans, such as starting communication. it seems that we can make eye contact if we look at each other. however, this alone cannot complete eye contact. in addition, we need to be aware of being looked by each other. we propose a method of active eye contact for human-robot communication considering both conditions. the robot changes its facial expressions according to the observation results of the human to make eye contact. then, we present a robot that can recognize hand gestures after making eye contact with the human to show the effectiveness of eye contact as a means of controlling communication.
making an impression: force-controlled pen input for handheld devices. the properties of force-based input on a handheld device were examined. twenty-one participants used force input to set 10 different target levels representing consecutive force ranges (0 to 4n) with visual feedback (digits or bar graphs) or no feedback. both accuracy and speed were greater with analog feedback (bar graph). statistical comparisons of adjacent targets/digits indicated that subjects differentiated roughly seven input levels within the set of ten force ranges actually used. time taken to input the target force increased significantly with the size of the target force, suggesting that smaller force ranges should be considered in future implementations of force input. the results are discussed in terms of the design of appropriate feedback for force input.
technology at home: a digital personal scale. this project is a conceptual study for the design of a digital personal scale that allows for user personalization and weight data tracking. the study is a demonstration of an integrated hardware/software development process, of an approach to ubiquitous computing and of the inclusion of socio-cultural study into the product development process. it is designed for the home market and special emphasis is given to providing a rich user experience.
ar pad: an interface for face-to-face ar collaboration. the ar pad is a handheld display with a spaceball and a camera, which can be used to view and interact with augmented reality models in collaborative setting.
lmnkui: overlaying computer controls on a piano controller keyboard. we introduce the look ma no keyboard user interface, an ergonomic and intuitive method for controlling music sequencing software from a piano controller by adding a momentary foot switch. after describing the current practices and the design of our system, we discuss the results of user testing, comparing the conventional input device with ours.
combining handhelds with a whole-class display to support the learning of scientific control. third grade students used wireless handhelds and a large shared display to discover strategies for control of variables in scientific experiments. the technology suite supported activity requirements including synchronous individual control, face-to-face discourse, and instantaneous display updates. in an empirical study, students demonstrated learning in both original and transfer domains.
roomquake: embedding dynamic phenomena within the physical space of an elementary school classroom. authentic practice in science requires access to phenomena. in this paper, we introduce roomquake, an application designed to foster the growth of a community of learning around scientific practice in seismology. rather than treating seismic activity as remote events, roomquake seeks to enhance salience by situating those phenomena directly in the classroom. using fixed-position pdas as simulated seismographs, students determine the magnitude and distance of a series of "randomly" timed events by reading characteristic waveforms and using calibrated tape measures to sweep out arcs from multiple stations until they literally collide, physically enacting mathematical trilateration. we describe our experience in a six-week unit in a fifth-grade classroom.
storygrid: a tangible interface for student expression. storygrid is a classroom-based design and presentation system for interactive multimedia posters. employing the technology base first used in eden's pitaboard, storygrid allows groups of learners to manipulate projected multimedia objects on a horizontal board using a small collection of shared physical tokens. in this paper, we present the ongoing design history of storygrid in the context of its introduction within an urban high school literature class. interface modifications based on student and teacher feedback led on changes in token semantics and media importing methods. we describe how storygrid features enriched students' interpretations of literature, with particular emphasis in two areas: (1) attention to audience, and (2) reflection of multiple perspectives.
a user interface framework for kinetic typography-enabled messaging applications. kinetic typography has recently emerged as a technology to enhance text with speech-like expressiveness. in this paper we describe a framework for an effective user interface of a kinetic typography-enabled messaging application. it supports the user creating a dynamic text that is easy to read, has a coherent appearance and reflects the user's communicative intentions. our prototype uses automated phrasing and accentuation to enhance readability. the overall design is based on a visual framework, which allows for a wide range of distinct emotions and is still visually coherent at the same time. with this framework the user can concentrate on generating a text that is in accordance with his intentions by specifying a suitable animation for the desired emotion and emphasizing words that are important for him.
politics and usability: test your skills against the experts. in this highly interactive panel we will present and discuss a usability business case for professional self-assessment dealing with the politics of usability. a usability business case is a hypothetical but realistic scenario that serves to illustrate points of great importance to usability professionals. our usability business case will focus on the politics of usability: the fundamental rules that apply when attempting to sell or even evangelize usability in an organization. this panel is particularly important since preliminary tests of our business case with experienced usability professionals shows that the general familiarity with our key points is limited.
tips and tricks for a better international usability test. in this sig experienced usability testers will share tips and tricks for practical international usability testing.
comparative expert reviews. in this workshop we will try to obtain a better understanding of the strengths and weaknesses of the expert review and heuristic inspection methods. we will do this by comparing results of independent expert reviews, heuristic inspections and usability tests of the same state-of-the-art website carried out by participating expert usability professionals.
tips and tricks for better usability test recommendations. in this sig experienced usability professionals will share tips and tricks for useful and usable recommendations resulting from usability tests. the discussion will be based on carefully analyzed, real-world examples.
new tips and tricks for a better usability test. in this sig, experienced usability testers will exchange tips and tricks for practical usability testing.
cuhtec: the centre for usable home technology. cuhtec is a joint venture initiated by the joseph rowntree foundation and the university of york in september 2003. cuhtec promotes a user-centred approach to the development of appropriate information and communication technology for use in the home. within this broad focus consideration will be given to technology to enable people with disabilities and the elderly to live independently. cuhtec draws on research skills in psychology, computer science and electronics. an important part of the centre will be the responsive home, a fully-equipped house that will be used for both the development and the demonstration of new products and systems.
designing an integrated review sheet for an electronic textbook. in this paper, we present findings and design decisions arisen while designing a review sheet within the confines of a pre-existing digital textbook, adaptivebook. through user studies, we found that instructors and students cited a lack of both context and integration as the major problems in current high-tech teaching and studying tools. because research on electronic books indicates that metaphors "reduce users' cognitive load when navigating and acquiring information" [1], our design aims to address the lack of context and integration by creating an intuitive review sheet metaphor while leveraging the power of a digital medium.
360 degrees of usability. global usability testing and gathering ongoing user feedback from initial concept through post launch was critical to the project success. several different methodologies were deployed during the process. during pre launch, surveys were used to gather high-level feature preference assessments; live baseline usability testing determined areas of the flow that were difficult for users to comprehend and complete. data from the surveys and baseline usability tests was incorporated into the redesign of the feature and page flow. iterative prototype testing of the redesign focused on identifying major usability issues and updating the design after each round of testing to solidify and finalize the design direction. community involvement using regular focus groups and a live, interactive preview helped inform the community and soften reaction to the change. during post launch, community feedback was leveraged to gather feedback on feature enhancements while additional rounds of iterative prototype testing tested the flow efficacy. the enhancements were presented to focus groups to ensure community needs were addressed, thus completing the usability feedback loop.
self reflection can substitute eye contact. in video communication systems, gaze is an important topic and is widely being studied. unlike other studies, displaying user's reflections on the video screen we stopped imitating the gazes during face-to-face conversation but tries to solve the problem by providing an environment that enables other expressions to substitute for the roles of gazes during conversation. the relative positioning of their self reflections among other reflections (rpar) serves as gaze and helps smooth communication, which was experimentally verified.
hypermirror: a video-mediated communication system. 'hypermirror', a video-mediated communication that includes reflected images of users is reported here. the users of this system, present in front of respective local cameras, can communicate with each other. they are not required to wear or operate any equipment. the images taken at the respective local sites are used to create a composite reflected image which represents a virtual room where all users seem to be present. this composite image is outputted to the respective local screens. results of our experiment participated by users indicate that the system can provide such high reality to the composite image that many users show a tendency to talk to the screen even when the target person is locally present.
free head motion eye gaze tracking without calibration. this paper introduces a novel technique for remote eye gaze tracking and detection of point of regard that is specially designed for wide use in hci. it addresses and eliminates two of the major problems of commercial remote eye gaze tracking, namely the need for user calibration before each session and of accuracy degradation with head movement. the new technique uses a single calibrated camera, several light sources with known positions and a physical model of the eye to estimate the 3d position of the eye and its gaze direction. simulation results using ray tracing are used to study the accuracy and robustness of the system, and demonstrate its operability.
alternative "vision": a haptic and auditory assistive device. we have used two cameras and a sensable technologies "phantom" force-feedback haptic display to haptically render a three-dimensional surface that represents key aspects of a visual scene. in addition to rendering depth and contour information with the phantom, we capture optic flow and present this to the user using sound cues. we propose that with further development, this system could be used as an assistive device that would allow visually impaired individuals to explore the "visual" world.
catalyzing social interaction with ubiquitous computing: a needs assessment of elders coping with cognitive decline. this paper describes design directions for ubiquitous computing to facilitate social interaction. the study focuses on elders coping with cognitive decline and their caregivers, but it is expected that the concepts will have much broader applicability. social needs and barriers were examined in a qualitative study of 45 households across the u.s. directions for ubiquitous computing concepts are outlined to address these social needs and barriers. two example concepts, an ambient display to facilitate joint activity and a social memory aid, are described in detail. an underlying principal of these design directions and concepts is the use of computing technologies as catalysts rather than substitutes for human relationships. these concepts are part of an integrated system of home health technologies under development in a multiyear "aging in place" study.
multi-touch interaction. many everyday activities rely on our hands' ability to deftly control the physical attributes of objects. most graphical interfaces only use the hand's position as input. for my dissertation, i study how multi-touch input lets us make better use of our dexterity.
gesture navigation: an alternative 'back' for the future. this paper describes the evaluation of a gesture-based mechanism for issuing the back and forward commands in web navigation. results show that subjects were able to navigate significantly faster when using gestures compared to the normal back button. they were also extremely enthusiastic about the technique, with several expressing their wish that "all browsers should support this".
airhockey over a distance. in modern society, people increasingly lack social interaction, although beneficial to work and personal life. airhockey over a distance addresses this issue by recreating the social experience facilitated by physical game play in a distributed environment. we networked two airhockey tables and augmented them with a videoconference. concealed mechanics on each table allow for a physical puck to be shot back and forth between the two locations. supporting the hitting of a fast-moving, tangible puck between the two players creates a compelling social game experience which was confirmed by about 30 players. our preliminary findings suggest that our casual physical game supports social interactions and contributes to an increased connectedness between people who are geographically apart.
transparent hearing. this paper describes what we call transparent hearing: the use of microphone equipped headphones for augmented audio. it provides a framework for experiments like real-time audio alteration, multi-modal sensory integration and collaborative listening experiences. we attach high-quality microphones to headphones and send the signal through a computer to these headphones. we have built headphones that stop the music if somebody wants to talk to you, a pseudophone, and collaborative i hear what you hear headphones that are triggered by eye-contact.
hug over a distance. people in close relationships, who are separated by distance, often have difficulty expressing intimacy adequately. based on the results of an ethnographic study with couples, a prototype was developed to test the feasibility of technology in the domain of intimacy. hug over a distance is an air-inflatable vest that can be remotely triggered to create a sensation resembling a hug. although the couples did not consider the vest to be useful in their daily lives, the prototype served to provoke and stimulate design ideas from the couples during participative design workshops. an additional and unexpected benefit was also found: the prototype enhanced the couples' understanding of the researchers' methods, suggesting that prototypes can serve as tools to make participatory design volunteers aware of their importance in academic research.
bioculars: a virtual ecosystem for wilderness parks. bioculars is a concept system that allows visitors to state and national wilderness parks to create virtual animals and observe them in a continually running simulation based on the park's natural environment. users create fantasy animals with a computer interface that, inverted, transforms into a binocular-like device. when users look through the device, they can see their virtual species "living in" and interacting with the park's real ecosystem. bioculars was designed by a stanford university student team using an iterative design process that emphasized repeated prototyping and user testing.
what is connected by mutual gaze?: user's behavior in video-mediated communication. video-mediated communication systems such as teleconferencing and videophone have become popular. as with face-to-face communication, non-verbal cues such as gaze, facial expression, head orientation and gestures in visual systems play an important role. existing systems, however, do not support mutual gaze because the lay-out of the camera and monitor is restricted. thus, conversations using visual systems differ from those in face-to-face communication. this paper clarifies the problems of the video-mediated system, specifically for comparing the system with communication using eye-contact and with communication using no-eye-contact. this study focuses on the protocol of opening communication, e.g. establishment of a visual-audio link, person identification and confirmation of the acceptance of conversation. we conducted experiments using the two systems. analysis of recorded video sequences revealed that the system using communication with eye-contact induced behavior similar to the system using face-to-face communication.
"readness": a design exploration of personal document management in historical and collaborative context. when faced with many documents, people often use systems that characterize documents as read or unread. most email and document management systems treat this distinction as a binary - either a document has been read, or not. this poster explores designs that expand this binary distinction into a continuum of "readness," based on the user's personal history and collaborative context. the work focuses on late-breaking design concepts.
shared landmarks in complex coordination environments. we explore the concept of social landmarks in complex, shared information and coordination environments. previous research in navigation and shared spaces has tended to emphasize individual navigation, formally inscribed spaces, social filtering, and boundary objects. based on ethnographic research into complex collaborative work in organizations, we extend the concept of navigational "landmarks" to include not only individually-used documents, but also shared landmarks in the form of persons, roles, and events. this emerging concept of social landmarks may be applied in identifying and representing these coordinating points, to support the work of teams and organizations in complex projects.
workshop: creating and refining knowledges, identities, and understandings in on-line communities. this two-day workshop examines the ways that on-line communities create and refine their shared resources, in-cluding both the formal and observable artifacts (docu-ments, chats, threads) and the less tangible conventions, roles, and identities in the community.
nutrastick: portable diet assistant. this paper describes the design of a programmable barcode scanner (the nutrastick) that aims to revolutionize the way people on any kind of diet shop. the nutrastick uses barcode scanning technology alongside an onboard ingredient/nutritional information database to give feedback (red or green light) as to whether a particular food item is suitable or not for a person on a specific diet. usability engineering protocols were used in the design process including feasibility testing and a user orientated interface design process. the use of this methodology allowed for a user friendly, simple, effective, and innovate design.
usability and requirements: what role can usability professionals play in requirements definition? the sig will be a forum for discussing issues related to requirements and usability. usability professionals have been working to move their realm of influence earlier in the development process from the traditional testing after completion. but how early is early enough? for example, with user centred design (ucd), involvement begins with an analysis phase which uses the requirements or product concept as the starting point. why not get involved in defining the requirements and even the concept? we have the skills and the correct orientation on users and their work where we could make significant contributions to this level of product development.
social regulation in virtual spaces. the described dissertation focuses on social regulation of user behavior within virtual social spaces. a multi-year field study of two fantasy-based game muds (multi-user dungeons) was conducted to gain a detailed understanding of the work involved in regulating behavior in these virtual environments. this field study examines the work and techniques employed by game administrators (immortals) to maintain social regulation over their respective game muds. one key feature of social regulation in such virtual spaces is the use and possible use of specialized software routines to regulate specific behaviors. ongoing analysis of the field study data is expected to provide an understanding of how aspects of the virtual world affect the manner in which social regulation is performed.
the multimodal gui: developing auditory cues as tools for performance and usability. designers who use sound in the computer interface must do so judiciously. the inclusion of auditory cues within an interface should be a mechanism for the improvement of task performance and the facilitation of usability. gaver [6] and blattner [1] have demonstrated the utility of auditory cues in communicating information to users. the usage of "spatially-enhanced" speech and nonspeech elements could provide an additional source of data that might help or hurt performance. the usefulness of an auditory cue could be linked to acoustical parameters, spatialization, and task type. the proposed study will assess the improvement of user performance for various types of auditory cues as applied to spatial and verbal computer tasks. these results will be important to multimedia developers who want to create software that facilitates user acceptance or the quality of user performance.
examining mobile phone text legibility while walking. in this study, alternative methods for studying legibility of text while walking with a mobile phone were examined. normal reading and pseudo-text search were used as visual tasks in four walking conditions. visual performance and subjective evaluation of task difficulty were used as measures of text legibility. according to the results, visual performance suffers from increasing walking speed, and the effects are greater on reading velocity for pseudo-text search. subjects also use more homogenous strategies when reading compared to pseudo-text search, and therefore it is concluded that reading is a more useful measure of legibility. subjective measures are found to be more sensitive to small variations in legibility than objective measures, and give additional information about task demands. hence, without both objective and subjective measurements important information about legibility in different conditions and with different tasks will be lost.
towards time design: pacing of hypertext navigation by system response times. two experiments investigated the effects of system response time (srt) on hypertext navigation. dependent variables were residence time, emotional strain and memory performance. a synchronization between human and computer response time was observed.
the amulet user interface development environment (special interest group meeting). the user interface software group at cmu is investigating ways to make the design, prototyping, and implementation of user interfaces substantially easier. unlike other user interface development environments that deal only with widgets like menus, scroll bars and buttons, we concentrate on the insides of application windows, which is the part that takes most of the programmer's time to design and implement. typical applications of the technology include visualizations and visual programming environments, drawing programs, user interfaces for expert systems, graph editors, graphical programming languages, game user interfaces, simulation and process monitoring programs, user interface construction tools, cad/cam programs, etc.
end users creating effective software. is it possible to bring the benefits of rigorous software engineering methodologies to end users? end users create software when they use spreadsheet systems, web authoring tools and graphical languages, when they write educational simulations, spreadsheets, and dynamic e-business web applications. unfortunately, however, errors are pervasive in end-user software, and the resulting impact is sometimes enormous. a growing number of researchers and developers are working on ways to make the software created by end-users more reliable. this special interest group meeting will help start to form a community of researchers who are addressing this topic.
end users creating effective software. is it possible to bring the benefits of rigorous software engineering methodologies to end users? end users create software when they use spreadsheet systems, web authoring tools and graphical languages, when they write educational simulations, spreadsheets, and dynamic e-business web applications. unfortunately, however, errors are pervasive in end-user software, and the resulting impact is sometimes enormous. a growing number of researchers and developers are working on ways to make the software created by end users more reliable. this special interest group meeting will help support the community of researchers who are addressing this topic.
invited research overview: end-user programming. in the past few decades there has been considerable work on empowering end users to be able to write their own programs, and as a result, users are indeed doing so. in fact, we estimate that over 12 million people in american workplaces would say that they "do programming" at work, and almost 50 million people use spreadsheets or databases (and therefore may potentially program), compared to only 3 million professional programmers. the "programming" systems used by these end users include spreadsheet systems, web authoring tools, business process authoring tools such as visual basic, graphical languages for demonstrating the desired behavior of educational simulations, and even professional languages such as java. the motivation for end-user programming is to have the computer be useful for each person's specific individual needs. while the empirical study of programming has been an hci topic since the beginning the field, it is only recently that there has been a focus on the end-user programmer as a separate class from novices who are assumed to be studying to be professional programmers. another recent focus is on making end-user programming more reliable, using "end-user software engineering." this paper gives a brief summary of some current and past research in the area of end-user programming.
the amulet user interface development environment. the amulet research project is developing a new user interface development environment [2] which incorporates a number of design and implementation innovations including new models for objects, constraints, animation, output, input, commands, and undo. amulet has an open architecture, so that user interface researchers can replace and extend components. amulet, which stands for <u>a</u>utomatic <u>m</u>anufacture of <u>u</u>sable and <u>l</u>earnable <u>e</u>ditors and <u>t</u>oolkits, is implemented in c++, and runs on x/11, windows nt, windows 95, and the macintosh.
"sketching" nurturing creativity: commonalities in art, design, engineering and research. the workshop seeks to bring together researchers and practitioners from diverse creative practices such as interaction design, industrial design, architectural design, media art, music, programming, writing, and scholarly work, to gain insight into the creative process. each of these disciplines has established ways to nurture a creative impulse through to a concrete result. this is done in part by fostering a continuing internal dialog between creative instinct and external representations. sketching is an activity common to these practices that is exercised during such creative refinement. by sketching, we mean not only hand-drawing on paper using a pencil, but also rapid, undetailed, brief, light, informal representations that practitioners produce and interact with. by investigating the sketching process in each practice, we expect to find commonalities that will to point out essential elements for designing tools to support the creative process.
multimodal presentation method for a dance training system. this paper presents a multimodal information presentation method for a basic dance training system. the system targets on beginners and enables them to learn basics of dances easily. one of the most effective ways of learning dances is to watch a video showing the performance of dance masters. however, some information cannot be conveyed well through video. one is the translational motion, especially that in the depth direction. we cannot tell exactly how far does the dancers move forward or backward. another is the timing information. although we can tell how to move our arms or legs from video, it is difficult to know when to start moving them. we solve the first issue by introducing an image display on a mobile robot. we can learn the amount of translation just by following the robot. we introduce active devices for the second issue. the active devices are composed of some vibro-motors and are developed to direct action-starting cues with vibration. experimental results show the effectiveness of our multimodal information presentation method.
estimating communication context through location information and schedule information: a study with home office workers. we have developed a communication support system that estimates the situation of a person by using the location information of a phs (personal handy phone system) and the schedule information. the system supports communication among dispersed and mobile individuals by using the estimated situation. in this paper, we describe it and a study with a small group of home office workers.
the traveling café: a communication encouraging system for partitioned offices. in this paper we illustrate the "traveling café" that provides opportunities for informal communication by encouraging people to serve coffee to each other. this system consists of "sensor-equipped coasters," "a coffee pot with a supersonic wave oscillator," and "an lcd monitor and a light to display user situations." for two weeks we conducted pilot experiments to evaluate the system's effects and found that it triggered communication even in partitioned offices.
scaling the card sort method to over 500 items: restructuring the google adwords help center. in this paper we describe the method we used to redesign the information architecture of the google adwords help center. we adapted the card sorting method to accommodate over 500 items, and produced a new help center structure that enables users to find information faster and with fewer errors, as verified in a formal experiment. our process can be used as a model by those faced with organizing or reorganizing a large body of information, where conducting a traditional card sort would not be practical.
integrating hardware and software: augmented reality based prototyping method for digital products. for digital products, the relationship between the hardware and the software is important but their integration is largely achieved in the later phase of the design process. this paper presents new prototyping methods that allow digital product designers to effectively integrate the hardware and the software of the products from the early phase of the design process. the integration is accomplished by accurately overlaying a virtual display onto a quickly made functional hardware prototype using two augmented reality techniques; 1) using a video see through hmd and 2) using video projection. the results of the preliminary evaluation suggest that the early integrated prototypes are effective for design development and user studies.
letting every pupil learn japanese hand alphabets with viual interfaces. this paper discusses the effects of a visual interface for the japanese hand language system. the system practice! yubimoji aiueo (pya) we are developing aims at letting ordinary pupils learn basic character expressions (aiueo) of the japanese hand characters (yubimoji). because very few pupils in japan are currently able to communicate with handicapped people and there are only complex, expensive, and difficult software systems and/or textbooks available to learn the language system, it is critical to deliver easy-to-use software systems on a pc at elementary schools. this paper describes what are the principles of pya, how pya works, and why pya is effective from pedagogical and computer human interaction points of view.
beyond being in the lab: using multi-agent modeling to isolate competing hypotheses. in studies of virtual teams, it is difficult to determine pure effects of geographic isolation and uneven communication technology. we developed a multi-agent computer model in netlogo to complement laboratory-based organizational simulations [3]. in the lab, favoritism among collocated team members (collocators) appeared to increase their performance. however, in the computer simulation, when controlled for communication delay, in-group favoritism had a detrimental effect on the performance of collocators. this suggested that the advantage of collocators shown in the lab was due to synchronous communication, not favoritism. the canceling-out effects of in-group bias and communication delay explained why many studies did not see performance difference between collocated and remote team members. the multi-agent modeling in this case proved its value by both clarifying previous laboratory findings and guiding design of future experiments.
model-based design of hypermedia presentations. users' mental representations and cognitive strategies have a profound influence on how well they comprehend multimodal information that hypermedia systems present. this implies that cognitive models of comprehension ought to drive the design of effective hypermedia information presentation systems (hips). we report on a current research project that applies this principle to the design of hypermedia manuals of complex machines. this paper describes the comprehension model derived from prior empirical and theoretical research, discusses intermediate results, and presents a roadmap of the research project.
interactive ethnography: digital photography at lincoln high school. we demonstrate our cd-rom, "digital photography at lincoln high school: an interactive ethnography," as well as a web-based example of interactive ethnography. the goal of the work is to demonstrate a new medium for presenting the results of ethnographic studies to a wide audience. the richness of the ethnographic experience is easily lost in a text-only format. the cd-rom uses audio, video, text, quicktime vr, scanned images and digital photos to bring alive the experiences of the students and staff in the digital photography class.
tactile virtual buttons for mobile devices. this paper presents a technique to add the tactile cues of real buttons to virtual buttons displayed on mobile devices with touch screens. when the user's finger is on the display, tactile feedback coveys a feeling of button location and activation. we describe two implementations of the technique, using a personal digital assistant (pda) and a pressure sensitive tablet.
improving automotive safety by pairing driver emotion and car voice emotion. this study examines whether characteristics of a car voice can affect driver performance and affect. in a 2 (driver emotion: happy or upset) x 2 (car voice emotion: energetic vs. subdued) experimental study, participants (n=40) had emotion induced through watching one of two sets of 5-minute video clips. participants then spent 20 minutes in a driving simulator where a voice in the car spoke 36 questions (e.g., "how do you think that the car is performing?") and comments ("my favorite part of this drive is the lighthouse.") in either an energetic or subdued voice. participants were invited to interact with the car voice. when user emotion matched car voice emotion (happy/energetic and upset/subdued), drivers had fewer accidents, attended more to the road (actual and perceived), and spoke more to the car. implications for car design and voice user interface design are discussed.
social and natural interfaces: theory and design. this tutorial will cover issues related to the theory and design of social interfaces. the presentation is based on a long-term research project at stanford university called social responses to communication technology (srct). this research shows that all people expect computers to obey a wide range of social and natural rules. the tutorial will cover 24 different concepts taken from the social science literature (e.g., personality, politeness, emotions), discussing both experimental results and the implications of results for the design of interfaces. the presentation will include an evaluation of current interfaces. the tutorial is for designers, usability specialists, and anyone interested in creating or assessing interfaces that conform with social and natural rules. no knowledge of programming is necessary.
ubiquitous computing: by the people, for the people. one of the challenges in building and evaluating ubiquitous computing systems emanates from the fact that they generally have been built to showcase technological innovation without considering how to foretell whether and how people will eventually accept them in their lives. in this study, participants are introduced to the notion of ubiquitous computing via a scenario-centric presentation including basic everyday objects imbued with some computational power to convey information. through a detailed survey, participants provide feedback relating to their impressions, rating the performance of each interface on a number of metrics and making comparisons between the ubiquitous and desktop interfaces. we inspire them to think of new ways to use existing ubiquitous interfaces to support their current and possible information needs, as well as better interfaces that can convey this information.
elearning sig. many chi attendees are involved in elearning as a student, teacher, or developer of online courses or technologies. however, to date there has been insufficient focus on designing and facilitating a good learner experience. this sig builds upon the well-attended elearning sigs from chi 2001 and 2002 by examining in greater depth the issues and needs of the elearning and hci communities and fostering better communication and collaboration between these communities. elearning is a special area for chi 2003, and there will be an invited session on elearning, focusing, like the sig, on bringing the lessons from hci to elearning.
online health communities. online health communities provide a means for patients and their families to learn about an illness, seek and offer support, and connect with others in similar circumstances. they are supported by a variety of technologies (e.g., email lists, forums, chat rooms) and are hosted by patients, advocacy groups, medical organizations, and corporations. they raise difficult design challenges because of the wide variability of members' medical expertise, the severity of problems due to misinformation, and the need for emotional support. the importance of on-line health communities is evidenced by their popularity, as well as the significant impact they have on the lives of their members. this special interest group (sig) will explore current trends in online health communities, as well as discuss the socio-technical design challenges and opportunities that they afford.
elearning and fun. elearning is becoming more prevalent for education and training, yet many online courses are poorly designed. some are little more than electronic versions of paper-based materials; others attempt to replicate a traditional classroom offering; while others follow an instructional design approach used for classroom instruction. as a result, the reputation of online courses is not good and the exception, rather than the rule, is a well-designed course that effectively teaches a topic to its target students.in this special interest group (sig), we will look at one aspect of elearning: making online courses engaging and fun. "fun and pleasure are elusive concepts" [1] and there is no consensus on how to design enjoyable experiences [2]. engagement is accepted as important in online learning but is similarly elusive. we will look at how courses can be designed to increase enjoyment; if fun can increase motivation, engagement, and retention; how multimedia, games, entertainment, and fun are related; and the impact of peers, instructors, mentors, and support staff on fun with respect to the learning experience.
designing usable and visually appealing web sites. this full day tutorial consists of groups that work through the design rationale and building of a web site specification and paper prototype via highly participatory exercise sessions. short lectures will introduce topics, design techniques, and methods, supported by examples, for immediate application to that phase of the web site design.
0 to 50 in 4 years: cuis at boeing. the common user interface services (cuis) group at boeing is a full-featured support organization for boeing user interface developers. the group has achieved key successes and has increased the visibility of the importance of usability engineering to the point where it has been established as a key corporate initiative in 1996.
computer assisted foundations - interactive design problems. two art professors and a software designer have written computer assisted foundations design curriculum using interactive problems written in macromedia director. these problems are designed to produce many possible solutions, some of which are further developed using traditional artist's materials such as collage and paint. we would like to demonstrate four of these problems.
gooey interfaces: an approach for rapidly repurposing digital content. with the acceleration of technological development we are reaching the point where our systems and their user interfaces become to some degree outdated 'legacy systems' as soon as they are released. this raises the question of how can we maintain, extend, override, and adapt these systems while preserving what people depend on in them? in this paper we describe an approach for dynamically restructuring user interfaces into a set of communicating processes that 1) provide methods for changing their appearance, behavior, and state; and 2) report their proposed state changes so that other processes may override their actions in updating themselves to a new state. we do this for both new and wrapped legacy user interface components, thereby allowing us to repurpose user interfaces for our evolving needs. we describe how this approach has been successfully used in rapidly creating and deploying interfaces that repurpose content for new appearances and behaviors.
beyond "from" and "received": exploring the dynamics of email triage. email triage is the process of going through unhandled email and deciding what to do with it. email triage can quickly become a serious problem for users as the amount of unhandled email grows. we investigate the problem of email triage by presenting interview and survey results that articulate user needs. the results suggest the need for email user interfaces to provide additional socially salient information in order to bring important emails to the forefront.
hci for older and disabled people in the queen mother research centre at dundee university, scotland. this paper describes research carried out within the queen mother research centre for information technology to support older and disabled people and how this led to the development of an approach to research into accessibility and usability which is instantiated in the facilities of the new building.
theatre as an intermediary between users and chi designers. we have investigated the possibilities of using theatre, including professional actors, scriptwriters and artistic directors, within requirements gathering, and usability testing, and for communicating the results of such work to the design community, or individual designers. the research on which we will report focuses on older people, but we believe that a consideration of the issues involved in designing for this group highlights many of the challenges found in chi research more generally, and the techniques can apply to usability testing, and to communicating the findings of such research and testing to designers.
preliminary evidence for top-down and bottom-up processes in web search navigation. in current theories of web navigation, link evaluation has been treated primarily as a bottom-up process involving assessing the semantic distance between a search goal and a given link in the information source. in this paper we investigate whether link evaluation could be subject to top-down influence from knowledge of the information source. we measured fixation durations that occurred during link evaluation and found shorter durations in the search for easy goals. this preliminary finding suggests that for goals with category names readily retrievable from knowledge of the information source, search is likely aided by top-down influences.
email archive overviews using subject indexes. archived discussion lists are becoming significant reference sources. this paper describes a new type of overview for such lists, using a back-of-the-book style index containing headwords selected from subject lines and subentries derived from their subject-line-contexts.
do chi papers work for you?: addressing concerns of authors, audiences and reviewers. chi papers serve unique and vital purposes within the hci community. their ability to serve these purposes is of particular concern to authors, audiences (both attendees at conference sessions and readers of proceedings) and reviewers. however, these stakeholders rarely have an opportunity to state their concerns and influence how they are addressed. this sig will offer such an opportunity. it has been organized by members of the chi papers support team, who will lead discussions of major issues. the outcome will be a set of recommended further actions by the support team and future papers co-chairs.
disruption of meetings by laptop use: is there a 10-second solution? we have conducted a study of meetings to gain an understanding of the sources of disruption when laptops are present. we videotaped five workplace meetings in which over 600 information tasks were performed by participants using paper or laptops. we saw evidence that people preferred task durations not to exceed approximately 10 seconds. tasks performed by laptop users were more likely to exceed this limit, and this could contribute to disruptions. we suggest that laptop software may need to assist users in keeping tasks within 10 seconds' duration.
pins push in and pouts pop out: creating a tangible pin-board that ejects physical documents. there is an asymmetry in many tangible interfaces: while phicons can be used to manipulate digital information, the reverse is often not possible - the digital world cannot push back. we describe a tangible pin-board that pushes back by physically ejecting paper documents when they are digitally deleted. this is realized using pouts, addressable pin-like devices that communicate with a pin&play board and that can eject themselves by contracting an internal muscle wire actuator to trigger a mechanical latch. to demonstrate and begin to evaluate the technology we have developed an initial application of pouts involving a game where online players vote to eject physical pictures from a pin-board.
whisper: analysis and design for a community event service. we present an analysis of what we call the community event space, looking at how social events are planned and organized. based on a series of interviews, field studies, and a focus group, we introduce a framework outlining six phases of events: proposition, polling, participation, parting, perpetuation, and persuasion. we also present the design of whisper, a web-based event service that addresses the planning and organizational challenges identified in this framework. this analysis and design serves as a blueprint for existing and future community event services.
phemail: designing a privacy honoring email system. controlling one's personal and private information could help alleviate one of the greatest harms facing the internet today - the loss of attention due to the over abundance of unsolicited email (spam). if one could control the dissemination and usage of one's email address, one could eliminate spam. we introduce a privacy honoring email system that leverages the user's social network to provide access control to the user's email.
informing automatic generation of remote control interfaces with human designs. embedded processors are making it possible for common appliances, such as cable boxes, micorwaves, and fax machines, to provide even more fuctionality. unfortunately, as these appliances become more complex, their interfaces are also becoming harder to use. at the same time, more people are carrying hand-held computerized devices that can communicate. we envision a future in which people will use their handhelds to communicate with and control common appliances in their environment. this work describes the design of a specification language and the construction of an automatic interface generator, using lessons learned from analyzing manually created interfaces.
personal universal controllers: controlling complex appliances with guis and speech. we envision a future where each person will carry with them a personal universal controller (puc), a portable computerized device that allows the user to control any ap-pliance within their environment. the puc has a two-way communication channel with each appliance. it downloads a specification of the appliance's features and then automati-cally generates an interface for controlling that appliance (graphical, speech, or both). in this demonstration we pre-sent a working puc system that automatically generates graphical and speech interfaces, and controls real appli-ances, including a shelf stereo and a sony camcorder.
electronic privacy, trust and self-disclosure in e-recruitment. the present study extends the research on user trust in e-commerce to the area of e-recruitment, focusing specifically on the importance of perceived privacy to evoke user trust and self-disclosure. two websites of a fictitious online recruitment site were compared, which differed only in their level of perceived privacy. it was found that an interface conveying a high level of privacy significantly increased user trust. although users with high trust scores also disclosed more and more sensitive information than users with low trust scores, this could not be attributed solely to the perceived privacy of the online job bank.
community source development: an emerging model with new opportunities. this paper focuses on an emerging model for software development in higher education: community source. community source seeks to blend aspects of both open source and traditional development processes. volunteers join at the institutional level and share resources and ideas to develop applications for common needs. the code remains open, but the collaboration exists in a meritocracy; those who contribute the most have the most influence on the outcome. while many in the hci community have long abandoned the prospect of affecting change in open source development, average computer users, rather than developers, are becoming the main audience. as open source matures and community source emerges, some new opportunities are presenting themselves. they require a dialogue within our profession to yield new processes and vocabularies that work within the open source framework.
user interface design for the www. you are up against a million other web sites: how do you get users to stay at your site? only by providing valuable content and a highly usable interface. coll is getting cold.
humor modeling in the interface. humor is a multi-disciplinary field of research. people have been working on humor in many fields of research, such as psychology, philosophy and linguistics, sociology and literature. especially in the context of computer science humor research aims at modeling humor in a computationally tractable way. having computational models of humor allows interface designers to have the computer generate and interpret humor when interacting with users.in different studies it has been shown that humans respond in the same way to computers as they do to persons with respect to psychosocial phenomena such as personality, politeness, flattery, and in-group favoritism. making use of this paradigm we may investigate a similar role to be played in human-computer interaction for various types of humor use and we can see whether the regulating and social-psychological aspects of humor can play positive roles in human-computer interaction.
the virtuality continuum revisited. we survey the themes and the aims of a workshop devoted to the state-of-the-art virtuality continuum. in this continuum, ranging from fully virtual to real physical environments, allowing for mixed, augmented and desktop virtual reality, several perspectives can be taken. originally, the emphasis was on display technologies. here we take the perspective of the inhabited environment, that is, environments positioned somewhere on this continuum that are inhabited by virtual (embodied) agents, that interact with each other and with their human partners. hence, we look at it from the multi-party interaction perspective. in this workshop we will investigate the current state of the art, its shortcomings and a future research agenda.
building security and trust in online banking. growing threats to online banking security (e.g. phishing, personal identify fraud) and the personal nature of the data make the balance between security, trust and usability vital. however, there is little published research about what influences users' perceptions of online banking security and trust. this study identifies that the type of authentication system used can affect users' subsequent perceived control, situational awareness and trust. the results from a questionnaire and in-depth interviews with 86 participants were triangulated to compare two different authentication processes, namely, a 'security box' (i.e. random system generated passwords at the users' location) and 'fixed passwords' (i.e. user owned and constant). the security box and login procedures were perceived significantly more trustworthy and secure at any location than 'fixed passwords'. four main concepts were identified: "trust" "the authentication system", "location" and "control". the implications of these findings for hci are discussed.
nostalgia: an evocative tangible interface for elderly users. nostalgia is a prototype which users can use for listening to old news and music from the twentieth century. the design of nostalgia is an attempt to design an artefact that in a seamless and simple way can trigger the memory of past events both individually and in the company of others. nostalgia has been developed in collaboration with elderly people from an old people's home. a preliminary evaluation with the target group showed that nostalgia could be an appreciated artefact in their every day lives.
use of keyboard for mouseless data entry in ui design. the web relies on a "point and click" mentality that becomes greatly impaired when no pointing or clicking medium is available. in the airline industry, mouseless operation is a standard form of user interface design: in fact, it is a requirement. unfortunately, technical constraints for software design require that airline employees, commonly known as agents, manipulate long lists of data records by first selecting the records from a larger list, consolidating them into a smaller list, and then choosing from another list an action to perform against them. this paper describes our design solution which relies on a particular configuration of commands mapped to specific keys of the keyboard to provide efficient and memorable operation of the ui that allows for quick selection, consolidation, and applied action.
a musical instrument for facilitating musical expressions. in this paper, we propose a new musical instrument that allows people to concentrate on controlling indiscrete elements so that they can directly create their musical expressions. we describe a prototype musical instrument and demonstrate two applications of the prototype to show its effectiveness.
hands-on learning of computer programming in introductory stage using a model railway layout. this research aims to develop a new methodology and its supporting technologies for learning about computation and programming in the introductory stage through a hands-on playing experience with toys. this allows a beginner to acquire the concepts and knowledge of computation and programming by playing with a model railway set.
laboratory for automation psychology and decision processes. the laboratory for automation psychology and decision processes (lapdp) focuses on the cognitive/psychological aspects of human/computer interaction and does both basic and applied research in this area. it is housed in the department of psychology and is affiliated with the human/computer interaction laboratory (hcil) in the university of maryland institute for advanced computer studies (umiacs).
fusion: interactive coordination of diverse data, visualizations, and mining algorithms. fusion is a web-based system that enables end-users to rapidly and dynamically construct personalized visualization workspaces without programming. users first use advanced data schemas to link diverse data sources. then they use visualization schemas to coordinate visualization components and data-mining algorithms according to the unique needs of their data and tasks. they create a custom interactive visualization workspace that can be published on the web. this is accomplished through the fusion model and user interface that is based on schema concepts that are easy to learn and simple to use.
implementation of an electronic report viewing application for multi-cultural users. it is necessary to customise computer interfaces for south african users from different cultural groups who work on the same comuter system in a corporate environment? this question is addressed by a combination of a literature review and testing the ideas in a case study in south african financial institution.both components of the sutdy suggest that customized user interfaces may not be necessary for users of the same computer based systems in south african businesses.
improving international communication and cooperation in sigchi. sigchi, as the world's leading association for computer-human interaction, aspires to being a world-wide venue for our community. of sigchi's local chapters, nine are located in canada, france, italy, mexico, the netherlands, russia and switzerland, and fourteen are in the usa. this demonstrates the success of sigchi's work to become more relevant internationally but, as indicated in the latest "from the chairs" column in the sigchi bulletin, there is still much to be done. some issues include:&bull; differences in intellectual and research traditions&bull; practices and perceptions of sigchi within national communities&bull; language barriers and problems in sharing hci research and publications&bull; differences in cultural traditions&bull; differences in social and business interaction stylesthrough identifying and addressing these sorts of issues. sigchi can leverage its past and current work on internationalization.
graphical encoding in information visualization. in producing a design to visualize search results for a digital library called envision [5, 7], we found that choosing graphical devices and document attributes to be encoded with each graphical device is a surprisingly difficult task. by graphical devices we mean those visual display elements (e.g., color, shape, size, position, etc.) used to convey encoded information. research in several areas provides scientific guidance for design and evaluation of graphical encodings which might otherwise be reduced to opinion and personal taste. however, literature offers inconclusive and often conflicting viewpoints, leading us to further empirical research.
exploring search results with envision. envision is a multimedia digital library of computer science literature, with full-text searching and full-content retrieval capabilities. the envision system is noteworthy for two characteristics: 1) the high quality of the search results returned by our free text search system and 2) a highly usable user interface that provides powerful information visualization facilities, enabling users explore patterns in the literature, changing the display as their interests change.
usability services at compuware-madison: bringing usability to data processing. this presentation describes the usability services group at compuware-madison. compuware-madison is part of the national compuware professional services division, which provides consulting services for the computing industry, primarily data processing divisions of corporations. the usability services group was developed to help clients who are moving from traditional mainframe environments to newer technologies that use graphical user interfaces (guis). a group organized specifically to address usability issues is atypical in the data processing area, both from the client corporation and the consulting provider's perspective. this presentation describes how the group came to be, its projects, the challenges it faces, and its successes.
investigating police patrol practice for design of it. this paper describes an ongoing research project aiming to find design implications for information technology supporting police patrol work. a field study of approximately 300 hours over a twelve-month period has been conducted. tentative findings are structured as three design dimensions that are used to discuss a possible it design.
my health, my life: a web-based health monitoring application. using a handwritten journal to track meals, exercise, and weight is a common practice in the dieting and exercise industry. however, one major problem with using these journals is that they do not simplify the laborious process of calculating the nutritional content of a meal. in addition, the journals are difficult to share with other people, especially asynchronously. the "my health, my life" web application helps users reach their goals by simplifying the data entry process, while also connecting the user with professionals and people who have similar interests and goals.
txtboard: from text-to-person to text-to-home. the design of existing mobile phone technology has emphasised the primacy of person-to-person communication for voice, sms and image-based communication. it may be contrasted with place-to-place communication, the key property of fixed line telephony. however, other forms of communication may mix these two approaches: these include place-to-person or person-to place for example. these patterns may afford different values to users. this reports a field study of a prototype person-to-place sms communications device, 'txtboard'. this is a small, fixed display appliance for home settings. it displays text messages sent to it from any standard mobile phone. the study highlights how the person-to-place character of the device, combined with the 'public' or situated characteristics of its placement within home settings in particular, create new opportunities for use of sms.
a typology for educational interfaces. interfaces intended to support learning should be considered with respect to a typology based on student audience, constructive functionality, navigation support, cognitive cost and added learning value. analysed like this, the quality of interfaces used by students has noticeably improved over the past 10 years, in dramatic contrast to the much slower change in pedagogic value of educational software. the potential for the use of computers in support of interaction between learners, their peers and remote information sources has revealed important weaknesses inherent in current approaches to navigation support. key problems include scaleability, accessing peer learners and the shape and size of information spaces.
automatic support for web user studies with scone and tea. this paper describes the concepts of tea, a flexible tool that supports user tests by automating repetitive tasks and collecting data of user inputs and actions. tea was specifically designed for user studies in the world wide web and is able to interact with a web browser. building on a web intermediary (wbi) and a framework for web enhancement tools (scone), tea can be applied in a range of test settings - providing either a controlled laboratory environment or a quick tool for collecting informal data.
cues in the environment: a design principle for ambient intelligence. the aim of this paper is to propose design principles for ambient intelligence (ami) environments. the question we are investigating is how these environments can be designed to support a group to be able to carry out common goal-oriented activities. the approach we are taking in answering this question is informed by the concept of collective intelligence (ci). we are applying the concept of ci to ami as we have found it works well in biological and social systems. examples from nature demonstrate the power of ci stimulated by implicit cues in the environment. we use these examples to derive design principles for ami environments. by applying these design principles to a concrete scenario, we are able to propose ways to help decrease environmental pollution within urban areas.
chatel: a voice communication system for facilitating multithreaded conversation. in this paper we describe a novel voice communication system named "chatel" that achieves multithreaded voice communication. we confirmed that chatel facilitates multithreaded conversations based on user studies.
evaluating look-to-talk: a gaze-aware interface in a collaborative environment. we present "look-to-talk", a gaze-aware interface for directing a spoken utterance to a software agent in a multi-user collaborative environment. through a prototype and a wizard-of-oz (woz) experiment, we show that "look-to-talk" is indeed a natural alternative to speech and other paradigms.
weak gaze awareness in video-mediated communication. we present a video mediated communication system that conveys gaze information to a remote location. unlike existing video mediated communication system, this system does not send visual information directly, only gaze position and face direction. the appearance of those cues on the display depends on the distance between the screen and the user's eyes, which allows the user to control the appearance of her gaze. face direction is represented as a still image, which changes when the user's gaze position moves. with this system, people are able to transfer visual cues without becoming self-conscious about their face.
just blink your eyes: a head-free gaze tracking system. we propose a head-free, easy-setup gaze tracking system designed for a gaze-based human-computer interaction. our system enables the user to interact with the computer soon after catching the user's eye blinks. the user can move his/her head freely since the system keeps tracking the user's eye. in addition, our system only needs a 10 second calibration procedure at the very first time of use. an eye tracking method based on our unique eye blink detection and a sophisticated gaze estimation method using the geometrical eyeball model realize these advantages.
design expo 2. in this panel, we explore four sets of designs with different objectives and audiences. we discuss design approach, design goals, and design results, and how these designs might be different had they employed different design approaches and criteria for success. this panel builds on the design expo of chi2001 to explore approaches to design through the display and discussion of design artifacts.
a study of preferences for sharing and privacy. we describe studies of preferences about information sharing aimed at identifying fundamental concerns with privacy and at understanding how people might abstract the details of sharing into higher-level classes of recipients and information that are treated similarly. thirty people specified what information they are willing to share with whom.. although people vary in their overall level of comfort in sharing, we identified key classes of recipients and information. such abstractions highlight the promise of developing expressive controls for sharing and privacy.
hci at the university of michigan's school of information. the school of information at the university of michigan is a new graduate school that offers highly interdisciplinary opportunities in education and research. we have a program in hci as well as library and information sciences, archives and record management, and are discussing offerings in future systems architecture, organizational information systems.
using ethnography to design a mass detection tool (mdt) for the early discovery of insurance fraud. we describe a mass detection tool (mdt) for early detection of insurance fraud. ethnography was used to specify needs and process, capture expertise, and design an interface for triggering fraud indicators while capturing unexpected anomalies detected by claims handlers. the mdt uses a dynamic bayesian belief network of fraud indicators, whose weights are determined by how predictive each indicator is of specific types of fraud. the system uses automated knowledge updating to keep pace with dynamically changing fraud, adding new indicators that emerge from patterns of repeated anomalies.
aggregate pointers to support large group collaboration using telepointers. aggregate pointers, a new type of telepointer, can be used to support the collaboration of many people in interactive environments. an aggregate pointer can make it easy for people to understand the overall direction of others' intentions or interests, and help achieve a group decision or build consensus. moreover, aggregation can make distracting behavior or noise less disruptive. aggregate pointers prevent such problems from disturbing collaborative work. we conducted experiments to show that people are not good at accurately locating the focus that is reflected by multiple telepointers, and that aggregate pointers help people share more accurate aggregation and complement individual telepointers.
quantifying interpersonal influence in face-to-face conversations based on visual attention patterns. a novel measure for automatically quantifying the amount of interpersonal influence present in face-to-face conversations is proposed based on the visual-attention patterns of the participants as inferred from video sequences. first, we focus on the gaze of the participants as an indicator of addressing / listening behavior and build a probabilistic conversation model for inferring the gaze directions and conversation structures like monologue and dialogue, from observed utterances and head directions measured with image-based head trackers. next, based on the estimates, the amount of influence is defined based on the amount of attention paid to speakers in monologues and to persons with whom the participants interact with during the dialogues. experiments confirm that the proposed measures reveal some aspects of interpersonal influence in conversations.
interrupted cognition and design for non-disruptiveness: the skilled memory approach. interruptions have gained in importance as a topic in current hci research. through a series of experiments, we take a step toward analyzing the active role of human memory in controlling interruptions. the results of these experiments lead us to propose a novel approach, the skilled memory approach, to how uis can support memory in skilled man-agement of and recovery from interruptions.
a cognitive meta-analysis of design approaches to interruptions in intelligent environments. minimizing interruptions to users is a crucial and acknowledged precondition for the adoption of new intelligent technologies such as ubiquitous and proactive computing. this paper takes a step toward achieving a consensus among the numerous existing approaches addressing the challenge posed by interruptions. we start by explicating why interruptions are considered important. we then reveal similarities and differences among the approaches from a cognitive viewpoint. it appears that the approaches draw from different assumptions about human cognition. some of the approaches contain inconsistencies. the cognitive analysis also inspires directions for future work.
containers: a new hierarchical model for browser interfaces. the development of a low bandwidth, high error tolerant neural browser, called the brainbrowser, has raised new navigational issues. with this paradigm shift of two-dimensional spatial organization and navigation, one possible solution is to serialize the interface.due to the inherent complexity of this paradigm, new methods of hierarchical spatial organization can help to relieve the sense of a labyrinthine structural organization that a user must overcome when using this method of browser navigation. this issue has created the opportunity to explore the possibility of incorporating "containers" as an additional navigational capability that will allow the resulting serial interface to be organized hierarchically. this ultimately will increase the user's navigational "sense of place" as well as minimizing the user's cognitive burden.
a study of reviews and ratings on the internet. many online sites use rating and review systems to attract new users by providing diverse opinions from their users. however, there is not much research on how to design these types of systems better. in this research, we explore how people perceive reviews and ratings on the internet in order to inform the design of rating and review systems. in this ongoing project, we have conducted preliminary user studies to uncover the ways people use and perceive reviews and ratings on the internet. our initial findings show some interesting insights about different personal interpretation and utilization of ratings and reviews in different contexts. we conclude by listing recommendations for designers of online rating and review systems.
kick-up menus. interaction with mobile applications is often awkward due to the limited and miniaturized input modalities available. kick-up menus exploit the video capabilities of camera equipped smart-phones and pda's to provide a fun solution for interaction tasks like menu selection and simple games.
privacy and self-disclosure online. in this paper we present early results from a study which provides a detailed examination of the interaction between people's willingness to disclose personal information online and their privacy concerns and behaviors. an online survey was administered to participants in two parts using an internet based surveying system. part 1 of the survey measured participants' privacy concerns and behaviors. part 2 measured participants' willingness to provide information using behavioral and dispositional measures of self-disclosure. structural equation modeling identified two different types of privacy processes contributing to disclosure: a state process (trust and perceived privacy) and a trait process (privacy attitudes and behaviors), which were found to act independently on self disclosure. the results provide a valuable insight into people's privacy concerns and the disclosure of personal information to web sites.
appropriateness of foot interaction for non-accurate spatial tasks. this paper describes alternative methods for manipulating graphical user interfaces with a foot. feet are used in many real world tasks together with the rest of the body, but in computer environments they are almost completely put aside as an interaction possibility. one of the major problems in choosing input methods for different tasks in user interfaces is determining what kind of method is appropriate for a certain task. feet could easily be used as a supportive input method in interaction with computers together with the traditional mouse. in this paper, we discuss the possibility of using foot input in different non-accurate spatial tasks, and the efficiency and usability experience the users have of foot interaction compared with a traditional hand-based interface with the same input device. the aim is to find out how well foot interaction suits for non-accurate spatial tasks.
safety-critical interaction: usability in incidents and accidents. recent years have seen an increasing use of sophisticated interaction techniques in the field of command and control systems. the use of such techniques has been required in order to increase the bandwidth between the users and the systems and thus to help them deal efficiently to increasingly complex systems. these techniques come from research and innovation done in the field of hci but very little has been done to improve their reliability and their tolerance to human error. it can be difficult to know how to assess the risks that such systems can create for the successful operation of safety-critical systems. one consequence of this is that interaction issues are almost entirely missing from international development standards in safety-critical systems, such as iec615098 or do 178b. this sig will provide a forum for academics and industrials to exchange research problem as well as best practice in the field of safety critical interactive systems.
groupware adoption & adaptation. this paper describes my research on the adoption of groupware technologies in business organizations, and their subsequent integration with individual and organizational work practices as a result of wide, sustained use. an initial study of two organizations successfully using a particular group-ware technology---electronic calendars and meeting schedulers---revealed several technical, behavioral, and organizational factors that enabled initial adoption. additional findings from this study suggested that groupware technology was integrated into work practices quite differently at each site, despite similarities in adoption patterns and other organizational features. my dissertation research will continue to elaborate the conditions that enable adoption of groupware technologies. my investigations will also explore the way electronic calendars are subsequently integrated into local work practices, and the organizational ramifications of these particular adaptations.
the impact of human-centered features on the usability of a programming system for children. hands is a new programming system for children that was designed for usability. this paper examines the effectiveness of three features of hands: queries, aggregate operations, and data visibility. the system is compared with a limited version that lacks these features. in the limited version, programmers can achieve the same results but must use more traditional programming techniques. children using the full-featured hands system performed significantly better than their peers who used the limited version. this provides evidence that usability of programming systems can be improved by including these features.
the magic carpet: physical sensing for immersive environments. an interactive environment has been developed that uses a pair of doppler radars to measure upper-body kinematics (velocity, direction of motion, amount of motion) and a grid of piezoelectric wires hidden under a 6 x 10 foot carpet to monitor dynamic foot position and pressure. this system has been used in an audio installation, where users launch and modify complex musical sounds and sequences as they wander about the carpet. this paper describes the floor and radar systems, quantifies their performance, and outlines the musical application.
passive acoustic knock tracking for interactive windows. we describe a novel interface that locates and characterizes knocks and taps atop a large glass window. our current setup uses four contact piezoelectric pickups located near the sheet's corners to record the acoustic wavefront coming from the knocks. a digital signal processor extracts relevent characteristics from these signals, such as amplitudes, frequency components and differential timings, which are used to estimate the location of the hit and provide other parameters, including the rough accuracy of this estimate, the nature of each hit (e.g., knuckle knock, metal tap, or fist bang), and the strike intensity. this system requires only simple hardware, needs no special adaptation of the glass pane, and allows all transducers to be mounted on the inner surface, hence it is quite easy to deploy as a retrofit to existing windows. this opens many applications, such as an interactive storefront, with projected content controlled by knocks on the display window.
interactive therapy with instrumented footwear. musical feedback can aid in learning to move properly, for example in physical therapy, sports medicine, or training. by appropriately instrumenting the body to detect the correct motion (or the motion to be avoided), and mapping its characteristics causally onto an interactive musical stream, a patient can, in certain cases, be discouraged from making the incorrect motion and encouraged to move properly. we describe a heavily instrumented pair of shoes that were developed to function as a wearable gait laboratory, and overview some of the initial work performed using these shoes for real-time interactive therapy based exploiting musical feedback.
sharable digital tv: relating ethnography to design through un-useless product suggestions. the results presented here are part of an in depth study of current digital tv usage carried out for a manufacturer of domestic appliances. a systematic review of the literature revealed a set of issues that informed the design of an ethnographic study of five households of differing type. the concerns identified were then further explored through sketch-based conceptual designs, four of which are reported here. they are: (i) putting the electronic program guide (epg) onto a mobile phone to facilitate personalisation and to allow one person to use it while another is watching a programme; (ii) family voting to make explicit certain power relationships in the family and perhaps democratise them; (iii) using the tv for other purposes when not watching programs (e.g., as a message board or electronic picture frame) to avoid the ugliness of a blank tv screen, and (iv) multi-channel hopping to facilitate idly flicking through the channels. these suggestions are not fully worked designs but provocative concepts to relate the concerns identified to design. in this sense they are "un-useless" and draw on the playful and provocative tradition of chindogu.
an interactive speech interface for summarizing agile project planning meetings. in this paper we present an autonomous meeting summarizer that transcribes an agile planning meeting and produces a textual summary of the discussion. we explore the issues involved in designing a speech-based interactive system that communicates with humans in a natural language. the inherent nature of ambiguity in conversational speech is overcome by suggesting a list of possible phrases to listen for. the system interacts with users in an interview-style dialogue for data collections. this is possible because we used the highly constrained structure and terminologies of agile planning meetings to make the approach successful.
influences of personal preference on product usability. this study intended to demonstrate experimentally that user trust or affection for a brand affects the results of usability tests. for the experimental method, experimentees were exposed to products made by companies they preferred and did not preferred, and these products were then tested with a group of tasks for each product. for the test assessments, nasa-tlx was utilized to measure the mental and physical demands on the experimentees, along with the measure of error rate and time of product operation.the results were that, even though the experimentees performed the same tasks, they had decreased mental and physical demands operating products that they preferred. that is, it was shown that an individual's psychological state greatly influences the usability of a product and that, for a usability test, the user's image of the product's brand is also an important variable.
magic asian art. throughout history, paintings have had a static perspective, as determined by the artist. nowadays, viewers are not passive anymore. this proposal focuses on dynamic painting, and active audiences. magic asian art allows viewers to enjoy dynamic asian painting, and furthermore, each audience recreates the same painting according to their personal preference or the impression of a painting. it is quite similar that conductor conducts an orchestra for the same music differently. we extract viewer's intension based on the emotional status or impression of the painting by using gaze tracker and the painting will be more dynamic and fun. magic asian art is neither movies by cinematographer, nor video games by an algorithm, but novel interactive painting media by each user.
designing an immersive tour experience system for cultural tour sites. along with the change in tour paradigm, tourists are increasingly seeking for new and meaningful experiences. however, most cultural tour sites today still maintain a conventional form of tour that is static and information centered. to reflect the new needs of tourists, the concept of immersive tour experience has been investigated. immersive tour experience refers to a type of tour where the tourist lively experiences the historical scenes that occurred at the tour site, as if the tourist had traveled to the past. a system named "immersive tour post" was designed to realize this concept. this system is in a post form and uses of audio and video augmented reality to provide the immersive experience. through an experiment conducted at an actual tour site, this application proved to increase the interest level as well as facilitate understanding of the content. through this research, the potential of immersive tour experience in improving the quality of tour for cultural tour sites was verified. moreover, a new user experience was developed by implementing hci technology in a new context. with further development, the proposed system is expected to become a useful application that attracts tourists and create greater value for our cultural assets.
creating an enhanced reality user interface - ersolitaire. an enhanced reality user interface uses aspects of the real world and simulated computer perception to yield a simplified.
glume: exploring materiality in a soft augmented modular modeling system. we introduce glume, a modular scalable building system with the physical immediacy of a soft and malleable material. the glume system consists of soft and translucent augmented modules, which communicate capacitively to their neighbors to determine a network topology and are responsive to human touch. glume explores a unique area of augmented building materials by combining a discrete internal structure with a soft and organic material quality to relax the rigidity of structure and form in previous tangible building block approaches. we envision glume as a tool for constructing and manipulating models, visualizations and simulations of organically based three dimensional data sets.
a method for graphical input on the www. using the world wide web (web) is rapidly becoming one of the main ways in which people interact with computers. however, although the web has permitted a rich variety of hypertext output, input has, until recently, been restricted to text or simple menu choices. the advent of languages like java, which permit interactive programs to be included on a page, clearly changes what is possible. this contribution discusses the requirement for graphical input on the web and describes an initial implementation which permits graphical objects to be manipulated on a web page to provide input for subsequent analysis and computation.
design of usable multi-platform interactive systems. recent years have seen the introduction of many types of computers and devices. in this sig we want to discuss how to provide developers with tools, methods and languages able to support both the development of single interactive applications for multiple platforms and the dynamic execution of these applications in a changing environment while preserving usability. since chi is the most important conference on human-computer interaction, it is the most suitable place where to discuss such issues, the results achieved so far, compare them with other results obtained by other groups in the world and discuss the opportunity provided by joining efforts.
privacy and hci: methodologies for studying privacy issues. this workshop aims to reflect on methodologies to empirically study privacy issues related to advanced technology. the goal is to address methodological concerns by drawing upon both theoretical perspectives as well as practical experiences.
hci and security systems. this workshop will seek to understand the roles and demands placed on users of security systems, and explore design solutions that can assist in making security systems usable and effective. in addition to examining end-users, this workshop will also examine the issues faced by security system developers and operators. the goal of the workshop is to build a network of interested people, share research activities and results, discuss high priority areas for research and development, and explore opportunities for collaboration.
using an interaction model as a resource for communication in design. many design models and representations have been proposed to support user-centered system design, such as scenarios, use cases, and prototypes. with these artifacts, designers typically deal with representations of fragments of the application, and sometimes have difficulties communicating with one another about design decisions. to face some of the communication challenges during design, we believe that we could use a global view of the system's apparent behavior, from the users' point of view. such a representation would serve as a common reference for hci designers from different disciplinary backgrounds, helping to foster communication among them. in our goal to promote a shared understanding of the application, we have investigated different professionals' usage of molic, an interaction modeling language that follows an interaction-as-conversation metaphor. molic allows designers to build a blueprint of all the interactions that may take place when the application is used.
gameplay issues in the design of spatial 3d gestures for video games. we describe preliminary tests that form the first phase of research into issues involved with the design of spatial 3d gestures for video games. early research on 3d gesture and spatial interaction was largely the domain of virtual reality (vr) [1]. more recent work looks at 3d gestures for mobile devices [2] and pervasive computing [3]. we are investigating issues affecting usability and fun [4] in the context of 3d gestures and spatial movement in video games where emotion, immediacy and immersion are more important than breadth of functionality and user task efficiency. these tests use our 3motion™ system, a wireless inertial motion tracking device and gesture sdk. this enables a range of gesture types from tight, precise movements to whole arm gestures, and from direct mapping of movement to recognition of 3d symbolic gestures. four game scenarios using different spatial gesture characteristics were used to identify gameplay issues that have an impact on the design of 3d interaction.
presentation discovery: building a better icon. icons have become an inseparable part of graphical user interfaces. there is well-developed literature describing novel applications of icons and methods for evaluating existing icons. however, there has been comparatively little research into the processes necessary to design effective new icons. this paper will introduce a novel design methodology for developing graphical interface components, including icons, called presentation discovery. the method is grounded in semiotics and personal construct theory, and adapts knowledge acquisition approaches to the graphical domain. a pilot study applying presentation discovery in a biomedical domain is presented.
user activity histories. current software interfaces fail to incorporate historical data from user interaction into their design. while some systems exhibit a minimalist use of history in the form of undo and redo, selective menu items, and other static elements, there has been a lack of use of history in the dynamic elements of interaction. we propose a more widespread use of historical data from user-software interaction to augment the desktop and application environment. we believe the use of historical data can improve the user's experience at many different levels. our approach begins by assuming that everything the user is doing on the desktop is important to them, and that it will be important again in the future.
overlaying motion, time and distance in 3-space. an innovative method for visually and functionally combining the elements of motion, time and distance in a three-dimensional computer animation is presented. at a glance, the elapsed time of the movement, distance traveled, relative velocity, scale and the object orientation can be derived from a single visual representation. creation and editing of animations can also be simplified through the use of an interrelated set of immersive three-dimensional user interface elements.
making sense of social networks. social network analysis has emerged as a powerful method for understanding the importance of relationships among interacting units in a variety of domains. however, interactive exploration of social networks is challenging because: (1) it is difficult to comprehend the characteristics and structure of networks when there are many edges and nodes, and (2) current systems are often a medley of statistical methods and overwhelming visual output which leaves many analysts uncertain about how to explore in an orderly manner. this results in exploration that is largely opportunistic. the contributions of our work are principles and an interface to support systematic analysis of social networks. we believe our approach will enable users to better understand the structure of networks and the social groups within.
taming of the ring: context specific social mediation for communication devices. taming of the ring is an interactive system that lessens the problems of social disturbance caused by cell phone communication. as cell phone usage levels increase, social disturbance becomes an increasingly important issue. callers and receivers have a need to discretely handle phone communication in delicate social situations. early cell phone usage observations led to an interaction model hypothesis. a functional prototype was created to test the concept in the field. preliminary results indicate that both calling and receiving users want more responsibility and control when placing phone calls, and that two remotely-mediated options, "hold" and "meeting," were enough to fill this communication need in the majority of situations.
pet pals: a game for social mediation. pet pals is a game that facilitates social interaction in a real world group context. early user research of pre-teens indicated that children establish a social hierarchy through sharing and trading. the needs revealed in the study led to a game design to mediate peer interaction through trade. a functional prototype was developed to test the game on two groups of users. pet pals is a game of trading that globally monitors who is participating in real-time by tracking the exchange of objects and dynamically altering each object's value to encourage those not participating to interact with each other, in part by making their objects more valuable to others. through bouth and neagative reinforcement, the system promotes face-to-face communication.
practical usability evaluation. practical usability evaluation is an introduction to cost-effective, low-skill, low-investment methods of usability assessment. the methods include (1) inspection methods (e.g., heuristic evaluation), (2) observational skills and video (including user testing with think-aloud protocols), (3) program instrumentation, and (4) questionnaires. the tutorial features many step-by-step procedures to aid in evaluation plan design.
acm sigchi information infrastructure. we describe recent improvements to the acm sigchi information infrastructure, mainly in the sigchi web site and sigchi use of the acm listserv for mailing lists and aliases, and how they have been applied to provide general information, support committees, publications and conferences, and technical discussions. we then describe some key areas where volunteers are needed to improve sigchi information services, particularly in the area of databases.
usability testing of system status displays for army missile defense. modernizing workstations for military applications is a challenge: designers must increase performance without affecting safety in any way. furthermore, interaction efficiency is required to avoid fatigue and minimize error rates which could cost lives. soldiers are understandably reluctant to use a new interface design on systems where life critical decisions are made. it is paramount to obtain user assessment of interface designs early and continually throughout the software development cycle to insure user acceptance and optimize user performance. statistical based usability tests were performed with soldiers to determine display designs for the u.s. army's theater high altitude area defense (thaad) radar soldier user interface.
anthropomorphic visualization: a new approach for depicting participants in online spaces. anthropomorphic visualization is a new approach to presenting historical information about participants in online spaces using the human form as the basis for the visualization. various data about an individual's online behavior are mapped to different parts of a "body", resulting in an abstract yet humanoid representation of a person. we explain the details of the approach and make some initial observations about the visualization in use. we also discuss broader issues relating to presenting data that has been mined from individuals' messages, using the human form to depict this data, and evaluating visualizations used for social purposes.
remarkable computing: the challenge of designing for the home. the vision of ubiquitous computing is floating into the domain of the household, despite arguments that lessons from design of workplace artefacts cannot be blindly transferred into the domain of the household. this paper discusses why the ideal of unremarkable or ubiquitous computing is too narrow with respect to the household. it points out how understanding technology use, is a matter of looking into the process of use and on how the specific context of the home, in several ways, call for technology to be remarkable rather than unremarkable.
floor interaction hci reaching new ground. within architecture, there is a long tradition of careful design of floors. the design has been concerned with both decorating floors and designing floors to carry information. ubiquitous computing technology offers new opportunities for designing interactive floors. this paper presents three different interactive floor concepts. through an urban perspective it draws upon the experiences of floors in architecture, and provides a set of design issues for designing interactive floors.
augmenting icons for deaf computer users. tooltips (tts) can be used to make icons more understandable to users. however, text-based tooltips will not assist users with print disabilities. four types of tts to assist deaf and hearing impaired users were implemented: sign language, picture (an enlarged icon and text explanation of the function), human mouth and digital lips (the last two to assist in lip reading). an evaluation of 16 tts of each type with 15 deaf users found that the sign language and picture tts were very positively rated on satisfaction and understanding and would be used again, but that human mouth and digital lips were of no assistance in their current implementation to deaf users in lip reading the names of icons.
the use of declarative and procedural knowledge in intelligent navigation displays. one theory of environmental cognition suggests that both declarative landmark knowledge and procedural route knowledge are essential in structuring internal representations of the environment; such representations facilitate effective navigation in that environment [5, 7]. the proposed study will provide data to test this theory. the application that will be studied is an advanced traveler information system (atis), which provides route guidance information to automobile drivers. current route guidance systems incorporate only procedural route information in their route guidance displays (i. e., they give directions for getting to your destination without supplying landmarks to identify the route [e.g., 3]). this study will evaluate how the inclusion of landmark icons in atis displays affects users' navigation performance. the results will be important to atis developers, who need to know what informational elements to include in atis route guidance displays to most effectively support navigation tasks. the results will also be important in a theoretical sense, by testing a theory of environmental cognition with real-world navigation tasks.
future interfaces: social and emotional. this panel addresses 'science fact' for future social-emotional interfaces. we discuss new theory and upcoming interface technologies that enable or augment social-emotional interaction between people and computers, and between people via new forms of computers. the theme is rooted in: (1) findings that human-computer interaction is social and emotional even when interfaces are not designed with such interaction as a goal, and (2) advances in technology, enabling computers to recognize, express, and respond to emotional and social information. the panelists will describe the guiding theory for this research, show examples of emerging technologies including new wearable, implantable, and robotic interfaces, and discuss the implications of social-emotional interaction for interface development, design, and testing.
wi-fi and handhelds: perfect synergy. consumers assume when they make a purchase of a wi-fi handheld they will have to spend all day to set up and get it connected. when palmone inc. decided to produce a wi-fi product, we wanted to create a handheld that users could turn on and go. the goal was to give the users a simple and elegant experience with wi-fi, unlike competitive products that were hard to use, and often intimidated the users.palmone had an opportunity to branch out the product line with wi-fi and position the company as mobile broadband product providers. the challenge was to create a solid wi-fi user experience that connected users seamlessly in various locations without taking away the control of the handheld from the user.we introduced a simple wizard that stepped users through the initial connection process then automatically connected in different locations and simplified configuration of hidden or encrypted networks.
pegblocks: a learning aid for the elementary classroom. in this paper we describe the implementation of pegblocks - an educational toy that can be used to illustrate some basic physics principles to elementary students.
query previews in networked information systems: the case of eosdis. dynamic queries have been shown to be an effective technique to browse information, and to find patterns and exceptions. dynamic queries involve the interactive control by a user of visual query parameters that generate rapid (100 ms update), animated, and visual displays of database search results. the data of early implementations was stored in local memory to guarantee optimal speed. problems arise when the data is very large and distributed over a network. to overcome the problems of slow networks and data volume we propose a two-phase approach to query formulation using query previews and query refinements [1]. preview mechanisms have been used in the past [2] and we believe that their use will be a major component of successful networked information systems interfaces (e.g. [3]).
technologies for families. in this workshop, we propose to bring together researchers from industry and academia to discuss the design of new technologies for families. we will focus on both design techniques and the technologies themselves. through discussions and brainstorming we hope to discover new ideas, which can be disseminated more broadly.
tamil market: a spoken dialog system for rural india. in this paper, we describe the design process, results, and observations from a pilot user study for tamil market, a speech-driven agricultural query system, conducted in community centers in rural india. the primary users were rural villagers of varying degrees of literacy from three districts of tamil nadu. preliminary findings from a wizard-of-oz field study show that rural villagers are able to navigate through a dialog system using their voice, regardless of literacy level and previous experience with technology. traditional user study techniques, however, favor literate users and are ill-suited to research in developing regions.
evaluating a sketch environment for novice programmers. this paper describes the evaluation of an electronic sketch interface design tool for novice programmers. a comparative study was undertaken with small groups using two different shared space environments; a conventional informal design environment and the pen based digital whiteboard. the students reacted positively to the electronic environment, where they worked informally with their design ideas and checked them more carefully.
interacting with sketched interface designs: an evaluation study. digital hand-drawn sketches provide a new and unique way of interacting with a prototype user interface design while it is still rendered as a sketch. the successful use of prototypes and scenarios for exploring design ideas is well documented. hand-sketched designs have also been found preferable to formal diagrams during early design. the study reported here shows that interacting with digital sketches adds an exciting new dimension to the interface design process, we found that people do more revisions and more accurate revisions with digital sketches.
universal design for mobile phones: a case study. in this paper we describe a case study of universal design applied to mobile phone physical devices. using a user-centered design process, we tried to integrate visually-impaired, hearing-impaired and elderly peoples' needs to design mock-ups adapted in terms of usability and design style.
collaborative multimedia learning environments. i use the term "collaborative", to identify a way that enables conversation to occur in, about, and around the digital medium, therefore making the "digital artifacts" contributed by all individuals a key element of a conversation as opposed to consecutive, linear presentations used by most faculty at the design school.installations of collaborative multimedia in classrooms at the harvard university graduate school of design show an enhancement of the learning process via shared access to media resources and enhanced spatial conditions within which these resources are engaged. through observation and controlled experiments i am investigating how the use of shared, collaborative interfaces for interaction with multiple displays in a co-local environment enhances the learning process. the multiple spatial configurations and formats of learning mandate that with more effective interfaces and spaces for sharing digital media with fellow participants, the classroom can be used much more effectively and thus, learning and interaction with multimedia can be improved.
on interfaces projected onto real-world objects. this paper describes preliminary results of research on the perception and usability of interfaces projected onto real-world objects. using a projector setup that enables us to compare users' color preferences, we show that the objects onto which colors are projected influence a user's choices. we also observe that many users are unable to recall and/or were unaware of the objects onto which the color interface was projected. these results suggest that there may be complex interactions affecting the use of interfaces that integrate the virtual and the real world.
d20: interaction with multifaceted display devices. in this paper we investigate the principles for desiging multifaceted displays and their potential interfaces. d20 is a prototype of a handheld digital device which has an icosahedron shape. each face of the device is a triangular display, the entire surface of the device forms one continuous multisided display. the user interacts with the device by manipulating it. the principles that we develop can be applied to other non-rectilinear multifaceted displays.
haptic feedback for pen computing: directions and strategies. we seek to improve the xperience of using pen computing devices by augmenting them with haptic, tactile feedback displays. we present the design of the haptic display for pen computers, and explore interaction techniques that allow users to feel gui elements, textures, photographs and other interface elements with a pen. we discuss research directions in haptic displays for pen devices and report results of an early experimental study that evaluated the benefits of tactile feedback in pen computing.
touchengine: a tactile display for handheld devices. in this paper we describe the design of a haptic display for mobile handheld devices, including the development of a new miniature actuator, the construction of a haptic display using this actuator and prototypes of early applications.
voronoi diagrams, vectors and the visually impaired. we describe an algorithm for the detection of targets which will be encountered by a visually impaired user while exploring a two dimensional diagram. a user test examining the success of this algorithm during a targeted search task is described. we discuss the implications of this work on interface design for the visually impaired, including the planned inclusion of this algorithm in a multi-modal document browser.
tutorial - color and type in information design. work with color and type in the chi community is often undertaken with a base of experience and a sense of craftsmanship, but without a firm foundation in the principles of perception, science, and engineering. in this tutorial, you will learn the perceptual, color science, and engineering principles that underlie effective information presentation. you will learn to apply these principles to the design of graphical user interfaces and information displays.this tutorial is directed to graphic designers, interface designers, human factors engineers, usability specialists, and developers of on-line information. you should have experience in developing user interfaces, experience in creating and manipulating digital imagery, or experience in writing or illustration.
breakdown visualization: multiple foci polyarchies of values and attributes. breakdown analysis involves decomposing data into sub-groups to allow for comparison and identification of problem areas. good analysis requires the ability to group data based on attributes or values. breakdown visualization provides a mechanism to support this analysis through user guided decomposition and exploration of tabular data with a polyarchy structure. this is useful in domains such as sports statistics and corporate financial reports. breakdown visualization utilizes a spreadsheet format for comparison of adjacent visualizations.
the kite geometry manipulator. we introduce a new geometry manipulator, a tool for 2d geometrical object manipulations in drawing packages. the manipulator is an extended combination of two standard approaches. we performed an experiment, where users tested three types of manipulator. we evaluated the manipulators on perceived flexibility, efficiency of use, and subjective satisfaction. our new manipulator scored high on all aspects.
ambient agoras: inforiver, siam, hello.wall. this demonstration reports results from the eu-funded project ambient agoras, investigating future applications of ubiquitous and ambient computing in workspaces. instead of presenting underlying system technologies or evaluation findings, this demonstration will focus on three running prototypes that emerged from the project: inforiver, siam, and hello.wall. the systems are meant to support work-related processes in office buildings while at the same time fostering informal communication. the inforiver implements the information river metaphor for information flow through a building or an organization. siam is a task-management system enriched with collaboration support to foster group communication and awareness. hello.wall is a new ambient display that can "borrow" mobile artefacts. all prototypes are multi-user and multi-device systems enabling coherent and engaging interaction experiences with a variety of sensor-enhanced smart artefacts.
an experience with an enriched task model for educational software. the educational domain brings new issues and specific requirements to interface design. often traditional hci principles and guidelines need to be disregarded or broken in order to allow for the intended learning to take place [1, 6]. how to adapt existing hci methods and techniques to this domain is still an open issue for the hci and education fields [5]. in this paper we propose the scaffold representation model (srm), which allows intended educational support for learners in the application to be abstractly described. the model allows for the generation of educational information that can be added to a traditional hci task model. we describe an experiment in which srm was used in the design of a learning support system and its contribution to the process of design.
spam, spam, spam, spam: how can we stop it. how do we keep our channels of electronic communication, both individual and group, open, while keeping out inappropriate and unrelated materials, such as spam? does someone other than the intended recipient have the right to control what electronic mail users see? might this lead to censorship? if others do have the right to control what e-mail users see, how should this filtering or censorship occur? are users aware of this filtering? if others are not controlling what users receive, what can users themselves do to control their environments to limit the amount of incoming spam? these are some of the topics that this chi panel will address.
what's sigchi's role in strengthening communities? on september 11 we saw how a tightly knit group worked together to penetrate the us and carry out a carefully orchestrated attack on the world trade center and pentagon. we also saw how citizens spontaneously organized themselves to care for victims and their families, and support each other. how can the chi community build on its knowledge of computer-mediated communication and socio-technical systems design to build a more cooperative society? the aim of this discussion is to develop a research and action agenda for chi that strengthens communities locally, nationally and internationally. the underlying premise is that such socio-technical systems can be assessed and improved so that they more effectively facilitate information exchange, emotional support, and consensus building.
utopia appropriated: the future as it was. this program takes a critical look at mid-20th-century utopian promises and persuasions as dramatized in industrial and advertising films released between 1936 and 1965. in these films and related advertising campaigns, major american corporations appropriated old utopian ideas as their own, promising a bright, affluent future enabled by cybernetics, household technology, and new means of transportation and communication. despite the amusing anachronisms in these films, many of the ideas they promote are still very much part of corporate discourse today, and have had a tremendous effect on shaping public expectations and attitudes towards information technology.
a historical perspective of hci development in romania. in this paper, we are presenting the hci development in romania from a historical perspective. after a brief introduction in the historical context, we outline the main hci programs in the romanian universities. then we present some key activities of rochi (the romanian chi group), which are supposed to promote hci in our country, and we propose some directions for the cooperation of rochi with other sigs.
usability research challenges for cyberinfrastructure and tools. we summarize the motivation and aims for this workshop on usability research challenges for cyberinfrastructure and tools, and outline workshop preparations and program.
mobi-d: a model-based development environment for user-centered design. mobi-d (model-based interface designer) is a software environment the design and development of user interfaces from declarative interface models. end-users informally describe tasks and data, from end-users, from which developers construct formal models of user tasks and domain objects. the system supports development of presentation and dialog specifications from such models, and allows visualization of interface designs as units encompassing all relations and dependencies among the elements of task, data and user-interface specifications, mobi-d is the first development environment to define an interface model as a comprehensive conceptual object, to identify an interface design as a declarative component of an interface model, and to establish a development cycle based on such a model. the sharable nature of the interface modeling language of mobi-d, along with the open architecture of its system opens the door for many research areas in hci to explore the benefits and potential of using interface models.
stresscam: non-contact measurement of users' emotional states through thermal imaging. we present a novel methodology for monitoring the affective states of computer users. the method is based on thermal imaging of the face. to the user, the imaging system appears much like a video-conferencing camera. the method does not require contact with the subject and is passive; therefore, monitoring can be continuous and transparent to the computer user. we have found that user stress is correlated with increased blood flow in the frontal vessel of the forehead. this increased blood flow dissipates convective heat, which can be monitored through thermal imaging. the system has been evaluated on 12 subjects, and compared against real-time measurements of energy expenditure (ee). the new method is highly correlated with the established, but awkward ee methodology. the stresscam methodology is applicable to many instances where the real time measurement of users' emotional state is needed.
uxnet: making connections. this position paper for the chi2005 development consortium describes the vision that led to the formation of the user experience network (uxnet) and cross-disciplinary needs it addresses, for individual practitioners and for the ongoing development of the field as a whole.
magic land: live 3d human capture mixed reality interactive system. "magic land" is a cross-section of art and technology. it not only demonstrates the latest advances in human-computer interaction and human-human communication: mixed reality, tangible interaction, and 3d-live human capture technology; but also defines new approaches of dealing with live mixed reality content for artists of any discipline. in this system, the user is captured by cameras from many angles and her live 3d avatar is created to be confronted with 3d computer-generated virtual animations. the avatars and virtual objects can interact with each other in a virtual scenery in the mixed reality context; and users can tangibly interact with these characters using their own hands.
ideakeeper notepads: scaffolding digital library information analysis in online inquiry. online inquiry activities are important for k-12 learners to explore substantive driving questions in different areas, especially science. however, the inquiry process is complex for learners who need extensive support to mindfully engage in these activities. we are addressing this with the digital ideakeeper, a scaffolded work environment for online inquiry. while online inquiry includes many different activities (e.g., planning, information seeking, synthesis), this paper focuses on supporting learners with information analysis so they can effectively read and make sense of articles they find in digital libraries. here we spotlight scaffolded notepads, which connect to articles learners are reading in a browser. notepads support learners by connecting their goals to their reading, guiding reflection and articulation, and implementing a framework by which learners' notes and articles are linked, saved and viewed together to aid with more seamless information management.
developing an airline freight management system: meeting airline and end-user challenges. a commercial freight management application for airlines must address the business concerns of airlines as well as offer limited job interference for end-users whose primary occupation is to move cargo. discussion includes usability challenges and interactive design solutions, methodology for quick development in a time- and resource-constrained budget, and compromises required for commercial success.
use of video in user interfaces that require non-linguistic cues. this case study describes the creation of a user interface for a self-service kiosk that collects biographic and biometric data from non-english-speaking individuals who are unfamiliar with american/western culture, with little formal education, and little-to-no experience with computers. the users were also completely unfamiliar with the task and in a very stressful environment. therefore, unlike most commercial software interfaces that "tell" users how to complete a task by relying on entry fields labels and controls, or use language to provide context for tasks, we need to "show" users how to interact with interface. the goals for our user interface are similar to the goals of arcade video game machines that use a short demonstration video, without words, to draw the viewer's attention, create an expectation in the viewer of what is to come, and demonstrate the task to the viewer. user testing found that demonstration videos could meet these requirements.
artificial window view of nature. previous research from environmental psychology shows that human well-being suffers in windowless environments in many ways. in addition, research shows that a window view of nature is psychologically and physiologically beneficial to humans. current window substitutes, still images and video, lack three dimensional properties necessary for a realistic viewing experience - primarily motion parallax. we present a new system using a head-coupled display and image-based rendering to simulate a photorealistic artificial window view of nature with motion parallax. evaluation data obtained from a group of human subjects suggest that the system prototype is a better window substitute than a static image, and has significantly more positive effects on observers' moods. the test subjects judged the system prototype as a good simulation of, and acceptable replacement for, a real window, and accorded it much higher ratings for realism and preference than a static image.
super cilia skin: an interactive membrane. in this paper we introduce super cilia skin, a new approach for integrating haptic and visual communication. super cilia skin is conceived as a computationally enhanced membrane coupling tactile input with tactile and visual output. we present the design of our prototype, an array of individual actuators (cilia) that use changes in orientation to display images or physical gestures. we discuss ongoing research to develop tactile input capabilities and we present examples of how it can enrich interpersonal communication and children's learning.
viewing and annotating media with memorynet. in this paper we describe an investigation into how we might share and annotate media objects (namely photographs) among people in our personal networks. we describe a prototype, the memorynet viewer (mnv) and present results of a user study. we conclude with future developments.
does think aloud work?: how do we know? the think aloud method is widely used in usability research to collect user's reports of the experience of interacting with a design so that usability evaluators can find the underlying usability problems. however, concerns remain about the validity and usefulness of think aloud in usability studies. in this panel we will present current studies of the think aloud method, examine and question its usage in the field, discuss the possible pitfalls that may threaten the validity of the method, and provide comments/suggestions on the application of the method. panel participants will discuss results drawn from both applied research and basic research.we believe that this panel discussion will be useful for hci designers and usability practitioners in that it will acquaint them with concerns that people have about the think aloud method and provide them with suggestions for improved use of the method. for hci or usability researchers, this panel discussion will address the importance of formally investigating currently used or newly designed usability methods.
a generic approach for augmenting tactile diagrams with spatial non-speech sounds. blind or visually impaired users typically access diagrams in the tactile medium. this paper describes touchmelody, a system designed for augmenting such existing diagrams with 3d spatial auditory information to increase their usefulness, information content and reduce tactile clutter. the motivation for this system, an overview of its development and early experiences are presented. the two major technologies used are the polhemus fastrak and the lakedsp cp4 to facilitate the creation of a directly manipulated dynamic 3d spatial soundscape.
cognitive and software solutions for computer-related anxiety. the goal of this workshop is to focus discussion on how to design inexpensive but effective techniques for the management of computer-related anxiety. these techniques may be geared either towards the design of software, or towards the design of training or stress-management techniques.
design and evaluation challenges of serious games. as the computer game industry grows, game capabilities and designs are being re-used for purposes other than entertainment. the study of 'serious games', i.e. games for education and policy making, is of growing interest in many sectors. this sig will bring together people interested in the topic area to discuss emerging opportunities and challenges. a panel discussion will cover new uses for games, ways of incorporating new measures such as physiological arousal into traditional usability testing, and ways of pursuing new goals such as peer learning with games. breakout groups will elaborate on panel topics, and also devise next steps for this interest community. a report of this sig's outcomes will be submitted to the sig chi bulletin.
genetic algorithm to generate optimized soft keyboard. in this paper, we propose a genetic algorithm formal framework to optimize character location on a soft keyboard. this method is described regardless of the language and layout used and can then easily be adapted to any language and layout. in this scope, we present a measure, based on mackenzie's model, to estimate the performances of the best characters in a given layout. we apply our method to common english language and two different layouts (hexagonal and rectangular layout) in order to compare with fitaly, opti or metropolis keyboards. in all configurations, our method has the best performance.
the chici group. this paper describes the work, the vision, and the approach of the child computer interaction (chici) group at the university of central lancashire in the uk. this group, formed four years ago, has grown to become one of the leaders in its field whilst maintaining a democratic structure, an open mind, and an invigorating message. the paper describes the group's creation, outlines its current activities, and contemplates its future.
usability in practice: formative usability evaluations - evolution and revolution. formative evaluation is a collection of "find-and-fix" usability engineering methods, focused on identifying usability problems before a product is completed. in this forum, four experienced usability professionals will address different aspects of formative evaluations:which methods are most effective,how to maximize the chances of effecting change and implementing the usability recommendations,the importance of the usability professional's relationship with the product developer, andthe importance of developing a science of user interface design, to minimize the need for iterative evaluations.
interaction in a collaborative augmented reality environment. in this paper we describe an augmented reality (ar) system which allows multiple participants to interact with two- and three-dimensional data using tangible user interfaces. interactively controllable 2d and 3d information is seamless integrated into the system.
parallel worlds: immersion in location-based experiences. this paper analyses the stages and circumstances for immersion based on quantitative and qualitative feedback from 700 people who took part in a three week long public trial of a location-based audio drama. ratings of enjoyment, immersion and how much history came alive all scored highly and people often spent up to an hour in the experience. a model of immersion as a cycle of transient states triggered by events in the overall experience is defined. this model can be used to design for immersion in future experiences.
virtual rap dancer: invitation to dance. this paper presents a virtual rap dancer that is able to dance to the beat of music coming in from music recordings, beats obtained from music, voice or other input through a microphone, motion beats detected in the video stream of a human dancer, or motions detected from a dance mat. the rap dancer's moves are generated from a lexicon that was derived manually from the analysis of the video clips of rap songs performed by various rappers. the system allows for adaptation of the moves in the lexicon on the basis of style parameters. the rap dancer invites a user to dance along with the music.
thumbsense: automatic input mode sensing for touchpad-based interactions. while manipulating the touchpad, a user's hand position must be away from the keyboard's home position. this effect hinders smooth switching between text entry and pointer manipulation, and is considered to be the one of the major drawback of the touchpad against to the trackpoint. this paper introduces thumbsense, a new input technique aims to solve this problem by automatically sensing users' input mode based on finger contact to the touchpad. a key on the keyboard, such as the f key, transparently acts both as a normal key as well as a mouse button. this technique is implemented by using the sensor feature of the touchpad, and is possible to apply most of currently available portable computers without requiring any additional hardware/sensors.
smartpad: a finger-sensing keypad for mobile interaction. this paper introduces smartpad, a new input device for mobile computers that is an enhanced physical keypad by a finger position sensor. this input device acts as a normal keypad for mobile devices, such as cellular phones, and also recognizes finger position on the keypad be before the user presses the key. this feature is used to recognize finger gesture on the keypad, and can also be used to give preview information to the user before the user actually pressing the key. this previewable function helps users to predict the effect of the action, and it is also helpful when the key definitions are frequently changed according to the context, such as in the case of universal commanders.
presenseii: bi-directional touch and pressure sensing interactions with tactile feedback. this paper introduces a new input device called "presenseii" that recognizes position, touch and pressure of a user's finger. this input device acts as a normal touchpad, but also senses pressure for additional control. tactile feedback is provided to indicate the state of the user interface to the user. by sensing the finger contact area, pressure can be treated in two ways. this combination enables various user interactions, including multiple hardware button emulation, map scrolling with continuous scale change, and list scrolling with pressure-based speed control.
sensing gamepad: electrostatic potential sensing for enhancing entertainment oriented interactions. this paper introduces a novel way to enhance input devices to sense a user's foot motion. by measuring the electrostatic potential of a user, this device can sense the user's footsteps and jumps without requiring any external sensors such as a floor mat or sensors embedded in shoes. we apply this sensing principle to the gamepad to explore a new class of game interactions that combine the player's physical motion with gamepad manipulations. we also discuss other possible in-put devices that can be enhanced by the proposed sensing architecture such as a portable music player that can sense foot motion through the headphone and musical instruments that can be affected by the players' motion.
the strategy for selecting a minute target and the minute maximum value on a pen-based computer. this study deals with the relations between target-pointing strategies and target sizes. an evaluation experiment was performed in which the experimental system changed each of five kinds of targets (1, 3, 5, 7 and 9 dots in diameter respectively, 0.36 mm per dot) and eight directions of penmovement, while using each of six kinds of strategies of approaching the target on a pen-based computer. two results were obtained: (1) the "land-on2" strategy was found to be the best strategy for selecting a minute target among the six strategies, in terms of error rates, selection time and subjective evaluation. (2) this study also clarified a boundary value of target which controlled difficulty of strategy. when a target is less than 5 dots (1.80 mm), it is necessary to pay attention to the determination of the strategy in the software design.
regressions re-visited: a new definition for the visual display paradigm. we revisit the definition of regressions in eye tracking, having found existing definitions, formulated within a reading paradigm, unsuitable for visual display assessment. the new definition is tested using eye movement data recorded during a usability evaluation of two series of graph designs. the new definition gave a stronger result in the usability assessment than was obtained using the previous measure, and gave a result consistent with other eye movement usability metrics derived for the two series of graph designs. the newly defined measure is easily computed and is sensitive enough to reveal a correlation between improved performance and a decrease in regressions.
getting a measure of satisfaction from eyetracking in practice. eyetracking is now an almost standard offering from commercial hci analysts. however, what are the best ways to exploit the strengths and minimise the weaknesses of this technique? this workshop aims to gather individuals who have an interest in using eyetracking for the evaluation and design of digital interfaces such as websites, games, itv, mobile phones and more. there are two expected outcomes from this workshop. one is to define best practice, suggest answers to continuing areas of doubt and highlight unanswered questions about eyetracking in both the scientific and commercial environment. the other is to explore how best to measure the satisfaction element of the iso 9241 definition of usability through eye movement analysis especially in the genre of display cited above.please note interactive eyetracking such as eye typing is not within the focus of this workshop.
the agentsheets behavior exchange: supporting social behavior processing. in end-user programming it is still hard to overcome the tension between usability and expressiveness. some end-user programming approaches focus on simple use but they make it hard or even impossible to write programs expressing useful functionality. other programming approaches can be very expressive by allowing the construction of arbitrary complex programs but this expressiveness comes at the price of usability. end user programming approaches that are at least reasonably usable and expressive at the same time require not merely a syntactic improvement of programming languages but a new way to conceptualize the programming process in a social context. social behavior processing describes the idea of elevating programming components to the level of easily composable and decomposable entities that can be shared through the world wide web with a community of end-users. the agentsheets behavior exchange is outlined here as a forum for end-user programmers, including middle school kids and professionals, to (a) compose behaviors in order to create interactive simcity&trade;-like simulations and games, to (b) comprehend behaviors created by other users or by themselves, and to (c) share these behaviors with other users.
tangible user interfaces for children. tangible user interfaces, which provide interactivity using real physical objects, hold enormous promise for children. exploring and manipulating physical objects is a key component of young children's learning. the educational power of digital technology for children has typically been limited by the fact that users explore and manipulate abstract two-dimensional screen-based representations, and not real physical objects. embedding interactivity into physical objects, therefore, allows the "best of both worlds" - supporting traditional exploratory play with physical objects that can be extended and enhanced by the interactive power of digital technology. participants in this sig are invited to share ideas regarding the design and development of tangible interfaces, and to bring demos or slides/videos showing work in this area. participants will review as many examples as time allows, and discuss the issues surrounding design and development of such interfaces. a primary goal of this sig is to foster the development of a community of researchers and practitioners who are focused on designing and developing tangible interfaces for children.
affective sensors, privacy, and ethical contracts. sensing affect raises critical privacy concerns, which are examined here using ethical theory, and with a study that illuminates the connection between ethical theory and privacy. we take the perspective that affect sensing systems encode a designer's ethical and moral decisions: which emotions will be recognized, who can access recognition results, and what use is made of recognized emotions. previous work on privacy has argued that users want feedback and control over such ethical choices. in response, we develop ethical contracts from the theory of contractualism, which grounds moral decisions on mutual agreement. current findings indicate that users report significantly more respect for privacy in systems with an ethical contract when compared to a control.
z-tiles: building blocks for modular, pressure-sensing floorspaces. a new interactive floorspace has been developed which uses modular odes connected together to create a pressure-sensitive area of varying size and shape, giving it the potential to be integrated into an interactive environment. the floorspace uses an array of force-sensitive resistors on each node to detect pressure, and that pressure information is output by way of a self-organised network formed by the floor nodes. this paper describes the pressure sensing and network systems, suggests potential applications of the floorspace, and introduces the further research on in-network data aggregation being carried out using the system's framework.
understanding meeting capture and access. meeting capture has been a common subject of research in the ubiquitous computing community for the past decade. however, the majority of the research has focused on technologies to support the capture but not enough on the motivation for accessing the captured record and the impact on everyday work practices based on extended authentic use of a working capture and access system. our long-term research agenda is to build capture services for distributed workgroups that provide appropriate motivation and to further understand how access of captured meetings impacts work practices. to do this, we have developed a testbed for meeting capture as part of a larger distributed work system called teamspace. we will put this system into real use in a variety of settings.
a transformational approach to multi-device interfaces. using the same application on different devices requires the user to perform a mental transformation in order to adapt his knowledge to a new platform. in this work we describe how this process can be employed in multi-device development.
a transformation strategy for multi-device menus and toolbars. the increasing variety of different devices with different screen size, interaction paradigms and application areas raises the need for new technologies of cross-device development. automatic transformation of user interfaces between devices of different screen size and interaction devices can increase the speed of multi-device software development and decrease the costs for testing and maintenance while providing inter- and intra-device consistency. therefore transformation strategies have to be developed and evaluated. in this article we introduce a classification scheme for such transformation strategies. an example transformation strategy for menus and toolbars supporting the migration between desktop pcs an palm-sized devices has been developed and evaluated.
the many faces of consistency in cross-platform design. this workshop addresses the role consistency plays in the design of applications and services that span several different computing devices. we will discuss the benefits and limitations of consistency, and methods to support the design and evaluation of consistent multi-device applications.
indexing unstructured activities with peripheral cues. a variety of ubiquitous computing systems have been built to automatically capture everyday activities in a number of domains. many capture systems record streams of information that structure and form indices into the recording, providing users easy access to portions of interest. but this is challenging in very unstructured situations or unpredictable environments. in this paper, we explore introducing structure into the activity through the use of an artificial, unrelated, peripheral stream of information. we investigate the feasibility of this idea by integrating a stream of images into an existing meeting capture system. our study suggests that this technique may be used effectively in some situations, and reveals similar methods of capturing and using indices that could be explored.
visible or invisible links? this paper reports on experimental research that compares two interfaces in software designed for foreign language reading: one with visible and one with invisible links. the links lead to dictionary definitions and translations. the study focussed on differences in consulting behaviour, learning outcomes (vocabulary and comprehension) and on a possible interaction effect of condition and task. the results indicate that the two interfaces mainly differ in the users' willingness to consult the additional information. differences in learning outcomes and a combined effect of condition and task could not be established.
interpersonal cues and consumer trust in e-commerce. e-commerce stretches interactions over space and time, and thus requires more trust than traditional shopping. current approaches to trust-building in e-commerce focus on cognitive trust. human trust decisions, however, are also based on affective reactions, which can be triggered by interpersonal cues. this research investigates the effect of visual interpersonal cues on users' trust in e-commerce. first results indicate that visual interpersonal cues in the form of photographs have an effect on users' decision-making. this effect, however, strongly depends on context variables, as well as individual differences. a further issue under investigation is the potential negative effect of interpersonal cues on task performance. thus, in a next stage, this research will combine eye-tracking with physiological measurements to investigate effects on task performance and user cost.
face it - photos don't make a web site trustworthy. use of staff photographs is frequently advocated as a means of increasing customer confidence in an e-shop. however, these claims are not conceptually or empirically grounded. in this paper we describe a qualitative study, which elicited customer reactions towards an e-commerce site that displayed staff photographs and links to richer media. the results suggest that employing social and affective cues, particularly in the form of photos, can be a risky strategy. to be effective they should be combined with functionality and targeted specifically at the user types we identified.
do people trust their eyes more than ears?: media bias in detecting cues of expertise. enabling users to identify trustworthy actors is a key design concern in online systems and expertise is a core dimension of trustworthiness. in this paper, we investigate (1) users' ability to identify expertise in advice and (2) effects of media bias in different representations. in a laboratory study, we presented 160 participants with two advisors -- one represented by text-only; the other represented by one of four alternate formats: video, audio, avatar, or photo+text. unknown to the participants, one was an expert (i.e. trained) and the other was a non-expert (i.e. untrained). we observed participants' advice seeking behavior under financial risk as an indicator of their trust in the advisor. for all rich media representations, participants were able to identify the expert, but we also found a tendency for seeking video and audio advice, irrespective of expertise. avatar advice, in contrast, was rarely sought, but -- like the other rich media representations -- was seen as more enjoyable and friendly than text-only advice. in a future step we plan to analyze our data for effects on advice uptake.
reinventing trust, collaboration and compliance in social systems. the objective of this paper is to set the research agenda for a workshop focusing on novel approaches to supporting trust, collaboration, and compliance in social systems. suggested approaches are: self-awareness, reparative and social recommender mechanisms.
designing between borders: the distributed ui design team at adobe. the user interface team at adobe has members in 8 (soon to be 9) national and international sites including germany, canada, and india. what does it mean to have a centralized ui team with so many remote members? in this paper we discuss how our locations came into being, challenges and issues encountered, and steps we've taken to build a cohesive team identity. we also discuss the vision driving plans for growing teams in india and japan.
when one isn't enough: an analysis of virtual desktop usage strategies and their implications for design. screen space is a limited resource for computer users-multiple monitors are one means of workspace expansion, and "virtual desktops" are yet another way to increase screen real-estate. we present a taxonomy of organization strategies based on our observations during a series of interviews with virtual desktop users. additionally, we explore causes of varying user preferences for physical versus virtual means of screen-space expansion. finally, we discuss the design implications of our findings.
automated message prioritization: making voicemail retrieval more efficient. navigating through new voicemall messages to find messages of interest is a time-consuming task, particularly for high-volume users. when checking messages under a time contraint (e.g., during a brief meeting break), users need to identify those messages requiring urgent action since not all messages can be processed in limited time. for these users, it would be useful if messages of greater urgency can be played first. for other users, distinguishing personal from business voicemail is a pressing need, to separate their home and business lives. we have successfully applied machine-learning techniques to lexical, acoustic, and contextual features of voicemail in order to sort messages based on urgency and on business-relevance.
release, relocate, reorient, resize: fluid techniques for document sharing on multi-user interactive tables. group work frequently involves transitions between periods of active collaboration and periods of individual activity. we aim to support this typical work practice by introducing four tabletop direct-manipulation interaction techniques that can be used to transition the status of an electronic document from private to group-accessible. after presenting our four techniques - release, relocate, reorient, and resize - we discuss the results of an empirical study that compares and evaluates these mechanisms for sharing documents in a co-located tabletop environment.
sonictexting. sonictexting is a system for inputting text -- 'texting' -- using gestures and sound. as in musical instruments and everyday mechanical objects, sound in sonictexting is synchronous and responsive to actions. sonictexting explores people's hand-ear coordination and demonstrates the use of informative digital sound. it proposes that through touch and sound, a functional activity like text entry can become an experience on the borders between performing a task, playing an instrument and playing a game.
the effect of content customization on learnability and perceived workload. one of the key e-commerce challenges is to maintain an increasing amount of information up-to-date. this is a challenging task because frequently there is a substantial amount of data being created under tight deadlines. it is important that data management tools used for these tasks are efficient and easy to use. the present study describes the effect of ui content customization on learnability and perceived workload. participants were asked to create 20 different products using four different web prototypes that varied in content density and customization capability. mean time on task over 20 trials was fit using a power function and perceived workload was collected using nasa task load index. the results obtained indicate that content customization allows users to reach peak performance faster and reduce task learning. also, content customization reduces perceived mental demand and frustration as content density increases. finally, participants performed faster and with higher satisfaction under the customization conditions.
looks good to me. our primary goal was to assess users' reactions to web sites and to better understand why they respond more favorably to some web sites than to others. in the present study, we replicated earlier research1 in which participants performed tasks on 12 different web sites and subsequently rated each of the sites along 14 dimensions. as occurred in the earlier research, reliable differences were observed in the ratings of the web sites. however, in contrast to the earlier study where organization was the primary predictor of overall ratings, attractiveness was the strongest predictor of their overall impression of the sites. it may be that the differing results were due either to different stimulus sets or to different subject populations.
voting and political information gathering on paper and online. electronic voting is slowly making its way into american politics. at the same time, more voters and potential voters are using online news and political information sources to help them make voting choices. we conducted a mock-voting study, using real candidates, issues, and campaign materials. political information was browsed either online or on paper, and participants marked electronic ballots either while they browsed or later, in a separate step. our initial data shows that voters prefer electronic browsing although they are no faster or slower with paper materials. voters felt that they understood the issues best when they voted during browsing, and they felt most confident about their decisions when they studied electronic campaign materials alongside an active electronic ballot.
using converging methods across disciplines to guide the redesign of a large, information-rich web site. this paper summarizes how differing research methodologies were sequenced during formative evaluation of a large-scale government web site in order to generate consensus for site redesign and a clear typology of users. each method was selected by an interdisciplinary research team to bring to the study a convergence of approaches across the fields of human computer interaction, information science, health communication, and social marketing. researchers can use the study framework in optimizing their own program of organizational and user research, particularly if they are designing and testing large-scale information-rich sites with varied content accessed by a diverse set of users.
nonprogrammer web application development. we propose to investigate the feasibility of nonprogrammer web application development. the main target audience for this research is webmasters without programming experience - a group likely to be interested in building web applications. we choose a subset of web applications as the target for our analysis: basic web-based data collection, storage & retrieval applications. we propose to study the mental models of our target audience, collect requirements for a sufficiently powerful end-user programming tool, evaluate new programming paradigms, and implement a proof-of-concept prototype using participatory design techniques.
the domestic economy: a broader unit of analysis for end user programming. domestic ubicomp applications often assume individual users will program and configure their technology in isolation, decoupled from complex domestic environments in which they are situated. to investigate this assumption, we conducted a two week study of vcr use by eight families. each household member old enough to write completed a diary, interviews were conducted before and after, and information on demographics and appliance ownership was collected. our key finding supports the notion of the domestic economy and the trading of programming expertise. we use the attention investment paradigm, and discuss how the model fits with multi-user programming situations. we discuss the importance of the parent v/s child roles in vcr use, as well as, the tension between direct manipulation (e.g. pressing record) and programming ahead of time. we propose that future work on end user programming must focus on the household as a domestic system rather than on the individual.
typing in thin air: the canesta projection keyboard - a new method of interaction with electronic devices. canesta keyboard is a novel interface to electronic devices that consists of a projection system and a sensor module instead of the mechanical switches of a traditional keyboard. users input text by pressing keys on a projected image of a keyboard. this paper describes the advantages and drawbacks of this interface compared to existing input methods for mobile devices in terms of data entry speed, error rate, user satisfaction and physical size as revealed through usability testing.
create: center for research and education on aging and technology enhancement. in this paper we describe the interdisciplinary and cross-university center for research and education on aging and technology enhancement (create). this center is a consortium of the university of miami (um), georgia institute of technology (gt), and florida state university (fsu). it is a multidisciplinary (psychology and engineering), collaborative center, funded by the national institutes of health (national institute on aging), dedicated to solving problems of aging and computer technology use.
finger talk: collaborative decision-making using talk and fingertip interaction around a tabletop display. we describe a study that investigated how a shared interactive tabletop (diamondtouch) can be designed to provide new opportunities for supporting collaborative decision-making. small groups of users were required to work together using the table by selecting and placing digital images into a calendar template and justifying their choices to one-to-another. a variety of novel fingertip interactions were developed to support simultaneous, shared direct manipulation at the tabletop. our findings showed that new forms of distributed interactions emerged while the groups worked together. alongside conventional methods of communication, group members talked to each other with their fingers. the role of this finger talk served a number of functions, including the support of turn-taking, the emphasis on and substitution for speech acts and the encouragement of balanced contributions from all participants. we discuss how finger talk is integral to the collaborative use of the interactive tabletop surface.
remail: a reinvented email prototype. the collaborative user experience research group has been investigating how people use email and how we might design and build a better email system. in this demonstration, we will show a prototype email client developed as part of a larger project on "reinventing email." among other new capabilities, this integrated prototype incorporates 1) novel visualizations of the documents within mail databases to aid understanding and navigation, 2) advanced text analysis of the content of email messages, and 3) several unique features for helping users manage their attention.
usability community: past, present, and future. this sig is sponsored by the chi 2006 and chi 2007 usability community chairs to collect feedback and discuss how chi can best serve the usability community, both at the annual conference and in other activities. if you're a practitioner or a researcher interested in usability, please join us and contribute your ideas!.
usability in practice: alternatives to formative evaluations-evolution and revolution. the adoption of user experience methods within companies has followed a similar evolution over the past two decades. typically organizations originally institute formative lab-based evaluations, and then add field studies and other user experience methods to their repertoire. this evolution typically occurs because the organization recognizes the need for more data on customer profiles, feature requirements, and task flows, along with the ability to iterate quickly among various design ideas and directions. these methods that fall outside of the categories of formative usability evaluations and field studies are addressed in this paper. although there are a wide variety of methods within this 'alternative' category, a few representative samples will be discussed in more detail here. in actuality, these methods are not 'alternatives,' rather, they are additions to the toolkit of user experience methods that should be used in conjunction with formative usability studies and field studies.
the rise of intrusive online advertising and the response of user experience research at yahoo! over the past five years, online advertising has shifted dramatically toward much greater levels of intrusiveness in an effort to increase advertising effectiveness. advances in user experience through good design or improvements in usability in many products have been tarnished by forms of online advertising that have become increasingly annoying to users. since advertising is often the primary source of revenue for many products, user experience design and research teams have had to accept online advertising as a "design constraint," with little influence on the advertising format selected. here, we describe the emergence of a new user experience research role and our ongoing effort at yahoo! to understand the nature and negative impacts of online advertising on user experience, with the goal of feeding this knowledge into the decision making process for ad formats, ad characteristics, and where ads are best placed within the yahoo! network.
mobile itv: new challenges for the design of pervasive multimedia systems. this sig will stimulate informal debate around the futures of interfaces for pervasive multimedia systems such as mobile and ubiquitous itv with special attention to the new contextual usage of this media in entertainment, work and government contexts.it aims to create a provocative framework to uncover future usage scenarios and generate debate about novel processes for creation, sharing, and consumption of digital content that match the nomadic lifestyles of mobile users and about related new applications and original interaction models that support social use. likewise it intends to discuss possible controversial evolutions and trends of this prospected scenario such as 'an utterly controlled society' (as in aldous huxley's book 'brave new world'), applications in nano and biotechnology, etc.
unfolding the user experience in new scenarios of pervasive interactive tv. this paper presents a research carried out at the bt it mobility research centre starting in august 2004 with the aim of uncovering the user experience in future scenarios of mobile and pervasive itv, paying special attention to the new contextual usage of this media within the entertainment, work and government environments. it uses innovative ethno-methodologies, collaborative design approaches and advanced evaluation techniques in order to unveil feasible and relevant future communications scenarios for mobile and pervasive itv, that is, the use of handhelds as interfaces to extend and enhance the tv experience outside the home boundaries.
tableau machine: an alien presence in the home. we present tableau machine, a non-human social actor for the home. the machine senses, interprets and reports abstract qualities of human activity through the language of visual art. the goal of the machine is to serve as a strange mirror of everyday life, open unusual viewpoints and generate engaging and long lasting conversations and reflections. we introduce new models for sensing, interpreting, and reporting human activity and we describe results of our formative evaluation which suggest reflection and social engagement among participants.
food information network: informed shopping for healthier living. the food information network is a system designed to help people make better choices about the food products they purchase. the system will have access to a large amount of data and will allow such activities as finding alternative food products and the products available at different grocery stores. the system has also been designed to try to encourage people to prepare their own meals by helping them spend less time shopping for healthier food and showing them that it is neither so difficult nor time-consuming to cook at home. the system also encourages users to share nutritional recipes with friends.the design process followed a scenario-based design methodology, which included field studies, writing activity scenarios, and early user testing with a paper-based prototype. a portion of the system was then implemented and additional user testing was done with the system running on a cell phone and a palm™ simulator.
a tour of teamrooms. teamrooms is a groupware environment based on the metaphor of shared virtual rooms. the system contains user-defined rooms, each with a shared whiteboard, chat tool and customizable groupware applets. the system also supports a number of features to help maintain awareness, as well as a rich persistence mechanism that can act as a group memory.
special interest group on current issues in assessing and improving information usability. the usability of information is vital to successful websites, products, and services. managers and developers often recognize the role of information or content in overall product usability, but miss opportunities to improve information usability as part of the product-development effort. this meeting is an annual forum on human factors of information design, in which we discuss issues selected by the group from the facilitators' list of topics, augmented by attendees' suggestions.
focus groups in hci: wealth of information or waste of resources? many hci professionals frown on focus groups, while some believe focus group methodology can be successfully applied to collect usability data. this panel features interaction among hci professionals with very different experiences and opinions.
current issues in assessing and improving documentation usability. user documentation is now a vital element of successful computer products. managers and developers recognize that the common model of documentation as remediation for deficient design must not persist, but they often don't know how to build documentation usability into an ongoing product-development effort. the challenges of documentation usability have grown with the proliferation of available media:&bull; traditional print-based documentation&bull; online tutorials and documentation delivered with the product&bull; online help systems&bull; documentation delivered over the www&bull; "educational" and performance support elements of the user interface: wizards, error messages, screen dialogue
current issues in assessing and improving information usability. the usability of information is vital to successful websites, products, and services. managers and developers often recognize the role of information or content in overall product usability, but miss opportunities to improve information usability as part of the product-development effort. this meeting is an annual forum on human factors of information design, in which we discuss issues selected by the group from the facilitators' list of topics, augmented by attendees' suggestions.
current issues in assessing and improving information usability. the usability of information is vital to successful websites, products, and services. managers and developers often recognize the role of information or content in overall product usability, but miss opportunities to improve information usability as part of the product-development effort. this meeting is an annual forum on human factors of information design, in which we discuss issues selected by the group from the facilitators' list of topics, augmented by attendees' suggestions.
usability in practice: user experience lifecycle - evolution and revolution. the practice of usability and user-centered design must integrate with many other activities in the product development lifecycle. this integration requires political savvy, knowledge of a wide variety of methods, flexibility in using methods, inspiration, and innovation. the speakers and their colleagues have met these requirements and describe their experience fitting various methods into design and development efforts. this forum highlights their successes and setbacks.
24/7 or bust: designing for the challenges of global ucd. the globalization of oracle's development organization, customer base, and product lines has had an ongoing impact on the evolution of the oracle ui group (oui). it has changed not only the product and user requirements to be met via the ucd process but also the nature of that process. this overview describes some of the internal and external challenges inherent to the globalization of enterprise software and how oui has attempted to address them by creating deep connections with both its user and developer communities.
evaluating globally: how to conduct international or intercultural usability research. this panel will educate the audience on the methods and tools available for conducting international or intercultural usability research. the panel will also address the challenges of conducting international or intercultural usability research and provide tips on how to overcome these challenges.
unified associative information storage and retrieval. we present a novel system for performing information management in a unified manner. users currently must manage large amounts of data which may be fragmented across file formats and applications. our system, called iolite, attempts to consolidate this information by automatically discovering associations within the data. iolite uses these associations to provide a unified interface to navigate and operate on this information space.
interactivity and conceptual learning in virtual environments for children. the topic of this doctoral research is to investigate user interaction in virtual environments (ves), focusing on the role of interactivity in learning through virtual reality (vr) technology. the intention is to examine how interaction and conceptual learning are related in the context of virtual environments developed in informal educational settings. in order to study this, a set of exploratory studies was carried out with children aged 7-12. the children were asked to complete tasks, such as the assembly of ancient columns from parts, which were designed to promote constructivist learning. their interaction in the ve was analyzed using an activity theory framework [1],[2]. the result of this analysis has informed the design of the main studies, which is currently underway.
him: a framework for haptic instant messaging. instant messaging (im) is a popular chatting platform on the internet and increasingly permeates teenage life. even intimate and emotional content is discussed. as touch is a powerful signal for emotional content, haptic signals, and especially hapticons can contribute to overcome the inevi-table loss of subtle non-verbal communication cues. audio-visual extensions of im to share emotions, in particular emoticons, have been received enthusiastically by im users. this indicates a realistic user-need for hapticons in im.the haptic instant messaging (him) framework introduced in this paper combines communication of textual messages with haptic effects and hapticons. the application is build as an open framework and supports small chatting communities to explore the design and use of hapticons and haptic io devices. researchers can use the him framework to monitor the use of haptics in communication and how haptics contribute to the fun and meaning of instant messaging.
participatory adaptation. expert users of programs that handle complicated data management problems develop methods for coping with data overload, multi-user cooperation, and real-time situations. these expert methods incorporate domain and/or user interface knowledge. if such methods were inherent in a system, then novice users could benefit from the expert's experience, the learning curve would be shortened and a more effective system would result. defining and implementing a complete set of expert methods at design time is a daunting task. collecting such information from a system's usage, after it has been deployed, should provide a more accurate database of expert methodologies, current adaptive systems attempt to capture and automate such features during run-time. however, these systems can never evolve very far beyond their original design, since the adaptations occur within the scope of that design. our method is to offer the expert's usage database as input to the designer, reintroducing the designer in the development cycle after a system has been deployed initially, so that a more effective system can be produced in the next generation.
put a grammar here: bi-directional parsing in multimodal interaction. despite over two decades of research, no dominant paradigm has yet emerged to generically represent language in multimodal interaction (mmi). a commonality amongst many divergent approaches, however, is an apparent reluctance to treat multimodal language as a unique linguistic phenomenon, which results in computational models retrofitted to older approaches, and integration engines tied to their application. in this paper we present the gs algorithm - a new grammar-based unification parser for mmi, and discuss its implications and ongoing analysis.
billow: networked hospital playspace for children. through exploring play as a therapeutic process, we have developed a system called "billow" which allows children in hospitals, who are quarantined or otherwise isolated, to play in a virtual audio-visual cloudscape using a malleable, egg-shaped input/output device. this prototype was designed in collaboration with child psychologists and art therapists who are advocates for these children in the hospital setting. it is intended to address the children's need for increased human interaction and social development, mastery and control, and comfort and security. billow addresses these needs by enabling isolated children to play together and communicate in a locally networked, audio-visual play environment.
the rotating compass: a novel interaction technique for mobile navigation. in current mobile navigation systems users receive the navigational instructions on a visual display or by descriptive audio. the mapping between the provided navigation information and the surrounding world has still to be performed by the users. in our approach that aims at public spaces, we combine a public display that shows directions with a synchronized output on a personal device. we describe a system where on the public display a compass with a rotating needle is shown. when the compass needle points in the desired direction, the mobile device of the user vibrates. this unobtrusive cue, allows the user to navigate without listening to or looking at the mobile device. in this paper we introduce the concept of synchronized information displays for navigation. we describe our prototype of such a system and report on a user study, that shows the feasibility of the approach.
ibm almaden's user sciences & experience research lab. the ibm research division is roughly 3,000 people strong, located at 8 sites worldwide. this paper outlines the history and work of the user sciences & experience research (user) lab at ibm's almaden research center in silicon valley. the user lab has long been the focus for a number of pivotal developments in input devices for ibm personal computers. more recently, the lab has been extending its research activities to include new kinds of input methods, as well as fundamental work in collaboration technologies and sensemaking.
querylines: approximate query for visual browsing. we introduce approximate query techniques for searching and analyzing two-dimensional data sets such as line or scatter plots. our techniques allow users to explore a dataset by defining querylines: soft constraints and preferences for selecting and sorting a subset of the data. by using both preferences and soft constraints for query composition, we allow greater flexibility and expressiveness than previous visual query systems. when the user over-constrains a query, for example, a system using approximate techniques can display "near misses" to enable users to quickly and continuously refine queries.
designing the world as your palette. "the world as your palette" is our ongoing effort to design and develop tools to allow artists to create visual art projects with elements (specifically, the color, texture, and moving patterns) extracted directly from their personal objects and their immediate environment. our tool called "i/o brush" looks like a regular physical paintbrush, but contains a video camera, lights, and touch sensors. outside of the drawing canvas, the brush can pick up colors, textures, and movements of a brushed surface. on the canvas, artists can draw with the special "ink" they just picked up from their immediate environment. we describe the evolution and development of our system, from kindergarten classrooms to an art museum, as well as the reactions of our users to the growing expressive capabilities of our brush, as an iterative design process.
capturing and viewing media on the treo 650 smartphone and tungsten t5 handheld. today digital photographs and videos are everywhere: on our computers, on our cell phones, on our pdas. as palmone releases new smartphones and handheld devices, we continually look for ways to make the experience of capturing, viewing, managing and sharing photos and videos easier, more enjoyable, and more integral to the overall user experience. this paper discusses the release of the latest version of the palmone media applications for the treo 650 and tungsten t5. it steps through the 9-month development process and highlights many of the 'transparent' interactions that make the software compelling and simple to use.
supporting telepresence by visual and physical cues in distributed 3d collaborative design environments. we present new interaction techniques for supporting telepresence in distributed 3d collaborative design environments. synchronized turntables enhance physicality in manipulation of virtual 3d objects and provide physical cues for awareness of others. virtual shadows, visualization of hand movements of remote partners, imply not only location and activities of others but also indicate pointing and gestures toward 3d objects. aspects of augmented reality are employed to maximize spatiality in the 3d workspace. preliminary studies show that users found the system useful with regard to intuitive manipulation and heightening telepresence by visual and physical cues conveyed via the turntables and shadows. this led to rapid and efficient remote collaboration.
ubiquitous computing design principles: supporting human-human and human-computer transactions. in this paper, we discuss the results from ethnographic and informance work related to transactions in retail settings as related to the design of interactive ubiquitous computing systems. we find that - for practical considerations of design and implementation - transactions can be represented as balanced exchanges in the context of a trust relationship. we've proposed that such exchanges become trusted - and that trust must be accommodated - through at least three characteristics of social systems as applied to transactions: accountability, real-time inspectability and the capacity to exercise recourse. in this paper, we extend further recent work on designing for accountability (eriksén, 2002). we suggest that ubiquitous computing technologies applied to transactions in general and, retail transactions more specifically, need to explicitly consider these characteristics in their design to support trusted, balanced exchanges.
introduction to design ethnography. design ethnography is a set of data collection and analysis perspectives, assumptions and skills that can be used effectively and efficiently to understand a particular environment, or domain, of people for the express purposes of designing new technology products. working from the data one forms models of the environment explicitly considering the peoples' relationship to other people, space, time, artifacts, activities and nature. the models, graphically represented, are used explicitly to derive and test product concepts.
organizational collaboration: an stc perspective. in this proposal i submit personal qualifications for participation in the chi 2005 development consortium, along with a review of some issues to be discussed and possible resolutions.
blind learners programming through audio. the development of programming skills is a motivating issue in computer science. most programming languages are focused on sighted users. this study introduces apl, audio programming language for blind learners. apl is based on audio interfaces to assist novice blind learners to develop problem solving and algorithmic thinking skills. apl was designed by and for blind learners to construct meaning by making programs. we tested apl with novice blind programmers during and after development. they tried, analyzed, and make improvements to apl. learners wrote programs to solve problems with increasingly complexity. our preliminary results evidence that audio programming languages such as apl can be constructed to fit the needs and mental models of blind learners to motivate and help them to enter to the programming world.
audiobattleship: blind learners collaboration through sound. a growing number of audio-based applications for blind learners have being produced in the last few years. many of them focus on the development of 3d audio interfaces to map the entire surrounding space. other studies center on the impact of sound interaction on cognition by evaluating the usability of these applications. no previous work has centered on using spatialized sound to develop collaborative skills in blind learners. this ongoing research study introduces audiobattleship, an interactive audio-based environment to enhance collaboration and cognition in blind learners. audiobattleship mimics the traditional game battleship for sighted people but without visual cues. a preliminary pilot study has been implemented showing that blind children collaboration can be enhanced through the interaction with spatialized sound.
supporting emotional ties among mexican elders and their families living abroad. the aging of the population is a phenomenon faced by most nations, such as mexico, where 7.5% of the population is older than 60 years, a significant proportion of whom live alone (10%). this fact is related with the ever increasing migration of one or more of their relatives, mostly to the usa. our work aims to provide a technological solution that eases the isolation of elder people living alone in mexico while their families are abroad. to envision and inform our design we interviewed independent old persons living alone. we propose an electronic family newspaper, through which elders and their families share information, personal reminiscences and cultural stories, and occasionally interact with each other. through its functionality, the electronic newspaper enables elders not only to maintain close social ties, but ameliorate cognitive decline.
designing for collective remembering. this paper outlines the rationale for the workshop topic and offers an overview of its objectives.
context-sensitive design and human-centered interactive systems. context is a critical element in forming the performance of interactive systems. as the functional diversity and range of use context of the system increase, context sensitivity becomes a critical mechanism to enhance system performance and interactive qualities. particularly in the design and management of ubiquitous computing and mobile communication environments embodying the concept of ambient intelligence, understanding diverse and changing contexts of people's life and work and incorporation of an accommodating context-sensitivity into the system need to be pursued. this sig attempts to introduce a representation framework for contextual information critical to develop a methodological foundation for user-centered design practice. first, the concept of context is discussed including questions such as what composes a context, how contexts are structured and assessed, and how they can be described in relation to interactive systems development. then, strategies and methods to incorporate context sensitivity are discussed from the perspective of system development in relation to types of system architecture that can effectively implement context-sensitivity.
rfid assistance system for faster book search in public libraries. this paper presents a comprehensive overview and study of a proposed rfid assistance system that uses existing technology and devices to enable faster book search, information overlay, and check out in a public library. the proposed system uses an interactive graphic interface contrary to the conventional alpha numeric character systems used in the dewey decimal or the library of congress system currently used in public libraries.for the user study, we set up an analog version of the proposed system to compute accessibility as well as response times. the survey also lists responses to the usability of such a system for library search and check out.
connecting with kids: so what's new? from pre-schools to high schools, at home and in museums, the educational community has embraced the use of computers as a teaching tool. yet many institutions will simply install "what everyone else is using" without questioning how technology can be best used to enhance education. for this panel, we have assembled a broad range of researchers and practitioners who are on the forefront of using computers to teach kids in novel ways. each panelist will summarize their approach with examples of projects that they believe will demonstrate "what's new". we will then have videotaped children pose their toughest educational challenges to the panelists. panelists will answer by talking about how they would meet these challenges. finally, attendees will get to vote for their favorite solution. this will expose the chi audience to a range of educational challenges, with a taste of the different ways that these problems can be solved.
design of an audience voting system for the olympic games. in this paper we describe an audience voting system which can be used for all kinds of judged sport events like diving, synchronised swimming, gymnastics, and ice-skating. the basis of the system is cameras, which are fixed to the ceiling. each camera can cover approximately 1000 spectators of the audience. the image processing software recognises the judging, displayed by boards from every individual spectator. the cost of the solution is quite low, because we need less than 20 cameras for an audience of up to 15,000 spectators and you can use them for surveillance purposes, too.
test methodologies for pedestrian navigation aids in old age. assistive technology offers great promise for improving the quality of aging, if the design of the devices is adapted to the needs of the user. in this paper we describe a test environment and first studies to evaluate mobile navigation systems in respect of the usability for elderly people.
teen use of messaging media. teenagers compromise a large proportion of our population, and their technology use is a bellwether of future trends. today's teens are coming of age with the rapid development of advanced communication and media tools. this paper describes a study exploring teen communication media usage patterns and their design implications.
tokyo youth at leisure: towards the design of new media to support leisure planning and practice. an extensive research project was performed to characterize leisure planning and practice for tokyo youth. findings will aid in the design of new media to support leisure outings.
blogging by the rest of us. weblogs (or blogs) are frequently updated webpages with posts typically in reverse-chronological order. blogging is the latest form of online communication to gain widespread popularity and it is rapidly becoming mainstream. media attention tends to focus on "heavy-hitting" blogs devoted to politics, punditry and technology, but it has recently become apparent that vast majority of blogs are written by ordinary people for much smaller audiences, and on largely personal themes. surprisingly little is known about this "blogging by the rest of us", especially from the blogger's point of view. this paper presents the preliminary results of an ethnographic study of blogging as a form of personal expression and communication. we characterize a number of blogging practices, and then consider blogging as personal journaling. we find blogging to be a surprisingly versatile medium, with uses similar to an online diary, personal chronicle or newsletter, and much more. the next few years should provide a fascinating opportunity for research and design as blogging tools improve and blog usage evolves and flourishes.
interaction design for electronic musical interfaces. in this research we want to study the interaction between musicians and the technology they use, by designing novel musical interfaces and performing a series of user tests. we propose a novel interface for building digital signal processing (dsp) algorithms and creating sound and music.
merging the benefits of paper notebooks with the power of computers in dynomite. dynomite is a portable electronic notebook that merges the benefits of paper note-taking with the organizational capabilities of a computer. dynomite incorporates four complementary features that combine to form an easy to use system for the capture and retrieval of handwritten and audio notes. first, dynomite has a paper-like user interface. second, dynomite uses ink properties and text keywords for content indexing of notes. third, dynomite's properties and keywords allow retrieval of specific ink and notes: the user sees a view of a subset of the notebook content that dynamically changes as the users add new information. finally, dynomite continuously records audio, but only permanently stores portions highlighted by the user, making it is possible to augment handwritten notes with audio on devices with limited storage.
using a gestural interface toolkit for tactile input to a dynamic virtual space. in this paper, we describe the development of a gesture interface toolkit that has been applied to an application of tactile gesture recognition within an artificial life environment. the goal is to design a gestural semantics of caress, in which qualitative attributes of gesture are expressed as a function of tactility. a touch-sensitive tablet capable of detecting multiple simultaneous contacts was used to provide a source of tactile gestures (stroking, pressing, tapping, wrapping, spreading, pinching, nudging) which were then interpreted by the software as events to be sent to the active creature in the environment. participants could observe the creature reactions within a three-dimensional immersive display system.
medium preference and medium effects in person-person communication. how does user's media preference vary with communication situation, and does media preference in a certain situation, and does media preference in a certain situation predict actual performance? preference study shows that user's choice of communication medium seems to follow a common pattern, relatively independent of the communication task at hand - video being most preferred, text chat the least. parallel effect studies of person-person communication show, however, that actual task outcome varies with the type of task performed.
utilizing mobile phones as ambient information displays. mobile phones have become a ubiquitous technology and for many people a daily companion, primarily used for communication and information access. the fact that the phone is accompanying the user makes it an interesting platform for building applications that utilize the phone as an ambient display. we explore the domain of ambient displays and persuasive technology with regard to communication. in this paper we first analyze the technical capabilities of mobile phones that can support the collection of information. then we present designs of how the screen saver on a phone can raise users' awareness of their personal communication behavior.
what makes people trust online gambling sites? a validated model of trust was used as a framework for an empirical study to identify on- and offline factors that influence gamblers' perception of an online casino's trustworthiness. the results suggest that the quality with which casino's address gamblers' trust concerns by providing appropriate content is the prime factor. however, designing for trust must be part of consistent strategy that also involves customer service usability.
eyepliances: attention-seeking devices that respond to visual attention. we present eyepliances: appliances and devices that detect and respond to human visual attention using eye contact sensors. eyepliances receive implicit input from users, in the form of eye gaze, and respond by opening communication channels. by allowing devices to recognize the attentional cues people already provide, requests for explicit input from users can be reduced. further, eye contact sensing gives devices a mechanism to determine whether a user is available for interruption, and can provide the missing environmental context to improve speech recognition.
responsive graphs: understanding engineering concepts through interactive experience. understanding scientific engineering concepts requires learners to correlate between different model representations. simple engineering models are formulated mathematically, visualized with one or more graphs, and verbally interpreted with engineering terminology. past [4] and present systems [1] allow learners to modify a limited set of model parameters but not the graph-plot itself. this paper describes a set of interactive learning models consisting of standard interactors together with novel direct-manipulation responsive graphs. by setting values with sliders and visually modifying graph-plots, users qualitatively explore and comprehend abstract engineering concepts through interactive experimentation. all model representations are continuously updated in real-time enabling users to compare and move between different model representations. these highly interactive learning experiences are the result of a collaboration between interaction designers seeking direct manipulation of graphics and engineering domain-experts.
towards a quantitative analysis of audio scrolling interfaces. we present the results of a user study inspired by previous work in document navigation comparing rate and position control for navigating an audio timeline. although interfaces for controlling playback speed (rate) are favored over playback position, we found that position control is, on average, 15-19% faster than rate control when searching for targets 90 to 100 seconds away in the audio timeline. additional studies are being planned to further characterize audio scrolling performance with position and rate controls.
a framework for building reality-based interfaces for wireless-grid applications. the pervasive adoption of wireless technologies is creating a growing demand for seamless interaction with wireless services. by sharing resources across devices such as pda's, sensors and cameras, wireless grids provide the opportunity to allow users seamless access to services via a new generation of user interfaces. these interfaces draw upon users existing skills of interaction with objects in the real physical world thus, we refer to them as reality-based interfaces. although these interfaces offer the promise of ease of use, they are currently more difficult to build than traditional ones. the aim of this research is to simplify the task of developing reality-based interfaces and adapting them to a changing landscape of resources. this goal will be accomplished by providing developers with a high level user interface description language (uidl) and a user interface management system (uims) which describes and enables to develop these interfaces given the uncertainty of the input-output devices they will employ.
utilizing mobile devices to capture case stories for knowledge management. this study examines how the increasing number of new mobile devices that enable rich in situ information capture can be utilized to improve knowledge management practices. an ethnographic study is being conducted of a heating and cooling services company focusing on the exchange of case stories. with knowledge gained from this study a prototype system is being built that allows in situ multi-media data capture, and retrieval via the internet. the proposed field study of this system will extend our understanding of how to effectively design for in situ multi-media data capture so that it is integrated in organizational processes.
cords. we present a new popup widget, called cor2ds (context-rooted rotatable draggables), designed for multi-user direct-touch tabletop environments. cor2ds are interactive callout popup objects that are visually connected (rooted) at the originating displayed object by a semi-transparent colored swath. cor2ds can be used to bring out menus, display drilled-down or off-screen ancillary data such as metadata and attributes, as well as instantiate tools. cor2ds can be freely moved, rotated, and re-oriented on a tabletop display surface by fingers, hands, pointing devices (mice) or marking devices (such as a stylus or light pen). cor2ds address five issues for interaction techniques on interactive tabletop display surfaces: occlusion, reach, context on a cluttered display, readability, and concurrent/coordinated multi-user interaction. in this paper, we present the design, interaction and implementation of cor2ds. we also discuss a set of current usage scenarios.
early research strategies in context: adobe photoshop lightroom. in january of 2006, adobe systems introduced the public beta of lightroom, a digital imaging solution designed specifically for professional photographers and serious amateurs [1]. the appeal of lightroom is that it offers a modular, task-based environment that flexibly supports a complete photography workflow. this paper describes two foundation-setting research strategies pursued during the early concept and definition phases of lightroom. it discusses why certain research strategies were undertaken by the placing the decisions to pursue these strategies within a broader context, including the stage of lightroom's development, the evolving assumptions of the lightroom team, product positioning issues, time and resource constraints, and stakeholder engagement. to emphasize the context in which specific research approaches were crafted rather than simply executed, the term research strategies is used in favor of research methods.
hunter gatherer: within-web-page collection making. hunter gatherer is a tool that lets web users carry out three main tasks: (1) collect components from within web pages; (2) represent those components in a collection; and (3) edit those collections. we report on the design and evaluation of the tool and contextualize tool use in terms of our research goals to investigate possible shifts in information interaction practices resulting from tool use.
project virgo: creation of a surrogate companion for the elderly. the voice intelligent reciprocating gemutlich orator (virgo) was developed from perceptions of companionship held by persons 65 years of age and older. the knowledge gained from ethnographic interaction with segments of the target population was applied toward the creation of a device. virgo is expected to fulfill various companionship needs derived from user-centered research, expert advice and those of the sponsor.a brief review of the data collected is provided and implications toward the operationalization of various features of companionship are described. important findings of the data include the need for activity to continue as a matter of over all health and as a management tool for recovery from a loss. the importance of continued learning and physical activity is also indicated as a means of maintaining wellbeing. a brief analysis of the findings from design testing and their implications for redesign is also described.
hunter gatherer: a collection making tool for the web. task analysis of how users collect information from within web pages indicates that while capturing information within-web-page is a common task, it is not a frequent one. tool support for this interaction is poor: users must move between browsers for copying and editors for pasting content they must also name the components captured and remember to copy and add the url from the source. these subtasks force users away from their primary focus of information gathering and into information management. hunter gatherer is a browser-based tool designed to address the specific problems of forced divided attention in information gathering smaller-than-web-page sized components.
effect of an external viewpoint on therapist performance in virtual reality exposure therapy. in virtual reality exposure therapy, therapist are usually only supplied with the same viewpoint of the virtual enviroment (ve) as the patient. this paper investigates the effect of an external viewpoint on the performance of therapists in a ve. results show that even though this second viewpoint increases the precision with which the therapist can align real and virtual objects, subjects navigate through the ve in a less efficient manner.
a collaborative foraging approach to web browsing enrichment. as the amount of web content grows and diversifies, traditional organizational structures such as keyword search engines and static directories become less useful and comprehensive, requiring more user effort to find relevant information. information foraging theory [4] and collaborative filtering [6] address this problem in different but compatible ways. this paper introduces an approach called collaborative foraging that applies the biological metaphors of information foraging to the cooperative filtering. the approach assumes that humans best pursue relevent web content according to optimal foraging behavior, collaborating with communities of like-minded foragers. this paper gives preliminary results of a limited implementation.
smmaps: scenario-based multimedia manual authoring and presentation system and its application to a disaster evacuation manual for special needs. when a disaster strikes, people must make important survival decisions. they must clearly understand the situation and decide what to do immediately. a well-designed disaster preparedness manual would facilitate making the best choices. this paper begins by specifying drawbacks with currently available manuals from the standpoint of people with disabilities or the elderly; these drawbacks include communication or physical accessibility problems and content accessibility or the person's ability to comprehend the situation. we propose a system for producing a disaster evacuation manual equipped with accessible, versatile materials to address various needs and a variety of disastrous situations. we describe its prototype implementation using the preliminary results of a field test.
agile development: opportunity or fad? the importance of integrating software engineering and hci methods has been recognised for many years. agile development is a new approach to software engineering that explicitly champions an active role for the customer. indeed, extreme programming (xp), one of the most popular agile development methods, strives to include a real user(s) in the team who is located 'on-site' with software developers.in this panel we will debate whether or not agile software development provides an opportunity to integrate hci and software engineering concerns. the panel members represent a wide cross-section of experiences in this area and will consider how agile development can help improve the current situation, consider specific example scenarios provided by the audience, and, with the audience's help, will decide whether agile development is an opportunity not to be missed, or just another fad that will pull the two communities further apart.
technology education for woman by d.i.y. technology in closing gender gap. today more than ever, the importance of technology is increasing rapidly and related job opportunities are growing in electrical engineering, computer science and other related fields. despite this trend, female employment in these fields is still low and it is hard to find renowned female scientists and programmers. in addition, most attendees at technology exhibitions and readers of technology magazines are male. why aren't women interested in computer science and electrical engineering? i believe that creating an interest in technology and science for women from a young age could help increase the number of females in technology-based fields. when a mother and daughter make electronic crafts together, the mother becomes a good role model for technology use, and can help stimulate her child's interests in science and technology. this paper explores the reasons why women are not interested in technology and how this can be overcome.
mobile search with text messages: designing the user experience for google sms. sms (short message service) is already a hugely popular communication technology for mobile phones, with users sending billions of text messages to each other every year. the goal of the google sms service is to provide this large existing base of users with access to the types of information they are most likely to need when mobile. users simply send their query as a text message and receive their results in the reply. this enables users to search for information without having to upgrade their phone or subscribe to specialized mobile data services. in this paper we describe how we worked with the google sms team on the iterative design of the service's user experience. in particular, we focus on how we attempted to overcome two major constraints: the technical limitations of the sms standard, and users' current conceptual models of both sms and google search.
user profiling. a number of global trends have a large influence on the way we use technology in our life and work, like:increasing connectivity and connected devices (any time, any place, anywhere)broadbandincreasing data storage capacity, both local and in the networksmart objects (ambient intelligence, intelligent multi-modal user interfaces)heterogeneous environmentsaccording to technology providers this means enrichment. a necessity for this promise is the adoption of products and services to the profiles of their users. a possible concern for end users is the large number and wide variety of different products and services to deal with. in this workshop we will discuss the width and depth of the topic of profiling and will try to come to requirements and recommendations from an end user perspective.
a history-centric approach for enhancing web browsing experiences. browsing web pages, which plays an important part of our daily creative knowledge work, often includes purposefully revisiting pages we have browsed before. many of the existing tools and approaches for revisitation clearly distinguish the use of history from web browsing. the approach presented in this paper blurs the distinction between browsing the web and visiting stored pages in a personal web browsing history database. the hcb (history-centric browsing) system allows a user to browse a previously visited web page stored in the history database in the same way as browsing a page on the web. the system associates pages from the database to the currently displayed page through three types of relevancies: temporal sequence, url/location-based proximity, and content similarity. the hcb-stat, hcb-vis, and hcb-tempo components use the associations to enrich the current page-viewing experience.
gummi: user interface for deformable computers. we show interaction possibilities and a graphical user interface for deformable, mobile devices. wimp (windows, icons, mouse, pointer) interfaces are not practical on mobile devices. gummi explores an alternative interaction technique based on bending of a handheld device.
project view im: a tool for juggling multiple projects and teams. previous research suggests working on multiple projects may lead to stress and misallocation of attention. a modest redesign of instant messenger (im) could help team members juggle multiple projects and teams. this paper describes the implementation of this redesign--an im plug-in called project view im (pvim). pvim uses automatic project status logging to show active project-related files and team members. in a preliminary evaluation experiment, participants working collaboratively with different partners on two projects found pvim and im to be equally usable and informative but pvim participants reported less workload stress. we discuss future work to iterate the design and measure allocation of attention and task performance.
making a difference: integrating socially relevant projects into hci teaching. enriching courses on human-computer interaction with socially-relevant projects provides a compelling opportunity for students to improve their education and make socially beneficial contributions. by having clearly defined user communities outside the classroom, students have the chance to practice their interview, observation, and usability testing skills, while developing projects that continue beyond the semester. these projects often give students life-changing exposure to genuine needs and impressive results to include in their portfolio when seeking employment. educators will present their strategies for arranging, supervising, and grading these projects. students will describe their experience and how it influenced them.
wands: tools for designing and testing distributed documents. designing documents that will be viewed from remote locations via a network requires an understanding of traditional document and interaction design issues, plus an understanding of how network delays will impact document delivery. unfortunately, being aware of networking issues is not always sufficient since designers usually have no way of viewing their documents as if those documents were being delivered to a remote site. this paper describes a set of tools that allow designers to view documents stored locally while experiencing response time delays as if the documents were delivered from a different location on the network. by using measured network latencies to drive an instrumented world-wide web server, we allow designers to view the documents they create from the perspective of someone sitting down the hall, across the country, or across an ocean.
chi@20: fighting our way from marginality to power. the special interest group on computer human interaction (sigchi) has had a successful history of 20 years of growth in its numbers and influence. to help guide the continued evolution of the academic discipline and professional community, we invite several senior members to offer their visions for what the field of chi actually accomplished over the past several decades, and what do we still need to accomplish? what do we need to do differently/ better/smarter? what haven't we tried because the technology, the money or the will wasn't there in the past, but perhaps is now.the chi field is more than just technology. we understand that our work can have a profound effect on individuals, families, neighborhoods, corporations, and countries. we know that we can influence education, commerce, healthcare, and government. how can we contribute to bridging the digital divides in developed and developing countries? what agendas can we offer for the academic, research, industrial, and civic spheres for the next 20 years? how can we be more ambitious? how can we truly serve human needs.
internet delay effects: how users perceive quality, organization, and ease of use of information. in this paper we report the results of an investigation designed to determine the effects of internet delays on users perceptions of ease of locating information, organization of information, quality of information, and navigation problems. the results demonstrated user sensitivity to delays. as expected, for text-and-graphics documents, shorter delays provoked more favorable responses. however, for text-only documents, the shorter the delay, the less favorably a document was viewed. the results indicated that users may prefer multi-media web sites but are unwilling to tolerate the substantial network delays often associated with delivering graphics, video, animation, and audio.
project massive: a study of online gaming communities. massively multiplayer online games (mmogs) continue to be a popular and lucrative sector of the gaming market. project massive was created to assess mmog players' social experiences both inside and outside of their gaming environments and the impact of these activities on their everyday lives. the focus of project massive has been on the persistent player groups or "guilds" that form in mmogs. the survey has been completed online by 1836 players, who reported on their play patterns, commitment to their player organizations, and personality traits like sociability, extraversion and depression. here we report our cross-sectional findings and describe our future longitudinal work as we track players and their guilds across the evolving landscape of the mmog product space.
keywords for a universal speech interface. in this paper, we describe an internet survey conducted to help choose keywords for a universal speech interface. we present the background of and motivation for this study, and discuss its results and implications for our project.
simulator sickness and presence in a high field-of-view virtual environment. this paper describes a study that investigated the effect of field-of-view, display type, and user role on the experience of simulator sickness and presence in users of a virtual environment. though it interacted with the other experimental factors, field-of-view was found to be the major determinant of both simulator sickness and presence.
paper prototyping - what is it good for?: a comparison of paper- and computer-based low-fidelity prototyping. this study investigated the differences between computer-based and paper-based low-fidelity prototypes. it researched whether subjects confronted with these two kinds of prototypes differ in their willingness to criticize a system and to give suggestions for its improvement. the chosen approach was an empirical study including test sessions using both kinds of prototypes. quantitative and qualitative methods were applied to measure and to explain possible differences.
usability of interaction patterns. interaction patterns are becoming an important method for bridging the gap between analysis and design in user-centered design. recent studies, however, have indicated problems in their usability. our overall research goal is to improve the usability of interaction patterns. in the first part of the research -- discussed in this paper -- we have empirically evaluated the usability of interaction patterns and outline proposals for improvements.
a new playground experience: going digital? we explore how an interactive pathway impacts children's play patterns in outdoor playgrounds. the paper describes our experience designing and testing the prototype at various stages of development with twenty children age three to five enrolled in a preschool childcare center. we provide examples of the children's diverse play patterns and conclude with initial reflections on the design of responsive playground elements.
chameleon tables: using context information in everyday objects. the chameleon table project created a set of hexagonal tables. they are modular and are able to snap together. the design portrays some goals that can be achieved by having a table that is aware of changes in its surroundings and includes this as part of its technology. by creating this infastructure, we have been able to make several scenarios including musical instruments, sending messages between tables, and menus that change with apparent use in a food scenario. this paper also shows the use of a network for broadcasting context information.
e-windshield: a study of using. the e-windshield is a study in augmenting information with external knowledge as well as automobile relevant information. a prototype projection windshield is used to demonstrate 4 scenarios for using imagery on automobile windshields. scenarios are subdivided into two conditions: driving and non-driving. in the first condition it demonstrates the use of annotation to draw drivers attention to objects. in the second condition the system presents an interface the size of the windshield providing a multimedia experience to the user. when a car is not occupied, it can be used as a public information board, showing information concerning time, things that are around it or simply presenting advertising. this display can also be used in collaboration with other displays to form a large screen array.
voting: user experience, technology and practice. this panel brings together usability and voting experts to discuss voting user experience in american governmental elections. technological improvements and voting debacles have made this a special time for improving voting user experience. can technologists improve the confidence citizens have in the voting system? what are the roles of teaching materials, registration processes, ballot design, polling place practices, equipment manufacturer relationships, and other human computer interaction processes in elections? voting officials and politicians are eager for improvements in voting.this panel includes speakers from government and the chi community to present legislative perspective, usability evaluation approach, administrators' view and behavioral science's suggestions for voting interface evaluation, design and deployment.
peek-a-drawer: communication by furniture. peek-a-drawer is a new communication device that uses furniture to support lightweight communication between people. it provides virtual shared drawers that connect family members who are located at a distance. when a user puts something in the upper drawer and closes it, a photograph is taken automatically and the image appears in the lower drawer at a distant place. the operation is as simple as using a drawer, allowing even children to communicate with their grandparents. as the camera only takes pictures of objects inside the drawer, privacy is assured.
finding objects in "strata drawer". looking for a document in a stack of papers is a difficult job. if the "strata" of the drawer contents is known, then locating will be much easier. strata drawer is a camera-enhanced cabinet used for storage. this cabinet has a single, deep drawer equipped with a camera, a depth-sensor and a computer. when a user places an object in the drawer and closes it, a photograph is automatically taken, and the height of the contents is measured by a laser beam. a user can browse pictures of strata in the drawer's contents, with timestamps and height information.
mobile interaction using paperweight metaphor. conventional scrolling methods for small sized display in pdas or mobile phones are difficult to use when frequent switching of scrolling and editing operations are required, for example, browsing and operating large sized www pages.in this paper, we have proposed a new user-interface method to provide seamless switching of scrolling / zooming mode and editing mode, based on a "paperweight metaphor". a sheet of paper that has been placed on a slippery table is difficult to draw on. therefore, in order to write or draw something on the sheet of paper, a person must secure the paper with his/her palm to avoid the paper from moving. this will be a good metaphor to design switching operation of scroll and editing modes.we have made a prototype system by placing a touch sensor under a pda screen where user's palm will be hit. we also have developed an application program to switch scrolling / editing mode by the sensor output and assessed our method.
the whereabouts clock: early testing of a situated awareness device. we describe the initial deployment of a prototype device to support awareness of people's location and activities in an office environment. this is a first step toward the design and testing of a related device for the home. findings from this workplace trial show its value in helping people have a virtual presence, in locating people, and in fostering a sense of group belonging. however, the results also suggest how the design could be made more flexible and expressive which we will explore in the upcoming home trial.
opportunities and barriers in implementing e-services for citizens in poland. this paper presents current issues relevant to building information society in poland in relevance to complying european union regulations on public information access.
hci and the arts: a conflicted convergence? a potential convergence is arising between hci and the interactive arts. the goal of this sig is to develop a conversation on the potential role of the arts in the hci community, based on the soon-to-be released us national academies national computer science and telecommunications board's report on information technology (it) and creative practices [2]. what kinds of activities are taking place that combine serious creative artwork with hci issues? what kinds of topics should hci study to support interactive art? how could hci benefit from a deep engagement with the arts, and what would such an engagement likely entail? what kinds of challenges might engagement between hci and the arts present for the self-conception of each field? what institutions are available or should be created for interdisciplinary work between the arts and hci? in what forums can this work be exchanged and discussed.
transferring usability engineering to software houses: some practical experiences. this paper describes market-related and social background of existing limitations in transferring usability engineering methods into software companies in poland. typical approaches of software vendors, developers, managers and users are shortly presented as possible reasons of low usability of many local software products. providing information, guidelines and usability services are discussed as means for developing usability consciousness among all stakeholders involved in developing software for management support.
reflective hci: articulating an agenda for critical practice. reflective hci is a style of hci research that integrates technical practice with ongoing critical reflection. in the last thirty years, hci researchers and practitioners have expanded their interests from aspects of cognitive ergonomics concerned with individuals using desktop computers at work to include concern for social and communal aspects of technology use and for affective and aesthetic aspects of design. this has been accompanied by the appropriation of a variety of disciplinary practices, concepts, and methodologies by hci. in terms of the development and coherence of the discipline, it is timely to take a critical look at the assumptions, values, and traditions of each of these positions, their implications for hci research agendas, and to try to understand the historical, cultural, and political emergence of hci as a discipline itself. the main aim of this workshop will be to develop a systematic research agenda for reflective hci.
changes in online health usage over the last 5 years. this paper describes changes in the use of e-health services over a 5-year period. it compares findings from two large-scale questionnaire studies undertaken in 2000 and 2005. key changes in usage and trust practices are noted with patients "acting as scientists" using web sites to test out theories regarding their health. future analyses regarding trust and identity markers are discussed.
promoting a healthy lifestyle through a virtual specialist solution. as reported by the world health organization (who), malnutrition is a health problem faced by many nations around the world. in mexico around 50% of adult population is obese; this in turn situates people on risk of contracting other diseases such as diabetes, and hypertension. to address this problem, one of the main institutes of health in mexico has implemented a program for preventing diseases related to bad feeding and physical activity habits. in our aim to provide a technological solution to help people with such problems, we conducted a field study around this program to envision and inform our design. we propose a virtual specialist (vs) that stays with the patient and advice him at all times on issues related to keeping diet and exercise programs. we argue that patients that use this solution would feel more motivated to keep working on their programs, since they get a feeling of being personally attended.
take it to the next stage: the roles of role playing in the design process. using role play at every stage of the design process has been a vital tool for ideo in working with clients and users. with the dual properties of bringing participants into the moment and making shared activities physical rather than just mental, role playing techniques make the process more experiential and creatively generative. role playing is complimentary to traditional design techniques providing additional team dynamics and insights that bring the process and designs to another level. this paper describes how we have used role-playing in our design process and how it can be integrated into any hci project.
ucd of financial services at the smart internet technology centre. in this paper i describe the experience of contributing sociological and anthropological perspectives to the user-centered design of financial services in the smart internet technology cooperative research centre in australia.
persona development for information-rich domains. designing information architecture for complex websites requires understanding user information needs and mental models in that domain. personas, or user archetypes, created for such domains should also reflect types of information needs, and usage of information set. we have created a statistical technique to identify important underlying groupings of information needs. in a preliminary study, we show how designers can use this information in conjunction with data from interviews and observations to generate and refine personas.
the role of transparency in recommender systems. recommender systems act as a personalized decision guides, aiding users in decisions on matters related to personal taste. most previous research on recommender systems has focused on the statistical accuracy of the algorithms driving the systems, with little emphasis on interface issues and the user's perspective. the goal of this research was to examine the role of transprency (user understanding of why a particular recommendation was made) in recommender systems. to explore this issue, we conducted a user study of five music recommender systems. preliminary results indicate that users like and feel more confident about recommendations that they perceive as transparent.
auramirror: artistically visualizing attention. we present auramirror, a system that visualizes virtual windows of attention: the commodity of visual attention people exchange during interactions in small groups. auramirror acts as a dynamic 'painting' that passively gathers and displays attentional data by superimposing auras over each viewer's head in a real time video mirror. this permits users to see how they distribute their attention in group interactions, and the effect of interruption on this process. finally, we describe how auramirror can be extended to model attention among both participants and ubiquitous devices.
interaction design for literature-based discovery. rapid growth in the scientific literature makes it increasingly difficult for scientists to keep abreast of findings outside their own narrowing fields of expertise. to help biomedical researchers address this problem, litlinker uses literature-based discovery to find new connections between biomedical terms that could lead to new directions in research. in this paper, we discuss the design of an interface that supports researchers' interactive exploration of the identified connections. because the interface suggests many possible new connections, researchers must be able to understand how connections are established and to evaluate those connections based on their own expertise. based on the results of our user study, we have further tailored the interface to support the work processes of biomedical researchers. litlinker's interaction design promotes user-comprehension of the complex relationships among connected terms and allows for dialogue with researchers on the use of literature in scientific discovery.
hci in the czech republic. the paper describes the current situation and historical development in the hci field in the czech republic. an outline of the most important features in this area is given. the reader can get ideas about the current state of art especially in research and education. a description of the situation in some specific applications is also given. in summary, the reader can find a short evaluation given together with some proposals on how to improve the current situation in the hci field in this particular country.
the djammer: "air-scratching" and freeing the dj to join the party. traditional disc jockeys use vinyl records and turntables to manipulate music in real time. we describe the development of the djammer, a new device that enables its users to manipulate digital music using a portable handheld sensor. in addition to the standard actions offered by most portable digital music players, the djammer provides its users with control capabilities previously offered only through the use of turntables. using the djammer, djs can "air-scratch" digital music via simple hand motions similar to those used when scratching vinyl records, fade the music, and jump to a predefined position within the song using a wireless sensor designed to fit in the dj's hand. the preliminary study of the device by experienced djs suggests that it can play a role as an accessory to their professional equipment, freeing them to step away from their consoles during the performance and uncovering opportunities for creativity and personalization.
design of spatially aware graspable displays. we propose spatially aware portable displays which use movement in real physical space to control navigation in the digital information space within. this paper describes two interface design studies which use physical models, such as friction and gravity, in relating the movement of the display to the movement of information on the display surface. in combining input and output aspects of the interface into a single object, we can improve control and provide a meaningful relationship between the interface and the body of the user.
web accessibility for people with cognitive disabilities. this pilot study investigated individuals with developmental cognitive disabilities (dcd) navigating w3c accessibility-compliant web sites and the impact of four cognitive determinants: situation awareness, spatial awareness, task-set switching, and anticipated system response. participants were placed into one of two search conditions and were asked to complete information-finding tasks. the usability evaluation demonstrated that the majority of users with dcd were able to access the web but they were unable to successfully use the w3c accessibility-compliant web sites/. the use of navigation aids was examined, different web navigation problems were identified as well as user satisfaction and perceived usability. it is clear from this study that current web accessibility guidelines do not sufficiently address the needs of people with cognitive disabilities. additional research is needed to understand how cognitive disabilities affect using web-based media.
creating a system to share user experience best practices at ebay. increasingly, organizations are looking for ways to use technology to document and share information in order to increase effectiveness and foster a sense of community [1, 3]. as one example of a "community of practice" [4, 10], the ebay user experience & design group recently created a knowledge management system known as the playbook to enable the ebay design community to share design best practices and other information. this paper describes the considerations that went into creating the playbook and how the working team enabled the rest of the ebay design community throughout the world to contribute their best practices. we also discuss how the group as a whole has benefited from this system as well as lessons learned during this process which may help other design communities outside of ebay.
java-based user interface development. this tutorial provide attendees with an understanding of the possibilities provided by the world wide web for application development and a more detailed understanding of the issues involved in developing user interfaces for the web in java.
art and design student demos. for the past five years, students from the computer related design program at the royal college of art have demonstrated their work informally to an ever growing chi audience. however, because of this informality many people have not been able to see the work properly and have suggested that it should have a more convenient and prominent setting.
overhear: augmenting attention in remote social gatherings through computer-mediated hearing. one of the problems with mediated communication systems is that they limit the user's ability to listen to informal conversations of others within a remote space. in what is known as the cocktail party phenomenon, participants in noisy face-to-face conversations are able to focus their attention on a single individual, typically the person they look at. media spaces do not support the cues necessary to establish this attentive mechanism. we addressed this issue in our design of overhear, a media space that augments the user's attention in remote social gatherings through computer mediated hearing. overhear uses an eye tracker embedded in the webcam display to direct the focal point of a robotic shotgun microphone mounted in the remote space. this directional microphone is automatically pointed towards the currently observed individual, allowing the user to overhear this person's conversations.
paperspace: a system for managing digital and paper documents. here we present paperspace a computer vision based document management system that allows users to combine paper and digital documents. using paperspace users can locate paper copies of printed digital documents, retrieve digital versions of paper documents and fluidly move between digital and paper documents. the system works by tracking 2d identity and operation codes printed in the margins of each page of the document. users can activate commands by selecting the command from the command bar at the bottom of each document. through an informal evaluation we found that all users felt our system would be valuable in helping them organize their cluttered desk and manage digital and paper documents better.
curve dial: eyes-free parameter entry for guis. in this demonstration, we introduce "curve dial" a technique designed to extend gesture-based interactions like flowmenus with eyes-free parameter entry. flowmenus, let users enter numerical parameters with "dialing" strokes surrounding the center of a radial menu. this centering requires users to keep their eyes on the menu in order to align the pen with its center before initiating a gesture. curve dial instead tracks the curvature of the path created by the pen: since curvature is location-independent, curvature dialging does not require users to keep track of the menu center and is therefore eyes-free. we demonstrate curvature dial with the example of a simple application that allows users to scroll through a document eyes-free.
the rise platform: supporting social interaction for on-line education. we present rise (real-time interactive social environment), a platform supporting data sharing and high quality audio conferencing under control of a word-wide web (www) user interface and making extensive use of a database to track and support users. we report the results of our initial educational trial and discuss some more generic uses for the platform.
improviz: visual explorations of jazz improvisations. improviz is a visualization technique for diagramming music that brings to light the signature patterns of a jazz musician's improvisational style. improviz consists of two parts: (1) melodic landscapes show the general contours of musical phrasing; and (2) harmonic palettes represent the musician's tendency to use a particular combination of notes in a given part of the song. viewing the jazz standard all blues through the lens of improviz illustrates the contrasting melodic and harmonic styles of three musicians. this analysis uncovers some surprises, such as how miles davis played musical ideas that contradicted his own composition. improviz offers jazz students a new way to study jazz theory and can also serve as a real-time improvisational aid, allowing a student to borrow the harmonic vocabulary of jazz masters.
consultants' forum: successful adaptation during tough economic times. this sig focuses on the challenges specific to hci consultants, whether independent or those working in larger consultancies. those considering an hci consulting career are also welcome. there will be four main discussion topics: marketing, collaboration/partnerships, consultants' knowledge base/faq, and the future of hci consulting.
icap: an informal tool for interactive prototyping of context-aware applications. icap is a system that assists users in prototyping context-aware applications. icap supports sketching for creating input and output devices, and using these devices to design interaction rules, which can be prototyped in a simulated or real context-aware environment. we were motivated to build our system by the lack of tools currently available for developing rich sensor-based applications. we iterated on the design of our system using paper prototypes and obtained feedback from fellow researchers, to develop a robust system for prototyping context-aware applications.
videotable: a tangible interface for collaborative exploration of video material during design sessions. in this paper our videotable and videocards. the videotable is an augmented meeting table enabling collaborative exploration of video material through a multi-user tangible interface. the videocards are paper card representations of video snippets. playback of video is initiated by a pushbutton permanently attached to a videocard. videocards can be manipulated alongside other physical design artifacts present on the videotable. preliminary observations of use indicate that the physical ebmodiment of digital video provided by our videocards enables the seamless mix of video with other physical design artifacts that we are aiming for. our implementation is based on modified passive radio frequency identificaton (rfid) tags.
emotional expressiveness in visual-sonic integration: a framework for multimedia design. a review of studies from psychology, music and cognitive science suggests that emotional expressiveness from the perception of visual and sonic information is comprised of two dimensions - valence and activation. these two dimensions can be used as a framework to guide design for emotional expressiveness in multimedia. this paper discusses the formation of this theoretically derived framework.
disneyworld.com redesign. disneyworld.com has recently been redesigned from the ground up. this paper discusses the challenges facing the design team given the enormous and unique physical aspects of the property, a very challenging business climate for the travel industry in the post-911 world, and the need to uphold the magical imperative of the world's pre-eminent entertainment brand.our solution needed to address two very specific and disparate groups of users: "intenders" and "repeaters". it needed to enfranchise new back-end systems and commerce processes. and it needed to tie into walt disney world's® overarching crm initiative.the design solution is a holistic and scalable experience, allowing guests to navigate via geographic and/or experience-based facets, incorporating a vast array of multimedia assets. although the site has only been live for a little over a month, the early results are overwhelmingly positive.
recent developments in text-entry error rate measurement. previously, we defined robust and easy-to-calculate error metrics for text entry research. herein, we announce a software implementation of this error analysis technique. we build on previous work, by introducing two new metrics, and we extend error rate analyses to high key-stroke-per-character entry techniques, such as multi-tap.
multimodal spatial reference in mediated environments: users' preferences and the pragmatics of pointing and talking. this paper describes the current results and future developments of a project on multimodal spatial reference in mediated environments. the database consists of video-recorded sessions, with 120 participants in three experimental designs, contrasting types of pointing (no pointing, natural pointing, mediated pointing), types of co-presence (mediated versus natural) and type of task (locative versus descriptive). the project investigates which verbal and non-verbal resources participants prefer to use in the different conditions, and which integration strategies they adopt. the goal, relevant to people interested in communication with/through technologies, or in multimodal communication in general, is to clarify the pragmatic meaning of the different resources. so far, the analysis of the data has focused on the verbal resources; further analysis will focus on the pointing strategies, and their integration with verbal spatial reference.
minnesang: speak medieval german. we present a prototype of the minnesang exhibit that translates visitors' utterances into medieval german in their own voice. this lets visitors experience how they would have spoken in medieval times. the project illustrates new variants of voice conversion and their use in human-computer interaction.
the experience engineering framework applied in two contexts. analysis of existing user-centered design methods revealed an underlying common framework consisting of three components and three principles. the components are (1) a multi-faceted view of experience, (2) a set of goal driven phases, and (3) a repository of best practices for navigating those phases. the principles are (1) team-based design, (2) facilitation of divergence and then convergence of ideasce, and (3) alignment of teams and phases. we call this framework the experience engineering framework (eef) and use it to construct a ucd process tailored for each project or design problem by using the right components and principles for that project. this abstract briefly presents two applications of the eef in two very different contexts.
metacrystal: visual interface for meta searching. metacrystal visualizes the degree of overlap between the top results returned by different search engines. linked overview tools support rapid exploration, facilitate advanced filtering operations and guide users toward relevant information. the direct manipulation interface enables users to iteratively compose and edit meta searches. metacrystal addresses the problem of the effective fusion of different search engine results by helping users control and gain insight into how to combine and filter them.
measuring website usability. web design is still primarily an artistic endeavor. however, we are beginning to see empirical research results that tell us what pitfalls to avoid in order to create successful websites.
product usability: survival techniques. product developers are typically faced with small budgets, tight schedules, and over-committed resources. to deliver high-quality products under these constraints, developers need an understanding of basic design principles, techniques that allow them to work effectively with materials on hand, and a development process that is built around the use of such techniques. this workshop explains how low-fidelity prototyping and usability testing can be used in a process of iterative refinement in order to develop more usable products.
tangible newspaper for the visually impaired users. this paper outlines a novel interaction technique allowing the visually impaired users to examine the layout of complex paper documents (e.g. a newspaper page). the document is placed on a desk in the view of a camera placed above it. the tip of user's index finger is tracked by means of algorithms of computer vision. as the user moves the finger over the document, the layout of its logical units (articles) is revealed by means of a simple sonification of their boundaries and the speech synthesis. in the paper, implementation of the test application is described and evaluated. the main advantage of our system is the direct mapping of the kinaesthetic experience to the layout of the physical document, enabling the user to employ any strategy to traverse the document. the prototype has been implemented using the artoolkit library.
the effect of tangible interfaces on children's collaborative behaviour. the physical nature of the classroom means that children are continually divided into small groups. the present study examined collaboration on a story creation task using technologies believed to encourage and support collaborative behaviour. four children used tangible technologies over three sessions. the technology consisted of a large visual display in which they could input content (using personal digital assistants (pda) and a scanner), record sounds (using rf-id tags) and navigate around the environment using an arrangement of sensors called 'the magic carpet'. the children could then retell their story using bar-coded images and sounds. the three sessions were video recorded and analysed. results indicate the importance of immediate feedback and visibility of action for effective collaboration to take place.
visual interaction design special interest area meeting. the visual interaction design special interest area (vidsia) meeting provides a place for visual design practitioners, educators, and supporters to gather informally and share ideas and work. vidsia was formed at chi 92 and has met at chi since. we created visual-l, a popular electronic distibution list for those interested in visual aspects of interaction design, and the vidsia column of the sigchi bulletin.
use of mobile appointment scheduling devices. one hundred thirty-eight subjects participated in a study on mobile appointment scheduling. subjects completed a questionnaire on their primary method of managing appointments when away from their desks. immediately afterwards, subjects completed a session of scheduling four appointments with the interviewer. the most common scheduling systems, in order of popularity, were paper-based day planners, memory, scrap paper, and pda's. however, 43% of the claimed pda users and 68% of day planner users switched to another, more readily accessible method when scheduling an appointment. interviews revealed a practice of using memory or scrap paper to "buffer" appointments for later entry into the pda or planner.
supporting student-built algorithm animation as a pedagogical tool. this demonstration describes a new approach to algorithm animation, one in which the students construct the animations. we introduce the samba system that facilitates this process and describe how it has been used an undergraduate algorithms courses as a teaching aid. having students build the animations, that is, construct the mapping from concepts to images, appears to enable true understanding of the algorithm under study.
understanding and enhancing call centre computer-. there are many interactions that take place at a call centre; between the customer and agent, the agent and computer, and indirectly between the customer and computer. this paper proposes areas of research, eg auditory feedback and human-human communication, which could provide insight and possible improvement to the interaction. the paper also describes studies that have been carried out, as well as studies that are being planned.
the use of auditory feecback in call centre chhi. initial investigations have been carried out to evaluate issues of the computer-human-human interaction (chhi) commonly found in call centre scenarios. these investigations suggest some benefits in the use of auditory icons and earcons.
effective product selection in electronic catalogs. product catalogs are crucial for electronic commerce on the internet, but it is still a challenging task for casual users to perform effective product selection. recently, a promising technique for product selection has been proposed: incremental restriction on interactive tables. it allows customers to build complex queries with a few mouse clicks, but still to browse the available products at any stage. this paper describes effective and ineffective strategies of users working with this technique. these strategies were identified in a study with casual users.
a picture says more than a thousand words: photographs as trust builders in e-commerce websites. virtual re-embedding, i.e., adding social cues to a website, has been suggested as a possible strategy to increase consumer trust in online-vendors. numerous online retailers meanwhile incorporate this strategy, for example by adding photographs and names of customer service agents or by creating chat and callback opportunities. yet, little is is known about the effectiveness of virtual re-embedding. the present study examined the effectiveness of a comparably simple strategy, the inclusion of photograph in an e-bank's website and found a significant positive effect on perceived trustworthiness of the examined website. it is suggested that virtual re-embedding is an effective way to increase customer trust and that it does not even have to be costly to implement.
the toilet entertainment system. a toilet is not only a place where people answer calls of nature. it is also a place for contemplation and reflection - and a place where people read information. but bringing things to read into a public toilet is not always socially accepted and it might be embarrassing to be discovered. we have chosen to address this problem by printing information such as news directly onto the disposable toilet paper.the project described here is an attempt to question the nat-uralness of having ubiquitous computers, cause reflections concerning what kind of problems ubiquitous computing really are solving and to indicate that there might be places where computation is not desirable.
the living memory box: function, form and user centered design. the living memory box project examines how to research and design user-centered system to support the collection, archiving and sharing of moments from a child's life. this research has provided us with details of key features to enhance our user-centered design and encompass all aspects of the system. we plan to use these findings to influence the development of ubiquitous capture and access methods. it is our contention that this method of desing can yield a strong foundation for the development of user-centered design throughout all aspects of the system.
single display groupware. face-to-face collaboration of small groups is one of the most common forms of group work, yet group-aware computer support for this type of collaboration is limited. my research examines the effectiveness of single display groupware (sdg), computer systems that support face-to-face collaboration around a single computer display. together with the help of a group of elementary school children, i will design and build a prototype sdg system called sushi that is an authoring tool for interactive multimedia stories.
transition relevance place: a proposal for adaptive user interface in natural language dialog management systems. in this paper, we describe how users transfer language behavior commonly associated with directed dialog to natural language systems: they respond to the initial prompt with a single word (holophrase) instead of the naturally occurring unit of conversation (a sentence). we evaluate two solutions to this problem and offer a conversational turn-taking method together with a discourse clause tutorial as the effective way to get repeat callers to adapt to the natural language dialog style.
head orientation and gaze direction in meetings. detecting who is looking at whom during multiparty interaction is useful for various tasks such as meeting analysis. there are two contributing factors in the formation of where a person is looking at : head orientation and eye orientation. in this poster, we present an experiment aimed at evaluating the potential of head orientation estimation in detecting who is looking at whom, because head orientation can be estimated accurately and robustly with non-intrusive methods while eye orientation can not. experimental results show that head orientation contributes 68.9% on average to the overall gaze direction, and focus of attention estimation based on head orientation alone can get an average accuracy of 88.7% in a meeting application scenario with four participants. we conclude that head orientation is a good indicator of focus of attention in human computer interaction applications.
designing a mobile terminal for horse aficionados. in this paper we describe the development and use of a novel, practical approach to the design of a mobile multimedia terminal for a virtual community. the specific design goal was a dedicated mobile terminal concept for horse aficionados who belong to the virtual stables community. we had to use a creative approach since the design was for a device of non-existent type, and to be used in a virtual environment by an atypical and challenging user segment. using this approach we were able to get valuable contribution from the potential users to the design of the new terminal.
a commonsense approach to predictive text entry. people cannot type as fast as they think, especially when faced with the constraints of mobile devices. there have been numerous approaches to solving this problem, including research in augmented input devices and predictive typing aids. we propose an alternative approach to predictive text entry based on commonsense reasoning. using omcsnet, a large-scale semantic network that aggregates and normalizes the contributions made to open mind common sense (omcs), our system is able to show significant success in predicting words based on their first few letters. we evaluate this commonsense approach against traditional statistical methods, demonstrating comparable performance, and suggest that combining commonsense and statistical approaches could achieve superior performance. mobile device implementations of the commonsense predictive typing aid demonstrate that such a system could be applied to just about any computing environment.
shrimp views: an interactive environment for information visualization and navigation. the shrimp (simple hierarchical multi-perspective) visualization technique was designed to enhance how people browse and explore complex information spaces. shrimp uses a nested graph view to present information that is hierarchically structured. it introduces the concept of nested interchangeable views to allow a user to explore multiple perspectives of information at different levels of abstraction. shrimp combines a hypertext following metaphor with animated panning and zooming motions over the nested graph to provide continuous orientation and contextual cues for the user. in this demo, we show how these ideas are proving useful in the areas of software visualization, knowledge management and flow diagram visualization.
waypointing and social tagging to support program navigation. as the "software space" of source code, documentation, models, and other programming artifacts continue to grow in size and complexity, programmers face the challenge of navigating this space, as well as documenting and sharing their journeys for other developers and future successors. current navigational structures are either closely tied to the semantics of the software or are constructed in a constrained top-down fashion to match the architecture or requirements of the system. in this paper, we introduce the notion of combining waypoints from geographical positioning and social tagging from shared bookmark systems to allow programmers to create shared, tagged points in software space. we report preliminary progress on our prototype (tagsea), and discuss our future plans.
roomware: the second generation. in this paper, we describe our 'formal demonstration presentation' and provide background information on the video published in the video proceedings. the presentation provides an account of the development of the second generation of roomware&copy; components based on our experiences with the first generation. the redesign, resp. new design and implementation resulted in a comprehensive environment consisting of several different roomware components and software facilitating new forms of human computer interaction and cooperation. we present the second generation consisting of: dynawall, interactable, commchairs, connectable, and the passage mechanism, together with the corresponding software beach, palmbeach, and magnets.
a prototype design tool for participants in graphical multiuser environments. users of this software construction kit can design layouts for virtual spaces. the elements of the software kit are based on kevin lynch's elements of the city image: districts, paths, edges, nodes, and landmarks (lynch, 1960; banerjee & southworth, 1990).
kana no senshi (kana warrior): a new interface for learning japanese characters. this paper presents the design and testing of kana warrior, a new interface for basic japanese character recognition based on a game-style user interface. kana warrior is a game designed to help japanese students learn to read characters quickly. a small pilot study has been conducted with very encouraging results. these results support the idea that game-style interfaces may be of benefit to users outside of the realm of entertainment programs.
investigation of subjective preferences in multiple degrees-of-freedom inputs. with the rapid proliferation of a wide range of input devices, there are many choices in designing or selecting a 6dof input device. user perception of the devices is an important aspect of design. we complement existing literature on the influence of grip of dominant hand on performance times with our experiments on the influence of grip of non-dominant hand on perceived ease-of-use, control and fatigue. our results show that for the non-dominant hand, the finger grip is perceived as being easy to use, less fatiguing and more controllable.
internet scrapbook: creating personalized world wide web pages. this paper describes an information personalization system, called internet scrapbook, which enables users to create a personal page by clipping and merging their necessary data gathered from multiple web pages. even when the source web pages are modified, the system updates the personal page, replacing with the latest data extracted from the source pages. therefore, once a user creates their personal pages, she can browse her necessary information only.
a portable system for anywhere interactions. interactions have taken off from the confinement of a single screen into various personal devices. projected an interface onto different parts of a physical environment is an escape beyond traditional display devices. imagine that any walls or floors can turn into a direct manipulation space without a lot of effort. this demonstration of ed-lite, a combination of a laptop, custom software, off-the-shelf digital camera and projector, shows projected interfaces with interactions on any surfaces including those not necessarily perpendicular to the projector. ed-lite is a derivation of our previous work on everywhere displays (ed) and steerable interfaces. this portable version has an automatic calibration feature that makes applications usable on any surfaces in a drop. more importantly, it is now possible to be taken on the road for demonstrations.
augmenting a retail environment using steerable interactive displays. this paper describes a prototype retail environment in which information interactions occur in situ, within the actual space of the merchandise. by combining a steerable projected display and recognition of user gestures and actions, and user position tracking through peripheral cameras, we have developed several innovative interaction techniques designed to augment the reality of a retail store.
virtual rear projection: do shadows matter? rear projection of large-scale upright displays is often preferred over front projection because of the lack of shadows that occlude the projected image. however, rear projection is not always a feasible option for space and cost reasons. recent research suggests that many of the desirable features of rear projection, in particular shadow elimination, can be reproduced using new front projection techniques. we report on the results of an empirical study comparing two new projection techniques with traditional rear projection and front projection.
flipper: a new method of digital document navigation. page flipping is an important part of paper-based document navigation. however this affordance of paper document has not been fully transferred to digital documents. in this paper we present flipper, a new digital document navigation technique inspired by paper document flipping. flipper combines speed-dependent automatic zooming (sdaz) [6] and rapid serial visual presentation (rsvp) [3], to let users navigate through documents at a wide range of speeds. it is particularly well adapted to rapid visual search. user studies show flipper is faster than both conventional scrolling and sdaz and is well received by users.
gender differences in trust perception when using im and video. the effect of gender information on trust building in virtual settings is an important yet unexplored area in hci. in this paper we empirically investigate gender differences in trust perception in two media, video and instant messaging (im), while performing negotiation and brainstorming tasks. participants who did not previously know each other were recruited to form homogeneous pairs, male-male and female-female. each pair carried out a task via computer-mediated communication using either video or im. our preliminary results uncover a significant gender difference in trust perception, with female pairs perceiving higher levels of trust than male pairs when gender information about the partner is explicitly provided before using the im channel. the results also show that both female and male pairs perceive higher levels of trust in the brainstorming task than in the negotiation task.
emoto: affectively involving both body and mind. it is known that emotions are experienced by both body and mind. oftentimes, emotions are evoked by sub-symbolic stimuli, such as colors, shapes, gestures, or music. we have built emoto, a mobile service for sending affective messages to others, with the explicit aim of addressing such sensing. through combining affective gestures for input with affective expressions that make use of colors, shapes and animations for the background of messages, the interaction pulls the user into an embodied 'affective loop'. we present a user study of emoto where 12 out of 18 subjects got both physically and emotionally involved in the interaction. the study also shows that the designed 'openness' and ambiguity of the expressions, was appreciated and understood by our subjects.
subtle expressivity for characters and robots. people, both consciously and unconsciously, use subtle expressions to indirectly communicate their emotions and intentions through variations of the gaze direction, voice tone and gesture speed. people also perceive changes in the internal states of others from subtle changes in their expressivities while interacting with them. subtle expressivity plays the supporting part to the leading role of explicit expressivity, such as contents of speech or category of facial expressions. however, subtle expressivity plays an important role to give moderate effects or gently regulate the relationship among the participants through a continuous interaction.these subtle expressivities are little focused on the design of interactive media in the context of software products and computers. only in the area of computer games in which pre-designed animated characters are used, the full potential of subtle expressivity is fully understood and used.although the general interest of the human-computer interaction research community in life-likeness and personality as a goal of software design is growing for reducing cognitive load [1,2], we are far from having coherent understanding of what subtle expressivity actually is and how products and processes can address it. we might question whether designing for subtle expressivity will result in gentle emotional effects on people and whether the processes and topics involved differ in any significant way from designing for believability or personality.
design of force feedback utilizing air pressure toward untethered human interface. in order to apply vr technologies to tools for everyday life, it is necessary to develop human interface technologies that do not constrain the users' activities. to achieve this goal, we propose a new force feedback method that utilizes air pressure to provide a force sensation to users. this force feedback system does not constrain users by an arm or a wire that connected with devices, and allows users to move their bodies and hands freely. this paper introduces the concept and the initial implementation of the air-pressure-based force feedback system.
evaluating social trails. we performed a 6-month study of a food recommender system to determine the influence of social trails on users choice of recipes. to measure the impact of the recom-mender functionality, we choose to avoid predictive accu-racy metrics, and opted for contextualised subjective meas-ures, comparing recommendations to searching and brows-ing. 18% of the selected recipes came from the list of rec-ommended recipes. in addition, users liked and understood the recommendation functionality.
predicting user satisfaction from subject satisfaction. in this paper, we describe work-in-progress in comparing user satisfaction ratings after user tests with ratings obtained following actual use of a digital music library software. we identify some of the variables that hamper prediction, and we reflect on the utility of surveys for predicting user/subject gaps in satisfaction.
notes on fridge surfaces. drawing on ongoing ethnographic investigations into home life, this paper presents detailed findings from a preliminary examination of refrigerator surfaces. the use and organization of items on fridge surfaces are shown to be closely tied to the material properties of both fridges and their surroundings. emphasis is placed on the importance of fridge magnets as they are seen to contribute to a fluidity and reconfigurability that make fridge surfaces unique. building on this, it is argued that the negotiation of family relations is afforded by the presented properties of the fridge and of magnets. to conclude, we introduce some general points to consider in designing interactive surfaces for the home.
what is that?: gesturing to determine device identity. computing devices can seamlessly recognize one another as they join and leave a wireless network, but users often experience difficulty identifying a desired device from a continuously changing list of devices surrounding them. this paper describes our custom implementation of a stylus and tags that enable users to rapidly identify devices in dynamic environments. our system utilizes a natural pointing gesture to identify a device, and subsequently transfer data over a wireless network.
affective gaming: measuring emotion through the gamepad. in search of suitable methods for measuring the affective state of video-game players, this study investigates the hypothesis that the player's state of arousal will correspond with the pressure used to depress buttons on a gamepad. a video game was created that would detect the force of each button press during play. it was found that as the difficulty level of the game increased, players would hit the gamepad buttons significantly harder.
player-centred game design. videogames are not your typical software application. they are often designed to elicit a negative emotional response, such as frustration or fear, the antithesis of usability. however, this is not to suggest that hci has little to offer the game design community. indeed, the exact opposite appears to be true. a number of user-centred design techniques have evolved which can support each stage of the game design process, from concept through to post-production. however, there is currently no archive of appropriate techniques showing how they might be applied to videogame design. given the differences in goals from these products to traditional software, this is clearly necessary. the purpose of this workshop is to identify those techniques appropriate to game design, and elicit practitioners' experience when applying such methodologies. the intended result is a prescriptive process which demonstrates how user-centred methodologies can best be applied to game design.
factors defining face-to-face interruptions in the office environment. this paper presents an on-going investigation on interruptions in the office caused by face-to-face interactions between knowledge workers. the study aims to identify opportunities for interactive solutions that will support both, the interrupters and the interrupted. the study involves contextual interviews and observations of how administrative assistants manage interruptions.
framework for evaluating application adaptivity. in the future, ubiquitous applications, services and environments will need adaptivity and context awareness in order to adapt to their users' requirements and needs. before these kinds of applications can be developed, we need to know when adaptivity is at an adequate level. this article introduces a framework (dimensions and degrees) for evaluating application adaptivity, showing how it can be used when evaluating commercial applications.
telmea2003: social summarization in online communities. we propose the concept of social summarization as an alternative to the content-based technology for summarization, report on its use in the community system telmea2003 implemented and employed to investigate techniques for social summarization, and discuss its effectiveness in supporting collaborative activities in online communities.
trust as an underlying factor of system administrator interface choice. system administrators are the unsung heroes of the information age, working behind the scenes to configure, maintain, and troubleshoot the computer infrastructure that underlies much of modern life. while graphical user interfaces (guis) are being offered as system administration tools, they mostly continue to use command-line interfaces (clis). based on an extensive survey of system administrators, we provide insights regarding this preference, analyze why many of these power users perceive clis as more effective than guis, and discuss findings as supported by observations from our parallel field studies. our analysis indicates that cognition-based trust and monitoring play major roles in the interface preference for clis vs. guis. we also propose next steps for further exploration of trust in human-computer interfaces.
you're getting warmer!: how proximity information affects search behavior in physical spaces. this paper describes the results of a wizard of oz study of people's search behavior using buddysystem, a proximity-sensing system designed to help end-users locate people, places, and things. buddysystem uses distance estimation based on signal strength alone, since direction is difficult to obtain in ad-hoc radio-based systems. overall findings indicate that the buddysystem changed people's search behavior to reduce walking area, but may increase search times if the system demands too much of the user's attention, suggesting that reducing distractions and adjusting search strategies could improve search effectiveness of proximity-based tracking systems in physical spaces.
multimodal human computer interaction research at toshiba research and development center. toshiba's human interface research group is pursuing media understanding and intelligent interaction technologies to achieve natural multimodal hci (human-computer interaction). in collaboration with toshiba's other corporate laboratories, engineering laboratories and business divisions, we have been developing practical interactive systems and products related to information services, consumer electronics, document filing and industrial equipment.
impact of video editing based on participants' gaze in multiparty conversation. this paper presents a video cut editing rule based on participants' gaze for establishing video editing rules that can accurately and clearly convey the flow of conversation in multiparty conversations to viewers. demand is growing to be able to effectively archive meetings and teleconferences to facilitate human communication. conventional systems use fixed-viewpoint cameras and simple camera selection based on participants' utterances etc. however, these systems fail to convey a sufficient amount of nonverbal information about the participants and the flow of conversation. on the basis of participants' gaze behavior in multiparty conversation, we propose a new video cut editing rule; the rule uses majority decision with regard to participants' gaze direction. we then present experiments that compare the proposed method to conventional visual representations. we conclude that the proposed method can more successfully convey 1) who is talking to whom and 2) hearers' response to speakers, which are extremely crucial pieces of information that allow viewers to understand the flow of conversation.
automatic video editing system using stereo-based head tracking for multiparty conversation. this paper presents an automatic video editing system based on head tracking for multiparty conversations. systems that record meetings and those that support teleconferences are attracting considerable interest. conventional systems use a fixed-viewpoint camera and simple camera selection based on participants' utterances. however, conventional systems fail to adequately convey who is talking to whom to the viewer. we focus on the participants' head orientation since this information is useful in detecting the speaker and who the speaker is talking to. in order to automatically estimate each participant's head orientation, our system combines several modules for stereo-based head tracking. the system selects the shot of the participant that most participants are looking at, based on majority decision. experiments confirm the effectiveness of our system in several 3-participant conversations. the results show that our system can more successfully convey who is talking to whom which is an extremely crucial piece of information that allows the viewer to better under-stand conversation content.
estimating human interruptibility in the home for remote communication. this paper presents a method for automatically estimating human interruptibility in home environments. to make online remote communication smoother, determining if it is appropriate to interrupt the remote partner is critical. as a first step in achieving this goal, several audio-visual features, extracted from data streams provided by a camera and a microphone, are correlated to human interruptibility. based on these features, the level of interruptibility is estimated using the trained support vector regression (svr) technique. finally, we discuss the potential of our method based on the results of several experiments.
information search: the intersection of visual and semantic space. in the context of an information search task, does the visual salience of items interact with information scent? that is, do things like bold headlines or highlighted phrases interact with local semantic cues about the usefulness of distal sources of information? most research on visual search and highlighting has used stimuli with no semantic content, while studies on information search have assumed equal visual salience of items in the search space. in real information environments like the web, however, these things do not occur in isolation. thus, we used a laboratory study to examine how these factors interact. the almost perfectly additive results imply that good information scent cannot overcome poor visual cues, or vice versa, and that both factors are equally important.
effects of voice vs. remote on u.s. and japanese user satisfaction with interactive hdtv systems. a between-participants (n=60) experiment explores the effect of input modality (voice with 100% recognition vs. remote) and culture (us vs. japan) on user's opinions of an interactive high definition television system (ihdtv). there was a significant interaction: .japanese participants completed tasks more easily and thought the interface was better with a remote control. conversely, united states participants completed tasks more easily and thought the interface was better with voice control. participants from both cultures liked content more and felt more uncomfortable when using voice control.
information voyeurism: social impact of physically large displays on information privacy. a common observation when working on physically large displays, such as wall-sized projection, is that a certain amount of information privacy is lost. a common explanation for this loss in privacy is the higher legibility of information presented on large displays. in this paper, we present a novel paradigm for measuring whether or not a user has read certain content. we show that, even with constant visual angles and legibility, visitors are still more likely to glance over a user's shoulder to read information on a large wall-projected display than on a smaller traditional desktop monitor. we assert that, in addition to legibility, there are more subtle social factors that may contribute to the loss of privacy on physically large displays. implementing hardware and software ideas for mitigating this loss of privacy remains future research.
wincuts: manipulating arbitrary window regions for more effective use of screen space. each window on our computer desktop provides a view into some information. although users can currently manipulate multiple windows, we assert that being able to spatially arrange smaller regions of these windows could help users perform certain tasks more efficiently. in this paper, we describe a novel interaction technique that allows users to replicate arbitrary regions of existing windows into independent windows called wincuts. each wincut is a live view of a region of the source window with which users can interact. we also present an extension that allows users to share wincuts across multiple devices. next, we classify the set of tasks for which wincuts may be useful, both in single as well as multiple device scenarios. we present high level implementation details so that other researchers can replicate this work. and finally, we discuss future work that we will pursue in extending these ideas.
pre-emptive shadows: eliminating the blinding light from projectors. users interacting with front-projected displays often work between the projector and the display surface. this causes undesirable projection on the user as well as temporary blindness from looking into the bright light of the projector. in this paper, we present pre-emptive shadows, a technique that uses a camera-projector system to detect and turn off pixels that would otherwise be needlessly cast upon users' bodies, especially their faces. we present measurements that show that system reduces the brightness of the blinding light by about a factor of 5.
kinesthetic cues aid spatial memory. we are interestind in building and evaluating human computer interfaces that make information more memorable. psychology research informs us that humans access memories through cues, or "memory hooks," acquired at the time we learn the information. in this paper, we show that kinesthetic cues, or the awareness of parts of our body's position with respect to itself or to the environment, are useful for recalling the positions of objects in space. we report a user study demonstrating a 19% increase in spatial memory for information controlled with a touchscreen, which provides direct kinesthetic cues, as compared to a standard mouse interface. we also report results indicating that females may benefit more than males from using the touchscreen device.
design concept to promote both reflective and experimental cognition for creative design work. we discuss the disadvantages of the current design support systems that arise from a poor understanding of the human-cognitive characteristics, such as the reflective and experimental modes, and the selection of a suitable media for use in the creative design process. then we demonstrate the current prototype system called "godzilla" that supports the creative design especially for the car exterior designer. the designers can draw the concept image on a 2d pad (tablet with an lcd). when they grasp it and put it in midair, the shape of the 2d sketch is automatically recognized and appears as 3d sketch on a 3d pad (stereovision tv). they can sketch, modify, and observe from different viewpoints in both 2d and 3d. note that 3d images are not displayed as a beautiful cg image, but a 3d sketch that consists of many 3d-cursive lines produced by mimicking the designer's pen touch in order to keep the designers in the reflective cognitive mode and to provide them with rich stimuli for their creative activities.
new findings on pupil response in gazing to flashed divided displays. we show that the pupil responds to the small area being gazed when it is flashed. the experiments revealed that the pupil reacts to the brightness of the small area being gazed at. surprisingly, the resolution is 1.6 degrees at the viewing angle. this is equivalent to the spatial resolution of a 21 x 16 mm area at a distance of 60 cm. finally, the feasibility of the new findings is demonstrated by applying it to character input.
evaluation of thumbwheel text entry methods. text entry becomes increasingly complex as devices shrink in size. this paper presents the findings of a comparison study of two thumbwheel text entry methods for mobile devices. in the first method, the character set (letters, numbers, punctuation) was implemented as a continuous loop. in the second method, characters were arranged in a two-level menu structure. thumbwheel methods provide a viable and realistic alternative to keyboard, keypad, stylus, or voice text entry on ultra-small mobile devices.
testing visual notification cues on a mobile device. this paper discusses field-testing of visual notification cues on a mobile handheld device. each cue consisted of three multicolored lights preceded by a tactile signal (vibration). after being customized, the cues were sent periodically to the device over a wireless network as users went about their normal activities. user personalization seemed to enhance learning and usefulness of the cues, while the additional tactile signal aided arrival awareness.
protecting private data in public. current technologies allow users to access information in virtually any public setting. this creates situations where sensitive information, both organizational and personal in nature, can be seen and captured by nearby people and technology. therefore, methods are necessary to ensure the privacy and security of information displayed in public spaces. the authors have developed web browser privacy blinders, which hide sensitive information from view while leaving other information unobscured. results of two pilot studies supported the viability and potential usefulness of the privacy blinder concept, and have set the stage for continued development of the technique through large-scale controlled studies and field tests.
logimoo: a multi-user virtual world with agents and natural language programming. logimoo is a binprolog-based virtual world running under netscape or internet explorer. it is user extensible and supports distributed group-work over the internet. virtual places, virtual objects and agents are programmable through a "controlled english" interface.
age invaders: social and physical inter-generational family entertainment. this paper introduces age invaders (ai), a novel interactive intergeneration social-physical game which allows the elderly to play harmoniously together with children in physical space while parents can participate in the game play in real time remotely through the internet.
polymorphic letters: transforming pen movements to extend written expression. we are developing a digital writing tool, polymorphic letters (pl), to investigate hand and pen movements as they may extend and enrich expression in written language. pl recognizes individual letters and associated spatial, temporal and pressure qualities of pen movements. the system maps these features to typography and colour variables, creating lively representations on-screen. writers will use the tool in learning environments emphasizing the role of personal expressions. we explore style and voice as they pertain to expressions through hand, pen, and words, and describe the rationale for pl, its iterative design, and next steps based on writers' and readers' experiences.
how people recall search result lists. people commonly interact with lists of information -- incoming emails are listed in a person's inbox, search engines return lists of results, news stories appear as lists on newspaper web sites, and people navigate file systems by listing directory contents. while the changes that occur to a list can be interesting -- a new search result is interesting to the person searching for new information -- changes are often secondary to the primary goal of using information. new search results are inconsequential when a person wants to summarize a set of results or return to a previously viewed web page. this paper presents a study of which aspects of a list are memorable and thus are likely to be noticed when they change, and which are not memorable and thus are unlikely to be missed if changed. the study shows that what people remember about a list item is a function of their interaction with the item and the item's location in the list.
poultry.internet: a remote human-pet interaction system. poultry.internet leverages on the reach of the internet to connect humans and pets at different locations. this system has a tangible interface encompassing both visual and tactile modes of communication. it allows humans to interact remotely with pets anytime, anywhere. the pet owner views the real time movement of the pet in the form of a pet doll sitting on a mechanical positioning system. meanwhile, the real pet wears a special jacket, which is able to reproduce the touching sensation. the pet owner can tangibly touch the pet doll, sending touch signals to the pet far away. also, the pet owner receives a haptic feedback from the movement of the pet.
comparisons of keystroke-level model predictions to observed data. comparison of model prediction against observed data is an investigative step used in cognitive modeling research for human-computer interaction. in this paper we describe comparisons between keystroke-level model (klm) predictions and user behavior by total duration, aggregated events and cohen's kappa. our preliminary investigations support the validity of klm mental preparation duration and placement rules in modeling interaction with handheld devices but suggest changing a previously-published parameter.
information visualization and interaction techniques for collaboration across multiple displays. this two day workshop looks at the challenges and issues associated with supporting collaborative analytical reasoning tasks over a range of displays and interaction environments. the focus is not only on visualization and interaction, but also on perception, cognition, and sense-making in collaborative settings.
social net: using patterns of physical proximity over time to infer shared interests. we describe social net, a novel interest-matching application that uses patterns of collocation, over time, to infer shared interests between users. social net demonstrates new possibilities and methods for using the capabilities of mobile devices equipped with rf-communications.
an ordering of secondary task display attributes. we found that established display design guidelines for focal images cannot be extended to images displayed as a secondary task in a dual-task situation. this paper describes an experiment that determines a new ordering guideline for secondary task image attributes according to human cognitive ability to extract information. the imperative for alternate guidelines is based on the difference in an image's ability to convey meaning, which decreases when moved from a focal to a secondary task situation. secondary task attribute ordering varies with the level of degradation in the primary task.
does habituation affect fingerprint quality? interest in the environmental factors that affect biometric image quality is increasing as biometric technologies are currently being implemented in various business applications. this study aims to determine, through repeated trials, the effects of various external factors on the image quality and usability of prints collected by an electronic reader. these factors include age and gender but also the absence or presence of immediate feedback. a key factor in biometric systems that will be used daily or routinely is habituation. the user's behavior could potentially change as a result of acclimatization; one's input might increase in quality as one learns how to use the system better, or decrease in quality since comfort with the system could translate into carelessness.
acclairism: questioning biometric technology through an airport security clearance system. biometric technologies are becoming socially acceptable in the wake of recent terrorist events. bio-data is developing into a legitimate source for identity detection and assessment. acclairism is an attempt to bring to light some of the conflicts and questions these technologies give rise to: what defines us as unique individuals? what defines us as trusted members of society? how much personal information will we willingly give away and under which circumstances? through acclairism we explore a situation wherein people freely accept a highly invasive, highly authoritative manipulation in return for tangible rewards and an upgraded social status. we perform this investigation through acclair, a company providing brain-testing services as part of an exclusive security clearance for air-travelers.
beyond just the facts: transforming the museum learning experience. we present museum detective, a handheld system designed for use by school children to encourage guided learning through paired discovery of one object in an art museum. initial analysis showed that children were able to use the devices cooperatively and exhibited longer-term retention of information about the artifacts in the gallery. we propose that the design of the museum detective interface can be refined to further encourage students to actively transform their museum learning experience.
hci techniques from idea to deployment: a case study for a dynamic learning environment. ihis paper describes the plan and execution hci techniques that were used in the iterative design and evaluation of a "dynamic learning environment." this system is now operational for ibm software group employees and is being extended to other venues and audiences.
the voice of the people: a system for enriching olympic experiences. during a 14-week student design project, we developed a concept for a three-component system that allows audience members to voice their opinions at olympic events. aside from completing chi's primary goal of creating a voting device, we found that audience members need a knowledge base and a feeling of empowerment in order to feel secure with their vote. based on fieldwork with past and potential olympic attendees, we focused on wearable technology that senses pre-existing methods of showing appreciation and translates audience enthusiasm into an opportunity for learning and empowerment. building from previous research, we implemented a unique method of creating a system for audience participation that requires no training or learning curve on behalf of its user. these methods were then tested and refined until they were well received by a large majority of users regardless of age, gender and nationality. in our paper we describe our process through an explanation of our immersion in the project, its early ideation, testing and refinement, and our final solution.
photophone entertainment. this paper introduces photophone entertainment (ppe), applications for mobile and wireless devices with camera functionality, and describes a number of design examples of such applications. the applications are designed for people waiting for a few minutes at a bus stop and do all encourage some form of social interaction such as collaboration with, or competition against, other users at the bus stop.
ubiquitous display for dynamically changing environment. this paper proposes a novel method for ubiquitous displays using projectors in indoor environments. in particular, our method consists of two distinct features: automatic scene modeling of a dynamically changing indoor environment, and automatic selection of surfaces onto which various contents are displayed by taking into account both geometric and photometric properties. as a result, our method can be applied to dynamically changing scenes such as a meeting room where furniture and other objects are moved frequently.
improving user interaction with spoken dialog systems via shaping. speech-based interfaces offer the promise of simple human-computer communication, yet the current state-of-the-art often produces inefficient interactions. many inefficiencies are caused by understanding or recognition errors. such errors can be minimized by designing interaction protocols in which users are required to speak in a standardized way, but this requirement presents additional difficulties: this way of speaking can be unnatural for users, and in order to learn the standardized interface, users must spend time in tutorial mode rather than in task mode. i propose a strategy of shaping that helps users adapt their interaction to match what the system understands best, thereby reducing the chance for misunderstandings and improving interaction efficiency.
shaping user input in speech graffiti: a first pass. speech graffiti is a standardized interaction protocol for spoken dialog systems designed to address some com-mon difficulties with asr. we have proposed a strategy of shaping to help users adapt their interaction to match what the system understands best, thereby re-ducing the chance for misunderstandings and improving interaction efficiency. in this paper we report on an evaluation of our initial implementation of shaping in speech graffiti, noting that our baseline strategy was not as powerful as expected, and discussing proposed changes to improve its effectiveness.
multiple virtual rafts: a multi-user paradigm for interacting with communities of autonomous characters. this paper describes a multi-user version of the "virtual raft project" being exhibited in the interactivity program at chi 2005. the virtual raft project is an interactive installation in which communities of autonomous animated characters inhabit desktop "virtual islands." a human participant may transport the characters between the islands via a mobile device-based "virtual raft." this paper describes an implementation of a multi-user version of this project, in which several virtual rafts may be used simultaneously to carry characters among the islands. the multi-user experience improves on the single-user original in four ways: increased throughput, increased collaboration among the participants, increased enjoyment for the participants, and the introduction of a new mode of interaction (characters jumping directly from one raft to another). this paper also provides a preliminary evaluation of the entire system through observations from a deployment of the virtual raft project to approximately two hundred people.
the ecoraft project: a multi-device interactive graphical exhibit for learning about restoration ecology. the ecoraft project, an interactive installation designed to help children learn about restoration ecology, allows participants to engage physically with animated agents via a natural and intuitive interface. this physical engagement occurs when the agents transfer seamlessly from stationary computers to mobile devices, on which the agents are realized as quasi-physical manifestations. utilizing tablet pcs to act simultaneously as objects in the physical world and as mobile virtual spaces, the system incorporates embodied mobile agents that increase levels of engagement. the project has been publicly shown at several venues, where over 2000 participants interacted with the system. this paper presents initial evaluation results based on interviews with participants indicating that the embodied, physical interaction in this installation leads to participant engagement and collaboration, and enhanced educational effectiveness.
the virtual raft project: a mobile interface for interacting with communities of autonomous characters. this paper presents a novel and intuitive paradigm for interacting with autonomous animated characters. this paradigm utilizes a mobile device to allow people to transport characters among different virtual environments. the central metaphor in this paradigm is that virtual space is like land and real space is like water for virtual characters. the tangible interface described here serves as a virtual raft with which people may carry characters across a sea of real space from one virtual island to another. by increasing participants' physical engagement with the autonomous characters, this interaction paradigm contributes to the believability of those characters.
the neurally controllable internet browser (brainbrowser). the internet has become an important part of our daily lives, with browsers serving as the main tool of navigation. for users with severe disabilities, access to the internet can be crucial to quality of life, providing a myriad of services and opportunities. the gsu brainlab is researching methods of controlling computer interfaces directly with brain signals, to assist users who are completely paralyzed and have no other means of interaction. adapting a web browser for neural control provides us a unique opportunity to study navigation issues for assistive technology. the neural internet brainbrowser project is currently exploring new human computer interaction paradigms, web usability concepts, and interface serialization techniques.
chick clique: persuasive technology to motivate teenage girls to exercise. we are developing a preventative health cell phone application that helps motivate teenage girls to exercise by exploiting their social desire to stay connected with their peers. we targeted girls because they are more likely to become less active throughout adolescence and are more likely to use dangerous techniques for losing weight. the intent of chick clique is to provide information at opportune times in order to modify the behaviors of girls and ultimately lead to improved health habits. our study investigated how collecting, sharing and comparing personal fitness information impacts activity level and health awareness.
phonological and visual working memory in processing of route guidance information. the goal of my proposed thesis is to examine the role of working memory in processing route guidance information while driving. i will also assess how changes in the presentation and processing of route guidance and secondary task information influences the primary task of vehicle control. results will be analyzed in terms of whether a change of route navigation presentation from visual to auditory will change the memory resources used to process the information. furthermore, analyses will be done to assess whether changes in the processing of route navigation and secondary task information affect driving performance. to examine what working memory subsystems (i.e., phonological, visual, spatial, central executive) are used to process visual versus auditory route guidance information, the present research will require participants to drive a driving simulator while performing a route navigation task and a secondary working memory task. performance of these secondary tasks will permit us to assess demands of route navigation tasks upon the various working memory subsystems. accordingly, participants will retain a memory load while performing the route navigation tasks. this research is expected to raise significant hci implications for the design of safer interfaces for vehicles and provide much needed detail about how specific mental codes and processes are involved in processing route navigation information.
cell phone communication and driver visual behavior: the impact of cognitive distraction. with the advent of new technology in vehicles, drivers can access information in many different forms (email, address books, web pages) and from many information sources (cell phones, pdas, driver support systems). with these new information sources finding their way into cars comes increasing concern about the potential adverse effects resulting from drivers' interactions with such multi-function devices. this paper examines the disruptive impact of complex, interactive, hands-free cell phone communications upon the visual awareness of drivers proceeding through high volume intersections. the present study documents changes in driver visual behavior, resulting from cognitive distraction of speech-based interactions, that may contribute to intersection crashes. the results of this research raise significant hci implications for the design of interactive intelligent transportation systems (its) within the automotive sector.
designing smooth connections between worlds. currently there is a lack of explicit theories and few detailed guidelines to support the development of mixed reality (mr) technology and its varied applications. this research focuses on this lack by supporting the design, development and evaluation of mr lifecycle phases. the discussed methodology is based on the model-based approach for the design support and on analysis of continuous interaction properties to measure interaction techniques.
usable browsers for ontological knowledge acquisition. in this paper we compare the usability of several presentation formats for ontological knowledge of events. the goal is to support further work in knowledge acquisition from informants who are not necessarily experienced with knowledge representations. this work investigates the question: how can we present detailed ontological information to such informants, in a format that is easy to understand, modify, and augment? we compare three formats: two commonly-used diagram styles and one lisp-like list of knowledge axioms. ongoing work on this topic will expand the investigation into a study of the role of natural language in knowledge acquisition.
creating conversational interfaces for interactive software agents. while much research and design has been presented on designing interactive agents and on speech interfaces, little has been said about combining these areas. this tutorial presents recommended guidelines for creating conversational interfaces with agents presented as interactive characters.
how do users think about ubiquitous computing? as ubiquitous computing technology migrates into the home environment, there has been a concurrent effort to allow users to build and customize such technologies to suit their own specific needs. many tools have been built to enable users with little or no programming knowledge to build such applications. despite the de-emphasis on programming, however, these tools are often device-centric, rather than user-centric. in this paper, we investigate how people describe and conceptualize ubiquitous computing applications and technology. we examine how people naturally express ideas for novel applications to build conceptual models upon which to base future interfaces for creating ubiquitous computing applications.
devices for sharing thoughts and affection at a distance. interpersonal communication involves more than just words. many forms of communication involve physical acts showing warm thoughts and affection, such as giving flowers or displaying photos. yet these forms of personal communication are difficult at a distance. in this paper, we describe the concept of devices for communicating affection and thoughts from a distance. we detail two devices that we are exploring to support many of these physical interpersonal interactions-an augmented candy dispenser and a digital picture frame-and discuss design issues we have encountered as we investigate this interesting application space.
an empirical assessment of adaptation techniques. the effectiveness of adaptive user interfaces highly depends on the how accurately adaptation satisfies the needs of users. this paper presents an empirical study that examined two adaptation techniques applied on lists of textual selections. the study measured user performance controlling the accuracy of the suggestions made by the adaptive user interface. the results indicate that different adaptation techniques bare different costs and gains, which are affected by the accuracy of adaptation.
triba: a cable television retrieval & awareness system. this paper discusses the design of a physical and digital system intended to allow for easy manipulation and interaction with the tremendous amount of options present in advanced multimedia devices, such as digital cable television. as user demand for access to large quantities of data increases, and cable companies offer more choices to their audiences, traditional content selection techniques become less useful and much more difficult to understand. triba is the result of a ten week research and design exploration investigating how users can easily manipulate and comprehend tremendously large data sets. the findings of this research indicate a need for utilizing interactive agents to bridge the gap between the user and their goal. as technology is created and consumer electronics becomes more integrated into our lives, devices speak a language that users are expected to learn. triba is a product embracing the philosophical idea that users should not have to learn a new language to interact with a futuristic and useful product, but instead products and devices must learn to speak the same language as the user.
layered touch panel: the input device with two touch panel layers. we developed layered touch panel that expands the interaction techniques of touch panel. layer touch panel has two touch panel layers, so that it is able to distinguish two touch states such as "finger on screen" and "finger above screen". with the structure, rollover effect and pick & drop that are not available in normal touch panel are available in layered touch panel.as the result of a usability test, 88% of test users answered that layered touch panel is more usable than normal touch panel.therefore, we consider that layered touch panel is useful for the products that have touch panel.
connecting bridges across the digital divide. connecting people across the digital divide is as much a social effort as a technological one. we are developing a community-centered approach to learn how interaction techniques can compensate for poor communication across the digital divide. preliminary trials have yielded interfaces that deal with poor quality by adapting instant messaging techniques for multiple modalities, providing improved semi-synchronous communication. lessons learned suggest new ways to design user interfaces specifically for the developing world.
asynchronous collaborative design. as new usability support analysts at sas institute, the authors were challenged with the goal of gathering design input from a diverse population of internal and external design stakeholders. after considering participatory design as the methodology of choice, it was found that simultaneous, collaborative sessions were not possible due to prospective participant time constraints. this constraint motivated the authors to devise and use asynchronous collaborative design methods that were tailored to the specific needs of the data gathering efforts that took place throughout the duration of the project. all methods resulted in a rich set of data that informed subsequent design decisions. however, methods were also associated with drawbacks. the pros and cons of each method are described in this paper.
human interface design at fidelity investments. this presentation describes the human interface design department at fidelity investments. although not in the computer hardware or software business, fidelity develops an amazingly wide variety of systems in support of our business. the human interface design department, which is composed of people from a variety of backgrounds, provides several key services to systems development projects throughout the company, including user interface design and prototyping, usability testing, and online help development. we are also responsible for the corporate graphical user interface style guide and web design guide. examples of the development projects we assist with are described, as well as strategic projects that address more general human interface issues.
designating required vs. optional input fields. this paper describes a study comparing different techniques for visually distingishing required from optional input fields in a form-filling application. seven techniques were studied: no indication, bold field labels, chevrons in front of the labels, check marks to the right of the input fields, a different background color, grouping them separately, and a status bar indication. performance and preference data were collected. in general, we found that the two worst methods were no indication and the status bar. the best method was separate groups.
using personal photos as pictorial passwords. pictorial passwords, where the user recognizes "target" images among "distractors", appear to have potential for improving the usability of authentication systems. we conducted three exploratory studies on the use of personal photos for authentication over a three-month period. participants provided 8-20 photos of personal significance to them but which they believed others would not recognize. they also chose four photos to remember from a set of stock photos. recognition accuracy for the personal photos was significantly higher than the stock photos. we also manipulated the number of target and distractor photos as well as their similarity, and we tested how well others who know the users could guess their photos. larger numbers of distractors and greater similarity to the targets made it harder for others to guess the correct photos, while having no impact on the user's own recognition accuracy.
inner circle: people centered email client. we present an automatic people-centered organization of the email message store, where all the information is organized by the association with the message sender or recipients. by using a zoomable list control, we can show most frequent contacts on the top level, and still scale to a large number of contacts overall. messages exchanged with a person or any ad-hoc defined group are displayed as a continuous conversation. individual nuggets sent in email, such as attachments and links, are extracted from messages and put into their own window. organizing nuggets into people-oriented shared spaces supports email-based collaboration. the proposed email client enhancements tested very well in a preliminary user study.
anchoreddisplays: the web on walls. with the world wide web, mountains of information are suddenly within easy reach. unfortunately, accessing this information still requires a computer screen, a keyboard and a mouse. this paper describes anchoreddisplays, a new metaphor for exploiting physical location to help display and organize dynamically changing information. anchoreddisplays are inexpensive battery operated display screens that can be affixed on walls, doors and desks. the displays can be configured to present information such as weather, traffic, stock quotes and sports scores extracted from the web. once configured, users can place these displays wherever they feel relevant. suddenly, dynamic information becomes much easier to find and assimilate; a user might place tomorrow's weather near the light switch and sports scores near the phone. hardware and software implementations of a prototype anchoreddisplay system are described.
intuitive visualizations for presence and recency information for ambient displays. the semi-public displays project utilizes public displays to assist in the interactions of small groups. this paper describes a set of visualizations for presence information of group members designed for the displays. here we show that visual mappings of such information can be intuitive. through our interviews, we also identify data usage, data ambiguity, and data recording as issues influencing how comfortable participants were with privacy in relation to semi-public displays of such information.
soft toys with computer hearts: building personal storytelling environments. sage is an authoring tool that allows children to design their own wise storytellers to interact with. it explicitly aims to enable them to explore their inner world, as well as to learn about storytelling and technology. in order to foster emotional engagement and explore the integration of physical and computer interfaces, the sage storyteller was embodied in a interactive stuffed animal.
photovote: olympic judging system. this proposal is designed to be an easy and fun way to vote at olympic games and at other events. much effort has been put in to making this solution realistic, cost efficient, innovative and simple. the audience can use this system to vote on an athlete's performance by simply holding up a coloured page from the athletic event program. to further enhance the experience of visiting the olympic games another new feature is introduced, which gives the audience all information about what the professional judges thought about the performance by presenting it visually directly in the replay. the origin of this project was based on the criticism that some olympic events have received in previous years for challengeable judgment. by focusing on information flow and understandability, the design team has proposed a flexible, versatile and relatively low-cost solution.
visualizing complex medical phenomena for medical students. this paper introduces some early findings and preliminary results of the experiments of the virtual laboratory project, in which we designed and implemented a learning environment for medical students. the focus in our research is to improve students' abilities to learn and recall certain complex phenomena in the mechanisms and diagnostics of infectious diseases by visualizing these phenomena with animations, three-dimensional models, photos and videos. furthermore, we are aiming to provide conceptual cues on the processes of the essential elements, and to support the construction of a mental model of that phenomenon. in medicine, some complex, dynamic, and multi-level phenomena are difficult to learn using conventional learning material, which is either based on text and is written mainly for experts, or is based on static images, and the relationships between objects and multi-level processes are not so evident. in our project, we design multimedia material on the mechanisms and diagnostics of infectious diseases. our aim is to study usability issues and user interface design principles that could support cognition. the paper presents the general user interface design issues involving visualization of complex processes. issues related to the context of use are also discussed.
hypermedia extension based on recursive abstractions. there are many well documented problems facing the ordinary user, as opposed to the enthusiast, of hypermedia (hm) technology which can lead these users to be frustrated by, or give-up using hypermedia technology altogether. among these classic hm problems are: the framing problem, framing and intercomparision combined, link types, versioning and historical backtrack, closed context and open media, adding these aspects later, disorientation [3], information structuring systems [2], visualizing [4]. this paper focuses on one of these key problems, "the framing problem" - as the number of hypermedia objects grows the problem of restricting our attention to only the relevant connections becomes harder [3]. how can we structure the source hypermedia to show semantically related clusters? by solving this problem it is possible to offer new ways for people to search and browse hypermedia.
making oracle behave. in this paper, we describe a software development project in which usability experts fought an unusual battle against the limitations of oracle designer. based on this specific case, we give tips and tricks for usability experts who face the challenge of designing user interfaces by making use of counteracting development tools.
dolltalk: a computational toy to enhance children's creativity. this paper presents a novel approach and interface for encouraging children to tell and act out original stories. dolltalk is a toy that simulates speech recognition by capturing the gestures and speech of a child. the toy then plays back a child's pretend-play speech in altered voices representing the characters of the child's story. dolltalk's tangible interface and ability to retell a child's story may enhance a child's creativity in narrative elaboration.
defining scenarios for mobile design and evaluation. this paper presents results from the design experiences of several mobile applications. it starts by addressing the difficulties that emerged through the data gathering, prototyping and evaluation stages. we explain how these problems and challenges were tackled, resulting in the creation of a conceptual scenario generation and selection framework. the framework and suggested guidelines aim at aiding designers on the scenario generation and selection process during design and evaluation of mobile applications. we address several case studies in which these guidelines were applied, stressing their contributions and results.
best practices and future visions for search user interfaces: a workshop. this one-day workshop will create a roadmap of current best practices and future needs for search user interface design. it will provide an interactive forum for participants to actively discuss submitted papers, industry trends, and gaps in our knowledge. participants will come away with new research findings, key contacts, and identified opportunities for research. participants will be both practitioners and academics to balance the discussion between theory and application.
connecting with large market customers: can we still call it usability? in this panel we will present the opinions and experiences of a set of experts who have worked with large-market customers, also known as enterprise customers, in a usability context. we will provide a brief overview of the differences in usability engineering with large-market customers compared to business-to-consumer or small to mid-market customers. we will then present, in an interview format, the opinions of our panelists on a set of questions challenging the 'usability' nature of working with this set of stakeholders.
interfaces for advanced manufacturing technology. due to the rapid computerization of advanced manufacturing workplaces, there is an increasing need for interfaces which can support this specific set of applications and users. however, workers in these situations tend to be highly trained in the specific tasks that they must accomplish, but may be relative novices on computing systems. this paper describes the design of easy assemble, a windows based support system to assist workers in a flexible assembly task. six subjects used easy assemble as real-time instructional support to assemble four products in a simulated manufacturing environment. subjects assembled products in less than half the time and with variances much lower than the control group which used the traditional method of blueprints. furthermore, subjects made significantly fewer errors. the system provides a starting point for the development of fully integrated systems for the advanced manufacturing environment.
video matters! when communication ability is stressed, video helps. this study assesses whether remotely located pairs of people working on a collaborative task benefit from using video, looking in particular at people for whom communication is stressed. in this study, we extend the research on video-mediated communication to the domain of non-native speaker interactions. thirty-six pairs performed a map task using either audio-only or audio-plus-video for communication. half the pairs were non-native speakers, half were native speakers. as in many studies of video connectivity with native speakers, no benefit from the video was found. however, non-native speakers performed significantly better with a video connection than with audio-only.
conversational awareness in multiparty vmc. in this demonstration, we present a number of videoconferencing systems which differ in support for conversational awareness. we argue that such systems should convey speech, relative position, gaze direction and gaze of the participants, but not necessarily full-motion video.
designing attentive cell phone using wearable eyecontact sensors. we present a prototype attentive cell phone that uses a low-cost eyecontact sensor and speech analysis to detect whether its user is in a face-to-face conversation. we discuss how this information can be communicated to callers to allow them to employ basic social rules of interrruption.
media eyepliances: using eye tracking for remote control focus selection of appliances. this paper discusses the use of eye contact sensing for focus selection operations in remote controlled media appliances. focus selection with remote controls tends to be cumbersome as selection buttons place the remote in a device-specific modality. we addressed this issue with the design of media eyepliances, home theatre appliances augmented with a digital eye contact sensor. an appliance is selected as the focus of remote commands by looking at its sensor. a central server subsequently routes all commands provided by remote, keyboard or voice input to the focus eyepliance. we discuss a calibration-free digital eye contact sensing technique that allows media eyepliances to determine the user's point of gaze.
gaze-2: an attentive video conferencing system. gaze-2 is an attentive video conferencing system that conveys whom users are talking to by measuring whom a user looks at and then rotating his video image towards that person in a 3d meeting room. attentive videotunnels ensure a parallax-free image by automatically broadcasting the feed from the camera closest to where the user looks. the system allows attentive compression by reducing resolution of video and audio feeds from users that are not being looked at.
a magic box for understanding intergenerational play. this paper explores the nature of intergenerational play and opportunities for technologies to mediate playful activities. we report on a cultural probe study of four extended families and introduce the magic box as a new probe for understanding playful engagement at a distance.
applying contextual design to erp system implementation. the aim of enterprise resource planning (erp) systems is to integrate a company's information systems and to make the company's business processes more efficient. erp systems are commercial-off-the-shelf products (cots) that seldom totally fit into the company's existing business processes. contextual design (cd) can be used to model the context of use of an erp system. three cases demonstrate that the application of cd supports the selection of a suitable system and helps the organization and people adjust their tasks to the new erp system's processes.
gelforce: a vision-based traction field computer interface. we propose a tactile sensor based on computer vision that measures a dense traction field, or a distribution of 3d force vectors over a 2d surface, which humans also effectively sense through a dense array of mechanoreceptors in the skin. the proposed "gelforce" tactile sensor has an elegant and organic design and can compute large and structurally rich traction fields in real time. we present how this sensor can serve as a powerful and intuitive computer interface for both existing and emerging desktop applications.
conveying user values between families and designers. current research in domestic technology focuses on a subset of the breadth of values that may be present in the domestic environment. in this paper, we present one possible method for conveying a larger potential breadth of user values between families and designers. we describe the ways that we tailored cultural probes specifically for values elicitation as well as the results of both families' and designers' interactions with the probes. we also draw from the social psychology research of milton rokeach, whose framework for values was used to scaffold designers in foregrounding user values in domestic design.
interviewing over instant messaging. interviews often serve as the cornerstone of human-computer interaction research. as a research method, they can both be deeply valuable and distinctly challenging. pragmatic challenges of interviews include the travel that may be required to meet face-to-face with a respondent or the time necessary to transcribe the exchange. as a tool for conducting interviews, instant messaging presents some compelling potential benefits to mitigate challenges such as these. and yet, over the medium of instant messaging, the genre of the interview takes on a different character. drawing from our experiences conducting interviews over instant messaging, we reflect on the implications of using this new medium for conducting interviews.
cross-dressing and border crossing: exploring experience methods across disciplines. as designers of interactive systems (spaces, process and products for people), we find ourselves stretching the limits of methodological structures that enable us to explore, build, communicate, and prototype experience. this workshop aims to investigate divergent disciplines that each contains rich knowledge and rigorous methodologies for for addressing human experience in interactive systems.
an interactive poster exhibit puts visitors in the picture, in real time. this describes the usability and interaction challenges in creating a unique museum exhibit which utilizes real-time compositing, and hides complex computational tasks behind a simple user interface.
assessing haptic properties for data representation. this paper describes the results of a series of forced choice design experiments investigating the discrimination of material properties using a phantom haptic device. research has shown that the phantom is effective at displaying graphical information to blind people, but the techniques used so far have been very simple. our experiments showed that subjects' discrimination of friction was significantly better than that of stiffness or the spatial period of sinusoidal textures, over the range of stimuli investigated. thus, it is proposed that graphical data could be made more easily accessible to blind users by scaling the data values to friction rather than shape or size, as in traditional bar charts.
'visual literacy' as challenge to the internationalisation of interfaces: a study of south african student web users. following a social semiotic approach, this paper questions the western cultural assumptions underpinning the web's evolving navigational conventions, and investigates to what extent a group of south african students command the currently dominant western conventions. south african students (both novices and experienced web users) completed a series of visual exercises, where they interpreted a set of interface and conceptual conventions in common use on the web. conceptual questions attempted to address to what extent students were familiar with and able to reproduce the conventional western visual design resources for representing classificational taxonomies or 'tree structures' and various other visual devices for the implicit portrayal of hierarchical information structures (kress and van leeuwen 1996). interface questions probed student recognition of common web icons. some broadly cultural factors were found to explain at least some of the variation in the group. finally, we consider the implications of our study for training, design, and the diverse range of south african representational resources.
dynamic viewpoint tethering: enhancing control performance in virtual worlds. in this study, we focus on investigating users' navigational performance with respect to the display frame of reference. dynamic viewpoint tethering is proposed as a means to increase user control and reduce the need for mental rotations, thus facilitating the acquisition of configurational knowledge about the virtual space.the concept of dynamic viewpoint tethering is explained and recent research findings are presented. twelve volunteers participated in an experiment in which they were instructed to control an aircraft-shaped cursor flying through a set of virtual tunnels and to answer questions about the environment. experimental results showed that neither the loose dynamic tether nor the rigid tether supported the best control performance. rather, optimal tether configuration lies at the centre of the rigidity continuum. the research results provide useful guidelines for the design of navigational system interfaces.
fingersense: augmenting expressiveness to physical pushing button by fingertip identification. in this paper, we propose a novel method, fingersense to enhance the expressiveness of physical buttons. in a fingersense enabled input device, a pressing action is differentiated according to the finger involved. we modeled the human performance of fingersense interfaces and derived related parameters from a preliminary usability study. overall findings indicate that fingersense is faster compared with traditional keypads when the finger switching action could be paralleled.
tinymotion: camera phone based interaction methods. this paper presents tinymotion, a pure software approach that detects the movements of cell phones in real time by analyzing image sequences captured by the built-in camera. typical movements that tinymotion detects include - horizontal and vertical movements, rotational movements and tilt movements. in contrast to earlier work, tinymotion does not require additional sensors, special scenes or backgrounds and can run on today's main-stream camera phones without hardware modification. we describe the design and implementation of tinymotion and analyze the potential interactions that can leverage tinymotion. three applications and two games were created to test tinymotion. benchmarking results and usability study show that tinymotion can detect camera movement reliably under most background and illumination conditions.
end-user place annotation on mobile devices: a comparative study. advances in location-based services (lbs) are opening opportunities for using the location of people, places, and things to augment or streamline interaction. while computers work with physical locations like latitude and longitude directly, people usually think and speak in terms of places, which adds personal, environmental and social meaning to a location. to address this conceptual mismatch, location-aware applications must incorporate the notion of place to achieve their full potential. in this paper, we investigate four techniques for collecting end-user place annotations interactively using cell phones. the results from a usability study suggest that while all the four methods receive similar preference ratings in understandability, the "photo memo plus offline editing" method is the most favorite approach in ease of use. in addition, users indicated their desire to adopt more than one place annotation method in location-aware applications.
virtual information piles for small screen devices. we describe an implementation that has users 'flick' notes, images, audio, and video files onto virtual piles beyond the display of small-screen devices. this scheme allows pda users to keep information close at hand without sacrificing valuable screen real estate. our approach takes advantage of human spatial memory capabilities. it also obviates the need to browse complex folder trees during a working session. the system also allows co-located individuals with pdas to share and organize information items (e.g., photos, text, sound clips, etc.) by placing them in shared, imaginary off-screen piles. we also introduce an extension that allows pda owners to transfer information piles to and from a shared tabletop display.
ujudge: a voting system for audience members of the 2004 olympics. in this paper, the methodology and process used to create a voting system for the olympic games to be held in athens will be addressed. initially, the problem space, including the user experience and context, will be defined, to help guide the design team. having defined the problem space, a survey of the available technology and infrastructure will be explored. a framework built from design principles and requirements will be used to guide the design process. next, the prototype and system will be discussed, followed by usability testing and a final solution - ujudge, an innovative voting system which contains several components: a central server, handheld devices, jumbotron, and wi-fi infrastructure.
a haptic memory game using the stress tactile display. a computer implementation of a classic memory card game was adapted to rely on touch rather than vision. instead of memorizing pictures on cards, players explore tactile graphics on a computer-generated virtual surface. tactile sensations are created by controlling dynamic, distributed lateral strain patterns on a fingerpad in contact with a tactile display called stress2. the tactile graphics are explored by moving the device within the workspace of a 2d planar carrier. three tactile rendering methods were developed and used to create distinct tactile memory cards. the haptic memory game showcases the capabilities of this novel tactile display technology.
object manipulation in virtual environments: human bias, consistency and individual differences. this paper investigates human bias, consistency and individual differences when performing object manipulation in a virtual environment. eight subjects were asked to manipulate a wooden cube to match a 3-d graphic target cube presented in 3 locations and 2 orientations. there were two visual conditions for the experiment: the subject performed the tasks with or without vision of the hand and the wooden cube. the constant errors of object translation and orientation suggested specific human biases. in terms of the variable errors, visual feedback appeared to be more critical for object transportation than object orientation. it was also found that individual differences were more pronounced in human bias than in consistency during object manipulation. these results suggest tolerance for human bias and variability should be accommodated in human-computer interface design.
communicating emotions in online chat using physiological sensors and animated text. we present a chat system that uses animateddynamic text associated with emotional information to show the affective state of the user. the system obtains the affective state of a chat user from a physiological sensor attached to the user's body. this paper describes preliminary experiments and provides examples of possible applications of our chat system. observations from informal experiments comparing our animated chat system with a conventional system suggest that an online interface that conveys emotional information helps online users to interact with each other more efficiently.
designing a generalized 3d carousel view. in this paper we describe a 3d carousel view design. we take the basic carousel model and elaborate it to hold an arbitrary number of items in an efficient manner. we equip this model with various interaction methods and a novel component: the termination marker. we also explore more detailed design issues, like animation, by implementing a prototype. we report essential user feedback and how it affected our design.
nreader: reading news quickly, deeply and vividly. in this paper we present our design of a novel system, named nreader, to help people read online news. according to researches on news recommendation and a newly deployed survey on user's feeling and requirement about current news reading style, we build our system by adding extra feature to the framework of the popular rss (rich site summary) system.we designed corresponding views in our reading tools to support browsing mode and intensively reading mode. after a preliminary user testing, the feedback is encouraging. a wider and more delicate user study will be performed to boost our system and interface to give user a more convenient and comfortable online news reading experience.
public social private design (pspd). we present a computer-based tool for the support of collaborative sketching activities in design: public social private design (pspd). we provide an overview of the empirical studies that have informed the development of pspd. we present the current version of pspd, briefly report an initial evaluation and highlight future developments and studies.
navigation via continuously adapted music. listening to music on personal, digital devices while mobile is an enjoyable, everyday activity. we explore a scheme for exploiting this practice to immerse listeners in navigation cues. our prototype, ontrack, continuously adapts audio, modifying the spatial balance and volume to lead listeners to their target destination. an initial lab-based evaluation has demonstrated the approach's efficacy: users were able to complete tasks within a reasonable time and their subjective feedback was positive. encouraged by these findings, we are building a pocket-sized prototype for further testing.
visual resonator: interface for interactive cocktail party phenomenon. we present visual resonator (vr), an auditory interface that promises to provide an interactive realization of the cocktail party phenomenon. the wearer of this interface can hear a voice or auditory information only from the direction in which he/she is facing, and can send his/her voice only in the direction towards which he/she is facing. in addition, individuals who are within sight of each other can have a conversation, even if they are not close enough to talk directly, since an infrared signal is used to transmit the auditory information.
in the lab and out in the wild: remote web usability testing for mobile devices. in this paper we discuss a pilot usability study using wireless internet-enabled personal digital assistants (pdas). we compared usability data gathered in traditional lab studies with a proxy-based clickstream logging and analysis tool. we found that this remote testing technique can more easily gather many of the content-related usability issues, but device-related issues are more difficult to capture.
evaluating real-time multimedia audio and video quality. the aim of this research is to assess and establish quality thresholds for real-time internet audio and video. real-time multimedia conferencing over the internet has huge potential, but there are limitations to the quality of audio and video that can be achieved, due to bandwidth limitations and the processing power of individual workstations. assessing the effects of these limitations on the conference participant is not straightforward. the novel types of degradation found over the internet means that existing speech and video quality assessment methods may not be applicable to multimedia conferencing experiences. this phd will assess existing tests for measuring perceived quality from the psychology and telecommunications literature with respect to multimedia conferencing. the long term aim is to produce guidelines as to required bandwidth and quality for different multimedia conferencing tasks and applications.
conversation thumbnails for large-scale discussions. we present a new interface for large-scale online conversations. our technique, the conversation thumbnail, differs from existing discussion interfaces in two respects. first, it employs a focus+context visualization technique that exploits message-level metadata to provide an easily navigable overview of a discussion. second, it helps reduce conversational redundancy and improve coherence via a fast automatic search mechanism that highlights related messages during message composition. the conversation thumbnail viewer is currently implemented as a java applet that can be applied to a variety of discussion data sources.
passwords you'll never forget, but can't recall. we identify a wide range of human memory phenomena as potential certificates of identity. these "imprinting" behaviors are characterized by vast capacity for complex experiences, which can be recognized without apparent effort and yet cannot be transferred to others. they are suitable for use in near zero-knowledge protocols, which minimize the amount of secret information exposed to prying eyes while identifying an individual. we sketch several examples of such phenomena[1-3], and apply them in secure certification protocols. this provides a novel approach to human-computer interfaces, and raises new questions in several classic areas of psychology.
user centered design at european patent office. this paper describes how a large organisation implemented a user centered design process initiative to meet the business goals of minimising training for users.
audio tools for sports fan interaction. in this paper we describe the process of conceptualizing, testing and designing an audio-based online chat system for a virtual community of sports fans.
patterns in practice: a workshop for ui designers. this one-day workshop focuses on how ui designers are using patterns today. the scope includes the two overlapping areas of concern to design practitioners: (1) writing valid and useful patterns and (2) using patterns effectively in a design assignment.
a meeting browser evaluation test. we introduce a browser evaluation test (bet), and describe a trial run application of the test. bet is a method for assessing meeting browser performance using the number of observations of interest found in the minimum amount of time as the evaluation metric, where observations of interest are statements about a meeting collected by independent observers. the resulting speed and accuracy scores aim to be objective, comparable and repeatable.
a comparison of information visualization methods. large hierarchies of information (such as maps, graphs, amd web pages) that must be fit onto small areas are present everywhere. the size restriction prevents the user from viewing the entire structure at once, which causes the context of the information to be lost. conversely, if the entire structure is visible all at once, the details are too small to read and specific information is lost to the user. the present research studies different visualization techniques that present detailed specific information from large hierarchies on a single screen, while preserving the information's context within the global structure. results show that internet explorer supported superior user performance in both time and accuracy when compared to three other methods of information visualization.
comprehension and usability variances among multicultural web users in south africa. a usability test was performed to evaluate the effectiveness of a web site in terms of language-use by multicultural users. the results indicated that south african web site developers should take cognisance of the fact that afrikaans-speaking people find it easier to search for information in afrikaans (in contrast to english). it seems, however, that there is no need to translate web sites into an african language.
user experiences with sharing and access control. the sharing of network-based information is a key component of recreational and professional interaction, from email attachments to p2p networks. however, people need to accommodate technical challenges in successful and secure content sharing. in particular, people have to manage access control policies that are both social and technical: deciding what to share and who to share it with, and how to technically effect their decisions. in this paper, we focus on the usability of access control: how people manage file sharing among various groups, organizations, and tasks. we present survey and interview data regarding content sharing and content protection, and discuss the implications for the design of networked collaboration tools.
scroll ring performance evaluation. this study compares a touchpad scroll ring to a mouse scroll wheel and touchpad scroll zone using a fitts' law testing methodology. time, error, and subjective results reveal that the scroll ring offers the most performance advantages over the scroll wheel and scroll zone.
imagery saystems for enhanced crewmember habitability, performance and productivity on iss. in this paper, a description is provided for the process of determining the functional and technical requirements for an imagery system onboard the international space station (iss). with the advent of the iss and the experience of russian, european, and us crewmembers on mir, the importance of the psychological element in long duration missions is increasingly recognized. an imagery system could enhance the habitability, performance, and productivity for long term stays in space. because this is type of system is a new concept for space, functional and technical requirements need to be explored.
introducing hci in technical university of szczecin, poland. with a couple of noble exceptions, in polish academic world the issues of hci, usability and user-centered development are still nonexistent. the following paper describes author's efforts to introduce hci in technical university of szczecin, poland, along with lessons learned and suggestions on how the efforts can be improved in the future.
vista: interactive coffee-corner display. in the contemporary information-saturated world, there is a need for an easier, faster, and more social way to keep office workers updated and better aware of surrounding activities. today's information management systems tend to consume time rather than simplify information sharing.the vista system tries to solve this problem. it is designed to be used in places of social interaction, where it displays information about professional activities happening in the department. in this paper, the origins of the project, the user-centered design process, and iterative evaluation of the concept are described. the paper concludes with observations regarding the social acceptance of vista and reflections on future research aspects.vista is the result of a design project conducted in cooperation between the user-system interaction postgraduate program at eindhoven university of technology, and the research group of océ technologies in the netherlands.
an hour in the life: towards requirements for modelling multiple task work. it is accepted that changes in technology, work practices and the general socio-economic environment affect the way we plan and perform tasks. support, opportunity and pressure for people to 'multitask' has increased. we cannot assume that because an it is designed well for a single-user single-task perspective, that it will effectively support multitasking. some work has been undertaken into understanding these phenomena in a hci context, but with little permeation into mainstream hci methods. this paper provides an interim report into work into multiple task phenomena within the task knowledge structures task analysis approach.
the message center: enhancing elder communication. the message center is a home-based communication solution specifically designed for elders. our research indicates that insufficient communication amongst elders causes several challenges in their daily activities such as loneliness, social isolation, and decreased appetite. the biggest cause of these challenges is that elders are increasingly removed from communication technology including email, text messaging, and mobile phones due to cognitive and physical difficulties. to overcome this problem, we incorporate a familiar pen and paper based interaction that allows instantaneous messaging via digital network. by designing the message center, we strive to create an easier venue for more active cross-generational communication between elders and younger family members who are often the caregivers. this paper demonstrates a user sensitive inclusive design process from the generation of user needs to the evaluation of prototypes. a key theme of the message center project is to show how usable and emotional design derived from a user inclusive design process can encourage elders to adopt new communication technology.
photo annotation on a camera phone. in this paper we describe a system that allows users to annotate digital photos at the time of capture. the system uses camera phones with a lightweight client application and a server to store the images and metadata and assists the user in annotation on the camera phone by providing guesses about the location and content of the photos. by conducting user interface testing, surveys, and focus groups we were able to evaluate the usability of this system and uncover usage patterns and motivations that will inform our development of future mobile media annotation applications. in this paper we present usability issues encountered in using a camera phone as an image annotation device immediately after image capture and users' responses to use of such a system.
exploring wearable ambient displays for social awareness. mobile phones represent not only a means of communication, but an increasingly omnipresent computing platform, enabling diverse modes of communication including ambient displays that are tied to bodies and social groups, rather than physical environments. as an example of such a display, we present damage, a prototype device for mobile ambient awareness of a social group, and discuss design considerations for such devices.
msn 9: new user-centered desirability methods produce compelling visual design. the msn user experience team developed new user-centered methods to provide structured user input on the visual design of the newly-released msn explorer, an integrated software package. in the final product, users rated "appearance" above all of the product's features. this case describes how the msn user experience team derived a design direction to set the most appropriate pace of visual change for millions of users with widely variant preferences. it discloses how these new methods maximized the product's visual appeal to the widest segment of the potential user base. the methods included design mark-up, a semantic design-description task, a statement rating task, a semantic desirability group card sort task, and a modified focus group discussion. this case documents the value of these new methods in predicting user reaction to visual design. lessons learned from this collaboration are discussed from three perspectives: user experience management, design and usability.
designing effective haptic interaction: inverted damping. in this paper, we describe a new force-feedback technique termed "inverted damping", which aids users in manually selecting specific items from within a range of possible choices. typically, the identity of the goal item is not known beforehand by the system. the technique therefore infers users' intentions from the type of movements carried out and increases the amount of resistance provided as the speed of the user's movements decreases. although the technique might initially sound counter-intuitive, the results of the experiment, reported in this paper, confirm the effectiveness of this approach. we believe that this new technique is likely to have beneficial and wide-ranging applicability across a wide range of devices in everyday life.
pointing without a pointer. we present a method for performing selection tasks based on continuous control of multiple, competing agents who try to determine the user's intentions from their control behaviour without requiring an explicit pointer. the entropy in the selection process decreases in a continuous fashion -- we provide experimental evidence of selection from 500 initial targets. the approach allows adaptation over time to best make use of the multimodal communication channel between the human and the system. this general approach is well suited to mobile and wearable applications, shared displays and security conscious settings.
evaluating images of virtual agents. this study examined the perceived attributes of virtual agents, based on their appearance. the aim was to determine the nature of the psychological processes that influence judgements. it was expected that many of the usual characterisitics of stereotypical judgements would influence attributions made with regard to computer agents. fourteen agents from a population of 150 were used to obtain similarity judgements, preference data, dimensional analysis, and personality judgements. multidimensional scaling analysis suggested that computer agents were categorized according to 2 main dimensions (gender and anthropomorphism). the clustering of agents were across dimensions predicted attributions made, with more positive attrbutions made to female agents, less positive to cartoon agents, and the most negative responses to male agents.
a context-aware recognition survey for data collection using ubiquitous sensors in the home. identifying what people do in the home can both inform ubiquitous computing application design decisions and provide training data to the machine learning algorithms used in their implementation. this paper describes an unsupervised technique in which contextual information gathered by ubiquitous sensors is used to help users label a multitude of anonymous activity episodes. this context-aware recognition survey is a game-like computer program in which users attempt to correctly guess which activity is happening after seeing a series of symbolic images that represent sensor values generated during the activity. we report a user study of the system, focusing on how well subjects were able to recognize their own activities, the activities of others, and counterfeits that did not correspond to any activity.
mspace mobile: a ui gestalt to support on-the-go info-interaction. mspace mobile interaction presents a ui gestalt of 7 techniques for mobile/on-the-move information retrieval and assessment that enables multiple views of the information within a persistent focus+context viewer. it uses the web but breaks the web page paradigm to support effective rapid triage.
hotwire: an apparatus for simulating primary tasks in wearable computing. in this paper we present a novel apparatus for simulating real world primary tasks typically found in wearable computing. additionally, we report on a preliminary interruption study using the new apparatus in a laboratory experiment and compare its results with previous work to show its applicability for research in human-computer interaction for wearable computers.
integration of browsing, searching, and filtering in an applet for web information access. improvements to information access on the world wide web has to be considered one of today's strategic challenges. in this paper we present a java applet called amit (animated multiscale interactive treeviewer) that integrates fisheye tree browsing with search and filtering techniques. used in combination with a web walker, a search server, and a tree server, it shows promise as a scalable solution to information access in configurable web spaces.
usability in practice: field methods evolution and revolution. field methods are a collection of tools and techniques for conducting studies of users, their tasks, and their work environments in the actual context of those environments. the promise of such methods is that they help teams design products that are both useful and usable by providing data about what people really do. participants in this forum will address: the origins and framework of contextual designthe application of field methods to task analysisa review of ways to adapt these methods to practical constraintsa discount approach to field studies.
in your own words: using full sentences as feedback. many applications have cluttered dialogs that require users to make complicated settings. some settings even determine the availability and state of other settings, creating interdependencies that can be hard to discern. most afforadances, although they aid the use of individual widgets, provide no feedback about overall configurations. here i present a technique for providing feedback in configuration tools using grammar-generated sentences that update instantly as the user acts. experimental results confirm the technique has promise.
the benefits of physical edges in gesture-making: empirical support for an edge-based unistroke alphabet. people with motor impairments often cannot use a keyboard or a mouse. our previous work showed that a handheld device, connected to a pc, could be effective for computer access for some people with motor impairments. but text entry was slow, and the popular unistroke methods like graffiti proved difficult for some people with motor control problems. we are now investigating how physical edges can provide stability for stylus gestures, and we are designing a unistroke alphabet whose letter-forms are defined along the edges of a small plastic square hole. this paper presents data on the benefits of physical edges in making gestures. it then describes edgewrite, a new unistroke alphabet designed to leverage physical edges for greater stability in text entry.
maximizing the guessability of symbolic input. guessability is essential for symbolic input, in which users enter gestures or keywords to indicate characters or commands, or rely on labels or icons to access features. we present a unified approach to both maximizing and evaluating the guessability of symbolic input. this approach can be used by anyone wishing to design a symbol set with high guessability, or to evaluate the guessability of an existing symbol set. we also present formulae for quantifying guessability and agreement among guesses. an example is offered in which the guessability of the edgewrite unistroke alphabet was improved by users from 51.0% to 80.1% without designer intervention. the original and improved alphabets were then tested for their immediate usability with the procedure used by mackenzie and zhang (1997). users entered the original alphabet with 78.8% and 90.2% accuracy after 1 and 5 minutes of learning, respectively. the improved alphabet bettered this to 81.6% and 94.2%. these improved results were competitive with prior results for graffiti, which were 81.8% and 95.8% for the same measures.
flexible interface/application design for online awards catalog. a catalog of merchandise used for incentive programs has been in the carlson companies product line for 65 years. this is a direct outgrowth of the gold bond stamp incentive program our company was founded on.in 2002, we decided to improve the user experience for the online awards catalog and solve application maintenance issues as there grew to be more than 50 iterations of the catalog interface and numerous versions of application code. the old interfaces proved to be inflexible, time consuming to maintain, and could no longer meet client's needs.therefore, the goal of our redesign project was to create a flexible interface and application framework that would improve the online catalog's user experience, mimic the client's corporate style guides to allow better integration with the client's own web properties, and provide a better approach for adding new functionality and maintaining existing awards catalog sites.
depictive interaction with visual information using sketches - divius. querying of visual databases has relied predominantly on text based systems. words do not provide an appropriate or adequate means of describing visual artifacts. a system (divius) has been developed which allows users to describe and query objects in a pictorial database, using a visual language derived from the database objects. users can also indicate their level of uncertainty regarding certain attributes of the query.
modeling analyst performance for usability inspection. this research takes an analyst-centred approach to improving usability inspection methods. the research approach adopts novel instruments and methods, especially manipulation and monitoring of analyst's knowledge resources during usability inspection. the research aims to develop and validate a predictive model of analyst performance that supports improvement of usability inspection, resulting in a positive impact on design quality.
document co-organization in an online knowledge community. we introduce the concept of "document co-organization" and describe such a system. by document co-organization we mean that individuals are allowed to hierarchically organize documents personally and share their hierarchies with others, while the system generates a "consensus" hierarchy from these personal hierarchies, which provides a full, common, and emergent view of all documents. by allowing users to retrieve documents from their own organization (hierarchy), another user's, the consensus hierarchy, or a time-based hierarchy, we provide access corresponding to different characteristics of knowledge tasks: they are personal, collective, social, and time-sensitive. in a class website experiment, we show that for a complex knowledge task, hierarchies are used more frequently than search. one surprising finding is how often students use others' personal hierarchies.
tangible programming elements for young children. tangible programming elements offer the dynamic and programmable properties of a computer without the complexity introduced by the keyboard, mouse and screen. this paper explores the extent to which programming skills are used by children during interactions with a set of tangible programming elements: the electronic blocks. an evaluation of the electronic blocks indicates that children become heavily engaged with the blocks, and learn simple programming with a minimum of adult support.
visualization techniques for collaborative trajectory management. we developed a set of visualization techniques to portray multiple threads or trajectories of events and activities to provide awareness support. visualizing the historical and projected temporal patterns of trajectories may provide support to collaborating workers and promote anticipatory behaviors.
sheep and wolves: test bed for human-robot interaction. this paper presents a dynamic experimental test bed for exploring and evaluating human-robot interaction (hri). our system is designed around the concept of playing board games involving collaboration between humans and robots in a shared physical environment. unlike the classic human-versus-machine situation often established in computer-based board games, our test bed takes advantage of the rich interaction opportunities that arise when humans and robots play collaboratively as a team. to facilitate interaction within a shared physical environment, our game is played on a large checkerboard where human and robotic players can be situated and play as game pieces within the game. with meaningful interaction occurring within our confined setup, various aspects of human-robot interaction can be easily explored and evaluated such as interface methods. we also present the results of a user evaluation which shows the sensitivity of our system in assessing robotic behaviours.
an unencumbering, localized olfactory display. olfaction is considered to be an important sensory modality in next-generation virtual reality (vr) systems. we currently focus on spatiotemporal control of odor, rather than capturing and synthesizing odor itself. if we simply diffused the odor into the atmosphere, it would be difficult to clean it away in a short time. several olfactory displays that inject the scented air under the nose through tubes have been proposed to realize spatiotemporal control of olfaction, but they require the user to wear something on one's face. here, we propose an unencumbering olfactory display, by conveying a clump of scented air from a certain remote place to the user's nose. to implement this concept, we used an "air cannon" that generates toroidal vortices of the scented air. we conducted a preliminary experiment to examine the possibility of this method's ability to display scent to a restricted space. the result shows that we could successfully display incense to the target user.
multiple perspectives for collaborative navigation in cve. drawn from empirical studies on spatial cognition, this work explores ways of dynamically integrating others' perspectives and incorporating different views into a single interface for a 3d cve user. it also designs an empirical study to test the effectiveness of different perspective displays on collaborative navigation performance.
deciphering visual gist and its implications for video retrieval and interface design. how do people make sense of a video based on viewing a few frames of that video? what elements constitute the "visual gist" in their minds? answers to these questions will give implications to both content-based video retrieval and the interface design (e.g., key-frame selection) of digital video libraries. a preliminary study was conducted to unravel the issues and 45 subjects participated in the study. after viewing a fast forward surrogate, the subjects were asked to choose pictures which they thought would "belong to" the video. and they were also asked to think aloud during their selection processes. nine visual gist attributes (e.g., people, objects and actions) were generated using the grounded theory method and their frequencies were also compared and analyzed.
private communications in public meetings. out-of-band communication during audio conferences can improve the effectiveness of distributed meetings. it provides a means for people to privately consult with one another, supports breakout sessions, and allows individuals to resolve problems without interrupting the discussion. conversely, off-topic chat and poorly timed interruptions can degrade meeting effectiveness. we considered these trade-offs in adding a private text chat capability and a novel, multi-channel voice chat feature to the meeting central collaboration suite. in this paper, we explain the motivation behind adding these features and then describe our initial implementation, the usability and field testing we conducted, and the changes that we made as a result of that user research.
toss-it: intuitive information transfer techniques for mobile devices. in recent years, mobile devices have rapidly penetrated into our daily lives. however, several drawbacks of mobile devices have been mentioned so far. the proposed system called toss-it provides intuitive information transfer techniques for mobile devices, by fully utilizing their mobility. a user of toss-it can send information from the user's pda to other electronic devices with a toss or swing action, as the user would toss a ball or deal cards to others. this paper describes the current implementation of toss-it and its user studies.
a picture is worth a thousand keywords: image-based object search on a mobile platform. finding information based on an object's visual appearance is useful when specific keywords for the object are not known. we have developed a mobile image-based search system that takes images of objects as queries and finds relevant web pages by matching them to similar images on the web. image-based search works well when matching full scenes, such as images of buildings or landmarks, and for matching objects when the boundary of the object in the image is available. we demonstrate the effectiveness of a simple interactive paradigm for obtaining a segmented object boundary, and show how a shape-based image matching algorithm can use the object outline to find similar images on the web.
ideixis: image-based deixis for finding location-based information. we demonstrate an image-based approach to specifying location and finding location-based information from camera-equipped mobile devices. we introduce a point-by-photograph paradigm, where users can specify a location simply by taking pictures. our technique uses content-based image retrieval methods to search the web or other databases for matching images and their source pages to find relevant location-based information. in contrast to conventional approaches to location detection, our method can refer to distant locations and does not require any physical infrastructure beyond mobile internet service. we have developed a prototype on a camera phone and conducted user studies to demonstrate the efficacy of our approach compared to other alternatives.
gaze estimation model for eye drawing. this paper describes a model that can be employed in eye drawing software applications. unlike most of the existing interfaces for eye typing, eye drawing focuses on small target selection and moves the cursor to a precise location. this is made possible by a proposed gaze estimation model which interprets users' interest when they want to draw new objects in a particular position.
supporting intercultural computer-mediated discourse: methods, models, and architectures. we use the term "intercultural" instead of "cultural" to emphasis the dialogical relationship of at least two participants from different cultures in computer-mediated communication and cooperation contexts. supporting intercultural computer-mediated communication (i-cmc) requires, on the one hand, the understanding of both enabling and constraining aspects (barriers) of such a dialogical situations, and calls for, on the other hand, new ideas for tools, architectures, etc., which may support, promote or enable computer-mediated intercultural communication and cooperation.this workshop explores the challenges in the intercultural computer-mediated communication and cooperation environments and will provide a platform for discussing empirical insights into the intercultural communication barriers and practical and theoretical works for new designs, tools and architectures that aims at overcoming them and enabling computer-mediated intercultural communication and cooperation.
from creating virtual gestures to "writing" in sign languages. sign languages have been proven to be natural languages, as capable of expressing human thoughts and emotions as traditional languages are. the distinct visual and spatial nature of sign languages seems to be an insurmountable barrier for developing a sign language "word processor". however, we argue that with the advancement of computer graphics technology and graphical implementations of linguistic results obtained from the study of sign languages, "writing" in a sign language should not be difficult. we have pursued exploratory work in constructing virtual gestures, applying hand constraints to facilitate the creation of natural gestures, and combining these gestures into meaningful american sign language (asl) parts that follow the asl movement-hold model. the results, although preliminary, are encouraging. we believe that space effective sign language composition is possible space with the implementation of easy-to-use graphical user interfaces and the development of specialized data management methods.
2004 athens 'diskos': olympic voting kit. the proposed system allows spectators to cast votes in real time. the results serve only for entertainment purposes to show the difference between the spectators' and judges' scores and will not affect the official judging. the design of the judging system is flexible enough to be used for both diving and gymnastics competitions. it is cost-efficient, accessible to an international audience, reliable, easy to understand, tamper resistant and eco-friendly. the system consists of a booklet with a game description, voting rules and a rotating disk, which employs rfid technology and an integrated sensor. to vote, the spectator turns the wheel to set the score and then via a send button transmits it to receivers placed at strategic positions from which a central computer collects the data, sums it up and calculates the results. these results are subsequently displayed on a big screen next to the judges' results. when leaving the arena, the spectator can either return the device to special bins or take it home as a souvenir.
effect of latency of response on life-like communication using a dog-like robot. using a dog-like robot, the effectiveness of latency of response for life-like communication was examined. the participant touched the robot's head, it lifted up the head, and he/she evaluated its from the point of living and intention. as results, the effect of latency of response was not clear because of a variety of life-like impressions. the life-like response seemed to be emotional, but at least two kinds of emotions could be perceived. negative emotion was seen in shorter latency as well as in longer latency. life-like impression was not the same as perceptual intention. these findings should be investigated in the situation properly simulated the communication, not in a simple and single reaction.
single complex glyphs versus multiple simple glyphs. designers of information visualization systems have the choice to present information in a single integrated view or in multiple views. in practice, there is a continuum between the two strategies and designers must decide how much of each strategy to apply. although high-level design guidelines (heuristics) are available, there are few low-level perceptual design guidelines for making this decision. we performed a controlled experiment with one, two, and four views to evaluate the strengths and weaknesses of these strategies on target detection and trend finding tasks in the context of multidimensional glyphs overlaid onto geographic maps. results from the target detection tasks suggest that visual encoding is a more important factor when detecting a single attribute than the number of views. additionally, for detecting two attributes, the trend indicates that reusing the most perceptually salient visual feature in multiple views provides faster performance than an integrated view that must map one of the attributes to a less salient feature.
improving web accessibility using content-aware plug-ins. this paper describes a novel approach to improve blind and visually impaired people's access to the web by using a content-aware web browser plug-in coupled with audio and haptic tools. the web plug-in accesses the current mouse position on-screen, and makes the co-ordinates available to the audio and haptic modalities. this allows the user to be informed when they are in the vicinity of an image or hyperlink; previously they would only have been informed when they are physically on the link. thus, when the user is close to an image or hyperlink, haptics and audio will be used to inform and guide them to the actual spatial position. the web browser plug-in and the associated audio and haptic feedback tools are described in the paper. finally, results from a pilot study on the usability of this system are also presented.
emoticons convey emotions without cognition of faces: an fmri study. in this paper, we describe the brain activities that are associated with emoticons by using functional mri (fmri). in communication over a computer network, we use abstract faces such as computer graphics (cg) avatars and emoticons. these faces convey users' emotions and enrich their communications. in particular, when we see some abstract faces, we feel that they are more vivid and lively than photorealistic faces. however, the manner in which these faces influence the mental process is as yet unknown. in this research, we conducted an experiment by using fmri for the most abstract faces?emoticons. the experimental results show that emoticons convey emotions without the cognition of faces. this result is very important in order to promote an understanding of how abstract faces affect our behaviors.
a usability evaluation method for e-learning: focus on motivation to learn. in this paper the development of a questionnaire-based usability evaluation method for e-learning applications is described. the method aims at extending the current practice by proposing intrinsic motivation to learn as a new usability measure to evaluate e-learning designs. the method was developed according to an established methodology in hci research and relied upon a conceptual framework that combines web and instructional design parameters and associates them with a main affective learning dimension, intrinsic motivation to learn. two large empirical studies were conducted in order to test the method. results provide significant evidence for reliability of the method. further work focuses on validation process so that usability practitioners can use it with confidence when evaluating the design of e-learning applications.
age-centered research-based web design guidelines. this paper presents the methodology and the results of the development of a set of age-centered research-based web design guidelines. an initial set of guidelines was first developed through careful literature review of the hci & aging literature. then a series of classification methods (card sorting, affinity diagrams) were employed as a means for obtaining a revised and more robust classified set of guidelines. finally the revised set of guidelines and the original set were tested through their application to a number of age-related websites.
towards knowledge building in professional groups. in this submission for the chi05 development forum, i reflect on my experience leading the experience design community of interest of the american institute of graphic arts and suggest that the focus of the group needs to shift in order to successfully accomplish our mission.
story lifecycle in a product development organization. this poster describes an integrated set of stories and story-based activities that we have used in product development in ibm software group's lotus product organizations. we use five types of stories (stories from the field, concept stories, design-exploration stories, partner-integration stories, and product demonstrations). we describe the "inputs" and "outcomes" of each stage of our developing "story lifecycle," illustrating our method with multiple case studies.
city lights: contextual views in minimal space. city lights are space-efficient fisheye techniques that provide contextual views along the borders of windows and subwindows that describe unseen objects in all directions. we present a family of techniques that use a range of graphical dimensions to depict varied information about unseen objects. city lights can be used alone or in conjunction with scrollbars, 2d overview+detail, and interaction techniques such as zoomable user interfaces.
dual stream input for pointing and scrolling. to find ways to improve users' performance of tasks that involve both scrolling and pointing, we studied three dual-stream input methods, with one stream for pointing and one for scrolling. the results showed that a mouse augmented with a tracking wheel did not outperform the conventional single stream mouse. two other methods, a mouse with an isometric rate-control joystick and a two handed system significantly improved users' performance.
producing human-centered, usability-sensitive, and hci-competent managers, cios, and ceos. taking a collaborative and multi-disciplinary perspective, we discuss issues and opportunities in college education so that our future managers, cios, and ceos are inherently and intrinsically human-centered, usability-sensitive, and hci-competent.
swim: fostering social network based information search. compare to searching online information directly, asking friends or finding referral to a human expert is preferred in many information-gathering tasks. it's easier to judge the quality of the information from a personal referral as well as to obtain information that is not publicly published [1]. instant messaging (im) has potentials to effectively support such social network based information seeking [3], which are not fully explored other than providing better communications. for instance, a user usually does not know what his friends' friends know. if none of his friends in his im buddy list knows the sought information, he either gives up this search method or needs intensive personal helps from a friend who transfers questions and answers in between.previous studies indicated that it is feasible to add social network search functionalities to im systems. watts et al. [2] found that social networks have the surprising property of being searchable. systems such as referralweb [1], show that it is possible to mine people's social relationships and information identities from electronic resources and use them for referral or matchmaker purposes. based on these ideas, we designed and implemented the small world instant messenger (swim).
the effectiveness of multiscale collaboration in virtual environments. adding multiscale capabilities to collaborative virtual environments can potentially help people work on very large electronic worlds. our experiment shows that the user performance on cross-scale tasks is indeed improved.
info-lotus: a peripheral visualization for email notification. we designed a peripheral notification visualization called "info-lotus". the info-lotus is an aesthetically pleasing visualization that offers users a "glance-able" overview of incoming emails of interest in a non-disruptive manner. the goal is to strike a balance among three critical parameters: interruption, reaction, and comprehension. we first present the design of the info-lotus. we then discuss the usability study that compares the "toast" notification in microsoft office outlook with the info-lotus. finally, we present a redesign for an improved info-lotus, based on the feedbacks of the user study.
imlooking: image-based face retrieval in online dating profile search. textual search, the approach used by the majority of existing online dating sites, successfully covers a variety of attributes, such as age range and gender, but falls short when searching for facial features. meanwhile, by using images as the query in a search, current image-based face-retrieval applications ease the challenge of textual description from users, but only focus on finding the same person. we believe there is a gap that needs to be filled in image-based face retrieval to further support the interpersonal search scenarios on internet dating sites. therefore, we are introducing a profile search prototype -- imlooking - using an augmented image-based face retrieval filter. first, we present a prototype design and offer technical support. in a user study, participants quickly felt at home in user interface and acclimatized to the way the prototype operates. in addition, they reported they enjoyed the interaction process.
interactive sonification of geo-referenced data. this paper describes an investigation of using interactive sonification (non-speech sound) to present geo-referenced statistical data to vision-impaired users for problem solving and decision making. by working with vision-impaired users, the work will identify effective interaction and sound designs for geo-referenced data, and derive principles that can guide general interactive data sonification designs for auditory information seeking.
exploratory inspection: a learning model for improving open source software usability. we contend that overcoming the lack of usability expertise within the open source software community will further its competitiveness. motivated by the unique user-driven model, we propose an exploratory learning method for assisting non-expert users in contributing to open source usability inspection. this method emphasizes providing usability knowledge during usability inspection and explores the impact of the "fading-out/phasing-in" method on the inspection effectiveness. the results of a pilot study we conducted through a web-based inspection system are provided.
the design of an interactive and dynamic representation of the firm. interpretation and audit of financial information is a significant undertaking that must rest on a fuller understanding of the firm and its operations. a pictorial representation of firm activity offers promise for supporting this requirement. after reviewing the literature related to visualizations, we describe the design of an interactive animated version of the cycle model. business animator assists users in developing an intuitive sense about the cycle model itself, while exploring and visualizing how firms at various stages of growth, sustenance, and decay are affected by specific operating decisions. principles and findings from the accounting and information systems literatures were used to drive the design of the representation and software used to control it. this resulting system adds depth to traditional accounting representations by conveying information about the momentum of the firm's activities, the rate of change at which various activities are occurring. the animation facilitates identification of backlogs or breaks in operating processes, thus increasing understanding of the firm's financial health.
"i hear the pattern": interactive sonification of geographical data patterns. interactive sonification (non-speech sound) is a novel strategy to present the geographical distribution patterns of statistical data to vision impaired users. we discuss the design space with dimensions of interaction actions, data representation forms, input devices, navigation structures, and sound feedback encoding. two interfaces were designed, one using a keyboard and another using a smooth surface touch tablet. a study with three blind users shows that they are able to perceive patterns of 5-category values on both familiar and unknown maps, and learn new map geography, in both interfaces.
an experiment in discovering personally meaningful places from location data. as mobile devices become location-aware, they offer the promise of powerful new applications. while computers work with physical locations like latitude and longitude, people think and speak in terms of places, like "my office" or ``sue's house''. therefore, location-aware applications must incorporate the notion of places to achieve their full potential. this requires systems to acquire the places that are meaningful for each user. previous work has explored algorithms to discover personal places from location data. however, we know of no empirical, quantitative evaluations of these algorithms, so the question of how well they work currently is unanswered. we report here on an experiment that begins to provide an answer; we show that a place discovery algorithm can do a good job of discovering places that are meaningful to users. the results have important implications for system design and open up interesting avenues for future research.
matrix browser: visualizing and exploring large networked information spaces. we present a new approach for visualizing and exploring large networked information structures which may represent, for instance, linked information resources or metadata structures such as ontologies. an interactive matrix display is used for showing relations between concepts and concept hierarchies displayed along the two axes of a matrix. initial user testing shows performance advantages as well as reduced visual search in comparison to conventional graph representations.
bodybeats: whole-body, musical interfaces for children. this work in progress presents the bodybeats suite--three prototypes built to explore the interaction between children and computational musical instruments by using sound and music patterns. our goals in developing the bodybeats prototypes are (1) to help children engage their whole bodies while interacting with computers, (2) foster collaboration and pattern learning, and (3) provide a playful interaction for creating sound and music. we posit that electronic instruments for children that incorporate whole-body movement can provide active ways for children to play and learn with technology (while challenging a growing rate of childhood obesity). we describe how we implemented our current bodybeats prototypes and discuss how users interact with them. we then highlight our plans for future work in the fields of whole-body interaction design, education, and music.
myinfo: a personal news interface. we present a novel interface design for myinfo, a personal news application that processes and combines content from tv and the web. myinfo provides personalized content selectable by topic such as weather or traffic. in addition, users can play back a personal news program as a tv show, leaving themselves free to complete tasks such as making breakfast. we detail our design process from concept generation to focus group exploration to final design. the main design challenges include (i) understanding what kinds of tv/web applications people want, and (ii) developing an interface that fits people's lifestyles.
exposing profiles to build trust in a recommender. this paper describes a method for increasing trust in a tv show recommender. we look for people in common between programs users watch and new programs that are highly rated by our tv show recommender. we then present these to users in a conversational sentence, helping them decide if they want to try the new show. this method has been implemeted in our current tv show recommender interface and will be tested in the near future.
whither or whether hci: requirements analysis for multi-sited, multi-user cyberinfrastructures. cyberinfrastructures bring together distributed resources to support scientific discoveries. cyberinfrastructures currently under development are intended to enable the cooperative work of diverse users over long periods of time. we analyze the challenges that cyberinfrastructures present to existing methods of user requirements analysis.
toward a unified universal remote console standard. wireless communication technologies make it feasible to remotely control devices and services from virtually any mobile and stationary device. however, there is no stan-dard available today which would allow manufacturers to define an abstracted user interface for their product whose functionality can be instantiated and presented in different ways and modalities on a wide variety of controller tech-nologies, such as, phones, pdas, and computers. such a standard could also facilitate usability, natural language agents, internationalization, and accessibility.participants in this sig will present and discuss require-ments and current activities that could contribute to the de-velopment of a 'universal remote console' standard. the goal of this sig is to gather requirements, identify related research, development, commercial, and other activities, and to initiate an ongoing effort developing a unified uni-versal remote console standard in the future.
prototype implementations for a universal remote console specification. a 'universal remote console' (urc) is a personal device that can be used to control any electronic and information technology device (target device/service), such as thermostats, tvs, or copy machines. the urc renders the user interface (ui) of the target device in a way that accommodates the user's preferences and abilities. this paper introduces the efforts of user groups, industry, government and academia to develop a standard for 'alternate interface access' within the v2 technical committee of the national committee for information technology standards (ncits). some preliminary design aspects of the standard in work are discussed shortly.
universal remote console standard: toward natural user interaction in ambient intelligence. the draft standard on a universal remote console (urc) framework is on its way to be reviewed and released by ansi in 2004. this standard will contribute to the goal of ambient intelligence by allowing users to interact with networked devices and services in their environments in universal and natural ways, utilizing technologies such as natural language interaction and wearable computing. this sig will follow up on last year's successful sig, whose contributions helped to shape the urc draft standard.participants in this sig will present and discuss the impact of the urc draft standard on the field of ambient intelligence. the goal of this sig is to build a network of people from industry and academia who are interested in moving the universal remote console standard forward, and in pursuing its wide-spread adoption in order to implement adaptable and usable user interfaces for networked devices and services.
navigating persistent audio. this paper gives an overview of radioactive, a large-scale asynchronous audio messaging platform for mobile devices. it supports persistent chat spaces that allow users to engage in discussion on demand. our goal is to allow users to easily navigate and participate in large audio-based discussions with minimal cognitive overhead. radioactive attempts to eliminate problems that habitually plague audio-only designs by using a novel combined visual and audio interface.
a physical interface for system dynamics simulation. we present the system blocks, a new physical interactive system that makes it easier for kids to explore dynamic systems. a set of computationally enhanced children blocks, made of wood and electronics, the system blocks can assist k-12 educators to teach the complex concepts of system dynamics and causalities. system dynamics and system thinking are methods for studying the world around us. they deal with understanding how complex systems change over time, and how structure influences behavior. in this paper we will show how the system blocks enable young children (as early as four years old) to create and interact with systems that simulate real-life dynamic behavior such as a bank account; population growth; or the delicate equilibrium of an ecosystem. the system blocks gives young children a hands-on environment to learn about complex behavior and encourage new ways of thinking.
interactive 3d flow visualization using a streamrunner. flow visualization in 3d is challenging due to perceptual problems such as occlusion, lack of directional cues, lack of depth cues, and visual complexity. in this paper we present an interaction technique that addresses these special problems for 3d flow visualization. the feature we present, a streamrunner, games the user interactive control over the evolution of streamlines from the time they are seeds until they reach their full length. the interactive streamrunner control minimizes occlusion and visual complexity and maximizes directional and depth cues for 3d flow visualization tools, the streamrunner gives a brand new level of control to the user investigating the vector field.
magic cubes for social and physical family entertainment. physical and social interactions are constrained,and natural interactions are lost in most of present digital family entertainment systems [5]. magic cubes strive for bringing the computer storytelling, doll 's house,and board game back into reality so that the children can interact socially and physically as what we did in the old days. magic cubes are novel augmented reality systems that explore to use cubes to interact with three dimensional virtual fantasy world. magic cubes encourage discussion, idea exchange, collaboration, social and physical interactions among families.
designing interactive environments for outdoors gaming and play. recent years have seen an increase in the design of outdoor interactive environments. in this sig we want to discuss the key points in the design of an outdoor interactive environment, including interaction techniques, appropriate technologies, usage patterns, robustness, and safety. the sig organizer and presenters are researchers from four universities around the world, who are actively designing and building interactive environments. the three presenters represent state-of-the-art work in distinct areas of the field. the sig will focus on design process, challenges, implementation, and real-world evaluation, to be followed by an open discussion about the state-of-the-art and critical design factors in the field. since chi is the premier conference on human-computer interaction, it is the most suitable venue to discuss these issues, the results achieved so far, compare with other groups around the world, and discuss potential collaboration. we hope that this sig can serve as a starting point to form a community of researchers and practitioners interested in interactive environments for outdoor gaming and play.
the state of tangible interfaces: projects, studies, and open issues. in recent years, the chi community has seen growth in projects that involve tangible user interfaces and tangible interaction. but, many researchers feel that this emerging field lacks in justifying research, industry adoption, and conceptual frameworks. this panel gathers pioneers and active researchers in the field, in an effort to understand the bigger picture of the tui field. the panelists will focus on discussion rather than presentations, and will answer questions regarding projects, findings, and the field at large. we hope to review the open issues in the field, and help interested researchers to better direct their future research efforts.the panel will have three moderators and six panelists. the panelists will start with very short introductions, and then quickly shift to discussion led by the moderators, and to a q&a session with the audience.
positional prediction: consonant cluster prediction text entry method for burmese (myanmar language). i am investigating a consonant cluster prediction text entry method for myanmar language based on positional vowel information. the concept of this method is adapted by inspecting and carefully considering the nature of myanmar language word formations or hand writing orders. according to the initial user study with our software keyboard prototype, users were able to type at ~41.57 characters per minute with mouse, ~41.84 characters per minute with stylus pen, ~14.76 characters per minute with logitech dual thumbstick game pad and ~20.52 characters per minute with nintendo wii remote controller. these numbers are sure to improve as further refinements on program interface are made. the merits of the proposed predictive text input method is that even first time users can type myanmar sentences with appropriate typing speed, and that this approach is applicable for various kinds of mobile devices (see figure.1) and extendable for other similar syllabic languages such as khmer (language of cambodia), nepali (language of nepal), thai (language of thailand) and hindi (one of the languages of india) etc.
providing affective information to family and friends based on social networks. we are developing a computer system which provides information about babies in neonatal intensive care to family members and friends. a key challenge is deciding what information should be given to each individual; we believe this can be based on social networks of the parents. if successful, this technique could also be used in other contexts where a diverse set of family and friends would like information about a patient.
beyond current user research: designing methods for new users, technologies, and design processes. with the rapid diversification of computing technologies, user researchers often encounter new applications, new users and scenarios of use, and even new design processes that require new research approaches. (for instance, how do you assess the usability of a roving, multi-user, activity-based system? or how do you assess a device intended to support a social network?) in this workshop we will examine case studies from user researchers who have modified a classic user research technique or created a new technique to meet the exigencies of such challenges. the workshop is organized around three aspects of methods design: the impetus for creating the new or modified method, the challenges of implementing the method, and the impact of the innovation on the design or design process.
increasing the impact of usability work in software development. a key challenge when producing usable and useful software is the lack of impact of usability work on software development. we aim at developing a more coherent and realistic understanding of this challenge and the possibilities of how to increase the impact from usability work when developing high quality software products. we present a workshop gathering usability practitioners and researchers in order to establish and thoroughly discuss a corpus of case studies covering a broad range of usability practices in software development. the result of the workshop will be summarized in a conference paper and an international recognized scientific publisher will publish the case studies.
heuristic evaluations at bell labs: analyses of evaluator overlap and group session. in this paper we examined a set of seven heuristic evaluations with specific attention to issue identification overlap among professional heuristic evaluation reviewers. we also evaluated the effectiveness of conducting a group review.
investigating response similarities between real and mediated social touch: a first test. in this paper, we investigate whether the gender differences generally found in same and opposite sex social touch are also present in mediated situations. participants were led to believe that a male or female stranger was remotely touching them by means of a vest equipped with vibrotactile actuators. affective responses varied with the stimulated body location, but the effect of dyad composition was not significant. in sum, we found partial support for the assumption that mediated social touch is actually perceived of as a real touch. possible improvements to haptic communication devices are discussed.
devices as interactive physical containers: the shoogle system. shoogle is a novel interface for sensing data within a mobile device, such as presence and properties of text messages or remaining resources. it is based around active exploration: devices are shaken, revealing contents rattling around "inside". vibrotactile display and realistic impact sonification create a compelling system. inertial sensing is used for completely eyes-free, single-handed interaction. prototypes run on both pda's a standard mobile phones with a wireless sensor pack.
tangible avatar and tangible earth: a novel interface for astronomy education. the capability to support spatial perception plays an important role in developing material for astronomy education. considering this, we developed a novel tangible user interface consisting of a glove and a physical avatar attached on its surface. virtual reality graphics of the solar system can be controlled manually with the glove and avatar. preliminary experiments have indicated the advantages of the proposed tangible user interface for astronomy education.
woz pro: a pen-based low fidelity prototyping environment to support wizard of oz studies. because they are easy to create and modify, low fidelity prototypes are commonly used in early evaluations of user interface designs. designers typically use either pen-and-paper or various computer-based tools to create and test low fidelity prototypes; however, our informal analyses of these existing technologies indicate that they do not optimally support the two key, complementary tasks of (a) prototype creation and (b) wizard of oz testing. to address this problem, we have been developing woz pro (wizard of oz prototyper), a pen-based software environment for the quick and easy creation and testing of low fidelity user interface prototypes. we are designing woz pro to be as easy to use as pen-and-paper, but to hold key advantages over pen-and-paper and existing computer-based tools. when designing interface screens in woz pro, designers can easily (a) propagate a design change to other related screens, and (b) specify the set of screens that are reachable from a given screen. in a wizard of oz test, woz pro reduces the cognitive load on the wizard by allowing navigation only to those next screens that are valid. we are planning a controlled experiment to compare woz pro against paper-and-pencil along several measures in a set of prototype creation and evaluation tasks.
an extensible platform for the interactive exploration of fitts' law and related movement time models. this paper describes a new software platform for the interactive exploration of human performance models such as fitts' law. the software is written in java and provides a flexible environment for hci research and education. its distributed, object-oriented architecture provides a framework for exploring new performance models, task types, and selection modes.
exploring the use of large displays in american megachurches. within the hci community, there is a growing interest in how technology is used and appropriated outside the workplace. in this paper, we present preliminary findings of how large displays, projection systems, and presentation software are used in american megachurches to support religious practice. these findings are based on ten visits to church services by the study.s authors. we describe how large display technology augments and replaces certain church traditions, and finish by discussing issues related to the design for church environments that are highlighted by this use of technology.
building upon everyday play. most of today's video game strategies are based on a static set of game controls and player actions that remain oblivious to the player's context and own creativity. building upon everyday play is the result of a collaboration of control freaks, a pervasive gaming experience project, and exemplar, a toolkit that uses programming-by-demonstration to author sensor-based interactions. in combination, building upon everyday play furthers a pervasive gaming experience through appropriation of objects in the player's environment and enables new ways to play. the project consists of a combination of a portable, wireless motion-sensing clamp that can be attached to everyday objects to turn them into game controllers by proxy, and a programming-by-demonstration system that translates sensor data reported by the controller into game events. in the demonstration, participants will be able to play custom video games projected on a large 2d screen by attaching the clamp to their bodies or provided household objects, and to invent their own moves to control the provided games.
when two methods are better than one: combining user study with cognitive modeling. we discuss the benefits of combining user studies and cognitive modeling in the context of firefox tabbed browsing. we studied new users' ability to use tabbed browsing without assistance, and then evaluated alternatives for closing browser tabs to improve the new user experience through user tests and cognitive modeling. in general, our experience highlights the advantages of using user studies and modeling together to do user interface evaluation: user studies provided validation of design intuitions and data to support modeling of user behavior; modeling provided a fast and efficient ability to play "what if" with the design change; the combination of qualitative user test data and quantitative modeling results proved to be a far more convincing package of evidence than either result in isolation, given the variety of perspectives inthe design and development team.
applying a user-centered metric to identify active blogs. current methods of determining whether a blog is active or abandoned tend to rely on simple rules, such as identifying whether it has been posted to within the last 7 or 30 days. individual bloggers vary widely in their posting activity levels, however, and so using such fixed cutoffs can result in both misses (calling active blogs "abandoned") and false positives (calling abandoned blogs "active"). we suggest using an alternative metric that varies the cutoff date according to the properties of each individual blog, and show how its results relate to those of the standard 30-day active metric. from our initial analysis, we believe that such a metric offers a more accurate representation of the intuitive notion of blog activity.
online health communities. online health communities provide a means for patients and their families to learn about an illness, seek and offer support, and connect with others in similar circumstances. online health communities raise difficult design challenges because of the wide variability of members. medical expertise, health literacy, and technology literacy, and the potential severity of problems due to misinformation. the importance of online health communities is evidenced by their popularity, as well as the significant impact they have on the lives of their members. this special interest group (sig) will explore current trends in online health communities and how the design and evaluation expertise of the chi community can benefit and improve online health community research and development.
interaction with user-adaptive information filters.: trust, transparency and acceptance. this phd-project investigates interaction with user-adaptive systems. experiments and user studies are used to explore the factors that lead to trust and acceptance of such systems. this research aims to inform design of transparent user-adaptive and (semi-)autonomous systems. focus is on interaction with content-based user-adaptive information filters.
designing mobile phone interface with children. this paper presents the design and evaluation of a mobile phone interface with and for children. ten children aged 8-13 years old took part in a participatory design process and ten others evaluated the design. whilst there were similarities in the problems and desired features children and adults share, children had some unique requirements and preferences, such as cartoon-styled icons or placing access to emergency number at the home screen. this study enlists some requirements of mobile phone interface for children. the methods used in this study can also be adapted to other design and evaluation processes with children.
bridging the social-technical gap in location-aware computing. building ubiquitous applications that exploit location requires integrating underlying infrastructure for linking sensors with high-level representation of the measure space to support human activities. however, the real-world constraints limit the efficiency of location technologies. the inherent spatial uncertainty embedded in mobile and location systems constantly challenges the coexistence of digital and physical spaces. consequently, the technical mechanisms fail to match the highly flexible, nuanced, and contextual human spatial activities. these discrepancies generate a social-technical gap between what should be socially supported and what can be technically achieved. my research aims at exploring, and hopefully reducing this gap in the context of location-aware computing.
eventstream: integrated transit information system. eventstream was designed to help out-of-town attendees of seminars or conferences use public transportation (pt) to travel to and from these meetings. since the dominant business travel mode is the personal vehicle [2], this would help reduce habitual and inefficient travel in single occupant vehicles. using recommendations from studies on travel mode choice [4], we designed eventstream to offer customized transit information for this target group. we deliver this information via email, our website, to an ipod, or through short message service (sms) to a cell phone. our user studies indicated a willingness to attempt pt use in an unfamiliar town when provided information that supports informed choices.
value scenarios: a technique for envisioning systemic effects of new technologies. in this paper we argue that there is a scarcity of methods which support critical, systemic, long-term thinking in current design practice, technology development and deployment. to address this need we introduce value scenarios, an extension of scenario-based design which can support envisioning the systemic effects of new technologies. we identify and describe five key elements of value scenarios; stakeholders, pervasiveness, time, systemic effects, and value implications. we provide two examples of value scenarios, which draw from our current work on urban simulation and human-robotic interaction . we conclude with suggestions for how value scenarios might be used by others.
incentive design for home computer security. home computer users frequently lack the skills necessary to ensure proper security. hackers exploit this to control large networks of computers (.botnets.) that are used for spam, extortion, and fraud. i integrate ideas from psychology and economics to design software that provides incentives that induce better security choices by home computer users.
usability on patrol. the introduction of computers into police patrol cars comes with an increase in driver distraction issues. we will describe the usability process and techniques we adapted to study computers in law enforcement patrol cars. our approach to assess the risk of driver distraction in the police vehicles was a combination of a national highway traffic safety administration (nhtsa) workload assessment protocol and cognitive modeling. this combination proved useful without the high cost of driving simulators and instrumented test subjects. using cognitive modeling, we could identify the potential problems for certain tasks. for example, we found that automating the task of running a license plate with a typical mouse-keyboard interface, could increase the workload by more than seven hundred percent compared with doing the same task via radio contact with dispatcher. we also found measuring by glances instead of time to be a useful technique in practice.
enabling nutrition-aware cooking in a smart kitchen. we present a smart kitchen that can enhance the traditional meal preparation and cooking process by raising awareness of the nutrition facts in food ingredients that go into a meal. the goal is to promote healthy cooking. our smart kitchen is augmented with sensors to detect cooking activities and provides digital feedbacks to users about nutritional information on the used food ingredients. we have created a preliminary prototype for evaluation, and the result is promising.
porta-person: telepresence for the connected conference room. this paper describes a telepresence device called porta-person. this is the first project in a larger initiative known as the connected conference room, which aims to improve the user experience for remote people connected to meetings taking place in conference rooms. the porta-person is designed to enhance a sense of social presence for remote meeting participants. it does this by providing a high-fidelity audio connection and a remotely controlled telepresence display with video or animation.
content-aware layout. we describe content-aware layout (cal), a technique that automatically arranges windows on a user.s desktop. unlike conventional window managers that automatically cascade or tile each window without regard to its content, cal uses information about the contents of windows to help decide if and where they should be placed. we present the approach to designing cal, as well as its implementation. we then conclude with a discussion about future work and cal.s potential use in large display environments.
the use of aesthetics in hci systems. as computing expands its domain from workplace to pervasive and domestic environments, interest in aesthetics for designing is increasing in hci. hci literatures in aesthetics provide wide variety of theoretical foundations for how aesthetics might be interpreted and potentially used for design. however, aesthetics in designing hci systems have been mainly studied as a source for decoration or visualizing information. in this paper, we present our initial investigation on a qualitative study with an awareness information system prototype to explore what decorative artallcan bring to hci systems beyond decoration and/or effective communication.
scinews online: scaffolding the construction of scientific explanations. middle and high-school science teachers have traditionally introduced current events in the classroom to leverage news topics relevant to the curriculum, such as the sumatra tsunami or hurricane katrina. scinews online is an online research environment co-designed with science teachers for learners to construct web reports on the science behind the news on natural disasters. writing scientific explanations provides valuable learning opportunities for learners to engage in a realistic and educationally relevant science task. here i highlight the design of the scientific explanation activity, a scaffolded environment that supports learners. construction of scientific explanations using multiple online sources. the scientific explanation activity focuses on supporting the development of key information literacy skills for sense-making in science inquiry, namely information integration across sources and effective scientific argumentation.
galvanic skin response (gsr) as an index of cognitive load. multimodal user interfaces (mmui) allow users to control computers using speech and gesture, and have the potential to minimise users. experienced cognitive load, especially when performing complex tasks. in this paper, we describe our attempt to use a physiological measure, namely galvanic skin response (gsr), to objectively evaluate users. stress and arousal levels while using unimodal and multimodal versions of the same interface. preliminary results show that users. gsr readings significantly increase when task cognitive load level increases. moreover, users. gsr readings are found to be lower when using a multimodal interface, instead of a unimodal interface. cross-examination of gsr data with multimodal data annotation showed promising results in explaining the peaks in the gsr data, which are found to correlate with sub-task user events. this interesting result verifies that gsr can be used to serve as an objective indicator of user cognitive load level in real time, with a very fine granularity.
"let me show you what i want": engaging individuals with cognitive disabilities and their families in design. in this paper i describe an ongoing multi-stage, participatory design study with individuals with cognitive disabilities and their family caregivers. i use a technology probe to inspire families to co-design a picture-based remote communication system. the technology platform is a pda.smart phone.. i will present early findings from this study and discuss how it was a successful approach to engage with individuals with significant cognitive disabilities as co-designers of their own technology.
up health: ubiquitously persuasive health promotion with an instant messaging system. the spread of ubiquitous technologies into the health domain provide an opportunity to investigate interactive communications that can persuade users to adopt certain beneficial behaviors.. we are interested in understanding how networked devices can support and leverage social influence. the aim of this research is to explore the potential of online group interaction for promoting healthy behavior patterns and to investigate how the participation in the online group activity can influence an individual.s off-line health-related behavior. as first part of this research, we devised an instant messaging (im) system which shares context information relating to health and covering things such as physical activity and smoking behavior.
children distinguish conventional from moral violations in interactions with a personified agent. this paper describes the preliminary results of a study conducted to answer two questions: (1) do children generalize their understanding of distinctions between conventional and moral violations in human-human interactions to human-agent interactions? and (2) does the agent.s ability to make claims to its own rights influence children's judgments? a two condition, between-subjects study was conducted in which 60 eight and nine year-old children interacted with a personified agent and observed a researcher interacting with the same agent. a semi-structured interview was conducted to investigate the children.s judgments of the observed interactions. results suggest that children do distinguish between conventional and moral violations in human-agent interactions and that the ability of the agent to make claims to its own rights significantly increases children.s likelihood of distinguishing the two violations.
current issues in assessing and improving information usability. the usability of information is vital to successful websites, products, and services. managers and developers often recognize the role of information or content in overall product usability, but miss opportunities to improve information usability as part of the product-development effort. this meeting is an annual forum on human factors of information design, in which we discuss issues selected by the group from the facilitators. list of topics, augmented by attendees. suggestions.
beyond usability for safety critical systems: how to be sure (safe, usable, reliable, and evolvable)? while a significant effort is currently being undertaken by the chi community in order to apply and extend current usability evaluation techniques to new kinds of interaction techniques very little has been done to improve the reliability of software offering these kinds of interaction techniques. as these new interaction techniques are currently more and more used in the field of command and control safety critical systems the potential of incident or accidents increases. similarly, the non reliability of interactive software can jeopardize usability evaluation by showing unexpected or undesired behaviors. lastly, iterative design processes promote multiple designs through evolvable prototypes in order to accommodate requirements changes and results from usability evaluations thus reducing reliability of the final system by lack of global and structured design. the aim of this sig is to provide a forum for both researchers and practitioners interested in safety critical interactive systems. our goal is to define a roadmap of activities to cross fertilize usability, reliability and safety for these kinds of systems to minimize duplicate efforts and reuse knowledge in all the communities involved.
the effect of brand awareness on the evaluation of search engine results. in this paper we investigate the effect of search engine brand (i.e., identifying name that distinguishes a product from its competitors) on evaluation of system performance. our research is motivated by the large amount of search traffic directed to less than a handful of web search engines, even though many are of equal technical quality with similar interfaces. we conducted a laboratory experiment with 32 participants measuring the effect of four search engine brands while controlling for the quality of search engine results. based on average relevance ratings, there was a 25% difference between the most highly rated search engine and the lowest, even though search engine results were identical in both content and presentation. we discuss implications for search engine marketing and the design of empirical studies measuring search engine quality.
a bridging design prototype for investigating concept mapping in the preschool community. this paper reports on studies where teachers from two different preschools incorporated a bridging design prototype (bdp) for concept mapping into classroom activities. designed under inclusive, participatory, and user-centered principles, the bdp was used to perform observations for assessing an interaction problem and refining the user community profile. the observation findings will inform next stage of product development.
exploring augmented live video streams for remote participation. augmented video streams display information within the context of the physical environment. in contrast to augmented reality, they do not require special equipment, they can support many users and are location-independent. in this paper we are exploring the potentials of augmented video streams for remote participation. we present our design considerations for remote participation user interfaces, briefly describe their development and explain the design of three different application scenarios: watching a pervasive game, observing the quality of a production process and exploring interactive science exhibits. the paper also discusses how to develop high quality augmented video streams along with which information and control options are required in order to obtain a viable remote participation interface.
iterative design of an audio-haptic drawing application. this paper presents the ongoing design and evaluation of an audio-haptic drawing program that allows visually impaired users to create and access graphical images. the application is developed in close collaboration with a user reference group of five blind/low vision school children. the objective of the application is twofold. it is used as a research vehicle to investigate user interaction techniques and do basic research on navigation strategies and help tools, including e.g. sound fields, shape creation tools and beacons with pulling forces in the context of drawing. in the progress of the development, the preferred features have been implemented as standard tools in the application. the final aim of the application in its current form is to aid school work in different subjects, and part of the application development is also to create tasks relevant in a school setting.
designing tangibles for children: what designers need to know. new forms of tangible and spatial child computer interaction and supporting technologies can be designed to leverage the way children develop intelligence in the world. in order to design playful learning tangibles designers must understand how children interact with and understand the representations embedded in tangible systems. in this short work in progress paper the author summarizes relevant theory from cognitive developmental psychology which may provide grounding for the design of tangibles to support children's learning.
willcam: a digital camera visualizing users. interest. with the increased usage of digital cameras and camera-enabled mobile phones in recent years, large numbers of photos are being taken. many of the photos that are taken are used little, if at all. researchers and companies have developed systems where photos can be annotated or tagged to facilitate storage and retrieval. however, people are often unwilling to spend the time and effort to carry out annotation. to solve this problem, we focus on real-time annotation where photographs are annotated at the time when they are taken. we propose a novel digital camera,.willcam., which enables users to capture various information, such as location, temperature, ambient noise, and photographer facial expression, in addition to the photo itself. willcam also helps users express their interest -what object or information in the picture/scene is most important for them- visually.
evolution of a concept: from technology to end-user to enterprise. in this report we describe our experiences designing and trialing a hands-free, context-aware, mobile communications system for enterprise workers. our concept, inspired by a new consumer technology, was designed with a heavy focus on the end-user. through our trial we became aware of various factors in the enterprise that impacted design and deployment.
the digital music box: using cultural and critical theory to inform design. this work draws on studies which explore resistance to the music industry's construal of copying music files as theft. following a previous ethnography on participants."technology scruples" it considers the issue as a design challenge rather than a legal problem. drawing on critical theory it considers how value might be added to digital music by embedding it in artifacts. three product design students were briefed to create concept designs for.digital music boxes. that would contain and display particular back catalogues of music. the paper reflects on their sketches and models and argues that critical theory can inform new approaches to design work.
finding communication hot spots of location-based postings. the growing amount of location-based public postings will challenge the current visualization and access methods of location-based information. the aim of our work is to provide a clear overview of location-based postings and to support easy access to information the user is interested in. we designed a prototype using a semi-transparent heat map over a map view to visualize posting density on the area of interest. automatically extracted keywords and dynamic time selection support the search and filtering of location-based public postings. based on our evaluation, users found the heat map as a familiar abstraction of the location based information. clustering and displaying the salient words as keywords over the map view was considered to be especially useful.
on nurturing strong-tie distant relationships: from theory to prototype. this paper presents our research on the process of creating new communication experiences in the private sphere of users. to do this, we have chosen to study the concept of social presence, and also the notion of communication. the communication models that we have examined come from various disciplines and all have in common the fact that they focus on exploring the communication act once the decision to communicate has been taken. we have build upon them and conceived a model that includes an analysis of the factors that influence the decision to communicate. this initial analysis has helped us integrate the specific needs of our targeted users and has allowed us to materialize them in a working prototype of a communication terminal called tact.
scaffolding cooperative multi-device activities in an informal learning environment. informal learning environments, e.g. children's science museums, provide special challenges for educational software design: the software must (1) be immediately accessible, (2) convey educational content within short episodes of use, and (3) should allow multiple users to participate at the same time. while mobile technology allows for multiple simultaneous users, significant scaffolding is required to allow groups to walk up and productively use it. using a design experiment approach, my research focuses on the design and evaluation of distributed scaffolds that enable informal learners to use mobile technology effectively.
jogging over a distance: supporting a "jogging together" experience although being apart. jogging is a healthy activity and many people enjoy jogging with others for social and motivational reasons. however, jogging partners might not always live in the same location, and it may be difficult to find a local jogger who runs at the same pace, we found through a survey "jogging over a distance" allows geographically distant joggers to socialize and motivate one another by using spatialized audio to convey presence and pace cues, similar to the experience of running side by side. we hope our approach encourages active and prospective joggers to jog longer and more often, while simultaneously supporting friendships.
the liliput prototype: a wearable lab environment for user tests of mobile telecommunication applications. user trials for future mobile telecommunication applications inherently pose several particular challenges which are difficult to meet in a traditional lab environment. in this paper we describe liliput (lightweight lab equipment for portable user testing in telecom-munications), a highly flexible wearable test system which has been realized as a fully operational prototype at the telecommunications research center vienna (ftw.). then we illustrate how we use liliput for testing various types of mobile application in the wild.
thinking but not seeing: think-aloud for non-sighted users. this paper discusses some of the methodological challenges that can be encountered when usability testing with visually impaired users. these include (1) the need for customized test environments, (2) the potential for audio interference between screen reader output and the moderator to participant dialogue, and (3) the difficulty for observers inexperienced in accessibility technology. in this paper we outline several techniques for dealing with these challenges, including some variations on traditional think-aloud techniques that are useful when a usability participant is using a screen reader.
practical approaches to comforting users with relational agents. interactions in which computer agents comfort users through expressed empathy have been shown to be important in alleviating user frustration and increasing user liking of the agent, and may have important healthcare applications. given the current state of technology, designers of these systems are forced to choose between (a) allowing users to freely express their feelings, but having the agents provide imperfect empathic responses, or (b) greatly restricting how users can express themselves, but having the agents provide very accurate empathic feedback. this study investigates which of these options leads to better outcomes, in terms of comforting users and increasing user-agent social bonds. results, on almost all measures, indicate that empathic accuracy is more important than user expressivity.
human guided evolution of xul user interfaces. graphical user interface design is a time consuming, expensive, and complex software design process. user interface design is both art and science in that we use both objective and subjective design metrics to evaluate interfaces. an automated process that relies on both subjective and objective metrics to guide the evolution of effective, personalized user interfaces could significantly change current gui development and maintenance practice. this paper uses an interactive genetic algorithm to evolve xul user interface layouts by combining objective and subjective metrics. the genetic algorithm encodes expert knowledge from prominent usability guidelines as objective heuristics. further, the graphical user interface developer (or user!) biases and guides the evolution of the interfaces by subjectively evaluating and selecting the.best. and.worst. interfaces from a small set of displayed interface prototypes. we explore how the selection of individuals from the population to be displayed to the user for subjective evaluation affects the convergence of the genetic algorithm and show that our methodology can produce effective interfaces that reflect subjective user-preferred aesthetics.
a research agenda for mobile usability. the turn of this decade marked a renewed interest for mobile usability research within the field of human computer interaction. a challenge, however, exists in that many scholars define and operationalize usability differently. with the introduction of mobile commerce circa 1999, a review of relevant peer-reviewed literature would highlight areas of past emphasis and opportunities for future empirical research specific to mobile usability.this work-in-progress presents a research agenda for mobile usability that consists of two parts. first, a framework is adapted for the taxonomy of empirical mobile usability studies. second, results of a qualitative review of 45 empirical mobile usability studies include: i) a summary of the core and peripheral usability dimensions measured; ii) a detailed analysis of contextual factors studied; and iii) key findings that provide the basis for a research agenda in mobile usability.
interactive technologies for autism. in meeting health, education, and lifestyle goals, technology can both assist individuals with autism, and support those who live and work with them, such as family, caregivers, coworkers, and friends. the uniqueness of each individual with autism and the context of their lives provide interesting design challenges for the successful creation and adoption of technologies for this domain. this special interest group (sig) aims to bring together those who study the use of technology by and for individuals with autism, those who design and de-velop new technologies, and those who are curious about getting involved. areas that this sig will consider include assistive technologies; tools for data collection and analysis; educational software; virtual reality rehabilitation environments; identifying users; need finding; user-centered collaborative design processes that include individuals who cannot speak or write; and product assessment. this sig will provide opportunities for participants to join together and share their own pro-jects, design challenges, and lessons learned while fo-cusing on directions for future development. those with experience and newcomers to the field are both equally encouraged to attend.
striking a c[h]ord: vocal interaction in assistive technologies, games, and more. vocal interaction research has primarily been focused on the use of systems for automatic speech recognition and synthesis. whilst asr has been successful in various domains, it can be impractical in some contexts of use such as in time-sensitive and continuous controls and in applications involving users with speech impairment. this workshop aims to discuss the state of the art in vocal interaction methods that go beyond word recognition by exploiting the information contained within non-verbal vocalizations (e.g. pitch, volume, or timbre). the overarching objective of this workshop is to sketch a research agenda on the topic of the emerging discipline of non-verbal vocal interaction and its implications for the design of interactive systems. the workshop will be of interest to researchers, designers, developers, and users that are interested or would benefit from use of the non-verbal interaction.
dealing with key challenges in international usability and user research. in this sig, we will present scenarios that exemplify many of the key challenges of doing user research and usability evaluation internationally. we will use these to stimulate discussion about solutions and approaches, and then share our own recommendations.
range: exploring proxemics in collaborative whiteboard interaction. range is an interactive whiteboard designed to support collocated, ad-hoc meetings. it employs proximity sensing to proactively transition between ambient and authoring modes, clear space for writing, and cluster ink strokes. the inspiration for range stems from longitudinal studies of student design teams, in which we observed that shifts in collaborative activity correlated with changes in the users physical proximity to the whiteboard. through iterative design, we developed techniques for incorporating implicit input like that of the proximity sensors into interaction.
vuelta: creating animated characters and props using real-world objects. when authoring in visual storytelling environments, children are often limited to use characters and props available in libraries or have to create their own using software. we present a novel alternative in the early design and implementation of vuelta, a tool for creating animated characters and props using real-world objects. vuelta authors can create animations for real-world characters and props by capturing animation frames using a high-definition camera. each frame is captured from many directions enabling the characters and props to be positioned in any direction. we use an image difference algorithm to extract the characters and props from the frames. our setup is designed to support creativity by enabling authors to use objects of their choice that they may create with their own hands and by not putting limits on the types of animations that may be created. vuelta is also designed to support collaboration by enabling more than one author to participate in the process. the next steps in our development of vuelta include working with children to design a tool to edit the animations, as well as integrating vuelta with a storytelling environment we are developing.
exploring design as a research activity. human-computer interaction research often includes a significant design component. in cases where software or other tools are developed and described, but no empirical evaluation is provided, the research consists almost entirely of the knowledge marshaled in support of and as a result of design activities. very little analysis has been carried out, however, into the scientific and epistemological bases underpinning this kind of research. the purpose of this workshop is to provide a forum for researchers and practitioners to present and discuss different perspectives on the nature of design as a research activity, and the challenges facing researchers who employ design as a methodology.
physically present, mentally absent: technology use in face-to-face meetings. this work-in-progress discusses qualitative findings about the impact of portable technologies in collocated collaboration. laptops, cell phones, and other handheld devices are both a distraction during face-to-face meetings, and at the same time allow spontaneous access to needed information. interviews with fifteen professionals were conducted to elicit why and how these technologies are used in meeting settings. responses across participants varied strongly and indicate that this emerging research area must look at the notion of context in new ways to support both individual and group needs.
education, entertainment and authenticity: lessons learned from designing an interactive exhibit about medieval music. in this paper we describe the design experience gathered from creating an interactive exhibit about medieval music. this system was designed as an educational exhibit that relies on audio as its only feedback channel. we focused our work on three major goals: educational value, entertainment aspects, and historic authenticity. we present insight into the challenges in designing a system with these goals, and how they could be solved.
exploring tabletop file system interaction. tabletop interfaces provide a new medium for collocated collaboration. consequently, tabletops need to support access to file systems, just as a core facility of conventional computer systems is to provide an interface to a file system. however, the constraints of tabletop interfaces call for rethinking standard approaches to file system interaction. this paper presents the design of ontop, a novel associative-search approach to file system interaction: users navigate multiple file systems by selecting focus files, retrieving similar ones. we report a small-scale qualitative evaluation of ontop against a more conventional file browser approach: ontop was consistently preferred and found to be more efficient, especially for larger file collections.
gaze-enhanced scrolling techniques. we present several gaze-enhanced scrolling techniques developed as part of continuing work in the guide (gaze-enhanced user interface design) project. this effort explores how gaze information can be effectively used as input that augments keyboard and mouse. the techniques presented below use gaze both as a primary input and as an augmented input in order to enhance scrolling and panning techniques. we also introduce the use of off-screen gaze-actuated buttons which can be used for document navigation and control.
user-centered design gymkhana. the user-centered design (ucd) gymkhana is a tool for human-computer interaction practitioners to demonstrate through a game the key user-centered design methods and how they interrelate in the design process. the target audiences are other organizational departments unfamiliar with ucd but whose work is related to the definition, creation, and update of a product or service.
computer aided observations of complex mobile situations. designing mobile and wearable applications is a challenge. the context of use is more important than ever and traditional methodologies for elicitation and specification reach their limits. this paper investigates the challenge of creating and communicating information about the user's primary task with regards to its fine grained temporal structure. taskobserver is a tabletpc software that allows real-time logging of events during observations of complex mobile scenarios. the results are communicated to other team members using task trace graphs of the events observed.
interactive generation of overview information using speech. in non-visual interfaces, using non-speech audio can be a more effective and efficient way of obtaining overview information than using speech. however, users who are blind regularly use speech-based tools to access information in computers, and often prefer this technology over others that pose steeper learning curves. this paper proposes a technique to explore numerical data tables interactively in order to extract overview information by optimising the use of speech.
supporting proactive planning of multiple activities. many studies have shown that the nature of information work demands constant switching among multiple activities. this doctoral dissertation aims at expanding the understanding of the process and strategies involved in personal activity management (pam), including planning, managing and organizing multiples activities and their resources, with the goal of designing, implementing and testing appropriate supportive information technology.
studying activity patterns in cscw. we study small distributed work groups capturing, managing, and reusing knowledge in a collaborative activity. we conceive this process as adaptation of a group to an activity and we study it in a realistic semi-controlled setting. we briefly describe our approach, method, preliminary results, and research trajectory.
bluetuna: let your neighbour know what music you like. bluetuna is an application running on bluetooth-enabled mobile phones that allows users to share information about their favourite music. with bluetuna people can select a list of favourite artists or songs and see who else in proximity share their taste in music, or they can search whom nearby has selected specific artists, and check out what other preferences in terms of music these people have. moreover, bluetuna users can exchange messages with each other over bluetooth, connect to the internet to download their profile and obtain music recommendations from last. fm website. to enrich this experience, people can interact with each other through their mobile phones while sitting in cafes by accessing the bluetuna hotspots and a wider range of music sharing options.
who killed design?: addressing design through an interdisciplinary investigation. this extended abstract describes the grounding for an interdisciplinary discussion regarding the contemporary meaning of "design","designer", and "designed" and the role it will play in the future of chi and chi-related disciplines.
design and comparison of acceleration methods for touchpad. as the resolution of a notebook display increases, the efficiency of a touchpad is becoming a more important issue. in particular, it is often observed that users scrape the pad repeatedly to reach the close button of a window. in this paper, we propose two new cursor control methods utilizing the contact-area information that is provided by most touchpads. we compared the new methods with the mouse acceleration that is the most common cursor control method. an evaluation study showed that the new methods required smaller number of scrapings and shorter distance of scraping on the touchpad while their efficiency is similar to that of the mouse acceleration. all participants preferred the new methods to the mouse acceleration.
dreaming of adaptive interface agents. this interactive project uses the metaphor of human sleep and dreaming to present a novel paradigm that helps address problems in adaptive user interface design. two significant problems in adaptive interfaces are: interfaces that adapt when a user does not want them to do so, and interfaces where it is hard to understand how it changed during the process of adaptation. in the project described here, the system only adapts when the user allows it to go to sleep long enough to have a dream. in addition, the dream itself is a visualization of the transformation of the interface, so that a person may see what changes have occurred. this project presents an interim stage of this system, in which an autonomous agent collects knowledge about its environment, falls asleep, has dreams, and reconfigures its internal representation of the world while it dreams. people may alter the agent's environment, may prevent it from sleeping by making noise into a microphone, and may observe the dream process that ensues when it is allowed to fall asleep. by drawing on the universal human experience of sleep and dreaming, this project seeks to make adaptive interfaces more effective and comprehensible.
sounding board: a handheld device for mutual assessment in education. we are developing a set of handheld input devices for mutual assessment in the course of a learning activity and a system to give on-the-spot feedback concerning the summary of the assessment to the learners visually with the aid of charts. this paper describes its design concept and provides an overview of the system.
continuing motivation for game design. in this paper we share experiences from a 2-week game-design project using the introductory programming environment agentsheets with middle school students (6-8 grades) during a summer computing course at a public middle school in northern california. we examine factors that influence students. desire to continue working with the software, looking at similarities and differences between boys and girls, students with high or low levels of prior experience, and variables which we hypothesize might contribute to continuing motivation. our findings suggest that programming in the context of game design can be of interest to a broad range of students, not only those who already are engaged in technological activities.
analysis of human interruptibility in the home environment. many studies have explored the issues of interruption and availability in workplace environments, however, few have focused on human interruptibility in home environments. to make the initiation of online remote communication smoother, determining if it is appropriate to interrupt the remote communication partner is critical. as a preliminary investigation for developing a method that can automatically estimate interruptibility in the home environments, this paper determines the characteristics of human interruptibility by analyzing self-reported data of subjects in the home. the results indicate that factors such as individual differences, activities and certain home locations influence interruptibility.
beyond usability: taking social, situational, cultural, and other contextual factors into account. design and evaluation in mainstream hci have often relied on scientific measurements of efficiency and error. although usability and usefulness are still primary concerns for hci, researchers and designers in the field are attempting to move beyond, investigating a variety of approaches such as user experience, aesthetic interaction, ambiguity, slow technology, and various ways to understand the social, cultural, and other contextual aspects of our world. while some are driven by non-utilitarian theoretical frameworks, many are not informed by any particular framework or theory. regardless, there has not been a coherent body of discussion in the field of hci. this sig will provide a forum for people to discuss current and future design approaches that move beyond usability. it will address both the relation of underlying paradigms and the relation of design and research.
mapping semantic relevancy of information displays. semantic relevancy maps are a visual analytic technique for representing the distribution of semantic relevancy across an information display. the maps highlight the text areas of the display corresponding to the relevance of that text to user goals, with stronger highlights indicating higher degrees of relevance. semantic relevancy maps were developed as a tool for high-fidelity computational cognitive models that search complex information displays in the same manner as humans. however, they offer the potential to be a standalone tool for quickly evaluating the spatial layout of information for designers or, more simply, for identifying the spatial location of sought-for information by any computer user.
guide: gaze-enhanced ui design. the guide (gaze-enhanced user interface design) project in the hci group at stanford university explores how gaze information can be effectively used as an augmented input in addition to keyboard and mouse. we present three practical applications of gaze as an augmented input for pointing and selection, application switching, and scrolling. our gaze-based interaction techniques do not overload the visual channel and present a natural, universally-accessible and general purpose use of gaze information to facilitate interaction with everyday computing devices.
common & particular needs: a challenge to participatory design. a design story about the design of a visualization for controllers who monitor ibm's controls process, provides the backdrop for reflections on the success of a participatory design process. the story illustrates that while the design process appears to lead to a successful general technical solution, the solution fairs less well when viewed from the perspectives of: support for evolving work practices, or support for the particular and contextual tasks of individuals. this leads us to reframe our participatory design process as the design and socialization of end-user programming tools.
a gestural input through finger writing on a textured pad. we describe a new input method that utilizes patterned vibration that is generated through the finger writing on a textured pad. using a flexible or a foldable textured pad which can be worn by the user can bring more diverse applications than conventional input interfaces such as a touchpad or tablet screen.
music organisation using colour synaesthesia. the movement of music from physical discs to digital resources managed on a computer has had an effect on the listening habits of users. we explore using the potential of the innate synaesthesia that some people report feeling between colour and mood in a novel interface that enables a user to explore their music collection and create musical playlists in a more relevant way. we show that there is a reasonable degree of consistency between users' associations of colour and music, and show that an indirect descriptor can aid in the recall of music via mood, making playlist generation a simpler and more useful process.
supporting non-professional users in the new media landscape. this workshop will discuss the implications of the new media landscape allowing non-professional users to co-produce and share media content in applications for (interactive) television, websites and mobile devices. this new media landscape represents an important shift away from professionally produced media content for the mass-market towards a more homemade media landscape. more specifically, the workshop will focus on methodologies and techniques that are suitable to design co-creative applications for non-professional users in different contexts of use like the office, the home, or in public spaces. special attention goes to stimulating user participation and motivation in small network communities, and how social interaction can be supported through the interface. co-experience is an evolving concept, which gives insight both into the lives and interaction between people and their in-between user experience. a special focus lies also on advanced evaluation approaches for the production of these forms of user experience in different contexts of use. designing for co-creative and co-experiences targeting non-professional users will be critical in the further developments of interactive technologies in the new media landscape.
connectedness: support to communities in diaspora via ict. the continuous migratory flows from mexico to the us have yielded the creation of transnational communities. communication is essential for these people to keep their community awareness high. even though recent advances on ict have enabled people to be in touch with remote family or friends, community context obtained by migrants is arguably partial. my dissertation will focus on an exploratory study of different communication channels used by migrants to communicate to and from their community of origin. the contributions of my work will provide an understanding of the nature of community connectedness of migrants as well as the information elements involved on increasing the sense of connection itself. this knowledge might be used for the better design of communication technologies.
iprocam: a lens-sharing projector-camera system for augmented reality applications. projector-based augmented reality techniques are expected to become a practical display solution for hand-held devices in the near future. a new problem in the new environment is that neither a projector nor a projection surface is fixed in space . this means that calibration between the two coordinate systems of a projector and a camera will have to be no more a one-time setup procedure but a dynamic process. the best solution will be to remove the need for calibration from the beginning by having a projector and a camera share the same lens system. the iprocam is a projector-camera system that realized this idea using a beam splitter and a time-multiplexing scheme. sharing the same lens system also makes it possible to keep a projector in focus by keeping a camera in focus. this paper presents the implementation details of an iprocam prototype and the results of experiments conducted to verify the concept.
reality-based interaction: unifying the new generation of interaction styles. we are in the midst of an explosion of emerging human-computer interaction techniques that have redefined our understanding of both computers and interaction. we propose the notion of reality-based interaction (rbi) as a unifying concept that ties together a large subset of these emerging interaction styles. through rbi we are attempting to provide a framework that can be used to understand, compare, and relate current paths of hci research. viewing interaction through the lens of rbi can provide insights for designers and allows us to find gaps or opportunities for future development. furthermore, we are using rbi to develop new evaluation techniques for features of emerging interfaces that are currently unquantifiable.
using activity theory to develop a design framework for rural development. many attempts to bridge the digital divide between lesser-developed countries (ldc) through information & communication technology (ict) projects have had little success. with the concurrent rise in number of ict projects in rural areas, the current situation calls for better design. however, it is our claim that the nature of villages.being devoid of digital artifacts.requires much of hci theory and methodologies to be re-examined. hci theory has evolved in urban environments over the past 30 years and may not be suitable for the village environment. however, activity theory lends itself well to these environments as its primary focus is on pre-existing activities and goals rather than digital artifacts themselves. using this theory as basis, we examine past failures and successes of ict interventions. from this examination we intend to derive a practical framework for guiding future hci-design (hcid) in the developing world.
finding your way with campuswiki: a location-aware wiki. wikis provide a simple and unique approach to collaborative authoring, allowing any member of the community to contribute new, or change existing information. however, wikis are typically disconnected from the physical context of users who are utilizing or creating content, resulting in suboptimal support for geographic communities. in addition, geographic communities might find the highly skewed generation of content by a few individuals problematic. here we present research into addressing these challenges through location-awareness and lightweight user content rating mechanisms. we describe one such location-aware wiki, campuswiki and initial results from a field study demonstrating the value of location-linked content and the rating approach. we conclude with a discussion of design implications.
how do robotic agents' appearances affect people's interpretations of the agents' attitudes? an experimental investigation of how the appearance of robotic agents affects interpretations people make of the agents.' attitudes is described. we conducted a psychological experiment where participants were presented artificial sounds that can make people estimate specific agents' primitive attitudes from three kinds of agents, e.g., a mindstorms robot, aibo robot, and normal laptop pc. they were also asked to select the correct attitudes based on the sounds expressed by these three agents. the results showed that the participants had higher interpretation rates when a pc presented the sounds, while they had lower rates when mindstorms and aibo robots presented the sounds, even though the artificial sounds expressed by these agents were completely the same.
encouraging contribution to shared sketches in brainstorming meetings. brainstorming in small design groups typically involves one person taking notes and sketching at a whiteboard while other group members remain seated and contribute verbally. we believe that lowering the threshold for shared sketching improves idea generation from all members and supports building off the ideas of other members. we have designed and completed preliminary testing of a collaborative sketching system that enables simultaneous contribution to and viewing of a shared canvas through individual devices (tablet pcs) and a digital whiteboard. a pilot study indicates that such a system helps equalize sketching contribution within a group although it reduces total sketching of the group as a whole. this finding suggests that individual access to a shared sketching space has implications for the brainstorming process such as a greater awareness of the quality and the relative amount of individual idea contribution.
an interface to aid rural health workers in the preliminary diagnosis of cataract at the slit lamp using locs iii. in india there is an inequitable distribution of wealth and resources; while 70% of population lives in villages, about 80 % of ophthalmologists practice in cities [4]. india has 1 ophthalmologist per 100,000 of its population [4] and this ratio is even more dismal for rural areas. in such circumstances, ophthalmologist- based model is not a cost- effective screening method. on the other hand, an ophthalmologist led screening model offers a cost-effective and feasible screening model for screening of eye diseases. such a model can be beneficial in filling the critical gaps in the government health services. based on ethnographic studies conducted in assam, india, we propose and discuss the design of an experimental interactive interface that can help trained rural health workers diagnose and classify the extent of cataract in the preliminary stages. this has two significant benefits:1. the cataract patients, usually old, and living in rural areas do not have to travel miles away from home only to be told to come back a few months later as the cataract was not sufficiently mature for a surgery yet.2. it provides for a more efficient system that helps the already overburdened ophthalmologists concentrate their time on patients who actually need immediate surgeries thus directly influencing the quality of eye care.
end user software engineering: chi 2007 special interest group meeting. recently, researchers have been working to bring the benefits of rigorous software engineering methodologies to end users who find themselves in programming situations, to try to make their software more reliable. end users create software whenever they write, for instance, educational simulations, spreadsheets, or dynamic e-business web applications. unfortunately, errors are pervasive in end-user software, and the resulting impact is sometimes enormous. this special interest group meeting has three purposes: to bring the results of a recent (february 2007) week-long "dagstuhl" meeting on end-user software engineering to interested researchers at chi; to incorporate attendees' ideas and feedback into an emerging survey of the state of this interesting new subarea; and generally to bring together the community of researchers who are addressing this topic, with the companies that are creating end-user programming tools.
bodyspace: inferring body pose for natural control of a music player. we describe the bodyspace system, which uses inertial sensing and pattern recognition to allow the gestural control of a music player by placing the device at different parts of the body. we demonstrate a new approach to the segmentation and recognition of gestures for this kind of application and show how simulated physical model-based techniques can shape gestural interaction.
i/o brush: beyond static collages. i/o brush is our ongoing effort to empower people to create new expressions and meanings by painting with attributes of everyday objects and movements in their physical world. using examples from our case studies with kindergarteners and artists, we discuss i/o brush's most distinguishing features, its dynamic ink and history functions, and how they enable people to invent new expressions and meaning making with objects in their physical environment.
establishing relationships for designing rural information systems. designing for the developing world presents unique challenges. establishing rapport with local partners is important to overcome contextual unfamiliarity and ensure the relevance of proposed solutions. in this paper, we discuss our experiences designing a cam-based mobile data capture system for asobagri, a rural coffee cooperative in barillas, guatemala. cam is a camera-based mobile application framework designed based on fieldwork with rural microfinance groups in india. our local partners in india are now using the cam framework in a real application. we list some practices that have helped us establish and sustain both these design relationships.
mobile spatial interaction. mobile phones are starting to become the major platform for interaction with spatial information. recent research has yielded promising applications and approaches for exploring, accessing and augmenting information related to the user's immediate surroundings. the chi workshop "mobile spatial interaction" (msi) aims at gathering researchers working on this emerging and multifaceted, but quickly evolving topic. a forum for open dialogue is needed to enable researchers to obtain a picture of the facets and the benefits of mobile spatial interaction as well as its challenges. potential ways to combine the various approaches will be examined and discussed.
converging on a science of design through the synthesis of design methodologies. the goals of this workshop are: (1) to bring together the community of researchers who are exploring innovative design theories and different design methodologies; (2) to evaluate the appropriateness of design methodologies for specific contexts and explore their respective difference and synergies; and (3) to strengthen the community of researchers who are interested and involved to make progress toward creating a science of design.
exploratory search and hci: designing and evaluating interfaces to support exploratory search interaction. the model of search as a turn-taking dialogue between the user and an intermediary has remained unchanged for decades. however, there is growing interest within the search community in evolving this model to support search-driven information exploration activities. so-called "exploratory search" describes a class of search activities that move beyond fact retrieval toward fostering learning, investigation, and information use. exploratory search interaction focuses on the user-system communication essential during exploratory search processes. given this user-centered focus, the chi conference is an ideal venue to discuss mechanisms to support exploratory search behaviors. specifically, this workshop aims to gather researchers, academics, and practitioners working in human-computer interaction, information retrieval, and other related disciplines, for a discussion of the issues relating to the design and evaluation of interfaces to help users explore, learn, and use information. these are important issues with far-reaching implications for how many computer users accomplish their tasks.
journey planning based on user needs. in this paper we discuss potential developments to the design of pre-trip in-home journey planning services, to include support for additional user needs. these needs were identified through stakeholder interviews as contributing to actual decisions in route selection scenarios and include: safety, weather and even fitness. a journey planner was designed to allow users to articulate these constraints and a series of paper prototypes were evaluated through cognitive walkthroughs. an exploratory study compared three designs and provided rationale for the most effective interaction method, informing an implementation plan.
comparing visualizations for tracking off-screen moving targets. in games, aircraft navigation systems and in control systems, users have to track moving targets around a large workspace that may extend beyond the users. viewport. this paper presents on-going work that investigates the effectiveness of two different off-screen visualization techniques for accurately tracking off-screen moving targets. we compare the most common off-screen representation, halo, with a new fisheye-based visualization technique called edgeradar. our initial results show that users can track off-screen moving objects more accurately with edgeradar over halos. this work presents a preliminary but promising step toward the design of visualization techniques for tracking off-screen moving targets.
taking chi for a drive: interaction in the car. with the increasing number of cars on the road, longer commutes, and the proliferation of complex information and entertainment features, there is a greater need for careful interaction design in the car. the automobile is a challenging environment for designing and deploying good user interfaces. interaction designers must balance brand identity, safety, legislation, and manufacturability, among other issues. in this panel, practitioners and researchers from industry, industrial labs, and academia will discuss the challenges of interaction design in an automotive environment. while some members of the chi community are active in the automotive field, the general chi community may not be aware of this work, the open research issues, and opportunities for collaboration in this area. this panel will provide an introduction into hci research in the automotive industry. some successful examples of interaction design will be discussed, as well as a few not-so-successful examples. questions and comments from the audience are welcomed.
awareless authentication: insensible input based authentication. to increase the security of handheld devices, we propose awareless authentication. since insensible input prevents the leakage of the key information, it can provide more secure authentication scheme. experiments that used a pressure sensor show that users can input a preset rhythm by insensible finger motion, and the boundary between insensible and sensible is extended by adding vibration while input.
surrogate users: a pragmatic approach to defining user needs. it is often difficult for practising interaction designers to engage with real end-users because of the competing economic pressures on projects. preliminary research with end-users (a particularly rich source of information) may be squeezed in favour of more tangible, later-stage project deliverables. this case study paper presents a pragmatic approach to getting closer to end-users by briefing project stakeholders to think as surrogate users within managed 90 to 120 minute-long focus groups. it concludes with an evaluation of the approach in terms of the experiences of the research participants and its merits in terms of project delivery and outcomes. it finds that the method described is particularly useful in multi-stakeholder projects and provides a rich design brief with clear, agreed, user-centred design goals.
integrating user performance time models in the design of tangible uis. one of the aspects that are important for judging an application is the time an experienced user needs to complete a task. this can be assessed by a keystroke-level model (klm) of that task. in this paper we show a method that allows designers to prototype hardware applications entirely in software and still be able to draw conclusions about the time to completion of given tasks on the envisioned hardware implementation. we provide versatile, easily extensible tools and examples that give developers quick access to klm data for their prototypes and applications.
distributed tabletops: territoriality and orientation in distributed collaboration. previous research has shown that orientation and territory serve key roles during tabletop collaboration. however, no one has yet investigated whether they can play similar roles in distributed collaboration. in this paper, we design and implement distributed tabletops to address this problem and hence improve distributed collaboration. we show that distributed tabletops allowgeographically-separated collaborators to use orientation and territory to mediate their interactions as they would in co-located collaboration. we also suggest that distributed tabletops offer further benefits such as an increased sense of presence.
blogcentral: the role of internal blogs at work. this paper describes a preliminary investigation into an internal corporate blogging community called blogcentral. we conducted semi-structured interviews with fourteen active bloggers to investigate the role of blogging and its effects on work processes. our findings suggest that blogcentral facilitates access to tacit knowledge and resources vetted by experts, and, most importantly, contributes to the emergence of collaboration across a broad range of communities within the enterprise.
what you said about where you shook your head: a hands-free implementation of a location-based notification system. the mit smart helmet is an ongoing project at the mit media lab that incorporates context-aware technology into a bicycle helmet for the purpose of enhancing rider safety. the following paper is an evaluation of a proposed feature being considered for integration: a location-based notification system that can be operated without the use of the hands.
wikinavmap: a visualisation to supplement team-based wikis. wikis are an invaluable tool for quickly and easily creating and editing a collection of web pages. their use is particularly interesting in small teams to serve as a support for group communication, for co-ordination, as well as for creating collaborative document products. in spite of the very real appeal of the wiki for these purposes, there is a serious challenge due to their complexity. team members can have difficulty identifying the structure and salient elements of the wiki. this paper describes the design of wikinavmap, an alternative visual representation for wikis, which provides an overview of the wiki structure. based on analysis of student wikis, we identified factors that help team members identify which wiki pages are currently relevant to them. we hypothesised that a structural overview coupled with the visual representations of these factors could assist users with wiki navigation decisions. we report a preliminary evaluation with a large group wiki, created over a full university semester by a group of ten users. the results are promising for a small wiki but point to challenges in coping with the complexity of a larger one.
trust 2.1: advancing the trust debate. trust has a considerable research tradition in the chi community. it has been investigated in the context of e-commerce, virtual teams, online gaming, social networking. to name a few. in this paper, we give an overview on this research. we delineate existing research along the key dimensions of objects of trust and related risks, methods and background of research, models of trust, and goals of trust research. our aim is to provide a basis for the discussion at a special interest group (sig), but also to give researchers and practitioners with an interest in the field an entry point to existing work. more importantly we hope that the sig and this abstract will help in driving and structuring future trust research.
visualizing an enterprise wiki. this paper describes the iterative development of a visualization for a wiki used in a large enterprise to manage research projects. an initial prototype-based field study exposed two main usage problems and provided five design ideas, which led to the development of an interactive visualization called cherrytree. the paper describes cherrytree, discusses the reactions of users, and discusses future directions for this work.
designing software for consumers to easily set up a secure home network. home networking continues to expand into a collection of computers and networked devices that are becoming more complex to setup and manage. research indicated that new techniques were needed to help people set up a secure home network. the techniques should satisfy the expectations of advanced users, without requiring technical knowledge on the part of novice users. a central design theme influenced the software solution: if a networking expert was advising a user on how to set up, configure, and secure a home network, what would this person tell the user to do?. in this case study, insights about creating a new home networking program to solve the challenges are discussed. results indicated animations, good default settings and a network map increased the user success rate for network setup.
towards the perfect infrastructure for usability testing on mobile devices. in this paper, we describe various setups that allow usability professionals to conduct effective user studies on mobile devices. we describe the factors relevant when building a solution for mobile device observation and the various designs we worked with in the google user experience research environment as we iterated to meet changing study needs. we highlight several systems that can successfully be used in an industry environment, including a novel setup that is fully portable, can be used in a usability lab as well as in the field, accommodates a large variety of different mobile devices, and allows for live observation by product teams around the world.
let's get emotional: emotion research in human computer interaction. emotion is a topic of growing interest in the hci community. studying emotion within the hci discipline is an exciting interdisciplinary task. this can be facilitated by the exchange of thoughts and ideas with others working on related projects. the aim of this sig is to bring together an interdisciplinary group of researchers and practitioners actively working on projects where emotion is an essential component. the goals of the sig are to identify current themes related to emotion specific hci work and discuss strategies for moving forward.
location, location, location: a study of bluejacking practices. we present an initial exploration of bluejacking, the practice of using bluetooth-enabled mobile phones to send unsolicited messages to other bluetooth-enabled mobile phones within a transmission range of 10 meters. a content analysis was conducted on 427 bluejacks from bluejackq, an online community of bluejackers, in which the contextual characteristics of bluejacking were examined. bluejacking was found to be highly location-dependent, primarily transpiring in everyday public places. the message content of the bluejacks was also inspired by the physical location where bluejacking took place. we also discuss implications of bluejacking with regards to its relationship to public space and comment on how these findings are relevant to mobile social computing.
supporting design studio culture in hci. the workshop considers the needs and possibilities for integrating design studio culture within the research, education, and practice of interaction design and hci. the primary goals of the workshop are (i) to assess the current state of design studio culture within hci in comparison with other design disciplines, (ii) to invite participants to collaborate on the design of the artifice required to support design studio culture within hci, and (iii) to aggregate insights from these designs into strategies for the future.
observation-based design methods for gestural user interfaces. the design of gestural user interfaces is uniquely challenging because the input is freeform, personal, and often carries subconscious meanings that are domain-specific and difficult to articulate. these features suggest an approach of observation-based design: learning from what people do, rather than relying on what they say. to facilitate observation-based design, this dissertation is exploring two design methods: gesture brainstorming, a wizard of oz method for early prototyping of new interfaces, and gesture log analysis, a machine learning-based log analysis method for improving existing interfaces. these design methods will be tested by applying them to two gestural interfaces: a 3d pathway selection interface (cinch, see figure 1), and a 3d modeler (google sketchup). experience with cinch already suggests the utility of observation-based design, while work on google sketchup is anticipated to begin this summer. these test cases should inform observation-based design for gestural user interfaces in general.
making personas memorable. although cisco's tag line for fiscal year 2007 is "lead the experience," not all cisco product teams have historically focused on designing products that facilitate user success and delight. the cisco user experience design (uxd) group provides tools that stimulate a uxd culture, one of which is personas to catalyze a common understanding of users and a centralized persona database. the challenge has been that engineers at cisco could opt out of using personas. this uxd group therefore had to produce personas and artifacts that increase the fun and the stickiness of persona characteristics as a basis for product design. in november 2005, the uxd team won an award for developing best practices in product development for creating these personas by vice presidents from across cisco.
the role of paralinguistic voice-control of interactive media in augmenting awareness of voice characteristics in the hearing-impaired. explaining voice characteristics to the deaf is not an easy undertaking for their instructors. furthermore, many existing strategies for conveying these characteristics and teaching the deaf how to perceive them do not seem efficient, especially when dealing with the concept of pitch. as a result, some deaf people are not fully capable of differentiating between voice characteristics. paradoxically, this doesn.t only apply to the deaf, but many of the hearing do not know the difference between pitch and loudness; when asked to generate a higher-pitched sound, many generate a louder sound. these were some of several reasons that led to my exploration of additional approaches to the visual representation of voice. i developed and employed non-speech voice-controlled applications in analyzing the interaction patterns of seven deaf children. the aim was to explore the potential role of paralinguistic vocal control of interactive media in enabling the deaf to have a greater understanding of voice and to offer their instructors more efficient and engaging strategies for explaining voice characteristics.
airplane: an information retrieval pattern language. interaction patterns and pattern languages have been discussed for years in hci literature yet there have been few empirical studies conducted. we describe airplane: an information retrieval pattern language, its discovery, and the experimental design we use to examine its impact on the design of information retrieval interfaces. the results of a pattern sorting exercise are the focus of this paper.
design and evaluation of 3d models for electronic dental records. we present the results of a field study of some of the work practices and software used by dentists. we also present the design, implementation, and evaluation of a user interface that streamlines some of these practices, as well as providing a novel 3d visualization of a patient's mouth that also displays relevant radiographs depending on what teeth are visible in the visualization. dentists found the 3d synchronized navigation intuitive, even with little to no 3d navigation experience, but further research is needed to see the effect on real clinical outcomes.
management of personal information scraps. we introduce research on information scraps. short, self-contained personal notes that fall outside of traditional filing schemes. we report on a preliminary study of information scraps. nature and outline plans for the next phase of our user study. based on ongoing study results, we describe our designs and prototypes for information scrap capture and access tools.
longitudinal study of continuous non-speech operated mouse pointer. this paper reports a longitudinal study of a non-speech input-controlled continuous cursor control system: whistling user interface (u3i). this study combines quantitative (target acquisition tasks, subjective ratings and a simple reaction time test) and qualitative (interview) methods to arrive at a more nuanced understanding novice users. experience over time. the progress of training of ten participants has been observed. the study shows that the performance improved over time and plateaued on day four of the five days of the study.
coming to terms: comparing and combining the results of multiple evaluators performing heuristic evaluation. in this paper we describe a new way to perform heuristic evaluations, which allows multiple evaluators to easily compare and combine the results of their reviews. this method was developed to provide a single, reliable, result to the client, but it also allowed us to easily negotiate differences in our findings, and to prioritize usability problems identified by the evaluation. an unexpected side effect is that, by using this evaluation method, the practitioner can measure and predict the effect of usability improvements.
speed sonic across the span: building a platform audio game. we describe the design process and initial user study of an audio game created for the visually impaired. until the advent of 3d graphics games, platform games where the player jumps from platform to platform, such as mario and sonic, [1] were wildly popular. although many audio games have been developed over the past decade, the platform genre has been all but ignored. to fill this gap and to add to the limited choices visually impaired gamers have, we developed a platform game that can be also be played via audio-only interface and compared it to a traditional audio-visual version.
altverto: using intervention and community to promote alternative transportation. we seek to motivate drivers who regularly use web-based local and mapping services and have access to viable alternative transit methods - such as public transportation, carpooling, walking or bicycling - to use these alternatives instead of driving alone. altverto works with users' existing habits to intervene during trip planning, and then sustains long-term positive behavior through progress tracking and community-building around alternatives to driving. our study investigates how computer-mediated intervention at decision making moments and online transit-related community motivates and sustains the use of alternative transit methods.
towards a new method for the evaluation of reality based interaction. in this paper we present work toward a new method of evaluation for reality-based interaction styles that we call cognitive description and evaluation of interaction (codein). this framework is similar to goms, but also shares similarities with cognitive architectures, such as act-r and soar. we apply this new approach to a tangible user interface, built as a wizard of oz interface, to illustrate the new method, and compare codein.s results to a goms model. we show that codein provides some promise of representing the parallel processing and new modes of physical interaction inherent in reality-based interfaces, and codein does a better job in predicting the completion time of an example task than goms.
txt 4 l8r: lowering the burden for diary studies under mobile conditions. we present and evaluate a new technique for performing diary studies under mobile or active conditions. diary studies play an important role as a means for ecologically valid participant data capture. unfortunately, when participants are asked to capture data while mobile or active, they are often unwilling or unable to invest time in thorough, reflective entries. ultimately, this leads to lowered entry quality and quantity. the technique presented here suggests the capture of only small snippets of information in the field. these snippets then serve as prompts for participants when completing full diary entries at a convenient time. we describe how this system automates collection of snippets via text (sms), picture (mms) and voicemail messages and later presents these snippets for full entry elicitation. we then present results from a preliminary evaluation of this technique.
using isovist views to study placement of large displays in natural settings. in this paper we present the concept of an isovist, derived from the architectural literature, and describe how isovists can help hci researchers understand visibility in a physical environment. an isovist is defined as the set of all points visible in all directions from a given vantage point in space. the overlap in isovists from two or more locations can be used to assess reciprocal visibility and thereby assist in the placement of large displays for public or shared use. we illustrate the value of isovists for hci research using field data from two or suites in two major urban hospitals. first, we show how patterns of interaction between anesthesiologists and nurses in each of two or suites are associated with quantity of isovist overlap. then, we show how an isovist analysis can be used to determine a better placement for the shared display in one of the or suites to enhance coordination between groups.
imaging the city: exploring the practices and technologies of representing the urban environment in hci. developing and employing technologies for the urban environment requires visualization techniques that can reflect and challenge how and what we design for this space. this one-day workshop will explore the practices and technologies of imaging the city from the perspective of human-computer interaction, bringing together designers, hci experts, and urban planners to deeply address the roles for imaging technologies in civic space.
facebook ride connect. ride connect is a tool integrated into the social networking site facebook's (www.facebook.com) event planning feature. ride connect helps people coordinate transportation to specific events. we chose to focus on undergraduate students because changes in their attitudes and habits towards shared transportation will lead to a sustainable increase in public transportation (pt) use. ride connect encourages pt use through social incentives and by conveniently presenting user-generated transportation options. our study investigates how social incentives and convenient pt information lead to increased pt use, and how pt use, coupled with a reduction in stigma, leads to long-term behavioral and attitudinal changes towards p.
supple interfaces: designing and evaluating for richer human connections and experiences. the aim of this workshop is to create a common language for discussing the issues involved, the research challenges, and progress already made in designing and evaluating "supple" interfaces. supple interfaces aim to build richer connections between people as well as deeper emotional experiences through interface. examples include affective interactive systems, games, and relationship-building systems. for these kinds of applications, the chi community is struggling with a new set of design values and accompanying challenges that can be hard to articulate and thus to advance as a community. these application spaces and interaction modes require an emphasis on the quality of experience rather than outcome, and often involve subtleties of the dynamics of engagement with such interfaces and with others through these interfaces. through hands-on experiences, presentations, and active discussion during the day, we hope to make a start at creating a coherent working framework for this area that can be shared with the larger chi community.
software design and engineering as a social process. traditionally, software engineering processes are based on a formalist model that emphasizes strict documentation, procedural and validation standards. although this is a poor fit for multidisciplinary research and development communities, such groups can benefit from common practices and standards. we have approached this dilemma through a process model derived from theories of collaborative work rather than formal process control. this paper describes this model and our experiences in applying it in software development.
learning shape writing by game playing. we present a computer game designed to efficiently and playfully teach users shape writing - a new text entry method for pen-based devices.
carloop: leveraging common ground to develop long-term carpools. we developed and tested a website and public display to connect and sustain carpoolers in the workplace. we arrived at this design through study of traffic congestion and its causes. after finding that many problems are deeply rooted in transportation infrastructure, we discovered several that could be addressed through design of an interface to carpooling. we found that people are often hesitant to carpool with unknown drivers. our system offers numerous features to create and nurture sustainable carpools, bringing together design principles with organizational principles and workplace knowledge. preliminary testing of our system encourages us that its combination of features could increase the success rate of workplace carpools.
an initial investigation into non-visual computer supported collaboration. in this paper we present an initial study of computer supported collaboration between visually impaired users based around the interactive browsing and manipulation of simple graphs. we specifically looked at supporting awareness of others activities and interaction between participants. we found that shared audio and haptic locating tools, to allow users to find each other, are useful. however further work is required to determine the general applicability of our findings.
dynamics of tilt-based browsing on mobile devices. a tilt-controlled photo browsing method for small mobile devices is presented. the implementation uses continuous inputs from an accelerometer, and a multimodal (visual, audio and vibrotactile) display coupled with the states of this model. the model is based on a simple physical model, with its characteristics shaped to enhance usability. we show how the dynamics of the physical model can be shaped to make the handling qualities of the mobile device fit the browsing task. we implemented the proposed algorithm on samsung mits pda with tri-axis accelerometer and a vibrotactile motor. the experiment used seven novice users browsing from 100 photos. we compare a tilt-based interaction method with a button-based browser and an ipod wheel. we discuss the usability performance and contrast this with subjective experience from the users. the ipod wheel has significantly poorer performance than button pushing or tilt interaction, despite its commercial popularity.
fast-tracking product innovation. this paper describes the coming-of-age of an analytical application that was built using agile development processes, tightly interlinked with an iterative user experience methodology, but at times at odds with the legacy of more rigid development methods such as prescriptive pattern-based design and strictly separated core disciplines. we pioneered a variety of ways to deal with these challenges, most of which focused on empowering the user experience discipline in decision-making processes, development impact, and in leading product definition overall. this ensured that innovative forces were least constrained while fast-tracking this product, while still achieving effectiveness, efficiency, and satisfaction of the application's user experience.
the sound of touch. in this paper we describe the sound of touch, a new instrument for real-time capture and sensitive physical stimulation of sound samples using digital convolution. our hand-held wand can be used to (1) record sound, then (2) playback the recording by brushing, scraping, striking or otherwise physically manipulating the wand against physical objects. during playback, the recorded sound is continuously filtered by the acoustic interaction of the wand and the material being touched. our texture kit allows for convenient acoustic exploration of a range of materials.an acoustic instrument.s resonance is typically determined by the materials from which it is built. with the sound of touch, resonant materials can be chosen during the performance itself, allowing performers to shape the acoustics of digital sounds by leveraging their intuitions for the acoustics of physical objects. the sound of touch permits real-time exploitation of the sonic properties of a physical environment, to achieve a rich and expressive control of digital sound that is not typically possible in electronic sound synthesis and control systems.
neat-o-games: ubiquitous activity-based gaming. the role of non-exercise activity thermogenes is (neat) has become a key component of obesity research, prevention, and treatment. this paper describes research that aims to suppress the obesity epidemic by infusing neat in the sedentary lifestyle of an average person. the method combines unobtrusive physiologic sensing and novel human-computer interaction (hci) technologies. it supports a strong motivational framework based on ubiquitous computer gaming, appealing enough to likely change the behavior of "couch potatoes" on their own volition. this novel generation of computer games (neat-o-games) is fueled by activity data recorded by small wearable sensors. data from the sensors are logged wirelessly to a personal digital assistant/cell phone (pda), which acts as the central computing unit of the system. algorithmic software processes these data and computes the energy expenditure of the user in real-time. the paper presents a prototype implementation of neat-o-games and initial evaluation results.
moving ux into a position of corporate influence: whose advice really works? professionals working to move user experience (ux) into a position of corporate influence are impeded by conflicting recommendations, including those regarding the roles of documenting and evangelizing ux work, ownership of ux, organizational positioning, calculating return on investment, and conducting "ethnographic" research. in this interactive session, a group of senior ux management personnel who have moved ux into positions of rapidly increasing influence in their varied places of work debate their different perspectives and approaches to help resolve conflicting recommendations and generate some new and improved guidance.
celerometer and idling reminder: persuasive technology for school bus eco-driving. we are designing a feedback system to encourage more fuel-efficient driving habits among school-bus drivers. we chose to design for the school bus because as one of the largest public transport systems in the u.s., it is a major contributor to the country's total fuel consumption and pollutant emissions. our design uses persuasive technology to discourage excessive idling and aggressive driving by providing real-time in-vehicle feedback for self-monitoring.
defining high-throughput email users. in this paper we make the case for the existence and importance of a special class of email user, the high-throughput email user, whose needs are not well-served by current clients. we establish these groups by quantitative and qualitative definitions derived from fieldwork, a large-scale survey, and subsequent analysis of the user population, along with analysis of current email clients. we conclude with directions for future research.
osi and et: originating source of information and evidence traceability. originating source of information (osi) is the idea of following all data, facts, and citations that documents rely on for their arguments back their source. osi then helps people perform evidence traceability (et), which allows them to understand the questions about the different sources used in documents such as how many unique sources were used, where the sources came from, when the sources were obtained, and how the sources were obtained. answering these questions allows people to better question the validity of documents, reevaluate hypotheses, or continue work or research when original authors are not available.
touch: sensitive apparel. touch•sensitive is a haptic apparel that allows massage therapy to be diffused, customized and controlled by people while on the move. it provides individuals with a sensory cocoon. made of modular garments, touch•sensitive applies personalized stimuli. we present the design process and a series of low fidelity prototypes that lead us to the touch•sensitive apparel.
pottering: a design-oriented investigation. in this paper we examine a ubiquitous yet overlooked aspect of home-life, pottering. the oxford english dictionary defines pottering as "to occupy oneself in an ineffectual or trifling way; to work or act in a feeble or desultory manner; to trifle, to dabble." it is thus a term used to describe a variety of activities but none in particular. below, we give shape to the practice of pottering and in doing so aim to demonstrate how such an investigation has broad implications for hci and designing for the home. we also report on our experiences of using design sketching as an analytical resource.
user centered design and international development. this workshop explores user centered design (ucd) challenges and contributions to international economic and community development. we are addressing interaction design for parts of the world that are often marginalized by the global north as well as people in the global north who are themselves similarly marginalized by poverty or other barriers. we hope to extend the boundaries of the field of human computer interaction (hci) by spurring a discussion on how existing ucd practices can be adapted and modified, and how new practices be developed, to deal with the unique challenges posed by this context.
interactive exploration of city maps with auditory torches. city maps are an important means to get an impression of the structure of cities. they represent visual abstraction of urban areas with different geographic entities, their locations, and spatial relations. however, this information is not sufficiently accessible today to blind and visually impaired people. to provide a non-visual access to map information, we developed an interactive auditory city map, which uses 3d non-speech sound to convey the position, shape, and type of geographic objects. for the interactive exploration of the auditory map, we designed a virtual walk-through. this allows the user to gain an overview of an area. to be able to focus on certain regions of the map, we equip the user with an auditory torch. with the auditory torch users can change the number of displayed objects in a self directed way. to further aid in getting a global idea of the displayed area we additionally introduce a bird's eye view on the auditory map. our evaluation shows that our approaches enable the user to gain an understanding of the explored environment.
ri-ri: assisting bus conductors in madras (chennai). in this paper, we present a tool to increase the efficiency of public transport buses inside the metropolitan city of madras (chennai) in south india. the amount of people dropping out of the public bus system is growing at an alarming rate, and arresting this problem is at the root of our prototype. by increasing efficiency of the system, we hope that this problem will be stopped and will lead to more people entering the system, rather than abandoning it.
extending a theory of remote scientific collaboration to corporate contexts. in this paper we present preliminary results of a research project aimed at understanding the theoretical basis for successful remote collaboration in corporations. we evaluate some corporate distributed teams with respect to a theory of remote scientific collaboration to identify similarities and differences in corporate contexts. preliminary results indicate that distance collaboration in corporations differs from distance collaboration in scientific research in three key ways: (1) the importance of functional (as opposed to geographic) distance, (2) new collaboration paradigms (i.e. offshoring) with varying degrees of.otherness. and (3) different incentives. we additionally discuss future research plans based upon our initial findings.
making dead history come alive through mobile game-play. this work in progress presents a design approach to digitally enhancing an existing paper-based game to support young students learning history at an archaeological site, by making use of recent advantages provided by mobile technology. it requires minimal investments and changes to the existing site exhibition because it runs on the visitors. own cellular phones. it is expected that game-play will trigger a desire to learn more about ancient history and to make archaeological visits more effective and exciting.
the internal consultancy model for strategic uxd relevance. experts in the field of hci have spoken at length about how to increase the strategic influence of user experience design (uxd) teams in industry [3]. some have offered courses in hci management [1]. others have presented recommendations on how to prove a return on investment for usability-related activities [2]. nielsen [5] has described the usability maturity model, presenting implicit management challenges and structures at different phases.few though have discussed the value and process for an embedded uxd group functioning as an internal consultancy to different product teams within their organizations, and how this model can increase the strategic relevance of uxd in their companies. the cisco uxd group evolved through several funding and organizational models (central funding, client-funding, distributed teams), and now follows an internal consultancy model. this paper describes the experiences that led to this model and how it has helped increase the strategic influence of uxd within cisco.
rexplorer: a mobile, pervasive spell-casting game for tourists. rexplorer is a mobile, pervasive spell-casting game designed for tourists of regensburg, germany. the game uses location sensing to create player encounters with spirits (historical figures) that are associated with historical buildings in an urban setting. a novel mobile interaction mechanism of "casting a spell" (making a gesture by waving a mobile phone through the air) allows the player to awaken and communicate with a spirit to continue playing the game. the game is designed to make learning history fun for young (and young at heart) tourists and influence their path through the city.
hci and new media arts: methodology and evaluation. successful collaborations between new media arts and hci tend to develop hybrid techniques that promote balanced contributions from both disciplines. however, since many of these collaborations are one-off or highly dependent on the researchers/artists involved, systematic discussions of the role and impact of the various evaluation techniques and methodologies are missing. this workshop is aimed at practitioners from both hci and the arts as a venue to discuss the contribution that one another's techniques have made to their own practice, evaluate critical issues in hci/new media collaboration, and examine ways that existing approaches can be extended for a deeper role in practice, design, and research.
tangible user interfaces in context and theory. tangible user interface (tui) research has become increasingly widespread over the past 25 years. it is an essential component of ubiquitous computing and augmented reality research. it introduces many challenging problems in the theory and practice of interaction design. however much day-to-day research is concerned with the practicalities of making these systems work. in this workshop, we focus on the analytic and generative theories of tui use, and the ways in which these can be applied to the design and evaluation of tuis in real contexts.
towards a tool for predicting user exploration. cogtool-explorer is a tool to predict user exploration choices given a user interface and task. we describe the integration of components that make up cogtool-explorer, and how it interprets the text of both the task description and interface elements to make its exploration choices. we present cogtool-explorer's performance on a web navigational search task compared to human performance.
persona based rapid usability kick-off. the paper reports on the evaluation of a rapid usability kick-off technique (ruko). ten mobile service development projects in the company applied the technique during the early analysis phase. the technique was designed for non-usability experts (nues), to enable them to perform usability work. the effect was that usability awareness and end user focus in projects increased. however, there was an increased need for usability expertise in later phases.
mandala: supporting social presence and interaction in the chinese home. multiple factors lead social software to be unevenly adopted by differing age segments in urban china. this paper presents user research to understand the discrepancy between parents and their children and attempts to address them with the design of an information appliance. the appliance uses novel techniques to magnify and emphasize unidirectional social presence data so as to comply with cultural social protocol. it attempts to support interaction ranging from peripheral awareness to real-time conversation. initial reactions to the design are also presented.
sensemaking handoff: theory and recommendations. sensemaking work is often handed off between people. yet handoff can cause problems, somewhat similar to an interruption. this dissertation examines the issues related to sensemaking handoff by integrating existing theories and drawing predictions about the effects of premature handoff. these predictions and the related design recommendations for systems will be verified using short-term ethnography, interviews, laboratory observations and experiments.
environmental sustainability and interaction. by its nature, the discipline of human computer interaction must take into consideration the issues that are most pertinent to humans. we believe that the chi community faces an unanswered challenge in the creation of interactive systems: sustainability. for example, climate scientists argue that the most serious consequences of climate change can be averted, but only if fundamental changes are made. the goal of this sig is to raise awareness of these issues in the chi community and to start a conversation about the possibilities and responsibilities we have to address issues of sustainability.
k-menu: a keyword-based dynamic menu interface for small computers. in this paper, we introduce k-menu, a keyword-based dynamic menu interface. when a user enters a keyword, a menu with items related to the keyword is constructed dynamically and presented to the user. we implemented k-menu as a top-level interface for major mobile applications and mobile web services on a smartphone environment. a subsequent user test confirmed the task efficiency and the user acceptance of k-menu.
conversation votes: enabling anonymous cues. in this work we describe conversation votes, a visualization to create new backchannels in conversation and augment collocated interaction. we expand the idea of a social mirror, a reflection of interaction, to incorporate direct user feedback in the form of anonymous voting. by capturing user input, the mirror becomes more demonstrative of context as participants add their interpretation into the visualization. the end result produces a visualization to provide a more accurate reflection of interaction and create flags of salient moments in conversation.
carpool.umd: community carpooling. with the demand on energy resources increasing as the supply decreases, energy costs in the united states have been at an all-time high. despite these costs, congestion is still steadily increasing. carpooling has for a long time been an option to help reduce congestion, but commuters currently under use it. carpool.umd is a social-networking website designed to make carpooling to and from the university of maryland, college park easier. the website allows users to search for carpools, learn more about other riders and manage their carpools. carpool.umd aims to create a safe and friendly community as well as making it convenient to carpool to and from the university.
usability and free/libre/open source software sig: hci expertise and design rationale. the usability of free/libre/open source software (floss) is a new challenge for hci professionals. although hci professionals are working on usability issues in floss, the chi community has not yet organized with respect to floss. the purpose of this sig is to bring together hci professionals and researchers to discuss current issues in floss. specifically, this sig looks at usability, the role of hci expertise, and design rationale in floss projects.
walkmsu: an intervention to motivate physical activity in university students. in this paper, we describe an interface whose application is designed to motivate college students to increase their level of physical activity in daily life. the design idea is based on inducing a.just in time. intervention when a user is in a decision making stage. the design described in this paper is a spatial intervention which is intended to increase awareness towards physical activity while students negotiate the urban landscape of a college campus.
"get real!": what's wrong with hci prototyping and how can we fix it? a prototype of computing technology.as a means to evaluate and communicate a good idea.is often an essential step towards useful, shipping products and towards a deeper understanding of what people really need. prototyping and user evaluation can be enormously expensive and failure rates are high. moreover, prototype user evaluations are often far from real with respect to user representatives, tasks, and measures. but to.get real. in hci prototyping and evaluations risks placing even greater (more unrealistic) demands upon the hci researcher. do very real costs and constraints force hci prototyping to the margins? can we change acceptable hci prototyping methods, helping hci prototyping "get real," in both its conduct and in the implications of its results.
minimizing modality bias when exploring input preferences for multimodal systems in new domains: the archivus case study. in this paper we discuss the problems faced when trying to design an evaluation protocol for a multimodal system using novel input modalities and in a new domain. in particular, we focus on the problem of trying to minimize bias towards certain modalities and interaction patterns. such bias might be introduced by experimenters in the instructions given to users which explain how the system can be used.
shared encounters. our everyday lives are characterised by encounters, some are fleeting and ephemeral and others are more enduring and meaningful exchanges. shared encounters are the glue of social networks and have a socializing effect in terms of mutual understanding, empathy, respect and thus tolerance towards others. the quality and characteristics of such encounters are affected by the setting, or situation in which they occur. in a world shaped by communication technologies, non-place-based networks often coexist alongside to the traditional local face-to-face social networks. as these multiple and distinct on and off-line communities tend to carry out their activities in more and more distinct and sophisticated spaces, a lack of coherency and fragmentation emerges in the sense of a shared space of community. open public space with its streets, parks and squares plays an important role in providing space for shared encounters among and between these coexisting networks. mobile and ubiquitous technologies enable social encounters located in public space, albeit not confined to fixed settings, whilst also offering sharing of experiences from non-place based networks. we will look at how to create or support the conditions for meaningful and persisting shared encounters. in particular we propose to explore how technologies can be appropriated for shared interactions that can occur spontaneously and playfully and in doing so re-inhabit and connect place-based social networks.
prime iii: a user centered voting system. mr. wilson never votes. he doesn't vote because he is not confident in his reading capabilities; however, he decided that he will vote this year because he heard that blind people will be able to privately cast their vote. he said, "if blind people can vote, then so can i" at the voting precinct, he shows his identification and receives a blank, numbered ballot sheet. he enters a voting booth, placing the ballot into the printer. using a headset with a microphone, he is able to make his selections by speaking numbers, which gives him confidence that his vote is private. before printing his ballot, he listens to a summary of his selections. he leaves the voting booth and places his printed ballot into a secure box. like mr. wilson, there are millions of people that don't participate in our electoral process due to disabilities and lack of confidence in the equipment. through usable security, prime iii aims to broaden voter participation and confidence.
design and evaluation of reduced-functionality interfaces. many types of reduced-functionality interfaces have been proposed to manage user interface complexity. this dissertation research explores issues of evaluation and feasibility within this space.
ears ))): a methodological framework for auditory display design. in this paper we will present a methodological framework for the design of auditory displays called ears ))). it provides methods to create, maintain and apply design knowledge in the form of design patterns for experts and novices to effectively re-use existing expertise. the context space, a key concept in the framework is presented which allows efficient matching of design problems and design knowledge to advance the use of the auditory interaction channel in human-computer interaction.
decision-making strategies in design meetings. this project aims to further our understanding of the practice of user-centered design (ucd) by observing the argumentation strategies used by designers in face-to-face meetings in the critical periods between usability research and prototype iteration. in order to conduct such an investigation, i recorded ten meetings of graduate student designers charged with redesigning documents for the united states postal service. i then used discourse analysis techniques to determine how the designers used findings from research phases as evidence to support proposed design decisions in meetings concerning prototype alterations. results show that these designers overwhelmingly do not support their design decisions with specific evidence from usability studies. this neglect of research-based evidence may indicate that these novice ucd designers may resort to designer-centric design behaviors in decision-making periods. my analysis will focus on the rhetorical reasons why designers may avoid research-based evidence.
gazetop: interaction techniques for gaze-aware tabletops. gazetop is a tabletop system that tracks multi-user eye movement in a co-located setting. knowledge of eye movement is highly relevant to tabletop interaction: eyes can point to distant targets on large tables, address usability issues imposed by rotation sensitive objects, such as menu and text, and facilitate new types of multimodal interactions. this research will evaluate a set of novel eye-controlled interactions and explore the design space of gaze-aware tabletop systems.
evaluating experience-focused hci. there is growing interest in experience-focused, rather than task-focused, hci. task-focused hci has developed methods for creating and validating knowledge, but those methods may not be applicable or sufficient for experience-focused technology. in particular, new evaluation techniques to validate knowledge need to be created, discussed, and understood. i address this in three ways. first, it is important to understand the historical, technical and social factors that impact the evaluation criteria the community consider valid today. second, i propose an ethnomethodological approach to evaluation that emphasizes the ways users use and make sense of technologies. and third, i demonstrate the validity of my approaches by means of several case studies.
playing with fire: participatory design of wearable computing for fire fighters. in this paper we present our approach of using game-like techniques for designing wearable computing solutions for the paris fire brigade, consisting of namely a board game and a virtual environment for collaborative prototyping during simulated interventions. we provide first results on the approach.s benefits and difficulties.
authorable virtual peers for children with autism. for my dissertation, i am designing, implementing and evaluating the use of a new kind of.authorable. virtual peer that allows children with autism to learn about reciprocal social interaction by building their own virtual humans. this work has three stages: (1) study the verbal and nonverbal reciprocal social interaction behaviors of children with autism; (2) use the results of the study to design and implement an authorable virtual peer for children with autism; and (3) evaluate the effectiveness of the system in improving reciprocal social interaction behaviors of children with autism.
designing for totality of mobile and non-mobile interaction: a case study. the focus of the project is to design for mobile needs of users to support activities that closely relate to non-mobile contexts. we selected the real estate industry for a case study and conducted an in-depth research to gain a deeper understanding of the office (non-mobile) and mobile work environments of realtors and the social context of interaction with their clients. we identified some unique challenges that such a mixed work environment proposes. recording contextual data in the mobile environment and streamlining it with huge amount of other related unorganized information in the non-mobile environment was identified as the main challenge. we designed an integrated system of a web-based application "remap" (for information analysis) and a mobile device "notepod" (for information capture). the paper talks about some of the main research and findings, the design concept proposed, and finally some lessons learnt that we could extend to similar mixed contexts.
in-between theory and practice: dialogues in design research. why wait? and betwixt are two of the workshops we have recently run on the theme of in-between-ness. the approach of social computing, where researchers work to understand how the socio-cultural aspects of human life relate to the design of new technologies, was the starting point for our investigation. by observing actual instances of in-between-ness in context we explored how design activities can be used as an opportunity to discuss and take positions on a specific theme, and as a space for narrowing the gap in design research between theoretical and practical thinking.
towards systematic research of multimodal interfaces for non-desktop work scenarios. non-desktop workplaces often generate challenging multitasking situations for a user attempting to interact with supporting technology. multimodal applications promise great advantages in this type of context. however, current research does not provide enough knowledge for the ergonomic optimization of multimodal interfaces. in order to advance in the research area concerning non-desktop work, a systematic research approach is needed. this paper discusses a possible strategy for advancing towards systematic research, and describes a preliminary experiment attempting to evaluate a real scenario using this strategy.
a theory-based approach to designing student learning context. how can we keep technology-focused computing and software engineering students interested and engaged in a soft subject like hci? how can we avoid leaving the less gifted and less enthused students behind in a 12-week module packed with theories, methodologies and with a new development tool to learn? this paper describes how educational research findings were deployed to address the above issues across four semesters in an hci module at a uk university. kolb's experiential learning cycle was successfully applied to the design and scheduling of course content and learning activities to enhance students' learning outcomes. surveys of the students - both at the beginning and at the end of each semester - consistently showed improvement in students' understanding, perception and satisfaction with the module.
learning observation skills by making peanut butter and jelly sandwiches. in this report we describe our experience conducting a class activity where students learned and practiced observation skills. in the activity, students in small groups observed and were observed making peanut butter and jelly sandwiches. the groups then used their observations to sketch designs for a peanut butter and jelly maker that they presented to the class. we found that the activity helped students learn about the difficulties involved in observing and being observed. it also taught them about the value of observing users, even if they are performing tasks familiar to the observer. having international students in the class brought an additional perspective to the activity which benefited everyone. these students discussed the difficulty of observing experts conduct tasks that are unfamiliar to the observer. in spite of the overall positive outcome, we discuss ways of improving the activity given our experience.
how to look beyond what users say that they want. this paper shares our experience with a strategic design project for defining the key user experience scenarios for utilizing location information available on mobile devices. while the domain area has been known both in industry and academia alike for many years, our stakeholders wanted to know what would be most appealing user experiences in the coming years, particularly beyond what is expected and available in the market right now. therefore gaining confidence in understanding user needs and desires was considered crucial in the project. we pursued two main tracks of design research activities to bring insights on the current users' perceptions, needs and wants (contextual interviews) as well as implicit wishes and aspirations (exploration probes and creative workshop) we should fulfill when designing location aware solutions. we describe our rationales of how we designed the design research process, and compare the results of the two tracks.
ui toolkit for non-designers in the enterprise applications industry. this report describes a user interface (ui) toolkit used for prototyping by non-designers. the toolkit enables the development of standardized ui wireframes and click-through prototypes that comply with user experience ui style guides and design specifications.
implementation of interactive poster "suipo". this paper explains an implementation of new media "suipo," or suica poster, which uses a combination of ic card ticket "suica" and internet accessible mobile phone. customers can get e-mail information by touching their ic card ticket on the reader located near the poster. two pilot tests are conducted before the service has begun. the first test revealed that many people preferred the interactive poster but the registration process was complicated. the second test was conducted after improving the registration process. the lessons learned through two pilot tests are that in addition to the easier registration process, the increased popularity of two dimensional barcode reader in mobile phone has lowered the barrier of registration process. the suipo has been introduced in july 31st, 2006 and started service at shinjuku station and tokyo station. we hope the implementation would change customers' perception of suica not only as a ticket or e-money but also as an information tool.
how informances can be used in design ethnography. in this paper we discuss how we've adapted the technique of informance design for use in design ethnography. we detail our design ethnography workflow method and describe our informances.
semantic web hci: discussing research implications. semantic web progress is very active, and this past year shows a much greater focus on the subject of user interaction. w3c leaders talk about the importance and.grand challenges. for user interaction. workshops showcase more well-developed projects and innovative interaction designs. a w3c mailing list has begun. but what are the implications for the hci community? what research and practice contributions can be made, and what relationships can be fostered with the semantic web research community? this collaborative, interactive session will give chi participants a chance to discuss the issues that have surfaced at recent semantic web workshops.
recommendations on recommendations. this interactive session discusses the quality of recommendations for improving a user interface resulting from a usability evaluation. problems with the quality of recommendations include recommendations that are not actionable, ones that developers are likely to misunderstand, and ones that may not improve the overall usability of the application. the session will discuss characteristics of useful and usable recommendations, that is, recommendations for solving usability problems that lead to changes that efficiently improve the usability of a product. to make the session as useful as possible we have deliberately left 2-3 panel seats open for people with demonstrated abilities in writing useful and usable recommendations. we intend to fill these seats through a pre-conference contest.
soap: how to make a mouse work in mid-air. computer mice do not work in mid air. the reason is that a mouse is really only half an input device - the other half being the surface the mouse is operated on, such as a mouse pad. in this demo, we demonstrate how to combine a mouse and a mouse pad into soap, a device that can be operated in mid air with a single hand. we have used soap to control video games, interact with wall displays and windows media center, and to give slide presentations.
the mixed reality book: a new multimedia reading experience. we are introducing a new type of digitally enhanced book which symbiotically merges different type of media in a seamless approach. by keeping the traditional book (and its affordance) and enhancing it visually and aurally, we provide a highly efficient combination of the physical and digital world. our solution utilizes recent developments in computer vision tracking, advanced gpu technology and spatial sound rendering. the systems' collaboration capabilities also allow other users to be part of the story.
tangible programming in the classroom with tern. this interactivity demonstrates tern, a tangible programming language for middle school and late elementary school students. tern consists of a collection of wooden blocks shaped like jigsaw puzzle pieces. children connect these blocks to form physical computer programs, which may include action commands, loops, branches, and subroutines. with tern we attempt to provide the ability for teachers to conduct engaging programming activities in their classrooms, even if there are only one or two computers available. in designing tern, we focused on creating an inexpensive, durable, and practical system for classroom use.
impulse. impulse is a modular design object that senses pulse and allows users to wirelessly transmit their heartbeat rhythms to companion impulse units. by synchronizing light and vibrations with users' personal heartbeats, these devices create intimacy across distance.
emi: a system to improve and promote the use of public transportation. this paper presents a project to improve the public transportation in the city of huajuapan de león, oaxaca, méxico. interactive multimedia stations (emi, for its spanish acronym), the system proposed here, has the following purposes: to increase the use of public transportation through an information system comprised of routes and schedules, to improve public services with a module of users. complaints and suggestions, along with a module of incentives, which would raise the awareness of a culture of road safety education through informative capsules to the general public.
txt bus: wait time information on demand. this paper describes an sms based text messaging system that delivers real time bus information to users' mobile phones. many public transit systems provide schedule and fare information on their web sites, and a small subset of these have recently experimented with bus stop countdown displays. in contrast, an sms based delivery system allows users to receive real time updates wherever they may be. given that lack of information is an often cited barrier to transit use, particularly among "choice riders" (i.e. those who have access to other forms of transit), such a solution also creates an opportunity for transit organizations to improve their services, thus promoting ridership [6].
senior travel buddies: sustainable ride-sharing & socialization. we are developing a system to be implemented at continuing care retirement communities (ccrcs) throughout the united states in an effort to encourage ride-sharing among residents in order to decrease their carbon emissions. we are focusing on senior citizens for two reasons. they are a growing segment of the population with driving habits that result in higher pollution, but they are also a population that is at risk of isolation and the mental and physical harm that can result from being isolated. our system addresses both of these issues while leveraging the infrastructure and culture of ccrcs in addition to hiding the technology from the senior residents themselves.
the vvip system: encouraging the use of public transport in edinburgh. this article is concerned with the encouragement and promotion of the use of buses in edinburgh, especially among visually impaired users and tourists / migrant workers. the report outlines the key issues these groups encounter when using buses, and introduces vvip, or visual and vocal information platform as a solution. the report contains detailed research methodology and findings which led to the development of vvip, and the design and evaluation procedures undertaken by the group. vvip is a cost effective and easily deployed dynamic location based system which offers passengers a visual and auditory display of where the bus is in relation to its next stop facilitating and improved bus travel experience.
comparing internal uxd business models. experts in the field of hci have spoken at length about how to increase the strategic influence of user experience design (uxd) teams in industry [3]. some have offered courses in hci management [1]. others have presented recommendations on how to prove a return on investment for usability-related activities [2]. this sig is an extension of the chi experience report.the internal consultancy model for strategic uxd relevance,. [5] and explores four common uxd organizational models. in this sig, we will develop a swot analysis (analyzing strengths, weaknesses, opportunities, and threats) of each model. the sig will facilitate a systematic exploration by attendees whose organizations follow, or are considering, one or more of these models. it will result in a broader understanding for managers of uxd teams on how they can optimally structure their internal uxd functions, given their unique corporate environments and cultures.
evaluating experience-focused hci. a growing trend in the field is the development of experience-focused hci, which emphasizes the experience of using the technology, rather than the focus on the task that is characteristic of many other approaches hci. a focus on experience also means that research concentrating on such technologies produces a different kind of knowledge than task-focused hci, and that this knowledge must be validated in different ways. importantly, this focus means that evaluation techniques designed for evaluating task-focused measures, such as classical notions of usability, are inadequate (although far from unnecessary) for the evaluation of experience. in this sig, participants who are interested in designing, building or currently evaluating experience-focused projects will discuss ways to do so. this sig is intended to appeal to a broad cross section of the chi community, ranging from practitioners and developers to computer and social scientists.
sig: capturing longitudinal usability: what really affects user performance over time? in this special interest group (sig) the attendees will discuss methods for capturing usability data over time. specifically, we will share industry best practices, brainstorm alternative solutions, as well as compare and contrast usability engineering methods for capturing usability problems that persist over time. we will also explore why longitudinal research is not a more common ucd practice.
social impacts of a video blogging system for clinical instruction. in the past decade, digital technology has become widely integrated into many professional training settings, yet at present we lack a detailed understanding of how new technology alters networks of social and technology-mediated interactions present in such environments. i have been engaged in a multi-year ethnography-for-design study in a dental hygiene training program in national city, ca. during the project, i helped design a new clinical training laboratory, equipped with embedded digital media technology, such as flat-panel monitors, computer workstations and overhead cameras. here, i detail the ethnographic motivations for the design of the technology integrated into the training program. i also present an analysis of how a collaborative video blogging system (a .vlog.), used in an introductory clinical instruction course, affects the network of social and technology-mediated interactions. in particular, i examine how interactions with videos structured the way students and instructors work with each other in the clinic. additionally, i report how the faculty.s acceptance of technology was influenced by the presentation of divergent methodology in the vlog content.
the impact of digital iconic realism on anonymous interactants' mobile phone communication. in this paper, i describe progress in research designed to explore the effect of the combination of behavioral and visual fidelity of avatars on users. social presence in synchronous and emotionally engaged mobile phone communication. i specifically focus on ways to secure mobile phone users. anonymity while preserving their most important nonverbal affective behaviors. the research measures social presence in several dimensions, and investigates the impact of combinations of behavioral and iconic realism of avatars on the measures.
2d meets 3d: a human-centered interface for visual data exploration. there is still a controversial debate on the usefulness of 3d user interfaces. most of the time, 2d metaphors are force-fitted to establish a rich set of functionality. with the aim of shifting the 20-year-old 2d wimp (windows, icons, menus, and pointing device) paradigm towards a more natural and intuitive 3d user interface, we have developed a hybrid 2d + 3d prototype targeted at immersive environments. our complementary display and interaction environment combines visual design techniques with mixed-mode interaction to support typical tasks of information workers to the greatest potential. to achieve this, we match visualization and interaction metaphors by the principle of dimensional congruence. this results in a sophisticated and more intuitive user interface. an ongoing evaluation gives encouraging feedback and shows that even non-expert users can efficiently work with the system.
an investigation into the use of spatialised sound in locative games. this paper shows how spatialised sound can be used to guide users around a located gaming environment. thus far, despite growing interest in delivering location-relevant media information to users, accurate delivery of virtual spatialised sound using limited-processing portable devices, such as personal digital assistants (pdas), has not yet been explored. the use of spatialised sound allows users to judge accurately which direction a virtual sound is coming from through a pair of stereo headphones. the initial findings of this research demonstrates that spatialised sound can be used to navigate users in a locative game running on a pda.
posture monitoring and improvement for laptop use. both repetitive stress injuries and laptop use have increased. the poor ergonomic design of laptops has the potential to create or exacerbate existing rsi. we propose a persuasive attentive user interface which provides feedback in order to improve user neck posture. this system measures the angle of the user.s neck and determines the quality of his/her neck posture. we then provide exercises to strengthen the neck and improve the user.s posture. we performed a study which showed an increase in neck comfort among our system.s users. the study demonstrated the potential of our system, which should be further tested.
a study of co-worker awareness in remote collaboration over a shared application. following recent developments in groupware that allow teams of co-located and distributed users to work simultaneously on a shared application, differences in the relative awareness of co-located and remote users have been identified. this paper examines users' perceived awareness of others and their observed direction of attention in this context. a study of six groups of three users distributed across two sites reveals that the disparity in awareness between co-located and remote users may not be such a problem as previously suggested. results also show that for the tasks employed herein, users rely predominantly on cues within the shared application such as multiple cursors, rather than the videoconference channel, to remain aware of the actions of their collaborators. the study also provides further evidence for the importance of additional awareness cues, such as "video arms".
malibu personal productivity assistant. the malibu system provides peripheral access to andawareness of activities, tasks, social-bookmarkresources, and feeds to assist knowledge workers intheir activity-centric work. we describe theexperimental system, a usage scenario and somepreliminary usage data.
socialbrowsing: integrating social networks and web browsing. in this paper we introduce socialbrowsing, a firefox extension that adds social context to the web browsing experience. the extension is paired with services provided by social networking websites, analyzes the page's contents, and adds tooltips and highlighting to indicate when there is relevant social information. we present an overview of the tool and implementation, and outline future steps for analysis.
improving dictionary-based disambiguation text entry method accuracy. text entry on mobile devices is problematic because of ever-decreasing device sizes. dictionary-based keypad text entry methods are relatively effective, but still run into problems of word ambiguity, especially when used with small numbers of keys. common text entry disambiguation methods only use word frequency information to resolve conflicts. this paper proposes a new method that also looks at semantic information (distances between word meanings). simulations show encouraging results, suggesting potential practical applications of this method to mobile devices.
addressing constraints: multiple usernames task spillage and notions of identity. in this work in progress report, we present preliminary results from an interview study on people's use of email addresses and instant messenger usernames. based on these interview findings, we speculate that many people use multiple identifiers reactively and prosaically, rather than simply proactively and strategically. this has implications for understanding the scope of previous studies; for developing cross-platform methodologies for analysis of people's practices; for understanding identifier selection; and for design of communication tools and protocols. we believe that a focus on "identity", which we characterize to be a set of strategic and coherent practices for self-presentation/protection, has led to an under-representation of reactive and prosaic practices of identifier selection that can result from organizational policy, technological implementations, and social and task information flow management.
new parameters for tacton design. tactons (tactile icons) are structured vibrotactile messages which can be used for non-visual information presentation. information can be encoded in a set of tactons by manipulating parameters available in the tactile domain. one limitation is the number of available usable parameters and research is ongoing to find further effective ones. this paper reports an experiment investigating different techniques (amplitude modulation, frequency, and waveform) for creating texture as a parameter for use in tacton design. the results of this experiment show recognition rates of 94% for waveform, 81% for frequency, and 61% for amplitude modulation, indicating that a more effective way to create tactons using the texture parameter is to employ different waveforms to represent roughness. these results will aid designers in creating more effective and usable tactons.
talking about "stuff": artifacts and expectation in social communication. in this work, we use qualitative field studies to examine the role of physical artifacts in conjunction with and comparison to digital communication. we investigate what people convey through the choice of a communicative medium, how choices of medium are perceived and intended, and how people combine digital and physical media and artifacts to maintain social connections.
game controller text entry with alphabetic and multi-tap selection keyboards. in this paper we present a longitudinal study comparing an alphabetical selection keyboard to a multi-tap selection keyboard using a game controller as input device. our experiment showed the alphabetic selection keyboard to be faster for novice (7.72 wpm vs. 6.34 wpm) and expert users (11.87 wpm vs. 9.64 wpm). the multi-tap selection keyboard was more error prone than the alphabetic selection keyboard. qualitative results showed that over time the alphabetic selection keyboard was preferred by the users.
i/o plant: a tool kit for designing augmented human-plant interactions. in this paper, we introduce the versatile creative tool called "i/o plant" which generates new-style interactions among humans, plants and computers. it enables designers to manipulate plants as modules by attaching actuators and sensors to plants. it has been designed to create original hybrid circuits. we report not only our tool, but also use patterns and several examples. i/o plant cultivates new creativity toward the interaction design.
caws: alla wiki system to improve workspace awareness to advance effectiveness of co-authoring activities. crucial to effective collaborative writing is knowledge of what other people are doing and have done, what meaningful changes are made to a document, who is editing each section of a document and why. this is because awareness of individual and group activities is critical to successful collaboration. this paper presents the problems that surround co-authoring activities, and the advantages of using caws are explained and compared with other implementation and techniques for collaborative authoring. this co-authoring wiki based system (caws), aims to improve workspace awareness in order to improve user.s response to the document development activit.
jogging over a distance: supporting a "jogging together" experience although being apart. jogging is a healthy activity and many people enjoy jogging with others for social and motivational reasons. however, jogging partners might not always live in the same location, and it may be difficult to find a local jogger who runs at the same pace, we found through a survey "jogging over a distance" allows geographically distant joggers to socialize and motivate one another by using spatialized audio to convey presence and pace cues, similar to the experience of running side by side. we hope our approach encourages active and prospective joggers to jog longer and more often, while simultaneously supporting friendships.
mapmail: restructuring an email client for use in distributed teams. in this paper we examine a solution for coping with information sharing across location, time zone, and organizational boundaries. email, a principal tool for such collaboration, relies on textual and/or numeric sorting, filtering and presentation by subject, data, sender addresses and/or time. typically, spatial properties of presentation are limited to filtering incoming messages into folders. we have been designing for a different form of social expressiveness. mapping email by geographic region. we describe an example of how an email client was extended, preserving its original familiarity and functions, but augmented with new features expressed in a spatial map arrangement. we describe how this approach exemplifies a general technique we call.application surrogates.. we discuss application surrogates in terms of emerging.mashup. approaches to application development.
a motion-based marking menu system. the rapid development of handheld devices is driving the development of new interaction styles. this paper examines one such technique: using hand motions to control a menu system. previous research on this topic deals with systems which rely heavily on graphical feedback, a disadvantage in many mobile scenarios. inspired by marking menus, our system is designed to be used "eyes-free" and based on making relatively large scale rotational strokes. we describe the system and an initial evaluation in detail. the results indicate that its performance is comparable to previous motion menu systems, but that this can be attained without visual feedback. this represents a substantial benefit.
pointer delegation for group collaboration using telepointers. pointer delegation, a new function for a telepointer, allows people to delegate the rights of their own pointers to the pointer of someone who they can trust, which helps to achieve better group collaboration through a kind of fair voting system in interactive environments that include many people. a telepointer that has a pointer delegation function is called a delegate pointer. the appearance of delegate pointers in an interactive environment can show the weight of voting. moreover, delegate pointers can be used to limit the manipulators of objects to only one or a small group in order to reduce any conflicting manipulation. experiments were conducted to evaluate the appropriateness of the appearance of pointers to show the voting weight, and to test the feasibility of the delegate pointer.
squeeze: designing for playful experiences among co-located people in homes. squeeze is a multi-person, flexible and interactive furniture that allows for collective and playful exploration of the family history among co-located people in homes. it is designed to explore how we can use digital technology to create settings where co-located family members can collectively and actively engage in playful activities as part of their everyday lives at home. it is argued that this is for the most part an unexplored design space, which is awaiting the interest of the chi community. our work has both a strategic and theoretical outset. it is designed from a strategic point to open up the design space for digital domestic technology emphasizing the potential in designing for playful experiences among co-located family members. secondly, it is designed from a theoretical perspective, namely that of designing for playfulness and aesthetics of interaction.
a grid-based extension to an assistive multimodal interface. this paper describes an extension to a multimodal system designed to improve internet accessibility for the visually impaired. here we discuss the novel application of a grid (patent pending) to our assistive web interface. findings from our evaluation have shown that the grid enhances interaction by improving the user.s positional awareness when exploring a web page.
syncdecor: appliances for sharing mutual awareness between lovers separated by distance. many lovers separated by distance worry about their relationships, despite the fact that the use of various means of communication such as mobile phones and e-mail is now widespread. we interviewed some such couples, who expressed the desire to feel a sense of connection and synchronization with their partners. they also expressed the desire to have devices that provide awareness about their partners. for this purpose, we propose "syncdecor" devices, which are pairs of remotely installed appliances that synchronize each other.
rating, voting & ranking: designing for collaboration & consensus. the openchoice system, currently in development, is an open source, open access community rating and filtering service that would improve upon the utility of currently available web content filters. the goal of openchoice is to encourage community involvement in making filtering classification more accurate and to increase awareness in the current approaches to content filtering. the design challenge for openchoice is to find the best interfaces for encouraging easy participation amongst a community of users, be it for voting, rating or discussing web page content. this work in progress reviews some initial designs while reviewing best practices and designs from popular web portals and community sites.
flickr and public image-sharing: distant closeness and photo exhibition. this paper presents an empirical study in progress of the use of flickr.com, part of an on-going research program on personal digital media, including images. two new kinds of image-sharing with flickr are.distant closeness. and.photo exhibition.. we are seeing changing uses of images in social interaction and increased multi-modal communication.
on context of content: a comparative methodology review of how hci and mass communication analyze blogs and social media. across contexts, researchers have most recently applied content analysis -an unobtrusive scientific method originated to draw social inferences from mass media contents-to studying weblogs and social media (wsm). in this paper, we look at the classic and contemporary definitions of content analysis and identify the methodology's key premises and uses. against these premises and uses, we present findings from individual methodology reviews of twelve wsm studies involving content analyses by two disciplines -mass communication and human-computer interaction (hci). we cross-tabulate the individual reviews by discipline, in terms of (1) what content-analysis premises and uses were involved and (2) what research inferences -from media contents to social contexts-were made. we conclude with a collective comparison of the mass communication and hci approaches to wsm and suggest one discipline complement the other in analyzing the contents as well as in drawing inferences on the user psychology and social behavior of wsm.
comparing two methods for gesture based short text input using chording. we report on the design and initial evaluation of two methods for short text input in wearable computing applications using hand gestures. a wireless data glove able to recognize 4 basic gestures is used together with the chording principle. we present two different concepts to map gestures to characters. a presentation of preliminary experiment results shows that simple free hand gestures in combination with different key maps are easier to learn and allow faster typing than distinct gestures assigned for each character.
the facial expression effect of an animated agent on the decisions taken in the negotiation game. this paper investigates the manner in which decision-making is influenced by the impressions given by life-like agents in negotiation situations. these impressions comprise an agent's facial expressions such as happy and sad, and the history of relationship with the agent. in this paper, we introduce a negotiation game as one of the basic interactions based on the soft game theory. the experimental results reveal that expressions and history significantly influence the receiver's impressions and decision-making. the findings of this study can be beneficial for designing the nonverbal expressions of an animated agent who can negotiate and make a deal with users.
security user studies: methodologies and best practices. interest in usable security -- the research, development, and study of systems that are both usable and secure -- has been growing both in the chi and information security communities in the past several years. despite this interest, however, the process of designing and conducting security-related user studies remains extremely difficult. users deal with security infrequently and irregularly, and most do not notice or care about security until it is missing or broken. security is rarely a primary goal or task of users, making many traditional hci evaluation techniques difficult or even impossible to use. this workshop will bring together researchers and practitioners from the hci and information security communities to explore methodological challenges and best practices for conducting security-related user studies.
culture and collaborative technologies. this workshop will explore interactions among culture, features of collaborative technologies, and group processes and outcomes. the workshop will address several key challenges to this area of research, including identifying important dimensions of cultural variability, specifying how these dimensions interact with features of technology to impact group processes and outcomes, developing design specifications for multi-cultural and cross cultural collaborative tools, and addressing methodological issues that arise in cross cultural research. workshop goals include identifying key areas for future research, specifying initial design recommendations, fostering new collaborations among researchers interested in culture and computer mediated collaboration, and, if there is sufficient interest among participants, creating an edited volume on this topic.
exertion interfaces. exertion as an interface for computing technology has generated increased attention recently due to the belief that it can address health issues such as obesity, contribute to social benefits, and open new markets for entertainment industries. we are proposing a workshop on this topic to bring researchers and industry participants from related areas together to strengthen the scientific influence on this field and promote a multidisciplinary agenda. the workshop will support the development of future collaborative efforts in this rapidly growing area.
emotional instant messaging with kim. this paper describes a kinetic typography instant messaging client called kim. kim aims to improve the instant messaging experience by allowing the conveyance of more expressive content than is normally found in text-based communication. kim also demonstrates a unique approach to applying animation to text by using keyword matching against a list of emotional words. this paper then describes the implementation and challenges faced when developing kim, concluding with feedback obtained from user testing.
supporting selective information sharing with people-tagging. we explore the idea of tagging people for selective information sharing in the context of a social-personal information management (spim) system. each new tag applied to a person has a distinctly specifiable visibility, and people tagged with the same key word form a relationship group that can be used as an access control option for each piece of information. we introduce the idea and motivation behind people-tagging, describe a research implementation we have created to experiment with the concept, and provide a preliminary discussion of potential usage and directions for future work.
design and evaluation of korean text entry methods for mobile phones. this paper presents a new keypad layout for korean mobile phones and provides a preliminary evaluation of the feasibility of the design. at present the keypad layout for korean mobile phones has not been standardized and different manufacturers produce phones with different layouts. the proposed layout is inspired by the structure of the korean script and is designed to promote faster learning curve and ease of use.
lifesampler: enabling conversational video documentary. today's multidisciplinary, fast-paced and innovative workplaces present new challenges in facilitating effective communication between diverse team members and ensuring successful transfer of knowledge within a flexible workforce. in this paper, we present conversational documentary, a model for supporting constructive audiovisual dialog between workplace colleagues that also aims to archive and interpret the work practices and approaches of a creative community. we discuss the development and initial evaluation of the lifesampler, a prototype audiovisual system designed to support and test our model, and propose directions for future development based on our preliminary results.
agile user centered design: enter the design studio - a case study. in this paper we describe the merger of user centered design into agile (team) development practice as manifest in a one day design studio. benefits and challenges to a design studio approach are discussed, and the evolution of one design using the design studio process is presented.
twend: twisting and bending as new interaction gesture in mobile devices. in this work we present a hardware prototype that uses bending gestures as input for a mobile device and experimental setups that compare possible gestures with other, more traditional input methods in mobile computing. these will eventually result in guidelines for researchers and designers how to build bendable devices and show new interaction metaphors for computer user interfaces.
give me a reason: hedonic product choice and justification. recently, researchers and practitioners of human-computer interaction started to distinguish instrumen-tal, task-related, pragmatic quality aspects (i.e., use-fulness, usability) of interactive products from non-instrumental, self-referential, hedonic quality aspects (e.g., beauty, novelty). although both qualities are ap-preciated while using a product, hedonic quality tends to be downplayed in the moment of product choice. we suggest and test the idea that this is the consequence of an increased experienced pressure to justify hedonic choices and according expenditures.
distributed participatory design. over the years a consensus has developed that involving users directly in the software development process can lead to more useful and usable systems. this has found its clearest expression in the participatory design (pd) movement. however, a limitation of pd is that it has primarily focused on project stakeholders being co-located, whereas in recent years we are starting to see software development projects involve more distributed collaborations. this workshop is aimed at researchers and practitioners with an interest to overcome the challenges of performing pd in distributed design teams. several critical issues need examination in order to understand the usefulness and constraints of distributed participatory design (dpd).
human-in-the-loop: rethinking security in mobile and pervasive systems. in this paper we argue that pervasive systems introduce human-driven security vulnerabilities that traditional usability design cannot address. we claim that there is a need to understand better the appropriate role of humans in the context of pervasive systems security, and to develop quantifiable and measurable concepts that describe humans and their relationship with our systems. here, we highlight mobility and sociability as two new sources of security vulnerabilities for pervasive systems, and describe our method for developing quantifiable metrics for these concepts.
predicting user interface preferences of culturally ambiguous users. to date, localized user interfaces are still being adapted to one nation, not taking into account cultural ambiguities of people within this nation. we have developed an approach to cultural user modeling, which allows to personalize user interfaces to an individual's cultural background. the study presented in this paper shows how we use this approach to predict user interface preferences. results show that we are able to reduce the absolute error on this prediction to 1.079 on a rating scale of 5. these findings suggest that it is possible to automate the process of localization and, thus, to automatically personalizing user interfaces for users of different cultural backgrounds.
supporting long-distance parent-child interaction in divorced families. children in divorced families benefit from meaningful contact with both parents. currently, there are few technologies that effectively support distributed contact between parents and children. this work presents the results of interviews with 10 parents and 5 children from divorced families to better understand the challenges and needs of this group.
generative ui design in sapi project. in this paper we provide an overview of the sapi project, an initiative of poste italiane in collaboration with rcost-university of sannio, itslab and criai, supported by miur, italian ministry of university and research. the project is aimed at developing a software platform, that implementing a novel approach to the user interface generation centered on search based techniques, will provide automatic and semi-automatic adaptation of user interface to vision impaired people.
buddywall: a tangible user interface for wireless remote communication. buddywall is a system comprised of a wall-mounted panel with mobile wireless objects that represent remote friends on a virtual network. it uses established software and hardware for communication among a networked set of objects. the purpose of this interface is to allow for communication among remotely located friends and to display an awareness of group presence and others' availability through an ambient wall display. this project illustrates the transparency of a physical interface that provides aesthetically pleasing and emotionally engaging access to digital information for anyone. this paper describes the design of the system and interaction techniques developed in the context of this work. the aesthetics of physical objects can also enrich the digital experience and make it emotionally evocative.
the usability perspective framework. the usability perspective framework is a tool under development supporting various stakeholders in contributing to software systems usability. this paper describes the work conducted so far and argues how the framework is expected to contribute to both academia and practitioners in industry. the framework's fit to software development systems is discussed and we argue why the framework might succeed where current usability work often fails. finally the plans and ideas for future work are described.
content visualization and management of geo-located image databases. in the last years, several algorithms and platforms for photo sharing have been developed. usually, in order to index huge quantities of images for a fast and intuitive retrieval, additional textual tags attached to the pictures are considered. in this paper, we present a set of solutions for an effective management of geo-located images, i.e. pictures equipped with tags indicating the geographical coordinates of acquisition. this brings towards an intuitive content visualization and management of large geo-located image databases.
brightshadow: shadow sensing with synchronous illuminations for robust gesture recognition. we introduce a new sensor architecture for robust gesture recognition that uses a combination of a high-speed camera and synchronous led illumination. this sensor looks at shadows cast by a user's hand for recognizing position. the position of the hand can be robustly recognized by independently tracking multiple shadows and by using multiple light sources with time-synchronous modulation with the camera. we also developed a multi-finger tracking system that uses similar modulated illumination from multiple light positions. we expect that these sensing configurations can be naturally integrated into our daily environments as led lighting becomes more commonplace.
touch proxy interaction. the purpose of this research is to build and evaluate collaborative touch devices that influence behavior change over individuals in small group situations. this paper presents touch proxy objects for collocated collaboration and communication. touch proxy objects afford and represent touch in order to allow the sense of touch to be shared between people. this paper presents preliminary observations from studies performed on existing touch communication objects.
simulating hci for all. computers offer valuable assistance to people with physical disabilities. however designing human-computer interfaces for these users is complicated. the range of abilities is more diverse than for able-bodied users, which makes analytical modelling harder. practical user trials are also difficult and time consuming. i am developing a simulator to help with the evaluation of assistive interfaces. it can predict the likely interaction patterns when undertaking a task using a variety of input devices, and estimate the time to complete the task in the presence of different disabilities and for different levels of skills.
revisiting usability's three key principles. the foundations of much hci research and practice were elaborated over 20 years ago as three key principles by gould and lewis [7]: early focus on users and tasks; empirical measurement; and iterative design. close reading of this seminal paper and subsequent versions indicates that these principles evolved, and that success in establishing them within software development involved a heady mix of power and destiny. as hci's fourth decade approaches, we re-examine the origins and status of gould and lewis' principles, and argue that is time to move on, not least because the role of the principles in reported case studies is unconvincing. few, if any, examples of successful application of the first or second principles are offered, and examples of the third tell us little about the nature of successful iteration. more credible, better grounded and more appropriate principles are needed. we need not so much to start again, but to start for the first time, and argue from first principles for apt principles for designing.
first steps in role playing. this paper presents and evaluates examples from our work with role playing in design education. rationales for role playing in design are: communication within the design process, the increase of technological complexity, the experience and empathy of designers, the tangibility of interaction, and attentiveness to social change. these rationales inform our inclusion of role playing techniques in design education. our aim is that the students can and do incorporate the techniques into their own design activity. here, we focus on three questions: : 1. whether the techniques helped the students understand and question interaction, 2. whether the techniques helped students in ideation, and 3. whether the role playing exercises inspired students to use the techniques in own work. we identify several ways in which the techniques are effective for the students in their design work.
beyond the hype: sustainability & hci. in this panel we explore: (1) the burgeoning discourse on sustainability concerns within hci, (2) the material and behavioral challenges of sustainability in relation to interaction design, (3) the benefits and risks involved in labeling a project or product as environmentally sustainable, and (4) implications of taking on (or ignoring) sustainability as a research, design, and teaching topic for hci.
the mobile forum: real-time information exchange in mobile sms communities. in this paper we propose a definition for a mobile community based on the value of knowledge exchange among locally dispersed community members. against this conceptual background, we propose a low-tech mobile community setting using sms messaging and customary mobile phones. the feasibility of this approach is tested in a field study. results show that successful information exchange is established with high user traffic and that participants judge the communication to be helpful. user requirements hint to the need for a better structuring of sms messages, alternative input/output devices and location-based services. implications for the future support of mobile communities are discussed.
towards a shared definition of user experience. user experience (ux) is still an elusive notion with many different definitions, despite some recent attempts to develop a unified view on ux. the lack of a shared definition of ux not only confuses or even misleads customers of a product/service but also undermines the effectiveness of researching, managing and teaching ux. diverse ideas have been generated in scientific activities that aim to develop a common understanding about the meaning and scope of ux. it is plausible, with sound methodologies, to converge these divergences, driving the ux community closer to a common definition and integrated views of ux. this sig tackles this challenge by systematically assembling a set of existing definitions and viewpoints of ux and collecting opinions on them from known ux experts/researchers and general chi'08 attendees.
remote impact: shadowboxing over a distance. exertion games - games that require physical effort from the user - have been attributed with many social, mental and in particular physical health benefits. however, research has shown that most current implementations support only light or moderate exercise. we are presenting "remote impact - shadowboxing over a distance", in which players punch and kick a life-size shadow of a remote participant in order to win the game. the game includes a novel multi-touch large-scale interaction surface that is soft (so no-one gets hurt), but can detect the location as well as the intensity of the players' even most extreme impacts. remote impact shows that computer-augmented games can support extreme exertion while supporting novel experiences, such as a reduced risk of injury and supporting distant players, offering a new way of thinking in which areas human-computer interaction research can contribute to our lives.
what is a chi portfolio? chi participants are increasingly creating work in multiple formats and media. much of this work is well suited to the kind of efficient and effective graphic and text presentation found in what has traditionally been called within design communities as a portfolio. building on the theme of this year's conference we would like to provide an opportunity to engage the "dots" in art.science.balance. we propose a portfolio development session designed to present the notion of 'portfolio' as it relates to all fields within chi.
quantifying adaptation parameters for information support of trauma teams. trauma centers are stressful, noisy and dynamic environments, with many people performing complex tasks, and with little in the way of information support. information must be prioritized and filtered to avoid overload or loss. this work quantifies the information-selection parameters that will guide adaptive user interfaces for trauma teams.
letterscroll: text entry using a wheel for visually impaired users. four text entry techniques for visually impaired users are presented. letterscroll uses a mouse wheel to maneuver a cursor across a sequence of characters, and a button for character selection. keystrokes per character (kspc) vary from 6.97 to 2.68. after extensive analyses and pilot testing, two variations were chosen for initial evaluation. method 1 (m1) uses the mouse alone to enter text. method 4 (m4) also uses the keyboard to access vowels. in a study with seven blindfolded participants, entry rates averaged 2.9 wpm for m1 and 4.4 wpm for m4. error rates for both methods were about 3.4%.
designing and evaluating mobile phone-based interaction with public displays. this paper outlines the rationale for the workshop topic and offers an overview of its objectives.
collocated social practices surrounding photos. recent developments in technology mean that it is becoming increasingly possible to support collaboration around digital photos. this makes an exploration of the existing collocated social practices that are associated with photos both timely and relevant. this workshop will explore social practices in the areas of photowork, photo sharing and photo displays, with the aim of drawing together current research and considering how the findings might inform technology innovation.
a resource kit for participatory socio-technical design in rural kenya. we describe our approach and initial results in the participatory design of technology relevant to local rural livelihoods. our approach to design and usability proceeds from research in theory and practice of cross-cultural implementations, but the novelty is in beginning not with particular technologies but from community needs, and structuring technology in terms of activities. we describe our project aims and initial data collected, which show that while villagers have no clear mental models for using computers or the internet, they show a desire to have and use them. we then describe our approach to interaction design, our expectations and next steps as the technology and activities are first introduced to the villages.
flexible shortcuts: designing a new speech user interface for command execution. this paper proposes a new speech user interface for command execution called "flexible shortcuts." with this approach, users can select any commands by using "continuous keyword input," a voice input method using a series of keywords related to the command. keywords are defined by a hierarchically structured command set, called the "functional structure." two kinds of interactions are designed to support user-friendliness and effectiveness: interaction for exploration and interaction for the resolution of ambiguity. a probabilistic formulation for this approach is also considered. an experiment and objective evaluation method are designed so that the new interface for command execution can be compared with the conventional "command and control" interface. a comparative experiment to measure the efficiency and usability is also conducted and reported in this paper. experimental results show that the proposed approach is superior to the conventional approach from both objective and subjective points of view.
the effects of web site aesthetics and shopping task on consumer online purchasing behavior. this research-in-progress investigates the effects of website aesthetics and shopping task type on consumer attitude towards electronic shopping sites. the conceptualization of website aesthetics is based on the two-dimensional structure, namely, classical and expressive aesthetics, proposed by lavie and tractinsky (2004). the online shopping tasks are categorized as hedonic versus utilitarian shopping tasks. a pre-test was conducted for selection of utilitarian and hedonic products. based on the results of the pre-test, a laboratory experiment was designed to capture the effects of website aesthetics on online consumer purchasing behavior across different shopping tasks.
conversation clusters: human-computer dialog for topic extraction. in this paper, we look at projects leveraging human knowledge and understanding in computer systems for extracting conversational topics. tasks like speech recognition are difficult for computers, but simple for people engaged in conversation. this task is a cornerstone of transcription, speech summarization, and topic recognition. we propose using tabletop interaction to enhance the computer's basic categorization. we then describe how the results of tabletop interaction help to create meaningful archival visualizations and personal reflecting tools.
photochat: communication support system based on sharing photos and notes. this paper proposes photochat, a system that facilitates communication among users who want to share experiences by enabling them to share photos and notes. photochat is designed to be used as a digital camera and to run on mobile pcs with a camera module. photochat users can comment on the shared photos with a pen interface. the data, i.e., photos and comments, are distributed among photochat users in real time to enable them to learn others' interests and to chat easily. in this paper, we show an implementation of our photochat system and interaction patterns among photochat users observed during our experimental evaluations.
snapandgrab: accessing and sharing contextual multi-media content using bluetooth enabled camera phones and large situated displays. in this paper we describe a novel interaction technique that allows users to access and share rich multi-media content via a large, situated public display and their own bluetooth enabled camera phone. the proposed system differs from other solutions in that it does not require any client software to be installed on the user's device. we believe that our solution provides a practical and holistic approach for device-based interactions with a public multi-media information system.
speculative devices for photo display. in this paper, we describe three purposefully provocative, digital photo display technologies designed for home settings. the three devices have been built to provoke questions around how digital photographs might be seen and interacted with in novel ways. they are also intended for speculation about the expressive resources afforded by digital technologies for displaying photos. it is hoped interactions with the devices will help researchers and designers reflect on new design possibilities. the devices are also being deployed as part of ongoing home-oriented field research.
accessibility challenge - a game show investigating the accessibility of computer systems for disabled people. a professional live theatre event in the form of a game show has been designed to raise awareness of the challenges computer technology provides to older and disabled people and the advantages and disadvantages of various accessibility options that can be found within some software. it also demonstrates one way in which theatre can be used within hci research and development. it is designed to be a stimulating event with a serious purpose. a pilot version of the event proved successful as a plenary "social" activity at a recent conference on computer science education, where very positive evaluation results were obtained. it has since been modified to focus particularly on hci issues of accessibility.
guarddv: a proximity detection device for homeless survivors of domestic violence. research in homelessness points to a recent increase in the population of homeless women. survivors of domestic violence who become homeless as a result of their flight from an abusive situation seem to comprise an increasingly significant segment of this group. guarddv is a system that seeks to address the safety concerns of domestic violence survivors who do not possess a stable residence. the system warns the potential victim and the corresponding law enforcement organizations about the physical proximity of the aggressor. for this project, an interdisciplinary team committed to improve the quality of life of dv homeless survivors employed qualitative accounts as part of a participatory design [10] effort.
sun dial: exploring techno-spiritual design through a mobile islamic call to prayer application. we present the design and formative evaluation of sun dial, an application that supports muslims' prayer practices. we report on a study that involved identifying prayer as an activity that can be supported with technology; the development of a prototype; and a short-term evaluation of sun dial conducted with our local muslim community. in addition to presenting a novel design idea, our case study contributes to the growing corpus of research examining technology and religion.
premote: a user customizable remote control. the premote ('p' stands for personal) is an alternative input device based on digital pen technology, paper-based interface layouts and text recognition. compared to standard remote controls the concept allows the creation of personal interfaces by the user, the use of different templates during running an application and an alternative for text input by writing with a pen. in our work we developed a design study of the premote which was evaluated with eight users. the concept was appreciated by almost all of the participants. we exemplified the concept for controlling an already developed media application. the premote should establish a basis for further evaluations of different input designs.
socially respectful enjoyment tracking for tabletop games. this paper describes the current state of our ongoing work developing tools for tracking player enjoyment in traditional face-to-face tabletop gaming situations. the challenge presented is that of quantifying game enjoyment whilst minimising the effects of the measurement techniques on the validity of the study. this paper presents the development of a self-report tool for cellular phones that aims to gauge player enjoyment with minimal impact on the "magic circle" of play. its design for non-invasive and meaningful self-report data is described along with initial preliminary results from casual trials that indicate the potential value of the technique along with avenues for further study.
accenture technology labs: hci research. this paper describes the high level goals of accenture technology labs' research group, and concentrates specifically on the hci research domain. we discuss three representative projects in order to give the reader a sense of our research agenda, as well as the culture of the group itself.
they call it surfing for a reason: identifying mobile internet needs through pc internet deprivation. in this case study we describe the details of a pc internet deprivation study used to gather information on mobile internet needs. eight participants in our study used a mobile device as their only means of internet access for four days. the case study describes details of the research methodology as well as design insights and implications that resulted from the study.
bluereach: harnessing synchronous chat to support expertise sharing in a large organization. we present a case study of bluereach, an expertise sharing application that uses synchronous chat to connect question askers with subject-matter experts. we discuss how the solution evolved over time, and the generally high level of acceptance from users and volunteer experts. we include survey findings and usage data, which indicate that in spite of initial concerns that the experts would be overwhelmed by questions, usage has been fairly low and relatively flat. we examine this phenomenon and conclude with a discussion of lessons learned.
optimizing agile user-centred design. the goal of this workshop is to improve future agile user centred design (ucd) experiences for user experience (ux) practitioners (such as interaction designers, usability professionals, ui designers, etc.) by investigating best practices for agile ucd. to achieve this, senior ux practitioners with prior experience on an agile project will share their knowledge, collaborating in order to: identify success factors for agile ucd find and remove obstacles that block agile ucd find opportunities that agile projects give us identify best ux practices for agile ucd identify ux skills that agile projects need. the results of this investigation will be shared with the wider ux community (including those new to agile development practices).
"front-stage" and "back-stage" information. this paper presents an ongoing observational study to explore a "front-stage-back-stage" model of information processes during group discussions (multidiscipli-nary rounds) in the pediatric intensive care unit (picu) of an academic medical center. participants were observed to collaborate on "front-stage" processes of case presentation, discussion of issues, and treatment planning, while in parallel they performed "back-stage" in-formation activities. the front-stage and backstage information processes were interdependent to address the need for fluid, highly time-pressured discourse with potential life-and-death consequences. we believe the front-stage-back-stage model adds to our understanding of collaborative information exchange and holds implications for computer supported cooperative work (cscw) systems. for example, computing support may increase the efficiency and reliability of information transfer by enhancing the ability to "choreograph" front-stage and back-stage information processes during critical discourse such as medical rounds.
the effects of semantic grouping on visual search. this paper reports on work-in-progress to better understand how users visually interact with hierarchically organized semantic information. experimental reaction time and eye movement data are reported that give insight into strategies people employ while searching visual layouts containing words that are either grouped by category (i.e. semantically cohesive) or randomly grouped. additionally, sometimes the category labels of the cohesive groups are displayed as part of the group. preliminary results suggest that: (a) when groups are cohesive, people tend to search labeled and unlabeled layouts similarly. (b) people seem to trust the categorical information of labels more than non-labels. this work will be used to extend current computational models of visual search to better predict users visual interaction with interfaces.
tips and tricks for avoiding common problems in usability test facilitation. in this sig experienced usability test practitioners and hci researchers will discuss common errors in usability test facilitation. usability test facilitation is the actual encounter between a test participant and a facilitator from the moment the test participant arrives at the test location to the moment the test participant leaves the test location. the purpose of this sig is to identify common approaches to usability test facilitation that work and do not work, and to come up with realistic suggestions for how to prevent typical problems.
age differences in online social networking. this study presents an analysis of age-related differences of user behavior in the social network site myspace.com. we focus on two age groups: older people (60+ years of age) and teenagers (between 13 and 19 years of age). we used locally developed web crawlers to collect large sets of data from myspace's user profile pages. we used different analytic techniques to quantify any differences that exist in the networks of friends of older people and teenagers. content analysis was applied to investigate age-related differences concerning the way users represent themselves on their profile pages. our findings show that teenagers tend to have much larger networks of friends compared to older users. also, we found that the majority of teenage users' friends are in their own age range (age +/- 2 years), whilst older people's friends tend to have a more diverse age distribution.
interaction criticism: a proposal and framework for a new discipline of hci. though interaction designers critique interfaces as a regular part of their research and practice, the field of hci lacks a proper discipline of interaction criticism. by interaction criticism we mean rigorous, evidence-based interpretive analysis that explicates relationships among elements of an interface and the meanings, affects, moods, and intuitions they produce in the people that interact with them; the immediate goal of this analysis is the generation of innovative design insights. we summarize existing work offering promising directions in interaction criticism to build a case for a proper discipline. we then propose a framework for the discipline, relating each of its parts to recent hci research.
requirements gathering with diverse user groups and stakeholders. an interactive theatre piece has been designed to facilitate requirements gathering with a diverse range of user groups and stakeholders within the conceptual stage of telecare equipment for the home environment. the piece has been devised and produced by theatre professionals in consultation with computer engineers as part of a major research programme developing computer systems to support older and disabled people. by the interaction of a researcher, two actors and some video-clips, this piece demonstrates: a) the vital importance of all stakeholders being properly consulted and for them to inter-communicate well, and b) the role of theatre as a tool in this process. the rationale and methodology of this technique is discussed in an interactive session with the audience.
achieving accessibility with self-interested designers: a strategic knowledge-acquisition approach. we introduce a new approach towards a more accessible web by means of more accessible knowledge acquisition mechanisms. our strategy is to detect the web designer's needs for knowledge that can be collected from minorities of web users, and subsequently to design mechanisms that allow the proper elicitation of such knowledge from web users. we discuss how this scenario places marginal web users in a privileged position that appeals for their inclusion. additionally, we illustrate how this approach might help build a more accessible web, to the benefit of visually-impaired knowledge contributors.
experience-scapes. experience-scapes systems enable scripted sequences of media events (acoustic, visual, and haptic) to be triggered based on time and/or sensed activity. these systems use event-based schedulers and sensors in physical environments to detect and respond to individual and group activity. they are designed to motivate, sustain, and augment a wide variety of human behaviors. ongoing user testing is geared toward understanding how these systems can be used to better understand, encourage, and organize personal and group activities. a primary goal of experience-scapes research is to leverage increasingly available ubiquitous and physical computing platforms to enhance personal and group self-awareness and self-efficacy. through user testing and refinement, experience-scape systems are becoming readily deployable, interactive, smart environments that empower people to reflect on their everyday activities.
comparing access methods and quality of 3g mobile video streaming services. in this paper we examine the access methods and the quality of experience of current unicast video streaming services in 3g mobile networks. a packet-switched mobile video client, a packet-switched video portal and two variants of circuit-switched streaming (standard vs. short code access) are evaluated in a user study. we found that the particular access method is an influential factor in the overall acceptance of a mobile video service. this makes circuit-switched streaming video with short code access a viable alternative to the currently predominant packet-switched video services.
gaze beats mouse: hands-free selection by combining gaze and emg. facial emg for selection is fast, easy and, combined with gaze pointing, it can provide completely hands-free interaction. in this pilot study, 5 participants performed a simple point-and-select task using mouse or gaze for pointing and a mouse button or a facial-emg switch for selection. gaze pointing was faster than mouse pointing, while maintaining a similar error rate. emg and mouse-button selection had a comparable performance. from analyses of completion time, throughput and error rates, we concluded that the combination of gaze and facial emg holds potential for outperforming the mouse.
interface metaphor design and instant messaging for older adults. instant messaging is currently not widely adopted among older computer users. an investigation has therefore been conducted into the use of instant messaging by older computer novices, with particular emphasis on the use of an alternative metaphor in the user interface to try to produce a more usable and acceptable solution for older adults. two messenger interfaces (a traditional one and an experimental alternative) were designed for the study and compared in use by older computer novices, through measurement and participant interview. results showed that the alternative metaphor interface performed better overall and that the majority of the participants preferred it for future use.
wellness applications -- ui design to support long-term usage motivation. due to the high penetration rate of mobile phones today, they have the potential to provide accessible and easy-to-use applications that help people manage their health and be physically more active. this paper describes the aim and progress of the author's phd studies on the user interaction, usability and motivational issues related to mobile wellness applications.
early olpc experiences in a rural uruguayan school. in this paper, we discuss children's and teachers' experiences in a small rural town in uruguay where every child in elementary school has received a laptop from the olpc foundation. in conducting activities in classrooms, observing children, and speaking with their teachers we found that the laptops have had a positive impact so far, with children accessing information resources that were previously unavailable, creating content for the world to see, collaborating and learning from each other, and increasing their interest in reading and writing. we also noted several challenges that need to be addressed, some directly related to human-computer interaction including problems with input devices, basic interactions, and the conceptual design and localization of user interfaces.
re-thinking fashion trade shows: creating conversations through mobile tagging. in this paper we discuss our explorations encouraging discussion and information exchange in high-bandwidth, real-time settings such as trade shows, fairs and conferences. we detail the iterative construction and planned testing of the "pittimobi" system, a mobile phone system designed to augment face to face communication between buyers, sellers and the press at a series of fashion trade shows. a platform for the creation of viral digital conversations that link people at physical gatherings is envisioned and discussed as a tool for further study.
the science of fun: one-to-many moderated game research. native environments are of particular importance in game research, where findings depend even more than usual on the user's mood and comfort level. using remote voice chat to moderate game research sessions enables researchers to remove the distracting and discomforting physical presence of the moderator, providing a more convincing native environment. this paper describes the benefits and addresses the methodological pitfalls of this approach.
end user software engineering: chi'2008 special interest group meeting. end users create software whenever they write, for instance, educational simulations, spreadsheets, or dynamic e-business web applications. researchers are working to bring the benefits of rigorous software engineering methodologies to these end users to try to make their software more reliable. unfortunately, errors are pervasive in end-user software, and the resulting impact is sometimes enormous. this special interest group meeting has two purposes: to incorporate attendees' and feedback into an emerging survey of the state of this interesting new sub-area, and generally to bring together the community of researchers who are addressing this topic, with the companies that are creating end-user programming tools.
redesigning video analysis: an interactive ink annotation tool. video recording and analysis is an important tool for user experience researchers. this project aimed to learn more about how an interactive video annotation method might affect video analysis. ink annotations on video were used as the annotation method, and an early prototype was demonstrated to professional user experience researchers. feedback on the interactive video analysis method was positive. a new tool was designed and is being implemented that emphasized the insights gained from analysis of the initial research, including: collaborative timeline visualization, refined interaction with ink annotation tools, a refined general annotation toolset, and a toolset for reporting findings. further lessons from implementation are noted, including: video manipulation, space limitations for tool navigation, and reporting tool development.
spontaneous scenarios: an approach to user engagement. in this paper we present work on a scenario and persona based approach to exploring social software solutions for a globally distributed network of researchers, designers and artists. we discuss issues identified with scenario based approaches and a potential participatory solution adopted in this project.
dynamic knobs: shape change as a means of interaction on a mobile phone. in this paper, we introduce the change of a mobile phone's hardware shape as a means of tactile interaction. the alteration of shape is implemented in a hardware prototype using a dynamic knob as an interaction device for the user. the knob alters the phone's shape according to different events and states, like incoming calls, new voice mail, or missed calls. therefore, the user can explore the phone's status by touching it -- ambiently, even through the pocket. initial user testing showed that this form of tactile interaction was easy to understand and handy to interact with, also for unexperienced users.
spoken words: activating text-to-speech through eye closure. writing is a predominantly visual task. in the following, we describe a system that adds a new modality to computer-supported text editing: listening with closed eyes. we present a prototype, for which we combined a text-to-speech software, microsoft word and a face tracking system. it reads out the current sentence in microsoft word as soon as the user closes both eyes. in this paper we discuss further details of the concept and its background, describe the implementation of the prototype and disclose first user testing results, before we conclude our findings with an outlook on future research.
information spaces - building meeting rooms in virtual environments. virtual worlds are typically designed to recreate the familiar physical world, both in the design of the spaces and the ways that people interact within them. in this paper we describe an alternate approach that uses the computational capabilities unique to the virtual world to augment social interaction and personal experience. we propose a specific design for supporting medium sized group meetings using avatar's positions in the space to represent their feelings about the discussion and discuss our preliminary testing results.
generating and using gaze-based document annotations. in this paper we describe a prototypical system that is able to generate document annotations based on eye movement data. document parts can be annotated as being read or skimmed. we further explain ideas how such gaze-based document annotations could enhance document-centered office work in the future.
the hinge between input and output: understanding the multimodal input fusion results in an agent-based multimodal presentation system. a multimodal interface provides multiple modalities for input and output, such as speech, eye gaze and facial expression. with the recent progresses in multimodal interfaces, various approaches about multimodal input fusion and output generation have been proposed. however, less attention has been paid to how to integrate them together in a multimodal input and output system. this paper proposes an approach, termed as the hinge, in providing agent-based multimodal presentations in accordance with multimodal input fusion results. the analysis of experiment result shows the proposed approach enhances the flexibility of the system while maintains its stability.
a solution to interface evolution issues: the multi-layer interface. updating an operational system is often complex and awkward. in this article, we will explain how the concept of multi-layer interface could facilitate the evolution of operational interactive systems. we will explain how the division in several layers could increase the application acceptance and smooth out learning phases. furthermore, we will present how we implement this concept in the aster project.
presence disparity in mixed presence collaboration. we present the design of an experiment investigating presence disparity in mixed presence collaboration using digital tabletops. in an attempt to verify previous work and relate their results, we examined different presence representations of remote collaborators: audio, video, telepointers and video arms. our early results show some interesting trends that we are currently investigating in more detail through further analysis of our data.
rapid image analysis using neural signals. the problem of extracting information from large collections of imagery is a challenge with few good solutions. computers typically cannot interpret imagery as effectively as humans can, and manual analysis tools are slow. the research reported here explores the feasibility of speeding up manual image analysis by tapping into split second perceptual judgments using electroencephalograph sensors. experimental results show that a combination of neurophysiological signals and overt physical responses--detected while a user views imagery in high speed bursts of approximately 10 images per second--provide a basis for detecting targets within large image sets. results show an approximately six-fold, statistically significant, reduction in the time required to detect targets at high accuracy levels compared to conventional broad-area image analysis.
chromirror: a real-time interactive mirror for chromatic and color-harmonic dressing. this study presents the "chromirror" system, a digital mirror imaging system which helps users select appropriate clothing color combinations. by digitally rendering a mirror image of the user wearing clothing in different color-harmonic combinations, this system enables users to easily and playfully explore a wide variety of chromatic and color-harmonic clothing combinations (i.e., without having to physically change clothing). a long-term goal of the chromirror system is to encourage users to experiment with colorful and color-harmonic clothes.
all roads lead to chi: interaction in the automobile. the way we interact with the automobile is changing. new factors in automotive interaction include driver assistance technologies, new media and information options, new power train technologies, environmental concerns, and the introduction of automobiles into emerging markets. in this special interest group session, practitioners and researchers from industry, industrial labs, and academia will discuss several key interaction issues of the automotive environment. these may include personal devices and media, interaction technologies and methods, cognitive load and human factors, and international and cultural factors. participants will also be able to share their work and recent results in short presentations to other researchers and practitioners. the goal of this session is to establish and reinforce connections between individuals in the academic and industrial communities, open new lines of communication, and foster new partnerships. these collaborations will help create a better understanding of the automotive interaction design space and address important issues in product design, safety, manufacturability, and environmental sustainability.
fragile: a case study for evoking specific emotional responses. designers and artists often seek to evoke specific, nuanced sets of emotional responses [1], but attempting to predict the reaction of a given target audience can be daunting. as a first step, it is helpful to create prototypical systems of objects and interactions in order to observe whether or not participants express certain intended emotional responses. the insight gleaned from such explorations can then be applied to future work in which the crafting of a particular experience is desired. this paper documents such an exploration, which took place in the form of an immersive, interactive environment. the environment, entitled "fragile" included delicate movable lamps that rewarded the user with a combination of ambient sounds based on the lamps' positioning on a host object. [2]
supporting orientation for blind people using museum guides. novel environments exploiting recent technology can enhance several tasks in applications such as mobile guides. however, in the many museum mobile guides that have been proposed, accessibility is often not explicitly addressed and the benefits of such technology are rarely made available to blind users. in this paper, we propose a solution for flexible orientation support in a multimodal and location-aware museum guide, which has been developed specifically for blind users.
hci for emergencies. emergencies put people in a particular state of mind and often also in difficult physical situations. when de-signing information technology for emergencies, these two sides have to be taken into account in the various activities supporting design. this includes studying and understanding the users and the influential factors for good designs, engaging the users in the design process as well as evaluating designs in realistic ways. there are challenges specific to emergencies in all of these activities, as well as in new technologies ranging from wearable computing to distributed information systems. this workshop is meant as an opportunity for interdis-ciplinary discussion as well as practical hands-on ex-change of experiences regarding these challenges. the goal is to work towards a better understanding of the challenges, technologies, practices, and design meth-odologies relevant to hci in emergencies.
multimodal capture of consumer intent in retail. in this paper we present a prototype for capturing retail related consumer intent using multiple devices and in multimodal input formats such as text, audio, and still images. the prototype was used in a longitudinal user study to analyze the process that consumers go through in order to make purchasing decisions. based on these findings, we recommend desirable features for information management systems specifically designed for the retail environment.
{hi}stories: supporting user generated history. with more and more digital information being produced by individuals every day, we will soon be able to use it to understand the past. based on this premise this paper presents {hi}stories, a system to support the creation and access of user generated contents as historical evidences. in {hi}stories users aggregate contents from internet and are invited to contribute their own material. it combines a number of research themes: collaborative information structuring, combination of contents from online services, and visualization and browsing of structured information collections.
the openinterface framework: a tool for multimodal interaction. the area of multimodal interaction has expanded rapidly. however, the implementation of multimodal systems still remains a difficult task. addressing this problem, we describe the openinterface (oi) framework, a component-based tool for rapidly developing multimodal input interfaces. the oi underlying conceptual component model includes both generic and tailored components. in addition, to enable the rapid exploration of the multimodal design space for a given system, we need to capitalize on past experiences and include a large set of multimodal interaction techniques, their specifications and documentations. in this work-in-progress report, we present the current state of the oi framework and the two exploratory test-beds developed using the openinterface interaction development environment.
slurp: tangibility spatiality and an eyedropper. the value of tangibility for ubiquitous computing is in its simplicity-when faced with the question of how to grasp a digital object, why not just pick it up? but this is problematic; digital media is powerful due to its extreme mutability and is therefore resistant to the constraints of static physical form. we present slurp, a tangible interface for locative media interactions in a ubiquitous computing environment. based on the affordances of an eyedropper, slurp provides haptic and visual feedback while extracting and injecting pointers to digital media between physical objects and displays.
towards designing a user-adaptive web-based e-learning system. this work-in-progress report presents the groundwork for the design of a user-adaptive web-based e-learning system. a survey and two randomized controlled experiments were carried out to compare the effects of active versus passive interaction on attitude and learning and to compare user vs. system initiated control of information presentation. results showed that the more time-consuming active interaction was indeed more helpful to less-proficient students, but it was not as helpful to more-proficient students. results also indicate that both more- and less-proficient students learn more from system initiated information presentation. these results will help to design a user-adaptive e-learning system that can determine which kind of interactivity and information presentation works best for which students and when.
renaissance panel: the roles of creative synthesis in innovation. the renaissance ideal can be expressed as a creative synthesis between cultural disciplines, standing in stark contrast to our traditional focus on scientific specialization. this panel presents a number of experts who approach the synthesis of art and science as the modus operandi for their work, using it as a tool for creativity, research, and practice. understanding these approaches allows us to identify the roles of synthesis in successful innovation and improve the implementation of interdisciplinary synthesis in research and practice.
probing an agile usability process. in this paper we describe adaptations to the classical extreme programming (xp) process. the approach described integrates hci (human computer interaction) instruments. the implemented hci instruments are: user studies, extreme personas (a variation of the personas approach), usability expert evaluations, usability tests, and automated usability evaluations. by combining xp and ucd (user centered development) processes we take advantages of both approaches.
longitudinal usability data collection: art versus science? in this proposal the authors describe an exciting panel for chi 2008 on longitudinal usability data collection. collecting usability data over time is increasingly becoming best practice in industry, but lacks "thought leadership" in the current literature -- very few articles or books exist addressing the topic. to inspire academic research and share best practices with practitioners, we propose a panel to debate some key questions that arose from the chi 2007 sig on the same topic.
meta-perception: reflexes and bodies as part of the interface. meta-perception is both an interaction design concept and the theme of a research group at the university of tokyo. as a design concept, meta-perception is used to describe experience of novel phenomena made possible by devices that extend the human precepts. as a research group, our goal is to develop methods for capturing and manipulating information that is normally inaccessible to humans and machines. in this paper we describe various displays and devices that exemplify meta-perception. these include: several displays with which the human bodily interacts and wearable haptic devices that act as an extended skin. we reflect upon a design approach which borrows from elements of philosophy and media art to describe a different relationship between humans and technology.
minimal connectedness: exploring the effects of positive messaging using mobile technology. this paper describes a lightweight mobile technology designed to investigate the potential of positive messaging. we introduce the concept of minimal connectedness and examine how this form of connectivity supports and gives rise to user's positive affect. to explore this idea, a mobile application called posipost me was developed, allowing users to randomly share positive messages. we present a study of the ways in which it was used and understood. as well as encouraging positive thoughts, analysis shows how the form of minimal social connectedness afforded by the application is marked by its minimal social obligation, curiosity and ambiguity.
urban encounters: the game of real life. in this paper we describe our ongoing work on modelling urban encounters by extending conway's game of life. we develop our model based on empirical data collected using a tamagotchi-like mobile game that recorded people's encounters by sensing nearby devices using bluetooth. our findings include the identification of useful ways to capture and analyse data to derive a model of encounter, and a set of rules that can be used to drive our model. we also identify interesting patterns in the behaviour of our simulations that can help us understand, and in certain cases predict, urban encounter.
surflex: a programmable surface for the design of tangible interfaces. in this paper we describe surflex, a programmable surface for the design and visualization of physical forms. surflex combines the physical properties of shape-memory alloy and foam to create a surface that can be electronically controlled to deform and gain new shapes. we describe implementation details, the possibilities enabled by the use of smart materials and soft mechanics in human computer interaction, as well as future applications for this technology.
scenario-based usability engineering techniques in agile development processes. improving the users' experience is a common goal of both software engineering and usability engineering. however, although practitioners of both disciplines collaborate in practice, development processes often rely on a sequential division of labor, and thus limit the effectiveness of a meeting of different perspectives. in this paper, we report on experiences we made in both academia and industry as we put an agile development process pattern to the test -- combining extreme programming and scenario-based usability engineering, based on a blend of perspectives on equal terms.
security practitioners in context: their activities and interactions. this study develops the context of interactions of it security practitioners. preliminary qualitative analysis of 22 interviews (to date) and participatory observation has identified eight different types of activities that require interactions between security practitioners and different stakeholders. our analysis shows that the tools used by our participants do not provide sufficient support for their complex security tasks, including the interactions with other stakeholders. we provide recommendations to improve tool support for security practitioners.
designing for children's physical play. in this paper we describe preliminary results of our work on designing innovative sport concepts to stimulate children's physical play. we are exploring how embedding sensor and actuator technology in products can stimulate children to practice sport related skills. it incorporates ideas from game design, persuasive technology and sport motivation theories. we illustrate our approach with two case studies, in the context of football and basketball and discuss our experiences with embedding sensor technology to provide a motivating play experience for children.
chi'08 alt.chi / auralscapes: engaging ludic ambiguity in the design of a spatial system. ambiguity as a resource for interactive systems is gaining momentum within hci. in this paper we describe a spatial system designed at the intersection of architecture and computing; using ludic ambiguity as its theoretical construct. through description of the system and an examination of the ambiguous nature of the representations we will explore how such mediations could lead to richer interpretations of information.
international user research in product development cycle. as an increasing number of software products enter the global market, the popularity of international user research is on the rise. though the concept of studying international users to inform global designs is clear-cut, the actual practice is not. there are many open questions and challenges present, such as, in what stages of the development cycle and using what methods should international research be done? how might different language interfaces be studied? in this sig, we will review actual case studies focused on international user research, and discuss best practices for conducting international user research to maximize global usability and roi.
values, value and worth: their relationship to hci? this workshop explores the territory of 'value-centered hci' with the intention of freeing us from the tricky complexity of this topic and the multiple meanings of the words 'value' and 'values'.
digital paper bookmarks: collaborative structuring, indexing and tagging of paper documents. bookmarks provide an efficient and well established means for structuring, indexing and tagging documents, all important processes for successful learning. we present a prototype of digital paper bookmarks, writable adhesive stickers which combine the intuitiveness of paper bookmarks with electronic processing. electronic tracking of the bookmarking actions performed on a paper printout provides for tangible bookmarking and tagging of electronic documents. a collaborative visualization of own bookmarks and shared ones of other users allows contrasting the own understanding with those of others. four different semantic types of bookmarks scaffold learners in their learning processes and enable automatic aggregations.
design of human-map system interaction. in this work-in-progress we present some ideas and findings involving map design and human performance. satellites has once and for all automated geographic positioning and resulted in a plethora of map applications, not only in professional transportation but also in the private sphere, in cars and even for street use in mobile phones. but many people have problems using the traditional bird's-eye view maps. a maze experiment presented here show that an egocentric (out of the window) view of the map results in faster decision making and fewer errors. can this also address some of the human-out-of-the-loop problems of navigation automation?
shybot: friend-stranger interaction for children living with autism. this paper presents shybot, a personal mobile robot designed to both embody and elicit reflection on shyness behaviors. shybot is being designed to detect human presence and familiarity from face detection and proximity sensing in order to categorize people as friends or strangers to interact with. shybot also can reflect elements of the anxious state of its human companion through leds and a spinning propeller. we designed this simple social interaction to open up a new direction for intervention for children living with autism. we hope that from minimal social interaction, a child with autism or social anxiety disorders could reflect on and more deeply attain understanding about personal shyness behaviors, as a first step toward helping make progress in developing greater capacity for complex social interaction.
current issues in assessing and improving information usability. the usability of information is vital to successful websites, products, and services. managers and developers often recognize the role of information or content in overall product usability, but miss opportunities to improve information usability as part of the product-development effort. this meeting is an annual forum on human factors of information design, in which we discuss issues selected by the group from the facilitators' list of topics, augmented by attendees' suggestions.
social data analysis workshop. this workshop addresses a new online phenomenon: social data analysis, that is, collective analysis of data supported by social interaction. the recent democratization of data sources on the internet--from mandated publication of government-generated data to scientific repositories of experimental data sets--has enabled a new kind of web site where users upload and collaboratively analyze the most varied sorts of data. so far, most of these sites have relied on visualization as an intrinsic part of their analytical arsenal. the goals of this workshop are to: bring together, for the first time, the social data analysis community examine the design of social data analysis sites today discuss the role that visualizations play in social data analysis explore how users are utilizing the various sites that allow them to exchange data-based insights.
a multimodal interactive system to create and explore graph structures. this work introduces a multimodal interactive system to create, edit and explore graph structures through direct manipulation operations. the system being designed is based on audio-haptic interaction, supported by visual feedback. a star life design and development cycle was undertaken. the main design choices and early implementation and evaluation results are illustrated.
hci@aachen: experiments in the future of media and mobility. this paper presents the media computing group at rwth aachen university and its goal to explore the future of collaborative, ubiquitous interaction with audiovisual media. it explains how this initial research vision has led to work on the levels of hci theory, algorithms, toolkits, testbeds, and design patterns. it also introduces some of our external collaborations, in particular the excellence initiative, germany's most fundamental change in government research funding to date, which supports rwth and our group.
international ethnographic observation of social networking sites. current research on social networking largely covers us providers. to investigate broader trends, we examine cross-cultural differences in the usage patterns of social networking services with observation and ethnographic interviews in multiple cultures. this appears to be the first systematic investigation of social networking behavior across multiple cultures. we report here on the first four locations with observation and interviews of 36 respondents, 8-10 in each of the us, france, china, and south korea. the results show three dimensions of cultural difference for typical social networking behaviors: the users' goals, typical pattern of self expression, and common interaction behaviors. these differences exemplify a developmental path of interest in social networking and the gradual integration of social networking behavior into more general communications behaviors. future work in other cultures and with additional methods will evaluate the hypotheses presented here.
sensemaking. when confronted with a large or complex amount of information, how do people come to understand it? this workshop will focus on the most recent work in sensemaking, the activities, technologies and behaviors that people do when making sense of their complex information spaces.
wheels around the world: windows live mobile interface design. we present a unique interface design for mobile devices that addresses major user pain points with deep menu systems and page scrolling. using a series of 1-5 wheels of content, arranged in a combination-lock style on a single mobile screen, this design enables a user to consume a multitude of personalized internet and web content without ever scrolling up/down or selecting from a menu. additionally, the wheels are easily mapped to a personalized pc experience such as those from my msn, live.com, and myyahoo!, enabling users to access their pc content from anywhere. results from iterative testing across us, japan, and china show the model to be an effective and desirable mode of consuming personal and internet content on the mobile device, despite very different navigation paradigms and cultural expectations in each of the countries.
all the news that's fit to e-ink. we describe a design project of a future electronic news device and service. the project employs about 20 researchers, designers and developers. it uses advances in product technologies and in social computing to deal with the challenges of transferring the print newspaper reading experience onto a mobile, hand-held device, and of transferring the editor's power to decide what constitutes worthy news to the reader.
co-located group interaction design. this design theatre experience explores the use of choreographic improvisation exercises to reflect on the structures of interaction in a mobile, co-located group. the design technique is motivated by studies of clinical ward rounds, and applies analytic models from kendon, garfinkel and hutchins.
re-phrase: chat-by-click: a fundamental new mode of human communication over the internet. there is a fast growing need for companies to handle full text interaction via internet with chat-like functionality, think of online helpdesk, demand aggregation, etc. however, even state-of-the-art language technology is not able to automatically handle consumer requests in a reliable and sensible manner. semantic text understanding systems are brittle and expensive to maintain, and simple pattern matching text-bots cannot handle the complexity of natural language and often give useless or wrong answers. re-phrase meets this need by starting from threads of real human textual interaction (chat, helpdesk) and then storing and re-cycling it for fast multiple-choice conversation with automated replies. it is a new technology for users to interact via the internet, which combines browsing and chatting. it makes use of an adaptive and collaboratively growing database of conversation phrases. it is fast, adaptive, allows full text entry, and is well suited for different types of browsers and platforms.
"seeing like a rover": embodied experience on the mars exploration rover mission. although they work with two non-humanoid robots located several million miles away, the distributed team that operates the mars exploration rovers demonstrates an uncanny sympathy for their robotic teammates. this paper examines not only how the rovers are anthropomorphized by the human team, but also how the team takes on characteristics of the rovers while conducting science and operations on mars. based on two years of ethnographic fieldwork with the mars rover mission, the paper places the configuration of the user in social context and probes the role of the machine as social resource, with implications for hci.
using comics to communicate qualitative user research findings. this paper is a case study of how exploratory, qualitative interview findings were communicated to product teams through the visual design language of comics.
mystorymaker. in this paper we describe the development of our storytelling program for children mystorymaker based on the concept of literacy learning through play. the focus is on designing interfaces inducive to play and open to user interpretation.
brain-computer interfaces for hci and games. in this workshop we study the research themes and the state-of-the-art of brain-computer interaction. brain-computer interface research has seen much progress in the medical domain, for example for prosthesis control or as biofeedback therapy for the treatment of neurological disorders. here, however, we look at brain-computer interaction especially as it applies to research in human-computer interaction (hci). through this workshop and continuing discussions, we aim to define research approaches and applications that apply to disabled and able-bodied users across a variety of real-world usage scenarios. entertainment and game design is one of the application areas that will be considered.
playware: augmenting natural play to teach sign language. we discuss playware--a system of augmented dress-up clothes, toys, and a digital environment that teaches simple asl vocabulary to young children. we present a preliminary evaluation of the system in a school setting and plans for improving the playware system for future deployment.
design for intuitive use: beyond usability. after a short introduction to our concept of intuitive use of user interfaces we would like to invite the interdisci-plinary chi community to discuss at least two impor-tant issues, namely: how does intuitive use and aes-thetics relate? and, does physicality enable intuitive use? in the following, we present some provoking the-ses to trigger the discussion of these questions.
do that again? the proposal is for a design theatre session that explores the readability of a staged interaction. this is based on our work with role playing in design education, design research and design work. it is also based on our background in both observational research and interaction design. reading an interaction is not straightforward. presenting an interaction is not, either. in this presentation, a very small interaction is presented in several different ways. the audience is invited to guess and discuss about the readability of this interaction and about the consequences of the possible readings for design.
interactivity: constructed narratives. constructed narratives is a digital media research project and game that explores the design of tangible social interfaces that facilitate discourse and information sharing in public spaces. designed for experiments in social networking and learning in physical environments, the tangible social interface (tsi) is based on the premises of the tangible user interface (tui) -- physical objects embedded with hardware sensors for responsive output when manipulated. the tangible social interface gives unique output based on manipulation technique as well as profile information about the person who is doing the manipulation.
visually querying the e-lis ontology: a proposal. the e-lis dictionary includes the first web dictionary from italian sign language to italian. albeit innovative, its interface makes it a dictionary for experts of italian sign language and of its sign composition rules. in this paper, we present a novel visual interface for the e-lis dictionary. our interface visualises the e-lis ontology, which encodes the composition rules of signs of the dictionary. thus our interface supports the dictionary users in querying by transparently browsing the ontology. the prototype of our interface was designed with the user centred design methodology.
biometric daemons: authentication via electronic pets. a well-known security and identification problem involves the creation of secure but usable identification and authentication tools that the user is fully motivated to adopt. we describe an innovative solution to this problem: the biometric daemon, which takes its inspiration from two sources. it is firstly conceived as a biometric device which is initially imprinted with the fixed biometric properties of its owner, and is then regularly updated with the fluid biometric properties of its owner. however it also acts as an electronic pet which (i) part-shares identity with its owner, (ii) needs nurturing and (iii) effectively dies when separated from its owner for any length of time. our proposal was inspired by the literary daemons described by philip pullman. our biometric daemon synthesizes the properties of biometric token and daemon and we argue that it offers the basis for secure, usable and engaging identification and authentication.
beliv'08: beyond time and errors: novel evaluation methods for information visualization. information visualization systems allow users to produce insights, innovations and discoveries. evaluating such tools is a challenging task and the goal of beliv'08 is to make a step ahead in the comprehension of such a complex activity. current evaluation methods exhibit noticeable limitations and researchers in the area experiment some frustration with evaluation processes that are time consuming and too often leading to unsatisfactory results. the most used evaluation metrics such as task time completion and number of errors appear insufficient to quantify the quality of an information visualization system; thus the name of the workshop: "beyond time and errors".
can an orc catch a cab in stormwind?: cybertype preference in the world of warcraft character creation interface. virtual worlds are reaching a point of critical mass as a medium for the exchange of business, entertainment and other cultural products and values. as cultural interfaces, virtual worlds mediate the access to remediated cultural data. this remediation of cultural data may transfer existing, repressive racial ideologies to new media. limited research about racial stereotypes in virtual worlds exists and this paper contributes to the growing research body by demonstrating a novel study of a dominant racial stereotype in the character creation interface of world of warcraft.
pensieve: augmenting human memory. human memory is fallible. we remember certain things, while we completely forget others. some of the events we experience end up stored in our episodic memory, others disappear completely. even those stored, very often remain inaccessible, since we do not have reliable mechanisms to retrieve them when required. in this paper we describe pensieve, a system for augmenting episodic memory, that facilitates capturing of events and retrieving them later, using various relevant cues and associative browsing.
globetoddler: designing for remote interaction between preschoolers and their traveling parents. in recent decades, families in the western world have become more geographically distributed, making it more difficult for family members to achieve and maintain a feeling of connectedness. different time zones and contexts and a limited awareness of the other family members' availability and mood are some of many factors that make "being together" more challenging when physically apart. besides, when it comes to preschool children, existing communication technologies, such as phones and computers, may not even be an option. as a result, many families simply accept the fact that being apart leads to fragmented, or even non-existent, interaction. in this paper we describe initial work on a tangible system, globetoddler, which aims to make remote interaction between preschool children and their traveling parents easy and enjoyable. the paper describes the process of defining design principles for this system, as well as the content and implications of these principles.
semantic web user interactions: exploring hci challenges. the purpose of this workshop is to engage interaction researchers and designers in the user interaction challenges posed by the semantic web. the workshop will be the fifth workshop in the swui series - it has previously been hosted at either the world wide web conference or the international semantic web conference. we have sufficient exemplars of both tools and approaches now that we can demonstrate the concepts of the space to participants and make it very clear why there are design/research challenges for the chi community. we want to explore current and future chi research that fits this problem space, and so invite participants exploring many interaction issues.
toped: enabling end-user programmers to validate data. inputs to spreadsheets and web forms often contain typos or other errors. however, existing tools require end-user programmers (eups) to write regular expressions or even scripts to validate data, which is slow and error-prone. we present a new technique enabling eups to describe data as a series of constrained parts. we incorporate our technique in a prototype tool called toped, which generates validation code for excel and web forms. our technique enables eups to validate data more quickly and accurately than with existing techniques, finding 90% of invalid inputs in a lab study.
hands-on the process control: users preferences and associations on hand movements. design of future smart environments is challenging especially when we are talking about smart control room environments for advanced process control activity. one key element of our concept of a future smart control room is a movable multi-touch table called "affordance table". in this paper we present the results of a user test in which we explored what kind of hand gestures are intuitive and comfortable when using multi-touch sensitive displays. overall, simple gestures were preferred over more complex ones, and dimensions of gestures such as duration, force and direction have an impact on participants' evaluations. some gestures also evoked similar associations among them. our results suggest that user preferences and associations should be carefully considered when mapping gestures to system commands.
designing an interactive forest through sensor-based installations. we describe the design approach of an interactive exhibition called "the interactive laurissilva". the exhibition is about madeira island's endemic forest, and is composed of 15 sensor-based interactive installations. we discuss the interaction styles that were adopted, reflecting upon the ethnographic observation of visitors and we summarize the lessons learned.
influence of social setting on player experience of digital games. recent studies have indicated that playing games against other people is more fun and more exciting than playing alone. the current study aims to further explore the influence of social setting on player experience in digital games; in particular, it sets out to test the level of social presence of the co-player as a determinant of player experience. dependent variables include a comprehensive self-report measure of player experience (the geq) and state aggression. the first results demonstrate significant differences in playing against a computer, a mediated other, or a co-located other on player experience in terms of positive affect, competence, tension and hostility.
: text entry using three degrees of motion. this paper introduces unigest, a technique that provides pointer input and text entry in a single device without occupying the display. it uses a nintendo wii motion-sensing remote to capture gestures that are mapped to character input. a gesture alphabet is proposed, with each gesture composed of at most two primitive motions. a web-based user study measured movement times for primitive motions. results range from 296 to 481 ms, implying an upper-bound unigest text entry performance prediction of 27.9 wpm.
evaluating user preferences for adaptive reminding. we are developing an adaptive reminding system that tailors its reminders to its users' reminding preferences through real-time interaction and feedback. to determine the potential utility of such a system, we conducted a multi-phase user study, presented in this paper, in which we evaluate people's preferences for the visual presentation of reminders. results indicate that people generally agree on the relative annoyance levels of visual reminders, and further, in certain contexts, more "annoying" or intrusive reminder styles are preferred. however, while there are some overarching patterns of agreement about the contexts in which certain types of reminders are preferable, preliminary evaluation also indicates that there are significant differences among people's preferences for specific visual reminders. this motivates the design and development of adaptive reminding systems that learn their users' individual preferences.
designing embodied interfaces for casual sound recording devices. in the special moment project we prototype and evaluate the design of interfaces for casual sound recording devices. these devices are envisioned to be used by a casual user to capture and store their everyday experiences in the form of "sound albums" -- collections of recordings related to a certain situation. we formulate a number of design principles for such recording devices, as well as implement and evaluate two working prototypes. a candle recorder allows for capturing the general atmosphere at a party, and the children's book recorder records the interactions between parents and children while reading a book together.
nomaticbubbles: visualizing communal whereabouts. we describe the design of the nomaticbubbles, a visualization that provides cues of communal whereabouts. unlike most location displays showing whereabouts on a geographical map, the nomaticbubbles depicts historical and aggregate traces of participants' whereabouts in an abstract and ambiguous manner. we describe the design of the nomaticbubbles, and discuss some early experiences and feedback we got, as well as future work.
secrets and lies in computer-mediated interaction: theory, methods and design. the keeping of secrets and practicing of deception are commonplace in everyday social interaction. they also serve an important role in encouraging social cohesion. however, for hci practitioners, the challenge is to design systems that enable exactly this kind of flexibility and ambiguity in social behavior while also maintaining trust and authenticity. this workshop will bring together researchers of both deception and secrecy in computer-mediated interaction, alongside designers of systems, to face up to these challenges and develop a road map for the future. the workshop will act as a venue for the synthesis of theory with design, and propose ways to face the challenges of enabling authentic social interaction in computerized environments.
shaping how advertisers see me: user views on implicit and explicit profile capture. public electronic displays are increasingly used for advertising. in a drive to improve the effectiveness of such displays, advertisers and researchers are exploring the creation of systems that show adverts tailored to the context of the display or to the profile of the audience in close proximity to the display. in this paper we explore, through structured interviews with potential users in two european countries, reactions to the ideas of implicit and explicit generation of such profiles and relate these to more general user views on privacy and targeted advertising. the initial results suggest that users are prepared to trade off ease of use against increased levels of control over their data and are therefore more comfortable with an explicit system.
assocaptcha: designing human-friendly secure captchas using word associations. captchas are challenge-response tests to verify that the user is a human (and not a program/robot). captchas use problems that are trivial for humans to solve, but are hard for computers. unfortunately, captchas have focused only on one aspect of human ability: image/word recognition. this paper explores the usage of other human abilities: particularly, finding associations between related concepts; to design secure, human-friendly human interaction proofs (hips) in this paper, we present assocaptcha: captchas so designed that they require no greater user-interaction than conventional solutions, yet have orders of magnitude greater security. preliminary tests confirm user acceptance and efficiency of the system.
location and activity sharing in everyday mobile communication. we present a study on current, real-world communication of location and activity information based on analyzing context-sharing practices in recorded mobile phone calls. in 176 conversations, we found that over 70 percent contain disclosures of location or activity for one of eight main purposes. based on our observations, we provide implications for the design of new systems for mobile social software.
chi'08 alt.chi / do we bump into things more while speaking on a cell phone? we observed more than 8,800 cases of people passing by an obstacle that was placed at different heights at the entrance to a university cafeteria. of those cases, 491 were of pedestrians speaking on a cell phone. overall, 2,422 bumping cases were recorded. using a cell phone while walking did not increase the risk of bumping into protruding obstacles. the results suggest that the effective visual field of people who are involved in a highly automated, relatively slow- paced task, such as walking, under low rates of information input, is not degraded by speaking on a cell phone.
privacy and technology: folk definitions and perspectives. in this paper we present preliminary results from a study of individual differences in privacy beliefs and relate folk definitions of privacy to extant privacy theory. focus groups were conducted with younger and older adult participants who shared their individual definitions of privacy and engaged in a discussion of privacy across six scenarios. taken together, westin's and altman's theories of privacy accounted for both younger and older adults' ideas about privacy; however, neither theory successfully accounted for findings across all age and gender groups. whereas males tended to think of privacy in terms of personal needs and convenience, females focused more on privacy in terms of others, respecting privacy rights, and safety. older adults tended to be more concerned with privacy of space than information privacy. initial results suggest that designing for commonalities in privacy perceptions among group members is feasible.
select-and-point: a novel interface for multi-device connection and control based on simple hand gestures. select-and-point provides us with a new interface and intuitive interaction style in our daily computer use. with simple selection and pointing hand gestures, users can eliminate cumbersome processes in managing connections and controls between multiple devices as well as in sharing information/data. we implemented a select-and-point system in an intelligent meeting room and performed a preliminary user study in this environment. the results show that select-and-point is easily accepted by users and it can significantly improve users' interaction with various devices in a ubiquitous computing environment.
media spaces: past visions, current realities, future promise. established researchers and practitioners active in the development and deployment of media spaces review what seemed to be promised twenty years ago, what has actually been achieved, and what we might anticipate over the next twenty years.
child computer interaction. the study of child computer interaction is a growing subfield of hci. child computer interaction encompasses traditional hci but also specifically reaches out into the areas of child psychology, learning and play. the aim of this sig is to bring together researchers and practitioners working in this area, to discover current themes, to explore the creation of a more formal working group, to locate publishing opportunities and to foster international co-operation.
force feedback: new frontier as the innovative driving comfort tool. previous human factors studies in the automotive field showed that drivers performance is influenced by the type of force feedback (ff) reproduced by the steering wheel. in the present study, six ff were compared. \ \ results suggest that the effect of the type of ff depend on the specific driving scenario, thus suggesting the utility of an adaptive force feedback based steering wheel. \ \ in the final part of the paper, we describe how such a system could be implemented.
fighting fragmentation: an enterprise framework for creating unified online workspaces. this paper describes vanguard's efforts to create an enterprise-wide framework for producing unified online workspaces. this framework was developed to accommodate diverse business lines and job roles while leveraging cross-organizational components and services, providing for optimal scalability, flexibility and customizability, and ensuring cohesive user experiences. it addresses these goals by mapping business units, job roles and attributes to a core set of features/capabilities, thereby providing a consistent yet adaptable set of design patterns that can be leveraged in the creation of new workspaces and the further tailoring of existing ones. it is especially useful for large enterprises where a variety of job functions exist across multiple business lines and users struggle with moving between complex information spaces.
what is good?: a comparison between the quality criteria used in design and science. the human-computer interaction community is an umbrella for many disciplines. conflicts occur from time to time, in particular between scientists and designers. this article compares the quality criteria used in design with those used in science, in order to gain insight into what design can contribute to the development of science. from the scientific perspective, the weakest point of design knowledge is its limited generalizability.
landscaping personification technologies: from interactions to relationships. personification technologies are technologies that encourage people to anthropomorphize. these technologies try to get people to form relationships with them rather than simply interact with them. they may do this through having behaviours that encourage people to attribute personality or emotion to them. they may be persuasive technologies in the sense of fogg that aim to get people to do things they would rather not do. they may promote trust. the convergence of a number of technologies is making personification technologies possible. speech as an interaction is finally becoming robust and useable and is very influential in people attributing intelligence to devices and systems. human language technologies allow devices to understand, or appear to understand, conversation. interactions are becoming more natural and engaging. avatars appear more congenial and coordinated. building on the experience of a previous project, and drawing on the experience of a four year multi-disciplinary project, called companions, the authors are keen to build community relationships around the notion of personification technologies. this includes the design, engineering, research (including ethics and social issues) and usability communities.
using cognitive models to evaluate safety-critical interfaces in healthcare. we investigated the feasibility of using a gomsl model to assess the user interface of a medications prescribing application in a hospital setting. a gomsl model was developed for key prescribing tasks identified in an observational study. task execution times predicted by the gomsl model for six clinical scenarios were comparable with times from a pilot user study. model-based evaluation may be useful in identifying features more susceptible to errors in safety-critical healthcare interfaces.
visual filler: facilitating smooth turn-taking in video conferencing with transmission delay. turn-taking in a smooth conversation is supported by the anticipation of the floor handover timing among participants. however, it becomes difficult to maintain natural turn-taking in video conferencing with transmission delays because the utterances and movements of each participant are presented to the others with a time lag, which often leads to a collision of utterances. in order to facilitate smooth communication over a video-conferencing system, we propose a novel method, "visual filler," that fills temporal gaps in turn-taking caused by the existence of delays. visual filler overlays an artificial visual stimulus that has a function similar to that of filler sounds on a screen with participant images. we have evaluated the effectiveness of a visual filler for reducing the unnaturalness of turn-taking on a simulated dyadic dialog situation with a delay.
sketch worth, catch dreams, be fruity. this design theatre uses method acting: we act out a method. it is didactic theatre: we must sketch designing, not just designs. we act out a sketching process to make maps that we can later act on.
multimodal communication involving movements of a robot. communication between humans is multimodal and involves movements as well. while communication between humans and robots is becoming more and more multimodal, movements of a robot in 2d space have not yet been used for communication. in this paper, we present a new approach to multimodal communication with (semi-)autonomous robots, that even includes movements of a robot in 2d space as a form of expressing communicative acts. we also show how such a multimodal human-robot interface can be generated from a discourse-based interaction design that does not even include information about modalities.
increasing the accessibility of pen-based technology: an investigation of age-related target acquisition difficulties. this paper describes the author's dissertation research on improving the accessibility of pen-based technology. the first step for this research was to gather information on the underlying causes of target acquisition difficulty. to meet this goal, a controlled laboratory study was conducted, which uncovered three sources of difficulty: slipping, drifting, and missing just below. the remaining work will be to address these difficulties by implementing new interaction techniques and experimentally evaluating their effectiveness.
healthy technology. one of the biggest struggles user experience teams face is breaking through traditional notions of product strategy, planning and development to bring actionable awareness to the bigger picture around delivering full experiences that people really care about. user research and design is often focused around product & feature design in a space that is defined by out-dated boundaries imposed by history or pre-existing constraints. research is used to create new features or product direction within these walls, and many design tools are employed to ensure the experience delivered is acceptable. this paper uses a case study of a project titled "healthy technology" to highlight the important role that metaphors can play in shifting conversations & strategy, from executive managers to development teams, leading to new boundaries, new strategies, a fresh look at what it means to set direction that targets complete user experiences rather than consumer appreciated features. the metaphor is discussed, through example, as more than a tool for user interface design, exploring the same as a means to alter strategic thinking in upper management as well as guide design and development teams in rethinking notions of technology to create new categories, rethink the problem space and to think beyond features. this paper outlines the research processes that lead to the creation of a metaphor and the functions of the metaphor in overcoming traditional boundaries and thinking. it describes key challenges and methods in this process of moving from research to strategic initiatives that fundamentally shift thinking, providing direction for business models, services, technologies, and industry alignment that come together to provide more than just features or products.
invoking emotional support in a health crisis. this dissertation research explores the invocation of emotional support from friends and family for parents who have a baby in a neonatal intensive care unit, through the use of textual summaries of clinical and non-clinical data.
creating social value of interactive media installation: case study of designing "wish spark". we present a public interactive media installation, "wish spark" that evokes people's participation, sharing and giving. different from art-based interactive media installation, wish spark has a practical feature; an aid for making donation a pleasurable, meaningful, and interactive activity. our main concept is to make a system that appeals donation behavior as an act of fun not as a buggy activity, and finally lead people to make freewill contribution for society. this paper presents design process on how to make synergic effect of charitable giving as well as makes people have fun together. the act of throwing coin into the fountain was found to be a powerful and traditional way of making donation, thus it was used as a main metaphor for our solution. when people throw coins with their wish into wish spark, light and sound expressions occur to create a pleasurable user experience. the corrected coins are represented as people's wishes. wish spark is suggested to install in the landing gate of the airport because people can easily have a chance to give donation with small effort. in this project, we suggest a possibility to extend the social value of media installation by introducing interaction design process between human and public environment.
emotional response as a measure of human performance. emotional reactions are a key part of the user experience, and are particularly of interest to the design of systems that consider user emotions. this dissertation studies methods of measuring emotional responses through a novel two-dimensional tool, based on the model of valence and arousal. a study on reactions to storyboard and video prototypes motivated the need for continuous, quantitative, affective self-report. a pilot study with a slider revealed significant differences between the experiences of several video conferencing techniques. next steps include prototyping two-dimensional affective self-report capture devices, and an experiment to compare relative ease of use and cognitive complexity of different methods of emotional measurement.
sustainable informal it learning in community-based nonprofits. nonprofit organizations (npos) play a substantial role in the economies of many countries, in the delivery of social services, and in many quasi-government functions. but npos face many resource challenges; for example, they depend on volunteer labor that is often under-trained and has high turnover resulting in limited knowledge acquisition and decreased sustainability. ethnographic data from a three-year multi-organizational analysis reveals the occurrence of social and technical patterns during informal technology learning. construction of a pattern schema grounded in organizational learning and activity theories will enable the development of lightweight interventions in establishing information technology sustainability, self-directed learning, and management processes in npos.
special session in honor of randy pausch. randy pausch is an inspiration to all with his research, teaching, the way he has lived his life, and his courage while confronting pancreatic cancer. this session brings together people he has touched through various phases of his career to discuss his research and legacy.
the virtual midas touch: helping behavior after a mediated social touch. a brief touch on the upper arm increases people's altruistic behavior and willingness to comply to a request. in this paper, we investigate whether this midas touch effect would also occur under mediated conditions (i.e., a text messaging system and an arm strap equipped with vibrotactile actuators). although helping behavior was more frequently endorsed in the touch, compared to the no touch condition, this difference was not found to be statistically significant. such a failure to find response similarities between vibrotactile stimulation and real (i.e., unmediated) physical contact undermines the design rationale of the field of mediated social touch, which aims to provide an alternative for real physical contact.
extracting "broken expectations" from call center records: and . currently, despite the explicit industrial consideration to improve the appeal and usability of technically sound electronics products, users increasingly seem to have dissatisfactory experiences in interacting with them. these unforeseen experiences (attributable to specifications omissions, usability/learnability problems, or specific usage context) lead to a large and increasing share of unknown field complaints. to correct and prevent such complaints or user reports, we promote effective exploitation of call centers: valuable usage data is retrievable from the field by adopting a user-centered failure classification model that we developed. we also report on the supporting results of a test from applying our model to a set of call center data.
enhancing online personal connections through the synchronized sharing of online video. going to movies in a group and inviting friends over to watch tv are common social activities. this social engagement both improves the viewing experience and helps us stay close with our friends and family. to bring this feeling of co-presence to the internet, we developed a set of prototypes that enable people to feel more connected by watching web video together in sync. we present the preliminary results of a quantitative usage study and show initial evidence that simultaneous video sharing online can help people feel closer and more connected to their friends and family.
qr-codes for the chronically homeless. we propose a system to use qr codes and cheap cell phones to alleviate some challenges faced by the chronically homeless. we propose combining the affordability, simplicity and portability of cell phones with the fast emerging qr code technology to develop an information system which could augment current data entry methods utilized by homeless service agencies. the system offers simple interfaces which employ qr codes for configuring cell phones to perform basic functions such as setting up reminders. the system is robust to the loss of its components, individual phones and qr cards. we developed and refined our design concept through an iterative design process of contextual inquiry, persona development, prototyping, and user tests.
night and darkness: interaction after dark. many of us work and socialize late into the night, some increasingly so. however, most information technology is still designed in the daytime and largely to be used in the light. little thought is given to its behavior in darkness, even if the technology itself can sense darkness, or sleep. the aim of the workshop outlined below is to examine night and darkness as a starting point for designing ubiquitous computing. we aim to explore if and how the behavior of our technology should change as night falls. the workshop will use the topics of darkness, safety, 'nighttime people' and nighttime activities to think about new design opportunities for interaction design and ubiquitous computing. practicing what we preach, so to speak, the workshop participants will also critique their ideas and designs in the dark, in florence.
culture calling: where is chi? despite some incredible books and works on culture in the past decade by wonderful designers, anthropologists and thinkers like kenji ekuan, genevieve bell and howard rheingold, the chi community is still sparse on conversations and publications surrounding the place and significance of world cultures on design and hci. [4, 6, 12] culture as a lifestyle, a set of beliefs and value systems that shape everyday life in countries around the world, is at the core of understanding what our community calls 'the user'. it is the context that explains all data and inspiration we use in our design and creative processes. this sig provides members of hci & design communities with an opportunity to explore and discuss different ways in which we can integrate culture as an essential aspect of our thinking, research and design of products, services and systems.
the design of gaze behavior for embodied social interfaces. non-verbal behavior, particularly gaze, is a crucial part of human communication. to interact with humans in a rich, natural way, social interfaces need to use this communicative channel effectively. while the role and mechanics of human gaze are extensively studied, how gaze might be used effectively by embodied interfaces is not well explored. the goal of my dissertation is to gain a deeper understanding of how gaze behavior affects people's interactions with embodied social interfaces and how we can design gaze for effective communication. this research focuses on four main social functions of gaze: regulation, expression, establishing joint attention, and initiating/avoiding of social encounters and four sets of design variables: temporal, spatial, physiological, and contextual. a systematic study of how these functions and design variables affect each other is conducted through a series of empirical studies.
measuring affect in hci: going beyond the individual. the measurement of affect in hci research is a challenging and complex issue. although a number of techniques for measuring affect have been developed, a systematic discussion of their effectiveness and applicability in different contexts remains lacking, especially in social contexts with multiple users. as computing shifts to increasingly collaborative and ubiquitous models, it is important to discuss affect measurement beyond the individual level. this workshop will provide a forum where designers, practitioners, and researchers can 1) introduce novel methods of affect measurement that go beyond physiological and self-report measures, 2) advance our understanding of existing measurement methods and how they can be expanded, and 3) critically evaluate issues of affect measurement.
public displays of affect: deploying relational agents in public spaces. design principles for deploying agents designed for social and relational interactions with users in public spaces are discussed. these principles are applied to the development of a virtual science museum guide agent that uses human relationship-building behaviors to engage visitors. the agent appears in the form of a human-sized anthropomorphic robot, and uses nonverbal conversational behavior, empathy, social dialogue, reciprocal self-disclosure and other relational behavior to establish social bonds with users. the agent also uses a biometric identification system so that it can re-identify visitors it has already talked to. results from a preliminary study indicate that most users enjoy the conversational and relational interaction with the agent.
dynamic design elements for the peripheral interaction of ambient media. ambient media utilize peripheral awareness in interaction with people, which can be described as peripheral interaction. it represents information through dynamic changes of light, sound, form, or color in a physical space. in this study we present dynamic design elements and methods to apply them for peripheral interaction of ambient media in a physical space. we report on characteristics of dynamic design elements for peripheral interaction by reviewing literatures in psychology or related to ambient media. based on the characteristics, we describe our design and prototype system of new ambient media, cyber pung-kyung, focusing on how to apply dynamic design elements for peripheral interaction.
developing a novel interface for capturing self reports of affect. this paper describes the subtle stone, a tangible handheld tool which supports the communication of emotional experience in the classroom. the results of an initial evaluation suggest that this novel interface is easy to use within a busy working context, and renders the concept of emotion more accessible to young learners. the highly adaptable nature of the tool may make it a useful research instrument within other experimental contexts as well as a communication device for different experiential reports.
evaluating automatically generated location-based stories for tourists. tourism provides over six percent of the world's gross domestic product. as a result, there have been many efforts to use technology to improve the tourist's experience via mobile tour guide systems. one key bottleneck in such location-based systems is content development; existing systems either provide trivial information at a global scale or present quality narratives but at an extremely local scale. the primary reason for this dichotomy is that, although good narrative content is more educationally effective (and more entertaining) than a stream of simple, disconnected facts, it is time-intensive and expensive to develop. however, the wikear system uses narrative theory-informed data mining methodologies in an effort to produce high-quality narrative content for any location on earth. it allows tourists to interact with these narratives using their camera-enabled cell phones and an innovative interface designed around a magic lens and paper map metaphor. in this paper, we describe a first evaluation of these narratives and the wikear interface, which reported promising, but not conclusive, results. we also present ideas for future work that will use this feedback to improve the narratives.
attending to large dynamic displays. although studies have shown that physically large displays bring benefits in performance and user satisfaction, the expanded field-of-view (fov) places considerably higher demands on our cognitive capacities. understanding how we process information over a wide fov is increasingly important to optimize interface design. so far, however, empirical investigations are scarce. we present an experimental paradigm and framework for research with large displays and we report a preliminary experiment that explores attentional performance over a wide fov. the paradigm simulates aspects of tasks that are facilitated by large displays. our data suggest that processing abilities in the center and periphery are similar only if distractors are not present. with distractors, peripheral processing is disrupted and performance is poorer than in the center. in general, both accuracy and speed decline if the user must process information simultaneously in both areas. we discuss the implications for interface design, and describe further work that we are planning within this framework.
uvmode: usability verification mixed reality system for mobile devices. uvmode is a mixed reality based usability evaluation system for mobile information device development. the system contributes to increasing efficiency of the usability evaluation process by replacing real products with virtual models. with our system, users can change the design of a virtual product easily, and investigate how it affects its usability. while users can review and test the virtual product by manipulating it with mr interfaces, the system also provides evaluation tools for measuring objective usability measures, including estimated design quality and users' hand load. in this paper, we present the system design and implementation details of our system, and discuss how it could improve the current usability evaluation processes held in mobile information device industry.
chi policy issues around the world. while public policy is a recognized important topic within human-computer interaction, not enough attention has been paid to public policy efforts outside of the usa. we propose a panel at chi 2008 to focus on chi policy issues around the world. specifically, we plan to address at least three major topics: accessibility, privacy, and voting.
implementing eye-based user-aware e-learning. we propose an e-learning scenario where eye tracking is exploited to get valuable data about user behavior. what we look at - as well as how we do that - can in fact be used to improve the learning process, revealing information which would otherwise remain hidden. the prototype system we are developing at the university of pavia takes into account both the user's "emotional status" and the way learning activities are carried out, employing these data to adapt content presentation in real-time.
master of the game: assessing approachability in future game design. game approachability principles (gap) is proposed as a set of useful guidelines for game designers to create better tutorials, or first learning levels-especially for the casual gamer. developing better first learning levels can be a key step to ease the casual gamer into play and to do so proactively-before it is too costly or cumbersome to restructure the tutorials to be more effective. thus, game approachability in the context of game development is defined as making games initially more friendly and accessible for players who have the desire to play, yet do not always follow-through to actually play. gap has evolved through a series of stages assessing applicability as a stand alone, heuristic based approach versus one-on-one usability testing. outcomes suggest potential for gap as (1) effective heuristic evaluation, (2) adjunct to usability testing, and (3) as proactive filters in beginning conceptual and first learning level tutorial design to increase game approachability--for all levels of gamers.
where no interface has gone before: what can the phaser teach us about label usage in hci? most research on how people represent procedures suggests that control labels are central. however, our data suggest that even moderately-experienced users do not rely on labels to locate interface elements.
interactive control of music using emotional body expressions. this paper presents a novel music mixing interface which allows users to blend between pieces of music by moving their whole body in different emotional styles. although the interface itself would be most applicable for the performing arts and gaming, the principles concerning the use of emotions and body motion analysis apply to many other areas interested in the design of intelligent user interfaces. we report the results of a pilot user study which suggest that such an interface could afford an emotionally immersive experience. however, individual user differences in the expression of emotions need to be accounted for.
hci for community and international development. this workshop explores the challenges in applying, extending and inventing appropriate methods and contributions of human computer interaction (hci) to international economic and community development. we address interaction design for parts of the world that are often marginalized by the global north as well as people in the global north who are themselves similarly marginalized by poverty or other barriers. we hope to extend the boundaries of the field of human computer interaction by spurring a discussion on how existing methods and practices can be adapted and modified, and how new practices can be developed, to deal with the unique challenges posed by these contexts.
tag-it, snag-it, or bag-it: combining tags, threads, and folders in e-mail. we describe the design of bluemail, a web-based email system that provides message tagging, message threading, and email folders. we wanted to explore how this combination of features would help users manage and organize their email. we conducted a limited field test of the prototype by observing how users triage their own email using bluemail. our study identified ways in which users liked tagging, threading, and foldering capabilities, but also some of the complex ways in which they can interact. our study elicited early user input to guide the iterative design of these features. it also involved a user study researcher, designer, and developer in the field test to quickly integrate different perspectives during development.
paperproof: a paper-digital proof-editing system. we present paperproof, a paper-digital proof-editing application that allows users to edit digital documents by means of gesture-based mark-up of their printed versions. this enables users to switch seamlessly back and forth between paper and digital instances of a document throughout the document lifecycle, working with whichever medium is preferred for a given task. importantly, by maintaining a logical mapping between the printed and digital instances, editing operations on paper can later be integrated into the digital document even if other users have edited the digital version in parallel. the system is based on anoto digital pen and paper technology and is implemented using the ipaper framework for interactive paper.
recovering trust and avoiding escalation: an overlooked design goal of social systems. the online trust discussion is focused on mechanisms for building and maintaining user trust. this paper introduces the relevance of providing for the repair of trust breakdowns. three criteria are proposed for designing reparative mechanisms within trading systems. the reparative ability of two existing systems is then evaluated by using these criteria as a framework.
development of information terminal 'it scarecrow' for rural station. this paper explains the development of an information terminal for a rural station and its background system. the information terminal, which we call 'it scarecrow', displays traffic information based on a train location system. it is designed like a scarecrow to blend into a rural station. the service the system provides depends mainly on passengers' surveys and discussions with the rural community. in addition, we tried to make the system at low cost. in the spring of 2007, we made some preliminary system tests followed by an experiment in an actual station. as a result, we learned what the critical conditions for the next implementation should be. the it scarecrow is consulted as a representative of communication between a railway and a local community. we hope the system will expand and also that it be implemented as a mobile guidance system.
the grocerymate: eliciting community empathy and transforming it into purposeful action. people who are homeless in the united states lack adequate amounts of nutritious food which is detrimental to their health. we are designing a grocery shopping assistance device that strategically requests affordable and nutritious food donations that charitable organizations need to feed the homeless. we target grocery shoppers, since doing so allows us to leverage mass participation, as well as frequent and balanced community participation. this device employs persuasive technology to elicit emotions of empathy and alter the behavior of grocery shoppers to encourage them to donate. the device provides the shopper with an enhanced, personalized shopping experience making it appealing to use.
cogtool-explorer: towards a tool for predicting user interaction. in recent years, research predicting search through webpages has begun to be successful. however, existing tools ignore the order in which on-screen options are evaluated and therefore might make inaccurate predictions. we developed cogtool-explorer and used it to model a previously published web-based experiment. its predictions were better than those of a previously published tool, and included the order of evaluation effect not accounted for by previous tools. these more accurate predictions can be attributed to the approach used in cogtool-explorer.
can blogs empower women?: designing agency-enhancing and community-building interfaces. the much-touted empowerment potential of blogs is empirically examined in this study through an online survey of female bloggers (n = 340). our findings indicate that by affording users either a strong sense of community, or a deep sense of agency, or both, blogging is indeed psychologically empowering to those undertaking it. this is part of an ongoing series of investigations into the empowerment potential of web 2.0 interfaces for marginalized groups in society. implications for design are discussed.
a framework for understanding mobile internet motivations and behaviors. why do people access information via the mobile internet? this qualitative study examines a group of active users and proposes a new preliminary framework for understanding their motivations and behaviors.
barriers to virtual collaboration. this paper reports on the implementation and use of a virtual collaboration system - a virtual collaborative desk (vcd) that has been introduced to a software design team in an organizational context. virtual collaboration systems are complex and can be considered as social-technical systems, oftentimes encompassing several layers of both technical and social issues. if this multi-layered social-technical system is to work effectively and provide a dependable service, then all the layers must be well understood and structured accordingly. otherwise, these layers can become barriers to virtual collaboration if they impede the collaborating users of a virtual team from attaining their goals. an amalgamation of principles from life-cycle and ethnomethodologically informed ethnography approaches in the evaluation of a virtual collaborative system is demonstrated in a case-study to enable researchers to understand what these issues are and how the different types of issues can prevent effective virtual collaboration.
eye movements as implicit relevance feedback. reading detection is an important step in the process of automatic relevance feedback generation based on eye movements for information retrieval tasks. we describe a reading detection algorithm and present a preliminary study to find expressive eye movement measures.
methodological advancements of cross-cultural user-analysis. in this paper we describe the formatting requirements for chi2007 extended abstracts and offer recommendations on writing for the worldwide sigchi readership.
dip - it: digital infrared painting on an interactive table. in this paper we report on our work to develop a novel input technique for a digital paint system. using a brush with infrared (ir) light emitting fibers, we were able to create a natural paint interface on an interactive table. this ir-brush adds two important properties to our paint environment: haptic feedback and an accurate brush footprint. the modified brush approaches the haptic feedback of the traditional paint brush. the use of ir-light in the brush enables tracking the contact area of the brush on the interactive table. informal usability tests show that our digital paint environment offers an intuitive interface and contributes to an enhanced user experience in digital painting.
intelligent object group selection. current object group selection techniques such as lasso or rectangle selection can be time consuming and error prone. this is apparent when selecting distant objects on a large display or objects arranged along curvilinear paths in a dense area. we present a novel group selection technique based on the gestalt principles of proximity and good continuity. the results of a user study show that our new technique outperforms lasso and rectangle selection for object groups in(curvi)linear arrangements or clusters, i.e. groups with an implicit structure.
the new face of procedural content: a real world approach. this paper describes a large-scale project to improve the effectiveness of knowledge base (kb) articles on a support website in solving problems experienced by novice to intermediate computer users. the project encompasses the structure of the content, the quality of the writing and graphics, and the user interface presentation. in addition, we are developing guidelines intended for the designers and writers of new kb articles. we leveraged product knowledge, research findings, and extensive experience in user support to develop and empirically test three prototypes. preliminary test results show improved solve rates ranging from 17% to 26%, with still better results from pilot content currently released to the public.
exploring characteristics of collective content: a field study with four user communities. people increasingly share online information with the communities they belong to. this paper presents an empirical field study of four communities on how they interact with collective content. our results reveal users' motivations for creating collective content. the results indicate the defining characteristics by which collective content can be described: semantic content of the content item, the level of sharing and the community's contribution. furthermore, we found that collectivity of content is not primarily an ownership issue but more a matter of users' perceptions of communality of content.
preliminary evaluation of a remote mobile collaborative environment. mces (mobile collaborative environments) are systems designed to allow users to collaborate any time and anywhere using wireless networks and mobile devices. in this paper we report on our findings from the development and testing of a fully functional mce photo-conferencing service that enables seamless synchronous collaboration between remote mobile users over existing 3g cellular networks. key to the development of mces is an understanding of the effects of remote gestural interactions between mobile participants. we report on the results of an initial evaluation of our photo-conferencing service, examining the effects of two remote gestural interactions, 'pointing' and 'scaling', assessing their impact on performance measurements. our findings begin to inform the design of future mobile collaborative environments.
ecovillages, values, and interactive technology: balancing sustainability with daily life in 21st century america. this project seeks to provide a rich account of the adaptive process that occurs as individuals with explicit value commitments interact with information technology. specifically, ethnographic methods are being used to investigate the information technology adaptive process as it unfolds in the daily life of two ecovillages, communities made up of individuals striving to balance their use of technology with a lifestyle that is environmentally, socially, and economically sustainable. anticipated research outcomes include: (1) an analytic description of information technology adaptive process; (2) a categorization of technological functionalities which support or constrain certain values, (3) an empirical extension of value sensitive design, and (4) an analysis of the negotiation around tensions which emerge as a community's values influence the use of information technology features and, reciprocally, as information technology features influence a community's values. most broadly this work contributes to our larger understanding of how the information technology adaptive process influences the human experience.
common sense assistant for writing stories that teach social skills. people on the autistic spectrum often have difficulties with social interaction, and these difficulties are compounded when a person faces the uncertainty of not knowing what to expect in a new social setting. detailed, step-by-step explanations of people's intentions and plausible actions can often help autistic people make sense of the situation, adapt to the social rules, and reduce stress associated with the social encounter. carol gray's social stories? are carefully structured stories designed to prepare autistic people for everyday situations such as smiling at friends, waiting in a line, and staying calm in an audience when the speaker's slides don't match the handouts. teachers or parents writing these stories often forget to include explanations of simple, "common sense" facts and simple variations of the story that might occur in different circumstances. we present a new tool that helps the writer explain salient points and think of more variations of the story. it uses a knowledge base of common sense sentences, open mind common sense, and inference in a semantic network, conceptnet. we are investigating whether this new tool's suggestions are useful by examining how often the writers choose and use the suggestions that it generates.
effect of agent appearance on people's interpretation of agent's attitude. we conducted psychological experiments in which participants were presented with artificial sounds that were intended to convey the attitudes of three different agents: a mindstorms robot, an aibo, and a laptop pc. the participants were asked to select the correct attitudes based on the sounds expressed by these three agents. the results showed that the participants had higher interpretation rates when the pc presented the sounds, even though the utilized artificial sounds were the same for all three agents.
human-centered space design for the homeless: clean dignity. the goal of this document is to present both the methods employed by the team in collecting useful information pertaining to homelessness, and the proposal for a possible solution that was arrived at after analysis of the results. emphasis is placed by the authors on the process of information collection, the interpersonal interaction with the homeless subjects, and the subtleties of the problem space explored in defining a solution.
tabletop interface using a table's circular vibration and controllable friction. in tabletop interfaces, there have been many proposals to control moving objects on the table. but it was hard to miniaturize or simplify the system. in this paper we propose a new simple tabletop system using table's circular vibration and controllable friction of the moving object.
exploring evaluation methods for ambient information systems. in this paper, we begin by laying out our motivation for exploring methods of evaluating ambient information systems, with a strong push toward in-situ studies. next, we describe a simple study which was conducted to give us further insight into this research domain. we conclude by discussing the insights gained from our study, and possible ways to improve our evaluation results in future iterations.
accessibility in virtual worlds. virtual worlds present both an opportunity and a challenge to people with disabilities. standard ways to make such worlds accessible to a broad set of users have yet to emerge, although some core requirements are already clear. this paper describes work in progress towards an accessible 3d multi-player game that includes a set of novel tools for orienting, searching and navigating the world.
homeless healthshare: connecting health professionals and the homeless. we are developing a web-based system that helps improve the health of homeless individuals by aiding healthcare professionals in identifying, locating, and contacting homeless patients in order to initiate and continue effective healthcare. poor health is both a significant cause and a symptom of homelessness, carrying high costs for the general public as well. our system addresses health problems amongst the homeless by allowing healthcare professionals and other homeless service professionals from multiple organizations to better share, manage, and communicate information vital to effective healthcare.
providing insight into group process. this paper presents ongoing work towards development of a reporting tool for providing group work facilitators with insight into group work processes. the work includes three main phases, including feasibility testing, initial design based on data analysis of interviews, and iterative design based on user testing. here, the work completed to date on the first two phases is presented along with ideas for the last phase of the work.
the next challenge: from easy-to-use to easy-to-develop. are you ready? the main challenge of next years is to allow users of software systems, who are non-professional software developers, to create, modify or extend software artefacts. in this panel we want to discuss with the chi community the key aspects in the area of end user development and an associated research agenda, which should be then proposed to the main research agencies, such as nsf and eu ict.
evolving tuis with smart objects for multi-context interaction. we present our ongoing work, an application framework created to extend the concept of natural and tangible interfaces to environments composed of many interactive systems disseminated in an indoor space. in such environments users can perform solo or collaborative activities using different systems (like interactive tabletops or walls) and interacting with them through tangible smart objects provided with sensors, storage, processing and wireless communication capabilities. the smart objects become the representatives of the user navigating in the environment, and while retaining their basic affordance suggested by their shape, can assume different roles in relation to the system they approach. we investigated some application scenarios and present early observations related to the design and implementation, as well as future directions.
a gesture based game for image tagging. this paper proposes and discusses the asaa (application for semi-automatic annotation) interface, a new computer game for image tagging. the application is composed by a 3d game interface, a game engine that uses a system for automatic image annotation and gestural input to play the game. the paper describes the rational and design principles for the application and presents ideas for future developments.
the cuetable: cooperative and competitive multi-touch interaction on a tabletop. in this paper we explain how we built cuetable, a multi-touch interactive tabletop, as a base technology to explore new interaction concepts for cooperative and competitive multi-touch applications. we present the puh game application. and most of all we report on user feedback to the cuetable and the puh game.
storytelling with digital photographs: supporting the practice, understanding the benefit. storytelling has been a mainstay of communication between humans for centuries. despite the sharp increase in digital photography and tools to support digital photo practices, constructing personal narratives with digital photographs remains a difficult problem. creating personal narratives requires story-writing, media editing, and media composition skills. this research explores how to support everyday people through the challenges of narrative composition with photographs by leveraging everyday photo practices to make storytelling with photos easier. it is also concerned with providing a satisfying experience to authors and audiences alike.
visualizations: speech, language & autistic spectrum disorder. without speech, we can have great difficulty communicating wants, emotions, needs, and interacting with society at large. during typical child development, an infant acquires language skills without explicit teaching. however, some children, including those with autistic spectrum disorder (asd) have explicit difficulty developing these skills in the context of everyday interactions. hci is situated to help by developing technology and techniques to teach speech and language skills to children with asd through the use of visual and auditory feedback. this paper examines preliminary results from a study, as well as describes new directions of research.
fishing for sustainability: the effects of indirect and direct persuasion. websites and technologies that promote sustainable behavior often employ direct persuasion by being open about persuasive intent. we examined the use of indirect persuasion, methods that do not make persuasive intent clear. we built two variants of a recipe website designed to induce changes in users: one using direct persuasion and the other using indirect methods. we measured the effects of each site on users' attitudes and actions towards the environment. preliminary results show that the direct style influenced actions while the indirect style influenced attitudes. we discuss the implications of this dissociation for research and applications.
agile or awkward: surviving and flourishing in an agile/scrum project. the agile development methodology poses challenges to the traditional user centered design process. in this panel discussion differing experiences and approaches will be shared and debated along the panelists with the audience encouraged to contribute to the discussion. the goal of the session is both a survey of ucd experience with the agile/scrum method and collectively developing best practices on working within an agile/scrum environment.
the nestegg: a budgeting tool. the nestegg is a simple to use budgeting tool designed to help people who earn a low income. these individuals may be one paycheck away from no longer being able to afford housing, thus living on the edge of homelessness. sometimes referred to as the "working poor," one in every five people in the united states was classified as such by the u.s. department of labor in 2003 [1]. by providing a mechanism to track their income and expenses and teach solid money management skills, financial stability can be achieved, aiding in the prevention of homelessness.
interpersonal connectedness: conceptualization and directions for a measurement instrument. interpersonal connectedness is the sense of belonging based on the appraisal of having sufficient close social contacts. this feeling is regarded as one of the major outcomes of successful (mediated) social interaction and as such an important construct for hci. however, the exact nature of this feeling, how to achieve it, and how to assess it remain unexplored to date. in the current paper we start the theoretical conceptualization of this phenomenon by exploring its basic origins in psychological literature and simultaneously formulate requirements for a measurement instrument to be developed in the service of exploring and testing cmc applications, in particular awareness technologies.
study and modeling of user errors for virtual scanning keyboard design. virtual scanning keyboards are text entry systems used by individuals with severe speech and motion impairments. in this paper, we present results of our empirical study on user errors for such keyboards. we also propose a computational error model and a method for evaluation of such keyboards taking errors into account. the work is aimed to help designers make appropriate choice from a large number of design alternatives with minimum user involvement.
confidence camp. homeless people who want to leave homelessness have a really hard time doing this, because they are stuck in the very same environment and have to face their problems alone. our solution provides homeless people with a much needed vacation from their daily lives at the same time as they can learn new skills and build network that will help them in the future. the idea is a camp for the homeless based on four features that we have found are important to get out of homelessness; change of environment, activation, improvement of self-efficacy and improvement of social abilities. it is a place where they can prepare for the long journey out of homelessness.
real ethics in a virtual world. this paper investigates the ethics of the appearance and behavior of avatars in massively multi-user online communities, in particular, avatars created for virtual business interactions in second life. the ethics of research conducted with avatars in 3d online environments is also discussed.
: using gaze and pupil size to control a game. we present an eyes-only computer game, invisible eni, which uses gaze, blinking and as a novelty pupil size to affect game state. pupil size can be indirectly controlled by physical activation, strong emotional experiences and cognitive effort. invisible eni maps the pupil size variations to the game mechanics and allows players to control game objects by use of willpower. we present the design rationale behind the interaction in invisible eni and consider the design implications of using pupil measurements in the interface. we discuss limitations for pupil based interaction and provide suggestions for using pupil size as an active input modality.
intelligent interactions in email using social networks and ai. this work is directed toward high-throughput email users, and uses machine learning and other artificial intelligence approaches to allow these users to triage and search email using automatically extracted social networks. while this approach makes use of (potentially) complex algorithms, these algorithms are abstracted through user interface design such that a non-technical user can take advantage of them, customizing when appropriate. my dissertation work will crystallize the needs of high-throughput email users into concrete tools to allow these users to better and more easily manage their information needs.
using wearable computing solutions in real-world applications. in this paper we report on the wearit@work project. with the wearit@work project the european commission and 42 partners from 16 countries invested into a new technology empowering mobile workers. the first 42 months of this project are over and industrial demonstrators, evaluations and results and an exploitation strategy are available. beside the four application domains of maintenance, production, healthcare and emergency response further domains like cultural heritage, a rural living lab for the prevention of environmental disasters and einclusion are first extensions to new application domains. in this paper based on the results of the third development cycle of the project results and an approach of the exploitation strategy are presented.
what would you do with a 1 million dollar user experience marketing budget?: internal vs. external user experience evangelism. user experience evangelism inside an organization is a frequent topic. methods for marketing user centered design to internal stakeholders have been analyzed in many papers and on panels. emerging media and new venues have recently presented an opportunity to reexamine methods and goals for external user experience marketing and evangelism. this interactive panel will address motivations and brainstorm about discount methods for promoting the role of the human factors profession to the general public, and communicating directly with the end users. this will be contrasted with the position that a well designed product should market itself, and that money is best spent on design and internal evangelism instead. the panel itself will involve 3 parts: 1. moderator collecting answers to the "what would you do with a 1 million dollar ux marketing budget?" question via index cards. 2. four panelists presenting short sales pitch proposing what they would do when faced with the same question. 3. panel discussion focusing on the contributions from the audience and focused on producing two lists. one would include specific user experience marketing venues (targeted bloggers, un-conferences, think tanks, specific ad words, design-friendly printed publications like business week, etc.). the second list would focus on goals and of user experience marketing (raising awareness and promoting better image of user experience vs. engineering and other disciplines, increased sales, better brand, recruiting, swaying executives, etc.). the panel would continue to live after external publication of the two lists, with new blog installments, comments, and any subsequent and open discussions.
mobile science learning for the blind. science learning for blind people is limited. for a variety of reasons there is a very low emphasis on science learning for such users, especially those from deprived communities. we have designed, implemented and evaluated the usability of audionature, an audio-based interface implemented for pocketpc devices to assist with science learning in users with visual impairments. the usability and the cognitive impact of the device were evaluated. users accepted the interface, enjoyed the interaction with audionature, felt motivated, and learned science. preliminary results provided evidence that points towards gains in problem solving skills and showed that game-based learning activities facilitate the user's interaction with the software.
unhelpful helpers: when scaffolding structures veil collaborative interactions. collaborative software tools are designed to support users in individual and group efforts to engage in complex tasks and/or to acquire and develop complex cognitive skills. the aim is to help users by alleviating or lessening the burden of complexity or even to hide or veil the complexity inherent in these tasks and skills. these embedded design structures act as scaffolds to provide support and laddering for users' attempts at climbing through, or mastering, skills and tool use. tools whose scaffolds and structures fail to support and/or mediate collaborative interactions and exchanges become "unhelpful helpers". unhelpful helpers stifle, hinder, and sometimes inhibit the collaborative interactions they were designed to support. through the use of both metaphysical and natural representations of scaffolding and collaborative interactions, we examine the emergence of unhelpful helping as a by-product, in particular, of the design of scaffolding in collaborative tools. we argue that collaborative tools should be designed with a realistic and deep understanding of the context and practices in which they will be used. furthermore, we argue that special attention and care should be given to the design of scaffolding structures to ensure that they support and help collaborative interactions and exchanges in ways they were intended.
using participants' real data in usability testing: lessons learned. in usability testing, we place great importance on authentic tasks, real users, and the appropriate fidelity of prototypes, considering them carefully in our efforts to simulate people's real-life interactions with our products. we often place less importance on the data with which we ask participants to interact. commonly, test data are fabricated, created for participants to imagine as their own. but relating to artificial data can be difficult for participants, and this difficulty can affect their behavior and ultimately call our research results into question. incorporating users' real data into your usability test requires additional time and effort, along with certain considerations, but it can lead to richer and more valid usability results.
meta-gui-builders: generating domain-specific interface builders for multi-device user interface creation. nowadays, there is a growing demand to design user interfaces that run on many devices. however, existing multi-device design approaches are not suitable for domain experts, whose input can be invaluable to come to a suitable user interface for a specific domain. existing techniques often require the manipulation of high-level models and transformations which are difficult to interpret and predict by a domain expert without a technical background. we present meta-gui-builders, a new generation of graphical user interface builder tools that allows domain experts to create multi-device gui designs themselves. these tools automatically adapt their workspace to a specific domain by encapsulating domain-specific elements in the designer's tool palette. engaging domain experts in a multi-device design approach is a first step towards creating aesthetic user interfaces that can be deployed on many devices, a combination that is hard to achieve with previous approaches.
a comparative evaluation of heuristic-based usability inspection methods. given that heuristic evaluation (he) is a popular evaluation method among practitioners despite criticisms surrounding its performance and reliability, there is a need to improve the method's performance. several studies have shown he-plus, an emerging variant of he, to outperform he in both effectiveness and reliability. he-plus uses the same set of heuristics as he; the only difference between these two methods is the 'usability problems profile' element in he-plus. this paper reports our attempt to verify the original profile employed in he-plus based on usability problem classification in the user action framework and an experiment evaluating its outcome by comparing he with two he variants using a profile (he-plus and he++) and a control group. our results confirmed the role of the 'usability problems profiles' on improving the performance and reliability of heuristic evaluation: both he-plus and he++ outperformed he in terms of effectiveness as well as reliability.
technology in mental health. mental illness has been identified as one of the greatest challenges facing society in the coming decades. however, there are significant barriers to access for many people suffering from mental illness, including overburdened public health care systems, geographic distance from point of care, difficulties encountered by individuals in engaging with services, and the stigma associated with mental illness. technology has the potential to significantly improve access, engagement, effectiveness and affordability of treatment, yet relatively little use has been made of technology to date. significant opportunities exist for further research and development, but the domain throws up a variety of challenges for hci design and hci methods.
rub the stane. stane is a hand-held interaction device controlled by tactile input: scratching or rubbing textured surfaces and tapping. the system has a range of sensors, including contact microphones, capacitive sensing and inertial sensing, and provides audio and vibrotactile feedback. the surface textures vary around the device, providing perceivably different textures to the user. we demonstrate that the vibration signals generated by stroking and scratching these surfaces can be reliably classified, and can be used as a very cheap to manufacture way to control different aspects of interaction. the system is demonstrated as a control for a music player, and in a mobile spatial interaction scenario.
information and communication tools as aids to collaborative sensemaking. collaborative sensemaking occurs when multiple actors engage in understanding an unfamiliar, information-rich environment. we present preliminary results from a field study of the collaborative activities of healthcare providers in an emergency department. the goal of our study was to explore the nature of collaborative sensemaking and the role various information and communication tools play in the process. we describe how paper, whiteboards, and the computerized provider order entry system support common external representations to enhance collaborative sensemaking; but at the same time gaps in collaborative sensemaking occur, leading to representation shifts.
natural interaction sensitivetable. the sensitivetable is a large multi-touch display that detects and tracks hands and objects in contact with it at 60 frames per second with a resolution of about 1.5 millimeters. a software application framework allows the creation of custom natural experiences. the table is equipped with array microphones and rfid antennas on its edges. the table runs a speaker independent speech recognition engine, based on a very small vocabulary, that is invoked only in specific circumstances. rfid tagged objects are used to populate the interface with contents, activate functions and authenticate users. due to its analytical nature (high resolution and multi-point gestures), the table in the public space is used mostly as a form of digital mediation between two or more persons (e.g. consultant and customer): the expert can lead the novice through the more complex and less intuitive dynamics of interaction. we provide the sensitivetable as an example of analytical natural interaction.
asister: scheduling for homeless women with special needs. homeless women need special care and attention especially during pregnancy or while trying to overcome substance abuse. we present a solution to help counselors working with these women. the solution allows the counselor to send text messages, which can be used to remind women of their daily schedule, as well as provide them with health and nutritional information. the system will also serve as a persuasive tool to help them develop positive behavior through the delivery of encouraging messages. cell phone technology usage is increasing rapidly among the homeless population. the system uses text messaging which is an inexpensive and non-obtrusive method of communication. our study contains details on the design of such a system and also attempts to evaluate the efficacy of such a text messaging system.
evaluating touch gestures for scrolling on notebook computers. we describe a new circular touch gesture for scrolling called chiralmotiontm and report on work to measure its performance. in a study using a document scrolling task, chiralmotion outperformed linear virtual scrolling on a notebook computer touchpad. participants also indicated a preference for chiralmotion in a follow-up questionnaire. we discuss the results and our plans for follow-up studies incorporating other devices.
defending design decisions with usability evidence: a case study. this case study takes a close look at what novice designers discursively use as evidence to support design decisions. user-centered design has suggested that all design decisions should be made with the concern for the user at the forefront, and, ideally, this concern should be represented by findings discovered within user-centered research. however, the data from a 12-month longitudinal study suggests that although these novice designers are well-versed with user-centered design theory, in practice they routinely do not use user-centered research findings to defend their design decisions. instead these novice designers use less definitive and more designer-centered forms of evidence. this move away from the user, though perhaps unintentional, may suggest that design pedagogy may need to be re-evaluated to ensure that novice designers continue to adhere to the implications of user-centered research throughout the design process.
seeing the bigger picture: a multi-method field trial of google maps for mobile. this case study discusses a 2-week field trial of google maps for mobile with 24 participants (in london, manchester, hamburg, munich). the field trial served as a pilot, because it combined many methods previously used individually: group briefing sessions, recorded usage, multiple telephone interviews for additional context around recorded use, and 1:1 debriefs in a lab setting with the development team observing. in this paper we describe our approach, as well as substantive and methodological findings. insights were gained along several dimensions: user experience at different levels of product familiarity (e.g. from download/install to habitual use); specific usability fixes (100+) as well as product strategy drivers; and hurdles to user experience arising from the mobile eco-system (e.g. carrier and handset platforms).
real-time snowboard training system. we present a wireless prototype system for real-time snowboard training. this system can be used to detect common mistakes during snowboarding and to give students immediate feedback on how to correct their mistakes. the project illustrates new ways to assist students during sports training and to enhance their learning experience on the slope.
particle display system: a real world display with physically distributable pixels. in this paper, the author designs and implements a new display system called particle display system, which can be installed on the non-planar surface of any objects. it consists of hundreds of full-color and wireless light emitting diode (led) nodes with a pc and video camera. the wireless capability makes the each node freely movable without distant limitation of the use of wire cables. by processing the images from the camera, the system calculates the positioning information of the each node and performs the timing control of the led in the each node in real time. therefore, the author is able to design a uniquely arranged pattern in full-color in the real world, by distributing and controlling the smart nodes. this paper describes the design and implementation of the prototype of particle display system.
monitoring time-headway in car-following task. this study investigates the effect of the follower and leader vehicles' speed on time headway variation during deceleration in a car-following task. significant results were found in deceleration onset; headway varies significantly when absolute and relative follower speed are high. these results suggest possible application in the tuning of in-vehicle advanced system for longitudinal safety control.
informatics at uc irvine. computer science, as a single discipline, can no longer speak to the broad relevance of digital technologies in society. the department of informatics in the donald bren school of information and computer sciences at the university of california, irvine, serves as the institutional home for research on relationships between technological, organizational, and social aspects of information technology. here, we describe the research landscape of the department of informatics and its relation to the diverse field of human-computer interaction.
driving the family: empowering the family technology lead. advances in technology continually increase the ability, but also the complexity of consumer electronics. this is especially true when several devices must be configured to work together, such as a digital tv and satellite box. manufacturers of consumer electronics attempt to remedy this by designing interfaces that consolidate multiple, complex user interfaces into a single, simple interface. however, the problem remains that end-users are still expected to configure and learn to operate these new interfaces on their own. this paper addresses the problem by proposing a radically new goal in terms of user interfaces for in-home, networked consumer electronics. instead of trying and failing to make interfaces simple enough for everyone to use, we propose making interfaces that allow a "technology lead" - the person in the family responsible for supporting the technology-to more easily administer devices in his or her own home and in the homes of other family members. in japan, where this study is taking place, user-centered research methods show that families usually have a single technology lead who is challenged with supporting people remotely in several homes. by enabling the technology lead to remotely support family members at a distance, the natural family dynamic can be used to support users who either find the new breed of consumer electronics too difficult to learn or do not wish to invest the time to learn how they work.
cutting edge usability design and smashing graphics: the perfect recipe for firing up a sophisticated pharmaceutical touch screen application. in this case study, we describe a complex pharmaceutical touch screen software development project in which an appealing graphical design on top of a well-thought user interface elevate the benefits of a good user interface design. based on this specific case, we emphasis the importance of a clear and simple navigation and interaction in a complex pharmaceutical touch screen application.
user experience over time. the way we experience and evaluate interactive products develops over time. an exploratory study aimed at understanding how users form evaluative judgments during the first experiences with a product as well as after four weeks of use. goodness, an evaluative judgment related to the overall satisfaction with the product, was largely formed on the basis of pragmatic aspects (i.e. utility and usability) during the first experiences; after four weeks of use identification (i.e. what the products expresses about its owner) became a dominant aspect of how good a product is. surprisingly, beauty judgments were largely affected by stimulation (e.g. novelty) during the first experiences. over time stimulation lost its power to make the product beautiful in the users' eyes.
ubipay: conducting everyday payments with minimum user involvement. as services embedded into public spaces become increasingly transparent, one peripheral aspect of use continues to demand explicit user attention: payment. ubipay is a system that carries out small everyday payments in a way that minimises user involvement by choosing an interaction method based on context information. the aim is to make paying like breathing: something we are only peripherally aware of unless we exert our resources beyond the usual. this idea has powerful implications for business and design.
development of a location and movement monitoring system to quantify physical activity. there are currently 1 billion overweight adults in the world according to the world health organization (who). being overweight can pose a major risk to the health of an individual. the main reason for the increase in obesity in the west is the large changes in society, for example, our work and our leisure pursuits are becoming increasingly less physically demanding. one of the main ways that, according to the who, an individual can combat this is to undertake 30 minutes of moderate physical activity a day. however, it can be difficult for a person to gauge this moderate physical activity. this paper describes the design of a prototype system which collects and subsequently combines data from an activity monitor and gps device in order to help people to examine their activity patterns. the intention is that the integrated system will provide data to the user and others that will enable them to assess the effectiveness of attempts to increase activity and indicate where barriers to increased activity may exist, particularly those caused by the external environment.
a framework for mobile evaluation. in this paper we present a software framework which supports the construction and evaluation of mixed-fidelity prototypes for mobile devices. the framework is available for desktop and mobile devices and allows designers and users to 1) test the prototypes on actual devices; 2) gather usage information, both passively and actively supporting contextual and ubiquitous evaluation; 3) convey common prototyping procedures with effective data gathering methods that can be used on ubiquitous scenarios; 4) support in-situ prototyping and participatory design on-the-go. we address the framework's features and its contributions to the evaluation of applications for mobile devices and the field of mobile interaction design, presenting real-life case studies and achieved results.
blocked sites and offensive videos: the challenges of teen computer use. teenagers are often presented as comfortable users of technology. to better understand this assumption, we asked 27 teenagers to complete a survey about the previous day's media use; we then interviewed the participants about these entries. the participants actively used computers for information, communication and entertainment. most of the comments about technology were positive, but our study also revealed problems in the teenagers' computer use. they had stories about parents and teachers restricting their use of the web and there were several instances in which the teens themselves found the web to be offensive, inappropriate and unreliable.
itone: a japanese text input method for a dual joystick game controller. in this paper, we report the design and evaluation of a japanese text input method called itone. it uses a dual joystick game controller to input japanese text. the left and right joysticks are respectively assigned to the left and right halves of the japanese syllabary chart. the combination of left and right joystick signals selects a character. itone is theoretically faster than the japanese selection chart. results of a preliminary user study show that users prefer itone to egconvert: its smoothness during operation and accuracy measures are significantly higher. in addition, the learning curve of itone suggests that it can be learned easily and that it potentially provides higher performance.
social and psychological reactions to receiving help from a robot. computer systems, including humanoid robots, are becoming capable of recognizing human activity and, in the future, may offer unsolicited help in a variety of contexts. this helpfulness may improve people's performance on certain tasks, but there could be negative social and psychological consequences. help recipients may feel vulnerable--that their self-esteem and their control over the task have been threatened. to better understand the social psychological impact of receiving help from a robot, this thesis explores strategies used in human-human conversation to deliver unsolicited help and observes participants' reactions to these strategies in human-robot dialogue.
keyholes: selective sharing in close collaboration. documents are changing, becoming more malleable. content operations progress, from command lines to annotation and tagging. our studies reveal that people in practice share entire documents when portions would suffice. readers hunt for relevant information. authors describe laborious processes of selective sharing and redaction. overload and loss of focus arises. we describe keyholes, content annotations where authors or readers enter meta-data within a document to indicate what gets shared, with whom, and why. we argue that leveraging established practices (tags, social annotation, and command-line automation) clashes with chi notions of technical contribution, but creates new social dynamism within document texts.
twelvepixels: drawing & creativity on a mobile phone. twelvepixels is an interface for drawing pixel-based imagery using only the standard keys on the mobile phone handset. using an essentially simple drawing method, an extensive range of imagery can be created and shared between users. this paper explores the rationale and details behind the development of the twelvepixels interface; tracking possible applications for promoting creativity, communication, and content sharing on mobile phones.
what about a local wrapper around an universal core? in this paper, i examine the possibility of restructuring our premise about cross cultural design and explore a possible new way to look at how we can create products in one culture and yet have the whole 'flat world' use it!
increasing design buy-in among software developer communities. this paper is based on projects in which the user experience (ux) team in bangalore adopted a user centered design approach to increase design buy-in among the developer community of our product and improve working relations with them. this paper provides ethnographical insights into the work practices our developers, their needs & limitations that prevent them from adopting the design process. we share our learning and methods we adopted to address these scenarios.
designing large-display workspaces for cooperative travel consultancy. this paper discusses the design and first deployment experiences of an interactive large-display workspace for face-to-face travel consultancy. the stickiness of client preferences, the asymmetry of information about the solution space and the emotional colouring of client choices, make this complex cooperative process difficult to perform. to support such collocated consultancies we propose a large-display system providing a shared visualization of information resources that can be manipulated jointly by both parties. the use of natural touch interaction and multimedia resources furthers emotional involvement of the user. results of a preliminary evaluation suggest that such a large-display workspace can greatly improve the cooperation process and both customer and agent satisfaction.
user interface description languages for next generation user interfaces. in recent years hci researchers have developed a broad range of new interfaces that diverge from the "window, icon, menu, pointing device" (wimp) paradigm, employing a variety of novel interaction techniques and devices. developers of these next generation user interfaces face challenges that are currently not addressed by state of the art user interface software tools. as part of the user interface software community's effort to address these challenges, the concept of a user interface description language (uidl), reemerge as a promising approach. to date, the uidl research area has demonstrated extensive development, mainly targeting multi-platform and multi-modal user interfaces. however, many open questions remain regarding the usefulness and effectiveness of uidls in supporting the development of next generation interfaces. the aim of this workshop is to bring together both developers of next generation user interfaces and uidl researchers in an effort to identify key challenges facing this community, to jointly develop new approaches aimed at solving these challenges and finally to consider future spaces for uidl research.
extreme usability: adapting research approaches for agile development. agile development is being adopted by many leading software companies, such as those represented by this panel. though many instructional resources exist to guide companies through a change to agile development, there are few resources available on the subject of agile development and user centered design (ucd). as a result, user experience practitioners have had to develop their own tactics and strategies for maintaining sound ucd practices within their organizations when moving to agile. this panel consists of six practitioners who actively work with development teams using agile. panel members will share the challenges and successes they face while championing ucd within their respective development organizations. panelists will focus on adaptations to research methodology and strategy that make ucd possible to attain within agile cultures.
acceptance of augmented reality instructions in a real work setting. the differences between augmented reality (ar) systems and computer display based systems create a need for a different approach to the design and development of ar systems. to understand the potential of ar systems in real world tasks the technology must be tested in real world scenarios. this case study includes two qualitative user studies where ar was used for giving instructions to users in a hospital. the data show that the users in the context of medical care are positive towards ar systems as a technology and as a tool for instructions in terms of usefulness and social acceptance. the results indicate that ar technology, should it be introduced as technical support in this context, may become an accepted, and appreciated, part of every day work.
understanding consultants' information-seeking practices: knowledge management's touchpoint. this note reports on preliminary findings from a study of consultants' information-seeking practices in a global it services company. we conducted semi-structured interviews with consultants in addition to observing their interactions with a knowledge repository in the course of everyday problem-solving events. initial analyses suggest that consultants interacted with the knowledge repository with very instrumental ends in mind, looking for information that resembled more tidbits than knowledge. time was also an important constraint--search was rarely approached without a perceived time cost. though deeper analysis is pending, our data points to broader implications for the design of knowledge repositories, designers' and scholars' conceptualizations of them, and subsequently, approaches to studying them. we end with a discussion of next steps toward developing this work more fully.
the bandwagon effect of collaborative filtering technology. advancements in collaborative filtering and related technologies have resulted in the ubiquitous presence of other users' opinions and actions on a variety of websites and portals, ranging from news to music to photo sites. but, do these cues about others' behaviors guide our own decisions online? our lab group has begun exploring this "bandwagon effect" from a variety of perspectives. in one pilot study reported here, outcomes such as purchase intention and attitudes toward products on an e-commerce site are dictated by user perceptions of others' opinions about the site's products. empirical determination of the cues triggered by collaborative filtering technologies and the psychological mechanisms by which they lead to bandwagon effects have important implications for interface design of technologies that display user input.
opportunities to support parents in managing their children's health. parents always desire to take good care of their children and manage their numerous responsibilities. one of parents' main responsibilities is to manage their children's health. through their actions of caring for their children, parents want to know they're doing the best job to ensure their children's well being. unfortunately, much of the time this responsibility is a challenge-particularly for busy, dual-income parents-because it involves the collection, organization, retrieval, and transfer of information between many people in many different contexts. in our user research with dual-income parents they shared their experiences of forgetting to give medication, and of both not having an easy way of recording information and not having the information they needed when communicating with childcare and healthcare providers. smart home technology appears to offer a promise to easy this situation for parents; however, the hci community has only investigated healthcare in the home with a focus on elders. to better understand this opportunity area we conducted a user-centered design project looking at the management of children's by their parents.
looking good on the web: evaluating the visual impact of political websites. we present a study designed to measure the perceptions of the visual design for political websites. we use as our sample population approximately 400 different websites for united states congressional office-holders. in the analysis and presentation of our results we use the united states map divided into congressional districts, and then encode the study participants' perceptions of the visual design of the websites according to a color scale that maps to the perceived favorability of the site. our motivation for the visualization is, of course, the well known red-blue map that depicts election results according to support for a particular political party. further, we intend to look at the competitiveness of the districts where congressional elected officials reside, the noticeable features on their websites (for example, if a blog or visible contact information exists), as well as the results in relation to demographic information about the individual (political party, gender, age, etc). beyond developing an understanding of the political landscape, our study aims to suggest a set of heuristics that tend to lead to more favorably perceived website designs.
collaborative search and sensemaking of patents. despite the large number of patent searches conducted by professional patent searchers and inventors, little is known about how such searches are actually performed. here we describe a qualitative study of experienced patent searchers as they conducted in-context searches at a technology transfer office. based on studies of expert search and sensemaking in other domains, we expected the professional searchers to (1) use well-formed search strategies that were effective for patent search, and (2) rapidly make sense of the novelty of an invention by constructing new representations to organize existing patents that appear relevant. instead, we observed the searchers perform simplistic preliminary searches and then exchange their search process and results with inventors and patent lawyers to collaboratively make sense of the patentability and licensability of the invention. furthermore, their sensemaking consisted of selecting known representations of patents to organize the new information, an approach we call "weak" sensemaking. these results suggest implications for designing systems that support the observed collaborative "weak" sensemaking with the goal of helping the users to more effectively determine the patentability and licensability of an invention.
the disappearing desktop: pim 2008. in an ideal world, we would always have the right information, in the right form, with the right context, right when we needed it. unfortunately, we do not live in an ideal world. this workshop looks at how people in the real world manage to process massive amounts of information, and discusses how tools can bring real information interactions closer to the ideal.
a large 2d+3d focus+context screen. today, the amount of unstructured, multidimensional information is becoming more and more complex and overwhelming. one promising approach to face these problems is the efficient use of large displays. their immersive effect is even stronger when using a stereoscopic representation of information. however, the technical limitations of such 3d projective systems result in a loss of detail and a bad readability of textual information. we present a novel approach which enhances a 3d projective system by providing an additional high resolution 2d focus area.
portalis: using competitive online interactions to support aid initiatives for the homeless. we designed a web-based system with game-like properties that utilizes crowdsourcing to facilitate the beneficial transfer-of-knowledge to case managers (cms) working with the homeless. this has two significant impacts: first, portalis allows cms to make informed decisions in managing client cases. second, it enables individuals who would like to volunteer their services but are limited by time constraints to contribute.
the georgia tech aware home. the aware home research initiative (ahri) at georgia tech is devoted to the multidisciplinary exploration of emerging technologies and services based in the home. starting in 1998, our collection of faculty and students has created a unique research facility that allows us to simulate and evaluate user experiences with off-the-shelf and state-of-the-art technologies. with specific expertise in health, education, entertainment and usable security, we are able to apply our research to problems of significant social and economic impact.
photos for information: a field study of cameraphone computer vision interactions in tourism. advances in mobile computing and computer vision can support camera-based interactions with mobile devices, including systems that use image-matching to support getting information about objects identified by the camera. these interfaces, sometimes considered mobile augmented reality, can be applied in many domains. this paper reports on a field study of these interfaces in a tourism application, which begins to address questions about embodied interaction, existing photo-taking practices, and alternative interfaces.
digital rubbing: playful and intuitive interaction technique for transferring a graphic image onto paper with pen-based computing. in this paper, we introduce digital rubbing, which is a playful and intuitive interaction technique for transferring a graphic image directly onto paper. we designed transpen and mimeopad to realize digital rubbing. with these drawing tools, children and adults can use rubbing motions to transfer a digital image directly to paper and produce a drawing with a personal touch and natural texture, just as in traditional rubbing. we expect that digital rubbing technique would be useful in arts and design as a new way of expression in the process of drawing and editing ideas. in addition, the suggested interaction devices have the full potential to become new drawing toys for children.
meeting mediator: enhancing group collaboration with sociometric feedback. in this paper we present the meeting mediator (mm), a real-time, personal, and portable system providing feedback to enhance group collaboration. social interactions are captured using sociometric badges [6] and are visualized on mobile phones to promote change in behavior. in a study on brainstorming and problem-solving meetings, mm had a significant effect on overlapping speaking time and interactivity level without distracting the subjects. our system encourages effective group dynamics that may lead to higher performance and satisfaction. we envision mm to be deployed in real-world organizations to improve interactions across various group collaboration contexts.
design, marketing, strategy: where does user research belong? in this interactive session, a panel of experts will discuss and debate an emerging and pressing issue: to have maximum impact on the user experience, how and where should a user research team be structured within a corporation whose business depends on the development of successful interactive products through cross-functional collaboration? this has significant implications for organizations such as user experience, marketing, design, strategy, and academic programs preparing students entering corporate environments.
implicit personalization of public environments using bluetooth. implicit and remote personalization of public environments is technically easily possible by using bluetooth technology. we present a concept to allow people to individually influence public content such as songs played in shopping malls, news displayed on big displays, and advertisements shown etc. based on the bluetooth functionality in their mobile. users define once their preferences and store them encoded in the bluetooth friendly name of their mobile phone. we describe the underlining idea, the implementation of the prototype "bluemusic" as well as the conducted online survey and the initial user trail. the results suggested that the participants are cautious regarding privacy issues but very interested in such implicit interaction possibilities with public environments.
using online communities to drive commercial product development. this paper demonstrates how human computer interaction (hci) practitioners utilize an online community to drive commercial product innovation, definition, and development. upper management's increased interest in user feedback suggests that this development strategy promotes the case for stronger human-centered design processes to be included in corporate strategic planning.
realfind: managing personal items in the physical world. while in recent years some effort has been put into helping users manage their personal information in their computers, little has been done to provide meaningful ways to organize and retrieve a user's personal physical objects. nowadays, technologies such as rfid tags can help bridge the gap between the real and electronic worlds. we propose that a tool that keeps track of the users' objects and seamlessly inter-relates information about them with other relevant autobiographical and contextual data, about the users and their activities, can help manage and retrieve both physical and electronic items in meaningful ways. we describe a prototype tool, realfind that allows this to take place in a synergistic and effective way. objects can be searched for based on their properties, but also by relating them to a wide range of contextual information stored on their computers.
if you build it, they will come ... if they can: pitfalls of releasing the same product globally. as companies based in the us launch more "web 2.0"-style products, the rest of the world may not be moving at the same speed. this presentation will reveal the pitfalls of building the same product for all audiences across many countries, especially when it comes to economic, environmental, technological, and cultural disparities. this illustrates the point that even if global users want to access new products, they may not always have the means.
future craft: how digital media is transforming product design. the open and collective traditions of the interaction community have created new opportunities for product designers to engage in the social issues around industrial production. this paper introduces future craft, a design methodology which applies emerging digital tools and processes to product design toward new objects that are socially and environmentally sustainable. we present the results of teaching the future craft curriculum at the mit media lab including principal themes of public, local and personal design, resources, assignments and student work. novel ethnographic methods are discussed with relevance to informing the design of physical products. we aim to create a dialogue around these themes for the product design and hci communities.
creativity interventions: physical-digital activities for promoting group creativity. arizona state university's arts, media, and engineering program is currently addressing the need to assess the growth of group creativity in trans-disciplinary collaboration. this paper describes our initial work in developing criteria and a framework for constructing creativity interventions, or activities designed for building, tracking and evaluating creative group behaviors in diverse communities of it practitioners.
exploring gestural mode of interaction with mobile phones. the study explores the users' perceptions to a novel interaction method with mobile phones. we study responses and reactions of participants towards gestures as a mode of input with the help of a low fidelity prototype of a camera mobile phone. the study uses an approach inspired by participatory design to gauge the acceptance of gestures as an interaction mode.
engaging the crowd: studies of audience-performer interaction. in this work-in-progress we explore audience behavior at large musical events and present our prototype, a "cheering meter" developed to aid voting at rap competitions. we report from use of the cheering meter at eight concerts and conclude by highlighting how augmented interaction can increase the sense of participation among the audience at large-scale performances.
hd touch: multi-touch and object sensing on a high definition lcd tv. in this paper, we describe our first prototype in implementing a robust and low-cost multi-touch and tangible system using a high definition lcd monitor. since our prototype utilizes an lcd, we discuss and compare the advantages that hd lcd monitors provide over projectors. secondly, we give an overview of the sensing data the system can detect, and what interaction techniques it enables. since our approach is scalable, we anticipate being able to implement multi-touch and tangible interactions on large high-definition lcd monitors in the future.
memorability of persuasive passwords. text passwords are the primary authentication method used for most online services. many online users select weak passwords. regrettably, most proposed methods of strengthening passwords compromise memorability. this paper explores a lightweight password creation mechanism's effect on password memorability. our system employs persuasive technology to assist users in creating stronger passwords. results show that our improvement scheme affected password memorability only for users who created secure passwords before the system applied its improvement. this result warns researchers to not alienate users who are already security-aware when trying to assist security-unaware users to behave more securely.
when the designer becomes the user: designing a system for therapists by becoming a therapist. in this paper, we present the design process for developing a technology to support therapists for children with autism. to learn about the domain for which we were designing, one researcher became trained as a therapist and worked as one part time for over 10 months. this case study outlines the process by which the researcher was trained, the ways in which it was helpful in the design and evaluation of a technology system, and the aspects of the experience that we feel led to a better and more successful design.
idea management in creative lives. this research explores how ideas occur in creative work and the strategies and tools used to represent and develop them. we describe the analysis of an open questionnaire survey of creative practitioners' use of devices to represent ideas and capture inspirational material. unconscious processes, novel experiences and time away from practice frequently provoke ideas. our analysis finds that ubiquitous devices are important to practitioners for making initial representations for personal use. paper and pen remains by far the most common device employed, however respondents perceived organisational advantages in new technology. representations are created as initial memory aids, platforms for development, or to share ideas. a single representation is rarely suitable for all these purposes.
hxi: research down under in distributed intense collaboration between teams. the australian hxi initiative led by csiro, dsto, and nicta investigates how the application of information and communication technology can help geographically distributed teams collaborate more effectively. the hxi initiative embraces not only the development of world-class scientific and industrial outcomes, but the development of human capital in this multi-disciplinary research field. in its first project, [braccetto], a team of engineers, computer scientists, and social scientists are collaborating on overarching research goals to explore the principles underlying distributed intense collaboration and to develop effective applications. we present our research challenges, the research platform, and a suite of experiments conducted during the first year of the [braccetto] project.
dogooder: fostering volunteer communities to serve the homeless. we developed an online system, dogooder, to foster volunteer social networks. through an extensive user-centered design process, including interviews and a literature review, we learned that people experiencing homelessness face a wide range of issues. most organizations helping the homeless depend heavily on volunteers to enhance their service capacity. one agency we studied was able to extend its budget by 30% as a result of volunteer labor. research shows that social relationships play a key role in galvanizing potential volunteers and motivating existing ones. dogooder connects volunteers with opportunities and service organizations, and builds a community of volunteers to encourage each other. preliminary usability testing indicates that dogooder will successfully help organizations to recruit, retain, and organize volunteers to meet the diverse needs of various populations facing homelessness.
free-sketch recognition: putting the chi in sketching. sketch recognition techniques have generally fallen into two camps. gesture-based techniques, such as those used by the palm pilot's graffiti, can provide high-accuracy, but require the user to learn a particular drawing style in order for shapes to be recognized. free-sketch recognition allows users to draw shapes as they would naturally, but most current techniques have low accuracies or require significant domain-level tweaking to make them usable. our goal is to recognize free-hand sketches with high accuracy by developing generalized techniques that work for a variety of domains, including design and education. this is a work-in-progress, but we have made significant advancements toward our over-arching goal.
user experience at google: focus on the user and all else will follow. this paper presents an overview of the user experience (ux) team at google. we focus on four aspects of working within google's product development organization: (1) a bottom-up 'ideas' culture, (2) a data-driven engineering approach, (3) a fast, highly iterative web development cycle, and (4) a global product perspective of designing for multiple countries. each aspect leads to challenges and opportunities for the ux team. we discuss these, and outline some of the methodological approaches we employ to deal with them, along with some examples of our work.
sonic interaction design: sound, information and experience. sonic interaction design (sid) is an emerging field that is positioned at the intersection of auditory display, ubiquitous computing, interaction design, and interactive arts. sid can be used to describe practice and inquiry into any of various roles that sound may play in the interaction loop between users and artifacts, services, or environments, in applications that range from the critical functionality of an alarm, to the artistic significance of a musical creation. this field is devoted to the privileged role the auditory channel can assume in exploiting the convergence of computing, communication, and interactive technologies. an over-emphasis on visual displays has constrained the development of interactive systems that are capable of making more appropriate use of the auditory modality. today the ubiquity of computing and communication resources allows us to think about sounds in a proactive way. this workshop puts a spotlight on such issues in the context of the emerging domain of sid.
preliminary evaluation of the audience-driven movie. in this paper we introduce an audience-driven theater experience, dim movie, in which audience participates in a pre-created cg movie as its roles, and report the subjective and physiological evaluations for the audience experience offered by dim movie. specifically, we present three different experiences to an audience-a traditional movie, its self-dim (sdim) version with the audience's participation, and its self-friend-dim (sfdim) version with co-participation of the audience and his friends. the evaluation results show that the dim movies (sdim and sfdim) elicit greater subjective sense of presence, engagement, and emotional reaction, and stronger physiological response (galvanic skin response, gsr) as compared with the traditional movie form; moreover, audiences show a phasic gsr increase responding to the appearance of their own or friends' cg characters on the movie screen.
eye-mouse coordination patterns on web search results pages. we analyzed the patterns of coordination between users' eye movements and mouse movements when scanning a web search results page, using data gathered from a study with 32 participants. we discovered 3 patterns of active mouse usage: following the eye vertically with the mouse, following the eye horizontally with the mouse, and using the mouse to mark a promising result.
bringing the target to the cursor: proxy targets for older adults. studies in the literature have proposed techniques to facilitate pointing in graphical user interfaces through the use of proxy targets. proxy targets effectively bring the target to the cursor, thereby reducing the distance that the cursor must travel. this paper describes a study which aims to provide an initial understanding of how older adults respond to proxy targets, and compares older with younger users. we found that users in both age groups adjusted to the proxy targets without difficulty, and there was no indication in the cursor trajectories that users were confused about which target, i.e. the original versus the proxy, was to be selected. in terms of times, preliminary results show that for younger users, proxies did not provide any benefits over direct selection, while for older users, times were increased with proxy targets. a full analysis of the movement times, error rates, throughput and subjective feedback is currently underway.
do knobs have character?: exploring diversity in users' inferences. physical controls are now ubiquitous in everyday interactions. empirical studies of physical interactions have traditionally been exploring instrumental aspects such as error rate and experienced workload. recently, affective aspects of physical interaction have attracted an increased interest. in this paper we further argue that physical controls might have a character. we describe an exploratory study that aimed at understanding whether individuals form character judgments of physical controls based on haptic information, and explored the diversity across individuals' inference processes.
making user engagement visible: a multimodal strategy for interactive media experience research. this paper describes an industry-academic collaborative research initiative, focused on determining useful measures of user engagement and experience with social media (e.g., video games, virtual worlds, social networking sites, etc.) and digital devices. using newly designed hardware and software, the research initiative addresses the relationships among neurological, physiological, behavioral, and cognitive assessments of engagement in ongoing and short duration user experiences. it is a centerpiece of an iterative strategy toward understanding and modeling relationships among different engagement measures. the research will lead to design proposals for model-based assessments of engagement calibrated to individuals' responses.
an evaluation scheme for hierarchical information browsing structures. there is no widely accepted means of evaluating category systems for information search and browsing. this presentation outlines an evaluation scheme and an evaluation method that applies the scheme. the scheme delineates features broadly classified under comprehensiveness, coherence, and correctness. the method evaluates the category system through a survey distributed among subject domain experts. the method requires minimal resources, is easily conducted remotely, and is easily modified. the approach finds the over- and under-sensitivities of the method of generating the system. a case study has demonstrated the usefulness of the approach, and the inter-rater reliability found suggests that the evaluation scheme is meaningful.
exertion interfaces. exertion as an interface for computing technology has generated increased attention recently due to the belief that it can address health issues such as obesity, contribute to social benefits, and open new markets for entertainment industries. we are proposing a workshop on this topic to bring researchers and industry participants from related areas together to strengthen the scientific influence on this field and promote a multidisciplinary agenda. the workshop will support the development of future collaborative efforts in this rapidly growing area.
personal inventories: toward durable human-product relationships. in this paper, i build on perspectives in human-computer interaction (hci) and design literature to develop a theoretical lens to conduct personal inventories of human-product relationships within the home. i describe an ongoing empirical study examining participants' attitudes toward and relationships with interactive technology, and frame this research within the nascent and growing literature in hci on environmental sustainability. i will present early findings from this study and discuss how these implications can inform potential future design practice within the hci community.
surrounded by ambient persuasion. this workshop will discuss the implications of the use of ambient intelligence (ami) for persuasion. ami allows surrounding the user with persuasive technology in their everyday life, giving the possibility for persuasive interventions just at the right time and in the right place. the workshop will focus on the potential of ambient persuasion for applications in the area of sustainability, health and well-being and related areas. it will also address the need for theoretical foundations and frameworks on which to ground such applications. the use of ami for persuasion also raises a number of ethical and privacy questions. these issues play an important part in the overall user experience of persuasive ami applications, where a special focus of this workshop lies.
collaboration-oriented design of disaster response system. it is of the utmost importance, we argue, to specifically tailor disaster response systems with users' collaboration in mind. such an approach, building on top of, and extending the classic single- and multi-user human-computer interaction paradigm is described in this paper. in what follows, we outline our evacuation support system for walking wounded. the proposed system follows a user-centered design method, coupled with navigationally relevant aspects of human cognition and exemplifies our collaboration-oriented design.
icandy: a tangible user interface for itunes. for more than half a century, musicians used artwork as a way of visually describing the contents of an album. 'cover art' attracts attention, reminds the listener of the contents, and when printed on the album cover, provides a tangible representation of the music that's easily used for organization and sharing. over the past few decades, the benefits of the physical album 'package' were lost as it changed from a 12" vinyl album to an electronic file and thumbnail image downloaded from an online music store. in this demonstration we present a tangible user interface called icandy that restores the benefits of physical albums for the electronic music in the itunes multimedia application and provides a method for easy access to recorded media. the system also includes several desktop visualizations that enhance the overall experience especially when dealing with large collections of music and video.
enroll me!: a portable device to facilitate homeless student enrollment. we are designing an information transfer device to expedite the enrollment of homeless children to schools. homeless children change schools often, seriously disrupting their educational experience. our design uses existing, familiar technology to unobtrusively facilitate the enrollment process for both the school staff and the homeless parents.
bridging gaps: affective communication in long distance relationships. this study examines communication methods and needs of people in long distance romantic relationships to understand how intimate computing can help create or augment already existing artifacts to promote feeling of connectivity within non-collocated couples. we report our research in progress and provide a collection of initial design concepts based on the user research.
nightmarket workshops: art & science in action. during the past three years in taiwan, we organized a series of nightmarket workshops to investigate taiwanese sociocultural phenomena, and to provide cross-disciplinary environments for college students and practitioners to create interactive art pieces. in this process, we were intrigued by how the collaboration of art and science in the context of the nightmarket can deeply engage people in participatory ways of designing, demonstrating, and exhibiting. we present a 10-minute documentary film to illustrate the experience in which we see art and science in action.
usable artificial intelligence. "the ai and hci communities have often been characterized as having opposing views of how humans and computers should interact" observes winograd in "shifting viewpoints". reconciling these views requires a thoughtful balancing of assistance and control, of mental and system representations, and of abstract process and contextualized workflow. this workshop examines the gap between hci and artificial intelligence, with the goal of improving usability of ai systems.
design for creating, uploading and sharing user generated content. the power of users playing the roles of authors and editors is undeniable these days [1]. new media, not only the internet, are enabling people to become active users related to content production and sharing, and in co-creation of user generated content (ugc). in particular younger users and heavy users of internet use networked applications to create and share content [1]. there is a need for ugc applications targeting a broader market, including older users and average internet users. today, the knowledge in designing and building for co-creation in networked media is still rather weak. the lack of information about ugc characteristics makes it difficult to expect what kind and amount of content will be produced, and to understand and interpret the reasons why users and user communities arise or fail. a significant effort is currently made by the hci community in order to support active user involvement into the design and evaluation of networked applications [6]. non-professional users are encouraged to become active producers and designers themselves [1]. however, there is still the need to explore how to apply and further extend these approaches and methods to better understand, design for and evaluate ugc applications. this sig will contribute to this discussion by actively involving the audience in ugc creation.
a novel interface to present emotional tactile sensation to a palm using air pressure. we propose a new tactile interface to present various types of tactile sensation, especially a feeling of "softness". a user holds our interface, containing two speakers, with both hands while the speakers vibrate air between the speakers and palms. the user feels suctioning and pushing sensations to the palms due to the air pressure. by changing the frequency of vibration, the user experiences not only normal vibration but also "soft" feelings like that of liquid, spring-like objects, and living matter.
taking up the mop: identifying future wikipedia administrators. as wikipedia grows, so do the messy byproducts of collaboration. backlogs of administrative work are increasing, suggesting the need for more users with privileged admin status. this paper presents a model of editors who have successfully passed the peer review process to become admins. the lightweight model is based on behavioral metadata and comments, and does not require any page text. it demonstrates that the wikipedia community has shifted in the last two years to prioritizing policymaking and organization experience over simple article-level coordination, and mere edit count does not lead to adminship. the model can be applied as an "adminfinderbot" to automatically search all editors' histories and pick out likely future admins, as a self-evaluation tool, or as a dashboard of relevant statistics for voters evaluating admin candidates.
mind your p's and q's: when politeness helps and hurts in online communities. little is known about the impact of politeness in online communities. this project combines deductive and inductive approaches to automatically model linguistic politeness in online discussion groups and determine the impact of politeness on desired outcomes, such as getting people to reply to one another. we find that politeness triples reply rates in some technical groups, but rudeness is more effective in others. the model can be applied as a "politeness checker" to encourage people to write in ways likely to garner a response from specific communities.
user interface history. user interfaces have been around as long as computers have existed, even well before the field of human-computer interaction was established. over the years, some papers on the history of human-computer interaction and user interfaces have appeared, primarily focusing on the graphical interface era and early visionaries such as bush, engelbart and kay. with the user interface being a decisive factor in the proliferation of computers in society and since it has become a cultural phenomenon, it is time to paint a more comprehensive picture of its history. this sig will investigate the possibilities of launching a concerted effort towards creating a history of user interfaces.
lessons learned from a pilot study quantifying face contact and skin conductance in teens with asperger syndrome. this paper presents lessons learned from a preliminary study quantifying face contact and corresponding physiological reactivity in teenagers with asperger syndrome. in order to detect face contact and physiological arousability, we created a wearable system that combines a camera with opencv face detection and skin conductance sensors. in this paper, we discuss issues involved in setting up experimental environments for wearable platforms to detect face contact and skin conductance levels simultaneously, and address technological, statistical, and ethical considerations for future technological interventions.
communication patterns and usability problem finding in cross-cultural thinking aloud usability testing. communication plays an important role for the evaluator to find accurate usability problems in formative thinking aloud usability testing in the industrial area. this study investigates the communication patterns of evaluators in cross-cultural usability testing, and the influence on usability problem finding by doing experiments with danish users and chinese users. the purpose of this research is to propose effective communication patterns for evaluators to do usability tests with western and east asian users.
weaving memories into handcrafted artifacts with spyn. handcrafted objects, such as knit scarves or sweaters, subtly signify the time and skill involved in their creation. yet a handcraft artifact itself cannot convey the experience of its creation. we present the design, implementation, and preliminary evaluation of spyn, a system for knitters to virtually weave stories into their creations. using spyn, a knitter can record, playback and share information involved in the creation of hand-knit products. spyn uses patterns of infrared ink printed on yarn in combination with computer vision techniques to correlate locations in knit fabric with events recorded during the knitting process. using spyn, knitters can capture their activities as audio, image, video, and spatio-temporal data. when users photograph the knit material, the spyn system analyzes the ink patterns on the material and visualizes events over the photograph of the knit. in the design of spyn, we investigate the role that technology can play in preserving and sharing the handcraft process over space and time.
gamelunch: forging a dining experience through sound. the gamelunch is a sonically augmented dining table. by means of the gamelunch, we aim at investigating the closed loop between interaction, sound and emotion by exploiting the power and flexibility of physically-based sound models for an effective and coherent process of interactive sound design. continuous interaction gestures are captured by means of various force transducers, providing data that are coherently mapped onto physically-based sound synthesis algorithms. investigation of the above mentioned loop is carried out by the principle of contradiction: while performing usual dining actions, such as cutting and slicing, dressing the salad, pouring beverages, the user encounters contradicting and unexpected sound feedbacks, thus experiencing -- per absurdum -- the importance of environmental sounds in everyday-life acts.
challenges in computerized job search for the developing world. we examine the broad challenges facing a computer-based system to help match low-income domestic workers from an urban slum with potential middle-class employers in bangalore, india. due to the near impossibility of implementing such a system in one shot, we first implemented a paper-based system that provides the intended functionality but without a computer. this system proved a significant challenge in itself, and among the lessons learned are the crucial role of human intermediaries (necessary even in the final computer-based system), the importance of building skills among the domestic workers, the need for a strong value proposition for both employers and employees well above existing systems, and the requirement of technological literacy. we then show that these lessons are applicable to other scenarios where computing technology is applied to developing-world challenges, by analyzing corresponding issues in related work. \ \ our broad conclusion is that computer-based systems to solve developing-world problems often require significant work above and beyond an implementation of the technology, with trustworthy human intermediaries playing a critical role. \
mashups: who? what? why? in recent years major web services have opened their systems to outside use through the implementation of public apis. as a result, web developers have begun to experiment with mashups - software applications that merge separate apis and data sources into one integrated interface. because the apis and data sources are publicly available, in principle anyone can create a mashup. however, because relatively advanced programming languages are required to integrate these apis, creating a mashup still requires considerable programming expertise. in this paper we share the results of an exploratory study of web developers and their experiences with building mashups. we profile the characteristics of mashup developers, examine the mashups they create, and the reasons they create mashups. from the results of this initial survey we outline a course for future research.
backchan.nl: integrating backchannels with physical space. in this paper, we describe backchan.nl, a web based backchannel system that focuses on managing questions for presenters by allowing audience members propose and vote on other people's questions. top rated questions are projected in the presentation space so audience members, moderators, and panelists can see them. we discuss the results of deploying this system at a conference and relate those results to the particular design of our system, demonstrating how backchannel systems can be more than just shared chat rooms.
eyepass - eye-stroke authentication for public terminals. authentication on public terminals e.g. on atms and ticket vending machines is a common practice. due to the weaknesses of the traditional authentication approaches pin and password, it is possible that other people gain access to the authentication information and thus to the users' personal data. this is mainly due to the physical interaction with the terminals, which enables various manipulations on these devices. in this paper, we present eyepass, an authentication mechanism based on passshape and eye-gestures that has been created to overcome these problems by eliminating the physical connection to the terminals. eyepass additionally assists the users by providing easy-to-remember passshapes instead of pins or passwords. we present the concept, the prototype and the first evaluations performed. additionally, the future work on the evaluation is outlined and expected results are discussed.
now let's do it in practice: user experience evaluation methods in product development. as the selection of products and services becomes profuse in the technology market, it is often the delighting user experience (ux) that differentiates a successful product from the competitors. product development is no longer about implementing features and testing their usability, but understanding users' daily lives and evaluating if a product resonates with the in-depth user needs. although ux is a widely adopted term in industry, the tools for evaluating ux in product development are still inadequate. based on industrial case studies and the latest research on ux evaluation, this workshop forms a model for aligning the used ux evaluation methods to product development processes. the results can be used to advance the state of "putting ux evaluation into practice".
social resonance: balancing reputation with tangible design. new forms of tangible systems can be designed to leverage the strengths, and bridge the discrepancies, of reputation systems. this paper presents the ongoing design of a tangible reputation system, social resonance, that uses a wearable device to merge face-to-face interaction with online networking. like its virtual counterparts, this system aims to make explicit the perspective of anonymous actors. yet unlike online reputations, this system is negotiated through real-world action and signals. we present an overview of the system, including potential opportunities and related work, and conclude with future steps for analysis.
facet folders: flexible filter hierarchies with faceted metadata. facet folders are a visualization and interaction concept for filtering collections of personal data. although visually derived from the ubiquitous folder hierarchies of file managers, facet folders explicitly expose the faceted metadata used for filtering. facet folders can be arranged into persistent hierarchies, enabling the construction of dynamically updating views across multiple facets. if demands change, the hierarchy can be easily rearranged.
finding a balance: social support v. privacy during weight-management. this work investigates current attitudes towards the involvement of others during weight-management (wm). it is prompted by ongoing attempts to harness social influence within system design so as to promote an increase in physical activity, with obesity often cited as a motivation. through in-depth interviews, we have found that the complexities of sharing information in existing wm practices are not reflected in current system designs. initial findings highlight the design tension raised by the need for social support as well as privacy. preliminary design concepts of selective disclosure and relative comparison are offered to developers of sociocentric systems supporting wm-specific behavioural change.
a study on a flight display using retro-reflective projection technology and a propeller. the head up display (hud) is becoming increasingly common in the aerospace field because it has many benefits such as enabling operations in poor visibility and improving flight safety. the hud is a kind of augmented reality display that enables a pilot to observe the scene outside the cockpit while simultaneously viewing an artificial image of flight information. however, the hud is too expensive and heavy for light airplanes. in this paper, we propose a new method to combine real and artificial images using retro-reflective projection technology and rotating objects, and we apply the method to an airplane with a single propeller to compose a simple hud. in this report, we also describe the developed system and preliminary experimental results.
the associative pda 2.0. in this paper i describe the associative pda 2.0, a mobile system for personal information management (pim), based on an associative information network. in addition to associate items manually, context information is used for defining associations and thereby indexing data automatically. the design is limited to note-taking, allowing a representative example of a pim application. i conducted initial interviews to receive background information about note-taking. the system will be evolved following a user centered design. it will be evaluated in a long-term study with authentic personal information to verify the design and usefulness.
pointing with fingers, hands and arms for wearable computing. pointing is a fundamental enabling operation for human-computer interaction across a broad spectrum of scenarios. the paper presents a study exploring how to develop a pointing system for truly wearable, rather than hand-held, computing. it describes a fitts' law study of pointing based on motions in free-space captured using an inertial sensor pack. it compares performance when the pack is held in the hand, mounted on the back of the hand and finally on the wrist. the results show a significant, but numerically small, advantage in using the hands over using the upper arm only. this suggests that for wearable tasks where pointing is relatively infrequent a wrist based sensor pack may well be sufficient to enable effective and usable interaction.
verbal associations to tactile patterns: a step towards textured legends in multimodal maps. in this paper we present a pilot study designed to investigate how tactile patterns are spontaneously interpreted by subjects. participants were confronted to a sample of 40 tactile patterns. the results show strong correlations in the way subjects spontaneously associate verbal description to a clearly identified set of patterns. in terms of application, the study aimed to provide empirical evidence that can support the selection of appropriate tactile patterns in multimodal maps for blind or visually impaired users.
vocal interaction. vocal interaction research has slowly been gaining popularity in the mainstream hci, assistive technology, arts and game development communities. one main reason for the uptake of this interaction style is the potential of exploiting one of the most natural means of expression: human vocalizations, speech, and vocal gestures. this sig meeting has three purposes: to communicate the results of the chi 2007 workshop on vocal interaction to interested chi attendees; to sketch a research agenda on the topic of the emerging interaction styles in the context of vocal interaction and its implications for the design of interactive systems; and to bring together the communities of researchers and practitioners who are addressing this topic.
social networking 2.0. in this paper we describe the development of a platform that enables us to systematically study online social networks alongside their real-world counterparts. our system, entitled cityware, merges users' online social data, made available through facebook, with mobility traces captured via bluetooth scanning. furthermore, our system is constantly growing, since it enables users to contribute their own mobility traces. in addition to describing cityware's architecture, we discuss the type of data we are collecting, and the analyses we intend to carry out.
evaluating user experiences in games. null
urban mixed realities: technologies, theories and frontiers. this workshop will address the approaches, challenges, benefits and aspects of interaction within urban mixed reality environments. it will seek to draw upon existing research into place, presence and situated interaction while exploring areas of art, flow, ambience, urban design, performance and technology. in doing so, it will bridge the divide between art and science which exists in the growing research area of urban mixed realities. the anticipated outcome is a closer examination of the issues relevant to interacting within urban mixed realities and how to drive the research agenda forward.
studying paper use to inform the design of personal and portable technology. this paper introduces design guidelines for new technology that leverage our understanding of traditional interactions with bound paper in the form of books and notebooks. existing, physical interactions with books have evolved over hundreds of years, providing a rich history that we can use to inform our design of new computing technologies. in this paper, we initially survey existing paper technology and summarize previous historical and anthropological analyses of people's interactions with bound paper. we then present our development of three design principles for personal and portable technologies based on these analyses. for each design guideline, we describe a design scenario illustrating these principles in action.
there's always one!: modelling outlying user performance. informal analysis of many usability tests suggests that there is regularly one participant that is substantially slower than all the others. moreover, such outliers are more extreme and more frequent than would be predicted by a normal distribution. we propose using a rational model to explain the outliers and the work described here begins to parameterise the model based on empirical data to provide accurate analyses of user performance. this prediction appears to be correct and the model begins to reflect the outlying performance. moreover, by using an executable model, we believe that it could be used in future as an analytical tool to help designers improve usability for those users who are struggling the most.
interpersonal interruptibility: a framework and research program. to date, research exploring interpersonal technology-mediated interruptions has focused on understanding how knowledge of an "interruptee's-local-context" can be utilized to reduce unwanted intrusions. however, the value of everyday interruptions are strongly tied to interrupter-interruptee relationships, interrupter's context and interruption content that we refer to as the 'relational context'. this suggests that a fresh approach to interruptibility research is needed that focuses on understanding how the knowledge of this relational context can be used to improve interruption management decisions. to address this concern a theoretical framework and associated research program are presented. the validity of fundamental aspects of this framework is then demonstrated through a study of cell phone call handling decisions. it shows that "who" is calling is used most of the time (87.4%) by individuals to make call handling decisions (n=834) unlike the interruptee's current local social (34.9%) or cognitive (43%) contexts. in addition, a clear disconnect was shown between the influence of local interrupee-context and relational context in terms of call handling decisions, suggesting that interruption management systems that focus only on an interruptee's-local-context will be ineffective. an alternative design approach is described to address these short comings.
sharing the squid: tangible workplace collaboration. effective communication is central in building trust and negotiating differences in diverse, multidisciplinary working environments. in this paper we discuss a tangible mediated environment designed to facilitate positive social interaction between colleagues in a research workplace. through our multi-user tangible interface in the form of a plush squid, participants can share media resources and collaborate in a playful and inviting setting. results from preliminary studies indicate that playful mediated work environments stimulate constructive discourse, strengthen social bonds, and enhance creative output.
human, organizational, and technological factors of it security. this paper describes the hot admin research project, which is investigating the human, organizational, and technological factors of it security from the perspective of security practitioners. we use qualitative methods to examine their experiences along several themes including: unique characteristics of this population, the challenges they face within the organization, their activities, their collaborative interactions with other stakeholders, the sub-optimal situations they face as a result of distributed security management, and the impact of the security management model in place. we present preliminary results for each theme, as well as the implications of these results on the field of usable security and other research areas within hci.
contact-and-connect: designing new pairing interface for short distance wireless devices. to solve the problem of the current pairing method of wireless devices with button interface, this paper suggests a new way of pairing wireless devices in short distance with which it requires physically contacting them together, which we call contact-and-connect interface. through prototyping, we examined the usability of this new interface, and as a result, we realized that all of the participants recognized the pairing easily due to the following three factors: contact action, led visualization of connection, and instant feedback of what is happening. we also figured out which external forms have better affordance for the contact action, and the ones having no sharp edges with a perfect fit worked best.
measuring users' emotional reactions to websites. initial research to investigate users' emotional reactions to websites is presented. an emotion words priming list (ewpl) was developed for uk english speakers and used to prompt users in an evaluation of 6 websites. only half the words on the ewpl v1 were amongst the most frequently used emotion words in the retrospective verbal protocols. however a list of 16 emotion words emerged from this study that constitute version 2 of the ewpl, to be validated in a future study.
collaborative editing of micro-tags. this paper introduces the insight system, which was designed to explore two new concepts in social tagging. in this system, we introduce the concept of community-editable tags, a methodology that allows a community of users to edit, modify and delete tags of each other. the goal is to improve the quality of tags, and to reduce the proliferation of incorrect or incomplete tags often found in social networking systems. we also explore the concept of "micro-tagging," which has begun to appear in web-based applications. in "micro-tagging," the user attaches a tag to a subset of large media, such as a segment in a video or a region of an image. insight allows users to create and edit video micro-tags. users can mark specific time intervals within a video, and specific spatial locations within video frames, and these tags can be edited by subsequent users. we also present an empirical study which demonstrates an improvement in factual tag quality when the community of users is allowed to edit and delete each others' tags. these results provide a first step in demonstrating how refining tags would make them more valuable for search.
exploring the cognitive consequences of social search. to what extent can social interactions augment people's natural search experiences? what factors influence the decision to turn to a friend for help? our paper presents the preliminary results of a social sensemaking task that begin to address such questions by examining the cognitive consequences of social search.
implementing emotion-based user-aware e-learning. we propose an intelligent e-learning system featuring with affective agent tutor. the agent tutor "alice" is not only fully aware of the affective state of the students through facial expression, speech and text, but also fully capable of adapting to these states wisely guided by a case-based method with facial expression generation and emotional speech synthesis ability.
when one-arm bandits go digital: designing a casino back-end system. frog design collaborated with a gaming machine manufacturer to design a back-end system to address the needs of casino floor managers. as casinos migrate to server-based slot machines, they also need to transform their back-end systems. the frog team conducted user research and designed a new system of floor management software. our design helped optimize the experience of casino workers, pushed the brand envelop of the gaming provider within their industry, and won a productivity award from global gaming expo in 2007.
talkative cushion: a phatic audio device to support family communication. the 'talkative cushion' is a novel audio recorder which transforms recorded voices into humorous and ludicrous sounds. it is proposed as a phatic device for homes. it is designed to make people playful and funny when communicating in homes because a delightful situation makes people active to talk. in this paper, we describe why and how a cushion is selected as our target object and how the concept of phatic technologies applied to the cushion.
asynchronous gameplay in pervasive multiplayer mobile games. one of the interesting features in pervasive multiplayer games is that gaming can be blended into other daily activities. however, the players' current context creates challenges for this parallel activity and therefore, the game design should enable the players to participate in the game whenever it is suitable for them. in this paper, we present initial results from a study which explored one game design solution for this challenge, namely asynchronous gameplay. we wanted to find out how asynchronous gameplay was used and what the players' attitudes were towards this new playing style. the results indicate that the players received asynchronous gameplay positively and that asynchronous gameplay does not diminish the player's opportunities for winning the game.
dinnerware: why playing with food should be encouraged. dinnerware is an exploration of eating as a medium for computation and aesthetic expression. it consists of a dining service electronically equipped to react to the properties of the food that it holds and respond to a user's eating gestures.
file management with hierarchical folders and tags. hierarchical folders have been widely used for managing digital files. previous research has revealed problems with them. users frequently have to turn to desktop search to re-find files, even if they thought they had saved them in a memorable place. tagging may have the potential to improve information navigation and organization. this research in progress aims at exploring the possibility of incorporating tagging into the hierarchical folder structure for file management, especially for the process of file organization and file re-finding. this work will provide design implications for future file management tools.
api usability: chi'2009 special interest group meeting. programmers of all types from novice end-user developers to professional software engineers make use of application programming interfaces (api) within their various designs. and, while the use of these interfaces is ubiquitous, there is little research about their design. recently, a number of researchers and practitioners have begun to treat api design as a first-order object of study and practice. the purpose of this special interest group meeting is to bring together the community of usability researchers and professionals interested in api usability. the time will be used to discuss attendees' ideas and opinions in order to stimulate this new and exciting emerging field that crosses the boundaries between human-computer interaction and software engineering.
origami simulator: a multi-touch experience. we present a 3d origami simulator with multi-touch interaction. this is a preliminary exploration of manipulating 3d models with multi-touch. following a user centered approach, we analyzed how people make paper origami models and mapped the common actions into two-touch gestures. the user study suggested that people enjoyed the simulator and think the techniques can be applied to other 3d modeling environments.
why we cannot work without paper even in a computerized work environment. as work environment becomes more computerized, it has been long expected that the computer will substitute for paper. however, in fact, this expectation has strayed. paper is still around in the work environment; moreover, computers and papers are used in conjunction with each other. in this study, we suggest the term "human-computer-paper interaction" considering these phenomena. using contextual inquiry and lab-based user study, we explored the switchover in human-computer-paper interaction and determined what incites this interaction. through this study, we attempted to provide considerable insights into the hci design area.
dancing with myself: the interactive visual canon platform. the canon is a composition pattern with a long history and many forms. the concept of the canon has also been applied to experimental film making and on japanese television. we describe our interactive visual canon platform (ivcp) that enables creators of visual canons to design their movements through rapid cycles of performance and evaluation. the ivcp system provides real time support for the actors; they can see the canon resulting from their movements while they are still performing. we describe some possible approaches to a solution, and reasons for choosing the approach that we have implemented. the hardware has reached a stable state, but we are still optimizing the visual processing of the system. a first user test is planned to provide us with information for improving the system.
wearable eog goggles: eye-based interaction in everyday environments. in this paper, we present an embedded eye tracker for context-awareness and eye-based human-computer interaction - the wearable eog goggles. in contrast to common systems using video, this unobtrusive device relies on electrooculography (eog). it consists of goggles with dry electrodes integrated into the frame and a small pocket-worn component with a powerful microcontroller for eog signal processing. using this lightweight system, sequences of eye movements, so-called eye gestures, can be efficiently recognised from eog signals in real-time for hci purposes. the device is self-contained solution and allows for seamless eye motion sensing, context-recognition and eye-based interaction in everyday environments.
an objective and subjective evaluation of an autostereoscopic 3d display. an autostereoscopic 3d display is evaluated to objective and subjective evaluations. the results confirm that the spatial image reconstruction provided by the 3d display can transfer more information than the standard flat image. this suggests the possibility of eliminating the current limitations imposed by display size and resolution.
shapewriter on the iphone: from the laboratory to the real world. we present our experience in bringing shapewriter, a novel hci research product, from the laboratory to real world users through iphone's app store.
multi-user interaction in virtual audio spaces. audio guides are a common way to provide museum visitors with an opportunity for personalized, self-paced information retrieval. however, this personalization conflicts with some of the reasons many people go to museums, i.e., to socialize, to be with friends, and to discuss the exhibit as they experience it [1]. we developed an interactive museum experience based on audio augmented reality that lets the visitor interact with a virtual spatial audio soundscape. in this paper, we present some new interaction metaphors we use in the design of this audio space, as well as some techniques to generate a group experience within audio spaces.
towards a sensible integration of paper-based tangible user interfaces into creative work processes. we live in a hybrid world where standard computers with graphical user interfaces (guis) have become an integral part of our daily life. additionally, novel user interfaces like tangible user interfaces (tuis) are among emerging interaction styles that offer new potential as tools for supporting creative tasks and weak-structured workflows. in order to meet the users' needs, the most suitable user interface for a task should be chosen and different kinds of user interfaces have to be integrated appropriately. we addressed these topics and applied a generative framework to structure and analyze a creative work process in the domain of art history. on this basis, we designed the integration of tui and gui elements and constructed as well as tested a tabletop tui to support creative work.
disembodied performance. early in tod machover's opera death and the powers, the main character, simon powers, is subsumed into a technological environment of his own creation. the theatrical set comes alive in the form of robotic, visual, and sonic elements that allow the actor to extend his range and influence across the stage in unique and dynamic ways. this environment must compellingly assume the behavior and expression of the absent simon. in order to distill the essence of this character, we recover performance parameters in real time from physiological sensors, voice, and vision systems. these gesture and performance parameters are then mapped to a visual language that incorporates cognitive and semantic models informed by modal relationships. this language allows the off-stage actor to express emotion and interact with others on stage. our disembodied performance system takes a new direction in augmented performance by employing a non-representational abstraction of a human presence that fully translates a character into an environment.
to answer or not to answer: that is the question for cell phone users. people are constantly making decisions to answer or ignore cell phone calls based on inferences derived from partial information about the incoming call. to gain an understanding of this information deficit we conducted a survey study of cell phone call handling practices. the results highlight the type and extent of information desired about incoming cell phone calls. it also shows that desired information is largely unknown and often misattributed by the receiver. our findings can be used by designers to prioritize the presentation of additional types of call related information on cell phone displays, and in so doing, empower users to make informed call handling decisions.
growing up programming: democratizing the creation of dynamic, interactive media. young people interact with games, animations, and simulations all of the time. but few of them are able to create interactive media. the obstacle: traditional programming languages are too difficult to learn and understand. this panel brings together a group of researchers, developers, and educators who are aiming to democratize the activity of programming. they are developing a new generation of programming environments that enable children and teens to create their own interactive games, stories, animations, and simulations. panelists will discuss and critique their programming environments, then set up interactive demonstration stations for focused exploration and small-group discussion. audience members will also have the opportunity to download the environments onto their own laptops, so that they can experiment in greater depth.
experimenting with an organic metaphor and hypervisual links for the interface of a video collection. in this paper we describe the prototype of an archive of short movies. the project proposes two original solutions for implementing the interface of this archive: an organic metaphor and a hypervisual navigation mechanism.
gaze-augmented manual interaction. this project will demonstrate a new approach to employing users' gaze in the context of human-computer interaction. this new approach uses gaze passively in order to improve the speed and precision of manually controlled pointing techniques. designing such gazeaugmented manual techniques requires an understanding of the principles that govern the coordination of hand and eye. this coordination is influenced by situational parameters (task complexity, input device used, etc.), which this project will explore in controlled experiments.
analyzing collaborative learning activities in wikis using social network analysis. this paper investigates the potential of existing methods for analyzing collaboration in wiki environments. after a short description of the motivation for this research paper a presentation of analysis methods in cscl will be given, including a special focus on social network analysis. the next section points out the main characteristics of wikis and their differences compared to other cscl tools. in the following step, the methods for collaboration analysis are transferred to wiki contexts. the paper concludes with open issues and an outlook on future research on this topic area.
cropconnect: enabling community supported agriculture. this research describes a user-centered design effort to facilitate community supported agriculture programs. this process resulted in a paper prototype of a web-based system that connects a diverse user group more efficiently and robustly than at present. the prototype was evaluated by several stakeholders who were able to successfully accomplish their tasks.
expressive typing: a new way to sense typing pressure and its applications. in this paper, we propose a new way for measuring key typing pressure when using off-the-shelf laptop computers. accelerometers embedded in laptop computers to protect hard discs from sudden motion are becoming very common. this paper explores the concept of utilizing this accelerometer for sensing non-verbal aspects of key typing, such as key typing pressure. this possibility enables a wide variety of pressure-sensitive user interfaces through the use of software without requiring any additional hardware/sensors. such software can be distributed easily to a substantial number of potential users. to confirm the feasibility of this idea, we compared typing finger velocities (obtained by high-speed camera images) with sensor data from an accelerometer embedded in a laptop computer. we then confirmed that there is a clear correlation between these two sets of data. we also investigated differences in typing pressure patterns among different users. by combining keystroke speeds and typing pressure, we found it is possible to distinguish among users. this feature can be used for security purposes such as preventing a laptop computer from being used by non-owners. we also present possible application ideas such as rich text expression, new types of user interface elements, and authentication.
low-cost gaze pointing and emg clicking. some severely disabled people are excluded from using gaze interaction because gaze trackers are usually expensive (above $10.000). in this paper we present a low-cost gaze pointer, which we have tested in combination with a desktop monitor and a wearable display. it is not as accurate as commercial gaze trackers, and walking while pointing with gaze on a wearable display turned out to be particularly difficult. however, in front of a desktop monitor it is precise enough to support communication. supplemented with a commercial emg switch it offers a complete hands-free, gaze-and-click control for less than $200.
photo khipu: organizing a public record of social transaction. traditional photo albums are important not only for storing and organizing photographs but also for their ability to display photos in an aesthetically pleasing manner. a beautiful photo album augments the browsing experience for individual recollection or sharing with others. we present a digital photo album that organizes and displays photos in a form based on an ancient accounting device, the incan khipu. the khipu metaphor provides an overview of the photos in a collection and a historical record of individual albums. this interface is meant to be an evocative and functional interactive display in the home for visitors and occupants alike.
adaptive pointing: implicit gain adaptation for absolute pointing devices. we present adaptive pointing, a novel approach to addressing the common problem of accuracy when using absolute pointing devices for distant interaction. the intention behind this approach is to improve pointing performance for absolute input devices by implicitly adapting the control-display gain to the current user's needs without violating users' mental model of absolute-device operation. first evaluation results show that adaptive pointing leads to a significant improvement compared with absolute pointing in terms of movement time (19%), error rate (63%), and user satisfaction.
spatio-temporal interest points for video analysis. in this paper, we discuss the need for an effective representation of video data to aid analysis of large datasets of video clips and describe a prototype developed to explore the use of spatio-temporal interest points for action recognition. our focus is on ways that computation can assist analysis.
home, work, (play). the first two segments of a three part series, these shorts were developed for microsoft volume studios. designed as purely inspirational pieces, to explore in a poetic narrative way how certain developing technologies could begin to blend and augment our daily lives.
displayobjects: functional prototyping on real objects. this video introduces displayobjects, a rapid prototyping workbench that allows functional displays to be projected on real 3d physical prototypes. displayobjects uses a vicon motion capture system to track the location of physical models. 3d software renditions of the 3d physical model are then texture-mapped with interactive behavior and projected back onto the physical model to allow real-time interactions with the object. this simulates the functionality of future 3d interactive oled display skins for product designs. we show a selection of interaction techniques used to design a number of displayobjects.
usable intelligent interactive systems: chi 2009 special interest group meeting. the ai and hci communities have often been characterized as having opposing views of how humans and computers should interact" observes winograd in shifting viewpoints. it is time to narrow this gap. what was once considered the forefront of artificial intelligence (ai) research can now be found in commercial products. while some have failed, others, such as face detection in digital cameras or product recommendation systems, have become so mainstream they are no longer thought of as artificial intelligence. this special interest group provides a forum to examine the apparent gap between hci and ai communities, to explore how intelligent technologies can enable novel interaction with computation, and to investigate the challenges associated with understanding human abilities, limitations, and preferences in order to drive the design of intelligent interactive systems.
visualizing remote voice conversations. online voice conversations are becoming ever more popular. people have been logging online text conversations, but what about voice conversations? walter ong simply states, "written words are residue. oral tradition has no such residue or deposit" [6]. however, we do not just want to archive conversations, we want to enable users to have some meaning in these "logs". we introduce a project that takes a remote conversation and visualizes it. it does so in a way that takes volume, pitch and content into account. with this information, the visualizations display the data in a meaningful way. users can use these images in the future to review past conversations whether it is for nostalgia's sake or to recall some piece of information. in this paper, we describe the early design and iteration of system for archiving and creating artifacts from remote audio conversations.
using bookmark visualizations for self-reflection and navigation. web users have been employing numerous methods for recalling websites. bookmarks have been around for some time, but the usefulness of such a system has been under question. the lack of intuitive organization in web browsers forces users to make arbitrary choices on where to store bookmarks. as a result, bookmarks are often lost, never to be used again. these web pages a user bookmarks can say a lot about the user, though. a person's personality is reflected by the web pages a user visits and deems important enough to bookmark. by taking the user's bookmarks along with one's browser history and visualizing them, the user is able to notice things about oneself that he or she did not notice before. in this paper, we describe the iteration of a tool that visualizes all of user's bookmarks. we conclude with areas for future work.
perspective probe: many parts add up to a whole perspective. this case study describes a variation of cultural, technology, and other probes, called a "perspective probe." the perspective probe consisted of multiple activities that participants completed on their own and then discussed with the researcher. the participant's responses to the individual activities added up to their whole perspective. the probe's activities helped guide the conversation around a sensitive topic instead of asking directly about it. this paper illustrates how the perspective probe methodology was used to gather information for google finance. the focus is on the method rather than the particular findings from the study. the perspective probe methodology was useful in getting rich data from participants and building a holistic understanding of the participant's perspective on a difficult topic, in this case money and investing.
wiis: multimodal simulation for exploring the world beyond visual sense. this paper describes a pilot study of a computer simulation called wiis, which is designed to extend students' learning experience of the sizes of the objects beyond human vision. by interacting with a simulation that incorporates temporal, aural, and visual representation (tavr), students are expected to refine their mental model of the sizes of the objects too small to see with human eyes (called submacroscopic objects). the goals of the study are to explore whether middle school students can understand tavr in a simulation and how they use their experience of interacting with tavrs to refine their mental model of the sizes of submacroscopic objects.
material awareness: promoting reflection on everyday materiality. drawing on existing design approaches, this paper argues for the experiential desirability and critical importance--in terms of environmental sustainability--of designing for reflection on everyday material things themselves. this paper motivates and proposes a material awareness design approach, further drawing on developments from philosophy of technology and design theory. a series of conceptual designs are presented to help illustrate this approach.
best practices in longitudinal research. this workshop will identify best practices for longitudinal research through an in-depth exploration of methods and metrics for collecting and analyzing user data over time. this is the fourth event in an ongoing effort by the organizers to enhance our current body of knowledge about longitudinal research.
action planning with commonsense knowledge. understanding other people's goals is an essential part of interpersonal interactions. this capability enables a person to naturally predict another person's future actions in a situation and produce appropriate joint or shared actions. in like manner, a human-like planning agent (or sociable robot) should be able to understand the user's action goal and come up with subgoal-based plans to achieve the goal. in this paper we focus on how the agent can automatically construct the subgoal-based action hierarchy corresponding to the user's high-level goal. as a first step, we implement an action-planning engine based on conceptnet, and indicate the drawbacks of using conceptnet for this purpose. also, we present the structure of a new goal-oriented commonsense-reasoning knowledgebase for the agent's action-goal representation and action planning.
a short film about vjs: using documentary film to engage performers in design. vjing is a live performance of visual media. in their performances vjs utlize technologies in ways which subvert and evolve current interfaces; presenting qualities such as performativeness and expression. by developing interfaces in direct response to a vj's work, we can learn how to develop fresh styles of interaction. the subtle nuances of a vj's use of technology may not be achieved through a simple observation or dialogue with vjs; as they are difficult to decouple from the performer's creative process. in this film we present a design process that utilizes video documentary to explore the working practices of a collection of vjs. the documentary frames our engagement with the creative processes which shape an individual artist's performance. we describe the process detailing the initial creation of the documentary, and a participatory design workshop inspired by the film. we conclude with an example of how the process has been used in the design of a personal interactive tool for one of our participants.
see you on the subway: exploring mobile social software. this project explores the social possibilities of mobile technology in transitional spaces such as public transport. based on a cultural probes study of stockholm subway commuters, we designed a location-based friend finder that displays only people in the same train as the user. we aim at reaching a critical mass of users and therefore decided to make the system compatible with as many phones as possible, thus it was designed as a simple web application. an initial informal study pointed out consequences of certain design decisions on the user experience and highlighted social tensions created by presence awareness.
usability, playability, and long-term engagement in computer games. does usability affect long term user engagement in computer games, or are other factors more influential? this paper explores this issue, discussing an evaluation study that measured the relevance of usability versus playability factors for long-term user engagement in eight commercial games.
rhythms of non-use of device ensembles. the proliferation of portable devices has transformed our everyday practices, blurring second and third places. however, almost no research exists on how the perpetual possession of devices impacts how we escape them. in this paper, we explore the notion of non-use of portable devices. drawing from the results of a multi-step qualitative study, we provide a discussion on how non-use interplays with the dynamics of everyday life. specifically, we discuss practices surrounding hybridities of portable devices and social circles. the layerings of portables help in de-personalizing interactions through evasions, pretence, and resistance. we argue that non-use is not a reason for failure, but is a form of use in itself.
dynamically transparent window. in this paper, we present a case study of dynamically transparent windows installed during a five weeks period in the facade of a major department store on a busy high street. the windows are fitted with so-called electro-chromatic foil that can change from opaque to transparent when an electric current runs through it. by using strips or rectangles of the foil, narrow bands on the façade interactively change and reveal what is on display in the store in order to draw the by-passers closer, and encourage them to explore the display. our evaluation based on log-data, video observations, and in-situ observations points to a number of challenges concerning 1) interaction issues related to the movement vector of pedestrians, 2) behaviour and attention issues, and 3) issues pertaining to the diversity of the situations and external conditions in the high street setting.
towards improving mental models of personal firewall users. windows vista's personal firewall provides its diverse users with a basic interface that hides many operational details. however, our study of this interface revealed that concealing the impact of network context on the security state of the firewall results in mental models that are unclear about the protection provided by the firewall resulting in an inaccurate understanding of the firewall configuration. we developed a prototype to support more contextually complete mental models through inclusion of network context information. results from our initial evaluation of the prototype support our approach of improving user understanding of underlying system states by revealing hidden context, while considering the tension between complexity of the interface and security of the system.
blobby: how to guide a blind person. for the majority of blind people, walking in unknown places is a very difficult, or even impossible, task to perform, when without help. the adoption of the white cane is the main aid to a blind user's mobility. however, the major difficulties arise in the orientation task. the lack of reference points and the inability to access visual cues are its main causes. we aim to overcome this issue allowing users to walk through unknown places, by receiving a familiar and easily understandable feedback. our preliminary contributions are in understanding, through user studies, how blind users explore an unknown place, their difficulties, capabilities and needs. we also analyzed how these users create their own mental maps, verbalize a route and communicate with each other. structuring and generalizing this information, we were able to create a prototype that generates familiar and adequate instructions, behaving like a blind companion, one with similar capabilities that understands his "friend" and speaks the same language. we evaluated the system with the target population, validating our approach and orientation guidelines, while gathering overall user satisfaction.
triptip: a trip planning service with tag-based recommendation. in this paper we suggest a design for a system, triptip, the aim of which is to help negotiate their way through the immense amount of information that is often available by recommending a set of choices. triptip recommends to the users the next place, which they would most likely want to visit given their preference in previous choices. to generate this information, tags that are attached on a given place by users give the characteristics of a place and the reasons for visiting the place.
facilitating benign deceit in mediated communication. this research explores how to communicate an individuals' self-reported emotional state to members of their personal social network, through automatic, computer-generated, personalised updates. results of two qualitative studies are described where participants were unwilling to disclose their emotional state fully to all of their network members, choosing to deceive selected members instead. further, participants indicated that they would want automatic personalised updates for network members to incorporate these deceits.
designing user interfaces for multi-touch and gesture devices. initially designers only had a keyboard and lines of text to design. then, the mouse enabled a richer design ecosystem with two dimensional plains of ui. now the design and research communities have access to multi-touch and gestural interfaces which have been released on a mass market scale. this allows them to design and develop new, unique, and richer design patterns and approaches. these methods are no longer confined to research projects or innovation labs, but are now offered on a large scale to millions of consumers. with these new interface behaviors, in combination with multiple types of hardware devices that can affect the interface, there are new problems and patterns that have increased the complexity of designing interfaces. the aim of this sig is to provide a forum for designers, researchers, and usability professionals to discuss this new and emerging technology trends for multi-touch and gesture interfaces, as well as discuss current design patterns within these interfaces. our goal is to cross pollinate ideas and current solutions from practitioners and researchers across communities to help drive awareness of this new field for those interested in, just starting in, or currently involved in the design of these systems.
using hands and feet to navigate and manipulate spatial data. we demonstrate how multi-touch hand gestures in combination with foot gestures can be used to perform navigation tasks in interactive systems. the geospatial domain is an interesting example to show the advantages of the combination of both modalities because the complex user interfaces of common geographic information system (gis) requires a high degree of expertise from its users. recent developments in interactive surfaces that enable the construction of low cost multi-touch displays and relatively cheap sensor technology to detect foot gestures allow the deep exploration of these input modalities for gis users with medium or low expertise. in this paper, we provide a categorization of multitouch hand and foot gestures for the interaction with spatial data on a large-scale interactive wall. in addition we show with an initial evaluation how these gestures can improve the overall interaction with spatial information.
choosing the right knob. people with dementia have problems carrying out multi-step tasks such as making a hot drink. intelligent systems are being built to prompt people through such tasks. however, the prompts used by these systems are likely to be viewed as novel. as people with dementia are known to be sensitive to novelty this could be a problem. an experiment was performed to determine how to prompt people with dementia with which knob controls which burner on a cooking range. a highly novel implicit attentional cue using fluorescent wire was found to provide comparable or better results than more conventional alternatives. it is concluded that design in this area does not need to be constrained by the need to avoid novelty. the experiment is also of interest because of the way that it was embedded in a natural cooking task suitable for people of varied cognitive capacity.
ethnochat: an instant messenger program for ethnography. this paper describes the design of ethnochat, an instant messaging (im) program built for ethnographers to conduct computer-mediated, semi-structured or unstructured interviews. to our knowledge, this is the first program of its kind. ethnographic techniques are becoming a common method to investigate social interactions and settings in digital contexts, and this creates a demand for a proper tool with which ethnographers can practice their craft. this paper details the design and articulates how ethnochat will have significant implications for hci practice.
adaptive brain-computer interface. passive brain-computer interfaces are designed to use brain activity as an additional input, allowing the adaptation of the interface in real time according to the user's mental state. while most current brain computer interface research (bci) is designed for direct use with disabled users, i focus my research on passive bcis for healthy users. the goal of my dissertation is to employ functional near-infrared spectroscopy (fnirs), a non-invasive brain measurement device, to augment an interface so it uses brain activity measures as an additional input channel. i have measured and classified brain signals that are interesting in hci context, such as mental workload and difficulty level of a task. my future work will focus on creating an interface that responds to one of those measures by adapting the interface. by combining brain signal measured with an adaptive interface i expect to contribute a functional passive brain-computer interface that measures and adapts to the user's brain signal.
the reflective transformative design process. the department of industrial design at the eindhoven university of technology distinct itself through a unique combination of focus (designing highly intelligent systems, products, and related services) and education model (competency-centred learning). based on the foundations of our department we identify three implications for our preferred design process: it is flexible and open, it values design action as a generator of knowledge and it is driven by a vision on the design opportunities that are afforded by emerging intelligent technology. in this paper we explain the reflective transformative design process and the rationale behind.
how do people talk with a robot?: an analysis of human-robot dialogues in the real world. this paper reports the preliminary results of a human-robot dialogue analysis in the real world with the goal of understanding users' interaction patterns. we analyzed the dialogue log data of roboceptionist, a robotic receptionist located in a high-traffic area in an academic building [2][3]. the results show that (i) the occupation and background (persona) of the robot help people establish common ground with the robot, and (ii) there is great variability in the extent that users follow social norms of human-human dialogues in human-robot dialogues. based on these results, we describe implications for designing the dialogue of a social robot.
gaze-based interaction with massively multiplayer on-line games. people with motor impairments can benefit greatly from being able to take part in massively multiplayer on-line games, such as world of warcraft. we are investigating how to use eye gaze as a high bandwidth input modality for the range of tasks necessary to participate in the game. we approach this from two directions; in the bottom-up approach we iteratively implement and eva-luate various gaze-interaction techniques, and in the top-down approach we analyze the interaction in mmogs and develop a theory to map games tasks to gaze-based interaction techniques. we present preliminary results from a recently conducted set of trials which have studied how well tasks in world of warcraft can be carried out using gaze only. we describe this in the context of the whole project.
one-handed behind-the-display cursor input on mobile devices. behind-the-display interaction has gained popularity for interactions on handheld devices as researchers have demonstrated the viability of such interactions on small devices. however, most designs have investigated the use of direct input behind the screen. we demonstrate that behind-the-display interaction with cursor input is promising and can be a useful augmentation to handheld devices. we developed a prototypical system on a pda to which we affixed a wireless mouse. the mouse is mounted on the rear of the pda with the optical sensor facing outwards. the system is designed to be used with one hand, and prevents occlusion and finger-reach. through several applications we propose the benefits associated with behind-the-display cursor interaction. a preliminary user evaluation indicates that users can benefit from such an interaction when operating a handheld using one hand.
exploring social and temporal dimensions of emotion induction using an adaptive affective mirror. this paper investigates if and how a digital, interactive affective mirror induces positive emotions in participants. we study whether the induced affect is repeatable after a fixed interval (study 1) and how the social presence affects the emotion induction (study 2). results show that participants systematically feel more positive after an affective mirror session; this effect is shown to be repeatable, and co-presence of a friend is shown to boost this effect.
suchef: an in-kitchen display to assist with "everyday" cooking. decisions about what to eat are often made close to mealtime, when hunger clouds people's ability to think creatively or conscientiously about their meal choices. as a result, people we studied tended to resort to "everyday meals": recipes that are tasty, quick, and cheap. these choices often run counter to cooks' stated values regarding health, variety, ingredient choice, and so forth, but are chosen for their convenience and familiarity. this lack of variety seemed to stem from a scarcity of "everyday" recipes compounded by the fact that usually, at the time they are preparing the meal, cooks are tired, hungry, and don't want to search for or try less familiar recipes. based on a study of current cooking practices, we developed the suchef prototype: a low-fidelity probe supporting the in-kitchen display of everyday meal ideas along with the sharing of recipes among members of social groups. the probe was deployed for a week among 5 geographically dispersed but socially connected households and yielded insights into the design space for technology to support everyday cooking.
imaging-based cosmetics advisory service. in this paper we describe a multimodal cosmetic advisory system that recommends cosmetics appropriate for users' skin tone. this system is intended for commercial use to address the problem of color selection of cosmetic foundation. based on surveys and semi-structured interviews we have verified that visual selection of color foundation cosmetics is error prone, and the results of our study indicate that both mobile and kiosk touch points are essential to cover the entire target population (women of all ages) since technical vs. social comfort, accuracy vs. convenience and social vs. individual needs play a huge role in the usage and adoption of personal advisory services.
context menus for the real world: the stick-anywhere computer. in this video, we present a context-aware menu system made out of simulated digital paper. built on the ubiquitous yellow sticky notes found in offices everywhere, our computer provides a contextual interactive paper menu that can be used to operate numerous everyday electric and electronic devices, such as lamps, speakers and computers. stuck on a device, the sticky screen displays contextual information and control options which may be selected with a single touch of the finger. the stick-anywhere computer is an example of a context-aware organic user interface that, through a flexible paper-like display, allows software to reside directly on the product or task. the stick-anywhere computer was implemented using a xuuk eyebox2 ir camera that tracks nearly invisible ir markers on post-it notes as well as fingers, and uses a projector to render interactive content directly onto the paper note.
programming reality: from transitive materials to organic user interfaces. over the past few years, a quiet revolution has been redefining our fundamental computing technologies. flexible e-ink, oled displays, shape-changing materials, parametric design, e-textiles, sensor networks, and intelligent interfaces promise to spawn entirely new user experiences that will redefine our relationship with technology. this workshop invites researchers and practitioners to imagine and debate this future, exploring two converging themes. transitive materials focuses on how emerging materials and computationally-driven behaviors can operate in unison blurring the boundaries between form and function, human body and environment, structures and membranes. organic user interfaces (oui) explores future interactive designs and applications as these materials become commonplace.
caraclock: an interactive photo viewer designed for family memories. caraclock is an interactive photo viewing device which allows for the sharing of "collective memory" among family members. the server-based algorithm uses a bayesian network that employs probabilistic computation to model each user's interpersonal relationships. when multiple caraclock devices are synchronized, they display related photos according the settings. this often results in serendipitous discoveries for the whole family by reminding them of their collective experiences through images of their past.
collocated mobile collaboration. mobile devices have changed, and continue to shape, the world in which we live. when these devices were first introduced they were most often used in isolation to schedule appointments, take notes, play games, or view or edit pictures and stories. the extent of the collaboration on these mobile devices was to make phone calls, which has led to their worldwide distribution. despite their broad proliferation, there are limitations such as small screen size and limited interaction space. we believe that by bringing devices and people together, these limitations can be overcome. in this video submission, we illustrate the potential of devices and people working together by showing how children can collaboratively read and create stories using mobile devices and exploit the shoulder-to-shoulder collaborative situation to share and expand the interactive space.
connected space. connected space connects remote spaces based on sensor data values that users collect. diverse spaces that have similar ambient data are connected. because sensor data is quantified data which falls outside the scope of human senses, users need a solution to understand it. connected space maps the data into a visual representation and allows interaction with the data. connected space suggests a new way to connect remote spaces with sensor data in telecommunication art and also suggests ways to enable users to understand quantified data with interaction in a more concrete way.
adaptive personalisation for researcher-independent brain body interface usage. in this case study, we report what we believe to be the first prolonged in-situ use of a brain-body interface for rehabilitation of individuals with severe neurological impairment due to traumatic brain injury with no development researchers present. we attribute this success to the development of an adaptive cursor acceleration algorithm based on screen tiling, which we combined with an adaptable user interface to achieve inclusive design through personalisation for each individual. a successful evaluation of this approach encouraged us to leave our brain-body interface in the care settings of our evaluation participants with traumatic brain injury, where it was used with support from health care professionals and other members of participants' care circles
mirroring bodily experiences over time. the affective health system is a mobile lifestyle application that aims to empower people to reflect on their lives and lifestyles. the system logs a mixture of biosensor-data and other contextually oriented data and transforms these to a colorful, animated expression on their mobiles. it is intended to create a mirror and thereby empower users to see activity patterns and relate these to their experiences of stress. people's different cultural backgrounds and their different physiological and psychological composition give them different perceptions and associations of time. we explore the time dimension of our system through working through a set of different designs that organize events as time going linearly forward, in a circular movement or relating to geographical places. here we discuss the process of designing a mobile interface for presenting temporal data in a way that allows multiple and subjective interpretation.
users' ongoing work on managing computational artifacts. in a computing environment where computational artifacts come and go at rapid pace, products become easily outdated, resulting in lack of support. consequently, users are constantly challenged to think about the trade-offs between maintaining and appropriating the current product and adopting an alternative product. this challenges us to think beyond designing individual products to be useful, usable, aesthetic, or learnable and consider what is necessary for sustainable and long-term use. in order to further understand users and find potential solutions to the design challenge, i explore how users perceive their everyday computational resources becoming outdated and in reaction how they deal with the problem during maintenance, appropriation, and adoption of computational resources on an ongoing fashion.
open by design: how ibm partnered with the user community in the redesign of lotus notes. this paper describes the methods used to successfully redesign the ibm® lotus notes® user experience. the methods we found most valuable were designed to be open to a rich dialog with the wide community of notes users. based on our experience, we share practical benefits and challenges with using these methods.
support for seamless linkage between less-detailed and more-detailed representations for comic design. through a study of comic design practice, we observed that comic designers created three components -- character-config, plot, and storyboard -- and used a trial-and-error approach with iterative progression from less detailed to more detailed representations during the early stages of design. however, existing comic design tools do not support these tasks very well. in the light of these observations, we created a system that helps comic designers in the early stages of design. our prototype supports sketching input, allows seamless movement backward or forward among the different granularities of representations across the three components, and concurrent use of multiple related sheets.
mobile technologies for the world's children. in this panel, academic, non-profit, and industry professionals will discuss their global perspectives on mobile technologies for the world's children. panelists will explore such issues concerning children's access to mobile devices, the decreasing age that children have access to these technologies, mobile innovations for learning, and challenges/opportunities in diverse countries. this interactive session will begin with each panelist giving a short summary of their work-to-date with children and various mobile applications. then the panelists will be asked questions by children from different countries via pre-recorded video. audience members will be invited to offer their thoughts and comments as well as the panelists during the video question period. audience members will also be able to ask further questions throughout the panel discussion.
activeshare: sharing challenges to increase physical activities. this paper discusses the use of social goal setting as a strategy to achieve persuasion through technology. this approach was applied in the design of activeshare a system developed to motivate people with sedentary lifestyles to increase their physical activity. in this system, users obtain and share their goals through challenges, which are posted on a social networking website. the paper describes the iterative design process followed, including concept tests, a focus group, and a field test with a fully functional prototype. preliminary results are promising, although we found no significant increase on physical activity during the one week test. suggested improvements to the design and plans for a follow up study are outlined.
pressuretext: pressure input for mobile phone text entry. pressure sensitive buttons are appealing for reducing repetitive tasks such as text entry on mobile phone keypads, where multiple key presses are currently necessary to record an action. we present pressuretext, a text-entry technique for a pressure augmented mobile phone. in a study comparing pressuretext to multitap, we found that despite limited visual feedfback for pressure input, users overall performed equally well with pressuretext as with multitap. expertise was a determining factor for improved performance with pressuretext. expert users showed a 33.6% performance gain over novices. additionally, expert users were 5% faster on average with pressuretext than multitap, suggesting that pressure input is a valuable augmentation to mobile phone keypads.
aesthetics matter: leveraging design heuristics to synthesize visually satisfying handheld interfaces. we present a tool for automatically generating ui layouts for handheld devices based on design principles. this tool introduces a gestalt approach to visual interface design rather, complementing prior work on user cost minimization. we aim to increase user satisfaction using this approach. the tool automatically generates size and position of widgets drawn from the ui design heuristics of simplicity, structuring, and proportion. simplicity refers to excluding non-core functionality; structuring to contextual grouping, and proportion to best-practice geometric ratios of width, height, and spacing. layouts are generated from device constraints and simple xml containing ui component hierarchy. these layouts can be directly manipulated using a gui editor.
investigating background & foreground interactions using spatial audio cues. audio is a key feedback mechanism in eyes-free and mobile computer interaction. spatial audio, which allows us to localize a sound source in a 3d space, can offer a means of altering focus between audio streams as well as increasing the richness and differentiation of audio cues. however, the implementation of spatial audio on mobile phones is a recent development. therefore, a calibration of this new technology is a requirement for any further spatial audio research. in this paper we report an evaluation of the spatial audio capabilities supported on a nokia n95 8gb mobile phone. participants were able to significantly discriminate between five audio sources on the frontal horizontal plane. results also highlighted possible subject variation caused by earedness and handedness. we then introduce the concept of audio minimization and describe work in progress using the nokia n95's 3d audio capability to implement and evaluate audio minimization in an eyes-free mobile environment.
an evaluation of one-handed techniques for multiple-target selection. recent research has revealed that a large population of mobile users usually use one hand when interacting with mobile devices. however, very few techniques have been developed to support multiple-target selection. in this paper, we introduce burst and zoomtap, two techniques that aim to facilitate accurate and fast multiple-target acquisition with one-handed thumb operation on touch-based mobile devices. we compare our two techniques to shift in a controlled experiment. the results show that for multiple-target selection, burst and zoomtap can outperform shift; also according to the questionnaire, participants prefer burst and zoomtap to shift.
connecting the dots with related notes. during visual analysis, users must often connect insights discovered at various points of time to understand implicit relations within their analysis. this process is often called "connecting the dots." in this paper, we describe an algorithm to recommend related notes from a user's past analysis based on his/her current line of inquiry during an interactive visual exploration process. we have implemented the related notes algorithm in harvest, a web based visual analytic system.
influences of mood on information seeking behavior. in this study, we explored how moods influence the way people seek information. we conducted a controlled lab study to test our hypotheses drawn from affect-as-information theory. fifty-eight participants were randomly assigned to the happy or sad condition. they were primed for a certain mood, and they then performed a search task and finished a series of questionnaires. our findings supported affect-as-information: the comparatively happy participants were inclined to process more general and less specific information; the comparatively sad participants were likely to process more specific information. the findings advances theoretical and empirical understanding concerning the characteristics of users' information seeking behavior under different moods. our study will contribute to affective search systems design.
exploring cues and rhythm for designing multimodal tools to support mobile users in wayfinding. in recent navigation hci studies, the shift from investigating map-based mobile applications towards supporting mobile users' wayfinding tasks with multimodal navigation aids is apparent. while there have been many studies of navigation design guidelines for using maps or speech- or tactile-based guidance in mobile devices, in this paper we propose an initial study of multimodal navigation design utilising the theory of designing episodes of motion originating from urban planning. the implications of designing cues and providing rhythm, as the theory of episodes of motions suggests, are explored, with pedestrians as the subjects using wayfinding tasks in an urban area. the main contributions of this paper are in investigating the design principles, evaluating them in the context of mobile wayfinding tasks, and reflecting upon the results in terms of users' wayfinding behaviour. it is concluded that by designing predictive clues and rhythm into mobile multimodal navigation applications, we can improve navigation aids for users.
the mousegrip. computer games, often played with others, are a compelling pastime for many. however, they have been criticized for their mouse and keyboard or gamepad interactions, as they support a sedentary lifestyle. in contrast, a "hand exerciser" handgrip device can help strengthen hand and forearm muscles extensively through a simple spring mechanism. our system "mousegrip" is an exertion interface to control computer applications while simultaneously exercising hand and arm muscles based on a handgrip device. we present a casual game of pong for two distributed players who control the game with a mousegrip each, demonstrating a low-cost approach to "exertion interactions over a distance". by showing how easy it can be to include exertion in interactions with computers, we hope to encourage other researchers and designers to consider exertion activity in their designs in order to support a healthy lifestyle.
the reign of catz & dogz at chi 2009. despite the enormous commercial successes of products such as nintendogs, very little is known about people's interactions with artificial representations of animals. however there is an increasing body of research in different disciplines which could be used to better understand such interactions. the reign of catz & dogz at chi 2009 is a one day workshop which will bring together researchers in an inter-disciplinary, international and multi-cultural setting to explore the relevant issues surrounding interactions with virtual creatures and the role such creatures will play in the future.
towards intelligent authoring tools for machinima creation. as user-created content increasingly becomes an ever more prominent element of modern game design, tools have been developed to aide in the creative process for several forms of digital media, including machinima. because creating content that will be valued by the community is a challenging process, tools are needed that will assist novices in both technical realization and optimization of content. we are exploring tools for machinima authoring that use a 3-pronged approach: authoring via metaphor, performance, and automation. future work involves using ai to provide feedback to machinima authors, suggesting sensible attributes for scenes based on prior input by acting as a surrogate audience.
wuw - wear ur world: a wearable gestural interface. information is traditionally confined to paper or digitally to a screen. in this paper, we introduce wuw, a wearable gestural interface, which attempts to bring information out into the tangible world. by using a tiny projector and a camera mounted on a hat or coupled in a pendant like wearable device, wuw sees what the user sees and visually augments surfaces or physical objects the user is interacting with. wuw projects information onto surfaces, walls, and physical objects around us, and lets the user interact with the projected information through natural hand gestures, arm movements or interaction with the object itself.
let's clean up this mess: exploring multi-touch collaborative play. multi-touch play is inherently collaborative, but little work currently explores this aspect. we present preliminary observations of multi-touch collaborative gameplay, focusing on the physical-social environment of a multi-touch surface and its technical issues.
the doctor as the second opinion and the internet as the first. people who use the internet for health information often obtain their first opinion that way, and then, if they go to a doctor, the doctor's advice is relegated to the second opinion. using the internet, or dr. google, as a first opinion can be problematic due to misinformation, misinterpretation of valid information, and the fears that can arise due to lack of medical knowledge, inexperience, and limited perspectives. when patients do visit their doctor for a second opinion, some do not disclose the fact they already received their first opinion and often their doctors do not ask. the result is that patients may suffer needlessly if their fears, concerns, misunderstandings, and misinterpretations are not addressed by the healthcare providers with the expertise and skills to assist them. a pernicious disconnect exists between many patients who use the internet for health information and the medical professionals who care for them. the medical profession can alleviate this disconnect by taking the lead in establishing guidelines for systematically talking to patients about, and guiding, their internet research. human-computer interaction professionals can collaborate with the medical community in ensuring credible health web sites become the gold standard that patients use to achieve better health.
a gesture-based and eyes-free control method for mobile devices. a novel interaction method for eyes-free control of a mobile phone or a media player is introduced. the method utilizes acceleration sensors along three axes to sense input gestures, such as pointing and tilting. a spherical auditory menu and feedback are provided using speech and 3d sound. a gestural pointing interface, multiple menu configurations, and their implementation details is presented. evaluation results suggest that fast and accurate selection of menu items is possible without visual feedback. combining the gestural interface, positions of menu items in 3d and a browsing method with a dynamically adjustable target size of the menu items allow large menus with intuitive, easy access.
supporting the design of network-spanning applications. in this case study, we describe our use of ect, a tool intended to simplify the design and development of network-spanning applications. we have used ect throughout the course of a two-year collaboration, which has involved individuals with expertise in a variety of fields, including interaction design and computer systems engineering. we describe our experiences with this tool, with a particular focus on its emerging role in helping us to structure our collaboration. we conclude by presenting lessons that we have learned, and by suggesting future directions for the development of tools to support the design of network-spanning applications.
a hand clap interface for sonic interaction with the computer. we present a hand clapping interface for sonic interaction with the computer. the current implementation has been built on the pure data (pd) software. the interface makes use of the cyclic nature of hand clapping and recognition of the clap type, and enables interactive control over different applications. three prototype applications for the interface are presented: a virtual crowd of clappers, controlling the tempo of music, and a simple sampler. preliminary tests indicate that rather than having total control via the interface, the user negotiates with the computer to control the tempo.
designing and deploying usetube, google's global user experience observation and recording system. in this paper, we describe various systems that can be used to record and observe user research activities. we examine the different user needs in this space and the key variables that determine how these needs can be addressed. we then focus on the system we designed and built for the user experience team at google. features of that system include the ability to watch high-definition study videos live from anywhere on the google network using any browser on any major operating system in real time as studies are being conducted around the world, a complete and easily accessible archive of all study videos ever recorded at google, one-button self-serve operation for study moderators, and minimal system maintenance. since implementing this system, we have seen a dramatic increase in the number of observers who directly experience our end users.
multi-touch interface for controlling multiple mobile robots. we must give some form of a command to robots in order to have the robots do a complex task. an initial instruction is required even if they do their tasks autonomously. we therefore need interfaces for the operation and teaching of robots. natural languages, joysticks, and other pointing devices are currently used for this purpose. these interfaces, however, have difficulty in operating multiple robots simultaneously. we developed a multi-touch interface with a top-down view from a ceiling camera for controlling multiple mobile robots. the user specifies a vector field followed by all robots on the view. this paper describes the user interface and its implementation, and future work of the project.
single stroke gaze gestures. this paper introduces and explains the concept of single stroke gaze gestures. some preliminary results are presented which indicate the potential efficiency of this interaction method and we show how the method could be implemented for the benefit of disabled users and generally how it could be integrated with gaze dwell to create a new dimension in gaze controlled interfaces.
a design evaluation of a user interface for tending long-term tasks. organizational processes often take place over long periods of time and require intermittent attention. remembering and reasoning about upcoming process tasks is important, but not adequately supported by existing tools. this paper describes longitude, a tool that provides a compact timeline of tasks and deadlines. we discuss findings from an exploratory study of the system and propose new requirements for tools that help people participate in long-running group processes requiring intermittent and sporadic attention.
beyond the dyad: understanding sharing in instant messaging. instant messaging allows users to exchange presence and availability information, and to have spontaneous online conversations. we report on a study of account sharing in im, and present distinct types of sharing as well as practices of sharing.
out from behind the curtain: learning from a human auditory display. in this paper we describe an approach to gathering design requirements for a software auditory display by analyzing user interactions with an ideal partner: a talking human controlling a computer. we explain the potential benefits of studying such unconstrained user interaction before detailing the design and execution of our qualitative evaluation. we report the results of our thematic coding analysis and give examples of each of the seven major user techniques, difficulties, and preferences identified. to conclude the paper, we summarize the application of our results to the design of a software auditory display for common office computing tasks.
designing with unconscious human behaviors for eco-friendly interaction. eco-design has become a central research issue for interaction design, as emerging interactive products can create serious environmental impacts while products are being used. we investigate a design method and develop case studies for eco-friendly interaction. a main concept of the design method is to apply unconscious human behaviors in interaction design. products designed with this method are expected to be used unconsciously by users with reduced environmental impacts. in this paper, we present a framework of design space matrix and initial case studies for the design method. for the framework, we identified the types of interaction behaviors causing environmental impacts and the attributes of unconscious human behaviors. based on the framework, three design cases - a power cord, a trashcan and a speedometer of an automobile - were developed. the proposed framework and design cases can be used as a base of an advanced eco-friendly interaction design method.
facilitating multiple target tracking using semantic depth of field (sdof). users of radar control systems and monitoring applications have to constantly extract essential information from dynamic scenes. in these environments a critical and elemental task consists of tracking multiple targets that are moving simultaneously. however, focusing on multiple moving targets is not trivial as it is very easy to lose continuity, particularly when the objects are situated within a very dense or cluttered background. while focus+context displays have been developed to improve users' ability to attend to important visual information, such techniques have not been applied to the visualization of moving objects. in this paper we evaluate the effectiveness of a focus+context technique, referred to as semantic depth of field (sdof), to the task of facilitating multiple target tracking. results of our studies show an inclination for better performance with sdof techniques, especially in low contrast scenarios.
adwil: adaptive windows layout manager. this paper addresses a challenge for the design of visual analytics software, managing placement of multiple windows while accomplishing a cognitively challenging analysis task. we are designing an adaptive windows layout manager that will support the user's creativity by facilitating concentration on the task at hand.
xplml: a hci pattern formalizing and unifying approach. in this paper we describe an approach to formalize and unify human-computer-interaction (hci) design patterns. the goal is to help pattern authors, users, and software engineers to work more efficiently with design patterns. to this end, we have investigated seven building blocks for setting up a unified form of hci design patterns. they will serve as the necessary requirements for successful integration into the semantic web, pattern management tools, and the hci community.
utilizing pathfinder in the design of an intranet website. usability analyses of the homepage categories and sub-categories at sandia national laboratories were undertaken to identify potential improvement opportunities to the current architecture. through traditional card sorting methods, as well as a novel implementation of pathfinder analysis, a novel re-structuring and minimal nomenclature changes are suggested for future user testing. additionally, the study finds pathfinder analysis a useful addition to traditional usability methods and suggests related methodological research opportunities.
learning design principles for a collaborative information seeking system. while collaboration is a natural choice in many situations, there is a lack of specialized tools for collaboratively seeking information. we present design specifications and implementation of a collaborative information seeking system. we test this system through several pilot studies and cognitive walkthroughs. user interactions and feedback from these studies help us refine our design specifications for a better collaborative information seeking system.
soft(n): toward a somaesthetics of touch. this paper explores the concept of somaesthetics as an approach to the design of expressive interaction. this concept is exemplified through the design process of soft(n), an interactive tangible art installation developed in conjunction with v2_lab in rotterdam. somaesthetics is a term coined by richard shusterman, a pragmatist philosopher interested in the critical study of bodily experience as a focus of sensory-aesthetic appreciation and agency. in the context of interaction, somaesthetics offers a bridging strategy between embodied practices based in somatics, and the design of an aesthetics of interaction for hci. this paper argues for the value of exploring design strategies that employ a somaesthetic approach, presents a definitional framework of somaesthetics that can be applied to interaction, and links the concept of somaesthetics to a specific design case in which tactile interaction is applied to the design of a networked, tangible interactive artwork called soft(n).
synchronized communication and coordinated views: qualitative data discovery for team game user studies. we present a tool for qualitative data discovery that aids researchers in analyzing synchronized log data with audio collected from multiple computers. the tool was originally developed for team games in which the goal of play is to exercise coordination skills. in team coordination games, players cooperate toward a shared objective by communicating effectively and synchronizing their game world actions. to evaluate such games, researchers observe communication between players synchronized with their actions in-game, discovering instances of team coordination. coordination is a composite of communication and in-game action; thus it is essential to observe both in context. the tool enables simultaneous observation from each player's viewpoint, synchronized with communication using log files and time-stamped audio. viewpoints and voice tracks can be selectively soloed and muted, enabling researchers to focus attention. the application can be expanded to support logs and audio from other user studies.
the creativity support index. we present a draft survey tool called the creativity support index (csi). the csi is similar to the nasa task load index survey but is designed specifically for evaluating creativity support tools, based on concepts and theories from creativity research.
mobile user experience research: challenges, methods & tools. we are currently witnessing rapid innovation in mobile user experience (ux) research. the hci community is creating and adapting research methods, tools, and infrastructure for mobile-specific challenges and opportunities. this workshop brings together researchers from industry and academia, designers, and creators of research tools, who faced the challenges of mobile ux research and responded with innovative approaches. we will examine the co-evolution of methods and tools by considering their goals and requirements, and how these are shared across different approaches.
designing for reflection on experience. this paper outlines the rationale for the workshop and offers an outline of its objectives.
building a unified framework for the practice of experience design. this workshop challenges design practitioners and researchers to begin creating a unified framework for the practice of experience design.
double-side multi-touch input for mobile devices. we present a new mobile interaction model, called double-side multi-touch, based on a mobile device that receives simultaneous multi-touch input from both the front and the back of the device. this new double-sided multi-touch mobile interaction model enables intuitive finger gestures for manipulating 3d objects and user interfaces on a 2d screen.
interaction programming: next steps. interaction programming bridges the gap between interaction design and programming, but it has not yet been related directly to mainstream development practice. this paper presents ui model discovery tools to enable existing systems and traditional development processes to benefit from interaction programming tools and methods.
designing unobtrusive interfaces with minimal presence. the vision of ubiquitous computing is a world of invisible technologies. technologies are so woven into the fabric of everyday life that they become indistinguishable [1]. in this paper, we discuss unobtrusive interfaces having minimal presence. by merging into everyday objects and environments, the presence of an interface can be minimized, making our everyday life more interactive without increasing its complexity. to obtain minimal presence, physical plasticity of the interface is considered in the present work. this allows the interface to shift between invisible and visible states; the concealed interface appears when it is put into use and disappears after use. in addition, our recent project, shade pixel, is presented as an example of an unobtrusive interface with minimal presence. we also briefly describe a design concept for the interface to provide inspiration for its practical application.
co-reflection: user involvement for highly dynamic design processes. user involvement in systems, products and related services design has increased considerably in relevance. the way user involvement actually progresses depends on how the users are situated in relation to the design process. their influence may extend from the results of the design project to planning and managing the course of the design project. sequential techniques developed for the rational problem solving or reflective process have a limited application in highly dynamic design processes. more precisely, in sequential design processes validation steers reflection into a single direction. for this reason, a methodological approach not based on the sequential (hypothetical-deductive) paradigm but on the dialectical inquiry (inductive paradigm) between designers and users is considered. the versatile and holistic nature of this co-reflective process makes it suitable for dynamic and unstructured design processes based on different streams of reflection.
identtop: a flexible platform for exploring identity-enabled surfaces. only a subset of tabletop designs support the ability to determine which user has performed a given action. these identity-enabled (ie) surfaces offer significant functional advantages over systems with no such capability. distinguishing between the two types of surfaces enables a valuable discourse that should serve to improve the usefulness of all tabletop designs. to facilitate examinations of the ie design space, we have developed a toolkit called identtop, which greatly simplifies the process of prototyping new ie applications, and we present a few sample applications to demonstrate identtop's effectiveness.
new mobile ui with hand-grip recognition. today, mobile phones are no longer devices supporting only voice communications. many people use their mobile phones as multimedia players, cameras, messaging systems, etc. therefore, it is required to design a user interface that improves the usability of multi-functional mobile phones. for this purpose, we proposed a novel user interface that utilizes touch sensing technology to support multi-functional devices. the proposed user interface is based on the assumption that the device can detect how a user holds the device. by analyzing the user's grip-pattern, the device recognizes the user's intention and adjusts itself to meet the specific needs of the user such as accessing an application. the concept of the user interface is presented through several use-case scenarios. in addition, the technical feasibility of the proposed interface is validated by implementing a working prototype system.
improving the learnability of mobile device applications for older adults. mobile devices have the potential to support many older adults (age 65+) in their daily lives. however, older adults find it difficult to learn to use many existing mobile device applications and their interfaces. the goal of this dissertation research is to improve the learnability of mobile software user interfaces for older adults. to achieve this goal, we will investigate three complementary design approaches that have not been well explored for this population.
an online forum as a user diary for remote workplace evaluation of a work-integrated learning system. this paper presents and discusses the use of an online diary for the remote evaluation at the workplace of a new knowledge management tool that supports self-directed learning at work, the second aposdle prototype. the workplace evaluation was carried out collaboratively in four different organizations, across different european countries. the online diary was built with the open source discussion forum software phpbb. used in combination with other research methods, the diary allowed gathering data on the system design and performance as well as the user experience. its flexibility met participants' preferences and needs. with its use, the diary became the communication tool between users, researchers and developers, giving voice to the users in the evaluation and redesign process.
the changing face of digital science: new practices in scientific collaborations. the confluence of two major trends in scientific research is leading to an upheaval in standard scientific practice. a new generation of scientists, working in large-scale collaborations, is repurposing social software for use in collaborative science. existing social tools such as chat, im, and friendfind are being adopted and modified for use as group problem-solving facilities. at the same time, exponentially greater and more complex datasets are being generated at a rate that is challenging the limits of current hardware, software, and human cognitive capability. a concerted effort to develop new software tools to handle this data tsunami is redefining the collaboratory and represents a new frontier for computer supported cooperative work. we are hoping this workshop can build community among researchers studying and/or building software for scientific collaborations.
kte2: an engine for kinetic typography. in this paper we describe a kinetic typography engine, which allows the creation of text animation sequences. kinetic typography can bring written text closer to the realm of film by adding expressive power to it. thus kinetic typography can be used to enhance the digital communication between people. the engine supports various animation effects, some inspired by traditional animation, and others specifically for use with kinetic typography, and has an extensible architecture that allows new effects to be added in future. the engine can also be easily integrated into third party applications to support a wide range of uses.
studying appropriation of everyday technologies: a cognitive approach. the ways in which users appropriate uses of technology - or invent new ones - have attracted interest in cscw-oriented research, but much less has been written on its cognitive foundations, although concepts such as practical problem-solving, perception, and action are central to its understanding. i attempt to address this gap here by triangulating the phenomenon both theoretically and methodologically. in this paper, a reflection of the process provides a starting point for a study with a more focused research question.
calibration-free gaze tracking using a binocular 3d eye model. this paper presents a calibration-free method for estimating the point of gaze (pog) on a display by using two pairs of stereo cameras. by using one pair of cameras and two light sources, the optical axis of the eye and the position of the center of the cornea can be estimated. this estimation is carried out by using a spherical model of the cornea. one pair of cameras is used for the estimation of the optical axis of the left eye, and the other pair is used for the estimation of the optical axis of the right eye. the point of intersection of optical axis with the display is termed the point of the optical axis (poa). the pog is approximately estimated as the midpoint of the line joining poas of both the eyes with the display. we have developed a prototype system based on this method and demonstrated that the midpoint of poas was closer to the fiducial point that the user gazed at than each poa.
pulp-based computing: a framework for building computers out of paper. in this video, we describe a series of techniques for building sensors, actuators and circuit boards that behave, look, and feel like paper. by embedding electro-active inks, conductive threads and smart materials directly into paper during the papermaking process, we have developed seamless composites that are capable of supporting new and unexpected application domains in ubiquitous and pervasive computing at affordable costs.
coralog: use-aware visualization connecting human micro-activities to environmental change. this paper describes the goal, design approach and specification, and preliminary use test of a use-aware ambient media called coralog. coralog is a widget that detects the duration of a user's computer idle time (i.e. leaving the computer on without active usage) and communicates the energy consumption behavior through the visualization of the health of coral reefs. by occasionally consulting the non-intrusive widget, users can immediately acknowledge the impact of their computing behavior on ecosystems. therefore, the goal of this application is to make the public become aware of the connection between their everyday activities and global climate change, which will educate them about the formerly unseen effects that their actions may have and potentially lead to a sustainable living.
thinking with hands: an embodied approach to the analysis of children's interaction with computational objects. we present the theory and mixed methods approach for analyzing how children's hands can help them think during interaction with computational objects. the approach was developed for a study investigating the benefits of different input methods for object manipulation activities in digitally supported problem solving. we propose a classification scheme based on the notions of complementary and epistemic actions in spatial problem solving. in order to overcome inequities in number of access points when comparing different input methods, we develop a series of relative measures based on our classification scheme.
cubebrowser: a cognitive adapter to explore media databases. cubebrowser is the concept study for a six-display cube with digital screens that makes it possible to browse online databases like flickr. the control of navigation is exclusively accomplished by performing manual actions on the object. this creates a playful way of exploring image collections that are networked by tags.
towards systematic usability verification. although usability is the core aspect of the whole hci research field, it still waits for its economic breakthrough. there are some corporations that are famous for their usable products, but small and medium-sized businesses tend to prefer features over usability. we think, the primary reason is that there are no inexpensive methods to at least prevent huge design flaws. we propose the use of test specifications. once defined for a domain, these allow non-usability experts to systematically verify the usability of a given system without any users involved. we picked a sample domain with some basic tasks and found strong indication of our hypothesis: test specifications can be applied by non-experts and are able to find major design flaws. future work will extend this method to more complex tasks and evaluate the economic benefit.
gaze-controlled driving. we investigate if the gaze (point of regard) can control a remote vehicle driving on a racing track. five different input devices (on-screen buttons, mouse-pointing low-cost webcam eye tracker and two commercial eye tracking systems) provide heading and speed control on the scene view transmitted from the moving robot. gaze control was found to be similar to mouse control. this suggests that robots and wheelchairs may be controlled "hands-free" through gaze. low precision gaze tracking and image transmission delays had noticeable effect on performance.
engagement by design. the focus of this workshop is on the development of interfaces for long-term, voluntary use, spanning dozens, if not thousands, of interactions, and in which maintenance of user adherence to a desired interaction usage pattern is of primary interest. domains in which these issues are important include: wellness applications, such as long-term exercise or diet promotion; web site "stickiness"; multi-session intelligent tutoring systems; and computer games. this one-day chi'09 workshop brings together researchers from a wide spectrum of disciplines who share a common interest in finding theoretical frameworks, models, and design methodologies to support longitudinal hci.
interrupted. the 'intentional and planned' interference of the human physical, sensational, and conscious behavior could increase the probability of new forms of creation.
waterhouse: enabling secure e-mail with social networking. we present waterhouse, a system for sending and receiving cryptographically protected electronic mail ("secure e-mail"). we show how an existing e-mail interface can be modified to make exchanging secure e-mail nearly effortless. our system integrates with social networking services (such as facebook) to automatically exchange cryptographic keys between friends. when a user sends a message to a friend, our system automatically encrypts the contents to thwart eavesdroppers. when a user receives a message from a friend, waterhouse uses the recipient's social network to verify the sender's identity. our prototype shows senders' photos as an intuitive indicator of message authenticity. we describe our planned user study and conclude with directions for future work.
multi-point touch input method for korean text entry. multi-touch interfaces are becoming popular as a new input means for the various applications. in this paper, we suggest a new korean text entry method using a multi-touch interface called mpt (multi-point touch) input method. we conducted a text entry performance test comprising 4 sessions for 10 participants, and compared the result with an existing commercial spt (single-point touch) input method. the experimental results show that the entry speed of mpt was slower than that of spt method in the initial session. however, the entry speed of mpt input method was improved more rapidly than the speed of spt method as sessions were proceeded. we observed a statistically significant learning effect from the result of mpt method. moreover, we found no significant difference between the task loads of spt and mpt input methods.
'broken expectations' from a global business perspective. especially in the past few years, there has been an increase in the rejection rate of interactive consumer electronics products in the field, not due to broken hardware or software, but due to 'broken expectations' of users. however, operational methods to capture triggering contextual reasons are not functional in the industry. in addressing this gap, we propose systematic analysis of qualitative user feedback data resources from the field by utilizing our disconfirmed expectations ontology (deo). deo provides for an efficient means to elicit relevant -but currently unrecognizable- feedback from the field to communicate that to the respective units in a product development process. we further demonstrate the utilization of deo on a rich qualitative data set regarding the apple iphone".
interactive slide: an interactive playground to promote physical activity and socialization of children. we present a novel playground platform that will hopefully help in countering two important issues in children in the developed world: lack of physical activity and lack of socialization. the system underlying the platform will eventually adapt automatically to and modulate the amount of physical activity of children by applying a new notion in interaction: that of "interaction tempo". the concept of beats per minute seems especially adequate as the base structure of a physically-based activity. as an exertion interface we expect that, through the design of collaborative experiences, it will also enhance socialization of children.
gesture-based interaction with virtual 3d objects on large display: what makes it fun? in this paper, we describe a virtual game where game play is afforded by the user's silhouette interacting with on-screen 3d gaming objects, e.g. a soccer ball or a "chapteh" (shuttlecock kicking) -- a game played traditionally in villages, i.e. "kampongs", in asia. the virtual game system projects a life-size image of the location where the game is often played, e.g. soccer field when soccer is played or village playground in the case of "chapteh". the player's silhouette is super-imposed on the screen as the user interacts with the on-screen virtual 3d object using his body movement, e.g. bounce or lift. we compare the game play when different design variables were changed, e.g. replacing the soccer field image or removing the silhouette outline, to evaluate which design variable affects a user's experience during game play.
human computer biosphere interaction: towards a sustainable society. this paper presents the author's vision of human computer biosphere interaction (hcbi): towards a sustainable society. hcbi extends the subject of hci from countable people, objects, pets, and plants to an auditory biosphere that is uncountable, complex, and non-linguistic. by realizing hcbi, soundmarks in a forest can help us feel as one with nature, beyond the physical distance. the goal of hcbi is to realize the benefits of belonging to nature without causing environmental destruction. this paper presents the concept overview, related work, the method and developed interfaces.
citedness, uncitedness, and the murky world between. we test a recent claim in an opinion piece (interactions, may/june 2008, pp. 45-47) that publications by hci researchers have little or no impact. the alleged "phenomenon of uncitedness" was not supported. an examination of all 443 papers in the chi proceedings (1991-1995), acm tochi (1994-1999), and human-computer interaction (1991-1995) found an average of 93.8, 106.7, and 80.4 citations per paper, respectively. h-index as an impact measure is explained, with values given for members of the chi academy. the mean of 34.3 suggests that the group, taken as a whole, have had a significant impact on human-computer interaction.
authority vs. peer: how interface cues influence users. from the most e-mailed stories of the day to the most favorite stocks of the week, web interfaces are rife with cues conveying other users' ratings and reviews of products and services. do these peer opinions indeed affect our decisions? and if so, are they as strong in their impact as cues conveying authority/expertise (i.e., high source credibility)? we explored these questions through an experiment (n = 243) guided by the heuristic-systematic model in social psychology. bandwagon/peer cues are generally more persuasive, but when they are inconsistent, the authority cue influences decisions. in general, task involvement promotes systematic processing of these cues. interestingly, we found no difference in perceived authority between cnet editor's choice seal and a seal from a fictitious "authority" (zig!), among other indications of heuristic processing. we discuss design implications for user interfaces in general and recommendation agents in particular.
storytelling through drawings: evaluating tangible interfaces for children. this paper presents an ongoing study comparing the potential and the quality of the experiences provided by tangible versus traditional interfaces. the study was carried with two groups of kindergarten children using two interfaces that aim to motivate children to the practice of oral hygiene. children's drawings were one of the methods used to assess their experience. we found differences quantitatively and qualitatively between the drawings of the children interacting with the tangible interface and the traditional interface. the drawings suggest that by interacting with the tangible interface children felt more actively involved with the task.
acquiring a professional "second life": problems and prospects for the use of virtual worlds in business. the current surge of interest in virtual worlds suggests they are poised to make an evolutionary leap to the workplace, as instant messaging did a decade ago. in recent work we have introduced dozens of new users to teambuilding activities in the second life® environment, meeting both enthusiasm and skepticism. we document five issues for professional users of virtual environments: initial motivation, technical difficulties, interacting competently, becoming socially proficient, and finding compelling activities. based on these we describe a training strategy to enable professional users of virtual worlds.
springboard: exploring embodiment, balance and social justice. in this paper we describe the theory and design of a prototype interactive environment called springboard. springboard supports users to explore concepts in social justice through embodied interaction. we present the foundational theory of embodied conceptual metaphor, focusing on the twin-pan balance schema. we describe the application of balance metaphors in the design of the interaction model for our interactive environment. we conclude with a discussion of design choices and describe future research based on our prototype.
"it's like a circus in here!": affect and information sharing in an emergency department. the following research begins to address the relationship between affect and information sharing in order to inform the design of collaborative systems. through ethnographic observations of affect and face-to-face information sharing in an emergency department we begin to see trends on the occurrence of affect due to context as well as the relationship between affect and information sharing outcomes.
mobile gesture interaction using wearable tactile displays. we present an interaction method for mobile gesture interaction using wearable tactile displays. we are attempting to show that wrist-worn tactile displays provide adequate feedback to enable reversible and error-resistant gesture-based interaction. in support of this effort, we present pilot study results demonstrating users' sensitivity in perceiving vibratory directional patterns on the wrist.
jadeite: improving api documentation using usage information. jadeite is a new javadoc-like api documentation system that takes advantage of multiple users' aggregate experience to reduce difficulties that programmers have learning new apis. previous studies have shown that programmers often guessed that certain classes or methods should exist, and looked for these in the api. jadeite's "placeholders" let users add new "pretend" classes or methods that are displayed in the actual api documentation, and can be annotated with the appropriate apis to use instead. since studies showed that programmers had difficulty finding the right classes from long lists in documentation, jadeite takes advantage of usage statistics to display commonly used classes more prominently. programmers had difficulty finding the right helper objects and discovering how to instantiate objects, so jadeite uses a large corpus of sample code to automatically identify the most common ways to construct an instance of any given class.
extend: reducing e-waste through redistribution of local it resources. we designed a system of online classified ads that facilitates cascading used information technology (it) equipment such as computers, printers, and monitors from computing-intensive labs in higher education institutions to lower-end labs and then to administrative sites within the institution and finally the local community. after ethnographic research and a literature review, we found that it departments in higher education institutions tend to recycle instead of reuse it equipment largely because there is no system in place that fosters equipment reuse. in the university of michigan, this results in 50 tons of electronics being recycled annually, an estimated 40% of which could be re-used either elsewhere in the institution or in the wider local community. extend will promote decreased consumption of new equipment which will lead to a decrease in the generation of local e-waste.
an evaluation of techniques for selecting moving targets. moving targets are found in numerous applications such as computer games, air traffic control systems, and video surveillance. the selection of moving targets is considerably more difficult and error prone than traditional stationary target selection. in this paper, we introduce comet tails and target lock, two techniques that support the selection of moving targets. our goal is to facilitate accurate and fast selection of moving targets. we compare our two techniques to unassisted selection in a controlled experiment. the results show that for moving target selection, comet tails and target lock can outperform unassisted selection, and result in fewer errors. according to post-experiment questionnaires, participants indicate a stronger preference for assisted target selection with comet tails and target lock than unassisted selection.
species-appropriate computer mediated interaction. given the importance of our non-human companions, do we not want to extend social media to our nonhuman co-species? if "human computer interfaces" should be designed for "anyone. anywhere." (the theme of chi 2001), then why not for all species? recent pioneering efforts have shown that computer mediated interactions between humans and dogs, cats, chickens, cows, hamsters, and other species are technically possible. these efforts excite the imagination and challenge our understanding the basic nature of computer mediated interaction.
exploring the design of accessible goal crossing desktop widgets. prior work has shown that goal crossing may be a more accessible interaction technique than conventional pointing-and-clicking for motor-impaired users. although goal crossing with pen-based input devices has been studied, pen-based designs have limited applicability on the desktop because the pen can "fly in," cross, and "fly out," whereas a persistent mouse cursor cannot. we therefore explore possible designs for accessible mouse-based goal crossing widgets that avoid triggering unwanted goals by using secondary goals, gestures, and corners and edges. we identify four design principles for accessible desktop goal crossing widgets: ease of use for motor-impaired users, safety from false selections, efficiency, and scalability.
tangible sketching in 3d with posey. posey is a physical construction kit that is instrumented to capture assembly and configuration information and convey it to a host computer. we have used posey to build applications that deploy a reconfigurable physical model as a tangible interface for various domains. we demonstrate these applications to support a case for computationally enhanced construction kits as a semi-general interaction modality.
multilingual search strategies. we explored the search strategies of multilingual searchers, i.e., users who use multiple languages when searching for information. we wanted to understand factors that determine the language multilingual searchers choose to search in, if they switch languages within a search task, and if they encounter challenges when searching in a non-native language. our results indicate that availability and perceived quality of information were the primary reasons for searching in a non-native language. language switching within a search only occurred when information could not be found with the original search language. we also observed a language-related use case where the goal was not to find information in a typical sense, but rather to check for correct phrases in the non-native language using search engines. our research highlights several areas of future work for further understanding the multilingual search process.
on the internet, everybody knows you're a dog: the human-pet relationship in online social networks. the benefits of pet ownership to physical and mental health are extensive and well documented. online social networks have the potential to strengthen these relationships and build community among pet owners. in this work, we present several results on the difference in behavior between dog and cat owners in pet-oriented social networks. we extend this analysis to divisions between urban and rural users. our results show that there are significant differences among these groups. we propose a theory for future testing that more socially isolated the owners are from real-world communities of similar pet owners, the more active they are in forming social connections on these websites, and we offer initial evidence to support this. these results show that these pet social networks are already being used to help support the human-animal bond online, and that different types of pet owners would benefit from different types of support within the systems.
digital heritage. the india digital heritage project is a collaborative initiative between the industry and academia, with the aim of using novel techniques to efficiently capture and present various aspects of india's diverse heritage, while at the same time advancing the state-of-the art in related research areas. as part of the digital heritage project, we have built a prototype virtual tour of a south indian temple that, for the first time, integrates technologies such as photosynth and hdview, opening up new ways to interactively explore visually complex sites. these technologies are combined with audio, video and guided walkthroughs, to provide a compelling end user experience. the accompanying video highlights the key scenarios of our prototype.
multimodal programming environment for kids: a "thought bubble" interface for the pleo robotic character. we introduce a mixed physical and digital programming environment for children to control robotic characters. we present our design rationale, our initial prototype, report the results from our initial evaluation, and discuss ongoing work.
city browser: developing a conversational automotive hmi. this paper introduces city browser, a prototype multimodal, conversational, spoken language interface for automotive navigational aid and information access. a study designed to evaluate the impact of age and gender on device interaction errors, perceptions and experiences with the system along with physiological indices of workload is outlined. preliminary results, plans for further analysis and a larger scale user evaluation are presented.
supporting privacy by preventing misclosure. despite extensive concerns about privacy and multiple potential consequences of revealing personal information, many users still experience invasions of privacy when interacting with technology. for this reason, privacy is an important and complex issue in hci. this thesis focuses on specific psychological issues of privacy in hci, primarily the accidental disclosure of information or misclosure. using multiple methods including focus groups, a diary study, and an experimental manipulation, this thesis seeks to catalog the incidence of such errors, identify the interface issues associated with each type of error, and provide design recommendations for preventing each type of disclosure error.
tag trails: navigation with context and history. we describe a technique for preserving and presenting context and history while navigating web resources described by keywords. we use tagging and tag clouds as an application area for our technique. the technique is illustrated by employing it in a prototype that interfaces data from a social tagging website used to bookmark academic articles. the prototype displays a "tag trail" which can reveal contextual connections between web resources and the associated tags. we argue that the user's understanding of web resources is aided by making such connections explicit.
selective message distribution with people-tagging in user-collaborative environments. oftentimes, we would like to distribute call-for-participation messages by email to people who are potentially interested in the topics of the corresponding events. meanwhile, people either broadcast such messages to everyone in their organizations or maintain a number of mailing lists for different topics. but both approaches have drawbacks. in this paper, we explore the idea of automatically selecting recipients for broadcasting messages on different topics using people-tagging. in a collaborative people-tagging system, users can tag each other with the terms they want, and tags from different users are combined and aggregated. tags applied to a user usually describe the user's attributes, such as her affiliation, expertise, and the projects she has been involved in. we can thus effectively find interested recipients by matching the content of messages with people's tags. a prototype of our solution has been implemented for a real-world and large-scale people-tagging system in ibm.
toward an experimental methodology for studying persuasion-based online security. in this paper we highlight a controlled experimental design in development to investigate how the intersection of a brand's familiarity and persuasive appeal impact user willingness to engage in increased web security procedures. we offer the results of a 2 (source: familiar vs. unfamiliar brand) x 2 (persuasive strategy: benefit to user vs. benefit to site) web experiment (n=48) using this approach to demonstrate its viability and generate ideas for future directions. lessons learned and opportunities to improve this experimental methodology to further psychological research in the web security domain are discussed.
artful surfaces in design practices. a largely overlooked aspect of innovative design practices is how workplace surfaces play a role in supporting designers' everyday work. in this paper we introduce the idea of artful surfaces. artful surfaces (figure 1) are full of informative, inspirational and creative artefacts that help designers accomplish their everyday design practices. the way these surfaces are created and used could provide information about how designers work. we identify four types of artful surfaces: personal, shared, project-specific and live surfaces; and describe them using examples.
tactful calling: urgency-augmented phone calls through high-resolution pressure input on mobile phones. in this paper we present a system that simulates urgency-augmented phone calls on mobile phones. different scenarios and interaction techniques are discussed. we report a user study that indicates a general need for such a system and explored the applicability of using a force sensor as a way of intuitive call urgency articulation. the proposed system allows trying out urgency-augmented phone calls hands-on.
'phonephone': nfc phone as a musical instrument. this paper describes 'phonephone', an approach to create a musical instrument using a near field communication enabled mobile phone. designs of prototypes leading to the instrument are described in step by step fashion with an explanation of the rationale behind the instrument implementation. the result is a conceptual prototype, which can be used to play different sounds, e.g. piano and drums.
adapt: audience design of ambient persuasive technology. we discuss our experiences with applying participatory design methods to the development of a persuasive ambient display. by combining these two approaches, we hoped to engage community members in reducing environmental waste on our college campus. we describe our design process and rationale, the resulting design, lessons learned, and future research directions.
wii can do it: using co-design for creating an instructional game. there are many children for whom learning is difficult if they need to remain still. the nintendo wii, with its motion-controlled sensors, can support learning experiences that enable children to be physically active learners. this paper presents the methodologies and results from a multi-day, co-design session at the university of maryland's human-computer interaction lab. the goal of the sessions was to design an instructional game that leveraged the nintendo wii's motion controls to teach about u.s. national parks.
leveraging open-source software in the design and development process. this paper presents a case study of the nasa ames research center hci group's design and development of a problem reporting system for nasa's next generation vehicle (to replace the shuttle) based on the adaptation of an open source software application. we focus on the criteria used for selecting a specific system (bugzilla) and discuss the outcomes of our project including eventual extensibility and maintainability. finally, we address whether our experience may generalize considering where bugzilla lies in the larger quantitative picture of current open source software projects.
storytags: once upon a time, there was a photo. with the growing volume of digital information users must deal with, management and retrieval tasks have become increasingly problematic. a popular way to help users organize their information is tagging, as is the case in web sites such as flickr, delicious or youtube. unlike traditional hierarchically-based organization principles, tagging is less strict and easier to employ. however, it is not without its own problems. low tag reuse is just one of several issues that might hinder retrieval of a document or photo at a later time. we propose that narratives can provide a better way of tagging photos. describing a photo by telling a story about it may yield more and better tags, as information in stories is organized as a structured, coherent whole. we present a prototype web application, storytags, that allows users to tell stories to tag their photos, and then to use those stories to retrieve them.
user experience evaluation in the wild. this article details experience feedback resulting from a user experience study in the wild (i.e. in-situ). the system under test was a mobile device for skiers, which aimed at improving their users' experience. the skiers were equipped with a mini-camera, an accelerometer and a geo-localization system. thanks to a smartphone, they could replay, on trails, theirs best performances (video, maximum speed, ...). the article focuses both on the methodological and the technological issues encountered during these experimentations, and proposes recommendations.
senseablerays: opto-haptic substitution for touch-enhanced interactive spaces. this paper proposes a new haptic interaction system based on optical-haptic substitution. this system combines time-modulated structured light emitted to the workspace and a mobile or finger-mounted module consisting of a photo-detector with a tactile actuator. unlike other tactile feedback systems, it does not require any complicated mechanism for position sensing and tactile actuation. instead, it directly converts time-modulated structured light into haptic sensations. by sensing this light with a photo detector, users can feel this time-modulated light as haptic sensations. the system can easily add haptic feedback to a wide variety of applications, including surface computing systems and 3d interactive spaces.
take me home: designing safer in-vehicle navigation devices. in this paper we will propose a new design for a safer and more usable in-vehicle navigation system. in order to focus our design on safety and usability, we generated several design points based on prior research. from our design points, we are able to propose a design for a system which uses voice controls as the primary input modality, and the rear-view mirror as a heads-up display. in addition, we will propose displaying limited amounts of information to decrease the likeliness of a driver's focus straying away from the road. if we are able to show that our design is superior to current commercial navigation devices, we will continue to apply our design points and system design towards other aspects of in-vehicle information systems.
supporting intercultural collaboration with dynamic feedback systems: preliminary evidence from a creative design task. intercultural collaboration is often hampered by the manner in which teams communicate, or fail to com-municate, their ideas, concerns, and feelings. computer-mediated communication and the virtual nature of collaboration tend to exacerbate such communication issues into problems of conversation dominance, misattribution, and group conflict. new communication tools have the potential to mitigate some of these problems by augmenting individuals' and team's awareness of their communication inputs and processes. we explore how such feedback affects the communication content, attention distribution, and affective states of chinese and american collaborators engaged in a creative de-sign task. we describe our tool, present preliminary findings from an ongoing lab experiment, and discuss next steps in our research regarding ways of detecting the impact of real-time conversation feedback in inter-cultural collaboration environments.
enabling always-available input: through on-body interfaces. most current input devices require dedicated attention by our hands through physical transducers such as the keys on a keyboard. similarly, computer output is dominated by visual displays requiring most of our visual attention. while keyboards and monitors are effective i/o devices for dedicated computing activities, when our primary task is not using a computer, our hands may not be free to manipulate an input device. the goal of my dissertation is to explore how on-body interfaces can better support computing in our everyday activities.
designing cally, : a cell-phone robot. this proposal describes the early phase of our design process developing a robot cell-phone named cally, with which we are exploring the roles of facial and gestural expressions of robotic products in human computer interaction. we introduce non-verbal anthropomorphic affect features as media for building emotional intimacy between a user and a product. also, two social robot application ideas generated from brainstorming and initial participatory design workshop are presented with their usage scenarios and implementations. we learned from the pilot test that the prototyping and bodystorming ideation technique enabled participants to more actively take part in generating new ideas when designing robotic products.
enhancing input device evaluation: longitudinal approaches. in this paper we present our experiences with longitudinal study designs for input device evaluation. in this domain, analyzing learning is currently the main reason for applying longitudinal designs. we will shortly discuss related research questions and outline two case studies in which we used different approaches to address this issue. finally, we will point out future research tasks in the context of longitudinal evaluation methods.
dress for success: automating the recycling of school uniforms. in this paper we present the dress for success (d4s) system, a web-supported vending machine for school uniforms. the main goal of the d4s system is to encourage and facilitate the recycling of school uniforms by automating the exchange between parents and minimizing the work necessary to donate and obtain second-hand school uniforms. by creating a sustainable system that facilitates the reuse of this clothing, we hope to reduce both the environmental and monetary cost associated with current uniform purchasing practices.
developing shared home behavior datasets to advance hci and ubiquitous computing research. researchers in human-computer interaction and allied fields are increasingly interested in using new sensing capabilities to create context-aware interfaces and devices for the home. data from sensors worn on the body or installed in an environment can be used by algorithms to infer what activities the home occupant may be engaged in and enable applications to respond accordingly. this one-day chi'09 workshop would convene a multidisciplinary group of researchers to discuss strategies for creating community resources that might accelerate research on development of home technologies. in particular, the participants will discuss how to collaboratively gather high quality synchronized data streams from real homes, as well as qualitative material about home occupants and their behaviors. the resultant datasets could facilitate work on context modeling and enable researchers in other areas of hci to explore contextual factors influencing the use of technology in naturalistic settings. the outcome of the workshop will be a community index of existing shared datasets of home behavior and guidelines for those interested in creating and disseminating new datasets.
bubblewrap: a textile-based electromagnetic haptic display. we are investigating actuators that are able to provide different types of haptic sensations and that can be wrapped around a wide range of surfaces and objects. our first prototype, bubblewrap, consists of a matrix of electromagnetic actuators, enclosed in fabric, with individually controllable cells that expand and contract. it provides both active haptic feedback, using vibration, as well passive haptic feedback, using shape and firmness. an initial experiment demonstrated that users could reliably discriminate among the three firmness levels displayed on our prototype.
tracking behavior in persuasive apps: is sensor-based detection always better than user self-reporting? this paper aims to discuss the roles for the two types of tracking user behavior. considering these two types of tracking, sensor based recognition has a great advantage when sensing human activity, but it is not always adequate when tracking in the real world. in this paper, we compare the benefits and drawbacks of sensor-based tracking versus self-reported data in persuasive applications called ecoisland.
a material focus: exploring properties of computational composites. in this paper we build on the notion of computational composites, which hold a material perspective on computational technology. we argue that a focus on the material aspects of the technology could be a fruitful approach to achieve new expressions and to gain a new view on the technology's role in design. we study two of the computer's material properties: computed causality and connectability and through developing two computational composites that utilize these properties we begin to explore their potential expressions.
can an arg run automatically? alternative reality games (args) provide an interesting platform to explore the nature of game play as they combine fictional and real world elements to create a unique gaming experience. a typical arg plays over a set time span and players collaborate via an ongoing narrative orchestrated by 'puppet masters'. this paper presents a six week study based around an arg which was designed to be repeatable, allowing players to enter the game at anytime. through the use of temporal trajectories we analyse player's interactions and unveil a number of problems that hindered game play. the players lifestyle, pace and gameplay traits all impacted on the game and raises the question of whether a repeatable arg can really work. we close with some design pointers that might make it feasible.
product interest and engagement scale, beta (pies-beta): initial development. we report a work in progress: development and initial validation of the product interest and engagement scale (pies), a short assessment instrument measuring consumer interest in technology products. pies reflects an explicitly multidimensional, hierarchical, and extensible model of product interest. it assesses consumer product interest in terms of an overall interest scale plus three subscales assessing interest in features and choices, personal image as affected by a product, and interest in optimizing one's choice with regards to a product. we report factor structure in a sample of n=225 us consumers and replication with n=180 us consumers. the results establish reliability of the overall 12-item scale and subscales in a broad consumer sample (cronbach's alpha = 0.89 overall, 0.82-0.88 for subscales). validity measures in the validation sample demonstrate convergent and discriminant validity with product ownership and product involvement measures. we regard pies as currently being in beta form (pies-beta). it is suitable for usage now but will undergo further revision in 2009.
productive love: a new approach for designing affective technology. the importance of love is reflected in literature, movies and music, therefore it seems necessary to understand what role technology plays in relation to love and the roles it could to play in the future. we review studies related to love in hci and we identify a lack of consideration of philosophy as a background for love understanding. based on literature review, we offer a proposal of guidelines for designing technology that aims to improve loving relationships. besides, we explore principles of engagement with technology that may be important when designing love-promoting technology. finally we propose a practical design example.
age matters: bridging the generation gap through technology-mediated interaction. internet-based, mobile and pervasive technologies provide the means for older people to establish and maintain intergenerational relationships over long distances. however the significance of this intergenerational context has been largely ignored when considering potential interactions and the design of new technologies. this workshop aims to explore what the important issues are when considering intergenerational contact as a significant context for design. the overarching objective of this workshop is to identify key research themes in respect of intergenerational communication and its implications for the design of interactive systems.
enhancing brain-machine interface throughput using simultaneous activation detection. in this work, we investigate the viability of a novel combination of evoked responses as input signals for a general-purpose brain machine interface (bmi). we demonstrate response accuracy to alphanumeric stimuli in valid and mirror-reversed orientations, and show task-related activity differences correlated with rotation degree and character validity in superior parietal and inferior frontal gyrus regions of the brain. by observing simultaneous task-related activation in spatially dissociated regions, we increase the amount of information used for inferring user intent in control interfaces.
an fnir based bmi for letter construction using continuous control. a long term goal of assistive technology research is to build creative expression applications where subjects can extemporaneously express themselves. sketch drawing is one form of creative expression. in this work, we demonstrate the usability of a brain-machine interface (bmi) for expression using a letter drawing task. we describe empirical results that represent a first step toward assistive applications for creative expression.
local sensor: click to find and point to do. local sensor is a direction and distance tracking application using low power wireless connectivity. it enables new mobile user experiences bridging the physical and digital world. there are lots of challenges in user experience design since it is new for most end users. this paper introduces how the user experience design was conducted to make local sensor an appealing feature for mobile phone users.
analytics for the internet of things. this paper presents ongoing work on an approach to remotely observe the usage of connected products, analyze collected data and dynamically refine the observation mechanisms for better data. this allows for iteratively working towards the most elaborate, meaningful, and relevant representation of usage behavior in the form of structured and semantically annotated data traces. we show an implementation of the approach in the d'puis framework.
second skin: motion capture with actuated feedback for motor learning. second skin aims to combine three-dimensional motion tracking with real-time tactile feedback for the purpose of improving users' motor-learning ability. the system tracks a user's body and limb movements as he or she is performing an action, and the user is given automatic, real-time tactile feedback to aid in the correction of movement and position errors. a number of components integral to the motion tracking and tactile feedback systems must be bound to the user's body, and as such, an important goal is to design a lightweight and minimally inhibitive wearable suit that contains all of these elements.
creativity challenges and opportunities in social computing. there is a convergence in recent theories of creativity that go beyond characteristics and cognitive processes of individuals to recognize the importance of the social construction of creativity. in parallel, there has been a rise in social computing supporting the collaborative construction of knowledge. the panel will discuss the challenges and opportunities from the confluence of these two developments by bringing together the contrasting and controversial perspective of the individual panel members. it will synthesize from different perspectives an analytic framework to understand these new developments, and how to promote rigorous research methods and how to identify the unique challenges in developing evaluation and assessment methods for creativity research.
bringing usability to industrial control systems. i want to examine how domain-specific hci design patterns can be introduced into an existing software development process for industrial test systems. this paper describes the first findings of a contextual inquiry in the domain of test automation systems. based on these results, i will collect a set of patterns that are relevant to the field. in the future, these patterns will be applied in a real development process. the final aim is to investigate how the patterns can help the developers and product managers to make design decisions for the user interfaces of the developed software.
effects of spatial locations and luminance on finding and re-finding information in a desktop environment. we studied how spatial locations and luminance affect finding and re-finding information in a desktop environment. in an experiment conducted with computer icons, fixed locations led to more frequent accesses to icons while change of luminance led to worse recall of icon titles and locations. results are consistent with the notion that information search behavior is adaptive to the cost-benefit structure of the interface, and search strategies are adaptive to different external representations of icons. results also suggest that both external representations and human information processes are critical in determining the effectiveness of different gui designs.
a biologically inspired approach to learning multimodal commands and feedback for human-robot interaction. in this paper we describe a method to enable a robot to learn how a user gives commands and feedback to it by speech, prosody and touch. we propose a biologically inspired approach based on human associative learning. in the first stage, which corresponds to the stimulus encoding in natural learning, we use unsupervised training of hmms to model the incoming stimuli. in the second stage, the associative learning, these models are associated with a meaning using an implementation of classical conditioning. top-down processing is applied to take into account the context as a bias for the stimulus encoding. in an experimental study we evaluated the learning of user feedback with our learning method using special training tasks, which allow the robot to explore and provoke situated feedback from the user. in this first study, the robot learned to discriminate between positive and negative feedback with an average accuracy of 95.97%.
evaluating non-interactive domestic situated sms messaging. we present our evaluation of our sms-to-photo-frame messaging system in diverse households. we explored whether low-cost, non-interactive ambient displays were useful when applied to domestic messaging. we performed an ethnographic study with two different types of households, during which we analysed their usage of the system and conducted a series of interviews. we found that all households used the system to some degree, but that the social context and communication styles were distinctly different between households comprised of families and those with fictive kin. this highlights the importance of considering the household structure when designing domestic technology. additionally, our preliminary study explored the minimum requirements for a useful messaging appliance for the home, particularly with respect to interactivity.
supporting volunteer activities with mobile social software. many community organizations rely extensively on volunteer work. however, people who wish to help often have difficulties finding the time to volunteer. we are developing mobile social software that is intended to motivate users to volunteer and to help users find volunteering opportunities. in order to understand how technology might support volunteering, we interviewed 9 recent volunteers about their volunteer work. we report on their motivations to volunteer, obstacles to volunteering, and strategies they use to manage the demands of volunteering. we discuss how these factors are shaping the design of a mobile social application to support volunteering.
hyperlinking reality via camera phones. novel user interface concept for camera phones, demonstrated in this video, is based on state-of-the-art computer vision techniques. instead of typing keywords on a small and inconvenient keypad, the user just snaps a photo of his surroundings and objects on the photo become hyperlinks to information. the photo of the user's environment on the camera phone's screen thus becomes a natural interaction device allowing intuitive access to information with a simple tap of a finger.
fast finger tracking system for in-air typing interface. we developed a system which performs 3d motion tracking of human's hand and fingers from images of a single high-frame-rate camera and that recognizes his/her typing motion in the air. our template-matching-based method using hand textures reduces background effect and enables markerless tracking. in addition, use of a high-frame-rate camera enables recognition of rapid typing motion which is difficult to track using standard cameras. in order to realize real-time recognition, we developed hardware which parallelizes and accelerates image processing. as a result, we achieved real-time recognition of typing motion with the throughput of 138 fps (frames per second) and the latency of 29 ms.
give peace a chance: a call to design technologies for peace. peace is an extremely important value for humankind, yet it has been largely ignored by the computing and human-computer interaction community. this paper seeks to begin a discussion within the human-computer interaction community on how we can design technologies that have peace as an explicit goal. to begin this discussion, i review empirical studies on the factors that contribute to conflict and those that make conflict less likely. based on this, i identify areas where human-computer interaction research has already contributed to prevent conflict and promote peace, and open areas where our community can make a positive difference.
project chicago: green research. the "project chicago: green research" video showcases a technology concept for a sustainability analysis dashboard. this dashboard could be used with building information modeling (bim) software to provide architects, engineers and designers with real-time graphical feedback about the impact of their design decisions on the leed® (leadership in energy and environmental design) rating of a project. our goal was to showcase a highly graphic, interactive technology concept to evaluate water and energy reduction, indoor environmental quality, and carbon footprint impacts and give designers an immediate sense of the results of different building designs. using real scenarios from bnim: berkebile nelson immenschuh mcdowell architects' lewis and clark state office building in missouri, we portrayed a design team developing alternative concepts and improving their designs as measured by the us green building council's leed® rating system for green buildings. the proposed sustainability dashboard concept is demonstrated on a 6'x3' touch screen to explore its potential use as a collaborative tool. the dashboard was presented by autodesk® as a technology concept and it is not a commercially available product.
designing interfaces for presentation of opinion diversity. news aggregators rely on links and users votes to select and present subsets of the large quantity of news and opinion items generated each day. opinion diversity in the output sets can provide several benefits. we outline a range of diversity goals and discuss user reactions to a pilot implementation that selects for diversity as well as popularity. we then describe plans for research on alternative presentations and their impacts on users.
user experience evaluation: do you know which method to use? high quality user experience (ux) has become a central competitive factor of product development in mature consumer markets. although the term ux is widely used, the methods and tools for evaluating ux are still inadequate. this sig session collects information and experiences about ux evaluation methods used in both academia and industry, discusses the pros and cons of each method, and ideates on how to improve the methods.
phatics and the design of community. proposed thesis research uses twitter-a young channel for phatics communication-as a catalyst to promote community awareness and strengthen connections between members. this paper examines the phatic function, or messages about the communication channel, and its growing interest in hci research. examples of projects are described in the context of better understanding the role phatics play in community development.
auditory priming for upcoming events. psychologically preparing for upcoming events can be a difficult task, particularly when switching social contexts, e.g., from office work to a family event. to help with such transitions, the audio priming system uses pre-recorded audio messages to psychologically prepare a person for an upcoming event. in this system, audio priming is being used to prepare a person's state of mind to improve one's sociability in the upcoming social context.
the shared worlds of industrial design tu/e and philips research. in this exhibition booth at the design vignettes venue we show through projects, demos and information the joined worlds of the department of industrial design at the eindhoven university of technology and philips research, eindhoven. we show through the results of different joined and related projects, how we envision that design can transform society through intelligent systems, products and related services, and how we can and are educating a new type of designer who is working in the realm of ambient intelligence and who is able to join the worlds of design, engineering and science.
intentions: a game for classifying search query intent. knowing the intent of a search query allows for more intelligent ways of retrieving relevant search results. most of the recent work on automatic detection of query intent uses supervised learning methods that require a substantial amount of labeled data; manually collecting such data is often time-consuming and costly. human computation is an active research area that includes studies of how to build online games that people enjoy playing, while in the process providing the system with useful data. in this work, we present the design principles behind a new game called intentions, which aims to collect data about the intent behind search queries.
television on the internet: new practices, new viewers. television is increasingly viewed through computers in the form of downloaded or steamed content, yet computer based television consumption has received little attention in hci. in this paper we describe a study of the uses and practices of tech-savvy college students, studying their television consumption through the internet. we find that users personalize their viewing but that tv is still a richly social experience - not as communal watching, but instead through communication around television programs. we explore new possibilities for technology-based interaction around television.
integrating user experience into free/libre open source software: chi 2009 special interest group. the importance of software in daily life for casual and business purposes has led to a strong increase in the formal integration of usability in commercial software development processes. however, usability still appears to be largely an afterthought for free/libre/open source software (floss). the intent of this special interest group (sig) is to encourage participation by the user experience (ux) community and to identify solutions for better integration of ux into the floss development process.
flux: a tilting multi-touch and pen based surface. flux is an interactive touch-sensitive tilting surface that can be used either as a sketching board, as an interactive discussion table, and as a digital presentation whiteboard. the surface, based on a rear-projection screen, supports both multi-touch interaction as well as multiple pen interaction with individual identification of each pen. our setup combines two tracking technologies. for the hand-tracking, we take advantage of the frustrated total internal reflection (ftir) technology. for the pen-tracking, we are using the tracking technology developed by anoto.
the moral accountability of a personified agent: young adults' conceptions. this paper describes the preliminary results of a study conducted to answer the question: do users attribute moral accountability to personified agent technologies? a pilot study was conducted in which 20 college students interacted with a personified agent, were insulted by the agent, and observed a researcher interacting and insulting the same agent. a semi-structured interview was conducted to investigate the participants' judgments of the observed interactions. results suggest that most users will hold a designer, programmer or creator responsible for moral violations enacted by the personified agent, rather than attributing accountability to the agent itself.
p-recognition: you are already recognized. the user's intention is reflected in not only the actual input action but the ones immediately before it as well. "p-recognition"" recognizes the preceding actions, and predicts the intention just when the actual action starts. this paper tests p-recognition in a pen-based map navigation interface as an example, where the map is panned by user's dragging strokes and zoomed by user's enclosure by a circle. the feasibility of the proposal is confirmed in an experiment. we find that dragging and circling actions are distinguishable before the pen touches the screen. moreover, for some users we can recognize their intention to write text. it is confirmed that the user's intention is present in the preceding actions and so is detectable.
puyosheet and puyodots: simple techniques for adding "button-push" feeling to touch panels. two simple techniques for touch-panel based portable information devices are proposed. a soft-gel based transparent film named "puyosheet" placed over a touch panel provides button-push feeling to the fingertips. another configuration, soft-gel based small dots, named "puyodots", is attached to the backside of a handheld device provides button-edge and button-push feelings to the fingertip(s) that hold the device. preliminary evaluations indicate that proposed techniques improve "usability" and "preference" without deteriorating input speed or error rate compared with an ordinary touch panel device.
using language tests and emotional expressions to determine the learnability of artificial languages. the study described hereunder lies within the context of a larger project focusing on the design and implementation of a "robotic interaction language". the research goal of this project is to find the right balance between the effort necessary from the user to learn a new or artificial language and the resulting benefit of robust communication between a robot and the user as a direct consequence of optimized speech recognition. to measure the first criteria we have explored two methods to evaluate language learnability, namely language tests and analyzing expressed emotions during interaction in an artificial language. our results indicate that both have potential in being used as measurement tools for evaluating the learnability of artificial languages.
map torchlight: a mobile augmented reality camera projector unit. the advantages of paper-based maps have been utilized in the field of mobile augmented reality (ar) in the last few years. traditional paper-based maps provide high-resolution, large-scale information with zero power consumption. there are numerous implementations of magic lens interfaces that combine high-resolution paper maps with dynamic handheld displays. from an hci perspective, the main challenge of magic lens interfaces is that users have to switch their attention between the magic lens and the information in the background. in this paper, we attempt to overcome this problem by using a lightweight mobile camera projector unit to augment the paper map directly with additional information. the "map torchlight" is tracked over a paper map and can precisely highlight points of interest, streets, and areas to give directions or other guidance for interacting with the map.
improving with age: designing enduring interactive products. this study explores people's relationships with digital and non-digital objects in the home--with an eye toward the ways in which products improve rather than deteriorate over time--and how this knowledge might inform the design of more enduring and sustainable interactive products. we report our research in progress and provide a collection of initial design themes and design concepts inspired by user studies.
web-active users working with data. mashups have emerged as an area of interest for end-user programming research. while many users may find the ability to develop mashups useful, there are still many barriers to locating interesting data, figuring out how to "mash" it together and creating a useful view of the result. furthermore, there is still much to learn about the motivations and needs of the user. in this paper, we present the results of interviews and think-aloud studies of non-programmers working with xml data and a mashup building tool. this work aims to better understand the users' mental models as they first attempt to use a novel mashup tool. we identify key areas where breakdowns occur and propose a future path for research.
readingmate: an infrared-camera-based content stabilization technique to help joggers read while running on a treadmill. though reading could be a useful activity while a jogger runs on a treadmill, reading while running can be quite tiresome. in order to alleviate this difficulty, we developed a content stabilization technique, called ""readingmate,"" using head-tracking to track the location of the jogger's head/eyes and relocate the position of the contents on a screen, so that the contents appear to be stabilized. we conducted an experiment with ten participants, and eight out of ten reported positive experiences in using readingmate. thus, readingmate could be a potential solution for joggers who would like to read while running, and possible future work is also discussed.
the accidental tutor: overlaying an intelligent tutor on an existing user interface. intelligent tutoring systems (itss) have been shown to have dramatic impact on student learning [9]. however, these gains have been mostly in topics in which the interface has been designed with the intelligent tutor in mind. this research investigates the hci challenges that result from creating two model-tracing itss for use with existing interfaces. we describe overlaying a tutor on an image-editing program and a web-based application. we highlight three main hci challenges: 1) integrating a problem scenario in the context of the existing application, 2) providing learners with appropriate feedback during task performance, and 3) allowing learners to explore the interface while making sure they complete the task.
crowd computer interaction. hci had moved from considering how individuals interact with computers to thinking about how groups collaborate using technology. while there has been research focused on large-scale on-line communities, little attention has been paid to large groups of collocated assemblies, namely crowds. the evidence from social psychology and sociology suggest that the social dynamics and behaviours of crowds are distinct from those of smaller group formations. in this workshop we want to think about new opportunities for designing crowd-centric technologies and explore the factors that will shape interaction design for large scale crowd computing. the workshop will explore themes related to crowd-centric computing through hands-on crowd-based exercises, position papers and discussion.
exploring effectiveness of physical metaphor in interaction design. one direction of the emerging paradigm of interface design is the use of physical metaphors, the adoption of physical phenomenon from the real world with physical principles such as gravity or inertia. to explore effectiveness of physical metaphors in interaction design, we conducted an exploratory study by selecting one specific task where a physical metaphor was applied with physics: searching for a phone number in a contact list using an inertial scroll method with a mouse and touch screen interface environment. the result from this initial study showed that employing a physical metaphor does not always guarantee an improvement of performance; a different effect can be drawn according to the interaction style.
designing a privacy label: assisting consumer understanding of online privacy practices. this project describes the continuing development of a privacy label to present to consumers the ways organizations collect, use, and share personal information. several studies have indicated the importance of privacy for consumers, yet current mechanisms to present privacy policies of websites have not been successful. this research addresses the present gap in the communication and understanding of privacy policies, by creating an information design that improves the visual presentation and comprehensibility of privacy policies. drawing from the nutrition, warning, and energy labeling, as well as from the effort towards creating a standardized banking privacy notification, i present the process and ongoing results of the development of a usable information design for privacy policies.
detecting cognitive and physical stress through typing behavior. monitoring of cognitive and physical function is central to the care of people experiencing or at risk for various health conditions, but existing solutions rely on intrusive methods that are inadequate for continuous tracking. this research explores the possibility of detecting cognitive and physical stress by monitoring keyboard interactions with the eventual goal of detecting acute or chronic changes in cognitive and physical function. preliminary results indicate that it is possible to classify cognitive and physical stress conditions relative to non-stress conditions based on keystroke and text features with accuracy rates comparable to those currently obtained using affective computing methods. the proposed approach is attractive because it requires no additional hardware, is unobtrusive, is adaptable to each user, and is very low-cost.
perceived productivity and the social rules for laptop use in work meetings. people multitask with laptops in organizational meetings and this may impact a team's productivity and group dynamics. this paper discusses the results from fieldwork at a fortune 500 software development company and survey data from a sample of 40 information workers across the united states on the topic of technological multitasking in group meetings. preliminary results suggest that there is a perceived loss of productivity when using laptops during meetings and that the type of meeting is the strongest determinant for when technological multitasking occurs.
impad: an inexpensive multi-touchpressure acquisition device. recently, there has been great interest in multi-touch interfaces. these have taken the form of optical systems such as microsoft surface and perceptive pixel's ftir display as well as hand-held devices using capacitive sensors such as the apple iphone. however, optical systems are inherently bulky while capacitive systems are only practical in small form factors and are limited in their application because they only respond to human touch. we have created a technology that enables the creation of inexpensive multi-touch pressure acquisition devices (impad) which are paper-thin, flexible and can easily scale down to fit on a portable device or scale up to cover an entire table. these devices can sense varying levels of pressure at a resolution high enough to sense and distinguish multiple fingertips, the tip of a pen or pencil and other objects. other potential applications include writing pads, floor mats and entry indicators, bio-pressure sensors, musical instruments, baby monitoring, drafting tables, reconfigurable control panels, inventory tracking, portable electronic devices, hospital beds, construction materials, wheelchairs, sports equipment, sports clothing and tire pressure sensing.
more than kimchi and cash: designing for cultural identity. this project was motivated by one question: can products be instruments for designing and shaping culture? we know that there are products that can destroy a culture. for example, the nazis created sophisticated products to annihilate groups of people. more recently, many of the visually impaired have complained about not being able to hear hybrid vehicles before crossing the street. if certain products are destructive to a culture, can other ones enhance it? my hypothesis is that there are products or a class of products - centered around appropriate activities - that can support an environment for people to participate and shape. this project focuses on a specific cultural environment and the impact a product could have in facilitating relationships and participation in that context.
quickies: the future of sticky notes. in this paper, we present 'quickies', an attempt to bring one of the most useful inventions of the 20th century into the digital age: the ubiquitous sticky notes. 'quickies' enriches the experience of using sticky notes by linking hand-written sticky notes to the mobile phones, digital calendars, task-lists, e-mail and instant messaging clients. the project explores how the use of artificial intelligence (ai), natural language processing (nlp), rfid, and ink recognition technologies can make it possible to augment physical sticky notes that can be searched, located, can send reminders and messages, and more broadly, can act as an i/o interface to the digital information world.
can machines call people?: user experience while answering telephone calls initiated by machine. current state-of-the-art spoken dialog systems are aimed at handling telephone calls to automate incoming caller requests. in this paper we explore a scenario which is symmetric to a traditional human-initiated interaction. we report on an initial qualitative study focusing on the opposite type of interaction, i.e. when automated agents place telephone calls to recipients that request interactive dialog from the recipients. the study consisted of 16 telephone calls to participants placed by a simulated agent, followed by debriefing interviews with the participants. the data gained in the study were analyzed to identify factors that influence the acceptance of such calls.
lessons from participatory design with adolescents on the autism spectrum. participatory user interface design with adolescent users on the autism spectrum presents a number of unique challenges and opportunities. through our work developing a system to help autistic adolescents learn to recognize facial expressions, we have learned valuable lessons about software and hardware design issues for this population. these lessons may also be helpful in assimilating iterative user input to customize technology for other populations with special needs.
workshop on end user programming for the web. in the past several years, there has been a resurgence in research activity in end user programming (eup), all focused on the web. this work is spread across a variety of institutions and has been published in a variety of conference venues, including chi, uist, iui, and www. this workshop will bring these researchers together for a common discussion, with the following goals:establish a sense of community amongst researchers in this area; discuss common problems and lessons learned about doing research in eup for the web; define a standard corpus of tasks that can be used to evaluate current and future eup systems; and plan the publication of an edited book on the topic of end user programming for the web.
cost-effective wearable sensor to detect emf. in this paper we present the design of a cost-effective wearable sensor to detect and indicate the strength and other characteristics of the electric field emanating from a laptop display. our electromagnetic field detector bracelet can provide an immediate awareness of electric fields radiated from an object used frequently. our technology thus supports awareness of ambient background emanation beyond human perception. we discuss how detection of such radiation might help to "fingerprint" devices and aid in applications that require determination of indoor location.
the science of fun. this video details the principles underlying our company's player experience research project on behalf of electronic arts for their latest game, spore. electronic arts employees discuss the benefits of the "simulated native environment" methodology as compared to focus groups, and scott rigby, ceo of immersyve inc., describes the pens (player experience of need satisfaction) metrics, which were used to gather quantitative feedback in this study.
activenotes: computer-assisted creation of patient progress notes. we present activenotes, a prototype application that supports the creation of critical care notes by physicians in a hospital intensive care unit. activenotes integrates automated, context-sensitive patient data retrieval and user control of automated data updates and alerts into the note-creation process. in a user study at new york presbyterian hospital, we gathered qualitative feedback on the prototype from 15 physicians. the physicians found activenotes to be valuable and said they would use it to create both formal notes for medical records and informal notes. one surprising finding is that while physicians have rejected template-based clinical documentation systems in the past, they expressed a desire to use activenotes to create personalized, physician-specific note templates to be reused with a given patient, or for a given condition.
research ethics in the facebook era: privacy, anonymity, and oversight. ethical standards for human subjects research have not kept up with new research paradigms. several research areas are particularly problematic for the chi community. online social research is testing the boundaries of public observation, third-party disclosure, and anonymization methods. furthermore, there are differences in norms about what is and is not ethical among various research disciplines studying the web. this sig brings together members of the chi community who are interested in research ethics for studying the web. we invite seasoned veterans from industry and academia, educators, and newcomers to the field to share their experiences and advice, ask questions, and to form an interest group that can help shape university and corporate best practices for online research.
evaluating weight perception using digital facial-image feedback. in this paper we describe the mophmed study, a joint effort between technologists and doctors to explore the effects of facial image modification on children's body image and on parental support for children's healthy dietary and physical activity behaviors.
designing a wearable social network. this paper presents a framework and design for a wearable social network based on facebook. we begin with a discussion of social networking by isolating key characteristics of social interactions in three research areas: social networking sites, mobile computing, and wearable computing. these characteristics are analyzed to suggest a design framework that can be applied to the design of social networks. using this framework, we have designed and created a wearable social network called patches, which extends the social interactions available in most wearable devices today.
grounding geovisualization interface design: a study of interactive map use. building the most effective tools to support user-centered geographic visualization faces a significant challenge: not enough is known about how people interact with maps. map use research has often focused on higher order use goals or cognitive interpretations of static map representations. in order to address the problem of understanding foundational user-map interaction behavior, we are studying user interactions in complex geovisualizations, with an initial focus on analysis tasks. this paper describes an exploratory user study to examine general interaction issues with complex map visualizations. our results highlight the need for map tools to improve interactivity and support basic analysis tasks to aid users in decision making.
letting tools talk: interactive technology for firefighting. in this work-in-progress report we present the results of a preliminary analysis of a set of fieldwork studies conducted in collaboration with a firefighter school and a firefighter brigade. to inspire the design of ubiquitous computing systems, we provide a description of the equipment used by firefighters, practices built upon them and a set of common properties.
supporting family engagement in weight management. as obesity is increasing in many countries, helping people manage their weight has become an important issue. medical research has shown that the family context may be important to promote lifestyle changes. our work aims at designing a collaborative environment to engage a family in support of an individual needing to manage his or her weight. this paper presents the first step in our iterative design process which aimed at collecting information about the needs of overweight and obese people, and about the type of environment they would find useful for them and their family.
treasurehunter: a system to increase the reuse of local used goods. increasing the reuse of locally available consumer goods is one way to make consumption more sustainable. we present treasurehunter, a system to help consumers find and share used goods available at thrift stores in their local area. treasurehunter enlists frequent thrift store shoppers to help find requested items for those who lack the time or inclination to search for the items themselves. incentive-centered design was used to craft a solution to fit the needs of all types of shoppers. treasurehunter consists of an online community that is also accessible from mobile phones so that it can be used while at a thrift store. the proposed system works best on smartphones, though any internet-capable phone could also be used. by motivating more people to buy used goods instead of new, everyone can benefit as consumers pay less for the goods they desire and fewer resources are wasted in the transportation and consumption of new goods.
emotional experience on facebook site. although user behavior in the popular facebook social network site has been intensely investigated since the site came live in 2004, we know little about users' emotions and values weaved in the fabric of their interactions. we report on a diary study for collecting daily accounts of users' most memorable experiences. outcomes emphasize the distinction between public and private presentation together with user motivation for engaging in each of these roles. findings also suggest that at their heart, people's most memorable experiences with facebook are all about positive emotions, in particular those concerned with connectedness and entertainment.
tailoring websites to increase contributions to online communities. many online communities experience insufficient contributions from their members. in order to encourage contributions to the community, we examined a website tailoring approach to fit a community's website interface with the motivations of the community. in particular, we used the characteristics of other websites as a method of gauging user motivation. we built two different websites with financial and altruistic themes, and conducted an online experiment with 122 users to test the impact of both segmenting and tailoring on contributions to a recycling community. preliminary results show that both tailoring and segmenting techniques were effective with altruistic users.
visualization and interaction techniques for mobile devices. this paper presents ongoing work toward the development of one-handed interaction techniques for mobile devices with a small touch-screen. this work comprises three main parts: the analysis of the state of the art, the development and the evaluation of novel interaction techniques, a proposal of tools that would help designing new techniques. this paper presents the work that has been already performed on the first two phases and some ideas for developing the last phase.
investigating computer game immersion and the component real world dissociation. in this paper we describe research being conducted to investigate the experience of computer game immersion, in particular the component "real world dissociation".
some statistical analyses of chi. in this paper i show a variety of ways to represent and think about statistical aspects of chi and its sister conferences. in particular, i look at author counts, gender analysis, and representations of repeat authors. i use these visualizations to motivate questions about what the preferred state of chi should be. for example, should we strive for gender equality at chi, and if so, why, and if not, why not? should we encourage the current trend of increasing number of authors per paper, or might we be loosing something in that process? i do not hope to answer these questions, but rather to encourage their discussion.
localbuy: a system for serving communities with local food. we seek to make local and sustainably produced food available and easy to buy by linking consumers with local producers of meat, vegetables, fruit, and much more. our dynamic website will enable buyers to purchase fresh and healthy food directly from the manufacturers of these products, contributing to local economy. we are advantageously positioned to help farmers avoid the middlemen, the wholesalers, the big box stores and allow them to meaningfully connect with their consumers.
metamouse: multiple mice for legacy applications. single display groupware (sdg) solutions have been used to create software for disadvantaged children, particularly in the developing world. sdg allows for greater utilization of the limited infrastructure available to these kids. however, sdg faces challenges in working with legacy applications. our technology, called metamouse, takes a step toward an integrated multi-user application by allowing users to collaborate within unmodified legacy educational software. we conducted a preliminary qualitative user study of our technology with educational software in schools around bangalore, india. we found that metamouse is easily learned, encourages collaborative discussion among students, and allows for the use of existing educational applications with no modification.
diy for chi: methods, communities, and values of reuse and customization. people tinker, hack, fix, reuse, and assemble materials in creative and unexpected ways, often codifying and sharing their production process with others. do-it-yourself (diy) encompasses a range of design activities that have become increasingly prominent in online discussion forums and blogs, in addition to a small-but-growing presence in professional/research forums such as chi. this workshop will explore diy practice from the ground up--examining diy as a set of methods, communities, values and goals and examining its impact in the domains of traditional crafts, technology development, and sustainable design.
ten steps of integrating user feedback into the product definition process: a closed loop approach. an appropriate and timely integration of results from user feedback studies into product definition and development efforts is an important but challenging goal. in this paper we describe some best practices and processes at sap which are facilitating this integration. they are based on several years of experience of applying user centered design principles to sap business bydesign software.
what can user experience learn from food design? this panel will bring together a group of user experience experts, with a group often overlooked in the art and science of user experience -- food designers. the panelists will include: two james beard award-winning chefs, a user experience practitioner, and a world-renowned hci academic. together, the panel will compare and contrast concepts from food design and user experience including the challenges of meeting demanding end-user needs, and best practices from food design that one could potentially apply to the design of everyday things.
social groups, social media, and civic participation of high school youth: concepts and methods for design implications. high school social groups (e.g., "jocks" and "nerds") and social media (e.g., instant messaging and social network sites) are prominent in the lives of high school students. social groups affect what high school students find acceptable doing. however, little is known about how social groups affect students' shaping of civic and political selves, or whether social media bridge social relationships across distant high school social groups and engender positive spill-over effects for civic participation. this socio-technical mixed methods study is positioned at the intersection of high school social groups, uses of social media, and students' participation in extracurricular activities, with particular interest in civic participation. design implications will be drawn from analysis of three data sets: a student questionnaire with sociometric questions, interviews, and observations of students' daily activities. conceptual and methodological contributions to the hci literature are discussed.
aurally and visually enhanced audio search with soundtorch. finding a specific or an artistically appropriate sound in a vast collection comprising thousands of audio files containing recordings of, say, footsteps, gunshots, and thunderclaps easily becomes a chore. to improve on this, we have developed an enhanced auditory and graphical zoomable user interface that leverages the human brain's capability to single out sounds from a spatial mixture: the user shines a virtual flashlight onto an automatically created 2d arrangement of icons that represent sounds. all sounds within the light cone are played back in parallel through a surround sound system. a gpu-accelerated visualization facilitates identifying the icons on the screen with acoustic items in the dense cloud of sound. test show that the user can pick the "right" sounds more quickly and/or with more fun than with standard file-by-file auditioning.
tangible message bubbles for children's communication and play. we introduce tangible message bubbles, a new composition and communication tool that invites youngsters to express and record their everyday expressions, play with these original recordings, and share these personal creations with their friends and family. we present a design rationale that focuses on supporting both co-located and remote collaboration, and on balancing play with tool design. results from pilot evaluations with our initial prototypes informed us with ways to leverage the physical properties of the toys and support playful exploration of children's recorded video messages for sharing.
designing for families. in this special interest group (sig) we plan to focus on discussions and activities surrounding the design of technologies to support families. many researchers and designers study domestic routines to inform technology design, create novel interactive systems, and evaluate these systems through real world use. bringing together researchers, designers and practitioners interested in technologies for families at a sig provides a forum for discussing shared interests including methods for gaining an understanding of the user, metrics for evaluating interventions, and shared definitions of the concept of the family.
a personalized walk through the museum: the chip interactive tour guide. more and more museums aim at enhancing their visitors' museum experiences in a personalized, intensive and engaging way inside the museum. the chip1 (cultural heritage information personalization) project offers various online and mobile tools to the users to be their own curators, e.g. browsing the online collections, planning personalized museum tours, getting recommendations about interesting artworks to see, and quickly finding their ways in the museum. in this paper we present the new version of the personalized museum guide2 offered on a mobile device in the physical museum space. we maintain a dynamic user model to ensure high relevance of recommended artworks and museum tours and in this way (1) support personalized interaction both online and in the museum and (2) provide an intuitive bridge between the online and on-site experiences. we apply semantic web technologies to enrich the museum collection and guarantee serendipity, novelty and relevance of the recommendations.
bezier lights: establishing virtual boundaries in indoor environments. in this paper we introduce bezier lights, an intelligent lighting system that allows users to intuitively establish virtual boundaries in indoor environments. boundaries can be easily created/modified by arranging the layouts of disk-shaped devices ("stones") on the building floor. the immediate purpose of the system is to assist users in incorporating location-aware capabilities into private properties, esp. individual households and offices, with the longer-term goal of serving as a key component in our vision of "synthetic space" -- architectural space of the future where all building elements (walls, windows, etc.) can be dynamically reconfigured in real time.
automatic storytelling in comics: a case study on world of warcraft. this paper presents a development of our comic generation system that automatically summarizes players' actions and interactions in the virtual world. the feature of the system is that it analyzes the log and screenshots of a game, decides which events are important and memorable, and then generates comics in a fully automatic manner. also, the interface of our system allows users to customize their own comics. as a result, users can easily use the system to share their stories and create individual comics for archival purposes or storytelling.
saltate!: a sensor-based system to support dance beginners. we present saltate!, a wireless prototype system to support beginners of ballroom dancing. saltate! acquires data from force sensors mounted under the dancers' feet, detects steps, and compares their timing to the timing of beats in the music playing. if it detects mistakes, saltate! emphasizes the beats in the music acoustically to help the dancing couple stay in sync with the music.
cell phone software aiding name recall. senior citizens often find it difficult to remember names. this paper describes a novel cell phone application that uses information about one's social network and the places one frequents to suggest the names of individuals one might plausibly encounter in a particular place. we anticipate that this "names prosthesis" will help senior citizens to improve socialization, functional memory and levels of autonomy. we motivate the need for this application space before describing our design process, first implementations, and early testing and iterative improvement of both the concept and the implementation.
design an interactive visualization system for core drilling expeditions using immersive empathic method. in this paper, we propose an immersive empathic design method and used it to create an interactive high-resolution core visualization system for real-world geological core drilling expeditions. a high domain knowledge barrier makes it difficult for a person from outside this field to imagine the user experience simply through observation. the globally distributed nature of the core drilling community imposes further design constraints. we used this approach to embed a computer scientist trained as a junior core technician. this process allowed the developer to experience authentic user activities and enabled the design of an innovative system for solving real-world problems. this approach made the best use of precious co-located opportunities, overcame the initial domain knowledge barrier, and established a trust relationship between the developer and the domain scientists. the system designed through this approach formed a sustainable and adaptive foundation that the domain scientists can build on. through in-situ deployment, observation and interview evaluations from on-going expeditions, we present the advantages of this process.
designing interactive information access technologies for small scale rural indian farmers. more than 60% of the indian population resides in rural areas with agriculture as the main profession. although small scale rural indian farmers possess deep knowledge about traditional agricultural practices, they oftentimes lack immediate, contextual and real time access to vital information such as the current state of the agro-market, making the right choice of pesticides and fungicides for pest management, weather conditions, and knowledge about newly introduced agricultural tools, techniques and practices. in this paper, i report the preliminary findings of an ongoing contextual user research study conducted in three different indian villages in maharashtra state. this research is targeted to uncover a deeper understanding of the information needs of indian rural farmers through field observations and interviews, as well as to guide the human-centered design of potential information and communication technology (ict) solutions to cater to the information needs of small scale rural farmers in india.
rethinking the esp game. the esp game was designed to harvest human intelligence to assign labels to images - a task which is still difficult for even the most advanced systems in image processing. however, the esp game as it is currently implemented encourages players to assign "obvious" labels, which can be easily predicted given previously assigned labels. we present a language model which can assign probabilities to the next label to be added. this model is then used in a program, which plays the esp game without looking at the image. even without any use of the actual image, the program manages to agree with the randomly assigned human partner on a label for 69% of all images, and for 81% of images which have at least one "off-limits" term assigned to them. we discuss how the scoring system and the design of the esp game can be improved to encourage users to add less predictable labels, thereby improving the quality of the collected information.
natural throw and tilt interaction between mobile phones and distant displays. to provide intuitive ways of interacting with media data, this research work addresses the seamless combination of sensor-enabled phones with large displays. an intuitive basic set of tilt gestures is introduced for a stepwise or continuous interaction with both mobile applications and distant user interfaces by utilizing the handheld as a remote control. in addition, we introduce throwing gestures to transfer media documents and even running interfaces to a large display. to improve usability, data and interfaces can be thrown from a mobile phone to a distant screen and also fetched back to achieve mobility. we demonstrate the feasibility of the interaction methods with several advanced application prototypes facilitating a natural flow of interaction.
a comparative study of interaction metaphors for large-scale displays. large-scale displays require new interaction techniques because of their physical size. there are technologies that tackle the problem of interaction with such devices by providing natural interaction to larger surfaces. we argue, however, that large-scale displays offer physical freedom that is not yet being applied to interaction. to better understand how distance affects user interaction, we present a comparative study of interaction metaphors for large-scale displays. we present three metaphors: grab, point and mouse. the metaphors were included in our tests as we felt that each would be more suited to a specific distance: this is the focus of our tests. we then asked the users to solve a puzzle using those metaphors from different distances. we discovered that the point metaphor achieves better results on all tests. however, there is evidence that grab and mouse remain valid for specific tasks.
understanding user needs for conceptual design phases of architecture projects. this paper describes design research methods used to understand user needs, identify user requirements and create new conceptual design workflows for an existing architectural software application.
live recruiting on the web. this animated video describes the concept of recruiting participants for remote user research.
supporting carers in their caring role through design. carers are people who look after family, partners or friends who could not manage without them because of frailness, illness or disability. our contribution is to show the potential for design to support carers in their vital caring role, focusing on health information sharing. we describe why it is important to recognise and consider carers in the design of home health monitoring technology, and why it is important to help carers maintain their health and well being. we present design guidelines for home monitoring technology. these guidelines are distilled from a survey distributed to carers in a rural part of scotland on health information sharing. we used these guidelines to design a new home monitoring system called @hand. the main difference with current systems is the focus on facilitating information sharing between cared-for and carer rather than cared-for and health professional.
"i felt more of a member of this class": increasing students' sense of community with video commenting. public displays are typically situated in strategic places like town centers, and in salient positions on walls within buildings. however, currently most public displays are non-interactive and are typically used for information broadcasting (tv news, advertisements etc). people passing by pay little attention to them. as a consequence, public displays are under-utilized in the everyday world. we are investigating whether use of interactive public displays might increase people's interaction with one another, with a resulting increase in sense of community. in this paper we describe the design and first deployment experiences of a platform-independent, interactive video commenting system using a large public display in two sections of a large-enrollment university class. our preliminary evaluation suggests that students enjoyed the activity of commenting, that they participated a great deal, and that their sense of community was greater after using the system. we discuss lessons we have learned from this initial experience, and describe further work we are planning using this and similar interactive activities.
device ecology mapper: a tool for studying users' ecosystems of interactive artifacts. this paper presents a tool for both researchers and designers called the device ecology mapper, which allows users to share devices they own and describe to researchers how they believe these devices are connected. we built this tool from the theoretical perspective of ecology of artifacts in which designed artifacts do not exist independently, but rather in complex ecosystems with other artifacts through physical and perceptual connections. we designed the evaluations of this tool to evaluate the extent to which designers found the tool valuable and users found the tool true to the way they understand their ecology of interactive artifacts-rather than how closely user's perception of their ecology represents how these devices are actually connected. we found evidence for both perspectives from these studies.
wattbot: a residential electricity monitoring and feedback system. electricity production emits carbon dioxide and other gases into the atmosphere, adversely influences global climate change, depletes limited natural resources, and negatively impacts the lives of those who live near power plants. we designed a residential electricity monitoring and feedback system called wattbot, that allows users to track their home energy usage and encourages them to reduce consumption. our solution is an application for the apple iphone and ipod touch that receives data from a wireless hub, allowing users to view, compare and analyze their electricity usage over time.
stress outsourced: a haptic social network via crowdsourcing. stress outsourced (sos) is a peer-to-peer network that allows anonymous users to send each other therapeutic massages to relieve stress. by applying the emerging concept of crowdsourcing to haptic therapy, sos brings physical and affective dimensions to our already networked lifestyle while preserving the privacy of its members. this paper first describes the system, its three unique design choices regarding privacy model, combining mobility and scalability, and affective communication for an impersonal crowd, and contrasts them with other efforts in their respective areas. finally, this paper describes future work and opportunities in the area of haptic social networks.
mifresh: promoting local produce consumption. in this paper we introduce mifresh, a grocery store system consisting of a large display and individual kiosks that aims to increase the demand of local produce. in cities like detroit, where poverty and health are major concerns, increasing consumption of local produce can help create local jobs, sustain the environment, and improve health. we used rapid contextual design to analyze detroit's existing food system and, based on our findings, iteratively design a solution. mifresh uses proven techniques such as coupons and rewards points programs and delivers education and awareness about the importance of consuming local produce. user testing results among the target population are promising.
comm.unity: leveraging social and physical proximity. comm.unity is a new software platform implementing a wireless, device-to-device information system that bypasses the need for any centralized servers, coordination, or administration. a key feature of this platform is the fact that it combines knowledge, awareness, and learning of the user's social relationships and integrates this information into the communication protocols and network services. comm.unity is designed to work on as many devices as possible, and with as many different radios as possible (wifi, bluetooth, ir, etc.). it is designed as a platform over which many different networked applications could be developed with ease, from the bottom layers of the network all the way up to the user interface. in this short movie we present some use cases for comm.unity based applications, including the "social dashboard" -- a readily usable control for one's digital aura -- as well as a brief working demo showing an image propagate across multiple devices.
understanding teamwork in high-risk domains through analysis of errors. trauma care is an example of dynamic, complex, and safety-critical teamwork. the staff in trauma centers works under time pressure and lacks effective information technologies to support teamwork and reduce errors. this work presents a qualitative study that looked at the teamwork errors and their causes to better understand the challenges in providing computerized support for this user group.
making sense of accelerometer measurements in pervasive physical activity applications. in the last few years, accelerometer-based entertainment and health applications have been receiving increased attention in the research and commercial worlds. the effect of accelerometer placement on different parts of the body, despite its apparent significance, received little consideration. this paper documents through experimentation the different characteristics of accelerometer output on the waist, arm, wrist, thigh, and ankle in the context of translational body motion (walk). furthermore, it offers experimental formulas that transform peripheral body measurements to more reliable, center body (i.e., waist) measurements, and these in turn to caloric measurements, which are the standard physical activity units. the importance of these results on the design of ubiquitous health applications and the ensuing user experiences cannot be underestimated. the paper's methodology can be used in further studies in other physical activity contexts, where more elaborate body motion patterns are involved.
opportunities for actuated tangible interfaces to improve protein study. we outline strategies for actuated tangible user interfaces (tuis) to improve the study of proteins. current protein study tools miss fundamental biology concepts because graphical and symbolic interfaces do not allow users to intuitively manipulate complex physical forms. actuated, tangible tools may enhance understanding at all levels of protein study. to advance tui awareness of protein study, we present an overview of protein concepts and current protein study tools. thirty-six protein researchers, engineers, professors and students recommend design guidelines for tangible interfaces in protein study, and we outline research directions for tuis to improve protein study at all educational levels.
weigh your waste: a sustainable way to reduce waste. an increased concern for the environment has brought about an arena to develop and experiment with new devices to support sustainable design. the 'weigh your waste' (wyw) device will allow the user to monitor their waste charges and provide a platform for the user to learn and explore areas such as: recycling, reusing old items, how to make compost and many other green activities. some districts are encouraged to recycle by paying for their waste according to its weight. similarly, some businesses are subject to a 'pay by weight' scheme. the wyw system proposes to tackle issues for users in these schemes. however, users that are not subject to these schemes can still benefit from the device by using it as a learning tool.
designing for email response management. email is the most widely used form of computer-mediated communication. and replying to messages is one of the main activities email interfaces need to support. in this paper we address the problems users face when managing emails that need a reply. previous work has found that users have difficulty remembering to reply to messages when they postpone response, and have trouble re- finding messages they want to respond to. we review related work on email management, and describe three designs developed to facilitate email response management.
end user software engineering: chi: 2009 special interest group meeting. end users create software whenever they write, for instance, educational simulations, spreadsheets, or dynamic e-business web applications. researchers are working to bring the benefits of rigorous software engineering methodologies to these end users to try to make their software more reliable. unfortunately, errors are pervasive in end-user software, and the resulting impact is sometimes enormous. this special interest group meeting will bring together the community of researchers who are addressing this topic with the companies that are creating and using end-user programming tools.
simplified user interfaces for design and user testing of architecture software applications. in this paper we describe the value of creating simplified user interfaces for architectural software applications intended for use in early conceptual design phases. by reducing the interface the team was able to solicit specific feedback about new tools without the overhead or pre-conceptions associated with using an existing software platform. as a result, the team was able to iterate rapidly on specific problems.
occlusion-aware menu design for digital tabletops. in this paper, we describe the design of menus for multi-user digital tabletops. on direct input surfaces, occlusions created by the user's hand decrease interaction performance with menus. the key design criteria are to avoid these occlusions and to adapt the menu placement to the user's handedness and position on the tabletop. we present an adaptive menu placement method based on direct touch and pen tracking that allows correct menu placement around the table. as an extension, we propose adding a gesture input area for fast interaction which can be partly occluded by the user's hand.
predicting query reformulation during web searching. his paper reports results from a study in which we automatically classified the query reformulation patterns for 964,780 web searching sessions (composed of 1,523,072 queries) in order to predict what the next query reformulation would be. we employed an n-gram modeling approach to describe the probability of searchers transitioning from one query reformulation state to another and predict their next state. we developed first, second, third, and fourth order models and evaluated each model for accuracy of prediction. findings show that reformulation and assistance account for approximately 45 percent of all query reformulations. searchers seem to seek system searching assistant early in the session or after a content change. the results of our evaluations show that the first and second order models provided the best predictability, between 28 and 40 percent overall, and higher than 70 percent for some patterns. implications are that the n-gram approach can be used for improving searching systems and searching assistance in real time.
time sequences. visualisations of dynamic data change in appearance over time, reflecting changes in the underlying data, be that the development of a social network, or the addition or removal of a device node in an ad-hoc communications network. as viewers of these visualisation tools, it is up to us to accurately perceive and keep up with the constantly shifting view, mentally noting as visual elements are added, removed, changed and rearranged, sometimes at great pace. in a complex data set with a lot happening, this can be a strain on the observer's comprehension, with changes in layout and visual population disrupting their internalised "mental model" of the data, leading to errors in perception. we present time sequences, a novel dual visualisation technique which dilates the flow of time in the visualisation so that observers are given proportionally more time to understand changes based on the density of activity in the visualisation.
web search and browsing behavior under poor connectivity. web search and browsing have been streamlined for a comfortable experience when the network connection is fast. existing tools, however, are not optimized for scenarios where connectivity is poor, as is the case for many users in developing regions where fast connections are expensive, rare, or unavailable. this study examined how users' web search and browsing behavior differs when the connection is slow, and whether users employ techniques to alleviate the problem. in a preliminary study involving 15 subjects on a university campus in kerala, india, we identify unique mitigating behaviors of users who routinely suffer low-bandwidth or intermittent connections. we examine the challenges faced by these users and find that existing web search and browsing infrastructure is simply incapable of providing a good experience. finally we outline potential design improvements.
an education-friendly construction platform for wearable computing. wearable computing and e-textiles has a lot of potential as an educational computing topic. they allow students to exercise their creativity and imagination while learning about concepts in computing and technology. however, there are still numerous difficulties involved in deploying existing technology in an educational environment. in this paper, we present the teeboard, a construction platform for e-textiles and wearable computing that is designed to be robust, reliable, easy to construct and to program. it has also passed initial tests in a practical workshop for high school students.
interacting with ehealth: towards grand challenges for hci. while health records are increasingly stored electronically, we have little access to this data about ourselves. we're not used to thinking of these official records either as ours or as something we'd understand if we had access to them in any case. we increasingly turn to the web, however, to query any ache, pain or health goal we may have before consulting with health care professionals. likewise, for proactive health care, such as nutrition or fitness, or post diagnosis support, to find fellow-sufferers, we turn to online resources. there is, it seems, a potential disconnect between points at which professional and proactive health care intersect. such gaps in information sharing may have direct impact on practices we decide to take up, the care we seek, and the support professionals offer. in this panel, we consider several places within proactive, preventative health care in particular hci has a role towards enhancing health knowledge discovery and health support interaction. our goal is to demonstrate how now is the time for ehealth to come to the forefront of the hci research agenda.
towards new metrics for multitasking behavior. in this paper we propose new metrics to investigate computer-based multitasking behavior. these metrics range from a very lean dichotomous variable to a very rich measure based on switches that combines user, task and technology considerations. we demonstrate how to calculate these measures with an exploratory study based on self-reported user logs. the development of new metrics to research multitasking behavior lays the foundation to incorporate this variable in future studies of human-computer interaction.
design and adoption of social collaboration software within businesses. social networking and collaboration sites are having a large impact on people's personal lives. these same applications, similar functions and related experiences are being adopted within businesses. this special interest group will address the issues around social collaboration software in the business setting. what is the value for the business and its users? how do you measure success? what strategic design and user experience issues are key for successful adoption? what roles do user experience professionals play in this type of social system?
emotion barometer of reading: user interface design of a social cataloging website. reading fiction is many people's favorite pastime. there is no denying that one of the needs of human beings is to share what they read and understand other readers' feelings about the books they have read. recent developments in web 2.0 technologies characterizing personalized information organization have led to an interest in social tagging behavior of a variety of items, such as books, images, web pages, videos, etc. however, a major issue with this kind of application is that tags are growing in an uncontrolled manner. in fact, it is chaos. several studies have recognized the existence of affective tags, but there is no user interface designed to separate affective tags from other tags. to address that affective tags are navigation aids for readers, this work gives an account of design of a novel interface for visualization of affective tags at a social cataloging website, librarything.com.
shiftr: a user-directed, link-based system for ad hoc sensemaking of large heterogeneous data collections. we present a novel method and prototype system to help users make sense of and reorganize large amounts of heterogeneous information. our work is grounded in theories of categorization from cognitive psychology and is designed for ad hoc sensemaking; that is, supporting people's shifting goals and flexible mental representations of concepts. shiftr adapts a carefully chosen belief propagation algorithm from large-scale graph mining to efficiently assist users in interactively clustering information of arbitrary types. the system functions effectively with few human-labeled examples, and supports the use of both positive and negative examples. we demonstrate shiftr's utility through sensemaking scenarios, one of which uses the dblp bibliography dataset, which contains more than 1.7 million author-paper relationships.
predicting shoppers' interest from social interactions using sociometric sensors. marketing research has longed for better ways to measure consumer behavior. in this paper, we explore using sociometric data to study social behaviors of group shoppers. we hypothesize that the interaction patterns among shoppers will convey their interest level, predicting probability of purchase. to verify our hypotheses, we observed co-habiting couples shopping for furniture. we have verified that there are sensible differences in customer behavior depending on their interest level. when couples are interested in an item they observe the item for a longer duration of time and have a more balanced speaking style. a real-time prediction model was constructed using a decision tree with a prediction accuracy reaching 79.8% and a sensitivity of 63%.
hci for the real world. hci as a field comfortably and unquestionably links itself with the corporate world. what does this mean in terms of an ethics of problem choice, meaning the considerations that influence what types of design projects hci researchers consider as important? using the work of the industrial designer victor papanek, i foreground the agency of the designer. by undertaking a close reading of a recent publication of a major corporate research lab, i examine what important social and political aspects are missing from their vision of the future. i end by examining the work of the design team anthony dunne and fiona raby, describing how hci can be involved in the formation of new forms of subjectivity that are not subservient to a market-based ideology.
social mediating technologies: developing the research agenda. social mediating technologies (smts) range from e-mail to social networking sites and community websites. the popularity of these technologies is increasing rapidly, yet we have little understanding about how and why people find these technologies so appealing. the research challenge is to try to understand the causal drivers for usage of social technologies, and theory-based understanding of how the affordances of such technologies meet with people's cognitive and social needs. this workshop will provide a forum for researchers to synthesise current knowledge on smts and map out future research directions.
emotional gaze behavior generation in human-agent interaction. gaze behavior plays an important role in face to face communication in that it conveys nonverbal information and emotional intent beyond speech. this research proposes a computational framework for generating emotional gaze behavior in a virtual agent, concentrating on analysis and synthesis of primary and intermediate emotions through gaze behavior. we utilize parameters picked from the au-coded facial expression database and real-time eye movement data (pupil size, blink rate and saccade) to model primary emotions and describe a rule-based approach to generate intermediate ones.
the design of viva: a mixed-initiative visual vocabulary for aphasia. in this paper, we present the design of viva, a visual vocabulary for aphasia. aphasia is an acquired language disorder that causes variability of impairments affecting individual's ability to speak, comprehend, read and write. existing communication aids lack flexibility and adequate customization functionality failing to address this variability and to satisfy individual user needs. we tackle these shortcomings by incorporating adaptive and adaptable capabilities in viva which is designed to assist communication for users suffering from aphasia. the visual vocabulary for aphasia implements a novel approach that organizes the words in the vocabulary according to user preferences, word usage and certain semantic measures, thus continuously tailoring the tool to the user's profile.
film as invisible design: the example of the biometric daemon. film is an accessible medium that can be used naturally to elicit comment and critique. in this sense film can be as the natural language for experience design. we are developing a series of experimental films that can convey user-experience without explicitly depicting the object that generates that experience. in doing this, we are building upon the idea (well rehearsed in the scientific debate about mental imagery) that some visual representations can be inexplicitly non-committal about the presence or absence of certain objects or features. our films are explicitly non-committal about the objects they describe -- in the sense that the devices are deliberately kept hidden or invisible to the user. we present one such film that captures a security device we call a biometric daemon -- essentially an electronic pet that thrives on biometric signals. crucially, the daemon is never shown in the film, while the relationship between the daemon and the user is made apparent.
uncertainty visualization: why might it fail? there is a gulf between the rhetoric in visualization about the importance of uncertainty, and the practice of visualization in which uncertainty is rarely seen other than as a laboratory exercise. we reflect on why something viewed as fundamental in science and engineering is rarely if ever adopted in visualization practice. our analysis is informed both by research progress and by our own experience in an ongoing industrial case study on modelling and mapping underground assets, where it would appear that uncertainty plays a major role. in this case study, we try to identify promoting and limiting factors. we conclude that the value of uncertainty visualization is severely limited by the quality and scope of uncertainty data, by the limited confidence in the data itself, and by the perceptual and cognitive confusion that the depiction of this data can generate. we hope to broaden the discussion on the utility of uncertainty in visualization from the purely technical and perceptual issues to social and organizational factors.
evaluating new interactions in healthcare: challenges and approaches. new technologies for supporting the provision of healthcare are increasingly pervasive. while healthcare computing previously referred to a desktop computer within the consulting room, we are now seeing an ever broader range of software, hardware and settings. this workshop is concerned with how to conduct evaluations which allow assessment of the overall impact of technology. the workshop will explore challenges and approaches for evaluating new interactions in healthcare. in this paper we outline the goals for this workshop and summarize the issues and questions it intends to explore.
recognizing and using goals in event management. personal event management involves planning when, where and how events should occur, making sure the event's prerequisites are satisfied, and developing contingencies for when things go wrong. conventional calendar and project management tools, however, only record and visualize explicit human decisions regarding event specifics. we present event minder, a calendar program that takes into account the goals for which the events are scheduled. users can input descriptions of events in natural language, mixing high-level objectives, concrete time and place decisions, and omit "obvious" common sense details. a commonsense knowledge base provides sensible defaults, and machine learning refines these defaults with experience. we can make recommendations for alternative plans, including alternatives that satisfy higher-level goals in different ways as well as those that meet immediate constraints. our current system covers dining-related events, integrating commonsense with domain knowledge about specific restaurants, bars and hotels.
when user experience met agile: a case study. in mid-2007, one part of the technology organization at our company decided to develop a very large project using scrum, an agile programming methodology. the decision to go with scrum was made from a software development perspective and how the user experience (ux) teams doing the design work would fit into that methodology was not clear. as a result, the ux teams faced many challenges and we have had to evolve our approach to how ux teams work with development scrum teams. this case study details our ux teams' experiences working with scrum for the past 18 months, describing the challenges and issues that we faced, and the solutions that we implemented to resolve those issues. we recommend best practices for ux teams working in scrum, particularly in a fast-paced and large corporate environment. we hope that others can avoid the common pitfalls that we faced in our initial adjustment to agile and scrum.
investigating the impact of a minimalist in-home energy consumption display. we investigated the impact of a minimal in-home energy consumption display (ecd), both stationary and portable versions, on household energy awareness and consumption. we deployed the ecd in eight homes for three weeks each, providing half of the participants with a portable version and the others with a stationary one. this work presents an account of each user's experience through pre- and post-surveys, power meter data, and post-deployment interviews and results of the study, which show that users reduced energy consumption by identifying high-power devices in their home and by playfully setting conservation goals.
building support for multi-session tasks. in two previous studies, we explored how users perform multi-session web tasks using the currently available tools. we also proposed three guidelines to help developers design browser support for these types of tasks. in this paper, we describe three prototypes that we designed using these guidelines and present the results of a preliminary evaluation.
heat, fire and temperature: the industrial revolution and hci. hci has many challenges and internal debates (for example, where is our theory? what is the role of design in hci? what is the relationship between research and practice? how do we make an impact?) that recur at the chi conference and that students either ask themselves or find they are asked by others. this paper takes a historical look at this issue and describes some of the discoveries made during the industrial revolution about heat, fire and temperature (the development of thermodynamics) and how these discoveries were made. the parallels to human-computer interaction today are explored with two primary intentions: - to show how important it is that we continue to debate and investigate the precise nature of concepts we take for granted (e.g. usability, user interfaces, user experience), and to illustrate how practice contributes to the development of theoretical concepts.
nextslideplease: navigation and time management for hyperpresentations. slide-ware presentations typically involve an uninterrupted progression of bulleted slides introduced by a lone figure before a passive audience. this format does not encourage active discussion or facilitate improvisational presentation of material. two studies were conducted to evaluate how presenters author, rehearse for and deliver presentations. from these studies, feature recommendations for a prototype hyperpresentation system were developed.
a tool to study affective touch. touch is an important part of many forms of emotional communication, but has been studied far less than visual and auditory expressions of affect. we are developing the haptic creature to investigate fundamentals of affective touch, and its applications in companionship and anxiety management. this small robot senses the world solely by being touched, and communicates its internal state via vibrotactile purring, stiffening its ears, and modulating its breathing. this paper outlines the motivation for its creation and design, and overviews the current version of its architecture and mechatronics.
body-based interaction for desktop games. interaction for desktop games is mostly limited to keyboard and mouse input. we are investigating the benefits of adding body-based interaction to complement keyboard and mouse interaction in desktop gaming. we present a proof-of-concept implementation of body-based navigation for the game world of warcraft, and a formative evaluation to test the feasibility of this kind of interaction. our observations provide evidence that body-based interaction in addition to keyboard and mouse can help players perform more tasks at the same time and can be especially attractive and helpful to new players. our study also revealed design consideration for this type of interaction.
inphase: a communication system focused on "happy coincidences" of daily behaviors. to supplement existing forms of communication such as telephone and e-mail, this research proposes a new method of communicating "awareness" between people who are separated by long distances. in this paper, we investigate cases where coincidences in daily behaviors lead to casual conversation and thus intimacy and togetherness. we propose a new method of communicating these "happy coincidences" between a pair of remotely located houses. by equipping furniture and appliances such as doors, sofas, refrigerators and televisions with sensors, we developed a system where these items are connected to remote equivalents and their near simultaneous use is communicated.
micro-blogging as online word of mouth branding. in this paper, we report research results investigating micro-blogging as a form of online word of mouth branding. we analyzed 149,472 micro-blog postings containing branding comments, sentiments, and opinions. we investigated the overall structure of these micro-blog postings, types of expressions, and sentiment fluctuations. of the branding micro-blogs, nearly 20 percent contained some expressions of branding sentiments. of these tweets with sentiments, more than 50 percent were positive and 33 percent critical of the company or product. we discuss the implications for organizations in using micro-blogging as part of their overall marketing strategy and branding campaigns.
the effect of affective iconic realism on anonymous interactants' self-disclosure. in this paper, we describe progress in research designed to explore the effect of the combination of avatars' visual fidelity and users' anticipated future interaction on self-disclosure in emotionally engaged and synchronous communication. we particularly aim at exploring ways to allow users' self-disclosure while securing their anonymity, even with minimal cues of a virtual human, when users anticipate future interaction. the research investigates users' self-disclosure through measuring their behaviors and feelings of social presence in several dimensions. design and implementation of the stimulus materials and equipments are complete and data collection has begun.
wantknot: connecting organizations to improve their waste management practices. commercial businesses represent a large portion of all waste generation; furthermore, their waste streams are large and consistent enough to provide a steady resource to other organizations that can use the waste as inputs for their own processes. however, businesses find it difficult to connect with other organizations, especially those in different industries. we conducted a user-centered design process in which we interviewed 17 local organizations, built an affinity diagram, and devised personas and scenarios. using this information, we designed a social network, wantknot, which allows businesses to find other local organizations interested in absorbing some of their waste streams. based on a preliminary round of usability testing, we found that wantknot connects businesses in valuable ways, and in doing so, reduces waste and transportation resources.
montage: a platform for physically navigating multiple pages of web content. montage is a platform for rendering multiple pages of web content on large tiled displays (several desktop lcds arranged in a spatially contiguous matrix). we discuss the advantages of data visualization using a newsstand metaphor, showing many content items at once and allowing users to quickly refine visual searches by walking (physically navigating) closer to specific data on the display. we have used montage to build three applications that demonstrate the variety of applications that are possible on this platform. these applications have benefits for both everyday use and as research tools.
eek! a mouse! organic user interfaces: tangible, transitive materials and programmable reality. in this panel, we explore the role emerging transitive materials, like flexible thin-film displays, multi-touch input skins, e-textiles, micro-actuators and claytronics might play in re-defining the human interface towards a programmable form of reality. panelist will extrapolate historical trends from tangibles to new developments in organic user interfaces, trying to identify a future in which interfaces will no longer be predominantly flat, but instead have any possible shape or form: from skins that are foldable, flexible and physical to three-dimensional products that are fully kinetic.
sensemaking workshop chi 2009. how does one make sense of a large or complex task? by the term "sensemaking" we mean the processes people go through to frame, collect, organize and structure information to help understand a problem. sensemaking is what people do to get from the earliest phases of an information collecting and organizing task to the conclusion. sensemaking tasks are commonplace, and this workshop is dedicated to understanding the range of sensemaking behaviors and systems that can support sensemaking.
using tactile rhythm to convey interpersonal distances to individuals who are blind. this paper presents a scheme for using tactile rhythms to convey interpersonal distance to individuals who are blind or visually impaired, with the goal of providing access to non-verbal cues during social interactions. a preliminary experiment revealed that subjects could identify the proposed tactile rhythms and found them intuitive for the given application. future work aims to improve recognition results and increase the number of interpersonal distances conveyed by incorporating temporal change information into the proposed methodology.
cheese cam: unconscious interaction between humans and a digital camera. in everyday life, humans interact with many products. in many of these interactions, a person performs an action with, toward, or in the vicinity of a product and then the product reacts to that action. in this paper, however, the opposite interaction pattern, where a product performs an action to induce a user reaction, is presented by a new camera, 'cheese cam', concept. cheese cam is a camera that can induce unconscious facial reactions in a photography subject, based on mirror neuron theory and facial mimicry theories. a small facial expression icon displayed on cheese cam's screen induces unconscious facial reactions in the subject. experiments were conducted to investigate the effects of cheese cam on the facial reactions of subjects, and the results are discussed in this paper. through this study, we explored possibilities of unconscious interaction.
tangibles for children, : the challenges. a significant proportion of research in the field of tangible interaction involves children. a common aspiration is to offer benefits through tangibility, related to ease of use and overall user experience while also support learning and developmental processes. however, evaluation results are often equivocal, and expectations of researchers not always verified. this workshop aims to attract researchers who approach this topic of tangibility and children from an empirical or design perspective. the purpose is to obtain a good picture of what benefits we expect tangibility to provide (including novel and future applications), establish what is the current empirical evidence to support such claims (or what is missing), and motivate appropriate evaluation methodologies for children.
head-movement evaluation for first-person games. a first-person view is often used in games to enhance players' sense of presence. camera movements are added to provide a walking sensation when the player is moving around. several variations of camera movement are used in current games to simulate head movement. this work aims to evaluate these different types of camera movements by measuring subjective responses of users when exposed to them. in this first stage of research, five important movements were identified, and evaluated in a pair-wise fashion, resulting in subject preferences that contradicted our initial hypothesis.
design models for interactive problem-solving: context & ontology, representation & routines. we describe and illustrate a new framework for the design of interactive problem-solving based on recent research on the psychology of distributed cognition.
chistory. how might the world view human-computer interaction a century from now? in this video, set one hundred years in the future, we playfully re-envision the early history of hci. as the video opens, the great usability cataclysm of 2068 has erased all previous knowledge of hci. the world has been plunged into an age of darkness where terror, fear, and poor usability reign. unearthing fragments of previously lost archival footage, a disembodied hci historian (jonathan grudin) introduces a first attempt to reconstruct the history of our field. pioneering systems like nls and sketchpad are reviewed alongside more recent work from chi and related conferences. the results may surprise and perplex as much as they entertain, but most of all, we hope they inspire reflection on the past and future of our field.
co-located collaborative web search: understanding status quo practices. co-located collaborative web search is a surprisingly common activity, despite the fact that web browsers and search engines are not designed to support collaboration. we report the findings of two studies (a diary study and an observational study) that provide insights regarding the frequency of co-located collaborative searching, the strategies participants use, and the pros and cons of these strategies. we then articulate design implications for next-generation tools that could enhance the experience of co-located collaborative search.
whole body interaction. in this workshop we explore the notation of whole body interaction. we bring together different disciplines to create a new research direction for study of this emerging form of interaction
warp speed design: a rapid design method for use with children. this paper introduces a new design method - warp speed design - for use with older children (aged 9+) for the design of workable tangible games. the rationale for the method is presented and then a workshop, in which the method was evaluated, is described. the method introduced children to basic programming concepts and worked surprisingly well. almost all of the designs made by the children were so well specifies at the end of the brief workshop that they were able to be developed with very little uncertainty.
multitouch and surface computing. natural user interfaces (nui) such as multitouch and surface computing are positioned as the next major evolution in computing and user interfaces. just graphical user interfaces (guis) brought unprecedented interaction capabilities to their command-line predecessors, we believe multitouch and surface computing will spawn novel ways to interact with media and improve social usage patterns. since experimentation and deployment are currently limited, the exploration of applications and interfaces in this area is still at an early stage.
do hci and nlp interact? we examine the relationship between hci and natural language processing (nlp) by performing a bibliometric analysis and looking at the specific example of bionlp. we identify opportunities for hci to fertilise current nlp research and suggest that hci will benefit from looking at advances in nlp more closely.
agile user experience sig. agile development is being adopted by companies with greater frequency every year, resulting in changes to the way user experience practitioners work. unfortunately, there has been little guidance on how to incorporate user centered design (ucd) into the agile process so most practitioners either struggle alone or seek out others in the same boat. the goal of this sig is to draw upon the shared experience of these practitioners to uncover the best practices for agile user-centered design to facilitate optimal product development.
writing to your car: handwritten text input while driving. for in-car navigation, information and entertainment systems, text input is increasingly important. we investigate handwriting as a text input modality and assess where to best position the input surface and how to provide feedback. for this purpose, we created different prototypes that allow text input on the steering wheel and in the central console, as well as visual feedback on the input surface and on the dashboard. the results of the study indicate that handwritten text input on the steering wheel is well-received by the users and that the visual feedback should be presented in the dashboard area or on the steering wheel. we also observed that the number of corrective actions and the remaining errors were significantly smaller (25% less) on the steering wheel than in the central console and that entering text while driving made people drive slower.
comparing emotions using acoustics and human perceptual dimensions. understanding the difference between emotions based on acoustic features is important for computer recognition and classification of emotions. we conducted a study of human perception of six emotions based on three perceptual dimensions and compared the human classification with machine classification based on many acoustic parameters. results show that the six emotions cluster differently according to acoustic features and to perceptual dimensions. acoustic features fail to characterize the perceptual dimension of valence. more research is needed to find acoustic features that have a close relation to human perception.
three environmental discourses in human-computer interaction. a review of the past decade of human-computer interaction relating to environmental issues identifies three discourses whose commitments and assumptions have consequences for the design of new interfaces and interactive systems: sustainable interaction design, re-visioning consumption and citizen sensing. it suggests two promising directions for future research: participatory design and infrastructure.
spore player research outtakes. this video contains outtakes from a player experience research study for electronic arts' spore. users played a working build of spore while communicating with moderators who were stationed in a remote observation room; media streams from the game, webcam, and voice chat were captured and synced for later analysis.
mental workload in multi-device personal information management. knowledge workers increasingly use multiple devices such as desktop computers, laptops, cell phones, and pdas for personal information management (pim) tasks. the use of several of these devices together creates higher task difficulty for users than when used individually (as reported in a recent survey we conducted). prompted by this, we are conducting an experiment to study mental workload in multi-device scenarios. while mental workload has been shown to decrease at sub-task boundaries, it has not been studied if this still holds for sub-tasks performed on different devices. we hypothesize that the level of support provided by the system for task migration affects mental workload. mental workload measurements can enable designers to isolate critical sub-tasks and redesign or optimize the user experience selectively. in addition, we believe that mental workload shows promise as a cross-tool, cross-task method of evaluating pim tools, services and strategies, thus fulfilling a need expressed by several researchers in the area of personal information management. in this paper, we describe our ongoing experiment of measuring mental workload (via physiological as well as subjective measures) and its implications for users, designers and researchers in pim.
interacting with temporal data. time serves as a basis for measuring the occurrence and evolution of natural phenomena, and governs the coordination of many of our everyday life activities. as the capacities of our digital tools have grown, they have begun to make readily available to us unprecedented quantities of new, rich, structured temporal information about the people and things in our lives. this abundance of information has laid open avenues for new tools and applications - applications which, in turn, introduce new demands on interface mechanisms used to display, represent and interact with temporal data. this workshop, the second in a series on capturing, interacting with and visualizing temporal data, will focus on such demands, examining interaction challenges emerging across new application domains.
global mapping of usability labs and centers. this paper will highlight the global spread of usability expertise by presenting data on the location of usability testing centers and laboratories around the world. the possibilities for future expansion of the database and global networking of usability expertise and knowledge will be discussed.
at your service: using butlers as a model to overcome the mobile attention deficit. advances in mobile phones and cellular network capabilities have enabled many opportunities for information access on the move. these capabilities provide instant access for the mobile user, but have exacerbated the problem of interaction in a mobile context. mobile users are often engaged in another task that makes it difficult for them to filter and interact with their mobile device at the same time. mobile multitasking creates an attention deficit for the user. this paper proposes using butlers as a model to overcome this problem by offloading the burden of interaction from the user to the device. we describe how a suite of butlers can opportunistically and proactively offer information to the user in the moment, allowing mobile users to stay focused on their task at hand.
fault lines of user experience: the intersection of business and design. one of the central challenges of the user experience discipline has always been how early in the development cycle it can exert any degree of influence. the challenge that our field is facing today more pronounced than ever is how to influence the decision makers that give directions guiding individual product development. and vice versa, this early decision making process can benefit from user experience approaches that help ground its direction in user research, and inform its decisions creatively through concepts and design thinking -- see for example the concept of business design™ (as taught by the rotman school of management, with similar approaches being the foundation of successes such as design consultancies like ideo). the goal of the panel will be to draw together a community of experts and interested audience members in this topic and initiate a discourse on its key issues and opportunities.
lessons from brain age on persuasion for computer security. users generally have difficulty understanding and managing computer security tasks. we examined nintendo's brain age games for ways to help users remember more secure passwords. instead, we found design elements that encouraged users to continually perform cognitive tasks that would otherwise be tedious. this paper discusses these elements using existing persuasive technology principles, and explores how they could be leveraged to make computer security tasks easier and more engaging.
overcoming challenges in mobile ux research methods and tools. judging by the year-by-year increasing number of chi publications on mobile research methods and tools, it is clear that the community is currently rapidly innovating on tools, infrastructure, and methods for mobile user experience (ux) research. to reflect on this development, this sig extends the workshop, "mobile user experience research: challenges, methods & tools" [8], and will open up the discussion to a wider group of practitioners and researchers.
location and the web: (locweb 2009). location-based services are becoming increasingly web-based, as a result of the availability of networked mobile devices and mobile internet access. the "location and the web (locweb)" workshop targets the capabilities and constraints of web-based location-based services, which can be implemented as browser-based applications, or as native applications using web services. the focus of this chi workshop is on approaches which handle the complexity of location-based services, specifically looking at location abstractions, location sharing, context-relevant information, privacy issues, and interface and interaction design. the goal of this workshop is to serve as a starting point for attaining a better understanding of how the web has to change in order to embrace location as a first-level concept, and how these changes might be reflected in applications and user interfaces that transform the web into a platform for location-based services.
figuring out the "one thing" that will move ux into a position of strategic relevance. a common question asked of successful user experience (ux) leaders is what "one thing" they needed to do in order to move their organizations into a position of strategic relevance. however, the answers often vary, posing a challenge to those struggling to figure out how to achieve the same goal where they work. in this interactive session, a subset of answers will be highlighted, then real-world scenarios from around the globe -- most presented by recruited conference attendees -- will be evaluated to determine which "one thing" should be attempted in each case. the process of figuring that out will be explicitly addressed so that session attendees can leave better able to do so themselves for their own situations.
investigating web search strategies and forum use to support diet and weight loss. healthcare is shifting from being reactive to preventive, with a focus on maintaining general wellness through positive decisions on diet, exercise, and lifestyle. in this paper, we investigate search behavior as people navigate the web and find support for dietary and weight loss plans. inspecting the web search logs of nearly 2,000 users, we show that people progressively narrow their searches to support their progress through these plans. interestingly, people that visit online health forums seem to progress through the plans' phases more quickly. based on these results, we conducted a survey to further explore the roles and importance of online forums in supporting dieting and weight loss.
ibookmark: locative texts and place-based authoring. with the recent developments in epaper technology, consumer ebook readers have display qualities and form factors that are approaching that of traditional books. these ebook readers are already replacing paper in some commercial domains, but the potential of ebooks to extend forms of writing and storytelling has not been significantly explored. using the digital and dynamic characteristics afforded by ebook readers, we are developing ibookmark, a gps-enabled ebook reader. in ibookmark, writers can create stories that change in response to the location of the ebook itself. by setting context variables based on current and past locations of the ebook reader and using these in the rule-based generation of text and illustrations. we are developing new rhetorical device for writers that extend the expressive range of ebook delivered stories.
computational creativity support: using algorithms and machine learning to help people be more creative. the emergence of computers as a core component of creative processes, coupled with recent advances in machine-learning, signal-processing, and algorithmic techniques for manipulating creative media, offers tremendous potential for building end-user creativity-support tools. however, the scientific community making advances in relevant algorithmic techniques is not, in many cases, the same community that is currently making advances in the design, evaluation, and user-experience aspects of creativity support. the primary objective of this workshop is thus to bring together participants from diverse backgrounds in the hci, design, art, machine-learning, and algorithms communities to facilitate the advancement of novel creativity support tools.
assisted-care robot initiation of communication in multiparty settings. this paper presents on-going work in developing service robots that provide assisted-care to the elderly in multi-party settings. in typical japanese day-care facilities, multiple caregivers and visitors are co-present in the same room and any caregiver may provide assistance to any visitor. in order to effectively work in such settings, a robot should behave in a way that a person who has a request can easily initiate communication with the robot. based on findings from observations at several day-care facilities, we have developed a robot system that displays availability to multiple persons and then displays recipiency to an individual person who wants to initiate interaction. our robot system and its experimental evaluation are detailed in this paper.
haptic feedback in remote pointing. we investigate the use of haptic feedback for enhancing user performance with remote pointing devices. we present a number of concepts that use haptic feedback on such devices and the results of the first user study, in which we have compared the effects of different feedback types on users' performance and preference in remote pointing tasks. the study showed that the addition of haptic feedback significantly improves the performance, while it has also revealed a seemingly low user acceptance of haptic feedback. we discuss the implications of our findings and outline the future work.
software ergonomics: relating subjective and objective measures. the use of computers in the workplace is now commonplace. correspondingly, injuries associated with computer use have increased. however, little research has been done investigating whether these injuries are associated with the software being used. one reason is the difficulty in measuring muscle strain (a predictor of muscle related injuries). here we present preliminary results of study on the relationship between objective and subjective measures of muscle strain during computer use. as users completed sets of tasks using msword®, semg muscle activity was recorded for the muscles associated with using a keyboard and mouse. after each task set, users completed surveys asking the level of strain they experienced during the tasks. correlations between the measures suggest that subjective measures can provide reliable information regarding the muscle strain associated with software use. these easily obtained subjective measurements could assist in producing software interaction designs that are better for users.
breaking down brick walls: design, construction, and prototype fabrication knowledge in architecture. architectural designs are not just collections of 3d objects. architects have both high-level aesthetic design intent, and intent for the functionality of the building; these must eventually translate into real-world construction materials and processes. physical prototypes are still essential for the architect and their clients to get a feel for whether designs "work". an exciting recent development in architecture is the use of industrial robots to automatically construct 3d prototype architectural models. but programming the robots requires tedious procedures of low-level commands, far removed from the designer's intent. adeon is a system that integrates high-level architectural design knowledge, including aesthetic and stylistic intent, with knowledge about materials and construction processes, and robot programming code for constructing prototype 3d physical models. it centers around collecting and associating "common sense" knowledge, expressed in english and converted to a knowledge representation about the various levels. it provides a graphic editor that allows architects to draw high-level aesthetic designs, perhaps referencing known styles or historical examples, and retrieving relevant construction, materials, and cost information. it automatically produces a robot program for constructing the prototype. we present examples detailing the design of various styles of brick walls. adeon is an interesting example of how to provide an interface for creative work that spans both high-level and low-level concerns.
safety, speed, and style: interaction design of an in-vehicle user interface. constrained by tight schedule and driven by both safety-critical and aesthetic concerns, an interdisciplinary team designed a novel in-vehicle multimodal, multimedia interface by an unconventional, streamlined process. the distinctive interface architecture and interaction design emphasize style and simplified interaction through strong visual design to speed user recognition, interpretation, and task completion, reducing driver distraction and cognitive load.
squidy: a zoomable design environment for natural user interfaces. we introduce the interaction library squidy, which eases the design of natural user interfaces by unifying relevant frameworks and toolkits in a common library. squidy provides a central design environment based on high-level visual data flow programming combined with zoomable user interface concepts. the user interface offers a simple visual language and a collection of ready-to-use devices, filters and interaction techniques. the concept of semantic zooming enables nevertheless access to more advanced functionality on demand. thus, users are able to adjust the complexity of the user interface to their current need and knowledge.
exploring participatory performance to inform the design of collaborative public interfaces. we describe a new application of interactive participatory performance in interaction design. our pragmatic strategy permits us to use performance as an investigatory tool in the exploration of user behavior. by taking a holistic view of the evaluation of the interplay between the designed artifact (the performance content) and the people who interact and relate to it, we can extract insights from the performance with the intention of informing the process of designing interaction mechanisms for more conventional public interfaces.
the birth of mobile chinese keypad & hybrid input methods. almost all the language input devices were designed based on western linguistic and psychological model. they are just localized by changing the printings without any key layout modification for eastern countries. in this paper, the design process and user study of a chinese style keypad and a hybrid input method are introduced.
intermediated technology interaction in rural contexts. access to information technology in developing countries is often indirect, involving human intermediaries. a computer kiosk is a typical instance of three-way interaction between user, kiosk operator, and kiosk technology. we describe a pilot experimental study that investigates whether manipulating the social prominence of the intermediary versus the technology affects perceived information characteristics and attitudes toward the interaction. we suggest that a better understanding of such locally specific interaction models is needed to address culturally influenced issues in information technology use throughout the developing world. ongoing methodological challenges in conducting experimental studies in such contexts are discussed.
associative personal information management. personal information management (pim) is an important and hard research problem. previous systems suffer inflexibility because of strict hierarchies and immobility. i present an alternative approach, based on associations and moving beyond today's desktop metaphor, to provide ways of managing information while mobile. to illustrate the concepts, i introduce the associative pda, a prototype we have designed and evaluated. finally, i discuss some design principles, which will guide my future work.
physical heart in a virtual body. in this video we present a special guitar that combines physical acoustic properties with virtual capabilities. a wooden resonator - a unique, replaceable piece of wood that gives the guitar a unique acoustic sound, will embody the acoustical values. the acoustic signal created by this wooden heart will be digitally processed in a virtual sound box in order to create flexible sound design. the project shows that traditional values can be embedded into a digital object.
development of evaluation heuristics for web service user experience. positive user experience (ux), including its pragmatic and hedonic aspects, is a central design target for interactive products and services. increasingly, web services are developed for both pcs and mobile terminals to support user needs for media content management and social interaction. even though many ux models have been developed over the last decade, the specific characteristics affecting ux of web services have not been studied systematically. in this paper we present the first phase of our service ux study in which three web services were evaluated by three ux experts each, using an initial set of service ux evaluation heuristics. we discuss how well these heuristics covered the positive and negative service ux evaluation findings, and how the heuristics and the expert evaluation approach of ux should be developed further.
beyond usability: evaluating emotional response as an integral part of the user experience. the role of emotion as an integral component of user experience has mostly been overlooked in the hci literature. instead, usability has been relied upon as the key indicator of user experience. we developed a methodology that combined verbal and nonverbal emotion scales. a usability study was then conducted, in which we collected both traditional usability metrics and emotional response data. results indicated insignificant differences in usability metrics but numerous significant differences between emotional responses of users. exploration of these emotional responses successfully provided additional insight into the user experience.
you scratch my back and i'll scratch yours: combating email overload collaboratively. email is no longer perceived as a communication marvel, but rather as a constant source of information overload. several studies have shown that accessing, managing, and archiving email threatens to affect users' productivity. while several strategies and tools have been proposed to assuage this burden, none have attempted to empower users to fight the overload collaboratively. we hypothesize that despite differences in email management practices and frequencies of filing among users, there is some degree of similarity in the end-product of the organizational structures reached by those working in close cooperative roles (e.g. members of a research group, employees of an organization). in this paper, we describe a system that enables collaborators to share their filing strategies among themselves. tags applied by one user are suggested to other recipients of the same email, thereby amortizing the cost of tagging and email management across all stakeholders. we wish to examine if such system support for semi-automated tagging reduces email overload for all users, and whether it leads to overall time savings for an entire enterprise as network effects propagate over time.
brainy hand: an ear-worn hand gesture interaction device. existing wearable hand gesture interaction devices are very bulky and cannot be worn in everyday life, because of the presence of a large visual feedback device. in particular, an eyeglass-type head-mounted display is very large for constant usage. to solve this problem, we propose brainy hand, which is a simple wearable device that adopts laser line, or more specifically, a mini-projector as a visual feedback device. brainy hand consists of a color camera, an earphone, and a laser line or mini-projector. this device uses a camera to detect 3d hand gestures. the earphone is used for receiving audio feedback. in this study, we introduce several user interfaces using brainy hand. (e.g., music player, phone)
investigating the psychology of task-based and presentation-based ui customization. even with a profusion of customization tools on uis, we do not see commensurate usage. while some users are known to use available customization tools to the fullest extent, most others make do with bare minimum features and default settings. in my dissertation i propose that empirically investigating customization as functional (task-based) and cosmetic (presentation-based) will enhance our understanding of user psychology surrounding customization, thereby giving us insight into ui design principles. this paper describes the main aim of my dissertation and progress made thus far.
it's what it's in: evaluating the usability of large-scale integrated systems. today's systems are often composed of many heterogeneous, distributed components including computing and communications infrastructure, other hardware devices, and system and application software. evaluating the usability of these systems is difficult, especially in the early stages of development when their use cannot be observed in context. while many different evaluation methods have been proposed for evaluating stand-alone technologies, evaluating very large-scale integrated systems requires techniques appropriate both for individual components, and the whole of the human-computing context being designed. results from the case study reported here suggest that the usability of any individual application is highly determined by its integration with other applications in the distributed system. modern evaluation methods need to account for this integration in both their perspective and the measures they use.
slap widgets: bridging the gap between virtual and physical controls on tabletops. we present silicone illuminated active peripherals (slap), a system of tangible, transparent widgets for use on vision-based multi-touch tabletops. slap widgets are cast from silicone or made of acrylic and include sliders, knobs, keyboards, and keypads. they add tactile feedback to multi-touch tables and can be dynamically relabeled with rear projection. they are inexpensive, battery-free, and untethered widgets combining the flexibility of virtual objects with tangible affordances of physical objects. our demonstration shows how slap widgets can augment input on multi-touch tabletops with modest infrastructure costs.
sharing digital photographs in the home by tagging memorabilia. within the home, digital photos lack the physical affordances that make collocated photo-sharing easy and opportunistic. family members have difficulty accessing the personal accounts of the photo organizer, navigating to these photos, or finding the desired ones within the vast number of photos stored on disk. viewing photos on a standard pc screen is also awkward due to crowding. to promote in-home photo sharing, we designed souvenirs, an rfid-based system that lets people quickly link digital photo sets to physical memorabilia. these memorabilia trigger memories and serve as social instruments; a person can enrich their story-telling by moving the physical memorabilia close to their large-format television screen, and the associated photos are immediately displayed. a person can also bring a mobile device near memorabilia: the photos appear on that display. through pick and drop, a person can also transfer the photo display from the mobile device to the large screen for easier viewing. this video motivates and illustrates how all this works.
information foraging in e-voting. in this paper, we present a case study of human-information interaction in the online realm of politics. the case study consists of a participant observed while searching and browsing the internet for campaign information in a mock-voting situation while taking notes that were to be shared with others. interaction analysis of the case study data consisted of applying information foraging theory to understand participant specific behaviors in searching and browsing. case study results show skewed time allocation to activities, a tradeoff between enrichment vs. exploitation of search results, and issues with lack of scent, low value perception, and value depletion of information. potential implications for voter-centered design of e-voting portals are discussed and future work is outlined.
challenges in evaluating usability and user experience of reality-based interaction. this workshop aims to further the understanding of the challenges relating to the evaluation methods of usability and user experience that are specific to reality-based interaction (rbi), and to identify effective practical responses to these challenges. the emergence of post-wimp interfaces has led to new ways of interacting with technologies. however, there are still no integrated ways of evaluating the usability and user experience of these interfaces. developers and designers are left to discover their own metrics and evaluation methods. this approach presents problems, in that the metrics used in each case may provide results that are neither valid nor meaningful. for this reason, the time is ripe to integrate the methods that have been developed for evaluating interfaces that belong to the rbi umbrella. the measures and techniques will then be turned into a framework that enables designers of rbi interfaces to select appropriately existing methods and tools to evaluate systematically the usability and user experience of their prototypes and products. reusing and adapting validated evaluation approaches can not only avoid reinventing the wheel and wasting time but also further improve and consolidate these approaches. such a framework will also provide a basis for comparison between designs of rbi interfaces in different application contexts.
designing for discovery: opening the hood for open-source end user tinkering. according to the free software movement, the user ought to have "the freedoms to make changes, and to publish improved versions" and "to study how the program works, and adapt it to your needs". the open source initiative expects users to access source code, explaining that "you can't evolve programs without modifying them. since our purpose is to make evolution easy, we require that modification be made easy". these philosophies can shape a unique perspective on software usability that has not been addressed thoroughly in the open-source domain. that is: how to design user-interfaces and tools that facilitate access to source code and encourage the behaviors envisioned above, namely, to improve the code, to personalize it, to learn from it, and to share it. and, as the open source initiative recommends, to make this easy. in addition to presenting this research perspective, we suggest some fruitful approaches to answering these questions and our current and future steps.
visualizing student activity in a wiki-mediated co-blogging exercise. students benefit from jointly reasoning, explaining or "arguing" about the course material. there are significant advantages for moving the discussion online e.g. where students co-blog vis-à-vis a wiki. for the teacher, keeping track of who is participating and the degree to which they participate is not straightforward. this paper presents visualization mechanisms we are developing that address these issues.
using temporal patterns (t-patterns) to derive stress factors of routine tasks. we describe the use of a statistical technique called t-pattern analysis to derive and characterize the routineness of tasks. t-patterns provide significant advantages over traditional sequence analyses by incorporating time. a t-pattern is characterized by a significant time window (critical interval) that describes the duration of this pattern. our analysis is based on data collected from shadowing 10 knowledge workers over a total of 29 entire work days. we report on the statistics of detected t-patterns and derived correlations with participant perceptions of workload, autonomy, and productivity.
designing the melody of interaction through movies, maps, mechanisms, prototypes and presentations. now that computers are no longer merely a means to do our job but help us to pursue our lives, one could question the appropriateness of functionality and efficiency as the main guiding principles for design. user experience and aesthetics of interaction are becoming increasingly paramount. but what makes for aesthetic of interaction and how to design for it? in the module "aesthetics of interaction" we used a variety of methods to discuss, experience and analyse the concept of aesthetics of interaction in depth. in this extended abstract we elucidate the methods used, i.e., movies, interaction maps, interaction mechanisms, prototypes and silent presentations, including the rationale behind them.
understanding consumer perception of technological product failures: an attributional approach. besides the widely promoted advantages the influx of new technology is bringing to consumers, the disadvantages due to increasing cognitive complexity of such technological advanced products have also been recognized. among other things, an increasing number of unknown field complaints is one of the evidences. since consumers often perceive a product's (mal)functioning differently than designers do, we propose an attributional approach to evaluate potential product failures. in this paper, we present the results of an exploratory empirical study to evaluate the attribution of picture quality failures in lcd televisions for a diverse group of consumers. this approach is aimed to provide designers better insight into how consumers perceive (potential) product failures, in order to support critical design decisions in the product development process.
defining the role of hci in the challenges of sustainability. sustainability is an increasingly prominent and critical theme in the field of hci. more needs to be known about how to critique and assess design from the perspective of sustainability, and how to integrate sustainability into the practice of hci. this workshop focuses on achieving this integration, identifying challenges, and defining directions for sustainable interaction design (sid).
tagged photos: concerns, perceptions, and protections. photo sharing has become a popular feature of many online social networking sites. many of the photo sharing applications on these sites, allow users to annotate photos with those who are in them. a number of researchers have examined the social uses and privacy issues of online photo sharing sites, but few have explored the privacy issues of photo sharing in social networks. in this paper, we begin by examining some of our findings from a series of focus groups on photo privacy in the social networking domain. we then devise a new mechanism to enhance photo privacy based on these findings.
collaborative translation by monolingual users. this paper describes a research effort to support collaborative translation by monolingual speakers, or people that speak only the source or target language. i hypothesize that sharing knowledge across the language barrier is possible with a combination of automated (but poor quality) machine translation, language-independent communication, and existing background knowledge. i demonstrate this possibility with proof-of-concept experiments.
bringing web 2.0 to government research: a case study. dashlink is a public nasa research collaboration website. web 2.0 style content generation and social software technologies along with a community-moderated posting policy make it easier and faster for nasa scientists and research partners to share data and knowledge with each other and the general public. designing and building an open collaboration website tested the boundaries of government information sharing rules and policies. in this paper we describe our experiences with and solutions to government specific design challenges.
human-centered computing in international development. this workshop continues the dialog on exploring the challenges in applying, extending, and inventing appropriate methods and contributions of humancentered computing (hcc) to international economic and community development, borne out of tremendously successful hci4d workshops at chi 2007 and 2008. the workshop aims at 1) providing a platform to discuss interaction design practices that allow for meaningful embedding of interactive systems in the cultural, infrastructural, and political settings where they will be used 2) addressing interaction design issues in developing regions, as well as areas in the developed world marginalized by poverty or other barriers. we hope to continue to extend the boundaries of the field of humancentered computing (hcc) by spurring on more discussion on how existing methods and practices can be adapted/ modified, and how new practices be developed, to combat
burn your memory away: one-time use video capture and storage device to encourage memory appreciation. although modern ease of access to technology enables many of us to obsessively document our lives, much of the captured digital content is often disregarded and forgotten on storage devices, with no concerns of cost or decay. can we design technology that helps people better appreciate captured memories? what would people do if they only had one more chance to relive past memories? in this paper, we present a prototype design, py-rom, a matchstick-like video recording and storage device that burns itself away after being used. this encourages designers to consider lifecycles and human-computer relationships by integrating physical properties into digitally augmenting everyday objects.
driving user centered design into it organizations: is it possible? in many organizations, actively engaging in user-centered design (ucd) techniques is standard practice when delivering products into the commercial marketplace or to external customers. but in these same organizations -- or in organizations not delivering products to an external customer -- the creation of systems for use by employees is a conversation between it and the business unit. ucd professionals are either not participating, or they have very limited influence. this sig creates a forum for people with real-world experience and challenges to discuss how -- and whether it is even possible -- to bring ucd into the it organization.
ptz control with head tracking for video chat. this paper describes a user interface for video chat that is capable of panning, tilting, and zooming (ptz) operation using head tracking. the approach is to map a captured 3d position from head tracker to ptz parameters of a remote camera so that a user can intuitively change the view just as people change their sight by moving their head. the preliminary user study gave encouraging results and clarified the point for further improvement.
are people drawn to faces on webpages? three studies were conducted to investigate the effects of faces on webpages. in study i, eye-tracking data showed that users were clearly drawn to faces when asked to look at pages and report what they remember. in study ii, the presence of a face next to a message on a webpage caused users to have a harder time finding that message. in study iii, photos of the authors of opinion articles caused users to be less likely to find the article and to give the page worse ratings.
designing for and with diaspora: a case study of work for the truth and reconciliation commission of liberia. we describe our experiences in designing new media technologies in cooperation with liberia's truth and reconciliation commission. this work includes two major projects: a dynamic, interactive web site for the commission, and a mobile video-sharing kiosk intended for use in-country where connectivity is limited. we place specific focus on our design exercises with members of the liberian diaspora in atlanta. our report includes lessons learned both in designing technologies directly for diaspora users, and in using diaspora members as surrogates for users in-country. these lessons include the need to recognize diversity even within the diaspora community, the sensitivity of content to cultural nuances, and the overall value of the perspective of interaction with diaspora members.
designing for all users: including the odd users. the field of hci has played an important role in broadening the spectrum of users of computational artifacts. however, users with extreme preferences are mostly ignored by the designers and researchers because they do not constitute a large portion of the market and the users lack generalizable characteristics. in order to further discuss these concerns, this paper introduces a case about the extreme users and the challenges they face. the paper ends with discussing future directions and challenges in designing for all users in the field of hci.
mediating programming through chat for the olpc. we built a text-based programming environment that enables youth to design and implement a chat client for the one laptop per child xo. the environment allows users to program and chat simultaneously. we conducted two one-week workshops at a girl scout camp to test user engagement with the environment. in this paper, we examine how chat mediated the programming experience in a collocated environment and its implications for motivating participation in computing.
low-cost gaze interaction: ready to deliver the promises. eye movements are the only means of communication for some severely disabled people. however, the high prices of commercial eye tracking systems limit the access to this technology. in this pilot study we compare the performance of a low-cost, webcam-based gaze tracker that we have developed with two commercial trackers in two different tasks: target acquisition and eye typing. from analyses on throughput, words per minute and error rates we conclude that a low-cost solution can be as efficient as expensive commercial systems.
spectator understanding of error in performance. the development of computer-based devices for music control has created a need to study how spectators understand new performance technologies and practices. as a part of a larger project examining how interactions with technology can be communicated to spectators, we present a model of a spectator's understanding of error by a performer. this model is broadly applicable throughout hci, as interactions with technology are increasingly public and spectatorship is becoming more common.
edible earth: dining on seasonal and local ingredients. college students are primarily concerned with the price and convenience of the food they choose to eat. environmental impact is not a consideration in their food decisions. we present a web-based solution that simplifies meal choices and addresses the perception that home-prepared meals are inconvenient and expensive. the solution provides a web service that suggests convenient recipes that use local and seasonal ingredients tailored to the user's location. this promotes sustainable food purchasing habits. the solution uses a location-aware mobile device as an example platform. the study presents the participatory design process that informed the development of this solution.
rehabilitation of handwriting skills in stroke patients using interactive games: a pilot study. this paper describes an interactive application that aims to support the rehabilitation of handwriting skills in people that suffer from paralysis after a stroke. the purpose of the application is to make the rehabilitation of handwriting skills fun and engaging. four platform-independent games with adjustable levels of difficulty were created in order to target varying levels of skills. the application also features a performance history, audio-visual feedback, and posture reminders. it was evaluated with medical staff and patients from the hoensbroeck rehabilitation centre in the netherlands. the initial results indicated that the games are more motivating and fun than traditional pen and paper exercises. the feedback received from therapists supports our claim that the games are a useful addition to the rehabilitation of handwriting.
new tools for task workflow analysis. this paper describes first steps in the use of a technique for the visualization, and analysis of users' workflows, well-suited to the study of user behavior in the completion of complex tasks.
"hiya-atsu" media: augmenting digital media with temperature. despite the development of many types of telecommunication systems, it is still hard to convey various types of information in an expressive manner to a remote partner. our research focuses on using variations in temperature to achieve this. hiya-atsu-mouse, which we developed to implement this idea, is a mouse device with thermal capabilities; the device becomes warmer or colder to the user's palm or fingertip according to the "temperature" of objects on the computer screen. this article evaluates the thermal performance of the device. the comments made by users are collected. finally, we introduce a practical hiya-atsu-mouse and describe it in operation.
dying, death, and mortality: towards thanatosensitivity in hci. what happens to human-computer "interaction" when the human user is no longer alive? this exploratory paper uses insights from the critical humanist tradition to argue for the urgent need to consider the facts of mortality, dying, and death in hci research. using an interdisciplinary approach, we critically reflect upon how the intersection of death and computing is currently navigated and illustrate the conceptual and practical complexities presented by mortality, dying, and death in hci. finally, we introduce the concept of thanatosensitivity to describe an approach that actively integrates the facts of mortality, dying, and death into hci research and design.
automatic retargeting of web page content. we present a novel technique for automatically retargeting content from one web page onto the layout of another. web pages are decomposed into their perceptual hierarchical representations. we then use a structured-prediction algorithm to learn reasonable mappings between the perceptual trees. using the mappings, we are able to merge the content of one page with the layout of another.
contemporary domestic infrastructures and technology design. in this proposal, i describe my examination of two contemporary domestic infrastructures. specifically, i am investigating whether we need to surface more information about these systems to make them intelligible to end-users. i describe my empirical research to date and the design of two technology probes which i will use to learn more how home infrastructure affects domestic technology design.
generating affective music icons in the emotion plane. in this paper, we discuss the generation of icons that represent the emotion expressed in music. we use the emotion plane for connecting the music with the icon shape affectively. a model to project arbitrary music on the plane is introduced using the result of a user survey and various features of audio signals. icon shapes are located on the plane from the result of user survey. the icon shape of the input music is obtained by blending neighbor icon shapes of the point of the music on the emotion plane. using this method, one can easily guess the emotion of music from the corresponding icon shape and find the music he or she wants.
knowledge-based extraction of named entities. the usual approach to named-entity detection is to learn extraction rules that rely on linguistic, syntactic, or document format patterns that are consistent across a set of documents. however, when there is no consistency among documents, it may be more effective to learn document-specific extraction rules.this paper presents a knowledge-based approach to learning rules for named-entity extraction. document-specific extraction rules are created using a generate-and-test paradigm and a database of known named-entities. experimental results show that this approach is effective on web documents that are difficult for the usual methods.
expertise identification using email communications. a common method for finding information in an organization is to use social networks---ask people, following referrals until someone with the right information is found. another way is to automatically mine documents to determine who knows what. email documents seem particularly well suited to this task of "expertise location", as people routinely communicate what they know. moreover, because people explicitly direct email to one another, social networks are likely to be contained in the patterns of communication. can these patterns be used to discover experts on particular topics? is this approach better than mining message content alone? to find answers to these questions, two algorithms for determining expertise from email were compared: a content-based approach that takes account only of email text, and a graph-based ranking algorithm (hits) that takes account both of text and communication patterns. an evaluation was done using email and explicit expertise ratings from two different organizations. the rankings given by each algorithm were compared to the explicit rankings with the precision and recall measures commonly used in information retrieval, as well as the d' measure commonly used in signal-detection theory. results show that the graph-based algorithm performs better than the content-based algorithm at identifying experts in both cases, demonstrating that the graph-based algorithm effectively extracts more information than is found in content alone.
mining officially unrecognized side effects of drugs by combining web search and machine learning. we consider the problem of finding officially unrecognized side effects of drugs. by submitting queries to the web involving a given drug name, it is possible to retrieve pages concerning the drug. however, many retrieved pages are irrelevant and some relevant pages are not retrieved. more relevant pages can be obtained by adding the active ingredient of the drug to the query. in order to eliminate irrelevant pages, we propose a machine learning process to filter out the undesirable pages. the process is shown experimentally to be very effective. since obtaining training data for the machine learning process can be time consuming and expensive, we provide an automatic method to generate the training data. the method is also shown to be very accurate. the side effects of three drugs which are not recognized by fda are validated by an expert. we believe that the same approach can be applied to many real life problems and will yield high precision. thus, this could lead a new way to perform retrieval with high accuracy.
securing xml data in third-party distribution systems. web-based third-party architectures for data publishing are today receiving growing attention, due to their scalability and the ability to efficiently manage large numbers of users and great amounts of data. a third-party architecture relies on a distinction between the owner and the publisher of information. the owner is the producer of information, whereas publisher provides data management services and query processing functions for (a portion of) the owner's information. in such architecture, there are important security concerns especially if we do not want to make any assumption on the trustworthy of the publishers. although approaches have been proposed [4, 5] providing partial solutions to this problem, no comprehensive framework has been so far developed able to support all the most important security properties in the presence of an untrusted publisher. in this paper, we develop an xml-based solution to such problem, which makes use of non-conventional digital signature techniques and queries over encrypted data.
incremental test collections. corpora and topics are readily available for information retrieval research. relevance judgments, which are necessary for system evaluation, are expensive; the cost of obtaining them prohibits in-house evaluation of retrieval systems on new corpora or new topics. we present an algorithm for cheaply constructing sets of relevance judgments. our method intelligently selects documents to be judged and decides when to stop in such a way that with very little work there can be a high degree of confidence in the result of the evaluation. we demonstrate the algorithm's effectiveness by showing that it produces small sets of relevance judgments that reliably discriminate between two systems. the algorithm can be used to incrementally design retrieval systems by simultaneously comparing sets of systems. the number of additional judgments needed after each incremental design change decreases at a rate reciprocal to the number of systems being compared. to demonstrate the effectiveness of our method, we evaluate trec ad hoc submissions, showing that with 95% fewer relevance judgments we can reach a kendall's tau rank correlation of at least 0.9.
misuse detection for information retrieval systems. we present a novel approach to detect misuse within an information retrieval system by gathering and maintaining knowledge of the behavior of the user rather than anticipating attacks by unknown assailants. our approach is based on building and maintaining a profile of the behavior of the system user through tracking, or monitoring of user activity within the information retrieval system. any new activity of the user is compared to the user profile to detect a potential misuse for the authorized user. we propose four different methods to detect misuse in information retrieval systems. our experimental results on $2$ gb collection favorably demonstrate the validity of our approach.
a new cache replacement algorithm for the integration of web caching and prefectching. web caching and web prefetching are two important techniques to reduce the noticeable response time perceived by users. note that by integrating web caching and web prefetching, these two techniques can complement each other since web caching technique exploits the temporal locality whereas web prefetching technique utilizes the spatial locality of web objects. however, without circumspect design, the integration of these two techniques might cause significant performance degradation to each other. in view of this, we propose in this paper an innovative cache replacement algorithm, which not only considers the caching effect in the web environment but also evaluates the prefetching rules provided by various prefetching schemes. specifically, we formulate a normalized profit function to evaluate the profit from caching an object (i.e., either a non-implied object or an implied object according to some prefetching rule). based on the normalized profit function devised, we devise an innovative web cache replacement algorithm, referred to as algorithm iwcp (standing for the integration of web caching and prefetching). using an event-driven simulation, we evaluate the performance of algorithm iwcp under several circumstances. the experimental results show that algorithm iwcp consistently outperforms the companion schemes in various performance metrics.
: adaptively monitoring the recent change of frequent itemsets over online data streams. knowledge embedded in a data stream is likely to be changed as time goes by. consequently, identifying the recent change of the knowledge quickly can provide valuable information for the analysis of the data stream. however, most of mining algorithms or frequency approximation algorithms for a data stream do not able to extract the recent change of information in a data stream adaptively. this paper proposes a sliding window-based method that finds recently frequent itemsets over an online data stream adaptively. the size of a window defines a desired life-time of the information in a newly generated transaction. consequently, only recently generated transactions in the range of the window are considered to find the frequent itemsets of a data stream.
a geometric interpretation and analysis of r-precision. average precision and r-precision are two of the most commonly cited measures of overall retrieval performance, but their correlation, though well-known, has defied explanation. we recently devised a geometric interpretation of r-precision which suggests that under a reasonable set of assumptions, r-precision approximates the area under the precision-recall curve, as does average precision, thus explaining their correlation. in this paper, we consider these assumptions and our geometric interpretation of r-precision in order to further understand, and make reasonable use of, the information that r-precision provides. given our geometric interpretation of r-precision, we show that r-precision is highly informative by demonstrating that it can be used to (1) accurately infer precision-recall curves, (2) accurately infer other measures of retrieval performance, and (3) devise new measures of retrieval performance. through our analysis, we also state the conditions under which r-precision is informative.
towards maintaining consistency of spatial databases. this paper focuses on the consistency issues related to integrating multiple sets of spatial data in spatial information systems such as geographic information systems (giss). data sets to be integrated are assumed to hold information about the same geographic features which can be drawn from different sources at different times, which may vary in reliability and accuracy, and which may vary in the scale of presentation resulting in possible multiple spatial representations for these features. a systematic approach is proposed which relies first on breaking down the consistency issue by identifying a range of consistency classes which can be checked in isolation. these classes are a representative set of properties and relationships which can completely identify the geographic objects in the data sets. different levels of consistency are then proposed, namely, total, partial and conditional, which can be checked for every consistency class. this provides the flexibility for two data sets to be integrated without necessarily being totally consistent in every aspect. the second step of the proposed approach is to explicitly represent the different classes and levels of consistency in the system. as an example, a simple structure which stores adjacency relationships is given which can be used for the explicit representation of topological consistency. the paper also proposes that the set of consistent knowledge in the data sets (which is mostly qualitative) be explicitly represented in the database and that uncertainty or ambiguity inherent in the knowledge be represented as well.
obsolescent materialized views in query processing of enterprise information systems. in recent years, query processing has become more complex as data sources are frequently replicated and data are periodically processed and embedded within several data sources simultaneously. these trends have necessitated the optimization of techniques for query processing in order to exploit these new alternatives. accordingly, this paper introduces an improved query optimization technique, which is capable of assessing query plans that use both current and obsolescent data. in particular, we provide a cost model by which the trade-offs of using obsolescent materialized views can be evaluated and we also discuss the method's applicability to contemporary query optimization techniques.
a unified model for metasearch, pooling, and system evaluation. we present a unified model which, given the ranked lists of documents returned by multiple retrieval systems in response to a given query, simultaneously solves the problems of (1) fusing the ranked lists of documents in order to obtain a high-quality combined list (metasearch); (2) generating document collections likely to contain large fractions of relevant documents (pooling); and (3) accurately evaluating the underlying retrieval systems with small numbers of relevance judgments (efficient system assessment). our approach is based on the hedge algorithm for on-line learning. in effect, our proposed system "learns" which documents are likely to be relevant from a sequence of on-line relevance judgments. in experiments using trec data, our methodology is shown to outperform standard methods for metasearch, pooling, and system evaluation, often remarkably so.
real time user context modeling for information retrieval agents. the success of personal information agents depends on their ability to provide task-relevant information. this paper presents wordsieve, a new algorithm that generates context descriptions to guide document indexing and retrieval. wordsieve exploits information about the sequence of accessed documents to identify words which indicate a shift in context. we have tested wordsieve in a personal information agent, calvin, which monitors a user's document access, generates a representation of the user's task context, indexes the resources consulted, and presents recommendations for other resources that were consulted in similar prior contexts. in initial experiments, wordsieve outperforms term frequency/inverse document frequency at matching documents to hand-coded vector representations of the task contexts in which they were originally consulted, where the task context representations are term vectors representing a specific search task given to the user.
hierarchical graph indexing. traffic analysis, in the context of telecommunications or internet and web data, is crucial for large network operations. data in such networks is often provided as large graphs with hundreds of millions of vertices and edges. we propose efficient techniques for managing such graphs at the storage level in order to facilitate its processing at the interface level(visualization). the methods are based on a hierarchical decomposition of the graph edge set that is inherited from a hierarchical decomposition of the vertex set. real time navigation is provided by an efficient two level indexing schema called the gkd*-tree. the first level is a variation of a kd-tree index that partitions the edge set in a way that conforms to the hierarchical decomposition and the data distribution (the gkd-tree). the second level is a redundant r-tree that indexes the leaf pages of the gkd-tree. we provide computational results that illustrate the superiority of the gkd-tree against conventional indexes like the kd-tree and the r*-tree both in creation as well as query response times.
managing trust in a peer-2-peer information system. managing trust is a problem of particular importance in peer-to-peer environments where one frequently encounters unknown agents. existing methods for trust management, that are based on reputation, focus on the semantic properties of the trust model. they do not scale as they either rely on a central database or require to maintain global knowledge at each agent to provide data on earlier interactions. in this paper we present an approach that addresses the problem of reputation-based trust management at both the data management and the semantic level. we employ at both levels scalable data structures and algorithms that require no central control and allow to assess trust by computing an agents reputation from its former interactions with other agents. thus the meethod can be implemented in a peer-to-peer environment and scales well for very large numbers of participants. we expect that scalable methods for trust management are an important factor, if fully decentralized peer-to-peer systems should become the platform for more serious applications than simple file exchange.
using titles and category names from editor-driven taxonomies for automatic evaluation. evaluation of ir systems has always been difficult because of the need for manually assessed relevance judgments. the advent of large editor-driven taxonomies on the web opens the door to a new evaluation approach. we use the odp (open directory project) taxonomy to find sets of pseudo-relevant documents via one of two assumptions: 1) taxonomy entries are relevant to a given query if their editor-entered titles exactly match the query, or 2) all entries in a leaf-level taxonomy category are relevant to a given query if the category title exactly matches the query. we compare and contrast these two methodologies by evaluating six web search engines on a sample from an america online log of ten million web queries, using mrr measures for the first method and precision-based measures for the second. we show that this technique is stable with respect to the query set selected and correlated with a reasonably large manual evaluation.
building xml statistics for the hidden web. there have been several techniques proposed for building statistics for static xml data. however, very little work has been done in the area of building xml statistics for data sources that export xml views of data that is stored in relational or other databases. for such data sources, we need statistics that are built in an on-line manner, by observing the xml queries to the data sources and their results. in this paper, we present a technique for building on-line xml statistics by observing the xpath queries issued to a data source and their result sizes. these xpath queries select parts of the virtual xml document representing the xml view of the data at the data source. we convert these xpath queries to a more abstract and generalized form that we call annotated path expressions. we present a technique for storing these annotated path expressions and information about their selectivity for use in estimating the selectivity of future xpath queries. we also present an experimental evaluation of our proposed approach.
a system for knowledge management in bioinformatics. the emerging biochip technology has made it possible to simultaneously study expression (activity level) of thousands of genes or proteins in a single experiment in the laboratory. however, in order to extract relevant biological knowledge from the biochip experimental data, it is critical not only to analyze the experimental data, but also to cross-reference and correlate these large volumes of data with information available in external biological databases accessible online. we address this problem in a comprehensive system for knowledge management in bioinformatics called e2e. to the biologist or biological applications, e2e exposes a common semantic view of inter-relationship among biological concepts in the form of an xml representation called expressml, while internally, it can use any data integration solution to retrieve data and return results corresponding to the semantic view. we have implemented an e2e prototype that enables a biologist to analyze her gene expression data in geml or from a public site like stanford, and discover knowledge through operations like querying on relevant annotated data represented in expressml using pathways data from kegg, publication data from medline and protein data from swiss-prot.
bootstrapping for hierarchical document classification. managing the hierarchical organization of data is starting to play a key role in the knowledge management community due to the great amount of human resources needed to create and maintain these organized repositories of information. machine learning community has in part addressed this problem by developing hierarchical supervised classifiers that help maintainers to categorize new resources within given hierarchies. although such learning models succeed in exploiting relational knowledge, they are highly demanding in terms of labeled examples, because the number of categories is related to the dimension of the corresponding hierarchy. hence, the creation of new directories or the modification of existing ones require strong investments.this paper proposes a semi-automatic process (interleaved with human suggestions) whose aim is to minimize (simplify) the work required to the administrators when creating, modifying, and maintaining directories. within this process, bootstrapping a taxonomy with examples represents a critical factor for the effective exploitation of any supervised learning model. for this reason we propose a method for the bootstrapping process that makes a first hypothesis of categorization for a set of unlabeled documents, with respect to a given empty hierarchy of concepts. based on a revision of self-organizing maps, namely taxsom, the proposed model performs an unsupervised classification, exploiting the a-priori knowledge encoded in a taxonomy structure both at the terminological and topological level. the ultimate goal of taxsom is to create the premise for successfully training a supervised classifier.
redundant documents and search effectiveness. the web contains a great many documents that are content-equivalent, that is, informationally redundant with respect to each other. the presence of such mutually redundant documents in search results can degrade the user search experience. previous attempts to address this issue, most notably the trec novelty track, were characterized by difficulties with accuracy and evaluation. in this paper we explore syntactic techniques --- particularly document fingerprinting --- for detecting content equivalence. using these techniques on the trec gov1 and gov2 corpora revealed a high degree of redundancy; a user study confirmed that our metrics were accurately identifying content-equivalence. we show, moreover, that content-equivalent documents have a significant effect on the search experience: we found that 16.6% of all relevant documents in runs submitted to the trec 2004 terabyte track were redundant.
haystack: per-user information environments. traditional information retrieval (ir) systems are designed to provide uniform access to centralized corpora by large numbers of people. the haystack project emphasizes the relationship between a particular individual and his corpus. an individual's own haystack priviliges information with which that user interacts, gathers data about those interactions, and uses this metadata to further personalize the retrieval process. this paper describes the prototype haystack system.
swam: a family of access methods for similarity-search in peer-to-peer data networks. peer-to-peer data networks (pdns) are large-scale, self-organizing, distributed query processing systems. familiar examples of pdn are peer-to-peer file-sharing networks, which support exact-match search queries to locate user-requested files. in this paper, we formalize the more general problem of <i>similarity-search</i> in pdns, and propose a <i>family</i> of distributed access methods, termed <i>small-world access methods (swam)</i>, for efficient execution of various similarity-search queries, namely exact-match, range, and k-nearest-neighbor queries. unlike its predecessors, i.e., lh* and dhts, swam does not control the assignment of data objects to pdn nodes; each node autonomously stores its own data. besides, swam supports all similarity-search queries on multiple attributes. swam guarantees that the query object will be found (if it exists in the network) in average time logarithmically proportional to the network size. moreover, once the query object is found, all the similar objects would be in its proximate network neighborhood and hence enabling efficient range and k-nearest-neighbor queries. as a specific instance of swam, we propose <i>swam-v</i>, a voronoi-based swam that indexes pdns with multi-attribute data objects. for a pdn with <i>n</i> nodes swam-v has query time, communication cost, and computation cost of <i>o</i>(log <i>n</i>) for exact-match queries, and <i>o</i>(log <i>n</i> + <b>s</b><i>n</i>) and <i>o</i>(log <i>n</i> + <b>k</b>) for range queries (with selectivity <b>s</b>) and <b>k</b>nn queries, respectively. our experiments show that swam-v consistently outperforms a similarity-search enabled version of can in query time and communication cost by a factor of 2 to 3.
internet scale string attribute publish/subscribe data networks. with this work we aim to make a three-fold contribution. we first address the issue of supporting efficiently queries over string-attributes involving prefix, suffix, containment, and equality operators in large-scale data networks. our first design decision is to employ distributed hash tables (dhts) for the data network's topology, harnessing their desirable properties. our next design decision is to derive dht-independent solutions, treating dht as a black box. second, we exploit this infrastructure to develop efficient content based publish/subscribe systems. the main contribution here are algorithms for the efficient processing of queries (subscriptions) and events (publications). specifically, we show that our subscription processing algorithms require o(logn) messages for a n-node network, and our event processing algorithms require o(l x logn) messages (with l being the average string length).third, we develop algorithms for optimizing the processing of multi-dimensional events, involving several string attributes. further to our analysis, we provide simulation-based experiments showing promising performance results in terms of number of messages, required bandwidth, load balancing, and response times.
approximate searches: k-neighbors + precision. it is known that all multi-dimensional index structures fail to accelerate content-based similarity searches when the feature vectors describing images are high-dimensional. it is possible to circumvent this problem by relying on approximate search-schemes trading-off result quality for reduced query execution time. most approximate schemes, however, provide none or only complex control on the precision of the searches, especially when retrieving the k nearest neighbors (nns) of query points.in contrast, this paper describes an approximate search scheme for high-dimensional databases where the precision of the search can be probabilistically controlled when retrieving the k nns of query points. it allows a fine and intuitive control over this precision by setting at run time the maximum probability for a vector that would be in the exact answer set to be missed in the approximate set of answers eventually returned. this paper also presents a performance study of the implementation using real datasets showing its reliability and efficiency. it shows, for example, that our method is 6.72 times faster than the sequential scan when it handles more than 5 106 24-dimensional vectors, even when the probability of missing one of the true nearest neighbors is below 0.01.
answering aggregation queries on hierarchical web sites using adaptive sampling. we study how to answer aggregation queries over hierarchical web sites using adaptive sampling.
using speculation to reduce server load and service time on the www. abstract speculative service implies that a client''s request for a document is serviced by sending, in addition to the document requested, a number of other documents that the server speculates will be requested by the client in the near future. this speculation is based on statistical information that the server maintains for each document it serves. the notion of speculative service is analogous to prefetching, which is used to improve cache performance in distributed/parallel shared memory systems, with the exception that servers (not clients) control when and what to prefetch. using trace simulations based on the logs of our departmental http server http://cs-www.bu.edu, we show that both server load and service time could be reduced considerably, if speculative service is used. this is above and beyond what is currently achievable using client-side caching and server-side dissemination. we identify a number of parameters that could be used to fine-tune the level of speculation performed by the server based on the level of lookahead, the state of the network, the tradeoffs between bulk and individual transmission of documents, and the relative popularity of documents, among other factors.
protein structure alignment using geometrical features. a novel approach for similarity search on protein structure databases is proposed which incorporates the three dimensional coordinates of the main atoms of each amino acid and extracts a geometrical signature along with the direction of the given amino acid. as a result, each protein is presented by a series of feature vectors representing local geometry, shape, direction, and secondary structure assignment of its amino acid constituents. furthermore, a residue-to-residue distance matrix is calculated and is incorporated into a local alignment dynamic programming algorithm to find the similar portions of two given proteins and finally a sequence alignment step is used as the last filtration step. the optimal superimposition of the detected similar regions is used to assess the quality of the results. the proposed algorithm is fast and accurate and hence could be used for the analysis of large protein structure similarity.
predicting accuracy of extracting information from unstructured text collections. exploiting lexical and semantic relationships in large unstructured text collections can significantly enhance managing, integrating, and querying information locked in unstructured text. most notably, named entities and relations between entities are crucial for effective question answering and other information retrieval and knowledge management tasks. unfortunately, the success in extracting these relationships can vary for different domains, languages, and document collections. predicting extraction performance is an important step towards scalable and intelligent knowledge management, information retrieval and information integration. we present a general language modeling method for quantifying the difficulty of information extraction tasks. we demonstrate the viability of our approach by predicting performance of real world information extraction tasks, named entity recognition and relation extraction.
mining all maximal frequent word sequences in a set of sentences. we present an efficient algorithm for finding all maximal frequent word sequences in a set of sentences. a word sequence s is considered frequent, if all its words occur in at least σ sentences and the words occur in each of these sentences in the same order as in s, given a frequency threshold σ. hence, the words of a sequence s do not have to occur consecutively in the sentences.
hyperthesis: the grna spell on the curse of bioinformatics applications integration. in this paper, we describe a graphical workflow management system called hyperthesis to address the challenges of integrating bioinformatics applications. hyperthesis is an integral component of the genomics research network architecture (grna). the grna was designed and developed to address the challenges of developing new bioinformatics applications. specifically, hyperthesis makes constructing workflows (pipelines of execution of applications) in the grna fast and intuitive for biologists and bio-programmers alike. it provides a large repository of interconnectable, parameterized workflow components for processing and relating diverse biological data and software programs. it also enables us to add new workflow components as new algorithms develop in ones area of interest. hyperthesis has been fully implemented using java.
modeling behavior, a step towards defining functionally correct views of complex objects in concurrent engineering. multidisciplinary concurrent engineering needs to model and manage different views of complex designs. previous attempts to address the problem of creating views of complex objects in object oriented database systems focus on the structure of complex objects; little attention is paid to how complex object behavior is effected when creating views. we believe that designing functionally correct behavior for a complex object should be a major consideration when defining a view to guarantee correctness of the derived classes.in this paper, we study the problem for designing functionally correct views of complex objects in concurrent engineering. view behavioral modeling requirements are presented. a behavior model that satisfies these requirements is presented. this model is demonstrated on an example complex object that represents process management.
multi-level operator combination in xml query processing. a core set of efficient access methods is central to the development of any database system. in the context of an xml database, there has been considerable effort devoted to defining a good set of primitive operators and inventing efficient access methods for each individual operator. these primitive operators have been defined either at the macro-level (using a "pattern tree" to specify a selection, for example) or at the micro-level (using multiple explicit containment joins to instantiate a single xpath expression).in this paper we argue that it is valuable to consider operations at each level. we do this through a study of operator merging: the development of a new access method to implement a combination of two or more primitive operators. it is frequently the case that access methods for merged operators are superior to a pipelined execution of separate access methods for each operator. we show operator merging to be valuable at both the micro-level and the macro-level. furthermore, we show that the corresponding merged operators are hard to reason with at the other level.specifically, we consider the influence of projections and set operations on pattern-based selections and containment joins. we show, through both analysis and extensive experimentation, the benefits of considering these operations all together. even though our experimental verification is only with a native xml database, we have reason to believe that our results apply equally to rdbms-based xml query engines.
coolcat: an entropy-based algorithm for categorical clustering. in this paper we explore the connection between clustering categorical data and entropy: clusters of similar poi lower entropy than those of dissimilar ones. we use this connection to design an incremental heuristic algorithm, coolcat, which is capable of efficiently clustering large data sets of records with categorical attributes, and data streams. in contrast with other categorical clustering algorithms published in the past, coolcat's clustering results are very stable for different sample sizes and parameter settings. also, the criteria for clustering is a very intuitive one, since it is deeply rooted on the well-known notion of entropy. most importantly, coolcat is well equipped to deal with clustering of data streams(continuously arriving streams of data point) since it is an incremental algorithm capable of clustering new points without having to look at every point that has been clustered so far. we demonstrate the efficiency and scalability of coolcat by a series of experiments on real and synthetic data sets.
incorporating topical support documents into a small training set in text categorization. this paper explores the incorporation of topical support documents into a training set as a means of compensating for a shortage of positive training data in text categorization. to support topical representation, our method applies a simple transformation to documents, i.e., making new documents from existing positive documents by squaring a conventional term weight. the topical support documents thus created not only are expected to preserve the topic, but even improve the topical representation by emphasizing terms with higher weights. experiments with support vector machines showed the effectiveness on rcv1 collection with a small number of positive training data. our topical support representation achieved 52.01% and 8.83% improvements for 33 and 56 categories of rcv1 topic in micro-averaged f1 with less than 100 and 300 positive documents in learning, respectively. result analyses based on robustness indicate that topical support documents contribute to a steady and stable improvement.
combining multiple classifiers for text categorization. a major problem facing online information services is how to index and supplement large document collections with respect to a rich set of categories. we focus upon the routing of case law summaries to various secondary law volumes in which they should be cited. given the large number (> 13,000) of closely related categories, this is a challenging task that is unlikely to succumb to a single algorithmic solution. our fully implemented and recently deployed system shows that a superior classification engine for this task can be constructed from a combination of classifiers. the multi-classifier approach helps us leverage all the relevant textual features and meta data, and appears to generalize to related classification tasks.
query expansion using associated queries. hundreds of millions of users each day use web search engines to meet their information needs. advances in web search effectiveness are therefore perhaps the most significant public outcomes of ir research. query expansion is one such method for improving the effectiveness of ranked retrieval by adding additional terms to a query. in previous approaches to query expansion, the additional terms are selected from highly ranked documents returned from an initial retrieval run. we propose a new method of obtaining expansion terms, based on selecting terms from past user queries that are associated with documents in the collection. our scheme is effective for query expansion for web retrieval: our results show relative improvements over unexpanded full text retrieval of 26%--29%, and 18%--20% over an optimised, conventional expansion approach.
using specification-driven concepts for distributed data management and dissemination. at the mitre corporation-center for advanced aviation system development (caasd), software engineers work closely with both analyst and domain experts to develop software simulations in the air traffic management domain. in this environment, software simulations are applications that take large amounts of real-world operational information, and through calculations, derivations, and display extends the original information to produce some new insight into the domain. this new insight or knowledge typically comes in the form of a pertinent set of data. based on this set of information other research groups can further extend this knowledge. the challenge in this environment is a distributed data management system that will allow a distributed set of researchers to share their extended knowledge. this paper presents the motivation and design of such an architecture to support this collaborative knowledge/data sharing environment. this run-time configurable architecture is implemented using web-based technologies such as the extensible markup language (xml), java servlets, extensible stylesheets (xsl), and a relational database management system (rdbms).
predicting the cost-quality trade-off for information retrieval queries: facilitating database design and query optimization. efficient, flexible, and scalable integration of full text information retrieval (ir) in a dbms is not a trivial case. this holds in particular for query optimization in such a context. to facilitate the bulk-oriented behavior of database query processing, a priori knowledge of how to limit the data efficiently prior to query evaluation is very valuable at optimization time. the usually imprecise nature of ir querying provides an extra opportunity to limit the data by a trade-off with the quality of the answer. in this paper we present a mathematically derived model to predict the quality implications of neglecting information before query execution. in particular we investigate the possibility to predict the retrieval quality for a document collection for which no training information is available, which is usually the case in practice. instead, we construct a model that can be trained on other document collections for which the necessary quality information is available, or can be obtained quite easily. we validate our model for several document collections and present the experimental results. these results show that our model performs quite well, even for the case were we did not train it on the test collection itself.
closure maintenance in an object-oriented query model. an object-algebra is presented as a formal query model for object-oriented data models. the algebra serves not only to access and manipulate the structure and behavior of objects, but it also supports the creation of new objects and the introduction of new relationships into the schema. it provides a more powerful and flexible tool than messages for effectively dealing with complex situations and meeting associative access requirements. operands as well as the results of operations in the proposed algebra are formally characterized as a pair of sets&mdash;a set of objects capturing the states and a set of message expressions comprised of sequences of messages modeling the object behavior. the closure property is achieved in a natural way by letting the results of operations possess the same characteristics as the operands in an algebra expression. some operators of the algebra resemble those of the relational algebra but with different syntax and semantics. additional operators are introduced to complement them. a class is shown to posses the properties of an operand by defining a set of objects and deriving a set of message expressions for it. furthermore, the result of an object algebra expression is shown to have the characteristics of a class whose superclass/subclass relationships with its operand class(es) can be established providing a mechanism to properly and persistently place it in the class lattice (schema).
effects of web document evolution on genre classification. the world wide web is a massive corpus that constantly evolves. classification experiments usually grab a snapshot (temporally and spatially) of the web for a corpus. in this paper, we examine the effects of page evolution on genre classification of web pages. web genre refers to the type of the page characterized by features such as style, form or presentation layout, and meta-content; web genre can be used to tune spider crawling re-visits and inform relevance judgments for search engines. we found that pages in some genres change rarely if at all and can be used in present-day research experiments without requiring an updated version. we show that an old corpus can be used for training when testing on new web pages, with only a marginal drop in accuracy rates on genre classification. we also show that features found to be useful in one corpus do not transfer well to other corpora with different genres.
effective arabic-english cross-language information retrieval via machine-readable dictionaries and machine translation. in cross-language information retrieval (clir), queries in one language retrieve relevant documents in other languages machine-readable dictionary (mrd) and machine translation (mt) are important resources for query translation in clir. we investigate mt and mrd to arabic-english clir. the translation ambiguity associated with these resources is the key problem. we present three methods of query translation using a bilingual dictionary for arabic-english clir. first, we present the every-match (em) method. this method yields ambiguous translations since many extraneous terms are added to the original query. to disambiguate the query translation, we present the first-match (fm) method that considers the first match in the dictionary as the candidate term. finally, we present the two-phase (tp) method. we show that good retrieval effectiveness can be achieved without complex resources using the two-phase method for arabic-english clir. we also empirically evaluate the effectiveness of the mt-based method using short, medium, and long queries from trec. the effects of the query length on the quality of the mt-based clir are investigated.
on arabic search: improving the retrieval effectiveness via a light stemming approach. the inflectional structure of a word impacts the retrieval accuracy of information retrieval systems of latin-based languages. we present two stemming algorithms for arabic information retrieval systems. we empirically investigate the effectiveness of surface-based retrieval. this approach degrades retrieval precision since arabic is a highly inflected language. accordingly, we propose root-based retrieval. we notice a statistically significant improvement over the surface-based approach. many variant word senses are based on an identical root; thus, the root-based algorithm creates invalid conflation classes that result in an ambiguous query which degrades the performance by adding extraneous terms. to resolve ambiguity, we propose a novel light-stemming algorithm for arabic texts. this automatic rule-based stemming algorithm is not as aggressive as the root extraction algorithm. we show that the light stemming algorithm significantly outperforms the root-based algorithm. we also show that a significant improvement in retrieval precision can be achieved with light inflectional analysis of arabic words.
flexible intrinsic evaluation of hierarchical clustering for tdt. the topic detection and tracking (tdt) evaluation program has included a "cluster detection" task since its inception in 1996. systems were required to process a stream of broadcast news stories and partition them into non-overlapping clusters. a system's effectiveness was measured by comparing the generated clusters to "truth" clusters created by human annotators. starting in 2003, tdt is moving to a more realistic model that permits overlapping clusters (stories may be on more than one topic) and encourages the creation of a hierarchy to structure the relationships between clusters (topics). we explore a range of possible evaluation models for this modified tdt clustering task to understand the best approach for mapping between the human-generated "truth" clusters and a much richer hierarchical structure. we demonstrate that some obvious evaluation techniques fail for degenerate cases. for a few others we attempt to develop an intuitive sense of what the evaluation numbers mean. we settle on some approaches that incorporate a strong balance between cluster errors (misses and false alarms) and the distance it takes to travel between stories within the hierarchy.
incremental encoding of multiple inheritance hierarchies. incremental updates to multiple inheritance hierarchies are becoming more prevalent with the increasing number of persistent applications supporting complex objects, making the efficient computation of lattice operations such as greatest lower bound (glb), least upper bound (lub), and subsumption more and more important. general techniques for the compact encoding of a hierarchy are presented. one such method is to plunge the given ordering into a boolean lattice of binary words, leading to an almost constant-time complexity of the lattice operations. the method is based on an inverted version of the encoding of ait-kaci et al. to allow incremental update. simple grouping is used to reduce the code space while keeping the lattice operations efficient. comparisons are made to an incremental version of the range compression scheme of agrawal et al., where each class is assigned an interval, and relationships are based on containment in the interval. the result is two encoding methods which have their relative merits. the former being better for smaller, more structured hierarchies, and the latter for larger, less organized hierarchies.
metadata and data structures for the historical newspaper digital library. we examine metadata and data-structure issues for the historical newspaper digital library. this project proposes to digitize and then do ocr and linguisting processing on several years worth of historical newspapers. newspapers are very complex information objects so developing a rich description of their content is challenging. in addition to frameworks for the logical structure and physical layout, we propose metadata relevant to the image processing and to the historians who will use this collection. finally, we consider how the metadata infrastructure might be managed as it evolves with improved text processing capabilities and how an infrastructure might be developed to support a community of users.
lessons from the implementation of an adaptive parts acquisition eportal. in recent work we have developed a novel approach to the design and implementation of an online portal (eportal) to help application engineers find replacements for electronic parts that have become obsolete (and hence will no longer be produced). our approach makes use of machine learning techniques to improve the performance of a database search function. however, the purpose of this note is not to describe in detail the application nor our technical solution - that has been done elsewhere (see [1,2]). rather, it is our intention to present some of the lessons learned from our project. below, we provide a brief introduction to the technical approach, concentrate on several of the most salient lessons, and conclude with a description of the current state of the project.
improving document representations using relevance feedback: the rfa algorithm. in this paper we present a document representation improvement technique, named the relevance feedback accumulation (rfa) algorithm. using prior relevance feedback assessments and a data mining measure called "support", the algorithm's learning function gradually improves document representations, over time and across users. results show that the modified document representations yield lower dimensionality while improving retrieval effectiveness. the algorithm is efficient and scalable, suited for retrieval systems managing large document collections.
model-guided information discovery for intelligence analysis. intelligence analysis can be aided and guided by models of the analysts' interests and priorities. this paper describes our approach to analyst modeling as part of the ant café project, in which analyst models are used to guide the searching behavior of a swarm of intelligent agents. structural elements of our analyst model include concepts and relations, both of which help to capture the analyst's current interest and concerns. in addition, the concepts and relationships have associated scalar parameters to provide a quantitative measure of the user's level of interest. we have developed algorithms for dynamically adapting the weights and evolving the elements of the model itself. to evaluate these algorithms we have built an analyst modeling environment workbench. we have tested our approach on this workbench using traces generated by human analysts, and have demonstrated improvements over current state of the art search engines.
generating better concept hierarchies using automatic document classification. this paper presents a hybrid concept hierarchy development technique for web returned documents retrieved by a meta-search engine. the aim of the technique is to separate the initial retrieved documents into topical oriented categories, prior to the actual concept hierarchy generation. the topical categories correspond to different semantic aspects of the query. this is done using a 1-of-n automatic document classification, on the initial set of returned documents. then, an individual topical concept hierarchy is automatically generated inside each of the resulted categories. both steps are executed on the fly at retrieval time. due to the efficiency constraints imposed by the web retrieval context, the algorithm only uses document snippets (rather than full web pages) for both document classification and concept hierarchy generation. experimental results show that the algorithm is able to improve the quality of the concept hierarchy presented to the searcher; at the same time, the efficiency parameters are kept within reasonable intervals.
introducing semantics in conceptual schema reuse. although standard components' manufacture and reuse is common practice in many engineering domains (e.g. electrical and mechanical engineering), this is not yet the case with respect to software development. ironically, in such a highly &ldquo;automated&rdquo; domain, users still fail to find available components that match their needs faster than developing them again. the gap between what designers expect from reuse (and how it should be offered), and the actual reuse attempts remains the main barrier. this paper deals with conceptual schema construction in terms of reuse and the respective semantic requirements. it proposes a semantic retrieval mechanism based on imprecise queries for the reuse of conceptual schema components.
extending and inferring functional dependencies in schema transformation. we study the representation, derivation and utilization of a special kind of constraints in multidatabase systems. a major challenge is when component database schemas are <i>schematic discrepant</i> from each other, i.e., data values of one database correspond to schema labels of another. we propose "qualified functional dependencies" (or qualified fds), an extension to conventional fds to formalize integrity constraints in multidatabase systems. we first give inference rules to derive qualified fds in fixed schemas, then study the derivation of qualified fds during the transformations between schematic discrepant schemas. propagation rules are given to derive qualified fds of transformed schemas from qualified fds of original schemas. our work can be used in different stages of building and accessing a multidatabase system, e.g., to detect and resolve value inconsistency in schema integration, to verify lossless schema transformations, to normalize integrated schemas, to verify the integrity of data, and to optimize queries at an integration level. in particular, as an application of our theory, we will use fds to check the validity of schemasql views (schemasql is a powerful multidatabase language).
logical and physical support for heterogeneous data. heterogeneity arises naturally in virtually all real-world data. this paper presents evolutionary extensions to a relational database system for supporting three classes of data heterogeneity: variational, structural and annotational heterogeneities. we define these classes and show the impact of these new features on data storage, data-access mechanisms, and the data-description language. since xml is an important source of heterogeneity, we describe how the system automatically utilizes these new features when storing xml documents.
static score bucketing in inverted indexes. maintaining strict static score order of inverted lists is a heuristic used by search engines to improve the quality of query results when the entire inverted lists cannot be processed. this heuristic, however, increases the cost of index generation and requires complex index build algorithms. in this paper, we study a new index organization based on static score bucketing. we show that this new technique significantly improves in index build performance while having minimal impact on the quality of search results.
learning to summarise xml documents using content and structure. documents formatted in extensible markup language (xml) are becoming increasingly available in collections of various document types. in this paper, we present an approach for the summarisation of xml documents. the novelty of this approach lies in that it is based on features not only from the content of documents, but also from their logical structure. we follow a machine learning like, sentence extraction-based summarisation technique. to find which features are more effective for producing summaries this approach views sentence extraction as an ordering task. we evaluated our summarisation model using the inex dataset. the results demonstrate that the inclusion of features from the logical structure of documents increases the effectiveness of the summariser, and that the learnable system is also effective and well-suited to the task of summarisation in the context of xml documents.
the virgis wfs-based spatial mediation system. the proliferation of spatial data on the internet is beginning to allow a much wider access to data currently available in various geographic information systems (gis). in order to provide effective spatial database integration, we need to provide flexible and powerful gis data integration solutions. indeed, gis are highly heterogeneous: not only they differ by their data representations, but they also offer radically different query languages. a gis mediation approach should provide an integrated view of the data supplied by all sources, and a geographical query language to access and manipulate integrated data.
advances in phonetic word spotting. phonetic speech retrieval is used to augment word based retrieval in spoken document retrieval systems, for in and out of vocabulary words. in this paper, we present a new indexing and ranking scheme using metaphones and a bayesian phonetic edit distance. we conduct an extensive set of experiments using a hundred hours of hub4 data with ground truth transcript and twenty-four thousands query words. we show improvement of up to 15% in precision compare to results obtained speech recognition alone, at a processing time of 0.5 sec per query.
a self-managing data cache for edge-of-network web applications. database caching at proxy servers enables dynamic content to be generated at the edge of the network, thereby improving the scalability and response time of web applications. the scale of deployment of edge servers coupled with the rising costs of their administration demand that such caching middleware be adaptive and self-managing. to achieve this, a cache must be dynamically populated and pruned based on the application query stream and access pattern. in this paper, we describe such a cache which maintains a large number of materialized views of previous query results. cached "views" share physical storage to avoid redundancy, and are usually added and evicted dynamically to adapt to the current workload and to available resources. these two properties of large scale (large number of cached views) and overlapping storage introduce several challenges to query matching and storage management which are not addressed by traditional approaches. in this paper, we describe an edge data cache architecture with a flexible query matching algorithm and a novel storage management policy which work well in such an environment. we perform an evaluation of a prototype of such an architecture using the tpc-w benchmark and find that it reduces query response times by up to 75%, while reducing network and server load.
multi-resolution disambiguation of term occurrences. we describe a system for extracting mentions of terms such as company and product names, in a large and noisy corpus of documents, such as the world wide web. since natural language terms are highly ambiguous, a significant challenge in this task is disambiguating which occurrences of each term are truly related to the right meaning, and which are not. we describe our approach for disambiguation, and show that it achieves very high accuracy with only limited training. this serves as a necessary first step for applications that strive to do analytics on term mentions.
topic-based document segmentation with probabilistic latent semantic analysis. this paper presents a new method for topic-based document segmentation, i.e., the identification of boundaries between parts of a document that bear on different topics. the method combines the use of the probabilistic latent semantic analysis (plsa) model with the method of selecting segmentation points based on the similarity values between pairs of adjacent blocks. the use of plsa allows for a better representation of sparse information in a text block, such as a sentence or a sequence of sentences. furthermore, segmentation performance is improved by combining different instantiations of the same model, either using different random initializations or different numbers of latent classes. results on commonly available data sets are significantly better than those of other state-of-the-art systems.
efficient query evaluation using a two-level retrieval process. we present an efficient query evaluation method based on a two level approach: at the first level, our method iterates in parallel over query term postings and identifies candidate documents using an approximate evaluation taking into account only partial information on term occurrences and no query independent factors; at the second level, promising candidates are fully evaluated and their exact scores are computed. the efficiency of the evaluation process can be improved significantly using dynamic pruning techniques with very little cost in effectiveness. the amount of pruning can be controlled by the user as a function of time allocated for query evaluation. experimentally, using the trec web track data, we have determined that our algorithm significantly reduces the total number of full evaluations by more than 90%, almost without any loss in precision or recall. at the heart of our approach there is an efficient implementation of a new boolean construct called wand or weak and that might be of independent interest.
key problems in integrating structured and unstructured information. this forum will host a discussion among the panelists - and with the audience - on key trends in information technology, as well as on industry and government problems in search of technology solutions. the panel will focus on the core problems inherent in integrating structured and unstructured textual information, moving from application-centric to user-centric software, and merging knowledge management with data management.
towards speech as a knowledge resource. speech is a tantalizing mode of human communication. on the one hand, humans understand speech with ease and use speech to express complex ideas, information, and knowledge. on the other hand, automatic speech recognition with computers is still very hard, and extracting knowledge from speech is even harder. in this paper we motivate the study of speech as a knowledge resource and briefly survey a family of related applications and systems being developed at ibm research aimed towards the goal of exploiting speech as a knowledge resource.
a learning approach to processor allocation in parallel systems. given a typical parallel system and a collection of applications that are to execute on the system, a common problem is determining an effective allocation of processors among the applications. in this paper a learning approach is applied to processor allocation. the approach is to use a stochastic learning automaton (sla) as a decision tool. an sla uses values of the current state description, makes an allocation decision, evaluates its decision at some later time, modifies its decision making process, and tries to find the best allocation strategy by learning from its previous mistakes. the method is applied to the problem of allocating processors to parallel applications in a distributed system such as a cluster of workstations, and is validated through simulation. the result of this study show that a learning approach that utilizes a stochastic learning automaton is effective at making processor allocation decisions in a parallel system.
faciliating knowledge flow through the enterprise. this paper is concerned with the issues we encountered when attempting to achieve enterprise level knowledge reuse. we present 3 pilot studies where new visualization techniques were used to allow manufacturing and service operations take advantage of engineering knowledge embodied in 3d models. though all these studies showed dramatic productivity increases, only one business unit from the studies is currently working to achieve the reuse. there are a number of reasons why this is so, but the key underlying theme is a lack of enterprise level commitment to knowledge sharing and a lack of an adequate knowledge architecture for sharing knowledge across organizational boundaries. we conclude with an approach for facilitating knowledge flow across functional units.
archiving telemeetings. this paper presents a prototype system for modeling and managing the complete life-time of telemeetings/teleconferences. the system provides services for modeling telemeetings, storing telemeetings in a telemeeting database, annotating telemeetings and querying the telemeeting database.
experimental evaluation of dynamic data allocation strategies in a distributed database with changing workloads. traditionally, allocation of data in distributed database management systems has been determined by off-line analysis and optimization. this technique works well for static database access patterns, but is often inadequate for frequently changing workloads. in this paper we address how to dynamically reallocate data for partionable distributed databases with changing access patterns. rather than complicated and expensive optimization algorithms, a simple heuristic is presented and shown, via an implementation study, to improve system throughput by 3 based system. based on artificial wide area network delays, we show that dynamic reallocation can improve system throughput by a factor of two and a half for wide area networks. we also show that individual site load must be taken into consideration when reallocating data, and provide a simple policy that incorporates load in the reallocation decision.
hashing by proximity to process duplicates in spatial databases. in a spatial database, an object may extend arbitrarily in space. as a result, many spatial data structures (e.g., the quadtree, the cell tree, the r+-tree) represent an object by partitioning it into multiple, yet simple, pieces, each of which is stored separately inside the data structure. many operations on these data structures are likely to produce duplicate results because of the multiplicity of object pieces. a novel approach for duplicate processing based on proximity of spatial objects is presented. this is different from conventional duplicate elimination in database systems because, with spatial databases, different pieces of the same object can span multiple buckets of the underlying data structure. example algorithms are presented to perform duplicate processing using proximity for quadtree representation of line segments and arbitrary rectangles. the complexity of the algorithms is seen to depend on a geometric classification of different instances of the spatial objects. by using proximity and the spatial properties of the objects, the number of disk-i/o requests as well as the run-time storage during duplicate processing can be reduced.
intelligent caching: selecting, representing, and reusing data in an information server. accessing information sources to retrieve data requested by a user can be expensive, especially when dealing with distributed information sources. one way to reduce this cost is to cache the results of queries, or related classes of data. this paper presents an approach to caching and addresses the issues of which information to cache, how to describe what has been cached, and how to use the cached information to answer future queries. we consider these issues in the context of the sims information server, which is a system for retrieving information from multiple heterogeneous and distributed information sources. the design of this information server is ideal for representing and reusing cached information since each class of cached information is simply viewed as another information source that is available for answering future queries.
inferring query models by computing information flow. the language modelling approach to information retrieval can also be used to compute query models. a query model can be envisaged as an expansion of an initial query. the more prominent query models in the literature have a probabilistic basis. this paper introduces an alternative, non-probabilistic approach to query modelling whereby the strength of information flow is computed between a query q and a term w. information flow is a reflection of how strongly w is informationally contained within the query q. the information flow model is based on hyperspace analogue to language (hal) vector representations, which reflects the lexical co-occurrence information of terms. research from cognitive science has demonstrated the cognitive compatibility of hal representations with human processing. query models computed from trec queries by hal-based information flow are compared experimentally with two probabilistic query language models. experimental results are provided showing the hal-based information flow model be superior to query models computed via markov chains, and seems to be as effective as a probabilistically motivated relevance model.
generalized contextualization method for xml information retrieval. a general re-weighting method, called contextualization, for more efficient element ranking in xml retrieval is introduced. re-weighting is based on the idea of using the ancestors of an element as a context: if the element appears in a good context -- good interpreted as probability of relevance -- its weight is increased in relevance scoring; if the element appears in a bad context, its weight is decreased. the formal presentation of contextualization is given in a general xml representation and manipulation frame, which is based on utilization of structural indices. this provides a general approach independent of weighting schemas or query languages.contextualization is evaluated with the inex test collection. we tested four runs: no contextualization, parent, root and tower contextualizations. the contextualization runs were significantly better than no contextualization. the root contextualization was the best among the re-weighted runs.
itopn: incremental extraction of the n most visible objects. the visual exploration of large databases calls for a tight coupling of database and visualization systems. current visualization systems typically fetch all the data and organize it in a scene tree, which is then used to render the visible data. for immersive data explorations, where an observer navigates in a potentially huge data space and explores selected data regions this approach is inadequate. a scalable approach is to make the database system observer-aware and exchange the data that is visible and most relevant to the observer.in this paper we present itopn an incremental algorithm for extracting the most visible objects relative to the current position of the observer. we implement itopn and compare it to an improved version of the r-tree that extends lru with the caching of the top levels of the r-tree (lw-lru). our experiments show that itopn is orders of magnitude faster than lw-lru given the same amount of memory. our experiments also show that for lw-lru to perform as fast as itopn it needs three times as much memory.
indexing time vs. query time: trade-offs in dynamic information retrieval systems. we examine issues in the design of fully dynamic information retrieval systems supporting both document insertions and deletions. the two main components of such a system, index maintenance and query processing, affect each other, as high query performance is usually paid for by additional work during update operations. two aspects of the system -- incremental updates and garbage collection for delayed document deletions -- are discussed, with a focus on the respective indexing vs. query performance trade-offs. depending on the relative number of queries and update operations, different strategies lead to optimal overall performance.
extracting meaningful labels for websom text archives. self-organizing maps, being used mainly with data that are not pre-labeled, need automatic procedures for extracting keywords as labels for each of the map units. the websom methodology for building very large text archives has a very slow method for extracting such unit labels. it computes the relative frequencies of all the words of all the documents associated to each unit and then compares these to the relative frequencies of all the words of all the other units of the map. since maps may have more than 100,000 units and the archive may contain up to 7 million documents, the existing websom method is not practical. this paper describes how the meaningful labels per map unit can be deduced by analyzing the relative weight distribution of the som weight vectors and by taking advantage of some characteristics of the random projection method used in dimensionality reduction. the effectiveness of this technique is demonstrated on archives of the well studied reuters and cnn collections. comparisons with the websom method are provided.
hierarchical document categorization with support vector machines. automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. standard machine learning techniques like support vector machines and related large margin methods have been successfully applied for this task, albeit the fact that they ignore the inter-class relationships. in this paper, we propose a novel hierarchical classification method that generalizes support vector machine learning and that is based on discriminant functions that are structured in a way that mirrors the class hierarchy. our method can work with arbitrary, not necessarily singly connected taxonomies and can deal with task-specific loss functions. all parameters are learned jointly by optimizing a common objective function corresponding to a regularized upper bound on the empirical loss. we present experimental results on the wipo-alpha patent collection to show the competitiveness of our approach.
structural proximity searching for large collections of semi-structured data. the richness of the xml data format allows data to be structured in a way which precisely captures the semantics required by the author. it is the structure of the data, however, which forms the basis of all xml query languages. without at least some notion of the structure, a user cannot meaningfully query the data. this problem is compounded when one considers that heterogeneous data adhering to different schema are likely to exist in the database(s) being queried. this paper proposes a solution based on an efficient proximity index. in particular, we describe a family of encoding and compression schemes which enable us to build an index to efficiently implement the proximity search. our index is extremely small, and can reflect updates in the underlying database in modest time. experiments show that our algorithm and implementation are fast and scale well.
a study of parameter tuning for term frequency normalization. most current term frequency normalization approaches for information retrieval involve the use of parameters. the tuning of these parameters has an important impact on the overall performance of the information retrieval system. indeed, a small variation in the involved parameter(s) could lead to an important variation in the precision/recall values. most current tuning approaches are dependent on the document collections. as a consequence, the effective parameter value cannot be obtained for a given new collection without extensive training data. in this paper, we propose a novel and robust method for the tuning of term frequency normalization parameter(s), by measuring the normalization effect on the within document frequency of the query terms. as an illustration, we apply our method on amati \& van rijsbergen's so-called normalization 2. the experiments for the ad-hoc trec-6,7,8 tasks and trec-8,9,10 web tracks show that the new method is independent of the collections and able to provide reliable and good performance.
automatic query expansion based on divergence. in this paper we are mainly concerned with discussion of a formal model, based on the basic concept of divergence from information theory, for automatic query expansion. the basic principles and ideas on which our study is based are described. a theoretical framework is established, which allows the comparison and evaluation of different term scoring functions for identifying good terms for query expansion. the approaches proposed in this paper have been implemented and evaluated on collections from trec. preliminary results show that our approaches are viable and worthy of continued investigation.
query expansion using term relationships in language models for information retrieval. language modeling (lm) has been successfully applied to information retrieval (ir). however, most of the existing lm approaches only rely on term occurrences in documents, queries and document collections. in traditional unigram based models, terms (or words) are usually considered to be independent. in some recent studies, dependence models have been proposed to incorporate term relationships into lm, so that links can be created between words in the same sentence, and term relationships (e.g. synonymy) can be used to expand the document model. in this study, we further extend this family of dependence models in the following two ways: (1) term relationships are used to expand query model instead of document model, so that query expansion process can be naturally implemented; (2) we exploit more sophisticated inferential relationships extracted with information flow (if). information flow relationships are not simply pairwise term relationships as those used in previous studies, but are between a set of terms and another term. they allow for context-dependent query expansion. our experiments conducted on trec collections show that we can obtain large and significant improvements with our approach. this study shows that lm is an appropriate framework to implement effective query expansion.
combining link-based and content-based methods for web document classification. this paper studies how link information can be used to improve classification results for web collections. we evaluate four different measures of subject similarity, derived from the web link structure, and determine how accurate they are in predicting document categories. using a bayesian network model, we combine these measures with the results obtained by traditional content-based classifiers. experiments on a web directory show that best results are achieved when links from pages outside the directory are considered. link information alone is able to obtain gains of up to 46 points in f1, when compared to a traditional content-based classifier. the combination with content-based methods can further improve the results, but too much noise may be introduced, since the text of web pages is a much less reliable source of information. this work provides an important insight on which measures derived from links are more appropriate to compare web documents and how these measures can be combined with content-based algorithms to improve the effectiveness of web classification.
multi-resolution modeling of large scale scientific simulation data. to provide scientists and engineers with the ability to explore and analyze tera-scale size data-sets we are using a twofold approach. first, we model the data with the objective of creating a compressed yet manageable representation. second, with that compressed representation, we provide the ability to query the resulting approximation in order to obtain approximate yet sufficient answers; a process called ad-hoc querying. this paper is concerned with a wavelet modeling technique that seeks to capture the important physical characteristics of the target scientific data. our approach is driven by the compression, which is necessary for viable throughput, along with the end user requirements from the discovery process. our work contrasts existing research which applies wavelets to range querying, change detection, and clustering problems by working directly with the wavelet decomposition of the data. the difference in this procedure is due primarily to the nature of the data and the requirements of the scientists and engineers. our approach directly uses the wavelet coefficients of the data to compress as well as query. we describe how the wavelet decomposition is used to facilitate data compression and how queries are posed on the resulting compressed model. results of this process will be shown for several problems of interest.
discovery of decision rules in relational databases: a rough set approach. we develop an attribute-oriented rough set approach for the discovery of decision rules in relational databases. our approach combines machine learning techniques and rough set theory. we consider a learning procedure to consist of the two phases data generalization and data reduction. in the data generalization phase, utilizing knowledge about concept hierarchies and relevance of the data, an attribute-oriented induction is performed attribute by attribute. some undesirable attributes of the discovery task are removed and the primitive data in the databases are generalized to the desirable level; this process greatly decreases the number of tuples which must be examined for the discovery task and substantially reduces the computational complexity of the database learning processes. subsequently, in data reduction phase, rough set theory is applied to the generalized relation; the cause-effect relationships among the condition and decision attributes in the databases are analyzed and the non-essential or irrelevant attributes to the discovery task are eliminated without losing information of the original database system. this process further reduces the generalized relation. thus very concise and more accurate decision rules for each class in the decision attribute with little or no redundancy information, can be extracted automatically from the reduced relation during the learning process. our study shows that attribute-oriented induction combined with rough set theory provide an efficient and effective mechanism for discovering decision rules in database systems.
addressing the lack of direct translation resources for cross-language retrieval. most cross language information retrieval research concentrates on language pairs for which direct, rich, and often multiple translation resources already exist. however, for most language pairs, translation via an intermediate language is necessary. two distinct methods for dealing with the additional ambiguity introduced by the extra translation step have been proposed and individually, shown to improve retrieval effectiveness. two previous works indicated that in combination, the methods were ineffective. this paper provides strong empirical evidence that the methods can be combined to produce consistent and often significant improvements in retrieval effectiveness. the improvement is shown across a number of different intermediate languages and test collections.
web-dl: an experience in building digital libraries from the web. the web contains a huge volume of information, almost all unstructured and, therefore, difficult to manage. in digital libraries, however, information is explicitly organized, described, and managed. in this paper, we propose an architecture that allows the construction of digital libraries from the web, using standard protocols and archival technologies, and incorporating powerful digital library and data extraction tools, thus benefiting from the breadth of the web contents, but supporting services and organization available in digital libraries. the proposed architecture was applied to the networked digital library of theses and dissertations, providing an important first step toward rapid construction of large dls from the web, as well as a large-scale solution for interoperability between independent digital libraries.
f4: large-scale automated forecasting using fractals. forecasting has attracted a lot of research interest, with very successful methods for periodic time series. here, we propose a fast, automated method to do non-linear forecasting, for both periodic as well as chaotic time series. we use the technique of delay coordinate embedding, which needs several parameters; our contribution is the automated way of setting these parameters, using the concept of `intrinsic dimensionality'. our operational system has fast and scalable algorithms for preprocessing and, using r-trees, also has fast methods for forecasting. the result of this work is a black-box which, given a time series as input, finds the best parameter settings, and generates a prediction system. tests on real and synthetic data show that our system achieves low error, while it can handle arbitrarily large datasets.
searching web databases by structuring keyword-based queries. on-line information services have become widespread in the web nowadays. however, web users are non-specialized and have a great variety of interests. thus, interfaces for web databases must be simple and uniform. in this paper we present an approach, based on bayesian networks, for querying web databases using keywords only. according to this approach, the user inputs a query through a simple search-box interface. from the input query, one or more plausible structured queries are derived and submitted to web databases. the results are then retrieved and presented to the user as ranked answers. our approach reduces the complexity of existing on-line interfaces and offers a solution to the problem of querying several distinct web databases with a single interface. the applicability of the proposed approach was demonstrated by experimental results with 3 databases, obtained with a prototype search system that implements it. we have found that from 77% to 95% of the time, one of the top three resulting structured queries is the proper one. further, when the user selects one of these three top queries for processing, the ranked answers present average precision figures from 60% to about 100%.
rapid association rule mining. association rule mining is a well-researched area where many algorithms have been proposed to improve the speed of mining. in this paper, we propose an innovative algorithm called rapid association rule mining (rarm) to once again break this speed barrier. it uses a versatile tree structure known as the support-ordered trie itemset (sotrieit) structure to hold pre-processed transactional data. this allows rarm to generate large 1-itemsets and 2-itemsets quickly without scanning the database and without candidate 2-itemset generation. it achieves significant speed-ups because the main bottleneck in association rule mining using the apriori property is the generation of candidate 2-itemsets. rarm has been compared with the classical mining algorithm apriori and it is found that it outperforms apriori by up to two orders of magnitude (100 times), much more than what recent mining algorithms are able to achieve.
performance and implications of semantic indexing in a distributed environment. a research prototype is presented for semantic indexing and retrieval in information retrieval. the prototype is motivated by a desire to provide a more efficient and effective information retrieval system compared to the current state of the art. an overview of the interspace architecture layers is discussed. an object model supporting semantic operations is developed. the model contains a rich set of classes and relationships of the data for the semantic indexing module. the basis of our semantic indexing is done by the creation of concept space. a concept space is an index of a collection that uses document statistics to capture the relationships between concepts. it is useful for boosting text search, by term suggestion of alternative terms semantically related to query terms. over the years, we have developed generic technology for concept spaces computation on large collections across many subjects. recent computations on discipline-scale collections have been made on high-end supercomputers. this paper describes our implementation and implications of the computation in a distributed computing environment. experimental results using different collection sizes and number of processes are presented to show the feasibility of this approach. we also show that laboratory and community collections are already easily computable using a group of pcs in a lab via a message-passing model. we conclude that pc clusters will shortly be able to compute semantic indexes for any real collections.
analytical version control management in a hypertext system. in this paper it is shown how structural and cognitive versioning issues can be efficiently managed in a petri nets based hypertextual model. the advantages of this formalism are enhanced by modular and structured modeling; modularity allows to focus the attention only on some modules, while giving the abstraction of the others. each module owns metaknowledge that is useful in defining new layers and contexts.the central point of the data model is the formulation and resolution of three recurrence equations, effective in describing both the versioning and the derivation history; these equations permit to express in precise terms both the structural evolution (changes operated on specific nodes of the net) and the behavioral one (changes concerning browsing).
facilitating transformations in a human genome project database. human genome project databases present a confluence of interesting database challenges: rapid schema and data evolution, complex data entry and constraint management, and the need to integrate multiple data sources and software systems which range over a wide variety of models and formats. while these challenges are not necessarily unique to biological databases, their combination, intensity and complexity are unusual and make automated solutions imperative. we illustrate these problems in the context of the philadelphia genome center for human chromosome 22, and describe a new approach to a solution for these problems, by means of a deductive language for expressing database transformations and constraints.
digital annotation of printed documents. we present a general model and information server for the digital annotation of printed documents. the resulting annotation framework supports both informal and structured annotations as well as context-dependent services. a demonstrator application for mammography that features both enhanced writing and reading activities is described.
a music recommendation system based on music data grouping and user interests. with the growth of the world wide web, a large amount of music data is available on the internet. in addition to searching expected music objects for users, it becomes necessary to develop a recommendation service. in this paper, we design the music recommendation system (mrs) to provide a personalized service of music recommendation. the music objects of midi format are first analyzed. for each polyphonic music object, the representative track is first determined, and then six features are extracted from this track. according to the features, the music objects are properly grouped. for users, the access histories are analyzed to derive user interests. the content-based, collaborative and statistics-based recommendation methods are proposed, which are based on the favorite degrees of the users to the music groups. a series of experiments are carried out to show that our approach is feasible.
replication and retrieval strategies of multidimensional data on parallel disks. aside from enhancing data availability during disk failures, replication of data is also used to speed up i/o performance of read-intensive applications. there are two issues that need to be addressed: (a) data placement (which disks should store the copies of each data block?) and (b) scheduling (given a query q, and a placement scheme p of the data, from which disk should each block in q be retrieved so that retrieval time is minimized?) in this paper, we consider range queries and assume that the dataset is a multidimensional grid and r copies of each unit block of the grid must be stored among m disks. to accurately measure performance of a scheduling algorithm, we consider a metric that takes into account the scheduling overhead as well as the time it takes to retrieve the data blocks from the disks. we describe several combinations of data placement schemes and scheduling algorithms and analyze their performance for range queries with respect to the above metric. we then present simulation results for the most interesting case r=2, showing that the strategies do perform better than the previously known method, especially for large queries.
on the efficient evaluation of relaxed queries in biological databases. in this paper, a new technique is developed to support the query relaxation in biological databases. query relaxation is required due to the fact that queries tend not to be expressed exactly by the users, especially in scientific databases such as biological databases, in which complex domain knowledge is heavily involved. to treat this problem, we propose the concept of the so-called fuzzy equivalence classes to capture important kinds of domain knowledge that is used to relax queries. this concept is further integrated with the canonical techniques for pattern searching such as the position tree and automaton theory. as a result, fuzzy queries produced through relaxation can be efficiently evaluated. this method has been successfully utilized in a practical biological database - the gpcrdb.
mass: a multi-axis storage structure for large xml documents. effective indexing for xml must consider both the query requirements of the xpath language and the dynamic nature of xml. we introduce mass, a multiple axis storage structure, to provide scalable indexing for xpath expressions with guaranteed update performance. we describe the building blocks of mass and provide results that demonstrate mass's scalability. we show that mass can outperform other state-of-the-art xml indexing solutions, even with constrained system resources.
xkvalidator: a constraint validator for xml. the role of xml in data exchange is evolving from one of merely conveying the structure of data to one that also conveys its semantics. in particular, several proposals for key and foreign key constraints have recently appeared, and aspects of these proposals have been adopted within xmlschema.in this paper, we examine the problem of checking keys and foreign keys in xml documents using a validator based on sax. the algorithm relies on an indexing technique based on the paths found in key definitions, and can be used for checking the correctness of an entire document (bulk checking) as well as for checking updates as they are made to the document (incremental checking). the asymptotic performance of the algorithm is linear in the size of the document or update. furthermore, experimental results demonstrate reasonable performance.
using conjunction of attribute values for classification. advances in the efficient discovery of frequent itemsets have led to the development of a number of schemes that use frequent itemsets to aid developing accurate and efficient classifiers. these approaches use the frequent itemsets to generate a set of composite features that expand the dimensionality of the underlying dataset. in this paper, we build upon this work and (i) present a variety of schemes for composite feature selection that achieve a substantial reduction in the number of features without adversely affecting the accuracy gains, and (ii) show (both analytically and experimentally) that the composite features can lead to improved classification models even in the context of support vector machines, in which the dimensionality can automatically be expanded by the use of appropriate kernel functions.
statistical relationship determination in automatic thesaurus construction. statistical relationship determination among terms is one of the key issues in automatic thesaurus construction. we systematically analyze existing relevant approaches based on their underlying probabilistic assumptions, and propose a combined approach that overcomes their limitations.
i/o-efficient techniques for computing pagerank. over the last few years, most major search engines have integrated link-based ranking techniques in order to provide more accurate search results. one widely known approach is the pagerank technique, which forms the basis of the google ranking scheme, and which assigns a global importance measure to each page based on the importance of other pages pointing to it. the main advantage of the pagerank measure is that it is independent of the query posed by a user; this means that it can be precomputed and then used to optimize the layout of the inverted index structure accordingly. however, computing the pagerank measure requires implementing an iterative process on a massive graph corresponding to billions of web pages and hyperlinks.in this paper, we study i/o-efficient techniques to perform this iterative computation. we derive two algorithms for pagerank based on techniques proposed for out-of-core graph algorithms, and compare them to two existing algorithms proposed by haveliwala. we also consider the implementation of a recently proposed topic-sensitive version of pagerank. our experimental results show that for very large data sets, significant improvements over previous results can be achieved on machines with moderate amounts of memory. on the other hand, at most minor improvements are possible on data sets that are only moderately larger than memory, which is the case in many practical scenarios.
local methods for estimating pagerank values. the google search engine uses a method called pagerank, together with term-based and other ranking techniques, to order search results returned to the user. pagerank uses link analysis to assign a global importance score to each web page. the pagerank scores of all the pages are usually determined off-line in a large-scale computation on the entire hyperlink graph of the web, and several recent studies have focused on improving the efficiency of this computation, which may require multiple hours on a workstation. however, in some scenarios, such as online analysis of link evolution and mining of large web archives such as the internet archive, it may be desirable to quickly approximate or update the pageranks of individual nodes without performing a large-scale computation on the entire graph. we address this problem by studying several methods for efficiently estimating the pagerank score of a particular web page using only a small subgraph of the entire web. in our model, we assume that the graph is accessible remotely via a link database (such as the altavista connectivity server) or is stored in a relational database that performs lookups on disks to retrieve node and connectivity information. we show that a reasonable estimate of the pagerank value of a node is possible in most cases by retrieving only a moderate number of nodes in the local neighborhood of the node.
regularizing ad hoc retrieval scores. the cluster hypothesis states: closely related documents tend to be relevant to the same request. we exploit this hypothesis directly by adjusting ad hoc retrieval scores from an initial retrieval so that topically related documents receive similar scores. we refer to this process as score regularization. score regularization can be presented as an optimization problem, allowing the use of results from semi-supervised learning. we demonstrate that regularized scores consistently and significantly rank documents better than unregularized scores, given a variety of initial retrieval algorithms. we evaluate our method on two large corpora across a substantial number of topics.
an optimal graph traversal algorithm for evaluating linear binary-chain programs. grahne et al. have presented a graph algorithm for a subset of recursive queries. this method consists of two phases. in the first phase, the method transforms a linear binary-chain program into a set of equations over expressions containing predicate symbols. in the second phase, a graph is constructed from the equations and the answers are produced by traversing the relevant paths. here we describe a new algorithm which requires less time than the algorithm of grahne et al. the key idea of the improvement is to reduce the search space that will be traversed when a query is invoked. further, we speed up the evaluation of cyclic data by generating most answers directly in terms of the answers already found and the associated &ldquo;path information&rdquo; instead of traversing the corresponding paths as usual. in this way, our algorithm achieves a linear time complexity for both cyclic and non-cyclic data.
clustermap: labeling clusters in large datasets via visualization. with the rapid increase of data in many areas, clustering on large datasets has become an important problem in data analysis. since cluster analysis is a highly iterative process, cluster analysis on large datasets prefers short iteration on a relatively small representative set. thus, a two-phase framework "sampling/summarization - iterative cluster analysis" is often applied in practice. since the clustering result only labels the small representative set, there are problems with extending the result to the entire large dataset, which are almost ignored by the traditional clustering research. this extending is often named as labeling process. labeling irregular shaped clusters, distinguishing outliers and extending cluster boundary are the main problems in this stage. we address these problems and propose a visualization-based approach to dealing with them precisely. this approach partially involves human into the process of defining and refining the structure "clustermap". based on this structure, the clustermap algorithm scans the large dataset to adapt the boundary extension and generate the cluster labels for the entire dataset. experimental result shows that clustermap can preserve cluster quality considerably with low computational cost, compared to the distance-comparison-based labeling algorithms.
swoogle: a search and metadata engine for the semantic web. swoogle is a crawler-based indexing and retrieval system for the semantic web. it extracts metadata for each discovered document, and computes relations between documents. discovered documents are also indexed by an information retrieval system which can use either character n-gram or urirefs as keywords to find relevant documents and to compute the similarity among a set of documents. one of the interesting properties we compute is <i>ontology rank</i>, a measure of the importance of a semantic web document.
categorizing information objects from user access patterns. many web sites have dynamic information objects whose topics change over time. classifying these objects automatically and promptly is a challenging and important problem for site masters. traditional content-based and link structure based classification techniques have intrinsic limitations for this task. this paper proposes a framework to classify an object into an existing category structure by analyzing the users' traversals in the category structure. the key idea is to infer an object's topic from the predicted preferences of users when they access the object. we compare two approaches using this idea. one analyzes collective user behavior and the other each user's accesses. we present experimental results on actual data that demonstrate a much higher prediction accuracy and applicability with the latter approach. we also analyze the correlation between classification quality and various factors such as the number of users accessing the object. to our knowledge, this work is the first effort in combining object classification with user access prediction.
time weight collaborative filtering. collaborative filtering is regarded as one of the most promising recommendation algorithms. the item-based approaches for collaborative filtering identify the similarity between two items by comparing users' ratings on them. in these approaches, ratings produced at different times are weighted equally. that is to say, changes in user purchase interest are not taken into consideration. for example, an item that was rated recently by a user should have a bigger impact on the prediction of future user behaviour than an item that was rated a long time ago. in this paper, we present a novel algorithm to compute the time weights for different items in a manner that will assign a decreasing weight to old data. more specifically, the users' purchase habits vary. even the same user has quite different attitudes towards different items. our proposed algorithm uses clustering to discriminate between different kinds of items. to each item cluster, we trace each user's purchase interest change and introduce a personalized decay factor according to the user own purchase behaviour. empirical studies have shown that our new algorithm substantially improves the precision of item-based collaborative filtering without introducing higher order computational complexity.
evaluating window joins over punctuated streams. we explore join optimizations in the presence of both time-based constraints (sliding windows) and value-based constraints (punctuations). we present the first join solution named pwjoin that exploits such combined constraints to shrink the runtime join state and to propagate punctuations to benefit downstream operators. we design a state structure for pwjoin that facilitates the exploitation of both constraint types. we also explore optimizations enabled by the interactions between window and punctuation, e.g., early punctuation propagation. the costs of the pwjoin are analyzed using a cost model. we also conduct an experimental study using cape continuous query system. the experimental results show that in most cases, by exploiting punctuations, pwjoin outperforms the pure window join with regard to both memory overhead and throughput. our technique complements the joins in the literature, such as symmetric hash join or window join, to now require less runtime resources without compromising the accuracy of the result.
expedite: a system for encoded xml processing. as xml becomes an increasingly popular format for information exchange, the efficient processing of broadcast xml data on a constrained device (for example, a cell phone or a pda) becomes a critical task. in this paper we present the expedite system: a new model of data processing in an information exchange environment, which "migrates" the power of the data-sending server to receivers for efficient processing. it consists of a simple and general encoding scheme for servers, and streaming query processing algorithms on encoded xml stream for data receivers with constrained computing abilities. experiments show the impressive performance of expedite.
a practical system of keyphrase extraction for web pages. keyphrases can be used to facilitate web users grasping the main topic(s) of a web page. we present a practical system of automatic keyphrase extraction for web pages. in this system, a regression model was first trained based on a set of human-labeled documents. then it was used to extract keyphrases from new pages automatically. this paper makes three contributions. first, the structure information in a web page was investigated for keyphrase extraction task. second, the query log data associated with a web page collected by a search engine server were used to help keyphrase extraction. third, a method was put forward in this paper in order to evaluate the similarity of phrases.
an optimized implementation for vml based on pattern matching and dynamic programming. in an object-oriented database system (oodbs), objects exist persistently and object i/o is transparent to the programmer. therefore, some mechanism in the system must initiate i/o as the program runs. in this paper we present an approach based on pattern matching and dynamic programming that allows a program to interact efficiently with the runtime storage layer. we are interested in allowing programs to manipulate very large objects without necessarily reading them entirely. if a program touches only a small part of a large object, the problem is how to determine the part of the object needed. in this paper, we present an approach based on pattern matching and dynamic programming to resolve this problem.we discuss and solve this problem in the context of vml, a modeling language of an open object-oriented database language. the vml compiler translates vml programs into c++ programs which contain calls to the object manager. we provide a detailed description of our implementation with the hope that our approach will foster the development of object-oriented database systems based on c++.
practical evaluation of ir within automated classification systems. this paper describes some of the work we have done to evaluate and compare the use of three ir systems (verity, lsi, and smart) as black boxes within an automated classification environment. we use automated classification to make a quantitative comparison of the effectiveness of the systems within this context. in so doing, we also develop criteria for the construction of a useful training set. these results lead to metrics useful in the integration of ir systems into larger applications. we conclude with an initial api for an ir component within an automated classification architecture.
an extended logic programming based multi-agent system formalization in mobile environments. in this paper, we propose an extended logic programming based formalization for a multi-agent system in mobile environments. such a system consists of a number of agents connected via wire or wireless communication channels. our formalization is knowledge oriented and has declarative semantics inherited from extended logic programming. this model can be used to study the details of knowledge transaction in mobile environments.
auto-generation of topic hierarchies for web images from users' perspectives. in this paper, we propose an approach to automatically generating a yahoo!-like topic hierarchy for organizing web images from users' perspectives. relatively little effort has been devoted towards providing such a taxonomy simultaneously considering users' image requests for semantic and visual information. based on the characteristic that a web-image query may be refined by various attributes, the proposed approach hierarchically groups similar queries from search engine logs into topic classes at different semantic levels. the generated topic hierarchy has the advantages of organizing image data from users' perspectives for browsing, searching, annotation and users' needs analysis.a series of experiments have been conducted on real-world image search engine logs. experimental results show that the proposed approach is feasible to generate topic hierarchies for web images. moreover, the generated hierarchy has been successfully applied to analysis of users' search interests, which have more focuses on some specific domains when compared with document requests.
a pattern matching language for spatio-temporal databases. we propose a pattern matching language for spatio-temporal databases. the matching process in time dimension is based upon the evolutionary nature of time, but in spatial dimension it is based on placement, shape and sizes of regions. the concept of pattern matching introduced in this paper is independent of the choice of the underlying model for spatio-temporal databases. in particular, the pattern matching language seamlessly extends our sql-like query language parasql for spatio-temporal databases. the pattern matching language would also have application in active databases, because patterns can be used as triggers.
database support for species extraction from the biosystematics literature: a feasibility demonstration. a part of the biosystematics literature is currently being digitized and manually marked up with xml. fast search on such documents shall be feasible. but marking up such documents incurs high costs, and biologists would like to know the value of such an activity in advance. deploying standard xml database technology in a straightforward way is not feasible, because of two characteristics of biosystematics documents. the first one is that descriptions of taxa are related, i.e., a more specific taxon should inherit from a more general one. the combination of inheritance with information-retrieval mechanisms gives rise to difficulties addressed in this article. the second issue is the frequent occurrence of very specific technical terms in such documents, i.e., geographical information or biological terms. to investigate the characteristics of the search in the presence of such difficulties, we have designed and implemented a respective system, based on relational database technology. we use a collection of xml documents that mimics the characteristics of biosystematics documents, as we will explain. we propose two query-evaluation alternatives and compare them by means of performance experiments. it turns out that our techniques can administer the envisioned corpus of documents efficiently and cope with those problems at the same time.
requirement-based data cube schema design. on-line analytical processing (olap) requires efficient processing of complex decision support queries over very large databases. it is well accepted that pre-computed data cubes can help reduce the response time of such queries dramatically. a very important design issue of an efficient olap system is therefore the choice of the right data cubes to materialize. we call this problem the data cube schema design problem. in this paper we show that the problem of finding an optimal data cube schema for an olap system with limited memory is np-hard. as a more computationally efficient alternative, we propose a greedy approximation algorithm cmp and its variants. algorithm cmp consists of two phases. in the first phase, an initial schema consisting of all the cubes required to efficiently answer the user queries is formed. in the second phase, cubes in the initial schema are selectively merged to satisfy the memory constraint. we show that cmp is very effective in pruning the search space for an optimal schema. this leads to a highly efficient algorithm. we report the efficiency and the effectiveness of cmp via an empirical study using the tpc-d benchmark. our results show that the data cube schemas generated by cmp enable very efficient olap query processing.
word segmentation and recognition for web document framework. it is observed that a better approach to web information understanding is to base on its document framework, which is mainly consisted of (i) the title and the url name of the page, (ii) the titles and the url names of the web pages that it points to, (iii) the alternative information source for the embedded web objects, and (iv) its linkage to other web pages of the same document. investigation reveals that a high percentage of words inside the document framework are &ldquo;compound words&rdquo; which cannot be understood by ordinary dictionaries. they might be abbreviations or acronyms, or concatenations of several (partial) words. to recover the content hierarchy of web documents, we propose a new word segmentation and recognition mechanism to understand the information derived from the web document framework. a maximal bi-directional matching algorithm with heuristic rules is used to resolve ambiguous segmentation and meaning in compound words. an adaptive training process is further employed to build a dictionary of recognisable abbreviations and acronyms. empirical results show that over 75% of the compound words found in the web document framework can be understood by our mechanism. with the training process, the success rate of recognising compound words can be increased to about 90%.
mailrank: using ranking for spam detection. can we use social networks to combat spam? this paper investigates the feasibility of mailrank, a new email ranking and classification scheme exploiting the social communication network created via email interactions. the underlying email network data is collected from the email contacts of all mailrank users and updated automatically based on their email activities to achieve an easy maintenance. mailrank is used to rate the sender address of arriving emails such that emails from trustworthy senders can be ranked and classified as spam or non-spam. the paper presents two variants: basic mailrank computes a global reputation score for each email address, whereas in personalized mailrank the score of each email address is different for each mailrank user. the evaluation shows that mailrank is highly resistant against spammer attacks, which obviously have to be considered right from the beginning in such an application scenario. mailrank also performs well even for rather sparse networks, i.e., where only a small set of peers actually take part in the ranking of email addresses.
processing xpath queries with xml summaries. range labeling and structural joins are well-studied techniques for efficiently processing xpath queries. however, when xpath queries become long, many times of structural joins are required. to solve this problem, we developed a method to reduce the number of joins and nodes read from the disk using strong dataguides. our method can process single paths without any joins and twig patterns with joins amongst branching nodes and leaves in queries. experimental results verified that our approach outperforms the best optimization technique for structural joins by factors of up to several hundreds of times.
node ranking in labeled directed graphs. our work is motivated by the problem of ranking hyper-linked documents for a given query. given an arbitrary directed graph with edge and node labels, we present a new flow-based model and an efficient method to dynamically rank the nodes of this graph with respect to any of the original labels. ranking documents for a given query in a hyper-linked document set and ranking of authors/articles for a given topic in a citation database are some typical applications of our method. we outline the structural conditions that the graph must satisfy for our ranking to be different from the traditional <i>pagerank</i>. we have built a system using two indices that is capable of dynamically ranking documents for any given query. we validate our system and method using experiments on a few datasets: a crawl of the ibm intranet (12 million pages), a crawl of the <b>www</b> (30 million pages) and the dblp citation dataset. we compare our method to existing schemes for topic-biased ranking that require a classifier and the traditional <i>pagerank</i>. in these experiments, we demonstrate that our method is well suited for fine-grained ranking and that our method performs better than the existing schemes. we also demonstrate that our system can obtain an improved ranking with very little impact on query time.
the liberal media and right-wing conspiracies: using cocitation information to estimate political orientation in web documents. this paper introduces a simple method for estimating <i>cultural orientation</i>, the affiliation of online entities in a polarized field of discourse. in particular, cocitation information is used to estimate the political orientation of hypertext documents. a type of cultural orientation, the political orientation of a document is the degree to which it participates in traditionally left- or right-wing beliefs. estimating documents' political orientation is of interest for personalized information retrieval and recommender systems. in its application to politics, the method uses a simple probabilistic model to estimate the strength of association between a document and left- and right-wing communities. the model estimates the likelihood of cocitation between a document of interest and a small number of documents of known orientation. the model is tested on three sets of data, 695 partisan web documents, 162 political weblogs, and 72 non-partisan documents. accuracy above 90% is obtained from the cocitation model, outperforming lexically based classifiers at statistically significant levels.
dynamic and hierarchical spatial access method using integer searching. dynamic and complex computation in the area of geographic information system (gis) or mobile computing system involves huge amount of spatial objects such as points, boxes, polygons, etc and requires a scalable data structure and an efficient management tool for this information. in this paper, for a dynamic management of spatial objects, we construct a hierarchical dynamic data structure, called an ist/opg hierarchy, which may overcome some limitations of existing spatial access methods (sams). the hierarchy is constructed by combining three primary components: (1) minimum boundary rectangle (mbr), which is the most widely used method among sams; (2) the population-based domain slicing, which is modified from the grid file [14]; (3) extended optimal integer searching algorithm [4]. for dynamic management of spatial objects in the ist/opg hierarchy, a number of primary and supplementary operations are introduced. this paper includes a comparative analysis of our approach with previous sams, such as r-tree, r+-tree and r*-tree and qsf-tree. the results of analysis show that our approach is better than other sams in construction and query time and space requirements. specifically, for a given search domain with n objects, our query operations yield $o($ \scriptsize $\sqrt {\frac {\log n} {\log\log n}}$\normalsize $)$ compared to $o(\log n)$ of the fast sam and an ist/opg hierarchy containing $n$ objects can be constructed in $o(n$ \scriptsize $\sqrt {\frac {\log n}{\log\log n}}$\normalsize $)$ time and o(n) space.
computing consistent query answers using conflict hypergraphs. a consistent query answer in a possibly inconsistent database is an answer which is true in every (minimal) repair of the database. we present here a practical framework for computing consistent query answers for large, possibly inconsistent relational databases. we consider relational algebra queries without projection, and denial constraints. because our framework handles union queries, we can effectively (and efficiently) extract indefinite disjunctive information from an inconsistent database. we describe a number of novel optimization techniques applicable in this context and summarize experimental results that validate our approach.
alternative representations and abstractions for moving sensors databases. moving sensors refers to an emerging class of data intensive applications that inpacts disciplines such as communication, health-care, scientific applications, etc. these applications consist of a fixed number of sensors that move and produce streams of data as a function of time. they may require the system to match these streams against stored streams to retrieve relevant data (patterns). with communication, for example, a speaking impaired individual might utilize a haptic glove that translates hand signs into written (spoken) words. the glove consists of sensors for different finger joints. these sensors report their location and values as a function of time, producing streams of data. these streams are matched against a repository of spatio-temporal streams to retrieve the corresponding english character or word.the contributions of this study are two fold. first, it introduces a framework to store and retrieve "moving sensors" data. the framework advocates physical data independence and software-reuse. second, we investigate alternative representations for storage and retrieve of data in support of query processing. we quantify the tradeoff associated with these alternatives using empirical data robocup soccer matches.
the verity federated infrastructure. in the course of researching a subject, it is often necessary to submit the same search request to multiple heterogeneous information sources in order to (a) aggregate as much information as possible, and (b) integrate different aspects of the subject into a coherent report. while it is clear that there is value in providing a federated search solution to make dealing with multiple sources less time-consuming, not all organizations aggregate from the same sources, and once the information has been retrieved, not all organizations want them to be integrated in the same way.the verity federated infrastructure addresses this problem by providing a flexible framework for adding new sources and customizing the way in which results are integrated, post-processed and presented. a new source is made available by writing a java module called a worker that abides by the search interface of the source. sources can range from simple information feeds to more complex applications, e.g., crm systems, relational databases, etc. workers also perform post-processing on the results returned by other workers, e.g., to provide uniform scores for results from different sources, filtering, etc. this post-processing enables different results to be integrated into a coherent report. post-processing is triggered by events that propagate between workers and is done asynchronously in the background while results are being viewed. this ability to do background post-processing allows execution of time-consuming operations that provide substantial value without adversely affecting user experience. finally, search results are returned and viewed incrementally, which enables searching of peer-to-peer networks via peer workers that we have developed.
operational requirements for scalable search systems. prior research into search system scalability has primarily addressed query processing efficiency [1, 2, 3] or indexing efficiency [3], or has presented some arbitrary system architecture [4]. little work has introduced any formal theoretical framework for evaluating architectures with regard to specific operational requirements, or for comparing architectures beyond simple timings [5] or basic simulations [6, 7]. in this paper, we present a framework based upon queuing network theory for analyzing search systems in terms of operational requirements. we use response time, throughput, and utilization as the key operational characteristics for evaluating performance. within this framework, we present a scalability strategy that combines index partitioning and index replication to satisfy a given set of requirement.
automatically classifying database workloads. the type of the workload on a database management system (dbms) is a key consideration in tuning the system. allocations for resources such as main memory can be very different depending on whether the workload type is online transaction processing (oltp) or decision support system (dss). in this paper, we present an approach to automatically identifying a dbms workload as either oltp or dss. we build a classification model based on the most significant workload characteristics that differentiate oltp from dss, and then use the model to identify any change in the workload type. we construct a workload classifier from the browsing and ordering profiles of the tpc-w benchmark. experiments with an industry-supplied workload show that our classifier accurately identifies the mix of oltp and dss work within an application workload.
a practical web-based approach to generating topic hierarchy for text segments. it is crucial in many information systems to organize short text segments, such as keywords in documents and queries from users, into a well-formed topic hierarchy. in this paper, we address the problem of generating topic hierarchies for diverse text segments with a general and practical approach that uses the web as an additional knowledge source. unlike long documents, short text segments typically do not contain enough information to extract reliable features. this work investigates the possibilities of using highly ranked search-result snippets to enrich the representation of text segments. a hierarchical clustering algorithm is then applied to create the hierarchical topic structure of text segments. different from traditional clustering algorithms, which tend to produce cluster hierarchies with a very unnatural shape, the approach tries to produce a more natural and comprehensive hierarchy. extensive experiments were conducted on different domains of text segments. the obtained results have shown the potential of the proposed approach, which is believed able to benefit many information systems.
frequent pattern discovery with memory constraint. we explore in this paper a practicably interesting mining task to retrieve frequent itemsets with memory constraint. as opposed to most previous works that concentrate on improving the mining efficiency or on reducing the memory size by best effort, we first attempt to constrain the upper memory size that can be utilized by mining frequent itemsets in this paper.
a multiple-resolution method for edge-centric data clustering. recent works in spatial data clustering view the input data set in terms of inter-point edge lengths rather than the points themselves. cluster detection in such a system is a matter of finding connected paths of edges whose weight is no greater than some user input threshold or cutoff value. the smtin algorithm[9] is one such system that uses delaunay triangulation to compute the set of nearest neighbor edges quickly and efficiently. experiments demonstrate a substantial performance and accuracy improvement using smtin in comparison to other clustering systems.the resolution of the clusters discovered in the smtin system is directly related to the choice of a cutoff threshold, which makes smtin perform poorly for input sets with clusters at multiple resolutions. in this work we introduce an edge-centric clustering method that detects clusters at multiple resolutions. our algorithm detects differences in density among groups of points and uses multiple cutoff points in order to account for clusters at different resolutions. one of the main benefits of the multi-resolution approach of our system is the ability to accurately cluster points that other systems would consider to be noise. experiments indicate a substantial improvement in the clustering quality of our system in comparison to smtin as well as the removal of the requirement of an input distance-threshold, achieved with comparable theoretical as well as actual runtime performance. we present promising directions for this new algorithm.
on lossy time decompositions of time stamped documents. constructing time decompositions of time stamped documents is an important first step in extracting temporal information from a document set. efficient algorithms are described for computing optimal lossy decompositions for a given document set, where the loss of information is constrained to be within a specified bound. a novel and efficient algorithm is proposed for computing information loss values required to construct optimal lossy decompositions. experimental results are reported comparing optimal lossy decompositions and equal length decompositions in terms of a number of parameters such as information loss. in particular, our results show that optimal lossy decompositions outperform equal length decompositions by preserving more of the information content of the underlying document set. the results also demonstrate that permitting even small amounts of variability in the length of the subintervals of a decomposition results in capturing more of the temporal information content of a document set when compared to equal length decompositions. this paper builds upon our earlier work on time decompositions where the problem of computing optimal lossy decomposition of the time period associated with a document set was first formulated.
determining the semantic orientation of terms through gloss classification. sentiment classification is a recent subdiscipline of text classification which is concerned not with the topic a document is about, but with the opinion it expresses. it has a rich set of applications, ranging from tracking users' opinions about products or about political candidates as expressed in online forums, to customer relationship management. functional to the extraction of opinions from text is the determination of the orientation of ``subjective'' terms contained in text, i.e. the determination of whether a term that carries opinionated content has a positive or a negative connotation. in this paper we present a new method for determining the orientation of subjective terms. the method is based on the quantitative analysis of the glosses of such terms, i.e. the definitions that these terms are given in on-line dictionaries, and on the use of the resulting term representations for semi-supervised term classification. the method we present outperforms all known methods when tested on the recognized standard benchmarks for this task.
topic-oriented collaborative crawling. a major concern in the implementation of a distributed web crawler is the choice of a strategy for partitioning the web among the nodes in the system. our goal in selecting this strategy is to minimize the overlap between the activities of individual nodes. we propose a topic-oriented approach, in which the web is partitioned into general subject areas with a crawler assigned to each. we examine design alternatives for a topic-oriented distributed crawler, including the creation of a web page classifier for use in this context. the approach is compared experimentally with a hash-based partitioning, in which crawler assignments are determined by hash functions computed over urls and page contents. the experimental evaluation demonstrates the feasibility of the approach, addressing issues of communication overhead, duplicate content detection, and page quality assessment.
future directions in data mining: streams, networks, self-similarity and power laws. how to spot abnormalities in a stream of temperature data from a sensor? or from a network of sensors? how does the internet look like? are there 'abnormal' sub-graphs in a given social network, possibly indicating, e.g., money-laundering rings?we present some recent work and list many remaining challenges for these two fascinating issues in data mining, namely, streams and networks. streams appear in numerous settings, in the form of, e.g., temperature readings, road traffic data, series of video frames for surveillance, patient physiological data. in all these settings, we want to equip the sensors with nimble, but powerful enough algorithms to look for patterns and abnormalities,<ol>(a) on a semi-infinite stream,(b) using finite memory, and (c) without human intervention.</ol.for networks, the applications are also numerous: social networks recording who knows/calls/emails whom; the internet itself, as well as the web, with routers and links, or pages and hyper-links; the genes and how they are related; customers and products they buy. in fact, any "many-to-many" database relationship eventually leads to a graph/network. in all these settings we want to find patterns and 'abnormalities'; the most central/important nodes; we also want to predict how the network will evolve; and we want to tackle huge graphs, with millions or billions of nodes and edges.as a promising direction towards these problems, we present some surprising tools from the theory of fractals, self-similarity and power laws. we show how the 'intrinsic' or 'fractal' dimension can help us find patterns, when traditional tools and assumptions fail. we show that self-similarity and power laws models work well in an impressive variety of settings, including real, bursty disk and web traffic; skewed distributions of click-streams; and multiple, real internet graphs.
mining gene expression datasets using density-based clustering. given the recent advancement of microarray technologies, we present a density-based clustering approach for the purpose of co-expressed gene cluster identification. the underlying hypothesis is that a set of co-expressed gene clusters can be used to reveal a common biological function. by addressing the strengths and limitations of previous density-based clustering approaches, we present a novel clustering algorithm that utilizes a neighborhood defined by <i>k</i>-nearest neighbors. experimental results indicate that the proposed method identifies biologically meaningful and co-expressed gene clusters.
composable xml integration grammars. the proliferation of xml as a standard for data representation and exchange in diverse, next-generation web applications has created an emphatic need for effective xml data-integration tools. for several real-life scenarios, such xml data integration needs to be <i>dtd-directed</i> -- in other words, the target, integrated xml database must conform to a prespecified, user- or application-defined dtd. in this paper, we propose a novel formalism, <i>xml integration grammars (xigs)</i>, for specifying dtd-directed integration of xml data. abstractly, an xig maps data from multiple xml sources to a target xml document that conforms to a predefined dtd. an xig extracts source xml data via queries expressed in a fragment of xquery, and controls target document generation with tree-valued attributes and the target dtd. the novelty of xigs consists in not only their automatic support for dtd-conformance but also in their: an xig may embed local and remote xigs in its definition, and invoke these xigs during its evaluation. this yields an important modularity property for our xigs that allows one to divide a complex integration task into manageable sub-tasks and conquer each of them separately. to efficiently evaluate xigs we provide algorithms for merging xml queries in an xig and for scheduling queries and embedded xigs. these lead to an effective framework, as well as a design tool for xquery, for effectively specifying and computing complex, dtd-directed xml integration.
a novel approach for privacy-preserving video sharing. to support privacy-preserving video sharing, we have proposed a novel framework that is able to protect the video content privacy at the individual video clip level and prevent statistical inferences from video collections. to protect the video content privacy at the individual video clip level, we have developed an effective algorithm to automatically detect privacy-sensitive video objects and video events. to prevent the statistical inferences from video collections, we have developed a distributed framework for privacy-preserving classifier training, which is able to significantly reduce the costs of data transmission and reliably limit the privacy breaches by determining the optimal size of blurred test samples for classifier validation. our experiments on a specific domain of patient training and counseling videos show convincing results.
thematic mapping - from unstructured documents to taxonomies. verity inc. has developed a comprehensive suite of tools for accurately and efficiently organizing enterprise content which involves four basic steps: (i) creating taxonomies, (ii) building classification models, (iii) populating taxonomies with documents, and (iv) deploying populated taxonomies in enterprise portals. a taxonomy is a hierarchical representation of categories. a taxonomy provides a navigation structure for exploring and understanding the underlying corpus without sifting through a huge volume of documents. thematic mapping automatically discovers a concept tree from a corpus of unstructured documents and assigns meaningful labels to concepts based on a semantic network. integrating with verity intelligent classifier's user-friendly gui, a user can drill down a concept tree for navigation, perform a conceptual search to retrieve documents pertaining to a concept, build a taxonomy from the concept tree, as well as edit a taxonomy to tailor it into various views (customized taxonomies) of the same corpus. classification rules can be generated automatically from concepts. these classification rules can be used for populating documents into the taxonomy.
augeas: authoritativeness grading, estimation, and sorting. when searching for content in in a large heterogeneous document collections like the world wide web it is not easy to know which documents provide reliable authoritative information about a subject. the problem is particularly pointed as it concerns content search for "high-value" informational needs such as retrieving medical information, where the cost of error may be high. in this paper, a method is described for estimating the authoritativeness of a document based on textual, non-topical cues. this method is complementary to estimates of authoritativeness based on link structure, such as the pagerank and hits algorithms. this method is particularly suited to "high-value" content search where the user is interested in searching for information about a specific topic. a method for combining textual estimates of authoritativeness with link analysis is also presented. the types of textual cues to authoritativeness that are easily computed and utilized by our method are described, as well as the method used to select a subset of cues to increase the computation speed. methods for applying authoritativeness estimates to re-ranking documents returned from search engines, combining textual authoritativeness with social authority, and use in query expansion are also presented. by combining textual authority with link analysis, a more complete and robust estimate can be made of a document's authoritativeness.
summarization of discussion groups. in this paper, we describe an algorithm to generate textual summaries of discussion groups. our system combines sentences extracted from individual postings into variable-length summaries by utilizing the hierarchical discourse context provided by discussion threads. we have incorporated this algorithm into a web-based application called ids (interactive discussion summarizer).
approximating the top-m passages in a parallel question answering system. we examine the problem of retrieving the top-<i>m</i> ranked items from a large collection, randomly distributed across an <i>n</i>-node system. in order to retrieve the top <i>m</i> overall, we must retrieve the top <i>m</i> from the subcollection stored on each node and merge the results. however, if we are willing to accept a small probability that one or more of the top-<i>m</i> items may be missed, it is possible to reduce computation time by retrieving only the top <i>k < m</i> from each node. in this paper, we demonstrate that this simple observation can be exploited in a realistic application to produce a substantial efficiency improvement without compromising the quality of the retrieved results. to support our claim, we present a statistical model that predicts the impact of the optimization. the paper is structured around a specific application~---~passage retrieval for question answering~---~but the primary results are more broadly applicable.
a reliable storage management layer for distributed information retrieval systems. we present a storage management layer that facilitates the implementation of parallel information retrieval systems, and related applications, on networks of workstations. the storage management layer automates the process of adding and removing nodes, and implements a dispersed mirroring strategy to improve reliability. when nodes are added and removed, the document collection managed by the system is redistributed for load balancing purposes. the use of dispersed mirroring minimizes the impact of node failures and system modifications on query performance.
query processing of streamed xml data. we are addressing the efficient processing of continuous xml streams, in which the server broadcasts xml data to multiple clients concurrently through a multicast data stream, while each client is fully responsible for processing the stream. in our framework, a server may disseminate xml fragments from multiple documents in the same stream, can repeat or replace fragments, and can introduce new fragments or delete invalid ones. a client uses a light-weight database based on our proposed xml algebra to cache stream data and to evaluate xml queries against these data. the synchronization between clients and servers is achieved through annotations and punctuations transmitted along with the data streams. we are presenting a framework for processing xml queries in xquery form over continuous xml streams. our framework is based on a novel xml algebra and a new algebraic optimization framework based on query decorrelation, which is essential for non-blocking stream processing.
a domain independent environment for creating information extraction modules. text-mining is a growing area of interest within the field of data mining and knowledge discovery. given a collection of text documents, most approaches to text mining perform knowledge-discovery operations either on external tags associated with each document, or on the set of all words within each document. both approaches suffer from limitations. this paper focuses on an intermediate approach, one that we call text mining via information extraction, in which knowledge discovery takes place on focused, relevant terms, phrases and facts, as extracted from the documents.
interconnection semantics for keyword search in xml. a framework for describing semantic relationships among nodes in xml documents is presented. in contrast to earlier work, the xml documents may have id references (i.e., they correspond to graphs and not just trees). a specific interconnection semantics in this framework can be defined explicitly or derived automatically. the main advantage of interconnection semantics is the ability to pose queries on xml data in the style of keyword search. several methods for automatically deriving interconnection semantics are presented. the complexity of the evaluation and the satisfiability problems under the derived semantics is analyzed. for many important cases, the complexity is tractable and hence, the proposed interconnection semantics can be efficiently applied to real-world xml documents.
automatic construction of multifaceted browsing interfaces. databases of text and text-annotated data constitute a significant fraction of the information available in electronic form. searching and browsing are the typical ways that users locate items of interest in such databases. interfaces that use multifaceted hierarchies represent a new powerful browsing paradigm which has been proven to be a successful complement to keyword searching. thus far, multifaceted hierarchies have been created manually or semi-automatically, making it difficult to deploy multifaceted interfaces over a large number of databases. we present automatic and scalable methods for creation of multifaceted interfaces. our methods are integrated with traditional relational databases and can scale well for large databases. furthermore, we present methods for selecting the best portions of the generated hierarchies when the screen space is not sufficient for displaying all the hierarchy at once. we apply our technique to a range of large data sets, including annotated images, television programming schedules, and web pages. the results are promising and suggest directions for future research.
query expansion using random walk models. it has long been recognized that capturing term relationships is an important aspect of information retrieval. even with large amounts of data, we usually only have significant evidence for a fraction of all potential term pairs. it is therefore important to consider whether multiple sources of evidence may be combined to predict term relations more accurately. this is particularly important when trying to predict the probability of relevance of a set of terms given a query, which may involve both lexical and semantic relations between the terms.we describe a markov chain framework that combines multiple sources of knowledge on term associations. the stationary distribution of the model is used to obtain probability estimates that a potential expansion term reflects aspects of the original query. we use this model for query expansion and evaluate the effectiveness of the model by examining the accuracy and robustness of the expansion methods, and investigate the relative effectiveness of various sources of term evidence. statistically significant differences in accuracy were observed depending on the weighting of evidence in the random walk. for example, using co-occurrence data later in the walk was generally better than using it early, suggesting further improvements in effectiveness may be possible by learning walk behaviors.
improved string matching under noisy channel conditions. many document-based applications, including popular web browsers, email viewers, and word processors, have a 'find on this page' feature that allows a user to find every occurrence of a given string in the document. if the document text being searched is derived from a noisy process such as optical character recognition (ocr), the effectiveness of typical string matching can be greatly reduced. this paper describes an enhanced string-matching algorithm for degraded text that improves recall, while keeping precision at acceptable levels. the algorithm is more general than most approximate matching algorithms and allows string-to-string edits with arbitrary costs. we develop a method for evaluating our technique and use it to examine the relative effectiveness of each sub-component of the algorithm. of the components we varied, we find that using confidence information from the recognition process lead to the largest improvements in matching accuracy.
scalable ranking for preference queries. top-k preference queries with multiple attributes are critical for decision-making applications. previous research has concentrated on improving the computational efficiency mainly by using novel index structures and search strategies. since current applications need to scale to terabytes of data and thousands of users, performance of such systems is strongly impacted by the amount of available memory. this paper proposes a scalable approach for memory-bounded top-k query processing.
exploiting redundancy in sensor networks for energy efficient processing of spatiotemporal region queries. sensor networks are made of autonomous devices that are able to collect, store, process and share data with other devices. spatiotemporal region queries can be used for retrieving information of interest from such networks. such queries require the answers only from the subset of the network nodes that fall into the query region. if the network is redundant in the sense that the measurements of some nodes can be substituted by those of other nodes with a certain degree of confidence, then a much smaller subset of nodes may be sufficient to answer the query at a lower energy cost. we investigate how to take advantage of such data redundancy and propose two techniques to process spatiotemporal region queries under these conditions. our techniques reduce up to twenty times the energy cost of query processing compared to the typical network flooding, thus prolonging the lifetime of the sensor network.
mining inter-transaction associations with templates. multi-dimensional, inter-transaction association rules extend the traditional association rules to describe more general associations among items with multiple properties cross transactions. &ldquo;after mcdonald and burger king open branches, kfc will open a branch two months later and one mile away&rdquo; is an example of such rules. since the number of potential inter-transaction association rules tends to be extremely large, mining inter-transaction associations poses more challenges on efficient processing than mining intra-transaction associations. in order to make such association mining truly practical and computationally tractable, in this study, we present a template model to help users declare the interesting inter-transaction associations to be mined. with the guidance of templates, several optimization techniques are devised to speed up the discovery of inter-transaction association rules. we show, through a series of experiments, that these optimization techniques can yield significant performance benefits.
automatic recognition of distinguishing negative indirect history language in judicial opinions. we describe a model-based filtering application that generates candidate case-to-case distinguishing citations. we developed the system to aid editors in identifying indirect relationships among judicial opinions in a database of over 5 million documents. using a training collection of approximately 30,000 previously edited cases, the filter application provides ranked sets of textual evidence for current case law documents in the editorial process. these sets contain judicial language with a strong probability of containing distinguishing relationships. integrating this application into the editorial review environment has greatly improved the coverage and efficiency of the work flow to identify and generate new distinguishing relationship entries.
efficient processing of conical queries. conical queries are a novel type of query with an increasing number of applications. traditional index structures and retrieval mechanisms, in general, have been optimized for rectangular and circular queries, rather than conical queries. in this paper, we focus on conical queries which can be defined as a multi-dimensional cone in a multi-dimensional data space. we develop a model for expressing such queries and suggest efficient techniques for evaluating them. in particular, we explore the retrieval problem in the context of conical query processing and develop multi-disk allocation methods specifically for processing conical queries.
online duplicate document detection: signature reliability in a dynamic retrieval environment. as online document collections continue to expand, both on the web and in proprietary environments, the need for duplicate detection becomes more critical. few users wish to retrieve search results consisting of sets of duplicate documents, whether identical duplicates or close matches. our goal in this work is to investigate the phenomenon and determine one or more approaches that minimize its impact on search results. recent work has focused on using some form of signature to characterize a document in order to reduce the complexity of document comparisons. a representative technique constructs a 'fingerprint' of the rarest or richest features in a document using collection statistics as criteria for feature selection. one of the challenges of this approach, however, arises from the fact that in production environments, collections of documents are always changing, with new documents, or new versions of documents, arriving frequently, and other documents periodically removed. when an enterprise proceeds to freeze a training collection in order to stabilize the underlying repository of such features and its associated collection statistics, issues of coverage and completeness arise. we show that even with very large training collections possessing extremely high feature correlations before and after updates, underlying fingerprints remain sensitive to subtle changes. we explore alternative solutions that benefit from the development of massive meta-collections made up of sizable components from multiple domains. this technique appears to offer a practical foundation for fingerprint stability. we also consider mechanisms for updating training collections while mitigating signature instability. our research is divided into three parts. we begin with a study of the distribution of duplicate types in two broad-ranging news collections consisting of approximately 50 million documents. we then examine the utility of document signatures in addressing identical or nearly identical duplicate documents and their sensitivity to collection updates. finally, we investigate a flexible method of characterizing and comparing documents in order to permit the identification of non-identical duplicates. this method has produced promising results following an extensive evaluation using a production-based test collection created by domain experts.
clustering declustered data for efficient retrieval. as databases increasingly integrate multimedia information in the form of image, video, and audio data, both the dimensionality and the amount of data that need to be processed is increasing rapidly. it becomes necessary to support the efficient retrieval of large amounts of multimedia data. declustering techniques for multi-disk architectures have been effectively used for storage in relational databases. in this paper, we first establish that besides exploiting the parallelism, a careful organization of each disk must be considered for fast searching. we introduce the notion of page allocation and data space mapping which can be used to organize and retrieve multidimensional data. we work on these notions based on three different partitioning strategies: regular grid partitioning, concentric hypercubes and hyperpyramids. we develop techniques that satisfy efficient retrieval by optimizing the number of buckets retrieved by the query, disk arm movement and i/o parallelism. we prove that concentric hypercube based mapping satisfies the optimal clustering and optimal parallelism. we develop techniques based on hyperpyramid partitioning which reduces the number of buckets retrieved by the query and has very efficient inter and intra disk organizations. we evaluate the performance of proposed techniques by comparing it with the current best approaches. the new techniques lead to very significant improvement, up to 43 times, over the existing techniques, therefore resulting in fast retrieval of multimedia data.
detecting similar documents using salient terms. we describe a system for rapidly determining document similarity among a set of documents obtained from an information retrieval (ir) system. we obtain a ranked list of the most important terms in each document using a rapid phrase recognizer system. we store these in a database and compute document similarity using a simple database query. if the number of terms found to not be contained in both documents is less than some predetermined threshold compared to the total number of terms in the document, these documents are determined to be very similar. we compare this to the shingles approach.
approximately common patterns in shared-forests. we present a proposal intended to demonstrate the applicability of tabulation techniques for detecting approximately common patterns when dealing with structures sharing some common parts. this sharing saves on the space needed to represent the structures and also on their later processing, by factorizing the filtering of substructure matching. as a consequence, preliminary experimental tests indicate a reduction of the running time.
termination analysis of active rules modular sets. this paper presents an algorithm for static termination analysis of active rules in a context of modular design. several recent works have suggested proving termination by using the concept of triggering graph. we propose here an original approach, based on these works, and that allows to guarantee the termination of a set of rules, conceived by several designers, even when none of the designers knows the set of the active rules. we introduce the notions of private event and of public event, and we refine the notion of triggering graph (by enclosing also events in graphs). we replace then the notion of cycle (which is no more relevant in a context of modular design) by the notion of maximal private path preceding a rule. by means of these tools, we show that it is possible to prove termination of active rules modular sets.
kqml as an agent communication language. this paper describes the design of and experimentation with the knowledge query and manipulation language (kqml), a new language and protocol for exchanging information and knowledge. this work is part of a larger effort, the arpa knowledge sharing effort which is aimed at developing techniques and methodology for building large-scale knowledge bases which are sharable and reusable. kqml is both a message format and a message-handling protocol to support run-time knowledge sharing among agents. kqml focuses on an extensible set of performatives, which defines the permissible &ldquo;speech acts&rdquo; agents may use and comprise a substrate on which to develop higher-level models of interagent interaction such as contract nets and negotiation. in addition, kqml provides a basic architecture for knowledge sharing through a special class of agent called communication facilitors which coordinate the interactions of other agents. the ideas which underlie the evolving design of kqml are currently being explored through experimental prototype systems which are being used to support several testbeds in such areas as concurrent engineering, intelligent design and intelligent planning and scheduling.
representing interests as a hyperlinked document collection. we describe a latent variable model for representing a user's interests as a hyperlinked document collection. by collecting hyper-text documents that a user views, creates or updates whilst at their computer, we are able to use not only the content of these documents but also the inter-connectivity of the collection to model the user's interests. the model uses probabilistic latent semantic analysis and probabilistic hypertext induced topic selection and decomposes the user's document collection into a set of factors each of which represents a user's interest. this model can be used to personalise information access tasks such as a personalised search engine or a personalised news service. our latent variable model's performance is compared with that of a more conventional vector space clustering algorithm.
semantic similarity over the gene ontology: family correlation and selecting disjunctive ancestors. many bioinformatics applications would benefit from comparing proteins based on their biological role rather than their sequence. in most biological databases, proteins are already annotated with ontology terms. previous studies identified a correlation between the sequence similarity and the semantic similarity of proteins. the semantic similarity of proteins was computed from their annotated go terms. however, proteins sharing a biological role do not necessarily have a similar sequence.this paper introduces our study of the correlation between go and family similarity. family similarity overcomes some of the limitations of sequence similarity, thus we obtained a strong correlation between go and family similarity. additionally, this paper introduces grasm, a novel method that uses all the information in the graph structure of the go, instead of considering it as a hierarchical tree. when calculating the semantic similarity of two concepts, grasm selects the disjunctive common ancestors rather than only using the most informative common ancestor. grasm produced a higher family similarity correlation than the original semantic similarity measures.
efficient ordering for xml data. with the increasing popularity of xml, there arises the need for managing and querying information in this form. several query languages, such as xquery, have been proposed which return their results in document order. however, most recent efforts focused on query optimization have disregarded order. this paper presents a simple yet elegant method to maintain document ordering for xml data. analysis of our method shows that it is indeed efficient and scalable, even for changing data.
a framework for selective query expansion. query expansion is a well-known technique that has been shown to improve <i>average</i> retrieval performance. this technique has not been used in many operational systems because of the fact that it can greatly degrade the performance of some individual queries. we show how comparison between language models of the unexpanded and expanded retrieval results can be used to predict when the expanded retrieval has strayed from the original sense of the query. in these cases, the unexpanded results are used while the expanded results are used in the remaining cases (where such straying is not detected). we evaluate this method on a wide variety of trec collections.
joint deduplication of multiple record types in relational data. record deduplication is the task of merging database records that refer to the same underlying entity. in relational data-bases, accurate deduplication for records of one type is often dependent on the decisions made for records of other types. whereas nearly all previous approaches have merged records of different types independently, this work models these inter-dependencies explicitly to collectively deduplicate records of multiple types. we construct a conditional random field model of deduplication that captures these relational dependencies, and then employ a novel relational partitioning algorithm to jointly deduplicate records. for two citation matching datasets, we show that collectively deduplicating paper and venue records results in up to a 30% error reduction in venue deduplication, and up to a 20% error reduction in paper deduplication.
the role of the database community in the national information infrastructure. the computer science community is increasingly focusing its efforts on tasks related to the national information infrastructure. hardware and software advances are being sought to make wide-area networks and technological resources in general more useful to mainstream society. with this transition comes a set of unavoidable political and social issues that have never been satisfactorily dealt with in the past. grand challenges face the computer science community on both the technical and the socio-political sides of this &ldquo;major upgrade.&rdquo; this paper discusses various aspects of the enormous coordination problem that faces all of us and considers what the database community can do to help.
an evaluation of evolved term-weighting schemes in information retrieval. this paper presents an evaluation of evolved term-weighting schemes on short, medium and long trec queries. a previously evolved global (collection-wide) term-weighting scheme is evaluated on unseen trec data and is shown to increase mean average precision over idf. a local (within-document) evolved term-weighting scheme is presented which is dependent on the best performing global scheme. the full evolved scheme (i.e. the combined local and global scheme) is compared to both the bm25 scheme and the pivoted normalisation scheme.our results show that the local evolved solution does not perform well on some collections due to its document normalisation properties and we conclude that okapi-tf can be tuned to interact effectively with the evolved global weighting scheme presented and increase mean average precision over the standard bm25 scheme.
concept-based interactive query expansion. despite the recent advances in search quality, the fast increase in the size of the web collection has introduced new challenges for web ranking algorithms. in fact, there are still many situations in which the users are presented with imprecise or very poor results. one of the key difficulties is the fact that users usually submit very short and ambiguous queries, and they do not fully specify their information needs. that is, it is necessary to improve the query formation process if better answers are to be provided. in this work we propose a novel concept-based query expansion technique, which allows disambiguating queries submitted to search engines. the concepts are extracted by analyzing and locating cycles in a special type of query relations graph. this is a directed graph built from query relations mined using association rules. the concepts related to the current query are then shown to the user who selects the one concept that he interprets is most related to his query. this concept is used to expand the original query and the expanded query is processed instead. using a web test collection, we show that our approach leads to gains in average precision figures of roughly 32%. further, if the user also provides information on the type of relation between his query and the selected concept, the gains in average precision go up to roughly 52%.
minimal document set retrieval. this paper presents a novel formulation and approach to the minimal document set retrieval problem. minimal document set retrieval (mdsr) is a promising information retrieval task in which each query topic is assumed to have different subtopics; the task is to retrieve and rank relevant document sets with maximum coverage but minimum redundancy of subtopics in each set. for this task, we propose three document set retrieval and ranking algorithms: novelty based method, cluster based method and subtopic extraction based method. in order to evaluate the system performance, we design a new evaluation framework for document set ranking which evaluates both relevance between set and query topic, and redundancy within each set. finally, we compare the performance of the three algorithms using the trec interactive track dataset. experimental results show the effectiveness of our algorithms.
connecting topics in document collections with stepping stones and pathways. in this paper, we present stepping stones and pathways (ssp), an alternative model of building and presenting answers for the cases when queries on document collections cannot be answered just by a ranked list. stepping stones can handle questions like: "what is the relation of topics x and y?" ssp addresses when the contents of a small set of related documents is needed as an answer rather than a single document, or when "query splitting" is required to satisfactorily explore a document space. query results are networks of document groups representing topics, each group relating to and connecting (by documents) to other groups in the network. thus, a network answers the user's information need. we devise new and more effective representations and techniques to visualize such answers, and to involve users as part of the answer-finding process. in order to verify the validity of our approach, and since the questions we aim to answer involve multiple topics, we performed a study involving a custom built broad collection of operating systems research papers, and evaluated the results with interested computer science students, using multiple measures.
time-based language models. we explore the relationship between time and relevance using trec ad-hoc queries. a type of query is identified that favors very recent documents. we propose a time-based language model approach to retrieval for these queries. we show how time can be incorporated into both query-likelihood models and relevance models. these models were used for experiments comparing time-based language models to heuristic techniques for incorporating document recency in the ranking. our results show that time-based models perform as well as or better than the best of the heuristic techniques.
optimizing cursor movement in holistic twig joins. holistic twig join algorithms represent the state of the art for evaluating path expressions in xml queries. using inverted indexes on xml elements, holistic twig joins move a set of index cursors in a coordinated way to quickly find structural matches. because each cursor move can trigger i/o, the performance of a holistic twig join is largely determined by how many cursor moves it makes, yet, surprisingly, existing join algorithms have not been optimized along these lines. in this paper, we describe twigoptimal, a new holistic twig join algorithm with optimal cursor movement. we sketch the proof of twigoptimal's optimality, and describe how twigoptimal can use information in the return clause of xquery to boost its performance. finally, experimental results are presented, showing twigoptimal's superiority over existing holistic twig join algorithms.
tempus fugit: a system for making semantic connections. tempus fugit ("time flies") is the first of a new generation of personal information management (pim) systems. a pim system incorporates an electronic calendar, "to-do" list and address book. the premise behind tempus fugit is that information stored in electronic calendars, to-do lists and address books can be given richer semantic interpretation and automatically processed to make its users more effective. tempus fugit also tracks the physical and virtual locations of users and uses this information to predict meeting attendance and help them as they travel during their day.
a design space approach to analysis of information retrieval adaptive filtering systems. in this paper we suggest a new approach to analysis and design of ir systems. we argue for design space exploration in constructing ir systems and in analyzing the effects of individual modules and parameters. we present results of experiments with parametric interpolation, or "homotopy", between two systems, and show, incidentally, that the best results are not achieved at the endpoints, and may lie outside the bounding hypercube defined by our choice of parameterization. three distinct classes of interpolation are introduced to deal with the complexities of the specific example.
exploiting a controlled vocabulary to improve collection selection and retrieval effectiveness. vocabulary incompatibilities arise when the terms used to index a document collection are largely unknown, or at least not well-known to the users who eventually search the collection. no matter how comprehensive or well-structured the indexing vocabulary, it is of little use if it is not used effectively in query formulation. this paper demonstrates that techniques for mapping user queries into the controlled indexing vocabulary have the potential to radically improve document retrieval performance. we also show how the use of controlled indexing vocabulary can be employed to achieve performance gains for collection selection. finally, we demonstrate the potential benefit of combining these two techniques in an interactive retrieval environment. given a user query, our evaluation approach simulates the human user's choice of terms for query augmentation given a list of controlled vocabulary terms suggested by a system. this strategy lets us evaluate interactive strategies without the need for human subjects.
applications of approximate word matching in information retrieval. as more online databases are integrated into digital libraries, the issue of quality control of the data becomes increasingly important, especially as it relates to the effective retrieval of information. the need to discover and reconcile variant forms of strings in bibliographic entries, i.e., authority work, will become more difficult. spelling variants, misspellings, and transliteration differences will all increase the difficulty of retrieving information. approximate string matching has traditionally been used to help with this problem. in this paper we introduce the notion of approximate word matching and show how it can be used to improve detection and categorization of variant forms.
a hybrid approach to ner by memm and manual rules. this paper describes a framework for defining domain specific feature functions in a user friendly form to be used in a maximum entropy markov model (memm) for the named entity recognition (ner) task. our system called merge allows defining general feature function templates, as well as linguistic rules incorporated into the classifier. the simple way of translating these rules into specific feature functions are shown. we show that merge can perform better from both purely machine learning based systems and purely-knowledge based approaches by some small expert interaction of rule-tuning.
on scalable information retrieval systems. implementing scalable information retrieval systems requires the design and development of efficient methods to ingest data from multiple sources, search and retrieve results from both english and foreign language document collections and from collections comprising of multiple data types, harness high performance computer technology, and accurately answer user questions. some recent efforts related to the development of scalable information retrieval systems are described. particular emphasis is placed on those efforts that were adopted into commercial use.
reorganizing web sites based on user access patterns. in this paper, an approach for reorganizing web sites based on user access patterns is proposed. the approach consists of three steps: preprocessing, page classification, and site reorganization. in preprocessing, pages on a web site are processed to create an internal representation of the site, and page access information of its users is extracted from its server log. in page classification, the web pages on the site are classified into two categories, index pages and content pages, based on the page access information. after the pages are classified, in site reorganization, the web site is examined to find better ways to organize and arrange the pages on the site. our experiments on a large real data set show that the approach is efficient and practical for adaptive web sites.
incremental stock time series data delivery and visualization. sb-tree is a binary tree data structure proposed to represent time series according to the importance of data points. its use in stock data management is distinguished by preserving the critical data points' attribute values, retrieving time series data according to the importance of data points and facilitating multi-resolution time series retrieval. as new stock data are available continuously, an effective updating mechanism for sb-tree is needed. in this paper, a study of different updating approaches is reported. three families of updating methods are proposed. they are periodic rebuild, batch update and point-by-point update. their efficiency, effectiveness and characteristics are compared and reported.
index compression vs. retrieval time of inverted files for xml documents. query languages for retrieval of xml documents allow for conditions referring both to the content and the structure of documents. in this paper, we investigate two different approaches for reducing index space of inverted files for xml documents. first, we consider methods for compressing index entries. second, we develop the new xs tree data structure which contains the structural description of a document in a rather compact form, such that these descriptions can be kept in main memory. experimental results on two large xml document collections show that very high compression rates for indexes can be achieved, but any compression increases retrieval time. on the other hand, highly compressed indexes may be feasible for applications where storage is limited, such as in pdas or e-book devices.
evaluating continuous nearest neighbor queries for streaming time series via pre-fetching. for many applications, it is important to quickly locate the nearest neighbor of a given time series. when the given time series is a streaming one, nearest neighbors may need to be found continuously at all time positions. such a standing request is called a continuous nearest neighbor query. this paper seeks fast evaluation of continuous queries on large databases. the initial strategy is to use the result of one evaluation to restrict the search space for the next. a more fundamental idea is to extend the existing indexing methods, used in many traditional nearest neighbor algorithms, with pre-fetching. specifically, pre-fetching is to predict the next value of the stream before it arrives, and to process the query as if the predicted value were the real one in order to load the needed index pages and time series into the allocated cache memory. furthermore, if the pre-fetched candidates cannot fit into the cache memory, they are stored in a sequential file to facilitate fast access to them. experiments show that pre-fetching improves the response time greatly over the direct use of traditional algorithms, even if the caching provided by the operating system is taken into consideration.
taxonomies by the numbers: building high-performance taxonomies. in this paper, we describe a system for the construction of taxonomies which yield high accuracies with automated categorization systems, even on web and intranet documents. in particular, we describe the way in which measurement of five key features of the system can be used to predict when categories are sufficiently well defined to yield high accuracy categorization. we describe the use of this system to construct a large (8800-category) general-purpose taxonomy and categorization system.
motion adaptive indexing for moving continual queries over moving objects. this paper describes a <i>motion adaptive</i> indexing scheme for efficient evaluation of moving continual queries (mcqs) over moving objects. it uses the concept of <i>motion-sensitive bounding boxes</i> (<i>msb</i>s) to model moving objects and moving queries. these bounding boxes automatically adapt their sizes to the dynamic motion behaviors of individual objects. instead of indexing frequently changing object positions, we index less frequently changing object and query <i>msb</i>s, where updates to the bounding boxes are needed only when objects and queries move across the boundaries of their boxes. this helps decrease the number of updates to the indexes. more importantly, we use <i>predictive query results</i> to optimistically precalculate query results, decreasing the number of searches on the indexes. motion-sensitive bounding boxes are used to incrementally update the predictive query results. our experiments show that the proposed motion adaptive indexing scheme is efficient for the evaluation of moving continual range queries.
adaptive load shedding for windowed stream joins. we present an adaptive load shedding approach for windowed stream joins. in contrast to the conventional approach of dropping tuples from the input streams, we explore the concept of selective processing for load shedding. we allow stream tuples to be stored in the windows and shed excessive cpu load by performing the join operations, not on the entire set of tuples within the windows, but on a dynamically changing subset of tuples that are learned to be highly beneficial. we support such dynamic selective processing through three forms of runtime adaptations: adaptation to input stream rates, adaptation to time correlation between the streams and adaptation to join directions. indexes are used to further speed up the execution of stream joins. experiments are conducted to evaluate our adaptive load shedding in terms of output rate. the results show that our selective processing approach to load shedding is very effective and significantly outperforms the approach that drops tuples from the input streams.
browsing large digital library collections using classification hierarchies. summarization of intermediary query result sets plays an important role when users browse through digital library collections. summarization enables users to quickly digest the results of their queries, and provides users with important information they can use to narrow their search interactively. techniques from the field of data analysis may be applied to the problem of generating summaries of query results efficiently. such techniques should permit the incorporation of classification hierarchies in order to provide powerful browsing environments for digital library users.
collective multi-label classification. common approaches to multi-label classification learn independent classifiers for each category, and employ ranking or thresholding schemes for classification. because they do not exploit dependencies between labels, such techniques are only well-suited to problems in which categories are independent. however, in many domains labels are highly interdependent. this paper explores multi-label conditional random field (crf)classification models that directly parameterize label co-occurrences in multi-label classification. experiments show that the models outperform their single-label counterparts on standard text corpora. even when multi-labels are sparse, the models improve subset classification error by as much as 40%.
management of disk space with rebate. the past decade has witnessed a proliferation of respositories whose workload consists of queries that retrieve information. these repositories provide on-line access to vast amount of data and serve as an integral component of many application domains (e.g., library information systems, scientific applications, entertainment industry). their storage subsystem is expected to be hierarchical consisting of memory, disk drives, and one or more tertiary storage devices. the database resides permanently on the tertiary storage devices and objects are swapped onto the magnetic disk drives on demand (and deleted once the disk storage capacity is exhausted). this may fragment the disk space over a period of time, resulting in a non-contiguous layout of an object across the surface of a disk drive. this is undesirable because, once the object is referenced, the disk drive is required to reposition its read head multiple times (incur seek operations) when retrieving the object, resulting in a low performance.this paper presents the design of rebate. rebate ensures the contiguous layout of each object across the surface of a disk drive by partitioning the available disk space into regions where each region manages objects of approximately the same size. we describe the tradeoffs of using rebate and its possible limitations.
a comparison of alternative continuous display techniques with heterogeneous multi-zone disks. a number of recent technological trends have made data intensive applications such as continuous media (audio and video) servers a reality. these servers are expected to play an important role in applications such as video-on-demand, digital library, news-on-demand, distance learning, etc. continuous media applications are data intensive and might require storage subsystems that consist of hundreds of (multi-zone) disk drives. with the current technological trends, a homogeneous disk subsystem might evolve to consist of a heterogeneous collection of disk drives. given such a storage subsystem, the system must continue to support a hiccup-free display of audio and video clips. this study describes extensions of four continuous display techniques for multi-zone disk drives to a heterogeneous platform. these techniques include ibm's logical track [21], hp's track pairing [4], and usc's fixb [9] and deadline driven techniques [10]. we quantify the performance tradeoff associated with these techniques using analytical models and simulation studies. the obtained results demonstrate tradeoffs between the cost per simultaneous stream supported by a technique, the wasted disk space, and the incurred startup latency.
mining the web to create minority language corpora. the web is a valuable source of language specific resources but the process of collecting, organizing and utilizing these resources is difficult. we describe corpusbuilder, an approach for automatically generating web-search queries for collecting documents in a minority language. it differs from pseudo-relevance feedback in that retrieved documents are labeled by an automatic language classifier as relevant or irrelevant, and this feedback is used to generate new queries. we experiment with various query-generation methods and query-lengths to find inclusion/exclusion terms that are helpful for retrieving documents in the target language and find that using odds-ratio scores calculated over the documents acquired so far was one of the most consistently accurate query-generation methods. we also describe experiments using a handful of words elicited from a user instead of initial documents and show that the methods perform similarly. experiments applying the same approach to multiple languages are also presented showing that our approach generalizes to a variety of languages.
speech user interfaces for information retrieval. the research proposed here concentrates on the problem of designing and developing a spoken query retrieval (sqr) system to access large document databases via voice. the main challenge is to identify and address issues related to designing an effective and efficient speech user interface (sui), especially if the aim is to facilitate spoken queries of large document databases. furthermore, the task of presenting large query result sets aurally should be performed such that the user's short term memory is not overloaded. in this paper, a framework allowing information retrieval to large document databases via voice is presented and findings from a research study using the framework will be discussed as well.
visualization of communication patterns in collaborative innovation networks - analysis of some w3c working groups. collaborative innovation networks (coins) are groups of self-motivated individuals from various parts of an organization or from multiple organizations, empowered by the internet, who work together on a new idea, driven by a common vision. in this paper we report first results of a project that examines innovation networks by analyzing the e-mail archives of some w3c (www consortium) working groups. these groups exhibit ideal characteristics for our purpose, as they form truly global networks working together over the internet to develop next generation technologies. we first describe the software tools we developed to visualize the temporal communication flow, which represent communication patterns as directed acyclic graphs, we then show initial results, which revealed significant variations between the communication patterns and network structures of the different groups., we were also able to identify distinctive communication patterns among group leaders, both those who were officially appointed and other who were assuming unofficial coordinating roles.
architecture of a metasearch engine that supports user information needs. when a query is submitted to a metasearch engine, decisions are made with respect to the underlying search engines to be used, what modifications will be made to the query, and how to score the results. these decisions are typically made by considering only the user's keyword query, neglecting the larger information need. users with specific needs, such as &ldquo;research papers&rdquo; or &ldquo;homepages,&rdquo; are not able to express these needs in a way that affects the decisions made by the metasearch engine. in this paper, we describe a metasearch engine architecture that considers the user's information need for each decision. users with different needs, but the same keyword query, may search different sub-search engines, have different modifications made to their query, and have results ordered differently. our architecture combines several powerful approaches together in a single general purpose metasearch engine.
inferring hierarchical descriptions. we create a statistical model for inferring hierarchical term relationships about a topic, given only a small set of example web pages on the topic, without prior knowledge of any hierarchical information. the model can utilize either the full text of the pages in the cluster or the context of links to the pages. to support the model, we use "ground truth" data taken from the category labels in the open directory. we show that the model accurately separates terms in the following classes: self terms describing the cluster, parent terms describing more general concepts, and child terms describing specializations of the cluster. for example, for a set of biology pages, sample parent, self, and child terms are science, biology, and genetics respectively. we create an algorithm to predict parent, self, and child terms using the new model, and compare the predictions to the ground truth data. the algorithm accurately ranks a majority of the ground truth terms highly, and identifies additional complementary terms missing in the open directory.
svm binary classifier ensembles for image classification. we study how the svm-based binary classifiers can be effectively combined to tackle the multi-class image classification problem. we study several ensemble schemes, including opc (one per class), pwc (pairwise coupling), and ecoc (error-correction output coding), that aim to achieve good error correction capability through redundancy. to enhance these ensemble schemes' accuracy, we propose methods that on the one hand boost the margins (i.e., confidence) of the svm-based binary classifiers, and, on the other hand, remove the noise of irrelevant classifiers from class prediction. from empirical study we show that our margin boosting and noise reduction methods lead to higher classification accuracy than ensemble schemes that are solely designed for maximum error correction capability.
context interchange: overcoming the challenges of large-scale interoperable database systems in a dynamic environment. research in database interoperability has primarily focused on circumventing schematic and semantic incompatibility arising from autonomy of the underlying databases. we argue that, while existing integration strategies might provide satisfactory support for small or static systems, their inadequacies rapidly become evident in large-scale interoperable database systems operating in a dynamic environment. this paper highlights the problem of receiver heterogeneity, scalability, and evolution which have received little attention in the literature, provides an overview of the context interchange approach to interoperability, illustrates why this is able to better circumvent the problems identified, and forges the connections to other works by suggesting how the context interchange framework differs from other integration approaches in the literature.
on off-topic access detection in information systems. we focus on detecting insider access violations to off-topic documents. previously, we utilized information retrieval techniques, e.g., clustering and relevance feedback, to warn of potential misuse. for the relevance feedback approach, we minimize the indicative features needed for detection using data mining techniques. we show that the derived reduced feature subset achieves equivalent performance to that of the previously derived full set of features.
bootstrapping for example-based data extraction. the effortless generation of wrappers for web data sources is a crucial task if proper access to the huge amount of semi-structured data on the web is to be granted. in particular, the development of strategies for wrapper generation based on user-given examples is currently one of the most promising research directions in web data extraction. in this paper we show how to use a pre-existing data repository to automatically generate examples and allow full automated example-based data extraction. to demonstrate the feasibility of our approach we provide a number of results obtained from experiments we carried out and discuss how our ideas can be used to improve extraction rates and for providing resilience and adaptiveness for example-based generated wrappers.
framework and algorithms for trend analysis in massive temporal data sets. mining massive temporal data streams for significant trends, emerging buzz, and unusually high or low activity is an important problem with several commercial applications. in this paper, we propose a framework based on relational records and metric spaces to study such problems. our framework provides the necessary mathematical underpinnings for this genre of problems, and leads to efficient algorithms in the stream/sort model of massive data sets (where the algorithm makes passes over the data, computes a new stream on the fly, and is allowed to sort the intermediate data). our algorithm makes novel use of metric approximations in the data stream context, and highlights the role of hierarchical organization of large data sets in designing efficient algorithms in the stream/sort model.
a probabilistic description-oriented approach for categorizing web documents. the automatic categorisation of web documents is becoming crucial for organising the huge amount of information available in the internet. we are facing a new challenge due to the fact that web documents have a rich structure and are highly heterogeneous. two ways to respond to this challenge are (1) using a representation of the content of web documents that captures these two characteristics and (2) using more effective classifiers.our categorisation approach is based on a probabilistic description-oriented representation of web documents, and a probabilistic interpretation of the k-nearest neighbour classifier. with the former, we provide an enhanced document representation that incorporates the structural and heterogeneous nature of web documents. with the latter, we provide a theoretical sound justification for the various parameters of the k-nearest neighbour classifier.experimental results show that (1) using an enhanced representation of web documents is crucial for an effective categorisation of web documents, and (2) a theoretical interpretation of the k-nearest neighbour classifier gives us improvement over the standard k-nearest neighbour classifier.
powerdb-ir - information retrieval on top of a database cluster. our current concern is a scalable infrastructure for information retrieval (ir) with up-to-date retrieval results in the presence of frequent, continuous updates. timely processing of updates is important with novel application domains, e.g., e-commerce. we want to use off-the-self hardware and software as much as possible. these issues are challenging, given the additional requirement that the resulting system must scale well. we have built powerdb-ir, a system that has the characteristics sought. this paper describes its design, implementation, and evaluation. powerdb-ir is a coordination layer for a database cluster. the rationale behind a database cluster is to 'scale-out', i.e., to add further cluster nodes, whenever necessary for better performance. we build on ir-to-database mappings and service decomposition to support high-level parallelism. we follow a three-tier architecture with the database cluster as the bottom layer for storage management. the middle tier provides ir-specific processing and update services. powerdb-ir has the following features: it allows to insert and retrieve documents concurrently, and it ensures freshness with almost no overhead. alternative physical data organization schemes provide adequate performance for different workloads. query processing techniques for the different data organizations efficiently integrate the ranked retrieval results from the cluster nodes. we have run extensive experiments with our prototype using commercial database systems and middleware software products. the main result is that powerdb-ir shows surprisingly ideal scalability and low response times.
xmltm: efficient transaction management for xml documents. a common approach to storage and retrieval of xml documents is to store them in a database, together with materialized views on their content. the advantage over "native" xml storage managers seems to be that transactions and concurrency are for free, next to other benefits. but a closer look and preliminary experiments reveal that this results in poor performance of concurrent queries and updates. the reason is that database lock contention hinders parallelism unnecessarily. we therefore investigate concurrency control at the semantic, i.e., xml level and describe a respective transaction manager xmltm. it features a new locking protocol dglock. it generalizes the protocol for locking on directed acyclic graphs by adding simple predicate locking on the content of elements, e.g., on their text. instead of using the original xml documents, we propose to take advantage of an abstraction of the xml document collection known as dataguides. xmltm allows to run xml processing at the underlying database at low ansi isolation degrees and to release database locks early without sacrificing correctness in this setting. we have built a complete prototype system that is implemented on top of the xml extender for ibm db2. our evaluation shows that our approach consistently yields performance improvements by an order of magnitude. we stress that our approach can also be implemented within a native xml storage manager, and we expect even better performance.
discovering approximate keys in xml data. keys are very important in many aspects of data management, such as guiding query formulation, query optimization, indexing, etc. we consider the situation where an xml document does not come with key definitions, and we are interested in using data mining techniques to obtain a representation of the keys holding in a document. in order to have a compact representation of the set of keys holding in a document, we define a partial order on the set of all key expressions. this order is based on an analysis of the properties of absolute and relative keys for xml. given the existence of the partial order, only a reduced set of key expressions need to be discovered.due to the semistructured nature of xml documents, it turns out to be useful to consider keys that hold in "almost" the whole document, that is, they are violated only in a small part of the document. to this end, the support and confidence of a key expression are also defined, and the concept of approximate key expression is introduced. we give an efficient algorithm to mine a reduced set of approximate keys from an xml document.
inferring document similarity from hyperlinks. assessing semantic similarity between text documents is a crucial aspect in information retrieval systems. in this work, we propose to use hyperlink information to derive a similarity measure that can then be applied to compare any text documents, with or without hyperlinks. as linked documents are generally semantically closer than unlinked documents, we use a training corpus with hyperlinks to infer a function a,b → sim(a,b) that assigns a higher value to linked documents than to unlinked ones. two sets of experiments on different corpora show that this function compares favorably with okapi matching on document retrieval tasks.
categorizing web queries according to geographical locality. web pages (and resources, in general) can be characterized according to their geographical locality. for example, a web page with general information about wildflowers could be considered a global page, likely to be of interest to a geographically broad audience. in contrast, a web page with listings on houses for sale in a specific city could be regarded as a local page, likely to be of interest only to an audience in a relatively narrow region. similarly, some search engine queries (implicitly) target global pages, while other queries are after local pages. for example, the best results for query [wildflowers] are probably global pages about wildflowers such as the one discussed above. however, local pages that are relevant to, say, san francisco are likely to be good matches for a query [houses for sale] that was issued by a san francisco resident or by somebody moving to that city. unfortunately, search engines do not analyze the geographical locality of queries and users, and hence often produce sub-optimal results. thus query [wildflowers] might return pages that discuss wildflowers in specific u.s. states (and not general information about wildflowers), while query [houses for sale] might return pages with real estate listings for locations other than that of interest to the person who issued the query. deciding whether an unseen query should produce mostly local or global pages---without placing this burden on the search engine users---is an important and challenging problem, because queries are often ambiguous or underspecify the information they are after. in this paper, we address this problem by first defining how to categorize queries according to their (often implicit) geographical locality. we then introduce several alternatives for automatically and efficiently categorizing queries in our scheme, using a variety of state-of-the-art machine learning tools. we report a thorough evaluation of our classifiers using a large sample of queries from a real web search engine, and conclude by discussing how our query categorization approach can help improve query result quality.
on the complexity of computing peer agreements for consistent query answering in peer-to-peer data integration systems. peer-to-peer (p2p) data integration systems have recently attracted significant attention for their ability to manage and share data dispersed over different peer sources. while integrating data for answering user queries, it often happens that inconsistencies arise, because some integrity constraints specified on peers' global schemas may be violated. in these cases, we may give semantics to the inconsistent system by suitably "repairing" the retrieved data, as typically done in the context of traditional data integration systems. however, some specific features of p2p systems, such as peer autonomy and peer preferences (e.g., different source trusting), should be properly addressed to make the whole approach effective. in this paper, we face these issues that were only marginally considered in the literature. we first present a formal framework for reasoning about autonomous peers that exploit individual preference criteria in repairing the data. the idea is that queries should be answered over the best possible database repairs with respect to the preferences of all peers, i.e., the states on which they are able to find an agreement. then, we investigate the computational complexity of dealing with peer agreements and of answering queries in p2p data integration systems. it turns out that considering peer preferences makes these problems only mildly harder than in traditional data integration systems.
the role of variance in term weighting for probabilistic information retrieval. in probabilistic approaches to information retrieval, the occurrence of a query term in a document contributes to the probability that the document will be judged relevant. it is typically assumed that the weight assigned to a query term should be based on the expected value of that contribution. in this paper we show that the degree to which observable document features such as term frequencies are expected to vary is also important. by means of stochastic simulation, we show that increased variance results in degraded retrieval performance. we further show that by decreasing term weights in the presence of variance, this degradation can be reduced. hence, probabilistic models of information retrieval must take into account not only the expected value of a query term's contribution but also the variance of document features.
consistent query answering under key and exclusion dependencies: algorithms and experiments. research in consistent query answering studies the definition and computation of "meaningful" answers to queries posed to inconsistent databases, i.e., databases whose data do not satisfy the integrity constraints (ics) declared on their schema. computing consistent answers to conjunctive queries is generally conp-hard in data complexity, even in the presence of very restricted forms of ics (single, unary keys). recent studies on consistent query answering for database schemas containing only key dependencies have analyzed the possibility of identifying classes of queries whose consistent answers can be obtained by a first-order rewriting of the query, which in turn can be easily formulated in sql and directly evaluated through any relational dbms. in this paper we study consistent query answering in the presence of key dependencies and exclusion dependencies. we first prove that even in the presence of only exclusion dependencies the problem is conp-hard in data complexity, and define a general method for consistent answering of conjunctive queries under key and exclusion dependencies, based on the rewriting of the query in datalog with negation. then, we identify a subclass of conjunctive queries that can be first-order rewritten in the presence of key and exclusion dependencies, and define an algorithm for computing the first-order rewriting of a query belonging to such a class of queries. finally, we compare the relative efficiency of the two methods for processing queries in the subclass above mentioned. experimental results, conducted on a real and large database of the computer science engineering degrees of the university of rome "la sapienza", clearly show the computational advantage of the first-order based technique.
intelligent creation of notification events in information systems: concept, implementation and evaluation. an important feature of information systems is the ability to inform users about changes of the stored information. therefore, systems have to 'know' what changes a user wants to be informed about. this is well known from the field of publish-/subscribe architectures. in this paper, we propose a solution for information system designers of how to extend their information model in a way that the notification mechanism can consider semantic knowledge when determining which parties to inform. two different kinds of implementations are introduced and evaluated: one based on aspect oriented programming (aop), the other one based on traditional database triggers. the evaluation of both approaches leads to a combined approach preserving the advantages of both techniques, using model driven architecture (mda) to create the triggers from a uml model enhanced with stereotypes.
efficient data dissemination using locale covers. location-dependent data are central to many emerging applications, ranging from traffic information services to sensor networks. the standard pull- and push-based data dissemination models become unworkable since the data volumes and number of clients are high. we address this problem using locale covers, a subset of the original set of locations of interest, chosen to include at least one location in a suitably defined neighborhood of any client. since location-dependent values are highly correlated with location, a query can be answered using a location close to the query point. typical closeness measures might be euclidean distance, or a k-nearest neighbor criterion. we show that location-dependent queries may be answered satisfactorily using locale covers. our approach is independent of locations and speeds of clients, and is applicable to mobile clients. we also introduce a nested locale cover scheme that ensures fair access latencies, and allows clients to refine the accuracy of their information over time. we also prove two important results: one regarding the greedy algorithm for sensor covers and the other pertaining to randomized locale covers for k-nearest neighbor queries.
exposing the vagueness of query results on partly inaccessible databases. query processing on partly inaccessible databases generally does not yield exact, but vague result sets. a good notion of vague sets fulfills two aims: it keeps the degree of vagueness of the query result as small as possible, and it clarifies the degree of and the reasons for the vagueness to the end user. the first goal requires a good internal representation, while the second goal requires a good external representation of a vague set. in this paper, we present a novel calculus for expressive vague sets that meets both requirements. this is the first approach that is well suited for both internal and external representation of vagueness induced by partial inaccessibility. it consists of a data representation that is capable of holding all the necessary information. complementary, we have accordingly adapted the usual query language operations. these adaptations are independent of a concrete query language, to make them applicable to most existing query languages. the adapted operations minimize the vagueness of the result, propagate the reasons of uncertainty of the individual vague candidates, and compute an expressive description of the missing elements.
exact match search in sequence data using suffix trees. we study suitable indexing techniques to support efficient exact match search in large biological sequence databases. we propose a suffix tree (st) representation, called sta-df, as an alternative to the array representation of st (sta) proposed in [7] and utilized in [18]. to study the performance of sta and sta-df, we develop a memory efficient st-based exact match (stem) search algorithm. we implemented stem and both representations of st and conducted extensive experiments. our results indicate that the sta and sta-df representations are very similar in construction time, storage utilization, and search time using stem. in terms of the access patterns by stem, our results show that compared to sta, the sta-df representation exhibits better spatial and sequential locality of reference. this suggests that sta-df would require less number of disk i/os, and hence is more amenable to efficient and scalable disk-based computation.
decentralized coordination of transactional processes in peer-to-peer environments. business processes executing in peer-to-peer environments usually invoke web services on different, independent peers. although peer-to-peer environments inherently lack global control, some business processes nevertheless require global transactional guarantees, i.e., atomicity and isolation applied at the level of processes. this paper introduces a new decentralized serialization graph testing protocol to ensure concurrency control and recovery in peer-to-peer environments. the uniqueness of the proposed protocol is that it ensures global correctness without relying on a global serialization graph. essentially, each transactional process is equipped with partial knowledge that allows the transactional processes to coordinate. globally correct execution is achieved by communication among dependent transactional processes and the peers they have accessed. in case of failures, a combination of partial backward and forward recovery is applied. experimental results exhibit a significant performance gain over traditional distributed locking-based protocols with respect to the execution of transactions encompassing web service requests.
integrating a part relationship into an open oodb system using metaclasses. the part-whole semantic relationship (the part relationship, for short) is an important modeling primitive in many advanced application domains such as manufacturing, design, and document processing. in this paper, we examine the problem of integrating such a construct into an oodb system. specifically, two questions are addressed in this regard. this first is: can a part relationship be made an intrinsic construct of an existing oodb system without having to rewrite a substantial portion of the system? the second: can an &ldquo;open&rdquo; oodb system which claims to support such an integration really do so, and, more specifically, can the integration be done using a metaclass mechanism which purports to bring extensibility to the vodak model language (vml)?to demonstrate that both questions can be answered &ldquo;yes,&rdquo; we introduce and discuss the details of a custom vml metaclass&mdash;the &ldquo;holonymicmeronymic&rdquo; metaclass&mdash;which we have built. this metaclass comprises two items, an &ldquo;instance&rdquo; type and an &ldquo;instance-instance&rdquo; type. together, the two endow the classes of a part hierarchy and their instances with structure and behavior consistent with our comprehensive part relationship model and the notions of &ldquo;part&rdquo; and &ldquo;whole.&rdquo; complete descriptions of each of these two aspects of the metaclass are presented and their effect on schema construction and database usage is discussed.
alternatives to the k-means algorithm that find better clusterings. we investigate here the behavior of the standard k-means clustering algorithm and several alternatives to it: the k-harmonic means algorithm due to zhang and colleagues, fuzzy k-means, gaussian expectation-maximization, and two new variants of k-harmonic means. our aim is to find which aspects of these algorithms contribute to finding good clusterings, as opposed to converging to a low-quality local optimum. we describe each algorithm in a unified framework that introduces separate cluster membership and data weight functions. we then show that the algorithms do behave very differently from each other on simple low-dimensional synthetic datasets and image segmentation tasks, and that the k-harmonic means method is superior. having a soft membership function is essential for finding high-quality clusterings, but having a non-constant data weight function is useful also.
feature-based recommendation system. the explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems--a personalized information filtering technology used to identify a set of n items that will be of interest to a certain user. user-based and model-based collaborative filtering are the most successful technology for building recommender systems to date and is extensively used in many commercial recommender systems. the basic assumption in these algorithms is that there are sufficient historical data for measuring similarity between products or users. however, this assumption does not hold in various application domains such as electronics retail, home shopping network, on-line retail where new products are introduced and existing products disappear from the catalog. another such application domains is home improvement retail industry where a lot of products (such as window treatments, bathroom, kitchen or deck) are custom made. each product is unique and there are very little duplicate products. in this domain, the probability of the same exact two products bought together is close to zero. in this paper, we discuss the challenges of providing recommendation in the domains where no sufficient historical data exist for measuring similarity between products or users. we present feature-based recommendation algorithms that overcome the limitations of the existing top-n recommendation algorithms. the experimental evaluation of the proposed algorithms in the real life data sets shows a great promise. the pilot project deploying the proposed feature-based recommendation algorithms in the on-line retail web site shows 75% increase in the recommendation revenue for the first 2 month period.
intelligent metasearch engine for knowledge management. the explosive growth of available information sources and the resulting information overload pose several problems for users in many business organizations and educational institutions. first, searching through several information sources, one at a time, is a source of enormous frustration for users. second, top-ranked documents in search results are frequently irrelevant to what users are interested in. to address these problems, we have developed ixmeta™, a powerful metasearch engine that gathers, evaluates, ranks, and reports the most relevant results from multiple information sources, including library catalogs, proprietary databases, intranets, and web search engines. in addition to basic metasearch capabilities, ixmetafind uses personalization and clustering techniques to find the most relevant results for users. in this paper, we briefly describe technologies used in ixmetafind and present pinpoint™ from sagebrush corporation, the smart research tool™ in the kindergarten through twelfth grade (k-12) school environment. pinpoint showcases ixmetafind in the knowledge management domain of the k-12 school environment.
logicbase: a deductive database system prototype. a deductive database system prototype, logicbase, has been developed, with an emphasis on efficient compilation and query evaluation of application-oriented recursions in deductive databases. the system identifies different classes of recursions and compiles recursions into chain or psuedo-chain forms when appropriate. queries posed to the compiled recursions are analyzed systematically with efficient evaluation plans generated and executed, mainly based on a chained-based query evaluation method. the system has been tested using sophisticated recursions and queries with satisfactory performance. this paper introduces the general design principles and implementation techniques of the system and discusses its strength and limitations.
using navigation data to improve ir functions in the context of web search. as part of the process of delivering content, devices like proxies and gateways log valuable information about the activities and navigation patterns of users on the web. in this study, we consider how this navigation data can be used to improve web search. a query posted to a search engine together with the set of pages accessed during a search task is known as a search session. we develop a mixture model for the observed set of search sessions, and propose variants of the classical em algorithm for training. the model itself yields a type of navigation-based query clustering. by implicitly borrowing strength between related queries, the mixture formulation allows us to identify the "highly relevant" urls for each query cluster. next, we explore methods for incorporating existing labeled data (the yahoo! directory, for example) to speed convergence and help resolve low-traffic clusters. finally, the mixture formulation also provides for a simple, hierarchical display of search results based on the query clusters. the effectiveness of our approach is evaluated using proxy access logs for the outgoing lucent proxy.
cooperative caching by mobile clients in push-based information systems. recent advances in computer and wireless communication technologies have increased interest in push-based information systems in which a server repeatedly broadcasts data to clients through a broadband channel. in this paper, assuming an environment where clients in push-based information systems construct ad hoc networks, we propose three caching strategies in which clients cooperatively cache broadcast data items. these strategies shorten the average response time for data access by replacing cached items based on their access frequencies, the network topology, and the time remaining until each item is broadcast next. we also show the results of simulation experiments conducted to evaluate the performance of our proposed strategies.
order checking in a cpoe using event analyzer. in this paper we present our experience in applying event analyzer, a processing engine we have developed to extract patterns from a sequence of events, in the checking of medical orders of a cpoe system. we present some extensions we have implemented in event analyzer in order to fulfill the needs of those orders checking, as well as some performance evaluation results. we also outline some problems we are facing now to adapt event analyzer's pattern detection engine to support streaming orders in an on-line cpoe checking system.
event analyzer: a tool for sequential data processing. in this paper we present a tool called event analyzer that processes events that compose a sequence. we present the data model in which event analyzer is based, as well as its query language that allows the expression of complex patterns to be searched over the sequence of events. the event analyzer has been developed and it now integrates the fujitsu symfoware e-business intelligence suite premium.
the semantic web: managing knowledge for planet earth. the semantic web (sweb) is a vision - actually, a number of visions - which is beginning to show some signs of potential reality. the core of the vision is a synergy between machine-accessible knowledge and the global reach of the web. the deployment of knowledge technologies on a planet-wide open network brings new challenges and opportunities, many of them not yet fully realized. this talk briefly surveys the current state of play in sweb standards and technology, including some of the rather heated controversies, and tries to give a high-level view of some of these challenges and opportunities. some traditional hard problems in km may largely evaporate; but new ones will take their place.
organizing structured web sources by query schemas: a clustering approach. in the recent years, the web has been rapidly "deepened" with the prevalence of databases online. on this deep web, many sources are <i>structured</i> by providing structured query interfaces and results. organizing such structured sources into a domain hierarchy is one of the critical steps toward the integration of heterogeneous web sources. we observe that, for structured web sources, query schemas <i>ie</i>, attributes in query interfaces) are discriminative representatives of the sources and thus can be exploited for source characterization. in particular, by viewing query schemas as a type of categorical data, we abstract the problem of source organization into the clustering of categorical data. our approach hypothesizes that "homogeneous sources" are characterized by the same hidden generative models for their schemas. to find clusters governed by such statistical distributions, we propose a new objective function, <i>model-differentiation</i>, which employs principled hypothesis testing to maximize statistical heterogeneity among clusters. our evaluation over hundreds of real sources indicates that (1) the schema-based clustering accurately organizes sources by object domains <i>eg</i>, books, movies), and (2) on clustering web query schemas, the model-differentiation function outperforms existing ones, such as likelihood, entropy, and context linkages, with the hierarchical agglomerative clustering algorithm.
compact reachability labeling for graph-structured data. testing reachability between nodes in a graph is a well-known problem with many important applications, including knowledge representation, program analysis, and more recently, biological and ontology databases inferencing as well as xml query processing. various approaches have been proposed to encode graph reachability information using node labeling schemes, but most existing schemes only work well for specific types of graphs. in this paper, we propose a novel approach, hlss(hierarchical labeling of sub-structures), which identifies different types of substructures within a graph and encodes them using techniques suitable to the characteristics of each of them. we implement hlss with an efficient two-phase algorithm, where the first phase identifies and encodes strongly connected components as well as tree substructures, and the second phase encodes the remaining reachability relationships by compressing dense rectangular submatrices in the transitive closure matrix. for the important subproblem of finding densest submatrices, we demonstrate the hardness of the problem and propose several practical algorithms. experiments show that hlss handles different types of graphs well, while existing approaches fall prey to graphs with substructures they are not designed to handle.
quasi-dynamic two-phase locking. among the plethora of concurrency control algorithms that have been proposed and analyzed, two-phase locking (2pl) has been adapted as the industry de facto standard concurrency control. in accord, current research in concurrency control is focusing on enhancing the scalability of 2pl performance in highly concurrent and contentious environments. this is especially needed in future on-line transaction processing systems, where thousand transaction per second performance will be required.static locking (sl) and dynamic locking (dl) are two famous adaptations of 2pl that are used under different degrees of data contention. in this paper, we offer our observation that 2pl is indeed a family of methods, of which sl and dl are extreme case members. further, we argue for and verify the existence of other 2pl member methods that, under variable conditions, outperform sl and dl. we propose two novel schemes which we categorize as quasi-dynamic two-phase locking on account of their behavior in comparison with dynamic/static two-phase locking. we present a simulation study of the performance of the proposed schemes and their comparison to dynamic and static locking methods.
how foreign function integration conquers heterogeneous query processing. with the emergence of application systems which encapsulate databases and related application components, pure data integration using, for example, a federated database system is not possible anymore. instead, access via predefined functions is the only way to get data from an application system. as a result, retrieval of such heterogeneous and encapsulated data sources needs the combination of generic query as well as predefined function access. in this paper, we present a middleware approach supporting such a novel and extended kind of integration. starting with the overall architecture, we explain the functionality and cooperation of its core components: a federated database system and a workflow management system connected via a wrapper. afterwards, we concentrate on essential aspects of query processing across these heterogeneous components focusing on the impact of the functions included. we discuss the operations the wrapper should provide in order to extend the workflow system's native functionality. in addition to selection and projection, these operations could include aggregation and the support of subqueries. moreover, we point out modifications to the traditional cost model needed to consider the cost estimates for the function calls as well.
syynx solutions: practical knowledge management in a medical environment. in this paper we describe the knowledge management approach for the biomedical scientific community developed by syynx solutions gmbh [1].
from bits and bytes to information and knowledge. unstructured data is a valuable source of information and implicit knowledge. yet, the bits and bytes of, e.g., text, image, or click-stream data need to be interpreted in order to transform them into business intelligence and actionable information. clearly, this process needs to be automated to the largest possible extend in order to be scalable to the typical volumes of data. one way to accomplish this is through the use of machine learning and statistical modelling techniques. this talk will provide an overview of recent progress and new trends in machine learning and discuss their relevance for developing intelligent tools for search, information filtering, categorization, and knowledge extraction.
sql text parsing for information retrieval. the concept of using a relational database to perform information retrieval (ir) search functions is well established. prior work demonstrates the capability to perform common functions and advanced ranking algorithms using standard, unchanged sql. the previous work does not address the preprocessing of unstructured text within the relational model. in fact, the parsing of the unstructured data into a structured data set was done outside of the database, usually using sequential programming languages such as c. this work proves that ir preprocessing does not require proprietary application code to build the framework necessary for searching document databases. furthermore, the resulting environment is relational and integrates with other data sources within an organization.
efficient mining of association rules in text databases. in this paper, we propose two new algorithms for mining association rules between words in text databases. the characteristics of text databases are quite different from those of retail transaction databases, and existing mining algorithms cannot handle text databases efficiently because of the large number of itemsets (i.e., words) that need to be counted. two well-known mining algorithms, apriori algorithm and direct hashing and pruning (dhp) algorithm, are evaluated in the context of mining text databases, and are compared with the new proposed algorithms named multipass-apriori (m-apriori) and multipass-dhp (m-dhp). it has been shown that the proposed algorithms have better performance for large text databases.
indexing text data under space constraints. an important class of queries is the like predicate in sql. in the absence of an index, like queries are subject to performance degradation. the notion of indexing on substrings (or <i>q</i>-grams) has been explored earlier without sufficient consideration of efficiency. <i>q</i>-grams are used to prune away rows that do not qualify for the query. the problem is to identify a finite number of grams subject to storage constraint that gives maximal pruning for a given query workload. our contributions include: i) a formal problem definition, that produces results within a provable error bound, ii) performance evaluation of the application of the novel method to real data, and iii) parallelization of the algorithm, scaling considerations and a proposal to handle scaling issues.
an optimal construction of invalidation reports for mobile databases. mobile computing is characterized by frequent disconnection, limited communication capability, narrow bandwidth, etc. caching can play a vital role in mobile computing by reducing the amount of data transferred. in order to reuse caches after short disconnections, invalidation reports are broadcasted to clients to help update/invalidate their caches. detailed reports may not be desirable because they can be very long and consume large bandwidth. on the other hand, false invalidations may set in if detailed timing information of updates is not provided in the report. in this research, we aim to reduce the false invalidation rates of the reports. it is found that false invalidation rates are closely related to clients' reconnection patterns (i.e., the distribution of the time spans between disconnections and reconnections). by using newton's method, we show how a report with a minimal false invalidation rate can be constructed for any given disconnection pattern.
integrating dct and dwt for approximating cube streams. for time-relevant multi-dimensional data sets (mds), users usually pose a huge amount of data due to the large dimensionality, and approximating query processing has emerged as a viable solution. specifically, the cube streams handle mdss in a continuous manner. traditional cube approximation focuses on generating single snapshots rather than continuous ones. to address this issue, the application of generating snapshots for cube streams, called scs, is investigated in this paper. such an application collects data events for cube streams on-line and generates snapshots with limited resources in order to keep the approximated information in synopsis memory for further analysis. as compared to olap applications, the scs ones are subject to much more resource constraints for both processing time and memory and cannot be dealt with by existing methods due to the limited resources. in this paper, the dawa algorithm, standing for a hybrid algorithm of dct for data and discrete wavelet transform, is proposed to approximate the cube streams. the dawa algorithm combines the advantage of high compression rate from dwt and that of low memory cost from dct. consequently, dawa costs much smaller working buffer and outperforms both dwt-based and dct-based methods in execution efficiency. also, it is shown that dawa provides answers of good quality for scs applications with a small working buffer and short execution time. the optimality of algorithm dawa is theoretically proved and also empirically demonstrated by our experiments.
the effectiveness study of various music information retrieval approaches. in this paper, we describe the ultima project which aims to construct a platform for evaluating various approaches of music information retrieval. two kinds of approaches are adopted in this project. these approaches differ in various aspects, such as representations of music objects, index structures, and approximate query processing strategies. for a fair comparison, we propose a measurement of the retrieval effectiveness by recall-precision curves with a scaling factor adjustment. finally, the performance study of the retrieval effectiveness based on various factors of these approaches is presented.
classification algorithms for netnews articles. we propose several algorithms using the vector space model to classify the news articles posted on the netnews according to the newsgroup categories. the baseline method combines the terms of all the articles of each newsgroup in the training set to represent the newsgroups as single vectors. after training, the incoming news articles are classified based on their similarity to the existing newsgroup categories. we propose to use the following techniques to improve the classification performance of the baseline method: (1) use routing (classification) accuracy and the similarity values to refine the training set; (2) update the underlying term structures periodically during testing; and (3) apply k-means clustering to partition the newsgroup articles and represent each newsgroup by k vectors. our test collection consists of the real news articles and the 519 subnewsgroups under the rec newsgroup of netnews in a period of 3 months. our experimental results demonstrate that the technique of refining the training set reduces from one-third to two-thirds of the storage. the technique of periodical updates improves the routing accuracy ranging from 20% to 100% but incurs runtime overhead. finally, representing each newsgroup by k vectors (with k = 2 or 3) using clustering yields the most significant improvement in routing accuracy, ranging from 60% to 100%, while causing only slightly higher storage requirements.
a near optimal algorithm for generating broadcast programs on multiple channels. in a wireless environment, the bandwidth of the channels and the energy of the portable devices are limited. data broadcast has become an excellent method for efficient data dissemination. in this paper, the problem for generating a broadcast program of a set of data items with the associated access frequencies on multiple channels is explored. in our approach, an expected average access time of the broadcast data items is first derived. the broadcast program is then generated, which minimizes the expected average access time. simulation is performed to compare the performance of our approach with two existing approaches. the result of the experiments shows that our approach outperforms others and is in fact close to the optimal.
indexing techniques for wireless data broadcast under data clustering and scheduling. this paper investigates power conserving indexing techniques for data disseminated on a broadcast channel. a hybrid indexing method combining strengths of the signature and the index tree techniques is presented. different from previous studies, our research takes into consideration two important data organization factors, namely, clustering and scheduling. cost models for index, signature and hybrid methods are derived by taking into account various data organizations accommodating these two factors. based on our analytical comparisons, the signature and the hybrid indexing techniques are the best choices for power conserving indexing of various data organizations on wireless broadcast channels.
mining undiscovered public knowledge from complementary and non-interactive biomedical literature through semantic pruning. two complementary and non-interactive literature sets of articles, when they are considered together, can reveal useful information of scientific interest not apparent in either of the two document sets. swanson called the existence of such knowledge, undiscovered public knowledge (udpk). this paper proposes a semantic-based mining model for udpk. our method replaces manual ad-hoc pruning with using semantic knowledge from the biomedical ontologies. using the semantic types and semantic relationships of the biomedical concepts, our prototype system can identify the relevant concepts collected from medline and generate the novel hypothesis between these concepts. the system successfully replicates swanson's two famous discoveries: raynaud disease/fish oils and migraine/magnesium. compared with previous approaches, our methods generate much fewer but more relevant novel hypotheses, and require much less human intervention in the discovery procedure.
comparison of interestingness functions for learning web usage patterns. livelink is a collaborative intranet, extranet and e-business application that enables employees and business partners of an organization to capture, share and reuse business information and knowledge. the usage of the livelink software has been recorded by the livelink web server in its log files. we present an application of data mining techniques to the livelink web usage data. in particular, we focus on how to find interesting association rules and sequential patterns from the livelink log files. a number of interestingness measures are used in our application to identify interesting rules and patterns. we present a comparison of these measures based on the feedback from domain experts. some of the interestingness measures are found to be better than others.
exploring group mobility for replica data allocation in a mobile environment. the growth in wireless communication technologies attracts a considerable amount of attention in mobile ad-hoc networks. since mobile hosts in an ad-hoc network usually move freely, the topology of the network changes dynamically and disconnection occurs frequently. these characteristics make a mobile ad-hoc network be likely to be separated into several disconnected partitions, and the data accessibility is hence reduced. several schemes are proposed to alleviate the reduction of data accessibility by replicating data items. however, little research effort was elaborated upon exploiting the group mobility where the group mobility refers to the phenomenon that several mobile nodes tend to move together. in this paper, we address the problem of replica allocation in a mobile ad-hoc network by exploring group mobility. we first analyze the group mobility model and derive several theoretical results. in light of these results, we propose a replica allocation scheme to improve the data accessibility. several experiments are conducted to evaluate the performance of the proposed scheme. the experimental results show that the proposed scheme is able to not only obtain higher data accessibility but also produce lower network traffic than prior schemes.
a new permutation approach for distributed association rule mining. privacy preserving distributed data mining has become a promising research area. this paper addresses the problem of association rule mining where the global database is vertically partitioned. when transactions are distributed in different sites, scalar product is a feasible tool to discover frequent itemsets. we present a new protocol to compute scalar product between two parties with a permutation approach. we analyze the protocol in detail and demonstrate its effectiveness and high privacy properties, and compare it to other published protocols.
compression schemes for differential categorical stream clustering. stream data analysis differs significantly from traditional data processing. to process the data online the algorithm has to work in one pass, incorporating new data into a model maintained in main memory. storing a model or synopsis of processed data in the memory, which we call "data compression", is an important technique in both incremental and differential stream mining. this paper proposes several data compression schemes in one-pass categorical data clustering, and demonstrates their performance on synthetic and real data. our compression schemes can efficiently generate compact representations of original data, so as to enable the algorithm to process streams at high speed and detect the changes in underlying data. the example algorithm based on these compression schemes achieves good accuracy in short execution time.
binary interpolation search for solution mapping on broadcast and on-demand channels in a mobile computing environment. we explore in this paper the problem of dynamic data and channel allocations with the number of communication channels and the number of data items given. it is noted that the combined use of broadcast and on-demand channels can utilize the bandwidth effectively for data dissemination in a mobile computing environment. we first derive the an-alytical models of the expected delays when the data are requested through the broadcast and on-demand channels. then, we transform this problem into to a guided search problem. in light of the theoretical properties derived, we devise an algorithm based on binary interpolation search, referred to as algorithm bis, to obtain solutions of high quality efficiently. in essence, algorithm bis is guided to explore the solution space with higher likelihood to be the optimal first, thereby leading to an efficient and effective search. it is shown by our simulation results that the solution obtained by algorithm bis is of very high quality and is in fact very close to the optimal one. sensitivity analysis on several parameters, including the number of data items and the number of communication channels, is conducted.
industrial evaluation of a highly-accurate academic ir system. in this paper we report the results of an independent experimental evaluation of an information retrieval (ir) system developed at the illinois institute of technology (iit). the system, which is called the advanced information retrieval engine (aire), consists of a set of tools and utilities providing indexing, extraction, searching and visualization. we evaluated aire on three data sets from the text retrieval conference (trec) - trec 8, 9 and 10. overall, our results indicate that aire is a highly accurate ir system. compared with results published by iit, in our experiments aire consistently scored higher in recall. aire also scored higher in precision, but only for automatic tasks. in manual tasks, aire scored lower in precision in our experiments, but we attributed that to factors external to aire. our final conclusion is that aire is a highly accurate ir system.
emerging data management systems: close-up and personal. conventional data management occurs primarily in centralized servers or in well-interconnected distributed systems. these are removed from their end users, who interact with the systems mostly through static devices to obtain generic services around main-stream applications: banking, retail, business management, etc. several recent advances in technologies, however, give rise to a new breed of applications, which change altogether the user experience and sense of data management. very soon several such systems will be in our pockets, many more in our homes, the kitchen appliances, our clothes, etc. how would these systems operate? many system and user aspects must be approached in novel ways, while several new issues come up and need to be addressed for the first time. highlights include personalization, privacy, information trading, annotation, new interaction devices and corresponding interfaces, visualization, etc. in this talk, we take a close look at and give a very personal guided tour to this emerging world of data management, offering some thoughts on how the new technical challenges might be approached.
group formation mechanisms for transactions in isis. distributed toolkits like isis provide means of replicating data but not means for making it persistent. this makes the use of transactions desirable, even in non-database applications. using isis can alleviate the programming cost of distributed transaction processing the multi-phase commit protocols. using the isis transaction tool, however, imposes additional cost, and we examine the effect of group formation strategies on the overhead. the paper presents three different group formation mechanisms in isis and compares the costs associated with them.
an object-oriented extension of xml for autonomous web applications. while the idea of extending xml to include object-oriented features has been gaining popularity in general, the potential of inheritance in document design has not been well recognized in contemporary research. in this paper we demonstrate that xml with dynamic inheritance aids better document designs and decreased management overheads and support increased autonomy. as an extended application, we point out that dynamic inheritance also helps effective automated web portal and ontology designs.we present an object-oriented extension to the language of xml to include dynamic inheritance and describe a middle layer that implements our system. we explain our system with several practical examples.
towards a visual query interface for phylogenetic databases. querying and visualization of phylogenetic databases remain a great challenge due to their complex tree type semi structured nature. naturally, successful phylogenetic databases such as the tree of life database at the university of arizona are implemented as web documents in html. while web implementation of such databases facilitate the representation, and in part, visualization of their contents, querying remains an issue. the interoperability of web-based phylogenetic databases with other similar databases such as treebase and rdb which are implemented using traditional database management systems, has not been possible due to the impedance mismatch between the underlying query and data representation framework. in this paper, we present a novel approach to phylogentic database management using existing database technologies without compromising potential opportunities for visualization and interoperability. we present a web-based tool for the creation, querying and visualization of phylogenetic databases. we demonstrate the functional capabilities and strengths of our system by recreating the tree of life database in our system and performing queries that are not possible in the original tree of life database.
an effective mechanism for index update in structured documents. indexing and retrieval of structured documents have been drawing attention increasingly since they enable to retrieve and access a certain part of a document easily. so far, several methods have been proposed in the setting that documents are rarely changed. these can be applied for the books or journals possessed in libraries, but hardly work for the documents that are subject to change frequently in the business domain. this paper aims at enabling incremental update of indices whenever parts of documents are changed. for this, it employs the index-organized table that has been developed for the full-text retrieval in oracle. it creates several index-organized tables that are essential in implementing the bottom up scheme strategy, which has been developed for manipulating structured documents efficiently.along with an experiment, the technique presented here does not add much index overhead to the original one taken to the index organized table. in addition, the updates of indices are performed quickly as soon as parts of documents are changed.
parallelizing the buckshot algorithm for efficient document clustering. we present a parallel implementation of the buckshot document clustering algorithm. we demonstrate that this parallel approach is highly efficient both in terms of load balancing and minimization of communication. in a series of experiments using the 2gb of sgml data from trec disks 4 and 5, our parallel approach was shown to be scalable in terms of processors efficiently used and the number of clusters created.
finding similar questions in large question and answer archives. there has recently been a significant increase in the number of community-based question and answer services on the web where people answer other peoples' questions. these services rapidly build up large archives of questions and answers, and these archives are a valuable linguistic resource. one of the major tasks in a question and answer service is to find questions in the archive that a semantically similar to a user's question. this enables high quality answers from the archive to be retrieved and removes the time lag associated with a community-based system. in this paper, we discuss methods for question retrieval that are based on using the similarity between answers in the archive to estimate probabilities for a translation-based retrieval model. we show that with this model it is possible to find semantically similar questions with relatively little word overlap.
induction of integrated view for xml data with heterogeneous dtds. this paper proposes a novel approach to integrating heterogeneous xml dtds. with this approach, an information agent can be easily extended to integrate heterogeneous xml-based contents and perform federated search. based on a tree grammar inference technique, this approach derives an integrated view of xml dtds in an information integration framework. the derivation takes advantages of naming and structural similarities among dtds in similar domains. the complete approach consists of three main steps. (1) dtd clustering clusters dtds in similar domains into classes. (2) schema learning applies a tree grammar inference technique to generate a set of tree grammar rules from the dtds in a class from the previous step. (3) minimization optimizes the rules generated in the previous step and transforms them into an integrated view. we have implemented the proposed approach into a system called deep and tested the system on artificial and real domains. the experimental results reveal that this system can effectively and efficiently integrate radically different dtds.
queueing analysis of relational operators for continuous data streams. currently, stream data processing is an active area of research, which includes everything from algorithms and architectures for stream processing to modelling, and analysis of various components of a stream processing system. in this paper, we present an analysis of relational operators used for stream processing using queueing theory and study behaviors of streaming data in a query processing system. our approach enables us to compute the fundamental performance metrics of relational operators ---select, project, and join over data streams. furthermore, this approach establishes a way to find the probability distribution functions of both the number of tuples and the waiting time of tuples in the system. finally, we designed and implemented a number of experiments to validate the accuracy and effectiveness of our analysis.
re-evaluating indexing schemes for nested objects. performance is a major issue in the acceptance of object-oriented database management systems (oodbms). the nested index and path index schemes have been criticized for their heavy costs and poor handling of update operations. this paper re-evaluates three index schemes (nested index, path index, and multi-index) applicable to queries on nested attributes. among these, we found that a multi-index scheme is best supported in the object-oriented or extended relational dbms environment. multi-index schemes not only provide a better balance between retrieval and update costs than do the nested or path indices, but they also scale well for update when the number of indices increases. in this paper, we propose a multi-index design that reuses the single-table index structures already present in a dbms. our performance study extends previous models by permitting attributes to be multi-valued as well as single-valued. we also suggest that a combination of nested index and multi-index schemes offers a feasible solution to the support of queries on nested objects.
accurately extracting coherent relevant passages using hidden markov models. in this paper, we present a principled method for accurately extracting coherent relevant passages of variable lengths using hmms. we show that with appropriate parameter estimation, the hmm method outperforms a number of strong baseline methods on two data sets.
retrieving answers from frequently asked questions pages on the web. we address the task of answering natural language questions by using the large number of frequently asked questions (faq) pages available on the web. the task involves three steps: (1) fetching faq pages from the web; (2) automatic extraction of question/answer (q/a) pairs from the collected pages; and (3) answering users' questions by retrieving appropriate q/a pairs. we discuss our solutions for each of the three tasks, and give detailed evaluation results on a collected corpus of about 3.6gb of text data (293k pages, 2.8m q/a pairs), with real users' questions sampled from a web search engine log. specifically, we propose simple but effective methods for q/a extraction and investigate task-specific retrieval models for answering questions. our best model finds answers for 36% of the test questions in the top 20 results. our overall conclusion is that faq pages on the web provide an excellent resource for addressing real users' information needs in a highly focused manner.
dynamically maintaining frequent items over a data stream. it is challenge to maintain frequent items over a data stream, with a small bounded memory, in a dynamic environment where both insertion/deletion of items are allowed. in this paper, we propose a new novel algorithm, called hcount, which can handle both insertion and deletion of items with a much less memory space than the best reported algorithm. our algorithm is also superior in terms of precision, recall and processing time. in addition, our approach does not request the preknowledge on the size of range for a data stream, and can handle range extension dynamically. given a little modification, algorithm hcount can be improved to hcount*, which even owns significantly better performance than before.
collaborative filtering with decoupled models for preferences and ratings. in this paper, we describe a new model for collaborative filtering. the motivation of this work comes from the fact that two users with very similar preferences on items may have very different rating schemes. for example, one user may tend to assign a higher rating to all items than another user. unlike previous models of collaborative filtering, which determine the similarity between two users only based on their rating performance, our model treats the user's preferences on items separately from the user's rating scheme. more specifically, for each user, we build two separate models: a preference model capturing which items are favored by the user and a rating model capturing how the user would rate an item given the preference information. the similarity of two users is computed based on the underlying preference model, instead of the surface ratings. we compare the new model with several representative previous approaches on two data sets. experiment results show that the new model outperforms all the previous approaches that are tested consistently on both data sets.
localized signature table: fast similarity search on transaction data. recently, techniques for supporting efficient similarity search over huge transaction datasets have emerged as an important research area. several indexing schemes have been proposed towards this direction. typically, these schemes provide a tradeoff between searching efficiency and indexing overhead in terms of space. in this paper, we propose a novel indexing scheme for similarity search on transaction data. based on well-studied clustering techniques, we develop a construction algorithm for the proposed index and a branch-and-bound searching strategy for answering similarity search. unlike previous techniques, our indexing scheme exhibits high search efficiency and low space requirements by trading-off the pre-computation time. this behavior is ideal for applications with low update but high read volume <i>e.g.</i>, data warehousing, collaborative filtering, <i>etc.</i>). moreover, our experimental results illustrate that our method is robust to the varying characteristics of the datasets.
linguistic instruments and qualitative reasoning for schema integration. two major problems in schema integration are to identify correspondences between different conceptual schemas and to verify that the proposed correspondences are consistent with the semantics of the schemas. we propose a heuristic method, based on the use of galois lattices, for identifying schema correspondences. we show how the results of this method can be checked for correctness by introducing a number of necessary conditions for schema mergeability. these conditions are formulated in the context of a semantically rich modelling formalism, the distinguishing feature of which is the use of case grammar.
extending complex ad-hoc olap. large scale data analysis and mining activities require sophisticated information extraction queries. many queries require complex aggregation, and many of these aggregates are non-distributive. conventional solutions to this problem involve defining user defined aggregate functions (udafs). however, the use of udafs entails several problems. defining a new udaf can be a significant burden for the user, and optimizing queries involving udafs is difficult because of the &ldquo;black box&rdquo; nature of the udaf.in this paper, we present a method for expressing nested aggregates in a declarative way. a nested aggregate, which is a rollup of another aggregated value, expresses a wide range of useful non-distributive aggregation. for example, most frequent type aggregation can be naturally expressed using nested aggregation, e.g. &ldquo;for each product, report its total sales during the month with the largest total sales of the product&rdquo;. by expressing compex aggregates declaratively, we relieve the user of the burden of defining udafs, and allow the evalution of the complex aggregates to be optimized.we use the extended multi-feature (emf) syntax as the basis for expressing nested aggregation. an advantage of this approach is that emf sql can already express a wide range of complex aggregation in a succinct way, and emf sql is easily optimized into efficient query plans. we show that nested aggregation queries can be evaluated efficiently by using a small extension to the emf sql query evaluation algorithm. a side effect of this extension is to extend emf sql to permit complex aggregation of data from multiple sources.
keeping found things found on the web. this paper describes the results of an observational study into the methods people use to manage web information for re-use. people observed in our study used a diversity of methods and associated tools. for example, several participants emailed web addresses (urls) along with comments to themselves and to others. other methods observed included printing out web pages, saving web pages to the hard drive, pasting the address for a web page into a document and pasting the address into a personal web site. ironically, two web browser tools that have been explicitly developed to help users track web information - the bookmarking tool and the history list - were not widely used by participants in this study. a functional analysis helps to explain the observed diversity of methods. methods vary widely in the functions they provide. for example, a web address pasted into a self-addressed email can provide an important reminding function together with a context of relevance: the email arrives in an inbox which is checked at regular intervals and the email can include a few lines of text that explain the url's relevance and the actions to be taken. on the other hand, for most users in the study, the bookmarking tool ("favorites" or "bookmarks" depending on the browser) provided neither a reminding function nor a context of relevance. the functional analysis can help to assess the likely success of various tools, current and proposed.
serf: integrating human recommendations with search. today's university library has many digitally accessible resources, both indexes to content and considerable original content. using off-the-shelf search technology provides a single point of access into library resources, but we have found that such full-text indexing technology is not entirely satisfactory for library searching. in response to this, we report initial usage results from a prototype of an entirely new type of search engine - the system for electronic recommendation filtering (serf) - that we have designed and deployed for the oregon state university (osu) libraries. serf encourages users to enter longer and more informative queries, and collects ratings from users as to whether search results meet their information need or not. these ratings are used to make recommendations to later users with similar needs. over time, serf learns from the users what documents are valuable for what information needs. in this paper, we focus on understanding whether such recommendations can increase other users' search efficiency and effectiveness in library website searching. based on examination of three months of usage as an alternative search interface available to all users of the oregon state university libraries website (http://osulibrary.oregonstate.edu/), we found strong evidence that the recommendations with human evaluation could increase the efficiency as well as effectiveness of the library website search process. those users who received recommendations needed to examine fewer results, and recommended documents were rated much higher than documents returned by a traditional search engine.
kalchas: a dynamic xml search engine. this paper outlines the system architecture and the core data structures of kalchas, a fulltext search engine for xml data with emphasis on dynamic indexing, and identifies features worth demonstrating. the concept of dynamic index implies that the aim is to re ect the creation of, deletion of, and updates to relevant files in the search index as early as possible. this is achieved by a number of techniques, including ideas drawn from partitioned b-trees and inverted indices. the actual ranked retrieval of document is implemented with xml-specific query operators for lowest common ancestor queries.a live demonstration will discuss kalchas' behaviour in typical use cases, such as interactive editing sessions and bulk loading large amounts of static files as well as querying the contents of the indexed files; it tries to clarify both the short-comings and the advantages of the method.
a local search mechanism for peer-to-peer networks. one important problem in peer-to-peer (p2p) networks is searching and retrieving the correct information. however, existing searching mechanisms in pure peer-to-peer networks are inefficient due to the decentralized nature of such networks. we propose two mechanisms for information retrieval in pure peer-to-peer networks. the first, the modified breadth-first search (bfs) mechanism, is an extension of the current gnuttela protocol, allows searching with keywords, and is designed to minimize the number of messages that are needed to search the network. the second, the intelligent search mechanism, uses the past behavior of the p2p network to further improve the scalability of the search procedure. in this algorithm, each peer autonomously decides which of its peers are most likely to answer a given query. the algorithm is entirely distributed, and therefore scales well with the size of the network. we implemented our mechanisms as middleware platforms. to show the advantages of our mechanisms we present experimental results using the middleware implementation.
web-centric language models. we investigate language models for informational and navigational web search. retrieval on the web is a task that differs substantially from ordinary ad hoc retrieval. we perform an analysis of prior probability of relevance for a wide range of non-content features, shedding further light on the importance of non-content features for web retrieval. this directly explains the success or failure of various techniques, e.g., why the link topology is particularly helpful to single out important sites. language models can naturally incorporate multiple document representations, as well as non-content information. for the former, we employ mixture language models based on document full-text, incoming anchor-text, and document titles. for the latter, we study a range of priors based on document length, url structure, and link topology. we look at three types of topics--distillation, home page, and named page--as well as for a mixed query set. we find that the mixture models lead to considerable improvement of retrieval effectiveness for all topic types. the web-centric priors generally lead to further improvement of retrieval effectiveness.
structured queries in xml retrieval. document-centric xml is a mixture of text and structure. with the increased availability of document-centric xml content comes a need for query facilities in which both structural constraints and constraints on the content of the documents can be expressed. how does the expressiveness of languages for querying xml documents help users to express their information needs? we address this question from both an experimental and a theoretical point of view. our experimental analysis compares a structure-ignorant with a structure-aware retrieval approach using the test-suite of the 2004 edition of the inex xml retrieval evaluation initiative. theoretically, we create mathematical models of users' knowledge of a set of documents and define query languages which exactly fit these models. one of these languages corresponds to an xml version of fielded search, the other to the inex query language. our main findings are: first, while structure is used in varying degrees of complexity, over half of the queries can be expressed in a fielded-search like format which does not use the hierarchical structure of the documents. second, structure is used as a search hint, and not a strict requirement, when judged against the underlying information need. third, the use of structure in queries functions as a precision enhancing device.
fast webpage classification using url features. we demonstrate the usefulness of the uniform resource locator (url) alone in performing web page classification. this approach is faster than typical web page classification, as the pages do not have to be fetched and analyzed. our approach segments the url into meaningful chunks and adds component, sequential and orthographic features to model salient patterns. the resulting features are used in supervised maximum entropy modeling. we analyze our approach's effectiveness on two standardized domains. our results show that in certain scenarios, url-based methods approach the performance of current state-of-the-art full-text and link-based methods.
a method of geographical name extraction from japanese text for thematic geographical search. a text retrieval method called the thematic geographical search method has been developed and applied to a japanese encyclopedia called the world encyclop&aelig;dia. in this method, the user specifies a search theme using free words, then obtains a sorted list of excerpts and hyperlinks to encyclopedia sentences that contain geographical names. using this list, the user can also open maps that indicate the locations of the names. to generate an index of names for this searching, a method of extracting geographical names has been developed. in this method, geographical names are extracted, matched to names in a geographical name database, and identified. geographical names, however, often have several types of ambiguities. ambiguities are resolved by using non-local context analysis, which uses a stack and several other techniques. as a result, the precision of extracted names is more than 96% on average. this method depends on features of the japanese language, but the strategy and most of the techniques can be applied to texts in english or other languages.
establishing value mappings using statistical models and user feedback. in this paper, we present a "value mapping" algorithm that does not rely on syntactic similarity or semantic interpretation of the values. the algorithm first constructs a statistical model (e.g., co-occurrence frequency or entropy vector) that captures the unique characteristics of values and their co-occurrence. it then finds the matching values by computing the distances between the models while refining the models using user feedback through iterations. our experimental results suggest that our approach successfully establishes value mappings even in the presence of opaque data values and thus can be a useful addition to the existing data integration techniques.
regularizing translation models for better automatic image annotation. the goal of automatic image annotation is to automatically generate annotations for images to describe their content. in the past, statistical machine translation models have been successfully applied to automatic image annotation task [8]. it views the process of annotating images as a process of translating the content from a 'visual language' to textual words. one problem with the existing translation models is that common words are usually associated with too many different image regions. as a result, uncommon words have little chance to be used for annotating images. uncommon words are important for automatic image annotation because they are often used in the queries. in this paper, we propose two modified translation models for automatic image annotation, namely the normalized translation model and the regularized translation model, that specifically address the problem of common annotated words. the basic idea is to raise the number of blobs that are associated with uncommon words. the normalized translation model realizes this by scaling translation probabilities of different words with different factors. the same goal is achieved in the regularized translation model through the introduction of a special dirichlet prior. empirical study with the corel dataset has shown that both two modified translation models outperform the original translation model and several existing approaches for automatic image annotation substantially.
indexing field values in field oriented systems: interval quadtree. with the extension of spatial database applications, field oriented systems emerge as an important research issue in order to deal with continuous natural phenomena during the last years. it however has a large volume of data and efficient indexing methods for field data are necessary to overcome the performance obstacle. in special, we introduce indexing methods for field value queries (i.e. searching some regions where the temperature is more 20 degrees). we introduce the concept of subfield and show how we make use of this concept to index field values in field oriented systems. we present two implementation methods based on quadtree space subdivision. we modify traditional linear quadtree implementation method for field value query processing using subfields. we analyze the performance of our methods. experimentation with real terrain data shows that proposed indexing methods improve the query processing time of field value queries in comparison with the case of no indexing method.
entropy-based link analysis for mining web informative structures. in this paper, we study the problem of mining the informative structure of a news web site which consists of thousands of hyperlinked documents. we define the informative structure of a news web site as a set of index pages (or referred to as toc, i.e., table of contents, pages) and a set of article pages linked by toc pages through informative links. it is noted that the hyperlink induced topics search (hits) algorithm has been employed to provide a solution to analyzing authorities and hubs of pages. however, most of the content sites tend to contain some extra hyperlinks, such as navigation panels, advertisements and banners, so as to increase the add-on values of their web pages. therefore, due to the structure induced by these extra hyperlinks, hits is found to be insufficient to provide a good precision in solving the problem. to remedy this, we develop an algorithm to utilize entropy-based link analysis on mining web informative structures. this algorithm is referred to as lamis. the key idea of lamis is to utilize information entropy for representing the knowledge that corresponds to the amount of information in a link or a page in the link analysis. experiments on several real news web sites show that the precision and the recall of lamis are much superior to those obtained by heuristic methods and conventional ink analysis methods.
updates and view maintenance in soft real-time database systems. a database system contains base data items which record and model a physical, real world environment. for better decision support, base data items are summarized and correlated to derive views. these base data and views are accessed by application transactions to generate the ultimate actions taken by the system. as the environment changes, updates are applied to the base data, which subsequently trigger view recomputations. there are thus three types of activities: base data update, view recomputation, and transaction execution. in a real-time system, two timing constrains need to be enforced. we require transactions meet their deadlines (transaction timeliness) and read fresh data (data timeliness). in this paper we define the concept of absolute and relative temporal consistency from the perspective of transactions. we address the important issue of transaction scheduling among the three types of activities such that the two timing requirements can be met. we also discuss how a real-time database system should be designed to enforce different levels of temporal consistency.
user assisted text classification and knowledge management. while there are many aspects to managing corporate knowledge, one key issue is how to organize corporate documents into categories of interest. in this paper, we focus on using user assisted text classification in conjunction with a web portal, multiple document management systems and an ontology, to provide a powerful solution for organizing information about a company's technology. we propose a system that interacts with an author using an automatic text classifier to suggest controlled keywords to be used as metadata. the proposed approach does not require professional librarians or that the end users have extensive training. the use of a controlled vocabulary allows for a more consistent description of corporate documents, and promotes easier access by people across the company. it is easier to find similar documents which use different nomenclature. finally, the interactive nature of the system results in a more correct and precise description of each document than a fully automatic system would.
a storage system for scalable knowledge representation. twenty years of ai research in knowledge representation has produced frame knowledge representation systems (frss) that incorporate a number of important advances. however, frss lack two important capabilities that prevent them from scaling up to realistic applications: they cannot provide high-speed access to large knowledge bases (kbs), and they do not support shared, concurrent kb access by multiple users. our research investigates the hypothesis that one can employ an existing database management system (dbms) as a storage subsystem for an frs, to provide high-speed access to large, shared kbs. we describe the design and implementation of a general storage system that incrementally loads referenced frames from a dbms, and saves modified frames back to the dbms, for two different frss: loom and theo. we also present experimental results showing that the performance of our prototype storage subsystem exceeds that of flat files for simulated applications that reference or update up to one third of the frames from a large loom kb.
evaluation of item-based top-n recommendation algorithms. the explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems---a personalized information filtering technology used to identify a set of n items that will be of interest to a certain user. user-based collaborative filtering is the most successful technology for building recommender systems to date, and is extensively used in many commercial recommender systems. unfortunately, the computational complexity of these methods grows linearly with the number of customers that in typical commercial applications can grow to be several millions. to address these scalability concerns item-based recommendation techniques have been developed that analyze the user-item matrix to identify relations between the different items, and use these relations to compute the list of recommendations.in this paper we present one such class of item-based recommendation algorithms that first determine the similarities between the various items and then used them to identify the set of items to be recommended. the key steps in this class of algorithms are (i) the method used to compute the similarity between the items, and (ii) the method used to combine these similarities in order to compute the similarity between a basket of items and a candidate recommender item. our experimental evaluation on five different datasets show that the proposed item-based algorithms are up to 28 times faster than the traditional user-neighborhood based recommender systems and provide recommendations whose quality is up to 27% better.
semantics-based information brokering. the rapid advances in computer and communication technologies, and their merger, is leading to a global information market place. it will consist of federations of very large number of information systems that will cooperate to varying extents to support the users' information needs. we discuss an approach to information brokering in the above environment. we discuss two of its tasks: information resource discovery, which identifies relevant information sources for a given query, and query processing, which involves the generation of appropriate mapping from relevant but structurally heterogeneous objects. query processing consists of information focusing and information correlation.our approach is based on: semantic proximity, which represents semantic similarities based on the context of comparison, and schema correspondences which are used to represent structural mappings and are associated with the context. the context of comparison of the two objects is the primary vehicle to represent the semantics for determining semantic proximity. specifically, we use a partial context representation to capture the semantics in terms of the assumptions in the intended use of the objects and the intended meaning of the user query. information focusing is supported by subsequent context comparison. the same mechanism can be used to support information resource discovery. context comparison leads to changes in schema correspondences that are used to support information correlation.
xel: extended ephemeral logging for log storage management. extended ephemeral logging (xel) is a more general variation of the ephemeral logging (el) technique for managing a log of database activity on disk; it does not require a timestamp to be maintained with each object in the database. xel does not require periodic checkpoints and does not abort lengthy transactions as frequently as traditional firewall logging for the same amount of disk space. therefore, it is well suited for concurrent databases and applications which have a wide distribution of transaction lifetimes.simulation results indicate that xel can offer significant savings in disk space, at the expense of slightly higher bandwidth for logging and more main memory. the reduced size of the log permits much faster recovery after a crash as well as cost savings.
features of documents relevant to task- and fact-oriented questions. we describe results from an ongoing project that considers question types and document features and their relationship to retrieval techniques. we examine eight document features from the top 25 documents retrieved from 74 questions and find that lists and faqs occur in more documents judged relevant to task-oriented questions than those judged relevant to fact-oriented questions.
automated index management for distributed web search. distributed heterogeneous search systems are an emerging phenomenon in web search, in which independent topic-specific search engines provide search services, and metasearchers distribute user's queries to only the most suitable search engines. previous research has investigated methods for engine selection and merging of search results (i.e. performance improvements from the user's perspective). we focus instead on performance from the service provider's point of view (e.g, income from queries processed vs. resources used to answer them). we consider a scenario in which individual search engines compete for user queries by choosing which documents (topics) to index. the difficulty here stems from the fact that the utilities of local engine actions should depend on the uncertain actions of competitors. thus, naive strategies (e.g, blindly indexing lots of popular documents) are ineffective. we model the competition between search engines as a stochastic game, and propose a reinforcement learning approach to managing search index contents. we evaluate our approach using a large log of user queries to 47 real search engines.
effective nearest neighbor indexing with the euclidean metric. the nearest neighbor search is an important operation widely-used in multimedia databases. in higher dimensions, most of previous methods for nearest neighbor search become inefficient and require to compute nearest neighbor distances to a large fraction of points in the space. in this paper, we present a new approach for processing nearest neighbor search with the euclidean metric, which searches over only a small subset of the original space. this approach effectively approximates clusters by encapsulating them into geometrically regular shapes and also computes better upper and lower bounds of the distances from the query point to the clusters. for showing the effectiveness of the proposed approach, we perform extensive experiments. the results reveal that the proposed approach significantly outperforms the x-tree as well as the sequential scan.
o-preh: optimistic transaction processing algorithm based on pre-reordering in hybrid broadcast environments. in recent years, there has been a lot of research effort in the periodic push model where the server repetitively disseminates information without explicit request. we call the broadcast model supporting backchannel as hybrid broadcast. in this paper, we devise a new transaction processing algorithm called o-preh, which is based on the notion of pre-reordering. if one or more conflicts for mobile transactions are found from server's periodic invalidation report, conflict orders are determined not to violate the consistency( pre-reordering) and then the remaining operations have to be executed pessimistically.
spatial match representation scheme supporting ranking in iconic images databases. because content-based image retrieval is essential to retrieve relevant multimedia documents, we represent images as a set of recognizable symbols, i.e., icon objects, and do indexing by regarding the icon object as a representative of a given document. when users request content-based image retrieval, we convert a query image into icon objects and retrieve relevant images in the database. in this paper, we propose a new spatial-match representation scheme, called srr(spatial-match representation supporting ranking) scheme, which combine directional operators with positional operators. therefore, our srr scheme can represent spatial relationships between icon objects precisely and can provide ranking for the retrieved images. in addition, we compare our scheme with the conventional 9dlt and smr schemes in terms of retrieval effectiveness. finally, we show from our experiment that our srr scheme holds about 25% higher recall and about 10% higher precision, compared with the 9dlt and the smr.
partial rollback in object-oriented/object-relational database management systems. in a database management system (dbms), partial rollback is an important mechanism for canceling only part of the operations executed in a transaction back to a savepoint. partial rollback complicates buffer management because it should restore the state of the buffers as well as that of the database. several relational dbmss (rdbmss) currently provide this mechanism using page buffers. however, object-oriented or object-relational dbmss (oo/ordbmss) cannot utilize the partial rollback scheme of rdbmss as is because, unlike rdbmss, many of them use a dual buffer consisting of an object buffer and a page buffer. in this paper, we propose a thorough study of partial rollback schemes of oo/ordbmss with a dual buffer. first, we classify the partial rollback schemes of oo/ordbmss into a single buffer-based scheme and a dual buffer-based scheme by the number of buffers used to process rollback. next, we propose four alternative partial rollback schemes: a page buffer-based scheme, an object buffer-based scheme, a dual buffer-based scheme using a soft log, and a dual buffer-based scheme using shadows. we then evaluate their performance through simulations. the results show that the dual buffer-based partial rollback scheme using shadows provides the best performance. partial rollback in oo/ordbms has not been addressed in the literature; yet, it is a useful mechanism that must be implemented. the proposed schemes are practical ones that can be implemented in such dbmss.
functionality and architecture of a cooperative database system: a vision. a database system fostering the cooperative usage and modification of a common data pool should provide standard database functionality (e.g. application-independent correctness criteria and data modelling) plus means for a step-wise, cooperative refinement of data over a long period of time. key ingredients are a hierarchical organization of work, a sound data model covering cooperative uncertainly, and support for long-living cooperative processes. furthermore, mechanisms for data passing and hiding, negotiation means, and notification are of prominent importance. in the paper, the rationale behind such a functionality is described. furthermore, a proposal is made for the software architecture of what is called a cooperative database system (cdbms).
finding interesting rules from large sets of discovered association rules. association rules, introduced by agrawal, imielinski, and swami, are rules of the form &ldquo;for 90% of the rows of the relation, if the row has value 1 in the columns in set w, then it has 1 also in column b&rdquo;. efficient methods exist for discovering association rules from large collections of data. the number of discovered rules can, however, be so large that browsing the rule set and finding interesting rules from it can be quite difficult for the user. we show how a simple formalism of rule templates makes it possible to easily describe the structure of interesting rules. we also give examples of visualization of rules, and show how a visualization tool interfaces with rule templates.
processing search queries in a distributed environment. endeca's approach to processing search queries in a distributed computing environment is predicated on concerns of correctness, scalability, and flexibility in deployment. using a master-slave architecture, we are able to support classic search as well as more advanced features. we avoid bottlenecking the master with excessive computation or communication by limiting the information from the slaves in the expected case.
summarization as feature selection for text categorization. we address the problem of evaluating the effectiveness of summarization techniques for the task of document categorization. it is argued that for a large class of automatic categorization algorithms, extraction-based document categorization can be viewed as a particular form of feature selection performed on the full text of the document and, in this context, its impact can be compared with state-of-the-art feature selection techniques especially devised to provide good categorization performance. such a framework provides for a better assessment of the expected performance of a categorizer if the compression rate of the summarizer is known.
query workload-aware overlay construction using histograms. peer-to-peer(p2p) systems over an efficient means of data sharing among a dynamically changing set of a large number of a tonomous nodes.each node in a p2p system is connected with a small number of other nodes thus creating an overlay network of nodes. a query posed at a node is routed through the overlay network towards nodes hosting data items that satisfy it. in this paper, we consider building overlays that exploit the query workload so that nodes are clustered based on their results to a given query workload. the motivation is to create overlays where nodes that match a large number of similar queries are a fewlinks apart. query frequency is also taken into account so that popular queries have a greater effect on the formation of the overlay than unpopular ones. we focus on range selection queries and se histograms to estimate the query results of each node. then, nodes are clustered based on the similarity of their histograms. to this end,we introd ce a workload-aware edit distance metric between histograms that takes into account the query workload. our experimental results show that workload-aware overlays increase the percentage of query results returned for a given number of nodes visited as compared to both random (i.e., unclustered)overlays and non workload-aware clustered overlays (i.e., overlays that cluster nodes based solely on the nodes' content).
leveraging collective knowledge. as more organizations begin to deploy taxonomies for categorization and faceted search, the cost of producing these knowledge models is becoming the largest expense on a project. at a cost of 200 - 300 dollars per topic, manually developing subject area taxonomies does not scale for any but the smallest of projects. this paper will discuss an approach called orthogonal corpus indexing ( oci ). oci leverages existing published knowledge in the subject area of the taxonomy model. this knowledge is algorithmically mapped into multiple taxonomies via the oci algorithm. the resulting taxonomy costs are 1/ 100th of the cost of manual methods and are created with embedded rule sets for categorization engines. this paper will discuss the theory of oci, its practical use as well as examples of knowledge management techniques that are possible when taxonomies are large, detailed and inexpensive.
stemming and lemmatization in the clustering of finnish text documents. stemming and lemmatization were compared in the clustering of finnish text documents. since finnish is a highly inflectional and agglutinative language, we hypothesized that lemmatization, involving splitting of the compound words, would be more appropriate normalization approach than the straightforward stemming. the relevance of the documents were evaluated with a four-point relevance assessment scale, which was collapsed into binary one by considering all the relevant and only the highly relevant documents relevant, respectively. experiments with four hierarchical clustering methods supported the hypothesis. the stringent relevance scale showed that lemmatization allowed the single and complete linkage methods to recover especially the highly relevant documents better than stemming. in comparison with stemming, lemmatization together with the average linkage and ward's methods produced higher precision. we conclude that lemmatization is a better word normalization method than stemming, when finnish text documents are clustered for information retrieval.
y!q: contextual search at the point of inspiration. contextual search tries to better capture a user's information need by augmenting the user's query with contextual information extracted from the search context (for example, terms from the web page the user is currently reading or a file the user is currently editing).this paper presents y!q---a first of its kind large-scale contextual search system---and provides an overview of its system design and architecture. y!q solves two major problems. first, how to capture high quality search context. second, how to use that context in a way to improve the relevancy of search queries. to address the first problem, y!q introduces an information widget that captures precise search context and provides convenient access to its functionality at the point of inspiration. for example, y!q can be easily embedded into web pages using a web api, or it can be integrated into a web browser toolbar. this paper provides an overview of y!q's user interaction design, highlighting its novel aspects for capturing high quality search context.to address the second problem, y!q uses a semantic network for analyzing search context, possibly resolving ambiguous terms, and generating a contextual digest comprising its key concepts. this digest is passed through a query planner and rewriting framework for augmenting a user's search query with relevant context terms to improve the overall search relevancy and experience. we show experimental results comparing contextual y!q search results side-by-side with regular yahoo! web search results. this evaluation suggests that y!q results are considered significantly more relevant.the paper also identifies interesting research problems and argues that contextual search may represent the next major step in the evolution of web search engines.
efficient and effective server-sided distributed clustering. clustering has become an increasingly important task in modern application domains where the data are originally located at different sites. in order to create a central clustering, all clients have to transmit their data to a central server. due to technical limitations and security aspects, at the central site often only vague object descriptions are available. the server then has to carry out the clustering based on vague and uncertain data. in a recent paper, an approach for clustering uncertain data was proposed based on the concept of medoid clusterings. the idea of this approach is to create first several sample clusterings. then based on suitable distance functions between clusterings the most average clustering, i.e. the medoid clustering, was determined. in this paper, we extend this approach for partitioning clustering algorithms and propose to compute a centroid clustering based on these input sample clusterings. these centroid clusterings are new artificial clusterings which minimize the distance to all the sample clusterings.
towards smarter documents. document analysis research typically focuses on document image understanding or classic problems in text classification, clustering, summarization and discovery. while that is an important aspect of document management, in practice, documents lifecycles are often determined by the context of the business process that they are relevant to. it therefore becomes necessary for the document analysis techniques to recognize and leverage the contextual information provided by a supporting schema and business process. this paper presents an intelligent document management framework with relevant document analysis, metadata extraction, and business process association algorithms and methodology. the architecture supporting this framework seamlessly integrates a runtime environment with an authoring environment by combining relational data modeling tools with document classification techniques. the runtime environment accepts incoming documents, classifies the document, extracts metadata and executes customized business logic. the authoring environment supports the association of a class of documents with a relational document schema, identification of attribute values that must be extracted automatically, generation of relevant business logic, and deployment of authoring artifacts into the runtime architecture. we demonstrate the use of this framework with representative real-world document transformative applications.
a clustering algorithm for asymmetrically related data with applications to text mining. clustering techniques find a collection of subsets of a data set such that the collection satisfies a criterion that is dependent on a relation defined on the data set. the underlying relation is traditionally assumed to be symmetric. however, there exist many practical scenarios where the underlying relation is asymmetric. one example of an asymmetric relation in text analysis is the inclusion relation, i.e., the inclusion of the meaning of a block of text in the meaning of another block. in this paper, we consider the general problem of clustering of asymmetrically related data and propose an algorithm to cluster such data. to demonstrate its usefulness, we consider two applications in text mining: (1) summarization of short documents, and (2) generation of a concept hierarchy from a set of documents. our experiments show that the performance of the proposed algorithm is superior to that of more traditional algorithms.
biasing web search results for topic familiarity. depending on a web searcher's familiarity with a query's target topic, it may be more appropriate to show her introductory or advanced documents. the trec hard [1] track defined topic familiarity as meta-data associated with a user's query. we instead define a user-independent and query-independent model of topic-familiarity required to read a document, so it can be matched to a given user in response to a query. an introductory web page is defined as a web page that doesn't presuppose any background knowledge of the topic it is on, and to an extent introduces or defines the key terms in the topic. while an advanced web page is defined as a web page that assumes sufficient background knowledge of the topic it is on, and familiarity with the key technical/ important terms in the topic, and potentially builds on them. we develop a method for biasing the initial mix of documents returned by a search engine to increase the number of documents of desired familiarity level up to position 5, and up to position 10. our method involves building a supervised text classifier, incorporating features based on reading level, the distribution of stop-words in the text, and non-text features such as average line-length. using this familiarity classifier, we achieve statistically significant improvements at reranking the result set to show introductory documents higher up the ranked list. our classifier can be seamlessly integrated into current search engine technology without involving any major modifications to existing architectures.
query expansion using domain adapted, weighted thesaurus in an extended boolean model. in this paper, we address there important issues with query expansion using a thesaurus; how to give weights to the terms in expanded queries, how to select additional search terms in the thesaurus, and how to enrich the terms in the manual thesaurus (namely, thesaurus reconstruction). to weight the terms in expanded queries, we construct the weighted thesaurus that has a similarity value between the terms in the thesaurus, using statistical co-occurrence in a corpus. to enrich the terms in the manual thesaurus, domain dependent terms which occur in a corpus are inserted into the weighted thesaurus using the co-occurrence information. in this paper, the reconstructed thesaurus with weights is defined as a domain-adapted, weighted thesaurus. then we explain query expansion using the domain-adapted, weighted thesaurus in an extended boolean retrieval model. to select additional search terms during query expansion, our model uses semi-automatic query expansion and a restriction method. in the experiments, our system had almost twice the recall of the boolean retrieval system not using the thesaurus or the query expansion retrieval system using the original thesaurus. and also, the precision of our system was almost the same precision as the other systems.
yahoo! as an ontology: using yahoo! categories to describe documents. we suggest that one (or a collection) of names of yahoo! (or any other www indexer's) categories can be used to describe the content of a document. such categories offer a standardized and universal way for referring to or describing the nature of real world objects, activities, documents and so on, and may be used (we suggest) to semantically characterize the content of documents. www indices, like yahoo! provide a huge hierarchy of categories (topics) that touch every aspect of human endeavors. such topics can be used as descriptors, similarly to the way librarians use for example, the library of congress cataloging system to annotate and categorize books.in the course of investigating this idea, we address the problem of automatic categorization of webpages in the yahoo! directory. we use telltale as our classifier; telltale uses n-grams to compute the similarity between documents. we experiment with various types of descriptions for the yahoo! categories and the webpages to be categorized. our findings suggest that the best results occur when using the very brief descriptions of the yahoo! categorized entries; these brief descriptions are provided either by the entries' submitters or by the yahoo! human indexers and accompany most yahoo!-indexed entries.
automatic identification of best entry points for focused structured document retrieval. focussed structured document retrieval employs the concept of best entry points (beps), which are intended to provide optimal starting-points from which users can browse to relevant document components. this paper describes two small-scale studies, using experimental data from the shakespeare user study, which developed and evaluated different approaches to the problem of automatic identification of beps.
efficient synchronization for mobile xml data. many handheld applications receive data from a primary database server and operate in an intermittently connected environment these days. they maintain data consistency with data sources through sychronization. in certain applications such as sales force automation, it is highly desirable if updates on the data source can be reflected at the handheld applications immediately. this paper proposes an efficient method to synchronize xml data on multiple mobile devices. each device retrieves and caches a local copy of data from the database source based on a regular path expression. these local copies may be overlapping or disjoint with each other. an efficient mechanism is proposed to find all the disjoint copies to avoid unnecessary synchronizations. each update to the data source will then be checked to identify all handheld applications which are affected by the update. communication costs can be further reduced by eliminating the forwarding of unnecessary operations to groups of mobile clients.
application of a symbolico-connectionist approach for the design of a highly interactive documentary database interrogation system with on-line learning capabilities. the nomad system is a documentary database interrogration system based on a symbolico-connectionist approach.nomad makes use of the synthesis capabilities and flexibility inherent in this type of approach to increase its processing power as compared as compared to existing systems while proposing new operating modes directly accessible to a large number of users:&bull;nomad manages multiple synthetic type views on its documentary contents in the form of neural topographies acting as case-memories as well as elaborated thematic browsing tools.&bull;nomad manages a session memory based on the neural model of the novelty detector with the following three functions: cumulative recording of user need, managing user contradictions and proposing new orientations.&bull;nomad also has extended learning capabilities, enabling it to improve its performance in the long term.in the introduction of this article, we justify the modelling choices made for nomad. the system will then be described in detailed, stressing the new possibilities regarding help in query formulation and improvement in retrieval performance. the evaluation campaign and the numerous evolution perspectives provided by the model are described in the final section.
adaptive information filtering: detecting changes in text streams. the task of information filtering is to classify documents from a stream as either relevant or non-relevant according to a particular user interest with the objective to reduce information load. when using an information filter in an environment that is changing with time, methods for adapting the filter should be considered in order to retain classification accuracy. we favor a methodology that attempts to detect changes and adapts the information filter only if inevitable in order to minimize the amount of user feedback for providing new training data. yet, detecting changes may require costly user feedback as well. this paper describes two methods for detecting changes without user feedback. the first method is based on evaluating an expected error rate, while the second one observes the fraction of classification decisions made with a confidence below a given threshold. further, a heuristics for automatically determining this threshold is suggested and the performance of this approach is experimentally explored as a function of the threshold parameter. some empirical results show that both methods work well in a simulated change scenario with real world data.
on the estimation of frequent itemsets for data streams: theory and experiments. in this paper, we devise a method for the estimation of the true support of itemsets on data streams, with the objective to maximize one chosen criterion among {precision, recall} while ensuring a degradation as reduced as possible for the other criterion. we discuss the strengths, weaknesses and range of applicability of this method that relies on conventional uniform convergence results, yet guarantees statistical optimality from different standpoints.
distributional term representations: an experimental comparison. a number of content management tasks, including term categorization, term clustering, and automated thesaurus generation, view natural language <i>terms</i> (e.g. words, noun phrases) as first-class objects, i.e. as objects endowed with an internal representation which makes them suitable for explicit manipulation by the corresponding algorithms. the information retrieval (ir) literature has traditionally used an extensional (aka <i>distributional</i>) representation for terms according to which a term is represented by the "bag of documents" in which the term occurs. the computational linguistics (cl) literature has independently developed an alternative distributional representation for terms, according to which a term is represented by the "bag of terms" that co-occur with it in some document. this paper aims at discovering which of the two representations is most effective, i.e. brings about higher effectiveness once used in tasks that require terms to be explicitly represented and manipulated. we carry out experiments on (i) a term categorization task, and (ii) a term clustering task; this allows us to compare the two different representations in closely controlled experimental conditions. we report the results of experiments in which we categorize/cluster under 42 different classes the terms extracted from a corpus of more than 65,000 documents. our results show a substantial difference in effectiveness between the two representation styles; we give both an intuitive explanation and an information-theoretic justification for these different behaviours.
indexing and retrieval of scientific literature. the web has greatly improved access to scientific literature. however, scientific articles on the web are largely disorganized, with research articles being spread across archive sites, institution sites, journal sites, and researcher homepages. no index covers all of the available literature, and the major web search engines typically do not index the content of postscript/pdf documents at all. this paper discusses the creation of digital libraries of scientific literature on the web, including the efficient location of articles, full-text indexing of the articles, autonomous citation indexing, information extraction, display of query-sensitive summaries and citation context, hubs and authorities computation, similar document detection, user profiling, distributed error correction, graph analysis, and detection of overlapping documents. the software for the system is available at no cost for non-commercial use.
a self-organized file cabinet. the self-organizing file cabinet is an information retrieval system associated with a user's physical file cabinet. it enhances a physical file cabinet with electronic information about the papers in it. it can remember, organize, update, and help the user find documents contained in the physical file cabinet. the system consists of a module for extracting electronic information about the papers stored in the file cabinet, a module for representing and storing this information in multiple views, and a module that allows a user to interact with this information. the focus of this paper is on the design and evaluation of the self-organized file cabinet.
an automated approach for retrieving hierarchical data from html tables. among the html elements, html tables [rhj98] encapsulate hierarchically structured data (hierarchical data in short) in a tabular structure. html tables do not come with a rigid schema and almost any forms of two-dimensional tables are acceptable according to the html grammar. this relaxation complicates the process of retrieving hierarchical data from html tables. in this paper, we propose an automated approach for retrieving hierarchical data from html tables. the proposed approach constructs the content tree of an html table, which captures the intended hierarchy of the data content of the table, without requiring the internal structure of the table to be known beforehand. also, the user of the content tree does not deal with html tags while retrieving the desired data from the content tree. our approach can be employed by (i) a query language written for retrieving hierarchically structured data, extracted from either the contents of html tables or other sources, (ii) a processor for converting html tables to xml documents, and (iii) a data warehousing repository for collecting hierarchical data from html tables and storing materialized views of the tables. the time complexity of the proposed retrieval approach is proportional to the number of html elements in an html table.
semql: a semantic query language for multidatabase systems. an essential prerequisite to achieving interoperability in multidatabase systems is to be able to identify semantically equivalent or related data items in component databases. another problem in multidatabase systems is allowing users to handle information from different databases that refer to the same realworld entity. in this paper, we provide semantic networks so that multidatabase systems can detect and resolve semantic heterogeneities among component databases. and we provide a semantic query language, semql, to capture the concepts about what users want. it enables users to issue queries to a large number of autonomous databases without prior knowledge of their schemas.
page access scheduling in join processing. the join relational operation is one of the most expensive among database operations. in this study, we consider the problem of scheduling page accesses in join processing. this raises two interesting problems: 1) determining a page access sequence that uses the minimum number of buffer pages without any page reaccesses, and 2) determining a page access sequence that minimizes the number of page reaccesses for a given buffer size. we use a graph model to represent the pages from the relations that contain tuples to be joined, and present new heuristics for the two problems based on the sort-merge join and the simple tid algorithm. our experimental results show that the new heuristics perform well.
semantic caching via query matching for web sources. a semantic caching scheme suitable for wrappers wrapping web sources is presented. since the web sources have typically weaker querying capabilities than conventional databases, existing semantic caching schemes cannot be applied directly. a seamlessly integrated query translation and capability mapping between the wrappers and web sources in semantic caching is described. in addition, an analysis on the match types between the user's input query and cached queries is presented. semantic knowledge acquired from the data can be used to avoid unnecessary access to the web sources by transforming the cache miss to the cache hit. a polynomial time algorithm based on the proposed query matching technique is presented to find the best matched query in the cache. experimental results reveal the effectiveness of the proposed semantic caching scheme.
efficient evaluation of multiple queries on streaming xml data. traditionally, xml documents are processed at where they are stored. this allows the query processor to exploit pre-computed data structures (e.g., index) to retrieve the desired data efficiently. however, this mode of processing is not suitable for many applications where the documents are frequently updated. in such situations, efficient evaluation of multiple queries over streaming xml documents becomes important. this paper introduces a new operator, mqx-scan, which efficiently evaluates multiple queries with a single pass on streaming xml data. to facilitate matching, mqx-scan utilizes templates containing paths that have been traversed to match regular path expression patterns in a pool of queries. results of the experiments demonstrate the efficiency and scalability of the mqx-scan operator.
training a selection function for extraction. in this paper we compare performance of several heuristics in generating informative generic/query-oriented extracts for newspaper articles in order to learn how topic prominence affects the performance of each heuristic. we study how different query types can affect the performance of each heuristic and discuss the possibility of using machine learning algorithms to automatically learn good combination functions to combine several heuristics. we also briefly describe the design, implementation, and performance of a multilingual text summarization system summarist.
information integration with attributio support for corporate profiles. the proliferation of electronically available data within large organizations as well as publicly available data (e.g. over the world wide web) poses challenges for users who wish to efficiently interact with and integrate multiple heterogeneous sources. this paper presents ci3, a corporate information integrator, which applies xml as a tool to facilitate data mediation and integration amongst heterogeneous sources in the context of financial analysts creating corporate profiles. sources include lotus notes, relational databases, and the world wide web. ci3 applies a unified xml data model to automate integration. by preserving metadata about the source of each datum in the integrated result set, ci3 supports source attribution. users may trace the attribution metadata from the result back to the underlying sources and leverage their expertise in interpreting the data and, if necessary, use their judgment in assessing the authenticity and veracity of results. we present a functional overview of ci3, its system architecture including the xml data model, and the integration procedures. we conclude by reflecting on lessons learned.
question answering from the web using knowledge annotation and knowledge mining techniques. we present a strategy for answering fact-based natural language questions that is guided by a characterization of real-world user queries. our approach, implemented in a system called aranea, extracts answers from the web using two different techniques: knowledge annotation and knowledge mining. knowledge annotation is an approach to answering large classes of frequently occurring questions by utilizing semi\-structured and structured web sources. knowledge mining is a statistical approach that leverages massive amounts of web data to overcome many natural language processing challenges. we have integrated these two different paradigms into a question answering system capable of providing users with concise answers that directly address their information needs.
an evaluation of the incorporation of a semantic network into a multidimensional retrieval engine. this paper describes a new method for incorporating a hierarchical category dimension into an information retrieval framework. the approach is to use the synonym sets and the hyponym ("is-a") relations defined within wordnet in order to derive a conceptual hierarchical category dimension. the hierarchical nature of a category dimension not only provides an overview of a set of documents but also facilitates the effectiveness and the efficiency of searching documents. an evaluation is performed on two different types of models and the multidimensional approach shows a significant reduction in the number of page accesses over a large document collection.
handling frequent updates of moving objects. a critical issue in moving object databases is to develop appropriate indexing structures for continuously moving object locations so that queries can still be performed efficiently. however, such location changes typically cause a high volume of updates, which in turn poses serious problems on maintaining index structures. in this paper we propose a lazy group update (lgu) algorithm for disk-based index structures of moving objects. lgu contains two key additional structures to group ``similar'' updates so that they can be performed together: a disk-based insertion buffer (i-buffer) for each internal node, and a memory-based deletion table (d-table) for the entire tree. different strategies of ``pushing down'' an overflow i-buffer to the next level are studied. comprehensive empirical studies over uniform and skewed datasets, as well as simulated street traffic data show that lgu achieves a significant improvement on update throughput while allowing a reasonable performance for queries.
using path information for query processing in object-oriented database systems. this paper argues that most queries in object-oriented databases require traversing from one object to another in the aggregation hierarchy. thus, the connections between objects through object identifiers are essential to the efficiency of query processing and should be represented separately from the database. we introduce the concept of path dictionary and describe how it supports queries of different types. we evaluate the storage overhead, query and update costs of the path dictionary. compared to the path index, the path dictionary has better overall query and update performance and lower storage overhead.
zbroker: a query routing broker for z39.50 databases. a query routing broker is a software agent that determines from a large set of accessing information sources the ones most relevant to a user's information need. as the number of information sources on the internet increases dramatically, future users will have to rely on query routing brokers to decide a small number of information sources to query without incurring too much query processing overheads. in this paper, we describe a query routing broker known as zbroker developed for bibliographic database servers that support the z39.50 protocol. zbroker samples the content of each bibliographic database by using training queries and their results, and summarizes the bibliographic database content into a knowledge base. we present the design and implementation of zbroker and describe its web-based user interface.
sliding-window filtering: an efficient algorithm for incremental mining. we explore in this paper an effective sliding-window filtering (abbreviatedly as swf) algorithm for incremental mining of association rules. in essence, by partitioning a transaction database into several partitions, algorithm swf employs a filtering threshold in each partition to deal with the candidate itemset generation. under swf, the cumulative information of mining previous partitions is selectively carried over toward the generation of candidate itemsets for the subsequent partitions. algorithm swf not only significantly reduces i/o and cpu cost by the concepts of cumulative filtering and scan reduction techniques but also effectively controls memory utilization by the technique of sliding-window partition. algorithm swf is particularly powerful for efficient incremental mining for an ongoing time-variant transaction database. by utilizing proper scan reduction techniques, only one scan of the incremented dataset is needed by algorithm swf. the i/o cost of swf is, in orders of magnitude, smaller than those required by prior methods, thus resolving the performance bottleneck. experimental studies are performed to evaluate performance of algorithm swf. it is noted that the improvement achieved by algorithm swf is even more prominent as the incremented portion of the dataset increases and also as the size of the database increases.
unsupervised question answering data acquisition from local corpora. data-driven approaches in question answering (qa) are increasingly common. since availability of training data for such approaches is very limited, we propose an unsupervised algorithm that generates high quality question-answer pairs from local corpora. the algorithm is ontology independent, requiring very small seed data as its starting point. two alternating views of the data make learning possible: 1) question types are viewed as relations between entities and 2) question types are described by their corresponding question-answer pairs. these two aspects of the data allow us to construct an unsupervised algorithm that acquires high precision question-answer pairs. we show the quality of the acquired data for different question types and perform a task-based evaluation. with each iteration, pairs acquired by the unsupervised algorithm are used as training data to a simple qa system. performance increases with the number of question-answer pairs acquired confirming the robustness of the unsupervised algorithm. we introduce the notion of <i>semantic drift</i> and show that it is a desirable quality in training data for question answering systems.
design and evaluation rules for building adaptive schema in an object-oriented data and knowledge base system. we develop a selection of design and evaluation rules for building an adaptive schema in an object-oriented data and knowledge base system. this set of style rules include not only those which we use to preserve validity and minimality of an object-oriented schema, but also those which help us to promote extensibility, reusability and adaptiveness of an object-oriented schema against future requirement changes. we encourage to use the set of style rules proposed as a means for validating quality of a schema, and for transforming an object-oriented schema into a better style regarding to adaptiveness and robustness, rather than as a user-oriented method solely for designing the schema.
passage retrieval based on language models. previous research has shown that passage-level evidence can bring added benefits to document retrieval when documents are long or span different subject areas. recent developments in language modeling approach to ir provided a new effective alternative to traditional retrieval models. these two streams of research motivate us to examine the use of passages in a language model framework. this paper reports on experiments using passages in a simple language model and a relevance model, and compares the results with document-based retrieval. results from the inquery search engine, which is not based on a language modeling approach, are also given for comparison. test data include two heterogeneous and one homogeneous document collections. our experiments show that passage retrieval is feasible in the language modeling context, and more importantly, it can provide more reliable performance than retrieval based on full documents.
net & cot: translating relational schemas to xml schemas using semantic constraints. two algorithms, called net and cot, to translate relational schemas to xml schemas using various semantic constraints are presented. the xml schema representation we use is a language-independent formalism named xschema, that is both precise and concise. a given xschema can be mapped to a schema in any of the existing xml schema language proposals. our proposed algorithms have the following characteristics: (1) net derives a nested structure from a flat relational model by repeatedly applying the nest operator on each table so that the resulting xml schema becomes hierarchical, and (2) cot considers not only the structure of relational schemas, but also semantic constraints such as inclusion dependencies during the translation. it takes as input a relational schema where multiple tables are interconnected through inclusion dependencies and converts it into a good xschema. to validate our proposals, we present experimental results using both real schemas from the uci repository and synthetic schemas from tpc-h.
batch data warehouse maintenance in dynamic environments. data warehouse view maintenance is an important issue due to the growing use of warehouse technology for information integration and data analysis. given the dynamic nature of modern distributed environments, both data updates and schema changes are likely to occur in different data sources. in applications that the real-time refreshment of data warehouse extent under source changes is not critical, the source updates are usually maintained in a batch fashion to reduce the maintenance overhead. however, most prior work can only deal with batch source data updates. in this paper, we provide a solution strategy that is capable of batching both source data updates and schema changes. we propose techniques to first preprocess the initial source updates to summarize delta changes for each source. we then design a view adaptation algorithm to adapt the warehouse view under these delta changes. we have implemented our solutions and incorporated into an existing data warehouse prototype system. the experimental studies demonstrate excellent performance achievable by our batch techniques.
intelligent knowledge discovery in peer-to-peer file sharing. emerging peer-to-peer computing provides new possibilities but also challenges for distributed applications. despite their significant potential, current peer-to-peer networks lack efficient knowledge discovery and management. this paper addresses this deficiency and proposes the intelligent file sharing framework, which provides an effective and flexible query for p2p file sharing. the ifs is based on powerful schema and flexible inference, as well as efficiently integrated and extensible retrieval algorithms. experimental results have provided evidence of the high performance and scalability of the intelligent file sharing (ifs) system in peer-to-peer environments.
a singer identification technique for content-based classification of mp3 music objects. as there is a growing amount of mp3 music data available on the internet today, the problems related to music classification and content-based music retrieval are getting more attention recently. in this paper, we propose an approach to automatically classify mp3 music objects according to their singers. first, the coefficients extracted from the output of the polyphase filters are used to compute the mp3 features for segmentation. based on these features, an mp3 music object can be decomposed into a sequence of notes (or phonemes). then for each mp3 phoneme in the training set, its mp3 feature is extracted and used to train an mp3 classifier which can identify the singer of an unknown mp3 music object. experiments are performed and analyzed to show the effectiveness of the proposed method.
efficient incremental view maintenance in data warehouses. in the data warehouse environment, the concept of a materialized view is nowadays common and important in an objective of efficiently supporting olap query processing. materialized views are generally derived from select-project-join of several base relations. these materialized views need to be updated when the base relations change. since the propagation of updates to the views may impose a significant overhead, it is very important to update the warehouse views efficiently. though various view maintenance strategies have been discussed so far, they typically require too much access to base relations, resulting in the performance degradation.in this paper we propose an efficient incremental view maintenance strategy called delta propagation that can minimize the total size of base relations accessed by analyzing the properties of base relations. we first define the delta expression and a delta propagation tree which are core concepts of the strategy. then, a dynamic programming algorithm that can find the optimal delta expression are proposed. we also present various experimental results that show the usefulness and efficiency of the strategy.
computer image retrieval by features: selecting the best facial features for suspect identification systems. correct suspect identification of known offenders by witnesses deteriorates rapidly as more are examined in mugshot albums. feature approaches, where mugshots are displayed in order of similarity to witnesses' descriptions, increase identification success by reducing this number. system performance depends on selection of system features. four methods of selecting features are evaluated empirically: theory, random, hill-climbing algorithm, and hybrid. the theory asserts success depends on five properties of system features: informativeness, orthogonality, sufficiency, consistency, and observability. comparing system performance on the best 10 features selected (from a pool of 90) by each method supports our contention. in four experimental tests of a system with 1000 official mugshots, over 90% of witness searches resulted in photos of target suspects retrieved in the first ten mugshots displayed for examination (using all 90 system features). on average, suspects were retrieved in the first 54, 7, 22, and 70 mugshots when using only the best 10 model features. hybrid and hill-climbing algorithms did not improve on this performance, and performance of randomly selected sets of 10 features was poor.
xclust: clustering xml schemas for effective integration. it is increasingly important to develop scalable integration techniques for the growing number of xml data sources. a practical starting point for the integration of large numbers of document type definitions (dtds) of xml sources would be to first find clusters of dtds that are similar in structure and semantics. reconciling similar dtds within such a cluster will be an easier task than reconciling dtds that are different in structure and semantics as the latter would involve more restructuring. we introduce xclust, a novel integration strategy that involves the clustering of dtds. a matching algorithm based on the semantics, immediate descendents and leaf-context similarity of dtd elements is developed. our experiments to integrate real world dtds demonstrate the effectiveness of the xclust approach.
algebraic equivalences among nested relational expressions. algebraic optimization is both theoretically and practically important for query processing in (nested) relational databases. in this paper, we consider this issue and investigate some algebraic properties concerning the nested relational operators. we also outline a heuristic optimization algorithm for nested relational expressions by adopting algebraic transformation rules developed in this paper and previous related work.
the egg/yolk reliability hierarchy : semantic data integration using sorts with prototypes. integration of disparate heterogeneous databases requires translation of types. because a type in one system often has no exact counterpart in the others, fully reliable integration requires deep understanding of the subject domain, with conceptual analysis of type meanings. so far, reliable translation has had to be done by hand. in practice, few types are so crucial as to require full reliability. the egg/yolk hierarchy ranks types by the tolerable rashness in translation, based on prototypes in each type. each defined class (egg) has a subclass of typical members (yolk) defined. we exploit cui, cohn and randell's qualitative spatial simulation program to create the hierarchy of all possible relations between source and target egg/yolk types, ranked by reliability. our eventual ranking is based on a poset combining four different preference criteria.
restructuring batch view maintenance efficiently. materialized views defined over distributed data sources are a well recognized technology for modern applications. state-of the-art incremental view maintenance requires o(<i>n</i><sup>2</sup>) or more maintenance queries to remote data sources with <i>n</i> being the number of data sources in the view definition. in this poster, we illustrate basic ideas of novel view maintenance strategies that dramatically reduce the number of maintenance queries. such reduction brings the tradeoff between the number of maintenance queries and the complexity of each query. these algorithms have been implemented in a working prototype system. experimental studies illustrate major performance improvement in terms of total processing time compared with existing batch algorithms.
content-based retrieval of mp3 music objects. in recent years, the searching and indexing techniques for multimedia data are getting more attention in the area of multimedia databases. as many research works were done on the content-based retrieval of image and video data, less attention was received to the content-based retrieval of audio data. in this paper, we propose an approach to retrieve mp3 music objects based on their content. in our approach, the coefficients extracting from the output of the polyphase filters are used to compute the mp3 features for indexing the mp3 objects. we also propose an mp3 similarity measuring function to provide users the ability to approximately retrieve the desired mp3 objects. experiments are performed and analyzed to show the efficiency and the effectiveness of the proposed method.
detecting changes on unordered xml documents using relational databases: a schema-conscious approach. several relational approaches have been proposed to detect the changes to xml documents by using relational databases. these approaches store the xml documents in the relational database and issue sql queries (whenever appropriate) to detect the changes. all of these relational-based approaches use the schema-oblivious xml storage strategy for detecting the changes. however, there is growing evidence that schema-conscious storage approaches perform significantly better than schema-oblivious approaches as far as xml query processing is concerned. in this paper, we study a relational-based unordered xml change detection technique (called h<small>elios</small>) that uses a schema-conscious approach (shared-inlining) as the underlying storage strategy. h<small>elios</small> is up to 52 times faster than x-diff [7] for large datasets (more than 1000 nodes). it is also up to 6.7 times faster than x<small>andy</small> [4]. the result quality of deltas detected by h<small>elios</small> is comparable to the result quality of deltas detected by xandy.
maintaining views in object-relational databases. view materialization is an important way of improving the performance of query processing. when an update occurs to the source data from which a materialized view is derived, the materialized view has to be updated so that it is consistent with the source data. this update process is called view maintenance . the incremental method of view maintenance, which computes the new view using the old view and the update to the source data, is widely preferred to full view recomputation when the update is small in size. in this paper we investigate how to incrementally maintain views in object-relational (or) databases. the investigation focuses on maintaining views defined in or-sql, a language containing the features of object referencing, inheritance, collection, and aggregate functions including user-defined set aggregate functions. we propose an architecture and algorithms for incremental or view maintenance. we implement all algorithms and analyze the performance of them in comparison with full view recomputation. the analysis shows that the algorithms significantly reduce the cost of updating a view when the size of an update to the source data is relatively small.
fast on-line index construction by geometric partitioning. inverted index structures are the mainstay of modern text retrieval systems. they can be constructed quickly using off-line merge-based methods, and provide efficient support for a variety of querying modes. in this paper we examine the task of on-line index construction -- that is, how to build an inverted index when the underlying data must be continuously queryable, and the documents must be indexed and available for search as soon they are inserted. when straightforward approaches are used, document insertions become increasingly expensive as the size of the database grows. this paper describes a mechanism based on controlled partitioning that can be adapted to suit different balances of insertion and querying operations, and is faster and scales better than previous methods. using experiments on 100gb of web data we demonstrate the efficiency of our methods in practice, showing that they dramatically reduce the cost of on-line index construction.
extracting a website's content structure from its link structure. hierarchical models are commonly used to organize a website's content. a website's content structure can be represented by a topic hierarchy, a directed tree rooted at a website's homepage in which the vertices and edges correspond to web pages and hyperlinks. in this work, we propose an algorithm for extracting a website's topic hierarchy from its link structure. the proposed algorithm consists of a construction stage and a refining stage, in which we analyze the semantic relationships between web pages based on link structure, web page content and directory structure. we've done extensive experiments using different websites and obtained very promising results.
evaluating document clustering for interactive information retrieval. we consider the problem of organizing and browsing the top ranked portion of the documents returned by an information retrieval system. we study the effectiveness of a document organization in helping a user to locate the relevant material among the retrieved documents as quickly as possible. in this context we examine a set of clustering algorithms and experimentally show that a clustering of the retrieved documents can be significantly more effective than traditional ranked list approach. we also show that the clustering approach can be as effective as the interactive relevance feedback based on query expansion while retaining an important advantage -- it provides the user with a valuable sense of control over the feedback process.
rule-based data quality. in the business intelligence/data warehouse user community, there is a growing confusion as to the difference between data cleansing and data quality. while many data cleansing products can help in applying data edits to name and address data, or help in transforming data during an etl process, there is usually no persistence in this cleansing. this paper describes how we have implemented a business rules approach to build a data validation engine, called guardianiq, that transforms declarative data quality rules into code that objectively measures and reports levels of data quality based on user expectations.
text document clustering based on frequent word sequences. in this paper, we propose a new text clustering algorithm, named clustering based on frequent word sequences (cfws). a word sequence is frequent if it occurs in more than certain percentage of the documents in the text database. in the past, the vector space model was commonly used for information retrieval, but it treats documents as bags of words, ignoring the sequential pattern of word occurrences in the documents. however, the meaning of natural languages strongly depends on the word sequences, and the frequent word sequences can provide compact and valuable information about the text database. bisecting k-means and fihc algorithms are evaluated on the performance of text clustering, and are compared with the proposed cfws algorithm. it has been shown that cfws has much better performance.
boosting to correct inductive bias in text classification. this paper studies the effects of boosting in the context of different classification methods for text categorization, including decision trees, naive bayes, support vector machines (svms) and a rocchio-style classifier. we identify the inductive biases of each classifier and explore how boosting, as an error-driven resampling mechanism, reacts to those biases. our experiments on the reuters-21578 benchmark show that boosting is not effective in improving the performance of the base classifiers on common categories. however, the effect of boosting for rare categories varies across classifiers: for svms and decision trees, we achieved a 13-17% performance improvement in macro-averaged f1 measure, but did not obtain substantial improvement for the other two classifiers. this interesting finding of boosting on rare categories has not been reported before.
novelty detection based on sentence level patterns. the detection of new information in a document stream is an important component of many potential applications. in this paper, a new novelty detection approach based on the identification of sentence level patterns is proposed. given a user's information need, some patterns in sentences such as combinations of query words, named entities and phrases, may contain more important and relevant information than single words. therefore, the proposed novelty detection approach focuses on the identification of previously unseen query-related patterns in sentences. specifically, a query is preprocessed and represented with patterns that include both query words and required answer types. these patterns are used to retrieve sentences, which are then determined to be novel if it is likely that a new answer is present. an analysis of patterns in sentences was performed with data from the trec 2002 novelty track and experiments on novelty detection were carried out on data from the trec 2003 and 2004 novelty tracks. the experimental results show that the proposed pattern-based approach significantly outperforms all three baselines in terms of precision at top ranks.
personalized web search by mapping user queries to categories. current web search engines are built to serve all users, independent of the needs of any individual user. personalization of web search is to carry out retrieval for each user incorporating his/her interests. we propose a novel technique to map a user query to a set of categories, which represent the user's search intention. this set of categories can serve as a context to disambiguate the words in the user's query. a user profile and a general profile are learned from the user's search history and a category hierarchy respectively. these two profiles are combined to map a user query into a set of categories. several learning and combining algorithms are evaluated and found to be effective. among the algorithms to learn a user profile, we choose the rocchio-based method for its simplicity, efficiency and its ability to be adaptive. experimental results indicate that our technique to personalize web search is both effective and efficient.
a new approach to intranet search based on information extraction. this paper is concerned with 'intranet search'. by intranet search, we mean searching for information on an intranet within an organization. we have found that search needs on an intranet can be categorized into types, through an analysis of survey results and an analysis of search log data. the types include searching for definitions, persons, experts, and homepages. traditional information retrieval only focuses on search of relevant documents, but not on search of special types of information. we propose a new approach to intranet search in which we search for information in each of the special types, in addition to the traditional relevance search. information extraction technologies can play key roles in such kind of 'search by type' approach, because we must first extract from the documents the necessary information in each type. we have developed an intranet search system called 'information desk'. in the system, we try to address the most important types of search first - finding term definitions, homepages of groups or topics, employees' personal information and experts on topics. for each type of search, we use information extraction technologies to extract, fuse, and summarize information in advance. the system is in operation on the intranet of microsoft and receives accesses from about 500 employees per month. feedbacks from users and system logs show that users consider the approach useful and the system can really help people to find information. this paper describes the architecture, features, component technologies, and evaluation results of the system.
discovering the representative of a search engine. given a large number of search engines on the internet, it is difficult for a person to determine which search engines could serve his/her information needs. a common solution is to construct a metasearch engine on top of the search engines. upon receiving a user query, the metasearch engine sends it to those underlying search engines which are likely to return the desired documents for the query. the selection algorithm used by a metasearch engine to determine whether a search engine should be sent the query typically makes the decision based on the search-engine representative, which contains characteristic information about the database of a search engine. however, an underlying search engine may not be willing to provide the needed information to the metasearch engine. this paper shows that the needed information can be estimated from an uncooperative search engine with good accuracy. two pieces of information which permit accurate search engine selection are the number of documents indexed by the search engine and the maximum weight of each term. in this paper, we present techniques for the estimation of these two pieces of information.
efficient prediction of web accesses on a proxy server. web access prediction is an active research topic with many applications. various approaches have been proposed for web access prediction in the domain of individual web servers but they have to be tailored to the domain of proxy servers to satisfy its special requirements in prediction efficiency and scalability. in this paper, the design and implementation of proxy-based prediction service (pps) is presented. for prediction efficiency, pps applies a new prediction scheme which employs a two-layer navigation model to capture both inter-site and intra-site access patterns, incorporated with a bottom-up prediction mechanism that exploits reference locality in proxy logs. for system scalability, pps manages the navigation model in disk database and adopts a predictive cache replacement strategy for data shipping between the model database and cache. we show the superiority of our prediction scheme over existing approaches and validate our model management and caching strategies, with a detailed performance study using real-world data.
pruning long documents for distributed information retrieval. query-based sampling is a method of discovering the contents of a text database by submitting queries to a search engine and observing the documents returned. in prior research sampled documents were used to build resource descriptions for automatic database selection, and to build a centralized sample database for query expansion and result merging. an unstated assumption was that the associated storage costs were acceptable.when sampled documents are long, storage costs can be large. this paper investigates methods of pruning long documents to reduce storage costs. the experimental results demonstrate that building resource descriptions and centralized sample databases from the pruned contents of sampled documents can reduce storage costs by 54-93% while causing only minor losses in the accuracy of distributed information retrieval.
mining community structure of named entities from free text. although community discovery has been studied extensively in the web environment, limited research has been done in the case of free text. co-occurrence of words and entities in sentences and documents usually implies connections among them. in this paper, we investigate the co-occurrences of named entities in text, and mine communities among these entities. we show that identifying communities from free text can be transformed into a graph clustering problem. a hierarchical clustering algorithm is then proposed. our experiment shows that the algorithm is effective to discover named entity communities from text documents.
word sense disambiguation in queries. this paper presents a new approach to determine the senses of words in queries by using wordnet. in our approach, noun phrases in a query are determined first. for each word in the query, information associated with it, including its synonyms, hyponyms, hypernyms, definitions of its synonyms and hyponyms, and its domains, can be used for word sense disambiguation. by comparing these pieces of information associated with the words which form a phrase, it may be possible to assign senses to these words. if the above disambiguation fails, then other query words, if exist, are used, by going through exactly the same process. if the sense of a query word cannot be determined in this manner, then a guess of the sense of the word is made, if the guess has at least 50% chance of being correct. if no sense of the word has 50% or higher chance of being used, then we apply a web search to assist in the word sense disambiguation process. experimental results show that our approach has 100% applicability and 90% accuracy on the most recent robust track of trec collection of 250 queries. we combine this disambiguation algorithm to our retrieval system to examine the effect of word sense disambiguation in text retrieval. experimental results show that the disambiguation algorithm together with other components of our retrieval system yield a result which is 13.7% above that produced by the same system but without the disambiguation, and 9.2% above that produced by using lesk's algorithm. our retrieval effectiveness is 7% better than the best reported result in the literature.
qed: a novel quaternary encoding to completely avoid re-labeling in xml updates. the method of assigning labels to the nodes of the xml tree is called a labeling scheme. based on the labels only, both ordered and un-ordered queries can be processed without accessing the original xml file. one more important point for the labeling scheme is the label update cost in inserting or deleting a node into or from the xml tree. all the current labeling schemes have high update cost, therefore in this paper we propose a novel quaternary encoding approach for the labeling schemes. based on this encoding approach, we need not re-label any existing nodes when the update is performed. extensive experimental results on the xml datasets illustrate that our qed works much better than the existing labeling schemes on the label updates when considering either the number of nodes or the time for re-labeling.
on reducing redundancy and improving efficiency of xml labeling schemes. the basic relationships to be determined in xml query processing are ancestor-descendant (a-d), parent-child (p-c), sibling and ordering relationships. the containment labeling scheme can determine the a-d, p-c and ordering relationships fast, but it is very expensive in determining the sibling relationship. the prefix labeling scheme can determine all the four basic relationships fast if the xml tree is shallow. however, if the xml tree is deep, the prefix scheme is inefficient since the prefix is long. furthermore, the prefix label is repeated by all the siblings (only the self labels of these siblings are different). thus in this paper, we propose the p-containment and p-prefix schemes which can determine all the four basic relationships faster no matter what the xml structure is; meanwhile p-prefix can reduce the redundancies in the prefix labeling scheme.
content-based retrieval in hybrid peer-to-peer networks. hybrid peer-to-peer architectures use special nodes to provide directory services for regions of the network ("regional directory services"). hybrid peer-to-peer architectures are a potentially powerful model for developing large-scale networks of complex digital libraries, but peer-to-peer networks have so far tended to use very simple methods of resource selection and document retrieval. in this paper, we study the application of content-based resource selection and document retrieval to hybrid peer-to-peer networks. the directory nodes that provide regional directory services construct and use the content models of neighboring nodes to determine how to route query messages through the network. the leaf nodes that provide information use content-based retrieval to decide which documents to retrieve for queries. the experimental results demonstrate that using content-based retrieval in hybrid peer-to-peer networks is both more accurate and more efficient for some digital library environments than more common alternatives such as gnutella 0.6.
relational computation for mining association rules from xml data. we develop a fixpoint operator for computing large item sets and demonstrate three query paradigm solutions for association rule mining that use the idea of least fixpoint computation and indicates some optimisation issues. the results of our research provide theoretical foundation for relational computation of association rules and its application on xml mining.
on combining multiple clusterings. many problems can be reduced to the problem of combining multiple clusterings. in this paper, we first summarize different application scenarios of combining multiple clusterings and provide a new perspective of viewing the problem as a categorical clustering problem. we then show the connections between various consensus and clustering criteria and discuss the complexity results of the problem. finally we propose a new method to determine the final clustering. experiments on kinship terms and clustering popular music from heterogeneous feature sets show the effectiveness of combining multiple clusterings.
efficient processing of xml twig patterns with parent child edges: a look-ahead approach. with the growing importance of semi-structure data in information exchange, much research has been done to provide an effective mechanism to match a twig query in an xml database. a number of algorithms have been proposed recently to process a twig query holistically. those algorithms are quite efficient for quires with only ancestor-descendant edges. but for queries with mixed ancestor-descendant and parent-child edges, the previous approaches still may produce large intermediate results, even when the input and output size are more manageable. to overcome this limitation, in this paper, we propose a novel holistic twig join algorithm, namely <i>twigstacklist</i>. our main technique is to look-ahead read some elements in input data steams and cache limited number of them to <i>lists</i> in the main memory. the number of elements in any list is bounded by the length of the longest path in the xml document. we show that <i>twigstacklist</i> is i/o optimal for queries with only ancestor-descendant relationships below branching nodes. further, even when queries contain parent-child relationship below branching nodes, the set of intermediate results in <i>twigstacklist</i> is guaranteed to be a subset of that in previous algorithms. we complement our experimental results on a range of real and synthetic data to show the significant superiority of <i>twigstacklist</i> over previous algorithms for queries with <i>parent</i>-<i>child</i> relationships.
learning similarity measures in non-orthogonal space. many machine learning and data mining algorithms crucially rely on the similarity metrics. the cosine similarity, which calculates the inner product of two normalized feature vectors, is one of the most commonly used similarity measures. however, in many practical tasks such as text categorization and document clustering, the cosine similarity is calculated under the assumption that the input space is an orthogonal space which usually could not be satisfied due to <i>synonymy</i> and <i>polysemy</i>. various algorithms such as latent semantic indexing (lsi) were used to solve this problem by projecting the original data into an orthogonal space. however lsi also suffered from the high computational cost and data sparseness. these shortcomings led to increases in computation time and storage requirements for large scale realistic data. in this paper, we propose a novel and effective similarity metric in the non-orthogonal input space. the basic idea of our proposed metric is that the similarity of features should affect the similarity of objects, and vice versa. a novel iterative algorithm for computing non-orthogonal space similarity measures is then proposed. experimental results on a synthetic data set, a real msn search click-thru logs, and 20ng dataset show that our algorithm outperforms the traditional cosine similarity and is superior to lsi.
using micro information units for internet search. internet search is one of the most important applications of the web. a search engine takes the user's keywords to retrieve and to rank those pages that contain the keywords. one shortcoming of existing search techniques is that they do not give due consideration to the micro-structures of a web page. a web page is often populated with a number of small information units, which we call micro information units (miu). each unit focuses on a specific topic and occupies a specific area of the page. during the search, if all the keywords in the user query occur in a single miu of a page, the top ranking results returned by a search engine are generally relevant and useful. however, if the query words scatter at different mius in a page, the pages returned can be quite irrelevant (which causes low precision). the reason for this is that although a page has information on individual mius, it may not have information on their intersections. in this paper, we propose a technique to solve this problem. at the off-line pre-processing stage, we segment each page to identify the mius in the page, and index the keywords of the page according to the mius in which they occur. in searching, our retrieval and ranking algorithm utilizes this additional information to return those most relevant pages. experimental results show that this method is able to significantly improve the search precision.
text classification using esc-based stochastic decision lists. we propose a new method of text classification using stochastic decision lists. a stochastic decision list is an ordered sequence of if-then-else rules, and our method can be viewed as a rule-based method for text classification having advantages of readability and refinability of acquired knowledge. our method is unique in that decision lists are automatically constructed on the basis of the principle of minimizing extended stochastic complexity (esc), and with it we are able to construct decision lists that have fewer errors in classification. the accuracy of classification achieved with our method appears better than or comparable to those of existing rule-based methods. we have empirically demonstrated that rule-based methods like ours result in high classification accuracy when the categories to which texts are to be assigned are relatively specific ones and when the texts tend to be short. we have also empirically verified the advantages of rule-based methods over non-rule-based ones.
applying cosine series to join size estimation. this paper provides a general overview of two innovative applications of cosine series in xml joins and data stream joins.
analysis of pre-computed partition top method for range top-k queries in olap data cubes. in decision support systems, having knowledge on the top k values is more informative and crucial than the maximum value. unfortunately, the naive method involves high computational cost and the existing methods for range-max query are inefficient if applied directly. in this paper, we propose a pre-computed partition top method (ppt) to partition the data cube and pre-store a number of top values for improving query performance. the main focus of this study is to find the optimum values for two parameters, i.e., the partition factor (b) and the number of pre-stored values (r), through analytical approach. a cost function based on poisson distribution is used for the analysis. the analytical results obtained are verified against simulation results. it is shown that the ppt method outperforms other alternative methods significantly when proper b and r are used.
efficient multi-way text categorization via generalized discriminant analysis. text categorization is an important research area and has been receiving much attention due to the growth of the on-line information and of internet. automated text categorization is generally cast as a multi-class classification problem. much of previous work focused on binary document classification problems. support vector machines (svms) excel in binary classification, but the elegant theory behind large-margin hyperplane cannot be easily extended to multi-class text classification. in addition, the training time and scaling are also important concerns. on the other hand, other techniques naturally extensible to handle multi-class classification are generally not as accurate as svm. this paper presents a simple and efficient solution to multi-class text categorization. classification problems are first formulated as optimization via discriminant analysis. text categorization is then cast as the problem of finding coordinate transformations that reflects the inherent similarity from the data. while most of the previous approaches decompose a multi-class classification problem into multiple independent binary classification tasks, the proposed approach enables direct multi-class classification. by using generalized singular value decomposition (gsvd), a coordinate transformation that reflects the inherent class structure indicated by the generalized singular values is identified. extensive experiments demonstrate the efficiency and effectiveness of the proposed approach.
situation-aware risk management in autonomous agents. we present a novel approach to enable decision-making in a highly distributed multiagent environment where individual agents need to act in an autonomous fashion. our architecture framework integrates risk management, knowledge management, and agent deliberation to enable sophisticated, autonomous decision-making. instead of a centralized knowledge repository, our approach supports a highly distributed knowledge base in which each agent manages a fraction of the knowledge needed by the entire system.
localized routing trees for query processing in sensor networks. in this paper, we propose a novel energy-efficient approach, a localized routing tree (lrt) coupled with a route redirection (rr) strategy, to support various types of queries. lrts take care of the sensors near the sink and reduce the energy consumption of these sensors, and rr reduces the energy cost of data receptions. compared to the existing approaches, simulation studies show that lrt together with rr has significant improvement on the query capacity.
automatically extracting structure and data from business reports. a considerable amount of clean semistructured data is internally available to companies in the form of business reports. however, business reports are untapped for data mining, data warehousing, and querying because they are not in relational form. business reports have a regular structure that can be reconstructed. we present algorithms that automatically infer the regular structure underlying business reports and automatically generate wrappers to extract relational data.
the link prediction problem for social networks. given a snapshot of a social network, can we infer which new interactions among its members are likely to occur in the near future? we formalize this question as the link prediction problem, and develop approaches to link prediction based on measures the "proximity" of nodes in a network. experiments on large co-authorship networks suggest that information about future interactions can be extracted from network topology alone, and that fairly subtle measures for detecting node proximity can outperform more direct measures.
typed functional query languages with equational specifications. we present a framework for functionally modeling query languages and data models. data and queries are uniformly represented by first-order functions, and query-language constructs by polymorphic higher-order functions. the functions are typed by a database-oriented type system that supports polymorphism and nesting of types, thus one can perform static type-checking and type-inferencing of query-expressions. the query language can be freely extended by introducing new querying constructs as polymorphic higher-order functions.while type information gives the input-output description of the functions, the semantic information is captured by equational specifications. knowledge about the functions is represented as equalities of functional expressions in the form of equations. by equational axiomatization of the query language, database problems of query equivalence and answering-query with views can be posed as equational word-problems and equational matching.
a horizontal fragmentation algorithm for the fact relation in a distributed data warehouse. data warehousing is one of the major research topics of appliedside database investigators. most of the work to date has focused on building large centralized systems that are integrated repositories founded on pre-existing systems upon which all corporate-wide data are based. unfortunately, this approach is very expensive and tends to ignore the advantages realized during the past decade in the area of distribution and support for data localization in a geographically dispersed corporate structure. this research investigates building distributed data warehouses with particular emphasis placed on distribution design for the data warehouse environment. the article provides an architectural model for a distributed data warehouse, the formal definition of the relational data model for data warehouse and a methodology for distributed data warehouse design along with a &ldquo;horizontal&rdquo; fragmentation algorithm for the fact relation.
qfilter: fine-grained run-time xml access control via nfa-based query rewriting. at present, most of the state-of-the-art solutions for xml access controls are either (1) document-level access control techniques that are too limited to support fine-grained security enforcement; (2) view-based approaches that are often expensive to create and maintain; or (3) impractical proposals that require substantial security-related support from underlying xml databases. in this paper, we take a different approach that assumes no security support from underlying xml databases and examine three alternative fine-grained xml access control solutions, namely <i>primitive, pre-processing</i> and <i>post-processing</i> approaches. in particular, we advocate a pre-processing method called <i>qfilter</i> that uses non-deterministic finite automata (nfa) to rewrite user's query such that any parts violating access control rules are pruned. we show the construction and execution of a qfilter and demonstrate its superiority to other competing methods.
image similarity search with compact data structures. the recent theoretical advances on compact data structures (also called "sketches") have raised the question of whether they can effectively be applied to content-based image retrieval systems. the main challenge is to derive an algorithm that achieves high-quality similarity searches while using compact metadata. this paper proposes a new similarity search method consisting of three parts. the first is a new region feature representation with weighted $=<i></i><inf>1</inf> distance function, and emd* match, an improved emd match, to compute image similarity. the second is a thresholding and transformation algorithm to convert feature vectors into very compact data structures. the third is an emd embedding based filtering method to speed up the query process. we have implemented a prototype system with the proposed method and performed experiments with a 10,000 image database. our results show that the proposed method can achieve more effective similarity searches than previous approaches with metadata 3 to 72 times more compact than previous systems. the experiments also show that our emd embedding based filtering technique can speed up the query process by a factor of 5 or more with little loss in query effectiveness.
learning probabilistic datalog rules for information classification and transformation. probabilistic datalog is a combination of classical datalog (i.e., function-free horn clause predicate logic) with probability theory. therefore, probabilistic weights may be attached to both facts and rules. but it is often impossible to assign exact rule weights or even to construct the rules themselves. instead of specifying them manually, learning algorithms can be used to learn both rules and weights. in practice, these algorithms are very slow because they need a large example set and have to test a high number of rules. we apply a number of extensions to these algorithms in order to improve efficiency. several applications demonstrate the power of learning probabilistic datalog rules, showing that learning rules is suitable for low dimensional problems (e.g., schema mapping) but inappropriate for higher dimensions like e.g. in text classification.
a multi-system analysis of document and term selection for blind feedback. experiments were conducted to explore the impact of combining various components of eight leading information retrieval systems. each system demonstrated improved effectiveness with the use of <i>blind feedback</i>, in which the results of a preliminary retrieval step were used to augment the efficacy of a secondary retrieval step. the hybrid combination of primary and secondary retrieval steps from different systems in a number of cases yielded better effectiveness than either of the constituent systems alone. this positive combining effect was observed when entire documents were passed between the two retrieval steps, but not when only the expansion terms were passed. several combinations of primary and secondary retrieval steps were fused using the combmnz algorithm; all yielded significant effectiveness improvement over the individual systems, with the best yielding a an improvement of 13% (<i>p</i> = 10<sup>-6</sup>) over the best individual system and an improvement of 4% (<i>p</i> = 10<sup>-5</sup>) over a simple fusion of the eight systems.
information retrieval and machine learning for probabilistic schema matching. schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain, or for distributed ir in federated digital libraries. this paper introduces a probabilistic framework, called splmap, for automatically learning schema mapping rules, based on given instances of both schemas. different techniques, mostly from the ir and machine learning fields, are combined for finding suitable mapping candidates. our approach gives a probabilistic interpretation of the prediction weights of the candidates, selects the rule set with highest matching probability, and outputs probabilistic rules which are capable to deal with the intrinsic uncertainty of the mapping process. our approach with different variants has been evaluated on several test sets.
extracting unstructured data from template generated web documents. we propose a novel approach that identifies web page templates and extracts the unstructured data. extracting only the body of the page and eliminating the template increases the retrieval precision for the queries that generate irrelevant results. we believe that by reducing the number of irrelevant results; the users are encouraged to go back to a given site to search. our experimental results on several different web sites and on the whole cnnfn collection demonstrate the feasibility of our approach.
rstar: an rdf storage and query system for enterprise resource management. modern corporations operate in an extremely complex environment and strongly depend on all kinds of information resources across the enterprise. unfortunately, with the growth of an enterprise, its information resources are not only heterogeneous but also distributed in physically different systems and databases. how to effectively exploit information across the enterprise is becoming a critical but hard problem. in recent years, metadata which is the detailed description of the data is used to efficiently exploit information resources in the web. the world wide web consortium (w3c) recommends the resource description framework (rdf) as a standard for the definition and use of metadata descriptions of resources in the web. in this paper, we present an rdf storage and query system called rstar for enterprise resource management. rstar uses a relational database as the persistent data store and defines rstar query language (rsql) for resource retrieval. currently, most of existing rdf storage and query systems are evaluated on small data sets and no detailed performance analysis is given for such systems. therefore, we conduct extensive experiments on a large scale data set to investigate the performance problem in rdf storage. such analysis will be helpful for designing rdf storage and query systems as well as for understanding not well-solved issues in rdf based enterprise resource management. in addition, experiences and lessons learned in our implementation are presented for further research and development.
a framework for refining similarity queries using learning techniques. in numerous applications that deal with similarity search, a user may not have an exact idea of his information need and/or may not be able to construct a query that exactly captures his notion of similarity. a promising approach to mitigate this problem is to enable the user to submit a rough approximation of the desired query and use the feedback on the relevance of the retrieved objects to refine the query. in this paper, we explore such a refinement strategy for a general class of sql similarity queries. our approach casts the refinement problem as that of learning concepts using examples. this is achieved by viewing the tuples on which a user provides feedback as a labeled training set for a learner. under this setup, sql query refinement consists of two learning tasks, namely learning the structure of the sql query and learning the relative importance of the query components. the paper develops appropriate machine learning approaches suitable for these two learning tasks. the primary contribution of the paper is a general refinement framework that decides when each learner is invoked in order to quickly learn the user query. experimental analyses over many real life datasets and queries show that our strategy outperforms the existing approaches significantly in terms of retrieval accuracy and query simplicity.
ontologies for semantically interoperable systems. in this paper, we discuss the use of ontologies for semantic interoperability and integration. we argue that information technology has evolved into a world of largely loosely coupled systems and as such, needs increasingly more explicit, machine-interpretable semantics. ontologies in the form of logical domain theories and their knowledge bases offer the richest representations of machine-interpretable semantics for systems and databases in the loosely coupled world, thus ensuring greater semantic interoperability and integration. finally, we discuss how ontologies support semantic interoperability in the real, commercial and governmental world.
adding numbers to text classification. many real-world problems involve a combination of both text- and numerical-valued features. for example, in email classification, it is possible to use instance representations that consider not only the text of each message, but also numerical-valued features such as the length of the message or the time of day at which it was sent. text-classification methods have thus far not easily incorporated numerical features. in earlier work we described an approach for converting numerical features into bags of tokens so that text classification methods can be applied to numerical classification problems, and showed that the resulting learning methods are competitive with traditional numerical classification methods. in this paper we use this as a way to learn on problems that involve a combination of text and numbers. we show that the results outperform competing methods. further, we show that selecting a best classification method using text-only features and then adding numerical features to the problem (as might happen if numerical features are only later added to a pre existing text-classification problem) gives performance that rivals a more time-consuming approach of evaluating all classification methods using the full set of both text and numerical features.
xml parsing: a threat to database performance. xml parsing is generally known to have poor performance characteristics relative to transactional database processing. yet, its potentially fatal impact on overall database performance is being underestimated. we report real-word database applications where xml parsing performance is a key obstacle to a successful xml deployment. there is a considerable share of xml database applications which are prone to fail at an early and simple road block: xml parsing. we analyze xml parsing performance and quantify the extra overhead of dtd and schema validation. comparison with relational database performance shows that the desired response times and transaction rates over xml data can not be achieved without major improvements in xml parsing technology. thus, we identify research topics which are most promising for xml parser performance in database systems.
dynamic extraction topic descriptors and discriminators: towards automatic context-based topic search. effective knowledge management may require going beyond initial knowledge capture, to support decisions about how to extend previously-captured knowledge. electronic <i>concept maps,</i> interlinked with other concept maps and multimedia resources, can provide rich <i>knowledge models</i> for human knowledge capture and sharing. this paper presents research on methods for supporting experts as they extend these knowledge models, by searching the web for new context-relevant topics as candidates for inclusion. this topic search problem presents two challenges: first, how to formulate queries to seek topics that reflect the context of the current knowledge model, and, second, how to identify candidate topics with the right balance of novelty and relevance. more generally, this problem raises the broad question of the interaction of topic information from the local analysis space (a collected set of documents) and the global search space (the web). the paper develops a framework for understanding this interaction, and proposes and evaluates techniques for addressing the query formation and topic identification questions by dynamically extracting topic descriptors and discriminators from a knowledge model, to characterize information needs for retrieval and filtering of relevant material. using these techniques, we have developed a support tool that starts from a knowledge model under construction and automatically produces a set of suggestions for topics to include, proactively supporting users as they extend knowledge models.
the effectiveness of query expansion for distributed information retrieval. query expansion has been shown effective for both single database retrieval and for distributed information retrieval where complete collection information is available. one might expect that query expansion would then work for distributed information retrieval when complete collection information is not available. however, this does not appear to be the case. when using local context analysis for query expansion in distributed retrieval with partial information, the most significant reason query expansion does not work is that merging scores of documents retrieved by expanded queries is very difficult. however, we have found that using sampled information for query expansion can give boosts in a single database environment, and that when more information is available, query expansion can work in distributed environments. we also show that most of the benefit of query expansion in distributed retrieval comes from finding good documents, and not from selecting good databases.
sampling from databases using b+-trees. sampling techniques are becoming increasingly important for very large databases. however, the problem of obtaining a random sample from index structures has not received much attention. in this paper, we examine sampling techniques for b^+-tree. as the fanout of each node varies, a random walk through the index structure does not produce a good representative sample of the data set. we propose a new technique, called b^+-tree based weighted random sampling (btwrs), that alters the inclusion probabilities of records accordingly to allow more records from leaves, along the paths with higher fanouts, to be extracted. we extensively evaluated our method, and the results show that there is an improvement in btwrs over the existing schemes in terms of the quality of the samples obtained and the efficiency of the sampling process. the proposed method can be readily adopted in existing commercial systems.
foci: flexible organizer for competitive intelligence. this paper describes how an integrated web-based application, code-named foci (flexible organizer for competitive intelligence), can help the knowledge worker in the gathering, organizing, tracking, and dissemination of competitive intelligence or knowledge bases on the web. it shows how text mining techniques including a novel user-configurable clustering, trend analysis and visualization techniques can be used synergistically to address the problem of managing information gathered from the web. foci allows a user to define and personalize the organization of the information clusters according to their needs and preferences into portfolios. predefined sections for organizing information in specific domains is also supported. the personalized portfolios created can be saved and subsequently tracked and shared with other users. in addition, foci is designed to handle multilingual documents.
versatile structural disambiguation for semantic-aware applications. in this paper, we propose a versatile disambiguation approach which can be used to make explicit the meaning of structure based information such as xml schemas, xml document structures, web directories, and ontologies. it can be of support to the semantic-awareness of a wide range of applications, from schema matching and query rewriting to peer data management systems, from xml data clustering to ontology-based automatic annotation of web pages and query expansion. the effectiveness of the achieved results has been experimentally proved and is founded both on a flexible exploitation of the structure context, whose extraction can be tailored on the specific application needs, and of the information provided by commonly available thesauri such as wordnet.
light-weight xpath processing of xml stream with deterministic automata. several applications based on xml stream processing have recently emerged, such as those for air traffic control and the selective dissemination of information (sdi). their common need is to process a large number of xpath expressions in continuous xml streams at high throughput.this paper proposes four techniques for xpath expression processing based on deterministic finite automata (dfa) for two purposes: to improve the memory usage efficiency of the automata and to support the processing of branching xpath expressions. the first technique, called n-dfa, clusters the given xpath expressions into n clusters to reduce the number of dfa states. the second, called shared nfa state table, lets the non-deterministic finite automata (nfa) state set be shared among the dfa states. our experiments show that memory usage in an 8-dfa can, with the shared nfa state table, be reduced to 1/40th that of the original 1-dfa. the optimized nfa conversion and general xpath expression processing algorithm techniques contribute to the processing of branching xpath expressions efficiently; overall performance is better than is possible with earlier approaches.
a syntactic approach for searching similarities within sentences. textual data is the main electronic form of knowledge representation. sentences, meant as logic units of meaningful word sequences, can be considered its backbone. in this paper, we propose a solution based on a purely syntactic approach for searching similarities within sentences, named approximate sub2sequence matching. this process being very time consuming, efficiency in retrieving the most similar parts available in large repositories of textual data is ensured by making use of new filtering techniques. as far as the design of the system is concerned, we chose a solution that allows us to deploy approximate sub2 sequence matching without changing the underlying database.
frem: fast and robust em clustering for large data sets. clustering is a fundamental data mining technique. this article presents an improved em algorithm to cluster large data sets having high dimensionality, noise and zero variance problems. the algorithm incorporates improvements to increase the quality of solutions and speed. in general the algorithm can find a good clustering solution in 3 scans over the data set. alternatively, it can be run until it converges. the algorithm has a few parameters that are easy to set and have defaults for most cases. the proposed algorithm is compared against the standard em algorithm and the on-line em algorithm.
improving intranet search-engines using context information from databases. information in enterprises comes in documents and data bases. from a semantic viewpoint, both kinds of information are usually tightly connected. in this paper, we propose to enhance common search-engines with contextual information retrieved from databases. we establish system requirements and anecdotally demonstrate how documents and database information can be represented as the nodes of a graph. then, we give an example how we exploit this graph information for document retrieval.
clustering high-dimensional data using an efficient and effective data space reduction. this paper introduces a new algorithm for clustering data in high-dimensional feature spaces, called gardenhd. the algorithm is organized around the notion of data space reduction, i.e. the process of detecting dense areas (dense cells) in the space. it performs effective and efficient elimination of empty areas that characterize typical high-dimensional spaces and an efficient adjacency-connected agglomeration of dense cells into larger clusters. it produces a compact representation that can effectively capture the essence of data. gardenhd is a hybrid of cell-based and density-based clustering. however, unlike typical clustering methods in its class, it applies a recursive partition of sparse regions in the space using a new space-partitioning strategy. the properties of this partitioning strategy greatly facilitate data space reduction. the experiments on synthetic and real data sets reveal that gardenhd and its data space reduction are effective, efficient, and scalable.
recent developments in text summarization. with the explosion in the quantity of on-line text and multimedia information in recent years, demand for text summarization technology is growing. increased pressure for technology advances is coming from users of the web, on-line information sources, and new mobile devices, as well as from the need for corporate knowledge management. commercial companies are increasingly starting to offer text summarization capabilities, often bundled with information retrieval tools. in this paper, i will discuss the significance of some recent developments in summarization technology.
joint optimization of cost and coverage of query plans in data integration. existing approaches for optimizing queries in data integration use decoupled strategies--attempting to optimize coverage and cost in two separate phases. since sources tend to have a variety of access limitations, such phased optimization of cost and coverage can unfortunately lead to expensive planning as well as highly inefficient plans. in this paper we present techniques for joint optimization of cost and coverage of the query plans. our algorithms search in the space of parallel query plans that support multiple sources for each subgoal conjunct. the refinement of the partial plans takes into account the potential parallelism between source calls, and the binding compatibilities between the sources included in the plan. we start by introducing and motivating our query plan representation. we then briefly review how to compute the cost and coverage of a parallel plan. next, we provide both a system-r style query optimization algorithm as well as a greedy local search algorithm for searching in the space of such query plans. finally we present a simulation study that demonstrates that the plans generated by our approach will be significantly better, both in terms of planning cost, and in terms of plan execution cost, compared to the existing approaches.
ordinal association rules for error identification in data sets. a new extension of the boolean association rules, ordinal association rules, that incorporates ordinal relationships among data items, is introduced. one use for ordinal rules is to identify possible errors in data. a method that finds these rules and identifies potential errors in data is proposed.
mining coverage statistics for websource selection in a mediator. recent work in data integration has shown the importance of statistical information about the coverage and overlap of sources for efficient query processing. despite this recognition there are no effective approaches for learning the needed statistics. the key challenge in learning such statistics is keeping the number of needed statistics low enough to have the storage and learning costs manageable. naive approaches can become infeasible very quickly. in this paper we present a set of connected techniques that estimate the coverage and overlap statistics while keeping the needed statistics tightly under control. our approach uses a hierarchical classification of the queries, and threshold based variants of familiar data mining techniques to dynamically decide the level of resolution at which to learn the statistics. we describe the details of our method, and present experimental results demonstrating the efficiency of the learning algorithms and the effectiveness of the learned statistics.
a statistical model for scientific readability. in this paper, we present a new method of using statistical models to estimate readability [1]. language model is used to capture the content information. it is combined with linguistic feature model by a linear form. experiments show that this new method has a better performance than the widely used flesch-kincaid readability formula.
knowledge discovery in patent databases. in our days the business, scientific and personal databases are growing in an exponential rate. however, what is truly valuable is the knowledge that can be extracted from the stored data. knowledge discovery in patent databases was traditionally based on manual analysis carried out from statistical experts. nowadays the increasing interest of many actors have led to the development of new tools for discovering and exploiting information related to technological activities and innovation, "hidden" in patent databases. in this paper we present a system that combines efficient and innovative methodologies and tools for the analysis of patent data stored in international databases and the production of scientific and technological indicators.
on the storage and retrieval of continuous media data. continuous media applications, which require a guaranteed transfer rate of the data, are becoming an integral part of daily computational life. however, conventional file systems do not provide rate guarantees, and are therefore not suitable for the storage and retrieval of continuous media data (e.g., audio, video). to meet the demands of these new applications, continuous media file systems, which provide rate guarantees by managing critical storage resources such as memory and disks, must be designed.in this paper, we highlight the issues in the storage and retrieval of continuous media data. we first present a simple scheme for concurrently retrieving multiple continuous media streams from disks. we then introduce a a clever allocation technique for storing continuous media data that eliminates disk latency and thus, drastically reduces ram requirements. we present, for video data, schemes for implementing the operations fast-forward, rewind and pause. finally, we conclude by outlining directions for future research in the storage and retrieval of continuous media data.
a model for weighting image objects in home photographs. the paper presents a contribution to image indexing consisting in a weighting model for visible objects -- or image objects -- in home photographs. to improve its effectiveness this weighting model has been designed according to human perception criteria about what is estimated as important in photographs. four basic hypotheses related to human perception are presented, and their validity is estimated as compared to actual observations from a user study. finally a formal definition of this weighting model is presented and its consistence with the user study is evaluated.
on structuring formal, semi-formal and informal data to support traceability in systems engineering environments. the development of large, complex systems poses a number of challenges for systems engineers, not least of which is the ability to ensure user requirements have been satisfied. effective requirements management - an amalgam of information capture, information <i>storage</i> and <i>management</i>, and information <i>dissemination</i> activities - is crucial in that respect. in this paper we concentrate on one of the core issues of <i>information management</i> in a requirements management context - namely <i>traceability</i>. traceability is the common term for mechanisms to record and navigate relationships between artifacts produced by development processes. however, realising effective traceability in systems engineering environments is complicated by the fact that engineers use a range of notations to describe complex systems. these range from natural language (informal), to graphical notations such as statecharts (semi-formal) to languages with a well defined (formal) semantics such as vdm-sl and spark ada. most have tool support, although a lack of well-defined approaches to integration leads to inconsistencies and limits traceability between their respective data sets (internal models). this paper demonstrates an approach based on meta-modelling that enables traceability links to be established and consistency maintained between tools.
infer: a relational query language without the complexity of sql. the infer query language allows users to express queries without referencing relations or specifying joins. since the infer syntax is similar to but less restrictive than sql, users can easily write highly expressive queries that are automatically completed by infer's inference engine. infer's sql-based syntax is familiar to current database users, and its improved ranking and query explanation system makes it easier to use.
task-oriented world wide web retrieval by document type classification. this paper proposes a novel approach to accurately searching web pages for relevant information in problem solving by specifying a web document category instead of the user's task. accessing information from world wide web pages as an approach to problem solving has become commonplace. however, such a search is difficult with current search services, since these services only provide keyword-based search methods that are equivalent to narrowing down the target references according to domains. however, problem solving usually involves both a domain and a task. accordingly, our approach is based on problem solving tasks. to specify a user's problem solving task, we introduce the concept of document types that directly relate to the problem solving tasks; with this approach, users can easily designate problem solving tasks. we implemented pagetypesearch system based on our approach. classifier of pagetypesearch classifies web pages into the document types by comparing their pages with typical structural characteristics of the types. we compare pagetypesearch using the document typeindices with a conventional keyword-based search system in experiments. the average precision of the document type-based search is 88.9%, while the average precision of the keyword-based search is 31.2%. moreover, the number of irrelevant references gathered by our system is about one-thirteenth that of traditional keyword-based search systems. our approach has practical advantages for problem solving by introducing the viewpoint of tasks to achieve higher performance.
"geoplot": spatial data mining on video libraries. are "tornado" touchdowns related to "earthquakes"? how about to "floods", or to "hurricanes"? in informedia [14], using a gazetteer on news video clips, we map news onto points on the globe and find correlations between sets of points. in this paper we show how to find answers to such questions, and how to look for patterns on the geo-spatial relationships of news events. the proposed tool is "geoplot", which is fast to compute and gives a lot of useful information which traditional text retrieval can not find.we describe our experiments on 2-year worth of video data (~ 20 gbytes). there we found that geoplot can find unexpected correlations that text retrieval would never find, such as those between "earthquake" and "volcano", and "tourism" and "wine".in addition, geoplot provides a good visualization of a data set's characteristics. characteristics at all scales are shown in one plot and a wealth of information is given, for example, geo-spatial clusters, characteristic scales, and intrinsic (fractal) dimensions of the events' locations.
incremental evaluation of a monotone xpath fragment. this paper shows a scheme for incremental evaluation of xpath queries. here, we focus on a monotone fragment of xpath, i.e., when a data is deleted from (or inserted to) the database, only deletion (insertion, resp.) may occur to query answers. for efficiently processing deletions, we store information on partial matchings, i.e., which elements were participating in matchings for which query answers, and also store counters showing how many matchings each query answer had. we use the information on the partial matchings also for skipping a part of computation upon data insertion. we investigate properties of the xpath fragment in order to keep the amount of information we store as small as possible.
the enosys markets data integration platform: lessons from the trenches. enosys markets offers a state-of-the-art data integration software platform to support the development of the next generation of ebusiness applications that deliver value by providing new levels of function for customer relationship management, e-commerce, supply chain management, and decision support. these applications require that data be integrated from information sources that exist both within and across organizational boundaries. the enosys markets data integration architecture and product family provides a complete end-to-end xml-based solution for integrating and querying distributed information sources. it incorporates advanced research into xml and database technology. we present the product architecture and components, discuss the key technical challenges, and outline the technical concepts and innovations employed in the enosys platform.
lattice-based tagging using support vector machines. tagging algorithms have become increasingly important for identifying lexical and semantic features of unstructured text. we describe an approach to lattice-based tagging that estimates joint transition and emission probabilities using support vector machines. the technique offers several advantages over alternative methods, including the ability to accommodate non-local features, support for hundreds of thousands of features, and language-neutrality. we demonstrate the technique on two tagging applications: named entity recognition and part-of-speech tagging.
caching constrained mobile data. as mobile devices get ubiquitous and grow in computational power, their management of interdependent data also becomes increasingly important. the mobile environment exhibits all the characteristics of a distributed database plus the feature of whimsical connectivity. consequently, transactions respecting data consistency can suffer unbounded and unpredictable delays at both mobile and stationary nodes. the currently popular multi-tier model, in which mobile devices are in one end and always-connected stationary servers in the other, has certain practical advantages. however, it assumes that all integrity constraints are evaluated at the servers and hence relies on the semantics of operations for any autonomy enhancement of the mobile devices. in this paper, we examine the idea of constraint localization in cases where two mobile nodes each own data that share a constraint. it relies on reformulation of a constraint into more flexible local constraints that give more autonomy to the mobile nodes. the scheme also involves dynamic changes of these local constraints through negotiation, which we call re-localization. to overcome the problem of simultaneous requests for such re-localization, we give algorithms along with experimental results indicating their effectiveness.
a unified environment for fusion of information retrieval approaches. prior work has shown that combining results of various retrieval approaches and query representations can improve search effectiveness. today, many meta-search engines exist which combine the results of various search engines in the hopes of improving overall effectiveness. however, the combination of results from different search engines masks variations in parsers, and other indexing techniques (stemming, stop words, etc.) this makes it difficult to assess the utility of the fusion technique. we have implemented the two most prevalent retrieval strategies: probabilistic and vector space using the same parser and the same relational retrieval engine. first, we identified a model that enables the fusion of an arbitrary number of sources. next, we tested various linear combinations of these two methods as well as various thresholds for identifying retrieved documents. our results show some improvement of effectiveness, but they also provide us for a baseline from which we can continue with other retrieval strategies and test the effect of fusing these strategies.
unified utility maximization framework for resource selection. this paper presents a unified utility framework for resource selection of distributed text information retrieval. this new framework shows an efficient and effective way to infer the probabilities of relevance of all the documents across the text databases. with the estimated relevance information, resource selection can be made by explicitly optimizing the goals of different applications. specifically, when used for database recommendation, the selection is optimized for the goal of high-recall (include as many relevant documents as possible in the selected databases); when used for distributed document retrieval, the selection targets the high-precision goal (high precision in the final merged list of documents). this new model provides a more solid framework for distributed information retrieval. empirical studies show that it is at least as effective as other state-of-the-art algorithms.
a dimensionality reduction technique for efficient similarity analysis of time series databases. efficiently searching for similarities among time series and discovering interesting patterns is an important and non-trivial problem with applications in many domains. the high dimensionality of the data makes the analysis very challenging. to solve this problem, many dimensionality reduction methods have been proposed. pca (piecewise constant approximation) and its variant have been shown efficient in time series indexing and similarity retrieval. however, in certain applications, too many false alarms introduced by the approximation may reduce the overall performance dramatically. in this paper, we introduce a new piecewise dimensionality reduction technique that is based on vector quantization. the new technique, pvqa (piecewise vector quantized approximation), partitions each sequence into equi-length segments and uses vector quantization to represent each segment by the closest (based on a distance metric) codeword from a codebook of key-sequences. the efficiency of calculations is improved due to the significantly lower dimensionality of the new representation. we demonstrate the utility and efficiency of the proposed technique on real and simulated datasets. by exploiting prior knowledge about the data, the proposed technique generally outperforms pca and its variants in similarity searches.
dist: a distributed spatio-temporal index structure for sensor networks. we consider the general problem of tracking moving objects in sensor networks. the specific application we consider is that of tracking a chemical plume moving over a large infrastructure network. we present a distributed index structure dist that stores and updates distributed summaries as the plume moves. we present algorithms for range queries on the history of the plume. dist localizes information with respect to time and space using a hierarchy that scales with the plume size. the highlight of our work is an analytical model to predict the cost of query algorithms based on the query location, query size, and plume's spatio-temporal distribution. using this model, our adaptive scheme chooses the optimal scheme. experimental results show that dist outperforms alternative techniques in query, update, and storage costs, and scales well with the number of plumes.
using bi-modal alignment and clustering techniques for documents and speech thematic segmentations. in this paper, we describe a new method for a simultaneous thematic segmentation of the meeting dialogs and the documents discussed or visible throughout the meeting. this bi-modal method is suitable for multimodal applications that are centered on documents, such as meetings and lectures, where documents can be aligned with meeting dialogs. bringing into play this alignment, our bi-modal segmentation method first transforms its results into a set of nodes in a 2d graph space, where the two axes represent respectively the document units and the meeting dialogs units. secondly, via a clustering method, the most connected regions in the constituted bi-graph are detected. finally, the denser clusters are projected on the two axes. the two sequences of segments, obtained on both axes, represent the thematic structure of the document and of the meeting dialogs respectively. we present in this article this bi-modal segmentation technique and its performance compared with two mono-modal segmentation methods.
prefix-querying: an approach for effective subsequence matching under time warping in sequence databases. this paper discusses an index-based subsequence matching that supports time warping in large sequence databases. time warping enables finding sequences with similar patterns even when they are of different lengths. in our earlier work, we suggested an efficient method for whole matching under time warping. this method constructs a multi-dimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. for filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality.in this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. for indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multi-dimensional index using a feature vector as indexing attributes. for query processing, we perform a series of index searches using the feature vectors of qualifying query prefixes. our approach provides effective and scalable subsequence matching even with a large volume of a database. we also prove that our approach does not incur false dismissal. to verify the superiority of our method, we perform extensive experiments. the results reveal that our method achieves significant speedup with real-world s&p 500 stock data and with very large synthetic data.
context modeling and discovery using vector space bases. in this paper, context is modeled by vector space bases and its evolution is modeled by linear transformations from one base to another. each document or query can be associated to a distinct base, which corresponds to one context. also, algorithms are proposed to discover contexts from document, query or groups or them. linear algebra can thus by employed in a mathematical framework to process context, its evolution and application.
a novel method for stemmer generation based on hidden markov models. in this paper, we present a method based on hidden markov models (hmms) to generate statistical stemmers. using a list of words as training set, the method estimates the hmm parameters which are used to calculate the most probable stem for an arbitrary word. stemming is performed by computing the most probable path, through the hmm states, corresponding to the input word. linguistic knowledge or a training set of manually stemmed words are not required. we describe the method and the results of the experiments carried out using standard test collections for five different languages.
unified filtering by combining collaborative filtering and content-based filtering via mixture model and exponential model. collaborative filtering and content-based filtering are two types of information filtering techniques. combining these two techniques can improve the recommendation effectiveness. the main problem with previous research is that the content information and the rating information are not combined in an integrated way. this paper presents a unified probabilistic framework that allows the mutual interaction between these two types of information. experiments have shown that the new unified filtering algorithm outperforms a pure collaborative filtering approach, a pure content-based filtering approach and another unified filtering algorithm.
evaluation of a mca-based approach to organize data cubes. in the olap context, exploration of huge and sparse data cubes is a tedious task that does not always lead to efficient results. we propose to use a multiple correspondence analysis (mca) in order to enhance data cube representations and make them more suitable for visualization and thus, easier to analyze. we also provide an original quality criterion to measure the relevance of the obtained data representations. experimental results we led on real data samples have shown the interest and the efficiency of our approach.
ontology-driven peer profiling in peer-to-peer enabled semantic web. peer-to-peer (p2p) systems and semantic web are two novel technologies that face a lot of shortcomings if considered as isolated paradigms. we present an approach that utilizes ontologies to set up a peer profile containing all the data, necessary for peer-to-peer interoperability. using this profile can help eliminate some major issues persistent in current p2p networks, such as security, resource aggregation, group management. we also consider applications of peer profiling for semantic web built on p2p networks, such as an improved semantic search for resources, not explicitly published on the web, but available in a p2p system. we develop the ontology-based peer profile in rdf format and demonstrate its manifold benefits for peer communication and knowledge discovery in both p2p networks and semantic web.
similarity measures for tracking information flow. text similarity spans a spectrum, with broad topical similarity near one extreme and document identity at the other. intermediate levels of similarity -- resulting from summarization, paraphrasing, copying, and stronger forms of topical relevance -- are useful for applications such as information flow analysis and question-answering tasks. in this paper, we explore mechanisms for measuring such intermediate kinds of similarity, focusing on the task of identifying where a particular piece of information originated. we consider both sentence-to-sentence and document-to-document comparison, and have incorporated these algorithms into <small>recap</small>, a prototype information flow analysis tool. our experimental results with <small>recap</small> indicate that new mechanisms such as those we propose are likely to be more appropriate than existing methods for identifying the intermediate forms of similarity.
incremental and interactive sequence mining. the discovery of frequent sequences in temporal databases is an important data mining problem. most current work assumes that the database is static, and a database update requires rediscovering all the patterns by scanning the entire old and new database. in this paper, we propose novel techniques for maintaining sequences in the presence of a) database updates, and b) user interaction (e.g. modifying mining parameters). this is a very challenging task, since such updates can invalidate existing sequences or introduce new ones. in both the above scenarios, we avoid re-executing the algorithm on the entire dataset, thereby reducing execution time. experimental results confirm that our approach results in execution time improvements of up to several orders of magnitude in practice.
document clustering using character n-grams: a comparative evaluation with term-based and word-based clustering. we propose a novel method for document clustering using character n-grams. in the traditional vector-space model, the documents are represented as vectors, in which each dimension corresponds to a word. we propose a document representation based on the most frequent character n-grams, with window size of up to 10 characters. we derive a new distance measure, which produces uniformly better results when compared to the word-based and term-based methods. the result becomes more significant in the light of the robustness of the n-gram method with no language-dependent preprocessing. experiments on the performance of a clustering algorithm on a variety of test document corpora demonstrate that the n-gram representation with n=3 outperforms both word and term representations. the comparison between word and term representations depends on the data set and the selected dimensionality.
using rankboost to compare retrieval systems. this paper presents a new pooling method for constructing the assessment sets used in the evaluation of retrieval systems. our proposal is based on rankboost, a machine learning voting algorithm. it leads to smaller pools than classical pooling and thus reduces the manual assessment workload for building test collections. experimental results obtained on an xml document collection demonstrate the effectiveness of the approach according to different evaluation criteria.
score region algebra: building a transparent xml-r database. a unified database framework that will enable better comprehension of ranked xml retrieval is still a challenge in the xml database field. we propose a logical algebra, named score region algebra, that enables transparent specification of information retrieval (ir) models for xml databases. the transparency is achieved by a possibility to instantiate various retrieval models, using abstract score functions within algebra operators, while logical query plan and operator definitions remain unchanged. our algebra operators model three important aspects of xml retrieval: element relevance score computation, element score propagation, and element score combination. to illustrate the usefulness of our algebra we instantiate four different, well known ir scoring models, and combine them with different score propagation and combination functions. we implemented the algebra operators in a prototype system on top of a low-level database kernel. the evaluation of the system is performed on a collection of ieee articles in xml format provided by inex. we argue that state of the art xml ir models can be transparently implemented using our score region algebra framework on top of any low-level physical database engine or existing rdbms, allowing a more systematic investigation of retrieval model behavior.
acquisition of categorized named entities for web search. the recognition of names and their associated categories within unstructured text traditionally relies on semantic lexicons and gazetteers. the amount of effort required to assemble large lexicons confines the recognition to either a limited domain (e.g., <i>medical imaging</i>), or a small set of pre-defined, broader categories of interest (e.g., <i>persons</i>, <i>countries</i>, <i>organizations</i>, <i>products</i>). this constitutes a serious limitation in an information seeking context. in this case, the categories of potential interest to users are more diverse (<i>universities</i>, <i>agencies</i>, <i>retailers</i>, <i>celebrities</i>), often refined (e.g., <i>slr digital cameras</i>, <i>programming languages</i>, <i>multinational oil companies</i>), and usually overlapping (e.g., the same entity may be concurrently a <i>brand name</i>, a <i>technology company</i>, and an <i>industry leader</i>). we present a lightly supervised method for acquiring named entities in arbitrary categories. the method applies lightweight lexico-syntactic extraction patterns to the unstructured text of web documents. the method is a departure from traditional approaches to named entity recognition in that: 1) it does not require any start-up seed names or training; 2) it does not encode any domain knowledge in its extraction patterns; 3) it is only lightly supervised, and data-driven; 4) it does not impose any a-priori restriction on the categories of extracted names. we illustrate applications of the method in web search, and describe experiments on 500 million web documents and news articles.
automatic analysis of call-center conversations. we describe a system for automating call-center analysis and monitoring. our system integrates transcription of incoming calls with analysis of their content; for the analysis, we introduce a novel method of estimating the domain-specific importance of conversation fragments, based on divergence of corpus statistics. combining this method with information retrieval approaches, we provide knowledge-mining tools both for the call-center agents and for administrators of the center.
mining sequential patterns with constraints in large databases. constraints are essential for many sequential pattern mining applications. however, there is no systematic study on constraint-based sequential pattern mining. in this paper, we investigate this issue and point out that the framework developed for constrained frequent-pattern mining does not fit our missions well. an extended framework is developed based on a sequential pattern growth methodology. our study shows that constraints can be effectively and efficiently pushed deep into sequential pattern mining under this new framework. moreover, this framework can be extended to constraint-based structured pattern mining as well.
similarity among melodies for music information retrieval. here we discuss how to look for similar melody in music databases by giving monophonic melody in sheet. in this work, we utilize text expression (or sheet music) to describe music and introduce pitch spectrum of melodies. by this feature, we concisely distinguish music from tempo, transposition or other arbitrary expressions. we show the usefulness by experimental results.
access control for xml: a dynamic query rewriting approach. being able to express and enforce role-based access control on xml data is a critical component of xml data management. however, given the semi-structured nature of xml, this is non-trivial, as access control can be applied on the values of nodes as well as on the structural relationship between nodes. in this context, we adopt and extend a graph editing language for specifying role-based access constraints in the form of security views. a security annotated schema (sas) is proposed as the internal representation for the security views and can be automatically constructed from the original schema and the security view specification. to enforce the access constraints on user queries, we propose secure query rewrite (sqr) -- a set of rules that can be used to rewrite a user xpath query on the security view into an equivalent xquery expression against the original data, with the guarantee that the users only see information in the view but not any data that was blocked. experimental evaluation demonstrates the efficiency and the expressiveness of our approach.
irregularity in multi-dimensional space-filling curves with applications in multimedia databases. a space-filling curve is a way of mapping the multi-dimensional space into the one-dimensional space. it acts like a thread that passes through every cell element (or pixel) in the n-dimensional space so that every cell is visited at least once. thus, a space-filling curve imposes a linear order of the cells in the n-dimensional space. there are numerous kinds of space-filling curves. the difference between such curves is in their way of mapping to the one-dimensional space. selecting the appropriate curve for any application requires a brief knowledge of the mapping scheme provided by each space-filling curve. irregularity is proposed as a quantitative measure of the quality of the mapping of the space-filling curve. closed formulas are developed to compute the irregularity for any general dimension d with n points in each dimension for different space-filling curves.a comparative study of different space-filling curves with respect to irregularity is conducted and results are presented and discussed. the applicability of this research is the area of multimedia databases is illustrated with a discussion of the problems that arise.
relevance score normalization for metasearch. given the ranked lists of documents returned by multiple search engines in response to a given query, the problem of metasearch is to combine these lists in a way which optimizes the performance of the combination. this problem can be naturally decomposed into three subproblems: (1) normalizing the relevance scores given by the input systems, (2) estimating relevance scores for unretrieved documents, and (3) combining the newly-acquired scores for each document into one, improved score.research on the problem of metasearch has historically concentrated on algorithms for combining (normalized) scores. in this paper, we show that the techniques used for normalizing relevance scores and estimating the relevance scores of unretrieved documents can have a significant effect on the overall performance of metasearch. we propose two new normalization/estimation techniques and demonstrate empirically that the performance of well known metasearch algorithms can be significantly improved through their use.
citeseer-api: towards seamless resource location and interlinking for digital libraries. we introduce citeseer-api, a public api to citeseer-like services. citeseer-api is soap/wsdl based and allows for easy programmatical access to all the specific functionalities offered by citeseer services, including full text search of documents and citations and citation-based document discovery. in order to enable operability and interlinking with arbitrary software agents and digital library systems, citeseer-api uses digital content signatures to create system-independent handles for the document, citation and group resources of citeseer servers. we discuss specific functionalities of citeseer-api that take advantage of these handlers in order to enable seamless location of citeseer resources. finally we argue that the digital signature scheme used by citeseer-api is well suited for the creation of machine-usable semantic descriptions of digital library services which is the key toward seamless discovery and integration of services such as citeseer-api. citeseer-api is currently showcased on citeseer.ist, the citeseer server of the school of information science and technology at the pennsylvania state university.
condorcet fusion for improved retrieval. we present a new algorithm for improving retrieval results by combining document ranking functions: condorcet-fuse. beginning with one of the two major classes of voting procedures from social choice theory, the condorcet procedure, we apply a graph-theoretic analysis that yields a sorting-based algorithm that is elegant, efficient, and effective. the algorithm performs very well on trec data, often outperforming existing metasearch algorithms whether or not relevance scores and training data is available. condorcet-fuse significantly outperforms borda-fuse, the analogous representative from the other major class of voting algorithms.
harmonic models for polyphonic music retrieval. most work in the ad hoc music retrieval field has focused on the retrieval of monophonic documents using monophonic queries. polyphony adds considerably more complexity. we present a method by which polyphonic music documents may be retrieved by polyphonic music queries. a new harmonic description technique is given, wherein the information from all chords, rather than the most significant chord, is used. this description is then combined in a new and unique way with markov statistical methods to create models of both documents and queries. document models are compared to query models and then ranked by score. though test collections for music are currently scarce, we give the first known recall-precision graphs for polyphonic music retrieval, and results are favorable.
mining temporal classes from time series data. in this investigation, we discuss how to mine temporal class schemes to model a collection of time series data. from the viewpoint of temporal data mining, this problem can be seen as discretizing time series data or aggregating them. also this can be considered as screening (or noise filtering). from the viewpoint of temporal databases, the issue is how we represent the data and how we can obtain intensional aspects as temporal schemes. in other words, we discuss scheme discovery for temporal data. given a collection of temporal objects along with time axis (called log), we examine the data and we introduce a notion of temporal frequent classes to describe them. as the main results of this investigation, we can show that there exists one and only one interval decomposition and the temporal classes related to them. also we give experimental results that prove the feasibility to time series data.
multi-dimensional sequential pattern mining. sequential pattern mining, which finds the set of frequent subsequences in sequence databases, is an important data-mining task and has broad applications. usually, sequence patterns are associated with different circumstances, and such circumstances form a multiple dimensional space. for example, customer purchase sequences are associated with region, time, customer group, and others. it is interesting and useful to mine sequential patterns associated with multi-dimensional information.in this paper, we propose the theme of multi-dimensional sequential pattern mining, which integrates the multidimensional analysis and sequential data mining. we also thoroughly explore efficient methods for multi-dimensional sequential pattern mining. we examine feasible combinations of efficient sequential pattern mining and multi-dimensional analysis methods, as well as develop uniform methods for high-performance mining. extensive experiments show the advantages as well as limitations of these methods. some recommendations on selecting proper method with respect to data set properties are drawn.
efficient evaluation of parameterized pattern queries. many applications rely on sequence databases and use extensively pattern-matching queries to retrieve data of interest. this paper extends the traditional pattern-matching expressions to parameterized patterns, featuring variables. parameterized patterns are more expressive and allow to define concisely regular expressions that would be very complex to describe without variables. they can also be used to express additional constraints on patterns' variables.we show that they can be evaluated without additional cost with respect to traditional techniques (e.g., the knuth-morris-pratt algorithm). we describe an algorithm that enjoys low memory and cpu time requirements, and provide experimental results which illustrate the gain of the optimized solution.
energy management schemes for memory-resident database systems. with the tremendous growth of system memories, memory-resident databases are increasingly becoming important in various domains. newer memories provide a structured way of storing data in multiple chips, with each chip having a bank of memory modules. current memory-resident databases are yet to take full advantage of the banked storage system, which offers a lot of room for performance and energy optimizations. in this paper, we identify the implications of a banked memory environment in supporting memory-resident databases, and propose hardware (memory-directed) and software (query-directed) schemes to reduce the energy consumption of queries executed on these databases. our results show that high-level query-directed schemes (hosted in the query optimizer) better utilize the low-power modes in reducing the energy consumption than the respective hardware schemes (hosted in the memory controller), due to their complete knowledge of query access patterns. we extend this further and propose a query restructuring scheme and a multi-query optimization. queries are restructured and regrouped based on their table access patterns to maximize the likelihood that data accesses are clustered. this helps increase the inter-access idle times of memory modules, which in turn enables a more effective control of their energy behavior. this heuristic is eventually integrated with our hardware optimizations to achieve maximum savings. our experimental results show that the memory energy reduces by 90% if query restructuring method is applied along with basic energy optimizations over the unoptimized version. the system-wide performance impact of each scheme is also studied simultaneously.
symbolic photograph content-based retrieval. photograph retrieval systems face the difficulty to deal with the different ways to apprehend the content of images. we consider and demonstrate here the use of multiple index representations of photographs to achieve effective retrieval. the use of multiple indexes allows integration of the complementary strengths of different indexing and retrieval models. the proposed representation supports multiple labels for regions and attributes, and handles inferences and relationships. we define links between indexing levels and the related query modes. the experiment conducted on 2400 home photographs shows the behavior of the multiple indexing levels during retrieval.
scalable summary based retrieval in p2p networks. much of the present p2p-ir literature is focused on distributed indexing structures. within this paper, we present an approach based on the replication of peer data summaries via rumor spreading and multicast in a structured overlay.we will describe rumorama, a p2p framework for similar-ity queries inspired by gloss and cori and their p2p-adaptation, planetp. rumorama achieves a hierarchization of planetp-like summary-based p2p-ir networks. in a rumorama network, each peer views the network as a small planetp network with connections to peers that see other small planetp networks. one important aspect is that each peer can choose the size of the planetp network it wants to see according to its local processing power and bandwidth. even in this adaptive environment, rumorama manages to process a query such that the summary of each peer is considered exactly once in a network without churn. however, the actual number of peers to be contacted for a query is a small fraction of the total number of peers in the network.within this article, we present the rumorama base protocol, as well as experiments demonstrating the scalability and viability of the approach under churn.
towards a framework for integrating multilevel secure models and temporal data models. within many organizations the number of databases containing classified or otherwise sensitive data is increasing rapidly. access to these databases must be restricted and controlled to limit the unauthorized disclosure, or malicious modification of data contained in them. however, the conventional models of authorization that have been designed for database systems supporting the hierarchical, network and relational models of data do not provide adequate mechanisms to support controlled access of temporal objects and context based temporal information. in this paper we extend the multilevel secure relational model to capture the functionality required of a temporal database, i.e. a database that supports some aspect of time, not counting user-defined time. in particular we assign class access to bitemporal timestamped attributes, and give explicit security classifications to temporal elements.
building information systems for mobile environments. it is expected that in the near future, tens of millions of users will have access to distributed information systems through wireless connections. the technical characteristics of the wireless medium and the resulting mobility of both data resources and data consumers raise new challenging questions regarding the development of information systems appropriate for mobile environments. in this paper, we report on the development of such a system. first, we describe the general architecture of the information system and the main considerations of our design. then, based on these considerations, we present our system support for maintaining the consistency of replicated data and for providing transaction schemas that account for the frequent but predictable disconnections, the mobility, and the vulnerability of the wireless environment.
mining soft-matching association rules. variation and noise in database entries can prevent data mining algorithms, such as association rule mining, from discovering important regularities. in particular, textual fields can exhibit variation due to typographical errors, mispellings, abbreviations, etc.. by allowing partial or "soft matching" of items based on a similarity metric such as edit-distance or cosine similarity, additional important patterns can be detected. this paper introduces an algorithm, softapriori that discovers soft-matching association rules given a user-supplied similarity metric for each field. experimental results on several "noisy" datasets extracted from text demonstrate that softapriori discovers additional relationships that more accurately reflect regularities in the data.
providing consistent and exhaustive relevance assessments for xml retrieval evaluation. comparing retrieval approaches requires test collections, which consist of documents, queries and relevance assessments. obtaining consistent and exhaustive relevance assessments is crucial for the appropriate comparison of retrieval approaches. whereas the evaluation methodology for flat text retrieval approaches is well established, the evaluation of xml retrieval approaches is a research issue. this is because xml documents are composed of nested components that cannot be considered independent in terms of relevance. this paper describes the methodology adopted in inex (the initiative for the evaluation of xml retrieval) to ensure consistent and exhaustive relevance assessments.
capturing term dependencies using a language model based on sentence trees. we describe a new probabilistic sentence tree language modeling approach that captures term dependency patterns in topic detection and tracking's (tdt) story link detection task. new features of the approach include modeling the syntactic structure of sentences in documents by a sentence-bin approach and a computationally efficient algorithm for capturing the most significant sentence-level term dependencies using a maximum spanning tree approach, similar to van rijsbergen's modeling of document-level term dependencies.the new model is a good discriminator of on-topic and off-topic story pairs providing evidence that sentence-level term dependencies contain significant information about relevance. although runs on a subset of the tdt2 corpus show that the model is outperformed by the unigram language model, a mixture of the unigram and the sentence tree models is shown to improve on the best performance especially in the regions of low false alarms.
relevant query feedback in statistical language modeling. in traditional relevance feedback, researchers have explored relevant document feedback, wherein, the query representation is updated based on a set of relevant documents returned by the user. in this work, we investigate relevant query feedback, in which we update a document's representation based on a set of relevant queries. we propose four statistical models to incorporate relevant query feedback.to validate our models, we considered anchor text of incoming links to a given document as feedback queries and performed experiments on the home-page retrieval task of trec 2001. our results show that three of our four models outperform the query-likelihood baseline by at least 35% in mrr score on a test set.
data fusion with estimated weights. this paper proposes an adptive approach for data fusion of information retrieval systems, which exploits estimated performances of all component input systems without relevance judgement or training. the estimation is conducted prior to the fusion but uses the same data as fusion applies. the experiment shows that our algorithms are competitive with, and often outperform combmnz, one of the most effective algorithms in use.
event threading within news topics. with the overwhelming volume of online news available today, there is an increasing need for automatic techniques to analyze and present news to the user in a meaningful and efficient manner. previous research focused only on organizing news stories by their topics into a flat hierarchy. we believe viewing a news topic as a flat collection of stories is too restrictive and inefficient for a user to understand the topic quickly. in this work, we attempt to capture the rich structure of events and their dependencies in a news topic through our event models. we call the process of recognizing events and their dependencies <i>event threading</i>. we believe our perspective of modeling the structure of a topic is more effective in capturing its semantics than a flat list of on-topic stories. we formally define the novel problem, suggest evaluation metrics and present a few techniques for solving the problem. besides the standard word based features, our approaches take into account novel features such as temporal locality of stories for event recognition and time-ordering for capturing dependencies. our experiments on a manually labeled data sets show that our models effectively identify the events and capture dependencies among them.
mining generalised disjunctive association rules. this paper introduces generalised disjunctive association rules such as "people who buy bread also buy butter jam", and "people who buy either raincoats or umbrellas also buy flashlights". a generalised disjunctive association rule allows the disjunction of conjuncts, "people who buy jackets also buy bow ties or neckties and tiepins". such rules capture contextual inter-relationships among items.given a context (antecedent), there may be a large number of generalised disjunctive association rules that satisfy the minsupp and minconf constraints. it is computationally expensive to find all such rules. we present algorithm thrifty traverse which borrows concepts such as subsumption from propositional logic to mine a subset of such rules in a computationally feasible way. we experimented with our algorithm on us census data as well as transaction data from a grocery superstore to demonstrate its computational feasibility, utility and scalability.
document clustering based on cluster validation. this paper presents a cluster validation based document clustering algorithm, which is capable of identifying both important feature words and true model order (cluster number). important feature subset is selected by optimizing a cluster validity criterion subject to some constraint. for achieving model order identification capability, this feature selection procedure is conducted for each possible value of cluster number. the feature subset and cluster number which maximize the cluster validity criterion are chosen as our answer. we have applied our algorithm to several datasets from 20newsgroup corpus. experimental results show that our algorithm can find important feature subset, estimate the model order and yield higher micro-averaged precision than other four document clustering algorithms which require cluster number to be provided.
distance-function design and fusion for sequence data. sequence-data mining plays a key role in many scientific studies and real-world applications such as bioinformatics, data stream, and sensor networks, where sequence data are processed and their semantics interpreted. in this paper we address two relevant issues: sequence-data representation, and representation-to-semantics mapping. for representation, since the best one is dependent upon the application being used and even the type of query, we propose representing sequence data in multiple views. for each representation, we propose methods to construct a <i>valid kernel</i> as the distance function to measure <i>similarity</i> between sequences. for mapping, we then find the best combination of the individual distance functions, which measure similarity of different views, to depict the target semantics. we propose a <i>super-kernel function-fusion</i> scheme to achieve the optimal mapping. through theoretical analysis and empirical studies on uci and real world datasets, we show our approach of multi-view representation and fusion to be mathematically valid and very effective for practical purposes.
an efficient and effective algorithm for density biased sampling. in this paper we describe a new density-biased sampling algorithm. it exploits spatial indexes and the local density information they preserve, to provide improved quality of sampling result and fast access to elements of the dataset. it attains improved sampling quality, with respect to factors like skew, noise or dimensionality. moreover, it has the advantage of efficiently handling dynamic updates, and it requires low execution times. the performance of the proposed method is examined experimentally. the comparative results illustrate its superiority over existing methods.
selectivity-based partitioning: a divide-and-union paradigm for effective query optimization. modern query optimizers select an efficient join ordering for a physical execution plan based essentially on the average join selectivity factors among the referenced tables. in this paper, we argue that this "monolithic" approach can miss important opportunities for the effective optimization of relational queries. we propose selectivity-based partitioning, a novel optimization paradigm that takes into account the join correlations among relation fragments in order to essentially enable multiple (and more effective) join orders for the evaluation of a single query. in a nutshell, the basic idea is to carefully partition a relation according to the selectivities of the join operations, and subsequently rewrite the query as a union of constituent queries over the computed partitions. we provide a formal definition of the related optimization problem and derive properties that characterize the set of optimal solutions. based on our analysis, we develop a heuristic algorithm for computing efficiently an effective partitioning of the input query. results from a preliminary experimental study verify the effectiveness of the proposed approach and demonstrate its potential as an effective optimization technique.
automatic discovery of salient segments in imperfect speech transcripts. this paper addresses the problem of automatic detection of salient video segments for real-world applications such as corporate training based on associated speech transcriptions. we present a novel segmentation algorithm based on automatic speech recognition (asr) applied to the audio track of the video. our feature set consists of word n-grams extracted from the imperfect speech transcriptions. we use a two-pass algorithm that combines a boundary-based method with a content-based method. in the first pass, we analyze the temporal distribution and the rate of arrival of features to compute an initial segmentation. in the second pass, we detect changes in content-bearing words by using the content-bearing features as queries in an information retrieval system. the content-based second pass validates the initial segments and merges them as needed. variations in the structure of the audio/video content, and the accuracy of asr have an impact on the feasibility of the segmentation task. for realistic data we observe that we can identify content-rich segments of the audio. in the best scenario a high-level table-of-contents is generated and in the worse scenario a single salient segment is identified. we illustrate the algorithm in detail with some examples and validate the data with manual segmentation boundaries.
dsac: integrity for outsourced databases with signature aggregation and chaining. database outsourcing is an important trend which involves data owners farming out their data management needs to an external service provider. one important requirement is to maintain the integrity and authenticity of outsourced data. whenever an outsourced database is queried, the corresponding query reply must be demonstrably authentic. furthermore, a reply must include a proof of completeness to convince the querier that no data matching the query predicate(s) has been omitted. in this paper, we suggest new techniques in support of efficient authenticity and completeness guarantees of such query replies.
maximal termsets as a query structuring mechanism. search engines process queries conjunctively to restrict the size of the answer set. further, it is not rare to observe a mismatch between the vocabulary used in the text of web pages and the terms used to compose the web queries. the combination of these two features might lead to irrelevant query results, particularly in the case of more specific queries composed of three or more terms. to deal with this problem we propose a new technique for automatically structuring web queries as a set of smaller subqueries. to select representative subqueries we use information on their distributions in the document collection. this can be adequately modeled using the concept of maximal termsets derived from the formalism of association rules theory. experimentation shows that our technique leads to improved results. for the trec-8 test collection, for instance, our technique led to gains in average precision of roughly 28% with regard to a bm25 ranking formula.
xml, the web and database functionality?. with the advance of xml, dtd's, xml-schema, x-path, x-link, xml-query, xml-protocol, rdf, semantic web and other information description tools and mechanisms the web develops more and more into a huge structured information and data network that becomes computer processable via "semi"-automatic "intelligent" means.however, most of these multimedia information resources are kept in hierarchical file-type systems or relatively unstructured relational systems with none or very little of what is commonly known as "database functionality" for the various information types represented. do we still need transaction properties, interoperability, security, reliability, scalability and others?if yes, then why are these concepts not really taken into the web-world?are the database people too far away to be able to adopt their existing solutions?are the information system people too process-oriented to care about data?are the knowledge handlers too occupied with semantic representations and ontology discussions?does the document community even see the problem?and do the web people care whether human resources are wasted through attempts to achieve database functionality through careful "behaviour"?the panel will offer opinions about these aspects but will also want to raise these issues with the audience.
towards integrative enterprise knowledge portals. knowledge portals make an important contribution to enabling enterprise knowledge management by providing users with a consolidated, personalized user interface that allows efficient access to various types of (structured and unstructured) information. today's portal systems allow combining access modules to different information sources side by side on a single portal webpage. however, there is no interaction between those so called portlets. when a user navigates within one portlet, the others remain unchanged, which means that each source has to be searched individually for relevant information.this paper discusses integration aspects within enterprise knowledge portals and presents an approach for communicating the user context (revealing the user's information need) among portlets, utilizing semantic web technologies. for example, the query context of an olap portlet, which provides access to structured data stored in a data warehouse, can be used by an information retrieval portlet in order to automatically provide the user with related documents found in the organization's document management system. the paper shortly presents a prototype that we are building to evaluate our approach, demonstrating such an olap and information retrieval integration.
ready for prime time: pre-generation of web pages in tiscover. in large data- and access-intensive web sites, efficient and reliable access is hard to achieve. this situation gets even worse for web sites providing precise structured query facilities and requiring topicality of the presented information even in face of a highly dynamic content. the achievement of these partly conflicting goals is strongly influenced by the approach chosen for page generation, ranging from composing a web page upon a user's request to its generation in advance. the official austrian web-based tourism information and booking system tiscover tries to reconcile these goals by employing a hybrid approach of page generation. in tiscover, web pages are not only generated on request in order to support precise structured queries on the content managed by a database system. rather, the whole web site is also pre-generated out of the extremely dynamic content and synchronized with the database on the basis of metadata. thus, topicality of information is guaranteed, while ensuring efficient and reliable access. this paper discusses the hybrid approach as realized in tiscover, focussing in particular on the concepts used for pre-generation.1
multiversion divergence control of time fuzziness. epsilon serializability (esr) has been proposed to manage and control inconsistency in extending the classic transaction processing. esr increases system concurrency by tolerating a bounded amount of inconsistency. in this paper, we present multiversion divergence control (mvdc) algorithms that support esr with not only value but also time fuzziness in multiversion databases. unlike value fuzziness, accumulating time fuzziness is semantically different. a simple summation of the length of two time intervals may either underestimate the total time fuzziness, resulting in incorrect execution, or overestimate the total time fuzziness, unnecessarily degrading the effectiveness of mvesr. we present a new operation, called timeunion, to accurately accumulate the total time fuzziness. because of the accurate control of time and value fuzziness by the mvdc algorithm, mvesr is very suitable for the use of multiversion databases for real-time applications that may tolerate a limited degree of data inconsistency but prefer more data recency.
a function-based access control model for xml databases. xml documents are frequently used in applications such as business transactions and medical records involving sensitive information. typically, parts of documents should be visible to users depending on their roles. for instance, an insurance agent may see the billing information part of a medical document but not the details of the patient's medical history. access control on the basis of data location or value in an xml document is therefore essential. in practice, the number of access control rules is on the order of millions, which is a product of the number of document types (in 1000's) and the number of user roles (in 100's). therefore, the solution requires high scalability and performance. current approaches to access control over xml documents have suffered from scalability problems because they tend to work on individual documents. in this paper, we propose a novel approach to xml access control through rule functions that are managed separately from the documents. a rule function is an executable code fragment that encapsulates the access rules (paths and predicates), and is shared by all documents of the same document type. at runtime, the rule functions corresponding to the access request are executed to determine the accessibility of document fragments. using synthetic and real data, we show the scalability of the scheme by comparing the accessibility evaluation cost of two rule function models. we show that the rule functions generated on user basis is more efficient for xml databases.
rhist: adaptive summarization over continuous data streams. maintaining approximate aggregates and summaries over data streams is crucial to handle the olap query workload that arises in applications, such as network monitoring and telecommunications. furthermore, since the entire data is not available at all times the maintenance task must be done incrementally. we show that r(elaxed)hist(ogram) is an appropriate summarization under data stream scenario. in order to reduce query estimation errors, we propose adaptive approaches which not only capture the data distribution, but also integrate independent query patterns. we introduce a workload decay model to efficiently capture global workload information and ensure that the query patterns from the recent past are weighted more than queries that are further in the past. we verify experimentally that our approach successfully adapts to continuously changing workload as well as data streams.
index filtering and view materialization in rolap environment. using materialized view to accelerate olap queries is one of the most common methods used in rolap systems. however, high storage and computation cost make this method very difficult to be implemented in the actual environment. among various issues associated with this, index selection and view materialization are two of the top challenges. in this paper, we propose to build indexes on subsets of the primary keys rather than the full sets if the index selectivity for these smaller indexes can be maintained above the required level. based on that we propose an index filtering rule, dominant prime (dprime) index set filter, to filter out candidate indexes that have insufficient index selectivity or have cheaper alternatives. in the second part, we propose a view materialization method, nested relation approach, to group tuples with the same value for index attributes into one super tuple using a nested relation and implement this method using oracle varray. in performance tests, our method outperforms others significantly.
graph-based object-oriented approach for structural and behavioral representation of multimedia data. the management of multimedia information poses special requirements for multimedia information systems. both representation and retrieval of the complex and multifaceted multimedia data are not easily handled with the flat relational model and require new data models. in the last several years, object-oriented and graph-based data models are actively pursued approaches for handling the multimedia information. in this paper the characteristics of the novel graph-based object-oriented data model are presented. this model represents the structural and behavioral aspects of data that form multimedia information systems. it also provides for handling the continuously changing user requirements and the complexity of the schema and data representation in multimedia information systems using the schema versioning approach and perspective version abstraction.
mining the web for answers to natural language questions. the web is now becoming one of the largest information and knowledge repositories. many large scale search engines (google, fast, northern light, etc.) have emerged to help users find information. in this paper, we study how we can effectively use these existing search engines to mine the web and discover the "correct" answers to factual natural language questions.we propose a probabilistic algorithm called qasm (question answering using statistical models) that learns the best query paraphrase of a natural language question. we validate our approach for both local and web search engines using questions from the trec evaluation. we also show how this algorithm can be combined with another algorithm (ansel) to produce precise answers to natural language questions.
summarization evaluation using relative utility. we present a series of experiments to demonstrate the validity of relative utility (ru) as a measure for evaluating extractive summarizers. ru is applicable in both single-document and multi-document summarization, is extendable to arbitrary compression rates with no extra annotation effort, and takes into account both random system performance and interjudge agreement. our results using the jhu summary corpus indicate that ru is a reasonable and often superior alternative to several common evaluation metrics.
knowledge discovery from texts: a concept frame graph approach. we address the text content mining problem through a concept based framework by constructing a conceptual knowledge base and discovering knowledge therefrom. defining a novel representation called the concept frame graph (cfg), we propose a learning algorithm for constructing a cfg knowledge base from text documents. an interactive concept map visualization technique is presented for user-guided knowledge discovery from the knowledge base. through experimental studies on real life documents, we observe that the proposed approach is promising for mining deeper knowledge.
the edam project: mining mass spectra and more. the edam project is a collaborative effort between computer scientists and environmental chemists at carleton college and uw-madison. the goal is to develop data mining techniques for advancing the state of the art in analyzing atmospheric aerosol datasets. the traditional approach for particle measurement, which is the collection of bulk samples of particulates on filters, is not adequate for studying particle dynamics and real-time correlations. this has led to the development of a new generation of real-time instruments that provide continuous or semi-continuous streams of data about certain aerosol properties. however, these instruments have added a significant level of complexity to atmospheric aerosol data, and dramatically increased the amounts of data to be collected, managed, and analyzed. we are investigating techniques for automatically labeling mass spectra from different kinds of aerosol mass spectrometers, and then analyzing and exploring the rich spatiotemporal information collected from multiple geographically distributed instruments. in this talk, i will present an overview of some novel data mining problems, describe some of the techniques we are developing to address them, and discuss the broader applicability of these techniques to problems from other domains.
a structure-sensitive framework for text categorization. this paper presents a framework called structure sensitive categorization(sscat), that exploits document structure for improved categorization. there are two parts to this framework, viz. (1) documents often have layout structure, such that logically coherent text is grouped together into fields using some mark-up language. we use a log-linear model, which associates one or more features with each field. weights associated with the field features are learnt from training data and these weights quantify the per-class importance of the field features in determining the category for the document. (2) we employ a technique that exploits the parse tree of fields that are phrasal constructs, such as title and associates weights with words in these constructs while boosting weights of important words called focus words. these weights are learnt from example instances of phrasal constructs, marked with the corresponding focus words. the learning is accomplished by training a classifier that uses linguistic features obtained from the text's parse structure. the weighted words, in fields with phrasal constructs, are used in obtaining features for the corresponding fields in the overall framework. sscat was tested on the supervised categorization task of over one million products from yahoo!'s on-line shopping data. with an accuracy of over 90%, our classifier outperforms naive bayes and support vector machines. this not only shows the effectiveness of sscat but also strengthens our belief that linguistic features based on natural language structure can improve tasks such as text categorization.
techniques for efficient fragment detection in web pages. the existing approaches to fragment-based publishing, delivery and caching of web pages assume that the web pages are manually fragmented at their respective web sites. however manual fragmentation of web pages is expensive, error prone, and not scalable. this paper proposes a novel scheme to automatically detect and flag possible fragments in a web site. our approach is based on an analysis of the web pages dynamically generated at given web sites with respect to their information sharing behavior, personalization characteristics and change patterns.
structural features in content oriented xml retrieval. the structural features of xml components are an extra source of information that should be used in a content-oriented retrieval task on this type of documents. in this paper we explore one of the structural features from the inex collection [1] that could be used in content-oriented search. we analyse the gain this knowledge could add to the performance of an information retrieval system and present a first approach on how this structural information could be extracted from a relevance feedback process to be used as priors in a language modelling framework.
approaches to collection selection and results merging for distributed information retrieval. we have investigated two major issues in distributed information retrieval (dir), namely: collection selection and search results merging. while most published works on these two issues are based on pre-stored metadata, the approaches described in this paper involve extracting the required information at the time the query is processed. in order to predict the relevance of collections to a given query, we analyse a limited number of full documents (e.g., the top five documents) retrieved from each collection and then consider term proximity within them. on the other hand, our merging technique is rather simple since input only requires document scores and lengths of results lists. our experiments evaluate the retrieval effectiveness of these approaches and compare them with centralised indexing and various other dir techniques (e.g., cori). we conducted our experiments using two testbeds: one containing news articles extracted from four different sources (2 gb) and another containing 10 gb of web pages. our evaluations demonstrate that the retrieval effectiveness of our simple approaches is worth considering.
towards data warehouse design. this paper focuses on data warehouse modelling. the conceptual model we defined, is based on object concepts extended with specific concepts like generic classes, temporal classes and archive classes. the temporal classes are used to store the detailed evolutions and the archive classes store the summarised data evolutions. we also provide a flexible concept allowing the administrator to define historised parts and non-historised parts into the warehouse schema. moreover, we introduce constraints which configure the data warehouse behaviour and these various parts. to validate our propositions, we describe a prototype dedicated to the data warehouse design.
exploiting hierarchical relationships in conceptual search. as the number of available web pages grows, users experience increasing difficulty finding documents relevant to their interests. one of the underlying reasons for this is that most search engines find matches based on keywords, regardless of their meanings. to provide the user with more useful information, we need a system that disambiguates queries by including information about the user's conceptual framework. this is the goal of keyconcept, a conceptual search engine. during indexing, keyconcept automatically classifies documents into concepts selected from a reference concept hierarchy. during retrieval, keyconcept ranks documents based on a combination of keyword and conceptual similarity. this paper describes the system architecture and discusses the results of experiments that evaluate the effect of exploiting the hierarchical relationships between concepts during retrieval. our results confirm that conceptual match significantly improves the precision of the search results over keyword match alone. in addition, the use of the concept hierarchy to prune irrelevant search results also significantly increases precision.
efficient runtime generation of association rules. mining frequent patterns in transaction databases has been a popular subject in data mining research. common activities include finding patterns in database transactions, times-series, and exceptions. the apriori algorithm is a widely accepted method of generating frequent patterns. the algorithm can require many scans of the database and can seriously tax resources. new methods of finding association rules, such as the frequent pattern tree (fp-tree) have improved performance, but still have problems when new data becomes available and require two scans of the database.this paper proposes a new method, which requires only one scan of the database and supports update of patterns when new data becomes available. we design a new structure called pattern repository (pr), which stores all of the relevant information in a highly compact form and allows direct derivation of the fp-tree and association rules quickly with a minimum of resources. in addition, it supports run-time generation of association rules by considering only those patterns that meet on-line data requirements.
a vertical distance-based outlier detection method with local pruning. "one person's noise is another person's signal". outlier detection is used to clean up datasets and also to discover useful anomalies, such as criminal activities in electronic commerce, computer intrusion attacks, terrorist threats, agricultural pest infestations, etc. thus, outlier detection is critically important in the information-based society. this paper focuses on finding outliers in large datasets using distance-based methods. first, to speedup outlier detections, we revise knorr and ng's distance-based outlier definition; second, a vertical data structure, instead of traditional horizontal structures, is adopted to facilitate efficient outlier detection further. we tested our methods against national hockey league dataset and show an order of magnitude of speed improvement compared to the contemporary distance-based outlier detection approaches.
the robustness of content-based search in hierarchical peer to peer networks. hierarchical <i>peer to peer</i> networks with multiple directory services are an important architecture for large-scale file sharing due to their effectiveness and efficiency. recent research argues that they are also an effective method of providing large-scale content-based federated search of text-based digital libraries. in both cases the directory services are critical resources that are subject to attack or failure, but the latter architecture may be particularly vulnerable because content is less likely to be replicated throughout the network. this paper studies the robustness, effectiveness and efficiency of content-based federated search in hierarchical <i>peer to peer</i> networks when directory services fail unexpectedly. several recovery methods are studied using simulations with varying failure rates. experimental results show that quality of service and efficiency degrade gracefully as the number of directory service failures increases. furthermore, they show that content-based search mechanisms are more resilient to failures than the match-based search techniques.
a lock method for kbmss using abstraction relationships' semantics. knowledge base management systems (kbmss) are a growing research area finding applicability in different domains. as a consequence, the demand for ever-larger knowledge bases (kbs) is growing more and more. inside this context, knowledge sharing turns out to be a crucial point to be supported by kbmss. in this paper, we propose a way of controlling knowledge sharing. we show how we obtain serializability of transactions providing many different locking granules, which are based on the semantics of the abstraction relationships. the main benefit of our technique is the high degree of potential concurrency, to be obtained through a logical partitioning of the kb graph and the provision of lock types used for each referenced partition. by this way, we capture more of the semantics contained in a kb graph, through an interpretation of its edges grounded in the abstraction relationships, and make feasible a full exploitation of all inherent parallelism in a knowledge representation approach.
extracting semi-structured data through examples. in this paper, we describe an innovative approach to extracting semi-structured data from web sources. the idea is to collect a couple of example objects from the user and to use this information to extract new objects from new pages or texts. to perform the extraction of new objects, we introduce a bottom-up extration strategy and, through experimentation, demonstrate that it works quite effectively with distinct web sources, even if only a few examples are provided by the user.
of parts and relationships: an unending quest. systems biology is a field which focuses on the interpretation of large, diverse sets of biological measurements in order to elucidate the complex mechanisms that underly important and (seemingly simple) macroscopic phenotypes. the problem at hand is hierarchical in nature, with the hierarchy spanning many levels. each of these levels can be thought of as comprising multiple active agents that are diverse in their nature (e.g. genes, proteins, pathways, organelles, etc) and also in their behavior. it is within this setting that one seeks to build an integrated view of the system under study, as soon as the relevant units and the complex inter- and intra-level relationships in which these units participate have been characterized. implicit in the above outline are the assumptions that a) a complete and presumably correct list of parts exists for the system that is being studied; and, b) most, if not all, of the relevant relationships involving these parts are available. through the research work of my group and of others, there is increasing evidence that the situation is likely to be more complicated than initially estimated, and that one should be watchful when it comes to making or relying on the above two assumptions. in fact, more surprising and currently undiscovered things may be lurking in the ?genomics? box: support for this possibility will be provided through the brief summaries of recent advances that we have made in diverse areas such as association discovery, gene discovery, horizontal gene transfer and rna interference. throughout this quest, repositories of biological information will continue to remain our guiding light, whereas time-honored computational methods will continue to be the mainstay of our arsenal.
simple bm25 extension to multiple weighted fields. this paper describes a simple way of adapting the bm25 ranking formula to deal with structured documents. in the past it has been common to compute scores for the individual fields (e.g. title and body) independently and then combine these scores (typically linearly) to arrive at a final score for the document. we highlight how this approach can lead to poor performance by breaking the carefully constructed non-linear saturation of term frequency in the bm25 function. we propose a much more intuitive alternative which weights term frequencies <i>before</i> the non-linear term frequency saturation function is applied. in this scheme, a structured document with a title weight of two is mapped to an unstructured document with the title content repeated twice. this more verbose unstructured document is then ranked in the usual way. we demonstrate the advantages of this method with experiments on reuters vol1 and the trec dotgov collection.
high-performing feature selection for text classification. this paper reports a controlled study on a large number of filter feature selection methods for text classification. over 100 variants of five major feature selection criteria were examined using four well-known classification algorithms: a naive bayesian (nb) approach, a rocchio-style classifier, a k-nearest neighbor (knn) method and a support vector machine (svm) system. two benchmark collections were chosen as the testbeds: reuters-21578 and small portion of reuters corpus version 1 (rcv1), making the new results comparable to published results. we found that feature selection methods based on chi2 statistics consistently outperformed those based on other criteria (including information gain) for all four classifiers and both data collections, and that a further increase in performance was obtained by combining uncorrelated and high-performing feature selection methods.the results we obtained using only 3% of the available features are among the best reported, including results obtained with the full feature set.
quality of service transferred to information retrieval: the adaptive information retrieval system. users often quit an information retrieval system (ir system) very frustrated, because they cannot find the information matching their information needs. we have identified the following two main reasons: too high expectations and wrong use of the system. our approach which addresses both issues is based on the transfer of the concept of quality of service to ir systems: the user first negotiates the retrieval success rates with the ir system, so he knows what to expect from the system in advance. second, by dynamic adaptation to the retrieval context, the ir system tries to improve the user's queries and thereby tries to exploit the underlying information source as best as possible.
hierarchical classification as an aid to database and hit-list browsing. a navigational aid for databases that relies on unsupervised hierarchical classification is presented. the approach to hierarchical classification, based on both functional and topological features, supports the creation of deep hierarchies in which succeeding levels represent increasing degrees of abstraction. this allows the user to quickly evaluate the result of a query and to locate interesting items and classes of items by performing a tree traversal rather than a sequential perusal of a hit list or a series of ad hoc query refinements. in very large databases where classical querying methods are increasingly inadequate such as chemical reaction databases, such a browsing method is required in order to manage the flood of information with which the user is confronted.
structural extraction from visual layout of documents. most information extraction systems focus on the textual content of the documents. they treat documents as sequences or of words, disregarding the physical and typographical layout of the information.. while this strategy helps in focusing the extraction process on the key semantic content of the document, much valuable information can also be derived form the document physical appearance. often, fonts, physical positioning and other graphical characteristics are used to provide additional context to the information. this information is lost with pure-text analysis. in this paper we describe a general procedure for structural extraction, which allows for automatic extraction of entities from the document based on their visual characteristics and relative position in the document layout. our structural extraction procedure is a learning algorithm, which knows how to automatically generalizes from examples. the procedure is a general one, applicable to any document format with visual and typographical information. we also then describe a specific implementation of the procedure to pdf documents, called pes (pdf extraction system). pes works with pdf documents and is able to extract such fields such as author(s), title, date, etc. with very high accuracy.
teg: a hybrid approach to information extraction. this paper describes a hybrid statistical and knowledge-based information extraction model, able to extract entities and relations at the sentence level. the model attempts to retain and improve the high accuracy levels of knowledge-based systems while drastically reducing the amount of manual labor by relying on statistics drawn from a training corpus. the implementation of the model, called teg (trainable extraction grammar), can be adapted to any ie domain by writing a suitable set of rules in a scfg (stochastic context free grammar) based extraction language, and training them using an annotated corpus. the system does not contain any purely linguistic components, such as pos tagger or parser. we demonstrate the performance of the system on several named entity extraction and relation extraction tasks. the experiments show that our hybrid approach outperforms both purely statistical and purely knowledge-based systems, while requiring orders of magnitude less manual rule writing and smaller amount of training data. the improvement in accuracy is slight for named entity extraction task and more pronounced for relation extraction.
document release versus data access controls: two sides of the same coin?. the database and document worlds have traditionally had different approaches to security. databases provide access controls on structured data, while document security interrogates the outgoing information, based on document markings and actual contents. for the emerging world in which many documents are generated from structured data (and vice versa), the separation can cause failure, implementation-dependence, inconsistency, and wasted effort. after comparing approaches and mechanisms in the two areas, we identify issues in security administration and implementation in military and medical applications. we then present elements of a unifying model.
optimizing candidate check costs for bitmap indices. in this paper, we propose a new strategy for optimizing the placement of bin boundaries to minimize the cost of query evaluation using bitmap indices with binning. for attributes with a large number of distinct values, often the most efficient index scheme is a bitmap index with binning. however, this type of index may not be able to fully resolve some user queries. to fully resolve these queries, one has to access parts of the original data to check whether certain candidate records actually satisfy the specified conditions. we call this procedure the candidate check, which usually dominates the total query processing time. given a set of user queries, we seek to minimize the total time required to an-swer the queries by optimally placing the bin boundaries. we show that our dynamic programming based algorithm can efficiently determine the bin boundaries. we verify our analysis with some real user queries from the sloan digital sky survey. for queries that require significant amount of time to perform candidate check, using our optimal bin boundaries reduces the candidate check time by a factor of 2 and the total query processing time by 40%.
semantic verification for fact seeking engines. we present the architecture of our web question answering (fact seeking) system and introduce a novel algorithm to validate semantic categories of the expected answers. when tested on the questions used by the prior research, our system demonstrated the performance comparable to the current state of the art systems. our semantic verification algorithm has improved the accuracy of answers of the affected questions by 30%.
discretization based learning approach to information retrieval. we have designed a representation scheme, which is based on the discrete representation of a document ranking function, which is capable of reproducing and enhancing the properties of such popular ranking functions as tf.idf, bm25 or those based on language models. our tests have demonstrated the capability of our approach to achieve the performance of the best known scoring functions solely through training, without using any known heuristic or analytic formulas.
towards automatic association of relevant unstructured content with structured query results. faced with growing knowledge management needs, enterprises are increasingly realizing the importance of seamlessly integrating critical business information distributed across both structured and unstructured data sources. in existing information integration solutions, the application needs to formulate the sql logic to retrieve the needed structured data on one hand, and identify a set of keywords to retrieve the related unstructured data on the other. this paper proposes a novel approach wherein the application specifies its information needs using only a sql query on the structured data, and this query is automatically ``translated'' into a set of keywords that can be used to retrieve relevant unstructured data. we describe the techniques used for obtaining these keywords from (i) the query result, and (ii) additional related information in the underlying database. we further show that these techniques achieve high accuracy with very reasonable overheads.
a classification algorithm for supporting object-oriented views. in recent years, object-oriented (oo) views have been recognized as a powerful mechanism for customizing the structural as well as behavioral aspects of interfaces to object-oriented databases (oodbs) for diverse users. in this context, classification is concerned with the integration of virtual classes derived using an oo query into one unifying schema. existing approaches either require the user to explicitly specify the relationship between a virtual class and existing base classes, or they relate a virtual class directly with its source class(es) or with the root of the schema. in this paper, we propose a solution to this classification problem that accomplishes the following goals: (1) generate maximally informative, and thus comprehensible, schemas that explicitly model the subclass relationships between base and virtual classes, and (2) support efficient type resolution for shared property functions by supporting upwards inheritance for both base and virtual classes. correctness and complexity of the classification algorithm are also discussed.
self maintenance of multiple views in data warehousing. materialized views (mv) at the data warehouse (dw) can be kept up to date in response to changes in data sources without accessing data sources for additional information. this process is usually refered to as &ldquo;self maintenance of views&rdquo;. a number of algorithms have been proposed for self maintenance of views, which use auxiliary views (av) to keep some additional information in dw. in this paper we propose an algorithm for self maintainability of multiple mvs using the above approach. our algorithm generates a simple maintenance query to incrementally maintain an mv along with its av at dw. the algorithm maintains these views by minimizing the number and the size of the avs. our approach provides better insight into view maintenance issues by exploiting the dependencies and constraints that might exist in the data sources and multiple mvs at dw.
structural inference for semistructured data. semistructured data presents many challenges, mainly due to its lack of a strict schema. these challenges are further magnified when large amounts of data are gathered from heterogeneous sources. we address this by investigation and development of methods to automatically infer structural information from example data. using xml as a reference format, we approach the schema generation problem by application of inductive inference theory. in doing so, we review and extend results relating to the search spaces of grammatical inferences. we then adapt a method for evaluating the result of an inference process from computational linguistics. further, we combine several inference algorithms, including both new techniques introduced by us and those from previous work. comprehensive experimentation reveals our new hybrid method, based upon recently developed optimisation techniques, to be the most effective.
circumstance-based categorization analysis of knowledge management systems for the japanese market. we conducted a survey of thirty of the approximately 1,700 customers of justsystem corporation's knowledge-management applications. our goal was to discover the kinds of functions that customers hoped to address in their next-generation use of knowledge management technology and to assess the core processes that we will need to deploy in our products to address their desired solutions. in particular, we sought to analyze our customers' requirements along dimensions that take account of both the context of use of the application and its stage in the cycle of knowledge creation and use. as part of our analysis, we were able to classify all customer cases as focused by one or more of three goals, supported by one or more of eleven technology means. to establish appropriate categories of use, we exploited the stages of the <i>seci model</i>, several other transactional categories of knowledge use, and whether activities were targeted at internal or external users. through the analysis, we found the typical technology components (means) for each stage of knowledge creation and use associated with each set of goals. we consider such analysis essential to the task of designing next-generation knowledge-management applications and critical to overcoming the unfortunate tendency of developers to devise solutions that bear little relation to the true needs of users.
sql database primitives for decision tree classifiers. scalable data mining in large databases is one of today's challenges to database technologies. thus, substantial effort is dedicated to a tight coupling of database and data mining systems leading to database primitives supporting data mining tasks. in order to support a wide range of tasks and to be of general usage these primitives should be rather building blocks than implementations of specific algorithms. in this paper, we describe primitives for building and applying decision tree classifiers. based on the analysis of available algorithms and previous work in this area we have identified operations which are useful for a number of classification algorithms. we discuss the implementation of these primitives on top of a commercial dbms and present experimental results demonstrating the performance benefit.
meta-recommendation systems: user-controlled integration of diverse recommendations. in a world where the number of choices can be overwhelming, recommender systems help users find and evaluate items of interest. they do so by connecting users with information regarding the content of recommended items or the opinions of other individuals. such systems have become powerful tools in domains such as electronic commerce, digital libraries, and knowledge management. in this paper, we address such systems and introduce a new class of recommender system called meta-recommenders. meta-recommenders provide users with personalized control over the generation of a single recommendation list formed from a combination of rich data using multiple information sources and recommendation techniques. we discuss experiments conducted to aid in the design of interfaces for a meta-recommender in the domain of movies. we demonstrate that meta-recommendations fill a gap in the current design of recommender systems. finally, we consider the challenges of building real-world, usable meta-recommenders across a variety of domains.
advanced grouping and aggregation for data integration. new applications from the areas of analytical data processing and data integration require powerful features to condense and reconcile available data. as outlined in [1], the general concept of grouping and aggregation appears to be a fitting paradigm for a number of these issues, but in its common form of equality based groups or with current extensions like simple user-defined functions to derive group-by values on a per tuple basis and restricted aggregate functions a number of problems remain unsolved. we describe two extensions to the grouping mechanism, a generic one to support holistic user-defined grouping functions and higher level construct that provides similarity based grouping suitable in a number of applications like duplicate detection and elimination.
query association for effective retrieval. we introduce a novel technique for document summarisation which we call query association. query association is based on the notion that a query that is highly similar to a document is a good descriptor of that document. for example, the user query "richmond football club" is likely to be a good summary of the content of a document that is ranked highly in response to the query. we describe this process of defining, maintaining, and presenting the relationship between a user query and the documents that are retrieved in response to that query. we show that associated queries are an excellent technique for describing a document: for relevance judgement, associated queries are as effective as a simple online query-biased summarisation technique. as future work, we suggest additional uses for query association including relevance feedback and query expansion.
boosting support vector machines for text classification through parameter-free threshold relaxation. support vector machine (svm) learning algorithms focus on finding the hyperplane that maximizes the margin (the distance from the separating hyperplane to the nearest examples) since this criterion provides a good upper bound of the generalization error. when applied to text classification, these learning algorithms lead to svms with excellent precision but poor recall. various relaxation approaches have been proposed to counter this problem including: asymmetric svm learning algorithms (soft svms with asymmetric misclassification costs); uneven margin based learning; and thresholding. a review of these approaches is presented here. in addition, in this paper, we describe a new threshold relaxation algorithm. this approach builds on previous thresholding work based upon the beta-gamma algorithm. the proposed thresholding strategy is parameter free, relying on a process of retrofitting and cross validation to set algorithm parameters empirically, whereas our previous approach required the specification of two parameters (beta and gamma). the proposed approach is more efficient, does not require the specification of any parameters, and similarly to the parameter-based approach, boosts the performance of baseline svms by at least 20% for standard information retrieval measures.
index construction for linear categorisation. categorisation is a useful method for organising documents into subcollections that can be browsed or searched to more accurately and quickly meet information needs. on the web, category-based portals such as yahoo! and dmoz are extremely popular: dmoz is maintained by over 56,000 volunteers, is used as the basis of the popular google directory, and is perhaps used by millions of users each day. support vector machines (svm) is a machine-learning algorithm which has been shown to be highly effective for automatic text categorisation. however, a problem with iterative training techniques such as svm is that during their learning or training phase, they require the entire training collection to be held in main-memory; this is infeasible for large training collections such as dmoz or large news wire feeds. in this paper, we show how inverted indexes can be used for scalable training in categorisation, and propose novel heuristics for a fast, accurate, and memory efficient approach. our results show that an index can be constructed on a desktop workstation with little effect on categorisation accu-racy compared to a memory-based approach. we conclude that our techniques permit automatic categorisation using very large train-ing collections, vocabularies, and numbers of categories.
semantic-based delivery of olap summary tables in wireless environments. with the rapid growth in mobile and wireless technologies and the availability, pervasiveness and cost effectiveness of wireless networks, mobile computers are quickly becoming the normal front-end devices for accessing enterprise data. in this paper, we are addressing the issue of efficient delivery of business decision support data in the form of summary tables to mobile clients equipped with olap front-end tools. towards this, we propose a new on-demand scheduling algorithm, called sbs, that exploits both the derivation semantics among olap summary tables and the mobile clients' capabilities of executing simple sql queries. it maximizes the aggregated data sharing between clients and reduces the broadcast length compared to the already existing techniques. the degree of aggregation can be tuned to control the tradeoff between access time and energy consumption. further, the proposed scheme adapts well to different request rates, access patterns and data distributions. the algorithm effectiveness with respect to access time and power consumption is evaluated using simulation.
finding similar images quickly using object shapes. retrieving images from a large image collection has been an active area of research. most of the existing works have focused on content representation. in this paper, we address the issue of identifying relevant images quickly. this is important in order to meet the users' performance requirements. we propose a framework for fast image retrieval based on object shapes extracted from objects within images. the framework builds a hierarchy of approximations on object shapes such that shape representation at a higher level is a coarser representation of a shape at the lower level. in other words, multiple shapes at a lower level can be mapped into a single shape at a higher level. in this way, the hierarchy serves to partition the database at various granularities. given a query shape, by searching only the relevant paths in the hierarchy, a large portion of the database can thus be pruned away. we propose the angle mapping (am) method to transform a shape from one level to another (higher) level. am essentially replaces some edges of a shape by a smaller number of edges based on the angles between the edges, thus reducing the complexity of the original shape. based on the framework, we also propose two hierarchical structures to facilitate speedy retrieval. the first, called hierarchical partitioning on shape representation (hpsr), uses the shape representation as the indexing key. the second, called hierarchical partitioning on angle vector (hpav), captures the angle information from the shape representation. we conducted an extensive study on both methods to see their quality and efficiency. our experiments on sets of images, each of which has objects around from 1 to 30, showed that the framework can provide speedy image retrieval without sacrificing on the quality. both proposed schemes can improve the efficiency by as much as hundreds of times to sequential scanning. the improvement grows as image database size, objects per image or object dimension increase.
integrating heterogeneous reatures for efficient content based music retrieval. in this paper, we present a novel feature extraction method facilitating efficient content-based music retrieval and classification, called <i>inmaf</i>. the goal of our approach is to allow straightforward incorporation of multiple musical features, such as timbral texture, pitch and rhythm structure, into a single low dimensional vector that is effective for retrieval and classification. unlike earlier approaches that used only acoustic properties as the basis for retrieval, our approach can easily incoporate human music perception to improve accuracy of retrieval and classification process. the superiority of our method is demonstrated by comparing it with state-of-the-art approaches in the areas of music classification (using a variety of machine learning algorithms), query effectiveness and robustness against audio distortion.
implicit user modeling for personalized search. information retrieval systems (e.g., web search engines) are critical for overcoming information overload. a major deficiency of existing retrieval systems is that they generally lack user modeling and are not adaptive to individual users, resulting in inherently non-optimal retrieval performance. for example, a tourist and a programmer may use the same word "java" to search for different information, but the current search systems would return the same results. in this paper, we study how to infer a user's interest from the user's search context and use the inferred implicit user model for personalized search. we present a decision theoretic framework and develop techniques for implicit user modeling in information retrieval. we develop an intelligent client-side web search agent (ucair) that can perform eager implicit feedback, e.g., query expansion based on previous queries and immediate result reranking based on clickthrough information. experiments on web search show that our search agent can improve search accuracy over the popular google search engine.
leonardo's laptop: human needs and the new computing technologies. the old computing was about what computers could do; the new computing is about what people can do.to accelerate the shift from the old to the new computing designers need to:reduce computer user frustration. recent studies show 46% of time is lost to crashes, confusing instructions, navigation problems, etc. public pressure for change could promote design improvements and increase reliability, thereby dramatically enhancing user experiences.promote universal usability. interfaces must be tailorable to a wide range of hardware, software, and networks, and users. when broad services such as voting, healthcare, and education are envisioned, the challenge to designers is substantial.envision a future in which human needs more directly shape technology evolution. four circles of human relationships and four human activities map out the human needs for mobility, ubiquity, creativity, and community. the world wide med and million-person communities will be accessible through desktop, palmtop and fingertip devices to support e-learning, e-business, e-healthcare, and e-government.leonardo da vinci could help as an inspirational muse for the new computing. his example could push designers to improve quality through scientific study and more elegant visual design. leonardo's example can guide us to the new computing, which emphasizes empowerment, creativity, and collaboration. information visualization and personal photo interfaces will be shown: photomesa (www.cs.umd.edu/hcil/photomesa) and photofinder (www.cs.umd.edu/hcil/photolib).for more: http://mitpress.mit.edu/leonardoslaptop and http://www.cs.umd.edu/hcil/newcomputing.
performance of clustering policies in object bases. in this paper, we address the problem of clustering graphs in object-oriented databases. unlike previous studies which focused only on a workload consisting of a single operation, this study tackles the problem when the workload is a set of operations (method and queries) that occur with a certain probability. thus, the goal is to minimize the expected cost of an operation in the workload, while maintaining a similarly low cost for each individual operation class.to this end, we present a new clustering policy based on the nearest-neighbor graph partitioning algorithm. we then demonstrate that this policy provides considerable gains when compared to a suite of well-known clustering policies proposed in the literature. our results are based on two widely referenced object-oriented database benchmarks; namely, the tektronix hypermodel and oo7.
discovering quasi-equivalence relationships from database systems. association rule mining has recently attracted strong attention and proven to be a highly successful technique for extracting useful information from very large databases. in this paper, we explore a generalized affinity-based association mining which discovers quasi-equivalent media objects in a distributed information-providing environment consisting of a network of heterogeneous databases which could be relational databases, hierarchical databases, object-oriented databases, multimedia databases, etc. online databases, consisting of millions of media objects, have been used in business management, government administration, scientific and engineering data management, and many other applications owing to the recent advances in high-speed communication networks and large-capacity storage devices. because of the navigational characteristic, queries in such an information-providing environment tend to traverse equivalent media objects residing in different databases for the related data records. as the number of databases increases, query processing efficiency depends heavily on the capability to discover the equivalence relationships of the media objects from the network of databases. theoretical terms along with an empirical study of real databases are presented.
a language modeling framework for resource selection and results merging. statistical language models have been proposed recently for several information retrieval tasks, including the resource selection task in distributed information retrieval. this paper extends the language modeling approach to integrate resource selection, ad-hoc searching, and merging of results from different text databases into a single probabilistic retrieval model. this new approach is designed primarily for intranet environments, where it is reasonable to assume that resource providers are relatively homogeneous and can adopt the same kind of search engine. experiments demonstrate that this new, integrated approach is at least as effective as the prior state-of-the-art in distributed ir.
goal-oriented methods and meta methods for document classification and their parameter tuning. automatic text classification methods come with various calibration parameters such as thresholds for probabilities in bayesian classifiers or for hyperplane distances in svm classifiers. in a given application context these parameters should be set so as to meet the relative importance of various result quality metrics such as precision versus recall. in this paper we consider classifiers that can accept a document for a topic, reject it, or abstain. we aim to meet the application's goals in terms of accuracy (i.e., avoid false acceptances or rejections) and loss (i.e., limit the fraction of documents for which no decision is made). to this end we investigate restrictive forms of support vector machine classifiers and we develop meta methods that split the training data into subsets for independently trained classifiers and then combine the results of these classifiers. these techniques tend to improve accuracy at the expense of document loss. we develop estimators that help to predict the accuracy and loss for a given setting of the methods' tuning parameters, and a methodology for efficiently deriving a setting that meets the application's goals. our experiments confirm the practical viability of the approach.
a visual interface technique for exploring olap data with coordinated dimension hierarchies. multi-dimensional data occurs in many domains while a wide variety of text based and visual interfaces for querying such data exists. but many of these interfaces are not applicable to olap, as they do not support use of dimension hierarchies for selection and aggregation. we introduce an interface technique which supports visual querying of olap data, that has been implemented in the sgviewer tool. it is based on a data graph rather than a data cube representation of the data. our interface presents each dimension hierarchy in a zoomable panel which supports selection and aggregation at multiple levels. users explore data and query it by making selections in several dimension views. three view coordinations are identified; progressive, global and result only. our main contribution, the progressive view coordination provides better support for query refinement than existing interfaces, by helping users decide the next query step with intermediate result overviews, and by helping users change a previous selection decision with retained selection context views. our interface technique is demonstrated with a web log dataset of visits organised into time, download, visitor and referrer address dimensions.
processing content-oriented xpath queries. document-centric xml collections contain text-rich documents, marked up with xml tags that add lightweight semantics to the text. querying such collections calls for a hybrid query language: the text-rich nature of the documents suggests a content-oriented (ir) approach, while the mark-up allows users to add structural constraints to their ir queries. hybrid queries tend to be more expressive, which should lead---in principle---to better retrieval performance. in practice, the processing of these hybrid queries within an ir systems turns out to be far from trivial, because a delicate balance between structural and content information needs to be sought. we propose an approach to processing such hybrid content-and-structure queries that decomposes a query into multiple content-only queries whose results are then combined in ways determined by the structural constraints of the original query. we evaluate our methods using the inex 2003 test-suite, and show (1) that effective ways of processing of content-oriented xpath queries are non-trivial, (2) that there are differences in the effectiveness for different topics types, but (3) that with appropriate processing methods retrieval effectiveness can improve.
viper: augmenting automatic information extraction with visual perceptions. in this paper we address the problem of unsupervised web data extraction. we show that unsupervised web data extraction becomes feasible when supposing pages that are made up of repetitive patterns, as it is the case, e.g., for search engine result pages. hereby the extraction rules are generated automatically without any training or human interaction, by means of operating on the dom tree respectively the flat tag token sequence of a single page.our contribution to automatic data extraction through this paper is twofold. first, we identify and rank potential repetitive patterns with respect to the user's visual perception of the web page, well aware that location and size of matching elements within a web page constitute important criteria for defining relevance. second, matching sub-sequences of the pattern with the highest weightiness are aligned with global multiple sequence alignment techniques. experimental results show that our system is able to achieve high accuracy in distilling and aligning regularly structured objects inside complex web pages.
high dimensional reverse nearest neighbor queries. reverse nearest neighbor (rnn) queries are of particular interest in a wide range of applications such as decision support systems, profile based marketing, data streaming, document databases, and bioinformatics. the earlier approaches to solve this problem mostly deal with two dimensional data. however most of the above applications inherently involve high dimensions and high dimensional rnn problem is still unexplored. in this paper, we propose an approximate solution to answer rnn queries in high dimensions. our approach is based on the strong correlation in practice between k-nn and rnn. it works in two phases. in the first phase the k-nn of a query point is found and in the next phase they are further analyzed using a novel type of query boolean range query (brq). experimental results show that brq is much more efficient than both nn and range queries, and can be effectively used to answer rnn queries. performance is further improved by running multiple brq simultaneously. the proposed approach can also be used to answer other variants of rnn queries such as rnn of order k, bichromatic rnn, and matching query which has many applications of its own. our technique can efficiently answer nn, rnn, and its variants with approximately same number of i/o as running a nn query.
automated cleansing for spend analytics. the development of an aggregate view of the procurement spend across an enterprise using transactional data is increasingly becoming a very important and strategic activity. not only does it provide a complete and accurate picture of what the enterprise is buying and from whom, it also allows it to consolidate suppliers, as well as negotiate better prices. the importance, as well as the complexity, of this cleansing exercise is further magnified by the increasing popularity of business transformation outsourcing (bto) wherein enterprises are turning over non-core activities, such as indirect procurement, to third parties, who now need to develop an integrated view of spend across multiple enterprises in order to optimize procurement and generate maximum savings. however, the creation of such an integrated view of procurement spend requires the creation of a homogeneous data repository from disparate (heterogeneous) data sources across various geographic and functional organizations throughout the enterprise(s). such repositories get transactional data from various sources such as invoices, purchase orders, account ledgers. as such, the transactions are not cross-indexed, refer to the same suppliers by different names, and use different ways of representing information about the same commodities. before an aggregated spend view can be developed, this data needs to be cleansed, primarily to normalize the supplier names and correctly map each transaction to the appropriate commodity code. commodity mapping, in particular, is made more difficult by the fact that it has to be done on the basis of unstructured text descriptions found in the various data sources. we describe an on-demand system to automatically perform this cleansing activity using techniques from information retrieval and machine learning. built on standard integration and application infrastructure software, this system provides enterprises with a fast, reliable, accurate and on-demand way of cleansing transactional data and generating an integrated view of spend. this system is currently in the process of being deployed by ibm for use in its bto practice.
design of a data warehouse system for network/web services. this paper describes the architecture and design of a data warehouse for at&t business services. the main purpose of our system is to generate reports about the performance and reliability of the network. we describe the architecture of our system and discuss some open research problems in this area.
similarity based retrieval from sequence databases using automata as queries. similarity based retrieval from sequence databases is of importance in many applications such as time-series, video and textual databases. in this paper, automata based formalisms are introduced for specifying queries over such databases. various measures defining the distance of a database sequence from an automaton are defined. efficient methods for similarity based retrieval are presented for each of the distance measures. these methods answer nearest neighbor queries (i.e. retrieval of k closest subsequences), or range queries (i.e., retrieval of all sequences with in a given distance).
an adaptive view element framework for multi-dimensional data management. we present an adaptive wavelet view element framework for managing different types of multi-dimensional data in storage and retrieval applications. we consider the problems of multi-dimensional data compression, multi-resolution subregion access, selective materialization, progressive retrieval and similarity searching. the framework uses wavelets to partition the multi-dimensional data into view elements that form the building blocks for synthesizing views of the data. the view elements are organized and managed using different view element graphs. the graphs are used to guide cost-based view element selection algorithms for optimizing compression, access, retrieval and search performance.we present the adaptive wavelet view element framework and describe its application in managing multi-dimensional data such as 1-d time series data, 2-d images, video sequences, and multi-dimensional data cubes. we present experimental results that demonstrate that the adaptive wavelet view element framework improves performance of compressing, accessing, and retrieving multi-dimensional data compared to non-adaptive methods.
securely sharing neuroimagery. shared scientific data, such as neuroimagery, offers great benefits to science. however, data owners must exercise custodial responsibilities which can conflict with the unhindered sharing of their data. given simple choices of sharing widely or not at all, the result will frequently be no sharing. we hypothesize that neuroimagery sharing will be enhanced if data owners are provided with well-defined intermediate levels of data visibility. in this paper, we describe a broadly applicable data sharing model, structured sharing communities (ssc), in which data becomes incrementally visible to communities structured as a complete partial-order; the associated properties of privacy and fairness regulate access to shared data. within ssc, a customized policy space is defined capturing the sharing relationships among specific collaborators.
a general language model for information retrieval. statistical language modeling has been successfully used for speech recognition, part-of-speech tagging, and syntactic parsing. recently, it has also been applied to information retrieval. according to this new paradigm, each document is viewed as a language sample, and a query as a generation process. the retrieved documents are ranked based on the probabilities of producing a query from the corresponding language models of these documents. in this paper, we will present a new language model for information retrieval, which is based on a range of data smoothing techniques, including the good-turning estimate, curve-fitting functions, and model combinations. our model is conceptually simple and intuitive, and can be easily extended to incorporate probabilities of phrases such as word pairs and word triples. the experiments with the wall street journal and trec4 data sets showed that the performance of our model is comparable to that of inquery and better than that of another language model for information retrieval. in particular, word pairs are shown to be useful in improving the retrieval performance.
transformation-based spatial join. spatial join finds pairs of spatial objects having a specific spatial relationship in spatial database systems. a number of spatial join algorithms have recently been proposed in the literature. most of them, however, perform the join in the original space. joining in the original space has a drawback of dealing with sizes of objects and thus has difficulty in developing a formal algorithm that does not rely on heuristics. in this paper, we propose a spatial join algorithm based on the transformation technique. an object having a size in the two-dimensional original space is transformed into a point in the four-dimensional transform space, and the join is performed on these point objects. this can be easily extended to n-dimensional cases. we show the excellence of the proposed approach through analysis and extensive experiments. the results show that the proposed algorithm has a performance generally better than that of the r*-based algorithm proposed by brinkhoff et al. this is a strong indicating that corner transformation preserves clustering among objects and that spatial operations can be performed better in the transform space than in the original space. this reverses the common belief that transformation will adversely affect clustering. we believe that our result will provide a new insight towards transformation-based spatial query processing.
adaptive commitment for distributed real-time transactions. distributed real-time transaction systems are useful for both real-time and high-performance database applications. standard transaction management approaches that use the two-phase commit protocol suffer from its high costs and blocking behavior which is problematic in real-time computing environments. our approach in this paper is to identify ways in which a commit protocol can be made adaptive in the sense that under situations that demand it, such as a transient local overload, the system can dynamically change to a different commitment strategy. the decision to do so can be taken autonomously at any site. the different commitment strategies exploit a trade-off between the cost of commitment and the obtained degree of atomicity. our protocols are based on optimistic commitment strategies, and they rely on local compensatory actions to recover from non-atomic executions. we provide the necessary framework to study the logical and temporal correctness criteria, and we describe examples to illustrate the use of our strategies.
unapparent information revelation: a concept chain graph approach. information generated by multiple authors working independently at different times when analyzed synergistically reveals more information than apparent. for example, a traditional search for connections between the trucking industry and iraqi banks may not produce any documents mentioning both. however, a search that follows trails of associations across documents may suggest a connection between an auto parts manufacturer who exports to iraq, and an iraqi bank providing loans to buy cars. the work described here extends link analysis based on named entities and labeled relationships to general concepts and unnamed associations. unapparent information revelation involves finding chains connecting concepts across documents: it uses a new representation formalism called concept chain graphs.
exploiting syntactic structure of queries in a language modeling approach to ir. natural language processing (nlp) techniques have been explored to enhance the performance of information retrieval (ir) methods with varied results. most efforts in using nlp techniques have been to identify better index terms for representing documents. this use in the indexing phase of ir has implicit effect on retrieval performance. however, the explicit use of nlp techniques during the retrieval or information seeking phase has been restricted to interactive or dialogue systems. recent advances in ir are based on using statistical language models (slm) to represent documents and ranking them based on their model generating a given user query. this paper presents a novel method for using nlp techniques on user queries, specifically, a syntactic parse of a query, in the statistical language modeling approach to ir. in the proposed method, named concept language models, a query is viewed as a sequence of concepts and a concept as a sequence terms. the paper presents different approximations to estimate the concept and term probabilities and compute the query likelihood estimate for documents. some empirical results on trec test collections comparing concept language models with smoothed n-gram language models are presented.
grammar-based task analysis of web logs. the daily use of internet-based services is involved with hundreds of different tasks being performed by multiple users. a single task is typically involved with a sequence of web urls invocation. we study the problem of pattern detection in web logs to identify tasks performed by users, and analyze task trends over time using a grammar-based framework. our results are demonstrated on a corporate intranet portal application with 7000 users over a 6 week period and demonstrate compelling business value from this high-level task analysis.
a compact and efficient image retrieval approach based on border/interior pixel classification. this paper presents \bic (border/interior pixel classification), a compact and efficient cbir approach suitable for broad image domains. it has three main components: (1) a simple and powerful image analysis algorithm that classifies image pixels as either border or interior, (2) a new logarithmic distance (dlog) for comparing histograms, and (3) a compact representation for the visual features extracted from images. experimental results show that the bic approach is consistently more compact, more efficient and more effective than state-of-the-art cbir approaches based on sophisticated image analysis algorithms and complex distance functions. it was also observed that the dlog distance function has two main advantages over vectorial distances (e.g., l1): (1) it is able to increase substantially the effectiveness of (several) histogram-based cbir approaches and, at the same time, (2) it reduces by 50% the space requirement to represent a histogram.
raindrop: a uniform and layered algebraic framework for xqueries on xml streams. xml stream applications bring the challenge of efficiently processing queries on sequentially accessible token-based data. while the automata model is naturally suited for pattern matching on tokenized xml streams, the algebraic model in contrast is a well-established technique for set-oriented processing of self-contained tuples. however, neither automata nor algebraic models are well-equipped to handle both computation paradigms. the goal of the raindrop project is to accommodate these two paradigms within one algebraic framework to take advantage of both. in our query model, both tokenized data and self-contained tuples are supported in a uniform manner. query plans can be flexibly rewritten using equivalence rules to change what computation is done using tokenized data versus tuples. this paper highlights the four abstraction levels in raindrop, namely, semantics-focused plan, stream logical plan, stream physical plan and execution plan. various optimization techniques are provided at each level. the necessity of such a uniform and layered plan is shown by experimental study
information extraction from biomedical literature: methodology, evaluation and an application. journals and conference proceedings represent the dominant mechanisms of reporting new biomedical results. the unstructured nature of such publications makes it difficult to utilize data mining or automated knowledge discovery techniques. annotation (or markup) of these unstructured documents represents the first step in making these documents machine analyzable. in this paper we first present a system called bioannotator for identifying and annotating biological terms in documents. bioannotator uses domain based dictionary look-up for recognizing known terms and a rule engine for discovering new terms. the combination and dictionary look-up and rules result in good performance (87% precision and 94% recall on the genia 1.1 corpus for extracting general biological terms based on an approximate matching criterion). to demonstrate the subsequent mining and knowledge discovery activities that are made feasible by bioannotator, we also present a system called medsummarizer that uses the extracted terms to identify the common concepts in a given group of genes.
web unit mining: finding and classifying subgraphs of web pages. in web classification, most researchers assume that the objects to classify are individual web pages from one or more web sites. in practice, the assumption is too restrictive since a web page itself may not always correspond to a concept instance of some semantic concept (or category) given to the classification task. in this paper, we want to relax this assumption and allow a concept instance to be represented by a subgraph of web pages or a set of web pages. we identify several new issues to be addressed when the assumption is removed, and formulate the web unit mining problem. we also propose an iterative web unit mining (iwum) method that first finds subgraphs of web pages using some knowledge about web site structure. from these web subgraphs, web units are constructed and classified into semantic concepts (or categories) in an iterative manner. our experiments using the webkb dataset showed that iwum improves the overall classification performance and works very well on the more structured parts of a web site.
extracting significant time varying features from text. we propose a simple statistical model for the frequency of occurrence of features in a stream of text. adoption of this model allows us to use classical significance tests to filter the stream for interesting events. we tested the model by building a system and running it on a news corpus. by a subjective evaluation, the system worked remarkably well: almost all of the groups of identified tokens corresponded to news stories and were appropriately placed in time. a preliminary objective evaluation was also used to measure the quality of the system and it showed some of the weaknesses and the power of our approach.
a competition-based connectionist model for information retrieval using a merged thesaurus. this paper investigates a network-based information retrieval model using diagnostic inferencing techniques. a basic inference network in information retrieval consists of two component networks: the document component and the query component. in our approach, there is a layer of nodes corresponding to the documents, and a layer of nodes corresponding to the index terms extracted from the document set, with links connecting documents to the related index terms 1. a thesaurus is used to provide concept categories; these categories are represented by another layer of nodes, with links connecting the index terms and the related categories 2. the query component uses a symmetric structure. each query causes markings of category nodes, hence markings of the related index term nodes, in the document component of the network. in our previous work, we adapted a competition-based connectionist model for diagnostic problem solving to information retrieval. in this model, documents are treated as &ldquo;disorders&rdquo; and user information needs, represented by the marked index term nodes, as &ldquo;manifestations&rdquo;. a competitive activation mechanism is then used which converges to a set of disorders that best explain the given manifestations. our experiments showed that the retrieval performance of this model is comparable to or better than that of various information retrieval models reported in the literature. in this paper, we report further enhancements of the model by using a merged thesaurus.
associative document retrieval by query subtopic analysis and its application to invalidity patent search. we propose an associative document retrieval method, in which a document is used as a query to search for other similar documents. because a long document usually includes more than one topic, we first analyze a query document to extract multiple subtopics. for each subtopic element, a sub-query is produced and similar documents are retrieved with a relevance score. the relevance scores are weighted by the importance of each subtopic element and are integrated to determine the final relevant documents. in the calculation of the subtopic importance, the specificity of a query term is evaluated using entropy, which is the deviation degree of the appearances of the term in each subtopic element. we apply this method to an invalidity patent search. by exploiting certain unique features of japanese patent claims, we use features distinguishing the preamble and the essential portion in a query patent claim. to demonstrate the effectiveness of our method, we experimentally evaluated our associative document retrieval method on five years of patent documents.
from object evolution to object emergence. database applications which model aspects of the real world should be able to express as accurately as possible the different nuances of reality; that includes the need to evolve internally in response to signals of updates coming from the environment. these updates are not always supplied in an ideal and complete manner and are not always predefined or precisely defined. in practice, requirements for evolution generally occur during the manipulation of objects while running the database. it is frequently necessary to change individual objects, less frequently the database schema. database systems need to have mechanisms capable, whenever and as well as possible, of assimilating this new information correctly and diagnosing and implementing the changes necessary.this paper concerns the evolution of objects inside databases. our two main objectives are:to allow objects to evolve their structures dynamically during database maintenance and use, with all necessary impacts on the database schema;to allow, similarly, the creation and display of different plans for evolving the design, like ways of schema evolution, giving in this way a simulation tool for database design and maintenance.so, we propose a genetic evolution object model developed to have inherent capabilities for auto-adaptation between classes and instances.
a novel refinement approach for text categorization. in this paper we present a novel strategy, dragpushing, for improving the performance of text classifiers. the strategy is generic and takes advantage of training errors to successively refine the classification model of a base classifier. we describe how it is applied to generate two new classification algorithms; a refined centroid classifier and a refined naïve bayes classifier. we present an extensive experimental evaluation of both algorithms on three english collections and one chinese corpus. the results indicate that in each case, the refined classifiers achieve significant performance improvement over the base classifiers used. furthermore, the performance of the refined centroid classifier implemented is comparable, if not better, to that of state-of-the-art support vector machine (svm)-based classifier, but offers a much lower computational cost.
balancing performance and confidentiality in air index. studies on the performance issues (i.e., access latency and energy conservation) of wireless data broadcast have appeared in the literature. however, the important security issues have not been well addressed. this paper investigates the tradeoff between performance and security of signature-based air index schemes in wireless data broadcast. from the performance perspective, keeping low false drop probability helps clients retrieve the information from a broadcast channel efficiently. meanwhile, from the security perspective, achieving high false guess probability prevents the hacker from guessing the information easily. there is a tradeoff between these two aspects. an administrator of the wireless broadcast system may balance this tradeoff by carefully configuring the signatures used in broadcast. this study provides a guidance for parameter settings of the signature schemes in order to meet the performance and security requirements. experiments are performed to validate the analytical results and to obtain optimal signature configuration corresponding to different application criteria.
focused crawling for both topical relevance and quality of medical information. subject-specific search facilities on health sites are usually built using manual inclusion and exclusion rules. these can be expensive to maintain and often provide incomplete coverage of web resources. on the other hand, health information obtained through whole-of-web search may not be scientifically based and can be potentially harmful.to address problems of cost, coverage and quality, we built a focused crawler for the mental health topic of depression, which was able to selectively fetch higher quality relevant information. we found that the relevance of unfetched pages can be predicted based on link anchor context, but the quality cannot. we therefore estimated quality of the entire linking page, using a learned ir-style query of weighted single words and word pairs, and used this to predict the quality of its links. the overall crawler priority was determined by the product of link relevance and source quality.we evaluated our crawler against baseline crawls using both relevance judgments and objective site quality scores obtained using an evidence-based rating scale. both a relevance focused crawler and the quality focused crawler retrieved twice as many relevant pages as a breadth-first control. the quality focused crawler was quite effective in reducing the amount of low quality material fetched while crawling more high quality content, relative to the relevance focused crawler.analysis suggests that quality of content might be improved by post-filtering a very big breadth-first crawl, at the cost of substantially increased network traffic.
an iterative strategy for pattern discovery in high-dimensional data sets. high-dimensional data representation in which each data item (termed target object) is described by many features, is a necessary component of many applications. for example, in dna microarrays, each sample (target object) is represented by thousands of genes as features. pattern discovery of target objects presents interesting but also very challenging problems. the data sets are typically not task-specific, many features are irrelevant or redundant and should be pruned out or filtered for the purpose of classifying target objects to find empirical pattern. uncertainty about which features are relevant makes it difficult to construct an informative feature space. this paper proposes an iterative strategy for pattern discovery in high-dimensional data sets. in this approach, the iterative process consists of two interactive components: discovering patterns within target objects and pruning irrelevant features. the performance of the proposed method with various real data sets is also illustrated.
mining multiple phenotype structures underlying gene expression profiles. dna microarray technology is now widely used in basic biomedical research for mrna expression profiling and are increasingly being used to explore patterns of gene expression in clinical research. automatically detecting phenotype structures from gene expression profiles can provide deep insight into the nature of many diseases as well as lead in the development of new drugs. while most of the previous studies focus on only mining empirical phenotype structure which the experiment controls, it is also interesting to detect possible hidden phenotype structures underlying gene expression profiles.since the number of samples is usually limited, such data sets are very sparse in high-dimensional gene space. furthermore, most of the genes of interest are buried in large amount of noise. unsupervised phenotype structure discovery of such sparse high-dimensional data sets present interesting but challenging problems. in this paper, we propose the model of simultaneously mining both empirical and hidden phenotype structures from gene expression data. we demonstrate the effectiveness and efficiency of the proposed method on various real-world data sets.
queryable acyclic production systems. we pose a query problem about the behavior of a consultation system s: given a constraint formula q and a potential conclusion c for s, determine if there is a user input binding that satisfies q and causes s to conclude c. existing rule-based expert systems, both forward and backward chaining[3], implement a consultation mechanism s, but are not designed for these queries about s. for general production systems, the queries are undecidable. here we solve the problem for useful sublanguages of acyclic production systems.we implement a query tool in a datalog + constraints framework, and optimize for &ldquo;embedded decision trees&rdquo; in the rule system. our data complexity is &thgr;(n&middot;&fnof;(n)) in the size of the embedded trees, versus &thgr;(n&middot;&fnof;(n) + n2) for existing datalog evaluation algorithms, where &fnof;(n) is the cost of destructively conjoining a constraint of unit size into a conjunction of n constraints.
the power-method: a comprehensive estimation technique for multi-dimensional queries. existing estimation approaches for multi-dimensional databases often rely on the assumption that data distribution in a small region is uniform, which seldom holds in practice. moreover, their applicability is limited to specific estimation tasks under certain distance metric. this paper develops the power-method, a comprehensive technique applicable to a wide range of query optimization problems under various metrics. the power-method eliminates the local uniformity assumption and is accurate even in scenarios where existing approaches completely fail. furthermore, it performs estimation by evaluating only one simple formula with minimal computational overhead. extensive experiments confirm that the power-method outperforms previous techniques in terms of accuracy and applicability to various optimization scenarios.
scoring missing terms in information retrieval tasks. an usual approach to address mismatching vocabulary problem is to augment the original query using dictionaries and other lexical resources and/or by looking at pseudo-relevant documents. either way, terms are added to form a new query that will be used to score all documents in a subsequent retrieval pass, and as consequence the original query's focus may drift because of the newly added terms. we propose a new method to address the mismatching vocabulary problem, expanding original query terms only when necessary and complementing the user query for missing terms while scoring documents. it allows related semantic aspects to be included in a conservative and selective way, thus reducing the possibility of query drift. our results using replacements for the <i>missing query terms</i> in modified document and passages retrieval methods show significant improvement over the original ones.
semantic querying of tree-structured data sources using partially specified tree patterns. nowadays, huge volumes of data are organized or exported in a tree-structured form. querying capabilities are provided through queries that are based on branching path expression. even for a single knowledge domain structural differences raise difficulties for querying data sources in a uniform way. in this paper, we present a method for semantically querying tree-structured data sources using partially specified tree patterns. based on dimensions which are sets of semantically related nodes in tree structures, we define dimension graphs. dimension graphs can be automatically extracted from trees and abstract their structural information. they are semantically rich constructs that support the formulation of queries and their efficient evaluation. we design a tree-pattern query language to query multiple tree-structured data sources. a central feature of this language is that the structure can be specified fully, partially, or not at all in the queries. therefore, it can be used to query multiple trees with structural differences. %and we study the derivation of structural expressions in queries by introducing a set of inference rules for structural expressions. we define two types of query unsatisfiability and we provide necessary and sufficient conditions for checking each of them. our approach is validated through experimental evaluation.
query-sensitive similarity measures for the calculation of interdocument relationships. the application of document clustering to information retrieval has been motivated by the potential effectiveness gains postulated by the cluster hypothesis. the hypothesis states that relevant documents tend to be highly similar to each other, and therefore tend to appear in the same clusters. in this paper we propose that, for any given query, pairs of relevant documents will exhibit an inherent similarity which is dictated by the query itself. our research describes an attempt to devise means by which this similarity can be detected. we propose the use of query-sensitive similarity measures that bias interdocument relationships towards pairs of documents that jointly possess attributes that are expressed in a query. we experimentally tested query-sensitive measures against conventional ones that do not take the context of the query into account. we calculated interdocument relationships for varying numbers of top-ranked documents for five document collections. our results show a consistent and significant increase in the number of relevant documents that become nearest neighbours of any given relevant document when query-sensitive measures are used. these results suggest that the effectiveness of a cluster-based ir system has the potential to increase through the use of query-sensitive similarity measures.
calculating similarity between texts using graph-based text representation model. knowledge discovery from a large volumes of texts usually requires many complex analysis steps. the graph-based text representation model has been proposed to simplify the steps. the model represents texts in a formal manner, subject graphs, and provides text handling operations whose inputs and outputs are identical in form, i.e. a set of subject graphs, so they can be combined in any order. a subject graph uses node weight to represent the significance of each term, and link weight to represent that of each term-term association. this paper concentrates on the algorithms for making subject graphs and calculating the similarity between them. an evaluation shows that subject graphs can calculate the similarity between texts more precisely than term vectors, since they incorporate the significance of association between terms.
a new framework to combine descriptors for content-based image retrieval. in this paper, we propose a novel framework using genetic programming to combine image database descriptors for content-based image retrieval (cbir). our framework is validated through several experiments involving two image databases and specific domains, where the images are retrieved based on the shape of their objects.
visual structures for image browsing. content-based image retrieval (cbir) presents several challenges and has been subject to extensive research from many domains, such as image processing or database systems. database researchers are concerned with indexing and querying, whereas image processing experts worry about extracting appropriate image descriptors. comparatively little work has been done on designing user interfaces for cbir systems. this, in turn, has a profound effect on these systems since the concept of image similarity is strongly influenced by user perception. this paper describes an initial effort to fill this gap, combining recent research in cbir and information visualization, studied from a human-computer interface perspective. it presents two visualization techniques based on spiral and concentric rings implemented in a cbir system to explore query results. the approach is centered on keeping user focus on both the query image, and the most similar retrieved images. experiments conducted so far suggest that the proposed visualization strategies improves system usability.
vulnerabilities in similarity search based systems. similarity based queries are common in several modern database applications, such as multimedia, scientific, and biomedical databases. in most of these systems, database responds with the tuple with the closest match according to some metric. in this paper we investigate some important security issues related to similarity search in databases. we investigate the vulnerability of such systems against users who try to copy the database by sending automated queries. we analyze two models for similarity search, namely reply model and score model. reply model responds with the tuple with best match and score model responds with only the score of similarity search. for these models we analyze possible ways of attacks and strategies that can be used to detect attacks. our analysis shows that in score model it is much easier to plug the vulnerabilities than in reply model. sophisticated attacks can easily be used in reply model and the database is limited in capability to prevent such attacks.
text classification in a hierarchical mixture model for small training sets. documents are commonly categorized into hierarchies of topics, such as the ones maintained by yahoo! and the open directory project, in order to facilitate browsing and other interactive forms of information retrieval. in addition, topic hierarchies can be utilized to overcome the sparseness problem in text categorization with a large number of categories, which is the main focus of this paper. this paper presents a hierarchical mixture model which extends the standard naive bayes classifier and previous hierarchical approaches. improved estimates of the term distributions are made by differentiation of words in the hierarchy according to their level of generality/specificity. experiments on the newsgroups and the reuters-21578 dataset indicate improved performance of the proposed classifier in comparison to other state-of-the-art methods on datasets with a small number of positive examples.
how to improve the pruning ability of dynamic metric access methods. complex data retrieval is accelerated using index structures, which organize the data in order to prune comparisons between data during queries. in metric spaces, comparison operations can be specially expensive, so the pruning ability of indexing methods turns out to be specially meaningful. this paper shows how to measure the pruning power of metric access methods, and defines a new measurement, called "prunability," which indicates how well a pruning technique carries out the task of cutting down distance calculations at each tree level. it also presents a new dynamic access method, aiming to minimize the number of distance calculations required to answer similarity queries. we show that this novel structure is up to 3 times faster and requires less than 25% distance calculations to answer similarity queries, as compared to existing methods. this gain in performance is achieved by taking advantage of a set of global representatives. although our technique uses multiple representatives, the index structure still remains dynamic and balanced.
merging techniques for performing data fusion on the web. data fusion on the web refers to the merging, into a unified single list, of the ranked document lists, which are retrieved in response to a user query by more than one web search engine. it is performed by metasearch engines and their merging algorithms utilise the information present in the ranked lists of retrieved documents provided to them by the underlying search engines, such as the rank positions of the retrieved documents and their retrieval scores. in this paper, merging techniques are introduced that take into account not only the rank positions, but also the title and the summary accompanying the retrieved documents. furthermore, the data fusion process is viewed as being similar to the combination of belief in uncertain reasoning and is modelled using dempster-shafer's theory of evidence. our evaluation experiments indicate that the above merging techniques yield improvements in the effectiveness and that their effectiveness is comparable to that of the approach that merges the ranked lists by downloading and analysing the web documents.
managing ifc for civil engineering projects. the "industrial foundation classes" (ifc) are an iso norm to define all components of a building in a civil engineering project. ifc files are textual files whose size can reach 100 megabytes. several ifc files can coexist on the same civil engineering project. due to their size, their handling and sharing is a complex task. in this paper, we present an approach to automatically identify business objects in the ifc files and simplify their visualization and manipulation on the internet. we construct an ifc viewer which transforms the ifc file into a xml ifc tree manipulated through the 3d visualization of the building. the ifc viewer composed a web-based platform called active3d build server. this platform lets geographically dispersed project participants-from architects to electricians-directly use and exchange project documents in a centralized virtual environment during the life cycle of a civil engineering project.
structure-based query-specific document summarization. summarization of text documents is increasingly important with the amount of data available on the internet. the large majority of current approaches view documents as linear sequences of words and create query-independent summaries. however, ignoring the structure of the document degrades the quality of summaries. furthermore, the popularity of web search engines requires query-specific summaries. we present a method to create query-specific summaries by adding structure to documents by extracting associations between their fragments.
preserving update semantics in schema integration. in this paper, we propose a methodology for schema integration where the semantics of updates is preserved during the view integration process. we propose to divide view integration into three steps: combination, restructuring, and optimization. in the view combination step, we define the combined schema that contains all original views, plus a new set of constraints that express how data in distinct views are interrelated. the restructuring step is devoted to normalizing the views so that merging becomes possible. the optimization step tries to reduce redundancy and the size of the schema. our methodology defines a set of transformation primitives that allows schema integration to be realized in a safe (information preserving) and algorithmic way. in the proposed transformation primitives, the relationship between the original and transformed schema is formally specified by the instance and update mappings. we introduce the notion of an update semantics preserving transformation, which guarantees that the relationships between each view and the global schema, originated during the view integration process, reflect exactly the relationships between the views as defined by the combined schema. in our approach, the view definition mappings and the view update translator can be directly defined from the instance and update mappings between the different intermediate schemas generated during the view integration process.
rotation invariant indexing of shapes and line drawings. we present data representations, distance measures and organizational structures for fast and efficient retrieval of similar shapes in image databases. using the hough transform we extract shape signatures that correspond to important features of an image. the new shape descriptor is robust against line discontinuities and takes into consideration not only the shape boundaries, but also the content inside the object perimeter. the object signatures are eventually projected into a space that renders them invariant to translation, scaling and rotation. in order to provide support for real-time query-by-content, we also introduce an index structure that hierarchically organizes compressed versions of the extracted object signatures. in this manner we can achieve a significant performance boost for multimedia retrieval. our experiments suggest that by exploiting the proposed framework, similarity search in a database of 100,000 images would require under 1 sec, using an off-the-shelf personal computer.
question answering in trec. traditional text retrieval systems return a ranked list of documents in response to a user's request. while a ranked list of documents can be an appropriate response for the user, frequently it is not. usually it would be better for the system to provide the answer itself instead of requiring the user to search for the answer in a set of documents. the text retrieval conference (trec) is sponsoring a question answering "track" to foster research on the problem of retrieving answers rather than document lists.trec is a workshop series sponsored by the national institute of standards and technology and the u.s. department of defense [7]. the purpose of the conference series is to encourage research on text retrieval for realistic applications by providing large test collections, uniform scoring procedures, and a forum for organizations interested in comparing results. the conference has focused primarily on the traditional ir problem of retrieving a ranked list of documents in response to a statement of information need, but has also included other tasks, called tracks, that focus on new areas or particularly difficult aspects of information retrieval. a question answering track was introduced in trec-8 1999. the track has generated wide-spread interest in the qa problem [2, 3, 4], and has documented significant improvements in question answering system effectiveness in its two-year history.this paper provides a brief summary of the findings of the trec question answering track to date and discusses the future directions of the track. the paper is extracted from a fuller description of the track given in "the trec question answering track" [8]. complete details about the trec question answering track can be found in the trec proceedings.
efficient and effective metasearch for a large number of text databases. metasearch engines can be used to facilitate ordinary users for retrieving information from multiple local sources (text databases). in a metasearch engine, the contents of each local database is represented by a representative. each user query is evaluated against the set of representatives of all databases in order to determine the appropriate databases to search. when the number of databases is very large, say in the order of tens of thousands or more, then a traditional metasearch engine may become inefficient as each query needs to be evaluated against too many database representatives. furthermore, the storage requirement on the site containing the metasearch engine can be very large. in this paper, we propose to use a hierarchy of database representatives to improve the efficiency. we provide an algorithm to search the hierarchy. we show that the retrieval effectiveness of our algorithm is the same as that of evaluating the user query against all database representatives. we also show that our algorithm is efficient. in addition, we propose an alternative way of allocating representatives to sites so that the storage burden on the site containing the metasearch engine is much reduced.
simple qsf-trees: an efficient and scalable spatial access method. the development of high-performance spatial access methods that can support complex operations of large spatial databases continues to attract considerable attention. this paper introduces qsf-trees, an efficient and scalable structure for indexing spatial objects, which has some important advantages over r*-trees. qsf-trees eliminate overlapping of index regions without forcing object clipping or sacrificing the selectivity of spatial operations. the method exploits the semantics of topological relations between spatial objects to further reduce the number of index nodes visited during the search. a series of experiments involving randomly-generated spatial objects was conducted to compare the structure with two variations of r*-trees. the experiments show qsf-trees to be more efficient and more scalable to the increase in the data-set size, the size of spatial objects, and the number of dimensions of the spatial universe.
person resolution in person search results: webhawk. finding information about people on the web using a search engine is difficult because there is a many-to-many mapping between person names and specific persons (i.e. referents). this paper describes a person resolution system, called webhawk. given a list of pages obtained by submitting a person query to a search engine, webhawk facilitates person search in three steps: first of all, a filter removes those pages that contain no information about any person. secondly, a cluster groups the remaining pages into different clusters, each for one specific person. to make the resulting clusters more meaningful, an extractor is used to induce query-oriented personal information from each page. finally, a namer generates an informative description for each cluster so that users can find any specific person easily. the architecture of webhawk is presented, and the four components are discussed in detail, with a separate evaluation of each component presented where appropriate. a user study shows that webhawk complements most existing search engines and successfully improves users' experience of person search on the web.
an agent-based approach to knowledge management. traditional approaches to knowledge management are essentially limited to document management. however, much knowledge in organizations or communities resides in an informal social network and may be accessed only by asking the right people. this paper describes mars, a multiagent referral system for knowledge management. mars assigns a software agent to each user. the agents facilitate their users' interactions and help manage their personal social networks. moreover, the agents cooperate with one another by giving and taking referrals to help their users find the right parties to contact for a specific knowledge need.
the earth mover's distance as a semantic measure for document similarity. different words are usually assumed to be semantically independent in most existing similarity measures, which is not often true in practice. the semantic relatedness between words cannot be conveniently employed in the existing measures. we propose a novel similarity measure based on the earth mover's distance (emd). in the proposed measure, the semantic distances between words are computed based on the electronic lexical database-wordnet and then the emd is employed to calculate the document similarity with a many-to-many matching between words. experiments and results demonstrate the effectiveness of the proposed similarity measure.
selecting relevant instances for efficient and accurate collaborative filtering. collaborative filtering uses a database about consumers' preferences to make personal product recommendations and is achieving widespread success in both e-commerce and information filtering applications nowadays. however, the traditional collaborative filtering algorithms do not scale well to the ever-growing number of consumers. the quality of the recommendation also needs to be improved in order to gain more trust from the consumers. in this paper, we present a novel method to improve the scalability and the accuracy of the collaborative filtering algorithm. we introduce an information theoretic approach to measure the relevance of a consumer (instance) for predicting the preference for the given product (target concept). the proposed method reduces the training data set by selecting only highly relevant instances. our experimental evaluation on the well-known eachmovie data set shows that our method doesn't only significantly speed up the prediction, but also results in a better accuracy.
removing redundancy and inconsistency in memory-based collaborative filtering. the application range of memory-based collaborative filtering (cf) is limited due to cf's high memory consumption and long runtime. the approach presented in this paper removes redundant and inconsistent instances (users) from the data. this paper aims to distinguish informative instances (users) from large raw user preference database and thus alleviate the memory and runtime cost of the widely used memory-based collaborative filtering (cf) algorithm. our work shows that a satisfactory accuracy can be achieved by using only a small portion of the original data set, thereby alleviating the storage and runtime cost of the cf algorithm. in our approach, we consider instance selection as the problem of selecting informative data that increase the we begin by discussing the instance selection problem in a general sense that is to increase a posteriori probability of the optimal model by selecting informative data. we evaluate the empirical performance of our approach pf on two real-world data sets and attain very promisingpositive experimental results. the ddata size and the prediction time are significantly reduced, while the prediction accuracy is on a par with almost the same as the results achieved by using the complete database.
text classification from positive and unlabeled documents. most existing studies of text classification assume that the training data are completely labeled. in reality, however, many information retrieval problems can be more accurately described as learning a binary classifier from a set of incompletely labeled examples, where we typically have a small number of labeled positive examples and a very large number of unlabeled examples. in this paper, we study such a problem of performing text classification without labeled negative data tc-won). in this paper, we explore an efficient extension of the standard support vector machine (svm) approach, called svmc (support vector mapping convergence) [17]for the tc-won tasks. our analyses show that when the positive training data is not too under-sampled, svmc significantly outperforms other methods because svmc basically exploits the natural "gap" between positive and negative documents in the feature space, which eventually corresponds to improving the generalization performance. in the text domain there are likely to exist many gaps in the feature space because a document is usually mapped to a sparse and high dimensional feature space. however, as the number of positive training data decreases, the boundary of svmc starts overfitting at some point and end up generating very poor results.this is because when the positive training data is too few, the boundary over-iterates and trespasses the natural gaps between positive and negative class in the feature space and thus ends up fitting tightly around the few positive training data.
towards estimating the number of distinct value combinations for a set of attributes. accurately and efficiently estimating the number of distinct values for some attribute(s) or sets of attributes in a data set is of critical importance to many database operations, such as query optimization and approximation query answering. previous work has focused on the estimation of the number of distinct values for a single attribute and most existing work adopts a data sampling approach. this paper addresses the equally important issue of estimating the number of distinct value combinations for multiple attributes which we call colscard (for column set cardinality). it also takes a different approach that uses existing statistical information (e.g., histograms) available on the individual attributes to assist estimation. we start with cases where exact frequency information on individual attributes is available, and present a pair of lower and upper bounds on colscard that are consistent with the available information, as well as an estimator of colscard based on probability. we then proceed to study the case where only partial information (in the form of histograms) is available on individual attributes, and show how the proposed estimator can be adapted to this case. we consider two types of widely used histograms and show how they can be constructed in order to obtain optimal approximation. an experimental evaluation of the proposed estimation method on synthetic as well as two real data sets is provided.
a framework for mining topological patterns in spatio-temporal databases. mining topological patterns in spatial databases has received a lot of attention. however, existing work typically ignores the temporal aspect and suffers from certain efficiency problems. they are not scalable for mining topological patterns in spatio-temporal databases. in this paper, we study the problem for mining topological patterns by incorporating the temporal aspect in the mining process. we introduce a summary-structure that records the instances' count information of a feature in a region within a time window. using this structure, we design an algorithm, topologyminer, to find interesting topological patterns without the need to generate candidates. experimental results show that topologyminer is effective and scalable in finding topological patterns and outperforms apriori-like algorithm by a few orders of magnitudes.
evaluating contents-link coupled web page clustering for web search results. clustering is currently one of the most crucial techniques for dealing (e.g. resources locating, information interpreting) with massive amount of heterogeneous information on the web. unlike clustering in other fields, web page clustering separates unrelated pages and clusters related pages (to a specific topic) into semantically meaningful groups, which is useful for discrimination, summarization, organization and navigation of unstructured web pages. we have proposed a contents-link coupled clustering algorithm that clusters web pages by combining contents and link analysis. in this paper, we particularly study the effects of out-links (from the web pages), in-links (to the web page) and terms on the final clustering results as well as how to effectively combine these three parts to improve the quality of clustering results. we apply it to cluster web search results. preliminary experiments and evaluations are conducted on various topics. as the experimental results show, the proposed clustering algorithm is effective and promising.
feature selection with conditional mutual information maximin in text categorization. feature selection is an important component of text categorization. this technique can both increase a classifier's computation speed, and reduce the overfitting problem. several feature selection methods, such as information gain and mutual information, have been widely used. although they greatly improve the classifier's performance, they have a common drawback, which is that they do not consider the mutual relationships among the features. in this situation, where one feature's predictive power is weakened by others, and where the selected features tend to bias towards major categories, such selection methods are not very effective. in this paper, we propose a novel feature selection method for text categorization called <i>conditional mutual information maximin</i> (cmim). it can select a set of individually discriminating and weakly dependent features. the experimental results show that cmim can perform much better than traditional feature selection methods.
a latent semantic classification model. latent semantic indexing (lsi) has been successfully applied to information retrieval and text classification. however, when lsi is used in classification, some important features for small classes may be ignored because of their small feature values. to solve this problem, we propose the latent semantic classification (lsc) model which extends the lsi model in the following way: the classification information of the training documents is introduced into the latent semantic structure via a second set of latent variables, so that both indexing and classification information can be taken into account during the classification process. our experiments on reuters show that our new model performs better than the existing classification methods such as knn and svm.
using lsi for text classification in the presence of background text. this paper presents work that uses latent semantic indexing (lsi) for text classification. however, in addition to relying on labeled training data, we improve classification accuracy by also using unlabeled data and other forms of available "background" text in the classification process. rather than performing lsi's singular value decomposition (svd) process solely on the training data, we instead use an expanded term-by-document matrix that includes both the labeled data as well as any available and relevant background text. we report the performance of this approach on data sets both with and without the inclusion of the background text, and compare our work to other efforts that can incorporate unlabeled data and other background text in the classification process.
efficient refreshment of materialized views with multiple sources. a data warehouse collects and maintains a large amount of data from multiple distributed and autonomous data sources. often the data in it is stored in the form of materialized views in order to provide fast access to the integrated data. however, maintaining a certain level consistency of warehouse data with the source data is challenging in a distributed multiple source environment. transactions containing multiple updates at one or more sources further complicate the consistency issue.following the four level consistency definition of view in a warehouse, we first present a complete consistency algorithm for maintaining spj-type materialized views incrementally. our algorithm speed-ups the view refreshment time, provided that some extra moderate space in the warehouse is available. we then give a variant of the proposed algorithm by taking the update frequencies of sources into account. we finally discuss the relationship between a view's certain level consistency and its refresh time. it is difficult to propose an incremental maintenance algorithm such that the view is always kept at a certain level consistency with the source data and the view's refresh time is as fast as possible. we trade-off these two factors by giving an algorithm with faster view refresh time, while the view maintained by the algorithm is strong consistency rather than complete consistency with the source data.
knowledge and information management: is it possible to do interesting and important research, get funded, be useful and appreciated? the survey of the cikm call for papers for the period 1998 - 2002 demonstrates that the cikm organizers very accurately "identify challenging problems facing the development of future knowledge and information systems [in] applied and theoretical research" [1998] and also play an important role fostering "bridging traditionally separated areas such as databases and information retrieval, or those that apply techniques from one area to another" [2001, 2002]. the presented cikm papers also indicate that researchers work on interesting problems. this talk will discuss some additional research topics for future consideration by the cikm community.in most cases, to achieve important results, research needs to be well supported. if you are not getting the funding you need, this talk may provide some pointers where you can look for finding. if you are well supported, i will try to convince you that you can be instrumental in improving the funding scenario for everybody, by mentoring the junior members of the cikm community, by forming collaborative (international, interdisciplinary) teams and by letting the funders know what you find conducive to your research and what you consider a hindrance. regardless if you are well funded or not, it is most helpful if you are active in identifying new research directions and also assist in evaluating the priorities.the most frequent problem for inadequate funding is lack of funds. however, researchers can help! this can be achieved in many different ways: thinking about long-term applications of fundamental research to societal needs; working with communities that can directly benefit from research; sharing the research results not only with the research colleagues, but also wider constituencies - at their appropriate levels; and informing your funders about your spectacular achievements, i.e., providing good reasons for increasing the research funding.cikm strives to bring together research communities that traditionally do not work together. providing a forum for interdisciplinary research is laudable and very important, as very often interdisciplinary or international research is not "appreciated". this talk will discuss how we could gradually change the discipline- and country-based "appraisal" cultures. we will also attempt to answer the question: "what is the ultimate appreciation?" (nobel prize? ...successful .com?... ???).
web page clustering enhanced by summarization. traditional web page clustering algorithms use the full-text in the documents to generate feature vectors. such methods often produce unsatisfactory results because there is much noisy information, such as decoration, interaction, and advertisement, in web pages. the varying-length problem of the web pages is also a significant negative factor affecting the performance. in this paper, we investigate the use of several summarization techniques to tackle these issues when clustering web pages. compared with the full-text representation of the web pages, our experimental results indicate that our proposed approach effectively solves the problems of noisy information and varying-length, and thus significantly boosts the clustering performance.
model-based feedback in the language modeling approach to information retrieval. the language modeling approach to retrieval has been shown to perform well empirically. one advantage of this new approach is its statistical foundations. however, feedback, as one important component in a retrieval system, has only been dealt with heuristically in this new retrieval approach: the original query is usually literally expanded by adding additional terms to it. such expansion-based feedback creates an inconsistent interpretation of the original and the expanded query. in this paper, we present a more principled approach to feedback in the language modeling approach. specifically, we treat feedback as updating the query language model based on the extra evidence carried by the feedback documents. such a model-based feedback strategy easily fits into an extension of the language modeling approach. we propose and evaluate two different approaches to updating a query language model based on feedback documents, one based on a generative probabilistic model of feedback documents and one based on minimization of the kl-divergence over feedback documents. experiment results show that both approaches are effective and outperform the rocchio feedback approach.
weakly-supervised relation classification for information extraction. this paper approaches the relation classification problem in information extraction framework with bootstrapping on top of support vector machines. a new bootstrapping algorithm is proposed and empirically evaluated on the ace corpus. we show that the supervised svm classifier using various lexical and syntactic features can achieve promising classification accuracy. more importantly, the proposed <i>bootproject</i> algorithm based on random feature projection can significantly reduce the need for labeled training data with only limited sacrifice of performance.
clustering transactions using large items. in traditional data clustering, similarity of a cluster of objects is measured by pairwise similarity of objects in that cluster. we argue that such measures are not appropriate for transactions that are sets of items. we propose the notion of large items, i.e., items contained in some minimum fraction of transactions in a cluster, to measure the similarity of a cluster of transactions. the intuition of our clustering criterion is that there should be many large items within a cluster and little overlapping of such items across clusters. we discuss the rationale behind our approach and its implication on providing a better solution to the clustering problem. we present a clustering algorithm based on the new clustering criterion and evaluate its effectiveness.
intelligent gp fusion from multiple sources for text classification. this paper shows how citation-based information and structural content (e.g., title, abstract) can be combined to improve classification of text documents into predefined categories. we evaluate different measures of similarity -- five derived from the citation information of the collection, and three derived from the structural content -- and determine how they can be fused to improve classification effectiveness. to discover the best fusion framework, we apply genetic programming (gp) techniques. our experiments with the acm computing classification scheme, using documents from the acm digital library, indicate that gp can discover similarity functions superior to those based solely on a single type of evidence. effectiveness of the similarity functions discovered through simple majority voting is better than that of content-based as well as combination-based support vector machine classifiers. experiments also were conducted to compare the performance between gp techniques and other fusion techniques such as genetic algorithms (ga) and linear fusion. empirical results show that gp was able to discover better similarity functions than ga or other fusion techniques.
scalable sequential pattern mining for biological sequences. biosequences typically have a small alphabet, a long length, and patterns containing gaps (i.e., "don't care") of arbitrary size. mining frequent patterns in such sequences faces a different type of explosion than in transaction sequences primarily motivated in market-basket analysis. in this paper, we study how this explosion affects the classic sequential pattern mining, and present a scalable two-phase algorithm to deal with this new explosion. the <i>segment phase</i> first searches for short patterns containing no gaps, called <i>segments</i>. this phase is efficient. the <i>pattern phase</i> searches for long patterns containing multiple segments separated by variable length gaps. this phase is time consuming. the purpose of two phases is to exploit the information obtained from the first phase to speed up the pattern growth and matching and to prune the search space in the second phase. we evaluate this approach on synthetic and real life data sets.
combining structural and citation-based evidence for text classification. this paper discusses how citation-based information and structural content (e.g., title, abstract) can be combined to improve classification of text documents into predefined categories. we evaluate different measures of similarity derived from the citation structure and the structural content of the collection, and determine how they can be fused to improve classification effectiveness. to discover the best fusion framework, we apply genetic programming (gp) techniques. our empirical experiments using documents from the acm digital library and the acm computing classification system show that we can discover similarity functions that work better than using evidence in isolation and whose combined performance through a simple majority voting is comparable to that of support vector machine classifiers.
discovering strong skyline points in high dimensional spaces. current interests in skyline computation arise due to their relation to preference queries. since it is guaraneed that a skyline point will not lose out in all dimensions when compared to any other point in the data set, this means that for each skyline point, there exists a set of weight assignments to the dimensions such that the point will become the top user preference.we believe that the usefulness of skyline points is not limited to such application and can be extended to data analysis and knowledge discovery as well. however, since the skyline of high dimensional datasets (which are common in data analysis applications) can contain too many points, various means must be developed to filter off the less interesting skyline points in high dimensions. in this paper, we will propose algorithms to find a set of interesting skyline points called strong skyline points. extensive experiments show that our proposal is both effective and efficient.
infoanalyzer: a computer-aided tool for building enterprise taxonomies. in this paper we study the problem of collecting training samples for building enterprise taxonomies. we develop a computer-aided tool named infoanalyzer, which can effectively assist the enterprise to prepare large set of samples used for machine learning in text categorization. in our system, the enterprise category tree is initially defined by some keywords, then the google search engine is used to construct a small set of labeled documents, and topic tracking algorithm based on document length normalization is applied to enlarge the training corpus on the bases of the seed stories. furthermore, we design a method to check the consistency of the training corpus. experiments show that the training corpus is good enough for statistical classification methods and meets human's requirements as well.
rule-based query optimization, revisited. we present the architecture and a performance assessment of an extensible query optimizer written in venus. venus is a general-purpose active-database rule language embedded in c++. following the developments in extensible database query optimizers, first in rule-based form, followed by optimizers written as object-oriented programs, the venus-based optimizer avails to the advantages of both. venus' modular structure allows us to go a step further and provide extensibility in search by defining parameterized search components in a declarative form that has the additional effect of integrating heuristic and cost-based optimization. we compare optimizers developed with volcano, opt++ and venus. venus' optimizing compiler yields code whose performance is comparable with volcano and opt++ on smaller queries. the ability to introduce additional pruning heuristics yields better scalability on larger queries. evaluation of the system using quantitative software metrics supports a claim that the venus-based optimizer is more easily maintained and extended than are its predecessors.
architecture of a networked image search and retrieval system. large scale networked image retrieval systems face a number of problems that are not fully satisfied by current systems. on one hand, integrated solutions that store all image data centrally are often limited in terms of scalability and autonomy of data providers. on the other hand, www-based search engines proved to be fairly scalable, and data providers retain their autonomy. however, such engines often confront users with links to servers that are not available or to images that no longer exist, i.e., they are unable to keep their meta-database consistent with the repositories' contents. furthermore, existing solutions often neglect the cost of image delivery. the considerable variations in the effective bandwidth in today's internet lead to highly unpredictable response times, which are often intolerable from the user's point of view.this paper presents the architecture of chariot, a networked image search and retrieval system that tackles these concerns. with respect to scalability and autonomy, chariot follows the approach of www-based search engines by maintaining only the meta-data in a central database. various specialized components (feature extraction, indexes, images servers) are coordinated by a middleware component that employs transactional process management to enforce consistency between the meta-data and all components. moreover, chariot incorporates mechanisms to provide more predictable response times for the image delivery over the internet by employing network-aware image servers. these servers trade off the quality of the images to be delivered with the bandwidth required to transmit the images.
learning cross-document structural relationships using boosting. multi-document discoure analysis has emerged with the potential of improving various information retrieval applications. based on the newly proposed cross-document structure theory (cst), this paper describes an empirical study that uses boosting to classify cst relationships between sentence pairs extracted from topically related documents. we show that the binary classifier for determining existence of structural relationships significantly outperforms the baseline. we also achieve promising results on the multi-class case in which the full taxonomy of relationships are considered.
efficient region-based image retrieval. region-based image retrieval(rbir) was recently proposed as an extension of content-based image retrieval(cbir). an rbir system automatically segments images into a variable number of regions, and extracts for each region a set of features. then, a dissimilarity function determines the distance between a database image and a set of reference regions. unfortunately, the large evaluation costs of the dissimilarity function are restricting rbir to relatively small databases. in this paper, we apply a multi-step approach to enable region-based techniques for large image collections. we provide cheap lower and upper bounding distance functions for a recently proposed dissimilarity measure. as our experiments show, these bounding functions are so tight, that we have to evaluate the expensive distance function for less than 0.5\%of the images. for a typical image database with more than 370,000images, our multi-step approach improved retrieval performance by a factor of more than5 compared to the currently fastest methods.
mining conserved xml query paths for dynamic-conscious caching. existing xml query pattern-based caching strategies focus on extracting the set of frequently issued query pattern trees based on the number of occurrences of the query pattern trees in the history. each occurrence of the same query pattern tree is considered equally important for the caching strategy. however, the same query pattern tree may occur at different timepoints in the history of xml queries. this temporal feature can be used to improve the caching strategy. in this paper, we propose a novel type of query pattern called conserved query paths for efficient caching by integrating the support and temporal features together. conserved query paths are paths in query pattern trees that never change or do not change significantly most of the time (if not always) in terms of their support values during a specific time period. we proposed an algorithm to extract those conserved query paths. by ranking those conserved query paths, a dynamic-conscious caching (dcc) strategy is proposed for efficient xml query processing. experiments show that the dcc caching strategy outperforms the existing xml query pattern tree-based caching strategies.
wam-miner: in the search of web access motifs from historical web log data. existing web usage mining techniques focus only on discovering knowledge based on the statistical measures obtained from the static characteristics of web usage data. they do not consider the dynamic nature of web usage data. in this paper, we focus on discovering novel knowledge by analyzing the change patterns of historical web access sequence data. we present an algorithm called w<small>am</small>-m<small>iner</small> to discover web access motifs (wams). wams are web access patterns that never change or do not change significantly most of the time (if not always) in terms of their support values during a specific time period. wams are useful for many applications, such as intelligent web advertisement, web site restructuring, business intelligence, and intelligent web caching.
an approach for implicitly detecting information needs. searchers can have problems devising queries that accurately express their, often dynamic, information needs. in this paper we describe an adaptive approach that uses unobtrusive monitoring of interaction to help alleviate such problems and support searchers in their seeking. the approach we propose implicitly selects terms to better represent information needs, gathers evidence on potential changes in these needs, and uses this evidence to tailor the result presentation accordingly. a user evaluation of an interface implementing our approach, presented in [7], shows it can select terms that approximate current information needs and provide evidence to track changes in these needs.
discovering frequently changing structures from historical structural deltas of unordered xml. recently, a large amount of work has been done in xml data mining. however, we observed that most of the existing works focus on the snapshot xml data, while xml data is dynamic in real applications. to the best of our knowledge, none of the existing works has addressed the issue of mining the history of changes to xml documents. such mining results can be useful in many applications such as xml change detection, xml indexing, association rule mining, and classification etc. in this paper, we propose a novel approach to discover the <i>frequently changing structures</i> from the sequence of historical <i>structural deltas</i> of unordered xml. to make the structure discovering process efficient, an expressive and compact data model, <b>h</b>istorical-<b>d</b>ocument <b>o</b>bject <b>m</b>odel (<b>h-dom</b>), is proposed. using this model, two basic algorithms, which can discover all the <i>frequently changing structures</i> with only two scans of the xml sequence, are presented. experimental results show that our algorithms, together with the optimization techniques, are efficient and scalable.
using appraisal groups for sentiment analysis. little work to date in sentiment analysis (classifying texts by `positive' or `negative' orientation) has attempted to use fine-grained semantic distinctions in features used for classification. we present a new method for sentiment classification based on extracting and analyzing appraisal groups such as ``very good'' or ``not terribly funny''. an appraisal group is represented as a set of attribute values in several task-independent semantic taxonomies, based on appraisal theory. semi-automated methods were used to build a lexicon of appraising adjectives and their modifiers. we classify movie reviews using features based upon these taxonomies combined with standard ``bag-of-words'' features, and report state-of-the-art accuracy of 90.2%. in addition, we find that some types of appraisal appear to be more significant for sentiment classification than others.
evaluation of hierarchical clustering algorithms for document datasets. fast and high-quality document clustering algorithms play an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. in particular, hierarchical clustering solutions provide a view of the data at different levels of granularity, making them ideal for people to visualize and interactively explore large document collections.in this paper we evaluate different partitional and agglomerative approaches for hierarchical clustering. our experimental evaluation showed that partitional algorithms always lead to better clustering solutions than agglomerative algorithms, which suggests that partitional clustering algorithms are well-suited for clustering large document datasets due to not only their relatively low computational requirements, but also comparable or even better clustering performance. we present a new class of clustering algorithms called constrained agglomerative algorithms that combine the features of both partitional and agglomerative algorithms. our experimental results showed that they consistently lead to better hierarchical solutions than agglomerative or partitional algorithms alone.
strategies for minimising errors in hierarchical web categorisation. on the web, browsing and searching categories is a popular method of finding documents. two well-known category-based search systems are the yahoo!~and dmoz hierarchies, which are maintained by experts who assign documents to categories. however, manual categorisation by experts is costly, subjective, and not scalable with the increasing volumes of data that must be processed. several methods have been investigated for effective automatic text categorisation. these include selection of categorisation methods, selection of pre-categorised training samples, use of hierachies, and selection of document fragments or features. in this paper, we further investigate categorisation into web hierarchies and the role of hierarchical information in improving categorisation effectiveness. we introduce new strategies to reduce errors in hierarchical categorisation. in particular, we propose novel techniques that shift the assignment into higher level categories when lower level assignment is uncertain. our results show that absolute error rates can be reduced by over 2%.
soft clustering criterion functions for partitional document clustering: a summary of results. recently published studies have shown that partitional clustering algorithms that optimize certain criterion functions, which measure key aspects of inter- and intra-cluster similarity, are very effective in producing hard clustering solutions for document datasets and outperform traditional partitional and agglomerative algorithms. in this paper we study the extent to which these criterion functions can be modified to include soft membership functions and whether or not the resulting soft clustering algorithms can further improve the clustering solutions. specifically, we focus on four of these hard criterion functions, derive their soft-clustering extensions, and present an experimental evaluation involving twelve different datasets. our results show that introducing softness into the criterion functions tends to lead to better clustering results for most datasets.
knowing a web page by the company it keeps. web page classification is important to many tasks in information retrieval and web mining. however, applying traditional textual classifiers on web data often produces unsatisfying results. fortunately, hyperlink information provides important clues to the categorization of a web page. in this paper, an improved method is proposed to enhance web page classification by utilizing the class information from neighboring pages in the link graph. the categories represented by four kinds of neighbors (parents, children, siblings and spouses) are combined to help with the page in question. in experiments to study the effect of these factors on our algorithm, we find that the method proposed is able to boost the classification accuracy of common textual classifiers from around 70% to more than 90% on a large dataset of pages from the open directory project, and outperforms existing algorithms. unlike prior techniques, our approach utilizes same-host links and can improve classification accuracy even when neighboring pages are unlabeled. finally, while all neighbor types can contribute, sibling pages are found to be the most important.
tracking changes in user interests with a few relevance judgments. keeping track of changes in user interests from a document stream with a few relevance judgments is not an easy task. to tackle this problem, we propose a novel method that integrates (1) pseudo-relevance feedback mechanism, (2) assumption about the persistence of user interests and (3) incremental method for data clustering. this approach has been empirically evaluated using reuters-21578 corpus in a setting for information filtering. the experiment results reveal that it significantly improves the performances of existing user-interest-tracking systems without requiring additional, actual relevance judgments.
an adaptive algorithm for learning changes in user interests. in this paper, we describe a new scheme to learn dynamic user's interests in an automated information filtering and gathering system running on the internet. our scheme is aimed to handle multiple domains of long-term and short-term user's interests simultaneously, which is learned through positive and negative user's relevance feedback. we developed a 3-descriptor approach to represent the user's interest categories. using a learning algorithm derived for this representation, our scheme adapts quickly to significant changes in user interest, and is also able to learn exceptions to interest categories.
improving novelty detection for general topics using sentence level information patterns. the detection of new information in a document stream is an important component of many potential applications. in this work, a new novelty detection approach based on the identification of sentence level information patterns is proposed. first, the information-pattern concept for novelty detection is presented with the emphasis on new information patterns for general topics (queries) that cannot be simply turned into specific questions whose answers are specific named entities (nes). then we elaborate a thorough analysis of sentence level information patterns on data from the trec novelty tracks, including sentence lengths, named entities, sentence level opinion patterns. this analysis provides guidelines in applying those patterns in novelty detection particularly for the general topics. finally, a unified pattern-based approach is presented to novelty detection for both general and specific topics. the new method for dealing with general topics will be the focus. experimental results show that the proposed approach significantly improves the performance of novelty detection for general topics as well as the overall performance for all topics from the 2002-2004 trec novelty tracks.
eigen-trend: trend analysis in the blogosphere based on singular value decompositions. the blogosphere - the totality of blog-related web sites - has become a great source of trend analysis in areas such as product survey, customer relationship, and marketing. existing approaches are based on simple counts, such as the number of entries or the number of links. in this paper, we introduce a novel concept, coined eigen-trend, to represent the temporal trend in a group of blogs with common interests and propose two new techniques for extracting eigen-trends in blogs. first, we propose a trend analysis technique based on the singular value decomposition. extracted eigen-trends provide new insights into multiple trends on the same keyword. second, we propose another trend analysis technique based on a higher-order singular value decomposition. this analyzes the blogosphere as a dynamic graph structure and extracts eigen-trends that reflect the structural changes of the blogosphere over time. experimental studies based on synthetic data sets and a real blog data set show that our new techniques can reveal a lot of interesting trend information and insights in the blogosphere that are not obtainable from traditional count-based methods.
database model for web-based cooperative applications. in this paper we propose a model of a database that could become a kernel of cooperative database applications. first, we propose a new data model cdm (collaborative data model) that is oriented for the specificity of multiuser environments, in particular: cooperation scenarios, cooperation techniques and cooperation management. second, we propose to apply to databases supporting collaboration so called multiuser transactions. multiuser transactions are flat transactions in which, in comparison to classical acid transactions, the isolation property is relaxed.
opportunity map: a visualization framework for fast identification of actionable knowledge. data mining techniques frequently find a large number of patterns or rules, which make it very difficult for a human analyst to interpret the results and to find the truly interesting and actionable rules. due to the subjective nature of "interestingness", human involvement in the analysis process is crucial. in this paper, we propose a novel visual data mining framework for the purpose of identifying actionable knowledge quickly and easily from discovered rules and data. this framework is called the opportunity map. it is inspired by some interesting ideas from quality engineering, in particular quality function deployment (qfd) and the house of quality. it associates summarized data or discovered rules with the application objective using an interactive matrix, which enables the user to quickly identify where the opportunities are. the proposed system can be used to visually analyze discovered rules, and other statistical properties of the data. the user can also interactively group actionable attributes and values, and see how they affect the targets of interest. combined with drill-down and comparative analysis, the user can analyze rules and data at different levels of detail. the proposed visualization framework thus represents a systematic and yet flexible method of rule analysis. applications of the system to large-scale data sets from our industrial partner have yielded promising results.
spatial data traversal in road map databases: a graph indexing approach. spatial data are found in geographic information systems such as digital road map databases where city and road attributes are associated with nodes and links in a directed graph. queries on spatial data are expensive because of the recursive property of graph traversal. we propose a graph indexing technique to expedite spatial queries where the graph topology remains relatively stationary. using a probabilistic analysis, this paper shows that the graph indexing technique significantly improves the efficiency of constrained spatial queries.
a case for reconfigurable parallel architectures for information retrieval. as the volume of data and computational requirements of modern information retrieval systems continue to expand, it is inevitable that parallel systems will be necessary to meet these demands. in this research, we provide a conceptual model of a reconfigurable parallel information retrieval system in a multicomputer environment. we develop strategies for scheduling queries in such systems, provide simulation results for implementing these strategies under various different theoretical situations, and present an analytical model of the system behavior.
document quality models for web ad hoc retrieval. the quality of document content, which is an issue that is usually ignored for the traditional ad hoc retrieval task, is a critical issue for web search. web pages have a huge variation in quality relative to, for example, newswire articles. to address this problem, we propose a document quality language model approach that is incorporated into the basic query likelihood retrieval model in the form of a prior probability. our results demonstrate that, on average, the new model is significantly better than the baseline (query likelihood model) in terms of precision at the top ranks.
hybrid index structures for location-based web search. there is more and more commercial and research interest in location-based web search, i.e. finding web content whose topic is related to a particular place or region. in this type of search, location information should be indexed as well as text information. however, the index of conventional text search engine is set-oriented, while location information is two-dimensional and in euclidean space. this brings new research problems on how to efficiently represent the location attributes of web pages and how to combine two types of indexes. in this paper, we propose to use a hybrid index structure, which integrates inverted files and r*-trees, to handle both textual and location aware queries. three different combining schemes are studied: (1) inverted file and r*-tree double index, (2) first inverted file then r*-tree, (3) first r*-tree then inverted file. to validate the performance of proposed index structures, we design and implement a complete location-based web search engine which mainly consists of four parts: (1) an extractor which detects geographical scopes of web pages and represents geographical scopes as multiple mbrs based on geographical coordinates; (2) an indexer which builds hybrid index structures to integrate text and location information; (3) a ranker which ranks results by geographical relevance as well as non-geographical relevance; (4) an interface which is friendly for users to input location-based search queries and to obtain geographical and textual relevant results. experiments on large real-world web dataset show that both the second and the third structures are superior in query time and the second is slightly better than the third. additionally, indexes based on r*-trees are proven to be more efficient than indexes based on grid structures.
efficient retrieval for browsing large image databases. the management of large image databases poses several interesting and challenging problems. these problems range from ingesting the data and extracting meta-data to the efficient storage and retrieval of the data. of particular interest are the retrieval methods and user interactions with an image database during browsing. in image databases, the response to a given query is not an exact well-defined set, rather, the user poses a query and expects a set of responses that should contain many possible candidates from which the user chooses the answer set. we first present the browsing model in alexandria, a digital library for maps and satellite images. designed for content-based retrieval, the relevant information in an image is encoded in the form of a multi-% dimensional feature vector. various techniques have been previously proposed for the efficient retrieval of such vectors by reducing the dimensionality of such vectors. we show that for even moderately large databases (in fact, only 1856 texture images), these approaches do not scale well for exact retrieval. however, as a browsing tool, these dimensionality reduction techniques hold much promise.
ontology-based web site mapping for information exploration. centralized search process requires that the whole collection reside at a single site. this imposes a burden on both the system storage of the site and the network traffic near the site. it thus comes to require the search process to be distributed. recently, more and more web sites provide the ability to search their local collection of web pages. query brokering systems are used to direct queries to the promising sites and merge the results from these sites. creation of meta-information of the sites plays an important role in such systems. in this article, we introduce an ontology-based web site mapping method used to produce conceptual meta-information, the vector space approach, and present a serial of experiments comparing it with na&iuml;ve-bayes approach. we found that the vector space approach produces better accuracy in ontology-based web site mapping.
interval query indexing for efficient stream processing. a large number of continual range queries can be issued against a data stream. usually, a main memory-based query index with a small storage cost and a fast search time is needed, especially if the stream is rapid. in this paper, we present a cei-based query index that meets both criteria for efficient processing of continual interval queries in a streaming environment. this new query index is centered around a set of predefined virtual <i>containment-encoded intervals</i>, or ceis. the ceis are used to first decompose query intervals and then perform efficient search operations. the ceis are defined and labeled such that containment relationships among them are encoded in their ids. the containment encoding makes decomposition and search operations efficient because integer additions and logical shifts can be used to carry out most of the operations. simulations are conducted to evaluate the effectiveness of the cei-based query index and to compare it with alternative approaches. the results show that the cei-based query index significantly outperforms existing approaches in terms of both storage cost and search time.
trajectory queries and octagons in moving object databases. an important class of queries in moving object databases involves trajectories. we propose to divide trajectory predicates into topological and non-topological parts; extend the 9 intersection model of egenhofer-franzosa to a 3-step evaluation strategy for trajectory queries: a filter step, a refinement step, and a tracing step.the filter and refinement steps are similar to region searches. as in spatial databases, approximations of trajectories are typically used in evaluating trajectory queries. in earlier studies, minimum bounding boxes (mbrs) are used to approximate trajectory segments which allow index structures to be built, e.g., tb-trees and r*-trees. the use of mbrs hinders the efficiency since mbrs are very coarse approximations especially for trajectory segments. to overcome this problem, we propose a new type of approximations, "minimum bounding octagon prism" mbop. we extend r*-tree to a new index structure "octagon-prism tree" (op-tree) for mbops of trajectory segments. we conducted experiments to evaluate efficiency of op-trees in performing region searches and trajectory queries. the results show that op-trees improve region searches significantly over synthetic trajectory data sets to tb-trees and r*-trees and can significantly reduce the evaluation cost of trajectory queries compared to tb-trees.
domain-specific keyphrase extraction. document keyphrases provide semantic metadata characterizing documents and producing an overview of the content of a document. they can be used in many text-mining and knowledge management related applications. this paper describes a keyphrase identification program (kip), which extracts document keyphrases by using prior positive samples of human identified domain keyphrases to assign weights to the candidate keyphrases. the logic of our algorithm is: the more keywords a candidate keyphrase contains and the more significant these keywords are, the more likely this candidate phrase is a keyphrase. to obtain prior positive inputs, kip first populates its glossary database using manually identified keyphrases and keywords. it then checks the composition of all noun phrases of a document, looks up the database and calculates scores for all these noun phrases. the ones having higher scores will be extracted as keyphrases.
distributed pagerank computation based on iterative aggregation-disaggregation methods. pagerank has been widely used as a major factor in search engine ranking systems. however, global link graph information is required when computing pagerank, which causes prohibitive communication cost to achieve accurate results in distributed solution. in this paper, we propose a distributed pagerank computation algorithm based on iterative aggregation-disaggregation (iad) method with block jacobi smoothing. the basic idea is divide-and-conquer. we treat each web site as a node to explore the block structure of hyperlinks. local pagerank is computed by each node itself and then updated with a low communication cost with a coordinator. we prove the global convergence of the block jacobi method and then analyze the communication overhead and major advantages of our algorithm. experiments on three real web graphs show that our method converges 5-7 times faster than the traditional power method. we believe our work provides an efficient and practical distributed solution for pagerank on large scale web graphs.
a performance comparison of bitmap indexes. we present a comparison of two new word-aligned schemes with some schemes for compressing bitmap indexes, including the well-known byte-aligned bitmap code (bbc). on both synthetic data and real application data, the new word-aligned schemes use only 50% more space, but perform logical operations on compressed data 12 times faster than bbc. the new schemes achieve this performance advantage by guaranteeing that during logical operations every machine instruction performs useful work on words rather than on bytes or bits as in bbc.
taxonomy-driven computation of product recommendations. recommender systems have been subject to an enormous rise in popularity and research interest over the last ten years. at the same time, very large taxonomies for product classification are becoming increasingly prominent among e-commerce systems for diverse domains, rendering detailed machine-readable content descriptions feasible. amazon.com makes use of an entire plethora of hand-crafted taxonomies classifying books, movies, apparel, and various other goods. we exploit such taxonomic background knowledge for the computation of personalized recommendations. hereby, relationships between super-concepts and sub-concepts constitute an important cornerstone of our novel approach, providing powerful inference opportunities for profile generation based upon the classification of products that customers have chosen. ample empirical analysis, both offline and online, demonstrates our proposal's superiority over common existing approaches when user information is sparse and implicit ratings prevail.
finding more useful information faster from web search results. in this paper, we propose a prototype system for automatic generation of concept hierarchies to be used as an overview of search results. the system sends a user's query to five search engines and receives a returned list of relevant web pages. the system then extracts query-oriented concept terms from snippets that come with the returned hits. concept terms are organized into a concept hierarchy using a co-occurrence-based classification technique. finally, concepts in returned documents are dynamically highlighted according to terms in the selected concept branch that lead to the chosen document. the user study shows that concept hierarchies do provide easy navigation and browsing of web returned documents. the results also show that users can find a document of interest no matter how low it is ranked in the retrieved list.
measuring the meaning in time series clustering of text search queries. we use a combination of proven methods from time series analysis and machine learning to explore the relationship between temporal and semantic similarity in web query logs; we discover that the combination of correlation and cycles is a good, but not perfect, sign of semantic relationship.
efficient query monitoring using adaptive multiple key hashing. monitoring continual queries or subscriptions is to determine the subset of all queries or subscriptions whose predicates match a given event. predicates contain not only equality but also non-equality clauses. event matching is usually accomplished by first identifying a "small" candidate set of subscriptions for an event and then determining the matched subscriptions from the candidate set. prior work has focused on using equality clauses to identify the candidate set. however, we found that completely ignoring non-equality clauses can result in a much larger candidate set. in this paper, we present and evaluate an adaptive multiple key hashing (amkh) method to judiciously include an effective subset of non-equality clauses in candidate set identification. each subscription is mapped to a data point in a multidimensional space based on its predicate clauses. amkh is then used to maintain subscriptions and perform event matching. amkh further provides a controlling mechanism to limit the hash range of a non-equality clause, hence reducing the size of the candidate set. simulations are conducted to study the performance of amkh. the results show that (1) a small number of non-equality clauses can be effectively included by amkh and (2) the attributes whose overall non-equality predicate clauses are most selective should be chosen for inclusion by amkh.
performance thresholding in practical text classification. in practical classification, there is often a mix of learnable and unlearnable classes and only a classifier above a minimum performance threshold can be deployed. this problem is exacerbated if the training set is created by active learning. the bias of actively learned training sets makes it hard to determine whether a class has been learned. we give evidence that there is no general and efficient method for reducing the bias and correctly identifying classes that have been learned. however, we characterize a number of scenarios where active learning can succeed despite these difficulties.
local replication for proxy web caches with hash routing. this paper studies controlled local replication for hash routing, such as carp, among a collection of loosely-coupled proxy web cache servers. hash routing partitions the entire url space among the shared web caches, creating a single logical cache. each partition is assigned to a cache server. duplication of cache contents is eliminated and total incoming traffic to the shared web caches is minimized. client requests for non-assigned-partition objects are forwarded to sibling caches. however, request forwarding increases not only inter-cache traffic but also cpu utilization, thus slows the client response time. we propose a controlled local replication of non-assigned-partition objects in each cache server to effectively reduce the inter-cache traffic. we use a multiple-exit lru to implement controlled local replication. trace-driven simulations are conducted to study the performance impact of local replication. the results show that (1) regardless of cache sizes, with a controlled local replication, the average response time, inter-cache traffic and cpu overhead can be effectively reduced without noticeable increases in incoming traffic; (2) for very large cache sizes, a larger amount of local replication can be allowed to reduce inter-cache traffic without increasing incoming traffic; and (3) local replication is effective even if clients are dynamically assigned to different cache servers.
self-managing technology in ibm db2 universal database. as the cost of both hardware and software falls due to technological advancements and economies of scale, the cost of ownership for database applications is increasingly dominated by the cost of people to manage them. databases are growing rapidly in scale and complexity, while skilled database administrators (dbas) are becoming rarer and more expensive. the scope of responsibility of dbas is indeed daunting. this paper describes the self-managing technology in ibm db2 universal database to illustrate how self-managing technology can enhance the usability of enterprise middleware and reduce the total cost of ownership (tco).
a relational algebra for data/metadata integration in a federated database system. the need for interoperability among databases has increased dramatically with the proliferation of readily available dbms and application software. even within a single organization, data from disparate relational databases must be integrated. a framework for interoperability in a federated system of relational databases should be inherently relational, so that it can use existing techniques for query evaluation and optimization where possible and retain the key features of sql, such as a modest complexity and ease of query formulation. our contribution is a logspace relational algebra, the meta-algebra (ma), for data/metadata integration among relational databases containing semantically similar information in schematically disparate formats. the ma is a simple yet powerful extension of the classical relational algebra (ra). the ma has a natural declarative counterpart, the meta-query language (mql), which we briefly describe. we state a result showing mql and the ma are computationally equivalent, which enables us to algebratize mql queries in fundamentally the same way as ordinary sql queries. this algebratization in turn enables us to use ma equivalences to facilitate the application of known query optimization techniques to mql query evaluation.
a formal characterization of pivot/unpivot. pivot is an important relational operation that allows data in rows to be exchanged for columns. although most current relational database management systems support pivot-type operations, to date a purely formal, algebraic characterization of pivot has been lacking. in this paper, we present a characterization in terms of extended relational algebra operators τ (transpose), π (drop projection), and μ (unique optimal tuple merge). this enables us to (1) draw parallels with pivot and existing operators employed in dynamic data mapping systems (ddms), (2) formally characterize invertible pivot instances, and (3) provide complexity results for pivot-type operations. these contributions are an important part of ongoing work on formal models for relational olap.
estimating average precision with incomplete and imperfect judgments. we consider the problem of evaluating retrieval systems using incomplete judgment information. buckley and voorhees recently demonstrated that retrieval systems can be efficiently and effectively evaluated using incomplete judgments via the bpref measure [6]. when relevance judgments are complete, the value of bpref is an approximation to the value of average precision using complete judgments. however, when relevance judgments are incomplete, the value of bpref deviates from this value, though it continues to rank systems in a manner similar to average precision evaluated with a complete judgment set. in this work, we propose three evaluation measures that (1) are approximations to average precision even when the relevance judgments are incomplete and (2) are more robust to incomplete or imperfect relevance judgments than bpref. the proposed estimates of average precision are simple and accurate, and we demonstrate the utility of these estimates using trec data.
using a compact tree to index and query xml data. indexing xml is crucial for efficient xml query processing. we propose a compact tree (ctree) for xml indexing, which provides not only concise path summaries at group level but also detailed child-parent relationships at element level. based on ctree, we are able to measure how well xml data is structured. we also propose a three-step query processing method. its efficiency is achieved by: (1) summarizing large xml data structures into a condensed ctree; (2) pruning irrelevant groups to significantly reduce the search space; (3) eliminating join operations between the matches for value predicates and those for structure constraints and (4) using ctree properties such as regular groups to reduce query processing time. our experiments reveal that ctree is an effective data structure for managing xml data.
erknn: efficient reverse k-nearest neighbors retrieval with local knn-distance estimation. the reverse k-nearest neighbors (rknn) queries are important in profile-based marketing, information retrieval, decision support and data mining systems. however, they are very expensive and existing algorithms are not scalable to queries in high dimensional spaces or of large values of k. this paper describes an efficient estimation-based rknn search algorithm (erknn) which answers rknn queries based on local knn-distance estimation methods. the proposed approach utilizes estimation-based filtering strategy to lower the computation cost of rknn queries. the results of extensive experiments on both synthetic and real life datasets demonstrate that erknn algorithm retrieves rknn efficiently and is scalable with respect to data dimensionality, k, and data size.
dynamic versioning concurrency control for index-based data access in main memory database systems. we present a concurrency control scheme using dynamic versioning for index-based data access in main memory database systems. this scheme enables read-only transactions read correct version without holding any locks or latches, while update transactions only obtain a few locks or latches without deadlocks. efficient version management is designed to support high concurrency level and low space overhead. the interaction between dynamic versioning and indexing is considered so that all available versions can be accessed through indexing. experiment results show that dynamic versioning can improve the performance in concurrent environment significantly.
tracking dragon-hunters with language models. we are interested in the problem of understanding the connections between human activities and the content of textual information generated in regard to those activities. firstly, we define and motivate this problem as an important part in making sense of various life events. secondly, we introduce the domain of massive online collaborative environments, specifically online virtual worlds, where people meet, exchange messages, and perform actions as a rich data source for such an analysis. finally, we outline three experimental tasks and show how statistical language modeling and text clustering techniques may allow us to explore those connections successfully.
slicing*-tree based web page transformation for small displays. we propose a new web page transformation method for browsing on mobile devices with small displays. in our approach, an original web page that does not fit into the screen is transformed into a set of pages, each of which fits into the screen. this transformation is done through slicing the original page. the resulting set of transformed pages form a multi-level tree structure, called a slicing*-tree, in which an internal node consists of a thumbnail image with hyperlinks and a leaf node is a block from the original web page. our slicing*-tree based web page transformation eases web browsing on small displays by providing screen-fitting visual context and reducing page scrolling effort.
re-ranking search results using query logs. this work addresses two common problems in search, frequently occurring with underspecified user queries: the top-ranked results for such queries may not contain documents relevant to the user's search intent, and fresh and relevant pages may not get high ranks for an underspecified query due to their freshness and to the large number of pages that match the query, despite the fact that a large number of users have searched for parts of their content recently. we propose a novel method, q-rank, to effectively refine the ranking of search results for any given query by constructing the query context from search query logs. evaluation results show that q-rank gains a considerable advantage over the current ranking system of a large-scale commercial web search engine, being able to improve the relevance of search results for 82% of the queries.
supporting ranked search in parallel search cluster networks. we investigate how to support ranked keyword search in a parallel search cluster network, which is a newly proposed peer-to-peer network overlay. in particular, we study how to efficiently acquire and distribute the global information required by ranked keyword search by taking advantage of the architectural features of pscns.
amnesic online synopses for moving objects. we present a hierarchical tree structure for online maintenance of time-decaying synopses over streaming data. we exemplify such an amnesic behavior over streams of locations taken from numerous moving objects in order to obtain reliable trajectory approximations as well as affordable estimates regarding distinct count spatiotemporal queries.
privacy leakage in multi-relational databases via pattern based semi-supervised learning. in multi-relational databases, a view, which is a context- and content-dependent subset of one or more tables (or other views), is often used to preserve privacy by hiding sensitive information. however, recent developments in data mining present a new challenge for database security even when traditional database security techniques, such as database access control, are employed. this paper presents a data mining framework using semi-supervised learning that demonstrates the potential for privacy leakage in multi-relational databases. many different types of semi-supervised learning techniques, such as the k-nearest neighbor (knn) method, can be used to demonstrate privacy leakage. however, we also introduce a new approach to semi-supervised learning, hyperclique pattern based semi-supervised learning (hpsl), which differs from traditional semi-supervised learning approaches in that it considers the similarity among groups of objects instead of only pairs of objects. our experimental results show that both the knn and hpsl methods have the ability to compromise database security, although hpsl is better at this privacy violation than the knn method.
designing semantics-preserving cluster representatives for scientific input conditions. in scientific domains, knowledge is often discovered from experiments by grouping or clustering them based on the similarity of their output. the causes of similarity are analyzed based on the input conditions characterizing a given type of output, i.e., a given cluster. this analysis helps in applications such as decision support in industry. cluster representatives form at-a-glance depictions for such applications. randomly selecting a set of conditions in a cluster as its representative is not sufficient since distinct combinations of inputs could lead to the same cluster. in this paper, an approach called descond is proposed to design semantics-preserving cluster representatives for scientific input conditions. we define a notion of distance for conditions to capture semantics based on the types of their attributes and their relative importance. using this distance, methods of building candidate cluster representatives with different levels of detail are proposed. candidates are compared using the descond encoding proposed in this paper that assesses their complexity and information loss, given user interests. the candidate with the lowest encoding for each cluster is returned as its designed representative. descond is evaluated with real data from materials science. evaluation with domain expert interviews and formal user surveys shows that designed representatives consistently outperform randomly selected ones and different candidates suit different users.
pruning strategies for mixed-mode querying. web information retrieval systems face a range of unique challenges, not the least of which is the sheer scale of the data that must be handled. also specific to web retrieval is that queries may be a mix of boolean and ranked features, and documents may have static score components that must also be factored into the ranking process. in this paper we consider a range of query semantics used in web retrieval systems, and show that impact-sorted indexes provide support for dynamic pruning mechanisms and in doing so allow fast document-at-a-time resolution of typical mixed-mode queries, even on relatively large volumes of data. our techniques also extend to more complex query semantics, including the use of phrase, proximity, and structural constraints.
structure-based querying of proteins using wavelets. the ability to retrieve molecules based on structural similarity has use in many applications, from disease diagnosis and treatment to drug discovery and design. in this paper, we present a method to represent protein molecules that allows for the fast, flexible and efficient retrieval of similar structures, based on either global or local attributes. we begin by computing the pair-wise distance between amino acids, transforming each 3d structure into a 2d distance matrix. we normalize this matrix to a specific size and apply a 2d wavelet decomposition to generate a set of approximation coefficients, which serves as our global feature vector. this transformation reduces the overall dimensionality of the data while still preserving spatial features and correlations. we test our method by running queries on three different protein data sets that have been used previously in the literature, basing our comparisons on labels taken from the scop database. we find that our method significantly outperforms existing approaches, in terms of retrieval accuracy, memory utilization and execution time. specifically, using a k-d tree and running a 10-nearest-neighbor search on a dataset of 33,000 proteins against itself, we see an average accuracy of 89% at the scop superfamily level and a total query time that is up to 350 times faster than previously published techniques. in addition to processing queries based on global similarity, we also propose innovative extensions to effectively match proteins based solely on shared local substructures, allowing for a more flexible query interface.
optimizing web search using web click-through data. the performance of web search engines may often deteriorate due to the diversity and noisy information contained within web pages. user click-through data can be used to introduce more accurate description (metadata) for web pages, and to improve the search performance. however, noise and incompleteness, sparseness, and the volatility of web pages and queries are three major challenges for research work on user click-through log mining. in this paper, we propose a novel iterative reinforced algorithm to utilize the user click-through data to improve search performance. the algorithm fully explores the interrelations between queries and web pages, and effectively finds "virtual queries" for web pages and overcomes the challenges discussed above. experiment results on a large set of msn click-through log data show a significant improvement on search performance over the naive query log mining algorithm as well as the baseline search engine.
cache-oblivious nested-loop joins. we propose to adapt the newly emerged cache-oblivious model to relational query processing. our goal is to automatically achieve an overall performance comparable to that of fine-tuned algorithms on a multi-level memory hierarchy. this automaticity is because cache-oblivious algorithms assume no knowledge about any specific parameter values, such as the capacity and block size of each level of the hierarchy. as a first step, we propose recursive partitioning to implement cache-oblivious nested-loop joins (nljs) without indexes, and recursive clustering and buffering to implement cache-oblivious nljs with indexes. our theoretical results and empirical evaluation on three different architectures show that our cache-oblivious nljs match the performance of their manually optimized, cache-conscious counterparts.
generating concise association rules. association rule mining has made many achievements in the area of knowledge discovery. however, the quality of the extracted association rules is a big concern. one problem with the quality of the extracted association rules is the huge size of the extracted rule set. as a matter of fact, very often tens of thousands of association rules are extracted among which many are redundant thus useless. mining non-redundant rules is a promising approach to solve this problem. the min-max exact basis proposed by pasquier et al [pasquier05] has showed exciting results by generating only non-redundant rules. in this paper, we first propose a relaxing definition for redundancy under which the min-max exact basis still contains redundant rules; then we propose a condensed representation called reliable exact basis for exact association rules. the rules in the reliable exact basis are not only non-redundant but also more succinct than the rules in min-max exact basis. we prove that the redundancy eliminated by the reliable exact basis does not reduce the belief to the reliable exact basis. the size of the reliable exact basis is much smaller than that of the min-max exact basis. moreover, we prove that all exact association rules can be deduced from the reliable exact basis. therefore the reliable exact basis is a lossless representation of exact association rules. experimental results show that the reliable exact basis significantly reduces the number of non-redundant rules.
mrssa: an iterative algorithm for similarity spreading over interrelated objects. we introduce the multiple relationship similarity spreading algorithm (mrssa) to enhance ir effectiveness. this method has similarity computed in an iterative "spreading" fashion for multiple object types, combining both inter- and intra-object relationships. we demonstrate the value of this approach in the context of the www, where the key objects are web pages and queries, relationships considered are derived from hyperlinks (in- and out-links) and click-through logs.
mining coherent patterns from heterogeneous microarray data. microarray technology is a powerful tool for geneticists to monitor interactions among tens of thousands of genes simultaneously. there has been extensive research on coherent subspace clustering of gene expressions measured under consistent experimental settings. however, these methods assume that all experiments are run using the same batch of microarray chips with similar characteristics of noise. algorithms developed under this assumption may not be applicable for analyzing data collected from heterogeneous settings, where the set of genes being monitored may be different and expression levels may be not directly comparable even for the same gene. in this paper, we propose a model, f-cluster, for mining subspace coherent patterns from heterogeneous gene expression data. we compare our model with previously proposed models. we analyze the search space of the problem and give a naïve solution for it.
describing differences between databases. we study the novel problem of efficiently computing the update distance for a pair of relational databases. in analogy to the edit distance of strings, we define the update distance of two databases as the minimal number of set-oriented insert, delete and modification operations necessary to transform one database into the other. we show how this distance can be computed by traversing a search space of database instances connected by update operations. this insight leads to a family of algorithms that compute the update distance or approximations of it. in our experiments we observed that a simple heuristic performs surprisingly well in most considered cases.our motivation for studying distance measures for databases stems from the field of scientific databases. there, replicas of a single database are often maintained at different sites, which typically leads to (accidental or planned) divergence of their content. to re-create a consistent view, these differences must be resolved. such an effort requires an understanding of the process that produced them. we found that minimal update sequences of set-oriented update operations are a proper and concise representation of systematic errors, thus giving valuable clues to domain experts responsible for conflict resolution.
a probabilistic relevance propagation model for hypertext retrieval. a major challenge in developing models for hypertext retrieval is to effectively combine content information with the link structure available in hypertext collections. although several link-based ranking methods have been developed to improve retrieval results, none of them can fully exploit the discrimination power of contents as well as fully exploit all useful link structures. in this paper, we propose a general relevance propagation framework for combining content and link information. the framework gives a probabilistic score to each document defined based on a probabilistic surfing model. two main characteristics of our framework are our probabilistic view on the relevance propagation model and propagation through multiple sets of neighbors. we compare eight different models derived from the probabilistic relevance propagation framework on two standard trec web test collections. our results show that all the eight relevance propagation models can outperform the baseline content only ranking method for a wide range of parameter values, indicating that the relevance propagation framework provides a general, effective and robust way of exploiting link information. our experiments also show that using multiple neighbor sets outperforms using just one type of neighbors significantly and taking a probabilistic view of propagation provides guidance on setting propagation parameters.
virtual cursors for xml joins. structural joins are a fundamental operation in xml query processing and a large body of work has focused on index-based algorithms for executing them. in this paper, we describe how two well-known index features -- path indices and ancestor information -- can be combined in a novel way to replace one or more of the physical index cursors in a structural join with <i>virtual cursors</i>. the position of a virtual cursor is derived from the path and ancestor information of a physical cursor. implementation results are provided to show that, by eliminating index i/o, virtual cursors can improve the performance of structural joins by an order of magnitude or more.
topic evolution and social interactions: how authors effect research. we propose a method for discovering the dependency relationships between the topics of documents shared in social networks using the latent social interactions, attempting to answer the question: given a seemingly new topic, from where does this topic evolve? in particular, we seek to discover the pair-wise probabilistic dependency in topics of documents which associate social actors from a latent social network, where these documents are being shared. by viewing the evolution of topics as a markov chain, we estimate a markov transition matrix of topics by leveraging social interactions and topic semantics. metastable states in a markov chain are applied to the clustering of topics. applied to the citeseer dataset, a collection of documents in academia, we show the trends of research topics, how research topics are related and which are stable. we also show how certain social actors, authors, impact these topics and propose new ways for evaluating author impact.
cooperative caching for k-nn search in ad hoc networks. mobile ad hoc networks have multiple limitations in performing similarity-based nearest neighbor search - dynamic topology, frequent disconnections, limited power, and restricted bandwidth. cooperative caching is an effective technique to reduce network traffic and increase accessibility. in this paper, we propose to solve the k-nearest-neighbor search problem in ad hoc networks using a semantic-based caching scheme which reflects the content distribution in the network. the proposed scheme describes the semantic similarity among data objects using constraints, and employs cooperative caching to estimate the content distribution in the network. the query resolution based on the cooperative caching scheme is non-flooding and hierarchy-free.
voting for candidates: adapting data fusion techniques for an expert search task. in an expert search task, the users' need is to identify people who have relevant expertise to a topic of interest. an expert search system predicts and ranks the expertise of a set of candidate persons with respect to the users' query. in this paper, we propose a novel approach for predicting and ranking candidate expertise with respect to a query. we see the problem of ranking experts as a voting problem, which we model by adapting eleven data fusion techniques.we investigate the effectiveness of the voting approach and the associated data fusion techniques across a range of document weighting models, in the context of the trec 2005 enterprise track. the evaluation results show that the voting paradigm is very effective, without using any collection specific heuristics. moreover, we show that improving the quality of the underlying document representation can significantly improve the retrieval performance of the data fusion techniques on an expert search task. in particular, we demonstrate that applying field-based weighting models improves the ranking of candidates. finally, we demonstrate that the relative performance of the adapted data fusion techniques for the proposed approach is stable regardless of the used weighting models.
margin-based local regression for adaptive filtering. adaptive information filtering is an open challenge in information retrieval. one of the tough issues is the optimization of decision thresholds over time, based on partial relevance feedback on the system-retrieved documents in chronological order. we developed a new approach, namely margin-based local regression, that automatically adjusts the thresholds based on a sliding window over the truly positive examples for which the system predicted "yes" with respect to a particular class, and a second sliding window over the other documents being processed by the system. using the means of the scores of the documents in the two windows, we monitor the temporal drifting of the margin that is a function of both the current classification model and the threshold calibration strategy, and that suggests the bounds for the optimal threshold at a given time. examining this approach together with a rocchio-style classifier on the trec 2001 and trec 2002 benchmark data sets in adaptive filtering, we obtained significant improvements in performance (measured using fβ=0.5) over the baseline system that did not adapt the threshold over time, and the best result ever reported on the trec 2002 benchmark corpus for adaptive filtering evaluations. these empirical results suggest that it is important to use both system-accepted and system-rejected documents to optimize thresholds instead of just using system-accepted documents alone, as well as to make the thresholding function temporally sensitive to the shifting centroids of on-topic and off-topic documents.
finding highly correlated pairs efficiently with powerful pruning. we consider the problem of finding highly correlated pairs in a large data set. that is, given a threshold not too small, we wish to report all the pairs of items (or binary attributes) whose (pearson) correlation coefficients are greater than the threshold. correlation analysis is an important step in many statistical and knowledge-discovery tasks. normally, the number of highly correlated pairs is quite small compared to the total number of pairs. identifying highly correlated pairs in a naive way by computing the correlation coefficients for all the pairs is wasteful. with massive data sets, where the total number of pairs may exceed the main-memory capacity, the computational cost of the naive method is prohibitive. in their kdd'04 paper [15], hui xiong et al. address this problem by proposing the taper algorithm. the algorithm goes through the data set in two passes. it uses the first pass to generate a set of candidate pairs whose correlation coefficients are then computed directly in the second pass. the efficiency of the algorithm depends greatly on the selectivity (pruning power) of its candidate-generating stage.in this work, we adopt the general framework of the taper algorithm but propose a different candidate-generation method. for a pair of items, taper's candidate-generation method considers only the frequencies (supports) of individual items. our method also considers the frequency (support) of the pair but does not explicitly count this frequency (support). we give a simple randomized algorithm whose false-negative probability is negligible. the space and time complexities of generating the candidate set in our algorithm are asymptotically the same as taper's. we conduct experiments on synthesized and real data. the results show that our algorithm produces a greatly reduced candidate set - one that can be several orders of magnitude smaller than that generated by taper. because of this, our algorithm uses much less memory and can be faster. the former is critical for dealing with massive data.
information retrieval from relational databases using semantic queries. relational databases are widely used today as a mechanism for providing access to structured data. they, however, are not suitable for typical information finding tasks of end users. there is often a semantic gap between the queries users want to express and the queries that can be answered by the database. in this paper, we propose a system that bridges this semantic gap using domain knowledge contained in ontologies. our system extends relational databases with the ability to answer semantic queries that are represented in sparql, an emerging semantic web query language. users express their queries in sparql, based on a semantic model of the data, and they get back semantically relevant results. we define different categories of results that are semantically relevant to the users' query and show how our system retrieves these results. we evaluate the performance of our system on sample relational databases, using a combination of standard and custom ontologies.
on the complexity of schema inference from web pages in the presence of nullable data attributes. an increasingly large number of web pages are machine-generated by filling in templates with data stored in backend databases. these templates can be viewed as the implicit schemas of those web pages. the ability to infer the implicit schema from a collection of web pages is important for scalable data extraction, since the inferred schema can be used to automatically identify schema attributes that are "encoded" in web pages.however, the task of inferring a "good" schema is complicated due to the existence of nullable (missing) data attributes. usually if an attribute contains a null value, then it will be omitted in the generated web page, giving rise to different variations and permutations of layout structures in web pages that are generated from the same template.in this paper we investigate the complexity of schema inference from web pages in the presence of nullable data attributes. we introduce the notion of unambiguity as a quality measure for inferred schemas and prove that the problem of inferring "good" (unambiguous) schemas is np-complete. our complexity results imply that ambiguity resolution is one of the root causes of the computational difficulty underlying schema inference from web pages.
salsa: computing the skyline without scanning the whole sky. skyline queries compute the set of pareto-optimal tuples in a relation, ie those tuples that are not dominated by any other tuple in the same relation. although several algorithms have been proposed for efficiently evaluating skyline queries, they either require to extend the relational server with specialized access methods (which is not always feasible) or have to perform the dominance tests on all the tuples in order to determine the result. in this paper we introduce salsa (sort and limit skyline algorithm), which exploits the sorting machinery of a relational engine to order tuples so that only a subset of them needs to be examined for computing the skyline result. this makes salsa particularly attractive when skyline queries are executed on top of systems that do not understand skyline semantics or when the skyline logic runs on clients with limited power and/or bandwidth.
in search of meaning for time series subsequence clustering: matching algorithms based on a new distance measure. recent papers have claimed that the result of k-means clustering for time series subsequences (sts clustering) is independent of the time series that created it. our paper revisits this claim. in particular, we consider the following question: given several time series sequences and a set of sts cluster centroids from one of them (generated by the k-means algorithm), is it possible to reliably determine which of the sequences produced these cluster centroids? while recent results suggest that the answer should be no, we answer this question in the affirmative.we present cluster shape distance, an alternate distance measure for time series subsequence clusters, based on cluster shapes. given a set of clusters, its shape is the sorted list of the pairwise euclidean distances between their centroids. we then present two algorithms based on this distance measure, which match a set of sts cluster centroids with the time series that produced it. while the first algorithm creates dqg reuse this term more smaller "fingerprints" for the sequences, the second is more accurate. in our experiments with a dataset of 10 sequences, it produced a correct match 100% of the time.furthermore, we offer an analysis that explains why our cluster shape distance provides a reliable way to match sts clusters to the original sequences, whereas cluster set distance fails to do so. our work establishes for the first time a strong relation between the result of k-means sts clustering and the time series sequence that created it, despite earlier predictions that this is not possible.
efficient data access to multi-channel broadcast programs. this paper studies fast access to data that are broadcast on multiple channels. broadcast is a useful data dissemination technique because of its scalability, but is lacking when it comes to response time. increasing the number of available broadcast channels is a logical way of increasing throughput. little work, however, has considered the access structures necessary for making effective use of the additional channels. we propose various indexing schemes for a multi-channel broadcast program. we demonstrate the effectiveness of our techniques in decreasing response time and tuning time via extensive experiments over a wide range of parameters.
how i learned to stop worrying and love the imminent internet singularity. in 1993, verner vinge [3] introduced the notion of the singularity -- a step function to nearly unlimited technological capability -- which would be realized if the acceleration of scientific progress continues to produce such things as strong ai, nanotechnology, and super-human intelligence. since its introduction, the idea of the singularity has been met with both evangelism (by ray kurzweil [2]) and apocalyptic warnings (by bill joy [1]).in this talk, i will introduce a more modest version of the idea, which i call the internet singularity. like the original, the internet singularity suggests continued acceleration of progress, but makes greater emphasis on our ability to improve science, analytic methods, and engineering on data as opposed to the physical world. i make the case for the internet singularity in four steps.first, there is a general trend of more capabilities being more available to more people. these increasing capabilities span content creation, community, and commerce, yielding more power to today's "amateur" than yesterday's "professional". as a result, the boundary between producers and consumers is becoming increasingly blurred over time.second, in many parts of the internet we see power law distributions with a heavy tail. one implication of heavy tail distributions is that the aggregate impact of "small" participants can be greater than that of the "large" participants.third, with the internet comes entirely new means for authoring new and derivative works: aggregations, mashups, tagging, remixing, etc. the greater emphasis on collaboration and sharing yields direct and indirect network effects. network effects, can produce entirely new utility, making online activities potentially more efficient or valuable than the offline equivalent.fourth, on the internet, advances are effectively decoupled from the physical constraints of the offline world: startups costs are smaller; customer, collaborator, and audience pools are dramatically larger; and improvements happen in more of a continuous rather than discreet manner. as a result the effective "clock cycle" of progress is potentially much faster online.putting these four pieces together reveals a compelling pattern: more people contribute to the collective pool; the collective pool contains entirely new value that is derived from its data; and the new value from the data increases individual and aggregate capabilities. in combination, these components mutually reinforce one another, forming something of a virtuous cycle. this is the internet singularity.conceptually, if we consider engineering to be the ability to create artifacts, mathematical analysis to be the ability to analyze numerical properties, and science to be the pursuit of knowledge, then each of these activities -- when focused on digital objects as they exist on the internet -- can be amplified in a manner consistent with the internet singularity.the implications for the internet singularity are profound as they suggest nothing less than the evolution of the scientific method itself. moreover, these trends also imply that now may be the best possible moment in the history of the universe to be a computer scientist.
mining compressed commodity workflows from massive rfid data sets. radio frequency identification (rfid) technology is fast becoming a prevalent tool in tracking commodities in supply chain management applications. the movement of commodities through the supply chain forms a gigantic workflow that can be mined for the discovery of trends, flow correlations and outlier paths, that in turn can be valuable in understanding and optimizing business processes.in this paper, we propose a method to construct compressed probabilistic workflows that capture the movement trends and significant exceptions of the overall data sets, but with a size that is substantially smaller than that of the complete rfid workflow. compression is achieved based on the following observations: (1) only a relatively small minority of items deviate from the general trend, (2)only truly non-redundant deviations, ie, those that substantially deviate from the previously recorded ones, are interesting, and (3) although rfid data is registered at the primitive level, data analysis usually takes place at a higher abstraction level. techniques for workflow compression based on non-redundant transition and emission probabilities are derived; and an algorithm for computing approximate path probabilities is developed. our experiments demonstrate the utility and feasibility of our design, data structure, and algorithms.
an rsa-based time-bound hierarchical key assignment scheme for electronic article subscription. the time-bound hierarchical key assignment problem is to assign time sensitive keys to security classes in a partially ordered hierarchy so that legal data accesses among classes can be enforced. two time-bound hierarchical key assignment schemes have been proposed in the literature, but both of them were proved insecure against collusive attacks. in this paper, we will propose an rsa-based time-bound hierarchical key assignment scheme and describe its possible application. the security analysis shows that the new scheme is safe against the collusive attacks.
multi-task text segmentation and alignment based on weighted mutual information. text segmentation is important for text analysis, while text alignment is to determine shared sub-topics among similar documents. multi-task text segmentation and alignment is the extension of single-task segmentation to utilize information of multi-source documents. in this paper we introduce a novel domain-independent unsupervised method for multi-task segmentation and alignment based on the idea that the optimal segmentation and alignment maximizes weighted mutual information, mutual information with term weights. the experiment results show that our approach works well.
using domain knowledge in knowledge discovery. with the explosive growth of the size of databases, many knowledge discovery applications deal with large quantities of data. there is an urgent need to develop methodologies which will allow the applications to focus search to a potentially interesting and relevant portion of the data, which can reduce the computational complexity of the knowledge discovery process and improve the interestingness of discovered knowledge. previous work on semantic query optimization, which is an approach to take advantage of domain knowledge for query optimization, has demonstrated that significant cost reduction can be achieved by reformulating a query into a less expensive yet equivalent query which produces the same answer as the original one. in this paper, we introduce a method to utilize three types of domain knowledge in reducing the cost of finding a potentially interesting and relevant portion of the data while improving the quality of discovered knowledge. in addition, we propose a method to select relevant domain knowledge without an exhaustive search of all domain knowledge. the contribution of this paper is that we lay out a general framework for using domain knowledge in the knowledge discovery process effectively by providing guidelines.
intelligent query answering in deductive and object-oriented databases. in the near future, we believe that we will need much more sophisticated answer-finding schemes in an object-oriented database in order to satisfy the needs of truly intelligent information system. in this paper, we introduce a method to apply the intensional query processing techniques of deductive databases to object-oriented databases. so, we can generate intensional answers to represent answer-set abstractly for a given query in object-oriented databases.our approach consists of four steps: rule generation, pre-resolution, resolution, and post-resolution. in rule generation, we generate a set of deductive rules based on an object-oriented database schema. in pre-resolution, rule transformation is done to get unique intensional literals and extended term-restricted rules. in resolution, we identify rules that are potentially relevant to a query. in post-resolution, we find relevant resolvents as candidates for intensional answers among potentially relevant resolvents. we also use the notion of potentially relevant resolvents and relevant resolvents to avoid generating certain meaningless intensional answers.
query result ranking over e-commerce web databases. to deal with the problem of too many results returned from an e-commerce web database in response to a user query, this paper proposes a novel approach to rank the query results. based on the user query, we speculate how much the user cares about each attribute and assign a corresponding weight to it. then, for each tuple in the query result, each attribute value is assigned a score according to its "desirableness" to the user. these attribute value scores are combined according to the attribute weights to get a final ranking score for each tuple. tuples with the top ranking scores are presented to the user first. our ranking method is domain independent and requires no user feedback. experimental results demonstrate that this ranking method can effectively capture a user's preferences.
an approximate multi-word matching algorithm for robust document retrieval. document generation from low level data and its utilization is one of the most challenging tasks in document engineering. word occurrence detection is a fundamental problem in the recognized document utilization obtained by a recognizer, such as ocr and speech recognition. given a set of words, such as a dictionary, this paper proposes an efficient dynamic programming (dp) algorithm to find the occurrences of each word in a text. in this paper, the string similarity is measured by a statistical similarity model that enables a definition of the similarities in the character level as well as edit operation level. the proposed algorithm uses tree structures to measure similarities in order to avoid measuring similarities of the same substrings appearing in different parts of the text and words. the time complexity of the proposed algorithm is o(|w|⋅|s|⋅|q|), where |w| (resp. |s|) denote the number of nodes in the trees representing the word set (resp. the text), and |q| donotes the number of the states of the model used for string similarity. this paper shows the proposed algorithm is experimentally about six times faster than a naive dp algorithm.
out-of-context noun phrase semantic interpretation with cross-linguistic evidence. the acquisition of semantic knowledge is paramount for any application that requires a deep understanding of natural language text. motivated by the problem of building a noun phrase-level semantic parser and adapting it to various applications, such as machine translation and multilingual question answering, in this paper we present a domain-independent model for noun phrase semantic interpretation. we investigate the problem based on cross-linguistic evidence from a set of four romance languages: spanish, italian, french, and romanian. the focus on romance languages is well motivated. it is generally the case that english noun phrases translate into constructions of the form "n p n" in romance languages where, as we will show, the p (preposition) varies in ways that correlate with the semantics. thus, based on a set of 22 semantic interpretation categories (such as part-whole, agent, possession) we present empirical observations regarding the distribution of these semantic categories in a cross-lingual corpus and their mapping to various syntactic constructions in english and romance. furthermore, given a training set of english noun phrases along with their translations in the four romance languages, our algorithm automatically learns classification rules and applies them to unseen noun phrase instances for semantic interpretation. experimental results are compared against a state-of-the-art model reported in the literature.
translation enhancement: a new relevance feedback method for cross-language information retrieval. as an effective technique for improving retrieval effectiveness, relevance feedback (rf) has been widely studied in both monolingual and cross-language information retrieval (clir) settings. the studies of rf in clir have been focused on query expansion (qe), in which queries are reformulated before and/or after they are translated. however, rf in clir actually not only can help select better query terms, but also can enhance query translation by adjusting translation probabilities and even resolve some out-of-vocabulary terms. in this paper, we propose a novel rf method called translation enhancement (te), which uses the extracted translation relationships from relevant documents to revise the translation probabilities of query terms and to identify extra translation alternatives if available so that the translated queries are more tuned to the current search. we studied te using pseudo relevance feedback (prf) and interactive relevance feedback (irf). our results show that te can significantly improve clir with both types of rf methods, and that the improvement is comparable to that of qe. more importantly, the effects of te and qe are complementary. their integration can produce further improvement, and makes clir more robust for a variety of queries.
utility scoring of product reviews. we identify a new task in the ongoing research in text sentiment analysis: predicting utility of product reviews, which is orthogonal to polarity classification and opinion extraction. we build regression models by incorporating a diverse set of features, and achieve highly competitive performance for utility scoring on three real-world data sets.
a dual-view approach to interactive network visualization. visualizing network data, from tree structures to arbitrarily connected graphs, is a difficult problem in information visualization. a large part of the problem is that in network data, users not only have to visualize the attributes specific to each data item, but also the links specifying how those items are connected to each other. past approaches to resolving these difficulties focus on zooming, clustering, filtering and applying various methods of laying out nodes and edges. such approaches, however, focus only on optimizing a network visualization in a single view, limiting the amount of information that can be shown and explored in parallel. moreover, past approaches do not allow users to cross reference different subsets or aspects of large, complex networks. in this paper, we propose an approach to these limitations using multiple coordinated views of a given network. to illustrate our approach, we implement a tool called dualnet and evaluate the tool with a case study using an email communication network. we show how using multiple coordinated views improves navigation and provides insight into large networks with multiple node and link properties and types.
semi-automatic annotation and mpeg-7 authoring of dance videos. this paper presents a system (danvideo) that is implemented using j2se and jmf to annotate manually the macro and micro features of the dance videos by the dance experts. as mpeg-7 has reached a matured state for the description of the multimedia structure and semantics through the descriptors and description schemes, danvideo generates a mpeg-7 instance that conforms to the mpeg-7 schema, semi-automatically and effortlessly from the dance annotations.
towards efficient search on unstructured data: an intelligent-storage approach. applications that create and consume unstructured data have grown both in scale of storage requirements and complexity of search primitives. we consider two such applications: exhaustive search and integration of structured and unstructured data. current block-based storage systems are either incapable or inefficient to address the challenges bought forth by the above applications. we propose a storage framework to efficiently store and search unstructured and structured data while controlling storage management costs. experimental results based on our prototype show that the proposed system can provide impressive performance and feature benefits.
representing documents with named entities for story link detection (sld). several information organization, access, and filtering systems can benefit from different kind of document representations than those used in traditional information retrieval (ir). topic detection and tracking (tdt) is an example of such an application. in this paper we demonstrate that named entities serve as better choices of units for document representation over all words. in order to test this hypothesis we study the effect of words-based and entity-based representations on story link detection (sld) - a core task in tdt research. the experiments on tdt corpora show that entity-based representations give significant improvements for sld. we also propose a mechanism to expand the set of named entities used for document representation, which enhances the performance in some cases. we then take a step further and analyze the limitations of using only named entities for the document representation. our studies and experiments indicate that adding additional topical terms can help in addressing such limitations.
language models, probability of relevance and relevance likelihood. this paper proposes a measure of relevance likelihood derived specifically for language models. such a measure may be used to guide a user on how far to browse through the list of retrieved items or for pseudo-relevance feedback. to derive this measure, it is necessary to make the assumption that a user is seeking an ideal (usually non-existent) document and the actual relevant documents in the collection will contain fragments of this ideal document. thus, in deriving this measure we propose a novel way of capturing relevance in language modelling.
k nearest neighbor classification across multiple private databases. distributed privacy preserving data mining tools are critical for mining multiple databases with a minimum information disclosure. we present a framework including a general model as well as multi-round algorithms for mining horizontally partitioned databases using a privacy preserving k nearest neighbor (knn) classifier.
distributed spatio-temporal similarity search. in this paper we introduce the distributed spatio-temporal similarity search problem: given a query trajectory q, we want to find the trajectories that follow a motion similar to q, when each of the target trajectories is segmented across a number of distributed nodes. we propose two novel algorithms, ub-k and ublb-k, which combine local computations of lower and upper bounds on the matching between the distributed subsequences and q. such an operation generates the desired result without pulling together all the distributed subsequences over the fundamentally expensive communication medium. our solutions find applications in a wide array of domains, such as cellular networks, wild life monitoring and video surveillance. our experimental evaluation using realistic data demonstrates that our framework is both efficient and robust to a variety of conditions.
cto: concept tree based semantic overlay for pure peer-to-peer information retrieval. inspired by how search behavior works in human society, we propose cto, a self-organized semantic overlay based on concept tree for p2p ir infrastructure, which is efficient for full text search in pure p2p environment without any central control or powerful peer as hub node. especially, cto performs very well on searching the unpopular resources shared by a few peers. in our experiment, while searching for the scarce documents shared by the peers, cto achieves about 80% recall rate when the search covers less than 5% peers in the overlay. the search latency of cto is also very low, which is controlled in the range about 5~12 hops.
query-specific clustering of search results based on document-context similarity scores. this paper presents a pilot study of query-specific clustering that uses our novel document-context based similarity scores as compared with document similarity scores. clustering is applied to the top 1000 retrieved documents for a given query. clustering effectiveness is evaluated based on the mk1 score for trec-2, trec-6 and trec-7 test collections. encouraging results were obtained whereby document-context clustering produces better mk1 scores than document clustering with a 95% confidence level if precision and recall are equally important.
movie review mining and summarization. with the flourish of the web, online review is becoming a more and more useful and important information resource for people. as a result, automatic review mining and summarization has become a hot research topic recently. different from traditional text summarization, review mining and summarization aims at extracting the features on which the reviewers express their opinions and determining whether the opinions are positive or negative. in this paper, we focus on a specific domain - movie review. a multi-knowledge based approach is proposed, which integrates wordnet, statistical analysis and movie knowledge. the experimental results show the effectiveness of the proposed approach in movie review mining and summarization.
towards interactive indexing for large chinese calligraphic character databases. in this paper, based on a novel shape-similarity-based retrieval method, we propose an interactive partial-distance-map (pdm)- based high-dimensional indexing scheme to speed up the retrieval performance of the large chinese calligraphic character databases. specifically, we use the approximate minimal bounding hyper- sphere of query character to search the pdm and utilize the users' relevance feedback to refine the search process. we conduct comprehensive experiments to testify the efficiency and effectiveness of the proposed method.
a comparison of statistical significance tests for information retrieval evaluation. information retrieval (ir) researchers commonly use three tests of statistical significance: the student's paired t-test, the wilcoxon signed rank test, and the sign test. other researchers have previously proposed using both the bootstrap and fisher's randomization (permutation) test as non-parametric significance tests for ir but these tests have seen little use. for each of these five tests, we took the ad-hoc retrieval runs submitted to trecs 3 and 5-8, and for each pair of runs, we measured the statistical significance of the difference in their mean average precision. we discovered that there is little practical difference between the randomization, bootstrap, and t tests. both the wilcoxon and sign test have a poor ability to detect significance and have the potential to lead to false detections of significance. the wilcoxon and sign tests are simplified variants of the randomization test and their use should be discontinued for measuring the significance of a difference between means.
coupling feature selection and machine learning methods for navigational query identification. it is important yet hard to identify navigational queries in web search due to a lack of sufficient information in web queries, which are typically very short. in this paper we study several machine learning methods, including naive bayes model, maximum entropy model, support vector machine (svm), and stochastic gradient boosting tree (sgbt), for navigational query identification in web search. to boost the performance of these machine techniques, we exploit several feature selection methods and propose coupling feature selection with classification approaches to achieve the best performance. different from most prior work that uses a small number of features, in this paper, we study the problem of identifying navigational queries with thousands of available features, extracted from major commercial search engine results, web search user click data, query log, and the whole web's relational content. a multi-level feature extraction system is constructed.our results on real search data show that 1) among all the features we tested, user click distribution features are the most important set of features for identifying navigational queries. 2) in order to achieve good performance, machine learning approaches have to be coupled with good feature selection methods. we find that gradient boosting tree, coupled with linear svm feature selection is most effective. 3) with carefully coupled feature selection and classification approaches, navigational queries can be accurately identified with 88.1% f1 score, which is 33% error rate reduction compared to the best uncoupled system, and 40% error rate reduction compared to a well tuned system without feature selection.
automatic computation of semantic proximity using taxonomic knowledge. taxonomic measures of semantic proximity allow us to compute the relatedness of two concepts. these metrics are versatile instruments required for diverse applications, e.g., the semantic web, linguistics, and also text mining. however, most approaches are only geared towards hand-crafted taxonomic dictionaries such as wordnet, which only feature a limited fraction of real-world concepts. more specific concepts, and particularly instances of concepts, i.e., names of artists, locations, brand names, etc., are not covered.the contributions of this paper are two fold. first, we introduce a framework based on google and the open directory project (odp), enabling us to derive the semantic proximity between arbitrary concepts and instances. second, we introduce a new taxonomy-driven proximity metric tailored for our framework. studies with human subjects corroborate our hypothesis that our new metric outperforms benchmark semantic proximity metrics and comes close to human judgement.
index compression is good, especially for random access. index compression techniques are known to substantially decrease the storage requirements of a text retrieval system. as a side-effect, they may increase its retrieval performance by reducing disk i/o overhead. despite this advantage, developers sometimes choose to store index data in uncompressed form, in order to not obstruct random access into each index term's postings list. in this paper, we show that index compression does not harm random access performance. in fact, we demonstrate that, in some cases, random access into a term's postings list may be realized more efficiently if the list is stored in compressed form instead of uncompressed. this is regardless of whether the index is stored on disk or in main memory, since both types of storage - hard drives and ram - do not support efficient random access in the first place.
on the structural properties of massive telecom call graphs: findings and implications. with ever growing competition in telecommunications markets, operators have to increasingly rely on business intelligence to offer the right incentives to their customers. toward this end, existing approaches have almost solely focussed on the individual behaviour of customers. call graphs, that is, graphs induced by people calling each other, can allow telecom operators to better understand the interaction behaviour of their customers, and potentially provide major insights for designing effective incentives.in this paper, we use the call detail records of a mobile operator from four geographically disparate regions to construct call graphs, and analyse their structural properties. our findings provide business insights and help devise strategies for mobile telecom operators. another goal of this paper is to identify the shape of such graphs. in order to do so, we extend the well-known reachability analysis approach with some of our own techniques to reveal the shape of such massive graphs. based on our analysis, we introduce the treasure-hunt model to describe the shape of mobile call graphs. the proposed techniques are general enough for analysing any large graph. finally, how well the proposed model captures the shape of other mobile call graphs needs to be the subject of future studies.
trips and tides: new algorithms for tree mining. recent research in data mining has progressed from mining frequent itemsets to more general and structured patterns like trees and graphs. in this paper, we address the problem of frequent subtree mining that has proven to be viable in a wide range of applications such as bioinformatics, xml processing, computational linguistics, and web usage mining. we propose novel algorithms to mine frequent subtrees from a database of rooted trees. we evaluate the use of two popular sequential encodings of trees to systematically generate and evaluate the candidate patterns. the proposed approach is very generic and can be used to mine embedded or induced subtrees that can be labeled, unlabeled, ordered, unordered, or edge-labeled. our algorithms are highly cache-conscious in nature because of the compact and simple array-based data structures we use. typically, l1 and l2 hit rates above 99% are observed. experimental evaluation showed that our algorithms can achieve up to several orders of magnitude speedup on real datasets when compared to state-of-the-art tree mining algorithms.
optimisation methods for ranking functions with multiple parameters. optimising the parameters of ranking functions with respect to standard ir rank-dependent cost functions has eluded satisfactory analytical treatment. we build on recent advances in alternative differentiable pairwise cost functions, and show that these techniques can be successfully applied to tuning the parameters of an existing family of ir scoring functions (bm25), in the sense that we cannot do better using sensible search heuristics that directly optimize the rank-based cost function ndcg. we also demonstrate how the size of training set affects the number of parameters we can hope to tune this way.
efficient search ranking in social networks. in social networks such as orkut, www.orkut.com, a large portion of the user queries refer to names of other people. indeed, more than 50% of the queries in orkut are about names of other users, with an average of 1.8 terms per query. further, the users usually search for people with whom they maintain relationships in the network. these relationships can be modelled as edges in a friendship graph, a graph in which the nodes represent the users. in this context, search ranking can be modelled as a function that depends on the distances among users in the graph, more specifically, of shortest paths in the friendship graph. however, application of this idea to ranking is not straightforward because the large size of modern social networks (dozens of millions of users) prevents efficient computation of shortest paths at query time. we overcome this by designing a ranking formula that strikes a balance between producing good results and reducing query processing time. using data from the orkut social network, which includes over 40 million users, we show that our ranking, augmented by this new signal, produces high quality results, while maintaining query processing time small.
a structure-oriented relevance feedback method for xml retrieval. relevance feedback (rf) is a technique allowing to enrich an initial query according to the user feedback. the goal is to express more precisily the user's needs. some open issues appear when considering semi-structured documents like xml documents. most of the rf approaches proposed in xml retrieval are simple adaptations of traditional rf to the new granularity of information. they enrich queries by adding terms extracted from relevant elements instead of terms extracted from whole documents. in this paper we show how structural constraints can also be used in rf. we propose a new approach that is able to extend the initial query by adding one or more generative structures. this approach is applied to unstructured queries. experiments are carried out on inex collection and results show the interest of our method.
probabilistic document-context based relevance feedback with limited relevance judgments. this paper presents our novel relevance feedback (rf) algorithm that uses the probabilistic document-context based retrieval model with limited relevance judgments for document re-ranking. probabilities of the document-context based retrieval model are estimated from the top n (=20) documents in the initial retrieval. we use document-context based cosine similarity measure to find similar data for better probability estimation in order to reduce the data scarcity problem and the negative weighting problem. our rf algorithm is promising because its mean average precision is statistically significantly better than the baseline using trec-6 and trec-7 data collections.
a novel scheme for domain-transfer problem in the context of sentiment analysis. in this work, we attempt to tackle domain-transfer problem by combining old-domain labeled examples with new-domain unlabeled ones. the basic idea is to use old-domain-trained classifier to label some informative unlabeled examples in new domain, and retrain the base classifier over these selected examples. the experimental results demonstrate that proposed scheme can significantly boost the accuracy of the base sentiment classifier on new domain.
term context models for information retrieval. at their heart, most if not all information retrieval models utilize some form of term frequency.the notion is that the more often a query term occurs in a document, the more likely it is that document meets an information need. we examine an alternative. we propose a model which assesses the presence of a term in a document not by looking at the actual occurrence of that term, but by a set of non-independent supporting terms, i.e. context. this yields a weighting for terms in documents which is different from and complementary to tf-based methods, and is beneficial for retrieval.
a combination of trie-trees and inverted files for the indexing of set-valued attributes. set-valued attributes frequently occur in contexts like market-basked analysis and stock market trends. late research literature has mainly focused on set containment joins and data mining without considering simple queries on set valued attributes. in this paper we address superset, subset and equality queries and we propose a novel indexing scheme for answering them on set-valued attributes. the proposed index superimposes a trie-tree on top of an inverted file that indexes a relation with set-valued data. we show that we can efficiently answer the aforementioned queries by indexing only a subset of the most frequent of the items that occur in the indexed relation. finally, we show through extensive experiments that our approach outperforms the state of the art mechanisms and scales gracefully as database size grows.
evaluation by comparing result sets in context. familiar evaluation methodologies for information retrieval (ir) are not well suited to the task of comparing systems in many real settings. these systems and evaluation methods must support contextual, interactive retrieval over changing, heterogeneous data collections, including private and confidential information.we have implemented a comparison tool which can be inserted into the natural ir process. it provides a familiar search interface, presents a small number of result sets in side-by-side panels, elicits searcher judgments, and logs interaction events. the tool permits study of real information needs as they occur, uses the documents actually available at the time of the search, and records judgments taking into account the instantaneous needs of the searcher.we have validated our proposed evaluation approach and explored potential biases by comparing different whole-of-web search facilities using a web-based version of the tool. in four experiments, one with supplied queries in the laboratory and three with real queries in the workplace, subjects showed no discernable left-right bias and were able to reliably distinguish between high- and low-quality result sets. we found that judgments were strongly predicted by simple implicit measures.following validation we undertook a case study comparing two leading whole-of-web search engines. the approach is now being used in several ongoing investigations.
practical private data matching deterrent to spoofing attacks. private data matching between the data sets of two potentially distrusted parties has a wide range of applications. however, existing solutions have substantial weaknesses and do not meet the needs of many practical application scenarios. in particular, practical private data matching applications often require discouraging the matching parties from spoofing their private inputs. in this paper, we address this challenge by forcing the matching parties to "escrow" the data they use for matching to an auditorial agent, and in the "after-the-fact" period, they undertake the liability to attest the genuineness of the escrowed data.
high-performance distributed inverted files. we present a general method of parallel query processing that allows scalable performance on distributed inverted files. the method allows the realization of a hybrid that combines the advantages of the document and term partitioned inverted files.
adapting association patterns for text categorization: weaknesses and enhancements. the use of association patterns for text categorization has attracted great interest and a variety of useful methods have been developed. however, the key characteristics of pattern-based text categorization remain unclear. indeed, there are still no concrete answers for the following two questions: first, what kind of association patterns are the best candidate for pattern-based text categorization? second, what is the most desirable way to use patterns for text categorization? in this paper, we focus on answering the above two questions. specifically, we show that hyperclique patterns are more desirable than frequent patterns for text categorization. along this line, we develop an algorithm for text categorization using hyperclique patterns. the experimental results show that our method provides better performance than state-of-the-art methods in terms of both computational performance and classification accuracy.
classification spanning correlated data streams. in many applications, classifiers need to be built based on multiple related data streams. for example, stock streams and news streams are related, where the classification patterns may involve features from both streams. thus instead of mining on a single isolated stream, we need to examine multiple related data streams in order to find such patterns and build an accurate classifier. other examples of related streams include traffic reports and car accidents, sensor readings of different types or at different locations, etc. in this paper, we consider the classification problem defined over sliding-window join of several input data streams. as the data streams arrive in fast pace and the many-to-many join relationship blows up the data arrival rate even more, it is impractical to compute the join and then build the classifier each time the window slides forward. we present an efficient algorithm to build a naïve bayesian classifier in such context. our method does not need to perform the join operations but is still able to build exactly the same classifier as if built on the joined result. it only examines each input tuple twice, independent of the number of tuples it joins in other streams, therefore, is able to keep pace with the fast arriving data streams in the presence of many-to-many join relationships. the experiments confirmed that our classification algorithm is more efficient than conventional methods while maintaining good classification accuracy.
ranking robustness: a novel framework to predict query performance. in this paper, we introduce the notion of ranking robustness, which refers to a property of a ranked list of documents that indicates how stable the ranking is in the presence of uncertainty in the ranked documents. we propose a statistical measure called the robustness score to quantify this notion. we demonstrate that the robustness score significantly and consistently correlates with query performance in a variety of trec test collections including the gov2 collection. we compare the robustness score with the clarity score method which is the state-of-the-art technique for query performance prediction. our experimental results show that the robustness score performs better than or at least as good as the clarity score. we find that the clarity score is barely correlated with query performance on the gov2 collection while the correlation between the robustness score and query performance remains significant. we also notice that a combination of the two usually results in more prediction power.
an on-line interactive method for finding association rules data streams. in order to trace the changes of association rules over an online data stream efficiently, this paper proposes two different methods of generating all association rules directly over the changing set of currently frequent itemsets. while all of the currently frequent itemsets are monitored by the estdec method, all the association rules of every frequent itemset in the prefix tree of the estdec method are generated. for this purpose, a traversal stack is introduced to efficiently enumerate all association rules. these online methods can avoid the drawbacks of the conventional two-step approach. in an on-line environment, a user may be interested in finding those association rules whose antecedents or consequents are fixed to be a specific itemset. since generating all the association rules may take too long to produce them timely, two additional methods, namely assoc-x and assoc-y, are introduced. finally, the proposed methods are compared by a series of experiments to identify their various characteristics.
spam filtering for short messages. we consider the problem of content-based spam filtering for short text messages that arise in three contexts: mobile (sms) communication, blog comments, and email summary information such as might be displayed by a low-bandwidth client. short messages often consist of only a few words, and therefore present a challenge to traditional bag-of-words based spam filters. using three corpora of short messages and message fields derived from real sms, blog, and spam messages, we evaluate feature-based and compression-model-based spam filters. we observe that bag-of-words filters can be improved substantially using different features, while compression-model filters perform quite well as-is. we conclude that content filtering for short messages is surprisingly effective.
a segment-based hidden markov model for real-setting pinyin-to-chinese conversion. hidden markov model (hmm) is frequently used for pinyin-to-chinese conversion. but it only captures the dependency with the preceding character. higher order markov models can bring higher accuracy, but are computationally unaffordable to average pc settings. we propose a segment-based hidden markov model (shmm), which has the same magnitude of complexity as first-order hmm, but generates higher decoding accuracy. shmm tells a word from a bigram connecting two words, and assigns a reasonable probability to words as a whole. it is more powerful than hmm to decode words containing over two characters. we conduct a comprehensive pinyin-to-chinese conversion evaluation on lancaster corpus. the experiment shows the perfect sentence accuracy is improved from 34.7% (hmm) to 43.3% (shmm). the one-error sentence accuracy is increased from 72.7% to 78.3%. furthermore, shmm can seamlessly integrate with pinyin typing correction, acronym pinyin input, user-defined words, and self-adaptive learning all of which are a must for a commercial pinyin-to-chinese conversion product in order to improve the efficiency of pinyin input.
efficient range-constrained similarity search on wavelet synopses over multiple streams. due to the resource limitation in the data stream environment, it has been reported that answering user queries according to the wavelet synopsis of a stream is an essential ability of a data stream management system (dsms). in this paper, motivated by the fact that a user may be interested in an arbitrary range of the data streams, we investigate two important types of range-constrained queries in time series streaming environments: the distance queries (which aim at obtaining the euclidean distance between two streams) and the knn queries (which aim at discovering k nearest neighbors to a reference stream). to achieve high efficiency in processing these two types of queries, we propose procedure red (standing for range-constrained euclidean distance) and algorithm eks (standing for enhanced knn search). compared to the existing methods in the prior research, the advantageous features of our approaches are in two folds. first, our approaches are capable of processing the queries directly from the wavelet synopses retained in the main memory without using idwt to reconstruct the data cells. this feature allows us to save the complexity in both memory and time. moreover, our approaches enable the users to query the dsms within their range of interest. unlike the conventional methods which only support the full-range query processing, this feature will enhance the flexibility at the client side. we evaluate procedure red and algorithm eks on live and synthetic datasets empirically and show that the proposed approaches are efficient in similarity search and knn discovery within arbitrary ranges in the time series streaming environments.
concept frequency distribution in biomedical text summarization. text summarization is a data reduction process. the use of text summarization enables users to reduce the amount of text that must be read while still assimilating the core information. the data reduction offered by text summarization is particularly useful in the biomedical domain, where physicians must continuously find clinical trial study information to incorporate into their patient treatment efforts. such efforts are often hampered by the high-volume of publications. our contribution is two-fold: 1) to propose the frequency of domain concepts as a method to identify important sentences within a full-text; and 2) propose a novel frequency distribution model and algorithm for identifying important sentences based on term or concept frequency distribution. an evaluation of several existing summarization systems using biomedical texts is presented in order to determine a performance baseline. for domain concept comparison, a recent high-performing frequency-based algorithm using terms is adapted to use concepts and evaluated using both terms and concepts. it is shown that the use of concepts performs closely with the use of terms for sentence selection. our proposed frequency distribution model and algorithm outperforms a state-of-the-art approach.
exploiting asymmetry in hierarchical topic extraction. topic or feature extraction is often used as an important step in document classification and text mining. topics are succinct representation of content in a document collection and hence are very effective when used as content identifiers in peer-to-peer systems and other large scale distributed content management systems. effective topic extraction is dependent on the accuracy of term clustering that often has to deal with problems like synonymy and polysemy. retrieval techniques based on spectral analysis like latent semantic indexing (lsi) are often used to effectively solve these problems. most of the spectral retrieval schemes produce term similarity measures that are symmetric and often, not an accurate characterization of term relationships. another drawback of lsi is its running time that is polynomial in the dimensions of the m x n matrix, a. this can get prohibitively large for some ir applications. in this paper, we present efficient algorithms using the technique of locality-sensitive hashing (lsh) to extract topics from a document collection based on the asymmetric relationships between terms in a collection. the relationship is characterized by the term co-occurrences and other higher-order similarity measures. our lsh based scheme can be viewed as a simple alternative to lsi. we show the efficacy of our algorithms via experiments on a set of large documents. an interesting feature of our algorithms is that it produces a natural hierarchical decomposition of the topic space instead of a flat clustering.
privacy preserving sequential pattern mining in distributed databases. research in the areas of privacy preserving techniques in databases and subsequently in privacy enhancement technologies have witnessed an explosive growth-spurt in recent years. this escalation has been fueled by the growing mistrust of individuals towards organizations collecting and disbursing their personally identifiable information (pii). digital repositories have become increasingly susceptible to intentional or unintentional abuse, resulting in organizations to be liable under the privacy legislations that are being adopted by governments the world over. these privacy concerns have necessitated new advancements in the field of distributed data mining wherein, collaborating parties may be legally bound not to reveal the private information of their customers. in this paper, we present a new algorithm pripsep (privacy preserving sequential patterns) for the mining of sequential patterns from distributed databases while preserving privacy. a salient feature of pripsep is that due to its flexibility it is more pertinent to mining operations for real world applications in terms of efficiency and functionality. under some reasonable assumptions, we prove that our architecture and protocol employed by our algorithm for multi-party computation is secure.
the real-time nature and value of homeland security information. ensuring the security of our homeland depends in large measure on two quite distinct factors: having the knowledge necessary to prevent, predict, prepare for, or respond, if necessary, to any manner of terrorist attack or a natural or manmade disaster and collaborating or sharing knowledge with a broad range of international, federal, state, local, and tribal agencies, as well as other private or public organizations. the essential problem with adequately addressing these factors, despite the many advancements made in the past decade, is twofold. first, it is not so much the mass but rather the diffuse nature and complexity of the data, information, and knowledge required for understanding terrorism and accounting for the manifold consequences of disasters that make possession of the right knowledge difficult. and, second, that diffuseness and complexity is magnified by the extreme diversity and wide distribution of the many potential homeland security collaborators. retrospective analysis, and even knowledge discovery, is less useful under these conditions than prospective, real-time synthesis of information for multiple users. also, privacy is as important as, if not more important than, security. this suggests that database designs and techniques for information retrieval, and knowledge management must take advantage of such technologies as semantic nets, visualization, and discrete mathematics to build knowledge systems capable for homeland security applications.
finding dense and isolated submarkets in a sponsored search spending graph. methods for improving sponsored search revenue are often tested or deployed within a small submarket of the larger marketplace. for many applications, the ideal submarket contains a small number of nodes, a large amount of spending within the submarket, and a small amount of spending leaving the submarket. we introduce an efficient algorithm for finding submarkets that are optimal for a user-specified tradeoff between these three quantities. we apply our algorithm to find submarkets that are both dense and isolated in a large spending graph from yahoo! sponsored search.
on gmap: and other transformations. as an alternative to the usual mean average precision, some use is currently being made of the geometric mean average precision (gmap) as a measure of average search effectiveness across topics. gmap is specifically used to emphasise the lower end of the average precision scale, in order to shed light on poor performance of search engines. this paper discusses the status of this measure and how it should be understood.
type nanotheories: a framework for term comparison. we present in this paper type nanotheories (tn), a framework for representing the knowledge necessary for performing similarity comparisons between pairs of terms of the same type. tn itself uses another methodology, namely support outcomes, which is also introduced. many ir and nlp applications use redundancy as a factor to increase confidence, and tn-based comparisons can determine redundancy better than simple string comparisons. results include a showing of a 14% increase in confidence-weighted score for an end-to-end qa system and an up to 68% improvement over baseline in an answer-key equivalencing experiment.
concept-based document readability in domain specific information retrieval. domain specific information retrieval has become in demand. not only domain experts, but also average non-expert users are interested in searching domain specific (e.g., medical and health) information from online resources. however, a typical problem to average users is that the search results are always a mixture of documents with different levels of readability. non-expert users may want to see documents with higher readability on the top of the list. consequently the search results need to be re-ranked in a descending order of readability. it is often not practical for domain experts to manually label the readability of documents for large databases. computational models of readability needs to be investigated. however, traditional readability formulas are designed for general purpose text and insufficient to deal with technical materials for domain specific information retrieval. more advanced algorithms such as textual coherence model are computationally expensive for re-ranking a large number of retrieved documents. in this paper, we propose an effective and computationally tractable concept-based model of text readability. in addition to textual genres of a document, our model also takes into account domain specific knowledge, i.e., how the domain-specific concepts contained in the document affect the document's readability. three major readability formulas are proposed and applied to health and medical information retrieval. experimental results show that our proposed readability formulas lead to remarkable improvements in terms of correlation with users' readability ratings over four traditional readability measures.
autonomously semantifying wikipedia. berners-lee's compelling vision of a semantic web is hindered by a chicken-and-egg problem, which can be best solved by a bootstrapping method - creating enough structured data to motivate the development of applications. this paper argues that autonomously "semantifying wikipedia" is the best way to solve the problem. we choose wikipedia as an initial data source, because it is comprehensive, not too large, high-quality, and contains enough manually-derived structure to bootstrap an autonomous, self-supervised process. we identify several types of structures which can be automatically enhanced in wikipedia (e.g., link structure, taxonomic data, infoboxes, etc.), and we describea prototype implementation of a self-supervised, machine learning system which realizes our vision. preliminary experiments demonstrate the high precision of our system's extracted data - in one case equaling that of humans.
matching directories and owl ontologies with aroma. this paper presents a simple and adaptable matching method dealing with web directories, catalogs and owl ontologies. by using a well-known knowledge discovery in databases model, such as the association rule paradigm, this method has the originality to be both extensional and asymmetric. it works at the terminological level (by selecting concept-relevant terms contained in documents) and permits to discover equivalence and also subsumption relations holding between entities (concepts and properties). this method relies on the implication intensity measure, a probabilistic model of deviation from independence. selection of significant rules between concepts (or properties) is lead by two criteria permitting to assess respectively the implication quality and the generativity of the rule. finally, the proposed method is evaluated on two benchmarks. the first contains two conceptual hierarchies populated with textual documents and the second one is composed of owl ontologies.
on subspace clustering with density consciousness. in this paper, a problem, called "the density divergence problem" is explored. this problem is related to the phenomenon that the densities of the clusters vary in different subspace cardinalities. we take the densities into consideration in subspace clustering and explore an algorithm to adaptively determine different density thresholds to discover clusters in different subspace cardinalities.
a system for query-specific document summarization. there has been a great amount of work on query-independent summarization of documents. however, due to the success of web search engines query-specific document summarization (query result snippets) has become an important problem, which has received little attention. we present a method to create query-specific summaries by identifying the most query-relevant fragments and combining them using the semantic associations within the document. in particular, we first add structure to the documents in the preprocessing stage and convert them to document graphs. then, the best summaries are computed by calculating the top spanning trees on the document graphs. we present and experimentally evaluate efficient algorithms that support computing summaries in interactive time. furthermore, the quality of our summarization method is compared to current approaches using a user survey.
efficient model selection for regularized linear discriminant analysis. classical linear discriminant analysis (lda) is not applicable for small sample size problems due to the singularity of the scatter matrices involved. regularized lda (rlda) provides a simple strategy to overcome the singularity problem by applying a regularization term, which is commonly estimated via cross-validation from a set of candidates. however, cross-validation may be computationally prohibitive when the candidate set is large. an efficient algorithm for rlda is presented that computes the optimal transformation of rlda for a large set of parameter candidates, with approximately the same cost as running rlda a small number of times. thus it facilitates efficient model selection for rlda.an intrinsic relationship between rlda and uncorrelated lda (ulda), which was recently proposed for dimension reduction and classification is presented. more specifically, rlda is shown to approach ulda when the regularization value tends to zero. that is, rlda without any regularization is equivalent to ulda. it can be further shown that ulda maps all data points from the same class to a common point, under a mild condition which has been shown to hold for many high-dimensional datasets. this leads to the overfitting problem in ulda, which has been observed in several applications. thetheoretical analysis presented provides further justification for the use of regularization in rlda. extensive experiments confirm the claimed theoretical estimate of efficiency. experiments also show that, for a properly chosen regularization parameter, rlda performs favorably in classification, in comparison with ulda, as well as other existing lda-based algorithms and support vector machines (svm).
a cdd-based formal model for expert finding. searching an organization's document repositories for experts is a frequently faced problem in intranet information management. this paper proposes a candidate-centered model which is referred as candidate description document (cdd)-based retrieval model. the expertise evidence about an expert candidate scattered over repositories is mined and aggregated automatically to form a profile called the candidate's cdd, which represents his knowledge. we present the model from its foundations through its logical development and argue in favor of this model for expert finding. we devise and compare the different strategies for exploring a variety of expertise evidence. the experiments on trec enterprise corpora demonstrate that the cdd-based model achieves significant and consistent improvement on performance through comparative studies with non-cdd methods.
pseudo-anchor text extraction for searching vertical objects. this paper examines the problem of utilizing pseudo-anchor text to help ranking web objects in vertical search. we adopt a machine learning based approach to extract pseudo-anchor text for a vertical object from its candidate anchor blocks. experiments in academic search domain indicate that our approach is able to dramatically improve search performance.
heuristic containment check of partial tree-pattern queries in the presence of index graphs. the wide adoption of xml has increased the interest of the database community on tree-structured data management techniques. querying capabilities are provided through tree-pattern queries. the need for querying tree-structured data sources when their structure is not fully known, and the need to integrate multiple data sources with different tree structures have driven, recently, the suggestion of query languages that relax the complete specification of a tree pattern. in this paper, we use a query language which allows partial tree-pattern queries (ptpqs). the structure in a ptpq can be flexibly specified fully, partially or not at all. to evaluate a ptpq, we exploit index graphs which generate an equivalent set of "complete" tree-pattern queries.in order to process ptpqs, we need to efficiently solve the ptpq satisfiability and containment problems. these problems become more complex in the context of ptpqs because the partial specification of the structure allows new, non-trivial, structural expressions to be derived from those explicitly specified in a ptpq. we address the problem of ptpq satisfiability and containment in the absence and in the presence of index graphs, and we provide necessary and sufficient conditions for each case. to cope with the high complexity of ptpq containment in the presence of index graphs,we study a family of heuristic approaches for ptpq containment based on structural information extracted from the index graph in advance and on-the-fly. we implement our approaches and we report on their extensive experimental evaluation and comparison.
comparing the effectiveness of hits and salsa. this paper compares the effectiveness of two well-known query-dependent link-based ranking algorithms, "hyperlink-induced topic search" (hits) and the "stochastic approach for link-structure analysis" (salsa). the two algorithms are evaluated on a very large web graph induced by 463 million crawled web pages and a set of 28,043 queries and 485,656 results labeled by human judges. we employed three different performance measures - mean average precision (map), mean reciprocal rank (mrr), and normalized discounted cumulative gain (ndcg). we found that as an isolated feature, salsa substantially outperforms hits. this is quite surprising, given that the two algorithms operate over the same neighborhood graph induced by the query result set. we also studied the combination of salsa and hits with bm25f, a state-of-the-art text-based scoring function that incorporates anchor text. we found that the combination of salsa and bm25f outperforms the combination of hits and bm25f. finally, we broke down our query set by query specificity, and found that salsa (and to a lesser extent hits) is most effective for general queries.
task-based process know-how reuse and proactive information delivery in tasknavigator. knowledge management approaches for weakly-structured, adhoc knowledge work processes need to be lightweight, i.e., they cannot rely on high upfront modeling efforts. this paper presents tasknavigator, a novel prototype to support weakly-structured processes by integrating a standard task list application with a state-of-the-art document classification system. the resulting system allows for a task-oriented view on office workers' personal knowledge spaces in order to realize a proactive and contextsensitive information support during daily, knowledge-intensive tasks. moreover, tasknavigator supports process know-how reuse by proactively suggesting similar tasks or relevant process models, based on textual similarities. finally, we report on a feasibility test and a case study that have been conducted in order to evaluate the system in the context of daily research task management and software requirements analysis.
improving query i/o performance by permuting and refining block request sequences. the i/o performance of query processing can be improved using two complementary approaches: improve the buffer and the file system management policies of the db buffer manager and the os file system manager (e.g. page replacement), or improve the sequence of requests that are submitted to a file system manager and that lead to actual i/o's (block request sequences). this paper takes the latter approach. exploiting common file system practices as found in linux, we propose four techniques for permuting and refining block request sequences: block-level i/o grouping, file-level i/o grouping, i/o ordering, and block recycling. to manifest these techniques, we create two new plan operations, mms and shj, each of which adopts some of the block request refinement techniques above. we implement the new plan operations on top of postgres running on linux, and show experimental results that demonstrate up to a factor of 4 performance benefit from the use of these techniques.
effective keyword search for valuable lcas over xml documents. in this paper, we study the problem of effective keyword search over xml documents. we begin by introducing the notion of valuable lowest common ancestor (vlca) to accurately and effectively answer keyword queries over xml documents. we then propose the concept of compact vlca (cvlca) and compute the meaningful compact connected trees rooted as cvlcas as the answers of keyword queries. to efficiently compute cvlcas, we devise an effective optimization strategy for speeding up the computation, and exploit the key properties of cvlca in the design of the stack-based algorithm for answering keyword queries. we have conducted an extensive experimental study and the experimental results show that our proposed approach achieves both high efficiency and effectiveness when compared with existing proposals.
an efficient one-phase holistic twig join algorithm for xml data. in view of the inefficiency of the traditional two-phase twig-stack algorithm, we propose a single-phase holistic twig pattern matching method based on the twigstack algorithm by applying a novel stack structure.
on progressive sequential pattern mining. when sequential patterns are generated, the newly arriving patterns may not be identified as frequent sequential patterns due to the existence of old data and sequences. in practice, users are usually more interested in the recent data than the old ones. to capture the dynamic nature of data addition and deletion, we propose a general model of sequential pattern mining with a progressive database. in addition, we present a progressive concept to progressively discover sequential patterns in recent time period of interest.
predictive user click models based on click-through history. web search engines consistently collect information about users interaction with the system: they record the query they issued, the url of presented and selected documents along with their ranking. this information is very valuable: it is a poll over millions of users on the most various topics and it has been used in many ways to mine users interests and preferences. query logs have the potential to partially alleviate the search engines from thousand of searches by providing a way to predict answers for a subset of queries and users without knowing the content of a document. even if the predicted result is at rank one, this analysis might be of interest: if there is enough confidence on a user's click, we might redirect the user directly to the page whose link would be clicked. in this paper, we present three different models for predicting user clicks, ranging from most specific ones (using only past user history for the query) to very general ones (aggregating data over all users for a given query). the former model has a very high precision at low recall values, while the latter can achieve high recalls. we show that it is possible to combine the different models to predict with high accuracy (over 90%) a high subset of query sessions (24% of all the sessions).
annotation propagation revisited for key preserving views. this paper revisits the analysis of annotation propagation from source databases to views defined in terms of conjunctive (spj) queries. given a source database d, an spj query q, the view q(d) and a tuple δv in the view, the view (resp. source) side-effect problem is to find a minimal set δd of tuples such that the deletion of δd from d results in the deletion of δv from q(d) while minimizing the side effects on the view (resp. the source). a third problem, referred to as the annotation placement problem, is to find a single base tuple δd such that annotation in a field of δd propagates to δv while minimizing the propagation to other fields in the view q(d). these are important for data provenance and the management of view updates. however important, these problems are unfortunately np-hard for most subclasses of spj views [5].to make the annotation propagation analysis feasible in practice, we propose a key preserving condition on spj views, which requires that the projection fields of an spj view q retain a key of each base relation involved in q. while this condition is less restrictive than other proposals [11, 14], it often simplifies the annotation propagation analysis. indeed, for key-preserving spj views the annotation placement problem coincides with the view side-effect problem, and the view and source side-effect problems become tractable. in addition we generalize the setting of [5] by allowing δv to be a group of tuples to be deleted, and investigate the insertion of tuples to the view. we show that group updates make the analysis harder: these problems become np-hard for several subclasses of spj views. we also show that for spj views the source and view side-effect problems are np-hard for single-tuple insertion, but are tractable for some subclasses of spj for group insertions, in the presence or in the absence of the key preservation condition.
discovering and exploiting keyword and attribute-value co-occurrences to improve p2p routing indices. peer-to-peer (p2p) search requires intelligent decisions for query routing: selecting the best peers to which a given query, initiated at some peer, should be forwarded for retrieving additional search results. these decisions are based on statistical summaries for each peer, which are usually organized on a per-keyword basis and managed in a distributed directory of routing indices. such architectures disregard the possible correlations among keywords. together with the coarse granularity of per-peer summaries, which are mandated for scalability, this limitation may lead to poor search result quality.this paper develops and evaluates two solutions to this problem, sk-stat based on single-key statistics only, and mk-stat based on additional multi-key statistics. for both cases, hash sketch synopses are used to compactly represent a peer's data items and are efficiently disseminated in the p2p network to form a decentralized directory. experimental studies with gnutella and web data demonstrate the viability and the trade-offs of the approaches.
introduction to a new farsi stemmer. in this poster, a new farsi (also called persian) stemmer which works without dictionary is introduced. evaluation results show significant improvement in performance (precision/recall) of the information retrieval (ir) system using this stemmer.
window join approximation over data streams with importance semantics. load shedding techniques generate approximate sliding window join results when memory constraints prevent exact computation. the previously proposed random load shedding method drops input tuples without consideration for the number of outputs created, while the recently proposed semantic load shedding technique aims to produce the largest possible result set. we consider a new model in which data stream tuples contain numerical importance values relevant to the query source and seek to maximize the importance of the approximate join result. we show that both random load shedding and semantic load shedding are sub-optimal in this situation, while the techniques presented in this paper satisfy the objective function by considering both tuple importance and join attribute distributions. we extend the existing offline semantic approximation technique to make it compatible with our objective function and show that it is less space and time efficient than our new optimal offline algorithm for small and large join memory allotments. we also introduce four efficient online algorithms, which are quite promising in maximizing the importance of the approximate join result without foreknowledge of input streams.
efficiently clustering transactional data with weighted coverage density. it is widely recognized that developing efficient and fully automated algorithms for clustering large transactional datasets is a challenging problem. in this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. our approach has three unique features. first, we use the concept of weighted coverage density as a categorical similarity measure for efficient clustering of transactional datasets. the concept of weighted coverage density is intuitive and allows the weight of each item in a cluster to be changed dynamically according to the occurrences of items. second, we develop two transactional data clustering specific evaluation metrics based on the concept of large transactional items and the coverage density respectively. third, we implement the weighted coverage density clustering algorithm and the two clustering validation metrics using a fully automated transactional clustering framework, called scale (sampling, clustering structure assessment, clustering and domain-specific evaluation). the scale framework is designed to combine the weighted coverage density measure for clustering over a sample dataset with self-configuring methods that can automatically tune the two important parameters of the clustering algorithms: (1) the candidates of the best number k of clusters; and (2) the application of two domain-specific cluster validity measures to find the best result from the set of clustering results. we have conducted experimental evaluation using both synthetic and real datasets and our results show that the weighted coverage density approach powered by the scale framework can efficiently generate high quality clustering results in a fully automated manner.
ontology module extraction for ontology reuse: an ontology engineering perspective. problems resulting from the management of shared, distributed knowledge has led to ontologies being employed as a solution, in order to effectively integrate information across applications. this is dependent on having ways to share and reuse existing ontologies; with the increased availability of ontologies on the web, some of which include thousands of concepts, novel and more efficient methods for reuse are being devised. one possible way to achieve efficient ontology reuse is through the process of ontology module extraction. a novel approach to ontology module extraction is presented that aims to achieve more efficient reuse of very large ontologies; the motivation is drawn from an ontology engineering perspective. this paper provides a definition of ontology modules from the reuse perspective and an approach to module extraction based on such a definition. an abstract graph model for module extraction has been defined, along with a module extraction algorithm. the novel contribution of this paper is a module extraction algorithm that is independent of the language in which the ontology is expressed. this has been implemented in modtool; a tool that produces ontology modules via extraction. experiments were conducted to compare modtool to other modularisation methods.
the visual funding navigator: analysis of the nsf funding information. this paper presents an interactive visualization toolkit for navigating and analyzing the national science foundation (nsf) funding information. our design builds upon an improved 2.5d treemap layout and the stacked graph to contribute customized techniques for visually navigating and interacting with the hierarchical data of nsf programs and proposals. furthermore, an incremental layout method is adopted to handle information on a large scale. the improved treemap visualization will help to visually analyze the static funding related data and the stacked graph is utilized to analyze the time-series data. through these visual analysis techniques, research trends of nsf, popular nsf programs are quickly identified.
utilizing a geometry of context for enhanced implicit feedback. implicit feedback algorithms utilize interaction between searchers and search systems to learn more about users' needs and interests than expressed in query statements alone. this additional information can be used to formulate improved queries or directly improve retrieval performance. in this paper we present a geometric framework that utilizes multiple sources of evidence present in this interaction context (e.g., display time, document retention) to develop enhanced implicit feedback models personalized for each user and tailored for each search task. we use rich interaction logs (and associated metadata such as relevance judgments), gathered during a longitudinal user study, as relevance stimuli to compare an implicit feedback algorithm developed using the framework with alternative algorithms. our findings demonstrate both the effectiveness of our proposed algorithm and the potential value of incorporating multiple sources of interaction evidence when developing implicit feedback algorithms.
incorporating query difference for learning retrieval functions in world wide web search. we discuss information retrieval methods that aim at serving a diverse stream of user queries such as those submitted to commercial search engines. we propose methods that emphasize the importance of taking into consideration of query difference in learning effective retrieval functions. we formulate the problem as a multi-task learning problem using a risk minimization framework. in particular, we show how to calibrate the empirical risk to incorporate query difference in terms of introducing nuisance parameters in the statistical models, and we also propose an alternating optimization method to simultaneously learn the retrieval function and the nuisance parameters. we work out the details for both l1 and l2 regularization cases, and provide convergence analysis for the alternating optimization method for the special case when the retrieval functions belong to a reproducing kernel hilbert space. we illustrate the effectiveness of the proposed methods using modeling data extracted from a commercial search engine. we also point out how the current framework can be extended in future research.
genre identification and goal-focused summarization. in this paper, we present a novel technique of first performing document genre identification, then utilizing the genre for producing tailored summaries based on a user's information seeking needs - genre oriented goal-focused summarization - such as a plot or opinion summary of a movie review. we create a test corpus to determine genre classification accuracy for 16 genres, and examine performance on various amounts of training data for machine learning algorithms - random forests, svm light and naïve bayes. results show that random forests outperforms svm light and naïve bayes. the genre tag is used to inform a downstream summarization engine. we define types of summaries for 7 genres, create a ground truth corpus and analyze the results of genre oriented goal-focused summarization, showing that this type of user based summarization requires different algorithms than the leading sentence baseline which is known to perform well in the case of news articles.
incremental hierarchical clustering of text documents. incremental hierarchical text document clustering algorithms are important in organizing documents generated from streaming on-line sources, such as, newswire and blogs. however, this is a relatively unexplored area in the text document clustering literature. popular incremental hierarchical clustering algorithms, namely cobweb and classit, have not been widely used with text document data. we discuss why, in the current form, these algorithms are not suitable for text clustering and propose an alternative formulation that includes changes to the underlying distributional assumption of the algorithm in order to conform with the data. both the original classit algorithm and our proposed algorithm are evaluated using reuters newswire articles and ohsumed dataset.
hypothesis testing with incomplete relevance judgments. information retrieval experimentation generally proceeds in a cycle of development, evaluation, and hypothesis testing. ideally, the evaluation and testing phases should be short and easy, so as to maximize the amount of time spent in development. there has been recent work on reducing the amount of assessor effort needed to evaluate retrieval systems, but it has not, for the most part, investigated the effects of these methods on tests of significance. in this work, we explore in detail the effects of reduced sets of judgments on the sign test. we demonstrate both analytically and empirically the relationship between the power of the test, the number of topics evaluated, and the number of judgments available. using these relationships, we can determine the number of topics and judgments needed for the least-cost but highest-confidence significance evaluation. specifically, testing pairwise significance over 192 topics with fewer than 5 judgments for each is as good as testing significance over 25 topics with an average of 166 judgments for each - 85% less effort producing no additional errors.
processing relaxed skylines in pdms using distributed data summaries. peer data management systems (pdms) are a natural extension of heterogeneous database systems. one of the main tasks in such systems is efficient query processing. insisting on complete answers, however, leads to asking almost every peer in the network. relaxing these completeness requirements by applying approximate query answering techniques can significantly reduce costs. since most users are not interested in the exact answers to their queries, rank-aware query operators like top-k or skyline play an important role in query processing. in this paper, we present the novel concept of relaxed skylines that combines the advantages of both rank-aware query operators and approximate query processing techniques. furthermore, we propose a strategy for processing relaxed skylines in distributed environments that allows for giving guarantees for the completeness of the result using distributed data summaries as routing indexes.
filtering or adapting: two strategies to exploit noisy parallel corpora for cross-language information retrieval. noisy parallel corpora have been widely used for cross-language information retrieval (clir). however, the previous studies only focus on truly parallel corpus. in this paper, we examine two possible approaches to exploit noisy corpora: filtering out noise from the corpora or adapting the training process of translation model to the noise corpora. our experiments show that the second approach is better suited to clir.
towards practically feasible answering of regular path queries in lav data integration. regular path queries (rpq's) are given by means of regular expressions and ask for matching patterns on labeled graphs. rpq's have received great attention in the context of semistructured data, which are data whose structure is irregular, partially known, or subject to frequent changes. one of the most important problems in databases today is the integration of semistructured data from multiple sources modeled as views. the well-know paradigm of computing first a view-based rewriting of the query, and then evaluating the rewriting on the view extensions is indeed possible for rpq's. however, computing the rewriting is computationally hard as it can only be done (in the worst case) in not less than 2exptime. in this paper, we provide practical evidence that computing the rewriting is hard on the average as well. on the positive side, we propose automata-theoretic techniques, which efficiently compute and utilize instead the complement of the rewriting. notably using the latter, it is possible to answer a query, and this makes the view-based answering of rpq's fairly feasible in practice.
text classification improved through multigram models. classification algorithms and document representation approaches are two key elements for a successful document classification system. in the past, much work has been conducted to find better ways to represent documents. however, most of the attempts rely on certain extra resources such as wordnet, or they face the problem of extremely high dimension. in this paper, we propose a new document representation approach based on n-multigram language models. this approach can automatically discover the hidden semantic sequences in the documents under each category. based on n-multigram language models and n-gram language models, we put forward two text classification algorithms. the experiments on rcv1 show that our proposed algorithm based on n-multigram models alone can achieve the similar or even better classification performance compared with the classifier based on n-gram models but the model size of our algorithm is much smaller than that of the latter. another proposed algorithm based on the combination of n-multigram models and n-gram models improves the micro-f1 and macro-f1 values from 89.5% to 92.6% and 87.2% to 91.1% respectively. all these observations support the validity of our proposed document representation approach.
predicting individual priorities of shared activities using support vector machines. activity-centric collaboration environments help knowledge workers to manage the context of their shared work activities by providing a representation for an activity and its resources. activity management systems provide more structure and organization than email to execute the shared activity but, as the number of shared activities increases, it becomes more and more difficult for users to focus on important activities that need their attention. this paper describes a personalized activity prioritization approach implemented on top of the lotus connections activities management system. our prototype implementation allows each user to view activities ordered by her/his predicted priorities. the predictions are made using a ranking support vector machine model trained with the user's past interactions with the activities system. we describe the prioritization interface and the results of an offline experiment based on data from 13 users over 6-months. our results show that our feature set derived from shared activity structures can significantly increase prediction accuracy compared to a recency baseline.
combining feature selectors for text classification. we introduce several methods of combining feature selectors for text classification. results from a large investigation of these combinations are summarized. easily constructed combinations of feature selectors are shown to improve peak r-precision and f1 at statistically significant levels.
very efficient mining of distance-based outliers. in this work a novel algorithm, named dolphin, for detecting distance-based outliers is presented. the proposed algorithm performs only two sequential scans of the dataset. it needs to store into main memory a portion of the dataset, to efficiently search for neighbors and early prune inliers. the strategy pursued by the algorithm allows to keep this portion very small. both theoretical justification and empirical evidence that the size of the stored data amounts only to a few percent of the dataset are provided. another important feature of dolphin is that the memory-resident data are indexed by using a suitable proximity search approach. this allows to search for nearest neighbors looking only at a small subset of the main memory stored data. temporal and spatial cost analysis show that the novel algorithm achieves both near linear cpu and i/o cost. dolphin has been compared with state of the art methods, showing that it outperforms existing ones.
efficient mining of max frequent patterns in a generalized environment. this poster paper summarizes our solution for mining max frequent generalized itemsets (g-itemsets), a compact representation for frequent patterns in the generalized environment.
search result summarization and disambiguation via contextual dimensions. topic hierarchies are a popular method of summarizing the results obtained in response to a query in various search applications. however, topic hierarchies are rigid when they are pre-defined and somewhat unintuitive when they are dynamically generated by statistical techniques. in this paper, we propose an alternative approach to query disambiguation and result summarization by placing the results in set of contextual dimensions which can be viewed as facets. for the generic search scenario, we illustrate our approach by using three types of contextual dimensions, namely, concepts, features, and specializations. we use nlp techniques and a data mining algorithm to select distinct contexts.
efficient lca based keyword search in xml data. keyword search in xml documents based on the notion of lowest common ancestors (lcas) and modifications of it has recently gained research interest [2, 3, 4]. in this paper we propose an efficient algorithm called indexed stack to find answers to keyword queries based on xrank's semantics to lca [2]. the complexity of the indexed stack algorithm is o(kd|s1|\log|s|) where k is the number of keywords in the query, d is the depth of the tree and |s1 | (|s|) is the occurrence of the least (most) frequent keyword in the query. in comparison, the best worst case complexity of the core algorithms in [2] is o(kd|s|). we analytically and experimentally evaluate the indexed stack algorithm and the two core algorithms in [2]. the results show that the indexed stack algorithm outperforms in terms of both cpu and i/o costs other algorithms by orders of magnitude when the query contains at least one low frequency keyword along with high frequency keywords.
efficient processing of complex similarity queries in rdbms through query rewriting. multimedia and complex data are usually queried by similarity predicates. whereas there are many works dealing with algorithms to answer basic similarity predicates, there are not generic algorithms able to efficiently handle similarity complex queries combining several basic similarity predicates. in this work we propose a simple and effective set of algorithms that can be combined to answer complex similarity queries, and a set of algebraic rules useful to rewrite similarity query expressions into an adequate format for those algorithms. those rules and algorithms allow relational database management systems to turn complex queries into efficient query execution plans. we present experiments that highlight interesting scenarios. they show that the proposed algorithms are orders of magnitude faster than the traditional similarity algorithms. moreover, they are linearly scalable considering the database size.
designing clustering-based web crawling policies for search engine crawlers. the world wide web is growing and changing at an astonishing rate. web information systems such as search engines have to keep up with the growth and change of the web. due to resource constraints, search engines usually have difficulties keeping the local database completely synchronized with the web. in this paper, we study how tomake good use of the limited system resource and detect as many changes as possible. towards this goal, a crawler for the web search engine should be able to predict the change behavior of the webpages. we propose applying clustering-based sampling approach. specifically, we first group all the local webpages into different clusters such that each cluster contains webpages with similar change pattern. we then sample webpages from each cluster to estimate the change frequency of all the webpages in that cluster. finally, we let the crawler re-visit the cluster containing webpages with higher change frequency with a higher probability. to evaluate the performance of an incremental crawler for a web search engine, we measure both the freshness and the quality of the query results provided by the search engine. we run extensive experiments on a real web data set of about 300,000 distinct urls distributed among 210 websites. the results demonstrate that our clustering algorithm effectively clusters the pages with similar change patterns, and our solution significantly outperforms the existing methods in that it can detect more changed webpages and improve the quality of the user experience for those who query the search engine.
investigating the exhaustivity dimension in content-oriented xml element retrieval evaluation. inex, the evaluation initiative for content-oriented xml retrieval, has since its establishment defined the relevance of an element according to two graded dimensions, exhaustivity and specificity. the former measures how exhaustively an xml element discusses the topic of request, whereas specificity measures how focused the element is on the topic of request. the reason for having two dimensions was to provide a more stable measure of relevance than if assessors were asked to rate the relevance of an element on a single scale. however, obtaining relevance assessments is a costly task. as each document must be assessed for relevance by a human assessor. in xml retrieval this problem is exacerbated as the elements of the document must also be assessed with respect to the exhaustivity and specificity dimensions. a continuous discussion in inex has been whether such a sophisticated definition of relevance, and in particular the exhaustivity dimension, was needed. this paper attempts to answer this question through extensive statistical tests to compare the conclusions about system performance that could be made under different assessment scenarios.
vector and matrix operations programmed with udfs in a relational dbms. in general, a relational dbms provides limited capabilities to perform multidimensional statistical analysis, which requires manipulating vectors and matrices. in this work, we study how to extend a dbms with basic vector and matrix operators by programming user-defined functions (udfs). we carefully analyze udf features and limitations to implement vector and matrix operations commonly used in statistics, machine learning and data mining, paying attention to dbms, operating system and computer architecture constraints. udfs represent a c programming interface that allows the definition of scalar and aggregate functions that can be used in sql. udfs have several advantages and limitations. a udf allows fast evaluation of arithmetic expressions, memory manipulation, using multidimensional arrays and exploiting all c language control statements. nevertheless, a udf cannot perform disk i/o, the amount of heap and stack memory that can be allocated is small and the udf code must consider specific architecture characteristics of the dbms. we experimentally compare udfs and sql with respect to performance, ease of use, flexibility and scalability. we profile udfs based on call overhead, memory management and interleaved disk access. we show udfs are faster than standard sql aggregations and as fast as sql arithmetic expressions.
robust periodicity detection algorithms. periodicity detection is an important pre-processing step for many time series algorithms. it provides important information about the structural properties of a time series. feature vectors based on periodicity can be used for clustering, classification, abnormality detection, and human motion understanding. the periodicity detection task is not difficult in case of simple and uncontaminated signal. unfortunately, most of the real datasets exhibit one or more of the following properties: i) non-stationarity, ii) interlaced cyclic patterns and iii) data contamination, which makes the period detection extremely challenging. a seemingly straightforward solution is to develop individual specialized algorithms for handling each case separately. however, determining if a time series is non-stationary or is contaminated in itself is an extremely difficult task. in this article, we propose generic algorithms which can detect periods in complex, noisy and incomplete datasets. the algorithm leverages the frequency characterization and autocorrelation structure inherent in a time series to estimate its periodicity. we extend the methods to handle non-stationary time series by tracking the candidate periods using a kalman filter. we also address the interesting problem of finding multiple interlaced periodicities.
polestar: collaborative knowledge management and sensemaking tools for intelligence analysts. in this paper, we describe polestar (policy explanation using stories and arguments), an integrated suite of knowledge management and collaboration tools for intelligence analysts.polestar provides built-in support for analyst workflow, including collection of textual facts from source documents, structured argumentation, and automatic citation in analytic product documents. underlying polestar is a scalable dependency repository, which provides traceability from product documents to source snippets. the repository's notification engine allows polestar to alert analysts when dependent sources are discredited and aid them in repairing affected arguments. the paper then discusses recent extensions to polestar to support collaborative analysis through community-of-interest finding, portfolio sharing, and peer review of arguments. we conclude with a preview of future research and summary of polestar's primary benefits from the point of view of its deployed users.
mining blog stories using community-based and temporal clustering. in recent years, weblogs, or blogs for short, have become an important form of online content. the personal nature of blogs, online interactions between bloggers, and the temporal nature of blog entries, differentiate blogs from other kinds of web content. bloggers interact with each other by linking to each other's posts, thus forming online communities. within these communities, bloggers engage in discussions of certain issues, through entries in their blogs. since these discussions are often initiated in response to online or offline events, a discussion typically lasts for a limited time duration. we wish to extract such temporal discussions, or stories, occurring within blogger communities, based on some query keywords. we propose a content-community-time model that can leverage the content of entries, their timestamps, and the community structure of the blogs, to automatically discover stories. doing so also allows us to discover hot stories. we demonstrate the effectiveness of our model through several case studies using real-world data collected from the blogosphere.
diva: a variance-based clustering approach for multi-type relational data. clustering is a common technique used to extract knowledge from a dataset in unsupervised learning. in contrast to classical propositional approaches that only focus on simple and flat datasets, relational clustering can handle multi-type interrelated data objects directly and adopt semantic information hidden in the linkage structure to improve the clustering result. however, exploring linkage information will greatly reduce the scalability of relational clustering. moreover, some characteristics of vector data space utilized to accelerate the propositional clustering procedure are no longer valid in relational data space. these two disadvantages restrain the relational clustering techniques from being applied to very large datasets or in time-critical tasks, such as online recommender systems. in this paper we propose a new variance-based clustering algorithm to address the above difficulties. our algorithm combines the advantages of divisive and agglomerative clustering paradigms to improve the quality of cluster results. by adopting the idea of representative object, it can be executed with linear time complexity. experimental results show our algorithm achieves high accuracy, efficiency and robustness in comparison with some well-known relational clustering approaches.
constrained subspace skyline computation. in this paper we introduce the problem of constrained subspace skyline queries. this class of queries can be thought of as a generalization of subspace skyline queries using range constraints. although both constrained skyline queries and subspace skyline queries have been addressed previously, the implications of constrained subspace skyline queries has not been examined so far. constrained skyline queries are usually more expensive than regular skylines. in case of constrained subspace skyline queries additional performance degradation is caused through the projection. in order to support constrained skylines for arbitrary subspaces, we present approaches exploiting multiple low-dimensional indexes instead of relying on a single high-dimensional index. effective pruning strategies are applied to discard points from dominated regions. an important ingredient of our approach is the workload-adaptive strategy for determining the number of indexes and the assignment of dimensions to the indexes. extensive performance evaluation shows the superiority of our proposed technique compared to its most related competitors.
multi-evidence, multi-criteria, lazy associative document classification. we present a novel approach for classifying documents that combines different pieces of evidence (e.g., textual features of documents, links, and citations) transparently, through a data mining technique which generates rules associating these pieces of evidence to predefined classes. these rules can contain any number and mixture of the available evidence and are associated with several quality criteria which can be used in conjunction to choose the "best" rule to be applied at classification time. our method is able to perform evidence enhancement by link forwarding/backwarding (i.e., navigating among documents related through citation), so that new pieces of link-based evidence are derived when necessary. furthermore, instead of inducing a single model (or rule set) that is good on average for all predictions, the proposed approach employs a lazy method which delays the inductive process until a document is given for classification, therefore taking advantage of better qualitative evidence coming from the document. we conducted a systematic evaluation of the proposed approach using documents from the acm digital library and from a brazilian web directory. our approach was able to outperform in both collections all classifiers based on the best available evidence in isolation as well as state-of-the-art multi-evidence classifiers. we also evaluated our approach using the standard webkb collection, where our approach showed gains of 1% in accuracy, being 25 times faster. further, our approach is extremely efficient in terms of computational performance, showing gains of more than one order of magnitude when compared against other multi-evidence classifiers.
a fast and robust method for web page template detection and removal. the widespread use of templates on the web is considered harmful for two main reasons. not only do they compromise the relevance judgment of many web ir and web mining methods such as clustering and classification, but they also negatively impact the performance and resource usage of tools that process web pages. in this paper we present a new method that efficiently and accurately removes templates found in collections of web pages. our method works in two steps. first, the costly process of template detection is performed over a small set of sample pages. then, the derived template is removed from the remaining pages in the collection. this leads to substantial performance gains when compared to previous approaches that combine template detection and removal. we show, through an experimental evaluation, that our approach is effective for identifying terms occurring in templates - obtaining f-measure values around 0.9, and that it also boosts the accuracy of web page clustering and classification methods.
a study on the effects of personalization and task information on implicit feedback performance. while implicit relevance feedback (irf) algorithms exploit users' interactions with information to customize support offered to users of search systems, it is unclear how individual and task differences impact the effectiveness of such algorithms. in this paper we describe a study on the effect on retrieval performance of using additional information about the user and their search tasks when developing irf algorithms. we tested four algorithms that use document display time to estimate relevance, and tailored the threshold times (i.e., the time distinguishing relevance from non-relevance) to the task, the user, a combination of both, or neither. interaction logs gathered during a longitudinal naturalistic study of online information-seeking behavior are used as stimuli for the algorithms. the findings show that tailoring display time thresholds based on task information improves irf algorithm performance, but doing so based on user information worsens performance. this has implications for the development of effective irf algorithms.
a comparative study on classifying the functions of web page blocks. in this paper, we study the problem of learning block classification models to estimate block functions. we distinguish general models, which are learned across multiple sites, and site-specific models, which are learned within individual sites. we further consider several factors that affect the learning process and model effectiveness. these factors include the layout features, the content features, the classifiers, and the term selection methods. we have empirically evaluated the performance of the models when the factors are varied. our main results are that layout features do better than content features for learning both general and site-specific models.
clustering for unsupervised relation identification. unsupervised relation identification is the task of automatically discovering interesting relations between entities in a large text corpora. relations are identified by clustering the frequently co-occurring pairs of entities in such a way that pairs occurring in similar contexts end up belonging to the same clusters. in this paper we compare several clustering setups, some of them novel and others already tried. the setups include feature extraction and selection methods and clustering algorithms. in order to do the comparison, we develop a clustering evaluation metric, specifically adapted for the relation identification task. our experiments demonstrate significant superiority of the single-linkage hierarchical clustering with the novel threshold selection technique over the other tested clustering algorithms. also, the experiments indicate that for successful relation identification it is important to use rich complex features of two kinds: features that test both relation slots together ("relation features"), and features that test only one slot each ("entity features"). we have found that using both kinds of features with the best of the algorithms produces very high-precision results, significantly improving over the previous work.
matching and evaluation of disjunctive predicates for data stream sharing. new optimization techniques, e.g., in data stream management systems (dsmss), make the treatment of disjunctive predicates a necessity. in this paper, we introduce and compare methods for matching and evaluating disjunctive predicates.
semiautomatic evaluation of retrieval systems using document similarities. semiautomatic evaluation of retrieval systems using document similarities.
pair-wise entity resolution: overview and challenges. information integration is one of the oldest and most important computer science problems: information from diverse sources must be combined, so that users can access and manipulate the information in a unified way. one of the central problems in information integration is that of entity resolution (er) (sometimes referred to as deduplication). er is the process of identifying and merging incoming records judged to represent the same real-world entity.for example, consider a company that has different customer databases (e.g., one for each subsidiary), and would like to integrate them. identifying matching records is challenging because there are no unique identifiers across the different sources or databases. a given customer may appear in different ways in each database, and there is a fair amount of guesswork in determining which customers match. deciding if records match is often computationally expensive, e.g., may involve finding maximal common subsequences in two strings. how to combine matching records is often also application dependent. for example, say different phone numbers appear in two records to be merged. in some cases we may wish to keep both of them, while in others we may want to pick just one as the "consolidated" number.another source of complexity is that newly merged records may match with other records. for instance, when we combine records r1 and r2 we may obtain a record r12 that now matches r3. the original records, r1 and r2, may not match with r3, but because r12 contains more information about the same real-word entity that r1 and r2 represent, the "connection" to r3 may now be apparent. such "chained" matches imply that new merged records must be recursively compared to all records.there are many ways to perform er, but in this talk i will explore only one general approach, where the decision of what records represent the same real-world entity is done in a pair-wise fashion. furthermore, we assume that the matching is done by a "black-box" function, which makes our approach generic and applicable to many domains. thus, given two records, r1 and r2, the match function m(r1, r2) returns true if there is enough evidence in the two records that they both refer to the same real-world entity. we also assume a black-box merge function that combines a pair of matching records.in this talk i will discuss the advantages and disadvantages of such a generic, pair-wise approach to er. and even though the approach is relatively simple, there are still many interesting challenges. for instance, how can one minimize the number of invocations to the match and merge black-boxes? are there any properties of the functions that can significantly reduce the number of calls? if one has available multiple processors, how can one distribute the computational load? if records have confidences associated with them, how does the problem complexity change, and how can we efficiently find the confidence of the resolved records? in the talk i will address these challenges, and report on some preliminary work we have done at stanford. (this stanford work in joint with omar benjelloun, tyson condie, johnson (heng) gong, jeff jonas, hideki kawai, tait e. larson, david menestrina, nicolas pombourcq, qi su, steven whang, jennifer widom.for additional information on er and our stanford serf project, please visit http://www-db.stanford.edu/serf/.
approximate reverse k-nearest neighbor queries in general metric spaces. in this paper, we propose an approach for efficient approximative rknn search in arbitrary metric spaces where the value of k is specified at query time. our method uses an approximation of the nearest-neighbor-distances in order to prune the search space. in several experiments, our solution scales significantly better than existing non-approximative approaches while producing an approximation of the true query result with a high recall.
an integer programming approach for frequent itemset hiding. the rapid growth of transactional data brought, soon enough, into attention the need of its further exploitation. in this paper, we investigate the problem of securing sensitive knowledge from being exposed in patterns extracted during association rule mining. instead of hiding the produced rules directly, we decide to hide the sensitive frequent itemsets that may lead to the production of these rules. as a first step, we introduce the notion of distance between two databases and a measure for quantifying it. by trying to minimize the distance between the original database and its sanitized version (that can safely be released), we propose a novel, exact algorithm for association rule hiding and evaluate it on real world datasets demonstrating its effectiveness towards solving the problem.
a dictionary for approximate string search and longest prefix search. in this paper we propose a dictionary data structure for string search with errors where the query string may didiffer from the expected matching string by a few edits. this data structure can also be used to find the database string with the longest common prefix with few errors. specifically, with a database of n random strings, each of length of o(m), we show how to perform string search on a query string that differs from its closest match by k edits using a data structure of linear size and query time equal to õ(log n 2 log n klog a 2m over 2m). this means that if k < m over log a 2m log n, then the query time is õ(1). this is of significant in practice as there are several applications where k is small relative to m. our approach converts strings into bit vectors so that similar strings can map to similar bit vectors with small hamming distance. a simple reduction can be used to obtain similar results for approximate longest prefix search.
kddcs: a load-balanced in-network data-centric storage scheme for sensor networks. we propose an in-network data-centric storage (indcs) scheme for answering ad-hoc queries in sensor networks. previously proposed in-network storage (ins) schemes suffered from storage hot-spots that are formed if either the sensors' locations are not uniformly distributed over the coverage area, or the distribution of sensor readings is not uniform over the range of possible reading values. our k-d tree based data-centric storage (kddcs) scheme maintains the invariant that the storage of events is distributed reasonably uniformly among the sensors. kddcs is composed of a set of distributed algorithms whose running time is within a poly-log factor of the diameter of the network. the number of messages any sensor has to send, as well as the bits in those messages, is poly-logarithmic in the number of sensors. load balancing in kddcs is based on defining and distributively solving a theoretical problem that we call the weighted split median problem. in addition to analytical bounds on kddcs individual algorithms, we provide experimental evidence of our scheme's general efficiency, as well as its ability to avoid the formation of storage hot-spots of various sizes, unlike all previous indcs schemes.
effective and efficient similarity search in time series. we present dsa - derivative time series segment approximation, a novel representation model for time series designed for effective and efficient similarity search. dsa substantially exploits derivative estimation, segmentation and dimensionality reduction to meet at least the requirements of high sensitivity to main features (trends) of time series and robustness to outliers. experiments show that dsa is drastically faster and still as good or better than the prominent state-of-the-art similarity methods.
effective and efficient classification on a search-engine model. traditional document classification frameworks, which apply the learned classifier to each document in a corpus one by one, are infeasible for extremely large document corpora, like the web or large corporate intranets. we consider the classification problem on a corpus that has been processed primarily for the purpose of searching, and thus our access to documents is solely through the inverted index of a large scale search engine. our main goal is to build the "best" short query that characterizes a document class using operators normally available within large engines. we show that surprisingly good classification accuracy can be achieved on average over multiple classes by queries with as few as 10 terms. moreover, we show that optimizing the efficiency of query execution by careful selection of these terms can further reduce the query costs. more precisely, we show that on our set-up the best 10 terms query canachieve 90% of the accuracy of the best svm classifier (14000 terms), and if we are willing to tolerate a reduction to 86% of the best svm, we can build a 10 terms query that can be executed more than twice as fast as the best 10 terms query.
resource-aware kernel density estimators over streaming data. a fundamental building block of many data mining and analysis approaches is density estimation as it provides a comprehensive statistical model of a data distribution. for that reason, its application to transient data streams is highly desirable. a convenient, nonparametric method for density estimation utilizes kernels. however, its computational complexity collides with the rigid processing requirements of data streams. in this work, we present a new approach to this problem that combines linear processing cost with a constant amount of allocated memory. our approach also supports a dynamic memory adaptation to changing system resources.
a neighborhood-based approach for clustering of linked document collections. this paper addresses the problem of automatically structuring linked document collections by using clustering. in contrast to traditional clustering, we study the clustering problem in the light of available link structure information for the data set (e.g., hyperlinks among web documents or co-authorship among bibliographic data entries). our approach is based on iterative relaxation of cluster assignments, and can be built on top of any clustering algorithm. this technique results in higher cluster purity, better overall accuracy, and make self-organization more robust.
continuous keyword search on multiple text streams. in this paper we address the issue of continuous keyword queries on multiple textual streams. this line of work represents a significant departure from previous keyword search models that assumed a static database. in our model the user poses a query comprised by a collection of keywords, which is subsequently applied on multiple text streams (these can be rss news feeds, tv closed captions, emails, etc). a result to a query is a combination of streams "sufficiently correlated" to each other that collectively contain all query keywords within a specified time span.
3dstring: a feature string kernel for 3d object classification on voxelized data. classification of 3d objects remains an important task in many areas of data management such as engineering, medicine or biology. as a common preprocessing step in current approaches to classification of voxelized 3d objects, voxel representations are transformed into a feature vector description.in this article, we introduce an approach of transforming 3d objects into feature strings which represent the distribution of voxels over the voxel grid. attractively, this feature string extraction can be performed in linear runtime with respect to the number of voxels. we define a similarity measure on these feature strings that counts common k-mers in two input strings, which is referred to as the spectrum kernel in the field of kernel methods. we prove that on our feature strings, this similarity measure can be computed in time linear to the number of different characters in these strings. this linear runtime behavior makes our kernel attractive even for large datasets that occur in many application domains. furthermore, we explain that our similarity measure induces a metric which allows to combine it with an m-tree for handling of large volumes of data. classification experiments on two published benchmark datasets show that our novel approach is competitive with the best state-of-the-art methods for 3d object classification.
integration of cluster ensemble and em based text mining for microarray gene cluster identification and annotation. in this paper, we design and develop a unified system ge-miner (gene expression miner) to integrate cluster ensemble, text clustering and multi document summarization and provide an environment for comprehensive gene expression data analysis. we present a novel cluster ensemble approach to generate high quality gene cluster. in our text summarization module, given a gene cluster, our expectation maximization (em) based algorithm can automatically identify subtopics and extract most probable terms for each topic. then, the extracted top k topical terms from each subtopic are combined to form the biological explanation of each gene cluster. experimental results demonstrate that our system can obtain high quality clusters and provide informative key terms for the gene clusters.
adaptive non-linear clustering in data streams. data stream clustering has emerged as a challenging and interesting problem over the past few years. due to the evolving nature, and one-pass restriction imposed by the data stream model, traditional clustering algorithms are inapplicable for stream clustering. this problem becomes even more challenging when the data is high-dimensional and the clusters are not linearly separable in the input space. in this paper, we propose a nonlinear stream clustering algorithm that adapts to the stream's evolutionary changes. using the kernel methods for dealing with the non-linearity of data separation, we propose a novel 2-tier stream clustering architecture. tier-1 captures the temporal locality in the stream, by partitioning it into segments, using a kernel-based novelty detection approach. tier-2 exploits this segment structure to continuously project the streaming data nonlinearly onto a low-dimensional space (lds), before assigning them to a cluster. we demonstrate the effectiveness of our approach through extensive experimental evaluation on various real-world datasets.
regularized locality preserving indexing via spectral regression. we consider the problem of document indexing and representation. recently, locality preserving indexing (lpi) was proposed for learning a compact document subspace. different from latent semantic indexing (lsi) which is optimal in the sense of global euclidean structure, lpi is optimal in the sense of local manifold structure. however, lpi is not efficient in time and memory which makes it difficult to be applied to very large data set. specifically, the computation of lpi involves eigen-decompositions of two dense matrices which is expensive. in this paper, we propose a new algorithm called regularized locality preserving indexing (rlpi). benefit from recent progresses on spectral graph analysis, we cast the original lpi algorithm into a regression framework which enable us to avoid eigen-decomposition of dense matrices. also, with the regression based framework, different kinds of regularizers can be naturally incorporated into our algorithm which makes it more flexible. extensive experimental results show that rlpi obtains similar or better results comparing to lpi and it is significantly faster, which makes it an efficient and effective data preprocessing method for large scale text clustering, classification and retrieval.
cp/cv: concept similarity mining without frequency information from domain describing taxonomies. domain specific ontologies are heavily used in many applications. for instance, these form the bases on which similarity/dissimilarity between keywords are extracted for various knowledge discovery and retrieval tasks. existing similarity computation schemes can be categorized as (a) structure- or (b) information-based approaches. structure based approaches compute dissimilarity between keywords using a (weighted) count of edges between two keywords. information-base approaches, on the other hand, leverage available corpora to extract additional information, such as keyword frequency, to achieve better performance in similarity computation than structure-based approaches. unfortunately, in many application domains (such as applications that rely on unique-keys in a relational database), frequency information required by information-based approaches does not exist. in this paper, we note that there is a third way of computing similarity: if each node in a given hierarchy can be represented as a vector of related concepts, these vectors could be compared to compute similarities. this requires mapping concept-nodes in a given hierarchy onto a concept space. in this paper, we propose a concept propagation (cp) scheme, which relies on the semantical relationships between concepts implied by the structure of the hierarchy to annotate each concept-node with a concept-vector (cv). we refer to this approach as cp/cv. comparison of keyword similarity results shows that cp/cv provides significantly better (upto 33%) results than existing structure-based schemes. also, even if cp/cv does not assume the availability of an appropriate corpus to extract keyword frequency information, our approach matches (and slightly improves on) the performance of information-based approaches.
secure search in enterprise webs: tradeoffs in efficient implementation for document level security. document level security (dls) -- enforcing permissions prevailing at the time of search -- is specified as a mandatory requirement in many enterprise search applications. unfortunately, depending upon implementation details and values of key parameters, dls may come at a high price in increased query processing time, leading to an unacceptably slow search experience. in this paper we present a model and a method for carrying out secure search in the presence of dls within enterprise webs. we report on two alternative commercial dls search implementations. using a 10,000 document experimental dls environment, we graph the dependence of query processing time on result set size and visibility density for different classes of user. scaled up to collections of tens of thousands of documents, our results suggest that query times will be unacceptable if exact counts of matching documents are required and also for users who can view only a small proportion of documents. we show that the time to conduct access checks is dramatically increased if requests must be sent off-server, even on a local network, and discuss methods for reducing the cost of security checks. we conclude that enterprises can effectively reduce dls overheads by organizing documents in such a way that most access checking can be at collection rather than document level, by forgoing accurate match counts, by using caching, batching or hierarchical methods to cut costs of dls checking and, if applicable, by using a single portal both to access and search documents.
a data stream language and system designed for power and extensibility. by providing an integrated and optimized support for user-defined aggregates (udas), data stream management systems (dsms) can achieve superior power and generality while preserving compatibility with current sql standards. this is demonstrated by the stream mill system that, through is expressive stream language (esl), efficiently supports a wide range of applications - including very advanced ones such as data stream mining, streaming xml processing, time-series queries, and rfid event processing. esl supports physical and logical windows (with optional slides and tumbles) on both built-in aggregates and udas, using a simple framework that applies uniformly to both aggregate functions written in an external procedural languages and those natively written in esl. the constructs introduced in esl extend the power and generality of dsms, and are conducive to uda-specific optimization and efficient execution as demonstrated by several experiments.
estimation, sensitivity, and generalization in parameterized retrieval models. in this work we investigate three important aspects of parameterized retrieval models: estimation, sensitivity, and generalization. since all parameterized models, even those based on heuristics, have inherent uncertainty, we study these issues using statistical tools.
maximizing the sustained throughput of distributed continuous queries. monitoring systems today often involve continuous queries over streaming data, in a distributed collaborative system. the distribution of query operators over a network of processors, and their processing sequence, form a query configuration with inherent constraints on the throughput it can support. in this paper we propose to optimize stream queries with respect to a version of throughput measure, the profiled input throughput. this measure is focused on matching the expected behavior of the input streams. to prune the search space we used hill-climbing techniques that proved to be efficient and effective.
capturing community search expertise for personalized web search using snippet-indexes. we describe and evaluate an approach to capturing and re-using search expertise within a community of like minded searchers, such as the employees of a company or organisation. within knowledge based industries, search expertise - the ability to quickly and accurately locate information according to a specific information need - is an important corporate asset and in our approach we attempt to capture this knowledge by mining the title and snippet texts of results that have been selected by community members in response to their queries. our assumption is that the snippet text of a result must play a role in helping users to judge the initial relevance of that result and that the snippet terms of selected results must contain especially informative terms about the goals and preferences of the searchers. in other words, results are selected because the user recognises certain combinations of terms in their snippets which are related to their information needs. our approach seeks to build a community-based snippet index that reflects the evolving interests of a group of searchers. this index is then used to re-rank the results returned by some underlying search engine by boosting the ranking of key results that have been frequently selected for similar queries by community members in the past.
ir principles for content-based indexing and retrieval of functional brain images. in this paper, we explore the concept of a "library of brain images", which implies not only a repository of brain images, but also efficient search and retrieval mechanisms that are based on models derived from ir practice. as a preliminary study, we have worked with a collection of functional mri brain images assembled in the study of several distinct cognitive tasks. we adapt several classical ir methods (inverted indexing, tfidf and latent semantic indexing(lsi)) to content-based brain image retrieval. our results show that efficient and accurate retrieval of brain images is possible, and that representations motivated by the ir perspective are somewhat more effective than are methods based on retaining the full image information.
estimating corpus size via queries. we consider the problem of estimating the size of a collection of documents using only a standard query interface. our main idea is to construct an unbiased and low-variance estimator that can closely approximate the size of any set of documents defined by certain conditions, including that each document in the set must match at least one query from a uniformly sampleable query pool of known size, fixed in advance.using this basic estimator, we propose two approaches to estimating corpus size. the first approach requires a uniform random sample of documents from the corpus. the second approach avoids this notoriously difficult sample generation problem, and instead uses two fairly uncorrelated sets of terms as query pools; the accuracy of the second approach depends on the degree of correlation among the two sets of terms.experiments on a large trec collection and on three major search engines demonstrates the effectiveness of our algorithms.
a document-centric approach to static index pruning in text retrieval systems. we present a static index pruning method, to be used in ad-hoc document retrieval tasks, that follows a document-centric approach to decide whether a posting for a given term should remain in the index or not. the decision is made based on the term's contribution to the document's kullback-leibler divergence from the text collection's global language model. our technique can be used to decrease the size of the index by over 90%, at only a minor decrease in retrieval effectiveness. it thus allows us to make the index small enough to fit entirely into the main memory of a single pc, even for large text collections containing millions of documents. this results in great efficiency gains, superior to those of earlier pruning methods, and an average response time around 20 ms on the gov2 document collection.
computing block importance for searching on web sites. in this paper we consider the problem of using the block structure of a web page to improve ranking results when searching for information on web sites. given the block structure of the web pages as input, we propose a method for computing the importance of each block (in the form of block weights) in a web collection. as we show through experiments, the deployment of our method may allow a significant improvement in the quality of search results. we ran experiments to compare the quality of search results when using our method to the quality obtained when using no structure information. when compared to a ranking method that considered pages as monolithic units, our block-based ranking method led to improvements in the quality of search results in experiments with two sites with heterogeneous structures. further, our method does not increase the cost of processing queries when compared to the systems using no structural information.
constructing better document and query models with markov chains. document and query expansions have been used separately in previous studies to enhance the representation of documents and queries. in this paper, we propose a general method that integrates both of them. expansion is carried out using multi-stage markov chains. our experiments show that this method significantly outperforms the existing approaches.
learning to join everything. text, speech, images, video, dna sequences provide information about entities that people can recognize when looking at a particular instance. but those entities and their attributes and relationships are not directly accessible to queries that join across types of sources. information extraction methods based on supervised machine learning recognize mentions of entities and relationships of predefined types in different kinds of sources, which can then be used to answer some useful types of queries. however, supervised learning relies on hand-annotated training sets that are difficult to create and limit what types of entities and relationships can be joined for new applications. these limitations have prompted research into unsupervised extraction methods that rely on correlations among sources rather than hand-annotated training sets. while these methods are not yet as accurate as those based on supervised learning, they have the potential for a new query-by-example approach to information integration in which seed sets of query answers are expanded into ranked lists of potential answers by learning occurrence patterns from the seed answers. i will give examples of both types of methods from our research on biomedical information extraction, leading to some ideas on a possible convergence of search and databases through machine learning.
efficient join processing over uncertain data. in many applications data values are inherently uncertain. this includes moving-objects, sensors and biological databases. there has been recent interest in the development of database management systems that can handle uncertain data. some proposals for such systems include attribute values that are uncertain. in particular, an attribute value can be modeled as a range of possible values, associated with a probability density function. previous efforts for this type of data have only addressed simple queries such as range and nearest-neighbor queries. queries that join multiple relations have not been addressed in earlier work despite the significance of joins in databases. in this paper we address join queries over uncertain data. we propose a semantics for the join operation, define probabilistic operators over uncertain data, and propose join algorithms that provide efficient execution of probabilistic joins. the paper focuses on an important class of joins termed probabilistic threshold joins that avoid some of the semantic complexities of dealing with uncertain data. for this class of joins we develop three sets of optimization techniques: item-level, page-level, and index-level pruning. these techniques facilitate pruning with little space and time overhead, and are easily adapted to most join algorithms. we verify the performance of these techniques experimentally.
efficient interactive query expansion with complete search. we present an efficient realization of the following interactive search engine feature: as the user is typing the query, words that are related to the last query word and that would lead to good hits are suggested, as well as selected such hits. the realization has three parts: (i) building clusters of related terms, (ii) adding this information as artificial words to the index such that (iii) the described feature reduces to an instance of prefix search and completion. an efficient solution for the latter is provided by the completesearch engine, with which we have integrated the proposed feature. for building the clusters of related terms we propose a variant of latent semantic indexing that, unlike standard approaches, is completely transparent to the user. by experiments on two large test-collections, we demonstrate that the feature is provided at only a slight increase in query processing time and index size.
query taxonomy generation for web search. we propose an approach that organizes the search-result clusters into a hierarchical structure, called a query taxonomy, from the user's perspective. the proposed approach is based on an unsupervised classification method, which uses the dynamic web as the training corpus. with query taxonomy, users can browse relevant web documents more conveniently and comprehensibly. our experimental results verify the feasibility and the effectiveness of the proposed approach to query taxonomy generation in web search.
ranking web objects from multiple communities. vertical search is a promising direction as it leverages domain-specific knowledge and can provide more precise information for users. in this paper, we study the web object-ranking problem, one of the key issues in building a vertical search engine. more specifically, we focus on this problem in cases when objects lack relationships between different web communities, and take high-quality photo search as the test bed for this investigation. we proposed two score fusion methods that can automatically integrate as many web communities (web forums) with rating information as possible. the proposed fusion methods leverage the hidden links discovered by a duplicate photo detection algorithm, and aims at minimizing score differences of duplicate photos in different forums. both intermediate results and user studies show the proposed fusion methods are practical and efficient solutions to web object ranking in cases we have described. though the experiments were conducted on high-quality photo ranking, the proposed algorithms are also applicable to other ranking problems, such as movie ranking and music ranking.
finding and linking incidents in news. news reports are being produced and disseminated in overwhelming volume, making it difficult to keep up with the newest information. most previous research in automatic news organization treated news topics as a flat list, ignoring the intrinsic connection among individual reports. we argue that more contextual information within and across the topics will benefit users in their news understanding process. a news organization infrastructure, incident threading, is proposed in this article. all text snippets describing the occurrence of a real-world happening are combined into a news incident, and a network is composed of incidents that are interconnected by links in certain types. a limited vocabulary of connection types is defined and corresponding rules are established based upon the human experience of news understanding. the incident threading system is implemented with two different algorithms. one starts from clustering of text passages and then creates links with pre-built rules. the other method defines a global score function over the whole collection and solves the optimization problem with simulated annealing. the former achieves higher accuracy in the identification of incidents and the latter generates better links, which is preferred since the links are more important for the formation of the incident network.
web search: from information retrieval to microeconomic modeling. in scarcely a decade, web search has gone from simply scaling traditional information retrieval, to a groundswell of new opportunities that are changing marketing as we know it. in this lecture, we begin by reviewing the progress, pointing out that web search is no longer a purely computer sceince problem. we then hint at the role of other disciplines in this ongoing revolution and a number of directions for research.
parameter sensitivity in the probabilistic model for ad-hoc retrieval. the term frequency normalisation parameter sensitivity is an important issue in the probabilistic model for information retrieval. a high parameter sensitivity indicates that a slight change of the parameter value may considerably affect the retrieval performance. therefore, a weighting model with a high parameter sensitivity is not robust enough to provide a consistent retrieval performance across different collections and queries. in this paper, we suggest that the parameter sensitivity is due to the fact that the query term weights are not adequate enough to allow informative query terms to differ from non-informative ones. we show that query term reweighing, which is part of the relevance feedback process, can be successfully used to reduce the parameter sensitivity. experiments on five text retrieval conference (trec) collections show that the parameter sensitivity does remarkably decrease when query terms are reweighed.
summarizing local context to personalize global web search. the pc desktop is a very rich repository of personal information, efficiently capturing user's interests. in this paper we propose a new approach towards an automatic personalization of web search in which the user specific information is extracted from such local desktops, thus allowing for an increased quality of user profiling, while sharing less private information with the search engine. more specifically, we investigate the opportunities to select personalized query expansion terms for web search using three different desktop oriented approaches: summarizing the entire desktop data, summarizing only the desktop documents relevant to each user query, and applying natural language processing techniques to extract dispersive lexical compounds from relevant desktop resources. our experiments with the google api showed at least the latter two techniques to produce a very strong improvement over current web search.
detecting distance-based outliers in streams of data. in this work a method for detecting distance-based outliers in data streams is presented. we deal with the sliding window model, where outlier queries are performed in order to detect anomalies in the current window. two algorithms are presented. the first one exactly answers outlier queries, but has larger space requirements. the second algorithm is directly derived from the exact one, has limited memory requirements and returns an approximate answer based on accurate estimations with a statistical guarantee. several experiments have been accomplished, confirming the effectiveness of the proposed approach and the high quality of approximate solutions.
query optimization using restructured views. we study optimization of relational queries using materialized views, where views may be regular or restructured. in a restructured view, some data from the base table(s) are represented as metadata - that is, schema information, such as table and attribute names - or vice versa.using restructured views in query optimization opens up a new spectrum of views that were not previously available, and can result in significant additional savings in query-evaluation costs. these savings can be obtained due to a significantly larger set of views to choose from, and may involve reduced table sizes, elimination of self-joins, clustering produced by restructuring, and horizontal partitioning.in this paper we propose a general query-optimization framework that treats regular and restructured views in a uniform manner and is applicable to sql select-project-join queries and views with or without aggregation. within the framework we provide (1) algorithms to determine when a view (regular or restructured) is usable in answering a query, and (2) algorithms to rewrite a query using usable views.semantic information, such as knowledge of the key of a view, can be used to further optimize a rewritten query. within our general query-optimization framework, we develop techniques for determining the key of a (regular or restructured) view, and show how this information can be used to further optimize a rewritten query. it is straightforward to integrate all our algorithms and techniques into standard query-optimization algorithms.
communities in graphs and hypergraphs. in this paper we define a type of cohesive subgroups - called communities - in hypergraphs, based on the edge connectivity of subhypergraphs. we describe a simple algorithm for the construction of these sets and show, based on examples from image segmentation and information retrieval, that these groups may be useful for the analysis and accessibility of large graphs and hypergraphs.
validating associations in biological databases. erroneous data can often be found in databases, and detecting it is normally a non-trivial task. for example, to cope with the large amount of biological sequences being produced, a significant number of genes and proteins have been annotated by automated tools. a protein annotation is an association between a protein and a term describing its role. these tools have produced a significant number of misannotations that are now present in biological databases. this paper proposes a new method for automatically scoring associations by comparing them to preexisting curated associations. an association is a pair that links two entities. the score can be used to filter incorrect or uncommon associations.we evaluated the method using the automated protein annotations submitted to biocreative, an international evaluation of state-of-the-art text-mining systems in biology. the method scored each of these annotations and those scored below a certain threshold were discarded. the results have shown a small trade-off in recall for a large improvement in precision. for example, we were able to discard 44.6%, 66.8% and 81% of the misannotations, maintaining 96.9%, 84.2%, and 47.8% of the correct annotations, respectively. moreover, we were able to outperform each individual submission to biocreative by proper adjustment of the threshold.
computing explanations for unlively queries in databases. a query is unlively if it always returns an empty answer. debugging a database schema requires not only determining unlively queries, but also fixing them. to the best of our knowledge, the existing methods do not provide the designer with an explanation of why a query is not lively. in this paper, we propose a method for computing explanations that is independent of the particular method used to determine liveliness. it provides three levels of search: one explanation, a maximal set of non-overlapping explanations, and all explanations. the first two levels require only a linear number of calls to the underlying method. we also propose a filter to reduce the number of these calls, and experimentally compare our method with the best known method for finding unsatisfiable subsets of constraints.
efficient and effective link analysis with precomputed salsa maps. salsa is a link-based ranking algorithm that takes the result set of a query as input, extends the set to include additional neighboring documents in the web graph, and performs a random walk on the induced subgraph. the stationary probability distribution of this random walk, used as a relevance score, is significantly more effective for ranking purposes than popular query-independent link-based ranking algorithms such as pagerank. unfortunately, this requires significant effort at query-time, to access the link graph and compute the stationary probability distribution. in this paper, we explore whether it is possible to perform most of the computation off-line, prior to the arrival of any queries. the off-line phase of our approach computes a "score map" for each node in the web graph by performing a salsa-like algorithm on the neighborhood of that node and retaining the scores of the most promising nodes in the neighborhood graph. the on-line phase takes the results to a query, retrieves the score map of each result, and returns for each result a score that is the sum of the matching scores from each score map. we evaluated this algorithm on a collection of about 28,000 queries with partially labeled results, and found that it is significantly more effective than pagerank, although not quite as effective as salsa. we also studied the trade-off between ranking effectiveness and space requirements.
workload-based optimization of integration processes. the efficient execution of integration processes between distributed, heterogeneous data sources and applications is a challenging research area of data management. these integration processes are an abstraction for workflow-based integration tasks, used in eai servers and wfms. the major problem are significant workload changes during runtime. the performance of integration processes strongly depends on those dynamic workload characteristics, and hence workload-based optimization is important. however, existing approaches of workflow optimization only address the rule-based optimization and disregard changing workload characteristics. to overcome the problem of inefficient process execution in the presence of workload shifts, here, we present an approach for the workload-based optimization of instance-based integration processes and show that significant execution time reductions are possible.
entity-based query reformulation using wikipedia. many real world applications increasingly involve both structured data and text, and entity based retrieval is an important problem in this realm. in this paper, we present an automatic query reformulation approach based on entities detected in each query. the aim is to utilize semantics associated with entities for enhancing document retrieval. this is done by expanding a query with terms/phrases related to entities in the query. we exploit wikipedia as a large repository of entity information. our reformulated approach consists of three major steps : (1) detect representative entity in a query; (2) expand the query with entity related terms/phrases; and (3) facilitate term dependency features. we evaluate our approach in ad-hoc retrieval task on four trec collections, including two large web collections. experiments results show that significant improvement is possible by utilizing entity corresponding information.
automatic online news topic ranking using media focus and user attention based on aging theory. news topics, which are constructed from news stories using the techniques of topic detection and tracking (tdt), bring convenience to users who intend to see what is going on through the internet. however, it is almost impossible to view all the generated topics, because of the large amount. so it will be helpful if all topics are ranked and the top ones, which are both timely and important, can be viewed with high priority. generally, topic ranking is determined by two primary factors. one is how frequently and recently a topic is reported by the media; the other is how much attention users pay to it. both media focus and user attention varies as time goes on, so the effect of time on topic ranking has already been included. however, inconsistency exists between both factors. in this paper, an automatic online news topic ranking algorithm is proposed based on inconsistency analysis between media focus and user attention. news stories are organized into topics, which are ranked in terms of both media focus and user attention. experiments performed on practical web datasets show that the topic ranking result reflects the influence of time, the media and users. the main contributions of this paper are as follows. first, we present the quantitative measure of the inconsistency between media focus and user attention, which provides a basis for topic ranking and an experimental evidence to show that there is a gap between what the media provide and what users view. second, to the best of our knowledge, it is the first attempt to synthesize the two factors into one algorithm for automatic online topic ranking.
evaluating topic models for information retrieval. we explore the utility of different types of topic models, both probabilistic and not, for retrieval purposes. we show that: (1) topic models are effective for document smoothing; (2) more elaborate topic models that capture topic dependencies provide no additional gains; (3) smoothing documents by using their similar documents is as effective as smoothing them by using topic models; (4) topics discovered on the whole corpus are too coarse-grained to be useful for query expansion. experiments to measure topic models' ability to predict held-out likelihood confirm past results on small corpora, but suggest that simple approaches to topic model are better for large corpora.
"more like these": growing entity classes from seeds. we present a corpus-based approach to the class expansion task. for a given set of seed entities we use co-occurrence statistics taken from a text collection to define a membership function that is used to rank candidate entities for inclusion in the set. we describe an evaluation framework that uses data from wikipedia. the performance of our class extension method improves as the size of the text collection increases.
reasoning about vague topological information. topological information plays a fundamental role in the human perception of spatial configurations and is thereby one of the most prominent geographical features in natural language. as vagueness abounds in geography, flexible formalisms with the ability to capture vague topological information are often needed in practice. while such formalisms have already been introduced by various authors, complete reasoning procedures are usually not discussed. in this paper, we show how many interesting reasoning tasks, such as consistency checking and entailment checking, can be supported in a generalization of the well-known rcc-8 calculus. in particular, we present decision procedures based on linear programming, solving all reasoning tasks of interest. we furthermore show how deciding the consistency of vague topological information can be reduced to the consistency problem of the original rcc-8.
web search personalization with ontological user profiles. every user has a distinct background and a specific goal when searching for information on the web. the goal of web search personalization is to tailor search results to a particular user based on that user's interests and preferences. effective personalization of information access involves two important challenges: accurately identifying the user context and organizing the information in such a way that matches the particular context. we present an approach to personalized search that involves building models of user context as ontological profiles by assigning implicitly derived interest scores to existing concepts in a domain ontology. a spreading activation algorithm is used to maintain the interest scores based on the user's ongoing behavior. our experiments show that re-ranking the search results based on the interest scores and the semantic evidence in an ontological user profile is effective in presenting the most relevant results to the user.
protecting location privacy against location-dependent attack in mobile services. privacy preservation has recently received considerable attention for location-based mobile services. in this paper, we present location-dependent attack resulting from continuous and dependent location updates and propose an incremental clique-based cloaking algorithm, called icliquecloak, to defend against location-dependent attack. the main idea is to incrementally maintain maximal cliques for location cloaking in an un-directed graph that takes into consideration the effect of continuous location updates.
identifying opinion leaders in the blogosphere. opinion leaders are those who bring in new information, ideas, and opinions, then disseminate them down to the masses, and thus influence the opinions and decisions of others by a fashion of word of mouth. opinion leaders capture the most representative opinions in the social network, and consequently are important for understanding the massive and complex blogosphere. in this paper, we propose a novel algorithm called influencerank to identify opinion leaders in the blogosphere. the influencerank algorithm ranks blogs according to not only how important they are as compared to other blogs, but also how novel the information they can contribute to the network. experimental results indicate that our proposed algorithm is effective in identifying influential opinion leaders.
ranking with semi-supervised distance metric learning and its application to housing potential estimation. this paper proposes a semi-supervised distance metric learning algorithm for the ranking problem. instead of giving the computer what are the important factors that affect the final rank value, we only give several most certainly ranked points which implicitly contain the knowledge of the ranking factors. then the computer can automatically use the most certain points and plenty of unlabeded data to learn an informative metric for ranking. this metric not only can help to regress an order in the observed data, but also can be used to retrieve the data by querying new test points. moreover, the lower-rank distance metric can be used to visualize high-dimensional data. we also present an application to the housing potential estimation problem. it is shown that the algorithm is efficient to help consultants to refine their consulting work.
evaluation of partial path queries on xml data. xml query languages typically allow the specification of structural patterns of elements. finding the occurrences of such patterns in an xml tree is the key operation in xml query processing. many algorithms have been presented for this operation. these algorithms focus mainly on the evaluation of path-pattern or tree-pattern queries. in this paper, we define a partial path-pattern query language, and we address the problem of its efficient evaluation on xml data. in order to process partial path-pattern queries, we introduce a set of sound and complete inference rules to characterize structural relationship derivation. we provide necessary and sufficient conditions for detecting query unsatisfiability and node redundancy. we show how partial path-pattern queries can be equivalently put in a canonical directed acyclic graph form. we developed two stack-based algorithms for the evaluation of partial path-pattern queries, partialmj and partialpathstack. partialmj computes answers to the query by merge-joining the results of the root-to-leaf paths of a spanning tree of the query. partialpathstack exploits a topological order of the nodes of the query graph to match the query pattern as a whole to the xml tree. the experimental evaluation of our algorithms shows that partialpathstack is independent of intermediate results and largely outperforms partialmj.
sigma encoded inverted files. compression of term frequency lists and very long document-id lists within an inverted file search engine are examined. several compression schemes are compared including elias γ and δ codes, golomb encoding, variable byte encoding, and a class of word-based encoding schemes including simple-9, relative-10 and carryover-12. it is shown that these compression methods are not well suited to compressing these kinds of lists of numbers. of those tested, carryover-12 is preferred because it is both effective at compression and fast at decompression. a novel technique, sigma encoding prior to compression, is proposed and tested. sigma encoding utilizes a parameterized dictionary to reduce the number of bits necessary to store an integer. this method shows an about 0.3 bit per integer improvement over carryover-12 while costing only about 3 extra clock cycles per integer to decompress.
dynamic index pruning for effective caching. ram and dynamic pruning schemes to reduce query evaluation times. while only a small portion of lists are processed with dynamic pruning, current systems still store the entire inverted list in cache. in this paper we investigate caching only the pieces of the inverted lists that are actually used to answer a query during dynamic pruning. we examine an lru cache model, and two recently proposed models. we also introduce a new dynamic pruning scheme for impact-ordered inverted lists. using two large web collections and corresponding query logs we show that, using an lru cache, our new pruning scheme reduces the number of disk accesses during query processing time by 7%-15% over the state-of-the-art impact-ordered baseline, without reducing answer quality. surprisingly, however, we discover that using our new pruning scheme makes little difference to disk traffic when the more sophisticated caching schemes are employed.
improve retrieval accuracy for difficult queries using negative feedback. how to improve search accuracy for difficult topics is an under-addressed, yet important research question. in this paper, we consider a scenario when the search results are so poor that none of the top-ranked documents is relevant to a user's query, and propose to exploit negative feedback to improve retrieval accuracy for such difficult queries. specifically, we propose to learn from a certain number of top-ranked non-relevant documents to rerank the rest unseen documents. we propose several approaches to penalizing the documents that are similar to the known non-relevant documents in the language modeling framework. to evaluate the proposed methods, we adapt standard trec collections to construct a test collection containing only difficult queries. experiment results show that the proposed approaches are effective for improving retrieval accuracy of difficult queries.
probabilistic correlation-based similarity measure of unstructured records. computing the similarity between unstructured records is a fundamental function in multiple applications. approximate string matching and full text retrieval techniques do not show the best performance when applied directly, since the information are limited in unstructured records of short record length. in this paper, we propose a novel probabilistic correlation-based similarity measure. rather than simply conducting the exact matching tokens of two records, our similarity evaluation enriches the information of records by considering the correlations of tokens. we define the probabilistic correlation between tokens as the probability that these tokens appear in the same records. then we compute the weight of tokens and discover the correlations of records based on the probabilistic correlations of tokens. finally, we present extensive experimental results to demonstrate the effectiveness of our approach.
matching task profiles and user needs in personalized web search. personalization has been deemed one of the major challenges in information retrieval with a significant potential for providing better search experience to individual users. especially, the need for enhanced user models better capturing elements such as users' goals, tasks, and contexts has been identified. in this paper, we introduce a statistical language model for user tasks representing different granularity levels of a user profile, ranging from very specific search goals to broad topics. we propose a personalization framework that selectively matches the actual user information need with relevant past user tasks, and allows to dynamically switch the course of personalization from re-finding very precise information to biasing results to general user interests. in the extreme, our model is able to detect when the user's search and browse history is not appropriate for aiding the user in satisfying her current information quest. instead of blindly applying personalization to all user queries, our approach refrains from undue actions in these cases, accounting for the user's desire of discovering new topics, and changing interests over time. the effectiveness of our method is demonstrated by an empirical user study.
association thesaurus construction methods based on link co-occurrence analysis for wikipedia. wikipedia, a huge scale web based encyclopedia, attracts great attention as an invaluable corpus for knowledge extraction because it has various impressive characteristics such as a huge number of articles, live updates, a dense link structure, brief anchor texts and url identification for concepts. we have already proved that we can use wikipedia to construct a huge scale accurate association thesaurus. the association thesaurus we constructed covers almost 1.3 million concepts and its accuracy is proved in detailed experiments. however, we still need scalable methods to analyze the huge number of web pages and hyperlinks among articles in the web based encyclopedia. in this paper, we propose a scalable method for constructing an association thesaurus from wikipedia based on link co-occurrences. link co-occurrence analysis is more scalable than link structure analysis because it is a one-pass process. we also propose integration method of tfidf and link co-occurrence analysis. experimental results show that both our proposed methods are more accurate and scalable than conventional methods. furthermore, the integration of tfidf achieved higher accuracy than using only link co-occurrences.
evaluating partial tree-pattern queries on xml streams. the streaming evaluation is a popular way of evaluating queries on xml documents. besides its many advantages, it is also the only option for a number of important xml applications. unfortunately, existing algorithms focus almost exclusively on tree-pattern queries (tpqs). requirements for flexible querying of xml data have motivated recently the introduction of query languages that are more general and flexible than tpqs. we consider a partial tree-pattern query (ptpq) language which generalizes and strictly contains tpqs. ptpqs can express a fragment of xpath which comprises reverse axes and the node identity equality ($is$) operator, in addition to forward axes, wildcards and predicates. we outline an original streaming algorithm for ptpqs. our algorithm is the first one to support the streaming evaluation of such a broad fragment of xpath.
dr. searcher and mr. browser: a unified hyperlink-click graph. we introduce a unified graph representation of the web, which includes both structural and usage information. we model this graph using a simple union of the web's hyperlink and click graphs. the hyperlink graph expresses link structure among web pages, while the click graph is a bipartite graph of queries and documents denoting users' searching behavior extracted from a search engine's query log. our most important motivation is to model in a unified way the two main activities of users on the web: searching and browsing, and at the same time to analyze the effects of random walks on this new graph. the intuition behind this task is to measure how the combination of link structure and usage data provide additional information to that contained in these structures independently. our experimental results show that both hyperlink and click graphs have strengths and weaknesses when it comes to using their stationary distribution scores for ranking web pages. furthermore, our evaluation indicates that the unified graph always generates consistent and robust scores that follow closely the best result obtained from either individual graph, even when applied to "noisy" data. it is our belief that the unified web graph has several useful properties for improving current web document ranking, as well as for generating new rankings of its own. in particular stationary distribution scores derived from the random walks on the combined graph can be used as an indicator of whether structural or usage data are more reliable in different situations.
cache-aware load balancing for question answering. the need for high performance and throughput question answering (qa) systems demands for their migration to distributed environments. however, even in such cases it is necessary to provide the distributed system with cooperative caches and load balancing facilities in order to achieve the desired goals. until now, the literature on qa has not considered such a complex system as a whole. currently, the load balancer regulates the assignment of tasks based only on the cpu and i/o loads without considering the status of the system cache. this paper investigates the load balancing problem proposing two novel algorithms that take into account the distributed cache status, in addition to the cpu and i/o load in each processing node. we have implemented, and tested the proposed algorithms in a fully fledged distributed qa system. the two algorithms show that the choice of using the status of the cache was determinant in achieving good performance, and high throughput for qa systems.
key blog distillation: ranking aggregates. searchers on the blogosphere often have a need to identify other key bloggers with similar interests to their own. however, a main difference of this blog distillation task from normal adhoc or web document retrieval is that each blog can be seen as an aggregate of its constituent posts. on the other hand, we show that the task is similar to the expert search task, where a person's expertise is derived from the aggregate of their publications or emails. in this paper, we investigate several aspects of blog retrieval: firstly, we experiment whether a blog should be represented as a whole unit, or as by considering each of its posts as indicators of its relevance, showing that expert search techniques can be adapted for blog search; secondly, we examine whether indexing only the xml feed provided by each blog (and which is often incomplete) is sufficient, or whether the full-text of each blog post should be downloaded; lastly, we use approaches to detect the central or recurring interests of each blog to increase the retrieval effectiveness of the system. using the trec 2007 blog dataset, the results show that our proposed expert search paradigm is indeed useful in identifying key bloggers, achieving high retrieval effectiveness.
anomaly-free incremental output in stream processing. continuous queries enable alerts, predictions, and early warning in various domains such as health care, business process monitoring, financial applications, and environment protection. currently, the consistency of the result cannot be assessed by the application, since only the query processor has enough internal information to determine when the output has reached a consistent state. to our knowledge, this is the first paper that addresses the problem of consistency under the assumptions and constraints of a continuous query model. in addition to defining an appropriate consistency notion, we propose techniques for guaranteeing consistency. we implemented the proposed techniques in our existing stream engine, and we report on the characteristics of the observed performance. as we show, these methods are practical as they impose only a small overhead on the system.
non-local evidence for expert finding. the task addressed in this paper, finding experts in an enterprise setting, has gained in importance and interest over the past few years. commonly, this task is approached as an association finding exercise between people and topics. existing techniques use either documents (as a whole) or proximity-based techniques to represent candidate experts. proximity-based techniques have shown clear precision-enhancing benefits. we complement both document and proximity-based approaches to expert finding by importing global evidence of expertise, i.e., evidence obtained using information that is not available in the immediate proximity of a candidate expert's name occurrence or even on the same page on which the name occurs. examples include candidate priors, query models, as well as other documents a candidate expert is associated with. using the cerc data set created for the trec 2007 enterprise track we identify examples of non-local evidence of expertise. we then propose modified expert retrieval models that are capable of incorporating both local (either document or snippet-based) evidence and non-local evidence of expertise. results show that our refined models significantly outperform existing state-of-the-art approaches.
translating topics to words for image annotation. one of the classic techniques for image annotation is the language translation model. it views an image as a document, i.e., a set of visual words which are obtained by vector quatitizing the image regions generated by unsupervised image segmentation. annotating images are achieved by translating visual words to textual words, just like translating a document in english to a document in french. in this paper, we also view an image as a document, but we view the annotation processes as two consecutive processes, i.e., document summarization and translation. in the document summarization process, an image document is firstly summarized into its own visual language, which we called visual topics. the translation process translates these visual topics to textual words. compared to the original translation model, our visual topics learned by the probabilistic latent semantic analysis (plsa) approach provide an intermediate abstract level of visual description. we show improved annotation performance on the corel image dataset.
learning query-biased web page summarization. query-biased web page summarization is the summarization of a web page reflecting the relevance of it to a specific query. it plays an important role in search results representation of web search engines. in this paper, we propose a learning-based query-biased web page summarization method. the summarization problem is solved within the typical sentence selection framework. different from existing web page summarization methods that use page content or link context alone, both of them are considered as the sources of sentences in this work. most of existing learning-based summarization methods treat summarization as a sentence classification problem and train a classifier to discriminate between extracted sentences and non-extracted sentences of all training documents. the basic assumption of these methods is that sentences from different documents are comparable with respect to the class information. in contrast to the classification scheme, a ranking scheme is introduced to rank extracted sentences higher than non-extracted sentences of each training document. the underlying assumption that sentences within a document are comparable is weaker and more reasonable than the assumption of classification-based scheme. extensive results using intrinsic evaluation metrics gauge many aspects of the proposed method.
reconstructing ddc for interactive classification. the automated text categorization (tc) has made prominent progress in recent years. however, seldom work is done on automatic classification with library classification systems, the largest and most sophisticated classification systems people ever built, such as the dewey decimal classification (ddc). the library classification is a very laborious and time-consuming job that requires qualification and good training. the large-scale classification schemes, such as the ddc, impose several obstacles to the state-of-art tc technologies, including very deep hierarchy, data sparseness, and skewed category distribution. these problems characterize large corpora of real-world applications and it is very hard, if not impossible, to obtain satisfactory results. in this paper, we propose a novel algorithm to reconstruct classification schemes according to the document density and category distribution, and to transform the category hierarchy into a balanced virtual taxonomy by merging sparse categories, lopping dense branches and flattening the hierarchy. to make the classification performance acceptable to real-world applications, we also propose an interactive classification model that only needs two or three times of user interaction. extensive experiments are conducted on a 10-year bibliographic data collection of the library of congress to verify the proposed methodology.
shine: search heterogeneous interrelated entities. heterogeneous entities or objects are very common and are usually interrelated with each other in many scenarios. for example, typical web search activities involve multiple types of interrelated entities such as end users, web pages, and search queries. in this paper, we define and study a novel problem: <ul>s</ul>earch <ul>h</ul>eterogeneous <ul>in</ul>terrelated <ul>e</ul>ntities (shine). given a shine-query which can be any type(s) of entities, the task of shine is to retrieve multiple types of related entities to answer this query. this is in contrast to the traditional search,which only deals with a single type of entities (e.g., web pages). the advantages of shine include: (1) it is feasible for end users to specify their information need along different dimensions by accepting queries with different types. (2) answering a query by multiple types of entities provides informative context for users to better understand the search results and facilitate their information exploration. (3) multiple relations among heterogeneous entities can be utilized to improve the ranking of any particular type of entities. to attain the goal of shine, we propose to represent all entities in a unified space through utilizing their interaction relationships. two approaches, m-lsa and e-vsm, are discussed and compared in this paper. the experiments on 3 data sets (i.e., a literature data set, a search engine log data set, and a recommendation data set) show the effectiveness and flexibility of our proposed methods.
mining redundancy in candidate-bearing snippets to improve web question answering. conventional question answering (qa) techniques independently process candidate-bearing snippets to select an exact answer to a question from candidate answers. this paper presents two novel ways of utilizing redundancy in candidate-bearing snippets to help select an exact answer to a question in our web qa system, i.e., cluster-based language model (clm-m) and unsupervised svm classifier (u-svm) techniques. the comparative experiments demonstrate that the proposed methods significantly outperform the language model-based (lm-m) and supervised svm-based (s-svm) techniques that do not utilize this redundancy in the candidate-bearing snippets. using the clm-m, the top_1 score is increased from 36.03% (lm-m) to 46.96%; and the top_1 improvement in the u-svm over the s-svm is about 23%. moreover, a cross-model comparison shows that the performance ranking of these models is: u-svm > clm-lm > lm-m > s-svm > r-m (the retrieval-based model).
using social annotations to improve language model for information retrieval. this poster is concerned with the problem of exploring the use of social annotations for improving language models for information retrieval (denoted as lmir). two properties of social annotations, namely keyword property and structure property are studied for this aim. the keyword property improves lmir by concatenating all the annotations of a document to generate a summary of the document. the structure property can boost lmir further when similarity among annotations and similarity among documents are taken into consideration simultaneously. the two properties of social annotations are leveraged for the use of language modeling with a mixture model named as "language annotation model" (denoted as lam). evaluations using del.icio.us data show that lam outperforms the traditional lmir approaches significantly.
query expansion using probabilistic local feedback with application to multimedia retrieval. as one of the most effective query expansion approaches, local feedback is able to automatically discover new query terms and improve retrieval accuracy for different retrieval models. however, the performance of local feedback is heavily dependent on the assumption that most top-ranked documents are relevant to the query topic. although this assumption might be sensible for ad-hoc text retrieval, it is usually violated in many other retrieval tasks such as multimedia retrieval. in this paper, we develop a robust local analysis approach called probabilistic local feedback (plf) based on a discriminative probabilistic retrieval framework. the proposed model is effective for improving retrieval accuracy without assuming the most top-ranked documents are relevant. it also provides a sound probabilistic interpretation and a convergence guarantee on the iterative result updating process. although derived from variational techniques, this approach only involves an iterative process of simple operations on ranking features and thus can be computed efficiently in practice. our multimedia retrieval experiments on trecvid'03-'05 collections have demonstrated the advantage of the proposed plf approaches which can achieve noticeable gains in terms of mean average precision over various baseline methods and prf-augmented results.
link analysis using time series of web graphs. link analysis is a key technology in contemporary web search engines. most of the previous work on link analysis only used information from one snapshot of web graph. since commercial search engines crawl the web periodically, they will naturally obtain time series data of web graphs. the historical information contained in the series of web graphs can be used to improve the performance of link analysis. in this paper, we argue that page importance should be a dynamic quantity, and propose defining page importance as a function of both pagerank of the current web graph and accumulated historical page importance from previous web graphs. specifically, a novel algorithm named temporalrank is designed to compute the proposed page importance. we try to use a kinetic model to interpret this page importance and show that it can be regarded as the solution to an ordinary differential equation. experiments on link analysis using web graph data in five snapshots show that the proposed algorithm can outperform pagerank in many measures, and can effectively filter out newly appeared link spam websites.
nugget discovery in visual exploration environments by query consolidation. queries issued by casual users or specialists exploring a dataset often point us to important subsets of the data, be it clusters, outliers or other meaningful features. capturing and caching such queries (henceforth called nuggets) has many potential benefits, including the optimization of the system performance and the search experience of users. unfortunately, current visual exploration systems have not yet tapped into this potential resource of identifying and sharing important queries. in this paper, we introduce a query consolidation strategy aimed at solving the general problem of isolating important queries from the potentially huge amount of queries submitted. our solution clusters redundant queries caused by exploration-style query specification, which is prevalent in data exploration systems. to measure the similarity between queries, we designed an effective distance metric that incorporates both the query specification and the actual query result. to overcome its high complexity when comparing queries with large result sets, we designed an approximation method, which is efficient while still providing excellent accuracy. a user study conducted on multivariate data sets comparing our proposed technique to others in the literature confirms that the proposed distance metric indeed matches well with users' intuition. as proof of feasibility, we integrated our proposed query consolidation solution into the nugget management system (nms) framework [22], which is based on a visual exploration system xmdvtool. a second user study indicates that both the efficiency and accuracy of users' visual exploration are enhanced when supported by nms.
ontology evaluation using wikipedia categories for browsing. ontology evaluation is a maturing discipline with methodologies and measures being developed and proposed. however, evaluation methods that have been proposed have not been applied to specific examples. in this paper, we present the state-of-the-art in ontology evaluation - current methodologies, criteria and measures, analyse appropriate evaluations that are important to our application - browsing in wikipedia, and apply these evaluations in the context of ontologies with varied properties. specifically, we seek to evaluate ontologies based on categories found in wikipedia.
ranking very many typed entities on wikipedia. we discuss the problem of ranking very many entities of different types. in particular we deal with a heterogeneous set of types, some being very generic and some very specific. we discuss two approaches for this problem: i) exploiting the entity containment graph and ii) using a web search engine to compute entity relevance. we evaluate these approaches on the real task of ranking wikipedia entities typed with a state-of-the-art named-entity tagger. results show that both approaches can greatly increase the performance of methods based only on passage retrieval.
recognition and classification of noun phrases in queries for effective retrieval. it has been shown that using phrases properly in the document retrieval leads to higher retrieval effectiveness. in this paper, we define four types of noun phrases and present an algorithm for recognizing these phrases in queries. the strengths of several existing tools are combined for phrase recognition. our algorithm is tested using a set of 500 web queries from a query log, and a set of 238 trec queries. experimental results show that our algorithm yields high phrase recognition accuracy. we also use a baseline noun phrase recognition algorithm to recognize phrases from the trec queries. a document retrieval experiment is conducted using the trec queries (1) without any phrases, (2) with the phrases recognized from a baseline noun phrase recognition algorithm, and (3) with the phrases recognized from our algorithm respectively. the retrieval effectiveness of (3) is better than that of (2), which is better than that of (1). this demonstrates that utilizing phrases in queries does improve the retrieval effectiveness, and better noun phrase recognition yields higher retrieval performance.
a constraint-based probabilistic framework for name disambiguation. this paper is concerned with the problem of name disambiguation. by name disambiguation, we mean distinguishing persons with the same name. it is a critical problem in many knowledge management applications. despite much research work has been conducted, the problem is still not resolved and becomes even more serious, in particular with the popularity of web 2.0. previously, name disambiguation was often undertaken in either a supervised or unsupervised fashion. this paper first gives a constraint-based probabilistic model for semi-supervised name disambiguation. specifically, we focus on investigating the problem in an academic researcher social network (http://arnetminer.org). the framework combines constraints and euclidean distance learning, and allows the user to refine the disambiguation results. experimental results on the researcher social network show that the proposed framework significantly outperforms the baseline method using unsupervised hierarchical clustering algorithm.
an efficient algorithm for approximate biased quantile computation in data streams. we propose an efficient algorithm for approximate biased quantile computation in large data streams. our algorithm computes decomposable biased quantile summaries on fixed sized blocks and dynamically maintains the biased quantile summary for the entire stream as the exponential histogram over the block-wise quantile summaries. the algorithm is computationally efficient and achieves an amortized computational cost of o(log(1⁄∈log(∈n))) and a space requirement of o(log3∈n↬∈). our algorithm does not assume prior knowledge of the stream sizes or the range of data values in the streams. in practice, our algorithm is able to efficiently maintain summaries over large data streams with over tens of millions of observations and achieves significant performance improvement over prior algorithms.
boolean representation based data-adaptive correlation analysis over time series streams. correlation analysis is a basic problem in the field of data stream mining. typical approaches add sliding window to data streams to get the recent results, but the window length defined by users is always fixed which is not suitable for the changing stream environment. we propose a boolean representation based data-adaptive method for correlation analysis among a large number of time series streams. the periodical trends of each stream series to are monitored to choose the most suitable window size and group the series with the same trends together. instead of adopting complex pair-wise calculation, we can also quickly get the correlation pairs of series at the optimal window sizes. all the processing is realized by simple boolean operations. both the theory analysis and the experimental evaluations show that our method has good computation efficiency with high accuracy.
opinion retrieval from blogs. opinion retrieval is a document retrieval process, which requires documents to be retrieved and ranked according to their opinions about a query topic. a relevant document must satisfy two criteria: relevant to the query topic, and contains opinions about the query, no matter if they are positive or negative. in this paper, we describe an opinion retrieval algorithm. it has a traditional information retrieval (ir) component to find topic relevant documents from a document set, an opinion classification component to find documents having opinions from the results of the ir step, and a component to rank the documents based on their relevance to the query, and their degrees of having opinions about the query. we implemented the algorithm as a working system and tested it using trec 2006 blog track data in automatic title-only runs. our result showed 28% to 32% improvements in map score over the best automatic runs in this 2006 track. our result is also 13% higher than a state-of-art opinion retrieval system, which is tested on the same data set.
effective top-k computation in retrieving structured documents with term-proximity support. modern web search engines are expected to return top-k results efficiently given a query. although many dynamic index pruning strategies have been proposed for efficient top-k computation, most of them are prone to ignore some especially important factors in ranking functions, e.g. term proximity (the distance relationship between query terms in a document). the inclusion of term proximity breaks the monotonicity of ranking functions and therefore leads to additional challenges for efficient query processing. this paper studies the performance of some existing top-k computation approaches using term-proximity-enabled ranking functions. our investigation demonstrates that, when term proximity is incorporated into ranking functions, most existing index structures and top-k strategies become quite inefficient. according to our analysis and experimental results, we propose two index structures and their corresponding index pruning strategies: structured and hybrid, which performs much better on the new settings. moreover, the efficiency of index building and maintenance would not be affected too much with the two approaches.
classifying networked entities with modularity kernels. statistical machine learning techniques for data classification usually assume that all entities are i.i.d. (independent and identically distributed). however, real-world entities often interconnect with each other through explicit or implicit relationships to form a complex network. although some graph-based classification methods have emerged in recent years, they are not really suitable for complex networks as they do not take the degree distribution of network into consideration. in this paper, we propose a new technique, modularity kernel, that can effectively exploit the latent community structure of networked entities for their classification. a number of experiments on hypertext datasets show that our proposed approach leads to excellent classification performance in comparison with the state-of-the-art methods.
the query-flow graph: model and applications. query logs record the queries and the actions of the users of search engines, and as such they contain valuable information about the interests, the preferences, and the behavior of the users, as well as their implicit feedback to search engine results. mining the wealth of information available in the query logs has many important applications including query-log analysis, user profiling and personalization, advertising, query recommendation, and more. in this paper we introduce the query-flow graph, a graph representation of the interesting knowledge about latent querying behavior. intuitively, in the query-flow graph a directed edge from query qi to query qj means that the two queries are likely to be part of the same "search mission". any path over the query-flow graph may be seen as a searching behavior, whose likelihood is given by the strength of the edges along the path. the query-flow graph is an outcome of query-log mining and, at the same time, a useful tool for it. we propose a methodology that builds such a graph by mining time and textual information as well as aggregating queries from different users. using this approach we build a real-world query-flow graph from a large-scale query log and we demonstrate its utility in concrete applications, namely, finding logical sessions, and query recommendation. we believe, however, that the usefulness of the query-flow graph goes beyond these two applications.
ranked feature fusion models for ad hoc retrieval. we introduce the ranked feature fusion framework for information retrieval system design. typical information retrieval formalisms such as the vector space model, the best-match model and the language model first combine features (such as term frequency and document length) into a unified representation, and then use the representation to rank documents. we take the opposite approach: documents are first ranked by the relevance of a single feature value and are assigned scores based on their relative ordering within the collection. a separate ranked list is created for every feature value and these lists are then fused to produce a final document scoring. this new "rank then combine" approach is extensively evaluated and is shown to be as effective as traditional "combine then rank" approaches. the model is easy to understand and contains fewer parameters than other approaches. finally, the model is easy to extend (integration of new features is trivial) and modify. this advantage includes but is not limited to relevance feedback and distribution flattening.
optimal proactive caching in peer-to-peer network: analysis and application. as a promising new technology with the unique properties like high efficiency, scalability and fault tolerance, peer-to-peer (p2p) technology is used as the underlying network to build new internet-scale applications. however, one of the well known issues in such an application (for example www) is that the distribution of data popularities is heavily tailed with a zipf-like distribution. with consideration of the skewed popularity we adopt a proactive caching approach to handle the challenge, and focus on two key problems: where (i.e. the placement strategy: where to place the replicas) and how (i.e. the degree problem: how many replicas are assigned to one specific content)? for the where problem, we propose a novel approach which can be generally applied to structured p2p networks. next, we solve two optimization objectives related to the how problem: max_perf and min_cost. our solution is called <b>popcache</b>, and we discover two interesting properties: (1) the number of replicas assigned to each content is proportional to its popularity; (2) the derived optimal solutions are related to the entropy of popularity. to our knowledge, none of the previous works has mentioned such results. finally, we apply the results of popcache to propose a p2p base web caching, called as web-popcache. by means of web cache trace driven simulation, our extensive evaluation results demonstrate the advantages of popcache and web-popcache.
bns feature scaling: an improved representation over tf-idf for svm text classification. in the realm of machine learning for text classification, tf-idf is the most widely used representation for real-valued feature vectors. however, idf is oblivious to the training class labels and naturally scales some features inappropriately. we replace idf with bi-normal separation (bns), which has been previously found to be excellent at ranking words for feature selection filtering. empirical evaluation on a benchmark of 237 binary text classification tasks shows substantially better accuracy and f-measure for a support vector machine (svm) by using bns scaling. a wide variety of other feature representations were later tested and found inferior, as well as binary features with no scaling. moreover, bns scaling yielded better performance without feature selection, obviating the need for feature selection.
energy-efficient skyline query processing and maintenance in sensor networks. the skyline query, as an important operator in databases for multi-preference analysis and decision making, has received much attention recently due to its wide application backgrounds. in this paper, we consider the skyline query problem in wireless sensor network with an objective to maximize the network lifetime by proposing filter-based distributed algorithms for skyline evaluation and maintenance. we also conduct preliminary experiments to evaluate the performance of the proposed algorithms. the experimental results demonstrate that the proposed algorithms significantly outperform existing algorithms on various datasets.
how evaluator domain expertise affects search result relevance judgments. traditional search evaluation approaches have often relied on domain experts to evaluate results for each query. unfortunately, the range of topics present in any representative sample of web queries makes it impractical to have expert evaluators for every topic. in this paper, we investigate the effect of using "generalist" evaluators instead of experts in the domain of queries being evaluated. empirically, we ind that for queries drawn from domains requiring high expertise, (1) generalists tend to give shallow, inaccurate ratings as compared to experts. (2) further experiments show that generalists disagree on the underlying meaning of these queries significantly more often than experts, and often appear to "give up'' and fall back on surface features such as keyword matching. (3) finally, by estimating the percentage of "expertise requiring'' queries in a web query sample, we estimate the impact of using generalists, versus the ideal of having domain experts for every "expertise requiring'' query.
efficient frequent pattern mining over data streams. this paper proposes a prefix-tree structure, called cps-tree (compact pattern stream tree) that efficiently discovers the exact set of recent frequent patterns from high-speed data stream. the cps-tree introduces the concept of dynamic tree restructuring technique in handling stream data that allows it to achieve highly compact frequency-descending tree structure at runtime and facilitates an efficient fp-growth-based [1] mining technique.
scalable community discovery on textual data with relations. every piece of textual data is generated as a method to convey its authors' opinion regarding specific topics. authors deliberately organize their writings and create links, i.e., references, acknowledgments, for better expression. thereafter, it is of interest to study texts as well as their relations to understand the underlying topics and communities. although many efforts exist in the literature in data clustering and topic mining, they are not applicable to community discovery on large document corpus for several reasons. first, few of them consider both textual attributes as well as relations. second, scalability remains a significant issue for large-scale datasets. additionally, most algorithms rely on a set of initial parameters that are hard to be captured and tuned. motivated by the aforementioned observations, a hierarchical community model is proposed in the paper which distinguishes community cores from affiliated members. we present our efforts to develop a scalable community discovery solution for large-scale document corpus. our proposal tries to quickly identify potential cores as seeds of communities through relation analysis. to eliminate the influence of initial parameters, an innovative attribute-based core merge process is introduced so that the algorithm promises to return consistent communities regardless initial parameters. experimental results suggest that the proposed method has high scalability to corpus size and feature dimensionality, with more than 15 topical precision improvement compared with popular clustering techniques.
boosting social annotations using propagation. this paper is concerned with the problem of boosting social annotations using propagation, which is also called social propagation. in particular, we focus on propagating social annotations of web pages (e.g., annotations in del.icio.us). although social annotations are developing fast, they cover only a small proportion of web pages on the world wide web. to alleviate the low coverage problem, a general propagation model based on random surfer is proposed. specifically, four steps are included: basic propagation, multiple-annotation propagation, multiple-link-type propagation, and constraint-guided propagation. experimental results show that the proposed model is very effective in increasing coverage of annotations as well as preserving property of social annotations.
search-based query suggestion. in this paper, we proposed a unified strategy to combine query log and search results for query suggestion. in this way, we leverage both the users' search intentions for popular queries and the power of search engines for unpopular queries. the suggested queries are also ranked according to their relevance and qualities; and each suggestion is described with a rich snippet including a photo and related description.
on quantifying changes in temporally evolving dataset. in this paper, we present a general framework to quantify changes in temporally evolving data. we focus on changes that materialize due to evolution and interactions of features extracted from the data. the changes are captured by the following key transformations: create, merge, split, continue, and cease. first, we identify various factors which influence the importance of each transformation. these factors are then combined using a weight vector. the weight vector encapsulates domain knowledge. we evaluate our algorithm using the following datasets: dblp, imdb, text and scientific dataset.
understanding the relationship between searchers' queries and information goals. we describe results from web search log studies aimed at elucidating user behaviors associated with queries and destination urls that appear with different frequencies. we note the diversity of information goals that searchers have and the differing ways that goals are specified. we examine rare and common information goals that are specified using rare or common queries. we identify several significant differences in user behavior depending on the rarity of the query and the destination url. we find that searchers are more likely to be successful when the frequencies of the query and destination url are similar. we also establish that the behavioral differences observed for queries and goals of varying rarity persist even after accounting for potential confounding variables, including query length, search engine ranking, session duration, and task difficulty. finally, using an information-theoretic measure of search difficulty, we show that the benefits obtained by search and navigation actions depend on the frequency of the information goal.
revisiting the relationship between document length and relevance. the scope hypothesis in information retrieval (ir) states that a relationship exists between document length and relevance, such that the likelihood of relevance increases with document length. a number of empirical studies have provided statistical evidence supporting the scope hypothesis. however, these studies make the implicit assumption that modern test collections are complete (i.e. all documents are assessed for relevance). as a consequence the observed evidence is misleading. in this paper we perform a deeper analysis of document length and relevance taking into account that test collections are incomplete. we first demonstrate that previous evidence supporting the scope hypothesis was an artefact of the test collection, where there is a bias towards longer documents in the pooling process. we evaluate whether this length bias affects system comparison when using incomplete test collections. the results indicate that test collections are problematic when considering map as a measure of effectiveness but are relatively robust when using bpref. the implications of the study indicate that retrieval models should not be tuned to favour longer documents, and that designers of new test collections should take measures against length bias during the pooling process in order to create more reliable and robust test collections.
edsc: efficient density-based subspace clustering. subspace clustering mines clusters hidden in subspaces of high-dimensional data sets. density-based approaches have been shown to successfully mine clusters of arbitrary shape even in the presence of noise in full space clustering. exhaustive search of all density-based subspace clusters, however, results in infeasible runtimes for large high-dimensional data sets. this is due to the exponential number of possible subspace projections in addition to the high computational cost of density-based clustering. in this paper, we propose lossless efficient detection of density-based subspace clusters. in our edsc (efficient density-based subspace clustering) algorithm we reduce the high computational cost of density-based subspace clustering by a complete multistep filter-and-refine algorithm. our first hypercube filter step avoids exhaustive search of all regions in all subspaces by enclosing potentially density-based clusters in hypercubes. our second filter step provides additional pruning based on a density monotonicity property. in the final refinement step, the exact unbiased density-based subspace clustering result is detected. as we prove that pruning is lossless in both filter steps, we guarantee completeness of the result. in thorough experiments on synthetic and real world data sets, we demonstrate substantial efficiency gains. our lossless edsc approach outperforms existing density-based subspace clustering algorithms by orders of magnitude.
probabilistic polyadic factorization and its application to personalized recommendation. multiple-dimensional, i.e., polyadic, data exist in many applications, such as personalized recommendation and multiple-dimensional data summarization. analyzing all the dimensions of polyadic data in a principled way is a challenging research problem. most existing methods separately analyze the marginal relationships among pairwise dimensions and then combine the results afterwards. motivated by the fact that various dimensions of polyadic data jointly affect each other, we propose a probabilistic polyadic factorization approach to directly model all the dimensions simultaneously in a unified framework. we then show the connection between the probabilistic polyadic factorization and a non-negative version of the tucker tensor factorization. we provide detailed theoretical analysis of the new modeling framework, discuss implementation techniques for our models, and propose several extensions to the basic framework. we then apply the proposed models to the application of personalized recommendation. extensive experiments on a social bookmarking dataset, delicious, and a paper citation dataset, citeseer, demonstrate the effectiveness of the proposed models.
rewriting of visibly pushdown languages for xml data integration. in this paper, we focus on xml data integration by studying rewritings of xml target schemas in terms of source schemas. rewriting is very important in data integration systems where the system is asked to find and assemble xml documents from the data sources and produce documents which satisfy a target schema. as schema representation, we consider visibly pushdown automata (vpas) which accept visibly pushdown languages (vpls). the latter have been shown to coincide with the family of (word-encoded) regular tree languages which are the basis of formalisms for specifying xml schemas. furthermore, practical semi-formal xml schema specifications (defined by simple pattern conditions on xml) compile into vpas which are exponentially more concise than other representations based on tree automata. notably, vpls enjoy a "well-behavedness" which facilitates us in addressing rewriting problems for xml data integration. based on vpas, we positively solve these problems, and present detailed complexity analyses.
vanity fair: privacy in querylog bundles. a recently proposed approach to address privacy concerns in storing web search querylogs is bundling logs of multiple users together. in this work we investigate privacy leaks that are possible even when querylogs from multiple users are bundled together, without any user or session identifiers. we begin by quantifying users' propensity to issue own-name vanity queries and geographically revealing queries. we show that these propensities interact badly with two forms of vulnerabilities in the bundling scheme. first, structural vulnerabilities arise due to properties of the heavy tail of the user search frequency distribution, or the distribution of locations that appear within a user's queries. these heavy tails may cause a user to appear visibly different from other users in the same bundle. second, we demonstrate analytical vulnerabilities based on the ability to separate the queries in a bundle into threads corresponding to individual users. these vulnerabilities raise privacy issues suggesting that bundling must be handled with great care.
an automatic approach to construct domain-specific web portals. we describe the architecture of an automatic domain-specific web portal construction system. the system has three major components: i) a focused crawler that collects the domain-specific pages on the web, ii) an information extraction engine that extracts useful fields from these web pages, and iii) a query engine that allows both typical keyword based queries on the pages and advanced queries on the extracted data fields. we present a prototype system that works for the course homepages domain on the web. a user study with the prototype system shows that our approach produces high quality results and achieves better precision figures than the typical keyword based search.
just-in-time contextual advertising. contextual advertising is a type of web advertising, which, given the url of a web page, aims to embed into the page (typically via javascript) the most relevant textual ads available. for static pages that are displayed repeatedly, the matching of ads can be based on prior analysis of their entire content; however, ads need to be matched also to new or dynamically created pages that cannot be processed ahead of time. analyzing the entire body of such pages on-the-fly entails prohibitive communication and latency costs. to solve the three-horned dilemma of either low-relevance or high-latency or high-load, we propose to use text summarization techniques paired with external knowledge (exogenous to the page) to craft short page summaries in real time. empirical evaluation proves that matching ads on the basis of such summaries does not sacrifice relevance, and is competitive with matching based on the entire page content. specifically, we found that analyzing a carefully selected 5% fraction of the page text sacrifices only 1%-3% in ad relevance. furthermore, our summaries are fully compatible with the standard javascript mechanisms used for ad placement: they can be produced at ad-display time by simple additions to the usual script, and they only add 500-600 bytes to the usual request.
inferring document relevance from incomplete information. recent work has shown that average precision can be accurately estimated from a small random sample of judged documents. unfortunately, such "random pools" cannot be used to evaluate retrieval measures in any standard way. in this work, we show that given such estimates of average precision, one can accurately infer the relevances of the remaining unjudged documents, thus obtaining a fully judged pool that can be used in standard ways for system evaluation of all kinds. using trec data, we demonstrate that our inferred judged pools are well correlated with assessor judgments, and we further demonstrate that our inferred pools can be used to accurately infer precision recall curves and all commonly used measures of retrieval performance.
merging distributed database summaries. the database summarization system coined s<scp>aint</scp>e<scp>ti</scp>q provides multi-resolution summaries of structured data stored into acentralized database. summaries are computed online with a conceptual hierarchical clustering algorithm. however, most companies work in distributed legacy environments and consequently the current centralized version of s<scp>aint</scp>e<scp>ti</scp>q is either not feasible (privacy preserving) or not desirable (resource limitations). to address this problem, we propose new algorithms to generate a single summary hierarchy given two distinct hierarchies, without scanning the raw data. the greedy merging algorithm (gma) takes all leaves of both hierarchies and generates the optimal partitioning for the considered data set with regards to a cost function (compactness and separation). then, a hierarchical organization of summaries is built by agglomerating or dividing clusters such that the cost function may emphasize local or global patterns in the data. thus, we obtain two different hierarchies according to the performed optimisation. however, this approach breaks down due to its exponential time complexity. two alternative approaches with constant time complexity w.r.t. the number of data items, are proposed to tackle this problem. the first one, called merge by incorporation algorithm (mia), relies on the s<scp>aint</scp>e<scp>ti</scp>q engine whereas the second approach, named merge by alignment algorithm (maa), consists in rearranging summaries by levels in a top-down manner. then, we compare those approaches using an original quality measure in order to quantify how good our merged hierarchies are. finally, an experimental study, using real data sets, shows that merging processes (mia and maa) are efficient in terms of computational time.
efficient evaluation of high-selective xml twig patterns with parent child edges in tree-unaware rdbms. recent study showed that native twig join algorithms and tree-aware relational framework significantly outperform tree-unaware approaches in evaluating structural relationships in xml twig queries. in this paper, we present an efficient strategy to evaluate high-selective twig queries containing only parent-child relationships in a tree-unaware relational environment. our scheme is built on top of our s<scp>ucxent</scp>++ system. we show that by exploiting the encoding scheme of s<scp>ucxent</scp>++, we can devise efficient strategy for evaluating such twig queries. extensive performance studies on various data sets and queries show that our approach performs better than a representative tree-unaware approach (g<scp>lobal</scp>-o<scp>rder</scp>) and a state-of-the-art native twig join algorithm (tjf<scp>ast</scp>) on all benchmark queries with the highest observed gain factors being 243 and 95, respectively. additionally, our approach reduces significantly the performance gap between tree-aware and tree-unaware approaches and even outperforms a tree-aware approach(m<scp>onet</scp>db/xq<scp>uery</scp>) for certain high-selective twig queries. we also report our insights to the plan choices a relational optimizer made during twig query evaluation by visually characterizing its behavior over the relational selectivity space.
structure and semantics for expressive text kernels. several text categorization applications require a representation beyond the standard bag-of-words paradigm. kernel-based learning has approached this problem by (i) considering information about syntactic structure or by (ii) incorporating knowledge about the semantic similarity of term features. we propose a generalized framework consisting of a family of kernels that jointly incorporate syntactic and semantic similarity and demonstrate the power of this approach in a series of experiments.
external perfect hashing for very large key sets. we present a simple and efficient external perfect hashing scheme (referred to as eph algorithm) for very large static key sets. we use a number of techniques from the literature to obtain a novel scheme that is theoretically well-understood and at the same time achieves an order-of-magnitude increase in the size of the problem to be solved compared to previous "practical" methods. we demonstrate the scalability of our algorithm by constructing minimum perfect hash functions for a set of 1.024 billion urls from the world wide web of average length 64 characters in approximately 62 minutes, using a commodity pc. our scheme produces minimal perfect hash functions using approximately 3.8 bits per key. for perfect hash functions in the range {0,...,2n - 1} the space usage drops to approximately 2.7 bits per key. the main contribution is the first algorithm that has experimentally proven practicality for sets in the order of billions of keys and has time and space usage carefully analyzed without unrealistic assumptions.
conceptual modeling by analogy and metaphor. metaphor is not merely a rhetorical device, characteristic of language alone, but rather a fundamental feature of the human conceptual system. a metaphor is understood by finding an analogy mapping between two domains. this paper argues that analogy mappings facilitate conceptual modeling by allowing the designer to reinterpret fragments of familiar conceptual models in other contexts. the contributions of the paper are expressed within the tradition of the entity-relation model.
self-correcting queries for xml. it has been observed that queries over xml data sources are often unsatisfiable. unsatisfiability may stem from several different sources, e.g., the user may be insufficiently familiar with the labels appearing the documents, or may not be intimately aware of the hierarchical structure of the documents. this difficulty may be compounded by the fact that errors in query formulation lead to an empty answer, and not to some sort of compilation error. to deal with query and document mismatches, previous research has considered returning answers that maximally satisfy (in some sense) the query, instead of only returning strictly satisfying answers. however, this breaks the golden database rule that only strictly satisfying answers are returned when querying. indeed, the relationship between the query and answers is no longer clear, when unsatisfying answers are returned. to revive the golden database rule, this paper proposes a framework for deriving self-correcting queries over xml. this framework generates similar satisfiable queries, when the user query is unsatisfiable. the user can then choose a satisfiable query of interest, and receive exactly satisfying answers to this query.
leveraging context in user-centric entity detection systems. a user-centric entity detection system is one in which the primary consumer of the detected entities is a person who can perform actions on the detected entities (e.g. perform a search, view a map, shop, etc.). we contrast this with machine-centric detection systems where the primary consumer of the detected entities is a machine. machine-centric detection systems typically focus on the quantity of detected entities, measured by precision and recall metrics, with the goal of correctly identifying every single entity in a document. however, the simple precision/recall scores of machine-centric entity detection systems fail to accurately reflect the quality of detected entities in user-centric systems, where users may not necessarily want to "see" every possible entity. we posit that not all of the detected entities in a given piece of text are necessarily relevant to the main topic of the text, nor are they necessarily interesting enough to the user to warrant further action. in fact, presenting all of the detected entities to a user may annoy the user to the point where he decides to turn this capability off completely, an undesirable outcome. therefore, we propose to measure the quality and utility of user-centric entity detection systems in three core dimensions: the accuracy, the interestingness, and the relevance of the entities it presents to the user. we show that leveraging surrounding context can greatly improve the performance of such systems in all three dimensions by employing novel algorithms for generating a concept vector and for finding concept extensions using search query logs. we extensively evaluate the proposed algorithms within contextual shortcuts - a large-scale user-centric entity detection platform - using 1,586 entities detected over 1,519 documents. the results confirm the importance of using context within user-centric entity detection systems, and validate the usefulness of the proposed algorithms by showing how they improve the overall entity detection quality within contextual shortcuts.
extending query translation to cross-language query expansion with markov chain models. dictionary-based approaches to query translation have been widely used in cross-language information retrieval (clir) experiments. however, translation has been not only limited by the coverage of the dictionary, but also affected by translation ambiguities. in this paper we propose a novel method of query translation that combines other types of term relation to complement the dictionary-based translation. this allows extending the literal query translation to related words, which produce a beneficial effect of query expansion in clir. in this paper, we model query translation by markov chains (mc), where query translation is viewed as a process of expanding query terms to their semantically similar terms in a different language. in mc, terms and their relationships are modeled as a directed graph, and query translation is performed as a random walk in the graph, which propagates probabilities to related terms. this framework allows us to incorporating different types of term relation, either between two languages or within the source or target languages. in addition, the iterative training process of mc allows us to attribute higher probabilities to the target terms more related to the original query, thus offers a solution to the translation ambiguity problem. we evaluated our method on three clir benchmark collections, and obtained significant improvements over traditional dictionary-based approaches.
a fast unified optimal route query evaluation algorithm. we investigate the problem of how to evaluate, fast and efficiently, classes of optimal route queries on a massive graph in a unified framework. to evaluate a route query effectively, a large network is partitioned into a collection of fragments, and distances of some optimal routes in the network are pre-computed. under such a setting, we find a unified algorithm that can evaluate classes of optimal route queries. the classes that can be processed efficiently are called constraint preserving (cp) which include, among others, shortest path, forbidden edges, forbidden nodes and α-autonomy optimal route query classes. we prove the correctness of the unified algorithm. we then turn our attention to the optimization of the proposed algorithm. several pruning and optimization techniques are derived that minimize the search time and i/o accesses. we show empirically that these techniques are effective. the proposed optimal route query evaluation algorithm, with all these techniques incorporated, is compared with a main-memory and a disk-based brute-force cp algorithms. we show experimentally that the proposed unified algorithm outperforms the brute-force algorithms, both in term of cpu time and i/o cost, by a wide margin.
domain knowledge conceptual inter-media indexing: application to multilingual multimedia medical reports. conceptual indexing is a way to produce only one index for many multilingual documents. inter-media conceptual indexing promotes the use of common concepts between two media in order to use a single index for several media. in this paper we explore such an advance indexing point of view. we show the benefit of an automatic conceptual indexing for texts and its extension for text and image documents. tests are conducted on the multilingual image and text medical document corpus of the clef initiative, where we obtain best results on text in 2005 and 2006, and show promising results on images, and best results for the combination of image and text.
an experimental study of the impact of information extraction accuracy on semantic search performance. researchers have shown that various natural language processing techniques can be used in document analysis to impact search performance. for the most part, they examined how an analysis system with certain performance characteristics can be leveraged to improve document and/or passage search results. we have previously shown that semantic queries which utilize named entity and relation information extracted from the corpus can lead to significant improvement in search performance. in this paper, we extend our previous efforts and examine how search performance degrades in the face of imperfect named entity and relation extraction. our study was carried out by developing gold standard annotated corpora and applying different error models to the gold standard annotations to simulate errors made by automatic recognizers. we identify automatic recognizer characteristics that make them more amenable to our search tasks, show that recognizer recall has more significant impact on semantic search performance than its precision, and demonstrate that significant improvement in both map and exact precision scores can be achieved by adopting automatic named entity and relation recognizers with near state-of-the-art performance.
the t4sql temporal query language. time characterizes every aspect of our life and its management when storing and querying data is very important. in this paper we propose a new temporal query language, called t4sql, supporting multiple temporal dimensions of data. besides the well-known valid and transaction times, it encompasses two additional temporal dimensions, namely, availability and event times. the availability time records when information is known and treated as true by the information system; the event times record the occurrence times of both the event that starts the valid time and the event that ends it. t4sql is capable to deal with different temporal semantics (atemporal aka non-sequenced, current, sequenced, next) with respect to every temporal dimension. moreover, t4sql provides a novel temporal grouping clause and an orthogonal management of temporal properties when defining the selection condition(s) and the schema for the output relation.
discovering interesting usage patterns in text collections: integrating text mining with visualization. this paper addresses the problem of making text mining results more comprehensible to humanities scholars, journalists, intelligence analysts, and other researchers, in order to support the analysis of text collections. our system, featurelens1, visualizes a text collection at several levels of granularity and enables users to explore interesting text patterns. the current implementation focuses on frequent itemsets of n-grams, as they capture the repetition of exact or similar expressions in the collection. users can find meaningful co-occurrences of text patterns by visualizing them within and across documents in the collection. this also permits users to identify the temporal evolution of usage such as increasing, decreasing or sudden appearance of text patterns. the interface could be used to explore other text features as well. initial studies suggest that featurelens helped a literary scholar and 8 users generate new hypotheses and interesting insights using 2 text collections.
a strategy for allowing meaningful and comparable scores in approximate matching. the goal of approximate data matching is to assess whether two distinct data instances represent the same real world object. this is usually achieved through the use of a similarity function, which returns a score that defines how similar two data instances are. if this score surpasses a given threshold, both data instances are considered as representing the same real world object. the score values returned by a similarity function depend on the algorithm that implements the function and have no meaning to the user (apart from the fact that a higher similarity value means that two data instances are more similar). in this paper, we propose that instead of defining the threshold in terms of the scores returned by a similarity function, the user specifies the precision that is expected from the matching process. precision is a well known quality measure and has a clear interpretation from the user's point of view. our approach relies on mapping between similarity scores and precision values based on a training data set. experimental results show the training may be executed against a representative data set, and reused for other databases from the same domain.
quickmig: automatic schema matching for data migration projects. a common task in many database applications is the migration of legacy data from multiple sources into a new one. this requires identifying semantically related elements of the source and target systems and the creation of mapping expressions to transform instances of those elements from the source format to the target format. currently, data migration is typically done manually, a tedious and timeconsuming process, which is difficult to scale to a high number of data sources. in this paper, we describe quickmig, a new semi-automatic approach to determining semantic correspondences between schema elements for data migration applications. quickmig advances the state of the art with a set of new techniques exploiting sample instances, domain ontologies, and reuse of existing mappings to detect not only element correspondences but also their mapping expressions. quickmig further includes new mechanisms to effectively incorporate domain knowledge of users into the matching process. the results from a comprehensive evaluation using real-world schemas and data indicate the high quality and practicability of the overall approach.
rk-hist: an r-tree based histogram for multi-dimensional selectivity estimation. database query engines typically rely upon query size estimators in order to evaluate the potential cost of alternate query plans. in multi-dimensional database systems, such as those typically found in large data warehousing environments, these selectivity estimators often take the form of multi-dimensional histograms. but while single dimensional histograms have proven to be quite accurate, even in the presence of data skew, the multi-dimensional variations have generally been far less reliable. in this paper, we present a new histogram model that is based upon an r-tree space partitioning. the localization of the r-tree boxes is in turn controlled by a hilbert space filling curve, while a series of efficient area equalization heuristics restructures the initial boxes to provide improved bucket representation. experimental results demonstrate significantly improved estimation accuracy relative to state of the art alternatives, as well as superior consistency across a variety of record distributions.
mapgraph: efficient methods for complex olap hierarchies. online analytical processing is a database paradigm that provides for the rich analysis of multi-dimensional data. olap is often supported by a logical structure known as the cube. however, supporting efficient olap query resolution in enterprise scale environments is an issue of considerable complexity. in practice, the difficulty of the problem is exacerbated by the existence of dimension hierarchies that sub-divide core dimensions into aggregation layers of varying granularity. common hierarchy-sensitive query operations such as rollup and drilldown can be very costly on large cubes. moreover, facilities for the representation of more complex hierarchical relationships are not well supported by conventional techniques. this paper presents a robust hierarchy infrastructure called mapgraph that supports the efficient and transparent manipulation of attribute hierarchies within olap environments. experimental results verify that, when compared to the alternatives, very little additional overhead is introduced, even when advanced functionality is exploited.
learning on the border: active learning in imbalanced data classification. this paper is concerned with the class imbalance problem which has been known to hinder the learning performance of classification algorithms. the problem occurs when there are significantly less number of observations of the target concept. various real-world classification tasks, such as medical diagnosis, text categorization and fraud detection suffer from this phenomenon. the standard machine learning algorithms yield better prediction performance with balanced datasets. in this paper, we demonstrate that active learning is capable of solving the class imbalance problem by providing the learner more balanced classes. we also propose an efficient way of selecting informative instances from a smaller pool of samples for active learning which does not necessitate a search through the entire dataset. the proposed method yields an efficient querying system and allows active learning to be applied to very large datasets. our experimental results show that with an early stopping criteria, active learning achieves a fast solution with competitive prediction performance in imbalanced data classification.
randomized metric induction and evolutionary conceptual clustering for semantic knowledge bases. we present an evolutionary clustering method which can be applied to multi-relational knowledge bases storing semantic resource annotations expressed in the standard languages for the semantic web. the method exploits an effective and language-independent semi-distance measure defined for the space of individual resources, that is based on a finite number of dimensions corresponding to a committee of features represented by a group of concept descriptions (discriminating features). we show how to obtain a maximally discriminating group of features through a feature construction method based on genetic programming. the algorithm represents the possible clusterings as strings of central elements (medoids, w.r.t. the given metric) of variable length. hence, the number of clusters is not needed as a parameter since the method can optimize it by means of the mutation operators and of a proper fitness function. we also show how to assign each cluster with a newly constructed intensional definition in the employed concept language. an experimentation with some ontologies proves the feasibility of our method and its effectiveness in terms of clustering validity indices.
evaluation of phrasal query suggestions. this paper evaluates the uptake and efficacy of a unified approach to phrasal query suggestions in the context of a high-precision search engine. the search engine performs ranked extended-boolean searches with the proximity operator <scp>near</scp> being the default operation. suggestions are offered to the searcher when the length of the result list falls outside predefined bounds. if the list is too long, the engine suggests narrowing the query through the use of super phrases; if the list is too short, the engine suggests broadening the query through the use of proximal subphrases. we evaluated uptake of phrasal query suggestions by analyzing search log data from before and after the suggestion feature was added to a commercial version of the search engine. we looked at approximately 1.5 million queries and found that, after they were added, suggestions represented nearly 30% of the total queries. we evaluated efficacy through a controlled study of 24 participants performing nine searches using three different search engines. we found that the engine with phrase suggestions had better high-precision recall than both the same search engine without suggestions and a search engine with a similar interface but using an okapi bm25 ranking algorithm.
improving the classification of newsgroup messages through social network analysis. improving the classification of newsgroup messages through social network analysis. in this paper, we focus on automatic classification of message replies into several types. for representing messages we consider rich feature sets that combine the standard author reply-to network properties with features derived from four additional structures identified in the data: 1) a network of authors who participate in the same threads, 2) network of authors who post similar content, 3) network of threads sharing common authors, and 4) network of content-related threads. for selected newsgroups we train linear svm classifiers to identify agreement and disagreement with the original message, and question and answer patterns in the threads. we show that the use of newly defined features substantially improves classification of messages in comparison with the svm model based only on the standard reply-to network.
optimizing parallel itineraries for knn query processing in wireless sensor networks. spatial queries for extracting data from wireless sensor networks are important for many applications, such as environmental monitoring and military surveillance. one such query is k nearest neighbor (knn) query that facilitates sampling of monitored sensor data in correspondence with a given query location. recently, itinerary-based knn query processing techniques, that propagate queries and collect data along a pre-determined itinerary, have been developed concurrently [12] [14]. these research works demonstrate that itinerary-based knn query processing algorithms are able to achieve better energy efficiency than other existing algorithms. however, how to derive itineraries based on different performance requirements remains a challenging problem. in this paper, we propose a new itinerary-based knn query processing technique, called pciknn, that derives different itineraries aiming at optimizing two performance criteria, response latency and energy consumption. the performance of pciknn is analyzed mathematically and evaluated through extensive experiments. experimental results show that pciknn has better performance and scalability than the state-of-the-art.
ntjfsatnot: a novel method for query with not-predicates on xml data. previous researches, in the filed of xml databases, have been done to evaluate xml queries with and-branches. however, as far as we know, very little work has examined the efficient processing of xml queries with not-predicates. also these methods have to process all of the query nodes in the document when dealing with queries with not-branch. in this paper, with some modification in tjfast method, we propose a new manner for answering to various not-queries. this method processes nodes efficiently, in a way that in the ideal state, we obtain part of the answer after the process of each node, and we don't have any unreasonable processing of each node.
efficient on-line index maintenance for dynamic text collections by using dynamic balancing tree. previous on-line index maintenance strategies are mainly designed for document insertions without considering document deletions. in a truly dynamic search environment, however, documents may be added to and removed from the collection at any point in time. in this paper, we examine issues of on-line index maintenance with support for instantaneous document deletions and insertions. we present a dbt merge strategy that can dynamically adjust the sequence of sub-index merge operations during index construction, and offers better query processing performance than previous methods, while providing an equivalent level of index maintenance performance when document insertions and deletions exist in parallel. using experiments on 426 gb of web data we demonstrate the efficiency of our method in practice, showing that on-line index construction for dynamic text collections can be performed efficiently and almost as fast as for growing text collections.
combination of evidences in relevance feedback for xml retrieval. the main objective in xml retrieval is to select the relevant elements of xml document instead of the whole document. many open issues appear when considering relevance feedback (rf) in xml documents. they are mainly related to the form of xml documents, which mix content and structure information and to the new information granularity. in this paper, a new flexible method of relevance feedback in xml retrieval using two sources of evidence is described. we propose to use the context criterion to select terms to extend the initial query and to use generative structures to express structural constraints. both approaches are applied in different combined forms. experiments are carried out with the inex evaluation campaign and results show the effectiveness of our approach.
a correlation-based model for unsupervised feature selection. we propose a new model for feature evaluation and selection that assesses the propensity of the features to support two-set classification. for each item of the data set, the collection of features induce a ranking (ordered list) of the remaining items. the evaluation criterion favors features that result in the most consistent discrimination between relevant and non-relevant items within these ranked lists. the discrimination boundaries within a single list are determined combinatorially, according to the degree of correlation among the relevant sets of its members. the model makes no special assumptions on the nature of the data. a selection heuristic based on the model is also proposed using sequential forward generation, and an experimental comparison is made with other unsupervised feature selection methods.
measuring article quality in wikipedia: models and evaluation. wikipedia has grown to be the world largest and busiest free encyclopedia, in which articles are collaboratively written and maintained by volunteers online. despite its success as a means of knowledge sharing and collaboration, the public has never stopped criticizing the quality of wikipedia articles edited by non-experts and inexperienced contributors. in this paper, we investigate the problem of assessing the quality of articles in collaborative authoring of wikipedia. we propose three article quality measurement models that make use of the interaction data between articles and their contributors derived from the article edit history. our b<scp>asic</scp> model is designed based on the mutual dependency between article quality and their author authority. the p<scp>eer</scp>r<scp>eview</scp> model introduces the review behavior into measuring article quality. finally, our p<scp>rob</scp>r<scp>eview</scp> models extend p<scp>eer</scp>r<scp>eview</scp> with partial reviewership of contributors as they edit various portions of the articles. we conduct experiments on a set of well-labeled wikipedia articles to evaluate the effectiveness of our quality measurement models in resembling human judgement.
comments-oriented blog summarization by sentence extraction. much existing research on blogs focused on posts only, ignoring their comments. our user study conducted on summarizing blog posts, however, showed that reading comments does change one's understanding about blog posts. in this research, we aim to extract representative sentences from a blog post that best represent the topics discussed among its comments. the proposed solution first derives representative words from comments and then selects sentences containing representative words. the representativeness of words is measured using requt (i.e., reader, quotation, and topic). evaluated on human labeled sentences, requt together with summation-based sentence selection showed promising results.
a method for online analytical processing of text data. there are increasingly visible demands for structured/ unstructured information integration and advanced analytics. however, conventional database technology has not been able to present a robust and practical implementation of a truly integrated architecture for such purposes. after working on several industrial applications (in particular, in the healthcare and life sciences area), we have identified fundamental issues and technical approaches to tackle the issues. in this paper, we propose data representations and algebraic operations for integrating semantic information (e.g., ontologies) into olap systems, which allow us to analyze a huge set of textual documents with their underlying semantic information. the performance of the prototype implementation has been evaluated using real world datasets, and the high scalability and flexibility of our approach have been confirmed with respect to the computation time.
ix-cubes: iceberg cubes for data warehousing and olap on xml data. with increasing amount of data being stored in xml format, olap queries over these data become important. olap queries have been well studied in the relational database systems. however, the evaluation of olap queries over xml data is not a trivial extension of the relational solutions, especially when a schema is not available. in this paper, we introduce the ix-cube (iceberg xml cube) over xml data to tackle the problem. we extend olap operations to xml data. we also develop efficient approaches to ix-cube computation and olap query evaluation using ix-cubes.
a two-stage approach to domain adaptation for statistical classifiers. in this paper, we consider the problem of adapting statistical classifiers trained from some source domains where labeled examples are available to a target domain where no labeled example is available. one characteristic of such a domain adaptation problem is that the examples in the source domains and the target domain are known to follow different distributions. thus a regular classification method would tend to overfit the source domains. we present a two-stage approach to domain adaptation, where at the first <generalization stage, we look for a set of features generalizable across domains, and at the second adaptation stage, we pick up useful features specific to the target domain. observing that the exact objective function is hard to optimize, we then propose a number of heuristics to approximately achieve the goal of generalization and adaptation. our experiments on gene name recognition using a real data set show the effectiveness of our general framework and the heuristics.
"i know what you did last summer": query logs and user privacy. we investigate the subtle cues to user identity that may be exploited in attacks on the privacy of users in web search query logs. we study the application of simple classifiers to map a sequence of queries into the gender, age, and location of the user issuing the queries. we then show how these classifiers may be carefully combined at multiple granularities to map a sequence of queries into a set of candidate users that is 300-600 times smaller than random chance would allow. we show that this approach remains accurate even after removing personally identifiable information such as names/numbers or limiting the size of the query log. we also present a new attack in which a real-world acquaintance of a user attempts to identify that user in a large query log, using personal information. we show that combinations of small pieces of information about terms a user would probably search for can be highly effective in identifying the sessions of that user. we conclude that known schemes to release even heavily scrubbed query logs that contain session information have significant privacy risks.
indexing multiversion databases. an efficient management of multiversion data with branched evolution is crucial for many applications. it requires database designers aware of tradeoffs among index structures and policies. this paper defines a framework and an analysis method for understanding the behavior of different indexing policies. given data and query characteristics the analysis allows determining the most suitable index structure. the analysis is validated by an experimental study.
discovering authorities in question answer communities by using link analysis. question-answer portals such as naver and yahoo! answers are quickly becoming rich sources of knowledge on many topics which are not well served by general web search engines. unfortunately, the quality of the submitted answers is uneven, ranging from excellent detailed answers to snappy and insulting remarks or even advertisements for commercial content. furthermore, user feedback for many topics is sparse, and can be insufficient to reliably identify good answers from the bad ones. hence, estimating the authority of users is a crucial task for this emerging domain, with potential applications to answer ranking, spam detection, and incentive mechanism design. we present an analysis of the link structure of a general-purpose question answering community to discover authoritative users, and promising experimental results over a dataset of more than 3 million answers from a popular community qa site. we also describe structural differences between question topics that correlate with the success of link analysis for authority discovery.
parallel linkage. we study the parallelization of the (record) linkage problem - i.e., to identify matching records between two collections of records, a and b. one of main idiosyncrasies of the linkage problem, compared to database join, is the fact that once two records a in a and b in b are matched and merged to c, c needs to be compared to the rest of records in a and b again since it may incur new matching. this re-feeding stage of the linkage problem requires its solution to be iterative, and complicates the problem significantly. toward this problem, we first discuss three plausible scenarios of inputs - when both collections are clean, only one is clean, and both are dirty. then, we show that the intricate interplay between match and merge can exploit the characteristics of each scenario to achieve good parallelization. our parallel algorithms achieve 6.55-7.49 times faster in speedup compared to sequential ones with 8 processors, and 11.15-18.56% improvement in efficiency compared to p-swoosh.
generalizing from relevance feedback using named entity wildcards. traditional adaptive filtering systems learn the user's interests in a rather simple way - words from relevant documents are favored in the query model, while words from irrelevant documents are down-weighted. this biases the query model towards specific words seen in the past, causing the system to favor documents containing relevant but redundant information over documents that use previously unseen words to denote new facts about the same news event. this paper proposes news ways of generalizing from relevance feedback by augmenting the traditional bag-of-words query model with named entity wildcards that are anchored in context. the use of wildcards allows generalization beyond specific words, while contextual restrictions limit the wildcard-matching to entities related to the user's query. we test our new approach in a nugget-level adaptive filtering system and evaluate it in terms of both relevance and novelty of the presented information. our results indicate that higher recall is obtained when lexical terms are generalized using wildcards. however, such wildcards must be anchored to their context to maintain good precision. how the context of a wildcard is represented and matched against a given document also plays a crucial role in the performance of the retrieval system.
structure-based inference of xml similarity for fuzzy duplicate detection. fuzzy duplicate detection aims at identifying multiple representations of real-world objects stored in a data source, and is a task of critical practical relevance in data cleaning, data mining, or data integration. it has a long history for relational data stored in a single table (or in multiple tables with equal schema). algorithms for fuzzy duplicate detection in more complex structures, e.g., hierarchies of a data warehouse, xml data, or graph data have only recently emerged. these algorithms use similarity measures that consider the duplicate status of their direct neighbors, e.g., children in hierarchical data, to improve duplicate detection effectiveness. in this paper, we propose a novel method for fuzzy duplicate detection in hierarchical and semi-structured xml data. unlike previous approaches, it not only considers the duplicate status of children, but rather the probability of descendants being duplicates. probabilities are computed efficiently using a bayesian network. experiments show the proposed algorithm is able to maintain high precision and recall values, even when dealing with data containing a high amount of errors and missing information. our proposal is also able to outperform a state-of-the-art duplicate detection system on three different xml databases.
just in time indexing for up to the second search. e-commerce and intranet search systems require newly arriving content to be indexed and made available for search within minutes or hours of arrival. applications such as file system and email search demand even faster turnaround from search systems, requiring new content to become available for search almost instantaneously. however, incrementally updating inverted indices, which are the predominant datastructure used in search engines, is an expensive operation that most systems avoid performing at high rates. we present jiti, a just-in-time indexing component that allows searching over incoming content (nearly) as soon as that content reaches the system. jiti's main idea is to invest less in the preprocessing of arriving data, at the expense of a tolerable latency in query response time. it is designed for deployment in search systems that maintain a large main index and that rebuild smaller stop-press indices once or twice an hour. jiti augments such systems with instant retrieval capabilities over content arriving in between the stop-press builds. a main design point is for jiti to demand few computational resources, in particular ram and i/o. our experiments consisted of injecting several documents and queries per second concurrently into the system over half-hour long periods. we believe that there are search applications for which the combination of the workloads we experimented with and the response times we measured present a viable solution to a pressing problem.
ensembling bayesian network structure learning on limited data. in recent years, bagging method has been applied to learn bayesian networks (bns), especially on limited datasets. however, the bns learned using bagging method from limited datasets can be biased towards complex models. we present an efficient approach to produce more accurate bns from limited datasets. based on the markov condition of bn learning, we proposed a novel sampling method, called root nodes based sampling (rns), and a bns fusion method. the experimental results reveal that our ensemble method can achieve more accurate results in terms of accuracy on limited datasets.
expertise drift and query expansion in expert search. pseudo-relevance feedback, or query expansion, has been shown to improve retrieval performance in the adhoc retrieval task. in such a scenario, a few top-ranked documents are assumed to be relevant, and these are then used to expand and refine the initial user query, such that it retrieves a higher quality ranking of documents. however, there has been little work in applying query expansion in the expert search task. in this setting, query expansion is applied by assuming a few top-ranked candidates have relevant expertise, and using these to expand the query. nevertheless, retrieval is not improved as expected using such an approach. we show that the success of the application of query expansion is hindered by the presence of topic drift within the profiles of experts that the system considers. in this work, we demonstrate how topic drift occurs in the expert profiles, and moreover, we propose three measures to predict the amount of drift occurring in an expert's profile. finally, we suggest and evaluate ways of enhancing query expansion in expert search using our new insights. our results show that, once topic drift has been anticipated, query expansion can be successfully applied in a general manner in the expert search task.
dex: high-performance exploration on large graphs for information retrieval. link and graph analysis tools are important devices to boost the richness of information retrieval systems. internet and the existing social networking portals are just a couple of situations where the use of these tools would be beneficial and enriching for the users and the analysts. however, the need for integrating different data sources and, even more important, the need for high performance generic tools, is at odds with the continuously growing size and number of data repositories. in this paper we propose and evaluate dex, a high performance graph database querying system that allows for the integration of multiple data sources. dex makes graph querying possible in different flavors, including link analysis, social network analysis, pattern recognition and keyword search. the richness of dex shows up in the experiments that we carried out on the internet movie database (imdb). through a variety of these complex analytical queries, dex shows to be a generic and efficient tool on large graph databases.
automatic feature selection in the markov random field model for information retrieval. previous applications of the markov random field model for information retrieval have used manually chosen features. however, it is often difficult or impossible to know, a priori, the best set of features to use for a given task or data set. therefore, there is a need to develop automatic feature selection techniques. in this paper we describe a greedy procedure for automatically selecting features to use within the markov random field model for information retrieval. we also propose a novel, robust method for describing classes of textual information retrieval features. experimental results, evaluated on standard trec test collections, show that our feature selection algorithm produces models that are either significantly more effective than, or equally effective as, models with manually selected features, such as those used in the past.
wikify!: linking documents to encyclopedic knowledge. this paper introduces the use of wikipedia as a resource for automatic keyword extraction and word sense disambiguation, and shows how this online encyclopedia can be used to achieve state-of-the-art results on both these tasks. the paper also shows how the two methods can be combined into a system able to automatically enrich a text with links to encyclopedic knowledge. given an input document, the system identifies the important concepts in the text and automatically links these concepts to the corresponding wikipedia pages. evaluations of the system show that the automatic annotations are reliable and hardly distinguishable from manual annotations.
a knowledge-based search engine powered by wikipedia. this paper describes koru, a new search interface that offers effective domain-independent knowledge-based information retrieval. koru exhibits an understanding of the topics of both queries and documents. this allows it to (a) expand queries automatically and (b) help guide the user as they evolve their queries interactively. its understanding is mined from the vast investment of manual effort and judgment that is wikipedia. we show how this open, constantly evolving encyclopedia can yield inexpensive knowledge structures that are specifically tailored to expose the topics, terminology and semantics of individual document collections. we conducted a detailed user study with 12 participants and 10 topics from the 2005 trec hard track, and found that koru and its underlying knowledge base offers significant advantages over traditional keyword search. it was capable of lending assistance to almost every query issued to it; making their entry more efficient, improving the relevance of the documents they return, and narrowing the gap between expert and novice seekers.
hybrid results merging. the problem of results merging in distributed information retrieval environments has been approached by two different directions in research. estimation approaches attempt to calculate the relevance of the returned documents through ad-hoc methodologies (weighted score merging, regression etc) while download approaches, download all the documents locally, partially or completely, in order to estimate "first hand" their relevance. both have their advantages and disadvantages. it is assumed that download algorithms are more effective but they are very expensive in terms of time and bandwidth. estimation approaches on the other hand, usually rely on document relevance scores being returned by the remote collections in order to achieve maximum performance. in addition to that, regression algorithms, which have proved to be more effective than weighted scores merging, rely on a significant number of overlap documents in order to function effectively, practically requiring multiple interactions with the remote collections. the new algorithm that is introduced reconciles the above two approaches, combining their strengths, while minimizing their weaknesses. it is based on downloading a limited, selected number of documents from the remote collections and estimating the relevance of the rest through regression methodologies. the proposed algorithm is tested in a variety of settings and its performance is found to be better than estimation approaches, while approximating that of download.
automatic call section segmentation for contact-center calls. this paper presents a svm (support vector machine) classification system which divides contact-center call transcripts into "greeting", "question", "refine", "research", "resolution", "closing" and "out-of-topic" sections. this call section segmentation is useful to improve search and retrieval functions and to provide more detailed statistics on calls. we use an off-the-shelf automatic speech recognition (asr) system to generate call transcripts from recorded calls between customers and service representatives. we first classify an individual utterance into a call section by applying the svm classifier and then merge adjacent utterances classified into a same call section. we experiment with the proposed system on 100 automatically transcribed calls. the 10-fold cross validation shows 87.2% classification accuracy. we also compare the proposed algorithm with two other approaches - the most frequent section only method and a maximum entropy-based segmentation. the evaluation shows that our system's accuracy is 12% higher than the first baseline system and 6% higher than the second baseline system respectively.
grid-based subspace clustering over data streams. a real-life data stream usually contains many dimensions and some dimensional values of its data elements may be missing. in order to effectively extract the on-going change of a data stream with respect to all the subsets of the dimensions of the data stream, a grid-based subspace clustering algorithm is proposed in this paper. given an n-dimensional data stream, the on-going distribution statistics of data elements in each one-dimension data space is firstly monitored by a list of grid-cells called a sibling list. once a dense grid-cell of a first-level sibling list becomes a dense unit grid-cell, new second-level sibling lists are created as its child nodes in order to trace any cluster in all possible two-dimensional rectangular subspaces. in such a way, a sibling tree grows up to the nth level at most and a k-dimensional subcluster can be found in the kth level of the sibling tree. the proposed method is comparatively analyzed by a series of experiments to identify its various characteristics.
mining web multi-resolution community-based popularity for information retrieval. the pagerank algorithm is used in web information retrieval to calculate a single list of popularity scores for each page in the web. these popularity scores are used to rank query results when presented to the user. by using the structure of the entire web to calculate one score per document, we are calculating a general popularity score, not particular to any community. therefore, the pagerank scores are more suited to general queries. in this paper, we introduce a more general form of pagerank, using web multi-resolution community-based popularity scores, where each document obtains a popularity score dependent on a given web community. when a query is related to a specific community, we choose the associated set of popularity scores and order the query results accordingly. using web-community based popularity scores, we achieved an 11% increase in precision over pagerank.
lightweight web-based fact repositories for textual question answering. since answers to fact-seeking questions usually reside within small factual text nuggets, often "hidden" within full-length documents, their relevance to a question is not necessarily correlated to the relevance of the full-length document to the question. yet previous approaches to open-domain textual question answering from large document collections quasi-unanimously employ a document retrieval stage, in order to apply widely different, often expensive answer mining techniques to only a small subset of documents. depending on the collection size, 95% or more of the documents in the collection (much more in the case of the web) are left out of the selected subset for any given query, and thus become invisible to subsequent processing stages for actual answer mining. this paper introduces a new model for answer retrieval for question answering. the collection is distilled offline into large repositories of facts. each fact constitutes a potential direct answer to questions seeking a particular kind of entity or relation, such as questions asking about the date of particular events. question answering becomes equivalent to online fact retrieval, which greatly simplifies the de-facto system architecture for fact-seeking question answering. in addition to simplicity, experiments on a fact repository acquired from approximately a billion web documents illustrate the impact of fact repositories in extracting accurate answers to a standard evaluation set of open-domain test questions and additional sets of domain-specific questions.
weakly-supervised discovery of named entities using web search queries. a seed-based framework for textual information extraction allows for weakly supervised extraction of named entities from anonymized web search queries. the extraction is guided by a small set of seed named entities, without any need for handcrafted extraction patterns or domain-specific knowledge, allowing for the acquisition of named entities pertaining to various classes of interest to web search users. inherently noisy search queries are shown to be a highly valuable, albeit little explored, resource for web-based named entity discovery.
the role of documents vs. queries in extracting class attributes from text. challenging the implicit reliance on document collections, this paper discusses the pros and cons of using query logs rather than document collections, as self-contained sources of data in textual information extraction. the differences are quantified as part of a large-scale study on extracting prominent attributes or quantifiable properties of classes (e.g., top speed, price and fuel consumption for carmodel) from unstructured text. in a head-to-head qualitative comparison, a lightweight extraction method produces class attributes that are 45% more accurate on average, when acquired from query logs rather than web documents.
using word similarity to eradicate junk emails. emails are one of the most commonly used modern communication media these days; however, unsolicited emails obstruct this otherwise fast and convenient technology for information exchange and jeopardize the continuity of this popular communication tool. waste of valuable resources and time and exposure to offensive content are only a few of the problems that arise as a result of junk emails. in addition, the monetary cost of processing junk emails reaches billions of dollars per year and is absorbed by public users and internet service providers. even though there has been extensive work in the past dedicated to eradicate junk emails, none of the existing junk email detection approaches has been highly successful in solving these problems, since spammers have been able to infiltrate existing detection techniques. in this paper, we present a new tool, junex, which relies on the content similarity of emails to eradicate junk emails. junex compares each incoming email to a core of emails marked as junk by each individual user to identify unwanted emails while reducing the number of legitimate emails treated as junk, which is critical. conducted experiments on junex verify its high accuracy.
proximity-based document representation for named entity retrieval. one aspect in which retrieving named entities is different from retrieving documents is that the items to be retrieved - persons, locations, organizations - are only indirectly described by documents throughout the collection. much work has been dedicated to finding references to named entities, in particular to the problems of named entity extraction and disambiguation. however, just as important for retrieval performance is how these snippets of text are combined to build named entity representations. we focus on the trec expert search task where the goal is to identify people who are knowledgeable on a specific topic. existing language modeling techniques for expert finding assume that terms and person entities are conditionally independent given a document. we present theoretical and experimental evidence that this simplifying assumption ignores information on how named entities relate to document content. to address this issue, we propose a new document representation which emphasizes text in proximity to entities and thus incorporates sequential information implicit in text. our experiments demonstrate that the proposed model significantly improves retrieval performance. the main contribution of this work is an effective formal method for explicitly modeling the dependency between the named entities and terms which appear in a document.
latent semantic fusion model for image retrieval and annotation. this paper studies the effect of latent semantic analysis (lsa) on two different tasks: multimedia document retrieval (mdr) and automatic image annotation (aia). the contributions of this paper are twofold. first, to the best of our knowledge, this work is the first study of the influence of lsa on the retrieval of a significant number of multimedia documents (i.e. collection of 20000 tourist images). second, it shows how different image representations (region-based and keypoint-based) can be combined by lsa to improve automatic image annotation. the document collections used for these experiments are the corel photo collection and imageclef 2006 collection.
modeling historical and future movements of spatio-temporal objects in moving objects databases. spatio-temporal databases deal with geometries changing over time. in general, geometries do not only change discretely but continuously; hence we are dealing with moving objects. in the past, a few moving object data models and query languages have been proposed. each of them supports either historical movements or future movements but not both together. consequently, queries that start in the past and extend into the future cannot be supported. to model both historical and future movements of an object, two separate concepts with different properties are required, and extra attention is necessary to avoid their conflicts. furthermore, current definitions of moving objects are too general and vague. it is unclear how a moving object is allowed to move through space and time. for instance, the continuity or discontinuity of motion is not specified. in this paper, we propose a new moving object data model called balloon model which provides integrated support for both historical and future movements of moving objects. as part of the model, we provide formal definitions of moving objects with respect to their past and future movements. all kinds of queries including past queries, future queries, and queries that start in the past and end in the future are supported in our model.
semantic components enhance retrieval of domain-specific documents. we seek to leverage knowledge about information organization in a domain to effectively and efficiently meet targeted information needs of expert users. the semantic components model represents document content in a manner that is complementary to full text and keyword indexing. semantic component instances are segments of text about a particular aspect of the main topic of the document and may not correspond to structural elements in the document. this paper describes the semantic components model and presents experimental evidence from a large interactive searching study showing that semantic components, used to supplement full text and keyword indexing and to extend the query language, enhanced the retrieval of domain-specific documents in response to realistic queries posed by real users.
satisfaction balanced mediation. we consider a distributed information system that allows autonomous consumers to query autonomous providers. we focus on the problem of query allocation from a new point of view, by considering consumers and providers' satisfaction in addition to query load. we define satisfaction as a long-run notion based on the consumers and providers' preferences. we propose and validate a mediation process, called sbmediation, which is compared to capacity based query allocation. the experimental results show that sbmediation significantly outperforms capacity based when confronted to autonomous participants.
efficient web matrix processing based on dual reordering. pagerank is one of the most important ranking techniques used in search engines nowadays. since billions of pages already existed in web, many pagerank acceleration techniques were explored by many researchers. however, in the real web, just like the existence of pages without out-links, there are many pages without in-links. (in this paper, a web page without in-links is called a reverse-dangling page.) given the state of the art, we propose a new reordered pagerank algorithm, called two-way reordered pagerank algorithm, which exploits both dangling nodes and reverse-dangling nodes to reduce the computational complexity of the pagerank vector.
semantic verification in an online fact seeking environment. many artificial intelligence tasks, such as automated question answering, reasoning or heterogeneous database integration, involve verification of a semantic category (e.g. "coffee" is a drink, "red" is a color, while "steak" is not a drink and "big" is not a color). we present a novel algorithm to automatically validate a semantic category. contrary to the methods suggested earlier, our approach does not rely on any manually codified knowledge but instead capitalizes on the diversity of topics and word usage on the world wide web. we have tested our approach within our online fact-seeking (question answering) environment. when tested on the trec questions that expect the answer to belong to a specific semantic category, our approach has improved the accuracy by up to 14% depending on the model and metrics used.
polyhedral transformation for indexed rank order correlation queries. rank order correlation has been used extensively when the data is non-parametric or when the relationship between two variables is nonlinear and monotonic. in such cases, linear correlation measures, such as the product-moment coefficient, are inadequate and fail to detect correlative relations. we present a polyhedral indexing technique for rank order correlation queries for time series data. we use an interesting geometry interpretation of rank order correlation which lends itself to indexing by spatial indexes such as r-trees. our experimental results indicate one to two orders of magnitudes improvement over sequential scan - the only alternative solution.
high-dimensional descriptor indexing for large multimedia databases. in this paper we address the subject of large multimedia database indexing for content-based retrieval. we introduce multicurves, a new scheme for indexing high-dimensional descriptors. this technique, based on the simultaneous use of moderate-dimensional space-filling curves, has as main advantages the ability to handle high-dimensional data (100 dimensions and over), to allow the easy maintenance of the indexes (inclusion and deletion of data), and to adapt well to secondary storage, thus providing scalability to huge databases (millions, or even thousands of millions of descriptors). we use multicurves to perform the approximate k nearest neighbors search with a very good compromise between precision and speed. the evaluation of multicurves, carried out on large databases, demonstrates that the strategy compares well to other up-to-date k nearest neighbor search strategies. we also test multicurves on the real-world application of image identification for cultural institutions. in this application, which requires the fast search of a large amount of local descriptors, multicurves allows a dramatic speed-up in comparison to the brute-force strategy of sequential search, without any noticeable precision loss.
modeling and exploiting query interactions in database systems. the typical workload in a database system consists of a mixture of multiple queries of different types, running concurrently and interacting with each other. hence, optimizing performance requires reasoning about query mixes and their interactions, rather than considering individual queries or query types. in this paper, we show the significant impact that query interactions can have on workload performance. we present a new approach based on planning experiments and statistical modeling to capture the impact of query interactions. this approach requires no prior assumptions about the internal workings of the database system or the nature or cause of query interactions, making it portable across systems. as a concrete demonstration of the potential of capturing, modeling, and exploiting query interactions, we develop a novel interaction-aware query scheduler that targets report-generation workloads in business intelligence (bi) settings. under certain assumptions, the schedule found by this scheduler is within a constant factor of optimal. an experimental evaluation with tpc-h queries on ibm db2 demonstrates that our scheduler consistently outperforms (up to 4x) conventional schedulers that do not account for query interactions.
local approximation of pagerank and reverse pagerank. we consider the problem of approximating the pagerank of a target node using only local information provided by a link server. we prove that local approximation of pagerank is feasible if and only if the graph has low in-degree and admits fast pagerank convergence. while natural graphs, such as the web graph, are abundant with high in-degree nodes, making local pagerank approximation too costly, we show that reverse natural graphs tend to have low indegree while maintaining fast pagerank convergence. it follows that calculating reverse pagerank locally is frequently more feasible than computing pagerank locally. finally, we demonstrate the usefulness of reverse pagerank in five different applications.
predicting web spam with http session information. web spam is a widely-recognized threat to the quality and security of the web. web spam pages pollute search engine indexes, burden web crawlers and web mining services, and expose users to dangerous web-borne malware. to defend against web spam, most previous research analyzes the contents of web pages and the link structure of the web graph. unfortunately, these heavyweight approaches require full downloads of both legitimate and spam pages to be effective, making real-time deployment of these techniques infeasible for web browsers, high-performance web crawlers, and real-time web applications. in this paper, we present a lightweight, predictive approach to web spam classification that relies exclusively on http session information (i.e., hosting ip addresses and http session headers). concretely, we built an http session classifier based on our predictive technique, and by incorporating this classifier into http retrieval operations, we are able to detect web spam pages before the actual content transfer. as a result, our approach protects web users from web-propagated malware, and it generates significant bandwidth and storage savings. by applying our predictive technique to a corpus of almost 350,000 web spam instances and almost 400,000 legitimate instances, we were able to successfully detect 88.2% of the web spam pages with a false positive rate of only 0.4%. these classification results are superior to previous evaluation results obtained with traditional link-based and content-based techniques. additionally, our experiments show that our approach saves an average of 15.4 kb of bandwidth and storage resources for every successfully identified web spam page, while only adding an average of 101 microseconds to each http retrieval operation. therefore, our predictive technique can be successfully deployed in applications that demand real-time spam detection.
a method to predict social annotations. this paper predicts the stabilized tag set of a resource, with feedback of a small amount of user annotations, aiming to reduce the requirement of sufficient user annotations and to resolve the cold-start problem in a social annotation system.
active relevance feedback for difficult queries. relevance feedback has been demonstrated to be an effective strategy for improving retrieval accuracy. the existing relevance feedback algorithms based on language models and vector space models are not effective in learning from negative feedback documents, which are abundant if the initial query is difficult. the probabilistic retrieval model has the advantage of being able to naturally improve the estimation of both the relevant and non-relevant models. the dirichlet compound multinomial (dcm) distribution, which relies on hierarchical bayesian modeling techniques, is a more appropriate generative model for the probabilistic retrieval model than the traditional multinomial distribution. we propose a new relevance feedback algorithm, based on a mixture model of the dcm distribution, to effectively model the overlaps between the positive and negative feedback documents. consequently, the new algorithm improves the retrieval performance substantially for difficult queries. to further reduce human relevance evaluation, we propose a new active learning algorithm in conjunction with the new relevance feedback model. the new active learning algorithm implicitly models the diversity, density and relevance of unlabeled data in a transductive experimental design framework. experimental results on several trec datasets show that both the relevance feedback and active learning algorithm significantly improve retrieval accuracy.
shopsmart: product recommendations through technical specifications and user reviews. this paper describes a new method for providing recommendations tailored to a user's preferences using text mining techniques and online technical specifications of products. we first learn a model that can predict the price of a product given automatically-determined features describing technical specifications and users' opinions. we then use this model to rank a list of products based on individual users' preferences about various features. on a data set collected from amazon reviews and online technical specifications, rankings produced by this model rank the best product for a user in the 87th percentile of products in its category, on average. our approach outperforms several comparison systems by 21 percentiles or more.
an effective algorithm for mining 3-clusters in vertically partitioned data. conventional clustering algorithms group similar data points together along one dimension of a data table. bi-clustering simultaneously clusters both dimensions of a data table. 3-clustering goes one step further and aims to concurrently cluster two data tables that share a common set of row labels, but whose column labels are distinct. such clusters reveal the underlying connections between the elements of all three sets. we present a novel algorithm that discovers 3-clusters across vertically partitioned data. our approach presents two new and important formulations: first we introduce the notion of a 3-cluster in partitioned data; and second we present a mathematical formulation that measures the quality of such clusters. our algorithm discovers high quality, arbitrarily positioned, overlapping clusters, and is efficient in time. these results are exhibited in a comprehensive study on real datasets.
joke retrieval: recognizing the same joke told differently. in a corpus of jokes, a human might judge two documents to be the "same joke" even if characters, locations, and other details are varied. a given joke could be retold with an entirely different vocabulary while still maintaining its identity. since most retrieval systems consider documents to be related only when their word content is similar, we propose joke retrieval as a domain where standard language models may fail. other meaning-centric domains include logic puzzles, proverbs and recipes; in such domains, new techniques may be required to enable us to search effectively. for jokes, a necessary component of any retrieval system will be the ability to identify the "same joke," so we examine this task in both ranking and classification settings. we exploit the structure of jokes to develop two domain-specific alternatives to the "bag of words" document model. in one, only the punch lines, or final sentences, are compared; in the second, certain categories of words (e.g., professions and countries) are tagged and treated as interchangeable. each technique works well for certain jokes. by combining the methods using machine learning, we create a hybrid that achieves higher performance than any individual approach.
exploiting pipeline interruptions for efficient memory allocation. efficiency of memory-intensive operations is a key factor in obtaining good performance during multi-join query processing. the pipelined execution of these queries forces the operations in the query plan to be processed concurrently. making a wrong decision regarding the amount of memory allocated for such operations can have a drastic impact on the response time. however, some of the execution algorithms used at run time interrupt the pipelined execution, ensuring that some operations are never executed concurrently. because of this, it is essential to explore new approaches in order to improve memory exploitation. in this paper, we address the problem of memory allocation for multiple concurrent operations in a query execution plan. first, we study the dynamic needs for memory during the execution time, and define when two operations coexist. then, we propose a post-optimization phase, which (i) identifies the operations that are concurrently executed at run time and (ii) costs different memory allocation combinations to find a near optimal solution for any type of query execution plan. we have implemented our techniques in the ibm®db2® universal database" (db2 udb) showing that they achieve significant execution time improvements compared with previous approaches, especially for multi-join queries accessing large data volumes.
an algorithm to determine peer-reviewers. the peer-review process is the most widely accepted certification mechanism for officially accepting the written results of researchers within the scientific community. an essential component of peer-review is the identification of competent referees to review a submitted manuscript. this article presents an algorithm to automatically determine the most appropriate reviewers for a manuscript by way of a co-authorship network data structure and a relative-rank particle-swarm algorithm. this approach is novel in that it is not limited to a pre-selected set of referees, is computationally efficient, requires no human-intervention, and, in some instances, can automatically identify conflict of interest situations. a useful application of this algorithm would be to open commentary peer-review systems because it provides a weighting for each referee with respects to their expertise in the domain of a manuscript. the algorithm is validated using referee bid data from the 2005 joint conference on digital libraries.
scaling up duplicate detection in graph data. duplicate detection determines different representations of real-world objects in a database. recent research has considered the use of relationships among object representations to improve duplicate detection. in the general case where relationships form a graph, research has mainly focused on duplicate detection quality/effectiveness. scalability has been neglected so far, even though it is crucial for large real-world duplicate detection tasks. we scale up duplicate detection in graph data (ddg) to large amounts of data using the support of a relational database system. we first generalize the process of ddg and then present how to scale ddg in space (amount of data processed with limited main memory) and in time. finally, we explore how complex similarity computation can be performed efficiently. experiments on data an order of magnitude larger than data considered so far in ddg clearly show that our methods scale to large amounts of data.
clustering multi-way data via adaptive subspace iteration. clustering multi-way data is a very important research topic due to the intrinsic rich structures in real-world datasets. in this paper, we propose the subspace clustering algorithm on multi-way data, called asi-t (adaptive subspace iteration on tensor). asi-t is a special version of high order svd (hosvd), and it simultaneously performs subspace identification using 2dsvd and data clustering using k-means. the experimental results on synthetic data and real-world data demonstrate the effectiveness of asi-t.
a survey of pre-retrieval query performance predictors. the focus of research on query performance prediction is to predict the effectiveness of a query given a search system and a collection of documents. if the performance of queries can be estimated in advance of, or during the retrieval stage, specific measures can be taken to improve the overall performance of the system. in particular, pre-retrieval predictors predict the query performance before the retrieval step and are thus independent of the ranked list of results; such predictors base their predictions solely on query terms, the collection statistics and possibly external sources such as wordnet. in this poster, 22 pre-retrieval predictors are categorized and assessed on three different trec test collections.
cross-document cross-lingual coreference retrieval. in this work, we address coreference retrieval, which involves identifying aliases that are distinct references to an entity. we begin with a known alias and discover unknown aliases that refer to the same entity. we use entity language models to capture the contextual language around the known alias, which aids in finding new aliases. we also show that modeling the significant dates of the known aliases improves alias discovery performance.
exploiting temporal contexts in text classification. due to the increasing amount of information being stored and accessible through the web, automatic document classification (adc) has become an important research topic. adc usually employs a supervised learning strategy, where we first build a classification model using pre-classified documents and then use it to classify unseen documents. one major challenge in building classifiers is dealing with the temporal evolution of the characteristics of the documents and the classes to which they belong. however, most of the current techniques for adc do not consider this evolution while building and using the models. previous results show that the performance of classifiers may be affected by three different temporal effects (class distribution, term distribution and class similarity). further, it is shown that using just portions of the pre-classified documents, which we call contexts, for building the classifiers, result in better performance, as a consequence of the minimization of the aforementioned effects. in this paper we define the concept of temporal contexts as being the portions of documents that minimize those effects. we then propose a general algorithm for determining such contexts, discuss its implementation-related issues, and propose a heuristic that is able to determine temporal contexts efficiently. in order to demonstrate the effectiveness of our strategy, we evaluated it using two distinct collections: acm-dl and medline. we initially evaluated the reduction in terms of both the effort to build a classifier and the entropy associated with each context. further, we evaluated whether these observed reductions translate into better classification performance by employing a very simple classifier, majority voting. the results show that we achieved precision gains of up to 30% compared to a version that is not temporally contextualized, and the same accuracy of a state-of-the-art classifier (svm), while presenting an execution time up to hundreds of times faster.
exploiting context to detect sensitive information in call center conversations. protecting sensitive information while preserving the share-ability and usability of data is becoming increasingly important. in call-centers a lot of customer related sensitive information is stored in audio recordings. in this work, we address the problem of protecting sensitive information in audio recordings and speech transcripts. we present a semi-supervised method to model sensitive information as a directed graph. effectiveness of this approach is demonstrated by applying it to the problem of detecting and locating credit card transaction in real life conversations between agents and customers in a call center.
semi-supervised ranking aggregation. ranking aggregation is important in data mining and information retrieval. in this paper, we proposed a semi-supervised ranking aggregation method, in which the order of several item pairs are labeled as side information. the core idea is to learn a ranking function based on the ordering agreement of different rankers. the ranking scores assigned by this ranking function on the labeled data are consistent with the given pairwise order constraints while the ranking scores on the unlabeled data obey the intrinsic manifold structure of the rank items. the experiment results show our method work well.
a coarse-grain grid-based subspace clustering method for online multi-dimensional data streams. this paper proposes a subspace clustering algorithm which combines grid-based clustering with frequent itemset mining. given a d-dimensional data stream, the on-going distribution statistics of its data elements in every one-dimensional data space is monitored by a list of fine-grain grid-cells called a sibling list, so that all the one-dimensional clusters are accurately identified. by tracing a set of frequently co-occurred one-dimensional clusters, it is possible to find a coarse-grain dense rectangular space in a higher dimensional subspace. an st-tree is introduced to continuously monitor dense rectangular spaces in all the subspaces of the d dimensions. among the spaces, those ones whose densities are greater than or equal to a user defined minimum support threshold smin are corresponding to final clusters.
scalable complex pattern search in sequential data. searching data streams has been traditionally very limited, either in the complexity of the search or in the size of the searched dataset. in this paper, we investigate the design and optimization of constructs that enable sql to express complex patterns. in particular we propose the rsps (recursive sequential pattern search) algorithm which exploits the inter-dependencies between the elements of a sequential pattern to minimize repeated passes over the same data. performance gains derived experimental results show impressive speedup up to 100 times.
categorizing blogger's interests based on short snippets of blog posts. blogs have become an important medium for people to express opinions and share information on the web. predicting the interests of bloggers can be beneficial for information retrieval and knowledge discovery in the blogosphere. in this paper, we propose a two-layer classification model to categorize the interests of bloggers based on a set of short snippets collected from their blog posts. experiments were conducted on a list of bloggers collected from blog directories, with their snippets collected from google blog search. the results show that the proposed method is robust to errors in the lower level and achieve satisfactory performance in categorizing blogger's interests.
a framework for estimating complex probability density structures in data streams. probability density function estimation is a fundamental component in several stream mining tasks such as outlier detection and classification. the nonparametric adaptive kernel density estimate (akde) provides a robust and asymptotically consistent estimate for an arbitrary distribution. however, its extensive computational requirements make it difficult to apply this technique to the stream environment. this paper tackles the issue of developing efficient and asymptotically consistent akde over data streams while heeding the stringent constraints imposed by the stream environment. we propose the concept of local regions to effectively synopsize local density features, design a suite of algorithms to maintain the akde under a time-based sliding window, and analyze the estimates' asymptotic consistency and computational costs. in addition, extensive experiments were conducted with real-world and synthetic data sets to demonstrate the effectiveness and efficiency of our approach.
using the current browsing context to improve search relevance. in this paper, we investigate the problem of improving the relevance of a web search engine by adapting it to the dynamic needs of the user. we examine a representative case of sudden information need change, namely the exposure of the user to news data. in our earlier work we showed that the majority of queries submitted by users after browsing documents in the news domain are related to the most recently browsed document. we explore several methods of biasing the search by performing query expansion and re-ranking of the search results of a major search engine for queries identified as good candidates for contextualization. we show that these methods highly increase the similarity between the obtained top 10 search results and the most recently browsed document.
a novel email abstraction scheme for spam detection. prior studies on collaborative spam filtering with near-duplicate similarity matching scheme mainly represent each email by a succinct abstraction derived from email content text. since these abstractions of emails cannot fully catch the evolving nature of spams, we propose in this paper a novel email abstraction scheme, which considers email layout structure to represent emails. with the proposed abstraction, we design a near-duplicate matching scheme to efficiently match each incoming email with a huge spam database.
real-time data pre-processing technique for efficient feature extraction in large scale datasets. due to the continuous and rampant increase in the size of domain specific data sources, there is a real and sustained need for fast processing in time-sensitive applications, such as medical record information extraction at the point of care, genetic feature extraction for personalized treatment, as well as off-line knowledge discovery such as creating evidence based medicine. since parallel multi-string matching is at the core of most data mining tasks in these applications, faster on-line matching in static and streaming data is needed to improve the overall efficiency of such knowledge discovery. to solve this data mining need not efficiently handled by traditional information extraction and retrieval techniques, we propose a block suffix shifting-based approach, which is an improvement over the state of the art multi-string matching algorithms such as aho-corasick, commentz-walter, and wu-manber. the strength of our approach is its ability to exploit the different block structures of domain specific data for off-line and online parallel matching. experiments on several real world datasets show how our approach translates into significant performance improvements.
modeling document features for expert finding. we argue that expert finding is sensitive to multiple document features in an organization, and therefore, can benefit from the incorporation of these document features. we propose a unified language model, which integrates multiple document features, namely, multiple levels of associations, pagerank, indegree, internal document structure, and url length. our experiments on two trec enterprise track collections, i.e., the w3c and csiro datasets, demonstrate that the natures of the two organizational intranets and two types of expert finding tasks, i.e., key contact finding for csiro and knowledgeable person finding for w3c, influence the effectiveness of different document features. our work provides insights into which document features work for certain types of expert finding tasks, and helps design expert finding strategies that are effective for different scenarios.
data degradation: making private data less sensitive over time. trail disclosure is the leakage of privacy sensitive data, resulting from negligence, attack or abusive scrutinization or usage of personal digital trails. to prevent trail disclosure, data degradation is proposed as an alternative to the limited retention principle. data degradation is based on the assumption that long lasting purposes can often be satisfied with a less accurate, and therefore less sensi-tive, version of the data. data will be progressively degraded such that it still serves application purposes, while decreasing accuracy and thus privacy sensitivity.
the effect of contextualization at different granularity levels in content-oriented xml retrieval. in the hierarchical xml structure, the ancestors form the context of an xml element. the process of taking element's context into account in element scoring is called contextualization. the aim of this paper is to separate different granularity levels and test the effect of contextualization on these levels.
generalized inverse document frequency. inverse document frequency (idf) is one of the most useful and widely used concepts in information retrieval. there have been various attempts to provide theoretical justifications for idf. one of the most appealing derivations follows from the robertson-sparck jones relevance weight. however, this derivation, and others related to it, typically make a number of strong assumptions that are often glossed over. in this paper, we re-examine these assumptions from a bayesian perspective, discuss possible alternatives, and derive a new, more generalized form of idf that we call generalized inverse document frequency. in addition to providing theoretical insights into idf, we also undertake a rigorous empirical evaluation that shows generalized idf outperforms classical versions of idf on a number of ad hoc retrieval tasks.
comparing citation contexts for information retrieval. in previous work, we have shown that using terms from around citations in citing papers to index the cited paper, in addition to the cited paper's own terms, can improve retrieval effectiveness. now, we investigate how to select text from around the citations in order to extract good index terms. we compare the retrieval effectiveness that results from a range of contexts around the citations, including no context, the entire citing paper, some fixed windows and several variations with linguistic motivations. we conclude with an analysis of the benefits of more complex, linguistically motivated methods for extracting citation index terms, over using a fixed window of terms. we speculate that there might be some advantage to using computational linguistic techniques for this task.
searching the wikipedia with contextual information. we propose a framework for searching the wikipedia with contextual information. our framework extends the typical keyword search, by considering queries of the type (q,p), where q is a set of terms (as in classical web search), and p is a source wikipedia document. the query terms q represent the information that the user is interested in finding, and the document p provides the context of the query. the task is to rank other documents in wikipedia with respect to their relevance to the query terms q given the context document p. by associating a context to the query terms, the search results of a search initiated in a particular page can be made more relevant. we suggest a number of features that extend the classical query-search model so that the context document p is considered. we then use ranksvm (joachims 2002) to learn weights for the individual features given suitably constructed training data. documents are ranked at query time using the inner product of the feature and the weight vectors. the experiments indicate that the proposed method considerably improves results obtained by a more traditional approach that does not take the context into account.
predicting individual disease risk based on medical history. the monumental cost of health care, especially for chronic disease treatment, is quickly becoming unmanageable. this crisis has motivated the drive towards preventative medicine, where the primary concern is recognizing disease risk and taking action at the earliest signs. however, universal testing is neither time nor cost efficient. we propose care, a collaborative assessment and recommendation engine, which relies only on a patient's medical history using icd-9-cm codes in order to predict future diseases risks. care uses collaborative filtering to predict each patient's greatest disease risks based on their own medical history and that of similar patients. we also describe an iterative version, icare, which incorporates ensemble concepts for improved performance. these novel systems require no specialized information and provide predictions for medical conditions of all kinds in a single run. we present experimental results on a medicare dataset, demonstrating that care and icare perform well at capturing future disease risks.
summarization of social activity over time: people, actions and concepts in dynamic networks. we present a framework for automatically summarizing social group activity over time. the problem is important in understanding large scale online social networks, which have diverse social interactions and exhibit temporal dynamics. in this work we construct summarization by extracting activity themes. we propose a novel unified temporal multi-graph framework for extracting activity themes over time. we use non-negative matrix factorization (nmf) approach to derive two interrelated latent spaces for users and concepts. activity themes are extracted from the derived latent spaces to construct group activity summary. experiments on real-world flickr datasets demonstrate that our technique outperforms baseline algorithms such as lsi, and is additionally able to extract temporally representative activities to construct meaningful group activity summary.
learning a two-stage svm/crf sequence classifier. learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. for example, recognizing that a handwritten word is "cat", based on three images of handwritten letters and on general knowledge of english letter combinations, is a sequence classification task. this paper describes a new two-stage approach to learning a sequence classifier that is (i) highly accurate, (ii) scalable, and (iii) easy to use in data mining applications. the two-stage approach combines support vector machines (svms) and conditional random fields (crfs). it is (i) highly accurate because it benefits from the maximum-margin nature of svms and also from the ability of crfs to model correlations between neighboring output tags. it is (ii) scalable because the input to each svm is a small training set, and the input to the crf has a small number of features, namely the svm outputs. it is (iii) easy to use because it combines existing published software in a straightforward way. in detailed experiments on the task of recognizing handwritten words, we show that the two-stage approach is more accurate, or faster and more scalable, or both, than leading other methods for learning sequence classifiers, including max-margin markov networks (m3ns) and standard crfs.
estimating retrieval effectiveness using rank distributions. in this paper, we consider the task of estimating query effectiveness, i.e., assessment of the retrieval system performance in absence of the user relevance judgments. in our approach we model the score associated with each document in the result set as a gaussian random variable. the mean and the variance of each document score can then be used to estimate the probability that a document will be ranked above another one and thus calculate the expected rank of the document in the ranked list. we propose to measure the effectiveness of the system performance by comparing the predicted and actual ranks of the retrieved documents. in our experiments we consider two retrieval models and five document scoring methods and evaluate their impact on the proposed estimation measures. our experiments with standardized data sets that include document relevance judgments and the task of predicting the relative query effectiveness show that the expected rank metric is robust to variations in document scoring and retrieval algorithms.
improved query difficulty prediction for the web. query performance prediction aims to predict whether a query will have a high average precision given retrieval from a particular collection, or low average precision. an accurate estimator of the quality of search engine results can allow the search engine to decide to which queries to apply query expansion, for which queries to suggest alternative search terms, to adjust the sponsored results, or to return results from specialized collections. in this paper we present an evaluation of state of the art query prediction algorithms, both post-retrieval and pre-retrieval and we analyze their sensitivity towards the retrieval algorithm. we evaluate query difficulty predictors over three widely different collections and query sets and present an analysis of why prediction algorithms perform significantly worse on web data. finally we introduce improved clarity, and demonstrate that it outperforms state-of-the-art predictors on three standard collections, including two large web collections.
metadata extraction and indexing for map search in web documents. in academic scientific articles, maps are widely used to provide the related geographic information and to give readers a visual understanding of the document content. as more digital documents containing maps become accessible on the web, there is a growing demand for a web search system to provide users with tools to retrieve documents based on the information available within a document's maps. in this paper, we design methods and algorithms to extract, identify, and index maps from academic and scientific documents in digital libraries. experimental results show that our approach can accurately locate maps and significantly improve the retrieve quality for maps in digital documents.
identification of class specific discourse patterns. in this paper we address the problem of extracting important (and unimportant) discourse patterns from call center conversations. call centers provide dialog based calling-in support for customers to address their queries, requests and complaints. a call center is the direct interface between an organization and its customers and it is important to capture the voice-of-customer by gathering insights into the customer experience. we have observed that the calls received at a call center contain segments within them that follow specific patterns that are typical of the issue being addressed in the call. we present methods to extract such patterns from the calls. we show that by aggregating over a few hundred calls, specific discourse patterns begin to emerge for each class of calls. further, we show that such discourse patterns are useful for classifying calls and for identifying parts of the calls that provide insights into customer behaviour.
learning to link with wikipedia. this paper describes how to automatically cross-reference documents with wikipedia: the largest knowledge base ever known. it explains how machine learning can be used to identify significant terms within unstructured text, and enrich it with links to the appropriate wikipedia articles. the resulting link detector and disambiguator performs very well, with recall and precision of almost 75%. this performance is constant whether the system is evaluated on wikipedia articles or "real world" documents. this work has implications far beyond enriching documents with explanatory links. it can provide structured knowledge about any unstructured fragment of text. any task that is currently addressed with bags of words - indexing, clustering, retrieval, and summarization to name a few - could use the techniques described here to draw on a vast network of concepts and semantics.
identifying table boundaries in digital documents via sparse line detection. most prior work on information extraction has focused on extracting information from text in digital documents. however, often, the most important information being reported in an article is presented in tabular form in a digital document. if the data reported in tables can be extracted and stored in a database, the data can be queried and joined with other data using database management systems. in order to prepare the data source for table search, accurately detecting the table boundary plays a crucial role for the later table structure decomposition. table boundary detection and content extraction is a challenging problem because tabular formats are not standardized across all documents. in this paper, we propose a simple but effective preprocessing method to improve the table boundary detection performance by considering the sparse-line property of table rows. our method easily simplifies the table boundary detection problem into the sparse line analysis problem with much less noise. we design eight line label types and apply two machine learning techniques, conditional random field (crf) and support vector machines (svm), on the table boundary detection field. the experimental results not only compare the performances between the machine learning methods and the heuristics-based method, but also demonstrate the effectiveness of the sparse line analysis in the table boundary detection.
efficient processing of probabilistic spatio-temporal range queries over moving objects. range queries for querying the current and future positions of the moving objects have received growing interests in the research community. existing methods, however, assume that an object only moves along an anticipated path. in this paper, we study the problem of answering probabilistic range queries on moving objects based on an uncertainty model, which captures the possible movements of objects with probabilities. we conduct a performance study, which shows our proposal significantly reduces the number of object examinations and the overall cost of the query evaluation.
representative entry selection for profiling blogs. many applications on blog search and mining often meet the challenge of handling huge volume of blog data, in which one single blog could contain hundreds or even thousands of entries. we investigate novel techniques for profiling blogs by selecting a subset of representative entries for each blog. we propose two principles for guiding the entry selection task: representativeness and diversity. further, we formulate the entry selection task into a combinatorial optimization problem and propose a greedy yet effective algorithm for finding a good approximate solution by exploiting the theory of submodular functions. we suggest blog classification for judging the performance of the proposed entry selection techniques and evaluate their performance on a real blog dataset, in which encouraging results were obtained.
sorec: social recommendation using probabilistic matrix factorization. data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system confronts. many existing approaches to recommender systems can neither handle very large datasets nor easily deal with users who have made very few ratings or even none at all. moreover, traditional recommender systems assume that all the users are independent and identically distributed; this assumption ignores the social interactions or connections among users. in view of the exponential growth of information generated by online social networks, social network analysis is becoming important for many web applications. following the intuition that a person's social network will affect personal behaviors on the web, this paper proposes a factor analysis approach based on probabilistic matrix factorization to solve the data sparsity and poor prediction accuracy problems by employing both users' social network information and rating records. the complexity analysis indicates that our approach can be applied to very large datasets since it scales linearly with the number of observations, while the experimental results shows that our method performs much better than the state-of-the-art approaches, especially in the circumstance that users have made few or no ratings.
a step towards incremental maintenance of the composed schema mapping. schema mapping plays a fundamental role in modern information systems. mapping composition is an operator that combines a chain of successive schema mappings into a single schema mapping. by pre-computing the composed schema mapping, the system can achieve significant performance benefits. however, when a change occurs on any mapping in the chain, the composed schema mapping has to be maintained correspondingly. in this paper we consider a restricted form of the problem in the xml setting and propose an incremental maintenance approach. specifically, given a chain of successive mappings, we transform intermediately them into trees that consist of atomic rules and then divide the composition into sub-compositions of the atomic rules. the dividing composition approach provides a fine-grained perspective of the composition relationships between the mappings. we depict such information through an auxiliary data structure called composition relationship graph (crg). when changes occur on any mapping in the chain, the corresponding maintenance algorithms are developed based on the dividing approach and the crg, which compute the changes on the composed mapping and then repair it into the new version, such that the computation involves only the atomic rules that are relevant with the maintenance. we evaluate our maintenance approach and report the first experiments results, which show that it is efficient.
markov logic: a unifying language for knowledge and information management. modern information and knowledge management is characterized by high degrees of complexity and uncertainty. complexity is well handled by first-order logic, and uncertainty by probabilistic graphical models. what has been sorely missing is a seamless combination of the two. markov logic provides this by attaching weights to logical formulas and treating them as templates for features of markov random fields. this talks surveys markov logic representation, inference, learning and applications. inference algorithms combine ideas from satisfiability testing, resolution, markov chain monte carlo and belief propagation. learning algorithms involve statistical weight learning and inductive logic programming. markov logic has been successfully applied to a wide range of information and knowledge management problems, including information extraction, entity resolution, ontology learning, link prediction, heterogeneous knowledge bases, and others. it is the basis of the open-source alchemy system (http://alchemy.cs.washington.edu).
peer production of structured knowledge -: an empirical study of ratings and incentive mechanisms. creating and maintaining semantic structures such as ontologies on a large scale is a labor-intensive task, which a sole individual cannot perform. established automated solutions for this task do not yet exist. peer production is a promising approach to create structured knowledge: members of an online community create and maintain semantic structures collaboratively. to motivate members to participate and to ensure the quality of the data, rating-based incentive mechanisms are promising. members mutually rate the quality of their contributions and are rewarded for good contributions and truthful ratings. until now, there has been no systematic evaluation of such rating mechanisms in the context of structured knowledge. we have developed a platform for the collaborative creation of semantic structures. to evaluate the effect of ratings and incentive mechanisms on the quality of peer-produced data, we have conducted an extensive empirical study in an online community. we show that ratings are a reliable measure of the quality of contributions by comparing user ratings with an ex post evaluation by experts. further experimental results are that incentive mechanisms increase the quality of contributions. we conclude that ratings and incentive mechanisms are promising to foster and improve the peer production of structured knowledge.
how does clickthrough data reflect retrieval quality? automatically judging the quality of retrieval functions based on observable user behavior holds promise for making retrieval evaluation faster, cheaper, and more user centered. however, the relationship between observable user behavior and retrieval quality is not yet fully understood. we present a sequence of studies investigating this relationship for an operational search engine on the arxiv.org e-print archive. we find that none of the eight absolute usage metrics we explore (e.g., number of clicks, frequency of query reformulations, abandonment) reliably reflect retrieval quality for the sample sizes we consider. however, we find that paired experiment designs adapted from sensory analysis produce accurate and reliable statements about the relative quality of two retrieval functions. in particular, we investigate two paired comparison tests that analyze clickthrough data from an interleaved presentation of ranking pairs, and we find that both give accurate and consistent results. we conclude that both paired comparison tests give substantially more accurate and sensitive evaluation results than absolute usage metrics in our domain.
trada: tree based ranking function adaptation. machine learned ranking approaches have shown successes in web search engines. with the increasing demands on developing effective ranking functions for different search domains, we have seen a big bottleneck, i.e., the problem of insufficient training data, which has significantly limited the fast development and deployment of machine learned ranking functions for different web search domains. in this paper, we propose a new approach called tree based ranking function adaptation ("tree adaptation") to address this problem. tree adaptation assumes that ranking functions are trained with regression-tree based modeling methods, such as gradient boosting trees. it takes such a ranking function from one domain and tunes its tree-based structure with a small amount of training data from the target domain. the unique features include (1) it can automatically identify the part of model that needs adjustment for the new domain, (2) it can appropriately weight training examples considering both local and global distributions. experiments are performed to show that tree adaptation can provide better-quality ranking functions for a new domain, compared to other modeling methods.
modeling multi-step relevance propagation for expert finding. an expert finding system allows a user to type a simple text query and retrieve names and contact information of individuals that possess the expertise expressed in the query. this paper proposes a novel approach to expert finding in large enterprises or intranets by modeling candidate experts (persons), web documents and various relations among them with so-called expertise graphs. as distinct from the state of-the-art approaches estimating personal expertise through one-step propagation of relevance probability from documents to the related candidates, our methods are based on the principle of multi-step relevance propagation in topic specific expertise graphs. we model the process of expert finding by probabilistic random walks of three kinds: finite, infinite and absorbing. experiments on trec enterprise track data originating from two large organizations show that our methods using multi-step relevance propagation improve over the baseline one-step propagation based method in almost all cases.
identification of gene function using prediction by partial matching (ppm) language models. in this paper, we describe the utilization of text encoding and prediction by partial matching language modeling to identify gene functions within abstracts of biomedical papers. the national center for biotechnology information has "generif" - a collection of the best possible functional representations for a subset of abstracts from pubmed. we use generif to test the efficiency of our technique. we discuss the methodology adopted to construct models necessary to enable the text mining toolkit to distinguish between gene functions and the rest of the abstract (non gene functions). we also describe the similarity based approach we deploy on the list of automatically annotated functions to generate the most likely gene function representative of the paper. the results indicate that our combined approach to identify gene functions in scientific abstracts performs very well on both precision and recall, and therefore presents exciting opportunities for use in extracting other entities embedded in scientific text.
combining concept hierarchies and statistical topic models. statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. while topic models can potentially discover a broad range of themes in a data set, the interpretability of the learned topics is not always ideal. human-defined concepts, on the other hand, tend to be semantically richer due to careful selection of words to define concepts but they tend not to cover the themes in a data set exhaustively. in this paper, we propose a probabilistic framework to combine a hierarchy of human-defined semantic concepts with statistical topic models to seek the best of both worlds. experimental results using two different sources of concept hierarchies and two collections of text documents indicate that this combination leads to systematic improvements in the quality of the associated language models as well as enabling new techniques for inferring and visualizing the semantics of a document.
online spam-blog detection through blog search. in this work, we propose a novel post-indexing spam-blog (or splog) detection method, which capitalizes on the results returned by blog search engines. more specifically, we analyze the search results of a sequence of temporally-ordered queries returned by a blog search engine, and build and maintain blog profiles for those blogs whose posts frequently appear in the top-ranked search results. with the blog profiles, 4 splog scoring functions were evaluated using real data collected from a popular blog search engine. our experiments show that the proposed method could effectively detect splogs with a high accuracy.
achieving both high precision and high recall in near-duplicate detection. to find near-duplicate documents, fingerprint-based paradigms such as broder's shingling and charikar's simhash algorithms have been recognized as effective approaches and are considered the state-of-the-art. nevertheless, we see two aspects of these approaches which may be improved. first, high score under these algorithms' similarity measurement implies high probability of similarity between documents, which is different from high similarity of the documents. but how similar two documents are is what we really need to know. second, there has to be a tradeoff between hash-code length and hash-code multiplicity in fingerprint paradigms, which makes it hard to maintain a satisfactory recall level while improving precision. in this paper our contributions are two-folded. first, we propose a framework for implementing the longest common subsequence (lcs) as a similarity measurement in reasonable computing time, which leads to both high precision and recall. second, we present an algorithm to get a trustable partition from the lcs to reduce the negative impact from templates used in web page design. a comprehensive experiment was conducted to evaluate our method in terms of its effectiveness, efficiency, and quality of result. more specifically, the method has been successfully used to partition a set of 430 million web pages into 68 million subsets of similar pages, which demonstrates its effectiveness. for quality, we compared our method with simhash and a cosine-based method through a sampling process (cosine is compared to lcs as an alternative similarity measurement). the result showed that our algorithm reached an overall precision of 0.95 while simhash was 0.71 and cosine was 0.82. at the same time our method obtains 1.86 times as much recall as simhash and 1.56 times as much recall as cosine. comparison experiment was also done for documents in the same web sites. for that, our algorithm, simhash and cosine find almost the same number of true-positives at a precision of 0.91, 0.50 and 0.63 respectively. in terms of efficiency, our algorithm takes 118 hours to process the whole archive of 430 million topic-type pages on a cluster of six linux boxes, at the same time the processing time of simhash and cosine is 94 hours and 68 hours respectively. when considering the need of word segmentation for languages such as chinese, the processing time of cosine should be multiplied and in our experiment it is 602 hours.
some rewrite optimizations of db2 xquery navigation. ibm® db2® 9 is a truly hybrid commercial database system that combines xml and relational data. it provides native support for xml storage and indexing, and query evaluation support for xquery. by building a hybrid system, the designers of db2 9 were able to use the existing sql query evaluation and optimization techniques to develop similar methods for xquery. however, sql and xquery are sufficiently different that new optimization techniques can and are being developed in the new xquery domain. this paper describes a few such techniques, all based on static rewrites of xquery expressions.
a language for manipulating clustered web documents results. we propose a novel conception language for exploring the results retrieved by several internet search services (like search engines) that cluster retrieved documents. the goal is to offer users a tool to discover relevant hidden relationships between clustered documents. the proposal is motivated by the observation that visualization paradigms, based on either the ranked list or clustered results, do not allow users to fully exploit the combined use of several search services to answer a request. when the same query is submitted to distinct search services, they may produce partially overlapped clustered results, where clusters identified by distinct labels collect some common documents. moreover, clusters with similar labels, but containing distinct documents, may be produced as well. in such a situation, it may be useful to compare, combine and rank the cluster contents, to filter out relevant documents. in the proposed language, we define several operators (inspired by relational algebra) that work on groups of clusters. new clusters (and groups) can be generated by combining (i.e., overlapping, refining and intersecting) clusters (and groups), in a set oriented fashion. furthermore, several ranking functions are also proposed, to model distinct semantics of the combination.
ranking in folksonomy systems: can context help? folksonomy systems have shown to contribute to the quality of web search ranking strategies. in this paper, we analyze and compare different graph-based ranking algorithms, namely folkrank, socialpagerank, and socialsimrank. we enhance these algorithms by exploiting the context of tag assignmets, and evaluate the results on the groupme! dataset. in groupme!, users can organize and maintain arbitrary web resources in self-defined groups. when users annotate resources in groupme!, this can be interpreted in context of a certain group. the grouping activity delivers valuable semantic information about resources and their context. we show how to use this information to improve the detection of relevant search results, and compare different strategies for ranking result lists in folksonomy systems.
to swing or not to swing: learning when (not) to advertise. web textual advertising can be interpreted as a search problem over the corpus of ads available for display in a particular context. in contrast to conventional information retrieval systems, which always return results if the corpus contains any documents lexically related to the query, in web advertising it is acceptable, and occasionally even desirable, not to show any results. when no ads are relevant to the user's interests, then showing irrelevant ads should be avoided since they annoy the user and produce no economic benefit. in this paper we pose a decision problem "whether to swing", that is, whether or not to show any of the ads for the incoming request. we propose two methods for addressing this problem, a simple thresholding approach and a machine learning approach, which collectively analyzes the set of candidate ads augmented with external knowledge. our experimental evaluation, based on over 28,000 editorial judgments, shows that we are able to predict, with high accuracy, when to "swing" for both content match and sponsored search advertising.
statistical power in retrieval experimentation. the power of a statistical test specifies the sample size required to reliably detect a given true effect. in ir evaluation, the power corresponds to the number of topics that are likely to be sufficient to detect a certain degree of superiority of one system over another. to predict the power of a test, one must estimate the variability of the population being sampled from; here, of between-system score deltas. this paper demonstrates that basing such an estimation either on previous experience or on trial experiments leaves wide margins of error. iteratively adding more topics to the test set until power is achieved is more efficient; however, we show that it leads to a bias in favour of finding both power and significance. a hybrid methodology is proposed, and the reporting requirements of the experimenter using this methodology are laid out. we also demonstrate that greater statistical power is achieved for the same relevance assessment effort by evaluating a large number of topics shallowly than a small number deeply.
extremely fast text feature extraction for classification and indexing. most research in speeding up text mining involves algorithmic improvements to induction algorithms, and yet for many large scale applications, such as classifying or indexing large document repositories, the time spent extracting word features from texts can itself greatly exceed the initial training time. this paper describes a fast method for text feature extraction that folds together unicode conversion, forced lowercasing, word boundary detection, and string hash computation. we show empirically that our integer hash features result in classifiers with equivalent statistical performance to those built using string word features, but require far less computation and less memory.
modeling lsh for performance tuning. although locality-sensitive hashing (lsh) is a promising approach to similarity search in high-dimensional spaces, it has not been considered practical partly because its search quality is sensitive to several parameters that are quite data dependent. previous research on lsh, though obtained interesting asymptotic results, provides little guidance on how these parameters should be chosen, and tuning parameters for a given dataset remains a tedious process. to address this problem, we present a statistical performance model of multi-probe lsh, a state-of-the-art variance of lsh. our model can accurately predict the average search quality and latency given a small sample dataset. apart from automatic parameter tuning with the performance model, we also use the model to devise an adaptive lsh search algorithm to determine the probing parameter dynamically for each query. the adaptive probing method addresses the problem that even though the average performance is tuned for optimal, the variance of the performance is extremely high. we experimented with three different datasets including audio, images and 3d shapes to evaluate our methods. the results show the accuracy of the proposed model: the recall errors predicted are within 5% from the real values for most cases; the adaptive search method reduces the standard deviation of recall by about 50% over the existing method.
humane data mining. data mining has made tremendous strides in the last decade. it is time to take data mining to the next level of contributions, while continuing to innovate for the current mainstream market. we postulate that a fruitful future direction could be humane data mining: applications to benefit individuals. the potential applications include personal data mining (e.g. personal health), enable people to get a grip on their world (e.g. dealing with the long tail of search), enable people to become creative (e.g. inventions arising from linking non-interacting scientific literature), enable people to make contributions to society (e.g. education collaboration networks), and data-driven science (e.g. study ecological disasters, brain disorders). rooting our future work in these (and similar) applications, will lead to new data mining abstractions, algorithms, and systems.
a new method for indexing genomes using on-disk suffix trees. we propose a new method to build persistent suffix trees for indexing the genomic data. our algorithm digest (disk-based genomic suffix tree) improves significantly over previous work in reducing the random access to the input string and performing only two passes over disk data. digest is based on the two-phase multi-way merge sort paradigm using a concise binary representation of the dna alphabet. furthermore, our method scales to larger genomic data than managed before.
estimating the number of answers with guarantees for structured queries in p2p databases. structured p2p overlays supporting standard database functionalities are a popular choice for building large-scale distributed data management systems. in such systems, estimating the number of answers for structured queries can help approximating query completeness, but is especially challenging. in this paper, we propose to use routing graphs in order to achieve this. we introduce the general approach and briefly discuss further aspects like overhead and guarantees.
query optimization in xml-based information integration. the problem of decentralized data sharing is relevant for a wide range of applications and is still a source of major theoretical and practical challenges, in spite of many years of sustained research in information integration. we focus on the challenge of efficiency of query evaluation in information-integration systems, with the objective of developing query-processing strategies that are widely applicable and easy to implement in real-life applications. in our algorithms we take into account important features of today's data-sharing applications, namely: xml as likely interface to or representation for data sources; potential for information overlap across data sources; and the need for inter-source processing (i.e., joins of data across data sources) in many applications. to the best of our knowledge, our methods are the first to account for the practical issues of information overlap across data sources and of inter-source processing. while most of our algorithms are platform- and implementation-independent, we also propose xml-specific optimization techniques that allow for system-level tuning of query processing performance. finally, using real-life datasets and our implementation of an information-integration system shell, we provide experimental results that demonstrate that our algorithms are efficient and competitive in the information-integration setting. for all the details, please see [1].
an extension of plsa for document clustering. in this paper we propose an extension of the plsa model in which an extra latent variable allows the model to co-cluster documents and terms simultaneously. we show on three datasets that our extended model produces statistically significant improvements with respect to two clustering measures over the original plsa and the multinomial mixture mm models.
yizkor books: a voice for the silent past. yizkor book collections contain firsthand commemorative accounts of events from the era surrounding the rise and fall of nazi germany, including documents from before, during, and after the holocaust. prior to our effort, information regarding the content and location of each yizkor book volume was limited. we established a centralized index and metadata repository for the yizkor book collection and developed a detailed search interface accessible worldwide.
information shared by many objects. if kolmogorov complexity [25] measures information in one object and information distance measures information shared by two objects, how do we measure information shared by many objects? this paper provides an initial pragmatic study of this fundamental data mining question. firstly, em(x1,x2,...,xn) is defined to be the minimum amount of thermodynamic energy needed to convert from any xi to any xj. with this definition several theoretical problems have been solved. second, our newly proposed theory is applied to select a comprehensive review and a specialized review from many reviews: (1) core feature words, expanded words and dependent words are extracted respectively. (2) comprehensive and specialized reviews are selected according to the information among them. this method of selecting a single review can be extended to select multiple reviews as well. finally, experiments show that this comprehensive and specialized review mining method based on our new theory can do the job efficiently.
improve the effectiveness of the opinion retrieval and opinion polarity classification. opinion retrieval is a document retrieving and ranking process. a relevant document must be relevant to the query and contain opinions toward the query. opinion polarity classification is an extension of opinion retrieval. it classifies the retrieved document as positive, negative or mixed, according to the overall polarity of the query relevant opinions in the document. this paper (1) proposes several new techniques that help improve the effectiveness of an existing opinion retrieval system; (2) presents a novel two-stage model to solve the opinion polarity classification problem. in this model, every query relevant opinionated sentence in a document retrieved by our opinion retrieval system is classified as positive or negative respectively by a svm classifier. then a second classifier determines the overall opinion polarity of the document. experimental results show that both the opinion retrieval system with the proposed opinion retrieval techniques and the polarity classification model outperformed the best reported systems respectively.
nested region algebra extended with variables for tag-annotated text search. this paper presents a framework for searching text regions with specifying annotated information in tag-annotated text by using region algebra. we extend the efficient algorithm for region algebra to handle both nested and crossed regions and introduce variables for attribute values to treat tag-annotations in which attributes indicate another tag regions. our framework have been implemented in a text search engine for medline, which is a large textbase of abstracts in medical science. experiments in tag-annotated medline abstracts demonstrate the effectiveness of specifying annotations and the efficiency of our framework.
natural language retrieval of grocery products. in this paper we describe modifications to a natural language grocery retrieval system, introduced in our earlier work. we also compare our system against an off-the-shelf retrieval tool, and show that our system is significantly better for top-ranked retrieval results.
transaction reordering with application to synchronized scans. traditional workload management methods mainly focus on the current system status while information about the interaction between queued and running transactions is largely ignored. an exception to this is the transaction reordering method, which reorders the transaction sequence submitted to the rdbms and improves the transaction throughput by considering both the current system status and information about the interaction between queued and running transactions. the existing transaction reordering method only considers the reordering opportunities provided by analyzing the lock conflict information among multiple transactions. this significantly limits the applicability of the transaction reordering method. in this paper, we extend the existing transaction reordering method into a general transaction reordering framework that can incorporate various factors as the reordering criteria. we show that by analyzing the resource utilization information of transactions, the transaction reordering method can also improve the system throughput by increasing the resource sharing opportunities among multiple transactions. we provide a concrete example on synchronized scans and demonstrate the advantages of our method through experiments with a commercial parallel rdbms.
finding informative commonalities in concept collections. the problem of finding commonalities characterizes several knowledge management scenarios involving collection of resources. the automatic extraction of shared features in a collection of resource descriptions formalized in accordance with a logic language has been in fact widely investigated in the past. in particular, with reference to description logics concept descriptions, least common subsumers have been specifically introduced. nevertheless, such studies focused on identifying features shared by the whole collection. the paper proposes instead novel reasoning services in description logics, aimed at identifying commonalities in a significant portion of the collection, rather than in the collection as a whole. in particular, common subsumers adding informative content to the one provided by the least common subsumer are here investigated. the new services are useful in all scenarios where features are not required to be fully shared, like the one motivating our research: core competence extraction in knowledge intensive companies.
on low dimensional random projections and similarity search. random projection (rp) is a common technique for dimensionality reduction under l2 norm for which many significant space embedding results have been demonstrated. however, many similarity search applications often require very low dimension embeddings in order to reduce overhead and boost performance. inspired by the use of symmetric probability distributions in previous work, we propose a novel rp algorithm, beta random projection, and give its probabilistic analyses based on beta and gaussian approximations. we evaluate the algorithm in terms of standard similarity metrics with other rp algorithms as well as the singular value decomposition (svd). our experimental results show that brp preserves both similarity metrics well and, under various dataset types including random point sets, text (trec5) and images, provides sharper and consistent performance.
real-time new event detection for video streams. online detection of video clips that present previously unseen events in a video stream is still an open challenge to date. for this online new event detection (oned) task, existing studies mainly focus on optimizing the detection accuracy instead of the detection efficiency. as a result, it is difficult for existing systems to detect new events in real time, especially for large-scale video collections such as the video content available on the web. in this paper, we propose several scalable techniques to improve the video processing speed of a baseline oned system by orders of magnitude without sacrificing much detection accuracy. first, we use text features alone to filter out most of the non-new-event clips and to skip those expensive but unnecessary steps including image feature extraction and image similarity computation. second, we use a combination of indexing and compression methods to speed up text processing. we implemented a prototype of our optimized oned system on top of ibm's system s. the effectiveness of our techniques is evaluated on the standard trecvid 2005 benchmark, which demonstrates that our techniques can achieve a 480-fold speedup with detection accuracy degraded less than 5%.
characterization of tpc-h queries for a column-oriented database on a dual-core amd athlon processor. in this paper, we characterize the performance of the tpc-h benchmark for a popular column-oriented database called monetdb running on a dual-core amd athlon machine. specifically, we measure the performance of key microarchitectural components and analyze in detail the nature of various stalls namely cache stalls, branch misprediction stalls and resource stalls. we compare our results with published results on the characterization of tpc-h for row-oriented databases. as opposed to the previous approaches, we use thread-level monitoring of database threads to study the performance of the database in isolation from the rest of the system.
blog site search using resource selection. a blog site consists of many individual blog postings. current blog search services focus on retrieving postings but there is also a need to identify relevant blog sites. blog site search is similar to resource selection in distributed information retrieval, in that the target is to find relevant collections of documents. we introduce resource selection techniques for blog site search and evaluate their performance. further, we propose a "diversity factor" that measures the topic diversity of each blog site. our results show that the appropriate combination of the resource selection techniques and the diversity factor can achieve significant improvements in retrieval performance compared to baselines. we also report results using these techniques on the trec blog distillation task.
academic conference homepage understanding using constrained hierarchical conditional random fields. we address the problem of academic conference homepage understanding for the semantic web. this problem consists of three labeling tasks - labeling conference function pages, function blocks, and attributes. different from traditional information extraction tasks, the data in academic conference homepages has complex structural dependencies across multiple web pages. in addition, there are logical constraints in the data. in this paper, we propose a unified approach, constrained hierarchical conditional random fields, to accomplish the three labeling tasks simultaneously. in this approach, complex structural dependencies can be well described. also, the constrained viterbi algorithm in the inference process can avoid logical errors. experimental results on real world conference data have demonstrated that this approach performs better than cascaded labeling methods by 3.6% in f1-measure and that the constrained inference process can improve the accuracy by 14.3%. based on the proposed approach, we develop a prototype system of use-oriented semantic academic conference calendar. the user simply needs to specify what conferences he/she is interested in. subsequently, the system finds, extracts, and updates the semantic information from the web, and then builds a calendar automatically for the user. the semantic conference data can be used in other applications, such as finding sponsors and finding experts. the proposed approach can be used in other information extraction tasks as well.
are click-through data adequate for learning web search rankings? learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. a traditional way of generating training examples is to employ human experts to judge the relevance of documents. unfortunately, it is difficult, time-consuming and costly. in this paper, we study the problem of exploiting click-through data for learning web search rankings that can be collected at much lower cost. we extract pairwise relevance preferences from a large-scale aggregated click-through dataset, compare these preferences with explicit human judgments, and use them as training examples to learn ranking functions. we find click-through data are useful and effective in learning ranking functions. a straightforward use of aggregated click-through data can outperform human judgments. we demonstrate that the strategies are only slightly affected by fraudulent clicks. we also reveal that the pairs which are very reliable, e.g., the pairs consisting of documents with large click frequency differences, are not sufficient for learning.
collaborative partitioning with maximum user satisfaction. our collaborative partitioning model posits a bicriteria objective in which we seek the best item clustering that satisfies the most users at the highest level of satisfaction. we consider two basic methods for determining user satisfaction. the first method is based on how well each user's preferences match a given partition, and the second method is based on average correlation scores taken over sufficiently large subpopulations of users. we show these problems are np-hard and develop a set of heuristic approaches for solving them. we provide lower bounds on the satisfaction level on random data, and error bounds in the planted partition model, which provide confidence levels for our heuristic methods. finally, we present experiments on several real examples that demonstrate the effectiveness of our framework.
a two-stage text mining model for information filtering. mismatch and overload are the two fundamental issues regarding the effectiveness of information filtering. both term-based and pattern (phrase) based approaches have been employed to address these issues. however, they all suffer from some limitations with regard to effectiveness. this paper proposes a novel solution that includes two stages: an initial topic filtering stage followed by a stage involving pattern taxonomy mining. the objective of the first stage is to address mismatch by quickly filtering out probable irrelevant documents. the threshold used in the first stage is motivated theoretically. the objective of the second stage is to address overload by apply pattern mining techniques to rationalize the data relevance of the reduced document set after the first stage. substantial experiments on rcv1 show that the proposed solution achieves encouraging performance.
detecting significant distinguishing sets among bi-clusters. a fundamental task of data analysis is comprehending what distinguishes clusters found within the data. we present the problem of mining distinguishing sets; which seeks to find sets of objects or attributes that induce the most incremental change between adjacent bi-clusters of a binary dataset. viewing the lattice of bi-clusters formed within a data set as a weighted directed graph, we mine the most significant distinguishing sets by growing a maximal-cost spanning tree of the lattice.
supporting sub-document updates and queries in an inverted index. inverted indexes have become the standard indexing method for supporting search queries in a variety of content-based applications. examples of such applications include enterprise document management, e-mail, web search, and social networks. one shortcoming in current inverted index designs is that they support only document-level updates, forcing a full document to be reindexed even if just part of it changes. this paper describes a new inverted index design that enables applications to break a document into semantically meaningful sub-documents or "sections". each section of a document can be updated separately, but search queries can still work seamlessly across sections. our index design is motivated by applications where there is metadata associated with each document that tends to be smaller and more frequently updated than the document's content, but at the same time, it is desireable to search the metadata and content with the same index structure. a novel self-optimizing query execution algorithm is described to efficiently join the sections of a document in the inverted index. experimental results on trec and patent data are provided, showing that sections can dramatically improve overall system throughput on a mixed workload of updates and queries.
intra-document structural frequency features for semi-supervised domain adaptation. in this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access to large amounts of labeled data from other related, but distinct source domains, and seemingly no way to transfer knowledge from one to the other. experimentally, we focus on the problem of extracting protein mentions from academic publications in the field of biology, where the source domain data are abstracts labeled with protein mentions, and the target domain data are wholly unlabeled captions. we mine the large number of such full text articles freely available on the internet in order to supplement the limited amount of annotated data available. by exploiting the explicit and implicit common structure of the different subsections of these documents, including the unlabeled full text, we are able to generate robust features that are insensitive to changes in marginal and conditional distributions of classes and data across domains. we supplement these domain-insensitive features with automatically obtained high-confidence positive and negative predictions on the target domain to learn extractors that generalize well from one section of a document to another. finally, lacking labeled target testing data, we employ comparative user preference studies to evaluate the relative performance of the proposed methods with respect to existing baselines.
a novel optimization approach to efficiently process aggregate similarity queries in metric access methods. a similarity query considers an element as the query center and searches a dataset to find either the elements far up to a bounding radius or the k nearest ones from the query center. several algorithms have been developed to efficiently execute similarity queries. however, there are queries that require more than one center, which we call aggregate similarity queries. such queries appear when the user gives multiple desirable examples, and requests data elements that are similar to all of the examples, as in the case of applying relevance feedback. here we give the first algorithms that can handle aggregate similarity queries on metric access methods (mam) such as the m-tree and slim-tree. our method, which we call metric aggregate similarity search (mass) has the following properties: (a) it requires only the triangle inequality property; (b) it guarantees no false-dismissals, as we prove that it lower-bounds the aggregate distance scores; (c) it can work with any mam; (d) it can handle any number of query centers, which are either scattered all over the space or concentrated on a restricted region. experiments on both real and synthetic data show that our method scales on both the number of elements and, if the dataset is in a spatial domain, also on its dimensionality. moreover, it achieves better results than previous related methods.
answering general time sensitive queries. time is an important dimension of relevance for a large number of searches, such as over blogs and news archives. so far, research on searching over such collections has largely focused on locating topically similar documents for a query. unfortunately, topic similarity alone is not always sufficient for document ranking. in this paper, we observe that, for an important class of queries that we call time-sensitive queries, the publication time of the documents in a news archive is important and should be considered in conjunction with the topic similarity to derive the final document ranking. earlier work has focused on improving retrieval for "recency" queries that target recent documents. we propose a more general framework for handling time-sensitive queries and we automatically identify the important time intervals that are likely to be of interest for a query. then, we build scoring techniques that seamlessly integrate the temporal aspect into the overall ranking mechanism. we extensively evaluated our techniques using a variety of news article data sets, including trec data as well as real web data analyzed using the amazon mechanical turk. we examined several alternatives for detecting the important time intervals for a query over a news archive and for incorporating this information in the retrieval process. our techniques are robust and significantly improve result quality for time-sensitive queries compared to state-of-the-art retrieval techniques.
decomposition of terminology graphs for domain knowledge acquisition. we propose a graph decomposition algorithm for analyzing the structure of complex graph networks. after multi-word term extraction, we apply techniques from text mining and visual analytics in a novel way by integrating symbolic and numeric information to build clusters of domain topics. terms are clustered based on surface linguistic variations and clusters are inserted in an association network based on their intersection with documents. the graph is then decomposed based on atom graph structure into central (non-decomposable) atom and peripheral atoms. the whole process is applied to publications from the sloan digital sky survey (sdss) project in the astronomy field. the mapping obtained was evaluated by a domain expert and appeared to have captured interesting conceptual relations between different domain topics.
a consensus based approach to constrained clustering of software requirements. managing large-scale software projects involves a number of activities such as viewpoint extraction, feature detection, and requirements management, all of which require a human analyst to perform the arduous task of organizing requirements into meaningful topics and themes. automating these tasks through the use of data mining techniques such as clustering could potentially increase both the efficiency of performing the tasks and the reliability of the results. unfortunately, the unique characteristics of this domain, such as high dimensional, sparse, noisy data sets, resulting from short and ambiguous expressions of need, as well as the need for the interactive engagement of stakeholders at various stages of the process, present difficult challenges for standard clustering algorithms. in this paper, we propose a semi-supervised clustering framework, based on a combination of consensus-based and constrained clustering techniques, which can effectively handle these challenges. specifically, we provide a probabilistic analysis for informative constraint generation based on a co-association matrix, and utilize consensus clustering to combine multiple constrained partitions in order to generate high-quality, robust clusters. our approach is validated through a series of experiments on six well-studied trec data sets and on two sets of user requirements.
using sequence classification for filtering web pages. web pages often contain text that is irrelevant to their main content, such as advertisements, generic format elements, and references to other pages on the same site. when used by automatic content-processing systems, e.g., for web indexing, text classification, or information extraction, this irrelevant text often produces substantial amount of noise. this paper describes a trainable filtering system based on a feature-rich sequence classifier that removes irrelevant parts from pages, while keeping the content intact. most of the features the system uses are purely form-related: html tags and their positions, sizes of elements, etc. this keeps the system general and domain-independent. we also experiment with content words and show that while they perform very poorly alone, they can slightly improve the performance of pure-form features, without jeopardizing the domain-independence. our system achieves very high accuracy (95% and above) on several collections of web pages. we also do a series of tests with different features and different classifiers, comparing the contribution of different components to the system performance, and comparing two known sequence classifiers, robust risk minimization (rrm) and conditional random fields (crf), in a novel setting.
an effective statistical approach to blog post opinion retrieval. finding opinionated blog posts is still an open problem in information retrieval, as exemplified by the recent trec blog tracks. most of the current solutions involve the use of external resources and manual efforts in identifying subjective features. in this paper, we propose a novel and effective dictionary-based statistical approach, which automatically derives evidence for subjectivity from the blog collection itself, without requiring any manual effort. our experiments show that the proposed approach is capable of achieving remarkable and statistically significant improvements over robust baselines, including the best trec baseline run. in addition, with relatively little computational costs, our proposed approach provides an effective performance in retrieving opinionated blog posts, which is as good as a computationally expensive approach using natural language processing techniques.
proqid: partial restarts of queries in distributed databases. in a number of application areas, distributed database systems can be used to provide persistent storage of data while providing efficient access for both local and remote data. with an increasing number of sites (computers) involved in a query, the probability of failure at query time increases. recovery has previously only focused on database updates while query failures have been handled by complete restart of the query. this technique is not always applicable in the context of large queries and queries with deadlines. in this paper we present an approach for partial restart of queries that incurs minimal extra network traffic during query recovery. based on results from experiments on an implementation of the partial restart technique in a distributed database system, we demonstrate its applicability and significant reduction of query cost in the presence of failures.
fast correlation analysis on time series datasets. there has been increasing interest for efficient techniques for fast correlation analysis of time series data in different application domains. we present three algorithms for (1) bivariate correlation queries, (2) multivariate correlation queries, and (3) correlation queries based on a new correlation measure we introduce using dynamic time warping. to support these algorithms, we use a variant of the compact multi-resolution index (cmri). in addition to conventional nearest neighbor and range queries supported by cmri, the proposed algorithms compute all answers to user-defined, ad hoc and parametric correlation queries. the results of our experiments indicate a speed-up of two orders of magnitude over the brute force algorithm, and an order of magnitude improvement on average, while offering more functionalities than provided by existing techniques such as statstream and the spatial cone tree.
group-based learning: a boosting approach. this paper points out that many machine learning problems in ir should be and can be formalized in a novel way, referred to as 'group-based learning'. in group-based learning, it is assumed that training data as well as testing data consist of groups. the classifier is created and utilized across groups. furthermore, evaluation in testing and also in training are conducted at group level, with the use of evaluation measures defined on a group. this paper addresses the problem and presents a boosting algorithm to perform the new learning task. the algorithm, referred to as adaboost.group, is proved to be able to improve accuracies in terms of group-based measures during training.
a novel statistical chinese language model and its application in pinyin-to-character conversion. in this paper, we present a novel chinese language model, and study its applications, in particular in chinese pinyin-to-character conversion. in the new model, each word is associated with supporting context constructed by mining the frequent sets of nearby phrases and their distances to the word. such information was usually overlooked in previous n-gram model and its variants. we apply the model to chinese pinyin-to-character conversion and find that it offers a better solution to chinese input. the model has lower perplexity in our evaluation and higher prediction accuracy than the state-of-the-art n-gram markov model for chinese language.
sql extension for exploring multiple tables. the standard sql assumes that the users are aware of all tables and their schemas to write queries. this assumption may be valid when the users deal with a relatively small number of tables, but writing a sql query on a large number of tables is often challenging; (1) the users do not know what tables are relevant to their query, (2) it is too cumbersome to explicitly list tens of (or even hundreds of) relevant tables in the from clause and (3) the schemas of those tables are not identical. we now propose an intuitive yet powerful extension to sql that helps users explore and aggregate information spread over a large number of tables.
snif tool: sniffing for patterns in continuous streams. continuous time-series sequence matching, specifically, matching a numeric live stream against a set of redefined pattern sequences, is critical for domains ranging from fire spread tracking to network traffic monitoring. while several algorithms exist for similarity matching of static time-series data, matching continuous data poses new, largely unsolved challenges including online real-time processing requirements and system resource limitations for handling infinite streams. in this work, we propose a novel live stream matching framework, called n-snippet indices framework (in short, snif), to tackle these challenges. snif employs snippets as the basic unit for matching streaming time-series. the insight is to perform the matching at two levels of granularity: bag matching of subsets of snippets of the live stream against prefixes of the patterns, and order checking for maintaining successive candidate snippet bag matches. we design a two-level index structure, called snif index, which supports these two modes of matching. we propose a family of online two-level prefix matching algorithms that trade off between result accuracy and response time. the effectiveness of snif to detect patterns has been thoroughly tested through experiments using real datasets from the domains of fire monitoring and sensor motes. in this paper, we also present a study of snif's performance, accuracy and tolerance to noise compared against those of the state-of-the-art continuous query with prediction (cqp) approach.
using structured text for large-scale attribute extraction. we propose a weakly-supervised approach for extracting class attributes from structured text available within web documents. the overall precision of the extracted attributes is around 30% higher than with previous methods operating on web documents. in addition to attribute extraction, this approach also automatically identifies values for a subset of the extracted class attributes.
integrating web query results: holistic schema matching. the emergence of numerous data sources online has presented a pressing need for more automatic yet accurate data integration techniques. for the data returned from querying such sources, most works focus on how to extract the embedded structured data more accurately. however, to eventually provide an integrated access to these query results, a last but not least step is to combine the extracted data coming from different sources. a critical task is finding the correspondence of the data fields between the sources - a problem well known as schema matching. query results are a small and biased sample set of instances obtained from sources; the obtained schema information is thus very implicit and incomplete, which often prevents existing schema matching approaches from performing effectively. in this paper, we develop a novel framework for understanding and effectively supporting schema matching on such instance-based data, especially for integrating multiple sources. we view discovering matching as constructing a more complete domain schema that best describes the input data. with this conceptual view, we can leverage various data instances and observed regularities seamlessly with holistic, multiple-source schema matching to achieve more accurate matching results. our experiments show that our framework consistently outperforms baseline pairwise and clustering-based approaches (raising f-measure from 50-89% to 89-94%) and works uniformly well for the surveyed domains.
fast spatial co-location mining without cliqueness checking. in this paper, we propose a novel, spatial co-location mining algorithm which automatically generates co-located spatial features without generating any non-clique candidates at each level. subsequently our algorithm is more efficient than other existing level-wise co-location algorithms because no cliqueness checking is performed in our algorithm. in addition, our algorithm produces a smaller number of co-location candidates than the other existing algorithms.
handling implicit geographic evidence for geographic ir. most geographic information retrieval systems depend on the detection and disambiguation of place names in documents, assuming that the documents with a specific geographic scope contain explicit place names in the text that are strongly related to the document scopes. however, some non-geographic names such as companies, monuments or sport events, may also provide indirect relevant evidence that can significantly contribute to the assignment of geographic scopes to documents. in this paper, we analyze the amount of implicit and explicit geographic evidence in newspaper documents, and measure its impact on geographic information retrieval by evaluating the performance of a retrieval system using the geoclef evaluation data.
data weaving: scaling up the state-of-the-art in data clustering. the enormous amount and dimensionality of data processed by modern data mining tools require effective, scalable unsupervised learning techniques. unfortunately, the majority of previously proposed clustering algorithms are either effective or scalable. this paper is concerned with information-theoretic clustering (itc) that has historically been considered the state-of-the-art in clustering multi-dimensional data. most existing itc methods are computationally expensive and not easily scalable. those few itc methods that scale well (using, e.g., parallelization) are often outperformed by the others, of an inherently sequential nature. first, we justify this observation theoretically. we then propose data weaving - a novel method for parallelizing sequential clustering algorithms. data weaving is intrinsically multi-modal - it allows simultaneous clustering of a few types of data (modalities). finally, we use data weaving to parallelize multi-modal itc, which results in proposing a powerful dataloom algorithm. in our experimentation with small datasets, dataloom shows practically identical performance compared to expensive sequential alternatives. on large datasets, however, dataloom demonstrates significant gains over other parallel clustering methods. to illustrate the scalability, we simultaneously clustered rows and columns of a contingency table with over 120 billion entries.
link privacy in social networks. we consider a privacy threat to a social network in which the goal of an attacker is to obtain knowledge of a significant fraction of the links in the network. we formalize the typical social network interface and the information about links that it provides to its users in terms of lookahead. we consider a particular threat in which an attacker subverts user accounts to gain information about local neighborhoods in the network and pieces them together in order to build a global picture. we analyze, both experimentally and theoretically, the number of user accounts an attacker would need to subvert for a successful attack, as a function of his strategy for choosing users whose accounts to subvert and a function of the lookahead provided by the network. we conclude that such an attack is feasible in practice, and thus any social network that wishes to protect the link privacy of its users should take great care in choosing the lookahead of its interface, limiting it to 1 or 2, whenever possible.
mining term association patterns from search logs for effective query reformulation. search engine logs are an emerging new type of data that offers interesting opportunities for data mining. existing work on mining such data has mostly attempted to discover knowledge at the level of queries (e.g., query clusters). in this paper, we propose to mine search engine logs for patterns at the level of terms through analyzing the relations of terms inside a query. we define two novel term association patterns (i.e., context-sensitive term substitutions and term additions) and propose new methods for mining such patterns from search engine logs. these two patterns can be used to address the mis-specification and under-specification problems of ineffective queries. experiment results on real search engine logs show that the mined context-sensitive term substitutions can be used to effectively reword queries and improve their accuracy, while the mined context-sensitive term addition patterns can be used to support query refinement in a more effective way.
beyond the session timeout: automatic hierarchical segmentation of search topics in query logs. most analysis of web search relevance and performance takes a single query as the unit of search engine interaction. when studies attempt to group queries together by task or session, a timeout is typically used to identify the boundary. however, users query search engines in order to accomplish tasks at a variety of granularities, issuing multiple queries as they attempt to accomplish tasks. in this work we study real sessions manually labeled into hierarchical tasks, and show that timeouts, whatever their length, are of limited utility in identifying task boundaries, achieving a maximum precision of only 70%. we report on properties of this search task hierarchy, as seen in a random sample of user interactions from a major web search engine's log, annotated by human editors, learning that 17% of tasks are interleaved, and 20% are hierarchically organized. no previous work has analyzed or addressed automatic identification of interleaved and hierarchically organized search tasks. we propose and evaluate a method for the automated segmentation of users' query streams into hierarchical units. our classifiers can improve on timeout segmentation, as well as other previously published approaches, bringing the accuracy up to 92% for identifying fine-grained task boundaries, and 89-97% for identifying pairs of queries from the same task when tasks are interleaved hierarchically. this is the first work to identify, measure and automatically segment sequences of user queries into their hierarchical structure. the ability to perform this kind of segmentation paves the way for evaluating search engines in terms of user task completion.
in the development of a spanish metamap. metamap is an online application that allows mapping text to umls metathesaurus concepts, which is very useful interoperability among different languages and systems within the biomedical domain. metamap transfer (mmtx) is a java program that makes metamap available to biomedical researchers. currently there is no spanish version of metamap, which difficults the use of umls metathesaurus to extract concepts from spanish biomedical texts. our ongoing research is mainly focused on using biomedical concepts for cross-lingual text classification and retrieval [3]. in this context the use of concepts instead of bag of words representation allows us to face text classification tasks abstracting from the language [4]. in this paper we evaluate the possibility of combining automatic translation techniques with the use of biomedical ontologies to produce an english text that can be processed by mmtx.
semi-supervised metric learning by maximizing constraint margin. distance metric learning is an old problem that has been researched in the supervised learning field for a very long time. in this paper, we consider the problem of learning a proper distance metric under the guidance of some weak supervisory information. specifically, those information are in the form of pairwise constraints which specify whether a pair of data points are in the same class (must link constraints) or in the different classes (cannot link constraints). given those constraints, our algorithm aims to learn a distance metric under which the points with must link constraints are pushed as close as possible, while simultaneously the points with cannot link constraints are pulled away as far as possible. finally the experimental results are presented to show the effectiveness of our method.
coreex: content extraction from online news articles. we developed and tested a heuristic technique for extracting the main article from news site web pages. we construct the dom tree of the page and score every node based on the amount of text, the number of links it contains and additional heuristics. the method is site-independent and does not use any language-based features. we tested our algorithm on a set of 1120 news article pages from 27 domains. our algorithm achieved over 97% precision and 98% recall, and an average processing speed of under 15ms per page.
a system for finding biological entities that satisfy certain conditions from texts. finding biological entities (such as genes or proteins) that satisfy certain conditions from texts is an important and challenging task in biomedical information retrieval and text mining. it is essential for many biomedical applications, such as drug discovery which normally requires collecting existing scientific facts from documents. this paper presents an effective ir system for this task, in which 1) domain knowledge is incorporated to improve retrieval effectiveness; 2) query expansion with related concepts on multiple semantic levels is employed; 3) a gene symbol disambiguation technique is implemented. we evaluated these techniques and examined two different concept-based ir models. experiments based upon the proposed framework yield significant improvement (22% for automatic and 16.7% for non-automatic) over the best reported results of passage retrieval in the genomics track of trec 2007.
closing the loop in webpage understanding. the two most important tasks in information extraction from the web are webpage structure understanding and natural language sentences processing. however, little work has been done toward an integrated statistical model for understanding webpage structures and processing natural language sentences within the html elements. our recent work on webpage understanding introduces a joint model of hierarchical conditional random fields (hcrfs) and extended semi-markov conditional random fields (semi-crfs) to leverage the page structure understanding results in free text segmentation and labeling. in this top-down integration model, the decision of the hcrf model could guide the decision making of the semi-crf model. however, the drawback of the top-down integration strategy is also apparent, i.e., the decision of the semi-crf model could not be used by the hcrf model to guide its decision making. this paper proposed a novel framework called webnlp, which enables bidirectional integration of page structure understanding and text understanding in an iterative manner. we have applied the proposed framework to local business entity extraction and chinese person and organization name extraction. experiments show that the webnlp framework achieved significantly better performance than existing methods.
comparing metrics across trec and ntcir: the robustness to system bias. test collections are growing larger, and relevance data constructed through pooling are suspected of becoming more and more incomplete and biased. several studies have used evaluation metrics specifically designed to handle this problem, but most of them have only examined the metrics under incomplete but unbiased conditions, using random samples of the original relevance data. this paper examines nine metrics in a more realistic setting, by reducing the number of pooled systems. even though previous work has shown that metrics based on a condensed list, obtained by removing all unjudged documents from the original ranked list, are effective for handling very incomplete but unbiased relevance data, we show that these results do not hold in the presence of system bias. in our experiments using trec and ntcir data, we first show that condensed-list metrics overestimate new systems while traditional metrics underestimate them, and that the overestimation tends to be larger than the underestimation. we then show that, when relevance data is heavily biased towards a single team or a few teams, the condensed-list versions of average precision (ap), q-measure (q) and normalised discounted cumulative gain (ndcg), which we call ap', q' and ndcg', are not necessarily superior to the original metrics in terms of discriminative power, i.e., the overall ability to detect pairwise statistical significance. nevertheless, even under system bias, ap' and q' are generally more discriminative than bpref and the condensed-list version of rank-biased precision (rbp), which we call rbp'.
a densitometric approach to web page segmentation. web page segmentation is a crucial step for many applications in information retrieval, such as text classification, de-duplication and full-text search. in this paper we describe a new approach to segment html pages, building on methods from quantitative linguistics and strategies borrowed from the area of computer vision. we utilize the notion of text-density as a measure to identify the individual text segments of a web page, reducing the problem to solving a 1d-partitioning task. the distribution of segment-level text density seems to follow a negative hypergeometric distribution, described by frumkina's law. our extensive evaluation confirms the validity and quality of our approach and its applicability to the web.
a georeferencing multistage method for locating geographic context in web search. the geographic scope of web pages is becoming an essential dimension of web search, especially for mobile users. this paper shows a multistage method for assigning a geographic focus to web pages (georeferencing) according to their text contents. we suggest several heuristics for the disambiguation toponyms and a scoring procedure for focus determination. furthermore, we provide an experimental methodology for evaluating the accuracy. finally, we obtained promising results of over 70% accuracy with a city-level resolution.
transfer learning from multiple source domains via consensus regularization. recent years have witnessed an increased interest in transfer learning. despite the vast amount of research performed in this field, there are remaining challenges in applying the knowledge learnt from multiple source domains to a target domain. first, data from multiple source domains can be semantically related, but have different distributions. it is not clear how to exploit the distribution differences among multiple source domains to boost the learning performance in a target domain. second, many real-world applications demand this transfer learning to be performed in a distributed manner. to meet these challenges, we propose a consensus regularization framework for transfer learning from multiple source domains to a target domain. in this framework, a local classifier is trained by considering both local data available in a source domain and the prediction consensus with the classifiers from other source domains. in addition, the training algorithm can be implemented in a distributed manner, in which all the source-domains are treated as slave nodes and the target domain is used as the master node. to combine the training results from multiple source domains, it only needs share some statistical data rather than the full contents of their labeled data. this can modestly relieve the privacy concerns and avoid the need to upload all data to a central location. finally, our experimental results show the effectiveness of our consensus regularization learning.
speed up semantic search in p2p networks. peer-to-peer architectures become popular in modern massively distributed systems, which are often in very large scale and contain a huge volume of heterogeneous data. to facilitate the information retrieval process in p2p networks, we consider semantic search approach, where syntax-based queries are shipped to peers based on semantic correlations. motivated by an interesting experience in web information retrieval, we propose a novel ontology-based scheme to measure similarity of peer interests accurately and consistently in a decentralized way, and group peers under a scalable hierarchical overlay network. given queries, our approach either floods them within local peer groups or guides them towards remote groups based on the similarity of interests. our work overcomes the limitations of the existing p2p hybrid-search approaches by avoiding costly data popularity measurement. performance evaluation and comparison against baseline algorithms show that our approach provides a better solution for information retrieval in large-scale p2p networks.
pattern-based semantic class discovery with multi-membership support. a semantic class is a collection of items (words or phrases) sharing common semantic properties. this paper proposes an approach to constructing one or multiple semantic classes for an input item. two challenges are addressed: multi-membership, and noise-tolerance.
redus: finding reducible subspaces in high dimensional data. finding latent patterns in high dimensional data is an important research problem with numerous applications. the most well known approaches for high dimensional data analysis are feature selection and dimensionality reduction. being widely used in many applications, these methods aim to capture global patterns and are typically performed in the full feature space. in many emerging applications, however, scientists are interested in the local latent patterns held by feature subspaces, which may be invisible via any global transformation. in this paper, we investigate the problem of finding strong linear and nonlinear correlations hidden in feature subspaces of high dimensional data. we formalize this problem as identifying reducible subspaces in the full dimensional space. intuitively, a reducible subspace is a feature subspace whose intrinsic dimensionality is smaller than the number of features. we present an effective algorithm, redus, for finding the reducible subspaces. two key components of our algorithm are finding the overall reducible subspace, and uncovering the individual reducible subspaces from the overall reducible subspace. a broad experimental evaluation demonstrates the effectiveness of our algorithm.
ghost: an effective graph-based framework for name distinction. name ambiguity stems from the fact that many people or objects share identical names. in this paper, we focus on investigating the problem in digital libraries to distinguish publications written by authors with identical names. we present an effective graph-based framework, ghost (abbr. graph-based framework for name distinction), to solve the problem systematically. we evaluated the framework on the real dblp dataset, and the experimental results show that ghost outperforms the state-of-the-art method.
multi-aspect expertise matching for review assignment. review assignment is a common task that many people such as conference organizers, journal editors, and grant administrators would have to do routinely. as a computational problem, it involves matching a set of candidate reviewers with a paper or proposal to be reviewed. a common deficiency of all existing work on solving this problem is that they do not consider the multiple aspects of topics or expertise and all match the entire document to be reviewed with the overall expertise of a reviewer. as a result, if a document contains multiple subtopics, which often happens, existing methods would not attempt to assign reviewers to cover all the subtopics; instead, it is quite possible that all the assigned reviewers would cover the major subtopic quite well, but not covering any other subtopic. in this paper, we study how to model multiple aspects of expertise and assign reviewers so that they together can cover all subtopics in the document well. we propose three general strategies for solving this problem and propose new evaluation measures for this task. we also create a multi-aspect review assignment test set using acm sigir publications. experiment results on this data set show that the proposed methods are effective for assigning reviewers to cover all topical aspects of a document.
overlapping community structure detection in networks. many systems in nature and human society take the form of networks with community structures. in this paper, we describe a simple algorithm cocd(clique-based overlapping community detection) to efficiently mine the overlapping communities in large-scale networks, which is useful for us to have a better understanding of the nested sub-structures embedded in the whole network.
e-discovery. it is common practice in the u.s. for courts to require that the parties to a legal case make available to one another all material relevant to the case, including electronically held data and documents. for large corporations, such relevant information may encompass terabytes of e-mail and other files spanning many years. the challenge of e-discovery in response to a court order is (in a relatively short amount of time) to identify, assemble, individuate, access, categorize, and analyze an organization's electronically held material, segregate all "privileged" material (which can be legally withheld), and present to the court all (and only) the required documents. the techniques needed to accomplish such a task necessarily include search, clustering, classification, filtering, social network analysis, extraction, and more - and no one of these is sufficient. the panel will describe this problem in detail, providing additional background and context on e-discovery generally, and will explore specific techniques and cases that amply demonstrate why e-discovery is quintessentially a "cikm" problem -- multi-disciplinary, multi-technology, and "multi-difficult".
large maximal cliques enumeration in sparse graphs. here we study a variant of maximal clique enumeration problem by incorporating a minimum size criterion. we describe preprocessing techniques to reduce the graph size. this is of practical interest since enumerating maximal cliques is a computationally hard problem and the execution time increases rapidly with the input size. we discuss basics of an algorithm for enumerating large maximal cliques which exploits the constraint on minimum size of the desired maximal cliques. social networks are prime examples of large sparse graphs where enumerating large maximal cliques is of interest. we present experimental results on the social network formed by the call detail records of one of the world's largest telecom service providers. our results show that the preprocessing methods achieve significant reduction in the graph size. we also characterize the execution behaviour of our large maximal clique enumeration algorithm.
proactive learning: cost-sensitive active learning with multiple imperfect oracles. proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications. active learning seeks to select the most informative unlabeled instances and ask an omniscient oracle for their labels, so as to retrain the learning algorithm maximizing accuracy. however, the oracle is assumed to be infallible (never wrong), indefatigable (always answers), individual (only one oracle), and insensitive to costs (always free or always charges the same). proactive learning relaxes all four of these assumptions, relying on a decision-theoretic approach to jointly select the optimal oracle and instance, by casting the problem as a utility optimization problem subject to a budget constraint. results on multi-oracle optimization over several data sets demonstrate the superiority of our approach over the single-imperfect-oracle baselines in most cases.
dual encryption for query integrity assurance. in database outsourcing, an enterprise contracts its database management tasks to an outside database service provider to eliminate in-house hardware, software, and expertise needs for running dbmss. this is attractive especially for the parties with limited abilities in managing their own data. typically, the client applications want to obtain quality assurance (e.g., data authenticity and query completeness) of the outsourced database service at a low cost. previous work on database outsourcing has focused on issues such as communication overhead, secure data access, and data privacy. recent work has introduced the issue of query integrity assurance, but usually, to obtain such assurance incurs a high cost. in this paper, we present a new method called dual encryption to provide low-cost query integrity assurance for outsourced database services. dual encryption enables "cross examination" of the outsourced data, which consists of the original data stored under a certain encryption scheme, and another small percentage of the original data stored under a different encryption scheme. we generate queries against the additional piece of data and analyze their results to obtain integrity assurance. our scheme is provable secure, that is, it is impossible to break our scheme unless some security primitives can be broken. experiments on commercial workloads show the effectiveness of our approach.
search advertising using web relevance feedback. the business of web search, a $10 billion industry, relies heavily on sponsored search, whereas a few carefully-selected paid advertisements are displayed alongside algorithmic search results. a key technical challenge in sponsored search is to select ads that are relevant for the user's query. identifying relevant ads is challenging because queries are usually very short, and because users, consciously or not, choose terms intended to lead to optimal web search results and not to optimal ads. furthermore, the ads themselves are short and usually formulated to capture the reader's attention rather than to facilitate query matching. traditionally, matching of ads to queries employed standard information retrieval techniques using the bag of words approach. here we propose to go beyond the bag of words, and augment both queries and ads with additional knowledge-rich features. we use web search results initially returned for the query to create a pool of relevant documents. classifying these documents with respect to an external taxonomy and identifying salient named entities give rise to two new feature types. empirical evaluation based on over 9,000 query-ad pairwise judgments confirms that using augmented queries produces highly relevant ads. our methodology also relaxes the requirement for each ad to explicitly specify the exhaustive list of queries ("bid phrases") that can trigger it.
fast mining of complex time-stamped events. given a collection of complex, time-stamped events, how do we find patterns and anomalies? events could be meetings with one or more persons and one or more agenda items at zero or more locations (e.g., teleconferences), or they could be publications with authors, keywords, publishers, etc. in such settings, we want to find time stamps that look similar to each other and group them; we also want to find anomalies. in addition, we want our approach to provide interpretations of the clusters and anomalies by annotating them. furthermore, we want our approach to automatically find the right time-granularity in which to do analysis. lastly, we want fast, scalable algorithms for all these problems. we address the above challenges through two main ideas. the first (t3) is to turn the problem into a graph analysis problem, by carefully treating each time stamp as a node in a graph. this viewpoint brings to bear the vast machinery of graph analysis methods (pagerank, graph partitioning, proximity analysis, and centerpiece subgraphs, to name a few). thus, t3 can automatically group the time stamps into meaningful clusters and spot anomalies. moreover, it can select representative events/persons/locations for each cluster and each anomaly, as their interpretations. the second idea (mt3) is to use temporal multi-resolution analysis (e.g., minutes, hours, days). we show that mt3 can quickly derive results from finer-to-coarser resolutions, achieving up to 2 orders of magnitude speedups. we verify the effectiveness as well as efficiency of t3 and mt3 on several real datasets.
records retention in relational database systems. the recent introduction of several pieces of legislation mandating minimum and maximum retention periods for corporate records has prompted the enterprise content management (ecm) community to develop various records retention solutions. records retention is a significant subfield of records management, and legal records retention requirements apply over corporate records regardless of their shape or form. unfortunately, the scope of existing solutions has been largely limited to proper identification, classification and retention of documents, and not of data more generally. in this paper we address the problem of managed records retention in the context of relational database systems. the problem is significantly more challenging than it is for documents for several reasons. foremost, there is no clear definition of what constitutes a business record in relational databases; it could be an entire table, a tuple, part of a tuple, or parts of several tuples from multiple tables. there are also no standardized mechanisms for purging, anonymizing and protecting relational records. functional dependencies, user defined constraints, and side effects caused by triggers make it even harder to guarantee that any given record will actually be protected when it needs to be protected or expunged when the necessary conditions are met. most importantly, relational tuples may be organized such that one piece of data may be part of various legal records and subject to several (possibly conflicting) retention policies. we address the above problems and present a complete solution for designing, managing, and enforcing records retention policies in relational database systems. we experimentally demonstrate that the proposed framework can guarantee compliance with a broad range of retention policies on an off-the-shelf system without incurring a significant performance overhead for policy monitoring and enforcement.
inferring semantic query relations from collective user behavior. in this paper we describe how high quality transaction data comprising of online searching, product viewing, and product buying activity of a large online community can be used to infer semantic relationships between queries. we work with a large scale query log consisting of around 115 million queries from ebay. we discuss various techniques to infer semantic relationships among queries and show how the results from these methods can be combined to measure the strength and depict the kinds of relationships. further, we show how this extraction of relations can be used to improve search relevance, related query recommendations, and recovery from null results in an ecommerce context.
effective pattern taxonomy mining in text documents. many data mining techniques have been proposed for mining useful patterns in databases. however, how to effectively utilize discovered patterns is still an open research issue, especially in the domain of text mining. most existing methods adopt term-based approaches. however, they all suffer from the problems of polysemy and synonymy. this paper presents an innovative technique, pattern taxonomy mining, to improve the effectiveness of using discovered patterns for finding useful information. substantial experiments on rcv1 demonstrate that the proposed solution achieves encouraging performance.
mining social networks using heat diffusion processes for marketing candidates selection. social network marketing techniques employ pre-existing social networks to increase brands or products awareness through word-of-mouth promotion. full understanding of social network marketing and the potential candidates that can thus be marketed to certainly offer lucrative opportunities for prospective sellers. due to the complexity of social networks, few models exist to interpret social network marketing realistically. we propose to model social network marketing using heat diffusion processes. this paper presents three diffusion models, along with three algorithms for selecting the best individuals to receive marketing samples. these approaches have the following advantages to best illustrate the properties of real-world social networks: (1) we can plan a marketing strategy sequentially in time since we include a time factor in the simulation of product adoptions; (2) the algorithm of selecting marketing candidates best represents and utilizes the clustering property of real-world social networks; and (3) the model we construct can diffuse both positive and negative comments on products or brands in order to simulate the complicated communications within social networks. our work represents a novel approach to the analysis of social network marketing, and is the first work to propose how to defend against negative comments within social networks. complexity analysis shows our model is also scalable to very large social networks.
structure feature selection for graph classification. with the development of highly efficient graph data collection technology in many application fields, classification of graph data emerges as an important topic in the data mining and machine learning community. towards building highly accurate classification models for graph data, here we present an efficient graph feature selection method. in our method, we use frequent subgraphs as features for graph classification. different from existing methods, we consider the spatial distribution of the subgraph features in the graph data and select those ones that have consistent spatial location. we have applied our feature selection methods to several cheminformatics benchmarks. our method demonstrates a significant improvement of prediction as compared to the state-of-the-art methods.
corpus microsurgery: criteria optimization for medical cross-language ir. automatic subset selection from a parallel corpus significantly cross-lingual information retrieval (clir) performance, in addition to increasing its efficiency. our selection method extracts relevant training data by incorporating additional criteria (i.e. estimated corpus quality, taxonomy projection and size) in addition to lexical-based criteria. the challenge lies in combining these criteria using a meaningful scoring function that can be used for ranking parallel sentence candidates. we choose weighted geometric mean for its soft-and properties, and we optimize criteria weights by wrapping the clir task in an optimization shell. due to the indeterminate nature of the search space convexity properties, we have explored continuous reactive tabu search (crts), a global optimization method. we use a large parallel corpus in the medical domain to examine the effect of adaptation criteria and their combination on clir performance. in our experiments, 100 selected sentences yield 90% of the performance obtained with 5,000 times more in-domain parallel sentences. our optimized criteria weights considerably outperform the uniform distribution baseline, as well as lexical similarity adaptation.
clustered subset selection and its applications on it service metrics. motivated by the enormous amounts of data collected in a large it service provider organization, this paper presents a method for quickly and automatically summarizing and extracting meaningful insights from the data. termed clustered subset selection (css), our method enables program-guided data explorations of high-dimensional data matrices. css combines clustering and subset selection into a coherent and intuitive method for data analysis. in addition to a general framework, we introduce a family of css algorithms with different clustering components such as k-means and close-to-rank-one (cro) clustering, and subset selection components such as best rank-one approximation and rank-revealing qr (rrqr) decomposition. from an empirical perspective, we illustrate that css is achieving significant improvements over existing subset selection methods in terms of approximation errors. compared to existing subset selection techniques, css is also able to provide additional insight about clusters and cluster representatives. finally, we present a case-study of program-guided data explorations using css on a large amount of it service delivery data collection.
error-driven generalist+experts (edge): a multi-stage ensemble framework for text categorization. we introduce a multi-stage ensemble framework, error-driven generalist+expert or edge, for improved classification on large-scale text categorization problems. edge first trains a generalist, capable of classifying under all classes, to deliver a reasonably accurate initial category ranking given an instance. edge then computes a confusion graph for the generalist and allocates the learning resources to train experts on relatively small groups of classes that tend to be systematically confused with one another by the generalist. the experts' votes, when invoked on a given instance, yield a reranking of the classes, thereby correcting the errors of the generalist. our evaluations showcase the improved classification and ranking performance on several large-scale text categorization datasets. edge is in particular efficient when the underlying learners are efficient. our study of confusion graphs is also of independent interest.
an integration strategy for mining product features and opinions. with the development of web 2.0, the web has become an extremely valuable source for mining opinions. in this paper, we study how to automatically mine product features and opinions by integrating multiple review sources. we propose an integration strategy to solve the problem. experiments show that the proposed strategy is effective.
characterizing and predicting community members from evolutionary and heterogeneous networks. mining different types of communities from web data have attracted a lot of research efforts in recent years. however, none of the existing community mining techniques has taken into account both the dynamic as well as heterogeneous nature of web data. in this paper, we propose to characterize and predict community members from the evolution of heterogeneous web data. we first propose a general framework for analyzing the evolution of heterogeneous networks. then, the academic network, which is extracted from 1 million computer science papers, is used as an example to illustrate the framework. finally, two example applications of the academic network are presented. experimental results with a real and very large heterogeneous academic network show that our proposed framework can produce good results in terms of community member recommendation. also, novel knowledge and insights can be gained by analyzing the community evolution pattern.
spam characterization and detection in peer-to-peer file-sharing systems. spam is highly pervasive in p2p file-sharing systems and is difficult to detect automatically before actually downloading a file due to the insufficient and biased description of a file returned to a client as a query result. to alleviate this problem, we first characterize spam and spammers in the p2p file-sharing environment and then describe feature-based techniques for automatically detecting spam in p2p query result sets. experimental results show that the proposed techniques successfully decrease the amount of spam by 9% in the top-200 results and by 92% in the top-20 results.
mining influential attributes that capture class and group contrast behaviour. contrast data mining is a key tool for finding differences between sets of objects, or classes, and contrast patterns are a popular method for discrimination between two classes. however, such patterns can be limited in two primary ways: i) they do not readily allow second order differentiation - i.e. discovering contrasts of contrasts, ii) mining contrast patterns often results in an overwhelming volume of output for the user. to address these limitations, this paper proposes a method which can identify contrast behaviour across both classes and also groups of classes. furthermore, to increase interpretability for the user, it presents a new technique for finding the attributes which represent the key underlying factors behind the contrast behaviour. the associated mining task is computationally challenging and we describe an efficient algorithm to handle it, based on binary decision diagrams. experimental results demonstrate that our technique can efficiently identify and explain contrast behaviour which would be difficult or impossible to isolate using standard techniques.
semi-supervised text categorization by active search. in automated text categorization, given a small number of labeled documents, it is very challenging, if not impossible, to build a reliable classifier that is able to achieve high classification accuracy. to address this problem, a novel web-assisted text categorization framework is proposed in this paper. important keywords are first automatically identified from the available labeled documents to form the queries. search engines are then utilized to retrieve from the web a multitude of relevant documents, which are then exploited by a semi-supervised framework. to our best knowledge, this work is the first study of this kind. extensive experimental study shows the encouraging results of the proposed text categorization framework: using google as the web search engine, the proposed framework is able to reduce the classification error by 30% when compared with the state-of-the-art supervised text categorization method.
multi-scale characterization of social network dynamics in the blogosphere. we have developed a computational framework to characterize social network dynamics in the blogosphere at individual, group and community levels. such characterization could be used by corporations to help drive targeted advertising and to track the moods and sentiments of consumers. we tested our model on a widely read technology blog called engadget. our results show that communities transit between states of high and low entropy, depending on sentiments (positive / negative) about external happenings. we also propose an innovative method to establish the utility of the extracted knowledge, by correlating the mined knowledge with an external time series data (the stock market). our validation results show that the characterized groups exhibit high stock market movement predictability (89%) and removal of 'impactful' groups makes the community less resilient by lowering predictability (26%) and affecting the composition of the groups in the rest of the community.
adasum: an adaptive model for summarization. topic representation mismatch is a key problem in topic-oriented summarization for the specified topic is usually too short to understand/interpret. this paper proposes a novel adaptive model for summarization, adasum, under the assumption that the summary and the topic representation can be mutually boosted. adasum aims to simultaneously optimize the topic representation and extract effective summaries. this model employs a mutual boosting process to minimize the topic representation mismatch for base summarizers. furthermore, a linear combination of base summarizers is proposed to further reduce the topic representation mismatch from the diversity of base summarizers with a general learning framework. we prove that the training process of adasum can enhance the performance measure used. experimental results on duc 2007 dataset show that adasum significantly outperforms the baseline methods for summarization (e.g. mrp, lexrank, and gsps).
using a graph-based ontological user profile for personalizing search. in this poster, we describe a personalized search approach, which involves a graph based user profile issued from ontology and a session boundary recognition mechanism. the user profile refers to the short term user interest and is used for re-ranking the search results of queries in the same search session. the session boundary recognition is based on tracking changes in the dominant concepts held by the query and the user profile. experimental evaluation was carried out using the hard 2003 trec collection and shows that our approach is effective.
investigating external corpus and clickthrough statistics for query expansion in the legal domain. we apply language modeling keyword search augmented with berger and lafferty's (1999) translation model for query expansion to formulate three query expansion methods using word co-occurrence statistics from a large external corpus and user clickthrough data. we study the performance of these methods on a vertical domain (case law documents) using standard metrics and an evaluation framework designed specifically to measure the performance of query expansion under varying degrees of query-document term mismatch.
content-based filtering for efficient online materialized view maintenance. real-time materialized view maintenance has become increasingly popular, especially in real-time data warehousing and data streaming environments. upon updates to base relations, maintaining the corresponding materialized views can bring a heavy burden to the rdbms. a traditional method to mitigate this problem is to use the where clause condition in the materialized view definition to detect whether an update to a base relation is relevant and can affect the materialized view. however, this detection method does not consider the content in the base relations and hence misses a large number of filtering opportunities. in this paper, we propose a content-based method for detecting irrelevant updates to base relations of a materialized view. at the cost of using more space, this method increases the probability of catching irrelevant updates by judiciously designing filtering relations to capture the content in the base relations. based on the content-based method, a prototype real-time data warehouse has been implemented on top of ibm's system s using ibm db2. using an analytical model and our prototype, we show that the content-based method can catch most (or all) irrelevant updates to base relations that are missed by the traditional method. thus, when the fraction of irrelevant updates is non-negligible, the load on the rdbms due to materialized view maintenance can be significantly reduced.
modeling hidden topics on document manifold. topic modeling has been a key problem for document analysis. one of the canonical approaches for topic modeling is probabilistic latent semantic indexing, which maximizes the joint probability of documents and terms in the corpus. the major disadvantage of plsi is that it estimates the probability distribution of each document on the hidden topics independently and the number of parameters in the model grows linearly with the size of the corpus, which leads to serious problems with overfitting. latent dirichlet allocation (lda) is proposed to overcome this problem by treating the probability distribution of each document over topics as a hidden random variable. both of these two methods discover the hidden topics in the euclidean space. however, there is no convincing evidence that the document space is euclidean, or flat. therefore, it is more natural and reasonable to assume that the document space is a manifold, either linear or nonlinear. in this paper, we consider the problem of topic modeling on intrinsic document manifold. specifically, we propose a novel algorithm called laplacian probabilistic latent semantic indexing (lapplsi) for topic modeling. lapplsi models the document space as a submanifold embedded in the ambient space and directly performs the topic modeling on this document manifold in question. we compare the proposed lapplsi approach with plsi and lda on three text data sets. experimental results show that lapplsi provides better representation in the sense of semantic structure.
dynamic faceted search for discovery-driven analysis. we propose a dynamic faceted search system for discovery-driven analysis on data with both textual content and structured attributes. from a keyword query, we want to dynamically select a small set of "interesting" attributes and present aggregates on them to a user. similar to work in olap exploration, we define "interestingness" as how surprising an aggregated value is, based on a given expectation. we make two new contributions by proposing a novel "navigational" expectation that's particularly useful in the context of faceted search, and a novel interestingness measure through judicious application of p-values. through a user survey, we find the new expectation and interestingness metric quite effective. we develop an efficient dynamic faceted search system by improving a popular open source engine, solr. our system exploits compressed bitmaps for caching the posting lists in an inverted index, and a novel directory structure called a bitset tree for fast bitset intersection. we conduct a comprehensive experimental study on large real data sets and show that our engine performs 2 to 3 times faster than solr.
the social (open) workspace. social networking promises individuals new dimensions of freedom to interact, associate, and give expression to their talents. recently, systems such as mechanical turk have started to facilitate self-organizing collaboration on work-related tasks. such developments raise interesting questions. is it possible to create (and sustain) businesses that do not have traditional, formal structure - without traditional "employees"? can we find and organize (and optimize) talent on the web for task-oriented work - spontaneously and efficiently? how do people relate to one another in possibly evanescent workgroups? one aspect of the challenge in the social workspace is understanding and modeling the user behavior and the economic basis for creating, preserving, and exchanging value in the marketplace when workgroup identity, orientations to property, recruiting and managing appropriate talent are not organized under traditional company structures. another aspect is the technology needed to support virtual organizations and work. the panel will discuss trends in social work and the evolving (scientific) basis of our understanding of new models of workers and organizations.
re-considering neighborhood-based collaborative filtering parameters in the context of new data. the movielens dataset and the herlocker et al. study of 1999 have been very influential in collaborative filtering. yet, the age of both invites re-examining their applicability. we use netflix challenge data to re-visit the prior results. in particular, we re-evaluate the parameters of herlocker et al.'s method on two critical factors: measuring similarity between users and normalizing the ratings of the users. we find that normalization plays a significant role and that pearson correlation is not necessarily the best similarity metric.
estimating real-valued characteristics of criminals from their recorded crimes. offender profiling concerns making inferences about a criminal from the crime(s) he has committed. where descriptionsof the crimes are recorded electronically, text mining techniques provide a means by which recorded characteristics of the offenders can be linked with features of his crimes as revealed in the text. past studies have used language modelling to identify characteristics that can be described by a categorical variable e.g. gender. here we adapt the language modelling approach to allow estimation of numerical quantities such as age and distance travelled.
can all tags be used for search? collaborative tagging has become an increasingly popular means for sharing and organizing web resources, leading to a huge amount of user generated metadata. these tags represent quite a few different aspects of the resources they describe and it is not obvious whether and how these tags or subsets of them can be used for search. this paper is the first to present an in-depth study of tagging behavior for very different kinds of resources and systems - web pages (del.icio.us), music (last.fm), and images (flickr) - and compares the results with anchor text characteristics. we analyze and classify sample tags from these systems, to get an insight into what kinds of tags are used for different resources, and provide statistics on tag distributions in all three tagging environments. since even relevant tags may not add new information to the search procedure, we also check overlap of tags with content, with metadata assigned by experts and from other sources. we discuss the potential of different kinds of tags for improving search, comparing them with user queries posted to search engines as well as through a user survey. the results are promising and provide more insight into both the use of different kinds of tags for improving search and possible extensions of tagging systems to support the creation of potentially search-relevant tags.
a sparse gaussian processes classification framework for fast tag suggestions. tagged data is rapidly becoming more available on the world wide web. web sites which populate tagging services offer a good way for internet users to share their knowledge. an interesting problem is how to make tag suggestions when a new resource becomes available. in this paper, we address the issue of efficient tag suggestion. we first propose a multi-class sparse gaussian process classification framework (sgps) which is capable of classifying data with very few training instances. we suggest a novel prototype selection algorithm to select the best subset of points for model learning. the framework is then extended to a novel multi-class multi-label classification algorithm (mmsg) that transforms tag suggestion into the problem of multi-label ranking. experiments on bench-mark data sets and real-world data from del.icio.us and bibsonomy suggest that our model can greatly improve the performance of tag suggestions when compared to the state-of-the-art. overall, our model requires linear time to train and constant time to predict per case. the memory consumption is also significantly less than traditional batch learning algorithms such as svms. in addition, results on tagging digital data also demonstrate that our model is capable of recommending relevant tags to images and videos by using their surrounding textual information.
using tag semantic network for keyphrase extraction in blogs. folksonomies provide a comfortable way to search and browse the blogosphere. as the tags in the blogosphere are sparse, ambiguous and too general, this paper proposes both a supervised and an unsupervised approach that extract tags from posts using a tag semantic network. we evaluate the two methods on a blog dataset and observe an improvement in f1-measure from 0.23 to 0.50 when compared to the baseline system.
retrievability: an evaluation measure for higher order information access tasks. evaluation in information retrieval (ir) has long focused on effectiveness and efficiency. however, new and emerging access tasks now demand alternative evaluation measures which go beyond this traditional view. a retrieval system provides a means of gaining access to documents, therefore intuitively, our view of the collection is shaped by the retrieval system. in this paper, we outline some emerging information access related scenarios that require knowledge about how the retrieval system affects the users' ability to access information. this provides the motivation for the proposed evaluation measures and methodology where the focus is on capturing the behavior of the system, in terms of how retrievable it makes individual documents within the collection. to demonstrate the utility of the proposed methods, we perform an extensive analysis on two trec collections showing how the measures can be applied to evaluate different information access questions. for higher order information access tasks that are inherently dependent on retrievability, our novel evaluation methodology emphasizes that effectiveness is an insufficient characterization of a retrieval system. this paper provides the foundations for the evaluation of higher order access related tasks.
linear time membership in a class of regular expressions with interleaving and counting. the extension of regular expressions (res) with an interleaving (shuffle) operator has been proposed in many occasions, since it would be crucial to deal with unordered data. however, interleaving badly affects the complexity of basic operations, and, expecially, makes membership np-hard [13], which is unacceptable for most uses of res. res form the basis of most xml type languages, such as dtds and xml schema types, and xduce types [16, 11]. in this context, the interleaving operator would be a natural addition to the language of res, as witnessed by the presence of limited forms of interleaving in xsd (the all group), relax-ng, and sgml, provided that the np-hardness of membership could be avoided. we present here a restricted class of res with interleaving and counting which admits a linear membership algorithm, and which is expressive enough to cover the vast majority of real-world xml types. we first present an algorithm for membership of a list of words into a re with interleaving and counting, based on the translation of the re into a set of constraints. we generalize the approach in order to check membership of xml trees into a class of edtds with interleaving and counting, which models the crucial aspects of dtds and xsd schemas.
pruning nested xquery queries. we present in this paper an approach for xquery optimization that exploits minimization opportunities raised in composition-style nesting of queries. more precisely, we consider the simplification of xquery queries in which the intermediate result constructed by a subexpression is queried by another subexpression. based on a large subset of xquery, we describe a rule-based algorithm that recursively prunes query expressions, eliminating useless intermediate results. our algorithm takes as input an xquery expression that may have navigation within its subexpressions and outputs a simplified, equivalent xquery expression, and is thus readily usable as an optimization module in any existing xquery processor. we demonstrate by experiments the impact of our rewriting approach on query evaluation costs and we prove formally its correctness.
siphon++: a hidden-webcrawler for keyword-based interfaces. the hidden web consists of data that is generally hidden behind form interfaces, and as such, it is out of reach for traditional search engines. with the goal of leveraging the high-quality information in this largely unexplored portion of the web, in this paper, we propose a new strategy for automatically retrieving data hidden behind keyword-based form interfaces. unlike previous approaches to this problem, our strategy adapts the query generation and selection by detecting features of the index. we describe an extensive experimental evaluation which shows that: our strategy is able to derive appropriate queries to obtain high coverage while, at the same time, avoiding the retrieval of redundant data; and it obtains higher coverage and is more efficient approaches that use a fixed strategy for query generation.
view and index selection for query-performance improvement: quality-centered algorithms and heuristics. selecting and precomputing indexes and materialized views, with the goal of improving query-processing performance, is an important part of database-performance tuning. the significant complexity of the view- and index-selection problem may result in high total cost of ownership for database systems. in this paper, we develop efficient methods that deliver user-specified quality of the set of selected views and indexes when given view- and index-based plans as problem inputs. here, quality means proximity to the globally optimum performance for the input query workload given the input query plans. our experimental results and comparisons on synthetic and benchmark instances demonstrate the competitiveness of our approach and show that it provides a winning combination with end-to-end view- and index-selection frameworks such as those of [1, 2].
query suggestion using hitting time. generating alternative queries, also known as query suggestion, has long been proved useful to help a user explore and express his information need. in many scenarios, such suggestions can be generated from a large scale graph of queries and other accessory information, such as the clickthrough. however, how to generate suggestions while ensuring their semantic consistency with the original query remains a challenging problem. in this work, we propose a novel query suggestion algorithm based on ranking queries with the hitting time on a large scale bipartite graph. without involvement of twisted heuristics or heavy tuning of parameters, this method clearly captures the semantic consistency between the suggested query and the original query. empirical experiments on a large scale query log of a commercial search engine and a scientific literature collection show that hitting time is effective to generate semantically consistent query suggestions. the proposed algorithm and its variations can successfully boost long tail queries, accommodating personalized query suggestion, as well as finding related authors in research.
a generative retrieval model for structured documents. structured documents contain elements defined by the author(s) and annotations assigned by other people or processes. structured documents pose challenges for probabilistic retrieval models when there are mismatches between the structured query and the actual structure in a relevant document or erroneous structure introduced by an annotator. this paper makes three contributions. first, a new generative retrieval model is proposed to deal with the mismatch problem. this new model extends the basic keyword language model by treating structure as hidden variable during the generation process. second, variations of the model are compared. third, term-level and structure-level smoothing strategies are studied. evaluation was conducted with inex xml retrieval and question-answering retrieval tasks. experimental results indicate that the optimal structured retrieval model is task dependent, two-level dirichlet smoothing significantly outperforms two-level jelinek-mercer smoothing, and with accurate structured queries, the proposed structured retrieval model outperforms keyword retrieval significantly, on both qa and inex datasets.
an approximate string matching approach for handling incorrectly typed urls. in this paper we approach the problem of providing corrections for incorrectly typed urls. this problem is significantly different from the classical spelling correction problem. we describe our contribution - building a custom data structure and a search algorithm that can find approximate matches for incorrect urls. we evaluate the quality of our results through experiments with analysts. our system is now being used in the google search engine.
pbfilter: indexing flash-resident data through partitioned summaries. nand flash has become the most popular persistent data storage medium for mobile and embedded devices. the hardware characteristics of nand flash (e.g. page granularity for read/write with a block-erase-before-rewrite constraint, limited number of erase cycles) preclude in-place updates. in this paper, we propose a new indexing scheme, called pbfilter, designed from the outset to exploit the peculiarities of nand flash.
utilization of navigational queries for result presentation and caching in search engines. we propose result page models with varying granularities for navigational queries and show that this approach provides a better utilization of cache space and reduces bandwidth requirements.
deriving non-redundant approximate association rules from hierarchical datasets. association rule mining plays an important job in knowledge and information discovery. however, there are still shortcomings with the quality of the discovered rules and often the number of discovered rules is huge and contain redundancies, especially in the case of multi-level datasets. previous work has shown that the mining of non-redundant rules is a promising approach to solving this problem, with work by [6,8,9,10] focusing on single level datasets. recent work by shaw et. al. [7] has extended the non-redundant approaches presented in [6,8,9] to include the elimination of redundant exact basis rules from multi-level datasets. here we propose a continuation of the work in [7] that allows for the removal of hierarchically redundant approximate basis rules from multi-level datasets by using a dataset's hierarchy or taxonomy.
valid scope computation for location-dependent spatial query in mobile broadcast environments. wireless data broadcast is an efficient and scalable means to provide information access for a large population of clients in mobile environments. with location-based services (lbss) deployed upon a broadcast channel, mobile clients can collect data from the channel to answer their location-dependent spatial queries (ldsqs). since the results of ldsqs would become invalid when mobile client moves to new locations, the knowledge of valid scopes for ldsq results is necessary to assist clients to determine if their previous ldsq results can be reused after they moved. this effectively improves query response time and client energy consumption. in this paper, we devise efficient algorithms to determine valid scopes for various ldsqs including range, window and nearest neighbor queries along with ldsq processing over a broadcast channel. we conduct an extensive set of experiments to evaluate the performance of our proposed algorithms. while the proposed valid scope algorithm incurs only little extra processing overhead, unnecessary ldsq reevaluation is significantly eliminated, thus providing faster query response and saving client energy.
passage relevance models for genomics search. we present a passage relevance model for integrating semantic and statistical evidence of biomedical concepts and topics using a probabilistic graphical model. component models of topics, concepts, terms, and document are represented as potential functions within a markov random field. the probability of a passage being relevant to a biologist's information need is represented as the joint distribution across all potential functions. relevance model feedback of top ranked passages is used to improve distributional estimates of concepts and topics in context, and a dimensional indexing strategy is used for efficient aggregation of concept and term statistics. by integrating multiple sources of evidence including dependencies between topics, concepts, and terms, we seek to improve genomics literature passage retrieval precision. using this model, we are able to demonstrate statistically significant improvements in retrieval precision using a large genomics literature corpus.
learning latent semantic relations from clickthrough data for query suggestion. for a given query raised by a specific user, the query suggestion technique aims to recommend relevant queries which potentially suit the information needs of that user. due to the complexity of the web structure and the ambiguity of users' inputs, most of the suggestion algorithms suffer from the problem of poor recommendation accuracy. in this paper, aiming at providing semantically relevant queries for users, we develop a novel, effective and efficient two-level query suggestion model by mining clickthrough data, in the form of two bipartite graphs (user-query and query-url bipartite graphs) extracted from the clickthrough data. based on this, we first propose a joint matrix factorization method which utilizes two bipartite graphs to learn the low-rank query latent feature space, and then build a query similarity graph based on the features. after that, we design an online ranking algorithm to propagate similarities on the query similarity graph, and finally recommend latent semantically relevant queries to users. experimental analysis on the clickthrough data of a commercial search engine shows the effectiveness and the efficiency of our method.
trust, authority and popularity in social information retrieval. we present a social information retrieval (sir) model comprising the social network of actors (e.g., authors, publishers, consumers), the graph representing relations in data (e.g., publications), and the links between the social and data network that reflect activities in the network such as search, authoring, annotation, etc. building on this hybrid network, we describe relevance in terms of the trust propagated through the network and rendered onto a given item. in particular, relevance is a function of the approval votes from the associated sub-graph and the reputation of the sub-graph nodes. we explore a model that differentiates between approval from actors who are perceived authorities by the user and the approval by a wider community, representing the popular opinion.
discovering leaders from community actions. we introduce a novel frequent pattern mining approach to discover leaders and tribes in social networks. in particular, we consider social networks where users perform actions. actions may be as simple as tagging resources (urls) as in del.icio.us, rating songs as in yahoo! music, or movies as in yahoo! movies, or users buying gadgets such as cameras, handhelds, etc. and blogging a review on the gadgets. the assumption is that actions performed by a user can be seen by their network friends. users seeing their friends' actions are sometimes tempted to perform those actions. we are interested in the problem of studying the propagation of such "influence", and on this basis, identifying which users are leaders when it comes to setting the trend for performing various actions. we consider alternative definitions of leaders based on frequent patterns and develop algorithms for their efficient discovery. our definitions are based on observing the way influence propagates in a time window, as the window is moved in time. given a social graph and a table of user actions, our algorithms can discover leaders of various flavors by making one pass over the actions table. we run detailed experiments to evaluate the utility and scalability of our algorithms on real-life data. the results of our experiments confirm on the one hand, the efficiency of the proposed algorithm, and on the other hand, the effectiveness and relevance of the overall framework. to the best of our knowledge, this the first frequent pattern based approach to social network mining.
a random walk on the red carpet: rating movies with user reviews and pagerank. although pagerank has been designed to estimate the popularity of web pages, it is a general algorithm that can be applied to the analysis of other graphs other than one of hypertext documents. in this paper, we explore its application to sentiment analysis and opinion mining: i.e. the ranking of items based on user textual reviews. we first propose various techniques using collocation and pivot words to extract a weighted graph of terms from user reviews and to account for positive and negative opinions. we refer to this graph as the sentiment graph. using pagerank and a very small set of adjectives (such as 'good', 'excellent', etc.) we rank the different items. we illustrate and evaluate our approach using reviews of box office movies by users of a popular movie review site. the results show that our approach is very effective and that the ranking it computes is comparable to the ranking obtained from the box office figures. the results also show that our approach is able to compute context-dependent ratings.
answering questions with authority. this paper presents a novel approach to textual question answering (qa) which identifies answers to natural language questions by leveraging large collections of question-answer pairs extracted from web sources or generated automatically from text. instead of using the traditional retrieve-and-rerank approach common to most previous approaches to factoid question answering, we introduce a new model of answer authority which allows question-answering systems to estimate the quality of answers not just in isolation - but in the larger context of the information contained in the corpus as a whole. our approach in this paper hinges on the creation of a new representation of the information stored in a document collection, known as a question-answer database (quab).we assume that a quab represents a weighted directed graph consisting of the set of factoid question-answer pairs (qap) that can be asked - and answered - given the content of a corpus. once a set of qap have been generated, we use inferential relationships identified by a system for recognizing textual entailment in order to construct the link structure necessary to compute the authority of each interconnected question or answer. we have found access to the quab graph not only improves the accuracy of current answer retrieval techniques, but also allows for the determination of when no valid answer can be found for a question in a text corpus. experimental results show that the authority derived from a graph of question-answer pairs can increase the performance of a factoid qa system by nearly 30%.
table summarization with the help of domain lattices. table summarization is necessary in various scenarios where it is hard to display a large table. it can benefit from knowledge about acceptable value clustering alternatives. in this paper, we formulate the problem of table summarization with the help of domain knowledge lattices. we provide the outline of a fuzzy mechanism to express alternative clustering strategies. we further sketch a novel ranked set cover based evaluation mechanism (rsc) to tackle with the inherent complexity.
a heuristic approach for checking containment of generalized tree-pattern queries. query processing techniques for xml data have focused mainly on tree-pattern queries (tpqs). however, the need for querying xml data sources whose structure is very complex or not fully known to the user, and the need to integrate multiple xml data sources with different structures have driven, recently, the suggestion of query languages that relax the complete specification of a tree pattern. in order to implement the processing of such languages in current dbmss, their containment problem has to be efficiently solved. in this paper, we consider a query language which generalizes tpqs by allowing the partial specification of a tree pattern. partial tree-pattern queries (ptpqs) constitute a large fragment of xpath that flexibly permits the specification of a broad range of queries from keyword queries without structure, to queries with partial specification of the structure, to complete tpqs. we address the containment problem for ptpqs. this problem becomes more complex in the context of ptpqs because the partial specification of the structure allows new, non-trivial, structural expressions to be inferred from those explicitly specified in a query. we show that the containent problem cannot be characterized by homomorphisms between ptpqs, even when ptpqs are put in a canonical form that comprises all derived structural expressions. we provide necessary and sufficient conditions for this problem in terms of homomorphisms between ptpqs and (a possibly exponential number of) tpqs. to cope with the high complexity of ptpq containment, we suggest a heuristic approach for this problem that trades accuracy for speed. an extensive experimental evaluation of our heuristic shows that our heuristic approach can be efficiently implemented in a query optimizer.
semi-automated logging of contact center telephone calls. modern businesses use contact centers as a communication channel with users of their products and services. the largest factor in the expense of running a telephone contact center is the labor cost of its agents. ibm research has built a new system, contact-center agent buddies (cab), which is designed to help reduce the average handle time (aht) for customer calls, thereby also reducing their cost. in this paper, we focus on the call logging subsystem, which helps agents reduce the time they spend documenting those calls. we built a template cab and a call logging cab, using a pipeline consisting of audio capture of a telephone conversation, automatic speech recognition, text analysis, and log generation. we developed techniques for asr text cleansing, including normalization of expressions and acronyms, domain terms, capitalization, and boundaries for sentences, paragraphs, and call segments. we found that simple heuristics suffice to generate high-quality logs from the normalized sentences. the pipeline yields a candidate call log which the agents can edit in less time than it takes them to generate call logs manually. evaluation of the call logging cab in an industrial contact center environment shows that it reduces the amount of time agents spend logging calls by at least 50% without compromising the quality of the resulting call documentation.
coreference resolution using expressive logic models. coreference resolution is regarded as a crucial step for acquiring linkages among pieces of information extracted. traditionally, coreference resolution models make use of independent attribute-value features over pairs of noun phrases. however, dependency and deeper relations between features can more adequately describe the properties of coreference relations between noun phrases. in this paper, we propose a framework of coreference resolution based on first-order logic and probabilistic graphical model, the markov logic network. the proposed framework enables the use of background knowledge and captures more complex coreference linkage properties through rich expression of conditions. moreover, the proposed conditions can capture the structural pattern within a noun phrase as well as contextual information between noun phrases. our experiments show improvement with the use of the expressive logic models and the use of pattern-based conditions.
adaptive distributed indexing for structured peer-to-peer networks. structured peer-to-peer networks support keyword search by building a distributed index over the collective content shared by all peers. building the index and processing queries involve data transfer among peers, thus it is important to keep both of these activities bandwidth-efficient. however, this goal is difficult to attain, as smaller, less precise indices reduce index building and access costs but increase query processing cost, which potentially increases overall cost. we study the trade-off between indexing cost and query processing cost in a structured peer-to-peer network and propose a cost-reducing, adaptive, distributed indexing technique based on the term distributions in local shared contents and user query logs. using this information, we reduce costs by tuning the precision of the index. the approach we take is to group local documents and to index the groups instead of either individual documents or entire peer collections. we control total cost by controlling the number and contents of groups. we propose a probabilistic model to estimate the cost of grouping, which allows us to identify the optimal number of groups to be created. in addition, we propose a cost-based distance function to guide the document grouping process. experimental results show that our adaptive indexing technique reduces cost by up to 47% compared with peer-level grouping and by up to 73% compared with document-level grouping.
suppressing outliers in pairwise preference ranking. many of the recently proposed algorithms for learning feature-based ranking functions are based on the pairwise preference framework, in which instead of taking documents in isolation, document pairs are used as instances in the learning process. one disadvantage of this process is that a noisy relevance judgment on a single document can lead to a large number of mis-labeled document pairs. this can jeopardize robustness and deteriorate overall ranking performance. in this paper we study the effects of outlying pairs in rank learning with pairwise preferences and introduce a new meta-learning algorithm capable of suppressing these undesirable effects. this algorithm works as a second optimization step in which any linear baseline ranker can be used as input. experiments on eight different ranking datasets show that this optimization step produces statistically significant performance gains over state-of-the-art methods.
a latent variable model for query expansion using the hidden markov model. we propose a novel probabilistic method based on the hidden markov model(hmm) to learn the structure of a latent variable model (lvm) for query language modeling. in the proposed lvm, the combinations of query terms are viewed as the latent variables and the segmented chunks from the feedback documents are used as the observations given these latent variables. our extensive experiments shows that our method significantly outperforms a number of strong baselines in terms of both effectiveness and robustness.
relating dependent indexes using dempster-shafer theory. traditional information retrieval (ir) approaches assume that the indexing terms are independent, which is not true in reality. although some previous studies have tried to consider term relationships, strong simplifications had to be made at the very basic indexing step, namely, dependent terms are assigned independent counts or probabilities. in this study, we propose to consider dependencies between terms using dempster-shafer theory of evidence. an occurrence of a string in a document is considered to represent the set of all the terms implied in it. probability is assigned to such a set of terms instead of individual terms. during query evaluation phase, a part of the probability of a set can be transferred to those of the query that are related, allowing us to integrate language-dependent relations in ir. this approach has been tested on several chinese ir collections. our experimental results show that our model can outperform the existing state-of-the-art approaches. the proposed method can be used as a general way to consider different types of relationship between terms and for other languages.
privacy-preserving data publishing for horizontally partitioned databases. there is an increasing need for sharing data repositories containing personal information across multiple distributed, possibly untrusted, and private databases. such data sharing is subject to constraints imposed by privacy of data subjects as well as data confidentiality of institutions or data providers. we developed a set of decentralized protocols that enable data sharing for horizontally partitioned databases given these constraints. our approach includes a distributed anonymization protocol that allows independent data providers to build a virtual anonymized database, and a distributed querying protocol that allows clients to query the virtual database.
integrating clustering and multi-document summarization to improve document understanding. document understanding techniques such as document clustering and multi-document summarization have been receiving much attention in recent years. current document clustering methods usually represent documents as a term-document matrix and perform clustering algorithms on it. although these clustering methods can group the documents satisfactorily, it is still hard for people to capture the meanings of the documents since there is no satisfactory interpretation for each document cluster. in this paper, we propose a new language model to simultaneously cluster and summarize the documents. by utilizing the mutual influence of the document clustering and summarization, our method makes (1) a better document clustering method with more meaningful interpretation and (2) a better document summarization method taking the document context information into consideration.
road: an efficient framework for location dependentspatial queries on road networks. in this research, we develop road, a system framework for processing location dependent spatial queries (ldsqs) that search for spatial objects of interest on road networks. by exploiting search space pruning, road is very efficient and flexible for various ldsqs on different types of objects over large-scale networks. in road, a large road network is organized as a set of interconnected regional sub-networks (called rnets) augmented with 1) shortcuts for accelerating search traversals; and 2) object abstracts for guiding object search. in this poster, we outline this framework and explain how it can support efficient location-dependent nearest neighbor search.
tinylex: static n-gram index pruning with perfect recall. inverted indexes using sequences of characters (n-grams) as terms provide an error-resilient and language-independent way to query for arbitrary substrings and perform approximate matching in a text, but present a number of practical problems: they have a very large number of terms, they exhibit pathologically expensive worst-case query times on certain natural inputs, and they cannot cope with very short query strings. in word-based indexes, static index pruning has been successful in reducing index size while maintaining precision, at the expense of recall. taking advantage of the unique inclusion structure of n-gram terms of different lengths, we show that the lexicon size of an n-gram index can be reduced by 7 to 15 times without any loss of recall, and without any increase in either index size or query time. because the lexicon is typically stored in main memory, this substantially reduces the memory required for queries. simultaneously, our construction is also the first overlapping n-gram index to place tunable worst-case bounds on false positives and to permit efficient queries on strings of any length. using this construction, we also demonstrate the first feasible n-gram index using words rather than characters as units, and its applications to phrase searching.
on effective presentation of graph patterns: a structural representative approach. in the past, quite a few fast algorithms have been developed to mine frequent patterns over graph data, with the large spectrum covering many variants of the problem. however, the real bottleneck for knowledge discovery on graphs is neither efficiency nor scalability, but the usability of patterns that are mined out. currently, what the state-of-art techniques give is a lengthy list of exact patterns, which are undesirable in the following two aspects: (1) on the micro side, due to various inherent noises or data diversity, exact patterns are usually not too useful in many real applications; and (2) on the macro side, the rigid structural requirement being posed often generates an excessive amount of patterns that are only slightly different from each other, which easily overwhelm the users. in this paper, we study the presentation problem of graph patterns, where structural representatives are deemed as the key mechanism to make the whole strategy effective. as a solution to fill the usability gap, we adopt a two-step smoothing-clustering framework, with the first step adding error tolerance to individual patterns (the micro side), and the second step reducing output cardinality by collapsing multiple structurally similar patterns into one representative (the macro side). this novel, integrative approach is never tried in previous studies, which essentially rolls-up our attention to a more appropriate level that no longer looks into every minute detail. the above framework is general, which may apply under various settings and incorporate a lot of extensions. empirical studies indicate that a compact group of informative delegates can be achieved on real datasets and the proposed algorithms are both efficient and scalable.
measuring user preference changes in digital libraries. much research has been conducted using web access logs to study implicit user feedback and infer user preferences from clickstreams. however, little research measures the changes of user preferences of ranking documents over time. we present a study that measures the changes of user preferences based on an analysis of access logs of a large scale digital library over one year. a metric based on the accuracy of predicting future user actions is proposed. the results show that although user preferences change over time, the majority of user actions should be predictable from previous browsing behavior in the digital library.
wildcards for lightweight information integration in virtual desktops. we present a flexible information integration approach which addresses the dynamic integration needs in a personal desktop environment where only partial mappings are defined between the sources to be integrated. our approach is based on query rewriting using substitution rules. in addition to exploiting defined mappings, we employ substitution strategies, which are inspired by the idea of using wildcards in querying and filtering tasks. starting from a triple based query language as used for querying rdf data, unmapped ontological elements are substituted in a controlled way with variables, leading to a controlled form of query relaxation. in addition, the approach also provides evidences for refining the existing mapping based on the results of executing the relaxed queries. different strategies for replacing non-matched ontology elements with variables are presented and evaluated over real-world data sets.
a spam resistant family of concavo-convex ranks for link analysis. a parameterized family of non-linear, link analytic ranking functions is proposed that includes pagerank as a special case and uses the convexity property of those functions to be more resistant to link spam attacks. a contribution of the paper is the construction of such a scheme with provable uniqueness and convergence guarantees. the paper also demonstrates that even in an unlabelled scenario this family can have spam resistance comparable to trustrank [3] that uses labels of spam or nat-spam on a training set. the proposed method can use labels, if available, to improve its performance to provide state of the art level of link spam protection.
incorporating place name extents into geo-ir ranking. this paper proposes a novel geo-ir ranking method that realizes effective searches that emphasize the user's immediate surroundings. it assesses the extent implied by place names in documents and then emphasizes place names that are highly specific in terms of identifying locations.
ce2: towards a large scale hybrid search engine with integrated ranking support. the web contains a large amount of documents and increasingly, also semantic data in the form of rdf triples. many of these triples are annotations that are associated with documents. while structured query is the principal mean to retrieve semantic data, keyword queries are typically used for document retrieval. clearly, a form of hybrid search that seamlessly integrates these formalisms to query both documents and semantic data can address more complex information needs. in this paper, we present ce2, an integrated solution that leverages mature database and information retrieval technologies to tackle challenges in hybrid search on the large scale. for scalable storage, ce2 integrates database with inverted indices. hybrid query processing is supported in ce2 through novel algorithms and data structures, which allow for advanced ranking schemes to be integrated more tightly into the process. experiments conducted on dbpedia and wikipedia show that ce2 can provide good performance in terms of both effectiveness and efficiency.
an empirical study of required dimensionality for large-scale latent semantic indexing applications. the technique of latent semantic indexing is used in a wide variety of commercial applications. in these applications, the processing time and ram required for svd computation, and the processing time and ram required during lsi retrieval operations are all roughly linear in the number of dimensions, k, chosen for the lsi representation space. in large-scale commercial lsi applications, reducing k values could be of significant value in reducing server costs. this paper explores the effects of varying dimensionality. the approach taken here focuses on term comparisons. pairs of terms are considered which have strong real-world associations. the proximities of members of these pairs in the lsi space are compared at multiple values of k. the testing is carried out for collections of from one to five million documents. for the five million document collection, a value of k ≈ 400 provides the best performance. the results suggest that there is something of an 'island of stability' in the k = 300 to 500 range. the results also indicate that there is relatively little room to employ k values outside of this range without incurring significant distortions in at least some term-term correlations.
a matrix-based approach for semi-supervised document co-clustering. in order to derive high quality information from text, the field of text mining has advanced swiftly from simple document clustering to co-clustering documents and words. however, document co-clustering without any prior knowledge or background information is a challenging problem. in this paper, we propose a semi-supervised non-negative matrix factorization (ss-nmf) based framework for document co-clustering. our method computes a new word-document matrix by incorporating user provided constraints through distance metric learning. using an iterative algorithm, we perform tri-factorization of the new matrix to infer the document and word clusters. through extensive experiments conducted on publicly available data sets, we demonstrate the superior performance of ss-nmf for document co-clustering.
simultaneous multilingual search for translingual information retrieval. we consider the problem of translingual information retrieval, where monolingual searchers issue queries in a different language than the document language(s) and the results must be returned in the language they know, the query language. we present a framework for translingual ir that integrates document translation and query translation into the retrieval model. the corpus is represented as an aligned, jointly indexed "pseudo-parallel" corpus, where each document contains the text of the document along with its translation into the query language. the queries are formulated as multilingual structured queries, where each query term and its translations into the document language(s) are treated as synonym sets. this model leverages simultaneous search in multiple languages against jointly indexed documents to improve the accuracy of results over search using document translation or query translation alone. for query translation, we compared a statistical machine translation (smt) approach to a dictionary-based approach. we found that using a wikipedia-derived dictionary for named entities combined with an smt-based dictionary worked better than smt alone. simultaneous multilingual search also has other important features suited to translingual search, since it can provide an indication of poor document translation when a match with the source document is found. we show how close integration of clir and smt allows us to improve result translation in addition to ir results.
web-scale named entity recognition. automatic recognition of named entities such as people, places, organizations, books, and movies across the entire web presents a number of challenges, both of scale and scope. data for training general named entity recognizers is difficult to come by, and efficient machine learning methods are required once we have found hundreds of millions of labeled observations. we present an implemented system that addresses these issues, including a method for automatically generating training data, and a multi-class online classification training method that learns to recognize not only high level categories such as place and person, but also more fine-grained categories such as soccer players, birds, and universities. the resulting system gives precision and recall performance comparable to that obtained for more limited entity types in much more structured domains such as company recognition in newswire, even though web documents often lack consistent capitalization and grammatical sentence construction.
unsolved problems in search: (and how we approach them). search applications have become ubiquitous and very successful. major advances have been made in understanding how to deliver effective results very efficiently for a class of queries. as the range of applications broaden to include web search, desktop search, enterprise search, vertical search, social search, etc., the number of new research challenges has appeared to grow rather than shrink. many of these challenges are variations on underlying themes and principles that information retrieval has focused on for more than 40 years. in this talk, several unsolved problems arising from new search applications will be discussed and some potential paths to solutions for these problems will be outlined.
a note on search based forecasting of ad volume in contextual advertising. in contextual advertising, estimating the number of impressions of an ad is critical in planning and budgeting advertising campaigns. however, producing this forecast, even within large margins of error, is quite challenging. we attack this problem by simulating the presence of a given ad with its associated bid over historical data, involving billions of impressions. this apparently enormous computational task is reduced to a search task involving only the set of distinct pages in the data. furthermore the search is made more efficient using a two-level search process. experimental results show that our approach can accurately forecast the expected number of impressions of contextual ads in real time.
social tags: meaning and suggestions. this paper aims to quantify two common assumptions about social tagging: (1) that tags are "meaningful" and (2) that the tagging process is influenced by tag suggestions. for (1), we analyze the semantic properties of tags and the relationship between the tags and the content of the tagged page. our analysis is based on a corpus of search keywords, contents, titles, and tags applied to several thousand popular web pages. among other results, we find that the more popular tags of a page tend to be the more meaningful ones. for (2), we develop a model of how the influence of tag suggestions can be measured. from a user study with over 4,000 participants, we conclude that roughly one third of the tag applications may be induced by the suggestions. our results would be of interest for designers of social tagging systems and are a step towards understanding how to best leverage social tags for applications such as search and information extraction.
kernel methods, syntax and semantics for relational text categorization. previous work on natural language processing for information retrieval has shown the inadequateness of semantic and syntactic structures for both document retrieval and categorization. the main reason is the high reliability and effectiveness of language models, which are sufficient to accurately solve such retrieval tasks. however, when the latter involve the computation of relational semantics between text fragments simple statistical models may result ineffective. in this paper, we show that syntactic and semantic structures can be used to greatly improve complex categorization tasks such as determining if an answer correctly responds to a question. given the high complexity of representing semantic/syntactic structures in learning algorithms, we applied kernel methods along with support vector machines to better exploit the needed relational information. our experiments on answer classification on web and trec data show that our models greatly improve on bag-of-words.
a light weighted damage tracking quarantine and recovery scheme for mission-critical database systems. as online applications gain popularity in today's e-business world, surviving dbms from an attack is becoming crucial because of the increasingly critical role that database servers are playing. although a number of research projects have been done to tackle the emerging data corruption threats, existing mechanisms are still limited in meeting four highly desired requirements: near zero run time overhead, zero system down time. in this paper, we propose trace, a light weighted database damage tracking, quarantine, and recovery (dtqr) solution with negligible run time overhead.
minimum-effort driven dynamic faceted search in structured databases. in this paper, we propose minimum-effort driven navigational techniques for enterprise database systems based on the faceted search paradigm. our proposed techniques dynamically suggest facets for drilling down into the database such that the cost of navigation is minimized. at every step, the system asks the user a question or a set of questions on different facets and depending on the user response, dynamically fetches the next most promising set of facets, and the process repeats. facets are selected based on their ability to rapidly drill down to the most promising tuples, as well as on the ability of the user to provide desired values for them. our facet selection algorithms also work in conjunction with any ranked retrieval model where a ranking function imposes a bias over the user preferences for the selected tuples. our methods are principled as well as efficient, and our experimental study validates their effectiveness on several application scenarios.
can phrase indexing help to process non-phrase queries? modern web search engines, while indexing billions of web pages, are expected to process queries and return results in a very short time. many approaches have been proposed for efficiently computing top-k query results, but most of them ignore one key factor in the ranking functions of commercial search engines - term-proximity, which is the metric of the distance between query terms in a document. when term-proximity is included in ranking functions, most of the existing top-k algorithms will become inefficient. to address this problem, in this paper we propose to build a compact phrase index to speed up the search process when incorporating the term-proximity factor. the compact phrase index can help more accurately estimate the score upper bounds of unknown documents. the size of the phrase index is controlled by including a small portion of phrases which are possibly helpful for improving search performance. phrase index has been used to process phrase queries in existing work. it is, however, to the best of our knowledge, the first time that phrase index is used to improve the performance of generic queries. experimental results show that, compared with the state-of-the-art top-k computation approaches, our approach can reduce average query processing time to 1/5 for typical setttings.
medsearch: a specialized search engine for medical information retrieval. people are thirsty for medical information. existing web search engines often cannot handle medical search well because they do not consider its special requirements. often a medical information searcher is uncertain about his exact questions and unfamiliar with medical terminology. therefore, he sometimes prefers to pose long queries, describing his symptoms and situation in plain english, and receive comprehensive, relevant information from search results. this paper presents medsearch, a specialized medical web search engine, to address these challenges. medsearch uses several key techniques to improve its usability and the quality of search results. first, it accepts queries of extended length and reforms long queries into shorter queries by extracting a subset of important and representative words. this not only significantly increases the query processing speed but also improves the quality of search results. second, it provides diversified search results. lastly, it suggests related medical phrases to help the user quickly digest search results and refine the query. we evaluated medsearch using medical questions posted on medical discussion forums. the results show that medsearch can handle various medical queries effectively and efficiently.
efficient techniques for document sanitization. sanitization of a document involves removing sensitive information from the document, so that it may be distributed to a broader audience. such sanitization is needed while declassifying documents involving sensitive or confidential information such as corporate emails, intelligence reports, medical records, etc. in this paper, we present the erase framework for performing document sanitization in an automated manner. erase can be used to sanitize a document dynamically, so that different users get different views of the same document based on what they are authorized to know. we formalize the problem and present algorithms used in erase for finding the appropriate terms to remove from the document. our preliminary experimental study demonstrates the efficiency and efficacy of the proposed algorithms.
structural relevance: a common basis for the evaluation of structured document retrieval. this paper presents a unified framework for the evaluation of a range of structured document retrieval (sdr) approaches and tasks. the framework is based on a model of tree retrieval, evaluated using a novel extension of the structural elevance (sr) measure. the measure replaces the assumption of independence in traditional information retrieval (ir) with a notion of redundancy that takes into account the user navigation inside documents while seeking relevant information. unlike existing metrics for sdr, our proposed framework does not require the computation of an ideal ranking which has, thus far, prevented the practical application of such measures. instead, sr builds on a markovian model of user navigation that can be estimated through the use of structural summaries. the results of this paper (supported by experimental validation using inex data) show that sr defined over a tree retrieval model can provide a common basis for the evaluation of sdr approaches across various structured search tasks.
tag-based filtering for personalized bookmark recommendations. this paper investigates using social tags for the purpose of making personalized content recommendations. our tag-based recommender creates a personalized bookmark recommendation model for each user based on "current" and "general interest" tags, defined by different time intervals.
a pattern-based analyzer for french in the context of spoken language translation: first prototype and evaluation. in this paper, we describe a first prototype of a pattern-based analyzer developed in the context of a speech-to-speech translation project using a pivot-based approach (the pivot is called if). the chosen situation involves a french client talking to an italian travel agent (both in their own language) to organize a stay in the trentino area.an if consists of a dialogue act, and a list, possibly empty, of argument values. the analyzer applies a "phrase spotting" mechanism on the output of the speech recognition module. it finds well-formed phrases corresponding to argument values. a dialogue act is then built according to the instantiated arguments and some other features of the input.the current version of the prototype has been involved in an evaluation campaign on an unseen corpus of four dialogues consisting of 235 speech turns. the results are given and commented in the last part of the paper. we think they pave the way for future enhancements to both the coverage and the development methodology.
lhip: extended dcgs for configurable robust parsing. we present lhip, a system for incremental grammar development using an extended dcg for malism. the system uses a robust island-based parsing method controlled by user-defined performance thresholds.
uniform recognition for acyclic context-sensitive grammars is np-complete. context-sensitive grammars in which each rule is of the form &alpha;z&beta; &rarr; &alpha;&gamma;&beta; are acyclic if the associated context-free grammar with the rules z &rarr; &gamma; is acyclic. the problem whether an input string is in the language generated by an acyclic context-sensitive grammar is np-complete.
a solution for the problem of interactive disambiguation. after the experiences of dialogue based mt systems with its [9], n-tran [6] and kbmt-89 [5], the lidia project aims at the construction of a mock-up of a personal mt system for a monolingual user. one major aspect of the lidia project is thus, the study of a dialogue of standardization and disambiguation between the system and the user so as to produce a high quality translation. this dialogue satisfies two properties: its questions are explicit, so no linguistic knowledge is required; its questions are monolingual, so no foreign language knowledge is needed. here, we focus on one part of the disambiguation process: the disambiguation of the structure produced by the analyser. the structure produced by our analyser is called mmc (multisolution, multilevel and concrete). multisolution means that the analyser produces every analysis fitting with the syntagmatic, syntactic and logico-semantic model of the grammar (an example is shown fig. 1). multilevel means that the same structure consists of three levels of linguistic interpretation, namely the level of syntactic and syntagmatic classes, the level of syntactic functions and the level of logic and semantic relations. finally, the structure is said to be concrete because the original utterance can be found back by a simple left-to-right reading of the structure. we have taken into account three kinds of differences between the solutions produced for one sentence, and each kind of difference is associated with the name of an ambiguity. we have defined ambiguities of syntactic classes (cf fig. 2), ambiguities of geometry (cf fig. 3) and ambiguities of syntactic, logic and semantic decoration (cf fig. 4). we have also defined three principles (&sect; iii. 1) to order the questions if there is more than one to be asked. the first principle is: first of all, find out the right segmentation into simple sentences. the second principle is: for each common predicate in the mmc structure, find out the right subject, objects and adjuncts. the last principle is: for each simple sentence, find the right structure. with those principles we are able to define a strategy (cf fig. 5). we have also isolated some patterns in the three classes of ambiguity. the class of ambiguities of syntactic classes needs no refinement (&sect; iii. 3.1). on the other hand we create four patterns of ambiguity of geometry (&sect; iii. 3.2) called: verbal coordination, argument structure of the verb, non verbal coordination, subordination; and three patterns of ambiguity of syntactic, logic and semantic decoration (&sect; iii. 3.3) called: logico-semantic labelling, argument order of direct transitive verbs, syntactic labelling. here is an example with the interpretations for each pattern we have chosen: <i>problem of class</i>. le pilote ferme la porte: the firm pilot carries her. the pilot shuts the door. <i>problem of verbal coordination</i>. ii regarde la photo et la classe: he looks at the photograph and the class. he looks at the photograph and files it. <i>problem of the argument structure of the verb</i>. ii parle de l'&eacute;cole de cuisine: he talks about the cooking school. he talks from the cooking school. he talks from the school about cooking. <i>problem of non-verbal coordination</i>. ii prend des crayons et des cahiers noirs: he takes pencils and black notebooks. he takes black pencils and black notebooks. <i>problem of subordination</i>. l'&eacute;cole de cuisine lyonnaise est ferm&eacute;e: the lyonnaise cooking school is closed. the school of lyonnaise cooking is closed. <i>problem of logico-semantic labelling</i>. pierre fait porter des chocolats &agrave; lucie: pierre lets lucie carry chocolates. pierre gets chocolates to be delivered to lucie. <i>problem of argument order of direct transitive verbs</i>. quel auteur cite ce conf&eacute;rencier: which author this lecturer is quoting? which lecturer this author is quoting? <i>problem of syntactic labelling</i>. ii parle de la tour eiffel: he is talking about the eiffel tower. he is talking from the eiffel tower. for each pattern we have defined a method to produce the appropriate dialogue (&sect; iii. 3). these methods use two kinds of processing: projection and paraphrase. to build paraphrases we use basically three operators: an operator of semantic replacement of occurrence, an operator of permutation of groups of occurrences and an operator of distribution of occurrences. the examples (&sect; iv) give an idea. in conclusion we can say that our method is quite simple but fixed once and for all. we are going to study two points in the near future. the first one is to reduce the number of analysis and thus, by getting information from the user, reduce the time to spend on the disambiguation. the second is to try to build tools which will allow the linguist, designer of the linguistic part of the lidia system, to define its own methods of disambiguation.
feasible learnability of formal grammars and the theory of natural language acquisition. we propose to apply a complexity theoretic notion of feasible learnability called "polynomial learnability" to the evaluation of grammatical formalisms for linguistic description. polynomial learnability was originally defined by valiant in the context of boolean concept learning and subsequently generalized by blumer et al. to infinitary domains. we give a clear, intuitive exposition of this notion of learnability and what characteristics of a collection of languages may or many not help feasible learn ability under this paradigm. in particular, we present a novel, nontrivial constraint on the degree of "locality" of grammars which allows a rich class of mildly context sensitive languages to be feasibly learnable. we discuss possible implications of this observation to the theory of natural language acquisition.
improved iterative scaling can yield multiple globally optimal models with radically differing performance levels. log-linear models can be efficiently estimated using algorithms such as improved iterative scaling (iis) (lafferty et al., 1997). under certain conditions and for a particular class of problems, iis is guaranteed to approach both the maximum-likelihood and maximum entropy solution. this solution, in likelihood space, is unique. unfortunately, in realistic situations, multiple solutions may exist, all of which are equivalent to each other in terms of likelihood, but radically different from each other in terms of performance. we show that this behaviour can occur when a model contains overlapping features and the training material is sparse. experimental results, from the domain of parse selection for stochastic attribute value grammars, shows the wide variation in performance that can be found when estimating models using iis. further results show that the influence of the initial model can be diminished by selecting either uniform weights, or else by model averaging.
a kana-kanji translation system for non-segmented input sentences based on syntactic and semantic analysis. this paper presents a disambiguation approach for translating non-segmented-kana into kanji. the method consists of two steps. in the first step, an input sentence is analyzed morphologically and ambiguous morphemes are stored in a network form. in the second step, the best path, which is a string of morphemes, is selected by syntactic and semantic analysis based on case grammar. in order to avoid the combinatorial explosion of possible paths, the following heuristic search method is adopted. first, a path that contains the smallest number of weighted-morphemes is chosen as the quasi-best path by a best-first-search technique. next, the restricted range of morphemes near the quasi-best path is extracted from the morpheme network to construct preferential paths.an experimental system incorporating large dictionaries has been developed and evaluated. a translation accracy of 90.5% was obtained. this can be improved to about 95% by optimizing the dictionaries.
bootstrapping bilingual data using consensus translation for a multilingual instant messaging system. one of the primary issues in training statistical translation models is the paucity of bilingual data. in this paper, we propose techniques to alleviate the bilingual data bottleneck by creating a consensus from translations of monolingual data provided by several off-the-shelf translation engines. we compute the consensus alignment using a multi-sequence alignment algorithm used for dna sequence alignment. we present an application of this technique to bootstrap bilingual data for the general domain of instant messaging. we train hierarchical statistical translation models on the bootstrapped bilingual data and show that the resulting statistical translation model outperforms each individual off-the-shelf translation system.
a learning of object structures by verbalism. in this paper an attempt of learning by verbalism is shown in order to create the models for ancidentification of unknown objects. when we expect a computer to recognize objects, the models of them must be given to it, however there are cases where some objects may not be, matched to the models or there is no model with which object is compared. at that time, this system can augment or create new descriptions by being explicitly taught using verbal instructions.
exploiting a probabilistic hierarchical model for generation. previous stochastic approaches to generation do not include a tree-based representation of syntax. while this may be adequate or even advantageous for some applications, other applications profit from using as much syntactic knowledge as is available, leaving to a stochastic model only those issues that are not determined by the grammar. we present initial results showing that a tree-based model derived from a tree-annotated corpus improves on a tree model derived from an unannotated corpus, and that a tree-based stochastic model with a hand-crafted grammar outperforms both.
on froff: a text processing system for english texts and figures. in order to meet the needs of a publication of papers in english, many systems to run off texts have been developed. in this paper, we report a system froff which can make a fair copy of not only texts but also graphs and tables indispensable to our papers. its selection of fonts, specification of character size are dinamically changeable, and the typing location can be also changed in lateral or longitudinal directions. each character has its own width and a line length is counted by the sum of each character. by using commands or rules which are defined to facilitate the construction of format expected or some mathematical expressions, elaborate and pretty documments can be successfully obtained.
incremental identification of inflectional types. we present an approach to the incremental accrual of lexical information for unknown words that is constraint-based and compatible with standard unification-based grammars. although the techniques are language-independent and can be applied to all kinds of information, in this paper we concentrate on the domain of german noun inflection. we show how morphological information, especially inflectional class, is successfully acquired using a type-based hpsg-like analysis. furthermore, we sketch an alternative strategy which makes use of finite-state transducers.
parsing french with tree adjoining grammar: some linguistic accounts. we present the first sizable grammar written for tag. we present the linguistic coverage of our grammar, and explain the linguistic reasons which lead us to choose the particular representations. we show that tag formalism provides sufficient constraints for handling most of the linguistic phenomena, with minimal linguistic stipulations. we first state the basic structures needed for parsing french, with a particular emphasis on tag's extended domain of locality that enables us to state complex sub-categorization phenomena in a natural way. we then give a detailed analysis of sentential complements, because it has lead us to introduce substitution in the formalism, and because tag makes interesting predictions. we discuss the different linguistic phenomena corresponding to adjunction and to substitution respectively. we then move on to support verb constructions, which are represented in a tag in a simpler way than the usual double analysis. it is the first time support verb constructions are handled in a parser. we lastly give an overview of the treatment of adverbs, and suggest a treatment of idioms which make them fall into the same representations as 'free' structures.
reasoning in metaphor understanding: the att-meta approach and system. a detailed approach has been developed for core aspects of the task of understanding a broad class of metaphorical utterances. the utterances in question are those that depend on known metaphorical mappings but that nevertheless contain elements not mapped by those mappings. a reasoning system has been implemented that partially instantiates the theoretical approach. the system, called att meta, will be demonstrated. the paper briefly indicates how the system works, and outlines some specific aspects of the system, approach and the overall project.
a word database for natural language processing. the paper describes the design of a fair sized lexical database that is to be used with a natural language based expert system with german as the language of interaction. sources for entries and tools for constructing and maintaining the database are discussed, as well as the information needed in the lexicon for the purposes of syntactic and semantic processing.
using lexicalized tags for machine translation. lexicalized tree adjoining grammar (ltag) is an attractive formalism for linguistic description mainly because of its extended domain of locality and its factoring recursion out from the domain of local dependencies (joshi, 1985, kroch and joshi, 1985, abeill&eacute;, 1988). ltag's extended domain of locality enables one to localize syntactic dependencies (such as filler-gap), as well as semantic dependencies (such as predicate-arguments). the aim of this paper is to show that these properties combined with the lexicalized property of ltag are especially attractive for machine translation.the transfer between two languages, such as french and english, can be done by putting directly into correspondence large elementary units without going through some interlingual representation and without major changes to the source and target grammars. the underlying formalism for the transfer is "synchronous tree adjoining grammars" (shieber and schabes [1990]). transfer rules are stated as correspondences between nodes of trees of large domain of locality which are associated with words. we can thus define lexical transfer rules that avoid the defects of a mere word-to-word approach but still benefit from the simplicity and elegance of a lexical approach.we rely on the french and english ltag grammars (abeill&eacute; [1988], abeille [1990 (b)], abeille et al. [1990], abeille and schabes [1989, 1990]) that have been designed over the past two years jointly at university of pennsylvania and university of paris 7-jussieu.
wordform- and class-based prediction of the components of german nominal compounds in an aac system. in word prediction systems for augmentative and alternative communication (aac), productive word-formation processes such as compounding pose a serious problem. we present a model that predicts german nominal compounds by splitting them into their modifier and head components, instead of trying to predict them as a whole. the model is improved further by the use of class-based modifier-head bigrams constructed using semantic classes automatically extracted from a corpus. the evaluation shows that the split compound model with class bigrams leads to an improvement in keystroke savings of more than 15% over a no split compound baseline model. we also present preliminary results obtained with a word prediction model integrating compound and simple word prediction.
extending drt with a focusing mechanism for pronominal anaphora and ellipsis resolution. cormack (1992) proposed a framework for pronominal anaphora resolution. her proposal integrates focusing theory (sidner et al.) and drt (kamp and reyle). we analyzed this methodology and adjusted it to the processing of portuguese texts. the scope of the framework was widened to cover sentences containing restrictive relative clauses and subject ellipsis. tests were conceived and applied to probe the adequacy of proposed modifications when dealing with processing of current texts.
concept clustering and knowledge integration from a children's dictionary. knowledge structure called concept clustering knowledge graphs (cckgs) are introduced along with a process for their construction from a machine readable dictionary. cckgs contain multiple concepts interrelated through multiple semantic relations together forming a semantic cluster represented by a conceptual graph. the knowledge acquisition is performed on a children's first dictionary. the concepts involved are general and typical of a daily life conversation. a collection of conceptual clusters together can form the basis of a lexical knowledge base, where each cckg contains a limited number of highly connected words giving useful information about a particular domain or situation.
interaction between lexicon and image: linguistic specifications of animation. certains textes d'une langue peuvent &ecirc;tre consid&eacute;r&eacute;s comme des sp&eacute;cifications linguistiques capables d'engendrer des animations qui simulent la compr&eacute;hension des textes d'entr&eacute;e. pour r&eacute;aliser un tel programme, il nous semble indispensable de construire des repr&eacute;sentations interm&eacute;diaires compatibles, d'un c&ocirc;t&eacute; avec les descriptions s&eacute;mantiques d'unit&eacute;s linguistiques, et d'un autre c&ocirc;t&eacute; avec des sp&eacute;cifications d'animation d'images. comprendre un texte relatif &agrave; des mouvements spatiaux revient: i) &agrave; repr&eacute;senter s&eacute;mantiquement le texte; ii) &agrave; engendrer une animation mettant en jeu des images; cette animation vise &agrave; reproduire ce qui est compris lors de la lecture du texte. ce programme ambitieux suppose qu'au pr&eacute;alable chaque verbe ait des repr&eacute;sentations que nous appelons sch&egrave;mes s&eacute;mantico-cognitifs (ssc), correspondant aux diff&eacute;rentes significations du verbe. tout sch&eacute;ma de mouvement associ&eacute; &agrave; la signification d'un verbe repr&eacute;sente trois types de connaissances: i) des d&eacute;clarations et des relations invariantes pendant le mouvement; ii) la description cin&eacute;matique du mouvement qui fait passer d'une phase initiale (sit<inf>1</inf>) &agrave; une phase finale (sit<inf>2</inf>); iii) les conditions dynamiques &eacute;ventuelles qui rendent possibles ou qui contr&ocirc;lent le mouvement cin&eacute;matique. nous reprenons l'approche de r. schank ou de j. sowa qui remet en cause une association directe mot-concept pour adopter une d&eacute;composition de la signification des unit&eacute;s linguistiques en &eacute;l&eacute;ments de "sens" plus petits. notre formalisme a pour but d'une part, de mieux traiter les probl&egrave;mes de temps, et d'autre part, de fonder notre cheix de primitives, dans le cadre d'une th&eacute;orie qui articule les niveaux de repr&eacute;sentation linguistiques et cognitifs. introduisons quelques distinctions: 1- le verbe est une entit&eacute; lexicale qui peut &ecirc;tre polys&eacute;mique. ex: <i>circuler</i>. 2- le verbe syntaxique entre dans une construction syntaxique. ex: n<inf>1</inf> circuler prep n<inf><i>loc.</i></inf> 3- le pr&eacute;dicat logique n-aire est associ&eacute; au verbe syntaxique. ex: circuler est l'expression du pr&eacute;dicat 1-aire circuler<inf>1</inf>. 4- a un pr&eacute;dicat correspondent un ou plusieurs sens, d&eacute;sign&eacute;s par /verbe<sup><i>i</i></sup>/, repr&eacute;sent&eacute;s chacun par un ssc. un ssc est organis&eacute; &agrave; partir de primitives cognitives; il conduit &agrave; une repr&eacute;sentation cognitive d&egrave;s qu'il est instanci&eacute;. 5- l'arch&eacute;type cognitif not&eacute;/verbe/, s'il existe, se pr&eacute;sente alors comme "le sens abstrait" commun &agrave; tous les ssc d'une m&ecirc;me entr&eacute;e lexicale polys&eacute;mique. la construction de l'arch&eacute;type repose sur une organisation des ssc en r&eacute;seau. elle utilise une description analogue &agrave; celle de j. picoche. a partir de l'exemple d'un texte fran&ccedil;ais qui repr&eacute;sente des mouvements spatio-temporels, nous donnerons pour quelques verbe du texte les ssc et les animations correspondantes. l'animation compl&egrave;te d&eacute;clench&eacute;e par la compr&eacute;hension de texte n&eacute;cessite cette premi&egrave;re phase de recherche. les sch&egrave;mes que nous proposons sont int&eacute;grables dans un dictionnaire s&eacute;mantique du fran&ccedil;ais. notre &eacute;tude pr&eacute;sentera &agrave; partir de l'exemple choisi la m&eacute;thodologie appuy&eacute;e par une r&eacute;alisation. <u>mots-cl&eacute;s:</u> {<i>compr&eacute;hension de texte, repr&eacute;sentation des connaissances dynamiques, lexique verbal, m&eacute;thodologie, choiz de primitives s&eacute;mantico-cognitives, verbes de mouvement, analyse d'un texte, dictionnaire s&eacute;mantique, sp&eacute;cification linguistique et animation</i>}
a modular architecture for constraint-based parsing. this paper presents a framework and a system for implementing, comparing and analyzing parsers for the some classes of constraint-based grammars. the framework consists in a uniform theoretic description of parsing algorithms, and provides the structure for decomposing the system into logical components, with possibly several interchangeable implementations. many parsing algorithms can be obtained by composition of the modules of our system. modularity is also a way of achieving code sharing for the common parts of these various algorithms. furthemore, the design helps reusing the existing modules when implementing, other algorithms. the system uses the flexible modularity provided by the programing languages alcool-90, based on a type system that ensures the safety of module composition.
a logic programming view of relational morphology. we use the more abstract term "relational morphology" in place of tile usual "two-level morphology" in order to emphasize an aspect of koskenniemi's work which has been overlooked in favor of implementation issues using the finite state paradigm, namely, that a mathematical relation can be specified between the lexical and surface levels of a language. relations, whether finite state or not, can be computed using any of several paradigms, and we present a logical reading of a notation for relational morphological rules (similar to that of koskenniemi's) which can in fact be used to automatically generate prolog program clauses. like the finite state implementations, the relation can be computed in either direction, either from the surface to the lexieal level, or vice versa. at rite very least, this provides a morphological complement to logic grammars which deal mainly with syntax and semantics, in a programming environment which is more user-friendly than the finite state programming paradigm. the morphological rules often compile simply into unification of the arguments in the generated morphology predicate followed by a recursive call of the said predicate. further speed can be obtained when a prolog compiler, rather than an interpreter, is used for execution.
a "not-so-shallow" parser for collocational analysis. collocational analysis is the basis of many studies on lexical acquisition. collocations are extracted from corpora using more or less shallow processing techniques, that span from purely statistical methods to patial parsers. our point is that, despite one of the objectives of collocational analysis is to acquire high-coverage lexical data at low human cost, this is often not the case. human work is in fact required for the initial training of most statistically based methods. a more serious problem is that shallow processing techniques produce a noise that is not acceptable for a fully automated system.we propose in this paper a not-so-shallow parsing strategy that reliably detects binary and ternary relations among words. we show that adding more syntactic knowledge to the recipe significantly improves the recall and precision of the detected collocations, regardless of any subsequent statistical computation, while still meeting the computational requirements of corpus parsers.
decision trees as explicit domain term definitions. terminology acquisition (ta) methods are viable solutions for the knowledge bottleneck problem that confines knowledge-intensive information access systems (such as information extraction systems) to restricted application scenarios. ta can be seen as a way to inspect large text collections for extracting concise domain knowledge. in this paper we argue that major insights over the notion of term can be obtained by investigating a more domain-based term definition. we propose a decision tree learning approach as an interesting model of the human ta activity. an incremental model is proposed to study the evolution of the term definition during the ta process over a particular implicit domain model. the experimental apparatus is based on robust text processing tools that support a large scale investigation. the good results suggest that the proposed automatic ta model can support the development of conceptual domain dictionaries as required by knowledge-based information systems.
cognitive models for computer vision. this paper is focused on the relations existing between language and vision. its goal is to discuss how linguistic informations about objects, shapes, positions and spatial relations with other objects can be integrated into a cognitive model tailored to spatial inferencing operations.
finding translation equivalents: an application of grammatical metaphor. in this paper i describe how a significant class of cases that would involve (possibly complex) structural transfer in machine translation can be handled avoiding transfer. this is achieved by applying a semantic organization developed for monolingual text generation that is sufficiently abstract to remain invariant, within theoretically specifiable limits, across different languages. the further application of a mechanism motivated from within monolingual text generation, 'grammatical metaphor', then allows candidate appropriate translations to be isolated. the incorporation of these essentially monolingual mechanisms within the machine translation process promises to significantly improve translational capabilities; examples of this are presented for english and german.
natural language driven image generation. in this paper the experience made through the development of a natural language driven image generation is discussed. this system is able to imagine a static scene described by means of a sequence of simple phrases. in particular, a theory for equilibrium and support will be outlined together with the problem of object positioning.
the nondirectional representation of systemic functional grammars and semantics as typed feature structures. a small fragment of the systemic functional grammar of the penman system is reformulated in the typed feature structure language. through this reformulation we gain full reversibility for the sfg description and access for unification-based grammar descriptions to the rich semantic levels of description that sfg supports. we illustrate this reformulation with respect to both generation and semantic analysis and set out the future goals for research this result establishes.
converting large on-line valency dictionaries for nlp applications: from proton descriptions to metal frames. in this paper, we report on a large-scale conversion experiment with on-line valency dictionaries. a linguistically motivated valency dictionary in prolog is converted into a valency dictionary for a large-scale machine translation system. several aspects of the two dictionaries and their background projects are discussed, as well as the way their representations are mapped. the results of the conversion are looked at from an economic perspective (fast conding for nlp), and also from a computational-lexicographic perspective (requirements for conversions and for standardization of lexicon information).
integrating syntactic and prosodic information for the efficient detection of empty categories. we describe a number of experiments that demonstrate the usefulness of prosodic information for a processing module which parses spoken utterances with a feature-based grammar employing empty categories. we show that by requiring certain prosodic properties from those positions in the input, where the presence of an empty category has to be hypothesized, a derivation can be accomplished more efficiently. the approach has been implemented in the machine translation project verbmobil and results in a significant reduction of the work-load for the parser.
from cogram to alcogram: toward a controlled english grammar checker. in this paper we describe the roots of controlled english (ce), the analysis of several existing ce grammars, the development of a well-founded 150-rule ce grammar (cogram), the elaboration of an algorithmic variant (alcogram) as a basis for nlp applications, the use of alcogram in a cai program teaching writers how to use it effectively, and the preparatory study into a controlled english grammar and style checker within a desktop publishing (dtp) environment.
customizing and evaluating a multilingual discourse module. in this paper, we first describe how we have customized our data-driven multilingual discourse module within our text understanding system for different languages and for a particular nlp application by utilizing hierarchically organized discourse kb's. then, we report quantitative and qualitative findings from evaluating the system both with and without discourse processing, and discuss how resolving certain kinds of anaphora affects system performance.
an empirical evaluation of lfg-dop. this paper presents an empirical assessment of the lfg-dop model introduced by bod & kaplan (1998). the parser we describe uses fragments from lfg-annotated sentences to parse new sentences and monte carlo techniques to compute the most probable parse. while our main goal is to test bod & kaplan's model, we will also test a version of lfg-dop which treats generalized fragments as previously unseen events. experiments with the verbmobil and homecentre corpora show that our version of lfg-dop outperforms bod & kaplan's model, and that lfg's functional information improves the parse accuracy of tree structures.
a word-grammar based morphological analyzer for agglutinative languages. agglutinative languages present rich morphology and for some applications they need deep analysis at word level. the work here presented proposes a model for designing a full morphological analyzer.the model integrates the two-level formalism and a unification-based formalism. in contrast to other works, we propose to separate the treatment of sequential and non-sequential morphotactic constraints. sequential constraints are applied in the segmentation phase, and non-sequential ones in the final feature-combination phase. early application of sequential morphotactic constraints during the segmentation process makes feasible an efficient implementation of the full morphological analyzer.the result of this research has been the design and implementation of a full morphosyntactic analysis procedure for each word in unrestricted basque texts.
tge: tlinks generation environment. this paper describes the enhancements made, within a unification framework, based on typed feature structures, in order to support linking of lexical entries to their translation equivalents. to help this task we have developed an interactive environment: tge. several experiments, corresponding to rather "closed" semantic domains, have been developed in order to generate lexical cross-relations between english and spanish.
efficiency considerations for lfg-parsers - incremental and table-lookup techniques. the paper presents a concise description of the lfg-parser-generator developed at the ewh in koblenz. special attention is paid to efficiency considerations to speed up the system in the execution phase. lexicon is separated, 11(k)-parsing tables are used and some preliminary unifications are carried out before the actual execution. the run time system follows the single path strategy and produces the f-structures simultaneously with the processing of the c-structures.
a morphological recognizer with syntactic and phonological rules. this paper describes a morphological analyzer which, when parsing a word, uses two sets of rules: rules describing the syntax of words, and rules describing facts about orthography.
word sense disambiguation using conceptual density. this paper present a method for the resolution of lexical ambiguity of nouns and its automatic evaluation over the brown corpus. the method relies on the use of the wide-coverage noun taxonomy of wordnet and the notion of conceptual distance among concepts, captured by a conceptual density formula developed for this purpose. this fully automatic method requires no hand coding of lexical entries, hand tagging of text nor any kind of training process. the results of the experiments have been automatically evaluted against semcor, the sense-tagged version of the brown corpus.
functional constraints in knowledge-based natural language understanding. many knowledge-based systems of semantic interpretation rely explicitly or implicitly on an assumption of structural isomorphy between syntactic and semantic objects, handling exceptions by ad hoc measures. in this paper i argue that constraint equations of the kind used in the lfg- (or patr-) fomalisms provide a more general, and yet restricted formalism in which not only isomorphic correspondences are expressible, but also many cases of non-isomorphic correspondences. i illustrate with treatments of idioms, speech act interpretation and discourse pragmatics.
backwards phonology. this paper constitutes an investigation into the generative capabilities of two-level phonology with respect to unilevel generative phonological rules. proponents of two-level phonology have claimed, but not demonstrated, that two-level rules and grammars of two-level rules are reversible and that grammars of unilevel rules are not. this paper makes "reversibility" explicit and demonstrates by means of examples from tunica and klamath that two-level phonology does have certain desirable cababilities that are not found in grammars of unilevel rules.
a grammar combining phrase structure and field structure. a grammar formalism, field and category grammar (fcg), is described, which beside constituent structure and functional structure recognizes a level of field structure. it is argued that the formalism offers descriptive and computational advantages for the analysis of scandinavian and other languages that distinguish clause types topologically. it is also argued that the clear distinction between fields and constituents makes fcgs theoretically sounder than other proposed field grammars. a comparison is made of the word order rules and assumptions of fcgs with the partial orderings employed by gpsg and other models.
storing text using integer codes. traditionally, text is stored on computers as a stream of characters. the goal of this research is to store text in a form that facilitates word manipulation whilst reducing storage space. a word list with syntactic linear ordering is stored and words in a text are given two-byte integar codes that point to their respective positions in this list. the implementation of the encoding scheme is described and the performance statistics of this encoding scheme is presented.
machine translation using isomorphic ucgs. this paper discusses the application of unification categorial grammar (ucg) to the framework of isomorphic grammars for machine translation pioneered by landsbergen. the isomorphic grammars approach to mt involves developing the grammars of the source and target languages in parallel, in order to ensure that sl and tl expressions which stand in the translation relation have isomorphic derivations. the principle advantage of this approach is that knowledge concerning translation equivalence of expressions may be directly exploited, obviating the need for answers to semantic questions that we do not yet have. semantic and other information may still be incorporated, but as constraints on the translation relation, not as levels of textual representation.after introducing this approach to mt system design, and the basics of monolingual ucg, we will show how the two can be integrated, and present an example from an implemented bi-directional english-spanish fragment. finally we will present some outstanding problems with the approach.
a method of cluster-based indexing of textual data. this paper presents a framework for clustering in text-based information retrieval systems. the prominent feature of the proposed method is that documents, terms, and other related elements of textual information are clustered simultaneously into small overlapping clusters. in the paper, the mathematical formulation and implementation of the clustering method are briefly introduced, together with some experimental results.
a compositional approach to the translation of temporal expression in the rosetta system. this paper discusses the translation of temporal expressions, in the framework of the machine translation system rosetta. the translation method of rosetta, the 'isomorphic grammar method', is based on montague's compositionality principle. it is shown that a compositional approach leads to a transparent account of the complex aspects of time in natural language and can be used for the translation of temporal expressions.
a computational model of language performance: data oriented parsing. data oriented parsing (dop) is a model where no abstract rules, but language experiences in the form of an analyzed corpus, constitute the basis for language processing. analyzing a new input means that the system attempts to find the most probable way to reconstruct the input out of fragments that already exist in the corpus. disambiguation occurs as a side-effect dop can be implemented by using conventional parsing strategies.
a machine translation system for foreign news in satellite broadcasting. a machine translation system of english to japanese is described, which has been used in 24-hour direct satellite broadcasting by nhk to translate "world news."in order to treat a wide scope of news sentences, the system is provided with more than 100,000 lexical entries as well as about 3,000 grammatical rules which can robustly analyze various types of undefined words. it is also effective in translation of news sentences to preprocess proper nouns, to resolve structural ambiguities by weighting grammatical rules, and to select appropriate words using semantic markers. the operational experiments on machine translation in satellite broadcasting are briefly discussed.
the e-framework: a formalism for natural language processing. this paper presents the most important characteristic of the new formalism used in eurotra, the e-framework. it is a formalism for natural language processing within a stratificational model.in the e-framework, mapping between levels of representation is performed on the basis of transitions between trees and partial descriptions of objects, called descriptors. these descriptors are completed using the definition of the target level.the tree to descriptor strategy simplifies the expression of complex two-way relations between text and abstract representations when major structural changes have to be performed on the input. this is illustrated by way of a detailed example showing the interaction of the two formal devices of the e-framework, the translator and the generator, the basic ideas of which are also briefly described.the e-framework has been implemented and forms the basis of the development of eurotra's pre-industrial prototype of a transfer-based, multi-lingual machine translation system.
using a natural-artificial hybrid language for database access. in this paper we propose a natural-artificial hybrid language for database access. the global construction of a sentence in this language is highly schematic, but allows expressions in the chosen language such as japanese or english. its artificial language part, sml, is closely related to our newly introduced data model, called scaled lattice. adopting japanese as its natural language part, we implemented a japanese-sml hybrid language processing system for our compact database system sclams, whose database consists of scaled lattices. the main features of this implementation are (1) a small lexicon and limited grammar, and (2) an almost free form in writing kana japanese.
a stochastic topological parser for german. we present a new approach to topological parsing of german which is corpus-based and built on a simple model of probabilistic cfg parsing. the topological field model of german provides a linguistically motivated, flat macro structure for complex sentences. besides the practical aspect of developing a robust and accurate topological parser for hybrid shallow and deep nlp, we investigate to what extent topological structures can be handled by context-free probabilistic models. we discuss experiments with systematic variants of a topological treebank grammar, which yield competitive results.
arabic finite-state morphological analysis and generation. this paper describes a large-scale system that performs morphological analysis and generation of on-line arabic words represented in the standard orthography, whether fully voweled, partially voweled or unvoweled. analyses display the root, pattern and all other affixes together with feature tags indicating part of speech, person, number, mood, voice, aspect, etc. the system is based on lexicons and rules from an earlier kimmo-style two-level morpholgical system, reworked extensively using xerox finite-state morphology tools. the results is an arabic finite-state lexical transducer that is applied with the same runtime code used for english, french, german, spanish, portuguese, dutch and italian lexical transducers.
methodology and verifiability in montague grammar. methodological problems in montague grammar are discussed. our observations show that a model-theoretic approach to natural language semantics in inadequate with respect to its verifiability from logical point of view. but, the formal attitudes seem to be of use for the development in computational linguistics.
periphrase: lingware for parsing and structural transfer. periphrase is a high-level computer language developed by a.l.p. systems to facilitate parsing and structural transfer. it is designed to speed the development of computer-assisted translation systems and grammar checkers. we describe the syntax and semantics of this tool, its integrated development environment, and some of our experience with it.
situational investigation of presupposition. this paper gives a formal theory of presupposition using situation semantics developed by barwise and perry. we will slightly modify barwise and perry's original theory of situation semantics so that we can deal with non-monatonic reasonings which are very important for the formalization of presupposition in natural language. this aspect is closely related to the formalization of incomplete knowledge in artificial intelligence.
knowledge representation method based on predicate calculus in an intelligent cai system. the knowledge representation method is introduced to be applied in the icai system to teach programming language. knowledge about syntax and semantios of that language is represented by a set of axioms written in the predicate calculus language. the directed graph of concepts is mentioned as a method to represent an instructional structure of the domain knowledge. the proof procedure to answer student's questions is described.
consequence relations in drt. we discuss some consequence relations in drt useful to discourse semantics. we incorporate some consequence relations into drt using sequent calculi. we also show some connections of these consequence relations and existing partial logics. our attempt enables us to display several versions of drt by employing different consequence relations.
feature graphs and abstract data types: a unifying approach. feature graphs appearing in unification-based grammar formalisms and algebraic specifications of abstract data types (adts) are both used for defining a collection of objects together with functions between these object sets. starting from this observation we define an algebraic semantics for feature graphs by assigning an algebraic specification to each feature graph. this opens the rich world of semantical foundations for abstract data types to the area of feature graphs and thus to unification grammar formalisms. using results from adt theory we define a simple and fast syntactic decision procedure testing the usual consistency, constant/complex consistency and acyclicity on the algebraic specification assigned to a feature graph. with this machinery at hand feature graph unification becomes union of feature graph specifications followed by the consistency test.
a bayesian approach for user modeling in dialogue systems. user modeling is an important components of dialog systems. most previous approaches are rule-based methods. in this paper, we propose to represent user models through bayesian networks. some advantages of the bayesian approach over the rule-based approach are as follows. first, rules for updating user models are not necessary because updating is directly performed by the evaluation of the network based on probability theory; this provides us a more formal way of dealing with uncertainties. second, the bayesian network provides more detailed information of users' knowledge, because the degree of belief on each concept is provided in terms of probability. we prove these advantages through a preliminary experiment.
learning grammars for different parsing tasks by partition search. this paper describes a comparative application of grammar learning by partition search to four different learning tasks: deep parsing, np identification, flat phrase chunking and np chunking. in the experiments, base grammars were extracted from a treebank corpus. from this starting point, new grammars optimised for the different parsing tasks were learnt by partition search. no lexical information was used. in half of the experiments, local structural context in the form of parent phrase category information was incorporated into the grammars. results show that grammars which contain this information outperform grammars which do not by large margins in all tests for all parsing tasks. it makes the biggest difference for deep parsing, typically corresponding to an improvement of around 5%. overall, partition search with parent phrase category information is shown to be a successful method for learning grammars optimised for a given parsing task, and for minimising grammar size. the biggest margin of improvement over a base grammar was a 5.4% increase in the f-score for deep parsing. the biggest size reductions were 93.5% fewer nonterminals (for np identification), and 31.3% fewer rules (for xp chunking)
using language and translation models to select the best among outputs from multiple mt systems. this paper addresses the problem of automatically selecting the best among outputs from multiple machine translation (mt) systems. existing approaches select the output assigned the highest score according to a target language model. in some cases, the existing approaches do not work well. this paper proposes two methods to improve performance. the first method is based on a multiple comparison test and checks whether a score from language and translation models is significantly higher than the others. the second method is based on probability that a translation is not inferior to the others, which is predicted from the above scores. experimental results show that the proposed methods achieve an improvement of 2 to 6% in performance.
weakly restricted stochastic grammars. a new type of stochastic grammars in introduced for investigation: weakly restricted stochastic grammars. in this paper we will concentrate on the consistency problem. to find conditions for stochastic grammars to be consistent, the theory of multitype galton-watson brancning processes and generating functions is of central importance. the unrestricted stochastic grammar formalism generates the same class of languages as the weakly restricted formalism. the inside-outside algorithm is adapted for use with weakly restricted grammars.
unsupervised learning of a rule-based spanish part of speech tagger. this paper describes a spanish part-of-speech (pos) tagger which applies and extends brill's algorithm for unsupervised learning of rule-based taggers (brill, 1995). first, we discuss our general approach including extensions we made to the algorithm in order to handle unknown words and parameterize learning and tagging options. next, we report and analyze our experimental results using different parameters. then, we describe our "hybrid" approach which was necessary in order to overcome a fundamental limitation in brill's original algorithm. finally, we compare our tagger with hidden markov model (hmm)-based taggers.
compilation of unification grammars with compositional semantics to speech recognition packages. in this paper a method to compile unification grammars into speech recognition packages is presented, and in particular, rules are specified to transfer the compositional semantics stated in unification grammars into speech recognition grammars. the resulting compiler creates a context-free backbone of the unification grammar, eliminates left-recursive productions and removes redundant grammar rules. the method was tested on a medium-sized unification grammar for english using nuance speech recognition software on a corpus of 131 utterances of 12 different speakers. results showed no significant computational overhead with respect to speech recognition performances for speech recognition grammar with compositional semantics compared to grammars without.
rule merging in a rule-based arabic stemmer. semitic languages require more complicated systems for processing their morphology. arabic language, for example, exhibits a very complex but very regular morphological structure. many approaches were proposed to analyze arabic language at the morphological level. proposed approaches can be classified into table lookup, linguistic, combinatorial and rule-based techniques.this paper proposes a new approach to enhance a rule-based arabic stemmer. the enhancement is based on rule merging process to reduce number of rules, increase language coverage and maintain the same level of performance.
presupposition & vp-ellipsis. we discuss a treatment of vp-ellipsis resolution in drt in general, and particularly cases where the source clause of the elliptical vp contains presupposition triggers. we propose to restrain vp-ellipsis resolution by presupposition neutralization. we view presupposition as a kind of anaphora, with the ability to accommodate an antecedent if not provided by discourse.
automatic semantic grouping in a spoken language user interface toolkit. with the rapid growth of real application domains for nlp systems, there is a genuine demand for a general toolkit from which programmers with no linguistic knowledge can build specific nlp systems. such a toolkit should provide an interface to accept sample sentences and convert them into semantic representations so as to allow programmers to map them to domain actions. in order to reduce the workload of managing a large number of semantic forms individually, the toolkit will perform what we call semantic grouping to organize the forms into meaningful groups. in this paper, we present three semantic grouping methods: similarity-based, verb-based and category-based grouping, and their implementation in the slui toolkit. we also discuss the pros and cons of each method and how they can be utilized according to the different domain needs.
an evaluation to detect and correct erroneous characters wrongly substituted, deleted and inserted in japanese and english sentences using markov models. in optical character recognition and continuous speech recognition of a natural language, it has been difficult to detect error characters which are wrongly deleted and inserted. in order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a japanese "bunsetsu" and an english word, and to correct these errors, this paper proposes new methods using m-th order markov chain model for japanese "kanjikana" characters and english alphabets, assuming that markov probability of a correct chain of syllables or "kanji-kana" characters is greater than that of erroneous chains.from the results of the experiments, it is concluded that the methods is useful for detecting as well as correcting these errors in japanese "bunsetsu" and english words.
processing word order variation within a modified id/lp framework. from a well represented sample of world languages steele (1078) shows that about 70% of languages exhibit significant word order variation. only recently has this wide-spread phenomenon been drawing appropriate attention. perhaps id/lp (immediate dominance and linear precedence) framework is the most debated theories in this area. we point out some difficulties in processing standard id/lp grammar and present a modified version of the grammar. in the modified version, the right hand side of phrase structure rules is treated as a set or partially ordered set. an instance of the framework is implemented.
extending a broad-coverage parser for a general nlp toolkit. with the rapid growth of real world applications for nlp systems, there is a genuine demand for a general toolkit from which programmers with no linguistic knowledge can build specific nlp systems. such a toolkit should have a parser that is general enough to be used across domains, and yet accurate enough for each specific application. in this paper, we describe a parser that extends a broad-coverage parser, minipar (lin, 2001), with an adaptable shallow parser so as to achieve both generality and accuracy in handling domain specific nl problems. we test this parser on our corpus and the results show that the accuracy is significantly higher than a system that uses minipar alone.
some problems of machine translation between closely related languages. we describe the linguistic background of a czech-to-russian mt system, stressing its features resulting from the closed relatedness of the two languages, above all the possibility of a minimization of the transfer. related linguistic problems are analyzed within the mt project, as well as in the perspective of contrastive linguistics.
learning word clusters from data types. the paper illustrates a linguistic knowledge acquisition model making use of data types, infinite memory, and an inferential mechanism for inducing new information from known data. the model is compared with standard stochastic methods applied to data tokens, and tested on a task of lexico-semantic classification.
robust processing in machine translation. in this paper we provide an abstract characterisation of different kinds of robust processing in machine translation and natural language processing systems in terms of the kinds of problem they are supposed to solve. we focus on one problem which is typically exacerbated by robust processing, and for which we know of no existing solutions. we discuss two possible approaches to this, emphasising the need to correct or repair processing malfunctions.
an algorithm for identifying cognates between related languages. the algorithm takes as only input a list of words, preferably but not necessarily in phonemic transcription, in any two putatively related languages, and sorts it into decreasing order of probable cognation. the processing of a 250-item bilingual list takes about five seconds of cpu time on a dec kl1091, and requires 56 pages of core memory. the algorithm is given no information whatsoever about the phonemic transcription used, and even though cognate identification is carried out on the basis of a context-free one-for-one matching of individual characters, its cognation decisions are bettered by a trained linguist using more information only in cases of wordlists sharing less than 40% cognates and involving complex, multiple sound correspondences.
two methods for learning alt-j/e translation rules from examples and a semantic hierarchy. this paper presents our work towards the automatic acquisition of translation rules from japanese-english translation examples for ntt's alt-j/e machine translation system. we apply two machine learning algorithms: haussler's algorithm for learning internal disjunctive concept and quinlan's id3 algorithm. experimental results show that our approach yields rules that are highly accurate compared to the manually created rules.
combination of n-grams and stochastic context-free grammars for language modeling. this paper describes a hybrid proposal to combine n-grams and stochastic context-free grammars (scfgs) for language modeling. a classical n-gram model is used to capture the local relations between words, while a stochastic grammatical model is considered to represent the long-term relations between syntactical structures. in order to define this grammatical model, which will be used on large-vocabulary complex tasks, a category-based scfg and a probabilistic model of word distribution in the categories have been proposed. methods for learning these stochastic models for complex tasks are described, and algorithms for computing the word transition probabilities are also presented. finally, experiments using the penn treebank corpus improved by 30% the test set perplexity with regard to the classical n-gram models.
a model for transfer control in the metal mt-system. the present paper tries to outline a model to enhance the transfer control within the metal machine translation system. the model is being currently tested in the german-spanish system which is under development in barcelona and relies upon techniques belonging to the gpsg framework. the central idea is to extract from the transfer part of the phrase structure rules currently used by metal all the relevant generalizable information about feature traffic and control dependences, and put it in form of language-dependent tables. this information is then accessed and handled by a few high-level rule operators, called during the transfer process, implementing three general feature principles. the grammar writer is thereby relieved from the tedious task of controlling all the feature traffic between nodes, this resulting in a clearer, shorter and safer grammar for the system.
how the linguistic negation can have an effect in object-based knowledge representation model. in this paper, the coherence is considered within the framework of knowledge representation of texts. though the incoherence of a text may result from a lot of phenomena, we restrict ourselves in this communication to incoherence stemming from negations. we present the model and the effect of negation on its objects.
several directions for minority languages computerization. less than 1% of the languages spoken in the world are correctly "computerized": spell checkers, hyphenation, machine translation are still lacking for the others. in this paper, we present several directions that may help the computerization of minority languages as well as two projects where we apply some of these directions to the lao language.
computational semantics of time/negation interaction. the purpose of this paper is to study the interaction of time and negation in natural language, from a syntax/semantics interface point of view. this requires the definition of linguistically grounded semantic and syntactic representations. this is what we present in this paper; we show how the two representations we propose fit together in a computationally satisfying construction procedure.
un systeme inferentiel oriente objet pour des applications en langues naturelles. up to now, there is still no specific model for solving the problem of natural language representation and reasoning. in this paper, we propose an object oriented formalism for supporting knowledge representation, extraction and exploitation in the context of natural language processing.in the natural language analysis, this system is situated after the morpho-syntax and the linguistic semantics. it represents two classes of concepts: objects of discourse and action schemata, the former resulting from nominal syntagms and the latter from the 'processes'. we are concerned here just by the representation of objects.in the natural language discourse, manipulated objects are complex objects and the reasoning is by nature first inferential and then deductive. to take into account this kind of reasoning we need a suitable representation: a model of inferential objects.the theoretical foundations of the proposed model are lesniewski's logical systems: the calculus of names and the mereology. the former is based on a primitive functor called "epsilon" interpreted as is-a, the latter is based on a part-of relation which is called the "ingredience". the whole system is supported by these two primitives and theirs derived functions.the concepts of our model result from a collaboration between linguists and computer scientists. the main concepts are the intensional and extensional universes, notions and types.the possible inferential reasoning can be of different types: it can concern the status, the denominations, the structures or the "fonctifs" of the objects.
communication in large distributed ai systems for natural language processing. we are going to describe the design and implementation of a communication system for large ai projects, capable of supporting various software components in a heterogeneous hardware and programming-language environment. the system is based on a modification of the channel approach introduced by hoare (1978). it is a three layered approach with a de facto standard network layer (pvm), core routines, and interfaces to five different programming languages together with support for the transparent exchange of complex data types. a special component takes over name service functions. it also records the actual configuration of the modules present in the application and the created channels.we describe the intergration of this communication facility in two version of a speech-to-speech translation system, which differ with regard to quality and quantity of data distributed within the applications and with regard to the degree of interactivity involved in processing.
connotation as a form of inference. story-processing systems have to deal, or avoid dealing, with inference control..6, 11, 13; when designing one such system2, we were greatly helped by the "(erc)rc" expression for connotation1. our system is specialised in multifaceted descriptions of characters (not, however, in the most difficult problems of beliefs about beliefs4 and 8): here we present another aspect of the story character processing, namely the recursive explanation of inconsistencies appearing in the description of a character.we give a very schematic system overview, then some details about the connotation rules and an example of their application to a story.
rapid development of translation tools: application to persian and turkish. the computing research laboratory (crl) is developing a machine translation toolkit that allows rapid deployment of translation capabilities. this toolkit has been used to develop several machine translation systems, including a persian-english and a turkish-english system, which will be demonstrated. we present the architecture of these system as well as the development methodology.
bounded context parsing and easy learnability. natural languages are often assumed to be constrained so that they are either easily learnable or parsable, but few studies have investigated the connection between these two "functional" demands. without a formal model of parsability or learnability, it is difficult to determine which is more "dominant" in fixing the properties of natural languages. in this paper we show that if we adopt one precise model of "easy" parsability, namely, that of bounded context parsability, and a precise model of "easy" learnability, namely, that of degree 2 learnability, then we can show that certain families of grammars that meet the bounded context parsability condition will also be degree 2 learnable. some implications of this result for learning in other subsystems of linguistic knowledge are suggested.1
a karaka based approach to parsing of indian languages. a karaka based approach for parsing of indian languages is described. it has been used for building a parser of hindi for a prototype machine translation system.a lexicalised grammar formalism has been developed that allows constraints to be specified between 'demand' and 'source' words (e.g., between verb and its karaka roles). the parser has two important novel features: (i) it has a local word grouping phase in which word groups are formed using 'local' information only. they are formed based on finite state machine specifications thus resulting in a fast grouper. (ii) the parser is a general constraint solver. it first transforms the constraints to an integer programming problem and then solves it.
multilingual text processing in a two-byte code. national and international standards committees are now discussing a two-byte code for multilingual information processing. this provides for 65,536 separate character and control codes, enough to make permanent code assignments for all the characters of all national alphabets of the world, and also to include chinese/japanese characters.this paper discusses the kinds of flexibility required to handle both roman and non-roman alphabets. it is crucial to separate information units (codes) from graphic forms, to maximize processing power.comparing alphabets around the world, we find that the graphic devices (letters, digraphs, accent marks, punctuation, spacing, etc.) represent a very limited number of information units. it is possible to arrange alphabet codes to provide transliteration equivalence, the best of three solutions compared as a framework for code assignments.
parsing free word order languages in prolog. the prolog programming language allows the user to write powerful parsers in the form of metamorphosis grammars. however, the metamorhosis grammars, as defined by colmerauer2, have to specify strictly the order of terminal and nonterminal symbols. a modification of prolog has been implemented which allows "floating terminals" to be included in a metamorphosis grammar together with some information enabling to control the search for such a terminal in the unprocessed part of the input. the modification is illustrated by several examples from the polish language and some open questions are discussed.
referring to world objects with text and pictures. it often makes sense to employ both text and pictures when referring to world objects. in this paper, we present a model for referring which is based on the assumption that concepts may be activated not only by text, but also by pictures and text-picture combinations. by means of a case study, we demonstrate that failure and success of referring acts can be explained by the user's ability to infer certain links between mental representations and object descriptions. finally, we show how the model has been incorporated into a plan-based multimedia presentation system by defining operators for concept activation.
clg(n): constraint logic grammars. clg(2) is the latest member of a family of grammar formalisms centered around the notion of complex constraint expression for describing phrasal and lexical information and principles of language. complex constrains can be expressed in a slightly restriced form of first order predicate logic, which makes clg(2) well suited for expressing, amongst others, hpsg-style of grammars. a sound implementation of the formal semantics of clg(2) is achieved by resorting to delayed evaluation of non equational constraints.
encoding standards for large text resources: the text encoding initiative. the text encoding initiative (tei) is an international project established in 1988 to develop guidelines for the preparation and interchange of electronic texts for research, and to satisfy a broad range of uses by the language industries more generally. the need for standardized encoding practices has become inxreasingly critical as the need to use and, most importantly, reuse vast amounts of electronic text has dramatically increased for both research and industry, in particular for natural language processing. in january 1994, the tei issued its guidelines for the encoding and interchange of machine-readable texts, which provide standardized encoding conventions for a large range of text types and features relevant for a broad range of applications.
coping with ambiguity in a large-scale machine translation system. in an interlingual knowledge-based machine translation system, ambignuity arises when the source language analyzer produces more than one interlingua expression for a source sentence. this can have a negative impact on translation quality, since a target sentence may be produced from an unintended meaning. in this paper we describe the methods used in the kant machine translation system to reduce or eliminate ambiguity in a large-scale application domain. we also test these methods on a large corpus of test sentences, in order to illustrate how the different disambiguation methods reduce the average number of parses per sentence.
chinese segmentation disambiguation. a technique of reasoning under uncertainty is studied in an attempt to solve disambiguation problems of chinese segmentation. a knowledge-based inexact reasoning theory incorporating knowledge in morphology, syntax, semantics and pragmatics is presented.
the effects of word order and segmentation on translation retrieval performance. this research looks at the effects of word order and segmentation on translation retrieval performance for an experimental japanese-english translation memory system. we implement a number of both bag-of-words and word order-sensitive similarity metrics, and test each over character-based and word-based indexing. the translation retrieval performance of each system configuration is evaluated empirically through the notion of word edit distance between translation candidate outputs and the model translation. our results indicate that character-based indexing is consistently superior to word-based indexing, suggesting that segmentation is an unnecessary luxury in the given domain. word order-sensitive approaches are demonstrated to generally outperform bag-of-words methods, with source language segment-level edit distance proving the most effective similarity metric.
automatic dictionary organization in nlp systems for oriental languages. this paper presents a description of automatic dictionaries (ads) and dictionary entry (de) schemes for nlp systems dealing with oriental languages. the uniformity of the ad organization and of the de pattern does not prevent the system from taking into account the structural differences of isolating (analytical), agglutinating and internal-flection languages.the "speech statistics" (spst) project team has been designing a linguistic automaton aimed at nl processing in a variety of forms.in addition to germanic and romance languages the system under development is to handle text processing of a number of oriental languages. the strategy adopted by the spst group is characterized by a lexicalized approach: the nlp algorithms for any language are entirely ad dependent, i.e., a large lexicon database has been provided, its entries being loaded with information including not only lexical, but also morphological, syntactic and semantic data. this information concentrated in dictionary entries (des) is essential for both source text analysis and target (russian) text generation.the de structure is largely determined by the typological features of the source language. the spst group has hitherto had to deal with european languages and it was for these languages (inflective and inflective-analytical) that the prototype entry schemes were elaborated and adopted. no doubt, the typological characteristics of oriental languages required certain modifications to be made to the basic scheme. hence in the present paper each of the language types is given consideration. agglutinating languages proved to be the most suitable to process according to the spst strategy. but an isolating language will be the first to be proposed for discussion.
from shallow to deep parsing using constraint satisfaction. we present in this paper a technique allowing to choose the parsing granularity within the same approach relying on a constraint-based formalism. its main advantage lies in the fact that the same linguistic resources are used whatever the granularity. such a method is useful in particular for systems such as text-to-speech that usually need a simple bracketing, but in some cases requires a precise syntactic structure. we illustrate this method in comparing the results for three different granularity levels and give some figures about their respective performance in parsing a tagged corpus.
selectional restrictions in hps. selectional restrictions are semantic sortal constraints imposed on the participants of linguistic constructions to capture contextually-dependent constraints on interpretation. despite their limitations, selectional restrictions have proven very useful in natural language applications, where they have been used frequently in word sense disambiguation, syntactic disambiguation, and anaphora resolution. given their practical value, we explore two methods to incorporate selectional restrictions in the hpsg theory, assuming that the reader is familiar with hpsg. the first method employs hpsg's background feature and a constraint-satisfaction component pipe-lined after the parser. the second method uses subsorts of referential indices, and blocks readings that violate selectional restrictions during parsing. while theoretically less satisfactory, we have found the second method particularly useful in the development of practical systems.
bringing the dictionary to the user: the foks system. the dictionary look-up of unknown words is particularly difficult in japanese due to the complicated writing system. we propose a system which allows learners of japanese to look up words according to their expected, but not necessarily correct, reading. this is an improvement over previous systems which provide no handling of incorrect readings. in preprocessing, we calculate the possible readings each kanji character can take and different types of phonological and conjugational changes that can occur, and associate a probability with each. using these probabilities and corpus-based frequencies we calculate a plausibility measure for each generated reading given a dictionary entry, based on the naive bayes model. in response to a reading input, we calculate the plausibility of each dictionary entry corresponding to the reading and display a list of candidates for the user to choose from. we have implemented our system in a web-based environment and are currently evaluating its usefulness to learners of japanese.
a tool for collecting domain dependent sortal constraints from corpora. in this paper, we describe a tool designed to generate semi-automatically the sortal constraints specific to a domain to be used in a natural language (nl) understanding system. this tool is evaluated using the sri gemini nl understanding system in the atis domain.
a robust approach for handling oral dialogues. present limits of speech recognition and understanding in the context of free spoken language (although with a limited vocabulary) have perverse effects on the flow of the dialogue with a system. typically a non robust dialogue manager will fail to face with these limits and conversations will often be a failure. this paper presents some possibilities of a structural approach for handling communication failures in task-oriented oral dialogues. several types of communication failures are presented and explained. they must be dealt with by the dialogue manager if we strike to have a robust system. the exposed strategies for handling these failures are based on a structural approach of the conversation and are implemented in the sundial system. we first recall some aspects of the model and then describe the strategies for preventing and repairing communication failure in oral conversations with a system.
nl domain explanations in knowledge based mat. this paper discusses an innovative approach to knowledge based machine aided translation (mat) where the translator is supported by an user-friendly environment providing linguistic and domain knowledge explanations. our project aims at integration of a knowledge base (kb) in a mat system and studies the integration principles as well as the internal interface between language and knowledge. the paper presents some related work, reports the solutions applied in our project and tries to generalize our evaluation of the selected mat approach.
a high-level morphological description language exploiting inflectional paradigms. a high-level language for the description of inflectional morphology is presented, in which the organization of word formation rules into an inheritance hierarchy of paradigms allows for a natural encoding of the kinds of rules typically presented in grammar books. we show how the language, composed of orthographic rules, word formation rules, and paradigm inheritance, can be compiled into a run-time data structure for efficient morphological analysis and generation with a dynamic secondary storage lexicon.
automatic processing of written french language. an automatic processor of written french language is described. this processor uses syntactic and semantic informations about words in order to construct a semantic net representing the meaning of the sentences. the structure of the network and the principles of the parser are explained. an application to the processing of the medical records is then discussed.
an application of lexical semantics to knowledge acquisition from corpora. in this paper, we describe a program of research designed to explore how a lexical semantic theory may be exploited for extracting information from corpora suitable for use in information retrieval applications. unlike with purely statistical collocational analyses, the framework of a semantic theory allows the automatic construction of predictions about semantic relationships among words appearing in collocational systems. we illustrate the approach for the acquisition of lexical information for several classes of nominals.
finite-state phonology in hpsg. attention on constraint-based grammar formalisms such as head-driven phrase structure grammar (hpsg) has focussed on syntax and semantics to the exclusion of phonology. this paper investigates the incorporation of a non-procedural theory of phonology into hpsg, based on the 'one-level' model of bird & ellison (1992). the standard rule-representation distinction is replaced by the description-object distinction which is more germane in the context of constraint-based grammar. prosodic domains, which limit the applicability of phonological constraints, are expressed in a prosodic type hierarchy modelled on hpsg's lexical type hierarchy. interactions between phonology and morphology and between phonology and syntax are discussed and exemplified.
parsing spoken language without syntax. parsing spontaneous speech is a difficult task because of the ungrammatical nature of most spoken utterances. to overpass this problem, we propose in this paper to handle the spoken language without considering syntax. we describe thus a microsemantic parser which is uniquely based on an associative network of semantic priming. experimental results on spontaneous speech show that this parser stands for a robust alternative to standard ones.
the <c, a>, t framework in eurotra: a theoretically committed notation for mt. this paper describes a model for mt, developed within the eurotra mt project, based on the idea of <u>compositional translation</u>, by describing a basic, experimental notation which embodies the idea. the introduction provides background, section 1 introduces the basic ideas and the notation, and section 2 discusses some of the theoretical and practical implications of the model, including some concrete extensions, and some more speculative discussion.
using active constraints to parse gpsgs. active constraints of the constraint logic programming paradigm allow (1) the reduction of the search space of programs and (2) a very concise representation of the problems. these two properties are particularly interesting for parsing problems: they can help us to reduce non-determinism and to use large coverage grammars. in this paper, we describe how to use such constraints for parsing id/lp grammars and propose an implementation in prolog iii.
bottom-up filtering: a parsing strategy for gpsg. in this paper, we propose an optimized strategy, called bottom-up filtering, for parsing gpsgs. this strategy is based on a particular, high level, interpretation of gpsgs. it permits a significant reduction of the non-determinism inherent to the rule selection process.
ebl2: an approach to automatic lexical acquisition. a method for automatic lexical acquisition is outlined. an existing lexicon that, in addition to ordinary lexical entries, contains prototypical entries for various non-exclusive paradigms of open-class words, is extended by inferring new lexical entries from texts containing unknown words. this is done by comparing the constraints placed on the unknown words by the natural language system's grammar with the prototypes and a number of hand-coded phrase templates specific for each paradigm. once a sufficient number of observations of the word in different contexts have been made, a lexical entry is constructed for the word by assigning it to one or several paradigm(s).parsing sentences with unknown words is normally very time-consuming due to the large number of grammatically possible analyses. to circumvent this problem, other phrase templates are extracted automatically from the grammar and domain-specific texts using an explanation-based learning method. these templates represent grammatically correct sentence patterns. when a sentence matches a template, the original parsing component can be bypassed, reducing parsing times dramatically.
embedding drt in a situation theoretic framework. this paper proposes the use of situation theory as a basic semantic formalism for defining general semantic theories. astl, a computational situation theoretic language, is described which goes some way to offering such a system. after a general description of discourse representation theory an encoding of drt in astl is given. advantages and disadvantages of this method are then discussed.
integrating linguistic and performance-based constraints for assigning phrase breaks. the mapping between syntactic structure and prosodic structure is a widely discussed topic in linguistics. in this work we use insights gained from research on syntax-to-prosody mapping in order to develop a computational model which assigns prosodic structure to unrestricted text. the resulting structure is intended to help a text-to-speech (tts) system to predict phrase breaks. in addition to linguistic constraints, the model also incorporates a performance-oriented parameter which approximates the effect of speaking rate. the model is rule-based rather than probabilistic, and does not require training. we present the model and implementations for both english and german, and give evaluation results for both implementations. we then examine how far the approach can account for the different break patterns which are associated with slow, normal and fast speech rates.
action relations in rationale clauses and means clauses. communication among agents collaborating on a task often involves complex utterances about multiple action. in this paper, we analyze two particular multiaction constructions, utterances with means clauses and utterances with rationale clauses. we present the distinctive features of these constructions, describe their logical form, and define interpretation rules for deriving their meaning in terms of the generation, enablement and contributes relations between actions which have been motivated independently by research in plan recognition. we also demonstrate that these rules yield the appropriate properties of rationale clauses and means clauses and show how these constructions can be distinguished algorithmically.
functional unification grammar: a formalism for machine translation. functional unification grammar provides an opportunity to encompass within one formalism and computational system the parts of machine translation systems that have usually been treated separately, natably analysis, transfer, and synthesis. many of the advantages of this formalism come from the fact that it is monotonic allowing data structures to grow differently as different nondeterministic alternatives in a computation are pursued, but never to be modified in any way. a striking feature of this system is that it is fundamental reversible, allowing a to translate as b only if b could translate as a.
syntactic description of free word order languages. a framework for the description of syntactic structures of free word order languages is proposed, based on combination of intuitions underlying immediate constitutent description, dependency description and communicative dynamism. the combined approach is compared to its sources and shown superior in descriptive power, esp. in the area of free intermixing of (any number of) adjuncts with complements and in coordination. close resemblance to two other recent approaches is pointed out.
an evaluation semantics for datr theories. this paper describes an operational semantics for datr theories. the semantics is presented as a set of inference rules that axiomatises the evaluation relationship for datr expressions. the inference rules provide a clear picture of the way in which datr works, and should lead to a better understanding of the mathematical and computational properties of the language.
an ontology of systematic relations for a shared grammar of slavic. sharing portions of grammars across languages greatly reduces the costs of multilingual grammar engineering. related languages share a much wider range of linguistic information than typically assumed in standard multilingual grammar architectures. taking grammatical relatedness seriously, we are particularly interested in designing linguistically motivated grammatical resources for slavic languages to be used in applied and theoretical computational linguistics. in order to gain the perspective of a language-family oriented grammar design, we consider an array of systematic relations that can hold between syntactical units. while the categorisation of primitive linguistic entities tends to be language-specific or even construction-specific, the relations holding between them allow various degrees of abstraction. on the basis of slavic data, we show how a domain ontology conceptualising morpho-syntactic "building blocks" can serve as a basis of a shared grammar of slavic.
automatic text categorization by unsupervised learning. the goal of text categorization is to classify documents into a certain number of predefined categories. the previous works in this area have used a large number of labeled training documents for supervised learning. one problem is that it is difficult to create the labeled training documents. while it is easy to collect the unlabeled documents, it is not so easy to manually categorize them for creating training documents. in this paper, we propose an unsupervised learning method to overcome these difficulties. the proposed method divides the documents into sentences, and categorizes each sentence using keyword lists of each category and sentence similarity measure. and then, it uses the categorized sentences for training. the proposed method shows a similar degree of performance, compared with the traditional supervised learning methods. therefore, this method can be used in areas where low-cost text categorization is needed. it also can be used for creating training documents.
a reliable approach to automatic assessment of short answer free responses. this paper discusses an innovative approach to the computer assisted scoring of student responses in weblas (web-based language assessment system)- a language assessment system delivered entirely over the web. expected student responses are limited production free response questions.the portions of weblas with which we are concerned are the task creation and scoring modules. within the task creation module, instructors and language experts do not only provide the task input and prompt. more importantly, they interactively inform the system how and how much to score student responses. this interaction consists of weblas' natural language processing (nlp) modules searching for alternatives of the provided "gold standard" (hirschman et al, 2000) answer and asking for confirmation of score assignment. weblas processes and stores all this information within its database, to be used in the task delivery and scoring phases.
software tools for the environment of a computer aided translation system. in this paper we will present three systems, atlas, tham and visulex, which have been designed and implemented at geta (study group for machine translation) in collaboration with ifci (institut de formation et de conseil en informatique) as tools operating around the ariane-78 system. we will describe in turn the basic characteristics of each system, their possibilities, actual use, and performance.
chatr: a generic speech synthesis system. this paper describes a generic speech synthesis system called chatr which is being developed at atr. chatr is designed in a modular way so that module parameters and even which modules are actually used may be set and selected at runtime. although some interdependencies exist between modules, chatr offers a useful research tool in which functionally equivalent modules may be easily compared. it also acts as a simple system for those less interested in the internals of speech synthesis but just wish their computer to talk.
text categorization using feature projections. this paper proposes a new approach for text categorization, based on a feature projection technique. in our approach, training data are represented as the projections of training documents on each feature. the voting for a classification is processed on the basis of individual feature projections. the final classification of test documents is determined by a majority voting from the individual classifications of each feature. our empirical results show that the proposed approach, text categorization using feature projections (tcfp), outperforms k-nn, rocchio, and na&iuml;ve bayes. most of all, tcfp is about one hundred times faster than k-nn. since tcfp algorithm is very simple, its implementation and training process can be done very easily. for these reasons, tcfp can be a useful classifier in the areas, which need a fast and high-performance text categorization task.
perspectives of dbmt for monolingual authors on the basis of lidia-1, an implemented mock-up. dbmt is researched here in the context of future systems for the general public, where a monolingual author wants to translate into several languages. we have produced a complete mock-up, lidia-1, which demonstrates how a french hypercard&trade; stack could be translated into german, russian and english. we present the computational, linguistic and ergonomic aspects of the mock-up, and discuss them in the perspective of building an operational prototype in the future.
a reusable lexical database tool for machine translation. this paper describes the lexical database tool lola (linguistic-oriented lexical database approach) which has been developed for the construction and maintenance of lexicons for the machine translation system lmt. first, the requirements such a tool should meet are discussed, then lmt and the lexical information it requires, and some issues concerning vocabulary acquisition are presented. afterwards the architecture and the components of the lola system are described and it is shown how we tried to meet the requirements worked out earlier. although lola originally has been designed and implemented for the german-english lmt prototype, it aimed from the beginning at a representation of lexical data that can be reused for other lmt or mt prototypes or even other nlp applications. a special point of discussion will therefore be the adaptability of the tool and its components as well as the reusability of the lexical data stored in the database for the lexicon development for lmt or for other applications.
generating referring expressions using multiple knowledge sources. in this paper we present a brief look at some of the knowledge-based processes used in generating referring expressions in the natural language advisory system wisber. although wisber is fully capable of exploiting syntactic information to generate contextually appropriate references, the work described here concentrates on the use of conceptual and contingent knowledge about objects in the domain of discourse to generate natural-sounding references. a short description of the knowledge sources available is followed by examples of the processes that transform "deep structures" encoding system intentions into verbalizable form. finally, we discuss a number of problems of specifier selection and their solution within a knowledge-based framework.
trace & unification grammar. this paper presents trace & unification grammar (tug), a declarative and reversible grammar formalism that brings together unification grammar (ug) and ideas of government & binding theory (gb). the main part of the paper consists in a description of many free word order phenomena of german syntax. it will be shown that the use of traces allows for an easier and more elegant way of description than competing approaches like id/lp-format rules as used e.g. in gpsg and hpsg. grammars written in the tug-formalism can be compiled to a very efficient parser. the occurrence of head movement, wh-movement and scrambling in one sentence does not lead to any decrease in parsing efficiency.
a system for creating and manipulating generalized wordclass transition matrices from large labelled text-corpora. this paper deals with the training phase of a markov-type linguistic model that is based on transition probabilities between pairs and triplets of syntactic categories. to determine the optimal level of detail for a set of syntactic classes we developed a system that uses a set-theoretical formalism to define such sets and has some measures to compare and optimize them individually.in section two we describe the optimization problem (in terms of prediction, information and economy requirements) and our approach to its solution. section three introduces the system that will assist a linguist in handling the prediction and economy criteria and in the last section we present some sample results that can be achieved with it.
parsing with the shortest derivation. common wisdom has it that the bias of stochastic grammars in favor of shorter derivations of a sentence is harmful and should be redressed. we show that the common wisdom is wrong for stochastic grammars that use elementary trees instead of context-free rules, such as stochastic tree-substitution grammars used by data-oriented parsing models. for such grammars a non-probabilistic metric based on the shortest derivation outperforms a probabilistic metric on the atis and ovis corpora, while it obtains competitive results on the wall street journal (wsj) corpus. this paper also contains the first published experiments with dop on the wsj.
software support for practical grammar development. even though progress in theoretical linguistics does not necessarily rely on the construction of working programs, a large proportion of current research in syntactic theory is facilitated by suitable computational tools. however, when natural language processing applications seek to draw on the results from new developments in theories of grammar, not only the nature of the tools has to change, but they face the challenge of reconciling the seemingly contradictory requirements of notational perspicuity and efficiency of performance. in this paper, we present a comparison and an evaluation of a number of software systems for grammar development, and argue that they are inadequate as practical tools for building wide-coverage grammars. we discuss a number of factors characteristic of this task, demonstrate how they influence the design of a suitable software environment, and describe the implementation of a system which has supported efficient development of a large computational grammar of english.
the effects of analysing cohesion on document summarisation. we argue that in general, the analysis of lexical cohesion factors in a document can drive a summarizer, as well as enable other content characterization tasks. more narrowly, this paper focuses on how one particular cohesion factor--simple lexical repetition---can enhance an existing sentence extraction summarizer, by enabling strategies for overcoming some particularly jarring end-user effects in the summaries, typically due to coherence degradation, readability deterioration, and topical under-representation. lexical repetition is instrumental to, among other things, the topical make-up of a text, and in our framework a lexical repetition-based model of discourse segmentation, capable of detecting topic shifts, is integrated with a linguistically-aware summarizer utilizing notions of salience and dynamically-adjustable summary size. we show that even by leveraging lexical repetition alone, summaries are of comparable, and under certain conditions better, quality than the ones delivered by a state-of-the-art summarizer. this is encouraging for a broad research platform focusing on the recognition and use of cohesive devices in text for a range of content characterisation and document management tasks.
lexical ambiguity and the role of knowledge representation in lexicon design. the traditional framework for ambiguity resolution employs only 'static' knowledge, expressed generally as selectional restrictions or domain specific constraints, and makes no use of any specific knowledge manipulation mechanisms apart from the simple ability to match valences of structurally related words. in contrast, this paper suggests how a theory of lexical semantics making use of a knowledge representation framework offers a richer, more expressive vocabulary for lexical information. in particular, by performing specialized inference over the ways in which aspects of knowledge structures of words in context can be composed, mutually compatible and contextully relevant lexical components of words and phrases are highlighted. in the view presented here, lexical ambiguity resolution is an integral part of the same procedure that creates the semantic interpretation of a sentence itself.
creating a universal networking language module within an advanced nlp system. a multifunctional nlp environment, etap-3, is presented. the environment has several nlp applications, including a machine translation system, a natural language interface to sql type databases, synonymous paraphrasing of sentences, syntactic error correction module, and a computer-assisted language learning tool. emphasis is laid on a new module of the processor responsible for the interface with the universal networking language, a recent product by the un university intended for the facilitation of multilanguage, multiethnic access to communication networks such as www. the unl module of etap-3 naturally combines the two major approaches accepted in machine translation: the transfer-based approach and the interlingua approach.
dependency treebank for russian: concept, tools, types of information. the paper describes a tagging scheme designed for the russian treebank, and presents tools used for corpus creation.
towards personal mt: general design, dialogue structure, potential role of speech. personal mt (pmt) is a new concept in dialogue-based mt (dbmt), which we are currently studying and prototyping in the lidia project ideally, a pmt system should run on pcs and be usable by everybody. to get his/her text translated into one or several languages, the writer would accept to cooperate with the system in order to standardize and clarify his/her document. there are many interesting aspects in the design of such a system. the paper briefly presents some of them (hypertext, distributed architecture, guided language, hybrid transfer/interlingua, the goes on to study in more detail the structure of the dialogue with the writer and the place of speech synthesis [1].
towards personal mt: general design, dialogue structure, potential role of speech. personal mt (pmt) is a new concept in dialogue-based mt (dbmt), which we are currently studying and prototyping in the lidia project ideally, a pmt system should run on pcs and be usable by everybody. to get his/her text translated into one or several languages, the writer would accept to cooperate with the system in order to standardize and clarify his/her document. there are many interesting aspects in the design of such a system. the paper briefly presents some of them (hypertext, distributed architecture, guided language, hybrid transfer/interlingua, the goes on to study in more detail the structure of the dialogue with the writer and the place of speech synthesis [1].
present and future paradigms in the automatized translation of natural languages. useful automatized translation must be considered in a problem-solving setting, composed of a linguistic environment and a computer environment. we examine the facets of the problem which we believe to be essential, and try to give some paradigms along each of them. those facets are the linguistic strategy, the programming tools, the treatment of semantics, the computer environment and the types of implementation.
expert systems and other new techniques in mt systems. our mt systems integrate many advanced concepts from the fields of computer science, linguistics, and ai: specialized languages for linguistic programming based on production systems, complete linguistic programming environment, multilevel representations, organization of the lexicons around "lexical units", units of translation of the size of several paragraphs, possibility of using text-driven heuristic strategies.we are now beginning to integrate new techniques: unified design of an "integrated" lexical data-base containing the lexicon in "natural" and "coded" form, use of the "static grammars" formalism as a specification language, addition of expert systems equipped with "extralinguistic" or "metalinguistic" knowledge, and design of a kind of structural metaeditor (driven by a static grammar) allowing the interactive construction of a document in the same way as syntactic editors are used for developing programs. we end the paper by mentioning some projects for long-term research.
toward integrated dictionaries for m(a)t: motivations and linguistic organization. in the framework of machine (aided) translation systems, two types of lexical knowledge are used, "natural" and "formal". in the form of on-line terminological resources for human translators or revisors and of coded dictionaries for machine translation proper.a new organization is presented, which allows to integrate both types in a unique structure, called "fork" integrated dictionary, or fid. a given fid is associated with one natural language and may give access to translations into several other languages.the fids associated to languages l1 and l2 contain all information necessary to generate coded dictionaries of m(a)t systems translating from l1 into l2 or vice-versa. the skeleton of a fid may be viewed as a classical monolingual dictionary, augmented with one (or several) bilingual dictionary. each item is a tree structure, constructed by taking the "natural" information (a tree) and "grafting" onto it some "formal" information.various aspects of this design are refined and illustrated by detailed examples, several scenarii for the construction of fids are presented, and some problems of organization and implementation are discussed. a prototype implementation of the fid structure is under way in grenoble.
the "whiteboard" architecture: a way to integrate heterogeneous components of nlp systems. we present a new software architecture for nlp systems made of heterogeneous components, and demonstrate an architectural prototype we have built at atr in the context of speech translation.
theory and practice of ambiguity labelling with a view to interactive disambiguation in text and speech mt. in many contexts, automatic analyzers cannot fully disambiguate a sentence or an utterance reliably, but can produce ambiguous results containing the correct interpretation. it is useful to study vatious properties of these ambiguities in the view of subsequent total or partial interactive disambiguation. we have proposed a technique for labelling ambiguities in texts and in dialogue transcriptions, and experimented it on mulitilingual data. it has been first necessary to define formally the very notion of ambiguity relative to a representation system, as well as associated concepts such as ambiguity kernel, ambiguity scope, ambiguity occurrence.
representation trees and string-tree correspondences. the correspondence between a string of a language and its abstract representation, usually a (decorated) tree, is not straightforward. however, it is desirable to maintain it, for example to build structured editors for texts written in natural language. as such correspondences must be compositional, we call them "structured string-free correspondences" (sstc).we argue that a sstc is in fact composed of two interrelated correspondences, one between nodes and substrings, and the other between subtrees and substrings, the substrings being possibly discontinucus in both cases. we then proceed to show how to define a sstc with a structural correspondence static grammar (scsg), and which constraints to put on the rules of the scsg to get a "natural" sstc.
transformation of natural language into logical formulas. this paper presents an attempt of elaboration of a full parsing system for polish natural language which is being worked out in the institute of informatics of warsaw university. our system was adapted to the parsing of the corpus of real medical texts which concern a subdomain of medicine. we made use of the experience of such famous authors as (6), (7), (8), (9), (10), (11), (12), (13), (14).
jdii: parsing italian with a robust constraint grammar. italian is a language presenting a lot of syntactical problems, such as a rather unrestricted word order, unbounded agreement controls, long distance structure checkings and so on. things get worse and worse if we pass from "sentences of linguists" to real texts. in this paper we will present a system able to retrieve and signal syntactic errors in real italian texts.
co-ordinative ellipsis in russian texts: problem of description and restoration. russian elliptic constructions are examined from the point of view of syntactic analysis. reciprocal elements in a co-ordinative elliptic sentence are exposed and possible types of their similarity are explored. linear formulae of ellipsis for most textual cases are constructed and statistics of their use is discussed. as a result the main steps of ellipsis restoration algorithm are outlined.
countability and number in japanese to english machine translation. this paper presents a heuristic method that uses information in the japanese text along with knowledge of english countability and number stored in transfer dictionaries to determine the countability and number of english noun phrases. incorporating this method into the machine translation system alt-j/e, helped to raise the percentage of noun phrases generated with correct use of articles and number from 65% to 73%.
classifiers in japanese-to-english machine translation. this paper proposes an analysis of classifiers into four major types: unit, metric, group and species, based on properties of both japanese and english. the analysis makes possible a uniform and straightforward treatment of noun phrases headed by classifiers in japanese-to-english machine translation, and has been implemented in the mt system alt-j/e. although the analysis is based on the characteristics of, and differences between, japanese and english, it is shown to be also applicable to the unrelated language thai.
reusing an ontology to generate numeral classifiers. in this paper, we present a solution to the problem of generating japanese numeral classifiers using semantic classes from an ontology. most nouns must take a numeral classifier when they are quantified in languages such as chinese, japanese, korean, malay and thai. in order to select an appropriate classifier, we propose an algorithm which associates classifiers with semantic classes and uses inheritance to list only those classifiers which have to be listed. it generates sortal classifiers with an accuracy of 81%. we reuse the ontology provided by goi-taikei---a japanese lexicon, and show that it is a reasonable choice for this task, requiring information to be entered for less than 6% of individual nouns.
using an ontology to determine english countability. in this paper we show to what degree the countability of english nouns is predictable from their semantics. we found that at 78% of nouns' countability could be predicted using an ontology of 2,710 nodes. we also show how this predictability can be used to aid non-native speakers to determine the countability of english nouns when building a bilingual machine translation lexicon.
flexible parsing of discretely uttered sentences. in this paper we describe a syntactic semantic parser of spoken sentences pertaining to a subset of natural italian language. error-free and fast analysis, partial interpretation ability, man-machine dialogue trend, different semantic environment adaptability and natural language usage are its main characteristics. all of these features are supported by a technique of input reliability evaluation. particular attention is devoted to the description of the knowledge internal representation and of the mechanism that manages, at different points of the anlysis, the whole process.
you'll take the high road and i'll take the low road: using a third language to improve bilingual word alignment. while language-independent sentence alignment programs typically achieve a recall in the 90 percent range, the same cannot be said about word alignment systems, where normal recall figures tend to fall somewhere between 20 and 40 percent, in the language-independent case. as words (and phrases) for various reasons are more interesting to align than sentences, we need methods to increase word alignment recall, preferably without sacrificing precision. this paper reports on a series of experiments with pivot alignment, which is the use of one or more additional languages to improve bilingual word alignment. the conclusion is that in a multilingual parallel corpus, pivot alignment is a safe way to increase word alignment recall without lowering the precision.
two-component teaching system that understands and correct mistakes. this paper presents a computer-tool teaching system supplied by a language processor. its aim is to correct mistakes in texts written by foreign students learning russian as a second language. since a text may include grammar mistakes, the system cannot use morphological analysis to fool extent. so one must compile a programm capable of finding and correcting mistakes without traditional means of analysis.to solve this problem we propone a system that includes a vocabulary and rules of finding and re-writing words. so the process consists of finding word stems and than correcting word endings. semantic and syntactic information("a model of ruling"/mel'&ccaron;uk 1974/) necessary for that is written in the vocabulary of verbs as a frame. the slots of this frame contain semantic and morphological information about words that depend on this word.the vocabulary containing now approximately 200 lexemes is enough for beginners
an inference-based approach to dialogue system design. we present an architecture for spoken dialogue systems where first-order inference (both theorem proving and model building) plays a crucial role in interpreting utterances of dialogue participants and deciding how the system should respond and carry out instructions. the dialogue itself is represented as a drs which is translated into first-order logic for inference tasks. the system is implemented as a society of oaa-agents, and evaluated against a specific application (home automation).
processing metonymy- a domain-model heuristic graph traversal approach. we address here the treatment of metonymic expressions from a knowledge representation perspective, that is, in the context of a text understanding system which aims to build a conceptual representation from texts according to a domain model expressed in a knowledge representation formalism. we focus in this paper on the part of the semantic analyser which deals with semantic composition. we explain how we use the domain model to handle metonymy dynamically, and more generally, to underlie semantic composition, using the knowledge descriptions attached to each concept of our ontology as a kind of concept-level, multiple-role qualia structure. we rely for this on a heuristic path search algorithm that exploits the graphic aspects of the conceptual graphs formalism. the methods described have been implemented and applied on french texts in the medical domain.
mental state adjectives: the perspective of generative lexicon. this paper focusses on mental state adjectives and offers a unified analysis in the theory of generative lexicon (pustejovsky, 1991, 1995). we show that, instead of enumerating the various syntactic constructions they enter into, with the different senses which arise, it is posible to give them a rich typed semantic representation which will explain both their semantic and syntactic polymorphism.
a lexicalist account of icelandic case marking. recent theoretical descriptions of the icelandic case system distinguish between lexical and structural case. lexical case is assigned in the lexicon, whereas structural case is assigned in syntax, under the provision that it does not override lexical case assignment. this analysis is problematic for grammatical theories such as categorial unification grammar (cug) and head driven phrase structure grammar (hpsg) as the introduction of a syntactic case component is incompatible with the lexicalist ideology underlying these frameworks. furthermore, the default character of syntactic case introduces a procedural aspect into the grammar which goes against the declarative spirit of unification-based frameworks in general. in this paper, i propose an alternative analysis, formulated in terms of cug, in which all case constraints are expressed lexically and in which default reasoning is restricted to nonmonotonic inheritance of lexical information only.
surface grammatical analysis for the extraction of terminological noun phrases. lexter is a software package for extracting terminology. a corpus of french language texts on any subject field is fed in, and lexter produces a list of likely terminological units to be submitted to an expert to be validated. to identify the terminological units, lexter takes their form into account and proceeds in two main stages: analysis, parsing. in the first stage, lexter uses a base of rules designed to indentify frontier markers in view to analysing the texts and extracting maximal-length noun phrases. in the second stage, lexter parses these maximal-length noun phrases to extract subgroups which by virtue of their grammatical structure and their place in the maximal-length noun phrases are likely to be terminological units. in this article, the type of analysis used (surface grammatical analysis) is highlighted, as the methodological approach adopted to adapt the rules (experimental approach).
a metric space defined on english and its relation to error correction. a distance function is proposed that maps pairs of strings to the real numbers. it has been shown that given suitable constraints the function is a metric over the free monoid generated from a set of grammatical symbols. the necessary constraints modify the metric so that it maps pairs of strings to a lattice of real numbers. thus for each string the metric defines a countable set of nested neighbourhoods. this aspect of the space has proved useful for the correction of certain kinds of grammatical errors that occur in english sentences. an english parser was written that used the metric to propose corrections to a variety of ungrammatical sentences. experience with the program suggests that in many cases the intuitive notion of grammatical similarity corresponds closely to the mathematical definition of nearest neighbour in the space.
binding constraints as instructions of binding machines. binding constraints have resisted to be fully integrated into the course of grammatical processing despite its practical relevance and cross-linguistic generality. the ultimate root for this is to be found in the exponential "overgenerate & filter" procedure of the mainstream rationale for their satisfaction. in this paper we design an alternative approach based on the view that nominals are binding machines.
branching split obliqueness at the syntax-semantics interface. in this paper it is argued that the accuracy of the syntax-semantics interface is improved by adopting a non-linear obliqueness hierarchy for subcategorized arguments.
probabilistic parsing and psychological plausibility. given the recent, evidence for probabilistic mechanisms in models of human ambiguity resolution, this paper investigates the plausibility of exploiting current wide-coverage, probabilistic parsing techniques to model human linguistic performance. in particular, we investigate the performance of standard stochastic parsers when they are revised to operate incrementally, and with reduced memory resources. we present techniques for ranking and filtering analyses, together with experimental results. our results confirm that stochastic parsers which adhere to these psychologically motivated constraints achieve good performance. memory can be reduced down to 1% (compared to exhausitve search) without reducing recall and precision. additionally, these models exhibit substantially faster performance. finally, we argue that this general result is likely to hold for more sophisticated, and psycholinguistically plausible, probabilistic parsing models.
lexical rules: what are they? horizontal redundancy is inherent to lexica consisting of descriptions of fully formed objects. this causes an unwelcome expansion of the lexical database and increases parsing time. to climinate it, direct relations between descriptions of fully formed objects are often defined. these are additional to the (typed multiple) inheritance network which already structures the lexicon. many implementations of horizontal relations, however, fail to generate lexical entries on a needs-driven basis, so eliminate neither the problem of lexicon expansion nor that of inefficient parsing. alternatively, we propose that lexical entries are descriptions of objects open to contextual specification of their properties on the basis of constraints defined within the type system. this guarantees that only those grammatical lexical entries are infered that are needed for efficient parsing. the proposal is extremely modest, making use of only basic inference power and expressivity.
linking propositions. the function words of a language provide explicit information about how propositions are to be related. we have examined a subset of these function words, namely the subordinating conjunctions which link propositions within a sentence, using sentences taken from corpora stored on magnetic tape. on the basis of this analysis, a computer program for dutch language generation and comprehension has been extended to deal with the subordinating conjunctions. we present an overview of the underlying dimensions that were used in describing the semantics and pragmatics of the dutch subordinating conjunctions. we propose a universal set of linking dimensions, sufficient to specify the subordinating conjunctions in any language. this uld is a first proposal for the representation required for a computer program to understand or translate the subordinating conjunctions of any natural language.
formal description of multi-word lexemes with the finite-state formalism idarex. most multi-word lexemes (mwls) allow certain types of variation. this has to be taken into account for their description and their recognition in texts. we suggest to describe their syntactic restrictions and their idiosyncratic peculiarities with local grammar rules, which at the same time allow to express in a general way regularities valid for a whole class of mwls. the local grammars can be written in a very convenient and compact way as regular expressions in the formalism idarex which uses a two-level morphology. idarex allows to define various types of variables, and to mix canonical and inflected word forms in the regular expressions.
partial descriptions and systemic grammar. this paper examines the properties of featurebased partial descriptions built on top of halliday's systemic networks. we show that the crucial operation of consistency checking for such descriptions is np-complete, and therefore probably intractable, but proceed to develop algorithms which can sometimes alleviate the unpleasant consequences of this intractability.
the role of semantic processing in an automatic speech understanding system. we present the semantics component of a speech understanding and dialogue system that is developed at our institute. due to pronunciation variabilities and vagueness of the word recognition process, semantics in a speech understanding system has to resolve additional problems. its main task is not only to build up a representation structure for the meaning of an utterance, as in a system for written input, semantic knowledge is also employed to decide between alternative word hypotheses, to judge the plausibility of syntactic structures, and to guide the word recognition process by expectations resulting from partial analyses.
a rule-based approach to prepositional phrase attachment disambiguation. in this paper, we describe a new corpus-based approach to prepositional phrase attachment disambiguation, and present results comparing performance of this algorithm with other corpus-based approaches to this problem.
terminology data banks as a basis for high-quality translation. currently existing terminology data banks serve various purposes. two major groups, i.e. standardization-oriented and translation-oriented terminology data banks are of special significance. this paper deals exclusively with translation-oriented banks and uses as an example the team terminology data bank system developed by the language services department of siemens.
control structures and theories of interaction in speech understanding systems. in this paper, we approach the problem of organisation and control in automatic speech understanding systems firstly, by presenting a theory of the non-serial interactions necessary between two processors in the system: namely, the morphosyntactic and the prosodic, and secondly, by showing how, when generalised, this theory allows one to specify a highly efficient architecture for a speech understanding system with a simple control structure and genuinely independent components. the theory of non-serial interactions we present predicts that speech is temporally organised in a very specific way; that is, the system would not function effectively if the temporal distribution of various types of information in speech were different. the architecture we propose is developed from a study of the task of speech understanding and, furthermore, is specific to this task. consequently, the paper argues that general problem solving methods are unnecessary for speech understanding.
betatext: an event driven text processing and text analyzing system. betatext can be described as an <u>event driven</u> production system, in which (combinations of) text events lead to certain actions, such as the printing of sentences that exhibit certain, say, syntactic phenomena. the analysis mechanism used allows for arbitrarily complex parsing, but is particularly suitable for finite state parsing. a careful investigation of what is actually needed in linguistically relevant text processing resulted in a rather small but carefully chosen set of "elementary actions" to be implemented.
the use of instrumentation in grammar engineering. this paper explores the usefulness of a technique from software engineering, code instrumentation, for the development of large-scale natural language grammars. information about the usage of grammar rules in test and corpus sentences is used to improve grammar and testsuite, as well as adapting a grammar to a specific genre. results show that less than half of a large-coverage grammar for german is actually tested by two large testsuites, and that 10--30% of testing time is redundant. this methodology applied can be seen as a re-use of grammar writing knowledge for testsuite compilation. the construction of genre-specific grammars results in performance gains of a factor of four.
concurrent lexicalized dependency parsing: the parsetalk model. a grammar model for concurrent, object-oriented natural language parsing is introduced. complete lexical distribution of grammatical knowledge is achieved building upon the head-oriented notions of valency and dependency, while inheritance mechanisms are used to capture lexical generalizations. the underlying concurrent computation model relies upon the actor paradigm. we consider message passing protocols for establishing dependency relations and ambiguity handling.
advice-giving dialogue: an integrated system. in this paper we present the implementation of an advice-giving system for financial investment for the final phase of the project esteam-316. this system integrates multiple agents in a single architecture allowing cooperation between a natural language dialoguer, "intelligent" data base access modules, and a problem solver in the financial domain. using a user model, this system adapts the mixed initiative dialogue during both the formulation of the problem and its resolution by the expert. a novice user thus has access to expert knowledge despite the weakness of his own knowledge.
automated generalization of translation examples. previous work has shown that adding generalization of the examples in the corpus of an example-based machine translation (ebmt) system can reduce the required amount of pretranslated example text by as much as an order of magnitude for spanish-english and french-english ebmt. using word clustering to automatically generalize the example corpus can provide the majority of this improvement for french-english with no manual intervention; the prior work required a large bilingual dictionary tagged with parts of speech and the manual creation of grammar rules. by seeding the clustering with a small amount of manually-created information, even better performance can be achieved. this paper describes a method whereby bilingual word clustering can be performed using standard monolingual document clustering techniques, and its effectiveness at reducing the size of the example corpus required.
example-based machine translation in the pangloss system. the pangloss example-based machine translation engine (panebmt) is a translation system requiring essentially no knowledge of the structure of a language, merely a large parallel corpus of example sentences and a bilingual dictionary. input texts are segmented into sequences of words occurring in the corpus, for which translations are determined by subsentential alignment of the sentence pairs containing those sequences. these partial translations are then combined with the results of other translation engines to form the final translation produced by the pangloss system. in an internal evaluation, panebmt achieved 70.2% coverage of unrestricted spanish news-wire text, despite a simplistic subsentential alignment algorithm, a suboptimal dictionary, and a corpus from a different domain than the evaluation texts.
a statistical approach to language translation. an approach to automatic translation is outlined that utilizes techniques of statistical information extraction from large data bases. the method is based on the availability of pairs of large corresponding texts that are translations of each other. in our case, the texts are in english and french.fundamental to the technique is a complex glossary of correspondence of fixed locutions. the steps of the proposed translation process are: (1) partition the source text into a set of fixed locutions. (2) use the glossary plus contextual information to select the corresponding set of fixed locutions into a sequence forming the target sentence. (3) arrange the words of the target fixed locutions into a sequence forming the target sentence.we have developed statistical techniques facilitating both the automatic creation of the glossary, and the performance of the three translation steps, all on the basis of an alignment of corresponding sentences in the two texts.while we are not yet able to provide examples of french / english translation, we present some encouraging intermediate results concerning glossary creation and the arrangement of target word sequences.
a conceptual framework for automatic and dynamic thesaurus updating in information retrieval systems. this paper aims at presenting a methodology for automatic thesaurus construction in order to help the search of documents and we want to obtain the development of classes for specific topics (for a given corpus) without a priori semantic information. information contained in the thesaurus lead to new search formulations via automatic and/or user feedback. this presentation even being theoretical is oriented toward a database implementation.
genus disambiguation: a study in weighted preference. the automatic construction of an is_a taxonomy of noun senses from a machine readable dictionary (mrd) has long been sought, but achieved with only limited success. the task requires the solution to two problems: 1) to define an algorithm to automatically identify the genus or hypernym of a noun definition, and 2) to define an algorithm for lexical disambiguation of the genus term. in the last few years, effective methods for solving the first problem have been developed, but the problem of creating an algorithm for lexical disambiguation of the genus terms is one that has proven to be very difficult. in coling 90 we described our initial work on the automatic creation of a taxonomy of noun senses from longman's dictionary of contemporary english (ldoce). the algorithm for lexical disambiguation of the genus term was accurate about 80% of the time and made use of the semantic categories, the subject area markings and the frequency of use information in ldoce. in this paper we report a series of experiments which weight the three factors in various ways, and describe our improvements to the algorithm (to about 90% accuracy).
a client/server architecture for word sense disambiguation. this paper presents a robust client/server implementation of a word sense disambiguator for english. this system associates a word with its meaning in a given context using dictionaries as tagged corpora in order to extract semantic disambiguation rules. semantic rules are used as input of a semantic application program which encodes a linguistic strategy in order to select the best disambiguation rule for the word to be disambiguated. the semantic disambiguation rule application program is part of the client/server architecture enabling the processing of large corpora.
formal specificaiton of natural language syntax using two-level grammar. the two-level grammar is investigated as a notation for giving formal specification of the context-free and context-sensitive aspects of natural language syntax. in this paper, a large class of english declarative sentences, including post-noun-modification by relative clauses, is formalized using a two-level grammar. the principal advantages of two-level grammar are: 1) it is very easy to understand and may be used to give a formal description using a structured form of natural language; 2) it is formal with many well-known mathematical properties; and 3) it is directly implementable by interpretation. the significance of the latter fact is that once we have written a two-level grammar for natural language syntax, we can derive a parser automatically without writing any additional specialized computer programs. because of the ease with which two-level grammars may express logic and their turing computability we expect that they will also be very suitable for future extensions to semantics and knowledge representation.
design of a machine translation system for a sublanguage. this paper describes the design of a prototype machine translation system for a sublanguage of job advertisements. the design is based on the hypothesis that specialized linguistic subsystems may require special computational treatment and that therefore a relatively shallow analysis of the text may be sufficient for automatic translation of the sublanguage. this hypothesis and the desire to minimize computation in the transfer phase has led to the adoption of a flat tree representation of the linguistic data.
the resolution of quantificational ambiguity in the tendum system. a method is described for handling the ambiguity and vagueness that is often found in quantifications - the semantically complex relations between nominal and verbal constituents. in natural language certain aspects of quantification are often left open; it is argued that the analysis of quantification in a model-theoretic framework should use semantic representation in which this may also be done. this paper shows a form for such a representation and how "ambiguous" representations are used in an elegant and efficient procedure for semantic analysis, incorporated in the tendum dialogue system.
feaspar - a feature structure parser learning to parse spoken language. we describe and experimentally evaluate a system, feaspar, that learns parsing spontaneous speech. to train and run feaspar (feature structure parser), only limited handmodeled knowledge is required.the feaspar architecture consists of neural networks and a search. the networks split the incoming sentence into chunks, which are labeled with feature values and chunk relations. then, the search finds the most probable and consistent feature structure.feaspar is trained, tested and evaluated with the spontaneous scheduling task, and compared with a handmodeled lr-parser. the handmodeling effort for feaspar is 2 weeks. the handmodeling effort for the lr-parser was 4 months. feaspar performed better than the lr-parser in all six comparisons that are made.
tagging of very large corpora: topic-focus articulation. after a brief characterization of the theory of the topic-focus articulation of the sentence (tfa), rules are formulated that determine the assignment of appropriate values of the tfa attribute in the process of syntactico-semantic tagging of a very large corpus of czech.
a constructive view of gpsg or how to make it work. using the formalism of generalized phrase structure grammar (gpsg) in an nl system (e.g. for machine translation (mt) is promising since the modular structure of the formalism is very well suited to meet some particular needs of mt. however, it seems impossible to implement gpsg in its 1985 version straightforwardly. this would involve a vast overgeneration of structures as well as processes to filter out everything but the admissible tree(s). we therefore argue for a constructive version of gpsg where information is gathered in subsequent steps to produce syntactic structures. as a result, we consider it necessary to incorporate procedural aspects into the formalism in order to use it as a linguistic basis for nl parsing and generation. the paper discusses the major implications of such a modified view of gpsg.
semantic case role detection for information extraction. if information extraction wants to make its results more accurate, it will have to resort increasingly to a coherent implementation of natural language semantics. in this paper, we will focus on the extraction of semantic case roles from texts. after setting the essential theoretical framework, we will argue that it is possible to detect case roles on the basis of morphosyntactic and lexical surface phenomena. we will give a concise overview of our methodology and of a preliminary test that seems to confirm our hypotheses.
gramcheck: a grammar and style checker. this paper presents a grammar and style checker demonstrator for spanish and greek native writers developed within the project gramcheck. besides a brief grammar error typology for spanish, a linguistically motivated approach to detection and diagnosis is presented, based on the generalized use of prolog exteusions to highly typed unification-based grammars. the demonstrator, currently including full coverage for agreement errors and certain head-argument relation issues, also provides correction by means of an analysis-transfer-synthesis cycle. finally, future extensions to the current system are discussed.
syntactic analyses for parallel grammars: auxiliaries and genitive nps. this paper focuses on two disparate aspects of german syntax from the perspective of parallel grammar development. as part of a cooperative project, we present an innovative approach to auxiliaries and multiple genitive nps in german. the lfg-based implementation presented here avoids unnessary structural complexity in the representation of auxiliaries by challenging the traditional analysis of auxiliaries as raising verbs. the approach developed for multiple genitive nps provides a more abstract, language independent representation of genitives associated with nominalized verbs. taken together, the two approaches represent a step towards providing uniformly applicable treatments for differing languages, thus lightening the burden for machine translation.
syllable-based morphology. this paper presents a language for the description of morphological alternations which is based on syllable structure. the justification for such an approach is discussed with reference to examples from a variety of languages and the approach is compared to koskenniemi's two-level account of morphonology.
cross linguistic phoneme correspondences. cross-linguistic phoneme correspondences, or metaphonemes, can be defined across languages which are relatively closely related in exactly the same way as correspondences can be defined for dialects, or accents, of a single language (e.g. o'connor, 1973; fitt, 2001). in this paper we present the theory of metaphonemes, comparing them with traditional archi- and morphophonemes as well as with similar work using "keysymbols" done for accents of english. we describe the metaphoneme inventory defined for dutch, english and german, comparing the results for vowels and consonants. we also describe some of the unexpected information that arose from the analysis of cognate forms we undertook to find the metaphoneme correspondences.
thistle and interarbora. we present a system for manipulating a wide class of linguistic diagrams, which is configurable and extensible, and allows deployment as a web-delivered system. a major theme of this work is the transfer of the devices of formal grammar into the analysis and construction of diagrams.
unification categorial grammar: a concise, extenable grammar for natural language processing. unification categorial grammar (ucg) combines the syntactic insights of categorial grammar with the semantic insights of discourse representation theory. the addition of unification to these two frameworks allows a simple account of interaction between different linguistic levels within a constraining, monostraial theory. the resulting, computationally efficient, system provides an explicit formal framework for linguistic description, within which large fragments of grammars for french and english have already been developed. we present the formal basis of ucg, with independent definitions of well-formedness for syntactic and semantic dimensions. we will also focus on the concept of modifier within the theory.
detecting patterns in a lexical data base. in a well-structured lexical data base, a number of relations among lexical entries can be interactively evidenced. the present article examines hyponymy, as an example of paradigmatic relation, and "restriction" relation, as a syntagmatic relation. the theoretical results of their implementation are illustrated.
acquisition of semantic information from an on-line dictionary. after the first work on machine-readable dictionaries (mrds) in the seventies, and with the recent development of the concept of a lexical database (ldb) in which interaction, flexibility and multidimensionality can be achieved, but everything must be explicitly stated in advance, a new possibility which is now emerging is that of a procedural exploitation of the full range of semantic information implicitly contained in mrds. the dictionary is considered in this framework as a primary source of basic general knowledge. in the paper we describe a project to develop a system which has word-sense acquisition from information contained in computerized dictionaries and knowledge organization as its main objectives. the approach consists in a discovery procedure technique operating on natural language definitions, which is recursively applied and refined. we start from free-text definitions, in natural language linear form, analyzing and converting them into informationally equivalent structured forms. this new approach, which aims at reorganizing free text into elaborately structured information, could be called the lexical knowledge base (lkb) approach.
computation of modifier scope in np by a language-neutral method. the relative logical scope of multiple modifiers within np is often semantically significant. this paper proposes a structurally based method for computing the relative scope of such modifiers, based on their order, type, and syntactic complexity. the algorithm is language-neutral, in that it works with minimal errors for a wide range of languages without language-specific stipulations.
speech-rate variation and the prediction of duration. a comparison between the output from a set of duration rules based on klatt '76 and measured durations in a text allows quantification of speech rate at a local as well as a global level. the rules account for known correlates of duration change, such as stress, phonetic and phrasal context, and inherent differences in the durations of each segment, but make no allowance for local changes of rate within a text. the degree of fit of the output from such a system to the observed durations in the text provides a guide both to the accuracy of the rule-set and to the rate-related variation within that text. statistical procedures can be applied to reduce the rule-related error and thereby strengthen both the predictions of the rules and the quantification of the rate variation. this paper describes research in progress.
a principle-based hierarchical representation of ltags. lexicalized tree adjoining grammars have proved useful for nlp. however, numerous redundancy problems face ltags developers, as highlighted by vijay-shanker and schabes (92).we present a compact hierarchical organization of syntactic descriptions, that is linguistically motivated and a tool that automatically generates the tree families of an ltag. the tool starts from the syntactic hierarchy and principles of well-formedness and carries out all the relevant combinations of linguistic phenomena.
base noun phrase translation using web data and the em algorithm. we consider here the problem of base noun phrase translation. we propose a new method to perform the task. for a given base np, we first search its translation candidates from the web. we next determine the possible translation(s) from among the candidates using one of the two methods that we have developed. in one method, we employ an ensemble of na&iuml;ve bayesian classifiers constructed with the em algorithm. in the other method, we use tf-idf vectors also constructed with the em algorithm. experimental results indicate that the coverage and accuracy of our method are significantly better than those of the baseline methods relying on existing technologies.
user models: the problem of disparity. a significant component of a user model in an information-seeking dialogue is the task-related plan motivating the information-seeker's queries. a number of researchers have modeled the plan inference process and used these models to design more robust natural language interfaces. however in each case, it has been assumed that the system's context model and the plan under construction by the information-seeker are never at variance. this paper addresses the problem of disparate plans. it presents a four phase approach and argues that handling disparate plans requires an enriched context model. this model must permit the addition of components suggested by the information seeker but not fully supported by the system's domain knowledge, and must differentiate among its components according to the kind of support accorded each component as a correct part of the information-seeker's overall plan. it is shown how a component's support should affect the system's hypothesis about the source of error once plan disparity is suggested.
anaphora resolution: a multy-strategy approach. anaphora resolution has proven to be a very difficult problem; it requires the integrated application of syntactic, semantic, and pragmatic knowledge. this paper examines the hypothesis that instead of attempting to construct a monolithic method for resolving anaphora, the combination of multiple strategies, each exploiting a different knowledge source, proves more effective - theoretically and computationally. cognitive plausibility is established in that human judgements of the optimal anaphoric referent accord with those of the strategy-based method, and human inability to determine a unique referent corresponds to the cases where different strategies offer conflicting candidates for the anaphoric referent.
coping with extragrammaticality. practical natural language interfaces must exhibit robust behaviour in the presence of extragrammatical user input. this paper classifies different types of grammatical deviations and related phenomena at the lexical and sentential levels, discussing recovery strategies tailored to specific phenomena in the classification. such strategies constitute a tool chest of computationally tractable methods for coping with extragrammaticality in restricted domain natural language. some of the strategies have been tested and proven viable in existing parsers.
a model of competence for corpus-based machine translation. in this paper i elaborate a model of competence for corpus-based machine translation (cbmt) along the lines of the representations used in the translation system. representations in cbmt-systems can be rich or austere, molecular or holistic and they can be fine-grained or coarse-grained. the paper shows that different cbmt architectures are required dependent on whether a better translation quality or a broader coverage is preferred according to boitet (1999)'s formula: "coverage * quality = k".
planning to fail, not failing to plan: risk-taking and recovery in task-oriented dialogue. we hypothesise that agents who engage in task oriented dialogue usually try to complete the task with the least effort which will produce a satisfactory solution. our analysis of a corpus of map navigation task dialogues shows that there are a number of different aspects of dialogue for which agents can choose either to expend extra effort when they produce their initial utterances, or to take the risk that they will have to recover from a failure in the dialogue. some of these decisions and the strategies which agents use to recover from failures due to high risk choices are simulated in the jam system. the human agents of the corpus purposely risk failure because this is generally the most efficient behaviour. incorporating the same behaviour in the jam system produces dialogue with more "natural" structure than that of traditional dialogue systems.
rug: regular unification grammar. the paper describes a new unification based grammar formalism called regular unification grammar (rug). the formalism is under development at the research unit of computational linguistics, university of helsinki. in outline, rug can be described as a combination of an extended graph unification formalism with a fixed minimal finite state syntax.section i of the paper outlines the rug formalism. section ii describes some aspects of its current implementation. section iii describes an experimental rug grammar for finnish.
independent transfer using graph unification. we present a mt system that applies graph unification in transfer from english to finnish. the work described below is an outgrowth of a multilingual mt project initiated by the ibm in 1987 with the aim of studying multilingual translation using a common english language parser.the transfer system presented here is independent of the parsing and generation modules. any source language parser can be used whose output can be expressed in a directed graph form. the transfer system is responsible for generating target language phrase structure. target language word order and morphology are left to the generation modules.the transfer system is lexically based. transfer rules, presented in the form of bilingual graphs, are declarative statements of symmetric transfer relationships between words, phrases or constructions in the two intertranslatable languages.transfer is structure driven in that the transfer algorithm traverses the source language graph, nondeterministically trying to apply the relevant transfer rules in the lexicon. each successful transfer yields a bilingual graph, whose target language half is extracted and subjected to linearization and morphological generation.the main focus of attention in our project is the development of the lexicon subsystem. the lexicon system consists of separate transfer and monolingual lexicons and a common lexicon of language independent definitions.
high precision extraction of grammatical relations. a parsing system returning analyses in the form of sets of grammatical relations can obtain high precision if it hypothesises a particular relation only when it is certain that the relation is correct. we operationalise this technique---in a statistical parser using a manually-developed wide-coverage grammar of english---by only returning relations that form part of all analyses licensed by the grammar. we observe an increase in precision from 75% to over 90% (at the cost of a reduction in recall) on a test corpus of naturally-occurring text.
unification and transduction in computational phonology. in this paper unification and transduction mechanisms are applied in a new approach to phonological parsing. it is shown that unification in the sense of kay as used in unification grammars, and transduction, a process deriving from automata theory, are both valuable tools for use in computational phonology. by way of illustration, a brief outline of the allophonic parser described by church is given. then a linear unification parser for english syllables is introduced. this parser takes phonetic input in the form of feature bundles and uses phonological rules represented by networks of transduction relations together with unification, and an iterative finite-state process to produce phonemic output with marked syllable boundar les. a fundamental distinction is made between two domains: the representations at the phonetic and phonological levels, and the processing of these representations. on this basis, a distinction is made between networks of transduction relations e.g. between allophones and phonemes), and a set of possible processors (i.e. parsers and transducers) for the interpretation of such networks.
phonological processing of speech variants. this paper describes a strategy for the extension of the phonological lexicon in order that nonstandard forms which arise in fast speech may be processed by a speech recognition system. by way of illustration, an outline of the phonological processing of standard wordforms by the phonological parser (phopa) is given and then the extension procedure which is based on this phonological parser is discussed. the lexicon extension procedure has two stages: phonotactic extension which involves the introduction of additional restrictions into the phonotactic network for the standard language in the form of metarules describing phonological processes, and specialised word model construction whereby for each standard phonemic wordform a verification net which contains all variants of this standard form is compiled. the complete system serves as a phonologically oriented lexicon development tool, and its theoretical interest lies in its contribution to the field of speech variant learning.
efficient disjunctive unification for bottom-up parsing. this paper describes two novel techniques which, when applied together, in practice significantly reduce the time required for unifying disjunctive feature structures. the first is a safe but fast method for discarding irrelevant disjunctions from newly-created structures. the second reduces the time required to check the consistency of a structure from exponential to polynomial in the number of disjunctions, except in cases that, it will be argued, should be very unusual in practical systems. the techniques are implemented in an experimental japanese analyser that uses a large, existing disjunctive japanese grammar and lexicon. observations of the time behaviour of this analyser suggest that a significant speed gain is achieved.
simplifying deterministic parsing. this paper presents a model for deterministic parsing which was designed to simplify the task of writing and understanding a deterministic grammar. while retaining structures and operations similar to those of marcus' parsifal parser [marcus 80] the grammar language incorporates the following changes. (1) the use of productions operating in parallel has essentially been eliminated and instead the productions are organized into sequences. not only does this improve the understandability of the grammar, it is felt that this organization corresponds more closely to the task of performing the sequence of buffer transformations and attachments required to parse the most common constituent types. (2) a general method for interfacing between the parser and a semantic representation system is introduced. this interface is independent of the particular semantic representation used and hides all details of the semantic processing from the grammar writer. (3) the interface also provides a general method for dealing with syntactic ambiguities which arise from the attachment of optional modifiers such as prepositional phrases. this frees the grammar writer from determining each point at which such ambiguities can occur.
repair work in human-computer dialogue. if human-computer interaction is to be effective, it is vital that there are opportunities to check on understanding, and repair that understanding when it fails. this paper discusses this idea of repair in human-computer interaction, and provides a number of examples of different types of repair work in an interactive explanation system.
exogeneous and endogeneous approaches to semantic categorization of unknown technical terms. acquiring and updating terminological resources are difficult and tedious tasks, especially when semantic information should be provided. this paper deals with term semantic categorization. the goal of this process is to assign semantic categories to unknown technical terms. we propose two approaches to the problem that rely on different knowledge sources. the exogeneous approach exploits contextual information extracted from corpora. the endogeneous approach relies on a lexical analysis of the technical terms. after describing the two implemented methods, we present the experiments that we conducted on significant test sets. the results demonstrate that term categorization can provide a reliable help in the terminology acquisition processes.
structural disambiguation of morpho-syntactic categorial parsing for korean. the korean combinatory categorial grammar (kccg) formalism can uniformly handle word order variation among arguments and adjuncts within a clause as well as in complex clauses and across clause boundaries, i.e., long distance scrambling. in this paper, incremental parsing technique of a morpheme graph is developed using the kccg. we present techniques for choosing the most plausible parse tree using lexical information such as category merge probability, head-head co-occurrence heuristic, and the heuristic based on the coverage of subtrees. the performance results for various models for choosing the most plausible parse tree are compared.
semantics-based representation for multimodal interpretation in conversational systems. to support context-based multimodal interpretation in conversational systems, we have developed a semantics-based representation to capture salient information from user inputs and the overall conversation. in particular, we present three unique characteristics: fine-grained semantic models, flexible composition of feature structures, and consistent representation at multiple levels. this representation allows our system to use rich contexts to resolve ambiguities, infer unspecified information, and improve multimodal alignment. as a result, our system is able to enhance understanding of multimodal inputs including those abbreviated, imprecise, or complex ones.
representing information need with semantic relations. information retrieval systems can be made more effective by providing more expressive query languages for users to specify their information need. this paper argues that this can be achieved through the use of semantic relations as query primitives, and describes a new technique for extracting semantic relations from an online dictionary. in contrast to existing research, this technique involves the composition of basic semantic relations, a process akin to constrained spreading activation in semantic networks. the proposed technique is evaluated in the context of extracting semantic relations that are relevant for retrieval from a corpus of pictures.
a chinese characters coding scheme for computer input and internal stopage. a coding scheme for inputting chinese characters by means of a conventional keyboard has been developed. the code for each chinese character is composed of two strings of keys, one corresponds to the spelling and the other the ideographic property of the character. each code requires no more than seven keys (average five and a half keys) and 99.5% of the ten thousand characters in a dictionary 'xiandai hanyu cidian' have unique codes. each input code can be packed into 32 bits for internal representation.
motivations and methods for text simplification. long and complicated sentences prove to be a stumbling block for current systems relying on nl input. these systems stand to gain from methods that syntactically simplify such sentences. to simplify a sentence, we need an idea of the structure of the sentence, to identify the components to be separated out. obviously a parser could be used to obtain the complete structure of the sentence. however, full parsing is slow and prone to failure, especially on complex sentences. in this paper, we consider two alternatives to full parsing which could be used for simplification. the first approach uses a finite state grammar (fsg) to produce noun and verb groups while the second uses a supertagging model to produce dependency linkages. we discuss the impact of these two input representations on the simplification process.
putting frames in perspective. this paper attempts to bridge the gap between framenet frames and inference. we describe a computational formalism that captures structural relationships among participants in a dynamic scenario. this representation is used to describe the internal structure of framenet frames in terms of parameters for event simulations. we apply our formalism to the commerce domain and show how it provides a flexible means of accounting for linguistic perspective and other inferential effects.
coupling an automatic dictation system with a grammar checker. automatic dictation systems (ads) are nowadays powerful and rellable. however, some inadequacies of the underlying models still cause errors. in this paper, we are essentially interested in the language model implemented in the linguistic component, and we leave aside the acoustic module. more precisely, we aim at improving this linguistic model by coupling the ads with a syntactic parser, able to diagnose and correct grammatical errors. we describe the characteristics of such a coupling, and show how the performance of the ads improves with the actual coupling realized for french between the tangora ads and the grammar checker developed at the ibm france scientific center.
word sense disambiguation of adjectives using probabilistic networks. in this paper, word sense disambiguation (wsd) accuracy achievable by a probabilistic classifier, using very minimal training sets, is investigated. we made the assumption that there are no tagged corpora available and identified what information, needed by an accurate wsd system, can and cannot be automatically obtained. the lesson learned can then be used to focus on what knowledge needs manual annotation. our system, named bayesian hierarchical disambiguator (bhd), uses the internet, arguably the largest corpus in existence, to address the sparse data problem, and uses wordnet's hierarchy for semantic contextual features. in addition, bayesian networks are automatically constructed to represent knowledge learned from training sets by modeling the selectional preference of adjectives. these networks are then applied to disambiguation by performing inferences on unseen adjective-noun pairs. we demonstrate that this system is able to disambiguate adjectives in unrestricted text at good initial accuracy rates without the need for tagged corpora. the learning and extensibility aspects of the model are also discussed, showing how tagged corpora and additional context can be incorporated easily to improve accuracy, and how this technique can be used to disambiguate other types of word pairs, such as verb-noun and adverb-verb pairs.
maximum entropy models for word sense disambiguation. a maximum entropy-based word sense disambiguation system is presented, consisting of individual word experts that are trained on both labeled and partially labeled corpora. the classification probabilities from the individual word experts are integrated using a new search algorithm, which balances time complexity and accuracy. the model is evaluated using established procedures on the english-all-words task from the senseval-2 workshop, a large test set consisting of words from all word groups to be disambiguated. lastly, an ongoing project that integrates pos tagging, parsing, and sense disambiguation in one system is presented. once in place, it will be boot-strapped with existing partially labeled corpora, to process and then train from them. the goal is to show that with each successive iteration, the accuracy of all three processes, pos tagging, parsing, and wsd, will improve as the system learns from more accurate, self-generated training data.
a logic-based government-binding parser for mandarin chinese. mandarin chinese is a highly flexible and context-sensitive language. it is difficult to do the case marking and index assignment during the parsing of chinese sentences. this paper proposes a logic-based government-binding approach to treat this problem. the grammar formalism is specified in a formal way. uniform treatments of movements, arbitrary number of movement non-terminals, automatic detection of grammar errors beforehand, and clear declarative semantics are its specific features. many common linguistic phenomena of chinese sentences are represented with this formalism. for example, topic-comment structures, the ba-constructions, the bei-constructions, relative clause constructions, appositive clause constructions, and serial verb constructions. a simple pronoun resolution is touched upon. the expressive capabilities and the design methodologies show this mechanism is also suitable for other flexible and context-sensitive languages.
towards automatic generation of natural language generation systems. systems that interact with the user via natural language are in their infancy. as these systems mature and become more complex, it would be desirable for a system developer if there were an automatic method for creating natural language generation components that can produce quality output efficiently. we conduct experiments that show that this goal appears to be realizable. in particular we discuss a natural language generation system that is composed of spot, a trainable sentence planner, and fer-gus, a stochastic surface, realizer. we show how these stochastic nlg components can be made to work together, that they can be ported to new domains with apparent ease, and that such nlg components can be integrated in a real-time dialog system.
automatic semantic classification for chinese unknown compound nouns. the paper describes a similarity-based model to present the morphological rules for chinese compound nouns. this representation model serves functions of 1) as the morphological rules of the compounds, 2) as a mean to evaluate the properness of a compound construction, and 3) as a mean to disambiguate the semantic ambiguity of the morphological head of a compound noun. an automatic semantic classification system for chinese unknown compounds is thus implemented based on the model. experiments and error analyses are also presented.
nlp and ir approaches to monolingual and multilingual link detection. this paper considers several important issues for monolingual and multilingual link detection. the experimental results show that nouns, verbs, adjectives and compound nouns are useful to represent news stories; story expansion is helpful; topic segmentation has a little effect; and a translation model is needed to capture the differences between languages.
a part-of-speech-based alignment algorithm. to align bilingual texts becomes a crucial issue recently. rather than using length-based or translation-based criterion, a part-of-speech-based criterion is proposed. we postulate that source texts and target texts should share the same concepts, ideas, entities, and events. simulated annealing approach is used to implement this alignment algorithm. the preliminary experiments show good performance. most importantly, the experimental objects are chinese-english texts, which are selected from different language families.
a rule-based and mt-oriented approach to prepositional phrase attachment. prepositional phrase is the key issue in structural ambiguity. recently, researches in corpora provide the lexical cue of prepositions with other words and the information could be used to partly resolve ambiguity resulted from prepositional phrases. two possible attachments are considered in the literature; either noun attachment or verb attachment. in this paper, we consider the problem from viewpoint of machine translation. four different attachments are told out according to their functionality: noun attachment. both lexical knowledge and semantic knowledge are involved resolving attachment in the proposed mechanism. experimental results show that considering more types of prepositional phrases is useful in machine translation.
information-based case grammar. in this paper we propose a framework of information-based case grammar (icg). this grammatical formalism entails that the lexical entry for each word contain both semantic and syntactic feature structures. in the feature structure of a phrasal head, we encode syntactic and semantic constraints on grammatical phrasal patterns in terms of thematic structures, and encode the precedence relations in terms of adjunct structures. such feature structures denote partial information which defines the set of legal phrases. they also provide sufficient information to identify thematic roles. with this formalism, parsing and thematic analysis can be achieved simultaneously. due to the simplicity and flexibility of information-based case grammar, context dependent and discontinuous relations such as agreements, coordinations, long-distance dependencies, and control and binding, can be easily expressed. icg is a kind of unification-based formalism. therefore it inherits the advantages of unification-based formalisms and more.
a muitilingual news summarizer. huge multilingual news articles are reported and disseminated on the internet. how to extract the key information and save the reading time is a crucial issue. this paper proposes architecture of multilingual news summarizer, including monolingual and multilingual clustering, similarity measure among meaningful units, and presentation of summarization results. translation among news stories, idiosyncrasy among languages, implicit information, and user preference are addressed.
word identification for mandarin chinese sentences. chinese sentences are composed with string of characters without blanks to mark words. however the basic unit for sentence parsing and understanding is word. therefore the first step of processing chinese sentences is to identify the words. the difficulties of identifying words include (1) the identification of complex words, such as determinative-measure, reduplications, derived words etc., (2) the identification of proper names, (3) resolving the ambiguous segmentations. in this paper, we propose the possible solutions for the above difficulties. we adopt a matching algorithm with 6 different heuristic rules to resolve the ambiguities and achieve an 99.77% of the success rate. the statistical data supports that the maximal matching algorithm is the most effective heuristics.
identification and classification of proper nouns in chinese texts. various strategies are proposed to identify and classify three types of proper nouns in chinese texts. clues from character, sentence and paragraph levels are employed to resolve chinese personal names. character, syllable and frequency conditions are presented to treat transliterated personal names. to deal with organization names, keywords, prefix, word association and parts-of-speech are applied. for fair evaluation, large scale test data are selected from six sections of a newspaper. the precision and the recall for these three types are (88.04%, 92.56%), (50.62%, 71.93%) and (61.79%, 54.50%), respectively. when the former two types are regarded as a category, the performance becomes (81.46%, 91.22%). compared with other approaches, our approach has better performance and our classification is automatic.
a new design of prolog-based bottom-up parsing system with government-binding theory. this paper addresses the problems of movement transformation in prolog-based bottom-up parsing system. three principles of government-binding theory are employed to deal with these problems. they are empty category principle, c-command principle, and subjacency principle. a formalism based upon them is proposed. translation algorithms are given to add these linguistic principles to the general grammar rules, the leftward movement grammar rules, and the rightward movement grammar rules respectively. this approach has the following specific features: the uniform treatments of leftward and rightward movements, the arbitrary number of movement non-terminals in the rule body, and automatic detection of grammar errors before parsing. an example in chinese demonstrates all the concepts.
unknown word extraction for chinese documents. there is no blank to mark word boundaries in chinese text. as a result, identifying words is difficult, because of segmentation ambiguities and occurrences of unknown words. conventionally unknown words were extracted by statistical methods because statistical methods are simple and efficient. however the statistical methods without using linguistic knowledge suffer the drawbacks of low precision and low recall, since character strings with statistical significance might be phrases or partial phrases instead of words and low frequency new words are hardly identifiable by statistical methods. in addition to statistical information, we try to use as much information as possible, such as morphology, syntax, semantics, and world knowledge. the identification system fully utilizes the context and content information of unknown words in the steps of detection process, extraction process, and verification process. a practical unknown word extraction system was implemented which online identifies new words, including low frequency new words, with high precision and high recall rates.
an acquisition model for both choosing and resolving anaphora in conjoined mandarin chinese sentences. anaphoric reference is an important linguistic phenomenon to understand the discourse structure and content. in chinese natural language processing, there are both the problems of choosing and resolving anaphora. in mandarin chinese, several linguists have attempted to propose criteria to explain the phenomenon of anaphora but with controversial results. on the other hand, search-based computational techniques for resolving anaphora are neither the best way to resolve chinese anaphora nor to facilitate choosing anaphora. thus, to facilitate both choosing and resolving anaphora with accuracy and efficiency, we propose a case-based learning model g-unimem to automatically acquire anaphoric regularity from a sample set of training sentences, which are annotated with a list of features. the regularity acquired from training was then tested and compared with other approaches in both choosing and resolving anaphora.
mining tables from large scale html texts. table is a very common presentation scheme, but few papers touch on table extraction in text data mining. this paper focuses on mining tables from large-scale html texts. table filtering, recognition, interpretation, and presentation are discussed. heuristic rules and cell similarities are employed to identify tables. the f-measure of table recognition is 86.50%. we also propose an algorithm to capture attribute-value relationships among table cells. finally, more structured data is extracted and presented.
recovering latent information in treebanks. many recent statistical parsers rely on a preprocessing step which uses hand-written, corpus-specific rules to augment the training data with extra information. for example, head-finding rules are used to augment node labels with lexical heads. in this paper, we provide machinery to reduce the amount of human effort needed to adapt existing models to new corpora: first, we propose a flexible notation for specifying these rules that would allow them to be shared by different models; second, we report on an experiment to see whether we can use expectation-maximization to automatically fine-tune a set of hand-written rules to a particular corpus.
syntactic ambiguity resolution using a discrimination and robustness oriented adaptive learning algorithm. in this paper, a discrimination and robustness oriented adaptive learning procedure is proposed to deal with the task of syntactic ambiguity resolution. owing to the problem of insufficient training data and approximation error introduced by the language model, traditional statistical approaches, which resolve ambiguities by indirectly and implicitly using maximum likelihood method, fail to achieve high performance in real applications. the proposed method remedies these problems by adjusting the parameters to maximize the accuracy rate directly. to make the proposed algorithm robust, the possible variations between the training corpus and the real tasks are also taken into consideration by enlarging the separation margin between the correct candidate and its competing members. significant improvement has been observed in the test. the accuracy rate of syntactic disambiguation is raised from 46.0% to 60.62% by using this novel approach.
looking for candidate translational equivalents in specialized, comparable corpora. previous attempts at identifying translational equivalents in comparable corpora have dealt with very large 'general language' corpora and words. we address this task in a specialized domain, medicine, starting from smaller non-parallel, comparable corpora and an initial bilingual medical lexicon. we compare the distributional contexts of source and target words, testing several weighting factors and similarity measures. on a test set of frequently occurring words, for the best combination (the jaccard similarity measure with or without tf.idf weighting), the correct translation is ranked first for 20% of our test words, and is found in the top 10 candidates for 50% of them. an additional reverse-translation filtering step improves the precision of the top candidate translation up to 74%, with a 33% recall.
an augmented chart data structure with efficient word lattice parsing scheme in speech recognition applications. in this paper, an augmented chart data structure with efficient word lattice parsing scheme in speech recognition applications is proposed. the augmented chart and the associated parsing algorithm can represent and parse very efficiently a lattice of word hypotheses produced in speech recognition with high degree of lexical ambiguity without changing the fundamental principles of chart parsing. every word lattice can be mapped to the augmented chart with the ordering and connection relation among word hypotheses being well preserved in the augmented chart. a jump edge is defined to link edges representing word hypotheses physically separated but practically possible to be connected. preliminary experimental results show that with the augmented chart parsing all possible constituents of the input word lattice can be constructed and no constituent needs to be built more than once. this will reduce the computation complexity significantly especially when serious lexical ambiguity exists in the input word lattice as in many speech recognition problems. this augmented chart parsing is thus a very useful and efficient approach to language processing problems in speech recognition applications.
named entity recognition: a maximum entropy approach using global information. this paper presents a maximum entropy-based named entity recognizer (ner). it differs from previous machine learning-based ners in that it uses information from the whole document to classify each word, with just one classifier. previous work that involves the gathering of information from the whole document often uses a secondary classifier, which corrects the mistakes of a primary sentence-based classifier. in this paper, we show that the maximum entropy framework is able to make use of global information directly, and achieves performance that is comparable to the best previous machine learning-based ners on muc-6 and muc-7 test data.
an english-to-korean machine translator: mates/ek. this note introduces an english-to-korean machine translation system mates/ek, which has been developed as a research prototype and is still under upgrading in kaist (korea advanced institute of science and technology). mates/ek is a transfer-based system and it has several subsystems that can be used to support other mt-developments. they are grammar developing environment systems, dictionary developing tools, a set of augmented context free grammars for english syntactic analysis, and so on.
recherches sur la representation des connaissances le systeme arches. ce papier pr&eacute;sente la description formelle d'un syst&egrave;me symbolique de repr&eacute;sentation de connaissances, le syst&egrave;me arches. comme tout syst&egrave;me formel, il est form&eacute; de deux composantes interd&eacute;pendantes. la premi&egrave;re est relative aux modalit&eacute;s de repr&eacute;sentation des connaissances qui sont d&eacute;termin&eacute;es par le langage objet de arches et l'organisation alg&eacute;brique de ses &eacute;l&eacute;ments. la deuxi&egrave;me est relative &agrave; son activit&eacute; inf&eacute;rentielle qui permet de mettre en oeuvre deux types de raisonnement: le raisonnement d&eacute;ductif pour lequel un principe de r&eacute;solution a &eacute;t&eacute; d&eacute;fini; et le raisonnement analogique fond&eacute; sur un mod&egrave;le analogique particulier qui rend consistant le syst&egrave;me arches.
preferred argument structure for discourse understanding. the main purpose of communication is to exchange information. any discourse understanding model should be able to process the flow of information throughout the entire text. according to du bois (1987)'s studies of information flow in discourse across a number of languages, information distribution among argument positions in clauses is by no means random, but certain grammatical patterns tend to recur consistently. he thus formulated a preferred argument structure (pas) for the preferential structural configurations of arguments. in our examination of chinese narrative discourse, the language also displays pas, yet the chinese pas challenges the universality of the one du bois proposed. based on the quantity and distribution of lexical arguments and new referents across grammatical roles in discourse, it is realized that chinese pas also maintains one new argument at most within a basic information processing unit. since new referents in chinese have to be encoded in full np form, it is thus less likely to have more than one lexical argument within a clause. moreover, this single new argument appears preferentially in the o role, rather than the a and s roles du bois's pas formulates.since the structure of information flow has a corresponding grammatical patterning, both grammatical and pramatic processing can be carried out simultaneously, in that the information status of an argument can be identified by virtue of grammatical analysis. although pas is neither universal nor categorical, it can function in a discourse understanding model as heuristic device to process the information structure of a connected spoken discourse.
a phonological knowledge base system using unification-based formalism - a case study of korean phonology. this paper describes the framework of a korean phonological knowledge base system using the unification based grammar formalism: korean phonology structure grammar (kpsg). the approach of kpsg provides an explicit development model for constructing a computational phonological system: speech recognition and synthesis system. we show that the proposed approach is more describable than other approaches such as those employing a traditional generative phonological approach.
nara: a two-way simultaneous interpretation system between korean and japanese - a methodological study. this paper presents a new computing model for constructing a two-way simultaneous interpretation system between korean and japanese. we also propose several methodological approaches to the construction of a two-way simultaneous interpretation system, and realize the two-way interpreting process as a model unifying both linguistic competence and linguistic performance. the model is verified theoretically and through actual applications.we are deeply grateful to prof. h. yamada for his encouragement. we would like to thank dr. a. adachi and dr. k. hashida, for many stimulating discussions and for detailed comments, and mr. y. shirai and mr. i. fujishiro for suggestions to improve the paper.
empirical estimates of adaptation: the chance of two noriegas is closer to p/2 than p2. repetition is very common. adaptive language models, which allow probabilities to change or adapt after seeing just a few words of a text, were introduced in speech recognition to account for text cohesion. suppose a document mentions noriega once. what is the chance that he will be mentioned again? if the first instance has probability p, then under standard (bag-of-words) independence assumptions, two instances ought to have probability p2, but we find the probability is actually closer to p/2. the first mention of a word obviously depends on frequency, but surprisingly, the second does not. adaptation depends more on lexical content than frequency; there is more adaptation for content words (proper nouns, technical terminology and good keywords for information retrieval), and less adaptation for function words, cliches and ordinary first names.
categorial grammars for strata of non-cf languages and their parsers. we introduce a generalization of categorial grammar extending its descriptive power, and a simple model of categorial grammar parser. both tools can be adjusted to particular strata of languages via restricting grammatical or computational complexity.
explaining away ambiguity: learning verb selectional preference with bayesian networks. this paper presents a bayesian model for unsupervised learning of verb selectional preferences. for each verb the model creates a bayesian network whose architecture is determined by the lexical hicrarchy of wordnet and whose parameters are estimated from a list of verb-object pairs found from a corpus. "explaining away", a well-known property of bayesian networks, helps the model deal in a natural fashion with word sense ambiguity in the training data. on a word sense disambiguation test our model performed better than other state of the art systems for unsupervised learning of selectional preferences. computational complexity problems, ways of improving this approach and methods for implementing "explaining away" in other graphical frameworks are discussed.
knowledge extraction from texts by sintesi. in this paper we present sintesi, a system for the knowledge extraction from italian inputs, currently under development in our research centre. it is used on short descriptive diagnostic texts, in order to summarise their technical content and to build a knowledge base on faults. often in these texts complex linguistic constructions like conjunctions, negations, ellipsis and anaphorae are involved. the presence of extragrammaticalities and of implicit knowledge is also frequent, especially because of the use of a sublanguage. sintesi extracts the diagnostic information by performing a full text analysis; it is based on a semantics driven approach integrated by a general syntactic module and it is able to cope with the complexity of the (sub)language, maintaining both accuracy and robustness. currently the system has been tested on about 1.000 texts and by a few users; in the near future it will be used by dozens of users every day.
a class-based probabilistic approach to structural disambiguation. knowledge of which words are able to fill particular argument slots of a predicate can be used for structural disambiguation. this paper describes a proposal for acquiring such knowledge, and in line with much of the recent work in this area, a probabilistic approach is taken. we develop a novel way of using a semantic hierarchy to estimate the probabilities, and demonstrate the general approach using a prepositional phrase attachment experiment.
uses of c-gpaphs in a prototype for altomatic twislation. this paper presents a prototype, not completely operational, that is intended to use c-graphs in the translation of assemblers. firstly, the formalization of the structure and its principal notions (substructures, classes of substructures, order, etc.) are presented. next section describes the prototype which is bassed on a transformational system as well as on a rewriting system of c-graphs which constitutes the nodes of the transformatinal system. the following part discusses a set of operations on the structure. finally, the implementation in its present state is shown.
semantics of portions and partitive nouns for nlp. this paper describes a system of representation of nouns denoting portions, segments and relative quantities of entities, in order to account for this case of part-whole relationship. the semantics of both constructions denoting portions and nouns used to build them are discussed and eventually formalised in a unification-based formalism (lkb-lrl) in terms of pustejovsky's theory of qualia and jackendoff's conceptual semantics.
evaluating and comparing three text-production techniques. what are the benefits of using natural language generation in an industrial application? we have attempt to answer part of this question with a description of an assessment of three techniques for producing multisentential text: semi-automatic fill-in-the-blank interfacing, automatic linguistic-and-templates hybrid generation, and human writing. this assessment used a black-box methodology, with an independent blind-tested jury that gave different quality levels in relation to a set of criteria. the texts used for the assessment were business reply letters.
a formalism for the structural analysis of dialogues. this paper outlines a formalism for conversational analysis that captures multiple interactional patterns of mixed-initiative and fix the historical skeleton of a dialogue. the formalism, composed by a grammar of dialogues (syntax and semantic component) and a collection of attached scenarios (pragmatic component), is written in prolog and implemented in a program which converses in portugu<u>e</u> se to provide a library service.
a computational theory of the function of clue words in argument understanding. this paper examines the use of clue words in argument dialogues. these are special words and phrases directly indicating the structure of the argument to the hearer. two main conclusions are drawn: 1) clue words can occur in conjunction with coherent transmissions, to reduce processing of the hearer 2) clue words must occur with more complex forms of transmission, to facilitate recognition of the argument structure. interpretation rules to process clues are proposed. in addition, a relationship between use of clues and complexity of processing is suggested for the case of exceptional transmission strategies.
n-gram cluster identification during empirical knowledge representation generation. this paper presents an overview of current research concerning knowledge extraction from technical texts. in particular, the use of empirical techniques during the identification and generation of a semantic representation is considered. a key step is the discovery of useful n-grams and correlations between clusters of these n-grams.
extracting the names of genes and gene products with a hidden markov model. we report the results of a study into the use of a linear interpolating hidden markov model (hmm) for the task of extracting technical terminology from medline abstracts and texts in the molecular-biology domain. this is the first stage in a system that will extract event information for automatically updating biology databases. we trained the hmm entirely with bigrams based on lexical and character features in a relatively small corpus of 100 medline abstracts that were marked-up by domain experts with term classes such as proteins and dna. using cross-validation methods we achieved an f-score of 0.73 and we examine the contribution made by each part of the interpolation model to overcoming data sparseness.
can computers handle adverbs? the adverb is the most complicated, and perhaps also the most interesting part of speech. past research in natural language processing, however, has not dealt seriously with adverbs, though linguists have done significant work on this word class. the current paper draws on this linguistic research to organize an adverbial lexicon which will be useful for information retrieval and natural language processing systems.
conveying implicit content in narrative summaries. one of the key characteristics of any summary is that it must be concise. to achieve this the content of the summary (1) must be focused on the key events, and (2) should leave out any information that the audience can infer on their own. we have recently begun a project on summarizing simple narrative stories. in our approach, we assume that the focus of the story has already been determined and is explicity given in the story's long-term representation; we concentrate instead on how one can plan what inferences an audience will be able to make when they read a summary. our conclusion is that one should think about inferences as following from the audience's recognition of the central concepts in the story's plot, and then plan the textual structure of the summary so as to reinforce that recognition.
parsing and case analysis in tanka. the tanka project seeks to build a model of a technical domain by semi-automatically processing unedited english text that describes this domain. each sentence is parsed and conceptual elements are extracted from the parse. concepts are derived from the case structure of a sentence, and added to a conceptual network that represents knowledge about the domain. the dipett parser has a particularly broad coverage of english syntax; its newest version can also process sentence fragments. the haiku subsystem is responsible for user-assisted semantic interpretation. it contains a case analyzer module that extracts phrases marking concepts from the parse and uses its past processing experience to derive the most likely case realizations of each with almost no a priori semantic knowledge. the user must validate these selections. a key issue in our research is minimizing the number of interactions with the user by intelligently generating the alternatives offered.
towards machine translation using contextual information. a proposal is made for the use of contextual information in the machine translation of japanese and english. this paper describes the use of a context monitor to maintain contextual information dynamically and the augmentation of appropriate features to a semantic network to enable simple inference. the approach taken is that of "best guess" processing with the contextual information being handled with semantic information on a shallow level.
a binding rule for government-binding parsing. in this paper i propose a binding rule for the identification of pronoun and anaphor referents in phrase-structure tress, assuming the general framework of the government-binding theory outlined by chomsky (1981). the binding rule, specified by means of an attribute grammar, is a particular instantiation of the free indexing rule and binding axioms in chomsky's binding theory, with certain empirical and practical advantages. the complexities of the binding rule proposed, as well as that inherent in chomsky's binding theory, are studied, and it is shown that the new rule is more psychologically plausible and computationally efficient than the original theory on which it is based. the fragment of the attribute grammar shown here is part of an english grammar and parser being developed in the prolog and plnlp languages.
lexical disambiguation using simulated annealing. the resolution of lexical ambiguity is important for most natural language processing tasks, and a range of computational techniques have been proposed for its solution. none of these has yet proven effective on a large scale. in this paper, we describe a method for lexical disambiguation of text using the definitions in a machine-readable dictionary together with the technique of simulated annealing. the method operates on complete sentences and attempts to select the optimal combinations of word senses for all the words in the sentence simultaneously. the words in the sentences may be any of the 28,000 headwords in longman's dictionary of contemporary english (ldoce) and are disambiguated relative to the senses given in ldoce. our initial results on a sample set of 50 sentences are comparable to those of other researchers, and the fully automatic method requires no hand-coding of lexical entries, or hand-tagging of text.
the week at a glance - cross-language cross-document information extraction and translation. work on the production of texts in english describing instances of a particular event type from multiple news sources will be described. a system has been developed which extracts events, such as meetings, from texts in english, russian, spanish, and japanese. the extraction is currently carried out using only ontological information. the results of a set of such extractions were combined to produce a table of event instances, date stamped, with links back to the original documents. the original documents can then be summarized and translated by the system on demand.by using techniques from information retrieval, information extraction, summarization, and machine translation, in a multi-lingual environlment, new documents can be produced which provide "at a glance" access to news ell events from multiple sources.the paper concludes with a discussion of the key resources which need to be developed to enhance the accuracy and coverage of the techniques used in our experiment.
a matching technique in example-based machine translation. this paper addresses an important problem in example-based machine translation (embt), namely how to measure similarity between a sentence fragment and a set of stored examples. a new method is proposed that measures similarity according to both surface structure and content. a second contribution is the use of clustering to make retrieval of the best matching example from the database more efficient. results on a large number of test cases from the celex database are presented.
an empirical investigation of the relation between discourse structure and co-reference. we compare the potential of two classes of linear and hierarchical models of discourse to determine co-reference links and resolve anaphors. the comparison uses a corpus of thirty texts, which were manually annotated for co-reference and discourse structure.
frame based recognition of theme continuity. the paper describes a system which determines continuity and shifts in english texts on the basis of sentential themes. the theme object within the thematic component of a sentence is determined and a search is made to associate it with a frame shared with the previous theme or themes. if the theme object cannot be associated directly with one of these frames, interpretive rules are applied to do so indirectly through one of the frames normally associated with the object but not yet with the text.
gate-a general architecture for text engineering. much progress has been made in the provision of reusable data resources for natural language engineering, such as grammars, lexicons, thesauruscs. although a number of projects have addressed the provision of reusable algorithmic resources (or 'tools'), takeup of these resources has been relatively slow. this paper describes gate, a general architecture for text engineering, which is a freely-available system designed to help alleviate the problem.
augmented x'-schemes. the paper presents the embedding of an original parsing strategy for romanian, called segmentation-cohesion-dependency (scd), into chomsky's well-known government and binding (bg) theory. in order to bring closer the scd concepts and techniques to the gb theory, the following questions have had to be dealt with: (1) a specification of the principle of maximal projection (pmp), (2) extending the x'-theory (x - bar) by introdusing augmented x' (ax')-schemes, these ones being obtained by (3) specific constraints imposed on the new shapes of x'-schemes. (4) the ax'-schemes can be represented in terms of a tree (paranthetic) language, whose translation in a logic programming language follows naturally.
grafon: a grapheme-to-phoneme conversion system for duth. we describe a set of modules that together make up a grapheme-to-phoneme coversion system for dutch. modules include a syllabification program, a fast morphological parser, a lexical database, a phonological knowledge base, transliteration rules, and phonological rules. knowledge and procedures were implemented object-orientedly. we contrast grafon to recent pattern recognition and rule-compiler approaches and try to show that the first fails for languages with concatenative compounding (like dutch, german, and scandinavian languages) while the second lacks the flexibility to model different phonological theories. it is claimed that syllables (and not graphemes/phonemes or morphemes) should be central units in a rule-based phonemisation algorithm. furthermore, the architecture of grafon and its user interface make it ideally suited as a rule-testing tool for phonologists.
unsupervised discovery of phonological categories through supervised learning of morphological rules. we describe a case study in the application of symbolic machine learning techniques for the discovery of linguistic rules and categories. a supervised rule induction algorithm is used to learn to predict the correct diminutive suffix given the phonological representation of dutch nouns. the system produces rules which are comparable to rules proposed by linguists. furthermore, in the process of learning this morphological task, the phonemes used are grouped into phonologically relevant categories. we discuss the relevance of our method for linguistics and language technology.
automatic processing of large corpora for the resolution of anaphora references. manual acquisition of semantic constraints in broad domains is very expensive. this paper presents an automatic scheme for collecting statistics on cooccurrence patterns in a large corpus. to a large extent, these statistics reflect semantic constraints and thus are used to disambiguate anaphora references and syntactic ambiguities. the scheme was implemented by gathering statistics on the output of other linguistic tools. an experiment was performed to resolve references of the pronoun "it" in sentences that were randomly selected from the corpus. the results of the experiment show that in most of the cases the cooccurrence statistics indeed reflect the semantic constraints and thus provide a basis for a useful disambiguation tool.
kind types in knowledge representation. this paper describes kind types (kt), a system which uses commonsense knowledge to reason about natural language text. kt encodes some of the knowledge underlying natural language understanding, including category distinctions and descriptions differentiating real-world objects, states and events. it embeds an ontology reflecting the ordinary person's top-level cognitive model of real-world distinctions and a database of prototype descriptions of real-world entities. kt is transportable, empirically-based and constrained for efficient reasoning in ways similar to human reasoning processes.
morphological rule induction for terminology acquisition. we present the identification in corpora of french relational adjectives (radj) such as gazeux (gascous) which is derived from the noun gaz (gas). radj appearing in nominal phrases are interesting for terminology acquisition because they hold a naming function. the derivational rules employed to compute the noun from which has been derived the radj are acquired semi-automatically from a tagged and a lemmatized corpora. these rules are then integrated into a termer which identifies radj thanks to their property of being paraphrasable by a prepositional phrase. radj and compound nouns which include a radj are then quantified, their linguistic precision is measured and their informative status is evaluated thanks to a thesaurus of the domain.
towards automatic extraction of monolingual and bilingual terminology. in this paper, we make use of linguistic knowledge to identify certain noun phrases, both in english and french, which are likely to be terms. we then test and compare different statistical scores to select the "good" ones among the candidate terms, and finally propose a statistical method to build correspondences of multi-words units across languages.
modeling syntactic constraints on anaphoric binding. syntactic constraints on antecedent-anaphor relations can be stated within the theory of lexical functional grammar (henceforth lfg) through the use of functional uncertainty (kaplan and maxwell 1988; halvorsen and kaplan 1988; kaplan and zaenen 1989). in the following, we summarize the general characteristics of syntactic constraints on anaphoric binding. next, we describe a variation of functional uncertainty called inside-out functional uncertainty and show how it can be used to model anaphoric binding. finally, we discuss some binding constraints claimed to hold in natural language to exemplify the mechanism. we limit our attention throughout to coreference possibilities between definite antecedents and anaphoric elements and ignore interactions with quantifiers. we also limit our discussion to intrasentential relations.
on the satisfiability of complex constraints. the main problem arising from the use of complex constraints in computational linguists is due to the np-hardness of checking whether a given set of constraints is satisfiable and, in the affirmative case, of generating the set of minimal models which satisfy the constraints. in this paper we show how the clg approach to rewriting constraints while constructing a partial model can greatly reduce the size of the original constraints and thus contribute to reduce the computational problem.
pronouncing text by analogy. pronunciation-by-analogy (pba) is an emerging technique for text-phoneme conversion based on a psychological model of reading aloud. this paper explores the impact of certain basic implementational choices on the performance of various pba models. these have been tested on their ability to pronounce sets of short pseudowords previously used in similar studies, as well as lexical words temporarily removed from the dictionary. best results of 85.7% and 67.9% words correct are obtained for the pseudowords and lexical words respectively, casting doubt on certain previous-reported performance figures in the literature.
simple features for chinese word sense disambiguation. in this paper we report on our experiments on automatic word sense disambiguation using a maximum entropy approach for both english and chinese verbs. we compare the difficulty of the sense-tagging tasks in the two languages and investigate the types of contextual features that are useful for each language. our experimental results suggest that while richer linguistic features are useful for english wsd, they may not be as beneficial for chinese.
integrating compositional semantics into a verb lexicon. we present a class-based approach to building a verb lexicon that makes explicit the close association between syntax and semantics for levin classes. we have used lexicalized tree adjoining grammars to capture the syntax associated with each verb class and have augmented the trees to include selectional restrictions. in addition, semantic predicates are associated with each tree, which allow for a compositional interpretation.
conceptual and linguistic decisions in generation. generation of texts in natural language requires making conceptual and linguistic decisions. this paper shows first that these decisions involve the use of a discourse grammar, secondly that they are all dependent on one another but that there is a priori no reason to give priority to one decision rather than another. as a consequence, a generation algorithm must not be modularized in components that make these decisions in a fixed order.
a complete integrated nlg system using ai and nlu tools. a standard architecture for an nlg system has been defined in (reiter and dale, 2000). their work describes the modularization of an nlg system and the tasks of each module. however, they do not indicate what kind of tools can be used by each module. nevertheless, we believe that certain tools widely used by the ai or nlu community are appropriate for nlg tasks. this paper presents a complete integrated nlg system which uses a description logic for the content determination module, segmented discourse representation theory for the document structuring module and a lexicalized formalism for the tactical component. the nlg system, which takes into account a user model, is illustrated with a generator which produces texts explaining the steps taken by a proof assistant.
synthesis of spoken messages from semantic representations. semantic-representation-to-speech system. a semantic-representation-to-speech system communicates orally the information given in a semantic representation. such a system must integrate a text generation module, a phonetic conversion module, a prosodic module and a speech synthesizer. we will see how the syntactic information elaborated by the text generation module is used for both phonetic conversion and prosody, so as to produce the data that must be supplied to the speech synthesizer, namely a phonetic chain including prosodic information.
morphology and cross dependencies in the synthesis of personal pronouns in romance languages. this paper describes some of the problems that arise from the synthesis of personal pronouns in a system that generates texts in romance languages. it puts the emphasis first on the fact that the morphological level has to be taken into account early in the generation process, second on the numerous "cross dependency" phenomena which are to be found when the synthesis of an element x depends upon that of another element y and when the synthesis of y depends upon that of x. the linguistic examples are taken from french and italian languages, for which a robust generation system has been implemented.
corpus-based annotated test set for machine translation evaluation by an industrial user. this article is concerned with the building of a test data set for assisting the industrial user in machine translation evaluation. the emphasis is laid on the interest of an approach based on the study of bilingual corpus pragmatic characteristics. the study of one chapter of the maintenance manual of the super puma helicopter made it possible to identify the pragmatic characteristics relevant in the choice of the morpho-syntactic structures and translation processes actually used. the textual test set consists in a sgml file including the source text sequences aligned with the reference translation sequences and also including the pragmatic, formal and translational characteristics in the form of annotations (labels and formal descriptions).
aligning sentences in bilingual texts french - english and french - arabic. in this paper, we will tackle the problem raised by the automatic alignment of sentences belonging to bilingual text pairs. the method that we advocate here is inspired by what a person with a fair knowledge of the other langage would do intuitively. it is based on the matching of the elements which are similar in both sentences. however, to match these elements correctly, we first have to match the sentences that contain them. there seems to be a vicious circle here. we will show how to break it. on the one hand, we will describe the hypotheses we made, and, on the other hand, the algorithms which ensued. the experiments are carried out with french-english and french-arabic text pairs.we will show that matching sentences and, later, expressions, amounts to raising a new problem in the machine translation field, i. e. the problem of recognition instead of that of translation, strictly speaking.
dealing with cross-sentential anaphora resolution in alep. the experiments described here have been done in connection with the ls-gram project, which is concerned with the development of large scale grammars and thus foreseen the coverage of "real life texts". but in order to deal with such texts, it is also necessary to process linguistic units which are larger than sentences. the resolution of cross-sentential anaphora is one of the problems we have to deal with, when we switch towards the analysis of such larger linguistic units. in order to propose an analysis of the cross-sentential anaphora, one has to be able to refer back to an antecedent, which is to be found in a preceding sentence. this will be done on the basis of an information-passing framework. using also the simple unification technique a resolution of the pronoun can then be tried out: parts of the content information of the pronoun are going to be compared (unified) with specific parts of the content information of the (possible) antecedent.
authoring multimedia documents using wysiwym editing. (1)this paper outlines a future 'ideal' multimedia document authoring system that allows authors to specify content and form of the document independently of each other and at a high level of abstraction;(2)it describes a working system that implements a small but significant part of the functionality of such an ideal system, based on semantic modeling of the pictures as well as the text of the document; and(3)it explains what needs to be done to bridge the gap between the implemented system and the ideal one.
theory refinement and natural language learning. this paper presents a learning system for identifying syntactic structures. this system relies on the use of background knowledge and default values in order to build up an initial grammar and the use of theory refinement in order to improve this grammar. this combination provides a good machine learning framework for natural language learning. we illustrate this point with the presentation of allis, a learning system which generates a regular expression grammar of non-recursive phrases from bracketed corpora.
an approach based on multilingual thesauri and model combination for bilingual lexicon extraction. this paper focuses on exploiting different models and methods in bilingual lexicon extraction, either from parallel or comparable corpora, in specialized domains. first, a special attention is given to the use of multilingual thesauri, and different search strategies based on such thesauri are investigated. then, a method to combine the different models for bilingual lexicon extraction is presented. our results show that the combination of the models significantly improves results, and that the use of the hierarchical information contained in our thesaurus, umls/mesh, is of primary importance. lastly, methods for bilingual terminology extraction and thesaurus enrichment are discussed.
a message processing system with object-centered semantics. this paper presents a report processing method with object-centered semantics. the syntactic analysis is performed along classical generative principles, though with a deliberately simple output as a list of index-value doublets, which the semantic module processes using methods in an object-oriented framework. the final representation is made of two types of object-centered structures: first, case like, event level dated structures corresponding to the input clauses: second, detailed representation of the current state of an agent of the reference world, plus records for the follow-up of a task over time. uncertainty, imprecision and prevision are handled using specialized fields. this framework is applied to the processing of daily naval reports in english.
language-specific mappings from semantics to syntax. we present a study of the mappings from semantic content to syntactic expression with the aim of isolating the precise locus and role of pragmatic information in the generation process. from a corpus of english, french, and portuguese instructions for consumer products, we demonstrate the range of expressions of two semantic relations, generation and enablement (goldman, 1970) in each language, and show how the available choices are constrained syntactically, semantically, and pragmatically. the study reveals how multilingual nlg can be informed by language-specific principles for syntactic choice.
rapid prototyping for spoken dialogue systems. we implemented a spoken dialogue system architecture for rapid prototyping. the features that support rapid prototyping include a clear separation of generic dialogue processing algorithms from domain and language specific knowledge sources. in an experiment, it could be shown that six individuals could specify these domain and language specific knowledge sources within 8 to 12 hours to come up with a prototypical implementation of a spoken dialogue system. to that end, no dialogue strategy had to be specified. rather, it was sufficient to provide an ontology, a description of the services offered by the system, parsing grammars, database conversion rules and generation templates. furthermore, the experiment shows that it is possible to formulate dialogue strategies in a domain and language independent manner; thus not requiring a system designer to be knowledgeable about dialogue processing.
using focus to generate complex and simple sentences. one problem for the generation of natural language text is determining when to use a sequence of simple sentences and when a single complex one is more appropriate. in this paper, we show how focus of attention is one factor that influences this decision and describe its implementation in a system that generates explanations for a student advisor expert system. the implementation uses tests on functional information such as focus of attention within the prolog definite clause grammar formalism to determine when to use complex sentences, resulting in an efficient generator that has the same benefits as a functional grammar system.
generation of thesaurus in different languages a computer based system. the development of the theory of library classification and of subject indexing, for the organisation, storage and retrieval of subjects embodied in documents has a striking parallelism to the search for 'universal forms' and deep structure' in language and linguistic studies. the significant contributions of the theories of classification and subject indexing are the subject analysis techniques of ranganathan and bhattacharyya's popsi. a computer based system, for generating an information retrieval thesaurus, from modulated subject-propositions, formulated according to the subject analysis techniques, enriched with certain codes for relating the terms in the subject-propositions has been developed. the system generates hierarchic, associative, coordinate and synonymous relationships between terms and presents them as an alphabetical thesaurus. also, once a thesaurus is generated in one language it is possible to produce the same thesaurus in different languages by just forming a table of equivalent terms in the required language.
the parallel expert parser (pep): a thoroughly revised descendent of the word expert parser (wep). in this paper we present pep (the parallel expert parser, devos 1987), a radically revised descendant of wep (the word expert parser, small 1980). wep's idea of linguistic entities as interacting processes has been retained, but its adherence to the word as the only entity has been rejected. experts exist at different levels, communicate through rigidly defined protocols and are now fully designed to run in parallel. a prototype of pep is implemented in flat concurrent prolog and runs in a logix environment.
gpsg parsing, bidirectional charts, and connection graphs. this paper describes a tractable method for parsing gpsg grammars without altering the modularity and expressiveness of this formalism. the proposed method is based on a constraint propagation mechanism which reduces the number of unnecessary structures built at parse time through the early detection of inadmissible local trees. the propagation of constraints is rendered efficient by indexing constraints and categories in a connection graph and by using a bidirectional chart parser together with a bottom-up strategy centered around head constituents.
stylistic grammars in language translation. we are developing stylistic grammars to provide the basis for a french and english stylistic parser. our stylistic grammar is a branching stratificational model, built upon a foundation dealing with lexical, syntactic, and semantic stylistic realizations. its central level uses a vocabulary of constituent stylistic elements common to both english and french, while the top level correlates stylistic goals, such as clarity and concreteness, with patterns of these elements.overall, we are implementing a computational schema of stylistics in french-to-english translation. we believe that the incorporation of stylistic analysis into machine translation systems will significantly reduce the current reliance on human post-editing and improve the quality of the systems' output.
tree directed grammars. tree directed grammars as a special kind of translation grammars are defined. it is shown that a loop-free tree directed grammar can be transformed into an equivalent top-down tree transducer, and from this fact it follows that given an arbitrary context-free language as input, a tree directed grammar produces an output language which is at most context-sensitive.
communicative triad as a structural element of language interaction. researches on dialogue natural-language interaction with intellectual "human-computer" systems are based on models of language "human-to-human" interaction, these models representing descriptions of communication laws. an aspect of developing language interaction models is an investigation of dialogue structure. in the paper a notion of elementary communicative triad (sr-triad) is introduced to model the "stimulus-reaction" relation between utterances in the dialogue. the use of the sr-triad apparatus allows us to represent a scheme of any dialogue as a triad structure. sr-triad structure being inherent both to natural and programming language dialogues, sr-system is claimed to be necessary while developing dialogue processors.
exploiting reference interaction in resolving temporal reference. this paper provides an account of the role that the interaction between nominal and temporal reference plays in resolving temporal reference. exploiting this interaction in resolving temporal reference clarifies how the process of resolving nominal reference interacts with the process of resolving temporal reference, and how a restricted set of world knowledge contributes to resolving temporal reference.
a computational model of incremental utterance production in task-oriented dialogues. this paper presents a computational model of incremental utterance production in task-oriented dialogues. this model incrementally produces utterances to propose the solution of a given problem, while simultanceously solving the problem in a stepwise manner. even when the solution has been partially determined, this model starts utterances to satisfy time constraints where pauses in mid-utterance must not exceed a certain length. the results of an analysis of discourse structure in a dialogue corpus are presented and the fine structure of discourse that contributes to the incremental strategy of utterance production is described. this model utilizes such a discourse structure to incrementally produce utterances constituting a discourse. pragmatic constraints are exploited to guarantee the relevance of discourses, which are evaluated by an utterance simulation experiment.
translation ambiguity resolution based on text corpora of source and target languages. we propose a new method to resolve ambiguity in translation and meaning interpretation using linguistic statistics extracted from dual corpora of source and target languages in addition to the logical restrictions described on dictionary and grammar rules for ambiguity resolution. it provides reasonable criteria for determining a suitable equivalent translation or meaning by making the dependency relation in the source language be reflected in the translated text. the method can be tractable because the required statistics can be computed semi-automatically in advance from a source language corpus and a target language corpus, while an ordinal corpus-based translation method needs a large volume of bilingual corpus of strict pairs of a sentence and its translation. moreover, it also provides the means to compute the linguistic statistics on the pairs of meaning expressions.
word sense ambiguation: clustering related senses. this paper describes a heuristic approach to automatically identifying which senses of a machinereadable dictionary (mrd) headword are semantically related versus those which correspond to fundamentally different senses of the word. the inclusion of this information in a lexical database profoundly alters the nature of sense disambiguation: the appropriate "sense" of a polysemous word may now correspond to some set of related senses. our technique offers benefits both for on-line semantic processing and for the challenging task of mapping word senses across multiple mrds in creating a merged lexical database.
word manager: a system for the definition, access and maintenance of lexical databases. this paper describes word manager, a system which is currently the object of a research project at the university of z&uuml;rich computer science department. word manager supports the definition, access and maintenance of lexical databases. it comprises a formal language for the implemenation of morphological knowledge. this formal language is integrated in a graphics-oriented, high-level user interface and is language independent. the project is now in the prototyping phase where parts of the software are pretty far advanced (the user interface) and others are still rudimentary (the rule compiler/runtime system). the design of the system was strongly influenced by koskenniemi's two-level model /koskenniemi 1983/, its successors /bear 1986/, /black 1986/, /borin 1986/, /darymple 1987/, the ansi-sparc 3-schema concept /ansi-x3-sparc 1975/ and visual programming techniques /bocker 1986/, /myers 1986/; we will focus the discussion on one aspect: the user interfacing for the construction of the lexical data base.
lexeme-based morphology: a computationaily expensive approach intended for a server-architecture. this paper presents an approach to computational morphology which can be considered as being derived from the two-level model but differs from this substantially. lexemes rather than formatives are the most important entities distinguished in this approach. the consequence is that a new formalism for the specification of morphological knowledge is required. a short description of a system called word manager will outline the characteristics of such a formalism, the most prominent of which is that different subformalisms for inflectional rules and word-formation rules are distinguished. these rules are applied separately though not independently and support the concept of lexicalization. the primary advantage of this is that the system can build up a network of knowledge on how formatives, lexemes, and rules depend on each other while individual lexemes are lexicalized. thus, the system will know the inflectional forms of a lexeme, the destructuring of these forms into formatives, how the lexeme has been derived or composed if it is a word-formation, etc. this requires much memory, yet, the philosophy behind the approach is that the system runs as a server on a local area network, so that an entire machine can be dedicated to the task, if necessary.
towards a dedicated database management system for dictionaries. this paper argues that a lexical database should be implemented with a special kind of database management system (dbms) and outlines the design of such a system. the major difference between this proposal and a general purpose dbms is that its data definition language (ddl) allows the specification of the entire morphology, which turns the lexical database from a mere collection of 'static data into a real-time word-analyser. moreover, the dedication of the system conduces to the feasibility of user interfaces with very comfortable monitor-and manipulation functions.
xtag system - a wide coverage grammar for english. this paper present the xtag system, a grammar development tool based on the tree adjoining grammar (tag) formalism that includes a wide-coverage syntactic grammar for english. the various components of the system are discussed and preliminary evaluation results from the parsing of various corpora are given. results from the comparison of xtag against the ibm statistical parser and the alvey natural language tool parser are also given.
integrating stress and intonation into a concept-to-speech system. the paper deals with the integration of intonation algorithms into a concept-to-speech system for german. the algorithm for computing the stress hierarchy of a sentence introduced by kiparski (1973) and the theory of syntactic grouping for intonation patterns developed by bierwisch (1973) have been studied extensively, but they have never been implemented in a concept-to-speech system like the one presented here. we describe the back end of this concept-to-speech system: the surface generator transfers a hierarchical dependency structure of a sentence into a phoneme string by traversing it in a recursive-descent manner. surface structures unfold while generation proceeds, which means that at no point of the process does the full syntactic tree structure exist. as they depend on syntactic features, both the indices introduced by the kiparski (degrees of stress) and the bierwisch (indexed border markers) formalism have to be inserted by the generator. this implies some changes to the original algorithms, which are demonstrated in this paper. the generator has been tested in the domain of an expert system that helps to debug electronic circuits. the synthesized utterances of the test domain show significant improvements over monotonous forms of speech produced by systems not making use of intonation information.
semantic-based transfer. this article presents a new semantic-based transfer approach developed and applied within the verbmobil machine translation project. we give an overview of the declarative transfer formalism together with its procedural realization. our approach is discussed and compared with several other approaches from the mt literature. the results presented in this article have been implemented and integrated into the verbmobil system.
parameterization of the interlingua in machine translation. the task of designing as interlingual machine translation system is difficult, first because the designer must have a knowledge of the principles underlying crosslinguistic distinctions for the languages under consideration, and second because the designer must then be able to incorporate this knowledge effectively into the system. this paper provides a catalog of several types of distinctions among spanish, english, and german, and describes a parametric approach that characterizes these distinctions, both at the syntactic level and at the lexical-semantic level. the approach described here is implemented in a system called unitran, a machine translation system that translates english, spanish, and german bidirectionally.
role of word sense disambiguation in lexical acquisition: predicting semantics from syntactic cues. this paper addresses the issue of word-sense ambiguity in extraction from machine-readable resources for the construction of large-scale knowledge sources. we describe two experiments: one which ignored word-sense distinctions, resulting in 6.3% accuracy for semantic classification of verbs based on (levin, 1993); and one which exploited word-sense distinctions, resulting in 97.9% accuracy. these experiments were dual purpose: (1) to validate the central thesis of the work of (levin, 1993), i.e., that verb semantics and syntactic behavior are predictably related; (2) to demonstrate that a 15-fold improvement can be achieved in deriving semantic information from syntactic cues if we first divide the syntactic cues into distinct groupings that correlate with different word senses. finally, we show that we can provide effective acquisition techniques for novel word senses using a combination of online sources.
feature logic with disjunctive unification. we introduce feature terms containing sorts, variables, negation and named disjunction for the specification of feature structures. we show that the possibility to label disjunctions with names has major advantages both for the use of feature logic in computational linguistics and its implementation. we give an open world semantics for feature terms, where the denotation of a term is determined in dependence on the disjunctive context, i.e. the choices taken for the disjunctions. we define context-unique feature descriptions, a relational, constraint-based representation language and give a normalization procedure that allows to test consistency of feature terms. this procedure does not only avoid expansion to disjunctive normal form but maintains also structure sharing between information contained in different disjuncts as much as possible. context-unique feature descriptions can be easily implemented in environments that support ordinary unification (such as prolog).
discourse anaphora. this paper reports on a model that serves anaphora resolution. a distinction will be made between possible antecedents and preferred antecedents. the set of linguistically possible candidates will be defined in terms of compatibility and recency. preferred antecedents are a subset of the possible antecedents, selected by the application of extralinguistic knowledge. motivation for the particular design and comparison with other approaches are extensive.
towards robust patr. we report on the initial stages of development of a robust parsing system, to be used as part of the editor's assistant, a program that detects and corrects textual errors and infelicities in the area of syntax and style. our mechanism extends the standard patr-ii formalism by indexing the constraints on rules and abstracting away control of the application of these constraints. this allows independent specification of grouping and ordering of the constraints, which can improve the efficiency of processing, and in conjunction with information specifying whether constraints are necessary or optional, allows detection of syntactic errors.
hopfield models as nondeterministic finite-state machines. the use of neural networks for integrated linguistic analysis may be profitable. this paper presents the first results of our research on that subject: a hopfield model for syntactical analysis. we construct a neural network as an implementation of a bounded push-down automaton, which can accept context-free languages with limited center-embedding. the network's behavior can be predicted a priori, so the presented theory can be tested. the operation of the network as an implementation of the acceptor is provably correct. furthermore we found a solution to the problem of spurious states in hopfield models: we use them as dynamically constructed representations of sets of states of the implemented acceptor. the so-called neural-network acceptor we propose, is fast but large.
towards discourse-oriented nonmonotonic system. the purpose of this paper is to analyse the phenomenon of nonmonotonicity in a natural language and to formulate a number of general principles which should be taken into consideration while constructing a discourse oriented nonmonotonic formalism.
inferring knowledge from a large semantic network. in this paper, we present a rich semantic network based on a differential analysis. we then detail implemented measures that take into account common and differential features between words. in a last section, we describe some industrial applications.
grice incorporated cooperativity in spoken dialogue. the paper presents a consolidated set of principles of cooperative spoken human-machine dialogue which have the potential for being turned into practically applicable design guidelines. the principles have been validated in three ways. they were established from a wizard of oz simulation corpus used to develop the dialogue model for a spoken language dialogue system. developed independently of gricean theory, some of the principles were refined through comparison with grice's maxims of cooperativity in conversation. finally, the principles were tested in the user test of the implemented dialogue system. the paper shows that grice's maxims constitute a sub-set of the principles. the non-gricean principles and dialogue aspects they introduce are presented and discussed.
text authoring, knowledge acquisition and description logics. we present a principled approach to the problem of connecting a controlled document authoring system with a knowledge base. we start by describing closed-world authoring situations, in which the knowledge base is used for constraining the possible documents and orienting the user's selections. then we move to open-world authoring situations in which, additionally, choices made during authoring are echoed back to the knowledge base. in this way the information implicitly encoded in a document becomes explicit in the knowledge base and can be re-exploited for simplifying the authoring of new documents. we show how a datalog kb is sufficient for is the closed-world situation, while a description logic kb is better-adapted to the more complex open-world situation, all along, we pay special attention to logically sound solutions and to decidability issues in the different processes.
two approaches to commonsense inferencing for discourse analysis. the dominant philosophy regarding the formalization of commonsense inferencing in the physical domain consists in the exploitation of the "tarskian" scheme axiomatization <-> interpretation borrowed from mathematical logic. the commonsense postulates constitute the axiomatization, and the real world provides the "model" for this axiomatization.the observation of the effective activity of linguistic communication and of the commonsense inferencing processes which are involved in it show the unacceptability of this scheme.an alternative is proposed, where the notion of "conceptual category" plays a principal role, and where the principle of logical adequation of an axiomatization to a model is replaced by a notion of "projection" of a conceptual structure onto the observed reality.
a generalized greibach normal form for definite clause grammars. an arbitrary definite clause grammar can be transformed into a so-called generalized greibach normal form (ggnf), a generalization of the classical greibach normal form (gnf) for context-free grammars.the normalized definite clause grammar is declaratively equivalent to the original definite clause grammar, that is, it assigns the same analyses to the same strings. offline-parsability of the original grammar is reflected in an elementary textual property of the transformed grammar. when this property holds, a direct (top-down) prolog implementation of the normalized grammar solves the parsing problem: all solutions are enumerated on backtracking and execution terminates.when specialized to the simpler case of context-free grammars, the ggnf provides a variant to the gnf, where the transformed context-free grammar not only generates the same strings as the original grammar, but also preserves their degrees of ambiguity (this last property does not hold for the gnf).the ggnf seems to be the first normal form result for dcgs. it provides an explicit factorization of the potential sources of undecidability for the parsing problem, and offers valuable insights on the computational structure of unification grammars in general.
a simple transformation for onine-parsable grammars and its termination properties. we present, in easily reproducible terms, a simple transformation for offline-parsable grammars which results in a provably terminating parsing program directly top-down interpretable in prolog. the transformation consists in two steps: (1) removal of empty-productions, followed by: (2) left-recursion elimination. it is related both to left-corner parsing (where the grammar is compiled, rather than interpreted through a parsing program, and with the advantage of guaranteed termination in the presence of empty productions) and to the generalized greibach normal form for dcgs (with the advantage of implementation simplicity).
extended dependency structures and their formal interpretation. we describe two "semantically-oriented" dependency-structure formalisms, u-forms and s-forms. u-forms have been previously used in machine translation as interlingual representations, but without being provided with a formal interpretation. s-forms, which we introduce in this paper, are a scoped version of u-forms, and we define a compositional semantics mechanism for them. two types of semantic composition are basic: complement incorporation and modifier incorporation. binding of variables is done at the time of incorporation, permitting much flexibility in composition order and a simple account of the semantic effects of permuting several incorporations.
a symmetrical approach to parsing and generation. lexical grammars are a class of unification grammars which share a fixed rule component, for which there exists a simple left-recursion elimination transformation. the parsing and generation programs are seen as two dual non-left-recursive versions of the original grammar, and are implemented through a standard top-down prolog interpreter. formal criteria for termination are given as conditions on lexical entries: during parsing as well as during generation the processing of a lexical entry consumes some amount of a guide; the guide used for parsing is a list of words remaining to be analyzed, while the guide for generation is a list of the semantics of constituents waiting to be generated.
xml and multilingual document authoring: convergent trends. typical approaches to xml authoring view a xml document as a mixture of structure (the tags) and surface (text between the tags). we advocate a radical approach where the surface disappears from the xml document altogether to be handled exclusively by rendering mechanisms. this move is based on the view that the author's choices when authoring xml documents are best seen as language-neutral semantic decisions, that the structure can then be viewed as interlingual content, and that the textual output should be derived from this content by language-specific realization mechanisms, thus assimilating xml authoring to multilingual document authoring. however, standard xml tools have important limitations when used for such a purpose: (1) they are weak at propagating semantic dependencies between different parts of the structure, and, (2) current xml rendering tools are ill-suited for handling the grammatical combination of textual units. we present two related proposals for overcoming these limitations: one (gf) originating in the tradition of mathematical proof editors and constructive type theory, the other (ig), a specialization of definite clause grammars strongly inspired by gf.
context-free grammar rewriting and the transfer of packed linguistic representations. we propose an algorithm for the trausfer of packed linguistic structures, that is, finite collections of labelled graphs which share certain subparts. a labelled graph is seen as a word over a vocabulary of description elements (nodes, arcs, labels), and a collection of graphs as a set of such words, that is, as a language over description elements. a packed representation for the collection of graphs is then viewed as a context-free grammar which generates such a language. we present an algorithm that uses a conventional set of transfer rules but is capable of rewriting the cfg representing the source packed structure into a cfg representing the target packed structure that preserves the compaction properties of the source cfg.
partial ordering and aktionsarten in discourse representation theory. this paper presents an approach to deal with the underspecification of aktionsarten in german sentences. in german the difference between an accomplishment and the associated progressive state is often not marked on the sentence level. this distinction is important for correctly interpreting texts and for translation into languages which provide morphological markings of aktionsarten. to maintain compositionality we suggest a two-step analysis of a text with respect to the temporal relations and the classification as events or states. this analysis is guided by the discourse representation theory developed by kamp and makes use of world knowledge and an inference component.the problem of classification can be reformulated as the problem of finding an embedding function f from the representational entities onto the domain of a model. the models we use are structures built from intervals of time, events and individuals. considering intensional models of this type will allow us to give truth-conditions for progressive states related to corresponding accomplishments. we restrict ourselves to progressive states of intentional actions and use the beliefs of the agent.
on representing the temporal structure of a natural language text. a proposal to deal with tenses in the framework of discourse representation theory is presented, as it has been implemented for a fragment at the ims for the project lilog. it is based on the theory of tenses of h. kamp and ch. rohrer. the system uses the tense and aspect information, the information about the temporal discourse structure of the preceding text stored in a specific list of possible reference times, and background knowledge. these types of information interact in order to choose a suited temporal anchor for the event of a new sentence.with respect to extended texts, choosing the right reference time for a new event is a problem which has been largely neglected in the literature.
disambiguation by information structure in drt. text understanding and high quality machine translation often necessitate the disambiguation of ambigous structures or lexical elements. drawing inferences from the context can be a means for resolving semantic ambiguities. however, often, this is an expensive strategy that, in addition, not always comes up with a clear preference for one of the alternatives. in this paper, we argue that in a number of cases deep semantic analyses can be avoided by taking into account the constraints that the alternative readings impose onto the information structure. to this end, we present a study of the ambigous german adverb erst and point out the particular circumstances under which the given information structure disambiguates the adverb without further semantic analysis.
formal syntax and semantics of case stacking languages. in this paper the phenomenom of case stacking is investigated from a formal point of view. we will define a formal language with idealized case marking behaviour and prove that stacked cases have the ability to encode structural information on the word thereby allowing for unrestricted word order. furthermore, the case stacks help to compute this structure with a low complexity bound. as a second part we propose a compositional semantics for languages with stacked cases and show how this proposal may work for our formal language as well as for an example from warlpiri.
machine translation method using inductive learning with genetic algorithms. we have proposed a method of machine translation, which acquires translation rules from translation examples using inductive learning, and have evaluated the method. and we have confirmed that the method requires many translation examples. to resolve this problem, we applied genetic algorithms and evaluated it by some experiments. we confirmed that the accuracy rate of translation increased from 52.8% to 61.9% by applying genetic algorithms.
collaboration on reference to objects that are not mutually known. in conversation, a person sometimes has to refer to an object that is not previously known to the other participant. we present a plan-based model of how agents collaborate on reference of this sort. in making a reference, an agent uses the most salient attributes of the referent. in understanding a reference, an agent determines his confidence in its adequacy as a means of identifying the referent. to collaborate, the agents use judgment, suggestion, and elaboration moves to refashion an inadequate referring expression.
towards developing reusable nlp dictionaries. development of resuable dictionaries for nlp applications requires a carefully designed lexicological framework, a lexical acquisition strategy, an integrated development toolbox, and facilities to generate dictionaries for client applications. this paper presents results of the lexic project, which was set up to prepare the development of large multilingual lexical resources.
a lexical functional grammar system in prolog. this paper describes a system in prolog for the automatic transformation of a grammar, written in lfg formalism, into a dcg-based parser. it demonstrates the main principles of the transformation, the representation of f-structures and constraints, the treatment of long-distance dependencies, and left recursion.finally some problem areas of the system and possibilities for overcoming them are discussed.
directional constraint evaluation in optimality theory. weighted finite-state constraints that can count unboundedly many violations make optimality theory more powerful than finite-state transduction (frank and satta, 1998). this result is empirically and computationally awkward. we propose replacing these unbounded constraints, as well as non-finite-state generalized alignment constraints, with a new class of finite-state directional constraints. we give linguistic applications, results on generative power; and algorithms to compile grammars into transducers.
three new probabilistic models for dependency parsing: an exploration. after presenting a novel o(n3) parsing algorithm for dependency grammar, we develop three contrasting ways to stochasticize it. we propose (a) a lexical affinity model where words struggle to modify each other, (b) a sense tagging model where words fluctuate randomly in their selectional preferences, and (c) a generative model where the speaker fleshes out each word's syntactic and conceptual structure without regard to the implications for the hearer. we also give preliminary empirical results from evaluating the three models' parsing performance on annotated wall street journal training text (derived from the penn treebank). in these results, the generative model performs significantly better than the others, and does about equally well at assigning part-of-speech tags.
a formal description of arabic syntax in definite clause grammar. arabic has some special syntax features which lead to complex syntax structures. we have developed a formal description of arabic syntax in definite clause grammar. this grammar is characterized by its high descriptive power due to its dual formulation in terms of functions and in terms of grammatical categories. the developed grammar has a high coverage of arabic language and has context sensitive capabilities. it is suitable for the advanced applications of natural language processing.
generating coherent argumentative paragraphs. we address the problem of generating a coherent paragraph presenting arguments for a conclusion in a text generation system. existing text planning techniques are not appropriate for this task for two main reasons: they do not explain how arguments can be linked together in a linear presentation order and they do not explain how the rhetorical function of a proposition affects its wording.we present a mechanism to generate argumentative paragraphs where argumentative relations constrain not only the rhetorical structure of the paragraph, but also the surface form of each proposition. in our approach, a text planner relies on a set of specific argumentative relations to extract information from the knowledge base, to map it to scalar and context dependent evaluations and to organize it into chains of arguments. the same information used for planning is also used by the surface realization component to perform lexical choice at all the levels of the clause (connectives, main verb, adverbial adjuncts, adjectives and determiners). the mechanism is implemented in the advisor ii system using fuf, an extended functional unification formalism.
generating connectives. we present an implemented procedure to select an appropriate connective to link two propositions, which is part of a large text generation system. each connective is defined as a set of constraints between features of the propositions it connects. our focus has been to identify pragmatic features that can be produced by a deep generator to provide a simple representation of connectives. using these features, we can account for a variety of connective usages, and we can distinguish between similar connectives. we describe how a surface generator can produce complex sentences when given these features in input. the selection procedure is implemented as part of a large functional unification grammar.
language identification in unknown signals. this paper describes algorithms and software developed to characterise and detect generic intelligent language-like features in an input signal, using natural language learning techniques: looking for characteristic statistical "language-signatures" in test corpora. as a first step towards such species-independent language-detection, we present a suite of programs to analyse digital representations of a range of data, and use the results to extrapolate whether or not there are language-like structures which distinguish this data from other sources, such as music, images, and white noise. we assume that generic species-independent communication can be detected by concentrating on localised patterns and rhythms, identifying segments at the level of characters, words and phrases, without necessarily having to "understand" the content.we assume that a language-like signal will be encoded symbolically, i.e. some kind of character-stream. our language-detection algorithm for symbolic input uses a number of statistical clues: data compression ratio, "chunking" to find character bit-length and boundaries, and matching against a zipfian type-token distribution for "letters" and "words". we do not claim extensive (let alone exhaustive) empirical evidence that our language-detection clues are "correct"; the only real test will come when the search for extra-terrestrial intelligence finds true alien signals. if and when true seti signals are found, the first step to interpretation is to identify the language-like features, using techniques like the above. our current research goal is to apply natural language learning techniques to the identification of "higher-level" grammatical and semantic structure in a linguistic signal.
a phrase structure grammar of the arabic language. a lot of work has been done in the field of natural language processing (nlp) for arabic. few researchers have tried hard to apply on arabic the methods of computational linguistics, as for example, definite clause grammar (dcg) [1] and augmented transition networks (atn) [2]. because there is not a modern linguistic model for arabic grammar within the frame of computational linguistics, the results achieved are not comparable with that achieved on english.in this paper, we represent the phrase structures covering arabic. they are completely different from english.
organizing linguistic knowledge for multilingual generation. we propose an architecture for the organisation of linguistic knowledge which allows to (1) separately formulate generalizations for different types of linguistic information, and (2) state interrelations between partial information belonging to different levels of description. we use typed feature structures for encoding linguistic knowledge. we show the application of this representational device for the architecture of linguistic knowledge sources for multilingual generation. as an example, we describe the use of interacting collocational and syntactic constraints in the generation of french and german sentences.
typed unification grammars. we introduce tfs, a computer formalism in the class of logic formalisms which integrates a powerful type system. its basic data structures are typed feature structures. the type system encourages an object-oriented approach to linguistic description by providing a multiple inheritance mechanism and an inference mechanism which allows the specification of relations between levels of linguistic description defined as classes of objects. we illustrate this approach starting from a very simple dcg, and show how to make use of the typing system to enforce general constraints and modularize linguistic descriptions, and how further abstraction leads to a hpsg-like grammar.
knowledge integration in a robust and efficient morpho-syntactic analyser for french. we present a morpho-syntactic analyzer for french which is capable of automatically detecting and of correcting (automatically or with user help) spelling mistakes, agreement errors and certain frequently encountered syntactic errors. emphasizing the specific language knowledge that is used, we describe the major subtasks of this analyzer: word categorization by dictionary look-up and spelling correction, construction of a parse tree or of a forest of parse trees, correction of syntactic and morphological errors by processing the parse tree. the spelling corrector module is designed to help correct the spelling mistakes of a french novice, as opposed to those of an experienced typist. the syntax analysis module is driven by an empirical grammar for french and is based on the work of tomita. the presentation is based on the design and implementation of a prototype of the system which is written in lisp for the macintosh computer.
the implementation of a computational grammar of french using the grammar development environment. the design and implementation of a large-coverage computational grammar of french is described. this grammar is compared to a comprehensive computational grammar of english which was implemented using the same computer workbench. although many similarities may be observed in the two grammars, there are important structural differences which can be traced back to features specific to the french language, notably agreement and eliticization.
decomposition of japanese sentences into normal forms based on human linguistic process. a diversity and a flexibility of language expression forms are awkward problems for the machine processing of language, such as translation, indexing and question-answering. this paper presents a method of decomposing japanese sentences appearing in the patent documents on "pulse network", into normal forms. first, the linguistic information is analysed and classified based on the human linguistic process. then, predicate functions, phrase functions and operators are introduced as the normal forms. finally, the decomposing procedure and some experimental results are shown.
lexical functional grammar in speech recognition. the syntax component of the speech recognition system ikaros is described. the usefulness of a probabiefistic lexical functional grammar both for constraining bottom-up hypotheses and top-down predicting is shown.
indexation de textes: l'apprentissage des concepts. in technical fields, many documents go unread due to a lack of awareness of their existence. a system which indexes texts can find all relevant texts in response to a query. the problem is to establish the indexation. at present, advanced full text systems automatically index texts on the complete thesaurus with computed weights. another way of doing this can be a person choosing the set of relevant concepts. this second solution is better but more costly and dependent on the classification choices made by the operator.to meet these problems, ana (auomatic natural acquisition) had been developed. this system automatically extracts relevant concepts from free texts to produce a semantic network. it does not rely on grammar or lexicon but, instead, is based on an original statistical method.this research brings about two developments: on one hand the system is also capable of extracting the simple grammatical structures it encounters, most often in order to improve its performance, and on the other hand this will lead to an automatic definition of semantic classes of concepts, in order to structure the network.
bottom-up earley deduction. we propose a botto - up variant of earley deduction. bottom-up deduction is preferable to top-down deduction because it allows incremental processing (even for head-driven grammars), it is data-driven, no subsumption check is needed, and preference values attached to lexical items can be used to guide best-first search. we discuss the scanning step for bottom-up earley deduction and indexing schemes that help avoid useless deduction steps.
an integrated system for morphological analysis of the slovene language. the paper presents an integrated environment for morphological analysis of word-forms of the slovene language. the system consists of a lexicon input and maintenance module, a lexicon output module, for accessing lexical word forms, a two-level rule compiler and a two-level morphological analysis/synthesis unit. the basic paradigms and lexical alternations of word forms are handled by the lexicon system, while the two-level component takes care of phonologically induced alternations.
centering theory and the italian pronominal system. in this paper, i give an account, in terms of centering theory [gjw86], of some phenomena of pronominalization in italian, in particular the use of the null or the overt pronoun in subject position. after a general introduction to the italian pronominal system, i will review centering, and then show how the original rules given in [gjw86] have to be extended or modified. finally, i will show that centering does not account for two phenomena: first, the functional role of an utterance may override the predictions of centering; second, a null subject can be used to refer to a whole discourse segment. this later phenomenon should ideally be explained in the same terms that the other phenomena in volving null subject are.
the discourse functions of italian subjects: a centering approach. this paper examines the discourse functions that different types of subjects perform in italian within the centering framework (grosz et al., 1995). i build on my previous work (di eugenio, 1990) that accounted for the alternation of null and strong pronouns in subject position. i extend my previous analysis in several ways: for example, i refine the notion of continue and discuss the centering functions of full nps.
a logical formalism for the representation of determiners. determiners play an important role in conveying the meaning of an utterance, but they have often been disregarded, perhaps because it seemed more important to devise methods to grasp the global meaning of a sentence, even if not in a precise way. another problem with determiners is their inherent ambiguity.in this paper we propose a logical formalism, which, among other things, is suitable for representing determiners without forcing a particular interpretation when their meaning is still not clear.
on the interpretation of natural language instructions. in this paper, we discuss the approach we take to the interpretation of instructions. instructions describe actions related to each other and to other goals the agent may have; our claim is that the agent must actively compute the actions that s/he has to perform, not simply "extract" their descriptions from the input.we will start by discussing some inferences that are necessary to understand instructions, and we will draw some conclusions about action representation formalisms and inference processes. we will discuss our approach, which includes an action representation formalism based on conceptual structures [jac90], and the construction of the structure of the agent's intentions. we will conclude with an example that shows why such representations help us in analyzing instructions.
compiling a partition-based two-level formalism. this paper describes an algorithm for the compilation of a two (or more) level orthographic or phonological rule notation into finite state transducers. the notation is an alternative to the standard one deriving from koskenniemi's work: it is believed to have some practical descriptive advantages, and is quite widely used, but has a different interpretation. efficient interpreters exist for the notation, but until now it has not been clear how to compile to equivalent automata in a transparent way. the present paper shows how to do this, using some of the conceptual tools provided by kaplan and kay's regular relations calculus.
the analysis of tense and aspect in eurotra. this paper presents a framework for the model-theoretic analysis of tense and aspect forms in discourse. it has been developed for eurotra, the mt project of the european community, and has been applied to the nine eurotra languages: english, german, dutch, danish, greek, italian, french, spanish and portuguese.the paper consists of six parts. the first presents the problem of translating tense and aspect forms and indicates the type of solution i envisage. the second contains a formalism for the representation of time meanings. the third and the fourth present a theory of tense and aspect respectively. the fifth discusses the issue of compositionality and the sixth is about the use of the system in the eurotra framework.
interpretation of nominal compounds: combining domain-independent and domain-specific information. a domain independent model is proposed for the automated interpretation of nominal compounds in english. this model is meant to account for productive rules of interpretation which are inferred from the morpho-syntactic and semantic characteristics of the nominal constituents. in particular, we make extensive use of pustejovsky's principles concerning the predicative information associated with nominals. we argue that it is necessary to draw a line between generalizable semantic principles and domain-specific semantic information. we explain this distinction and we show how this model may be applied to the interpretation of compounds in real texts, provided that complementary semantic information are retrieved.
boosting variant recognition with light semantics. a reasonably simple, domain-independent, large-scale approach of lexical semantics to paraphrase recognition is presented in this paper. it relies on the enrichment of morphosyntactic rules and the addition of four boolean syntactico-semantic features to a set of 1,023 words. it results in a significant enhancement of precision of 30% with a slight decrease in recall of 10%.
particle homonymy and machine translation. the purpose of this contribution is to formulate ways in which the homonymy of socalled 'model particles' and their etymons can be handled. our aim is to show that not only a strategy for this type of homonymy can be worked out, but also a formalization of information beyond propositional content can be introduced with a view to its mt application.
thales: a software package for plane geometry constructions with a natural language interface. thales is a software package for plane geometry constructions, supplied with a natural language interface. using thales requires no knowledge of a programming language. the interface is capable of processing practically all kinds of instructions within the subset of plane geometry english. the "static semantic" module has been generated on the basis of a high-level attribute specification. transportability, modifiability and generality -- the key issues of natural language interface design -- are investigated in the project note. the notion of specifiability is introduced to replace the three features mentioned above.
a self-learning system for the chinese characters. we are prototyping a system for the self-learning of chinese characters, presently on a macintosh computer. the interactive information base provides the learner with basic universal properties of the characters (morphology, intrinsic meaning), extended with a quite comprehensive set of language- dependent aspects (phonetics, extended semantics, contextual or pragmatic attributes). the user is intended to have a professional or cultural non-academic motivation. the system allows to experiment on heisig's proposal involving the separation of chinese characters learning (or japanese kanji) from that of the language. a prototype under hypercard may be demonstrated on a subset of about 200 characters.
towards linguistic knowledge discovery assistants: application to learning lexical properties of chinese characters. it is highly desirable that users of systems which include nlp-based components, ranging from grammar - checkers to mt systems, can access the underlying linguistic knowledge base in a natural and gratifying way. our research aims at developing such linguistic discovery assistant by merging hyperdocuments, data base management systems and interpretive adaptive interfaces.we have followed a stepwise approach to the idea in the context of the discovery and learning of lexical properties of chinese characters, by developing several prototypes. we see this system as a facet of a broader based including dictionary knowledge.
lexical accommodation in machine-mediated interactions. we report results of lexical accommodation studies involving three different interpretion settings: human-human monolingual; human-interpreted bilingual; and machine-interpreted bilingual. we found significant accommodation in all three conversational settings, with the highest rate in the human-interpreted settings. there is evidence for long-range mutual accommodation in that setting, as compared to short-range accommodation in the machine-interpreted setting. motivations discussed in the accommodation literature, including speakers' concern for social standing and communicational efficiency, are examined in the light of the results obtained. finally, we draw implications for the design of multimedia human-computer interfaces.
the automatic creation of lexical entries for a multilingual mt system. in this paper, we describe a method of extracting information from an on-line resource for the construction of lexical entries for a multi-lingual, interlingual mt system (ultra). we have been able to automatically generate lexical entries for interlingual concepts corresponding to nouns, verbs, adjectives and adverbs. although several features of these entries continue to be supplied manually we have greatly decreased the time required to generate each entry and see this as a promising method for the creation of large-scale lexicons.
collative semantics. this paper introduces collative semantics (cs), a new domain-independent semantics for natural language processing (nlp) which addresses the problems of lexical ambiguity, metonymy, various semantic relations (conventional relations, redundant relations, contradictory relations, metaphorical relations and severely anomalous relations) and the introduction of new information. we explain the two techniques cs uses for matching together knowledge structures (kss) and why semantic vectors, which record the results of such matches, are informative enough to tell apart semantic relations and be the basis for lexical disambiguation.
metonymy and metaphor: what's the difference. a computational approach to metonymy and metaphor is proposed that distinguishes between them, literalness, and anomaly. the approach supports lakoff and johnson's (1980) views that metonymy and metaphor are quite different phenomena, that in metonymy an entity stands for another, whereas in metaphor an entity is viewed as another.
demonstration of genesys: a very large, semantically based systemic functional generator. this paper provides background material to the demonstration to be given at coling '90 of the genesys component of the communal system. a presenter of such a demonstration should say (1) what the system is good for; (2) why it is good for it; and (3) what makes it different from alternative systems. the system to be demonstrated is just a part (though the single most important part) of a much more complex system, and some of the answers to the questions must be related to the overall system. so i shall describe that first, and then the generator itself.
non-sentential utterances: grammar and dialogue dynamics in corpus annotation. dialogue is full of intuitively complete utterances that are not sentential in their outward form, most prototypically the "short answers" used to respond to queries. as is well known, processing such non-sentential utterances (nsus) is a difficult problem on both theoretical and computational grounds. in this paper we present a corpus-based study of nsus. we propose a comprehensive, theoretically grounded classification of nsus in dialogue based on a sub-portion of the british national corpus (bnc). the study suggests that the interpretation of nsus is amenable to resolution using a relatively intricate grammar combined with an utterance dynamics approach. that is, a strategy that keeps track of a highly structured dialogue record of entities that get introduced into context as a result of utterances. complex, domain-based reasoning is not, on the whole, very much in evidence.
besoins lexicaux a la lumiere de l'analyse statistique du corpus de textes du projet "bref" - le lexique "bdlex" du francais ecrit et oral. in this paper, we describe lexical needs for spoken and written french surface processing, like automatic text correction, speech recognition and synthesis.we present statistical observations made on a vocabulary compiled from real texts like articles. these texts have been used for building a recorded speech database called bref. developed by the limsi, within the research group gdr-prc chm (groupe de recherche - programme de recherches concert&eacute;es, communication homme-machine --- research group - concerted research program, man machine communication), this database is intended for dictation machine development and assessment.in this study, the informations available in our lexical database bdlex (base de donn&eacute;es lexicales - lexical database) are used as reference materials. belonging to the same research group than bref, bdlex has been developed for spoken and written french. its purpose is to create, organize and provide lexical materials intended for automatic speech and text processing.lexical covering takes an important part in such system assessment. our first purpose is to value the rate of lexical covering that a 50, 000 word lexicon can reach.by comparison between the vocabulary provided (lexbref, composed of 84, 900 items, mainly distinct inflected forms) and the forms generated from bdlex, we obtain about 62% of known forms, taking in account some acronyms and abbreviations.then, we approach the unexpected word question looking into the 38% of left forms. among them we can find numeration, neologisms, foreign words and proper names, as well as other acronyms and abbreviations. so, to obtain a large text covering, a lexical component must take in account all these kinds of words and must be fault tolerant, particularly with typographic faults.last, we give a general description of the bdlex project, specially of its lexical content. we describe some lexical data recently inserted in bdlex according to the observations made on real texts. it concerns more particularly the lexical item representation using phonograms (i.e. letters/sounds associations), informations about acronyms and abbreviations as well as morphological knowledge about derivative words. we also present a set of linguistic tools connected to bdlex and working on the phonological, orthographical and morphosyntactical levels.
a two level dialogue representation. in this paper a two level dialogue representation system is presented. it is intended to recognize the structure of a large range of dialogues including some nonverbal communicative acts which may be involved in an interaction. it provides a syntactic description of a dialogue which can be expressed in terms of re-writing rules. the semantic level of the proposed representation system is given by the goal and subgoal structure underlying the dialogue syntactic units. two types of goal are identified; goals which relate to the content of the dialogue, and those which relate to communicating the content.
using collocations for topic segmentation and link detection. we present in this paper a method for achieving in an integrated way two tasks of topic analysis: segmentation and link detection. this method combines word repetition and the lexical cohesion stated by a collocation network to compensate for the respective weaknesses of the two approaches. we report an evaluation of our method for segmentation on two corpora, one in french and one in english, and we propose an evaluation measure that specifically suits that kind of systems.
discourse semantics meets lexical field semantics. the focus of this article is the integration of two different perspectives on lexical semantics: discourse representation theory's (drt) inferentially motivated approach and semantic emphasis theory's (set) lexical field based view. a new joined representation format is developed which is exemplified by analyses of german verbs. the benefits thereof are on both sides. drt gains basic entries for whole lexical fields and, furthermore, a systematic interface between semantic and syntactic argument structures. set profits both from the much larger semantic coverage and from the fine grained lexical analyses which reflect inferential behaviour.
integrated information manipulation systems (ims) - a cognitive view. the personal computer of the future will offer its owner an <u>i</u>nformation <u>m</u>anipulation <u>s</u>ystem (ims). it will be a totally integrated system being able to manipulate arbitrary information structures, eg programs, prose, graphical objects and sound.an ims will be an important step towards achieving the goal that we can do all our work on-line -- placing in computer store all of our specifications, plans, designs, programs, docummentation, reports, memos, bibliography and reference notes and doing all of our scratch work, planning, designing, debugging and most of our intercommunication via the consoles.we outline the basic principles underlying the design of an ims. we discuss the cognitive dimensions (specifically for text processing and programming systems) which should serve as the design criteria for systems whose goal is to reduce the cognitive burden and augment the capabilities of a human user.
fine grained classification of named entities. while named entity extraction is useful in many natural language applications, the coarse categories that most ne extractors work with prove insufficient for complex applications such as question answering and ontology generation. we examine one coarse category of named entities, persons, and describe a method for automatically classifying person instances into eight finer-grained subcategories. we present a supervised learning method that considers the local context surrounding the entity as well as more global semantic information derived from topic signatures and wordnet. we reinforce this method with an algorithm that takes advantage of the presence of entities in multiple contexts.
rigid lambek grammars are not learnable from strings. this paper is concerned with learning categorial grammars in gold's model (gold, 1967). recently, learning algorithms in this model have been proposed for some particular classes of classical categorial grammars (kanazawa, 1998).we show that in contrast to classical categorial grammars, rigid and k-valued lambek grammars are not learnable from strings. this result holds for variants of lambek calculus; our proof consists in the construction of limit points in each class. such a result aims at clarifying the possible directions for future learning algorithms.
what not to say. a problem with most text production and language generation systems is that they tend to become rather verbose. this may be due to neglection of the pragmatic factors involved in communication. in this paper, a text production system, commentator, is described and taken as a starting point for a more general discussion of some problems in computational pragmatics. a new line of research is suggested, based on the concept of unification.
computation of relative social status on the basis of honorification in korean. this paper presents a way to compute relative social status of the individuals involved in korean dialogue. every korean sentence indicates whether honorification occurs in it. the occurrence of honorification in a sentence is constrained by relative social status of the individuals involved in the sentence. by using the information about social status and the information about sentence-external individuals such as speaker and addressee, we can explain why a sentence is felicitous in a restricted context and whether a dialogue is coherent or not. since it is possible and easy to include such contextual information in the hpsg formalism, that formalism is adopted here. the implementation of korean dialogue processing and the computation of social status is made based on ale system.
word completion- a first step toward target-text mediated imt. we argue that the conventional approach to interactive machine translation is not the best way to provide assistance to skilled translators, and propose an alternative whose central feature is the use of the target text as a medium of interaction. we describe an automatic word-completion system intended to serve as a vehicle for exploring the feasibility of this new approach, and give results in terms of keystrokes saved in a test corpus.
an experiment on incremental analysis using robust parsing techniques. the results of an experiment are presented in which an approach for robust parsing has been applied incrementally. they confirm that due to the robust nature of the underlying technology an arbitrary prefix of a sentence can be analysed into an intermediate structural description which is able to direct the further analysis with a high degree of reliability. most notably, this result can be achieved without adapting the grammar or the parsing algorithms to the case of incremental processing. the resulting incremental parsing procedure is significantly faster if compared to a non-incremental best-first search. additionally it turns out that longer sentences benefit most from this acceleration.
an experiment on learning appropriate selectional restrictions from a parsed corpus. we present a methodology to extract selectional restrictions at a variable level of abstraction from phrasally analyzed corpora. the method relays in the use of a wide-coverage noun taxonomy and a statistical measure of the co-occurrence of linguistic items. some experimental results about the performance of the method are provided.
extracting nested collocations. this paper provides an approach to the semi-automatic extraction of collocations from corpora using statistics. the growing availability of large textual corpora, and the increasing number of applications of collocation extraction, has given rise to various approaches on the topic. in this paper, we address the problem of nested collocations; that is, those being part of longer collocations. most approaches till now, treated substrings of collocations as collocations, only if they appeared frequently enough by themselves in the corpus. these techniques left a lot of collocations unextracted. in this paper, we propose an algorithm for a semi-automatic extraction of nested uninterrupted and interrupted collocations, paying particular attention to nested collocation.
an integrated architecture for example-based machine translation. this paper describes a machine translation architecture that integrates the use of examples for flexible, idiomatic translations with the use of linguistic rules for broad coverage and grammatical accuracy. we have implemented a prototype for english-to-japanese translation, and our evaluation shows that the system has good translation quality, and only requires reasonable computational resources.
searching the web by voice. spoken queries are a natural medium for searching the web in settings where typing on a keyboard is not practical. this paper describes a speech interface to the google search engine. we present experiments with various statistical language models, concluding that a unigram model with collocations provides the best combination of broad coverage, predictive power, and real-time performance. we also report accuracy results of the prototype system.
the weak generative capacity of parenthesis-free categorial grammars. we study the weak generative capacity of a class of parenthesis free categorial grammars derived from those of ades and steedman by varying the set of reduction rules. with forward cancellation as the only rule, the grammars are weakly equivalent to context free grammars. when a backward combination rule is added, it is no longer possible to obtain all the context-free language. with suitable restriction of the forward partial rule, the languages are still context-free and a push-down automaton can be used for recognition. using the unrestricted rule of forward partial combination, a context sensitive language is obtained.
a stochastic approach to sentence parsing. a description will be given of a procedure to assign the most likely probabilities to each of the rules of a given context-free grammar. the grammar developed by s. kuno at harvard university was picked as the basis and was successfully augmented with rule probabilities. a brief exposition of the method with some preliminary results, when used as a device for disambiguating parsing english texts picked from natural corpus, will be given.
detecting shifts in news stories for paragraph extraction. for multi-document summarization where documents are collected over an extended period of time, the subject in a document changes over time. this paper focuses on subject shift and presents a method for extracting key paragraphs from documents that discuss the same event. our extraction method uses the results of event tracking which starts from a few sample documents and finds all subsequent documents that discuss the same event. the method was tested on the tdt1 corpus, and the result shows the effectiveness of the method.
an automatic clustering of articles using dictionary definitions. in this paper, we propose a statistical approach for clustering of articles using on-line dictionary definitions. one of the characteristics of our approach is that every sense of word in articles is automatically disambiguated using dictionary definitions. the other is that in order to cope with the problem of a phrasal lexicon, linking which links words with their semantically similar words in articles is introduced in our method. the results of experiments demonstrate the effectiveness of the proposed method.
automatic recognition of verbal polysemy. polysemy is one of the major causes of difficulties in semantic clustering of words in a corpus. in this paper, we first give a definition of polysemy from the viewpoint of clustering and then, based on this definition, we propose a clustering method which recognises verbal polysemies from a textual corpus. the results of experiments demonstrate the effectiveness of the proposed method.
breaking down rhetorical relations for the purpose of analysing discourse structures. in rhetorical structure theory (rst) the definitions of some relations are rather vague because they are given on a pragmatic basis. this paper presents another way of seeing the relations which leads to a more precise specification of the relations. the relations are associated with constraints on the semantic relationships between the propositional contents of two clauses, their modality and tense/aspect.
forward and backward reasoning in automatic abstracting. the paper is devoted to present a new approach to automatic abstracting which is supported by the development of susy, an experimental system currently being implemented at the university of udine (italy). the original contribution of the research reported is mostly focused on the role of forward and backward reasoning in the abstracting activity. in the paper the specifications and basic methodologies of susy are introduced, its architecture is illustrated with particular attention to the organization of the basic algorithms, and an example to support the novel approach proposed is described.
tailoring importance evaluation to reader's goals: a contribution to descriptive text summerization. the paper deals with a new approach to importance evaluation of descriptive texts developed in the framework of susy, an experimental system in the domain of text summarization. the problem of taking into account the reader's goals in evaluating importance of different parts of a text is first analyzed. a solution to the design of a goal interpreter capable of computing a quantitative measure of the relevance degree of a piece of text according to a given goal is then proposed, and an example of goal interpreter operation is provided.
a distributed multi-agent architecture for natural language processing. the paper presents a distributed multi-agent architecture for natural language processing. this architecture proposes a novel concept of distributed problem solving, which incorporates in a unitary framework the following key-points; large-grained heterogeneous agents, centralized knowledge-based control, and mixed event-driven and goal-driven operation. it provides, moreover, a flexible tool for the design of natural language processing systems, both motivated from the cognitive point of view and computationally effective and robust. the proposed architecture has been implemented in a fully running prototype system, and has been successfully applied in the domain of text understanding.
processing japanese self-correction in speech dialog systems. speech dialog systems need to deal with various kinds of ill-formed speech inputs that appear in natural human-human dialog. self-correction (or speech-repair) is a particularly problematic phenomenon. although many ways of dealing with self-correction have been proposed, these have limitations in both detecting and correcting for this phenomenon. in this paper, we propose a method to overcome these problems in japanese speech dialog. we evaluate the proposed method using our speech dialog corpus and discuss its limitations and the work that remains to be done.
k-vec: a new approach for aligning parallel texts. various methods have been proposed for aligning texts in two or more languages such as the canadian parliamentary debates (hansards). some of these methods generate a bilingual lexicon as a by-product. we present an alternative alignment strategy which we call k-vec, that starts by estimating the lexicon. for example, it discovers that the english word fisheries is similar to the french p&ecirc;ches by noting that the distribution of fisheries in the english text is similar to the distribution of p&ecirc'ches in the french. k-vec does not depend on sentence boundaries.
cooperation between transfer and analysis in example-based framework. transfer-driven machine translation (tdmt) is presented as a method which drives the translation processes according to the nature of the input. in tdmt, transfer knowledge is the central knowledge of translation, and various kinds and levels of knowledge are cooperatively applied to input sentences. tdmt effectively utilizes an example-based framework for transfer and analysis knowledge. a consistent framework of examples makes the cooperation between transfer and analysis effective, and efficient translation is achieved. the tdmt prototype system, which translates japanese spoken dialogs into english, has shown great promise.
constituent boundary parsing for example-based machine translation. this paper proposes an effective parsing method for example-based machine translation. in this method, an input string is parsed by the top-down application of linguistic patterns consisting of variables and constituent boundaries. a constituent boundary is expressed by either a functional word or a part-of-speech bigram. when structural ambiguity occurs, the most plausible structure is selected using the total values of distance calculations in the example-based framework. transfer-driven machine translation (tdmt) achieves efficient and robust translation within the example-based framework by adopting this parsing method. using bidirectional translation between japanese and english, the effectiveness of this method in tdmt is also shown.
incremental translation utilizing constituent boundary patterns. we have proposed an incremental translation method in transfer-driven machine translation (tdmt). in this method, constituent boundary patterns are applied to an input in a bottom-up fashion. also, by dealing with best-only substructures, the explosion of structural ambiguity is constrained and an efficient translation of a lengthy input can be achieved. through preliminary experimentation our new tdmt has been shown to be more efficient while maintaining translation quality.
natural language and inference in a computer game. we present an engine for text adventures - computer games with which the player interacts using natural language. the system employs current methods from computational linguistics and an efficient inference system for description logic to make the interaction more natural. the inference system is especially useful in the linguistic modules dealing with reference resolution and generation and we show how we use it to rank different readings in the case of referential and syntactic ambiguities. it turns out that the player's utterances are naturally restricted in the game scenario, which simplifies the language processing task.
expressing quantifier scope in french generation. in this paper we propose a new method to express quantification and especially quantifier scope in french generation. our approach is based on two points: the identification of the sentence components between which quantifier scope can indeed be expressed and a mechanism to reinforce the expression of quantifier scope. this approach is being integrated in a written french generator, called herm&egrave;s, which will become the generator of a portable natural language interface.
learning to recognize names across languages. the development of natural language processing (nlp) systems that perform machine translation (mt) and information retrieval (ir) has highlighted the need for the automatic recognition of proper names. while various name recognizers have been developed, they suffer from being too limited; some only recognize one name class, and all are language specific. this work develops an approach to multilingual name recognition that allows a system optimized for one language to be ported to another with little additional effort and resources. an initial core set of linguistic features, useful for name recognition in most languages, is identified. when porting to a new language, these features need to be converted (partly by hand, partly by on-line lists), after which point machine learning (ml) techniques build decision trees that map features to name classes. a system initially optimized for english has been successfully ported to spanish and japanese. only a few days of human effort for each new language results in performance levels comparable to that of the best current english systems.
extraposition: a case study in german sentence realization. we profile the occurrence of clausal extraposition in corpora from different domains and demonstrate that extraposition is a pervasive phenomenon in german that must be addressed in german sentence realization. we present two different approaches to the modeling of extraposition, both based on machine learned decision tree classifiers. the two approaches differ in their view of the movement operation: one approach models multi-step movement through intermediate nodes to the ultimate target node, while the other approach models one-step movement to the target node. we compare the resulting models, trained on data from two domains and discuss the differences between the two types of models and between the results obtained in the different domains.
improving alignment quality in statistical machine translation using context-dependent maximum entropy models. typically, statistical alignment models are based on single-word dependencies. these models do not include contextual information, which can lead to inadequate alignments. in this paper, we present an approach to include contextual dependencies in the statistical alignment model by using a refined lexicon model. unlike previous work, we directly integrate this in the em algorithm of statistical alignment models. experimental results are given for the french-english canadian parliament hansards task and the verbmobil task. the evaluation is performed by comparing the obtained alignments with a manually annotated reference alignment.
focus and higher-order unification. pulman has shown that higher-order unification (hou) can be used to model the interpretation of focus. in this paper, we extend the unification-based approach to cases which are often seen as a test-bed for focus theory: utterances with multiple focus operators and second occurrence expressions. we then show that the resulting analysis favourably compares with two prominent theories of focus (namely, rooth's alternative semantics and krifka's structured meanings theory) in that it correctly generates interpretations which these alternative theories cannot yield. finally, we discuss the formal properties of the approach and argue that even though hou need not terminate, for the class of unification-problems dealt with in this paper, hou avoids this shortcoming and is in fact computationally tractable.
generating from a deep structure. noncanonical semantic representations are representations which cannot be derived by some grammar g although they are semantically equivalent to representations which can be derived by g. this paper presents a generation algorithm which deals with noncanonical input. the proposed approach also enhances portability and language independence in that (i) linguistic decisions made by independent modules (e.g., planner, transfer component) can be communicated to the generator in a natural way and (ii) the same algorithm coupled with different grammars will yield sentences in the corresponding languages.
manipulating human-oriented dictionaries with very simple tools. it is possible to manipulate real-size human-oriented dictionaries on a macintosh by using only very simple tools. our methodology has been applied in the construction of a french-english-malay dictionary. this dictionary has been obtained by "crossing" semi-automatically two bilingual dictionaries. to revise the dictionary, as well as to obtain a publishable paper form and an on-line electronic form, we use only microsoft word&trade;, a specialized language for writing transcriptors and a small but powerful dictionary tool.
modularity in a connectionist model of morphology acquisition. this paper describes a modular connectionist model of the acquisition of receptive inflectional morphology. the model takes inputs in the form of phones one at a time and outputs the associated roots and inflections. in its simplest version, the network consists of separate simple recurrent subnetworks for root and inflection identification; both networks take the phone sequence as inputs. it is shown that the performance of the two separate modular networks is superior to a single network responsible for both root and inflection identification. in a more elaborate version of the model, the network learns to use separate hidden-layer modules to solve the separate tasks of root and inflection identification.
sequencing in a connectionist model of language processing. recent research suggests that human language processing can be profitably viewed in terms of the spread of activation through a network of simple processing units. decision making in connectionist modcls such as these is distributed and consists in selections made from sets of mutually inhibiting candidate items which are activated on the basis of input features. in these models, however, there is the problem, especially for generation, of obtaining sequential behavior from an essentially parallel process. the thrust of this paper is that sequencing can also be modelled as a process of competition between candidates activated on the basis of input features. in the case of sequencing, the competition concerns which of a set of pharse constituents will appear in a particular output position. this account allows output ordering to arise out of the interaction of syntactic with semantic and pragmatic factors, as seems to be the case for human language generation. the paper describes a localized connectionist model of language generation, focusing on the representation and use of sequencing information. we also show how these same sequencing representations and mechanisms are usable in parsing as well.
une ontologie du temps pour le langage naturel. we propose a new ontology for the time in natural language which provides the following features:- it renders an account of most of the temporal phenomena of language (dates, duration, events, states) ; it offers capacities for the comprehension of the narratives ;- in the contrary to the traditional systems, it needs no hard "types" for dealing with the different classes used by the terminology: thus an event may date others "when john died, there were many demonstrations in the world", a date may be the beginning of an event "monday, paul was leaving for a six months tour" ; our ontology endures the fluidity of natural language which does not make rigid, in the narratives, the signification of the temporal entities ;- it allows some multiplicity of points of view (partially inconsistent) about a single event: in the sentence "the travel of christophe colomb, which endured a long time, has been the beginning of a rich period of exploration", "the voyage of cc" is seen as a simple event in the main proposition and as a complex event in the subordinate one.with respect to these issues, the ontology uses the following frameworks:- a klone-like network aiming at a quick detection of incoherences: it contains taxonomic inferences (including the whole terminology) plus the facts ; a bulk of rules (assertional device) embodying contingent properties ;- non-monotonic reasoning is needed to revise simplistic conclusions obtained from superficial descriptions: the rules and the links of the network may be default rules ;- the vade (variable depth) system supports our ontology ; it is implemented with an atms-like truth maintenance system.the flexible ontology we present offers an interesting frame for further researches in computational linguistics, in particular in the domain of the interpretation of the narratives.
la resoution d'anaphore a partir d'un lexique-grammaire des verbes anaphoriques. this paper presents a system which intends to resolve anaphora in the framework of the discourse representation theory, and using a lexicon-grammar of anaphoric verbs, through the application of selection criteria for assignment of a referent to an anaphora.from a semantic representation of text provided by a drt system implemented in prolog, the system uses several criteria of selection of referent. one of these criteria is the anaphoric conditions of verbs described as a lexicon-grammar of anaphoric verbs.the present paper investigates a transformational analysis of verbs related to their anaphoric behaviour, and the adequacy of extension of the lexicon-grammar of m. gross to anaphoric conditions on verbs.
direct and underspecified interpretations of lfg f-structures. we describe an approach to interpreting lfg f-structures (kaplan & bresnan, 1982) truth-conditionally as underspecified quasi-logical forms. f-structures are either interpreted indirectly in terms of a homomorphic embedding into quasi logical form (qlf) (alshawi, 1992; alshawi & crouch, 1992; cooper et al., 1994a) representations or directly in terms of adapting qlf interpretation clauses to f-structure representations. we provide a reverse mapping from qlfs to f-structures and establish isomorphic subsets of the qlf and lfg formalism. a simple mapping which switches off qlf contextual resolution can be shown to be truth preserving with respect to an independently given semantics (dalrymple et al., 1995). we compare our proposal with approaches discussed in the literature.
contribution of a category hierarchy to the robustness of syntactic parsing. we describe how the use of a hierarchy of lexical categories instead of a simple set of categories leads to the definition of a flexible and precise language for the description of dependency structures. after specifying the formalism we use to decorate these structures, we present an application aiming to detect and correct errors in a written text. we outline how the use of the hierarchy improves the manipulation of unknown words.
towards a more user-friendly correction. we first present our view of detection and correction of syntactic errors. we then introduce a new correction method, based on heuristic criteria used to decide which correction should be preferred. weighting of these criteria leads to a flexible and parametrable system, which can adapt itself to the user. a partitioning of the trees based on linguistic criteria: agreement rules, rather than computational criteria is then necessary. we end by proposing extensions to lexical correction and to some syntactic errors. our aim is an adaptable and user-friendly system capable of automatic correction for some applications.
distributing and porting general linguistic tools. our main motivation is to build general and adaptable linguistic tools and we have faced the problem of their portability. we first make a quick description of the linguistic tools we have at hand and we explain why linguistic tools, unlike other software tools, present particular portability problems. we then discuss code portability and also data portability and we describe the method we have used for a french lexicon, showing that portability leads to a more "natural" computational lexicon. we then propose the use of a command language to interface the tools with more complex applications and we show that this technique facilitates integration of tools from various sources, entails a better exploitation of linguistic resources and makes easier the distribution of tools on several machines.
parsing as tree traversal. this paper presents a unified approach to parsing, in which top-down, bottom-up and left-corner parsers are related to preorder, postorder and inorder tree traversals. it is shown that the simplest bottom-up and left-corner parsers are left recursive and must be converted using an extended greibach normal form. with further partial execution, the bottom-up and left-corner parsers collapse together as in the bup parser of matsumoto.
the correct and efficient implementation of appropriateness specifications for typed feature structures. in this paper, we argue that type inferencing incorrectly implements appropriateness specifications for typed feature structures, promote a combination of type resolution and unfilling as a correct and efficient alternative, and consider the expressive limits of this alternative approach. throughout, we use feature cooccurence restrictions as illustration and linguistic motivation.
semantic interpretation of pragmatic clues: connectives, modal verbs, and indirect speech acts. much work in current research in the field of semantic pragmatic analysis has been concerned with the interpretation of natural language utterances in the context of dialogs, in this paper, however, we will present methods for a primary pragmatic analysis of single utterances. our investigations involve problems which are not currently well understood, for example how to infer the speaker's intentions by using interpretation of connectives and modal verbs.
robust parsing of severely corrupted spoken utterances. this paper describes a technique for enabling a speech understanding system to deal with sentences for which some monosyllabic words are not recognized. such words are supposed to act as mere syntactic markers within the system linguistic domain. this result is achieved by combining a modified caseframe approach to linguistic knowledge representation with a parsing strategy able to integrate expectations from the language model and predictions from words. experimental results show that the proposed technique permits to greatly increase the quota of corrupted sentences correctly understandable without sensibly decreasing parsing efficiency.
the psi/phi architecture for prosodic parsing. in this paper an architecture and an implementation for a linguistically based prosodic analyser is presented. the implementation is designed to handle typical prosodic input in the form of parallel input channels, and processes each input channel independently in a data-directed, phonologically motivated configuration of partly parallel, partly cascaded feature modules and module clusters, each implemented as finite transducers, producing intonationally relevant categories as output. the design criteria included maximal restriction of computational power (the system could be compiled into one massive finite transducer); relevance to computational linguistic formalisms with a view to developing an integrated model mapping prosodic structures on to textual structures; relatability to speech recognition algorithms, and to phonological theories. it was implemented in an object oriented environment with parallel processing simulation (cheops), and a linguistically interesting surface language (batlan).
probabilistic models of verb-argument structure. we evaluate probabilistic models of verb argument structure trained on a corpus of verbs and their syntactic arguments. models designed to represent patterns of verb alternation behavior are compared with generic clustering models in terms of the perplexity assigned to held-out test data. while the specialized models of alternation do not perform as well, closer examination reveals alternation behavior represented implicitly in the generic models.
a computational approach to binding theory. this paper is a first step towards a computational account of binding theory (bt). two algorithms that compute, respectively, principle a and b have been provided. particular attention has been devoted to possible interactions of bt with other modules of the linguistic theory, such as those ruling argumental chains. finally, the computational complexity of the algorithms has been studied.
tbms: domain specific text management and lexicon development. the definition of a text base management system is introduced in terms of software engineering. that gives a basis for discussing practical text administration, including questions on corpus properties and appropriate retrieval criteria. finally, strategies for the derivation of a word data base from an actual tbms will be discussed.
an active bilingual lexicon for machine translation. an approach to the transfer phase of a machine translation system is presented, where the bilingual lexicon plays an active role, guiding transfer by means of executable descriptions of word senses. the means for lexical sense specification are, however, general enough and can in principle apply to other system architectures, e.g. in the generation phase if transfer is intentionally kept minimal. the active lexicon is the one and only system component which is exposed to users and can serve to linguistically control transfer effects. a unified approach to lexicon creation and maintenance is proposed, which contains means to gradually refine sense specification and tailor the definitions to specific text domains. the underlying linguistic principles, the nature of sense distinction required for translation, and the formal structure of the lexicon are discussed.
anytime algorithms for speech parsing? this paper discusses to which extent the concept of "anytime algorithms" can be applied to parsing algorithms with feature unification. we first try to give a more precise definition of what an anytime algorithm is. we arque that parsing algorithms have to be classified as contract algorithms as opposed to (truly) interruptible algorithms. with the restriction that the transaction being active at the time an interrupt is issued has to be completed before the interrupt can be executed, it is possible to provide a parser with limited anytime behavior, which is in fact being realized in our research prototype.
research on architectures for integrated speech/language systems in verbmobil. the german joint research project verbmobil (vm) aims at the development of a speech to speech translation system. this paper reports on research done in our group which belongs to verbmobil's subproject on system architectures (tp15). our specific research areas are the construction of parsers for spontaneous speech, investigations in the parallelization of parsing and to contribute to the development of a flexible communication architecture with distributed control.
a finite state approach to german verb morphology. this paper presents a new, language independent model for analysis and generation of word froms based on finite state transducers (fsts). it has been completely implemented on a pc and successfully tested with lexicons and rules covering all of german verb morphology and the most interesting subsets of french and spanish verbs as well. the linguistic databascs consist of a letter-tree structured lexicon with annotated feature lists and a fst which is constructed from a set of morphophonological rules. these rewriting rules operate on complete words unlike other fst-based systems.
controlling lexical substitution in computer text generation. this report describes paul, a computer text generation system designed to create cohesive text through the use of lexical substitutions. specifically, this system is designed to deterministically choose between pronominalization, superordinate substitution, and definite noun phrase reiteration. the system identifies a strength of antecedence recovery for each of the lexical substitutions, and matches them against the strength of potential antecedence of each element in the text to select the proper substitutions for these elements.
modularizing contexted constraints. this paper describes a method for compiling a constraint-based grammar into a potentially more efficient form for processing. this method takes dependent disjunctions within a constraint formula and factors them into non-interacting groups whenever possible by determining their independence. when a group of dependent disjunctions is split into smaller groups, an exponential amount of redundant information is reduced. at runtime, this means that an exponential amount of processing can be saved as well. since the performance of an algorithm for processing constraints with dependent disjunctions is highly determined by its input, the transformation presented in this paper should prove beneficial for all such algorithms.
denormalization and cross referencing in theoretical lexicography. a computational vehicle for lexicography was designed to keep to the constraints of meaning-text theory: sets of lexical correlates, limits on the form of definitions, and argument relations similar to lexical-functional grammar.relational data bases look like a natural framework for this. but linguists operate with a non-normalized view. mappings between semantic actants and grammatical relations do not fit actant fields uniquely. lexical correlates and examples are polyvalent, hence denormalized.cross referencing routines help the lexicographer work toward a closure state in which every term of a definition traces back to zero level terms defined extralinguistically or circularly. dummy entries produced from defining terms ensure no trace is overlooked. values of lexical correlates lead to other word senses. cross references for glosses produce an indexed unilingual dictionary, the start of a fully bilingual one.to assist field work a small structured editor for a systematically denormalized data base was implemented in ptp under rt-11; mumps would now be easier to implement on small machines. it allowed fields to be repeated and nonatomic strings included, and produced cross reference entries. it served for a monograph on a language of mexico and for student projects from africa and asia.1
natural language interfaces using limited semantic information. in order to analyze their input properly, natural language interfaces require access to domain-specific semantic information. however, design considerations for practical systems -- in particular, the desire to construct interfaces which are readily portable to new domains -- require us to limit and segregate this domain-specific information. we consider here the possibility of limiting ourselves to a characterization of the <u>structure of information</u> in a domain. this structure is captured in a <u>domain information schema</u>, which specifies the semantic classes of the domain, the words and phrases which belong to these classes, and the predicate-argument relationships among members of these classes which are meaningful in the domain. we describe how this schema is used by the various stages of two large natural language processing systems.
comlex syntax: building a computational lexicon. we describe the design of comlex syntax, a computational lexicon providing detailed syntactic information for approximately 38,000 english headwords. we consider the types of errors which arise in creating such a lexicon, and how such errors can be measured and controlled.
automated determination of sublanguage syntactic usage. sublanguages differ from each other, and from the "standard language", in their syntactic, semantic, and discourse properties. understanding these differnces is important if we are to improve our ability to process these sublanguages. we have developed a semiautomatic procedure for identifying sublanguage syntactic usage from a sample of text in the sublanguage. we describe the results of applying this procedure to three text samples: two sets of medical documents and a set of equipment failure messages.
information extraction and semantic constraints. we consider the problem of extracting specified types of information from natural language text. to properly analyze the text, we wish to apply semantic (selectional) constraints whenever possible; however, we cannot expect to have semantic patterns for all the input we may encounter in real texts. we therefore use preference semantics: selecting the analysis which maximizes the number of semantic patterns matched. we describe a specific information extraction task, and report on the benefits of using preference semantics for this task.
generalizing automatically generated selectional patterns. frequency information on co-occurrence patterns can be automatically collected from a syntactically analyzed corpus; this information can then serve as the basis for selectional constraints when analyzing new text from the same domain. this information, however, is necessarily incomplete. we report on measurements of the degree of selectional coverage obtained with different sizes of corpora. we then describe a technique for using the corpus to identify selectionally similar terms, and for using this similarity to broaden the selectional coverage for a fixed corpus size.
message understanding conference- 6: a brief history. we have recently completed the sixth in a series of "message understanding conferences" which are designed to promote and evaluate research in information extraction. muc-6 introduced several innovations over prior mucs, most notably in the range of different tasks for which evaluations were conducted. we describe some of the motivations for the new format and briefly discuss some of the results of the evaluations.
segmentation and labelling of slovenian diphone inventories. preparation, recording, segmentation and pitch labelling of slovenian diphone inventories are described. a special user friendly interface package was developed in order to facilitate these operations. as acquisition of a labelled diphone inventory or adaptation of a speech synthesis system to synthesise further voices is manually intensive, an automatic procedure is required. a speech recogniser, based on hidden markov models in forced segmentation mode is used to outline phone boundaries within spoken logatoms. a statistical evaluation of manual and automatic segmentation discrepancies is performed so as to estimate the reliability of automatically derived labels. finally, diphone boundaries are determined and pitch markers are assigned to voiced sections of the speech signal.
lexicon-grammar and the syntactic analysis of french. a lexicon-grammar is constituted of the elementary sentences of a language. instead of considering words as basic syntactic units to which grammatical information is attached, we use simple sentences (subject-verb-objects) as dictionary entries. hence, a full dictionary item is a simple sentence with a description of the corresponding distributional and transformational properties.the systematic study of french has led to an organization of its lexicon-grammar based on three main components:- the lexicon-grammar of free sentences, that is, of sentences whose verb imposes selectional restrictions on its subject and complements (e.g. to fall, to eat, to watch),- the lexicon-grammar of frozen or idiomatic expressions (e.g. n takes n into account, n raises a question,- the lexicon-grammar of support verbs. these verbs do not have the common selectional restrictions, but more complex dependencies between subject and complement (e.g. to have, to make in n has an impact on n, n makes a certain impression on n)these three components interact in specific ways. we present the structure of the lexicon-grammar built for french and we discuss its algorithmic implications for parsing.the construction of a lexicon-grammar of french has led to an accumulation of linguistic information that should significantly bear on the procedures of automatic analysis of natural languages. we shall present the structure of a lexicon-grammar built for french and will discuss its algorithmic main implications.
dialogic: a core natural-language processing system. the dialogic system translates english sentences into representations of their literal meaning in the context of an utterance. these representations, or "logical forms," are intended to be a purely formal language that is as close as possible to the structure of natural language, while providing the semantic compositionality necessary for meaning-dependent computational processing. the design of dialogic (and of its constituent modules) was influenced by the goal of using it as the core language-processing component in a variety of systems, some of which are transportable to new domains of application.
automatic construction of discourse representation structures. kamp's discourse representation theory is a major breakthrough regarding the systematic translation of natural language discourse into logical form. we have therefore chosen to marry the user specialty languages system, which was originally designed as a natural language frontend to a relational database system, with this new theory. in the paper we try to show taking - for the sake of simplicity - kamp's fragment of english how this is achieved. the research reported is going on in the context of the project linguistics and logic based legal expert system undertaken jointly by the ibm heidelberg scientific center and the universit&auml;t t&uuml;bingen.
goal oriented parsing: improving the efficiency of natural language access to relational data bases. this paper is devoted to present a new approach to natural language understanding which is called here goal-oriented parsing. the interaction in natural language with artificial systems (robots, data base systems, program generators, question-answering systems, etc.) does not require in most cases of actual interest a full (human like) comprehension of natural language in all its details and nuances. a partial understanding is often enough, wich extracts from the natural language expressions the only significant information which is necessary to construct a correct formal input for the target system. in such a model of comprehension the same meaning is assigned to several different natural language expressions, thus defining a many-to-one mapping between natural language sentences and corresponding formal representations. we argue that a bounded scope, restricted, goal-oriented understanding of natural language may greatly increase the efficency of representation models and parsing algorithms, thus allowing the construction of effective systems. this claim is supported by the design and implementation of a natural language interface to a relational data base called nli and developed at the milan polytechnic artificial intelligence project. in the paper the architecture of the system, the linguistic models, and the parsing algorithms are presented and illustrated through selected examples. promising directions for future research are outlined as well.
variables et categories grammaticales dans un modele ariane. toutes tes cat&eacute;gories grammaticales utilis&eacute;es dans un mod&eacute;le de traduction ariane sont formalis&eacute;es et cod&eacute;es de fa&ccedil; mn&eacute;monique en tant que variables et valeurs de variables. l'ensemble des variables d'un qui permet de d&eacute;crire la langue source et la langue cible de ce mod&eacute;le.la structure de donn&eacute;es du syst&egrave;me est une arborescence dont chaque noeud polte une d&eacute;coration. les d&eacute;corations contiennent les variables d&eacute;clar&eacute;es por le syst&egrave;me et affect&eacute;es de certaines valeur. les variables appraissent &eacute;galement dans les grammires d'analyse, de transfert et de g&eacute;n&eacute;ration, deans les dictionnaires monolingues d'analyse ou de g&eacute;n&eacute;ration et bilingues de transfert lexical, ainsl que dans les sp&eacute;cifications de mod&eacute;le linguistique (grammaires statiques).
a sign expansion approach to dynamic, multi-purpose lexicons. two problematic issues in most lexicon systems today are their size and restricted domain of use. in this paper, we introduce a new approach to lexical organization that leads to more compact and flexible lexicons. the lexical entries are conceptual/phonological frames rather then word entries, and a number of expansion rules are used to generate entries of actual words from these frames. a single frame supports not only all forms of a word, but also words of different categories that are derived from the same semantic basis. the whole theory is now being implemented in the troll lexicon project.
on the generation and interpretation of demonstrative expressions. this paper presents necessary and sufficient conditions for the use of demonstrative expressions in english and discusses implications for current discourse processing algorithms. we examine a broad range of texts to show how the distribution of demonstrative forms and functions is genre dependent. this research is part of a larger study of anaphoric expressions, the results of which will be incorporated into a natural language generation system.
parsing turkish using the lexical functional grammar formalism. this paper describes our work on parsing turkish using the lexical-functional grammar formalism. this work represents the first effort for parsing turkish. our implementation is based on tomita's parser developed at carnegie-mellon university center for machine translation. the grammar covers a substantial subset of turkish including simple and complex sentences, and deals with a reasonable amount of word order freeness. the complex agglutinative morphology of turkish lexical structures is handled using a separate two-level morphological analyzer. after a discussion of key relevant issues regarding turkish grammar, we discuss aspects of our system and present results from our implementation. our initial results suggest that our system can parse about 82% of the sentences directly and almost all the remaining with very minor pre-editing.
is there content in empty heads? we describe a technique for automatically constructing a taxonomy of word senses from a machine readable dictionary. previous taxonomies developed from dictionaries have two properties in common. first, they are based on a somewhat loosely defined notion of the is-a relation. second, they require human intervention to identify the sense of the genus term being used. we believe that for taxonomies of this type to serve a useful role in subsequent natural language processing tasks, the taxonomy must be based on a consistent use of the is-a relation which allows inheritance and transitivity. we show that hierarchies of this type can be automatically constructed, by using the semantic category codes and the subject codes of the longman dictionary of contemporary english (ldoce) to disambiguate the genus terms in noun definitions. in addition, we discuss how certain genus terms give rise to other semantic relations between definitions.
extension of zipf's law to words and phrases. zipf's law states that the frequency of word tokens in a large corpus of natural language is inversely proportional to the rank. the law is investigated for two languages english and mandarin and for n-gram word phrases as well as for single words. the law for single words is shown to be valid only for high frequency words. however, when single word and n-gram phrases are combined together in one list and put in order of frequency the combined list follows zipf's law accurately for all words and phrases, down to the lowest frequencies in both languages. the zipf curves for the two languages are then almost identical.
referential nets with attributes. one of the essential problems in natural language production and understanding is the problem of processing referential relations. in this paper i describe a model for representing and processing referential relations: referential nets with attributes. both processes (analyzing and generating referential expressions) are controlled by attributes. there are two types of attributes, on one hand, the ones to the internal substitutes of the objects spoken about, on the other hand, the ones to the descriptions of these objects.
plurals, cardinalities, and structures of determination. this paper presents an approach for processing incomplete and inconsistent knowledge. basis for attacking these problems are 'structures of determination', which are extensions of scott's approximation lattices taking into consideration some requirements from natural language processing and representation of knowledge. the theory developed is exemplified with processing plural noun phrases referring to objects which have to be understood as classes or sets. referantial processes are handled by processes on 'referential nets', which are a specific knowledge structure developed for the representation of object-oriented knowledge. problems of determination with respect to cardinality assumptions are emphasized.
a description of the vespra speech processing system. the vespra system is designed for the processing of chains of (not connected utterances of) wordforms. these strings of wordforms correspond to sentences except that they are not realised in connected speech. vespra means: verarbeitung und erkennung gesprochener sprache (processing and recognition of speech). vespra will be used to control different types of machines by voice input (for instance: non critical control functions in cars and in trucks, voice box in digital telephone systems, text processing systems, different types of office work-stations).
symbolic word clustering for medium-size corpora. when trying to identify essential concepts and relationships in a medium-size corpus, it is not always possible to rely on statistical methods, as the frequencies are too low. we present an alternative method, symbolic, based on the simplification of parse trees. we discuss the results on nominal phrases of two technical corpora, analyzed by two different robust parsers used for terminology updating in an industrial company. we compare our results with hindle's scores of similarity.
reading distinction in mt. in any system for natural language processing having a dictionary, the question arises as to which entries are included in it. in this paper, i address the subquestion as to whether a lexical unit having two senses should be considered ambiguous or vague with respect to them. the inadequacy of some common strategies to answer this question in machine translation (mt) systems is shown. from a semantic conjecture, tests are developed that are argued to give more consistent and theoretically well-founded results.
a knowledge acquisition and management system for morphological dictionaries. a system for the acquisition and management of reusable morphological dictionaries is clearly a useful tool for nlp. as such, most currently popular finite-state morphology systems have a number of drawbacks. in the development of word manager, these problems have been taken into account. as a result, its knowledge acquisition component is well-developed, and its knowledge representation enables more flexible use than typical finite-state systems.
multimodal database query. the paper proposes a multimodal interface for a real sales database application. we show how natural language processing may be integrated with a visual, direct manipulation method of database query, to produce a user interface which supports a flexible form of query specification, provides implicit guidance about the coverage of the linguistic component, and allows more focused discourse reference.
interaction of knowledge sources in a portable natural language interface. this paper describes a general approach to the design of natural language interfaces that has evolved during the development of datalog, an english database query system based on cascaded atn grammar. by providing separate representation schemes for linguistic knowledge, general world knowledge, and application domain knowledge, datalog achieves a high degree of portability and extendability.
textual expertise in word experts: an approach to text parsing based on topic/comment monitoring. in this paper prototype versions of two word experts for text analysis are dealt with which demonstrate that word experts are a feasible tool for parsing texts on the level of text cohesion as well as text coherence. the analysis is based on two major knowledge sources: context information is modelled in terms of a frame knowledge base, while the co-text keeps record of the linear sequencing of text analysis. the result of text parsing consists of a text graph reflecting the thematic organization of topics in a text.
on text coherence parsing. in this paper global patterns of thematic text organization are considered within the framework of a distributed model of text understanding. based on the parsing results of prior text cohesion analysis, specialized text grammar modules determine whether some well-defined text macro-organization pattern is computable from the available text representation structures. the model underlying text coherence parsing formalizes hither-to entirely intuitive textlinguistic notions whose origin can be traced back to danes's work on thematic progression patterns.
an integrated model of semantic and conceptual interpretation from dependency structures. we propose a two-layered model for computing semantic and conceptual interpretations from dependency structures. abstract interpretation schemata generate semantic interpretations of 'minimal' dependency subgraphs, while production rules whose specification is rooted in ontological categories derive a canonical conceptual interpretation from semantic interpretation structures. configurational descriptions of dependency graphs increase the linguistic generality of interpretation schemata, while interfacing schemata and productions to lexical and conceptual class hierarchies reduces the amount and complexity of semantic specifications.
topic essentials. an overview of topic is provided, a knowledge-based text information system for the analysis of german-language texts. topic supplies text condensates (summaries) on variable degrees of generality and makes available facts acquired from the texts. the presentation focuses on the major methodological principles underlying the design of topic: a frame representation model that incorporates various integrity constraints, text parsing with focus on text cohesion and text coherence properties of expository texts, a lexically distributed semantic text grammar in the format of word experts, a model of partial text parsing, and text graphs as appropriate representation structures for text condensates.
bridging textual ellipses. we present a hybrid text understanding methodology for the resolution of textual ellipsis. it integrates language-independent conceptual criteria and language-dependent functional constraints. the methodological framework for text ellipsis resolution is the centering model that has been adapted to constraints reflecting the functional information structure within utterances, i.e., the distinction between context-bound and unbound discourse elements.
formal morphology. it is generally accepted that in principle it''s possible to formalize completely almost all of present-day mathematics. the practicability of actually doing so is widely doubted, as is the value of the result. but in the computer age we believe that such formalization is possible and desirable. in contrast to the qed manifesto however, we do not offer polemics in support of such a project. we merely try to place the formalization of mathematics in its historical perspective, as well as looking at existing praxis and identifying what we regard as the most interesting issues, theoretical and practical.
spelling-checking for highly inflective languages. spelling-checkers have become an integral part of most text processing software. from different reasons among which the speed of processing prevails they are usually based on dictionaries of word forms instead of words. this approach is sufficient for languages with little inflection such as english, but fails for highly inflective languages such as czech, russian, slovak or other slavonic languages. we have developed a special method for describing inflection for the purpose of building spelling-checkers for such languages. the speed of the resulting program lies somewhere in the middle of the scale of existing spelling-checkers for english and the main dictionary fits into the standard 360k floppy, whereas the number of recognized word forms exceeds 6 million (for czech). further, a special method has been developed for easy word classification.
deletions and their reconstruction in tectogrammatical syntactic tagging of very large corpora. the procedure of reconstruction of the underlying structure of sentences (in the process of tagging a very large corpus of czech) is described, with a special attention paid to the conditions under which the reconstruction of ellipted nodes is carried out.
inferencing on linguistically based semantic structures. the paper characterizes natural language inferencing in the tibaq method of question-answering, focussing on three aspects: (i) specification of the structures on which the inference rules operate, (ii) classification of the rules that have been formulated and implemented up to now, according to the kind of modification of the input structure the rules invoke, and (iii) discussion of some points in which a properly designed inference procedure may help the search of the answer, and vice versa.
hierarchy of salience and discourse analysis and production. the hierarchy of salience of the items of the knowledge assumed by the speaker to be shared by him and by the hearer constitutes one aspect of a dynamic account of discourse (sect. 1). it is claimed that a representation of this hierarchy is a good support for discourse analysis (reference assignement, sect. 2) and for discourse production (pronominalization, definite description, sect. 3).
stock of shared knowledge - a tool for solving pronominal anaphora. the paper develops further the idea of using the notion of the stock of shared knowledge (ssk) for anaphora resolution following a more subtle treatment of the influence of the topic/focus articulation of the sentence on the degrees of salience of items of the ssk. an algorithmic evaluation procedure of the ssk is formulated taking into account the notions of contextual boundness, syntactic associations, complexity of the sentences and existence/nonexistence of possible competitors, and a general evaluating function is proposed, essential for the process of anaphora resolution. in the present paper the analysis is performed for czech; however, the considerations are claimed to be of a universal validity, the actual relations between different factors and the values, of course, being language-dependent.
statistical morphological disambiguation for agglutinative languages. in this paper, we present statistical models for morphological disambiguation in turkish. turkish presents an interesting problem for statistical models since the potential tag set size is very large because of the productive derivational morphology. we propose to handle this by breaking up the morhosyntactic tags into inflectional groups, each of which contains the inflectional features for each (intermediate) derived form. our statistical models score the probability of each morhosyntactic tag by considering statistics over the individual inflection groups in a trigram model. among the three models that we have developed and tested, the simplest model ignoring the local morphotactics within words performs the best. our best trigram model performs with 93.95% accuracy on our test data getting all the morhosyntactic and semantic features correct. if we are just interested in syntactically relevant features and ignore a very small set of semantic features, then the accuracy increases to 95.07%.
lexical-functional grammar and order-free semantic composition. this paper summarizes the extension of the theory of lexical-functional grammar to include a formal, model-theoretic, semantics. the algorithmic specification of the semantic interpretation procedures is order-free which distinguishes the system from other theories providing model-theoretic interpretation for natural language. attention is focused on the computational advantages of a semantic interpretation system that takes as its input functional structures as opposed to syntactic surface-structures.
a compression technique for arabic dictionaries: the affix analysis. in every application that concerns the automatic processing of natural language, the problem of the dictionary size is posed. in this paper, we propose a compression dictionary algorithm based on an affix analysis of the non diacritical arabic.it consists in decomposing a word into its first elements taking into account the different linguistic transformations that can affect the morphological structures.this work has been achieved as part of a study of the automatic detection and correction of spelling errors in the non diacritical arabic texts.
a reestimation algorithm for probabilistic recursive transition network. probabilistic recursive transition network (prtn) is an elevated version of rtn to model and process languages in stochastic parameters. the representation is a direct derivation from the rtn and keeps much the spirit of hidden markov model at the same time. we present a resetination algorithm for prtn that is a variation of inside-outside algorithm that computes the values of the probabilistic parameters from sample sentences (parsed or unparsed).
an intelligent digester for interactive text processings. this paper outlines a practical approach to our project to design an intelligent system that supports an expert user for his understanding and representing news reports on a special world of the japanese computer industry. with the extensive help of the intelligent system the expert user purposefully assimilates new information in a knowledge data base of a frame-like representation through a multiple window interface.
open-domain voice-activated question answering. voice-activated question answering (vaqa) systems represent the next generation capability for universal access by integrating state-of-the-art in question answering q&a and automatic speech recognition (asr) in such a way that the performance of the combined system is better than the individual components. this paper presents an implemented vaqa system and describes the techniques that enable the terative refinement of both q&a and asr. the results of our experiments show that spoken questions can be processed with surprising accuracy when using our vaqa implementation.
experiments with open-domain textual question answering. this paper describes the integration of several knowledge-based natural language processing techniques into a question answering system, capable of mining textual answers from large collections of texts. surprizing quality is achieved when several lightweight knowledge-based nlp techniques complement mostly shallow, surface-based approaches.
constraining tree adjoining grammars by unification. in a proposal, vijay-shanker and joshi presented a definition for combining the two formalisms tree adjoining grammars and patr unification. the essential idea for that combination is the separation of the two recursion operations - adjoining and unification - to preserve all properties of both formalisms which is not desirable for natural language applications. in this paper, a definition for the integrated use of both processes is given and the remaining properties of the resulting formalism are discussed - especially weighing the appropriateness of this definition for natural language processing.
a quantitative model of word order and movement in english, dutch and german complement constructions. we present a quantitative model of word order and movement constraints that enables a simple and uniform treatment of a seemingly heterogeneous collection of linear order phenomena in english, dutch and german complement constructions (wh-extraction, clause union, extraposition, verb clustering, particle movement, etc.). underlying the scheme are central assumptions of the psycholinguistically motivated performance grammar (pg). here we describe this formalism in declarative terms based on typed feature unification. pg allows a homogenous treatment of both the within- and between-language variations of the ordering phenomena under discussion, which reduce to different settings of a small number of quantitative parameters.
default handling in incremental generation. natural language generation must work with insufficient input. underspecifications can be caused by shortcomings of the component providing the input or by the preliminary state of incrementally given input. the paper aims to escape from such dead-end situations by making assumptions. we discuss global aspects of default handling. two problem classes for defaults in the incremental syntactic generator vm-gen are presented to substantiate our discussion.
vp ellipsis and contextual interpretation. a computational account of vp ellipsis is described, in which vp's are represented in the discourse model as contextually dependent semantic objects. it is argued that this approach can handle examples that are not allowed by alternative accounts. an implementation is defined in terms of extensions to the incremental interpretation system. the treatment of vp ellipsis is analogous to that of pronominal anaphora. it is suggested that the recency and salience constraints commonly thought to apply to pronominal anaphora might apply in a similar way to vp ellipsis.
centering in dynamic semantics. centering theory posits a discourse center, a distinguished discourse entity that is the topic of a discourse. a simplified version of this theory is developed in a dynamic semantics framework. in the resulting system, the mechanism of center shift allows a simple, elegant analysis of a variety of phenomena involving sloppy identity in ellipsis and "paycheck pronouns".
word boundary identification from phoneme sequence constraints in automatic continouos speech recognition. this paper explores the extent to which phoneme sequence constraints can be used to identify word boundaries in continuous speech recognition. the input cousists of phonemic transcriptions (without word boundaries indicated) of 145 utterances produced by 1 rp speaker. the constraints are derived by matching the complete set of 3 phoneme sequences that can occur across word boundaries to entries in large lexicons containing both citation and reduced form pronunciations. phonemic assimilatory adjustments across word boundaries are also taken into account. the results show that around 37% of all word boundaries can be correctly identified from a knowledge of such phoneme sequence contraints alone, and that this figure rises to 45% when a knowledge of one-and two-phoneme words and all legal, word-initial and word-final, two-phoneme sequences are taken into account. the possibility of including such constraints in the architecture of a continuous speech recogniser is discussed.
learning bilingual collocations by word-level sorting. this paper proposes a new method for learning bilingual collocations from sentence-aligned parallel corpora. our method comprises two steps: (1) extracting useful word chunks (n-grams) by word-level sorting and (2) constructing bilingual collocations by combining the word-chunks acquired in stage (1). we apply the method to a very challenging text pair: a stock market bulletin in japanese and its abstract in english. domain specific collocations are well captured even if they were not contained in the dictionaries of economic terms.
conditioned unification for natural language processing. this paper presents what we call a conditional unification a new method of unification for processing natural languages. the key idea is to annotate the patterns with a certain sort of conditions, so that they carry abundant information. this method transmits information from one pattern to another more efficiently than procedure attachments, in which information contained in the procedure is embedded in the program rather than directly attached to patterns. coupled with techniques in formal linguistics, moreover, conditioned unification serves most types of operations for natural language processing.
a cognitive account of unbounded dependency. a computational approach is employed here to explicate human language faculty. some phenomena involving unbounded dependency are thus provided with cognitive account based on the processing load imposed by relevant syntactic operations. in particular, a consideration on local structural ambiguity accounts for some island effect (the noun-complement cases of complex np constraint) which is currently unexplained by static approaches in traditional theories of syntax. this exemplifies that some rules of syntax handle local ambiguity, suggesting insufficiency of traditional approaches to to syntax.
a constraint-based approach to linguistic performance. this paper investigates linguistic performance, from the viewpoint that the information processing in cognitive systems should be designed in terms of constraints rather than procedures in order to deal with partiality of information. in this perspective, the same grammar, the same belief and the same processing architecture should underly both sentence comprehension and production. a basic model of sentence processing, for both comprehension and production, is derived along this line of reasoning. this model is demonstrated to account for diverse linguistic phenomena apparently unrelated to each other, lending empirical support to the constraint paradigm.
effects of adjective orientation and gradability on sentence subjectivity. subjectivity is a pragmatic, sentence-level feature that has important implications for text processing applications such as information extraction and information retrieval. we study the effects of dynamic adjectives, semantically oriented adjectives, and gradable adjectives on a simple subjectivity classifier, and establish that they are strong predictors of subjectivity. a novel trainable method that statistically combines two indicators of gradability is presented and evaluated, complementing existing automatic techniques for assigning orientation labels.
improving search strategies: an experiment in best-first parsing. viewing the syntactic analysis of natural language as a search problem, the right choice of parsing strategy plays an important role in the performance of natural language parsers. after a motivation of the use of various heuristic criteria, a framework for defining and testing parsing strategies is presented. on this basis systematic tests on different parsing strategies have been performed, the results of which are dicussed. generally these tests show that a "guided" depth oriented strategy gives a considerable reduction of search effort compared to the classical depth-first strategy.
a three-level revision model for improving japanese bad-styled expressions. this paper proposes a three-level revision model for improving badly-styled japanese expressions, especially in the field of technical communication. the model is a mixture of the regeneration-based model and the rewriting-based model. the first level divides long sentences, while the second level improves several badly-styled expressions with iterative partial rewriting operations. the last level performs regeneration, in which word ordering and punctuation to reduce the reading ambiguity are currently involved. experimental results show that our model is effective in realizing practical revision support systems.
entity-oriented parsing. an entity-oriented approach to restricted-domain parsing is proposed. in this approach, the definitions of the structure and surface representation of domain entities are grouped together. like semantic grammar, this allows easy exploitation of limited domain semantics. in addition, it facilitates fragmentary recognition and the use of multiple parsing strategies, and so is particularly useful for robust recognition of extragrammatical input. several advantages from the point of view of language definition are also noted. representative samples from an entity-oriented language definition are presented, along with a control structure for an entity-oriented parser, some parsing strategies that use the control structure, and worked examples of parses. a parser incorporating the control structure and the parsing strategies is currently under implementation.
parsing spoken language: a semantic caseframe approach. parsing spoken input introduces serious problems not present in parsing typed natural language. in particular, indeterminacies and inaccuracies of acoustic recognition must be handled in an integral manner. many techniques for parsing typed natural language do not adapt well to these extra demands. this paper describes an extension of semantic caseframe parsing to restricted-domain spoken input. the semantic caseframe grammar representation is the same as that used for earlier work on robust parsing of typed input. due to the uncertainty inherent in speech recognition, the caseframe grammar is applied in a quite different way, emphasizing island growing from caseframe headers. this radical change in application is possible due to the high degree of abstraction in the caseframe representation. the approach presented was tested successfully in a preliminary implementation.
automatic acquisition of hyponyms from large text corpora. we describe a method for the automatic acquisition of the hyponymy lexical relation from unrestricted text. two goals motivate the approach: (i) avoidance of the need for pre-encoded knowledge and (ii) applicability across a wide range of text. we identify a set of lexico-syntactic patterns that are easily recognizable, that occur frequently and across text genre boundaries, and that indisputably indicate the lexical relation of interest. we describe a method for discovering these patterns and suggest that other lexical relations will also be acquirable in this way. a subset of the acquisition algorithm is implemented and the results are used to augment and critique the structure of a large hand-built thesaurus. extensions and applications to areas such as information retrieval are suggested.
an experimental parser. uppsala chart processor is a linguistic processor for phonological, morphological, and syntactic analysis. it incorporates the basic mechanisms of the general syntactic processor. linguistic rules as well as dictionary articles are presented to the processor in a procedural formalism, the ucp-formalism. the control of the processing rests upon the grammar and the dictionaries. special attention has been devoted to problems concerning the interplay between different kinds of linguistic processes.
design and evaluation of grammar checkers in multiple languages. this paper describes issues involved in the development of a grammar checker in multiple languages at microsoft corporation. focus is on design (selecting and prioritizing error identification rules) and evaluation (determining product quality).
dependency unification grammar. this paper describes the analysis component of the language processing system plain from the viewpoint of unification grammers. the principles of dependency unification grammar (dug) are discussed. the computer language drl (dependency representation language) is introduced in which dugs can be formulated. a unification-based parsing procedure is part of the formalism. plain is implemented at the universities of heidelberg, bonn, flensburg, kiel, zurich and cambridge u.k.
chart parsing according to the slot and filler principle. a parser is an algorithm that assigns a structural description to a string according to a grammar. it follows from this definition that there are three general issues in parser design: the structure to be assigned, the type of grammar, the recognition algorithm. common parsers employ phrase structure descriptions, rule-based grammars, and derivation or transition oriented recognition. the following choices result in a new parser: the structure to be assigned to the input is a dependency tree with lexical, morpho-syntactic and functional-syntactic information associated with each node and coded by complex categories which are subject to unification. the grammar is lexicalized, i.e. the syntactical relationships are stated as part of the lexical descriptions of the elements of the language. the algorithm relies on the slot and filler principle in order to draw up complex structures. it utilizes a well-formed substring table (chart) which allows for discontinuous segments.
using syntactic analysis to increase efficiency in visualizing text collections. self-organizing maps (soms) are a good method to cluster and visualize large collections of documents, but they are computationally expensive. in this paper, we investigate linguistically motivated reductions on the usual bag-of-words representation, to improve efficiency. we find that reducing the document representation to heads of verb and noun phrases reduces the heavy computational cost without degrading the quality of the map, especially in combination with term reduction techniques. more severe reductions which focus on subject and object nominal phrases are not advantageous.
the merged upper model: a linguistic ontology for german and english. a detailed comparison of the penman upper model and the komet german upper model has been carried out in order to construct a new merged upper model capable of serving as the ideational basis for generation in both english and german. previously proposed criteria for conducting such a merge are expanded on and evaluated. it is established that no (semi-)automatic merging of such knowledge sources can be expected to produce a reasonable result and that detailed comparison of the kind reported is essential. the result of the merge is now being used as the basis for sentence generation in english, german and dutch.
pronominalization revisited. pronominalization has been related to the idea of a local focus - a set of discourse entities in the speaker's centre of attention, for example in gundel et al. (1993)'s givenness hierarchy or in centering theory. both accounts say that the determination of the focus depends on syntactic as well as pragmatic factors, but have not been able to pin those factors down. in this paper, we uncover the major factors which determine the focus set in descriptive texts. this new focus definition has been evaluated with respect to two corpora: museum exhibit labels, and newspaper articles. it provides an operationalizable basis for pronoun production, and has been implemented as the reusable module gnome-np. the algorithm behind gnome-np is compared with the most recent pronoun generation algorithm of mccoy and strube (1999).
normal form theorem proving for the lambek calculus. the possibility of multiple equivalent proofs presents a problem for efficient parsing of a number of flexible categorial grammar (cg) frameworks. in this paper i outline a normal form system for a sequent formulation of the product-free associative lambek calculus. this leads to a simple parsing approach that yields only normal form proofs. this approach is both safe in that all distinct readings for a sentence will be returned, and optimal in that there is only one normal form proof yielding each distinct meaning.
chart parsing lambek grammars: modal extensions and incrementality. this paper describes a method for chart parsing lambek grammars. the method is of particular interest in two regards. firstly, it allows efficient processing of grammars which use necessity operators, an extension proposed for handling locality phenomena. secondly, the method is easily adapted to allow incremental processing of lambek grammars, a possibility that has hitherto been unavailable.
a compilation-chart method for linear categorial deduction. recent work in categorial grammar has seen proposals for a wide range of systems, differing in their 'resource sensitivity' and hence, implicitly, their underlying notion of 'linguistic structure'. a common framework for parsing such systems is emerging, whereby some method of linear logic theorem proving is used in combination with a system of labelling that ensures that only deductions appropriate to the relevant categorial formalism are allowed. this paper presents a deduction method for implicational linear logic that brings with it the benefit that chart parsing provides for cfg parsing, namely avoiding the need to recompute intermediate results when searching exhaustively for all possible analyses. the method involves compiling possibly higher-order linear formulae to indexed first-order formulae, over which deduction is made using just a single inference rule.
kassys: a definition acquisition system in natural language. this paper is an introduction to kassys, a system that has been designed to extract information from defining statements in natural language. only hyperonymous definitions are dealt with here, for which systematic processing has been devised and implemented in the initial version of the system. the paper describes how kassys builds a taxinomic hierarchy by extracting the hyperonyms from these definitions. it also explains the way in which the system can answer closed questions (yes/no), thus enabling the user to check very quickly that a definition has been assimilated correctly. the under-lying formalism is that of conceptual graphs, with which the reader is assumed to be familiar.
crossing corefernece in discourse representation theory. sentences with crossing coreference (bach-peters-sentences) are notoriously difficult to explain in a natural manner. an intriguing parallel with certain properties of prolog suggests a modification to discourse representation theory which allows a simple and coherent explanation of these, and related, sentences.
knowledge representation and semantics in a complex domain: the unix natural language help system goethe. natural language help systems for complex domains require, in our view, an integration of semantic representation and knowledge base in order to adequately and efficiently deal with cognitively misconceived user input. we present such an integration by way of the notion of a frame-semantics that has been implemented for the purposes of a natural language help system for unix.
interactive paraphrasing based on linguistic annotation. we propose a method "interactive paraphrasing" which enables users to interactively paraphrase words in a document by their definitions, making use of syntactic annotation and word sense annotation. syntactic annotation is used for managing smooth integration of word sense definitions into the original document, and word sense annotation for retrieving the correct word sense definition for a word in a document. in this way, documents can be paraphrased so that they fit into the original context, preserving the semantics and improving the readability at the same time. no extra layer (window) is necessary for showing the word sense definition as in conventional methods, and other natural language processing techniques such as summarization, translation, and voice synthesis can be easily applied to the results.
communicating with multiple agents. previous dialogue systems have focussed on dialogues between two agents. many applications, however, require conversations between several participants. this paper extends speech act definitions to handle multi-agent conversations, based on a model of multi-agent belief attribution with some unique properties. our approach has the advantage of capturing a number of interesting phenomena in a straightforward way.
a compositional semantics for directional modifiers - locative case reopened. this paper presents a model-theoretic semantics for directional modifiers in english. the semantic theory presupposed for the analysis is that of montague grammar (cf. montague 1970, 1973) which makes it possible to develop a strongly compositional treatment of directional modifiers. such a treatment has significant computational advantages over case-based treatments of directional modifiers that are advocated in the al literature.
applying lexical rules under subsumption. lexical rules are used in constraint based grammar formalisms such as head-driven phrase structure grammar (hpsg) (pollard and sag 1994) to express generalizations among lexical entries. this paper discusses a number of lexical rules from recent hpsg analyses of german (hinrichs and nakazawa 1994) and shows that the grammar in some cases vastly overgenerates and in other cases introduces massive spurious structural ambiguity, if lexical rules apply under unification. such problems of overgeneration or spurious ambiguity do not arise, if a lexical rule applies to a given lexical entry iff the lexical entry is subsumed by the left-hand side of the lexical rule. finally, the paper discusses computational consequences of applying lexical rules under subsumption.
clustering words with the mdl principle. we address the problem of automatically constructing a thesaurus by clustering words based on corpus data. we view this problem as that of estimating a joint distribution over the cartesian product of a partition of a set of nouns and a partition of a set of verbs, and propose a learning algorithm based on the minimum description length (mdl) principle for such estimation. we empirically compared the performance of our method based on the mdl principle against the maximum likelihood estimator in word clustering, and found that the former outperforms the latter. we also evaluated the method by conducting pp-attachment disambiguation experiments using an automatically constructed thesaurus. our experimental results indicate that such a thesaurus can be used to improve accuracy in disambiguation.
automatic refinement of a pos tagger using a reliable parser and plain text corpora. this paper proposes a new unsupervised learning method for obtaining english part-of-speech (pos) disambiguation rules which would improve the accuracy of a pos tagger. this method has been implemented in the experimental system apras (automatic pos rule acquisition system), which extracts pos disambiguation rules from plain text corpora by utilizing different types of coded linguistic knowledge, i.e., pos tagging rules and syntactic parsing rules, which are already stored in a fully implemented mt system.in our experiment, the obtained rules were applied to 1.7% of the sentences in a non-training corpus. for this group of sentences, 78.4% of the changes made in tagging results were an improvement. we also saw a 15.5% improvement in tagging and parsing speed and an 8.0% increase of parsable sentences.
inherited feature-based similarity measure based on large semantic hierarchy and large text corpus. we describe a similarity calculation model called ifsm (inherited feature similarity measure) between objects (words/concepts) based on their common and distinctive features. we propose an implementation method for obtaining features based on abstracted triples extracted from a large text corpus utilizing taxonomical knowledge. this model represents an integration of traditional methods, i.e., relation based similarity measure and distribution based similarity measure. an experiment, using our new concept abstraction method which we call the flat probability grouping method, over 80,000 surface triples, shows that the abstraction level of 3000 is a good basis for feature description.
extracting important sentences with support vector machines. extracting sentences that contain important information from a document is a form of text summarization. the technique is the key to the automatic generation of summaries similar to those written by humans. to achieve such extraction, it is important to be able to integrate heterogeneous pieces of information. one approach, parameter tuning by machine learning, has been attracting a lot of attention. this paper proposes a method of sentence extraction based on support vector machines (svms). to confirm the method's performance, we conduct experiments that compare our method to three existing methods. results on the text summarization challenge (tsc) corpus show that our method offers the highest accuracy. moreover, we clarify the different features effective for extracting different document genres.
toward a redefinition of yes/no questions. while both theoretical and empirical studies of question-answering have revealed the inadequacy of traditional definitions of yes-no questions (ynqs), little progress has been made toward a more satisfactory redefinition. this paper reviews the limitations of several proposed revisions. it proposes a new definition of ynqs based upon research on a type of conversational implicature, termed here scalar implicature, that helps define appropriate responses to ynqs. by representing ynqs as scalar queries it is possible to support a wider variety of system and user responses in a principled way.
a measure of term representativeness based on the number of co-occurring salient words. we propose a novel measure of the representativeness (i.e., indicativeness or topic specificity) of a term in a given corpus. the measure embodies the idea that the distribution of words co-occurring with a representative term should be biased according to the word distribution in the whole corpus. the bias of the word distribution in the co-occurring words is defined as the number of distinct words whose occurrences are saliently biased in the co-occurring words. the saliency of a word is defined by a threshold probability that can be automatically defined using the whole corpus. comparative evaluation clarified that the measure is clearly superior to conventional measures in finding topic-specific words in the newspaper archives of different sizes.
an efficient treatment of japanese verb inflection for morphological analysis. because of its simple appearance, japanese verb inflection has never been treated seriously. in this paper we reconsider traditional lexical treatments of japanese verb inflection, and propose a new treatment of verb inflection which uses newly devised segmenting units. we show that our proposed treatment minimizes the number of lexical entries and avoids useless segmentation. it requires 20 to 40% less chart parsing computation and it is also suitable for error correction in optical character readers.
analysis of japanese compound nouns by direct text scanning. this paper aims to analyze word dependency structure in compound nouns appearing in japanese newspaper articles. the analysis is a difficult problem because such compound nouns can be quite long, have no word boundaries between contained nouns, and often contain unregistered words such as abbreviations. the non-segmentation property and unregistered words cause initial segmentation errors which result in erroneous analysis. this paper presents a corpus-based approach which scans a corpus with a set of pattern matchers and gathers cooccurrence examples to analyze compound nouns. it employs boot-strapping search to cope with unregistered words: if an unregistered word is found in the process of searching the examples, it is recorded and invokes additional searches to gather the examples containing it. this makes it possible to correct initial oversegmentation errors, and leads to higher accuracy. the accuracy of the method is evaluated using the compound nouns of length 5, 6, 7, and 8. a baseline is also introduced and compared.
a method of measuring term representativeness - baseline method using co-occurrence distribution. this paper introduces a scheme, which we call the baseline method, to define a measure of term representativeness and measures defined by using the scheme. the representativeness of a term is measured by a normalized characteristic value defined for a set of all documents that contain the term. normalization is done by comparing the original characteristic value with the characteristic value defined for a randomly chosen document set of the same size. the latter value is estimated by a baseline function obtained by random sampling and logarithmic linear approximation. we found that the distance between the word distribution in a document set and the word distribution in a whole corpus is an effective characteristic value to use for the baseline method. measures defined by the baseline method have several advantages including that they can be used to compare the representativeness of two terms with very different frequencies, and that they have well-defined threshold values of being representative. in addition, the baseline function for a corpus is robust against differences in corpora; that is, it can be used for normalization in a different corpus that has a different size or is in a different domain.
drawing pictures with natural language and direct manipulation. a multimodal user interface allows users to communicate with computers using multiple modalities, such as a mouse, a keyboard or voice, in various combined ways. this paper discusses a multimodal drawing tool, whereby the user can use a mouse, a keyboard and voice effectively. also, it describes an interpretation method, by which the system integrates voice inputs and pointing inputs using context.
building a large knowledge base for a natural language system. a sophisticated natural language system requires a large knowledge base. a methodology is described for constructing one in a principled way. facts are selected for the knowledge base by determining what facts are linguistically presupposed by a text in the domain of interest. the facts are sorted into clusters, and within each cluster they are organized according to their logical dependencies. finally, the facts are encoded as predicate calculus axioms.
natural language access to structured text. this paper discusses the problem of providing natural language access to textual material. we are developing a system that relates a request in english to specific passages in a document on the basis of correspondences between the logical representations of the information in the request and in the passages. in addition, we are developing procedures for automatically generating logical representations of text passages, directly from the text, by means of an analysis of the coherence structure of the passages.
a multilayered approach to the handling of word formation. the treatment of word formations has until recently been a neglected topic in natural language ai research. this paper proposes a multilayered approach to word formation which treats derivatives and compounds on several different levels of processing within a natural language dialogue system. analysis and generation strategies being developed for the dialogue system ham-ans are described. identification of word formations, semantic interpretation, and evaluation in the context of a dialogue are the main levels of analysis on which the system successively attempts to infer the implicit relations between word formation components. generation of word formations is viewed as a process comparable to the generation of elliptical utterances.
translating into free word order languages. in this paper, i discuss machine translation of english text into a relatively "free" word order language, specifically turkish. i present algorithms that use contextual information to determine what the topic and the focus of each sentence should be, in order to generate the contextually appropriate word orders in the target language.
webdiplomat: a web-based interactive machine translation system. we have implemented an interactive, web-based, chat-style machine translation system, supporting speech recognition and synthesis, local- or third-party correction of speech recognition and machine translation output, and online learning. the underlying client-server architecture, implemented in javatm, provides remote, distributed computation for the translation and speech subsystems. we further describe our web-based user interfaces, which can easily produce different useful configurations.
towards a more careful evaluation of broad coverage parsing systems. since treebanks have become available to researchers a wide variety of techniques has been used to make broad coverage parsing systems. this makes quantitative evaluation very important, but the current evaluation methods have a number of drawbacks such as arbitrary choices in the treebank and the difficulty in measuring statistical significance. we suggest a more detailed method for testing a parsing system using constituent boundaries, with a number of measures that give more information than current measures, and evaluate the quality of the test. we also show that statistical significance cannot be calculated in a straightforward way, and suggest a calculation method for the case of bracket recall.
varying cardinality in metonymic extensions to nouns. meaning shifting phenomena such as metonymy have recently attracted increasing interest of researchers. though these phenomena have been addressed by plenty of computational methods, the impacts of cardinalities of metonymically related items have been widely ignored in all of them. motivated by this lack of analysis, we have developed a method for representing expectations and knowledge about the cardinalities of metonymically related entities and for exploiting this information to build logical forms expressing metonymic relations, the entities related, and their cardinalities. the representation of lexically motivated knowledge is realized as an enhancement to pustejovsky's generative lexicon, and the process of building logical forms takes into account overwriting of default information and mismatch of cardinality requirements. our method enables a precise attachment of sentence complements, and it supports reference resolution in the context of metonymic expressions.
best analysis selection in inflectional languages. ambiguity is the fundamental property of natural language. perhaps, the most burdensome case of ambiguity manifests itself on the syntactic level of analysis. in order to face up to the high number of obtained derivation trees, this paper describes several techniques for evaluation of the figures of merit, which define a sort order on parsing trees. the presented methods are based on language specific features of synthetical languages and they improve the results of simple stochastic approaches.
learning the space of word meanings for information retrieval systems. several methods to represent meanings of words have been proposed. however. they are not useful for information retrieval systems because they cannot deal with the entities which cannot be universally represented by symbols.in this paper, we propose a notion of semantic space. semantic space is an euclidean space where words and entities are put. a word is one point in the space. the meanings of the word are represented as the space configuration around the word. the entities that cannot be represented by symbols can be identified in the space by the location the entity should be settled in. we also give a learning mechanism for the space. we prove the effectiveness of the proposed method by an experiment on information retrieval for the study of japanese literature.
presuppositions as beliefs. most theories of presupposition implicitly assume that presuppositions are facts, and that all agents involved in a discourse share belief in the presuppositions that it generates. these unrealistic assumptions can be eliminated if each presupposition is treated as the belief of an agent. however, it is not enough to consider only the beliefs of the speaker; we show that the beliefs of other agents are often involved. we describe a new model, including an improved definition of presupposition, that treats presuppositions as beliefs and considers the beliefs of all agents involved in the discourse. we show that treating presuppositions as beliefs makes it possible to explain phenomena that cannot be explained otherwise.
pause as a phrase demarcator for speech and language processing. in spontaneous speech understanding a sophisticated integration of speech recognition and language processing is especially crucial. however, the two modules are traditionally designed independently, with independent linguistic rules. in japanese speech recognition the bunsetsu phrase is the basic processing unit and in language processing the sentence is the basic unit. this difference has made it impractical to use a unique set of linguistic rules for both types of processing. further, spontaneous speech contains unexpected utterances other than well formed sentences, while linguistic rules for both speech and language processing expect well-formed sentences. they therefore fail to process everyday spoken language. to bridge the gap between speech and language processing, we propose that pauses be treated as phrase demarcators and that the interpausal phrase be the basic common processing unit. and to treat the linguistic phenomena of spoken language properly, we survey relevant features in spontaneous speech data. we then examine the effect of integrating pausal and spontaneous speech phenomena into syntactic rules for speech recognition, using 118 sentences. our experiments show that incorporating pausal phenomena as purely syntactic constraints degrades recognition accuracy considerably, while the additional degradation if some further spontaneous speech features are also incorporated.
construction of corpus-based syntactic rules for accurate speech recognition. this paper describes the syntactic rules which are applied in the japanese speech recognition module of a speech-to-speech translation system. japanese is considered to be a free word/phrase order language. since syntactic rules are applied as constraints to reduce the search space in speech recognition, applying rules which take into account all possible phrase orders can have almost the same effect as using no constraints. instead, we take into consideration the recognition weaknesses of certain syntactic categories and treat them precisely, so that a minimal number of rules can work most effectively. in this paper we first examine which syntactic categories are easily misrecognized. second, we consult our dialogue corpus, in order to provide the rules with great generality. based on both studies, we refine the rules. finally, we verify the validity of the refinement through speech recognition experiments.
a rule induction approach to modeling regional pronunciation variation. this paper describes the use of rule induction techniques for the automatic extraction of phonemic knowledge and rules from pairs of pronunciation lexica. this extracted knowledge allows the adaptation of speech processing systems to regional variants of a language. as a case study, we apply the approach to northern dutch and flemish (the variant of dutch spoken in flanders, a part of belgium), based on celex and fonilex, pronunciation lexica for northern dutch and flemish, respectively. in our study, we compare two rule induction techniques, transformation-based error-driven learning (tbedl) (brill, 1995) and c5.0 (quinlan, 1993), and evaluate the extracted knowledge quantitatively (accuracy) and qualitatively (linguistic relevance of the rules). we conclude that, whereas classification-based rule induction with c5.0 is more accurate, the transformation rules learned with tbedl can be more easily interpreted.
using knowledge to facilitate factoid answer pinpointing. in order to answer factoid questions, the webclopedia qa system employs a range of knowledge resources. these include a qa typology with answer patterns, wordnet, information about typical numerical answer ranges, and semantic relations identified by a robust parser, to filter out likely-looking but wrong candidate answers. this paper describes the knowledge resources and their impact on system performance.
dealing with conjunctions in a machine translation environment. the paper presents an algorithm, written in prolog, for processing english sentences which contain either gapping, right node raising (rnr) or reduced conjunction (rc). the dcg (definite clause grammar) formalism (pereira & warren 80) is adopted. the algorithm is highly efficient and capable of processing a full range of coordinate constructions containing any number of coordinate conjunctions ('and', 'or', and 'but'). the algorithm is part of an english-chinese machine translation system which is in the course of construction.
planning argumentative texts. this paper presents proverb a text planner for argumentative texts. proverb's main feature is that it combines global hierarchical planning and unplanned organization of text with respect to local derivation relations in a complementary way. the former splits the task of presenting a particular proof into subtasks of presenting subproofs. the latter simulates how the next intermediate conclusion to be presented is chosen under the guidance of the local focus.
a chinese corpus for linguistic research. this is a project note on the first stage of the construction of a comprehensive corpus of both modern and classical chinese. the corpus is built with the dual aim of serving as the central database for chinese language processing and for supporting in-depth linguistic research in mandarin chinese.
segmentation standard for chinese natural language processing. this paper proposes a segmentation standard for chinese natural language processing. the standard is proposed to achieve linguistic felicity, computational feasibility, and data uniformity. linguistic felicity is maintained by defining a segmentation unit to be equivalent to the theoretical definition of word, and by providing a set of segmentation principles that are equivalent to a functional definition of a word. computational feasibility is ensured by the fact that the above functional definitions are procedural in nature and can be converted to segmentation algorithms, as well as by the implementable heuristic guidelines which deal with specific linguistic categories. data uniformity is achieved by stratification of the standard itself and by defining a standard lexicon as part of the segmentation standard.
parsing in parallel. the paper is a description of a parallel model for natural language parsing, and a design for its implementation on the hypercube multiprocessor. the parallel model is based on the semantic definite clause grammar formation and integrates syntax and semantics through the communication of processes. the main processess, of which there are six, contain either purely syntactic or purely semantic information, giving the advantage of simple, transparent algorithms dedicated to only one aspect of parsing. communication between processes is used to impose semantic constraints on the syntactic processes.
disambiguation of morphological analysis in bantu languages. the paper describes problems in disambiguating the morphological analysis of bantu languages by using swahili as a test language. the main factors of ambiguity in this language group can be traced to the noun class structure on one hand and to the bi-directional word-formation on the other. in analyzing word-forms, the system applied utilizes swatwol, a morphological parsing program based on two-level formalism. disambiguation is carried out with the latest version (april 1996) of the constraint grammar parser (cgp). statistics on ambiguity are provided. solutions for resolving different types of ambiguity are presented and they are demonstrated by examples from corpus text. finally, statistics on the performance of the disambiguator are presented.
reversible resolution with an application to paraphrasing. this paper describes a reversible resolution method based on proof procedures. a modotonic semantics is given for a subset of the core language engine (cle)'s quasi-logical form (qlf) [ac92] which defines a relation (cat) realised by a series of declarative statements describing possible resolutions for terms. the application of paraphrasing is used to demonstrate the method in a useful function in a natural language processing environment.
layout and language: integrating spatial and linguistic knowledge for layout understanding tasks. complex documents stored in a flat or partially marked up file format require layout sensitive preprocessing before any natural language processing can be carried out on their textual content. contemporary technology for the discovery of basic textual units is based on either spatial or other content insensitive methods. however, there are many cases where knowledge of both the language and layout is required in order to establish the boundaries of the basic textual blocks. this paper describes a number of these cases and proposes the application of a general method combining knowledge about language with knowledge about the spatial arrangement of text. we claim that the comprehensive understanding of layout can only be achieved through the exploitation of layout knowledge and language knowledge in an inter-dependent manner.
on trying to do things with words: another plan-based approach to speech act interpretation. usual plan-based approaches to speech act interpretation require that performing a speech act implies its success. these approaches are thus useless for describing failing illocutionary or perlocutionary acts. we propose an alternative plan-based view of speech acts centered around the notion of trying to do - as opposed to actually doing - an action. this approach is contrasted with that of perrault which aims to overcome similar problems.
complexity of event structure in ie scenarios. this paper presents new information extraction scenarios which are linguistically and structurally more challenging than the traditional muc scenarios. traditional views on event structure and template design are not adequate for the more complex scenarios.the focus of this paper is to show the complexity of the scenarios, and propose a way to recover the structure of the event. first we identify two structural factors that contribute to the complexity of scenarios: the scattering of events in text, and inclusion relationships between events. these factors cause difficulty in representing the facts in an unambiguous way. then we propose a modular, hierarchical representation where the information is split in atomic units represented by templates, and where the inclusion relationships between the units are indicated by links. lastly, we discuss how we may recover this representation from text, with the help of linguistic cues linking the events.
semantic parsing as graph language transformation - a multidimensional approach to parsing highly inflectional languages. the structure of many languages with "free" word order and rich morphology like finnish is rather configurational than linear. although non-linear structures can be represented by linear formalisms it is often more natural to study multidimensional arrangement of symbols. graph grammars are a multidimensional generalization of linear string grammars. in graph grammars string rewrite rules are generalized into graph rewrite rules. this paper presents a graph grammar formalism and parsing scheme for parsing languages with inherent configurational flavor. a small experimental finnish parsing system has been implemented (hyv&ouml;nen 1983).
kana-kanji conversion system with input support based on prediction. we propose a kana-kanji conversion system with input support based on prediction. this system is composed of two parts: prediction of succeeding kanji character strings from typed kana ones, and ordinary kana-kanji conversion. it automatically shows candidates of kanji character strings which the user intends to input. our prediction method features: (i)arbitrary positions of typed kana character strings are regarded as the top of words. (ii)a system dictionary and a user dictionary are used, and each entry in the system dictionary has certainly factor calculated from the frequency of words in corpora. (iii)candidates are estimated by certainty factor and usefulness factor, and likely ones with greater factors than thresholds are shown. the proposed system could reduce the user's key input operations to 78% from the original ones in our experiments.
multext: multilingual text tools and corpora. multext (multilingual text tools and corpora) is the largest project funded in the commission of european communities linguistic research and engineering program. the project will contribute to the development of generally usable software tools to manipulate and analyse text corpora and to create multilingual text corpora with structural and linguistic markup. it will attempt to establish conventions for the encoding of such corpora, building on and contributing to the preliminary recommendations of the relevant international and european standardization initiatives. multext will also work towards establishing a set of guidelines for text software development, which will be widely published in order to enable future development by others. all tools and data developed within the project will be made freely and publicly available.
three typed pragmatics for dialogue structure analysis. an experimental system for dialogue structure analysis based on a new type plan recognition model for spoken dialogues has been implemented. this model is realized by using four typed plans which are categorized into three kinds of universal pragmatics and a kind of task-dependent knowledge related to common action hierarchies. two experimental system is characterized by higher modularity and computational efficiency through defining a hierarchical usage order between these knowledges. the system can grasp a dialogue structure making it possible to solve problems related to spoken dialogue interpretation.
a statistical method for extracting uninterrupted and interrupted collocations from very large corpora. in order to extract rigid expressions with a high frequency of use, new algorithm that can efficiently extract both uninterrupted and interrupted collocations from very large corpora has been proposed.the statistical method recently proposed for calculating n-gram of arbitrary n can be applied to the extraction of uninterrupted collocations. but this method posed problems that so large volumes of fractional and unnecessary expressions are extracted that it was impossible to extract interrupted collocations combining the results. to solve this problem, this paper proposed a new algorithm that restrains extraction of unnecessary substrings. this is followed by the proposal of a method that enable to extract interrupted collocations.the new methods are applied to japanese newspaper articles involving 8.92 million characters. in the case of uninterrupted collocations with string length of 2 or mere characters and frequency of appearance 2 or more times, there were 4.4 millions types of expressions (total frequency of 31.2 millions times) extracted by the n-gram method. in contrast, the new method has reduced this to 0.97 million types (total frequency of 2.6 million times) revealing a substantial reduction in fractional and unnecessary expressions. in the case of interrupted collocational substring extraction, combining the substring with frequency of 10 times or more extracted by the first method, 6.5 thousand types of pairs of substrings with the total frequency of 21.8 thousands were extracted.
semiautomatic labelling of semantic features. this paper presents the strategy and design of a highly efficient semiautomatic method for labelling the semantic features of common nouns, using semantic relationships between words, and based on the information extracted from an electronic monolingual dictionary. the method, that uses genus data, specific relators and synonymy information, obtains an accuracy of over 99% and a scope of 68,2% with regard to all the common nouns contained in a real corpus of over 1 million words, after the manual labelling of only 100 nouns.
sentence disambiguation by document oriented preference sets. this paper proposes document oriented preference sets(dops) for the disambiguation of the dependency structure of sentences. the dops system extracts preference knowledge from a target document or other documents automatically. sentence ambiguities can be resolved by using domain targeted preference knowledge without using complicated large knowledgebases. implementation and empirical results are described for the analysis of dependency structures of japanese patent claim sentences.
an abstraction method using a semantic engine based on language information structure. this paper describes the framework for a new abstraction method that utilizes event-units written in sentences. event-units are expressed in language information structure (lis) form and the projection of lis from a sentence is performed by a semantic engine. abex (abstraction extraction system) utilizes the lis output of the semantic engine. abex can extract events from sentences and classify them. since abex and the lis form use only limited knowledge, the system need not construct or maintain a large amount of knowledge.
another look at nominal compounds. we present a progress report on our research on nominal compounds (nc's). recent approaches to this problem in linguistics and natural language processing (nlp) are reviewed and criticized. we argue that the notion of "role nominal", which is at the interface of linguistic and extralinguistic knowledge, is crucial for characterizing nc's as well as other linguistic phenomena. we examine a number of constraints on the semantic interpretation rules for nc's. proposals are made that should improve the capability of nlp systems to deal with nc's.
critter: a translation system for agricultural market reports. the critter system is being developed to translate agricultural market reports between english and french. it is based on a transfer model, and designed to be reversible. the source and target language texts are described by means of: a) a surface syntactic representation consisting of a tree annotated with feature structures, built by an extraposition grammar, and b) a semantic representation exhibiting predicate argument structures and constrained by type checking, built in parallel with the syntactic structure in compositional fashion. critters's implementation is still incomplete, but results obtained so far are promising.
transfer and mt modularity. the transfer components of typical second generation (g2) mt systems do not fully conform to the principles of g2 modularity, incorporating extensive target language information while failing to seperate translation facts from linguistic theory. the exclusion from transfer of all non-contrastive information leads us to a system design in which the three major components operate in parallel rather than in sequence. we also propose that mt systems be designed to allow translators to express their knowledge in natural metalanguage statements.
context analysis system for japanese text. a natural language understanding system is described which extracts contextual information from japanese texts. it integrates syntactic, semantic and contextual processing serially. the syntactic analyzer obtains rough syntactic structures from the text. the semantic analyzer treats modifying relations inside noun phrases and case relations among verbs and noun phrases. then, the contextual analyzer obtains contextual information from the semantic structure extracted by the semantic analyzer. our system understands the context using precoded contextual knowledge on terrorism and plugs the event information in input sentences into the contextual structure.
an efficient parser generator for natural language. we have developed a parser generator for natural language processing. the generator named "nlyacc" accepts grammar rules written in the yacc format. nlyacc, unlike yacc, can handle arbitrary context-free grammars using the generalized lr parsing algorithm. the parser produced by nlyacc efficiently parses given sentences and executes semantic actions. nlyacc, which is a free and sharable software, runs on unix workstations and personal computers.
a lesniewskian version of montague grammar. we shall be concerned in this paper with the logical analysis of natural language on the basis of lesniewski's ontology, which is a logical system without type-distinction between individuals and monadic predicates. this, it is believed, is also one of the features of natural language, and use will be made of this feature for developing a fragment of natural language.
a bottom-up generation for principle-based grammars using constraint propagation. a bottom-up generation algorithm for principle-based grammars is proposed. bottom-up generation has (1) an inefficiency because of a high degree of nondeterminism, (2) a limitation caused by inability to process logical forms produced by grammar rules, and (3) an identity semantic problem. this paper describes a solution to these problems and implementation issues for the algorithm using a constraint logic programming language.
efficient support vector classifiers for named entity recognition. named entity (ne) recognition is a task in which proper nouns and numerical information are extracted from documents and are classified into categories such as person, organization, and date. it is a key technology of information extraction and open-domain question answering. first, we show that an ne recognizer based on support vector machines (svms) gives better scores than conventional systems. however, off-the-shelf svm classifiers are too inefficient for this task. therefore, we present a method that makes the system substantially faster. this approach can also be applied to other similar tasks such as chunking and part-of-speech tagging. we also present an svm-based feature selection method and an efficient training method.
knowledge structures for natural language generation. the development of natural language interfaces to artificial intelligence systems is dependent on the representation of knowledge. a major impediment to building such systems has been the difficulty in adding sufficient linguistic and conceptual knowledge to extend and adapt their capabilities. this difficulty has been apparent in systems which perform the task of language production, i. e. the generation of natural language output to satisfy the communicative requirements of a system.the ace framework applies knowledge representation fundamentals to the task of encoding knowledge about language. within this framework, linguistic and conceptual knowledge are organized into hierarchies, and structured associations are used to join knowledge structures that are metaphorically or referentially related. these structured associations permit specialized linguistic knowledge to derive partially from more abstract knowledge, facilitating the use of abstractions in generating specialized phrases. this organization, used by a generator called king (knowledge intensive generator), promotes the extensibility and adaptability of the generation system.
achieving bidirectionality. the topic of bidirectionality, using common knowledge in language processing for both analysis and generation, is of both practical and theoretical concern. theoretically, it is important to determine what knowledge structures can be applied to both. practically, it is important that a competent natural language system be able to generate outputs that are relevant to the inputs it understands, without excessive redundancy. this problem revolves around the ability to relate linguistic structures declaratively to their meaning.
concretion: assumption-based understanding. a language understanding program must produce as precise a meaning representation as possible from a linguistic input. concretion is the process of developing a specific interpretation by combining various levels of conceptual information. this process represents an assumption-based method of language interpretation, and departs from the traditional approach of treating multiple interpretations as independent. concretion allows the language analyzer to develop a sufficiently specific representation without excessive computation or brittle interpretation rules.
to parse or not to parse: relation-driven text skimming. we have designed and implemented a text processing system that can extract important information from hundreds of paragraphs per hour and can be transported within weeks to a new domain. the system performs efficiently because it determines the level of processing required to understand a text. this "skimming" method identifies surface relations in the input text that are likely to contribute to its interpretation in a domain. this approach differs from previous skimming techniques in that it uses conceptual information as part of bottom-up linguistic processing, thus using linguistic knowledge more fully while limiting grammatical complexity.
word sense acquisition for multilingual text interpretation. we discuss a method for using automated corpus analysis to acquire word sense information for multilingual text interpretation. our system, shogun, extracts data from news stories with broad coverage in japanese and english. our approach focuses on tying together word senses, using a combination of world knowledge (oatlogy) with word knowledge (corpus data). we explain the approach and its results in shogun.
guaranteeing parsing termination of unification grammars. unification grammars are known to be turing-equivalent; given a grammar g and a word w, it is undecidable whether w &epsilon; l (g). in order to ensure decidability, several constraints on grammars, commonly known as off-line parsability (olp) were suggested. the recognition problem is decidable for grammars which satisfy olp. an open question is whether it is decidable if a given grammar satisfies olp. in this paper we investigate various definitions of olp, discuss their inter-relations and show that some of them are undecidable.
the primordial soup algorithm: a systematic approach to the specification of parallel parsers. a general framework for parallel parsing is presented, which allows for a unified, systematic approach to parallel parsing. the primordial soup algorithm creates trees by allowing partial parse trees to combine arbitrarily. by adding constraints to the general algorithm, a large class of parallel parsing strategies can be defined. this is exemplified by cyk, (bottom-up) earley and de vreught & honig parsers. from such a parsing strategy algorithms for various machine architectures can be derived in a systematic way.
functional structures for parsing dependency constraints. this paper outlines a high-level language fundpl for expressing functional structures for parsing dependency constraints. the goal of the language is to allow a grammar writer to pinn down his or her grammar with minimal commitment to control. fundpl interpreter has been implemented on top of a lower-level language dpl which we have earlier implemented.
annotating 200 million words: the bank of english project. the bank of english is an international english language project sponsored by harper-collins publishers, glasgow, and conducted by the cobuild team at the university of birmingham, uk. the text bank will comprise some 200 million words of both written and spoken english. the whole 200 million word corpus is being annotated morphologically and syntactically during 1993--94 at the research unit for computational linguistics (rucl), university of helsinki, using the english morphological analyser (engtwol) and english constraint grammar (engcg) parser. the first half of the texts (103 million words) has already been processed in 1993. the project is lead by prof. john sinclair in birmingham, and prof. fred karlsson in helsinki. the present author is responsible for conducting the annotation.
design issue of ectst. this note presents an overview of the english-chinese translation system for tourists (ectst) currently under development at south china university of technology. a brief description of the bilingual dictionary is given, followed by descriptions of grammar rules representation and the main processes involved in translation.
a new probabilistic model for title generation. title generation is a complex task involving both natural language understanding and natural language synthesis. in this paper, we propose a new probabilistic model for title generation. different from the previous statistical models for title generation, which treat title generation as a generation process that converts the 'document representation' of information directly into a 'title representation' of the same information, this model introduces a hidden state called 'information source' and divides title generation into two steps, namely the step of distilling the 'information source' from the observation of a document and the step of generating a title from the estimated 'information source'. in our experiment, the new probabilistic model outperforms the previous model for title generation in terms of both automatic evaluations and human judgments.
the performance of a grammar checker with deviant language input. this paper reports on an evaluation performed on the grammar checker for norwegian (ngc), developed at the text laboratory, university of oslo. the ability of the ngc to find errors made by different "non-standard" linguistic groups is analysed and compared to its performance when tested on texts written by "standard" users. then possible ways of adapting the ngc for use on deviant language input are discussed.
catching the cheshire cat. finding useful phrases is important in applications like information retrieval, and text-to-speech systems. one of the currently most used statistics is the mutual information ratio. this paper compares the mutual information ratio and a measure that takes temporal ordering into account. using this modified measure, some local syntactic constraints as well as phrases are captured.
good bigrams. a desired property of a measure of connective strength in bigrams is that the measure should be insensitive to corpus size. this paper investigates the stability of three different measures over text genres and expansion of the corpus. the measures are (1) the commonly used mutual information, (2) the difference in mutual information, and (3) raw occurrence. mutual information is further compared to using knowledge about genres to remove overlap between genres. this last approach considers the difference between two products of the same process (human text-generation) constrained by different genres. the cancellation of overlap seems to provide the most specific word pairs for each genre.
a discovery procedure for certain phonological rules. acquisition of phonological systems can be insightfully studied in terms of discovery procedures. this paper describes a discovery procedure, implemented in lisp, capable of determining a set of ordered phonological rules, which may be in opaque contexts, from a set of surface forms arranged in paradigms.
discouse, anaphora and parsing. discourse representation theory, as formulated by hans kamp and others, provides a model of inter- and intra-sentential anaphoric dependencies in natural language. in this paper, we present a reformulation of the model which, unlike kamp's, is specified declaratively. moreover, it uses the same rule formalism for building both syntactic and semantic structures. the model has been implemented in an extension of prolog, and runs on a vax 11/750 computer.
semantic abstraction and anaphora. this paper describes a way of expressing syntactic rules that associate semantic formulae with strings, but in a manner that is independent of the syntactic details of these formulae. in particular we show how the same rules construct predicate argument formulae in the style of montague grammar[13], representations reminiscent of situation semantics(barwise and perry [2]) and of the event logic of davidson [5], or representations inspired by the discourse representations proposed by kamp [9]. the idea is that semantic representations are specified indirectly using semantic construction operators, which enforce an abstraction barrier between the grammar and the semantic representations themselves. first we present a simple grammar which is compatible with the three different sets of constructors for the three formalisms. we then extend the grammar to provide one treatment that accounts for quantifier raising in the three different semantic formalisms
compact non-left-recursive grammars using the selective left-corner transform and factoring. the left-corner transform removes left-recursion from (probabilistic) context-free grammars and unification grammars, permitting simple top-down parsing techniques to be used. unfortunately the grammars produced by the standard left-corner transform are usually much larger than the original. the selective left-corner transform described in this paper produces a transformed grammar which simulates left-corner recognition of a user-specified set of the original productions, and top-down recognition of the others. combined with two factorizations, it produces non-left-recursive grammars that are not much larger than the original.
deixis and conjunction in multimodal systems. in order to realize their full potential, multimodal interfaces need to support not just input from multiple modes, but single commands optimally distributed across the available input modes. a multimodal language processing architecture is needed to integrate semantic content from the different modes. johnston 1998a proposes a modular approach to multimodal language processing in which spoken language parsing is completed before multimodal parsing. in this paper, i will demonstrate the difficulties this approach faces as the spoken language parsing component is expanded to provide a compositional analysis of deictic expressions. i propose an alternative architecture in which spoken and multimodal parsing are tightly interleaved. this architecture greatly simplifies the spoken language parsing grammar and enables predictive information from spoken language parsing to drive the application of multimodal parsing and gesture combination rules. i also propose a treatment of deictic numeral expressions that supports the broad range of pen gesture combinations that can be used to refer to collections of objects in the interface.
finite-state multimodal parsing and understanding. multimodal interfaces require effective parsing and understanding of utterances whose content is distributed across multiple input modes. johnston 1998 presents an approach in which strategies for multimodal integration are stated declaratively using a unification-based grammar that is used by a multi-dimensional chart parser to compose inputs. this approach is highly expressive and supports a broad class of interfaces, but offers only limited potential for mutual compensation among the input modes, is subject to significant concerns in terms of computational complexity, and complicates selection among alternative multimodal interpretations of the input. in this paper, we present an alternative approach in which multimodal parsing and understanding are achieved using a weighted finite-state device which takes speech and gesture streams as inputs and outputs their joint interpretation. this approach is significantly more efficient, enables tight-coupling of multimodal understanding with speech recognition, and provides a general probabilistic framework for multimodal ambiguity resolution.
goal formulation based on communicative principles. the paper presents the constructive dialogue model as a new approach to formulate system goals in intelligent dialogue systems. the departure point is in general communicative principles which constrain cooperative and coherent communication. dialogue participants are engaged in a cooperative task whereby a model of the joint purpose is constructed. contributions are planned as reactions to the changing context, and no dialogue grammar is needed. also speech act classification is abandoned, in favour of contextual reasoning and rationality considerations.
exploring the role of punctuation in parsing natural text. few, if any, current nlp systems make any significant use of punctuation. intuitively, a treatment of punctuation seems necessary to the analysis and production of text. whilst this has been suggested in the fields of discourse structure, it is still unclear whether punctuation can help in the syntactic field. this investigation attempts to answer this question by parsing some corpus-based material with two similar grammars --- one including rules for punctuation, the other ignoring it. the punctuated grammar significantly out-performs the unpunctuated one, and so the conclusion is that punctuation can play a useful role in syntactic processing.
towards a syntactic account of punctuation. little notice has been taken of punctuation in the field of natural language processing, chiefly due to the lack of any coherent theory on which to base implementations. some work has been carried out concerning punctuation and parsing, but much of it seems to have been rather ad-hoc and performance-motivated. this paper describes the first step towards the construction of a theoretically-motivated account of punctuation. parsed corpora are processed to extract punctuation patterns, which are then checked and generalised to a small set of general punctuation rules. their usage is discussed, and suggestions are made for possible methods of including punctuation information in grammars.
toward a scoring function for quality-driven machine translation. we describe how we constructed an automatic scoring function for machine translation quality; this function makes use of arbitrarily many pieces of natural language processing software that has been designed to process english language text. by machine-learning values of functions available inside the software and by constructing functions that yield values based upon the software output, we are able to achieve preliminary, positive results in machine-learning the difference between human-produced english and machine-translation english. we suggest how the scoring function may be used for mt system development.
linguistically motivated descriptive term selection. a linguistically motivated approach to indexing, that is the provision of descriptive terms for texts of any kind, is presented and illustrated. the approach is designed to achieve good, i.e. accurate and flexible, indexing by identifying index term sources in the meaning representations built by a powerful general purpose analyser, and providing a range of text expressions constituting semantic and syntactic variants for each term concept. indexing is seen as a legitimate form of shallow text processing, but one requiring serious semantically based language processing, particularly to obtain well-founded complex terms, which is the main objective of the project described. the type of indexing strategy described is further seen as having utility in a range of applications environments.
processing of sentences with intra-sentential code-switching. speakers of certain bilingual communities systematically produce utterances in which they switch from one language to another, suggesting that the two language systems systematically interact with each other in the production (and recognition) of these sentences. we have investigated this phenomenon in a formal or computational framework which consists of two grammatical systems and a mechanism for switching between the two systems. a variety of constraints apparent in these sentences are then explained in terms of constraints on the switching mechanism, especially, those on closed class items.
an english to korean transliteration model of extended markov window. automatic transliteration problem is to transcribe foreign words in one's own alphabet. machine generated transliteration can be useful in various applications such as indexing in an information retrieval system and pronunciation synthesis in a text-to-speech system. in this paper we present a model for statistical english-to-korean transliteration that generates transliteration candidates with probability. the model is designed to utilize various information sources by extending a conventional markov window. also, an efficient and accurate method for alignment and syllabification of pronunciation units is described. the experimental results show a recall of 0.939 for trained words and 0.875 for untrained words when the best 10 candidates are considered.
markov random field based english part-of-speech tagging system. probabilistic models have been widely used for natural language processing. part-of-speech tagging, which assingns the most likely tag to each word in a given sentence, is one of the problems which can be solved by statistical approach. many researchers have tried to solve the problem by hidden markov model (hmm), which is well known as one of the statistical models. but it has many difficulties: integrating heterogeneous information, coping with data sparseness problem, and adapting to new environments. in this paper, we propose a markov radom field (mrf) model based approach to the tagging problem. the mrf provides the base frame to combine various statistical information with maximum entropy (me) method. as gibbs distribution can be used to describe a posteriori probability of tagging, we use it in maximum a posteriori (map) estimation of optimizing process. besides, several tagging models are developed to show the effect of adding information. experimental results show that the performance of the tagger gets improved as we add more statistical information, and that mrf-based tagging model is better than hmm based tagging in data sparseness problem.
a statistical approach to machine aided translation of terminology banks. this paper reports on a new statistical approach to machine aided translation of terminology bank. the text in the bank is hyphenated and then dissected into roots of 1 to 3 syllables. both hyphenation and dissection are done with a set of initial probabilities of syllables and roots. the probabilities are repeatedly revised using an em algorithm. after each iteration of hyphenation or dissection, the resulting syllables and roots are counted subsequently to yield more precise estimation of probability. the set of roots rapidly converges to a set of most likely roots. preliminary experiments have shown promising results. from a terminology bank of more than 4, 000 terms, the algorithm extracts 223 general and chemical roots, of which 91% are actually roots. the algorithm dissects a word into roots with around 86% hit rate. the set of roots and their hand-translation are then used in a compositional translation of the terminology bank. one can expect the translation of terminology bank using this approach to be more cost-effective, consistent, and with a better closure.
coordination in reconnaissance-attack parsing. a proposal for recognizing coordinate structures using the 'reconnaissance-attack' model is presented. the approach concentrates on distinguishing predicate coordination from other types of coordination and suggests that low-level structural cues (such as the number of predicates, coordinators, and subordinators occurring in the input string) can be exploited at little cost during the early phase of the parse, with dramatic results. the method is tested on a text of 16,000 words.
robust segmentation of japanese text into a lattice for parsing. we describe a segmentation component that utilizes minimal syntactic knowledge to produce a lattice of word candidates for a broad coverage japanese nl parser. the segmenter is a finite state morphological analyzer and text normalizer designed to handle the orthographic variations characteristic of written japanese, including alternate spellings, script variation, vowel extensions and word-internal parenthetical material. this architecture differs from conventional japanese wordbreakers in that it does not attempt to simultaneously attack the problems of identifying segmentation candidates and choosing the most probable analysis. to minimize duplication of effort between components and to give the segmenter greater freedom to address orthography issues, the task of choosing the best analysis is handled by the parser, which has access to a much richer set of linguistic information. by maximizing recall in the segmenter and allowing a precision of 34.7%, our parser currently achieves a breaking accuracy of ~97% over a wide variety of corpora.
automatic thesaurus generation through multiple filtering. in this paper, we propose a method of generating bilingual keyword clusters or thesauri from parallel or comparable bilingual corpora. the method combines morphological and lexical processing, bilingual word aligmnent, and graph-theoretic cluster generation. an experiment shows that the method is promising.
an efficient execution method for rule-based machine translation. a rule based system is an effective way to implement a machine translation system because of its extensibility and maintainability. however, it is disadvantageous in processing efficiency. in a rule based machine translation system, the grammar consists of a lot of rewriting rules. while the translation is carried out by repeating pattern matching and transformation of graph structures, most rules fail in pattern matching. it is to be desired that pattern matching of the unfruitful rules should be avoided. this paper proposes a method to restrict the rule application by activating rules dynamically. the logical relationship among rules are pre-analyzed and a set of antecedent actions, which are prerequisite for the condition of the rule being satisfied, is determined for each rule. in execution time, a rule is activated only when one of the antecedent actions are carried out. the probability of a rule being activated is reduced to near the occurrence probability of its relevant linguistic phenomenon. as most rules relate to linguistic phenomena that rarely occur, the processing efficiency is drastically improved.
extracting word correspondences from bilingual corpora based on word co-occurrence information. a new method has been developed for extracting word correspondences from a bilingual corpus. first, the co-occurrence information for each word in both languages is extracted from the corpus. then, the correlations between the co-occurrence features of the words are calculated pairwisely with the assistance of a basic word bilingual dictionary. finally, the pairs of words with the highest correlations are output selectively. this method is applicable to rather small, unaligned corpora; it can extract correspondences between compound words as well as simple words. an experiment using bilingual patent-specification corpora achieved 28% recall and 76% precision; this demonstrates that the method effectively reduces the cost of bilingual dictionary augmenntation.
learning translation templates from bilingual text. this paper proposes a two-phase example-based machine translation methodology which develops translation templates from examples and then translates using template matching. this method improves translation quality and facilitates customization of machine translation systems. this paper focuses on the automatic learning of translation templates. a translation template is a bilingual pair of sentences in which corresponding units (words and pharases) are coupled and replaced with variables. correspondence between units is determined by suing a bilingual dictionary and by analyzing the syntactic structure of the sentences. syntactic ambiguity and ambiguity in correspondence between units are simultaneously resolved. all of the translation templates generated from a bilingual corpus are grouped by their source language part, and then further refined to resolved conflicts among templates whose source language parts are the same but whose target language parts are different. by using the proposed method, not only transfer rules but also knowledge for lexical selection is effectively extracted from a bilingual corpus.
unsupervised word sense disambiguation using bilingual comparable corpora. an unsupervised method for word sense disambiguation using a bilingual comparable corpus was developed. first, it extracts statistically significant pairs of related words from the corpus of each language. then, aligning pairs of related words translingually, it calculates the correlation between the senses of a first-language polysemous word and the words related to the polysemous word, which can be regarded as clues for determining the most suitable sense. finally, for each instance of the polysemous word, it selects the sense that maximizes the score, i.e., the sum of the correlations between each sense and the clues appearing in the context of the instance. to overcome both the problem of ambiguity in the translingual alignment of pairs of related words and that of disparity of topical coverage between corpora of different languages, an algorithm for calculating the correlation between senses and clues iteratively was devised. an experiment using wall street journal and nihon keizai shimbun corpora showed that the new method has promising performance; namely, the applicability and precision of its sense selection are 88.5% and 77.7%, respectively, averaged over 60 test polysemous words.
corpus-dependent association thesauri for information retrieval. this paper presents a method for automatically generating an association thesaurus from a text corpus, and demonstrates its application to information retrieval. the thesaurus generation method consists of extracting terms and co-occurrence data from a corpus and analyzing the correlation between terms statistically. a new method for disambiguating the structure of compound nouns, which is a key component for term extraction, is also proposed. the automatically generated thesaurus is effectively used as a tool for exploring information. a thesaurus navigator having novel functions such as term clustering, thesaurus overview, and zooming-in is proposed.
completion of japanese sentences by inferring function words from content words. a method of generating a japanese sentence by inferring function words from content words using valency patterns is presented.a procedure for selecting an appropriate function word, on the assumption that correct content words have been selected for a given phrase lattice, is described. a method of inferring a correct verb when verbs are recognized less accurately than nouns by the speech recognition system is described. sentences are produced from content words as inputs by using the valency patterns obtained from collected dialogue sentences in a restricted task domain. using the semantic features of preceding nouns and valency patterns allow a fairly restricted number of candidate verbs to be inferred.this method eliminates possible errors at the interface between speech recognition and machine translation (component technologies of an automatic telephone interpretation system) and selects the most appropriate candidate from a lattice of typical phrases output by the speech recognition system.
a response to the need for summary responses. in this paper we argue that natural language interfaces to databases should be able to produce summary responses as well as listing actual data. we describe a system (incorporating a number of heuristics and a knowledge base built on top of the database) that has been developed to generate such summary responses. it is largely domain-independent, has been tested on many examples, and handles a wide variety of situations where summary responses would be useful.
"the first million is hardest to get": building a large tagged corpus as automatically as possible. the paper describes a recently started project in sweden. the goal of the project is to produce a corpus of (at least) one million words of running text from different genres, where all words are classified for word class and for a set of morpho-syntactic properties. a set of methods and tools for automating the process are being developed and will be presented, and problems and some solutions in connection with e.g. homography disambiguation will be discussed.
linguistic indeterminacy as a source of errors in tagging. most evaluations of part-of-speech tagging compare the utput of an automatic tagger to some established standard, define the differences as tagging errors and try to remedy them by, e.g., more training of the tagger. the present article is based on a manual analysis of a large number of tagging errors. some clear patterns among the errors can be discerned, and the sources of the errors as well as possible alternative methods of remedy are presented and discussed. in particular are the problems with undecidable cases treated.
a portable & quick japanese parser: qjp. qjp is a portable and quick software module for japanese processing. qjp analyzes a japanese sentence into segmented morphemes/words with tags and a syntactic bunsetsu kakari-uke structure based on the two strategies, a) morphological analysis based on character-types and functional-words and b) syntactic analysis by simple treatment of structural ambiguities and ignoring semantic information. qjp is small, fast and robust, because 1) dictionary size (less than 100kb) and required memory size (260kb) are very small, 2) analysis speed is fast (more than 100 words/sec on 80486-pc), and 3) even a 100-word long sentence containing unknown words is easily processed.using qjp and its analysis results as a base and adding other functions for processing japanese documents, a variety of applications can be developed on unix workstations or even on pcs.
a discrete model of degree concept in natural language. degree words in natural language, such as 'often' and 'sometimes,' do not have denotations in the real world. this causes some interesting characteristics for degree words. for example, the correspondence between the english word 'often' and the intnitively corresponding japanese word is not obvious. this paper proposes a conceptual representation to describe a wide range of linguistic phenomena which are related to degree concepts in natural language.
lexical information for determining japanese unbounded dependency. this paper presents a practical method for a global structure analyzing algorithm of japanese long sentences with lexical information, a method which we call lexical discourse grammar (ldg). this method assumes that japanese function words, such as conjunctive particles (postpositions) located at the end of each clause, have modality and suggest global structures of japanese long sentences in cooperation with modality within predicates or auxiliary verbs. ldg classifies the encapsulating powers of function words into six levels, and modality in predicates into four types. ldg presumes the inter-clausal dependency within japanese sentences prior to syntactic and semantic analyses, by utilizing the differences of the encapsulating powers each japanese function word has, and by utilizing modification preference between function words and predicates that reflects consistency of modality in them. in order to confirm the encapsulation power of japanese function words, we analyzed the speech utterances of a male announcer and found the correlation between a particle's encapsulating power and the pause length inserted after the clause with a conjunctive particle.
a hybrid japanese parser with hand-crafted grammar and statistics. this paper describes a hybrid parsing method for japanese which uses both a hand-crafted grammar and a statistical technique. the key feature of our system is that in order to estimate likelihood for a parse tree, the system uses information taken from alternative partial parse trees generated by the grammar. this utilization of alternative trees enables us to construct a new statistical model called triplet/quadruplet model. we show that this model can capture a certain tendency in japanese syntactic structures and this point contributes to improvement of parsing accuracy on a shallow level. we report that, with an underspecified hpsg-based grammar and a maximum entropy estimation, our parser achieved high accuracy: 88.6% accuracy in dependency analysis of the edr annotated corpus, and that it outperformed other purely statistical parsing methods on the same corpus. this result suggests that proper treatment of hand-crafted grammars can contribute to parsing accuracy on a shallow level.
english-to-korean transliteration using multiple unbounded overlapping phoneme chunks. we present in this paper the method of english-to-korean (e-k) transliteration and back-transliteration. in korean technical documents, many english words are transliterated into korean words in various forms in diverse ways. as english words and korean transliterations are usually technical terms and proper nouns, it is hard to find a transliteration and its variations in a dictionary. therefore an automatic transliteration system is needed to find the transliterations of english words without manual intervention.to explain e-k transliteration phenomena, we use phoneme chunks that do not have a length limit. by applying phoneme chunks, we combine different length information with easy. the e-k transliteration method has three steps. in the first, we make a phoneme network that shows all possible transliterations of the given word. in the second step, we apply phoneme chunks, extracted from training data, to calculate the reliability of each possible transliteration. then we obtain probable transliterations of the given english word.
syllable-based model for tiie korean morphology. this paper describes a syllable-based computational model for the korean morphology. in this model, morphological analysis is considered as a process of candidate generation and candidate selection. in order to increase the performance of the system, the number of candidates is highly reduced and the system requires small number of dictionary accesses. idiosynchratic features of a syllable, formalized as a characteristic function, make it possible to reject implausible candidates before dictionary confirmation. instead of a letter, syllable is a basic processing unit for the practical implementation of the morphological analyzer.
the rumors system of russian synthesis. the rumors synthesizer of russian is an integral part of the jarap experimental system of japanese-russian automatic translation, although it can also have other applications. morphologically, it is based, primarily, on a. a. zaliznyak's model of russian inflexion. syntactical functions of rumors rely on word-order and dependency data as input information. the synthesizer is implemented on ibm pc, ms dos, in turbo pascal.
lfg generation produces context-free languages. this paper examines the generation problem for a certain linguistically relevant subclass of lfg grammars. our main result is that the set of strings that such a grammar relates to a particular f-structure is a context-free language. this result obviously extends to other context-free based grammatical formalisms, such as patr, and also to formalisms that permit a context-free skeleton to be extracted (perhaps some variants of hpsg). the proof is constructive: from the given f-structure a particular context-free grammar is created whose yield is the desired set of strings. many existing generation strategies (top-down, bottom-up, head-driven) can be understood as alternative ways of avoiding the creation of useless context-free productions. our result can be established for the more general class of lfg grammars, but that is beyond the scope of the present paper.
recognizing text genres with simple metrics using discriminant analysis. a simple method for categorizing texts into pre-determined text genre categories using the statistical standard technique of discriminant analysis is demonstrated with application to the brown corpus. discriminant analysis makes it possible use a large number of parameters that may be specific for a certain corpus or information stream, and combine them into a small number of functions, with the parameters weighted on basis of how useful they are for discriminating text genres. an application to information retrieval is discussed.
vocnets - a tool for handling finite vocabularies. a method is proposed for storing a finite vocabulary in a manner which makes it convenient to recognize words and substrings of words. the representation, which can be generated automatically from a list of words or from given representations of other sets by means of which the vocabulary has been defined through set or string operations, has the form of a modified finite-state grammar, a form eliminating the multiplicative effects of conjunction, complementation, etc., on the node sets of conventional finite-state representations.
a freely available wide coverage morphological analyzer for english. this paper presents a morphological lexicon for english that handle more than 317000 inflected forms derived from over 90000 stems. the lexicon is available in two formats. the first can be used by an implementation of a two-level processor for morphological analysis (karttunen and wittenburg, 1983; antworth, 1990). the second, derived from the first one for efficiency reasons, consists of a disk-based database using a unix hash table facility (seltzer and yigit, 1991). we also built an x window tool to facilitate the maintenance and browsing of the lexicon. the package is ready to be integrated into an natural language application such as a parser through hooks written in lisp and c.to our knowledge, this package is the only available free english morphological analyzer with very wide coverage.
features and values. the paper discusses the linguistic aspects of a new general purpose facility for computing with features. the program was developed in connection with the course i taught at the university of texas in the fall of 1983. it is a generalized and expanded version of a system that stuart shieber originally designed for the patr-ii project at sri in the spring of 1983 with later modifications by fernando pereira and me. like its predecessors, the new texas version of the "dg (directed graph)" package is primarily intended for representing morphological and syntactic information but it may turn out to be very useful for semantic representations too.
an experimental parser for syntemic grammars. we describe a general parsing method for systemic grammars. systemic grammars contain a paradigmatic analysis of language in addition to structural information, so a parser must assign a set of grammatical features and functions to each constituent in addition to producing a constituent structure. our method constructs a parser by compiling systemic grammars into the notation of functional unification grammar. the existing methods for parsing with unification grammars have been extended to handle a fuller range of paradigmatic descriptions. in particular, the patr-ii system has been extended by using disjunctive and conditional information in functional descriptions that are attached to phrase structure rules. the method has been tested with a large grammar of english which was originally developed for text generation. this testing is the basis for some observations about the bidirectional use of a grammar.
modularizing codescriptive grammars for efficient parsing. unification-based theories of grammar allow to integrate different levels of linguistic descriptions in the common framework of typed feature structures. dependencies among the levels are expressed by coreferences. though highly attractive theoretically, using such codescriptions for analysis creates problems of efficiency. we present an approach to a modular use of codescriptions on the syntactic and semantic level. grammatical analysis is performed by tightly coupled parsers running in tandem, each using only designated parts of the grammatical description. in the paper we describe the partitioning of grammatical information for the parsers and present results about the performance.
finite-state description of semitic morphology: a case study of ancient accadian. this paper discusses the problems of description and computational implementation of phonology and morphology in semitic languages, using ancient akkadian as an example. phonological and morphophonological variations are described using standard finite-state two-level morphological rules. interdigitation, prefixation and suffixation are described by using an intersection of two lexicons which effectively defines lexical representations of words.
answering it with charts: dialogue in natural language and charts. a methodology is proposed for taking queries and requests expressed in natural language as input and answering them in charts through organizing that interaction into felicitous dialogue. charts and graphics, as well as languages, are important modes of communication. this is especially true of those which are used frequently when people analyze huge amount of data interactively, in order to find out its characteristics or to resolve questions about it. this paper raises the problem that in such situations the correctness of the charts depends on the context, and proposes a framework to resolve it. the core of the framework is a logical form that includes the specifications of the user's perspective and the proper treatment of the logical form for handling utterance fragments. the framework has been implemented and confirmed to be appropriate.
exploiting lexical regularities in designing natural language systems. this paper presents the lexical component of the start question answering system developed at the mit artificial intelligence laboratory. start is able to interpret correctly a wide range of semantic relationships associated with a alternate expressions of the arguments of verbs. the design of the system takes advantage of the results of recent linguistic research into the structure of the lexicon, allowing start to attain a broader range of coverage than many existing systems while maintaining modular organization.
linguistic error correction of japanese sentences. this paper describes a newly developed linguistic error correction system, which can correct errors and rejections of japanese sentences by using linguistic knowledge.conventional optical character readers (ocr) need human assistance to correct their recognition errors and rejections. an operator must teach the ocr correct answers whenever an illegible character pattern occurs. if this error correction operation is mechanized, the throughput of the ocr will increase.this linguistic error correction system offers means of automated error correction by analysing sentences of the ocr outputs linguistically. this system grammatically selects legal letters from the candidates which can not be decided uniquely by pattern recognition only, and recommends grammatically and semantically meaningful letters for the illegible letter.
fertilization of case frame dictionary for robust japanese case analysis. this paper proposes a method of fertilizing a japanese case frame dictionary to handle complicated expressions: double nominative sentences, non-gapping relation of relative clauses, and case change. our method is divided into two stages. in the first stage, we parse a large corpus and construct a japanese case frame dictionary automatically from the parse results. in the second stage, we apply case analysis to the large corpus utilizing the constructed case frame dictionary, and upgrade the case frame dictionary by incorporating newly acquired information.
anaphora for everyone: pronominal anaphora resolution without a parser. we present an algorithm for anaphora resolution which is a modified and extended version of that developed by (lappin and leass, 1994). in contrast to that work, our algorithm does not require in-depth, full, syntactic parsing of text. instead, with minimal compromise in output quality, the modifications enable the resolution process to work from the output of a part of speech tagger, enriched only with annotations of grammatical function of lexical items in the input text stream. evaluation of the results of our implementation demonstrates that accurate anaphora resolution can be realized within natural language processing frameworks which do not---or cannot--- employ robust and reliable parsing components.
probabilistic tagging with feature structures. the described tagger is based on a hidden markov model and uses tags composed of features such as part-of-speech, gender, etc. the contextual probability of a tag (state transition probaility) is deduced from the contextual probabilities of its feature-value-pairs.this approach is advantageous when the available training corpus is small and the tag set large, which can be the case with morphologically rich languages.
aligning more words with high precision for small bilingual corpora. in this paper, we propose an algorithm for aligning words with their translation in a bilingual corpus. conventional algorithms are based on word-by-word models which require bilingual data with hundreds of thousand sentences for training. by using a word-based approach, less frequent words or words with diverse translations generally do not have statistically significant evidence for confident alignment. consequently, incomplete or incorrect alignments occur. our algorithm attempts to handle the problem using class-based rules which are automatic acquired from bilingual materials such as a bilingual corpus or machine readable dictionary. the procedures for acquiring these rules is also described. we found that the algorithm can align over 80% of word pairs while maintaining a comparably high precision rate, even when a small corpus was used in training. the algorithm also poses the advantage of producing a tagged corpus for word sense disambiguation.
parallel replacement in finite state calculus. this paper extends the calculus of regular expressions with new types of replacement expressions that enhance the expressiveness of the simple replace operator defined in karttunen (1995). parallel replacement allows multiple replacements to apply simultaneously to the same input without interfering with each other. we also allow a replacement to be constrained by any number of alternative contexts. with these enhancements, the general replacement expressions are more versatile than two-level rules for the description of complex morphological alternations.
a spelling correction program based on a noisy channel model. this paper describes a new program, correct, which takes words rejected by the unix&reg; spell program, proposes a list of candidate corrections, and sorts them by probability. the probability scores are the novel contribution of this work. probabilities are based on a noisy channel model. it is assumed that the typist knows what words he or she wants to type but some noise is added on the way to the keyboard (in the form of typos and spelling errors). using a classic bayesian argument of the kind that is popular in the speech recognition literature (jelinek, 1985), one can often recover the intended correction, c, from a typo, t, by finding the correction c that maximizes pr(c) pr(t/c). the first factor, pr(c), is a prior model of word probabilities; the second factor, pr(t/c), is a model of the noisy channel that accounts for spelling transformations on letter sequences (e.g., insertions, delections, substitutions and reversals). both sets of probabilities were trained on data collected from the associated press (ap) newswire. this text is ideally suited for this purpose since it contains a large number of typos (about two thousand per month).
generation of informative texts with style. an approach to the computational treatment of style is presented in the case of generation of informative texts. we regard the style mostly as a means of controlled selection of alternatives faced at each level of text generation. the generation technique, as well as the style specification, are considered at four levels --- content production, discourse generation, surface structure development, and lexical choice. a style is specified by the frequency of occurrence of certain features examined through observation of particular texts. the algorithm for text generation ensures efficient treatment of the style requirements.
incremental sentence generation: implications for the structure of a syntactic processor. human speakers often produce sentences incrementally. they can start speaking having in mind only a fragmentary idea of what they want to say, and while saying this they refine the contents underlying subsequent parts of the utterance. this capability imposes a number of constraints on the design of a syntactic processor. this paper explores these constraints and evaluates some recent computational sentence generators from the perspective of incremental production.
tsnlp - test suites for natural language processing. the growing language technology industry needs measurement tools to allow researchers, engineers, managers, and customers to track development, evaluate and assure quality, and assess suitability for a variety of applications.the tsnlp (test suites for natural language processing) project has investigated various aspects of the construction, maintenance and application of systematic test suites as diagnostic and evaluation tools for nlp applications. the paper summarizes the motivation and main results of tsnlp: besides the solid methodological foundation of the project, tsnlp has produced substantial (i.e. larger than any existing general test suites) multi-purpose and multi-user test suites for three european languages together with a set of specialized tools that facilitate the construction, extension, maintenance, retrieval, and customization of the test data.the publicly available results of tsnlp represent a valuable linguistic resource that has the potential of providing a wide-spread pre-standard diagnostic and evaluation tool for both developers and users of nlp applications.
intelligent handling of weather forecasts. some typical cases of intelligent handling of weather forecasts such as translation, visualization, etc. are decomposed into two subprocesses--analysis and synthesis. specific techniques are presented for analysis and synthesis of weather forecast texts as well as for generation of weather maps. these techniques deal with the weather forecasts at different levels--syntactic, discourse and semantic. they are based on a conceptual model underlying weather forecasts as well as on formal descriptions of the means of expression used in particular natural and cartographic sublanguages.
automatic proofreading of frozen phrases in german. frozen phrases are introduced as a new level of automatic proofreading in between the standard level of spelling verification of isolated words and the level of grammar checking. the design and the implementation of a corresponding proofreading system are described in detail.
topic-comment structure of texts (and its contribution to the automatic processing of texts). in general, topic is informally defined as that part of the sentence which the sentence is about and comment as what is said in the sentence. this is, of course, not a formal definition but so far noone has succeeded to provide a viable formal definition for these notions. in the analysis of sentences and texts these notions can nevertheless be used with considerable success.
a novel disambiguation method for unification-based grammars using probabilistic context-free approximations. we present a novel disambiguation method for unification-based grammars (ubgs). in contrast to other methods, our approach obviates the need for probability models on the ubg side in that it shifts the responsibility to simpler context-free models, indirectly obtained from the ubg. our approach has three advantages: (i) training can be effectively done in practice, (ii) parsing and disambiguation of context-free readings requires only cubic time, and (iii) involved probability distributions are mathematically clean. in an experiment for a mid-size ubg, we show that our novel approach is feasible. using unsupervised training, we achieve 88% accuracy on an exact-match task.
an hpsg-to-cfg approximation of japanese. we present a simple approximation method for turning a head-driven phrase structure grammar into a context-free grammar. the approximation method can be seen as the construction of the least fixpoint of a certain monotonic function. we discuss an experiment with a large hpsg for japanese.
feature structure based semantic head driven generation. this paper proposes a generation method for feature-structure-based unification grammars. as compared with fixed arity term notation. feature structure notation is more flexible for representing knowledge needed to generate idiomatic structures as well as general constructions. the method enables feature structure retrieval via multiple indices. the indexing mechanism, when used with a semantic head driven generation algorithm, attains efficient generation even when a large amount of generation knowledge must be considered. our method can produce all possible structures in parallel, using structure sharing among ambiguous substructures.
identifying the coding system and language of on-line documents on the internet. this paper proposes a new algorithm that simultaneously identifies the coding system and language of a code string fetched from the internet, especially world-wide web. the algorithm uses statistic language models to select the correctly decoded string as well as to determine the language. the proposed algorithm covers 9 languages and 11 coding systems used in eastern asia and western europe. experimental results show that the level of accuracy of our algorithm is over 95% for 640 on-line documents.
parsing with category cooccurance restrictions. this paper summarizes the formalism of category cooccurrence restrictions (ccrs) and describes two parsing algorithms that interpret it. ccrs are boolean conditions on the cooccurrence of categories in local trees which allow the statement of generalizations which cannot be captured in other current syntax formalisms. the use of ccrs leads to syntactic descriptions formulated entirely with restrictive statements. the paper shows how conventional algorithms for the analysis of context free languages can be adapted to the ccr formalism. special attention is given to the part of the parser that checks the fulfillment of logical well-formedness conditions on trees.
qpatr and constraint threading. qpatr is an ms-dos arity/prolog implementation of the patr-ii formalism for unification grammar. the formalism has been extended to include the constraints of lfg as well as negation and disjunction, which are implemented with the disjunction and negation-as-failure of prolog itself. a technique of constraint threading is employed to collect negative and constraining conditions in prolog difference lists. the parser of qpatr uses a left-corner algorithm for context-free grammars and includes a facility for identifying new lexical items in input on the basis of contextual information.
top-down predictive linking and complex-feature-based formalisms. automatic compilation of the linking relation employed in certain parsing algorithms for context-free languages is examined. special problems arise in the extension of these algorithms to the possibly infinite domain of feature structures. a technique is proposed which is designed specifically for left-recursive categories and is based on the generalization of their occurrences in a derivation. particular attention is drawn to the top-down predictive character of the linking relation and to its significance not only as a filter for increasing the efficiency of syntactic analysis but as a device for the top-down instantiation of information, which then serves as a key to the directed analysis of inflected forms as well as "unknown" or "new" words.
korean language engineering: current status of the information platform. language engineering implements functions of a language and information via computers. the need for language engineering platforms has been generally recognized and several researches are being undertaken around the world. our goal is to establish korean information platform of linguistic resources and tools for korean language and information communities. the platform will support, researchers and engineers with well-developed and standardized resources and application tools thereby avoiding duplicate activities from scratch and amplifying overall effort on the domain. this paper reports the components and the current status of the project, and the importance of the effort.
a comparative evaluation of data-driven models in translation selection of machine translation. we present a comparative evaluation of two data-driven models used in translation selection of english-korean machine translation. latent semantic analysis(lsa) and probabilistic latent semantic analysis (plsa) are applied for the purpose of implementation of data-driven models in particular. these models are able to represent complex semantic structures of given contexts, like text passages. grammatical relationships, stored in dictionaries, are utilized in translation selection essentially. we have used k-nearest neighbor (k-nn) learning to select an appropriate translation of the unseen instances in the dictionary. the distance of instances in k-nn is computed by estimating the similarity measured by lsa and plsa. for experiments, we used trec data(ap news in 1988) for constructing latent semantic spaces of two models and wall street journal corpus for evaluating the translation accuracy in each model. plsa selected relatively more accurate translations than lsa in the experiment, irrespective of the value of k and the types of grammatical relationship.
unsupervised named entity classification models and their ensembles. this paper proposes an unsupervised learning model for classifying named entities. this model uses a training set, built automatically by means of a small-scale named entity dictionary and an unlabeled corpus. this enables us to classify named entities without the cost for building a large hand-tagged training corpus or a lot of rules.our model uses the ensemble of three different learning methods and repeats the learning with new training examples generated through the ensemble learning. the ensemble of various learning methods brings a better result than each individual learning method. the experimental result shows 73.16% in precision and 72.98% in recall for korean news articles.
decision-tree based error correction for statistical phrase break prediction in korean. in this paper, we present a new phrase break prediction architecture that integrates probabilistic approach with decision-tree based error correction. the probabilistic method alone usually suffers from performance degradation due to inherent data sparseness problems and it only covers a limited range of contextual information. moreover, the module can not utilize the selective morpheme tag and relative distance to the other phrase breaks. the decision-tree based error correction was tightly integrated to overcome these limitations.the initially phrase break tagged morpheme sequence is corrected with the error correcting decision tree which was induced by c4.5 from the correctly tagged corpus with the output of the probabilistic predictor. the decision tree-based post error correction provided improved results even with the phrase break predictor that has poor initial performance. moreover, the system can be flexibly tuned to new corpus without massive retraining.
a two-level morphological analysis of korean. the two-level morphology model has received a great deal of attention and has been implemented for languages like finnish, english, japanese, russian, french, and so on. however, this model has been claimed to be inappropriate for korean morphological analysis, because the complex conjugation (inflection) and agglutination in word formation, and the syllable-based representation of words may lead to a huge number of two-level morphological rules. in this paper, we show that the two-level model can be successfully applied to korean and its rule size is limited to only 52. an extension of two-level morphology is described for korean language.
structural feature selection for english-korean statistical machine translation. when aligning texts in very different languages such as korean and english, structural features beyond word or phrase give useful information. in this paper, we present a method for selecting structural features of two languages, from which we construct a model that assigns the conditional probabilities to corresponding tag sequences in bilingual english-korean corpora. for tag sequence mapping between two languages, we first define a structural feature function which represents statistical properties of empirical distribution of a set of training samples. the system, based on maximum entropy concept, selects only features that produce high increases in loglikelihood of training samples. these structurally mapped features are more informative knowledge for statistical machine translation between english and korean. also, the information can help to reduce the parameter space of statistical alignment by eliminating syntactically unlikely alignments.
human factors and linguistic considerations: keys to high-speed chinese character input. with a keyboard and supporting system developed at cornell university, input methods used to identify ideographs are adaptations of well-known schemes; innovation is in the addition of automatic machine selection of ambiguously identified characters.the unique feature of the cornell design is that a certain amount of intelligence has been built into the machine. this allows an operator to take advantage of the fact that about 60% of chinese characters in text are paired with other characters to form two-syllable compounds or phrase words. in speech and writing these pairings eliminate about 95% of the ambiguities created by ambiguously identified syllables.
typed feature structures as descriptions. a description is an entity that can be interpreted as true or false of an object, and using feature structures as descriptions accrues several computational benefits. in this paper, i create an explicit interpretation of a typed feature structure used as a description, define the notion of a satisfiable feature structure, and create a simple and effective algorithm to decide if a feature structure is satisfiable.
improvement in customizability using translation templates. this paper outlines customization of a machine translation system using translation templates, which enable users to represent the bilingual knowledge needed for complex translation. to evaluate their effectiveness, we analyzed a bilingual text to estimate the improvement in customizability. the result shows that about 60% of mistranslated sentences can be translated as model translations by combining the proposed framework with the conventional customizing functions.
interaction between structural changes in machine translation. this paper discusses complex structural changes during transfer within a non-destructive transfer framework. though the description of each individual structural change is not difficult, special provision must be made when they are combined, because interaction between them sometimes causes unexpected problems. transfer of coordinate structures is also discussed as this sometimes necessitates a structural change and interacts with other structural changes in a problematic way.
japanese sentence analysis for automatic indexing. a new method for automatic keyword extracting and "role" setting is proposed based on the japanese sentence structure analysis. the analysis takes into account the following features of japanese sentences, i.e., the structure of a sentence is determined by the noun-predicate verb dependency, and the case indicating words (kaku-joshi) play an important role in deep case structure. by utilizing the meaning of a noun as it depends on each prodicate verb, restricted semantic processing becomes possible. an automatic indexing system, equipped with a man-machine interactive error-correcting function, has been developed. the evaluation of the system is performed by applying it in news information retrieval. the results of this evaluation show that the system can be put to practical use.
hypertags. srinivas (97) enriches traditional morpho-syntactic pos tagging with syntactic information by introducing supertags. unfortunately, words are assigned on average a much higher number of supertags than traditional pos. in this paper, we develop the notion of hypertag, first introduced in kinyon (00a) and in kinyon (00b), which allows to factor the information contained in several supertags into a single structure and to encode functional information in a systematic manner. we show why other possible solutions based on mathematical properties of trees are unsatisfactory and also discuss the practical usefulness of this approach.
portuguese analysis with tree adjoining grammars. this article approaches syntactical analysis of portuguese language based upon a formalism called tree adjoining grammars (tags) [joshi 85]. it briefly describes the formalism and its main operations, outlines a portuguese subset for analysis, and presents a parser developed according tags concepts in order to validate an application of the formalism for this language.
multi-tape two-level morphology: a case study in semitic non-linear morphology. this paper presents an implemented multi-tape two-level model capable of describing semitic non-linear morphology. the computational framework behind the current work is motivated by [kay 1987]; the formalism presented here is an extension to the formalism reported by [pulman and hepple 1993]. the objectives of the current work are: to stay as close as possible, in spirit, to standard two-level morphology, to stay close to the linguistic description of semitic stems, and to present a model which can be used with case by the semitist. the paper illustrates that if finite-state transducers (fsts) in a standard two-level morphology model are replaced with multi-tape auxiliary versions (afsts), one can account for semitic root-and-pattern morphology using high level notation.
computing prosodic morphology. this paper establishes a framework under which various aspects of prosodic morphology, such as templatic morphology and inflxation, can be handled under two-level theory using an implemented multi-tape two-level model. the paper provides a new computational analysis of root-and-pattern morphology based on prosody.
on a device in dictionary operations in machine translation. a special programme converting classes of words of international usage directly from english to czech is described in its application in an experiment of machine translation as well as in general environments. the words undergo special morphemic analysis, they are adapted morphemically and orthographically to the target language form and, in the experimental version, they are assigned pertinent grammatical and semantic information.
tranditional means in machine translation. the chronic problems of machine translation cannot be solved in a fully automatic way. human intervention is inevitable. the development of "traditional" means in connexion with advances of computer technology represent most substantial contribution to further progress in the field of machine translation. some of the problems are illustrated using the example of the apac32 project.
scaled log likelihood ratios for the detection of abbreviations in text corpora. we describe a language-independent, flexible, and accurate method for the detection of abbreviations in text corpora. it is based on the idea that an abbreviation can be viewed as a collocation, and can be identified by using methods for collocation detection such as the log likelihood ratio. although the log likelihood ratio is known to show a good recall, its precision is poor. we employ scaling factors which lead to a strong improvement of precision. experiments with english and german corpora show that abbreviations can be detected with high accuracy.
pattern matching in the textract information extraction system. in information extraction systems, pattern matchers are widely used to identify information of interest in a sentence. in this paper, pattern matching in the textract information extraction system is described. it comprises a concept search which identifies key words representing a concept, and a template pattern search which identifies patterns of words and phrases. textract using the matcher performed well in the tipster/muc-5 evaluation. the pattern matching architecture is also suitable for rapid system development across different domains of the same language.
incremental sentence production with a parallel marker-passing algorithm. this paper describes a method of incremental natural language generation using a parallel marker-passing algorithm for modeling simultaneous interpretation. semantic and syntactic knowledge are represented in a memory network in which several types of markers are passed around in order to make inference, and explore implicit parallelism of sentence production. the model is consistent with several psycholinguistic studies. the model is actually implemented as a part of the &phi;dmdialog real-time speech-to-speech dialog translation system developed at the center for machine translation at carnegie mellon university, and publicly demonstrated since march 1989.
semantic network array processor as a massively parallel computing platform for high performance and large-scale natural language processing. this paper demonstrates the utility of the semantic network array processor (snap) as a massively parallel platform for high performance and large-scale natural language processing systems. snap is an experimental massively parallel machine which is dedicated to, but not limited to, the natural language processing using semantic networks. in designing the snap, we have investigated various natural language processing systems and theories to determine the scope of the hardware support and a set of micro-coded instructions to be provided. as a result, snap employs an extended marker-passing model and a dynamically modifiable network model. a set of primitive instructions is micro-coded to directly support a parallel marker-passing, bitoperations, numeric operations, network modifications, and other essential functions for natural language processing. this paper demonstrates the utility of snap for various paradigms of natural language processing. we have discovered that the snap provides milliseconds or microsectonds performance on several important applications such as the memory-based parsing and translation, classification-based parsing, and vlkb search. also, we argue that there are numerous opportunities in the nlp community to take advantages of the computational power of the snap.
embedded sublanguages and natural language processing. most recent systems for the large-scale intelligent processing of natural language texts are designed to accept only a restricted variety of language. in certain cases this restricted subseto of the language constitutes a <u>sublanguage</u>, for which it may be possible to write a relatively precise and compact <u>sublanguage grammar</u>. several research groups are currently exploiting the restrictions in scientific and technical sublanguage grammars for tasks such as information retrieval and automatic translation.
synthesizing weather forecasts from formatted data. this paper describes a system (rareas) which synthesizes marine weather forecasts directly from formatted weather data. such synthesis appears feasible in certain natural sublanguages with stereotyped text structure. rareas draws on several kinds of linguistic and non-linguistic knowledge and mirrors a forecaster's apparent tendency to ascribe less precise temporal adverbs to more remote meterological events. the approach can easily be adapted to synthesize bilingual or multi-lingual texts.
hypothesis selection in grammar acquisition. this paper presents some techniques for selecting linguistically adequate hypotheses of new grammatical knowledge to be used as resources of grammatical knowledge acquisition. in our framework of linguistic knowledge acquisition, a rule-based hypothesis generator is invoked in case of parsing failures and all the possible hypotheses of new grammar rules or lexical entries are generated from partial parsing results. although each hypothesis could recover the defects of the existing grammar, the greater part of hypotheses are linguistically unnatural. the techniques we propose here prevent such unnatural hypotheses from being generated without discarding plausible ones and make the following corpus-based acquisition process more efficient and more reliable.
"dialog navigator": a question answering system based on large text knowledge base. this paper describes a dialog based qa system, dialog navigator, which can answer questions based on large text knowledge base. in real world qa systems, vagueness of questions is a big problem. our system can navigates users to the desired answers using the following methods: asking users back with dialog cards, and description extraction of each retrieved text. another feature of the system is that it retrieves relevant texts precisely, using question types, synonymous expression dictionary, and modifier-head relations in japanese sentences.
complex: a computational lexicon for natural language systems. although every natural language system needs a computational lexicon, each system puts different amounts and types of information into its lexicon according to its individual needs. however, some of the information needed across systems is shared or "identical" information. this paper presents our experience in planning and building complex, a computational lexicon designed to be a repository of shared lexical information for use by natural language processing (nlp) systems. we have drawn primarily on explicit and implicit information from machine-readable dictionaries (mrd's) to create a broad coverage lexicon.
degrees of stativity: the lexical representation of verb aspect. l'acquisition automatique de connaissance lexicale &agrave; partir de larges corpus s'est essentiellement occup&eacute;e des ph&eacute;nom&egrave;nes de co-occurrence, aux d&eacute;pens des traits lexicaux inh&eacute;rents. nous pr&eacute;sentons ici une m&eacute;thodologie qui permet d'obtenir l'information s&eacute;mantique sur l'aspect du verbe en analysant automatiquement un corpus et en appliquant des tests linguistiques &agrave; l'aide d'une s&eacute;rie d'outils d'analyse structurale. lorsque ces deux t&acirc;ches sont accomplies, nous proposons une r&eacute;presentation de l'aspect du verbe qui associe une valeur de mesure pour les diff&eacute;rents types d'&eacute;v&egrave;nements. les mesures refl&egrave;tent l'usage typique du verbe, et par cons&eacute;quent une mesure de r&eacute;sistance ou de non-r&eacute;sistance &agrave; la coercion dans le contexte de la phrase. les r&eacute;sultats que nous rapportons ici ont &eacute;t&eacute; obtenus de deux mani&egrave;res: en extrayant l'information n&eacute;cessaire &agrave; partir du corpus &eacute;tiquet&eacute; de francis and ku&ccaron;era (1982), et en faisant tourner un analyseur syntaxique (mccord 1980, 1990) sur le corpus du reader's digest afin d'extraire une information plus pr&eacute;cise sur l'usage du verbe dans le texte.
the bicord system: combining lexical information from bilingual corpora and machine readable dictionaries. our goal is to explore methods for combining structured but incomplete information from dictionaries with the unstructured but more complete information available in corpora for the creation of a bilingual lexical data base. this paper concentrates on the class of action verbs of movement, and builds on earlier work on lexical correspondences between languages and specific to this verb class. the languages we explore here are english and french. we first examine the way prototypical verbs of movement are translated in the collins-robert (collins 1978, henceforth cr) bilingual dictionary. we then analyze the behavior of some of these verbs in a large bilingual corpus. we take advantage of the results of linguistic research on verb types (e.g. levin, to appear) coupled with data from machine readable dictionaries to motivate corpus-based text analysis for the purpose of establishing lexical correspondences with the full range of associated translations and then attach frequencies to translations.
machine-readable dictionaries in text-to-speech systems. this paper presents the results of an experiment using machine-readable dictionaries (mrds) and corpora for building concatenative units for text to speech (tts) systems. theoretical questions concerning the nature of phonemic data in dictionaries are raised; phonemic dictionary data is viewed as a representative corpus over which to extract n-gram phonemic frequencies in the language. dictionary data are compared to corpus data, and phoneme inventories are evaluated for coverage. a methodology is defined to compute phonemic n-grams for incorporation into a tts system.
data types in computational phonology. this paper examines certain aspects of phonological structure from the viewpoint of abstract data types. our immediate goal is to find a format for phonological representation which will be reasonably faithful to the concerns of theoretical phonology while being rigorous enough to admit a computational interpretation. the longer term goal is to incorporate such representations into an appropriate general framework for natural language processing.
robust interpretation of user requests for text retrieval in a multimodal environment. we describe a parser for robust and flexible interpretation of user utterances in a multi-modal system for web search in newspaper databases. users can speak or type, and they can navigate and follow links using mouse clicks. spoken or written queries may combine search expressions with browser commands and search space restrictions. in interpreting input queries, the system has to be fault-tolerant to account for spontanous speech phenomena as well as typing or speech recognition errors which often distort the meaning of the utterance and are difficult to detect and correct. our parser integrates shallow parsing techniques with knowledge-based text retrieval to allow for robust processing and coordination of input modes. parsing relies on a two-layered approach: typical meta-expressions like those concerning search, newspaper types and dates are identified and excluded from the search string to be sent to the search engine. the search terms which are left after preprocessing are then grouped according to co-occurrence statistics which have been derived from a newspaper corpus. these co-occurrence statistics concern typical noun phrases as they appear in newspaper texts.
recognition of abstract objects - a decision theory approach within natural language processing. the daisy/alibaba-system developed within the wai-project represents both a specific solution to the automatic indexing problem and a general framework for problems in the field of natural language processing, characterized by fuzziness and uncertainty. the wai approach to the indexing problem has already been published [3], [5]. this paper however presents the underlying paradigm of recognizing abstract objects. the basic concepts are described, including the decision theory approach used for recognition.
automatic text categorization using the importance of sentences. automatic text categorization is a problem of automatically assigning text documents to predefined categories. in order to classify text documents, we must extract good features from them. in previous research, a text document is commonly represented by the term frequency and the inverted document frequency of each feature. since there is a difference between important sentences and unimportant sentences in a document, the features from more important sentences should be considered more than other features. in this paper, we measure the importance of sentences using text summarization techniques. then a document is represented as a vector of features with different weights according to the importance of each sentence. to verify our new method, we conducted experiments on two language newsgroup data sets: one written by english and the other written by korean. four kinds of classifiers were used in our experiments: na&iuml;ve bayes, rocchio, k-nn, and svm. we observed that our new method made a significant improvement in all classifiers and both data sets.
combining deictic gestures and natural language for referent identification. in virtually all current natural-language dialog systems, users can only refer to objexts by using linguistic descriptions. however, in human face-to-face conversation, participants frequently use various sorts of deictic gestures as well. in this paper, we will present the referent identification component of xtra, a system for a natural-language access to expert systems. xtra allows the user to combine nl input together with pointing gestures on the terminal screen in order to refer to objects on the display. information about the location and type of this deictic gesture, as well as about the linguistic description of the referred object, the case frame, and the dialog memory are utilized for identifying the object. the system is tolerant in respect to impreciseness of both the deictic and the natural language input. the user can thereby refer to objects more easily, avoid referential failures, and employ vague everyday terms instead of precise technical notions.
strategic lazy incremental copy graph unification. the strategic lazy incremental copy graph unification method is a combination of two methods for unifying feature structures. one, called the lazy incremental copy graph unification method, achieves structure sharing with constant order data access time which reduces the required memory. the other, called the strategic incremental copy graph unification method, uses an early failure finding strategy which first tries to unify substructures tending to fail in unification; this method is based on stochastic data on the likelihood of failure and reduces unnecessary computation. the combined method makes each feature structure unification efficient and also reduces garbage collection and page swapping occurrences, thus increasing the total efficiency of natural language processing systems mainly based on typed feature structure unification such as natural language analysis and generation systems.
a treatment of negative descriptions of typed feature structures. a formal treatment of typed feature structures (tfss) is developed to augment tfss, so that negative descriptions of them can be treated. negative descriptions of tfss can make linguistic descriptions compact and thus easy to understand. negative descriptions can be classified into three primitive negative descriptions: (1) negations of type symbols, (2) negations of feature existences, and (3) negations of feature-address value agreements. the formalization proposed in this paper is based on a&iuml;t-kaci's complex terms. the first description is treated by extending type symbol lattices to include complement type symbols. the second and third are treated by augmenting term structures with structures representing these negations. algorithms for augmented-tfs unification have been developed using graph unification, and programs using these algorithms have been written in common lisp.
structure sharing problem and its solution in graph unification. the revised graph unification algorithms presented here are more efficient because they reduce the amount of copying that was necessary because of the assumption that data-structure sharing in inputs occurs only when feature-structure sharing occurs.
parsing plans situation-dependently in dialogues. this paper describes a plan parsing method that can handle the effects and preconditions of actions and that parses plans in a manner dependent on dialogue state changes, especially on the mental state changes of dialogue participants caused by utterances. this method is based on active chart parsing and uses augmented edge structures to keep state information locally and time map management to deal with state changes. it has been implemented in prolog and is used for plan recognition in dialogues.
generation from under - and overspecified structures. this paper describes informally an algorithm for the generation from under- and overspecified feature structures. the generator requires a grammar, a goal category and a feature structure as input, and derives all strings whose corresponding feature structure is not in contradiction to the input structure.
the general architecture of generation in acord. this paper describes the general architecture of generation in the acord project. the central module of this architecture is a planning component, which allows to plan single sentences as an answer to a kb query. the planner works for three different languages (english, french and german) and for sentence generators based on two different grammar formalisms (ucg for english and french, lfg for german) independent of the particular grammar or grammar formalism. it uses several knowledge sources of the acord system to make its decisions. the output of the planner is used for the language specific generators as well as for the update of information needed for pronoun resolution.
constructing a model of dialog. in the present paper communicative cycle (cc) is considered as a dialog arising between two partners during solving a problem. communicative strategy (cs) is seen as a general scheme by which a dialog participant is guided in achieving his goal. cc is described in terms of the goals of the participants and cs.
generating natural language text in a dialog system. the paper deals with generation of natural language text in a dialog system. the approach is based on principles underlying the dialog system tarlus under development at tartu state university. the main problems concerned are the architecture of a dialog system and its knowledge base. much attention is devoted to problems which arise in answering the user queries - the problems of planning an answer, the non-linguistic and linguistic phases of generating an answer.
sentence adverbials in a system of question answering without a prearranged data base. in the present paper we provide a report on a joint approach to the computational treatment of sentence adverbials (such as <u>surprisingly, presumably</u> or <u>probably</u>) and focussing adverbials (such as <u>only</u> or <u>atleast</u>, including negation <u>(not)</u> and some other adverbial expressions, such as <u>for example</u> or <u>inter alia)</u> within a system of question answering without a prearranged data base (tibaq).this approach is based on a joint theoretical account of the expressions in question in the framework of a functional description of language; we argue that in the primary case, the expressions in question occupy, in the underlying topic-focus articulation of a sentence, the focus-initial position, extending their scope over the focus, or the new information, of a sentence, thus specifying, in a broad sense of the word, how the new information of a sentence holds. on the surface the expressions in question are usually moved to scope-ambiguous positions, which can be analyzed by means of several general strategies.
on underspecified processing of dynamic semantics. we propose a new inference system which operates on underspecified semantic representations of scope and anaphora. this system exploits anaphoric accessibility conditions from dynamic semantics to disambiguate scope ambiguities if possible. the main feature of the system is that it deals with underspecified descriptions directly, i. e. without enumerating readings.
flexible mixed-initiative dialogue management using concept-level confidence measures of speech recognizer output. we present a method to realize flexible mixed-initiative dialogue, in which the system can make effective confirmation and guidance using concept-level confidence measures (cms) derived from speech recognizer output in order to handle speech recognition errors. we define two concept-level cms, which are on content-words and on semantic-attributes, using 10-best outputs of the speech recognizer and parsing with phrase-level grammars. content-word cm is useful for selecting plausible interpretations. less confident interpretations are given to confirmation process. the strategy improved the interpretation accuracy by 11.5%. moreover, the semantic-attribute cm is used to estimate user's intention and generates system-initiative guidances even when successful interpretation is not obtained.
efficient dialogue strategy to find users' intended items from information query results. we address a dialogue framework that narrows down the user's query results obtained by an information retrieval system. the follow-up dialogue to constrain query results is significant especially with the speech interfaces such as telephones because a lot of query results cannot be presented to the user. the proposed dialogue framework generates guiding questions based on an information theoretic criterion to eliminate retrieved candidates by a spontaneous query without assuming a semantic slot structure. we first describe its concept on general information query tasks, and then deal with a query task on the appliance manual where structured task knowledge is available. a hierarchical confirmation strategy is proposed by making use of a tree structure of the manual, and then three cost functions for selecting optimal question nodes are compared. experimental evaluation demonstrates that the proposed system helps users find their intended items more efficiently.
english generation from interlingua by example-based method. this paper describes the experiment of the english generation from interlingua by the example-based method. the generator is implemented by using english word dictionary and concept dictionary developed in edr. how to construct examples and how to define the similarities are main problems. the results of experiments are shown.
determining recurrent sound correspondences by inducing translation models. i present a novel approach to the determination of recurrent sound correspondences in bilingual wordlists. the idea is to relate correspondences between sounds in wordlists to translational equivalences between words in bitexts (bilingual corpora). my method induces models of sound correspondence that are similar to models developed for statistical machine translation. the experiments show that the method is able to determine recurrent sound correspondences in bilingual wordlists in which less than 30% of the pairs are cognates. by employing the discovered correspondences, the method can identify cognates with higher accuracy than the previously reported algorithms.
the complexity of parsing with extended categorial grammars. instead of incorporating a gap-percolation mechanism for handling certain "movement" phenomena, the extended categorial grammars contain special inference rules for treating these problems. the lambek categorial grammar is one representative of the grammar family under consideration. it allows for a restricted use of hypothetical reasoning. we define a modification of the cocke-younger-kasami (cky) parsing algorithm which covers this additional deductive power and analyze its time complexity.
syntactic-head-driven generation. the previously proposed semantic -head-driven generation methods run into problems if none of the daughter constituents in the syntacto-semantic rule schemata of a grammar fits the definition of a semantic head given in [shieber et al., 1990]. this is the case for the semantic analysis rules of certain constraint-based semantic representations, e.g. underspecified discourse representation structures (udrss) [frank and reyle, 1992].since head-driven generation in general has its merits, we simply return to a syntactic definition of 'head' and demonstrate the feasibility of syntaclic-head-driven generation. in addition to its generality, a syntactic-head-driven algorithm provides a basis for a logically well-defined treatment of the movement of (syntactic) heads, for which only ad-hoc solutions existed, so far.
a description language for syntactically annotated corpora. this paper introduces a description language for syntactically annotated corpora which allows for encoding both the syntactic annotation to a corpus and the queries to a syntactically annotated corpus.in terms of descriptive adequacy and computational efficiency, the description language is a compromise between script-like corpus query languages and high-level, typed unification-based grammar formalisms.
speech acts of assertion in cooperative informational dialogue. dialogue systems should provide a cooperative informational dialogue aimed at knowledge sharing. in the paper speech acts of assertion (saa) are assumed to be the means of achieving this goal. a typology of saas is proposed which reflects certain cognitive aspects of communicative situation at different stages of mutual informing process. information constituents of the type assertions are formally described to represent a current cognitive state of the speaker's knowledge base, each proposition in it being characterized by a subjective verisimilitude evaluation. the general scheme of information flow in the cooperative dialogue is considered. with regard to this scheme the dialogue functions of saas are discussed.
an education and research tool for computational semantics. this paper describes an interactive graphical environment for computational semantics. the system provides a teaching tool, a stand alone extendible grapher, and a library of algorithms together with test suites. the teaching tool allows users to work step by step through derivations of semantic representations, and to compare the properties of various semantic formalisms such as intensional logic, drt, and situation semantics. the system is freely available on the internet.
linking syntactic and semantic arguments in a dependency-based formalism. we propose a formal characterization of variation in the syntactic realization of semantic arguments, using hierarchies of syntactic relations and thematic roles, and a mechanism of lexical inheritance to obtain valency frames from individual linking types. we embed the formalization in the new lexicalized, dependency-based grammar formalism of topological dependency grammar (tdg) (duchier and debusmann, 2001). we account for arguments that can be alternatively realized as a np or a pp, and model thematic role alternations. we also treat auxiliary constructions, where the correspondance between syntactic and semantic argumenthood is indirect.
a general computational model for word-form recognition and production. a language independent model for recognition and production of word forms is presented. this "two-level model" is based on a new way of describing morphological alternations. all rules describing the morphophonological variations are parallel and relatively independent of each other. individual rules are implemented as finite state automata, as in an earlier model due to martin kay and ron kaplan. the two-level model has been implemented as an operational computer programs in several places. a number of operational two-level descriptions have been written or are in progress (finnish, english, japanese, rumanian, french, swedish, old church slavonic, greek, lappish, arabic, icelandic). the model is bidirectional and it is capable of both analyzing and synthesizing word-forms.
finite-state parsing and disambiguation. a language-independent method of finite-state surface syntactic parsing and word-disambiguation is discussed. input sentences are represented as finite-state networks already containing all possible roles and interpretations of its units. also syntactic constraint rules are represented as finite-state machines where each constraint excludes certain types of ungrammatical readings. the whole grammar is an intersection of its constraint rules and excludes all ungrammatical possibilities leaving the correct interpretation(s) of the sentence. the method is being tested for finnish, swedish and english.
complexity, two-level morphology and finnish. although, two-level morphology has been found in practice to be an extremely efficient method for processing finnish words on very small machines, [barton86] has recently shown the method to be np-hard. this paper will discuss barton's theoretical argument and explain why it has not been a problem for us in practice.
compiling and using finite-state syntactic rules. a language-independent framework for syntactic finite-state parsing is discussed. the article presents a framework, a formalism, a compiler and a parser for grammars written in this formalism. as a substantial example, fragments from a nontrivial finite-state grammar of english are discussed.the linguistic framework of the present approach is based on a surface syntactic tagging scheme by f. karlsson. this representation is slightly less powerful than phrase structure tree notation, letting some ambiguous constructions be described more concisely.the finite-state rule compiler implements what was briefly sketched by koskenniemi (1990). it is based on the calculus of finite-state machines. the compiler transforms rules into rule-automata. the run-time parser exploits one of certain alternative strategies in performing the effective intersection of the rule automata and the sentence automaton.fragments of a fairly comprehensive finite-state grammar of english are presented here, including samples from non-finite constructions as a demonstration of the capacity of the present formalism, which goes far beyond plain disambiguation or part of speech tagging. the grammar itself is directly related to a parser and tagging system for english created as a part of project simpr using karlsson's cg (constraint grammar) formalism.
transfer in a multilingual mt system. in the context of transferbased mt systems, the nature of the intermediate representations, and particularly their 'depth', is an important question. this paper explores the notions of 'independence of languages' and 'simple transfer', and provides some principles that may enable linguists to study this problem in a systematic way.
the textplanning component pit of the lilog system. in this paper we describe the construction and implementation of pit (presenting information by textplanning), a subsystem of the lilog textunderstanding system. pit is used for planning answers of paragraph length to questions of the kind what do you know about x? we concentrated on a simple, easy to implement mechanism that can be further extended. experiences with this planning component, especially concerning the integration of new plans and further extensions are discussed.
tdl-a type description language for constraint-based grammars. this paper presents tdl, a typed feature-based representation language and inference system. type definitions in tdl consist of type and feature constraints over the boolean counectives. tdl supports open-and closed-world reasoning over types and allows for partitions and incompatible types. working with partially as well as with fully expanded types is possible. efficient reasoning in tdl is accomplished through specialized modules.
multilinguality in a text generation system for three slavic languages. this paper describes a multilingual text generation system in the domain of cad/cam software instructions for bulgarian, czech and russian. starting from a language-independent semantic representation, the system drafts natural, continuous text as typically found in software manuals. the core modules for strategic and tactical generation are implemented using the kpml platform for linguistic resource development and generation. prominent characteristics of the approach implemented are a treatment of multilinguality that makes maximal use of the commonalities between languages while also accounting for their differences and a common representational strategy for both text planning and sentence generation.
markedness and frequency: a computational analysis. when the markedness analysis is extended to the lexical and grammatical levels, the question arises whether an analogue of the markedness/frequency correlation, observed in phonology, also exists on these higher linguistic levels. this article presents evidence that in some interesting cases, such as tense and aspect forms in english, the correlation does not hold and that this failure is due not simply to superficial stylistic factors but rather to the inability of the markedness hypothesis to provide an adequate framework for the analysis of the english verbal system.
local cohesive knowledge for a dialogue-machine translation system. in a natural dialogue, there are many disturbances in the context level because of interruptions and inserted sentences. in spite of such phenomena, cohesion is a very important idea for understanding the context correctly. in our approach, cohesive knowledge which judges cohesion between sentences is given to the system and then the knowledge is used to find cohesion in disarranged context. it is also applied to interpret anaphora, ellipsis and pro-forms in the context. in order to do so, we define the knowledge and use its definition to abstract knowledge from a linguistics database almost automatically.
schema method: a framework for correcting grammatically ill-formed input. the schema method is a framework for correcting grammatically ill-formed input. in a natural language processing system ill-formed input cannot be overlooked. a computer assisted instruction (cai) system, in particular, needs to show the user's errors. this framework diagnoses ill-formed input, corrects it and explains the error, if an input is ill-formed. the framework recognizes a sentence at two steps: first parses weak grammar, and then strongly filters the parsed sentence. when it is known what sentences are passed by the filter, it can be used even if it is imperfect. as the strong filter, a new method is used: an interpretation schema and an interpretation rule. an interpretation schema collects input information schemata and then an interpretation rule judges whether the collected schemata are correct or incorrect. this approach overcomes the problem of relaxation control, the major drawback of the previous syntactically-oriented methods, and is also more efficient.
lexical-functional transfer: a transfer framework in a machine translation system based on lfg. this paper presents a transfer framework called lft (lexical-functional transfer) for a machine translation system based on lfg (lexical-functional grammar). the translation process consists of subprocesses of analysis, transfer and generation. we adopt the so called f-structures of lfg as the intermediate representations or interfaces between those subprocesses, thus the transfer process converts a source f-structure into a target f-structure. since lfg is a grammatical framework for sentence structure analysis of one language, for the purpose, we propose a new framework for specifying transfer rules with lfg schemata, which incorporates corresponding lexical functions of two different languages into an equational representation. the transfer process, therefore, is to solve equations called target f-descriptions derived from the transfer rules applied to the source f-structure and then to produce a target f-structure.
a robust cross-style bilingual sentences alignment model. most current sentence alignment approaches adopt sentence length and cognate as the alignment features; and they are mostly trained and tested in the documents with the same style. since the length distribution, alignment-type distribution (used by length-based approaches) and cognate frequency vary significantly across texts with different styles, the length-based approaches fail to achieve similar performance when tested in corpora of different styles. the experiments show that the performance in f-measure could drop from 98.2% to 85.6% when a length-based approach is trained by a technical manual and then tested on a general magazine.since a large percentage of content words in the source text would be translated into the corresponding translation duals to preserve the meaning in the target text, transfer lexicons are usually regarded as more reliable cues for aligning sentences when the alignment task is performed by human. to enhance the robustness, a robust statistical model based on both transfer lexicons and sentence lengths are proposed in this paper. after integrating the transfer lexicons into the model, a 60% f-measure error reduction (from 14.4% to 5.8%) is observed.
an intonational delphi poll on future trends in "information linguistics". the results of an international delphi poll on information linguistics which was carried out between 1982 and 1983 are presented.as part of conceptual work being done in information science at the university of constance an international delphi poll was carried out from 1982 to 1983 with the aim of establishing a mid-term prognosis for the development of "information linguistics". the term "information linguistics" refers to a scientific discipline combining the fields of linguistic data processing, applied computer science, linguistics, artificial intelligence, and information science. a delphi poll is a written poll of experts - carried out in this case in two phases. the results of the first round were incorporated into the second round, so that participants in the poll could react to the trends as they took shape.
speech recongnition and the frequency of recently used words: a modified markov model for natural language. speech recognition systems incorporate a language model which, at each stage of the recognition task, assigns a probability of occurrence to each word in the vocabulary. a class of markov language models identified by jelinek has achieved considerable success in this domain. a modification of the markov approach, which assigns higher probabilities to recently used words, is proposed and tested against a pure markov model. parameter calculation and comparison of the two models both involve use of the lob corpus of tagged modern english.
an underspecified hpsg representation for information structure. information structure can be of great use in linguistic applications, especially in those involving a speech component. however, focus marking by prosody is often ambiguous. existing theories capture this by rules that produce alternative focus structures. this disjunction is hard to handle computationally. in this paper, a compact, graphically underspecified representation is proposed, along with composition principles and a resolution routine based on context information.
a prolog implementation of government-binding theory. a parser which is founded on chomsky's government-binding theory and implemented in prolog is described. by focussing on systems of constraints as proposed by this theory, the system is capable of parsing without an elaborate rule set and subcategorization features on lexical items. in addition to the parse, theta, binding, and control relations are determined simultaneously.
a news analysis system. this paper describes a prototype news analysis system which classifies and indexes news stories in real time. the system extracts stories from a newswire, parses the sentences of the story, and then maps the syntactic structures into a concept base. this process results in an index containing both general categories and specific details. central to this system is a government-binding parser which processes each sentence of a news item. the system is completely modular and can be interfaced with different news feeds or concept bases.
a parlog implementation of government-binding theory. the purpose of this paper is to report on research on a parallel parser based on the principles and constraints of government-binding theory. the parser outputs a set of licensing relations, notably thematic or &theta;-role assignments and antecedent/anaphor and other binding relationships. the primary goal of the system is as a linguistics tool for exploring concurrencyand autonomy among modules of the theory.
automatic indexing and government-binding theory. this project note describes a system that receives, parses, indexes, and routes news reports. the core of this automatic indexer is a parser based on government-binding theory which derives thematic and binding relationships of arguments of the sentences of stories. these syntactic structures are interpreted by a semantic processor which is linked to conceptual representations of terms from a controlled indexing vocabulary. as a result, the system is capable of indexing news with respect to a large set of terms that denote the content of the articles.
building an mt dictionary from parallel texts based on linguistic and statistical information. a method for generating a machine translation (mt) dictionary from parallel texts is described. this method utilizes both statistical information and linguistic information to obtain corresponding words or phrases in parallel texts. by combining these two types of information, translation pairs which cannot be obtained by a linguistic-based method can be extracted. over 70% accurate translations of compound nouns and over 50% of unknown words are obtained as the first candidate from small japanese/english parallel texts containing severe distortions.
temporal relations in texts and time logical interferences. a calculus is presented which allows an efficient treatment of the following components: tenses, temporal conjunctions, temporal adverbials (of "definite" type), temporal quantifications and phases. the phases are a means for structuring the set of time-points t where a certain proposition is valid. for one proposition there may exist several "phase"-perspectives. the calculus has integrative properties, i. e. all five components are represented by the same formal means. this renders possible a rather easy combination of all informations and coniditions coming from the aforesaid components.
instatiations and (obligatory vs. optional) actants. a formalism for the representation of "semantic emphases" is introduced, using principal and accessory instantiations. it makes it possible to convert predicate expressions into network-like structures. as an application criteria for obligatory and optional actants are dealt with.
an algorithm for estimating the parameters of unrestricted hidden stochastic context-free grammars. a new algorithm is presented for estimating the parameters of a stochastic context-free grammar (scfg) from ordinary unparsed text. unlike the inside/outside (i/o) algorithm which requires a grammar to be specified in chomsky normal form, the new algorithm can estimate an arbitrary scfg without any need for transformation. the algorithm has worst-case cubic complexity in the length of a sentence and the number of nonterminals in the grammar. instead of the binary branching tree structure used by the i/o algorithm, the new algorithm makes use of a trellis structure for computation. the trellis is a generalization of that used by the baum-welch algorithm which is used for estimating hidden stochastic regular grammars. the paper describes the relationship between the trellis and the more typical parse tree representation.
dynamic programming method for analyzing conjunctive structures in japanese. parsing a long sentence is very difficult, since long sentences often have conjunctions which result in ambiguities. if the conjunctive structures existing in a long sentence can be analyzed correctly, ambiguities can be reduced greatly and a sentence can be parsed in a high successful rate. since the prior part and the posterior part of a conjunctive structure have a similar structure very often, finding two similar series of words is an essential point in solving this problem. similarities of all pairs of words are calculated and then the two series of words which have the greatest sum of similarities are found by a technique of dynamic programming. we deal with not only conjunctive noun phrases, but also conjunctive predicative clauses created by "renyoh chuushi-ho". we will illustrate the effectiveness of this method by the analysis of 180 long japanese sentences.
automatic detection of discourse structure by checking surface information in sentences. in this paper, we propose an automatic method for detecting discourse structure using a variety of clues existing in the surface information of sentences. we have considered three types of clue information: clue expressions, occurrence of identical/synonymous words/phrases, and similarity between two sentences. experimental results have shown that, in the case of scientific and technical texts, considerable part of the discourse structure can be estimated by incorporating the three types of clue information, without performing sentence understanding processes which requires giving knowledge to computers.
ambiguity resolution in the human syntactic parser: an experimental study. models of the human syntactic parsing mechanism can be classified according to the ways in which they operate upon ambiguous input. each mode of operation carries particular requirements concerning such basic computational characteristics of the parser as its storage capacities and the scheduling of its processes, and so specifying which mode is actually embodied in human parsing is a useful approach to determining the functional organization of the human parser. in section 1, a preliminary taxonomy of parsing models is presented, based upon a consideration of modes of handling ambiguities; and then, in section 2, psycholinguistic evidence is presented which indicates what type of model best describes the human parser.
a model of natural language processing of time-related expressions. this paper proposes a model of automatic processing of time-related expressions by introducing the notion of focus in the cognition level. the linguistic categories of time are determined on the basis of the relationships among the time of an extralinguistic situation, the focused time and the time of utterance.
some linguistic aspects for automatic text understanding. this paper proposes a system of mapping classes of syntactic structures as instruments for automatic text understanding. the system illustrated in japanese consists of a set of verb classes and information on mapping them together with noun phrases, tense and aspect. the system, having information on direction of possible inferences between the verb classes with information on tense and aspect, is supposed to be utilized for reasoning in automatic text understanding.
learning morphology: algorithms for the identification of the stem changes. the aim of the current work is to create tools for the automatic recognition of the estonian stem changing rules. the main problem consists in bringing together the formal classification features available to the computer and classification based on human knowledge. this paper introduces two algorithms. first, in stlearn the supervised inductive learning technique is used to find out the suitable features for automatic recognising of the stem changes. two stem variants can be bounded by more than one stem change. the second algorithm is created for the identifying the whole set of rules for stem pairs.
(semi-)automatic detection of errors in pos-tagged corpora. this paper presents a simple yet in practice very efficient technique serving for automatic detection of those positions in a part-of-speech tagged corpus where an error is to be suspected. the approach is based on the idea of learning and later application of "negative bigrams", i.e. on the search for pairs of adjacent tags which constitute an incorrect configuration in a text of a particular language (in english, e.g., the bigram article - finite verb). further, the paper describes the generalization of the "negative bigrams" into "negative n-grams", for any natural n, which indeed provides a powerful tool for error detection in a corpus. the implementation is also discussed, as well as evaluation of results of the approach when used for error detection in the negra&reg; corpus of german, and the general implications for the quality of results of statistical taggers. illustrative examples in the text are taken from german, and hence at least a basic command of this language would be helpful for their understanding - due to the complexity of the necessary accompanying explanation, the examples are neither glossed nor translated. however, the central ideas of the paper should be understandable also without any knowledge of german.
incremental construction of a lexical transducer for korean. the paper describes the construction of a lexical transducer for korean that can be used for stemming and generation. the method contains two innovations: (1) two-level rules as well-formedness constraints in the initial phase; (2) the combination of intersection and composition of rule transducers in a deep cascade for the final result.
the role of inversion and pp-fronting in relating discourse elements: some implications for cognitive and computational models of natural language processing. this paper will explore and discuss the less obvious ways syntactic structure is used to convey information and how this information could be used by a natural language database system as a heuristic to organize and search a discourse space.the primary concern of this paper will be to present a general theory of processing which capitalizes on the information provided by such non-svo word orders as inversion, (wh) clefting and prepositional phrase (pp)fronting.
on the role of old information in generating readable text: a psychological and computational definition of 'old' and 'new' information in the nosvo system. nosvo is a natural language generation postprocessor which is sensitive to old/new information contrasts. we believe that generating old information first establishes cohesion in text promoting readability. this paper describes the nosvo system in detail and the motivations for building it. we also provide a phychological and computational definition of "old" and "new" information.
arguments desperately seeking interpretation: parsing german infinitives. in this paper we present a gb-parsing system for german and in particular the system's strategy for argument interpretation, which copes with the difficulty that word order is relatively free in german and also that arguments can precede their predicate. in this latter case, the parser makes a provisional interpretation, which is checked when the argument structure of the predicate is available. moreover, a strategy of argument transfer is used in cases of long-distance scrambling, according to which arguments and adjuncts are attached to the domain of the coherent verb, ecm verb, or raising verb, and transferred to the infinitival complement for interpretation.
structured lexical data: how to make them widely available, useful and reasonably protected? a practicalexample with a trilingual dictionary. we are studying under which constraints structured lexical data can bemade, at the same time, widely available to the general public (freely ornot), electronically supported, published and reasonably protected frompiracy? a three facet approach-with dictionary tools, web servers and e-mail servers--seems to be effective. we illustrate our views with alex, a genericdictionary tool, which is used with a french-english-malay dictionary. thevery distinction between output, logical and coding formats is made. storage is based onthe latter and output formats are dynamically generated on the fly atrequest times-making the tool usable in many configurations. keeping the data structuredis necessary to make them usable also by automated processes and to allowdynamic filtering.
a daml+oil-compliant chinese lexical ontology. this paper presents an ongoing task that will construct a daml+oil-compliant chinese lexical ontology. the ontology mainly comprises three components: a hierarchical taxonomy consisting of a set of concepts and a set of relations describing the relationships among the concepts, a set of lexical entries associated with the concepts and relations, and a set of axioms describing the constraints on the ontology. it currently contains 1,075 concepts, 65,961 lexical entries associated with the concepts, 299 relations among the concepts excluding the hypernym and hyponym relations, 27,004 relations between the lexical entries and the concepts, and 79,723 relations associating the lexical entries with the concepts.
using linguistic, world, and contextual knowledge in a plan recognition model of dialogue. this paper presents a plan-based model of dialogue that combines world, linguistic, and contextual knowledge in order to recognize complex communicative actions such as expressing doubt. linguistic knowledge suggests certain discourse acts, a speaker's beliefs, and the strength of those beliefs; contextual knowledge suggests the most coherent continuation of the dialogue; and world knowledge provides evidence that the applicability conditions hold for those discourse acts that capture the relationship of the current utterance to the discourse as a whole.
sage: a sentence parsing and generation system. sage (sentence analysis and generation system) is an operational parsing and generating system. it is used as a natural language frontend for esprit project esteam--316, whose purpose is to advise a novice user through a cooperative dialogue.the aim of our system is to validate the use of a lexicon--grammar (drawn from the ladl studies) for sentence--parsing and generation, and to implement linguistic knowledge in a declarative way using a formalism based upon functional descriptions (fd). we have also developed the parser and the generation module so that they share informations and knowledge bases as much as possible: they work on the same semantic dictionary and the same linguistic knowledge bases, except that they have their own grammar. we have also implemented a tracking of semantic objects that have been instantiated during a dialogue session: the so-called token history is provided for semantic reference and anaphor resolution during parsing and for pronoun production during generation.after introducing to esteam--316, this paper describes the linguistic knowledge bases required by sage, and then focuses on the generation module. section 4 explains how pronouns are handled. the last section is a brief evaluation of our present work.
solving ambiguities in the semantic representation of texts. one of the issues of artificial intelligence is the transfer of he knowledge conveyed by natural language into formalisms that a computer can interpret. in the natural language processing department of the ibm france paris scientific center, we are developing and evaluating a system prototype whose purpose is to build a semantic representation of written french texts in a rigorous formal model (the conceptual graph model, introduced by j. f. sowa[10]).the semantic representation of texts may then be used in various applications, such as intelligent information retrieval. the accuracy of the semantic representation is therefore crucial in order to obtain valid results in any subsequent applications. in this article we explain how ambiguities related to natural language may be solved by semantic analysis using the conceptual graph model.
machine translation based on logically isomorphic montague grammars. the paper describes a new approach to machine translation, based on montague grammar, and an experimental translation system, rosetta, designed according to this approach. it is a multi-lingual system which uses 'logical derivation trees' as intermediate expressions.
parsing incomplete sentences. an efficient context-free parsing algorithm is presented that can parse sentences with unknown parts of unknown length. it produces in finite form all possible parses (often infinite in number) that could account for the missing parts. the algorithm is a variation on the construction due to earley. however, its presentation is such that it can readily be adapted to any chart parsing schema (top-down, bottom-up, etc...).
the representation of constituent structures for finite-state parsing. a mixed prefix-postfix notation for representations of the constituent structures of the expressions of natural languages is proposed, which are of limited degree of center embedding if the original expressions are noncenter-embedding. the method of constructing these representations is applicable to expressions with center embedding, and results in representations which seem to reflect the ways in which people actually parse those expressions. both the representations and their interpretations can be computed from the expressions from left to right by finite-state devices.the class of acceptable expressions of a natural language l all manifest no more than a small, fixed, finite degree <u>n</u> of center embedding. from this observation, it follows that the ability of human beings to parse the expressions of l can be modeled by a finite transducer that associates with the acceptable expressions of l representations of the structural descriptions of those expressions. this paper considers some initial steps in the construction of such a model. the first step is to determine a method of representating the class of constituent structures of the expressions of l without center embedding in such a way that the members of that class themselves have no more than a small fixed finite degree of center embedding. given a grammar that directly generates that class of constituent structures, it is not difficult to construct a deterministic finite-state transducer (parser) that assigns the appropriate members of that class to the noncenter-embedded expressions of l from left to right. the second step is to extend the method so that it is capable of representing the class of constituent structures of expressions of l with no more than degree <u>n</u> of center embedding in a manner which appears to accord with the way in which human beings actually parse those sentences. given certain reasonable assumptions about the character of the rules of grammar of natural languages, we show how this step can also be taken.
syntactic normalization of spontaneous speech. this paper presents some techniques that provide a standard parsing system for the analysis of ill-formed utterances. these techniques are feature generalization and heuristically driven deletions.
reverse queries in datr. datr is a declarative representation language for lexical information and as such, in principle, neutral with respect to particular processing strategies. previous datr compiler/interpreter systems support only one access strategy that closely resembles the set of inference rules of the procedural semantics of datr (evans & gazdar 1989a). in this paper we present an alternative access strategy (reverse query strategy) for a non-trivial subset of datr.
a production system model of first language acquisition. amber is a model of first language acquisition that improves its performance through a process of error recovery. the model is implemented in actg, an adaptive production system language. amber starts with the ability to say only one word at a time, but adds rules for inserting additional words in the correct order, based on comparisons between predicted and observed sentences. these insertion rules may be overly general and lead to errors of commission; in turn, these lead to more conservative rules with additional conditions. amber's learning mechanisms account for many of the developments observed in children's speech.
a generalized reconstruction algorithm for ellipsis resolution. we present an algorithm which assigns interpretations to several major types of ollipsis structures through a generalized procedure of syntactic reconstruction. ellipsis structures are taken to be sequences of lexically realized arguments and/or adjuncts of an empty verbal head. reconstruction is characterized as the specification of a (partial) correspondence relation between the unrealized head verb of an elided clause and its argument and adjuncts on one hand, and the head of a non-elided antecedent sentence and its arguments and adjuncts on the other. the algorithm generates appropriate interpretations for cases of vp ellipsis, pseudo-gapping, bare ellipsis (stripping), and gapping. it provides a uniform computational approach to a wide range of ellipsis phenomena, and it has significant advantages over several other approaches to ellipsis which have recently been suggested in the computational and linguistic literature.
active schemata and their role in semantic parsing. in the past years we have been applying semantic atn-grammars - as introduced by brown & burton (1974) - to natural language question-answering tasks (e.g. a lisp-tutor [barth, 1977], a question-answering system about the micro-world of soccer [rathke & sonntag, 1979]). we found that semantic grammars execute efficiently, but become large very quickly even with moderate domains of discourse. we therefore looked for ways to support parsing by domain-dependent knowledge represented in an inheritance network [laubsch, 1979]. in this paper we first briefly describe our representation language objtalk, and then illustrate how it is used for building an understanding system for processing german newspaper texts about the jobmarket situation.
language generation from conceptual structure: synthesis of german in a japanese/german mt project. this paper describes the current state of the semsyn project, whose goal is to develop a module for generation of german from a semantic representation. the first application of this module is within the framework of a japanese/german machine translation project. the generation process is organized into three stages that use distinct knowledge sources. the first stage is conceptually oriented and language independent, and exploits case and concept schemata. the second stage employs realization schemata which specify choices to map from meaning structures into german linguistic constructs. the last stage constructs the surface string using knowledge about syntax, morphology, and style. this paper describes the first two stages.
machine translation : what type of post-editing on what type of documents for what type of users. various typologies of technical and scientifical texts have already been proposed by authors involved in multilingual transfer problems. they were usually aimed at a better knowledge of the criteria for deciding if a document has to be or can be machine translated. such a typology could also lead to a better knowledge of the typical errors occuring, and so lead to more appropriate post-editing, as well as to improvements in the system.raw translations being usable, as they are quite often for rapid information needs, it is important to draw the limits between a style adequate for rapid information, and an elegant, high quality style such as required for information large dissemination. style could be given a new definition through a linguistic analysis based on machine translation, on communication situations and on the users' requirements and satisfaction.
when something is missing: ellipsis, coordination and the chart. this paper deals with two linguistic phenomena which are usually considered cases of ill-formedness by the computational linguistics community: intersentential ellipsis and coordination (possibly with gaps). we present an original solution, if compared to those already known for the two phenomena. this solution is conceived within a relevant approach to parsing, i.e. chart parsing, and is coherent with the basic ideas of this approach.
multi-lingual translation of spontaneously spoken language in a limited domain. janus is a multi-lingual speech-to-speech translation system designed to facilitate communication between two parties engaged in a spontaneous conversation in a limited domain. in an attempt to achieve both robustness and translation accuracy we use two different translation components: the glr module, designed to be more accurate, and the phoenix module, designed to be more robust. we analyze the strengths and weaknesses of each of the approaches and describe our work on combining them. another recent focus has been on developing a detailed end-to-end evaluation procedure to measure the performance and effectiveness of the system. we present our most recent spanish-to-english performance evaluation results.
n-th order ergodic multigram hmm for modeling of languages without marked word boundaries. ergodic hmms have been successfully used for modeling sentence production. however for some oriental languages such as chinese, a word can consist of multiple characters without word boundary markers between adjacent words in a sentence. this makes word-segmentation on the training and testing data necessary before ergodic hmm can be applied as the language model. this paper introduces the n-th order ergodic multigram hmm for language modeling of such languages. each state of the hmm can generate a variable number of characters corresponding to one word. the model can be trained without word-segmented and tagged corpus, and both segmentation and tagging are trained in one single model. results on its application on a chinese corpus are reported.
proof-nets and dependencies. proof-nets (roorda 1990) are a good device for processing with categorial grammars, mainly because they avoid spurious ambiguities. nevertheless, they do not provide easily readable structures and they hide the true proximity between categorial grammars and dependency grammars. we give here an other kind of proof-nets which is much related to dependency structures similar to those we meet in, for instance (hudson 1984). these new proof-nets are called connection nets. we show that connection nets provide not only easily interpretable structures, but also that processing with them is more efficient.
contextual natural language processing and daml for understanding software requirements specifications. in software engineering a system requirements document written in a natural language (nl) needs to be translated into one of the formal specification languages for system execution. when this translation is to be automated, resolution of the ambiguity in the document and explicit definition of implicit domain knowledge are necessary. in our approach, contextual natural language processing is used to overcome the ambiguity and the domain knowledge is expressed in darpa agent markup language (daml). the result is a formal representation of the informal requirements in nl for prototyping and even for implementation.
the grammatical function analysis between korean adnoun clause and noun phrase by using support vector machines. this study aims to improve the performance of identifying grammatical functions between an adnoun clause and a noun phrase in korean. the key task is to determine the relation between the two constituents in terms of such functional categories as subject, object, adverbial, and appositive. the problem is mainly caused by the fact that functional morphemes, which are considered to be crucial for identifying the relation, are frequently omitted in the noun phrases. to tackle this problem, we propose to employ the support vector machines(svm) in determining the grammatical functions. through an experiment with a tagged corpus for training svms, the proposed model is found to be useful.
translation selection through source word sense disambiguation and target word selection. a word has many senses, and each sense can be mapped into many target words. therefore, to select the appropriate translation with a correct sense, the sense of a source word should be disambiguated before selecting a target word. based on this observation, we propose a hybrid method for translation selection that combines disambiguation of a source word sense and selection of a target word. knowledge for translation selection is extracted from a bilingual dictionary and target language corpora. dividing translation selection into the two sub-problems, we can make knowledge acquisition straight-forward and select more appropriate target words.
implicit ambiguity resolution using incremental clustering in korean-to-english cross-language information retrieval. this paper presents a method to implicitly resolve ambiguities using dynamic incremental clustering in korean-to-english cross-language information retrieval. in the framework we propose, a query in korean is first translated into english by looking up korean-english dictionary, then documents are retrieved based on the vector space retrieval for the translated query terms. for the top-ranked retrieved documents, query-oriented document clusters are incrementally created and the weight of each retrieved document is re-calculated by using clusters. in experiment on trec-6 clir test collection, our method achieved 28.29% performance improvement for translated queries without ambiguity resolution for queries. this corresponds to 97.27% of the monolingual performance for original queries. when we combine our method with query ambiguity resolution, our method even outperforms the monolingual retrieval.
table-driven neural syntactic analysis of spoken korean. a cyk-table-driven interactive relaxation parsing method of spoken korean, integrated with the cyk-based morphological analysis is introduced. an extension of the categorial grammar is introduced to treat the free wordorder in korean. the table-driven control of interactive relaxation gives efficiency in constituent searching and expectation generation. the lexical nature of the categorial grammar and the distributed nature of the interactive relaxation parsing together show a smooth integration of both bottom-up and top-down effects during the spoken language analysis.
natural language interpretations for heterogeneous database access. in order to query into diverse types of databases and to integrate the resulting information, dispersed throughout the network in a specific domain, we must address complex problems due primarily to heterogeneity of the involved databases. in this paper, we propose to model access to heterogeneous databases, by interpreting natural language queries into queries in formal languages such as sql, oql, and cpl by accounting for various language-specific constructions including join relations, path expressions, and object bindings with domain resources and a common lexicon, in a combinatory categorial grammar framework.
lexicalized hidden markov models for part-of-speech tagging. since most previous works for hmm-based tagging consider only part-of-speech information in contexts, their models cannot utilize lexical information which is crucial for resolving some morphological ambiguity. in this paper we introduce uniformly lexicalized hmms for part-of-speech tagging in both english and korean. the lexicalized models use a simplified back-off smoothing technique to overcome data sparseness. in experiments, lexicalized models achieve higher accuracy than non-lexicalized models and the back-off smoothing method mitigates data sparseness better than simple smoothing methods.
an ascription-based approach to speech acts. the two principal areas of natural language processing research in pragmantics are belief modelling and speech act processing. belief modelling is the development of techniques to represent the mental attitudes of a dialogue participant. the latter approach, speech act processing, based on speech act theory, involves viewing dialogue in planning terms. utterances in a dialogue are modelled as steps in a plan where understanding an utterance involves deriving the complete plan a speaker is attempting to achieve. however, previous speech act based approaches have been limited by a reliance upon relatively simplistic belief modelling techniques and their relationship to planning and plan recognition. in particular, such techniques assume precomputed nested belief structures. in this paper, we will present an approach to speech act processing based on novel belief modelling techniques where nested beliefs are propagated on demand.
automatic model refinement - with an application to tagging. statistical nlp models usually only consider coarse information and very restricted context to make the estimation of parameters feasible. to reduce the modeling error introduced by a simplified probabilistic model, the classification and regression tree (cart) method was adopted in this paper to select more discriminative features for automatic model refinement. because the features are adopted dependently during splitting the classification tree in cart, the number of training data in each terminal node is small, which makes the labeling process of terminal nodes not robust. this over-tuning phenomenon cannot be completely removed by cross - validation process (i.e., pruning process). a probabilistic classification model based on the selected discriminative features is thus proposed to use the training data more efficiently. in tagging the brown corpus, our probabilistic classification model reduces the error rate of the top 10 error dominant words from 5.71% to 4.35%, which shows 23.82% improvement over the unrefined model.
principar - an efficient, broad-coverage, principle-based parser. we present an efficient, broad-coverage, principle-based parser for english. the parser has been implemented in c++ and runs on sun sparcstations with x-windows. it contains a lexicon with over 90,000 entries, constructed automatically by applying a set of extraction and conversion rules to entries from machine readable dictionaries.
interpreting syntactically ill-formed sentences. the paper discusses three different kinds of syntactic ill-formedness: ellipsis, conjunctions, and actual syntactic errors. it is shown how a new grammatical formalism, based on a two-level representation of the syntactic knowledge is used to cope with ill-formed sentences. the basic control structure of the parser is briefly sketched; the paper shows that it can be applied without any substantial change both to correct and to ill-formed sentences. this is achieved by introducing a mechanism for the hypothesization of syntactic structures, which is largely independent of the rules defining the well-formedness. on the contrary, the second level of syntactic knowledge embodies those rules and is used to validate the hypotheses emitted by the first level. alternative hypotheses are obtained, when needed, by means of local reorganizations of the parse tree. sentence fragments are handled by the same mechanism, but in this case the second level rules are used to detect the absence of one (or more) constituents.
interpretation of noun phrases in intensional contexts. this paper presents a network formalism for representing the meaning of noun phrases occurring in the context of intensional verbs such as seek and want. the basic assumption is that an intermediate representation is useful to carry out the interpretation process perspicuously. the proposed representation keeps apart de-re (transparent) and de-dicto readings, stating, by means of suitable arcs and nodes, that in the first case there is a real counterpart of the described entity, whereas in the second case no such counterpart exists. moreover, the concept of relevance of the description is emphasized and the relationships between intensional contexts and the dicotomy existing between value-free and value-loaded readings of definite descriptions is discussed. finally, the impact of the intermediate representation on the discourse history is considered, in order to explain how such a representation accounts for the contextual data and updates them according to the informational contents of the sentence being analyzed.
anticipating the reader's problems and the automatic generation of paraphrases. the notion of paraphrase is discussed and compared with the similar notion of periphrase. the role of paraphrases in oral communication is described, and the results of a study on the role of paraphrases in texts are given. finally, a system which models the use of paraphrases in texts is described.
a theory of lexical access in speech production. the generation of words in speech involves a number of processing stages. there is, first, a stage of conceptual preparation; this is followed by stages of lexical selection, phonological encoding, phonetic encoding and articulation. in addition, the speaker monitors the output and, if necessary, self-corrects. major parts of the theory have been computer modelled. the paper concentrates on experimental reaction time evidence in support of the theory.
conversion of a french surface expression into its semantic representation according to the reseda metalanguage. the work we describe here is a preliminary study concerning the automatic translation of natural language statements into the reseda semantic metalanguage. a first stage of the procedure consists in marking the "triggers", defined as lexical units which call upon one or more of the predicative patterns allowed for in the metalanguage. the predicative patterns obtained are then merged, and their case slots filled with the elements found in surface structure according to the predictions associated with the slots.
a quantifier scoping algorithm without a free variable constraint. three recent demands on quantifier scoping algorithms have been that they should be explicitly stated, they should be sound and complete with respect to the input sentence [hobbs and shieber 1987] and they should not employ a 'free variable constraint' [pereira 1989]. the first demand is for good academic practice. the second is to ask for an algorithm that generates all and only the possible scopings of a sentence. the third demand is for an algorithm that avoids appealing to the syntax of logical form in order to determine possible scopings. i present a modified version of [hobbs and shieber 1987], which simplifies its operation, and can be considered sound and complete, depending on what interpretations of english sentences are deemed possible. finally, any doubts concerning the use of logical form syntax are avoided.
learning dependencies between case frame slots. we address the problem of automatically acquiring case frame patterns (selectional patterns) from large corpus data. in particular, we propose a method of learning dependencies between case frame slots. we view the problem of learning case frame patterns as that of learning a multi-dimensional discrete joint distribution, where random variables represent case slots. we then formalize the dependencies between case slots as the probabilistic dependencies between these random variables. since the number of parameters in a multi-dimensional joint distribution is exponential in general, it is infeasible to accurately estimate them in practice. to overcome this difficulty, we settle with approximating the target joint distribution by the product of low order component distributions, based on corpus data. in particular we propose to employ an efficient learning algorithm based on the mdl principle to realize this task. our experimental results indicate that for certain classes of verbs, the accuracy achieved in a disambiguation experiment is improved by using the acquired knowledge of dependencies.
non-directionality and self-assessment in an example-based system using genetic algorithms. we show the application of an optimisation technique to natural language processing: genetic algorithms, thanks to the definition of a data structure called board and a formal distance. the system has two interesting features: non-directionality, which is more than bidirectionality, and self-assessment, independently of the inner knowledge. results of experiments are presented and discussed.
parsing long english sentences with pattern rules. in machine translation, parsing of long english sentences still causes some problems, whereas for short sentences a good machine translation system usually can generate readable translations. in this paper a practical method is presented for parsing long english sentences of some patterns. the rules for the patterns are treated separately from the augmented context free grammar, where each context free grammar rule is augmented by some syntactic functions and semantic functions. the rules for patterns and augmented context free grammar are complimentary to each other. in this way long english sentences covered by the patterns can be parsed efficiently.
saussurian analogy: a theoretical account and its application. in the cours de linguistique g&eacute;n&eacute;rale, saussure mentions a phenomenon of tremendous importance in language, analogy. for example, given the series walk, walked and look, how can we coin the fourth term, looked? we give a possible account of this phenomenon in terms of edition distances, thus paving the way to computational applications. this explanation accounts for prefixing, suffixing and infixing. we show how it is possible to perform the analogical analysis and generation of sentences, using a tree-bank and approximate pattern-matching. as a consequence, our proposal finds its place in the example-based approach to natural language processing.
learning question classifiers. in order to respond correctly to a free form factual question given a large collection of texts, one needs to understand the question to a level that allows determining some of the constraints the question imposes on a possible answer. these constraints may include a semantic classification of the sought after answer and may even suggest using different strategies when looking for and verifying a candidate answer.this paper presents a machine learning approach to question classification. we learn a hierarchical classifier that is guided by a layered semantic hierarchy of answer types, and eventually classifies questions into fine-grained classes. we show accurate results on a large collection of free-form questions used in trec 10.
the effectiveness of dictionary and web-based answer reranking. we describe an in-depth study of using a dictionary (wordnet) and web search engines (altavista, msn, and google) to boost the performance of an automated question answering system, webclopedia, in answering definition questions. the results indicate applying dictionary and web-based answer reranking together increase the performance of webclopedia on a set of 102 trec-10 definition questions by 25% in mean reciprocal rank score and 14% in finding answers in the top 5.
location normalization for information extraction. ambiguity is very high for location names. for example, there are 23 cities named 'buffalo' in the u.s. country names such as 'canada', 'brazil' and 'china' are also city names in the usa. almost every city has a main street or broadway. such ambiguity needs to be handled before we can refer to location names for visualization of related extracted events. this paper presents a hybrid approach for location normalization which combines (i) lexical grammar driven by local context constraints, (ii) graph search for maximum spanning tree and (iii) integration of semi-automatically derived default senses. the focus is on resolving ambiguities for the following types of location names: island, town, city, province, and country. the results are promising with 93.8% accuracy on our test collections.
from trees to predicate-argument structures. the penn treebank encodes valuable information such as grammatical function, semantic roles, and identification of traces. the addition of such information was intended to facilitate the process of predicate-argument extraction. however, even with the enriched annotation this task is far from trivial and, to our knowledge, no complete set of predicate argument structures derived from the treebank exists. our paper describes a method for retrieving predicate-argument structures that circumvents the complexity of the tree structures in the corpus, while employing few template rules. our system operates on a flattened, morphologically enriched version of the corpus. this flattened representation allows access to all levels of the tree simultaneously and thus enables the detection of the main sentence constituents by means of simple template rules. a small number of rules apply to identify the head words of each constituent and the latter fill in the constituent templates, to build the logical forms representative of the predicate argument structure. the system is robust in the face of incomplete syntactic coverage.
on the structural complexity of natural language sentences. the objective of this paper is to formalize the intnition about the complexity of syntactic structures. we propose a definition of structural complexity such that sentences ranked by our definition as more complex are generally more difficult for humans to process. we justify the definition by showing how it is able to account for several seemingly unrelated phenomena in natural languages.
arbus, a tool for developing application grammars. the development of a natural language system usually requires frequent changes to the grammar used. it is then very useful to be able to define and modify the grammar rules easily, without having to tamper with the parsing program. the arbus system was designed to help develop grammars for natural language processing. with this system one can build, display, test, modify and file a grammar interactively in a very convenient way. this was achieved by packaging a parser and a grammar editor with an elaborate interface which isolates the user from implementation details and guides him as much as possible.
the automated acquisition of topic signatures for text summarization. in order to produce a good summary, one has to identify the most relevant portions of a given text. we describe in this paper a method for automatically training topic signatures-sets of related words, with associated weights, organized around head topics and illustrate with signatures we created with 6,194 trec collection texts over 4 selected topics. we describe the possible integration of topic signatures with outologies and its evaluaton on an automated text summarization system.
its: interactive translation system. at coling78 we reported on an interactive translation system now called its, which uses on-line man-machine interaction. this paper is an update on its with suggestions for future work.
concept discovery from text. broad-coverage lexical resources such as wordnet are extremely useful. however, they often include many rare senses while missing domain-specific senses. we present a clustering algorithm called cbc (clustering by committee) that automatically discovers concepts from text. it initially discovers a set of tight clusters called committees that are well scattered in the similarity space. the centroid of the members of a committee is used as the feature vector of the cluster. we proceed by assigning elements to their most similar cluster. evaluating cluster quality has always been a difficult task. we present a new evaluation methodology that is based on the editing distance between output clusters and classes extracted from wordnet (the answer key). our experiments show that cbc outperforms several well-known clustering algorithms in cluster quality.
error diagnosting and selection in a training system for second language learning. a diagnosing procedure to be used in intelligent systems for language instruction is presented. based on a knowledge representation scheme for a certain class of syntactic correctness conditions the system carries out a thorough analysis of possible error hypotheses and their consequences. a comparison with earlier attempts shows a clearly improved precision of diagnostic results. first of all, the procedure concentrates on an exact localization of rule violations, but - if desired - is able to infer information about factual faults as well.
hypothesis scoring over theta grids information in parsing chinese sentences with serial verb constructions. serial verb constructions (svcs) in chinese are popular structural ambiguities which make parsing difficult. in this paper, we propose a quantitative model, 's-model'. based on theta grids information, that can systematically resolve ambiguities of svcs to arbitrate competence between verbs in parsing svcs sentences. s-model has three major characteristics: (1) it can resolve svcs without relying on specific types of svcs classified by linguists; (2) it can handle long svcs, i.e., svcs with more than two verbs; (3) it can simultaneously determine whether a verb candidate is really acts as a verb in the sentence.
a corpus study of negative imperatives in natural language instructions. in this paper, we define the notion of a preventative expression and discuss a corpus study of such expressions in instructional text. we discuss our coding schema, which takes into account both form and function features, and present measures of inter-coder reliability for those features. we then discuss the correlations that exist between the function and the form features.
solving some persistent presupposition problems. /soames 1979/ provides some counterexamples to the theory of natural language presuppositions that is presented in /gazdar 1979/. /soames 1982/ provides a theory which explains these counterexamples. /mercer 1987/ rejects the solution found in /soames 1982/ leaving these counterexamples unexplained. by reappraising these insightful counterexamples, the inferential theory for natural language presuppositions described in /mercer 1987, 1988/ gives a simple and straightforward explanation for the presuppositional nature of these sentences.
ambiguity resolution and the retrieval of idioms: two approaches. when an idiomatic expression is encountered during natural language processing, the ambiguity between its idiomatic and non-idiomatic meaning has to be resolved. rather than including both meanings in further processing, a conventionality-principle could be applied. this results in best-first processing of the idiomatic analysis. two models are discussed fot the lexical representation of idioms. one extends the notion continuation class from two-level morphology, the other is a localist, connectionist model. the connectionist model has an important advantage over the continuation class model: the conventionality principle follows naturally from the architecture of the connectionist model.
a novel analysis of temporal frame-adverbials. in this paper interpretation principles for simple and complex frame-adverbial expressions are presented. central to these principles is a distinction between phases and periods together with the temporal hierarchy, where multiple scales of time and relations can be expressed. a system, clockwise, has been implemented which interprets swedish temporal expressions according to the principles outlined in the paper.
a plan recognition model for clarification subdialogues. one of the promising approaches to analyzing task-oriented dialogues has involved modeling the plans of the speakers in the task domain. in general, these models work well as long as the topic follows the task structure closely, but they have difficulty in accounting for clarification subdialogues and topic change. we have developed a model based on a hierarchy of plans and metaplans that accounts for the clarification subdialogues while maintaining the advantages of the plan-based approach.
parsing dependency grammar using ale. this paper describes a technique for parsing dependency grammars using a bottom-up chart parser originally designed for phrase-structure grammars, using typed feature structures as the only data structure. each lexical item is represented as a tree where nodes indicate lexical elements (the anchor, its dependents and governor) and edges (branches) indicate dependency relations between these elements. nodes may carry additional features, including one for node saturation. trees combine into derived trees provided that node and edge features unify. the ale system is used to implement an active chart parser where a chart edge represents a tree, and two adjacent edges are combined into a more saturated tree.
disambiguating cue phrases in text and speech. cue phrases are linguistic expressions such as 'now' and 'well' that may explicitly mark the structure of a discourse. for example, while the cue phrase 'incidentally' may be used sententially as an adverbial, the discourse use initiates a digression. in [8], we noted the ambiguity of cue phrases with respect to discourse and sentential usage and proposed an intonational model for their disambiguation. in this paper, we extend our previous characterization of cue phrases and generalize its domain of coverage, based on a larger and more comprehensive empirical study: an examination of all cue phrases produced by a single speaker in recorded natural speech. we also associate this prosodic model with orthographic and part-of-speech analyses of cue phrases in text. such a dual model provides both theoretical justification for current computational models of discourse and practical application to the generation of synthetic speech.
strategies for effective paraphrasing. in this paper we present a new dimension to paraphrasing text in which characteristics of the original text motivate strategies for effective paraphrasing. our system combines two existing robust components: the irus-ii natural language understanding system and the spokesman generation system. we describe the architecture of the system and enhancements made to these components to facilitate paraphrasing. we particularly look at how levels of representation in these two systems are used by specialists in the paraphraser which define potential problems and paraphrasing strategies. finally, we look at the role of paraphrasing in a cooperative dialog system. we will focus here on paraphrasing in the context of natural language interfaces and particularly on how multiple interpretations introduced by various kinds of ambiguity can be conbasted in paraphrases using both sentence structure and highlighting and formating the text itself.
automatic optimization of dialogue management. designing the dialogue strategy of a spoken dialogue system involves many nontrivial choices. this paper presents a reinforcement learning approach for automatically optimizing a dialogue strategy that addresses the technical challenges in applying reinforcement learning to a working dialogue system with human users. we then show that our approach measurably improves performance in an experimental system.
a corpus-based learning technique for building a self-extensible parser. human intervention and/or training corpora tagged with various kinds of information were often assumed in many natural language acquisition models. this assumption is a major source of inconsistencies, errors, an d inefficiency in learning. in this paper, we explore the extent to which a parser may extend it-self without relying on extra input from the outside world. a learning technique called sep is proposed and attached to the parser. the input to sep is raw sentences, while the output is the knowledge that is missing in the parser. since parsers and raw sentences are commonly available and no human intervention is needed in learning, sep could make fully automatic large-scale acquisition more feasible.
building a bilingual wordnet-like lexicon: the new approach and algorithms. a bilingual concept mrd is of significance for ie, mt, wsd and the like. however, it is reasonably difficult to build such a lexicon for there exist two ontologies, also, the evolution of such a lexicon is quite challenging. in this paper, we would like to put forth the new approach to building a bilingual wordnet-like lexicon and to dwell on some of the pivotal algorithms.a characteristic of this new approach is to emphasize the inheritance and transformation of the existent monolingual lexicon. on the one hand, we have extracted all the common knowledge in wordnet as the semantic basis for further use. on the other hand, we have developed a visualized developing tool for the lexicographers to interactively operate on to express the bilingual semantics. the bilingual lexicon has thus gradually come into being in this natural process.icl now has benefited a lot by employing this new approach to build ccd (chinese concept dictionary), a bilingual wordnet-like lexicon, in peking university.
an earley-type recognizer for dependency grammar. the paper is a first attempt to fill a gap in the dependency literature, by providing a mathematical result on the complexity of recognition with a dependency grammar. the paper describes an improved earley-type recognizer with a complexity o(igi2n3). the improvement is due to a precompilation of the dependency rules into parse tables, that determine the conditions of applicability of two primary actions, predict and scan, used in recognition.
inheritance in hierarchical relational structures. a brief survey is conducted of the inheritance principle - the conveyance of properties between components within a hierarchical relational structure. the standard form of inheritance is considered, using the subset (is-a) relation and highlighted as an example of downward inheritance. downward inheritance is extended to specialisation of actions, and cases are presented in which the rule fails.an alternative and less well-known form of inheritance is introduced - upward inheritance. several examples in which upward inheritance is valid and others in which it is not valid are given, in a treatment highlighting the analogy with downward inheritance. the validity of the rule, in those case in which it operates, is underlined, to distinguish it from induction.a brief account is given of the search for the underlying reasons for the validity of inheritance rules and these are then given. the solution turns out to be due to a hidden or implicit quantifier within the relations that are used. the semantical nature of the problem and of its solution are stressed, emphasising the impossibility of a purely syntactic analysis and solution to the problem. various points of interest arising from the analysis are listed and discussed.
towards a new generation of terminological resources: an experiment in building a terminological knowledge base. this paper describes a project to construct a terminological knowledge base, called cogniterm. first, we position our research framework in relationship to recent developments in computational lexicology and knowledge engineering. second, we describe the cogntterm prototype and discuss its advantages over conventional term banks. finally, we outline some of the methodological issues that have emerged from our work.
chart-based transfer rule application in machine translation. transfer-based machine translation systems require a procedure for choosing the set of transfer rules for generating a target language translation from a given source language sentence. in an mt system with many competing transfer rules, choosing the best set of transfer rules for translation may involve the evaluation of an explosive number of competing sets. we propose a solution to this problem based on current best-first chart parsing algorithms.
a new predictive analyzer of english. aspects of syntactic predictions made during the recognition of english sentences are investigated. we reinforce kuno's original predictive analyzer[1] by introducing five types of predictions. for each type of prediction, we discuss and present its necessity, its description method, and recognition mechanism. we make use of three kinds of stacks whose behavior is specified by grammar rules in an extended version of greibach normal form. we also investigate other factors that affect the predictive recognition process, i.e., preferences among syntactic ambiguities and necessary amount of lookahead. these factors as well as the proposed handling mechanisms of predictions are tested by analyzing two kinds of articles. in our experiment, more than seventy percent of sentences are recognized and looking two words ahead seems to be the critical length for the predictive recognition.
dynamic logic with possible world. this paper introduces a semantic theory dlpw, dynamic logic with possible world, which extends groenendijk's dpl and cresswell's indices semantics. the semantics can interpret the temporal and modal sense and anaphora.
alignment of shared forests for bilingual corpora. research in example-based machine translation (ebmt) has been hampered by the lack of efficient tree alignment algorithms for bilingual corpora. this paper describes an alignment algorithm for ebmt whose running time is quadratic in the size of the input parse trees. the algorithm uses dynamic programming to score all possible matching nodes between structure-sharing trees or forests. we describe the algorithm, various optimizations, and our implementation.
a transitive model for extracting translation equivalents of web queries through anchor text mining. one of the existing difficulties of cross-language information retrieval (clir) and web search is the lack of appropriate translations of new terminology and proper names. different from conventional approaches, in our previous research we developed an approach for exploiting web anchor texts as live bilingual corpora and reducing the existing difficulties of query term translation. although web anchor texts, undoubtedly, are very valuable multilingual and wide-scoped hypertext resources, not every particular pair of languages contains sufficient anchor texts in the web to extract corresponding translations in the language pair. for more generalized applications, in this paper we extend our previous approach by adding a phase of transitive (indirect) translation via an intermediate (third) language, and propose a transitive model to further exploit anchor-text mining in term translation extraction applications. preliminary experimental results show that many query translations which cannot be obtained using the previous approach can be extracted with the improved approach.
exploiting a large data base by longman. we wish to explore some of the aspects of the exploitation of two dictionary files by longman ltd, one for 'core' english and one for english idioms.we'll try to show the feasibility of an approach to language processing based on a lexicon, conceived of as the repository of grammatical, semantic and knowledge-of-the-world information.after giving a brief description of the computer files (section i) we'll focus on the following points:(a)a lexical approach to grammar allows a considerable simplification of the psg component of a parsing system (section ii, part one);(b)the syntactic potential of many lexemes (at surface structure level) can serve as a guide to their deep structure configurations (section ii, part two);(c)provided that a dictionary makes use of a limited defining vocabulary, the texts of the dictionary definitions can be processed on the basis of correlations between syntactic structures (filled with individual lexemes or lexemes belonging to specifiable classes) and semantic relationships such as that between a process verb and an instrument (section iii).
learning chinese bracketing knowledge based on a bilingual language model. this paper proposes a new method for automatic acquisition of chinese bracketing knowledge from english-chinese sentence-aligned bilingual corpora. bilingual sentence pairs are first aligned in syntactic structure by combining english parse trees with a statistical bilingual language model. chinese bracketing knowledge is then extracted automatically. the preliminary experiments show automatically learned knowledge accords well with manually annotated brackets. the proposed method is particularly useful to acquire bracketing knowledge for a less studied language that lacks tools and resources found in a second language more studied. although this paper discusses experiments with chinese and english, the method is also applicable to other language pairs.
approaches to thesaurus production. we contrast two approaches to thesaurus production: the traditional and intuitive one versus the amsler-type procedure, which interactively generates filiations among the genus words in a computerized dictionary. we discuss the application of such a procedure to our lexical data base (longman dictionary of contemporary english).
controlled active procedures as a tool for linguistic engineering. controlled active procedures are productions that are grouped under and activated by units called 'scouts'. scouts are controlled by units called 'missions', which also select relevant sections from the data structure for rule application. following the problem reduction method, the parsing problem is subdivided into ever smaller subproblems, each one of which is represented by a mission. the elementary problems are represented by scouts. the cap grammar formalism is based on experience gained with natural language (nl) analysis and translation by computer in the sonderforschungsbereich 100 at the university of saarbr&uuml;cken over the past twelve years and dictated by the wish to develop an efficient parser for random nl texts on a sound theoretical basis. the idea has ripened in discussions with colleagues from the eurotra-project and is based on what heinz-dieter maas has developed in the framework of the susy-ii system.in the present paper, cap is introduced as a means of linguistic engineering (cf. simmons 1985), which covers aspects like rule writing, parsing strategies, syntactic and semantic representation of meaning, representation of lexical knowledge etc.
instance based learning with automatic feature selection applied to word sense disambiguation. we describe an algorithm for word sense disambiguation (wsd) that relies on a lazy learner improved with automatic feature selection. the algorithm was implemented in a system that achieves excellent performance on the set of data released during the senseval-2 competition. we present the results obtained and discuss the performance of various features in the context of supervised learning algorithms for wsd.
partial synthesis of sentences by coroutining constraints on different levels of well-formedness. we show how the two main characteristics of the illico natural language interface --- guided composition mode by partial synthesis, and the modularity of the encoding of linguistic knowledge specifying the lexical, syntactic, semantic and conceptual levels of well-formedness --- have lead us to develop an approach and a system in which all the constraints on the different levels of well-formedness are coroutined when the system analyzes a given sentence or synthesizes a partial one. we describe the principle of the general coroutining process and the associated prolog program.
mt and topic-based techniques to enhance speech recognition systems for professional translators. our principle objective was to reduce the error rate of speech recognition systems used by professional translators. our work concentrated on spanish-to-english translation. in a baseline study we estimated the error rate of an off-the-shelf recognizer to be 9.98%. in this paper we describe two independent methods of improving speech recognizers: a machine translation (mt) method and a topic-based one. an evaluation of the mt method suggests that the vocabulary used for recognition cannot be completely restricted to the set of translations produced by the mt system and a more sophisticated constraint system must be used. an evaluation of the topic-based method showed significant error rate reduction, to 5.07%.
categorial grammar and discourse representation theory. in this paper it is shown how simple texts that can be parsed in a lambek categorial grammar can also automatically be provided with a semantics in the form of a discourse representation structure in the sense of kamp [1981]. the assignment of meanings to texts uses the curry-howard-van benthem correspondence.
an ibm-pc environment for chinese corpus analysis. this paper describes a set of computer programs for chinese corpus analysis. these programs include (1) extraction of different characters, bigrams and words; (2) word segmentation based on bigram, maximal-matching and the combined technique; (3) identification of special terms; (4) chinese concordancing; (5) compiling collocation statistics and (6) evaluation utilities. these programs run on the ibm-pc and batch programs co-ordinate the use of these programs.
a project report on np: an assumption-based nl plan inference system that uses feature structures. this paper presents a project report on np, a working natural language plan inference system that uses feature structures and is based on assumptions. input to the system is in the form of feature structures, which can be taken directly from the output of a semantic parser. plan actions are represented by feature-structure plan schemata with preconditions, hierarchical decompositions, and effects. output is in the form of a network of believed assertions represented in a knowledge base, and can be reported, used to answer generation-system queries, or drive side-effecting demons. the plan inference component is implemented using a feature-structure-based inference engine and models of plan recognition, prediction, and inference. the inference engine is implemented using a rewriting system for pattern-matching, and an assumption-based truth maintenance system (atms) for conjunctions. the atms allows pre-instantiation of hypothetically known assertions and implications, which can significantly reduce processing time. the atms also permits simultaneous consideration of multiple possible inputs or multiple possible inferred plan outputs; these can be mutually conflicting or supportive. this capability will be important for disambiguation. the np system is used to infer dialog- and domain-level plans, among other types.original contributions include: a plan inference system that works directly from feature structures; a plan inference system that uses an atms and plan schema actions with preconditions and effects to infer hierarchical and chained plans; and, an inference engine that works with multiple feature-structure assertions and rules.
chinese string searching using the kmp algorithm. this paper is about the modification of kmp (knuth, morris and pratt) algorithm for string searching of chinese text. the difficulty is searching through a text string of single-and multi-byte characters. we showed that proper decoding of the input as sequences of characters instead of bytes is necessary. the standard kmp algorithm can easily be modified for chinese string searching but at the worst-case time-complexity of o(3n) in terms of the number of comparisons. the finite-automaton implementation can achieve worst-case time complexity of o(2n) but constructing the transition table depends on the size of the alphabet, &sigma;, which is large for chinese (for big-5, &sigma; > 13,000). a mapping technique reduces the size the alphabet to at most /p/ where p is the pattern string.
a pdp architecture for processing sentences with relative clauses. a modular parallel distributed processing architecture for parsing, representing and paraphrasing sentences with multiple hierarchical relative clauses is presented. a lowel-level network reads the segments of the sentence word by word into partially specified case-role representations of the acts. a higher-level network combines these representations into a list of complete act representations. this internal representation stores the information conveyed by the sentence independent of its linguistic form. the information can be output in natural language in different form or style, e.g. as a sequence of simple sentences or as a complex sentence consisting of relative clauses. generating output is independent from parsing, and what actually gets generated depends on the training of the generator modules.
learning part-of-speech guessing rules from lexicon: extension to non-concatenative operations. one of the problems in part-of-speech tagging of real-word texts is that of unknown to the lexicon words. in (mikheev, 1996), a technique for fully unsupervised statistical acquisition of rules which guess possible parts-of-speech for unknown words was proposed. one of the over-simplification assumed by this learning technique was the acquisition of morphological rules which obey only simple concatenative regularities of the main word with an affix. in this paper we extend this technique to the non-concatenative cases of suffixation and assess the gain in the performance.
hybrid neuro and rule-based part of speech taggers. a hybrid system for tagging part of speech is described that consists of a neuro tagger and a rule-based corrector. the neuro tagger is an initial-state annotator that uses different lengths of context based on longest context priority. its inputs are weighted by information gains that are obtained by information maximization. the rule-based corrector is constructed by a set of transformation rules to make up for the shortcomings of the neuro tagger. computer experiments show that almost 20% of the errors made by the neuro tagger are corrected by these transformation rules, so that the hybrid system can reach an accuracy of 95.5% counting only the ambiguous words and 99.1% counting all words when a small thai corpus with 22,311 ambiguous words is used for training. this accuracy is far higher than that using an hmm and is also higher than that using a rule-based model.
self-organizing chinese and japanese semantic maps. this paper describes a corpus-based connectionist approach to the development of self-organizing chinese and japanese semantic maps, proposing an improved coding method using tfidf term-weighting and newly introducing a numerical evaluation for objectively judging the results. the adaption of tfidf term-weighting is proved to be effective by experimental comparisons with five other coding methods. the effectiveness and necessity of the proposed method for creating semantic maps are clarified by comparisons with a conventional clustering technique and multivariate statistical analysis.
modularity, parallelism, and licensing in a principle-based parser for german. this paper presents a direct implementation of government-binding theory in a parser for german, which faithfully models the modular structure of the theory. the modular design yields a flexible environment, in which it is possible to define and test various versions of principles and parameters. the several modules of linguistic theory and the parser proper are interleaved in parallel fashion for early elimination of ungrammatical structures. efficient processing of global constraints is made possible by the concept of licensing, and the use of tree indexing techniques.
the influence of tagging on the classification of lexical complements. a large corpus (about 100 mb of text) was selected and examples of 750 frequently occurring verbs were tagged with their complement class as defined by a large computational syntactic dictionary, comlex syntax. this tagging task led to the refinement of already existing classes and to the addition of classes that had previously not been defined. this has resulted in the enrichment and improvement of the original comlex syntax dictionary. tagging also provides statistical data which will allow users to select more common complements of a particular verb and ignore rare usage. we discuss below some of the problems encountered in tagging and their resolution.
parsing against lexical ambiguity. marcus' original deterministic parsing included almost no part-of-speech ambiguity. in this paper, the addition of part-of-speech ambiguity to a deterministic parser written in prolog is described. to handle this ambiguity, it was necessary to add no special mechanisms to the parser. instead the grammar rules were made to enforce agreement, and reject ungrammatical sentences. the resulting system is very effective and covers many examples of ambiguity.
the transfer of finite verb forms in a machine translation system. this paper is based on work done jointly by hanne ruus, ebbe spang-hanssen and the author, all of the university of copenhagen. the work was done within the framework of eurotra and sponsored by the commission of the european community. work on this paper was begun whilst the author was at issco, geneva.
coordination in an axiomatic grammar. for some time there has been interest in the idea of parsing as deduction. here we present a grammatical formalism, 'axiomatic grammar', which is based upon a small number of linguistically motivated axioms and deduction rules. each axion or rule combines a 'category' with a string of words to form a further category. this contrasts with the usual 'tree-structure' approach to syntactic analysis where constituents are combined with each other to form a further constituent.we describe a grammar for english which has a good coverage of 'non-constituent' coordination. the grammar has been integrated with a toy semantics, and has been implemented in a left-to-right parser with incremental semantic interpretation. the parser does not suffer from spurious ambiguity.
dynamics, dependency grammar and incremental interpretation. the paper describes two equivalent grammatical formalisms. the first is a lexicalised version of dependeney grammar, and this can be used to provide tree-structured analyses of sentences (though some-what flatter than those usually provided by phrase structure grammars). the second is a new formalism, 'dynamic dependency grammar', which uses axioms and deduction rules to provide analyses of sentences in terms of transitions between states.a reformulation of dependency grammar using state transitions is of interest on several grounds. firstly, it can be used to show that incremental interpretation is possible without requiring notions of overlapping, or flexible constituency (as in some versions of categorial grammar), and without destroying a transparent link between syntax and semantics. secondly, the reformulation provides a level of description which can act as an intermediate stage between the original grammar and a parsing algorithm. thirdly, it is possible to extend the reformulated grammars with further axioms and deduction rules to provide coverage of syntactic constructions such as coordination which are difficult to encode lexically.
non-constituent coordination: theory and practice. despite the large amount of theoretical work done on non-constituent coordination during the last two decades, many computational systems still treat coordination using adapted parsing strategies, in a similar fashion to the sysconj system developed for atns. this paper reviews the theoretical literature, and shows why many of the theoretical accounts actually have worse coverage than accounts based on processing. finally, it shows how processing accounts can be described formally and declaratively in terms of dynamic grammars.
a matrix representation of the inflectional forms of arabic words: a study of co-occurrence patterns. a proposed "matrix" method for the representation of the inflectional paradigms of arabic words is presented. this representation results in a classification of arabic words into a tree structure (fig(1)) whose leaves represent unique conjugational or derivational paradigms, each represented in the proposed "matrix" form.a study of about 2,500 stems from a high frequency arabic wordlist due to landau <1> has revealed a systematic set of co-occurrence patterns for the enclitic pronouns of arabic verbs and for the possessive pronouns attached to arabic nouns. each co-occurrence pattern represents a subcategorization frame that reflects the underlying semantic relationship.the key feature that distinguishes these semantic patterns has been observed to be whether the attached suffixes relate to the animate or inanimate. in some cases for verbs, the number of the subject is also a significant feature. these semantic features also extend to non-attached subjects and objects (for verbs) and to possessive noun complements (for nouns). therefore the semantic classes presented in this paper also assist in syntactic/semantic analysis.the first application that was developed, based upon the proposed representation is a stem-based arabic morphological analyser, from which a spell checker (on a ps/2 microcomputer) emerged as a by-product. currently, the system is being used to interact with an arabic syntactic parser and there are plans to use it in a machine assisted translation system.
incremental interpretation: applications, theory, and relationship to dynamic semantics. why should computers interpret language incrementally? in recent years psycholinguistic evidence for incremental interpretation has become more and more compelling, suggesting that humans perform semantic interpretation before constituent boundaries, possibly word by word. however, possible computational applications have received less attention. in this paper we consider various potential applications, in particular graphical interaction and dialogue. we then review the theoretical and computational tools available for mapping from fragments of sentences to fully scoped semantic representations. finally, we tease apart the relationship between dynamic semantics and incremental interpretation.
a matrix representation of the inflectional forms of arabic words: a study of co-occurrence patterns. a proposed "matrix" method for the representation of the inflectional paradigms of arabic words is presented. this representation results in a classification of arabic words into a tree structure (fig(1)) whose leaves represent unique conjugational or derivational paradigms, each represented in the proposed "matrix" form.a study of about 2,500 stems from a high frequency arabic wordlist due to landau <1> has revealed a systematic set of co-occurrence patterns for the enclitic pronouns of arabic verbs and for the possessive pronouns attached to arabic nouns. each co-occurrence pattern represents a subcategorization frame that reflects the underlying semantic relationship.the key feature that distinguishes these semantic patterns has been observed to be whether the attached suffixes relate to the animate or inanimate. in some cases for verbs, the number of the subject is also a significant feature. these semantic features also extend to non-attached subjects and objects (for verbs) and to possessive noun complements (for nouns). therefore the semantic classes presented in this paper also assist in syntactic/semantic analysis.the first application that was developed, based upon the proposed representation is a stem-based arabic morphological analyser, from which a spell checker (on a ps/2 microcomputer) emerged as a by-product. currently, the system is being used to interact with an arabic syntactic parser and there are plans to use it in a machine assisted translation system.
a methodology for terminology-based knowledge acquisition and integration. in this paper we propose an integrated knowledge management system in which terminology-based knowledge acquisition, knowledge integration, and xml-based knowledge retrieval are combined using tag information and ontology management tools. the main objective of the system is to facilitate knowledge acquisition through query answering against xml-based documents in the domain of molecular biology. our system integrates automatic term recognition, term variation management, context-based automatic term clustering, ontology-based inference, and intelligent tag information retrieval. tag-based retrieval is implemented through interval operations, which prove to be a powerful means for textual mining and knowledge acquisition. the aim is to provide efficient access to heterogeneous biological textual data and databases, enabling users to integrate a wide range of textual and non-textual resources effortlessly.
the parsody system: automatic prediction of prosodic boundaries for text-to-speech. as commercial text-to-speech systems move above the word level to the sentence level, the prediction of the correct prosodic informations becomes a significant factor in the perceived naturalness of the synthesised speech.this article reports on "parsody", an experimental system which combines a partial parser with a prosodic marking component to predict the location and relative strength of prosodic boundaries in text.
multitale: linking medical concepts by means of frames. in this paper multitale, a system for the semantic tagging of medical neurosurgical texts and for the semi-automatic expansion of the medical lexicon, will be presented. given the textual information explosion (in particular in, though not restricted to, specialized domains) there is an urgent need for tools enabling to exploit the information available in natural language texts. multitale has been devised therefore primarily with the aim to make explicit semantic information in medical texts, which should lead to more refined information retrieval results. by making "educated guesses" the system moreover has a possibility to expand its own lexicon of medical terms so to be able to cope with new texts.
hierarchical lexical structure and interpretive mapping in machine translation. large-scale knowledge-based machine translation requires significant amounts of lexical knowledge in order to map syntactic structures to conceptual structures. this paper presents a framework in which lexical knowledge is separated into different levels of representation, which are arranged in a hierarchical model based on principles of knowledge representation and lexical semantics. the proposed methodology is language-independent, and has been used to organize lexical knowledge for both english and japanese.
application of analogical modelling to example based machine translation. this paper describes a self-modelling, incremental algorithm for learning translation rules from existing bilingual corpora. the notions of supracontext and subcontext are extended to encompass bilingual information through simultaneous analogy on both source and target sentences and juxtaposition of corresponding results. analogical modelling is performed during the learning phase and translation patterns are projected in a multi-dimensional analogical network. the proposed framework was evaluated on a small training corpus providing promising results. suggestions to improve system performance are this kind of analysis unquestionably leads to more computationally expensive and difficult to obtain systems. our approach consists in a fully modular analogical framework, which can cope with lack of resources, and will perform even better when these are available.
tulips-2 - natural language learning system. the learning of a natural language is considered to be an important aspect of man-machine communication in human language. the methods of the russian language knowledge representation and acquisition implemented in the experimental under-standing system tulips-2 are described. these methods provides for understanding utterances that contain words and structures unknown to the system wherther they are grammatical or erroneous items, or the user's speech peculiarities.
an agreement corrector for russian. the paper describes an application-oriented system that corrects agreement errors. in order to correct a sentence with such errors, an extended morphological structure is created which contains various grammatical forms of the words used in the sentence. for this structure the bottom-up parsing is performed, and syntactic structures are found that contain minimal number of changes in comparison with the original sentence. experiments with real sentences have shown promising results.
identifying anaphoric and non-anaphoric noun phrases to improve coreference resolution. we present a supervised learning approach to identification of anaphoric and non-anaphoric noun phrases and show how such information can be incorporated into a coreference resolution system. the resulting system outperforms the best muc-6 and muc-7 coreference resolution systems on the corresponding muc coreference data sets, obtaining f-measures of 66.2 and 64.0, respectively.
expressive power of grammatical formalisms. we propose formalisms and concepts which allow to make precise the arguments in controversies over the adequacy of competing models of language, and over their formal equivalence.
learning how to answer questions using trivia games. in this paper we examine a sentence comprehension task: given a question, and an extended sentence known to answer that question, the goal is to extract the short answer to the question. as an initial solution, a novel robust statistical model is presented which combines the semantics of the expected answer with the expected context within which the answer will be found. two distinct trivia game databases, with no additional annotation, are used to train and test the model.
an integrated model for anaphora resolution. the paper discusses a new knowledge-based and sublanguage-oriented model for anaphora resolution, which integrates syntactic, semantic, discourse, domain and heuristical knowledge for the sublanguage of computer science. special attention is paid to a new approach for tracking the center throughout a discourse segment, which plays an important role in proposing the most likely antecedent to the anaphor in case of ambiguity.
learning mechanism in machine translation system "pivot". nec's machine translation system "pivot" provides analysis editing functions. the user can interactively correct errors in analysis results, such as dependency and case. however, without a learning mechanism, the user must correct similar dependency errors several times. we discuss the learning mechanism to utilize dependency and case information specified by the user. we compare four types of matching methods by simulation and show non-restricted best matching is the most effective.
discourse structures for text generation. text generation programs need to be designed around a theory of text organization. this paper introduces rhetorical structure theory, a theory of text structure in which each region of text has a central nuclear part and a number of satellites related to it. a natural text is analyzed as an example, the mechanisms of the theory are identified, and their formalization is discussed. in a comparison, rhetorical structure theory is found to be more comprehensive and more informative about text function than the text organization parts of previous text generation systems.
an overview of the edr electronic dictionary and the current status of its utilization. in this paper we present the specification and the structure of edr electronic dictionary which was developed in a nine-year project. the first version of edr dictionary (v1.0) and its revised version (vi.5) are already released and are now utilized at many sites for both academic and commercial purposes. we also describe the current status how the edr dictionary is utilized. finally we will give the outline of the new r&d project which edr will launch in fiscal 1996.
a software environment for developing natural language understanding system. this paper deals with a software environment for developing the natural language understanding system. the system called multi-layered software environment (mlse) is proposed for providing a designer of a language understanding system with wide varieties of design alternatives in software components which derive from computational linguistics. the mlse is a collection of module packages for building the tools for language understanding system. that is, by integrating the computational linguistics methods into the mlse scheme, we have emphasized the layered approach to build the software environment as the basis for developing the language understanding system. in order to illustrate the strategy of the mlse scheme, we have discussed the case study for designing question and answering system. based upon this case study, we have developed a new language understanding system called japanese q & a system (jqas) which was a product of the mise scheme. the mlse has implemented in variety of lisps such as inter-lisp on dec-20 and lisp f3 on ibm370.the jqas has domain specific q & a system for computer documentation and explanation system.
an approach to a semantic analysis of metaphor. the present study deals with conflict resolution process in metaphorical interpretation for the noun phrase. in order to make the problem more explicit, we have reviewed the knowledge representation with conflict both from cognitive psychology and artificial intelligence. then, we propose a semantic model which is optained from the notion of linguistics as chemistry. that is, the model called "semistry" is introduced so as to interprete a metaphor semantic bonds between nouns. by using production system couped with contex free parser (elingol), the working system called meta-sim is constructed to analyze the noun phrase metaphor. finally, there are discussions on a role of metaphor in human cognitive processing.
integrating shallow linguistic processing into a unification-based spanish grammar. this paper describes to what extent deep processing may benefit from shallow processing techniques and it presents a nlp system which integrates a linguistic pos tagger and chunker as a preprocessing module of a broad-coverage unification-based grammar of spanish. experiments show that the efficiency of the overall analysis improves significantly and that our system also provides robustness to the linguistic processing, while maintaining both the accuracy and the precision of the grammar.
the jarap experimental system of japanese-russian automatic translation. the paper is the first report on the experimental mt system developed as part of the japanese-russian automatic translation project (jarap). the system follows the transfer approach to mt. limited so far to lexico-morphological processing, it is seen as a foundation for more ambitions linguistic research. the system is implemented on ibm pc, ms dos, in arity prolog (analysis and transfer) and turbo pascal (synthesis).
a process-activation based parsing algorithm for the development of natural language grammars. a running system, named sail, for the development of natural language grammars is described. stress is put on the particular grammar rule model adopted, named complex grammar units, and on the parsing algorithm that runs rules written in according to this model. moreover, the parser is like a processor and sees grammar rules as processes which can be activated or inactivated, and can handle exchange of information, structured as messages, among rules for long distance analysis. a brief description of the framework of sail a user can interact with, named sis, is also given. finally, an example shows that different grammar formalisms can be implemented into the frame of sail.
lexical chains for question answering. the paper presents a method for finding topically related words on an extended wordnet. by exploiting the information in the wordnet glosses, the connectivity between the synsets is dramatically increased. topical relations expressed as lexical chains on extended wordnet improve the performance of a question answering system by increasing the document retrieval recall and by providing the much needed axioms that link question keywords with answers.
a computational analysis of complex noun phrases in navy messages. methods of text compression in navy messages are not limited to sentence fragments and the omissions of function words such as the copula be. text compression is also exhibited within "grammatical" sentences and is identified within noun phrases in navy messages. mechanisms of text compression include increased frequency of complex noun sequences and also increased usage of nominalizations. semantic relationships among elements of a complex noun sequence can be used to derive a correct bracketing of syntactic constructions.
control structures for actions in procedural texts and pt-chart. this paper describes a partial taxonomy of control structures for actions in procedural texts. on the basis of the taxonomy, we examine natural language expressions for control structures in japanese procedural texts and present pt (<u>p</u>rocedural <u>t</u>ext) -chart which represents the structure of a procedural text.
analysis and processing of compact text. this paper describes the characteristics of compact text as revealed in computer analysis of a set of physician notes. computer processing of the documents was performed using the lsp system for natural language analysis. a numerical breakdown of syntactic and semantic patterns found in the texts is presented. it is found that four major properties of compact text make it possible to process the content of the documents with syntactic procedures that operate on full free text.
representation and recognition method for multi-word translation units in korean-to-japanese mt system. due to grammatical similarities, even a one-to-one mapping between korean and japanese words (or morphemes) can usually result in a high quality korean-to-japanese machine translation. however, multi-word translation units (mwtu) such as idioms, compound words, etc., need an n-to-m mapping, and their component words often do not appear adjacently, resulting in a discontinuous mwtu. during translation, the mwtu should be treated as one lexical item rather than a phrase. in this paper, we define the types of mwtus and propose their representation and recognition method depending on their characteristics in korean-to-japanese mt system. in an experimental evaluation, the proposed method turned out to be very effective in handling mwtus, showing an average recognition accuracy of 98.4% and a fast recognition time.
representing regularities in the metaphoric lexicon. this paper describes a system for representing knowledge about conventional metaphors for use by natural language analysis, generation and acquisition systems. a system of hierarchically related structured associations is used. these associations are implemented as a part of the kodiak representation language. particular attention is paid in this paper to representational mechanisms that can capture generalizations over the system of conventional metaphors as a whole.
resolving syntactic ambiguities with lexico-semantic patterns: an analogy-based approach. a system for the resolution of syntactic ambiguities is illustrated which operates on morpho-syntactically ambiguous subject-object assignments in italian and tries to find the most likely analysis on the basis of the evidence contained in a knowledge base of linguistic data automatically extracted from on-line resources. the system works on the basis of a set of straighforward analogy-based principles. its performance on a substantial corpus of test data extracted from real texts is described.
syntactic features for high precision word sense disambiguation. this paper explores the contribution of a broad range of syntactic features to wsd: grammatical relations coded as the presence of adjuncts/arguments in isolation or as subcategorization frames, and instantiated grammatical relations between words. we have tested the performance of syntactic features using two different ml algorithms (decision lists and adaboost) on the senseval-2 data. adding syntactic features to a basic set of traditional features improves performance, especially for adaboost. in addition, several methods to build arbitrarily high accuracy wsd systems are also tried, showing that syntactic features allow for a precision of 86% and a coverage of 26% or 95% precision and 8% coverage.
the generation of high-level structure for extended explanations. this paper analyzes the structural features of naturally-occurring extended explanations and argues that current generation methodologies are inadequate for determining high-level structure. it presents a computational model based on the hypothesis that high-level structure - composed of a unifying framework and its associated basic blocks - can be determined by bottom-up processes that attempt to satisfy speaker, listener, and compositional goals, after which top-down strategies can be used to organize the material about the selected framework.
universal guides and finiteness and symmetry of grammar processing algorithms. this paper presents a novel technique called "universal guides" which explores inherent properties of logic grammars (changing variable binding status) in order to characterize formal criteria for termination in a derivation process. the notion of universal guides also offers a new framework in which both parsing and generation can be viewed merely as two different instances of the same generic process: guide consumption. this technique generalizes and exemplifies a new and original use of an existing concept of "proper guides" recently proposed in literature for controlling top-down left-to-right (tdlr) exccution in logic programs. we show that universal guides are independent of a particular grammar evaluation strategy. also, unlike proper guides they can be specified in the same manner for any given algorithm without knowing in advance whether the algorithm is a parsing or a generation algorithm. their introduction into a grammar prevents as well the occurrence of certain grammar rules an infinite number of times during a derivation process.
chart parsing and constraint programming. in this paper, parsing-as-deduction and constraint programming are brought together to outline a procedure for the specification of constraint-based chart parsers. following the proposal in shieber et al. (1995), we show how to directly realize the inference rules for deductive parsers as constraint handling rules (fr&uuml;hwirth, 1998) by viewing the items of a chart parser as constraints and the constraint base as a chart. this allows the direct use of constraint resolution to parse sentences.
information gain ratio as term weight: the case of summarization of ir results. this paper proposes a new term weighting method for summarizing documents retrieved by ir system. unlike query-biased summarization, our method utilizes not the information of query, but the similarity information among original documents by hierarchical clustering. to map the similarity structure of the clusters into the weight of each word, we adopt the information gain ratio of probabilistic distribution of each word as term weight.
jaunt: a constraint solver for disjunctive feature structures. to represent a combinatorial number of ambiguous interpretations of a natural language sentence efficiently, a "packed" or "factorized" representation is necessary. we propose a representation that comprises a set of explicit value disjunctions and constraints imposed on them. new constraints are successively added for disambiguation, during which local consistencies are maintained by an underlying mechanism. we have developed a constraint solver called jaunt that embodies this idea. the latest technques, including constraint propagation and forward checking, are employed as constraint satisfaction mechanisms. jaunt also allows an external meta-inference program to intervene in the constraint satisfaction process in order to control the application of the constraints.
a stochastic parser based on an slm with arboreal context trees. in this paper, we present a parser based on a stochastic structured language model (slm) with a flexible history reference mechanism. an slm is an alternative to an n-gram model as a language model for a speech recognizer. the advantage of an slm against an n-gram model is the ability to return the structure of a given sentence. thus slms are expected to play an important part in spoken language understanding systems. the current slms refer to a fixed part of the history for prediction just like an n-gram model. we introduce a flexible history reference mechanism called an act (arboreal context tree; an extension of the context tree to tree-shaped histories) and describe a parser based on an slm with acts. in the experiment, we built an slm-based parser with a fixed history and one with acts, and compared their parsing accuracies. the accuracy of our parser was 92.8%, which was higher than that for the parser with the fixed history (89.8%). this result shows that the flexible history reference mechanism improves the parsing ability of an slm, which has great importance for language understanding.
multiple discourse relations on the sentential level in japanese. in the spoken language machine translation project verbmobil, the semantic formalism language for underspecified discourse representation structures (lud) is used. lud describes a number of drss and allows for underspecification of scopal ambiguities. dealing with japanese-to-english translation besides german-to-english poses challenging problems. in this paper, a treatment of multiple discourse relation constructions on the sentential level is discussed. these are common in japanese but cause a problem for the formalism. it is shown that the underspecification is to be represented for them, too. additionally, it is possible to state a semantic constraint on the resolution of multiple discourse relations which seems to prevail over the syntactic c-command constraint.
a bootstrapping method for extracting bilingual text pairs. this paper proposes a method for extracting bilingual text pairs from a comparable corpus. the basic idea of the method is to apply bootstrapping to an existing corpus-based cross-language information retrieval (clir) approach. we conducted preliminary tests with english and japanese bilingual corpora. the bootstrapping method led to much better results for the task of extracting translation pairs compared with a corpus-based clir method without boot-strapping, and the extracted translation pairs could be useful training data for improving results of the corpus-based clir method.
zero pronouns and conditionals in japanese instruction manuals. this paper proposes a method of the zero pronoun resolution, which is one of the essential processes in understanding systems for japanese manual sentences. it is based on pragmatic properties of japanese conditionals. we examined a number of sentences appearing in japanese manuals according to the classification based on the types of agent and the types of verb phrase. as a result, we obtained the following pattern of usage in matrix clauses: 1) the connective particles to and reba have the same distribution of usage. tara and nara have the same distribution of usage. 2) the distribution of usage of to and reba, and that of tara and nara are complementary to each other. we show that these distributions of usage can be used for resolution of zero subjects.
word extraction from corpora and its part-of-speech estimation using distributional analysis. unknown words are inevitable at any step of analysis in natural language processing. we propose a method to extract words from a corpus and estimate the probability that each word belongs to given parts of speech (poss), using a distributional analysis. our experiments have shown that this method is effective for inferring the pos of unknown words.
a stochastic parser based on a structural word prediction model. in this paper, we present a stochastic language model using dependency. this model considers a sentence as a word sequence and predicts each word from left to right. the history at each step of prediction is a sequence of partial parse trees covering the preceding words. first our model predicts the partial parse trees which have a dependency relation with the next word among them and then predicts the next word from only the trees which have a dependency relation with the next word. our model is a generative stochastic model, thus this can be used not only as a parser but also as a language model of a speech recognizer. in our experiment, we prepared about 1,000 syntactically annotated japanese sentences extracted from a financial newspaper and estimated the parameters of our model. we built a parser based on our model and tested it on approximately 100 sentences of the same newspaper. the accuracy of the dependency relation was 89.9%, the highest accuracy level obtained by japanese stochastic parsers.
an hpsg-based generator for german an experiment in the reusability of linguistic resources. we describe the development of a generator for german built by reusing and adapting existing linguistic data and software. reusability is crucial for the successful application of nlp techniques to real-life problems since it helps to cut down on both development and adaptation effort. however, combining resources not designed to work together is not trivial. we describe the problems arising when integrating three preexisting resources (fuf, a unification-based generator, an hpsg grammar for german, and x2morf, a two-level morphology component) and the adaptations necessary to come up with a wide coverage tactical generator for german.
automatic detection of omissions in translations. adomit is an algorithm for automatic detection of omissions in translations. the algorithm relics solely on geometric analysis of bitext maps and uses no linguistic information. this property allows it to deal equally well with omissions that do not correspond to linguistic units, such as might result from word-processing mishaps. adomit has proven itself by discovering many errors in a hand-constructed gold standard for evaluating bitext mapping algorithms. quantitative evaluation on simulated omissions showed that, even with today's poor bitext mapping technology, adomit is a valuable quality control tool for translators and translation bureaus.
a computational model for generating referring expressions in a multilingual application domain. in this paper we analyse the problem of generating referring expressions in a multilingual generation system that produces instructions on how to fill out pension forms. the model we propose is an implementation of theoretical investigations of martin and is based on a clear representation of the knowledge sources and choices that contribute to the identification of the most appropriate linguistic expressions. to cope effectively with pronominalization we propose to augment the centering model with mechanisms exploiting the discourse structure. at every stage of the referring expressions generation process issues raised by multilinguality are considered and dealt with by means of rules customized with respect to the output language.
example-based speech intention understanding and its application to in-car spoken dialogue system. this paper proposes a method of speech intention understanding based on dialogue examples. the method uses a spoken dialogue corpus with intention tags to regard the intention of each input utterance as that of the sentence to which it is the most similar in the corpus. the degree of similarity is calculated according to the degree of correspondence in morphemes and dependencies between sentences, and it is weighted by the dialogue context information. an experiment on inference of utterance intentions using a large-scale in-car spoken dialogue corpus of ciair has shown 68.9% accuracy. furthermore, we have developed a prototype system of in-car spoken dialogue processing for a restaurant retrieval task based on our method, and confirmed the feasiblity of the system.
multi-level translation aids in a distributed system. at coling80, we reported on an interactive translation system called its. we will discuss three problems in the design of the first version of its: (1) human factors, (2) the "all or nothing" syndrome, and (3) traditional centralized processing. we will also discuss a new version of its, which is now being programmed. this new version will hopefully overcome these problems by placing the translator in control, providing multiple levels of aid, and distributing the processing.
word sense disambiguation using static and dynamic sense vectors. it is popular in wsd to use contextual information in training sense tagged data. co-occurring words within a limited window-sized context support one sense among the semantically ambiguous ones of the word. this paper reports on word sense disambiguation of english words using static and dynamic sense vectors. first, context vectors are constructed using contextual words in the training sense tagged data. then, the words in the context vector are weighted with local density. using the whole training sense tagged data, each sense of a target word is represented as a static sense vector in word space, which is the centroid of the context vectors. then contextual noise is removed using a automatic selective sampling. a automatic selective sampling method use information retrieval technique, so as to enhance the discriminative power. in each test case, a automatic selective sampling method retrieves n relevant training samples to reduce noise. using them, we construct another sense vectors for each sense of the target word. they are called dynamic sense vectors because they are changed according to a target word and its context. finally, a word sense of a target word is determined using static and dynamic sense vectors. the english senseval test suit is used for this experimentation and our method produces relatively good results.
stochastic dependency parsing of spontaneous japanese spoken language. this paper describes the characteristic features of dependency structures of japanese spoken language by investigating a spoken dialogue corpus, and proposes a stochastic approach to dependency parsing. the method can robustly cope with inversion phenomena and bunsetsus which don't have the head bunsetsu by relaxing the syntactic dependency constraints. the method acquires in advance the probabilities of dependencies from a spoken dialogue corpus tagged with dependency structures, and provides the most plausible dependency structure for each utterance on the basis of the probabilities. an experiment on dependency parsing for driver's utterances in ciair in-car spoken dialogue corpus has been made. the experimental result has shown our method to be effective for robust parsing of spoken language.
yet another paper about partial verb phrase fronting in german. i describe a very simple hpsg analysis for partial verb phrase fronting. i will argue that the presented account is more adequate than others made during the past years because it allows the description of constituents in fronted positions with their modifier remaining in the nonzfronted part of the sentence.a problem with ill-formed signs that are admitted by all hpsg accounts for partial verb phrase fronting known so far will be explained and a solution will be suggested that uses the difference between combinatoric relations of signs and their representation in word order domains.
linguistic processing using a dependency structure grammar for speech recognition and understanding. this paper proposes an efficient linguistic processing strategy for speech recognition and understanding using a dependency structure grammar. the strategy includes parsing and phrase prediction algorithms. after speech processing and phrase recognition based on phoneme recognition, the parser extracts the sentence with the best likelihood taking account of the phonetic likelihood of phrase candidates and the linguistic likelihood of the semantic inter-phrase dependency relationships. a fast parsing algorithm using breadth-first search is also proposed. the predictor pre-selects the phrase candidates using transition rules combined with a dependency structure to reduce the amount of phonetic processing. the proposed linguistic processor has been tested through speech recognition experiments. the experimental results show that it greatly increases the accuracy of speech recognitions, and the breadth-first parsing algorithm and predictor increase processing speed.
two approaches to semantic interfaces in text generation. this paper is a contribution towards the exploration of semantic interfaces in text generation systems. it suggests a general interpretation of semantics for the purpose of text generation as an interlevel between lexicogrammar (the resources of grammar and vocabulary) and higher levels of organization (knowledge base, user model, text planning, and so on). two approaches to the design of this interlevel that have been implemented in generation systems are then presented -- chooser & inquiry semantics and situation-specific semantic systems. they are compared and contrasted to bring out their relative merits.
semantic rule based text generation. this paper presents a semantically oriented, rule based method for single sentence text generation and discusses its implementation in the kafka generator. this generator is part of the xcalibur natural language interface developed at cmu to provide natural language facilities for a wide range of expert systems and data bases. kafka takes as input the knowledge representation used in xcalibur system and incrementally transforms it first into conceptual dependency graphs and then into english.1
b-sure: a believed situation and uncertain-action representation environment. this paper presents a system that is capable of representing situations, states, and nondeterministic nonmonotonic-outcome actions occurring in multiple possible worlds. the system supports explicit representations of actions and situations used in intentional action theory and situation theory. both types and instances are supported. situations and states before and after nonmonotomic actions can be represented simultaneously. agents have free will as to whether to choose to perform an action or not. situations and actions can have expected values, allowing the system to support decision-making and decision-based plan inferencing. the system can perform global reasoning simultaneously across multiple possible worlds, without being forced to extend each world explicitly. the resulting system is useful for such natural language tasks as plan recognition, intentions modeling, and parallel task scheduling.
a new formal tool: functorial variables representing assertions and presuppositions. the language of classical propositional logic is extended by <u>functorial variables</u> as a new syntactical category. functorial variables render to be a possible integrating representation of both assertion and presupposition in one and the same logical formula different from such using classical conjunction.
annotating topological fields and chunks - and revising pos tags at the same time. annotating a corpus of german with chunks, topological fields and clause boundaries is both a goal in itself and a step towards further syntactic annotation. partial annotation can serve as data to test linguistic hypotheses and it can be used as a pre-structuring for further linguistic annotation steps. if, however, the underlying part-of-speech (pos) annotation is imperfect, these errors will be passed on to the subsequent levels of annotation and increase annotation errors on those levels. it is especially damaging for subsequent annotation if pos tags are incorrect which provide the framework of the german sentence by demarcating the topological fields and the clause boundaries (e.g. subordinators and verbs). this paper presents a method to automatically annotate a corpus of german with chunks, topological fields and clause boundaries, and improve tagging accuracy at the same time in order to increase the overall annotation accuracy. tag improvement primarily relies on the linguistic knowledge encoded in the grammar for annotating the topological fields.
identifying terms by their family and friends. multi-word terms are traditionally identified using statistical techniques or, more recently, using hybrid techniques combining statistics with shallow linguistic information. approaches to word sense disambiguation and machine translation have taken advantage of contextual information in a more meaningful way, but terminology has rarely followed suit. we present an approach to term recognition which identifies salient parts of the context and measures their strength of association to relevant candidate terms. the resulting list of ranked terms is shown to improve on that produced by traditional methods, in terms of precision and distribution, while the information acquired in the process can also be used for a variety of other applications, such as disambiguation, lexical tuning and term clustering.
domain dependent natural language understanding. a natural language understanding system for a restricted domain of discourse - thermodynamic exercises at an introductory level - is presented. the system transforms texts into a formal meaning representation language based on cases. the semantical interpretation of sentences and phrases is controlled by case frames formulated around verbs and surface grammatical roles in noun phrases. during the semantical interpretation of a text, semantic constraints may be imposed on elements of the text. each sentence is analysed with respect to context making the system capable of solving anaphoric references such as definite descriptions, pronouns and elliptic constructions.the system has been implemented and succesfully tested on a selection of exercises.
surface analysis of queries directed toward a database. a natural language interface is directed toward the database query languages that access machine stored data. a pattern driven transformation mechanism supports natural language access. a natural language is mapped onto a more formal computer database language. a human-like "understanding" of the query statement is not required. the transformation mechanism is separate from the target database management system. a goal is independence from both domain content and dbms implementation. there is an emphasis on surface over content analysis.two particular questions are at issue. first, the extent to which a natural language interface to a database may operate independent of the subject domain of the database. specifically, the extent to which natural language queries can be evaluated without the use of a query world descriptive reference system. second, the extent to which natural language queries can be analyzed using pattern recognition techniques.
the treatment of scope and negation in rosetta. this paper deals with the treatment of scope and, in particular, negation in rosetta, a machine translation system which translates between dutch, english and spanish (spanish only as a target language). it will be argued that the sov- versus svo-character of a language has important consequences for its possibilities of reflecting scope through word order. a description will be given of the problems that arise translating from one type of language (the sov-language dutch) to the other (the svo-languages english and spanish). the extent to which these problems can be solved will be outlined.the paper has been divided into two main sections. in section one the phenomena are described linguistically, in section two a general idea is given of how these phenomena are dealt with in rosetta.
correcting object-related misconceptions: how should the system respond? this paper describes a computational method for correcting users' misconceptions concerning the objects modelled by a computer system. the method involves classifying object-related misconceptions according to the knowledge-base feature involved in the incorrect information. for each resulting class sub-types are identified, according to the structure of the knowledge base, which indicate what information may be supporting the misconception and therefore what information to include in the response. such a characterization, along with a model of what the user knows, enables the system to reason in a domain-independent way about how best to correct the user.
on a semantic model for multi-lingual paraphrasing. the aim of the present paper is to formalize semantic-directed lexical selection by virtue of frame-based semantic inference capability built in the cfl representation language. the dg model of paraphrasing semantic descriptions can explicate logical process of knowledge-based sentence generation excluding any particular procedures for lexical selection or syntax structure generation. in addition this paper emphasises that this model is basically not dependent on target languages.
analyzing japanese double-subject construction having an adjective predicate. this paper describes a method for analyzing japanese double-subject construction having an adjective predicate based on the valency structure. a simple sentence usually has only one subjective case in most languages. however, many japanese adjectives (and some verbs) can dominate two surface subjective cases within a simple sentence. such sentence structure is called the double-subject construction. this paper classifies the japanese double-subject construction into four types and describes problms arising when analyzing these types using ordinary japanese construction approaches. this paper proposes a method for analyzing a japanese double-subject construction having an adjective predicate in order to overcome the problems described. by applying this method to japanese sentence analysis in. japanese-to-english machine translation systems, translation accuracy can be improved because this method can analyze correctly the double-subject construction.
logic compression of dictionaries for multilingual spelling checkers. to provide practical spelling checkers on micro-computers, good compression algorithms are essential. current techniques used to compress lexicons for indo-european languages provide efficient spelling checker. applying the same methods to languages which have a different morphological system (arabic, turkish,...) gives insufficient results. to get better results, we apply other "logical" compression mechanisms based on the structure of the language itself. experiments with multilingual dictionaries show a significant reduction rate attributable to our logic compression alone and even better results when using our method in conjunction with existing methods.
bunsetsu identification using category-exclusive rules. this paper describes two new bunsetsu identification methods using supervised learning. since japanese syntactic analysis is usually done after bunsetsu identification, bunsetsu identification is important for analyzing japanese sentences. in experiments comparing the four previously available machine-learning methods (decision tree, maximum-entropy method, example-based approach and decision list) and two new methods using category-exclusive rules, the new method using the category-exclusive rules with the highest similarity performed best.
hierarchical orderings of textual units. text representation is a central task for any approach to automatic learning from texts. it requires a format which allows to interrelate texts even if they do not share content words, but deal with similar topics. furthermore, measuring text similarities raises the question of how to organize the resulting clusters. this paper presents cohesion trees (ct) as a data structure for the perspective, hierarchical organization of text corpora. cts operate on alternative text representation models taking lexical organization, quantitative text characteristics, and text structure into account. it is shown that cts realize text linkages which are lexically more homogeneous than those produced by minimal spanning trees.
discontinuities in narratives. this paper is concerned with heuristics for segmenting narratives into units that form the basic elements of discourse representations and the constrain the application of focusing algorithms. the following classes of discontinuities are identified: figure-groud, space, time, perspective, and topic. it is suggested that rhetorical relations between narrative units are macro labels that stand for frequently occurring clusters of discontinuities. heuristics for identifying discontinuities are presented and illustrated in an extended example.
lexical transfer: between a source rock and a hard target. lexical transfer is the point of transition between an unchangeable source text (a rock) and an infinite array of target texts (a hard place to find an acceptable one). the author's coling86 paper (pp. 104--106) described a new methodology for testing lexical transfer in machine translation. this paper reports on the application of that methodology to a test of the dlt system and describes a synchronized bilingual data base by-product. further use of the methodology is encouraged.
interlanguage signs and lexical transfer errors. a theory of interlanguage (il) lexicons is outlined, with emphasis on il lexical entries, based on the hpsg notion of lexical sign. this theory accounts for idiosyncratic or lexical transfer of syntactic subcategorisation and idioms from the first language to the il. it also accounts for developmental stages in il lexical grammar, and grammatical variation in the use of the same lexical item. the theory offers a tool for robust parsing of lexical transfer errors and diagnosis of such errors.
dependency analyzer: a knowledge-based approach to structural disambiguation. to resolve structural ambiguities in syntactic analysis of natural language, which are caused by prepositional phrase attachment, relative clause attachment, and so on, we developed an experimental system called the dependency analyzer. the system uses instances of dependency structures extracted from a terminology dictionary as a knowledge base. structural (attachment) ambiguity is represented by showing that a word has several words as candidate modifiees. the system resolves such ambiguity as follows first, it searches the knowledge base for modification relationships (dependencies) between the word and each of its possible modifiees, then assigns an order of preference to these relationships, and finally selects the most preferable dependency. the knowledge base can be constructed semi-automatically, since the source of knowledge exists in the form of texts, and these sentences can be analyzed by the parser and transformed into dependency structures by the system. we are realizing knowledge bootstrapping by adding the outputs of the system to its knowledge base.
a new method of n-gram statistics for large number of n and automatic extraction of words and phrases from large text data of japanese. in the process of establishing the information theory, c. e. shannon proposed the markov process as a good model to characterize a natural language. the core of this idea is to calculate the frequencies of strings composed of n characters (n-grams), but this statistical analysis of large text data and for a large n has never been carried out because of the memory limitation of computer and the shortage of text data. taking advantage of the recent powerful computers we developed a new algorithm of n-grams of large text data for arbitrary large n and calculated successfully, within relatively short time, n-grams of some japanese text data containing between two and thirty million characters. from this experiment it became clear that the automatic extraction or determination of words, compound words and collocations is possible by mutually comparing n-gram statistics for different values of n.
annotation-based multimedia summarization and translation. this paper presents techniques for multimedia annotation and their application to video summarization and translation. our tool for annotation allows users to easily create annotation including voice transcripts, video scene descriptions, and visual/auditory object descriptions. the module for voice transcription is capable of multilingual spoken language identification and recognition. a video scene description consists of semi-automatically detected keyframes of each scene in a video clip and time codes of scenes. a visual object description is created by tracking and interactive naming of people and objects in video scenes. the text data in the multimedia annotation are syntactically and semantically structured using linguistic annotation. the proposed multimedia summarization works upon a multimodal document that consists of a video, keyframes of scenes, and transcripts of the scenes. the multimedia translation automatically generates several versions of multimedia content in different languages.
an english japanese machine translation system of the titles of scientific and engineering papers. the title sentences of scientific and engineering papers are analyzed by simple parsing strategies, and only eighteen fundamental sentential structures are obtained from ten thousand titles. title sentences of physics and mathematics of some databases in english are translated into japanese with their keywords, author names, journal names and so on by using these fundamental structures. the translation accuracy for the specific areas of physics and mathematics from inspec database was about 93%.
an empirical study on rule granularity and unification interleaving toward an efficient unification-based parsing system. this paper describes an empirical study on the optimal granularity of the phrase structure rules and the optimal strategy for interleaving cfg parsing with unification in order to implement an efficient unification-based parsing system. we claim that using "medium-grained" cfg phrase structure rules, which balance the computational cost of cfg parsing and unification, are a cost-effective solution for making unification-based grammar both efficient and easy to maintain. we also claim that "late unification", which delays unification until a complete cfg parse is found, saves unnecessary copies of dags for irrelevant subparses and improves performance significantly. the effectiveness of these methods was proved in an extensive experiment. the results show that, on average, the proposed system parses 3.5 times faster than our previous one. the grammar and the parser described in this paper are fully implemented and used as the japanese analysis module in sl-trans, the speech-to-speech translation system of atr.
a stochastic japanese morphological analyzer using a forward-dp backward-a* n-best search algorithm. we present a novel method for segmenting the input sentence into words and assigning parts of speech to the words. it consists of a statistical language model and an efficient two-pass n-best search algorithm. the algorithm does not require delimiters between words. thus it is suitable for written japanese. the proposed japanese morphological analyzer achieved 95.1% recall and 94.6% precision for open text when it was trained and tested on the atr corpus.
context-based spelling correction for japanese ocr. we present a novel spelling correction method for those languages that have no delimiter between words, such as japanese, chinese, and thai. it consists of an approximate word matching method and an n-best word segmentation algorithm using a statistical language model. for ocr errors, the proposed word-based correction method outperforms the conventional character-based correction method. when the baseline character recognition accuracy is 90%, it achieves 96.0% character recognition accuracy and 96.3% word segmentation accuracy, while the character recognition accuracy of character-based correction is 93.3%.
zero pronouns as experiencer in japanese discourse. the process of finding the antecedent of zero pronoun, that is indispensable to japanese language understanding, is the topic of this paper. here we mainly concern with discourses comprising two sentences that are in a subordinate relation, especially one of them describes the agent's volitional action and the other describes the reason of the action. we propose basically two new principles: (1) the agent of an action should experience a certain psychological reason, (2) predicates reporting someone's psychological state are categorized into 1) weakly or 2) strongly bound to the expected point of view. combination of these principles accounts for some problematic japanese zero anaphora, which cannot be accounted for by the theories so far proposed.
detecting errors in corpora using support vector machines. while the corpus-based research relies on human annotated corpora, it is often said that a non-negligible amount of errors remain even in frequently used corpora such as penn treebank. detection of errors in annotated corpora is important for corpus-based natural language processing. in this paper, we propose a method to detect errors in corpora using support vector machines (svms). this method is based on the idea of extracting exceptional elements that violate consistency. we propose a method of using svms to assign a weight to each element and to find errors in a pos tagged corpus. we apply the method to english and japanese pos-tagged corpora and achieve high precision in detecting errors.
a parser based on connectionist model. this paper proposes a parser based fully upon the connectionist model(called "cm parser" here after). in order to realize the cm parser, we use sigma-pi-units to implement a constraint of grammatical category order or word order, and a copy mechanism of sub-parse trees. further more, we suppose there exist weak suppressive connection links between every pair of cm units. by these suppressive links, our cm parser explains why garden path sentences and/or deeply nested sentences are hard to recognize. our cm parser also explains the preference principles for syntactically ambiguous sentences.
semantics of complex sentences in japanese. the important part of semantics of complex sentence is captured as relations among semantic roles in subordinate and main clause respectively. however if there can be relations between every pair of semantic roles, the amount of computation to identify the relations that hold in the given sentence is extremely large. in this paper, for semantics of japanese complex sentence, we introduce new pragmatic roles called observer and molivated respectively to bridge sementic roles of subordinate and those of main clauses. by these new roles constraints on the relations among semantic/pragmatic roles are known to be almost local within subordinate or main clause. in other words, as for the semantics of the whole complex sentence, the only role we should deal with is a molivated.
anaphora resolution of japanese zero pronouns with deictic reference. this paper proposes a method to resolve the reference of deictic japanese zero pronouns which can be implemented in a practical machine translation system. this method focuses on semantic and pragmatic constraints such as semantic constraints on cases, modal expressions, verbal semantic attributes and conjunctions to determine the deictic refernce of japanese zero pronouns. this method is highly effective because the volume of knowledge that must be prepared before-hand is not very large and its precision of resolution is good. this method was implemented in the japanese-to-english machine translation system, alt-j/e. according to a window test for 175 zero pronouns with deictic referent in a sentence set for the evaluation of japanese-to-english machine translation systems, all of zero pronouns could be resolved consistently and correctly.
a system of verbal semantic attributes focused on the syntactic correspondence between japanese and english. this paper proposes a system of 97 verbal semantic attributes for japanese verbs which considers both dynamic characteristics and the relationship of verbs to cases. these attribute values are used to disambiguate the meanings of all japanese and english pattern pairs in a japanese to english transfer pattern dictionary consisting of 15,000 pairs of japanese valence patterns and equivalent english syntactic structures.
language model adaptation with additional text generated by machine translation. statistical language modeling requires a large corpus for the application domain. when a large corpus is not available, the language model adaptation technique has often been used in the speech recognition research domain. this adaptation needs only a small corpus of the application domain (the "target corpus") and the corpus should be written in the language of the model. however, it is sometimes difficult to collect even a small corpus, especially of spoken language, due to its high cost. to address this problem, this paper proposes a novel scheme that generates a small target corpus in the language of the model by machine translation of the target corpus in another language. as information about adjacent words, which is necessary for a statistical language model, is stored in the translation knowledge, it can be extracted by machine translation and used for adaptation. experiments showed that the language model improvement was about half of that which was obtained with a human collected corpus, and this provided some initial proof of the concept experiments.
neural network approach to word category prediction for english texts. word category prediction is used to implement an accurate word recognition system. traditional statistical approaches require considerable training data to estimate the probabilities of word sequences, and many parameters to memorize probabilities. to solve this problem, netgram, which is the neural network for word category prediction, is proposed. training results show that the performance of the netgram is comparable to that of the statistical model although the netgram requires fewer parameters than the statistical model. also the netgram performs effectively for unknown data, i.e., the netgram interpolates sparse training data. results of analyzing the hidden layer show that the word categories are classified into linguistically significant groups. the results of applying the netgram to hmm english word recognition show that the netgram improves the word recognition rate from 81.0% to 86.9%
extraction of semantic information from an ordinary english dictionary and its evaluation. the automatic extraction of semantic information especially semantic relationships between words, from an odinary english dictionary is described. for the extraction, the magnetic tape version of ldoce (longman dictionary of contemporary english, 1978 edition) is loaded into a relational database system. developed extraction programs analyze a definition sentence in ldoce with a pattern matching based algorithm. since this algorithm is not perfect, the result of the extraction has been compared with semantic information (semantic markers) which the magnetic tape version of ldoce contains. the result of comparison is also discussed for evaluating the reliability of such an automatic extraction.
grammar writing system (grade) of mu-machine translation project and its characteristics. a powerful grammar writing system has been developed. this grammar writing system is called grade (grammar describer). grade allows a grammar writer to write grammars including analysis, transfer, and generation using the same expression. grade has powerful grammar writing facility. grade allows a grammar writer to control the process of a machine translation. grade also has a function to use grammatical rules written in a word dictionary. grade has been used for more than a year as the software of the machine translation project from japanese into english, which is supported by the japanese government and called mu-project.
taking account of the user's view in 3d multimodal instruction dialogue. while recent advancements in virtual reality technology have created a rich communication interface linking humans and computers, there has been little work on building dialogue systems for 3d virtual worlds. this paper proposes a method for altering the instruction dialogue to match the user's view in a virtual environment. we illustrate the method with the system mid-3d, which interactively instructs the user on dismantling some parts of a car. first, in order to change the content of the instruction dialogue to match the user's view, we extend the refinement-driven planning algorithm by using the user's view as a plan constraint. second, to manage the dialogue smoothly, the system keeps track of the user's viewpoint as part of the dialogue state and uses this information for coping with interruptive subdialogues. these mechanisms enable mid-3d to set instruction dialogues in an incremental way; it takes account of the user's view even when it changes frequently.
a grammar and a parser for spontaneous speech. this paper classifies distinctive phenomena occurring in japanese spontaneous speech, and proposes a grammar and processing techniques for handling them. parsers using a grammar for written sentences cannot deal with spontaneous speech because in spontaneous speech there are phenomena that do not occur in written sentences. a grammar based on analysis of transcripts of dialogues was therefore developed. it has two distinctive features: it uses short units as input units instead of using sentences in grammars for written sentences, and it covers utterances including phrases peculiar to spontaneous speech. since the grammar is an augmentation of a grammar for written sentences, it can also be used to analyze complex utterances. incorporating the grammar into the distributed natural language processing model described elsewhere enables the handling of utterances including variety of phenomena peculiar to spontaneous speech.
topic detection based on dialogue history. in this paper, we propose a topic detection method using a dialogue history for a speech translator. the method uses a k-nearest neighbor method for the algorithm, automatically clusters target topics into smaller topics grouped by similarity, and incorporates dialogue history weighted in terms of time to detect and track topics on spoken phrases. from the evaluation of detection performance using test data comprised of realistic spoken dialogue, the method has shown to perform better with clustering incorporated, and when combined with dialogue history of three sentences, gives detection accuracy of 72.1%.
content-oriented categorization of document images. we have developed a technique that categorizes document images based on their content. unlike conventional methods that use optical character recognition (ocr), we convert document images into word shape takens, a shape-based representation of words. because we have only to recognize simple graphical features from image, this process is much faster than ocr. although the mapping between word shape tokens and words is one-to-many, they are a rich source of information for content characterization. using a vector space classifier with a scanned document image database, we show that the word shape token-based approach is quite adequate for content-oriented categorization in terms of accuracy compared with conventional ocr-based approaches.
error-tolerant tree matching. this paper presents an efficient algorithm for retrieving from a database of trees, all trees that match a given query tree approximately, that is, within a certain error tolerance. it has natural language processing applications in searching for matches in example-based translation systems, and retrieval from lexical databases containing entries of complex feature structures. the algorithm has been implemented on sparcstations, and for large randomly generated synthetic tree databases (some having tens of thousands of trees) it can associatively search for trees with a small error, in a matter of tenths of a second to few seconds.
a constraint-based case frame lexicon. we present a constraint-based case frame lexicon architecture for bi-directional mapping between a syntactic case frame and a semantic frame. the lexicon uses a semantic sense as the basic unit and employs a multi-tiered constraint structure for the resolution of syntactic information into the appropriate senses and/or idiomatic usage. valency changing transformations such as morphologically marked passivized or causativized forms are handled via lexical rules that manipulate case frames templates. the system has been implemented in a typed-feature system and applied to turkish.
interaction with a limited object domain - zapsib project. the report presents the basic principles of the zapsib project aimed at the development of a modular series of linguistic processors designed for natural language (nl) interaction with applied data bases. the general structure of the zapsib processors and functions of the main modules are discussed, as well as technology of the project including problem of processors adaptation to an object domain of the interaction.
the knowledge representation for a story understanding and simulation system. there exist many difficult problems to understand a situation and an event described in sentences or a story. one of them is to treat with more than one subject and their relations. another is the comprehension of movement of the subjects and their effects to the others. in this pater, micro-actor is used as the knowledge representation in which such the problems mentioned above are solved. the micro-actor is an artificial intelligence module for knowledge representation, which is realized hewitt's actor concept.a large problem is often solved by a group of specialists. each specialist has his own knowledge and technique. a specialist can accomplish independently a small work communicating with the others. the specialist is implemented in the form of micro-actor on a computer. the micro-actor is independent of the others, and communicating with the others using one kind of action: sending message to another micro-actor.we discuss the following four problems to understand stories and the approaches to them: (1) depth of understanding sentences to comprehend a story, (2) a method to deal with an event which happens on the specific condition, (3) synchronization of the events which occur at same time and (4) treatment of the event which involves more than one object.
robust method of pronoun resolution using full-text information. a consistent text contains rich information for resolving ambiguities within its sentences. even simple syntactic information such as word occurrence and collocation patterns, which can be extracted from the text without deep discourse analysis, improves the accuracy of sentence analysis. pronoun resolution is a typical proceeding that utilizes this information. through the use of this information, along with information on the syntactic position of each candidate, 93.8% of pronoun references were resolved correctly in an experiment on computer manuals.
full-text processing: improving a practical nlp system based on surface information within the context. rich information for resolving ambiguities in sentence analysis, including various context-dependent problems, can be obtained by analyzing a simple set of parsed trees of each sentence in a text without constructing a precise model of the context through deep semantic analysis. thus, processing a group of sentences together makes it possible to improve the accuracy of a practical natural language processing (nlp) system such as a machine translation system. in this paper, we describe a simple context model consisting of parsed trees of each sentence in a text, and its effectiveness for handling various problems in nlp such as the resolution of structural ambiguities, pronoun referents, and the focus of focusing subjects (e.g. also and only), as well as for adding supplementary phrases to some elliptical sentences.
a new parallel algorithm for generalized lr parsing. tomita's parsing algorithm [tomita 86], which adapted the lr parsing algorithm to context free grammars, makes use of a breadth-first strategy to handl lr table conflicts. as the breadth-first strategy is compatible with parallel processing, we can easily develop a parallel generalized lr parser based on tomita's algorithm [tanaka 89]. however, there is a problem in that this algorithm synchronizes parsing processes on each shift action for the same input word to merge many stacks into graph structured stacks (gss). in other words, a process that has completed a shift action must wait until all other processes have ended theirs --- a strategy that reduces parallel performance. we have developed a new parallel parsing algorithm that does not need to wait for shift actions before merging many stacks, using stream communication of a concurrent logic programming language called ghc [ueda 85]. thus we obtain a parallel generalized lr parser implemented in ghc.
the morphological analysis of bahasa malaysia. this paper describes a model for the automated morphological analysis of bahasa malaysia (the malay language) via the atef system, a component of the mechanical translation system known as ariane, which was developed by g.e.t.a. at grenoble. this model serves two purposes, that is, to test the capability of handling bahasa malaysia morphological analysis using atef and also to provide a first workign model.
the kant system: fast, accurate, high-quality translation in practical domains. knowledge-based interlingual machine translation systems produce semantically accurate translations, but typically require massive knowledge acquisition. ongoing research and development at the center for machine translation has focussed on reducing this requirement to produce large-scale practical applications of knowledge-based mt. this paper describes kant, the first system to combine principled source language design, semi-automated knowledge acquisition, and knowledge compilation techniques to produce fast, high-quality translation to multiple languages.
semantic and syntactic aspects of score function. in a machine translation system (mts), the number of possible analyses for a given sentence is largely due to the ambiguous characteristics of the source language. in this paper, a mechanism, called "score function", is proposed for measuring the "quality" of the ambiguous syntax trees such that the one that best fits interpretation by human is selected. it is featured by incorporating the objectiveness of the probability theory and the subjective expertise of linguists. the underlying uncertainty that is fundamental to linguistic knowledge is also allowed to be incorporated into this system. this feature proposes an easy resolution to select the best syntax tree and provides some strategic advantages for scored parsing. the linguists can also be relieved of the necessity to describe the language in strictly "correct" linguistic rules, which, if not impossible, is a very hard task.
two-way finite automata and dependency grammar: a parsing method for inflectional free word order languages. this paper presents a parser of an inflectional free word order language, namely finnish. two-way finite automata are used to specify a functional dependency grammar and to actually parse finnish sentences. each automaton gives a functional description of a dependency structure within a constituent. dynamic local control of the parser is realized by augmenting the automata with simple operations to make the automata, associated with the words of an input sentence, activate one another.
tools for extracting and structuring knowledge from texts. we demonstrate an approach and an accompanying unix toolbox for performing various kinds of knowledge extractions and structuring. the goal is to "practically" enhance the productivity while constructing resources for nlp systems on the basis of large corpora of technical texts., users are lexicon/grammar builders, terminologists and knowledge engineers. we stay open to already explored methods in this or neighbouring activities but put a greater stress on the use of linguistic knowledge. the originality of the work presented here lies in the scope of applications addressed and in the degree of use of linguistic knowledge.
querying temporal databases using controlled natural language. recent years have shown a surge in interest in temporal database systems, which allow users to store time-dependent information. we present a novel controlled natural language interface to temporal databases, based on translating natural language questions into sql/temporal, a temporal database query language. the syntactic analysis is done using the type-logical grammar framework, highlighting its utility not only as a theoretical framework but also as a practical tool. the semantic analysis is done using a novel theory of the semantics of temporal questions, focusing on the role of temporal preposition phrases rather than the more traditional focus on tense and aspect. our translation method is considerably simpler than previous attempts in this direction. we present a prototype software implementation.
an english-korean transliteration model using pronunciation and contextual rules. there is increasing concern about english-korean (e-k) transliteration recently. in the previous works, direct converting methods from english alphabets to korean alphabets were a main research topic. in this paper, we present an e-k transliteration model using pronunciation and contextual rules. unlike the previous works, our method uses phonetic information such as phoneme and its context. we also use word formation information such as english words of greek origin, with them, our method shows significant performance increase about 31% in word accuracy.
glosser-rug: in support of reading. this paper reports on ongoing work on a call system to facilitate foreign language learning: glosser-rug. the system is particularly dependent on advanced morphological analysis. following a brief introduction to the project, the paper describes the architecture of glosser-rug. then we describe in detail the main components/modules that are part of the implemented prototype. finally, implementation issues and details involving the user interfaces of the tool are discussed. we outline the design of an integrated system to support the reading of french text by dutch speakers.
restricted parallelism in object-oriented lexical parsing. we present an approach to parallel natural language parsing which is based on a concurrent, object-oriented model of computation. a depth-first, yet incomplete parsing algorithm for a dependency grammar is specified and several restrictions on the degree of its parallelization are discussed.
syntactic functions in gpsg. this paper motivates and proposes adding a new feature of <u>syntactic function</u> to the feature system of gpsg. later, it shows its necessity in number of syntactic constructs, such as passivization, extraposition, coordination etc. but adding such feature is not understood as a mere technicality, and thus some implications for the explanatory power of the theory are also discussed.
a head-driven approach to incremental and parallel generation of syntactic structures. this paper describes the construction of syntactic structures within an incremental multi-level and parallel generation system. incremental and parallel generation imposes special requirements upon syntactic description and processing. a head-driven grammar represented in a unification-based formalism is introduced which satisfies these demands. furthermore the basic mechanisms for the parallel processing of syntactic segments are presented.
simple parser for an hpsg-style grammar implemented in prolog. this paper describes basic ideas of a parser for hpsg style grammars without lp component. the parser works bottom-up using the left corner method and a chart for improving efficiency. attention is paid to the format of grammar rules as required by the parser, to the possibilities of direct implementation of principles of the grammar as well as to solutions of problems connected with storing partly specified categories in the chart.
self-monitoring with reversible grammars. we describe a method and its implementation for self-monitoring during natural language generation. in situations of communication where the generation of ambiguous utterances should be avoided our method is able to compute an unambiguous utterance for a given semantic input. the proposed method is based on a very strict integration of parsing and generation. during the monitored generation step, a previously generated (possibly) ambiguous utterance is parsed and the obtained alternative derivation trees are used as a 'guide' for re-generating the utterance. to achieve such an integrated approach the underlying grammar must be reversible.
the proper treatment of word order in hpsg. this paper describes a possibility of expressing ordering constraints among non-sister constituents in binary branching syntactic structures on a local basis, supported by viewing the binary branching structure as a list (rather than a tree) of constitutents within hpsg-style grammars. the core idea of such a description of ordering is constituted by creating a type lattice for lists. the possibilities of expressing different approaches to word order in the framework are briefly discussed, exemplified and compared to other methods.
towards convenient bi-directional grammar formalisms. this paper discusses the advantages for practical bi-directional grammars of combining a lexical focus with the gpsg-originated principle of immediate-dominance/linear-precedence (id/lp) rule partitioning. it also outlines an implementation approach following these guidelines. the approach is inspired by slot grammar, with additions including more explicit mappings between surface and internal representations, and preferential constituent ordering rules.
identifying concepts across languages: a first step towards a corpus-based approach to automatic ontology alignment. the growing importance of multilingual information retrieval and machine translation has made multilingual ontologies an extremely valuable resource. since the construction of an ontology from scratch is a very expensive and time consuming undertaking, it is attractive to consider ways of automatically aligning monolingual ontologies, which already exist for many of the world's major languages.
list automata with syntactically structured output. a new type of abstract automaton is introduced, and both formal and linguistic implications are discussed, most importantly a new possibility of proving certain formal properties of (natural) languages and their grammars (such as context-freeness) and of refinement of the chomsky hierarchy.
devied and valency-oriented parsing in speech understanding. a parsing scheme for spoken utterances is proposed that deviates from traditional 'one go' left to right sentence parsing in that it devides the parsing process first into two separate parallel processes. verbal constituents and nominal phrases (including prepositonal phrases) are treated seperately and only brought together in an utterance parser. this allows especially the utterance parser to draw on valency information right from beginning when amalgamating the nominal constituents to the verbal core by means of binary sentence rules. the paper also discusses problems of representing the valency information in case-frames arising in a spoken language environment.
notions of correctness when evaluating protein name taggers. this paper introduces four different notions of correctness to be used when measuring the performance of protein name taggers, each of which reflects certain characteristics of the tagger under evaluation. the discussion regarding the different notions is centered around the evaluation of two protein name taggers; yapex, developed by the authors, and kex developed by fukuda et al. (1998). for the purpose of illustrating the difference between the ways of evaluation, both taggers are applied to a test corpus of 101 medline abstracts in which all occurrences of protein names have been marked up by domain experts.
improving smt quality with morpho-syntactic analysis. in the framework of statistical machine translation (smt), correspondences between the words in the source and the target language are learned from bilingual corpora on the basis of so-called alignment models. many of the statistical systems use little or no linguistic knowledge to structure the underlying models. in this paper we argue that training data is typically not large enough to sufficiently represent the range of different phenomena in natural languages and that smt can take advantage of the explicit introduction of some knowledge about the languages under consideration. the improvement of the translation results is demonstrated on two different german-english corpora.
abstract generation based on rhetorical structure extraction. we have developed an automatic abstract generation system for japanese expository writings based on rhetorical structure extraction. the system first extracts the rhetorical structure, the compound of the rhetorical relations between sentences, and then cuts out less important parts in the extracted structure to generate an abstract of the desired length.evaluation of the generated abstract showed that it contains at maximum 74% of the most important sentences of the original text. the system is now utilized as a text browser for a prototypical interactive document retrieval system.
the procedure to construct a word predictor in a speech understanding system from a task-specific grammar defined in a cfg or a dcg. this paper describes a method for converting a task-dependent grammar into a word predictor of a speech understanding system. since the word prediction is a top-down operation, left recursive rules induces an infinite looping. we have solved this problem by applying an algorithm for bottom-up parsing.
termservice - an automated system for terminology services. the paper discusses the background, use environments and content of an automated system for multilingual terminology services, developed at the laboratory of mathematical linguistics of the institute of mathematics with computer centre affiliated to the bulgarian academy of sciences. particular emphasis is given to terminology acquistition and facilities for automated lexicography.
patrans- a patent translation system. this paper describes patrans-a fully automatic production mt system designed for producing raw translations of patent texts from english into danish. first we describe the backbone of the system: the eurotra research project and prototype. then we give an overview of the translation process and the basic functionality of patrans, and finally we describe some recent extensions for improving processing efficiency and the translation quality of unexpected input encountered in real-life texts.
lenient default unification for robust processing within unification based grammar formalisms. this paper describes new default unification, lenient default unification. it works efficiently, and gives more informative results because it maximizes the amount of information in the result, while other default unification maximizes it in the default. we also describe robust processing within the framework of hpsg. we extract grammar rules from the results of robust parsing using lenient default unification. the results of a series of experiments show that parsing with the extracted rules works robustly, and the coverage of a manually-developed hpsg grammar for penn treebank was greatly increased with a little overgeneration.
estimation of stochastic attribute-value grammars using an informative sample. we argue that some of the computational complexity associated with estimation of stochastic attribute value grammars can be reduced by training upon an informative subset of the full training set. results using the parsed wall street journal corpus show that in some circumstances, it is possible to obtain better estimation results using an informative sample than when training upon all the available material. further experimentation demonstrates that with unlexicalised models, a gaussian prior can reduce overfitting. however, when models are lexicalised and contain overlapping features, overfitting does not seem to be a problem, and a gaussian prior makes minimal difference to performance. our approach is applicable for situations when there are an infeasibly large number of parses in the training set, or else for when recovery of these parses from a packed representation is itself computationally expensive.
an indexing scheme for typed feature structures. this paper describes an indexing substrate for typed feature structures (istfs), which is an efficient retrieval engine for typed feature structures. given a set of typed feature structures, the istfs efficiently retrieves its subset whose elements are unifiable or in a subsumption relation with a query feature structure. the efficiency of the istfs is achieved by calculating a unifiability checking table prior to retrieval and finding the best index paths dynamically.
machine translation systems and computer dictionaries in the information service. ways of their development and operation. the paper outlines fields of application of machine translation systems and computer dictionaries in technical translation as well as possible ways of development and operation of computer dictionaries. interaction between linguists and commercial machine translation system is described.
interruptable transition networks. a specialized transition network mechanism, the interruptable transition network (itn) is used to perform the last of three stages in a multiprocessor syntactic parser. this approach can be seen as an exercise in implementing a parsing procedure of the active chart parser family.
evaluation metrics for knowledge-based machine translation. a methodology is presented for component-based machine translation (mt) evaluation through causal error analysis to complement existing global evaluation methods. this methodology is particularly appropriate for knowledge-based machine translation (kbmt) systems. after a discussion of mt evaluation criteria and the particular evaluation metrics proposed for kbmt, we apply this methodology to a large-scale application of the kant machine translation system, and present some sample results.
topic/focus articulation and intensional logic. a semantic analysis of topic and focus as two parts of tectogrammatical representation by means of transparent intensional logic (til) is presented. it is pointed out that two sentences (more precisely, their tectogrammatical representations) differing just in the topic/focus articulation (tfa) denote different propositions, i.e. that tfa has an effect upon the semantic content of the sentence. an informal short description of an algorithm handling the tfa in the translation of tectogrammatical representations into the constructions of til is added. the tfa algoriths divides a representation into two parts corresponding to the topic and focus; every part is analyzed (translated) in isolation and then the resulting construction is put together. the til construction discussed here reflect the scope of negation and some of the presuppositions observed.
a polynomial - order algorithm for optimal phrase sequence selection from a phrase lattice and its parallel layered implementation. this paper deals with a problem of selecting an optimal phrase sequence from a phrase lattice, which is often encountered in language processing such as word processing and post-processing for speech recognition. the problem is formulated as one of combinatorial optimization and a polynomial order algorithm is derived. this algorithm finds an optimal phrase sequence and its dependency structure simultaneously, and is therefore particularly suited for an interface between speech recognition and various language processing. what the algorithm does is numerical optimization rather than symbolic operation unlike conventional parsers. a parallel and layered structure to implement the algorithm is also presented. although the language taken up here is japanese, the algorithm can be extended to cover a wider family of languages.
measuring semantic coverage. the development of natural language processing systems is currently driven to a large extent by measures of knowledge-base size and coverage of individual phenomena relative to a corpus. while these measures have led to significant advances for knowledge-lean applications, they do not adequately motivate progress in computational semantics leading to the development of large-scale, general purpose nlp systems. in this article, we argue that depth of semantic representation is essential for covering a broad range of phenomena in the computational treatment of language and propose depth as an important additional dimension for measuring the semantic coverage of nlp systems. we propose an operationalization of this measure and show how to characterize an nlp system along the dimensions of size, corpus coverage, and depth. the proposed framework is illustrated using several prominent nlp systems. we hope the preliminary proposals made in this article will lead to prolonged debates in the field and will continue to be refined.
broad coverage automatic morphological segmentation of german words. a system for the automatic segmentation of german words into morphs was developed. the main linguistic knowledge sources used by the system are a word syntax and a morph dictionary. the syntax is written in the formalism of right linear regular grammars and comprises approximately 1, 400 rules describing the set of those sequences of morph classes which underlie syntactically well formed words. the morph dictionary contains almost 11, 000 morphs. each morph is assigned to up to 6 morph classes. - statistical evaluations with 6000 text words showed that more than 99% of the segmented words got a correct segmentation.
a framework for lexical selection in natural language generation. this paper describes a procedure for lexical selection of open-class lexical items in a natural language generation system. an optimum lexical selection module must be able to make realization decisions under varying contextual circumstances. first, it must be able to operate without the influence of context, based on meaning correspondences between elements of conceptual input and the lexical inventory of the target language. second, it must be able to use contextual constraints, as supported by collocational information in the generation lexicon. third, there must be an option of realizing input representations pronominally or through definite descriptions. finally, there must also be an option of using elliptical constactions. the nature of background knowledge and the algorithm we suggest for this task are described. the lexical selection procedure is a part of a comprehensive generation system, diogenes.
pos tagging using relaxation labelling. relaxation labelling is an optimization technique used in many fields to solve contraint satisfcation problems. the algorithm finds a combination of values for a set of variables such that satisfies -to the maximum possible degree- a set of given constraints. this paper describes some experiments performed applying it to pos tagging, and the results obtained. it also ponders the possibility of applying it to word sense disambiguation.
a metric for computational analysis of meaning: toward an applied theory of linguistic semantics. a metric for assessing the complexity of semantic (and pragmatic) analysis in natural language processing is proposed as part of a general applied theory of linguistic semantics for nlp. the theory is intended as a complete projection of linguistic semantics onto nlp and is designed as an exhaustive list of possible choices among strategies of semantic analysis at each level, from the word to the entire text. the alternatives are summarized in a chart, which can be completed for each existing or projected nlp system. the remaining components of the applied theory are also outlined.
referential properties of generic terms denoting things and situations. generic terms can be divided into two referentially different groups. generic term of the first group is a name (or a definite description) of the corresponding class of objects (of <u>jaguars in south america are extinct; the whale is a mammal</u>). as for generic terms of the second group, we propose to treat them as general terms (in the sense of w. o. quine): they are considered to be referentially incomplete expressions which, when constituting the theme of a generic proposition, undergo quantification which is expressed, explicitly or implicitly, inside the verb phrase.
on knowledge-based machine translation. this paper describes the design of the knowledge representation medium used for representing concepts and assertions, respectively, in a subworld chosen for a knowledge-based machine translation system. this design is used in the translator machine translation project. the knowledge representation language, or interlingua, has two components, dil and til. dil stands for 'dictionary of interlingua' and descibes the semantics of a subworld. til stands for 'text of interlingua' and is responsible for producing an interlingua text, which represents the meaning of an input text in the terms of the interlingua. we maintain that involved analysis of various types of linguistic and encyclopaedic meaning is necessary for the task of automatic translation. the mechanisms for extracting and manipulating and reproducing the meaning of texts will be reported in detail elsewhere. the linguistic (including the syntactic) knowledge about source and target languages is used by the mechanisms that translate texts into and from the interlingua. since interlingua is an artificial language, we can (and do, through til) control the syntax and semantics of the allowed interlingua elements. the interlingua suggested for translator has a broader coverage than other knowledge representation schemata for natural language. it involves the knowledge about discourse, speech acts, focus, time, space and other facets of the overall meaning of texts.
predicting co-occurrence restrictions by using semantic classifications in the lexicon. in this paper we investigate general principles of constructing semantic classifications that yield useful predictions concerning combinatory options of words. several semantic classes of russian words are discussed, implemented in an expert system named "lexicographer", the system being conceived as an aid both in the area of natural language processing and in traditional lexicography. semantic features proposed regulate co-occurence of verbs with their non-obligatory dependents - such as modifiers of place or time; instrumental and benefactive objects and the like.
hierarchical meaning representation and analysis of natural language documents. this paper attempts to systematize natural language analysis process by (1) use of a partitioned semantic network formalism as the meaning representation and (2) stepwise translation based on montague grammar. the meaning representation is obtained in two steps. the first step translates natural language into logical expression. the second step interprets logical expression to generate network structure. we have implemented set of programs which performs the stepwise translation. experiments are in progress for machine translation and question answering.
semantic dictionary viewed as a lexical database. in this paper an expert system is described which is called lexicographer and which aims at supplying the user with diverse information about russian words, including bibliographic information concerning individual lexical items. it is supposed that the system may be of use for a practical computational linguist and at the same time will serve as an instrument of linguistic research.
an english-japanese machine translation system based on formal semantics of natural language. this paper proposes a new model of machine translation. in this model, the lambda formula obtained from the syntactic and semantic analysis of a source language sentence is viewed as a target language generating function and the target language sentence is obtained as a result of evaluating the formula by functional application or &lambda;-calculus. this model provides a systematic and powerful way of incorporating human knowledge on the languages. a prototype is constructed on the lisp system. the performance was tested for four sample texts taken from existing technical reports and computer manuals.
combining functionality and object-orientedness for natural language processing. this paper proposes a method for organizing linguistic knowledge in both systematic and flexible fashion. we introduce a purely applicative language (pal) as an intermediate representation and an object-oriented computation mechanism for its interpretation. pal enables the establishment of a principled and well-constrained method of interaction among lexicon-oriented linguistic modules. the object-oriented computation mechanism provides a flexible means of abstracting modules and sharing common knowledge.
random generation of czech sentences. the experiments testing the theoretical adequacy and the practical usefulness of the functional generative description (fgd) are described. the fgd consists of a generative component, which, in the experimental version, has the shape of a context-free grammar combined with elements of dependency approach, and the other components having the form of pushdown store automata. the latter components have a transductive role, transducing the semantic (tectogrammatical) representations of sentences to the lower levels of the language system. the transduction is articulated into several steps corresponding more or less to the levels of language system (surface syntax, morphemics, morphophonemics, phonemics, or, as the case may be, graphemics) postulated in european structural linguistics. the theoretical and practical qualities of the system are evaluated.
surface and deep cases. in this paper we show the relation between the "surface (morphological) cases" and "deep cases" (participants), and the possible way to automate the creation of a syntactic dictionary provided with frames containing information about deep cases and their morphemic counterparts of particular lexical items (czech verbs).
maintaining consistency and plausibility in integrated natural language understanding. in this paper, we present an inference mechanism called the integrated parsing engine which provides a uniform abductive inference mechanism for natural language understanding. it can (1) make plausible assumptions, (2) reason with multiple alternatives, (3) switch the search process to the maximally plausible alternative, (4) detect contradiction and tame conclutions which depend on inconsistent assumptions, and (5) update plausibility factor of each belief based on new observations. we demonstrate that a natural language understanding system using the integrated parsing engine as a subsystem can pursue a guided search for most plausible interpretation by making use of syntax, semantics, and contextual information.
experiments with an mt-directed lexical knowledge bank. a crucial test for any mt system is its power to solve <u>lexical ambiguities</u>. the size of the lexicon, its structural principles and the availability of <u>extra-linguistic knowledge</u> are the most important aspects in this respect. this paper outlines the experimental development of the <u>swesil</u> system: a structured lexicon-based word expert system designed to play a pivotal role in the process of <u>distributed language translation</u> (dlt) which is being developed in the netherlands. it presents swesil's organizing principles, gives a short description of the present experimental set-up and shows how swesil is being tested at this moment.
japanese-english translation through internal expressions. this paper describes an approach to japanese-english translation through internal expressions which are similar to those used in our recent approach to english-japanese translation [2]. attention is focused on construction of the internal expressions of japanese sentences based on case structures of predicates and also conversion of the japanese internal expressions to the english ones for generating good english sentences in conventional use. finally, associated with translation, extraction of specified translated information from japanese patent claim sentences is described briefly.
empirical data and automatic analysis. the purpose of the present paper is to show the usefulness of (1) the computer processing of the manifold data of lexicographic works; and (2) the normal and reverse alphabetized concordances compiled on the basis of different texts.
english-japanese translation through case-structure conversion. this paper reports some trials on mechanical translation from english to japanese through a case structure constructed on hornby's verb patterns. though the general theoryof case structures is still at the beginning of study, it provides partial sentential patterns with rough but resonable classification labels. after determination of schematic dependency relations, multi-vocal problems for choosing appropriate equivalents are dissolved using subcategories of terms and cases. case structures of english are transformed into those of japanese if necessary, and from those, japanese sentences are generated by a japanese grammar.
building knowledge bases for the generation of software documentation. automated text generation requires a underlying knowledge base from which to generate, which is often difficult to produce. software documentation is one domain in which parts of this knowledge base may be derived automatically. in this paper, we describe drafter, an authoring support tool for generating usercentred software documentation, and in particular, we describe how parts of its required knowledge base can be obtained automatically.
feedback of correcting information in postediting to a machine translation system. this paper presents an attempt to construct a feedback system pecof which improves a japanese-english machine translation system by feedback of correcting information given by posteditors. pecof analyzes the error-correcting information by using an english-japanese machine translation system which works in the reverse direction to the original mt system, compares the intermediate expressions of the corrected patterns with those of the erroneous parts of the original mt output at every transfer stage and identifies the responsible parts of the original japanese-english mt system. then pecof corrects the irrelevant parts of the database or adds error correcting patterns to a document of postediting to ask users for further examinations for corrections.
automatic glossary extraction: beyond terminology identification. this paper describes a method for automatically extracting domain-specific glossaries from large document collections. we show that, compared with current text analysis methods for extracting technical terminology from text, our extracted glossaries more successfully support applications requiring knowledge of domain concepts. after presenting our methods, we illustrate the output of glossex, our glossary extraction tool, and present an informal evaluation of its performance.
informed parsing for coordination with combinatory categorial grammar. coordination in natural language hampers efficient parsing, especially due to the multiple and mostly unintended candidate conjuncts/disjuncts in a given sentence that shows structural ambiguity. the problem gets more serious in a combinatory categorial grammar framework, which is well known for its competent treatment of coordination, as the flexibility of syntactic analysis often strikes back as spurious ambiguity. we propose to address these ambiguities with predicate argument structures and semantic co-occurrence similarity information, and present encouraging results.
language acquisition as learning. chomsky's proposition that language is handled by a language-specific faculty needs more justification. in language acquisition in particular, it is still in question whether the faculty is necessary or not. we succeeded in explaining one constraint on language acquisition in terms of a general learning mechanism. this paper describes a machine learning system rhea applied to the domain of language acquisition and shows that rhea can learn the tendency which children confronting new words seem to have.
idiosyncratic gap: a tough problem to structure-bound machine translation. current practical machine translation system (mt, in short), which are designed to deal with a huge amount of document, are generally structure-bound. that is, the translation process is done based on the analysis and transformation of the structure of source sentence, not on the understanding and para-phrasing of the meaning of that. but each language has its own syntactic and semantic idiosyncrasy, and on this account, without understanding the total meaning of source sentences it is often difficult for mt to bridge properly the idiosyncratic gap between source- and target- language. a somewhat new method called "cross translation test (ctt, in short)" is presented that reveals the detail of idiosyncratic gap (ig, in short) together with the so-so satisfiable possibility of mt. it is also mentioned the usefulness of sublanguage approach to reducing the ig between source- and target- language.
a proper treatmemt of syntax and semantics in machine translation. a proper treatment of syntax and semantics in machine translation is introduced and discussed from the empirical viewpoint. for english-japanese machine translation, the syntax directed approach is effective where the heuristic parsing model (hpm) and the syntactic role system play important roles. for japanese-english translation, the semantics directed approach is powerful where the conceptual dependency diagram (cdd) and the augmented case marker system (which is a kind of semantic role system) play essential roles. some examples of the difference between japanese sentence structure and english sentence structure, which is vital to machine translation, are also discussed together with various interesting ambiguities.
corpus-based generation of numeral classifier using phrase alignment. a severe problem for nlp applications dealing with multilingual language resources is the acquisition of knowledge that is obligatory in one language but not explicitly expressed in another language. in this paper, we focus on numeral classifiers, which are required in languages like japanese but are usually not explicitly used in languages like english, which don't have such a classifier system.we propose a uniform method to assign the numeral classifiers of languages that have a numeral classifier system to the numerals of non-classifier languages. the omitted classifier information is extracted from a bilingual corpus based on phrasal correspondences in the contexts of the respective sentences.
a heuristic approach to english-into-japanese machine translation. practical machine translation must be considered from a heuristic point of view rather than from a purely rigid analytical linguistic method. an english-into-japanese translation system named athene based on a heuristic parsing model (hpm) has been developed. the experiment shows some advantageous points such as simplification of transforming and generating phase, semilocalization of multiple meaning resolution, and extendability for future grammatical refinement. hpm-base parsing process, parsed tree, grammatical data representation, and translation results are also described.
aspects of pattern-matching in data-oriented parsing. data-oriented parsing (dop) ranks among the best parsing schemes, pairing state-of-the art parsing accuracy to the psycholinguistic insight that larger chunks of syntactic structures are relevant grammatical and probabilistic units. parsing with the dop-model, however, seems to involve a lot of cpu cycles and a considerable amount of double work, brought on by the concept of multiple derivations, which is necessary for probabilistic processing, but which is not convincingly related to a proper linguistic backbone. it is however possible to reinterpret the dop-model as a pattern-matching model, which tries to maximize the size of the substructures that construct the parse, rather than the probability of the parse. by emphasizing this memory-based aspect of the dop-model, it is possible to do away with multiple derivations, opening up possibilities for efficient viterbistyle optimizations, while still retaining acceptable parsing accuracy through enhanced context-sensitivity.
tagging spoken language using written language statistics. this paper reports on two experiments with a probabilistic part-of-speech tagger, trained on a tagged corpus of written swedish, being used to tag a corpus of (transcribed) spoken swedish. the results indicate that with very little adaptations an accuracy rate of 85% can be achieved, with an accuracy rate for known words of 90%. in addition, two different treatments of pauses were explored but with no significant gain in accuracy under either condition.
co-occurrence vectors from corpora vs. distance vectors from dictionaries. a comparison was made of vectors derived by using ordinary co-occurrence statistics from large text corpora and of vectors derived by measuring the interword distances in dictionary definitions. the precision of word sense disambiguation by using co-occurrence vectors from the 1987 wall street journal (20m total words) was higher than that by using distance vectors from the collins english dictionary (60k head words + 1.6m definition words). however, other experimental results suggest that distance vectors contain some different semantic information from co-occurrence vectors.
conceptual analysis of garden-path sentences. by integrating syntactic and semantic processing, our parser (lazy) is able to deterministically parse sentences which syntactically appear to be garden path sentences although native speakers do not need conscious reanalysis to understand them. lazy comprises an extension to conceptual analysis which yields an explicit representation of syntactic information and a flexible interaction between semantic and syntactic knowledge.
automatic semantic sequence extraction from unrestricted non-tagged texts. mophological processing, syntactic parsing and other useful tools have been proposed in the field of natural language processing (nlp). many of those nlp tools take dictionary-based approaches. thus these tools are often not very efficient with texts written in casual wordings or texts which contain many domain-specific terms, because of the lack of vocabulary.in this paper we propose a simple method to obtain domain-specific sequences from unrestricted texts using statistical information only. this method is language-independent.we had experiments on sequence extraction on email texts in japanese, and succeeded in extracting significant semantic sequences in the test corpus. we tried morphological parsing on the test corpus with chasen, a japanese dictionary-based morphological parser, and examined our system's efficiency in extraction of semantic sequences which were not recognized with chasen. our system detected 69.06% of the unknown words correctly.
probabilistic unification-based integration of syntactic and semantic preferences for nominal compounds. in this paper, we describe a probabilistic framework for unification-based grammars that facilitates integrating syntactic and semantic constraints and preferences. we share many of the concerns found in recent work on massively-parallel language interpretation models, although the proposal reflects our belief in the value of a higher-level account that is not stated in terms of distributed computation. we also feel that inadequate learning theories severely limit existing massively-parallel language interpretation models. a learning theory is not only interesting in its own right, but must underlie any quantitative account of language interpretation, because the complexity of interaction between constraints and preferences makes ad hoc trial-and-error strategies for picking numbers infeasible, particularly for semantics in realistically-sized domains.
segmenting sentences into linky strings using d-bigram statistics. it is obvious that segmentation takes an important role in natural language processing(nlp), especially for the languages whose sentences are not easily separated into morphemes. in this study we propose a method of segmenting a sentence. the system described in this paper does not use any grammatical information or knowledge in processing. instead, it uses statistical information drawn from non-tagged corpus of the target language. most of the segmenting systems are to pick out conventional morphemes which is defined for human use. however, we still do not know whether those conventional morphemes are good units for computational processing.in this paper we explain our system's algorithm and its experimental results on japanese, though this system is not designed for a particular language.
a comparison of alignment models for statistical machine translation. in this paper, we present and compare various alignment models for statistical machine translation. we propose to measure the quality of an alignment model using the quality of the viterbi alignment compared to a manually-produced alignment and describe a refined annotation scheme to produce suitable reference alignments. we also compare the impact of different alignment models on the translation quality of a statistical machine translation system.
prepositional phrase attachment through a hybrid disambiguation model. prepositional phrase attachment is a major cause of structural ambiguity in natural language. recent work has been dependent on corpus-based approaches to deal with this problem. however, corpus-based approaches suffer from the sparse-data problem. to cope with this problem, we introduce a hybrid method of integrating corpus-based approach with knowledge-based techniques, using a wide-variety of information that comes from annotated corpora and a machinere-adable dictionary. when the occurrence frequency on the corpora is low, we use preference rules to determine pp attachment based on clues from conceptual information. an experiment has proven that our hybrid method is both effective and applicable in practice.
segmenting a sentence into morpiiemes using statistic information between words. this paper is on dividing non-separated language sentences (whose words are not separated from each other with a space or other separaters) into morphemes using statistical information, not grammatical information which is often used in nlp. in this paper we describe our method and experimental result on japanese and chinese sentences. as will be seen in the body of this paper, the result shows that this system is efficient for most of the sentences.
parsing with look-ahead in real-time on-line translation system. in order to increase parsing efficiency in a real-time on-line translation system interfaced with a keyboard conversation program, we have developed a version of the atn formalism with a look-ahead function. by permitting future input to be scanned, arcs can be reordered or suppressed. various mechanisms utilizing this capability are presented.
taxonomy learning - factoring the structure of a taxonomy into a semantic classification decision. the paper examines different possibilities to take advantage of the taxonomic organization of a thesaurus to improve the accuracy of classifying new words into its classes. the results of the study demonstrate that taxonomic similarity between nearest neighbors, in addition to their distributional similarity to the new word, may be useful evidence on which classification decision can be based.
formal properties of rule orderings in linguistics. the discovery in the late 1960's that standard linguistic theory (of chomsky's <u>aspects</u>) was equivalent in generative power to unrestricted rewrite rules caused linguists to search for a "stronger linguistic metatheory". it seemed to some of these researchers that this meant describing linguistic theory by means of rules which were more restricted than type 0 languages. such a view we call the l-view of constraints on linguistic theory: it advocates constraining the allowable rules in such a way that legitimate grammars can no longer generate arbitrary r.e. sets, but only some subset of them. to other researchers this discovery meant rather that one should place restrictions on linguistic theory so that the kinds of grammars allowed would be limited, regardless of whether such limitations affected the generative power of the theory. we call this the g-view of constraints. the l- and g-views are not equivalent limitations. for example, a g-view limitation on the class of regular grammars that any legitimate grammar be right-embedding is not thereby a l-view limitation, since this does not effect an alteration in generative power of the grammars allowed. the g-view is avowedly psychological; according to it, the point of placing constraints on grammars is to lessen directly the language learner's burden of choosing the correct grammar from all the possible ones. for the l-view, this is a side effect of disallowing whole classes of grammars in the first place.
machine translation by case generalization. case-based machine translation is a promising approach to resolving problems in rule-based machine translation systems, such as difficulties in control of rules and low adaptability to specific domains. we propose a new mechanism for case-based machine translation, in which a large set of cases is generalized into a smaller set of cases by using a thesaurus.
two theories for computing the logical form of mass expressions. there are various difficulties in accomodating the traditional mass/count distinction into a grammar for english which has a goal the production of "logical form" semantic translations of the initial english sentences. the present paper surveys some of these difficulties. one puzzle is whether the distinction is a syntactic one or a semantic one, i.e., whether it is a well-formedness constraint or whether it is a description of the semantic translations produced. another puzzle is whether it should be applied to simple words (as they occur in the lexicon) or whether it should apply only to longer units (such as entire nps). of the wide variety of possible theories, only two seem to produce the required results (having to do with plausible inferences and intuitively satisfying semantic representations). these two theories are developed and compared.
a grammatico-statistical approach to discourse partitioning. the paper presents a new approach to text segmentation - which concerns dividing a text into coherent discourse units. the approach builds on the theory of discourse segment (nomoto and nitta, 1993), incorporating ideas from the research on information retrieval (salton, 1988). a discourse segment has to do with a structure of japanese discourse; it could be thought of as a linguistic unit demarcated by wa, a japanese topic particle, which may extend over several sentences. the segmentation works with discourse segments and makes use of coherence measure based on tf-idf, a standard information retrieval measurement (salton, 1988; hearst, 1993). experiments have been done with a japanese newspaper corpus. it has been found that the present approach is quite successful in recovering articles from the unstructured corpus.
investigating the relationship between word segmentation performance and retrieval performance in chinese ir. it is commonly believed that word segmentation accuracy is monotonically related to retrieval performance in chinese information retrieval. in this paper we show that, for chinese, the relationship between segmentation and retrieval performance is in fact nonmonotonic; that is, at around 70% word segmentation accuracy an over-segmentation phenomenon begins to occur which leads to a reduction in information retrieval performance. we demonstrate this effect by presenting an empirical investigation of information retrieval on chinese trec data, using a wide variety of word segmentation algorithms with word segmentation accuracies ranging from 44% to 95%. it appears that the main reason for the drop in retrieval performance is that correct compounds and collocations are preserved by accurate segmenters, while they are broken up by less accurate (but reasonable) segmenters, to a surprising advantage. this suggests that words themselves might be too broad a notion to conveniently capture the general semantic meaning of chinese text.
an empirical architecture for verb subcategorization frame - a lexicon for a real-world scale japanese-english interlingual mt. the verb subcategorization frame information plays a major role of disambiguations in many nlp applications. japanese, however, imposes difficulties of subcategorizing in part because it allows arbitrary ellipses of case elements. we propose a new type of verb subcategorization frame code set that combines the verb's surface case set and the deep case set, as a solution to the difficulties of empirical researches on japanese. the lexicon developed by this design has comprehensive information on the correspondences between the surface case frame and the deep case frame, and yet restrains the potential combinatorial explosion of the number of verb subcategorization frames by carefully identifying superficially different frames with an idea of alternative case markers and semantic roles, and by introducing the notion of surface case frame permutations. the number of different surface/deep case mapping types is 250, after we completed the new subcategorization frame code development for 30,000 verbs and adjectives.
translation by understanding: a machine translation system lute. this paper presents a linguistic model for language understanding and describes its application to an experimental machine translation system called lute. the language understanding model is an interactive model between the memory structure and a text. the memory structure is hierarchical and represented in a frame-network. linguistic and non-linguistic knowledge is stored and the result of understanding the text is assimilated into the memory structure. the understanding process is interactive in that the text invokes knowledge and the understanding proceduro interprets the text by using that knowledge. a linguistic model, called the extended case structure model, is defined by adopting three kinds of information: structure, relation and concept. these three are used recursively and iteratively as the basis for memory organization. these principles are applied to the design and implementation of the lute which translates japanese into english and vice vorsa.
the semantics of grammar formalisms seen as computer languages. the design, implementation, and use of grammar formalisms for natural language have constituted a major branch of computational linguistics throughout its development. by viewing grammar formalisms as just a special case of computer languages, we can take advantage of the machinery of denotational semantics to provide a precise specification of their meaning. using dana scott's domain theory, we elucidate the nature of the feature systems used in augmented phrase-structure grammar formalisms, in particular those of recent versions of generalized phrase structure grammar, lexical functional grammar and patr-ii, and provide a denotational semantics for a simple grammar formalism. we find that the mathematical structures developed for this purpose contain an operation of feature generalization, not available in those grammar formalisms, that can be used to give a partial account of the effect of coordination on syntactic features.
reversible unification based machine translation. in this paper it will be shown how unification grammars can be used to build a reversible machine translation system.unification grammars are often used to define the relation between strings and meaning representations in a declarative way. such grammars are sometimes used in a bidirectional way, thus the same grammar is used for both parsing and generation. in this paper i will show how to use bidirectional unification grammars to define reversible relations between language dependent meaning representations. furthermore it is shown how to obtain a completely reversible mt system using a series of (bidirectional) unification grammars.
a linguistic discovery program that verbalizes its discoveries. we describe a discovery program, called univauto (universals authoringtool), whose domain of application is the study of language universals, a classic trend in contemporary linguistics. accepting as input information about languages, presented in terms of feature-values, the discoveries of another human agent arising from the same data, as well as some additional data, the program discovers the universals in the data, compares them with the discoveries of the human agent and, if appropriate, generates a report in english on its discoveries. running univauto on the data from the seminal paper of greenberg (1966) on word order universals, the system has produced several linguistically valuable texts, two of which are published in a refereed linguistic journal.
adjuncts and the processing of lexical rules. the standard hpsg analysis of germanic verb clusters can not explain the observed narrowscope readings of adjuncts in such verb clusters.we present an extension of the hpsg analysis that accounts for the systematic ambiguity of the scope of adjuncts in verb cluster constructions, by treating adjuncts as members of the subcat list. the extension uses powerful recursive lexical rules, implemented as complex constraints. we show how 'delayed evaluation' techiniques from constraint-logic programming can be used to process such lexical rules.
handling syntactical ambiguity in machine translation. the difficulties to be met with the resolution of syntactical ambiguity in mt can be at least partially overcome by means of preserving the syntactical ambiguity of the source language into the target language. an extensive study of the correspondences between the syntactically ambiguous structures in english and bulgarian has provided a solid empirical basis in favor of such an approach. similar results could be expected for other sufficiently related languages as well. the paper concentrates on the linguistic grounds for adopting the approach proposed.
learning linear precedence rules. a system is described which learns from examples the linear precedence rules in an immediate dominance/linear precedence grammar. given a particular immediate dominance grammar and hierarchies of feature values potentially relevant for linearization (=the system's bias), the learner generates appropriate natural language expressions to be evanaluted as positive or negative by a teacher, and produces as output linear precedence rules which can be directly used by the grammar.
generating a coherent text describing a traffic scene. if a system that embodies a reference semantic for motion verbs and prepositions is to generate a coherent text describing the recognized motions it needs a decision procedure to select the events. in naos event selection is done by use of a specialization hierarchy of motion verbs. the strategy of anticipated visualization is used for the selection of optional deep cases. the system exhibits low-level strategies which are based on verbinherent properties that allow the generation of a coherent descriptive text.
the lingo redwoods treebank: motivation and preliminary applications. the lingo redwoods initiative is a seed activity in the design and development of a new type of treebank. while several medium- to large-scale treebanks exist for english (and for other major languages), pre-existing publicly available resources exhibit the following limitations: (i) annotation is mono-stratal, either encoding topological (phrase structure) or tectogrammatical (dependency) information, (ii) the depth of linguistic information recorded is comparatively shallow, (iii) the design and format of linguistic representation in the treebank hard-wires a small, predefined range of ways in which information can be extracted from the treebank, and (iv) representations in existing treebanks are static and over the (often year- or decade-long) evolution of a large-scale treebank tend to fall behind the development of the field. lingo redwoods aims at the development of a novel treebanking methodology, rich in nature and dynamic both in the ways linguistic data can be retrieved from the treebank in varying granularity and in the constant evolution and regular updating of the treebank itself. since october 2001, the project is working to build the foundations for this new type of treebank, to develop a basic set of tools for treebank construction and maintenance, and to construct an initial set of 10,000 annotated trees to be distributed together with the tools under an open-source license.
soat: a semi-automatic domain ontology acquisition tool from chinese corpus. in this paper, we focus on the domain ontology acquisition from chinese corpus by extracting rules designed for chinese phrases. these rules are noun sequences with part-of-speech tags. experiments show that this process can construct domain ontology prototypes efficiently and effectively.
on formalizations of marcus' parser. lr(k,t), bcp (m,n) and lrrl (k) grammars, and their relations to marcus parsing are discussed.
on the semantic interpretation of nominals. in this paper we examine a subset of polysemous elements, the logical structure of nominals, and argue that many cases of polysemy have well-defined calculi, which interact with the grammar in predictable and determinate ways for disambiguation. these calculi constitute part of the lexical organization of the grammar and contribute to the lexical semantics of a word. the lexical system of the grammar is distinct from the conceptual representation associated with a lexical item, where polysemy is less constrained by grammar. we propose a structured semantic representation, the lexical conceptual paradigm (lcp) which groups nouns into paradigmatic classes exhibiting like behavior.
hinting by paraphrasing in an instruction system. previous work has amphasized the need for paraphrases as means of ensuring a feedback with a system. in this paper, we discuss how a paraphrase may be used as a heuristic device, viz. as a hint. we describe an experimental instruction system in mathematics incorporating this feature. the system accepts a restricted class of algebraic story problems, formulated in non-stylized bulgarian language, and is capable of solving them and providing one or more "hinting" paraphrases, that is, paraphrases alleviating their formalisation (-translation into equations).
parsing a flexible word order language. a logic formalism is presented which increases the expressive power of the id/lp format of gpsg by enlarging the inventory of ordering relations and extending the domain of their application to non-siblings. this allows a concise, modular and declarative statement of intricate word order regularities.
testing the projectivity hypothesis. the empirical validity of the projectivity hypothesis for bulgarian is tested. it is shown that the justification of the hypothesis presented for other languages suffers serious methodological deficiencies. our automated testing, designed to evade such deficiencies, yielded results falsifying the hypothesis for bulgarian: the non-projective constructions studied were in fact grammatical rather than ungrammatical, as implied by the projectivity thesis. despite this, the projectivity/non-projectivity distinction itself has to be retained in bulgarian syntax and, with some provisions, in the systems for automatic processing as well.
interaction grammars. interaction grammars (ig) are a new linguistic formalism which is based on descriptions of underspecified trees in the framework of intuitionistic linear logic (ill). syntactic composition, which is expressed by deduction in linear logic, is controlled by a system of polarized features. in this way, parsing amounts to generating models of trees descriptions and it is implemented as a constraint satisfaction problem.
elementary contracts as a pragmatic basis of language interaction. language interaction (li) as a part of interpersonal communication is considerably influenced by psychological and social roles of the partners and their pragmatic goals. these aspects of communication should be accounted for while elaborating advanced user-computer dialogue systems and developing formal models of li. we propose here a formal description of communicative context of li-situation, namely, a system of indices of li agents1 interest in achieving various pragmatic purposes and a system of contracts which reflect social and psychological roles of the li agents and conventionalize their "rights" and "duties" in the li process. different values of these parameters of communication allow us to state possibility or/and necessity of certain types of speech acts under certain conditions of li-situation.
new dependency based specification of underlying representations of sentences. in this lecture a pushdown store generator of deep, underlying structures (abbrev. us) of sentences is defined. this generator (a pushdown store generative grammar) developed inside the functional generative description (fgd) of language in prague is the first part (from the viewpoint of the generation of a sentence) of the whole stratificational fgd: the output of the generator (a generated us) is transduced to the lower levels of fgd in the direction from function to form (from weaning, generally, to its representation) in order to achieve the final phonetic (graphic) representation of the sentence. our framework comprises the three basic dimensions of the semantics of the sentence: a) valency frames (thetaroles, types of the dependency relation), b) coordination and apposition, and c) topic-focus articulation. the generative grammar reflects the interplay of the mentioned dimensions endeavouring to simulate more closely the process of the formulation of the sentence by a real speaker.
the impatient tutor: an integrated language understanding system. we describe a language understanding system that uses the techniques of segmenting the computation into autonomous modules that communicate by message passing. the goal is to integrate semantic and syntactic processing to achieve greater flexibility and robustness in the design of language understanding systems.
a message-passing control structure for text understanding. this paper describes an object-oriented, message-passing system for natural language text understanding. the application domain is the texts of texas instruments' patent descriptions. the object-oriented environment permits syntactic analysis modules to communicate with domain knowledge modules to resolve ambiguities as they arise.
a translator's workstation. a description is given of the present state of development of a workstation that has been designed to provide the translator with efficient and easy-to-use computational tools. the aim is to offer translators fast and flexible on-line access to existing dictionary databases and bilingual text archives and also to supply them with facilities for updating, adding to and personalizing the system data archives with their own material.
a computational approach to topic and focus in a production model. the aim of the presented research is the development of a linguistic model of the functional concepts topic and focus that can be used in natural language processing systems. the paper deals with two points of investigation: the first point concerns the identification of the topic and focus of an utterance. within the frame of the linguistic discussion on such concepts topic and focus will be considered as semantic, pragmatic and international rather then as syntactic phenomena. an operational definition of topic and focus is obtained on the basis of basic semantic-pragmatic categories which are defined in relation to a specified context. the second point concerns the integration of the topic and focus identification rules in a system for natural language generation. the aim of the application is the validation of the developed topic and focus model with respect to some aspect of the generation process like thematic progression and accent mapping. moreover the identification of topic and focus can be used to make prediction about the thematic progression and the accent mapping in the blocks world texts. for the prediction of indefinite pronouns like "one" and of definite articles within a noun phrase it is necessary to recur to the semantic-pragmatic categories.
modular mt with a learned bilingual dictionary: rapid deployment of a new language pair. the mt system described in this paper combines hand-built analysis and generation components with automatically learned example-based transfer patterns. up to now, the transfer component used a traditional bilingual dictionary to seed the transfer pattern learning process and to provide fallback translations at runtime. this paper describes an improvement to the system by which the bilingual dictionary used for these purposes is instead learned automatically from aligned bilingual corpora, making the system's transfer knowledge entirely derivable from corpora. we show that this system with a fully automated transfer process performs better than the system with a hand-crafted bilingual dictionary. more importantly, this has enabled us to create in less than one day a new language pair, french-spanish, which, for a technical domain, surpasses the quality bar of the commercial system chosen for comparison.
monotonic paradigmatic schemata in italian verb inflection. in recent years, morphological paradigms have been the focus of an extensive investigation, which has thrown in sharp relief the descriptive adequacy of a paradigm-based approach to the morphology of lightly inflecting languages, with particular emphasis on notoriously thorny problems such as stem selection and stem choice in verb conjugation. comparatively little has been done so far to show the practical descriptive advantages of an extensive use of paradigms in a computational system for word analysis/generation. in this paper we report in some detail the results of a fully developed, paradigm-based, computational treatment of the entire conjugational system of italian. we focus on the considerable descriptive economy resulting from drawing on the amount of redundancy exhibited by the paradigmatic structure of both regular and irregular verbs in italian. this redundancy, we suggest, is captured through so-called paradigmatic schemata. our implementation compares favourably with other nonparadigmatic strategies in terms of both descriptive adequacy and economy.
lr(k)-parsing of coupled-context-free grammars. coupled-context-free grammars are a generalization of context-free grammars obtained by combining nonterminals to parentheses which can only be substituted simultaneously. referring to the generative capacity of the grammars we obtain an infinite hierarchy of languages that comprises the context-free languages as the first and all the languages generated by tree adjoining grammars (tags) as the second element. here, we present a generalization of the context-free lr(k)-notion, which characterizes subclasses of coupled-context-free grammars-and therefore for tags - which can be parsed in linear time. the parsing procedure described works incrementally so that it can be used for on-line parsing of natural language. examples show that important tree adjoining languages, e.g. those modelling cross-serial dependencies, can be generated by lr(k)-coupled-context-free grammars.
a formal semantics for generating and editing plurals. we present a formal semantics for an object-oriented formalism which allows for the representation of plural objects (such as 'three n', most of the n', 'some n', . . .). the semantics is given in terms of a mapping to a variant of discourse representation theory. it is motivated by its suitability for natural language generation and interactives editing of the representations.
tagging and chunking with bigrams. in this paper we present an integrated system for tagging and chunking texts from a certain language. the approach is based on stochastic finite-state models that are learnt automatically. this includes biagram models or finite-state automata learnt using grammatical inference techniques. as the models involved in our system are learnt automatically, this is a very flexible and portable system.in order to show the viability of our approach we present results for tagging and chunking using bigram models on the wall street journal corpus. we have achieved an accuracy rate for tagging of 96.8%, and a precision rate for np chunks of 94.6% with a recall rate of 93.6%.
multi-level similar segment matching algorithm for translation memories and example-based machine translation. @we propose a dynamic programming algorithm for calculating the similarity between two segments of words of the same language. the similarity is considered as a vector whose coordinates refer to the levels of analysis of the segments. this algorithm is extremely efficient for retrieving the best example in translation memory systems. the calculus being constructive, it also gives the correspondences between the words of the two segments. this allows the extension of translation memory systems towards example-based machine translation.
text analysis learning strategies. aplec (l'aprenti-lecteur - or learning reader) is an extension of the d&eacute;redec software, a programming system devoted to the content analysis and linguistic treatment of texts.aplec will associate automatically to any text descriptive grammar (tdg - grammaire descriptive de texte) a question/answer module where the questions are asked in a given natural language by the user, and where the answers are tracked down in the textual corpus undergoing examination.
composition of translation schemes with d-trees. generative systems (gs) are defined in this paper as a composition of simple translation schemes with dependency trees. the following issues are discussed: (a) explicative power of gs, (b) the time complexity for the analysis and synthesis for gs.
generation, lambek calculus, montague's semantics and semantic proof nets. most of the studies in the framework of lambek calculus have considered the parsing process and ignored the generation process. this paper wants to rely on the close link between lambek calculus and linear logic to present a method for the generation process with semantic proof nets. we express the process as a proof search procedure based on a graph calculus and the solutions appear as a matrix computation preserving the decidability properties, and we characterize a polynomial time case.
a syntactic approach to discourse semantics. a correct structural analysis of a discourse is a prerequisite for understanding it. this paper sketches the outline of a discourse grammar which acknowledges several different levels of structure. this grammar, the "dynamic discourse model", uses an augmented transition network parsing mechanism to build a representation of the semantics of a discourse in a stepwise fashion, from left to right, on the basis of the semantic representations of the individual clauses which constitute the discourse. the intermediate states of the parser model the intermediate states of the social situation which generates the discourse.the paper attempts to demonstrate that a discourse may indeed be viewed as constructed by means of sequencing and recursive nesting of discourse constituents. it gives rather detailed examples of discourse structures at various levels, and shows how these structures are described in the framework proposed here.
processing complex noun phrases in a natural language interface to a statistical database. analysis of a corpus of queries to a statistical database has shown considerable variation in the location and order of modifiers in complex noun phrases. nevertheless, restrictions can be defined on nominal modification because of certain correspondences between nominal modifiers and the role they fulfill in a statistical database, notably that the names of database tables and columns, and values of columns, are all determined by the modifiers. these restrictions are described. incorporating these restrictions into head-driven phrase structure grammar (hpsg) has caused us to examine the treatment of nominal modification in hpsg. a new treatment is proposed and an implementation within an hpsg based natural language front-end to a statistical database is described.
data-driven classification of linguistic styles in spoken dialogues. language users have individual linguistic styles. a spoken dialogue system may benefit from adapting to the linguistic style of a user in input analysis and output generation. to investigate the possibility to automatically classify speakers according to their linguistic style three corpora of spoken dialogues were analyzed. several numerical parameters were computed for every speaker. these parameters were reduced to linguistically interpretable components by means of a principal component analysis. classes were established from these components by cluster analysis. unseen input was classified by trained neural networks with varying error rates depending on corpus type. a first investigation in using special language models for speaker classes was carried out.
morphological analysis for a german text-to-speech system. a central problem in speech synthesis with unrestricted vocabulary is the automatic derivation of correct pronunciation from the graphemic form of a text. the software module graphon was developed to perform this conversion for german and is currently being extended by a morphological analysis component. this analysis is based on a morph lexicon and a set of rules and structural descriptions for german word-forms. it provides each text input item with an individual characterization such that the phonological, syntactic, and prosodic components may operate upon it. this systematic approach thus serves to minimize the number of wrong transcriptions and at the same time lays the foundation for the generation of stress and intonation patterns, yielding more intelligible, natural-sounding, and generally acceptable synthetic speech.
data-oriented translation. in this article, we present a statistical approach to machine translation that is based on data-oriented parsing: data-oriented translation (dot). in dot, we use linked subtree pairs for creating a derivation of a source sentence. each linked subtree pair has a certain probability, and consists of two trees: one in the source language and one in the target language. when a derivation has been formed with these subtree pairs, we can create a translation from this derivation. since there are typically many different derivations of the same sentence in the source language, there can be as many different translations for it. the probability of a translation can be calculated as the total probability of all the derivations that form this translation. we give the computational aspects for this model, show that we can convert each subtree pair into a productive rewrite rule, and that the most probable translation can be computed by means of monte carlo disambiguation. finally, we discuss some pilot experiments with the verbmobil corpus.
planning texts by constraint satisfaction. a method is described by which a rhetorical-structure tree can be realized by a text structure made up of sections, paragraphs, sentences, vertical lists, and other textual patterns, with discourse connectives added (in the correct positions) to mark rhetorical relations. we show that text-structuring can be formulated as a constraint satisfaction problem, so that all solutions respecting constraints on text-structure formation and structural compatibility can be efficiently generated. of the many solutions generated by this method, some are stylistically preferable to others; we show how further constraints can be applied in order to select the best versions. finally, we discuss some extensions such as the generation of indented text structures.
using a probabilistic class-based lexicon for lexical ambiguity resolution. this paper presents the use of probabilistic class-based lexica for disambiguation in target-word selection. our method employs minimal but precise contextual information for disambiguation. that is, only information provided by the target-verb, enriched by the condensed information of a probabilistic class-based lexicon, is used. induction of classes and fine-tuning to verbal arguments is done in an unsupervised manner by em-based clustering techniques. the method shows promising results in an evaluation on real-world translations.
generalized memory manipulating actions for parsing natural language. current (computational) linguistic theories have developed specific formalisms for representing linguistic phenomena such as unbounded dependencies, relatives, etc. in this contribution we present a model of linguistic structures storing and accessing, which accounts for the same phenomena in a procedural way. such a model has been implemented in the frame of an atn parser.
generating the xtag english grammar using metarules. we discuss a grammar development process used to generate the trees of the wide-coverage lexicalized tree adjoining grammar (ltag) for english of the xtag project. result of the coupling of becker's metarules and a simple yet principled hierarchy of rule application, the approach has been successful to generate the large set of verb trees in the grammar, from a very small initial set of trees.
processing clinical narratives in hungarian. this paper describes a system that extracts information from hungarian descriptive texts of medical domain texts of clinical narratives define a sublanguage that uses limited syntax but holds the main characteristics of the language, namely free word order and rich morphology. we offer a fairly general parsing method for free word order languages and the way how to use it for parsing hungarian clinical texts. the system can handle simple cases of ellipses, anaphora, unknown words and typical abbreviations of clinical practice. the system translates texts of anamneses, patient visits, laboratory tests, medical examinations and discharge summaries into an information format usable for a medical expert system. similarly to this expert system, the information formatting program has been written in mprolog language adn its experimental version runs on proper-16, a hungarian made (ibm-xi compatible) microcomputer.
morphological analyzer as syntactic parser. we describe how a simple parser can be built on the basis of morphology and a morphological analyzer. our initial conditions have been the techniques and principles of humor, a reversible, string-based unification tool (pr&ograve;sz&eacute;ky 1994). parsing is performed by the same engine as morphological analysis. it is useful when there is not enough space to add a new engine to an existing morphology-based application (e.g. a spell-checker), but you would like to handle sentence-level information, as well (e.g. a grammar checker). the morphological analyzer breaks up words into several parts, all of which stored in the main lexicon. each part has a feature structure and the validity of the input word is checked by unifying them. the morphological analyzer returns various information about a word including its categorization. in a sentence, the category of each word (or morpheme) is considered a metaletter, and the sentence itself can be transformed into a meta-word that essentially behaves like a real one. thus the set of sentences recognized by the parser called humoresk can form a lexicon of meta-words that are processed much the same way as lexicons of real words (morphology). this means that algorithmic parsing step are substituted by lexicon look-up, which, by definition, is performed following the surface order of string elements. both the finitizer that transforms formal grammars into finite lexicons and the run-time parser of the proposed model have running implementations.
context-sensitive electronic dictionaries. this paper introduces a context-sensitive electronic dictionary that provides translations for any piece of text displayed on a computer screen, without requiring user interaction. this is achieved through a process of three phases: text acquisition from the screen, morpho-syntactic analysis of the context of the selected word, and the dictionary lookup. as with other similar tools available, this program usually works with dictionaries adapted from one or more printed dictionaries. to implement context sensitive features, however, traditional dictionary entries need to be restructured. by splitting up entries into smaller pieces and indexing them in a special way, the program is able to display a restricted set of information that is relevant to the context. based on the information in the dictionaries, the program is able to recognize---even discontinuous---multiword expressions on the screen.the program has three major features which we believe make it unique for the time being, and which the development focused on: linguistic flexibility (stemming, morphological analysis and shallow parsing), open architecture (three major architectural blocks, all replaceable along public documented apis), and flexible user interface (replaceable dictionaries, direct user feedback).in this paper, we assess the functional requirements of a context-sensitive dictionary as a start; then we explain the program's three phases of operation, focusing on the implementation of the lexicons and the context-sensitive features. we conclude the paper by comparing our tool to other similar publicly available products, and summarize plans for future development.
recognition assistance - treating errors in texts acquired from various recognition processes. texts acquired from recognition sources---continuous speech/handwriting recognition and ocr---generally have three types of errors regardless of the characteristics of the source in particular. the output of the recognition process may be (1) poorly segmented or not segmented at all; (2) containing underspecified symbols (where the recognition process can only indicate that the symbol belongs to a specific group), e.g. shape codes; (3) containing incorrectly identified symbols. the project presented in this paper addresses these errors by developing of a unified linguistic framework called the morphologic recognition assistant that provides feedback and corrections for various recognition processes. the framework uses customized morpho-syntactic and syntactic analysis where the lexicons and their alphabets correspond to the symbol set acquired from the recognition process. the successful framework must provide three services: (1) proper disambiguated segmentation, (2) disambiguation for underspecified symbols, (3) correction for incorrectly recognized symbols. the paper outlines the methods of morpho-syntactic and syntactic post-processing currently in use.
syntactic and semantic parsability. this paper surveys some issues that arise in the study of the syntax and semantics of natural languages (nl's) and have potential relevance to the automatic recognition, parsing, and translation of nl's. an attempt is made to take into account the fact that parsing is scarcely ever thought about with reference to syntax alone; semantic ulterior motives always underly the assignment of a syntactic structure to a sentence. first i consider the state of the art with respect to arguments about the language-theoretic complexity of nl's: whether nl's are regular sets, deterministic cfl's, cfl's, or whatever. while english still appears to be a cfl as far as i can tell, new arguments (some not yet published) appear to show for the first time that some languages are not cfl's. next i consider the question of how semantic filtering affects the power of grammars. then i turn to a brief consideration of some syntactic proposals that employ more or less modest extensions of the power of context-free grammars.
limited domain systems for language teaching. this abstract describes a natural language system which deals usefully with ungrammatical input and describes some actual and potential applications of it in computer aided second language learning. however, this is not the only area in which the principles of the system might be used, and the aim in building it was simply to demonstrate the workability of the general mechanism, and provide a framework for assessing developments of it.
when mariko talks to siegfried - experiences from a japanese/german machine translation project. in this paper we will report on our experiences from a 2 1/2 year project that designed and implemented a prototypical japanese to german translation system for titles of japanese papers.
attitude emergence - an effective interpretation scheme for persuasive discourse. previous approaches have used a reasoning mechanism called belief percolation to determine the actual speech intent of the speaker (e.g., (wilks and bien 1979)). in this paper, a similar mechanism, called attitude emergence, is proposed as a mechanism for inferring a speaker's attitude toward the propositions in a persuasive discourse. it is shown that in order to adequately interpret the statements in advertisements, associations of relevant semantic information, through bridging inferences, are to be percolated up through attitude model contexts to enhance and calibrate the interpretation of statements. a system called buyer is being implemented to recognize speech intents through attitude emergence in the domain of food advertisements taken from reader's digest. an example of buyer's processing is also presented in the paper.
on the proper role of coercion in semantic typing. in this paper, we discuss the phenomenon of logical polysemy in natural language as addressed by generative lexicon theory. we discuss generally the role of type and sortal coercion operations in the semantics, and specifically the conditions on the application of coercion in aspectual predicates and other contexts. we reply to some recent discussion regarding the use of coercion in the grammar, and show that type changing operations are both useful and explanatory mechanisms for capturing linguistic and computational generalizations.
an improved left-corner parsing algorithm. this paper proposes a series of modifications to the left corner parsing algorithm for context-free grammars. it is argued that the resulting algorithm is both efficient and flexible and is, therefore, a good choice for the parser used in a natural language interface.
generating multilingual documents from a knowledge base: the techdoc project. techdoc is an implemented system demonstrating the feasibility of generating multilingual technical documents on the basis of a language-independent knowledge base. its application domain is user and maintenance instructions, which are produced from underlying plan structures representing the activities, the participating objects with their properties, relations, and so on. this paper gives a brief outline of the system architecture and discusses some recent developments in the project: the addition of actual event simulation in the kb, steps towards a document authoring tool, and a multimodal user interface.
blending segmentation with tagging in chinese language corpus processing. this paper poses a new method for chinese language corpus processing. unlike the past researches, our approach has following charactericstics: it blends segmenation with tagging and integrates rule-based approach with statistics-based one in grammatical disambiguation. the principal ideas presented in the paper are incorporated in the development of a chinese corpus processing system. experimental results prove that the overall accuracy for segmentation is 97.68% and that for tagging is 94.55% in about 400,000 chinese characters.
probabilistic reasoning for entity & relation recognition. this paper develops a method for recognizing relations and entities in sentences, while taking mutual dependencies among them into account. e.g., the kill (johns, oswald) relation in: "j. v. oswald was murdered at jfk after his assassin, k. f. johns. . ." depends on identifying oswald and johns as people, jfk being identified as a location, and the kill relation between oswald and johns; this, in turn, enforces that oswald and johns are people.in our framework, classifiers that identify entities and relations among them are first learned from local information in the sentence; this information, along with constraints induced among entity types and relations, is used to perform global inference that accounts for the mutual dependencies among the entities.our preliminary experimental results are promising and show that our global inference approach improves over learning relations and entities separately.
using discourse predictions for ambiguity resolution. in this paper we discuss how we apply discourse predictions along with non context-based predictions to the problem of parse disambiguation in enthusiast, a spanish-to-english translation system (woszcyna et al., 1993; suhm et al., 1994; levin et al., 1995). we discuss extensions to our plan-based discourse processor in order to make this possible. we evaluate those extensions and demonstrate the advantage of exploiting context-based predictions over a purely non context-based approach.
pragmatics in machine translation. texan is a system of transfer-oriented text analysis. its linguistic concept is based on a communicative approach within the framework of speech act theory. in this view texts are considered to be the result of linguistic actions. it is assumed that they control the selection of translation equivalents. the transtion of this concept of linguistic actions (text acts) to the model of computer analysis is performed by a context-free illocution grammar processing categories of actions and a propositional structure of states of affairs. the grammar which is related to a text lexicon provides the connection of these categories and the linguistic surface units of a single language.
an hpsg parser based on description logics. in this paper i present a parser based on description logics (dl) for a german hpsg-style fragment. the specified parser relies mainly on the inferential capabilities of the underlying dl system. given a preferential default extension for dl disambiguation is achieved by choosing the parse containing a qualitatively minimal number of exceptions.
typology study of french technical texts, with a view to developing a machine translation system. within the industrial context of the information society, technical translation represents a considerable commercial stake. in the light of this, machine translation is considered as being an application of paramount importance. it is for this reason that the activities of b'vital have always centered around the processing of technical texts.the following article gives an account of the various tasks carried out over the last few years on corpus analysis. we have drawn conclusions as to the validity of the notion of text typologies, applied in particular to technical matter, with a view to developing a machine translation system. the stuyd was conducted using a fair amount of french documents and has led us to observe in particular, that a same typology may be identified in texts originating from varying fields.
arguing about planning alternatives. in discourse processing, two major problems are understanding the underlying connections between successive dialog utterances and deciding on the content of a coherent dialog response. this paper presents a computational model of these tasks for a restricted class of argumentative dialogs. in these dialogs, each response presents a belief that justifies or contradicts another belief presented or inferred earlier in the dialog. understanding a response involves relating a stated belief to these earlier beliefs, and producing a response involves selecting a belief to justify and deciding upon the set of beliefs to provide as its justification. our approach is knowledge based, using general, common-sense justification rules to recognize how a belief is being justified and to form new justifications for beliefs. this approach provides the ability to recognise and respond to never before seen belief justifications, a necessary capability for any system that participates in dialogs involving disagreements.
a formalism for universal segmentation of text. sumo is a formalism for universal segmentation of text. its purpose is to provide a framework for the creation of segmentation applications. it is called "universal" as the formalism itself is independent of the language of the documents to process and independent of the levels of segmentation (e.g. words, sentences, paragraphs, morphemes...) considered by the target application. this framework relies on a layered structure representing the possible segmentations of the document. this structure and the tools to manipulate it are described, followed by detailed examples highlighting some features of sumo.
les experiences d'indexation a l'inist. we talk, in this paper, about the operation of indexation at inist. we present two experiments carried out within the department of research and new products that aim at the automation of indexation process. the first one comes within the scope of scientometric studies on text database. we have developped a software toolbox with which we can build a chain of treatments up to the generation of hyperdocuments. therefore, indexation from a large corpus of source documents is the first module of that chain. in this part, we use linguistic and statistical methods to produce keywords from a stream of data. linguitic heuristics are used to extract compound nouns or noun phrases from the text and combinational treatments determine the importance of each term according to the document. keywords are here the input of an hypertext system. the second one is the development of a workstation for the information specialist integrating a computer-aided indexing system on title and abstract in bibliographical records. this indexing process works on a single bibliographical record and combines both linguistic methods and artificial intelligence (keywords generation). we use the same extraction module based on linguistic and add a knowledge based system to deduce implicit keywords. finally, we show that the original specifications and purpose of each experiment are different and we start a discussion on the interest of these methods in relation to the kind of indexation wanted and the qualities expected from automatic indexing systems.
argumentation in representation semantics. it seems rather natural to admit that language use is governed by rules that relate signs, forms and meanings to possible intentions or possible interpretations, in function of utterance situations. not less natural should seem the idea that the meaning of a natural language expression conveys enough material to the input of these rules, so that, given the situation of utterance, they determine the appropriate interpretation. if this is correct, the semantic description of a natural language expression should output not only the 'informative content' of that expression, but also all sorts of indications concerning the way this expression may be used or interpreted. in particular, the argumentative power of utterances is due to argumentative indications conveyed by the sentences uttered, indications that are not part of their informative content. this paper emphasizes the role of argumentation in language and shows how it could be accounted for in a formal representation semantics framework. an example of an analysis is provided in order to show the "system at work".
using contextual spelling correction to improve retrieval effectiveness in degraded text collections. the study presented relies on the design and evaluation of an improved ir system susceptible to cope with textual misspellings. after selecting an optimal weighting scheme for the engine, we evaluate the effect of misspellings on the retrieval effectiveness. then, we compare the improvement brought to the engine by the adjunction of two different non-interactive spelling correction strategies: a classical one, based on a string-to-string edit distance calculus, and a contextual one, which adds linguistically-motivated features to the string distance module. the results for the latter suggest that average precision in degraded texts can be reduced to a few percents (4%).
automatic translation of noun compounds. this paper describes the treatment of nominal compounds in a tranarer based machine translation system; it presents a new approach for resolving ambiguities in compound segmentation and constituent structure selection using a combination of linguistic rules and statistical data. an introduction to the general as well as to the german-english-specific problems of compound translation is given (sect. 1). in section 2, the analysis phase is described with its linguistics as well as its computational aspects. section 3 deals with the transfer and generation process, focussing on corpus based techniques.
a context-sensitive model for probabilistic lr parsing of spoken language with transformation-based postprocessing. this paper describes a hybrid approach to spontaneous speech parsing. the implemented parser uses an extended probabilistic lr parsing model with rich context and and its output is post-processed by a symbolic tree transformation routine that tries to eliminate systematic errors of the parser. the parser has been trained for three different languages and was successfully integrated in the verbmobil speech-to-speech translation system. the parser achieves more than 90%/90% labeled precision/recall on parsed verbmobil utterances while 3% of german and 5% of all english input cannot be parsed.
creating a finite-state parser with application semantics. parsli is a finite-state (fs) parser which can be tailored to the lexicon, syntax, and semantics of a particular application using a hand-editable declarative lexicon. the lexicon is defined in terms of a lexicalized tree adjoining grammar, which is subsequently mapped to a fs representation. this approach gives the application designer better and easier control over the natural language understanding component than using an off-the-shelf parser. we present results using parsli on an application that creates 3d-images from typed input.
genetic nps and habitual vps. we propose a simple, intuitively satisfying treatment of the semantics of bare plural nps. this treatment avoids the use of non-standard logics, and avoids the need for systematic ambiguity of verb semantics.
a syntactic and morphological analyzer for a text-to-speech system. this paper presents a system which analyzes an input text syntactically and morphologically and converts the text from the graphemic to the phonetic representation (or vice versa). we describe the grammar formalism used and report a parsing experiment which compared eight parsing strategies within the framework of chart parsing. although the morphological and syntactic analyzer has been developed for a text-to-speech system for german, it is language independent and general enough to be used for dialog systems, nl-interfaces or speech recognition systems.
aspect and aktionsart: fighting or cooperating? it is widely accepted that semantic theories should, as far as possible, be compositional. the claim that a theory is compositional, however, lacks bite if lexical and pre-lexical items are allowed to mean different things in different contexts. the aim of the current paper is to show how to deal with a well-known phenomenon by relying on combinatorial effects to infer different consequences from the same items in different contexts without altering the contributions that these items make individually.
kcat: a korean corpus annotating tool minimizing human intervention. while large pos (part-of-speech) annotated corpora play an important role in natural language processing, the annotated corpus requires very high accuracy and consistency. to build such an accurate and consistent corpus, we often use a manual tagging method. but the manual tagging is very labor intensive and expensive. furthermore, it is not easy to get consistent results from the human experts. in this paper, we present an efficient tool for building large accurate and consistent corpora with minimal human labor. the proposed tool supports semiautomatic tagging. using disambiguation rules acquired from human experts. it minimizes the human intervention in both the manual tagging and post-editing steps.
unscrambling english word order. we propose a treatment of 'extraposition' which allows items to be assimilated directly even when they appear far from their canonical positions. this treatment supports analyses of a number of phenomena which are otherwise hard to describe. the approach requires a generalisation of standard chart parsing techniques.
caramel: a flexible model for interaction between the cognitive processes underlying natural language understanding. in this paper we present a general natural language processing system called caramel (in french: compr&eacute;hension automatique de r&eacute;cits, apprentissage et mod&eacute;lisation des &eacute;changes langagiers). over the last few years our group has developed many programs to deal with different aspects of natural language processing. this paper describes a general architecture that integrates them in a flexible way, and provides a control strategy capable of adapting itself to the requirements of a particular task. the model is composed of three fundamental elements:- a structured memory containing permanent knowledge and working structures of the system- a set of processes, dedicated to the execution of the various cognitive tasks- a supervisor, whose function is to trigger, to run coherently and to synchronize the processes.the system contains a kind of blackboard, which is enhanced with a control mechanism driven by meta-rules. this architecture is fully implemented. we are currently developing the meta-rules necessary to use the model for various tasks.
problem localization strategies for pramatics processing in natural-language front ends. problem localization is the identification of the most significant failures in the and-or tree resulting from an unsuccessful attempt to achieve a goal, for instance, in planning, backward-chaining inference, or top-down parsing. we examine heuristics and strategies for problem localization in the context of using a planner to check for pragmatic failures in natural language input to computer systems, such as a cooperative natural language interface to unix&trade; our heuristics call for selecting the most hopeful branch at ors, but the most problematic one at ands. surprise scores and special-purpose rules are the main strategies suggested to determine this.
sesame a portable data base interface generator. sesame is being developed to provide an easy access to the content of relational data bases to users without a specific computer training. queries are typed in natural language either freely or with a guided mode. the system dynamically proposes through menus the different words and phrases that can make up a query. users are able to exploit the results of their queries with standard electronic office tools or specialized applications.the sesame system is a user interface generator. to develop a particular application, different knowledge bases have to be built: lexicon, conceptual schema of the data base... knowledge base editors and design methodologies provide help for the development of applications.sesame is a good example of techniques created in research laboratories and applied to the development of an industrial product.
quasi-indexical reference in propositional semantic networks. we discuss how a deductive question-answering system can represent the beliefs or other cognitive states of users, of other (interacting) systems, and of itself. in particular, we examine the representation of first-person beliefs of others (e.g., the <u>system's</u> representation of a <u>user's</u> belief that he himself is rich). such beliefs have as an essential component "quasi-indexical pronouns" (e.g., 'he himself'), and, hence, require for their analysis a method of representing these pronominal constructions and performing valid inferences with them. the theoretical justification for the approach to be discussed is the representation of <u>nested "de dicto"</u> beliefs (e.g., the system's belief that user-1 believes that system-2 believes that user-2 is rich). we discuss a computer implementation of these representations using the semantic network processing system (sneps) and an atn parser-generator with a question-answering capability.
the computation of word associations: comparing syntagmatic and paradigmatic approaches. it is shown that basic language processes such as the production of free word associations and the generation of synonyms can be simulated using statistical models that analyze the distribution of words in large text corpora. according to the law of association by contiguity, the acquisition of word associations can be explained by hebbian learning. the free word associations as produced by subjects on presentation of single stimulus words can thus be predicted by applying first-order statistics to the frequencies of word co-occurrences as observed in texts. the generation of synonyms can also be conducted on co-occurrence data but requires second-order statistics. the reason is that synonyms rarely occur together but appear in similar lexical neighborhoods. both approaches are systematically compared and are validated on empirical data. it turns out that for both tasks the performance of the statistical system is comparable to the performance of human subjects.
a constraint-based approach to translating anaphoric dependencies. the normal method for representing anaphoric dependencies in unification based grammar formalisms is that of re-entrance. in this paper, we address the problems that this representational device poses when such formalisms are used for translation. we demonstrate the inadequacies of existing proposals, and describe an approach which exploits the expressive possibilities of the equational constraint language in lfg and involves an inferential procedure combining underspecification in the statement of bilingual correspondences with the use of target language knowledge.
adjectival modification in text meaning representation. this work belongs to a family of research efforts, called microtheories and aimed at describing the static meaning of all lexical categories in several languages in the framework of the mikrokosmos project on computational semantics. the latter also involves other static microtheories describing world knowledge and syntax-semantics mapping as well as dynamic microtheories connected with the actual process of text analysis. this paper describes our approach to detecting and recording adjectival meaning, compares it with the body of knowledge on adjectives in literature and presents a detailed, practically tested methodology for the acquisition of lexical entries for adjectives. the work was based on the set of over 6,000 english and about 1,500 spanish adjectives obtained from task-oriented corpora.
pilot implementation of a bilingual knowledge bank. a bilingual knowledge bank is a syntactically and referentially structured pair of corpora, one being a translation of the other, in which translation units are cross-coded between the corpora. a pilot implementation is described for a corpus of some 20,000 words each in english, french and esperanto which has been cross-coded between english and esperanto and between esperanto and french. the aim is to develop a corpus-based general-purpose knowledge source for applications in machine translation and computer-aided translation.
a cooperative yes-no query system featuring discourse particles. cooperative dialog systems will offer extended answers to questions, that is, they will volunteer information not explicitly asked for. a complete response will be complex and the member sentences will evince an extensive parallel, the indirect answer substituting an alternative for a focus in the question. research on discourse particles has shown that they are necessary to ensure coherence between adjacent sentences evincing an extensive parallel, that is, that they reflect discourse relations as given in complex answers, so that such answers emerge as core contexts. thus the proper mode of representation for discourse particles in a system coincides with the framework of cooperative question-answering. the passat system centers on the rle of particles in characterizing and reflecting relations such as underlie complex response.
compiling language models from a linguistically motivated unification grammar. systems now exist which are able to compile unification grammars into language models that can be included in a speech recognizer, but it is so far unclear whether non-trivial linguistically principled grammars can be used for this purpose. we describe a series of experiments which investigate the question empirically, by incrementally constructing a grammar and discovering what problems emerge when successively larger versions are compiled into finite state graph representations and used as language models for a medium-vocabulary recognition task.
evaluating natural language systems: a sourcebook approach. this paper reports progress in development of evaluation methodologies for natural language systems. without a common classification of the problems in natural language understanding authors have no way to specify clearly what their systems do, potential users have no way to compare different systems and researchers have no way to judge the advantages or disadvantages of different approaches to developing systems.
parallel intersection and serial composition of finite state transducers. we describe a linguistically expressive and easy to implement parallel semantics for quasi-deterministic finite state transducers(fsts) used as acceptors. algorithms are given for determining acceptance of pairs of phoneme strings given a parallel suite of such transducers and for constructing the equivalent single transducer by parallel intersection. an algorithm for constructing the serial composition of a sequence of such transducers is also given. this algorithm can produce generally nondeterministic fsts and an algorithm is presented for eliminating the unacceptable nondeterminism. finally, the work is discussed in the context of other work on finite state transducers.
constructing verb semantic classes for french: methods and evaluation. in this paper, we study a reformulation, which is better adapted to nlp, of the alternation system developed for english by b. levin. we have studied a set of 1700 verbs from which we explain how verb semantic classes can be built in a systematic way. the quality of the results w.r.t. semantic classifications such as wordnet is then evaluated.
perception, concepts and language road and ipage. a two-level natural language generation system for situation and action descriptions (sads) of a simulated assembly robot is presented. in the first step, multimodal information is used to obtain a conceptual representation (cr) of an event. the second step is the parallel, incremental surface realization of utterances from the robot's perspective based on the cr. theoretical issues addressed are semantics of sads and distribution of lexical and syntactic processing, leading to a natural type of incrementality in nlg.
deafault logic, natural language and generalized quantifiers. the use of default logic to represent various linguistic constructions is explored in this paper. default logic is then integrated into a theory of natural language semantics, namely generalized quantifiers. finally, properties of interest to the ai community such as the characterization of truth persistence and some inferential patterns are emphasized.
a connectionist model of some aspects of anaphor resolution. this paper describes some recent developments in language processing involving computational models which more closely resemble the brain in both structure and function. these models employ a large number of interconnected parallel computational units which communicate via weighted levels of excitation and inhibition. a specific model is described which uses this approach to process some fragments of connected discourse.
interactive speech understanding. this paper introduces a robust interactive method for speech understanding. the generalized lr parsing is enhanced in this approach. parsing proceeds from left to right correcting minor errors. when a very noisy portion is detected, the parser skips that portion using a fake nonterminal symbol. the unidentified portion is resolved by re-utterance of that portion which is parsed very efficiently by using the parse record of the first utterance. the user does not have to speak the whole sentence again. this method is also capable of handling unknown words, which is important in practical systems. detected unknown words can be incrementally incorporated into the dictionary after the interaction with the user. a pilot system has shown great effectiveness of this approach.
bi-directional lr parsing from an anchor word for speech recognition. this paper introduces a new technique of parsing sentences from an arbitrary word which is highly reliable or semantically important. this technique adopts an efficient lr parsing method and uses a reverse lr table constructed besides a standard lr table. this technique is particularly suitable in parsing a lattice of words hypothesized by a speech recognition module. if we choose anchor symbols in such a way that they are almost always acoustically reliable, the bi-directional lr parsing performs better against misrecognized words than the regular left-to-right lr parser, while most of the lr efficiency is preserved. a pilot implementation shows a 43% reduction of the error rate against the left-to-right lr method in parsing the speech input.
parsing noisy sentences. this paper describes a method to parse and understand a "noisy" sentence that possibly includes errors caused by a speech recognition device. our parser is connected to a speech recognition device which takes a continuously spoken sentence in japanese and produces a sequence of phonemes. the output sequence of phonemes can quite possibly include errors: altered phonemes, extra phonemes and missing phonemes. the task is to parse the noisy phoneme sequence and understand the meaning of the original input sentence, given an augmented context-free grammar whose terminal symbols are phonemes. a very efficient parsing method is required, as the task's search space is much larger than that of parsing un-noisy sentences. we adopt the generalized lr parsing algorithm, and a certain scoring scheme to select the most likely sentence out of multiple sentence candidates. the use of a confusion matrix, which is created in advance by analyzing a large set of input/output pairs, is discussed to improve the scoring accuracy. the system has been integrated into cmu's knowledge-based machine translation system.
a fast algorithm for the generation of referring expressions. we simplify previous work in the development of algorithms for the generation of referring expressions while at the same time taking account of psycholinguistic findings and transcript data. the result is a straightforward algorithm that is computationally tractable, sensitive to the preferences of human users, and reasonably domain-independent. we provide a specification of the resources a host system must provide in order to make use of the algorithm, and describe an implementation used in the idas system.
a cd-rom retrieval system with multiple dialogue agents. in this paper, we proposed a new dialogue system with multiple dialogue agents. in our new system, three types of agents: a) domain agents, b) strategy agents, and c) context agents were realized. they give the following advantages to the user:&bull; the domain agents make the user aware of the boundary between the domains.&bull; the strategy agents make the user aware of the difference between the strategies.&bull; the context agents help the user to deal with multiple goals.we expect that the complex behaviors of the system will become more visible to the user in different situations. the experimental results show that the user can retrieve effectively and obtain the expected goals easily by using these multiple agents.
concept and structure of semantic markers for machine translation in mu-project. this paper discusses the semantic features of nouns classified into categories in japanese-to-english translation, and proposes a system for semantic markers. in our system syntactic analysis is carried out by checking the semantic compatibility between verbs and nouns. the semantic structure of a sentence can be extracted at the same time as its syntactic analysis.we also use semantic markers to select words in the transfer phase for translation into english.the system of the semantic markers for nouns consists of 13 conceptional faccts including one facct for "others" (discussed later), and is made up of 49 filial slots (semantic markers) as terminals. we have tested about 3,000 sample abstracts in science and technological fields. our research has revealed that our method is extremely effective in determining the meanings of wago verbs (basic japanese verbs) which have broader concepts like english verbs, "make", "get", "take", "put", etc.
dutch cross serial dependencies in hpsg. we present an analysis of dutch cross serial dependencies in head-driven phrase structure grammar ([p&s(1994)]). we start out from the assumption that causative and perceptual verbs, like auxiliaries, can lexically 'raise' the arguments of the non-finite verbs they govern to their own list of arguments through "argument composition" ([h&n(1989)]).
lexical parallelism in text structure determination and content analysis. in this paper the problem is discussed about the text structure determination and content analysis by lexical parallelism, or the repetition of lexical items. intersentential relations are determined through the identical, partly identical or lexico-semantic repetition in japanese scientific texts. lexical parallelism ratio and lexical parallelism indicator distance are obtained on computer and by hand. and the application of the characteristics to automatic content analysis is dicsussed.
left-corner parsing and psychological plausibility. it is well known that even extremely limited centerembedding causes people to have difficulty in comprehension, but that left- and right-branching constructions produce no such effect. if the difficulty in comprehension is taken to be a result of processing load, as is widely assumed, then measuring the processing load induced by a parsing strategy on these constructions may help determine its plausibility as a psychological model. on this basis, it has been argued [aj91, jl83] that by identifying processing load with space utilization, we can rule out both top-down and bottom-up parsing as viable candidates for the human sentence processing mechanism, and that left-corner parsing represents a plausible alternative.examining their arguments in detail, we find difficulties with each presentation. in this paper we revise the argument and validate its central claim. in so doing, we discover that the key distinction between the parsing methods is not the form of prediction (top-down vs. bottom-up vs. left-corner), but rather the ability to instantiate the operation of composition.
lexicon features for japanese syntactic analysis in mu-project-je. in this paper, we focus on the features of a lexicon for japanese syntactic analysis in japanese-to-english translation. japanese word order is almost unrestricted and <u>kakuio-shi</u> (postpositional case particle) is an important device which acts as the case label (case marker) in japanese sentences. therefore case grammar is the most effective grammar for japanese syntactic analysis.the case frame governed by <u>yougen</u> and having surface case <u>(kakuio-shi)</u>, deep case (case label) and semantic markers for nouns is analyzed here to illustrate how we apply case grammar to japanese syntactic analysis in our system.the parts of speech are classified into 56 sub-categories.we analyze semantic features for nouns and pronouns classified into sub-categories and we present a system for semantic markers. lexicon formats for syntactic and semantic features are composed of different features classified by part of speech.as this system uses lisp as the programming language, the lexicons are written as s-expression in lisp, punched onto tapes, and stored as files in the computer.
probabilistic tree-adjoining grammar as a framework for statistical natural language processing. in this paper, i argue for the use of a probabilistic form of tree-adjoining grammar (tag) in statistical natural language processing. i first discuss two previous statistical approaches --- one that concentrates on the probabilities of structural operations, and another that emphasizes co-occurrence relationships between words. i argue that a purely structural apprach, exemplified by probabilistic context-free grammar, lacks sufficient sensitivity to lexical context, and, conversely, that lexical co-occurence analyses require a richer notion of locality that is best provided by importing some notion of structure.i then propose probabilistic tag as a framework for statistical language modelling, arguing that it provides an advantageous combination of structure, locality, and lexical sensitivity. issues in the acquisition of probabilistic tag and parameter estimation are briefly considered.
on the use of term associations in automatic information retrieval. it has been recognized that single words extracted from natural language texts are not always useful for the representation of information content. associated or related terms. and comples content identifiers derived from thesauruses and knowledge bases, or constructed by automatic word grouping techniques, have therefore been proposed for text identification purposes.the area of associative content analysis and information retrievl is reviewed in this study. the available experimental evidence shows that none of the existing or proposed methodologies are guaranteed to improve retrieval performance in a replicable manner for document collections in different subject areas. the associative techniques are most valuable for restricted environments covering narrow subject areas, or in iterative search situations where user inputs are available to refine previously available query formulations and search output.
semantic relevance and aspect dependency in a given subject domain: contents-driven algorithmic processing of fuzzy wordmeanings to form dynamic stereotype representations. cognitive principles underlying the (re-) construction of word meaning and/or world knowledge structures are poorly understood yet. in a rather sharp departure from more orthodox lines of introspective acquisition of structural data on meaning and knowledge representation in cognitive science, an empirical approach is explored that analyses natural language data statistically, represents its numerical findings fuzzy-set theoretically, and interprets its intermediate constructs (stereotype meaning points) topologically as elements of semantic space. as connotative meaning representations, these elements allow an aspect-controlled, contents-driven algorithm to operate which reorganizes them dynamically in dispositional dependency structures (dds-trees) which constitute a procedurally defined meaning representation format.
inducing information extraction systems for new languages via cross-language projection. information extraction (ie) systems are costly to build because they require development texts, parsing tools, and specialized dictionaries for each application domain and each natural language that needs to be processed. we present a novel method for rapidly creating ie systems for new languages by exploiting existing ie systems via cross-language projection. given an ie system for a source language (e.g., english), we can transfer its annotations to corresponding texts in a target language (e.g., french) and learn information extraction rules for the new language automatically. in this paper, we explore several ways of realizing both the transfer and learning processes using off-the-shelf machine translation systems, induced word alignment, attribute projection, and transformation-based learning. we present a variety of experiments that show how an english ie system for a plane crash domain can be leveraged to automatically create a french ie system for the same domain.
using the same system for analyzing and synthesizing sentences. we specify the advantages of guided composition of sentences and illustrate them with examples from leader, a natural language interface we have developped. guided composition is achieved by using the same grammar for analysis and for synthesis. we detail the problems we have encountered and we provide solutions for partial synthesis. we give the principles of the analysis-synthesis algorithm.
a rational reconstruction of the proteus sentence planner. a revised and more structured version of davey's discourse generation program has been implemented, which constructs the underlying forms for sentences and clauses by using rules which annotate and segment the initial sequence of events in various ways.
a statistical theory of dependency syntax. a generative statistical model of dependency syntax is proposed based on tesni&egrave;re's classical theory. it provides a stochastic formalization of the original model of syntactic structure and augments it with a model of the string realization process, the latter which is lacking in tesni&egrave;re's original work. the resulting theory models crossing dependency links, discontinuous nuclei and string merging, and it has been given an efficient computational rendering.
the computational complexity of sentence derivation in functional unification grammar. functional unification (fu) grammar is a general linguistic formalism based on the merging of feature-sets. an informal outline is given of how the definition of derivation within fu grammar can be used to represent the satisfiability of an arbitrary logical formula in conjunctive normal form. this suggests that the generation of a structure from an arbitrary arbitrary fu grammar is np-hard, which is an undesirably high level of computational complexity.
text disambiguation by finite state automata, an algorithm and experiments on corpora. consulting a dictionary for the words of a given text provides multiple solutions, that is, ambiguities; thus, the sequence of words pilot studies could lead for example to:pilot: n singular, v infinitive, v (conjugated)studies: n plural, v (conjugated)pilot studies: n plural (compound).these informations could be organized in the form of a finite automaton such as:[see pdf for figure]the exploration of the context should provide clues that eliminate the non-relevant solutions. for this purpose we use local grammar constraints represented by finite automata. we have designed and implemented an algorithm which performs this task by using a large variety of linguistic constraints. both the texts and the rules (or constraints) are represented in the same formalism, that is finite automata. performing subtraction operations between text automata and constraint automata reduce the ambiguities. experiments were performed on french texts with large scale dictionaries (one dictionary of 600.000 simple inflected forms and one dictionary of 150.000 inflected compunds). syntactic patterns represented by automata, including shapes of compound nouns such as noun followed by an adjective (in gender-number agreement) (cf 5.1), can be matched in texts.this process is thus an extension of the classic matching procedures because of the on-line dictionary consultation and because of the grammar constraints. it provides a simple and efficient indexing tool.
handling sparse data by successive abstraction. a general, practical method for handling sparse data that avoids held-out data and iterative reestimation is derived from first principles. it has been tested on a part-of-speech tagging task and out-performed (deleted) interpolation with context-independent weights, even when the latter used a globally optimal parameter setting determined a posteriori.
two parsing algorithms by means of finite state transducers. we present a new approach, illustrated by two algorithms, for parsing not only finite state grammars but also context free grammars and their extension, by means of finite state machines. the basis is the computation of a fixed point of a finite-state function, i.e. a finite-state transducer. using these techniques, we have built a program that parses french sentences with a grammar of more than 200,000 lexical rules with a typical response time of less than a second. the first algorithm computes a fixed point of a non-deterministic finite-state transducer and the second computes a fixed point of a deterministic bidirectional device called a bimachine. these two algorithms point out a new connection between the theory of parsing and the theory of representation of rational transductions.
a mechanism for ellipsis resolution in dialogued systems. an ellipsi resolution mechanism is presented. the mechanism is a part of a natural language understanding system developed in the last years in order to be included as a main component of several projects based on man/machine interactions. capra, an intelligent system for teaching programming, and guai, a natural language interfaces generator, are two of such applications. in our approach, syntactic and knowledge-based techniques are combined in order to get a great coverage of elliptical cases.
temporal structure of discourse. in this paper discourse segments are defined and a method for discourse segmentation primarily based on abduction of temporal relations between segments is proposed. this method is precise and computationally feasible and is supported by previous work in the area of temporal anaphora resolution.
word knowledge acquisition, lexicon construction and dictionary compilation. we describe an approach to semiautomatic lexicon development from machine readable dictionaries with specific reference to verbal diatheses, envisaging ways in which the results obtained can be used to guide word classification in the construction of dictionary databases.
generating english paraphrasis from formal relational calculus expressions. this paper discusses a system for producing english descriptions (or "paraphrases") of the content of formal relational calculus (rc) formulae expressing a database (db) query. it explains the underlying design motivations and describes a conceptual model and focus selection mechanism necessary for delivering coherent paraphrases. the general paraphrasing strategy is discussed, as are the notions of "desirable" paraphrase and "paraphrasable query". two examples are included. the system was developed and implemented in prolog at the university of essex under a grant from icl.
effective structural inference for large xml documents. this paper investigates methods to automatically infer structural information from large xml documents. using xml as a reference format, we approach the schema generation problem by application of inductive inference theory. in doing so, we review and extend results relating to the search spaces of grammatical inferences for large data set. we evaluate the result of an inference process using the concept of minimum message length. comprehensive experimentation reveals our new hybrid method to be the most effective for large documents. finally tractability issues, including scalability analysis, are discussed.
virtual polysemy. we present an approach to lexical knowledge representation where different uses of the same word can be conflated into a single meta-entry which encodes regularities about sense/usage extensibility. this approach makes it possible to solve lexical ambiguities by using contextual information during language processing to ground underspecified word entries, and can be efficiently implemented within a typed feature structure formalism.
formalization of argumentation structures in newspaper texts. the paper discusses the role of argumentation schemata and their interaction with other knowledge sources within a computer model for in-depth understanding of newspaper texts about jobmarket developments. some of these schemata are presented; the "although ..."-argumentation (german: "trotz...") and its formalization are discussed in detail.
applying system combination to base noun phrase identification. we use seven machine learning algorithms for one task: identifying base noun phrases. the results have been processed by different system combination methods and all of these outperformed the best individual result. we have applied the seven learners with the best combinator, a majority vote of the top five systems, to a standard data set and managed to improve the best published result for this data set.
lexical gaps and idioms in machine translation. this paper describes the treatment of lexical gaps, collection information and idioms in the english to portuguese machine translation system portuga.the perspective is strictly bilingual, in the sense that all problems referenced above are considered to belong to the transfer phase, and not, as in other systems, to analysis or generation.the solution presented invokes a parser for the target language (portuguese) that analyses, producing the corresponding graph structure, the multiword expression selected as the result of lexical transfer.this process seems to bring considerable advantage in what readability and ease of bilingual dictionary development is concerned, and to furnish maximal flexibility together with minimal storage requirements. finally, it also provides complete independence between dictionary and grammar formalisms.
a tense and aspect calculus. this paper focuses on a theory of tense and aspect (the representation of time in natural language) that attempts a formal representation of the relevant linguistic devices as implication rules in first order logic.it presents a rich ontology as far as verb aspect is concerned, distinguishing between complex patterns and vagueness.examples and conclusions are drawn from the comparison between english and portuguese, pinpointing the importance of contrastive studies both for the understanding and for the evaluation of a general theory of tense and aspect.in the paper, we present the actual translations of a wide range of phenomena, and a short example.
linguistic bases for machine translation. my aim in organizing this panel is to stimulate the discussion between researchers working on mt and linguists interested in formal syntax and semantics. i am convinced that a closer cooperation will be fruitful for both sides. i will be talking about experimental mt or mt as a research project and not as a development project.[1]
coordination in tree adjoining grammars: formalization and implementation. in this paper we show that an account for coordination can be constructed using the derivation structures in a lexicalized tree adjoining grammar (ltag). we present a notion of derivation in ltags that preserves the notion of fixed constituency in the ltag lexicon while providing the flexibility needed for coordination phenomena. we also discuss the construction of a practical parser for ltags that can handle coordination including cases of non-constituent coordination.
des heuristiques pour la recherche du theme d'un discours et de l'antecedent d'un pronom. un des probl&egrave;mes r&eacute;siduels pour le traitement des r&eacute;f&eacute;rences dans les interfaces en langage naturel est le grand nombre d'ambiguit&eacute;s que g&eacute;n&eacute;re un pronom du point de vue de la recherche d'ant&eacute;c&eacute;dent. dans cet article, nous allons montrer comment l'utilisation de crit&eacute;res issus d'&eacute;tudes de psychologie exp&eacute;rimentale sur des m&eacute;thodes de construction d'un discours par des locuteurs peut apporter un plus pour r&eacute;soudre ce probl&egrave;me. nous pr&eacute;sentons tout d'abord des r&eacute;sultats de tests faits par des psychologues autour de la notion de th&egrave;me et de repr&eacute;sentation interne du discours; puis, nous utilisons ces r&eacute;sultats pour &eacute;noncer un certain nombre de crit&egrave;res pragmatiques concernant la recherche d'ant&eacute;c&eacute;dents. nous montrons enfin que ces crit&egrave;res, tout &eacute;tant concis et facilement programmables, sont assez g&eacute;n&eacute;raux au regard de ceux pr&eacute;sent&eacute;s dans des cadres similaires.
learning verb argument structure from minimally annotated corpora. in this paper we investigate the task of automatically identifying the correct argument structure for a set of verbs. the argument structure of a verb allows us to predict the relationship between the syntactic arguments of a verb and their role in the underlying lexical semantics of the verb. following the method described in (merlo and stevenson, 2001), we exploit the distributions of some selected features from the local context of a verb. these features were extracted from a 23m word wsj corpus based on part-of-speech tags and phrasal chunks alone. we constructed several decision tree classifiers trained on this data. the best performing classifier achieved an error rate of 33.4%. this work shows that a subcategorization frame (sf) learning algorithm previously applied to czech (sarkar and zeman, 2000) is used to extract sfs in english. the extracted sfs are evaluated by classifying verbs into verb alternation classes.
machine translation: the languages network (versus the intermediate language). jonathan slocum/slocum, 1985/ divides mt techniques from a linguistic point of view into three two-way perspectives which are not quite disjunct: "direct versus indirect; interlingua versus transfer; and local versus global scope.".in this paper we present a research paradigm which, in fact, does not exactly match any of these perspectives: the languages network. in this paradigm each pair of languages will be treated as within a transfer application but with the characteristics of indirect translation: analysis of the source language and synthesis of the target language are not totally dependent on each other.the proces must be split up into a large number of pieces which can be connected into a huge network performing mt from and into several languages.implementations of this paradigm are being carried out by the author by means of the translator generator sygmart (see/chauch&eacute;/, chauch&eacute;, 1974/ and/rolf, 1985/), which permits the linguist to implement whatever he wants in the field of mt in an efficient way on a wide range of computers (from atari1040stf via sun's to ibm vm/gms mainframes).
automatic extraction of subcategorization frames for czech. we present some novel machine learning techniques for the identification of subcategorization information for verbs in czech. we compare three different statistical techniques applied to this problem. we show how the learning algorithm can be used to discover previously unknown subcategorization frames from the czech prague dependency treebank. the algorithm can then be used to label dependents of a verb in the czech treebank as either arguments or adjuncts. using our techniques, we are able to achieve 88% precision on unseen parsed text.
derivation of underlying valency frames from a learner's dictionary. the authors collect lexical data for a module of english syntactic analysis in the context of a bilingual research project. the computer usable version of oald (hornby, 1974) is used as the primary source. the main focus is on the structure and derivation of valency frames for verbal entries in the target lexicon, illustration of the complex relation between oald's verb subcategorization codes and the target complementation paradigms is provided, and an approach to the derivation procedure design suggested.
a new strategy for providing definitions in task-oriented dialogues. definitions may be made up of one or more components, which correspond to strategic predicates. the selection of which components to use in giving a definition in a task-oriented dialogue depends heavily on the needs of the user. the selection strategy we present involves weighting possible strategic predicates and the propositions used to fill them at multiple points throughout an ongoing dialogue and at the actual time of giving the definition. weighting will be influenced by a model of the user's domain knowledge, task-related plans and goals, and receptivity to the different kinds of information that could be presented. an utterance can then be produced that incorporates the most important information while adhering to common rhetorical practices.
lexical semantics in human-computer communication. most linguistic studies of human-computer communication have focused on the issues of syntax and discourse structure. however, another interesting and important area is the lexical semantics of command laguages. the names that users and system designers give the objects and actions of a computer system can greatly affect its usability, and the lexical issues involved are as complicated as those in natural languages. this paper presents an overview of the various studies of naming in computer systems, examining such issues as suggestiveness, memorability, descriptions of categories, and the use of non-words as names. a simple featural framework for the analysis of these phenomena is presented.
acquisition of a language computational model for nlp. this paper describes an approach to actively acquire a language computational model. the purpose of this acquisition is rapid development of nlp systems. the model is created with the syntax module of the boas knowledge elicitation system for a quick ramp up of a standard transfer-based machine translation system from l into english.
an xml-based document suite. we report about the current state of development of a document suite and its applications. this collection of tools for the flexible and robust processing of documents in german is based on the use of xml as unifying formalism for encoding input and output data as well as process information. it is organized in modules with limited responsibilities that can easily be combined into pipelines to solve complex tasks. strong emphasis is laid on a number of techniques to deal with lexical and conceptual gaps that are typical when starting a new application.
learning semantic-level information extraction rules by type-oriented ilp. this paper describes an approach to using semantic representations for learning information extraction (ie) rules by a type-oriented inductive logic programming (ilp) system. nlp components of a machine translation system are used to automatically generate semantic representations of text corpus that can be given directly to an ilp system. the latest experimental results show high precision and recall of the learned rules.
named entity chunking techniques in supervised learning for japanese named entity recognition. this paper focuses on the issue of named entity chunking in japanese named entity recognition. we apply the supervised decision list learning method to japanese named entity recognition. we also investigate and incorporate several named-entity noun phrase chunking techniques and experimentally evaluate and compare their performance. in addition, we propose a method for incorporating richer contextual information as well as patterns of constituent morphemes within a named entity, which have not been considered in previous research, and show that the proposed method outperforms these previous approaches.
sgs: a system for mechanical generation of japanese sentences. sgs is a compact sentence generation system. inputs are the frames and specifications of a sentence. programs attached to context free rules carry out the generation task. output is a surface sentence with an associated derivation tree.
ctm: an example-based translation aid system. this paper describes a japanese-english translation aid system, ctm, which has a useful capability for flexible retrieval of texts from bilingual corpora or translation databases. translation examples (pairs of a text and its translation equivalent) are very helpful for us to translate the similar text. our character-based best match retrieval method can retrieve translation examples similar to the given input. this method has the following advantages: (1) this method accepts free-style translation examples, i.e., pairs of any text string and its translation equivalent, (2) morphological analysis is unneccessary, (3) this method accepts free-style inputs (i.e., any text strings) for retrieval. we show the retrieval examples with the following characteristic features: phrasal expression, long-distance dependency, idiom, synonym, and semantic ambiguity.
toward memory-based translation. an essential problem of example-based translation is how to utilize more than one translation example for translating one source sentence.this paper proposes a method to solve this problem. we introduce the representation, called matching expression, which represents the combination of fragments of translation examples. the translation process consists of three steps: (1) make the source matching expression from the source sentence. (2) transfer the source matching expression into the target matching expression. (3) construct the target sentence from the target matching expression.this mechanism generates some candidates of translation. to select the best translation out of them, we define the score of a translation.
extracting word sequence correspondences with support vector machines. this paper proposes a learning and extracting method of word sequence correspondences from non-aligned parallel corpora with support vector machines, which have high ability of the generalization, rarely cause over-fit for training samples and can learn dependencies of features by using a kernel function. our method uses features for the translation model which use the translation dictionary, the number of words, part-of-speech, constituent words and neighbor words. experiment results in which japanese and english parallel corpora are used archived 81.1% precision rate and 69.0% recall rate of the extracted word sequence correspondences. this demonstrates that our method could reduce the cost for making translation dictionaries.
disambiguation by prioritized circumscription. this paper presents a method of resolving ambiguity by using a variant of circumscription, prioritized circumscription. in a disambiguation task, human seems to use various preferences which have various strength. in prioritized circumscription, we can express these preferences as defeasible constraints with various strength and we infer the most preferable logical models which satisfy stronger constraints as much as possible. this representation is very natural for disambiguation since we can regard a logical interprentation as a possible reading and the most preferable logical models as the most preferable readings. we argue that prioritized circumscription is another promising method for the task. we also discuss an implementation of prioritized circumscription by a hirarchical logic programming (hclp) language.
knowledge representation and machine translation. this paper describes a new knowledge representation called "frame knowledge representation-0" (fkr-0), and an experimental machine translation system named atlas/i which uses fkr-0.the purpose of fkr-0 is to stored information required for machine translation processing as flexibly as possible, and to make the translation system as expandable as possible.
stochastic lexicalized tree-adjoining grammars. the notion of stochastic lexicalized tree-adjoining grammar (sltag) is formally defined. the parameters of a sltag correspond to the probability of combining two structures each one associated with a word. the characteristics of sltag are unique and novel since it is lexieally sensitive (as n-gram models or hidden markov models) and yet hierarchical (as stochastic context-free grammars).then, two basic algorithms for sltag arc introduced: an algorithm for computing the probability of a sentence generated by a sltag and an inside-outside-like iterative algorithm for estimating the parameters of a sltag given a training corpus.finally, we should how sltag enables to define a lexicalized version of stochastic context-free grammars and we report preliminary experiments showing some of the advantages of sltag over stochastic context-free grammars.
parsing strategies with 'lexicalized' grammars: application to tree adjoining grammars. in this paper we present a general parsing strategy that arose from the development of an earley-type parsing algorithm for tags (schabes and joshi 1988) and from recent linguistic work in tags (abeille 1988).in our approach elementary structures are associated with their lexical heads. these structures specify extended domains of locality (as compared to a context-free grammar) over which constraints can be stated. these constraints either hold within the elementary structure itself or specify what other structures can be composed with a given elementary structure.we state the conditions under which context-free based grammars can be 'lexicalized' without changing the linguistic structures originally produced. we argue that even if one extends the domain of locality of cfgs to trees, using only substitution does not give the freedom to choose the head of each structure. we show how adjunction allows us to 'lexicalize' a cfg freely.we then show how a 'lexicalized' grammar naturally follows from the extended domain of locality of tags and present some of the linguistic advantages of our approach.a novel general parsing strategy for 'lexicalized' grammars is discussed. in a first stage, the parser builds a set structures corresponding to the input sentence and in a second stage, the sentence is parsed with respect to this set. the strategy is independent of the linguistic theory adopted and of the underlying grammar formalism. however, we focus our attention on tags. since the set of trees needed to parse an input sentence is supposed to be finite, the parser can use in principle any search strategy. thus, in particular, a top-down strategy can be used since problems due to recursive structures are eliminated. the parser is also able to use non-local information to guide the search.we then explain how the earley-type parser for tags can be modified to take advantage of this approach.
concurrent lexicalized dependency parsing: a behavioral view on parsetalk events. the behavioral specification of an object-oriented grammar model is considered. the model is based on full lexicalization, head-orientation via valency constraints and dependency relations, inheritance as a means for non-redundant lexicon specification, and concurrency of computation. the computation model relies upon the actors paradigm, with concurrency entering through asynchronous message passing between actors. in particular, we here elaborate on principles of how the global behavior of a lexically distributed grammar and its corresponding parser can be specified in terms of event type networks and event networks, resp.
idioms in the rosetta machine translation system. this paper discusses one of the problems of machine translation, namely the translation of idioms. the paper describes a solution to this problem within the theoretical framework of the rosetta machine translation system.rosetta is an experimental translation system which uses an intermediate language and translates between dutch, english and, in the future, spanish.
experiments in german noun chunking. the paper describes a method to process recursive noun phrases with finite-state cascades. it is shown that chunking of recursive noun phrases necessitates a readjustment of the finite-state cascades approach. in particular, the property of monotonicity must be given up. furthermore, the paper explores the influence of pos tags and online agreement checking on the overall performance.
semantic construction from parse forests. the paper describes a system which uses packed parser output directly to build semantic representations. more specifically, the system takes as input packed shared forests in the sense of tomita (tomita, 1985) and produces packed underspecified discourse representation structures. the algorithm visits every node in the parse forest only a bounded number of times, so that a significant increase in efficiency is registered for ambiguous sentences.
experiments in automated lexicon building for text searching. this paper describes experiments in the automatic construction of lexicons that would be useful in searching large document collections for text fragments that address a specific information need, such as an answer to a question.
generating multimodal output - conditions, advantages and problems. in natural communication situations, multimodel referent specification is frequent and efficient. the linguistic component are deictic expressions, e.g. 'this and 'here'. extralinguistic devices in dialogs are different body movements, mainly pointing gestures. their functional equivalent in texts are means like arrows and indices.this paper has two intentions. first, it discusses the advantages of multimodal reference in interhuman communication which motivate the integration of extralinguistic "pointing" devices into nl dialog systems. the generation of multimodal output poses specific problems, which have no counterpart in the analysis of multimodal input. the second part presents the strategy for generating multimodal output which has been developed within the framework of the xtra system (a nl access system to expert systems). xtra allows the combination of verbal descriptions and pointing gestures in order to specify elements of the given visual context, i.e. a form displayed on the screen. the component popel generates referential expressions which may be accompanied by a pointing gesture. the appearance of these gestures depends on several factors, e.g. the type of referent (whether it is a region or an entry of the form) and its complexity.
a generative probability model for unification-based grammars. a generative probability model for unification-based grammars is presented in which rule probabilities depend on the feature structure of the expanded constituent. the presented model is the first model which requires no normalization and allows the application of dynamic programming algorithms for disambiguation (viterbi) and training (inside-outside). another advantage is the small number of parameters.
lexicalization of probabilistic grammars. two general methods for the lexicalization of probabilistic grammars are presented which are modular, powerful and require only a small number of parameters. the first method multiplies the unlexicalized parse tree probability with the exponential of the mutual information terms of all word-governor pairs in the parse. the second lexicalization method accounts for the dependencies between the different arguments of a word. the model is based on a em clustering model with word classes and selectional restrictions as hidden features. this model is useful for finding word classes, selectional restrictions and word sense probabilities.
part-of-speech tagging with neural networks. text corpora which are tagged with part-of-speech information are useful in many areas of linguistic research. in this paper, a new part-of-speech tagging method based on neural networks (net-tagger) is presented and its performance is compared to that of a hmm-tagger (cutting et al., 1992) and a trigram-based tagger (kempe, 1993). it is shown that the net-tagger performs as well as the trigram-based tagger and better than the hmm-tagger.
robust german noun chunking with a probabilistic context-free grammar. we present a noun chunker for german which is based on a head-lexicalised probabilistic context-free grammar. a manually developed grammar was semi-automatically extended with robustness rules in order to allow parsing of unrestricted text. the model parameters were learned from unlabelled training data by a probabilistic context-free parser. for extracting noun chunks, the parser generates all possible noun chunk analyses, scores them with a novel algorithm which maximizes the best chunk sequence criterion, and chooses the most probable chunk sequence. an evaluation of the chunker on 2,140 hand-annotated noun chunks yielded 92% recall and 93% precision.
a syntactic description of german in a formalism designated for machine translation. this paper presents a syntactic description of a fragment of german that has been worked out within the machine translation project eurotra. it represents the syntactic part of the german module of this multilingual translation system. the linguistic tool for the following analyses is the so-called cat-framework.in the first two sections of this paper an introduction of the formalism and a linguistic characterization of the framework is given. the cat formalism as a whole is a theory of machine translation, the syntactic analysis part which is the subject of this paper is an lfg-like mapping of a constituent structure onto a functional structure.a third section develops principles for a phrase structure and a functional structure for german and the mapping of phrase structure onto functional structure.in a fourth section a treatment of unbounded movement phenomena is sketched. as the cat-framework does not provide any global mechanisms i try to give a local treatment of this problem.
lean formalisms, linguistic theory and applications. grammar development in alep. this paper describes results achieved in a project which addresses the issue of how the gap between unification-based grammars as a scientific concept and real world applications can be narrowed down1. application-oriented grammar development has to take into account the following parameters: efficiency: the project chose a so called 'lean' formalism, a term-encodable language providing efficient term unification, alep. coverage: the project adopted a corpus-based approach. completeness: all modules needed from text handling to semantics must be there. the paper reports on a text handling component, two level morphology, word structure, phrase structure, semantics and the interfaces between these components. mainstream approach: the approach claims to be mainstream, very much indebted to hpsg, thus based on the currently most prominent and recent linguistic theory. the relation (and tension) between these parameters are described in this paper.
parsing schemata for grammars with variable number and order of constituents. we define state transition grammars (stg) as an intermediate formalism between grammars and parsing algorithms which is intended to separate the description of a parsing strategy from the grammar formalism. this allows to define more general parsing algorithms for larger classes of grammars, including grammars where the number and order of subconstituents defined by a production may not be fixed. various grammar formalisms are characterized in terms of properties of stg's. we define an earley parsing schema for stg's and characterize the valid parse items. we also discuss the usability of stg's for head-corner parsing and direct parsing of sets of tree constraints.
concurrent parsing in programmable logic array (pla-) nets problems and proposals. this contribution attempts a conceptual and practical introduction into the principles of wiring or constructing special machines for language processing tasks instead of programming a universal machine. construction would in principle provide higher descriptive adequacy in computationally based linguistics. after all, our heads do not apply programs on stored symbol arrays but are appropriately wired for understanding or producing language.
the translation of constitutent structure grammars into connectionist networks. description of a connectionist implementation of an earley parser.
the semantics and syntax of russian pronominal structure: a feature breakdown. elaborating one of the points of his coling bonn 1986 paper, the author discusses pronominality, which is due to a special semantic stratum, singulative identificational deixis. personal, reflexive and interrogative pronouns have additional transmissional deictic markings, but singulative identificational pronominality alone has a direct anaphoric effect and tends to reinforce syntactically. this explains, for instance, german <u>sich selbst</u>.
realizing expressions of doubt in collaborative dialogue. one way to begin a negotiation subdialogue is to express doubt at a proposition. however, expressions of doubt occur in a variety of forms, each of which conveys information about the nature of the doubt that is important for the subsequent resolution of the conflict. this paper presents our work on realizing expressions of doubt appropriately in natural language dialogues.
on parsing preferences. it is argued that syntactic preference principles such as <u>right association</u> and <u>minimal attachment</u> are unsatisfactory as usually formulated. among the difficulties are: (1) dependence on ill-specified or implausible principles of parser operation; (2) dependence on questionable assumptions about syntax; (3) lack of provision, even in principle, for integration with semantic and pragmatic preference principles; and (4) apparent counterexamples, even when discounting (1)--(3). a possible approach to a solution is sketched.
implicitness as a guiding principle in machine translation. multilingual extensibility requires an mt system to have a language-independent pivot. it is argued that an ideal, purely semantic pivot is impossible. a translation method is described in which semantic relations are kept implicit in syntax, while the semantic and distinctions are implicit in the words of a full-fledged language used as pivot.
interleaved semantic interpretation in environment-based parsing. this paper extends a polynomial-time parsing algorithm that resolves structural ambiguity in input sentences by calculating and comparing the denotations of rival constituents, given some model of the application environment (schuler, 2001). the algorithm is extended to incorporate a full set of logical operators, including quantifiers and conjunctions, into this calculation without increasing the complexity of the overall algorithm beyond polynomial time, both in terms of the length of the input and the number of entities in the environment model.
anaphoric reference to events and actions: a representation and its advantages. this paper focuses on anaphora interpreted as referring to entities of type event and action. it considers two issues: (i) what aspects of the discourse give evidence of the events and the actions the speaker is talking about, and (ii) how actions and events are represented in the discourse in order to be able to refer to them anaphorically.
language without a central pushdown stack. we will attempt to show how human performance limitations on various types of syntactic embedding constructions in germanic languages can be modelled in a relational network linguistic framework. after arguing against centralized data stores such as pushdown stacks and queues, we will demonstrate how interconnections among levels of linguistic structure can account for many of the psycholinguistic facts.
antonymy and conceptual vectors. for meaning representations in nlp, we focus our attention on thematic aspects and conceptual vectors. the learning strategy of conceptual vectors relies on a morphosyntaxic analysis of human usage dictionary definitions linked to vector propagation. this analysis currently doesn't take into account negation phenomena. this work aims at studying the antonymy aspects of negation, in the larger goal of its integration into the thematic analysis. we present a model based on the idea of symmetry compatible with conceptual vectors. then, we define antonymy functions which allows the construction of an antonymous vector and the enumeration of its potentially antinomic lexical items. finally, we introduce a measure which evaluates how a given word is an acceptable antonym for a term.
sensitive parsing: error analysis and explanation in an intelligent language tutoring system. we present a uniform framework for dealing with errors in natural language sentences within the context of automated second language teaching. the idea is to use a feature grammar and to analyse errors as being sentences where features have other values than those they should have. by using a feature grammar it is possible to describe various types of errors (agreement, syntactic and semantic errors) in a uniform framework, to define in a clear and transparent way what an error is and - this is very important for our application - to analyse errors as arising form a misunderstanding or ignorance of grammatical rules on the part of students.
extending the expressive capacity of the semantic component of the opera system. opera is a natural language question answering system allowing the interrogation of a data base consisting of an extensive listing of operas. the linguistic front-end of opera is a comprehensive grammar of french, and its semantic component translates the syntactic analysis into logical formulas (first order logic formulas).however there are quite a fiew constructions which can be analysed syntactically in the grammar but for which we are unable to specify translations. foremost among these are anaphoric and elliptic contructions. thus this paper describes the extension of opera to anaphoric and elliptic constructions on the basis of the discourse representation theory (drt).
presentation of the eurolang project. international trade in general and particularly the single european market will bring about a considerable increase in the already huge documentation market. nlp products will contribute to improving the competitiveness of industry in this strategic field.the industrial objective of eurolang is thus to provide efficient nlp tools and to give the european business community a better opportunity to maintain a command of multilingual technical and commercial communication.the technical objective of the eurolang project is to build an mt/nlp toolbox, offering a wide range of 'open' and powerful tools, which reflect the state-of-the-art in computing and linguistic techniques. these tools will then be validated via the production of a multilingual mt system based on second generation principles.with respect to the computing aspects, the main technical choices are: portability, maintainability, openness, possibility of evolution and ergonomy. this implies the use of standard techniques and tools (unix, x11, motif, c, sql, sgml).the linguistic developments, based on a syntactico-semantic analysis, will follow an industrial methodology, implying formal linguistic specifications. the use of specialised languages will ensure a better separation between software and lingware, and thus better modularity. the three-phase translation process guarantees the multilingual aspect of the mt system.
a probabilistic method for analyzing japanese anaphora integrating zero pronoun detection and resolution. this paper proposes a method to analyze japanese anaphora, in which zero pronouns (omitted obligatory cases) are used to refer to preceding entities (antecedents). unlike the case of general coreference resolution, zero pronouns have to be detected prior to resolution because they are not expressed in discourse. our method integrates two probability parameters to perform zero pronoun detection and resolution in a single framework. the first parameter quantifies the degree to which a given case is a zero pronoun. the second parameter quantifies the degree to which a given entity is the antecedent for a detected zero pronoun. to compute these parameters efficiently, we use corpora with/without annotations of anaphoric relations. we show the effectiveness of our method by way of experiments.
machine translation based on nlg from xml-db. the purpose of this study is to propose a new method for machine translation. we have proceeded through with two projects for report generation (kittredge and polguere, 2000): weather forecast and monthly economic report to be produced in four languages: english, japanese, french, and german. their input data is stored in xml-db. we applied a three-stage pipelined architecture (reiter and dale, 2000), and each stage was implemented as xml transformation processes. we regard xml stored data as language-neutral intermediate form and employ the so-called 'sublanguage approach' (somers, 2000). the machine translation process is implemented via xml-db as a kind of interlingua approach instead of the conventional structure transfer approach.
japanese dependency analysis using a deterministic finite state transducer. a deterministic finite state transducer is a fast device for analyzing strings. it takes o(n) time to analyze a string of length n. in this paper, an application of this technique to japanese dependency analysis will be described. we achieved the speed at a small cost in accuracy. it takes about 0.17 millisecond to analyze one sentence (average length is 10 bunsetsu, based on pentiumiii 650mhz pc, linux) and we actually observed the analysis time to be proportional to the sentence length. the accuracy is about 81% even though very little lexical information is used. this is about 17% and 9% better than the default and a simple system, respectively. we believe the gap between our performance and the best current performance on the same task, about 7%, can be filled by introducing lexical or semantic information.
modeling topic coherence for speech recognition. statistical language models play a major role in current speech recognition systems. most of these models have focussed on relatively local interactions between words. recently, however, there have been several attempts to incorporate other knowledge sources, in particular longer-range word dependencies, in order to improve speech recognizers. we will present one such method, which tries to antomatically utilize properties of topic continuity. when a base-line speech recognition system generates alternative hypotheses for a sentence, we will utilize the word preferences based on topic coherence to select the best hypothesis. in our experiment, we achieved a 0.65% improvement in the word error rate on top of the base-line system. it corresponds to 10.40% of the possible word error improvement.
japanese named entity extraction evaluation - analysis of results. we will report on one of the two tasks in the irex (information retrieval and extraction exercise) project, an evaluation-based project for information retrieval and information extraction in japanese (sekine and isahara, 2000) (irex committee, 1999). the project started in 1998 and concluded in september 1999 with many participants and collaborators (45 groups in total from japan and the us). in this paper, the named entity (ne) task is reported. it is a task to extract ne's, such as names of organizations, persons, locations and artifacts, time expressions and numeric expressions from newspaper articles. first, we will explain the task and the definition, as well as the data we created and the results. second, the analyses of the results will be described, which include analysis of task difficulty across the ne types and system types, analysis of domain dependency and comparison to human performance.
backward beam search algorithm for dependency analysis of japanese. backward beam search for dependency analysis of japanese is proposed. as dependencies normally go from left to right in japanese, it is effective to analyze sentences backwards (from right to left). the analysis is based on a statistical method and employs a beam search strategy. based on experiments varying the beam search width, we found that the accuracy is not sensitive to the beam width and even the analysis with a beam width of 1 gets almost the same dependency accuracy as the best accuracy using a wider beam width. this suggested a deterministic algorithm for backwards japanese dependency analysis, although still the beam search is effective as the n-best sentence accuracy is quite high. the time of analysis is observed to be quadratic in the sentence length.
analysis of titles and readers for title generation centered on the readers. the title of a document has two roles, to give a compact summary and to lead the reader to read the document. conventional title generation focuses on finding key expressions from the author's wording in the document to give a compact summary and pays little attention to the reader's interest. to make the title play its second role properly, it is indispensable to clarify the content ("what to say") and wording ("how to say") of titles that are effective to attract the target reader's interest. in this article, we first identify typical content and wording of titles aimed at general readers in a comparative study between titles of technical papers and headlines rewritten for newspapers. next, we describe the results of a questionnaire survey on the effects of the content and wording of titles on the reader's interest. the survey of general and knowledgeable readers shows both common and different tendencies in interest.
soft display key for kanji input. the concept of a soft display key as applied to input of large character sets or vocabularies such as kanji, the ancient chinese ideographic script is discussed. the japanese orthography and the necessity of using kanji characters in data terminals are explained. problems arising from the number and complexity of kanji symbols for the manufacture and use of keyboard devices are stated. a review is made of devices and methods presently used or suggested. the feasibility of the soft display key is then demonstrated. some requirements for the design and implementation of a soft display keyboard for kanji are considered. in conclusion, implications to man/computer interface design, human factors engineering and hardware unification and standardization are stated.
on unl as the future "html of the linguistic content" & the reuse of existing nlp components in unl-related applications with the example of a unl-french deconverter. after 3 years of specifying the unl (universal networking language) language and prototyping deconverters from more than 12 languages and enconverters for about 4, the unl project has opened to the community by publishing the specifications (v2.0) of the unl language, intended to encode the meaning of nl utterances as semantic hypergraphs and to be used as a "pivot" representation in multilingual information and communication systems.a unl document is an html document with special tags to delimit the utterances and their rendering in unl and in all natural languages currently handled. unl can be viewed as the future "html of the linguistic content". it is only an interface format, leading as well to the reuse of existing nlp components as to the development of original tools in a variety of possible applications, from automatic rough enconversion for information retrieval and information gathering translation to partially interactive enconversion or deconversion for higher quality.we illustrate these points by describing an unl-french deconverter organized as a specific "localizer" followed by a classical mt transfer and an existing generator.
making sense of reference to the unfamiliar? computational approaches to reference resolution, like centering theory, are best at resolving referring expressions which denote familiar referents. we demonstrate how, by taking a proof-theoretic approach to reference resolution within a centering-type framework, we are able to make sense of referring expressions for unfamiliar referents. these include, in addition to bridging descriptions, definite descriptions like "the first man" and "the first snowdrops of spring". we claim that the first of these denotes a unique subset of a plural discourse antecedent. while the second has no discourse antecedent, we similarly treat it as denoting a unique subset of a familiar referent.
natural language understanding and the perspectives of question answering. a method of automatic answering of questions in natural language, based only on input texts and a set of rules of inference, is described. a first experimental system including a grammatico-semantic analysis of the input texts and questions, a procedure of inferencing, a search for appropriate answers to individual questions and a synthesis of the answers are being implemented, mainly in the language q and pl/1. the output of the analysis, the underlying representations of the utterances of the input text, serves as a base of the knowledge representation scheme, on which the inference rules (mapping dependency trees into dependency trees) operate.
the simple core and the complex periphery of natural language - a formal and a computational view. a complex procedure of syntactic annotation of a large text corpus may be helpful in checking a rich descriptive framework (the praguian functional generative description) that makes it possible to distinguish between the core of natural language, structured in a relatively simple way, and its large periphery with indistinct borderlines. such a procedure underlies the prague dependency treebank, within which about 20 000 czech sentences from running texts have been analyzed in their underlying structure; for 2000 sentences also their topic-focus structures have been specified. we illustrate the wide range of the phenomena handled, i.e. the syntactic relations proper (arguments and adjuncts), coordination, topic-focus articulation, word order, deletion, positions of focusing particles, morphological categories such as number, tense, modality, their morphemic and analytical means of expression, and so on.
gtt: a general transducer for teaching computational linguistics. the gtt-system is a tree-to-tree transducer developed for teaching purposes in machine translation. the transducer is a specialized production system giving the linguists the tools for expressing information in a syntax that is close to theoretical linguistics. major emphasis was placed on developing a system that is user friendly, uniform and legible. this paper describes the linguistic data structure, the rule formalism and the control facilities that the linguist is provided with.
a parametric nl translator. this report outlines a machine translation system whose linguistic component is based on principles of government and binding. a "universal grammar" is defined, together with parameters of variation for specific languages. the system, written in prolog, parses, generates, and translates between english and spanish (both directions).
a corpus-based analysis for the ordering of clause aggregation operators. to better understand the ordering of clause aggregation operators in a text generation application, we manually annotated a small corpus. the annotated corpus supports the preferred ordering of transformations that result in shorter surface expressions, such as adjectives over relative clauses. in addition, we were able to explain why paratactic operators are applied before and after hypotactic operators.
generation of paraphrases from ambiguous logical forms. this paper presents a method for generating multiple paraphrases from ambiguous logical forms. the method is based on a chart structure with edges indexed on semantic information and annotations that relate edges to the semantic facts they express. these annotations consist of logical expressions that identify particular realizations encoded in the chart. the method allows simultaneous generation from multiple interpretations, without hindering the generation process or causing any work to be superfluously duplicated.
the need for mt-oriented versions of case and valency in mt. this paper looks at the use in machine translation systems of the linguistic model of case and valency. it is argued that neither of these models was originally developed with this use in mind, and both must be adapted somewhat to meet this purpose. in particular, the traditional valency distinction of complements and adjuncts leads to conflicts when valency frames in different languages are compared: a finer but more flexible distinction is required. also, these concepts must be extended beyond the verb, to include the noun and adjective as valency bearers. as far as case is concerned, too narrow an approach has traditionally been taken: work in this field has been too conerned only with cases for arguments in verb frames; case label systems for non-valency bound elements and also for elements in nominal groups must be elaborated. the paper suggests an integrated approach specifically oriented towards the particular problems found in mt.
the design of a computer language for linguistic information. a considerable body of accumulated knowledge about the design of languages for communicating information to computers has been derived from the subfields of programming language design and semantics. it has been the goal of the patr group at sri to utilize a relevant portion of this knowledge in implementing tools to facilitate communication of linguistic information to computers. the patr-ii formalism is our current computer language for encoding linguistic information. this paper, a brief overview of that formalism, attempts to explicate our design decisions in terms of a set of properties that effective computer languages should incorporate.
a simple reconstruction of gpsg. like most linguistic theories, the theory of generalized phrase structure grammar (gpsg) has described language axiomatically, that is, as a set of universal and language-specific constraints on the well-formedness of linguistic elements of some sort. the coverage and detailed analysis of english grammar in the ambitious recent volume by gazdar, klein, pullum, and sag entitled generalized phrase structure grammar [2] are impressive, in part because of the complexity of the axiomatic system developed by the authors. in this paper. we examine the possibility that simpler descriptions of the same theory can be achieved through a slightly different, albeit still axiomatic, method, rither than characterize the well-formed trees directly, we progress in two stages by procedurally characterizing the well-formedness axioms themselves, which in turn characterize the trees.
machine translation without a source text. this paper concerns an approach to machine translation which differs from the typical 'standard' approaches crucially in that it does not rely on the prior existence of a source text as a basis of the translation. our approach can be characterised as an 'intelligent secretary with knowledge of the foreign language', which helps monolingual users to formulate the desired target-language text in the context of a (key-board) dialogue translation systems.
a uniform architecture for parsing and generation. the use of a single grammar for both parsing and generation is an idea with a certain elegance, the desirability of which several researchers have noted. in this paper, we discuss a more radical possibility: not only can a single grammar be used by different processes engaged in various "directions" of processing, but one and the same language-processing architecture can be used for processing the grammar in the various modes. in particular, parsing and generation can be viewed as two processes engaged in by a single parameterized theorem prover for the logical interpretation of the formalism. we discuss our current implementation of such an architecture, which is parameterized in such a way that it can be used for either purpose with grammars written in the patr formalism. furthermore, the architecture allows fine tuning to reflect different processing strategies, including parsing models intended to mimic psycholinguistic phenomena. this tuning allows the parsing system to operate within the same realm of efficiency as previous architectures for parsing alone, but with much greater flexibility for engaging in other processing regimes.
synchronous tree-adjoining grammars. the unique properties of tree-adjoining grammars (tag) present a challenge for the application of tags beyond the limited confines of syntax, for instance, to the task of semantic interpretation or automatic translation of natural language. we present a variant of tags, called synchronous tags, which characterize correspondences between languages. the formalism's intended usage is to relate expressions of natural languages to their associated semantics represented in a logical form language, or to their translates in another natural language; in summary, we intend it to allow tags to be used beyond their role in syntax proper. we discuss the application of synchronous tags to concrete examples, mentioning primarily in passing some computational issues that arise in its interpretation.
semantic interpretation using kl-one. this paper presents extensions to the work of bobrow and webber [bobrow & webber 80a, bobrow & webber 80b] on semantic interpretation using kl-one to represent knowledge. the approach is based on an extended case frame formalism applicable to all types of phrases, not just clauses. the frames are used to recognize semantically acceptable phrases, identify their structure, and, relate them to their meaning representation through translation rules. approaches are presented for generating kl-one structures as the meaning of a sentence, for capturing semantic generalizations through abstract case frames, and for handling pronouns and relative clauses.
automatic corpus-based thai word extraction with the c4.5 learning algorithm. "word" is difficult to define in the languages that do not exhibit explicit word boundary, such as thai. traditional methods on defining words for this kind of languages have to depend on human judgement which bases on unclear criteria or procedures, and have several limitations. this paper proposes an algorithm for word extraction from thai texts without borrowing a hand from word segmentation. we employ the c4.5 learning algorithm for this task. several attributes such as string length, frequency, mutual information and entropy are chosen for word/non-word determination. our experiment yields high precision results about 85% in both training and test corpus.
mach : a supersonic korean morphological analyzer. this paper introduces a supersonic korean morphological analyzer named mach. it analyzes a 1 gb document within 5 minutes on a typical personal computer with a 1 ghz pentium iii cpu. this means that it analyzes about 500,000 words per second. in fact, the analysis speed of mach is 12-20 times faster than the most famous korean morphological analyzers. in spite of its supersonic speed, the analysis accuracy of mach is not degraded at all, compared with any other korean morphological analyzers.
classifier assignment by corpus-based approach. this paper presents an algorithm for selecting an appropriate classifier word for a noun. in thai language, it frequently happens that there is fluctuation in the choice of classifier for a given concrete noun, both from the point of view of the whole speech community and individual speakers. basically, there is no exact rule for classifier selection. as far as we can do in the rule-based approach is to give a default rule to pick up a corresponding classifier of each noun. registration of classifier for each noun is limited to the type of unit classifier because other types are open due to the meaning of representation. we propose a corpus-based method (biber, 1993; nagao, 1993; smadja, 1993) which generates noun classifier associations (nca) to overcome the problems in classifier assignment and semantic construction of noun phrase. the nca is created statistically from a large corpus and recomposed under concept hierarchy constraints and frequency of occurrences.
japanese sentence analysis as argumentation. this paper proposes that sentence analysis should be treated as defeasible reasoning, and presents such a treatment for japanese sentence analyses using an argumentation system by konolige, which is a formalization of defeasible reasoning, that includes arguments and defeat rules that capture defeasibility.
the automatic extraction of open compounds from text corpora. this paper describes a new method for extracting open compounds (uninterrupted sequences of words) from text corpora of languages, such as thai, japanese and korea that exhibit unexplicit word segmentation. without applying word segmentation techniques to the inputted plain text, we generate n-gram data from it. we then count the occurence of each string and sort them in alphabetical order. it is significant that the frequency of occurrence of strings decreases when the window size of observation is extended. from the statistical point of view, a word is a string with a fixed pattern that is used repeatedly, meaning that it should occur with a higher frequency than a string that is not a word. we observe the variation of frequency of the sorted n-gram data and extract the strings that experience a significant change in frequency of occurrence when their length is extended. we apply this occurrence test to both the right and left hand sides of all strings to ensure the accurate detection of both boundaries of the string. the method returned satisfying results regardless of the size of the input file.
design tool combining keyword analyzer and case-based parser for developing natural language database interfaces. we have designed and experimentally implemented a tool for developing a natural language systems that can accept extra-grammatical expressions, keyword sequences, and linguistic fragments, as well as ordinary natural language queries. the key to this tool's efficiency is its effective use of a simple keyword analyzer in combination with a conventional case-based parser. the keyword analyzer performs a majority of those queries which are simple data retrievals. since it uses only keywords in any query, this analyzer is robust with regard to extra-grammatical expressions. since little labor is required of the application designer in using the keyword analyzer portion of the tool, and since the case-based parser processes only those queries which the keyword analyzer fails to interpret, total labor required of the designer is less than that for a tool which employs a conventional case-based parser alone.
representing knowledge about knowledge and mutual knowledge. in order to represent speech acts, in a multi-agent context, we choose a knowledge representation based on the modal logic of knowledge kt4 which is defined by sato. such a formalism allows us to reason about knowledge and represent knowledge about knowledge, the notions of truth value and of definite reference.
multi-modal definite clause grammar. this paper describes the first reported grammatical framework for a multimodal interface. although multimodal interfaces offer the promise of a flexible and user friendly means of human-computer interaction, no study has yet appeared on formal grammatical frameworks for them. we have developed multi-modal definite clause grammar (mm-dcg), an extension of definite clause grammar. the major features of mm-dcg include capability to handle an arbitrary number of modes and temporal information in grammar rules. further, we have developed mm-dcg translator to transfer rules in mm-dcg into prolog predicates.
explanatory text planning in logic based systems. this paper discusses aspects of the planning of explanatory texts for logic based systems. it presents a method for deriving natural language text plans from natural deduction-based structures. this approach allows for the planning of explanatory texts in a general-purpose logic based system framework, ensuring a greater degree of portability across domains.
multi-modal-method: a design method for building multi-modal systems. this paper describes multi-modal-method, a design method for building grammar-based multi modal systems. multi-modal-method defines the procedure which interface designers may follow in developing multi-modal systems, and provides mm-dcg, a grammatical framework for multi-modal input interpretation. multi-modal-method has been inductively defined through several experimental multi-modal interface system developments. a case study of a multi-modal drawing tool development along with multi-modal-method is reported.
a dutch to sql database interface using generalized quantifier theory. this paper presents the treatment of quantification as it was implemented in a prototype of a natural language relational database interface for dutch. it is shown how the theoretical 'generalized quantifier' apparatus introduced in formal semantics by barwise and cooper can be tuned to implementational feasibility. compared to the traditional treatment of quantification, the alternative presented here offers greater expressive power, greater similarity to natural language and, as a consequence, the possibility of a more straightforward translation from natural language to formal representation.
understanding of stories for animation. this paper presents the story understanding mechanism for creating computer animation scenarios. the story understanding mechanism reads a natural language story and creates its scenario for realistic graphic animations. this paper presents three types of hidden actions and relations of actions that must be discovered for realistic animations of stories but which are not explicitly described in the stories. they are: 1) causality check among actions; 2) interpolation of a continuous action beyond a sentence; 3) interpolation of hidden actions between neighboring sentences. this paper also describes the inference mechanism which recognizes the need for interpolation of these hidden actions. multiple tms is introduced in the mechanism. the knowledge base is action-oriented, hence it is independent of individual stories domains.
processing self corrections in a speech to speech system. speech repairs occur often in spontaneous spoken dialogues. the ability to detect and correct those repairs is necessary for any spoken language system. we present a framework to detect and correct speech repairs where all relevant levels of information, i. e., acoustics, lexis, syntax and semantics can be integrated. the basic idea is to reduce the search space for repairs as soon as possible by cascading filters that involve more and more features. at first an acoustic module generates hypotheses about the existence of a repair. second a stochastic model suggests a correction for every hypothesis. well scored corrections are inserted as new paths in the word lattice. finally a lattice parser decides on accepting the repair.
an empirical method for identifying and translating technical terminology. this paper describes a method for retrieving patterns of words and expressions frequently used in a specific domain and building a dictionary for machine translation (mt). the method uses an untagged text corpus in retrieving word sequences and simplified part-of-speech templates in identifying their syntactic categories. the paper presents experimental results for applying the words and expressions to a pattern-based machine translation system.
a tagger/lemmatiser for dutch medical language. in this paper, we want to describe a tagger/lemmatiser for dutch medical vocabulary, which consists of a full-form dictionary and a morphological recogniser for unknown vocabulary coupled to an expert system-like disambiguation module. attention is also paid to the main datastructures: a lexical database and feature bundles implemented as directed acyclic graphs. some evaluation results are presented as well. the tagger/lemmatiser currently functions as a lexical front-end for a syntactic parser. for pure tagging/lemmatising purposes, a reduced tagset (not suited for sentence analysis) can be used as well.
applying and improving the restriction grammar approach for dutch patient discharge summaries. this paper starts by giving a short overview of one existing nlp project for the medical sublanguage (1). after having presented our objectives (2), we will describe the restriction grammar formalism (3), the datastructure we use for parsing (4) and our parser (5) enhanced with a special control structure (6). an attempt to build a bootstrap dictionary of medical terminology in a semi-automatic way will also be discussed (7). a brief evaluation (8) and a short outline of our future research (9) will conclude this article.
text genre detection using common word frequencies. in this paper we present a method for detecting the text genre quickly and easily following an approach originally proposed in authorship attribution studies which uses as style markers the frequencies of occurrence of the most frequent words in a training corpus (burrows, 1992). in contrast to this approach we use the frequencies of occurrence of the most frequent words of the entire written language. using as testing ground a part of the wall street journal corpus, we show that the most frequent words of the british national corpus, representing the most frequent words of the written english language, are more reliable discriminators of text genre in comparison to the most frequent words of the training corpus. moreover, the frequencies of occurrence of the most common punctuation marks play an important role in terms of accurate text categorization as well as when dealing with training data of limited size.
lexicase parsing: a lexicon-driven approach to syntactic analysis. this paper presents a lexicon-based approach to syntactic analysis, lexicase, and applies it to a lexicon-driven computational parsing system. the basic descriptive mechanism in a lexicase grammar is lexical features. the properties of lexical items are represented by contextual and non-contextual features, and generalizations are expressed as relationships among sets of these features and among sets of lexical entries. syntactic tree structures are representaed as notworks of pairwise dependency relationships among the words in a sentence. possible dependencies are marked as contextual features on individual lexical items, and lexicase parsing is a process of picking out words in a string and attaching dependents to them in accordance with their contextual features. lexicase is an appropriate vehicle for parsing because lexicase analyses are monostratal, flat, and relatively non-abstract, and it is well suited to machine translation because grammatical representations for corresponding sentences in two languages will be very similar to each other in structure and inter-constituent relations, and thus far easier to interconvert.
linguistic knowledge extraction from real language behavior. an approach to extract linguistic knowledge from real language behavior is described. this method depends on the extraction of word relations, patterns of which are obtained by structuring the dependency relations in sentences called kakari-uke relation in japanese. as the first step of this approach, an experiment of a word classification utilizing those patterns was made on the 4178 sentences of real language data. a system was made to analyze dependency structure of sentences utilizing the knowledge base obtained through this word classification and the effectiveness of the knowledge base was evaluated. to develop this approach further, the relation matrix which captures multiple interaction of words is proposed.
polibox: generating descriptions, comparisons, and recommendations from a database. we describe our ongoing work on "polibox", a web-based text generator producing adaptive hypertext from a product database, currently one of computational linguistics text-books. when given a specification of a desired ideal book, polibox selects suitable candidates from the database, and presents them one-by-one to the user. books are described, compared to one another, and, under the right circumstances, actively recommended. this project note concentrates on the stages of content selection, text planning and sentence planning.
talisman: un système multi-agents gouverné par des lois linguistiques pour le traitement de la langue naturelle. natural language processing raises the problem of ambiguities and multiple solutions which follow from them. the knowledge gained when using the morphosyntactic analyser crisstal showed how necessary it was to overcome this issue. the architecture with sequential levels, in which each module corresponds to a linguistic level (pretreatments, morphology, syntax, semantics) has shown its limits. a sequential architecture does not allow a real exchange between different modules. this leads to the non availability of the linguistic information for the reduction of ambiguities, at the moment they are needed.the necessity for cooperation between different modules has lead us to envisage a new architecture which stems from the techniques of distributed artificial intelligence.the paper presents this new architecture which based on distributed artificial intelligence techniques treats the inherent problems of natural language processing. one of the originalities resides in the distributed treatment of sentence analysis (as apposed to a classic sequential treatment) and in the introduction of linguistic laws which allow the management of the communication between agents, without appealing to a central control. the talisman system is an environment which integrates linguistic tools where different agents can bring into use different methods such as symbolic and/or statistic ones.the talisman system contributes to the following points in the linguistic domain:&bull;the restriction of ambiguities by agent cooperation,&bull;rendering structures less complex by using local grammar rules,&bull;the treatment of uncertain information.it can:&bull;function with partial analyses at different classical levels of analysis,&bull;change strategies according to the applications or the corpus used,&bull;use linguistic laws which are easily modifiable.at the implementation level, the system brings openess to the modification of dictionaries, grammars and strategies of analysis, and the necessary mechanisms for the integration of new modules.talisman is a linguistic environment based on the most recent techniques used in software engineering environments. it provides mechanisms for data and control integration of linguistic tools.this paper is organized as follows. after a short overview in section 2 about the problems of sequential architectures, we establish the main objectives of our work in section 3. we present, in section 4, the contribution of multi-agents systems "governed by laws". in section 5, we define the structure of an agent and of its society. the implementation is presented in section 6.
distributedness and non-linearity of lolita's semantic network. this paper describes semnet the internal knowledge representation for lolita. lolita is a large scale natural language engineering (nle) system. as such the internal representation must be richly expressive, natural (with respect to natural language), and efficient. in network representations knowledge is gleaned by traversing the graph. the paper introduces two properties, (distributedness and non-linearity) of networks which directly relate to the efficiency by which knowledge is obtained. semnet is shown to have the specified properties thus distinguishing it (in terms of efficiency) as a suitable representation for large scale nle.
a distributed architecture for text analysis in french: an application to complex linguistic phenomena processing. most natural language processing systems use a sequential architecture embodying classical linguistic layers. when one works with a general language and not a sublanguage, there are different cases of ambiguities at different classical levels; and more particularly when one works on complex language phenomena analysis (coordination, ellipsis, negation...) it is difficult to take into account all the different types of these constructions with a general grammar. indeed, the inconvenience of this approach is the possible risk of a combinatory explosion. so we have defined the talisman architecture that includes linguistic agents that correspond either to classical levels in linguistics (morphology, syntax, semantic) or to complex language phenomena analysis.
morphological aspect of japanese language processing. a comprehensive grammatical model produced for analyzing the agglutinated structure which characterizes the japanese language is presented. this model, which includes extensively idiomatic postpositional expressions as terminals, is quite effective for the development of the japanese language processor receptive to a reasonable variety of sentential forms and applicable to relatively wide fields.
parsing german. the first part of this paper is dedicated to an overview of the parser of the system vie-lang (viennese language understanding system). the parser is a production system which uses an interleaved method that combines syntax and semantics. it parses directly into the internal representation of the system, without producing an intermediate syntactic structure. the last part discusses the relationship between some special features of the german language, and properties of the parser that originate in the language.
content characterization using word shape tokens. by quickly classifying character images into character shape categories, it is possible to automatically extract syntactic information from the text of document images without optical character recognition. using word shape tokens composed of these character shape codes, a properly trained text tagger can extract part-of-speech information from scanned document images. later components of a document processing system can then use this information to locate topics, characterize document style, and assist in information retrieval.
treating 'free word order' in machine translation. in free word order languages, every sentence is embedded in its specific context. the order of constituents is determined by the categories theme, rheme and contraslive focus. this paper shows how to recognise and to translate these categories automatically on a sentential basis, so that sentence embedding can be achieved without having to refer to the context. traditionally neglected modifier classes are fully covered by the proposed method.
directing the generation of living space description. we have developed a computational model of the process of describing the layout of an apartment or house, a much-studied discourse task first characterized linguistically by linde (1974). the model is embodied in a program, apt, that can reproduce segments of actual tape-recorded descriptions, using organizational and discourse strategies derived through analysis of our corpus.
a dynamic language model based on individual word domains. we present a new statistical language model based on a combination of individual word language models. each word model is built from an individual corpus which is formed by extracting those subsets of the entire training corpus which contain that significant word. we also present a novel way of combining language models called the "union model", based on a logical union of intersections, and use this to combine the language models obtained for the significant words from a cache. the initial results with the new model provide a 20% reduction in language model perplexity over the standard 3-gram approach.
on the semantics of focus phenomena in eurotra. in this paper, we discuss issues connected to the phenomenon of linguistic focus or information distribution in the sentence in the context of the multi-lingual machine translation project eurotra. we shall present some of the arguments why a consideration of focus phenomena is important for the determination of linear order and for semantic interpretation. we shall proceed, in sections 2 and 3 of the paper, to mention the main lines of development in the dicussion of focus phenomena in computational linguistics and in linguistics respectively. section 4 contains an illustration of a pilot implementation covering some aspects of focus phenomena in eurotra-d.
extracting semantic clusters from the alignment of definitions. through the alignment of definitions from two or more different sources, it is possible to retrieve pairs of words that can be used indistinguishably in the same sentence without changing the meaning of the concept. as lexicographic work exploits common defining schemes, such as genus and differentia, a concept is similarly defined by different dictionaries. the difference in words used between two lexicographic sources lets us extend the lexical knowledge base, so that clustering is available through merging two or more dictionaries into a single database and then using an appropriate alignment technique. since alignment starts from the same entry of two dictionaries, clustering is faster than any other technique.the algorithm introduced here is analogy-based, and starts from calculating the levenshtein distance, which is a variation of the edit distance, and allows us to align the definitions. as a measure of similarity, the concept of longest collocation couple is introduced, which is the basis of clustering similar words. the process iterates, replacing similar pairs of words in the definitions until no new clusters are found.
augmenting noun taxonomies by combining lexical similarity metrics. this paper presents a method for augmenting taxonomies with domain information using a simple combination of three existing lexical similarity metrics. the combined approach is evaluated by comparing their results against the annotated semcor corpus. an implementation is described in which wordnet is augmented with thesaural information from the cide+ machine readable dictionary.
computer simulation of spontaneous speech production. this paper pinpoints some of the problems faced when a computer text production model (commentator) is to produce spontaneous speech, in particular the problem of chunking the utterances in order to get natural prosodic units. the paper proposes a buffer model which allows the accumulation and delay of phonetic material until a chunk of the desired size has been built up. several phonetic studies have suggested a similar temporary storage in order to explain intonation slopes, rythmical patterns, speech errors and speech disorders. small-scale simulations of the whole verbalization process from perception and thought to sounds, hesitation behaviour, pausing, speech errors, sound changes and speech disorders are presented.
automatic lexical acquisition based on statistical distributions. we automatically classify verbs into lexical semantic classes, based on distributions of indicators of verb alternations, extracted from a very large annotated corpus. we address a problem which is particularly difficult because the verb classes, although semantically different, show similar surface syntactic behavior. five grammatical features are sufficient to reduce error rate by more than 50% over chance: we achieve almost 70% accuracy in a task whose baseline performance is 34%, and whose expert-based upper bound we calculated at 86.5%. we conclude that corpus-driven extraction of grammatical features is a promising methodology for find-grained verb classification.
island parsing and bidirectional charts. chart parsing is directional in the sense that it works from the starting point (usually the beginning of the sentence) extending its activity usually in a rightward manner. we shall introduce the concept of a chart that works outward from islands and makes sense of as much of the sentence as it is actually possible, and after that will lead to predictions of missing fragments. so, for any place where the easily identifiable fragments occur in the sentence, the process will extend to both the left and the right of the islands, until possibly completely missing fragments are reached. at that point, by virtue of the fact that both a left and a right context were found, heuristics can be introduced that predict the nature of the missing fragments.
unifying disjunctive feature structures. this paper describes an algorithm for unifying disjunctive feature structures. unlike previous algorithms, except eisele & d&ouml;rre (1990), this algorithm is as fast as an algorithm without disjunction when disjunctions do not participate in the unification, it is also as fast as an algorithm handling only local disjunctions when there are only local disjunctions, and expensive only in the case of unifying full disjunction. the description is given in the framework of graph unification algorithms which makes it easy to implement as an extension of such an algorithm.
intex: a corpus processing system. intex is a text processor; it is usually used to parse corpora of several megabytes. it includes several built-in large coverage dictionaries and grammars represented by graphs; the user may add his/her own dictionaries and grammars. these tools are applied to texts in order to locate lexical and syntactic patterns, remove ambiguities, and tag words. intex builds concordances and indexes of all types of patterns; it is used by linguists to analyse corpora, but can also be viewed as an information retrieval system.
achieving flexibility in unification formalisms. we argue that flexibility is an important property for unification-based formalisms. by flexibility we mean the ability for the user to modify and extend the formalism according to the needs of his problem. the paper discusses some properties necessary to achieve a flexible formalism and presents the fluf formalism as a realization of these ideas.
computational complexity of probabilistic disambiguation by means of tree-grammars. this paper studies the computational complexity of disambiguation under probabilistic tree-grammars as in (bod, 1992; schabes and waters, 1993). it presents a proof that the following problems are np-hard: computing the most probable parse from a sentence or from a word-graph, and computing the most probable sentence (mps) from a word-graph. the np-hardness of computing the mps from a word-graph also holds for stochastic context-free grammars (scfgs).
an approach to non-singular terms in discourse. a new theory of names and descriptions that offers a uniform treatment for many types of non-singular concepts found in natural language discourse is presented. we introduce a layered model of the language denotational base (the universe) in which every world object is assigned a layer (level) reflecting its relative singularity with respect in other objects in the universe. we define the notion of relative singularity of world objects as an abstraction class of the layermembership relation
the costs of inheritance in semantic networks. questioning texts represented in semantic relations1 requires the recognition that synonyms, instances, and hyponyms may all satisfy a questioned term. a basic procedure for accomplishing such loose matching using inheritance from a taxonomic organization of the dictionary is defined in analogy with the unification algorithm used for theorem proving, and the costs of its application are analyzed. it is concluded that inheritance logic can profitably be included in the basic questioning procedure.
how to invert a natural language parser into an efficient generator: an algorithm for logic grammars. the use of a single grammar in natural language parsing and generation is most desirable for variety of reasons including efficiency, perspicuity, integrity, robustness, and a certain amount of elegance. in this paper we present an algorithm for automated inversion of a prolog-coded unification parser into an efficient unification generator, using the collections of minimal sets of essential arguments (msea) for predicates. the algorithm is also applicable to more abstract systems for writing logic grammars, such as dcg.
ttp: a fast and robust parser for natural language. in this paper we describe ttp, a fast and robust natural language parser which can analyze written text and generate regularized parse structures for sentences and phrases at the speed of approximately 0.5 sec/sentence, or 44 word per second. the parser is based on a wide coverage grammar for english, developed by the new york university's linguistic string project, and it uses the machine-readable version of the oxford advanced learner's dictionary as a source of its basic vocabulary. the parser operates on stochastically tagged text, and contains a powerful skip-and-fit recovery mechanism that allows it to deal with extra-grammatical input and to operate effectively under a severe time pressure. empirical experiments, testing parser's speed and accuracy, were performed on several collections: a collection of technical abstracts (cacm-3204), a corpus of news messages (muc-3), a selection from acm computer library database, and a collection of wall street journal articles, approximately 50 million words in total.
how to deal with ambiguities while parsing: exam - a semantic processing system for japanese language. it is difficult for a natural language understanding system (nlus) to deal with ambiguities. there is a dilemma: an nlus must be able to produce plausible interpretations for given sentences, avoiding the combinatorial explosion of possible interpretations. furthermore, it is desirable for an nlus to produce several interpretations if they are equally plausible. exam, the system described in this paper, is an experimental text understanding system designed to deal with ambiguities effectively and efficiently.
syntactic constraints on relativization in japanese. this paper discusses the formalization of relative clauses in japanese based on jpsg framework. we characterize them as adjuncts to nouns, and formalize them in terms of constraints among grammatical features. furthermore, we claim that there is a constraint on the number of slash elements and show the supporting facts.
a self-learning universal concept spotter. we describe the universal spotter, a system for identifying in-text references to entities of an arbitrary, user-specified type, such as people, organizations, equipment, products, materials, etc. starting with some initial seed examples, and a training text corpus, the system generates rules that will find further concepts of the same type. the initial seed information is provided by the user in the form of a typical lexical context in which the entities to be spotted occur, e.g., "the name ends with co.", or "to the right of produced or made", and so forth, or by simply supplying examples of the concept itself, e.g., ford taurus, gas turbine, big mac. in addition, negative examples can be supplied, if known. given a sufficiently large training corpus, an unsupervised learning process is initiated in which the system will: (1) find instances of the sought-after concept using the seed-context information while maximizing recall and precision; (2) find additional contexts in which these entities occur; and (3) expand the initial seed-context with selected new contexts to find even more entities. preliminary results of creating spotters for organizations and products are discussed.
anaphor resolution and the scope of syntactic constraints. an anaphor resolution algorithm is presented which relies on a combination of strategies for narrowing down and selecting from antecedent sets for reflexive pronouns, nonreflexive pronouns, and common nouns. the work focuses on syntactic restrictions which are derived from chomsky's binding theory. it is discussed how these constraints can be incorporated adequately in an anaphor resolution algorithm. moreover, by showing that pragmatic inferences may be necessary, the limits of syntactic restrictions are elucidated.
concept analysis and terminology: a knowledge-based approach to documentation. the central concern of terminology, a component of the general documentation process, is concept analysis, an activity which is becoming recognized as fundamental as term banks evolve into knowledge bases. we propose that concept analysis can be facilitated by knowledge engineering technology, and describe a generic knowledge acquisition tool called code (conceptually oriented design environment) that has been successfully used in two terminology applications: 1) a bilingual vocabulary project with the terminology directorate of the secretary of state of canada, and 2) a software documentation project with bell northern research. we conclude with some implications of computer-assisted concept analysis for terminology.
a parsing architecture based on distributed memory machines. the paper begins by defining a class of distributed memory machines which have useful properties as retrieval and filtering devices. these memory mechanisms store large numbers of associations on a single composite vector. they provide a natural format for encoding the syntactic and semantic constraints associated with linguistic elements. a computational architecture for parsing natural language is proposed which utilises the retrieval and associative features of these devices. the parsing mechanism is based on the principles of lexical functional grammar and the paper demonstrates how these principles can be derived from the properties of the memory mechanisms.
a new quantitative quality measure for machine translation systems. in this paper, an objective quantitative quality measure is proposed to evaluate the performance of machine translation systems. the proposed method is to compare the raw translation output of an mt system with the final revised version for the customers, and then compute the editing efforts required to convert the raw translation to the final version. in contrast to the other proposals, the evaluation process can be done quickly and automatically. hence, it can provide a quick response on any system change. a system designer can thus quickly find the advantages or faults of a particular performance dynamically. application of such a measure to improve the system performance on-line on a parameterized and feedback-controlled system will be demonstrated. furthermore, because the revised version is used directly as a reference, the performance measure can reflect the real quality gap between the system performance and customer expectation. a system designer can thus concentrate on practically important topics rather than on theoretically interesting issues.
distributed memory: a basis for chart parsing. the properties of distributed representations and memory systems are explored as a potential basis for non-deterministic parsing mechanisms. the structure of a distributed chart parsing representation is outlined. such a representation encodes both immediate-dominance and terminal projection information on a single composite memory vector. a parsing architecture is described which uses a permanent store of context-free rule patterns encoded as split composite vectors, and two interacting working memory units. these latter two units encode vectors which correspond to the active and inactive edges of an active chart parsing scheme. this type of virtual parsing mechanism is compatible with both a macro-level implementation based on standard sequential processing and a micro-level implementation using a massively parallel architecture.
a maximum entropy-based word sense disambiguation system. in this paper, a supervised learning system of word sense disambiguation is presented. it is based on conditional maximum entropy models. this system acquires the linguistic knowledge from an annotated corpus and this knowledge is represented in the form of features. several types of features have been analyzed using the senseval-2 data for the spanish lexical sample task. such analysis shows that instead of training with the same kind of information for all words, each one is more effectively learned using a different set of features. this best-feature-selection is used to build some systems based on different maximum entropy classifiers, and a voting system helped by a knowledge-based method.
unbounded dependency: tying strings to rings. this paper outlines a framework for connectionist representation based on the composition of connectionist states under vector space operators. the framwork is used to specify a level of connectionist structure defined in terms of addressable superposition space hierarchies. direct and relative address systems can be defined for such structures which use the functional components of linguistic structures as labels. unbounded dependency phenomena are shown to be related to the different properties of these labelling structures.
computational analysis of mandarin sounds with reference to the english language. in the analysis of mandarin, the author used a corpus composed of over 750,000 samples transcribed automatically from chinese characters by the computer through the sequential application of a set of phonetic rules developed by the author. the result is a classification and rank distribution of all speech sounds, the phonetic properties, frequency distribution of symbols, phonemes, syllables, tones, and their combinations. these statistical properties are compared with those of the english language.
machine translation: its history, current status, and future prospects. elements of the history, state of the art, and probable future of machine translation (mt) are discussed. the treatment is largely tutorial, based on the assumption that this audience is, for the most part, ignorant of matters pertaining to translation in general, and mt in particular. the paper covers some of the major mt r&d groups, the general techniques they employ(ed), and the roles they play(ed) in the development of the field. the conclusions concern the seeming permanence of the translation problem, and potential re-integration of mt with mainstream computational linguistics.
japanese honorifics and situation semantics. a model of japanese honorific expressions in situation semantics is proposed. situation semantics provides considerable power for analyzing the complicated structure of japanese honorific expressions. the main feature of this model is a set of basic rules for context switching in honorific sentences. mizutani's theory of japanese honorifics is presented and incorporated in the model which has been used to develope an experimental system capable of analyzing honorific context. some features of this system are described.
disambiguation of finite-state transducers. the objective of this work is to disambiguate transducers which have the following form: t = r o d and to be able to apply the determinization algorithm described in (mohri, 1997). our approach to disambiguating t = r o d consists first of computing the composition t and thereafter to disambiguate the transducer t. we will give an important consequence of this result that allows us to compose any number of transducers r with the transducer d, in contrast to the previous approach which consisted in first disambiguating transducers d and r to produce respectively d' and r', then computing t' = r' o d' where t' is unambiguous. we will present results in the case of a transducer d representing a dictionary and r representing phonological rules.
text processing of thai language "the three seals law". computer softwares for processing thai language are developed at national museum of ethnology, osaka, japan. we use a popular intelligent terminal tektronix 4051 for inputting and editing, ibm 370 model 138 for kwic making and sorting, and canon's laser beam printer for final output.using these systems, "kotmai tra sam duang" (the three seals law) which contains many kind of laws and ordinances proclaimed in thai between 1350--1805 a. d. is computerized. this text has 1700 pages and about 1400000 letters. kwic index becomes 200000 lines.some statistical data for this text are obtained. they are occurrence frequency data of single letter, group vowel, and letter combination (digram), etc.
efficiency tools in the speeches of martin luther king, jr. this thesis represents the results of a computer-aided analysis of aspects of speeches of the reverend martin luther king, jr. specifically, the analysis has investigated the occurrence of indicators of the efficiency function--tools facilitating the comprehension of a discourse by a hearer or reader--in four speeches of dr. king.contrary to the expectations of many who anticipate complex grammatical structures in the discourse of those who are speechmakers before many and diverse audiences, this study has demonstrated that the speeches of dr. king are replete with simple structural devices--sequential clauses as opposed to embedded clauses, sentences in which there are clear linkages between clauses, and clear linkages between sentences, to name a few.the analysis of the texts of dr. king was accomplished in part by a computer program which used as input a surface semantic description of a sentence as a basis for predicting the syntactic function of elements of the sentence.
parsing agglutinative word structures and its application to spelling checking for turkish. most of the research on parsing natural languages has been concerned with english, or with other languages morphologically similar to english. parsing agglutinative word structures has attracted relatively little attention most probably because agglutinative languages contain word structures of considerable complexity, and parsing words in such languages requires morphological analysis techniques. in this paper, we present the design and implementation of a morphological root-driven parser for turkish word structures which has been incorporated into a spelling checking kernel for on-line turkish text. the agglutinative nature of the language and the resulting complex word formations. various phonetic harmony rules and subtle exceptions present certain difficulties not usually encountered in the spelling checking of languages like english and make this a very challenging problem.
a bidirectional, transfer-driven machine translation system for spoken dialogues. this paper presents a brief overview of the bidirectional (japanese and english) transfer-driven machine translation system, currently being developed at atr. the aim of this development is to achieve bidirectional spoken dialogue translation using a new translation technique, tdmt, in which an example-based framework is fully utilized to translate the whole sentence. although the translation coverage is presently restricted to conference registration, the system meets requirements for spoken dialogue translation, such as two-way translation, high speed, and high accuracy with robust processing.
understanding of japanese in an interactive programming system. kips is an automatic programming system which generates standardized business application programs through interactive natural language dialogue. kips models the program under discussion and the content of the user's statements as organizations of dynamic objects in the object-oriented programming sense. this paper describes the statement-model and the program-model, their use in understanding japanese program specifications, and how they are shaped by the linguistic singularities of japanese input sentences.
optimization algorithms of deciphering as the elements of a linguistic theory. this paper presents an outline of the linguistic theory which may be identified with the partially ordered set of optimization algorithms of deciphering. an algorithm of deciphering is the operational definition of a given linguistic phenomenon which has the following three components: a set of admissible solutions, an objective function and a procedure which finds out the minimum or the maximum of the objective function.the paper contains the description of the four algorithms of the proposed type:1. the algorithms which classifies the letters into vowels and consonants.2. the algorithm which identifies the morphemes in the text without the boundaries between words.3. the algorithm which finds out the dependency tree of a sentence.4. the algorithm which finds out the mapping of the letters of an unknown language into the letters of a known one.
chinese named entity identification using class-based language model. we consider here the problem of chinese named entity (ne) identification using statistical language model(lm). in this research, word segmentation and ne identification have been integrated into a unified framework that consists of several class-based language models. we also adopt a hierarchical structure for one of the lms so that the nested entities in organization names can be identified. the evaluation on a large test set shows consistent improvements. our experiments further demonstrate the improvement after seamlessly integrating with linguistic heuristic information, cache-based model and ne abbreviation identification.
a method of utilizing domain and language specific constraints in dialogue translation. one of the characteristics of dialogue translation is that it is strongly dependent on the situation or the communicative goal where the utterance is spoken. moreover, the distance between the language pair is great, the possibilities of the transfer diverse and it would be difficult to guarantee the equivalence of translation.in this article, we propose a method of utilizing domain and language specific constraints from the view-point of transfer phase in a dialogue translation system. transfer processing sometimes requires various kinds of information: e.g., domain knowledge for ellipsis resolution, language dependent communicative structures(focus, theme, rheme, ...).our standpoint is that there are certain language specific strategies on producing utterances in communication. as steps towards clarifying those strategies, we first discuss the issue of typical idiosyncratic gaps between two language pairs. next, to resolve such problems we suggest a new framework of incorporating domain and language specific knowledge as transfer rules for dialogue translation from the viewpoint of transfer phase. finally we will mention related issues and further investigation.
using a broad-coverage parser for word-breaking in japanese. we describe a method of word segmentation in japanese in which a broad-coverage parser selects the best word sequence while producing a syntactic analysis. this technique is substantially different from traditional statistics- or heuristics-based models which attempt to select the best word sequence before handing it to the syntactic component. by breaking up the task of finding the best word sequence into the identification of words (in the word-breaking component) and the selection of the best sequence (a by-product of parsing), we have been able to simplify the task of each component and achieve high accuracy over a wide variety of data. word-breaking accuracy of our system is currently around 97-98%.
topic tracking using subject templates and clustering positive training instances. topic tracking, which starts from a few sample stories and finds all subsequent stories that discuss the same topic, is a new challenge for the text categorization task and is useful for timeline-based ir systems. much previous research on topic tracking use machine learning techniques. however, the small size of the training data, especially positive training stories, presents difficulties in training the parameters of the topic tracking system to produce optimal results. in this paper, we present a method for topic tracking using subject templates and <u>k</u>-means clustering algorithm to select a suitable training set. the method was tested on the tdt1 corpus, and the result shows the effectiveness of the method.
svm answer selection for open-domain question answering. this paper presents an answer selection method based on support vector machines (svm) for open-domain question answering (qa). selecting and ranking plausible answers from a large number of candidates in documents is one of the most critical parts of qa systems. it is extremely difficult to find good evaluation functions or rules for the answer selection. to overcome this issue, we apply svm to answer selection. we evaluate the performance measured by mean reciprocal rank (mrr) and the correct ratio of answer ranked first. the results show that the proposed svm-based method offers a statistically significant increase in performance compared to other machine learning methods such as decision tree learning (c4.5) boosting with decision tree learning (c5.0), and the maximum entropy method.
computer-aided grammatical tagging of spoken english. the paper presents an outline of a system for grammatical tagging of the london-lund corpus of spoken english consisting of some 450 000 words. the material, all of which will be available on magnetic computer tape, and part of which is now available in both machine-readable and printed form, has been transcribed orthographically with prosodic marking for tone units, nuclei, stresses, pauses, etc (see samples 1 and 2). whereas there is now considerable agreement on the usefulness of a tagged corpus, there is as yet no consensus on the best type of tagging, let alone the procedure involved. the analysis proposed here is of course specifically aimed at tagging spoken english, but should be largely applicable also to written english.
centering in japanese: a step towards better interpretation of pronouns and zero-pronouns. an extension of the notion of "centering" is desribed for interpreting zero pronouns and overt pronouns in naturally occurring japanese text. in previous work, one zero-pronoun encodes the backward-looking center, with pronouns and other zero-pronouns handled as if they were overtly expressed. an investigation is made, and from it pronouns and zero pronouns are concluded to be more salient than other overt noun phrases. this enables better interpretation of pronouns and zero-pronouns.
processing homonyms in the kana-to-kanji conversion. this paper proposes two new methods to identify the correct meaning of japanese homonyms in text based on the noun-verb co-occurrence in a sentence which can be obtained easily from corpora. the first method uses the near co-occurrence data sets, which are constructed from the above co-occurrence relation, to select the most feasible word among homonyms in the scope of a sentence. the second uses the far co-occurrence data sets, which are constructed dynamically from the near co-occurrence data sets in the course of processing input sentences, to select the most feasible word among homonyms in the scope of a sequence of sentences. an experiment of kana-to-kanji (phonogram-to-ideograph) conversion has shown that the conversion is carried out at the accuracy rate of 79.6% per word by the first method. this accuracy rate of our method is 7.4% higher than that of the ordinary method based on the word occurrence frequency.
portable knowledge sources for machine translation. in this paper, we describe the acquisition and organization of knowledge sources for machine translation (mt) systems. it has been pointed out by many users that one of the most annoying things about mt systems is the repeated occurrence of identical errors in word sense and attachment disambignuation. we show the limitations of a conventional user-dictionary method and explain how our approach solves the problem.
pattern-based machine translation. in this paper, we describe a "pattern-based" machine translation (mt) approach that we followed in designing a personal tool for users who have access to large volumes of text in languages other than their own, such as www pages. some of the critical issues involved in the design of such a tool include easy customization for diverse domains, the efficiency of the translation algorithm, and scalability (incremental improvement in translation quality through user interaction). we also describe how our patterns fit into the context-free parsing and generation algoritluns, and how we implemented a prototype tool.
critac - a japanese text proofreading system. critac (critiquing using a ccumulated knowledge) is an experimental expert system for proofreading japenese text. it detects mistypes, kana-to-kanji misconversions, and stylistic errors. this system combines prolog-coded heuristic knowledge with conventional japanese text processing techniques which involve heavy computation and access to large language databases.
recognizing topics through the use of interaction structures. a crucial problem in topic recognition is how to identify topic continuation. domain knowledge is generally indispensable for this. however, knowledge-based approaches are impractical because not all domain knowledge needed for the identification can be prepared in advance.this paper presents a topic recognition model using dialogue interaction structures. the model can deal with both task-oriented and non-task-orinted dialogues in any language. topic continuation is identified without domain knowledge because utterances of relevant topics are indicated by certain interaction structures. the model avoids the weak point of knowledge-based approaches. the model is validated by the result of a topic recognition experiment.
entering text with a four-button device. this paper presents the design of a text-entry device that requires only four buttons. such a device is applicable as the text interface of portable machines and as an interface for disabled people. the text-entry system is predictive; the basis for this is an adaptive language model. our evaluation showed that the system is at least as efficient for the entry of free text as the text-entry systems of current-generation mobile phones. the system requires fewer keystrokes than a full keyboard. after adaptation, one user reached a maximum speed of 23 wpm.
measuring the similarity between compound nouns in different languages using non-parallel corpora. this paper presents a method that measures the similarity between compound nouns in different languages to locate translation equivalents from corpora. the method uses information from unrelated corpora in different languages that do not have to be parallel. this means that many corpora can be used. the method compares the contexts of target compound nouns and translation candidates in the word or semantic attribute level. in this paper, we show how this measuring method can be applied to select the best english translation candidate for japanese compound nouns in more than 70% of the cases.
unit-to-unit interaction as a basis for semantic interpretation of japanese sentences. the notion of unit-to-unit interaction is introduced to analyse dependency relations between words in a sentence. a unit is a basic framework for concept representation and is composed of many slots. after generating a parsed tree from an input sentence, our semantic interpretation begins traversing the tree from right to left to discern the case frame in a stage as early as possible, since japanese is a language in which verb is in the sentence-final and has a case frame. unit-to-unit interaction, which is performed at each node of the parsed tree, follows a bottom-up progression. there are unit descriptions at terminal (bottom) nodes and the unit descriptions are modified or merged into other units in the course of the interaction. the results of the interaction will be transferred to upper nodes. the interaction process continues on upward until the top node; at this point, the semantic structure of the input sentence is finally obtained. the notion of unit-to-unit interaction is feasibly applicable to semantic interpretation of english.
dckr - knowledge representation in prolog and its application to natural language processing. semantic processing is one of the important tasks for natural language processing. basic to semantic processing is descriptions of lexical items. the most frequently used form of description of lexical items is probably frames or objects. therefore in what form frames or objects are expressed is a key issue for natural language processing. a method of the object representation in prolog called dckr will be introduced. it will be seen that if part of general knowledge and a dictionary are described in dckr, part of context processing and the greater part of semantic processing can be left to the functions built in prolog.
verbal case frame acquisition from a bilingual corpus: gradual knowledge acquisition. this paper describes acquisition of english surface case frames from a corpus, based on a gradual knowledge acquisition approach. to acquire and unambiguously accumulate precise knowledge, the process is divided into three steps which are assigned to the most appropriate processor: either a human or a computer. the data is prepared by human workers and the knowledge is acquired and accumulated by a leaning program. by using this method, inconsistent human judgement is minimized. the acquired case frames basically duplicate human work, but are more precise and intelligible.
decision tree learning algorithm with structured attributes: application to verbal case frame acquisition. the decision tree learning algorithms (dtlas) are getting keen attention from the natural language processing research community, and there have been a series of attempts to apply them to verbal case frame acquisition. however, a dtla cannot handle structured attributes like nouns, which are classified under a thesaurus. in this paper, we present a new dtla that can rationally handle the structured attributes. in the process of tree generation, the algorithm generalizes each attribute optimally using a given thesaurus. we apply this algorithm to a bilingual corpus and show that it successfully learned a generalized decision tree for classifying the verb "take" and that the tree was smaller with more prediction power on the open data than the tree learned by the conventional dtla.
extraction of lexical translations from non-aligned corpora. a method for extracting lexical translations from non-aligned corpora is proposed to cope with the unavailability of large aligned corpus. the assumption that "translations of two co-occurring words in a source language also co-occur in the target language" is adopted and represented in the stochastic matrix formulation. the translation matrix provides the co-occurring information translated from the source into the target. this translated co-occurring information should resemble that of the original in the target when the ambiguity of the translational relation is resolved. an algorithm to obtain the best translation matrix is introduced. some experiments were performed to evaluate the effectiveness of the ambiguity resolution and the refinement of the dictionary.
construction of a bilingual dictionary intermediated by a third language. when using a third language to construct a bilingual dictionary, it is necessary to discriminate equivalencies from inappropriate words derived as a result of ambiguity in the third language. we propose a method to treat this by utilizing the structures of dictionaries to measure the nearness of the meanings of words. the resulting dictionary is a word-to-word bilingual dictionary of nouns and can be used to refine the entries and equivalencies in published bilingual dictionaries.
shallow language processing architecture for bulgarian. this paper describes lingua - an architecture for text processing in bulgarian. first, the pre-processing modules for tokenisation, sentence splitting, paragraph segmentation, part-of-speech tagging, clause chunking and noun phrase extraction are outlined. next, the paper proceeds to describe in more detail the anaphora resolution module. evaluation results are reported for each processing task.
syntactic analysis of natural language using linguistic rules and corpus-based patterns. we are concerned with the syntactic annotation of unrestricted text. we combine a rule-based analysis with subsequent exploitation of empirical data. the rule-based surface syntactic analyser leaves some amount of ambiguity in the output that is resolved using empirical patterns. we have implemented a system for generating and applying corpus-based patterns. some patterns describe the main constituents in the sentence and some the local context of the each syntactic function. there are several (partly) reduntant patterns, and the "pattern" parser selects analysis of the sentence that matches the strictest possible pattern(s). the system is applied to an experimental corpus. we present the results and discuss possible refinements of the method from a linguistic point of view.
restructuring tagged corpora with morpheme adjustment rules. a part-of-speech tagged corpus is a very important knowledge source for natural language processing researchers. today, several part-of-speech tagged corpora are readily available for research use. however, because there is wide diversity of morphological information systems (word-segmentation, part-of-speech system, etc.), it is difficult to use tagged corpora with an incompatible morphological information system. this paper proposes a method of converting tagged corpora from one morpheme system to another.
matching a tone-based and tune-based approach to english intonation for concept-to-speech generation. the paper describes the results of a comparison of two annotation systems for intonation, the tone-based tobi approach and the tune-based approach proposed by systemic functional grammar (sfg). the goal of this comparison is to define a mapping between the two systems for the purpose of concept-to-speech generation of english. since tobi is widely used in speech synthesis and sfg is widely used in natural language generation and offers a linguistically motivated account of intonation, it appears a promising step to combine the two approaches for concept-to-speech. a corpus of english utterances has been analysed with both tobi and sfg categories; comparison of the analysis results has lead to the identification of some basic equivalents between the two systems on which a mapping can be based.
quantification of meaning and the computer. one of the major tasks of the quantitative semantic analysis is to disclose complex relations of sememes in communication, i.e. on the basis of their associations in the frame of syntactic structures. with the aid of computer it is possible to prepare a corpus of language material giving the possibility to quantify /1./semantics of syntactic functions, /2./ lexical meanings, /3./ meanings of morphological categories, esp. those of parts of speech, and to create a new type of semantic frequency dictionary.
applications of a lexicographical data base for german. the institut f&uuml;r deutsche sprache recently has begun setting up a lexicographical data base for german (leda). this data base is designed to improve efficiency in the collection, analysis, ordering and description of language material by facilitating access to textual samples within corpora and to word articles within machine readable dictionaries and by providing a frame to store results of lexicographical research for further processing. leda thus consists of the three components text bank, dictionary bank and result bank and serves as a tool to support monolingual german dictionary projects at the institute and elsewhere.
automatic extraction of semantic relations from specialized corpora. in this paper we address the problem of discovering word semantic similarities via statistical processing of text corpora. we propose a knowledge-poor method that exploits the sentencial context of words for extracting similarity relations between them as well as semantic in nature word clusters. the approach aims at full portability across domains and languages and therefore is based on minimal resources.
multi-dimensional text classification. this paper proposes a multi-dimensional framework for classifying text documents. in this framework, the concept of multidimensional category model is introduced for representing classes. in contrast with traditional flat and hierarchical category models; the multi-dimensional category model classifies each text document in a collection using multiple predefined sets of categories, where each set corresponds to a dimension. since a multi-dimensional model can be converted to flat and hierarchical models, three classification strategies are possible, i.e., classifying directly based on the multi-dimensional model and classifying with the equivalent flat or hierarchical models. the efficiency of these three classifications is investigated on two data sets. using k-nn, na&iuml;ve bayes and centroid-based classifiers, the experimental results show that the multi-dimensional-based and hierarchical-based classification performs better than the flat-based classifications.
parsing for grammar and style checking. the following paper describes some basic problems which have to be tackled if a morphosyntactic parser is to be configured in a grammar and style checking environment. whereas grammar checking has to deal with ill-formed input which by definition is outside the scope of a grammar, style checking has problems in grammar coverage and intentionality of style.to overcome these problems, a method is presented based on the metal grammar formalism which allows for fallback rules, levelling and scoring mechanisms, and other features which can be used. it will be described what kinds of information and processing are needed to implement such checkers.finally, some examples are given which illustrate the mode of operation of the method described.
incorporating metaphonemes in a multilingual lexicon. this paper describes a framework for multilingual inheritance-based lexical representation which allows sharing of information across languages at all levels of linguistic description. the paper focuses on phonology. it explores the possibility of establishing a phoneme inventory for a group of languages in which language-specific phonemes function as "allophones" of newly defined metaphonemes. dutch, english, and german were taken as a test bed and their vowel phoneme inventories were studied. the results of the cross-linguistic analysis are presented in this paper. the paper concludes by showing how these metaphonemes can be incorporated in a multilingual lexicon.
learning to select a good translation. within the machine translation system verbmobil, translation is performed simultaneously by four independent translation modules. the four competing translations are combined by a selection module so as to form a single optimal output for each input utterance. the selection module relies on confidence values that are delivered together with each of the alternative translations. since the confidence values are computed by four independent modules that are fundamentally different from one another, they are not directly comparable and need to be rescaled in order to gain comparative significance. in this paper we describe a machine learning method tailored to overcome this difficulty by using off-line human feedback to determine an appropriate confidence rescaling scheme. additionally, we describe some other sources of information that are used for selecting between the competing translations, and describe the way in which the selection process relates to quality of service specifications.
word re-ordering and dp-based search in statistical machine translation. in this paper, we describe a search procedure for statistical machine translation (mt) based on dynamic programming (dp). starting from a dp-based solution to the traveling salesman problem, we present a novel technique to restrict the possible word reordering between source and target language in order to achieve an efficient search algorithm. a search restriction especially useful for the translation direction from german to english is presented. the experimental tests are carried out on the verbmobil task (german-english, 8000-word vocabulary), which is a limited-domain spoken-language task.
a type-theoretical analysis of complex verb generation. tense and aspect, together with mood and modality, usually form the entangled structure of a complex verb. they are often hard to translate by machines, because of both syntactic and semantic differences between languages. this problem seriously affects upon the generation process because those verb components in interlingua are hardly rearranged correctly in the target language. we propose here a method in which each verb element is defined as a mathematical function according to its type of type theory. this formalism gives each element its legal position in the complex verb in the target language and certifies so-called partial translation. in addition, the generation algorithm is totally free from the stepwise calculation, and is available on parallel architecture.
free-ordered cug on chemical abstract machine. we propose a paradigm for concurrent natural language generation. in order to represent grammar rules distributively, we adopt categorial unification grammar (cug) where each category owns its functional type. we augment typed lambda calculus with several new combinators, to make the order of &lambda;-conversions free for partial / local processing. the concurrent calculus is modeled with chemical abstract machine. we show an example of a japanese causative auxiliary verb that requires a drastic rearrangement of case domination.
quasi-destructive graph unification with structure-sharing. graph unification remains the most expensive part of unification-based grammar parsing. we focus on one speed-up element in the design of unification algorithms: avoidance of copying of unmodified subgraphs. we propose a method of attaining such a design through a method of structure-sharing which avoids log(d) overheads often associated with structure-sharing of graphs without any use of costly dependency pointers. the proposed scheme eliminates redundant copying while maintaining the quasi-destructive scheme's ability to avoid over copying and early copying combined with its ability to handle cyclic structures without algorithmic additions.
lr parsers for natural languages. mlr, an extended lr parser, is introduced, and its application to natural language parsing is discussed. an lr parser is a shift-reduce parser which is deterministically guided by a parsing table. a parsing table can be obtained automatically from a context-free phrase structure grammar. lr parsers cannot manage ambiguous grammars such as natural language grammars, because their parsing tables would have multiply-defined entries, which precludes deterministic parsing. mlr, however, can handle multiply-defined entries, using a dynamic programming method. when an input sentence is ambiguous, the mlr parser produces all possible parse trees without parsing any part of the input sentence more than once in the same way, despite the fact that the parser does not maintain a chart as in chart parsing. our method also provides an elegant solution to the problem of multi-part-of-speech words such as "that". the mlr parser and its parsing table generator have been implemented at carnegie-mellon university.
disambiguating grammatically ambiguous sentences by asking. the problem addressed in this paper is to disambiguate grammatically ambiguous input sentences by asking the user, who need not be a computer specialist or a linguist, without showing any parse trees or phrase structure rules. explanation list comparison (elc) is the technique that implements this process. it is applicable to all parsers which are based on phrase structure grammar, regardless of the parser implementation. an experimental system has been implemented at carnegie-mellon university, and it has been applied to english-japanese machine translation at kyoto university.
combining lexicon-driven parsing and phrase-structure-based parsing. lexicon-driven formalisms (e.g. categorial grammar; hpsg and gb grammar), which do not have explicit phrase structure rules, are suitable for higher level syntax but not for low level language-specific constructions such as dates (july 15th, 15-jul-1987, etc), which seem to require the power of phrase structure rules. this paper presents an implementation method to combine lexicon-driven parsing and phrase structure parsing, with a special means called graph-structured stack.
another stride towards knowledge-based machine translation. building on the well-established premise that reliable machine translation requires a significant degree of text comprehension, this paper presents a recent advance in multi-lingual knowledge-based machine translation (kbmt). unlike previous approaches, the current method provides for separate syntactic and semantic knowledge sources that are integrated dynamically for parsing and generation. such a separation enables the system to have syntactic grammars, language specific but domain general, and semantic knowledge bases, domain specific but language general. subsequently, grammars and domain knowledge are precompiled automatically in any desired combination to produce very efficient and very thorough real-time parsers. a pilot implementation of our kbmt architecture using functional grammars and entity-oriented semantics demonstrates the feasibility of the new approach.1
logical form of hierarchical relation on verbs and extracting it from definition sentences in a japanese dictionary. we are studying how to extract hierachical relation on verbs from definition sentences in a japanese dictionary. the hierarchical relation on verbs has been dealt with as a binary relation on verbs, but it should be dealt with as logical relation on predicates. we will define the logical form of the hierarchical relation on verbs and then discuss which part of the syntactic structure of the definition sentence represents that relation. we will call the main predicate verb in this part the definition verb. furthermore we will describe how to semiautomatically select the proper meaning of the definition verb and the proper correspondence between cases of an entry verb and the definition verb in order to extract the hierarchical relation as logical relation.
an explanation facility for a grammar writing system. explanation has become a standard feature in many expert systems today. adapting from this work, a study was made to determine the types of explanation required in a grammar writing system and to investigate design and implementation issues. the first version of this explanation facility is based on a derivational history of the inferencing process, and although no supplementary knowledge is used, this explanation facility is able to furnish answers to the traditional why, how and what type of queries, and even the what-if (simulation) query. the explanation is also enhanced through the use of special files containing canned-text for describing grammar rules and variables.
an unsupervised learning method for associative relationships between verb phrases. this paper describes an unsupervised learning method for associative relationships between verb phrases, which is important in developing reliable q&a systems. consider the situation that a user gives a query "how much petrol was imported by japan from saudi arabia?" to a q&a system, but the text given to the system includes only the description "x tonnes of petrol was conveyed to japan from saudi arabia." we think that the description is a good clue to find the answer for our query, "x tonnes." but there is no large-scale database that provides the associative relationship between "imported" and "conveyed." our aim is to develop an unsupervised learning method that can obtain such an associative relationship, which we call scenario consistency. the method we are currently working on uses an expectation-maximization (em) based word-clustering algorithm, and we have evaluated the effectiveness of this method using japanese verb phrases.
computing phrasal-signs in hpsg prior to parsing. this paper describes techniques to compile lexical entries in hpsg (pollard and sag, 1987; pollard and sag, 1993)-style grammar into a set of finite state automata. the states in automata are possible signs derived from lexical entries and contain information raised from the lexical entries. the automata are augmented with feature structures used by a partial unification routine and delayed/frozen definite clause programs.
linguistic contribution to text-to-speech computer programs for french. this paper presents the development of computer programs used for transcribing french text into phonetic speech. based on an earlier program (maggs & trescases, 1980) made of a set of some 500 text-to-phonetics rules and of a compact set of prosodic rules for synthetic speech, the present research was primarily aiming at developing the best possible algorithm to account for practically any word in the french general lexicon, as opposed to most frequently used words only. in order to considerably enhance the original rules, these were systematically tested against a 50, 000 word french pronunciation dictionary and an equally important corpus of texts which were all entered in an ibm pc-xt. at the same time, a set of syntactic rules was developed for most liaisons, mandatory and forbidden, and homographs to be found in french speech. the result is a set of some 4, 800 conversion rules. tested against the 50, 000 words of the pronunciation dictionary, they yield a low percentage of error. errors in text are similarly minimal, and due mainly to foreign (english) words. to allow faster programing, while accounting for most commonly used words in french, a compact set of 2, 000 rules has been developed. it is essentially based on a statistical analysis yielding most frequently used general rules. the aim of both algorithms has been to make possible better text-to-speech software for french.
the application of two-level morphology to non-concatenative german morphology. in this paper we describe a hybrid system for morphological analysis and synthesis. we call it hybrid because it consists of two separate parts interacting with each other in a well-defined way. the treatment of morphonology and non-concatenative morphology is based on the two-level approach originally proposed by koskenniemi (1983). for the concatenative part of morphosyntax (i.e. affixation) we make use of a grammar based on feature-unification. both parts rely on the same morph lexicon.combinations of two-level morphology with feature-based morphosyntactic grammars have already been proposed by several authors (c.f. bear 1988a, carson 1988, g&ouml;rz & paulus 1988, schiller & steffens 1990) to overcome the shortcomings of the continuation-classes originally proposed by koskenniemi (1983) and karttunen (1983) for the description of morphosyntax. but up to now no linguistically satisfying solution has been proposed for the treatment of non-concatenative morphology in such a framework. in this paper we describe an extension to the model which will allow for the description of such phenomena. namely we propose to restrict the applicability of two-level rules by providing them with filters in the form of feature structures. we demonstrate how a well-known problem of german morphology, so-called "umlautung", can be described in our approach in a linguistically motivated and efficient way.
towards the automatic acquisition of lexical data. creating a knowledge base has always been a bottleneck in the implementation of ai systems. this is also true for natural language understanding (nlu) systems, particularly for data-driven ones. while a perfect system for automatic acquisition of all sorts of knowledge is still far from being realized, partial solutions are possible. this holds especially for lexical data. nevertheless, the task is not trivial, in particular when dealing with languages rich in inflectional forms like german. our system is to be used by persons with no specific linguistic knowledge, thus linguistic expertise has been put into the system to ascertain correct classification of words. classification is done by means of a small rule based system with lexical knowledge and language-specific heuristics. the key idea is the identification of three sorts of knowledge which are processed distinctly and the optimal use of knowledge already contained in the existing lexicon.
on the interaction of syntax and semantics in a syntactically guided caseframe parser. in this paper we describe a parser for german based on semantic caseframe instantiation guided by a syntactic analyzer. pure caseframe parsers lack the ability to capture syntactic regularities, which leads to redundancy in the lexicon and/or poor syntactic coverage. by combining caseframe matching with an explicit syntactic analysis our parser overcomes this problem.approaches well suited for english are not easily transported to german with its rich morphology and its free constituent order at the clause level. our parser which incorporates two different interacting parsing strategies is well adapted to the needs posed by german grammar.
morphology with a null-interface. we present an integrated architecture for word-level and sentence-level processing in a unification-based paradigm. the core of the system is a clp implementation of a unification engine for feature structures supporting relational values. in this framework an hpsg-style grammar is implemented. word-level processing uses x2morf, a morphological component based on an extended version of two-level morphology. this component is tightly integrated with the grammar as a relation. the advantage of this approach is that morphology and syntax are kept logically autonomous while at the same time minimizing interface problems.
computing first and follow functions for feature-theoretic grammars. this paper describes an algorithm for the computation of first and follow sets for use with feature-theoretic grammars, in which the value of the sets consists of pairs of feature-theoretic categories. the algorithm preserves as much information from the grammars as possible, using negative restriction to define equivalence classes. addition of a simple data structure leads to an order of magnitude improvement in execution time over a naive implementation.
connectivity in bag generation. this paper presents a pruning technique which can be used to reduce the number of paths searched in rule-based bag generators of the type proposed by (pozna&nacute;ski et al., 1995) and (popowich, 1995). pruning the search space in these generators is important given the computational cost of bag generation. the technique relies on a connetivity constraint between the semantic indices associated with each lexical sign in a bag. testing the algorithm on a range of sentences shows reductions in the generation time and the number of edges constructed.
applying an nvef word-pair identifier to the chinese syllable-to-word conversion problem. syllable-to-word (stw) conversion is important in chinese phonetic input methods and speech recognition. there are two major problems in the stw conversion: (1) resolving the ambiguity caused by homonyms; (2) determining the word segmentation. this paper describes a noun-verb event-frame (nvef) word identifier that can be used to solve these problems effectively. our approach includes (a) an nvef word-pair identifier and (b) other word identifiers for the non-nvef portion.our experiment showed that the nvef word-pair identifier is able to achieve a 99.66% stw accuracy for the nvef related portion, and by combining with other identifiers for the non-nvef portion, the overall stw accuracy is 96.50%.the result of this study indicates that the nvef knowledge is very powerful for the stw conversion. in fact, numerous cases requiring disambiguation in natural language processing fall into such "chicken-and-egg" situation. the nvef knowledge can be employed as a general tool in such systems for disambiguating the nvef related portion independently (thus breaking the chicken-and-egg situation) and using that as a good fundamental basis to treat the remaining portion. this shows that the nvef knowledge is likely to be important for general nlp. to further expand its coverage, we shall extend the study of nvef to that of other co-occurrence restrictions such as noun-noun pairs, noun-adjective pairs and verb-adverb pairs. we believe the stw accuracy can be further improved with the additional knowledge.
crosslinguistic transfer in automatic verb classification. we investigate the use of multilingual data in the automatic classification of english verbs, and show that there is a useful transfer of information across languages. specifically, we experiment with three lexical semantic classes of english verbs. we collect statistical features over a sample of english verbs from each of the classes, as well as over chinese translations of those verbs. we use the english and chinese data, alone and in combination, as training data for a machine learning algorithm whose output is an automatic verb classifier. we demonstrate that chinese data is indeed useful in helping to classify the english verbs (at 82% accuracy), and furthermore that a multilingual combination of data outperforms the english data alone (85% accuracy). moreover, our results using monolingual corpora show that it is not necessary to use a parallel corpus to extract the translations in order for this technique to be successful.
modelling speech repairs in german and mandarin chinese spoken dialogues. results presented in this paper strongly support the notion that similarities as well as differences in language systems can be empirically investigated by looking into the linguistic patterns of speech repairs in real speech data. a total of 500 german and 325 mandarin chinese overt immediate speech repairs were analysed with regard to their internal phrasal structures, with particular focus on the syntactic and morphological characteristics. computational models in the form of finite state automata (fsa) also illustrate the describable regularity of german and mandarin chinese speech repairs in a formal way.
jurilinguistic engineering in cantonese chinese: an n-gram-based speech to text transcription system. a cantonese chinese transcription system to automatically convert stenograph code to chinese characters is reported. the major challenge in developing such a system is the critical homocode problem because of homonymy. the statistical n-gram model is used to compute the best combination of characters. supplemented with a 0.85 million character corpus of domain-specific training data and enhancement measures, the bigram and trigram implementations achieve 95% and 96% accuracy respectively, as compared with 78% accuracy in the baseline model. the system performance is comparable with other advanced chinese speech-to-text input applications under development. the system meets an urgent need of the judiciary of post-1997 hong kong.
how to get preferred readings in natural language analysis. this paper describes a parsing program called kgw+p which is designed for integrating various sorts of knowledge to get most preferred structural descriptions of sentences. the system accepts not only a set of rules specifying constraints which any descriptions of sentences should satisfy, but also preferential rules which are utilized in selecting most preferred descriptions among possible ones. during the parsing process, the preferetial rules are utilized to select feasible parsing paths. furthermore, kgw+p is complete in the sense that it can generate all possible structural descriptions of sentences it required. the descriptions are generated in a preferential order.
analysis grammar of japanese in the mu-project: a procedural approach to analysis grammar. analysis grammar of japanese in the mu-project is presented. it is emphasized that rules expressing constraints on single linguistic structures and rules for selecting the most preferable readings are completely different in nature, and that rules for selecting preferale readings should be utilized in analysis grammars of practical mt systems. it is also claimed that procedural control is essential in integrating such rules into a unified grammar. some sample rules are given to make the points of discussion clear and concrete.
analysis of scene identification ability of associative memory with pictorial dictionary. semantic disambiguation depends on a process of defining the appropriate knowledge context. recent research directions suggest a connectionist approach which use dictionaries, but there remain problems of scale, analysis, and interpretation. here we focus on word disambiguation as scene selection, based on the oxford pictorial english dictionary. we present a results of a spatial-scene identification ability using our original associative memory, we show both theoretical and experimental analysis, based on a several different measures including information entropy.
an attempt to automatic thesaurus construction from an ordinary japanese language dictionary. how to obtain hierarchical relations (e.g. superordinate-hyponym relation, synonym relation) is one of the most important problems for thesaurus construction. a pilot system for extracting these relations automatically from an ordinary japanese language dictionary (shinmeikai kokugojiten, published by sansei-do, in machine readable form) is given. the features of the definition sentences in the dictionary, the mechanical extraction of the hierarchical relations and the estimation of the results are discussed.
a prototype english-japanese machine translation system for translating ibm computer manuals. this paper describes a prototype english-japanese machine translation (mt) system developed at the science institute of ibm japan, ltd. this mt system currently aims at the translation of ibm computer manuals. it is based on a transfer approach in which the transfer phase is divided into two sub-phases: english transformation and english-japanese conversion. an outline of the system and a detailed description of the english-japanese transfer method are presented.
a cheap and fast way to build useful translation lexicons. the paper presents a statistical approach to automatic building of translation lexicons from parallel corpora. we briefly describe the pre-processing steps, a baseline iterative method, and the actual algorithm. the evaluation for the two algorithms is presented in some detail in terms of precision, recall and processing time. we conclude by briefly presenting some of our applications of the multilingual lexicons extracted by the method described herein.
a mathematical model of the vocabulary-text relation. a new method for calculating vocabulary size as a function of text length is discussed. the vocabulary growth is treated as a probabilistic process governed by the principle of "the restriction of variety" of lexics. proceeding from the basic model of the vocabulary-text relation a formula with good descriptive power is constructed. the statistical fit and the possibilities of extrapolation beyond the limits of observable data are illustrated on the material of several languages belonging to different typological groups.
organizing dialogue from an incoherent stream of goals. human discourse appears coherent when it reflects coherent human thought. however, computers do not necessarily store or process information in the same way that people do and, therefore, cannot rely on the structure of their reasoning for the structure of their dialogues. instead, computer-generated conversation must rely on some other mechanism for its organisation. in this paper, we discuss one such mechanism. we describe a template that provides a guide for conversation. the template is built from schemata representing discourse convention. as goals arrive from the problem solver they are added to the template. because accepted discourse structures are used to connect a new goal to the existing template, goals are organised into sub-groups that follow conventional, coherent patterns of discourse. we present judis, an interface to a distributed problem solver that uses this approach to organise dialogues from an incoherent stream of goals.
lexical choice in context: generating procedural texts. this paper shows how lexical choice during text generation depends on linguistic context. we argue that making correct lexical choice in the textual context requires distinguishing properties of concepts, which are more or less independent of the language, from language-specific representations of text where lexemes and their semantic and syntactic relations are represented. in particular, lexical functions are well-suited to formalizing anaphoric lexical links in text, including the introduction of superordinates. this sheds new light on the notion of "basic level", which has recently been applied to lexical selection in generation. some constraints governing the generation of lexical and grammatical anaphora are proposed for procedural text, using examples from the sublanguage of recipes.
issues in text-to-speech for french. this paper reports the progress of the french text-to-speech system being developed at at&t bell laboratories as part of a larger project for multilingual text-to-speech systems, including languages such as spanish, italian, german, russian, and chinese. these systems, based on diphone and triphone concatenation, follow the general framework of the bell laboratories english tts system [?], [?]. this paper provides a description of the approach, the current status of the french text-to-speech project, and some problems particular to french.
a finite-state morphological processor for spanish. a finite transducer that processes spanish inflectional and derivational morphology is presented. the system handles both generation and analysis of tens of millions inflected forms. lexical and surface (orthographic) representations of the words are linked by a program that interprets a finite directed graph whose arcs are labelled by n-tuples of strings. each of about 55,000 base forms requires at least one are in the graph. representing the inflectional and derivational possibilities for these forms imposed an overhead of only about 3000 additional arcs, of which about 2500 represent (phonologically predictable) stem allomorphy, so that we pay a storage price of about 5% for compiling these forms offline. a simple interpreter for the resulting automaton processes several hundred words per second on a sun4.
word order acquisition from corpora. in this paper we describe a method of acquiring word order from corpora. word order is defined as the order of modifiers, or the order of phrasal units called 'bunsetsu' which depend on the same modifiee. the method uses a model which automatically discovers what the tendency of the word order in japanese is by using various kinds of information in and around the target bunsetsus. this model shows us to what extent each piece of information contributes to deciding the word order and which word order tends to be selected when several kinds of information conflict. the contribution rate of each piece of information in deciding word order is efficiently learned by a model within a maximum entropy framework. the performance of this trained model can be evaluated by checking how many instances of word order selected by the model agree with those in the original text. in this paper, we show that even a raw corpus that has not been tagged can be used to train the model, if it is first analyzed by a parser. this is possible because the word order of the text in the corpus is correct.
linguistic model based on the generative topological information space. based on the structuralism, we propose a generative semantic model which has a topological information space generative grammar as basic rules. in this model a semantic map which is called a topological information space, is generated by the grammar, and the space can express implications and similarities among concepts. in the syntax, a syntactic generative grammar is defined based on the space grammar, and a mapping from the map to the language is defined. the mapping is composed of two mappings: one is a meaning affix mapping &phi; which maps a conceptual area in the space to a token in the language, and the other is an operator mapping &psi; which maps a generative rule in semantics to a rewriting rule in syntax. by these mappings, a derivation tree in semantics is mapped to a derivation tree in syntax, and vice versa.an algebraic system on the space is defined, and an algebraic system on the sentences is derived by the (&phi;, &psi;) -mappings. english will be analyzed according to this model and the algebraic systems on them.finally an information processing model is described based on the model. the information processing in a natural language is carried out in the following steps: recognizing the inputs, parsing, interpreting, deducing, updating them, and outputting. these processes are discussed in details.
generation for dialogue translation using typed feature structure unification. this article introduces a bidirectional grammar generation system called feature structure-directed generation, developed for a dialogue translation system. the system utilizes typed feature structures to control the top-down derivation in a declarative way. this generation system also uses disjunctive feature structures to reduce the number of copies of the derivation tree. the grammar for this generator is designed to properly generate the speaker's intention in a telephone dialogue.
toward the "at-a-glance" summary: phrase-representation summarization method. we have developed a summarization method that creates a summary suitable for the process of sifting information retrieval results. unlike conventional methods that extract important sentences, this method constructs short phrases to reduce the burden of reading long sentences. we have developed a prototype summarization system for japanese. through a rather large-scale task-based experiment, the summary this system creates proved to be effective to sift ir results. this summarization method is also applicable to other languages such as english.
automatic compilation of modern chinese concordances. an an automatic indexing experiment in chinese is described. the first very large volume of modern chinese concordances (two sets of one million-line kwic index) has been compiled and materialized automatically with a modified kanji printer for japanese.
computational data analysis for syntax. methodology and results of complex computational analysis of present-day standard czech are presented. according to computer programmes various linguistic observations were achieved, concerning especially dependency syntax.
a best-match algorithm for broad-coverage example-based disambiguation. to improve the coverage of example-bases, two methods are introduced into the best-match algorithm. the first is for acquiring conjunctive relationships from corpora, as measures of word similarity that can be used in addition to thesauruses. the second, used when a word does not appear in an example-base or a thesaurus, is for inferring links to words in the example-base by comparing the usage of the word in the text and that of words in the example-base.
positioning unknown words in a thesaurus by using information extracted from a corpus. this paper describes a method for positioning unknown words in an existing thesaurus by using word-to-word relationships with relation (case) markers extracted from a large corpus. a suitable area of the thesaurus for an unknown word is estimated by integrating the human intuition buried in the thesaurus and statistical data extracted from the corpus. to overcome the problem of data sparseness, distinguishing features of each node, called "viewpoints" are extracted automatically and used to calculate the similarity between the unknown word and a word in the thesaurus. the results of an experiment confirm the contribution of viewpoints to the positioning task.
hierarchical clustering of words. this paper describes a data-driven method for hierarchical clustering of words in which a large vocabulary of english words is clustered bottom-up, with respect to corpora ranging in size from 5 to 50 million words, using a greedy algorithm that tries to minimize average loss of mutual information of adjacent classes. the resulting hierarchical clusters of words are then naturally transformed to a bit-string representation of (i.e. word bilts for) all the words in the vocabulary. introducing word bits into the atr decision-tree pos tagger is shown to significantly reduce the tagging error rate. portability of word bits from one domain to another is also disscussed.
categorial unification grammars. categorial unification grammars (cugs) embody the essential properties of both unification and categorial grammar formalisms. their efficient and uniform way of encoding linguistic knowledge in well-understood and widely used representations makes them attractive for computational applications and for linguistic research.in this paper, the basic concepts of cugs and simple examples of their application will be presented. it will be argued that the strategies and potentials of cugs justify their further exploration in the wider context of research on unification grammars. approaches to selected linguistic phenomena such as long-distance dependencies, adjuncts, word order, and extraposition are discussed.
combining unsupervised and supervised methods for pp attachment disambiguation. statistical methods for pp attachment fall into two classes according to the training material used: first, unsupervised methods trained on raw text corpora and second, supervised methods trained on manually disambiguated examples. usually supervised methods win over unsupervised methods with regard to attachment accuracy. but what if only small sets of manually disambiguated material are available? we show that in this case it is advantageous to intertwine unsupervised and supervised methods into one disambiguation algorithm that outperforms both methods used alone.
a statistical approach to the processing of metonymy. this paper describes a statistical approach to the interpretation of metonymy. a metonymy is received as an input, then its possible interpretations are ranked by applying a statistical measure. the method has been tested experimentally. it correctly interpreted 53 out of 75 metonymies in japanese.
a unified theory of irony and its computational formalization. this paper presents a unified theory of verbal irony for developing a computational model of irony. the theory claims that an ironic utterance implicitly communicates the fact that its utterance situation is surrounded by ironic environment which has three properties, but hearers can assume an utterance to be ironic even when they recognize that it implicitly communicates only two of the three properties. implicit communication of three properties is accomplished in such a way that an utterance alludes to the speaker's expectation, violates pragmatic principles, and implies the speaker's emotional attitude. this paper also describes a method for computationally formalizing ironic environment and its implicit communication using situation theory with action theory.
sense classification of verbal polysemy based-on bilingual class/class association. in the field of statistical analysis of natural langauge data, the measure of word/class association has proved to be quite useful for discovering a meaningful sense cluster in an arbitrary level of the thesaurus. in this paper, we apply its idea to the sense classification of japanese verbal polysemy in case frame acquisition from japanese-english parallel corpora. measures of bilingual class/class association and bilingual class/frame association are introduced and used for discovering sense clusters in the sense distribution of english predicates and japanese case element nouns. in a small experiment, 93.3% of the discovered clusters are correct in that none of them contains examples of more than one hand-classified senses.
buildrs: an implementation of dr theory and lfg. this paper examines a particular prolog implementation of discourse representation theory (dr theory) constructed at the university of texas. the implementation also contains a lexical functional grammar parser that provides f-structures: these f-structures are then translated into the semantic representations posited by dr theory, structures which are known as discourse representation structures (drss). our program handles some linguistically interesting phenomena in english such as (i) scope ambiguities of singular quantifiers, (ii) functional control phenomena, and (iii) long distance dependencies. finally, we have implemented an algorithm for anaphora resolution. our goal is to use purely linguistically available information in constructing a semantic representation of discourse as far as is feasible and to forego appeals to world knowledge.
bilingual text, matching using bilingual dictionary and statistics. this paper describes a unified framework for bilingual text matching by combining existing hand-written bilingual dictionaries and statistical techniques. the process of bilingual text matching consists of two major steps: sentence alignment and structural matching of bilingual sentences. statistical techniques are applied to estimate word correspondences not included in bilingual dictionaries. estimated word correspondences are useful for improving both sentence alignment and structural matching.
lexical knowledge acquisition from bilingual corpora. for practical research in natural language processing, it is indispensable to develop a large scale semantic dictionary for computers. it is especially important to improve the techniques for compiling semantic dictionaries from natural language texts such as those in existing human dictionaries or in large corpora. however, there are at least two difficulties in analyzing existing texts: the problem of syntactic ambiguities and the problem of polysemy. our approach to solve these difficulties is to make use of translation examples in two distinct languages that have quite different syntactic structures and word meanings. the reason we took this approach is that in many cases both syntactic and semantic ambiguities are resolved by comparing analyzed results from both languages. in this paper, we propose a method for resolving the syntactic ambiguities of translation examples of bilingual corpora and a method for acquiring lexical knowledge, such as case frames of verbs and attribute sets of nouns.
thesaurus-based efficient example retrieval by generating retrieval queries from similarities. in example-based nlp, the problem of computational cost of example retrieval is severe, since the retrieval time increases in proportion to the number of examples in the database. this paper proposes a novel example retrieval method for avoiding full retrieval of examples. the proposed method has the following three features, 1) it generates retrieval queries from similarities, 2) efficient example retrieval through the tree structure of a thesaurus, 3) binary search along subsumption ordering of retrieval queries. example retrieval time drastically decreases with the method.
a chart-parsing algorithm for efficient semantic analysis. in some contexts, well-formed natural language cannot be expected as input to information or communication systems. in these contexts, the use of grammar-independent input (sequences of uninflected semantic units like e.g. language-independent icons) can be an answer to the users' needs. however, this requires that an intelligent system should be able to interpret this input with reasonable accuracy and in reasonable time. here we propose a method allowing a purely semantic-based analysis of sequences of semantic units. it uses an algorithm inspired by the idea of "chart parsing" known in natural language processing, which stores intermediate parsing results in order to bring the calculation time down.
evaluation of an algorithm for the recognition and classification of proper names. we describe an information extraction system in which four classes of naming expressions - organisation, person, location and time names - are recognised and classified with nearly 92% combined precision and recall. the system applies a mixture of techniques to perform this task and these are described in detail. we have quantitatively evaluated the system against a blind test set of wall street journal business articles and report results not only for the system as a whole, but for each component technique and for each class of name. these results show that in order to have high recall, the system needs to make use not only of information internal to the naming expression but also information from outside the name. they also show that the contribution of each system component varies from one class of name expression to another.
an implementation of formal semantics in the formalism of relational databases. this paper presents an implementation of formal semantics as described in keenan and faltz's boolean semantics for natural language (4). the main characteristic of this implementation is that it avoids the intermediate step of translating nl into a formal language, such as an extended version of predicate calculus. my choice of not using any intermediate language, which montague already suggested in universal grammar (5), makes my implementation free of the problems related to the syntax of such a language like binding the variables and resolving scope ambiguities. on the other hand, not translating nl into an intermediate language requires every denotation (i.e. semantic value) to be explicitly and accurately represented in a database.
clustering verbs semantically according to their alternation behaviour. verbs were clustered semantically on the basis of their alternation behaviour, as characterised by their syntactic subcategorisation frames extracted from maximum probability parses of a robust statistical parser, and completed by assigning wordnet classes as selectional preferences to the frame arguments. the clustering was achieved (a) iteratively by measuring the relative entropy between the verbs' probability distributions over the frame types, and (b) by utilising a latent class analysis based on the joint frequencies of verbs and frame types.
algorithm for automatic interpretation of noun sequences. this paper describes an algorithm for automatically interpreting noun sequences in unrestricted text. this system uses broadcoverage semantic information which has been acquired automatically by analyzing the definitions in an on-line dictionary. previously, computational studies of noun sequences made use of hand-coded semantic information, and they applied the analysis rules sequentially. in contrast, the task of analyzing noun sequences in unrestricted text strongly favors an algorithm according to which the rules are applied in parallel and the best interpretation is determined by weights associated with rule applications.
natural-language-access systems and the organization and use of information. this paper describes a program of research whose objectives are to (1) develop systems that provide users with access to both data and text files through natural language dialogues; (2) study how people actually use the information to test hypotheses and solve problems; (3) modify the system designs on the basis of the results of the studies so that the systems more effectively support such uses and increasingly come to model the behavior of the users. two of the systems are in the medical domain: the first provides physicians with formatted information derived from patient medical records; the second responds to requests by eliciting relevant passages from a medical monograph. the third system is a more general information retrieval facility that will support interactions among system users and enable their successive experiences to be accumulated within the system database.
fluency and completeness in instance-based natural language generation. a fundamental assumption underlying candidate ranking in corpus-based approaches to natural language generation is the idea that in order to be fluent the output should be as similar to a (human-authored) corpus as possible. however, the goal of maximizing fluency can conflict with other goals, like conveying the maximal amount of input and being faithful. we employ an instance-based sentence generation system to investigate how the right balance between the different goals can be struck and show empirical results supporting our proposals.
machine-readable dictionaries. the papers in this panel consider machine-readable dictionaries from several perspectives: research in computational linguistics and computational lexicology, the development of tools for improving accessibility, the design of lexical reference systems for educational purposes, and applications of machine-readable dictionaries in information science contexts. as background and by way of introduction, a description is provided of a workshop on machine-readable dictionaries that was held at sri international in april 1983.
why human translators still sleep in peace? (four engineering and linguistic gaps in nlp). because they will keep their job quite for a few.this paper has been inspired by a recent editorial on the financial times, that gives a discouraging overview of commercial natural language processing systems ('the computer that can sustain a natural language conversation... is unlikely to exist for several decades'). computational linguists are not so much concerned with applications but computer scientists have the ultimate objective to build systems that can 'increase the acceptability of computers in everyday situations.' eventually, linguists as well would profit by a significant break-through in natural language processing.this paper is a brief dissertation on four engineering and linguistic issues we believe critical for a more striking success of nlp: extensive acquisition of the semantic lexicon, formal performance evaluation methods to evaluate systems, development of shell systems for rapid prototyping and customization, and finally a more linguistically motivated approach to word categorization.
cross-serial dependencies are not hard to process. cross-serial dependencies in dutch and swiss-german are the only known extracontext free natural language syntactic phenomena. psycholinguistic evidence suggests cross-serial orderings tend to be easier to process than nested constructions. we argue that the expressivity requirements of the corresponding formal languages do not actually entail that processing reduplication languages require the worst-case time complexity for languages of the same expressive class. we distinguish between context-free representability and context-free processing. we show that for any language with up to context free expressive power, processing cross-serial dependencies can be accommodated without affecting parsing complexity. this is related to other work on reduplication phenomena in formal models of computation.
utilisation du parallelisme en traduction automatisee par ordinateur. on pr&eacute;sente un syst&egrave;me de transformation de structures arborescentes adapt&eacute; au traitement parall&egrave;le. les structures de donn&eacute;es, appel&eacute;es <u>mat</u>, permettent une manipulation ais&eacute;e des ambigu&iuml;t&eacute;s et des choix structuraux. les r&egrave;gles et grammaires du syst&egrave;me, appel&eacute; star-pale, peuvent exprimer un certain nombre d'options de contr&ocirc;le, de reconnaissance et de transformation. on donne les id&eacute;es de base pour l'impl&eacute;mentation de ce type de syst&egrave;mes.
discourse and deliberation- testing a collaborative strategy. a discourse strategy is a strategy for communicating with another agent. designing effective dialogue systems requires designing agents that can choose among discourse strategies. we claim that the design of effective strategies must take cognitive factors into account, propose a new method for testing thehypothesized factors, and present experimental results on an effective strategy for supporting deliberation. the proposed method of computational dialogue simulation provides a new empirical basis for computational linguistics.
a case study of natural language customisation: the practical effects of world knowledge. this paper proposes a methodology for the customisation of natural language interfaces to information retrieval applications. we report a field study in which we tested this methodology by customising a commercially available natural language system to a large database of sales and marketing information. we note that it was difficult to tailor the common sense reasoning capabilities of the particular system we used to our application. this study validates aspects of the suggested methodology as well as providing insights that should inform the design of natural language systems for this class of applications.
xmltrans: a java-based xml transformation language for structured data. the recently completed mlis dicopro project addressed the need for a uniform, platform-independent interface for accessing multiple dictionaries and other lexical resources via the internet/intranets. lexical data supplied by dictionary publishers for the project was in a variety of sgml formats. in order to transform this data to a convenient standard format (html), a high level transformation language was developed. this language is simple to use, yet powerful enough to perform complex transformations not possible with similar transformation tools. xmltrans provides rooted/recursive transductions, similar to transducers used for natural language translation. the tool is written in standard java and is available to the general public.
morphosyntactic correction in natural language interfaces. morphosyntax cannot be simply ignored in natural-language man-machine dialogue since it constitutes an important part of the meaning. nevertheless, troublesome side effects can arise when morphosyntactic errors are combined with other types of errors. we describe here an efficient means of handling quite complex combinations of typographical, phonographic and agreement errors in french, which are typical of c.a.i. users: a sentence as erroneous as les cott&eacute; adgassan &agrave; i'ippeauttainuz son perpndiqul&egrave;re (!) will be perfectly recognized and translated into les c&ocirc;t&eacute;s adjacents &agrave; l'hypot&eacute;nuse sont perpendiculaires (the legs adjacent to the hypotenuse are perpendicular).
disjunctive feature structures as hypergraphs. in this paper, we present a new mathematical framework in which disjunctive feature structures are defined as directed acyclic hypergraphs. disjunction is defined in the feature structure domain, and not at the syntactic level in feature descriptions. this enables us to study properties and specify operations in terms of properties of, or operations on, hypergraphs rather than in syntactic terms. we illustrate the expressive power of this framework by defining a class of disjunctive feature structures with interesting properties (factored normal from or fnf), such as closure under factoring, unfactoring, unification, and generalization. unification, in particular, has the intuitive appeal of preserving as much as possible the particular factoring of the disjunctive feature structures to be unified. we also show that unification in the fnf class can be extremely efficient in practical applications.
syntactic preferences for robust parsing with semantic preferences. using constraints in robust parsing seems to have what we call "robust parsing paradox". preference semantics and connectionism both offered a promising approach to this problem. however, preference semantics has not addressed the problem of how to make full use of syntactic constraints, and connectionism has some inherent difficulties of its own which prevent it producing a practical system. in this paper we are proposing a method to add syntactic preferences to the preference semantics paradigm while maintaining its fundamental philosophy. it will be shown that syntactic preferences can be coded as a set of weights associated with the set of symbolically manipulatable rules of a new grammar formalism. the syntactic preferences such coded can be easily used to compute with semantic preferences. with the help of some techniques borrowed from connectionism, these weights can be adjusted through training.
word sense disambiguation with very large neural networks extracted from machine readable dictionaries. in this paper, we describe a means for automatically building very large neural networks (vlnns) from definition texts in machine-readable dictionaries, and demonstrate the use of these networks for word sense disambiguation. our method brings together two earlier, independent approaches to word sense disambiguation: the use of machine-readable dictionaries and spreading and activation models. the automatic construction of vlnns enables real-size experiments with neural networks for natural language processing, which in turn provides insight into their behaviour and design and can lead to possible improvements.
recognizing unregistered names for mandarin word identification. word identification has been an important and active issue in chinese natural language processing. in this paper, a new mechanism, based on the concept of sublanguage, is proposed for identifying unknown words, especially personal names, in chinese newspapers. the proposed mechanism includes title-driven name recognition, adaptive dynamic word formation, identification of 2-character and 3-character chinese names without title. we will show the experimental results for two corpora and compare them with the results by the nthu's statistic-based system, the only system that we know has attacked the same problem. the experimental results have shown significant improvements over the wi systems without the name identification capability.
a feature-based model for lexical databases. to date, no fully suitable data model for lexical databases has been proposed. as lexical databases have proliferated in multiple formats, there has been growing concern over the reusability of lexical resources. in this paper, we propose a model based on feature structures which overcomes most of the problems inherent in classical database models, and in particular enables accessing, manipulating or merging information structured in multiple ways. because of their widespread use in the representation of linguistic information, the applicability of feature structures to lexical databases seems natural, although to our knowledge this has not yet been implemented. the use of feature structures in lexical databases also opens up the possibility of compatibility with computational lexicons.
corpus-based development and evaluation of a system for processing definite descriptions. we present an implemented system for processing definite descriptions. the system is based on the results of a corpus analysis previously reported, which showed how common discourse-new descriptions are in newspaper corpora, and identified several problems to be dealt with when developing computational methods for interpreting bridging descriptions. the annotated corpus produced in this earlier work was used to extensively evaluate the proposed techniques for matching definite descriptions with their antecedents, discourse segmentation, recognizing discourse-new descriptions, and suggesting anchors for bridging descriptions.
building a large-scale annotated chinese corpus. in this paper we address issues related to building a large-scale chinese corpus. we try to answer four questions: (i) how to speed up annotation, (ii) how to maintain high annotation quality, (iii) for what purposes is the corpus applicable, and finally (iv) what future work we anticipate.
feature structures based tree adjoining grammars. we have embedded tree adjoining grammars (tag) in a feature structure based unification system. the resulting system, feature structure based tree adjoining grammars (ftag), captures the principle of factoring dependencies and recursion, fundamental to tag's. we show that ftag has an enhanced descriptive capacity compared to tag formalism. we consider some restricted versions of this system and some possible linguistic stipulations that can be made. we briefly describe a calculus to represent the structures used by this system, extending on the work of rounds, and kasper [rounds et al. 1986, kasper et al. 1986] involving the logical formulation of feature structures.
construction of a hierarchical translation memory. translation memories are promising devices for automatic translation. their main weakness, however, is poor coverage on unseen text. in this paper, the use of a hierarchical translation memory, consisting of a cascade of finite state transducers, is proposed. a number of transducers is applied to convert sentence pairs from a bilingual corpus into translation patterns, which are then used as a translation memory. preliminary results on the german english verbmobil corpus are given.
structure sharing in lexicalized tree-adjoining grammars. we present a scheme for efficiently representing a lexicalized tree-adjoining grammar (ltag). the proposed representational scheme allows for structure-sharing between lexical entries and the trees associated with the lexical items. a compact organization is achieved by organizing the lexicon in a hierarchical fashion and using inheritance as well as by using lexical and syntactic rules.while different organizations (flickinger, 1987; pollard and sag, 1987; shieber, 1986) of the lexicon have been proposed, in the scheme we propose, the inheritance hierarchy not only provides structure-sharing of lexical information but also of the associated elementary trees of extended domain of locality. furthermore, the lexical and syntactic rules can be used to derive new elementary trees from the default structures specified in the hierarchical lexicon.in the envisaged scheme, the use of a hierarchical lexicon and of lexical and syntactic rules for lexicalized tree-adjoining grammars will capture important linguistic generalizations and also allows for a space efficient representation of the grammar. this will allow for easy maintenance and facilitate updates to the grammar.
hmm-based word alignment in statistical translation. in this paper, we describe a new model for word alignment in statistical translation and present experimental results. the idea of the model is to make the alignment probabilities dependent on the differences in the alignment positions rather than on the absolute positions. to achieve this goal, the approach uses a first-order hidden markov model (hmm) for the word alignment problem as they are used successfully in speech recognition for the time alignment problem. the difference to the time alignment hmm is that there is no monotony constraint for the possible word orderings. we describe the details of the model and test the model on several bilingual corpora.
structural correspondence specification environment. this article presents the structural correspondence specification environment (scse) being implemented at geta.the scse is designed to help linguists to develop, consult and verify the scs grammars (scsg) which specify linguistic models. it integrates the techniques of data bases, structured editors and language interpreters. we argue that formalisms and tools of specification are as important as the specification itself.
tree adjoining and head wrapping. in this paper we discuss the formal relationship between thw classes of languages generated by tree adjoining grammars and head grammars. in particular, we show that head languages are included in tree adjoining languages and that tree adjoining grammars are equivalent to a modification of head grammars called modified head grammars. the inclusion of mhl in hl, and thus the equivalence of hg's and tag's in the most general case remains to be established.
finite-state phrase parsing by rule sequences. we present a novel approach to parsing phrase grammars based on eric brill's notion of rule sequences. the basic framework we describe has somewhat less power than a finite-state machine, and yet achieves high accuracy on standard phrase parsing tasks. the rule language is simple, which makes it easy to write rules. further, this simplicity enables the automatic acquisition of phrase-parsing rules through an error-reduction strategy.
issues in word choice. this paper discusses word choice for natural language generation. it examines 11 issues, the solutions that have been proposed for them, and their implications for design. the issues are:how are appropriate words chosen?how is conciseness ensured?when does choice stop?how are patterns of lexicalization respected?how are interactions among choices handrled?how are the correct parts of speech chosen?how are words chosen to satisfy constituency?what ensures that a word stands in the correct relation to its neighbors?how is word order determined?are all words chosen in the same way?in what order are the factors considered?this paper also discusses fig, a generator which incorporates novel solutions to many of these issues. fig violates common assumptions about the roles of modularity and grammar in generator design. analysis of fig leads to 4 principles for generator design, as follows:have an explicit representation of the status of the generation process at each point in time.use a single, unified representation.do not rely on the details of the structure of the input.treat most choices as emergent.
using sentence connectors for evaluating mt output. this paper elaborates on the design of a machine translation evaluation method that aims to determine to what degree the meaning of an original text is preserved in translation, without looking into the grammatical correctness of its constituent sentences. the basic idea is to have a human evaluator take the sentences of the translated text and, for each of these sentences, determine the semantic relationship that exists between it and the sentence immediately preceding it. in order to minimise evaluator dependence, relations between sentences are expressed in terms of the conjuncts that can connect them, rather than through explicit categories. for an n-sentence text this results in a list of n-1 sentence-to-sentence relationships, which we call the text's connectivity profile. this can then be compared to the connectivity profile of the original text, and the degree of correspondence between the two would be a measure for the quality of the translation.a set of "essential" conjuncts was extracted for english and japanese, and a computer interface was designed to support the task of inserting the most fitting conjuncts between sentence pairs. with these in place, several sets of experiments were performed.
an alternative to deep case for representing relational information. no one has come up with a completely satisfactory set of deep cases relations (or thematic relations). the underlying reason is that any finite set of case relations can capture only some of the generalizations desired. i propose instead a feature-space representation of relational information, where the axes are such things as degree of responsibility, degree of activity, and degree of affectedness. the role of a participant in an event can then be described as a point in this space, allowing more accurate representation of relational information. the domain of validity of each relevant linguistic generalizations corresponds to a prototype-centered region in the space. this proposal is easy to implement.
a method for accelerating cfg-parsing by using dependency information. this paper describes an algorithm for accelerating the cfg-parsing process by using dependency (or modifier-modifiee relationship) information given by, for instance, dependency estimation programs such as stochastic parsers, user's indication in an interactive application, and linguistic annotations added in a source text. this is a method for enhancing existing grammar-based cfg-parsing system by using dependency information.
a similarity-driven transfer system. the transfer phase in machine translation (mt) systems has been considered to be more complicated than analysis and generation, since it is inherently a conglomeration of individual lexical rules. currently some attempts are being made to use case-based reasoning in machine translation, that is, to make decisions on the basis of translation examples at appropriate points in mt. this paper proposes a new type of transfer system, called a similarity-driven transfer system (sim tran), for use in such case-based mt (cbmt).
a method for distinguishing exceptional and general examples in example-based transfer systems. distinguishing exceptional translation examples is an important issue in example-based transfer systems, because such systems use exceptional and general translation examples uniformly. this paper describes a mechanism for dealing with exceptional translation examples in our example-based transfer system, simtran, and proposes a method for identifying such examples in a translation example-base.
a method for abstracting newspaper articles by using surface clues. this paper describes a system which automatically creates an abstract of a newspaper article by selecting important sentences of a given text. to determine the importance of a sentence, several superficial features are considered, and weights for features are determined by multiple-regression analysis of a hand processed corpus.
finding structural correspondences from bilingual parsed corpus for corpus-based translation. in this paper, we describe a system and methods for finding structural correspondences from the paired dependency structures of a source sentence and its translation in a target language. the system we have developed finds word correspondences first, then finds phrasal correspondences based on word correspondences. we have also developed a gui system with which a user can check and correct the correspondences retrieved by the system. these structural correspondences will be used as raw translation patterns in a corpus-based translation system.
document classification using domain specific kanji characters extracted by x2 method. in this paper we describe a method of classifying japanese text documents using domain specific kanji characters. text documents are generally classified by significant words (keywords) of the documents. however, it is difficult to extract these significant words from japanese text, because japanese texts are written without using blank spaces, such as delimiters, and must be segmented into words. therefore, instead of words, we used domain specific kanji characters which appear more frequently in one domain than the other. we extracted these domain specific kanji characters by x2 method. then, using these domain specific kanji characters, we classified editorial columns "tensei jingo", editorial articles, and articles in "scientific american (in japanese)". the correct recognition scores for them were 47%, 74%, and 85%, respectively.
an annotation system for enhancing quality of natural language processing. natural language processing (nlp) programs are confronted with various difficulties in processing html and xml documents, and have the potential to produce better results if linguistic information is annotated in the source texts. we have therefore developed the linguistic annotation language (or lal), which is an xml-compliant tag set for assisting natural language processing programs, and nlp tools such as parsers and machine translation programs which can accept lal-annotated input. in addition, we have developed a lal-annotation editor which allows users to annotate documents graphically without seeing tags. further, we have conducted an experiment to check the translation quality improvement by using lal annotation.
bidirectional decoding for statistical machine translation. this paper describes the right-to-left decoding method, which translates an input string by generating in right-to-left direction. in addition, presented is the bidirectional decoding method, that can take both of the advantages of left-to-right and right-to-left decoding method by generating output in both ways and by merging hypothesized partial outputs of two directions. the experimental results on japanese and english translation showed that the right-to-left was better for englith-to-japanese translation, while the left-to-right was suitable for japanese-to-english translation. it was also observed that the bidirectional method was better for english-to-japanese translation.
free adjuncts in natural language instructions. in this paper, we give a brief account of our project animation from instructions, the view of instructions it reflects, and the semantics of one construction - the free adjunct - that is common in natural language instructions.
tokenization as the initial phase in nlp. in this paper, the authors address the significance and complexity of tokenization, the beginning step of nlp. notions of word and token are discussed and defined from the viewpoints of lexicography and pragmatic implementation, respectively. automatic segmentation of chinese words is presented as an illustration of tokenization. practical approaches to identification of compound tokens in english, such as idioms, phrasal verbs and fixed expressions, are developed.
a concept of derivation for lfg. in this paper a version of lfg will be developed, which has only one level of representation and is equivalent to the modified version of [2], presented in [3]. the structures of this monostratal version are f-structures, augmented by additional information about the derived symbols and their linear order. for these structures it is possible to define an adequate concept of direct derivability by which the derivation process becomes more efficient, as the f-description solution algorithm is directly simulated during the derivation of these structures, instead of being postponed. apart from this it follows from this reducability that lfg as a theory in its present form does not make use of the c-structure information that goes beyond the mere linear order of the derived symbols.
generation as structure driven derivation. this paper describes two algorithms which construct two different types of generators for lexical functional grammars (lfgs). the first type generates sentences from functional structures and the second from semantic structures. the latter works on the basis of oxtended lfgs, which contain a mapping from f-structures into semantic structures. both algorithms can be used on all grammars within the respective class of lfg-grammars. thus sentences can be generated from input structures by means of lfg-grammars and the same grammar formalism, although not necessarily the same grammar, can be used for both analysis and synthesis.
on inference-based procedures for lexical disambiguation. in this paper we sketch a decidable inference-based procedure for lexical disambiguation which operates on semantic representations of discourse and conceptual knowledge. in contrast to other approaches which use a classical logic for the disambiguating inferences and run into decidability problems, we argue on the basis of empirical evidence that the underlying inference mechanism has to be essentially incomplete in order to the (cognitively) adequate. since our conceptual knowledge can be represented in a rather restricted representation language, it is then possible to show that the restrictions satisfied by the conceptual knowledge and the inferences ensure in an empirically adequate way the decidability of the problem, although a fully expressive language is used to represent discourse.
sts: an experimental sentence translation system. sts is a small experimental sentence translation system developed to demonstrate the efficiency of our lexicalist model of translation. based on a gb-inspired parser, lexical transfer and lexical projection, sts provides real-time accurate english translations for a small but non-trivial subset of french sentences.
the ips system. the ips system is a large-scale interactive gb-based parsing system (english, french) under development at the university of geneva. this paper starts with an overview of the system, discussing some of its basic features as well as its general architecture. we then turn to a more detailed discussion of the "right corner" parsing strategy developed for this project. combining top down and bottom up features, this strategy is consistent with an incremental interpretation of sentences.
automatic english-to-korean text translation of telegraphic messages in a limited domain. this paper describes our work-in-progress in automatic english-to-korean text translation. this work is an initial step toward the ultimate goal of text and speech translation for enhanced multilingual and multinational operations. for this purpose, we have adopted an interlingua approach with natural language understanding (tina) and generation (genesis) modules at the core. we tackle the ambiguity problem by incorporating syntactic and semantic categories in the analysis grammar. our system is capable of producing accurate translation of complex sentences (38 words) and sentence fragments as well as average length (12 words) grammatical sentences. two types of system evaluation have been carried out: one for grammar coverage and the other for overall performance. for system robustness, integration of two subsystems is under way: (i) a rule-based part-of-speech tagger to handle unknown words/constructions, and (ii) a word-forword translator to handle other system failures.
using constraints in a constructive version of gpsg. complex categories are caracteristic of unification grammars as for example gpsg [shieber86a]. they are sets of pairs of features and values. the unification, which can be applied to two or more categories, is the essential operation.the papers of [shieber85], [barton85] and [ristad86] deal with the influence of complex categories on the efficiency of the parsing algorithm. this is one problem from using complex categories, another one arises when using a constructive version of gpsg (see [busemann/hauenschild88] in this volume). namely that the application of admissibility conditions, e.g. lp statements and fcrs1, to a local tree t is prevented because particular feature values of categories in t are not yet specified, but they will be instantiated later somewhere else in the complete tree. similar problems are described in [karttunen86] for d-patr.this work describes the latter problem and will present a solution working with computation, evaluation and propagation of constraints within local trees (depth 1). the constraint evaluation will reject local trees if the constraints of the subtrees of the daughters are violated.
term-rewriting as a basis for a uniform architecture in machine translation. in machine translation (mt) different levels of representation can be used to translate a source language sentence onto its target language equivalent. these levels have to be related to each other. this paper describes a declarative formalism on the basis of term-rewriting which maps one representation onto an equivalent adjacent one. the different levels (e.g. represented by derivational trees, feature structures or expressions of a knowledge representation language) can be represented as terms. the equivalences between them are stated as axioms which are directed to form a non-confluent and terminating term-rewrite system. a complete and coherent algorithm has been developed which interprets these systems and is able to handle default rules.
direct parsing with metarules. in this paper we argue for the direct application of metarules in the parsing process and introduce a slight restriction on metarules. this restriction relies on theoretical results about the termination of term-rewrite systems and does not reduce the expressive power of metarules as much as previous restrictions. we prove the termination for a set of metarules used in our german grammar and show how metarules can be integrated into the parser.
selforganizing classification on the reuters news corpus. in this paper we propose an integration of a selforganizing map and semantic networks from wordnet for a text classification task using the new reuters news corpus. this neural model is based on significance vectors and benefits from the presentation of document clusters. the hypernym relation in wordnet supplements the neural model in classification. we also analyse the relationships of news headlines and their contents of the new reuters corpus by a series of experiments. this hybrid approach of neural selforganization and symbolic hypernym relationships is successful to achieve good classification rates on 100,000 full-text news articles. these results demonstrate that this approach can scale up to a large real-world task and show a lot of potential for text classification.
learning dialog act processing. in this paper we describe a new approach for learning dialog act processing. in this approach we integrate a symbolic semantic segmentation parser with a learning dialog act network. in order to support the unforeseeable errors and variations of spoken language we have concentrated on robust data-driven learning. this approach already compares favorably with the statistical average plausibility method, produces a segmentation and dialog act assignment for all utterances in a robust manner, and reduces knowledge engineering since it can be bootstrapped from rather small corpora. therefore, we consider this new approach as very promising for learning dialog act processing.
a formal computational semantics and pragmatics of speech acts. this paper outlines a formal computational semantics and pragmatics of the major speech act types. a theory of force is given that allows us to give a semantically and pragmaticaly motivated taxonomy of speech acts. the relevance of the communication theory to complex distribution artificial intellince, dai, systems is described.
conceptual structures and ccc: linking theory and incorporated argument adjuncts. in combinatory categorial grammar (ccg) [ste90, ste91], semantic function-argument structures are compositionally produced through the course of a derivation. these structures identify, inter alia, which entities play the same roles in different events for expressions involving a wide range of coordinate constructs. this sameness of role (i.e. thematic) information is not identified, however, across cases of verbal diathesis. to handle these cases as well, the present paper demonstrates how to adapt the solution developed in conceptual semantics [jac90, jac91] to fit the ccg paradigm.the essence of the approach is to redefine the linking theory component of conceptual semantics in terms of ccg categories, so that derivations yield conceptual structures representing the desired thematic information; in this way no changes are required on the ccg side. while this redefinition is largely straightforward, an interesting problem arises in the case of conceptual semantics' incorporated argument adjuncts. in examining these, the paper shows that they cannot be treated as adjuncts in the ccg sense without introducing new machinery, nor without compromising the independence of the two theories. for this reason, the paper instead adopts the more traditional approach of treating them as oblique arguments.
a graph model for unsupervised lexical acquisition. this paper presents an unsupervised method for assembling semantic knowledge from a part-of-speech tagged corpus using graph algorithms. the graph model is built by linking pairs of words which participate in particular syntactic relationships. we focus on the symmetric relationship between pairs of nouns which occur together in lists. an incremental cluster-building algorithm using this part of the graph achieves 82% accuracy at a lexical acquisition task, evaluated against wordnet classes. the model naturally realises domain and corpus specific ambiguities as distinct components in the graph surrounding an ambiguous word.
identifying subjective characters in narrative. part of understanding fictional narrative text is determining for each sentence whether it takes some character's point of view and, if it does, identifying the character whose point of view is taken. this paper presents part of an algorithm for performing the latter. when faced with a sentence that takes a character's point of view, the reader has to decide whether that character is a previously mentioned character or one mentioned in the sentence. we give particular consideration to sentences about private states, such as seeing and wanting, for which both possibilities exist. our algorithm is based on regularities in the ways that texts initiate, continue, and resume a character's point of view, found during extensive examinations of published novels and short stories.
reversible delayed lexical choice in a bidirectional framework. we describe a bidirectional framework for natural language parsing and generation, using a typed feature formalism and an hpsg-based grammar with a parser and generator derived from parallel processing algorithms. we present an approach to delayed lexical choice in generation, based on subsumption within the sort hierarchy, using a lexicon of under-instantiated signs which are derived from the normal lexicon by lexical rules. we then show how delayed lexical choice can be used in parsing, so that some types of ill-formed inputs can be parsed, but well-formed outputs are generated, using the same shared linguistic information.
extending the lexicon by exploiting subregularities. this paper is concerned with the acquisition of the lexicon. in particular, we propose a method that uses analogical reasoning to hypothesize new polysemous word senses. this method is one of a number of knowledge acquisition devices to be included in dirc (domain independent retargetable consultant). dirc is a kind of intelligent, natural language-capable consultant kit that can be retargeted at different domains. dirc is essentially "empty-uc" (unix consultant, wilensky et al., 1988). dirc is to include the language and reasoning mechanisms of uc, plus a large grammar and a general lexicon. the user must then add domain knowledge, user knowledge and lexical knowledge for the area of interest.
using a hybrid system of corpus- and knowledge-based techniques to automate the induction of a lexical sublanguage grammar. porting a natural language processing (nlp) system to a new domain remains one of the bottleneeks in syntactic parsing, because of the amount of effort required to fix gaps in the lexicon, and to attune the existing grammar to the idiosyncracies of the new sublanguage. this paper shows how the process of fitting a lexicalized grammar to a domain can be automated to a great extent by using a hybrid system that combines traditional knowledge-based techniques with a corpus-based approach.
semiautomatic interactive muitilingual style analysis (simsa). a style checker is a tool which supports authors during the process of writing: certain style markers are analyzed, their values are compared with a given norm, deviations are detected, and recommendations are given to the author. the power of a style checker depends on available tools such as lexica, parser, etc. this paper describes a style checker which will be integrated in a workbench (translator's workbench) and which has access to lexica and parser. the style checker can be used for different languages and for different kinds of text.
incremental parsing and reason maintenance. the purpose of this paper is to compare different ways of adopting reason-maintenance techniques in incremental parsing (and interpretation). a reason-maintenance system supports incremental formation and revision of beliefs. by viewing the construction of partial analyses of a text as analogous to forming beliefs about the meanings of its parts, a relation between parsing and reason maintenance can be conceived. in line with this, reason maintenance can be used for realizing a strong notion of incremental parsing, allowing for revisions of previous analyses. moreover, an assumption-based reason-maintenance system (atms) can be used to support efficient comparisons of (competing) interpretations. the paper argues for an approach which is an extension of chart parsing, but which also can be seen as a system consisting of an inference engine (the parser proper) coupled with a simplified atms.
minimal change and bounded incremental parsing. ideally, the time that an incremental algorithm uses to process a change should be a function of the size of the change rather than, say, the size of the entire current input. based on a formalization of "the set of things changed" by an incremental modification, this paper investigates how and to what extent it is possible to give such a guarantee for a chart-based parsing framework and discusses the general utility of a minimality notion in incremental processing.
prosody and the resolution of pronominal anaphora. in this paper, we investigate the acoustic prosodic marking of demonstrative and personal pronouns in task-oriented dialog. although it has been hypothesized that acoustic marking affects pronoun resolution, we find that the prosodic information extracted from the data is not sufficient to predict antecedent type reliably. inter-speaker variation accounts for much of the prosodic variation that we find in our data. we conclude that prosodic cues should be handled with care in robust, speaker-independent dialog systems.
chinese word segmentation based on maximum matching and word binding force. a chinese word segmentation algorithm based on forward maximum matching and word binding force is proposed in this paper. this algorithm plays a key role in post-processing the output of a character or speech recognizer in determining the proper word sequence corresponding to an input line of character images or a speech waveform. to support this algorithm, a text corpus of over 63 millions characters is employed to enrich an 80,000-words lexicon in terms of its word entries and word binding forces. as it stands now, given an input line of text, the word segmentor can process on the average 210,000 characters per second when running on an ibm risc system/6000 3bt workstation with a correct word identification rate of 99.74%.
machine translation for monolinguals. we describe sister machine translation prototypes, ntran, an english to japanese system developed at umist, and aidtrans, japanese to english, at sheffield, both designed for use by an english monolingual. aidtrans uses extensive and sophisticated collocational analysis radically to reduce the need for conventional post-editing. ntran offers interactive query at three stages: on-line dictionary update, syntactic disambiguation, and japanese lexical selection. the second of these is described and illustrated in particular detail, and the underlying philosophy of monolingual interaction discussed.
machine learing of morphological rules by generalization and analogy. this paper describes an experimental procedure for the inductive automated learning of morphological rules from examples. at first an outline of the problem is given. then a formalism for the representation of morphological rules is defined. this formalism is used by the automated procedure, whose anatomy is subsequently presented. finally the performance of the system is evaluated and the most important unsolved problems are discussed.
massive disambiguation of large text corpora with flexible categorial grammar. a new method of automatic lexical disambiguation of big texts is described, using recent proof-theoretical results from the theory of categorial grammar.
dynamic lexical acquisition in chinese sentence analysis. dynamic lexical acquisition is a procedure where the lexicon of an nlp system is updated automatically during sentence analysis. in our system, new words and new attributes are proposed online according to the context of each sentence, and then get accepted or rejected during syntactic analysis. the accepted lexical information is stored in an auxiliary lexicon which can be used in conjunction with the existing dictionary in subsequent processing. in this way, we are able to process sentences with an incomplete lexicon and fill in the missing info without the need of human editing. as the auxiliary lexicons are corpus-based, domain-specific dictionaries can be created automatically by combining the existing dictionary with different auxiliary lexicons. evaluation shows that this mechanism significantly improves the coverage of our parser.
disambiguation and language acquisition through th phrasal lexicon. the phrasal approach to language processing emphasizes the role of the lexicon as a knowledge source. rather than maintaining a single generic lexical entry for each word e.g., take, the lexicon contains many phrases, e.g., take on, take to the streets, take to swimming, take over, etc. although this approach proves effective in parsing and in generation, there are two acute problems which still require solutions. first, due to the huge size of the phrasal lexicon, especially when considering subtle meanings and idiosyneratic behavior of phrases, encoding of lexical entries cannot be done manually. thus, phrase acquisition must be employed to construct the lexicon. second, when a set of phrases is morpho-syntactically equivalent, disambiguation must be performed by semantic means. these problems are addressed in the program rina.
figuring out most plausible interpretation from spatial descriptions. the problem we want to handle in this paper is vagueness. a notion of space, which we basically have, plays an important part in the faculty of thinking and speech. in this paper, we concentrate on a particular class of spatial descriptions, namely descriptions about positional relations on a two-dimensional space. a theoretical device we present in this paper is called the potential model. the potential model provides a means for accumulating from fragmentary information. it is possible to derive maximally plausible interpretation from a chunk of information accumulated in the model. when new information is given, the potential model is modefied so that that new information is taken into account. as a result, the interpretations with maximal plausibility may change. a program called sprint(spatial relation in-terpreter) reflecting our theory is in the way of construction.
tagging for learning: collecting thematic relations from corpus. recent work in text analysis has suggested that data on words that frequently occur together reveal important information about text content. co-occurrence relations can serve two main purposes in language processing. first, the statistics of co-occurrence have been shown to produce accurate results in syntactic analysis. second, the way that words appear together can help in assigning thematic roles in semantic interpretation. this paper discusses a method for collecting co-occurrence data, acquiring lexical relations from the data, and applying these relations to semantic analysis.
reconstructing spatial image from natural language texts. this paper describes the understanding process of the spatial descriptions in japanese. in order to understand the described world, the authors try to reconstruct the geometric model of the global scene from the scenic descriptions drawing a space. it is done by an experimental computer program sprint, which takes natural language texts and produces a model of the described world. to reconstruct the model, the authors extract the qualitative spatial constraints from the text, and represent them as the numerical constraints on the spatial attributes of the eutities. this makes it possible to express the vagueness of the spatial concepts and to derive the maximally plausible interpretation from a chunk of information accumulated as the constraints. the interpretation reflects the temporary belief about the world.
morphological analysis and synthesis by automated discovery and acquisition of linguistic rules. this paper describes a rule-based machine learning approach to morphological processing in the system called xmas. xmas discovers and acquires linguistic rules from examples of morphological combinations and accomplishes the morphological analysis and synthesis by applying the rules. this approach is independent of languages, saves time and effort for development and maintenance, and takes small lexicon space. a korean version of xmas is effectively working in the english-korean machine translation system kshalt.
machine translation by interaction between paraphraser and transfer. a machine translation model has been proposed where an input is translated through both source-language and target-language paraphrasing processes. we have implemented our prototype model for the japanese-chinese language pair. this paper. describes our core idea of translation, where a source language paraphraser and a language transfer cooperates in translation by exchanging information about the source input.
chinese syntactic parsing based on extended glr parsing algorithm with pcfg*. this paper presents an extended glr parsing algorithm with grammar pcfg* that is based on tomita's glr parsing algorithm and extends it further. we also define a new grammar---pcfg* that is based on pcfg and assigns not only probability but also frequency associated with each rule. so our syntactic parsing system is implemented based on rule-based approach and statistics approach. furthermore our experiments are executed in two fields: chinese base noun phrase identification and full syntactic parsing. and the results of these two fields are compared from three ways. the experiments prove that the extended glr parsing algorithm with pcfg* is an efficient parsing method and a straightforward way to combine statistical property with rules. the experiment results of these two fields are presented in this paper.
acquisition of phrase-level bilingual correspondence using dependency structure. this paper describes a method to find phrase-level translation patterns from parallel corpora by applying dependency structure analysis. we use statistical dependency parsers to determine dependency relations between base phrases in a sentence. our method is tested with a business expression corpus containing 10000 english-japanese sentence pairs and achieved approximately 90% accuracy in extracting bilingual correspondences. the result shows that the use of dependency relation helps to acquire interesting translation patterns.
paraphrasing of chinese utterances. one of the key issues in spoken language translation is how to deal with unrestricted expressions in spontaneous utterances. this research is centered on the development of a chinese paraphraser that automatically paraphrases utterances prior to transfer in chinese-japanese spoken language translation. in this paper, a pattern-based approach to paraphrasing is proposed for which only morphological analysis is required. in addition, a pattern construction method is described through which paraphrasing patterns can be efficiently learned from a paraphrase corpus and human experience. using the implemented paraphraser and the obtained patterns, a paraphrasing experiment was conducted and the results were evaluated.
predicting noun-phrase surface forms using contextual information. we propose a context-sensitive method to predict noun-phrases in the next utterance of a telephone inquiry dialogue. first, information about the utterance type and the discourse entities of the next utterance is grasped using a dialogue interpretation model. second, a domain-dependent knowledge base for noun-phrase usage is developed, focusing on the dialogue situations in context. finally, we propose a strategy to make a set of the appropriate expressions in the next utterance, using the information and the knowledge base. this set of expressions is used to select the correct candidate from the speech recognition output. this paper examines some of the processes creating sets of polite expressions, deicti&cacute; expressions, and compound noun phrases, which are common in telephone inquiry dialogue.
collocational analysis in japanese text input. this paper proposes a new disambiguation method for japanese text input. this method evaluates candidate sentences by measuring the number of word co-occurrence patterns (wcp) included in the candidate sentences. an automatic wcp extraction method is also developed. an extraction experiment using the example sentences from dictionaries confirms that wcp can be collected automatically with an accuracy of 98.7% using syntactic analysis and some heuristic rules to eliminate erroneous extraction. using this method, about 305,000 sets of wcp are collected. a co-occurrence pattern matrix with semantic categories is built based on these wcp, using this matrix, the mean number of candidate sentences in kana-to-kanji translation is reduced to about 1/10 of those from existing morphological methods.
complex features in description of chinese language. in this paper, the similarity of "multi---value label function" and "complex features" is discussed. the author especially emphasizes the necessity of complex features for description of chinese language.
local context templates for chinese constituent boundary prediction. in this paper, we proposed a shallow syntactic knowledge description: constituent boundary representation and its simple and efficient prediction algorithm, based on different local context templates learned from the annotated corpus. an open test on 2780 chinese real text sentences showed the satisfying results: 94% (92%) precision for the words with multiple (single) boundary tag output.
the semantic representation of spatial configurations: a conceptual motivation for generation in machine translation. this paper deals with the automatic translation of prepositions, which are highly polysemous. moreover, the same real situation is often expressed by different prepositions in different languages. we proceed from the hypothesis that different usage patterns are due to different conceptualizations of the same real situation. following cognitive principles of spatial conceptualization, we design a semantic interpretation process for spatial relations in which our translation system uses semantic features derived from a semantic sort hierarchy. thus we can differentiate subtle distinctions between spatially significant configurations.
an efficient syntactic tagging tool for corpora. the tree bank is an important resoures for mt and linguistics researches, but it requires that large number of sentences be annotated with syntactic information. it is time consuming and troublesome, and difficult to keep consistency, if annotation is done manually. in this paper, we presented a new technique for the semi-automatic tagging of chinese text. the system takes as input chinese text, and outputs the syntactically tagged sentence(dependency tree). we use dependency grammar and employ a stack based shift/ reduce context-dependent parser as the tagging mechanism. the system works in human-machine cooperative way, in which the machine can acquire tagging rules from human intervention. the automation level can be improved step by step by accumulating rules during annotation. in addition, good consistency of tagging is guaranteed.
the chinese aspect system and its semantic interpretation. motivated by a systematic representation of the chinese aspect forms that explores their intrinsic semantics and temporal logical relations, we are constructing a chinese aspect system network based on systemic functional grammar and implemented using the multilingual generator kpml. in this paper, we introduce the basic simple primary aspect forms and a set of secondary types of the unmarked-durative aspect in our chinese aspect system, describe the semantic temporal relations of complex aspect in terms of temporal logic theories, and propose principled semantic conditions for aspect combination. finally, we give a brief explanation of the system implementation.
a linear least squares fit mapping method for information retrieval from natural language texts. this paper describes a unique method for mapping natural language texts to canonical terms that identify the contents of the texts. this method learns empirical associations between free-form texts and canonical terms from human-assigned matches and determines a linear least squares fit (llsf) mapping function which represents weighted connections between words in the texts and the canonical terms. the mapping function enables us to project an arbitrary text to the canonical term space where the "transformed" text is compared with the terms, and similarity scores are obtained which quantify the relevance between the the text and the terms. this approach has superior power to discover synonyms or related terms and to preserve the context sensitivity of the mapping. we achieved a rate of 84% in both the recall and the precision with a testing set of 6,913 texts, outperforming other techniques including string matching (15%), morphological parsing (17%) and statistical weighting (21%).
considerations of linking wordnet with mrd. this paper introduces a bilingual mrd (english-chinese ldoce) to help with the construction of a chinese wordnet. considerable linking strategies are discussed and proper translations are attached to 28,388 noun synsets and 10,380 verb synsets of wn 1.7 automatically. the steady precision (92~94%) shows the corresponding headwords and matching keywords provide considerable guarantee for linking. the chinese phrases need to be processed further to match the correct synset due to the fine-grained senses of wordnet.
use of heuristic knowledge in chinese language analysis. this paper describes an analysis method which uses heuristic knowledge to find local syntactic structures of chinese sentences. we call it a preprocessing, because we use it before we do global syntactic structure analysis (1) of the input sentence. our purpose is to guide the global analysis through the search space, to avoid unnecessary computation.to realize this, we use a set of special words that appear in commonly used patterns in chinese. we call them "characteristic words". they enable us to pick out fragments that might figure in the syntactic structure of the sentence. knowledge concerning the use of characteristic words enables us to rate alternative fragments, according to pattern statistics, fragment length, distance between characteristic words, and so on. the preprocessing system proposes to the global analysis level a most "likely" partial structure. in case this choice is rejected, backtracking looks for a second choice, and so on.for our system, we use 200 characteristic words. their rules are written by 101 automata. we tested them against 120 sentences taken from a chinese physics text book. for this limited set, correct partial structures were proposed as first choice for 94% of sentences. allowing a 2nd choice, the score is 98%, with a 3rd choice, the score is 100%.
automatic acquisition of domain knowledge for information extraction. in developing an information extraction (ie) system for a new class of events or relations, one of the major tasks is identifying the many ways in which these events or relations may be expressed in text. this has generally involved the manual analysis and, in some cases, the annotation of large quantities of text involving these events. this paper presents an alternative approach, based on an automatic discovery procedure, exdisco, which identifies a set of relevant documents and a set of event patterns from un-annotaled text, starting from a small set of "seed patterns." we evaluate exdisco by comparing the performance of discovered patterns against that of manually constructed systems on actual extraction tasks.
the power of words in message planning. before engaging in a conversation, a message must be planned. while there are many ways to perform this task, i believe that people do this in the following way, in particular if the message is going to be long: first an outline is planned (global, or skeleton planning), which is then filled in with details (local planning, elaboration). planning proceeds thus from general to specific (breadth first), that is, sentences are planned incremetally by gradual refinement of some abstract thought rather than in one go (one-shot process) where every element is planned down to its last details.while global planning is largely language independent, local planning can be language dependent: the dictionary acts a mediator, interfacing language and thought. given the fact that words can be used to specify non linguistic thought, there is feedback from the lexical to the conceptual component. this being so, dictionaries may play a fundamental role in guiding and potentially modifying non linguistic thought. if my view is correct, this could have implications on the design of generation architectures: instead of separating message planning and realization, viewing the process as being strictly sequential, we could allow for feedback loops (interleaved process), whereby the linguistic component could feed back to the conceptual component.
unsupervised learning of generalized names. we present an algorithm, nomen, for learning generalized names in text. examples of these are names of diseases and infectious agents, such as bacteria and viruses. these names exhibit certain properties that make their identification more complex than that of regular proper names, nomen uses a novel form of bootstrapping to grow sets of textual instances and of their contextual patterns. the algorithm makes use of competing evidence to boost the learning of several categories of names simultaneously. we present results of the algorithm on a large corpus. we also investigate the relative merits of several evaluation strategies.
an automatic evaluation method for localization oriented lexicalised ebmt system. to help developing a localization oriented ebmt system, an automatic machine translation evaluation method is implemented which adopts edit distance, cosine correlation and dice coefficient as criteria. experiment shows that the evaluation method distinguishes well between "good" translations and "bad" ones. to prove that the method is consistent with human evaluation, 6 mt systems are scored and compared. theoretical analysis is made to validate the experimental results. correlation coefficient and significance tests at 0.01 level are made to ensure the reliability of the results. linear regression equations are calculated to map the automatic scoring results to human scorings.
word-sense disambiguation using statistical models of roget's categories trained on large corpora. this paper describes a program that disambiguates english word senses in unrestricted text using statistical models of the major roget's thesaurus categories. roget's categories serve as approximations of conceptual classes. the categories listed for a word in roget's index tend to correspond to sense distinctions; thus selecting the most likely category provides a useful level of sense disambiguation. the selection of categories is accomplished by identifying and weighting words that are indicative of each category when seen in context, using a bayesian theoretical framework.other statistical approaches have required special corpora or hand-labeled training examples for much of the lexicon. our use of class models overcomes this knowledge acquisition bottleneck, enabling training on unrestricted monolingual text without human intervention. applied to the 10 million word grolier's encyclopedia, the system correctly disambiguated 92% of the instances of 12 polysemous words that have been previously studied in the literature.
lfg system in prolog. in order to design and maintain a large scale grammar, the formal system for representing syntactic knowledge should be provided. lexical functional grammar (lfg) [kaplan, bresnan 82] is a powerful formalism for that purpose. in this paper, the prolog implementation of lfg system is described. prolog provides a good tools for the implementation of lfg. lfg can be translated into dcg [pereira, warren 80] and functional structures (f-structures) are generated during the parsing process.
can subcategorization help a statistical dependency parser? today there is a relatively large body of work on automatic acquisition of lexico-syntactical preferences (subcategorization) from corpora. various techniques have been developed that not only produce machine-readable subcategorization dictionaries but also they are capable of weighing the various subcategorization frames probabilistically. clearly there should be a potential to use such weighted lexical information to improve statistical parsing, though published experiments proving (or disproving) such hypothesis are comparatively rare. one experiment is described in (carroll et al., 1998) --- they use subcategorization probabilities for ranking trees generated by unification-based phrasal grammar. the present paper, on the other hand, involves a statistical dependency parser. although dependency and constituency parsing are of quite a different nature, we show that a subcategorization model is of much use here as well.
voice simulation: factors affecting quality and naturalness. in this paper we describe a flexible analysis-synthesis system which can be used for a number of studies in speech research. the main objective is to have a synthesis system whose characteristics can be controlled through a set of parameters to realize any desired voice characteristics. the basic synthesis scheme consists of two steps: generation of an excitation signal from pitch and gain contours and excitation of the linear system model described by linear prediction coefficients. we show that a number of basic studies such as time expansion/compression, pitch modifications and spectral expansion/compression can be made to study the effect of these parameters on the quality of synthetic speech. a systematic study is made to determine factors responsible for unnaturalness in synthetic speech. it is found that the shape of the glottal pulse determines the quality to a large extent. we have also made some studies to determine factors responsible for loss of intelligibility in some segments of speech. a signal dependent analysis-synthesis scheme is proposed to improve the intelligibility of dynamic sounds such as stops. a simple implementation of the signal dependent analysis is proposed.
more accurate tests for the statistical significance of result differences. statistical significance testing of differences in values of metrics like recall, precision and balanced f-score is a necessary part of empirical natural language processing. unfortunately, we find in a set of experiments that many commonly used tests often underestimate the significance and so are less likely to detect differences that exist between different techniques. this underestimation comes from an independence assumption that is often violated. we point out some useful tests that do not make this assumption, including computationally-intensive randomization tests.
towards a noise-tolerant, representation-independent mechanism for argument interpretation. we describe a mechanism for the interpretation of arguments, which can cope with noisy conditions in terms of wording, beliefs and argument structure. this is achieved through the application of the minimum message length principle to evaluate candidate interpretations. our system receives as input a quasi-natural language argument, where propositions are presented in english, and generates an interpretation of the argument in the form of a bayesian network (bn). performance was evaluated by distorting the system's arguments (generated from a bn) and feeding them to the system for interpretation. in 75% of the cases, the interpretations produced by the system matched precisely or almost-precisely the representation of the original arguments.
comparing two trainable grammatical relations finders. grammatical relationships (grs) form an important level of natural language processing, but different sets of grs are useful for different purposes. therefore, one may often only have time to obtain a small training corpus with the desired gr annotations. on such a small training corpus, we compare two systems. they use different learning techniques, but we find that this difference by itself only has a minor effect. a larger factor is that in english, a different gr length measure appears better suited for finding simple argument grs than for finding modifier grs. we also find that partitioning the data may help memory-based learning.
lexical query paraphrasing for document retrieval. we describe a mechanism for the generation of lexical paraphrases of queries posed to an internet resource. these paraphrases are generated using wordnet and part-of-speech information to propose synonyms for the content words in the queries. statistical information, obtained from a corpus, is then used to rank the paraphrases. we evaluated our mechanism using 404 queries whose answers reside in the la times subset of the trec-9 corpus. there was a 14% improvement in performance when paraphrases were used for document retrieval.
an empirical study on the generation of zero anaphors in chinese. in this paper, we describe the creation of rules for generating chinese zero anaphors through a sequence of experiments in a stepwise enhanced manner. in the experiments, we basically examined the occurence of zero anaphors in a real text and the ones generated by the algorithms employing the rules, assuming the same semantic and discourse structures as the text. the factors of locality, syntactic constraints, discourse structure and salience of objects were considered in the rules. the results of the experiment show that 93% of the zero anaphors in the text can be correctly generated by an algorithm using a rule involving all the above factors.
conceptual lexicon using an object-oriented language. this paper describes the construction of a lexicon representing abstract concepts. this lexicon is written by an object-oriented language, ctalk, and forms a dynamic network system controlled by object-oriented mechanisms. the content of the lexicon is constructed using a japanese dictionary. first, entry words and their definition parts are derived from the dictionary. second, syntactic and semantic information is analyzed from these parts. finally, superconcepts are assigned in the superconcept part in an object, static parts to the slot values, and dynamic operations to the message parts, respectively. one word has one object in a world, but through the superconcept part and slot part this connects to the subconcept of other words and worlds. when relative concepts are accumulated, the result will be a model of human thoughts which have conscious and unconscious parts.
deep sentence understanding in a restricted domain. we present here the current prototype of the text understanding system h&eacute;l&eacute;ne. the objective of this system is to achieve a deep understanding of small reports dealing with a restricted domain. sentence understanding builds a model of the state of the world described, through the application of several knowledge modules: (i) lfg parsing, (ii) syntactic disambiguation based on lexical entry semantic components, (iii) assembly of semantic components and instantiation of domain entities, and (iv) construction of a world model through activation of common sense and domain knowledge.
database system based on intensional logic. model theoretic semantics of database systems is studied. as rechard montague has done in his work,5 we translate statements of ddl and dml into intensional logic and the latter is interpreted with reference to a suitable model. major advantages of its approach include (i) it leads itself to the design of database systems which can handle historical data, (ii) it provides with a formal description of database semantics.
object-oriented parallel parsing for context-free grammars. this paper describes a new parallel parsing scheme for context-free grammars and our experience of implementing this scheme, and it also reports the result of our simulation for running the parsing program on a massive parallel processor.in our basic parsing scheme, a set of context free grammar rules is represented by a network of processor-like computing agents each having its local memory. each computing agent in the network corresponds to an occurrence of a non-terminal or terminal symbol appearing in the grammar rules. computing agents in the network work concurrently and communicate with one another by passing messages which are partial parse trees.this scheme is shown to be fast (0(n*h) time for the first complete parse tree, where n is the length of an input sentence and h is the height of the parse tree) and useful in various modes of parsing such as on-line parsing, overlap parsing, on-line unparsing, pipe-lining to semantics processing, etc. performance evaluation for implementing this scheme on a massive parallel machine is conducted by distributed event simulation using the time warp mechanism/jefferson85/.our parsing scheme is implemented in a programming language called abcl/1 which is designed for object-oriented concurrent programming and used for various concurrent programming /yonezawa86/. the program is currently runing on standard single-cpu machines such as sun3s and symbolics lisp machines (by simulated parallelism).in our experiment and simulation, a set of about 250 context-free grammar rules specifying a subset of english is represented by the corresponding network of objects (i.e., computing agents) and about 1100 concurrently executable objects are involved.
identifying temporal expression and its syntactic role using fst and lexical data from corpus. accurate analysis of the temporal expression is crucial for korean text processing applications such as information extraction and chunking for efficient syntactic analysis. it is a complicated problem since temporal expressions often have the ambiguity of syntactic roles. this paper discusses two problems: (1) representing and identifying the temporal expression (2) distinguishing the syntactic function of the temporal expression in case it has a dual syntactic role. in this paper, temporal expressions and the context for disambiguation which is called local context are represented using lexical data extracted from corpus and the finite state transducer. by experiments, it turns out that the method is effective for temporal expression analysis. in particular, our approach shows the corpus-based work could make a promising result for the problem in a restricted domain in that we can effectievely deal with a large size of lexical data.
a consideration on the concepts structure and language- in relation to selections of translation equivalents of verbs in machine translation system. to give appropriate translation equivalents for target words is one of the most fundamental problems in machine translation systems.especially, when the mt systems handle languages that have completely different structures like japanese and european languages as source and target languages. in this report, we discuss about the data structure that enables appropriate selections of translation equivalents for verbs in the target language. this structure is based on the concepts structure with associated information relating source and target languages.discussion have been made from the standpoint of realizability of the structure (e.g. from the standpoint of easiness of data collection and arrangement, easiness of realization and compactness of the size of storage space).
man-assisted machine construction of a semantic dictionary for natural language processing. this is a report on the semantic dictionary for natural language processing we are constructing now. this paper explains how to obtain the semantic information for the dictionary from an ordinary japanese language dictionary with about 60,000 items (which had already been put into machine readable form) and also explains what should be the frame for the representation of meaning of each item (word). then a man-assisted machine procedure that embeds the semantic graph with respect to the head word of the ordinary dictionary into the frame of a head word is discussed.
identifying zero pronouns in japanese dialogue. japanese dialogue containing zero pronouns is analyzed for the purpose of automatic japanese-english conversation translation. topic-driven discourse structure is formalized which identifies mainly non-human zero pronouns as a by-product. other zero pronouns are handled using cognitive and sociolinguistic information in honorific, deictic, speech-act and mental predicates. these are integrated into the model.
an analysis of indonesian language for interlingual machine-translation system. this paper presents bias (bahasa indonesia analyzer system), an analysis system for indonesian language suitable for multilingual machine translation system. bias is developed with a motivation to contribute to on-going cooperative research project in machine translation between indonesia and other asian countries. in addition, it may serve to foster nlp research in indonesia. it start with an overview of various methodologies for representation of linguistic knowledge and plausible strategies of automatic reasoning for indonesian language. we examine these methodologies from the perspective of their relative advantage and their suitability for an interlingual machine-translation environment. bias is a multi-level analyzer which is developed not only to extract the syntactic and semantic structure of sentences but also to provide a unifying method for knowledge reasoning. each phase of the analyzer is discussed with emphasis on indonesian morphology and case-grammatical constructions.
abl: alignment-based learning. this paper introduces a new type of grammar learning algorithm, inspired by string edit distance (wagner and fischer, 1974). the algorithm takes a corpus of flat sentences as input and returns a corpus of labelled, bracketed sentences. the method works on pairs of unstructured sentences that have one or more words in common. when two sentences are divided into parts that are the same in both sentences and parts that are different, this information is used to find parts that are interchangeable. these parts are taken as possible constituents of the same type. after this alignment learning step, the selection learning step selects the most probable constituents from all possible constituents.this method was used to bootstrap structure on the atis corpus (marcus et. al., 1993) and on the ovis! corpus (bonnema et al., 1997). while the results are encouraging (we obtained up to 89.25% non-crossing brackets precision), this paper will point out some of the shortcomings of our approach and will suggest possible solutions.
generation of accent in nominally premodified noun phrases. the primary purpose of this paper is to present a set of conditions that constrain accent placement in focused nominally premodified nps. selkirk (1984) argues that if the premodifier is an argument of the head, then the head can be deaccented. i agree with selkirk's proposal and argue that what is essential is not whether the premodifier is a grammatical argument of the head noun, but rather, whether it is a &theta;-complement in lexical conceptual structure. this proposal is evaluated by testing it against a corpus of naturally occurring data.
test-score semantics for natural languages. test-score semantics is based on the premise that almost everything that relates to natural languages is a matter of degree. viewed from this perspective, any semantic entity in a natural language, e.g., a predicate, predicate-modifier, proposition, quantifier, command, question, etc. may be represented as a system of elastic constraints on a collection of objects or derived objects in a universe of discourse. in this sense, test-score semantics may be viewed as a generalization of truth-conditional, possible-world and model-theoretic semantics, but its expressive power is substantially greater.
a computational theory of dispositions. informally, a disposition is a proposition which is preponderantly, but no necessarily always, true. for example, birds can fly is a disposition, as are the propositions swedes are blond and spaniards are dark.an idea which underlies the theory described in this paper is that a disposition may be viewed as a proposition with implicit fuzzy quantifiers which are approximations to all and always, e.g., almost all, almost always, most, frequently, etc. for example, birds can fly may be interpreted as the result of supressing the fuzzy quantifier most in the proposition most birds can fly. similarly, young men like young women may be read as most young men like mostly young women. the process of transforming a disposition into a proposition is referred to as explicitation or restoration.explicitation sets the stage for representing the meaning of a proposition through the use of test-score semantics (zadeh, 1978, 1982). in this approach to semantics, the meaning of a proposition, p, is represented as a procedure which tests, scores and aggregates the elastic constraints which are induced by p.the paper closes with a description of an approach to reasoning with dispositions which is based on the concept of a fuzzy syllogism. syllogistic reasoning with dispositions has an important bearing on commonsense reasoning as well as on the management of uncertainty in expert systems. as a simple application of the techniques described in this paper, we formulate a definition of typicality -- a concept which plays an important role in human cognition and is of relevance to default reasoning.
on compositional semantics. we prove a theorem stating that any semantics can be encoded as a compositional semantics, which means that, essentially, the standard definition of compositionality is formally vacuous. we then show that when one requires compositional semantics to be "systematic" (that is the meaning function cannot be arbitrary, but must belong to some class), one can easily distinguish between compositional and non-compositional semantics. we also present an example of a simple grammar for which there is no "systematic" compositional semantics. this implies that it is possible to distinguish "good" and "bad" grammars on the basis of whether they can have compositional semantics. as a result, we believe that the paper clarifies the concept of compositionality and opens a possibility of making systematic comparisons of different systems of grammars and nlu programs.
language acquisition: coping with lexical gaps. computer programs so far have not fared well in modeling language acquisition. for one thing, learning methodology applicable in general domains does not readily lend itself in the linguistic domain. for another, linguistic representation used by language processing systems is not geared to learning. we introduced a new linguistic representation, the dynamic hierarchical phrasal lexicon (dhpl) [zernik 88], to facilitate language acquisition. from this, a language learning model was implemented in the program rina, which enhances its own lexical hierarchy by processing examples in context. we identified two tasks: first, how linguistic concepts are acquired from training examples and organized in a hierarchy; this task was discussed in previous papers [zernik87]. second, we show in this paper how a lexical hierarchy is used in predicting new linguistic concepts. thus, a program does not stall even in the presence of a lexical unknown, and a hypothesis can be produced for covering that lexical gap.
nl understanding with a grammar of constructions. we present an approach to natural language understanding based on a computable grammar of constructions. a construction consists of a set of features of form and a description of meaning in a context. a grammar is a set of constructions. this kind of grammar is the key element of mincal, an implemented natural language speech-enabled interface to an on-line calendar system. the architecture has two key aspects: (a) the use of constructions, integrating descriptions of form, meaning and context into one whole; and (b) the separation of domain knowledge (about calendars) from application knowledge (about the particular on-line calendar).
scsl: a linguistic specification language for mt. nowadays, mt systems grow to such a size that a first specification step is necessary if we want to be able to master their developement and maintenance, for the software part as well for the linguistic part ("lingwares").advocating for a clean separation between linguistic tasks and programming tasks, we first introduce a specification/implementation/ validation framework for nlp then scsl, a language for the specification of analysis and generation modules.
interactive translation: a new approach. a new approach for interactive machine translation where the author interacts during the creation or the modification of the document is proposed. the explanation of an ambiguity or an error for the purpose of correction does not use any concepts of the underlying linguistic theory: it is a reformulation of the erroneous or ambiguous sentence. the interaction is limited to the analysis step of the translation process.this paper presents a new interactive disambiguation scheme based on the paraphrasing of a parser's multiple output. some examples of paraphrasing ambiguous sentences are presented.
nkrl, a knowledge representation language for narrative natural language processing. nkrl is a conceptual language which intends to provide a normalised, pragmatic description of the semantic contents (in short, the "meaning") of nl narrative documents. we introduce firstly the general architecture of nkrl, and we give some examples of its characteristics features. we supply, afterward, some sketchy information about the inference techniques and the nlp procedures associated with this language.
fast generation of abstracts from general domain text corpora by extracting relevant sentences. this paper describes a system for generating text abstracts which relies on a general, purely statistical principle, i.e., on the notion of "relevance", as it is defined in terms of the combination of feild weights of words in a sentence. the system generates abstracts from newspaper articles by selecting the "most relevant" sentences and combining them in text order. since neither domain knowledge nor text-sort-specific heuristics are involved, this system provides maximal generality and flexibility. also, it is fast and can be efficiently implemented for both on-line and off-line purposes. an experiment shows that recall and precision for the extracted sentences (taking the sentences extracted by human subjects as a baseline) is within the same range as recall/precision when the human subjects are compared amongst each other: this means in fact that the performance of the system is indistinguishable from the performance of a human abstractor. finally, the system yields significantly better results than a default "lead" algorithm does which chooses just some initial sentences from the text.
diasumm: flexible summarization of spontaneous dialogues in unrestricted domains. in this paper, we present a summarization system for spontaneous dialogues which consists of a novel multi-stage architecture. it is specifically aimed at addressing issues related to the nature of the texts being spoken vs. written and being dialogical vs. monological. the system is embedded in a graphical user interface and was developed and tested on transcripts of recorded telephone conversations in english and spanish (callhome).
closed yesterday and closed minds: asking the right questions of the corpus to distinguish thematic from sentential relations. collocation-based tagging and bracketing programs have attained promising results. yet, they have not arrived at the stage where they could be used as pre-processors for full-fledged parsing. accuracy, is still not high enough.to improve accuracy, it is necessary to investigate the points where statistical data is being misinterpreted, leading to incorrect results.in this paper we investigate inaccuracy which is injected when a pre-pocessor relies solely on collocations and blurs the distinction between two separate relations: thematic relations and sentential relations.thematic relations are word paris, not necessarily adjacent, (e.g., adjourn a meeting) that encode information at the concept level. sentential relations, on the other hand, concern adjacent word pairs that form a noun group. e.g., preferred stock is a noun group that must be identified as such at the syntactic level.blurring the difference between these two phenomena contributes to errors in tagging of pairs such as expressed concerns, a verb-noun construct, as opposed to preferred stocks, an adjective-noun construct. although both relations are manifested in the corpus as high mutual-information collocations, they possess different properties and they need to be separated.in our method, we distinguish between these two cases by asking additional questions of the corpus. by definition, thematic relations take on further variations in the corpus. expressed concerns (a thematic relation) takes concerns expressed, expressing concerns, express his concerns etc. on the other hand, preferred stock (a sentential relation) does not take any such syntactic variations.we show how this method impacts preprocessing and parsing, and we provide empirical results based on the analysis of an 80-million word corpus.
an empirically based approach towards a system of semantic features. a major problem in machine translation is the semantic description of lexical units which should be based on a semantic system that is both coherent and operationalized to the greatest possible degree. this is to guarantee consistency between lexical units coded by lexicographers. this article introduces a generating device for achieving wellformed semantic feature expressions.
default reasoning in natural language processing. in natural language, as in other computational task domains it is important to operate by default assumptions. first, many constraints required for constraint propagation are initially unspecified. second, in highly ambiguous tasks such as text analysis, ambiguity can be reduced by considering more plausible scenarios first. default reasoning is problematic for first-order logic when allowing non-monotonic inferences. whereas in monotonic logic facts can only be asserted, in non-monotonic logic a system must be maintained consistent even as previously assumed defaults are being retracted.non-monotonicty is pervasive in natural language due to the serial nature of utterances. when reading text left-to-right, it happens that default assumptions made early in the sentence must be withdrawn as reading proceeds. truth maintenance, which accounts for non-monotonic inferences, can resolve this issue and address important linguistic phenomena. in this paper we describe how in nmg (non-monotonic grammar), by monitoring a logic parser, a truth maintenance system can significantly, enhance the parser's capabilities.
universal quantification in machine translation. this approach has been developed in the context of the eurotra machine translation (mt) project and thus has been designed with respect to a syntax based stratificational translation process. we assume that in a semantic representation determiners are deleted and that their semantic function which is represented by semantic features is percolated into the mothernode. the semantic functions of determiners are explicated. the interaction between grammatical and lexical quantification is outlined. ensemble theory is applied to the "count"/"mass" noun distinction. transfer of quantification between german, english, and french is illustrated with respect to the "count"/"mass" distinction. the article closes with an outlook on the relevance of generalized quantifiers for machine translation.
cbc macs for arbitrary-length messages: the three-key constructions. we suggest some simple variants of the cbc mac that enable the efficient authentication of arbitrary-length messages. our constructions use three keys, k1, k2, k3, to avoid unnecessary padding and mac any message m &#x2208; {0,1}* using max{1, &#x2308; |m|/n&#x2309;} applications of the underlying n-bit block cipher. our favorite construction, xcbc, works like this: if |m| is a positive multiple of n then xor the n-bit key k2 with the last block of m and compute the cbc mac keyed with k1; otherwise, extend m&#x2019;s length to the next multiple of n by appending minimal 10&#x2113; padding (&#x2113; &#x2265; 0), xor the n-bit key k3 with the last block of the padded message, and compute the cbc mac keyed with k1. we prove the security of this and other constructions, giving concrete bounds on an adversary&#x2019;s inability to forge in terms of his inability to distinguish the block cipher from a random permutation. our analysis exploits new ideas which simplify proofs compared with prior work.
private computation - k-connected versus 1-connected networks. we study the role of connectivity of communication networks in private computations under information theoretical settings in the honest-but-curious model. we show that some functions can be 1-privately computed even if the underlying network is 1-connected but not 2-connected. then we give a complete characterisation of non-degenerate functions that can be 1-privately computed on non-2-connected networks. furthermore, we present a technique for simulating 1-private protocols that work on arbitrary (complete) networks on k-connected networks. for this simulation, at most $(1 - k/(n - 1)) \cdot l$ additional random bits are needed, where l is the number of bits exchanged in the original protocol and n is the number of players. finally, we give matching lower and upper bounds for the number of random bits needed to compute the parity function on k-connected networks 1-privately, namely $\lceil (n - 2)/(k - 1) \rceil - 1$ random bits for networks consisting of n players.
a calculus for access control in distributed systems. we study some of the concepts, protocols, and algorithms for access control in distributed systems, from a logical perspective. we account for how a principal may come to believe that another principal is making a request, either on his own or on someone else's behalf. we also provide a logical language for accesss control lists and theories for deciding whether requests should be granted.
searchable encryption revisited: consistency properties, relation to anonymous ibe, and extensions. we identify and fill some gaps with regard to consistency (the extent to which false positives are produced) for public-key encryption with keyword search (peks). we define computational and statistical relaxations of the existing notion of perfect consistency, show that the scheme of boneh et&#x00a0;al. (advances in cryptology&#x2014;eurocrypt 2004, ed. by c.&#x00a0;cachin, j.&#x00a0;camenisch, pp.&#x00a0;506&#x2013;522, 2004) is computationally consistent, and provide a new scheme that is statistically consistent. we also provide a transform of an anonymous identity-based encryption (ibe) scheme to a secure peks scheme that, unlike the previous one, guarantees consistency. finally, we suggest three extensions of the basic notions considered here, namely anonymous hierarchical identity-based encryption, public-key encryption with temporary keyword search, and identity-based encryption with keyword search.
how to sign given any trapdoor function. we present a digital signature scheme which combines high security with the property of being based on a very general assumption: the existence of trapdoor permutations. previous signature schemes with comparable levels of security were based on assumptions of the computational hardness of particular algebraic problems such as factoring. our contribution is to free this important cryptographic primitive from the fortunes of any specific algebraic problem by establishing a truly general signature scheme.
derandomization in cryptography. we give two applications of nisan-wigderson-type (nw-type) (&ldquo;noncryptographic&rdquo;) pseudorandom generators in cryptography. specifically, assuming the existence of an appropriate nw-type generator, we construct the following two protocols: (1) a one-message witness-indistinguishable proof system for every language in np, based on any trapdoor permutation. this proof system does not assume a shared random string or any setup assumption, so it is actually an &ldquo;np proof system.&rdquo; (2) a noninteractive bit-commitment scheme based on any one-way function. the specific nw-type generator we need is a hitting set generator fooling nondeterministic circuits. it is known how to construct such a generator if $e = dtime(2^{o(n)})$ has a function of nondeterministic circuit complexity $2^{\omega(n)}$. our witness-indistinguishable proofs are obtained by using the nw-type generator to derandomize the zaps of dwork and naor [proceedings of the 41st annual acm symposium on foundations of computer science, 2000, pp. 283-293]. to our knowledge, this is the first construction of an np proof system achieving a secrecy property. our commitment scheme is obtained by derandomizing the interactive commitment scheme of naor [j. cryptology, 4 (1991), pp. 151-158]. previous constructions of noninteractive commitment schemes were known only under incomparable assumptions.
instant ciphertext-only cryptanalysis of gsm encrypted communication. in this paper we present a very practical ciphertext-only cryptanalysis of gsm (global system for mobile communications) encrypted communication, and various active attacks on the gsm protocols. these attacks can even break into gsm networks that use &#x201c;unbreakable&#x201d; ciphers. we first describe a ciphertext-only attack on a5/2 that requires a few dozen milliseconds of encrypted off-the-air cellular conversation and finds the correct key in less than a second on a personal computer. we extend this attack to a (more complex) ciphertext-only attack on a5/1. we then describe new (active) attacks on the protocols of networks that use a5/1, a5/3, or even gprs (general packet radio service). these attacks exploit flaws in the gsm protocols, and they work whenever the mobile phone supports a weak cipher such as a5/2. we emphasize that these attacks are on the protocols, and are thus applicable whenever the cellular phone supports a weak cipher, for example, they are also applicable for attacking a5/3 networks using the cryptanalysis of a5/1. unlike previous attacks on gsm that require unrealistic information, like long known-plaintext periods, our attacks are very practical and do not require any knowledge of the content of the conversation. furthermore, we describe how to fortify the attacks to withstand reception errors. as a result, our attacks allow attackers to tap conversations and decrypt them either in real-time, or at any later time. we present several attack scenarios such as call hijacking, altering of data messages and call theft.
multiparty computation with faulty majority. the problem of performing a multiparty computation when more than half of the processors are cooperating byzantine faults is addressed. it is shown how to compute any boolean function of n inputs distributively, preserving the privacy of inputs held by nonfaulty processors and ensuring that faulty processors obtain the function value if and only if the nonfaulty processors do. if the nonfaulty processors do not obtain the correct function value, they detect cheating with high probability. the solution is based on a new type of verifiable secret sharing in which the secret is revealed not all at once but in small increments. this process ensures that all processors discover the secret at roughly the same time. the solution assumes the existence of an oblivious transfer protocol and uses broadcast channels. the processors are not required to have equal computing power.
identity-based encryption from the weil pairing. we propose a fully functional identity-based encryption (ibe) scheme. the scheme has chosen ciphertext security in the random oracle model assuming a variant of the computational diffie--hellman problem. our system is based on bilinear maps between groups. the weil pairing on elliptic curves is an example of such a map. we give precise definitions for secure ibe schemes and give several applications for such systems.
primality proving via one round in ecpp and one iteration in aks. in august 2002, agrawal, kayal and saxena announced the first deterministic and polynomial-time primality-testing algorithm. for an input n, the agarwal-kayal-saxena (aks) algorithm runs in time $\tilde{o}(\log^{7.5} n)$ (heuristic time $\tilde{o}(\log^6 n)$). verification takes roughly the same amount of time. on the other hand, the elliptic curve primality proving algorithm (ecpp) runs in random heuristic time $\tilde{o}(\log^{6} n)$ (some variant has heuristic time complexity $\tilde{o}(\log^4 n)$) and generates certificates which can be easily verified. however, it is hard to analyze the provable time complexity of ecpp even for a small portion of primes. more recently, berrizbeitia gave a variant of the aks algorithm, in which some primes (of density $o({ 1 / {\log}^2\,n })$) cost much less time to prove than a general prime does. building on these celebrated results, this paper explores the possibility of designing a randomized primality-proving algorithm based on the aks algorithm. we first generalize berrizbeitia's algorithm to one which has higher density ($\omega( {1/{\log}\log n })$) of primes whose primality can be proved in time complexity $\tilde{o}(\log^{4} n)$. for a general prime, one round of ecpp is deployed to reduce its primality proof to the proof of a random easily proved prime, thus we achieve heuristic time complexity $\tilde{o}(\log^{4} n)$ for all primes.
on the bounded sum-of-digits discrete logarithm problem in finite fields. in this paper, we study the bounded sum-of-digits discrete logarithm problem in finite fields. our results are concerned primarily with fields fqn, where n|q - 1. the fields are called kummer extensions of fq. it is known that we can efficiently construct an element g with order exponential in n. let $s_q(\bullet)$ be the function from integers to the sum of digits in their q-ary expansions. we first present an algorithm that, given ge (0 $\leq$ e qn), finds e in random polynomial time, provided that sq (e) n. we then show that the problem is solvable in random polynomial time for most of the exponent e with sq (e) n by exploring an interesting connection between the discrete logarithm problem and the problem of list decoding of reed--solomon codes and applying the guruswami--sudan algorithm. as far as we are aware, our algorithm is the first one which can solve discrete logarithms of $2^{\log^{1-\epsilon}{q^n}}$ many instances in polynomial time for infinite many constant characteristic fields fqn. furthermore, since every finite field has an extension of reasonable degree, which is a kummer extension, our result reveals an unexpected property of the discrete logarithm problem, namely, the bounded sum-of-digits discrete logarithm problem in any given finite field becomes polynomial-time solvable in certain low degree extensions. as a side result, we obtain a sharper lower bound on the number of congruent polynomials generated by linear factors than the one based on the stothers--mason abc-theorem. we also prove that, in the field fqq-1, the bounded sum-of-digits discrete logarithm with respect to g can be computed in random time o(f(w)log4 (qq-1)), where f is a subexponential function and w is the bound on the q-ary sum-of-digits of the exponent; hence the problem is fixed parameter tractable. these results are shown to be generalized to artin--schreier extension fpp, where p is a prime.
lower and upper bounds on obtaining history independence. history independent data structures, presented by micciancio, are data structures that possess a strong security property: even if an intruder manages to get a copy of the data structure, the memory layout of the structure yields no additional information on the history of operations applied on the structure beyond the information obtainable from the content itself. naor and teague proposed a stronger notion of history independence in which the intruder may break into the system several times without being noticed and still obtain no additional information from reading the memory layout of the data structure. an open question posed by naor and teague is whether these two notions are equally hard to obtain. in this paper we provide a separation between the two requirements for comparison-based algorithms. we show very strong lower bounds for obtaining the stronger notion of history independence for a large class of data structures, including, for example, the heap and the queue abstract data structures. we also provide complementary upper bounds showing that the heap abstract data structure may be made weakly history independent in the comparison based model without incurring any additional (asymptotic) cost on any of its operations. (a similar result is easy for the queue.) thus, we obtain the first separation between the two notions of history independence. the gap we obtain is exponential: some operations may be executed in logarithmic time (or even in constant time) with the weaker definition, but require linear time with the stronger definition.
pricing via processing or combatting junk mail. we present a computational technique for combatting junk mail, in particular, and controlling access to a shared resource, in general. the main idea is to require a user to compute a moderately hard, but not intractable, function in order to gain access to the resource, thus preventing frivolous use. to this end we suggest several pricing functions, based on, respectively, extracting square roots modulo a prime, the fiat-shamir signature scheme, and the ong-schnorr-shamir (cracked) signature scheme.
an efficient existentially unforgeable signature scheme and its applications. a signature scheme is existentially unforgeable if, given any polynomial (in the security parameter) number of pairs (m>sub<1>/sub<, s(m>sub<1>/sub<)), (m>sub<2>/sub<, s(m>sub<2>/sub<)), ... (m>sub<k>/sub<, s(m>sub<k>/sub<)) where s(m) denotes the signature on the message m, it is computationally infeasible to generate a pair (m>sub<k+1>/sub<, s(m>sub<k+1>/sub<)) for any message m>sub<k+1>/sub< i {m>sub<1>/sub<, ... m>sub<k>/sub< }. we present an existentially unforgeable signature scheme that requires at most 6 times the amount of time needed to generate a signature using rsa (which is not existentially unforgeable), and point out applications where its use is desirable.
efficient non-malleable commitment schemes. non-malleability protects against man-in-the middle attacks on cryptographic protocols. non-malleable commitment schemes, for example, assure that a commitment of a message does not help to produce a commitment of a related message. here we present efficient constructions of such commitment schemes in the common reference string model, based on standard assumptions such as rsa, factoring or discrete logarithm. our protocols require only three rounds and a few modular exponentiations, and provide statistical or even perfect secrecy of committed values. we also discuss differences between the notion of non-malleable commitment schemes used in previous works by dolev, dwork and naor and by di&#x00a0;crescenzo, ishai and ostrovsky. the former definition requires that it is infeasible to find a commitment such that there exists an encapsulated message which is related to another committed value (non-malleability with respect to commitment). the second approach allows the existence of such messages, but then it is hard to find them and to output them in the opening phase (non-malleability with respect to opening). we note that our solutions are of the second type.
rsa-oaep is secure under the rsa assumption. recently victor shoup noted that there is a gap in the widely believed security result of oaep against adaptive chosen-ciphertext attacks. moreover, he showed that, presumably, oaep cannot be proven secure from the one-wayness of the underlying trapdoor permutation. this paper establishes another result on the security of oaep. it proves that oaep offers semantic security against adaptive chosen-ciphertext attacks, in the random oracle model, under the partial-domain one-wayness of the underlying permutation. therefore, this uses a formally stronger assumption. nevertheless, since partial-domain one-wayness of the rsa function is equivalent to its (full-domain) onewayness, it follows that the security of rsa-oaep can actually be proven under the sole rsa assumption, although the reduction is not tight.
on the security of multi-party ping-pong protocols. we define a p-party ping-pong protocol and its security problem, along the lines of dolev and yao's definition for twoparty ping-pong protocol. in the case of two parties, it was assumed, with no loss of generality, that there exists a single saboteur in the net and the protocol was defined to be secure iff it was secure against the active interventions of one saboteur. we show that for more than 2 parties this assumption can no longer be made and that for p parties 3(p-2) + 1 is a lower bound on the number of saboteurs which should be considered for the security problem. on the other hand we establish a 3(p-2) + 2 upper bound on the number of saboteurs which should be considered. we conclude that for a fixed p, p-party ping-pong protocols can be tested for security in 0(n3) time and 0(n2) space, when n is the length of the protocol. we show that if p, the number of participants in the protocol, is part of the input then the security problem becomes np-hard. relaxing the definition of a ping-pong protocol so that operators can operate on half words (thus introducing commutativity of the operators) causes the security problem to become undecidable.
on the power of cascade ciphers. the unicity distance of a cascade of random ciphers, with respect to known plaintext attack, is shown to be the sum of the key lengths. a time-space trade-off for the exhaustive cracking of a cascade of ciphers is shown. the structure of the set of permutations realized by a cascade is studied; it is shown that only l.2k exhaustive experiments are necessary to determine the behavior of a cascade of l stages, each having k key bits. it is concluded that the cascade of random ciphers is not a random cipher. yet, it is shown that, with high probability, the number of permutations realizable by a cascade of l random ciphers, each having k key bits, is 2lk. next, it is shown that two stages are not worse than one, by a simple reduction of the cracking problem of any of the stages to the cracking problem of the cascade. finally, it is shown that proving a nonpolynomial lower bound on the cracking problem of long cascades is a hard task, since such a bound implies that p &nap; np.
public-key cryptosystems from lattice reduction problems. we present a new proposal for a trapdoor one-way function, from which we derive public-key encryption and digital signatures. the security of the new construction is based on the conjectured computational difficulty of lattice-reduction problems, providing a possible alternative to existing public-key encryption algorithms and digital signatures such as rsa and dss.
on the existence of pseudorandom generators. pseudorandom generators are known to exist, assuming the existence of functions that cannot be efficiently inverted on the distributions induced by applying the function iteratively polynomially many times. this sufficient condition is also necessary, but it is difficult to check whether particular functions, assumed to be one-way, are also one-way on their iterates. this raises the fundamental question of whether the mere existence of one-way functions suffices for the construction of pseudorandom generators. progress toward resolving this question is presented. regular functions in which every image of a k-bit string has the same number of preimages of length k are considered. it is shown that if a regular function is one-way, then pseudorandom generators do exist. in particular, assuming the intractability of general factoring, it can be proved that the pseudorandom generators do exist. another application is the construction of a pseudorandom generator based on the assumed intractability of decoding random linear codes.
session-key generation using human passwords only. we present session-key generation protocols in a model where the legitimate parties share only a human-memorizable password. the security guarantee holds with respect to probabilistic polynomial-time adversaries that control the communication channel (between the parties), and may omit, insert and modify messages at their choice. loosely speaking, the effect of such an adversary that controls m instances of the protocol is comparable to an on-line attack in which an adversary is only allowed to makes o(m) queries of the form ``is w the password of party&#x00a0;a''''. we stress that the result holds also in case the passwords are selected at random from a small dictionary so that it is feasible (for the adversary) to scan the entire directory.
can statistical zero knowledge be made non-interactive? or on the relationship of szk and niszk. we further extend the study, recently initiated by de-santis et. al (icalp98) of non-interactive statistical zero-knowledge proofs. our main focus is to compare the class niszk of problems possessing such non-interactive proofs to the class szk of problems possessing interactive statistical zero-knowledge proofs. along these lines, we first show that if statistical zero-knowledge is non-trivial then so is non-interactive statistical zero-knowledge, where by non-trivial we mean that the class includes problems which are not solvable in probabilistic polynomial-time. (the hypothesis holds under various assumptions, such as the intractability of the discrete logarithm problem.) furthermore, we show that if niszk is closed under complementation, then in fact szk=niszk, i.e. all statistical zero-knowledge proofs can be made non-interactive. the main tools in our analysis are two promise problems that are natural restrictions of promise problems known to be complete for szk. we show that these restricted problems are in fact complete for niszk, and using this relationship we derive our results comparing the two classes. the two problems refer to the statistical difference, and difference in entropy, respectively, of a given distribution from the uniform one. we also consider a weak form of niszk, in which only requires that for every inverse polynomial 1/p(n), there exists a simulator which achieves simulator deviation 1/p(n), and show that this weak form of niszk actually equals niszk.
public protection of software. one of the overwhelming problems that software producers must contend with is the unauthorized use and distribution of their products. copyright laws concerning software are rarely enforced, thereby causing major losses to the software companies. technical means of protecting software from illegal duplication are required, but the available means are imperfect. we present protocols that enable software protection, without causing substantial overhead in distribution and maintenance. the protocols may be implemented by a conventional cryptosystem, such as the des, or by a public key cryptosystem, such as the rsa. both implementations are proved to satisfy required security criteria.
limits on the provable consequences of one-way permutations. we present strong evidence that the implication, &ldquo;if one-way permutations exist, then secure secret key agreement is possible&rdquo;, is not provable by standard techniques. since both sides of this implication are widely believed true in real life, to show that the implication is false requires a new model. we consider a world where all parties have access to a black box for a randomly selected permutation. being totally random, this permutation will be strongly one-way in a provable, information-theoretic way. we show that, if p = n p, no protocol for secret key agreement is secure in such a setting. thus, to prove that a secret key agreement protocol which uses a one-way permutation as a black box is secure is as hard as proving p &ne; n p. we also obtain, as a corollary, that there is an oracle relative to which the implication is false, i.e., there is a one-way permutation, yet secret-exchange is impossible. thus, no technique which relativizes can prove that secret exchange can be based on any one-way permutation. our results present a general framework for proving statements of the form, &ldquo;cryptographic application x is not likely possible based solely on complexity assumption y.&rdquo;
identity escrow. we introduce the notion of {\em escrowed identity}, an application of key-escrow ideas to the problem of identification. in escrowed identity, one party $a$ does {\em not} give his identity to another party $b$, but rather gives him information that would allow an authorized third party $e$ to determine $a$''s identity. however, $b$ receives a guarantee that $e$ can indeed determine $a$''s identity. we give protocols for escrowed identity based on the el-gamal (signature and encryption) schemes and on the rsa function. a useful feature of our protocol is that after setting up $a$ to use the system, $e$ is only involved when it is actually needed to determine $a$''s identity.
scalable protocols for authenticated group key exchange. we consider the problem of authenticated group key exchange among n parties communicating over an insecure public network. a number of solutions to this problem have been proposed; however, all prior provably secure solutions do not scale well and, in particular, require o(n) rounds. our main contribution is the first scalable protocol for this problem along with a rigorous proof of security in the standard model under the ddh assumption; our protocol uses a constant number of rounds and requires only o(1) "full" modular exponentiations per user. toward this goal (and adapting work of bellare, canetti, and krawczyk), we first present an efficient compiler that transforms any group key-exchange protocol secure against a passive eavesdropper to an authenticated protocol which is secure against an active adversary who controls all communication in the network. this compiler adds only one round and o(1) communication (per user) to the original scheme. we then prove secure&#x2014;against a passive adversary&#x2014;a variant of the two-round group key-exchange protocol of burmester and desmedt. applying our compiler to this protocol results in a provably secure three-round protocol for authenticated group key exchange which also achieves forward secrecy.
a randomnesss-rounds tradeoff in private computation. we study the role of randomness in multiparty private computations. in particular, we give several results that prove the existence of a randomness-rounds tradeoff in multiparty private computation of $\fxor$. we show that with a single random bit, $\theta(n)$ rounds are necessary and sufficient to privately compute $\fxor$ of n input bits. with $d\ge 2$ random bits, $\omega(\log n/ d)$ rounds are necessary, and $o(\log n/ \log d)$ are sufficient. more generally, we show that the private computation of a boolean function f, using $d\ge 2 $ random bits, requires $\omega(\log s(f)/ d)$ rounds, where s(f) is the sensitivity of f. using a single random bit, $\omega(s(f))$ rounds are necessary.
a randomized protocol for signing contracts. randomized protocols for signing contracts, certified mail, and flipping a coin are presented. the protocols use a 1-out-of-2 oblivious transfer subprotocol which is axiomatically defined.the 1-out-of-2 oblivious transfer allows one party to transfer exactly one secret, out of two recognizable secrets, to his counterpart. the first (second) secret is received with probability one half, while the sender is ignorant of which secret has been received.an implementation of the 1-out-of-2 oblivious transfer, using any public key cryptosystem, is presented.
non-interactive timestamping in the bounded storage model. a timestamping scheme is non-interactive if a stamper can stamp a document without communicating with any other player. the only communication done is at validation time. non-interactive timestamping has many advantages, such as information theoretic privacy and enhanced robustness. non-interactive timestamping, however, is not possible against polynomial-time adversaries that have unbounded storage at their disposal. as a result, no non-interactive timestamping schemes were constructed up to date. in this paper we show that non-interactive timestamping is possible in the bounded-storage model, i.e., if the adversary has bounded storage, and a long random string is broadcast to all players. to the best of our knowledge, this is the first example of a cryptographic task that is possible in the bounded-storage model but is impossible in the &#x201c;standard cryptographic setting,&#x201d; even when assuming &#x201c;standard&#x201d; cryptographic assumptions. we give an explicit construction that is secure against all bounded storage adversaries and a significantly more efficient construction secure against all bounded storage adversaries that run in polynomial time.
two-party generation of dsa signatures. we describe a means of sharing the dsa signature function, so that two parties can efficiently generate a dsa signature with respect to a given public key but neither can alone. we focus on a certain instantiation that allows a proof of security for concurrent execution in the random oracle model and that is very practical. we also briefly outline a variation that requires more rounds of communication but that allows a proof of security for sequential execution without random oracles.
threshold password-authenticated key exchange. in most password-authenticated key exchange systems there is a single server storing password verification data. to provide some resilience against server compromise, this data typically takes the form of a one-way function of the password (and possibly a salt, or other public values) rather than the password itself. however, if the server is compromised, this password verification data can be used to perform an off-line dictionary attack on the user's password. in this paper we propose an efficient password-authenticated key exchange system involving a set of servers with known public keys, in which a certain threshold of servers must participate in the authentication of a user, and in which the compromise of any fewer than that threshold of servers does not allow an attacker to perform an off-line dictionary attack. we prove our system is secure in the random oracle model under the decision diffie-hellman assumption against an attacker that may eavesdrop on, insert, delete, or modify messages between the user and servers, and that compromises fewer than that threshold of servers.
digital signature scheme for computer communication networks. this paper introduces four new digital signature schemes for computer communication networks. these involve one or more arbitrators who validate and authenticate messages and signatures without having access to the actual contents of the messages.
private searching on streaming data. in this paper we consider the problem of private searching on streaming data, where we can efficiently implement searching for documents that satisfy a secret criteria (such as the presence or absence of a hidden combination of hidden keywords) under various cryptographic assumptions. our results can be viewed in a variety of ways: as a generalization of the notion of private information retrieval (to more general queries and to a streaming environment); as positive results on privacy-preserving datamining; and as a delegation of hidden program computation to other machines.
a polynomial time algorithm for breaking the basic merkle-hellman cryptosystem. the cryptographic security of the merkle-hellman cryptosystem has been a major open problem since 1976. in this paper we show that the basic variant of this cryptosystem, in which the elements of the public key are modular multiples of a superincreasing sequence, is breakable in polynomial time.
efficient and secure pseudo-random number generation. cryptographically secure pseudo-random number generators known so far suffer from the handicap of being inefficient; the most efficient ones can generate only one bit on each modular multiplication (n/sup 2/ steps). blum, blum and shub ask the open problem of outputting even two bits securely. we state a simple condition, the xor-condition, and show that any generator satisfying this condition can output logn bits on each multiplication. we also show that the logn least significant bits of rsa, rabin's scheme, and the x/sup 2/ mod n generator satisfy boolean predicates of these bits are secure. furthermore, we strengthen the security of the x/sup 2/ mod n generator, which being a trapdoor generator, has several applications, by proving it as hard as factoring.
secure hybrid encryption from weakened key encapsulation. we put forward a new paradigm for building hybrid encryption schemes from constrained chosen-ciphertext secure (ccca) key-encapsulation mechanisms (kems) plus authenticated symmetric encryption. constrained chosen-ciphertext security is a new security notion for kems that we propose. it has less demanding security requirements than standard ccca security (since it requires the adversary to have a certain plaintext-knowledge when making a decapsulation query) yet we can prove that it is ccca sufficient for secure hybrid encryption. our notion is not only useful to express the kurosawa-desmedt public-key encryption scheme and its generalizations to hash-proof systems in an abstract kem/dem security framework. it also has a very constructive appeal, which we demonstrate with a new encryption scheme whose security relies on a class of intractability assumptions that we show (in the generic group model) strictly weaker than the decision diffie-hellman (ddh) assumption. this appears to be the first practical public-key encryption scheme in the literature from an algebraic assumption strictly weaker than ddh.
information security economics - and beyond. the economics of information security has recently become a thriving and fast-moving discipline. as distributed systems are assembled from machines belonging to principals with divergent interests, incentives are becoming as important to dependability as technical design. the new field provides valuable insights not just into 'security' topics such as privacy, bugs, spam, and phishing, but into more general areas such as system dependability (the design of peer-to-peer systems and the optimal balance of effort by programmers and testers), and policy (particularly digital rights management). this research program has been starting to spill over into more general security questions (such as law-enforcement strategy), and into the interface between security and sociology. most recently it has started to interact with psychology, both through the psychology-and-economics tradition and in response to phishing. the promise of this research program is a novel framework for analyzing information security problems - one that is both principled and effective.
deterministic and efficiently searchable encryption. we present as-strong-as-possible definitions of privacy, and constructions achieving them, for public-key encryption schemes where the encryption algorithm is deterministic. we obtain as a consequence database encryption methods that permit fast (i.e. sub-linear, and in fact logarithmic, time) search while provably providing privacy that is as strong as possible subject to this fast search constraint. one of our constructs, called rsa-doaep, has the added feature of being length preserving, so that it is the first example of a public-key cipher. we generalize this to obtain a notion of efficiently-searchable encryption schemes which permit more flexible privacy to search-time trade-offs via a technique called bucketization. our results answer much-asked questions in the database community and provide foundations for work done there.
amplifying collision resistance: a complexity-theoretic treatment. we initiate a complexity-theoretic treatment of hardness amplification for collision-resistant hash functions, namely the transformation of weakly collision-resistant hash functions into strongly collision-resistant ones in the standard model of computation. we measure the level of collision resistance by the maximum probability, over the choice of the key, for which an efficient adversary can find a collision. the goal is to obtain constructions with short output, short keys, small loss in adversarial complexity tolerated, and a good trade-off between compression ratio and computational complexity. we provide an analysis of several simple constructions, and show that many of the parameters achieved by our constructions are almost optimal in some sense.
efficient constructions of composable commitments and zero-knowledge proofs. canetti et al. [7] recently proposed a new framework -- termed generalized universal composability (guc) -- for properly analyzing concurrent execution of cryptographic protocols in the presence of a global setup, and constructed the first known guc-secure implementations of commitment (gucc) and zero-knowledge (guc zk), which suffice to implement any two-party or multi-party functionality under several natural and relatively mild setup assumptions. unfortunately, the feasibility results of [7] used rather inefficient constructions.in this paper, we dramatically improve the efficiency of (adaptively-secure) gucc and guc zk assuming data erasures are allowed. namely, using the same minimal setup assumptions as those used by [7], we build a direct and efficient constant-round guc zk for r from any "dense" ¿-protocol [21] for r. as a corollary, we get a semi-efficient construction from any σ-protocol for r (without doing the cook-levin reduction), and a very efficient guc zk for proving knowledge of a discrete log representation. the first constant-rate (and constant-round) gucc scheme. additionally, we show how to properly model a random oracle in the guc framework without losing deniability, which is one of the attractive features of the guc framework. in particular, by adding the random oracle to the setup assumptions used by [7], we build the first two-round (which we show is optimal), deniable, straight-line extractable and simulatable zk proof for any np relation r.
founding cryptography on oblivious transfer - efficiently. we present a simple and efficient compiler for transforming secure multi-party computation (mpc) protocols that enjoy security only with an honest majority into mpc protocols that guarantee security with no honest majority, in the oblivious-transfer (ot) hybrid model. our technique works by combining a secure protocol in the honest majority setting with a protocol achieving only security against semi-honest parties in the setting of no honest majority.applying our compiler to variants of protocols from the literature, we get several applications for secure two-party computation and for mpc with no honest majority. these include: constant-rate two-party computation in the ot-hybrid model. we obtain a statistically uc-secure two-party protocol in the ot-hybrid model that can evaluate a general circuit c of size s and depth d with a total communication complexity of o(s) + poly(k, d, log s) and o(d) rounds. the above result generalizes to a constant number of parties. extending ots in the malicious model. we obtain a computationally efficient protocol for generating many string ots from few string ots with only a constant amortized communication overhead compared to the total length of the string ots. black-box constructions for constant-round mpc with no honest majority. we obtain general computationally uc-secure mpc protocols in the ot-hybrid model that use only a constant number of rounds, and only make a black-box access to a pseudorandom generator. this gives the first constant-round protocols for three or more parties that only make a black-box use of cryptographic primitives (and avoid expensive zero-knowledge proofs).
deterministic encryption: definitional equivalences and constructions without random oracles. we strengthen the foundations of deterministic public-key encryption via definitional equivalences and standard-model constructs based on general assumptions. specifically we consider seven notions of privacy for deterministic encryption, including six forms of semantic security and an indistinguishability notion, and show them all equivalent. we then present a deterministic scheme for the secure encryption of uniformly and independently distributed messages based solely on the existence of trapdoor one-way permutations. we show a generalization of the construction that allows secure deterministic encryption of independent high-entropy messages. finally we show relations between deterministic and standard (randomized) encryption.
security-amplifying combiners for collision-resistant hash functions. the classical combiner combh0, h1class (m) = h0(m)||h1(m) for hash functions h0, h1 provides collision-resistance as long as at least one of the two underlying hash functions is secure. this statement is complemented by the multi-collision attack of joux (crypto 2004) for iterated hash functions h0,h1 with n-bit outputs. he shows that one can break the classical combiner in n/2 ċ t0 + t1 steps if one can find collisions for h0 and h1 in time t0 and t1, respectively. here we address the question if there are security-amplifying combiners where the security of the building blocks increases the security of the combined hash function, thus beating the bound of joux. we discuss that one can indeed have such combiners and, somewhat surprisingly in light of results of nandi and stinson (eprint 2004) and of hoch and shamir (fse 2006), our solution is essentially as efficient as the classical combiner.
secure identification and qkd in the bounded-quantum-storage model. we consider the problem of secure identification: user u proves to server s that he knows an agreed (possibly low-entropy) password w, while giving away as little information on w as possible, namely the adversary can exclude at most one possible password for each execution of the scheme. we propose a solution in the bounded-quantum-storage model, where u and s may exchange qubits, and a dishonest party is assumed to have limited quantum memory. no other restriction is posed upon the adversary. an improved version of the proposed identification scheme is also secure against a man-in-the-middle attack, but requires u and s to additionally share a high-entropy key k. however, security is still guaranteed if one party loses k to the attacker but notices the loss. in both versions of the scheme, the honest participants need no quantum memory, and noise and imperfect quantum sources can be tolerated. the schemes compose sequentially, and w and k can securely be re-used. a small modification to the identification scheme results in a quantum-key-distribution (qkd) scheme, secure in the bounded-quantum-storage model, with the same re-usability properties of the keys, and without assuming authenticated channels. this is in sharp contrast to known qkd schemes (with unbounded adversary) without authenticated channels, where authentication keys must be updated, and unsuccessful executions can cause the parties to run out of keys.
practical cryptanalysis of sflash. in this paper, we present a practical attack on the signature scheme sflash proposed by patarin, goubin and courtois in 2001 following a design they had introduced in 1998. the attack only needs the public key and requires about one second to forge a signature for any message, after a one-time computation of several minutes. it can be applied to both sflashv2 which was accepted by nessie, as well as to sflashv3 which is a higher security version.
invertible universal hashing and the tet encryption mode. this work describes a mode of operation, tet, that turns a regular block cipher into a length-preserving enciphering scheme for messages of (almost) arbitrary length. when using an n-bit block cipher, the resulting scheme can handle input of any bit-length between n and 2n and associated data of arbitrary length. the mode tet is a concrete instantiation of the generic mode of operation that was proposed by naor and reingold, extended to handle tweaks and inputs of arbitrary bit length. the main technical tool is a construction of invertible "universal hashing" on wide blocks, which is as efficient to compute and invert as polynomial-evaluation hash.
improved analysis of kannan's shortest lattice vector algorithm. the security of lattice-based cryptosystems such as ntru, ggh and ajtai-dwork essentially relies upon the intractability of computing a shortest non-zero lattice vector and a closest lattice vector to a given target vector in high dimensions. the best algorithms for these tasks are due to kannan, and, though remarkably simple, their complexity estimates have not been improved since over twenty years. kannan's algorithm for solving the shortest vector problem (svp) is in particular crucial in schnorr's celebrated block reduction algorithm, on which rely the best known generic attacks against the lattice-based encryption schemes mentioned above. in this paper we improve the complexity upper-bounds of kannan's algorithms. the analysis provides new insight on the practical cost of solving svp, and helps progressing towards providing meaningful key-sizes.
distributed private data analysis: simultaneously solving how and what. we examine the combination of two directions in the field of privacy concerning computations over distributed private inputs --- secure function evaluation (sfe) and differential privacy. while in both the goal is to privately evaluate some function of the individual inputs, the privacy requirements are significantly different. the general feasibility results for sfe suggest a natural paradigm for implementing differentially private analyses distributively: first choose what to compute, i.e., a differentially private analysis; then decide how to compute it, i.e., construct an sfe protocol for this analysis. we initiate an examination whether there are advantages to a paradigm where both decisions are made simultaneously. in particular, we investigate under which accuracy requirements it is beneficial to adapt this paradigm for computing a collection of functions including binary sum, gap threshold, and approximate median queries. our results yield new separations between the local and global models of computations for private data analysis.
rerandomizable rcca encryption. we give the first perfectly rerandomizable, replayable-cca (rcca) secure encryption scheme, positively answering an open problem of canetti et al. (crypto 2003). our encryption scheme, which we call the double-strand cramer-shoup scheme, is a non-trivial extension of the popular cramer-shoup encryption. its security is based on the standard ddh assumption. to justify our definitions, we define a powerful "replayable message posting" functionality in the universally composable (uc) framework, and show that any encryption scheme that satisfies our definitions of rerandomizability and rcca security is a uc-secure implementation of this functionality. finally, we enhance the notion of rerandomizable rcca security by adding a receiver-anonymity (or key-privacy) requirement, and show that it results in a correspondingly enhanced uc functionality. we leave open the problem of constructing a scheme achieving this enhancement.
a tight high-order entropic quantum uncertainty relation with applications. we derive a new entropic quantum uncertainty relation involving min-entropy. the relation is tight and can be applied in various quantum-cryptographic settings. protocols for quantum 1-out-of-2 oblivious transfer and quantum bit commitment are presented and the uncertainty relation is used to prove the security of these protocols in the bounded-quantum-storage model according to new strong security definitions. as another application, we consider the realistic setting of quantum key distribution (qkd) against quantum-memory-bounded eavesdroppers. the uncertainty relation allows to prove the security of qkd protocols in this setting while tolerating considerably higher error rates compared to the standard model with unbounded adversaries. for instance, for the six-state protocol with one-way communication, a bit-flip error rate of up to 17% can be tolerated (compared to 13% in the standard model). our uncertainty relation also yields a lower bound on the min-entropy key uncertainty against known-plaintext attacks when quantum ciphers are composed. previously, the key uncertainty of these ciphers was only known with respect to shannon entropy.
on secure multi-party computation in black-box groups. we study the natural problem of secure n-party computation (in the passive, computationally unbounded attack model) of the n-product function fg(x1, . . . , xn) = x1 ċ x2 . . . xn in an arbitrary finite group (g, ċ), where the input of party pi is xi ∈ g for i = 1, . . . , n. for flexibility, we are interested in protocols for fg which require only black-box access to the group g (i.e. the only computations performed by players in the protocol are a group operation, a group inverse, or sampling a uniformly random group element). our results are as follows. first, on the negative side, we show that if (g, ċ) is non-abelian and n ≥ 4, then no ⌈n/2⌉-private protocol for computing fg exists. second, on the positive side, we initiate an approach for construction of black-box protocols for fg based on k-of-k threshold secret sharing schemes, which are efficiently implementable over any black-box group g. we reduce the problem of constructing such protocols to a combinatorial colouring problem in planar graphs. we then give two constructions for such graph colourings. our first colouring construction gives a protocol with optimal collusion resistance t < n/2, but has exponential communication complexity o(n(2t+1/t)2) group elements (this construction easily extends to general adversary structures). our second probabilistic colouring construction gives a protocol with (close to optimal) collusion resistance t < n/µ for a graph-related constant µ ≤ 2.948, and has efficient communication complexity o(nt2) group elements. furthermore, we believe that our results can be improved by further study of the associated combinatorial problems.
cryptography in the multi-string model. the common random string model introduced by blum, feldman and micali permits the construction of cryptographic protocols that are provably impossible to realize in the standard model. we can think of this model as a trusted party generating a random string and giving it to all parties in the protocol. however, the introduction of such a third party should set alarm bells going off: who is this trusted party? why should we trust that the string is random? even if the string is uniformly random, how do we know it does not leak private information to the trusted party? the very point of doing cryptography in the first place is to prevent us from trusting the wrong people with our secrets. in this paper, we propose the more realistic multi-string model. instead of having one trusted authority, we have several authorities that generate random strings. we do not trust any single authority; we only assume a majority of them generate the random string honestly. this security model is reasonable, yet at the same time it is very easy to implement. we could for instance imagine random strings being provided on the internet, and any set of parties that want to execute a protocol just need to agree on which authorities' strings they want to use. we demonstrate the use of the multi-string model in several fundamental cryptographic tasks. we define multi-string non-interactive zero-knowledge proofs and prove that they exist under general cryptographic assumptions. our multistring nizk proofs have very strong security properties such as simulation-extractability and extraction zero-knowledge, which makes it possible to compose them with arbitrary other protocols and to reuse the random strings. we also build efficient simulation-sound multi-string nizk proofs for circuit satisfiability based on groups with a bilinear map. the sizes of these proofs match the best constructions in the single common random string model. we suggest a universally composable commitment scheme in the multistring model. it has been proven that uc commitment does not exist in the plain model without setup assumptions. prior to this work, constructions were only known in the common reference string model and the registered public key model. one of the applications of the uc commitment scheme is a coin-flipping protocol in the multi-string model. armed with the coin-flipping protocol, we can securely realize any multi-party computation protocol.
universally-composable two-party computation in two rounds. round complexity is a central measure of efficiency, and characterizing the round complexity of various cryptographic tasks is of both theoretical and practical importance. we show here a universally-composable (uc) protocol (in the common reference string model) for two-party computation of any functionality, where both parties receive output, using only two rounds. (this assumes honest parties are allowed to transmit messages simultaneously in any given round; we obtain a three-round protocol when parties are required to alternate messages.) our results match the obvious lower bounds for the round complexity of secure two-party computation under any reasonable definition of security, regardless of what setup is used. thus, our results establish that secure two-party computation can be obtained under a commonly-used setup assumption with maximal security (i.e., security under general composition) in a minimal number of rounds. to give but one example of the power of our general result, we observe that as an almost immediate corollary we obtain a two-round uc blind signature scheme, matching a result by fischlin at crypto 2006 (though, in contrast to fischlin, we use specific number-theoretic assumptions).
cryptography with constant input locality. we study the following natural question: which cryptographic primitives (if any) can be realized by functions with constant input locality, namely functions in which every bit of the input influences only a constant number of bits of the output? this continues the study of cryptography in low complexity classes. it was recently shown by applebaum et al. (focs 2004) that, under standard cryptographic assumptions, most cryptographic primitives can be realized by functions with constant output locality, namely ones in which every bit of the output is influenced by a constant number of bits from the input. we (almost) characterize what cryptographic tasks can be performed with constant input locality. on the negative side, we show that primitives which require some form of non-malleability (such as digital signatures, message authentication, or non-malleable encryption) cannot be realized with constant input locality. on the positive side, assuming the intractability of certain problems from the domain of error correcting codes (namely, hardness of decoding a random binary linear code or the security of the mceliece cryptosystem), we obtain new constructions of one-way functions, pseudorandom generators, commitments, and semantically-secure public-key encryption schemes whose input locality is constant. moreover, these constructions also enjoy constant output locality and thus they give rise to cryptographic hardware that has constant-depth, constant fan-in and constant fan-out. as a byproduct, we obtain a pseudorandom generator whose output and input locality are both optimal (namely,&#x00a0;3).
public key encryption that allows pir queries. consider the following problem: alice wishes to maintain her email using a storage-provider bob (such as a yahoo! or hotmail email account). this storage-provider should provide for alice the ability to collect, retrieve, search and delete emails but, at the same time, should learn neither the content of messages sent from the senders to alice (with bob as an intermediary), nor the search criteria used by alice. a trivial solution is that messages will be sent to bob in encrypted form and alice, whenever she wants to search for some message, will ask bob to send her a copy of the entire database of encrypted emails. this however is highly inefficient. we will be interested in solutions that are communication-efficient and, at the same time, respect the privacy of alice. in this paper, we show how to create a public-key encryption scheme for alice that allows pir searching over encrypted documents. our solution is the first to reveal no partial information regarding the user's search (including the access pattern) in the public-key setting and with nontrivially small communication complexity. this provides a theoretical solution to a problem posed by boneh, dicrescenzo, ostrovsky and persiano on "public-key encryption with keyword search." the main technique of our solution also allows for single-database pir writing with sublinear communication complexity, which we consider of independent interest.
simulatable vrfs with applications to multi-theorem nizk. this paper introduces simulatable verifiable random functions (svrf). vrfs are similar to pseudorandom functions, except that they are also verifiable: corresponding to each seed sk, there is a public key pk, and for y = fpk(x), it is possible to prove that y is indeed the value of the function seeded by sk. a simulatable vrf is a vrf for which this proof can be simulated, so a simulator can pretend that the value of fpk(x) is any y. our contributions are as follows. we introduce the notion of svrf. we give two constructions: one from general assumptions (based on nizk), but inefficient, just as a proof of concept; the other construction is practical and based on a special assumption about composite-order groups with bilinear maps. we then use an svrf to get a direct transformation from a single-theorem non-interactive zero-knowledge proof system for a language l to a multi-theorem non-interactive proof system for the same language l.
scalable and unconditionally secure multiparty computation. we present a multiparty computation protocol that is unconditionally secure against adaptive and active adversaries, with communication complexity o(cn)k + o(dn2)k + poly(nκ), where c is the number of gates in the circuit, n is the number of parties, k is the bit-length of the elements of the field over which the computation is carried out, d is the multiplicative depth of the circuit, and κ is the security parameter. the corruption threshold is t < n/3. for passive security the corruption threshold is t < n/2 and the communication complexity is o(nc)k. these are the first unconditionally secure protocols where the part of the communication complexity that depends on the circuit size is linear in n. we also present a protocol with threshold t < n/2 and complexity o(cn)k+poly(nκ) based on a complexity assumption which, however, only has to hold during the execution of the protocol - that is, the protocol has so called everlasting security.
collusion-free protocols in the mediated model. prior approaches [14, 15] to building collusion-free protocols require exotic channels. by taking a conceptually new approach, we are able to use a more digitally-friendly communication channel to construct protocols that achieve a stronger collusion-free property.we consider a communication channel which can filter and rerandomize message traffic. we then provide a new security definition that captures collusion-freeness in this new setting; our new setting even allows for the mediator to be corrupted in which case the security gracefully fails to providing standard privacy and correctness. this stronger notion makes the property useful in more settings.to illustrate feasibility, we construct a commitment scheme and a zero-knowledge proof of knowledge that meet our definition in its two variations.
one-time programs. in this work, we introduce one-time programs, a new computational paradigm geared towards security applications. a one-time program can be executed on a single input, whose value can be specified at run time. other than the result of the computation on this input, nothing else about the program is leaked. hence, a one-time program is like a black box function that may be evaluated once and then "self destructs." this also extends to k-time programs, which are like black box functions that can be evaluated k times and then self destruct.one-time programs serve many of the same purposes of program obfuscation, the obvious one being software protection, but also including applications such as temporary transfer of cryptographic ability. moreover, the applications of one-time programs go well beyond those of obfuscation, since one-time programs can only be executed once (or more generally, a limited number of times) while obfuscated programs have no such bounds. for example, one-time programs lead naturally to electronic cash or token schemes: coins are generated by a program that can only be run once, and thus cannot be double spent.most significantly, the new paradigm of one-time computing opens new avenues for conceptual research. in this work we explore one such avenue, presenting the new concept of "one-time proofs," proofs that can only be verified once and then become useless and unconvincing.all these tasks are clearly impossible using software alone, as any piece of software can be copied and run again, enabling the user to execute the program on more than one input. all our solutions employ a secure memory device, inspired by the cryptographic notion of interactive oblivious transfer protocols, that stores two secret keys (k 0,k 1). the device takes as input a single bit b ¿ {0,1}, outputs k b , and then self destructs. using such devices, we demonstrate that for every input length, any standard program (turing machine) can be efficiently compiled into a functionally equivalent one-time program. we also show how this memory device can be used to construct one-time proofs. specifically, we show how to use this device to efficiently convert a classical witness for any np statement, into "one-time proof" for that statement.
beyond uniformity: better security/efficiency tradeoffs for compression functions. suppose we are given a perfect n + c-to-n bit compression function f and we want to construct a larger m + s-to-s bit compression function h instead. what level of security, in particular collision resistance, can we expect from h if it makes r calls to f? we conjecture that typically collisions can be found in 2(nr + cr ¿ m)/(r + 1) queries. this bound is also relevant for building a m + s-to-s bit compression function based on a blockcipher with k-bit keys and n-bit blocks: simply set c = k, or c = 0 in case of fixed keys.we also exhibit a number of (conceptual) compression functions whose collision resistance is close to this bound. in particular, we consider the following four scenarios: 1 a 2n-to-n bit compression function making two calls to an n-to-n bit primitive, providing collision resistance up to 2 n/3/n queries. this beats a recent bound by rogaway and steinberger that 2 n/4 queries to the underlying random n-to-n bit function suffice to find collisions in any rate-1/2 compression function. in particular, this shows that rogaway and steinberger's recent bound of 2(nr ¿ m ¿ s/2)/r) queries (for c = 0) crucially relies upon a uniformity assumption; a blanket generalization to arbitrary compression functions would be incorrect. 1 a 3n-to-2n bit compression function making a single call to a 3n-to-n bit primitive, providing collision resistance up to 2 n queries. 1 a 3n-to-2n bit compression function making two calls to a 2n-to-n bit primitive, providing collision resistance up to 2 n queries. 1 a single call compression function with parameters satisfying m ≤ n + c, n ≤ s, c ≤ m. this result provides a tradeoff between how many bits you can compress for what level of security given a single call to an n + c-to-n bit random function.
a framework for efficient and composable oblivious transfer. we propose a simple and general framework for constructing oblivious transfer (ot) protocols that are efficient, universally composable, and generally realizable under any one of a variety of standard number-theoretic assumptions, including the decisional diffie-hellman assumption, the quadratic residuosity and decisional composite residuosity assumptions, and worst-case lattice assumptions.our ot protocols are round-optimal (one message each way), quite efficient in computation and communication, and can use a single common string for an unbounded number of executions between the same sender and receiver. furthermore, the protocols can provide statistical security to either the sender or the receiver, simply by changing the distribution of the common string. for certain instantiations of the protocol, even a common uniformly random string suffices.our key technical contribution is a simple abstraction that we call a dual-mode cryptosystem. we implement dual-mode cryptosystems by taking a unified view of several cryptosystems that have what we call "messy" public keys, whose defining property is that a ciphertext encrypted under such a key carries no information (statistically) about the encrypted message.as a contribution of independent interest, we also provide a multi-bit amortized version of regev's lattice-based cryptosystem (stoc 2005) whose time and space complexity are improved by a linear factor in the security parameter n. the resulting amortized encryption and decryption times are only $\tilde{o}(n)$ bit operations per message bit, and the ciphertext expansion can be made as small as a constant; the public key size and underlying lattice assumption remain essentially the same.
noninteractive statistical zero-knowledge proofs for lattice problems. we construct noninteractive statistical zero-knowledge (niszk) proof systems for a variety of standard approximation problems on lattices, such as the shortest independent vectors problem and the complement of the shortest vector problem. prior proof systems for lattice problems were either interactive or leaked knowledge (or both).our systems are the first known niszk proofs for any cryptographically useful problems that are not related to integer factorization. in addition, they are proofs of knowledge, have reasonable complexity, and generally admit efficient prover algorithms (given appropriate auxiliary input). in some cases, they even imply the first known interactive statistical zero-knowledge proofs for certain cryptographically important lattice problems.we also construct an niszk proof for a special kind of disjunction (i.e., or gate) related to the shortest vector problem. this may serve as a useful tool in potential constructions of noninteractive (computational) zero knowledge proofs for np based on lattice assumptions.
dynamic threshold public-key encryption. this paper deals with threshold public-key encryption which allows a pool of players to decrypt a ciphertext if a given threshold of authorized players cooperate. we generalize this primitive to the dynamic setting, where any user can dynamically join the system, as a possible recipient; the sender can dynamically choose the authorized set of recipients, for each ciphertext; and the sender can dynamically set the threshold t for decryption capability among the authorized set. we first give a formal security model, which includes strong robustness notions, and then we propose a candidate achieving all the above dynamic properties, that is semantically secure in the standard model, under a new non-interactive assumption, that fits into the general diffie-hellman exponent framework on groups with a bilinear map. it furthermore compares favorably with previous proposals, a.k.a. threshold broadcast encryption, since this is the first threshold public-key encryption, with dynamic authorized set of recipients and dynamic threshold that provides constant-size ciphertexts.
key-recovery attacks on universal hash function based mac algorithms. this paper discusses key recovery and universal forgery attacks on several mac algorithms based on universal hash functions. the attacks use a substantial number of verification queries but eventually allow for universal forgeries instead of existential or multiple forgeries. this means that the security of the algorithms completely collapses once a few forgeries are found. some of these attacks start off by exploiting a weak key property, but turn out to become full-fledged divide and conquer attacks because of the specific structure of the universal hash functions considered. partial information on a secret key can be exploited too, in the sense that it renders some key recovery attacks practical as soon as a few key bits are known. these results show that while universal hash functions offer provable security, high speeds and parallelism, their simple combinatorial properties make them less robust than conventional message authentication primitives.
cryptanalysis of the gost hash function. in this article, we analyze the security of the gost hash function. the gost hash function, defined in the russian standard gost 34.11-94, is an iterated hash function producing a 256-bit hash value. as opposed to most commonly used hash functions such as md5 and sha-1, the gost hash function defines, in addition to the common iterative structure, a checksum computed over all input message blocks. this checksum is then part of the final hash value computation.as a result of our security analysis of the gost hash function, we present the first collision attack with a complexity of about 2105 evaluations of the compression function. furthermore, we are able to significantly improve upon the results of mendel et al. with respect to preimage and second preimage attacks. our improved attacks have a complexity of about 2192 evaluations of the compression function.
new state recovery attack on rc4. the stream cipher rc4 was designed by r. rivest in 1987, and it is a widely deployed cipher. in this paper we analyse the class rc4-n of rc4-like stream ciphers, where n is the modulus of operations, as well as the length of internal arrays. our new attack is a state recovery attack which accepts the keystream of a certain length, and recovers the internal state. for the reduced rc4-100, our attack has total complexity of around 293 operations, whereas the best previous attack (from knudsen et al.) needs 2236 of time.the complexity of the attack applied to the original rc4-256 depends on the parameters of specific states (patterns), which are in turn hard to discover. extrapolated parameters from smaller patterns give us the attack of complexity about 2241, and it is much smaller than the complexity of the best known previous attack 2779. the algorithm of the new attack was implemented and verified on small cases.
communication complexity in algebraic two-party protocols. in cryptography, there has been tremendous success in building various two-party protocols with small communication complexity out of homomorphic semantically-secure encryption schemes, using their homomorphic properties in a black-box way. a few notable examples of such primitives include items like single database private information retrieval (pir) schemes (introduced in [15]) and private database update with small communication (introduced in [5]). in this paper, we illustrate a general methodology for determining what types of protocols can and cannot be implemented with small communication by using homomorphic encryption in a black-box way.we hope that this work will provide a simple "litmus test" of feasibility for black-box use of known homomorphic encryption schemes by other cryptographic researchers attempting to develop new protocols with low communication. additionally, a precise mathematical language for reasoning about such problems is developed in this work, which may be of independent interest. we stress that the class of algebraic structures for which we prove communication complexity lower bounds is large, and covers practically all known semantically-secure homomorphic cryptosystems (including those based upon bilinear maps).finally, we show the following equivalence which relates group homomorphic encryption and a major open question of designing a so-called fully-homomorphic cryptosystem: a fully homomorphic encryption scheme (over a non-zero ring) exists if and only if there exists homomorphic encryption over any finite non-abelian simple group. this result somewhat generalizes results of barrington [1] (to any group containing a finite non-abelian simple subgroup) and of maurer and rhodes [18], and in fact gives a constructive proof of the 1974 result werner [28]. (this also answers an open question posed by rappe in [23], who in 2004 proved a special case of this result.)
preimages for reduced sha-0 and sha-1. in this paper, we examine the resistance of the popular hash function sha-1 and its predecessor sha-0 against dedicated preimage attacks. in order to assess the security margin of these hash functions against these attacks, two new cryptanalytic techniques are developed: reversing the inversion problem: the idea is to start with an impossible expanded message that would lead to the required digest, and then to correct this message until it becomes valid without destroying the preimage property. p 3 graphs : an algorithm based on the theory of random graphs that allows the conversion of preimage attacks on the compression function to attacks on the hash function with less effort than traditional meet-in-the-middle approaches. combining these techniques, we obtain preimage-style shortcuts attacks for up to 45 steps of sha-1, and up to 50 steps of sha-0 (out of 80).
improved bounds on security reductions for discrete log based signatures. despite considerable research efforts, no efficient reduction from the discrete log problem to forging a discrete log based signature (e.g. schnorr) is currently known. in fact, negative results are known. paillier and vergnaud [pv05] show that the forgeability of several discrete log based signatures cannot be equivalent to solving the discrete log problem in the standard model, assuming the so-called one-more discrete log assumption and algebraic reductions. they also show, under the same assumptions, that, any security reduction in the random oracle model (rom) from discrete log to forging a schnorr signature must lose a factor of at least $\sqrt{q_h}$ in the success probability. here q h is the number of queries the forger makes to the random oracle. the best known positive result, due to pointcheval and stern [ps00], also in the rom, gives a reduction that loses a factor of q h . in this paper, we improve the negative result from [pv05]. in particular, we show that any algebraic reduction in the rom from discrete log to forging a schnorr signature must lose a factor of at least $q_h^{2/3}$, assuming the one-more discrete log assumption. we also hint at certain circumstances (by way of restrictions on the forger) under which this lower bound may be tight. these negative results indicate that huge loss factors may be inevitable in reductions from discrete log to discrete log based signatures.
circular-secure encryption from decision diffie-hellman. we describe a public-key encryption system that remains secure even encrypting messages that depend on the secret keys in use. in particular, it remains secure under a "key cycle" usage, where we have a cycle of public/secret key-pairs (pk i ,sk i ) for i = 1,...,n, and we encrypt each sk i under ${\rm pk}_{(i \bmod n)+1}$. such usage scenarios sometimes arise in key-management systems and in the context of anonymous credential systems. also, security against key cycles plays a role when relating "axiomatic security" of protocols that use encryption to the "computational security" of concrete instantiations of these protocols.the existence of encryption systems that are secure in the presence of key cycles was wide open until now: on the one hand we had no constructions that provably meet this notion of security (except by relying on the random-oracle heuristic); on the other hand we had no examples of secure encryption systems that become demonstrably insecure in the presence of key-cycles of length greater than one.here we construct an encryption system that is circular-secure against chosen-plaintext attacks under the decision diffie-hellman assumption (without relying on random oracles). our proof of security holds even if the adversary obtains an encryption clique, that is, encryptions of sk i under pk j for all 1 ≤ i,j ≤ n. we also construct a circular counterexample: a one-way secure encryption scheme that breaks completely if an encryption cycle (of any size) is published.
constructing cryptographic hash functions from fixed-key blockciphers. we propose a family of compression functions built from fixed-key blockciphers and investigate their collision and preimage security in the ideal-cipher model. the constructions have security approaching and in many cases equaling the security upper bounds found in previous work of the authors [24]. in particular, we describe a 2n-bit to n-bit compression function using three n-bit permutation calls that has collision security n 0.5, where n = 2 n , and we describe 3n-bit to 2n-bit compression functions using five and six permutation calls and having collision security of at least n 0.55 and n 0.63.
programmable hash functions and their applications. we introduce a new information-theoretic primitive called programmable hash functions (phfs). phfs can be used to program the output of a hash function such that it contains solved or unsolved discrete logarithm instances with a certain probability. this is a technique originally used for security proofs in the random oracle model. we give a variety of standard model realizations of phfs (with different parameters).the programmability of phfs make them a suitable tool to obtain black-box proofs of cryptographic protocols when considering adaptive attacks. we propose generic digital signature schemes from the strong rsa problem and from some hardness assumption on bilinear maps that can be instantiated with any phf. our schemes offer various improvements over known constructions. in particular, for a reasonable choice of parameters, we obtain short standard model digital signatures over bilinear maps.
compression from collisions, or why crhf combiners have a long output. a black-box combiner for collision resistant hash functions (crhf) is a construction which given black-box access to two hash functions is collision resistant if at least one of the components is collision resistant.in this paper we prove a lower bound on the output length of black-box combiners for crhfs. the bound we prove is basically tight as it is achieved by a recent construction of canetti et al [crypto'07]. the best previously known lower bounds only ruled out a very restricted class of combiners having a very strong security reduction: the reduction was required to output collisions for both underlying candidate hash-functions given a single collision for the combiner (canetti et al [crypto'07] building on boneh and boyen [crypto'06] and pietrzak [eurocrypt'07]).our proof uses a lemma similar to the elegant "reconstruction lemma" of gennaro and trevisan [focs'00], which states that any function which is not one-way is compressible (and thus uniformly random function must be one-way). in a similar vein we show that a function which is not collision resistant is compressible. we also borrow ideas from recent work by haitner et al. [focs'07], who show that one can prove the reconstruction lemma even relative to some very powerful oracles (in our case this will be an exponential time collision-finding oracle).
a generalization of ddh with applications to protocol analysis and computational soundness. in this paper we identify the (p,q)-ddh assumption, as an extreme, powerful generalization of the decisional diffie-hellman (ddh) assumption: virtually all previously proposed generalizations of ddh are instances of the (p,q)-ddh problem. we prove that our generalization is no harder than ddh through a concrete reduction that we show to be rather tight in most practical cases. one important consequence of our result is that it yields significantly simpler security proofs for protocols that use extensions of ddh. we exemplify in the case of several group-key exchange protocols (among others we give an elementary, direct proof for the burmester-desmedt protocol). finally, we use our generalization of ddh to extend the celebrated computational soundness result of abadi and rogaway [1] so that it can also handle exponentiation and diffie-hellman-like keys. the extension that we propose crucially relies on our generalization and seems hard to achieve through other means.
finding small roots of bivariate integer polynomial equations: a direct approach. coppersmith described at eurocrypt 96 an algorithm for finding small roots of bivariate integer polynomial equations, based on lattice reduction. a simpler algorithm was later proposed in [9], but it was asymptotically less efficient than coppersmith's algorithm. in this paper, we describe an analogous simplification but with the same asymptotic complexity as coppersmith. we illustrate our new algorithm with the problem of factoring rsa moduli with high-order bits known; in practical experiments our method is several orders of magnitude faster than [9].
new efficient attacks on statistical disclosure control mechanisms. the goal of a statistical database is to provide statistics about a population while simultaneously protecting the privacy of the individual records in the database. the tension between privacy and usability of statistical databases has attracted much attention in statistics, theoretical computer science, security, and database communities in recent years. a line of research initiated by dinur and nissim investigates for a particular type of queries, lower bounds on the distortion needed in order to prevent gross violations of privacy. the first result in the current paper simplifies and sharpens the dinur and nissim result.the dinur-nissim style results are strong because they demonstrate insecurity of all low-distortion privacy mechanisms. the attacks have an all-or-nothing flavor: letting n denote the size of the database, ¿(n) queries are made before anything is learned, at which point ¿(n) secret bits are revealed. restricting attention to a wide and realistic subset of possible low-distortion mechanisms, our second result is a more acute attack, requiring only a fixed number of queries for each bit revealed.
on notions of security for deterministic encryption, and efficient constructions without random oracles. the study of deterministic public-key encryption was initiated by bellare et al. (crypto '07), who provided the "strongest possible" notion of security for this primitive (called priv) and constructions in the random oracle (ro) model. we focus on constructing efficient deterministic encryption schemes without random oracles. to do so, we propose a slightly weaker notion of security, saying that no partial information about encrypted messages should be leaked as long as each message is a-priori hard-to-guess given the others (while priv did not have the latter restriction). nevertheless, we argue that this version seems adequate for many practical applications. we show equivalence of this definition to single-message and indistinguishability-based ones, which are easier to work with. then we give general constructions of both chosen-plaintext (cpa) and chosen-ciphertext-attack (cca) secure deterministic encryption schemes, as well as efficient instantiations of them under standard number-theoretic assumptions. our constructions build on the recently-introduced framework of peikert and waters (stoc '08) for constructing cca-secure probabilistic encryption schemes, extending it to the deterministic-encryption setting as well.
scalable multiparty computation with nearly optimal work and resilience. we present the first general protocol for secure multiparty computation in which the total amount of work required by n players to compute a function f grows only polylogarithmically with n (ignoring an additive term that depends on n but not on the complexity of f). moreover, the protocol is also nearly optimal in terms of resilience, providing computational security against an active, adaptive adversary corrupting a (1/2 ¿ ¿) fraction of the players, for an arbitrary ¿> 0.
cryptographic complexity of multi-party computation problems: classifications and separations. we develop new tools to study the relative complexities of secure multi-party computation tasks in the universal composition framework. when one task can be securely realized using another task as a black-box, we interpret this as a qualitative, complexity-theoretic reduction between the two tasks. virtually all previous characterizations of mpc functionalities, in the uc model or otherwise, focus exclusively on secure function evaluation. in comparison, the tools we develop do not rely on any special internal structure of the functionality, thus applying to functionalities with arbitrary behavior. our tools additionally apply uniformly to both the ppt and unbounded computation models.our first main tool is an exact characterization of realizability in the uc framework with respect to a large class of communication channel functionalities. using this characterization, we can rederive all previously-known impossibility results as immediate and simple corollaries. we also complete the combinatorial characterization of 2-party secure function evaluation initiated by [12] and partially extend the combinatorial conditions to the multi-party setting. our second main tool allows us to translate complexity separations in simpler mpc settings (such as the honest-but-curious corruption model) to the standard (malicious) setting. using this tool, we demonstrate the existence of functionalities which are neither realizable nor complete, in the unbounded computation model.
public-key locally-decodable codes. in this paper we introduce the notion of a public-key encryption scheme that is also a locally-decodable error-correcting code (pkldc). in particular, we allow any polynomial-time adversary to read the entire ciphertext, and corrupt a constant fraction of the bits of the entire ciphertext. nevertheless, the decoding algorithm can recover any bit of the plaintext with all but negligible probability by reading only a sublinear number of bits of the (corrupted) ciphertext.we give a general construction of a pkldc from any semantically-secure public key encryption (ss-pke) and any private information retrieval (pir) protocol. since homomorphic encryption implies pir, we also show a reduction from any homomorphic encryption protocol to pkldc.applying our construction to the best known pir protocol (that of gentry and ramzan), we obtain a pkldc, which for messages of size n and security parameter k achieves ciphertexts of size $\mathcal{o}(n)$, public key of size $\mathcal{o}(n+k)$, and locality of size $\mathcal{o}(k^2)$. this means that for messages of length n = ¿(k 2 + ¿ ), we can decode a bit of the plaintext from a corrupted ciphertext while doing computation sublinear in n.
bits security of the elliptic curve diffie-hellman secret keys. we show that the least significant bits (lsb) of the elliptic curve diffie---hellman secret keys are hardcore. more precisely, we prove that if one can efficiently predict the lsb with non-negligible advantage on a polynomial fraction of all the curves defined over a given finite field $\mathbb{f}_p$, then with polynomial factor overhead, one can compute the entire diffie---hellman secret on a polynomial fraction of all the curves over the same finite field. our approach is based on random self-reducibility (assuming grh) of the diffie---hellman problem among elliptic curves of the same order. as a part of the argument, we prove a refinement of h. w. lenstra's lower bounds on the sizes of the isogeny classes of elliptic curves, which may be of independent interest.
efficient secure linear algebra in the presence of covert or computationally unbounded adversaries. in this work we study the design of secure protocols for linear algebra problems. all current solutions to the problem are either inefficient in terms of communication complexity or assume that the adversary is honest but curious. we design protocols for two different adversarial settings: first, we achieve security in the presence of a covert adversary, a notion recently introduced by [aumann and lindell, tcc 2007]. roughly speaking, this guarantees that if the adversary deviates from the protocol in a way that allows him to cheat, then he will be caught with good probability. second, we achieve security against arbitrary malicious behaviour in the presence of a computationally unbounded adversary that controls less than a third of the parties. our main result is a new upper bound of o(n 2 + 1/t ) communication for testing singularity of a shared n ×n matrix in constant round, for any constant t in both of these adversarial environments. we use this construction to design secure protocols for computing the rank of a shared matrix and solving a shared linear system of equations with similar efficiency.we use different techniques from computer algebra, together with recent ideas from [cramer, kiltz, and padró, crypto 2007], to reduce the problem of securely deciding singularity to the problem of securely computing matrix product. we then design new and efficient protocols for secure matrix product in both adversarial settings. in the two-party setting, we combine cut-and-choose techniques on random additive decomposition of the input, with a careful use of the random strings of a homomorphic encryption scheme to achieve simulation-based security. thus, our protocol avoids general zero-knowledge proofs and only makes a black-box use of a homomorphic encryption scheme.
cryptanalysis of minrank. in this paper, we investigate the difficulty of one of the most relevant problems in multivariate cryptography --- namely minrank --- about which no real progress has been reported since [9, 19]. our starting point is the kipnis-shamir attack [19]. we first show new properties of the ideal generated by kipnis-shamir's equations. we then propose a new modeling of the problem. concerning the practical resolution, we adopt a gröbner basis approach that permitted us to actually solve challenges a and b proposed by courtois in [8]. using the multi-homogeneous structure of the algebraic system, we have been able to provide a theoretical complexity bound reflecting the practical behavior of our approach. namely, when r ¿ the dimension of the matrices minus the rank of the target matrix in the minrank problem is constant, then we have a polynomial time attack $\mathcal{o}\left( \ln\left( q\right) \,n^{3\,r^{\prime2}}\right) $. for the challenge c [8], we obtain a theoretical bound of 266.3 operations.
on expected constant-round protocols for byzantine agreement. in a seminal paper, feldman and micali show an n-party byzantine agreement protocol in the plain model that tolerates t
hash functions and the (amplified) boomerang attack. since crypto 2004, hash functions have been the target of many attacks which showed that several well-known functions such as sha-0 or md5 can no longer be considered secure collision free hash functions. these attacks use classical cryptographic techniques from block cipher analysis such as differential cryptanalysis together with some specific methods. among those, we can cite the neutral bits of biham and chen or the message modification techniques of wang et al. in this paper, we show that another tool of block cipher analysis, the boomerang attack, can also be used in this context. in particular, we show that using this boomerang attack as a neutral bits tool, it becomes possible to lower the complexity of the attacks on sha-1.
pirate evolution: how to make the most of your traitor keys. we introduce a novel attack concept against trace and revoke schemes called pirate evolution. in this setting, the attacker, called an evolving pirate, is handed a number of traitor keys and produces a number of generations of pirate decoders that are successively disabled by the trace and revoke system. a trace and revoke scheme is susceptible to pirate evolution when the number of decoders that the evolving pirate produces exceeds the number of traitor keys that were at his possession. pirate evolution can threaten trace and revoke schemes even in cases where both the revocation and traceability properties are ideally satisfied: this is because pirate evolution may enable an attacker to "magnify" an initial key-leakage incident and exploit the traitor keys available to him to produce a great number of pirate boxes that will take a long time to disable. even moderately successful pirate evolution affects the economics of deployment for a trace and revoke system and thus it is important that it is quantified prior to deployment. in this work, we formalize the concept of pirate evolution and we demonstrate the susceptibility of the trace and revoke schemes of naor, naor and lotspiech (nnl) from crypto 2001 to an evolving pirate that can produce up to t ċ log n generations of pirate decoders given an initial set of t traitor keys. this is particularly important in the context of aacs, the new standard for high definition dvds (hd-dvd and blue-ray) that employ the subset difference method of nnl: for example using our attack strategy, a pirate can potentially produce more than 300 pirate decoder generations by using only 10 traitor keys, i.e., key-leakage incidents in aacs can be substantially magnified.
adaptive one-way functions and applications. we introduce new and general complexity theoretic hardness assumptions. these assumptions abstract out concrete properties of a random oracle and are significantly stronger than traditional cryptographic hardness assumptions; however, assuming their validity we can resolve a number of long-standing open problems in cryptography.
full key-recovery attacks on hmac/nmac-md4 and nmac-md5. at crypto '06, bellare presented new security proofs for hmac and nmac, under the assumption that the underlying compression function is a pseudo-random function family. conversely, at asiacrypt '06, contini and yin used collision techniques to obtain forgery and partial key-recovery attacks on hmac and nmac instantiated with md4, md5, sha-0 and reduced sha-1. in this paper, we present the first full key-recovery attacks on nmac and hmac instantiated with a real-life hash function, namely md4. our main result is an attack on hmac/nmac-md4 which recovers the full mac secret key after roughly 288 mac queries and 295 md4 computations. we also extend the partial key-recovery contini-yin attack on nmac-md5 (in the related-key setting) to a full key-recovery attack. the attacks are based on generalizations of collision attacks to recover a secret iv, using new differential paths for md4.
how many oblivious transfers are needed for secure multiparty computation? oblivious transfer (ot) is an essential building block for secure multiparty computation when there is no honest majority. in this setting, current protocols for n ≥ 3 parties require each pair of parties to engage in a single ot for each gate in the circuit being evaluated. since implementing ot typically requires expensive public-key operations (alternatively, expensive setup or physical infrastructure), minimizing the number of ots is a highly desirable goal. in this work we initiate a study of this problem in both an information-theoretic and a computational setting and obtain the following results. - if the adversary can corrupt up to t = (1 - ɛ)n parties, where ɛ ≥ 0 is an arbitrarily small constant, then a total of o(n) ot channels between pairs of parties are necessary and sufficient for general secure computation. combined with previous protocols for "extending ots", o(nk) invocations of ot are sufficient for computing arbitrary functions with computational security, where k is a security parameter. - the above result does not improve over the previous state of the art in the important case where t = n - 1, when the number of parties is small, or in the information-theoretic setting. for these cases, we show that an arbitrary function f : {0, 1}n → {0, 1}* can be securely computed by a protocol which makes use of a single ot (of strings) between each pair of parties. this result is tight in the sense that at least one ot between each pair of parties is necessary in these cases. a major disadvantage of this protocol is that its communication complexity grows exponentially with n. we present natural classes of functions f for which this exponential overhead can be avoided.
indistinguishability amplification. many aspects of cryptographic security proofs can be seen as the proof that a certain system (e.g. a block cipher) is indistinguishable from an ideal system (e.g. a random permutation), for different types of distinguishers. this paper presents a new generic approach to proving upper bounds on the information-theoretic distinguishing advantage (from an ideal system) for a combined system, assuming upper bounds of certain types for the component systems. for a general type of combination operation of systems, including the xor of functions or the cascade of permutations, we prove two amplification theorems. the first is a product theorem, in the spirit of xor-lemmas: the distinguishing advantage of the combination of two systems is at most twice the product of the individual distinguishing advantages. this bound is optimal. the second theorem states that the combination of systems is secure against some strong class of distinguishers, assuming only that the components are secure against some weaker class of distinguishers. a key technical tool of the paper is the proof of a tight two-way correspondence, previously only known to hold in one direction, between the distinguishing advantage of two systems and the probability of winning an appropriately defined game.
domain extension of public random functions: beyond the birthday barrier. a public random function is a random function that is accessible by all parties, including the adversary. for example, a (public) random oracle is a public random function {0,1}* → {0,1}n. the natural problem of constructing a public random oracle from a public random function {0, 1}m → {0, 1}n (for some m > n) was first considered at crypto 2005 by coron et al. who proved the security of variants of the merkle-damgård construction against adversaries issuing up to o(2n/2) queries to the construction and to the underlying compression function. this bound is less than the square root of n2m, the number of random bits contained in the underlying random function. in this paper, we investigate domain extenders for public random functions approaching optimal security. in particular, for all ɛ ∈ (0, 1) and all functions m and l (polynomial in n), we provide a construction cɛ,m,l(ċ) which extends a public random function r : {0, 1}n → {0, 1}n to a function cɛ,m,l(r) : {0, 1}m(n) → {0, 1}l(n) with time-complexity polynomial in n and 1/ɛ and which is secure against adversaries which make up to θ(2n(1-ɛ)) queries. a central tool for achieving high security are special classes of unbalanced bipartite expander graphs with small degree. the achievability of practical (as opposed to complexity-theoretic) efficiency is proved by a non-constructive existence proof. combined with the iterated constructions of coron et al., our result leads to the first iterated construction of a hash function {0, 1}* → {0, 1}n from a component function {0, 1}n → {0, 1}n that withstands all recently proposed generic attacks against iterated hash functions, like joux's multi-collision attack, kelsey and schneier's second-preimage attack, and kelsey and kohno's herding attacks.
random oracles and auxiliary input. we introduce a variant of the random oracle model where oracle-dependent auxiliary input is allowed. in this setting, the adversary gets an auxiliary input that can contain information about the random oracle. using simple examples we show that this model should be preferred over the classical variant where the auxiliary input is independent of the random oracle. in the presence of oracle-dependent auxiliary input, the most important proof technique in the random oracle model--lazy sampling--does not apply directly. we present a theorem and a variant of the lazy sampling technique that allows one to perform proofs in the new model almost as easily as in the old one. as an application of our approach and to illustrate how existing proofs can be adapted, we prove that rsa-oaep is ind-cca2 secure in the random oracle model with oracle-dependent auxiliary input.
the random oracle model and the ideal cipher model are equivalent. the random oracle model and the ideal cipher model are two well known idealised models of computation for proving the security of cryptosystems. at crypto 2005, coron et al. showed that security in the random oracle model implies security in the ideal cipher model; namely they showed that a random oracle can be replaced by a block cipher-based construction, and the resulting scheme remains secure in the ideal cipher model. the other direction was left as an open problem, i.e. constructing an ideal cipher from a random oracle. in this paper we solve this open problem and show that the feistel construction with 6 rounds is enough to obtain an ideal cipher; we also show that 5 rounds are insufficient by providing a simple attack. this contrasts with the classical luby-rackoff result that 4 rounds are necessary and sufficient to obtain a (strong) pseudo-random permutation from a pseudo-random function.
a hybrid lattice-reduction and meet-in-the-middle attack against ntru. to date the ntruencrypt security parameters have been based on the existence of two types of attack: a meet-in-the-middle attack due to odlyzko, and a conservative extrapolation of the running times of the best (known) lattice reduction schemes to recover the private key. we show that there is in fact a continuum of more efficient attacks between these two attacks. we show that by combining lattice reduction and a meet-in-the-middle strategy one can reduce the number of loops in attacking the ntruencrypt private key from 284.2 to 260.3, for the k = 80 parameter set. in practice the attack is still expensive (dependent on ones choice of cost-metric), although there are certain space/time tradeoffs that can be applied. asymptotically our attack remains exponential in the security parameter k, but it dictates that ntruencrypt parameters must be chosen so that the meet-in-the-middle attack has complexity 2k even after an initial lattice basis reduction of complexity 2k.
reducing trust in the pkg in identity based cryptosystems. one day, you suddenly find that a private key corresponding to your identity is up for sale at e-bay. since you do not suspect a key compromise, perhaps it must be the pkg who is acting dishonestly and trying to make money by selling your key. how do you find out for sure and even prove it in a court of law? this paper introduces the concept of traceable identity based encryption which is a new approach to mitigate the (inherent) key escrow problem in identity based encryption schemes. our main goal is to restrict the ways in which the pkg can misbehave. in our system, if the pkg ever maliciously generates and distributes a decryption key for an identity, it runs the risk of being caught and prosecuted. in contrast to other mitigation approaches, our approach does not require multiple key generation authorities.
chernoff-type direct product theorems. consider a challenge-response protocol where the probability of a correct response is at least &#x03b1; for a legitimate user and at most &#x03b2;<&#x03b1; for an attacker. one example is a captcha challenge, where a human should have a significantly higher chance of answering a single challenge (e.g., uncovering a distorted letter) than an attacker; another example is an argument system without perfect completeness. a natural approach to boost the gap between legitimate users and attackers is to issue many challenges and accept if the response is correct for more than a threshold fraction, for the threshold chosen between &#x03b1; and &#x03b2;. we give the first proof that parallel repetition with thresholds improves the security of such protocols. we do this with a very general result about an attacker&#x2019;s ability to solve a large fraction of many independent instances of a hard problem, showing a chernoff-like convergence of the fraction solved incorrectly to the probability of failure for a single instance.
how should we solve search problems privately? secure multiparty computation allows a group of distrusting parties to jointly compute a (possibly randomized) function of their inputs. however, it is often the case that the parties executing a computation try to solve a search problem, where one input may have a multitude of correct answers - such as when the parties compute a shortest path in a graph or find a solution to a set of linear equations. picking one output arbitrarily from the solution set has significant implications on the privacy of the algorithm. beimel et al. [stoc 2006] gave a minimal definition for private computation of search problems with focus on proving impossibility result. in this work we aim for stronger definitions of privacy for search problems that provide reasonable privacy. we give two alternative definitions and discuss their privacy guarantees. we also supply algorithmic machinery for designing such protocols for a broad selection of search problems.
a security analysis of the nist sp 800-90 elliptic curve random number generator. an elliptic curve random number generator (ecrng) has been approved in a nist standard and proposed for ansi and secg draft standards. this paper proves that, if three conjectures are true, then the ecrng is secure. the three conjectures are hardness of the elliptic curve decisional diffie-hellman problem and the hardness of two newer problems, the x-logarithm problem and the truncated point problem. the x-logarithm problem is shown to be hard if the decisional diffie-hellman problem is hard, although the reduction is not tight. the truncated point problem is shown to be solvable when the minimum amount of bits allowed in nist standards are truncated, thereby making it insecure for applications such as stream ciphers. nevertheless, it is argued that for nonce and key generation this distinguishability is harmless.
a note on secure computation of the moore-penrose pseudoinverse and its application to secure linear algebra. this work deals with the communication complexity of secure multi-party protocols for linear algebra problems. in our model, complexity is measured in terms of the number of secure multiplications required and protocols terminate within a constant number of rounds of communication. previous work by cramer and damgård proposes secure protocols for solving systems ax = b of m linear equations in n variables over a finite field, with m ≤ n. the complexity of those protocols is n5. we show a new upper bound of m4 + n2m secure multiplications for this problem, which is clearly asymptotically smaller. our main point, however, is that the advantage can be substantial in case m is much smaller than n. indeed, if m = √n, for example, the complexity goes down from n5 to n2.5. our secure protocols rely on some recent advances concerning the computation of the moore-penrose pseudo-inverse of matrices over fields of positive characteristic. these computations are based on the evaluation of a certain characteristic polynomial, in combination with variations on a well-known technique due to mulmuley that helps to control the effects of non-zero characteristic. we also introduce a new method for secure polynomial evaluation that exploits properties of chebychev polynomials, as well as a new secure protocol for computing the characteristic polynomial of a matrix based on leverrier's lemma that exploits this new method.
bug attacks. in this paper we present a new kind of cryptanalytic attack which utilizes bugs in the hardware implementation of computer instructions. the best known example of such a bug is the intel division bug, which resulted in slightly inaccurate results for extremely rare inputs. whereas in most applications such bugs can be viewed as a minor nuisance, we show that in the case of rsa (even when protected by oaep), pohlig-hellman, elliptic curve cryptography, and several other schemes, such bugs can be a security disaster: decrypting ciphertexts on any computer which multiplies even one pair of numbers incorrectly can lead to full leakage of the secret key, sometimes with a single well-chosen ciphertext.
pictorial recognition using affine-invariant spectral signatures. this paper describes an efficient approach to pose invariant object recognition employing pictorial recognition of image patches. a complete affine invariance is achieved by a representation which is based on a new sampling configuration in the frequency domain. employing singular value decomposition (svd), the affine transform is decomposed into slant, tilt, swing, scale and 2d translation. from this decomposition, we derive an affine invariant representation that allows to recognize image patches that correspond to object surfaces which are roughly planar -- invariant to their pose in space. the representation is in the form of spectral signatures that are derived from a set of cartesian logarithmic-logarithmic (log-log) sampling configuration in the frequency domain. unlike previous log-polar representations which are not invariant to slant (i.e. foreshortening only in one direction), our new configuration yields complete affine invariance. the proposed log-log configuration can be employed both globally or locally by a gabor or fourier transforms. local representation enables to recognize separately several objects in the same image. the actual signature recognition is performed by multi-dimensional indexing in a pictorial dataset represented in the frequency domain. the recognition also provides 3d pose information.
novel view synthesis in tensor space. we present a new method for synthesizing novel views of a 3d scene from few model images in full correspondence. the core of this work is the derivation of a tensorial operator that describes the transformation from a given tensor of three views to a novel tensor of a new configuration of three views. by repeated application of the operator on a seed tensor with a sequence of desired virtual camera positions we obtain a chain of warping functions (tensors) from the set of model images to create the desired virtual views.
mdl estimation for small sample sizes and its application to segmenting binary strings. minimum description length (mdl) estimation has proven itself of major importance in a large number of applications many of which are in the fields of computer vision and pattern recognition. a problem is encountered in applying the associated formulas, however, especially those associated with model cost. this is because most of these are asymptotic forms appropriate only for large sample sizes. j. rissanen has recently derived sharper code-length formulas valid for much smaller sample sizes. because of the importance of these results, it is our intent here to present a tutorial description of them. in keeping with this goal we have chosen a simple application whose relative tractability allows it to be explored more deeply than most problems: the segmentation of binary strings based on a piecewise bernoulli assumption. by that we mean that the strings are assumed to be divided into substrings, the bits of which are assumed to have been generated by a single (within a substring) bernoulli source.
optic flow calculation using robust statistics. a method for calculating optic flow, using robust statistics, is developed. the method generally out-performs all competing methods in terms of accuracy. one of the key features in the success of this method, is that we use least median of squares, which is known to be robust to outliers. the computational cost is kept very low by using an approximate solution to the least median of squares only in a first stage that detects outliers. the essential ingredients of our method should be applicable in a wide range of other computer vision problems.
limits on super-resolution and how to break them. nearly all super-resolution algorithms are based on the fundamental constraints that the super-resolution image should generate the low resolution input images when appropriately warped and down-sampled to model the image formation process. (these reconstruction constraints are normally combined with some form of smoothness prior to regularize their solution.) in the first part of this paper, we derive a sequence of analytical results which show that the reconstruction constraints provide less and less useful information as the magnification factor increases. we also validate these results empirically and show that, for large enough magnification factors, any smoothness prior leads to overly smooth results with very little high-frequency content (however, many low resolution input images are used). in the second part of this paper, we propose a super-resolution algorithm that uses a different kind of constraint, in addition to the reconstruction constraints. the algorithm attempts to recognize local features in the low-resolution images and then enhances their resolution in an appropriate manner. we call such a super-resolution algorithm a hallucination or recogstruction algorithm. we tried our hallucination algorithm on two different data sets, frontal images of faces and printed roman text. we obtained significantly better results than existing reconstruction-based algorithms, both qualitatively and in terms of rms pixel error.
pattern rejection. the efficiency of pattern recognition is particularly crucial in two scenarios; whenever there are a large number of classes to discriminate, and, whenever recognition must be performed a large number of times. we propose a single technique, namely, pattern rejection, that greatly enhances efficiency in both cases. a rejector is a generalization of a classifier, that quickly eliminates a large fraction of the candidate classes or inputs. this allows a recognition algorithm to dedicate its efforts to a much smaller number of possibilities. importantly, a collection of rejectors may be combined to form a composite rejector, which is shown to be far more effective than any of its individual components. a simple algorithm is proposed for the construction of each of the component rejectors. its generality is established through close relationships with the karhunen-loéve expansion and fisher's discriminant analysis. composite rejectors were constructed for two representative applications, namely, appearance matching based object recognition and local feature detection. the results demonstrate substantial efficiency improvements over existing approaches, most notably fisher's discriminant analysis.
3d reconstruction of the human jaw from a sequence of images. a novel approach is proposed to obtain a record of the patient's occlusion using computer vision. data acquisition is obtained using intra-oral video cameras. the technique utilizes shape from shading to extract 3d information from 2d views of the jaw, and a novel technique for 3d data registration using genetic algorithms. the resulting 3d model can be used for diagnosis, treatment planning, and implant purposes. the overall purpose of this research is to develop a model-based vision system for orthodontics to replace traditional approaches. this system will be flexible, accurate, and will reduce the cost of orthodontic treatments.
modelling of single mode distributions of colour data using directional statistics. three different statistical models of colour data for use in segmentation or tracking algorithms are proposed. results of a performance comparison of a tracking algorithm, applied to two separate applications, using each of the three different types of underlying model of the data are presented. from these a comparison of the performance of the statistical colour models themselves is obtained.
recursive estimation of motion and planar structure. abstract a specialized formulation of azarbayejani and pentland''s framework for recursive recovery of motion, structure and focal length from feature correspondences tracked through an image sequence is presented. the specialized formulation addresses the case where all tracked points lie on a plane. this planarity constraint reduces the dimension of the original state vector, and consequently the number of feature points needed to estimate the state. experiments with synthetic data and real imagery illustrate the system performance. the experiments confirm that the specialized formulation provides improved accuracy, stability to observation noise, and rate of convergence in estimation for the case where the tracked points lie on a plane.
extracting salient curves from images: an analysis of the saliency network. the saliency network proposed by shashua and ullman is a well-known approach to the problem of extracting salient curves from images while performing gap completion. this paper analyzes the saliency network. the saliency network is attractive for several reasons. first, the network generally prefers long and smooth curves over short or wiggly ones. while computing saliencies, the network also fills in gaps with smooth completions and tolerates noise. finally, the network is locally connected, and its size is proportional to the size of the image. nevertheless, our analysis reveals certain weaknesses with the method. in particular, we show cases in which the most salient element does not lie on the perceptually most salient curve. furthermore, in some cases the saliency measure changes its preferences when curves are scaled uniformly. also, we show that for certain fragmented curves the measure prefers large gaps over a few small gaps of the same total size. in addition, we analyze the time complexity required by the method. we show that the number of steps required for convergence in serial implementations is quadratic in the size of the network, and in parallel implementations is linear in the size of the network. we discuss problems due to coarse sampling of the range of possible orientations. we show that with proper sampling the complexity of the network becomes at least cubic in the size of the network. finally, we consider the possibility of using the saliency network for grouping. we show that the saliency network recovers the most salient curve efficiently, but it has problems with identifying any salient curve other than the most salient one.
verifying model-based alignments in the presence of uncertainty. this paper introduces a unified approach to the problem of verifying alignment hypotheses in the presence of substantial amounts of uncertainty in the predicted locations of projected model features. our approach is independent of whether the uncertainty is distributed or bounded, and, moreover, incorporates information about the domain in a formally correct manner. information which can be incorporated includes the error model, the distribution of background features, and the positions of the data features near each predicted model feature. experiments are described that demonstrate the improvement over previously used methods. furthermore, our method is efficient in that the number of operations is on the order of the number of image features that lie nearby the predicted model features.
model-based approach to accurate and consistent 3--d modeling of drainage and surrounding terrain. we propose an automated approach to modeling drainage channels---and, more generally, linear features that lie on the terrain---from multiple images, which results not only in high-resolution, accurate and consistent models of the features, but also of the surrounding terrain.in our specific case, we have chosen to exploit the fact that rivers flow downhill and lie at the bottom of local depressions in the terrain, valley floors tend to be ``u'' shaped, and the drainage pattern appears as a network of linear features that can be visually detected in single gray-level images.different approaches have explored individual facets of this problem. ours unifies these elements in a common framework. we accurately model terrain and features as 3--dimensional objects from several information sources that may be in error and inconsistent with one another. this approach allows us to generate models that are faithful to sensor data, internally consistent and consistent with physical constraints. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
photometric computation of the sign of gaussian curvature using a curve-orientation invariant. we compute the sign of gaussian curvature using a purely geometric definition. consider a point p on a smooth surface s and a closed curve g on s which encloses p. the image of g on the unit normal gaussian sphere is a new curve b. the gaussian curvature at p is defined as the ratio of the area enclosed by g over the area enclosed by b as g contracts to p. the sign of gaussian curvature at p is determined by the relative orientations of the closed curves g and b. we directly compute the relative orientation of two such curves from intensity data. we employ three unknown illumination conditions to create a photometric scatter plot. this plot is in one-to-one correspondence with the subset of the unit gaussian sphere containing the mutually illuminated surface normals. this permits direct computation of the sign of gaussian curvature without the recovery of surface normals. our method is albedo invariant. we assume diffuse reflectance, but the nature of the diffuse reflectance can be general and unknown. simulations, as well as empirical results, demonstrate the accuracy of our technique.
real-time extraction of connected components in 3-d sonar range images. this paper describes an efficient algorithm for the segmentation of echo clusters within a dynamic 3-d sonar image. the sensor centered image is an echo management framework grouping sonar returns into spherical cells, and allowing real-time organisation of 3-d range data using inexpensive equipment. each cell acts as a spatial key to the features related to this location. the spherical representation is effectively exploited for segmentation using an approach motivated from connected components analysis in binary video images. a fast algorithm (linear in time complexity) based on cell connectivity between sonar beams is presented, including methods for coping with sparse data.
a curvature based descriptor invariant to pose and albedo derived from photometric data. gaussian curvature is an invariant local descriptor of smooth surfaces. we present an object signature which is a condensed representation of the distribution of gaussian curvature information at visible object points. an invariant related to gaussian curvature at a point is derived from the covariance matrix of the photometric values in a neighborhood about that point. in addition, we introduce an albedo-normalization method that is capable of cancelling albedo on lambertian surfaces. we use three illumination conditions, two of which are unknown. the three-tuple of intensity values at a point is related via a one-to-one mapping to the surface normal at that point. the determinant of the covariance matrix of the local three-tuples is invariant to albedo, rotation and translation. the collection of determinants over mutually illuminated object points is combined into a signature distribution which is albedo, rotation, translation, and scale invariant. an object recognition methodology using these signatures is proposed.
stereo-motion that complements stereo and motion analyses. recovering three-dimensional (3d) information of a scene from its images is a fundamental problem in computer vision. there exists two major multi-ocular cues for it, namely the motion cue and the stereo cue. this paper presents a new approach of integrating the two cues when two cameras that move through the scene while taking pictures repeatedly are available. the approach is based on the singular value decomposition (svd) technique, with which the 3d structure of the scene, the image projection parameters, the motion parameters, and the stereo geometry are all separated. the approach offers the advantages of both cues: simple correspondence as well as accurate reconstruction. it can also work with relatively short image sequences.
finding corresponding points based on bayesian triangulation. in this paper, we consider the problems of finding corresponding points from multiple perspective projection images (the correspondence problem), and estimating the 3-d point from which these points have arisen (the triangulation problem). we pose the triangulation problem as that of finding the bayesian maximum a posteriori estimate of the 3-d point, given its projections in n images, assuming a gaussian error model for the image point co-ordinates and the camera parameters. we solve this by an iterative steepest descent method. we then consider the correspondence problem as a statistical hypothesis verification problem. given a set of 2-d points, under the hypothesis that the points are in correspondence, the map estimate of the 3-d point is computed. based on the map estimate, we derive a statistical test for verifying this hypothesis. to find sets of corresponding points when multiple points in each of n images are given, we propose a method that does the bayesian triangulation and hypothesis verification on each n-tuple of points, selecting those that pass the hypothesis test. we characterize the performance of the bayesian triangulation in terms of the average distance of the triangulated 3-d point from the true 3-d point, and of the point correspondence method in terms of its misdetection and false alarm rates.
shape indexing using approximate nearest-neighbour search in high-dimensional spaces. shape indexing is a way of making rapid associations between features detected in an image and object models that could have produced them. when model databases are large, the use of high-dimensional features is critical, due to the improved level of discrimination they can provide. unfortunately, finding the nearest neighbour to a query point rapidly becomes inefficient as the dimensionality of the feature space increases. past indexing methods have used hash tables for hypothesis recovery, but only in low-dimensional situations. in this paper, we show that a new variant of the k-d tree search algorithm makes indexing in higher-dimensional spaces practical. this best bin first, or bbf, search is an approximate algorithm which finds the nearest neighbour for a large fraction of the queries, and a very close neighbour in the remaining cases. the technique has been integrated into a fully developed recognition system, which is able to detect complex objects in real, cluttered scenes in just a few seconds.
what is the set of images of an object under all possible lighting conditions? the appearance of a particular object depends on both the viewpoint from which it is observed and the light sources by which it is illuminated. if the appearance of two objects is never identical for any pose or lighting conditions, then-in theory - the objects can always be distinguished or recognized. the question arises: what is the set of images of an object under all lighting conditions and pose? in this paper, we consider only the set of images of an object under variable illumination (including multiple, extended light sources and attached shadows). we prove that the set of n-pixel images of a convex object with a lambertian reflectance function, illuminated by an arbitrary number of point light sources at infinity, forms a convex polyhedral cone in ir/sup n/ and that the dimension of this illumination cone equals the number of distinct surface normals. furthermore, we show that the cone for a particular object can be constructed from three properly chosen images. finally, we prove that the set of n-pixel images of an object of any shape and with an arbitrary reflectance function, seen under all possible illumination conditions, still forms a convex cone in ir/sup n/. these results immediately suggest certain approaches to object recognition. throughout this paper, we offer results demonstrating the empirical validity of the illumination cone representation.
independent 3d motion detection based on depth elimination in normal flow fields. this paper considers a specific problem of visual perception of motion, namely the problem of visual detection of independent 3d motion. most of the existing techniques for solving this problem rely on restrictive assumptions about the environment, the observer's motion, or both. moreover, they are based on the computation of optical flow, which amounts to solving the ill-posed correspondence problem. in this work, independent motion detection is formulated as robust parameter estimation applied to the visual input acquired by a binocular, rigidly moving observer. depth and motion measurements are combined in a linear model. the parameters of this model are related to the parameters of self-motion (egomotion) and the parameters of the stereoscopic configuration of the observer. the robust estimation of this model leads to a segmentation of the scene based on 3d motion. the method avoids the correspondence problem by employing only normal flow fields. experimental results demonstrate the effectiveness of this method in detecting independent motion in scenes with large depth variations, without any constraints imposed on observer motion.
the bas-relief ambiguity. when an unknown object with lambertian reflectance is viewed orthographically, there is an implicit ambiguity in determining its 3-d structure: we show that the object&lsquo;s visible surface f(x, y) is indistinguishable from a &ldquo;generalized bas-relief&rdquo; transformation of the object&lsquo;s geometry, \bar f (x, y) &equals; &lambda;f(x, y) + &mu;x + &nu;y, and a corresponding transformation on the object&lsquo;s albedo. for each image of the object illuminated by an arbitrary number of distant light sources, there exists an identical image of the transformed object illuminated by similarly transformed light sources. this result holds both for the illuminated regions of the object as well as those in cast and attached shadows. furthermore, neither small motion of the object, nor of the viewer will resolve the ambiguity in determining the flattening (or scaling) &lambda; of the object&lsquo;s surface. implications of this ambiguity on structure recovery and shape representation are discussed.
interpreting and representing tabular documents. this paper describes a methodology to interpret the information from telephone company dsx assignment table drawings. horizontal lines are found using an efficient algorithm that works over the run-length encoded representation of the image. for vertical lines, the image is transposed using an efficient method we developed, and the algorithm for horizontal lines is applied again. using the information about the lines, the tabular structures are extracted by finding biconnected components on the graph formed by the lines and their intersections. a methodology has also been developed for the representation of end access to the entries inside the tables.
representation of objects in a volumetric frequency domain with application to face recognition. a novel method for representing 3-d objects that unifies viewer and model centered object representations is presented. a unified 3-d frequency-domain representation (called volumetric/iconic spectral signatures - v/iss) encapsulates both the spatial structure of the object and a continuum of its views in the same data structure. the frequency-domain image of an object viewed from any direction can be directly extracted employing an extension of the projection slice theorem, where each fourier-transformed view is a planar slice of the volumetric frequency representation. the v/iss representation can be employed for pose-invariant recognition of complex objects such as faces. the recognition and pose estimation is based on an efficient matching algorithm in a four dimensional fourier space. experimental examples of pose estimation and recognition of faces are also presented.
multilinear constraints in the infinitesimal-time cas. in this paper we study the infinitesimal-time case of the so called multilinear constraints that exist for each subsequence in a sequence of images. these constraints link the infinitesimal motion of the image points with the infinitesimal viewer motion. the analysis is done both for calibrated and uncalibrated cameras. two simplifications are also presented for the uncalibrated camera case. one simplification is made using affine reduction and kinetic depth. the second simplification is based upon a projective reduction with respect to the image of a planar patch.
resolving occlusion in augmented reality : a contour based approach without 3d reconstruction. we present a new approach for resolving occlusions in augmented reality. the main interest is that it does not require 3d reconstruction of the considered scene. our idea is to use a contour based approach and to label each contour point as being behind or in front of, depending on whether it is in front of or behind the virtual object. this labeling step only requires that the contours can be tracked from frame to frame. a proximity graph is then built in order to group the contours that belong to the same occluding object. finally, we use some kind of active contours to accurately recover the mask of the occluding object.
deformable multi template matching with application to portal images. the exact positioning of patients during radiotherapy is essentialfor high precision treatment. the registration of portal image sequences can help to control the patient position. the particular problem of such megavoltage x-ray imagery is its extremely low contrast, rendering accurate feature extraction a difficult task. to circumvent the step offeature extraction, the algorithm presented in this paper relies on anarea-bused matching of the image signal using deformable templates. this strategy contrasts with most state of the art registration algorithms for portal imagery. the paper includes the mathematical formalism of the least squares template matching method, as well as the framework for automated quality control, together yielding a fast, robust and very accurate image matching procedure. tests on i7 portal image series with more than 100 images in total have shown very satisfying results. artificially rotated and shifted images demonstrate the performance of the method with respect to a ground truth.
deformable multi template matching with application to portal images. the exact positioning of patients during radiotherapy is essentialfor high precision treatment. the registration of portal image sequences can help to control the patient position. the particular problem of such megavoltage x-ray imagery is its extremely low contrast, rendering accurate feature extraction a difficult task. to circumvent the step offeature extraction, the algorithm presented in this paper relies on anarea-bused matching of the image signal using deformable templates. this strategy contrasts with most state of the art registration algorithms for portal imagery. the paper includes the mathematical formalism of the least squares template matching method, as well as the framework for automated quality control, together yielding a fast, robust and very accurate image matching procedure. tests on i7 portal image series with more than 100 images in total have shown very satisfying results. artificially rotated and shifted images demonstrate the performance of the method with respect to a ground truth.
shadows and shading flow fields. many presume that parsing the shadows out of an image is a high-level task, because of the global nature of the shadow formation process. but shape-from-shading algorithms are low-level, in the sense that they seek solutions (surface normals or depth values) directly from image intensities. a dilemma arises: since shape-from-shading involves an illumination term, shadows must first be identified. we show that a structure intermediate between intensities and surfaces-the shading flow field-provides a solution to this dilemma. our analysis is based on the observation that the geometric information that can be derived from images supports different inferences than the photometric information, and our specific goal will be to articulate this geometric structure and to show how shading flow fields can be reliably computed.
reconstruction of 3d-curves from 2d-images using affine shape methods for curves. in this paper, we propose an algorithm for doing reconstruction of general sd-curves from a number of 2d-images taken by uncalibrated cameras. no point correspondences between the images are assumed. the curve and the view points are uniquely reconstructed, module common projective transformations and the point correspondence problem is solved. furthermore, the algorithm is independent of the choice of coordinates, as it is based on orthogonal projections and aligning subspaces. the algorithm is based on an extension of afine shape of finite point configurations to more general objects.
recursive structure and motion from image sequences using shape and depth spaces. in this paper a novel recursive method for estimating structure and motion from image sequences is presented. the novelty lies in the fact that the output of the algorithm is independent of the chosen coordinate systems in the images as well as the ordering of the points. it relies on subspace methods and is derived from both ordinary coordinate representations and camera matrices and from a so called depth and shape analysis. furthermore, no initial phase is needed to start up the algorithm. it starts directly with the first two images and incorporates new images as soon as new corresponding points are obtained. the performance of the algorithm is shown on simulated data.moreover, the two different approaches, one using camera matrices and the other using the concepts of affine shape and depth, are unified into a general theory of structure and motion from image sequences.
calibration of a foveated wide-angle lens on an active vision head. inspired by the properties of the humam visual system, a new active vision system called escher (etl stereo compact head for robot vision) has been recently implemented with foveated wide-angle lenses. the lenses exhibit a wide field of view along with a space-varying resolution for facilitating both detection and close observation. however, to handle such optical properties and achieve basic eye movement functions, new calibration methods are needed. therefore, two novel and online techniques are presented that in one case perform a global identification of the optical process through artificial neural techniques and in the other case compute the physical parameters by using environmental feature-tracking and controlled rotations of the cameras. self-alignment of the cameras is also achieved using a similar technique.
feature correspondence by interleaving shape and texture computations. the correspondence problem in computer vision is basically a matching task between two or more sets of features. in this paper, we introduce a vectorized image representation, which is a feature-based representation where correspondence has been established with respect to a reference image. the representation consists of two image measurements made at the feature points: shape and texture. feature geometry, or shape, is represented using the (x, y) locations of features relative to the some standard reference shape. image grey levels, or texture, are represented by mapping image grey levels onto the standard reference shape. computing this representation is essentially a correspondence task, and in this paper we explore an automatic technique for "vectorizing" face images. our face vectorizer alternates back and forth between computation steps for shape and texture, and a key idea is to structure the two computations so that each one uses the output of the other. in addition to describing the vectorizer, an application to the problem of facial feature detection will be presented.
ordinal measures for visual correspondence. we present ordinal measures for establishing image correspondence. linear correspondence measures like correlation and the sum of squared differences are known to be fragile. ordinal measures, which are based on relative ordering of intensity values in windows, have demonstrable robustness to depth discontinuities, occlusion and noise. the relative ordering of intensity values in each window is represented by a rank permutation which is obtained by sorting the corresponding intensity data. by using a novel distance metric between the rank permutations, we arrive at ordinal correlation coefficients. these coefficients are independent of absolute intensity scale, i.e they are normalized measures. further, since rank permutations are invariant to monotone transformations of the intensity values, the coefficients are unaffected by nonlinear effects like gamma variation between images. we have developed a simple algorithm for their efficient implementation. experiments suggest the superiority of ordinal measures over existing techniques under non-ideal conditions. though we present ordinal measures in the context of stereo, they serve as a general tool for image matching that is applicable to other vision problems such as motion estimation and image registration.
motion estimation using ordinal measures. we present a method for motion estimation using ordinal measures. ordinal measures are based on relative ordering of intensity values in an image region called rank permutation. while popular measures like the sum-of-squared-difference (ssd) and normalized correlation (ncc) rely on linearity between corresponding intensity values, ordinal measures only require them to be monotonically related so that rank permutations between corresponding regions are presented. this property turns out to be useful for motion estimation in tagged magnetic resonance images. we study the imaging equation involved in two methods of tagging and observe temporal monotonicity in intensity under certain conditions though the tags themselves fade. we compare our method to ssd and ncc in a rotating ring phantom image sequence. we present an experiment on a real heart image sequence which suggests the suitability of our method.
deterioration detection for digital film restoration. this paper presents a robust technique to detect local deteriorations of old cinematographic films. this method relies on spatio-temporal information and combines two different detectors: a morphological detector which uses spatial properties of deteriorations, and a dynamic detector based on motion estimation techniques. our deterioration detector has been validated on several film sequences and turned out to be a powerful tool for digital film restoration.
recognition of planar object classes. we present a new framework for recognizing planar object classes, which is based on local feature detectors and a probabilistic model of the spatial arrangement of the features. the allowed object deformations are represented through shape statistics, which are learned from examples. instances of an object in an image are detected by finding the appropriate features in the correct spatial configuration. the algorithm is robust with respect to partial occlusion, detector false alarms, and missed features. a 94\% success rate was achieved for the problem of locating quasi-frontal views of faces in cluttered scenes.
on a spectral attentional mechanism. this paper describes an attentional mechanism based on the interpretation of spectral signatures for detecting regular object configurations in areas of an image delineated using context information. the proposed global operator relies on the spectral analyse's of edge structure and exploits spatial as well as frequency domain constraints derived from known geometrical models of monitored objects. a decision theoretic method for learning decision regions is presented. applications of this mechanism are demonstrated for several aerial image interpretation tasks. specific examples are described for detecting vehicle formations (such as convoys), qualifying the geometry of detected formations, or monitoring the occupancy of regions of interest (such as parking areas, roads, or open areas). experiments and sensitivity analysis results are reported.
recognition via consensus of local moments of brightness and orientation. this study combines two useful methods in recognition: consensus or voting-based approaches and moment-based representations. matches between image patches are generated using a gaussian-weighted moment encoding of the patches and a feature indexing process. each match implies an object 3d position and orientation (pose) and generates a vote for this pose. recognition is accomplished by detecting significant clusters of votes in pose space. this combined method is an improvement over voting and moment methods in isolation. using image brightness moments, the idea is successfully demonstrated on examples of human faces undergoing full 3d pose change, as well as changes in features such as talking and blinking. the idea is then extended to moments of local texture orientation and successfully demonstrated under large variations in lighting nature and geometry.
learning parameterized models of image motion. a framework for learning parameterized models of optical flow from image sequences is presented. a class of motions is represented by a set of orthogonal basis flow fields that are computed from a training set using principal component analysis. many complex image motions can be represented by a linear combination of a small number of these basis flows. the learned motion models may be used for optical flow estimation and for model-based recognition. for optical flow estimation we describe a robust, multi-resolution scheme for directly computing the parameters of the learned flow models from image derivatives. as examples we consider learning motion discontinuities, non-rigid motion of human mouths, and articulated human motion.
autonomous recognition: driven by ambiguit. recognition ambiguity, due to noisy measurements and uncertain object models, can be quantified and actively used by an autonomous agent to efficiently gather new data and improve its information about the environment. in this work an information-based utility measure is used to derive from a learned classification of shape models an efficient data collection strategy, specifically aimed at increasing classification confidence when recognizing uncertain shapes. promising simulation results are presented and discussed.
controlling view-based algorithms using approximate world models and action information. most view-based vision algorithms are based on strong assumptions about the disposition of the objects in the image. to safely apply those algorithms in real world image sequences, we propose that a vision system should be divided into two components. the first component contains an approximate world model of the scene-a low accuracy, coarse description of the objects and actions in the world. approximate world models are constructed and updated by simple vision routines and by the use of action information provided by an external source. the second component employs view-based algorithms to perform required perceptual tasks; the selection and control of the view-based methods are determined by the information provided by the approximate world model. we demonstrate the approximate world model approach in a project to control cameras in a tv studio where the external context is provided by a script.
lie groups, space-variant fourier analysis and the exponential chirp transform. the use of visual representations in which retinal neurons receptive fields are not constant over the visual field is universal in the visual systems of higher vertebrates, and is coming to play an important role in active vision applications. the breaking of translation symmetry that is unavoidably associated with non-uniform sampling presents a major algorithmic complication for image processing. in this paper we use a lie group approach to derive a kernel which provides a quasi-shift (i.e. approximate shift) invariant template matching capability, under normal convolution in the distorted (range) coor- dinates of the non-uniform mapping. we work out the special case of the log- polar mapping, which is of great interest in vision; in this case, we call the associated linear integral transform the ``exponential chirp transform'' (ect). the method is, however, general for other forms of mapping, or warp, function.
experimental performance evaluation of feature grouping modules. we present five performance measures to evaluate grouping modules in the context of constrained search and indexing based object recognition. using these measures, we demonstrate a sound experimental framework based on statistical anova tests to compare and contrast three edge based organization modules, namely those of etemadi et al., jacobs, and sarkar-boyer in the domain of aerial objects using 50 images. with adapted parameters, the jacobs module is overall the best choice for constraint based recognition. for fixed parameters, the sarkar-boyer module is the best in terms of recognition accuracy and indexing speedup. etemadi et al.'s module performs equally well with fixed and adapted parameters while the jacobs module is most sensitive to fixed and adapted parameter choices. the overall performance ranking of the modules is jacobs, sarkar-boyer, and etemadi et al..
global training of document processing systems using graph transformer networks. we propose a new machine learning paradigm called graph transformer networks that extends the applicability of gradient-based learning algorithms to systems composed of modules that take graphs as inputs and produce graphs as output. training is performed by computing gradients of a global objective function with respect to all the parameters in the system using a kind of back-propagation procedure.a complete check reading system based on these concepts is described. the system uses convolutional neural network character recognizers, combined with global training techniques to provide record accuracy on business and personal checks. it is presently deployed commercially and reads million of checks per month.
corner detection with covariance propagation. this paper presents a statistical approach for detecting corners from chain encoded digital arcs. an arc point is declared as a corner if the estimated parameters of the two fitted lines of the two arc segments immediately to the right and left of the arc point are statistically significantly different. the corner detection algorithm consists of two steps: corner detection and optimization. while corner detection involves statistically identifying the most likely corner points along an arc sequence, corner optimization deals with improving the locational errors of the detected corners.the major contributions of this research include developing a method for analytically estimating the covariance matrix of the fitted line parameters and developing a hypothesis test statistic to statistically test the difference between the parameters of two fitted lines. this paper discusses the theory and performance characterization of the proposed corner detector.
a hierarchical approach to high resolution edge contour reconstruction. efficient edge detection algorithms such as canny's (1986) fail near curve singularities. moreover, the standard linking algorithms used on top of these detectors often fail because of instabilities in the tracking process (due to multiple responses to the same edge and interference of nearby edges). we propose a hierarchical approach to edge detection based on a graph stabilization method that allows bifurcation resolution in stages. curve singularities are recovered at the last stage by using "top-down" feedback to select the best curve connections.
head tracking via robust registration in texture map images. abstract a novel method for 3d head tracking in the presence of large head rotations and facial expression changes is described. tracking is formulated in terms of color image registration in the texture map of a 3d surface model. model appearance is recursively updated via image mosaicking in the texture map as the head orientation varies. the resulting dynamic texture map provides a stabilized view of the face that can be used as input to many existing 2d techniques for face recognition, facial expressions analysis, lip reading, and eye tracking. parameters are estimated via a robust minimization procedure; this provides robustness to occlusions, wrinkles, shadows, and specular highlights. the system was tested on a variety of sequences taken with low quality, uncalibrated video cameras. experimental results are reported.
a new bayesian framework for object recognition. we describe a new approach to feature-based object recognition, using maximum a posteriori (map) estimation under a markov random field (mrf) model. the main advantage of this approach is that it allows explicit modeling of dependencies between individual features of an object. for instance, we use the approach to model the fact that mismatched features due to partial occlusions tend to form spatially coherent groups rather than being independent. efficient computation of the map estimate in our framework can be accomplished by finding a minimum cut on an appropriately defined graph. an even more efficient approximation, that does not use graph cuts, is also presented. this approximation technique, which we call spatially coherent matching (scm), is closely related to generalized hausdorff matching. we report some monte carlo experiments showing that the scm technique improves substantially on the tradeoff between correct detection and false alarms compared with previous feature matching methods such as the hausdorff distance.
fast, reliable head tracking under varying illumination. abstract an improved technique for 3d head tracking under varying illumination conditions is proposed. the head is modeled as a texture mapped cylinder. tracking is formulated as an image registration problem in the cylinder''s texture map image. to solve the registration problem in the presence of lighting variation and head motion, the residual error of registration is modeled as a linear combination of texture warping templates and orthogonal illumination templates. fast and stable on-line tracking is then achieved via regularized, weighted least squares minimization of the registration error. the regularization term tends to limit potential ambiguities that arise in the warping and illumination templates. it enables stable tracking over extended sequences. tracking does not require a precise initial fit of the model; the system is initialized automatically using a simple 2-d face detector. the only assumption is that the target is facing the camera in the first frame of the sequence. the warping templates are computed at the first frame of the sequence. illumination templates are precomputed off-line over a training set of face images collected under varying lighting conditions. experiments in tracking are reported.
disparity component matching for visual correspondence. we present a method for computing dense visual correspondence based on general assumptions about scene geometry. our algorithm does not rely on correlation, and uses a variable region of support. we assume that images consist of a number of connected sets of pixels with the same disparity, which we call {\em disparity components}. at each pixel we compute a small set of plausible disparities, each of which is more likely to be the pixel's true disparity than not. a pixel is assigned a disparity $d$ based on connected components of pixels, where each pixel in a component considers $d$ to be plausible. our implementation chooses the largest plausible disparity component; however, global contextual constraints can also be applied. while the algorithm was originally designed for visual correspondence, it can also be used for other early vision problems such as image restoration. it runs in a few seconds on traditional benchmark images with standard parameter settings, and gives quite promising results.
markov random fields with efficient approximations. markov random fields (mrf''s) can be used for a wide variety of vision problems. in this paper we address the estimation of first-order mrf''s with a particular clique potential that resembles a well. we show that the maximum {\em a posteriori} estimate of such an mrf can be obtained by solving a multiway cut problem on a graph. this allows the application of near linear-time algorithms for computing provably good approximations. we formulate the visual correspondence problem as an mrf in our framework, and show that this yields quite promising results on real data with ground truth.
model-based multi-objective analysis of ultrasound image sequences in prenatal diagnosis. in this study, ultrasound image sequences of fetus head are examined for the bi-parietal diameter measurement. there are five parts of the fetus head that have to be seen clearly before such a measurement can be made. our approach is based on model-based multi-objective analysis. for each part, an objective function encoding both data and anatomic constraints is formulated. the resulting multi-objective problem is then transformed into a problem of coupled differential equations and is then solved using numerical integration. throughout the process, continuity principle is used between the frames so that the results of analysis on one frame can be used on the next frame-whenever possible.
stereo coupled active contours. we consider how tracking in stereo may be enhanced by coupling pairs of active contours in different views via affine epipolar geometry and various subsets of planar affine transformations, as well as by implementing temporal constraints imposed by curve rigidity. 3d curve tracking is achieved using a submanifold model, where it is shown how the coupling mechanisms can be decomposed to cater for fixed and variable epipolar geometries. in the case of tracking planar curves, the canonical frame model is developed such that the various geometrical constraints needed in different situations may be efficiently selected. the results show that coupled active contours add consistency and robustness to tracking in stereo.
coupled hidden markov models for complex action recognition. we present algorithms for coupling and training hidden markov models (hmms) to model interacting processes, and demonstrate their superiority to conventional hmms in a vision task classifying two-handed actions. hmms are perhaps the most successful framework in perceptual computing for modeling and classifying dynamic behaviors, popular because they offer dynamic time warping, a training algorithm and a clear bayesian semantics. however the markovian framework makes strong restrictive assumptions about the system generating the signal-that it is a single process having a small number of states and an extremely limited state memory. the single-process model is often inappropriate for vision (and speech) applications, resulting in low ceilings on model performance. coupled hmms provide an efficient way to resolve many of these problems, and offer superior training speeds, model likelihoods, and robustness to initial conditions.
learning and recognizing human dynamics in video sequences. this paper describes a probabilistic decomposition of human dynamics at multiple abstractions, and shows how to propagate hypotheses across space, time, and abstraction levels. recognition in this framework is the succession of very general low level grouping mechanisms to increased specific and learned model based grouping techniques at higher levels. hard decision thresholds are delayed and resolved by higher level statistical models and temporal context. low-level primitives are areas of coherent motion found by em clustering, mid-level categories are simple movements represented by dynamical systems, and high-level complex gestures are represented by hidden markov models as successive phases of simple movements. we show how such a representation can be learned from training data, and apply it to the example of human gait recognition.
recovering non-rigid 3d shape from image streams. this paper addresses the problem of recovering 3d non-rigid shape models from image sequences. for example, given a video recording of a talking person, we would like to estimate a 3d model of the lips and the full head and its internal modes of variation. many solutions that recover 3d shape from 2d image sequences have been proposed; these so-called structure-from-motion techniques usually assume that the 3d object is rigid. for example, tomasi and kanade''s factorization technique is based on a rigid shape matrix, which produces a tracking matrix of rank 3 under orthographic projection. we propose a novel technique based on a non-rigid model, where the 3d shape in each frame is a linear combination of a set of basis shapes. under this model, the tracking matrix is of higher rank, and can be factored in a three step process to yield to pose, configuration and shape. we demonstrate this simple but effective algorithm on video sequences of speaking people. we were able to recover 3d non-rigid facial models with high accuracy.
tracking people with twists and exponential maps. (november 1997)
indexing to 3d model aspects using 2d contour features. we present a shape-based method of indexing to model aspects from a single intensity image. objects are assumed to be rigid. a model aspect is represented by a 2 1/2d edgemap and the parts of the object silhouette. part decomposition is derived from a codon representation of the object silhouette. invariant features extracted from each part are then used to index into a hash table to generate model-aspect hypotheses. knowledge about parts is incorporated in voting schemes to order hypotheses for efficient verification of candidate models. verification of model-aspect hypotheses is carried out by an alignment algorithm that is robust to partial occlusion. results of tests using 658 model aspects from 100 objects demonstrate that accurate recognition can be achieved with very few verification attempts.
orientation space filtering for multiple orientation line segmentation. the goal of this paper is to present an appropriate method for the segmentation of lines at intersections (x-junctions) and branches (t-junctions), which can be regarded as local regions where lines occur at multiple orientations. a novel representation called ¿orientation space¿ is proposed, which is derived by adding the orientation axis to the abscissa and the ordinate of the image. the orientation space representation is constructed by treating the orientation parameter, to which gabor filters can be tuned, as a continuous variable. the problem of segmenting lines at multiple orientations is dealt with by thresholding 3d imagesin the orientation space and then detecting the connected components therein. in this way, x-junctions and t-junctions can be separated effectively. curve grouping can also be accomplished. the segmentation of mathematically modeled x-, t-, and l-junctions is demonstrated and analyzed. the sensitivity limits of the method are also discussed. experimental results using both synthesized and real images show the method to be effective for junction segmentation and curve grouping.
competitive mixture of deformable models for pattern classification. following the success of applying deformable models to feature extraction, a natural next step is to apply such models to pattern classification. recently, we have cast a deformable model under a bayesian framework for classification, giving promising results. however, deformable model methods are computationally expensive due to the required iterative optimization process. the problem is even more severe when there are a large number of models (e.g., for character recognition), because each of them has to deform and match with the input data before a final classification can be derived. in this paper, we propose to combine the deformable models into a mixture, in which the individual models compete with each other to survive the matching process during classification. models that do not compete well are eliminated early, thus allowing substantial savings in computation. this process of competition- elimination has been applied to handwritten digit recognition in which significant speedup can be achieved without sacrificing recognition accuracy.
local blur estimation and super-resolution. until now, all super-resolution algorithms have presumed that the images were taken under the same illumination conditions. this paper introduces a new approach to super-resolution---based on edge models and a local blur estimate---which circumvents these difficulties. the paper presents the theory and the experimental results using the new approach.
a divide-and-conquer strategy in shape from shading problem. a divide-and-conquer strategy in shape from shading problem under fully perspective condition is proposed for the information recovery of book surfaces. the whole recovery process is composed of three sequential steps : preprocessing, apparent shape recovery, and ortho-image generation. pure shade images are extracted at preprocessing step by introducing phenomenological model of interreflection and by removing pigment parts from observed images. using existing invariances, equations of slope and that of ortho-image being explicit are derived from equation of shading and that of observation being implicit. recurrence relation is derived from definition of mean slope in discrete image. theoretically, it become possible to recover unique shape without iteration using derived equations in case of lambertian cylinder. however, a feed-back shape recovery process is implemented as practical algorithm in order to overcome self-shadows. results of simulations and real experiments show the properness and acceptability of the proposed strategy and implemented algorithms.
global minimum for active contour models: a minimal path approach. a new boundary detection approach for shape modeling is presented. it detects the global minimum of an active contour model&lsquo;s energy between two end points. initialization is made easier and the curve is not trapped at a local minimum by spurious edges. we modify the &ldquo;snake&rdquo; energy by including the internal regularization term in the external potential term. our method is based on finding a path of minimal length in a riemannian metric. we then make use of a new efficient numerical method to find this shortest path.it is shown that the proposed energy, though based only on a potential integrated along the curve, imposes a regularization effect like snakes. we explore the relation between the maximum curvature along the resulting contour and the potential generated from the image.the method is capable to close contours, given only one point on the objects&lsquo; boundary by using a topology-based saddle search routine.we show examples of our method applied to real aerial and medical images.
a space-sweep approach to true multi-image matching. the problem of determining feature correspondences across multiple views is considered. the term "true multi-image" matching is introduced to describe techniques that make full and efficient use of the geometric relationships between multiple images and the scene. a true multi-image technique must generalize to any number of images, be of linear algorithmic complexity in the number of images, and use all the images in an equal manner. a new space-sweep approach to true multi-image matching is presented that simultaneously determines 2d feature correspondences and the 3d positions of feature points in the scene. the method is based on the premise that areas of space where several viewing rays intersect are the likely locations of observed 3d scene features. it is shown that the intersections of viewing rays with a plane sweeping through space can be determined very efficiently, and a statistical model is developed to tell how likely it is that a given number of viewing rays will pass through an area of the plane by chance. the method is illustrated on a seven-image matching example from the aerial image domain. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
multi-image focus of attention for rapid site model construction. a multi-image focus of attention mechanism has been developed that can quickly distinguish raised objects like buildings from structured background clutter typical to many aerial image scenarios. the underlying approach is the space-sweep stereo method, in which features from multiple images are backprojected onto a virtual, horizontal plane that is methodically swept through the scene. backprojected gradient orientations from multiple images are highly correlated when they come from scene locations containing structural edges that are roughly horizontal, like building roofs and terrain; otherwise, they tend to be uniformly distributed. these observations are used to define a structural salience measure that can determine whether a given volume of space contains a statistically signijicant number of structural edges, without first pe$otrning precise reconstruction of those edges. the utility of structural salience for computing focus of attention regions is illustrated on sample data from ft.hood, texas.
face detection with information-based maximum discrimination. antonio j. colmenarez and thomas s. huang in this paper we present a visual learning technique that maximizes the discrimination between positive and negative examples in a training set. we demonstrate our technique in the context of face detection with complex background without color or motion information, which has proven to be a challenging problem. we use a family of discrete markov processes to model the face and background patterns and estimate the probability models using the data statistics. then, we convert the learning process into an optimization, selecting the markov process that optimizes the information-based discrimination between the two classes. the detection process is carried out by computing the likelihood ratio using the probability model obtained from the learning procedure. we show that because of the discrete nature of these models, the detection process is, by almost two orders of magnitude, less computationally expensive than neural network approaches. however, no improvement in terms of correct-answer/false-alarm tradeoff is achieved.
robust analysis of feature spaces: color image segmentation. a general technique for the recovery of significant image features is presented. the technique is based on the mean shift algorithm, a simple nonparametric procedure for estimating density gradients. drawbacks of the current methods (including robust clustering) are avoided. feature space of any nature can be processed, and as an example, color image segmentation is discussed. the segmentation is completely autonomous, only its class is chosen by the user. thus, the same program can produce a high quality edge image, or provide, by extracting all the significant colors, a preprocessor for content-based query systems. a 512/spl times/512 color image is analyzed in less than 10 seconds on a standard workstation. gray level images are handled as color images having only the lightness coordinate.
depth from scattering. light power is affected when it crosses the atmosphere; there is a simple, albeit non-linear, relationship between the radiance of an image at any given wavelength and the distance between object and viewer. this phenomenon is called atmospheric scattering and has been extensively studied by physicists and meterologists. we present the first analysis of this phenomenon from an image understanding perspective: we investigate a group of techniques for extraction of depth cues solely from the analysis of atmospheric scattering effects in images. depth from scattering techniques are discussed for indoor and outdoor environments, and experimental tests with real images are presented. we have found that depth cues in outdoor scenes can be recovered with surprising accuracy and can be used as an additional information source for autonomous vehicles.
scale-space vector fields for feature analysis. this paper describes a vectorial representation that can be used to assess the symmetry of objects in 2d images. the method exploits a magneto-static analogy. commencing from the gradient-field extracted from filtered grey-scale images we construct a vector-potential. our magneto-static analogy is that tangential gradient vectors represent the elements of a current distribution on the image plane. by embedding the image plane in an augmented 3-dimensional space, we compute the vector potential by performing volume integration over the current distribution. the associated magnetic field is computed by taking the curl of the vector-potential. the auxiliary spatial dimension provides a natural scale-space sampling of the generating current-distribution; as the height above the image plane is increased, so the volume over which averaging is effected also increases. we extract edge and symmetry lines through a topographic analysis of the vector-field at various heights above the image plane. symmetry axes are lines of where the curl of the vector-potential vanishes; at edges the divergence of the vector-potential vanishes.
multi-modal tracking of faces for video communications. this paper describes a system which uses multiple visual processes to detect and track faces for video compression and transmission. the system is based on an architecture in which a supervisor selects and activates visual processes in cyclic manner. control of visual processes is made possible by a confidence factor which accompanies each observation. fusion of results into a unified estimation for tracking is made possible by estimating a covariance matrix with each observation. visual processes for face tracking are described using blink detection, normalized color histogram matching, and cross correlation (ssd and ncc). ensembles of visual processes are organized into processing states so as to provide robust tracking. transition between states is determined by events detected by processes. the result of face detection is fed into recursive estimator (kalman filter). the output from the estimator drives a pd controller for a pan/tilt/zoom camera. the resulting system provides robust and precise tracking which operates continuously at approximately 20 images per second on a 150 megahertz computer work-station.
character extraction of license plates from video. in this paper, we present a new approach to extract characters on a license plate of a moving vehicle given a sequence of perspective distortion corrected license plate images. we model the extraction of characters as a markov random field (mrf). with the mrf modeling, the extraction of characters is formulated as the problem of maximizing the a posteriori probability based on given prior and observations. a genetic algorithm with local greedy mutation operator is employed to optimize the objective function. experiments and comparison study were conducted. it is shown that our approach provides better performance than other single frame methods.
hand segmentation using learning-based prediction and verification for hand sign recognition. this paper presents a prediction-and-verification segmentation scheme wing attention images from multiple fixations. a major advantage of this scheme is that it can handle a large number of different deformable objects presented in complex backgrounds. the scheme is also relatively efficient since the segmentation is guided by the past knowledge through a prediction-and-verification scheme. the system has been tested to segment hands in the sequences of intensity images, where each sequence represents a hand sign. the experimental result showed a 95% correct segmentation rate with a 3% false rejection rate.
reflectance and texture of real-world surfaces authors. in this work, we investigate the visual appearance of real-world surfaces and the dependence of appearance on imaging conditions. we present a brdf (bidirectional reflectance distribution function) database with reflectance measurements for over 60 different samples, each observed with over 200 different combinations of viewing and source directions. we fit the brdf measurements to two recent models to obtain a brdf parameter database. these brdf parameters can be directly used for both image analysis and image synthesis. finally, we present a btf (bidirectional texture function) database with image textures from over 60 different samples, each observed with over 200 different combinations of viewing and source directions. each of these unique databases has important implications for a variety of vision algorithms and each is made publicly available.
active intrinsic calibration using vanishing points. we propose a new method for the estimation of the intrinsic parameters of an active camera. during a fixed axis camera rotation every point is moving on a conic section. if the point used is a vanishing point the conic section is invariant to possible translations of the observer. given the rotation axis and the inter-frame correspondence of a set of parallel lines we are able to compute the intrinsic parameters without knowledge of the rotation angles. we propagate the error covariances and we remove the bias in the computation of the conic. we experimentally study the sensitivity of calibration to the amount of rotation and we compare our performance to the performance of a recent active calibration technique.
integrated person tracking using stereo, color, and pattern detection. we present an approach to real-time person tracking in crowded and/or unknown environments using integration of multiple visual modalities. we combine stereo, color, and face detection modules into a single robust system, and show an initial application in an interactive, face-responsive display. dense, real-time stereo processing is used to isolate users from other objects and people in the background. skin-hue classification identifies and tracks likely body parts within the silhouette of a user. face pattern detection discriminates and localizes the face within the identified body parts. faces and bodies of users are tracked over several temporal scales: short-term (user stays within the field of view), medium-term (user exits/reenters within minutes), and long term (user returns after hours or days). short-term tracking is performed using simple region position and size correspondences, while medium and long-term tracking are based on statistics of user appearance. we discuss the failure modes of each individual module, describe our integration method, and report results with the complete system in trials with thousands of users.
active face tracking and pose estimation in an interactive room. we demonstrate real-time face tracking and pose estimation in an unconstrained office environment with an active foveated camera. using vision routines previously implemented for an interactive environment, we determine the spatial location of a user's head and guide an active camera to obtain foveated images of the face. faces are analyzed using a set of eigenspaces indexed over both pose and world location. closed loop feedback from the estimated facial location is used to guide the camera when a face is present in the foveated view. our system can detect the head pose of an unconstrained user in real-time as he or she moves about an open room.
focus: searching for multi-colored objects in a diverse image database. we describe a new multi-phase, color-based image retrieval system, focus (fast object color-based query system), with an online user interface which is capable of identifying multi-colored query objects in an image in the presence of significant, interfering backgrounds. the query object may occur in arbitrary sizes, orientations and locations in the database images. the color features used to describe an image have been developed based on the need for speed in matching and ease of computation on complex images while maintaining the scale and rotation invariance properties. the first phase matches the color content of an image computed as the peaks in the color histogram of the image, with the query object colors using an efficient indexing mechanism. the second phase matches the spatial relationships between color regions in the image with the query using a spatial proximity graph (spg) structure designed for the purpose. the method is fast and has low storage overhead. test results with multi-colored query objects from artificial and natural domains show that focus is quite effective in handling interfering backgrounds and large variations in scale. the experimental results on a database of diverse images highlights the capabilities of the system.
the representation and recognition of human movement using temporal templates. a new view-based approach to the representation and recognition of action is presented. the basis of the representation is a temporal template -- a static vector-image where the vector value at each point is a function of the motion properties at the corresponding spatial location in an image sequence. using 18 aerobics exercises as a test domain, we explore the representational power of a simple, two component version of the templates: the first value is a binary value indicating the presence of motion, and the second value is a function of the recency of motion in a sequence. we then develop a recognition method which matches these temporal templates against stored instances of views of known actions. the method automatically performs temporal segmentation, is invariant to linear changes in speed, and runs in real-time on a standard platform. we recently incorporated this technique into the kidsroom: an interactive, narrative play-space for children.
the integration of optical flow and deformable models with applications to human face shape and motion estimation. we present a formal methodology for the integration of optical flow and deformable models. the optical flow constraint equation provides a non-holonomic constraint on the motion of the deformable model. in this augmented system, forces computed from edges and optical flow are used simultaneously. when this dynamic system is solved, a model-based least-squares solution for the optical flow is obtained and improved estimation results are achieved. the use of a 3-d model reduces or eliminates problems associated with optical flow computation. this approach instantiates a general methodology for treating visual cues as constraints on deformable models. we apply this framework to human face shape and motion estimation. our 3-d deformable face model uses a small number of parameters to describe a rich variety of face shapes and facial expressions. we present experiments in extracting the shape and motion of a face from image sequences.
the integration of optical flow and deformable models with applications to human face shape and motion estimation. we present a formal methodology for the integration of optical flow and deformable models. the optical flow constraint equation provides a non-holonomic constraint on the motion of the deformable model. in this augmented system, forces computed from edges and optical flow are used simultaneously. when this dynamic system is solved, a model-based least-squares solution for the optical flow is obtained and improved estimation results are achieved. the use of a 3-d model reduces or eliminates problems associated with optical flow computation. this approach instantiates a general methodology for treating visual cues as constraints on deformable models. we apply this framework to human face shape and motion estimation. our 3-d deformable face model uses a small number of parameters to describe a rich variety of face shapes and facial expressions. we present experiments in extracting the shape and motion of a face from image sequences.
from projective to euclidean reconstruction. to make a euclidean reconstruction of the world seen through a stereo rig, we can either use a calibration grid, and the results will rely on the precision of the grid and the extracted points of interest, or use self-calibration. past work on self-calibration is focussed on the use of only one camera, and gives sometimes very unstable results. in this paper, we use a stereo rig which is supposed to be weakly calibrated using a method such as the one described in deriche et al. (1994). then, by matching two sets of points of the same scene reconstructed from different points of view, we try to find both the homography that maps the projective reconstruction to the euclidean space and the displacement from the first set of points to the second set of points. we present results of the euclidean reconstruction of a whole object from uncalibrated cameras using the method proposed here.
sparse representations for image decomposition with occlusions. we study the problem of how to detect "interesting objects'' appeared in a given image, i. our approach is to treat it as a function approximation problem based on an over-redundant basis, and also account for occlusions, where the basis superposition principle is no longer valid. since the basis (a library of image templates) is over-redundant, there are infinitely many ways to decompose i. we are motivated to select a sparse/compact representation of i, and to account for occlusions and noise. we then study a greedy and iterative "weighted lp matching pursuit" strategy, with 0
an mimd computing platform for a hierarchical foveal machine vision system. a multiple instruction multiple data (mimd) parallel computing platform built upon a network of tms320c40/44s (c40/c44) for real-time image processing of a hierarchical foveal machine vision (hfmv) system is described in this paper. the architecture of the system, the parallel algorithm development environment, and strategies to map tasks into the computing platform are described. the platform supports both static and dynamic computing resource allocation. the performance of the computing platform is illustrated by examples.
appearance matching of occluded objects using coarse-to-fine adaptive masks. in this paper, we discuss an appearance matching technique for the interpretation of color scenes containing occluded objects. dealing with occlusions is very difficult, and we have explored the use of an iterative, coarse-to-fine correlation-based method that uses hypothesized occlusion events to modify the scene-to-template similarity measure at run-time. specifically, a binary mask is used to adaptively exclude regions of the template image from the correlation computation. at each iteration, these masks are adjusted based on higher resolution scene data and the occluding interactions between multiple object hypotheses. we present results which demonstrate the technique is reasonably robust over a large database of color test scenes containing objects at a variety of scales, and tolerates minor object rotations and global illumination variations.
detecting binocular half-occlusions: empirical comparisons of four approaches. binocular half-occlusion points are those that are visible in one of the two views provided by a binocular imaging system. due to their importance in binocular matching as well as, subsequent interpretation tasks, a number of approaches have been developed for dealing with such points. in the current paper, we consider five methods that explicitly detect half-occlusions and report on a more uniform comparison than has previously been performed. taking a disparity image and its associated match goodness image as input, we generate images that show the half-occluded points in the underlying scene. we quantitatively and qualitatively compare these methods under a variety of conditions.
image editing in the contour domain. image editing systems are essentially pixel-based. in this paper, we propose a novel method for image editing in which the primitive working unit is not a pixel but an edge. the feasibility of this proposal is suggested by recent work showing that a gray-scale image can be accurately represented by its edge map if a suitable edge model and scale selection method are employed [1]. in particular, an efficient algorithm has been reported to invert such an edge representation to yield a high-fidelity reconstruction of the original image [2], [3]. we have combined these algorithms together with an efficient method for contour grouping and an intuitive user interface to allow users to perform image editing operations (crop, paste, delete) directly in the contour domain. experimental results suggest that this novel combination of vision algorithms may increase the efficiency of certain classes of image editing operations.
a robust and convergent iterative approach for determining the dominant plane from two views without correspondence and calibration. a robust, iterative approach is introduced for finding the dominant plane in a scene using binocular vision. neither camera calibration nor stereo correspondence is required. recently cohen formalized a framework guaranteeing (local) convergence of iterative two-step methods. in this paper, the framework is adopted, with a global step using tentative matches to estimate the planar projectivity, and a local step attempting to solve the stereo correspondence. a detected point in the first image is matched to an auxiliary point in the second image, on the line joining the transformed first image point, and its closest detected second image point. convergence is assured, while achieving robustness to both mismatching and non-coplanar points.
space scale localization, blur, and contour-based image coding. we have recently proposed a scale-adaptive algorithm for reliable edge detection and blur estimation. the algorithm produces a contour code which consists of estimates of position, brightness, contrast and blur for each edge point in the image. here we address two questions: 1. can scale adaptation be used to achieve precise localization of blurred edges? 2. how much of the perceptual content of an image is carried by the 1-d contour code? we report an efficient algorithm for subpixel localization, and show that local scale control allows excellent precision even for highly blurred edges. we further show how local scale control can quantitatively account for human visual acuity of blurred edge stimuli. to address the question of perceptual content, we report an algorithm for inverting the contour code to reconstruct an estimate of the original image. while reconstruction based on edge brightness and contrast alone introduces significant artifact, restitution of the local blur signal is shown to produce perceptually accurate reconstructions.
body plans. this paper describes a representation for people and animals, called a body plan, which is adapted to segmentation and to recognition in complex environments. the representation is an organized collection of grouping hints obtained from a combination of constraints on color and texture and constraints on geometric properties such as the structure of individual parts and the relationships between parts. body plans can be learned from image data, using established statistical learning techniques. the approach is illustrated with two examples of programs that successfully use body plans for recognition: one example involves determining whether a picture contains a scantily clad human, using a body plan built by hand; the other involves determining whether a picture contains a horse, using a body plan learned from image data. in both cases, the system demonstrates excellent performance on large, uncontrolled test sets and very large and diverse control sets.
learning bilinear models for two-factor problems in vision. in many vision problems, we want to infer two (or more) hidden factors which interact to produce our observations. we may want to disentangle illuminant and object colors in color constancy; rendering conditions from surface shape in shape-from-shading; face identity and head pose in face recognition; or font and letter class in character recognition. we refer to these two factors generically as ``style'' and ``content''.bilinear models offer a powerful framework for extracting the two-factor structure of a set of observations, and are familiar in computational vision from several well-known lines of research. this paper shows how bilinear models can be used to learn the style-content structure of a pattern analysis or synthesis problem, which can then be generalized to solve related tasks using different styles and/or content. we focus on three tasks: extrapolating the style of data to unseen content classes, classifying data with known content under a novel style, and translating data from novel content classes and style to a known style or content. we show examples from color constancy, face pose estimation, shape-from-shading, typography and speech.
a robust clustering algorithm based on competitive agglomeration and soft rejection of outliers. we present a new clustering algorithm that addresses two major issues associated with conventional partitional clustering: the difficulty in determining the number of clusters, and the sensitivity to noise and outliers. the proposed algorithm determines the number of clusters by a process of competitive agglomeration. noise immunity is achieved by integrating concepts from robust statistics into the algorithm. the proposed approach can incorporate different distance measures in the objective function to find an unknown number of clusters of various types including lines, planes and surfaces.
the use of hybrid models to recover cardiac wall motion in tagged mr images. we present a new algorithm for the automatic recovery of tag grid-line intersections in tagged mr images of the left ventricle of the heart. our method uses an active spring mesh to capture local properties of the motion and a global motion model to capture the global coherence of the motion. we recover the global component of the motion using robust estimation. different motion models have been developed for short and long axis views of the heart. the algorithm has been tested on healthy and pathological data.
efficient stereo with multiple windowing. we present a new, efficient stereo algorithm addressing robust disparity estimation in the presence of occlusions. the algorithm is an adaptive, multi-window scheme using left-right consistency to compute disparity and its associated uncertainty. we demonstrate and discuss performances with both synthetic and real stereo pairs, and show how our results improve on those of closely related techniques for both robustness and efficiency.
efficient regularity-based grouping. this paper summarizes a novel logic-based approach to grouping and perceptual organization (presented more thoroughly in \cite{feldman_ci}), and presents novel efficient methods for computing interpretations in this framework. grouping interpretations are first defined as logical structures, built out of atomic premises (``regularities'') that are derived from considerations of non-accidentalness. these interpretations can then be partially ordered by their degree of regularity or constraint (measured numerically by their {\it codimension\/}). the genericity constraint---the principle that interpretations should minimize coincidences in the observed configuration---dictates that the preferred interpretation will be the minimum in this partial order, i.e. the interpretation with {\it maximum codimension.\/} the preferred interpretation, called the {\it qualitative parse\/}, corresponds neatly to the interpretation intuitively preferred by human observers. as a side-effect, the ``most salient'' or most structured part of the scene can be identified, as the highest-codimension subtree of the qualitative parse. an efficient ($o(n^2)$) method for computing the maximum codimension interpretation is presented, along with examples.
adaptive b-splines and boundary estimation. this paper describes a boundary estimation scheme based on a new adaptive approach to b-spline curve fitting. the number of control points of the spline, their locations, and the observation parameters, are all considered unknown. the optimal number of control points is estimated via a new minimum description length (mdl) type criterion. the result is an adaptive parametrically deformable contour which also estimates the observation model parameters. experiments on synthetic and real (medical) images confirm the adequacy and good performance of the approach.
the confounding of translation and rotation in reconstruction from multiple views. if 3d rigid motion is estimated with some error a distorted version of the scene structure will in turn be computed. of computational interest are these regions in space where the distortions are such that the depths become negative, because in order to be visible the scene has to lie in front of the image. the stability analysis for the structure-from-motion problem presented in this paper investigates the optimal relationship between the errors in the estimated translational and rotational parameters of a rigid motion, that results in the estimation of a minimum number of negative depth values. the input used is the value of the flow along some direction, which is more general than optic flow or correspondence. for a planar retina it is shown that the optimal configuration is achieved when the projections of the translational and rotational errors on the image plane are perpendicular. furthermore, the projection of the actual and the estimated translation lie on a line passing through the image center. for a spherical retina given a rotational error, the optimal translation is the correct one, while given a translational error. the optimal rotational error is normal to the translational one at an equal distance from the real and estimated translations. the proofs, besides illuminating the confounding of translation and rotation in structure from motion, have an important application to ecological optics, explaining differences of planar and spherical eye or camera designs in motion and shape estimation.
efficient approximation of range images through data-dependent adaptive triangulations. this paper presents an efficient algorithm for generating adaptive triangular meshes from dense range images. the proposed technique consists of two stages. first, a quadrilateral mesh is generated from the given range image. the points of this mesh adapt to the surface shapes represented in the range image by grouping in areas of high curvature and dispersing in low-variation regions. the second stage splits each quadrilateral cell obtained before into two triangles. between the two possible flips, it is chosen the one whose diagonal' s direction is closest to the orientation of the discontinuities present in that cell. both stages avoid costly iterative optimization techniques. results with real range images are presented. they show low cpu times and accurate triangular approximations of the given images.
3-d model-based tracking of humans in action: a multi-view approach. we present a vision system for the 3-d model-based tracking of unconstrained human movement. using image sequences acquired simultaneously from multiple views, we recover the 3-d body pose at each time instant without the use of markers. the pose-recovery problem is formulated as a search problem and entails finding the pose parameters of a graphical human model whose synthesized appearance is most similar to the actual appearance of the real human in the multi-view images. the models used for this purpose are acquired from the images. we use a decomposition approach and a best-first technique to search through the high dimensional pose parameter space. a robust variant of chamfer matching is used as a fast similarity measure between synthesized and real edge images. we present initial tracking results from a large new humans-in-action (hia) database containing more than 2500 frames in each of four orthogonal views. they contain subjects involved in a variety of activities, of various degrees of complexity, ranging from the more simple one-person hand waving to the challenging two-person close interaction in the argentine tango.
color-based tracking of heads and other mobile objects at video frame rates. we develop a simple and very fast method for object tracking based exclusively on color information in digitized video images. running on a silicon graphics r4600 indy system with an indycam, our algorithm is capable of simultaneously tracking objects at full frame size ($640\times480$ pixels) and video frame rate (30 fps). robustness with respect to occlusion is achieved via an explicit hypothesis-tree model of the occlusion process. we demonstrate the efficacy of our technique in the challenging task of tracking people, especially tracking human heads and hands.
visual organization for figure/ground separation. a common factor in all illusory contour figures is the perception of a surface occluding part of a background. in our previous work we have shown that by detecting junctions and assigning a proper set of hypothesis at each junction, we could diffuse this information and obtain surface reconstructions where the surface boundaries represented illusory contours. amodal completions emerge at the overlapping surfaces. we here address the problem of selecting the best image organization (set of hypothesis). we propose two optimization criteria, one based on a coherence measure between pairs of junctions (correlation between the diffusion of each pair) and another one based on an entropy measure (sharpness of the reconstruction). we show their similarity and a statistical physics approach to select the best organization. the experiments suggest that despite the large number of possible organizations our approach may take a few steps to select the best organization (starting from random organizations).
a region-level graph labeling approach to motion-based segmentation. this paper deals with the problem of motion-based segmentation of image sequences. such partitions are multiple-purpose in dynamic scene analysis. we first extract a texture-based partition using an unsupervised mrf approach. the regions obtained are then grouped according to a motion-based criterion. this grouping process relies on two motion estimation techniques and exploits contextual information between regions. in contrast with clustering techniques, region grouping is formalized as a motion-based graph labeling process, within a markovian framework. results on real-world image sequences are shown and validate the proposed method.
combining region splitting and edge detection through guided delaunay image subdivision. in this paper, an adaptive split-and-merge segmentation method is proposed. the splitting phase of the algorithm employs the incremental delaunay triangulation competent of forming grid edges of arbitrary orientation and position. the tessellation grid, defined by the delaunay triangulation, is adjusted to the semantics of the image data by combining similarity and difference information among pixels. experimental results on synthetic images show that the method is robust to different object edge orientations, partially weak object edges and very noisy homogeneous regions. experiments on a real image indicate that the method yields good segmentation results even when there is a quadratic sloping of intensities particularly suited for segmenting natural scenes of man-made objects.
target detection in foveal atr systems. automatic target recognition (atr) applications require simultaneously a wide field of view (fov) for better detection and situation awareness, high resolution for target recognition and threat assessment, and high frame rate for detecting brief events and disambiguating frame-to-frame correlation. uniformly sampling the entire fov at recognition resolution is simply wasteful in atr scenarios with localized regions of interest (rois). foveal data acquisition with space-variant sampling and context- sensitive sensor articulation is highly optimized for active atr applications. we propose a multiscale local zernike filter-based front end target detection technique for a commercially feasible foveal sensor topology with piecewise constant resolution profile. anisotropic heat diffusion is employed for preprocessing of the foveal data. expansion template matching is used to derive a detection filter that optimizes the discriminant signal-to-noise ratio (snr). results are presented with simulated foveal imagery derived from real uniform acuity flir data.
a formal classification of 3d medial axis points and their local geometry. abstract--this paper proposes a novel hypergraph skeletal representation for 3d shape based on a formal derivation ofthe generic structure of its medial axis. by classifying each skeletal point by its order of contact, we show that, generically, the medial axis consists of five types of points, which are then organized into sheets, curves, and points: 1) sheets (manifolds with boundary) which are the locus of bitangent spheres with regular tangency a_1^2 (a_k^n notation means n distinct k{\hbox{-}}{\rm{fold}} tangencies of the sphere of contact, as explained in the text); two types of curves, 2) the intersection curve of three sheets and the locus of centers of tritangent spheres, a_1^3, and 3) the boundary of sheets, which are the locus of centers of spheres whose radius equals the larger principal curvature, i.e., higher order contact a_3 points; and two types of points, 4) centers of quad-tangent spheres, a_1^4, and 5) centers of spheres with one regular tangency and one higher order tangency, a_1a_3. the geometry of the 3d medial axis thus consists of sheets (a_1^2) bounded by one type of curve (a_3) on their free end, which corresponds to ridges on the surface, and attached to two other sheets at another type of curve (a_1^3), which support a generalized cylinder description. the a_3 curves can only end in a_1a_3 points where they must meet an a_1^3 curve. the a_1^3 curves meet together in fours at an a_1^4 point. this formal result leads to a compact representation for 3d shape, referred to as the medial axis hypergraph representation consisting of nodes (a_1^4 and a_1 a_3 points), links between pairs of nodes (a_1^3 and a_3 curves) and hyperlinks between groups of links (a_1^2 sheets). the description of the local geometry at nodes by itself is sufficient to capture qualitative aspects of shapes, in analogy to 2d. we derive a pointwise reconstruction formula to reconstruct a surface from this medial axis hypergraph together with the radius function. thus, this information completely characterizes 3d shape and lays the theoretical foundation for its use in recognition, morphing, design, and manipulation of shapes.
on the intrinsic reconstruction of shape from its symmetries. the main question we address is: what is the minimal information required to generate closed, nonintersecting planar boundaries? for this paper, we restrict ¿shape¿ to this meaning. more precisely, we examine whether the medial axis, together with dynamics, can serve as a language to design shapes and to effect shape changes, e.g., for modeling, to generate a morph sequence, etc. we represent the medial axis together with a direction of flow along the axis as the shock graph and examine the reconstruction of shape along each of the three types of medial axis points, (labeled a_1^2, a_1^3, a_3; see below for the a notation) and the associated six types of shock points. first, we show that the tangent and curvature of the medial axis and the speed and acceleration of the shock with respect to time of propagation, i.e., first and second order geometric and dynamic properties, are sufficient to determine the boundary tangent and curvature at corresponding points of the boundary. this implies that a rather coarse sampling of the symmetry axis, its tangent, curvature, speed, and acceleration is sufficient to regenerate accurately a local neighborhood of shape at regular axis points (a_1^2). we also show how higher order differential properties of the axis can be related to the higher-order differential properties of the boundary of the same order. second, we examine the reconstruction of shape at branch points (a_1^3) where three regular branches are joined. we show that the three pairs of geometry (that is, curvature) and dynamics (that is, acceleration) must satisfy certain constraints. finally, we derive similar results for the end points of shock branches (a_3 points). these formulas completely specify the local reconstruction of a shape from its shock-graph or medial axis and the conditions required to form a coherent shape from the medial axis.
histogram preserving image transformations. histograms are used to analyze and index images. they have been found experimentally to have low sensitivity to certain types of image morphisms, for example, viewpoint changes and object deformations. the precise effect of these image morphisms on the histogram, however, has not been studied. in this work we derive the complete class of local transformations that preserve or scale the magnitude of the histogram of all images. we also derive a more general class of local transformations that preserve the histogram relative to a particular image. to achieve this, the transformations are represented as solutions to families of vector fields acting on the image. the local effect of fixed points of the fields on the histograms is also analyzed. the analytical results are verified with several examples. we also discuss several applications and the significance of these transformations for histogram indexing.
projective registration with difference decomposition. current methods for registering image regions perform well for simple transformations or large image regions. the author presents a new method that is better able to handle small image regions as they deform with nonlinear transformations. he introduces difference decomposition, a novel approach to solving the registration problem. the method is a generalization of previous methods and can better handle nonlinear transforms. although the methods are general, he focuses on projective transformations and introduces piecewise-projective transformations for modeling the motions of non-planar objects. he concludes with examples from a prototype implementation.
real-time tracking of image regions with changes in geometry and illumination. historically, ssd or correlation-based visual tracking algorithms have been sensitive to changes in illumination and shading across the target region. this paper describes methods for implementing ssd tracking that is both insensitive to illumination variations and computationally efficient. we first describe a vector-space formulation of the tracking problem, showing how to recover geometric deformations. we then show that the same vector space formulation can be used to account for changes in illumination. we combine geometry and illumination into an algorithm that tracks large image regions on live video sequences using no more computation than would be required to trade with no accommodation for illumination changes. we present experimental results which compare the performance of ssd tracking with and without illumination compensation.
motion of disturbances: detection and tracking of multi-body non-rigid motion. we present a new approach to the tracking of very non rigid patterns of motion, such as water flowing down a stream. the algorithm is based on a "disturbance map," which is obtained by linearly subtracting the temporal average of the previous frames from the new frame. every local motion creates a disturbance having the form of a wave, with a "head" at the present position of the motion and a historical "tail" that indicates the previous locations of that motion. these disturbances serve as loci of attraction for "tracking particles" that are scattered throughout the image. the algorithm is very fast and can be performed in real time. we provide excellent tracking results on various complex sequences, using both stabilized and moving cameras, showing: a busy ant column, waterfalls, rapids and flowing streams, shoppers in a mall, and cars in a traffic intersection.
rectified catadioptric stereo sensors. it has been previously shown how mirrors can be used to capture stereo images with a single camera, an approach termed catadioptric stereo. in this paper, we present novel catadioptric sensors that use mirrors to produce rectified stereo images. the scan-line correspondence of these images benefits real-time stereo by avoiding the computational cost and image degradation due to resampling when rectification is performed after image capture. first, we develop a theory which determines the number of mirrors that must be used and the constraints on those mirrors that must be satisfied to obtain rectified stereo images with a single camera. then, we discuss in detail the use of both one and three mirrors. in addition, we show how the mirrors should be placed in order to minimize sensor size for a given baseline, an important design consideration. in order to understand the feasibility of building these sensors, we analyze rectification errors due to misplacement of the camera with respect to the mirrors.
/spl lambda//spl tau/-space representation of images and generalized edge detector. an image clad surface representation based on regularization theory is introduced in this paper. this representation is based on a hybrid model derived from the physical membrane and plate models. the representation, called the /spl lambda//spl tau/-representation, has two dimensions; one dimension represents smoothness or scale while the other represents the continuity of the image or surface. it contains images/surfaces sampled both in scale space and the weighted sobolev space of continuous functions. thus, this new representation can be viewed as an extension of the well-known scale space representation. we have experimentally shown that the proposed hybrid model results in improved results compared to the two extreme constituent model, i.e., the membrane and the plate models. based on this hybrid model, a generalized edge detector (ged) which encompasses most of the well-known edge detectors under a common framework is developed. the existing edge detectors can be obtained from the generalized edge detector by simply specifying the valves of two parameters, one of which controls the shape of the filter (/spl tau/) and the other controls the scale of the filter (/spl lambda/). by sweeping the valves of these two parameters continuously, one can generate an edge representation in the /spl lambda//spl tau/ space, which is very useful for developing a goal-directed edge detection scheme for a specific task. the proposed representation and the edge detector have been evaluated qualitatively and quantitatively on several different types of image data such as intensity, range and stereo images.
reconstruction of a scene with multiple linearly moving objects. in this paper we describe an algorithm to recover the scene structure, the trajectories of the moving objects and the camera motion simultaneously given a monocular image sequence. the number of the moving objects is automatically detected without prior motion segmentation. assuming that the objects are moving linearly with constant speeds, we propose a unified geometrical representation of the static scene and the moving objects. this representation enables the embedding of the motion constraints into the scene structure, which leads to a factorization-based algorithm. we also discuss solutions to the degenerate cases which can be automatically detected by the algorithm. extension of the algorithm to weak perspective projections is presented as well. experimental results on synthetic and real images show that the algorithm is reliable under noise.
graph matching by graduated assignment. a new algorithm for graph matching, which uses graduated assignment is presented, along with experimental results demonstrating large improvements in speed and accuracy over previous techniques. the softassign, a novel constraint satisfaction technique, is applied to a new graph matching energy function that uses a robust, sparse distance measure between the links of the two graphs. the softassign, which has emerged out of the neural network/statistical physics framework enforces two-way (assignment) constraints without the use of penalty terms. the algorithm's low order computational complexity [0(lm), where l and m are the number of links in the two graphs] compares favorably with most competing approaches. the method, not restricted to any special class of graph, is applied to subgraph isomorphism, weighted graph matching, and attributed relational graph matching. experiments on graphs generated from images and on randomly generated graphs, including benchmarks against a relation labeling algorithm and an algorithm employing potts glass dynamics are reported. over twenty-five thousand experiments were conducted. no comparable results have been reported by any other graph matching algorithm before in the research literature.
mirror and point symmetry under perspective skewing. over recent years, symmetry research has shifted from the detection of affinely to perspectively skewed mirror symmetry. also, links between invariance research and symmetry-specific geometric constraints have been established. the paper aims to contribute to both strands. several sets of symmetry specific invariants are derived, that can be used in different situations, depending on the a priori assumptions made. it is also argued that all the results directly apply to the case of perspectively skewed point symmetry.
lip reading from scale-space measurements. systems that attempt to recover the spoken word from image sequences usually require complicated models of the mouth and its motions. here we describe a new approach based on a fast mathematical morphology transform called the sieve. we form statistics of scale measurements in one and two dimensions and these are used as a feature vector for standard hidden markov models (hmms).
hierarchical recognition of articulated objects from single perspective views. this paper presents an approach to the recognition of articulated 3d objects in monocular video images. a hierarchical object representation models objects as a composition of rigid components which are explicitly connected by specific kinematic constraints, e.g., rotational and/or translational joints. the recognition task follows this tree-like structure by first estimating the 3d pose of the static component (root) and afterwards determining the relative 3d pose of the remaining components recursively. this method limits the search space for the actual correspondences between image and model features and copes with the problem of self-occlusion. experiments in the context of autonomous, mobile robots show the practicability of this approach.
computing optical flow with physical models of brightness variation. although most optical flow techniques presume brightness constancy, it is well-known that this constraint is often violated, producing poor estimates of image motion. this paper describes a generalized formulation of optical flow estimation based on models of brightness variations that are caused by time-dependent physical processes. these include changing surface orientation with respect to a directional illuminant, motion of the illuminant, and physical models of heat transport in infrared images. with these models, we simultaneously estimate the 2d image motion and the relevant physical parameters of the brightness change model. the estimation problem is formulated using total least squares (tls), with confidence bounds on the parameters. experiments in four domains, with both synthetic and natural inputs, show how this formulation produces superior estimates of the 2d image motion.
inference of segmented, volumetric shape from three intensity images. we present a method to infer segmented and full volumetric descriptions of objects from intensity images. we use three weakly calibrated images from closely spaced viewpoints as input. deriving full volumetric descriptions requires the development of robust inference rules. the inference rules are based on local properties of generalized cylinders (gcs). we first detect groups in each image based on proximity, parallelism and symmetry. the groups in the three images are matched and their contours are labelled as "true" and "limb" edges. we use the information about groups and the label associated with their contours to recover visible surfaces and their surface axes. to extract the complete volume in terms of a gc, we need to infer the gc axis, its cross section and the scaling function. the properties of straight and curved axis generalized cylinders are used locally on the visible surfaces to obtain the gc axis. the cross section is recovered if seen in the images, else it is inferred using the visible surfaces and gc properties. we consider groups with true edges, limb edges or a combination of both. the final descriptions are volumetric and in terms of parts. sometimes, when not enough information is present to make volumetric inferences, the descriptions remain at the surface level. we demonstrate results on real images of moderately complex objects with texture and shadows.
object-based video indexing for virtual studio productions. this paper introduces an object-based approach for temporal video partitioning and content-based indexing, where the basic indexing unit is ``lifespan of a video object," rather than a ``camera shot" or ``story unit." we propose a system to extract content-based features of video objects (vos), based on a compact 2d triangular mesh representation of them. an adaptive mesh-based video object tracking scheme is then employed to compute the motion trajectori of all node points. a set of ``key snapshots" which constitute a visual summary of the lifespan of the object are automatically selected using motion and shape information. the system provides direct access to the vos and gives the functionalities such as object-based search, manipulation, animation, and tracking.
using physics-based invariant representations for the recognition of regions in multispectral satellite images. we present a set of algorithms and a search strategy for the robust content- based retrieval of multispectral satellite images. since the property of interest in these images is usually the physical characteristics of ground cover, we use representations and methods that are invariant to illumination and atmospheric conditions. the representations and algorithms are derived for this application from a physical model for the formation of multispectral satellite images. the use of several representations and algorithms is necessary to interpret the diversity of physical and geometric structure in these images. algorithms are used that exploit multispectral distributions, multispectral spatial structure, and labeled classes. the performance of the system is demonstrated on a large set of multispectral satellite images taken over different areas of the united states under different illumination and atmospheric conditions.
comparison of edge detectors: a methodology and initial study. because of the difficulty of obtaining ground truth for real images, the traditional technique for comparing low-level vision algorithms is to present image results, side by side, and to let the reader subjectively judge the quality. this is not a scientifically satisfactory strategy. however, human rating experiments can be done in a more rigorous manner, to provide useful quantitative conclusions. we present a paradigm based on experimental psychology and statistics, in which humans rate the output of low level vision algorithms. we demonstrate the proposed experimental strategy by comparing four well known edge detectors: canny, nalwa-binford, sarkar-boyer, and sobel. we answer the following questions: is there a statistically significant difference in edge detector outputs as perceived by humans? do the edge detection results of an operator vary significantly with the choice of its parameters? for each detector, is it possible to choose a single set of optimal parameters for all the images without significantly affecting the edge output quality? does an edge detector produce edges of the same quality for all images, or does the edge quality vary with the image?
a four-step camera calibration procedure with implicit image correction. in geometrical camera calibration the objective is to determine a set of camera parameters that describe the mapping between 3-d reference coordinates and 2-d image coordinates. various methods for camera calibration can be found from the literature. however, surprisingly little attention has been paid to the whole calibration procedure, i.e., control point extraction from images, model fitting, image correction, and errors originating in these stages. the main interest has been in model fitting, although the other stages are also important. in this paper we present a four-step calibration procedure that is an extension to the two-step method. there is an additional step to compensate for distortion caused by circular features, and a step for correcting the distorted image coordinates. the image correction is performed with an empirical inverse model that accurately compensates for radial and tangential distortions. finally, a linear method for solving the parameters of the inverse model is presented.
tracking non-rigid, moving objects based on color cluster flow. in this contribution we present an algorithm for tracking non-rigid, moving objects in a sequence of colored images, which were recorded by a non-stationary camera. the application background is vision-based driving assistance in the inner city. in an initial step, object parts are determined by a divisive clustering algorithm, which is applied to all pixels in the first image of the sequence. the feature space is defined by the color and position of a pixel. for each new image the clusters of the previous image are adapted iteratively by a parallel k-means clustering algorithm. instead of tracking single points, edges, or areas over a sequence of images, only the centroids of the clusters are tracked. the proposed method remarkably simplifies the correspondence problem and also ensures a robust tracking behaviour.
canonical decomposition of steerable functions. this paper describes a general mathematical formulation for the problem of constructing steerable functions. the formulation is based on lie group theory and is thus applicable to transformations which are lie groups, such as, rotation, translation, scaling, and affine transformation. for one-parameter and abelian multi-parameter lie transformation groups, a canonical decomposition of all possible steerable functions, derived using the jordan decomposition of matrices, is developed. it is shown that any steerable function under lie transformation groups can be described using this decomposition. finally, a catalog of steerable functions for several common multi-parameter image transformation groups is also provided.
invariant histograms and deformable template matching for sar target recognition. recognizing a target in synthetic-aperture radar (sar) images is an important, yet challenging, application of the model-based vision technique. this paper describes a model-based sar recognition system based on invariant histograms and deformable template matching techniques. an invariant histogram is a histogram of invariant values defined by geometric features such as points and lines in sar images. although a few invariants are sufficient to recognize a target, we use a histogram of all invariant values given by all possible target feature pairs. this redundant histogram enables robust recognition under severe occlusions typical in sar recognition scenarios. multi-step deformable template matching examines the existence of an object by superimposing templates over potential energy field generated from images or primitive features. it determines the template configuration which has the minimum deformation and the best alignment of the template with features. the deformability of the template absorbs the instability of sar features. we have implemented the system and evaluated the system performance using hybrid sar images, generated from synthesized model signatures and real sar background signatures.
recognizing 3d objects by generating random actions. this paper presents a formal model of an active recognition system that can be programmed by learning. at each time step the system decides between producing an action to generate new data and stopping to issue the name of the object observed. the actions can be directed either towards the external environment or towards the internal perceptual system of the agent. the decision strategy is based on a quantitative evaluation of the system learning experience. the problem studied is the recognition of chess pieces using a moving camera and a multiscale feature detector. the recognition is difficult because the objects are complex -- neither polyhedral nor smooth -- and rather similar between classes, especially in certain view configurations. the system uses the information obtained by observing internal state transitions when the camera is moved or when the feature detector scale is changed. a simulation of the agent and the environment is used for experimental measures of the model performances.
real-time closed-world tracking. a real-time tracking algorithm that uses contextual information is described. the method is capable of simultaneously tracking multiple, non-rigid objects when erratic movement and object collisions are common. a closed-world assumption is used to adaptively select and weight image features used for correspondence. results of algorithm testing and the limitations of the method are discussed. the algorithm has been used to track children in an interactive, narrative playspace.
euclidean reconstruction from image sequences with varying and unknown focal length and principal point. in this paper the special case of reconstruction from image sequences taken by cameras with skew equal to 0 and aspect ratio equal to has been treated. these type of cameras, here called cameras with euclidean image planes, represent rigid projections where neither the principal point nor the focal length is known. it will be shown that it is possible to reconstruct an unknown object from images taken by a camera with euclidean image plane up to similarity transformations, i.e., euclidean transformations plus changes in the global scale. an algorithm, using bundle adjustment techniques, has been implemented. the performance of the algorithm is shown on simulated data.
catadioptric sensors that approximate wide-angle perspective projections. we present two families of reflective surfaces that are capable of providing a wide field of view, and yet still approximate a perspective projection to a high degree. these surfaces are derived by considering a plane perpendicular to the axis of a surface of revolution and finding the equations governing the distortion of the image of the plane in this surface.we then view this relation as a differential equation and prescribe the distortion term to be linear. by choosing appropriate initial conditions for the differential equation and solving it numerically, we derive the surface shape and obtain a precise estimate as to what degree the resulting sensor can approximate a perspective projection. thus, these surfaces act as computational sensors, allowing for a wide-angle perspective view of a scene without processing the image in software. the applications of such a sensor should be numerous, including surveillance, robotics and traditional photography.recently, many researchers in the robotics and vision community have begun to consider visual sensors that are able to obtain wide fields of view. such devices are the natural solution to various difficulties encountered with conventional imaging systems.the two most common means of obtaining wide fields of view are fish-eye lenses and reflective surfaces, also known as catoptrics. when catoptrics are combined with conventional lens systems, known as dioptrics, the resulting sensors are known as catadioptrics. the possible uses of these systems include applications such as robot control and surveillance. in this paper, we will consider only catadioptri-based sensors. often such systems consist of a camera pointing at a convex mirror.how to interpret and make use of the visual information obtained by such systems, e.g. how they should be used to control robots is not at all obvious. there are infinitely many different shapes that a mirror can have, and at least two different camera models (perspective and orthographic projection) with which to combine each mirror.the properties of the resulting sensors are very sensitive to these choices. the classic need for wide-angle lenses have, of course been in photography. in particular, underwater and architectural photography are two examples in which having a wide-angle lens is often crucial. the commercially available lens with the widest field of view (without radial distortion) that the authors are aware of is the nikon 13mm f/5.6 nikkor ais, which provides a field of view of 118 degrees at a cost of $(us) 12000. note that our prototype orthographic sensor provides a field of view of 142 degrees.
real-time estimation of human body posture from monocular thermal images. this paper introduces a new real-time method to estimate the posture of a human from thermal images acquired by an infrared camera regardless of the background and lighting conditions. distance transformation is performed for the human body area extracted from the thresholded thermal image for the calculation of the center of gravity. after the orientation of the upper half of the body is obtained by calculating the moment of inertia, significant points such as the top of the head, the tips of the hands and foot are heuristically located. in addition, the elbow and knee positions are estimated from the detected (significant) points using a genetic algorithm based learning procedure. the experimental results demonstrate the robustness of the proposed algorithm and real-time (faster than 20 frames per second) performance.
calibration of a structured light system: a projective approach. we present in this paper a novel calibration method that uses cross ratio to compute world points falling onto any given light stripe plane of a structured light system. we show that, by using 4 known non-coplanar sets of 3 collinear world points, the direct 4 x 3 image to-world transformation matrix for each light stripe plane can also be recovered from plane-to-plane homography. preliminary experiments conducted with a calibration target and a mannequin suggest that this novel calibration method is robust and is applicable to many shape measurement tasks.
linear fitting with missing data: applications to structure-from-motion and to characterizing intensity images. several vision problems can be reduced to the problem of fitting a linear surface of low dimension to data, including the problems of structure-from-affine-motion, and of characterizing the intensity images of a lambertian scene by constructing the {\em intensity manifold}. for these problems, one must deal with a data matrix with some missing elements. in structure-from-motion, missing elements will occur if some point features are not visible in some frames. to construct the intensity manifold missing matrix elements will arise when the surface normals of some scene points do not face the light source in some images. we propose a novel method for fitting a low rank matrix to a matrix with missing elements. we show experimentally that our method produces good results in the presence of noise. these results can be either used directly, or can serve as an excellent starting point for an iterative method.
3-d to 2-d recognition with regions. this paper presents a novel approach to parts-based object recognition in the presence of occlusion. we focus on the problem of determining the pose of a 3-d object from a single 2-d image when convex parts of the object have been matched to corresponding regions in the image. we consider three types of occlusions: self-occlusion, occlusions whose locus is identified in the image, and completely arbitrary occlusions. we derive efficient algorithms for the first two cases, and characterize their performance. for the last case, we prove that the problem of finding valid poses is computationally hard, but provide an efficient, approximate algorithm. this work generalizes our previous work on region-based object recognition, which focused on the case of planar models.
image based view synthesis of articulated agents. using a combination of techniques from visual representations, view synthesis, and visual-motor model estimation, we present a method for animating movements of an articulated agent (e.g. human or robot arm), without the use of any prior models or explicit 3d information. the information needed to generate simulated images can be acquired either on or off line, by watching the agent doing an arbitrary, possibly unrelated task.we present experimental results synthesizing image sequences of the simulated movement of a human arm and a puma 760 robot arm. control is in either image (camera), motor (joint), or cartesian world coordinates. we have created a user interface, where a user can input a movement program, and then upon execution, view movies of the (simulated) agent executing the program, along with the instantaneous values of the dynamics variables
building reconstruction from optical and range images. a technique is introduced for extracting and reconstructing a wide class of building types from a registered range image and optical image. an attentional focus stage, followed by model indexing, allows top-down robust surface fittting to reconstruct the 3d nature of the buildings in the data. because of the effectiveness of model selection, top-down processing of noisy range data still succeeds and the algorithm is capable of detecting and reconstructing several different building roof classes, including fiat single level, fiat multi-leveled, peaked, and curued rooftops. the algorithm is applicable to range data that may have been collected from several different range sensor types. we demonstrate reconstructions of different buildings classes in the presence of large amounts of noise. our results underline the usefuless of range data when processed in the context of a focus-of-attention area derived from the monocular optical image.
parametrized structure from motion for 3d adaptive feedback tracking of faces. a real-time system is described for automatically detecting, modeling and tracking faces in 3d. a closed loop approach is proposed which utilizes structure from motion to generate a 3d model of a face and then feed back the estimated structure to constrain feature tracking in the next frame. the system initializes by using skin classification, symmetry operations, 3d warping and eigenfaces to find a face. feature trajectories are then computed by ssd or correlation-based tracking. the trajectories are simultaneously processed by an extended kalman filter to stably recover 3d structure, camera geometry and facial pose. adaptively weighted estimation is used in this filter by modeling the noise characteristics of the 2d image patch tracking technique. in addition, the structural estimate is constrained by using parametrized models of facial structure (eigen-heads). the kalman filter's estimate of the 3d state and motion of the face predicts the trajectory of the features which constrains the search space for the next frame in the video sequence. the feature tracking and kalman filtering closed loop system operates at 25 hz.
reconstruction of linearly parameterized models from single images with a camera of unknown focal length. this paper deals with the problem of recovering the dimensions of an object and its pose from a single image acquired with a camera of unknown focal length. it is assumed that the object in question can be modeled as a polyhedron where the coordinates of the vertices can be expressed as a linear function of a dimension vector, $\lambda$. the reconstruction program takes as input, a set of correspondences between features in the model and features in the image. from this information, the program determines an appropriate projection model for the camera (scaled orthographic or perspective), the dimensions of the object, its pose relative to the camera and, in the case of perspective projection, the focal length of the camera. this paper describes how the reconstruction problem can be framed as an optimization over a compact set with low dimension¿no more than four. this optimization problem can be solved efficiently by coupling standard nonlinear optimization techniques with a multistart method which generates multiple starting points for the optimizer by sampling the parameter space uniformly. the result is an efficient, reliable solution system that does not require initial estimates for any of the parameters being estimated.
sitecity: a semi-automated site modelling system. this paper presents sitecity, a semi-automated building extraction system integrating photogrammetry, geometric constraints and image understanding algorithms. existing automated building extraction systems produce mixed results and it is clear that human intervention is required to correct mistakes from fully automated systems. sitecity gives human operators the ability to construct and manipulate three dimensional building objects using multiple images. image understanding algorithms are integrated into sitecity to assist users. the automated processes in sitecity use user-delineated roof boundaries as cues, and attempt to locate the floor of a building and match the building object in other images. in addition, photogrammetric cues are used to assist automated processes. these automated processes are described and their performance is evaluated, illustrating that automated processes in sitecity produce comparable performance to that of human subjects.
object recognition using appearance-based parts and relations. the recognition of general three-dimensional objects in cluttered scenes is a challenging problem. in particular, the design of a good representation suitable to model large numbers of generic objects that is also robust to occlusion has been an stumbling block in achieving success. in this paper, we propose a representation using appearance-based parts and relations to overcome these problems. appearance-based parts and relations are defined in terms of closed regions and the union of these regions, respectively. the regions are segmented using the mdl principle, and their appearance is obtained from collection of images and compactly represented by parametric manifolds in the two eigenspaces spanned by the parts and the relations.
image indexing using color correlograms. we define a new image feature called the color correlogram and use it for image indexing and comparison. this feature distills the spatial correlation of colors, and is both effective and inexpensive for content-based image retrieval. the correlogram robustly tolerates large changes in appearance and shape caused by changes in viewing positions, camera zooms, etc. experimental evidence suggests that this new feature outperforms not only the traditional color histogram method but also the recently proposed histogram refinement methods for image indexing/retrieval.
recognizing objects by matching oriented points. we present an approach to recognition of complex objects in cluttered 3-d scenes that does not require feature extraction or segmentation. our object representation comprises descriptive images associated with each oriented point on the surface of an object. using a single point basis constructed from an oriented point, the position of other points on the surface of the object can be described by two parameters. the accumulation of these parameters for many points on the surface of the object results in an image at each oriented point. these images, localized descriptions of the global shape of the object, are invariant to rigid transformations. through correlation of images, point correspondences between a model and scene data are established and then grouped using geometric consistency. the effectiveness of our algorithm is demonstrated with results showing recognition of complex objects in cluttered scenes with occlusion.
statistical color models with application to skin detection. the existence of large image datasets such as the set of photos on the world wide web make it possible to build powerful generic models for low-level image attributes like color using simple histogram learning techniques. we describe the construction of color models for skin and non-skin classes from a dataset of nearly 1 billion labelled pixels. these classes exhibit a surprising degree of separability which we exploit by building a skin pixel detector achieving a detection rate of 80% with 8.5% false positives. we compare the performance of histogram and mixture models in skin detection and find histogram models to be superior in accuracy and computational cost. using aggregate features computed from the skin pixel detector we build a surprisingly effective detector for naked people. our results suggest that color can be a more powerful cue for detecting people in unconstrained imagery than was previously suspected. we believe this work is the most comprehensive and detailed exploration of skin color models to date.
recognizing three-dimensional objects by comparing two-dimensional images. in this paper we address the problem of recognizing an object from a novel viewpoint, given a single ``model'' view of that object. as is common in model-based recognition, objects and images are represented as sets of feature points. we present an efficient algorithm for determining whether two sets of image points (in the plane) could be projections of a common object (a three-dimensional point set). the method relies on the fact that two sets of points in the plane are orthographic projections of the same three-dimensional point set exactly when they have a common projection onto a line. this is a form of the well-known epipolar constraint used in stereopsis. our algorithm can be used to recognize an object by comparing a stored two-dimensional view of the object against an unknown view, without requiring the correspondence between points in the views to be known a priori. we provide some examples illustrating the approach.
skin and bones: multi-layer, locally affine, optical flow and regularization with transparency. this paper describes a new method for estimating optical flow that strikes a balance between the flexibility of local dense computations and the robustness and accuracy of global parameterized flow models. an affine model of image motion is used within local image patches while a spatial smoothness constraint on the affine flow parameters of neighboring patches enforces continuity of the motion. we refer to this as a ``skin and bones'' model in which the affine patches can be thought of as rigid ``bones'' connected by a flexible ``skin''. since local image patches may contain multiple motions we use a layered representation for the affine bones. to regularize this layered motion representation we develop a new framework for "regularization with transparency".
analysis of gesture and action in technical talks for video indexing. in this paper, we present an automatic system for analyzing and annotating video sequences of technical talks. our method uses a robust motion estimation technique to detect key frames and segment the video sequence into subsequences containing a single overhead slide. the subsequences are stabilized to remove motion that occurs when the speaker adjusts their slides. any changes remaining between frames in the stabilized sequences may be due to speaker gestures such as pointing or writing and we use active contours to automatically track these potential gestures. given the constrained domain we define a simple ``vocabulary'' of actions which can easily be recognized based on the active contour shape and motion. the recognized actions provide a rich annotation of the sequence that can be used to access a condensed version of the talk from a web page.
gesture recognition using the perseus architecture. interpersonal communication involves more than simply spoken information. gestures are commonly used to more efficiently and precisely communicate. an important gesture because of its descriptive power and frequency of use is pointing. to produce a more natural and powerful human-robot interface, we have developed a purposive visual architecture called perseus and have used it to locate objects a person is pointing to. with perseus, in real-time, we are able to determine when a person enters the scene, track the relevant parts of the person including the hands and head, and recognize when she is pointing. once the person points, the object pointed to is located. the perseus architecture allows knowledge about the task and context to be used at all levels of visual analysis for improved performance. this knowledge is explicitly represented in the perseus system to facilitate the extension of perseus to other tasks and environments. in this paper we describe perseus and how it is used to solve this task. previous work on perseus is extended by describing a more sophisticated representation of the person and superior segmenting and tracking methods. experiments showing the success of the perseus system with numerous naive users in varied environments is presented.
model-based estimation of 3d human motion with occlusion based on active multi-viewpoint selection. dept. of comput. & inf. sci., pennsylvania univ., philadelphia, pa, usa abstract: we present a new method for the 3d model-based tracking of human body parts. to mitigate the difficulties arising due to occlusion among body parts, we employ multiple calibrated cameras in a mutually orthogonal configuration. in addition, we develop criteria for a time varying active selection of a set of cameras to track the motion of a particular human part. in particular, at every frame, each camera tracks a number of parts depending on the visibility of these parts and the observability of their predicted motion from the specific camera. to relate points on the occluding contours of the parts to points on their models we apply concepts from projective geometry. then, within the physics-based framework we compute the generalized forces applied from the parts' occluding contours to model points of the body parts. these forces update the translational and rotational degrees of freedom of the model, such as to minimize the discrepancy between the sensory data and the estimated model state. we present initial tracking results from a series of experiments involving the recovery of complex 3d motions in the presence of significant occlusion.
a stereo machine for video-rate dense depth mapping and its new applications. we have developed a video-rate stereo machine that has the capability of generating a dense depth map at the video rate. the performance bench marks of the cmu video-rate stereo machine are: 1) multi image input of up to 6 cameras; 2) throughput of 30 million point-disparity measurements per second; 3) frame rate of 30 frame/sec; 4) a dense depth map of up to 256 x 240 pixels; 5) disparity search range of up to 60 pixels; 6) high precision of depth output up to 8 bi ts (with interpolation). the capability of passively producing such a dense depth map (3d representation) of a scene at the video rate can open up a new class of applications of 3d vision:merging real and virtual worlds in real time.
3-d scene data recovery using omnidirectional multibaseline stereo. a traditional approach to extracting geometric information from a large scene is to compute multiple 3-d depth maps from stereo pairs or direct range finders, and then to merge the 3-d data. however, the resulting merged depth maps may be subject to merging errors if the relative poses between depth maps are not known exactly. in addition, the 3-d data may also have to be resampled before merging, which adds additional complexity and potential sources of errors.this paper provides a means of directly extracting 3-d data covering a very wide field of view, thus by-passing the need for numerous depth map merging. in our work, cylindrical images are first composited from sequences of images taken while the camera is rotated 360&deg; about a vertical axis. by taking such image panoramas at different camera locations, we can recover 3-d data of the scene using a set of simple techniques: feature tracking, an 8-point structure from motion algorithm, and multibaseline stereo. we also investigate the effect of median filtering on the recovered 3-d point distributions, and show the results of our approach applied to both synthetic and real scenes.
characterization of errors in compositing panoramic images. in this paper, we describe the effect of errors in the intrinsic camera parameters on reconstructed panoramic images. a panoramic image is created by first capturing a sequence of images while rotating the camera about a vertical axis a full 360 degrees. the subsequent steps are projecting the original rectilinear images onto cylindrical surfaces and compositing them to form the panoramic image.our analysis has led to a technique that allows simultaneous recovery of the camera focal length and properly composited panoramic images. the correct focal length can be determined by iterating the processes of projecting the original rectilinear images onto cylindrical surfaces given an estimate of the focal length and compositing the resulting images to yield an increasingly better estimate of the focal length. this paper shows that the convergence towards the correct focal length is exponential.
recognition of handwritten phrases as applied to street name images. a method for recognition of street name phrases collected from mail pieces is presented in this paper. some of the challenges posed by the problem are: (i) patron errors, (ii) non-standardized way of abbreviating names, and (iii) variable number of words in a street name image. a neural network has been designed to segment words in a phrase, a street name in this case, using distances between components and style of writing. the network learns the type of spacing (including size) that one should expect between different pairs of characters in handwritten text. experiments show perfect word segmentation performance at about 85% of cases. unlike conventional methods, where lexicon entries are expanded to take care of all variations of prefixes and suffixes, substring matching is attempted only between the main body of a lexicon entry and the word segments of an image. efforts to reduce computational complexity are successfully made by the sharing of character segmentation results between the segmentation and recognition phases. 83% phrase recognition accuracy is achieved on a test set.
content-based trademark retrieval system using visually salient features. an ever increasing number of registered trademarks has created greater demand for an automatic trademark retrieval system. we present a method for such a system based on the image content using shape features. zernike or pseudo-zernike moments of the image are employed as a feature set. to retrieve similar shapes, we take into account visually salient features that dominantly affect the global shape of the trademarks and ignore their minor detail. experimental results on a database of 3,000 trademark images demonstrate that the proposed method retrieves visually similar trademarks which agree well with human perception.
images as embedding maps and minimal surfaces: movies, color, and volumetric medical images. a general geometrical framework for image processing is presented. we consider intensity images as surfaces in the (x, i) space. the image is thereby a two dimensional surface in three dimensional space for gray level images. the new formulation unifies many classical schemes, algorithms, and measures via choices of parameters in "master" geometrical measure. more important, it is a simple and efficient tool for the design of natural schemes for image enhancement, segmentation, and scale space. here we give the basic motivation and apply the scheme to enhance images. we present the concept of an image as a surface in dimensions higher than the three dimensional intuitive space. this will help us handle movies, color, and volumetric medical images.
facial expression recognition and its degree estimatio. the purpose of this study is not only to recognize some kind of facial expressions which is associated with human emotion but also to estimate its degree. our method is based on the idea that facial expression recognition can be achieved by extracting a variation from expressionless face with considering face area as a whole pattern. for the purpose of extracting subtle changes in the face such as the degree of expressions, it is necessary to eliminate the individuality appearing in the facial image. using a elastic net model, a variation of facial expression is represented as motion vectors of the deformed net from a facial edge image. then, applying k-l expansion, the change of facial expression represented as the motion vectors of nodes is mapped into low dimensional eigen space, and estimation is achieved by projecting input images on to the emotion space. in this paper we have constructed three kinds of expression models: happiness, anger, surprise, and experimental results are evaluated.
interaction with on-screen objects using visual gesture recognition. this paper will review the design of a working system that visually recognizes hand gestures for the control of a window based user interface. after an overview of the system, it will explore one aspect of gestural interaction in depth, hand tracking, and what is needed for the user to be able to interact comfortably with on-screen objects. we describe how the location of the hand is mapped to a location on the screen, and how it is both necessary and possible to smooth the camera input using a non-linear physical model of the cursor. the performance of the system is examined, especially with respect to object selection. we show how a standard hci model of object selection (fitts' law) can be extended to model the selection performance of free-hand pointing.
non-linear operators in image restoration. we firstly present a variational approach such that during image restoration, edges detected in the original image are being preserved, and then we compare in a second part, the mathematical foundation of this method with respect to some of the well known methods recently proposed in the literature within the class of pde based algorithms (anisotropic diffusion, mean curvature motion, min/max flow technique,... ). the performance of our approach is carefully examined and compared to the classical methods. experimental results on synthetic and real images will illustrate the capabilities of all the studied approaches.
panoramic image acquisition. this paper is concerned with acquiring panoramic focused images using a small field of view video camera. when scene points are distributed over a range of distances from the sensor, obtaining a focused composite image involves focus computations and mechanically changing some sensor parameters (translation of sensor plane, panning of camera etc.) which can be time intensive. in this paper we present methods to optimize the image acquisition strategy in order to reduce redundancy. we show that panning a camera about a point f (focal length) in front of the camera eliminates redundancy. the non-frontal imaging camera (nicam) with tilted sensor plane has been previously introduced as a sensor that can acquire focused panoramic images. in this paper we also describe strategies for optimal selection of panning angle increments and sensor plane tilt for nicam. experimental results are presented for panoramic image acquisition using a regular camera as well as using nicam.
eigenfeatures for planar pose measurement of partially occluded objects. planar pose measurement from images is an important problem for automated assembly and inspection. in addition to accuracy and robustness, ease of use is very important for real world applications. recently, murase and nayar have presented the "parametric eigenspace " for object recognition and pose measurement based on training images. although their system is easy to use, it has potential problems with background clutter and partial occlusions. we present an algorithm that is robust in these terms. it uses several small features on the object rather than a monolithic template. these "eigenfeatures" are matched using a median statistic, giving the system robustness in the face of background clutter and partial occlusions. we demonstrate our algorithm's pose measurement accuracy with a controlled test, and we demonstrate its detection robustness on cluttered images with the objects of interest partially occluded.
object detection with vector quantized binary features. this paper presents a new algorithm for detecting objects in images, one of the fundamental tasks of computer vision. the algorithm extends the representational efficiency of eigenimage methods to binary features, which are less sensitive to illumination changes than gray-level values normally used with eigenimages. binary features (square subtemplates) are automatically chosen on each training image. using features rather than whole templates makes the algorithm more robust to background clutter and partial occlusions. instead of representing the features with real-valued eigenvector principle components, we use binary vector quantization to avoid floating point computations. the object is detected in the image using a simple geometric hash table and hough transform. on a test of 1000 images, the algorithm works on 99.3%. we present a theoretical analysis of the algorithm in terms of the receiver operating characteristic, which consists of the probabilities of detection and false alarm. we verify this analysis with the results of our 1000-image test and we use the analysis as a principled way to select some of the algorithm's important operating parameters.
novel active-vision-based visual-threat-cue for autonomous navigation tasks. this paper presents a new visual motion cue, we call the visual threat cue (vtc) that provides some measure for a relative change in range as well as clearance between a 3d surface and a fixing observer in motion. the vtc corresponds to visual fields surrounding a moving observer. the fields are time-based imaginary 3-d surfaces that move with the observer. they are analogous to equi-potential fields of an electric dipole. a practical method to extract the vtc is presented. the approach is independent of the 3d surface texture and needs no optical flow information, 3d reconstruction, segmentation, feature tracking or pre-processing. this algorithm to extract the vtc was applied to several indoor as well as outdoor real images of textures, where we observed a similar behavior for most of the textures employed.
an image-based visual-motion-cue for autonomous navigatio. this paper presents a novel time-based visual motion cue called the hybrid visual threat cue (hvtc) that provides some measure for a change in relative range as well as absolute clearances, between a 3d surface and a moving observer. it is shown that the hvtc is a linear combination of time-to-contact (ttc), visual looming and the visual threat cue (vtc). the visual field associated with the hvtc can be used to demarcate the regions around a moving observer into safe and danger zones of varying degree, which may be suitable for autonomous navigation tasks. the hvtc is independent of the 3d environment and needs almost no a-priori information about it. it is rotation independent, and is measured in ~time/sup -1/\ units several approaches to extract the hvtc, are suggested. also a practical method to extract it from a sequence of images of a 3d textured surface obtained by a visually fixating, fixed-focus monocular camera in motion is presented. this approach of extracting the hvtc is independent of the type of 3d surface texture and needs no optical flow information, 3d reconstruction, segmentation, feature tracking.
shape from the light field boundary. ray-based representations of shape have received little attention in computer vision. in this paper we show that the problem of recovering shape from silhouettes becomes considerably simplified if it is formulated as a reconstruction problem in the space of oriented rays that intersect the object. the method can be used with both calibrated and uncalibrated cameras, does not rely on point correspondences to compute shape, and does not impose restrictions on object topology or smoothness.
what is a light source? traditional light source modelling is concerned with specific types of light sources, the two most common of which are point sources and daylight. little attempt has been made, however, to relate different types of sources to each other. for example, how may the lighting from an overcast sky be compared to that from a lamp? having a theoretical framework to compare different types of light sources is important for computer vision, in particular for understanding shading and shadow cues. a vision system needs to take account of the light source in order to interpret these cues. in this paper, we present a framework for comparing types of light sources which is based on a dimensional analysis of the set of light rays in a free space. specifically, we introduce a 4-d light source hypercube in which the different types of sources may be embedded and compared. we also present a novel definition for light sources which generalizes the standard definition of a source as an emitter.
recovering the viewing parameters of random, translated and noisy projections of asymmetric objects. a method is described for the determination of the viewing parameters of randomly acquired projections of asymmetric objects. it extends upon the common lines algorithm by determining the relative orientation of projections from the location of lines of intersection among the fourier transforms of the projections in three-dimensional fourier space. a new technique for finding the lines of intersection in the presence of translational displacement, and for subsequently finding the translational displacement, is presented. a new technique for dealing with noise is also presented. the complete algorithm is described and its efficacy is demonstrated using real data. this technique may be applied to the three-dimensional reconstruction of viruses, molecules, and cells from in vivo images. it also has many other applications including the reconstruction of underwater scenes, radioastronomy, geoseismic analysis, and portable radiography for medical diagnosis and industrial inspection.
new, faster, more controlled fitting of implicit polynomial 2d curves and 3d surfaces to data . denote a point in the plane by z=(z,y) and a polynomial of nth degree in z by f(z) /spl sigma//sub i,j//spl ges/o/sub 1/i+j/spl les/n(a/sub ij/x/sup i/y/sup j/). denote by z(f) the set of points for which f(z)=0. z(f) is the 2d curve represented by f(z). in this paper, we present a new approach to fitting 2d curves to data in the plane (or 3d surfaces to range data) which has significant advantages over presently known methods. it requires considerably less computation and the resulting curve can be forced to lie close to the data set at prescribed points provided that there is an nth degree polynomial that can reasonably approximate the data. linear programming is used to do the fitting. the approach can incorporate a variety of distance measures and global geometric constraints.
using differential constraints to reconstruct complex surfaces from stereo. stereo reconstruction algorithms often fail to properly deal with complex surfaces, because there is not enough image information. to overcome this problem, we propose to guide the reconstruction process using a priori information about the differential geometry of the object surfaces. we use both linear structures such as crest lines or scalar fields such as curvature values to generate a reconstruction of the surface which is consistent with the differential properties. this method improves the accuracy of the reconstruction around the discontinuities and increases the compactness of the surface representation.
dealing with occlusions in the eigenspace approach. the basic limitations of the current appearance-based matching methods using eigenimages are non-robust estimation of coefficients and inability to cope with problems related to occlusions and segmentation. in this paper we present a new approach which successfully solves these problems. the major novelty of our approach lies in the way how the coefficients of the eigenimages are determined. instead of computing the coefficients by a projection of the data onto the eigenimages, we extract them by a hypothesize-and-test paradigm using subsets of image points. competing hypotheses are then subject to a selection procedure based on the minimum description length principle. the approach enables us not only to reject outliers and to deal with occlusions but also to simultaneously use multiple classes of eigenimages.
on perpendicular texture: why do we see more flowers in the distance? almost all work on texture in the computer vision and graphics communities has modeled the texture as tangential, i.e. lying in the tangent plane to the surface. this is equivalent to thinking of the texture as a pattern painted on the surface. three-dimensional textures, where the elements may point out of the surface, have largely been ignored. we study a special class of 3d textures, perpendicular textures where we can model the elements as being normal to the surface. the perspective projection of perpendicularly textured surfaces results in several interesting phenomena, which do not occur in the much-studied tangential texture case. these include occlusion, foreshortening and illumination.in this paper, we study the geometry of the problem, modeling the locations of the elements of the texture as being a realization of a spatial point process. relations between slant and tilt of the surface, density and height of elements and occlusions are derived. occlusions can now be used as a cue to infer shape, instead of being treated as a source of error.
bayesian image restoration and segmentation by constrained optimizatio. abstract: a constrained optimization method, called the lagrange-hopfield (lh) method, is presented for solving markov random field (mrf) based bayesian image estimation problems for restoration and segmentation. the method combines the augmented lagrangian multiplier technique with the hopfield network to solve a constrained optimization problem into which the original bayesian estimation problem is reformulated. the lh method effectively overcomes instabilities that are inherent in the penalty method (e.g. hopfield network) or the lagrange multiplier method in constrained optimization. an additional advantage of the lh method is its suitability for neural-like analog implementation. experimental results are presented which show that lh yields good quality solutions at reasonable computational costs.
geometric and photometric constraints for surface recovery. in this paper we present a novel approach to surface recovery from an image sequence of a rotating object. in this approach, the object is illuminated under a collinear light source (where the light source lies on or near the optical axis) and rotated on a controlled turntable. a wire-frame of 3d curves on the object surface is extracted by using shading and occluding contours in the image sequence. then the whole object surface is recovered by interpolating the surface between curves on the wire-frame. the interpolation can be done by using geometric or photometric methods. the photometric method uses shading information and is more powerful than geometric methods. the experimental results on real image sequence of matte and specular surfaces show that the technique is feasible and promising.
dynamic appearance-based recognition. we describe a hierarchical appearance-based method for learning, recognizing, and predicting arbitrary spatiotemporal sequences of images. the method, which implements a robust hierarchical form of the kalman filter derived from the minimum description length (mdl) principle, includes as a special case several well-known object encoding techniques including eigenspace methods for static recognition. successive levels of the hierarchical filter implement dynamic models operating over successively larger spatial and temporal scales. each hierarchical level predicts the recognition state at a lower level and modifies its own recognition state using the residual error between the prediction and the actual lower-level state. simultaneously, on a longer time scale, the filter learns an internal model of input dynamics by adapting its generative and state transition matrices at each level to minimize prediction errors. the resulting prediction/learning scheme thereby implements an on-line form of the well-known expectation-maximization (em) algorithm from statistics. we present experimental results demonstrating the method's efficacy in mediating robust spatiotemporal recognition in a variety of scenarios containing varying degrees of occlusions and clutter.
using chromaticity distributions and eigenspace analysis for pose, illumination, and specularity-invariant recognition of 3d objects. the distribution of object colors can be effectively utilized for recognition and indexing. difficulties arise in the recognition of object color distributions when there are variations in illumination color, changes in object pose with respect to illumination direction, and specular reflections. however, most of the recent approaches to color-based recognition focus mainly on illumination color invariance. we propose an approach that identifies object color distributions influenced by: (1) illumination pose, (2) illumination color and (3) specularity. we suggest the use of chromaticity distributions to achieve illumination pose invariance. to characterize changes in chromaticity distribution due to illumination color, a set of chromaticity histograms of each object is generated for a range of lighting colors based on linear models of illumination and reflectance, and the histograms are represented using a small number of eigen basis vectors constructed from principal components analysis. since specular reflections may alter the chromaticity distributions of test objects, a model-based specularity detection/rejection algorithm, called chromaticity differencing, is developed to reduce these effects.
texture features and learning similarity. this paper addresses two important issues related to texture pattern retrieval: feature extraction and similarity search. a gabor feature representation for textured images is proposed, and its performance in pattern retrieval is evaluated on a large texture image database. these features compare favorably with other existing texture representations. a simple hybrid neural network algorithm is used to learn the similarity by simple clustering in the texture feature space. with learning similarity, the performance of similar pattern retrieval improves significantly. an important aspect of this work is its application to real image data. texture feature extraction with similarity learning is used to search through large aerial photographs. feature clustering enables efficient search of the database as our experimental results indicate.
edge flow: a framework of boundary detection and image segmentation. a novel boundary detection scheme based on edgejow is proposed in this paper. this scheme utilizes a predictive coding model to identify the direction of change in color and texture at each image location at a given scale, and constructs an edge flow vector: by iteratively propagating the edge flow, the boundaries can be detected at image locations which encounter two opposite directions offrow in the stable state. a user defined image scale is the only significant control parameter that is needed by the algorithm. the scheme facilitates integration of color and texture into a single framework for boundary detection.
edge detection and ridge detection with automatic scale selection. when computing descriptors of image data, the type of information that can be extracted may be strongly dependent on the scales at which the image operators are applied. this article presents a systematic methodology for addressing this problem. a mechanism is presented for automatic selection of scale levels when detecting one-dimensional image features, such as edges and ridges.a novel concept of a scale-space edge is introduced, defined as a connected set of points in scale-space at which: (i) the gradient magnitude assumes a local maximum in the gradient direction, and (ii) a normalized measure of the strength of the edge response is locally maximal over scales. an important consequence of this definition is that it allows the scale levels to vary along the edge. two specific measures of edge strength are analyzed in detail, the gradient magnitude and a differential expression derived from the third-order derivative in the gradient direction. for a certain way of normalizing these differential descriptors, by expressing them in terms of so-called &gamma;-normalized derivatives, an immediate consequence of this definition is that the edge detector will adapt its scale levels to the local image structure. specifically, sharp edges will be detected at fine scales so as to reduce the shape distortions due to scale-space smoothing, whereas sufficiently coarse scales will be selected at diffuse edges, such that an edge model is a valid abstraction of the intensity profile across the edge.since the scale-space edge is defined from the intersection of two zero-crossing surfaces in scale-space, the edges will by definition form closed curves. this simplifies selection of salient edges, and a novel significance measure is proposed, by integrating the edge strength along the edge. moreover, the scale information associated with each edge provides useful clues to the physical nature of the edge.with just slight modifications, similar ideas can be used for formulating ridge detectors with automatic selection, having the characteristic property that the selected scales on a scale-space ridge instead reflect the width of the ridge.it is shown how the methodology can be implemented in terms of straightforward visual front-end operations, and the validity of the approach is supported by theoretical analysis as well as experiments on real-world and synthetic data.
viewpoint variation in the noise sensitivity of pose estimation. the paper presents an analysis of the stability of pose estimation. the investigated pose estimation technique is based on orientations of three edge segments and provides the rotation part of object pose.the specific emphasis of the analysis is on determining how the stability varies with view point relative to an object. the stability investigation propagates the uncertainty in edge segment orientations to the resulting effect on the pose parameters. it is shown that there is a very strong variation in noise sensitivity over the range of viewpoints and that exactly what viewpoints offer highest robustness towards noise can be determined in advance. experiments on real images verify the theoretical results and show that, dependent on viewpoint, pose parameter variance varies from 0.05 to 20 (degrees squared).
configuration based scene classification and image indexing. scene classification is a major open challenge in machine vision. most solutions proposed so far such as those based on color histograms and local texture statistics cannot capture a scene's global configuration, which is critical in perceptual judgments of scene similarity. we present a novel approach, "configural recognition", for encoding scene class structure. the approach's main feature is its use of qualitative spatial and photometric relationships within and across regions in low resolution images. the emphasis on qualitative measures leads to enhanced generalization abilities and the use of low-resolution images renders the scheme computationally efficient. we present results on a large database of natural scenes. we also describe how qualitative scene concepts may be learned from examples.
object tracking using affine structure for point correspondences. a new object tracking algorithm based on affine structure has been developed and it is shown that its performance is better than that of a kalman filter based correlation tracker. the algorithm is fast, reliable, viewpoint invariant, and insensitive to occlusion and/or individual corner disappearance or reappearance. detailed experimental analysis on a long real image sequence is also presented.
word spotting: a new approach to indexing handwriting. there are many historical manuscripts written in a single hand which it would be useful to index. examples include the early presidential papers at the library of congress and the collected works of w. b. dubois at the library of the university of massachusetts. the standard technique for indexing documents is to scan them in, convert them to machine readable form (ascii) using optical character recognition (ocr) and then index them using a text retrieval engine. however, ocr does not work well on handwriting. here an alternative scheme is proposed for indexing such texts. each page of the document is segmented into words. the images of the words are then matched against each other to create equivalence classes (each equivalence classes contains multiple instances of the same word). the user then provides ascii equivalents for say the top 2000 equivalence classes. the current paper deals with the matching aspects of this process. due to variations in even a single person''s handwriting, it is expected that the matching will be the most difficult step in the whole process. two different techniques for matching words are discussed. the first method, based on euclidean distance mapping, matches words assuming that the transformation between the words may be modelled by a translation (shift). the second method, based on an algorithm developed by scott and longuet higgins, matches words assuming that the transformation between the words may be modelled by an affine transform. experiments are shown demonstrating the feasibility of the approach for indexing handwriting.
controlled camera motions for scene reconstruction and exploration. this paper deals with the 3d structure estimation and exploration of a scene using active vision. our method is based on the structure from controlled motion approach which consists in constraining the camera motion in order to obtain a precise and robust estimation of the 3d structure of a geometrical primitive. since this approach involves to gaze on the considered primitive, we present a method for connecting up many estimations in order to recover the complete spatial structure of scenes composed of cylinders and segments. we have developed perceptual strategies able to perform a succession of robust estimations without any assumption on the number and on the localization of the different objects. furthermore, the proposed strategy ensures the completeness of the reconstruction. an exploration process centered on current visual features and on the structure of the previously studied primitives is presented. this leads to a gaze planning strategy that mainly uses a representation of known and unknown areas as a basis for selecting viewpoints. finally, experiments carried out on a robotic cell have proved the validity of our approach.
a class of probabilistic shape models. deformable models are related to other data representation methods. it was recently proposed a class of models based on a fuzzy energy function which includes many well known algorithms (snakes, elastic nets, fuzzy and hard c-means and kohonen maps). this paper describes a probabilistic extension of these algorithms in a bayesian framework, using gibbs-boltzman distributions. it is shown that the new class of models minimizes an energy function with an additional term: the log partition function. the role of the log partition function in probabilistic versions of snakes, c-means and elastic nets is studied and analytic expressions are derived in the case of probabilistic snakes. the log partition function produces an additional force field which improves the performance of these algorithms in some applications.
edge localization in surface reconstruction using optimal estimation theory. many relaxation based smoothing methods used in surface reconstruction algorithms filter out the effect of noise in image data, but result in the elimination of important discontinuity information as well. in this paper the inter-pixel interaction during relaxation is shown to be equivalent to a multiple measurement fusion problem which can be solved using optimal estimation theory. pixels in a given neighbourhood act as noisy information sources, combining their information to update the state of that neighbourhood. by formulating discontinuities as another ``noise'' source in the image, and by using the so-called curvature consistency reconstruction algorithm on range images, it is shown that optimal estimation theory offers a method for the automatic and adaptive localization of discontinuities while providing a smooth piece-wise continuous surface description.
physics-based segmentation: moving beyond color. we previously presented a framework for segmentation of complex scenes using multiple physical hypotheses for simple image regions. a consequence of that framework was a proposal for a new approach to the segmentation of complex scenes into regions corresponding to coherent surfaces rather than merely regions of similar color. herein we present an implementation of this new approach and show example segmentations for scenes containing multi-colored piece-wise uniform objects. using our approach we are able to intelligently segment scenes with objects of greater complexity than previous physics-based segmentation algorithms. the results show that by using general physical models we obtain segmentations that correspond more closely to coherent surfaces in the scene than segmentations found using only color.
a real-time computer vision system for measuring traffic parameters. for the problem of tracking vehicles on freeways using machine vision, existing systems work well in free-flowing traffic. traffic engineers, however, are more interested in monitoring freeways when there is congestion, and current systems break down for congested traffic due to the problem of partial occlusion. we have developed a feature-based tracking approach for the task of tracking vehicles under congestion. instead of tracking entire vehicles, vehicle sub-features are tracked to make the system robust to partial occlusion. in order to group together sub-features that come from the same vehicle, the constraint of common motion is used. here we describe the real-time implementation of the system using a network of dsp chips.
isotropic gradient estimatio. the vast majority of corner and edge detectors measure image intensity gradients in order to estimate the positions and strengths of features. however, many of the most popular intensity gradient estimators are inherently and significantly anisotropic. in spite of this, few algorithms take the anisotropy into account, and so the set of features uncovered is typically sensitive to rotations of the image, compromising recognition, matching (e.g. stereo), and tracking. we introduce an effective technique for removing unwanted anisotropies from analytical gradient estimates, by measuring local intensity gradients in four directions rather than the more traditional two. in experiments using real image data, our algorithm reduces the gradient anisotropy associated with conventional analytical gradient estimates by up to 85%, yeilding more consistent feature topologies.
dense nonrigid motion tracking from a sequence of velocity fields. we have addressed the problem of tracking the nonrigid motion of the heart using a sequence of velocity fields and a sequence of contours. the information from both the contours and the dense velocity fields is integrated into a deforming mesh that is placed over the myocardium at one time frame and then tracked over the entire cardiac cycle. the deformation is guided by a smoothing filter that provides a compromise between (i) believing the dense field velocity and the contour data when it is crisp and coherent in a local spatial and temporal sense and (ii) employing a temporally smooth cyclic model of cardiac motion when contour and velocity data are not trustworthy. the method has been carefully evaluated with simulated data and phantom data. experiments with in vivo data have also been conducted.
muse: robust surface fitting using unbiased scale estimates. despite many successful applications of robust statistics, they have yet to be completely adapted to many computer vision problems. range reconstruction, particularly in unstructured environments, requires a robust estimator that not only tolerates a large outlier percentage but also tolerates several discontinuities, extracting multiple surfaces in an image region. observing that random outliers and/or points from across discontinuities increase a hypothesized fit's scale estimate (standard deviation of the noise), our new operator, called muse (minimum unbiased scale estimator), evaluates a hypothesized fit over potential inlier sets via an objective function of unbiased scale estimates. muse extracts the single best fit from the data by minimizing its objective function over a set of hypothesized fits and can sequentially extract multiple surfaces from an image region. we show muse to be effective on synthetic data modelling small scale discontinuities and in preliminary experiments on complicated range data.
prediction intervals for surface growing range segmentation. the surface growing framework presented by besl and jain has served as the basis for many range segmentation techniques. it has been augmented with alternative fitting techniques, model selection criteria, and solid modelling components. all of these approaches, however, require global thresholds and large isolated seed regions. range scenes typically do not satisfy the global threshold assumption since it requires data noise characteristics to be constant throughout the scene. furthermore, as scene complexity increases, the number of surfaces, discontinuities, and outliers increase, hindering the identification of large seed regions.we present statistical criteria based on multivariate regression to replace the traditional decision criteria used in surface growing. we use local estimates and their uncertainties to construct criteria which capture the uncertainty in extrapolating estimated fits. we restrict surface expansion to very localized extrapolations, increasing the sensitivity to discontinuities and allowing regions to refine their estimates and uncertainties. our approach uses a small number of parameters which are either statistical thresholds or cardinality measures, i.e. we do not use thresholds defined by specific range distances or orientation angles.
interactive learning with a "society of models" . digital library access is driven by features, but the relevance of a feature for a query is not always obvious. this paper describes an approach for integrating a large number of context-dependent features into a semi-automated tool. instead of requiring universal similarity measures or manual selection of relevant features, the approach provides a learning algorithm for selecting and combining groupings of the data, where groupings can be induced by highly specialized features. the selection process is guided by positive and negative examples from the user. the inherent combinatorics of using multiple features is reduced by a multistage grouping generation, weighting, and collection process. the stages closest to the user are trained fastest and slowly propagate their adaptations back to earlier stages. the weighting stage adapts the collection stage's search space across uses, so that, in later interactions, good groupings are found given few examples from the user.
bayesian face recognition using deformable intensity surfaces. we describe a novel technique for face recognition based on deformable intensity surfaces which incorporates both the shape and texture components of the 2d image. the intensity surface of the facial image is modeled as a deformable 3d mesh in (z, y, i(x, y)) space. using an efficient technique for matching two surfaces (in terms of the analytic modes of vibration), we obtain a dense correspondence field (or 3d warp) between two images. the probability distributions of two classes of warps are then estimated from training data: interpersonal and extrapersonal variations. these densities are then used in a bayesian framework for image matching and recognition. experimental results with facial data from the us army feret database demonstrate an increased recognition rate over the previous best methods.
a hybrid framework for surface registration and deformable models. in computer vision, two complementary approaches have been widely used to perform object reconstruction and registration. the deformable model framework locally applies internal and external forces to fit 3d data. the non-rigid registration framework iteratively computes the best global transformation in order to minimize the distance between a template and the data. in this paper, we first show that applying a global transformation on a surface model, is equivalent to applying an external force on a deformable model without any regularizing force. second we propose a hybrid framework which combines the registration framework and the deformable models scheme. our hybrid deformation approach allows to control the scale at which the model is deformed. this is clearly beneficial for performing both reconstruction and registration tasks. we show many examples of this approach on active contours and deformable surfaces. furthermore, a global transformation based on axial symmetry is introduced.
closest point search in high dimensions. the problem of finding the closest point in high-dimensional spaces is common in computational vision. unfortunately, the complexity of most existing search algorithms, such as k-d tree and r-tree, grows exponentially with dimension, making them impractical for dimensionality above 15. in nearly all applications, the closest point is of interest only if it lies within a user specified distance \epsilon. we present a simple and practical algorithm to efficiently search for the nearest neighbor within euclidean distance \epsilon. our algorithm uses a projection search technique along with a novel data structure to dramatically improve performance in high dimensions. a complexity analysis is presented which can help determine \epsilon in structured problems. benchmarks clearly show the superiority of the proposed algorithm for high dimensional search problems frequently encountered in machine vision, such as real-time object recognition.
fast 3d stabilization and mosaic construction. we present a fast electronic image stabilization system that compensates for 3d rotation. the extended kalman filter framework is employed to estimate the rotation between frames, which is represented using unit quaternions. a small set of automatically selected and tracked feature points are used as measurements. the effectiveness of this technique is also demonstrated by constructing mosaic images from the motion estimates, and comparing them to mosaics built from 2d stabilization algorithms. two different stabilization schemes are presented. the first, implemented in a real-time platform based on a datacube mv200 board, estimates the motion between two consecutive frames and is able to process gray level images of resolution 128x120 at 10 hz. the second scheme estimates the motion between the current frame and an inverse mosaic; this allows better estimation without the need for indexing the new image frames. experimental results for both schemes using real and synthetic image sequences are presented.
registering multiple cartographic models with the hierarchical mixture of experts algorithm. this paper describes an application of the hierarchical mixture of experts algorithm to the registration of multiple cartographic models to noisy radar data according to the hme algorithm each model is represented by a set of maximum likelihood registration parameters together with a set of matching probabilities. this architecture can be viewed as providing simultaneous registration and hypothesis verification. the maps in the cartographic data-base compete to account for radar data through the imposed probability normalization. the resulting matching algorithm can be regarded as a generic tool for model retrieval from a data-base. our evaluation on radar images illustrates some of the characteristics of the algorithm. our main conclusions are that the method is both robust to added image noise and poor initialization.
parametric feature detection. we propose an algorithm to automatically construct feature detectors for arbitrary parametric features. to obtain a high level of robustness we advocate the use of realistic multi-parameter feature models and incorporate optical and sensing effects. each feature is represented as a densely sampled parametric manifold in a low dimensional subspace of a hilbert space. during detection, the brightness distribution around each image pixel is projected into the subspace. if the projection lies sufficiently close to the feature manifold, the feature is detected and the location of the closest manifold point yields the feature parameters. the concepts of parameter reduction by normalization, dimension reduction, pattern rejection, and heuristic search are all employed to achieve the required efficiency. by applying the algorithm to appropriate parametric feature models, detectors have been constructed for five features, namely, step edge, roof edge, line, corner, and circular disc. detailed experiments are reported on the robustness of detection and the accuracy of parameter estimation.
eigen-texture method: appearance compression based on 3d model. image-based and model-based methods are two representative rendering methods for generating virtual images of objects from their real images. extensive research on these two methods has been made in cv and cg communities. however, both methods still have several drawbacks when it comes to applying them to the mixed reality where we integrate such virtual images with real background images. to overcome these difficulties, we propose a new method, which we refer to as the eigen-texture method. the proposed method samples appearances of a real object under various illumination and viewing conditions, and compresses them in the 2d coordinate system defined on the 3d model surface. the 3d model is generated from a sequence of range images. the eigen-texture method is practical because it does not require any detailed reflectance analysis of the object surface, and has great advantages due to the accurate 3d geometric models. this paper describes the method, and reports on its implementation.
3-d object pose estimation by shading and edge data fusion ----simulating virtual manipulation on mental images. human beings seem to recognize objects based on a kind of model-matching, i.e., a virtual manipulation on mental images. this paper presents a 3-d object pose estimation method simulating the human recognition scheme. computer synthesizes not only an edge image but also a shading image from an object model. then, it matches the two kinds of synthesized images with the inputted images individually by using a non-linear least-squares method, and estimates the pose parameter values. finally, it chooses the better of the individually estimated poses. thus, the fusion of the shading and the edge information is achieved. since the two pieces of information complement each other, this method has the advantage of much higher robustness and accuracy of pose estimation than ordinary model-matching techniques which rely only on geometrical features such as vertices or edges.
detection and description of buildings from multiple aerial images. a method for detection and description of rectangular buildings from two or more registered aerial intensity images is proposed. the output is a 3d description of the buildings, with an associated confidence measure for each building. hierarchical perceptual grouping and matching across views is employed to increase the robustness of the system. verification of selected building hypotheses is done using shadow and wall evidence of the buildings. the system is largely feature-based. grouping and matching are performed in a hierarchical manner, utilizing primitives of increasing complexity, starting with line segments and junctions, and proceeding to higher level features. binocular and trinocular epipolar constraints are used to reduce the search space for matching features.
recovering affine motion and defocus blur simultaneously. motion in depth and/or zooming cause defocus blur. we show how the defocus blur in an image can be recovered simultaneously with affine motion. we introduce the theory, develop a solution method and demonstrate the validity of the theory and the solution by conducting experiments with real scenery.
global models with parametric offsets as applied to cardiac motion recovery. we introduce a new solid shape model formulation that includes built-in offsets from a base global component (e.g. an ellipsoid) which are functions of the global component's parameters. the offsets provide two features. first, they help to form an expected model shape which facilitates appropriate model data correspondences. second, they scale with the base global model to maintain the expected shape even in the presence of large global deformations. we apply this model formulation to the recovery of 3-d cardiac motion from a volunteer dataset of tagged-mr images. the model instance is a variation of the hybrid volumetric ventriculoid (hvv), a deformable thick-walled ellipsoid model resembling the left ventricle (lv) of the heart. a unique aspect of our implementation is the employment of constant volume constraints when recovering the cardiac motion. in addition, we present a novel geodesic-like prismoidal tessellation of the model which provides for more stable fits.
occlusion detectable stereo -- occlusion patterns in camera matrix. in stereo algorithms with more than two cameras, the improvement of accuracy is often reported since they are robust against noise. however, another important aspect of the polynocular stereo, that is the ability of occlusion detection, has been paid less attention. we intensively analyzed the occlusion in the camera matrix stereo (sea) and developed a simple but effective method to detect the presence of occlusion and to eliminate its effect in the correspondence search. by considering several statistics on the occlusion and the accuracy in the sea, we derived a few base masks which represent occlusion patterns and are effective for the detection of occlusion. several experiments using typical indoor scenes showed quite good performance to obtain dense and accurate depth maps even at the occluding boundaries of objects.
lines in one orthographic and two perspective views. we introduce a linear algorithm to recover the euclidean motion between an orthographic and two perspective cameras from straight line correspondences filling the gap in the analysis of motion estimation from line correspondences for various projection models. the general relationship between lines in three views is described by the trifocal tensor. euclidean structure from motion for three perspective views is a special case in which the relationship is defined by a collection of three matrices. here, we describe the case of two calibrated perspective views and an orthographic view. similar to the other cases, our linear algorithm requires 13 or more line correspondences to recover 27 coefficients of the trifocal tensor.
catadioptric omnidirectional camera. conventional video cameras have limited fields of view that make them restrictive in a variety of vision applications. there are several ways to enhance the field of view of an imaging system. however, the entire imaging system must have a single effective viewpoint to enable the generation of pure perspective images from a sensed image. a new camera with a hemispherical field of view is presented. two such cameras can be placed back-to-back, without violating the single viewpoint constraint, to arrive at a truly omnidirectional sensor. results are presented on the software generation of pure perspective images from an omnidirectional image, given any user-selected viewing direction and magnification. the paper concludes with a discussion on the spatial resolution of the proposed camera.
structure from linear or planar motions. we recently demonstrated a new approach to multiframe structure from motion from point features which, in the appropriate domain, provably reconstructs structure and motion correctly. the algorithm works for general motion and large perspective effects. in this paper, we describe how to adapt our approach to translational motion lying along a line or in a plane, with arbitrary rotations. an analysis of the bas--relief effect for multiple--motion sequences is also presented.
a new structure--from--motion ambiguity. this paper demonstrates the existence of a new, approximate, intrinsic ambiguity in euclidean structure from motion (sfm) which occurs as generically as the bas-relief ambiguity but, unlike it, strengthens for scenes with more depth variation. the ambiguity does not occur in projective sfm, but the reasons for this make projective reconstructions more likely to have large errors. our analysis gives a semiquantitative characterization of the least-squares error surface over a domain complementary to that analyzed by jepson, heeger, and maybank. as part of our analysis, we show that the least-squares error for infinitesimal motion¿the optical-flow error¿gives a good approximation to the least-squares error for moderate finite motions. we propose that many high-error local minima occur for epipoles in or near the image. we also establish the existence of a new local minimum in minimizing over the rotation, given the translation direction.
lafter: lips and face real-time tracker. this paper describes an active-camera real-time system for tracking, shape description, and classification of the human face and mouth using only an sgi indy computer. the system is based on use of 2-d blob features, which are spatially-compact clusters of pixels that are similar in terms of low-level image properties. patterns of behavior (e.g., facial expressions and head movements) can be classified in real-time using hidden markov model (hmm) methods. the system has been tested on hundreds of users and has demonstrated extremely reliable and accurate performance. typical classification accuracies are near 100 %
connectionist networks for feature indexing and object recognition. feature indexing techniques are promising for object recognition because of their ability to eliminate many feature set matches from consideration without much computation. this work exploits another property of such techniques. they have inherently parallel structure and connectionist network formulations are easy to develop. once indexing has been performed, a voting scheme such as geometric hashing [lamdan et al. 1990] can be used to generate object hypotheses in parallel. we give a framework for the connectionist implementation for such indexing and recognition techniques. with sufficient processing elements, recognition can be performed in a small number of time steps. the number of processing elements necessary to achieve peak performance and the fan-in/fan-out required for the processing elements is determined. these techniques have been simulated on a conventional architecture with good results.
affine invariant detection: edges, active contours, and segments. in this paper we undertake a systematic investigation of affine invariant object detection. edge detection is first presented from the point of view of the affine invariant scale-space obtained by curvature based motion of the image level-sets. in this case, affine invariant edges are obtained as a weighted difference of images at different scales. we then introduce the affine gradient as the simplest possible affine invariant differential function which has the same qualitative behavior as the euclidean gradient magnitude. these edge detectors are the basis both to extend the affine invariant scale-space to a complete affine flow for image denoising and simplification, and to define affine invariant active contours for object detection and edge integration. the active contours are obtained as a gradient flow in a conformally euclidean space defined by the image on which the object is to be detected. that is, we show that objects can be segmented in an affine invariant manner by computing a path of minimal weighted affine distance,the weight being given by functions of the affine edge detectors. the geodesic path is computed via an algorithm which allows to simultaneously detect any number of objects independently of the initial curve topology.
pedestrian detection using wavelet templates. this paper presents a trainable object detection architecture that is applied to detecting people in static images of cluttered scenes. this problem poses several challenges. people are highly non-rigid objects with a high degree of variability in size, shape, color, and texture. unlike previous approaches, this system learns from examples and does not rely on any a priori (handcrafted) models or on motion. the detection technique is based on the novel idea of the wavelet template that defines the shape of an object in terms of a subset of the wavelet coeficients of the image. it is invariant to changes in color and texture and can be used to robustly define a rich and complex class of objects such as people. we show how the invariant properties and computational eficiency of the wavelet template make it an effective tool for object detection.
training support vector machines: an application to face detection. we investigate the application of support vector machines (svms) in computer vision. svm is a learning technique developed by v. vapnik and his team (at\&t bell labs.) that can be seen as a new method for training polynomial, neural network, or radial basis functions classifiers. the decision surfaces are found by solving a linearly constrained quadratic programming problem. this optimization problem is challenging because the quadratic form is completely dense and the memory requirements grow with the square of the number of data points.we present a decomposition algorithm that guarantees global optimality, and can be used to train svm's over very large data sets. the main idea behind the decomposition is the iterative solution of sub-problems and the evaluation of optimality conditions which are used both to generate improved iterative values, and also establish the stopping criteria for the algorithm.we present experimental results of our implementation of svm, and demonstrate the feasibility of our approach on a face detection problem that involves a data set of 50,000 data points.
image velocity estimation from trajectory surface in spatiotemporal space. a new framework and method, based on image motion trajectories in spatiotemporal space (x-y-t space), are proposed to estimate image velocity from an image sequence. we focus on the surfaces of the trajectories in the x-y-t space formed by the edges and contours of moving objects and obtain image velocity from the orientation of the intersection line formed by tangent planes on the trajectories. the proposed method includes two hough transforms to detect the most dominant orientation in all possible intersection lines and reliably produces the dominant translational image velocity semi-locally. also, the confidence measure of estimates is defined to decide the optimal size of patch that suppresses the aperture problem. experimental results from several synthetic and real image sequences are presented to verify the effectiveness of the method and to confirm its robustness against noise and occlusion.
non-parametric similarity measures for unsupervised texture segmentation and image retrieval. in this paper we propose and examine non-parametric statistical tests to define similarity and homogeneity measures for textures. the statistical tests are applied to the coefficients of images filtered by a multi-scale gabor filter bank. we will demonstrate that these similarity measures are useful for both, texture based image retrieval and for unsupervised texture segmentation, and hence offer an unified approach to these closely related tasks. we present results on brodatz-like micro-textures and a collection of real-word images.
object detection using hierarchical mrf and map estimation. this paper presents a new scale, position and orientation invariant approach to object detection. the proposed method first chooses attention regions in an image based on the region detection result on the image. within the attention regions, the method then detects targets using a novel object detection algorithm that combines template matching methods with feature-based methods via hierarchical mrf and map estimation. hierarchical mrf and map estimation provide a flexible framework to incorporate various visual clues. the combination of template matching and feature detection helps to achieve robustness against complex backgrounds and partial occlusions in object detection. experimental results are given in the paper.
a fast and flexible statistical method for text extraction in document pages. this paper describes a fast and flexible method for extracting text regions from a document page containing text, graphics, and pictures. such regions can be given as an input to an ocr system. the user fixes two parameters, the minimum width w of the text to be detected, and the precision \epsilon needed (both expressed as a percentage of the image width), according to the implementation needs. the method works by subdividing the page into overlapping columns whose width and inter-shift depend on w and \epsilon, and by performing text lines extraction on each column separately. successively, a statistical analysis of the text line elements found in each column is performed, and they are connected to form complete text lines. finally, related pieces of text are merged into blocks so that a sensible reading order is provided for the ocr system. the algorithm is very fast, is able to work on low-resolution document pages and is robust against skew. the algorithm is also very flexible: no assumptions are made on the layout of the document, the shape of the text regions, and the font size and style; the main assumption is that the background is uniform and the text approximately horizontal. despite the statistical nature of the method, a single line of text of a certain font size is generally sufficient to warrant detection. experimental results are shown which demonstrate the effectiveness of the method on several different kinds of documents.
uncalibrated 1d projective camera and 3d affine reconstruction of lines. we describe a linear algorithm to recover 3d affine shape/motion from line correspondences over three views with uncalibrated affine cameras. the key idea is the introduction of a one-dimensional projective camera. this converts the 3d affine reconstruction of "lines" into 2d projective reconstruction of "points". using the full tensorial representation of three uncalibrated 1d views, we prove that the 3d affine reconstruction of lines from minimal data is unique up to a re-ordering of the views. 3d affine line reconstruction can be performed by properly rescaling image coordinates instead of using projection matrices. the algorithm is validated on both simulated and real image sequences.
a factorization method for affine structure from line correspondences. a family of structure from motion algorithms called the factorization method has been recently developed from the orthographic projection model to the affine camera model. all these algorithms are limited to handling only point features of the image stream. we propose in this paper an algorithm for the recovery of shape and motion from line correspondences by the factorization method with the affine camera. instead of one step factorization for points, a multi-step factorization method is developed for lines based on the decomposition of the whole shape and motion into three separate substructures. each of these substructures can then be linearly solved by factorizing the appropriate measurement matrices. it is also established that affine shape and motion with uncalibrated affine cameras can be achieved with at least seven lines over three views, which extends the previous results of koenderink and van doorn for points to lines.
panoramic mosaics by manifold projection. as the field of view of a picture is much smaller than our own visual field of view, it is common to paste together several pictures to create a panoramic mosaic having a larger field of view. images with a wider field of view can be generated by using fish-eye lens, or panoramic mosaics can be created by special devices which rotate around the camera's optical center (quicktime vr, surround video), or by aligning, and pasting, frames in a video sequence to a single reference frame. existing mosaicing methods have strong limitations on imaging conditions, and distortions are common. manifold projection enables the creation of panoramic mosaics from video sequences under more general conditions, and in particular the unrestricted motion of a hand-held camera. the panoramic mosaic is a projection of the scene into a virtual manifold whose structure depends on the camera's motion. this manifold is more general than the customary projections onto a single image plane or onto a cylinder. in addition to being more general than traditional mosaics, manifold projection is also computationally efficient, as the only image deformations used are image plane translations and rotations. real-time, software only, implementation on a pentium-pc, proves the superior quality and speed of this approach.
closed-loop object recognition using reinforcement learning. current computer vision systems whose basic methodology is open-loop or filter type typically use image segmentation followed by object recognition algorithms. these systems are not robust for most real-world applications. in contrast, the system presented here achieves robust performance by using reinforcement learning to induce a mapping from input images to corresponding segmentation parameters. this is accomplished by using the confidence level of model matching as a reinforcement signal for a team of learning automata to search for segmentation parameters during training. the use of the recognition algorithm as part of the evaluation function for image segmentation gives rise to significant improvement of the system performance by automatic generation of recognition strategies. the system is verified through experiments on sequences of indoor and outdoor color images with varying external conditions.
randomness and geometric features in computer vision. it is often necessary to handle randomness and geometry in computer vision, for instance to match and fuse together noisy geometric features such as points, lines or 3d frames, or to estimate a geometric transformation from a set of matched features. however, the proper handling of these geometric features is far more difficult than for points, and a number of paradoxes can arise. we analyse in this article three basic problems: (1) what is a uniform random distribution of features, (2) how to define a distance between features, and (3) what is the ``mean feature'' of a number of feature measurements, and we propose generic methods to solve them.
orientation diffusions. diffusions provide a convenient way of smoothing noisy brightness images, of analyzing images at multiple scales, and of enhancing discontinuities. some quantities of interest in computer vision are defined on curved manifolds; typical examples are orientation and hue that are defined on the circle. generalizing diffusions to orientation is not straightforward, especially in the case where a discrete implementation is sought. an example of what may go wrong is presented. a method is proposed to define diffusions of orientation-like quantities. first a definition in the continuum is discussed, then a discrete orientation diffusion is proposed. the behavior of such diffusions is explored both analytically and experimentally. it is shown how such orientation diffusions contain a nonlinearity that is reminiscent of edge-process and anisotropic diffusion. a number of open questions are proposed at the end.
optimal selection of camera parameters for recovery of depth from defocused images. in the depth from defocus (dfd) method, two defocused images of a scene are obtained by capturing the scene with different sets of camera parameters. an arbitrary selection of the camera settings can result in observed images whose relative blurring is insufficient to yield a good estimate of the depth. in this paper, we study the effect of the degree of relative blurring on the accuracy of the estimate of the depth by addressing the dfd problem in a maximum likelihood-based framework. we propose a criterion for optimal selection of camera parameters to obtain an improved estimate of the depth. the optimality criterion is based on the cramer-rao bound of the variance of the error in the estimate of blur. simulations as well as experimental results on real images are presented for validation.
the feret evaluation methodology for face-recognition algorithms. two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems. the face recognition technology (feret) program has addressed both issues through the feret database of facial images and the establishment of the feret tests. to date, 14,126 images from 1199 individuals are included in the feret database, which is divided into development and sequestered portions. in september 1996, the feret program administered the third in a series of feret face-recognition tests. the primary objectives of the third test were to (1) assess the state of the art, (2) identify future areas of research, and (3) measure algorithm performance on large databases.
a direct method for stereo correspondence based on singular value decomposition. this paper proposes a new algorithm for matching point features across pairs of images. despite the well-known combinatorial complexity of the problem, this work shows that an acceptably good solution can be obtained directly by singular value decomposition of an appropriate correspondence strength matrix. the approach draws from the method proposed previously but, besides suggesting its usefulness for stereo matching, in this work a correlation-weighted proximity function is used as correspondence strength to specifically cater for real images.
a stratified approach to metric self-calibration. camera calibration is essential to many computer vision applications. in practice this often requires cumbersome calibration procedures to be carried out regularly. in the last few years a lot of work has been done on self-calibration of cameras, ranging from weak calibration to metric calibration. it has been shown that a metric calibration of the camera setup (up to scale) was possible based on the rigidity of the scene only. in this paper a stratified approach is proposed which gradually retrieves the metric calibration of the camera setup. starting from an uncalibrated image sequence the projective calibration is retrieved first. in projective space the plane at infinity is then identified yielding the affine calibration. this is achieved using a constraint which can be formulated between any two arbitrary images of the sequence. once the affine calibration is known the upgrade to metric is easily obtained through linear equations.
epipolar geometry and linear subspace methods: a new approach to weak calibration. this paper addresses the problem of estimating the epipolar geometry from point correspondences between two images taken by uncalibrated perspective cameras. it is shown that jepson&lsquo;s and heeger&lsquo;s linear subspace technique for infinitesimal motion estimation can be generalized to the finite motion case by choosing an appropriate basis for projective space. this yields a linear method for weak calibration. the proposed algorithm has been implemented and tested on both real and synthetic images, and it is compared to other linear and non-linear approaches to weak calibration.
object detection and localization by dynamic template warping. a simple method is presented for detecting, localizing and recognizing instances of classes of objects, while accommodating a wide variation in an object's pose. the method utilizes a small two-dimensional template that is warped into an image, and converts localization to a one-dimensional sub-problem, with the search for a match between image and template executed by dynamic programming. for roughly cylindrical objects (like heads), the method recovers three of the six degrees of freedom of motion (2 translation, 1 rotation), and accommodates two more degrees of freedom in the search process (1 rotation, 1 translation). experiments demonstrate that the method provides an efficient search strategy that outperforms normalized correlation. this is demonstrated in the example domain of face detection and localization, and can extended to more general detection tasks. an additional technique recovers rough object pose from the match results, and is used in a two stage recognition experiment in conjunction with maximization of mutual information.
automated model acquisition from range images with view planning. we present an incremental system that builds accurate cad models of objects from multiple range images. using a hybrid of surface mesh and volumetric representations, the system creates a "water-tight" 3d model at each step of the modeling process, allowing reasonable models to be built from a small number of views. we also present a method that can be used to plan the next view and reduce the number of scans needed to recover the object. results are presented for the creation of 3d models of a computer game controller, a hip joint prosthesis, and a mechanical strut.
vision for a smart kiosk. we describe a novel computer vision application: vision-based human sensing for a smart kiosk interface. a smart kiosk is a free-standing information dispensing computer appliance capable of engaging in public interactions with multiple people. vision sensing is a critical component of the kiosk interface, where it is used to determine the context for the interaction. we present a taxonomy of vision problems for a kiosk interface and describe a prototype kiosk which uses color stereo tracking and graphical output to interact with several users.
constrained phase congruency: simultaneous detection of interest points and of their scales. a novel feature detector -- the constrained phase congruency transform (cpct) is introduced. it simultaneously detects interest points as well as their scale in various orientations. the cpct is especially important in registration applications: the local transformation between interest points can be determined based on their orientational scales. the cpct detects the features in mach bands and in sinusoidal waves. this cannot be done simply by looking for local maxima in intensity gradient nor by looking for local energy maxima. i conjecture that constraining the general phase congruency is sufficient for feature detection. the correct detection of features' location and of their scale is demonstrated. the robustness of the cpct is achieved by constraining the local phase. only four easy-to-detect phases are used in the computations. they correspond to symmetry and anti-symmetry in their neighborhood. the scale at any location and orientation is determined by the scale of the channel that conforms to the constraints and maximizes energy.
fast binary image processing using binary decision diagrams. many classical image processing tasks can be realized as evaluations of a boolean function over subsets of an image. for instance, the simplicity test used in 3d thinning requires examining the 26 neighbors of each voxel and computing a single boolean function of these inputs. in this article, we show how binary decision diagrams can be used to produce automatically very efficient and compact code for such functions. the total number of operations performed by a generated function is at most one test and one branching for each input value (e.g., in the case of 3d thinning, 26 tests and branchings). at each stage, the function is guaranteed to examine only the pertinent input data, i.e., the values which affect the result. as an example, we consider the 3d simplicity test in digital topology, and thinning processes. we produce functions much faster than our previously optimized implementations and than any other implementation we know of. in the case of 3d simplicity test, on average, at each voxel only 8.7 neighboring voxel values are examined.
modeling clutter and context for target detection in infrared images. in order to reduce false alarms and to improve the target detection performance of an automatic target detection and recognition system operating in a cluttered environment, it is important to develop the models not only for man-made targets but also of natural background clutters. because of the high complexity of natural clutters, this clutter model can only be reliably built through learning from real examples. if available, contextual information that characterizes each training example can be used to further improve the learned clutter model. in this paper, we present such a clutter model aided target detection system. emphases are placed on two topics: (1) learning the background clutter model from sensory data through a self-organizing process, (2) reinforcing the learned clutter model using contextual information.
inferring body pose without tracking body parts. abstract a novel approach for estimating articulated body posture and motion from monocular video sequences is proposed. human pose is defined as the instantaneous two dimensional configuration (i.e., the projection onto the image plane) of a single articulated body in terms of the position of a predetermined set of joints. first, statistical segmentation of the human bodies from the background is performed and low-level visual features are found given the segmented body shape. the goal is to be able to map these, generally low level, visual features to body configurations. the system estimates different mappings, each one with a specific cluster in the visual feature space. given a set of body motion sequences for training, unsupervised clustering is obtained via the expectation maximation algorithm. then, for each of the clusters, a function is estimated to build the mapping between low-level features to 3d pose. currently this mapping is modeled by a neural network. given new visual features, a mapping from each cluster is performed to yield a set of possible poses. from this set, the system selects the most likely pose given the learned probability distribution and the visual feature similarity between hypothesis and input. performance of the proposed approach is characterized using a new set of known body postures, showing promising results.
3d trajectory recovery for tracking multiple objects and trajectory guided recognition of actions. abstract a mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3d trajectory estimation), and high-level (action recognition) processes. it is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. a novel extended kalman filter formulation is used in estimating the relative 3d motion trajectories up to a scale factor. the recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. conversely, higher-level mechanisms provide feedback that allows the system to reliably segment and maintain the tracking of moving objects before, during, and after occlusion. the 3d trajectory, occlusion, and segmentation information are utlized in extracting stabilized views of the moving object. trajectory-guided recognition (tgr) is proposed as a new and efficient method for adaptive classification of action. the tgr approach is demonstrated using ``motion history images'''' that are then recognized via a mixture of gaussian classifier. the system was tested in recognizing various dynamic human outdoor activities; e.g., running, walking, roller blading, and cycling. experiments with synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.
a general filter for measurements with any probability distribution. the kalman filter is a very efficient optimal filter, however it has the precondition that the noises of the process and of the measurement are gaussian. the authors introduce 'the general distribution filter' which is an optimal filter that can be used even where the distributions are not gaussian. an efficient practical implementation of the filter is possible where the distributions are discrete and compact or can be approximated as such.
affine structure and photometry. motion of an observer relative to objects in a scene provides information about the structure of the scene. changing patterns of shading due to motion relative to the light source provide information about surface structure, albedos, and light sources. one can stratify this photometric information into affine, unitary, and metric structure, much like the stratification of structure from motion. for lambertian surfaces, if either motion or photometry give us more than affine structure, the two cues can be combined to yield full metric information. edge constraints plus unitary photometry also give us full metric photometry. affine structure alone contains much of the quantitative structure information, allowing us to judge such things as the ordinal relationships between the albedos.
optimal servoing for active foveated vision. foveated vision and two-mode tracking, as inspired by the human oculomotor system, are often used in active vision system. the purpose of this paper is to provide answers to the following basic questions which arise from implementations. first, is it beneficial to have foveated vision and what is the optimal size of the foveal window? second, is there a need for two control mechanisms (smooth pursuit and saccade) for improved performance and how can one efficiently switch between them? in order to do so, a setup is proposed in which these strategies can be evaluated in a systematic manner. it is shown that the fovea appears as a compromise between the tightness of the tracking specifications and computational constraints. introducing a model for the later and postulating some a priori knowledge of the target behavior, it is possible to compute the size of the fovea in an optimal way. as a by-product, "smooth-pursuit" can be defined in a natural way, and the use of a two-mode tracking scheme is justified. the second mode, i.e. "saccadic control", aims at re-centering the target on the fovea so that the smooth pursuit controller can continue to operate. it is shown that a control strategy can indeed be defined so that this objective can be met under appropriate operating conditions.
velocity and disparity cues for robust real-time binocular tracking. we have designed and implemented a real-time binocular tracking system which uses two independent cues commonly found in the primary functions of biological visual systems to robustly track moving targets in complex environments, without a-priori knowledge of the target shape or texture: a fast optical flow segmentation algorithm quickly locates independently moving objects for target acquisition and provides a reliable velocity estimate for smooth tracking. in parallel, target position is generated from the output of a zero-disparity filter where a phase-based disparity estimation technique allows dynamic control of the camera vergence to adapt the horopter geometry to the target location. the system takes advantage of the optical properties of our custom-designed foveated wide-angle lenses, which exhibit a wide field of view along with a high resolution fovea. methods to cope with the distortions introduced by the space-variant resolution, and a robust real-time implementation on a high performance active vision head are presented.
robust recovery of camera rotation from three frames. computing camera rotation from image sequences can be used for image stabilization, and when the camera rotation is known the computation of translation and scene structure are much simplified as well. a robust approach for recovering camera rotation is presented, which does not assume any specific scene structure (e.g. no planar surface is required), and which avoids prior computation of the epipole. given two images taken from two different viewing positions, the rotation matrix between the images can be computed from any three homgraphy matrices. the homographies are computed using the trilinear tensor which describes the relations between the projections of a 3d point into three images. the entire computation is linear for small angles, and is therefore fast and stable. iterating the linear computation can then be used to recover larger rotations as well.
neural network-based face detection. we present a neural network-based upright frontal face detection system. a retinally connected neural network examines small windows of an image and decides whether each window contains a face. the system arbitrates between multiple networks to improve performance over a single network. we present a straightforward procedure for aligning positive face examples for training. to collect negative examples, we use a bootstrap algorithm, which adds false detections into the training set as training progresses. this eliminates the difficult task of manually selecting nonface training examples, which must be chosen to span the entire space of nonface images. simple heuristics, such as using the fact that faces rarely overlap in images, can further improve the accuracy. comparisons with several other state-of-the-art face detection systems are presented, showing that our system has comparable performance in terms of detection and false-positive rates.
analyzing articulated motion using expectation-maximization. we present a novel application of the expectation-maximization algorithm to the global analysis of articulated motion. the approach utilizes a kinematic model to constrain the motion estimates, producing a segmentation of the flow field into parts with different articulated motions. experiments with synthetic and real images are described.
cylindrical rectification to minimize epipolar distortion. we propose anew rectification method for aligning epipolar lines of a pair of stereo images taken under any camera geometry. it effectively remaps both images onto the surface of a cylinder instead of a plane, which is used in common rectification methods. for a large set of camera motions, remapping to a plane has the drawback of creating rectified images that are potentially infinitely large and presents a loss of pixel information along epipolar lines. in contrast, cylindrical rectification guarantees that the rectified images are bounded for all possible camera motions and minimizes the loss of pixel information along epipolar line. the processes (e.g., stereo matching, etc.) subsequently applied to the rectified images are thus more accurate and general since they can accommodate any camera geometry.
efficient guaranteed search for gray-level patterns. we address the problem of locating a gray-level pattern in a gray-level image. the pattern can have been transformed by an affine transformation, and may have undergone some additional changes. we define a difference function based on comparing each pixel of the pattern with a window in the image, and search efficiently for transformations that minimize the difference function. the search is guaranteed: it will always find the transformation minimizing the difference function, and not get fooled by a local minimum; it is also efficient, in that it does not need to examine every transformation in order to achieve this guarantee. this technique can be applied to object location, motion tracking, optical flow, or block-based motion compensation in video image sequence compression (e.g., mpeg).
similarity queries in image database. query-by-content image database will be based on similarity, rater than on matching, where similarity is a measure that is defined and meaningful for every pair of images in the image space. since it is the human user that, in the end, has to be satisfied with the results of the query, it is natural to base the similarity measure that we will use on the characteristics of human similarity assessment. in the first part of this paper, we review some of these characteristics and define a similarity measure based on them. another problem that similarity-based databases will have to face is how to combine different queries into a single complex query. we present a solution based on three operators that are the analogous of the and, or, and not operators one uses in traditional databases. these operators are powerful enough to express queries of unlimited complexity, yet have a very intuitive behavior, making easy for the user to specify a query tailored to a particular need.
vector-valued active contours. a framework for object segmentation in vector-valued images is presented in this paper. the first scheme proposed is based on geometric active contours moving towards the objects to be detected in the vector-valued image. objects boundaries are obtained as geodesics or minimal weighted distance curves in a riemannian space. the metric in this space is given by a definition of edges in vector-valued images. the curve flow corresponding to the proposed active contours holds formal existence, uniqueness, stability, and correctness results. the techniques is applicable for example to color and texture images. the scheme automatically handles changes in the deforming curve topology. we conclude the paper presenting an extension of the color active contours which leads to a possible image flow for vector-valued image segmentation. the algorithm is based on moving each one of the image level-sets according to the proposed color active contours. this extension also shows the relation of the color geodesic active contours with a number of partial-differential-equations based image processing algorithms as anisotropic diffusion and shock filters.
on occluding contour artifacts in stereo vision. we study occluding contour artifacts in area-based stereo matching: they are false responses of the matching operator to the occlusion boundary and cause the objects extend beyond their true boundaries in disparity maps. most of the matching methods suffer from these artifacts; the effect is so strong that it cannot be ignored. we show what gives rise to the artifacts and design a matching criterion that accommodates the presence of occlusions as opposed to methods that identify and remove the artifacts. this approach leads to the problem of measurement contamination studied in statistics. we show that such a problem is hard given finite computational resources, unless more independent measurements directly related to occluding contours is available. what can be achieved is a substantial reduction of the artifacts, especially for large matching templates. reduced artifacts allow for easier hierarchical matching and for easy fusion of reconstructions from different viewpoints into a coherent whole.
complexity analysis of rbf networks for pattern recognition. the problem of non-parametric probability density function (pdf) estimation using radial basis function (rbf) neural networks is addressed here. we investigate two criteria, based on a modified kullback-leibler distance, that lead to an appropriate choice of the network architecture complexity. in the first criterion the modification consists in the addition of a term that penalizes complex architectures (mpl criterion). the second strategy involves the regularization of the network through the imposition of lower bounds on the standard deviation derived from conditions of existence of rejection tests (lbsd criterion). experimental results indicate that the mpl criterion outperforms the lbsd method.
quantitative measures of change based on feature organization: eigenvalues and eigenvectors. one important task of site monitoring is change detection from aerial images. change, in general, can be of various types. in this paper we address the problem of detecting change due to construction activity. specifically, we would like to know about new construction at a previously undeveloped site and possibly monitor its progress. model based approaches are not suited for this kind of change as it usually happens in unmodelled areas. since it is difficult to infer construction activity by predicting and verifying specific local features, we rely on more global statistical indicators. the thesis of this paper is that the change induced by human activity can be inferred from changes in the organization among the visual features. not only will the attributes of the individual image features change but also the relationships among these features will evolve. with the progress of construction we expect to see increased structure among the image features. we exploit this emerging structure, or organization, to infer change. in this paper, we propose four measures to quantify the global statistical properties of the individual features and the relationships among them. we base these measures on the theory of graph spectra. we provide extensive analysis of the robustness of these measures under various imaging conditions. we also demonstrate the ability of these organization based measures to discriminate between no development, onset of construction, and full development.
illumination distribution from shadows. the image irradiance of a three-dimensional object is known to be the function of three components: the distribution of light sources, the shape, and reflectance of a real object surface. in the past, recovering the shape and reflectance of an object surface from the recorded image brightness has been intensively investigated. on the other hand, there has been little progress in recovering illumination from the knowledge of the shape and reflectance of a real object. in this paper, we propose a new method for estimating the illumination distribution of a real scene from image brightness observed on a real object surface in that scene. more specifically, we recover the illumination distribution of the scene from a radiance distribution inside shadows cast by an object of known shape onto another object surface of known shape and reflectance. by using the occlusion information of incoming light, we are able to reliably estimate the illumination distribution of a real scene, even in a complex illumination environment.
name-it: association of face and name in video. this paper proposes a novel approach to extract meaningful content information from video by collaborative integration of image understanding and natural language processing. as an actual example, we developed a system that associates faces and names in videos, called name-it, which is given news videos as a knowledge source, then automatically extracts face and name association as content information. the system can infer the name of a given unknown face image, or guess faces which are likely to have the name given to the system. this paper explains the method with several successful matching results which reveal effectiveness in integrating heterogeneous techniques as well as the importance of real content information extraction from video, especially face-name association.
true multi-image alignment and its application to mosaicing and lens distortion correction. multiple images of a scene are related through 2d/3d view transformations and linear and non-linear camera transformations. in the traditional techniques to compute these transformations, especially the ones relying on direct intensity gradients, one image and its coordinate system have been assumed to be ideal and distortion free. in this paper, we present an algorithm for true multi-image alignment that does not rely on the measurements of a reference image being distortion free. the algorithm is developed to specifically align and mosaic images using parametric transformations in the presence of lens distortion. when lens distortion is present, none of the images can be assumed to be ideal. in our formulation, all the images are modeled as intensity measurements represented in their respective coordinate systems, each of which is related to an ideal coordinate system through an interior camera transformation and an exterior view transformation. the goal of the accompanying algorithm is to compute an image in the ideal coordinate system while solving for the transformations that relate the ideal system with each of the data images. key advantages of the technique presented in this paper are: (i) no reliance on one distortion free image, (ii) ability to register images and compute coordinate transformations even when the multiple images are of an extended scene with no overlap between the first and last frame of the sequence, and (iii) ability to handle linear and non-linear transformations within the same framework. results of applying the algorithm are presented for the correction of lens distortion, and creation of video mosaics.
stereo vision for view synthesis. we propose a new method for view synthesis from real images using stereo vision. the method does not explicitly model scene geometry, and enables fast and exact generation of synthetic views. we also re-evaluate the requirements on stereo algorithms for the application of view synthesis and discuss ways of dealing with partially occluded regions of unknown depth and with completely occluded regions of unknown texture. our experiments demonstrate that it is possible to efficiently synthesize realistic new views even from inaccurate and incomplete depth information.
stereo matching with non-linear diffusion. one of the central problems in stereo matching (and other image registration tasks) is the selection of optimal window sizes for comparing image regions. this paper addresses this problem with some novel algorithms based on iteratively diffusing support at different disparity hypotheses, and locally controlling the amount of diffusion based on the current quality of the disparity estimate. it also develops a novel bayesian estimation technique which significantly outperforms techniques based on area-based matching (ssd) and regular diffusion. we provide experimental results on both synthetic and real stereo image pairs.
combining greyvalue invariants with local constraints for object recognition. this paper addresses the problem of recognizing objects in large image databases. the method is based on local characteristics which are invariant to similarity transformations in the image. these characteristics are computed at automatically detected keypoints using the greyvalue signal. the method therefore works on images such as paintings for which geometry based recognition fails.due to the locality of the method, images can be recognized being given part of an image and in the presence of occlusions. applying a voting algorithm and semi-local constraints makes the method robust to noise, scene clutter and small perspective deformations. experiments show an efficient recognition for different types of images. the approach has been validated on an image database containing 1020 images, some of them being very similar by structure, texture or shape.
automatic line matching across views. the paper presents a new method for matching individual line segments between images. the method uses both grey-level information and the multiple view geometric relations between the images. for image pairs epipolar geometry facilitates the computation of a cross-correlation based matching score for putative line correspondences. for image triplets cross-correlation matching scores are used in conjunction with line transfer based on the trifocal geometry. algorithms are developed for both short and long range motion. in the case of long range motion the algorithm involves evaluating a one parameter family of plane induced homographies. the algorithms are robust to deficiencies in the line segment extraction and partial occlusion. experimental results are given for image pairs and triplets, for varying motions between views, and for different scene types. the three view algorithm eliminates all mismatches.
structure from multiple 2d affine correspondences without camera calibration. image motion induced by camera or object motion can be approximated locally by an affine coordinate transformation. we extract 3d information directly from the affine parameters, without camera calibration. the derivation relies on the following assumptions: the object is rigid, locally planar, and its local 3d motion is translation. these assumptions enable complete recovery of 3d structure, whereas it is impossible to compute the direction (and magnitude) of the motion. still, it is possible to distinguish between objects moving differently. explicit expressions for the structure and the motion indicators are given in terms of the 6 affine parameters, computed for each image patch. results of experiments on data with known ground truth are described.
coregistration of range and optical images using coplanarity and orientation constraints. a least-squares method simultaneously solves for the model-to-sensor-suite pose and sensor-to-sensor registration. the development is for a sensor-suite containing separate range and optical sensors. to address outliers and, more generally, match finding, a statistical method (median filtering) and a search method (local search) are developed. sensitivity to gaussian noise and the choice of initial pose estimates is investigated on synthetic data. both of the matching methods are demonstrated on real data.
photorealistic scene reconstruction by voxel coloring. a novel scene reconstruction technique is presented, different from previous approaches in its ability to cope with large changes in visibility and its modeling of intrinsic scene color and texture information. the method avoids image correspondence problems by working in a discretized scene space whose voxels are traversed in a fixed visibility ordering. this strategy takes full account of occlusions and allows the input cameras to be far apart and widely distributed about the environment. the algorithm identifies a special set of invariant voxels which together form a spatial and photometric reconstruction of the scene, fully consistent with the input images. the approach is evaluated with images from both inward-facing and outward-facing cameras.
a common framework for curve evolution, segmentation and anisotropic diffusio. in recent years, curve evolution has developed into an important tool in computer vision and has been applied to a wide variety of problems such as smoothing of shapes, shape analysis and shape recovery. the underlying principle is the evolution of a simple closed curve whose points move in the direction of the normal with prescribed velocity. a fundamental limitation of the method as it stands is that it cannot deal with important image features such as triple points. the method also requires a choice of an "edge-strength" function, defined over the image domain, indicating the likelihood of an object boundary being present at any point in the image domain. this implies a separate preprocessing step, in essence precomputing approximate boundaries in the presence of noise. one also has to choose the initial curve. it is shown here that the different versions of curve evolution used in computer vision together with the preprocessing step can be integrated in the form of a new segmentation functional which overcomes these limitations and extends curve evolution models. moreover, the numerical solutions obtained retain sharp discontinuities or "shocks", thus providing sharp demarcation of object boundaries.
a bayesian segmentation framework for textured visual images. this paper presents a new framework for segmentation of textured visual imagery. the proposed method consists of a bayesian formulation for labeling similar regions. similarity is defined via texture features obtained by gabor wavelets. multivariate gaussian distributions are employed to model the feature class-conditional densities, while the markov process is used to characterize the distributions of the region labeling due to each feature. a coarse nearest neighbor clustering is performed over the feature space to estimate the initial labelings. an iterative solution to the maximum a posteriori(map) estimation is developed, where the parameters of the prior distribution of region labels are estimated using the expectation-maximization(em) algorithm. finally, for man-made object segmentation, a region-growing procedure is used to analyze the classified texture regions by incorporating measures of local shape characteristics to obtain smooth boundaries and region homogeneity. results of the developed algorithm on real scene images are presented.
completion energies and scale. the detection of smooth curves in images and their completion over gaps are two important problems in perceptual grouping. in this study we examine the notion of completion energy of curve elements, showing and exploiting its intrinsic dependence on length and width scales. we introduce a fast method for computing the most likely completion between two elements, by developing novel analytic approximations and a fast numerical procedure for computing the curve of least energy. we then use our newly developed energies to find the most likely completions in images through a generalized summation of induction fields. this is done through multiscale procedures, i.e., separate processing at different scales with some interscale interactions. such procedures allow the summation of all induction fields to be done in a total of only o(n logn) operations, where n is the number of pixels in the image. more important, such procedures yield a more realistic dependence of the induction field on the length and width scales: the field of a long element is very different from the sum of the fields of its composing short segments.
subpixel image registration by estimating the polyphase decomposition of cross power spectrum. a method of registering images at subpixel accuracy has been proposed, which does not resort to interpolation. the method is based on the phase correlation method and is remarkably robust to correlated noise and uniform variations of luminance. we have shown that the cross power spectrum of two images, containing subpixel shifts, is a polyphase decomposition of a dirac delta function. by estimating the sum of polyphase components one can then determine subpixel shifts along each axis.
normalized cuts and image segmentation. we propose a novel approach for solving the perceptual grouping problem in vision. rather than focusing on local features and their consistencies in the image data, our approach aims at extracting the global impression of an image. we treat image segmentation as a graph partitioning problem and propose a novel global criterion, the normalized cut, for segmenting the graph. the normalized cut criterion measures both the total dissimilarity between the different groups as well as the total similarity within the groups. we show that an efficient computational technique based on a generalized eigenvalue problem can be used to optimize this criterion. we have applied this approach to segmenting static images, as well as motion sequences, and found the results to be very encouraging.
ridge's corner detection and correspondence. traditionally, corners are found along step edges. in this paper we present an alternative approach-corners along ridges/troughs and local minima points. these features seem to be more reliable for tracking. a new approach for sub-pixel localization of these corners is suggested, using a local approximation of the image surface.
a shock grammar for recognition. we confront the theoretical and practical difficulties of computing a representation for two-dimensional shape, based on shocks or singularities that arise as the shape's boundary is deformed. first, we develop subpixel local detectors for finding and classifying shocks. second, to show that shock patterns are not arbitrary but obey the rules of a grammar, and in addition satisfy specific topological and geometric constraints. shock hypotheses that violate the grammar or are topologically or geometrically invalid are pruned to enforce global consistency. survivors are organized into a hierarchical graph of shock groups computed in the reaction-diffusion space, where diffusion plays a role of regularization to determine the significance of each shock group. the shock groups can be functionally related to the object's parts, protrusions and bends, and the representation is suited to recognition: several examples illustrate its stability with rotations, scale changes, occlusion and movement of parts, even at very low resolutions.
area and length minimizing flows for shape segmentation. several active contour models have been proposed to unify the curve evolution framework with classical energy minimization techniques for segmentation, such snakes. the essential idea is to evolve a curve (in 20) or a surface (in 30) under constraints from image forces so that it clings to features of interest in an intensity image. recently the evolution equation has. been derived from first principles as the gradient flow that minimizes a modified length functional, tailored fo features such as edges. however, because the jlow may slow to converge in practice, a constant (hyperbolic) term is added to keep the curve/surface moving in the desired direction. in this paper, we provide a justification for this term based on the gradient flow derived from a weighted area functional, with image dependent weighting factor. when combined with the earlier modified length gradient flow we obtain a pde which offers number of advantages, as illustrated by several examples of shape segmentation on medical images. in many cases the weighted area flow may be used on its own, with significant computational savings.
further constraints on visual articulated motions. this paper derives what we term the euclidean hinge constraint for projective reconstruction of objects displaying articulated motion. a euclidean hinge is defined here to be an articulation axis with the proviso that any plane perpendicular to the articulation axis in link 1 has a coincident plane which is perpendicular to the articulation ads in link 2 and that these planes remain coincident under articulated motion. this constraint permits the independent projective reconstructions of two adjacent articulated links to be placed in a common frame. the constraint may be expressed mathematically by considering what we define as circular parallax. additionally the existence of a euclidean hinge permits the permits the projective frame to be brought nearer to a euclidean frame for the reconstructed object. a brief reprise of the method of articulation axis estimation is given together with a more extensive series of experimental results.
using a spectral reflectance model for the illumination-invariant recognition of local image structure. we represent local spatial structure in a color image using feature matrices that are computed from an image region. feature matrices contain significantly more information about local image structure than previous representations. although feature matrices are useful for surface recognition, this representation depends on the spectral properties of the scene illumination. using a finite dimensional linear model for surface spectral reflectance with the same number of parameters as the number of color bands, we show that illumination changes correspond to linear transformations of the feature matrices and that surface rotations correspond to circular shifts of the matrices. from these relationships we derive an algorithm for illumination and geometry invariant recognition of local surface structure. we demonstrate the algorithm with a series of experiments on images of real objects.
object recognition using invariant profiles. we derive a sensitivity analysis for moment invariants of multidimensional distributions. these invariants have many uses in computational systems and have recently been used for illumination-invariant recognition in color images. in this context, the sensitivity analysis predicts the response of moment invariants to partial occlusion. using the results of the sensitivity analysis, we develop a novel surface representation called the invariant profile which captures color distribution and spatial information while remaining invariant to the spectral content of the scene illumination. unlike previous representations, the recognition of invariant profiles does not require illumination correction. we demonstrate the sensitivity analysis and the use of invariant profiles for recognition with a set of experiments on color images.
video skimming and characterization through the combination of image and language understanding techniques. digital video is rapidly becoming important for education, entertainment, and a host of multimedia applications. with the size of the video collections growing to thousands of hours, technology is needed to effectively browse seg ments in a short time without losing the content of the video. we propose a method to extract the significant audio and video information and create a "skim" video which represents a very short synopsis of the original. the goal of this work is to show the utility of integrating lan guage and image understanding techniques for video skimming by extraction of significant information, such as specific objects, audio keywords and relevant video struc ture. the resulting skim video is much shorter, where com paction is as high as 20:1, and yet retains the essential content of the original segment.
motion from fixation. we study the problem of estimating rigid motion from a sequence of monocular perspective images obtained by navigating around an object while fixating a particular feature point. we cast the problem in the framework of "epipolar geometry", and propose a filter based upon implicit dynamical model for recursively estimating motion under the fixation constraint. this allows us to compare the quality of the estimates directly against the ones obtained assuming a general rigid motion simply by changing the geometry of the parameter space, while maintaining the same structure of the recursive estimator. we also present a closed-form static solution from two views, and a recursive estimator of the relative pose between the viewer and the scene.
reducing "structure from motion". the literature on recursive estimation of structure and motion from monocular image sequences comprises a large number of different models and estimation techniques. we propose a framework that allows us to derive and compare all models by following the idea of dynamical system reduction. the "natural" dynamic model, derived by the rigidity constraint and the perspective projection, is first reduced by explicitly decoupling structure (depth) from motion. then implicit decoupling techniques are explored, which consist of imposing that some function of the unknown parameters is held constant. by appropriately choosing such a function, not only can we account for all models seen so far in the literature, but we can also derive novel ones. casting all the different models in a common framework allows us to compare their geometric properties on common experimental grounds.
removing the bias from line detection. the extraction of curvilinear structures is an important low-level operation in computer vision. most existing operators use a simple model for the line that is to be extracted, i.e., they do not take into account the surroundings of a line. therefore, they will estimate a wrong line position whenever a line with different lateral contrast is extracted. in contrast, the algorithm proposed in this paper uses an explicit model for lines and their surroundings. by analyzing the scale-space behavior of a model line profile, it is shown how the bias that is induced by asymmetrical lines can be removed. thus, the algorithm is able to extract an unbiased line position and width, both with sub-pixel accuracy.
lens distortion calibration using point correspondences. this paper describes a new method for lens distortion calibration using only point correspondences in multiple views, without the need to know either the 3d location of the points or the camera locations. the standard lens distortion model is a model of the deviations of a real camera from the ideal pinhole or projective camera model.given multiple views of a set of corresponding points taken by ideal pinhole cameras there exist epipolar and trilinear constraints among pairs and triplets of these views. in practice, due to noise in the feature detection and due to lens distortion these constraints do not hold exactly and we get some error. the calibration is a search for the lens distortion parameters that minimize this error. using simulation and experimental results with real images we explore the properties of this method. we describe the use of this method with the standard lens distortion model, radial and decentering, but it could also be used with any other parametric distortion models. finally we demonstrate that lens distortion calibration improves the accuracy of 3d reconstruction.
model-based brightness constraints: on direct estimation of structure and motion. we describe a new direct method for estimating structure and motion from image intensities of multiple views. we extend the direct methods of horn and weldon [18] to three views. adding the third view enables us to solve for motion and compute a dense depth map of the scene, directly from image spatio-temporal derivatives in a linear manner without first having to find point correspondences or compute optical flow. we describe the advantages and limitations of this method which are then verified with experiments using real images
direct estimation of motion and extended scene structure from a moving stereo rig. we describe a new method for motion estimation and 3d reconstruction from stereo image sequences obtained by a stereo rig moving through a rigid world. we show that given two stereo pairs one can compute the motion of the stereo rig directly from the image derivatives (spatial and temporal). correspondences are not required. one can then use the images from both pairs combined to compute a dense depth map. the motion estimates between stereo pairs enable us to combine depth maps from all the pairs in the sequence to form an extended scene reconstruction and we show results from a real image sequence. the motion computation is a linear least squares computation using all the pixels in the image. areas with little or no contrast are implicitly weighted less so one does not have to explicitly apply a confidence measure.
towards accurate recovery of shape from shading under diffuse lighting. a new surface radiance model for diffuse lighting is presented which incorporates shadows, interreflections, and surface orientation. an algorithm is presented that uses this model to compute shape-from-shading under diffuse lighting. the algorithm is tested on both synthetic and real images, and is found to perform more accurately than the only previous algorithm for this problem.
critical motion sequences for monocular self-calibration and uncalibrated euclidean reconstruction. in this paper, sequences of camera motions that lead to inherent ambiguities in uncalibrated euclidean reconstruction or self-calibration are studied. our main contribution is a complete, detailed classification of these critical motion sequences (cms). the practically important classes are identified and their degrees of ambiguity are derived. we also discuss some practical issues, especially concerning the reduction of the ambiguity of a reconstruction.
runway obstacle detection by controlled spatiotemporal image flow disparity. this paper proposes a method for detecting obstacles on a runway by controlling their expected disparities. by approximating the runway by a planar surface, the initial model flow field (mff) corresponding to an obstacle-free runway is described by the data from on-board sensors (obs). the error variance of the initial mff is computed and used to estimate the mff. obstacles are detected by comparing the expected residual flow disparities with the residual flow field (rff) estimated after warping (or stabilizing) an image using the mff. expected temporal and spatial disparities are obtained from the use of the obs. this allows us to control the residual disparities by increasing the temporal baseline and/or by utilizing the spatial baseline if distant objects cannot be detected for a given temporal baseline. experimental results for two real flight image sequences are presented.
are textureless scenes recoverable? it is widely accepted that textureless surfaces cannot be recovered using passive sensing techniques. the problem is approached by viewing image formation as a fully three-dimensional mapping. it is shown that the lens encodes structural information of the scene within a compact three-dimensional space behind it. after analyzing the information content of this space and by using its properties we derive necessary and sufficient conditions for the recovery of textureless scenes. based on these conditions, a simple procedure for recovering textureless scenes is described. we experimentally demonstrate the recovery of three textureless surfaces, namely, a line, a plane, and a paraboloid. since textureless surfaces represent the worst case recovery scenario, all the results and the recovery procedure are naturally applicable to scenes with texture.
efficient image gradient-based object localisation and recognitio. this paper reports novel algorithms for the efficient localization and recognition of vehicles in traffic scenes, which eliminate the need for explicit symbolic feature extraction and matching. the algorithms make use of two a priori sources of knowledge about the scene and the objects: (i) the ground-plane constraint, and (ii) the fact that road vehicles are strongly rectilinear. the algorithms are demonstrated and tested using routine outdoor traffic images. success with a variety of vehicles demonstrates the efficiency and robustness of context-based computer vision in road traffic scenes. the limitations of the algorithms are also addressed in the paper.
shocks from images: propagation of orientation elements. the extraction of figure symmetry from image contours faces a number of fundamental difficulties: object symmetries are distorted due to (i) gaps in the bounding contour of a shape due to figure-ground blending, weak contrast edges, highlights, noise, etc.; (ii) an introduction of parts and occluders, and (iii) spurious edge elements due to surface markings, texture, etc. a framework for extracting such symmetries from real images is proposed based on the propagation of contour orientation information and the detection of four types of singularities (shocks) arising from the collision of propagating elements. in this paper, we show that an additional labeling of shocks based on whether the colliding wavefronts carry true orientation information (regular vs. rarefaction waves) allows a division of shocks into three sets: regular shocks are the partial shocks of partial contours as they remain invariant to the completion of the contour; semi-degenerate and degenerate shocks depict potential parts and gaps. finally, shocks altered due to spurious edges, occlusion, and gaps are recovered via a simulation of inter-penetrating waves generated at select shock groups which with the aid of the above shock labels leads to second and further generations of shocks.
a computational approach to steerable functions. we present a computational, group-theoretic approach to steerable functions. the approach is group-theoretic in that the treatment involves continuous transformation groups for which elementary lie group theory may be applied. the approach is computational in that the theory is constructive and leads directly to a procedural implementation. for functions that are steerable with $n$ finite number of basis functions under a $k$-parameter group, the procedure is efficient and is guaranteed to return the minimum number of basis functions. if the function is not steerable, a numerical implementation of the procedure could also be used to compute basis functions that approximately steer the function over a range of transformation parameters. examples of both applications are demonstrated.
non-rigid matching using demons. we present the concept of non-rigid matching based on demons, by reference to maxwell's demons. we contrast this concept with the more conventional viewpoint of attraction. we show that demons and attractive points are clearly distinct for large deformations, but also that they become similar for small displacements, encompassing techniques close to optical flow. we describe a general iterative matching method based on demons, and derive from it three different non-rigid matching algorithms, one using all the image intensities, one using only contours, and one for already segmented images. at last, we present results with synthesized and real deformations, with applications to computer vision and medical image processing.
comparison of approaches to egomotion computation. we evaluated six algorithms for computing egomotion from image velocities. we established benchmarks for quantifying bias and sensitivity to noise, and for quantifying the convergence properties of those algorithms that require numerical search. our simulation results reveal some interesting and surprising results. first, it is often written in the literature that the egomotion problem is difficult because translation (e.g., along the x-axis) and rotation (e.g., about the y-axis) produce similar image velocities. we found, to the contrary, that the bias and sensitivity of our six algorithms are totally invariant with respect to the axis of rotation. second, it is also believed by some that fixating helps to make the egomotion problem easier. we found, to the contrary, that fixating does not help when the noise is independent of the image velocities. fixation does help if the noise is proportional to speed, but this is only for the trivial reason that the speeds are slower under fixation. third, it is widely believed that increasing the field of view will yield better performance. we found, to the contrary, that this is not necessarily true.
boosting image retrieval. we present an approach for image retrieval using a very large number of highly selective features and efficient learning of queries. our approach is predicated on the assumption that each image is generated by a sparse set of visual &ldquo;causes&rdquo; and that images which are visually similar share causes. we propose a mechanism for computing a very large number of highly selective features which capture some aspects of this causal structure (in our implementation there are over 46,000 highly selective features). at query time a user selects a few example images, and the adaboost algorithm is used to learn a classification function which depends on a small number of the most appropriate features. this yields a highly efficient classification function. in addition we show that the adaboost framework provides a natural mechanism for the incorporation of relevance feedback. finally we show results on a wide variety of image queries.
an assessment of information criteria for motion model selection. rigid motion imposes constraints on the motion of image points between the two images. the matched points must conform to one of several possible constraints, such as that given by the fundamental matrix or image-image homography, and it is essential to know which model to fit to the data before recovery of structure, matching or segmentation can be performed successfully. this paper compares several model selection methods with a particular emphasis on providing a method that will work fully automatically on real imagery.
factorization methods for projective structure and motion. this paper describes a family of factorization-based algorithms that recover 3d projective structure and motion from multiple uncalibrated perspective images of 3d points and lines. they can be viewed as generalizations of the tomasi-kanade algorithm from affine to fully perspective cameras, and from points to lines. they make no restrictive assumptions about scene or camera geometry, and unlike most existing reconstruction methods they do not rely on `privileged' points or images. all of the available image data is used, and each feature in each image is treated uniformly. the key to projective factorization is the recovery of a consistent set of projective depths (scale factors) for the image points: this is done using fundamental matrices and epipoles estimated from the image data. we compare the performance of the new techniques with several existing ones, and also describe an approximate factorization method that gives similar results to svd-based factorization, but runs much more quickly for large problems.
autocalibration and the absolute quadric. the author describes a new method for camera autocalibration and scaled euclidean structure and motion, from three or more views taken by a moving camera with fixed but unknown intrinsic parameters. the motion constancy of these is used to rectify an initial projective reconstruction. euclidean scene structure is formulated in terms of the absolute quadric-the singular dual 3d quadric (4/spl times/4 rank 3 matrix) giving the euclidean dot-product between plane normals. this is equivalent to the traditional absolute conic but simpler to use. it encodes both affine and euclidean structure, and projects very simply to the dual absolute image conic which encodes camera calibration. requiring the projection to be constant gives a bilinear constraint between the absolute quadric and image conic, from which both can be recovered nonlinearly from m/spl ges/3 images, or quasi-linearly from m/spl ges/4. calibration and euclidean structure follow easily. the nonlinear method is stabler, faster, more accurate and more general than the quasi-linear one. it is based on a general constrained optimization technique-sequential quadratic programming-that may well be useful in other vision problems.
ego-motion estimation using optical flow fields observed from multiple cameras. in this paper, we consider a multi-camera vision system mounted on a moving object in a static three-dimensional environment. by using the motion flow fields seen by all of the cameras, an algorithm which does not need to solve the point-correspondence problem among the cameras is proposed to estimate the 3d ego-motion parameters of the moving object. our experiments have shown that using multiple optical flow fields obtained from different cameras can be very helpful for ego-motion estimation.
nonrigid motion analysis based on dynamic refinement of finite element models. in this paper, we propose new algorithms for accurate nonrigid motion tracking. given an initial model representing general knowledge of the object, a set of sparse correspondences, and incomplete or missing information about geometry or material properties, we can recover dense motion vectors using finite element models. the method is based on the iterative analysis of the differences between the actual and predicted behavior. large differences indicate that an object's properties are not captured properly by the model describing it. feedback from the images during the motion allows the refinement of the model by minimizing the error between the expected and true position of the object's points. these errors are due to flaws in the model parameter estimation such as geometry and material properties. unknown parameters are recovered using an iterative descent search for the best nonlinear finite element model that approximates nonrigid motion of the given object. during this search process, we not only estimate material properties, but also infer dense point correspondences from our initial set of sparse correspondences. thus, during tracking, the model is refined which, in turn, improves tracking quality. as a result, we obtain a more precise description of nonrigid motion. experimental results demonstrate the success of the proposed algorithm. the method was applied to man-made elastic materials and human skin to recover unknown elasticity, to complex 3d objects to find details of their geometry, and to a hand motion analysis application. our work demonstrates the possibility of accurate quantitative analysis of nonrigid motion in range image sequences with objects consisting of multiple materials and 3d volumes.
feature tracking from an image sequence using geometric invariants. in this paper two new feature tracking algorithms are proposed. in the first algorithm, a perspective camera model is used. making use of the projective invariant of barrett, and assuming the image feature points corresponding to 8 general points in space are tracked by a conventional method in the image sequence, the other feature points in the sequence can be tracked using a hough technique. correspondence between two reference images as required by the original barrett's invariant is not necessary. in the second algorithm, an affine camera model is assumed and the image feature points corresponding to 4 non-coplanar points in space are assumed tracked in the image sequence using a conventional method. these image points form the basis of affine coordinates in each image. after the correspondence of a fifth point is established between the first two images, the affine coordinates of all image points in the first images can be computed. as far as we know, this is the only algorithm which can transfer a point knowing only a single image. experiments showed that both algorithms gave highly accurate tracking results.
a framework for recognizing a facial image from a police sketch. we present a theory and practical computations for automatically matching a police artist sketch to a set of true photographs. we locate facial features in both the sketch as well as the set of photograph images. then, the sketch is photometrically standardized to facilitate comparison with a photo and then both the sketch and the photos are geometrically standardized. finally, for matching, eigenanalysis is employed. results using real police sketches and arrest photos are presented.
empirical bayesian em-based motion segmentation. a recent trend in motion-based segmentation has been to rely on statistical procedures derived from expectation-maximization (em) principles. em-based approaches have various attractives for segmentation, such as proceeding by taking non-greedy soft decisions with regards to the assignment of pixels to regions, or allowing the use of sophisticated priors capable of imposing spatial coherence on the segmentation. a practical difficulty with such priors is, however, the determination of appropriate values for their parameters. in this work, we exploit the fact that the em framework is itself suited for empirical bayesian data analysis to develop an algorithm that finds the estimates of the prior parameters which best explain the observed data. such an approach maintains the bayesian appeal of incorporating prior beliefs, but requires only a qualitative description of the prior, avoiding the requirement of a quantitative specification of its parameters. this eliminates the need for trial-and-error strategies for parameter determination and leads to better segmentations in less iterations.
a bootstrapping algorithm for learning linear models of object classes. flexible models of object classes, based on linear combinations of prototypical images, are capable of matching novel images of the same class and have been shown to be a powerful tool to solve several fundamental vision tasks such as recognition, synthesis and correspondence. the key problem in creating a specific flexible model is the computation of pixelwise correspondence between the prototypes, a task done until now in a semiautomatic way. in this paper we describe an algorithm that automatically bootstraps the correspondence between the prototypes. the algorithm - which can be used for 2d images as well as for 3d models - is shown to synthesize successfully a flexible model of frontal face images and a flexible model of handwritten digits.
structure and motion of curved 3d objects from monocular silhouettes. the silhouette of a smooth 3d object observed by a moving camera changes over time. past work has shown how surface geometry can be recovered using the deformation of the silhouette when the camera motion is known. this paper addresses the problem of estimating both the full euclidean surface structure and the camera motion from a dense set of silhouettes captured under orthographic or scaled orthographic projection. the approach relies on a viewpoint-invariant representation of curves swept by viewpoint-dependent features such as bitangents, inflections and contour points with parallel tangents. feature points, which form stereo frontier points between non-consecutive images, are matched using this representation. the camera's angular velocity is computed from constraints derived from this correspondence along with the image velocity of these features. from the angular velocity, the epipolar geometry is ascertained, and infinitesimal motion frontier points can be detected. in turn, the motion of these frontier points constrains the translation component of camera motion. finally, the surface is reconstructed using established techniques once the camera motion has been estimated.
blurring strategies for image segmentation using a multiscale linking model. multiscale approaches are an invaluable tool for image segmentation. a vast amount of research has been devoted to the construction of different multiscale representations of an image. in this paper we use the `hyperstack'--a multiscale linking model for image segmentation--for an in-depth comparison of four different scale space generators with respect to segmentation results. we consider the linear (gaussian) scale space both in the spatial and the fourier domain, the variable conductance diffusion according to the perona & malik equation, and the euclidean shortening flow. we have done experiments on mr images of the brain, for which a gold standard is available. the hyperstack proofs to be rather insensitive to the underlying scale space generator.
determining correspondences and rigid motion of 3-d point sets with missing data. this paper addresses the general 3-d rigid motion problem, where the point correspondences and the motion parameters between two sets of 3-d points are to be recovered. the existence of missing points in the two sets is the most difficult problem. we first show a mathematical symmetry in the solutions of rotation parameters and point correspondences. a closed-form solution based on the correlation matrix eigenstructure decomposition is proposed for correspondence recovery with no missing points. using a heuristic measure of point pair affinity derived from the eigenstructure, a weighted bipartite matching algorithm is developed to determine the correspondences in general cases where missing points occur. the use of the affinity heuristic also leads to a fast outlier removal algorithm, which can be run iteratively to refine the correspondence recovery. simulation results and experiments on real images are shown in both ideal and general cases.
illumination and geometry invariant recognition of texture in color images. we develop a method for recognizing color texture independent of rotation, scale, and illumination. color texture is modeled using spatial correlation functions defined within and between sensor bands. using a linear model for surface spectral reflectance with the same number of parameters as the number of sensor classes, we show that illumination and geometry changes in the scene correspond to a linear transformation of the correlation functions and a linear transformation of their coordinates. a several step algorithm which includes scale estimation and correlation moment computation is used to achieve the invariance. the key to the method is the new result that illumination and geometry changes in the scene correspond to a specific transformation of correlation function zernike moment matrices. these matrices can be estimated from a color image. this relationship is used to derive an efficient algorithm for recognition. the algorithm is substantiated using classification results on over 200 images of color textures obtained under various illumination conditions and geometric configurations.
extracting surface textures and microstructures from multiple aerial images. we present a surface texture and microstructure extraction system to provide added realism in visualization and virtual reality applications. the system uses multiple images, 3-d models and camera information, in addition to knowledge about man-made structures, to cope with problems such as perspective distortion, data deficiency, and corruption caused by shadows and occlusions. combined with the ascender site modeling system~\cite{collins_iuw} and scene rendering algorithms, the system is typically useful for urban site model refinement and visualization.
minimal operator set for passive depth from defocus. a fundamental problem in depth from defocus is the measurement of relative defocus between images. we propose a class of broadband operators that, when used together, provide invariance to scene texture and produce accurate and dense depth maps. since the operators are broadband, a small number of them are sufficient for depth estimation of scenes with complex textural properties. experiments are conducted on both synthetic and real scenes to evaluate the performance of the proposed operators. the depth detection gain error is less than 1%, irrespective of texture frequency. depth accuracy is found to be 0.5/spl sim/1.2% of the distance of the object from the imaging optics.
smoothness in layers: motion segmentation using nonparametric mixture estimation. grouping based on common motion, or ``common fate'' provides a powerful cue for segmenting image sequences. recently a number of algorithms have been developed that successfully perform motion segmentation by assuming that the motion of each group can be described by a low dimensional parametric model (e.g. affine). typically the assumption is that motion segments correspond to planar patches in 3d undergoing rigid motion. here we develop an alternative approach, where the motion of each group is described by a smooth dense flow field and the stability of the estimation is ensured by means of a prior distribution on the class of flow fields. we present a variant of the em algorithm that can segment image sequences by fitting multiple smooth flow fields to the spatiotemporal data. using the method of green's functions, we show how the estimation of a single smooth flow field can be performed in closed form, thus making the multiple model estimation computationally feasible. furthermore, the number of models is estimated automatically using similar methods to those used in the parametric approach. we illustrate the algorithm's performance on synthetic and real image sequences.
a unified mixture framework for motion segmentation: incorporating spatial coherence and estimating the number of models. describing a video sequence in terms of a small number of coherently moving segments is useful for tasks ranging from video compression to event perception. promising approach is to view the motion segmentation problem in a mixture estimation framework. however, existing formulations generally use only the motion data and thus fail to make use of static cues when segmenting the sequence. furthermore, the number of models is either specified in advance or estimated outside the mixture model framework. in this work we address both of these issues. we show how to add spatial constraints to the mixture formulations and present a variant of the em algorithm that makes use of both the form and the motion constraints. moreover this algorithm estimates the number of segments given knowledge about the level of model failure expected in the sequence. the algorithm's performance is illustrated on synthetic and real image sequences.
nonlinear shape restoration for document images. previous researches on nonlinear shape restoration are based on the assumptions that the original shapes and distortions of the images have known formulations under certain conditions. the main contribution of this research is the development of a new restoration algorithm, called multi-steps restoration. the algorithm is based on a liner interpolation theory that is able to detect and restore nonlinear shape distortions in any irregular quadrilateral-shaped patterns. the main idea of the algorithm is the use of two-dimensional spline functions in bicubic, biquadratic, and/or bilinear models to approximate the three-dimensional nonlinear distortion curves. the performance of the approach shown by experiment is promising.
using local 3d structure for segmentation of bone from computer tomography images. in this paper we focus on using local 3d structure for segmentation. a tensor descriptor is estimated for each neighbourhood, i.e. for each voxel in the data set. the tensors are created from a combination of the outputs form a set of 3d quadrature filters. the shape of the tensors describe locally the structure of the neighborhood in terms of how much it is like a plane, a line, and a sphere. we apply this to segmentation of bone from computer tomography data (ct). traditional methods are based purely on gray-level value discrimination and have difficulties in recovering thin bone structures due to so called partial voluming, a problem which is present in all such sampled data. we illuminate the partial voluming problem by showing that thresholding creates complicated artifacts even if the signal is densely enough sampled and can be perfectly reconstructed. the unwanted effects of thresholding can be reduced by a change of the signal basis. we show that by using additional local structure information can significantly reduce the degree of sampling artifacts. evaluation of the method on a clinical case is presented, the segmentation of a human skull from a ct volume. the method shows that many of the thin bone structures which disappear in a pure thresholding can be recovered.
attention control for robot vision. focus of attention mechanisms for robot vision are discussed. a new method for neglecting low level filter responses from already modelled structures is presented. the method is based on a filtering technique termed normalized convolution. in one experiment, the robot is continuously moving its arm in the scene while tracking other objects. it is shown how the arm can be made ``invisible'' so that only the moving object of interest is detected. this makes tracking of objects much simpler. in another experiment, the attention of the system is shifted between objects by simply cancelling the mask of the object to be attended to. with this strategy the low level processes do not need to know the difference between a new object entering the scene and a mask being cancelled, and thus a complex communication structure between high and low levels is avoided.
physically based fluid flow recovery from image sequences. this paper presents an approach to measuring fluid flow from image sequences. the approach centers around a motion recovery algorithm that is based on principles from fluid mechanics: the algorithm is constrained so that recovered flows observe conservation of mass as well as physically motivated boundary conditions. empirical results are presented from application of the algorithm to fluid flows captured via transmittance imagery (i.e., radiographs). in these experiments, fluids seeded with tracers were driven through simple physical systems. the significance of this work is twofold. first, from a theoretical point of view it is shown how information derived from the physical behavior of fluids can be used to motivate a flow recovery algorithm. second, from an applications point of view the developed algorithm can be used to augment the tools that are available for the measurement of fluid dynamics; other imaged flows that observe compatible constraints might benefit in a similar fashion.
hyper-patches for 3d model acquisition and tracking. automatic 3d model acquisition and 3d tracking of simple objects under motion using a single camera is often difficult due to the sparsity of information from which to establish the model. we have developed an automatic scheme that first computes a simple pointalistic euclidean model of the object and then enriches this model using hyper-patches. these hyper-patches contain information on both the orientation and intensity pattern variation of roughly planar patches on an object. this information allows both the spatial and intensity distortions of the projected patch to be modelled accurately under 3d object motion. we show that hyper-patches not only can be computed automatically during model acquisition from a monocular image sequence, but that they are also extremely appropriate for the task of visual tracking.
local parallel computation of stochastic completion fields. we describe a local parallel method for computing the stochastic completion field introduced in an earlier paper\cite{williams}. the stochastic completion field represents the likelihood that a completion joining two contour fragments passes through any given position and orientation in the image plane. it is based upon the assumption that the prior probability distribution of completion shape can be modeled as a random walk in a lattice of discrete positions and orientations. the local parallel method can be interpreted as a stable finite difference scheme for solving the underlying fokker-planck equation identified by mumford\cite{mumford}. the resulting algorithm is significantly faster than the previously employed method which relied on convolution with large-kernel filters computed by monte carlo simulation. the complexity of the new method is o(n3m) while that of the previous algorithm was o(n4m2) (for an n x n image with m discrete orientations). perhaps most significantly, the use of a local method allows us to model the probability distribution of completion shape using stochastic processes which are neither homogenous nor isotropic. for example, it is possible to modulate particle decay rate by a directional function of local image brightnesses (i.e., anisotropic decay). the effect is that illusory contours can be made to respect the local image brightness structure. finally, we note that the new method is more plausible as a neural model since 1) unlike the previous method, it can be computed in a sparse, locally connected network; and 2) the network dynamics are consistent with psychophysical measurements of the time course of illusory contour formation.
rational discrete generalized cylinders and their application to shape recovery in medical images. generalized cylinders (gcs) are a popular representational tool in computer vision. in medical imaging, the curved axis gc is particularly applicable to a number of elongated physical structures such as vasculature, bone and bronchi. in many of these instances, it is necessary to recover curved-axis gcs with arbitrary cross-sections. it is also vital that these structures, once recovered, can be analyzed and visualized with off-the-shelf algorithms and software packages. such tools are usually designed to operate on the domain of polynomial or rational surfaces. unfortunately most extant, suitably versatile gc representations do not admit rational parameterizations. we develop an entirely rational b-spline representation for generalized cylinders with curved axes and arbitrary cross-section functions. we demonstrate how our representation can be used as a deformable model by extracting a rational gc from pre-segmented spinal data using a discrete, dynamic surface fit.
temporal classification of natural gesture and application to video coding. a method for the temporal classification of natural gesture from video imagery is presented. the work is motivated by recent developments in the theory of natural gesture which have identified several key temporal aspects of gesture important to communication. in particular, gesticulation during conversation can be coarsely characterized as periods of bi-phasic or tri-phasic gesture separated by a rest state. we first present an automatic procedure for hypothesizing plausible rest state configurations of a speaker. second, we develop a state-based parsing algorithm used to both select among candidate rest states and to parse an incoming video stream into bi-phasic and tri-phasic gestures. finally, we demonstrate the use of the bi-phasic/tri-phasic labeling to select semantically significant static images for low bandwidth coding of video of story-telling speakers.
gauging relational consistency and correcting structural errors. the aim of this paper is to provide a comparative evaluation of a number of contrasting approaches to relational matching. unique to this study is the way in which we show how a diverse family of algorithms relate to one-another using a common bayesian framework. broadly speaking there are two main aspects to this study. firstly we focus on the issue of how relational inexactness may be quantified. we illustrate that several popular relational distance measures can be recovered as specific limiting cases of the same bayesian consistency measure. the second aspect of our comparison concerns the way in which structural inexactness is controlled. we investigate three different realisations of the matching process which draw on contrasting control models. the main conclusion of our study is that the active process of graph-editing outperforms the alternatives in terms of its ability to effectively control a large population of contaminating clutter.
a minimum-variance adaptive surface mesh. our main contribution in this paper is to describe a new class of the adaptive mesh. the mesh uses both split and merge operations to adapt itself to the structure of volumetric data-points. the adaptive behavior is controlled by the variance of the data-point positions about maximum-likelihood quadric patches. we show that the density of control points on the mesh is regulated by the curvature of the underlying surface. finally, we illustrate the effectiveness of the method on both real-world and simulated data-sets.
polarization phase-based method for material classification and object recognition in computer vision. a robust and accurate polarization phase-based technique for material classification is presented. the novelty of this technique is three-fold in (i) its theoretical development, (ii) its application, and, (iii) its experimental implementation. the concept of phase of polarization of a light wave is introduced to computer vision for discrimination between materials according to their intrinsic electrical conductivity, such as distinguishing conducting metals, and poorly-conducting dielectrics. previous work has used intensity, color and polarization component ratios. this new method is based on the physical principle that metals retard orthogonal components of light upon reflection while dielectrics do not. this method has significant complementary advantages with respect to existing techniques, is computationally efficient, and can be easily implemented with existing imaging technology. experiments for real circuit board inspection, non-conductive and conductive glass, and, outdoor object recognition have been performed to demonstrate its accuracy and potential capabilities.
error analysis of a real-time stereo syste. correlation-based real-time stereo systems have been proven to be effective in applications such as robot navigation, elevation map building etc. this paper provides an in-depth analysis of the major error sources for such a real-time stereo system in the context of cross-country navigation of an autonomous vehicle. three major types of errors: foreshortening error, misalignment error and systematic error, are identified. the combined disparity errors can easily exceed three-tenths of a pixel, which translates to significant range errors. upon understanding these error sources, we demonstrate different approaches to either correct them or model their magnitudes without excessive additional computations. by correcting those errors, we show that the precision of the stereo algorithm can be improved by 50%.
creating image-based vr using a self-calibrating fisheye lens. image-based virtual reality is emerging as a major alternative to the more traditional 3d-based vr. the main advantages of the image-based vr are its photo-quality realism and 3d illusion without any 3d information. unfortunately, creating content for image-based vr is usually a very tedious process. this paper proposes to use a non-perspective fisheye lens to capture the spherical panorama with very few images. unlike most of camera calibration in computer vision, self-calibration of the fisheye lens poses new questions regarding the parameterization of the distortion and wrap-around effects. because of its unique projection model and large field of view (near 180 degrees), most of the ambiguity problems in self-calibrating a traditional lens can be solved trivially. we demonstrate that with four fisheye lens images, we can seamlessly register them to create the spherical panorama, while self-calibrating its distortion and field of view.
determining a polyhedral shape using interreflections. we discuss the uniqueness of 3-d shape recovery of a polyhedron from a single shading image. first, we analytically show that multiple convex (and concave) shape solutions usually exist for a simple polyhedron if interreflections are not considered. then we propose a new approach to uniquely determine the concave shape solution using interreflections as a constraint. a numerical example, in which two convex shapes and two concave shapes exist for a trihedral corner, has been shown by horn. however, it is difficult to prove the uniqueness using constraint equations. we analytically show that multiple convex (and concave) shape solutions usually exist for a pyramid using a reflectance map, if interreflection distribution is not considered. however, if interreflection distribution is used as a constraint that limits the shape solution (for a concave polyhedron), the polyhedral shape can be uniquely determined. interreflections are used as a constraint to determine the shape solution in our approach.
gradient vector flow: a new external force for snakes. snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. problems associated with initialization and poor convergence to concave boundaries, however, have limited their utility. this paper develops a new external force for active contours, largely solving both problems. this external force, which we call gradient vector flow (gvf), is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. the resultant field has a large capture range and forces active contours into concave regions. examples on simulated images and one real image are presented.
temporal multi-scale models for flow and acceleration. a model for computing image flow in image sequences containing a very wide range of instantaneous flows is proposed. this model integrates the spatio-temporal image derivatives from multiple temporal scales to provide both reliable and accurate instantaneous flow estimates. the integration employs robust regression and automatic scale weighting in a generalized brightness constancy framework. in addition to instantaneous flow estimation the model supports recovery of dense estimates of image acceleration and can be readily combined with parameterized flow and acceleration models. a demonstration of performance on image sequences of typical human actions taken with a high frame-rate camera is given.
identification of salient contours in cluttered images. we present a model of contour extraction in which the perceptual salience of contours arises from long-range interactions between orientation-selective filters. it has been previously shown that salient contours may be extracted from noisy images by using a number heuristic features. our algorithm is based on cortical mechanisms, and simulations show close agreement with results from recent anatomical, physiological and psychophysical studies including recent results of d.j. field et al. (1993), i. kovacs et al., and m.k. kapadia et al. (1995). the performance of the algorithm is demonstrated on a range of psychophysical stimuli and real images.
robust occluding contour detection using the hausdorff distance. in this paper, a correlational approach for distinguishing occluding contours from object markings for 3d object modeling is presented. the proposed method is valid under weak perspective projection, does not require to search for correspondences between frames, can handle scaling between consecutive images, thus can estimate the full euclidean surface structure, and does not require camera calibration or camera motion measurement. extensive experimental results show that the method is robust to the occlusion of feature points and image noise unlike previous affine-based approaches. qualitative and quantitative results for the relation between the required minimum viewing angle change for the detection and the surface curvature are also presented.
surface shape from warping. we propose a variant of shape from shading which we call shape from image warping. the idea is that the three-dimensional shape of an object is estimated by determining how much the image of the object is warped with respect to the image of a known prototype shape. we demonstrate that, for a class of reflectance functions, there is a direct relationship between these image warps and geometric warps of the underlying three-dimensional shapes. therefore detecting the image warp relative to a prototype of known shape allows us to reconstruct the shape of the imaged object. we derive properties of these shape warps and illustrate the results by recovering the shapes of faces. this relationship between image and shape warps helps us understand the relationship between image based models of object recognition and approaches based on three dimensional object models.
shape and albedo from multiple images using integrability. previous work has developed an approach for estimating shape and albedo from multiple images assuming lambertian reflectance with single light sources. the main contributions of this paper are: (i) to show how the approach can be generalized to include ambient background illumination, (ii) to demonstrate the use of the integrability constraint for solving this problem, and (iii) an iterative algorithm which is able to improve the analysis by finding shadows and rejecting them.
learning in gibbsian fields: how accurate and how fast can it be? gibbsian fields or markov random fields are widely used in bayesian image analysis, but learning gibbs models is computationally expensive. the computational complexity is pronounced by the recent minimax entropy (frame) models which use large neighborhoods and hundreds of parameters. in this paper, we present a common framework for learning gibbs models. we identify two key factors that determine the accuracy and speed of learning gibbs models: the efficiency of likelihood functions and the variance in approximating partition functions using monte carlo integration. we propose three new algorithms. in particular, we are interested in a maximum satellite likelihood estimator, which makes use of a set of precomputed gibbs models called "satellites" to approximate likelihood functions. this algorithm can approximately estimate the minimax entropy model for textures in seconds in a hp workstation. the performances of various learning algorithms are compared in our experiments.
learning generic prior models for visual computation. this paper presents a novel theory for learning generic prior models from a set of observed natural images based on a minimax entropy theory that the authors studied in texture modeling. we start by studying the statistics of natural images including the scale invariant properties, then generic prior models were learnt to duplicate the observed statistics. the learned gibbs distributions confirm and improve the forms of existing prior models, and more interestingly inverted potentials are found to be necessary, and such potentials produce patterns and enhance preferred image features. the learned model is compared with existing prior models in experiments of image restoration.
fully 3d active surface models with self--inflation and self--deflation forces. in this paper, we propose fully 3d active surface models for image segmentation. our models are capable of fitting a diverse range of region shapes. they have low sensitivity to initial shape and position. we design self--inflation/deflation forces, which cooperate naturally with gradient forces. they permit the active surface to travel a long distance without the aid of any external forces. they are easily controlled in both their directions and magnitude. the models produce accurate segmentation when tested with synthetic and real images. they manifest robustness to image noise and imperfect image data. importantly, they are capable of converging to the correct boundary even if the initial estimate is not close.
frame: filters, random fields, and minimax entropy-- towards a unified theory for texture modeling. in this paper, a minimax entropy principle is studied, based on which a novel theory, called frame (filters, random fields and minimax entropy) is proposed for texture modeling. frame combines attractive aspects of two important themes in texture modeling: multi-channel filtering and markov random field (mrf) modeling. it incorporates the responses of a set of well selected filters into the distribution over a random field, and hence has a much stronger descriptive ability than the traditional mrf models. furthermore, it interprets and clarifies many previous concepts and methods for texture analysis and synthesis from a unified point of view. algorithms are proposed for probability inference, stochastic simulation and filter selection. experiments on a variety of textures are described to illustrate our theory and to show the performance of our algorithms. these experiments demonstrate that many textures previously considered as different categories can be modeled and synthesized in a common framework.
multi-scale classification of 3-d objects. we describe an approach to the classification of 3-d objects using a multi-scale representation. this approach starts with a smoothing algorithm for representing objects at different scales. smoothing is applied in curvature space directly, thus avoiding the usual shrinkage problems and allowing for efficient implementations. a 3-d similarity measure that integrates the representations of the objects at multiple scales is introduced. given a library of models, objects that are similar based on this multi-scale measure are grouped together into classes. the objects that are in the same class are combined into a single prototype object. finally, the prototypes are used for hierarchical recognition by first comparing the scene representation to the prototypes and then matching it only to the objects in the most likely class rather than to the entire library of models. beyond its application to object recognition, this approach provides an attractive implementation of the intuitive notions of scale and approximate similarity for 3-d shapes.
isotropic processing for gradient estimation. this paper concerns the influence of edge direction on the estimation of edge contrast and orientation. we show that the gradient estimated using radial filters is not affected by edge orientation. for non-radial filters the gradient can be affected by edge orientation. for instance, we find that the estimated edge orientation using a non-radial filter may be biased, even if the signal is noise-free. however, there are non-radial filters for which gradient is unaffected by edge orientation as in the case of radial filters. the properties of these functions are given in this paper. the results are illustrated by the study of the canny, deriche, and shen & castan detectors. we take into account discretization errors. these results give a clear indication of the effect of the rotation invariance property of an edge detector on its response, thus providing a more precise meaning for this property in edge detection.
using geometric corners to build a 2d mosaic from a set of image. the main problem for building a mosaic is the computation of the warping functions (homographies). in fact two cases are to be distinguished. the first is when the homography is mainly a translation (i.e. the rotation around the optical axis and the zooming factor are small). the second is the general case (when the rotation around the optical axis and zooming are arbitrary). some efficient methods have been developed to solve the first case. but the second case is more difficult, in particular, when the rotation around the optical axis is very large (90 degrees or more). often in this case human interaction is needed to provide a first approximation of the transformation that will bring us back to the first case. in this article we present a method to solve this problem without human interaction for any rotation around the optical axis and fairly large zooming factors.
self-maintaining camera calibration over time. the success of an intelligent robotic system depends on the performance of its vision-system which in turn depends to a great extend upon the quality of its calibration. during the execution of a task the vision-system is subject to external influences such as vibrations, thermal expansion etc. which affect and possibly render invalid the initial calibration. moreover, it is possible that the parameters of the vision-system like e.g. the zoom or the focus are altered intentionally in order to perform specific vision-tasks. this paper describes a technique for automatically maintaining calibration of stereovision systems over time without using again any particular calibration apparatus. it uses all available information, i.e. both spatial and temporal data. uncertainty is systematically manipulated and maintained. synthetical and real data are used to validate the proposed technique, and the results compare very favourably with those given by classical calibration methods.
nonlinear dynamical shape priors for level set segmentation. the introduction of statistical shape knowledge into level set based segmentation methods was shown to improve the segmentation of familiar structures in the presence of noise, clutter or partial occlusions. while most work has been focused on shape priors which are constant in time, it is clear that when tracking deformable shapes certain silhouettes may become more or less likely over time. in fact, the deformations of familiar objects such as the silhouettes of a walking person are often characterized by pronounced temporal correlations.in this paper, we propose a nonlinear dynamical shape prior for level set based image segmentation. specifically, we propose to approximate the temporal evolution of the eigenmodes of the level set function by means of a mixture of autoregressive models. we detail how such shape priors "with memory" can be integrated into a variational framework for level set segmentation. as an application, we experimentally validate that the nonlinear dynamical prior drastically improves the tracking of a person walking in different directions, despite large amounts of clutter and noise.
spectral matting. we present spectral matting: a new approach to natural image matting that automatically computes a basis set of fuzzy matting components from the smallest eigenvectors of a suitably defined laplacian matrix. thus, our approach extends spectral segmentation techniques, whose goal is to extract hard segments, to the extraction of soft matting components. these components may then be used as building blocks to easily construct semantically meaningful foreground mattes, either in an unsupervised fashion, or based on a small amount of user input.
bottom-up recognition and parsing of the human body. recognizing humans, estimating their pose and segmenting their body parts are key to high-level image understanding. because humans are highly articulated, the range of deformations they undergo makes this task extremely challenging. previous methods have focused largely on heuristics or pairwise part models in approaching this problem. we propose a bottom-up growing, similar to parsing, of increasingly more complete partial body masks guided by a set of parse rules. at each level of the growing process, we evaluate the partial body masks directly via shape matching with exemplars (and also image features), without regard to how the hypotheses are formed. the body is evaluated as a whole, not the sum of its parts, unlike previous approaches. multiple image segmentations are included at each of the levels of the growing/parsing, to augment existing hypotheses or to introduce ones. our method yields both a pose estimate as well as a segmentation of the human. we demonstrate competitive results on this challenging task with relatively few training examples on a dataset of baseball players with wide pose variation. our method is comparatively simple and could be easily extended to other objects. we also give a learning framework for parse ranking that allows us to keep fewer parses for similar performance.
efficient mrf deformation model for non-rigid image matching. we propose a novel mrf-based model for deformable image matching (also known as registration). the deformation is described by a field of discrete variables, representing displacements of (blocks of) pixels. discontinuities in the deformation are prohibited by imposing hard pairwise constraints in the model. exact maximum a posteriori inference is intractable and we apply a linear programming relaxation technique. we show that, when reformulated in the form of two coupled fields of x- and y-displacements, the problem leads to a simpler relaxation to which we apply the sequential tree-reweighted message passing (trw-s) algorithm [wainwright-03, kolmogorov-05]. this enables image registration with large displacements at a single scale. we employ fast message updates for a special type of interaction as was proposed [felzenszwalb and huttenlocher-04] for the max-product belief propagation (bp) and introduce a few independent speedups. in contrast to bp, the trw-s allows us to compute per-instance approximation ratios and thus to evaluate the quality of the optimization. the performance of our technique is demonstrated on both synthetic and real-world experiments.
on controlling light transport in poor visibility environments. poor visibility conditions due to murky water, bad weather, dust and smoke severely impede the performance of vision systems. passive methods have been used to restore scene contrast under moderate visibility by digital postprocessing. however, these methods are ineffective when the quality of acquired images is poor to begin with. in this work, we design active lighting and sensing systems for controlling light transport before image formation, and hence obtain higher quality data. first, we present a technique of polarized light striping based on combining polarization imaging and structured light striping. we show that this technique out-performs different existing illumination and sensing methodologies. second, we present a numerical approach for computing the optimal relative sensor-source position, which results in the best quality image. our analysis accounts for the limits imposed by sensor noise.
epitomic location recognition. this paper presents a novel method for location recognition, which exploits an epitomic representation to achieve both high efficiency and good generalization. a generative model based on epitomic image analysis captures the appearance and geometric structure of an environment while allowing for variations due to motion, occlusions, and non-lambertian effects. the ability to model translation and scale invariance together with the fusion of diverse visual features yields enhanced generalization with economical training. experiments on both existing and new labeled image databases result in recognition accuracy superior to state of the art with real-time computational performance.
accurate camera calibration from multi-view stereo and bundle adjustment. the advent of high-resolution digital cameras and sophisticated multi-view stereo algorithms offers the promise of unprecedented geometric fidelity in image-based modeling tasks, but it also puts unprecedented demands on camera calibration to fulfill these promises. this paper presents a novel approach to camera calibration where top-down information from rough camera parameter estimates and the output of a multi-view-stereo system on scaled-down input images is used to effectively guide the search for additional image correspondences and significantly improve camera calibration parameters using a standard bundle adjustment algorithm (lourakis and argyros 2008). the proposed method has been tested on six real datasets including objects without salient features for which image correspondences cannot be found in a purely bottom-up fashion, and objects with high curvature and thin structures that are lost in visual hull construction even with small errors in camera parameters. three different methods have been used to qualitatively assess the improvements of the camera parameters. the implementation of the proposed algorithm is publicly available at furukawa and ponce (2008b).
global stereo reconstruction under second order smoothness priors. second-order priors on the smoothness of 3d surfaces are a better model of typical scenes than first-order priors. however, stereo reconstruction using global inference algorithms, such as graph cuts, has not been able to incorporate second-order priors because the triple cliques needed to express them yield intractable (nonsubmodular) optimization problems. this paper shows that inference with triple cliques can be effectively performed. our optimization strategy is a development of recent extensions to \alpha--expansion, based on the “ qpbo” algorithm. the strategy is to repeatedly merge proposal depth maps using a novel extension of qpbo. proposal depth maps can come from any source, for example, frontoparallel planes as in \alpha-expansion, or indeed any existing stereo algorithm, with arbitrary parameter settings.
efficient sequential correspondence selection by cosegmentation. in many retrieval, object recognition, and wide-baseline stereo methods, correspondences of interest points (distinguished regions) are commonly established by matching compact descriptors such as sifts. we show that a subsequent cosegmentation process coupled with a quasi-optimal sequential decision process leads to a correspondence verification procedure that 1) has high precision (is highly discriminative), 2) has good recall, and 3) is fast. the sequential decision on the correctness of a correspondence is based on simple statistics of a modified dense stereo matching algorithm. the statistics are projected on a prominent discriminative direction by svm. wald's sequential probability ratio test is performed on the svm projection computed on progressively larger cosegmented regions. we show experimentally that the proposed sequential correspondence verification (scv) algorithm significantly outperforms the standard correspondence selection method based on sift distance ratios on challenging matching problems.
robust higher order potentials for enforcing label consistency. this paper proposes a novel framework for labelling problems which is able to combine multiple segmentations in a principled manner. our method is based on higher order conditional random fields and uses potentials defined on sets of pixels (image segments) generated using unsupervised segmentation algorithms. these potentials enforce label consistency in image regions and can be seen as a generalization of the commonly used pairwise contrast sensitive smoothness potentials. the higher order potential functions used in our framework take the form of the robust p n model and are more general than the p n potts model recently proposed by kohli et al. we prove that the optimal swap and expansion moves for energy functions composed of these potentials can be computed by solving a st-mincut problem. this enables the use of powerful graph cut based move making algorithms for performing inference in the framework. we test our method on the problem of multi-class object segmentation by augmenting the conventional crf used for object segmentation with higher order potentials defined on image regions. experiments on challenging data sets show that integration of higher order potentials quantitatively and qualitatively improves results leading to much better definition of object boundaries. we believe that this method can be used to yield similar improvements for many other labelling problems.
cost-sensitive face recognition. most traditional face recognition systems attempt to achieve a low recognition error rate, implicitly assuming that the losses of all misclassifications are the same. in this paper, we argue that this is far from a reasonable setting because, in almost all application scenarios of face recognition, different kinds of mistakes will lead to different losses. for example, it would be troublesome if a door locker based on a face recognition system misclassified a family member as a stranger such that she/he was not allowed to enter the house, but it would be a much more serious disaster if a stranger was misclassified as a family member and allowed to enter the house. we propose a framework which formulates the face recognition problem as a multiclass cost-sensitive learning task, and develop two theoretically sound methods for this task. experimental results demonstrate the effectiveness and efficiency of the proposed methods.
generating referring expressions involving relations. in this paper, we review dale's [1989] algorithm for determining the content of a referring expression. the algorithm, which only permits the use of one-place predicates, it revised and extended to deal with n-ary predicates. we investigate the problem of blocking "recursion" in complex noun phrases and propose a solution in the context of our algorithm.
disjunctions and inheritance in the context feature structure system. substantial efforts have been made in order to cope with disjunctions in constraint based grammar formalisms (e.g. [kasper, 1987; maxwell and kaplan, 1991; d&ouml;rre and eisele, 1990].). this paper describes the roles of disjunctions and inheritance in the use of feature structures and their formal semantics. with the notion of contexts we abstract from the graph structure of feature structures and properly define the search space of alternatives. the graph unification algorithm precomputes nogood combinations, and a specialized search procedure which we propose here uses them as a controlling factor in order to delay decisions as long as there is no logical necessity for deciding.
the incremental generation of passive sentences. this paper sketches some basic features of the synphonics account of the computational modelling of incremental language production with the example of the generation of passive sentences. the synphonics approach aims at linking psycholinguistic insights into the nature of the human natural language production process with well-established assumptions in theoretical and computational linguistics concerning the representation and processing of grammatical knowledge. we differentiate between two possible kinds of stimuli within the generation process that trigger the formation of passive sentences: a formulator-external stimulus and a formulator-internal one. the formulator-external stimulus is determined by the conceptual/contextual condition of agent backgrounding: an agentless semantic representation is verbalized by way of constructing an ergativized verbal complex in the morphological structure-building component, rather than by mapping the semantic representation directly onto a passive lemma. the formulator-internal stimulus is an effect of the constraints of rapid, incremental utterance production; in particular, it causes the formulator to integrate a thematically underspecified increment in a prominent structural enviornment. in this case, the formation of passives is a matter of an additional constraint on the lemma selection process: lemma selection is constrained by the structural representation of the utterance produced so far.
stochastic hpsg. in this paper we provide a probabilistic interpretation for typed feature structures very similar to those used by pollard and sag. we begin with a version of the interpretation which lacks a treatment of re-entrant feature structures, then provide an extended interpretation which allows them. we sketch algorithms allowing the numerical parameters of our probabilistic interpretations of hpsg to be estimated from corpora.
parsing idioms in lexicalized tags. we show how idioms can be parsed in lexicalized tags. we rely on extensive studies of frozen phrases pursued at l.a.d.l. that show that idioms are pervasive in natural language and obey, generally speaking, the same morphological and syntactical patterns as 'free' structures. by idiom we mean a structure in which some items are lexically frozen and have a semantics that is not compositional. we thus consider idioms of different syntactic categories: np, s, adverbials, compound prepositions... in both english and french.in lexicalized tags, the same grammar is used for idioms as for 'free' sentences. we assign them regular syntactic structures while representing them semantically as one non-compositional entry. syntactic transformations and insertion of modifiers may thus apply to them as to any 'free' structures. unlike previous approaches, their variability becomes the general case and their being totally frozen the exception. idioms are generally represented by extended elementary trees with 'heads' made out of several items (that need not be contiguous) with one of the items serving as an index. when an idiomatic tree is selected by this index, lexical items are attached to some nodes in the tree. idiomatic trees are selected by a single head node however the head value imposes lexical values on other nodes in the tree. this operation of attaching the head item of an idiom and its lexical parts is called lexical attachment. the resulting tree has the lexical items corresponding to the pieces of the idiom already attached to it.we generalize the parsing strategy defined for lexicalized tag to the case of 'heads' made out of several items. we propose to parse idioms in two steps which are merged in the two steps parsing strategy that is defined for 'free' sentences. the first step performed during the lexical pass selects trees corresponding to the literal and idiomatic interpretation. however it is not always the case that the idiomatic trees are selected as possible candidates. we require that all basic pieces building the minimal idiomatic expression must be present in the input string (with possibly some order constraints). this condition is a necessary condition for the idiomatic reading but of course it is not sufficient. the second step performs the syntax analysis as in the usual case. during the second step, idiomatic reading might be rejected. idioms are thus parsed as any 'free' sentences. except during the selection process, idioms do not require any special parsing mechanism. we are also able to account for cases of ambiguity between idiomatic and literal interpretations.factoring recursion from dependencies in tags allows discontinuous constituents to be parsed in an elegant way. we also show how regular 'transformations' are taken into account by the parser.
deterministic parsing and unbounded dependencies. this paper assesses two new approaches to deterministic parsing with respect to the analysis of unbounded dependencies (uds). uds in english are highly locally (and often globally) ambiguous. several researchers have argued that the difficulty of uds undermines the programme of deterministic parsing. however, their conclusion is based on critiques of various versions of the marcus parser which represents only one of many possible approaches to deterministic parsing. we examine the predictions made by a lr(1) deterministic parser and the lexicat deterministic parser concerning the analysis of uds. the lr(1) technique is powerful enough to resolve the local ambiguities we examine. however, the lexicat model provides a more psychologically plausible account of the parsing of uds, which also offers a unified account of the resolution of local and global ambiguities in these constructions.
a multi-purpose interface to an on-line dictionary. we argue that there are two qualitatively different modes of using a machine-readable dictionary in the context of research in computational linguistics: batch processing of the source with the purpose of collating information for subsequent use by a natural language application, and placing the dictionary on-line in an environment which supports fast interactive access to data selected on the basis of a number of linguistic constraints. while it is the former mode of dictionary use which is characteristic of most computational linguistics work to date, it is the latter which has the potential of making maximal use of the information typically found in a machine-readable dictionary. we describe the mounting of the machine-readable source of the longman dictionary of contemporary english on a single user workstation to make it available as a development tool for a number of research projects.
evaluating and combining approaches to selectional preference acquisition. previous work on the induction of selectional preferences has been mainly carried out for english and has concentrated almost exclusively on verbs and their direct objects. in this paper, we focus on class-based models of selectional preferences for german verbs and take into account not only direct objects, but also subjects and prepositional complements. we evaluate model performance against human judgments and show that there is no single method that overall performs best. we explore a variety of parametrizations for our models and demonstrate that model combination enhances agreement with human ratings.
parsing into discourse object descriptions. this paper reports work on the design of a natural language interface with a limited dialogue capability. it is argued that (i) the interpretation of the input is preferably represented as a structure of discourse object descriptions (dods); (ii) the dods must be determined on the basis of different types of knowledge such as grammatical knowledge, object type definitions and knowledge about existing discourse objects and their discourse status; (iii) the different types of knowledge are stored separately but integrated in the interpretation process which is based on constraints.
an experiment with heuristic parsing of swedish. heuristic parsing is the art of doing parsing in a haphazard and seemingly careless manner but in such a way that the outcome is still "good", at least from a statistical point of view, or, hopefully, even from a more absolute point of view. the idea is to find strategic shortcuts derived from guesses about the structure of a sentence based on scanty observations of linguistic units in the sentence. if the guess comes out right much parsing time can be saved, and if it does not, many subobservations may still be valid for revised guesses. in the (very preliminary) experiment reported here the main idea is to make use of (combinations of) surface phenomena as much as possible as the base for the prediction of the structure as a whole. in the parser to be developed along the lines sketched in this report main stress is put on arriving at independently working, parallel recognition procedures.the work reported here is both aimed at simulating certain aspects of human language perception and at arriving at effective algorithms for actual parsing of running text. there is, indeed, a great need for fast such algorithms, e.g. for the analysis of the literally millions of words of running text that already today comprise the data bases in various large information retrieval systems, and which can be expected to expand several orders of magnitude both in importance and in size in the foreseeable future.
interactive word alignment for language engineering. in this paper we report ongoing work on developing an interactive word alignment environment that will assist a user to quickly produce accurate full-coverage word alignment in bitexts for different language engineering tasks, such as mt lexicons and gold standards for evaluation. the system uses a graphical interface, static and dynamic resources as well as machine learning techniques. we also sketch how the system is being integrated with an automatic word aligner.
various representations of text proposed for eurotra. we introduce several general notions concerning the texts and the particularities of text processing on a computer support, in relation to some problems which are specific to m(a)t. and we present the solution we have proposed for the duration of the eurotra project.
talking through procedures: an intelligent space station procedure assistant. we present a prototype system aimed at providing spoken dialogue support for complex procedures aboard the international space station. the system allows navigation one line at a time or in larger steps. other user functions include issuing spoken corrections, requesting images and diagrams, recording voice notes and spoken alarms, and controlling audio volume.
carsim: an automatic 3d text-to-scene conversion system applied to road accident reports. carsim is an automatic text-to-scene conversion system. it analyzes written descriptions of car accidents and synthesizes 3d scenes of them. the conversion process consists of two stages. an information extraction module creates a tabular description of the accident and a visual simulator generates and animates the scene.we implemented a first version of carsim that considered a corpus of texts in french. we redesigned its linguistic modules and its interface and we applied it to texts in english from the national transportation safety board in the united states.
natural, language information retrieval system dialog. presented paper contains a description of an experimental version of the natural language information retrieval system dialog. the system is destined for the use in the field of medicine. its main purpose is to ensure access to information to phisicians in a conversational manner. the use of the system does not require ability of programming from its user.
reversing controlled document authoring to normalize documents. this paper introduces document normalization, and addresses the issue of whether controlled document authoring systems can be used in a reverse mode to normalize legacy documents. a paradigm for deep content analysis using such a system is proposed, and an architecture for a document normalization system is described.
generating and visualizing a soccer knowledge base. this demo abstract describes the smartweb ontology-based annotation system (soba). a key feature of soba is that all information is extracted and stored with respect to the smartweb integrated ontology (swinto). in this way, other components of the systems, which use the same ontology, can access this information in a straightforward way. we will show how information extracted by soba is visualized within its original context, thus enhancing the browsing experience of the end user.
an efficient method for determining bilingual word classes. in statistical natural language processing we always face the problem of sparse data. one way to reduce this problem is to group words into equivalence classes which is a standard method in statistical language modeling. in this paper we describe a method to determine bilingual word classes suitable for statistical machine translation. we develop an optimization criterion based on a maximum-likelihood approach and describe a clustering algorithm. we will show that the usage of the bilingual word classes we get can improve statistical machine translation.
a robust and efficient three-layered dialogue component for a speech-to-speech translation system. we present the dialogue component of the speech-to-speech translation system verbmobil. in contrast to conventional dialogue systems it mediates the dialogue while processing maximally 50% of the dialogue in depth. special requirements (robustness and efficiency) lead to a 3-layered hybrid architecture for the dialogue module, using statistics, an automaton and a planner. a dialogue memory is constructed incrementally.
danish field grammar in typed prolog. this paper describes a field grammar for danish and its implementations in a prolog version with predeclared types. in comparison to the ususal s -> np vp schema, this kind of grammar, where the first rule is s -> cnf ff nf cf enhances analysis effeciency because the fields specify constituents and syntactic function at the same time. the field grammar tradition is outlinedand an overview of the major rules of the prolog program, which implements the grammar, is given.
discontinuous constituents in trees, rules, and parsing. this paper discusses the consequences of allowing discontinuous constituents in syntactic representions and phrase-structure rules, and the resulting complications for a standard parser of phrase-structure grammar.it is argued, first, that discontinuous constituents seem inevitable in a phrase-structure grammar which is acceptable from a semantic point of view. it is shown that tree-like constituent structures with discontinuities can be given a precise definition which makes them just as acceptable for syntactic representation as ordinary trees. however, the formulation of phrase-structure rules that generate such structures entails quite intricate problems. the notions of linear precedence and adjacency are reexamined, and the concept of "n-place adjacency sequence" is introduced. finally, the resulting form of phrase-structure grammar, called "discontinuous phrase-structure grammar", is shown to be parsable by an algorithm for context-free parsing with relatively minor adaptations. the paper describes the adaptations in the chart parser which was implemented as part of the tendumdialogue system.
the resolution of local syntactic ambiguity by the human sentence processing mechanism. the resolution of local syntactic ambiguity by the human sentence processing mechanism is a topic which has provoked considerable interest in recent years. at issue is whether such ambiguities are resolved on the basis of syntactic information alone (cf. minimal attachment-frazier, 1979), or whether they are resolved on some other basis. crain & steedman (1982) suggest that the resolution process is governed not by minimal attachment but instead by whether or not a referring expression provides sufficient information with which to identify a unique referent. such an approach relies on the provision of adequate contextual information, something which has been lacking in experiments which have been claimed to support minimal attachment. in this paper i shall consider a number of such experiments, and the different patterns of results which emerge once contextual information is provided. although the importance of contextual information will be stressed, i shall briefly consider reasons why parsing preferences arise in the absence of any explicit prior context. the conclusion is that computational models of syntactic ambiguity resolution which are based on evidence which has ignored contextual considerations are models of something other than <u>natural</u> language processing.
automatic semantic classification of verbs from their syntactic contexts: an implemented classifier for stativity. this paper discusses an implemented program that automatically classifies verbs into those that describe only states of the world, such as to know, and those that describe events, such as to look. it works by exploiting the constraint between the syntactic environments in which a verb can occur and its meaning. the only input is on-line text. this demonstrates an important new technique for the automatic generation of lexical databases.
a two-stage approach to retrieving answers for how-to questions. this paper addresses the problem of automatically retrieving answers for how-to questions, focusing on those that inquire about the procedure for achieving a specific goal. for such questions, typical information retrieval methods, based on key word matching, are better suited to detecting the content of the goal (e.g., 'installing a windows xp server') than the general nature of the desired information (i.e., procedural, a series of steps for achieving this goal). we suggest dividing the process of retrieving answers for such questions into two stages, with each stage focusing on modeling one aspect of a how-to question. we compare the two-stage approach with two alternative approaches: a baseline approach that only uses the content of the goal to retrieve relevant documents and another approach that explores the potential of automatic query expansion. the result of the experiment shows that the two-stage approach significantly outperforms the baseline but achieves similar result with the systems using automatic query expansion techniques. we analyze the reason and also present some future work.
limits of a sentence based procedural approach for aspect choice in german-russian mt. in this paper we discuss some problems arising in german-russian machine translation with regard to tense and aspect. since the formal category of aspect is missing in german the information required for generating russian aspect forms has to be extracted from different representation levels. a sentence based procedure for aspect choice in the mt system virtex is presented which takes lexical, morphological and semantic criteria into account. the limits of this approach are shown. to overcome these difficulties a human interaction component is proposed.
subgrammars, rule classes and control in the rosetta translation system. the paper discusses a recent extension of the linguistic framework of the rosetta system. the original framework is elegant and has proved its value in practice, but it also has a number of deficiencies, of which the most salient is the impossibility to assign an explicit structure to the grammars. this may cause problems, especially in a situation where large grammars have to be written by a group of people. the newly developed framework enables us to divide a grammar into subgrammars in a linguistically motivated way and to control explicitly the application of rules in a subgrammar. on the other hand it enables us to divide the set of grammar rules into rule classes in such a way that we get hold of the more difficult translation relations. the use of both these divisions naturally leads to a highly modular structure of the system, which helps in controlling its complexity. we will show that these divisions also give insight into a class of difficult translation problems in which there is a mismatch of categories.
structure-driven generation from separate semantic representations. a new approach to structure-driven generation is presented that is based on a separate semantics as input structure. for the first time, a gpsg-based formalism is complemented with a system of pattern-action rules that relate the parts of a semantics to appropriate syntactic rules. this way a front end generator can be adapted to some application system (such as a machine translation system) more easily than would be possible with many previous generators based on modern grammar formalisms.
unsupervised discovery of persian morphemes. this paper reports the present results of a research on unsupervised persian morpheme discovery. in this paper we present a method for discovering the morphemes of persian language through automatic analysis of corpora. we utilized a minimum description length (mdl) based algorithm with some improvements and applied it to persian corpus. our improvements include enhancing the cost function using some heuristics, preventing the split of high frequency chunks, exploiting penalty for first and last letters and distinguishing pre-parts and post-parts. our improved approach has raised the precision, recall and f-measure of discovery by respectively %32, %17 and %23.
a flexible architecture for reference resolution. this paper describes an architecture for performing anaphora resolution in a flexible way. systems which conform to these guidelines are well-encapsulated and portable, and can be used to compare anaphora resolution techniques for new language understanding applications. our implementation of the architecture in a pronoun resolution testing platform demonstrates the flexibility of the approach.
the treegram index-an efficient technique for retrieval in linguistic treebanks. multiway trees (mt, henceforth) are a common and well-understood data structure for describing hierarchical linguistic information. with the availability of large treebanks, retrieval techniques for highly structured data now become essential. in this contribution, we investigate the efficient retrieval of mt structures at the cost of a complex index---the treegram index.we illustrate our approach with the venona retrieval system, which handles the bht (biblia hebraica transcripta) treebank comprising 508,650 phrase structure trees with maximum degree eight and maximum height 17, containing altogether 3.3 million old-hebrew words.
meaningful conversation with a mobile robot. we describe an implementation integrating a spoken dialogue system with a mobile robot, which the user can direct to specific locations, ask for information about its status, and supply information about its environment. the robot uses an internal map for navigation, and communicates its current orientation and accessible locations to the dialogue system using a topological map as interface.
focusing on focus: a formalization. we present an operable definition of focus which is argued to be of a cognito-pragmatic nature and explore how it is determined in discourse in a formalized manner. for this purpose, a file card model of discourse model and knowledge store is introduced enabling the decomposition and formal representation of its determination process as a programmable algorithm (fda). interdisciplinary evidence from social and cognitive psychology is cited and the prospect of the integration of focus via fda as a discourse-level construct into speech synthesis systems, in particular, concept-to-speech systems, is also briefly discussed.
experiments in reusability of grammatical resources. substantial formal grammatical and lexical resources exist in various nlp systems and in the form of textbook specifications. in the present paper we report on experimental results obtained in manual, semi-automatic and automatic migration of entire computational or textbook descriptions (as opposed to a more informal reuse of ideas or the design of a single "polytheoretic" representation) from a variety of formalisms into the alep formalism. the choice of alep (a comparatively lean, typed feature structure formalism based on rewrite rules) was motivated by the assumption that the study would be most interesting if the target formalism is relatively mainstream without overt ideological commitments to particular grammatical theories. as regards the source formalisms we have attempted migrations of descriptions in hpsg (which uses fullytyped feature structures and has a strong 'non-derivational' flavour), ets (an untyped stratificational formalism which essentially uses rewrite rules for feature structures and has run-time non-monotonic devices) and lfg (which is an un-typed constraint and cf-psg based formalism with extensions such as existential, negative and global well-formedness constraints).
morphonology in the lexicon. in this paper we present a means of defining morphonological phenomena in an inheritance based lexicon. we make use of the theory behind the formal language molusc, in which morphological alternations were defined as mappings between sequences of tree-structured syllables. we discuss how the alternations can be defined in the inheritance-based lexical representation language datr, and how the phonological aspects can be built upon to bring it closer to an integrated lexicon with representations which can be used by both the morphology and phonology of a language.
how to detect grammatical errors in a text without parsing it. the constituent likelihood automatic word-tagging system (claws) was originally designed for the low-level grammatical analysis of the million-word lob corpus of english text samples. claws does not attempt a full parse, but uses a first-order markov model of language to assign word-class labels to words. claws can be modified to detect grammatical errors, essentially by flagging unlikely word-class transitions in the input text. this may seem to be an intuitively implausible and theoretically inadequate model of natural language syntax, but nevertheless it can successfully pinpoint most grammatical errors in a text. several modifications to claws have been explored. the resulting system cannot detect all errors in typed documents; but then neither do far more complex systems, which attempt a full parse, requiring much greater computation.
paradigmatic morphology. we present a notation for the declarative statement of morphological relationships and lexical rules, based on the traditional notion of word and paradigm (cf hockett 1954). the phenomenon of blocking arises from a generalized version of kiparsky's (1973) elsewhere condition, state in terms of ordering by subsumption over paradigms. orthographic constraints on morphemic alternation are described by means of string equations (siekmann 1975). we indicate some criticisms to be made of our approach from both linguistic and computational perspectives and relate our approach to others such as finite-state morphology (koskenniemi 1983), datr (gazdar and evans 1989) and object-oriented morphophonemics (de smedt 1984, daelemans 1988). finally, we discuss the questions of whether a system involving string equations allows a reduction to finite-state techniques.
pattern recognition applied to the acquisition of a grammatical classification system from unrestricted english text. within computational linguistics, the use of statistical pattern matching is generally restricted to speech processing. we have attempted to apply statistical techniques to discover a grammatical classification system from a corpus of 'raw' english text. a discovery procedure is simpler for a simpler language model; we assume a first-order markov model, which (surprisingly) is shown elsewhere to be sufficient for practical applications. the extraction of the parameters of a standard markov model is theoretically straightforward; however, the huge size of the standard model for a natural language renders it incomputable in reasonable time. we have explored various constrained models to reduce computation, which have yielded results of varying success.
an algorithm for generation in unification categorial grammar. we present an algorithm for the generation of sentences from the semantic representations of unification categorial grammar. we discuss a variant of shieber's semantic monotonicity requirement and its utility in our algorithm. we indicate how the algorithm may be extended to other grammars obeying the same requirement. appendices contain a full listing of the program and a trace of execution of the algorithm.
an algorithm to co-ordinate anaphora resolution and pps disambiguation process. both anaphora resolution and prepositional phrase (pp) attachment are the most frequent ambiguities in natural language processing. several methods have been proposed to deal with each phenomenon separately, however none of proposed systems has considered the way of dealing both phenomena we tackle this issue here, proposing an algorithm to co-ordinate the treatment of these two problems efficiently, i.e., the aim is also to exploit at each step all the results that each component can provide.
focus and accent in a dutch text-to-speech system. in this paper we discuss an algorithm for the assignment of pitch accent positions in text-to-speech conversion. the algorithm is closely modeled on current linguistic accounts of accent placement, and assumes a surface syntactic analysis of the input. it comprises a small number of heuristic rules for determining which phrases of a sentence are to be focussed upon; the exact location of a pitch accent within a focussed phrase is determined mainly on the basis of the syntactic relations holding between the elements of the phrase. a perceptual evaluation experiment showed that the algorithm proposed here leads to improved subjective speech quality as compared to a naive algorithm which accents all and only content words.
aggregation in the nl-generator of the visual and natural language specification tool. in this paper we show how to use the socalled aggregation technique to remove redundancies in the fact base of the visual and natural language specification tool (vinst). the current aggregation modules of the natural language generator of vinst is described and an improvement is proposed with one new aggregation rule and a bidirectional grammar.
the problem of computing the most probable tree in data-oriented parsing and stochastic tree grammars. we deal with the question as to whether there exists a polynomial time algorithm for computing the most probable parse tree of a sentence generated by a data-oriented parsing (dop) model. (scha, 1990; bod, 1992, 1993a). therefore we describe dop as a stochastic tree-substitution grammar (stsg). in stsg, a tree can be generated by exponentially many derivations involving different elementary trees. the probability of a tree is equal to the sum of the probabilities of all its derivations.we show that in stsg, in contrast with stochastic context-free grammar, the viterbi algorithm cannot be used for computing a most probable tree of a string. we propose a simple modification of viterbi which allows by means of a "select-random" search to estimate the most probable tree of a string in polynomial time.experiments with dop on atis show that only in 68% of the cases, the most probable derivation of a string generates the most probable tree of that string. therefore, the parse accuracy obtained by the most probable trees (96%) is dramatically higher than the parse accuracy obtained by the most probable derivations (65%).it is still an open question whether the most probable tree of a string can be deterministically computed in polynomial time.
montagovian definite clause grammar. this paper reports a completed stage of ongoing research at the university of york. landsbergen's advocacy of analytical inverses for compositional syntax rules encourages the application of definite clause grammar techniques to the construction of a parser returning montague analysis trees. a parser mdcg is presented which implements an augmented friedman - warren algorithm permitting post referencing, and interfaces with a language of intensional logic translator lilt so as to display the derivational history of corresponding reduced il formulae. some familiarity with montague's ptq and the basic dcg mechanism is assumed.
why are they excited? identifying and explaining spikes in blog mood levels. we describe a method for discovering irregularities in temporal mood patterns appearing in a large corpus of blog posts, and labeling them with a natural language explanation. simple techniques based on comparing corpus frequencies, coupled with large quantities of data, are shown to be effective for identifying the events underlying changes in global moods.
an island parsing interpreter for the full augmented transition network formalism. island parsing is a powerful technique for parsing with augmented transition networks (atns) which was developed and successfully applied in the hwim speech understanding project. the hwim application grammar did not, however, exploit woods' original full atn specification. this paper describes an island parsing interpreter based on hwim, but containing substantial and important extensions to enable it to interpret any grammar which conforms to that full specification of 1970. the most important contributions have been to eliminate the need for prior specification of scope clauses, to provide more power by implementing liftr and sendr actions within the island parsing framework, and to improve the efficiency of the techniques used to merge together partially-built islands within the utterance.this paper also presents some observations about island parsing, based on the use of the parser described, and some suggestions for future directions for island parsing research.
domain-transcending mappings in a system for metaphorical reasoning. we illustrate how the use of metaphorical views for reasoning with metaphor requires the mapping of information such as event shape, event rate and mental/emotional states from the source domain to the target domain. such mappings are domain-independent and can be implemented by means of rules we call view neutral mapping adjuncts (vnmas). we give a list of the main vnmas that appear to be required, and show how they can be incorporated into a pre-existing system (att-meta) for metaphorical reasoning.
parsing with an extended domain of locality. one of the claimed benefits of tree adjoining grammars is that they have an extended domain of locality (edol). we consider how this can be exploited to limit the need for feature structure unification during parsing. we compare two wide-coverage lexicalized grammars of english, lexsys and xtag, finding that the two grammars exploit edol in different ways.
large linguistically-processed web corpora for multiple languages. the web contains vast amounts of linguistic data. one key issue for linguists and language technologists is how to access it. commercial search engines give highly compromised access. an alternative is to crawl the web ourselves, which also allows us to remove duplicates and near-duplicates, navigational material, and a range of other kinds of non-linguistic matter. we can also tokenize, lemmatise and part-of-speech tag the corpus, and load the data into a corpus query tool which supports sophisticated linguistic queries. we have now done this for german and italian, with corpus sizes of over 1 billion words in each case. we provide web access to the corpora in our query tool, the sketch engine.
parsing with an extended domain of locality. one of the claimed benefits of tree adjoining grammars is that they have an extended domain of locality (edol). we consider how this can be exploited to limit the need for feature structure unification during parsing. we compare two wide-coverage lexicalized grammars of english, lexsys and xtag, finding that the two grammars exploit edol in different ways.
proof figures and structural operators for categorial grammar. use of lambek's (1958) categorial grammar for linguistic work has generally been rather limited. there appear to be two main reasons for this: the notations most commonly used can sometimes obscure the structure of proofs and fail to clearly convey linguistic structure, and the calculus as it stands is apparently not powerful enough to describe many phenomena encountered in natural language.in this paper we suggest ways of dealing with both these deficiencies. firstly, we reformulate lambek's system using proof figures based on the 'natural deduction' notation commonly used for derivations in logic, and discuss some of the related proof-theory. natural deduction is generally regarded as the most economical and comprehensible system for working on proofs by hand, and we suggest that the same advantages hold for a similar presentation of categorial derivations. secondly, we introduce devices called structural modalities, based on the structural rules found in logic, for the characterization of commutation, iteration and optionality. this permits the description of linguistic phenomena which lambek's system does not capture with the desired sensitivity and generality.
lfg semantics via constraints. semantic theories of natural language associate meanings with utterances by providing meanings for lexical items and rules for determining the meaning of larger units given the meanings of their parts. traditionally, meanings are combined via function composition, which works well when constituent structure trees are used to guide semantic composition. more recently, the functional structure of lfg has been used to provide the syntactic information necessary for constraining derivations of meaning in a cross-linguistically uniform format. it has been difficult, however, to reconcile this approach with the combination of meanings by function composition. in contrast to compositional approaches, we present a deductive approach to assembling meanings, based on reasoning with constraints, which meshes well with the unordered nature of information in the functional structure. our use of linear logic as a 'glue' for assembling meanings also allows for a coherent treatment of modification as well as of the lfg requirements of completeness and coherence.
lexical acquisition in the core language engine. the sri core language engine (cle) is a general-purpose natural language front end for interactive systems. it translates english expressions into representations of their literal meanings. this paper presents the lexical acquisition component of the cle, which allows the creation of lexicon entries by users with knowledge of the application domain but not of linguistics or of the detailed workings of the system. it is argued that the need to cater for a wide range of types of back end leads naturally to an approach based on eliciting grammaticality judgments from the user. this approach, which has been used to define a 1200-word core lexicon of english, is described and evaluated.
auxiliaries and clitics in french ucg grammar. french auxilliaries and clitics have been analysed in the frame of u.c.g. (unification categorial grammar). concatenation of a functor sign and an adjacent argument sign is the basic operation of the model; unification allows (a) to verify if constraints on concatenation are respected; (b) to produce a flow of information between the functor sign and the argument sign.the rules of the grammar and the design structure of the sign allows to express: (a) the concatenation between french auxilliaries (etre and avoir) and the participle verb form within a single pattern, (b) transitions between clitics in a systematic way. two complex questions of french syntax are thus covered in a fairly simple way.
rapid development of morphological descriptions for full language processing systems. i describe a compiler and development environment for feature-augmented two-level morphology rules integrated into a full nlp system. the compiler is optimized for a class of languages including many or most european ones, and for rapid development and debugging of descriptions of new languages. the key design decision is to compose morphophonological and morphosyntactic information, but not the lexicon, when compiling the description. this results in typical compilation times of about a minute, and has allowed a reasonably full, feature-based description of french inflectional morphology to be developed in about a month by a linguist new to the system.
a new view on the process of translation. in this paper we describe a framework for research into translation that draws on a combination of two existing and independently constructed technologies: an analysis component developed for german by the eurotra-d (et-d) group of iai and the generation component developed for english by the penman group at isi. we present some of the linguistic implications of the research and the promise it bears for furthering understanding of the translation process.
towards an integrated environment for spanish document verification and composition. languages other than english have received little attention as far as the application of natural language processing techniques to text composition is concerned. the present paper describes briefly work under development aiming at the design of an integrated environment for the construction and verification of documents written in spanish. in a first phase, a dictionary of spanish has been implemented, together with a synonym dictionary. the main features of both dictionaries will be summarised, and how they are applied in an environment for document verification and composition.
a probabilistic approach to grammatical analysis of writtin english by computer. work at the unit for computer research on the english language at the university of lancaster has been directed towards producing a grammatically annotated version of the lancaster-oslo/bergen (lob) corpus of written british english texts as the preliminary stage in developing computer programs and data files for providing a grammatical analysis of unrestricted english text.from 1981--83, a suite of pascal programs was devised to automatically produce a single level of grammatical description with one word tag representing the word class or part of speech of each word token in the corpus. error analysis and subsequent modification to the system resulted in over 96 per cent of word tags being correctly assigned automatically. the remaining 3 to 4 per cent were corrected by human post-editors.work is now in progress to devise a suite of programs to provide a constituent analysis of the sentences in the corpus. so far, sample sentences have been automatically assigned phrase and clause tags using a probabilistic system similar to word tagging. it is hoped that the entire corpus will eventually be parsed.
a web-based demonstrator of a multi-lingual phrase-based translation system. this paper describes a multi-lingual phrase-based statistical machine translation system accessible by means of a web page. the user can issue translation requests from arabic, chinese or spanish into english. the same phrase-based statistical technology is employed to realize the three supported language-pairs. new language-pairs can be easily added to the demonstrator. the web-based interface allows the use of the translation system to any computer connected to the internet.
result stages and the lexicon: the proper treatment of event structure. i will argue in this paper that the standard notions of affectedness, change-of-state and result state are too coarse-grained, and will revise and enrich substantially their content, increasing their role in a compositional aspect construal procedure. i will claim in particular that a proper theory of event structure requires that enriched result states should be lexically represented, and will base on them a computational treatment of event structure within a feature-structure-based lexicon.
webcoop: a cooperative question answering system on the web. the main aim of this project is to explore, develop and evaluate the contribution of language technologies to the development of webcoop, a system that provides intelligent cooperative responses to web queries. such a system requires the integration of knowledge representation and the use of advanced reasoning procedures.
the development of lexical resources for information extraction from text combining wordnet and dewey decimal classification. lexicon definition is one of the main bottlenecks in the development of new applications in the field of information extraction from text. generic resources (e.g., lexical databases) are promising for reducing the cost of specific lexica definition, but they introduce lexical ambiguity. this paper proposes a methodology for building application-specific lexica by using wordnet. lexical ambiguity is kept under control by marking synsets in wordnet with field labels taken from the dewey decimal classification.
using plausible inference rules in description planning. current approaches to generating multi-sentence text fail to consider what the user may infer from the different statements in a description. this paper presents a system which contains an explicit model of the inferences that people may make from different statement types, and uses this model, together with assumptions about the user's prior knowledge, to pick the most appropriate sequence of utterances for achieving a given communicative goal.
beyond lexical units: enriching wordnets with phrasets. in this paper we present a proposal to extend wordnet-like lexical databases by adding phrasets, i.e. sets of free combinations of words which are recurrently used to express a concept (let's call them recurrent free phrases). phrasets are a useful source of information for different nlp tasks, and particularly in a multilingual environment to manage lexical gaps. two experiments are presented to check the possibility of acquiring recurrent free phrases from dictionaries and corpora.
the semantics of collocational patterns for reporting verbs. one of the hardest problems for knowledge extraction from machine readable textual sources is distinguishing entities and events that are part of the main story from those that are part of the narrative structure. importantly, however, reported speech in newspaper articles explicitly links these two levels. in this paper, we illustrate what the lexical semantics of reporting verbs must incorporate in order to contribute to the reconstruction of story and context. the lexical structures proposed are derived from the analysis of semantic collocations over large text corpora.
tagging french - comparing a statistical and a constraint-based method. in this paper we compare two competing approaches to part-of-speech tagging, statistical and constraint-based disambiguation, using french as our test language. we imposed a time limit on our experiment: the amount of time spent on the design of our constraint system was about the same as the time we used to train and test the easy-to-implement statistical model. we describe the two systems and compare the results. the accuracy of the statistical method is reasonably good, comparable to taggers for english. but the constraint-based tagger seems to be superior even with the limited time we allowed ourselves for rule development.
topic identification in discourse. this paper proposes a corpus-based language model for topic identification. we analyze the association of noun-noun and noun-verb pairs in lob corpus. the word association norms are based on three factors: 1) word importance, 2) pair co-occurrence, and 3) distance. they are trained on the paragraph and sentence levels for noun-noun and noun-verb pairs, respectively. under the topic coherence postulation, the nouns that have the strongest connectivities with the other nouns and verbs in the discourse form the preferred topic set. the collocational semantics then is used to identify the topics from paragraphs and to discuss the topic shift phenomenon among paragraphs.
multilingual term extraction from domain-specific corpora using morphological structure. morphologically complex terms composed from greek or latin elements are frequent in scientific and technical texts. word forming units are thus relevant cues for the identification of terms in domain-specific texts. this article describes a method for the automatic extraction of terms relying on the detection of classical prefixes and word-initial combining forms. word-forming units are identified using a regular expression. the system then extracts terms by selecting words which either begin or coalesce with these elements. next, terms are grouped in families which are displayed as a weighted list in html format.
new models for improving supertag disambiguation. in previous work, supertag disambiguation has been presented as a robust partial parsing technique. in this paper we present two approaches: contextual models, which exploit a variety of features in order to improve supertag performance, and class-based models, which assign sets of supertags to words in order to substantially improve accuracy with only a slight increase in ambiguity.
vocal interface for a man-machine dialog. we describe a dialogue-handling module used as an interface between a vocal terminal and a task-oriented device (for instance: a robot manipulating blocks). this module has been specially designed to be implanted on a single board using microprocessor, and inserted into the vocal terminal which already comprises a speech recognition board and a synthesis board. the entire vocal system is at present capable of conducting a real time spoken dialogue with its user.
data-oriented methods for grapheme-to-phoneme conversion. it is traditionally assumed that various sources of linguistic knowledge and their interaction should be formalised in order to be able to convert words into their phonemic representations with reasonable accuracy. we show that using supervised learning techniques, based on a corpus of transcribed words, the same and even better performance can be achieved, without explicit modeling of linguistic knowledge.in this paper we present two instances of this approach. a first model implements a variant of instance-based learning, in which a weighed similarity metric and a database of prototypical exemplars are used to predict new mappings. in the second model, grapheme-to-phoneme mappings are looked up in a compressed text-to-speech lexicon (table lookup) enriched with default mappings. we compare performance and accuracy of these approaches to a connectionist (backpropagation) approach and to the linguistic knowledge-based approach.
interpreting singular definite descriptions in database queries. the paper examines some of the characteristic features of natural language interaction with a database system and its implications for the processing of singular definite descriptions. some proposals are made for assessing the uniqueness claim of the singular definite article in the context of retrieval from a relational database. other standard assumptions such as the extensional evaluation and referent evaluation exclusively in the database - rather than within the discourse model - are critically examined.
french order without order. to account for the semi-free word order of french, unification categorial grammar is extended in two ways. first, verbal valencies are contained in a set rather than in a list. second, type-raised np's are described as two-sided functors. the new framework does not overgenerate i.e., it accepts all and only the sentences which are grammatical. this follows partly from the elimination of false lexical ambiguities - i.e., ambiguities introduced in order to account for all the possible positions a word can be in within a sentence -- and partly from a system of features constraining the possible combinations.
parametrized abstract objects for linguistic information processing. programming languages which have adequate primitives for linguistic information processing and a clear semantics at the formal computational level are now slowly emerging as a convergent effort from computer science, linguistics, and artificial intelligence. our work on the processing of a special kind of linguistic information, namely temporal information, has led us to advocate the use of a language with the following characteristic features:- high level of abstraction;- capacity for inference;- modularity.a high level of abstraction is needed to deal with complex linguistic notions which are not easily reducible to elementary data structures.a capacity for inference is required, as most criteria or tests in linguistics make use of particular kinds of deductions, at different levels of the linguistic analysis.as for modularity, a typical situation in linguistics has to do with a hierarchy of concepts or units, and the relations between those units at different levels.this paper discusses the relevance of the choice of parametrized abstract objects as tools for linguistic information processing and exemplifies the use of such objects for temporal information.
full text parsing using cascades of rules: an information extraction perspective. this paper proposes an approach to full parsing suitable for information extraction from texts. sequences of cascades of rules deterministically analyze the text, building unambiguous structures. initially basic chunks are analyzed; then argumental relations are recognized; finally modifier attachment is performed and the global parse tree is built. the approach was proven to work for three languages and different domains. it was implemented in the ie module of facile, a eu project for multilingual text classification and ie.
modeling extemporaneous elaboration. intelligent problem solving systems must be able to express their results in a coherent and flexible manner. one way this can be done is by extemporaneous elaboration, the method of language production that underlies more skilled tasks such as explanation. this paper outlines a computational model for extemporaneous elaboration that is implemented in a computer model called extemper, shows examples of its operation, and compares it with other models of language production. extemper contains the four components minimally required for elaboration: 1) an efficient method for linearizing a knowledge structure, 2) a translation/selection mechanism for producing a conceptual textbase from the knowledge structure, 3) local coherence operators which provide local connections between textbase elements, and 4) a conceptual generator to translate the coherent textbase into english.
combining distributional and morphological information for part of speech induction. in this paper we discuss algorithms for clustering words into classes from unlabelled text using unsupervised algorithms, based on distributional and morphological information. we show how the use of morphological information can improve the performance on rare words, and that this is robust across a wide range of languages.
a task independent oral dialogue model. this paper presents a human-machine dialogue model in the field of task-oriented dialogues. the originality of this model resides in the clear separation of dialogue knowledge from task knowledge in order to facilitate for the modeling of dialogue strategies and the maintenance of dialogue coherence. these two aspects are crucial in the field of oral dialogues with a machine considering the current state of the art in speech recognition and understanding techniques. one important theoretical innovation is that our dialogue model is based on a recent linguistic theory of dialogue modeling. the dialogue model considers real-life situations, as our work was based on a real man-machine corpus of dialogues.in this paper we describe the model and the designed formalisms used in the implementation of a dialogue manager module inside an oral dialogue system. an important outcome and proof of our model is that it is able to dialogue on three different applications.
fragmentation and part of speech disambiguation. that at least some syntax is necessary to support semantic processing is fairly obvious. to know exactly how much syntax is needed, however, and how and when to apply it, is still an open and crucial, albeit old, question. this paper discusses the solutions used in a semantic analyser of french called saba, developed at the university of liege, belgium. specifically, we shall argue in favor of the usefulness of two syntactic processes: fragmentation, which can be interleaved with semantic processing, and part-of-speech disambiguation, which can be performed as a preprocessing step.
a logical approach to arabic phonology. logical approaches to linguistic description, particularly those which employ feature structures, have generally treated phonology as though it was the same as orthography. this approach breaks down for languages where the phonological shape of a morpheme can be heavily dependent on the phonological shape of another, as is the case in arabic. in this paper we show how the tense logical approach investigated by blackburn (1989) can be used to encode hierarchical and temporal phonological information of the kind explored by bird (1990). then we show how some arabic morphemes may be represented and combined.
situations and prepositional phrases. this paper presents a format for representing the linguistic form of utterances, called situation schemata, which is rooted in the situation semantics of barwise and perry. a treatment of locative prepositional phrases is given, thus illustrating the generation of the situation schemata and their interpretation in situation semantics.
the genia project: corpus-based knowledge acquisition and information extraction from genome research papers. we present an outline of the genome information acquisition (genia) project for automatically extracting biochemical information from journal papers and abstracts. genia will be available over the internet and is designed to aid in information extraction, retrieval and visualisation and to help reduce information overload on researchers. the vast repository of papers available online in databases such as medline is a natural environment in which to develop language engineering methods and tools and is an opportunity to show how language engineering can play a key role on the internet.
acquisition of conceptual data models from natural language descriptions. acquiring information systems specifications from natural language description is presented as a problem class that requires a different treatment of semantics when compared with other applied nl systems such as database and operating system interfaces. within this problem class, the specific task of obtaining explicit conceptual data models from natural language text or dialogue is being investigated. the knowledge brought to bear on this task is classified into syntactic, semantic and systems analysis knowledge. investigations with a simple syntactic parse and with a semantic analysis using mccord's slot grammar are reported, and the structure of the systems analysis knowledge is considered.
coordination in unification-based grammars. within unification-based grammar formalisms, providing a treatment of cross-categorial coordination is problematic, and most current solutions either over-generate or under-generate. in this paper we consider an approach to coordination involving "composite" feature structures, which describe coordinate phrases, and present the augmentation to the logic of feature structures required to admit such feature structures. this augmentation involves the addition of two connectives, composite conjunction and composite disjunction, which interact to allow cross-categorial coordination data to be captured exactly. the connectives are initially considered to function only in the domain of atomic values, before their domain of application is extended to cover complex feature structures. satisfiability conditions for the connectives in terms of deterministic finite state automata are given, both for the atomic case and for the more complex case. finally, the prolog implementation of the connectives is discussed, and it is illustrated how, in the atomic case, and with the use of the freeze/2 predicate of second generation prologs, the connectives may be implemented.
analysis of unknown words through morphological decomposition. this paper describes a method of analysing words through morphological decomposition when the lexicon is incomplete. the method is used within a text-to-speech system to help generate pronunciations of unknown words. the method is achieved within a general morphological analyser system using koskenniemi two-level rules.
the role of initiative in tutorial dialogue. this work is the first systematic investigation of initiative in human-human tutorial dialogue. we studied initiative management in two dialogue strategies: didactic tutoring and socratic tutoring. we hypothesized that didactic tutoring would be mostly tutor-initiative while socratic tutoring would be mixed-initiative, and that more student initiative would lead to more learning (i.e., task success for the tutor). surprisingly, students had initiative more of the time in the didactic dialogues (21% of the turns) than in the socratic dialogues (10% of the turns), and there was no direct relationship between student initiative and learning. however, socratic dialogues were more interactive than didactic dialogues as measured by percentage of tutor utterances that were questions and percentage of words in the dialogue uttered by the student, and interactivity had a positive correlation with learning.
formalisms for morphographemic description. recently there has been some interest in rule formalisms for describing morphologically significant regularities in orthography of words, largely influenced by the work of koskenniemi. various implementations of these rules are possible, but there are some weaknesses in the formalism as it stands. an alternative specification formalism is possible which solves some of the problems. this new formalism can be viewed as a variant of the "pure" koskenniemi model with certain constraints relaxed. the new formalism has particular advantages for multiple character changes. an interpreter has been implemented for the formalism and a significant subset of english morphographemics has been described, but it has yet to be used for describing other languages.
an extension of earley's algorithm for s-attributed grammars. attribute grammars are an elegant formalization of the augmented context-free grammars characteristic of most current natural language systems. this paper presents an extension of earley's algorithm to knuth's attribute grammars, considering the case of s-attributed grammars. for this case, we study the conditions on the underlying base grammar under which the extended algorithm may be guaranteed to terminate. finite partitioning of attribute domains is proposed to guarantee the termination of the algorithm, without the need for any restrictions on the context-free base.
a specification language for lexical functional grammars. this paper defines a language &lambda; for specifying lfg grammars. this enables constraints on lfg's composite ontology (c-structures synchronised with f-structures) to be stated directly; no appeal to the lfg construction algorithm is needed. we use &lambda; to specify schemata annotated rules and the lfg uniqueness, completeness and coherence principles. broader issues raised by this work are noted and discussed.
esfinge a question answering system in the web using the web. esfinge is a general domain portuguese question answering system. it tries to take advantage of the great amount of information existent in the world wide web. since portuguese is one of the most used languages in the web and the web itself is a constantly growing source of updated information, this kind of techniques are quite interesting and promising.
talking about trees. in this paper we introduce a modal language lt for imposing constraints on trees, and an extension lt (lf) for imposing constraints on trees decorated with feature structures. the motivation for introducing these languages is to provide tools for formalising grammatical frameworks perspicuously, and the paper illustrates this by showing how the leading ideas of gpsg can be captured in lt (lf).in addition, the role of modal languages (and in particular, what we have called layered modal languages) as constraint formalisms for linguistic theorising is discussed in some detail.
an efficient implementation of a new dop model. two apparently opposing dop models exist in the literature: one which computes the parse tree involving the most frequent subtrees from a treebank and one which computes the parse tree involving the fewest subtrees from a treebank. this paper proposes an integration of the two models which outperforms each of them separately. together with a pcfg-reduction of dop we obtain improved accuracy and efficiency on the wall street journal treebank. our results show an 11% relative reduction in error rate over previous models, and an average processing time of 3.6 seconds per wsj sentence.
integrating semantics and flexible syntax by exploiting isomorphism between gramnatical and senantical relations. this work concerns integration between syntax and semantics. syntactic and semantic activities rely on separate bodies of knowledges. integration is obtained by exploiting the isomorphism between grammatical relations (among immediate constituents) and conceptual relations, thanks to a limited set of formal mapping rules. syntactic analysis does not construct all the explicit parse trees but just a graph that represents all the plausible grammatical relations among immediate constituents. such graph gives the semantic interpreter, based on conceptual graphs formalism, the discriminative power required to establish conceptual relations.
using an annotated corpus as a stochastic grammar. in data oriented parsing (dop), an annotated corpus is used as a stochastic grammar. an input string is parsed by combining subtrees from the corpus. as a consequence, one parse tree can usually be generated by several derivations that involve different subtrees. this leads to a statistics where the probability of a parse is equal to the sum of the probabilities of all its derivations. in (scha, 1990) an informal introduction to dop is given, while (bod, 1992a) provides a formalization of the theory. in this paper we compare dop with other stochastic grammars in the context of formal language theory. it it proved that it is not possible to create for every dop-model a strongly equivalent stochastic cfg which also assigns the same probabilities to the parses. we show that the maximum probability parse can be estimated in polynomial time by applying monte carlo techniques. the model was tested on a set of hand-parsed strings from the air travel information system (atis) spoken language corpus. preliminary experiments yield 96% test set parsing accuracy.
a strategy for dynamic interpretation: a fragment and an implementation. the strategy for natural language interpretation presented in this paper implements the dynamics of context change by translating natural language texts into a meaning representation language consisting of (descriptions of) programs, in the spirit of dynamic predicate logic (dpl) [5]. the difference with dpl is that the usual dpl semantics is replaced by an error state semantics [2]. this allows for the treatment of unbound anaphors, as in dpl, but also of presuppositions and presupposition projection.the use of this dynamic interpretation strategy is demonstrated in an implementation of a small fragment of natural language which handles unbound pronoun antecedent links, where it is assumed that the intended links are indicated in the input string, and uniqueness presuppositions of definite descriptions. the implementation consists of a syntax module which outputs parse trees, a semantic module mapping parse trees to dpl representations, a representation processor which determines truth conditions, falsity conditions and presupposition failure conditions, and an evaluator of these conditions in a database model.the implementation uses the logic programming language g&ouml;del [6], an experimental successor of prolog, with similar functionality and expressiveness, but with an improved declarative semantics.
efficient processing of flexible categorial grammar. from a processing point of view, however, flexible categorial systems are problematic, since they introduce spurious ambiguity. in this paper, we present a flexible categorial grammar which makes extensive use of the product-operator, first introduced by lambek (1958). the grammar has the property that for every reading of a sentence, a strictly left-branching derivation can be given. this leads to the definition of a subset of the grammar, for which the spurious ambiguity problem does not arise and efficient processing is possible.
multiple interpreters in a principle-based model of sentence processing. this paper describes a computational model of human sentence processing based on the principles and parameters paradigm of current linguistic theory. the syntactic processing model posits four modules, recovering phrase structure, long-distance dependencies, coreference, and thematic structure. these four modules are implemented as meta-interpreters over their relevant components of the grammar, permitting variation in the deductive strategies employed by each module. these four interpreters are also 'coroutined' via the freeze directive of constraint logic programming to achieve incremental interpretation across the modules.
prediction in chart parsing algorithms for categorial unification grammar. natural language systems based on categorial unification grammar (cug) have mainly employed bottom-up parsing algorithms for processing. conventional prediction techniques to improve the efficiency of the parsing process, appear to fall short when parsing cug. nevertheless, prediction seems necessary when parsing grammars with highly ambiguous lexicons or with noncanonical categorial rules. in this paper we present a lexicalist prediction technique for cug and show that this may lead to considerable gains in efficiency for both bottom-up and top-down parsing.
ellipsis and quantification: a substitutional approach. the paper describes a substitutional approach to ellipsis resolution giving comparable results to (dalrymple et al., 1991), but without the need for order-sensitive interleaving of quantifier scoping and ellipsis resolution. it is argued that the order-independence results from viewing semantic interpretation as building a description of a semantic composition, instead of the more common view of interpretation as actually performing the composition.
head-driven parsing for lexicalist grammars: experimental results. we present evidence that head-driven parsing strategies lead to efficiency gains over standard parsing strategies, for lexicalist, concatenative and unification-based grammars. a head-driven parser applies a rule only after a phrase matching the head has been derived. by instantiating the head of the rule important information is obtained about the left-hand-side and the other elements of the ritht-hand-side. we have used two different head-driven parsers and a number of standard parsers to parse with lexicalist grammars for english and for dutch. the results indicate that for important classes of lexicalist grammars it is fruitful to apply parsing strategies which are sensitive to the linguistic notion 'head'.
investigating gis and smoothing for maximum entropy taggers. this paper investigates two elements of maximum entropy tagging: the use of a correction feature in the generalised iterative scaling (gis) estimation algorithm, and techniques for model smoothing. we show analytically and empirically that the correction feature, assumed to be required for the correctness of gis, is unnecessary. we also explore the use of a gaussian prior and a simple cutoff for smoothing. the experiments are performed with two tagsets: the standard penn treebank pos tagset and the larger set of lexical types from combinatory categorial grammar.
an endogeneous corpus-based method for structural noun phrase disambiguation. in this paper, we describe a method for structural noun phrase disambiguation which mainly relies on the examination of the text corpus under analysis and doesn't need to integrate any domain-dependent lexico- or syntactico-semantic information. this method is implemented in the terminology extraction sottware lexter. we first explain why the integration of lexter in the lexter-k project, which aims at building a tool for knowledge extraction from large technical text corpora, requires improving the quality of the terminolgy extracted by lexter. then we briefly describe the way lexter works and show what kind of disambiguation it has to perform when parsing "maximal-length" noun phrases. we introduce a method of disambiguation which relies on a very simple idea: whenever lexter has to choose among several competing noun sub-groups in order to disambiguate a maximal-length noun phrase, it checks each of these sub-groups if it occurs anywhere else in the corpus in a non-ambiguous situation, and then it makes a choice. the half-a-million words corpus analysis resulted in an efficient strategy of disambiguation. the average rates are:27% no disambiguation70% correct disambiguation3% wrong disambiguation
abstract control structures and the semantics of quantifiers. intuitively, a <u>quantifier</u> is any word or phrase that expresses a meaning that answers one of the questions "how many?" or "how much?" typical english examples include <u>all, no, many, few, some but not many, all but at most a very few, wherever, whoever, whoever there is,</u> and also, it can be arguesd, <u>only</u> (keenan, 1971), <u>also</u> (cushing, 1978b), and <u>the</u> (chomsky, 1977), in this paper we review an empirically motivated analysis of such meanings (cushing, 1976; 1982a) and draw out its computational significance. for purposes of illustration, we focus our attention on the meanings expressed by the english words <u>whatever</u> and <u>some</u>, commonly represented, respectively, by the symbols "v" and "3", but most of what we say will generalize to the other meanings of this class.in section i, we review the notion of satisfaction in a model, through which logical formulas are customarily imbued implicitly with meaning. in section 2, we discuss quantifier relativization, a notion that becomes important for meanings other than v and 3. in section 3, we use these two notions to characterize quantifier meanings as structured function of a certain sort. in section 4, we discuss the computational significance of that analysis. in section 5, we elaborate on this significance by outlining a notion of abstract control structure that the analysis instantiates.
term extraction + term clustering: an integrated platform for computer-aided terminology. a novel technique for automatic thesaurus construction is proposed. it is based on the complementary use of two tools: (1) a term extraction tool that acquires term candidates from tagged corpora through a shallow grammar of noun phrases, and (2) a term clustering tool that groups syntactic variants (insertions). experiments performed on corpora in three technical domains yield clusters of term candidates with precision rates between 93% and 98%.
an automatic speech recognition system for the italian language. an automatic speech recognition system for italian language has been developed at ibm italy scientific center in rome. it is able to recognize in real time natural language sentences, composed with words from a dictionary of 6500 items, dictated by a speaker with short pauses among them. the system is speaker dependent, before using it the speaker has to perform the training stage reading a predefined text 15--20 minutes long. it runs on an architecture composed by an ibm 3090 mainframe and a pc/at based workstation with signal processing equipments.
cooperative error handling and shallow processing. this paper is concerned with the detection and correction of sub-sentential english text errors. previous spelling programs, unless restricted to a very small set of words, have operated as post-processors. and to date, grammar checkers and other programs which deal with ill-formed input usually step directly from spelling considerations to a full-scale parse, assuming a complete sentence. work described below is aimed at evaluating the effectiveness of shallow (sub-sentential) processing and the feasibility of cooperative error checking, through building and testing appropriately an error-processing system. a system under construction is outlined which incorporates morphological checks (using new two-level error rules) over a directed letter graph, tag positional trigrams and partial parsing. intended testing is discussed.
a tool for the automatic creation, extension and updating of lexical knowledge bases. a tool is described which helps in the creation, extension and updating of lexical knowledge bases (lkbs). two levels of representation are distinguished: a static storage level and a dynamic knowledge level. the latter is an object-oriented environment containing linguistic and lexicographic knowledge. at the knowledge level, constructors and filters can be defined. constructors are objects which extend the lkb both horizontally (new information) and vertically (new entries) using the linguistic knowledge. filters are objects which derive new lkbs from existing ones thereby optionally changing the storage structure. the latter use lexicographic knowledge.
cascaded markov models. this paper presents a new approach to partial parsing of context-free structures. the approach is based on markov models. each layer of the resulting structure is represented by its own markov model, and output of a lower layer is passed as input to the next higher layer. an empirical evaluation of the method yields very good results for np/pp chunking of german newspaper texts.
empirical studies of discourse representations for natural language interfaces. we present the results from a series of experiments aimed at uncovering the discourse structure of man-machine communication in natural language (wizard of oz experiments). the results suggest the existence of different classes of dialogue situations, requiring computational discourse representations of various complexity. important factors seem to be the number of different permissible tasks in the system and to what extent the system takes initiative in the dialogue. we also analyse indexical expressions and especially the use of pronouns, and suggest a psychological explanation of their restricted occurrence in these types of dialogues.
non standard uses of if. the present study examines the semantic problems involved in computing the meaning of the non standard uses of if. the central question is whether or not it is necessary to introduce different meanings of if.austin proposed two non standard meanings for if. we show that these can be accounted for by the standard meaning together with shifts in the position of the speech act within the sentence. these uses of if are among the 9 different non standard uses which we found in a sample of if sentences taken from the brown university corpus:1. counterfactual: if e had stuck to his plan he'd still be famous.2. factual: if r was a liar, he was also a canny gentleman.3. conditional speech act: you may come back to strasbourg, now, if you wish.4. performative speech act: he vowed vengence on l, if ever the chance came his way.5. noun clause: he wondered if the audience would let him finish.6. doubtful presupposition perfect entities, if they move at all, don't move to ...7. restrictive social relations impose courtesy, if not sympathy, ...8. concessive9. protasis only"if you want to see -" "never mind", she said sternly.each use was examined to see whether it could be accounted for by the standard meaning of if, together with other features of the sentence. similar differences in usage should then be found with other scs. this was the case for the first four uses. in three uses (6, 7, 8) if may/must occur in a phrase rather than in a full clause. the hypothesis that these uses can be derived from the standard meaning of if in an equivalent clause was explored and rejected. two of these uses (6, 7) require a material implication interpretation of if, also necessary for a few of the standard conditional sentences.two uses (5, 9) require only that the truth value of the following clause/phrase is unspecified. this is a property that all the uses have in common (with the exception of the factual use where the truth of the protasis is used to emphasise the truth of the apodosis) and is thus the feature that relates the different meanings of if. the standard use and the non standard uses using the standard meaning (1,2,3,4) require, in addition, that there is an inference relation from the protasis (the if sub clause) to the apodosis (the main clause in which the if clause is embedded).so we propose that three different meanings of if are required: inference (including the standard use), material implication (uses 6,7) and just doubting the truth value of the following proposition (uses 5,9). each of these three uses may be expected to be translated by different words in other languages, e.g. in dutch by als, zo and of (except for use 8) respectively.
towards better understanding of anaphora. this paper presents a syntactical method of interpreting pronouns in polish. using the surface structure of the sentence as well as grammatical and inflexional information accessible during syntactic analysis, an <u>area of reference</u> is marked out for each personal and possessive pronoun. this area consists of a few <u>internal areas</u> inside the current sentence and an <u>external area,</u> i.e. the part of the text preceding it. in order to determine that area of reference several syntactic sentence-level restrictions on anaphora interpretation are formulated.next, when looking at the area of pronoun's reference, all nps which number-gender agree with the pronoun can be selected and this way the set of <u>surface referents</u> of each pronoun can be created. it can be used as data for further semantic analysis.
the linguistic basis of text generation. this study presents an original and penetrating analysis of the complex problems surrounding the automatic generation of natural language text. laurence danlos provides a valuable critical review of current research in this important and increasingly active field, and goes on to describe a new theoretical model that is thoroughly grounded in linguistic principles.the model emphasizes the semantic, syntactic and lexical constraints that must be dealt with when establishing a relationship between meaning and form, and it is consideration of such linguistic constraints that determines danlos' generation algorithm. the book concludes with a description of a generation system based on this algorithm which produces texts in several domains and also a system for the synthesis of spoken messages from semantic representations.the book is a significant addition to the literature on text generation, and will be of particular interest to all computational linguists and ai researchers who have wrestled with the problem of vocabulary selection.
automatic acronym recognition. this paper deals with the problem of recognizing and extracting acronymdefinition pairs in swedish medical texts. this project applies a rule-based method to solve the acronym recognition task and compares and evaluates the results of different machine learning algorithms on the same task. the method proposed is based on the approach that acronym-definition pairs follow a set of patterns and other regularities that can be usefully applied for the acronym identification task. supervised machine learning was applied to monitor the performance of the rule-based method, using memory based learning (mbl). the rule-based algorithm was evaluated on a hand tagged acronym corpus and performance was measured using standard measures recall, precision and f-score. the results show that performance could further improve by increasing the training set and modifying the input settings for the machine learning algorithms. an analysis of the errors produced indicates that further improvement of the rule-based method requires the use of syntactic information and textual pre-processing.
constraint based integration of deep and shallow parsing techniques. to investigate the contributions of taggers or chunkers to the performance of a deep syntactic parser, weighted constraint dependency grammars have been extended to also take into consideration information from external sources. using a weak information fusion scheme based on constraint optimization techniques, a parsing accuracy has been achieved which is comparable to other (stochastic) parsers.
text alignment in the real world: improving alignments of noisy translations using common lexical features, string matching strategies and n-gram comparisons. alignment methods based on byte-length comparisons of alignment blocks have been remarkably successful for aligning good translations from legislative transcriptions. for noisy translations in which the parallel text of a document has significant structural differences, byte-alignment methods often do not perform well. the pan american health organization (paho) corpus is a series of articles that were first translated by machine methods and then improved by professional translators. many of the spanish paho texts do not share formatting conventions with the corresponding english documents, refer to tables in stylistically different ways and contain extraneous information. a method based on a dynamic programming framework, but using a decision criterion derived from a combination of byte-length ratio measures, hard matching of numbers, string comparisons and n-gram co-occurrence matching substantially improves the performance of the alignment process.
planning for problem formulation in advice-giving dialogue. we distinguish three main, overlapping activities in an advice-giving dialogue: problem formulation, resolution, and explanation. this paper focuses on a problem formulation activity in a dialogue module which interacts on one side with an expert problem solver for financial investing and on the other side with a natural language front-end. several strategies which reflect specific aspects of person-machine advice-giving dialogues are realized by incorporating planning at a high-level of dialogue.
a phonological processor for italian. a computer program for the automatic translation of any text of italian into naturally fluent synthetic speech is presented. the program, or phonological processor (hence fp) maps into prosodic structures the phonological rules of italian. structural information is provided by such hierarchical prosodic constitutents as syllable (s), metrical foot (mf), phonological word (pw), intonational group (ig). onto these structures, phonological rules are applied such as the "letter-to-sound" rules, automatic word stress rules, internal stress hierarchy rules indicating secondary stress, external sandhi rules, phonological focus assignment rules, logical focus assignment rules. the fp constitutes also a model to simulate the reading process aloud, and the psycholinguistics and cognitive aspects related will be discussed in the computational model of the fp. at present, logical focus assignment rules and the computational model are work in progress still to be implemented in the fp. recorded samples of automatically produced synthetic speech will be presented at the conference to illustrate the functioning of the rules.
parsing defficulties & phonological processing in italian. a recognition grammar to supply information to a text-to-speech system for the synthesis of italian must rely heavily upon lexical information, in order to instantiate the appropriate grammatical relations.italian is an almost free word order language which nonetheless adopts fairly analysable strategies to move major constituents: some of these can strongly affect the functioning of the phonological component. two basic claims will be made: i. difficulties in associating grammatical functions to constituent structure can be overcome only if lexical theory is adopted as a general theoretical framework, and translated into adequate computational formalisms like atn or chart; ii. decisions made at previous point affect focus structure construal rules, which are higher level phonological rules which individuate intonation centre, build up adequate intonational groups and assign pauses to adequate sites, all being very sensitive to syntactic and semantic information.we will concentrate on subject/object function association to c-structure in italian, and its relation to atn formalism, in particular hold mechanism and flagging. then we will show how syntactic decisions interact with an intonation grammar. we shall also introduce two functional notions: structure reversibility vs. functional reversibility in italian.
a preference mechanism based on multiple criteria resolution. this paper presents an experimental preference tool designed, implemented and tested in the eurotra project. the mechanism is based on preference rules which can either compare subtrees pairwise or single out a subtree on the basis of some specified constraints. scoring permits combining the effects of various preference rules.
discovering corpus-specific word senses. this paper presents an unsupervised algorithm which automatically discovers word senses from text. the algorithm is based on a graph model representing words and relationships between them. sense clusters are iteratively computed by clustering the local graph of similar words around an ambiguous word. discrimination against previously extracted sense clusters enables us to discover new senses. we use the same data for both recognising and resolving ambiguity.
on the notion of uniqueness. in the paper it is argued that for some linguistic phenomena, current discourse representation structures are insufficiently finegrained, both from the perspective of serving as representation in nlp and from a truth conditional perspective. one such semantic phenomenon is uniqueness. it is demonstrated that certain elements are forced to have a unique interpretation, from a certain point in discourse onwards. this could be viewed as the semantic counterpart of surface order. although it has always been acknowledged that the left-to-right order of constituents influences the meaning of an utterance, it is, for example, not reflected in standard discourse representation theory ([kamp, 1981]). in the paper, an alternative representation for unique constituents will be proposed, resulting in asymmetry of certain conjoined conditions in a drs-representation.
literal movement grammars. literal movement grammars (lmgs) provide a general account of extraposition phenomena through an attribute mechanism allowing top-down displacement of syntactical information. lmgs provide a simple and efficient treatment of complex linguistic phenomena such as cross-serial dependencies in german and dutch---separating the treatment of natural language into a parsing phase closely resembling traditional context-free treatment, and a disambiguation phase which can be carried out using matching, as opposed to full unification employed in most current grammar formalisms of linguistical relevance.
how to restrict ambiguity of discourse. we single out a class of <u>prototypes</u> i.e., a class of constructions forcing the obligatory coreference or obligatory noncoreference. an essential feature of prototypes is their undistinctiveness. in this sense they are the most natural and efficient means of communication in discourse.the non-application of prototype should be well motivated. this leads to the <u>rule of restricted choice</u> stating that whenever it is possible the application of a prototype should be preferred.the rule of the restricted choice suggests the general outline of interpreting ambiguous sentences, strictly speaking, the method of ordering admissible interpretations: those which can be equivalently expressed by means of a prototype are less probable. in other words, the rule of the restricted choice can be regarded as some kind of mechanism ordering the hypotheses for computation.
fail-soft ("emergency") measures in a production-oriented mt system. a system of fail-soft (emergency) measures for a production-oriented mt system is discussed, stating first the specific purposes of such a system, and showing then, how these measures are being used in the system of english-to-czech machine translation as prepared by the group of mathematical linguistics at charles university in prague.
ruslan - an mt system between closely related languages. a project of machine translation of czech computer manuals into russian is described, presenting first a description of the overall system structure and concentrating then mainly on input text preparation and a parsing algorithm based on bottom-up parser programmed in colmerauer's q-systems.
tenses as anaphora. a proposal to deal with french tenses in the frame-work of discourse representation theory is presented, as it has been implemented for a fragment at the ims. it is based on the theory of tenses of h. kamp and ch. rohrer.instead of using operators to express the meaning of the tenses the reichenbachian point of view is adopted and refined such that the impact of the tenses with respect to the meaning of the text is understood as contribution to the integration of the events of a sentences in the event structure of the preceeding text. thereby a system of relevant times provided by the preceeding text and by the temporal adverbials of the sentence being processed is used. this system consists of one or more reference times and temporal perspective times, the speech time and the location time. the special interest of our proposal is to establish a plausible choice of "anchors" for the new event out of the system of relevant times and to update this system of temporal coordinates correctly. the problem of choice is largely neglected in the literature. in opposition to the approach of kamp and rohrer the exact meaning of the tenses is fixed by the resolution component and not in the process of syntactic analysis.
structure of sentence and inferencing in question answering. in the present paper we characterize in more detail some of the aspects of a question answering system using as its starting point the underlying structure of sentences (which with some approaches can be identified with the level of meaning or of logical form). first of all, the criteria are described that are used to identify the elementary units of underlying structure and the operations conjoining them into complex units (sect.1), then the main types of units and operations resulting from an empirical investigation on the basis of the criteria are registered (sect.2), and finally the rules of inference, accounting for the relevant aspects of the relationship between linguistic and cognitive structures are illustrated (sect.3).
resolving discourse deictic anaphora in dialogues. most existing anaphora resolution algorithms are designed to account only for anaphors with np-antecedents. this paper describes an algorithm for the resolution of discourse deictic anaphors, which constitute a large percentage of anaphors in spoken dialogues. the success of the resolution is dependent on the classification of all pronouns and demonstratives into individual, discourse deictic and vague anaphora. finally, the empirical results of the application of the algorithm to a corpus of spoken dialogues are presented.
towards an automatic identipeation of topic and focus. the purpose of the paper is (i) to substantiate the claim that the output of an automatic analysis should represent among other things also the hierarchy of topic-focus articulation, and (ii) to present a general procedure for determining the topic-focus articulation in czech and english.(i) the following requirements on the output of an automatic analysis are significant:(a) in the output of the analysis it should be marked which elements of the analyzed sentence belong to its topic and which to the focus;(b) the scale of communicative dynamism (cd) should also be identified for every representation of a meaning of the analyzed sentence, since the degrees of cd correspond to the unmarked distribution of quantifier scopes in the semantic interpretation of the sentences;(c) the analysis should also distinguish topicless sentences from those having a topic, which is relevant for the scope of negation.(ii) for an automatic recognition of topic, focus and the degrees of cd, two points are crucial:(a) either the input language has(a considerable degree of) the so-called free word order (as in czech, russian), or its word order is determined mainly by the grammatical relations (as in english, french);(b) either the input is spoken discourse (and the recognition procedure includes an acoustic analysis), or written (printed) texts are analyzed.in accordance with these points, a general procedure for determining topic, focus and the degrees of cd is formulated for czech and english, with some hints how the preceding context can be taken into account.
multilevel semantic analysis in an automatic speech understanding and dialog system. at our institute a speech understanding and dialog system is developed. as an example we model an information system for timetables and other information about intercity trains.in understanding spoken utterances, additional problems arise due to pronunciation variabilities and vagueness of the word recognition process. experiments so far have also shown that the syntactical analysis produces a lot more hypotheses instead of reducing the number of word hypotheses. the reason for that is the possibility of combining nearly every group of word hypotheses which are adjacent with respect to the speech signal to a syntactically correct constituent. also, the domain independent semantic analysis cannot be used for filtering, because a syntactic sentence hypothesis normally can be interpreted in several different ways, respectively a set of syntactic hypotheses for constituents can be combined to a lot of semantically interpretible sentences. because of this combinatorial explosion it seems to be reasonable to introduce domain dependent and contextual knowledge as early as possible, also for the semantic analysis. on the other hand it would be more efficient prior to the whole semantic interpretation of each syntactic hypothesis or combination of syntactic hypotheses to find possible candidates with less effort and interpret only the more probable ones.
identifying topic and focus by an automatic procedure. an algorithm for automatic identification of topic and focus of the sentence is presented, based on dependency syntax and using written input, which is much more ambiguous than spoken utterance.
automating the acquisition of bilingual terminology. as the acquisition problem of bilingual lists of terminological expressions is formidable, it is worthwhile to investigate methods to compile such lists as automatically as possible. in this paper we discuss experimental results for a number of methods, which operate on corpora of previously translated texts.
parsing with polymorphism. certain phenomena resist coverage within the lambek calculus, such as scope-ambiguity and non-peripheral extraction. i have argued in previous work that an extension called polymorphic lambek calculus (plc), which adds variables and their universal quantification, covers these phenomena. however, a major problem is the absence of a known decision procedure for plc grammars. this paper proposes a decision procedure which covers a subset of all the possible plc grammars, a subset which, however, includes the plc grammars with wide coverage. the decision procedure is shown to be terminating, and correct, and a prolog implementation of it is described.
an atn treatment wh-movement. an atn-parser is presented with emphasis on the treatment of those phenomena which in the framework of transformational grammar are subsumed under the concept of wh-movement. the approach taken tries to embed these constructions into an atn grammar in a general, linguistically motivated and in terms of the atn grammar formalism descriptive way. to accomplish this goal the approach described incorporates the basic principles governing such constructions as formulated in the framework of the trace theory proposed in the development of the extended standard theory (est). thus a unified treatment for both relative clauses and wh-questions is achieved.
profit: prolog with features, inheritance and templates. profit is an extension of standard prolog with features, inheritance and templates. profit allows the programmer or grammar developer to declare an inheritance hierarchy, features and templates. sorted feature terms can be used in profit programs together with prolog terms to provide a clearer description language for linguistic structures. profit compiles all sorted feature terms into a prolog term representation, so that the built-in prolog term unification can be used for the unification of sorted feature structures, and no special unification algorithm is needed. profit programs are compiled into prolog programs, so that no meta-interpreter is needed for their execution. profit thus provides a direct step from grammars developed with sorted feature terms to prolog programs usable for practical nlp systems.
a probabilistic context-free grammar for disambiguation in morphological parsing. one of the major problems one is faced with when decomposing words into their constituent parts is ambiguity: the generation of multiple analyses for one input word, many of which are implausible. in order to deal with ambiguity, the mor-phological parser morpa is provided with a probabilistic context-free grammar (pcfg), i.e. it combines a "conventional" context-free morphological grammar to filter out ungrammatical segmentations with a probability-based scoring function which determines the likelihood of each successful parse. consequently, remaining analyses can be ordered along a scale of plausibility. test performance data will show that a pcfg yields good results in morphological parsing. morpa is a fully implemented parser developed for use in a text-to-speech conversion system.
well-nested parallelism constraints for ellipsis resolution. the constraint language for lambda structures (clls) is an expressive tree description language. it provides a uniform framework for underspecified semantics, covering scope, ellipsis, and anaphora. efficient algorithms exist for the sublanguage that models scope. but so far no terminating algorithm exists for sublanguages that model ellipsis. we introduce well-nested parallelism constraints and show that they solve this problem.
horn extended feature structures: fast unification with negation and limited disjunction. the notion of a horn extended feature structure (hoxf) is introduced, which is a feature structure constrained so that its only allowable extensions are those satisfying some set of horn clauses in feature-term logic. hoxf's greatly generalize ordinary feature structures in admitting explicit representation of negative and implicational constraints. in contradistinction to the general case in which arbitrary logical constraints are allowed (for which the best known algorithms are exponential), there is a highly tractable algorithm for the unification of hoxf's.
bilingually motivated domain-adapted word segmentation for statistical machine translation. we introduce a word segmentation approach to languages where word boundaries are not orthographically marked, with application to phrase-based statistical machine translation (pb-smt). instead of using manually segmented monolingual domain-specific corpora to train segmenters, we make use of bilingual corpora and statistical word alignment techniques. first of all, our approach is adapted for the specific translation task at hand by taking the corresponding source (target) language into account. secondly, this approach does not rely on manually segmented training data so that it can be automatically adapted for different domains. we evaluate the performance of our segmentation approach on pb-smt tasks from two domains and demonstrate that our approach scores consistently among the best results across different data conditions.
remarks on plural anaphora. the interpretation of plural anaphora often requires the construction of complex reference objects (refos) out of refos which were formerly introduced not by plural terms but by a number of singular terms only. often, several complex refos can be constructed, but only one of them is the preferred referent for the plural anaphor in question. as a means of explanation for preferred and non-preferred interpretations of plural anaphora, the concept of a common association basis (cab) for the potential atomic parts of a complex object is introduced in the following. cabs pose conceptual constraints on the formation of complex refos in general. we argue that in cases where a suitable cab for the atomic refos introduced in the text exists, the corresponding complex refo is constructed as early as in the course of processing the antecedent sentence and put into the focus domain of the discourse model. thus, the search for a referent for a plural anaphor is constrained to a limited domain of refos according to the general principles of focus theory in nlp. further principles of interpretation are suggested which guide the resolution of plural anaphora in cases where more than one suitable complex refo is in focus.
collocations in multilingual generation. we present a proposal for the structuring of collocation knowledge' in the lexicon of a multilingual generation system and show to what extent it can be used in the process of lexical selection. this proposal is part of polygloss, a new research project on multilingual generation, and it has been inspired by work carried out in the semsyn project (see e.g. [r&ouml;sner 1988]). the descriptive approach presented in this proposal is based on a combination of results from recent lexico-graphical research and the application of meaning-text-theory (mtt) (see e.g. [mel'&ccaron;uk et al. 1981], [mel'&ccaron;uk et al. 1984]). we first outline the overall structure of the dictionary system that is needed by a multilingual generator; section 2 gives an overview of the results of lexicographical work on collocations and compares them with "lexical functions" as used in meaning-text-theory. section 3 shows how we intend to integrate collocations in the generation dictionary and how "lexical functions" can be used in generation.
neural network probability estimation for broad coverage parsing. we present a neural-network-based statistical parser, trained and tested on the penn treebank. the neural network is used to estimate the parameters of a generative model of left-corner parsing, and these parameters are used to search for the most probable parse. the parser's performance (88.8% f-measure) is within 1% of the best current parsers for this task, despite using a small vocabulary size (512 inputs). crucial to this success is the neural network architecture's ability to induce a finite representation of the unbounded parse history, and the biasing of this induction in a linguistically appropriate way.
inference in datr. datr is a declarative language for representing a restricted class of inheritance networks, permitting both multiple and default inheritance. the principal intended area of application is the representation of lexical entries for natural language processing, and we use examples from this domain throughout. in this paper we present the syntax and inference mechanisms for the language. the goal of the datr enterprise is the design of a simple language that (i) has the necessary expressive power to encode the lexical entries presupposed by contemporary work in the unification grammar tradition, (ii) can express all the evident generalizations about such entries, (iii) has an explicit theory of inference, (iv) is computationally tractable, and (v) has an explicit declarative semantics. the present paper is primarily concerned with (iii), though the examples used may hint at our strategy in respect of (i) and (ii).
mixing modes of linguistic description in categorial grammar. recent work within the field of categorial grammar has seen the development of approaches that allow different modes of logical behaviour to be displayed within a single system, something corresponding to making available differing modes of linguistic description. earlier attempts to achieve this goal have employed modal operators called structural modalities, whose use presents a number of problems. i propose an alternative approach, involving co-existence and interrelation of different sublogics, that eliminates the need for structural modalities, whilst maintaining the descriptive power they provide.
wysiwym - building user interfaces with natural language feedback. wysiwym ('what you see is what you meant') is a user-interface technique which uses natural language generation (nlg) technology to provide feedback for user interactions. to date, the technology has been applied in a number of demonstrator applications, using customised, non-portable implementations. in this demonstration, we introduce a wysiwym library package, designed to be used as a modular component of a larger java-based application. we show how the overall design of the package aims to support a range of possible applications using simple configuration options and java subclassing, and illustrate the approach using examples ranging from the simplest proof-of-concept application to a complex web-delivered authoring tool for pharmaceutical leaflets.
parsing and derivational equivalence. it is a tacit assumption of much linguistic inquiry that all distinct derivations of a string should assign distinct meanings. but despite the tidiness of such derivational uniqueness, there seems to be no a priori reason to assume that a grammar must have this property. if a grammar exhibits derivational equivalence, whereby distinct derivations of a string assign the same meanings, naive exhaustive search for all derivations will be redundant, and quite possibly intractable. in this paper we show how notions of derivation-reduction and normal form can be used to avoid unnecessary work while parsing with grammars exhibiting derivational equivalence. with grammar regarded as analogous to logic, derivations are proofs; what we are advocating is proof-reduction, and normal form proof; the invocation of these logical techniques adds a further paragraph to the story of parsing-as-deduction.
experiments on candidate data for collocation extraction. the paper describes ongoing work on the evaluation of methods for extracting collocation candidates from large text corpora. our research is based on a german treebank corpus used as gold standard. results are available for adjective+noun pairs, which proved to be a comparatively easy extraction task. we plan to extend the evaluation to other types of collocations (e.g., pp+verb pairs).
descriptional anaphora in discourse representation theory. standard discourse representation theory (drt) was designed mainly to explain the so-called donkey-sentences. the pronouns playing such a prominent role in all these sentences belong, however, exclusively to one (particularly simple) type of pronoun. we try to extend drt in order to cover an equally important type of pronoun, the so-called "descriptional" pronoun. discourse referents are now used to carry information on the intension of their referents as well as on the extension. this allows, at the same time, to suggest accessibility rules for pronouns which are more appropriate than those suggested by traditional drt. these new rules are based on the genericness of the sentences involved.
iteration, habituality and verb form semantics. the verb forms are often claimed to convey two kinds of information:1. whether the event described in a sentence is present, past or future (= deictic information.2. whether the event described in a sentence is presented, as completed, going on, just starting or being finished (= aspectual information)it will be demonstrated in this paper that one has to add a third component to the analysis of verb form meanings, namely whether or not they express habituality.the framework of the analysis is model-theoretic semantics.
how does natural language quantify? it has traditionally been assumed that natural language uses explicit quantifier expressions (such as "all" and "most", "the" and "a") for the purpose of quantification. we argue that expressions of the first type are comparatively rare in real world natural language sentences, and that the latter (articles) cannot be considered straightforward quantifiers in the first place. however, practically all applications of natural language processing require sentences to be quantified unambiguously. we list a few possible (syntactical, semantical, and "pragmatical") sources of "implicit" quantificational information in natural language; they combine in sometimes intricate ways to give a sentence a (more or less) unambiguous quantification.
a machine learning approach to the identification of wh gaps. in this paper, we pursue a multi-modular, statistical approach to wh dependencies, using a feedforward network as our modeling tool. the empirical basis of this model and the availability of performance measures for our system address deficiencies in earlier computational work on wh gaps, which require richer sources of semantic and lexical information in order to run. the statistical nature of our models allows them to be simply combined with other modules of grammar, such as a syntactic parser.
generating sentences from different perspectives. certain pairs or groups of sentences appear to be semantically distinct, yet specify the same underlying state of affairs, from different perspectives. this leads to questions about what that underlying state of affairs might be, and, for generation, how and why the alternative expressions might be produced. this paper looks at how such sentences may be generated in a natural language interface to a database system.
algorithms for analysing the temporal structure of discourse. we describe a method for analysing the temporal structure of a discourse which takes into account the effects of tense, aspect, temporal adverbials and rhetorical structure and which minimises unnecessary ambiguity in the temporal structure. it is part of a discourse grammar implemented in carpenter's ale formalism. the method for building up the temporal structure of the discourse combines constraints and prefernces: we use constraints to reduce the number of possible structures, exploiting the hpsg type hierarchy and unification for this purpose; and we apply preferences to choose between the remaining options using a temporal centering mechanism. we end by recommending that an underspecified representation of the structure using these techniques be used to avoid generating the temporal/rhetorical structure until higher-level information can be used to disambiguate.
a dynamic logic formalisation of the dialogue gameboard. this paper explores the possibility of using the paradigm of dynamic logic (dl) to formalise information states and update processes on information states. in particular, we present a formalisation of the dialogue gameboard introduced by jonathan ginzburg. from a more general point of view, we show that dl is particularly well suited to develop rigorous formal foundations for an approach to dialogue dynamics based on information state updates.
a best-first search algorithm for generating referring expressions. existing algorithms for generating referential descriptions to sets of objects have serious deficits: while incremental approaches may produce ambiguous and redundant expressions, exhaustive searches are computationally expensive. mediating between these extreme control regimes, we propose a best-first searching algorithm for uniquely identifying sets of objects. we incorporate linguistically motivated preferences and several techniques to cut down the search space. preliminary results show the effectiveness of the new algorithm.
the donkey strikes back: extending the dynamic interpretation "constructively". the dynamic interpretation of a formula as a binary relation (inducing transitions) on states is extended by alternative treatments of implication, universal quantification, negation and disjunction that are more "dynamic" (in a precise sense) than the usual reductions to tests from quantified dynamic logic (which, nonetheless, can be recovered from the new connectives). an analysis of the "donkey" sentence followed by the assertion "it will kick back" is provided.
ambiguous propositions typed. ambiguous propositions are analyzed in a type system where disambiguation is effected during assembly (i.e. by coercion). ambiguity is introduced through a layer of types that are underspecified relative to a pre-existing collection of dependent types, construed as unambiguous propositions. a simple system of reasoning directly with such underspecification is described, and shown to be sound and complete for the full range of disambiguations. beyond erasing types, the system supports constraints on disambiguations, including co-variation.
integrating "free" word order syntax and information structure. multiset-ccg is a combinatory categorial formalism that can capture the syntax and interpretation of "free" word order in languages such as turkish. the formalism compositionally derives the predicate-argument structure and the information structure (e.g. topic, focus) of a sentence, and uniformly handles word order variation among arguments and adjuncts within a clause, as well as in complex clauses and across clause boundaries.
using a text model for analysis and generation. the following paper concerns a general scheme for multilingual text generation, as opposed to just translation. our system processes the text as a whole, from which it extracts a representation of the meaning of the text. from this representation, a new text is generated, using a text model and action rules.this process is done in six steps: word analysis, sentence analysis using a functional grammar, reference solving and inference, construction of the text pattern, sentence generation, and word generation. different kinds of information are used at each step of the process: text organization, syntax, semantic, etc.all the knowledge, as well as the text, is given in a declarative manner. it is expressed in a single formalism named functional descriptions. it consists of lexical data, a functional grammar, a knowledge network, action rules for reference solving and sentence generation, models of text, rules of structuration, and sentence schema.text representation, included in the semantic network, is composed of different kinds of objects (not necessarily distinct): text organization, syntactical information, objects introduced by the discourse, affirmations on these objects, and links between these affirmations.
exploiting conversational implicature for generating concise explanations. this paper presents an approach for achieving conciseness in generating explanations, which is done by exploiting formal reconstructions of aspects of the gricean principle of relevance to simulate conversational implicature. by applying contextually motivated inference rules in an anticipation feed-back loop, a set of propositions explicitly representing an explanation's content is reduced to a subset which, in the actual context, can still be considered to convey the message adequately.
effect of utilizing terminology on extraction of protein-protein interaction information from biomedical literature. as the amount of on-line scientific literature in the biomedical domain increases, automatic processing has become a promising approach for accelerating research. we are applying syntactic parsing trained on the general domain to identify protein-protein interactions. one of the main difficulties obstructing the use of language processing is the prevalence of specialized terminology. accordingly, we have created a specialized dictionary by compiling on-line glossaries, and have applied it for information extraction. we conducted preliminary experiments on one hundred sentences, and compared the extraction performance when (a) using only a general dictionary and (b) using this plus our specialized dictionary. contrary to our expectation, using only the general dictionary resulted in better performance (recall 93.0%, precision 91.0%) than with the terminology-based approach (recall 92.9%, precision 89.6%).
rigid grammars in the associative-commutative lambek calculus are not learnable. in (kanazawa, 1998) it was shown that rigid classical categorial grammars are learnable (in the sense of (gold, 1967)) from strings. surprisingly there are recent negative results for, among others, rigid associative lambek (l) grammars.in this paper the non-learnability of the class of rigid grammars in lp (associative-commutative lambek calculus) and lp&oslash; (same, but allowing the empty sequent in derivations) will be shown.
classifying biological full-text articles for multi-database curation. in this paper, we propose an approach for identifying curatable articles from a large document set. this system considers three parts of an article (title and abstract, mesh terms, and captions) as its three individual representations and utilizes two domain-specific resources (umls and a tumor name list) to reveal the deep knowledge contained in the article. an svm classifier is trained and cross-validation is employed to find the best combination of representations. the experimental results show overall high performance.
lexicon acquisition with a large-coverage unification-based grammar. we describe how unknown lexical entries are processed in a unification-based framework with large-coverage grammars and how from their usage lexical entries are extracted. to keep the time and space usage during parsing within bounds, information from external sources like part of speech (pos) taggers and morphological analysers is taken into account when information is constructed for unknown words.
dealing with conjunctions in a machine translation environment. a set of rules, named csdc (conjunct scope determination constraints), is suggested for attacking the conjunct scope problem, the major issue in the automatic processing of conjunctions which has been raising great difficulty for natural language processing systems. grammars embodying the csdc are incorporated into an existing atn parser, and are tested successfully against a wide group of "and" conjunctive sentences, which are of three types, namely clausal coordination, phrasal coordination, and gapping. with phrasal coordination the structure with two nps coordinated by "and" has been given most attention.it is hoped that an atn parser capable of dealing with a large variety of conjunctions in an efficient way will finally emerge from the present work.
rules for pronominalization. rigorous interpretation of pronouns in possible when syntax, semantics, and pragmatics of a discourse can be reasonably controlled. interaction with a database provides such an environment. in the framework of the user specialty languages system and discourse representation theory, we formulate strict and preferential rules for pronominalization and outline a procedure to find proper assignments of referents to pronouns.
grouping words using statistical context. this paper describes the use of statistical analyses of untagged corpora to detect similarities and differences in the meaning of words in text. this work is motivated by psychological as well as by computational issues. the limitations of the method of cluster analysis in assessing the success of such analyses are discussed, and ongoing research using an alternative unsupervised neural network approach is described.
a prolog implementation of lexical functional grammar as a base for a natural language processing system. the aim of this paper is to present parts of our system [2], which is to construct a database out of a narrative natural language text. we think the parts are of interest in their own. the paper consists of three sections:(1) we give a detailed description of the prolog - implementation of the parser which is based on the theory of lexical functional grammar (lfg). the parser covers the fragment described in [1,&sect;;4]. i.e., it is able to analyse constructions involving functional control and long distance dependencies. we will to show that- prolog provides an efficient tool for lfg-implementation: a phrase structure rule annotated with functional schemata likes s &rarr; np vp is to be interpreted as, first, indetifying the special grammatical relation of subject position of any sentence analyzed by this clause to be the np appearing in it, and second, as identifying all grammatical relations of the sentence with those of the vp. this universal interpretation of the lfg-metavariables &uarr; and &darr; corresponds to the universal quantification of variables appearing in prolog-clauses. the procedural semantics of prolog is such that the instantiation of the variables in a clause is inherited from the instantiation given by its subgoals, if they succeed. thus there is no need for a separate component which solves the set of equations obtained by applying the lfg algorithm.-there is a canonical way of translating lfg into a prolog programme.(ii) for the semantic representation of texts we use the discourse representation theory developped by hans kamp. at present the implementation includes the fragment described in [4]. in addition it analyses different types of negation and certain equi- and raising-verbs. we postulate some requirements a semantic representation has to fulfill in order to be able to analyse whole texts. we show how kamp's theory meets these requirements by analyzing sample discourses involving anaphoric np's.(iii) finally we sketch how the parser formalism can be augmented to yield as output discourse representation structures. to do this we introduce the new notion of 'logical head' in addition to the lfg notion of 'grammatical head'. the reason is the wellknown fact that the logical structure of a sentence is induced by the determiners and not by the verb which on the other hand determiners the thematic structure of the sentence. however the verb is able to restrict quantifier scope ambiguities or to induce a preference ordering on the set of possible quantifier scope relations. therefore there must be an interaction between the grammatical head and the logical head of a phrase.
automatic construction of machine translation knowledge using translation literalness. when machine translation (mt) knowledge is automatically constructed from bilingual corpora, redundant rules are acquired due to translation variety. these rules increase ambiguity or cause incorrect mt results. to overcome this problem, we constrain the sentences used for knowledge extraction to "the appropriate bilingual sentences for the mt." in this paper, we propose a method using translation literalness to select appropriate sentences or phrases. the translation correspondence rate (tcr) is defined as the literalness measure.based on the tcr, two automatic construction methods are tested. one is to filter the corpus before rule acquisition. the other is to split the acquisition process into two phases, where a bilingual sentence is divided into literal parts and the other parts before different generalizations are applied. the effects are evaluated by the mt quality, and about 4.9% of mt results were improved by the latter method.
automatic acquisition of script knowledge from a text collection. in this paper, we describe a method for automatic acquisition of script knowledge from a japanese text collection. script knowledge represents a typical sequence of actions that occur in a particular situation. we extracted sequences (pairs) of actions occurring in time order from a japanese text collection and then chose those that were typical of certain situations by ranking these sequences (pairs) in terms of the frequency of their occurrence. to extract sequences of actions occurring in time order, we constructed a text collection in which texts describing facts relating to a similar situation were clustered together and arranged in time order.we also describe a preliminary experiment with our acquisition system and discuss the results.
a natural language interface using a world model. databases are nowadays used by varied and diverse users, many of whom are unfamiliar with the workings of a computer, but who, nevertheless, want to use those databases more easily. rising to meet this demand, authors are developing a japanese language interface, called kid, as a database front-end system. kid incorporates a world model representing application and database knowledge to help make databases easier to use. kid has the following features: (1) parser extendability and robustness, (2) independence from the application domain, (3) ease of knowledge editing, (4) independence from the database. this paper focuses on the first three features. kid has already been applied to the fields of housing, sales, and drug testing, thus confirming its transportability and practicality.
word sense disambiguation in untagged text based on term weight learning. this paper describes unsupervised learning algorithm for disambiguating verbal word senses using term weight learning. in our method, collocations which characterise every sense are extracted using similarity-based estimation. for the results, term weight learning is performed. parameters of term weighting are then estimated so as to maximise the collocations which characterise every sense and minimise the other collocations. the results of experiment demonstrate the effectiveness of the method.
knowledge engineering approach to morphological analysis. finnish is a highly inflectional language. a verb can have over ten thousand different surface forms - nominals slightly fewer. consequently, a morphological analyzer is an important component of a system aiming at "understanding" finnish. this paper briefly describes our rule-based heuristic analyzer for finnish nominal and verb forms. our tests have shown it to be quite efficient: the analysis of a finnish word in a running text takes an average of 15 ms of dec 20 cpu-time.
a rule-based approach to evaluating importance in descriptive texts. importance evaluation is one of the most challenging problems in the field of text processing. in the paper we focus on the notion of importance from a computational standpoint, and we propose a procedural, rule-based approach to importance evaluation. this novel approach is supported by a prototype experimental system, called importance evaluator, that can deal with descriptive texts taken from computer science literature on operating systems. the evaluator relies on a set of importance rules that are used to assign importance values to the different parts of a text and to resolve or explain conflicting evaluations. the system utilizes world knowledge on the subject domain contained in an encyclopedia and takes into account a goal assigned by the user for specifying the pragmatic aspects of the understanding activity. the paper describes the role of the evaluator in the frame of a larger system for text summarization (susy); it illustrates its overall mode of operation, and discusses some meaningful examples.
a general feature space for automatic verb classification. we develop a general feature space for automatic classification of verbs into lexical semantic classes. previous work was limited in scope by the need for manual selection of discriminating features, through a linguistic analysis of the target verb classes (merlo and stevenson, 2001). we instead analyze the classification structure at a higher level, using the possible defining characteristics of classes as the basis for our feature space. the general feature space achieves reductions in error rates of 42--69%, on a wider range of classes than investigated previously, with comparable performance to feature sets manually selected for the particular classification tasks. our results show that the approach is generally applicable, and avoids the need for resource-intensive linguistic analysis for each new task.
tense generation in an intelligent tutor for foreign language teaching: some issues in the design of the verb expert. the paper presents some of the results obtained within a research project aimed at developing et (english tutor), an intelligent tutoring system which supports italian students in learning the english verbs. we concentrate on one of the most important modules of the system, the domain (i.e. verb) expert which is devoted to generate, in a cognitively transparent way, the right tense for the verb(s) appearing in the exercises presented to the student. an example which highlights the main capabilities of the verb expert is provided. a prototype version of et has been fully implemented.
automatic annotation for all semantic layers in framenet. we describe a system for automatic annotation of english text in the framenet standard. in addition to the conventional annotation of frame elements and their semantic roles, we annotate additional semantic information such as support verbs and prepositions, aspectual markers, copular verbs, null arguments, and slot fillers. as far as we are aware, this is the first system that finds this information automatically.
teaching the english tense: integrating naive and formal grammars in an intelligent tutor for foreign language teaching. a basic problem that must be dealt with in order to build an intelligent tutoring system (its) in the domain of foreign language teaching is that of establishing what kind of grammatical knowledge has to be included in the domain expert module. two basic options are possible: (i) to use a naive or pedagogical grammar, comprising knowledge derived from textbooks and school grammars or (ii) to use one of the formal grammars developed by theoretical and computational linguists. the paper discusses the relationships between naive and formal grammars in foreign language teaching and presents, as a case study, an attempt to integrate the two approaches within et (english tutor), an its aimed at helping italian students master english verb usage. more particularly, the paper focuses on the possibility of integrating a naive grammar into a systemic framework. the reliability of the proposed approach is currently being evaluated by means of a series of computational experiments with the verb generation expert of et.
a rich environment for experimentation with unification grammars. this paper describes some of the features of a sophisticated language and environment designed for experimentation with unification-oriented linguistic descriptions. the system, which is called und, has to date been used successfully as a development and prototyping tool in a research project on the application of situation schemata to the representation of real text, and in extensive experimentation in machine translation.while the ud language bears close resemblances to all the well-known unification grammar formalisms, it offers a wider range of features than any single alternative, plus powerful facilities for notational abstraction which allow users to simulate different theoretical approaches in a natural way.after a brief discussion of the motivation for implementing yet another unification device, the main body of the paper is devoted to a description of the most important novel features of und.the paper concludes with a discussion of some questions of implementation and completeness.
encoding a parallel corpus for automatic terminology extraction. we present a status report about an ongoing research project in the field of (semi-) automatic terminology acquisition at the european academy bolzano. the main focus will be on encoding a text corpus, which serves as a basis for applying term extraction programs.
a dialogue manager using initiative-response units and distributed control. this paper describes a system for managing dialogue in a natural language interface. the proposed approach uses a dialogue manager as the overall control mechanism. the dialogue manager accesses domain independent resources for interpretation, generation and background system access. it also uses information from domain dependent knowledge sources, which are customized for various applications.instead of using complex plan-based reasoning, the dialogue manager uses information about possible interaction structures and information from the specific dialogue situation to manage the dialogue. this is motivated from the analysis of a series of experiments where users interacted with a simulated natural language interface. the dialogue manager integrates information about segment types and moves into a hierarchical dialogue tree. the dialogue tree is accessed through a scoreboard which uses exchangeable access functions. the control is distributed and the dialogue is directed from action plans in the nodes in the dialogue tree.
a unification-based approach to multiple vp ellipsis resolution. an assumption shared by many theories of discourse is that discourse structure constrains anaphora resolution (cf. [grosz and sidner 1986] for definite nps, [lascarides and asher 1991], [nakhimovsky 1988] for temporal anaphora, [webber 1990] for deictic pronouns and [gardent 1991], [pr&uuml;st and scha 1990] for vp ellipsis). the aim of this paper is (i) to show that this assumption also applies to multiple vp ellipsis (vpe), (ii) to argue that other levels of linguistics information (such as syntax and semantics) interact with discourse structure in determining multiple vpe acceptability and (iii) to make these intuitions precise by providing a unification-based account of multiple vpe resolution.
plan revision in person-machine dialogue. dialogue is a cooperative process in which each speech act of the participants contributes to the overall purpose of the dialogue. participating in a full dialogue implies understanding at each point of the dialogue session the role of each speech act with respect to the rest of the dialogue. we concentrate in this paper on speech acts that diverge from the straight-forward unfolding of the dialogue. such speech acts represent dialogue deviations. we analyze the representation of different types and degrees of deviations and present a plan revision mechanism for dialogue management that permits their treatment in the context of advice giving dialogues between a novice user and an expert problem solver.
a probabilistic parser. the ucrel team at the university of lancaster is engaged in the development of a robust parsing mechanism, which will assign the appropriate grammatical structure to sentences in unconstrained english text. the techniques used involve the calculation of probabilities for competing structures, and are based on the techniques successfully used in tagging (i.e. assigning grammatical word classes) to the lob (lancaster-oslo/bergen) corpus.the first step in the parsing process involves dictionary lookup of successive pairs of grammatically tagged words, to give a number of possible continuations to the current parse. since this lookup will often not be able unambiguously to distinguish the point at which a grammatical constituent should be closed, the second step of the parsing process will have to insert closures and distinguish between alternative parses. it will generate trees representing these possible alternatives, insert closure points for the constituents, and compute a probability for each parse tree from the probability of each constituent within the tree. it will then be able to select a preferred parse or parses for output.the probability of a grammatical constituent is derived from a bank of manually parsed sentences.
parsing without lexicon: the morp system. morp is a system for automatic word class assignment on the basis of surface features. it has a very small lexicon of form words (&permil; entries), and for the rest works entirely on morphological and configurational patterns. this makes it robust and fast, and in spite of the (deliberate) restrictedness of the system, its performance reaches an average accuracy level above 91% when run on unrestricted swedish text.
rule-based acquisition and maintenance of lexical and semantic knowledge. the lexicons for knowledge-based machine translation systems require knowledge intensive morphological, syntactic and semantic information. this information is often used in different ways and usually formatted for a specific nlp system. this tends to make both the acquisition and maintenance of lexical databases cumbersome, inefficient and error-prone. in order to solve these problems, we have developed a program called cool which automates the acquisition and maintenance processes and allows us to standardize and centralize the databases. this system is currently being used in the estrato machine translation project at the center for machine translation.
representation of feature systems in a non-connectionist molecular machine. this paper is part of an enterprise whose aim is to represent linguistic knowledge in the form of a molecular machine (a dynamic network). that is, the molecules of the network not only store, but also send, receive, and process information. it is claimed that such a network can be conceived of as a model of the coalition structure of a connectionist network. the paper describes how the class of feature systems called unary feature hierarchies (whose importance is supported by phonological theory but will not be argued for in the paper) can be represented in the molecular machine.
translation by structural correspondences. we sketch and illustrate an approach to machine translation that exploits the potential of simultaneous correspondences between separate levels of linguistic representation, as formalized in the lfg notion of codescriptions. the approach is illustrated with examples from english, german and french where the source and the target language sentence show noteworthy differences in linguistic analysis.
restriction and correspondence-based translation. kaplan et al. (1989) present a framework for translation based on the description and correspondence concepts of lexical-functional grammar (kaplan and bresnan, 1982). certain phenomena, in particular the head-switching of adverbs and verbs, seem to be problematic for that approach. in this paper we suggest that these difficulties are more properly considered as the result of defective monolingual analyses. we propose a new description-language operator, restriction, to permit a succinct formal encoding of the informal intuition that semantic units sometimes correspond to subsets of functional information. this operator, in conjunction with an additional recursion provided by a description-by-analysis rule, is the basis of a more adequate account of head-switching that preserves the advantages of correspondence-based translation.
what humour tells us about discourse theories. many verbal jokes, like garden path sentences, pose difficulties to models of discourse since the initially primed interpretation needs to be discarded and a new one created based on subsequent statements. the effect of the joke depends on the fact that the second (correct) interpretation was not visible earlier. existing models of discourse semantics in principle generate all interpretations of discourse fragments and carry these until contradicted, and thus the dissonance criteria in humour cannot be met. computationally, maintaining all possible worlds in a discourse is very inefficient, thus computing only the maximum-likelihood interpretation seems to be a more efficient choice on average. in this work we outline a probabilistic lexicon based lexical semantics approach which seems to be a reasonable construct for discourse in general and use some examples from humour to demonstrate its working.
an approach to summarizing short stories. this paper describes a system that produces extractive summaries of short works of literary fiction. the ultimate purpose of produced summaries is defined as helping a reader to determine whether she would be interested in reading a particular story. to this end, the summary aims to provide a reader with an idea about the settings of a story (such as characters, time and place) without revealing the plot. the approach presented here relies heavily on the notion of aspect. preliminary results show an improvement over two na&iuml;ve baselines: a lead baseline and a more sophisticated variant of it. although modest, the results suggest that using aspectual information may be of help when summarizing fiction. a more thorough evaluation involving human judges is under way.
a discourse copying algorithm for ellipsis and anaphora resolution. we give an analysis of ellipsis resolution in terms of a straightforward discourse copying algorithm that correctly predicts a wide range of phenomena. the treatment does not suffer from problems inherent in identity-of-relations analyses. furthermore, in contrast to the approach of dalrymple et al. [1991], the treatment directly encodes the intutive distinction between full nps and the referential elements that corefer with them through what we term role linking. the correct predictions for several problematic examples of ellipsis naturally result. finally, the analysis extends directly to other discourse copying phenomena.
a multilevel approach to handle non-standard input. in the project "procedural dialogue models" being carried on at the university of bielefeld we have developed an incremental multilevel parsing formalism to reconstruct task-oriented dialogues. a major difficulty we have had to overcome is that the dialogues are real ones with numerous ungrammatical utterances. the approach we have devised to cope with this problem is reported here.
l'idee de grammaire avec le contexte naturel. commonly used grammars which describe natural languages /ex. atn, metamorphosis grammars/ can be hardly applied in describing higly inflectional languages. so i propose a grammar called the grammar with natural context which takes into consideration properties of highly inflectional languages /ex. polish / as well as structural languages /ex. english/. i introduce its normal form.
peas, the first instantiation of a comparative framework for evaluating parsers of french. this paper presents peas, the first comparative evaluation framework for parsers of french whose annotation formalism allows the annotation of both constituents and functional relations. a test corpus containing an assortment of different text types has been built and part of it has been manually annotated. precision/recall and crossing brackets metrics will be adapted to our formalism and applied to the parses produced by one parser from academia and another one from industry in order to validate the framework.
the semantics of resource sharing in lexical-functional grammar. we argue that the resource sharing that is commonly manifest in semantic accounts of coordination is instead appropriately handled in terms of structure-sharing in lfg f-structures. we provide an extension to the previous account of lfg semantics (dalrymple et al., 1993a) according to which dependencies between f-structures are viewed as resources; as a result a one-to-one correspondence between uses of f-structures and meanings is maintained. the resulting system is sufficiently restricted in cases where other approaches overgenerate; the very property of resource-sensitivity for which resource sharing appears to be problematic actually provides explanatory advantages over systems that more freely replicate resources during derivation.
transducers from rewrite rules with backreferences. context sensitive rewrite rules have been widely used in several areas of natural language processing, including syntax, morphology, phonology and speech processing. kaplan and kay, karttunen, and mohri & sproat have given various algorithms to compile such rewrite rules into finite-state transducers. the present paper extends this work by allowing a limited form of backreferencing in such rules. the explicit use of backreferencing leads to more elegant and general solutions.
towards an account of extraposition in hpsg. this paper investigages the syntax of extraposition in the hpsg framework. we present english and german data (partly taken from corpora), and provide an analysis using a nonlocal dependency and lexical rules. the condition for binding the dependency is formulated relative to the antecedent of the extraposed phrase, which entails that no fixed site for extraposition exists. our account allows to explains the interaction of extraposition with fronting and coordination, and predicts constraints on multiple extraposition.
what's there to talk about? a multi-modal model of referring behavior in the presence of shared visual information. this paper describes the development of a rule-based computational model that describes how a feature-based representation of shared visual information combines with linguistic cues to enable effective reference resolution. this work explores a language-only model, a visual-only model, and an integrated model of reference resolution and applies them to a corpus of transcribed task-oriented spoken dialogues. preliminary results from a corpus-based analysis suggest that integrating information from a shared visual environment can improve the performance and quality of existing discourse-based models of reference resolution.
a tractable extension of linear indexed grammars. vijay-shanker and weir (1993) show that linear indexed grammars (lig) can be processed in polynomial time by exploiting constraints which make possible the extensive use of structure-sharing. this paper describes a formalism that is more powerful than lig, but which can also be processed in polynomial time using similar techniques. the formalism, which we refer to as partially linear patr (plpatr) manipulates feature structures rather than stacks.
dialog control in a natural language system. in this paper a method for controlling the dialog in a natural language (nl) system is presented. it provides a deep modeling of information processing based on time dependent propositional attitudes of the interacting agents. knowledge about the state of the dialog is represented in a dedicated language and changes of this state are described by a compact set of rules. an appropriate organization of rule application is introduced including the initiation of an adequate system reaction. finally the application of the method in an nl consultation system is outlined.
finite structure query: a tool for querying syntactically annotated corpora. finite structure query (fsq for short) is a tool for querying syntactically annotated corpora. fsq employs a query language of high expressive power, namely full first order logic. it can be used to query arbitrary finite structures, not just trees.
finite state processing of tone systems. it is suggested in this paper that two--level morphology theory (kay, koskenniemi) can be extended to include morphological tone. this extension treats phonological features as i/o tapes for finite state transducers in a parallel sequential incrementation (psi) architecture; phonological processes (e.g. assimilation) are seen as variants of an elementary unification operation over feature tapes (linear unification phonology, lup). the phenomena analysed are tone terracing with tone---spreading (horizontal assimilation), downstep, upstep, downdrift, upsweep in two west african languages, tem (togo) and baule (c&ocirc;te d'ivoire). it is shown that an fst account leads to more insightful definitions of the basic phenomena than other approaches (e.g. phonological rules or metrical systems).
computational dialectology in irish gaelic. dialect groupings can be discovered objectively and automatically by cluster analysis of phonetic transcriptions such as those found in a linguistic atlas. the first step in the analysis, the computation of linguistic distance between each pair of sites, can be computed as levenshtein distance between phonetic strings. this correlates closely with the much more laborious technique of determining and counting isoglosses, and is more accurate than the more familiar metric of computing hamming distance based on whether vocabulary entries match. in the actual clustering step, traditional agglomerative clustering works better than the top-down technique of partitioning around medoids. when agglomerative clustering of phonetic string comparison distances is applied to gaelic, reasonable dialect boundaries are obtained, corresponding to national and (within ireland) provincial boundaries.
the simulation of stress patterns in synthetic speech - a two-level problem. this paper is part of an msc. report on a program called genie (generator of inflected english), written in cprolog, that acts as a front end to an existing speech synthesis program. it allows the user to type a sentence in english text, and then processes it so that the synthesiser will output it with natural-sounding inflection; that is, as well as transcribing text to a phonemic form that can be read by the system, it assigns this text an fo contour. the assigning of this stress is described in this paper, and it is asserted that the problem can be solved with reference to two main levels, the sentential and the syllabic.
a proposal for modifications in the formalism of gpsg. recent investigations show a remarkable convergence among contemporary unification-based formalisms for syntactic description. this convergence is now itself becoming an object of study, and there is an increasing recognition of the need for explicit characterizations of the properties that relate and distinguish similar grammar formalisms. the paper proposes a series of changes in the formalism of generalized phrase structure grammar that throw light on its relation to functional unification grammar.the essential contribution is a generalization of cooccurrence restrictions, which become the principal and unifying device of gpsg. introducing category cooccurrence restrictions (ccrs) for local trees (in analogy to feature cooccurrence restrictions for categories) provides a genuine gain in expressiveness for the formalism. other devices, such as feature instantiation principles and linear precedence statements can be regarded as special cases of ccrs. the proposals lead to a modified notion of unification itself.
automatic learning of word transducers from examples. this paper describes the application of markovian learning methods to the inference of word transducers. we show how the proposed method dispenses from the difficult design of hand-crafted rules, allows the use of weighed non deterministic transducers and is able to translate words by taking into account their whole rather than by making decisions locally. these arguments are illustrated on two examples: morphological analysis and grapheme-to-phoneme transcription.
datr as a lexical component for patr. the representation of lexical entries requires special means which basic patr systems do not include. the language datr, however, can be used to define an inheritance network serving as the lexical component. the integration of such a module into an existing patr system leads to various problems which are discussed together with possible solutions in this paper.
inheriting verb alternations. the paper shows how the verbal lexicon can be formalised in a way that captures and exploits generalisations about the alternation behaviour of verb classes. an alternation is a pattern in which a number of words share the same relationship between a pair of senses. the alternations captured are ones where the different senses specify different relationships between syntactic complements and semantic arguments, as between bake in "john is baking the cake" and "the cake is baking". the formal language used is datr. the lexical entries it builds are as specified in hpsg. the complex alternation behaviour shared between families of verbs is elegantly represented in a way that makes generalisations explicit, avoids redundancy, and offers practical benefits to computational lexicographers.
a computational treatment of sentence-final 'then'. we describe a computational system which parses discourses consisting of sequences of simple sentences. these contain a range of temporal constructions, including time adverbials, progressive aspect and various aspectual classes. in particular, the grammar generates the required readings, according to the theoretical analysis of (glasbey, forthcoming), for sentence-final 'then'.
the god model. god (general ontology discovery) is an unsupervised system to extract semantic relations among domain specific entities and concepts from texts. operationally, it acts as a search engine returning a set of true predicates regarding the query instead of the usual ranked list of relevant documents. our approach relies on two basic assumptions: (i) paradigmatic relations can be established only among terms in the same semantic domain an (ii) they can be inferred from texts by analyzing the subject-verb-object patterns where two domain specific terms co-occur. a qualitative analysis of the system output shows that god provide true, informative and meaningful relations in a very efficient way.
ambiguity resolution in the dmtrans plus. we present a cost-based (or energy-based) model of disambiguation. when a sentence is ambiguous, a parse with the least cost is chosen from among multiple hypotheses. each hypothesis is assigned a cost which is added when: (1) a new instance is created to satisfy reference success, (2) links between instances are created or removed to satisfy constraints on concept sequences, and (3) a concept node with insufficient priming is used for further processing. this method of ambiguity resolution is implemented in dmtrans plus, which is a second generation bi-directional english/japanese machine translation system based on a massively parallel spreading activation paradigm developed at the center for machine translation at carnegie mellon university.
towards a proper treatment of coercion phenomena. the interpretation of coercion constructions (to begin a book) has been recently considered as resulting from the operation of type changing. for instance, a phrase of type o (object) is coerced to a phrase of type e (event) under the influence of the predicate. we show that this procedure encounters empirical difficulties. focussing on the begin/commencer case, we show that the coercion interpretation results both from general semantic processes and properties of the predicate, and we argue that it is best represented at the lexical level. the solution is formulated in the hpsg formalism, where the lexical description of heads includes a specification of the argument and articulates syntax and semantics. we propose that the properties attached to the complement remain the same as they are outside the construction, but that the semantics of the predicate is enriched to include an abstract predicate of which the complement is an argument.
collocation map for overcoming data sparseness. statistical language models are useful because they can provide probabilistic information upon uncertain decision making. the most common statistic is n-grams measuring word cooccurrences in texts. the method suffers from data shortage problem, however. in this paper, we suggest bayesian networks be used in approximating the statistics of insufficient occurrences and of those that do not occur in the sample texts with graceful degradation. collocation map is a sigmoid belief network that can be constructed from bigrams. we compared the conditional probabilities and mutual information computed from bigrams and collocation map. the results show that the variance of the values from collocation map is smaller than that from frequency measure for the infrequent pairs by 48%. the predictive power of collocation map for arbitrary associations not observed from sample texts is also demonstrated.
how to parse gaps in spoken utterances. we describe glp, a chart parser that will be used as a syntax module of the erlangen speech understanding system. glp realizes an agenda-based multiprocessing scheme, which allows easily to apply various parsing strategies in a transparent way. we discuss which features have been incorporated into the parser in order to process speech data, in particular the ability to perform direction independent island parsing, to handle gaps in the utterance and its hypothesis scoring scheme.
xmg - an expressive formalism for describing tree-based grammars. in this paper we introduce extensible metagrammar, a system that facilitates the development of tree based grammars. this system includes both (1) a formal language adapted to the description of linguistic information and (2) a compiler for this language. it applies techniques of logic programming (e.g. warren's abstract machine), thus providing an efficient and theoretically motivated framework for the processing of linguistic meta-descriptions.
the textual development of non-stereotypic concepts. in this paper the text theoretical foundation of our text analysis system kontext is described. the basic premise of the kontext model is that new concepts are communicated by using the mechanisms of text constitution. the text model used assumes that the information conveyed in a text and the information describing its contextual organization can be structured into five layers (sentence structure, information on thematic progression, referential structure, conceptual representation of the text and conceptual background knowledge). the text analysis component constructs and traverses the information of these layers under control of the discourse development. in this way, it can incrementally construct a textual view on knowledge, rather than only recognizing precoded concepts.
linguistic knowledge acquisition from parsing failures. a semi-automatic procedure of linguistic knowledge acquisition is proposed, which combines corpus-based techniques with the conventional rule-based approach. the rule-based component generates all the possible hypotheses of defects which the existing linguistic knowledge might contain, when it fails to parse a sentence. the rule-based component does not try to identify the defects, but generates a set of hypotheses and the corpus-based component chooses the plausible ones among them. the procedure will be used for adapting or re-using existing linguistic resources for new application domains.
reftex - a context-based translation aid. the system presented in this paper produces bilingual passages of text from an original (source) text and one (or more) of its translated versions.the source text passage includes words or word compounds which a translator wants to retrieve for the current translating of another text. the target text passage is the equivalent version of the source text passage. on the basis of a comparison of the contexts of these words in the concorded passage and his own text, the translator has to decide on the utility of the translation proposed in the target text passage.the program might become a component of translator's work bench.
grammatical role labeling with integer linear programming. in this paper, we present a formalization of grammatical role labeling within the framework of integer linear programming (ilp). we focus on the integration of subcategorization information into the decision making process. we present a first empirical evaluation that achieves competitive precision and recall rates.
modelling knowledge for a natural language understanding system. in the field of knowledge based systems for natural language processing, one of the most challenging aims is to use parts of an existing knowledge base for different domains and/or different tasks. we support the point that this problem can only be solved by using adequate metainformation about the content and structuring principles of the representational systems concerned. one of the prerequisites in this respect is the transparency of modelling decisions.after a short introduction to our scenario, we will propose general dimensions for characterizing knowledge in knowledge based systems. these dimensions will be differentiated according to linguistic levels of investigation in order to deduce structuring principles for the modelling process. the resulting criteria will be evaluated in a detailed example taken from our prototypical implementation.we hope to contribute some promising steps towards a methodology of knowledge engineering with natural language and common sense orientation.
empirical methods for compound splitting. compounded words are a challenge for nlp applications such as machine translation (mt). we introduce methods to learn splitting rules from monolingual and parallel corpora. we evaluate them against a gold standard and measure their impact on performance of statistical mt systems. results show accuracy of 99.1% and performance gains for mt of 0.039 bleu on a german-english noun phrase translation task.
a cascaded finite-state parser for syntactic analysis of swedish. this report describes the development of a parsing system for written swedish and is focused on a grammar, the main component of the system, semiautomatically extracted from corpora. a cascaded, finite-state algorithm is applied to the grammar in which the input contains coarse-grained semantic class information, and the output produced reflects not only the syntactic structure of the input, but grammatical functions as well. the grammar has been tested on a variety of random samples of different text genres, achieving precision and recall of 94.62% and 91.92% respectively, and average crossing rate of 0.04, when evaluated against manually disambiguated, annotated texts.
towards the semantics of sentence adverbials. in the present paper we argue that the so-called sentence adverbials (typically, adverbs like <u>probably, admittedly</u>,...) should be generated, in the framework of functional generative description, by means of a special deep case - complementation of attitude (ca) on grounds of their special behaviour in the topic-focus articulation (tfa) of a sentence. from the viewpoint of the translation of ca expressions (and also of the multiple occurrence thereof inside a sentence) into a calculus of intensional logic, it should be noted that the tfa properties of ca expressions are directly correlated to the scope properties thereof. our approach, which is stated in terms of a linguistic theory, serves as a basis for an algorithm of analysis of ca for purposes of a system of man-machine communication without a pre-arranged data base.
towards a new type of morphenic analysis. the present paper provides a report on a new system of an automated morphemic analysis of technical texts in czech as a highly inflectional language, which is being prepared by the linguistic team of the faculty of mathematics and physics in prague, within the project of man-machine communication without a pre-arranged data base (tibaq). the kind of morphemic analysis presented here is based on a retrograde (right-to-left) analysis of words by means of morphemically unambiguous or irresolvably ambiguous word-ends, which do not coincide with the etymological word-endings but correspond to the structure of the accidental cases of morphemic ambiguity in an inflectional language (word-endings being accountable for in a certain way by word-ends). the algorithm of analysis can thus dispense with any dictionary (of morphemic irregularities and exceptions), economically accounting especially for productive word-endings. the word-ends of the analysis are assigned several kinds of morphemic information, concerning morphemic categories and lemmatization. the analysis is based on the absolute frequency of word-ends in technical texts and is able to interact with the semantic analysis.
an experiment on synthesis of russian parametric constructions. the paper describes an experimental model of syntactic structure generation starting from the limited fragment of semantics that deals with the quantitative values of object parameters. to present the input information the basic semantic units of four types are proposed: "object", "parameter", "function" and "constant". for the syntactic structure representation the system of syntactic components is used that combines the properties of the dependency and constituent systems: the syntactic components corresponding to wordforms and exocentric constituents are introduced and two basic subordinate relations ("actant" and "attributive") are claimed to be necessary. special attention has been devoted to problems of complex correspondence between the semantic units and lexical-syntactic means, in the process of synthesis such sections of the model as the lexicon, the syntactic structure generation rules, the set of syntactic restrictions and morphological operators are utilized to generate the considerable enough subset of russian parametric constructions.
the key role of semantics in the development of large-scale grammars of natural language. the aim of this paper is to show how large-scale (computational) grammars of natural language benefit from an organization of semantics which is based on minimal recursion semantics (mrs; copestake et al. (1999)). this we are doing by providing an account of valence alternations in german based on mrs, showing how such an account makes a computational grammar more efficient and less complicated for the grammar writer.
classifying the hungarian web. in this paper we present some lessons learned from building vizsla, the keyword search and topic classification system used on the largest hungarian portal, [origo.hu]. based on a simple statistical language, model, and the large-scale supporting evidence from vizsla, we argue that in topic classification only positive evidence matters.
natural languages and the chomsky hierarchy. the central claim of the paper is that nl stringsets are regular. three independent arguments are offered in favor of this position: one based on parsimony considerations, one employing the mccullogh-pitts (1943) model of neuruns, and a purely linguistic one. it is possible to derive explicit upper bounds for the number of (live) states in nl acceptors: the results show that finite state nl parsers can be implemented on present-day computers. the position of nl stringsets within the regular family is also investigated: it is proved that nls are counter-free, but not locally testable.
"lexifanis" a lexical analyzer of modern greek. lexifanis is a software tool designed and implemented by the authors to analyze modern greek language ('&delta;&eta;&mu;&omicron;&tau;&iota;&chi;&eta;). this system assigns grammatical classes (parts of speech) to 95--98% of the words of a text which is read and normalized by the computer.by providing the system with the appropriate grammatical knowledge (i.e.: dictionaries of non-inflected words, affixation morphology and limited surface syntax rules) any "variant" of modern greek language (dialect or idiom) can be processed.in designing the system, special consideration is given to the greek language morphological characteristics, primarily to the inflection and the accentuation.in linguistics, lexifanis, can assist the generation of indexes or lemmata; on the other hand readability or style analysis can be performed using this software as a basic component. in word processing this software may serve as a background to build dictionaries for a spelling checking and error detection package.through this study our research group has set the basis in designing an "expert system" which is intended to "understand" and process modern greek texts. lexifanis is the first working tool for modern greek language.
bootstrapping named entity recognition with automatically generated gazetteer lists. current named entity recognition systems suffer from the lack of hand-tagged data as well as degradation when moving to other domain. this paper explores two aspects: the automatic generation of gazetteer lists from unlabeled data; and the building of a named entity recognition system with labeled and unlabeled data.
mathematical aspects of command relations. in gb, the importance of phrase-structure rules has dwindled in favour of nearness conditions. today, nearness conditions play a major role in defining the correct linguistic representations. they are expressed in terms of special binary relations on trees called command relations. yet, while the formal theory of phrase-structure grammars is quite advanced, no formal investigation into the properties of command relations as been done. we will try to close this gap. in particular, we will study the intrinsic properties of command relations has relations on trees as well as the possibility to reduce nearness conditions expressed by command relations to phrase-structure rules.
suregen-2: a shell system for the generation of clinical documents. suregen-2 applications are intended for use as add-on modules for clinical information systems. currently, suregen-2 permits refinement of the predefined medical ontology, specification of text plans and description knowledge for objects of the ontology. it has built-in constructs for referential expressions, aggregation, enumeration and recurrent semantic constellations. a first application built with suregen-2, which currently supports german only, is in routine use.
the multilingual named entity recognition framework. this paper presents a multilingual system designed to recognize named entities in a wide variety of languages (currently more than 12 languages are concerned). the system includes original strategies to deal with a wide variety of encoding character sets, analysis strategies and algorithms to process these languages.
the multilingual named entity recognition framework. this paper presents a multilingual system designed to recognize named entities in a wide variety of languages (currently more than 12 languages are concerned). the system includes original strategies to deal with a wide variety of encoding character sets, analysis strategies and algorithms to process these languages.
an open-source environment for compiling typed unification grammars into speech recognisers. we present regulus, an open source environment which compiles typed unification grammars into context free grammar language models compatible with the nuance toolkit. the environment includes a large general unification grammar of english and corpus-based tools for creating efficient domain-specific recognisers from it. we will demo applications built using the system, including a speech translator and a command and control system for a simulated robotic domain, and show how the development environment can be used to edit and extend them.
information structure in topological dependency grammar. topological dependency grammar (tdg) is a lexicalized dependency grammar formalism, able to model languages with a relatively free word order. in such languages, word order variation often has an important function: the realization of information structure. the paper discusses how to integrate information structure into tdg, and presents a constraint-based approach to modelling information structure and the various means to realize it, focusing on (possibly simultaneous use of) word order and tune.
some remarks on case relations. the topic of the paper is the problem how to define case relations by semantic predicates. a general principle is outlined, which renders it possible to "calculate" case relations for a given representation of a (verb-)sememe by means of expressions. this principle is based on an assignment of case relations to primitive predicates and modification rules for nested expressions. contrary to the traditional case grammar it turns out that one needs mixed case relations, especially for two reasons: arguments occur at "too different" places in an expression or arguments have combined case relations. the consequence is that case relations don't form a set of isolated elements but a structured system.
a formal representation of propositions and temporal adverbials. the topic of the paper is the introduction of a formalism that permits a homogeneous representation of definite temporal adverbials, temporal quantifications (as frequency and duration), temporal conjunctions and tenses, and of their combinations with propositions. this unified representation renders it possible to show how these components refer to each other and interact in creating temporal meanings. the formal representation is based on the notions "phase-set" and "phase-operator", and it involves an interval logic. furthermore logical connections are used, but the (always troublesome) logical quantifications may be avoided. the expressions are rather near to linguistic structures, which facilitates the link to text analysis. some emprical confirmations are outlined.
µ-tbl lite: a small, extendible transformation-based learner. this short paper describes - and in fact gives the complete source for - a tiny prolog program implementing a flexible and fairly efficient transformation-based learning (tbl) system.
detecting novel compounds: the role of distributional evidence. research on the discovery of terms from corpora has focused on word sequences whose recurrent occurrence in a corpus is indicative of their terminological status, and has not addressed the issue of discovering terms when data is sparse. this becomes apparent in the case of noun compounding, which is extremely productive: more than half of the candidate compounds extracted from a corpus are attested only once. we show how evidence about established (i.e., frequent) compounds can be used to estimate features that can discriminate rare valid compounds from rare nonce terms in addition to a variety of linguistic features than can be easily gleaned from corpora without relying on parsed text.
determinants of adjective-noun plausibility. this paper explores the determinants of adjective-noun plausibility by using correlation analysis to compare judgements elicited from human subjects with five corpus-based variables: co-occurrence frequency of the adjective-noun pair, noun frequency, conditional probability of the noun given the adjective, the log-likelihood ratio, and resnik's (1993) selectional association measure. the highest correlation is obtained with the co-occurrence frequency, which points to the strongly lexicalist and collocational nature of adjective-noun combinations.
a semantics and pragmatics for the pluperfect. we offer a semantics and pragmatics of the pluperfect in narrative discourse. we examine in a formal model of implicature, how the reader's knowledge about the discourse, gricean-maxims and causation contribute to the meaning of the pluperfect. by placing the analysis in a theory where the interactions among these knowledge resources can be precisely computed, we overcome some problems with previous reichenbachian approaches.
temporal connectives in a discourse context. we examine the role of temporal connectives in multi-sentence discourse. in certain contexts, sentences containing temporal connectives that are equivalent in temporal structure can fail to be equivalent in terms of discourse coherence. we account for this by offering a novel, formal mechanism for accommodating the presuppositions in temporal subordinate clauses. this mechanism encompasses both accommodation by discourse attachment and accomodation by temporal addition. as such, it offers a precise and systematic model of interactions between presupposed material, discourse context, and the reader's background knowledge. we show how the results of accommodation help to determine a discourse's coherence.
an indexing technique for implementing command relations. command relations are important tools in linguistics, especially in anaphora theory. in this paper i present an indexing technique which allows us to implement a simple and efficient check for most cases of command relations which have been presented in linguistic literature. i also show a wide perspective of applications for the indexing technique in the implementation of other linguistic phenomena in syntax as well as in semantics.
morphology in the eurotra base level concept. in recent years the nature and the role of a morphological component in nlp systems has attracted a lot of attention.the two-level model of koskenniemi which relates graphemic to morphological structure has been succesfully implemented in the form of finite state automata.in eurotra a solution which combines morphological and surface syntactic processing in one cfg implemented in a unification grammar framework has been tried out. this article contrasts these two approaches considering especially the feasibility of building morphological modules for a big multilingual mt system in a decentralised r & d project.
criteria for measuring term recognition. this paper qualifies what a true term-recognition systems would have to recognize. the exact bracketing of the maximal termform is then proposed as an achieveable goal upon which current system performance should be measured. how recall and precision metrics are best adapted for measuring term recognition is suggested.
bidirectional parsing of lexicalized tree adjoining grammars. in this paper a bidirectional parser for lexicalized tree adjoining grammars will be presented. the algorithm takes advantage of a peculiar characteristic of lexicalized tags, i.e. that each elementary tree is associated with a lexical item, called its anchor. the algorithm employs a mixed strategy: it works bottom-up from the lexical anchors and then expands (partial) analyses making top-down predictions. even if such an algorithm does not improve the worst-case time bounds of already known tags parsing methods, it could be relevant from the perspective of linguistic information processing, because it employs lexical information in a more direct way.
towards efficient parsing with proof-nets. this paper presents a method for parsing associative lambek grammars based on graph-theoretic properties. connection graphs, which are a simplified version of proof-nets, are actually a mere conservative extension of the earlier method of syntactic connexion, discovered by ajduckiewicz [1935]. the method amounts to find alternating spannig trees in graphs. a sketch of an algorithm for finding such a tree is provided. interesting properties of time-complexity for this method are expected. it has some similarities with chart-parsing ([k&ouml;ning, 1991, 1992], [hepple, 1992]) but is different at least in the fact that intervals are here edges and words are vertices (or trees) instead of the contrary in classical chart-parsing.
a robust parser based on syntactic information. an extragrammatical sentence is what a normal parser fails to analyze. it is important to recover it using only syntactic information although results of recovery are better if semantic factors are considered. a geneal algorithm for least-errors recognition, which is based only on syntactic information, was proposed by g. lyon to deal with the extragrammaticality. we extended this algorithm to recover extragrammatical sentence into grammatical one in running text. our robust parser with recovery mechanism - extended general algorithm for least-errors recognition - can be easily scaled up and modified because it utilize only syntactic information. to upgrade this robust parser we proposed heuristics through the analysis on the penn treebank corpus. the experimental result shows 68% ~ 77% accuracy in error recovery.
non-deterministic recursive ascent parsing. a purely functional implementation of lr-parsers is given, together with a simple correctness proof. it is presented as a generalization of the recursive descent parser. for non-lr grammars the time-complexity of our parser is cubic if the functions that constitute the parser are implemented as memo-functions, i.e. functions that memorize the results of previous invocations. memo-functions also facilitate a simple way to construct a very compact representation of the parse forest. for lr(0) grammars, our algorithm is closely related to the recursive ascent parsers recently discovered by kruseman aretz [1] and roberts [2]. extended cf grammars (grammars with regular expressions at the right hand side) can be parsed with a simple modification of the lr-parser for normal cf grammars.
towards a core vocabulary for a natural language system. the desire to construct robust and portable natural language systems has led to research on how a core vocabulary for such systems can be defined. statistical methods and semantic criteria for doing this are discussed and compared. currently it does not seem possible to precisely define the notion of core vocabulary, but it is argued that workable criteria can nevertheless be found. finally it is emphasized that the implementation of a core vocabulary must be seen as a long-range research program rather than as a short-term goal.
language-based environment for natural language parsing. this paper introduces a special programming environment for the definition of grammars and for the implementation of corresponding parsers. in natural language processing systems it is advantageous to have linguistic knowledge and processing mechanisms separated. our environment accepts grammars consisting of binary dependency relations and grammatical functions. well-formed expressions of functions and relations provide constituent surroundings for syntactic categories in the form of two-way automata. these relations, functions, and automata are described in a special definition language.in focusing on high level descriptions a linguist may ignore computational details of the parsing process. he writes the grammar into a dpl-description and a compiler translates it into efficient lisp-code. the environment has also a tracing facility for the parsing process, grammar-sensitive lexical maintenance programs, and routines for the interactive graphic display of parse trees and grammar definitions. translator routines are also available for the transport of compiled code between various lisp-dialects. the environment itself exists currently in interlisp and franzlisp. this paper focuses on knowledge engineering issues and does not enter linguistic argumentation.
learning to identify fragmented words in spoken discourse. disfluent speech adds to the difficulty of processing spoken language utterances. in this paper we concentrate on identifying one disfluency phenomenon: fragmented words. our data, from the spoken dutch corpus, samples nearly 45,000 sentences of human discourse, ranging from spontaneous chat to media broadcasts. we classify each lexical item in a sentence either as a completely or an incompletely uttered, i.e. fragmented, word. the task is carried out both by the ib 1 and ripper machine learning algorithms, trained on a variety of features with an extensive optimization strategy. our best classifier has a 74.9% f-score, which is a significant improvement over the baseline. we discuss why memory-based learning has more success than rule induction in correctly classifying fragmented words.
a flexible natural language parser based on a two-level representation of syntax. in this paper we present a parser which a<u>l</u> lows to make explicit the interconnections between syntax and semantics, to analyze the sentences in a quasi-deterministic fashion and, in many cases, to identify the roles of the various constituents even if the sentance is ill-formed. the main fe<u>a</u>ture of the approach on which the parser is based consists in a two-level representation of the sy<u>n</u>tactic knowledge: a first set of rules emits h<u>y</u>potheses about the constituents of the sentence and their functional role and another set of rules verifies whether a hypothesis satisfies the co<u>n</u>straints about the well-formedness of sentences. however, the application of the second set of rules is delayed until the semantic knowledge co<u>n</u>firms the acceptability of the hypothesis. if the semantics reject it, a new hypothesis is obtained by applying a simple and relatively unexpensive "natural" modification; a set of these modific<u>a</u>tions is predefined and only when none of them is applicable a real backup is performed: in most cases this situation corresponds to a case where people would normally garden path.
lambek theorem proving and feature unification. feature unification can be integrated with lambek theorem proving in a simple and straightforward way. two principles determine all distribution of features in ltp. it is not necessary to stipulate other principles or include category-valued features where other theories do. the structure of categories is discussed with respect to the notion of category structure of gazdar et al. (1988).
contents and evaluation of the first slovenian-german online dictionary. this paper presents the first slovenian-german and german-slovenian online dictionary and contains evaluation figures for its slovenian part. evaluations are based on coverage of a slovenian newspaper corpus as well as on user queries.
computational semantics of mass terms. although the formalisms normally used for describing the semantics of natural languages are far from computationally tractable, it is possible to isolate particular semantic phenomena and interpret them within simpler formal systems. quantified mass noun phrases is one such part. we describe a simple formal system suitable for the interpretation of quantified mass noun phrases. the main issue of this paper is to develop an algorithm for deciding the validity of sentences in the formal system and hence for deciding the validity of natural language inferences where all the involved noun phrases are quantified mass noun phrases. the decision procedure is based on a tableau calculus.
repair strategies for lexicalized tree grammars. this paper presents a framework for the definition of monotonic repair rules on chart items and lexicalized tree grammars. we exploit island representations and a new level of granularity for the linearization of a tree called connected routes. it allows to take into account the topology of the tree in order to trigger additional rules. these local rules cover ellipsis and common extra-grammatical phenomena such as self-repairs. first results with a spoken language corpora are presented.
sublanguages in machine translation. there have been various attempts at using the sublanguage notion for disambiguation and the selection of target langauge equivalents in machine translation. in this paper a theoretical concept and its implementation in a real mt application are presented. above this, means of linguistic engineering like weighting mechanisms are proposed.
a fast partial parse of natural language sentences using a connectionist method. the pattern matching capabilities of neural networks can be used to locate syntactic constituents of natural language. this paper describes a fully automated hybrid system, using neural nets operating within a grammatic framework. it addresses the representation of language for connectionist processing, and describes methods of constraining the problem size. the function of the network is briefly explained, and results are given.
pearl: a probabilistic chart parser. this paper describes a natural language parsing algorithm for unrestricted text which uses a probability-based scoring function to select the "best" parse of a sentence. the parser, pearl, is a time-asynchronous bottom-up chart parser with earley-type top-down prediction which pursues the highest-scoring theory in the chart, where the score of a theory represents the extent to which the context of the sentence predicts that interpretation. this parser differs from previous attempts at stochastic parsers in that it uses a richer form of conditional probabilities based on context to predict likelihood. pearl also provides a framework for incorporating the results of previous work in part-of-speech assignment, unknown word models, and other probabilistic models of linguistic features into one parsing tool, interleaving these techniques instead of using the traditional pipeline architecture. in preliminary tests, pearl has been successful at resolving part-of-speech and word (in speech processing) ambiguity, determining categories for unknown words, and selecting correct parses first using a very loosely fitting covering grammar.
deterministic consistency checking of lp constraints. we provide a constraint based computational model of linear precedence as employed in the hpsg grammar formalism. an extended feature logic which adds a wide range of constraints involving precedence is described. a sound, complete and terminating deterministic constraint solving procedure is given. deterministic computational model is achieved by weakening the logic such that it is sufficient for linguistic applications involving word-order.
complementing wordnet with roget's and corpus-based thesauri for information retrieval. this paper proposes a method to overcome the drawbacks of wordnet when applied to information retrieval by complementing it with roget's thesaurus and corpus-derived thesauri. words and relations which are not included in wordnet can be found in the corpus-derived thesauri. effects of polysemy can be minimized with weighting method considering all query terms and all of the thesauri. experimental results show that our method enhances information retrieval performance significantly.
the tipster summac text summarization evaluation. the tipster text summarization evaluation (summac) has established definitively that automatic text summarization is very effective in relevance assessment tasks. summaries as short as 17% of full text length sped up decision-making by almost a factor of 2 with no statistically significant degradation in f-score accuracy. summac has also introduced a new intrinsic method for automated evaluation of informative summaries.
case role filling as a side effect of visual search. this paper addresses the problem of generating communicatively adequate extended responses in the absence of specific knowledge concerning the intensions of the questioner. we formulate and justify a heuristic for the selection of optional deep case slots not contained in the question as candidates for the additional information contained in an extended response. it is shown that, in a visually present domain of discourse, case role filling for the construction of an extended response can be regarded as a side effect of the visual search necessary to answer a question containing a locomotion verb. the paper describes the various representation constructions used in the german language dialog system ham-ans for dealing with the semantics of locomotion verbs and illustrates their use in generating extended responses. in particular, we outline the structure of the geometrical scene description, the representation of events in a logic-oriented semantic representation language, the case-frame lexicon and the representation of the referential semantics based on the flavor system. the emphasis is on a detailed presentation of the application of object-oriented programming methods for coping with the semantics of locomotion verbs. the process of generating an extended response is illustrated by an extensively annotated trace.
an efficient context-free parser for augmented phrase-structure grammars. in this paper we present an efficient context-free (cf) bottom-up, non deterministic parser. it is an extension of the ica (immediate constituent analysis) parser proposed by grishman (1976), and its major improvements are described.it has been designed to run augmented phrase-structure grammars (apsg) and performs semantic interpretation in parallel with syntactic analysis.it has been implemented in franz lisp and runs on vax 11/780 and, recently, also on a sun workstation, as the main component of a transportable natural language interface (sail = sistema per l'analisi e l'interpretazione del linguaggio). subsets of grammars of italian written in different formalisms and for different applications have been experimented with sail. in particular, a toy application has been developed in which sail has been used as interface to build a knowledge base in mrs (genesereth et al. 1980, genesereth 1981) about ski paths in a ski environment, and to ask for advice about the best touristic path under specific weather and physical conditions.
stochastic modeling of language via sentence space partitioning. in some computer applications of linguistics (such as maximum-likelihood decoding of speech or handwriting), the purpose of the language-handling component (language model) is to estimate the linguistic (a priori) probability of arbitrary natural-language sentences. this paper discusses theoretical and practical issues regarding an approach to building such a language model based on any equivalence criterion defined on incomplete sentences, and experimental results and measurements performed on such a model of the italian language, which is a part of the prototype for the recognition of spoken italian built at the ibm rome scintific center.
computing term translation probabilities with generalized latent semantic analysis. term translation probabilities proved an effective method of semantic smoothing in the language modelling approach to information retrieval tasks. in this paper, we use generalized latent semantic analysis to compute semantically motivated term and document vectors. the normalized cosine similarity between the term vectors is used as term translation probability in the language modelling framework. our experiments demonstrate that glsa-based term translation probabilities capture semantic relations between terms and improve performance on document classification.
enhancing explanation coherence with rhetorical strategies. this paper discusses the application of a previously reported theory of explanation rhetoric (maybury, 1988b) to the task of explaining constraint violations in a hybrid rule/frame based system for resource allocation (dawson et al, 1987). this research illustrates how discourse strategies of explanation, textual connectives, and additional justification knowledge can be applied to enhance the cohesiveness, structure, and clarity of knowledge based system explanations.
a computational theory of prose style for natural language generation. in this paper we report on initial research we have conducted on a computational theory of prose style. our theory speaks to the following major points:1. where in the generation process style is taken into account.2. how a particular prose style is represented; what "stylistic rules" look like;3. what modifications to a generation algorithm are needed; what the decision is that evaluates stylistic alternatives;4. what elaborations to the normal description of surface structure are necessary to make it usable as a plan for the text and a reference for these decisions;5. what kinds of information decisions about style have access to.our theory emerged out of design experiments we have made over the past year with our natural language generation system, the zetalisp program mumble. in the process we have extended mumble through the addition of an additional process that now mediates between content planning and linguistic realization. this new process, which we call "attachment", provides the further significant benefit that text structure is no longer dictated by the structure of the message: the sequential order and dominance relationships of concepts in the message no longer force one form onto the words and phrases in the text. instead, rhetorical and intentional directives can be interpreted flexibly in the context of the ongoing discourse and stylistic preferences. the text is built up through composition under the direction of linguistic organizing principles, rather than having to follow conceptual principles in lockstep.we will begin by describing what we mean by prose style and then introducing the generation task that lead us to this theory, the reproduction of short encyclopedia articles on african tribes. we will then use that task to outline the parts of our theory and the operations of the attachment process. finally we will compare our techniques to the related work of davey, mckeown and derr, and gabriel, and consider some of the possible psycholinguistic hypotheses that it may lead to.
the generation of term definitions from an on-line terminological thesaurus. a new type of machine dictionary is described, which uses terminological relations to build up a semantic network representing the terms of a particular subject field, through interaction with the user. these relations are then used to dynamically generate outline definitions of terms in on-line query mode. the definitions produced are precise, consistent and informative, and allow the user to situate a query term in the local conceptual environment. the simple definitions based on terminological relations are supplemented by information contained in facets and modifiers, which allow the user to capture different views of the data.
abductive explanation of dialogue misunderstandings. to respond to an utterance, a listener must interpret what others have said and why they have said it. misunderstandings occur when agents differ in their beliefs about what has been said or why. our work combines intentional and social accounts of discourse, unifying theories of speech act production, interpretation, and the repair of misunderstandings. a unified theory has been developed by characterizing the generation of utterances as default reasoning and using abduction to characterize interpretation and repair.
automated reasoning about natural language correctness. automated reasoning techniques applied to the problem of natural language correctness allow the design of flexible training aids for the teaching of foreign languages. the approach involves important advantages for both the student and the teacher by detecting possible errors and pointing out their reasons. explanations may be given on four distinct levels, thus offering differently instructive error messages according to the needs of the student.
generalised pp-attachment disambiguation using corpus-based linguistic diagnostics. we propose a new formulation of the pp attachment problem as a 4-way classification which takes into account the argument or adjunct status of the pp. based on linguistic diagnostics, we train a 4-way classifier that reaches an average accuracy of 73.9% (baseline 66.2%). compared to a sequence of binary classifiers, the 4-way classifier reaches better performance and individuates a verb's arguments more accurately, thus improving the acquisition of a crucial piece of information for many nlp applications.
towards a workbench for acquisition of domain knowledge from natural language. in this paper we describe an architecture and functionality of main components of a workbench for an acquisition of domain knowledge from large text corpora. the workbench supports an incremental process of corpus analysis starting from a rough automatic extraction and organization of lexico-semantic regularities and ending with a computer supported analysis of extracted data and a semiautomatic refinement of obtained hypotheses. for doing this the workbench employs methods from computational linguistics, information retrieval and knowledge engineering. although the work-bench is currently under implementation some of its components are already implemented and their performance is illustrated with samples from engineering for a medical domain.
named entity recognition without gazetteers. it is often claimed that named entity recognition systems need extensive gazetteers---lists of names of people, organisations, locations, and other named entities. indeed, the compilation of such gazetteers is sometimes mentioned as a bottleneck in the design of named entity recognition systems.we report on a named entity recognition system which combines rule-based grammars with statistical (maximum entropy) models. we report on the system's performance with gazetteers of different types and different sizes, using test material from the muc-7 competition. we show that, for the text type and task of this competition, it is sufficient to use relatively small gazetteers of well-known names, rather than large gazetteers of low-frequency names. we conclude with observations about the domain independence of the competition and of our experiments.
incremental interpretation of categorial grammar. the paper describes a parser for categorial grammar which provides fully word by word incremental interpretation. the parser does not require fragments of sentences to form constituents, and thereby avoids problems of spurious ambiguity. the paper includes a brief discussion of the relationship between basic categorial grammar and other formalisms such as hpsg, dependency grammar and the lambek calculus. it also includes a discussion of some of the issues which arise when parsing lexicalised grammars, and the possibilities for using statistical techniques for tuning to particular languages.
selective magic hpsg parsing. we propose a parser for constraint-logic grammars implementing hpsg that combines the advantages of dynamic bottom-up and advanced top-down control. the parser allows the user to apply magic compilation to specific constraints in a grammar which as a result can be processed dynamically in a bottom-up and goal-directed fashion. state of the art top-down processing techniques are used to deal with the remaining constraints. we discuss various aspects concerning the implementation of the parser as part of a grammar development system.
off-line optimization for earley-style hpsg processing. a novel approach to hpsg based natural language processing is described that uses an off-line compiler to automatically prime a declarative grammar for generation or parsing, and inputs the primed grammar to an advanced earley-style processor. this way we provide an elegant solution to the problems with empty heads and efficient bidirectional processing which is illustrated for the special case of hpsg generation. extensive testing with a large hpsg grammar revealed some important constraints on the form of the grammar.
lexicalized grammar acquisition. this paper presents a formalization of automatic grammar acquisition that is based on lexicalized grammar formalisms (e.g. ltag and hpsg). we state the conditions for the consistent acquisition of a unique lexicalized grammar from an annotated corpus.
expressing generalizations in unification-based grammar formalisms. this paper shows how higher levels of generalization can be introduced into unification grammars by exploiting methods for typing grammatical objects. we discuss the strategy of using global declarations to limit possible linguistic structures, and sketch a few unusual aspects of our type-checking algorithm. we also describe the sort system we use in our semantic representation language and illustrate the expressive power gained by being able to state global constraints over these sorts. finally, we briefly illustrate the sort system by applying it to some agreement phenomena and to problems of adjunct resolution.
learning translations of named-entity phrases from parallel corpora. we develop a new approach to learning phrase translations from parallel corpora, and show that it performs with very high coverage and accuracy in choosing french translations of english named-entity phrases in a test corpus of software manuals. analysis of a subset of our results suggests that the method should also perform well on more general phrase translation tasks.
user modelling, dialog structure, and dialog strategy in ham-ans. ai dialog systems are now developing from question-answering systems toward advising systems. this includes:- structuring dialog- understanding and generating a wider range of speech acts than simply information request and answer- user modellinguser modelling in ham-ans is closely connected to dialog structure and dialog strategy. in advising the user, the system generates and verbalizes speech acts. the choice of the speech act is guided by the user profile and the dialog strategy of the system.
higher-order linear logic programming of categorial deduction. we show how categorial deduction can be implemented in higher-order (linear) logic programming, thereby realising parsing as deduction for the associative and non-associative lambek calculi. this provides a method of solution to the parsing problem of lambek categorial grammar applicable to a variety of its extensions.
geometry of lexico-syntactic interaction. interaction of lexical and derivational semantics ---for example substitution and lambda conversion--- is typically a part of the on-line interpretation process. proof-nets are to categorial grammar what phrase markers are to phrase structure grammar: unique graphical structures underlying equivalence classes of sequential syntactic derivations; but the role of proof-nets is deeper since they integrate also semantics. in this paper we show how interaction of lexical and derivational semantics at the lexico-syntactic interface can be precomputed as a process of off-line lexical compilation comprising cut elimination in partial proof-nets.
tuples, discontinuity, and gapping in categorial grammar. this paper solves some puzzles in the formalisation of logic for discontinuity in categorial grammar. a 'tuple' operation introduced in [solias, 1992] is defined as a mode of prosodic combination which has associated projection functions, and consequently can support a property of unique prosodic decomposability. discontinuity operators are defined model-theoretically by a residuation scheme which is particularly ammenable proof-theoretically. this enables a formulation which both improves on the logic for wrapping and infixing of [moortgat, 1988] which is only partial, and resolves some problems of determinacy of insertion point in the application of these proposals to in-situ binding phenomena. a discontinuous product is also defined by the residuation scheme, enabling formulation of rules of both use and proof for a 'substring' product that would have been similarly doomed to partial logic.we show how the apparatus enables characterisation of discontinous functors such as particle verbs and phrasal idioms, and binding phenomena such as quantifier raising and pied piping. we conclude by showing how the apparatus enables a simple categorial analysis of (svo) gapping using the discontinuity product and the wrapping operator.
determination of syntactic functions in estonian constraint grammar. this article describes the current state of syntactic analysis of estonian using constraint grammar. constraint grammar framework divides parsing into two different modules: morphological disambiguation and determination of syntactic functions. this article focuses on the last module in detail. if the morphological disambiguator achieves the precision more than 85% and error rate is smaller than 2% then 80--88% of words becomes syntactically unambiguous. the error rate of parser is 1--4% depending on the ambiguity rate of input. the main goal of this work is to elaborate an efficient parser for estonian and annotate the corpus of estonian written texts syntactically. it is the first attempt to write a parser for estonian.
augmented dependency grammar: a simple interface between the grammar rule and the knowledge. this paper describes some operational aspects of a language comprehension model which unifies the linguistic theory and the semantic theory in respect to operations. the computational model, called augmented dependency grammar (adg), formulates not only the linguistic dependency structure of sentences but also the semantic dependency structure using the extended deep case grammar and field-oriented fact-knowledge based inferences. fact knowledge base and adg model clarify the qualitative difference between what we call semantics and logical meaning. from a practical view point, it provides clear image of syntactic/semantic computation for language processing in analysis and synthesis. it also explains the gap in semantics and logical meaning, and gives a clear computational image of what we call conceptual analysis.this grammar is used for analysis of japanese and synthesis of english, in the japanese-to-english machine translation system called venus (vehicle for natural language understanding and synthesis) currently developed by nec.
an extended lr parsing algorithm for grammars using feature-based syntactic categories. this paper proposes an lr parsing algorithm modified for grammars with feature-based categories. the proposed algorithm does not instantiate categories during preprocessing of a grammar as proposed elsewhere. as a result, it constructs a minimal size of goto/action table and eliminates the necessity of search for goto table entries during parsing.
temporal reasoning in natural language understanding: the temporal structure of the narrative. this paper proposes a new framework for discourse analysis, in the spirit of grosz and sidner (1986), webber (1987a,b) but differentiated with respect to the type or genre of discourse. it is argued that different genres call for different representations and processing strategies; particularly important is the distinction between subjective, performative discourse and objective discourse, of which narrative is a primary example. this paper concentrates on narratives and introduces the notions of temporal focus (proposed also in webber (1987b)) and narrative move. the processing tasks involved in reconstructing the temporal structure of a narrative (webber's e/s structure) are formulated in terms of these two notions. the remainder of the paper analyzes the durational and aspectual knowledge needed for those tasks. distinctions are established between grammatical aspect, aspectual class and the aspectual perspective of a sentence in discourse; it is shown that in english, grammatical aspect under-determines the aspectual perspective.
subject erasing and pronominalization in italian text generation. certain romance languages such as italian, spanish and portuguese allow the subject to be erased in tensed clauses. this paper studies subject erasing in the framework of a text generation system for italian. we will prove that it is first necessary to try to pronominalize the subject. therefore, we are led to study the synthesis of subject and complement personal pronouns. in romance languages, personal pronouns raise many syntactic problems, whose solution is complex in a generation system. we will see that pronominalization plays a fundamental role in the order in which the elements of a clause are synthesized, and consequently in the synthesis of this clause. moreover, the synthesis of a clause must take into account the fact that subject erasing and the synthesis of complements are phenomena which depend on each other. the complex algorithm that must be used for the synthesis of a clause will be illustred in various examples.
on abstract finite-state morphology. aspects of abstract finite-state morphology are introduced and demonstrated. the use of two-way finite automata for arabic noun stem and verb root inflection leads to abstractions based on finite-state transition network topology as well as the form and content of network arcs. nonconcatenative morphology is distinguished from concatenative morphology by its use of movement on the output tape rather than the input tape. the idea of specific automata for classes of inflection inheriting some or all of the nodes, arc form and arc content of the abstract automaton is also introduced. this can lead to novel linguistic generalities and application, as well as advantages in terms of procedural efficiency and representation.
the structure of communicative context of dialogue interaction. we propose a draft scheme of the model formalizing the structure of communicative context in dialogue interaction. the relationships between the interacting partners are considered as system of three automata representing the partners of the dialogue and environment.the communicative competence of the partners is defined by- the set m of all propositions reflecting the possible states of the three automata within the model;- the set k of "contracts" representing all kinds of human-to-human relationships (social, interpersonal, professional, etc.) which include fixation of particular roles for the partners;- the set t of possible topics related to given "contract".the authors believe the system of the notions presented may be used as a basis for forming the communicative component in the dialogue system.
online word sense disambiguation with structural semantic interconnections. in this paper we present an online implementation of a knowledge-based word sense disambiguation algorithm called structural semantic interconnections (ssi). we describe the system implementation and the user interface, and discuss the strengths and weaknesses of our approach.
generalized left-corner parsing. we show how techniques known from generalized lr parsing can be applied to left-corner parsing. the resulting parsing algorithm for context-free grammars has some advantages over generalized lr parsing: the sizes and generation times of the parsers are smaller, the produced output is more compact, and the basic parsing technique can more easily be adapted to arbitary context-free grammars.the algorithm can be seen as an optimization of algorithms known from existing literature. a strong advantage of our presentation is that it makes explicit the role of left-corner parsing in these algorithms.
splitting the reference time: temporal anaphora and quantification in drt. this paper presents an analysis of temporal anaphora in sentences which contain quantification over events, within the framework of discourse representation theory. the analysis in (partee, 1984) of quantified sentences, introduced by a temporal connective, gives the wrong truth-conditions when the temporal connective in the subordinate clause is before or after. this problem has been previously analyzed in (de swart, 1991) as an instance of the proportion problem, and given a solution from a generalized quantifier approach. by using a careful distinction between the different notions of reference time, based on (kamp and reyle, 1993), we propose a solution to this problem, within the framework of drt. we show some applications of this solution to additional temporal anaphora phenomena in quantified sentences.
comparison and classification of dialects. this project measures and classifies language variation. in contrast to earlier dialectology, we seek a comprehensive characterization of (potentially gradual) differences between dialects, rather than a geographic delineation of (discrete) features of individual words or pronunciations. more general characterizations of dialect differences then become available. we measure phonetic (un)relatedness between dialects using levenshtein distance, and classify by clustering distances but also by analysis through multidimensional scaling.
creating a multilingual collocations dictionary from large text corpora. this paper describes a system of terminological extraction capable of handling multi-word expressions, using a powerful syntactic parser. the system includes a concordancing tool enabling the user to display the context of the collocation, i.e. the sentence or the whole document where the collocation occurs. since the corpora are multilingual, the system also offers an alignment mechanism for the corresponding translated documents.
a bidirectional model for natural language processing. in this paper i will argue for a model of grammatical processing that is based on uniform processing and knowledge sources. the main feature of this model is to view parsing and generation as two strongly interleaved tasks performed by a single parametrized deduction process. it will be shown that this view supports flexible and efficient natural language processing.
resolving zero anaphora in japanese. the paper presents a computational theory for resolving japanese zero anaphora, based on the notion of discourse segment. we see that the discourse segment reduces the domain of antecedents for zero anaphora and thus leads to their efficient resolution.also we make crucial use of functional notions such as empathy hierarchy and minimal semantics thesis to resolve reference for zero anaphora [kuno, 1987]. our approach differs from the centering analysis [walker et al., 1990] in that the resolution works by matching one empathy hierarchy against another, which makes it possible to deal with discourses with no explicit topic and those with cataphora [halliday and hassan, 1990].the theory is formalized through the definite clause grammar (dcg) formalism [pereira and warren, 1980], [gazdar and mellish, 1989; longacre, 1979].finally, we show that graphology i.e., quotation mark, spacing, has an important effect on the interpretation of zero anaphora in japanese discourse.
an approach to sentence-level anaphora in machine translation. theoretical research in the area of machine translation usually involves the search for and creation of an appropriate formalism. an important issue in this respect is the way in which the compositionality of translation is to be defined. in this paper, we will introduce the anaphoric component of the mimo formalism. it makes the definition and translation of anaphoric relations possible, relations which are usually problematic for systems that adhere to strict compositionality. in mimo, the translation of anaphoric relations is compositional. the anaphoric component is used to define linguistic phenomena such as wh-movement, the passive and the binding of reflexives and pronouns monolingually. the actual working of the component will be shown in this paper by means of a detailed discussion of wh-movement.
an object-oriented approach to the design of dialogue management functionality. dialogues may be seen as comprising commonplace routines on the one hand and specialized, task-specific interactions on the other. object-orientation is an established means of separating the generic from the specialized. the system under discussion combines this object-oriented approach with a self-organizing, mixed-initiative dialogue strategy, raising the possibility of dialogue systems that can be assembled from ready-made components and tailored, specialized components.
the organization of the rosetta grammars. in this paper the organization of the grammars in the rosetta machine translation system is described and it is shown how this organization makes it possible to translate between words of different syntactic categories in a systematic way. it is also shown how the organization chosen makes it possible to translate 'small clauses' into full clauses and vice versa. the central concept worked out here in some detail is the concept of 'partial isomorphy' between subgrammars. the system as described here has been implemented and is currently being tested.
formal properties of metrical structure. this paper offers a provisional mathematical typology of metrical representations. first, a family of algebras corresponding to different versions of grid and bracketed grid theory is introduced. it is subsequently shown in what way bracketed grid theory differs from metrical theories using trees. finally, we show that there are no significant differences between the formalism of bracketed grids (for metrical structure) and the representation used in the work of [kaye, et al., 1985], [1990] for subsyllabic structure.
cast: a computer-aided summarisation tool. in this paper we propose computer-aided summarisation (cas) as an alternative approach to automatic summarisation, and present an ongoing project which aims to develop a cas system. the need for such an alternative approach is justified by the relatively poor performance of fully automatic methods used in summarisation. our system combines several summarisation methods, allowing the user of the system to interact with their parameters and output in order to improve the quality of the produced summary.
how to build a qa system in your back-garden: application for romanian. even though the question answering (qa) field appeared only in recent years, there are systems for english which obtain good results for open-domain questions. the situation is very different for other languages, mainly due to the lack of nlp resources which are normally used by qa systems. in this paper, we present a project which develops a qa system for romanian. the challenges we face and decisions we have to make are discussed.
pos disambiguation and unknown word guessing with decision trees. this paper presents a decision-tree approach to the problems of part-of-speech disambiguation and unknown word guessing as they appear in modern greek, a highly inflectional language. the learning procedure is tag-set independent and reflects the linguistic reasoning on the specific problems. the decision trees induced are combined with a high-coverage lexicon to form a tagger that achieves 93, 5% overall disambiguation accuracy.
semantic features and selection restrictions. one of the essential aspects is described of an expert system (called lexicographer), designed to supply the user with diverse information about russian words, including bibliographic information concerning individual lexical entries. the lexical database of the system contains semantic information that cannot be elicited from the existing dictionaries. the priority is given to semantic features influencing lexical or grammatical co-occurrence restrictions. possibilities are discussed of predicting selectional restrictions on the basis of semantic features of a word in the lexicon.
information structure and pauses in a corpus of spoken danish. this paper describes a study in which a corpus of spoken danish annotated with focus and topic tags was used to investigate the relation between information structure and pauses. the results show that intra-clausal pauses in the focus domain, tend to precede those words that express the property or semantic type whereby the object in focus is distinguished from other ones in the domain.
investigating nlg architectures: taking style into consideration. in this paper we propose a methodology for investigating the relationship between architectures of natural language generation (nlg) systems and stylistic properties of texts. biber's (1988) methodology is used to obtain both the characterisation of style of our corpus and the division of the corpus into sets of linguistically similar texts. these sets will be used for studying the architectural aspects.
gems: a model of sentence production. the paper describes gems, a system for generating and expressing the meaning of sentences, focussing on the generation task, i.e. how gems extracts a set of propositional units from a knowledge store that can be expressed with a well-formed sentence in a target language. gems is lexically distributed. after a central processor has selected the first unit(s) from the knowledge store and activated the corresponding lexical entry, the further construction of the sentences meaning is entrusted to the entries in the vocabulary. examples of how gems constructs the meaning of a number of english sentence types are briefly described.
saumer: sentence analysis using metarules. the saumer system uses specifications of natural language grammars, which consist of rules and metarules, to provide a semantic interpretation of an input sentence. the saumer specification language (ssl) is a programming language which combines some of the features of generalised phrase structure grammars (gazdar, 1981), like the correspondence between syntactic and semantic rules. with definite clause grammars (dcgs) (pereira and warren, 1980) to create an executable grammar specification. ssl rules are similar to dcg rules except that they contain a semantic component and may also be left recursive. metarules are used to generate new rules from existing rules before any parsing is attempted. an implementation is tested which can provide semantic interpretations for sentences containing topicalisation, relative clauses, passivisation, and questions.
a problem solving approach to generating text from systemic grammars. systemic grammar has been used for ai text generation work in the past, but the implementations have tended be ad hoc or inefficient. this paper presents an approach to systemic text generation where ai problem solving techniques are applied directly to an unadulterated systemic grammar. this approach is made possible by a special relationship between systemic grammar and problem solving: both are organized primarily as choosing from alternatives. the result is simple, efficient text generation firmly based in a linguistic theory.
generating referring expressions with a unification grammar. a simple formalism is proposed to represent the contexts in which pronouns, definite/indefinite descriptions, and ordinal descriptions (e.g. 'the second book') can be used, and the way in which these expressions change the context. it is shown that referring expressions can be generated by a unification grammar provided that some phrase-structure rules are specially tailored to express entities in the current knowledge base.
a structured representation of word-senses for semantic analysis. a framework for a structured representation of semantic knowledge (e.g. word-senses) has been defined at the ibm scientific center of roma, as part of a project on italian text understanding. this representation, based on the conceptual graphs formalism [sow84], expresses deep knowledge (pragmatic) on word-senses. the knowledge base data structure is such as to provide easy access by the semantic verification algorithm. this paper discusses some important problem related to the definition of a semantic knowledge base, as depth versus generality, hierarchical ordering of concept types, etc., and describes the solutions adopted within the text understanding project.
using grammatical relations to compare parsers. we use the grammatical relations (grs) described in carroll et al. (1998) to compare a number of parsing algorithms. a first ranking of the parsers is provided by comparing the extracted grs to a gold standard gr annotation of 500 susanne sentences: this required an implementation of gr extraction software for penn treebank style parsers. in addition, we perform an experiment using the extracted grs as input to the lappin and leass (1994) anaphora resolution algorithm. this produces a second ranking of the parsers, and we investigate the number of errors that are caused by the incorrect 'grs.
selecting the "right" number of senses based on clustering criterion functions. this paper describes an unsupervised knowledge-lean methodology for automatically determining the number of senses in which an ambiguous word is used in a large corpus. it is based on the use of global criterion functions that assess the quality of a clustering solution.
generating contextually appropriate intonation. one source of unnaturalness in the output of text-to-speech systems from the involvement of algorithmically generated default intonation contours, applied under minimal control from syntax and semantics. it is a tribute both to the resilience of human language understanding and to the ingenuity of the inventors of these algorithms that the results are as intelligible as they are. however, the result is very frequently unnatural, and may on occasion mislead the hearer. this paper extends earlier work on the relation between syntax and intonation in language understanding in combinatory categorial grammar (ccg). a generator with a simple and domain-independent discourse model can be used to direct synthesis of intonation contours for responses to data-base queries, to convey distinctions of contrast and emphasis determined by the discourse model.
example-based metonymy recognition for proper nouns. metonymy recognition is generally approached with complex algorithms that rely heavily on the manual annotation of training and test data. this paper will relieve this complexity in two ways. first, it will show that the results of the current learning algorithms can be replicated by the 'lazy' algorithm of memory-based learning. this approach simply stores all training instances to its memory and classifies a test instance by comparing it to all training examples. second, this paper will argue that the number of labelled training examples that is currently used in the literature can be reduced drastically. this finding can help relieve the knowledge acquisition bottleneck in metonymy recognition, and allow the algorithms to be applied on a wider scale.
extended access to the left context in an atn parser. some italian sentences related to linguistic phenomena largely known and recently discussed by many computational linguists are discussed in the framework of atn. they offer certain difficulties which seem to suggest a substantial revision of the atn formalism. the theoretical assumptions and an experimental implementation of such a revision are presented, together with examples. many related theoretical points such as some psycholinguistic implications and the relationship between deterministic and non-jeterministic hypothesis are also briefly discussed.
word classification based on combined measures of distributional and semantic similarity. the paper addresses the problem of automatic enrichment of a thesaurus by classifying new words into its classes. the proposed classification method makes use of both the distributional data about a new word and the strength of the semantic relatedness of its target class to other likely candidate classes.
a modular approach to story generation. one way of characterising texts is in terms of the discourse structures on which they appear to be built. each type of text, or genre, e.g. the sports report, the recipe, the sermon, the proverb, will have associated with it a characteristic organisation of units. in this paper, a general model of the structure of one text type, the story, is described. this model forms the basis of a program which combines the general story structure principles with rules governing a particular sub-genre, the old french epic, in order to generate story summaries.
a parser that doesn't. this paper describes an implemented parser-interpreter which is intended as an abstract formal model of part of the process of sentence comprehension. it is illustrated here for phrase structure grammars with a translation into a familiar type of logical form, although the general principles are intended to apply to any grammatical theory sharing certain basic assumptions, which are discussed in the paper. the procedure allows for incremental semantic interpretation as a sentence is parsed, and provides a principled explanation for some familiar observations concerning properties of deeply recursive constructions.
passives. the english passive construction has played a central role in the to-ings and fro-ings of grammatical theory over the last 30 years, from the earliest days of transformational grammar, to more recent, surface oriented theories of syntax. the casual reader of the linguistic literature might therefore suppose that the computational linguist looking for an off the shelf analysis of passives would be able to choose from among several competing analyses, each of which accommodated the facts. but perhaps derived them from (or from them) different theoretical principles. unfortunately. this is not the case. as we shall see. all of the analyses that i am familiar with are incomplete, or inaccurate in some respects, or simply unprogrammable in any straightforward form. the present paper is an attempt to remedy this situation, and to provide such an off the shelf analysis of the syntax and semantics of passives. the analysis of this central construction will be couched within a simple and computationally tractable syntactic and semantic formalism, and should translated easily to most currently popular formalisms. it will be quite eclectic, freelyborrowing from several different grammatical theories.
avm description compilation using types as modes. this paper provides a method for generating compact and efficient code to implement the enforcement of a description in typed feature logic. it does so by viewing information about types through the course of code generation as modes of instantiation --- a generalization of the common practice in logic programming of the binary instantiated/variable mode declarations that advanced prolog compilers use. section 1 introduces the description language. sections 2 and 3 motivate the view of mode and compilation taken here, and outline a mode declaration language for typed feature logic. sections 4 through 7 then present the compiler. an evaluation on two grammars is presented at the end.
comparatives and ellipsis. this paper analyses the syntax and semantics of english comparatives, and some types of ellipsis. it improves on other recent analyses in the computational linguistics literature in three respects: (i) it uses no tree- or logical-form rewriting devices in building meaning representations (ii) this results in a fully reversible linguistic description, equally suited for analysis or generation (iii) the analysis extends to types of elliptical comparative not elsewhere treated.
topological parsing. we present a new grammar formalism for parsing with freer word-order languages, motivated by recent linguistic research in german and the slavic languages. unlike cfgs, these grammars contain two primitive notions of constituency that are used to preserve the semantic or interpretational aspects of phrase structure, while at the same time providing a more efficient backbone for parsing based on word-order and contiguity constraints. a simple parsing algorithm is presented, and compilation of grammars into constraint handling rules is also discussed.
semantic role labeling for coreference resolution. extending a machine learning based coreference resolution system with a feature capturing automatically generated information about semantic roles improves its performance.
a model for preference. in this paper we address the problem of choosing the best solution(s) from a set of interpretations of the same object (in our case a segment of text). a notion of preference is stated, based on pairwise comparisons of complete interpretations in order to obtain a partial order among the competing interpretations. an experimental implementation is described, which uses prolog-like preference statements.
adaptivity in question answering with user modelling and a dialogue interface. most question answering (qa) and information retrieval (ir) systems are insensitive to different users' needs and preferences, and also to the existence of multiple, complex or controversial answers. we introduce adaptivity in qa and ir by creating a hybrid system based on a dialogue interface and a user model.
a morphological processor for modern greek. in this paper, we present a morphological processor for modern greek.from the linguistic point of view, we try to elucidate the complexity of the inflectional system using a lexical model which follows the recent work by lieber, 1980, selkirk 1982, kiparsky 1982, and others.the implementation is based on the concept of "validation grammars" (courtin 1977).the morphological processing is controlled by a finite automaton and it combinesa. a dictionary containing the stems for a representative fragment of modern greek and all the inflectional affixes withb. a grammar which carries out the transmission of the linguistic information needed for the processing. the words are structured by concatenating a stem with an inflectional part. in certain cases, phonological rules are added to the grammar in order to capture lexical phonological phenomena.
finding content-bearing terms using term similarities. this paper explores the issue of using different co-occurrence similarities between terms for separating query terms that are useful for retrieval from those that are harmful. the hypothesis under examination is that useful terms tend to be more similar to each other than to other query terms. preliminary experiments with similarities computed using first-order and second-order co-occurrence seem to confirm the hypothesis. term similarities could then be used for determining which query terms are useful and best reflect the user's information need. a possible application would be to use this source of evidence for tuning the weights of the query terms.
effective parsing with generalised phrase structure grammar. generalised phrase structure grammars (gpsg's) appear to offer a means by which the syntactic properties of natural languages may be very concisely described. the main reason for this is that the gpsg framework allows you to state a variety of meta-grammatical rules which generate new rules from old ones, so that you can specify rules with a wide variety of realisations via a very small number of explicit statements. unfortunately, trying to analyse a piece of text in terms of such rules is a very awkward task, as even a small set of gpsg statements will generate a large number of underlying rules.this paper discusses some of the difficulties of parsing with gpsg's, and presents a fairly straightforward bottom-up parser for them. this parser is, in itself, no more than adequate - all its components are implemented quite efficiently, but there is nothing tremendously clever about how it searches the space of possible rules to find an analysis of the text it is working on. its power comes from the fact that it learns from experience: not new rules, but how to recognise realisations of complex combinations of its existing rules. the improvement in the system's performance after even a few trials is dramatic. this is brought about by a mechanism for recording the analysis of text fragments. such recordings may be used very effectively to guide the subsequent analysis of similar pieces of text. given such guidance it becomes possible to deal even with text containing unknown or ambiguous words with very little search.
extended graph unification. we propose an apparently minor extension to kay's (1985) notation for describing directed acylic graphs (dags). the proposed notation permits concise descriptions of phenomena which out otherwise be difficult to describe, without incurring significant extra computational overheads in the process of unification. we illustrate the notation with examples from a categorial description of a fragment of english, and discuss the computational properties of unification of dags specified in this way.
on the syntactic-semantic analysis of bound anaphora. two well-known phenomena in the area of pronoun binding are considered: indirect binding of pronouns by indefinite nps ("donkey sentences") and surface-syntactic constraints on binding ("weak cross-over"). a common treatment is proposed, and general consequences for the relation between syntactic and semantic processing are discussed. it is argued that syntactic and semantic analysis must interact in a complex way, rather than in a simple sequential or strict rule-to-rule fashion.
a common framework for analysis and generation. it seems highly desirable to use a single representation of linguistic knowledge for both analysis and generation. we argue that the only part of the average nl system's knowledge that we can have any faith in is its vocabulary and, to a lesser extent, its syntactic rules, and we investigate the consequences of this for generation.
a flexible pragmatics-driven language generator for animated agents. this paper describes the neca mnlg; a fully implemented multimodal natural language generation module. the mnlg is deployed as part of the neca system which generates dialogues between animated agents. the generation module supports the seamless integration of full grammar rules, templates and canned text. the generator takes input which allows for the specification of syntactic, semantic and pragmatic constraints on the output.
a metaplan model for problem-solving discourse. the structure of problem-solving discourse in the expert advising setting can be modeled by adding a layer of metaplans to a plan-based model of the task domain. classes of metaplans are introduced to model both the agent's gradual refinement and instatiation of a domain plan for a task and the space of possible queries about preconditions or fillers for open variable slots that can be motivated by the exploration of particular classes of domain plans. this metaplan structure can be used to track an agent's problem-solving progress and to predict at each point likely follow-on queries based on related domain plans. the model is implemented in the pragma system where it is used to suggest corrections for ill-formed input.
exploring the sense distributions of homographs. this paper quantitatively investigates in how far local context is useful to disam-biguate the senses of an ambiguous word. this is done by comparing the co-occurrence frequencies of particular context words. first, one context word representing a certain sense is chosen, and then the co-occurrence frequencies with two other context words, one of the same and one of another sense, are compared. as expected, it turns out that context words belonging to the same sense have considerably higher co-occurrence frequencies than words belonging to different senses. in our study, the sense inventory is taken from the university of south florida homograph norms, and the co-occurrence counts are based on the british national corpus.
a logical treatment of semi-free word order and bounded discontinuous constituency. in this paper we present a logical treatment of semifree word order and bounded discontinuous constituency. we extend standard feature value logics to treat word order in a single formalism with a rigorous semantics without phrase structure rules. the elimination of phrase structure rules allows a natural generalisation of the approach to nonconfigurational word order and bounded discontinuous continuency via sequence union. sequence union formalises the notions of clause union and scrambling by providing a mechanism for describing word order domains larger than the local tree. the formalism incorporates the distinction between bounded and unbounded forms of discontinuous constituency. grammars are organised as algebraic theories. this means that linguistic generalisations are stated as axioms about the structure of signs. this permits a natural interpretation of implicational universals in terms of theories, subtheories and implicational axioms. the accompanying linguistic analysis is eclectic, borrowing insights from many current linguistic theories.
dealing with the notion "obligatory" in syntactic analysis. in the paper the use of the notion "obligatory complement" in syntactic analysis is discussed. in many theories which serve as bases for syntactic analysis procedures there are devices to express the difference between obligatory and optional complements on the rule level, i.e. via the lexicon the wordforms are connected with these rules where the fitting properties are expressed. i'll show that such an approach leads to some problems, ifwe want to handle real texts in syntactic analysis.in the first part i'll outline the theoretical framework we work with. then i'll discuss for which purpose the use of the notion obligatory has some advantages and in the last part i'll show shortly how we intend to use this notion- in lexical entries (with respect to morphological analysis) and- in the syntactic analysis process.
prosodic inheritance and morphological generalisations. prosodic inheritance (pi) morphology provides uniform treatment of both concatenative and non-concatenative morphological and phonological generalisations using default inheritance. models of an extensive range of german umlaut and arabic intercalation facts, implemented in datr, show that the pl approach also covers 'hard cases' more homogeneously and more extensively than previous computational treatments.
coping with derivation in a morphological component. in this paper a morphological component with a limited capability to automatically interpret (and generate) derived words is presented. the system combines an extended two-level morphology [trost, 1991a; trost, 1991b] with a feature-based word grammar building on a hierarchical lexicon. polymorphemic stems not explicitly stored in the lexicon are given a compositional interpretation. that way the system allows to minimize redundancy in the lexicon because derived words that are transparent need note to be stored explicitly. also, words formed ad-hoc can be recognized correctly. the system is implemented in commonlisp and has been tested on examples from german derivation.
robust and flexible mixed-initiative dialogue for telephone services. in this work, we present an experimental analysis of a dialogue system for the automatization of simple telephone services. starting from the evaluation of a preliminar version of the system we conclude the necessity to desing a robust and flexible system suitable to have to have different dialogue control strategies depending on the characteristics of the user and the performance of the speech recognition module. experimental results following the paradise framework show an important improvement both in terms of task success and dialogue cost for the proposed system.
dialogue processing in a call-system. in a call-environment (computer-assisted language learning) programs should ideally allow the learner to train his/her communicative competence, which is one of the main goals of foreign language teaching nowadays. this can be reached by allowing learners to use and train their knowledge of a foreign language in realistic dialogue-style exercises. all levels of linguistic and communicational analysis have to be considered to realize such a system. in this paper i will concentrate on the dialogue component of the concept, which relies on two main knowledge sources. the discourse grammar structures the dialogue elements (or dialogue acts) as possible parts of a dialogue and the dialogue knowledge base provides the possible contents of dialogues. additionally, a framing discourse stucture has to be built to provide the specific dialogue-exercise. a fsa (finite state automaton) based on the discourse grammar determines the possible moves which the dialogue might take. on the one hand this concept is restricted enough to allow for (relatively) easy maintenance as well as expansion and on the other hand it is advanced enough to allow for simulated complex dialogues.
on reasoning with ambiguities. the paper adresses the problem of reasoning with ambiguities. semantic representations are presented that leave scope relations between quantifiers and/or other operators unspecified. truth conditions are provided for these representations and different consequence relations are judged on the basis of intuitive correctness. finally inference patterns are presented that operate directly on these underspecified structures, i.e. do not rely on any translation into the set of their disambiguations.
on learning more appropriate selectional restrictions. we present some variations affecting the association measure and thresholding on a technique for learning selectional restrictions from on-line corpora. it uses a wide-coverage noun taxonomy and a statistical measure to generalize the appropriate semantic classes. evaluation measures for the selectional restrictions learning task are discussed. finally, an experimental evaluation of these variations is reported.
developing an approach for why-question answering. in the current project, we aim at developing an approach for automatically answering why-questions. we created a data collection for research, development and evaluation of a method for automatically answering why-questions (why-qa) the resulting collection comprises 395 why-questions. for each question, the source document and one or two user-formulated answers are available in the data set. the resulting data set is of importance for our research and it will contribute to and stimulate other research in the field of why-qa. we developed a question analysis method for why-questions, based on syntactic categorization and answer type determination. the quality of the output of this module is promising for future development of our method for why-qa.
on the generative power of two-level morphological rules. koskenniemi's model of two-level morphology has been very influential in recent years, but definitions of the formalism have generally been phrased in terms of a compilation (sometimes left unspecified) into a form of finite-state transducers, or else have consisted of an informal outline of the intended interpretation of the rule-formalism itself. analyses of the properties of the formalism have generally focussed on the transducer mechanism. it is, however, possible to give a fully formal definition of the original rule notation directly, in a way which reflects koskenniemi's original informal characterisation and which does not depend directly on the notion of a transducer (although it must retain the essential nature of parts of the notation as being regular expressions). this re-formulation allows a proof that the ability of this formalism to characterise mappings between strings is more limited than that of arbitrary transducers.
lexical transfer based on bilingual signs: towards interaction during transfer. the lexical transfer phase is the most crucial step in mt because most of difficult problems are caused by lexical differences between two languages. in order to treat lexical issues systematically in transfer-based mt systems, we introduce the concept of bilingual-sings which are defined by pairs of equivalent monolingual signs. the bilingual signs not only relate the local linguistic structures of two languages but also play a central role in connecting the linguistic processes of translation with knowledge based inferences. we also show that they can be effectively used to formulate appropriate questions for disambiguating "transfer ambiguities", which is crucial in interactive mt systems.
an assessment of semantic information automatically extracted from machine readable dictionaries. in this paper we provide a quantitative evaluation of information automatically extracted from machine readable dictionaries. our results show that for any one dictionary, 55--70% of the extracted information is garbled in some way. however, we show that these results can be dramatically reduced to about 6% by combining the information extracted from five dictionaries. it therefore appears that even if individual dictionaries are an unreliable source of semantic information, multiple dictionaries can play an important role in building large lexical-semantic databases.
categorial grammar, modalities and algebraic semantics. this paper contributes to the theory of substructural logics that are of interest to categorial grammarians. combining semantic ideas of hepple [1990] and morrill [1990], proof-theoretic ideas of venema [1993b; 1993a] and the theory of equational specifications, a class of resource-preserving logics is defined, for which decidability and completeness theorems are established.
helpful answers to modal and hypothetical questions. this paper describes a computational pragmatic model which is geared towards providing helpful answers to modal and hypothetical questions. the work brings together elements from formal semantic theories on modality and question answering, defines a wider, pragmatically flavoured, notion of answerhood based on non-monotonic inference and develops a notion of context, within which aspects of more cognitively oriented theories, such as relevance theory, can be accommodated. the model has been implemented. the research was funded by esrc grant number r000231279.
an algorithm for generating non-redundant quantifier scopings. this paper describes an algorithm for generating quantifier scopings. the algorithm is designed to generate only logically non-redundant scopings and to partially order the scopings with a given default scoping first. removing logical redundancy is not only interesting per se, but also drastically reduces the processing time. the input and output formats are described through a few access and construction functions. thus, the algorithm is interesting for a modular linguistic theory, which is flexible with respect to syntactic and semantic framework.
representing a system of lexical types using default unification. default inheritance is a useful tool for encoding linguistic generalisations that have exceptions. in this paper we show how the use of an order independent typed default unification operation can provide non-redundant highly structured and concise representation to specify a network of lexical types, that encodes linguistic information about verbal subcategorisation. the system of lexical types is based on the one proposed by pollard and sag (1987), but uses the more expressive typed default feature structures, is more succinct, and able to express linguistic sub-regularities more elegantly.
a two-way approach to structural transfer in mt. the metal machine translation project incorporates two methods of structural transfer - direct transfer and transfer by grammar. in this paper i discuss the strengths and weaknesses of these two approaches in general and with respect to the metal project, and argue that, for many applications, a combination of the two is preferable to either alone.
computational aspects of m-grammars. in this paper m-grammars that are used in the rosetta translation system will be looked at as the specification of attribute grammars. we will show that the attribute evaluation order is such that instead of the special-purpose parsing and generation algorithms introduced for m-grammars in appelo et al.(1987), also earley-like context-free parsing and ordinary generation strategies can be used. furthermore, it is illustrated that the attribute grammar approach gives an insight into the weak generative capacity of m-grammars and into the computational complexity of the parsing and generation process. finally, the attribute grammar approach will be used to reformulate the concept of isomorphic grammars.
a syntax-based part-of-speech analyser. there are two main methodologies for constructing the knowledge base of a natural language analyser: the linguistic and the data-driven. recent state-of-the-art part-of-speech taggers are based on the data-driven approach. because of the known feasibility of the linguistic rule-based approach at related levels of description, the success of the data-driven approach in part-of-speech analysis may appear surprising. in this paper, a case is made for the syntactic nature of part-of-speech tagging. a new tagger of english that uses only linguistic distributional rules is outlined and empirically evaluated. tested against a benchmark corpus of 38,000 words of previously unseen text, this syntax-based system reaches an accuracy of above 99%. compared to the 95--97% accuracy of its best competitors, this result suggests the feasibility of the linguistic approach also in part-of-speech analysis.
using noisy bilingual data for statistical machine translation. smt systems rely on sufficient amount of parallel corpora to train the translation model. this paper investigates possibilities to use word-to-word and phrase-to-phrase translations extracted not only from clean parallel corpora but also from noisy comparable corpora. translation results for a chinese to english translation task are given.
a language for the statement of binary relations over feature structures. unification is often the appropriate method for expressing relations between representations in the form of feature structures; however, there are circumstances in which a different approach is desirable. a declarative formalism is presented which permits direct mappings of one feature structure into another, and illustrative examples are given of its application to areas of current interest.
an experiment on the upper bound of interjudge agreement: the case of tagging. we investigate the controversial issue about the upper bound of interjudge agreement in the use of a low-level grammatical representation. pessimistic views suggest that several percent of words in running text are undecidable in terms of part-of-speech categories. our experiments with 55kw data give reason for optimism: linguists with only 30 hours' training apply the engcg-2 morphological tags with almost 100% interjudge agreement.
a generative grammar approach for the morphologic and morphosyntactic analysis of italian. a morphologic and morphosyntactic analyzer for the italian language has been implemented in vm/prolog |3| at the ibm rome scientific center as part of a project on text understanding.aim of this project is the development of a prototype which analyzes short narrative texts (press agency news) and gives a formal representation of their "meaning" as a set of first order logic expressions. question answering features are also provided.the morphologic analyzer processes every word by means of a context free grammar, in order to obtain its morphologic and syntactic characteristics.it also performs a morphosyntactic analysis to recognize fixed and variable sequences of words such as idioms, date expressions, compound tenses of verbs and comparative and superlative forms of adjectives.the lexicon is stored in a relational data base under the control of sql/ds [2], while the endings of the grammar are stored in the workspace as prolog facts.a friendly interface written in gddm [1] allows the user to introduce on line the missing lemmata, in order to directly update the dictionary.
jpsg parser on constraint logic programming. this paper presents a constraint logic programming language cu-prolog and introduces a simple japanese parser based on japanese phrase structure grammar (jpsg) as a suitable application of cu-prolog.cu-prolog adopts constraint unification instead of the normal prolog unification. in cu-prolog, constraints in terms of user defined predicates can be directly added to the program clauses. such a clause is called constraint added horn clause (cahc). unlike conventional clp systems, cu-prolog deals with constraints about symbolic or combinatorial objects. for natural language processing, such constraints are more important than those on numerical or boolean objects. in comparison with normal prolog, cu-prolog has more descriptive power, and is more declarative. it enables a natural implementation of jpsg and other unification based grammar formalisms.
the semantics of motion. in this paper we present a semantic study of motion complexes (ie. of a motion verb followed by a spatial preposition). we focus on the spatial and the temporal intrinsic semantic properties of the motion verbs, on the one hand, and of the spatial prepositions, on the other hand. then we address the problem of combining these basic semantics in order to formally and automatically derive the spatiotemporal semantics of a motion complex from the spatiotemporal properties of its components.
ambiguity resolution in a reductionistic parser. we are concerned with dependency-oriented morphosyntactic parsing of running text. while a parsing grammar should avoid introducing structurally unresolvable distinctions in order to optimise on the accuracy of the parser, it also is beneficial for the grammarian to have as expressive a structural representation available as possible. in a reductionistic parsing system this policy may result in considerable ambiguity in the input; however, even massive ambiguity can be tackled efficiently with an accurate parsing description and effective parsing technology.
a cross language document retrieval system based on semantic annotation. the paper describes a cross-lingual document retrieval system in the medical domain that employs a controlled vocabulary (umls1) in constructing an xml-based intermediary representation into which queries as well as documents are mapped. the system assists in the retrieval of english and german medical scientific abstracts relevant to a german query document (electronic patient record). the modularity of the system allows for deployment in other domains, given appropriate linguistic and semantic resources.
specifying a shallow grammatical representation for parsing purposes. is it possible to specify a grammatical representation (descriptors and their application guidelines) to such a degree that it can be consistently applied by different grammarians e.g. for producing a benchmark corpus for parser evaluation? arguments for and against have been given, but very little empirical evidence. in this article we report on a double-blind experiment with a surface-oriented morphosyntactic grammatical representation used in a large-scale english parser. we argue that a consistently applicable representation for morphology and also shallow syntax can be specified. a grammatical representation with a near-100% coverage of running text can be specified with a reasonable effort, especially if the representation is based on structural distinctions (i.e. it is structurally resolvable).
structural non-correspondence in translation. kaplan et al (1989) present an approach to machine translation based on co-description. in this paper we show that the notation is not as natural and expressive as it appears. we first show that the most natural analysis proposed in kaplan et al (1989) cannot in fact cover the range of data for the important translational phenomenon in question. this contribution extends the work reported on in sadler et al (1989) and sadler et al (1990). we then go on to discuss alternatives which depart from or extend the formalism proposed in kaplan et al (1989) in various respects, pointing out some directions for further research. the strategies discussed have been implemented.
experiments on the choice of features for learning verb classes. the choice of verb features is crucial for the learning of verb classes. this paper presents clustering experiments on 168 german verbs, which explore the relevance of features on three levels of verb description, purely syntactic frame types, prepositional phrase information and selectional preferences. in contrast to previous approaches concentrating on the sparse data problem, we present evidence for a linguistically defined limit on the usefulness of features which is driven by the idiosyncratic properties of the verbs and the specific attributes of the desired verb classification.
robust generic and query-based summarization. we present a robust summarisation system developed within the gate architecture that makes use of robust components for semantic tagging and coreference resolution provided by gate. our system combines gate components with well established statistical techniques developed for the purpose of text summarisation research. the system supports "generic" and query-based summarisation addressing the need for user adaptation.
designing illustrated texts: how language production is influenced by graphics generation. multimodal interfaces combining, e.g., natural language and graphics take advantage of both the individual strength of each communication mode and the fact that several modes can be employed in parallel, e.g., in the text-picture combinations of illustrated documents. it is an important goal of this research not simply to merge the verbalization results of a natural language generator and the visualization results of a knowledge-based graphics generator, but to carefully coordinate graphics and text in such a way that they complement each other. we describe the architecture of the knowledge-based presentation system wip which guarantees a design process with a large degree of freedom that can be used to tailor the presentation to suit the specific context. in wip, decisions of the language generator may influence graphics generation and graphical constraints may sometimes force decisions in the language production process. in this paper, we focus on the influence of graphical constraints on text generation. in particular, we describe the generation of cross-modal references, the revision of text due to graphical constraints and the clarification of graphics through text.
classical logics for attribute-value languages. this paper describes a classical logic for attribute-value (or feature description) languages which are used in unification grammar to describe a certain kind of linguistic object commonly called attribute-value structure (or feature structure). the algorithm which is used for deciding satisfiability of a feature description is based on a restricted deductive closure construction for sets of literals (atomic formulas and negated atomic formulas). in contrast to the kasper/rounds approach (cf. [kasper/rounds 90]), we can handle cyclicity, without the need for the introduction of complexity norms, as in [johnson 88] and [beierle/pletat 88]. the deductive closure construction is the direct proof-theoretic correlate of the congruence closure algorithm (cf. [nelson/oppen 80]), if it were used in attribute-value languages for testing satisfiability of finite sets of literals.
it would be much easier if went were goed. the paper proposes a paradigmatic approach to morphological knowledge acquisition. it addresses the problem of learning from examples rules for word-forms analysis and synthesis. these rules, established by generalizing the training data sets, are effectively used by a built-in interpreter which acts consequently as a morphological processor within the architecture of a natural language question-answering system. the paradigm system has no a prior knowledge which should restrict it to a particular natural language, but instead builds up the morphological rules based only on the examples provided, be they in romanian, english, french, russian, slovak and the like.
programming in logic with constraints for natural language processing. in this paper, we present a logic-based computational model for movement theory in government and binding theory. for that purpose, we have designed a language called dislog. dislog stands for programming in logic with discontinuities and permits to express in a simple, concise and declarative way relations or constraints between non-contiguous elements in a structure. dislog is also weel adapted to model other types of linguistic phenomena like quantifier raising involving long-distance relations or constraints.
processing language with logical types and active constraints. in this document, we present a language which associates type construction principles to constraint logic programming. we show that it is very appropriate for language processing, providing more uniform, expressive and efficient tools and treatments. we introduce three kinds of constraints, that we exemplify by motivational examples. finally, we give the procedural semantics of our language, combining type construction with sld-resolution.
some remarks on the decidability of the generation problem in lfg- and patr-style unification grammars. in this paper, we prove the decidability of the generation problem for those unification grammars which are based on context-free phrase structure rule skeletons, like e.g. lfg and patr-ii. the result shows a perhaps unexpected asymmetry, since it is valid also for those unification grammars whose parsing problem is undecidable, e.g. grammars which do not satisfy the off-line parsability constraint. the general proof is achieved by showing that the space of the derivations which have to be considered in order to decide the problem for a given input is always restricted to derivations whose length is limited by some fixed upper bound which is determined relative to the "size" of the input.
on the representation of query term relations by soft boolean operators. the language analysis component in most text retrieval systems is confined to a recognition of noun phrases of the type normally included in back-of-the-book indexes, and an identification of related terms included in a preconstructed thesaurus of quasi-synonyms. even such a restricted language analysis is fraught with difficulties because of the well-known problems in the analysis of compound nominals, and the hazards and cost of constructing word synonym classes valid for large text samples.in this study an extended (soft) boolean logic is used for the formulation of information retrieval queries which is capable of representing both the use of compound noun phrases as well as the inclusion of synonym constructions in the query statements. the operations of the extended boolean logic are described, and evaluation output is included to demonstrate the effectiveness of the extended logic compared with that of ordinary text retrieval systems.
type-driven semantic interpretation of f-structures. the formal architecture of lexical functional grammar offers a particular formal device, the structural correspondence, for modularizing the mapping between the surface forms of a language and representations of their underlying meanings. this approach works well when the structural discrepancies between form and meaning representations are finitely bounded, but there are some phenomena in natural language, e.g. adverbs in english, where this restriction does not hold. in this paper, we describe rule-based type-driven interpretation algorithms which cover cases of such a structural misalignment by exploiting a new descriptive device, the "restriction operator". the algorithms are set up in such a way that recursive rules can be derived for the interpretation of adjunct sets within a codescription approach (see [kaplan and wedekind, 1993] for details).
fallible rationalism and machine translation. approaches to mt have been heavily influenced by changing trends in the philosophy of language and mind. because of the artificial hiatus which followed the publication of the alpac report, mt research in the 1970s and early 1980s has had to catch up with major developments that have occurred in linguistic and philosophical thinking; currently, mt seems to be uncritically loyal to a paradigm of thought about language which is rapidly losing most of its adherents in departments of linguistics and philosophy. i argue, both in theoretical terms and by reference to empirical research on a particular translation problem, that the popperian "fallible rationalist" view of mental processes which is winning acceptance as a more sophisticated alternative to chomskyan "deterministic rationalism" should lead mt researchers to redefine their goals and to adopt certain currently-neglected techniques in trying to achieve those goals.
design and implementation of a lexical data base. this paper is concerned with the specifications and the implementation of a particular concept of word-based lexicon to be used for large natural language processing systems such as machine translation systems, and compares it with the morpheme-based conception of the lexicon traditionally assumed in computational linguistics.it will be argued that, although less concise, a relational word-based lexicon is superior to a morpheme-based lexicon from a theoretical, computational and also practical viewpoint.
representing text chunks. dividing sentences in chunks of words is a useful preprocessing step for parsing, information extraction and information retrieval. (ramshaw and marcus, 1995) have introduced a "convenient" data representation for chunking by converting it to a tagging task. in this paper we will examine seven different data representations for the problem of recognizing noun phrase chunks. we will show that the the data representation choice has a minor influence on chunking performance. however, equipped with the most suitable data representation, our memory-based learning chunker was able to improve the best published chunking results for a standard data set.
lexicalising word order constraints for implemented linearisation grammar. this paper presents a way in which a lexicalised hpsg grammar can handle word order constraints in a computational parsing system, without invoking an additional layer of representation for word order, such as reape's word order domain. the key proposal is to incorporate into lexical heads the woc (word order constraints) feature, which is used to constrain the word order of its projection. we also overview our parsing algorithm.
what sort of trees do we speak? a computational model of the syntax-prosody interface in tokyo japanese. what is the relationship between syntax, prosody and phonetics? this paper argues for a declarative constraint-based theory, in which each step in a derivation adds diverse constraints to a pool. some of these describe well formed objects in the feature structure domain, in terms of both syntactic and prosodic features. some characterise the relative prominence of constituents as a partial order over some discrete domain (playing the role of metrical grid). some are simultaneous equations in the reals, whose solutions represent the pitch level of phonetic objects --- high and low tones. the elements of such a theory are illustrated with a treatment of prosodic phrasing and tone scaling in tokyo japanese, and the theory is compared to selkirk and tateishi's analysis based on the strict layer hypothesis.
parsing the wall street journal with the inside-outside algorithm. we report grammar inference experiments on partially parsed sentences taken from the wall street journal corpus using the inside-outside algorithm for stochastic context-free grammars. the initial grammar for the inference process makes no assumption of the kinds of structures and their distributions. the inferred grammar is evaluated by its predicting power and by comparing the bracketing of held out sentences imposed by the inferred grammar with the partial bracketings of these sentences given in the corpus. using part-of-speech tags as the only source of lexical information, high bracketing accuracy is achieved even with a small subset of the available training material (1045 sentences): 94.4% for test sentences shorter than 10 words and 90.2% for sentences shorter than 15 words.
bayesian network, a model for nlp? the nlp systems often have low performances because they rely on unreliable and heterogeneous knowledge. we show on the task of non-anaphoric it identification how to overcome these handicaps with the bayesian network (bn) formalism. the first results are very encouraging compared with the state-of-the-art systems.
rule-based lexical modelling of foreign-accented pronunciation variants. this paper describes a novel approach to generate potential foreign-accented phonetic transcriptions using phonological rewrite rules. for each pair of a native language (l1) and a target language (l2), a set of postlexical rules is designed to transform canonical phonetic dictionaries of l2 into adapted dictionaries for native l1 speakers. some general considerations on the design of such a rule-based system are presented.
delimitedness and trajectory-of-motion events. the first part of the paper develops a novel, sortally-based approach to the problem of aspectual composition. the account is argued to be superior on both empirical and computational grounds to previous semantic approaches relying on referential homogeneity tests. while the account is restricted to manner-of-motion verbs, it does cover their interaction with mass terms, amount phrases, locative pps, and distance, frequency, and temporal modifiers. the second part of the paper describes an implemented system based on the theoretical treatment which determines whether a specified sequence of events is or is not possible under varying situationally supplied contraints, given certain restrictive and simplifying assumptions. briefly, the system extracts a set of contraint equations from the derived logical forms and solves them according to a best-value metric. three particular limitations of the system and possible ways of addressing them are discussed in the conclusion.
a cascaded finite-state parser for german. the paper presents two approaches to partial parsing of german: a tagger trained on dependency tuples, and a cascaded finite-state parser (abney, 1997). for the tagging approach, the effects of choosing different representations of dependency tuples are investigated. performance of the finite-state parser is boosted by delaying syntactically unsolvable disambiguation problems via underspecification. both approaches are evaluated on a 340,000-token corpus.
user studies and the design of natural language systems. this paper presents a critical discussion of the various approaches that have been used in the evaluation of natural language systems. we conclude that previous approaches have neglected to evaluate systems in the context of their use, e.g. solving a task requiring data retrieval. this raises questions about the validity of such approaches. in the second half of the paper, we report a laboratory study using the wizard of oz technique to identify nl requirements for carrying out this task. we evaluate the demands that task dialogues collected using this technique, place upon a prototype natural language system. we identify three important requirements which arose from the task that we gave our subjects: operators specific to the task of database access, complex contextual reference and reference to the structure of the information source. we discuss how these might be satisfied by future natural language systems.
right attachment and preference semantics. the paper claims that the right attachment rules for phrases originally suggested by frazier and fodor are wrong, and that none of the subsequent patchings of the rules by syntactic methods have improved the situation. for each rule there are perfectly straightforward and indefinitely large classes of simple counter-examples. we then examine suggestions by ford et al., schubert and hirst which are quasi-semantic in nature and which we consider ingenious but unsatisfactory. we point towards a straightforward solution within the framework of preference semantics, set out in detail elsewhere, and argue that the principal issue is not the type and nature of information required to get appropriate phrase attachments, but the issue of where to store the information and with what processes to apply it.
distributional part-of-speech tagging. this paper presents an algorithm for tagging words whose part-of-speech properties are unknown. unlike previous work, the algorithm categorizes word tokens in context instead of word types. the algorithm is evaluated on the brown corpus.
a comparison of rule-invocation strategies in context-free chart parsing. currently several grammatical formalisms converge towards being declarative and towards utilizing context-free phrase-structure grammar as a back-bone, e.g. lfg and patr-ii. typically the processing of these formalisms is organized within a chart-parsing framework. the declarative character of the formalisms makes it important to decide upon an overall optimal control strategy on the part of the processor. in particular, this brings the rule-invocation strategy into critical focus: to gain maximal processing efficiency, one has to determine the best way of putting the rules to use. the aim of this paper is to provide a survey and a practical comparison of fundamental rule-invocation strategies within context-free chart parsing.
natural and simulated pointing. referent identification in human conversation is performed both by describing the objects in question and by pointing at them. up till now, only the linguistic component could be simulated in dialog systems. but recently, technical innovations have made it possible to 'point' at the objects on a display as well.the paper has two intentions. first, it investigates natural pointing in more detail and offers some possibilities to classify the great variety of pointing actions. then, it tries to clarify the extent to which pointing by technical means (especially mouse-clicks) can be regarded as a simulation of natural pointing or as a functional equivalent. furthermore, some steps towards even more accurate simulation are briefly mentioned.
interactive incremental chart parsing. this paper presents an algorithm for incremental chart parsing, outlines how this could be embedded in an interactive parsing system, and discusses why this might be useful. incremental parsing here means that input is analysed in a piecemeal fashion, in particular allowing arbitrary changes of previous input without exhaustive reanalysis, interactive parsing means that the analysis process is prompted immediately at the onset of new input, and possibly that the system then may interact with the user in order to resolve problems that occur. the combination of these techniques could be used as a parsing kernel for highly interactive and "reactive" natural language processors, such as parsers for dialogue systems, interactive computer-aided translation systems, and language-sensitive text editors. an incremental chart parser embodying the ideas put forward in this paper has been implemented, and an embedding of this in an interactive parsing system is near completion.
a comparison of event models for naive bayes anti-spam e-mail filtering. we describe experiments with a naive bayes text classifier in the context of anti-spam e-mail filtering, using two different statistical event models: a multi-variate bernoulli model and a multinomial model. we introduce a family of feature ranking functions for feature selection in the multinomial event model that take account of the word frequency information. we present evaluation results on two publicly available corpora of legitimate and spam e-mails. we find that the multinomial model is less biased towards one class and achieves slightly higher accuracy than the multi-variate bernoulli model.
automatic processing of proper names in texts. this paper shows first the problems raised by proper names in natural language processing. second, it introduces the knowledge representation structure we use based on conceptual graphs. then it explains the techniques which are used to process known and unknown proper names. at last, it gives the performance of the system and the further works we intend to deal with.
an expert system for the production of phoneme strings from unmarked english text using machine-induced rules. the speech synthesis group at the computer-based education research laboratory (cerl) of the university of illinois at urbana-champaign is developing a diphone speech synthesis system based on pitch-adaptive short-time fourier transforms. this system accepts the phonemic specification of an utterance along with pitch, time, and amplitude warping functions in order to produce high quality speech output from stored diphone templates.this paper describes the operation of a program which operates as a front end for the diphone speech synthesis system. the utter (for "unmarked text transcription by expert rule") system maps english text onto a phoneme string, which is then used as an input to the diphone speech synthesis system. the program is a two-tiered expert system which operates first on the word level and then on the (vowel or consonant) cluster level. the system's knowledge about pronunciation is organized in two decision trees automatically generated by an induction algorithm on a dynamically specified "training set" of examples.
exploring the use of linguistic features in domain and genre classification. the central questions are: how useful is information about part-of-speech frequency for text categorisation? is it feasible to limit word features to content words for text classifications? this is examined for 5 domain and 4 genre classification tasks using limas, the german equivalent of the brown corpus. because limas is too heterogeneous, neither question can be answered reliably for any of the tasks. however, the results suggest that both questions have to be examined separately for each task at hand, because in some cases, the additional information can indeed improve performance.
dictionary organization for machine translation: the experience and implications of the umist japanese project. the organization of a dictionary system raises significant questions for all natural language processing applications. we concentrate here on three with specific reference to machine translation: the optimum grain-size for lexical entries, the division of information about separate languages, and the level of abstraction appropriate to the task of translation. these are discussed, and the solutions implemented in the umist english-japanese translation project are described and illustrated in detail.
machine translation, linguistics, and interlingua. an adequate, complete, and economical linguistic theory is necessary for mt and the question is whether a consistent use of the often unduly neglected dependency syntax, including a systematic description of topic and focus, cannot serve as a reliable base for the grammar of an interlingua, or of a set of interrelated interface structures.
the corpora management system based on java and oracle technologies. the paper discusses the corpora management system (cms) design that uses java and oracle9i dbms to support strategic corpora analysis. we present the pilot web-based cms to support linguists in their daily work. the system offers facilities to assist linguists and internet users as they search for relevant material, and then classify and annotate this material.
iterative operations. we present in this article, as a part of aspectual operation system, a generation system of iterative expressions using a set of operators called iterative operators. in order to execute the iterative operations efficiently, we have classified previously propositions denoting a single occurrence of a single event into three groupes. the definition of a single event is given recursively. the classification has been carried out especially in consideration of the durative / non-durative character of the denoted events and also in consideration of existence / non-existence of a culmination point ( or a boundary) in the events. the operations concerned with iteration have either the effect of giving a boundary to an event (in the case of a non-bounded event) or of extending an event through repetitions. the operators concerned are: n, f. direct iterative operators; i, g. boundary giving operators; i .. extending operator. there are direct and indirect operations: the direct ones change a non-repetitious proposition into a repetitious one directly, whereas the indirect ones change it indirectly. the indirect iteration is indicated with &sigma;. the scope of each operator is not uniquely definable, though the mutual relation of the operators can be given more or less explicitly.
qualifier: question answering by lexical fabric and external resources. one of the major challenges in trec-style question-answering (qa) is to overcome the mismatch in the lexical representations in the query space and document space. this is particularly severe in qa as exact answers, rather than documents, are required in response to questions. most current approaches overcome the mismatch problem by employing either data redundancy strategy through the use of web or linguistic resources. this paper investigates the integration of lexical relations and web knowledge to tackle this problem. the results obtained on trec11 qa corpus indicate that our approach is both feasible and effective.
detection of japanese homophone errors by a decision list including a written word as a default evidence. in this paper, we propose a practical method to detect japanese homophone errors in japanese texts. it is very important to detect homophone errors in japanese revision systems because japanese texts suffer from homophone errors frequently. in order to detect homophone errors, we have only to solve the homophone problem. we can use the decision list to do it because the homophone problem is equivalent to the word sense disambiguation problem. however, the homophone problem is different from the word sense disambiguation problem because the former can use the written word but the latter cannot. in this paper, we incorporate the written word into the original decision list by obtaining the identifying strength of the written word. the improved decision list can raise the f-measure of error detection.
a tradeoff between compositionality and complexity in the semantics of dimensional adjectives. linguistic access to uncertain quantitative knowledge about physical properties is provided by dimensional adjectives, e.g. long-short in the spatial and temporal senses, near-far, fast-slow, etc. semantic analyses of the dimensional adjectives differ on whether the meaning of the differential comparative (6 cm shorter than) and the equative with factor term (three times as long as) is a compositional function of the meanings the difference and factor terms (6 cm and three times) and the meanings of the simple comparative and equative, respectively. the compositional treatment comes at the price of a meaning representation that some authors ([pinkal, 1990], [klein, 1991]) find objectionally unparsimonious. in this paper, i compare semantic approaches by investigating the complexity of reasoning that they entail; specifically, i show the complexity of constraint propagation over real-valued intervals using the waltz algorithm in a system where the meaning representations of sentences appear as constraints (cf. [davis, 1987]). it turns out that the compositional account is more complex on this measure. however, i argue that we face a tradeoff rather than a knock-down argument against compositionality, since the increased complexity of the compositional approach may be manageable if certain assumptions about the application domain can be made.
focusing on scenario recognition in infomation extraction. this paper reports a research effort in information extraction, especially in template pattern matching. our approach uses reach domain knowledge in the football (soccer) area and logical form representation for necessary inferences of facts and templates filling. our system fret1 (football reports extraction templates) is compatible to the language-engineering environment gate and handles its internal representations and some intermediate analysis results.
development of corpora within the clark system: the bultreebank project experience. clark is an xml-based software system for corpora development. it incorporates several technologies: xml technology; unicode; regular cascaded grammars; constraints over xml documents. the basic components of the system are: a tagger, a concordancer, an extractor, a grammar processor, a constraint engine.
an evaluation of metal: the lrc machine translation system. the linguistics research center (lrc) at the university of texas at austin is currently developing metal, a fully-automatic high quality machine translation system, for market introduction in 1985. this paper will describe the current status of metal, emphasizing the results of the most recent post-editors' evaluation, and will briefly indicate some future directions for the system. a 6-page german original text and a raw (unedited, but automatically reformatted) metal translation of that text into english are included as appendices.
describing syntax with star-free regular expressions. syntactic constraints in koskenniemi's finite-state intersection grammar (fsig) are logically less complex than their formalism (koskenniemi et al., 1992) would suggest: it turns out that although the constraints in voutilainen's (1994) fsig description of english make use of several extensions to regular expressions, the description as a whole reduces to a finite combination of union, complement and concatenation. this is an essential improvement to the descriptive complexity of engfsig. the result opens a door for further analysis of logical properties and possible optimizations in the fsig descriptions. the proof contains a new formula for compiling koskenniemi's restriction operation without any marker symbols.
summarizing neonatal time series data. we describe our investigations in generating textual summaries of physiological time series data to aid medical personnel in monitoring babies in neonatal intensive care units. our studies suggest that summarization is a communicative task that requires data analysis techniques for determining the content of the summary. we describe a prototype system that summarizes physiological time series.
a unified management and processing of word-forms, idioms and analytical compounds. the paper presents a morpho-lexical environment, designed for the management of root-oriented natural language dictionaries. it also encapsulates the basic morpho-lexical processings: analysis and synthesis of individual word-forms or compounds (idioms and analytic constructions).
automatic authorship attribution. in this paper we present an approach to automatic authorship attribution dealing with real-world (or unrestricted) text. our method is based on the computational analysis of the input text using a text-processing tool. besides the style markes relevant to the output of this tool we also use analysis-dependent style markers, that is, measures that represent the way in which the text has been processed. no word frequency counts, nor other lexically-based measures are taken into account. we show that the proposed set of style markers is able to distinguish texts of various authors of a weekly newspaper using multiple regression. all the experiments we present were performed using real-world text downloaded from the world wide web. our approach is easily trainable and fully-automated requiring no manual text preprocessing nor sampling.
new frontiers beyond context-freeness: di-grammars and di-automata. a new class of formal languages will be defined - the distributed index languages (di-languages). the grammar-formalism generating the new class - the di-grammars - cover unbound dependencies in a rather natural way. the place of di-languages in the chomsky-hierarchy will be determined: like aho's indexed languages, di-languages represent a proper subclass of type 1 (contextsensitive languages) and properly include type 2 (context-free languages), but the di-class is neither a subclass nor a superclass of aho's indexed class. it will be shown that, apart from di-grammars, di-languages can equivalently be characterized by a special type of automata - di-automata. finally, the time complexity of the recognition-problem for an interesting subclass of di-grammars will approximately be determined.
string-tree correspondence grammar: a declarative grammar formalism for defining the correspondence between strings of terms and tree structures. the paper introduces a grammar formalism for defining the set of sentences in a language, a set of labeled trees (not the derivation trees of the grammar) for the representation of the interpretation of the sentences, and the (possibly non-projective) correspondence between subtrees of each tree and substrings of the related sentence. the grammar formalism is motivated by the linguistic approach (adopted at geta) where a multilevel interpretative structure is associated to a sentence. the topology of the multilevel structure is 'meaning' motivated, and hence its substructures may not correspond projectively to the substrings of the related sentence.
a state-transition grammar for data-oriented parsing. this paper presents a grammar formalism designed for use in data-oriented approaches to language processing. it goes on to investigate ways in which a corpus pre-parsed with this formalism may be processed to provide a probabilistic language model for use in the parsing of fresh texts.
towards reusable linquistic resources. 1. the paper will try to identify the various concurrent factors which, in the last years, have contributed to the increasing attention paid to the issue of reusable linguistic resources for natural language processing. the role of various major organisations (eec, council of europe, darpa, neh, etc.) will be examined, taking into account the reasons which seem to have stimulated their active participation. the recognition of the need of reusable linguistic resources by various sectors of "automated linguistic data processing" will also be considered as a catalyzer for the recent trend towards the cooperation of various scientific and professional associations (acl, allc, ach, etc.).2. various interpretations of the term "reusability" have been proposed. we shall consider the relationships and differences between:- the feasibility of the utilization of existing repositories of linguistic information, as potential sources for the construction of nlp components;- the feasibility of constructing new large linguistic knowledge bases, explicitly designed for multifunctional uses, in various research frameworks and development activities.in particular, we shall examine the connections between various core aspects of the construction of reusable linguistic resources, and- the general problems of the "evaluation" in the field of natural language processing, both at the general level of shareability of the state-of-the-art knowledge, and at the level of specific nlp systems or linguistic data collection;- the design of "standards" at the level of representation formalisms and of the identification of linguistic units and description categories.3. examples will be taken by some of the various international projects nowadays underway in the field of lexica (et7, acquilex, multilex, genelex, the lexical consortium, etc.), corpora (european network of textual corpora, british national corpus, data collection initiative, etc.), and standards (text encoding initiative).4. the paper will review and compare some of the results already acquired, and will state some problems, both at the scientific and organizational level which, in the opinion of the author, are still to be solved, and represent major controversial issues. it is expected that the round table, which will be held during the conference with the participation of the representatives of some of those projects, will discuss these problems and indicate priorities for research, practicable ways towards their solution, and possible convergence of efforts.
relating syntax and semantics: the syntactico-semantic lexicon of the system vie-lang. this paper describes the structure and evaluation of the syntactico-semantic lexicon (ssl) of the german natural language understanding system vie-lang [3]. vie-lang uses an si-net [2] as internal representation. the ssl contains the rules according to which the mapping between net-structures and surface structures of a sentence is carried out. this information is structured in a way that it can be evaluated from two sides. the parser interprets it as production-rules that control the analysis. syntactic and semantic features of the input sentence are evaluated and individuals are created in the semantic net. the generator uses the same rules to express selected net-structures in adequate natural language expressions. it is shown how both processes can make effective use of the ssl. the different possibilities for evaluating the ssl are explained and illustrated by examples.
a corpus-based approach to deriving lexical mappings. this paper proposes a novel, corpusbased, method for producing mappings between lexical resources. results from a preliminary experiment using part of speech tags suggests this is a promising area for future research.
developments in affect detection in e-drama. we report work in progress on adding affect-detection to an existing program for virtual dramatic improvisation, monitored by a human director. to partially automate the directors' functions, we have partially implemented the detection of emotions, etc. in users' text input, by means of pattern-matching, robust parsing and some semantic analysis. the work also involves basic research into how affect is conveyed by metaphor.
automatic verb classification using distributions of grammatical features. we apply machine learning techniques to classify automatically a set of verbs into lexical semantic classes, based on distributional approximations of diatheses, extracted from a very large annotated corpus. distributions of four grammatical features are sufficient to reduce error rate by 50% over chance. we conclude that corpus data is a usable repository of verb class information, and that corpus-driven extraction of grammatical features is a promising methodology for automatic lexical acquisition.
question answering using web news as knowledge base. answerbus news engine1 is a question answering system using the contents of cnn web site2 as its knowledge base. comparing to other question answering systems including its previous versions, it has a totally independent crawling and indexing system and a fully functioning search engine. because of its dynamic and continuous indexing, it is possible to answer questions on just-happened facts. again, it reaches high correct answer rate. in this demonstration we will present the living system as well as its new technical features.
distributives, quantifiers and a multiplicity of events. with the intention of indicating some temporal/event-theoretic characteristics of distributive clauses, a generalisation is made over distributives and clauses marked for iterative aspect: two kinds of semantic phenomena which have normally been confined to separate theoretical domains. it is shown that in particular, both give rise to an 'inferential set construction' problem. an informal outline is given of what might constitute such a generalisation. the generalisation is proposed intially on grounds of prima facie plausibility, but its ultimate defensibility and explanatory value will depend on the validity of its consequence, that distributive clauses entail a multiplicity of temporal entities or events. this proposal is considered with respect to two types of discourse phenomena; anaphoric reference to event entities, and temporal binding. these provide further support for making the generalisation, clarify its nature and indicate in what respect the entailment claim can be true of distributives. the set construction problem is of practical importance for computational models of natural language interaction, and since the concept of iterated action is central to planning, the generalisation across iteration and distributives, along with the observations about their nature, have interesting implications for work in this area.
theoretical evaluation of estimation methods for data-oriented parsing. we analyze estimation methods for data-oriented parsing, as well as the theoretical criteria used to evaluate them. we show that all current estimation methods are inconsistent in the "weight-distribution test", and argue that these results force us to rethink both the methods proposed and the criteria used.
coping with dynamic syntactic strategies: an experimental environment for an experimental parser. an environment built around wednesday 2, a chart based parser is introduced. the environment is in particular oriented towards exploring dynamic aspects of parsing. it includes a number of specialized tools that consent an easy, graphics-based interaction with the parser. it is shown in particular how a combination of the characteristics of the parser(based on the lexicon and on dynamic unification) and of the environment allow a nonspecialized user to explore heuristics that may alter the basica control of the system. in this way, for instance, a psycholinguist may explore ideas on human parsing strategies, or a "language engineer" may find useful heuristics for parsing within a particular application.
learning-based named entity recognition for morphologically-rich, resource-scarce languages. named entity recognition for morphologically rich, case-insensitive languages, including the majority of semitic languages, iranian languages, and indian languages, is inherently more difficult than its english counterpart. worse still, progress on machine learning approaches to named entity recognition for many of these languages is currently hampered by the scarcity of annotated data and the lack of an accurate part-of-speech tagger. while it is possible to rely on manually-constructed gazetteers to combat data scarcity, this gazetteer-centric approach has the potential weakness of creating irreproducible results, since these name lists are not publicly available in general. motivated in part by this concern, we present a learning-based named entity recognizer that does not rely on manually-constructed gazetteers, using bengali as our representative resource-scarce, morphologically-rich language. our recognizer achieves a relative improvement of 7.5% in f-measure over a baseline recognizer. improvements arise from (1) using induced affixes, (2) extracting information from online lexical databases, and (3) jointly modeling part-of-speech tagging and named entity recognition.
wednesday: parsing flexible word order languages. a parser for "flexible" word order languages must be substantially data driven. in our view syntax has two distinct roles in this connection: (1) to give impulses for assembling cognitive representations, (ii) to structure the space of search for fillers. wednesday is an interpreter for a language describing the lexicon and operating on natural language sentences. the system operates from left to right, interpreting the various words comprising the sentence one at a time. the basic ideas of the approach are the following:a) to introduce into the lexicon linguistic knowledge that in other systems is in a centralized module. the lexicon therefore carries not only morphological data and semantic descriptions. also syntactic knowledge is distributed throughout it, partly of a procedural kind.b) to build progressively a cognitive representation of the sentence in the form of a semantic network, in a global space, accessible from all levels of the analysis.c) to introduce procedures invoked by the words themselves for syntactic memory management. simply stated, these procedures decide on the opening, closing, and mantaining of search spaces; they use detailed constraints and take into account the active expectations.wednesday is implemented in magma-lisp and with a stress on the non-deterministic mechanism.
rich bitext projection features for parse reranking. many different types of features have been shown to improve accuracy in parse reranking. a class of features that thus far has not been considered is based on a projection of the syntactic structure of a translation of the text to be parsed. the intuition for using this type of bitext projection feature is that ambiguous structures in one language often correspond to unambiguous structures in another. we show that reranking based on bitext projection features increases parsing accuracy significantly.
parsetalk about sentence- and text-level anaphora. we provide a unified account of sentence-level and text-level anaphora within the framework of a dependency-based grammar model. criteria for anaphora resolution within sentence boundaries rephrase major concepts from gb's binding theory, while those for text-level anaphora incorporate an adapted version of a grosz-sidner-style focus model.
text summarization model based on maximum coverage problem and its variant. we discuss text summarization in terms of maximum coverage problem and its variant. we explore some decoding algorithms including the ones never used in this summarization formulation, such as a greedy algorithm with performance guarantee, a randomized algorithm, and a branch-and-bound method. on the basis of the results of comparative experiments, we also augment the summarization model so that it takes into account the relevance to the document cluster. through experiments, we showed that the augmented model is superior to the best-performing method of duc'04 on rouge-1 without stopwords.
incorporating "unconscious reanalyses" into an incremental, monotonic parser. this paper describes the author's implementation of a parser aimed at reproducing, in a computationally explicit system, the constraints of a particular psycholinguistic model (gorrell in press). in gorrell's model, "unconscious" garden paths may be processed via the addition of structural relations to a monotone increasing set at the point of disambiguation, but there is no discussion as to how the parser decides which relations to add. we model this decision as a search for a node in the tree at which an explicitly defined parsing operation, tree-lowering may be applied. with reference to english and japanese processing data, we show the importance of this search for empirical adequacy of the psycholinguistic model.
generating spatio-temporal descriptions in pollen forecasts. we describe our initial investigations into generating textual summaries of spatiotemporal data with the help of a prototype natural language generation (nlg) system that produces pollen forecasts for scotland.
a corpus-centered approach to spoken language translation. this paper reports the latest performance of components and features of a project named corpus-centered computation (c3), which targets a translation technology suitable for spoken language translation. c3 places corpora at the center of the technology. translation knowledge is extracted from corpora by both ebmt and smt methods, translation quality is gauged by referring to corpora, the best translation among multiple-engine outputs is selected based on corpora and the corpora themselves are paraphrased or filtered by automated processes.
sequential labeling with latent variables: an exact inference algorithm and its efficient approximation. latent conditional models have become popular recently in both natural language processing and vision processing communities. however, establishing an effective and efficient inference method on latent conditional models remains a question. in this paper, we describe the latent-dynamic inference (ldi), which is able to produce the optimal label sequence on latent conditional models by using efficient search strategy and dynamic programming. furthermore, we describe a straightforward solution on approximating the ldi, and show that the approximated ldi performs as well as the exact ldi, while the speed is much faster. our experiments demonstrate that the proposed inference algorithm outperforms existing inference methods on a variety of natural language processing tasks.
an english generator for a case-labelled dependency representation. the paper describes a program which has been constructed to produce english strings from a case-labelled dependency representation. the program uses an especially simple and uniform control structure with a well defined separation of the different knowledge sources used during generation. furthermore, the majority of the system's knowledge is expressed in a declarative form, so in principle the generator's knowledge bases could be used for purposes other than generation. the generator uses a two-pass control structure, the first translating from the semantically orientated case-labelled dependency structures into surface syntactic trees and the second translating from these trees into english strings.the generator is very flexible: it can be run in such a way as to produce all the possible syntactically legitimate variations on a given utterance, and has built in facilities to do some synonym substitution. it has been used in a number of application domains: notably as a part of a free text retrieval system and as part of a natural language front end to a relational database system.
rule filtering by pattern for efficient hierarchical translation. we describe refinements to hierarchical translation search procedures intended to reduce both search errors and memory usage through modifications to hypothesis expansion in cube pruning and reductions in the size of the rule sets used in translation. rules are put into syntactic classes based on the number of non-terminals and the pattern, and various filtering strategies are then applied to assess the impact on translation speed and quality. results are reported on the 2008 nist arabic-to-english evaluation task.
learning to interpret utterances using dialogue history. we describe a methodology for learning a disambiguation model for deep pragmatic interpretations in the context of situated task-oriented dialogue. the system accumulates training examples for ambiguity resolution by tracking the fates of alternative interpretations across dialogue, including subsequent clarificatory episodes initiated by the system itself. we illustrate with a case study building maximum entropy models over abductive interpretations in a referential communication task. the resulting model correctly resolves 81% of ambiguities left unresolved by an initial handcrafted baseline. a key innovation is that our method draws exclusively on a system's own skills and experience and requires no human annotation.
weakly supervised approaches for ontology population. we present a weakly supervised approach to automatic ontology population from text and compare it with two other unsupervised approaches. in our experiments we populate a part of our ontology of named entities. we considered two high level categories-geographical locations and person names and ten sub-classes for each category. for each sub-class we automatically learn a syntactic model from a list of training examples and a parsed corpus. a novel syntactic indexing method allowed us to use large quantities of syntactically annotated data. the syntactic model for each named entity sub-class is a set of weighted syntactic features, i.e. words which typically co-occur with the members of the class in the corpus. the method is weakly supervised, since no manually annotated corpus is used in the learning process. the syntactic models are used to classify the unknown named entities in the test set. the method achieved promising results, i.e. 65% accuracy, and outperforms significantly the other two approaches.
translation and extension of concepts across languages. we present a method which, given a few words defining a concept in some language, retrieves, disambiguates and extends corresponding terms that define a similar concept in another specified language. this can be very useful for cross-lingual information retrieval and the preparation of multi-lingual lexical resources. we automatically obtain term translations from multilingual dictionaries and disambiguate them using web counts. we then retrieve web snippets with co-occurring translations, and discover additional concept terms from these snippets. our term discovery is based on co-appearance of similar words in symmetric patterns. we evaluate our method on a set of language pairs involving 45 languages, including combinations of very dissimilar ones such as russian, chinese, and hebrew for various concepts. we assess the quality of the retrieved sets using both human judgments and automatically comparing the obtained categories to corresponding english wordnet synsets.
natural language generation as planning under uncertainty for spoken dialogue systems. we present and evaluate a new model for natural language generation (nlg) in spoken dialogue systems, based on statistical planning, given noisy feedback from the current generation context (e.g. a user and a surface realiser). we study its use in a standard nlg problem: how to present information (in this case a set of search results) to users, given the complex tradeoffs between utterance length, amount of information conveyed, and cognitive load. we set these trade-offs by analysing existing match data. we then train a nlg policy using reinforcement learning (rl), which adapts its behaviour to noisy feedback from the current generation context. this policy is compared to several baselines derived from previous work in this area. the learned policy significantly outperforms all the prior approaches.
the syntactic regularity of english noun phrases. approximately, 10,000 naturally occurring noun phrases taken from the lob corpus were used firstly, to evaluate the np component of the alvey anlt grammar (grover et al., 1987, 1989) and secondly, to retest sampson's (1987a) claim that this data provide evidence for the lack of a clear-cut distinction between grammatical and 'deviant' examples. the examples were sorted and classified on the basis of the lexical and syntactic analysis undertaken as part of the lob corpus project (sampson, 1987b). tokens of each resulting type were parsed using the anlt grammar and the results analysed to determine the success rate of the parses and the generality of the rules employed.
lexical morphology in machine translation: a feasibility study. this paper presents a feasibility study for implementing lexical morphology principles in a machine translation system in order to solve unknown words. multilingual symbolic treatment of word-formation is seducing but requires an in-depth analysis of every step that has to be performed. the construction of a prototype is firstly presented, highlighting the methodological issues of such approach. secondly, an evaluation is performed on a large set of data, showing the benefits and the limits of such approach.
feature-based method for document alignment in comparable news corpora. in this paper, we present a feature-based method to align documents with similar content across two sets of bilingual comparable corpora from daily news texts. we evaluate the contribution of each individual feature and investigate the incorporation of these diverse statistical and heuristic features for the task of bilingual document alignment. experimental results on the english-chinese and english-malay comparable news corpora show that our proposed discrete fourier transform-based term frequency distribution feature is very effective. it contributes 4.1% and 8% to performance improvement over pearson's correlation method on the two comparable corpora. in addition, when more heuristic and statistical features as well as a bilingual dictionary are utilized, our method shows an absolute performance improvement of 23.2% and 15.3% on the two sets of bilingual corpora when comparing with a prior information retrieval-based method.
an annotation scheme for discourse-level argumentation in research articles. in order to build robust automatic abstracting systems, there is a need for better training resources than are currently available. in this paper, we introduce an annotation scheme for scientific articles which can be used to build such a resource in a consistent way. the seven categories of the scheme are based on rhetorical moves of argumentation. our experimental results show that the scheme is stable, reproducible and intuitive to use.
syntactic phrase reordering for english-to-arabic statistical machine translation. syntactic reordering of the source language to better match the phrase structure of the target language has been shown to improve the performance of phrase-based statistical machine translation. this paper applies syntactic reordering to english-to-arabic translation. it introduces reordering rules, and motivates them linguistically. it also studies the effect of combining reordering with arabic morphological segmentation, a preprocessing technique that has been shown to improve arabic-english and english-arabic translation. we report on results in the news text domain, the un text domain and in the spoken travel domain.
co-dispersion: a windowless approach to lexical association. we introduce an alternative approach to extracting word pair associations from corpora, based purely on surface distances in the text. we contrast it with the prevailing window-based co-occurrence model and show it to be more statistically robust and to disclose a broader selection of significant associative relationships - owing largely to the property of scale-independence. in the process we provide insights into the limiting characteristics of window-based methods which complement the sometimes conflicting application-oriented literature in this area.
combining clues for word alignment. in this paper, a word alignment approach is presented which is based on a combination of clues. word alignment clues indicate associations between words and phrases. they can be based on features such as frequency, part-of-speech, phrase type, and the actual wordform strings. clues can be found by calculating similarity measures or learned from word aligned data. the clue alignment approach, which is proposed in this paper, makes it possible to combine association clues taking different kinds of linguistic information into account. it allows a dynamic tokenization into token units of varying size. the approach has been applied to an english/swedish parallel text with promising results.
bayesian word sense induction. sense induction seeks to automatically identify word senses directly from a corpus. a key assumption underlying previous work is that the context surrounding an ambiguous word is indicative of its meaning. sense induction is thus typically viewed as an unsupervised clustering problem where the aim is to partition a word's contexts into different classes, each representing a word sense. our work places sense induction in a bayesian context by modeling the contexts of the ambiguous word as samples from a multinomial distribution over senses which are in turn characterized as distributions over words. the bayesian framework provides a principled way to incorporate a wide range of features beyond lexical co-occurrences and to systematically assess their utility on the sense induction task. the proposed approach yields improvements over state-of-the-art systems on a benchmark dataset.
japanese dependency structure analysis based on maximum entropy models. this paper describes a dependency structure analysis of japanese sentences based on the maximum entropy models. our model is created by learning the weights of some features from a training corpus to predict the dependency between bunsetsus or phrasal units. the dependency accuracy of our system is 87.2% using the kyoto university corpus. we discuss the contribution of each feature set and the relationship between the number of training data and the accuracy.
generating a non-english subjectivity lexicon: relations that matter. we describe a method for creating a non-english subjectivity lexicon based on an english lexicon, an online translation service and a general purpose thesaurus: wordnet. we use a pagerank-like algorithm to bootstrap from the translation of the english lexicon and rank the words in the thesaurus by polarity using the network of lexical relations in wordnet. we apply our method to the dutch language. the best results are achieved when using synonymy and antonymy relations only, and ranking positive and negative words simultaneously. our method achieves an accuracy of 0.82 at the top 3,000 negative words, and 0.62 at the top 3,000 positive words.
a general, abstract model of incremental dialogue processing. we present a general model and conceptual framework for specifying architectures for incremental processing in dialogue systems, in particular with respect to the topology of the network of modules that make up the system, the way information flows through this network, how information increments are 'packaged', and how these increments are processed by the modules. this model enables the precise specification of incremental systems and hence facilitates detailed comparisons between systems, as well as giving guidance on designing new systems.
lattice parsing to integrate speech recognition and rule-based machine translation. in this paper, we present a novel approach to integrate speech recognition and rule-based machine translation by lattice parsing. the presented approach is hybrid in two senses. first, it combines structural and statistical methods for language modeling task. second, it employs a chart parser which utilizes manually created syntax rules in addition to scores obtained after statistical processing during speech recognition. the employed chart parser is a unification-based active chart parser. it can parse word graphs by using a mixed strategy instead of being bottom-up or top-down only. the results are reported based on word error rate on the nist hub-1 word-lattices. the presented approach is implemented and compared with other syntactic language modeling techniques.
contextual phrase-level polarity analysis using lexical affect scoring and syntactic n-grams. we present a classifier to predict contextual polarity of subjective phrases in a sentence. our approach features lexical scoring derived from the dictionary of affect in language (dal) and extended through wordnet, allowing us to automatically score the vast majority of words in our input avoiding the need for manual labeling. we augment lexical scoring with n-gram analysis to capture the effect of context. we combine dal scores with syntactic constituents and then extract n-grams of constituents from all sentences. we also use the polarity of all syntactic constituents within the sentence as features. our results show significant improvement over a majority class baseline as well as a more difficult baseline consisting of lexical n-grams.
enhancing unlexicalized parsing performance using a wide coverage lexicon, fuzzy tag-set mapping, and em-hmm-based lexical probabilities. we present a framework for interfacing a pcfg parser with lexical information from an external resource following a different tagging scheme than the treebank. this is achieved by defining a stochastic mapping layer between the two resources. lexical probabilities for rare events are estimated in a semi-supervised manner from a lexicon and large unannotated corpora. we show that this solution greatly enhances the performance of an unlexicalized hebrew pcfg parser, resulting in state-of-the-art hebrew parsing results both when a segmentation oracle is assumed, and in a real-word parsing scenario of parsing unsegmented tokens.
flexible answer typing with discriminative preference ranking. an important part of question answering is ensuring a candidate answer is plausible as a response. we present a flexible approach based on discriminative preference ranking to determine which of a set of candidate answers are appropriate. discriminative methods provide superior performance while at the same time allow the flexibility of adding new and diverse features. experimental results on a set of focused what ...? and which ...? questions show that our learned preference ranking methods perform better than alternative solutions to the task of answer typing. a gain of almost 0.2 in mrr for both the first appropriate and first correct answers is observed along with an increase in precision over the entire range of recall.
language id in the context of harvesting language data off the web. as the arm of nlp technologies extends beyond a small core of languages, techniques for working with instances of language data across hundreds to thousands of languages may require revisiting and recalibrating the tried and true methods that are used. of the nlp techniques that has been treated as "solved" is language identification (language id) of written text. however, we argue that language id is far from solved when one considers input spanning not dozens of languages, but rather hundreds to thousands, a number that one approaches when harvesting language data found on the web. we formulate language id as a coreference resolution problem and apply it to a web harvesting task for a specific linguistic data type and achieve a much higher accuracy than long accepted language id approaches.
large-coverage root lexicon extraction for hindi. this paper describes a method using morphological rules and heuristics, for the automatic extraction of large-coverage lexicons of stems and root word-forms from a raw text corpus. we cast the problem of high-coverage lexicon extraction as one of stemming followed by root word-form selection. we examine the use of pos tagging to improve precision and recall of stemming and thereby the coverage of the lexicon. we present accuracy, precision and recall scores for the system on a hindi corpus.
tbl-improved non-deterministic segmentation and pos tagging for a chinese parser. although a lot of progress has been made recently in word segmentation and pos tagging for chinese, the output of current state-of-the-art systems is too inaccurate to allow for syntactic analysis based on it. we present an experiment in improving the output of an off-the-shelf module that performs segmentation and tagging, the tokenizer-tagger from beijing university (pku). our approach is based on transformation-based learning (tbl). unlike in other tbl-based approaches to the problem, however, both obligatory and optional transformation rules are learned, so that the final system can output multiple segmentation and pos tagging analyses for a given input. by allowing for a small amount of ambiguity in the output of the tokenizer-tagger, we achieve a very considerable improvement in accuracy. compared to the pku tokenizer-tagger, we improve segmentation f-score from 94.18% to 96.74%, tagged word f-score from 84.63% to 92.44%, segmented sentence accuracy from 47.15% to 65.06% and tagged sentence accuracy from 14.07% to 31.47%.
evaluating the inferential utility of lexical-semantic resources. lexical-semantic resources are used extensively for applied semantic inference, yet a clear quantitative picture of their current utility and limitations is largely missing. we propose system- and application-independent evaluation and analysis methodologies for resources' performance, and systematically apply them to seven prominent resources. our findings identify the currently limited recall of available resources, and indicate the potential to improve performance by examining non-standard relation types and by distilling the output of distributional methods. further, our results stress the need to include auxiliary information regarding the lexical and logical contexts in which a lexical inference is valid, as well as its prior validity likelihood.
an alignment algorithm using belief propagation and a structure-based distortion model. in this paper, we first demonstrate the interest of the loopy belief propagation algorithm to train and use a simple alignment model where the expected marginal values needed for an efficient em-training are not easily computable. we then improve this model with a distortion model based on structure conservation.
semitic morphological analysis and generation using finite state transducers with feature structures. this paper presents an application of finite state transducers weighted with feature structure descriptions, following amtrup (2003), to the morphology of the semitic language tigrinya. it is shown that feature-structure weights provide an efficient way of handling the templatic morphology that characterizes semitic verb stems as well as the long-distance dependencies characterizing the complex tigrinya verb morphotactics. a relatively complete computational implementation of tigrinya verb morphology is described.
character-level dependencies in chinese: usefulness and learning. we investigate the possibility of exploiting character-based dependency for chinese information processing. as chinese text is made up of character sequences rather than word sequences, word in chinese is not so natural a concept as in english, nor is word easy to be defined without argument for such a language. therefore we propose a character-level dependency scheme to represent primary linguistic relationships within a chinese sentence. the usefulness of character dependencies are verified through two specialized dependency parsing tasks. the first is to handle trivial character dependencies that are equally transformed from traditional word boundaries. the second furthermore considers the case that annotated internal character dependencies inside a word are involved. both of these results from character-level dependency parsing are positive. this study provides an alternative way to formularize basic character-and word-level representation for chinese.
sentiment summarization: evaluating and learning user preferences. we present the results of a large-scale, end-to-end human evaluation of various sentiment summarization models. the evaluation shows that users have a strong preference for summarizers that model sentiment over non-sentiment baselines, but have no broad overall preference between any of the sentiment-based models. however, an analysis of the human judgments suggests that there are identifiable situations where one summarizer is generally preferred over the others. we exploit this fact to build a new summarizer by training a ranking svm model over the set of human preference judgments that were collected during the evaluation, which results in a 30% relative reduction in error over the previous best summarizer.
word lattices for multi-source translation. multi-source statistical machine translation is the process of generating a single translation from multiple inputs. previous work has focused primarily on selecting from potential outputs of separate translation systems, and solely on multi-parallel corpora and test sets. we demonstrate how multi-source translation can be adapted for multiple monolingual inputs. we also examine different approaches to dealing with multiple sources, including consensus decoding, and we present a novel method of input combination to generate lattices for multi-source translation within a single translation model.
company-oriented extractive summarization of financial news. the paper presents a multi-document summarization system which builds company-specific summaries from a collection of financial news such that the extracted sentences contain novel and relevant information about the corresponding organization. the user's familiarity with the company's profile is assumed. the goal of such summaries is to provide information useful for the short-term trading of the corresponding company, i.e., to facilitate the inference from news to stock price movement in the next day. we introduce a novel query (i.e., company name) expansion method and a simple unsupervized algorithm for sentence ranking. the system shows promising results in comparison with a competitive baseline.
using cycles and quasi-cycles to disambiguate dictionary glosses. we present a novel graph-based algorithm for the automated disambiguation of glosses in lexical knowledge resources. a dictionary graph is built starting from senses (vertices) and explicit or implicit relations in the dictionary (edges). the approach is based on the identification of edge sequences which constitute cycles in the dictionary graph (possibly with one edge reversed) and relate a source to a target word sense. experiments are performed on the disambiguation of ambiguous words in the glosses of wordnet and two machine-readable dictionaries.
personalizing pagerank for word sense disambiguation. in this paper we propose a new graph-based method that uses the knowledge in a lkb (based on wordnet) in order to perform unsupervised word sense disambiguation. our algorithm uses the full graph of the lkb efficiently, performing better than previous approaches in english all-words datasets. we also show that the algorithm can be easily ported to other languages with good results, with the only requirement of having a wordnet. in addition, we make an analysis of the performance of the algorithm, showing that it is efficient and that it could be tuned to be faster.
structural, transitive and latent models for biographic fact extraction. this paper presents six novel approaches to biographic fact extraction that model structural, transitive and latent properties of biographical data. the ensemble of these proposed models substantially outperforms standard pattern-based biographic fact extraction methods and performance is further improved by modeling inter-attribute correlations and distributions over functions of attributes, achieving an average extraction accuracy of 80% over seven types of biographic attributes.
learning efficient parsing. a corpus-based technique is described to improve the efficiency of wide-coverage high-accuracy parsers. by keeping track of the derivation steps which lead to the best parse for a very large collection of sentences, the parser learns which parse steps can be filtered without significant loss in parsing accuracy, but with an important increase in parsing efficiency. an interesting characteristic of our approach is that it is self-learning, in the sense that it uses unannotated corpora.
incremental dialogue processing in a micro-domain. this paper describes a fully incremental dialogue system that can engage in dialogues in a simple domain, number dictation. because it uses incremental speech recognition and prosodic analysis, the system can give rapid feedback as the user is speaking, with a very short latency of around 200ms. because it uses incremental speech synthesis and self-monitoring, the system can react to feedback from the user as the system is speaking. a comparative evaluation shows that na&iuml;ve users preferred this system over a non-incremental version, and that it was perceived as more human-like.
improving grammaticality in statistical sentence generation: introducing a dependency spanning tree algorithm with an argument satisfaction model. abstract-like text summarisation requires a means of producing novel summary sentences. in order to improve the grammaticality of the generated sentence, we model a global (sentence) level syntactic structure. we couch statistical sentence generation as a spanning tree problem in order to search for the best dependency tree spanning a set of chosen words. we also introduce a new search algorithm for this task that models argument satisfaction to improve the linguistic validity of the generated tree. we treat the allocation of modifiers to heads as a weighted bipartite graph matching (or assignment) problem, a well studied problem in graph theory. using bleu to measure performance on a string regeneration task, we found an improvement, illustrating the benefit of the spanning tree approach armed with an argument satisfaction model.
end-to-end evaluation in simultaneous translation. this paper presents the end-to-end evaluation of an automatic simultaneous translation system, built with state-of-the-art components. it shows whether, and for which situations, such a system might be advantageous when compared to a human interpreter. using speeches in english translated into spanish, we present the evaluation procedure and we discuss the results both for the recognition and translation components as well as for the overall system. even if the translation process remains the achilles' heel of the system, the results show that the system can keep at least half of the information, becoming potentially useful for final users.
analysing wikipedia and gold-standard corpora for ner training. named entity recognition (ner) for english typically involves one of three gold standards: muc, conll, or bbn, all created by costly manual annotation. recent work has used wikipedia to automatically create a massive corpus of named entity annotated text. we present the first comprehensive cross-corpus evaluation of ner. we identify the causes of poor cross-corpus performance and demonstrate ways of making them more compatible. using our process, we develop a wikipedia corpus which outperforms gold standard corpora on cross-corpus evaluation by up to 11%.
semi-supervised polarity lexicon induction. we present an extensive study on the problem of detecting polarity of words. we consider the polarity of a word to be either positive or negative. for example, words such as good, beautiful, and wonderful are considered as positive words; whereas words such as bad, ugly, and sad are considered negative words. we treat polarity detection as a semi-supervised label propagation problem in a graph. in the graph, each node represents a word whose polarity is to be determined. each weighted edge encodes a relation that exists between two words. each node (word) can have two labels: positive or negative. we study this framework in two different resource availability scenarios using wordnet and openoffice thesaurus when wordnet is not available. we report our results on three different languages: english, french, and hindi. our results indicate that label propagation improves significantly over the baseline and other semi-supervised learning methods like mincuts and randomized mincuts for this task.
weakly supervised part-of-speech tagging for morphologically-rich, resource-scarce languages. this paper examines unsupervised approaches to part-of-speech (pos) tagging for morphologically-rich, resource-scarce languages, with an emphasis on goldwater and griffiths's (2007) fully-bayesian approach originally developed for english pos tagging. we argue that existing unsupervised pos taggers unrealistically assume as input a perfect pos lexicon, and consequently, we propose a weakly supervised fully-bayesian approach to pos tagging, which relaxes the unrealistic assumption by automatically acquiring the lexicon from a small amount of pos-tagged data. since such relaxation comes at the expense of a drop in tagging accuracy, we propose two extensions to the bayesian framework and demonstrate that they are effective in improving a fully-bayesian pos tagger for bengali, our representative morphologically-rich, resource-scarce language.
treebank grammar techniques for non-projective dependency parsing. an open problem in dependency parsing is the accurate and efficient treatment of non-projective structures. we propose to attack this problem using chart-parsing algorithms developed for mildly context-sensitive grammar formalisms. in this paper, we provide two key tools for this approach. first, we show how to reduce non-projective dependency parsing to parsing with linear context-free rewriting systems (lcfrs), by presenting a technique for extracting lcfrs from dependency treebanks. for efficient parsing, the extracted grammars need to be transformed in order to minimize the number of nonterminal symbols per production. our second contribution is an algorithm that computes this transformation for a large, empirically relevant class of grammars.
dependency trees and the strong generative capacity of ccg. we propose a novel algorithm for extracting dependencies from the derivations of a large fragment of ccg. unlike earlier proposals, our dependency structures are always tree-shaped. we then use these dependency trees to compare the strong generative capacities of ccg and tag and obtain surprising results: both formalisms generate the same languages of derivation trees --- but the mechanisms they use to bring the words in these trees into a linear order are incomparable.
n-gram-based statistical machine translation versus syntax augmented machine translation: comparison and system combination. in this paper we compare and contrast two approaches to machine translation (mt): the cmu-uka syntax augmented machine translation system (samt) and upc-talp n-gram-based statistical machine translation (smt). samt is a hierarchical syntax-driven translation system underlain by a phrase-based model and a target part parse tree. in n-gram-based smt, the translation process is based on bilingual units related to word-to-word alignment and statistical modeling of the bilingual context following a maximum-entropy framework. we provide a step-by-step comparison of the systems and report results in terms of automatic evaluation metrics and required computational resources for a smaller arabic-to-english translation task (1.5m tokens in the training corpus). human error analysis clarifies advantages and disadvantages of the systems under consideration. finally, we combine the output of both systems to yield significant improvements in translation quality.
unsupervised methods for head assignments. we present several algorithms for assigning heads in phrase structure trees, based on different linguistic intuitions on the role of heads in natural language syntax. starting point of our approach is the observation that a head-annotated treebank defines a unique lexicalized tree substitution grammar. this allows us to go back and forth between the two representations, and define objective functions for the unsupervised learning of head assignments in terms of features of the implicit lexicalized tree grammars. we evaluate algorithms based on the match with gold standard head-annotations, and the comparative parsing accuracy of the lexicalized grammars they give rise to. on the first task, we approach the accuracy of hand-designed heuristics for english and inter-annotation-standard agreement for german. on the second task, the implied lexicalized grammars score 4% points higher on parsing accuracy than lexicalized grammars derived by commonly used heuristics.
supervised domain adaption for wsd. the lack of positive results on supervised domain adaptation for wsd have cast some doubts on the utility of hand-tagging general corpora and thus developing generic supervised wsd systems. in this paper we show for the first time that our wsd system trained on a general source corpus (bnc) and the target corpus, obtains up to 22% error reduction when compared to a system trained on the target corpus alone. in addition, we show that as little as 40% of the target corpus (when supplemented with the source corpus) is sufficient to obtain the same results as training on the full target data. the key for success is the use of unlabeled data with svd, a combination of kernels and svm.
fast full parsing by linear-chain conditional random fields. this paper presents a chunking-based discriminative approach to full parsing. we convert the task of full parsing into a series of chunking tasks and apply a conditional random field (crf) model to each level of chunking. the probability of an entire parse tree is computed as the product of the probabilities of individual chunking results. the parsing is performed in a bottom-up manner and the best derivation is efficiently obtained by using a depth-first search algorithm. experimental results demonstrate that this simple parsing framework produces a fast and reasonably accurate parser.
semi-supervised training for the averaged perceptron pos tagger. this paper describes pos tagging experiments with semi-supervised training as an extension to the (supervised) averaged perceptron algorithm, first introduced for this task by (collins, 2002). experiments with an iterative training on standard-sized supervised (manually annotated) dataset (106 tokens) combined with a relatively modest (in the order of 108 tokens) unsupervised (plain) data in a bagging-like fashion showed significant improvement of the pos classification task on typologically different languages, yielding better than state-of-the-art results for english and czech (4.12 % and 4.86 % relative error reduction, respectively; absolute accuracies being 97.44 % and 95.89 %).
improvements in analogical learning: application to translating multi-terms of the medical domain. handling terminology is an important matter in a translation workflow. however, current machine translation (mt) systems do not yet propose anything proactive upon tools which assist in managing terminological databases. in this work, we investigate several enhancements to analogical learning and test our implementation on translating medical terms. we show that the analogical engine works equally well when translating from and into a morphologically rich language, or when dealing with language pairs written in different scripts. combining it with a phrase-based statistical engine leads to significant improvements.
reconstructing false start errors in spontaneous speech text. this paper presents a conditional random field-based approach for identifying speaker-produced disfluencies (i.e. if and where they occur) in spontaneous speech transcripts. we emphasize false start regions, which are often missed in current disfluency identification approaches as they lack lexical or structural similarity to the speech immediately following. we find that combining lexical, syntactic, and language model-related features with the output of a state-of-the-art disfluency identification system improves overall word-level identification of these and other errors. improvements are reinforced under a stricter evaluation metric requiring exact matches between cleaned sentences annotator-produced reconstructions, and altogether show promise for general reconstruction efforts.
correcting a pos-tagged corpus using three complementary methods. the quality of the part-of-speech (pos) annotation in a corpus is crucial for the development of pos taggers. in this paper, we experiment with three complementary methods for automatically detecting errors in the pos annotation for the icelandic frequency dictionary corpus. the first two methods are language independent and we argue that the third method can be adapted to other morphologically complex languages. once possible errors have been detected, we examine each error candidate and hand-correct the corresponding pos tag if necessary. overall, based on the three methods, we hand-correct the pos tagging of 1,334 tokens (0.23% of the tokens) in the corpus. furthermore, we re-evaluate existing state-of-the-art pos taggers on icelandic text using the corrected corpus.
slacker semantics: why superficiality, dependency and avoidance of commitment can be the right way to go. this paper discusses computational compositional semantics from the perspective of grammar engineering, in the light of experience with the use of minimal recursion semantics in delph-in grammars. the relationship between argument indexation and semantic role labelling is explored and a semantic dependency notation (dmrs) is introduced.
automatic single-document key fact extraction from newswire articles. this paper addresses the problem of extracting the most important facts from a news article. our approach uses syntactic, semantic, and general statistical features to identify the most important sentences in a document. the importance of the individual features is estimated using generalized iterative scaling methods trained on an annotated newswire corpus. the performance of our approach is evaluated against 300 unseen news articles and shows that use of these features results in statistically significant improvements over a provenly robust baseline, as measured using metrics such as precision, recall and rouge.
who is "you"? combining linguistic and gaze features to resolve second-person references in dialogue. we explore the problem of resolving the second person english pronoun you in multi-party dialogue, using a combination of linguistic and visual features. first, we distinguish generic and referential uses, then we classify the referential uses as either plural or singular, and finally, for the latter cases, we identify the addressee. in our first set of experiments, the linguistic and visual features are derived from manual transcriptions and annotations, but in the second set, they are generated through entirely automatic means. results show that a multimodal system is often preferable to a unimodal one.
a logic of semantic representations for shallow parsing. one way to construct semantic representations in a robust manner is to enhance shallow language processors with semantic components. here, we provide a model theory for a semantic formalism that is designed for this, namely robust minimal recursion semantics (rmrs). we show that rmrs supports a notion of entailment that allows it to form the basis for comparing the semantic output of different parses of varying depth.
cube summing, approximate inference with non-local features, and dynamic programming without semirings. we introduce cube summing, a technique that permits dynamic programming algorithms for summing over structures (like the forward and inside algorithms) to be extended with non-local features that violate the classical structural independence assumptions. it is inspired by cube pruning (chiang, 2007; huang and chiang, 2007) in its computation of non-local features dynamically using scored k-best lists, but also maintains additional residual quantities used in calculating approximate marginals. when restricted to local features, cube summing reduces to a novel semiring (k-best+residual) that generalizes many of the semirings of goodman (1999). when non-local features are included, cube summing does not reduce to any semiring, but is compatible with generic techniques for solving dynamic programming equations.
growing finely-discriminating taxonomies from seeds of varying quality and size. concept taxonomies offer a powerful means for organizing knowledge, but this organization must allow for many overlapping and fine-grained perspectives if a general-purpose taxonomy is to reflect concepts as they are actually employed and reasoned about in everyday usage. we present here a means of bootstrapping finely-discriminating taxonomies from a variety of different starting points, or seeds, that are acquired from three different sources: wordnet, conceptnet and the web at large.
semi-supervised semantic role labeling. large scale annotated corpora are prerequisite to developing high-performance semantic role labeling systems. unfortunately, such corpora are expensive to produce, limited in size, and may not be representative. our work aims to reduce the annotation effort involved in creating resources for semantic role labeling via semi-supervised learning. our algorithm augments a small number of manually labeled instances with unlabeled examples whose roles are inferred automatically via annotation projection. we formulate the projection task as a generalization of the linear assignment problem. we seek to find a role assignment in the unlabeled data such that the argument similarity between the labeled and unlabeled instances is maximized. experimental results on semantic role labeling show that the automatic annotations produced by our method improve performance over using hand-labeled instances alone.
a robust and extensible exemplar-based model of thematic fit. this paper presents a new, exemplar-based model of thematic fit. in contrast to previous models, it does not approximate thematic fit as argument plausibility or 'fit with verb selectional preferences', but directly as semantic role plausibility for a verb-argument pair, through similarity-based generalization from previously seen verb-argument pairs. this makes the model very robust for data sparsity. we argue that the model is easily extensible to a model of semantic role ambiguity resolution during online sentence comprehension. the model is evaluated on human semantic role plausibility judgments. its predictions correlate significantly with the human judgments. it rivals two state-of-the-art models of thematic fit and exceeds their performance on previously unseen or low-frequency items.
incremental parsing with parallel multiple context-free grammars. parallel multiple context-free grammar (pmcfg) is an extension of context-free grammar for which the recognition problem is still solvable in polynomial time. we describe a new parsing algorithm that has the advantage to be incremental and to support pmcfg directly rather than the weaker mcfg formalism. the algorithm is also top-down which allows it to be used for grammar based word prediction.
using non-lexical features to identify effective indexing terms for biomedical illustrations. automatic image annotation is an attractive approach for enabling convenient access to images found in a variety of documents. since image captions and relevant discussions found in the text can be useful for summarizing the content of images, it is also possible that this text can be used to generate salient indexing terms. unfortunately, this problem is generally domain-specific because indexing terms that are useful in one domain can be ineffective in others. thus, we present a supervised machine learning approach to image annotation utilizing non-lexical features extracted from image-related text to select useful terms. we apply this approach to several subdomains of the biomedical sciences and show that we are able to reduce the number of ineffective indexing terms.
data-driven semantic analysis for multilingual wsd and lexical selection in translation. a common way of describing the senses of ambiguous words in multilingual word sense disambiguation (wsd) is by reference to their translation equivalents in another language. the theoretical soundness of the senses induced in this way can, however, be doubted. this type of cross-lingual sense identification has implications for multilingual wsd and mt evaluation as well. in this article, we first present some arguments in favour of a more thorough analysis of the semantic information that may be induced by the equivalents of ambiguous words found in parallel corpora. then, we present an unsupervised wsd method and a lexical selection method that exploit the results of a data-driven sense induction method. finally, we show how this automatically acquired information can be exploited for a multilingual wsd and mt evaluation more sensitive to lexical semantics.
em works for pronoun anaphora resolution. we present an algorithm for pronoun-anaphora (in english) that uses expectation maximization (em) to learn virtually all of its parameters in an unsupervised fashion. while em frequently fails to find good models for the tasks to which it is set, in this case it works quite well. we have compared it to several systems available on the web (all we have found so far). our program significantly outperforms all of them. the algorithm is fast and robust, and has been made publically available for downloading.
web augmentation of language models for continuous speech recognition of sms text messages. in this paper, we present an efficient query selection algorithm for the retrieval of web text data to augment a statistical language model (lm). the number of retrieved relevant documents is optimized with respect to the number of queries submitted. the querying scheme is applied in the domain of sms text messages. continuous speech recognition experiments are conducted on three languages: english, spanish, and french. the web data is utilized for augmenting in-domain lms in general and for adapting the lms to a user-specific vocabulary. word error rate reductions of up to 6.6% (in lm augmentation) and 26.0% (in lm adaptation) are obtained in setups, where the size of the web mixture lm is limited to the size of the baseline in-domain lm.
deriving generalized knowledge from corpora using wordnet abstraction. existing work in the extraction of commonsense knowledge from text has been primarily restricted to factoids that serve as statements about what may possibly obtain in the world. we present an approach to deriving stronger, more general claims by abstracting over large sets of factoids. our goal is to coalesce the observed nominals for a given predicate argument into a few predominant types, obtained as wordnet synsets. the results can be construed as generically quantified sentences restricting the semantic type of an argument position of a predicate.
unsupervised recognition of literal and non-literal use of idiomatic expressions. we propose an unsupervised method for distinguishing literal and non-literal usages of idiomatic expressions. our method determines how well a literal interpretation is linked to the overall cohesive structure of the discourse. if strong links can be found, the expression is classified as literal, otherwise as idiomatic. we show that this method can help to tell apart literal and non-literal usages, even for idioms which occur in canonical form.
human evaluation of a german surface realisation ranker. in this paper we present a human-based evaluation of surface realisation alternatives. we examine the relative rankings of naturally occurring corpus sentences and automatically generated strings chosen by statistical models (language model, log-linear model), as well as the naturalness of the strings chosen by the log-linear model. we also investigate to what extent preceding context has an effect on choice. we show that native speakers do accept quite some variation in word order, but there are also clearly factors that make certain realisation alternatives more natural.
predicting the fluency of text with shallow structural features: case studies of machine translation and human-written text. sentence fluency is an important component of overall text readability but few studies in natural language processing have sought to understand the factors that define it. we report the results of an initial study into the predictive power of surface syntactic statistics for the task; we use fluency assessments done for the purpose of evaluating machine translation. we find that these features are weakly but significantly correlated with fluency. machine and human translations can be distinguished with accuracy over 80%. the performance of pairwise comparison of fluency is also very high---over 90% for a multi-layer perceptron classifier. we also test the hypothesis that the learned models capture general fluency properties applicable to human-written text. the results do not support this hypothesis: prediction accuracy on the new data is only 57%. this finding suggests that developing a dedicated, task-independent corpus of fluency judgments will be beneficial for further investigations of the problem.
re-ranking models for spoken language understanding. spoken language understanding aims at mapping a natural language spoken sentence into a semantic representation. in the last decade two main approaches have been pursued: generative and discriminative models. the former is more robust to overfitting whereas the latter is more robust to many irrelevant features. additionally, the way in which these approaches encode prior knowledge is very different and their relative performance changes based on the task. in this paper we describe a machine learning framework where both models are used: a generative model produces a list of ranked hypotheses whereas a discriminative model based on structure kernels and support vector machines, re-ranks such list. we tested our approach on the media corpus (human-machine dialogs) and on a new corpus (human-machine and human-human dialogs) produced in the european luna project. the results show a large improvement on the state-of-the-art in concept segmentation and labeling.
on the use of comparable corpora to improve smt performance. we present a simple and effective method for extracting parallel sentences from comparable corpora. we employ a statistical machine translation (smt) system built from small amounts of parallel texts to translate the source side of the non-parallel corpus. the target side texts are used, along with other corpora, in the language model of this smt system. we then use information retrieval techniques and simple filters to create french/english parallel data from a comparable news corpora. we evaluate the quality of the extracted data by showing that it significantly improves the performance of an smt systems.
translation as weighted deduction. we present a unified view of many translation algorithms that synthesizes work on deductive parsing, semiring parsing, and efficient approximate search algorithms. this gives rise to clean analyses and compact descriptions that can serve as the basis for modular implementations. we illustrate this with several examples, showing how to build search spaces for several disparate phrase-based search strategies, integrate non-local features, and devise novel models. although the framework is drawn from parsing and applied to translation, it is applicable to many dynamic programming problems arising in natural language processing and other areas.
predicting strong associations on the basis of corpus data. current approaches to the prediction of associations rely on just one type of information, generally taking the form of either word space models or collocation measures. at the moment, it is an open question how these approaches compare to one another. in this paper, we will investigate the performance of these two types of models and that of a new approach based on compounding. the best single predictor is the log-likelihood ratio, followed closely by the document-based word space model. we will show, however, that an ensemble method that combines these two best approaches with the compounding algorithm achieves an increase in performance of almost 30% over the current state of the art.
person identification from text and speech genre samples. in this paper, we describe experiments conducted on identifying a person using a novel unique correlated corpus of text and audio samples of the person's communication in six genres. the text samples include essays, emails, blogs, and chat. audio samples were collected from individual interviews and group discussions and then transcribed to text. for each genre, samples were collected for six topics. we show that we can identify the communicant with an accuracy of 71% for six fold cross validation using an average of 22,000 words per individual across the six genres. for person identification in a particular genre (train on five genres, test on one), an average accuracy of 82% is achieved. for identification from topics (train on five topics, test on one), an average accuracy of 94% is achieved. we also report results on identifying a person's communication in a genre using text genres only as well as audio genres only.
outclassing wikipedia in open-domain information extraction: weakly-supervised acquisition of attributes over conceptual hierarchies. a set of labeled classes of instances is extracted from text and linked into an existing conceptual hierarchy. besides a significant increase in the coverage of the class labels assigned to individual instances, the resulting resource of labeled classes is more effective than similar data derived from the manually-created wikipedia, in the task of attribute extraction over conceptual hierarchies.
effects of word confusion networks on voice search. mobile voice-enabled search is emerging as one of the most popular applications abetted by the exponential growth in the number of mobile devices. the automatic speech recognition (asr) output of the voice query is parsed into several fields. search is then performed on a text corpus or a database. in order to improve the robustness of the query parser to noise in the asr output, in this paper, we investigate two different methods to query parsing. both methods exploit multiple hypotheses from asr, in the form of word confusion networks, in order to achieve tighter coupling between asr and query parsing and improved accuracy of the query parser. we also investigate the results of this improvement on search accuracy. word confusion-network based query parsing outperforms asr 1-best based query-parsing by 2.7% absolute and the search performance improves by 1.8% absolute on one of our data sets.
frequency matters: pitch accents and information status. this paper presents the results of a series of experiments which examine the impact of two information status categories (given and new) and frequency of occurrence on pitch accent realisations. more specifically the experiments explore within-type similarity of pitch accent productions and the effect information status and frequency of occurrence have on these productions. the results indicate a significant influence of both pitch accent type and information status category on the degree of within-type variability, in line with exemplartheoretic expectations.
correcting dependency annotation errors. building on work detecting errors in dependency annotation, we set out to correct local dependency errors. to do this, we outline the properties of annotation errors that make the task challenging and their existence problematic for learning. for the task, we define a feature-based model that explicitly accounts for non-relations between words, and then use ambiguities from one model to constrain a second, more relaxed model. in this way, we are successfully able to correct many errors, in a way which is potentially applicable to dependency parsing more generally.
parsing mildly non-projective dependency structures. we present parsing algorithms for various mildly non-projective dependency formalisms. in particular, algorithms are presented for: all well-nested structures of gap degree at most 1, with the same complexity as the best existing parsers for constituency formalisms of equivalent generative power; all well-nested structures with gap degree bounded by any constant k; and a new class of structures with gap degree up to k that includes some ill-nested structures. the third case includes all the gap degree k structures in a number of dependency treebanks.
text-to-text semantic similarity for automatic short answer grading. in this paper, we explore unsupervised techniques for the task of automatic short answer grading. we compare a number of knowledge-based and corpus-based measures of text similarity, evaluate the effect of domain and size on the corpus-based measures, and also introduce a novel technique to improve the performance of the system by integrating automatic feedback from the student answers. overall, our system significantly and consistently outperforms other unsupervised methods for short answer grading that have been proposed in the past.
cognitively motivated features for readability assessment. we investigate linguistic features that correlate with the readability of texts for adults with intellectual disabilities (id). based on a corpus of texts (including some experimentally measured for comprehension by adults with id), we analyze the significance of novel discourse-level features related to the cognitive factors underlying our users' literacy challenges. we develop and evaluate a tool for automatically rating the readability of texts for these users. our experiments show that our discourse-level, cognitively-motivated features improve automatic readability assessment.
inference rules and their application to recognizing textual entailment. in this paper, we explore ways of improving an inference rule collection and its application to the task of recognizing textual entailment. for this purpose, we start with an automatically acquired collection and we propose methods to refine it and obtain more rules using a hand-crafted lexical resource. following this, we derive a dependency-based structure representation from texts, which aims to provide a proper base for the inference rule application. the evaluation of our approach on the recognizing textual entailment data shows promising results on precision and the error analysis suggests possible improvements.
language-independent bilingual terminology extraction from a multilingual parallel corpus. we present a language-pair independent terminology extraction module that is based on a sub-sentential alignment system that links linguistically motivated phrases in parallel texts. statistical filters are applied on the bilingual list of candidate terms that is extracted from the alignment output. we compare the performance of both the alignment and terminology extraction module for three different language pairs (french-english, french-italian and french-dutch) and highlight language-pair specific problems (e.g. different compounding strategy in french and dutch). comparisons with standard terminology extraction programs show an improvement of up to 20% for bilingual terminology extraction and competitive results (85% to 90% accuracy) for monolingual terminology extraction, and reveal that the linguistically based alignment module is particularly well suited for the extraction of complex multiword terms.
mint: a method for effective and scalable mining of named entity transliterations from large comparable corpora. in this paper, we address the problem of mining transliterations of named entities (nes) from large comparable corpora. we leverage the empirical fact that multilingual news articles with similar news content are rich in named entity transliteration equivalents (netes). our mining algorithm, mint, uses a cross-language document similarity model to align multilingual news articles and then mines netes from the aligned articles using a transliteration similarity model. we show that our approach is highly effective on 6 different comparable corpora between english and 4 languages from 3 different language families. furthermore, it performs substantially better than a state-of-the-art competitor.
measuring frame relatedness. in this paper we introduce the notion of "frame relatedness", i.e. relatedness among prototypical situations as represented in the framenet database. we first demonstrate the cognitive plausibility of that notion through an annotation experiment, and then propose different types of computational measures to automatically assess relatedness. results show that our measures provide good performance on the task of ranking pairs of frames.
using lexical and relational similarity to classify semantic relations. many methods are available for computing semantic similarity between individual words, but certain nlp tasks require the comparison of word pairs. this paper presents a kernel-based framework for application to relational reasoning tasks of this kind. the model presented here combines information about two distinct types of word pair similarity: lexical similarity and relational similarity. we present an efficient and flexible technique for implementing relational similarity and show the effectiveness of combining lexical and relational models by demonstrating state-of-the-art results on a compound noun interpretation task.
lightly supervised transliteration for machine translation. we present a hebrew to english transliteration method in the context of a machine translation system. our method uses machine learning to determine which terms are to be transliterated rather than translated. the training corpus for this purpose includes only positive examples, acquired semi-automatically. our classifier reduces more than 38% of the errors made by a baseline method. the identified terms are then transliterated. we present an smt-based transliteration model trained with a parallel corpus extracted from wikipedia using a fairly simple method which requires minimal knowledge. the correct result is produced in more than 76% of the cases, and in 92% of the instances it is one of the top-5 results. we also demonstrate a small improvement in the performance of a hebrew-to-english mt system that uses our transliteration module.
performance confidence estimation for automatic summarization. we address the task of automatically predicting if summarization system performance will be good or bad based on features derived directly from either single- or multi-document inputs. our labelled corpus for the task is composed of data from large scale evaluations completed over the span of several years. the variation of data between years allows for a comprehensive analysis of the robustness of features, but poses a challenge for building a combined corpus which can be used for training and testing. still, we find that the problem can be mitigated by appropriately normalizing for differences within each year. we examine different formulations of the classification task which considerably influence performance. the best results are 84% prediction accuracy for single- and 74% for multi-document summarization.
an empirical study on class-based word sense disambiguation. as empirically demonstrated by the last senseval exercises, assigning the appropriate meaning to words in context has resisted all attempts to be successfully addressed. one possible reason could be the use of inappropriate set of meanings. in fact, wordnet has been used as a de-facto standard repository of meanings. however, to our knowledge, the meanings represented by wordnet have been only used for wsd at a very fine-grained sense level or at a very coarse-grained class level. we suspect that selecting the appropriate level of abstraction could be on between both levels. we use a very simple method for deriving a small set of appropriate meanings using basic structural properties of wordnet. we also empirically demonstrate that this automatically derived set of meanings groups senses into an adequate level of abstraction in order to perform class-based word sense disambiguation, allowing accuracy figures over 80%.
discovering global patterns in linguistic networks through spectral analysis: a case study of the consonant inventories. recent research has shown that language and the socio-cognitive phenomena associated with it can be aptly modeled and visualized through networks of linguistic entities. however, most of the existing works on linguistic networks focus only on the local properties of the networks. this study is an attempt to analyze the structure of languages via a purely structural technique, namely spectral analysis, which is ideally suited for discovering the global correlations in a network. application of this technique to phonet, the co-occurrence network of consonants, not only reveals several natural linguistic principles governing the structure of the consonant inventories, but is also able to quantify their relative importance. we believe that this powerful technique can be successfully applied, in general, to study the structure of natural languages.
clique-based clustering for improving named entity recognition systems. we propose a system which builds, in a semi-supervised manner, a resource that aims at helping a ner system to annotate corpus-specific named entities. this system is based on a distributional approach which uses syntactic dependencies for measuring similarities between named entities. the specificity of the presented method however, is to combine a clique-based approach and a clustering technique that amounts to a soft clustering method. our experiments show that the resource constructed by using this clique-based clustering system allows to improve different ner systems.
nlp and the humanities: the revival of an old liaison. this paper present an overview of some emerging trends in the application of nlp in the domain of the so-called digital humanities and discusses the role and nature of metadata, the annotation layer that is so characteristic of documents that play a role in the scholarly practises of the humanities. it is explained how metadata are the key to the added value of techniques such as text and link mining, and an outline is given of what measures could be taken to increase the chances for a bright future for the old ties between nlp and the humanities. there is no data like metadata!
tagging urdu text with parts of speech: a tagger comparison. in this paper, four state-of-art probabilistic taggers i.e. tnt tagger, treetagger, rf tagger and svm tool, are applied to the urdu language. for the purpose of the experiment, a syntactic tagset is proposed. a training corpus of 100,000 tokens is used to train the models. using the lexicon extracted from the training corpus, svm tool shows the best accuracy of 94.15%. after providing a separate lexicon of 70,568 types, svm tool again shows the best accuracy of 95.66%.
syntactic and semantic kernels for short text pair categorization. automatic detection of general relations between short texts is a complex task that cannot be carried out only relying on language models and bag-of-words. therefore, learning methods to exploit syntax and semantics are required. in this paper, we present a new kernel for the representation of shallow semantic information along with a comprehensive study on kernel methods for the exploitation of syntactic/semantic structures for short text pair categorization. our experiments with support vector machines on question/answer classification show that our kernels can be used to greatly improve system accuracy.
incremental parsing models for dialog task structure. in this paper, we present an integrated model of the two central tasks of dialog management: interpreting user actions and generating system actions. we model the interpretation task as a classification problem and the generation task as a prediction problem. these two tasks are interleaved in an incremental parsing-based dialog model. we compare three alternative parsing methods for this dialog model using a corpus of human-human spoken dialog from a catalog ordering domain that has been annotated for dialog acts and task/subtask information. we contrast the amount of context provided by each method and its impact on performance.
threading fundamental matrices. we present a new function that operates on fundamental matrices across a sequence of views. the operation, we call ¿threading¿, connects two consecutive fundamental matrices using the trifocal tensor as the connecting thread. the threading operation guarantees that consecutive camera matrices are consistent with a unique 3d model, without ever recovering a 3d model. applications include recovery of camera ego-motion from a sequence of views, image stabilization (plane stabilization) across a sequence, and multiview image-based rendering.
seeing behind occlusions. the location of objects in images is difficult owing to the view variance of geometric features but can be determined by developing view-insensitive descriptions of the intensities local to image points. view-insensitive descriptions are achieved in this work by describing points in terms of the responses of steerable filters at multiple scales. owing to the use of multiple scales, the vector for each point is, for all practical purposes, unique, and thus can be easily matched to other instances of the point in other images. we show that this method can be extended to handle the case where the area near a point of interest is partially occluded. the method uses a description of the occluder in the form of a template that can be obtained easily via active vision systems using a method such as disparity filtering.
generalised epipolar constraints. in this paper we will discuss structure and motion problems for curved surfaces. these will be studied using the silhouettes or apparent contours in the images. the problem of determining camera motion from the apparent contours of curved three-dimensional surfaces, is studied. it will be shown how special points, called epipolar tangency points or frontier points, can be used to solve this problem. a generalised epipolar constraint is introduced, which applies to points, curves, as well as to apparent contours of surfaces. the theory is developed for both continuous and discrete motion, known and unknown orientation, calibrated and uncalibrated, perspective, weak perspective and orthographic cameras. results of an iterative scheme to recover the epipolar line structure from real image sequences using only the outlines of curved surfaces, is presented. a statistical evaluation is performed to estimate the stability of the solution. it is also shown how the motion of the camera from a sequence of images can be obtained from the relative motion between image pairs.
triangulation for points on lines. triangulation consists in finding a 3d point reprojecting the best as possible onto corresponding image points. it is classical to minimize the reprojection error, which, in the pinhole camera model case, is nonlinear in the 3d point coordinates. we study the triangulation of points lying on a 3d line, which is a typical problem for structure-from-motion in man-made environments. we show that the reprojection error can be minimized by finding the real roots of a polynomial in a single variable, which degree depends on the number of images. we use a set of transformations in 3d and in the images to make the degree of this polynomial as low as possible, and derive a practical reconstruction algorithm. experimental comparisons with an algebraic approximation algorithm and minimization of the reprojection error using gauss-newton are reported for simulated and real data. our algorithm finds the optimal solution with high accuracy in all cases, showing that the polynomial equation is very stable. it only computes the roots corresponding to feasible points, and can thus deal with a very large number of views - triangulation from hundreds of views is performed in a few seconds. reconstruction accuracy is shown to be greatly improved compared to standard triangulation methods that do not take the line constraint into account.
symmetrical dense optical flow estimation with occlusions detection. traditional techniques of dense optical flow estimation do not generally yield symmetrical solutions: the results will differ if they are applied between images i 1 and i 2 or between images i 2 and i 1. in this work, we present a method to recover a dense optical flow field map from two images, while explicitely taking into account the symmetry across the images as well as possible occlusions in the flow field. the idea is to consider both displacements vectors from i 1 to i 2 and i 2 to i 1 and to minimise an energy functional that explicitely encodes all those properties. this variational problem is then solved using the gradient flow defined by the euler---lagrange equations associated to the energy. to prove the importance of the concepts of symmetry and occlusions for optical flow computation, we have extended a classical approach to handle those. experiments clearly show the added value of these properties to improve the accuracy of the computed flows.figures appear in color in the online version of this paper.
eigenfaces vs. fisherfaces: recognition using class specific linear projection. we develop a face recognition algorithm which is insensitive to large variation in lighting direction and facial expression. taking a pattern classification approach, we consider each pixel in an image as a coordinate in a high-dimensional space. we take advantage of the observation that the images of a particular face, under varying illumination but fixed pose, lie in a 3d linear subspace of the high dimensional image space¿if the face is a lambertian surface without shadowing. however, since faces are not truly lambertian surfaces and do indeed produce self-shadowing, images will deviate from this linear subspace. rather than explicitly modeling this deviation, we linearly project the image into a subspace in a manner which discounts those regions of the face with large deviation. our projection method is based on fisher's linear discriminant and produces well separated classes in a low-dimensional subspace, even under severe variation in lighting and facial expressions. the eigenface technique, another method based on linearly projecting the image space to a low dimensional subspace, has similar computational requirements. yet, extensive experimental results demonstrate that the proposed "fisherface" method has error rates that are lower than those of the eigenface technique for tests on the harvard and yale face databases.
linear pose estimation from points or lines. estimation of camera pose from an image of n points or lines with known correspondence is a thoroughly studied problem in computer vision. most solutions are iterative and depend on nonlinear optimization of some geometric constraint, either on the world coordinates or on the projections to the image plane. for real-time applications, we are interested in linear or closed-form solutions free of initialization. we present a general framework which allows for a novel set of linear solutions to the pose estimation problem for both n points and n lines. we then analyze the sensitivity of our solutions to image noise and show that the sensitivity analysis can be used as a conservative predictor of error for our algorithms. we present a number of simulations which compare our results to two other recent linear algorithms, as well as to iterative approaches. we conclude with tests on real imagery in an augmented reality setup.
markov random field models in computer vision. :markov random field (mrf) theory provides a basis for modeling contextual constraints in visual processing and interpretation. it enables us to develop optimal vision algorithms systematically when used with optimization principles. this book presents a comprehensive study on the use of mrfs for solving computer vision problems. the book covers the following parts essential to the subject: introduction to fundamental theories, formulations of mrf vision models, mrf parameter estimation, and optimization algorithms. various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. this book is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition, and applications of mrfs. it is also suitable as a text for advanced courses in these areas. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
robust affine structure matching for 3d object recognition. we consider model-based object localization based on local geometric feature matching between the model and the image data. the method is based on geometric constraint analysis, working in transformation space. we present a formal method which guarantees finding all feasible matchings in polynomial time. from there we develop more computationally feasible algorithms based on conservative approximations of the formal method. additionally, our formalism relates object localization, affine model indexing, and structure from multiple views to one another.
a probabilistic theory of occupancy and emptiness. this paper addresses the inference of 3d shape from a set of n noisy photos. we derive a probabilistic framework to specify what one can infer about 3d shape for arbitrarily-shaped, lambertian scenes and arbitrary viewpoint configurations. based on formal definitions of visibility, occupancy, emptiness, and photo-consistency, the theoretical development yields a formulation of the photo hull distribution, the tightest probabilistic bound on the scene''s true shape that can be inferred from the photos. we show how to (1) express this distribution in terms of image measurements, (2) represent it compactly by assigning an occupancy probability to each point in space, and (3) design a stochastic reconstruction algorithm that draws fair samples (i.e., 3d photo hulls) from it. we also show experimental results on two complex scenes.
eigentracking: robust matching and tracking of articulated objects using a view-based representation. this paper describes an approach for tracking rigid and articulated objects using a view-based representation. the approach builds on and extends work on eigenspace representations, robust estimation techniques, and parameterized optical flow estimation. first, we note that the least-squares image reconstruction of standard eigenspace techniques has a number of problems and we reformulate the reconstruction problem as one of robust estimation. second we define a &ldquo;subspace constancy assumption&rdquo; that allows us to exploit techniques for parameterized optical flow estimation to simultaneously solve for the view of an object and the affine transformation between the eigenspace and the image. to account for large affine transformations between the eigenspace and the image we define a multi-scale eigenspace representation and a coarse-to-fine matching strategy. finally, we use these techniques to track objects over long image sequences in which the objects simultaneously undergo both affine image motions and changes of view. in particular we use this &ldquo;eigentracking&rdquo; technique to track and recognize the gestures of a moving hand.
directions of motion fields are hardly ever ambiguous. if instead of the full motion field, we consider only the direction of the motion field due to a rigid motion, what can we say about the three-dimensional motion information contained in it? this paper provides a geometric analysis of this question based solely on the constraint that the depth of the surfaces in view is positive. the motivation behind this analysis is to provide a theoretical foundation for image constraints employing only the sign of flow in various directions and justify their utilization for addressing 3d dynamic vision problems.it is shown that, considering as the imaging surface the whole sphere, independently of the scene in view, two different rigid motions cannot give rise to the same directional motion field. if we restrict the image to half of a sphere (or an infinitely large image plane) two different rigid motions with instantaneous translational and rotational velocities(t<math>_1 &omega;_1) and(t<math>_2 ,&omega;_2) cannot give rise to the same directional motion field unless the plane through t_1 and t_2 is perpendicular to the plane through &omega;_1 and &omega;_2 (i.e., (t_1 &times; t_2) &middot; (&omega;_1 &times; &omega;_2) &equals; 0. in addition, in order to give practical significance to these uniqueness results for the case of a limited field of view, we also characterize the locations on the image where the motion vectors due to the different motions must have different directions.if (&omega;_1 &times; &omega;_2) &middot; (t_1 &times; t_2) &equals; 0 and certain additional constraints are met, then the two rigid motions could produce motion fields with the same direction. for this to happen the depth of each corresponding surface has to be within a certain range, defined by a second and a third order surface. similar more restrictive constraints are obtained for the case of multiple motions. consequently, directions of motion fields are hardly ever ambiguous. a byproduct of the analysis is that full motion fields are never ambiguous with a half sphere as the imaging surface.
active appearance models. we describe a new method of matching statistical models of appearance to images. a set of model parameters control modes of shape and gray-level variation learned from a training set. we construct an efficient iterative matching algorithm by learning the relationship between perturbations in the model parameters and the induced image errors.
analytical results on error sensitivity of motion estimation from two views. fundamental instabilities have been observed in the performance of the majority of the algorithms for three dimensional motion estimation from two views. many geometric and intuitive interpretations have been offered to explain the error sensitivity of the estimated parameters. in this contribution, the importance of the form of the error norm to be minimized with respect to the motion parameters is addressed. the error norms used by the existing algorithms are described in a unifying notation, and a geometric interpretation of them is given. then, for the continuous case of pure translational motion it is proved that the minimization of the objective function leading to an eigenvector solution suffers from a crucial instability. the analyticity of the results allows the examination of error sensitivity in terms of the translation direction, the viewing angle and the distance of the moving object from the camera. a norm possessing a reasonable geometric interpretation in the image plane is proposed to eliminate the effects of the instability mentioned above. due to the high nonlinearity of this norm it has not been possible to prove explicitly its stabilizing role. it is shown by analytical means that a simplification of this norm - leading to a closed form solution - has undesirable properties.
softposit: simultaneous pose and correspondence determination. the problem of pose estimation arises in many areas of computer vision, including object recognition, object tracking, site inspection and updating, and autonomous navigation when scene models are available. we present a new algorithm, called softposit, for determining the pose of a 3d object from a single 2d image when correspondences between object points and image points are not known. the algorithm combines the iterative softassign algorithm (gold and rangarajan, 1996; gold et al., 1998) for computing correspondences and the iterative posit algorithm (dementhon and davis, 1995) for computing object pose under a full-perspective camera model. our algorithm, unlike most previous algorithms for pose determination, does not have to hypothesize small sets of matches and then verify the remaining image points. instead, all possible matches are treated identically throughout the search for an optimal pose. the performance of the algorithm is extensively evaluated in monte carlo simulations on synthetic data under a variety of levels of clutter, occlusion, and image noise. these tests show that the algorithm performs well in a variety of difficult scenarios, and empirical evidence suggests that the algorithm has an asymptotic run-time complexity that is better than previous methods by a factor of the number of image points. the algorithm is being applied to a number of practical autonomous vehicle navigation problems including the registration of 3d architectural models of a city to images, and the docking of small robots onto larger robots.
tracking line segments. the development and implementation of a line segment-based token tracker is described. given a sequence of time-varying images, the goal is to track line segments corresponding to the edges extracted from the image being analysed. two representations for the line segments are presented and discussed. an uncertainty analysis on the parameters of each representation is performed, and the appropriate representation for the tracking problem is then derived. a tracking approach is presented that combines prediction and matching steps. the prediction step is a kalman filtering-based approach that is used to provide reasonable estimates of the region where the matching process has to seek for a possible match between tokens. correspondence in the search area is done through the use of a similarity function based on mahalanobis distance between carefully chosen attributes of the line segments. it is worthwhile to note that tokens as points of interest (corners, triple points) can also be considered without affecting deeply the algorithm. the efficiency of the proposed approach is illustrated in several experiments that have been carried out considering noisy synthetic data and real scenes obtained from the inria mobile robot.
region matching with missing parts. we present a variational approach to the problem of registering planar shapes despite missing parts. registration is achieved through the evolution of a partial differential equation that simultaneously estimates the shape of the missing region, the underlying 'complete shape' and the collection of group elements (euclidean, affine) corresponding to the registration. our technique can be used both for shapes, for instance represented as characteristic functions (binary images) and for grayscale images where it can be interpreted as region 'inpainting.' the novelty of the approach lies on the fact that, rather than estimating the missing region in each image independently, we pose the problem as a joint registration with respect to an underlying 'complete shape' from which the complete version of the original data is obtained via a group action. we simultaneously estimate the complete shape and the group action in an alternating minimization scheme.
local scale control for edge detection and blur estimation. the standard approach to edge detection is based on a model of edges as large step changes in intensity. this approach fails to reliably detect and localize edges in natural images where blur scale and contrast can vary over a broad range. the main problem is that the appropriate spatial scale for local estimation depends upon the local structure of the edge, and thus varies unpredictably over the image. here we show that knowledge of sensor properties and operator norms can be exploited to define a unique, locally computable minimum reliable scale for local estimation at each point in the image. this method for local scale control is applied to the problem of detecting and localizing edges in images with shallow depth of field and shadows. we show that edges spanning a broad range of blur scales and contrasts can be recovered accurately by a single system with no input parameters other than the second moment of the sensor noise. a natural dividend of this approach is a measure of the thickness of contours which can be used to estimate focal and penumbral blur. local scale control is shown to be important for the estimation of blur in complex images, where the potential for interference between nearby edges of very different blur scale requires that estimates be made at the minimum reliable scale.
self-calibration of a 1d projective camera and its application to the self-calibration of a 2d projective camera. we introduce the concept of self-calibration of a 1d projective camera from point correspondences, and describe a method for uniquely determining the two internal parameters of a 1d camera, based on the trifocal tensor of three 1d images. the method requires the estimation of the trifocal tensor which can be achieved linearly with no approximation unlike the trifocal tensor of 2d images and solving for the roots of a cubic polynomial in one variable. interestingly enough, we prove that a 2d camera undergoing planar motion reduces to a 1d camera. from this observation, we deduce a new method for self-calibrating a 2d camera using planar motions. both the self-calibration method for a 1d camera and its applications for 2d camera calibration are demonstrated on real image sequences.
carved visual hulls for image-based modeling. this article presents a novel method for acquiring high-quality solid models of complex 3d shapes from multiple calibrated photographs. after the purely geometric constraints associated with the silhouettes found in each image have been used to construct a coarse surface approximation in the form of a visual hull, photoconsistency constraints are enforced in three consecutive steps: (1) the rims where the surface grazes the visual hull are first identified through dynamic programming; (2) with the rims now fixed, the visual hull is carved using graph cuts to globally optimize the photoconsistency of the surface and recover its main features; (3) an iterative (local) refinement step is finally used to recover fine surface details. the proposed approach has been implemented, and experiments with seven real data sets are presented, along with qualitative and quantitative comparisons with several state-of-the-art image-based-modeling algorithms.
parallel and deterministic algorithms from mrfs: surface reconstruction and integration. in recent years many researchers have investigated the use of markov random fields (mrfs) for computer vision. the computational complexity of the implementation has been a drawback of mrfs. in this paper we derive deterministic approximations to mrfs models. all the theoretical results are obtained in the framework of the mean field theory from statistical mechanics. because we use mrfs models the mean field equations lead to parallel and iterative algorithms. one of the considered models for image reconstruction is shown to give in a natural way the graduate non-convexity algorithm proposed by blake and zisserman.
epipolar fields on surfaces. the view lines associated with a family of profile curves of the projection of a surface onto the retina of a moving camera defines a multi-valued vector field on the surface. the integral curves of this field are called epipolar curves and together with a parametrization of the profiles provide a parametrization of regions of the surface. in addition, one has the epipolar constraints which define curves in the images. these image curves are related to the epipolar curves on the surface but not by a simple projection. we present an investigation of epipolar curves on the object surface, in the spatio-temporal surface and the traces in the images. we address the question of when there is an epipolar parametrization. we have obtained detailed results which depend on a classification \cite{davydov} of vector fields on surfaces with boundary. these results give a systematic way of detecting the gaps left by reconstruction of a surface from profiles. they also suggest methods for filling in these gaps. this work was supported by nato grant crg 910221. in addition, the second author would like to acknowledge the support of darpa and tacom under contract daae07-91-c-r035 and nsf under grants iri-920892 and iri-9116297.
balanced exploration and exploitation model search for efficient epipolar geometry estimation. the estimation of the epipolar geometry is especially difficult when the putative correspondences include a low percentage of inlier correspondences and/or a large subset of the inliers is consistent with a degenerate configuration of the epipolar geometry that is totally incorrect. this work presents the balanced exploration and exploitation model search (beem) algorithm that works very well especially for these difficult scenes. the algorithm handles these two problems in a unified manner. it includes the following main features: (1) balanced use of three search techniques: global random exploration, local exploration near the current best solution and local exploitation to improve the quality of the model. (2) exploits available prior information to accelerate the search process. (3) uses the best found model to guide the search process, escape from degenerate models and to define an efficient stopping criterion. (4) presents a simple and efficient method to estimate the epipolar geometry from two sift correspondences. (5) uses the locality-sensitive hashing (lsh) approximate nearest neighbor algorithm for fast putative correspondences generation. the resulting algorithm when tested on real images with or without degenerate configurations gives quality estimations and achieves significant speedups compared to the state of the art algorithms.
the combinatorics of heuristic search termination for object recognition in cluttered environments. many current recognition systems terminate a search once an interpretation that is good enough is found. the author formally examines the combinatorics of this approach, showing that choosing correct termination procedures can dramatically reduce the search. in particular, the author provides conditions on the object model and the scene clutter such that the expected search is at most quartic. the analytic results are shown to be in agreement with empirical data for cluttered object recognition. these results imply that it is critical to use techniques that select subsets of the data likely to have come from a single object before establishing a correspondence between data and model features.
on the verification of hypthesized matches in model-based recognition. model-based recognition methods generally use ad hoc techniques to decide whether or not a model of an object matches a given scene. the most common such technique is to set an empirically determined threshold on the fraction of model features that must be matched to data features. conditions under which to accept a match as correct are rigorously derived. the analysis is based on modeling the recognition process as a statistical occupancy problem. this model makes the assumption that pairings of object and data features can be characterized as a random process with a uniform distribution. the authors present a number of examples illustrating that real image data are well approximated by such a random process. using a statistical occupancy model, they derive an expression for the probability that a randomly occurring match will account for a given fraction of the features of a particular object. this expression is a function of the number of model features, the number of data features, and bounds on the degree of sensor noise. it provides a means of setting a threshold such that the probability of a random match is very small.
incorporating non-motion cues into 3d motion segmentation. we address the problem of segmenting an image sequence into rigidly moving 3d objects. an elegant solution to this problem in the case of orthographic projection is the multibody factorization approach in which the measurement matrix is factored into lower rank matrices. despite progress in factorization algorithms, their performance is still far from satisfactory and in scenes with missing data and noise, most existing algorithms fail. in this paper we propose a method for incorporating 2d non-motion cues (such as spatial coherence) into multibody factorization. we show the similarity of the problem to constrained factor analysis and use the em algorithm to find the segmentation. we show that adding these cues improves performance in real and synthetic sequences.
video mensuration using a stationary camera. this paper presents a video metrology approach using an uncalibrated single camera that is either stationary or in planar motion. although theoretically simple, measuring the length of even a line segment in a given video is often a difficult problem. most existing techniques for this task are extensions of single image-based techniques and do not achieve the desired accuracy especially in noisy environments. in contrast, the proposed algorithm moves line segments on the reference plane to share a common endpoint using the vanishing line information followed by fitting multiple concentric circles on the image plane. a fully automated real-time system based on this algorithm has been developed to measure vehicle wheelbases using an uncalibrated stationary camera. the system estimates the vanishing line using invariant lengths on the reference plane from multiple frames rather than the given parallel lines, which may not exist in videos. it is further extended to a camera undergoing a planar motion by automatically selecting frames with similar vanishing lines from the video. experimental results show that the measurement results are accurate enough to classify moving vehicles based on their size.
reconstruction from projections using grassmann tensors. in this paper a general procedure is given for reconstruction of a set of feature points in an arbitrary dimensional projective space from their projections into lower dimensional spaces. this extends the methods applied in the well-studied problem of reconstruction of scene points in ¿3 given their projections in a set of images. in this case, the bifocal, trifocal and quadrifocal tensors are used to carry out this computation. it is shown that similar methods will apply in a much more general context, and hence may be applied to projections from ¿ n to ¿ m , which have been used in the analysis of dynamic scenes, and in radial distortion correction. for sufficiently many generic projections, reconstruction of the scene is shown to be unique up to projectivity, except in the case of projections onto one-dimensional image spaces (lines), in which case there are two solutions.projections from ¿ n to ¿2 have been considered by wolf and shashua (in international journal of computer vision 48(1): 53---67, 2002), where they were applied to several different problems in dynamic scene analysis. they analyzed these projections using tensors, but no general way of defining such tensors, and computing the projections was given. this paper settles the general problem, showing that tensor definition and retrieval of the projections is always possible.
confocal stereo. we present confocal stereo, a new method for computing 3d shape by controlling the focus and aperture of a lens. the method is specifically designed for reconstructing scenes with high geometric complexity or fine-scale texture. to achieve this, we introduce the confocal constancy property, which states that as the lens aperture varies, the pixel intensity of a visible in-focus scene point will vary in a scene-independent way, that can be predicted by prior radiometric lens calibration. the only requirement is that incoming radiance within the cone subtended by the largest aperture is nearly constant. first, we develop a detailed lens model that factors out the distortions in high resolution slr cameras (12mp or more) with large-aperture lenses (e.g., f1.2). this allows us to assemble an a×f aperture-focus image (afi) for each pixel, that collects the undistorted measurements over all a apertures and f focus settings. in the afi representation, confocal constancy reduces to color comparisons within regions of the afi, and leads to focus metrics that can be evaluated separately for each pixel. we propose two such metrics and present initial reconstruction results for complex scenes, as well as for a scene with known ground-truth shape.
dreams: deformable regions driven by an eulerian accurate minimization method for image and video segmentation. this paper deals with image and video segmentation using active contours. we propose a general form for the energy functional related to region-based active contours. we compute the associated evolution equation using shape derivation tools and accounting for the evolving region-based terms. then we apply this general framework to compute the evolution equation from functionals that include various statistical measures of homogeneity for the region to be segmented. experimental results show that the determinant of the covariance matrix appears to be a very relevant tool for segmentation of homogeneous color regions. as an example, it has been successfully applied to face segmentation in real video sequences.
robust multiple car tracking with occlusion reasoning. in this work we address the problem of occlusion in tracking multiple 3d objects in a known environment and propose a new approach for tracking vehicles in road traffic scenes using an explicit occlusion reasoning step. we employ a contour tracker based on intensity and motion boundaries. the motion of the contour of the vehicles in the image is assumed to be well describable by an affine motion model with a translation and a change in scale. a vehicle contour is represented by closed cubic splines the position and motion of which is estimated along the image sequence. in order to employ linear kalman filters we decompose the estimation process into two filters: one for estimating the affine motion parameters and one for estimating the shape of the contours of the vehicles. occlusion detection is performed by intersecting the depth ordered regions associated to the objects. the intersection part is then excluded in the motion and shape estimation. this procedure also improves the shape estimation in case of adjacent objects since occlusion detection is performed on slightly enlarged regions. in this way we obtain robust motion estimates and trajectories for vehicles even in the case of occlusions, as we show in some experiments with real world traffic scenes.
what energy functions can be minimized via graph cuts? many problems in computer vision can be naturally phrased in terms of energy minimization. in the last few years researchers have developed a powerful class of energy minimization methods based on graph cuts. these techniques construct a specialized graph, such that the minimum cut on the graph also minimizes the energy. the minimum cut in turn is efficiently computed by max flow algorithms. such methods have been successfully applied to a number of important vision problems, including image restoration, motion, stereo, voxel occupancy and medical imaging. however, each graph construction to date has been highly specific for a particular energy function. in this paper we address a much broader problem, by characterizing the class of energy functions that can be minimized by graph cuts, and by giving a general-purpose construction that minimizes any energy function in this class. our results generalize several previous vision algorithms based on graph cuts, and also show how to minimize an interesting new class of energy functions.
exemplar-based face recognition from video. a new exemplar-based probabilistic approach for face recognition in video sequences is presented. the approach has two stages: first, exemplars, which are selected representatives from the raw video, are automatically extracted from gallery videos. the exemplars are used to summarize the gallery video information.in the second part, exemplars are then used as centers for probabilistic mixture distributions for the tracking and recognition process. probabilistic methods are attractive in this context as they allow a systematic handling of uncertainty and an elegant way for fusing temporal information.contrary to some previous video-based approaches, our approach is not limited to a certain image representation. it rather enhances known ones, such as the pca, with temporal fusion and uncertainty handling. experiments demonstrate the effectiveness of each of the two stages. we tested this approach on more than 100 training and testing sequences, with 25 different individuals.
the relevance of non-generic events in scale space models. in order to investigate the deep structure of gaussian scale space images, one needs to understand the behaviour of spatial critical points under the influence of blurring. we show how the mathematical framework of catastrophe theory can be used to describe and model the behaviour of critical point trajectories when various different types of generic events, viz. annihilations and creations of pairs of spatial critical points, (almost) coincide. although such events are non-generic in mathematical sense, they are not unlikely to be encountered in practice due to numerical limitations. furthermore, the behaviour of these trajectories leads to the observation that fine-to-coarse tracking of critical points doesn't suffice, since they can form closed loops in scale space. the modelling of the trajectories include these loops. we apply the theory to an artificial image and a simulated mr image and show the occurrence of the described behaviour.
ellipse fitting with hyperaccuracy. for fitting an ellipse to a point sequence, ml (maximum likelihood) has been regarded as having the highest accuracy. in this paper, we demonstrate the existence of a "hyperaccurate" method which outperforms ml. this is made possible by error analysis of ml followed by subtraction of high-order bias terms. since ml nearly achieves the theoretical accuracy bound (the kcr lower bound), the resulting improvement is very small. nevertheless, our analysis has theoretical significance, illuminating the relationship between ml and the kcr lower bound.
uncalibrated factorization using a variable symmetric affine camera. in order to reconstruct 3-d euclidean shape by the tomasi-kanade factorization, one needs to specify an affine camera model such as orthographic, weak perspective, and paraperspective. we present a new method that does not require any such specific models. we show that a minimal requirement for an affine camera to mimic perspective projection leads to a unique camera model, called symmetric affine camera, which has two free functions. we determine their values from input images by linear computation and demonstrate by experiments that an appropriate camera model is automatically selected.
learning to combine bottom-up and top-down segmentation. bottom-up segmentation based only on low-level cues is a notoriously difficult problem. this difficulty has lead to recent top-down segmentation algorithms that are based on class-specific image information. despite the success of top-down algorithms, they often give coarse segmentations that can be significantly refined using low-level cues. this raises the question of how to combine both top-down and bottom-up cues in a principled manner.in this paper we approach this problem using supervised learning. given a training set of ground truth segmentations we train a fragment-based segmentation algorithm which takes into account both bottom-up and top-down cues simultaneously, in contrast to most existing algorithms which train top-down and bottom-up modules separately. we formulate the problem in the framework of conditional random fields (crf) and derive a feature induction algorithm for crf, which allows us to efficiently search over thousands of candidate fragments. whereas pure top-down algorithms often require hundreds of fragments, our simultaneous learning procedure yields algorithms with a handful of fragments that are combined with low-level cues to efficiently compute high quality segmentations.
direct evidence for occlusion in stereo and motion. discontinuities of surface properties are the most important locations in a scene; they are crucial for segmentation because they often coincide with object boundaries^1. standard approaches to discontinuity detection decouple detection of disparity discontinuities from disparity computation. we have developed techniques for locating disparity discontinuities using information internal to the stereo algorithm of drumheller and poggio^2 rather than by post-processing the stereo data. the algorithm determines displacements by maximizing the sum, at overlapping small regions, of local comparisons. the detection methods are motivated by analysis of the geometry of matching and occlusion, and the fact that detection is not just a pointwise decision. our methods can be used in combination to produce robust performance. this research is part of a project to build a vision machine^3 at mit that integrates outputs from early vision modules. our techniques have been extensively tested on real images.
elastically adaptive deformable models. we present a novel technique for the automatic adaptation of a deformable model's elastic parameters within a kalman filter framework for shape estimation applications. the novelty of the technique is that the model's elastic parameters are not constant, but spatio-temporally varying. the variation of the elastic parameters depends on the distance of the model from the data and the rate of change of this distance. each pass of the algorithm uses physics-based modeling techniques to iteratively adjust both the geometric and the elastic degrees of freedom of the model in response to forces that are computed from the discrepancy between the model and the data. by augmenting the state equations of an extended kalman filter to incorporate these additional variables, we are able to significantly improve the quality of the shape estimation. therefore, the model's elastic parameters are always initialized to the same value and they are subsequently modified depending on the data and the noise distribution. we present results demonstrating the effectiveness of our method for both two-dimensional and three-dimensional data.
hierarchical image analysis using irregular tessellations. a novel multiresolution image analysis technique based on hierarchies of irregular tessellations generated in parallel by independent stochastic processes is presented. like traditional image pyramids these hierarchies are constructed in a number of steps on the order of log(image-size) steps. however, the structure of a hierarchy is adapted to the image content and artifacts of rigid resolution reduction are avoided. two applications of these techniques are presented: connected component analysis of labeled images and segmentation of gray level images. in labeled images, every connected component is reduced to a separate root, with the adjacency relations among the components also extracted. in gray level images the output is a segmentation of the image into a small number of classes as well as the adjacency graph of the classes.
stereo using monocular cues within the tensor voting framework. we address the fundamental problem of matching in two static images. the remaining challenges are related to occlusion and lack of texture. our approach addresses these difficulties within a perceptual organization framework, considering both binocular and monocular cues. initially, matching candidates for all pixels are generated by a combination of matching techniques. the matching candidates are then embedded in disparity space, where perceptual organization takes place in 3d neighborhoods and, thus, does not suffer from problems associated with scanline or image neighborhoods. the assumption is that correct matches produce salient, coherent surfaces, while wrong ones do not. matching candidates that are consistent with the surfaces are kept and grouped into smooth layers. thus, we achieve surface segmentation based on geometric and not photometric properties. surface overextensions, which are due to occlusion, can be corrected by removing matches whose projections are not consistent in color with their neighbors of the same surface in both images. finally, the projections of the refined surfaces on both images are used to obtain disparity hypotheses for unmatched pixels. the final disparities are selected after a second tensor voting stage, during which information is propagated from more reliable pixels to less reliable ones. we present results on widely used benchmark stereo pairs.
limitations of non model-based recognition schemes. different approaches to visual object recognition can be divided into two general classes: model-based vs. non model-based schemes. in this paper we establish some limitation on the class of non model-based recognition schemes. we show that every function that is invariant to viewing position of all objects is the trivial (constant) function. it follows that every consistent recognition scheme for recognizing all 3-d objects must in general be model based. the result is extended to recognition schemes that are imperfect (allowed to make mistakes) or restricted to certain classes of objects.
assorted pixels: multi-sampled imaging with structural models. multi-sampled imaging is a general framework for using pixels on an image detector to simultaneously sample multiple dimensions of imaging (space, time, spectrum, brightness, polarization, etc.). the mosaic of red, green and blue spectral filters found in most solid-state color cameras is one example of multi-sampled imaging. we briefly describe how multi-sampling can be used to explore other dimensions of imaging. once such an image is captured, smooth reconstructions along the individual dimensions can be obtained using standard interpolation algorithms. typically, this results in a substantial reduction of resolution (and hence image quality). one can extract significantly greater resolution in each dimension by noting that the light fields associated with real scenes have enormous redundancies within them, causing different dimensions to be highly correlated. hence, multi-sampled images can be better interpolated using local structural models that are learned offline from a diverse set of training images. the specific type of structural models we use are based on polynomial functions of measured image intensities. they are very effective as well as computationally efficient. we demonstrate the benefits of structural interpolation using three specific applications. these are (a) traditional color imaging with a mosaic of color filters, (b) high dynamic range monochrome imaging using a mosaic of exposure filters, and (c) high dynamic range color imaging using a mosaic of overlapping color and exposure filters.
regularization, scale-space, and edge detection filters. computational vision often needs to deal with derivatives of digital images. such derivatives are not intrinsic properties of digital data; a paradigm is required to make them well-defined. normally, a linear filtering is applied. this can be formulated in terms of scale-space, functional minimization, or edge detection filters. the main emphasis of this paper is to connect these theories in order to gain insight in their similarities and differences. we do not want, in this paper, to take part in any discussion of how edge detection must be performed, but will only link some of the current theories. we take regularization (or functional minimization) as a starting point, and show that it boils down to gaussian scale-space if we require scale invariance and a semi-group constraint to be satisfied. this regularization implies the minimization of a functional containing terms up to infinite order of differentiation. if the functional is truncated at second order, the canny-deriche filter arises. it is also shown that higher dimensional regularization boils down to a rotated version of the one dimensional case, when cartesian invariance is imposed and the image is vanishing at the borders. this means that the results from 1d regularization can be easily generalized to higher dimensions. finally we show how an efficient implementation of regularization of order n can be made by recursive filtering using 2n multiplications and additions per output element without introducing any approximation.
the least-squares error for structure from infinitesimal motion. we analyze the least-squares error for structure from motion with a single infinitesimal motion ("structure from optical flow"). we present asymptotic approximations to the noiseless error over two, complementary regions of motion estimates: roughly forward and non-forward translations. our approximations are powerful tools for understanding the error. experiments show that they capture its detailed behavior over the entire range of motions. we illustrate the use of our approximations by deriving new properties of the least-squares error. we generalize the earlier results of jepson/heeger/maybank on the bas-relief ambiguity and of oliensis on the reflected minimum. we explain the error's complexity and its multiple local minima for roughly forward translation estimates (epipoles within the field of view) and identify the factors that make this complexity likely. for planar scenes, we clarify the effects of the two-fold ambiguity, show the existence of a new, double bas-relief ambiguity, and analyze the error's local minima. for nonplanar scenes, we derive simplified error approximations for reasonable assumptions on the image and scene. for example, we show that the error tends to have a simpler form when many points are tracked. we show experimentally that our analysis for zero image noise gives a good model of the error for large noise. we show theoretically and experimentally that the error for projective structure from motion is simpler but flatter than the error for calibrated images.
iterative extensions of the sturm/triggs algorithm: convergence and nonconvergence. we give the first complete theoretical convergence analysis for the iterative extensions of the sturm/triggs algorithm. we show that the simplest extension, siesta, converges to nonsense results. another proposed extension has similar problems, and experiments with “balanced” iterations show that they can fail to converge or become unstable. we present ciesta, an algorithm which avoids these problems. it is identical to siesta except for one simple extra computation. under weak assumptions, we prove that ciesta iteratively decreases an error and approaches fixed points. with one more assumption, we prove it converges uniquely. our results imply that ciesta gives a reliable way of initializing other algorithms such as bundle adjustment. a descent method such as gauss–newton can be used to minimize the ciesta error, combining quadratic convergence with the advantage of minimizing in the projective depths. experiments show that ciesta performs better than other iterations.
a fast approximation of the bilateral filter using a signal processing approach. the bilateral filter is a nonlinear filter that smoothes a signal while preserving strong edges. it has demonstrated great effectiveness for a variety of problems in computer vision and computer graphics, and fast versions have been proposed. unfortunately, little is known about the accuracy of such accelerations. in this paper, we propose a new signal-processing analysis of the bilateral filter which complements the recent studies that analyzed it as a pde or as a robust statistical estimator. the key to our analysis is to express the filter in a higher-dimensional space where the signal intensity is added to the original domain dimensions. importantly, this signal-processing perspective allows us to develop a novel bilateral filtering acceleration using downsampling in space and intensity. this affords a principled expression of accuracy in terms of bandwidth and sampling. the bilateral filter can be expressed as linear convolutions in this augmented space followed by two simple nonlinearities. this allows us to derive criteria for downsampling the key operations and achieving important acceleration of the bilateral filter. we show that, for the same running time, our method is more accurate than previous acceleration techniques. typically, we are able to process a 2 megapixel image using our acceleration technique in less than a second, and have the result be visually similar to the exact computation that takes several tens of minutes. the acceleration is most effective with large spatial kernels. furthermore, this approach extends naturally to color images and cross bilateral filtering.
matching hierarchical structures using association graphs. it is well-known that the problem of matching two relational structures can be posed as an equivalent problem of finding a maximal clique in a (derived) ¿association graph.¿ however, it is not clear how to apply this approach to computer vision problems where the graphs are hierarchically organized, i.e., are trees, since maximal cliques are not constrained to preserve the partial order. here, we provide a solution to the problem of matching two trees by constructing the association graph using the graph-theoretic concept of connectivity. we prove that, in the new formulation, there is a one-to-one correspondence between maximal cliques and maximal subtree isomorphisms. this allows us to cast the tree matching problem as an indefinite quadratic program using the motzkin-straus theorem, and we use ¿replicator¿ dynamical systems developed in theoretical biology to solve it. such continuous solutions to discrete problems are attractive because they can motivate analog and biological implementations. the framework is also extended to the matching of attributed trees by using weighted association graphs. we illustrate the power of the approach by matching articulated and deformed shapes described by shock trees.
perceptual smoothing and segmentation of colour textures. an approach for perceptual segmentation of colour image textures is described. a multiscale representation of the texture image, generated by a multiband smoothing algorithm based on human psychophysical measurements of colour appearance is used as the input. initial segmentation is achieved by applying a clustering algorithm to the image at the coarsest level of smoothing. using these isolated \em core clusters 3d colour histograms are formed and used for probabilistic assignment of all other pixels to the core clusters to form larger clusters and categorise the rest of the image. the process of setting up colour histograms and probabilistic reassignment of the pixels is then propagated through finer levels of smoothing until a full segmentation is achieved at the highest level of resolution.
a paraperspective factorization method for shape and motion recovery. the factorization method, first developed by tomasi and kanade, recovers both the shape of an object and its motion from a sequence of images, using many images and tracking many feature points to obtain highly redundant feature position information. the method robustly processes the feature trajectory information using singular value decomposition (svd), taking advantage of the linear algebraic properties of orthographic projection. however, an orthographic formulation limits the range of motions the method can accommodate. paraperspective projection, first introduced by ohta, is a projection model that closely approximates perspective projection by modeling several effects not modeled under orthographic projection, while retaining linear algebraic properties. our paraperspective factorization method can be applied to a much wider range of motion scenarios, including image sequences containing motion toward the camera and aerial image sequences of terrain taken from a low-altitude airplane.
bidirectional texture contrast function. three dimensional surface corrugations on globally smooth surfaces give rise to brightness modulations of global shading patterns. we study systematic variations of such 3d image texture as a function of illumination and viewing geometry. the 3d texture is especially noticeable near the shadow terminator (for collimated illumination) or near the dark pole (for hemispherical diffuse illumination). we find that a simple micro-facet model, assuming locally lambertian scattering, suffices to robustly describe texture contrast gradients of a large variety (measured and rendered textures; laboratory and field conditions) in a semi-quantitative manner. robust statistical measures of the texture allows one to draw inferences concerning the nature of the light field (collimated to diffuse) and of surface roughness parameters, which can be used as input to the simplest brdf models.
an optimal solution for mobile camera calibration. the problem of determining the intrinsic and extrinsic parameters of a mobile camera is addressed. an optimal solution which consists of the following steps is presented. first, the camera is calibrated in several working positions and, for each position, the corresponding transformation matrix is computed using a method developed by o.d. faugeras and g. toscani (1987). next, optimal intrinsic parameters are searched for all positions. finally, for each separate position, optimal extrinsic parameters are computed by minimizing a mean square error through a closed-form solution. experimental results show that such a technique yields a very large reduction of calibration errors and a considerable gain relative to other existing on-site calibration techniques
bayesian self-calibration of a moving camera. in this paper, a bayesian self-calibration approach using sequential importance sampling (sis) is proposed. given a set of feature correspondences tracked through an image sequence, the joint posterior distributions of both camera extrinsic and intrinsic parameters as well as the scene structure are approximated by a set of samples and their corresponding weights. the critical motion sequences are explicitly considered in the design of the algorithm. the probability of the existence of the critical motion sequence is inferred from the sample and weight set obtained from the sis procedure. no initial guess for the calibration parameters is required. the proposed approach has been extensively tested on both synthetic and real image sequences and satisfactory performance has been observed.
a fourier theory for cast shadows. cast shadows can be significant in many computer vision applications, such as lighting-insensitive recognition and surface reconstruction. nevertheless, most algorithms neglect them, primarily because they involve nonlocal interactions in nonconvex regions, making formal analysis difficult. however, many real instances map closely to canonical configurations like a wall, a v-groove type structure, or a pitted surface. in particular, we experiment with 3d textures like moss, gravel, and a kitchen sponge, whose surfaces include canonical configurations like v-grooves. this paper takes a first step toward a formal analysis of cast shadows, showing theoretically that many configurations can be mathematically analyzed using convolutions and fourier basis functions. our analysis exposes the mathematical convolution structure of cast shadows and shows strong connections to recent signal-processing frameworks for reflection and illumination.
a new image registration technique with free boundary constraints: application to mammography. in this paper, a new image-matching mathematical model is presented with its application to mammogram registration. in a variatianal framework, an energy minimization problem is formulated and a multigrid resolution algorithm is designed. the model focuses on the matching of regions of interest. it also combines several constraints which are both intensity- and segmentation-based. a new feature of our model is combining region matching and segmentation by formulation of the energy minimization problem with free boundary conditions. moreover, the energy has a new registration constraint. the performances of the new model and an equivalent model with fixed boundary conditions are compared on simulated mammogram pairs. it is shown that the model with free boundary is more robust to initialization inaccuracies than the one with fixed boundary conditions. both models are applied to several real bilateral mammogram pairs. the model ability to compensate significantly for some normal differences between mammograms is illustrated. results suggest that the new model could enable some improvements of mammogram comparisons and tumor detection system performances.
area and lenght preserving geometric invariant scale-spaces. in this paper, area preserving multi-scale representations of planar curves are described. this allows smoothing without shrinkage at the same time preserving all the scale-space properties. the representations are obtained deforming the curve via geometric heat flows while simultaneously magnifying the plane by a homethety which keeps the enclosed area constant. when the euclidean geometric heat flow is used, the resulting representation is euclidean invariant, and similarly it is affine invariant when the affine one is used. the flows are geometrically intrinsic to the curve, and exactly satisfy all the basic requirements of scale-space representations. in the case of the euclidean heat flow, it is completely local as well. the same approach is used to define length preserving geometric flows. a similarity (scale) invariant geometric heat flow is studied as well in this work.
object level grouping for video shots. we describe a method for automatically obtaining object representations suitable for retrieval from generic video shots. the object representation consists of an association of frame regions. these regions provide exemplars of the object's possible visual appearances.two ideas are developed: (i) associating regions within a single shot to represent a deforming object; (ii) associating regions from the multiple visual aspects of a 3d object, thereby implicitly representing 3d structure. for the association we exploit temporal continuity (tracking) and wide baseline matching of affine covariant regions.in the implementation there are three areas of novelty: first, we describe a method to repair short gaps in tracks. second, we show how to join tracks across occlusions (where many tracks terminate simultaneously). third, we develop an affine factorization method that copes with motion degeneracy.we obtain tracks that last throughout the shot, without requiring a 3d reconstruction. the factorization method is used to associate tracks into object-level groups, with common motion. the outcome is that separate parts of an object that are not simultaneously visible (such as the front and back of a car, or the front and side of a face) are associated together. in turn this enables object-level matching and recognition throughout a video.we illustrate the method on the feature film "groundhog day." examples are given for the retrieval of deforming objects (heads, walking people) and rigid objects (vehicles, locations).
on degeneracy of linear reconstruction from three views: linear line complex and applications. this paper investigates the linear degeneracies of projective structure estimation from line features across three views. we show that the rank of the linear system of equations for recovering the trilinear tensor of three views reduces to 23 (instead of 26) when the scene is a linear line complex (a set of lines in space intersecting at a common line). the llc situation is only linearly degenerate, and one can obtain a unique solution when the admissibility constraints of the tensor are accounted for. the line configuration described by an llc, rather than being some obscure case, is in fact quite typical. it includes, as a particular example, the case of a camera moving down a hallway in an office environment or down an urban street. furthermore, an llc situation may occur as an artifact such as in direct estimation from spatio-temporal derivatives of image brightness. therefore, an investigation into degeneracies and their remedy is important also in practice.
data and model-driven selection using color regions. a key problem in model-based object recognition is selection, namely, the problem of determining which regions in the image are likely to come from a single object. in this paper we present an approach that uses color as a cue to perform selection either based solely on image-data (data-driven), or based on the knowledge of the color description of the model (model-driven). specifically, the paper presents a method of color specification in terms of perceptual color categories and shows its relevance for the task of selection. the color categories are used to develop a fast region segmentation algorithm that extracts perceptual color regions in images. the color regions extracted form the basis for performing data and model-driven selection. data-driven selection is achieved by selecting salient color regions as judged by a color-saliency measure that emphasizes attributes that are also important in human color perception. the approach to model-driven selection, on the other hand, exploits the color and other region information in the 3d model object to locate instances of the object in a given image. the approach presented tolerates some of the problems of occlusion, pose and illumination changes that make a model instance in an image appear different from its original description. finally, the utility of color-based selection is demonstrated by showing the extent of search reduction possible when color-based selection is integrated with a recognition system.
shape ambiguities in structure from motion. this paper examines the fundamental ambiguities and uncertainties inherent in recovering structure from motion. by examining the eigenvectors associated with null or small eigenvalues of the hessian matrix, we can quantify the exact nature of these ambiguities and predict how they affect the accuracy of the reconstructed shape. our results for orthographic cameras show that the bas-relief ambiguity is significant even with many images, unless a large amount of rotation is present. similar results for perspective cameras suggest that three or more frames and a large amount of rotation are required for metrically accurate reconstruction.
stereo without search. search is not inherent in the correspondence problem. we propose a representation of images, called intrinsic curves, that combines the ideas of associative storage of images with connectedness of the representation: intrinsic curves are the paths that a set of local image descriptors trace as an image scanline is traversed from left to right. curves become surfaces when full images are considered instead of scanlines. because only the path in the space of descriptors is used for matching, intrinsic curves lose track of space, and are invariant with respect to disparity under ideal circumstances. establishing stereo correspondences then becomes a trivial lookup problem. we also show how to use intrinsic curves to match real images in the presence of noise, brightness bias, contrast fluctuations, and moderate geometric distortion, and we show how intrinsic curves can be used to deal with image ambiguity and occlusions. we carry out experiments on single-scanline matching to prove the feasibility of the approach and illustrate its main features.
impsac: synthesis of importance sampling and random sample consensus. this paper proposes a new method for recovery of epipolar geometry and feature correspondence between images which have undergone a significant deformation, either due to large rotation or wide baseline of the cameras. the method also encodes the uncertainty by providing an arbitrarily close approximation to the posterior distribution of the two view relation. the method operates on a pyramid from coarse to fine resolution, thus raising the problem of how to propagate information from one level to another in a statistically consistent way. the distribution of the parameters at each resolution is encoded nonparametrically as a set of particles. at the coarsest level, a ransac-mcmc estimator is used to initialize this set of particles, the posterior can then be approximated as a mixture of gaussians fitted to these particles. the distribution at a coarser level influences the distribution at a finer level using the technique of sampling-importance-resampling (sir) and mcmc, which allows for asymptotically correct approximations of the posterior distribution. the estimate of the posterior distribution at the level above is being used as the importance sampling function to generate a new set of particles, which can be further improved by mcmc. it is shown that the method is superior to previous single resolution ransac-style feature matchers.
topological reconstruction of a smooth manifold-solid from its occluding contour. this paper describes a simple construction for building a combinatorial model of a smooth manifold-solid from a labeled figure representing its occluding contour. the motivation is twofold. first, deriving the combinatorial model is an essential intermediate step in the visual reconstruction of solid-shape from image contours. a description of solid-shape consists of a metric and a topological component. both are necessary: the metric component specifies how the topological component is embedded in three-dimensional space. the {\it paneling construction} described in this paper is a procedure for generating the topological component from a labeled figure representing the occluding contour. second, the existence of this construction establishes the sufficiency of a labeling scheme for line-drawings of smooth solid-objects originally proposed by huffman. by sufficiency, it is meant that every set of closed plane-curves satisfying this labeling scheme is shown to correspond to a generic view of a manifold-solid. together with the whitney theorem, this confirms that huffman''s labeling scheme correctly distinguishes possible from impossible solid-objects.
a comparison of measures for detecting natural shapes in cluttered backgrounds. we propose a new measure of perceptual saliency and quantitatively compare its ability to detect natural shapes in cluttered backgrounds to five previously proposed measures. as defined in the new measure, the saliency of an edge is the fraction of closed random walks which contain that edge. the transition-probability matrix defining the random walk between edges is based on a distribution of natural shapes modeled by a stochastic motion. each of the saliency measures in our comparison is a function of a set of affinity values assigned to pairs of edges. although the authors of each measure define the affinity between a pair of edges somewhat differently, all incorporate the gestalt principles of good-continuation and proximity in some form. in order to make the comparison meaningful, we use a single definition of affinity and focus instead on the performance of the different functions for combining affinity values. the primary performance criterion is accuracy. we compute false-positive rates in classifying edges as signal or noise for a large set of test figures. in almost every case, the new measure significantly outperforms previous measures.
a closed-form solution to non-rigid shape and motion recovery. recovery of three dimensional (3d) shape and motion of non-static scenes from a monocular video sequence is important for applications like robot navigation and human computer interaction. if every point in the scene randomly moves, it is impossible to recover the non-rigid shapes. in practice, many non-rigid objects, e.g. the human face under various expressions, deform with certain structures. their shapes can be regarded as a weighted combination of certain shape bases. shape and motion recovery under such situations has attracted much interest. previous work on this problem (bregler, c., hertzmann, a., and biermann, h. 2000. in proc. int. conf. computer vision and pattern recognition; brand, m. 2001. in proc. int. conf. computer vision and pattern recognition; torresani, l., yang, d., alexander, g., and bregler, c. 2001. in proc. int. conf. computer vision and pattern recognition) utilized only orthonormality constraints on the camera rotations (rotation constraints). this paper proves that using only the rotation constraints results in ambiguous and invalid solutions. the ambiguity arises from the fact that the shape bases are not unique. an arbitrary linear transformation of the bases produces another set of eligible bases. to eliminate the ambiguity, we propose a set of novel constraints, basis constraints, which uniquely determine the shape bases. we prove that, under the weak-perspective projection model, enforcing both the basis and the rotation constraints leads to a closed-form solution to the problem of non-rigid shape and motion recovery. the accuracy and robustness of our closed-form solution is evaluated quantitatively on synthetic data and qualitatively on real video sequences.
shape and view independent reflectance map from multiple views. we consider the problem of estimating the 3d shape and reflectance properties of an object made of a single material from a set of calibrated views. to model the reflectance, we propose to use the view independent reflectance map (virm), which is a representation of the joint effect of the diffuse+specular bidirectional reflectance distribution function (brdf) and the environment illumination. the object shape is parameterized using a triangular mesh. we pose the estimation problem as minimizing the cost of matching input images, and the images synthesized using the shape and virm estimates. we show that by enforcing a constant value of virm as a global constraint, we can minimize the cost function by iterating between the virm and shape estimation. experimental results on both synthetic and real objects show that our algorithm can recover both the 3d shape and the diffuse/specular reflectance information. our algorithm does not require the light sources to be known or calibrated. the estimated virm can be used to predict the appearances of objects with the same material from novel viewpoints and under transformed illumination.
keypoint signatures for fast learning and recognition. statistical learning techniques have been used to dramatically speed-up keypoint matching by training a classifier to recognize a specific set of keypoints. however, the training itself is usually relatively slow and performed offline. although methods have recently been proposed to train the classifier online, they can only learn a very limited number of new keypoints. this represents a handicap for real-time applications, such as simultaneous localization and mapping (slam), which require incremental addition of arbitrary numbers of keypoints as they become visible.in this paper, we overcome this limitation and propose a descriptor that can be learned online fast enough to handle virtually unlimited numbers of keypoints. it relies on the fact that if we train a randomized tree classifier to recognize a number of keypoints extracted from an image database, all other keypoints can be characterized in terms of their response to these classification trees. this signature is fast to compute and has a discriminative power that is comparable to that of the much slower sift descriptor.
some objects are more equal than others: measuring and predicting importance. we observe that everyday images contain dozens of objects, and that humans, in describing these images, give different priority to these objects. we argue that a goal of visual recognition is, therefore, not only to detect and classify objects but also to associate with each a level of priority which we call `importance'. we propose a definition of importance and show how this may be estimated reliably from data harvested from human observers. we conclude by showing that a first-order estimate of importance may be computed from a number of simple image region measurements and does not require access to image meaning.
weakly supervised object localization with stable segmentations. multiple instance learning (mil) provides a framework for training a discriminative classifier from data with ambiguous labels. this framework is well suited for the task of learning object classifiers from weakly labeled image data, where only the presence of an object in an image is known, but not its location. some recent work has explored the application of mil algorithms to the tasks of image categorization and natural scene classification. in this paper we extend these ideas in a framework that uses mil to recognize and localize objects in images. to achieve this we employ state of the art image descriptors and multiple stable segmentations. these components, combined with a powerful mil algorithm, form our object recognition system called milss. we show highly competitive object categorization results on the caltech dataset. to evaluate the performance of our algorithm further, we introduce the challenging landmarks-18 dataset, a collection of photographs of famous landmarks from around the world. the results on this new dataset show the great potential of our proposed algorithm.
using multiple hypotheses to improve depth-maps for multi-view stereo. we propose an algorithm to improve the quality of depth-maps used for multi-view stereo (mvs). many existing mvs techniques make use of a two stage approach which estimates depth-maps from neighbouring images and then merges them to extract a final surface. often the depth-maps used for the merging stage will contain outliers due to errors in the matching process. traditional systems exploit redundancy in the image sequence (the surface is seen in many views), in order to make the final surface estimate robust to these outliers. in the case of sparse data sets there is often insufficient redundancy and thus performance degrades as the number of images decreases. in order to improve performance in these circumstances it is necessary to remove the outliers from the depth-maps. we identify the two main sources of outliers in a top performing algorithm: (1) spurious matches due to repeated texture and (2) matching failure due to occlusion, distortion and lack of texture. we propose two contributions to tackle these failure modes. firstly, we store multiple depth hypotheses and use a spatial consistency constraint to extract the true depth. secondly, we allow the algorithm to return an unknown state when the a true depth estimate cannot be found. by combining these in a discrete label mrf optimisation we are able to obtain high accuracy depth-maps with low numbers of outliers. we evaluate our algorithm in a multi-view stereo framework and find it to confer state-of-the-art performance with the leading techniques, in particular on the standard evaluation sparse data sets.
geos: geodesic image segmentation. this paper presents geos, a new algorithm for the efficient segmentation of n-dimensional image and video data.the segmentation problem is cast as approximate energy minimization in a conditional random field. a new, parallel filtering operator built upon efficient geodesic distance computation is used to propose a set of spatially smooth, contrast-sensitive segmentation hypotheses. an economical search algorithm finds the solution with minimum energy within a sensible and highly restricted subset of all possible labellings.advantages include: i) computational efficiency with high segmentation accuracy; ii) the ability to estimate an approximation to the posterior over segmentations; iii) the ability to handle generally complex energy models. comparison with max-flow indicates up to 60 times greater computational efficiency as well as greater memory efficiency.geos is validated quantitatively and qualitatively by thorough comparative experiments on existing and novel ground-truth data. numerous results on interactive and automatic segmentation of photographs, video and volumetric medical image data are presented.
3d face recognition by local shape difference boosting. a new approach, called collective shape difference classifier (csdc), is proposed to improve the accuracy and computational efficiency of 3d face recognition. the csdc learns the most discriminative local areas from the pure shape difference map (psdm) and trains them as weak classifiers for assembling a collective strong classifier using the real-boosting approach. the psdm is established between two 3d face models aligned by a posture normalization procedure based on facial features. the model alignment is self-dependent, which avoids registering the probe face against every different gallery face during the recognition, so that a high computational speed is obtained. the experiments, carried out on the frgc v2 and bu-3dfe databases, yield rank-1 recognition rates better than 98%. each recognition against a gallery with 1000 faces only needs about 3.05 seconds. these two experimental results together with the high performance recognition on partial faces demonstrate that our algorithm is not only effective but also efficient.
velocity-guided tracking of deformable contours in three dimensional space. this paper presents a 3d active contour model for boundary detection and tracking of non-rigid objects, which applies stereo vision and motion analysis to the class of energy-minimizing deformable contour models, known as snakes. the proposed contour evolves in three-dimensional space in reaction to a 3d potential function, which is derived by projecting the contour onto the 2d stereo images. the potential function is augmented by a kinetic term, which is related to the velocity field along the contour. this term is used to guide the inter-image contour displacement. the incorporation of inter-frame velocity estimates in the tracking algorithm is especially important for contours which evolve in 3d space, where the added freedom of motion can easily result in loss of tracking. the proposed scheme incorporates local velocity information seamlessly in the snake model, with little computational overhead, and does not require exogenous computation of the optical flow or related quantities in each image. the resulting algorithm is shown to provide good tracking performance with only one iteration per frame, which provides a considerable advantage for real time operation.
viewpoint invariant pedestrian recognition with an ensemble of localized features. viewpoint invariant pedestrian recognition is an important yet under-addressed problem in computer vision. this is likely due to the difficulty in matching two objects with unknown viewpoint and pose. this paper presents a method of performing viewpoint invariant pedestrian recognition using an efficiently and intelligently designed object representation, the ensemble of localized features (elf). instead of designing a specific feature by hand to solve the problem, we define a feature space using our intuition about the problem and let a machine learning algorithm find the best representation. we show how both an object class specific representation and a discriminative recognition model can be learned using the adaboost algorithm. this approach allows many different kinds of simple features to be combined into a single similarity function. the method is evaluated using a viewpoint invariant pedestrian recognition dataset and the results are shown to be superior to all previous benchmarks for both recognition and reacquisition of pedestrians.
a probabilistic approach to integrating multiple cues in visual tracking. this paper presents a novel probabilistic approach to integrating multiple cues in visual tracking. we perform tracking in different cues by interacting processes. each process is represented by a hidden markov model, and these parallel processes are arranged in a chain topology. the resulting linked hidden markov models naturally allow the use of particle filters and belief propagation in a unified framework. in particular, a target is tracked in each cue by a particle filter, and the particle filters in different cues interact via a message passing scheme. the general framework of our approach allows a customized combination of different cues in different situations, which is desirable from the implementation point of view. our examples selectively integrate four visual cues including color, edges, motion and contours. we demonstrate empirically that the ordering of the cues is nearly inconsequential, and that our approach is superior to other approaches such as independent integration and hierarchical integration in terms of flexibility and robustness.
multi-stage contour based detection of deformable objects. we present an efficient multi stage approach to detection of deformable objects in real, cluttered images given a single or few hand drawn examples as models. the method handles deformations of the object by first breaking the given model into segments at high curvature points. we allow bending at these points as it has been studied that deformation typically happens at high curvature points. the broken segments are then scaled, rotated, deformed and searched independently in the gradient image. point maps are generated for each segment that represent the locations of the matches for that segment. we then group k points from the point maps of k adjacent segments using a cost function that takes into account local scale variations as well as inter-segment orientations. these matched groups yield plausible locations for the objects. in the fine matching stage, the entire object contour in the localized regions is built from the k-segment groups and given a comprehensive score in a method that uses dynamic programming. an evaluation of our algorithm on a standard dataset yielded results that are better than published work on the same dataset. at the same time, we also evaluate our algorithm on additional images with considerable object deformations to verify the robustness of our method.
a generative shape regularization model for robust face alignment. in this paper, we present a robust face alignment system that is capable of dealing with exaggerating expressions, large occlusions, and a wide variety of image noises. the robustness comes from our shape regularization model, which incorporates constrained nonlinear shape prior, geometric transformation, and likelihood of multiple candidate landmarks in a three-layered generative model. the inference algorithm iteratively examines the best candidate positions and updates face shape and pose. this model can effectively recover sufficient shape details from very noisy observations. we demonstrate the performance of this approach on two public domain databases and a large collection of real-world face photographs.
learning spatial context: using stuff to find things. the sliding window approach of detecting rigid objects (such as cars) is predicated on the belief that the object can be identified from the appearance in a small region around the object. other types of objects of amorphous spatial extent (e.g., trees, sky), however, are more naturally classified based on texture or color. in this paper, we seek to combine recognition of these two types of objects into a system that leverages "context" toward improving detection. in particular, we cluster image regions based on their ability to serve as context for the detection of objects. rather than providing an explicit training set with region labels, our method automatically groups regions based on both their appearance and their relationships to the detections in the image. we show that our things and stuff (tas) context model produces meaningful clusters that are readily interpretable, and helps improve our detection ability over state-of-the-art detectors. we also present a method for learning the active set of relationships for a particular dataset. we present results on object detection in images from the pascal voc 2005/2006 datasets and on the task of overhead car detection in satellite images, demonstrating significant improvements over state-of-the-art detectors.
learning for optical flow using stochastic optimization. we present a technique for learning the parameters of a continuous-state markov random field (mrf) model of optical flow, by minimizing the training loss for a set of ground-truth images using simultaneous perturbation stochastic approximation (spsa). the use of spsa to directly minimize the training loss offers several advantages over most previous work on learning mrf models for low-level vision, which instead seek to maximize the likelihood of the data given the model parameters. in particular, our approach explicitly optimizes the error criterion used to evaluate the quality of the flow field, naturally handles missing data values in the ground truth, and does not require the kinds of approximations that current methods use to address the intractable nature of maximum-likelihood estimation for such problems. we show that our method achieves state-of-the-art results and requires only a very small number of training images. we also find that our method generalizes well to unseen data, including data with quite different characteristics than the training set.
recovering light directions and camera poses from a single sphere. this paper introduces a novel method for recovering both the light directions and camera poses from a single sphere. traditional methods for estimating light directions using spheres either assume both the radius and center of the sphere being known precisely, or they depend on multiple calibrated views to recover these parameters. it will be shown in this paper that the light directions can be uniquely determined from the specular highlights observed in a single view of a sphere without knowing or recovering the exact radius and center of the sphere. besides, if the sphere is being observed by multiple cameras, its images will uniquely define the translation vector of each camera from a common world origin centered at the sphere center. it will be shown that the relative rotations between the cameras can be recovered using two or more light directions estimated from each view. closed form solutions for recovering the light directions and camera poses are presented, and experimental results on both synthetic and real data show the practicality of the proposed method.
human activity recognition with metric learning. this paper proposes a metric learning based approach for human activity recognition with two main objectives: (1) reject unfamiliar activities and (2) learn with few examples. we show that our approach outperforms all state-of-the-art methods on numerous standard datasets for traditional action classification problem. furthermore, we demonstrate that our method not only can accurately label activities but also can reject unseen activities and can learn from few examples with high accuracy. we finally show that our approach works well on noisy youtube videos.
surface visibility probabilities in 3d cluttered scenes. many methods for 3d reconstruction in computer vision rely on probability models, for example, bayesian reasoning. here we introduce a probability model of surface visibilities in densely cluttered 3d scenes. the scenes consist of a large number of small surfaces distributed randomly in a 3d view volume. an example is the leaves or branches on a tree. we derive probabilities for surface visibility, instantaneous image velocity under egomotion, and binocular half---occlusions in these scenes. the probabilities depend on parameters such as scene depth, object size, 3d density, observer speed, and binocular baseline. we verify the correctness of our models using computer graphics simulations, and briefly discuss applications of the model to stereo and motion.
videocut: removing irrelevant frames by discovering the object of interest. we propose a novel method for removing irrelevant frames from a video given user-provided frame-level labeling for a very small number of frames. we first hypothesize a number of candidate areas which possibly contain the object of interest, and then figure out which area(s) truly contain the object of interest. our method enjoys several favorable properties. first, compared to approaches where a single descriptor is used to describe a whole frame, each area's feature descriptor has the chance of genuinely describing the object of interest, hence it is less affected by background clutter. second, by considering the temporal continuity of a video instead of treating the frames as independent, we can hypothesize the location of the candidate areas more accurately. third, by infusing prior knowledge into the topic-motion model, we can precisely follow the trajectory of the object of interest. this allows us to largely reduce the number of candidate areas and hence reduce the chance of overfitting the data during learning. we demonstrate the effectiveness of the method by comparing it to several other semi-supervised learning approaches on challenging video clips.
an experimental comparison of discrete and continuous shape optimization methods. shape optimization is a problem which arises in numerous computer vision problems such as image segmentation and multiview reconstruction. in this paper, we focus on a certain class of binary labeling problems which can be globally optimized both in a spatially discrete setting and in a spatially continuous setting. the main contribution of this paper is to present a quantitative comparison of the reconstruction accuracy and computation times which allows to assess some of the strengths and limitations of both approaches. we also present a novel method to approximate length regularity in a graph cut based framework: instead of using pairwise terms we introduce higher order terms. these allow to represent a more accurate discretization of the l 2-norm in the length term.
sparse structures in l-infinity norm minimization for structure and motion reconstruction. this paper presents a study on how to numerically solve the feasibility test problem which is the core of the bisection algorithm for minimizing the l &infin; error functions. we consider a strategy that minimizes the maximum infeasibility. the minimization can be performed using several numerical computation methods, among which the barrier method and the primal-dual method are examined. in both of the methods, the inequalities are sequentially approximated by log-barrier functions. an initial feasible solution is found easily by the construction of the feasibility problem, and newton-style update computes the optimal solution iteratively. when we apply the methods to the problem of estimating the structure and motion, every newton update requires solving a very large system of linear equations. we show that the sparse bundle-adjustment technique, previously developed for structure and motion estimation, can be utilized during the newton update. in the primal-dual interior-point method, in contrast to the barrier method, the sparse structure is all destroyed due to an extra constraint introduced for finding an initial solution. however, we show that this problem can be overcome by utilizing the matrix inversion lemma which allows us to exploit the sparsity in the same manner as in the barrier method. we finally show that the sparsity appears in both of the l &infin; formulations - linear programming and second-order cone programming.
online sparse matrix gaussian process regression and vision applications. we present a new gaussian process inference algorithm, called online sparse matrix gaussian processes (osmgp), and demonstrate its merits with a few vision applications. the osmgp is based on the observation that for kernels with local support, the gram matrix is typically sparse. maintaining and updating the sparse cholesky factor of the gram matrix can be done efficiently using givens rotations. this leads to an exact, online algorithm whose update time scales linearly with the size of the gram matrix. further, if approximate updates are permissible, the cholesky factor can be maintained at a constant size using hyperbolic rotations to remove certain rows and columns corresponding to discarded training examples. we demonstrate that, using these matrix downdates, online hyperparameter estimation can be included without affecting the linear runtime complexity of the algorithm. the osmgp algorithm is applied to head-pose estimation and visual tracking problems. experimental results demonstrate that the proposed method is accurate, efficient and generalizes well using online learning.
learning to localize objects with structured output regression. sliding window classifiers are among the most successful and widely applied techniques for object localization. however, training is typically done in a way that is not specific to the localization task. first a binary classifier is trained using a sample of positive and negative examples, and this classifier is subsequently applied to multiple regions within test images. we propose instead to treat object localization in a principled way by posing it as a problem of predicting structured data: we model the problem not as binary classification, but as the prediction of the bounding box of objects located in images. the use of a joint-kernel framework allows us to formulate the training procedure as a generalization of an svm, which can be solved efficiently. we further improve computational efficiency by using a branch-and-bound strategy for localization during both training and testing. experimental evaluation on the pascal voc and tu darmstadt datasets show that the structured training procedure improves performance over binary training as well as the best previously published scores.
robust multiple structures estimation with j-linkage. this paper tackles the problem of fitting multiple instances of a model to data corrupted by noise and outliers. the proposed solution is based on random sampling and conceptual data representation. each point is represented with the characteristic function of the set of random models that fit the point. a tailored agglomerative clustering, called j-linkage, is used to group points belonging to the same model. the method does not require prior specification of the number of models, nor it necessitate parameters tuning. experimental results demonstrate the superior performances of the algorithm.
something old, something new, something borrowed, something blue. my first paper of a "computer vision" signature (on invariants related to optic flow) dates from 1975. i have published in computer vision (next to work in cybernetics, psychology, physics, mathematics and philosophy) till my retirement earlier this year (hence the slightly blue feeling), thus my career roughly covers the history of the field. "vision" has diverse connotations. the fundamental dichotomy is between "optically guided action" and "visual experience". the former applies to much of biology and computer vision and involves only concepts from science and engineering (e.g., "inverse optics"), the latter involves intention and meaning and thus additionally involves concepts from psychology and philosophy. david marr's notion of "vision" is an uneasy blend of the two: on the one hand the goal is to create a "representation of the scene in front of the eye" (involving intention and meaning), on the other hand the means by which this is attempted are essentially "inverse optics". although this has nominally become something of the "standard model" of cv, it is actually incoherent. it is the latter notion of "vision" that has always interested me most, mainly because one is still grappling with basic concepts. it has been my aspiration to turn it into science, although in this i failed. yet much has happened (something old) and is happening now (something new). i will discuss some of the issues that seem crucial to me, mostly illustrated through my own work, though i shamelessly borrow from friends in the cv community where i see fit.
a segmentation based variational model for accurate optical flow estimation. segmentation has gained in popularity in stereo matching. however, it is not trivial to incorporate it in optical flow estimation due to the possible non-rigid motion problem. in this paper, we describe a new optical flow scheme containing three phases. first, we partition the input images and integrate the segmentation information into a variational model where each of the segments is constrained by an affine motion. then the errors brought in by segmentation are measured and stored in a confidence map. the final flow estimation is achieved through a global optimization phase that minimizes an energy function incorporating the confidence map. extensive experiments show that the proposed method not only produces quantitatively accurate optical flow estimates but also preserves sharp motion boundaries, which makes the optical flow result usable in a number of computer vision applications, such as image/video segmentation and editing.
robust optimal pose estimation. we study the problem of estimating the position and orientation of a calibrated camera from an image of a known scene. a common problem in camera pose estimation is the existence of false correspondences between image features and modeled 3d points. existing techniques such as ransac to handle outliers have no guarantee of optimality. in contrast, we work with a natural extension of the l &infin; norm to the outlier case. using a simple result from classical geometry, we derive necessary conditions for l &infin; optimality and show how to use them in a branch and bound setting to find the optimum and to detect outliers. the algorithm has been evaluated on synthetic as well as real data showing good empirical performance. in addition, for cases with no outliers, we demonstrate shorter execution times than existing optimal algorithms.
integration of multiview stereo and silhouettes via convex functionals on convex domains. we propose a convex framework for silhouette and stereo fusion in 3d reconstruction from multiple images. the key idea is to show that the reconstruction problem can be cast as one of minimizing a convex functional where the exact silhouette consistency is imposed as a convex constraint that restricts the domain of admissible functions. as a consequence, we can retain the original stereo-weighted surface area as a cost functional without heuristic modifications by balloon terms or other strategies, yet still obtain meaningful (nonempty) global minimizers. compared to previous methods, the introduced approach does not depend on initialization and leads to a more robust numerical scheme by removing the bias near the visual hull boundary. we propose an efficient parallel implementation of this convex optimization problem on a graphics card. based on a photoconsistency map and a set of image silhouettes we are therefore able to compute highly-accurate and silhouette-consistent reconstructions for challenging real-world data sets in less than one minute.
shape matching by segmentation averaging. we use segmentations to match images by shape. to address the unreliability of segmentations, we give a closed form approximation to an average over all segmentations. our technique has many extensions, yielding new algorithms for tracking, object detection, segmentation, and edge-preserving smoothing. for segmentation, instead of a maximum a posteriori approach, we compute the "central" segmentation minimizing the average distance to all segmentations of an image. our methods for segmentation and object detection perform competitively, and we also show promising results in tracking and edge---preserving smoothing.
analysis of building textures for reconstructing partially occluded facades. as part of an architectural modeling project, this paper investigates the problem of understanding and manipulating images of buildings. our primary motivation is to automatically detect and seamlessly remove unwanted foreground elements from urban scenes. without explicit handling, these objects will appear pasted as artifacts on the model. recovering the building facade in a video sequence is relatively simple because parallax induces foreground/background depth layers, but here we consider static images only. we develop a series of methods that enable foreground removal from images of buildings or brick walls. the key insight is to use a priori knowledge about grid patterns on building facades that can be modeled as near regular textures (nrt). we describe a markov random field (mrf) model for such textures and introduce a markov chain monte carlo (mcmc) optimization procedure for discovering them. this simple spatial rule is then used as a starting point for inference of missing windows, facade segmentation, outlier identification, and foreground removal.
efficient dense scene flow from sparse or dense stereo data. this paper presents a technique for estimating the three-dimensional velocity vector field that describes the motion of each visible scene point (scene flow). the technique presented uses two consecutive image pairs from a stereo sequence. the main contribution is to decouple the position and velocity estimation steps, and to estimate dense velocities using a variational approach. we enforce the scene flow to yield consistent displacement vectors in the left and right images. the decoupling strategy has two main advantages: firstly, we are independent in choosing a disparity estimation technique, which can yield either sparse or dense correspondences, and secondly, we can achieve frame rates of 5 fps on standard consumer hardware. the approach provides dense velocity estimates with accurate results at distances up to 50 meters.
similarity features for facial event analysis. each facial event will give rise to complex facial appearance variation. in this paper, we propose similarity features to describe the facial appearance for video-based facial event analysis. inspired by the kernel features, for each sample, we compare it with the reference set with a similarity function, and we take the log-weighted summarization of the similarities as its similarity feature. due to the distinctness of the apex images of facial events, we use their cluster-centers as the references. in order to capture the temporal dynamics, we use the k-means algorithm to divide the similarity features into several clusters in temporal domain, and each cluster is modeled by a gaussian distribution. based on the gaussian models, we further map the similarity features into dynamic binary patterns to handle the issue of time resolution, which embed the time-warping operation implicitly. the haar-like descriptor is used to extract the visual features of facial appearance, and adaboost is performed to learn the final classifiers. extensive experiments carried on the cohn-kanade database show the promising performance of the proposed method.
estimating 3d face model and facial deformation from a single image based on expression manifold optimization. facial expression modeling is central to facial expression recognition and expression synthesis for facial animation. previous works reported that modeling the facial expression with low-dimensional manifold is more appropriate than using a linear subspace. in this paper, we propose a manifold-based 3d face reconstruction approach to estimating the 3d face model and the associated expression deformation from a single face image. in the training phase, we build a nonlinear 3d expression manifold from a large set of 3d facial expression models to represent the facial shape deformations due to facial expressions. then a gaussian mixture model in this manifold is learned to represent the distribution of expression deformation. by combining the merits of morphable neutral face model and the low-dimensional expression manifold, we propose a new algorithm to reconstruct the 3d face geometry as well as the 3d shape deformation from a single face image with expression in an energy minimization framework. experimental results on cmu-pie image database and fg-net video database are shown to validate the effectiveness and accuracy of the proposed algorithm.
simultaneous motion detection and background reconstruction with a mixed-state conditional markov random field. we consider the problem of motion detection by background subtraction. an accurate estimation of the background is only possible if we locate the moving objects; meanwhile, a correct motion detection is achieved if we have a good available background model. this work proposes a new direction in the way such problems are considered. the main idea is to formulate this class of problem as a joint decision-estimation unique step. the goal is to exploit the way two processes interact, even if they are of a dissimilar nature (symbolic-continuous), by means of a recently introduced framework called mixed-state markov random fields. in this paper, we will describe the theory behind such a novel statistical framework, that subsequently will allows us to formulate the specific joint problem of motion detection and background reconstruction. experiments on real sequences and comparisons with existing methods will give a significant support to our approach. further implications for video sequence inpainting will be also discussed.
modeling and recognition of landmark image collections using iconic scene graphs. this paper presents an approach for modeling landmark sites such as the statue of liberty based on large-scale contaminated image collections gathered from the internet. our system combines 2d appearance and 3d geometric constraints to efficiently extract scene summaries, build 3d models, and recognize instances of the landmark in new test images. we start by clustering images using low-dimensional global "gist" descriptors. next, we perform geometric verification to retain only the clusters whose images share a common 3d structure. each valid cluster is then represented by a single iconic view, and geometric relationships between iconic views are captured by an iconic scene graph. in addition to serving as a compact scene summary, this graph is used to guide structure from motion to efficiently produce 3d models of the different aspects of the landmark. the set of iconic images is also used for recognition, i.e., determining whether new test images contain the landmark. results on three data sets consisting of tens of thousands of images demonstrate the potential of the proposed approach.
estimating geo-temporal location of stationary cameras using shadow trajectories. using only shadow trajectories of stationary objects in a scene, we demonstrate that using a set of six or more photographs are sufficient to accurately calibrate the camera. moreover, we present a novel application where, using only three points from the shadow trajectory of the objects, one can accurately determine the geo-location of the camera, up to a longitude ambiguity, and also the date of image acquisition without using any gps or other special instruments. we refer to this as "geo-temporal localization". we consider possible cases where ambiguities can be removed if additional information is available. our method does not require any knowledge of the date or the time when the pictures are taken, and geo-temporal information is recovered directly from the images. we demonstrate the accuracy of our technique for both steps of calibration and geo-temporal localization using synthetic and real data.
search space reduction for mrf stereo. we present an algorithm to reduce per-pixel search ranges for markov random fields-based stereo algorithms. our algorithm is based on the intuitions that reliably matched pixels need less regularization in the energy minimization and neighboring pixels should have similar disparity search ranges if their pixel values are similar. we propose a novel bi-labeling process to classify reliable and unreliable pixels that incorporate left-right consistency checks. we then propagate the reliable disparities into unreliable regions to form a complete disparity map and construct per-pixel search ranges based on the difference between the disparity map after propagation and the one computed from a winner-take-all method. experimental results evaluated on the middlebury stereo benchmark show our proposed algorithm is able to achieve 77% average reduction rate while preserving satisfactory accuracy.
brain hallucination. in this paper, we investigate brain hallucination, or generating a high resolution brain image from an input low-resolution image, with the help of another high resolution brain image. contrary to interpolation techniques, the reconstruction process is based on a physical model of image acquisition. our contribution is a new regularization approach that uses an example-based framework integrating non-local similarity constraints to handle in a better way repetitive structures and texture. the effectiveness of our approach is demonstrated by experiments on realistic magnetic resonance brain images generating automatically high-quality hallucinated brain images from low-resolution input.
reformulating and optimizing the mumford-shah functional on a graph - a faster, lower energy solution. active contour formulations predominate current minimization of the mumford-shah functional (msf) for image segmentation and filtering. unfortunately, these formulations necessitate optimization of the contour by evolving via gradient descent, which is known for its sensitivity to initialization and the tendency to produce undesirable local minima. in order to reduce these problems, we reformulate the corresponding msf on an arbitrary graph and apply combinatorial optimization to produce a fast, low-energy solution. the solution provided by this graph formulation is compared with the solution computed via traditional narrow-band level set methods. this comparison demonstrates that our graph formulation and optimization produces lower energy solutions than gradient descent based contour evolution methods in significantly less time. finally, by avoiding evolution of the contour via gradient descent, we demonstrate that our optimization of the msf is capable of evolving the contour with non-local movement.
helmholtz stereopsis: exploiting reciprocity for surface reconstruction. we present a method&mdash;termed helmholtz stereopsis&mdash;for reconstructing the geometry of objects from a collection of images. unlike existing methods for surface reconstruction (e.g., stereo vision, structure from motion, photometric stereopsis), helmholtz stereopsis makes no assumptions about the nature of the bidirectional reflectance distribution functions (brdfs) of objects. this new method of multinocular stereopsis exploits helmholtz reciprocity by choosing pairs of light source and camera positions that guarantee that the ratio of the emitted radiance to the incident irradiance is the same for corresponding points in the two images. the method provides direct estimates of both depth and surface normals, and consequently weds the advantages of both conventional stereopsis and photometric stereopsis. results from our implementation lend empirical support to our technique.
floor fields for tracking in high density crowd scenes. this paper presents an algorithm for tracking individual targets in high density crowd scenes containing hundreds of people. tracking in such a scene is extremely challenging due to the small number of pixels on the target, appearance ambiguity resulting from the dense packing, and severe inter-object occlusions. the novel tracking algorithm, which is outlined in this paper, will overcome these challenges using a scene structure based force model. in this force model an individual, when moving in a particular scene, is subjected to global and local forces that are functions of the layout of that scene and the locomotive behavior of other individuals in the scene. the key ingredients of the force model are three floor fields, which are inspired by the research in the field of evacuation dynamics, namely static floor field (sff), dynamic floor field (dff), and boundary floor field (bff). these fields determine the probability of move from one location to another by converting the long-range forces into local ones. the sff specifies regions of the scene which are attractive in nature (e.g. an exit location). the dff specifies the immediate behavior of the crowd in the vicinity of the individual being tracked. the bff specifies influences exhibited by the barriers in the scene (e.g. walls, no-go areas). by combining cues from all three fields with the available appearance information, we track individual targets in high density crowds.
rank classification of linear line structure in determining trifocal tensor. the problem we address is: given line correspondences over three views, what is the condition of the line correspondences for the spatial relation of the three associated camera positions to be uniquely recoverable? we tackle the problem from the perspective of trifocal tensor, a quantity that captures the relative positions of the cameras in relation to the three views. we show that the rank of the matrix that leads to the estimation of the tensor reduces to 7, 11, 15 respectively for line pencil, point star, and ruled plane, which are structures that belong to linear line space; and 12, 19, 23 for general ruled surface, general linear congruence, and general linear line complex. these critical structures are quite typical in reality, and thus the findings are important to the validity and stability of practically all algorithms related to structure from motion and projective reconstruction using line correspondences.
active image labeling and its application to facial action labeling. for many tasks in computer vision, it is very important to produce the groundtruth data. at present, this is mostly done manually. manual data labeling is labor-intensive and prone to the human errors. the training data it produces often lacks in both quantity and quality. fully automatic data labeling, on the other hand, is not feasible and reliable. in this paper, we propose an interactive image labeling technique for efficient and accurate data labeling.the proposed technique includes two parts: an automatic labeling part and a human intervention part. constructed on a bayesian network, the automatic image labeler produces an initial labeling of the image. a person then examines the initial labeling and makes some minor corrections. the selected human corrections and the image measurements are then integrated by the bayesian network framework to produce a refined labeling. to minimize the human involvement, an active user feedback strategy is developed, through which the optimal user feedback is determined, so that the labeling errors in the subsequent re-labeling process can be maximally reduced. the proposed framework combines the advantages of the human input with those of the machine so that the reliable, accurate, and efficient data labeling can be achieved. we demonstrate the validity of the proposed framework for interactive labeling of facial action units. the proposed methodology, however, is not limited to labeling of facial action units. it can be easily extended to other areas such as interactive image segmentation.
a lattice-preserving multigrid method for solving the inhomogeneous poisson equations used in image analysis. the inhomogeneous poisson (laplace) equation with internal dirichlet boundary conditions has recently appeared in several applications ranging from image segmentation [1, 2, 3] to image colorization [4], digital photo matting [5, 6] and image filtering [7, 8]. in addition, the problem we address may also be considered as the generalized eigenvector problem associated with normalized cuts [9], the linearized anisotropic diffusion problem [10, 11, 8] solved with a backward euler method, visual surface reconstruction with discontinuities [12, 13] or optical flow [14]. although these approaches have demonstrated quality results, the computational burden of finding a solution requires an efficient solver. design of an efficient multigrid solver is difficult for these problems due to unpredictable inhomogeneity in the equation coefficients and internal dirichlet boundary conditions with unpredictable location and value. previous approaches to multigrid solvers have typically employed either a data-driven operator (with fast convergence) or the maintenance of a lattice structure at coarse levels (with low memory overhead). in addition to memory efficiency, a lattice structure at coarse levels is also essential to taking advantage of the power of a gpu implementation [15,16,5,3]. in this work, we present a multigrid method that maintains the low memory overhead (and gpu suitability) associated with a regular lattice while benefiting from the fast convergence of a data-driven coarse operator.
multiple component learning for object detection. object detection is one of the key problems in computer vision. in the last decade, discriminative learning approaches have proven effective in detecting rigid objects, achieving very low false positives rates. the field has also seen a resurgence of part-based recognition methods, with impressive results on highly articulated, diverse object categories. in this paper we propose a discriminative learning approach for detection that is inspired by part-based recognition approaches. our method, multiple component learning (mcl), automatically learns individual component classifiers and combines these into an overall classifier. unlike previous methods, which rely on either fairly restricted part models or labeled part data, mcl learns powerful component classifiers in a weakly supervised manner, where object labels are provided but part labels are not. the basis of mcl lies in learning a set classifier; we achieve this by combining boosting with weakly supervised learning, specifically the multiple instance learning framework (mil). mcl is general, and we demonstrate results on a range of data from computer audition and computer vision. in particular, mcl outperforms all existing methods on the challenging inria pedestrian detection dataset, and unlike methods that are not part-based, mcl is quite robust to occlusions.
euclidean group invariant computation of stochastic completion fields using shiftable-twistable functions. we describe a method for computing the likelihood that a completion joining two contour fragments passes through any given position and orientation in the image plane. like computations in primary visual cortex (and unlike all previous models of contour completion), the output of our computation is invariant under rotations and translations of the input pattern. this is achieved by representing the input, output, and intermediate states of the computation in a basis of shiftable-twistable functions.
scale invariant action recognition using compound features mined from dense spatio-temporal corners. the use of sparse invariant features to recognise classes of actions or objects has become common in the literature. however, features are often "engineered" to be both sparse and invariant to transformation and it is assumed that they provide the greatest discriminative information. to tackle activity recognition, we propose learning compound features that are assembled from simple 2d corners in both space and time. each corner is encoded in relation to its neighbours and from an over complete set (in excess of 1 million possible features), compound features are extracted using data mining. the final classifier, consisting of sets of compound features, can then be applied to recognise and localise an activity in real-time while providing superior performance to other state-of-the-art approaches (including those based upon sparse feature detectors). furthermore, the approach requires only weak supervision in the form of class labels for each training sequence. no ground truth position or temporal alignment is required during training.
semi-supervised on-line boosting for robust tracking. recently, on-line adaptation of binary classifiers for tracking have been investigated. on-line learning allows for simple classifiers since only the current view of the object from its surrounding background needs to be discriminiated. however, on-line adaption faces one key problem: each update of the tracker may introduce an error which, finally, can lead to tracking failure (drifting). the contribution of this paper is a novel on-line semi-supervised boosting method which significantly alleviates the drifting problem in tracking applications. this allows to limit the drifting problem while still staying adaptive to appearance changes. the main idea is to formulate the update process in a semi-supervised fashion as combined decision of a given prior and an on-line classifier. this comes without any parameter tuning. in the experiments, we demonstrate real-time tracking of our semiboost tracker on several challenging test sequences where our tracker outperforms other on-line tracking methods.
what is a good nearest neighbors algorithm for finding similar patches in images? many computer vision algorithms require searching a set of images for similar patches, which is a very expensive operation. in this work, we compare and evaluate a number of nearest neighbors algorithms for speeding up this task. since image patches follow very different distributions from the uniform and gaussian distributions that are typically used to evaluate nearest neighbors methods, we determine the method with the best performance via extensive experimentation on real images. furthermore, we take advantage of the inherent structure and properties of images to achieve highly efficient implementations of these algorithms. our results indicate that vantage point trees, which are not well known in the vision community, generally offer the best performance.
localizing objects with smart dictionaries. we present an approach to determine the category and location of objects in images. it performs very fast categorization of each pixel in an image, a brute-force approach made feasible by three key developments: first, our method reduces the size of a large generic dictionary (on the order of ten thousand words) to the low hundreds while increasing classification performance compared to k-means. this is achieved by creating a discriminative dictionary tailored to the task by following the information bottleneck principle. second, we perform feature-based categorization efficiently on a dense grid by extending the concept of integral images to the computation of local histograms. third, we compute sift descriptors densely in linear time. we compare our method to the state of the art and find that it excels in accuracy and simplicity, performing better while assuming less.
grassmann registration manifolds for face recognition. motivated by image perturbation and the geometry of manifolds, we present a novel method combining these two elements. first, we form a tangent space from a set of perturbed images and observe that the tangent space admits a vector space structure. second, we embed the approximated tangent spaces on a grassmann manifold and employ a chordal distance as the means for comparing subspaces. the matching process is accelerated using a coarse to fine strategy. experiments on the feret database suggest that the proposed method yields excellent results using both holistic and local features. specifically, on the feret dup2 data set, our proposed method achieves 83.8% rank 1 recognition: to our knowledge the currently the best result among all non-trained methods. evidence is also presented that peak recognition performance is achieved using roughly 100 distinct perturbed images.
active matching. in the matching tasks which form an integral part of all types of tracking and geometrical vision, there are invariably priors available on the absolute and/or relative image locations of features of interest. usually, these priors are used post-hoc in the process of resolving feature matches and obtaining final scene estimates, via `first get candidate matches, then resolve' consensus algorithms such as ransac. in this paper we show that the dramatically different approach of using priors dynamically to guide a feature by feature matching search can achieve global matching with much fewer image processing operations and lower overall computational cost. essentially, we put image processing into the loop of the search for global consensus. in particular, our approach is able to cope with significant image ambiguity thanks to a dynamic mixture of gaussians treatment. in our fully bayesian algorithm, the choice of the most efficient search action at each step is guided intuitively and rigorously by expected shannon information gain. we demonstrate the algorithm in feature matching as part of a sequential slam system for 3d camera tracking. robust, real-time matching can be achieved even in the previously unmanageable case of jerky, rapid motion necessitating weak motion modelling and large search regions.
range flow for varying illumination. in this paper range flow estimation is extended to handle brightness changes in image data caused by inhomogeneous illumination. standard range flow computes 3d velocity fields from range and intensity image sequences. to this end it combines a depth change model and a brightness constancy model. in this contribution, the brightness constancy model is exchanged by (1) a gradient constancy model, (2) a combination of gradient and brightness constancy constraint that has been used successfully for optical flow estimation in literature, and (3) a physics-based brightness change model. insensitivity to brightness changes can also be achieved by prefiltering of the input intensity data. high pass or homomorphic filtering are the most well known approaches from literature. in performance tests therefore the well known version and the novel versions of range flow estimation are investigated on prefiltered or non-prefiltered data using synthetic ground-truth and real data from a botanical experiment.
beyond nouns: exploiting prepositions and comparative adjectives for learning visual classifiers. learning visual classifiers for object recognition from weakly labeled data requires determining correspondence between image regions and semantic object classes. most approaches use co-occurrence of "nouns" and image features over large datasets to determine the correspondence, but many correspondence ambiguities remain. we further constrain the correspondence problem by exploiting additional language constructs to improve the learning process from weakly labeled data. we consider both "prepositions" and "comparative adjectives" which are used to express relationships between objects. if the models of such relationships can be determined, they help resolve correspondence ambiguities. however, learning models of these relationships requires solving the correspondence problem. we simultaneously learn the visual features defining "nouns" and the differential visual features defining such "binary-relationships" using an em-based approach.
segmentation and recognition using structure from motion point clouds. we propose an algorithm for semantic segmentation based on 3d point clouds derived from ego-motion. we motivate five simple cues designed to model specific patterns of motion and 3d world structure that vary with object category. we introduce features that project the 3d cues back to the 2d image plane while modeling spatial layout and context. a randomized decision forest combines many such features to achieve a coherent 2d segmentation and recognize the object categories present. our main contribution is to show how semantic segmentation is possible based solely on motion-derived 3d world structure. our method works well on sparse, noisy point clouds, and unlike existing approaches, does not need appearance-based descriptors.experiments were performed on a challenging new video database containing sequences filmed from a moving car in daylight and at dusk. the results confirm that indeed, accurate segmentation and recognition are possible using only motion and 3d world structure. further, we show that the motion-derived information complements an existing state-of-the-art appearance-based method, improving both qualitative and quantitative performance.
illumination and person-insensitive head pose estimation using distance metric learning. head pose estimation is an important task for many face analysis applications, such as face recognition systems and human computer interactions. in this paper we aim to address the pose estimation problem under some challenging conditions, e.g., from a single image, large pose variation, and un-even illumination conditions. the approach we developed combines non-linear dimension reduction techniques with a learned distance metric transformation. the learned distance metric provides better intra-class clustering, therefore preserving a smooth low-dimensional manifold in the presence of large variation in the input images due to illumination changes. experiments show that our method improves the performance, achieving accuracy within 2-3 degrees for face images with varying poses and within 3-4 degrees error for face images with varying pose and illumination changes.
joint parametric and non-parametric curve evolution for medical image segmentation. this paper proposes a new joint parametric and nonparametric curve evolution algorithm of the level set functions for medical image segmentation. traditional level set algorithms employ non-parametric curve evolution for object matching. although matching image boundaries accurately, they often suffer from local minima and generate incorrect segmentation of object shapes, especially for images with noise, occlusion and low contrast. on the other hand, statistical model-based segmentation methods allow parametric object shape variations subject to some shape prior constraints, and they are more robust in dealing with noise and low contrast. in this paper, we combine the advantages of both of these methods and jointly use parametric and non-parametric curve evolution in object matching. our new joint curve evolution algorithm is as robust as and at the same time, yields more accurate segmentation results than the parametric methods using shape prior information. comparative results on segmenting ventricle frontal horn and putamen shapes in mr brain images confirm both robustness and accuracy of the proposed joint curve evolution algorithm.
efficiently learning random fields for stereo vision with sparse message passing. as richer models for stereo vision are constructed, there is a growing interest in learning model parameters. to estimate parameters in markov random field (mrf) based stereo formulations, one usually needs to perform approximate probabilistic inference. message passing algorithms based on variational methods and belief propagation are widely used for approximate inference in mrfs. conditional random fields (crfs) are discriminative versions of traditional mrfs and have recently been applied to the problem of stereo vision. however, crf parameter training typically requires expensive inference steps for each iteration of optimization. inference is particularly slow when there are many discrete disparity levels, due to high state space cardinality. we present a novel crf for stereo matching with an explicit occlusion model and propose sparse message passing to dramatically accelerate the approximate inference needed for parameter optimization. we show that sparse variational message passing iteratively minimizes the kl divergence between the approximation and model distributions by optimizing a lower bound on the partition function. our experimental results show reductions in inference time of one order of magnitude with no loss in approximation quality. learning using sparse variational message passing improves results over prior work using graph cuts.
building a compact relevant sample coverage for relevance feedback in content-based image retrieval. conventional approaches to relevance feedback in content-based image retrieval are based on the assumption that relevant images are physically close to the query image, or the query regions can be identified by a set of clustering centers. however, semantically related images are often scattered across the visual space. it is not always reliable that the refined query point or the clustering centers are capable of representing a complex query region.in this work, we propose a novel relevance feedback approach which directly aims at extracting a set of samples to represent the query region, regardless of its underlying shape. the sample set extracted by our method is competent as well as compact for subsequent retrieval. moreover, we integrate feature re-weighting in the process to estimate the importance of each image descriptor. unlike most existing relevance feedback approaches in which all query points share a same feature weight distribution, our method re-weights the feature importance for each relevant image respectively, so that the representative and discriminative ability for all the images can be maximized. experimental results on two databases show the effectiveness of our approach.
cross-view action recognition from temporal self-similarities. this paper concerns recognition of human actions under view changes. we explore self-similarities of action sequences over time and observe the striking stability of such measures across views. building upon this key observation we develop an action descriptor that captures the structure of temporal similarities and dissimilarities within an action sequence. despite this descriptor not being strictly view-invariant, we provide intuition and experimental validation demonstrating the high stability of self-similarities under view changes. self-similarity descriptors are also shown stable under action variations within a class as well as discriminative for action recognition. interestingly, self-similarities computed from different image features possess similar properties and can be used in a complementary fashion. our method is simple and requires neither structure recovery nor multi-view correspondence estimation. instead, it relies on weak geometric properties and combines them with machine learning for efficient cross-view action recognition. the method is validated on three public datasets, it has similar or superior performance compared to related methods and it performs well even in extreme conditions such as when recognizing actions from top views while using side views for training only.
tracking with dynamic hidden-state shape models. hidden state shape models (hssms) were previously proposed to represent and detect objects in images that exhibit not just deformation of their shape but also variation in their structure. in this paper, we introduce dynamic hidden-state shape models (dhssms) to track and recognize the non-rigid motion of such objects, for example, human hands. our recursive bayesian filtering method, called dp-tracking, combines an exhaustive local search for a match between image features and model states with a dynamic programming approach to find a global registration between the model and the object in the image. our contribution is a technique to exploit the hierarchical structure of the dynamic programming approach that on average considerably speeds up the search for matches. we also propose to embed an online learning approach into the tracking mechanism that updates the dhssm dynamically. the learning approach ensures that the dhssm accurately represents the tracked object and distinguishes any clutter potentially present in the image. our experiments show that our method can recognize the digits of a hand while the fingers are being moved and curled to various degrees. the method is robust to various illumination conditions, the presence of clutter, occlusions, and some types of self-occlusions. the experiments demonstrate a significant improvement in both efficiency and accuracy of recognition compared to the non-recursive way of frame-by-frame detection.
hamming embedding and weak geometric consistency for large scale image search. this paper improves recent methods for large scale image search. state-of-the-art methods build on the bag-of-features image representation. we, first, analyze bag-of-features in the framework of approximate nearest neighbor search. this shows the sub-optimality of such a representation for matching descriptors and leads us to derive a more precise representation based on 1) hamming embedding (he) and 2) weak geometric consistency constraints (wgc). he provides binary signatures that refine the matching based on visual words. wgc filters matching descriptors that are not consistent in terms of angle and scale. he and wgc are integrated within the inverted file and are efficiently exploited for all images, even in the case of very large datasets. experiments performed on a dataset of one million of images show a significant improvement due to the binary signature and the weak geometric consistency constraints, as well as their efficiency. estimation of the full geometric transformation, i.e., a re-ranking step on a short list of images, is complementary to our weak geometric consistency constraints and allows to further improve the accuracy.
improving people search using query expansions. in this paper we are interested in finding images of people on the web, and more specifically within large databases of captioned news images. it has recently been shown that visual analysis of the faces in images returned on a text-based query over captions can significantly improve search results. the underlying idea to improve the text-based results is that although this initial result is imperfect, it will render the queried person to be relatively frequent as compared to other people, so we can search for a large group of highly similar faces. the performance of such methods depends strongly on this assumption: for people whose face appears in less than about 40% of the initial text-based result, the performance may be very poor. the contribution of this paper is to improve search results by exploiting faces of other people that co-occur frequently with the queried person. we refer to this process as `query expansion'. in the face analysis we use the query expansion to provide a query-specific relevant set of `negative' examples which should be separated from the potentially positive examples in the text-based result set. we apply this idea to a recently-proposed method which filters the initial result set using a gaussian mixture model, and apply the same idea using a logistic discriminant model. we experimentally evaluate the methods using a set of 23 queries on a database of 15.000 captioned news stories from yahoo! news. the results show that (i) query expansion improves both methods, (ii) that our discriminative models outperform the generative ones, and (iii) our best results surpass the state-of-the-art results by 10% precision on average.
interactive tracking of 2d generic objects with spacetime optimization. we present a continuous optimization framework for interactive tracking of 2d generic objects in a single video stream. the user begins with specifying the locations of a target object in a small set of keyframes; the system then automatically tracks locations of the objects by combining user constraints with visual measurements across the entire sequence. we formulate the problem in a spacetime optimization framework that optimizes over the whole sequence simultaneously. the resulting solution is consistent with visual measurements across the entire sequence while satisfying user constraints. we also introduce prior terms to reduce tracking ambiguity. we demonstrate the power of our algorithm on tracking objects with significant occlusions, scale and orientation changes, illumination changes, sudden movement of objects, and also simultaneous tracking of multiple objects. we compare the performance of our algorithm with alternative methods.
image feature extraction using gradient local auto-correlations. in this paper, we propose a method for extracting image features which utilizes 2nd order statistics, i.e., spatial and orientational auto-correlations of local gradients. it enables us to extract richer information from images and to obtain more discriminative power than standard histogram based methods. the image gradients are sparsely described in terms of magnitude and orientation. in addition, normal vectors on the image surface are derived from the gradients and these could also be utilized instead of the gradients. from a geometrical viewpoint, the method extracts information about not only the gradients but also the curvatures of the image surface. experimental results for pedestrian detection and image patch matching demonstrate the effectiveness of the proposed method compared with other methods, such as hog and sift.
discriminative locality alignment. fisher's linear discriminant analysis (lda), one of the most popular dimensionality reduction algorithms for classification, has three particular problems: it fails to find the nonlinear structure hidden in the high dimensional data; it assumes all samples contribute equivalently to reduce dimension for classification; and it suffers from the matrix singularity problem. in this paper, we propose a new algorithm, termed discriminative locality alignment (dla), to deal with these problems. the algorithm operates in the following three stages: first, in part optimization, discriminative information is imposed over patches, each of which is associated with one sample and its neighbors; then, in sample weighting, each part optimization is weighted by the margin degree, a measure of the importance of a given sample; and finally, in whole alignment, the alignment trick is used to align all weighted part optimizations to the whole optimization. furthermore, dla is extended to the semi-supervised case, i.e., semi-supervised dla (sdla), which utilizes unlabeled samples to improve the classification performance. thorough empirical studies on the face recognition demonstrate the effectiveness of both dla and sdla.
semidefinite programming heuristics for surface reconstruction ambiguities. we consider the problem of reconstructing a smooth surface under constraints that have discrete ambiguities. these problems arise in areas such as shape from texture, shape from shading, photometric stereo and shape from defocus. while the problem is computationally hard, heuristics based on semidefinite programming may reveal the shape of the surface.
tracking of abrupt motion using wang-landau monte carlo estimation. we propose a novel tracking algorithm based on the wang-landau monte carlo sampling method which efficiently deals with the abrupt motions. abrupt motions could cause conventional tracking methods to fail since they violate the motion smoothness constraint. to address this problem, we introduce the wang-landau algorithm that has been recently proposed in statistical physics, and integrate this algorithm into the markov chain monte carlo based tracking method. our tracking method alleviates the motion smoothness constraint utilizing both the likelihood term and the density of states term, which is estimated by the wang-landau algorithm. the likelihood term helps to improve the accuracy in tracking smooth motions, while the density of states term captures abrupt motions robustly. experimental results reveal that our approach efficiently samples the object's states even in a whole state space without loss of time. therefore, it tracks the object of which motion is drastically changing, accurately and robustly.
perspective nonrigid shape and motion recovery. we present a closed form solution to the nonrigid shape and motion (nrsm) problem from point correspondences in multiple perspective uncalibrated views. under the assumption that the nonrigid object deforms as a linear combination of k rigid shapes, we show that the nrsm problem can be viewed as a reconstruction problem from multiple projections from ℙ3k to ℙ2. therefore, one can linearly solve for the projection matrices by factorizing a multifocal tensor. however, this projective reconstruction in ℙ3k does not satisfy the constraints of the nrsm problem, because it is computed only up to a projective transformation in ℙ3k . our key contribution is to show that, by exploiting algebraic dependencies among the entries of the projection matrices, one can upgrade the projective reconstruction to determine the affine configuration of the points in ℝ3, and the motion of the camera relative to their centroid. moreover, if k &ge; 2, then either by using calibrated cameras, or by assuming a camera with fixed internal parameters, it is possible to compute the euclidean structure by a closed form method.
local statistic based region segmentation with automatic scale selection. recently, new segmentation models based on local information have emerged. they combine local statistics of the regions along the contour (inside and outside) to drive the segmentation procedure. since they are based on local decisions, these models are more robust to local variations of the regions of interest (contrast, noise, blur, ...). they nonetheless also introduce some new difficulties which are inherent to the fact of basing a global property (the segmentation) on pure local decisions. this papers explores some of those difficulties and proposes some possible corrections. results on both 2d and 3d data are compared to those obtained without these corrections.
asn: image keypoint detection from adaptive shape neighborhood. we describe an accurate keypoint detector that is stable under viewpoint change. in this paper, keypoints correspond to actual junctions in the image. the principle of asn differs fundamentally from other keypoint detectors. at each position in the image and before any detection, it systematically estimates the position of a potential junction from the local gradient field. keypoints then appear where multiple position estimates are attracted. this approach allows the detector to adapt in shape and size to the image content. one further obtains the area where the keypoint has attracted solutions. comparative results with other detectors show the improved accuracy and stability with viewpoint change.
shadows in three-source photometric stereo. shadows are one of the most significant difficulties of the photometric stereo method. when four or more images are available, local surface orientation is overdetermined and the shadowed pixels can be discarded. in this paper we look at the challenging case when only three images under three different illuminations are available. in this case, when one of the three pixel intensity constraints is missing due to shadow, a 1 dof ambiguity per pixel arises. we show that using integrability one can resolve this ambiguity and use the remaining two constraints to reconstruct the geometry in the shadow regions. as the problem becomes ill-posed in the presence of noise, we describe a regularization scheme that improves the numerical performance of the algorithm while preserving data. we propose a simple mrf optimization scheme to identify and segment shadow regions in the image. finally the paper describes how this theory applies in the framework of color photometric stereo where one is restricted to only three images. experiments on synthetic and real image sequences are presented.
learning to recognize activities from the wrong view point. appearance features are good at discriminating activities in a fixed view, but behave poorly when aspect is changed. we describe a method to build features that are highly stable under change of aspect. it is not necessary to have multiple views to extract our features. our features make it possible to learn a discriminative model of activity in one view, and spot that activity in another view, for which one might poses no labeled examples at all. our construction uses labeled examples to build activity models, and unlabeled, but corresponding, examples to build an implicit model of how appearance changes with aspect. we demonstrate our method with challenging sequences of real human motion, where discriminative methods built on appearance alone fail badly.
discriminative learning for deformable shape segmentation: a comparative study. we present a comparative study on how to use discriminative learning methods such as classification, regression, and ranking to address deformable shape segmentation. traditional generative models and energy minimization methods suffer from local minima. by casting the segmentation into a discriminative framework, the target fitting function can be steered to possess a desired shape for ease of optimization yet better characterize the relationship between shape and appearance. to address the high-dimensional learning challenge present in the learning framework, we use a multi-level approach to learning discriminative models. our experimental results on left ventricle segmentation from ultrasound images and facial feature point localization demonstrate that the discriminative models outperform generative models and energy minimization methods by a large margin.
a perceptual comparison of distance measures for color constancy algorithms. color constancy is the ability to measure image features independent of the color of the scene illuminant and is an important topic in color and computer vision. as many color constancy algorithms exist, different distance measures are used to compute their accuracy. in general, these distances measures are based on mathematical principles such as the angular error and euclidean distance. however, it is unknown to what extent these distance measures correlate to human vision.therefore, in this paper, a taxonomy of different distance measures for color constancy algorithms is presented. the main goal is to analyze the correlation between the observed quality of the output images and the different distance measures for illuminant estimates. the output images are the resulting color corrected images using the illuminant estimates of the color constancy algorithms, and the quality of these images is determined by human observers. distance measures are analyzed how they mimic differences in color naturalness of images as obtained by humans.based on the theoretical and experimental results on spectral and real-world data sets, it can be concluded that the perceptual euclidean distance (ped) with weight-coefficients (w r = 0.26, w g = 0.70, w b = 0.04) finds its roots in human vision and correlates significantly higher than all other distance measures including the angular error and euclidean distance.
edge-preserving smoothing and mean-shift segmentation of video streams. video streams are ubiquitous in applications such as surveillance, games, and live broadcast. processing and analyzing these data is challenging because algorithms have to be efficient in order to process the data on the fly. from a theoretical standpoint, video streams have their own specificities --- they mix spatial and temporal dimensions, and compared to standard video sequences, half of the information is missing, i.e. the future is unknown. the theoretical part of our work is motivated by the ubiquitous use of the gaussian kernel in tools such as bilateral filtering and mean-shift segmentation. we formally derive its equivalent for video streams as well as a dedicated expression of isotropic diffusion. building upon this theoretical ground, we adapt a number of classical algorithms to video streams: bilateral filtering, mean-shift segmentation, and anisotropic diffusion.
robust 3d pose estimation and efficient 2d region-based segmentation from a 3d shape prior. in this work, we present an approach to jointly segment a rigid object in a 2d image and estimate its 3d pose, using the knowledge of a 3d model. we naturally couple the two processes together into a unique energy functional that is minimized through a variational approach. our methodology differs from the standard monocular 3d pose estimation algorithms since it does not rely on local image features. instead, we use global image statistics to drive the pose estimation process. this confers a satisfying level of robustness to noise and initialization for our algorithm, and bypasses the need to establish correspondences between image and object features. moreover, our methodology possesses the typical qualities of region-based active contour techniques with shape priors, such as robustness to occlusions or missing information, without the need to evolve an infinite dimensional curve. another novelty of the proposed contribution is to use a unique 3d model surface of the object, instead of learning a large collection of 2d shapes to accommodate for the diverse aspects that a 3d object can take when imaged by a camera. experimental results on both synthetic and real images are provided, which highlight the robust performance of the technique on challenging tracking and segmentation applications.
fast and accurate rotation estimation on the 2-sphere without correspondences. we present a refined method for rotation estimation of signals on the 2-sphere. our approach utilizes a fast correlation in the harmonic domain to estimate rotation angles of arbitrary size and resolution. the method is able to achieve great accuracy even for very low spherical harmonic expansions of the input signals without using correspondences or any other kind of a priori information. the rotation parameters are computed analytically without additional iterative post-processing or "fine tuning".the theoretical advances presented in this paper can be applied to a wide range of practical problems such as: shape description and shape retrieval, 3d rigid registration, robot positioning with omni-directional cameras or 3d invariant feature design.
the naked truth: estimating body shape under clothing. we propose a method to estimate the detailed 3d shape of a person from images of that person wearing clothing. the approach exploits a model of human body shapes that is learned from a database of over 2000 range scans. we show that the parameters of this shape model can be recovered independently of body pose. we further propose a generalization of the visual hull to account for the fact that observed silhouettes of clothed people do not provide a tight bound on the true 3d shape. with clothed subjects, different poses provide different constraints on the possible underlying 3d body shape. we consequently combine constraints across pose to more accurately estimate 3d body shape in the presence of occluding clothing. finally we use the recovered 3d shape to estimate the gender of subjects and then employ gender-specific body models to refine our shape estimates. results on a novel database of thousands of images of clothed and "naked" subjects, as well as sequences from the humaneva dataset, suggest the method may be accurate enough for biometric shape analysis in video.
robust real-time visual tracking using pixel-wise posteriors. we derive a probabilistic framework for robust, real-time, visual tracking of previously unseen objects from a moving camera. the tracking problem is handled using a bag-of-pixels representation and comprises a rigid registration between frames, a segmentation and online appearance learning. the registration compensates for rigid motion, segmentation models any residual shape deformation and the online appearance learning provides continual refinement of both the object and background appearance models. the key to the success of our method is the use of pixel-wise posteriors, as opposed to likelihoods. we demonstrate the superior performance of our tracker by comparing cost function statistics against those commonly used in the visual tracking literature. our comparison method provides a way of summarising tracking performance using lots of data from a variety of different sequences.
contour context selection for object detection: a set-to-set contour matching approach. we introduce a shape detection framework called contour context selection for detecting objects in cluttered images using only one exemplar. shape based detection is invariant to changes of object appearance, and can reason with geometrical abstraction of the object. our approach uses salient contours as integral tokens for shape matching. we seek a maximal, holistic matching of shapes, which checks shape features from a large spatial extent, as well as long-range contextual relationships among object parts. this amounts to finding the correct figure/ground contour labeling, and optimal correspondences between control points on/around contours. this removes accidental alignments and does not hallucinate objects in background clutter, without negative training examples. we formulate this task as a set-to-set contour matching problem. naive methods would require searching over 'exponentially' many figure/ground contour labelings. we simplify this task by encoding the shape descriptor algebraically in a linear form of contour figure/ground variables. this allows us to use the reliable optimization technique of linear programming. we demonstrate our approach on the challenging task of detecting bottles, swans and other objects in cluttered images.
a graph based subspace semi-supervised learning framework for dimensionality reduction. the key to the graph based semi-supervised learning algorithms for classification problems is how to construct the weight matrix of the p-nearest neighbor graph. a new method to construct the weight matrix is proposed and a graph based subspace semi-supervised learning framework (sslf) is developed. the framework aims to find an embedding transformation which respects the discriminant structure inferred from the labeled data, as well as the intrinsic geometrical structure inferred from both the labeled and unlabeled data. by utilizing this framework as a tool, we drive three semi-supervised dimensionality reduction algorithms: subspace semi-supervised linear discriminant analysis (sslda), subspace semi-supervised locality preserving projection (sslpp), and subspace semi-supervised marginal fisher analysis (ssmfa). the experimental results on face recognition demonstrate our subspace semi-supervised algorithms are able to use unlabeled samples effectively.
temporal surface tracking using mesh evolution. in this paper, we address the problem of surface tracking in multiple camera environments and over time sequences. in order to fully track a surface undergoing significant deformations, we cast the problem as a mesh evolution over time. such an evolution is driven by 3d displacement fields estimated between meshes recovered independently at different time frames. geometric and photometric information is used to identify a robust set of matching vertices. this provides a sparse displacement field that is densified over the mesh by laplacian diffusion. in contrast to existing approaches that evolve meshes, we do not assume a known model or a fixed topology. the contribution is a novel mesh evolution based framework that allows to fully track, over long sequences, an unknown surface encountering deformations, including topological changes. results on very challenging and publicly available image based 3d mesh sequences demonstrate the ability of our framework to efficiently recover surface motions .
2d image analysis by generalized hilbert transforms in conformal space. this work presents a novel rotational invariant quadrature filter approach - called the conformal monogenic signal - for analyzing i(ntrinsic)1d and i2d local features of any curved 2d signal such as lines, edges, corners and junctions without the use of steering. the conformal monogenic signal contains the monogenic signal as a special case for i1d signals and combines monogenic scale space, phase, direction/orientation, energy and curvature in one unified algebraic framework. the conformal monogenic signal will be theoretically illustrated and motivated in detail by the relation of the 3d radon transform and the generalized hilbert transform on the sphere. the main idea is to lift up 2d signals to the higher dimensional conformal space where the signal features can be analyzed with more degrees of freedom. results of this work are the low computational time complexity, the easy implementation into existing computer vision applications and the numerical robustness of determining curvature without the need of any derivatives.
pose priors for simultaneously solving alignment and correspondence. estimating a camera pose given a set of 3d-object and 2d-image feature points is a well understood problem when correspondences are given. however, when such correspondences cannot be established a priori, one must simultaneously compute them along with the pose. most current approaches to solving this problem are too computationally intensive to be practical. an interesting exception is the softposit algorithm, that looks for the solution as the minimum of a suitable objective function. it is arguably one of the best algorithms but its iterative nature means it can fail in the presence of clutter, occlusions, or repetitive patterns. in this paper, we propose an approach that overcomes this limitation by taking advantage of the fact that, in practice, some prior on the camera pose is often available. we model it as a gaussian mixture model that we progressively refine by hypothesizing new correspondences. this rapidly reduces the number of potential matches for each 3d point and lets us explore the pose space more thoroughly than softposit at a similar computational cost. we will demonstrate the superior performance of our approach on both synthetic and real data.
facial expression recognition based on 3d dynamic range model sequences. traditionally, facial expression recognition (fer) issues have been studied mostly based on modalities of 2d images, 2d videos, and 3d static models. in this paper, we propose a spatio-temporal expression analysis approach based on a new modality, 3d dynamic geometric facial model sequences, to tackle the fer problems. our approach integrates a 3d facial surface descriptor and hidden markov models (hmm) to recognize facial expressions. to study the dynamics of 3d dynamic models for fer, we investigated three types of hmms: temporal 1d-hmm, pseudo 2d-hmm (a combination of a spatial hmm and a temporal hmm), and real 2d-hmm. we also created a new dynamic 3d facial expression database for the research community. the results show that our approach achieves a 90.44% person-independent recognition rate for distinguishing six prototypic facial expressions. the advantage of our method is demonstrated as compared to methods based on 2d texture images, 2d/3d motion units, and 3d static range models. further experimental evaluations also verify the benefits of our approach with respect to partial facial surface occlusion, expression intensity changes, and 3d model resolution variations.
real time feature based 3-d deformable face tracking. in this paper, we develop a novel framework for 3d tracking of the non-rigid face deformation from a single camera. the difficulty of the problem lies in the fact that 3d deformation parameter estimation becomes unstable when there are few reliable facial features correspondences. unfortunately, this often occurs in real tracking scenario when there is significant illumination change, motion blur or large pose variation. in order to extract more information of feature correspondences, the proposed framework integrates three types of features which discriminate face deformation across different views: 1) the semantic features which provide constant correspondences between 3d model points and major facial features; 2) the silhouette features which provide dynamic correspondences between 3d model points and facial silhouette under varying views; 3) the online tracking features that provide redundant correspondences between 3d model points and salient image features. the integration of these complementary features is important for robust estimation of the 3d parameters. in order to estimate the high dimensional 3d deformation parameters, we develop a hierarchical parameter estimation algorithm to robustly estimate both rigid and non-rigid 3d parameters. we show the importance of both features fusion and hierarchical parameter estimation for reliable tracking 3d face deformation. experiments demonstrate the robustness and accuracy of the proposed algorithm especially in the cases of agile head motion, drastic illumination change, and large pose change up to profile view.
learning crfs using graph cuts. many computer vision problems are naturally formulated as random fields, specifically mrfs or crfs. the introduction of graph cuts has enabled efficient and optimal inference in associative random fields, greatly advancing applications such as segmentation, stereo reconstruction and many others. however, while fast inference is now widespread, parameter learning in random fields has remained an intractable problem. this paper shows how to apply fast inference algorithms, in particular graph cuts, to learn parameters of random fields with similar efficiency. we find optimal parameter values under standard regularized objective functions that ensure good generalization. our algorithm enables learning of many parameters in reasonable time, and we explore further speedup techniques. we also discuss extensions to non-associative and multi-class problems. we evaluate the method on image segmentation and geometry recognition.
active contour based segmentation of 3d surfaces. algorithms incorporating 3d information have proven to be superior to purely 2d approaches in many areas of computer vision including face biometrics and recognition. still, the range of methods for feature extraction from 3d surfaces is limited. very popular in 2d image analysis, active contours have been generalized to curved surfaces only recently. current implementations require a global surface parametrisation. we show that a balloon force cannot be included properly in existing methods, making them unsuitable for applications with noisy data. to overcome this drawback we propose a new algorithm for evolving geodesic active contours on implicit surfaces. we also introduce a new narrowband scheme which results in linear computational complexity. the performance of our model is illustrated on various real and synthetic 3d surfaces.
online tracking and reacquisition using co-trained generative and discriminative trackers. visual tracking is a challenging problem, as an object may change its appearance due to viewpoint variations, illumination changes, and occlusion. also, an object may leave the field of view and then reappear. in order to track and reacquire an unknown object with limited labeling data, we propose to learn these changes online and build a model that describes all seen appearance while tracking. to address this semi-supervised learning problem, we propose a co-training based approach to continuously label incoming data and online update a hybrid discriminative generative model. the generative model uses a number of low dimension linear subspaces to describe the appearance of the object. in order to reacquire an object, the generative model encodes all the appearance variations that have been seen. a discriminative classifier is implemented as an online support vector machine, which is trained to focus on recent appearance variations. the online co-training of this hybrid approach accounts for appearance changes and allows reacquisition of an object after total occlusion. we demonstrate that under challenging situations, this method has strong reacquisition ability and robustness to distracters in background.
shape-based retrieval of heart sounds for disease similarity detection. retrieval of similar heart sounds from a sound database has applications in physician training, diagnostic screening, and decision support. in this paper, we exploit a visual rendering of heart sounds and model the morphological variations of audio envelopes through a constrained non-rigid translation transform. similar heart sounds are then retrieved by recovering the corresponding alignment transform using a variant of shape-based dynamic time warping. results of similar heart sound retrieval are demonstrated for various diseases on a large database of heart sounds.
compressive sensing for background subtraction. compressive sensing (cs) is an emerging field that provides a framework for image recovery using sub-nyquist sampling rates. the cs theory shows that a signal can be reconstructed from a small set of random projections, provided that the signal is sparse in some basis, e.g., wavelets. in this paper, we describe a method to directly recover background subtracted images using cs and discuss its applications in some communication constrained multi-camera computer vision problems. we show how to apply the cs theory to recover object silhouettes (binary background subtracted images) when the objects of interest occupy a small portion of the camera view, i.e., when they are sparse in the spatial domain. we cast the background subtraction as a sparse approximation problem and provide different solutions based on convex optimization and total variation. in our method, as opposed to learning the background, we learn and adapt a low dimensional compressed representation of it, which is sufficient to determine spatial innovations; object silhouettes are then estimated directly using the compressive samples without any auxiliary image reconstruction. we also discuss simultaneous appearance recovery of the objects using compressive measurements. in this case, we show that it may be necessary to reconstruct one auxiliary image. to demonstrate the performance of the proposed algorithm, we provide results on data captured using a compressive single-pixel camera. we also illustrate that our approach is suitable for image coding in communication constrained problems by using data captured by multiple conventional cameras to provide 2d tracking and 3d shape reconstruction results with compressive measurements.
latent pose estimator for continuous action recognition. recently, models based on conditional random fields (crf) have produced promising results on labeling sequential data in several scientific fields. however, in the vision task of continuous action recognition, the observations of visual features have dimensions as high as hundreds or even thousands. this might pose severe difficulties on parameter estimation and even degrade the performance. to bridge the gap between the high dimensional observations and the random fields, we propose a novel model that replace the observation layer of a traditional random fields model with a latent pose estimator. in training stage, the human pose is not observed in the action data, and the latent pose estimator is learned under the supervision of the labeled action data, instead of image-to-pose data. the advantage of this model is twofold. first, it learns to convert the high dimensional observations into more compact and informative representations. second, it enables transfer learning to fully utilize the existing knowledge and data on image-to-pose relationship. the parameters of the latent pose estimator and the random fields are jointly optimized through a gradient ascent algorithm. our approach is tested on humaneva [1] --- a publicly available dataset. the experiments show that our approach can improve recognition accuracy over standard crf model and its variations. the performance can be further significantly improved by using additional image-to-pose data for training. our experiments also show that the model trained on humaneva can generalize to different environment and human subjects.
event modeling and recognition using markov logic networks. we address the problem of visual event recognition in surveillance where noise and missing observations are serious problems. common sense domain knowledge is exploited to overcome them. the knowledge is represented as first-order logic production rules with associated weights to indicate their confidence. these rules are used in combination with a relaxed deduction algorithm to construct a network of grounded atoms, the markov logic network. the network is used to perform probabilistic inference for input queries about events of interest. the system's performance is demonstrated on a number of videos from a parking lot domain that contains complex interactions of people and vehicles.
unsupervised structure learning: hierarchical recursive composition, suspicious coincidence and competitive exclusion. we describe a new method for unsupervised structure learning of a hierarchical compositional model (hcm) for deformable objects. the learning is unsupervised in the sense that we are given a training dataset of images containing the object in cluttered backgrounds but we do not know the position or boundary of the object. the structure learning is performed by a bottom-up and top-down process. the bottom-up process is a novel form of hierarchical clustering which recursively composes proposals for simple structures to generate proposals for more complex structures. we combine standard clustering with the suspicious coincidence principle and the competitive exclusion principle to prune the number of proposals to a practical number and avoid an exponential explosion of possible structures. the hierarchical clustering stops automatically, when it fails to generate new proposals, and outputs a proposal for the object model. the top-down process validates the proposals and fills in missing elements. we tested our approach by using it to learn a hierarchical compositional model for parsing and segmenting horses on weizmann dataset. we show that the resulting model is comparable with (or better than) alternative methods. the versatility of our approach is demonstrated by learning models for other objects (e.g., faces, pianos, butterflies, monitors, etc.). it is worth noting that the low-levels of the object hierarchies automatically learn generic image features while the higher levels learn object specific features.
determining patch saliency using low-level context. the increased use of context for high level reasoning has been popular in recent works to increase recognition accuracy. in this paper, we consider an orthogonal application of context. we explore the use of context to determine which low-level appearance cues in an image are salient or representative of an image's contents. existing classes of low-level saliency measures for image patches include those based on interest points, as well as supervised discriminative measures. we propose a new class of unsupervised contextual saliency measures based on co-occurrence and spatial information between image patches. for recognition, image patches are sampled using a weighted random sampling based on saliency, or using a sequential approach based on maximizing the likelihoods of the image patches. we compare the different classes of saliency measures, along with a baseline uniform measure, for the task of scene and object recognition using the bag-of-features paradigm. in our results, the contextual saliency measures achieve improved accuracies over the previous methods. moreover, our highest accuracy is achieved using a sparse sampling of the image, unlike previous approaches who's performance increases with the sampling density.
window annealing over square lattice markov random field. monte carlo methods and their subsequent simulated annealing are able to minimize general energy functions. however, the slow convergence of simulated annealing compared with more recent deterministic algorithms such as graph cuts and belief propagation hinders its popularity over the large dimensional markov random field (mrf). in this paper, we propose a new efficient sampling-based optimization algorithm called wa (window annealing) over squared lattice mrf, in which cluster sampling and annealing concepts are combined together. unlike the conventional annealing process in which only the temperature variable is scheduled, we design a series of artificial "guiding" (auxiliary) probability distributions based on the general sequential monte carlo framework. these auxiliary distributions lead to the maximum a posteriori (map) state by scheduling both the temperature and the proposed maximum size of the windows (rectangular cluster) variable. this new annealing scheme greatly enhances the mixing rate and consequently reduces convergence time. moreover, by adopting the integral image technique for computation of the proposal probability of a sampled window, we can achieve a dramatic reduction in overall computations. the proposed wa is compared with several existing monte carlo based optimization techniques as well as state-of-the-art deterministic methods including graph cut (gc) and sequential tree re-weighted belief propagation (trw-s) in the pairwise mrf stereo problem. the experimental results demonstrate that the proposed wa method is comparable with gc in both speed and obtained energy level.
articulated multi-body tracking under egomotion. in this paper, we address the problem of 3d articulated multi-person tracking in busy street scenes from a moving, human-level observer. in order to handle the complexity of multi-person interactions, we propose to pursue a two-stage strategy. a multi-body detection-based tracker first analyzes the scene and recovers individual pedestrian trajectories, bridging sensor gaps and resolving temporary occlusions. a specialized articulated tracker is then applied to each recovered pedestrian trajectory in parallel to estimate the tracked person's precise body pose over time. this articulated tracker is implemented in a gaussian process framework and operates on global pedestrian silhouettes using a learned statistical representation of human body dynamics. we interface the two tracking levels through a guided segmentation stage, which combines traditional bottom-up cues with top-down information from a human detector and the articulated tracker's shape prediction. we show the proposed approach's viability and demonstrate its performance for articulated multi-person tracking on several challenging video sequences of a busy inner-city scenario.
learning visual shape lexicon for document image content recognition. developing effective content recognition methods for diverse imagery continues to challenge computer vision researchers. we present a new approach for document image content categorization using a lexicon of shape features. each lexical word corresponds to a scale and rotation invariant shape feature that is generic enough to be detected repeatably and segmentation free. we learn a concise, structurally indexed shape lexicon from training by clustering and partitioning feature types through graph cuts. we demonstrate our approach on two challenging document image content recognition problems: 1) the classification of 4,500 web images crawled from google image search into three content categories -- pure image, image with text, and document image, and 2) language identification of 8 languages (arabic, chinese, english, hindi, japanese, korean, russian, and thai) on a 1,512 complex document image database composed of mixed machine printed text and handwriting. our approach is capable to handle high intra-class variability and shows results that exceed other state-of-the-art approaches, allowing it to be used as a content recognizer in image indexing and retrieval systems.
face alignment via component-based discriminative search. in this paper, we propose a component-based discriminative approach for face alignment without requiring initialization. unlike many approaches which locally optimize in a small range, our approach searches the face shape in a large range at the component level by a discriminative search algorithm. specifically, a set of direction classifiers guide the search of the configurations of facial components among multiple detected modes of facial components. the direction classifiers are learned using a large number of aligned local patches and misaligned local patches from the training data. the discriminative search is extremely effective and able to find very good alignment results only in a few (2~3) search iterations. as the new approach gives excellent alignment results on the commonly used datasets (e.g., ar [18], feret [21]) created under-controlled conditions, we evaluate our approach on a more challenging dataset containing over 1,700 well-labeled facial images with a large range of variations in pose, lighting, expression, and background. the experimental results show the superiority of our approach on both accuracy and efficiency.
improving the agility of keyframe-based slam. the ability to localise a camera moving in a previously unknown environment is desirable for a wide range of applications. in computer vision this problem is studied as monocular slam. recent years have seen improvements to the usability and scalability of monocular slam systems to the point that they may soon find uses outside of laboratory conditions. however, the robustness of these systems to rapid camera motions (we refer to this quality as agility) still lags behind that of tracking systems which use known object models. in this paper we attempt to remedy this. we present two approaches to improving the agility of a keyframe-based slam system: firstly, we add edge features to the map and exploit their resilience to motion blur to improve tracking under fast motion. secondly, we implement a very simple inter-frame rotation estimator to aid tracking when the camera is rapidly panning --- and demonstrate that this method also enables a trivially simple yet effective relocalisation method. results show that a slam system combining points, edge features and motion initialisation allows highly agile tracking at a moderate increase in processing time.
anisotropic geodesics for perceptual grouping and domain meshing. this paper shows how voronoi diagrams and their dual delaunay complexes, defined with geodesic distances over 2d reimannian manifolds, can be used to solve two important problems encountered in computer vision and graphics. the first problem studied is perceptual grouping which is a curve reconstruction problem where one should complete in a meaningful way a sparse set of noisy curves. from this latter curves, our grouping algorithm first designs an anisotropic tensor field that corresponds to a reimannian metric. then, according to this metric, the delaunay graph is constructed and pruned in order to correctly link together salient features. the second problem studied is planar domain meshing, where one should build a good quality triangulation of a given domain. our meshing algorithm is a geodesic delaunay refinement method that exploits an anisotropic tensor field in order to locally impose the orientation and aspect ratio of the created triangles.
relevant feature selection for human pose estimation and localization in cluttered images. we address the problem of estimating human body pose from a single image with cluttered background. we train multiple local linear regressors for estimating the 3d pose from a feature vector of gradient orientation histograms. each linear regressor is capable of selecting relevant components of the feature vector depending on pose by training it on a pose cluster which is a subset of the training samples with similar pose. for discriminating the pose clusters, we use kernel support vector machines (svm) with pose-dependent feature selection. we achieve feature selection for kernel svms by estimating scale parameters of rbf kernel through minimization of the radius/margin bound, which is an upper bound of the expected generalization error, with efficient gradient descent. human detection is also possible with these svms. quantitative experiments show the effectiveness of pose-dependent feature selection to both human detection and pose estimation.
deformed lattice discovery via efficient mean-shift belief propagation. we introduce a novel framework for automatic detection of repeated patterns in real images. the novelty of our work is to formulate the extraction of an underlying deformed lattice as a spatial, multi-target tracking problem using a new and efficient mean-shift belief propagation (msbp) method. compared to existing work, our approach has multiple advantages, including: 1) incorporating higher order constraints early-on to propose highly plausible lattice points; 2) growing a lattice in multiple directions simultaneously instead of one at a time sequentially; and 3) achieving more efficient and more accurate performance than state-of-the-art algorithms. these advantages are demonstrated by quantitative experimental results on a diverse set of real world photos.
smd: a locally stable monotonic change invariant feature descriptor. extraction and matching of discriminative feature points in images is an important problem in computer vision with applications in image classification, object recognition, mosaicing, automatic 3d reconstruction and stereo. features are represented and matched via descriptors that must be invariant to small errors in the localization and scale of the extracted feature point, viewpoint changes, and other kinds of changes such as illumination, image compression and blur. while currently used feature descriptors are able to deal with many of such changes, they are not invariant to a generic monotonic change in the intensities, which occurs in many cases. furthermore, their performance degrades rapidly with many image degradations such as blur and compression where the intensity transformation is non-linear. in this paper, we present a new feature descriptor that obtains invariance to a monotonic change in the intensity of the patch by looking at orders between certain pixels in the patch. an order change between pixels indicates a difference between the patches which is penalized. summation of such penalties over carefully chosen pixel pairs that are stable to small errors in their localization and are independent of each other leads to a robust measure of change between two features. promising results were obtained using this approach that show significant improvement over existing methods, especially in the case of illumination change, blur and jpeg compression where the intensity of the points changes from one image to the next.
robust object tracking by hierarchical association of detection responses. we present a detection-based three-level hierarchical association approach to robustly track multiple objects in crowded environments from a single camera. at the low level, reliable tracklets (i.e. short tracks for further analysis) are generated by linking detection responses based on conservative affinity constraints. at the middle level, these tracklets are further associated to form longer tracklets based on more complex affinity measures. the association is formulated as a map problem and solved by the hungarian algorithm. at the high level, entries, exits and scene occluders are estimated using the already computed tracklets, which are used to refine the final trajectories. this approach is applied to the pedestrian class and evaluated on two challenging datasets. the experimental results show a great improvement in performance compared to previous methods.
optimization of symmetric transfer error for sub-frame video synchronization. in this work we present a method to synchronize video sequences of events that are acquired via uncalibrated cameras at unknown and dynamically varying temporal offsets. unlike existing methods that synchronize videos of similar events (i.e., videos related to each other through the motion in the scene) up to an integer alignment, we establish sub-frame video synchronization. while contemporary synchronization algorithms implement a unidirectional alignment which biases the results towards a single reference sequence, we adopt a bi-directional or symmetrical alignment approach that results in a more optimal synchronization. to this end, we propose a novel symmetric transfer error which is dynamically minimized, and reduces the propagation of error from feature extraction and spatial mapping into temporal synchronization. the advantages of our approach are validated by tests conducted on (publicly available) real and synthetic sequences. we present qualitative and quantitative comparisons with another state-of-the-art algorithm. a unique application of this work in generating high-resolution 4d mri data from multiple low-resolution mri scans is described.
linear time maximally stable extremal regions. in this paper we present a new algorithm for computing maximally stable extremal regions (mser), as invented by matas et al. the standard algorithm makes use of a union-find data structure and takes quasi-linear time in the number of pixels. the new algorithm provides exactly identical results in true worst-case linear time. moreover, the new algorithm uses significantly less memory and has better cache-locality, resulting in faster execution. our cpu implementation performs twice as fast as a state-of-the-art fpga implementation based on the standard algorithm.the new algorithm is based on a different computational ordering of the pixels, which is suggested by another immersion analogy than the one corresponding to the standard connected-component algorithm. with the new computational ordering, the pixels considered or visited at any point during computation consist of a single connected component of pixels in the image, resembling a flood-fill that adapts to the grey-level landscape. the computation only needs a priority queue of candidate pixels (the boundary of the single connected component), a single bit image masking visited pixels, and information for as many components as there are grey-levels in the image. this is substantially more compact in practice than the standard algorithm, where a large number of connected components must be considered in parallel. the new algorithm can also generate the component tree of the image in true linear time. the result shows that mser detection is not tied to the union-find data structure, which may open more possibilities for parallelization.
video registration using dynamic textures. we propose a dynamic texture feature-based algorithm for registering two video sequences of a rigid or nonrigid scene taken from two synchronous or asynchronous cameras. we model each video sequence as the output of a linear dynamical system, and transform the task of registering frames of the two sequences to that of registering the parameters of the corresponding models. this allows us to perform registration using the more classical image-based features as opposed to space-time features, such as space-time volumes or feature trajectories. as the model parameters are not uniquely defined, we propose a generic method to resolve these ambiguities by jointly identifying the parameters from multiple video sequences. we finally test our algorithm on a wide variety of challenging video sequences and show that it matches the performance of significantly more computationally expensive existing methods.
a comparative analysis of ransac techniques leading to adaptive real-time random sample consensus. the random sample consensus (ransac) algorithm is a popular tool for robust estimation problems in computer vision, primarily due to its ability to tolerate a tremendous fraction of outliers. there have been a number of recent efforts that aim to increase the efficiency of the standard ransac algorithm. relatively fewer efforts, however, have been directed towards formulating ransac in a manner that is suitable for real-time implementation. the contributions of this work are two-fold: first, we provide a comparative analysis of the state-of-the-art ransac algorithms and categorize the various approaches. second, we develop a powerful new framework for real-time robust estimation. the technique we develop is capable of efficiently adapting to the constraints presented by a fixed time budget, while at the same time providing accurate estimation over a wide range of inlier ratios. the method shows significant improvements in accuracy and speed over existing techniques.
hierarchical support vector random fields: joint training to combine local and global features. recently, impressive results have been reported for the detection of objects in challenging real-world scenes. interestingly however, the underlying models vary greatly even between the most successful approaches. methods using a global feature descriptor (e.g. ) paired with discriminative classifiers such as svms enable high levels of performance, but require large amounts of training data and typically degrade in the presence of partial occlusions. local feature-based approaches (e.g. ) are more robust in the presence of partial occlusions but often produce a significant number of false positives. this paper proposes a novel approach called hierarchical support vector random field that allows 1) to combine the power of global feature-based approaches with the flexibility of local feature-based methods in one consistent multi-layer framework and 2) to automatically learn the tradeoff and the optimal interplay between local, semi-local and global feature contributions. experiments show that both the combination of local and global features as well as the joint training result in improved detection performance on challenging datasets.
fourier analysis of the 2d screened poisson equation for gradient domain problems. we analyze the problem of reconstructing a 2d function that approximates a set of desired gradients and a data term. the combined data and gradient terms enable operations like modifying the gradients of an image while staying close to the original image. starting with a variational formulation, we arrive at the "screened poisson equation" known in physics. analysis of this equation in the fourier domain leads to a direct, exact, and efficient solution to the problem. further analysis reveals the structure of the spatial filters that solve the 2d screened poisson equation and shows gradient scaling to be a well-defined sharpen filter that generalizes laplacian sharpening, which itself can be mapped to gradient domain filtering. results using a dct-based screened poisson solver are demonstrated on several applications including image blending for panoramas, image sharpening, and de-blocking of compressed images.
an efficient dense and scale-invariant spatio-temporal interest point detector. over the years, several spatio-temporal interest point detectors have been proposed. while some detectors can only extract a sparse set of scale-invariant features, others allow for the detection of a larger amount of features at user-defined scales. this paper presents for the first time spatio-temporal interest points that are at the same time scale-invariant (both spatially and temporally) and densely cover the video content. moreover, as opposed to earlier work, the features can be computed efficiently. applying scale-space theory, we show that this can be achieved by using the determinant of the hessian as the saliency measure. computations are speeded-up further through the use of approximative box-filter operations on an integral video structure. a quantitative evaluation and experimental results on action recognition show the strengths of the proposed detector in terms of repeatability, accuracy and speed, in comparison with previously proposed detectors.
efficient edge-based methods for estimating manhattan frames in urban imagery. we address the problem of efficiently estimating the rotation of a camera relative to the canonical 3d cartesian frame of an urban scene, under the so-called "manhattan world" assumption [1,2]. while the problem has received considerable attention in recent years, it is unclear how current methods stack up in terms of accuracy and efficiency, and how they might best be improved. it is often argued that it is best to base estimation on all pixels in the image [2]. however, in this paper, we argue that in a sense, less can be more: that basing estimation on sparse, accurately localized edges, rather than dense gradient maps, permits the derivation of more accurate statistical models and leads to more efficient estimation. we also introduce and compare several different search techniques that have advantages over prior approaches. a cornerstone of the paper is the establishment of a new public groundtruth database which we use to derive required statistics and to evaluate and compare algorithms.
regularized partial matching of rigid shapes. matching of rigid shapes is an important problem in numerous applications across the boundary of computer vision, pattern recognition and computer graphics communities. a particularly challenging setting of this problem is partial matching, where the two shapes are dissimilar in general, but have significant similar parts. in this paper, we show a rigorous approach allowing to find matching parts of rigid shapes with controllable size and regularity. the regularity term we use is similar to the spirit of the mumford-shah functional, extended to non-euclidean spaces. numerical experiments show that the regularized partial matching produces better results compared to the non-regularized one.
unsupervised classification and part localization by consistency amplification. we present a novel method for unsupervised classification, including the discovery of a new category and precise object and part localization. given a set of unlabelled images, some of which contain an object of an unknown category, with unknown location and unknown size relative to the background, the method automatically identifies the images that contain the objects, localizes them and their parts, and reliably learns their appearance and geometry for subsequent classification. current unsupervised methods construct classifiers based on a fixed set of initial features. instead, we propose a new approach which iteratively extracts new features and re-learns the induced classifier, improving class vs. non-class separation at each iteration. we develop two main tools that allow this iterative combined search. the first is a novel star-like model capable of learning a geometric class representation in the unsupervised setting. the second is learning of "part specific features" that are optimized for parts detection, and which optimally combine different part appearances discovered in the training examples. these novel aspects lead to precise part localization and to improvement in overall classification performance compared with previous methods. we applied our method to multiple object classes from caltech-101, uiuc and a sub-classification problem from pascal. the obtained results are comparable to state-of-the-art supervised classification techniques and superior to state-of-the-art unsupervised approaches previously applied to the same image sets.
simultaneous visual recognition of manipulation actions and manipulated objects. the visual analysis of human manipulation actions is of interest for e.g. human-robot interaction applications where a robot learns how to perform a task by watching a human. in this paper, a method for classifying manipulation actions in the context of the objects manipulated, and classifying objects in the context of the actions used to manipulate them is presented. hand and object features are extracted from the video sequence using a segmentation based approach. a shape based representation is used for both the hand and the object. experiments show this representation suitable for representing generic shape classes. the action-object correlation over time is then modeled using conditional random fields. experimental comparison show great improvement in classification rate when the action-object correlation is taken into account, compared to separate classification of manipulation actions and manipulated objects.
finding actions using shape flows. we propose a novel method for action detection based on a new action descriptor called a shape flow that represents both the shape and movement of an object in a holistic and parsimonious manner. we find actions by finding shape flows in a target video that are similar to a template shape flow. shape flows are largely independent of appearance, and the match cost function that we propose is invariant to scale changes and smooth nonlinear deformation in space and time. the problem of matching shape flows is difficult, however, yielding a large, non-convex, integer program. we propose a novel relaxation method based on successive convexification that converts this hard program into a vastly smaller linear program: by using only those variables that appear on the 4d lower convex hull of the matching cost volume, most of the variables in the linear program may be eliminated. experiments confirm that the proposed shape flow method can successfully detect complex actions in cluttered video, even with self-occlusion, camera motion, and intra-class variation.
scene segmentation using the wisdom of crowds. given a collection of images of a static scene taken by many different people, we identify and segment interesting objects. to solve this problem, we use the distribution of images in the collection along with a new field-of-view cue, which leverages the observation that people tend to take photos that frame an object of interest within the field of view. hence, image features that appear together in many images are likely to be part of the same object. we evaluate the effectiveness of this cue by comparing the segmentations computed by our method against hand-labeled ones for several different models. we also show how the results of our segmentations can be used to highlight important objects in the scene and label them using noisy user-specified textual tag data. these methods are demonstrated on photos of several popular tourist sites downloaded from the internet.
feature correspondence via graph matching: models and global optimization. in this paper we present a new approach for establishing correspondences between sparse image features related by an unknown non-rigid mapping and corrupted by clutter and occlusion, such as points extracted from a pair of images containing a human figure in distinct poses. we formulate this matching task as an energy minimization problem by defining a complex objective function of the appearance and the spatial arrangement of the features. optimization of this energy is an instance of graph matching, which is in general a np-hard problem. we describe a novel graph matching optimization technique, which we refer to as dual decomposition (dd), and demonstrate on a variety of examples that this method outperforms existing graph matching algorithms. in the majority of our examples dd is able to find the global minimum within a minute. the ability to globally optimize the objective allows us to accurately learn the parameters of our matching model from training examples. we show on several matching tasks that our learned model yields results superior to those of state-of-the-art methods.
fast automatic single-view 3-d reconstruction of urban scenes. we consider the problem of estimating 3-d structure from a single still image of an outdoor urban scene. our goal is to efficiently create 3-d models which are visually pleasant. we chose an appropriate 3-d model structure and formulate the task of 3-d reconstruction as model fitting problem. our 3-d models are composed of a number of vertical walls and a ground plane, where ground-vertical boundary is a continuous polyline. we achieve computational efficiency by special preprocessing together with stepwise search of 3-d model parameters dividing the problem into two smaller sub-problems on chain graphs. the use of conditional random field models for both problems allows to various cues. we infer orientation of vertical walls of 3-d model vanishing points.
statistical analysis of global motion chains. multiple elements such as lighting, colors, dialogue, and camera motion contribute to the style of a movie. among them, camera motion is commonly overlooked yet a crucial point. for instance, documentaries tend to use long smooth pans whereas action movies usually have short and dynamic movements. this information, also referred to as global motion, could be leveraged by various applications in video clustering, stabilization, and editing. we perform analyses to study the in-class characteristics of these motions as well as their relationship with motions of other movie types. in particular, we model global motion as a multi-scale distribution of transformation matrices from frame to frame. secondly, we quantify the difference between pairs of videos using the kl-divergence of these distributions. finally, we demonstrate an application modeling and clustering commercial and amateur videos. experiments performed show advantage compared to the usage of some local motion-based approaches.
region-based 2d deformable generalized cylinder for narrow structures segmentation. in this paper, we present a region-based deformable cylinder model, extending the work on classical region-based active contours and gradient-based ribbon snakes. defined by a central curve playing the role of the medial axis and a variable thickness, the model is endowed with a region-dependent term.this energy follows the narrow band principle, in order to handle local region properties while overcoming limitations of classical edge-based models. the energy is subsequently transformed and derived in order to allow implementation on a polygonal line deformed with gradient descent. the model is used to extract path-like objects in medical and aerial images.
robust scale estimation from ensemble inlier sets for random sample consensus methods. this paper proposes a ransac modification that performs automatic estimation of the scale of inlier noise. the scale estimation takes advantage of accumulated inlier sets from all proposed models. it is shown that the proposed method gives robust results in case of high outlier ratio data, in spite that no user specified threshold is needed. the method also improves sampling efficiency, without requiring any auxiliary information other than the data to be modeled.
kernel codebooks for scene categorization. this paper introduces a method for scene categorization by modeling ambiguity in the popular codebook approach. the codebook approach describes an image as a bag of discrete visual codewords, where the frequency distributions of these words are used for image categorization. there are two drawbacks to the traditional codebook model: codeword uncertainty and codeword plausibility. both of these drawbacks stem from the hard assignment of visual features to a single codeword. we show that allowing a degree of ambiguity in assigning codewords improves categorization performance for three state-of-the-art datasets.
behind the depth uncertainty: resolving ordinal depth in sfm. structure from motion(sfm) is beset by the noise sensitivity problem. previous works show that some motion ambiguities are inherent and errors in the motion estimates are inevitable. these errors may render accurate metric depth estimate difficult to obtain. however, can we still extract some valid and useful depth information from the inaccurate metric depth estimates? in this paper, the resolution of ordinal depth extracted from the inaccurate metric depth is investigated. based on a general depth distortion model, a sufficient condition is derived for ordinal depth to be extracted validly. by studying the geometry and statistics of the image regions satisfying this condition, we found that although metric depth estimates are inaccurate, ordinal depth can still be discerned locally if physical metric depth difference is beyond certain discrimination threshold. the resolution level of discernible ordinal depth decreases as the visual angle subtended by the points increases, as the speed of the motion carrying the depth information decreases, and as points recede from the camera. these findings suggest that accurate knowledge of qualitative 3d structure is ensured in a small local image neighborhood, which might account for biological foveated vision and shed light on the nature of the perceived visual space.
direct bundle estimation for recovery of shape, reflectance property and light position. given a set of images captured with a fixed camera while a point light source moves around an object, we can estimate the shape, reflectance property and texture of the object, as well as the positions of the light source. our formulation is a large-scale nonlinear optimization that allows us to adjust the parameters so that the images synthesized from all of the parameters optimally fit the input images. this type of optimization, which is a variation of the bundle adjustment for structure and motion reconstruction, is often employed to refine a carefully constructed initial estimation. however, the initialization task often requires a great deal of labor, several special devices, or both. in the present paper, we describe (i) an easy method of initialization that does not require any special devices or a precise calibration and (ii) an efficient algorithm for the optimization. the efficiency of the optimization method enables us to use a simple initialization. for a set of synthesized images, the proposed method decreases the residual to zero. in addition, we show that various real objects, including toy models and human faces, can be successfully recovered.
photo and video quality evaluation: focusing on the subject. traditionally, distinguishing between high quality professional photos and low quality amateurish photos is a human task. to automatically assess the quality of a photo that is consistent with humans perception is a challenging topic in computer vision. various differences exist between photos taken by professionals and amateurs because of the use of photography techniques. previous methods mainly use features extracted from the entire image. in this paper, based on professional photography techniques, we first extract the subject region from a photo, and then formulate a number of high-level semantic features based on this subject and background division. we test our features on a large and diverse photo database, and compare our method with the state of the art. our method performs significantly better with a classification rate of 93% versus 72% by the best existing method. in addition, we conduct the first study on high-level video quality assessment. our system achieves a precision of over 95% in a reasonable recall rate for both photo and video assessments. we also show excellent application results in web image search re-ranking.
partial difference equations over graphs: morphological processing of arbitrary discrete data. mathematical morphology (mm) offers a wide range of operators to address various image processing problems. these processing can be defined in terms of algebraic set or as partial differential equations (pdes). in this paper, a novel approach is formalized as a framework of partial difference equations (pdes) on weighted graphs. we introduce and analyze morphological operators in local and nonlocal configurations. our framework recovers classical local algebraic and pdes-based morphological methods in image processing context; generalizes them for nonlocal configurations and extends them to the treatment of any arbitrary discrete data that can be represented by a graph. it leads to considering a new field of application of mm processing: the case of high-dimensional multivariate unorganized data.
scale-dependent/invariant local 3d shape descriptors for fully automatic registration of multiple sets of range images. despite the ubiquitous use of range images in various computer vision applications, little has been investigated about the size variation of the local geometric structures captured in the range images. in this paper, we show that, through canonical geometric scale-space analysis, this geometric scale-variability embedded in a range image can be exploited as a rich source of discriminative information regarding the captured geometry. we extend previous work on geometric scale-space analysis of 3d models to analyze the scale-variability of a range image and to detect scale-dependent 3d features --- geometric features with their inherent scales. we derive novel local 3d shape descriptors that encode the local shape information within the inherent support region of each feature. we show that the resulting set of scale-dependent local shape descriptors can be used in an efficient hierarchical registration algorithm for aligning range images with the same global scale. we also show that local 3d shape descriptors invariant to the scale variation can be derived and used to align range images with significantly different global scales. finally, we demonstrate that the scale-dependent/invariant local 3d shape descriptors can even be used to fully automatically register multiple sets of range images with varying global scales corresponding to multiple objects.
automatic generator of minimal problem solvers. finding solutions to minimal problems for estimating epipolar geometry and camera motion leads to solving systems of algebraic equations. often, these systems are not trivial and therefore special algorithms have to be designed to achieve numerical robustness and computational efficiency. the state of the art approach for constructing such algorithms is the gröbner basis method for solving systems of polynomial equations. previously, the gröbner basis solvers were designed ad hoc for concrete problems and they could not be easily applied to new problems. in this paper we propose an automatic procedure for generating gröbner basis solvers which could be used even by non-experts to solve technical problems. the input to our solver generator is a system of polynomial equations with a finite number of solutions. the output of our solver generator is the matlab or c code which computes solutions to this system for concrete coefficients. generating solvers automatically opens possibilities to solve more complicated problems which could not be handled manually or solving existing problems in a better and more efficient way. we demonstrate that our automatic generator constructs efficient and numerically stable solvers which are comparable or outperform known manually constructed solvers. the automatic generator is available at http://cmp.felk.cvut.cz/minimal
segmenting fiber bundles in diffusion tensor images. we consider the problem of segmenting fiber bundles in diffusion tensor images. we cast this problem as a manifold clustering problem in which different fiber bundles correspond to different submanifolds of the space of diffusion tensors. we first learn a local representation of the diffusion tensor data using a generalization of the locally linear embedding (lle) algorithm from euclidean to diffusion tensor data. such a generalization exploits geometric properties of the space of symmetric positive semi-definite matrices, particularly its riemannian metric. then, under the assumption that different fiber bundles are physically distinct, we show that the null space of a matrix built from the local representation gives the segmentation of the fiber bundles. our method is computationally simple, can handle large deformations of the principal direction along the fiber tracts, and performs automatic segmentation without requiring previous fiber tracking. results on synthetic and real diffusion tensor images are also presented.
constrained maximum likelihood learning of bayesian networks for facial action recognition. probabilistic graphical models such as bayesian networks have been increasingly applied to many computer vision problems. accuracy of inferences in such models depends on the quality of network parameters. learning reliable parameters of bayesian networks often requires a large amount of training data, which may be hard to acquire and may contain missing values. on the other hand, qualitative knowledge is available in many computer vision applications, and incorporating such knowledge can improve the accuracy of parameter learning. this paper describes a general framework based on convex optimization to incorporate constraints on parameters with training data to perform bayesian network parameter estimation. for complete data, a global optimum solution to maximum likelihood estimation is obtained in polynomial time, while for incomplete data, a modified expectation-maximization method is proposed. this framework is applied to real image data from a facial action unit recognition problem and produces results that are similar to those of state-of-the-art methods.
view point tracking of rigid objects based on shape sub-manifolds. we study the task to infer and to track the viewpoint onto a 3d rigid object by observing its image contours in a sequence of images. to this end, we consider the manifold of invariant planar contours and learn the low-dimensional submanifold corresponding to the object contours by observing the object off-line from a number of different viewpoints. this submanifold of object contours can be parametrized by the view sphere and, in turn, be used for keeping track of the object orientation relative to the observer, through interpolating samples on the submanifold in a geometrically proper way. our approach replaces explicit 3d object models by the corresponding invariant shape submanifolds that are learnt from a sufficiently large number of image contours, and is applicable to arbitrary objects.
multi-scale improves boundary detection in natural images. in this work we empirically study the multi-scale boundary detection problem in natural images. we utilize local boundary cues including contrast, localization and relative contrast, and train a classifier to integrate them across scales. our approach successfully combines strengths from both large-scale detection (robust but poor localization) and small-scale detection (detail-preserving but sensitive to clutter). we carry out quantitative evaluations on a variety of boundary and object datasets with human-marked groundtruth. we show that multi-scale boundary detection offers large improvements, ranging from 20% to 50%, over single-scale approaches. this is the first time that multi-scale is demonstrated to improve boundary detection on large datasets of natural images.
a probabilistic cascade of detectors for individual object recognition. a probabilistic system for recognition of individual objects is presented. the objects to recognize are composed of constellations of features, and features from a same object share the common reference frame of the image in which they are detected. features appearance and pose are modeled by probabilistic distributions, the parameters of which are shared across features in order to allow training from few examples.in order to avoid an expensive combinatorial search, our recognition system is organized as a cascade of well-established, simple and inexpensive detectors. the candidate hypotheses output by our algorithm are evaluated by a generative probabilistic model that takes into account each stage of the matching process.we apply our ideas to the problem of individual object recognition and test our method on several data-sets. we compare with lowe's algorithm [7] and demonstrate significantly better performance.
sparse long-range random field and its application to image denoising. many recent techniques for low-level vision problems such as image denoising are formulated in terms of markov random field (mrf) or conditional random field (crf) models. nonetheless, the role of the underlying graph structure is still not well understood. on the one hand there are pairwise structures where each node is connected to its local neighbors. these models tend to allow for fast algorithms but do not capture important higher-order statistics of natural scenes. on the other hand there are more powerful models such as field of experts (foe) that consider joint distributions over larger cliques in order to capture image statistics but are computationally challenging. in this paper we consider a graph structure with longer range connections that is designed to both capture important image statistics and be computationally efficient. this structure incorporates long-range connections in a manner that limits the cliques to size 3, thereby capturing important second-order image statistics while still allowing efficient optimization due to the small clique size. we evaluate our approach by testing the models on widely used datasets. the results show that our method is comparable to the current state-of-the-art in terms of psnr, is better at preserving fine-scale detail and producing natural-looking output, and is more than an order of magnitude faster.
learning optical flow. assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. in contrast to standard heuristic formulations, we learn a statistical model of both brightness constancy error and the spatial properties of optical flow using image sequences with associated ground truth flow fields. the result is a complete probabilistic model of optical flow. specifically, the ground truth enables us to model how the assumption of brightness constancy is violated in naturalistic sequences, resulting in a probabilistic model of "brightness inconstancy". we also generalize previous high-order constancy assumptions, such as gradient constancy, by modeling the constancy of responses to various linear filters in a high-order random field framework. these filters are free variables that can be learned from training data. additionally we study the spatial structure of the optical flow and how motion boundaries are related to image intensity boundaries. spatial smoothness is modeled using a steerable random field, where spatial derivatives of the optical flow are steered by the image brightness structure. these models provide a statistical motivation for previous methods and enable the learning of all parameters from training data. all proposed models are quantitatively compared on the middlebury flow dataset.
belief propagation with directional statistics for solving the shape-from-shading problem. the shape-from-shading [sfs] problem infers shape from reflected light, collected using a camera at a single point in space only. reflected light alone does not provide sufficient constraint and extra information is required; typically a smoothness assumption is made. a surface with lambertian reflectance lit by a single infinitely distant light source is also typical.we solve this typical sfs problem using belief propagation to marginalise a probabilistic model. the key novel step is in using a directional probability distribution, the fisher-bingham distribution. this produces a fast and relatively simple algorithm that does an effective job of both extracting details and being robust to noise. quantitative comparisons with past algorithms are provided using both synthetic and real data.
output regularized metric learning with side information. distance metric learning has been widely investigated in machine learning and information retrieval. in this paper, we study a particular content-based image retrieval application of learning distance metrics from historical relevance feedback log data, which leads to a novel scenario called collaborative image retrieval. the log data provide the side information expressed as relevance judgements between image pairs. exploiting the side information as well as inherent neighborhood structures among examples, we design a convex regularizer upon which a novel distance metric learning approach, named output regularized metric learning, is presented to tackle collaborative image retrieval. different from previous distance metric methods, the proposed technique integrates synergistic information from both log data and unlabeled data through a regularization framework and pilots the desired metric toward the ideal output that satisfies pairwise constraints revealed by side information. the experiments on image retrieval tasks have been performed to validate the feasibility of the proposed distance metric technique.
a new baseline for image annotation. automatically assigning keywords to images is of great interest as it allows one to index, retrieve, and understand large collections of image data. many techniques have been proposed for image annotation in the last decade that give reasonable performance on standard datasets. however, most of these works fail to compare their methods with simple baseline techniques to justify the need for complex models and subsequent training. in this work, we introduce a new baseline technique for image annotation that treats annotation as a retrieval problem. the proposed technique utilizes low-level image features and a simple combination of basic distances to find nearest neighbors of a given image. the keywords are then assigned using a greedy label transfer mechanism. the proposed baseline outperforms the current state-of-the-art methods on two standard and one large web dataset. we believe that such a baseline measure will provide a strong platform to compare and better understand future annotation techniques.
efficient ncc-based image matching in walsh-hadamard domain. in this paper, we proposed a fast image matching algorithm based on the normalized cross correlation (ncc) by applying the winner-update strategy on the walsh-hadamard transform. walsh-hadamard transform is an orthogonal transformation that is easy to compute and has nice energy packing capability. based on the cauchy-schwarz inequality, we derive a novel upper bound for the cross-correlation of image matching in the walsh-hadamard domain. applying this upper bound with the winner update search strategy can skip unnecessary calculation, thus significantly reducing the computational burden of ncc-based pattern matching. experimental results show the proposed algorithm is very efficient for ncc-based image matching under different lighting conditions and noise levels.
sift flow: dense correspondence across different scenes. while image registration has been studied in different areas of computer vision, aligning images depicting different scenes remains a challenging problem, closer to recognition than to image matching. analogous to optical flow, where an image is aligned to its temporally adjacent frame, we propose sift flow, a method to align an image to its neighbors in a large image collection consisting of a variety of scenes. for a query image, histogram intersection on a bag-of-visual-words representation is used to find the set of nearest neighbors in the database. the sift flow algorithm then consists of matching densely sampled sift features between the two images, while preserving spatial discontinuities. the use of sift features allows robust matching across different scene/object appearances and the discontinuity-preserving spatial model allows matching of objects located at different parts of the scene. experiments show that the proposed approach is able to robustly align complicated scenes with large spatial distortions. we collect a large database of videos and apply the sift flow algorithm to two applications: (i) motion field prediction from a single static image and (ii) motion synthesis via transfer of moving objects.
serboost: semi-supervised boosting with expectation regularization. the application of semi-supervised learning algorithms to large scale vision problems suffers from the bad scaling behavior of most methods. based on the expectation regularization principle, we propose a novel semi-supervised boosting method, called serboost that can be applied to large scale vision problems. the complexity is mainly dominated by the base learners. the algorithm provides a margin regularizer for the boosting cost function and shows a principled way of utilizing prior knowledge. we demonstrate the performance of serboost on the pascal voc2006 set and compare it to other supervised and semi-supervised methods, where serboost shows improvements both in terms of classification accuracy and computational speed.
a convex formulation of continuous multi-label problems. we propose a spatially continuous formulation of ishikawa's discrete multi-label problem. we show that the resulting non-convex variational problem can be reformulated as a convex variational problem via embedding in a higher dimensional space. this variational problem can be interpreted as a minimal surface problem in an anisotropic riemannian space. in several stereo experiments we show that the proposed continuous formulation is superior to its discrete counterpart in terms of computing time, memory efficiency and metrication errors.
prior-based piecewise-smooth segmentation by template competitive deformation using partitions of unity. we propose a new algorithm for two-phase, piecewise-smooth segmentation with shape prior. the image is segmented by a binary template that is deformed by a regular geometric transformation. the choice of the template together with the constraint on the transformation introduce the shape prior. the deformation is guided by the maximization of the likelihood of foreground and background intensity models, so that we can refer to this approach as competitive deformation. in each region, the intensity is modelled as a smooth approximation of the original image. we represent the transformation using a partition of unity finite element method, which consists in representing each component with polynomial approximations within local patches. a conformity constraint between the patches provides a way to control the globality of the deformation. we show several results on synthetic images, as well as on medical data from different modalities.
a generic neighbourhood filtering framework for matrix fields. the nonlocal data and smoothness (nds) filtering framework for greyvalue images has been recently proposed by mrázek et al. this model for image denoising unifies m-smoothing and bilateral filtering, and several well-known nonlinear filters from the literature become particular cases. in this article we extend this model to so-called matrix fields. these data appear, for example, in diffusion tensor magnetic resonance imaging (dt-mri). our matrix-valued nds framework includes earlier filters developped for dt-mri data, for instance, the affine-invariant and the log-euclidean regularisation of matrix fields. experiments performed with synthetic matrix fields and real dt-mri data showed excellent performance with respect to restoration quality as well as speed of convergence.
vision-based multiple interacting targets tracking via on-line supervised learning. successful multi-target tracking requires locating the targets and labeling their identities. this mission becomes significantly more challenging when many targets frequently interact with each other (present partial or complete occlusions). this paper presents an on-line supervised learning based method for tracking multiple interacting targets. when the targets do not interact with each other, multiple independent trackers are employed for training a classifier for each target. when the targets are in close proximity or present occlusions, the learned classifiers are used to assist in tracking. the tracking and learning supplement each other in the proposed method, which not only deals with tough problems encountered in multi-target tracking, but also ensures the entire process to be completely on-line. various evaluations have demonstrated that this method performs better than previous methods when the interactions occur, and can maintain the correct tracking under various complex tracking situations, including crossovers, collisions and occlusions.
3d non-rigid surface matching and registration based on holomorphic differentials. 3d surface matching is fundamental for shape registration, deformable 3d non-rigid tracking, recognition and classification. in this paper we describe a novel approach for generating an efficient and optimal combined matching from multiple boundary-constrained conformal parameterizations for multiply connected domains (i.e., genus zero open surface with multiple boundaries), which always come from imperfect 3d data acquisition (holes, partial occlusions, change of pose and non-rigid deformation between scans). this optimality criterion is also used to assess how consistent each boundary is, and thus decide to enforce or relax boundary constraints across the two surfaces to be matched. the linear boundary-constrained conformal parameterization is based on the holomorphic differential forms, which map a surface with n boundaries conformally to a planar rectangle with (n - 2) horizontal slits, other two boundaries as constraints. the mapping is a diffeomorphism and intrinsic to the geometry, handles an open surface with arbitrary number of boundaries, and can be implemented as a linear system. experimental results are given for real facial surface matching, deformable cloth non-rigid tracking, which demonstrate the efficiency of our method, especially for 3d non-rigid surfaces with significantly inconsistent boundaries.
efficient camera smoothing in sequential structure-from-motion using approximate cross-validation. in the sequential approach to three-dimensional reconstruction, adding prior knowledge about camera pose improves reconstruction accuracy. we add a smoothing penalty on the camera trajectory. the smoothing parameter, usually fixed by trial and error, is automatically estimated using cross-validation. this technique is extremely expensive in its basic form. we derive gauss-newton cross-validation, which closely approximates cross-validation, while being much cheaper to compute. the method is substantiated by experimental results on synthetic and real data. they show that it improves accuracy and stability in the reconstruction process, preventing several failure cases.
the bi-directional framework for unifying parametric image alignment approaches. in this paper, a generic bi-directional framework is proposed for parametric image alignment, that extends the classification of [1]. four main categories (forward, inverse, dependent and bi-directional) form the basis of a consistent set of subclasses, onto which state-of-the-art methods have been mapped. new formulations for the esm [2] and the inverse additive [3] algorithms are proposed, that show the ability of this framework to unify existing approaches. new explicit equivalence relationships are given for the case of first-order optimization that provide some insights into the choice of an update rule in iterative algorithms.
multi-layered decomposition of recurrent scenes. there is considerable interest in techniques capable of identifying anomalies and unusual events in busy outdoor scenes, e.g. road junctions. many approaches achieve this by exploiting deviations in spatial appearance from some expected norm accumulated by a model over time. in this work we show that much can be gained from explicitly modelling temporal aspects in detail. specifically, many traffic junctions are regulated by lights controlled by a timing device of considerable precision, and it is in these situations that we advocate a model which learns periodic spatio-temporal patterns with a view to highlighting anomalous events such as broken-down vehicles, traffic accidents, or pedestrians jay-walking. more specifically, by estimating autocovariance of self-similarity, used previously in the context gait recognition, we characterize a scene by identifying a global fundamental period. as our model, we introduce a spatio-temporal grid of histograms built in accordance with some chosen feature. this model is then used to classify objects found in subsequent test data. in particular we demonstrate the effect of such characterization experimentally by monitoring the bounding box aspect ratio and optical flow field of objects detected on a road traffic junction, enabling our model to discriminate between people and cars sufficiently well to provide useful warnings of adverse behaviour in real time.
discriminative sparse image models for class-specific edge detection and image interpretation. sparse signal models learned from data are widely used in audio, image, and video restoration. they have recently been generalized to discriminative image understanding tasks such as texture segmentation and feature selection. this paper extends this line of research by proposing a multiscale method to minimize least-squares reconstruction errors and discriminative cost functions under ¿0 or ¿1 regularization constraints. it is applied to edge detection, category-based edge selection and image classification tasks. experiments on the berkeley edge detection benchmark and the pascal voc'05 and voc'07 datasets demonstrate the computational efficiency of our algorithm and its ability to learn local image descriptions that effectively support demanding computer vision tasks.
estimating 3d trajectories of periodic motions from stationary monocular views. we present a method for estimating the 3d trajectory of an object undergoing periodic motion in world coordinates by observing its apparent trajectory in a video taken from a single stationary camera. periodicity in 3d is used here as a physical constraint, from which accurate solutions can be obtained. a detailed analysis is performed, from which we gain significant insight regarding the nature of the problem and the information that is required to arrive at a unique solution. subsequently, a robust, numerical approach is proposed, and it is demonstrated that the cost function exhibits strong local convexity which is amenable to local optimization methods. experimental results indicate the effectiveness of the proposed method for reconstructing periodic trajectories in 3d.
multiple tree models for occlusion and spatial constraints in human pose estimation. tree-structured models have been widely used for human pose estimation, in either 2d or 3d. while such models allow efficient learning and inference, they fail to capture additional dependencies between body parts, other than kinematic constraints between connected parts. in this paper, we consider the use of multiple tree models, rather than a single tree model for human pose estimation. our model can alleviate the limitations of a single tree-structured model by combining information provided across different tree models. the parameters of each individual tree model are trained via standard learning algorithms in a single tree-structured model. different tree models can be combined in a discriminative fashion by a boosting procedure. we present experimental results showing the improvement of our approaches on two different datasets. on the first dataset, we use our multiple tree framework for occlusion reasoning. on the second dataset, we combine multiple deformable trees for capturing spatial constraints between non-connected body parts.
csdd features: center-surround distribution distance for feature extraction and matching. we present an interest region operator and feature descriptor called center-surround distribution distance (csdd) that is based on comparing feature distributions between a central foreground region and a surrounding ring of background pixels. in addition to finding the usual light(dark) blobs surrounded by a dark(light) background, csdd also detects blobs with arbitrary color distribution that "stand out" perceptually because they look different from the background. a proof-of-concept implementation using an isotropic scale-space extracts feature descriptors that are invariant to image rotation and covariant with change of scale. detection repeatability is evaluated and compared with other state-of-the-art approaches using a standard dataset, while use of csdd features for image registration is demonstrated within a ransac procedure for affine image matching.
beyond loose lp-relaxations: optimizing mrfs by repairing cycles. this paper presents a new mrf optimization algorithm, which is derived from linear programming and manages to go beyond current state-of-the-art techniques (such as those based on graph-cuts or belief propagation). it does so by relying on a much tighter class of lp-relaxations, called cycle-relaxations. with the help of this class of relaxations, our algorithm tries to deal with a difficulty lying at the heart of mrf optimization: the existence of inconsistent cycles. to this end, it uses an operation called cycle-repairing. the goal of that operation is to fix any inconsistent cycles that may appear during optimization, instead of simply ignoring them as usually done up to now. the more the repaired cycles, the tighter the underlying lp relaxation becomes. as a result of this procedure, our algorithm is capable of providing almost optimal solutions even for very general mrfs with arbitrary potentials. experimental results verify its effectiveness on difficult mrf problems, as well as its better performance compared to the state of the art.
a statistical confidence measure for optical flows. confidence measures are crucial to the interpretation of any optical flow measurement. even though numerous methods for estimating optical flow have been proposed over the last three decades, a sound, universal, and statistically motivated confidence measure for optical flow measurements is still missing. we aim at filling this gap with this contribution, where such a confidence measure is derived, using statistical test theory and measurable statistics of flow fields from the regarded domain. the new confidence measure is computed from merely the results of the optical flow estimator and hence can be applied to any optical flow estimation method, covering the range from local parametric to global variational approaches. experimental results using state-of-the-art optical flow estimators and various test sequences demonstrate the superiority of the proposed technique compared to existing 'confidence' measures.
star shape prior for graph-cut image segmentation. in recent years, segmentation with graph cuts is increasingly used for a variety of applications, such as photo/video editing, medical image processing, etc. one of the most common applications of graph cut segmentation is extracting an object of interest from its background. if there is any knowledge about the object shape (i.e. a shape prior), incorporating this knowledge helps to achieve a more robust segmentation. in this paper, we show how to implement a star shape prior into graph cut segmentation. this is a generic shape prior, i.e. it is not specific to any particular object, but rather applies to a wide class of objects, in particular to convex objects. our major assumption is that the center of the star shape is known, for example, it can be provided by the user. the star shape prior has an additional important benefit - it allows an inclusion of a term in the objective function which encourages a longer object boundary. this helps to alleviate the bias of a graph cut towards shorter segmentation boundaries. in fact, we show that in many cases, with this new term we can achieve an accurate object segmentation with only a single pixel, the center of the object, provided by the user, which is rarely possible with standard graph cut interactive segmentation.
optimizing binary mrfs with higher order cliques. widespread use of efficient and successful solutions of computer vision problems based on pairwise markov random field (mrf) models raises a question: does any link exist between the pairwise and higher order mrfs such that the like solutions can be applied to the latter models? this work explores such a link for binary mrfs that allow us to represent gibbs energy of signal interaction with a polynomial function. we show how a higher order polynomial can be efficiently transformed into a quadratic function. then energy minimization tools for the pairwise mrf models can be easily applied to the higher order counterparts. also, we propose a method to analytically estimate the potential parameter of the asymmetric potts prior. the proposed framework demonstrates very promising experimental results of image segmentation and can be used to solve other computer vision problems.
automatic image colorization via multimodal predictions. we aim to color greyscale images automatically, without any manual intervention. the color proposition could then be interactively corrected by user-provided color landmarks if necessary. automatic colorization is nontrivial since there is usually no one-to-one correspondence between color and local texture. the contribution of our framework is that we deal directly with multimodality and estimate, for each pixel of the image to be colored, the probability distribution of all possible colors, instead of choosing the most probable color at the local level. we also predict the expected variation of color at each pixel, thus defining a non-uniform spatial coherency criterion. we then use graph cuts to maximize the probability of the whole colored image at the global level. we work in the l-a-b color space in order to approximate the human perception of distances between colors, and we use machine learning tools to extract as much information as possible from a dataset of colored examples. the resulting algorithm is fast, designed to be more robust to texture noise, and is above all able to deal with ambiguity, in contrary to previous approaches.
unsupervised learning of skeletons from motion. humans demonstrate a remarkable ability to parse complicated motion sequences into their constituent structures and motions. we investigate this problem, attempting to learn the structure of one or more articulated objects, given a time-series of two-dimensional feature positions. we model the observed sequence in terms of "stick figure" objects, under the assumption that the relative joint angles between sticks can change over time, but their lengths and connectivities are fixed. we formulate the problem in a single probabilistic model that includes multiple sub-components: associating the features with particular sticks, determining the proper number of sticks, and finding which sticks are physically joined. we test the algorithm on challenging datasets of 2d projections of optical human motion capture and feature trajectories from real videos.
an extended phase field higher-order active contour model for networks and its application to road network extraction from vhr satellite images. this paper addresses the segmentation from an image of entities that have the form of a `network', i.e. the region in the image corresponding to the entity is composed of branches joining together at junctions, e.g. road or vascular networks. we present a new phase field higher-order active contour (hoac) prior model for network regions, and apply it to the segmentation of road networks from very high resolution satellite images. this is a hard problem for two reasons. first, the images are complex, with much `noise' in the road region due to cars, road markings, etc., while the background is very varied, containing many features that are locally similar to roads. second, network regions are complex to model, because they may have arbitrary topology. in particular, we address a severe limitation of a previous model in which network branch width was constrained to be similar to maximum network branch radius of curvature, thereby providing a poor model of networks with straight narrow branches or highly curved, wide branches. to solve this problem, we propose a new hoac prior energy term, and reformulate it as a nonlocal phase field energy. we analyse the stability of the new model, and find that in addition to solving the above problem by separating the interactions between points on the same and opposite sides of a network branch, the new model permits the modelling of two widths simultaneously. the analysis also fixes some of the model parameters in terms of network width(s). after adding a likelihood energy, we use the model to extract the road network quasi-automatically from pieces of a quickbird image, and compare the results to other models in the literature. the results demonstrate the superiority of the new model, the importance of strong prior knowledge in general, and of the new term in particular.
training hierarchical feed-forward visual recognition models using transfer learning from pseudo-tasks. building visual recognition models that adapt across different domains is a challenging task for computer vision. while feature-learning machines in the form of hierarchial feed-forward models (e.g., convolutional neural networks) showed promise in this direction, they are still difficult to train especially when few training examples are available. in this paper, we present a framework for training hierarchical feed-forward models for visual recognition, using transfer learning from pseudo tasks. these pseudo tasks are automatically constructed from data without supervision and comprise a set of simple pattern-matching operations. we show that these pseudo tasks induce an informative inverse-wishart prior on the functional behavior of the network, offering an effective way to incorporate useful prior knowledge into the network training. in addition to being extremely simple to implement, and adaptable across different domains with little or no extra tuning, our approach achieves promising results on challenging visual recognition tasks, including object recognition, gender recognition, and ethnicity recognition.
an effective approach to 3d deformable surface tracking. the key challenge with 3d deformable surface tracking arises from the difficulty in estimating a large number of 3d shape parameters from noisy observations. a recent state-of-the-art approach attacks this problem by formulating it as a second order cone programming (socp) feasibility problem. the main drawback of this solution is the high computational cost. in this paper, we first reformulate the problem into an unconstrained quadratic optimization problem. instead of handling a large set of complicated socp constraints, our new formulation can be solved very efficiently by resolving a set of sparse linear equations. based on the new framework, a robust iterative method is employed to handle large outliers. we have conducted an extensive set of experiments to evaluate the performance on both synthetic and real-world testbeds, from which the promising results show that the proposed algorithm not only achieves better tracking accuracy, but also executes significantly faster than the previous solution.
detecting carried objects in short video sequences. we propose a new method for detecting objects such as bags carried by pedestrians depicted in short video sequences. in common with earlier work [1,2] on the same problem, the method starts by averaging aligned foreground regions of a walking pedestrian to produce a representation of motion and shape (known as a temporal template) that has some immunity to noise in foreground segmentations and phase of the walking cycle. our key novelty is for carried objects to be revealed by comparing the temporal templates against view-specific exemplars generated offline for unencumbered pedestrians. a likelihood map obtained from this match is combined in a markov random field with a map of prior probabilities for carried objects and a spatial continuity assumption, from which we obtain a segmentation of carried objects using the map solution. we have re-implemented the earlier state of the art method [1] and demonstrate a substantial improvement in performance for the new method on the challenging pets2006 dataset [3]. although developed for a specific problem, the method could be applied to the detection of irregularities in appearance for other categories of object that move in a periodic fashion.
semi-automatic motion segmentation with motion layer mosaics. a new method for motion segmentation based on reference motion layer mosaics is presented. we assume that the scene is composed of a set of layers whose motion is well described by parametric models. this usual assumption is compatible with the notion of motion layer mosaic, which allows a compact representation of the sequence with a small number of mosaics only. we segment the sequence using a reduced number of distant image-to-mosaic comparisons instead of a larger number of close image-to-image comparisons. apart from computational advantage, another interest lies in the fact that motions estimated between distant images are more likely to be different from one region to another than when estimated between consecutive images. this helps the segmentation process. the segmentation is obtained by graph cut minimization of a cost function which includes an original image-to-mosaic data term. at the end of the segmentation process, it may happen that the obtained boundaries are not precisely the expected ones. often the user has no other possibility than modifying manually every segmentation one after another or than starting over all again the process with different parameters. we propose an original easy way for the user to manually correct the possible errors on the mosaics themselves. these corrections are then propagated to all the images of the corresponding video interval thanks to a second segmentation pass. experimental results demonstrate the potential of our approach.
object recognition by integrating multiple image segmentations. the joint tasks of object recognition and object segmentation from a single image are complex in their requirement of not only correct classification, but also deciding exactly which pixels belong to the object. exploring all possible pixel subsets is prohibitively expensive, leading to recent approaches which use unsupervised image segmentation to reduce the size of the configuration space. image segmentation, however, is known to be unstable, strongly affected by small image perturbations, feature choices, or different segmentation algorithms. this instability has led to advocacy for using multiple segmentations of an image. in this paper, we explore the question of how to best integrate the information from multiple bottom-up segmentations of an image to improve object recognition robustness. by integrating the image partition hypotheses in an intuitive combined top-down and bottom-up recognition approach, we improve object and feature support. we further explore possible extensions of our method and whether they provide improved performance. results are presented on the msrc 21-class data set and the pascal voc2007 object segmentation challenge.
generative image segmentation using random walks with restart. we consider the problem of multi-label, supervised image segmentation when an initial labeling of some pixels is given. in this paper, we propose a new generative image segmentation algorithm for reliable multi-label segmentations in natural images. in contrast to most existing algorithms which focus on the inter-label discrimination, we address the problem of finding the generative model for each label. the primary advantage of our algorithm is that it produces very good segmentation results under two difficult problems: the weak boundary problem and the texture problem. moreover, single-label image segmentation is possible. these are achieved by designing the generative model with the random walks with restart (rwr). experimental results with synthetic and natural images demonstrate the relevance and accuracy of our algorithm.
signature-based document image retrieval. as the most pervasive method of individual identification and document authentication, signatures present convincing evidence and provide an important form of indexing for effective document image processing and retrieval in a broad range of applications. in this work, we developed a fully automatic signature-based document image retrieval system that handles: 1) automatic detection and segmentation of signatures from document images and 2) translation, scale, and rotation invariant signature matching for document image retrieval. we treat signature retrieval in the unconstrained setting of non-rigid shape matching and retrieval, and quantitatively study shape representations, shape matching algorithms, measures of dissimilarity, and the use of multiple query instances in document image retrieval. extensive experiments using large real world collections of english and arabic machine printed and handwritten documents demonstrate the excellent performance of our system. to the best of our knowledge, this is the first automatic retrieval system for general document images by using signatures as queries, without manual annotation of the image collection.
multi-thread parsing for recognizing complex events in videos. this paper presents a probabilistic grammar approach to the recognition of complex events in videos. firstly, based on the original motion features, a rule induction algorithm is adopted to learn the event rules. then, a multi-thread parsing (mtp) algorithm is adopted to recognize the complex events involving parallel temporal relation in sub-events, whereas the commonly used parser can only handle the sequential relation. additionally, a viterbi-like error recovery strategy is embedded in the parsing process to correct the large time scale errors, such as insertion and deletion errors. extensive experiments including indoor gymnastic exercises and outdoor traffic events are performed. as supported by experimental results, the mtp algorithm can effectively recognize the complex events due to the strong discriminative representation and the error recovery strategy.
projected texture for object classification. algorithms for classification of 3d objects either recover the depth information lost during imaging using multiple images, structured lighting, image cues, etc. or work directly the images for classification. while the latter class of algorithms are more efficient and robust in comparison, they are less accurate due to the lack of depth information. we propose the use of structured lighting patterns projected on the object, which gets deformed according to the shape of the object. since our goal is object classification and not shape recovery, we characterize the deformations using simple texture measures, thus avoiding the error prone and computationally expensive step of depth recovery. moreover, since the deformations encode depth variations of the object, the 3d shape information is implicitly used for classification. we show that the information thus derived can significantly improve the accuracy of object classification algorithms, and derive the theoretical limits on height variations that can be captured by a particular projector-camera setup. a 3d texture classification algorithm derived from the proposed approach achieves a ten-fold reduction in error rate on a dataset of 30 classes, when compared to state-of-the-art image based approaches. we also demonstrate the effectiveness of the approach for a hand geometry based authentication system, which achieves a four-fold reduction in the equal error rate on a dataset containing 149 users.
structuring visual words in 3d for arbitrary-view object localization. we propose a novel and efficient method for generic arbitrary-view object class detection and localization. in contrast to existing single-view and multi-view methods using complicated mechanisms for relating the structural information in different parts of the objects or different viewpoints, we aim at representing the structural information in their true 3d locations. uncalibrated multi-view images from a hand-held camera are used to reconstruct the 3d visual word models in the training stage. in the testing stage, beyond bounding boxes, our method can automatically determine the locations and outlines of multiple objects in the test image with occlusion handling, and can accurately estimate both the intrinsic and extrinsic camera parameters in an optimized way. with exemplar models, our method can also handle shape deformation for intra-class variance. to handle large data sets from models, we propose several speedup techniques to make the prediction efficient. experimental results obtained based on some standard data sets demonstrate the effectiveness of the proposed approach.
background subtraction on distributions. environmental monitoring applications present a challenge to current background subtraction algorithms that analyze the temporal variability of pixel intensities, due to the complex texture and motion of the scene. they also present a challenge to segmentation algorithms that compare intensity or color distributions between the foreground and the background in each image independently, because objects of interest such as animals have adapted to blend in. therefore, we have developed a background modeling and subtraction scheme that analyzes the temporal variation of intensity or color distributions, instead of either looking at temporal variation of point statistics, or the spatial variation of region statistics in isolation. distributional signatures are less sensitive to movements of the textured background, and at the same time they are more robust than individual pixel statistics in detecting foreground objects. they also enable slow background update, which is crucial in monitoring applications where processing power comes at a premium, and where foreground objects, when present, may move less than the background and therefore disappear into it when a fast update scheme is used. our approach compares favorably with the state of the art both in generic low-level detection metrics, as well as in application-dependent criteria.
an incremental learning method for unconstrained gaze estimation. this paper presents an online learning algorithm for appea- rance-based gaze estimation that allows free head movement in a casual desktop environment. our method avoids the lengthy calibration stage using an incremental learning approach. our system keeps running as a background process on the desktop pc and continuously updates the estimation parameters by taking user's operations on the pc monitor as input. to handle free head movement of a user, we propose a pose-based clustering approach that efficiently extends an appearance manifold model to handle the large variations of the head pose. the effectiveness of the proposed method is validated by quantitative performance evaluation with three users.
a linear time histogram metric for improved sift matching. we present a new metric between histograms such as sift descriptors and a linear time algorithm for its computation. it is common practice to use the l 2 metric for comparing sift descriptors. this practice assumes that sift bins are aligned, an assumption which is often not correct due to quantization, distortion, occlusion etc.in this paper we present a new earth mover's distance (emd) variant. we show that it is a metric (unlike the original emd [1] which is a metric only for normalized histograms). moreover, it is a natural extension of the l 1 metric. second, we propose a linear time algorithm for the computation of the emd variant, with a robust ground distance for oriented gradients. finally, extensive experimental results on the mikolajczyk and schmid dataset [2] show that our method outperforms state of the art distances.
multi-camera tracking and atypical motion detection with behavioral maps. we introduce a novel behavioral model to describe pedestrians motions, which is able to capture sophisticated motion patterns resulting from the mixture of different categories of random trajectories. due to its simplicity, this model can be learned from video sequences in a totally unsupervised manner through an expectation-maximization procedure.when integrated into a complete multi-camera tracking system, it improves the tracking performance in ambiguous situations, compared to a standard ad-hoc isotropic markovian motion model. moreover, it can be used to compute a score which characterizes atypical individual motions.experiments on outdoor video sequences demonstrate both the improvement of tracking performance when compared to a state-of-the-art tracking system and the reliability of the atypical motion detection.
non-local regularization of inverse problems. this article proposes a new framework to regularize linear inverse problems using the total variation on non-local graphs. this non-local graph allows to adapt the penalization to the geometry of the underlying function to recover. a fast algorithm computes iteratively both the solution of the regularization process and the non-local graph adapted to this solution. we show numerical applications of this method to the resolution of image processing inverse problems such as inpainting, super-resolution and compressive sampling.
learning two-view stereo matching. we propose a graph-based semi-supervised symmetric matching framework that performs dense matching between two uncalibrated wide-baseline images by exploiting the results of sparse matching as labeled data. our method utilizes multiple sources of information including the underlying manifold structure, matching preference, shapes of the surfaces in the scene, and global epipolar geometric constraints for occlusion handling. it can give inherent sub-pixel accuracy and can be implemented in a parallel fashion on a graphics processing unit (gpu). since the graphs are directly learned from the input images without relying on extra training data, its performance is very stable and hence the method is applicable under general settings. our algorithm is robust against outliers in the initial sparse matching due to our consideration of all matching costs simultaneously, and the provision of iterative restarts to reject outliers from the previous estimate. some challenging experiments have been conducted to evaluate the robustness of our method.
unified frequency domain analysis of lightfield cameras. this paper presents a theory that encompasses both "plenoptic" (microlens based) and "heterodyning" (mask based) cameras in a single frequency-domain mathematical formalism. light-field capture has traditionally been analyzed using spatio-angular representation, with the exception of the frequency-domain "heterodyning" work. in this paper we interpret "heterodyning" as a general theory of multiplexing the radiance in the frequency domain. using this interpretation, we derive a mathematical theory of recovering the 4d spatial and angular information from the multiplexed 2d frequency representation. the resulting method is applicable to all lightfield cameras, lens-based and mask-based. the generality of our approach suggests new designs for lightfield cameras. we present one such novel lightfield camera, based on a mask outside a conventional camera. experimental results are presented for all cameras described.
real-time shape analysis of a human body in clothing using time-series part-labeled volumes. we propose a real-time method for simultaneously refining the reconstructed volume of a human body with loose-fitting clothing and identifying body-parts in it. time-series volumes, which are acquired by a slow but sophisticated 3d reconstruction algorithm, with body-part labels are obtained offline. the time-series sample volumes are represented by trajectories in the eigenspaces using pca. an input visual hull reconstructed online is projected into the eigenspace and compared with the trajectories in order to find similar high-precision samples with body-part labels. the hierarchical search taking into account 3d reconstruction errors can achieve robust and fast matching. experimental results demonstrate that our method can refine the input visual hull including loose-fitting clothing and identify its body-parts in real time.
calibration from statistical properties of the visual world. what does a blind entity need in order to determine the geometry of the set of photocells that it carries through a changing lightfield? in this paper, we show that very crude knowledge of some statistical properties of the environment is sufficient for this task.we show that some dissimilarity measures between pairs of signals produced by photocells are strongly related to the angular separation between the photocells. based on real-world data, we model this relation quantitatively, using dissimilarity measures based on the correlation and conditional entropy. we show that this model allows to estimate the angular separation from the dissimilarity. although the resulting estimators are not very accurate, they maintain their performance throughout different visual environments, suggesting that the model encodes a very general property of our visual world.finally, leveraging this method to estimate angles from signal pairs, we show how distance geometry techniques allow to recover the complete sensor geometry.
using 3d line segments for robust and efficient change detection from multiple noisy images. in this paper, we propose a new approach to change detection that is based on the appearance or disappearance of 3d lines, which may be short, as seen in a new image. these 3d lines are estimated automatically and quickly from a set of previously-taken learning-images from arbitrary view points and under arbitrary lighting conditions. 3d change detection traditionally involves unsupervised estimation of scene geometry and the associated brdf at each observable voxel in the scene, and the comparison of a new image with its prediction. if a significant number of pixels differ in the two aligned images, a change in the 3d scene is assumed to have occurred. the importance of our approach is that by comparing images of lines rather than of gray levels, we avoid the computationally intensive, and some-times impossible, tasks of estimating 3d surfaces and their associated brdfs in the model-building stage. we estimate 3d lines instead where the lines are due to 3d ridges or brdf ridges which are computationally much less costly and are more reliably detected. our method is widely applicable as man-made structures consisting of 3d line segments are the main focus of most applications. the contributions of this paper are: change detection based on appropriate interpretation of line appearance and disappearance in a new image; unsupervised estimation of "short" 3d lines from multiple images such that the required computation is manageable and the estimation accuracy is high.
facetracer: a search engine for large collections of images with faces. we have created the first image search engine based entirely on faces. using simple text queries such as "smiling men with blond hair and mustaches," users can search through over 3.1 million faces which have been automatically labeled on the basis of several facial attributes. faces in our database have been extracted and aligned from images downloaded from the internet using a commercial face detector, and the number of images and attributes continues to grow daily. our classification approach uses a novel combination of support vector machines and adaboost which exploits the strong structure of faces to select and train on the optimal set of features for each attribute. we show state-of-the-art classification results compared to previous works, and demonstrate the power of our architecture through a functional, large-scale face search engine. our framework is fully automatic, easy to scale, and computes all labels off-line, leading to fast on-line search performance. in addition, we describe how our system can be used for a number of applications, including law enforcement, social networks, and personal photo management. our search engine will soon be made publicly available.
fusion of feature- and area-based information for urban buildings modeling from aerial imagery. accurate and realistic building models of urban environments are increasingly important for applications, like virtual tourism or city planning. initiatives like virtual earth or google earth are aiming at offering virtual models of all major cities world wide. the prohibitively high costs of manual generation of such models explain the need for an automatic workflow.this paper proposes an algorithm for fully automatic building reconstruction from aerial images. sparse line features delineating height discontinuities and dense depth data providing the roof surface are combined in an innovative manner with a global optimization algorithm based on graph cuts. the fusion process exploits the advantages of both information sources and thus yields superior reconstruction results compared to the indiviual sources. the nature of the algorithm also allows to elegantly generate image driven levels of detail of the geometry.the algorithm is applied to a number of real world data sets encompassing thousands of buildings. the results are analyzed in detail and extensively evaluated using ground truth data.
compressive structured light for recovering inhomogeneous participating media. we propose a new method named compressive structured light for recovering inhomogeneous participating media. whereas conventional structured light methods emit coded light patterns onto the surface of an opaque object to establish correspondence for triangulation, compressive structured light projects patterns into a volume of participating medium to produce images which are integral measurements of the volume density along the line of sight. for a typical participating medium encountered in the real world, the integral nature of the acquired images enables the use of compressive sensing techniques that can recover the entire volume density from only a few measurements. this makes the acquisition process more efficient and enables reconstruction of dynamic volumetric phenomena. moreover, our method requires the projection of multiplexed coded illumination, which has the added advantage of increasing the signal-to-noise ratio of the acquisition. finally, we propose an iterative algorithm to correct for the attenuation of the participating medium during the reconstruction process. we show the effectiveness of our method with simulations as well as experiments on the volumetric recovery of multiple translucent layers, 3d point clouds etched in glass, and the dynamic process of milk drops dissolving in water.
texture-consistent shadow removal. this paper presents an approach to shadow removal that preserves texture consistency between the original shadow and lit area. illumination reduction in the shadow area not only darkens that area, but also changes the texture characteristics there. we achieve texture-consistent shadow removal by constructing a shadow-free and texture-consistent gradient field. first, we estimate an illumination change surface which causes the shadow and remove the gradients it induces. we approximate the illumination change surface with illumination change splines across the shadow boundary. we formulate estimating these splines as an optimization problem which balances the smoothness between the neighboring splines and their fitness to the image data. second, we sample the shadow effect on the texture characteristics in the umbra and lit area near the shadow boundary, and remove it by transforming the gradients inside the shadow area to be compatible with the lit area. experiments on photos from flickr demonstrate the effectiveness of our method.
sample sufficiency and pca dimension for statistical shape models. statistical shape modelling(ssm) is a popular technique in computer vision applications, where the variation of shape of a given structure is modelled by principal component analysis (pca) on a set of training samples. the issue of sample size sufficiency is not generally considered. in this paper, we propose a framework to investigate the sources of ssm inaccuracy. based on this framework, we propose a procedure to determine sample size sufficiency by testing whether the training data stabilises the ssm. also, the number of principal modes to retain (pca dimension) is usually chosen using rules that aim to cover a percentage of the total variance or to limit the residual to a threshold. however, an ideal rule should retain modes that correspond to real structural variation and discard those that are dominated by noise. we show that these commonly used rules are not reliable, and we propose a new rule that uses bootstrap stability analysis on mode directions to determine the pca dimension.for validation we use synthetic 3d face datasets generated using a known number of structural modes with added noise. a 4-way anova is applied for the model reconstruction accuracy on sample size, shape vector dimension, pca dimension, and the noise level. it shows that there is no universal sample size guideline for ssm, nor is there a simple relationship to the shape vector dimension (with p-value=0.2932). validation of our rule for retaining structural modes showed it detected the correct number of modes to retain where the conventional methods failed. the methods were also tested on real 2d (22 points) and 3d (500 points) face data, retaining 24 and 70 modes with sample sufficiency being reached at approximately 50 and 150 samples respectively. we provide a foundation for appropriate selection of pca dimension and determination of sample size sufficiency in statistical shape modelling.
key object driven multi-category object recognition, localization and tracking using spatio-temporal context. in this paper we address the problem of recognizing, localizing and tracking multiple objects of different categories in meeting room videos. difficulties such as lack of detail and multi-object co-occurrence make it hard to directly apply traditional object recognition methods. under such circumstances, we show that incorporating object-level spatio-temporal relationships can lead to significant improvements in inference of object category and state. contextual relationships are modeled by a dynamic markov random field, in which recognition, localization and tracking are done simultaneously. further, we define human as the key object of the scene, which can be detected relatively robustly and therefore is used to guide the inference of other objects. experiments are done on the chil meeting video corpus. performance is evaluated in terms of object detection and false alarm rates, object recognition confusion matrix and pixel-level accuracy of object segmentation.
toward global minimum through combined local minima. there are many local and greedy algorithms for energy minimization over markov random field (mrf) such as iterated condition mode (icm) and various gradient descent methods. local minima solutions can be obtained with simple implementations and usually require smaller computational time than global algorithms. also, methods such as icm can be readily implemented in a various difficult problems that may involve larger than pairwise clique mrfs. however, their short comings are evident in comparison to newer methods such as graph cut and belief propagation. the local minimum depends largely on the initial state, which is the fundamental problem of its kind. in this paper, disadvantages of local minima techniques are addressed by proposing ways to combine multiple local solutions. first, multiple icm solutions are obtained using different initial states. the solutions are combined with random partitioning based greedy algorithm called combined local minima (clm). there are numerous mrf problems that cannot be efficiently implemented with graph cut and belief propagation, and so by introducing ways to effectively combine local solutions, we present a method to dramatically improve many of the pre-existing local minima algorithms. the proposed approach is shown to be effective on pairwise stereo mrf compared with graph cut and sequential tree re-weighted belief propagation (trw-s). additionally, we tested our algorithm against belief propagation (bp) over randomly generated 30 ×30 mrf with 2 ×2 clique potentials, and we experimentally illustrate clm's advantage over message passing algorithms in computation complexity and performance.
temporal dithering of illumination for fast active vision. active vision techniques use programmable light sources, such as projectors, whose intensities can be controlled over space and time. we present a broad framework for fast active vision using digital light processing (dlp) projectors. the digital micromirror array (dmd) in a dlp projector is capable of switching mirrors "on" and "off" at high speeds (106/s). an off-the-shelf dlp projector, however, effectively operates at much lower rates (30-60hz) by emitting smaller intensities that are integrated over time by a sensor (eye or camera) to produce the desired brightness value. our key idea is to exploit this "temporal dithering" of illumination, as observed by a high-speed camera. the dithering encodes each brightness value uniquely and may be used in conjunction with virtually any active vision technique. we apply our approach to five well-known problems: (a) structured light-based range finding, (b) photometric stereo, (c) illumination de-multiplexing, (d) high frequency preserving motion-blur and (e) separation of direct and global scene components, achieving significant speedups in performance. in all our methods, the projector receives a single image as input whereas the camera acquires a sequence of frames.
what does the sky tell us about the camera? as the main observed illuminant outdoors, the sky is a rich source of information about the scene. however, it is yet to be fully explored in computer vision because its appearance depends on the sun position, weather conditions, photometric and geometric parameters of the camera, and the location of capture. in this paper, we propose the use of a physically-based sky model to analyze the information available within the visible portion of the sky, observed over time. by fitting this model to an image sequence, we show how to extract camera parameters such as the focal length, and the zenith and azimuth angles. in short, the sky serves as a geometric calibration target. once the camera parameters are recovered, we show how to use the same model in two applications: 1) segmentation of the sky and cloud layers, and 2) data-driven sky matching across different image sequences based on a novel similarity measure defined on sky parameters. this measure, combined with a rich appearance database, allows us to model a wide range of sky conditions.
flexible depth of field photography. the range of scene depths that appear focused in an image is known as the depth of field (dof). conventional cameras are limited by a fundamental trade-off between depth of field and signal-to-noise ratio (snr). for a dark scene, the aperture of the lens must be opened up to maintain snr, which causes the dof to reduce. also, today's cameras have dofs that correspond to a single slab that is perpendicular to the optical axis. in this paper, we present an imaging system that enables one to control the dof in new and powerful ways. our approach is to vary the position and/or orientation of the image detector, during the integration time of a single photograph. even when the detector motion is very small (tens of microns), a large range of scene depths (several meters) is captured both in and out of focus.our prototype camera uses a micro-actuator to translate the detector along the optical axis during image integration. using this device, we demonstrate three applications of flexible dof. first, we describe extended dof, where a large depth range is captured with a very wide aperture (low noise) but with nearly depth-independent defocus blur. applying deconvolution to a captured image gives an image with extended dof and yet high snr. next, we show the capture of images with discontinuous dofs. for instance, near and far objects can be imaged with sharpness while objects in between are severely blurred. finally, we show that our camera can capture images with tilted dofs (scheimpflug imaging) without tilting the image detector. we believe flexible dof imaging can open a new creative dimension in photography and lead to new capabilities in scientific imaging, vision, and graphics.
movie/script: alignment and parsing of video and text transcription. movies and tv are a rich source of diverse and complex video of people, objects, actions and locales "in the wild". harvesting automatically labeled sequences of actions from video would enable creation of large-scale and highly-varied datasets. to enable such collection, we focus on the task of recovering scene structure in movies and tv series for object tracking and action retrieval. we present a weakly supervised algorithm that uses the screenplay and closed captions to parse a movie into a hierarchy of shots and scenes. scene boundaries in the movie are aligned with screenplay scene labels and shots are reordered into a sequence of long continuous tracks or threads which allow for more accurate tracking of people, actions and objects. scene segmentation, alignment, and shot threading are formulated as inference in a unified generative model and a novel hierarchical dynamic programming algorithm that can handle alignment and jump-limited reorderings in linear time is presented. we present quantitative and qualitative results on movie alignment and parsing, and use the recovered structure to improve character naming and retrieval of common actions in several episodes of popular tv series.
what is a good image segment? a unified approach to segment extraction. there is a huge diversity of definitions of "visually meaningful" image segments, ranging from simple uniformly colored segments, textured segments, through symmetric patterns, and up to complex semantically meaningful objects. this diversity has led to a wide range of different approaches for image segmentation. in this paper we present a single unified framework for addressing this problem --- "segmentation by composition". we define a good image segment as one which can be easily composed using its own pieces, but is difficult to compose using pieces from other parts of the image. this non-parametric approach captures a large diversity of segment types, yet requires no pre-definition or modelling of segment types, nor prior training. based on this definition, we develop a segment extraction algorithm --- i.e., given a single point-of-interest, provide the "best" image segment containing that point. this induces a figure-ground image segmentation, which applies to a range of different segmentation tasks: single image segmentation, simultaneous co-segmentation of several images, and class-based segmentations.
semantic concept classification by joint semi-supervised learning of feature subspaces and support vector machines. the scarcity of labeled training data relative to the high-dimensionality multi-modal features is one of the major obstacles for semantic concept classification of images and videos. semi-supervised learning leverages the large amount of unlabeled data in developing effective classifiers. feature subspace learning finds optimal feature subspaces for representing data and helping classification. in this paper, we present a novel algorithm, locality preserving semi-supervised support vector machines (lpssvm), to jointly learn an optimal feature subspace as well as a large margin svm classifier. over both labeled and unlabeled data, an optimal feature subspace is learned that can maintain the smoothness of local neighborhoods as well as being discriminative for classification. simultaneously, an svm classifier is optimized in the learned feature subspace to have large margin. the resulting classifier can be readily used to handle unseen test data. additionally, we show that the lpssvm algorithm can be used in a reproducing kernel hilbert space for nonlinear classification. we extensively evaluate the proposed algorithm over four types of data sets: a toy problem, two uci data sets, the caltech 101 data set for image classification, and the challenging kodak's consumer video data set for semantic concept detection. promising results are obtained which clearly confirm the effectiveness of the proposed method.
linking pose and motion. algorithms designed to estimate 3d pose in video sequences enforce temporal consistency but typically overlook an important source of information: the 3d pose of an object, be it rigid or articulated, has a direct influence on its direction of travel.in this paper, we use the cases of an airplane performing aerobatic maneuvers and of pedestrians walking and turning to demonstrate that this information can and should be used to increase the accuracy and reliability of pose estimation algorithms.
automated delineation of dendritic networks in noisy image stacks. we present a novel approach to 3d delineation of dendritic networks in noisy image stacks. we achieve a level of automation beyond that of state-of-the-art systems, which model dendrites as continuous tubular structures and postulate simple appearance models. instead, we learn models from the data itself, which make them better suited to handle noise and deviations from expected appearance.from very little expert-labeled ground truth, we train both a classifier to recognize individual dendrite voxels and a density model to classify segments connecting pairs of points as dendrite-like or not. given these models, we can then trace the dendritic trees of neurons automatically by enforcing the tree structure of the resulting graph. we will show that our approach performs better than traditional techniques on brighfield image stacks.
scene discovery by matrix factorization. what constitutes a scene? defining a meaningful vocabulary for scene discovery is a challenging problem that has important consequences for object recognition. we consider scenes to depict correlated objects and present visual similarity. we introduce a max-margin factorization model that finds a low dimensional subspace with high discriminative power for correlated annotations. we postulate this space should allow us to discover a large number of scenes in unsupervised data; we show scene discrimination results on par with supervised approaches. this model also produces state of the art word prediction results including good annotation completion.
riemannian anisotropic diffusion for tensor valued images. tensor valued images, for instance originating from diffusion tensor magnetic resonance imaging (dt-mri), have become more and more important over the last couple of years. due to the nonlinear structure of such data it is nontrivial to adapt well-established image processing techniques to them. in this contribution we derive anisotropic diffusion equations for tensor-valued images based on the intrinsic riemannian geometric structure of the space of symmetric positive tensors. in contrast to anisotropic diffusion approaches proposed so far, which are based on the euclidian metric, our approach considers the nonlinear structure of positive definite tensors by means of the intrinsic riemannian metric. together with an intrinsic numerical scheme our approach overcomes a main drawback of former proposed anisotropic diffusion approaches, the so-called eigenvalue swelling effect. experiments on synthetic data as well as real dt-mri data demonstrate the value of a sound differential geometric formulation of diffusion processes for tensor valued data.
differential spatial resection - pose estimation using a single local image feature. robust local image features have been used successfully in robot localization and camera pose estimation; region tracking using affine warps is considered state of the art also for many years. although such correspondences provide a warp of the local image region and are quite powerful, in direct pose estimation they are so far only considered as points and therefore three of them are required to construct a camera pose. in this contribution we show how it is possible to directly compute a pose based upon one such feature, given the plane in space where it lies. this differential correspondence concept exploits the texture warp and has recently gained attention in estimation of conjugate rotations. the approach can also be considered as the limiting case of the well-known spatial resection problem when the three 3d points approach each other infinitesimally close. we show that the differential correspondence is more powerful than conic correspondences while its exploitation requires nothing more complicated than the roots of a third order polynomial. we give a detailed sensitivity analysis, a comparison against state-of-the-art pose estimators and demonstrate real-world applicability of the algorithm based on automatic region recognition.
simultaneous detection and registration for ileo-cecal valve detection in 3d ct colonography. object detection and recognition has achieved a significant progress in recent years. however robust 3d object detection and segmentation in noisy 3d data volumes remains a challenging problem. localizing an object generally requires its spatial configuration (i.e., pose, size) being aligned with the trained object model, while estimation of an object's spatial configuration is only valid at locations where the object appears. detecting object while exhaustively searching its spatial parameters, is computationally prohibitive due to the high dimensionality of 3d search space. in this paper, we circumvent this computational complexity by proposing a novel framework capable of incrementally learning the object parameters (ipl) of location, pose and scale. this method is based on a sequence of binary encodings of the projected true positives from the original 3d object annotations (i.e., the projections of the global optima from the global space into the sections of subspaces). the training samples in each projected subspace are labeled as positive or negative, according their spatial registration distances towards annotations as ground-truth. each encoding process can be considered as a general binary classification problem and is implemented using probabilistic boosting tree algorithm. we validate our approach with extensive experiments and performance evaluations for ileo-cecal valve (icv) detection in both clean and tagged 3d ct colonography scans. our final icv detection system also includes an optional prior learning procedure for ipl which further speeds up the detection.
dynamic integration of generalized cues for person tracking. we present an approach for the dynamic combination of multiple cues in a particle filter-based tracking framework. the proposed algorithm is based on a combination of democratic integration and layered sampling. it is capable of dealing with deficiencies of single features as well as partial occlusion using the very same dynamic fusion mechanism. a set of simple but fast cues is defined, which allow us to cope with limited computational resources. the system is capable of automatic track initialization by means of a dedicated attention tracker permanently scanning the surroundings.
image segmentation by branch-and-mincut. efficient global optimization techniques such as graph cut exist for energies corresponding to binary image segmentation from low-level cues. however, introducing a high-level prior such as a shape prior or a color-distribution prior into the segmentation process typically results in an energy that is much harder to optimize. the main contribution of the paper is a new global optimization framework for a wide class of such energies. the framework is built upon two powerful techniques: graph cut and branch-and-bound. these techniques are unified through the derivation of lower bounds on the energies. being computable via graph cut, these bounds are used to prune branches within a branch-and-bound search.we demonstrate that the new framework can compute globally optimal segmentations for a variety of segmentation scenarios in a reasonable time on a modern cpu. these scenarios include unsupervised segmentation of an object undergoing 3d pose change, category-specific shape segmentation, and the segmentation under intensity/color priors defined by chan-vese and grabcut functionals.
robust visual tracking based on an effective appearance model. most existing appearance models for visual tracking usually construct a pixel-based representation of object appearance so that they are incapable of fully capturing both global and local spatial layout information of object appearance. in order to address this problem, we propose a novel spatial log-euclidean appearance model (referred as slam) under the recently introduced log-euclidean riemannian metric [23]. slam is capable of capturing both the global and local spatial layout information of object appearance by constructing a block-based log-euclidean eigenspace representation. specifically, the process of learning the proposed slam consists of five steps--appearance block division, online log-euclidean eigenspace learning, local spatial weighting, global spatial weighting, and likelihood evaluation. furthermore, a novel online log-euclidean riemannian subspace learning algorithm (irsl) [14] is applied to incrementally update the proposed slam. tracking is then led by the bayesian state inference framework in which a particle filter is used for propagating sample distributions over the time. theoretic analysis and experimental evaluations demonstrate the promise and effectiveness of the proposed slam.
light-efficient photography. we consider the problem of imaging a scene with a given depth of field at a given exposure level in the shortest amount of time possible. we show that by (1) collecting a sequence of photos and (2) controlling the aperture, focus and exposure time of each photo individually, we can span the given depth of field in less total time than it takes to expose a single narrower-aperture photo. using this as a starting point, we obtain two key results. first, for lenses with continuously-variable apertures, we derive a closed-form solution for the globally optimal capture sequence, i.e., that collects light from the specified depth of field in the most efficient way possible. second, for lenses with discrete apertures, we derive an integer programming problem whose solution is the optimal sequence. our results are applicable to off-the-shelf cameras and typical photography conditions, and advocate the use of dense, wide-aperture photo sequences as a light-efficient alternative to single-shot, narrow-aperture photography.
priors for large photo collections and what they reveal about cameras. a large photo collection downloaded from the internet spans a wide range of scenes, cameras, and photographers. in this paper we introduce several novel priors for statistics of such large photo collections that are independent of these factors. we then propose that properties of these factors can be recovered by examining the deviation between these statistical priors and the statistics of a slice of the overall photo collection that holds one factor constant. specifically, we recover the radiometric properties of a particular camera model by collecting numerous images captured by it, and examining the deviation of this collection's statistics from that of a broader photo collection whose camera-specific effects have been removed. we show that using this approach we can recover both a camera model's non-linear response function and the spatially-varying vignetting of the camera's different lens settings. all this is achieved using publicly available photographs, without requiring images captured under controlled conditions or physical access to the cameras. we also apply this concept to identify bad pixels on the detectors of specific camera instances. we conclude with a discussion of future applications of this general approach to other common computer vision problems.
understanding camera trade-offs through a bayesian analysis of light field projections. computer vision has traditionally focused on extracting structure, such as depth, from images acquired using thin-lens or pinhole optics. the development of computational imaging is broadening this scope; a variety of unconventional cameras do not directly capture a traditional image anymore, but instead require the joint reconstruction of structure and image information. for example, recent coded aperture designs have been optimized to facilitate the joint reconstruction of depth and intensity. the breadth of imaging designs requires new tools to understand the tradeoffs implied by different strategies.this paper introduces a unified framework for analyzing computational imaging approaches. each sensor element is modeled as an inner product over the 4d light field. the imaging task is then posed as bayesian inference: given the observed noisy light field projections and a prior on light field signals, estimate the original light field. under common imaging conditions, we compare the performance of various camera designs using 2d light field simulations. this framework allows us to better understand the tradeoffs of each camera type and analyze their limitations.
passive reflectometry. different materials reflect light in different ways, so reflectance is a useful surface descriptor. existing systems for measuring reflectance are cumbersome, however, and although the process can be streamlined using cameras, projectors and clever catadioptrics, it generally requires complex infrastructure. in this paper we propose a simpler method for inferring reflectance from images, one that eliminates the need for active lighting and exploits natural illumination instead. the method's distinguishing property is its ability to handle a broad class of isotropic reflectance functions, including those that are neither radially-symmetric nor well-represented by low-parameter reflectance models. the key to the approach is a bi-variate representation of isotropic reflectance that enables a tractable inference algorithm while maintaining generality. the resulting method requires only a camera, a light probe, and as little as one hdr image of a known, curved, homogeneous surface.
regular texture analysis as statistical model selection. an approach to the analysis of images of regular texture is proposed in which lattice hypotheses are used to define statistical models. these models are then compared in terms of their ability to explain the image. a method based on this approach is described in which lattice hypotheses are generated using analysis of peaks in the image autocorrelation function, statistical models are based on gaussian or gaussian mixture clusters, and model comparison is performed using the marginal likelihood as approximated by the bayes information criterion (bic). experiments on public domain regular texture images and a commercial textile image archive demonstrate substantially improved accuracy compared to two competing methods. the method is also used for classification of texture images as regular or irregular. an application to thumbnail image extraction is discussed.
three dimensional curvilinear structure detection using optimally oriented flux. this paper proposes a novel curvilinear structure detector, called optimally oriented flux (oof). oof finds an optimal axis on which image gradients are projected in order to compute the image gradient flux. the computation of oof is localized at the boundaries of local spherical regions. it avoids considering closely located adjacent structures. the main advantage of oof is its robustness against the disturbance induced by closely located adjacent objects. moreover, the analytical formulation of oof introduces no additional computation load as compared to the calculation of the hessian matrix which is widely used for curvilinear structure detection. it is experimentally demonstrated that oof delivers accurate and stable curvilinear structure detection responses under the interference of closely located adjacent structures as well as image noise.
co-recognition of image pairs by data-driven monte carlo image exploration. we introduce a new concept of `co-recognition' for object-level image matching between an arbitrary image pair. our method augments putative local region matches to reliable object-level correspondences without any supervision or prior knowledge on common objects. it provides the number of reliable common objects and the dense correspondences between the image pair. in this paper, generative model for co-recognition is presented. for inference, we propose data-driven monte carlo image exploration which clusters and propagates local region matches by markov chain dynamics. the global optimum is achieved by a guiding force of our data-driven sampling and posterior probability model. in the experiments, we demonstrate the power and utility on image retrieval and unsupervised recognition and segmentation of multiple common objects.
scene segmentation for behaviour correlation. this paper presents a novel framework for detecting abnormal pedestrian and vehicle behaviour by modelling cross-correlation among different co-occurring objects both locally and globally in a given scene. we address this problem by first segmenting a scene into semantic regions according to how object events occur globally in the scene, and second modelling concurrent correlations among regional object events both locally (within the same region) and globally (across different regions). instead of tracking objects, the model represents behaviour based on classification of atomic video events, designed to be more suitable for analysing crowded scenes. the proposed system works in an unsupervised manner throughout using automatic model order selection to estimate its parameters given video data of a scene for a brief training period. we demonstrate the effectiveness of this system with experiments on public road traffic data.
action recognition with a bio-inspired feedforward motion processing model: the richness of center-surround interactions. here we show that reproducing the functional properties of mt cells with various center---surround interactions enriches motion representation and improves the action recognition performance. to do so, we propose a simplified bio---inspired model of the motion pathway in primates: it is a feedforward model restricted to v1-mt cortical layers, cortical cells cover the visual space with a foveated structure and, more importantly, we reproduce some of the richness of center-surround interactions of mt cells. interestingly, as observed in neurophysiology, our mt cells not only behave like simple velocity detectors, but also respond to several kinds of motion contrasts. results show that this diversity of motion representation at the mt level is a major advantage for an action recognition task. defining motion maps as our feature vectors, we used a standard classification method on the weizmann database: we obtained an average recognition rate of 98.9%, which is superior to the recent results by jhuang et al. (2007). these promising results encourage us to further develop bio---inspired models incorporating other brain mechanisms and cortical layers in order to deal with more complex videos.
learning from real images to model lighting variations for face images. for robust face recognition, the problem of lighting variation is considered as one of the greatest challenges. since the nine points of light (9pl) subspace is an appropriate low-dimensional approximation to the illumination cone, it yielded good face recognition results under a wide range of difficult lighting conditions. however building the 9pl subspace for a subject requires 9 gallery images under specific lighting conditions, which are not always possible in practice. instead, we propose a statistical model for performing face recognition under variable illumination. through this model, the nine basis images of a face can be recovered via maximum-a-posteriori (map) estimation with only one gallery image of that face. furthermore, the training procedure requires only some real images and avoids tedious processing like svd decomposition or the use of geometric (3d) or albedo information of a surface. with the recovered nine dimensional lighting subspace, recognition experiments were performed extensively on three publicly available databases which include images under single and multiple distant point light sources. our approach yields better results than current ones. even under extreme lighting conditions, the estimated subspace can still represent lighting variation well. the recovered subspace retains the main characteristics of 9pl subspace. thus, the proposed algorithm can be applied to recognition under variable lighting conditions.
locating facial features with an extended active shape model. we make some simple extensions to the active shape model of cootes et al. [4], and use it to locate features in frontal views of upright faces. we show on independent test data that with the extensions the active shape model compares favorably with more sophisticated methods. the extensions are (i) fitting more landmarks than are actually needed (ii) selectively using two- instead of one-dimensional landmark templates (iii) adding noise to the training set (iv) relaxing the shape model where advantageous (v) trimming covariance matrices by setting most entries to zero, and (vi) stacking two active shape models in series.
higher dimensional affine registration and vision applications. affine registration has a long and venerable history in computer vision literature, and extensive work have been done for affine registrations in ℝ2 and ℝ3. in this paper, we study affine registrations in ℝ m for m > 3, and to justify breaking this dimension barrier, we show two interesting types of matching problems that can be formulated and solved as affine registration problems in dimensions higher than three: stereo correspondence under motion and image set matching. more specifically, for an object undergoing non-rigid motion that can be linearly modelled using a small number of shape basis vectors, the stereo correspondence problem can be solved by affine registering points in ℝ3n . and given two collections of images related by an unknown linear transformation of the image space, the correspondences between images in the two collections can be recovered by solving an affine registration problem in ℝm, where m is the dimension of a pca subspace. the algorithm proposed in this paper estimates the affine transformation between two point sets in ℝm. it does not require continuous optimization, and our analysis shows that, in the absence of data noise, the algorithm will recover the exact affine transformation for almost all point sets with the worst-case time complexity of o(mk 2), k the size of the point set. we validate the proposed algorithm on a variety of synthetic point sets in different dimensions with varying degrees of deformation and noise, and we also show experimentally that the two types of matching problems can indeed be solved satisfactorily using the proposed affine registration algorithm.
image segmentation in the presence of shadows and highlights. the segmentation method proposed in this paper is based on the observation that a single physical reflectance can have many different image values. we call the set of all these values a dominant colour. these variations are caused by shadows, shading and highlights and due to varying object geometry. the main idea is that dominant colours trace connected ridges in the chromatic histogram. to capture them, we propose a new ridge based distribution analysis (rad) to find the set of ridges representative of the dominant colour. first, a multilocal creaseness technique followed by a ridge extraction algorithm is proposed. afterwards, a flooding procedure is performed to find the dominant colours in the histogram. qualitative results illustrate the ability of our method to obtain excellent results in the presence of shadow and highlight edges. quantitative results obtained on the berkeley data set show that our method outperforms state-of-the-art segmentation methods at low computational cost.
a pose-invariant descriptor for human detection and segmentation. we present a learning-based, sliding window-style approach for the problem of detecting humans in still images. instead of traditional concatenation-style image location-based feature encoding, a global descriptor more invariant to pose variation is introduced. specifically, we propose a principled approach to learning and classifying human/non-human image patterns by simultaneously segmenting human shapes and poses, and extracting articulation-insensitive features. the shapes and poses are segmented by an efficient, probabilistic hierarchical part-template matching algorithm, and the features are collected in the context of poses by tracing around the estimated shape boundaries. histograms of oriented gradients are used as a source of low-level features from which our pose-invariant descriptors are computed, and kernel svms are adopted as the test classifiers. we evaluate our detection and segmentation approach on two public pedestrian datasets.
constructing category hierarchies for visual recognition. class hierarchies are commonly used to reduce the complexity of the classification problem. this is crucial when dealing with a large number of categories. in this work, we evaluate class hierarchies currently constructed for visual recognition. we show that top-down as well as bottom-up approaches, which are commonly used to automatically construct hierarchies, incorporate assumptions about the separability of classes. those assumptions do not hold for visual recognition of a large number of object categories. we therefore propose a modification which is appropriate for most top-down approaches. it allows to construct class hierarchies that postpone decisions in the presence of uncertainty and thus provide higher recognition accuracy. we also compare our method to a one-against-all approach and show how to control the speed-for-accuracy trade-off with our method. for the experimental evaluation, we use the caltech-256 visual object classes dataset and compare to state-of-the-art methods.
graph decompositions and secret sharing schemes. in this paper, we continue a study of secret sharing schemes for access structures based on graphs. given a graph g, we require that a subset of participants can compute a secret key if they contain an edge of g otherwise, they can obtain no information regarding the key. we study the information rate of such schemes, which measures how much information is being distributed as shares as compared to the size of the secret key, and the average information rate, which is the ratio between the secret size and the arithmetic mean of the size of the shares. we give both upper and lower bounds on the optimal information rate and average information rate that can be obtained. upper bounds arise by applying entropy arguments due to capocelli et al [10]. lower bounds come from constructions that are based on graph decompositions. application of these constructions requires solving a particular linear programming problem. we prove some general results concerning the information rate and average information rate for paths, cycles and trees. also, we study the 30 (connected) graphs on at most five vertices, obtaining exact values for the optimal information rate in 26 of the 30 cases, and for the optimal avebage information rate in 28 of the 30 cases.
cryptanalysis of rsa with private key less than . we show that if the private exponent d used in the rsa public-key cryptosystem is less than n0:292 then the system is insecure. this is first improvement over an old result of wiener showing that when d < n0:25 the rsa system is insecure. we hope our approach can be used to eventually improve the bound to d < n0:5.
aggregate and verifiably encrypted signatures from bilinear maps. an aggregate signature scheme is a digital signature that supports aggregation: given n signatures on n distinct messages from n distinct users, it is possible to aggregate all these signatures into a single short signature. this single signature (and the n original messages) will convince the verifier that the n users did indeed sign the n original messages (i.e., user i signed message mi for i = 1, . . . , n). in this paper we introduce the concept of an aggregate signature, present security models for such signatures, and give several applications for aggregate signatures. we construct an efficient aggregate signature from a recent short signature scheme based on bilinear maps due to boneh, lynn, and shacham. aggregate signatures are useful for reducing the size of certificate chains (by aggregating all signatures in the chain) and for reducing message size in secure routing protocols such as sbgp. we also show that aggregate signatures give rise to verifiably encrypted signatures. such signatures enable the verifier to test that a given ciphertext c is the encryption of a signature on a given message m. verifiably encrypted signatures are used in contract-signing protocols. finally, we show that similar ideas can be used to extend the short signature scheme to give simple ring signatures.
two attacks on reduced idea. in 1991 lai, massey and murphy introduced the ipes (improved proposed encryption standard), later renamed idea (international data encryption algorithm). in this paper we give two new attacks on a reduced number of rounds of idea. a truncated differential attack on idea reduced to 3.5 rounds and a differential-linear attack on idea reduced to 3 rounds. the truncated differential attack contains a novel method for determining the secret key.
public-key encryption in a multi-user setting: security proofs and improvements. this paper addresses the security of public-key cryptosystems in a "multi-user" setting, namely in the presence of attacks involving the encryption of related messages under different public keys, as exemplified by håstad's classical attacks on rsa. we prove that security in the single-user setting implies security in the multi-user setting as long as the former is interpreted in the strong sense of "indistinguishability," thereby pin-pointing many schemes guaranteed to be secure against håstad-type attacks. we then highlight the importance, in practice, of considering and improving the concrete security of the general reduction, and present such improvements for two diffie-hellman based schemes, namely el gamal and cramer-shoup.
efficient proofs that a committed number lies in an interval. alice wants to prove that she is young enough to borrow money from her bank, without revealing her age. she therefore needs a tool for proving that a committed number lies in a specific interval. up to now, such tools were either inefficient (too many bits to compute and to transmit) or inexact (i.e. proved membership to a much larger interval). this paper presents a new proof, which is both efficient and exact. here, "efficient" means that there are less than 20 exponentiations to perform and less than 2 kbytes to transmit. the potential areas of application of this proof are numerous (electronic cash, group signatures, publicly verifiable secret encryption, etc ...).
batch diffie-hellman key agreement systems and their application to portable communications. rsa (rivest, shamir and adleman) is today's most popular public key encryption scheme. batch-rsa (due to fiat) is a method to compute many (n/log22(n), where n is the security parameter) rsa decryption operations at a computational cost approaching that of one normal decryption. it requires that all the operations use the same modulus, but distinct, relatively prime in pairs, short, public exponents. a star-like key agreement scheme could use such a system to slash computational complexity at the center. we show a real life example of such a system - secure portable telephony. unfortunately, in this system batch-rsa cannot be employed effectively, due to a delay component which arises from the nature of rsa key exchange. we show that mathematical ideas similar to fiat's can lead to a batch-diffie-hellman key agreement scheme, that does not suffer such delay and is comparable in efficiency to batch-rsa. we prove that with some precautions, this system is as hard to break as rsa with short public exponent. in practice our method improves processing time at the center by a factor of 6 to 17 when compared to (non-batch) diffie-hellman schemes with full-size exponents and moduli in the practical range. smaller improvements (on the order of 1.6 to 3) are obtainable when compared to a diffie-hellman scheme employing abbreviated exponents.
the exact security of digital signatures - how to sign with rsa and rabin. we describe an rsa-based signing scheme which combines essentially optimal efficiency with attractive security properties. signing takes one rsa decryption plus some hashing, verification takes one rsa encryption plus some hashing, and the size of the signature is the size of the modulus. assuming the underlying hash functions are ideal, our schemes are not only provably secure, but are so in a tight way-- an ability to forge signatures with a certain amount of computational resources implies the ability to invert rsa (on the same size modulus) with about the same computational effort. furthermore, we provide a second scheme which maintains all of the above features and in addition provides message recovery. these ideas extend to provide schemes for rabin signatures with analogous properties; in particular their security can be tightly related to the hardness of factoring.
how to broadcast a secret. a single transmitter wishes to broadcast a secret to some subset of his listeners. he does not wish to perform, for each of the intended recipients, a separate encryption either of the secret or of a single key with which to protect the secret. a general method for such a secret broadcasting scheme is proposed. it is based on "k out of n" secret sharing. an example using polynomial interpolation is presented as well as a related vector formulation.
on the development of a fast elliptic curve cryptosystem. in this paper, we look at the development of a high speed elliptic curve cryptosystem based on a 40 mhz. motorola m68030 processor and a high speed optimal normal basis coprocessor for the ground field gf(2155). the advantage of this system is the relatively small block size required for high security applications such as key management and digital signatures. in addition, the design is very compact and efficient and can be easily fit onto a standard smart card wafer (the coprocessor core requires less than 1.sq.mil. or < 48% of the area available on a smart card).
captcha: using hard ai problems for security. we introduce captcha, an automated test that humans can pass, but current computer programs can't pass: any program that has high success over a captcha can be used to solve an unsolved artificial intelligence (ai) problem. we provide several novel constructions of captchas. since captchas have many applications in practical security, our approach introduces a new class of hard problems that can be exploited for security purposes. much like research in cryptography has had a positive impact on algorithms for factoring and discrete log, we hope that the use of hard ai problems for security purposes allows us to advance the field of artificial intelligence. we introduce two families of ai problems that can be used to construct captchas and we show that solutions to such problems can be used for steganographic communication. captchas based on these ai problem families, then, imply a win-win situation: either the problems remain unsolved and there is a way to differentiate humans from computers, or the problems are solved and there is a way to communicate covertly on some channels.
foiling birthday attacks in length-doubling transformations - benes: a non-reversible alternative to feistel. for many cryptographic primitives, e.g., hashing and psendorandom functions & generators, doubling the output length is useful even if the doubling transformation is not reversible. for these cases, we present a non-reversible construction based on a belies network, as an alternative to the traditional feistel construction (which is the basis of des). assuming that a given primitive behaves likc an n-bit to n-bit random function, we present a length-doubling scheme that yields a 2n-bit to 2n-bit function that provably requires ω(2n) queries to distinguish with θ(1) probability from a truly random function of that length. this is true even if the adversary is of unlimited computing power arid is allowed to query the function adaptively. oiir construction is minimal in the sense that omitting any operation makes the resulting network susceptible to birthday attacks using o(2n/2) queries. feistel networks also use truly random n-bit functions to achieve 2n- bit functions. luby and rackoff [16] showed that 3 and 4 round feistel networks require ω(2n/2) queries to distinguish with θ(1) probability from truly random. we show that these bounds are tight by showing that these networks are susceptible various types of birthday attacks using o(2n/2) queries.
short discrete proofs. we show how to produce short proofs of theorems such that a distrusting verifier can be convinced that the theorem is true yet obtains no information about the proof itself. the proofs are non-interactive provided that the quadratic residuosity bit commitment scheme is available to the prover and verifier. for typical applications, the proofs are short enough to fit on a floppy disk.
non supersingular elliptic curves for public key cryptosystems. for public key cryptosystems multiplication on elliptic curves can be used instead of exponentiation in finite fields. one attack to such a system is embedding the elliptic curve group into the multiplicative group of a finite field via weilpairing; calculating the discrete logarithm on the curve by solving the discrete logarithm in the finite field. this attack can be avoided by constructing curves so that every embedding in a multiplicative group of a finite field requires a field of very large size.
the gchq protocol and its problems. the uk government is fielding an architecture for secure electronic mail based on the nsa's message security protocol, with a key escrow scheme inspired by diffie-hellman. attempts have been made to have this protocol adopted by other governments and in various domestic applications. the declared policy goal is to entrench commercial key escrow while simultaneously creating a large enough market that software houses will support the protocol as a standard feature rather than charging extra for it. we describe this protocol and show that, like the 'clipper' proposal of a few years ago, it has a number of problems. it provides the worst of both secret and public key systems, without delivering the advantages of either; it does not support nonrepudiation; and there are serious problems with the replacement of compromised keys, the protection of security labels, and the support of complex or dynamic administrative structures.
perfect and essentially perfect authentication schemes. suppose that a wants to send a message m to b. it is important that b receives the message without any alteration. on the other hand, a bad guy x looks for his chance to alter m in his favour. in order t o make the bad guy's life difficult, a authenticates the message m. for this, a and b have to agree on an authentication function f and a secret key k. the function f has m and k as its input, and the authenticator (also called message authentication code) f(m,k) as its output.
a public key encryption scheme based on the polynomial reconstruction problem. the polynomial reconstruction problem (pr) has been introduced in 1999 as a new hard problem. several cryptographic primitives established on this problem have been constructed, for instance naor and pinkas have proposed a protocol for oblivious polynomial evaluation. then it has been studied from the point of view of robustness, and several important properties have been discovered and proved by kiayias and yung. furthermore the same authors constructed a symmetric cipher based on the pr problem. in the present paper, we use the published security results and construct a new public key encryption scheme based on the hardness of the problem of polynomial reconstruction. the scheme presented is the first public key encryption scheme based on this polynomial reconstruction problem. we also present some attacks, discuss their performances and state the size of the parameters required to reach the desired security level. in conclusion, this leads to a cryptosystem where the cost of encryption and decryption per bit is low, and where the public key is kept relatively small.
a² codes from universal hash classes. we describe a general method to construct codes for unconditional authentication with arbitration (a2-codes), which protect not only against outside opponents but also against certain types of frauds from the receiver and transmitter. the constructions are based on orthogonal arrays and universal hash classes. the idea is to construct a2-codes out of pairs of a-codes. the hitherto known examples are special cases of the construction. along the way we also construct new universal hash classes.
uniform results in polynomial-time security. most security results can be established both in the non-uniform and the uniform model of computation. nonetheless, non-uniform results are often much easier to obtain than their uniform version. in this paper we initiate a general framework in which the classical sampling technique can be applied to obtain uniform results. our main theorem gives sufficient conditions under which a non-uniform result can be extended to a uniform one. as a consequence, we derive the uniform version of schrift and shamir's generalization of yao's theorem on the universality of the next-bit test.
tools for proving zero knowledge. we develop general techniques that can be used to prove the zero knowledge property of most of the known zero knowledge protocols. those techniques consist in reducing the circuit indistinguishability of the output distributions of two probabilistic turing machines to the indistinguishability of the output distributions of certain subroutines.
collision-free accumulators and fail-stop signature schemes without trees. one-way accumulators, introduced by benaloh and de mare, can be used to accumulate a large number of values into a single one, which can then be used to authenticate every input value without the need to transmit the others. however, the one-way property does is not sufficient for all applications. in this paper, we generalize the definition of accumulators and define and construct a collision-free subtype. as an application, we construct a fail-stop signature scheme in which many one-time public keys are accumulated into one short public key. in contrast to previous constructions with tree authentication, the length of both this public key and the signatures can be independent of the number of messages that can be signed.
cryptanalysis of patarin's 2-round public key system with s boxes (2r). in a series of papers patarin proposes new efficient public key systems. a very interesting proposal, called 2-round public key system with s boxes, or 2r, is based on the difficulty of decomposing the structure of several rounds of unknown linear transformations and s boxes. this difficulty is due to the difficulty of decomposing compositions of multivariate binary functions. in this paper we present a novel attack which breaks the 64-bit block variant with complexity about 230 steps, and the more secure 128-bit blocks variant with complexity about 260 steps. it is interesting to note that this cryptanalysis uses only the ciphertexts of selected plaintexts, and does not analyze the details of the supplied encryption code.
cryptoanalysis of the chaotic-map cryptosystem suggested at eurocrypt'91. in this conference, habutsu[1] suggested a cryptosystem based on iterating a chaotic map. in this paper several properties of this cryptosystem are studied and two cryptanalytic attacks are described.
cryptology - methods and maxims. this paper gives a survey of classical cryptographic methods and of the maxims to their proper use in order to resist illegitimate decryption, as a basis for an understanding of modern commercial, computer-based cryptographic systems and for a critical analysis of those.
cryptanalysis of skipjack reduced to 31 rounds using impossible differentials. in this paper we present a new cryptanalytic technique, based on impossible differentials, and use it to show that skipjack reduced from 32 to 31 rounds can be broken by an attack which is faster than exhaustive search.
minimal-latency secure function evaluation. sander, young and yung recently exhibited a protocol for computing on encrypted inputs, for functions computable in nc1. in their variant of secure function evaluation, bob (the "cryptocomputer") accepts homomorphically-encrypted inputs (x) from client alice, and then returns a string from which alice can extract f(x; y) (where y is bob's input, or e.g. the function f itself). alice must not learn more about y than what f(x; y) reveals by itself. we extend their result to encompass nlogspace (nondeterministic log-space functions). in the domain of multiparty computations, constant-round protocols have been known for years [bb89,fkn95]. this paper introduces novel parallelization techniques that, coupled with the [syy99] methods, reduce the constant to 1 with preprocessing. this resolves the conjecture that nlogspace subcomputations (including log-slices of circuit computation) can be evaluated with latency 1 (as opposed to just o(1)).
how to break a "secure" oblivious transfer protocol. we show how to break a protocol for oblivious transfer presented at eurocrypt 90 [11]. armed with a new set of definitions for proving the security of interactive computations, we found difficulties in proving the protocol secure. these difficulties led us to a simple attack that breaks the ot protocol in a subtle but fundamental way. the error that we found may be present in a wide variety of secure protocols. it reveals a fundamental flaw in the traditional definition of oblivious transfer itself.
equivocable oblivious transfer. we analyze and enhance oblivious transfer (ot) protocols to accommodate security against adaptive attacks. previous analysis has been static in nature, treating the security of alice and the security of bob as separate cases, determined in advance. it remains unclear whether existing protocols are provably secure against adaptive attacks, but we provide enhancements to make them provably secure against attacks by adaptive 1-adversaries, who can choose at any time whether to corrupt alice or bob. we determine circumstances under which ot can be executed "in the open," without encrypting the messages, thereby giving simple alternatives to encrypting an entire interaction. we isolate equivocation properties that provide enough flexibility for a simulator to handle adaptive attacks. these properties also provide a means for classifying ot protocols and understanding the subtle demands of security against adaptive adversaries, as well as designing protocols that can be proven secure against adaptive attacks.
differential cryptoanalysis of feal and n-hash. in [1,2] we introduced the notion of differential cryptanalysis and described its application to des[8] and several of its variants. in this paper we show the applicability of differential cryptanalysis to the feal family of encryption algorithms and to the n-hash hash function.
cryptographic protocols provably secure against dynamic adversaries. we introduce new techniques for generating and reasoning about protocols. these techniques are based on protocol transformations that depend on the nature of the adversaries under consideration. we propose a set of definitions that, captures and unifies the intuitive notions of correctness, privacy, and robustness, and enables us to give concise and modular proofs that our protocols possess these desirable properties. using these techniques, whose major purpose is to greatly simplify the design and verification of cryptographic protocols, we show how to construct a multiparty cryptographic protocol to compute any given feasible function of the parties' inputs. we prove that our protocol is secure against the malicious actions of any adversary, limited to feasible computation, but with the power to eavesdrop on all messages and to corrupt any dynamically chosen minority of the parties. this is the first proof of security against dynamic adversaries in the "cryptographic" model of multiparty protocols. we assume the existeuce of a one-way function and allow the participants to erase small portions of memory. our result combines the superior resilience of the cryptographic setting of [gmw87] with the stronger (dynamic) fault pattern of the "non-cryptographic" setting of [bgw88, ccd88].
a toolbox for cryptanalysis: linear and affine equivalence algorithms. this paper presents two algorithms for solving the linear and the affine equivalence problem for arbitrary permutations (s-boxes). for a pair of n × n-bit permutations the complexity of the linear equivalence algorithm (le) is o(n32n). the affine equivalence algorithm (ae) has complexity o(n322n). the algorithms are efficient and allow to study linear and affine equivalences for bijective s-boxes of all popular sizes (le is efficient up to n ≤ 32). using these tools new equivalent representations are found for a variety of ciphers: rijndael, des, camellia, serpent, misty, kasumi, khazad, etc. the algorithms are furthermore extended for the case of non-bijective n to m-bit s-boxes with a small value of |n - m| and for the case of almost equivalent s-boxes. the algorithms also provide new attacks on a generalized even-mansour scheme. finally, the paper defines a new problem of s-box decomposition in terms of substitution permutations networks (spn) with layers of smaller s-boxes. simple information-theoretic bounds are proved for such decompositions.
structural cryptanalysis of sasas. in this paper we consider the security of block ciphers which contain alternate layers of invertible s-boxes and affine mappings (there are many popular cryptosystems which use this structure, including the winner of the aes competition, rijndael). we show that a five-layer scheme with 128-bit plaintexts and 8-bit s-boxes is surprisingly weak against what we call a multiset attack, even when all the s-boxes and affine mappings are key dependent (and thus completely unknown to the attacker). we tested the multiset attack with an actual implementation, which required just 216 chosen plaintexts and a few seconds on a single pc to find the 217 bits of information in all the unknown elements of the scheme.
advanced slide attacks. recently a powerful cryptanalytic tool--the slide attack-- was introduced [3]. slide attacks are very successful in breaking iterative ciphers with a high degree of self-similarity and even more surprisingly are independent of the number of rounds of a cipher. in this paper we extend the applicability of slide attacks to a larger class of ciphers. we find very efficient known- and chosen-text attacks on generic feistel ciphers with a periodic key-schedule with four independent subkeys, and consequently we are able to break a des variant proposed in [2] using just 128 chosen texts and negligible time for the analysis (for one out of every 216 keys). we also describe known-plaintext attacks on desx and even-mansour schemes with the same complexity as the best previously known chosen-plaintext attacks on these ciphers. finally, we provide new insight into the design of gost by successfully analyzing a 20-round variant (gost⊕) and demonstrating weak key classes for all 32 rounds.
general short computational secret sharing schemes. a secret sharing scheme permits a secret to be shared among participants in such a way that only qualified subsets of participants can recover the secret. if any non qualified subset has absolutely no information about the secret, then the scheme is called perfect. unfortunately, in this case the size of the shares cannot be less than the size of the secret. krawczyk [9] showed how to improve this bound in the case of computational threshold schemes by using rabin's information dispersal algorithms [14], [15]. we show how to extend the information dispersal algorithm for general access structure (we call access structure, the set of all qualified subsets). we give bounds on the amount of information each participant must have. then we apply this to construct computational schemes for general access structures. the size of shares each participant must have in our schemes is nearly minimal: it is equal to the minimal bound plus a piece of information whose length does not depend on the secret size but just on the security parameter.
on the impossibility of highly-efficient blockcipher-based hash functions. fix a small nonempty set of blockcipher keys . we say a blockcipher-based hash function is highly-efficient if it makes exactly one blockcipher call for each message block hashed, and all blockcipher calls use a key from . although a few highly-efficient constructions have been proposed, no one has been able to prove their security. in this paper we prove, in the ideal-cipher model, that it is impossible to construct a highly-efficient iterated blockcipher-based hash function that is provably secure. our result implies, in particular, that the tweakable chain hash (tch) construction suggested by liskov, rivest, and wagner (advances in cryptologycrypto 02, lecture notes in computer science, vol. 2442, pp. 3146, springer, berlin, 2002) is not correct under an instantiation suggested for this construction, nor can tch be correctly instantiated by any other efficient means.
round-optimal zero-knowledge arguments based on any one-way function. we fill a gap in the theory of zero-knowledge protocols by presenting np-arguments that achieve negligible error probability and computational zero-knowledge in four rounds of interaction, assuming only the existence of a one-way function. this result is optimal in the sense that four rounds and a one-way function are each individually necassary to achieve a negligible error zero-knowledge argument for np.
efficient multiplicative sharing schemes. multiplicative threshold schemes are useful tools in threshold cryptography. for example, such schemes can be used with a wide variety of practical homomorphic cryptosystems (such as the rsa, the el gamal and elliptic curve systems) for threshold decryption, signatures, or proofs. the paper describes a new recursive construction for multiplicative threshold schemes which makes it possible to extend the number of users of such schemes for a relatively small expansion of the share size. we discuss certain properties of the schemes, such as the information rate and zero knowledge aspects. the paper extends the karnin-greene-hellman bound on the parameters of ideal secret sharing schemes to schemes which are not necessarily ideal and then uses this as a yardstick to compare the performance of currently known multiplicative sharing schemes.
a theoretical treatment of related-key attacks: rka-prps, rka-prfs, and applications. we initiate a theoretical investigation of the popular blockcipher design-goal of security against "related-key attacks" (rkas). we begin by introducing definitions for the concepts of prps and prfs secure against classes of rkas, each such class being specified by an associated set of "related-key deriving (rkd) functions." then for some such classes of attacks, we prove impossibility results, showing that no block-cipher can resist these attacks while, for other, related classes of attacks that include popular targets in the block cipher community, we prove possibility results that provide theoretical support for the view that security against them is achievable. finally we prove security of various block-cipher based constructs that use related keys, including a tweakable block cipher given in [14].
noisy polynomial interpolation and noisy chinese remaindering. the noisy polynomial interpolation problem is a new intractability assumption introduced last year in oblivious polynomial evaluation. it also appeared independently in password identification schemes, due to its connection with secret sharing schemes based on lagrange's polynomial interpolation. this paper presents new algorithms to solve the noisy polynomial interpolation problem. in particular, we prove a reduction from noisy polynomial interpolation to the lattice shortest vector problem, when the parameters satisfy a certain condition that we make explicit. standard lattice reduction techniques appear to solve many instances of the problem. it follows that noisy polynomial interpolation is much easier than expected. we therefore suggest simple modifications to several cryptographic schemes recently proposed, in order to change the intractability assumption. we also discuss analogous methods for the related noisy chinese remaindering problem arising from the well-known analogy between polynomials and integers.
a new paradigm for collision-free hashing: incrementality at reduced cost. we present a simple, new paradigm for the design of collision-free hash functions. any function emanating from this paradigm is incremental. (this means that if a message x which i have previously hashed is modified to x′ then rather than having to re-compute the hash of x′ from scratch, i can quickly "update" the old hash value to the new one, in time proportional to the amount of modification made in x to get x′). also any function emanating from this paradigm is parallelizable, useful for hardware implementation. we derive several specific functions from our paradigm. all use a standard hash function, assumed ideal, and some algebraic operations. the first function, muhash, uses one modular multiplication per block of the message, making it reasonably efficient, and significantly faster than previous incremental hash functions. its security is proven, based on the hardness of the discrete logarithm problem. a second function, adhash, is even faster, using additions instead of multiplications, with security proven given either that approximation of the length of shortest lattice vectors is hard or that the weighted subset sum problem is hard. a third function, lthash, is a practical variant of recent lattice based functions, with security proven based, again on the hardness of shortest lattice vector approximation.
generating eigamal signatures without knowing the secret key. we present a new method to forge elgamal signatures if the public parameters of the system are not chosen properly. since the secret key is hereby riot fourid this attack shows that forging elgamal signatures is sometimes easier than the underlying discrete logarithm problem.
foundations of group signatures: formal definitions, simplified requirements, and a construction based on general assumptions. this paper provides theoretical foundations for the group signature primitive. we introduce strong, formal definitions for the core requirements of anonymity and traceability. we then show that these imply the large set of sometimes ambiguous existing informal requirements in the literature, thereby unifying and simplifying the requirements for this primitive. finally we prove the existence of a construct meeting our definitions based only on the sole assumption that trapdoor permutations exist.
authenticated key exchange secure against dictionary attacks. password-based protocols for authenticated key exchange (ake) are designed to work despite the use of passwords drawn from a space so small that an adversary might well enumerate, off line, all possible passwords. while several such protocols have been suggested, the underlying theory has been lagging. we begin by defining a model for this problem, one rich enough to deal with password guessing, forward secrecy, server compromise, and loss of session keys. the one model can be used to define various goals. we take ake (with "implicit" authentication) as the "basic" goal, and we give definitions for it, and for entity-authentication goals as well. then we prove correctness for the idea at the center of the encrypted key-exchange (eke) protocol of bellovin and merritt: we prove security, in an ideal-cipher model, of the two-flow protocol at the core of eke.
sha: a design for parallel architectures? to enhance system performance computer architectures tend to incorporate an increasing number of parallel execution units. this paper shows that the new generation of md4-based customized hash functions (ripemd-128, ripemd-160, sha-1) contains much more software parallelism than any of these computer architectures is currently able to provide. it is conjectured that the parallelism found in sha-1 is a design principle. the critical path of sha-1 is twice as short as that of its closest contender ripemd-160, but realizing it would require a 7-way multiple-issue architecture. it will also be shown that, due to the organization of ripemd-160 in two independent lines, it will probably be easier for future architectures to exploit its software parallelism.
on binary sequences from recursions modulo 2 made non-linear by the bit-by-bit xor function. we consider binary sequences obtained by choosing the the most significant bit of each element in a sequence obtained from a feedback shift register of length n operating over the ring z/2e, that is with arithmetic carried out modulo 2e. the feedback has been made non-linear by using the bit-by-bit exclusive-or function as well as the linear operation of addition. this should increase the cryptologic strength without greatly increasing the computing overheads. the periods and linear equivalences are discussed. provided certain conditions are met it is easy to check that the period achieves its maximal value.
enhancing secrecy by data compression: theoretical and practical aspects. it was recognised by shannon that data compression increases the strength of secrecy systems when applied prior to encryption. compression techniques have advanced considerably in recent years. this paper considers the extent to which these techniques can increase security. estimates are obtained for how far practical compression schemes can increase unicity distance of symmetric ciphers. it is noted that there are other good reasons for using data compression prior to encryption. comparison is made with homophonic coding and it is suggested that data compression is more worthwhile for practical sources such as natural language.
provably secure password-authenticated key exchange using diffie-hellman. when designing password-authenticated key exchange protocols (as opposed to key exchange protocols authenticated using cryptographically secure keys), one must not allow any information to be leaked that would allow verification of the password (a weak shared key), since an attacker who obtains this information may be able to run an off-line dictionary attack to determine the correct password. we present a new protocol called pak which is the first diffie-hellman-based password-authenticated key exchange protocol to provide a formal proof of security (in the random oracle model) against both passive and active adversaries. in addition to the pak protocol that provides mutual explicit authentication, we also show a more efficient protocol called ppk that is provably secure in the implicit -authentication model. we then extend pak to a protocol called pak-x, in which one side (the client) stores a plaintext version of the password, while the other side (the server) only stores a verifier for the password. we formally prove security of pak-x, even when the server is compromised. our formal model for password-authenticated key exchange is new, and may be of independent interest.
restrictive blinding of secret-key certificates. many signature transporting mechanisms require a signer to issue triples, consisting of a secret key, a matching public key, and a certificate of the signer on the public key. of particular interest are so-called restrictive blind signature issuing protocols, in which the receiver can blind the issued public key and the certificate but not a certain predicate of the secret key. this paper describes the first generally applicable techniquc for designing efficient such issuing protocols, based on the recently introduced notion of secret-key certificates. the resulting three-move issuing protocols require the receiver to perform merely a single on-line multiplication, and the property of restrictive blinding can be proved with respect to a plausible intractability assumption. application of the new issuing protocols results in the most efficient and versatile off-line electronic cash systems known to date, without using the blind signature technique developed by chaum.
rapid demonstration of linear relations connected by boolean operators. consider a polynomial-time prover holding a set of secrets. we describe how the prover can rapidly demonstrate any satisfiable boolean formula for which the atomic propositions are relations that are linear in the secrets, without revealing more information about the secrets than what is conveyed by the formula itself. our protocols support many proof modes, and are as secure as the discrete logarithm assumption or the rsa/factoring assumption.
blinding for unanticipated signatures. previously known blind signature systems require an amount of computation at least proportional to the number of signature types, and also that the number of such types be fixed in advance. these requirements are not practical in some applications. here, a new blind signature technique is introduced that allows an unlimited number of signature types with only a (modest) constant amount of computation.
some weaknesses of "weaknesses of undeniable signatures". the weaknesses that are the subject of [dy 91] have already been addressed in the published literature [c 90 & cva 89]. the main class of these weaknesses consists of ways of cheating undeniable signatures; but these ways are shown here to themselves be "weak." specifically, a cheater using them can double-cross the other cheaters, to the extent that the original ways of cheating are rendered useless. the remaining cited weaknesses are re-statements of, or variations on, some previously observed blinding techniques [cva 89]. these techniques allow advantages in some applications when desired, but are also easily excluded when not desired.
oblivious transfers and privacy amplification. assume a owns two secret k-bit strings. she is willing to disclose one of them to b, at his choosing, provided he does not learn anything about the other string. conversely, b does not want a to learn which secret he chose to learn. a protocol for the above task is said to implement one-out-of-two string oblivious transfer, denoted (2 1)-otk. this primitive is particularly useful in a variety of cryptographic settings. an apparently simpler task corresponds to the case k = 1 of two one-bit secrets: this is known as one-out-of-two bit oblivious transfer, denoted (2 1)-ot. we address the question of reducing (2 1)-otk to (2 1)-ot. this question is not new: it was introduced in 1986. however, most solutions until now have implicitly or explicitly depended on the notion of self-intersecting codes. it can be proved that this restriction makes it asymptotically impossible to implement (2 1)-otk with fewer than about 3.5277k instances of (2 1)-ot. the current paper introduces the idea of using privacy amplification as underlying technique to reduce (2 1)-otk to (2 1)-ot. this allows for more efficient solutions at the cost of an exponentially small probability of failure: it is sufficient to use slightly more than 2k instances of (2 1)-ot in order to implement (2 1)-otk. moreover, we show that privacy amplification allows for the efficient implementation of (2 1)-otk from generalized versions of (2 1)-ot that would not have been suitable for the earlier techniques based on self-intersecting codes. an application of this more general reduction is given.
security aspects of practical quantum cryptography. the use of quantum bits (qubits) in cryptography holds the promise of secure cryptographic quantum key distribution schemes. unfortunately, the implemented schemes are often operated in a regime which excludes unconditional security. we provide a thorough investigation of security issues for practical quantum key distribution, taking into account channel losses, a realistic detection process, and modifications of the "qubits" sent from the sender to the receiver. we first show that even quantum key distribution with perfect qubits might not be achievable over long distances when fixed channel losses and fixed dark count errors are taken into account. then we show that existing experimental schemes (based on weak pulses) currently do not offer unconditional security for the reported distances and signal strength. finally we show that parametric downconversion offers enhanced performance compared to its weak coherent pulse counterpart.
an improved protocol for demonstrating possession of discrete logarithms and some generalizations. a new protocol is presented that allows a to convince b that she knows a solution to the discrete log problem--i.e. that she knows an x such that αx ≡ β (mod n) holds-- without revealing anything about x to b. protocols are given both for n prime and for n composite. we also give protocols for extensions of the discrete log problem allowing a to show possession of: - multiple discrete logarithms to the same base at the same time, i.e. knowing x1,....,xk such that αx1 ≡ β1,..., αxk βk - several discrete logarithms to different bases at the same time, i.e. knowing x1,..., xk such that the product α1x1 α2x2... αkxk ≡ β - a discrete logarithm that is the simultaneous solution of several different instances, i.e. knowing x such that α1x ≡ β1,..., αkx ≡ βk. we can prove that the sequential versions of these protocols do not reveal any "knowledge" about the discrete logarithm(s) in a well-defined sense, provided that a knows (a multiple of) the order of α.
group signatures. in this paper we present a new type of signature for a group of persons, called a group signature, which has the following properties: (i) only members of the group can sign messages; (ii) the receiver can verify that it is a valid group signature, but cannot discover which group member made it; (iii) if necessary, the signature can be "opened", so that the person who signed the message is revealed. the group signatures are a "generalization" of the credential/ membership authentication schemes, in which one person proves that he belongs to a certain group. we present four schemes that satisfy the properties above. not all these schemes arc based on the same cryptographic assumption. in some of the schemes a trusted centre is only needed during the setup; and in other schemes, each pason can create the group he belongs to.
transferred cash grows in size. all known methods for transferring electronic money have the disadvantages that the number of bits needed to represent the money after each payment increases, and that a payer can recognize his money if he sees it later in the chain of payments (forward traceability). this paper shows that it is impossible to construct an electronic money system providing transferability without the property that the money grows when transferred. furthermore it is argued that an unlimited powerful user can always recognize his money later. finally, the lower bounds on the size of transferred electronic money are discussed in terms of secret sharing schemes.
on the efficiency of group signatures providing information-theoretic anonymity. group signatures, introduced by chaum and van heijst at eurocrypt'91, allow members of a group to make signatures on behalf of the group while remaining anonymous. furthermore, in case of disputes a designated group authority, who is given some auxiliary information, can identify the signer. chaum and van heijst presented four schemes, one of which protects the anonymity of the signer information-theoretically. however, this scheme as well as subsequent schemes with this property requires that the signer basically needs a new secret key for each signature and that the group authority secretly stores a very long string. this paper analyses such group signature schemes and obtains lower bounds on the length of both the secret keys of the group members and the auxiliary information of the authority depending on the number of signatures each is allowed to make and the number of group members. these bounds are optimal as they are met by the scheme suggested by chaum and van heijst.
s-boxes with controllable nonlinearity. in this paper, we give some relationship between the nonlinearity of rational functions over f2n and the number of points of associated hyperelliptic curve. using this, we get a lower bound on nonlinearity of rational-typed vector boolean functions over f2n. while the previous works give us a lower bound on nonlinearity only for special-typed monomials, our result gives us general bound applicable for all rational fuctions defined over f2n. as an application of our results, we get a lower bound on nonlinearity of n × kn s-boxes.
on a fast correlation attack on certain stream ciphers. in this paper we present a new algorithm for the recovery of the initial state of a linear feedback shift register when a noisy output sequence is given. our work is focussed on the investigation of the asymptotical behaviour of the recovery process rather than on the construction of an optimal recovery procedure. our results show the importance of low-weight checks and show also that the complexity of the recovery problem grows less than exponentially with the length of the shift register, even if the number of taps grows linearly with the register length. our procedure works for shift register with arbitrary feedback polynomial.
the information leakage through a randomly generated function. if a randomly filled memory is used to combine some ml-shift registers then the obtained mutual information between the output and a set of inputs will be a random variable. its distribution is demonstrated to be approximately proportional to a χ2-distribution.
improved algorithms for efficient arithmetic on elliptic curves using fast endomorphisms. in most algorithms involving elliptic curves, the most expensive part consists in computing multiples of points. this paper investigates how to extend the τ -adic expansion from koblitz curves to a larger class of curves defined over a prime field having an efficiently-computable endomorphism φ in order to perform an efficient point multiplication with efficiency similar to solinas' approach presented at crypto '97. furthermore, many elliptic curve cryptosystems require the computation of k0p + k1q. following the work of solinas on the joint sparse form, we introduce the notion of φ-joint sparse form which combines the advantages of a φ-expansion with the additional speedup of the joint sparse form. we also present an efficient algorithm to obtain the φ-joint sparse form. then, the double exponentiation can be done using the φ endomorphism instead of doubling, resulting in an average of l applications of φ and l/2 additions, where l is the size of the ki's. this results in an important speed-up when the computation of φ is particularly effective, as in the case of koblitz curves.
physical protection of cryptographic devices. with the growth of user awareness for the need to protect sensitive computer data by cryptographic means, this paper explains the need to protect critical cryptographic variables (particularly keys, and in some cases algorithms) in a secure environment within cryptographic equipment, particularly those used in the area of high value funds transfer transactions. design principles are outlined, leading to the concept of tamper resistant and not tamper proof devices to protect key data, whether the data be retained within physically large devices or on small portable tokens. criteria for the detection of attempts to gain access to sensitive data rather than attack prevention are outlined, together with two types of attack scenario - invasive and non-invasive. the risks of attack on cryptographic devices are surveyed and intruder attack objectives are outlined, together with some typical scenarios. the available counter-measures are discussed. several discreet mechanisms are described. typical detection mechanisms and sensor systems are discussed plus the design trade-offs that must be made in implementation, in particular manufacturing and maintenance costs versus scope of attack protection. once an attack is detected, various data destruction mechanisms may be employed. the desirability of active data destruction by "intelligent" means is proposed, together with a discussion of alternative techniques with particular reference to the data storage device characteristics. some experiences of tamper resistant research and development highlight the potential manufacturing problems - particularly in respect of quality assurance, product fault analysis and life-testing. the desirability of tamper resistant standards and independent assessment facilities is expressed, the applicability of such standards and large scale protection methods on intelligent tokens, in particular smart cards and personal authenticators, is discussed.
homomorphisms of secret sharing schemes: a tool for verifiable signature sharing. franklin and reiter introduced at eurocrypt '95 verifiable signature sharing, a primitive for a fault tolerant distribution of signature verification. they proposed various practical protocols. for rsa signatures with exponent e = 3 and n processors their protocol allows for up to (n - 1)/5 faulty processors (in general (n - 1)/(2 + e)). we consider a new unifying approach which uses homomorphisms of secret sharing schemes, and present a verifiable signature sharing scheme for which as many as (n - 1)/3 processors can be faulty (for any value of e), and for which the number of interactions is reduced.
factorization of a 512-bit rsa modulus. this paper reports on the factorization of the 512-bit number rsa-155 by the number field sieve factoring method (nfs) and discusses the implications for rsa.
finding a small root of a univariate modular equation. we show how to solve a polynomial equation (mod n) of degree k in a single variable x, as long as there is a solution smaller than n1/k. we give two applications to rsa encryption with exponent 3. first, knowledge of all the ciphertext and 2/3 of the plaintext bits for a single message reveals that message. second, if messages are padded with truly random padding and then encrypted with an exponent 3, then two encryptions of the same message (with different padding) will reveal the message, as long as the padding is less than 1/9 of the length of n. with several encryptions, another technique can (heuristically) tolerate padding up to about 1/6 of the length of n.
lattice attacks on ntru. ntru is a new public key cryptosystem proposed at crypto 96 by hoffstein, pipher and silverman from the mathematics department of brown university. it attracted considerable attention, and is being advertised over the internet by ntru cryptosystems. its security is based on the difficulty of analyzing the result of polynomial arithmetic modulo two unrelated moduli, and its correctness is based on clustering properties of the sums of random variables. in this paper, we apply new lattice basis reduction techniques to cryptanalyze the scheme, to discover either the original secret key, or an alternative secret key which is equally useful in decoding the ciphertexts.
finding a small root of a bivariate integer equation; factoring with high bits known. we present a method to solve integer polynomial equations in two variables, provided that the solution is suitably bounded. as an application, we show how to find the factors of n = pq if we are given the high order ((1/4) log2 n) bits of p. this compares with rivest and shamit's requirement of ((1/3) log2 n) bits.
computationally private information retrieval with polylogarithmic communication. we present a single-database computationally private information retrieval scheme with polylogarithmic communication complexity. our construction is based on a new, but reasonable intractability assumption, which we call the φ-hiding assumption (φha): essentially the difficulty of deciding whether a small prime divides φ(m), where m is a composite integer of unknown factorization.
low-exponent rsa with related messages. in this paper we present a new class of attacks against rsa with low encrypting exponent. the attacks enable the recovery of plaintext messages from their ciphertexts and a known polynomial relationship among the messages, provided that the ciphertexts were created using the same rsa public key with low encrypting exponent.
efficient and generalized group signatures. the concept of group signatures was introduced by chaum et al. at eurocrypt '91. it allows a member of a group to sign messages anonymously on behalf of the group. in case of a later dispute a designated group manager can revoke the anonymity and identify the originator of a signature. in this paper we propose a new efficient group signature scheme. furthermore we present a model and the first realization of generalized group signatures. such a scheme allows to define coalitions of group members that are able to sign on the group's behalf.
new attacks on pkcs#1 v1.5 encryption. this paper introduces two new attacks on pkcs#1 v1.5, an rsa-based encryption standard proposed by rsa laboratories. as opposed to bleichenbacher's attack, our attacks are chosen-plaintext only, i.e. they do not make use of a decryption oracle. the first attack applies to small public exponents and shows that a plaintext ending by sufficiently many zeroes can be recovered efficiently when two or more ciphertexts c orresponding to the same plaintext are available. we believe the technique we employ to be of independent interest, as it extends coppersmith's low-exponent attack to certain length parameters. our second attack is applicable to arbitrary public exponents, provided that most message bits are zeroes. it seems to constitute the first chosen-plaintext attack on an rsa-based encryption standard that yields to practical results for any public exponent.
confirmer signature schemes secure against adaptive adversaries. the main difference between confirmer signatures and ordinary digital signatures is that a confirmer signature can be verified only with the assistance of a semitrusted third party, the confirmer. additionally, the confirmer can selectively convert single confirmer signatures into ordinary signatures. this paper points out that previous models for confirmer signature schemes are too restricted to address the case where several signers share the same confirmer. more seriously, we show that various proposed schemes (some of which are provably secure in these restricted models) are vulnerable to an adaptive signature-transformation attack. we define a new stronger model that covers this kind of attack and provide a generic solution based on any secure ordinary signature scheme and public key encryption scheme. we also exhibit a concrete instance thereof.
security analysis of the gennaro-halevi-rabin signature scheme. we exhibit an attack against a signature scheme recently proposed by gennaro, halevi and rabin [9]. the scheme's security is based on two assumptions namely the strong rsa assumption and the existence of a division-intractable hash-function. for the latter, the authors conjectured a security level exponential in the hash-function's digest size whereas our attack is sub-exponential with respect to the digest size. moreover, since the new attack is optimal, the length of the hash function can now be rigorously fixed. in particular, to get a security level equivalent to 1024-bit rsa, one should use a digest size of approximately 1024 bits instead of the 512 bits suggested in [9].
proving in zero-knowledge that a number is the product of two safe primes. we present the first efficient statistical zero-knowledge protocols to prove statements such as: - a committed number is a prime. - a committed (or revealed) number is the product of two safe primes, i.e., primes p and q such that (p - 1)=2 and (q - 1)=2 are prime. - a given integer has large multiplicative order modulo a composite number that consists of two safe prime factors. the main building blocks of our protocols are statistical zero-knowledge proofs of knowledge that are of independent interest. we show how to prove the correct computation of a modular addition, a modular multiplication, and a modular exponentiation, where all values including the modulus are committed to but not publicly known. apart from the validity of the equations, no other information about the modulus (e.g., a generator whose order equals the modulus) or any other operand is exposed. our techniques can be generalized to prove that any multivariate modular polynomial equation is satisfied, where only commitments to the variables of the polynomial and to the modulus need to be known. this improves previous results, where the modulus is publicly known. we show how these building blocks allow to prove statements such as those listed earlier.
efficient algorithms for solving overdefined systems of multivariate polynomial equations. the security of many recently proposed cryptosystems is based on the difficulty of solving large systems of quadratic multivariate polynomial equations. this problem is np-hard over any field. when the number of equations m is the same as the number of unknowns n the best known algorithms are exhaustive search for small fields, and a gröbner base algorithm for large fields. gröbner base algorithms have large exponential complexity and cannot solve in practice systems with n ≥ 15. kipnis and shamir [9] have recently introduced a new algorithm called "relinearization". the exact complexity of this algorithm is not known, but for sufficiently overdefined systems it was expected to run in polynomial time. in this paper we analyze the theoretical and practical aspects of relinearization. we ran a large number of experiments for various values of n and m, and analysed which systems of equations were actually solvable. we show that many of the equations generated by relinearization are linearly dependent, and thus relinearization is less efficient that one could expect. we then develop an improved algorithm called xl which is both simpler and more powerful than relinearization. for all 0 < ∈ ≤ 1/2, and m ≥ ∈n2, xl and relinearization are expected to run in polynomial time of approximately no(1/√ɛ). moreover, we provide strong evidence that relinearization and xl can solve randomly generated systems of polynomial equations in subexponential time when m exceeds n by a number that increases slowly with n.
construction of t-resilient functions over a finite alphabet. we extend the notions of correlation-immune functions and resilient functions to functions over any finite alphabet endowed with the structure of an abelian group. thus we generalize the results of gopalakrishnan and stinson as we give an orthogonal array characterization and a fourier transform characterization for resilient functions over any finite alphabet. this leads to a generalization of some related cryptographic objects as perfect local randomizers. it also enables us to construct new resilient functions by composition of resilient functions of smaller order.
algebraic attacks on stream ciphers with linear feedback. a classical construction of stream ciphers is to combine several lfsrs and a highly non-linear boolean function f. their security is usually analysed in terms of correlation attacks, that can be seen as solving a system of multivariate linear equations, true with some probability. at icisc'02 this approach is extended to systems of higher-degree multivariate equations, and gives an attack in 292 for toyocrypt, a cryptrec submission. in this attack the key is found by solving an overdefined system of algebraic equations. in this paper we show how to substantially lower the degree of these equations by multiplying them by well-chosen multivariate polynomials. thus we are able to break toyocrypt in 249 cpu clocks, with only 20 kbytes of keystream, the fastest attack proposed so far. we also successfully attack the nessie submission lili-128, within 257 cpu clocks (not the fastest attack known). in general, we show that if the boolean function uses only a small subset (e.g. 10) of state/lfsr bits, the cipher can be broken, whatever is the boolean function used (worst case). our new general algebraic attack breaks stream ciphers satisfying all the previously known design criteria in at most the square root of the complexity of the previously known generic attack.
the knapsack hash function proposed at crypto'89 can be broken. ivan damgård [4] suggested at crypto'89 concrete examples of hash functions among which a knapsack scheme. we will here show that a probabilistic algorithm can break this scheme with a number in the region of 232 computations. that number of operations is feasible in realistic time with modern computers. thus the proposed hash function is not very secure. among those computations a substantial number can be performed once for all. a faster result can be obtained since parallelism is easy. moreover, ways to extend the present algorithm to other knapsacks than the present (256, 128) suggested by damgård are investigated.
fast and secure immunization against adaptive man-in-the-middle impersonation. we present a simple method for constructing identification schemes resilient against impersonation and man-in-the-middle attacks. though zero-knowledge or witness hiding protocols are known to withstand attacks of the first kind, all such protocols previously proposed suffer from a weakness observed by bengio et al.: a malicious verifier may simply act as a moderator between the prover and yet another verifier, thus enabling the malicious verifier to pass as the prover. we exhibit a general class of identification schemes that can be efficiently and securely tranformed into identification schemes withstanding an adaptive man-in-the-middle attacker. the complexity of the resulting (witness hiding) schemes is roughly twice that of the originals. basically, any three-move, public coin identification scheme that is zero knowledge against the honest verifier and that is secure against passive impersonation attacks, is eligible for our transformation. this indicates that we need only seemlingly weak cryptographic intractability assumptions to construct a practical identification scheme resisting adative man-in-the-middle impersonation attacks. moreover, the required primitive protocols can efficiently be constructed under the factoring or discrete logarithm assumptions.
efficient multiparty computations secure against an adaptive adversary. we consider verifiable secret sharing (vss) and multiparty computation (mpc) in the secure-channels model, where a broadcast channel is given and a non-zero error probability is allowed. in this model rabin and ben-or proposed vss and mpc protocols secure against an adversary that can corrupt any minority of the players. in this paper, we first observe that a subprotocol of theirs, known as weak secret sharing (wss), is not secure against an adaptive adversary, contrary to what was believed earlier. we then propose new and adaptively secure protocols for wss, vss and mpc that are substantially more efficient than the original ones. our protocols generalize easily to provide security against general q2-adversaries.
exposure-resilient functions and all-or-nothing transforms. we study the problem of partial key exposure. standard cryptographic definitions and constructions do not guarantee any security even if a tiny fraction of the secret key is compromised. we show how to build cryptographic primitives that remain secure even when an adversary is able to learn almost all of the secret key. the key to our approach is a new primitive of independent interest, which we call an exposure-resilient function (erf) - a deterministic function whose output appears random (in a perfect, statistical or computational sense) even if almost all the bits of the input are known. erf's by themselves efficiently solve the partial key exposure problem in the setting where the secret is simply a random value, like in private-key cryptography. they can also be viewed as very secure pseudorandom generators, and have many other applications. to solve the general partial key exposure problem, we use the (generalized) notion of an all-or-nothing transform (aont), an invertible (randomized) transformation t which, nevertheless, reveals "no information" about x even if almost all the bits of t(x) are known. by applying an aont to the secret key of any cryptographic system, we obtain security against partial key exposure. to date, the only known security analyses of aont candidates were made in the random oracle model. we show how to construct erf's and aont's with nearly optimal parameters. our computational constructions are based on any one-way function. we also provide several applications and additional properties concerning these notions.
general secure multi-party computation from any linear secret-sharing scheme. we show that verifiable secret sharing (vss) and secure multi-party computation (mpc) among a set of n players can efficiently be based on any linear secret sharing scheme (lsss) for the players, provided that the access structure of the lsss allows mpc or vss at all. because an lsss neither guarantees reconstructability when some shares are false, nor verifiability of a shared value, nor allows for the multiplication of shared values, an lsss is an apparently much weaker primitive than vss or mpc. our approach to secure mpc is generic and applies to both the information-theoretic and the cryptographic setting. the construction is based on 1) a formalization of the special multiplicative property of an lsss that is needed to perform a multiplication on shared values, 2) an efficient generic construction to obtain from any lsss a multiplicative lsss for the same access structure, and 3) an efficient generic construction to build verifiability into every lsss (always assuming that the adversary structure allows for mpc or vss at all). the protocols are efficient. in contrast to all previous information-theoretically secure protocols, the field size is not restricted (e.g, to be greater than n). moreover, we exhibit adversary structures for which our protocols are polynomial in n while all previous approaches to mpc for non-threshold adversaries provably have super-polynomial complexity.
an efficient public key cryptosystem secure against adaptive chosen ciphertext attack. this paper proposes a simple threshold public-key cryptosystem (pkc) which is secure against adaptive chosen ciphertext attack, under the decisional diffie-hellman (ddh) intractability assumption. previously, it was shown how to design non-interactive threshold pkc secure under chosen ciphertext attack, in the random-oracle model and under the ddh intractability assumption [25]. the random-oracle was used both in the proof of security and to eliminate interaction. general completeness results for multi-party computations [6,13] enable in principle converting any single server pkc secure against cca (e.g., [19,17]) into a threshold one, but the conversions are inefficient and require much interaction among the servers for each ciphertext decrypted. the recent work by cramer and shoup [17] on single server pkc secure against adaptive cca is the starting point for the new proposal.
a forward-secure public-key encryption scheme. cryptographic computations are often carried out on insecure devices for which the threat of key exposure represents a serious and realistic concern. in an effort to mitigate the damage caused by exposure of secret data (e.g., keys) stored on such devices, the paradigm of forward security was introduced. in a forward-secure scheme, secret keys are updated at regular periods of time; furthermore, exposure of a secret key corresponding to a given time period does not enable an adversary to "break" the scheme (in the appropriate sense) for any prior time period. a number of constructions of forward-secure digital signature schemes, key-exchange protocols, and symmetric-key schemes are known. we present the first constructions of a (non-interactive) forward-secure public-key encryption scheme. our main construction achieves security against chosen plaintext attacks under the decisional bilinear diffie-hellman assumption in the standard model. it is practical, and all complexity parameters grow at most logarithmically with the total number of time periods. the scheme can also be extended to achieve security against chosen ciphertext attacks.
efficient multi-party computation over rings. secure multi-party computation (mpc) is an active research area, and a wide range of literature can be found nowadays suggesting improvements and generalizations of existing protocols in various directions. however, all current techniques for secure mpc apply to functions that are represented by (boolean or arithmetic) circuits over finite fields. we are motivated by two limitations of these techniques: - generality. existing protocols do not apply to computation over more general algebraic structures (except via a brute-force simulation of computation in these structures). - efficiency. the best known constant-round protocols do not efficiently scale even to the case of large finite fields. our contribution goes in these two directions. first, we propose a basis for unconditionally secure mpc over an arbitrary finite ring, an algebraic object with a much less nice structure than a field, and obtain efficient mpc protocols requiring only a black-box access to the ring operations and to random ring elements. second, we extend these results to the constant-round setting, and suggest efficiency improvements that are relevant also for the important special case of fields. we demonstrate the usefulness of the above results by presenting a novel application of mpc over (non-field) rings to the round-efficient secure computation of the maximum function.
multi-autority secret-ballot elections with linear work. we present new cryptographic protocols for multiauthority secret ballot elections that guarantee privacy, robustness, and universal verifiability. application of some novel techniques, in particular the construction of witness hiding/indistinguishable protocols from cramer, damgård and schoenmakers, and the verifiable secret sharing scheme of pedersen, reduce the work required by the voter or an authority to a linear number of cryptographic operations in the population size (compared to quadratic in previous schemes). thus we get significantly closer to a practical election scheme.
a secure and optimally efficient multi-authority election scheme. in this paper we present a new multi-authority secret-ballot election scheme that guarantees privacy, universal verifiability, and robustness. it is the first scheme for which the performance is optimal in the sense that time and communication complexity is minimal both for the individual voters and the authorities. an interesting property of the scheme is that the time and communication complexity for the voter is independent of the number of authorities. a voter simply posts a single encrypted message accompanied by a compact proof that it contains a valid vote. our result is complementary to the result by cramer, franklin, schoenmakers, and yung in the sense that in their scheme the work for voters is linear in the number of authorities but can be instantiated to yield information-theoretic privacy, while in our scheme the voter's effort is independent of the number of authorities but always provides computational privacy-protection. we will also point out that the majority of proposed voting schemes provide computational privacy only (often without even considering the lack of information-theoretic privacy), and that our new scheme is by far superior to those schemes.
on the limitations of universally composable two-party computation without set-up assumptions. the recently proposed universally composable (uc) security framework, for analyzing security of cryptographic protocols, provides very strong security guarantees. in particular, a protocol proven secure in this framework is guaranteed to maintain its security even when deployed in arbitrary multi-party, multi-protocol, multi-execution environments. protocols for securely carrying out essentially any cryptographic task in a universally composable way exist, both in the case of an honest majority (in the plain model, i.e., without set-up assumptions) and in the case of no honest majority (in the common reference string model). however, in the plain model, little was known for the case of no honest majority and, in particular, for the important special case of two-party protocols. we study the feasibility of universally composable two-party function evaluation in the plain model. our results show that very few functions can be computed in this model so as to provide the uc security guarantees. specifically, for the case of deterministic functions, we provide a full characterization of the functions computable in this model. (essentially, these are the functions that depend on at most one of the parties' inputs, and furthermore are "efficiently invertible" in a sense defined within.) for the case of probabilistic functions, we show that the only functions computable in this model are those where one of the parties can essentially uniquely determine the joint output.
efficient communication-storage tradeoffs for multicast encryption. we consider re-keying protocols for secure multicasting in a dynamic multicast group with a center. there is a variety of different scenarios using multicast, presenting a wide range of efficiency requirements with respect to several parameters. we give an upper bound on the tradeoff between storage and communication parameters. in particular, we suggest an improvement of the schemes by wallner et al. and wong et al. [13,14] with sub-linear center storage, without a significant loss in other parameters. correctly selecting the parameters of our scheme we can efficiently accommodate a wide range of scenarios. this is demonstrated by applying the protocol to some known benchmark scenarios. we also show lower bounds on the tradeoff between communication and user storage, and show that our scheme is almost optimal with respect to these lower bounds.
efficient cryptographic protocols based on noisy channels. the wire-tap channel of wyner [19] shows that a binary symmetric channel may be used as a basis for exchanging a secret key, in a cryptographic scenario of two honest people facing an eavesdropper. later crépeau and kilian [9] showed how a bsc may be used to implement oblivious transfer in a cryptographic scenario of two possibly dishonest people facing each other. unfortunately this result is rather impractical as it requires ω(n11) bits to be transmitted through the bsc to accomplish a single ot. the current paper provides efficient protocols to achieve the cryptographic primitives of bit commitment and oblivious transfer based on the existence of a binary symmetric channel. our protocols respectively require sending o(n) and o(n3) bits through the bsc. these results are based on a technique known as generalized privacy amplification [1] that allow two people to extract secret information from partially compromised data.
propagation characteristics and correlation-immunity of highly nonlinear boolean functions. we investigate the link between the nonlinearity of a boolean function and its propagation characteristics. we prove that highly nonlinear functions usually have good propagation properties regarding different criteria. conversely, any boolean function satisfying the propagation criterion with respect to a linear subspace of codimension 1 or 2 has a high nonlinearity. we also point out that most highly nonlinear functions with a three-valued walsh spectrum can be transformed into 1-resilient functions.
improved fast correlation attacks using parity-check equations of weight 4 and 5. this paper describes new techniques for fast correlation attacks, based on gallager iterative decoding algorithm using parity-check equations of weight greater than 3. these attacks can be applied to any key-stream generator based on lfsrs and it does not require that the involved feedback polynomial have a low weight. we give a theoretical analysis of all fast correlation attacks, which shows that our algorithm with parity-check equations of weight 4 or 5 is usually much more efficient than correlation attacks based on convolutional codes or on turbo codes. simulation results confirm the validity of this comparison. in this context, we also point out the major role played by the nonlinearity of the boolean function used in a combination generator.
on the reversibility of oblivious transfer. a(2 1)-ot2, (one-out-of-two bit oblivious transfer) is a technique by which a party s owning two secret bits b0, b1, can transfer one of them bc, to another party r, who chooses c. this is done in a way that does not release any bias about bt to r nor any bias about c to s. how can one build a 2to-(2 1) ((2 1)-ot2 from r to s) given a (2 1)-ot2, (from s to r)? this question is interesting because in many scenarios, one of the two parties will be much more powerful than the other. in the current paper we answer this question and show a number of related extensions. one interesting extension of this transfer is the (2 1)-ot2k (one-out-of-two string o.t.) in which the two secrets q0, q1 are elements of gfk(2) instead of bits. we show that 2kto-(2 1) can be obtained at about the same cost as (2 1)-ot2k, in terms of number of calls to (2 1)-ot2.
quantum oblivious mutual identification. we consider a situation where two parties, alice and bob, share a common secret string and would like to mutually check their knowledge of that string. we describe a simple and efficient protocol based on the exchange of quantum information to check mutual knowledge of a common string in such a way that honest parties will always succeed in convincing each other, while a dishonest party interacting with an honest party will have vanishingly small probability of convincing him. moreover, a dishonest party gains only a very small amount of information about the secret string from running the protocol: whoever enters the protocol with no knowledge of the secret string would have to enter this protocol an exponential number of times in order to gain non-negligible information about the string. our scheme offers an efficient identification technique with a security that depends on no computational assumption, only on the correctness of quantum mechanics. we believe such a system should be used in smartcards to avoid frauds from typing pin codes to dishonest teller machines.
more correlation-immune and resilient functions over galois fields and galois rings. we show that the usual constructions of bent functions, when they are suitably modified, allow constructions of correlation-immune and resilient functions over galois fields and, in some cases, over galois rings.
recycling random bits in composed perfect zero-knowledge. in this paper we give techniques for recycling random bits both in the interactive and in the non-interactive model for perfect zero-knowledge proofs. our first result is a non-interactive perfect zero-knowledge proof system for proving that at least one out of any given polynomial number of statements is true, in which the amount of public random bits used is the same as that for proving a single statement. our second result is an interactive perfect zero-knowledge proof system for proving any given polynomial number of statements, in which the amount of private random bits used by the prover is, apart from a constant factor, the same as that for proving a single statement. in order to get a randomness-efficient proof system, we also reduce the random string of the verifier by using a multi-bit commitment scheme. the statements considered are of quadratic non residuosity modulo a blum integer.
computing inverses over a shared secret modulus. we discuss the following problem: given an integer φ shared secretly among n players and a prime number e, how can the players efficiently compute a sharing of e-1 mod φ. the most interesting case is when φ is the euler function of a known rsa modulus n, φ = φ(n). the problem has several applications, among which the construction of threshold variants for two recent signature schemes proposed by gennaro-halevi-rabin and cramer-shoup. we present new and efficient protocols to solve this problem, improving over previous solutions by boneh-franklin and frankel et al. our basic protocol (secure against honest but curious players) requires only two rounds of communication and a single gcd computation. the robust protocol (secure against malicious players) adds only a couple of rounds and a few modular exponentiations to the computation.
single database private information retrieval implies oblivious transfer. a single-database private information retrieval (pir) is a protocol that allows a user to privately retrieve from a database an entry with as small as possible communication complexity. we call a pir protocol non-trivial if its total communication is strictly less than the size of the database. non-trivial pir is an important cryptographic primitive with many applications. thus, understanding which assumptions are necessary for implementing such a primitive is an important task, although (so far) not a well-understood one. in this paper we show that any non-trivial pir implies oblivious transfer, a far better understood primitive. our result not only significantly clarifies our understanding of any non-trivial pir protocol, but also yields the following consequences: - any non-trivial pir is complete for all two-party and multiparty secure computations. - there exists a communication-efficient reduction from any pir protocol to a 1-out-of-n oblivious transfer protocol (also called spir). - there is strong evidence that the assumption of the existence of a one-way function is necessary but not sufficient for any non-trivial pir protocol.
differential cryptanalysis of the stream ciphers py, py6 and pypy. py and pypy are efficient array-based stream ciphers designed by biham and seberry. both were submitted to the estream competition. this paper shows that py and pypy are practically insecure. if one key is used with about 216 ivs with special differences, with high probability two identical keystreams will appear. this can be exploited in a key recovery attack. for example, for a 16-byte key and a 16-byte iv, 223 chosen ivs can reduce the effective key size to 3 bytes. for a 32-byte key and a 32-byte iv, the effective key size is reduced to 3 bytes with 224 chosen ivs. py6, a variant of py, is more vulnerable to these attacks.
conditional oblivious transfer and timed-release encryption. we consider the problem of sending messages "into the future." previous constructions for this task were either based on heuristic assumptions or did not provide anonymity to the sender of the message. in the public-key setting, we present an efficient and secure timed-release encryption scheme using a "time server" which inputs the current time into the system. the server has to only interact with the receiver and never learns the sender's identity. the scheme's computational and communicational cost per request are only logarithmic in the time parameter. the construction of our scheme is based on a novel cryptographic primitive: a variant of oblivious transfer which we call conditional oblivious transfer. we define this primitive (which may be of independent interest) and show an efficient construction for an instance of this new primitive based on the quadratic residuosity assumption.
anonymous nizk proofs of knowledge with preprocessing. in this extended abstract we present an unpublished result in [6] which extends a result in [4]. we give a non-interactive zero-knowledge proof system of knowledge with preprocessing, whose main property is that, after executing two preprocessing phases and given a transcript of a proof phase, the verifier is not able to relate the transcript to any of the two preprocessing phases significantly better than random guessing. the technique used has motivated the cash scheme in [3]. because of this result, only mentioned but used in [3], the main observation of pfitzmann et al. in [8] against the cash scheme in [3] doesn't hold. we also discuss the other observations of pfitzmann et al. in [8] against the cash schemes in [3, 5] and show that all of them don't hold. as a conclusion, the cash schemes in [3, 5] are not broken at all.
linear complexity of periodically repeated random sequences. on the linear complexity λ(z) of a periodically repeated random bit sequence z, r. rueppel proved that, for two extreme cases of the period t, the expected linear complexity e[λ(z)] is almost equal to t, and suggested that e[λ(z)] would be close to t in general [6, pp. 33- 52] [7, 8]. in this note we obtain bounds of e[λ(z)], as well as bounds of the variance var[λ(z)], both for the general case of t, and we estimate the probability distribution of λ(z). our results on e[λ(z)] quantify the closeness of e[λ(z)] and t, in particular, formally confirm r. rueppel's suggestion.
efficient concurrent zero-knowledge in the auxiliary string model. we show that if any one-way function exists, then 3-round concurrent zero-knowledge arguments for all np problems can be built in a model where a short auxiliary string with a prescribed distribution is available to the players. we also show that a wide range of known efficient proofs of knowledge using specialized assumptions can be modified to work in this model with no essential loss of efficiency. we argue that the assumptions of the model will be satisfied in many practical scenarios where public key cryptography is used, in particular our construction works given any secure public key infrastructure. finally, we point out that in a model with preprocessing (and no auxiliary string) proposed earlier, concurrent zero-knowledge for np can be based on any one-way function.
collision free hash functions and public key signature schemes. in this paper, we present a construction of hash functions. these functions are collision free in the sense that under some cryptographic assumption, it is provably hard for an enemy to find collisions. assumptions that would be sufficient are the hardness of factoring, of discrete log, or the (possibly) more general assumption about the existence of claw free sets of permutations. the ability of a hash function to improve security and speed of a signature scheme is discussed: for example, we can combine the rsa-system with a collision free hash function based on factoring to get a scheme which is more efficient and much more secure. also, the effect of combining the goldwasser-micali-rest signature scheme with one of our functions is studied. in the factoring based implementation of the scheme using a k-bit modulus, the signing process can be speeded up by a factor roughly equal to kċo (log2(k)), while the signature checking process will be faster by a factor of o (log2(k)).
non-interactive circuit based proofs and non-interactive perfect zero-knowledge with proprocessing. in the first part of this paper, we present a noninteractive zero-knowledge proof system for circuit satisfiability. with this protocol, we can prove an arbitrary np-statement non-interactively without using karp-reductions to 3-sat or graph hamiltonicity. the proof system is based on the quadratic residuosity problem and allows processing of xor and not gates at virtually no cost. it is significantly more efficient than previously known non-interactive proof systems. in the second part, we present protocols based on the existence of collision intractable hash functions, leading to a statistical zero-knowledge noninteractive argument with preprocessing for any np-statement. under the certified discrete log assumption, the protocol is perfect zero-knowledge. in the preprocessing, the parties need only exchange messages of length independent of the theorem to be proved later. this is the first protocol with such efficient preprocessing that does not need to assume oblivious transfer. finally we present a perfect zero-knowledge non-interactive protocol based on discrete logarithms that may potentially remove the need for preprocessing.
on the (im)possibility of basing oblivious transfer and bit commitment on weakened security assumptions. we consider the problem of basing oblivious transfer (ot) and bit commitment (bc), with information theoretic security, on seemingly weaker primitives.we introduce a general model for describing such primitives, called weak generic transfer (wgt). this model includes as important special cases weak oblivious transfer (wot), where both the sender and receiver may learn too much about the other party's input, and a new, more realistic model of noisy channels, called unfair noisy channels. an unfair noisy channel has a known range of possible noise levels; protocols must work for any level within this range against adversaries who know the actual noise level. we give a precise characterization for when one can base ot on wot. when the deviation of the wot from the ideal is above a certain threshold, we show that no information-theoretic reductions from ot (even against passive adversaries) and bc exist; when the deviation is below this threshold, we give a reduction from ot (and hence bc) that is information-theoretically secure against active adversaries. for unfair noisy channels we show a similar threshold phenomenon for bit commitment. if the upper bound on the noise is above a threshold (given as a function of the lower bound) then no information-theoretic reduction from ot (even against passive adversaries) or bc exist; when it is below this threshold we give a reduction from bc. as a partial result, we give a reduction from ot to unc for smaller noise intervals.
new convertible undeniable signature schemes. undeniable signatures are like ordinary digital signatures, except that testing validity of a signature requires interaction with the signer. this gives the signer additional control over who will benefit from being convinced by a signature, and is particularly relevant when signing sensitive, non-public data. convertible undeniable signatures offer additional flexibility in that there is a separate verification key that can be used to verify a signature (without interaction). this allows the signer to delegate the ability to verify signatures to one or more participants, and ultimately to convert all signatures to ordinary ones by making the verification key public. while provably secure theoretical solutions exist for convertible schemes, earlier practical schemes proposed have either been broken or their status as far as security is concerned is very unclear. in this paper, we present two new convertible schemes, in which forging signatures is provably equivalent to forging el gamal signatures. the difficulty of verifying signatures without interacting with the signer is based on the factoring problem for one of the schemes and on the diffie-hellman problem for the other scheme.
a public key analog cryptosystem. in this paper we present a public key cryptosystem based on error correcting codes [1, 7, 15]. the new public key system is obtained by extending the public key cryptosystem of mceliece [6, 12]. in this scheme a message m, consisting of a column vector of k elements from a finite field is first scrambled by multiplying it by a non singular matrix q to get m′ = q m this scrambled message has parity check variables added to it, by multiplying it by a generator matrix g and then has all the variables reordered by multipliation by a permutation matrix p. noise is then added to obtain the encrypted message c = p g q m + z the product of the three matrices g′ = p g q is made public, but the factors are not.
an expanded set of s-box design criteria based on information theory and its relation to differential-like attacks. the security of des-like cryptosystems depends heavily on the strength of the substitution boxes (s-boxes) used. the design of new s-boxes is therefore an important concern in the creation of new and more secure cryptosystems. the full set of design criteria for the s-boxes of des has never been released and a complete set has yet to be proposed in the open literature. this paper introduces a unified s-box design framework based on information theory and illustrates how it provides immunity to the differential attack.
how to break a practical mix and design a new one. a mix net takes a list of ciphertexts (c1; ... ; cn) and outputs a permuted list of the plaintexts (m1; ... ;mn) without revealing the relationship between (c1; ... ; cn) and (m1; ... ;mn). this paper first shows that the jakobsson's mix net of eurocrypt'98, which was believed to be resilient and very efficient, is broken. we next propose an efficient t-resilient mix net with o(t2) servers in which the cost of each mix server is o(n). two new concepts are introduced, existential-honesty and limited-open-verification. they will be useful for distributed computation in general.
esign: an efficient digital signature implementation for smard cards. esign is an efficient digital signature algorithm [oks, ok], whose computation speed is more than twenty times faster than that of the rsa scheme, while its key length and signature length are comparable to those of the rsa scheme. this paper presents a software implementation of esign on an 8bit micro-processor smart card. this realizes a computation time for signature generation of about 0.2 seconds. to achieve this remarkable speed for signature generation, appropriate implementation techniques such as pre-computation and table look-up techniques are effectively used. moreover, this software implementation is compact enough for smart cards; the program size and the data size including the work area are at most 3kbytes each. practical identification schemes based on esign are also presented.
interactive bi-proof systems and undeniable signature schemes. this paper proposes a new construction of the minimum knowledge undeniable signature scheme which solves a problem inherent in chaum's scheme. we formulate a new proof system, the minimum knowledge interactive bi-proof system, and a pair of languages, the common witness problem, based on the random self-reducible problem. and we show that any common witness problem has the minimum knowledge interactive bi-proof system. a practical construction for undeniable signature schemes is proposed based on such a proof system. these schemes assure signature confirmation and disavowal with the same protocol (or at the same time).
ideals over a non-commutative ring and thier applications in cryptology. a new modification of the mceliece public-key cryptosystem is proposed that employs the so-called maximum-rank-distance (mrd) codes in place of goppa codes and that hides the generator matrix of the mrd code by addition of a randomly-chosen matrix. a short review of the mathematical background required for the construction of mrd codes is given. the cryptanalytic work function for the modified mceliece system is shown to be much greater than that of the original system. extensions of the rank metric are also considered.
facts and myths of enigma: breaking stereotypes. in spite of a relatively large number of publications about breaking enigma by the allies before and during the world war ii, this subject remains relatively unknown not only to the general public, but also to people professionally involved in cryptological research. for example, the story of enigma is rarely a part of a modern textbook on cryptology or a modern course on cryptography and network security. there exist multiple reasons for this situation. first, there are still a few unresolved issues, resulting from conflicting reports, the lack of reliable sources, and a long period required for declassifying documents related to any cryptological activity during the world war ii. secondly, the issue is highly political, and there is little consensus in weighing the contribution of all involved countries. thirdly, many contemporary cryptologists honestly believe that there is little to learn from the analysis of old cryptosystems, because of the tremendous progress in theory and practice of cryptography and a little similarity between old and modern ciphers. in this paper we confront these opinions by presenting a look at the current state of knowledge about cryptological methods and devices used to break enigma. we introduce all major players involved in these activities, and we make an effort to weigh their original contributions. finally, we show that the story of enigma can still provide contemporary cryptographers with many useful lessons regarding the way of organizing and building any large-scale security system.
massively parallel elliptic curve factorin. we describe our massively parallel implementations of the elliptic curve factoring method. one of our implementations is based on a new systolic version of montgomery multiplication.
concealment and its applications to authenticated encryption. we introduce a new cryptographic primitive we call concealment, which is related, but quite different from the notion of commitment. a concealment is a publicly known randomized transformation, which, on input m, outputs a hider h and a binder b. together, h and b allow one to recover m, but separately, (1) the hider h reveals "no information" about m, while (2) the binder b can be "meaningfully opened" by at most one hider h. while setting b = m, h = φ is a trivial concealment, the challenge is to make |b| ≪ |m|, which we call a "non-trivial" concealment. we show that non-trivial concealments are equivalent to the existence of collision-resistant hash functions. moreover, our construction of concealments is extremely simple, optimal, and yet very general, giving rise to a multitude of efficient implementations. we show that concealments have natural and important applications in the area of authenticated encryption. specifically, let ae be an authenticated encryption scheme (either public- or symmetric-key) designed to work on short messages. we show that concealments are exactly the right abstraction allowing one to use ae for encrypting long messages. namely, to encrypt "long" m, one uses a concealment scheme to get h and b, and outputs authenticated ciphertext 〈ae(b),h〉. more surprisingly, the above paradigm leads to a very simple and general solution to the problem of remotely keyed (authenticated) encryption (rkae) [12,13]. in this problem, one wishes to split the task of high-bandwidth authenticated encryption between a secure, but low-bandwidth/computationally limited device, and an insecure, but computationally powerful host. we give formal definitions for rkae, which we believe are simpler and more natural than all the previous definitions. we then show that our composition paradigm satisfies our (very strong) definition. namely, for authenticated encryption, the host simply sends a short value b to the device (which stores the actual secret key for ae), gets back ae(b), and outputs 〈ae(b), h〉 (authenticated decryption is similar). finally, we also observe that the particular schemes of [13,17] are all special examples of our general paradigm.
strengthening zero-knowledge protocols using signatures. recently there has been an interest in zero-knowledge protocols with stronger properties, such as concurrency, unbounded simulation soundness, non-malleability, and universal composability. in this paper, we show a novel technique to convert a large class of existing honest-verifier zero-knowledge protocols into ones with these stronger properties in the common reference string model. more precisely, our technique utilizes a signature scheme existentially unforgeable against adaptive chosen-message attacks, and transforms any σ-protocol (which is honest-verifier zero-knowledge) into an unbounded simulation sound concurrent zero-knowledge protocol. we also introduce ω-protocols, a variant of σ-protocols for which our technique further achieves the properties of non-malleability and/or universal composability. in addition to its conceptual simplicity, a main advantage of this new technique over previous ones is that it avoids the cook-levin theorem, which tends to be rather inefficient. indeed, our technique allows for very efficient instantiation based on the security of some efficient signature schemes and standard number-theoretic assumptions. for instance, one instantiation of our technique yields a universally composable zero-knowledge protocol under the strong rsa assumption, incurring an overhead of a small constant number of exponentiations, plus the generation of two signatures.
an algorithm for solving the discrete log problem on hyperelliptic curves. we present an index-calculus algorithm for the computation of discrete logarithms in the jacobian of hyperelliptic curves defined over finite fields. the complexity predicts that it is faster than the rho method for genus greater than 4. to demonstrate the efficiency of our approach, we describe our breaking of a cryptosystem based on a curve of genus 6 recently proposed by koblitz.
lower bounds for oblivious transfer reductions. we prove the first general and non-trivial lower bound for the number of times a 1-out-of-n oblivious transfer of strings of length l should be invoked so as to obtain, by an information-theoretically secure reduction, a 1-out-of-n oblivious transfer of strings of length l. our bound is tight in many significant cases. we also prove the first non-trivial lower bound for the number of random bits needed to implement such a reduction whenever the receiver sends no messages to the sender. this bound is also tight in many significant cases.
secure multiround authentication protocols. gemmell and naor proposed a new protocol for unconditionally secure authentication of long messages. however gehrmann showed that the proof of the security of the protocol was incorrect. here we generalize the multiround protocol model. we prove the security of a 3-round protocol and give for this case a new easy implementable construction which has a key size close to the fundamental lower bound for even extremely long messages. furthermore, we give a proof of a secure multiround protocol for an arbitrary number of rounds.
secure hash-and-sign signatures without the random oracle. we present a new signature scheme which is existentially unforgeable under chosen message attacks, assuming some variant of the rsa conjecture. this scheme is not based on "signature trees", and instead it uses the so called "hash-and-sign" paradigm. it is unique in that the assumptions made on the cryptographic hash function in use are well defined and reasonable (although non-standard). in particular, we do not model this function as a random oracle. we construct our proof of security in steps. first we describe and prove a construction which operates in the random oracle model. then we show that the random oracle in this construction can be replaced by a hash function which satisfies some strong (but well defined!) computational assumptions. finally, we demonstrate that these assumptions are reasonable, by proving that a function satisfying them exists under standard intractability assumptions.
verifiable signature sharing. we introduce verifiable signature sharing (vσs), a cryptographic primitive for protecting digital signatures. vσs enables the holder of a digitally signed document, who may or may not be the original signer, to share the signature among a set of proxies so that the honest proxies can later reconstruct it. we present efficient vσs schemes for exponentiation based signatures (e.g., rsa, rabin) and discrete log based signatures (e.g., elgamal, schnorr, dsa) that can tolerate the malicious (byzantine) failure of the sharer and a constant fraction of the proxies. we also describe our implementation of these schemes and evaluate their performance. among the applications of vσs is the incorporation of digital cash into multiparty protocols, e.g., to enable cash escrow and secure distributed auctions.
on the security loss in cryptographic reductions. almost all the important cryptographic protocols we have today base their security on unproven assumptions, which all imply np $\ne$ p, and thus having unconditional proofs of their security seems far beyond our reach. one research effort then is to identify more basic primitives and prove the security of these protocols by reductions to the security of these primitives. however, in doing so, one often observes some security loss in the form that the security of the protocols is measured against weaker adversaries, e.g., adversaries with a smaller running time. is such a security loss avoidable? we study two of the most basic cryptographic reductions: hardness amplification of one-way functions and constructing pseudorandom generators from one-way functions. we show that when they are done in a certain black-box way, such a security loss is in fact unavoidable.
robust threshold dss signatures. we present threshold dss (digital signature standard) signatures where the power to sign is shared by n players such that for a given parameter t < n/2 any subset of 2t + 1 signers can collaborate to produce a valid dss signature on any given message, but no subset of t corrupted players can forge a signature (in particular, cannot learn the signature key). in addition, we present a robust threshold dss scheme that can also tolerate n/3 players who refuse to participate in the signature protocol. we can also endure n/4 maliciously faulty players that generate incorrect partial signatures at the time of signature computation. this results in a highly secure and resilient dss signature system applicable to the protection of the secret signature key, the prevention of forgery, and increased system availability. our results significantly improve over a recent result by langford from crypto'95 that presents threshold dss signatures which can stand much smaller subsets of corrupted players, namely, t ≅ √n, and do not enjoy the robustness property. as in thc case of langford's result, our schemes require no trusted party. our techniques apply to other threshold elgamal-like signatures as well. we prove the security of our schemes solely based on the hardness of forging a regular dss signature.
secure distributed key generation for discrete-log based cryptosystems. distributed key generation is a main component of threshold cryptosystems and distributed cryptographic computing in general. solutions to the distributed generation of private keys for discrete-log based cryptosystems have been known for several years and used in a variety of protocols and in many research papers. however, these solutions fail to provide the full security required and claimed by these works. we show how an active attacker controlling a small number of parties can bias the values of the generated keys, thus violating basic correctness and secrecy requirements of a key generation protocol. in particular, our attacks point out to the places where the proofs of security fail. based on these findings we designed a distributed key generation protocol which we present here together with a rigorous proof of security. our solution, that achieves optimal resiliency, can be used as a drop-in replacement for key generation modules as well as other components of threshold or proactive discrete-log based cryptosystems.
perfectly concealing quantum bit commitment from any quantum one-way permutation. we show that although unconditionally secure quantum bit commitment is impossible, it can be based upon any family of quantum one-way permutations. the resulting scheme is unconditionally concealing and computationally binding. unlike the classical reduction of naor, ostrovski, ventkatesen and young, our protocol is non-interactive and has communication complexity o(n) qubits for n a security parameter.
a framework for password-based authenticated key exchange. in this paper we present a general framework for passwordbased authenticated key exchange protocols, in the common reference string model. our protocol is actually an abstraction of the key exchange protocol of katz et al. and is based on the recently introduced notion of smooth projective hashing by cramer and shoup. we gain a number of benefits from this abstraction. first, we obtain a modular protocol that can be described using just three high-level cryptographic tools. this allows a simple and intuitive understanding of its security. second, our proof of security is significantly simpler and more modular. third, we are able to derive analogues to the katz et al. protocol under additional cryptographic assumptions. specifically, in addition to the ddh assumption used by katz et al., we obtain protocols under both the quadratic and n-residuosity assumptions. in order to achieve this, we construct new smooth projective hash functions.
verifiable secret sharing as secure computation. verifiable secret sharing is a fundamental primitive for secure cryptographic design. we present a stronger nation of verifiable secret sharing and exhibit a protocol implementing it. we show that our new notion is preferable to the old ones whenever verifiable secret sharing is used as a tool within larger protocols, rather than being a goal in itself. indeed our definition, and so our protocol satisfying it, provably guarantees reducibilty. applications of this new notion in the field of secure multiparty computation are also provided.
certificate-based encryption and the certificate revocation problem. we introduce the notion of certificate-based encryption. in this model, a certificate - or, more generally, a signature - acts not only as a certificate but also as a decryption key. to decrypt a message, a keyholder needs both its secret key and an up-to-date certificate from its ca (or a signature from an authorizer). certificate-based encryption combines the best aspects of identity-based encryption (implicit certification) and public key encryption (no escrow). we demonstrate how certificate-based encryption can be used to construct an efficient pki requiring less infrastructure than previous proposals, including micali's novomodo, naor-nissim and aiello-lodha-ostrovsky.
predicting the shrinking generator with fixed connections. we propose a novel distinguishing attack on the shrinking generator with known feedback polynomial for the generating lfsr. the attack can e.g. reliably distinguish a shrinking generator with a weight 4 polynomial of degree as large as 10000, using 232 output bits. as the feedback polynomial of an arbitrary lfsr is known to have a polynomial multiple of low weight, our distinguisher applies to arbitrary shrunken lfsr's of moderate length. the analysis can also be used to predict the distribution of blocks in the generated keystream.
equivalent goppa codes and trapdoors to mceliece's public key cryptosystem. we show that contrary to a published statement, any instance of mceliece's public key cryptosystem always has many trapdoors. our proof leads to a natural equivalence relation on monic polynomials over a finite field f such that any two irreducible goppa codes over f whose goppa polynomials are equivalent under this relation are equivalent as codes.
the security of the gabidulin public key cryptosystem. the gabidulin public key cryptosystem (pkc), like the well known mceliece pkc, is based on error correcting codes, and was introduced as an alternative to the mceliece system with the claim that much smaller codes could be used, resulting in a more practical system. in this paper an attack on the gabidulin pkc is given which breaks it for codes of the size envisaged, destroying much of its advantage over the mceliece system. the attack succeeds in polynomial time for gabidulin's choice of one of his system parameters, but it does show how to choose this parameter more appropriately. it consists of a reduction of the decryption problem for the gabidulin pkc to consideration of a search problem that is easier to describe, and which with luck should be easier to analyse. it therefore provides a possible starting point for a proof that decryption for the gabidulin pkc is an np-complete problem.
a note on the limits of collusion-resistant watermarks. in one proposed use of digital watermarks, the owner of a document d sells slightly different documents, d1;d2;,... to each buyer; if a buyer posts his/her document di to the web, the owner can identify the source of the leak. more general attacks are however possible in which k buyers create some composite document d*; the goal of the owner is to identify at least one of the conspirators. we show, for a reasonable model of digital watermarks, fundamental limits on their efficacy against collusive attacks. in particular, if the effective document length is n, then at most o(√n= ln n) adversaries can defeat any watermarking scheme. our attack is, in the theoretical model, oblivious to the watermarking scheme being used; in practice, it uses very little information about the watermarking scheme. thus, using a proprietary system seems to give only a very weak defense.
which new rsa signatures can be computed from rsa signatures, obtained in a specific interactive protocol? we consider cetain interactive protocols, based on rsa. in these protocols, a signature authority z (which chooses the rsa-modulus n that is kept fixed) issues a fixed number of rsa-signatures to an individual a. these rsa-signatures consist of products of rational powers of residue classes modulo n some of these residue classes are chosen by z and the others can be chosen freely by a thus, a can influence the form of the signatures that be gets from z. a wants to choose his residue classes in such a way that he can use the signatures he gets from z to compute a signature of a type not issued by z. in previous literature, some special cases of our protocols were considered. namely that only a chooses the residue classes ([dav82), [denn84], [do85]) and that only z chooses the residue classes [evh92]. the results in our paper are used under the following assumptiom: • a cannot compute rsa-roots on randomly chosen residue classes modulo n. • in his computations, a uses only multiplications and divisions modulo n. our main result gives a necessary and sufficient condition under which a is able to influence the signatures he gets from z in such a way that he can use these rsa-signatures to compute a signature of a type not issued by z. it turns out that this condition is equivalent to the solvability of a particular quadratic equation in integral matrices. we also study a particular case of this problem in more detail.
self-certified public keys. we introduce the notion, and give two examples, of self-certified public keys, i.e. public keys which need not be accompanied with a separate certificate to be authenticated by other users. the trick is that the public key is computed by both the authority and the user, so that the certificate is "embedded" in the public key itself, and therefore does not take the form of a separate value. self-certified public keys contribute to reduce the amount of storage and computations in public key schemes, while secret keys are still chosen by the user himself and remain unknown to the authority. this makes the difference with identity-based schemes, in which there are no more certificates at all, but at the cost that secret keys are computed (and therefore known to) the authority.
cryptanalysis of countermeasures proposed for repairing iso 9796-1. iso 9796-1, published in 1991, was the first standard specifying a digital signature scheme with message recovery. in [4], coron, naccache and stern described an attack on a slight modification of iso 9796- 1. then, coppersmith, halevi and jutla turned it into an attack against the standard in full [2]. they also proposed five countermeasures for repairing it. in this paper, we show that all these countermeasures can be attacked, either by using already existing techniques (including a very recent one), or by introducing new techniques, one of them based on the decomposition of an integer into sums of two squares.
selective forgery of rsa signatures using redundancy. we show the weakness of several rsa signature schemes using redundancy (i.e. completing the message to be signed with some additional bits which are fixed or message-dependent), by exhibiting chosen-message attacks based on the multiplicative property of rsa signature function. our attacks, which largely extend those of dejonge and chaum [djc], make extensive use of an affine variant of euclid's algorithm, due to okamoto and shiraishi [os]. when the redundancy consists of appending any fixed bits to the message m to be signed (more generally when redundancy takes the form of an affine function of m), then our attack is valid if the redundancy is less than half the length of the public modulus. when the redundancy consists in appending to m the remainder of m modulo some fixed value (or, more generally, any function of this remainder), our attack is valid if the redundancy is less than half the length of the public modulus minus the length of the remainder. we successfully apply our attack to a scheme proposed for discussion inside iso.
an efficient pseudo-random generator provably as secure as syndrome decoding. we show a simple and efficient construction of a pseudo-random generator based on the intractability of an np-complete problem from the area of error-correcting codes. the generalor is proved as secure as a hard instance of the syndrome decoding problem. each application of the scheme generates a linear amount of bits in only quadratic computing time.
incremental cryptography and memory checkers. we introduce the relationship between incremental cryptography and memory checkers. we present an incremental message authentication scheme based on the xor macs which supports insertion, deletion and other single block operations. our scheme takes only a constant number of pseudorandom function evaluations for each update step and produces smaller authentication codes than the tree scheme presented in [bgg95]. furthermore, it is secure against message substitution attacks, where the adversary is allowed to tamper messages before update steps, making it applicable to virus protection. from this scheme we derive memory checkers for data structures based on lists. conversely, we use a lower bound for memory checkers to show that so-called message substitution detecting schemes produce signatures or authentication codes with size proportional to the message length.
pseudorandom function tribe ensembles based on one-way permutations: improvements and applications. pseudorandom function tribe ensembles are pseudorandom function ensembles that have an additional collision resistance property: almost all functions have disjoint ranges.we present an alternative to the construction of pseudorandom function tribe ensembles based on oneway permutations given by canetti, micciancio and reingold [7]. our approach yields two different but related solutions: one construction is somewhat theoretic, but conceptually simple and therefore gives an easier proof that one-way permutations suffice to construct pseudorandom function tribe ensembles. the other, slightly more complicated solution provides a practical construction; it starts with an arbitrary pseudorandom function ensemble and assimilates the one-way permutation to this ensemble. therefore, the second solution inherits important characteristics of the underlying pseudorandom function ensemble: it is almost as efficient and if the starting pseudorandom function ensemble is invertible then so is the derived tribe ensemble. we also show that the latter solution yields so-called committing private-key encryption schemes. i.e., where each ciphertext corresponds to exactly one plaintext -- independently of the choice of the secret key or the random bits used in the encryption process.
stronger security proofs for rsa and rabin bits. the rsa and rabin encryption function are respectively defined as en(x) = xe mod n and en(x) = x2 mod n, where n is a product of two large random primes p, q and e is relatively prime to φv;(n). we present a much simpler and stronger proof of the result of alexi, chor, goldreich and schnorr [acgs88] that the following problems are equivalent by probabilistic polynomial time reductions: (1) given en(x) find x (2) given en(x) predict the least-significant bit of x with success probability 1/2 + 1/poly(n), where n has n bits. the new proof consists of a more efficient algorithm for inverhg the rsa/rabin-function with the help of an oracle that predicts the least-significant bit of x. it yields provable security guarantees for rsa-message bits and for the rsa-random number generator for moduli n of practical size.
a signature scheme as secure as the diffie-hellman problem. we show a signature scheme whose security is tightly related to the computational diffie-hellman (cdh) assumption in the random oracle model. existing discrete-log based signature schemes, such as elgamal, dss, and schnorr signatures, either require non-standard assumptions, or their security is only loosely related to the discrete logarithm (dl) assumption using pointcheval and stern's "forking" lemma. since the hardness of the cdh problem is widely believed to be closely related to the hardness of the dl problem, the signature scheme presented here offers better security guarantees than existing discrete-log based signature schemes. furthermore, the new scheme has comparable efficiency to existing schemes. the signature scheme was previously proposed in the cryptographic literature on at least two occasions. however, no security analysis was done, probably because the scheme was viewed as a slight modification of schnorr signatures. in particular, the scheme's tight security reduction to cdh has remained unnoticed until now. interestingly, this discrete-log based signature scheme is similar to the trapdoor permutation based pss signatures proposed by bellare and rogaway, and has a tight reduction for a similar reason.
two-threshold broadcast and detectable multi-party computation. classical distributed protocols like broadcast or multiparty computation provide security as long as the number of malicious players f is bounded by some given threshold t, i.e., f ≤ t. if f exceeds t then these protocols are completely insecure. we relax this binary concept to the notion of two-threshold security: such protocols guarantee full security as long as f ≤ t for some small threshold t, and still provide some degraded security when t < f ≤ t for a larger threshold t. in particular, we propose the following problems. • broadcast with extended validity: standard broadcast is achieved when f ≤ t. when t < f ≤ t, then either broadcast is achieved, or every player learns that there are too many faults. furthermore, when the sender is honest, then broadcast is always achieved. • broadcast with extended consistency: standard broadcast is achieved when f ≤ t. when t < f ≤ t, then either broadcast is achieved, or every player learns that there are too many faults. furthermore, the players agree on whether or not broadcast is achieved. • detectable multi-party computation: secure computation is achieved when f ≤ t. when t < f ≤ t, then either the computation is secure, or all players detect that there are too many faults and abort. the above protocols for n players exist if and only if t = 0 or t+2t < n.
the automated cryptoanalysis of analog speech scramblers. an automated method of attacking commonly used speech scramblers is presented. the cryptanalysis relies on the availability of the scrambled speech only and makes use of the characteristics of speech. it is shown that some of the currently available time and frequency domain scramblers, based on a fixed permutation. can be cryptanalysed. for systems where the permutation is changed with time, methods for partial recovery of the encrypted speech for several existing systems are given. in the case of the frequency domain scramblers a novel method of attack using a codebook is presented.
linear statistical weakness of alleged rc4 keystream generator. a keystream generator known as rc4 is analyzed by the linear model approach. it is shown that the second binary derivative of the least significant bit output sequence is correlated to 1 with the correlation coefficient close to 15ċ2-3n where n is the variable word size of rc4. the output sequence length required for the linear statistical weakness detection may be realistic in high speed applications if n ≤ 8. the result can be used to distinguish rc4 from other keystream generators and to determine the unknown parameter n, as well as for the plaintext uncertainty reduction if n is small.
cryptanalysis of alleged a5 stream cipher. a binary stream cipher, known as a5, consisting of three short lfsrs of total length 64 that are mutually clocked in the stop/go manner is cryptanalyzed. it is allegedly used in the gsm standard for digital cellular mobile telephones. very short keystream sequences are generated from different initial states obtained by combining a 64-bit secret session key and a known 22-bit public key. a basic divide-and-conquer attack recovering the unknown initial state from a known keystream sequence is first introduced. it exploits the specific clocking rule used and has average computational complexity around 240. a time-memory trade-off attack based on the birthday paradox which yields the unknown internal state at a known time for a known keystream sequence is then pointed out. the attack is successful if t ċ m ≥ 2633.32, where t and m are the required computational time and memory (in 128-bit words), respectively. the precomputation time is o(m) and the required number of known keystream sequences generated from different public keys is about t/102. for example, one can choose t ≅ 227.67 and m ≅ 235.65. to obtain the secret session key from the determined internal state, a so-called internal state reversion attack is proposed and analyzed by the theory of critical and subcritical branching processes.
on the security of rdsa. a variant of schnorr's signature scheme called rdsa has been proposed by i. biehl, j. buchmann, s. hamdy and a. meyer in order to be used in finite abelian groups of unknown order such as the class group of imaginary quadratic orders. we describe in this paper a total break of rdsa under a plain known-message attack for the parameters that were originally proposed. it recovers the secret signature key from the knowledge of less than 10 signatures of known messages, with a very low computational complexity. we also compare a repaired version of rdsa with gps scheme, another schnorr variant with similar properties and we show that gps should be preferred for most of the applications.
the number of output sequences of a binary sequence generator. in this paper, a number of output sequences is proposed as a characteristic of binary sequence generators for cryptographic applications. sufficient conditions for a variable-memory binary sequence generator to produce maximum possible number of output sequences are derived.
correlation via linear sequential circuit approximation of combiners with memory. correlation properties of a general binary combiner with an arbitrary number of memory bits are analyzed. it is shown that there exists a pair of certain linear functions of the output and input, respectively, that produce correlated binary sequences. an efficient procedure, based on a linear sequential circuit approximation, is developed for finding such pairs of linear functions. the result may be a basis for a divide and conquer correlation attack on a stream cipher generator consisting of several linear feedback shift registers combined by a combiner with memory.
towards fast correlation attacks on irregularly clocked shift registers. a theoretical framework for fast correlation attacks on irregularly clocked linear feedback shift registers (lfsrs) based on a recently established linear statistical weakness of decimated lfsr sequences is developed. when the lfsr feedback polynomial is not known, methods for the statistical weakness detection and the feedback polynomial reconstruction are proposed. when the lfsr feedback polynomial is known, an iterative procedure for fast lfsr initial state reconstruction given an observed keystream sequence is introduced. the procedure is based on appropriately defmed parity-check sums and consists in iterative recomputation of the posterior probabilities for unknown elements of the decimation sequence. a convergence condition in terms of the numbers of the parity-check sums needed for successful reconstruction and the required polynomial computational complexity indicate that the proposed fast correlation attack may be realistic, especially in the constrained clocking case. the number of the feedback polynomial multiples of relatively low weight and not too large degree thus proves to be critical for the security of irregularly clocked lfsrs.
fast low order approximation of cryptographic functions. a fast and efficient procedure for finding low order approximations to large boolean functions, if such approximations exist, is developed. the procedure uses iterative error-correction algorithms for fast correlation attacks on certain stream ciphers and is based on representing low order boolean functions by appropriate linear recurring sequences generated by binary filter generators. applications and significance of the proposed method in thc analysis and design of block and stream ciphers are also discussed.
a generalized correlation attack with a probabilistic constrained edit distance. for a noisy clock-controlled shift register statistically optimal probabilistic constrained edit distance a recursive algorithm for its efficient computation are derived. corresponding generalized correlation attack is proposed.
are big s-boxes best? various probabilities of accidental linearities occurring in a random, reversible substitution lookup table (s-box) with m address and m contents bits are calculated. these probabilities decrease very dramatically with increasing m. it is conjectured that good s-boxes may be built by choosing a random, reversible table of sufficient size.
the maximum order complexity of sequence ensembles. in this paper we extend the theory of maximum order complexity from a single sequence to an ensemble of sequences. in particular, the maximum order complexity of an ensemble of sequences is defined and its properties discussed. also, an algorithm is given to determine the maximum order complexity of an ensemble of sequences linear in time and memory. it is also shown how to determine the maximum order feedback shift register equivalent of a given ensmble of sequences, i.e. including a feedback function. hence, the problem of finding the absolutely shortest (possibly nonlinear) feedback shift register, that can generate two or more given sequences with characters from some arbitrary finite alphabet, is solved. finally, the consequences for sequence prediction based on the minimum number of observations are discussed.
adaptively secure threshold cryptography: introducing concurrency, removing erasures. we put forward two new measures of security for threshold schemes secure in the adaptive adversary model: security under concurrent composition; and security without the assumption of reliable erasure. using novel constructions and analytical tools, in both these settings, we exhibit efficient secure threshold protocols for a variety of cryptographic applications. in particular, based on the recent scheme by cramer-shoup, we construct adaptively secure threshold cryptosystems secure against adaptive chosen ciphertext attack under the ddh intractability assumption. our techniques are also applicable to other cryptosystems and signature schemes, like rsa, dss, and elgamal. our techniques include the first efficient implementation, for a wide but special class of protocols, of secure channels in erasure-free adaptive model. of independent interest, we present the notion of a committed proof.
a chosen messages attack on the iso/iec 9796-1 signature scheme. we introduce an attack against the iso/iec 9796-1 digital signature scheme using redundancy, taking advantage of the multiplicative property of the rsa and rabin cryptosystems. the forged signature of 1 message is obtained from the signature of 3 others for any public exponent v. for even v, the modulus is factored from the signature of 4 messages, or just 2 for v = 2. the attacker must select the above messages from a particular message subset, which size grows exponentialy with the public modulus bit size. the attack is computationally inexpensive, and works for any modulus of 16z, 16z ± 1, or 16z ± 2 bits. this prompts the need to revise iso/iec 9796-1, or avoid its use in situations where an adversary could obtain the signature of even a few mostly chosen messages.
bucket hashing with a small key size. in this paper we consider very fast evaluation of strongly universal hash functions, or equivalently, authentication codes. we show how it is possible to modify some known families of hash functions into a form such that the evaluation is similar to "bucket hashing", a technique for very fast hashing introduced by rogaway. rogaway's bucket, hash family has a huge key size, which for common parameter choices can be more than a hundred thousand bits. the proposed hash families have a key size that is close to the key size of the theoretically best known constructions, typically a few hundred bits, and the evaluation has a time complexity that is similar to bucket hashing.
improved fast correlation attacks on stream ciphers via convolutional codes. this paper describes new methods for fast correlation attacks, based on the theory of convolutional codes. they can be applied to arbitrary lfsr feedback polynomials, in opposite to the previous methods, which mainly focus on feedback polynomials of low weight. the results improve significantly the few previous results for this general case, and are in many cases comparable with corresponding results for low weight feedback polynomials.
alternating step generators controlled by de bruijn sequences. the alternating step generator (asg) is a new generator of pseudo-random sequences which is closely related t o the stop-and-go generator. it shares all the good properties of this latter generator without posessing its weaknesses. the asg consists of three subgenerators k, m, and m. the main characteristic of its structure is that the output of one of the subgenerators, k, controls the clock of the two others, m and m. in the present contribution, we determine the period, the distribution of short patterns and a lower bound for the linear complexity of the sequences generated by an asg. the proof of the lower bound is greatly simplified by assuming that k generates a de bruijn sequence. under this and other not very restrictive assumptions the period and the linear complexity are found to be proportional to the period of the de bruijn sequence. furthermore the frequency of all short patterns as well as the autocorrelations turn out to be ideal. this means that the sequences generated by the asg are provably secure against the standard attacks.
cryptanalysis of the emd mode of operation. in this paper, we study the security of the encrypt-mask-decrypt mode of operation, also called emd, which was recently proposed for applications such as disk-sector encryption. the emd mode transforms an ordinary block cipher operating on n-bit blocks into a tweakable block cipher operating on large blocks of size nm bits. we first show that emd is not a secure tweakable block cipher and then describe efficient attacks in the context of disk-sector encryption. we note that the parallelizable variant of emd, called eme that was proposed at the same time is also subject to these attacks. in the course of developing one of the attacks, we revisit wagner's generalized birthday algorithm and show that in some special cases it performs much more efficiently than in the general case. due to the large scope of applicability of this algorithm, even when restricted to these special cases, we believe that this result is of independent interest.
analysis of multiple access channel using multiple level fsk. for multiple level fsk system of multiple user communication a model is considered containing independent parallel noisy or channels. the error probability is calculated if a random block code and a majority type decoding rule is applied.
a secret key cryptosystem by iterating a chaotic map. chaos is introduced to cryptology. as an example of the applications, a secret key cryptosystem by iterating a one dimensional chaotic map is proposed. this system is based on the characteristics of chaos, which are sensitivity of parameters, sensitivity of initial points, and randomness of sequences obtained by iterating a chaotic map. a ciphertext is obtained by the iteration of a inverse chaotic map from an initial point, which denotes a plaintext. if the times of the iteration is large enough, the randomness of the encryption and the decryption function is so large that attackers cannot break this cryptosystem by statistic characteristics. in addition to the security of the statistical point, even if the cryptosystem is composed by a tent map, which is one of the simplest chaotic maps, setting a finite computation size avoids a ciphertext only attack. the most attractive point of the cryptosystem is that the cryptosystem is composed by only iterating a simple calculations though the information rate of the cryptosystem is about 0.5.
on the optimality of linear, differential, and sequential distinguishers. in this paper, we consider the statistical decision processes behind a linear and a differential cryptanalysis. by applying techniques and concepts of statistical hypothesis testing, we describe precisely the shape of optimal linear and differential distinguishers and we improve known results of vaudenay concerning their asymptotic behaviour. furthermore, we formalize the concept of "sequential distinguisher" and we illustrate potential applications of such tools in various statistical attacks.
comparing the mov and fr reductions in elliptic curve cryptography. this paper addresses the discrete logarithm problem in elliptic curve cryptography. in particular, we generalize the menezes, okamoto, and vanstone (mov) reduction so that it can be applied to some non-supersingular elliptic curves (ecs); decrypt frey and rück (fr)'s idea to describe the detail of the fr reduction and to implement it for actual elliptic curves with finite fields on a practical scale; and based on them compare the (extended) mov and fr reductions from an algorithmic point of view. (this paper has primarily an expository role.)
encryption modes with almost free message integrity. we define a new mode of operation for block ciphers which, in addition to providing confidentiality, also ensures message integrity. in contrast, previously for message integrity a separate pass was required to compute a cryptographic message authentication code (mac). the new mode of operation, called integrity aware parallelizable mode (iapm), requires a total of m+1 block cipher evaluations on a plain-text of length m blocks. for comparison, the well-known cbc (cipher block chaining) encryption mode requires m block cipher evaluations, and the second pass of computing the cbc-mac essentially requires additional m+1 block cipher evaluations. as the name suggests, the new mode is also highly parallelizable.
public-key cryptosystems with very small key length. in some applications of public-key cryptography it is desirable, and perhaps even necessary, that the key size be as small as possible. moreover, the cryptosystem just needs to be secure enough so that breaking it is not cost-effective. the purpose of this paper is to hivestigate the security and practicality of elliptic curve cryptosystems with small key sizes of about 100 bits.
a generalization of linear cryptanalysis and the applicability of matsui's piling-up lemma. matsui's linear cryptanalysis for iterated block ciphers is generalized by replacing his linear expressions with i/o sums. for a single round, an i/o sum is the xor of a balanced binary-valued function of the round input and a balanced binary-valued function of the round output. the basic attack is described and conditions for it to be successful are given. a procedure for finding effective i/o sums, i.e., i/o sums yielding successful attacks, is given. a cipher contrived to be secure against linear cryptanalysis but vulnerable to this generalization of linear cryptanalysis is given. finally, it is argued that the ciphers idea and safer k-64 are secure against this generalization.
nearly one-sided tests and the goldreich-levin predicate. we study statistical tests with binary output that rarely outputs one, which we call nearly one-sided statistical tests. we provide an efficient reduction establishing improved security for the goldreich-levin hard-core bit against nearly one-sided tests. the analysis is extended to prove the security of the blum-micali pseudo-random generator combined with the goldreich-levin bit. furthermore, applications where nearly one-sided tests naturally occur are discussed. this includes cryptographic constructions that replace real randomness with pseudo-randomness and where the adversary's success easily can be verified. in particular, this applies to signature schemes that utilize a pseudo-random generator as a provider of randomness.
efficient and non-malleable proofs of plaintext knowledge and applications. we describe efficient protocols for non-malleable (interactive) proofs of plaintext knowledge for the rsa, rabin, paillier, and el gamal encryption schemes. we also highlight some important applications of these protocols: - chosen-ciphertext-secure, interactive encryption. in settings where both parties are on-line, an interactive encryption protocol may be used. we construct chosen-ciphertext-secure interactive encryption schemes based on any of the schemes above. in each case, the improved scheme requires only a small overhead beyond the original, semantically-secure scheme. - password-based authenticated key exchange. we derive efficient protocols for password-based key exchange in the public-key model [28, 5] whose security may be based on any of the cryptosystems mentioned above. - deniable authentication. our techniques give the first efficient constructions of deniable authentication protocols based on, e.g., the rsa or computational diffie-hellman assumption. of independent interest, we consider the concurrent composition of proofs of knowledge; this is essential to prove security of our protocols when run in an asynchronous, concurrent environment.
xor and non-xor differential probabilities. differential cryptanalysis is a well-known attack on iterated ciphers whose success is determined by the probability of predicting sequences of differences from one round of the cipher to the next. the notion of difference is typically defined with respect to the group operation (s) used to combine the subkey in the round function f. for a given round operation π of f, such as an s-box, let dp⊗(π) denote the probability of the most likely non-trivial difference for π when differences are defined with respect to ⊗. in this paper we investigate how the distribution of dp⊗(π) varies as the group operation ⊗ is varied when π is a uniformly selected permutation. we prove that dp⊗(π) is maximised with high probability when differences are defined with respect to xor.
round efficiency of multi-party computation with a dishonest majority. we consider the round complexity of multi-party computation in the presence of a static adversary who controls a majority of the parties. here, n players wish to securely compute some functionality and up to n - 1 of these players may be arbitrarily malicious. previous protocols for this setting (when a broadcast channel is available) require o(n) rounds. we present two protocols with improved round complexity: the first assumes only the existence of trapdoor permutations and dense cryptosystems, and achieves round complexity o(log n) based on a proof scheduling technique of chor and rabin [13]; the second requires a stronger hardness assumption (along with the non-black-box techniques of barak [2]) and achieves o(1) round complexity.
secure audio teleconferencing: a practical solution. secure audio teleconferencing is a multi-point communication service which uses encryption to prevent eavesdroppers from listening to the speech signals. its greatest vulnerability is the audio bridge - that component which combines the conferees' speech signals and returns the result to them. a new secure teleconferencing system is proposed here. it fits the public telephone network by eliminating the need for the conferees to share their secrete with the bridge. it combines a simplified ('instantaneous') bridging technique with secure bridging ideas previously suggested in the literature, overcoming their main practical disadvantages. in particular, it is not restricting the audio signals to be coded by linear pcm, a technique which is wasteful in terms of bit-rate. rather, it enables the use of conventional µ-law and a-law pcm, as well as vector quantized pcm, thus can be used with a conventional 64kb/s digital channel.
a note on discrete logorithms with special structure. many cryptographic systems assume the computational difficulty of the discrete logarithm (dl) problem. in order to accelerate such practical systems, it was proposed to use logarithms of special structure, such as small hamming weight. how difficult is the underlying restricted dl problem? by rephrasing shanks' method we provide a close to square-root algorithm for such problems.
on using prime polynomials in crypto generators. in this note a primality test for polynomials over a finite field is analyzed. it is particularly well suited to achieve fast computations in the binary case. lots of prime polynomials which do not have to possess the maximum length property can be easily accessed by means of the best. examples of binary polynomials generated through the use of the test are given for degrees from 35 up to 55. the computational requirements are compared with a related test for maximum length and also with some common factorization procedures. as main application the use of prime polynomials in certain crypto geenrators is considered. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
cox-rower architecture for fast parallel montgomery multiplication. this paper proposes a fast parallel montgomery multiplication algorithm based on residue number systems (rns). it is easy to construct a fast modular exponentiation by applying the algorithm repeatedly. to realize an efficient rns montgomery multiplication, the main contribution of this paper is to provide a new rns base extension algorithm. cox-rower architecture described in this paper is a hardware suitable for the rns montgomery multiplication. in this architecture, a base extension algorithm is executed in parallel by plural rower units controlled by a cox unit. each rower unit is a single-precision modular multiplier-and-accumulator, whereas cox unit is typically a 7 bit adder. although the main body of the algorithm processes numbers in an rns form, efficient procedures to transform rns to or from a radix representation are also provided. the exponentiation algorithm can, thus, be adapted to an existing standard radix interface of rsa cryptosystem.
the ghs attack revisited. we generalize the weil descent construction of the ghs attack to arbitrary artin-schreier extensions. we give a formula for the characteristic polynomial of frobenius of the obtained curves and prove that the large cyclic factor of the input elliptic curve is not contained in the kernel of the composition of the conorm and norm maps. as an application we almost square the number of elliptic curves which succumb to the basic ghs attack, thereby weakening curves over f2155 further. we also discuss other possible extensions or variations of the ghs attack and conclude that they are not likely to yield further improvements.
how to make efficient fail-stop signatures. fail-stop signatures (introduced in [wp89]) have the very nice property that the signer is secure against unlimited powerful forgers. however, the known fail-stap signatures require very long keys, and they are quite inefficient, because messages are signed bit-wise. this paper presents a fail-stop signature scheme, in which signing a message block requires two modular multiplications and verification requires less than two modular exponentiations. furthermore a construction is shown of an undeniable signature scheme, which is unconditionally secure for the signer, and which allows the signer to convert undeniable signatures into fail-stop signatures. this is the first published undeniable signature having this property.
efficient receipt-free voting based on homomorphic encryption. voting schemes that provide receipt-freeness prevent voters from proving their cast vote, and hence thwart vote-buying and coercion. we analyze the security of the multi-authority voting protocol of benaloh and tuinstra and demonstrate that this protocol is not receiptfree, opposed to what was claimed in the paper and was believed before. furthermore, we propose the first practicable receipt-free voting scheme. its only physical assumption is the existence of secret one-way communication channels from the authorities to the voters, and due to the public verifiability of the tally, voters only join a single stage of the protocol, realizing the "vote-and-go" concept. the protocol combines the advantages of the receipt-free protocol of sako and kilian and of the very efficient protocol of cramer, gennaro, and schoenmakers, with help of designated-verifier proofs of jakobsson, sako, and impagliazzo. compared to the receipt-free protocol of sako and kilian for security parameter l (the number of repetitions in the non-interactive cut-andchoose proofs), the protocol described in this paper realizes an improvement of the total bit complexity by a factor l.
new modular multiplication algorithms for fast modular exponentiation. a modular exponentiation is one of the most important operations in public-key cryptography. however, it takes much time because the modular exponentiation deals with very large operands as 512-bit integers. the modular exponentiation is composed of repetition of modular multiplications. therefore, we can rcducc the execution time of it by reducing thc execution time of each modular multiplication. in this paper, we propose two fast modular multiplication algorithms. one is for modular multiplications between different integers, and the other is for modular squarings. these proposed algorithms require single-precision multiplications fewer than those of montgomery modular multiplication algorithms by 1/2 and 1/3 times, respectively. implementing on pc, proposed algorithms reduce execution times by 50% and 30% compared with montgomery algorithms, respectively.
extracting group signatures from traitor tracing schemes. digital signatures emerge naturally from public-key encryption based on trapdoor permutations, and the "duality" of the two primitives was noted as early as diffie-hellman's seminal work. the present work is centered around the crucial observation that two well known cryptographic primitives whose connection has not been noticed so far in the literature enjoy an analogous "duality." the primitives are group signature schemes and public-key traitor tracing. based on the observed "duality," we introduce new design methodologies for group signatures that convert a traitor tracing scheme into its "dual" group signature scheme. our first methodology applies to generic public-key traitor tracing schemes. we demonstrate its power by applying it to the boneh-franklin scheme, and obtaining its "dual" group signature. this scheme is the first provably secure group signature scheme whose signature size is not proportional to the size of the group and is based only on ddh and a random oracle. the existence of such schemes was open. our second methodology introduces a generic way of turning any group signature scheme with signature size linear in the group size into a group signature scheme with only logarithmic dependency on the group size. to this end it employs the notion of traceability codes (a central component of combinatorial traitor tracing schemes already used in the first such scheme by chor, fiat and naor). we note that our signatures, obtained by generic transformations, are proportional to a bound on the anticipated maximum malicious coalition size. without the random oracle assumption our schemes give rise to provably secure and efficient identity escrow schemes.
unbalanced oil and vinegar signature schemes. in [16], j. patarin designed a new scheme, called "oil and vinegar", for computing asymmetric signatures. it is very simple, can be computed very fast (both in secret and public key) and requires very little ram in smartcard implementations. the idea consists in hiding quadratic equations in n unknowns called "oil" and v = n unknowns called "vinegar" over a finite field k, with linear secret functions. this original scheme was broken in [10] by a. kipnis and a. shamir. in this paper, we study some very simple variations of the original scheme where v > n (instead of v = n). these schemes are called "unbalanced oil and vinegar" (uov), since we have more "vinegar" unknowns than "oil" unknowns. we show that, when v ≃ n, the attack of [10] can be extended, but when v ≥ 2n for example, the security of the scheme is still an open problem. moreover, when v ≃ n2/2, the security of the scheme is exactly equivalent (if we accept a very natural but not proved property) to the problem of solving a random set of n quadratic equations in n2/2 unknowns (with no trapdoor). however, we show that (in characteristic 2) when v ≥ n2, finding a solution is generally easy. then we will see that it is very easy to combine the oil and vinegar idea and the hfe schemes of [14]. the resulting scheme, called hfev, looks at the present also very interesting both from a practical and theoretical point of view. the length of a uov signature can be as short as 192 bits and for hfev it can be as short as 80 bits.
discrete logarithm based protocols. the exponential security system (tess) developed at the european institute for system security is the result of an attempt to increase the security in heterogenous computer networks. in this paper we present the cryptographic protocols in the kernel of tess. we show how they can be used to implement access control, authentication, confidentiality protection, key exchange, digital signatures and distributed network security management. we also look at the compatibility of tess with existing standards, like the x.509 directory authentication framework, and compare it to established systems like kerberos. a comparison of tess with the non-electronic "paper"-world of authentication and data exchange shows strong parallels. finally we give a short overview of the current state of development and availability of different tess components.
large periods nearly de bruijn fcsr sequences. recently, a new class of feedback shift registers (fcsrs) was introduced, based on algebra over the 2-adic numbers. the sequences generated by these registers have many algebraic properties similar to those generated by linear feedback shift registers. however, it appears to be significantly more difficult to find maximal period fcsr sequences. in this paper we exhibit a technique for easily finding fcsrs that generate nearly maximal period sequences. we further show that these sequence have excellent distributional properties. they are balanced, and nearly have the debruijn property for distributions of subsequences.
some considerations concerning the selection of rsa moduli. in this contribution two conditions are stated which safe rsa moduli n = pċq must fulfill. otherwise the factors of n can be found. first we consider the cycle-lengths of the recursion c ← cφv;(n)-1 +1 mod n which leads to a condition in terms of fibonacci numbers. the second condition involves a property of euler's function. we introduce a number-theoretic distance measure - the power-of-two distance (ptd) - which may be useful for evaluating the security of rsa moduli against 'number-theoretic integration'. the ptd of an rsa prime p must not be too small.
cryptanalysis of an identification scheme based on the permuted perceptron problem. this paper describes an attack on an identification scheme based on the permuted perceptron problem (ppp) as suggested by point-cheval. the attack finds the secret key, a vector of n binary elements, in time much faster than estimated by its designer. the basic idea in the attack is to use several applications of a simulated annealing algorithm and combine the outcomes into an improved search. it is left as an open problem to what extent the methods developed in this paper are useful also in other combinatorial problems.
a new algorithm for the solution of the knapsack problem. a new algorithm for the solution of the knapsack problem is described. the algorithm is based upon successive reductions modulo suitably chosen integers. thus the original knapsack problem is transformed into a system of modified knapsack problems. very often a partial solution to the system can be found. the system and the original knapsack can then be reduced to a lower dimensionality and the algorithm repeated. so far we have not been able to characterize the class of knapsack problems for which the algorithm is effective. there are indications, however, that most knapsack problems for which we know that there is one and only one solution may be solved fast by the use of the new algorithm.
on the difficulty of software key escrow. at eurocrypt'95, desmedt suggested a scheme which allows individuals to encrypt in such a way that the receiver can be traced by an authority having additional information. this paper shows that the proposed scheme does not have the required properties, by devising three non-specified protocols misleading the authority. we also discuss how to repair desmedt's scheme, such that our attacks are no longer possible. however, by allowing slightly more general, but absolutely realistic attacks also this improved system can be broken. in fact, we argue that software key escrow as proposed by desmedt will be very hard to implement as it requires that the distributed public key can only be used in few, well-defincd systems. furthermore, even if this is achieved, most applications to key distribution can be broken.
non-linear approximations in linear cryptoanalysis. by considering the role of non-linear approximatioris in linear cryptanalysis we obtain a generalization of matsui's linear cryptanalytic techniques. this approach allows ihe cryptanalyst greater flexibility in mounting a linear cryptanalytic attack and we demonstrate the effectiveness of our non-linear techniques with some simple attacks on lok191. these attacks potentially allow for the recovery of seven additional bits of key information with less than 1/4 of the plaintext that is required using current linear cryptanalytic methods.
cryptoanalysis of mceliece's public-key cryptosystem. an approach is proposed for the cryptanalysis of the well-known version of mceliece's public-key cryptosystem that is based on a new iterative optimization algorithm for decoding an arbitrary linear code. the algorithm provides guaranteed correction of all error patterns with hamming weight less than d/2, where d is the minimum distance of the code, and has time complexity about o(n3) where n is the block length. the approach is illustrated by the cryptanalysis of mceliece's system when a (63, 36) binary code with d = 11 is the underlying linear code.
fast elliptic curve algorithm combining frobenius map and table reference to adapt to higher characteristic. a new elliptic curve scalar multiplication algorithm is proposed. the algorithm offers about twice the troughput of some conventional oef-base algorithms because it combines the frobenius map with the table reference method based on base-φ expansion. furthermore, since this algorithm suits conventional computational units such as 16, 32 and 64 bits, its base field fpm is expected to enhance elliptic curve operation efficiency more than fq (q is a prime) or f2n.
high-speed implementation methods for rsa scheme. this paper proposes two novel implementation methods for the rsa cryptographic scheme. (1) the most efficient rsa implementation known to the present authors. this implementation achieves 50 kbps at about 25 kgates for a 512-bit exponent e and a 512-bit modulus n. thus the efficiency is 2.0 bps/gate. (2) a systolic architecture useful for high-speed and efficient and flexible chip implementation of the rsa scheme.
secure conference key distribution schemes for conspiracy attack. at the eurocrypt'88 meeting, we proposed three identity-based conference key distribution schemes. at the asiacrypt'91 meeting, shimbo and kawamura presented a conspiracy attacking method which worked against our schemes to disclose a user's secret information. this paper proposes an improved identity-based conference key distribution scheme to counter this attack.
ripping coins for a fair exchange. a fair exchange of payments for goods and services is a barter where one of the parties cannot obtain the item desired without handing over the item he offered. we introduce the concept of ripping digital coins to solve fairness problems in payment transactions. we demonstrate how to implement coin ripping for a recently proposed payment scheme [9, 8], giving a practical and transparent coin ripping scheme. we then give a general solution that can be used in any payment scheme with a challenge. we also indicate how fairness can be obtained by building a contract into the coin.
new hash functions for message authentication. we show that toeplitz matrices generated by sequences drawn from small biased distributions provide hashing schemes applicable to secure message authentication. this work extends our previous results from crypto'94 [4] where an authentication scheme based on toeplitz matrices generated by linear feedback shift registers was presented. our new results have as special case the lfsr-based construction but extend to a much wider and general family of sequences, including several simple and efficient constructions with close to optimal security. examples of the new constructions include toeplitz matrices generated by the legendre symbols of consecutive integers modulo a prime (of size significantly shorter than required by public-key modular arithmetic) as well as other algebraic constructions. the interest of these schemes extends beyond the proposed cryptographic applications to other uses of universal hashing (including other cryptographic applications).
designated verifier proofs and their applications. for many proofs of knowledge it is important that only the verifier designated by the confirmer can obtain any conviction of the correctness of the proof. a good example of such a situation is for undeniable signatures, where the confirmer of a signature wants to make sure that only the intended verifier(s) in fact can be convinced about the validity or invalidity of the signature. generally, authentication of messages and off-the-record messages are in conflict with each other. we show how, using designation of verifiers, these notions can be combined, allowing authenticated but private conversations to take place. our solution guarantees that only the specified verifier can be convinced by t,he proof, even if he shares all his secret information with entities that want to get convinced. our solution is based on trap-door conim.itments [4], allowing the designated verifier to open up commitments in any way he wants. we demonstrate how a trap-door commitment scheme can be uscd to construct designated verifier proofs, both interactive and non-interactive. we examplify the verifier designation method for the confirmation protocol for undeniable signatures.
distributed "magic ink" signatures. the physical analog of "blind signatures" of chaum is a document and a carbon paper put into an envelope, allowing the signer to transfer his signature onto the document by signing on the envelope, and without opening it. only the receiver can present the signed document while the signer cannot "unblind" its signature and get the document signed. when an authority signs "access tokens", "electronic coins", "credentials" or "passports", it makes sense to assume that whereas the users can typically enjoy the disassociation of the blindly signed token and the token itself (i.e. anonymity and privacy), there may be cases which require "unblinding" of a signature by the signing authority itself (to establish what is known as "audit trail" and to "revoke anonymity" in case of criminal activity). this leads us to consider a new notion of signature with the following physical parallel: the signer places a piece of paper with a carbon paper on top in an envelope as before (but the document on the paper is not yet written). the receiver then writes the document on the envelope using magic ink, e.g., ink that is only visible after being "developed". due to the carbon copy, this results in the document being written in visible ink on the internal paper. then, the signer signs the envelope (so its signature on the document is made available). the receiver gets the internal paper and the signer retains the envelope with the magic ink copy. should the signer need to unblind the document, he can develop the magic ink and get the document copy on the envelope. note that the signing is not blinded forever to the signer. we call this new type of signature a magic ink signature. we present an efficient method for distributively generating magic ink signatures, requiring a quorum of servers to produce a signature and a (possibly different) quorum to unblind a signature. the scheme is robust, and the unblinding is guaranteed to work even if a set of up to a threshold of signers refuses to cooperate, or actively cheats during either the signing or the unblinding protocol. we base our specific implementation on the dss algorithm. our construction demonstrates the extended power of distributed signing.
almost k-wise independent sample spaces and their cryptologic applications. an almost k-wise independent sample space is a small subset of m bit sequences in which any k bits are "almost independent". we show that this idea has close relationships with useful cryptologic notions such as multiple authentication codes (multiple a-codes), almost strongly universal hash families and almost k-resilient functions. we use almost k-wise independent sample spaces to construct new efficient multiple a-codes such that the number of key bits grows linearly as a function of k (here k is the number of messages to be authenticated with a single key). this improves on the construction of atici and stinson [2], in which the number of key bits is ω(k2). we also introduce the concept of ɛ-almost k-resilient functions and give a construction that has parameters superior to k-resilient functions. finally, new bounds (necessary conditions) are derived for almost k-wise independent sample spaces, multiple a-codes and balanced ɛ-almost k- resilient functions.
combinatorial bounds for authentication codes with arbitration. unconditionally secure authentication codes with arbitration (a2-codes) protect against deceptions from the transmitter and the receiver as well as that from the opponent. in this paper, we present combinatorial lower bounds on the cheating probabilities for a2-codes in terms of the number of source states, that of the whole messages and that of messages which the receiver accepts as authentic for each source state. previously, only entropy based lower bounds were known. our bounds for the model without secrecy are tight because the a2-codes given by johansson meet our bounds with equality.
design of sac/pc(l) of order k boolean functions and three other cryptographic criteria. a boolean function f satisfies pc(l) of order k if f(x) ⊕ f(x ⊕ α)is balanced for any α such that 1 ≤ w(α) ≤ l even if any k input bits are kept constant, where w(α) denotes the hamming weight of α. this paper shows the first design method of such functions which provides deg(f) ≥ 3. more than that, we show how to design "balanced' such functions. high nonlinearity and large degree are also obtained. further, we present balanced sac(k) functions which achieve the maximum degree. finally, we extend our technique to vector output boolean functions.
one-way trapdoor permutations are sufficient for non-trivial single-server private information retrieval. we show that general one-way trapdoor permutations are sufficient to privately retrieve an entry from a database of size n with total communication complexity strictly less than n. more specifically, we present a protocol in which the user sends o(k2) bits and the server sends n - cn/k bits (for any constant c), where k is the security parameter of the trapdoor permutations. thus, for sufficiently large databases (e.g., when k = nɛ for some small ɛ) our construction breaks the information-theoretic lower-bound (of at least n bits). this demonstrates the feasibility of basing single-server private information retrieval on general complexity assumptions. an important implication of our result is that we can implement a 1-out-of- n oblivious transfer protocol with communication complexity strictly less than n based on any one-way trapdoor permutation.
dealing necessary and sufficient numbers of cards for sharing a one-bit secret key. using a random deal of cards to players and a computationally unlimited eavesdropper, all players wish to share a one-bit secret key which is information-theoretically secure from the eavesdropper. this can be done by a protocol to make several pairs of players share one-bit secret keys so that all these pairs form a spanning tree over players. in this paper we obtain a necessary and sufficient condition on the number of cards for the existence of such a protocol. our condition immediately yields an efficient linear-time algorithm to determine whether there exists a protocol to achieve such a secret key sharing.
hash function based on block ciphers. iterated hash functions based on block ciphers are treated. five attacks on an iterated hash function and on its round function are formulated. the wisdom of strengthening such hash functions by constraining the last block of the message to be hashed is stressed. schemes for constructing m-bit and 2m-bit hash round functions from m-bit block ciphers are studied. a principle is formalized for evaluating the strength of hash round functions, viz., that applying computationally simple (in both directions) invertible transformations to the input and output of a hash round function yields a new hash round function with the same security. by applying this principle, four attacks on three previously proposed 2m-bit hash round functions are formulated. finally, three new hash round functions based on an m-bit block cipher with a 2m-bit key are proposed.
a block lanczos algorithm for finding dependencies over gf(2). some integer factorization algorithms require several vectors in the null space of a sparse m × n matrix over the field gf(2). we modify the lanczos algorithm to produce a sequence of orthogonal subspaces of gf(2)n, each having dimension almost n, where n is the computer word size, by applying the given matrix and its transpose to n binary vectors at once. the resulting algorithm takes about n/(n - 0.76) iterations. it was applied to matrices larger than 106 × 106 during the factorizations of 105-digit and 119-digit numbers via the general number field sieve.
cryptanalysis of the public-key encryption based on braid groups. at crypto 2000, a new public-key encryption based on braid groups was introduced. this paper demonstrates how to solve its underlying problem using the burau representation. by this method, we show that the private-key can be recovered from the public-key for several parameters with significant probability in a reasonable time. our attack can be mounted directly on the revised scheme mentioned at asiacrypt 2001 as well. on the other hand, we give a new requirement for secure parameters against our attack, which more or less conflicts with that against brute force attack.
analysis and optimization of the twinkle factoring device. we describe an enhanced version of the twinkle factoring device and analyse to what extent it can be expected to speed up the sieving step of the quadratic sieve and number field sieve factoring algorithms. the bottom line of our analysis is that the twinkle-assisted factorization of 768-bit numbers is difficult but doable in about 9 months (including the sieving and matrix parts) by a large organization which can use 80,000 standard pentium ii pc's and 5,000 twinkle devices.
counting points on elliptic curves over finite fields of small characteristic in quasi quadratic time. let p be a small prime and q = pn. let e be an elliptic curve over fq. we propose an algorithm which computes without any preprocessing the j-invariant of the canonical lift of e with the cost of o(log n) times the cost needed to compute a power of the lift of the frobenius. let µ be a constant so that the product of two n-bit length integers can be carried out in o(nµ) bit operations, this yields an algorithm to compute the number of points on elliptic curves which reaches, at the expense of a o(n5/2) space complexity, a theoretical time complexity bound equal to o(nmax(1.19,µ)+µ+1/2log n). when the field has got a gaussian normal basis of small type, we obtain furthermore an algorithm with o(log(n)n2µ) time and o(n2) space complexities. from a practical viewpoint, the corresponding algorithm is particularly well suited for implementations. we outline this by a 100002-bit computation.
counting the number of points on elliptic curves over finite fields: strategies and performance. cryptographic schemes using elliptic curves over finite fields require the computation of the cardinality of the curves. dramatic progress have been achieved recently in that field by various authors. the aim of this article is to highlight part of these improvements and to describe an efficient implementation of them in the particular case of the fields gf(2n), for n ≤ 600.
dickson pseudoprimes and primality testing. the paper gives a general definition for the concept of strong dickson pseudoprimes which contains as special cases the carmichael numbers and the strong fibonacci pseudoprimes. furthermore, we give necessary and sufficient conditions for two important classes of strong dickson pseudoprimes and deduce some properties for their elements. a suggestion of how to improve a primality test by baillie&wagstaff concludes the paper.
some remarks on the cross correlation analysis of pseudo random generators. siegenthaler has shown how cross-correlation techniques can be applied to identify pseudo random generators consisting of linear feedback shift registers and a scrambling function [7]. these techniques may allow to attack one register in such a generator at a time. the original algorithm needs o(r2rn) operations to identify one register. (r denotes the length of the register examined, r the number of primitive polynomials of degree r. and n the minimal number of bits one has to observe). employing walsh-hadamard transform this analysis can be done in o(r(r2r+n)) operations [8]. we show that there exists a trade-off between the dimension of the hadamard matrix and the number of bits required to compute the cross correlation coefficients. the complexity of this attack is o(r(r2r-δ+2δn)). the integer δ can be selected so that the cost of the attack is minimized. the msr-generator will serve as an example to demonstrate our algorithm. furthermore we examine the correlation immunity of the s-boxes used in the des.
server (prover/signer)-aided verification of identity proofs and signatures. discrete log based identification and signature schemes are well-suited to identity proof and signature generation, but not suitable for verification, by smart cards, due to their highly asymmetric computational load between the prover/signer and the verifier. in this paper, we present very efficient and practical protocols for fast verification in these schemes, where the verifier with limited computing power performs its computation fast with the aid of the powerful prover/signer. the proposed protocols require very small amounts of computation and communication. the prover/signer only needs to perform a few modular exponentiations in real-time and the two interacting parties only need to communicate a few long numbers. using the proposed prover-aided verification (pav) protocol, the verifier can perform the schnorr-like identification scheme almost as fast as the guillou-quisquater scheme. we generalize the pav protocol into the signer-aided verification (sav) protocol, which can be used for verification of any public function.
a simpler construction of cca2-secure public-key encryption under general assumptions. in this paper we present a simpler construction of a publickey encryption scheme that achieves adaptive chosen ciphertext security (cca2), assuming the existence of trapdoor permutations. we build on previous works of sahai and de santis et al. and construct a scheme that we believe is the easiest to understand to date. in particular, it is only slightly more involved than the naor-yung encryption scheme that is secure against passive chosen-ciphertext attacks (cca1). we stress that the focus of this paper is on simplicity only.
a montgomery-suitable fiat-shamir-like authenication scheme. montgomery's algorithm [2] is a process for computing a b 2-|n| modulo n in o(log(n)) memory space. here we construct a fiat-shamir-like authentication scheme [1] suitable for montgomery environnments without introducing any overhead in the number of modular multiplications requested for the execution of the normal protocol. a very recent result [3] establishes (in a constructive way) that a b 2-|n|) mod n can be computed with the same complexity (timewise and hardwarewise) as a b (not mod n). this theoretical reduction of the problem of modular multiplication. recently applied to the design of today's fastest hardware modular multiplier, is very important since it implies that the protocol presented hereafter can be executed in the same time as a fiat-shamir where all modular multiplications are replaced by standard multiplications. the fact that no constants are to be precalculated beforehand and the small amount of ram requested for software implementation of the new protocol makes it highly convenient for smart-card applications.
a new public-key cryptosystem. this paper describes a new public-key cryptosystem where the ciphertext is obtained by multiplying the public-keys indexed by the message bits and the cleartext is recovered by factoring the ciphertext raised to a secret power. encryption requires four multiplications/byte and decryption is roughly equivalent to the generation of an rsa signature.
the sum of prps is a secure prf. given d independent pseudorandom permutations (prps) πi, ..., πd over {0; 1}n, it appears natural to define a pseudorandom function (prf) by adding (or xoring) the permutation results: sumd(x) = π1(x) ⊕...⊕πd(x). this paper investigates the security of sumd and also considers a variant that only uses one single prp over {0; 1}n.
a comparison of cryptoanalytic principles based on iterative error-correction. a cryptanalytic problem of a linear feedback shift register initial state reconstruction using a noisy output sequence is considered. the main underlying principles of three recently proposed cryptanalytic procedures based on the iterative error-correction are pointed out and compared.
distributed pseudo-random functions and kdcs. this work describes schemes for distributing between n servers the evaluation of a function f which is an approximation to a random function, such that only authorized subsets of servers are able to compute the function. a user who wants to compute f(x) should send x to the members of an authorized subset and receive information which enables him to compute f(x). we require that such a scheme is consistent, i.e. that given an input x all authorized subsets compute the same value f(x). the solutions we present enable the operation of many servers, preventing bottlenecks or single points of failure. there are also no single entities which can compromise the security of the entire network. the solutions can be used to distribute the operation of a key distribution center (kdc). they are far better than the known partitioning to domains or replication solutions to this problem, and are especially suited to handle users of multicast groups.
visual cryptography. in this paper we consider a new type of cryptographic scheme, which can decode concealed images without any cryptographic computations. the scheme is perfectly secure and very easy to implement. we extend it into a visual variant of the k out of n secret sharing problem, in which a dealer provides a transparency to each one of the n users; any k of them can see the image by stacking their transparencies, but any k-1 of them gain no information about it.
universal hash functions & hard core bits. in this paper we consider the bit-security of two types of universal hash functions: linear functions on gf[2n] and linear functions on the integers modulo a prime. we show individual security for all bits in the first case and for the o(log n) least significant bits in the second case. both types of functions are shown to have o(log n) simultaneous secure bits. for the second type of functions, primes of length ω(n) are needed. together with the goldreich-levin theorem, this shows that all the common types of universal hash functions provide so called hard-core bits.
software performance of universal hash functions. this paper compares the parameters sizes and software performance of several recent constructions for universal hash functions: bucket hashing, polynomial hashing, toeplitz hashing, division hashing, evaluation hashing, and mmh hashing. an objective comparison between these widely varying approaches is achieved by defining constructions that offer a comparable security level. it is also demonstrated how the security of these constructions compares favorably to existing mac algorithms, the security of which is less understood.
a new method for known plaintext attack of feal cipher. we propose a new known plaintext attack of feal cipher. our method differs from previous statistical ones in point of deriving the extended key in definite way. as a result, it is possible to break feal-4 with 5 known plaintexts and feal-6 with 100 known plaintexts respectively. moreover, we show a method to break feal-8 with 215 known plaintexts faster than an exhaustive search.
local randomness in candidate one-way functions. we call a distribution on n-bit strings (ɛ, e)-locally random, if for every choice of e ≤ n positions the induced distribution on e-bit strings is in the l1-norm at most ɛ away from the uniform distribution on e-bit strings. we establish local randomness in polynomial random number generators (rng) that are candidate one-way functions. let n be a squarefree integer and let f1, ..., fl be polynomials with coefficients in zn = z/nz. we study the rng that stretches a random x ɛ zn into the sequence of least significant bits of f1(x), ..., fl(x). we show that this rng provides local randomness if for every prime divisor p of n the polynomials f1,...,fl are linearly independent modulo the subspace of polynomials of degree ≤ 1 in zp[x]. we also establish local randomness in polynomial random function generators. this yields candidates for cryptographic hash functions. the concept of local randomness in families of functions extends the concept of universal families of hash functions by carter and wegman (1979). the proofs of our results rely on upper bounds for exponential sums.
new approaches to the design of self-synchronizing stream ciphers. self-synchronizing stream ciphers (sssc) are a commonly used encryption technique for channels with low bit error rate but for which bit synchronization can present a problem. most presently used such ciphers are based on a block cipher (e.g. des) in 1-bit cipher feedback mode. in this paper, several alternative design approaches for ssscs are proposed that are superior to the design based on a block cipher with respect to encryption speed and potentially also with respect to security. a method for combining several ssscs is presented that allows to prove that the combined sssc is at least as secure as any of the component ciphers. the problem of designing ssscs is contrasted with the problem of designing conventional synchronous additive stream ciphers and it is shown that different security criteria must be applied. furthermore, an efficient algorithm is presented for finding a function of low degree that approximates a given boolean function, if such an approximation exists. its significance for the cryptographic security of ssscs and its applications in coding theory are discussed.
a simplified and generalized treatment of luby-rackoff pseudorandom permutation generator. a paper by luby and rackoff on the construction of pseudorandom permutations from pseudorandom functions based on a design principle of the des has recently initiated a burst of research activities on applications and generalizations of these results. this paper presents a strongly simplified treatment of these results and generalizes them by pointing out the relation to locally random functions, thereby providing new insight into the relation between probability-theoretic and complexity-theoretic results in cryptography. the first asymptotically-optimal construction of a locally random function is presented and new design strategies for block ciphers based on these results are proposed.
perfect nonlinear s-boxes. a perfect nonlinear s-box is a substitution transformation with evenly distributed directional derivatives. since the method of differential cryptanalysis presented by e. biham and a. shamir makes use of nonbalanced directional derivatives, the perfect nonlinear s-boxes are immune to this attack. the main result is that for a perfect nonlinear s-box the number of input variables is at least twice the number of output variables. also two different construction methods are given. the first one is based on the maiorana-mcfarland construction of bent functions and is easy and efficient to implement. the second method generalizes dillon's construction of difference sets.
factoring with an oracle. the problem of factoring integers in polynomial time with the help of an (infinitely powerful) oracle who answers arbitrary questions with yes or no is considered. the goal is to minimize the number of oracle questions. let n be a given composite n-bit integer to be factored. the trivial method of asking for the bits of the smallest prime factor of n requires n/2 questions in the worst case. a non-trivial algorithm of rivest and shamir requires only n/3 questions for the special case where n is the product of two n/2-bit primes. in this paper, a polynomial-time oracle factoring algorithm for general integers is presented which, for any ɛ > 0, asks at most ɛn oracle questions for sufficiently large n. based on a conjecture related to lenstra's conjecture on the running time of the elliptic curve factoring algorithm it is shown that the algorithm fails with probability at most n-ɛ/2 for all sufficiently large n.
information-theoretically secure secret-key agreement by not authenticated public discussion. all information-theoretically secure key agreement protocols (e.g. based on quantum cryptography or on noisy channels) described in the literature are secure only against passive adversaries in the sense that they assume the existence of an authenticated public channel. the goal of this paper is to investigate information-theoretic security even against active adversaries with complete control over the communication channel connecting the two parties who want to agree on a secret key. several impossibility results are proved and some scenarios are characterized in which secret-key agreement secure against active adversaries is possible. in particular, when each of the parties, including the adversary, can observe a sequence of random variables that are correlated between the parties, the rate at which key agreement against active adversaries is possible is characterized completely: it is either 0 or equal to the rate achievable against passive adversaries, and the condition for distinguishing between the two cases is given.
the security of many-round luby-rackoff pseudo-random permutations. luby and rackoff showed how to construct a (super-)pseudo-random permutation {0, 1}2n → {0, 1}2n from some number r of pseudo-random functions {0, 1}n → {0, 1}n. their construction, motivated by des, consists of a cascade of r feistel permutations. a feistel permutation 1 for a pseudo-random function f is defined as (l,r) → (r,l⊕f(r)), where l and r are the left and right part of the input and ⊕ denotes bitwise xor or, in this paper, any other group operation on {0, 1}n. the only non-trivial step of the security proof consists of proving that the cascade of r feistel permutations with independent uniform random functions {0, 1}n → {0, 1}n, denoted ψ2nr, is indistinguishable from a uniform random permutation {0, 1}2n → {0, 1}2n by any computationally unbounded adaptive distinguisher making at most o(2cn) combined chosen plaintext/ciphertext queries for any c < α, where α is a security parameter. luby and rackoff proved α = 1/2 for r = 4. a natural problem, proposed by pieprzyk is to improve on α for larger r. the best known result, α = 3/4 for r = 6, is due to patarin. in this paper we prove α = 1- o(1/r), i.e., the trivial upper bound α = 1 can be approached. the proof uses some new techniques that can be of independent interest.
message recovery for signature schemes based on the discrete logarithm problem. the new signature scheme presented by the authors in [13] is the first signature scheme based on the discrete logarithm problem that gives message recovery. the purpose of this paper is to show that the message recovery feature is independent of the choice of the signature equation and that all elgamal-type schemes have variants giving message recovery. for each of the six basic elgamal-type signature equations five variants are presented with different properties regarding message recovery, length of commitment and strong equivalence. moreover, the six basic signature schemes have different properties regarding security and implementation. it turns out that the scheme proposed in [13] is the only inversionless scheme whereas the message recovery variant of the dsa requires computing of inverses in both generation and verification of signatures. in general, message recovery variants can be given for elgamal-type signature schemes over any group with large cyclic subgroup as the multiplicative group of gf(2n) or elliptic curve over a finite field.the present paper also shows how to integrate the dlp-based message recovery schemes with secret session key establishment and elgamal encryption. in particular, it is shown that with dlp-based schemes the same functionality as with rsa can be obtained. however, the schemes are not as elegant as rsa in the sense that the signature (verification) function cannot at the same time be used as the decipherment (encipherment) function.
information-theoretic key agreement: from weak to strong secrecy for free. one of the basic problems in cryptography is the generation of a common secret key between two parties, for instance in order to communicate privately. in this paper we consider information-theoretically secure key agreement. wyner and subsequently csiszár and körner described and analyzed settings for secret-key agreement based on noisy communication channels. maurer as well as ahlswede and csiszár generalized these models to a scenario based on correlated randomness and public discussion. in all these settings, the secrecy capacity and the secret-key rate, respectively, have been defined as the maximal achievable rates at which a highly-secret key can be generated by the legitimate partners. however, the privacy requirements were too weak in all these definitions, requiring only the ratio between the adversary's information and the length of the key to be negligible, but hence tolerating her to obtain a possibly substantial amount of information about the resulting key in an absolute sense. we give natural stronger definitions of secrecy capacity and secret-key rate, requiring that the adversary obtains virtually no information about the entire key. we show that not only secret-key agreement satisfying the strong secrecy condition is possible, but even that the achievable key-generation rates are equal to the previous weak notions of secrecy capacity and secret-key rate. hence the unsatisfactory old definitions can be completely replaced by the new ones. we prove these results by a generic reduction of strong to weak key agreement. the reduction makes use of extractors, which allow to keep the required amount of communication negligible as compared to the length of the resulting key.
enumerating nondegenerate permutations. every cryptosystem with an n-bit block length may be modeled as a system of n-bit boolean equations. the cipher is said to be nondegenerate if the equation fi that describes the output ci is nondegenerate, for 1 ≤ i ≤ n. let nn,n be the set of nondegenerate permutations. we will derive an exact expression for |nn,n|, and show that nn,n|/2n! = 1+o(√2n/22n-1+n).
non-interactive public-key cryptography. an identity-based non-interactive public key distribution system is presented that is based on a novel trapdoor one-way function allowing a trusted authority to compute the discrete logarithm of a given number modulo a publicly known composite number m while this is infeasible for an adversary not knowing the factorization of m. without interaction with a key distribution center or with the recipient of a given message a user can generate a mutual secure cipher key based solely on the recipient's identity and his own secret key and send the message, encrypted with the generated cipher key using a conventional cipher, over an insecure channel to the recipient. unlike in previously proposed identity-based systems, no public keys, certificates for public keys or other information need to be exchanged and thus the system is suitable for many applications such as electronic mail that do not allow for interaction.
convergence in differential distributions. differential cryptanalysis is a general attack based on the notion of differences. the success of the attack is derived from the probability of a differential. while it has been observed that the distribution of differentials can be modeled as a markov chain, there have been few analyses that take advantage of this observation because of the prohibitive computations involved. in this paper we apply the markov approach to the differentially 2-uniform mappings, and show that, they converge exponentially fast with high probability.
an analysis of exponentiation based on formal languages. a recoding rule for exponentiation is a method for reducing the cost of the exponentiation ae by reducing the number of required multiplications. if w(e) is the (hamming) weight of e, and e the result of applying the recoding rule a to e, then the purpose is to reduce wa(e) as compared to w(e). a well-known example of a recoding rule is to convert a binary exponent into a signed-digit representation in terms of the digits { 1;1; 0 } where 1 = -1, by recoding runs of 1's. in this paper we show how three recoding rules can be modelled via regular languages to obtain precise information about the resulting weight distributions. in particular we analyse the recoding rules employed by the 2k-ary, sliding window and optimal signed-digit exponentiation algorithms. we prove that the sliding window method has an expected recoded weight of approximately n/(k +1) for relevant k-bit windows and n-bit exponents, and also that the variance is small. we also prove for the optimal signed digit method that the expected weight is approximately n/3 with a variance of 2n/27. in general the sliding window method provides the best performance, and performs less than 85% of the multiplications required for the other methods for a majority of exponents.
suffix tree and string complexity. let s = (s1, s2, ..., sn) be a sequence of characters where si ɛ zp for 1 ≤ i ≤ n. one measure of the complexity of the sequence s is the length of the shortest feedback shift register that will generate s, which is known as the maximum order complexity of s [17, 18]. we provide a proof that the expected length of the shortest feedback register to generate a sequence of length n is less than 2 logp, n + o(1), and also give several other statistics of interest for distinguishing random strings. the proof is based on relating the maximum order complexity to a data structure known as a suflix tree.
communication security in remote controlled computer systems. nowadays remote controlled computer systems are in widespread use. several systems use the communication facilities offered by the public switched telephone network. in view of the public aspects of the network it is necessary that dial-up systems should have sufficient access security and communication security. in this paper it is proposed that this security be provided by the use of cryptography.
optimum secret sharing scheme secure against cheating. tompa and woll considered a problem of cheaters in (k, n) threshold secret sharing schemes. we first derive a tight lower bound on the size of shares |νi| for this problem: |νi|≥ (|s|-1)/δ+1, where νi denotes the set of shares of participant pi, s denotes thr set of secrets, and δ denotes the cheating probabilily. we next present an optimum scheme which meets the equality of our bound by using "difference sets."
secure bit commitment function against divertibility. some zero-knowledge interactive proofs (zkips) have divertibility, that is, evidence of proof issued by a genuine prover, a, can be transferred to plural verifiers, b and then c, where the intermediate verifier, b, acts as a, with a's help, to confound the other verifier c without revealing the relation between the a-b interaction and the b-c interaction. this property is a serious problem in practice, e.g. the mafia fraud attack on identification scheme and the multiverifier attack against undeniable signatures. this paper proposes a new concept, security against divertibility, and proves that naor's bit commitment function based on pseudo-random generators is secure against divertibility under the reasonable assumption. usage of this bit commitment in zkip can convert a divertible zkip to a divertible-free-zkip which is secure against the mafia fraud attack and the multi-verifier attack.
analysis of pseudo random sequence generated by cellular automata. the security of cellular automata for stream cipher applications is investigated. a cryptanalytic algorithm is developed for a known plaintext attack where the plaintext is assumed to be known up to the unicity distance. the algorithm is shown to be successful on small computers for key sizes up to n between 300 and 500 bits. for a cellular automaton to be secure against more powerful adversaries it is concluded that the key size n needs to be about 1000 bits. the cryptanalytic algorithm takes advantage of an equivalent description of the cryptosystem in which the keys are not equiprobable. it is shown that key search can be reduced considerably if one is contented to succeed only with a certain success probability. this is established by an information theoretic analysis of arbitrary key saurces with non-uniform probability distribution.
direct zero knowledge proofs of computational power in five rounds. zero-knowledge proofs of computational power have been proposed by yung and others. in this paper, we propose an efficient (direct) and constant round (five round) construction of zero knowledge proofs of computational power. to formulate the classes that can be applied to these efficient protocols, we introduce a class of invulnerable problems, fewpr and fewpru. we show that any invulnerable problem in fewpr and fewpru has an efficient and constant round zero knowledge proof of computational power, assuming the existence of a one-way function. we discuss some applications of these zero-knowledge proofs of computational power.
how intractable is the discrete logarithm for a general finite group? gdl is the discrete logarithm prablem for a general finite group g. this paper gives a characterization for the intractability of gdl from the viewpoint of computational complexity theory. it is shown that gdl ∈ np ∩ co-am, assuming that g is in np ∩ co-np, and that the group law operation of g can be cxecuted in a polynomial time of the element size. furthermore, as a natural probabilistic extension, the complexity of gdl is investigated under the assumption that the group law operation is executed in an expected polynomial time of the element size. in this case, it is shown that gdl ∈ ma ∩ co-am if g ∈ np ∩ co-np. finally, we show that gdl is less intractable than np-complete problems unless the polynomial time hierarchy collapses to the second level.
a public key cryptosystem based on elliptic curves over z/nz equivalent to factoring. elliptic curves over the ring z/nz where n is the product of two large primes have first been proposed for public key cryptosystems in [4]. the security of this system is based on the integer factorization problem, but it is unknown whether breaking the system is equivalent to factoring. in this paper, we present a variant of this cryptosystem for which breaking the system is equivalent to factoring the modulus n. moreover, we extend the ideas to get a signature scheme based on elliptic curves over z/nz.
the rsa group is pseudo-free. we prove, under the strong rsa assumption, that the group of invertible integers modulo the product of two safe primes is pseudo-free. more specifically, no polynomial-time algorithm can output (with non negligible probability) an unsatisfiable system of equations over the free abelian group generated by the symbols g 1,&#x2026;,g n , together with a solution modulo the product of two randomly chosen safe primes when g 1,&#x2026;,g n are instantiated to randomly chosen quadratic residues. ours is the first provably secure construction of pseudo-free abelian groups under a standard cryptographic assumption and resolves a conjecture of rivest (theory of cryptography conference&#x2014;proceedings of tcc 2004, lncs, vol.&#x00a0;2951, pp.&#x00a0;505&#x2013;521, 2004).
simulatable commitments and efficient concurrent zero-knowledge. we define and construct simulatable commitments. these are commitment schemes such that there is an efficient interactive proof system to show that a given string c is a legitimate commitment on a given value v, and furthermore, this proof is efficiently simulatable given any proper pair (c, v). our construction is provably secure based on the decisional diffie-hellman (ddh) assumption. using simulatable commitments, we show how to efficiently transform any public coin honest verifier zero knowledge proof system into a proof system that is concurrent zero-knowledge with respect to any (possibly cheating) verifier via black box simulation. by efficient we mean that our transformation incurs only an additive overhead (both in terms of the number of rounds and the computational and communication complexity of each round), and the additive term is close to optimal (for black box simulation): only ω(log n) additional rounds, and ω(log n) additional public key operations for each round of the original protocol, where n is a security parameter, and ω(log n) can be any superlogarithmic function of n independent of the complexity of the original protocol. the transformation preserves (up to negligible additive terms) the soundness and completeness error probabilities, and the new proof system is proved secure based on the ddh assumption, in the standard model of computation, i.e., no random oracles, shared random strings, or public key infrastructure is assumed.
optimal communication complexity of generic multicast key distribution. we prove a tight lower bound on the communication complexity of secure multicast key distribution protocols in which rekey messages are built using symmetric-key encryption, pseudo-random generators, and secret sharing schemes. our lower bound shows that the amortized cost of updating the group key for each group membership change (as a function of the current group size) is at least log2(n) - o(1) basic rekey messages. this lower bound matches, up to a subconstant additive term, the upper bound due to canetti et al. [proc. infocom 1999], who showed that log2(n) basic rekey messages (each time a user joins and/or leaves the group) are sufficient. our lower bound is, thus, optimal up to a small subconstant additive term. the result of this paper considerably strengthens previous lower bounds by canetti et al. [proc. eurocrypt 1999] and snoeyink et al. [computer networks, 47(3):2005], which allowed for neither the use of pseudorandom generators and secret sharing schemes nor the iterated (nested) application of the encryption function. our model (which allows for arbitrarily nested combinations of encryption, pseudorandom generators and secret sharing schemes) is much more general and, in particular, encompasses essentially all known multicast key distribution protocols of practical interest.
on diffie-hellman key agreement with short exponents. the difficulty of computing discrete logarithms known to be "short" is examined, motivated by recent practical interest in using diffie-hellman key agreement with short exponents (e.g. over zp, with 160-bit exponents and 1024-bit primes p). a new divide-and-conquer algorithm for discrete logarithms is presented, combining pollard's lambda method with a partial pohlig-hellman decomposition. for random diffie-hellman primes p, examination reveals this partial decomposition itself allows recovery of short exponents in many cases, while the new technique dramatically extends the range. use of subgroups of large prime order precludes the attack at essentially no cost, and is the recommended solution. using safe primes also precludes this particular attack and allows improved exponentiation performance, although parameter generation costs are dramatically higher.
security proofs for signature schemes. in this paper, we address the question of providing security proofs for signature schemes in the so-called random oracle model [1]. in particular, we establish the generality of this technique against adaptively chosen message attacks. our main application achieves such a security proof for a slight variant of the el garrial signature schemc [4] where committed values are hashed together with the message. this is a rather surprising result since the original el gamal is, as rsa [11], subject to existential forgery.
convergence of a bayesian iterative error-correction procedure on a noisy shift register sequence. convergence of an algorithm for a linear feedback shift register initial state reconstruction using the noisy output sequence, based on a bitwise bayesian iterative error-correction procedure and different weight parity-checks, is analyzed. it is proved that the self-composition of the bayes error probability converges to zero if and only if the noise probability is less than a critical value expressed in terms of the numbers of parity-checks. an alternative approach to the critical noise estimation based on the residual error-rate after each iterative revision is also discussed.
fast arithmetic architectures for public-key algorithms over galois fields gf((2)). this contribution describes a new class of arithmetic architectures for galois fields gf(2k). the main applications of the architecture are public-key systems which are based on the discrete logarithm problem for elliptic curves. the architectures use a representation of the field gf(2k) as gf((2n)m), where k = nċm. the approach explores bit parallel arithmetic in the subfield gf(2n), and serial processing for the extension field arithmetic. this mixed parallel-serial (hybrid) approach can lead to very fast implementations. the principle of these approach was initially suggested by mastrovito. as the core module, a hybrid multiplier is introduced and several optimizations are discussed. we provide two different approaches to squaring which, in conjunction with the multiplier, yield fast exponentiation architectures. the hybrid architectures are capable of exploring the time-space trade-off paradigm in a flexible manner. in particular, the number of clock cycles for one field multiplication, which is the atomic operation in most public-key schemes, can be reduced by a factor of n compared to all other known realizations. the acceleration is achieved at the cost of an increased computational complexity. we describe a proof-of-concept implementation of an asic for exponentiation in gf((2n)m), m variable.
public-key cryptosystems based on composite degree residuosity classes. this paper investigates a novel computational problem, namely the composite residuosity class problem, and its applications to public-key cryptography. we propose a new trapdoor mechanism and derive from this technique three encryption schemes : a trapdoor permutation and two homomorphic probabilistic encryption schemes computationally comparable to rsa. our cryptosystems, based on usual modular arithmetics, are provably secure under appropriate assumptions in the standard model.
simulation in quasi-polynomial time, and its application to protocol composition. we propose a relaxation of zero-knowledge, by allowing the simulator to run in quasi-polynomial time. we show that protocols satisfying this notion can be constructed in settings where the standard definition is too restrictive. specifically, we construct constant-round straight-line concurrent quasi-polynomial time simulatable arguments and show that such arguments can be used in advanced composition operations without any set-up assumptions. our protocols rely on slightly strong, but standard type assumptions (namely the existence of one-to-one one-way functions secure against subexponential circuits).
how to construct pseudorandom and super pseudorandom permutations from one single pseudorandom function. in this paper we will solve two open problems concerning pseudorandom permutations generators. 1. we will see that it is possible to obtain a pseudorandom permutation generator with only three rounds of des - like permutation and a single pseudorandom function. this will solve an open problem of [6]. 2. we will see that it is possible to obtain a super pseudorandom permutation generator with a single pseudorandom function. this will solve an open problem of [5]. for this we will use only four rounds of des - like permutation. for example, we will see that if ζ denotes the rotation of one bit, ψ(f,f,fo ζ o f) is a pseudorandom function generator. and ψ(f,f,f,f,o ζ o f) is a super pseudorandom function generator. here the number of rounds used is optimal. it should be noted that here we introduce an important new idea in that we do not use a composition of f, i times, but f o ζ o f for the last round, where ζ is a fixed and public function.
hidden fields equations (hfe) and isomorphisms of polynomials (ip): two new families of asymmetric algorithms. in [6] t. matsumoto and h. imai described a new asymmetric algorithm based on multivariate polynomials of degree two over a finite field, which was subsequently broken in [9]. here we present two new families of asymmetric algorithms that so far have resisted all attacks, if properly used: hidden field equations (hfe) and isomorphism of polynomials (ip). these algorithms can be seen as two candidate ways to repair the matsumoto-imai algorithm. hfe can be used to do signatures, encryption or authentication in an asymmetric way, with very short signatures and short encryptions of short messages. ip can be used for signatures and for zero knowledge authenticatinn. an extended version of this paper can be obtained from the author. another way to repair the matsumoto-imai algorithm will be presented in [10].
distributed provers with applications to undeniable signatures. this paper introduces distributed prover protocols. such a protocol is a proof system in which a polynomially bounded prover is replaced by many provers each having partial information about the witness owned by the original prover. as an application of this concept, it is shown how the signer of undeniable signatures can distribute part of his secret key to n agents such that any k of these can verify a signature. this facility is useful in most applications of undeniable signatures, and as the proposed protocols are practical, the results in this paper makes undeniable signatures more useful. the first part of the paper describes a method for verifiable secret sharing, which allows non-interactive verification of the shares and is as secure as the shamir secret sharing scheme in the proposed applications.
coin-based anonymous fingerprinting. fingerprinting schemes are technical means to discourage people from illegally redistributing the digital data they have legally purchased. these schemes enable the original merchant to identify the original buyer of the digital data. in so-called asymmetric fingerprinting schemes the fingerprinted data item is only known to the buyer after a sale and if the merchant finds an illegally redistributed copy, he obtains a proof convincing a third party whom this copy belonged to. all these fingerprinting schemes require the buyers to identify themselves just for the purpose of fingerprinting and thus offer the buyers no privacy. hence anonymous asymmetric fingerprinting schemes were introduced, which preserve the anonymity of the buyers as long as they do not redistribute the data item. in this paper a new anonymous fingerprinting scheme based on the principles of digital coins is introduced. the construction replaces the general zero-knowledge techniques from the known certificate-based construction by explicit protocols, thus bringing anonymous fingerprinting far nearer to practicality.
how to break another provably secure payment system. at euroctypt '94, stefano d'amiano and giovanni di crescenzo presented a protocol for untraceable electronic cash based on non-interactive zero-knowledge proofs of knowledge with preprocessing. it was supposed to be provably secure given this and a few other general cryptographic tools. we show that this protocol nevertheless does not provide any untraceability and has some further weaknesses. we also break another "provably secure" system proposed by di crescenzo at ciac 94. this is the second case of problems with "provably secure" payment systems. moreover, yet another system with this name tacitly solves a much weaker problem than the seminal paper by chaum, fiat, and naor and most other "practical" papers in this field (de santis and persiano, stacs 92). we therefore identify some principal problems with definitions and proofs of such schemes, and sketch better ways to handle them.
attacks on protocols for server-aided rsa computation. on crypto '88, matsumoto, kato, and imai presented protocols to speed up secret computations with insecure auxiliary devices. the two most important protocols enable a smart card to compute the secret rsa operation faster with the help of a server that is not necessarily trusted by the card holder. it was stated that if rsa is secure, the protocols could only be broken by exhaustive scarch in certain spacts. our main attacks show that much smaller search spaces suffice. these attacks are passive and therefore undetectable. it was already known that one of the protocols is vulnerable to active attacks. we show that this holds for the other protocol, too. more importantly, we show that our attack may still work if the smart card checks the correctness of the result; this was previously believed to be can easy measure excluding all active attacks. finally, we discuss attach on related protocols.
anonymous fingerprinting. fingerprinting schemes deter people from illegally redistributing digital data by enabling the original merchant of the data to identify the original buyer of a redistributed copy. recently, asymmetric fingerprinting schemes were introduced. here, only the buyer knows the fingerprinted copy after a sale, and if the merchant finds this copy somewhere, he obtains a proof that it was the copy of this particular buyer. a problem with all previous fingerprinting schemes arises in the context of electronic marketplaces where untraceable electronic cash offers buyers privacy similar to that when buying books or music in normal shops with normal cash. now buyers would have to identify themselves solely for the purpose of fingerprinting. to remedy this, we introduce and construct anonymous asymmetric fingerprinting schemes, where buyers can buy information anonymously, but can nevertheless be identified if they redistribute this information illegally. a subresult of independent interest is an asymmetric fingerprinting protocol with reasonable collusion tolerance and 2-party trials, which have several practical advantages over the previous 3-party trials. our results can also be applied to so-called traitor tracing, the equivalent of fingerprinting for broadcast encryption.
probabilistic analysis of elementary randimizers. in the paper, elementary randomizers based on random functions and the des structure are examined. first, it is proved that the randomizer with three different random functions produces the outputs which are independent and uniformly distributed random variables. next, randomizers based on two different random functions are considered and it is shown that their statistical properties depend upon the order of the functions used in them. finally, it is proved that the randomizer with a single random function gives outputs which are statistically related.
randomized authentication systems. in this work, the application of luby-rackoff randomizers for authentication purposes is examined. first randomized authentication codes are introduced. in these codes, the assignment of a cryptogram to a given message is done in two stages. in the first, the redundancy is introduced and in the second, the concatenation of several luby-rackoff randomizers is used. next, perfect a-codes are defined. the quality of the authentication codes (a-codes) is measured using the concept of distinguishing circuits. three a-codes with different redundancy stages are examined and proven that they are perfect if the suitable number of luby-rackoff randomizers is used in the second stage of the a-code.
fair secure two-party computation. we demonstrate a transformation of yao's protocol for secure two-party computation to a fair protocol in which neither party gains any substantial advantage by terminating the protocol prematurely. the transformation adds additional steps before and after the execution of the original protocol, but does not change it otherwise, and does not use a trusted third party. it is based on the use of gradual release timed commitments, which are a new variant of timed commitments, and on a novel use of blind signatures for verifying that the committed values are correct.
a new identification scheme based on the perceptrons problem. identification is a useful cryptographic tool. since zero-knowledge theory appeared [3], several interactive identification schemes have been proposed (in particular fiat-shamir [2] and its variants [8, 5, 4], schnorr [9]). these identifications are based on number theoretical problems. more recently, new schemes appeared with the peculiarity that they are more efficient from the computational point of view and that their security is based on np-complete problems: pkp (permuted kernels problem) [10], sd (syndrome decoding) [12] and cle (constrained linear equations) [13]. we present a new np-complete linear problem which comes from learning machines: the perceptrons problem. we have some constraints, m vectors xi of (-1, +1}n, and we want to find a vector v of (-1, +1}n such that xi ċ v ≥ 0 for all i. next, we provide some zero-knowledge interactive identification protocols based on this problem, with an evaluation of their security. eventually, those protocols are well suited for smart card applications.
new public key cryptosystems based on the dependent-rsa problems. since the diffie-hellman paper, asymmetric encryption has been a very important topic, and furthermore ever well studied. however, between the efficiency of rsa and the security of some less efficient schemes, no trade-off has ever been provided. in this paper, we propose better than a trade-off: indeed, we first present a new problem, derived from the rsa assumption, the "dependent-rsa problem". a careful study of its difficulty is performed and some variants are proposed, namely the "decisional dependent-rsa problem". they are next used to provide new encryption schemes which are both secure and efficient. more precisely, the main scheme is proven semantically secure in the standard model. then, two variants are derived with improved security properties, namely against adaptive chosen-ciphertext attacks, in the random oracle model. furthermore, all those schemes are more or less as efficient as the original rsa encryption scheme and reach semantic security.
fast authentication in a trapdoor - knapsack public key cryptosystem. public key cryptosystems based on the trapdoor knapsack method proposed by merkle and hellman are not well suited to provide authentication in the sense of public key authentication because only a small fraction of all possible message words of a typical length lead to a binary solution of the knapsack problem. in this paper, a new method is discussed which provides a nonbinary solution for the knapsack problem of a merkle/hellman scheme. the algorithm works for any message word with a comparatively short computation time. thus, the solution can be used as a secure authentication pattern. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
on the use of interconnection networks in cryptography. cryptosystems can be viewed as sets of permutations from which one permutation is chosen as cryptofunction by specifying a key. interconnection networks have been widely studied in the field of parallel processing. they have one property that makes them very interesting for cryptology, i.e. they give the opportunity to access and perform permutations at the same time. this paper presents two examples of how cryptology can benefit from the use of interconnection networks. one is a new construction of a pseudo-random permutation (generator) from one single pseudo-random function (generator). the search for such constructions has been of major interest since luby and rackoff gave the first construction in 1986. the second example presents a cryptosystem based on interconnection networks and a certain class of boolean functions. some arguments for its security are given. although there is a relation between the two examples they complement each other in using different properties of interconnection networks. this can be regarded as an argument that exploiting the full potential of interconnection networks can establish completely new techniques in cryptology.
fair encryption of rsa keys. cryptography is more and more concerned with elaborate protocols involving many participants. in some cases, it is crucial to be sure that players behave fairly especially when they use public key encryption. accordingly, mechanisms are needed to check the correctness of encrypted data, without compromising secrecy. we consider an optimistic scenario in which users have pairs of public and private keys and give an encryption of their secret key with the public key of a third party. in this setting we wish to provide a publicly verifiable proof that the third party is able to recover the secret key if needed. our emphasis is on size; we believe that the proof should be of the same length as the original key. in this paper, we propose such proofs of fair encryption for el gamal and rsa keys, using the paillier cryptosystem. our proofs are really efficient since in practical terms they are only a few hundred bytes long. as an application, we design a very simple and efficient key recovery system.
is the rsa scheme safe? we present a new factoring algorithm which under reasonable assumptions and for r ≥ 2 will factor about n(r-2)-(r-2) which integers in [1,n] within n1/2r multiplications i n g(-n). here g(-n) is the group of equivalence classes under sl2(z), of primitive, positive forms ax2+bxy+cy2 with discriminant -n = b2 - 4 ac. let h(-n) = |g(- n)| be the class number. then n will be factored within this time bound if (1) the largest prime divisor of h(-n) is ≤ n1/r (2) the second largest prime divisor of h(-n) is ≤ n1/2r. so far it is unpredictable which integers n satisfy these conditions. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
race integrity primitives evaluation (ripe): a status report. early in 1989, a call for integrity primitives was disseminated within the cryptographic community by the ripe consortium. the goal of this consortium is to put forward an ensemble of techniques to meet the anticipated requirements of the future integrated broadband communication network in the european community. the aim of this paper is to describe the status of the ripe project.
public key encryption and signature schemes based on polynomials over zn. the problem of computing roots of a polynomial over the ring zn, is equivalent to factoring n. starting from this intractable problem we construct a public key encryption scheme where the message blocks are encrypted as roots of a polynomial over zn and a signature scheme where the signature belonging to a message is a (set of) root(s) of a polynomial having the message blocks as coefficients. these schemes can be considered as extensions of rabin's encryption and signature scheme. however, our signature scheme has some new properties: a short signature can be generated for a long message without using a hash function, and the security features of the scheme can be chosen either to be similar to those of the rsa scheme or to be equivalent to those of rabin's scheme.
boolean functions satisfying higher order propagation criteria. boolean functions that satisfy higher order propagation criteria are studied. a complete characterization is given of the autocorrelation function and walsh spectrum of second order functions. the number of second order functions satisfying pc(k) is related to a problem in coding theory and can be computed explicitly for k = 1, n - 1 and n. a new interpretation of the number of balanced second order functions is given and a class of functions showing interesting properties is discussed.
on the security of two mac algorithms. the security of two message authentication code (mac) algorithms is considered: the md5-based envelope method (rfc 1828), and the banking standard maa (iso 8731-2). customization of a general mac forgery attack allows improvements in both cases. for the envelope method, the forgery attack is extended to allow key recovery; for example, a 128-bit key can be recovered using 267 known text-mac pairs and time plus 213 chosen texts. for maa, internal collisions are feud with fewer and shorter messages than previously by exploiting the algorithm's internal structure; consequently, the number of chosen texts (each 256 kbyte long) for a forgery can be reduced by two orders of magnitude, e.g. from 224 to 217. this attack can be extended to one requiring only short messages (224 messages shorter than 1 kbyte) to circumvent the special maa mode for long messages. moreover, certain internal collisions allow key recovery, and weak keys for maa are identified.
provably secure threshold password-authenticated key exchange. we present two protocols for threshold password authenticated key exchange. in this model, the password is not stored in a single authenticating server but rather shared among a set of n servers so that an adversary can learn the password only by breaking into t+1 of them. the protocols require n > 3t servers to work. the goal is to protect the password against hackers attacks that can break into the authenticating server and steal password information. all known centralized password authentication schemes are susceptible to such an attack. ours are the first protocols which are provably secure in the standard model (i.e. no random oracles are used for the proof of security). moreover our protocols are reasonably efficient and implementable in practice. in particular a goal of the design was to avoid costly zero-knowledge proofs to keep interaction to a minimum.
new bounds in secret-key agreement: the gap between formation and secrecy extraction. perfectly secret message transmission can be realized with only partially secret and weakly correlated information shared by the parties as soon as this information allows for the extraction of information-theoretically secret bits. the best known upper bound on the rate s at which such key bits can be generated has been the intrinsic information of the distribution modeling the parties', including the adversary's, knowledge. based on a new property of the secret-key rate s, we introduce a conditional mutual information measure which is a stronger upper bound on s. having thus seen that the intrinsic information of a distribution p is not always suitable for determining the number of secret bits extractable from p, we prove a different significance of it in the same context: it is a lower bound on the number of key bits required to generate p by public communication. taken together, these two results imply that sometimes, (a possibly arbitrarily large fraction of) the correlation contained in distributed information cannot be extracted in the form of secret keys by any protocol.
information-theoretic bounds for authentication frauds. several properties of authentication codes depend on a mathematical structure, called below a fraud scheme, which is much simpler than the one originally given. relying on this fact, we present a powerful lower bound, which is a sort of mould to painlessly derive a whole range of information-theoretic bounds to fraud probabilities in authentication coding.
on the concurrent composition of zero-knowledge proofs. we examine the concurrent composition of zero-knowledge proofs. by concurrent composition, we indicate a single prover that is involved in multiple, simultaneous zero-knowledge proofs with one or multiple verifiers. under this type of composition it is believed that standard zero-knowledge protocols are no longer zero-knowledge. we show that, modulo certain complexity assumptions, any statement in np has kɛ-round proofs and arguments in which one can efficiently simulate any ko(1) concurrent executions of the protocol.
on the security of the schnorr scheme using preprocessing. in this paper, it is shown that the schnorr scheme with preprocessing as proposed in [4] leaks too much information. an attack based on this information leakage is presented that retrieves the secret key. the complexity of this attack is upper bounded by 2k ċ k3(d-2) steps, and the expected required number of signatures is less than 2k ċ (k/2)(d-2), where k is a security parameter. this complexity is significantly lower than the kk(d-2) steps, conjectured in [4]. for example, for the security parameters that are proposed in [4], the secret key can on average be found in 237.5 steps, instead of in 272 steps, this shows that it is inevitable to either modify the preprocessing algorithm, or choose the values of the security paremeters larger than proposed in [4]. finally, we briefly discuar the possibility of averting the proposed attack by modifying the preprocessing algorithm.
on the complexity of hyperelliptic discrete logarithm problem. we give a characterization for the intractability of hyperelliptic discrete logarithm problem from a viewpoint of computational complexity theory. it is shown that the language of which complexity is equivalent to that of the hyperelliptic discrete logarithm problem is in np ∩ co-am, and that especially for elliptic curves, the corresponding language is in np ∩ co-np. it should be noted here that the language of which complexity is equivalent to that of the discrete logarithm problem defined over the multiplicative group of a finite field is also characterized as in np ∩ co-np.
practical threshold signatures. we present an rsa threshold signature scheme. the scheme enjoys the following properties: 1. it is unforgeable and robust in the random oracle model, assuming the rsa problem is hard; 2. signature share generation and verification is completely non-interactive; 3. the size of an individual signature share is bounded by a constant times the size of the rsa modulus.
using hash functions as a hedge against chosen ciphertext attack. the cryptosystem recently proposed by cramer and shoup [cs98] is a practical public key cryptosystem that is secure against adaptive chosen ciphertext attack provided the decisional diffie-hellman assumption is true. although this is a reasonable intractability assumption, it would be preferable to base a security proof on a weaker assumption, such as the computational diffie-hellman assumption. indeed, this cryptosystem in its most basic form is in fact insecure if the decisional diffie-hellman assumption is false. in this paper we present a practical hybrid scheme that is just as efficient as the scheme of of cramer and shoup; indeed, the scheme is slightly more efficient than the one originally presented by cramer and shoup; we prove that the scheme is secure if the decisional diffie-hellman assumption is true; we give strong evidence that the scheme is secure if the weaker, computational diffie-hellman assumption is true by providing a proof of security in the random oracle model.
a composition theorem for universal one-way hash functions. in this paper we present a new scheme for constructing universal one-way hash functions that hash arbitrarily long messages out of universal one-way hash functions that hash fixed-length messages. the new construction is extremely simple and is also very efficient, yielding shorter keys than previously proposed composition constructions.
when shift registers clock themselves. a new class of sequences, which we term [d,k] self-decimated sequences, is investigated. for appropriate choices of [d,k] these sequences possess large periods, balanced k-distributions, large linear complexities, and moderate out-of-phase autocorrelation magnitudes. furthermore, they are easy to generate. these properties suggest that [d,k] self-decimated sequences may have some applications in cryptography and spread spectrum communication.
on the security of a practical identification scheme. we analyze the security of an interactive identification scheme. the scheme is the obvious extension of the original square root scheme of goldwasser, micali and rackoff to 2mth roots. this scheme is quite practical, especially in terms of storage and communication complexity. although this scheme is certainly not new, its security was apparently not fully understood. we prove that this scheme is secure if factoring integers is hard, even against active attacks where the adversary is first allowed to pose as a verifier before attempting impersonation.
lower bounds for discrete logarithms and related problems. this paper considers the computational complexity of the discrete logarithm and related problems in the context of "generic algorithms"--that is, algorithms which do not exploit any special properties of the encodings of group elements, other than the property that each group element is encoded as a unique binary string. lower bounds on the complexity of these problems are proved that match the known upper bounds: any generic algorithm must perform ω(p1/2) group operations, where p is the largest prime dividing the order of the group. also, a new method for correcting a faulty diffie-hellman oracle is presented.
a formal approach to security architectures. we define a formal language whose symbols are security goals and mechanisms. this allows us to express every security architecture as a string. designing a security architecture becomes the task of generating a word in the language. analysing a security architecture becomes the task of parsing a string and determining if it belongs to the language. since not every complete security architecture achieves its goals equally efficient, we associate a complexity parameter to every goal and mechanism. this allows us to identify complexity- reducing and complexity-increasing mechanisms.
session key distribution using smart cards. in this paper, we investigate a method by which smart cards can be used to enhance the security of session key distribution in the third-party setting of needham & schroeder. we extend the security model of bellare & rogaway to take into account both the strengths and weaknesses of smart card technology, we propose a session key distribution protocol, and we prove that it is secure assuming pseudo-random functions exist.
a construction for one way hash functions and pseudorandom bit generators. we prove that if f is a n-bit one-way permutation, i.e., it has some hard bits, a one-way permutation with n - k provably simultaneous hard bits can be constructed with it. we apply this construction to improve the efficiency of blum-micali pseudo-random bit generator. then, we apply the construction to propose a new approach for building universal one-way hash functions. this approach merges damgard's design principle (or merkle's meta-method) and the method proposed by zheng, matsumoto and imai for the construction of hash functions for long messages.
a construction for super pseudorandom permutations from a single pseudorandom function. in this paper, we show how to construct a super pseudorandom permutation generator from a single pseudorandom function generator, based on des-like permutations. first, we show ψ(g, 1, f, g, 1, f), which consists of six rounds of des-like permutations with two different pseudorandom functions and a fixed permutation, is super psuedorandom. then, we show that with replacing a two-fold composition of one of the pseudorandom functions instead of the other one it is possible to construct a super pseudorandom permutation from a single pseudorandom function, where we need six rounds of des-like permutations and six references to the pseudorandom function.
authentication codes in plaintext and chosen-content attacks. we study authentication codes (a-codes) when the enemy has access to the content of the intercepted cryptogram. this is similar to plaintext attack in secrecy systems. enemy's success is defined in two ways. the first is as in simmons' model. we will also consider chosen-content attacks in which the success is by constructing a fraudulent cryptogram with a given content. we will obtain information theoretic bounds, define perfect protection and obtain lower bounds on the number of encoding rules for codes with perfect protection against chosen-content impersonation and chosen-content plaintext substitution. we characterize these a-codes when the number of encoding rules is minimum. we give methods of making an a-code resistant against plaintext and chosen-context plaintext attack.
factoring integers and computing discrete logarithms via diophantine approximations. let n be an integer with at least two distinct prime factors. we reduce the problem of factoring n to the task of finding random integer solutions (e1,..., et) ∈ zzt of the inequalities |σi=1tei log pi - log n|≤ n-c and σi=1t|ei log pi| ≤ (2c-1)log n+o(log pt), where c > 1 is fixed and p1, ..., pt are the first t primes. we show, under the assumption that the smooth integers distribute "uniformly", that there are ne+o(1) many solutions (e1,...,et) if c > 1 and if ɛ := c - 1 - (2c - 1) log log n / log pt > 0. we associate with the primes p1,...,pt a lattice l ⊂ rt+1 of dimension t and we associate with n a point n ∈ rt+1. we reduce the problem of factoring n to the task of finding random lattice vectors z that are sufficiently close to n in both the ∞-norm and thr 1-norm. the dimension t of the lattice l is polynomial in log n. for n ≅ 2512 it is about 6300. we also reduce the problem of computing, for a prime n, discrete logarithms of the units in zz/nzz to a similar diophantiue approximation problem.
message authentication with arbitration of transmitter/receiver disputes. in the most general model of message authentication, there are four essential participants: a transmitter who observes an information source, such as a coin toss, and wishes to communicate these observations to a remotely located receiver over a publicly exposed, noiseless, communications channel; a receiver who wishes to not only learn the state of the source (as observed by the transmitter) but also to assure himself that the communications (messages) he accepts actually were sent by the transmitter and that no alterations have been made to them subsequent to the transmitter having sent them, and two other parties, the opponent and the arbiter. the opponent wishes to deceive the receiver into accepting a message that will misinform him as to the state of the source. we assume, in accordance with kerckhoffs' criteria in cryptography, that the opponent is fully knowledgeable of the authentication system and that in addition he is able to both eavesdrop on legitimate communications in the channel and to introduce fraudulent communications of his own choice. we also assume that he has unlimited computing power, i.e., that any computation which can be done in principal can in fact be done in practice. given this, the opponent can achieve his objective in either of two ways: 1) he can impersonate the transmitter and send a fraudulent message when in fact no message was sent by the transmitter, or 2) he can wait to intercept a legitimate message from the transmitter and substitute in its stead some other message of his own devising.
receipt-free mix-type voting scheme - a practical solution to the implementation of a voting booth. we present a receipt-free voting scheme based on a mixtype anonymous channel[cha81, pik93]. the receipt-freeness property [bt94] enables voters to hide how they have voted even from a powerful adversary who is trying to coerce him. the work of [bt94] gave the first solution using a voting booth, which is a hardware assumption not unlike that in current physical elections. in our proposed scheme, we reduce the physical assumptions required to obtain receipt-freeness. our sole physical assumption is the existence of a private channel through which the center can send the voter a message without fear of eavesdropping.
relationships among the computational powers of breaking discrete log cryptosystems. we investigate the complexity of breaking cryptosystems of which security is based on the discrete logarithm problem. we denote the algorithms of breaking the diffie-hellman's key exchange scheme by dh, the bellare-micali's non-interactive oblivious transfer scheme by bm, the elgamal's public-key cryptosystem by eg, the okamoto's conferencekey sharing scheme by conf, and the shamir's 3-pass key-transmission scheme by 3pass, respectively. we show a relation among these cryptosystems that 3pass ≤mfp conf ≤mfp eg ≡mfp bm ≡mfp dh, where ≤mfp denotes the polynomial-time functionally many-teone reducibility, i.e. a function version of the ≤mp -reducibility. we further give some condition in which these algorithms have equivalent difficulty. namely, 1. if the complete factorization of p - 1 is given, i.e. if the the discrete logarithm problem is a certified one, then these cryptosystems are equivalent w.r.t. expected polynomial-time functionally turing reducibility. 2. if the underlying group is the jacobian of an elliptic curve over zp, with a prime order, then these cryptosystems are equivalent w.r.t. polynomial-time functionally many-to-one reducibility. we also discuss the complexity of several languages related to those computing problems.
construction of nonlinear boolean functions with important cryptographic properties. this paper addresses the problem of obtaining new construction methods for cryptographically significant boolean functions. we show that for each positive integer m, there are infinitely many integers n (both odd and even), such that it is possible to construct n-variable, m-resilient functions having nonlinearity greater than 2n-1 -2[n/2]. also we obtain better results than all published works on the construction of n-variable, m-resilient functions, including cases where the constructed functions have the maximum possible algebraic degree n - m - 1. next we modify the patterson-wiedemann functions to construct balanced boolean functions on n-variables having nonlinearity strictly greater than 2n-1 - 2n-1/2 for all odd n ≥ 15. in addition, we consider the properties strict avalanche criteria and propagation characteristics which are important for design of s-boxes in block ciphers and construct such functions with very high nonlinearity and algebraic degree.
encrypting by random rotations. this paper gives some well-known, little known, and new results on the problem of generating random elements in groups, with particular emphasis on applications to cryptography. the groups of greatest interest are the group of all orthogonal n × n matrices and the group of all permutations of a set. the chief application is to a. d. wyner's analog scrambling scheme for voice signals.
resource requirements for the application of addition chains in modulo exponentiation. addition chains or sequences can be usecd to reduce the amount of multiplications to accomplish an exponentiation at the cost of more memory required. we examine known methods of exponentiations based on addition sequences and derive the parameters determining operation count and number of required registers for storing intermediate results. as a result an improved method is proposed to choose window distributions as a basis for using known addition sequence heuristics.
fft-hash ii, efficient cryptographic hashing. we propose an efficient algorithm that hashes messages of arbitrary bit length into an 128 bit hash value. the algorithm is designed to make the production of a pair of colliding messages computationally infeasible. the algorithm performs a discrete fourier transform and a polynomial recursion over a finite field. each hash value in {0,1}128 occurs with frequency at most 2-120. this hash function is an improved variant of the algorithm fft-hash i presented in the rump session of crypto '91. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
cryptonalysis of the data encryption standard by the method of formal coding. the "method of formal coding" consists in representing each bit of a des ciphertext block as an xor-sum-of-products of the plaintext bits and the key bits. subsequent introduction of the "mfc-complexity measure" yields interesting results on the security of the des and the influecce of various parameters. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
ic-cards in high-security applications. ic-cards, which are credit-card-size plastic cards with integrated cpu and memory, have increasingly attracted public interest in recent years. mainly used as "electronic money" in the business of banking and as a storage medium at first, the ic-card is gaining more and more importance as a secure and user-optimised component for cryptographic systems. the following article analyses ic-cards with regard to their own security and their applications in the field of "edp security". the paper is concluded with a glance at the requirements to be met by future card generations and on possible developments. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
attacking the chor-rivest cryptosystem by improved lattice reduction. we introduce algorithms for lattice basis reduction that are improvements of the famous l3-algorithm. if a random l3-reduced lattice basis b1, . . . , bn, is given such that the vector of reduced gram-schmidt coefficients ({µi, j} 1 ≤ j < i ≤ n) is uniformly distributed in (0, 1)(n 2), then the pruned enumeration finds with positive probability a shortest lattice vector. we demonstrate the power of these algorithms by solving random subset sum problems of arbitrary density with 74 and 82 many weights, by breaking the chor-rivest cryptoscheme in dimensions 103 and 151 and by breaking damgård's hash function.
on the performance of hyperelliptic cryptosystems. in this paper we discuss various aspects of cryptosystems based on hyperelliptic curves. in particular we cover the implementation of the group law on such curves and how to generate suitable curves for use in cryptography. this paper presents a practical comparison between the performance of elliptic curve based digital signature schemes and schemes based on hyperelliptic curves. we conclude that, at present, hyperelliptic curves offer no performance advantage over elliptic curves.
publicly verifiable secret sharing. a secret sharing scheme allows to share a secret among several participants such that only certain groups of them can recover it. verifiable secret sharing has been proposed to achieve security against cheating participants. its first realization had the special property that everybody not only the participants, can verify that ihe shares are correctly distributed. we will call such schemes publicly verifiable secret sharing schemes, we discuss new applications to escrow cryptosystems and to payment systems with revocable anonymity, and we present two new realizations based on elgamal's cryptosystem.
fair blind signatures. a blind signature scheme is a protocol for obtaining a signature from a signer such that the signer's view of the protocol cannot be linked to the resulting message-signature pair. blind signature schemes are used in anonymous digital payment systems. since the existing proposals of blind signature schemes provide perfect unlinkability, such payment systems could be misused by criminals, e.g. to safely obtain a ransom or to launder money. in this paper, a new type of blind signature schemes called fair blind signature schemes is proposed. such schemes have the additional property that a trusted entity can deliver information allowing the signer to link his view of the protocol and the message-signature pair. two types of fair blind signature schemes are distinguished and several realizations are presented.
why provable security matters? recently, methods from provable security, that had been developped for the last twenty years within the research community, have been extensively used to support emerging standards. this in turn has led researchers as well as practitioners to raise some concerns about this methodology. should provable security be restricted to the standard computational model or can it rely on the so-called random oracle model? in the latter case, what is the practical meaning of security estimates obtained using this model? also, the fact that proofs themselves need time to be validated through public discussion was somehow overlooked. building on two case studies, we discuss these concerns. one example covers the public key encryption formatting scheme oaep originally proposed in [3]. the other comes from the area of signature schemes and is related to the security proof of esign [43]. both examples show that provable security is more subtle than it at first appears.
hypercubic lattice reduction and analysis of ggh and ntru signatures. in this paper, we introduce a new lattice reduction technique applicable to the narrow, but important class of hypercubic lattices, (l ≅ zn). hypercubic lattices arise during transcript analysis of certain ggh, and ntrusign signature schemes. after a few thousand signatures, key recovery amounts to discovering a hidden unitary matrix u, from its gram matrix g = uut. this case of the gram matrix factorization problem is equivalent to finding the shortest vectors in the hypercubic lattice, lg, defined by the quadratic form g. our main result is a polynomial-time reduction to a conjecturally easier problem: the lattice distinguishing problem. additionally, we propose a heuristic solution to this distinguishing problem with a distributed computation of many "relatively short" vectors.
non-interactive proofs for integer multiplication. we present two universally composable and practical protocols by which a dealer can, verifiably and non-interactively, secret-share an integer among a set of players. moreover, at small extra cost and using a distributed verifier proof, it can be shown in zero-knowledge that three shared integers a,b,c satisfy ab = c. this implies by known reductions non-interactive zero-knowledge proofs that a shared integer is in a given interval, or that one secret integer is larger than another. such primitives are useful, e.g., for supplying inputs to a multiparty computation protocol, such as an auction or an election. the protocols use various set-up assumptions, but do not require the random oracle model.
ate pairing on hyperelliptic curves. in this paper we show that the ate pairing, originally defined for elliptic curves, generalises to hyperelliptic curves and in fact to arbitrary algebraic curves. it has the following surprising properties: the loop length in miller's algorithm can be up to g times shorter than for the tate pairing, with g the genus of the curve, and the pairing is automatically reduced, i.e. no final exponentiation is needed.
a fast and key-efficient reduction of chosen-ciphertext to known-plaintext security. motivated by the quest for reducing assumptions in security proofs in cryptography, this paper is concerned with designing efficient symmetric encryption and authentication schemes based on any weak pseudorandom function (prf) which can be much more efficiently implemented than prfs. damgård and nielsen (crypto '02) have shown how to construct an efficient symmetric encryption scheme based on any weak prf that is provably secure against chosen-plaintext attacks. the main ingredient is a range-extension construction for weak prfs. by using well-known techniques, they also showed how their scheme can be made secure against the stronger chosen-ciphertext attacks.the results of our paper are three-fold. first, we give a range-extension construction for weak prfs that is optimal within a large and natural class of reductions (especially all known today). second, we propose a construction of a regular prf from any weak prf. third, these two results imply a (for long messages) much more efficient chosen-ciphertext secure encryption scheme than the one proposed by damgård and nielsen. the results also give answers to open questions posed by naor and reingold (crypto '98) and by damgård and nielsen.
sub-linear zero-knowledge argument for correctness of a shuffle. a shuffle of a set of ciphertexts is a new set of ciphertexts with the same plaintexts in permuted order. shuffles of homomorphic encryptions are a key component in mix-nets, which in turn are used in protocols for anonymization and voting. since the plaintexts are encrypted it is not directly verifiable whether a shuffle is correct, and it is often necessary to prove the correctness of a shuffle using a zero-knowledge proof or argument. in previous zero-knowledge shuffle arguments from the literature the communication complexity grows linearly with the number of ciphertexts in the shuffle. we suggest the first practical shuffle argument with sub-linear communication complexity. our result stems from combining previous work on shuffle arguments with ideas taken from probabilistically checkable proofs.
resistance against general iterated attacks. in this paper we study the resistance of a block cipher against a class of general attacks which we call "iterated attacks". this class includes some elementary versions of differential and linear cryptanalysis. we prove that we can upper bound the complexity of the attack by using decorrelation techniques. our main theorem enables to prove the security against these attacks (in our model) of some recently proposed block ciphers coconut98 and peanut98, as well as the aes candidate dfc.we outline that decorrelation to the order 2d is required for proving security against iterated attacks of order d.
universally composable multi-party computation using tamper-proof hardware. protocols proven secure within the universal composability (uc) framework satisfy strong and desirable security properties. unfortunately, it is known that within the "plain" model, secure computation of general functionalities without an honest majority is impossible. this has prompted researchers to propose various "setup assumptions" with which to augment the bare uc framework in order to bypass this severe negative result. existing setup assumptions seem to inherently require some trusted party (or parties) to initialize the setup in the real world.we propose a new setup assumption -- more along the lines of a physical assumption regarding the existence of tamper-proof hardware -- which also suffices to circumvent the impossibility result mentioned above. we suggest this assumption as potentially leading to an approach that might alleviate the need for trusted parties, and compare our assumption to those proposed previously.
an efficient protocol for secure two-party computation in the presence of malicious adversaries. check if we can apply woodruff's method to our protocol. we show an efficient secure two-party protocol, based on yao's construction, which provides security against malicious adversaries. yao's original protocol is only secure in the presence of semi-honest adversaries. security against malicious adversaries can be obtained by applying the compiler of goldreich, micali and wigderson (the "gmw compiler"). however, this approach does not seem to be very practical as it requires using generic zero-knowledge proofs.our construction is based on applying cut-and-choose techniques to the original circuit and inputs. security is proved according to the ideal/real simulation paradigm, and the proof is in the standard model (with no random oracle model or common reference string assumptions). the resulting protocol is computationally efficient: the only usage of asymmetric cryptography is for running o(1) oblivious transfers for each input bit (or for each bit of a statistical security parameter, whichever is larger). our protocol combines techniques from folklore (like cut-and-choose) along with new techniques for efficiently proving consistency of inputs. we remark that a naive implementation of the cut-and-choose technique with yao's protocol does not yield a secure protocol. this is the first paper to show how to properly implement these techniques, and to provide a full proof of security.our protocol can also be interpreted as a constant-round black-box reduction of secure two-party computation to oblivious transfer and perfectly-hiding commitments, or a black-box reduction of secure two-party computation to oblivious transfer alone, with a number of rounds which is linear in a statistical security parameter. these two reductions are comparable to kilian's reduction, which uses ot alone but incurs a number of rounds which is linear in the depth of the circuit [18].
predicting lattice reduction. despite their popularity, lattice reduction algorithms remain mysterious cryptanalytical tools. though it has been widely reported that they behave better than their proved worst-case theoretical bounds, no precise assessment has ever been given. such an assessment would be very helpful to predict the behaviour of lattice-based attacks, as well as to select keysizes for lattice-based cryptosystems. the goal of this paper is to provide such an assessment, based on extensive experiments performed with the ntl library. the experiments suggest several conjectures on the worst case and the actual behaviour of lattice reduction algorithms. we believe the assessment might also help to design new reduction algorithms overcoming the limitations of current algorithms.
evidence that xtr is more secure than supersingular elliptic curve cryptosystems. we show that finding an efficiently computable injective homomorphism from the xtr subgroup into the group of points over gf(p<sup>2</sup>) of a particular type of supersingular elliptic curve is at least as hard as solving the diffie&#x2013;hellman problem in the xtr subgroup. this provides strong evidence for a negative answer to the question posed by vanstone and menezes at the crypto 2000 rump session on the possibility of efficiently inverting the mov embedding into the xtr subgroup. as a side result we show that the decision diffie&#x2013;hellman problem in the group of points on this type of supersingular elliptic curves is efficiently computable, which provides an example of a group where the decision diffie&#x2013;hellman problem is simple, while the diffie&#x2013;hellman and discrete logarithm problems are presumably not. so-called distortion maps on groups of points on elliptic curves that play an important role in our cryptanalysis also lead to cryptographic applications of independent interest. these applications are an improvement of joux&#x2019;s one round protocol for tripartite diffie&#x2013;hellman key exchange and a non-refutable digital signature scheme that supports escrowable encryption. we also discuss the applicability of our methods to general elliptic curves defined over finite fields which includes a classification of elliptic curve groups where distortion maps exist.
zero-knowledge sets with short proofs. zero knowledge sets, introduced by micali, rabin and kilian in [17], allow a prover to commit to a secret set s in a way such that it can later prove, non interactively, statements of the form x ∈ s (or x ∉ s), without revealing any further information (on top of what explicitly revealed by the inclusion/exclusion statements above) on s, not even its size. later, chase et al. [5] abstracted away the micali, rabin and kilian's construction by introducing an elegant new variant of commitments that they called (trapdoor) mercurial commitments. using this primitive, it was shown in [5,4] how to construct zero knowledge sets from a variety of assumptions (both general and number theoretic). in this paper we introduce the notion of trapdoor q-mercurial commitments (qtmcs), a notion of mercurial commitment that allows the sender to commit to an ordered sequence of exactly q messages, rather than to a single one. following [17,5] we show how to construct zks from qtmcs and collision resistant hash functions. then, we present an efficient realization of qtmcs that is secure under the so called strong diffie hellman assumption, a number theoretic conjecture recently introduced by boneh and boyen in [3]. using our scheme as basic building block, we obtain a construction of zks that allows for proofs that are much shorter with respect to the best previously known implementations. in particular, for an appropriate choice of the parameters, our proofs are up to 33% shorter for the case of proofs of membership, and up to 73% shorter for the case of proofs of non membership.
binding elgamal: a fraud-detectable alternative to key-escrow proposals. we propose a concept for a worldwide information security infrastructure that protects law-abiding citizens, but not criminals, even if the latter use it fraudulently (i.e. when not complying with the agreed rules). it can be seen as a middle course between the inflexible but fraud-resistant kmi-proposal [8] and the flexible but non-fraud-resistant concept used in tis-cke [2]. our concept consists of adding binding data to the latter concept, which will not prevent fraud by criminals but makes it p t least detectable by third parties without the need of any secret information. in [19], we depict a worldwide framework in which this concept could present a security tool that is flexible enough to be incorporated in any national cryptography policy, on both the domestic and foreign use of cryptography. here, we present a construction for binding data for elgamal type public key encryption schemes. as a side result we show that a particular simplification in a multiuser version of elgamal does not affect its security.
precise concurrent zero knowledge. precise zero knowledge introduced by micali and pass (stoc'06) guarantees that the view of any verifier v can be simulated in time closely related to the actual (as opposed to worst-case) time spent by v in the generated view. we provide the first constructions of precise concurrent zero-knowledge protocols. our constructions have essentially optimal precision; consequently this improves also upon the previously tightest non-precise concurrent zero-knowledge protocols by kilian and petrank (stoc'01) and prabhakaran, rosen and sahai (focs'02) whose simulators have a quadratic worst-case overhead. additionally, we achieve a statistically-precise concurrent zero-knowledge property-which requires simulation of unbounded verifiers participating in an unbounded number of concurrent executions; as such we obtain the first (even non-precise) concurrent zero-knowledge protocols which handle verifiers participating in a super-polynomial number of concurrent executions.
strongly multiplicative ramp schemes from high degree rational points on curves. in this work we introduce a novel paradigm for the construction of ramp schemes with strong multiplication that allows the secret to be chosen in an extension field, whereas the shares lie in a base field. when applied to the setting of shamir's scheme, for example, this leads to a ramp scheme with strong multiplication from which protocols can be constructed for atomic secure multiplication with communication equal to a linear number of field elements in the size of the network. this is also achieved by the results from cramer, damgaard and de haan from eurocrypt 2007. however, our new ramp scheme has an improved privacy bound that is essentially optimal and leads to a significant mathematical simplification of the earlier results on atomic secure multiplication. as a result, by considering high degree rational points on algebraic curves, this can now be generalized to algebraic geometric ramp schemes with strong multiplication over a constant size field, which in turn leads to low communication atomic secure multiplication where the base field can now be taken constant, as opposed to earlier work.
protocols and lower bounds for failure localization in the internet. a secure failure-localization path-quality-monitoring (flpqm) protocols allows a sender to localize faulty links on a single path through a network to a receiver, even when intermediate nodes on the path behave adversarially. such protocols were proposed as tools that enable internet service providers to select high-performance paths through the internet, or to enforce contractual obligations. we give the first formal definitions of security for fl-pqm protocols and construct: 1. a simple fl-pqm protocol that can localize a faulty link every time a packet is not correctly delivered. this protocol's communication overhead is o(1) additional messages of length o(n) per packet (where n is the security parameter). 2. a more efficient fl-pqm protocol that can localize a faulty link when a noticeable fraction of the packets sent during some time period are not correctly delivered. the number of additional messages is an arbitrarily small fraction of the total number of packets. we also prove lower bounds for such protocols: 1. every secure fl-pqm protocol requires each intermediate node on the path to have some shared secret information (e.g. keys). 2. if secure fl-pqm protocols exist then so do one-way functions. 3. every black-box construction of a fl-pqm protocol from a random oracle that securely localizes every packet and adds at most o(log n) messages overhead per packet requires each intermediate node to invoke the oracle. these results show that implementing fl-pqm requires active cooperation (i.e. maintaining keys and agreeing on, and performing, cryptographic protocols) from all of the intermediate nodes along the path. this may be problematic in the internet, where links operate at extremely high speeds, and intermediate nodes are owned by competing business entities with little incentive to cooperate.
isogenies and the discrete logarithm problem in jacobians of genus 3 hyperelliptic curves. we describe the use of explicit isogenies to translate instances of the discrete logarithm problem from jacobians of hyperelliptic genus 3 curves to jacobians of non-hyperelliptic genus 3 curves, where they are vulnerable to faster index calculus attacks. we provide explicit formulae for isogenies with kernel isomorphic to (z/2z)3 (over an algebraic closure of the base field) for any hyperelliptic genus 3 curve over a field of characteristic not 2 or 3. these isogenies are rational for a positive fraction of all hyperelliptic genus 3 curves defined over a finite field of characteristic p > 3. subject to reasonable assumptions, our constructions give an explicit and efficient reduction of instances of the dlp from hyperelliptic to non-hyperelliptic jacobians for around 18.57% of all hyperelliptic genus 3 curves over a given finite field.
threshold rsa for dynamic and ad-hoc groups. we consider the use of threshold signatures in ad-hoc and dynamic groups such as manets ("mobile ad-hoc networks"). while the known threshold rsa signature schemes have several properties that make them good candidates for deployment in these scenarios, none of these schemes seems practical enough for realistic use in these highly-constrained environments. in particular, this is the case of the most efficient of these threshold rsa schemes, namely, the one due to shoup. our contribution is in presenting variants of shoup's protocol that overcome the limitations that make the original protocol unsuitable for dynamic groups. the resultant schemes provide the efficiency and flexibility needed in ad-hoc groups, and add the capability of incorporating new members (share-holders) to the group of potential signers without relying on central authorities. namely, any threshold of existing members can cooperate to add a new member. the schemes are efficient, fully non-interactive and do not assume broadcast.
on the security of 3gpp networks. later this year we shall see the release of the third generation partnership project (3gpp) specifications for wcdma - the first third generation standard for mobile communications. this 3g system combines elements of both a radical departure and a timid evolution from the 2g system known as gsm. it is radically different from gsm in having a wide-band cdma system for its air-interface, but it hangs on to the gsm/gprs core switching network with its map based signalling system. in this paper we consider the security features in wcdma, taking a critical look at where they depart from those in gsm, where they are still very much the same and how they may develop as the core switching network is replaced by an ip based infrastructure. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
the twin diffie-hellman problem and applications. we propose a new computational problem called the twin diffie-hellman problem. this problem is closely related to the usual (computational) diffie-hellman problem and can be used in many of the same cryptographic constructions that are based on the diffie-hellman problem. moreover, the twin diffie-hellman problem is at least as hard as the ordinary diffie-hellman problem. however, we are able to show that the twin diffie-hellman problem remains hard, even in the presence of a decision oracle that recognizes solutions to the problem -- this is a feature not enjoyed by the ordinary diffie-hellman problem. in particular, we show how to build a certain "trapdoor test" which allows us to effectively answer such decision oracle queries, without knowing any of the corresponding discrete logarithms. our new techniques have many applications. as one such application, we present a new variant of elgamal encryption with very short ciphertexts, and with a very simple and tight security proof, in the random oracle model, under the assumption that the ordinary diffie-hellman problem is hard. we present several other applications as well, including: a new variant of diffie and hellman's non-interactive key exchange protocol; a new variant of cramer-shoup encryption, with a very simple proof in the standard model; a new variant of boneh-franklin identity-based encryption, with very short ciphertexts; a more robust version of a password-authenticated key exchange protocol of abdalla and pointcheval.
new constructions for uc secure computation using tamper-proof hardware. the universal composability framework was introduced by canetti to study the security of protocols which are concurrently executed with other protocols in a network environment. unfortunately it was shown that in the so called plain model, a large class of functionalities cannot be securely realized. these severe impossibility results motivated the study of other models involving some sort of setup assumptions, where general positive results can be obtained. until recently, all the setup assumptions which were proposed required some trusted third party (or parties). katz recently proposed using a physical setup to avoid such trusted setup assumptions. in his model, the physical setup phase includes the parties exchanging tamper proof hardware tokens implementing some functionality. the tamper proof hardware is modeled so as to assume that the receiver of the token can do nothing more than observe its input/output characteristics. it is further assumed that the sender knows the program code of the hardware token which it distributed. based on the ddh assumption, katz gave general positive results for universally composable multi-party computation tolerating any number of dishonest parties making this model quite attractive. in this paper, we present new constructions for uc secure computation using tamper proof hardware (in a stronger model). our results represent an improvement over the results of katz in several directions using substantially different techniques. interestingly, our security proofs do not rely on being able to rewind the hardware tokens created by malicious parties. this means that we are able to relax the assumptions that the parties know the code of the hardware token which they distributed. this allows us to model real life attacks where, for example, a party may simply pass on the token obtained from one party to the other without actually knowing its functionality. furthermore, our construction models the interaction with the tamper-resistant hardware as a simple request-reply protocol. thus, we show that the hardware tokens used in our construction can be resettable. in fact, it suffices to use token which are completely stateless (and thus cannot execute a multiround protocol). our protocol is also based on general assumptions (namely enhanced trapdoor permutations).
secure communication in broadcast channels: the answer to franklin and wright's question. problems of secure communication and computation have been studied extensively in network models. goldreich, goldwasser, and linial, franklin and yung, and franklin and wright have initiated the study of secure communication and secure computation in multirecipient (broadcast) models. a "broadcast channel" (such as ethernet) enables one processor to send the same message--simultaneously and privately-- to a fixed subset of processors. in their eurocrypt '98 paper, franklin and wright have shown that if there are n broadcast lines between a sender and a receiver and there are at most t malicious (byzantine style) processors, then the condition n > t is necessary and sufficient for achieving efficient probabilisticly reliable and probabilisticly private communication. they also showed that if n > ⌈3t/2⌉ then there is an efficient protocol to achieve probabilisticly reliable and perfectly private communication. and they left open the question whether there exists an efficient protocol to achieve probabilisticly reliable and perfectly private communication when ⌈3t/2⌉ ≥ n > t. in this paper, by using a different authentication scheme, we will answer this question affirmatively and study related problems.
predicate encryption supporting disjunctions, polynomial equations, and inner products. predicate encryption is a new paradigm generalizing, among other things, identity-based encryption. in a predicate encryption scheme, secret keys correspond to predicates and ciphertexts are associated with attributes; the secret key skf corresponding to a predicate f can be used to decrypt a ciphertext associated with attribute i if and only if f(i) = 1. constructions of such schemes are currently known for relatively few classes of predicates. we construct such a scheme for predicates corresponding to the evaluation of inner products over zn (for some large integer n). this, in turn, enables constructions in which predicates correspond to the evaluation of disjunctions, polynomials, cnf/dnf formulae, or threshold predicates (among others). besides serving as a significant step forward in the theory of predicate encryption, our results lead to a number of applications that are interesting in their own right.
on the matsumoto and imai's human identification scheme. at eurocrypt'91, matsumoto and imai presented a human identification scheme for insecure channels, which is suitable for human ability of memorizing and processing a short secret. it prevents an intruder from peeping user in typing password on terminal connected to the central computer. however, in this paper, we are going to propose a new attack, called the replay challenge attack, where a malicious terminal pretends to be the host and replays the host's challenges to reveal the secret password. a modified scheme will be proposed to avoid this attack.
obfuscating point functions with multibit output. we construct obfuscators of point functions with multibit output and other related functions. a point function with multibit output returns a fixed string on a single input point and zero everywhere else. obfuscation of such functions has a useful application as a strong form of symmetric encryption which guarantees security even when the key has very low entropy: essentially, learning information about the plaintext is paramount to finding the key via exhaustive search on the key space. although the constructions appear to be simple and modular, their analysis turns out to be quite intricate. in particular, we uncover some weaknesses in the current definitions of obfuscation. one weakness is that current definitions do not guarantee security even under very weak forms of composition. we thus define a notion of obfuscation that is preserved under an appropriate composition operation. the constructions can use any obfuscator of point functions under the proposed definition. alternatively, they can use perfect one way (pow) functions with statistical indistinguishability, or with computational indistinguishability at the price of somewhat weaker security.
efficient non-interactive proof systems for bilinear groups. non-interactive zero-knowledge proofs and non-interactive witnessindistinguishable proofs have played a significant role in the theory of cryptography. however, lack of efficiency has prevented them from being used in practice. one of the roots of this inefficiency is that non-interactive zeroknowledge proofs have been constructed for general np-complete languages such as circuit satisfiability, causing an expensive blowup in the size of the statement when reducing it to a circuit. the contribution of this paper is a general methodology for constructing very simple and efficient non-interactive zero-knowledge proofs and non-interactive witness-indistinguishable proofs that work directly for groups with a bilinear map, without needing a reduction to circuit satisfiability. groups with bilinear maps have enjoyed tremendous success in the field of cryptography in recent years and have been used to construct a plethora of protocols. this paper provides non-interactive witness-indistinguishable proofs and non-interactive zero-knowledge proofs that can be used in connection with these protocols. our goal is to spread the use of non-interactive cryptographic proofs from mainly theoretical purposes to the large class of practical cryptographic protocols based on bilinear groups.
almost-everywhere secure computation. secure multi-party computation (mpc) is a central problem in cryptography. unfortunately, it is well known that mpc is possible if and only if the underlying communication network has very large connectivity -- in fact, ω(t), where t is the number of potential corruptions in the network. this impossibility result renders existing mpc results far less applicable in practice, since many deployed networks have in fact a very small degree. in this paper, we show how to circumvent this impossibility result and achieve meaningful security guarantees for graphs with small degree (such as expander graphs and several other topologies). in fact, the notion we introduce, which we call almost-everywhere mpc, building on the notion of almost-everywhere agreement due to dwork, peleg, pippenger and upfal, allows the degree of the network to be much smaller than the total number of allowed corruptions. in essence, our definition allows the adversary to implicitly wiretap some of the good nodes by corrupting sufficiently many nodes in the "neighborhood" of those nodes. we show protocols that satisfy our new definition, retaining both correctness and privacy for most nodes despite small connectivity, no matter how the adversary chooses his corruptions. instrumental in our constructions is a new model and protocol for the secure message transmission (smt) problem, which we call smt by public discussion, and which we use for the establishment of pairwise secure channels in limited connectivity networks.
collisions for the lps expander graph hash function. we analyse the hash function family based on walks in lps ramanujan graphs recently introduced by charles et al. we present an algorithm for finding collisions that runs in quasi-linear time in the length of the hashed value. a concrete instance of the hash function is considered, based on a 100-digit prime. a short collision is given, together with implementation details.
second preimage attacks on dithered hash functions. we develop a new generic long-message second preimage attack, based on combining the techniques in the second preimage attacks of dean [8] and kelsey and schneier [16] with the herding attack of kelsey and kohno [15]. we show that these generic attacks apply to hash functions using the merkle-damgård construction with only slightly more work than the previously known attack, but allow enormously more control of the contents of the second preimage found. additionally, we show that our new attack applies to several hash function constructions which are not vulnerable to the previously known attack, including the dithered hash proposal of rivest [25], shoup's uowhf[26] and the rox hash construction [2].we analyze the properties of the dithering sequence used in [25], and develop a time-memory tradeoff which allows us to apply our second preimage attack to a wide range of dithering sequences, including sequences which are much stronger than those in rivest's proposals. finally, we show that both the existing second preimage attacks [8,16] and our new attack can be applied even more efficiently to multiple target messages; in general, given a set of many target messages with a total of 2r message blocks, these second preimage attacks can find a second preimage for one of those target messages with no more work than would be necessary to find a second preimage for a single target message of 2r message blocks.
an implementation of the general number field sieve to compute discrete logarithms mod p. there are many cryptographic protocols the security of which depends on the difficulty of solving the discrete logarithm problem ([8], [9], [14], etc.). in [10] and [18] it was described how to apply the number field sieve algorithm to the discrete logarithm problem in prime fields. this resulted in the asymptotically fastest known discrete log algorithm for finite fields of p elements. very little is known about the behaviour of this algorithm in practice. in this report we write about our practical experience with our implementation of their algorithm whose first version was completed in october 1994 at the department of computer science at the universität des saarlandes.
a leakage-resilient mode of operation. a weak pseudorandom function (wprf) is a cryptographic primitive similar to --- but weaker than --- a pseudorandom function: for wprfs one only requires that the output is pseudorandom when queried on random inputs. we show that unlike "normal" prfs, wprfs are seed-incompressible, in the sense that the output of a wprf is pseudorandom even if a bounded amount of information about the key is leaked.as an application of this result we construct a simple mode of operation which --- when instantiated with any wprf --- gives a leakage-resilient stream-cipher. the implementation of such a cipher is secure against every side-channel attack, as long as the amount of information leaked per round is bounded, but overall can be arbitrary large. the construction is simpler than the previous one (dziembowski-pietrzak focs'08) as it only uses a single primitive (a wprf) in a straight forward manner.
key recovery on hidden monomial multivariate schemes. in this paper, we study the key recovery problem for the c* scheme and generalisations where the quadratic monomial of c* (the product of two linearized monomials) is replaced by a product of three or more linearized monomials. this problem has been further generalized to any system of multivariate polynomials hidden by two invertible linear maps and named the isomorphism of polynomials (ip) problem by patarin. some cryptosystems have been built on this apparently hard problem such as an authentication protocol proposed by patarin and a traitor tracing scheme proposed by billet and gilbert. here we show that if the hidden multivariate system is the projection of a quadratic monomial on a base finite field, as in c*, or a cubic (or higher) monomial as in the traitor tracing scheme, then it is possible to recover an equivalent secret key in polynomial time o(nd) where n is the number of variables and d is the degree of the public polynomials.
the one-round functions of the des generate the alternating group. in each of the 16 des rounds we have a permutation of 64-bitblocks. according to the corresponding key-block there are 248 possible permutations per round. in this paper we will prove that these permutations generate the alternating group. the main parts of the paper are the proof that the generated group is 3-transitive, and the application of a result from p. j. cameron based on the classification of finite simple groups. a corollary concerning n-round functions generalizes the result.
david and goliath commitments: uc computation for asymmetric parties using tamper-proof hardware. designing secure protocols in the universal composability (uc) framework confers many advantages. in particular, it allows the protocols to be securely used as building blocks in more complex protocols, and assists in understanding their security properties. unfortunately, most existing models in which universally composable computation is possible (for useful functionalities) require a trusted setup stage. recently, katz [eurocrypt '07] proposed an alternative to the trusted setup assumption: tamper-proof hardware. instead of trusting a third party to correctly generate the setup information, each party can create its own hardware tokens, which it sends to the other parties. each party is only required to trust that its own tokens are tamper-proof. katz designed a uc commitment protocol that requires both parties to generate hardware tokens. in addition, his protocol relies on a specific number-theoretic assumption. in this paper, we construct uc commitment protocols for "david" and "goliath": we only require a single party (goliath) to be capable of generating tokens. we construct a version of the protocol that is secure for computationally unbounded parties, and a more efficient version that makes computational assumptions only about david (we require only the existence of a one-way function). our protocols are simple enough to be performed by hand on david's side. these properties may allow such protocols to be used in situations which are inherently asymmetric in real-life, especially those involving individuals versus large organizations. classic examples include voting protocols (voters versus "the government") and protocols involving private medical data (patients versus insurance-agencies or hospitals).
towards key-dependent message security in the standard model. standard security notions for encryption schemes do not guarantee any security if the encrypted messages depend on the secret key. yet it is exactly the stronger notion of security in the presence of key-dependent messages (kdm security) that is required in a number of applications: most prominently, kdm security plays an important role in analyzing cryptographic multi-party protocols in a formal calculus. but although often assumed, the mere existence of kdm secure schemes is an open problem. the only previously known construction was proven secure in the random oracle model. we present symmetric encryption schemes that are kdm secure in the standard model (i.e., without random oracles). the price we pay is that we achieve only a relaxed (but still useful) notion of key-dependent message security. our work answers (at least partially) an open problem posed by black, rogaway, and shrimpton. more concretely, our contributions are as follows: 1. we present a (stateless) symmetric encryption scheme that is information-theoretically secure in face of a bounded number and length of encryptions for which the messages depend in an arbitrary way on the secret key. 2. we present a stateful symmetric encryption scheme that is computationally secure in face of an arbitrary number of encryptions for which the messages depend only on the respective current secret state/key of the scheme. the underlying computational assumption is minimal: we assume the existence of one-way functions. 3. we give evidence that the only previously known kdm secure encryption scheme cannot be proven secure in the standard model (i.e., without random oracles).
security/efficiency tradeoffs for permutation-based hashing. we provide attacks and analysis that capture a tradeoff, in the ideal-permutation model, between the speed of a permutation-based hash function and its potential security. we show that any 2n-bit to n-bit compression function will have unacceptable collision resistance it makes fewer than three n-bit permutation invocations, and any 3n-bit to 2n-bit compression function will have unacceptable security if it makes fewer than five n-bit permutation invocations. any rate-a hash function built from n-bit permutations can be broken, in the sense of finding preimages as well as collisions, in about n1-α queries, where n = 2n. our results provide guidance when trying to design or analyze a permutation-based hash function about the limits of what can possibly be done.
detection of algebraic manipulation with applications to robust secret sharing and fuzzy extractors. consider an abstract storage device σ(g) that can hold a single element x from a fixed, publicly known finite group g. storage is private in the sense that an adversary does not have read access to σ(g) at all. however, σ(g) is non-robust in the sense that the adversary can modify its contents by adding some offset δ ∈ g. due to the privacy of the storage device, the value δ can only depend on an adversary's a priori knowledge of x. we introduce a new primitive called an algebraic manipulation detection (amd) code, which encodes a source s into a value x stored on σ(g) so that any tampering by an adversary will be detected. we give a nearly optimal construction of amd codes, which can flexibly accommodate arbitrary choices for the length of the source s and security level. we use this construction in two applications: - we show how to efficiently convert any linear secret sharing scheme into a robust secret sharing scheme, which ensures that no unqualified subset of players can modify their shares and cause the reconstruction of some value s′ ≠ s. - we show how to build nearly optimal robust fuzzy extractors for several natural metrics. robust fuzzy extractors enable one to reliably extract and later recover random keys from noisy and non-uniform secrets, such as biometrics, by relying only on non-robust public storage. in the past, such constructions were known only in the random oracle model, or required the entropy rate of the secret to be greater than half. our construction relies on a randomly chosen common reference string (crs) available to all parties.
efficient sequential aggregate signed data. we generalize the concept of sequential aggregate signatures (sas), proposed by lysyanskaya, micali, reyzin, and shacham (lmrs) at eurocrypt 2004, to a new primitive called sequential aggregate signed data (sasd) that tries to minimize the total amount of transmitted data, rather than just signature length. we present sas and sasd schemes that offer numerous advantages over the lmrs scheme. most importantly, our schemes can be instantiated with uncertified claw-free permutations, thereby allowing implementations based on low-exponent rsa and factoring, and drastically reducing signing and verification costs. our schemes support aggregation of signatures under keys of different lengths, and the sasd scheme even has as little as 160 bits of bandwidth overhead. finally, we present a multi-signed data scheme that, when compared to the state-of-the-art multi-signature schemes, is the first scheme with non-interactive signature generation not based on pairings. all of our constructions are proved secure in the random oracle model based on families of claw-free permutations.
a practical attack on keeloq. keeloq is a lightweight block cipher with a 32-bit block size and a 64-bit key. despite its short key size, it is widely used in remote keyless entry systems and other wireless authentication applications. for example, authentication protocols based on keeloq are supposedly used by various car manufacturers in anti-theft mechanisms. this paper presents a practical key recovery attack against keeloq that requires 216 known plaintexts and has a time complexity of 244.5 keeloq encryptions. it is based on the slide attack and a novel approach to meet-in-the-middle attacks. the fully implemented attack requires 65 minutes to obtain the required data and 7.8 days of calculations on 64 cpu cores. a variant which requires 216 chosen plaintexts needs only 3.4 days on 64 cpu cores. using only 10 000 euro, an attacker can purchase a cluster of 50 dual core computers that will find the secret key in about two days. we investigated the way keeloq is intended to be used in practice and conclude that our attack can be used to subvert the security of real systems. an attacker can acquire chosen plaintexts in practice, and one of the two suggested key derivation schemes for keeloq allows to recover the master secret from a single key.
proving tight security for rabin-williams signatures. this paper proves "tight security in the random-oracle model relative to factorization" for the lowest-cost signature systems available today: every hash-generic signature-forging attack can be converted, with negligible loss of efficiency and effectiveness, into an algorithm to factor the public key. the most surprising system is the "fixed unstructured b-0 rabin-williams" system, which has a tight security proof despite hashing unrandomized messages.
on the indifferentiability of the sponge construction. in this paper we prove that the sponge construction introduced in [4] is indifferentiable from a random oracle when being used with a random transformation or a random permutation and discuss its implications. to our knowledge, this is the first time indifferentiability has been shown for a construction calling a random permutation (instead of an ideal compression function or ideal block cipher) and for a construction generating outputs of any length (instead of a fixed length).
isolated proofs of knowledge and isolated zero knowledge. we consider proof of knowledge protocols where the cheating prover may communicate with some external adversarial environment during the run of the proof. without additional setup assumptions, no witness hiding protocol can securely ensure that the prover knows a witness in this scenario. this is because the prover may just be forwarding messages between the environment and the verifier while the environment performs all the necessary computation. in this paper we consider an l-isolated prover, which is restricted to exchanging at most l bits of information with its environment. we introduce a new notion called l-isolated proofs of knowledge (l-ipok). these protocols securely ensure that an l-isolated prover knows the witness. to prevent the above-mentioned attack, an l-ipok protocol has to have communication complexity greater than l. we show that for any relation in np and any value l, there is an l-ipok protocol for that relation. in addition, the communication complexity of such a protocol only needs to be larger than l by a constant multiplicative factor.
kleptography: using cryptography against cryptography. the notion of a secretly embedded trapdoor with universal protection (setup) has been recently introduced. in this paper we extend the study of stealing information securely and subliminally from black-box cryptosystems. the setup mechanisms presented here, in contrast with previous ones, leak secret key information without using an explicit subliminal channel. this extends this area of threats, which we call "kleptography". we introduce new definitions of setup attacks (strong, regular, and weak setups) and the notion of m out of n leakage bandwidth. we show a strong attack which is based on the discrete logarithm problem. we then show how to use this setup to compromise the diffie-hellman key exchange protocol. we also strengthen the previous setup against rsa. the strong attacks employ the discrete logarithm as a one-way function (assuring what is called "forward secrecy"), public-key cryptography, and a technique which we call probabilistic bias removal.
new key-recovery attacks on hmac/nmac-md4 and nmac-md5. at crypto '07, fouque, leurent and nguyen presented full key-recovery attacks on hmac/nmac-md4 and nmac-md5, by extending the partial key-recovery attacks of contini and yin from asiacrypt '06. such attacks are based on collision attacks on the underlying hash function, and the most expensive stage is the recovery of the socalled outer key. in this paper, we show that the outer key can be recovered with near-collisions instead of collisions: near-collisions can be easier to find and can disclose more information. this improves the complexity of the fln attack on hmac/nmac-md4: the number of mac queries decreases from 288 to 272, and the number of md4 computations decreases from 295 to 277. we also improved the total complexity of the related-key attack on nmac-md5. moreover, our attack on nmac- md5 can partially recover the outer key without the knowledge of the inner key, which might be of independent interest.
hb: increasing the security and efficiency of hb. the innovative hb+ protocol of juels and weis [10] extends device authentication to low-cost rfid tags. however, despite the very simple on-tag computation there remain some practical problems with hb+ and despite an elegant proof of security against some limited active attacks, there is a simple man-in-the-middle attack due to gilbert et al. [8]. in this paper we consider improvements to hb+ in terms of both security and practicality. we introduce a new protocol that we denote random-hb#. this proposal avoids many practical drawbacks of hb+, remains provably resistant to attacks in the model of juels and weis, and at the same time is provably resistant to a broader class of active attacks that includes the attack of [8]. we then describe an enhanced variant called hb# which offers practical advantages over hb+.
cryptography without (hardly any) secrets ? the absolute privacy of the secret-keys associated with cryptographic algorithms has been the corner-stone of modern cryptography. still, in practice, keys do get compromised at times for a variety or reasons. a particularly disturbing loss of secrecy is as a result of side channel attacks. these attacks exploit the fact that every cryptographic algorithm is ultimately implemented on a physical device and such implementations enable `observations' which can be made and measured on secret data and secret keys. indeed, side channel observations can lead to information leakage about secret keys, which in turn can and have lead to complete breaks of systems which have been proved mathematically secure, without violating any of the underlying mathematical principles or assumptions. traditionally, such attacks have been followed by ad-hoc `fixes' which make particular implementation invulnerable to particular attacks, only to potentially be broken anew by new examples of side-channel attacks.in recent years, starting with the work on physically observable cryptography by [mr04] micali and reyzin, a new goal has been set to build a general theory of physical security against a large class of families of side channel attacks which one may call computational side-channel attacks. these include any side channel attack in which leakage of information on secrets occurs as a result of performing a computation on secrets. some well-known examples of such attacks include kocher's timing attacks [koc96] and power attacks [kjj99]. a basic defining feature of a computational side-channel attack, as put forth by [mr04] is that computation and only computation leaks information. namely, portions of memory which are not involved in computation do not leak information. a growing number of works [mr04, isw03, psp + 08, gkr08, dp08] have proposed cryptographic algorithms provably robust against computational side-channel attacks, by limiting in various ways the portions of the secret key which are involved in each step of the computation.in the work on one time programs this is taken to an extreme [gkr08] . goldwasser, tauman-kalai, and rothblum show how by using a new proposed type of secure-memory which never touches any secrets or data which is not ultimately fully revealed, it is possible to perform any secure computations which is provably secure against all computational side channel attacks.memory-attacks proposed by akavia, goldwasser, and vaikuntanathan [agv09] are an entirely very different family of side-channel attacks that are not included in the computational side-channel attack family, as they violate the basic premise of [mr04] that only computation leaks information. this class of attacks was inspired by (although not restricted to) the memory-freezing attack introduced recently by halderman et al. [hsh + 08] , where its is shown how to measure a significant fraction of the bits of secret keys if the keys were ever stored in a part of memory (e.g. dram), which could be accessed by an adversary even after the power of the machine has been turned off. thus, information leaks about portions of the secret key which may have never been involved in any computation. a memory-attack leaks a bounded number of bits computed as a result of applying an arbitrary function of bounded length (smaller than than the size of the secret key) to the content of the secret key of a cryptographic algorithm. naturally, this family of attacks is inherently parameterized and quantitative in nature, as if the attack would uncover the entire secret key at the outset, there would be no hope for any cryptography. the work of [agv09] exhibits a public-key encryption algorithm which is especially robust against memory-attacks. its security is based on the computationally intractability of the learning with errors (lwe) problem which is related to the intractability of approximating the length of the shortest vector in an integer lattice. finally, a new interesting variant on the idea of memory attacks, had been proposed by tauman-kalai etal [dtkl09] in their work on security with auximlary-inputs. they propose to replace the restriction of revealing a length shrinking function of the secret, to revealing functions of the secret which are exponentially hard to invert.in this talk we will survery this development, with special emphasis on the works of [gkr08, agv09, dtkl09].
order-preserving symmetric encryption. we initiate the cryptographic study of order-preserving symmetric encryption (ope), a primitive suggested in the database community by agrawal et al. (sigmod '04) for allowing efficient range queries on encrypted data. interestingly, we first show that a straightforward relaxation of standard security notions for encryption such as indistinguishability against chosen-plaintext attack (ind-cpa) is unachievable by a practical ope scheme. instead, we propose a security notion in the spirit of pseudorandom functions (prfs) and related primitives asking that an ope scheme look "as-random-as-possible" subject to the order-preserving constraint. we then design an efficient ope scheme and prove its security under our notion based on pseudorandomness of an underlying blockcipher. our construction is based on a natural relation we uncover between a random order-preserving function and the hypergeometric probability distribution. in particular, it makes black-box use of an efficient sampling algorithm for the latter.
hash functions and graphs with large girths. we propose and analyse an easily computable cryptographic hash function, for the purpose of signing long variable length texts, which is related to the construction of graphs with large girths.
cryptanalysis of mdc-2. we provide a collision attack and preimage attacks on the mdc-2 construction, which is a method (dating back to 1988) of turning an n-bit block cipher into a 2n-bit hash function. the collision attack is the first below the birthday bound to be described for mdc-2 and, with n = 128, it has complexity 2124.5, which is to be compared to the birthday attack having complexity 2128. the preimage attacks constitute new time/memory trade-offs; the most efficient attack requires time and space about 2 n , which is to be compared to the previous best known preimage attack of lai and massey (eurocrypt '92), having time complexity 23n/2 and space complexity 2 n/2, and to a brute force preimage attack having complexity 22n .
ecm on graphics cards. this paper reports record-setting performance for the elliptic-curve method of integer factorization: for example, 926.11 curves/second for ecm stage 1 with b 1 = 8192 for 280-bit integers on a single pc. the state-of-the-art gmp-ecm software handles 124.71 curves/second for ecm stage 1 with b 1 = 8192 for 280-bit integers using all four cores of a 2.4 ghz core 2 quad q6600.the extra speed takes advantage of extra hardware, specifically two nvidia gtx 295 graphics cards, using a new ecm implementation introduced in this paper. our implementation uses edwards curves, relies on new parallel addition formulas, and is carefully tuned for the highly parallel gpu architecture. on a single gtx 295 the implementation performs 41.88 million modular multiplications per second for a general 280-bit modulus. gmp-ecm, using all four cores of a q6600, performs 13.03 million modular multiplications per second.this paper also reports speeds on other graphics processors: for example, 2414 280-bit elliptic-curve scalar multiplications per second on an older nvidia 8800 gts (g80), again for a general 280-bit modulus. for comparison, the ches 2008 paper "exploiting the power of gpus for asymmetric cryptography" reported 1412 elliptic-curve scalar multiplications per second on the same graphics processor despite having fewer bits in the scalar (224 instead of 280), fewer bits in the modulus (224 instead of 280), and a special modulus (2224 ¿ 296 + 1).
auto-correlations and new bounds on the nonlinearity of boolean functions. it is a well known fact that the nonlinearity of a function f on the n-dimensional vector space vn is bounded from above by 2n-1- 21/2n-1. in cryptographic practice, nonlinear functions are usually constructively obtained in such a way that they support certain mathematical or cryptographic requirements. hence an important question is how to calculate the nonlinearity of a function when extra information is available. in this paper we address this question in the context of auto-correlations, and derive four (two upper and two lower) bounds on the nonlinearity of a function (see table 1). strengths and weaknesses of each bound are also examined. in addition, a few examples axe given to demonstrate the usefulness of the bounds in practical applications. we anticipate that these four bounds will be very useful in calculating the nonlinearity of a cryptographic function when certain extra information on the auto-correlations of the function is available.
realizing hash-and-sign signatures under standard assumptions. currently, there are relatively few instances of "hash-and-sign" signatures in the standard model. moreover, most current instances rely on strong and less studied assumptions such as the strong rsa and q-strong diffie-hellman assumptions. in this paper, we present a new approach for realizing hash-and-sign signatures in the standard model. in our approach, a signer associates each signature with an index i that represents how many signatures that signer has issued up to that point. then, to make use of this association, we create simple and efficient techniques that restrict an adversary which makes q signature requests to forge on an index no greater than $2^{\lceil \lg(q) \rceil} . finally, we develop methods for dealing with this restricted adversary. our approach requires that a signer maintains a small amount of state -- a counter of the number of signatures issued. we achieve two new realizations for hash-and-sign signatures respectively based on the rsa assumption and the computational diffie-hellman assumption in bilinear groups.
resettable zero-knowledge in the weak public-key model. a new public-key model for resettable zero-knowledge (rzk) protocols, which is an extension and generalization of the upperbounded public-key (upk) model introduced by micali and reyzin [eurocrypt' 01, pp. 373-393], is introduced and is named weak public-key (wpk) model. the motivations and applications of the wpk model are justified in the distributed smart-card/server setting and it seems more preferable in practice, especially in e-commerce over internet. in this wpk model a 3-round (optimal) black-box resettable zero-knowledge argument with concurrent soundness for np is presented assuming the security of rsa with large exponents against subexponential-time adversaries. our result improves micali and reyzin's result of resettable zero-knowledge argument with concurrent soundness for np in the upk model. note that although micali and reyzin' protocol satisfies concurrent soundness in the upk model, but it does not satisfy even sequential soundness in our wpk model. our protocol works in a somewhat "parallel repetition" manner to reduce the error probability and the black-box zero-knowledge simulator works in strict polynomial time rather than expected polynomial time. the critical tools used are: verifiable random functions introduced by micali, rabin and vadhan [focs'99, pp. 120-130], zap presented by dwork and naor [focs'00, pp. 283-293] and complexity leveraging introduced by canetti, goldreich, goldwasser and micali [stoc'00, pp. 235-244].
resettably secure computation. the notion of resettable zero-knowledge (rzk) was introduced by canetti, goldreich, goldwasser and micali (focs'01) as a strengthening of the classical notion of zero-knowledge. a rzk protocol remains zero-knowledge even if the verifier can reset the prover back to its initial state anytime during the protocol execution and force it to use the same random tape again and again. following this work, various extensions of this notion were considered for the zero-knowledge and witness indistinguishability functionalities.in this paper, we initiate the study of resettability for more general functionalities. we first consider the setting of resettable two-party computation where a party (called the user) can reset the other party (called the smartcard) anytime during the protocol execution. after being reset, the smartcard comes back to its original state and thus the user has the opportunity to start interacting with it again (knowing that the smartcard will use the same set of random coins). in this setting, we show that it is possible to secure realize all ppt computable functionalities under the most natural (simulation based) definition. thus our results show that in cryptographic protocols, the reliance on randomness and the ability to keep state can be made significantly weaker. our simulator for the aforementioned resettable two-party computation protocol (inherently) makes use of non-black box techniques. second, we provide a construction of simultaneous resettable multi-party computation with an honest majority (where the adversary not only controls a minority of parties but is also allowed to reset any number of parties at any point). interestingly, all our results are in the plain model.
asymmetric group key agreement. a group key agreement (gka) protocol allows a set of users to establish a common secret via open networks. observing that a major goal of gkas for most applications is to establish a confidential channel among group members, we revisit the group key agreement definition and distinguish the conventional (symmetric) group key agreement from asymmetric group key agreement (asgka) protocols. instead of a common secret key, only a shared encryption key is negotiated in an asgka protocol. this encryption key is accessible to attackers and corresponds to different decryption keys, each of which is only computable by one group member. we propose a generic construction of one-round asgkas based on a new primitive referred to as aggregatable signature-based broadcast (asbb), in which the public key can be simultaneously used to verify signatures and encrypt messages while any signature can be used to decrypt ciphertexts under this public key. using bilinear pairings, we realize an efficient asbb scheme equipped with useful properties. following the generic construction, we instantiate a one-round asgka protocol tightly reduced to the decision bilinear diffie-hellman exponentiation (bdhe) assumption in the standard model.
adaptive security in broadcast encryption systems (with short ciphertexts). we present new techniques for achieving adaptive security in broadcast encryption systems. previous work on fully collusion resistant broadcast encryption systems with very short ciphertexts was limited to considering only static security.first, we present a new definition of security that we call semi-static security and show a generic "two-key" transformation from semi-statically secure systems to adaptively secure systems that have comparable-size ciphertexts. using bilinear maps, we then construct broadcast encryption systems that are semi-statically secure in the standard model and have constant-size ciphertexts. our semi-static constructions work when the number of indices or identifiers in the system is polynomial in the security parameter.for identity-based broadcast encryption, where the number of potential indices or identifiers may be exponential, we present the first adaptively secure system with sublinear ciphertexts. we prove security in the standard model.
divisible e-cash systems can be truly anonymous. this paper presents an off-line divisible e-cash scheme where a user can withdraw a divisible coin of monetary value 2 l that he can parceled and spend anonymously and unlinkably. we present the construction of a security tag that allows to protect the anonymity of honest users and to revoke anonymity only in case of cheat for protocols based on a binary tree structure without using a trusted third party. this is the first divisible e-cash scheme that provides both full unlinkability and anonymity without requiring a trusted third party.
range extension for weak prfs; the good, the bad, and the ugly. we investigate a general class of (black-box) constructions for range extension of weak pseudorandom functions: a construction based on m independent functions f 1,...,f m is given by a set of strings over {1,...,m}*, where for example $\{\langle{2}\rangle, \langle{1,2}\rangle\}$ corresponds to the function x ¿[f 2(x),f 2(f 1(x))]. all efficient constructions for range expansion of weak pseudorandom functions that we are aware of are of this form.we completely classify such constructions as good, bad or ugly, where the good constructions are those whose security can be proven via a black-box reduction, the bad constructions are those whose insecurity can be proven via a black-box reduction, and the ugly constructions are those which are neither good nor bad.our classification shows that the range expansion from [10] is optimal, in the sense that it achieves the best possible expansion (2 m ¿ 1 when using m keys).along the way we show that for weak quasirandom functions (i.e. in the information theoretic setting), all constructions which are not bad --- in particular all the ugly ones --- are secure.
cryptanalysis on hmac/nmac-md5 and md5-mac. in this paper, we present the first distinguishing attack on hmac and nmac based on md5 without related keys, which distinguishes the hmac/nmac-md5 from hmac/nmac with a random function. the attack needs 297 queries, with a success probability 0.87, while the previous distinguishing attack on hmac-md5 reduced to 33 rounds takes 2126.1 messages with a success rate of 0.92. furthermore, we give distinguishing and partial key recovery attacks on mdx-mac based on md5. the mdx-mac was proposed by preneel and van oorschot in crypto'95 which uses three subkeys derived from the initial key. we are able to recover one 128-bit subkey with 297 queries.
secure computation from random error correcting codes. secure computation consists of protocols for secure arithmetic: secret values are added and multiplied securely by networked processors. the striking feature of secure computation is that security is maintained even in the presence of an adversary who corrupts a quorum of the processors and who exercises full, malicious control over them. one of the fundamental primitives at the heart of secure computation is secret-sharing. typically, the required secret-sharing techniques build on shamir's scheme, which can be viewed as a cryptographic twist on the reed-solomon error correcting code. in this work we further the connections between secure computation and error correcting codes. we demonstrate that threshold secure computation in the secure channels model can be based on arbitrary codes. for a network of size n, we then show a reduction in communication for secure computation amounting to a multiplicative logarithmic factor (in n) compared to classical methods for small, e.g., constant size fields, while tolerating $t players to be corrupted, where ¿> 0 can be arbitrarily small. for large networks this implies considerable savings in communication. our results hold in the broadcast/negligible error model of rabin and ben-or, and complement results from crypto 2006 for the zero-error model of ben-or, goldwasser and wigderson (bgw). our general theory can be extended so as to encompass those results from crypto 2006 as well. we also present a new method for constructing high information rate ramp schemes based on arbitrary codes, and in particular we give a new construction based on algebraic geometry codes.
atomic secure multi-party multiplication with low communication. we consider the standard secure multi-party multiplication protocol due to m. rabin. this protocol is based on shamir's secret sharing scheme and it can be viewed as a practical variation on one of the central techniques in the foundational results of ben-or, goldwasser, and wigderson and chaum, crépeau, and damgaard on secure multi-party computation. rabin's idea is a key ingredient to virtually all practical protocols in threshold cryptography.given a passive t-adversary in the secure channels model with synchronous communication, for example, secure multiplication of two secret-shared elements from a finite field k based on this idea uses one communication round and has the network exchange o(n 2) field elements, if t = ¿(n) and t < n/2 and if n is the number of players. this is because each of o(n) players must perform shamir secret sharing as part of the protocol. this paper demonstrates that under a few restrictions much more efficient protocols are possible; even at the level of a single multiplication.we demonstrate a twist on rabin's idea that enables one-round secure multiplication with just o(n) bandwidth in certain settings, thus reducing it from quadratic to linear. the ideas involved can additionally be employed in the evaluation of arithmetic circuits, where under appropriate circumstances similar efficiency gains can be obtained.
non-wafer-scale sieving hardware for the nfs: another attempt to cope with 1024-bit. significant progress in the design of special purpose hardware for supporting the number field sieve (nfs) has been made. from a practical cryptanalytic point of view, however, none of the published proposals for coping with the sieving step is satisfying. even for the best known designs, the technological obstacles faced for the parameters expected for a 1024-bit rsa modulus are significant.below we present a new hardware design for implementing the sieving step. the suggested chips are of moderate size and the inter-chip communication does not seem unrealistic. according to our preliminary analysis of the 1024-bit case, we expect the new design to be about 2 to 3.5 times slower than twirl (a wafer-scale design). due to the more moderate technological requirements, however, from a practical cryptanalytic point of view the new design seems to be no less attractive than twirl.
round-efficient secure computation in point-to-point networks. essentially all work studying the round complexity of secure computation assume broadcast as an atomic primitive. protocols constructed under this assumption tend to have very poor round complexity when compiled for a point-to-point network due to the high overhead of emulating each invocation of broadcast. this problem is compounded when broadcast is used in more than one round of the original protocol due to the complexity of handling sequential composition (when using round-efficient emulation of broadcast).we argue that if the goal is to optimize round complexity in point-to-point networks, then it is preferable to design protocols -- assuming a broadcast channel -- minimizing the number of rounds in which broadcast is used rather than minimizing the total number of rounds. with this in mind, we present protocols for secure computation in a number of settings that use only a single round of broadcast. in all cases, we achieve optimal security threshold for adaptive adversaries, and obtain protocols whose round complexity (in a point-to-point network) improves on prior work.
on the security of cryptosystems with quadratic decryption: the nicest cryptanalysis. we describe the first polynomial time chosen-plaintext total break of the nice family of cryptosystems based on ideal arithmetic in imaginary quadratic orders, introduced in the late 90's by hartmann, paulus and takagi [hpt99]. the singular interest of these encryption schemes is their natural quadratic decryption time procedure that consists essentially in applying euclid's algorithm. the only current specific cryptanalysis of these schemes is jaulmes and joux's chosen-ciphertext attack to recover the secret key [jj00]. originally, hartmann et al. claimed that the security against a total break attack relies only on the difficulty of factoring the public discriminant $\delta_q=-pq^2$, although the public key was also composed of a specific element of the class group of the order of discriminant δ q , which is crucial to reach the quadratic decryption complexity. in this article, we propose a drastic cryptanalysis which factors δ q (and hence recovers the secret key), only given this element, in cubic time in the security parameter. as a result, performing our cryptanalysis on a cryptographic example takes less than a second on a standard pc.
feistel networks made public, and applications. feistel network, consisting of a repeated application of the feistel transform, gives a very convenient and popular method for designing "cryptographically strong" permutations from corresponding "cryptographically strong" functions. up to now, all usages of the feistel network, including the celebrated luby-rackoff's result, critically rely on (a) the (pseudo)randomness of round functions; and (b) the secrecy of (at least some of) the intermediate round values appearing during the feistel computation. moreover, a small constant number of feistel rounds was typically sufficient to guarantee security under assumptions (a) and (b). in this work we consider several natural scenarios where at least one of the above assumptions does not hold, and show that a constant, or even logarithmic number of rounds is provably insufficient to handle such applications, implying that a new method of analysis is needed.on a positive side, we develop a new combinatorial understanding of feistel networks, which makes them applicable to situations when the round functions are merely unpredictable rather than (pseudo)random and/or when the intermediate round values may be leaked to the adversary (either through an attack or because the application requires it). in essence, our results show that in any such scenario a super-logarithmic number of feistel rounds is necessary and sufficient to guarantee security.of independent interest, our technique yields a novel domain extension method for messages authentication codes and other related primitives, settling a question studied by an and bellare in crypto 1999.
cryptanalysis of sflash with slightly modified parameters. sflash is a signature scheme which belongs to a family of multivariate schemes proposed by patarin et al. in 1998 [9]. the sflash scheme itself has been designed in 2001 [8] and has been selected in 2003 by the nessie european consortium [6] as the best known solution for implementation on low cost smart cards. in this paper, we show that slight modifications of the parameters of sflash within the general family initially proposed renders the scheme insecure. the attack uses simple linear algebra, and allows to forge a signature for an arbitrary message in a question of minutes for practical parameters, using only the public key. although sflash itself is not amenable to our attack, it is worrying to observe that no rationale was ever offered for this "lucky" choice of parameters.
ideal multipartite secret sharing schemes. multipartite secret sharing schemes are those having a multipartite access structure, in which the set of participants is divided into several parts and all participants in the same part play an equivalent role. several particular families of multipartite schemes, such as the weighted threshold schemes, the hierarchical and the compartmented schemes, and the ones with bipartite or tripartite access structure have been considered in the literature. the characterization of the access structures of ideal secret sharing schemes is one of the main open problems in secret sharing. in this work, the characterization of ideal multipartite access structures is studied with all generality. our results are based on the well-known connections between ideal secret sharing schemes and matroids. one of the main contributions of this paper is the application of discrete polymatroids to secret sharing. they are proved to be a powerful tool to study the properties of multipartite matroids. in this way, we obtain some necessary conditions and some sufficient conditions for a multipartite access structure to be ideal.our results can be summarized as follows. first, we present a characterization of matroid-related multipartite access structures in terms of discrete polymatroids. as a consequence of this characterization, a necessary condition for a multipartite access structure to be ideal is obtained. second, we use linear representations of discrete polymatroids to characterize the linearly representable multipartite matroids. in this way we obtain a sufficient condition for a multipartite access structure to be ideal. finally, we apply our general results to obtain a complete characterization of ideal tripartite access structures, which was until now an open problem.
non-trivial black-box combiners for collision-resistant hash-functions don't exist. a (k,¿)-robust combiner for collision-resistant hash-functions is a construction which from ¿ hash-functions constructs a hash-function which is collision-resistant if at least k of the components are collision-resistant. one trivially gets a (k,¿)-robust combiner by concatenating the output of any ¿¿ k + 1 of the components, unfortunately this is not very practical as the length of the output of the combiner is quite large. we show that this is unavoidable as no black-box (k,¿)-robust combiner whose output is significantly shorter than what can be achieved by concatenation exists. this answers a question of boneh and boyen (crypto'06).
the power of proofs-of-possession: securing multiparty signatures against rogue-key attacks. multiparty signature protocols need protection against rogue-key attacks, made possible whenever an adversary can choose its public key(s) arbitrarily. for many schemes, provable security has only been established under the knowledge of secret key (kosk) assumption where the adversary is required to reveal the secret keys it utilizes. in practice, certifying authorities rarely require the strong proofs of knowledge of secret keys required to substantiate the kosk assumption. instead, proofs of possession (pops) are required and can be as simple as just a signature over the certificate request message. we propose a general registered key model, within which we can model both the kosk assumption and in-use pop protocols. we show that simple pop protocols yield provable security of boldyreva's multisignature scheme [11], the lossw multisignature scheme [28], and a 2-user ring signature scheme due to bender, katz, and morselli [10]. our results are the first to provide formal evidence that pops can stop rogue-key attacks.
endomorphisms for faster elliptic curve cryptography on a large class of curves. efficiently computable homomorphisms allow elliptic curve point multiplication to be accelerated using the gallant-lambert- vanstone (glv) method. we extend results of iijima, matsuo, chao and tsujii which give such homomorphisms for a large class of elliptic curves by working over ${\mathbb f}_{p^2}$ and demonstrate that these results can be applied to the glv method.in general we expect our method to require about 0.75 the time of previous best methods (except for subfield curves, for which frobenius expansions can be used). we give detailed implementation results which show that the method runs in between 0.70 and 0.84 the time of the previous best methods for elliptic curve point multiplication on general curves.
oblivious-transfer amplification. oblivious transfer (ot) is a primitive of paramount importance in cryptography or, more precisely, two- and multi-party computation due to its universality. unfortunately, ot cannot be achieved in an unconditionally secure way for both parties from scratch. therefore, it is a natural question what information-theoretic primitives or computational assumptions ot can be based on.the results in our paper are threefold. first, we give an optimal proof for the standard protocol to realize unconditionally secure ot from a weak variant of ot called universal ot, for which a malicious receiver can virtually obtain any possible information he wants, as long as he does not get all the information. this result is based on a novel distributed leftover hash lemma which is of independent interest.second, we give conditions for when ot can be obtained from a faulty variant of ot called weak ot, for which it can occur that any of the parties obtains too much information, or the result is incorrect. these bounds and protocols, which correct on previous results by damgård et. al., are of central interest since in most known realizations of ot from weak primitives, such as noisy channels, a weak ot is constructed first.finally, we carry over our results to the computational setting and show how a weak ot that is sometimes incorrect and is only mildly secure against computationally bounded adversaries can be strengthened.
generic and practical resettable zero-knowledge in the bare public-key model. we present a generic construction for constant-round concurrsound resettable zero-knowledge (rzk-cs) arguments for $\mathcal{np}$ in the bare public-key (bpk) model under any (sub-exponentially strong) one-way function (owf), which is a traditional assumption in this area. the generic construction in turn allows round-optimal implementation for $\mathcal{np}$ still under general assumptions, and can be converted into a highly practical instantiation (under specific number-theoretic assumptions) for any language admitting σ-protocols. further, the rzk-cs arguments developed in this work also satisfy a weak (black-box) concurrent knowledge-extractability property as proofs of knowledge, in which case some super-polynomial-time assumption is intrinsic.
efficient two party and multi party computation against covert adversaries. recently, aumann and lindell introduced a new realistic security model for secure computation, namely, security against covert adversaries. the main motivation was to obtain secure computation protocols which are efficient enough to be usable in practice. aumann and lindell presented an efficient two party computation protocol secure against covert adversaries. they were able to utilize cut and choose techniques rather than relying on expensive zero knowledge proofs. in this paper, we design an efficient multi-party computation protocol in the covert adversary model which remains secure even if a majority of the parties are dishonest. we also substantially improve the two-party protocol of aumann and lindell. our protocols avoid general np-reductions and only make a black box use of efficiently implementable cryptographic primitives. our two-party protocol is constant-round while the multi-party one requires a logarithmic (in number of parties) number of rounds of interaction between the parties. our protocols are secure as per the standard simulation-based definitions of security. although our main focus is on designing efficient protocols in the covert adversary model, the techniques used in our two party case directly generalize to improve the efficiency of two party computation protocols secure against standard malicious adversaries.
finding preimages in full md5 faster than exhaustive search. in this paper, we present the first cryptographic preimage attack on the full md5 hash function. this attack, with a complexity of 2116.9, generates a pseudo-preimage of md5 and, with a complexity of 2123.4, generates a preimage of md5. the memory complexity of the attack is 245 ×11 words. our attack is based on splice-and-cut and local-collision techniques that have been applied to step-reduced md5 and other hash functions. we first generalize and improve these techniques so that they can be more efficiently applied to many hash functions whose message expansions are a permutation of message-word order in each round. we then apply these techniques to md5 and optimize the attack by considering the details of md5 structure.
zero knowledge and soundness are symmetric. we give a complexity-theoretic characterization of the class of problems in np having zero-knowledge argument systems. this characterization is symmetric in its treatment of the zero knowledge and the soundness conditions, and thus we deduce that the class of problems in np ¿ conp having zero-knowledge arguments is closed under complement. furthermore, we show that a problem in np has a statistical zero-knowledge argument system if and only if its complement has a computational zero-knowledge proof system. what is novel about these results is that they are unconditional, i.e., do not rely on unproven complexity assumptions such as the existence of one-way functions.our characterization of zero-knowledge arguments also enables us to prove a variety of other unconditional results about the class of problems in np having zero-knowledge arguments, such as equivalences between honest-verifier and malicious-verifier zero knowledge, private coins and public coins, inefficient provers and efficient provers, and non-black-box simulation and black-box simulation. previously, such results were only known unconditionally for zero-knowledge proof systems, or under the assumption that one-way functions exist for zero-knowledge argument systems.
breaking rsa generically is equivalent to factoring. we show that a generic ring algorithm for breaking rsa in ¿ n can be converted into an algorithm for factoring the corresponding rsa-modulus n. our results imply that any attempt at breaking rsa without factoring n will be non-generic and hence will have to manipulate the particular bit-representation of the input in ¿ n . this provides new evidence that breaking rsa may be equivalent to factoring the modulus.
efficient two-party secure computation on committed inputs. we present an efficient construction of yao's "garbled circuits" protocol for securely computing any two-party circuit on committed inputs. the protocol is secure in a universally composable way in the presence of malicious adversaries under the decisional composite residuosity (dcr) and strong rsa assumptions, in the common reference string model. the protocol requires a constant number of rounds (four-five in the standard model, two-three in the random oracle model, depending on whether both parties receive the output), o(|c|) modular exponentiations per player, and a bandwidth of o(|c|) group elements, where |c| is the size of the computed circuit.our technical tools are of independent interest. we propose a homomorphic, semantically secure variant of the camenisch-shoup verifiable cryptosystem, which uses shorter keys, is unambiguous (it is infeasible to generate two keys which successfully decrypt the same ciphertext), and allows efficient proofs that a committed plaintext is encrypted under a committed key.our second tool is a practical four-round (two-round in rom) protocol for committed oblivious transfer on strings (string-cot) secure against malicious participants. the string-cot protocol takes a few exponentiations per player, and is uc-secure under the dcr assumption in the common reference string model. previous protocols of comparable efficiency achieved either committed ot on bits, or standard (non-committed) ot on strings.
chosen-prefix collisions for md5 and colliding x.509 certificates for different identities. we present a novel, automated way to find differential paths for md5. as an application we have shown how, at an approximate expected cost of 250 calls to the md5 compression function, for any two chosen message prefixes p and p¿, suffixes s and s¿ can be constructed such that the concatenated values p||s and p¿||s¿ collide under md5. although the practical attack potential of this construction of chosen-prefix collisions is limited, it is of greater concern than random collisions for md5. to illustrate the practicality of our method, we constructed two md5 based x.509 certificates with identical signatures but different public keys and different distinguished name fields, whereas our previous construction of colliding x.509 certificates required identical name fields. we speculate on other possibilities for abusing chosen-prefix collisions. more details than can be included here can be found on www.win.tue.nl/hashclash/chosenprefixcollisions/ .
on the security of padding-based encryption schemes - or - why we cannot prove oaep secure in the standard model. we investigate the security of "padding-based" encryption schemes in the standard model. this class contains all public-key encryption schemes where the encryption algorithm first applies some invertible public transformation to the message (the "padding"), followed by a trapdoor permutation. in particular, this class contains oaep and its variants.our main result is a black-box impossibility result showing that one cannot prove any such padding-based scheme chosen-ciphertext secure even assuming the existence of ideal trapdoor permutations. the latter is a strong ideal abstraction of trapdoor permutations which inherits all security properties of uniform random permutations.
the collision intractability of mdc-2 in the ideal-cipher model. we provide the first proof of security for mdc-2, the most well-known construction for turning an n-bit blockcipher into a 2n-bit cryptographic hash function. our result, which is in the ideal-cipher model, shows that mdc-2, when built from a blockcipher having blocklength and keylength n, has security much better than that delivered by any hash function that has an n-bit output. when the blocklength and keylength are n = 128 bits, as with mdc-2 based on aes-128, an adversary that asks fewer than 274.9 queries usually cannot find a collision.
smashing squash-0. at the rfid security workshop 2007, adi shamir presented a new challenge-response protocol well suited for rfids, although based on the rabin public-key cryptosystem. this protocol, which we call squash-0, was using a linear mixing function which was subsequently withdrawn. essentially, we mount an attack against squash-0 with full window which could be used as a "known random coins attack" against rabin-saep. we then extend it for squash-0 with arbitrary window. we apply it with the proposed modulus 21 277¿ 1 to run a key recovery attack using 1 024 chosen challenges. since the security arguments equally apply to the final version of squash and to squash-0, we challenge the blame-game argument for the security of squash. nevertheless, our attacks are inefficient when using non-linear mixing so the security of squash remains open.
conditional computational entropy, or toward separating pseudoentropy from compressibility. we study conditional computational entropy: the amount of randomness a distribution appears to have to a computationally bounded observer who is given some correlated information. by considering conditional versions of hill entropy (based on indistinguishability from truly random distributions) and yao entropy (based on incompressibility), we obtain: a separation between conditional hill and yao entropies (which can be viewed as a separation between the traditional hill and yao entropies in the shared random string model, improving on wee's 2004 separation in the random oracle model); the first demonstration of a distribution from which extraction techniques based on yao entropy produce more pseudorandom bits than appears possible by the traditional hill-entropy-based techniques; a new, natural notion of unpredictability entropy, which implies conditional yao entropy and thus allows for known extraction and hardcore bit results to be stated and used more generally.
revisiting the efficiency of malicious two-party computation. in a recent paper mohassel and franklin study the efficiency of secure two-party computation in the presence of malicious behavior. their aim is to make classical solutions to this problem, such as zero-knowledge compilation, more efficient. the authors provide several schemes which are the most efficient to date. we propose a modification to their main scheme using expanders. our modification asymptotically improves at least one measure of efficiency of all known schemes. we also point out an error, and improve the analysis of one of their schemes.
a new mode of operation for block ciphers and length-preserving macs. we propose a new mode of operation, enciphered cbc, for domain extension of length-preserving functions (like block ciphers), which is a variation on the popular cbc mode of operation. our new mode is twice slower than cbc, but has many (property-preserving) properties not enjoyed by cbc and other known modes. most notably, it yields the first constant-rate variable input length (vil) mac from any length preserving fixed input length (fil) mac. this answers the question of dodis and puniya from eurocrypt 2007. further, our mode is a secure domain extender for prfs (with basically the same security as encrypted cbc). this provides a hedge against the security of the block cipher: if the block cipher is pseudorandom, one gets a vil-prf, while if it is "only" unpredictable, one "at least" gets a vil-mac. additionally, our mode yields a vil random oracle (and, hence, a collision-resistant hash function) when instantiated with length-preserving random functions, or even random permutations (which can be queried from both sides). this means that one does not have to re-key the block cipher during the computation, which was critically used in most previous constructions (analyzed in the ideal cipher model).
cryptanalysis of the sidelnikov cryptosystem. we present a structural attack against the sidelnikov cryptosystem [8]. the attack creates a private key from a given public key. its running time is subexponential and is effective if the parameters of the reed-muller code allow for efficient sampling of minimum weight codewords. for example, the length 2048, 3rd-order reed-muller code as proposed in [8] takes roughly an hour to break on a stock pc using the presented method.
simulation without the artificial abort: simplified proof and improved concrete security for waters' ibe scheme. waters' variant of the boneh-boyen ibe scheme is attractive because of its efficency, applications, and security attributes, but suffers from a relatively complex proof with poor concrete security. this is due in part to the proof's "artificial abort" step, which has then been inherited by numerous derivative works. it has often been asked whether this step is necessary.we show that it is not, providing a new proof that eliminates this step. the new proof is not only simpler than the original one but offers better concrete security for important ranges of the parameters. as a result, one can securely use smaller groups, resulting in significant efficiency improvements.
instance-dependent verifiable random functions and their application to simultaneous resettability. we introduce a notion of instance-dependent verifiable random functions (instd-vrfs for short). informally, an instd-vrf is, in some sense, a verifiable random function [23] with a special public key, which is generated via a (possibly)interactive protocol and contains an instance y ¿ l ¿ {0,1}* for a specific np language l, but the security requirements on such a function are relaxed: we only require the pseudorandomness property when y ¿ l and only require the uniqueness property when y ¿ l, instead of requiring both pseudorandomness and uniqueness to hold simultaneously. we show that this notion can be realized under standard assumption.our motivation is the conjecture posed by barak et al.[2], which states there exist resettably-sound resettable zero knowledge arguments for np. the instance-dependent verifiable random functions is a powerful tool to tackle this problem. we first use them to obtain two interesting instance-dependent argument systems from the barak's public-coin bounded concurrent zero knowledge argument [1], and then, we 1 construct the first (constant round) zero knowledge arguments for np enjoying a certain simultaneous resettability under standard hardness assumptions in the plain model, which we call bounded-class resettable zk arguments with weak resettable-soundness though the malicious party (prover or verifier) in such system is limited to a kind of bounded resetting attack, we put no restrictions on the number of the total resets made by malicious party. 1 show that, under standard assumptions, if there exist public-coin concurrent zero knowledge arguments for np, there exist the resettably-sound resetable zero knowledge arguments for np.
a public key encryption scheme secure against key dependent chosen plaintext and adaptive chosen ciphertext attacks. recently, at crypto 2008, boneh, halevi, hamburg, and ostrovsky (bhho) solved the long-standing open problem of "circular encryption," by presenting a public key encryption scheme and proving that it is semantically secure against key dependent chosen plaintext attack (kdm-cpa security) under standard assumptions (and without resorting to random oracles). however, they left as an open problem that of designing an encryption scheme that simultaneously provides security against both key dependent chosen plaintext and adaptive chosen ciphertext attack (kdm-cca2 security). in this paper, we solve this problem. first, we show that by applying the naor-yung "double encryption" paradigm, one can combine any kdm-cpa secure scheme with any (ordinary) cca2 secure scheme, along with an appropriate non-interactive zero-knowledge proof, to obtain a kdm-cca2 secure scheme. second, we give a concrete instantiation that makes use the above kdm-cpa secure scheme of bhho, along with a generalization of the cramer-shoup cca2 secure encryption scheme, and recently developed pairing-based nizk proof systems. this instantiation increases the complexity of the bhho scheme by just a small constant factor.
toward a rigorous variation of coppersmith's algorithm on three variables. in 1996, coppersmith introduced two lattice reduction based techniques to find small roots in polynomial equations. one technique works for modular univariate polynomials, the other for bivariate polynomials over the integers. since then, these methods have been used in a huge variety of cryptanalytic applications. some applications also use extensions of coppersmith's techniques on more variables. however, these extensions are heuristic methods. in the present paper, we present and analyze a new variation of coppersmith's algorithm on three variables over the integers. we also study the applicability of our method to short rsa exponents attacks. in addition to lattice reduction techniques, our method also uses gröbner bases computations. moreover, at least in principle, it can be generalized to four or more variables.
a new randomness extraction paradigm for hybrid encryption. we present a new approach to the design of ind-cca2 secure hybrid encryption schemes in the standard model. our approach provides an efficient generic transformation from 1-universal to 2-universal hash proof systems. the transformation involves a randomness extractor based on a 4-wise independent hash function as the key derivation function. our methodology can be instantiated with efficient schemes based on standard intractability assumptions such as decisional diffie-hellman, quadratic residuosity, and paillier's decisional composite residuosity. interestingly, our framework also allows to prove ind-cca2 security of a hybrid version of 1991's damgård's elgamal public-key encryption scheme under the ddh assumption.
mesh signatures. we define the mesh signature primitive as an anonymous signature similar in spirit to ring signatures, but with a much richer language for expressing signer ambiguity. the language can represent complex access structures, and in particular allows individual signature components to be replaced with complete certificate chains. because withholding one's public key from view is no longer a shield against being named as a possible cosignatory, mesh signatures may be used as a ring signature with compulsory enrollment.we give an efficient construction based on bilinear maps in the common random string model. our signatures have linear size, achieve everlasting perfect anonymity, and reduce to very efficient ring signatures without random oracles as a special case. we prove non-repudiation from a mild extension of the sdh assumption, which we introduce and justify meticulously.
on the portability of generalized schnorr proofs. the notion of zero knowledge proofs (of knowledge) [zkp] is central to cryptography; it provides a set of security properties that proved indispensable in concrete protocol design. these properties are defined for any given input and also for any auxiliary verifier private state, as they are aimed at any use of the protocol as a subroutine in a bigger application. many times, however, moving the theoretical notion to practical designs has been quite problematic. this is due to the fact that the most efficient protocols fail to provide the above zkp properties for all possible inputs and verifier states. this situation has created various problems to protocol designers who have often either introduced imperfect protocols with mistakes or with lack of security arguments, or they have been forced to use much less efficient protocols in order to achieve the required properties. in this work we address this issue by introducing the notion of "protocol portability," a property that identifies input and verifier state distributions under which a protocol becomes a zkp when called as a subroutine in a sequential execution of a larger application. we then concentrate on the very efficient and heavily employed "generalized schnorr proofs" (gsp) and identify the portability of such protocols. we also point to previous protocol weaknesses and errors that have been made in numerous applications throughout the years, due to employment of gsp instances while lacking the notion of portability (primarily in the case of unknown order groups). this demonstrates that cryptographic application designers who care about efficiency need to consider our notion carefully. we provide a compact specification language for gsp protocols that protocol designers can employ. our specification language is consistent with the ad-hoc notation that is currently widely used and it offers automatic derivation of the proof protocol while dictating its portability (i.e., the proper initial state and inputs) and its security guarantees. finally, as a second alternative to designers wishing to use gsps, we present a modification of gsp protocols that is unconditionally portable (i.e., zkp) and is still quite efficient. our constructions are the first such protocols proven secure in the standard model (as opposed to the random oracle model).
general encryption from exponent inversion ibe. among the three broad classes of identity-based encryption schemes built from pairings, the exponent inversion paradigm tends to be the most efficient, but also the least extensible: currently there are no hierarchical or other known extension of ibe based on those schemes. in this work, we show that such extensions can be realized from ibe systems that conform to a certain abstraction of the exponent inversion paradigm. our method requires no random oracles, and is simple and efficient.
a double-piped mode of operation for macs, prfs and pros: security beyond the birthday barrier. we revisit the double-pipe construction introduced by lucks at asiacrypt 2005. lucks originally studied the construction for iterated hash functions and showed that the approach is effective in improving security against various types of collision and (second-)preimage attacks. instead, in this paper we apply the construction to the secret-key setting, where the underlying fil (fixed-input-length) compression function is equipped with a dedicated key input. we make some adjustments to lucks' original design so that now the new mode works with a single key and operates as a multi-property-preserving domain extension of macs (message authentication codes), prfs (pseudo-random functions) and pros (pseudo-random oracles). though more than twice as slow as the merkle-damgård construction, the double-piped mode enjoys security strengthened beyond the birthday bound, most notably, high mac security. more specifically, when iterating an fil-mac whose output size is n-bit, the new double-piped mode yields an ail-(arbitrary-input-length-)mac with security up to $o\bigl(2^{5n/6}\bigr)$ query complexity. this bound contrasts sharply with the birthday bound of $o\bigl(2^{n/2}\bigr)$, which has been the best mac security accomplished by earlier constructions.
batch verification of short signatures. with computer networks spreading into a variety of new environments, the need to authenticate and secure communication grows. many of these new environments have particular requirements on the applicable cryptographic primitives. for instance, several applications require that communication overhead be small and that many messages be processed at the same time. in this paper we consider the suitability of public key signatures in the latter scenario. that is, we consider signatures that are 1) short and 2) where many signatures from (possibly) different signers on (possibly) different messages can be verified quickly.we propose the first batch verifier for messages from many (certified) signers without random oracles and with a verification time where the dominant operation is independent of the number of signatures to verify. we further propose a new signature scheme with very short signatures, for which batch verification for many signers is also highly efficient. prior work focused almost exclusively on batching signatures from the same signer. combining our new signatures with the best known techniques for batching certificates from the same authority, we get a fast batch verifier for certificates and messages combined. although our new signature scheme has some restrictions, it is the only solution, to our knowledge, that is a candidate for some pervasive communication applications.
traitors collaborating in public: pirates 2.0. this work introduces a new concept of attack against traitor tracing schemes. we call attacks of this type pirates 2.0 attacks as they result from traitors collaborating together in a public way. in other words, traitors do not secretly collude but display part of their secret keys in a public place; pirate decoders are then built from this public information. the distinguishing property of pirates 2.0 attacks is that traitors only contribute partial information about their secret key material which suffices to produce (possibly imperfect) pirate decoders while allowing them to remain anonymous. the side-effect is that traitors can publish their contributed information without the risk of being traced; giving such strong incentives to some of the legitimate users to become traitors allows coalitions to attain very large sizes that were deemed unrealistic in some previously considered models of coalitions.this paper proposes a generic model for this new threat, that we use to assess the security of some of the most famous traitor tracing schemes. we exhibit several pirates 2.0 attacks against these schemes, providing new theoretical insights with respect to their security. we also describe practical attacks against various instances of these schemes. eventually, we discuss possible variations on the pirates 2.0 theme.
simulatable adaptive oblivious transfer. we study an adaptive variant of oblivious transfer in which a sender has n messages, of which a receiver can adaptively choose to receive k one-after-the-other, in such a way that (a) the sender learns nothing about the receiver's selections, and (b) the receiver only learns about the k requested messages. we propose two practical protocols for this primitive that achieve a stronger security notion than previous schemes with comparable efficiency. in particular, by requiring full simulatability for both sender and receiver security, our notion prohibits a subtle selective-failure attack not addressed by the security notions achieved by previous practical schemes.our first protocol is a very efficient generic construction from unique blind signatures in the random oracle model. the second construction does not assume random oracles, but achieves remarkable efficiency with only a constant number of group elements sent during each transfer. this second construction uses novel techniques for building efficient simulatable protocols.
truly efficient 2-round perfectly secure message transmission scheme. in themodel of perfectly securemessage transmission schemes (psmts), there are n channels between a sender and a receiver. an infinitely powerful adversary a may corrupt (observe and forge) the messages sent through t out of n channels. the sender wishes to send a secret s to the receiver perfectly privately and perfectly reliably without sharing any key with the receiver. in this paper, we show the first 2-round psmt for n = 2t + 1 such that not only the transmission rate is o(n) but also the computational costs of the sender and the receiver are both polynomial in n. this means that we solve the open problem raised by agarwal, cramer and de haan at crypto 2006.
on randomizing hash functions to strengthen the security of digital signatures. halevi and krawczyk proposed a message randomization algorithm called rmx as a front-end tool to the hash-then-sign digital signature schemes such as dss and rsa in order to free their reliance on the collision resistance property of the hash functions. they have shown that to forge a rmx-hash-then-sign signature scheme, one has to solve a cryptanalytical task which is related to finding second preimages for the hash function. in this article, we will show how to use dean's method of finding expandable messages for finding a second preimage in the merkle-damgård hash function to existentially forge a signature scheme based on a t-bit rmx-hash function which uses the davies-meyer compression functions (e.g., md4, md5, sha family) in 2 t/2 chosen messages plus 2 t/2 + 1 off-line operations of the compression function and similar amount of memory. this forgery attack also works on the signature schemes that use davies-meyer schemes and a variant of rmx published by nist in its draft special publication (sp) 800-106. we discuss some important applications of our attack.
practical chosen ciphertext secure encryption from factoring. we propose a practical public-key encryption scheme whose security against chosen-ciphertext attacks can be reduced in the standard model to the assumption that factoring is intractable.
key agreement from close secrets over unsecured channels. we consider information-theoretic key agreement between two parties sharing somewhat different versions of a secret w that has relatively little entropy. such key agreement, also known as information reconciliation and privacy amplification over unsecured channels, was shown to be theoretically feasible by renner and wolf (eurocrypt 2004), although no protocol that runs in polynomial time was described. we propose a protocol that is not only polynomial-time, but actually practical, requiring only a few seconds on consumer-grade computers.our protocol can be seen as an interactive version of robust fuzzy extractors (dodis et al., crypto 2006). while robust fuzzy extractors, due to their noninteractive nature, require w to have entropy at least half its length, we have no such constraint. in fact, unlike in prior solutions, in our solution the entropy loss is essentially unrelated to the length or the entropy of w, and depends only on the security parameter.
generating genus two hyperelliptic curves over large characteristic finite fields. in hyperelliptic curve cryptography, finding a suitable hyperelliptic curve is an important fundamental problem. one of necessary conditions is that the order of its jacobian is a product of a large prime number and a small number. in the paper, we give a probabilistic polynomial time algorithm to test whether the jacobian of the given hyperelliptic curve of the form y 2 = x 5 + u x 3 + v x satisfies the condition and, if so, to give the largest prime factor. our algorithm enables us to generate random curves of the form until the order of its jacobian is almost prime in the above sense. a key idea is to obtain candidates of its zeta function over the base field from its zeta function over the extension field where the jacobian splits.
verifiable random functions from identity-based key encapsulation. we propose a methodology to construct verifiable random functions from a class of identity based key encapsulation mechanisms (ib-kem) that we call vrf suitable. informally, an ib-kem is vrf suitable if it provides what we call unique decryption (i.e. given a ciphertext c produced with respect to an identity ${\it{id}}$, all the secret keys corresponding to identity ${\it{id}}'$, decrypt to the same value, even if ${\it{id}}\neq {\it{id}}'$) and it satisfies an additional property that we call pseudorandom decapsulation. in a nutshell, pseudorandom decapsulation means that if one decrypts a ciphertext c, produced with respect to an identity ${\it{id}}$, using the decryption key corresponding to any other identity ${\it{id}}'$ the resulting value looks random to a polynomially bounded observer. interestingly, we show that most known ib-kems already achieve pseudorandom decapsulation. our construction is of interest both from a theoretical and a practical perspective. indeed, apart from establishing a connection between two seemingly unrelated primitives, our methodology is direct in the sense that, in contrast to most previous constructions, it avoids the inefficient goldreich-levin hardcore bit transformation.
double-base number system for multi-scalar multiplications. the joint sparse form is currently the standard representation system to perform multi-scalar multiplications of the form [n]p + m[q]. we introduce the concept of joint double-base chain, a generalization of the double-base number system to represent simultaneously n and m. this concept is relevant because of the high redundancy of double-base systems, which ensures that we can find a chain of reasonable length that uses exactly the same terms to compute both n and m. furthermore, we discuss an algorithm to produce such a joint double-base chain. because of its simplicity, this algorithm is straightforward to implement, efficient, and also quite easy to analyze. namely, in our main result we show that the average number of terms in the expansion is less than 0.3945log2 n. with respect to the joint sparse form, this induces a reduction by more than 20% of the number of additions. as a consequence, the total number of multiplications required for a scalar multiplications is minimal for our method, across all the methods using two precomputations, p + q and p ¿ q. this is the case even with coordinate systems offering very cheap doublings, in contrast with recent results on scalar multiplications. several variants are discussed, including methods using more precomputed points and a generalization relevant for koblitz curves. our second contribution is a new way to evaluate $\widehat\phi$, the dual endomorphism of the frobenius. namely, we propose formulae to compute $\pm{\widehat\phi}(p)$ with at most 2 multiplications and 2 squarings in the base field $\mathbb{f}_{2^d}$. this represents a speed-up of about 50% with respect to the fastest known techniques. this has very concrete consequences on scalar and multi-scalar multiplications on koblitz curves.
cube attacks on tweakable black box polynomials. almost any cryptographic scheme can be described by tweakable polynomials over gf(2), which contain both secret variables (e.g., key bits) and public variables (e.g., plaintext bits or iv bits). the cryptanalyst is allowed to tweak the polynomials by choosing arbitrary values for the public variables, and his goal is to solve the resultant system of polynomial equations in terms of their common secret variables. in this paper we develop a new technique (called a cube attack) for solving such tweakable polynomials, which is a major improvement over several previously published attacks of the same type. for example, on the stream cipher trivium with a reduced number of initialization rounds, the best previous attack (due to fischer, khazaei, and meier) requires a barely practical complexity of 255 to attack 672 initialization rounds, whereas a cube attack can find the complete key of the same variant in 219 bit operations (which take less than a second on a single pc). trivium with 735 initialization rounds (which could not be attacked by any previous technique) can now be broken with 230 bit operations. trivium with 767 initialization rounds can now be broken with 245 bit operations, and the complexity of the attack can almost certainly be further reduced to about 236 bit operations. whereas previous attacks were heuristic, had to be adapted to each cryptosystem, had no general complexity bounds, and were not expected to succeed on random looking polynomials, cube attacks are provably successful when applied to random polynomials of degree d over n secret variables whenever the number m of public variables exceeds d + log d n. their complexity is 2 d ¿ 1 n + n 2 bit operations, which is polynomial in n and amazingly low when d is small. cube attacks can be applied to any block cipher, stream cipher, or mac which is provided as a black box (even when nothing is known about its internal structure) as long as at least one output bit can be represented by (an unknown) polynomial of relatively low degree in the secret and public variables.
a unified framework for the analysis of side-channel key recovery attacks. the fair evaluation and comparison of side-channel attacks and countermeasures has been a long standing open question, limiting further developments in the field. motivated by this challenge, this work makes a step in this direction and proposes a framework for the analysis of cryptographic implementations that includes a theoretical model and an application methodology. the model is based on commonly accepted hypotheses about side-channels that computations give rise to. it allows quantifying the effect of practically relevant leakage functions with a combination of information theoretic and security metrics, measuring the quality of an implementation and the strength of an adversary, respectively. from a theoretical point of view, we demonstrate formal connections between these metrics and discuss their intuitive meaning. from a practical point of view, the model implies a unified methodology for the analysis of side-channel key recovery attacks. the proposed solution allows getting rid of most of the subjective parameters that were limiting previous specialized and often ad hoc approaches in the evaluation of physically observable devices. it typically determines the extent to which basic (but practically essential) questions such as "how to compare two implementations?" or "how to compare two side-channel adversaries?" can be answered in a sound fashion.
optimal randomness extraction from a diffie-hellman element. in this paper, we study a quite simple deterministic randomness extractor from random diffie-hellman elements defined over a prime order multiplicative subgroup g of a finite field ${\mathbb z}_p$ (the truncation), and over a group of points of an elliptic curve (the truncation of the abscissa). informally speaking, we show that the least significant bits of a random element in $g\subset {\mathbb z}_p^*$ or of the abscissa of a random point in $\mathcal{e}({\mathbb f}_p)$ are indistinguishable from a uniform bit-string. such an operation is quite efficient, and is a good randomness extractor, since we show that it can extract nearly the same number of bits as the leftover hash lemma can do for most elliptic curve parameters and for large subgroups of finite fields. to this aim, we develop a new technique to bound exponential sums that allows us to double the number of extracted bits compared with previous known results proposed at icalp'06 by fouque et al. it can also be used to improve previous bounds proposed by canetti et al. one of the main application of this extractor is to mathematically prove an assumption proposed at crypto '07 and used in the security proof of the elliptic curve pseudo random generator proposed by the nist. the second most obvious application is to perform efficient key derivation given diffie-hellman elements.
possibility and impossibility results for encryption and commitment secure under selective opening. the existence of encryption and commitment schemes secure under selective opening attack (soa) has remained open despite considerable interest and attention. we provide the first public key encryption schemes secure against sender corruptions in this setting. the underlying tool is lossy encryption. we then show that no non-interactive or perfectly binding commitment schemes can be proven secure with black-box reductions to standard computational assumptions, but any statistically hiding commitment scheme is secure. our work thus shows that the situation for encryption schemes is very different from the one for commitment schemes.
single-symbol ml decodable distributed stbcs for partially-coherent cooperative networks. a relay network with n relays and a single source-destination pair is called a partially-coherent relay channel (pcrc) if the destination has perfect channel state information (csi) of all the channels and the relays have only the phase information of the source-to-relay channels. in this paper, first, a new set of necessary and sufficient conditions for a space-time block code (stbc) to be single-symbol decodable (ssd) for co-located multiple antenna communication is obtained. then, this is extended to a set of necessary and sufficient conditions for a distributed stbc (dstbc) to be ssd for a pcrc. using this, several ssd dstbcs for pcrc are identified. it is proved that even if a ssd stbc for a co-located mimo channel does not satisfy the additional conditions for the code to be ssd for a pcrc, single-symbol decoding of it in a pcrc gives full-diversity and only coding gain is lost. it is shown that when a dstbc is ssd for a pcrc, then arbitrary coordinate interleaving of the in-phase and quadrature-phase components of the variables does not disturb its ssd property for pcrc. finally, it is shown that the possibility of channel phase compensation operation at the relay nodes using partial csi at the relays increases the possible rate of ssd dstbcs from 2/n when the relays do not have csi to 1/2, which is independent of n.
two-user opportunistic scheduling using hierarchical modulations in wireless networks with heterogenous average link gains. our contribution, in this paper, is two-fold. first, we analyze the performance of a hierarchical modulation-assisted two-best user opportunistic scheduling (tbs) scheme, which was proposed by the authors, in a fading environment where different users have different average link gains. specifically, we present a new expression for the spectral efficiency (se) of the users and using this expression, we compare the degrees of fairness (dof) of the tbs scheme with that of classical single user opportunistic scheduling schemes, namely, absolute carrier-to-noise ratio (cnr) based single-best user scheduling (sbs) and normalized cnr based proportional fair scheduling (pfs) schemes. the second contribution is that we propose a new hybrid two-user opportunistic scheduling (hts) scheme based on our earlier proposed tbs scheme. this hts scheme selects the first user based on the largest absolute cnr value among all the users while the second user is selected based on the ratios of the absolute cnrs to the corresponding average cnrs of the remaining users. the total transmission rate i.e., the constellation size is selected according to the absolute cnr of the first best user. the total transmission rate is then allocated among these selected users by joint consideration of their absolute cnrs and allocated number of information bit(s) are transmitted to them using hierarchical modulations. numerical results are presented for a fading environment where different users experience independent but non-identical (i.n.d.) channel fading. these selected numerical results show that the proposed hts scheme can considerably increase the system's fairness without any degradation of the link spectral efficiency (lse) i.e., the multiuser diversity gain compared to the classical sbs scheme. these results also show that the proposed hts scheme has a lower fairness in comparison to the pfs scheme which suffers from a considerable degradation in lse.
on the performance analysis of composite multipath/shadowing channels using the g-distribution. composite multipath fading/shadowing environments are frequently encountered in different realistic scenarios. these channels are generally modeled as a mixture of nakagamim multipath fading and log-normal shadowing. the resulting composite probability density function (pdf) is not available in closed form, thereby making the performance evaluation of communication links in these channels cumbersome. in this paper, we propose to model composite channels by the g- distribution. this pdf arises when the log-normal shadowing is substituted by the inverse-gaussian one. this substitution will prove to be very accurate for several shadowing conditions. in this paper we conduct a performance evaluation of single-user communication systems operating in a composite channel. our study starts by deriving an analytical expression for the outage probability. then, we derive the moment generating function of the g-distribution, hence facilitating the calculation of average bit error probabilities. we also derive analytical expressions for the channel capacity for three adaptive transmission techniques, namely, i) optimal rate adaptation with constant power, ii) optimal power and rate adaptation, and iii) channel inversion with fixed rate.
an autonomic service delivery platform for service-oriented network environments. in this paper, we propose a novel autonomic service delivery platform for service-oriented network environments. the platform enables a self-optimizing infrastructure that balances the goals of maximizing the business value derived from processing service requests and the optimal utilization of it resources. we believe that our proposal is the first of its kind to integrate several well-established theoretical and practical techniques from networking, microeconomics, and service-oriented computing to form a fully distributed service delivery platform. the principal component of the platform is a utility-based cooperative service routing protocol that disseminates congestion-based prices among intermediaries to enable the dynamic routing of service requests from consumers to providers. we provide the motivation for such a platform and formally present our proposed architecture. we discuss the underlying analytical framework for the service routing protocol, as well as key methodologies which together provide a robust framework for our service delivery platform that is applicable to the next-generation of middleware and telecommunications architectures. we discuss issues regarding the fairness of service rate allocations, as well as the use of nonconcave utility functions in the service routing protocol. we also provide numerical results that demonstrate the ability of the platform to provide optimal routing of service requests.
qrd-based precoded mimo-ofdm systems with reduced feedback. qr decomposition (qrd)-based precoded mimo-ofdm systems with reduced feedback are proposed to convert the mimo-ofdm channel into layered subchannels. qrd-m is further combined with either singular value (svd) or geometric mean decomposition (gmd) of the time-domain channel impulse response matrix. as a result, the receiver in the proposed systems only needs to feed back information describing one precoding matrix for all carriers. simulation results confirm the bit-error-rate (ber) and throughput performance superiority of the proposed systems compared to conventional svd per-carrier precoding schemes.
underwater acoustic sensor networks: target size detection and performance analysis. underwater acoustic sensor network consists of a variable number of sensors and vehicles that are deployed to perform collaborative monitoring tasks over a given area. scalability concern suggests a hierarchical organization of underwater sensor networks with the lowest level in the hierarchy being a cluster. in this paper, we show that an ultra-wide band (uwb) channel can be used for underwater channel modeling and propose a maximum-likelihood (ml) estimation algorithm for underwater target size detection using collaborative signal processing within a cluster in underwater acoustic sensor networks. theoretical analysis demonstrates that our underwater sensor network can tremendously reduce the variance of target size estimation. we show that our ml estimator is unbiased and the variance of parameter estimation matches the cramer-rao lower bound. simulations further validate these theoretical results.
sum-rate analysis of multiuser mimo system with zero-forcing transmit beamforming. in this letter, we present the exact sum-rate analysis of the multiuser multiple-input multiple-output (mimo) systems with zero-forcing transmit beamforming (zfbf). we develop the analytical expressions of the ergodic sum-rate for two low-complexity user selection strategies for the dual-transmitantenna scenario. based on the analytical results, we examine the parameter optimization problem to properly trade off between channel power gain and directional gain in term of maximizing the ergodic sum rate.
distributed space-time coding for two-way wireless relay networks. in this paper, we consider distributed space-time coding for two-way wireless relay networks, where communication between two terminals is assisted by relay nodes. relaying protocols using two, three, and four time slots are proposed. the protocols using four time slots are the traditional amplify-and-forward (af) and decode-and-forward (df) protocols, which do not consider the property of the two-way traffic. a new class of relaying protocols, termed as partial decode-and-forward (pdf), is developed for the two time slots transmission, where each relay first removes part of the noise before sending the signal to the two terminals. protocols using three time slots are proposed to compensate the fact that the two time slots protocols cannot make use of direct transmission between the two terminals. for all protocols, after processing their received signals, the relays encode the resulting signals using a distributed linear dispersion (ld) code. the proposed af protocols are shown to achieve the diversity order of min {n, k} (1-(log log p/log p), where n is the number of relays, p is the total power of the network, and k is the number of symbols transmitted during each time slot. when random unitary matrix is used for ld code, the proposed pdf protocols resemble random linear network coding, where the former operates on the unitary group and the latter works on the finite field. moreover, pdf achieves the diversity order of min {n, k} but the conventional df can only achieve the diversity order of 1. finally, we find that two time slots protocols also have advantages over four-time-slot protocols in media access control (mac) layer.
an analytical method for calculating the bit error rate performance of rake reception in uwb multipath fading channels. the bit error rate performance of rake reception of impulse radio ultra-wide bandwidth signals over the ieee 802.15.3a channel models is evaluated. instead of using gaussian approximation for the probability density function of the total disturbance which includes the multi-user interference and the background additive white gaussian noise, two new models dubbed the "composite lognormal-gaussian" and the "composite lognormal-laplacian" are proposed for modeling the multi-user interference and shadowing in ultra-wide bandwidth multipath fading channels. tractable formulae for bit error rate evaluation of rake reception in ultra-wide bandwidth multipath channels are derived for both models. numerical results indicate that these formulae predict the bit error rate performance with good accuracy, and can be rapidly and easily evaluated using commonplace computer resources.
joint connection admission control and routing in ieee 802.16-based mesh networks. connection admission control and routing are two important mechanisms in the provision of quality of service (qos) in ieee 802.16-based wireless mesh networks. in this paper, we propose a joint admission control and routing scheme for multiple service classes with the objective to maximize the overall revenue from all carried connections. qos constraints such as handoff dropping probability can be guaranteed. multiple service classes can be prioritized by imposing different reward rates. we formulate the problem as a decision process, and apply optimization techniques to obtain the optimal admission control policies. the effectiveness of the proposed approach is illustrated by numerical and simulation results. we show that the proposed joint admission control and routing scheme can produce maximum revenue obtainable by the system under qos constraints.we also show that the optimal joint admission control policy is a randomized policy, i.e., connections are admitted to the system with some probabilities when the system is in some states.
a collision-free mac scheme for multimedia wireless mesh backbone. wireless mesh networking is a promising wireless technology for future broadband internet access. in this paper, a novel collision-free medium access control (mac) scheme supporting multimedia applications is proposed for wireless mesh backbone. the proposed scheme is distributed, simple, and scalable. benefiting from the fixed locations of wireless routers, the proposed mac scheme reduces the control overhead greatly as compared with conventional contention-based mac schemes (e.g., ieee 802.11). in addition, the proposed scheme can provide guaranteed priority access to real-time traffic and, at the same time, ensure fair channel access to the routers with data traffic. unlike most of the existing mac schemes which focus on single-hop transmissions, the proposed mac scheme takes the intra-flow correlations between up-stream and downstream hops of a multi-hop flow into consideration. to avoid buffer overflow at bottleneck routers, a simple but effective congestion control mechanism is proposed. simulation results demonstrate that the proposed scheme significantly improves the delay performance of real-time traffic and the end-to-end data throughput, as compared with ieee 802.11 and distributed packet reservation multiple access (dprma). the performance analysis of the proposed scheme is also presented. the accuracy of the analytical results is verified by computer simulations.
blind cooperative diversity using distributed space-time coding in block fading channels. mobile users with single antennas can still take advantage of spatial diversity through cooperative space-time encoded transmission. in this paper, we consider a scheme in which a relay chooses to cooperate only if its source-relay channel is of an acceptable quality and we evaluate the usefulness of relaying when the source acts blindly and ignores the decision of the relays whether they may cooperate or not. in our study, we consider the regenerative relays in which the decisions to cooperate are based on a signal-to-noise ratio (snr) threshold and consider the impact of the possible erroneously detected and transmitted data at the relays. we derive the end-to-end bit-error rate (ber) expression and its approximation for binary phase-shift keying modulation and look at two power allocation strategies between the source and the relays in order to minimize the end-to-end ber at the destination for high snr. some selected performance results show that computer simulations based results coincide well with our analytical results.
cognitive network access using fuzzy decision making. we consider a scenario in which wireless users want to connect to the internet using one of several available network access opportunities, possibly using different radio technologies. we propose a distributed cognitive network access scheme with the aim of providing the best quality of service with respect to both radio link and core network performance and user application requirements. knowledge of the service quality experienced by active connections is shared, and prospective users use fuzzy logic techniques to process cross-layer communication quality metrics and to estimate the expected transport-layer performance. these estimates are compared to the quality of service requirements of the application using fuzzy decision making techniques to choose the most suitable access opportunity. this scheme naturally fits into the recently proposed cognitive network paradigm in that it defines a cognition process leveraging on end-to-end and cross-layer performance evaluation techniques as well as information sharing among users; moreover, it offers a significant amount of flexibility and extensibility, thanks to its modularity and its independence from the particular technology and application being used. the proposed scheme is shown to outperform state-of-the-art solutions in several multitechnology and multi-application scenarios, while at the same time achieving similar performance to application-specific omniscient schemes that we introduce in this paper as a benchmark.
optimal adaptive modulation and coding with switching costs. we present an optimal adaptive modulation and coding policy that minimizes the transmission latency and modulation/coding switching cost across a finite-state markovian fading channel. we formulate the optimal tradeoff between transmission latency and modulation/coding switching cost as a discounted infinite horizon markov decision problem (mdp). by exploiting special structures of the formulated mdp and under certain sufficient conditions, we show that optimal modulation and coding selection policies are monotone in the state variables. these monotone optimal policies are computationally inexpensive to implement and are scalable in terms of channel and switching cost parameters. numerical results confirm the monotonicity and threshold-based structure of the optimal modulation and coding scheme (mcs) selection policies under the proposed sufficient conditions.
locating congested segments on the internet by clustering the delay performance of multiple paths. delay variation-based detection and location of congestion in a large network is considered. since the internet is still highly prone to performance deterioration due to transient large delays, locating a part of the network (segments) responsible is vital to ensure that internet service providers can mitigate or prevent such performance deterioration. in the proposed method, the end-to-end packet delays from multiple origins to multiple destinations are actively and continuously measured. by analyzing those data on delay variation along each monitored path, congestion is detected by finding a delay performance deterioration worse than a predefined criteria and a congested segment responsible could be inferred by finding a set of paths among which delay variations are strongly correlated. this is a network tomographic approach based on a clustering technique that effectively tackles the correlation among packet delay variation along individual paths. the proposed method was evaluated through a real-world long-term experiment on the japan's commercial internet, and was shown to have considerable potential to promptly locate congested segments through various analyses on the experimental results.
opportunistic scheduling for wireless network coding. this letter addresses a scheduling problem for wireless network coding (wnc). in our previous work, we have theoretically shown that the optimum number of nodes to be included into a network-coded packet as well as its transmission rate depends on time-varying link condition between a transmitting node and receiving nodes [1]. based on this observation, this letter designs practical scheme which opportunistically selects scheduled nodes, packets to be coded and an employed modulation level according to time-varying channel conditions and packet length. the numerical results show that the proposed opportunistic scheduling can improve the overall throughput as compared with non-opportunistic approach.
downlink tcp performance under cross layer rate and power allocation in infrastructure th-ppm uwb networks. ultra wideband (uwb) systems are currently an important wireless infrastructure for efficient short-range communications and mobile applications. to improve the system efficiency while guaranteeing the radio link level quality of services, the transmission rate and power of the mobile nodes in uwb based infrastructure networks can be dynamically adjusted by executing an optimization algorithm at the access points (aps). in this paper, we present a cross layer rate and power allocation algorithm based on the multilayer model of time hopping (th) pulse position modulation (ppm) uwb multimedia networks. we consider the performance of the tcp protocol under the proposed cross layer allocation scheme in various realistic uwb based infrastructure networking scenarios.
sat and atpg: boolean engines for formal hardware verification. in this survey, we outline basic sat- and atpg- procedures as well as their applications in formal hardware verification. we attempt to give the reader a trace trough literature and provide a basic orientation concerning the problem formulations and known approaches in this active field of research.
dag-aware circuit compression for formal verification. the choice of representation for circuits and boolean formulae in a formal verification tool is important for two reasons. first of all, representation compactness is necessary in order to keep the memory consumption low. this is witnessed by the importance of maximum processable design size for equivalence checkers. second, many formal verification algorithms are sensitive to redundancies in the design that is processed. to address these concerns, three different auto-compressing representations for boolean circuit networks and formulas have been suggested in the literature. we attempt to find a blend of features from these alternatives that allows us to remove as much redundancy as possible while not sacrificing runtime. by studying how the network representation size varies when we change parameters, we show that the use of only one operator node is suboptimal, and demonstrate that the most powerful of the proposed reduction rules, two-level minimization, actually can be harmful. we correct the bad behavior of two-level optimization by devising a simple linear simplification algorithm that can remove tens of thousands of nodes on examples where all obvious redundancies already have been removed. the combination of our compactor with the simplest representation outperforms all of the alternatives we have studied, with a theoretical runtime bound that is at least as good as the three studied representations.
automatic generalized phase abstraction for formal verification. a standard approach to improving circuit performance is to use an n-phase design style where combinational logic is interspersed freely between level sensitive latches controlled by separate clocks. unfortunately, the use of an n-phase design style will increase the number of state variables by a factor of n, making formal verification many orders of magnitude harder. previous approaches to solving this problem restrict the kind of designs that can be handled severely and construct an abstracted netlist with fewer state variables by a syntactic analysis that requires the user to identify clocks. we extend the current state of the art by introducing a phase abstraction algorithm that (1) poses no restrictions on the design style that can be used, that (2) avoids an error prone syntactic analysis, that (3) requires no input from users, and that (4) can be integrated into any model checker without requiring hdl code analysis.
slope propagation in static timing analysis. static timing analysis has traditionally used the pert method for identifying the critical path of a digital circuit. due to the influence of the slope of a signal at a particular node on the subsequent path delay, an earlier signal with a signal slope greater than the slope of the later signal may result in a greater delay. therefore, the traditional method for timing analysis may identify the incorrect critical path and report an optimistic delay for the circuit. we show that the circuit delay calculated using the traditional method is a discontinuous function with respect to transistor and gate sizes, posing a severe problem for circuit optimization methods. we propose a new timing analysis algorithm which resolves both these issues. the proposed algorithm selectively propagates multiple signals through each timing edge in cases where there exists ambiguity regarding which arriving signal represents the critical path. the algorithm for propagating the corresponding required times is also presented. we prove that the proposed algorithm identifies a circuit's true critical path, where the traditional timing analysis method may not. we also show that under this method circuit delay and node slack are continuous functions with respect to a circuit's transistor and gate sizes. in addition, we present a heuristic method which reduces the number of signals to be propagated at the expense of a slight loss in accuracy. finally, we show how the proposed algorithm was efficiently implemented in an industrial static timing analysis and optimization tool, and present results for a number of industrial circuits. our results show that the traditional timing analysis method underestimates the circuit delay by as much as 38%, while that the proposed method efficiently finds the correct circuit delay with only a slight increase in run time.
ic power distribution challenges. with each technology generation, delivering a timevarying current with reduced nominal supply voltage variation is becoming more difficult due to increasing current and power requirements. the power delivery network design becomes much more complex and requires accurate analysis and optimizations at all levels of abstraction in order to meet the specifications. in this paper, we describe techniques for estimation of the supply voltage variations that can be used in the design of the power delivery network. we also describe the decoupling capacitor hierarchy that provides a low impedance to the increasing high-frequency current demand and limits the supply voltage variations. techniques for high-level power estimation that can be used for performance vs. power trade-offs to reduce the current and power requirements of the circuit are also presented.
design space exploration for aggressive test cost reduction in circularscan architectures. scan-based designs effectively reduce test generation complexity and thus deliver improved fault coverage. nevertheless, the traditional scan architectures suffer from increased test time and test data volume. the circularscan architecture (arslan and orailoglu) provides a flexible environment for test cost reduction. the new scan design enables the use of the captured response of the previously applied test pattern as a template. the subsequent pattern is loaded by efficiently performing the necessary changes on the template through the functionality provided by the new architecture, conceptually exploiting the inherent low specified bit density of the test patterns. we explore the space of possible design alternatives built on the circularscan architecture; the design alternatives are presented with accompanying test application methods. the experimental results indicate a substantial test cost reduction, reaching 90% levels. the proposed scheme is not only easily scalable but also promises further reductions in test cost when applied to large state of the art ics.
the formal verification of a pipelined double-precision ieee floating-point multiplier. floating-point circuits are notoriously difficult to design and verify. for verification, simulation barely offers adequate coverage, conventional model-checking techniques are infeasible, and theorem-proving based verification is not sufficiently mature. in this paper we present the formal verification of a radix-eight, pipelined, ieee double-precision floating-point multiplier. the verification was carried out using a mixture of model-checking and theorem-proving techniques in the voss hardware verification system. by combining model-checking and theorem-proving we were able to build on the strengths of both areas and achieve significant results with a reasonable amount of effort.
polarized observability don't cares. a new method is presented to compute the exact observability don't cares (odc} for multilevel combinational circuits. a new mathematical concept, called polarization, is introduced. polarization captures the essence of odc calculation on the otherwise difficult points of reconvergence. it makes it possible to derive the odc of a node from the odcs of its fanouts with a very simple formula. experimental results for the 39 largest mcnc benchmark examples show that the method is able to compute the odc set (expressed as a boolean network} for all but 1 circuit in at most a few seconds.
placement method targeting predictability robustness and performance. we study the relationship between robustness,predictability andperformance of vlsi circuits. it is shown that predictability andperformance are conflicting objectives. performance and robustnessare statically conflicting objectives but they are statistically non-conflicting.we propose and develop means for changing a standard timing-driven partitioning-based placement algorithm in order to design more predictable and robust circuits without sacrificingmuch of performance.
multi-objective circuit partitioning for cutsize and path-based delay minimization. in this paper we present multi-objective hmetis partitioning for simultaneous cutsize and circuit delay minimization. we change the partitioning process itself by introducing a new objective function that incorporates a truly path-based delay component for the most critical paths. to avoid semi-critical paths from becoming critical, the traditional slack based delay component is also included in the cost function. the proposed timing driven partitioning algorithm is built on top of the hmetis algorithm, which is very efficient. simulations results show that 14% average delay improvement can be obtained. smooth trade-off between cutsize and delay is possible in our algorithm.
algebraic decision diagrams and their applications. in this paper we present theory and experimental results on algebraic decision diagrams. these diagrams extend bdds by allowing values from an arbitrary finite domain to be associated with the terminal nodes of the diagram. we present a treatment founded in boolean algebras and discuss algorithms and results in several areas of application: matrix multiplication, shortest path algorithms, and direct methods for numerical linear algebra. although we report an essentially negative result for gaussian elimination per se, we propose a modified form of adds which appears to circumvent the difficulties in some cases. we discuss the relevance of our findings and point to directions for future work.
parametric test development for rf circuits targeting physical fault locations and using specification-based fault definitions. the test cost of rf systems is an increasing percentage of the overall system cost. this trend is mainly due to the traditional rf testing schemes based on the full measurement of specifications over a wide range of input conditions. in this paper, we present a test development methodology for rf circuits based on a novel parametric fault definition. we target deviations in physical circuit parameters, such as a resistance or the width of a transistor. however, we consider a circuit faulty only if it violates a specification. our test development method aims at reducing not only the number of measurements, but also the overall test hardware cost by incorporating the relative set-up cost of each measurement into our selection criteria. experimental results on a low-noise amplifier (lna) circuit show that our test development technique reduces the overall test time (49%-67%) as well as the number of required measurement set-ups (17%-33%) considerably. by defining the target faults based on specification violations, our technique also provides high confidence in the test quality.
a symbolic method to reduce power consumption of circuits containing false paths. power dissipation in technology mapped circuits can be reduced by performing gate re-sizing. recently we have proposed a symbolic procedure which exploits the compactness of the add data structure to accurately calculate the arrival times at each node of a circuit for any primary input vector. in this paper we extend our timing analysis tool to the symbolic calculation of required times and slacks, and we use this information to identify gates of the circuits that can be re-sized. the nice feature of our approach is that it takes into account the presence of false paths naturally. as shown by the experimental results, circuits re-synthesized with the technique we present in this paper are guaranteed to be at least as fast as the original implementations, but smaller and substantially less power-consuming.
addressing high frequency effects in vlsi interconnects with full wave model and cfh. abstract: in order to accurately characterize dispersive system of vlsi interconnects at higher frequencies, full wave analysis which takes into account all possible field components and satisfies all boundary conditions is required. however, conventional circuit simulation of interconnects with full wave models is extremely cpu expensive. this paper presents a new method to extend the moment matching technique, complex frequency hopping, to the case of interconnects modeled with full wave analysis. formulation of circuit equations is modified to incorporate interconnect stencil from full wave analysis. a new algorithm for the moment generation for interconnect networks with full wave models has been developed. full wave analysis has been carried out with the efficient 'spectral domain approach'. results have shown that the proposed method is accurate while it yields a speed up of one to three orders of magnitude over conventional simulation techniques. subject terms: circuit analysis computing; vlsi; integrated circuit interconnections; circuit cad; high-frequency effects; vlsi interconnects; high frequency effects; full wave model; cfh; spectral domain approach; dispersive system; full wave analysis; boundary conditions; moment matching technique; complex frequency hopping
a probabilistic-based design methodology for nanoscale computation. as current silicon-based techniques fast approach their practicallimits, the investigation of nanoscale electronics, devices andsystem architectures becomes a central research priority. it is expectedthat nanoarchitectures will confront devices and interconnectionswith high inherent defect rates, which motivates the searchfor new architectural paradigms.in this paper, we propose a probabilistic-based design methodologyfor designing nanoscale computer architectures based onmarkov random fields (mrf). the mrf can express arbitrarylogic circuits and logic operation is achieved by maximizing theprobability of state configurations in the logic network. maximizingstate probability is equivalent to minimizing a form of energythat depends on neighboring nodes in the network. once we developa library of elementary logic components, we can link themtogether to build desired architectures based on the belief propagationalgorithm. belief propagation is a way of organizing theglobal computation of marginal belief in terms of smaller localcomputations. we will illustrate the proposed design methodologywith some elementary logic examples.
unification of partitioning, placement and floorplanning. large macro blocks, pre-designed datapaths, embedded memories and analog blocks are increasingly used in asic designs. however, robust algorithms for large-scale placement of such designs have only recently been considered in the literature, and improvements by over 10% per paper are still common. large macros can be handled by traditional floorplanning, but are harder to account for in min-cut and analytical placement. on the other hand, traditional floorplanning techniques do not scale to large numbers of objects, especially in terms of solution quality. we propose to integrate min-cut placement with fixed-outline floor-planning to solve the more general placement problem, which includes cell placement, floorplanning, mixed-size placement and achieving routability. at every step of min-cut placement, either partitioning or wirelength-driven, fixed-outline floorplanning is invoked. if the latter fails, we undo an earlier partitioning decision, merge adjacent placement regions and re-floorplan the larger region to find a legal placement for the macros. empirically, this framework improves the scalability and quality of results for traditional wirelength-driven floorplanning. it has been validated on recent designs with embedded memories and accounts for routability. additionally, we propose that free-shape rectilinear floorplanning can be used with rough module-area estimates before synthesis.
boolean techniques for low power driven re-synthesis. we present a boolean technique to reduce power consumption of combinational circuits that have already been optimized for area and delay and then mapped onto a library of gates. in order to achieve a better optimization, we cluster gates by collapsing two or more levels of gates into a single node. when optimizing each cluster, our method extends the algorithms used in espresso, by adding heuristics that bias the minimization toward lowering the power dissipation in the circuit. the results of our method, on a number of benchmark circuits, show an average of 16% improvement in power savings compared to existing boolean techniques.
on whitespace and stability in mixed-size placement and physical synthesis. in the context of physical synthesis, large-scale standard-cell placementalgorithms must facilitate incremental changes to layout, bothlocal and global. in particular, flexible gate sizing, net buffering anddetail placement require a certain amount of unused space in everyregion of the die. the need for "local" whitespace is further emphasizedby temperature and power-density limits. another requirement,the stability of placement results from run to run, is importantto the convergence of physical synthesis loops. indeed, logic resynthesistargetting local congestion in a given placement or particularcritical paths may be irrelevant for another placement produced bythe same or a different layout tool.in this work we offer solutions to the above problems. we showhow to tie the results of a placer to a previously existing placement,and yet leave room for optimization. in our experiments this techniqueproduces placements with similar congestion maps. we alsoshow how to trade-off wirelength for routability by manipulatingwhitespace. empirically, our techniques improve circuit delay ofsparse layouts in conjunction with physical synthesis.in the context of earlier proposed techniques for mixed-size placement, we tune a state-of-the-art recursive bisection placer to betterhandle regular netlists that offer a convenient way to representmemories, datapaths and random-logic ip blocks. these modificationsand better whitespace distribution improve results on recentmixed-size placement benchmarks.
simulation and optimization of the power distribution network in vlsi circuits. in this paper, we present simulation techniques to estimate the worst-case voltage variation using a rc model for the power distribution network. pattern independent maximum envelope currents are used as a periodic input for performing the frequency-domain steady-state simulation of the linear rc circuit to evaluate the worst-case instantaneous voltage drop for the rc power distribution networks. the proposed technique unlike existing techniques, is guaranteed to give the maximum voltage drop at nodes in the rc power distribution network. we present experimental results to compare the frequency-domain and time-domain simulation techniques for estimating the maximum instantaneous voltage drop. we also present frequency domain sensitivity analysis based decoupling capacitance placement for reducing the voltage variation in the power distribution network. experimental results on circuits extracted from layout are presented to validate the simulation and optimization techniques.
extraction and lvs for mixed-domain integrated mems layouts. as design of integrated microelectromechanical systems (mems) matures, there is an increasing need for verification of mems layouts. this requires a mixed-domain lvs (layout-versus-schematic) methodology capable of extracting an integrated schematic from the mixed-domain layout and verifying it against the designed schematic. this paper reports on a prototype implementation of mems lvs and a mems extractor, which, in addition to reconstructing the extracted schematic also captures the domain-specific parasitics in the individual devices. this schematic is then used by a custom schematic-versus-schematic comparator to match connectivity of various elements between the designed and extracted schematics. finally, simulation of the extracted schematic also helps in capturing the true behavior of the system.
automatic generation and verification of sufficient correctness properties for synchronous processors. a general strategy for automatically generating and verifying sufficient correctness properties for a broad class of synchronous processors is presented. given a particular specification and implementation pair, it is shown how basic correctness properties can be algorithmically translated into a set of computation tree logic (ctl) formulae which are sufficient for equivalence between the behavioral and logic descriptions. preliminary experimental results on the verification of microcoded and array processors are presented
design exploration for high-performance pipelines. exploration plays an important role in the design of high-performance pipelines. we propose an exploration strategy for varying three design parameters by using a performance-constrained component selection and pipelining algorithm on different &ldquo;architectures&rdquo;. the architecture is specified manually by using a mix of behavioral and structural constructs, while the component selection and pipelining is performed automatically using our algorithms. results on two industrial-strength dsp systems, indicate the effectiveness of our strategy in exploring a large design space within a matter of seconds.
a new efficient approach to statistical delay modeling of cmos digital combinational circuits. this paper presents one of the first attempts to statistically characterize signal delays of basic cmos digital combinatorial circuits using the transistor level approach. hybrid analytical/iterative delay expressions in terms of the transistor geometries and technological process variations are created for basic building blocks. local delays of blocks along specific signal paths are combined together for the analysis of complex combinational vlsi circuits. the speed of analysis is increased by 2 to 4 orders of magnitude relative to spice, with about 5&ndash;10% accuracy. the proposed approach shows good accuracy in modeling the influence of the &ldquo;noise&rdquo; parameters on circuit delay relative to direct spice-based monte carlo analysis. examples of statistical delay characterization are shown. the important impact of the proposed approach is that statistical evaluation and optimization of delays in much larger vlsi circuits will become possible.
stars in vcc: complementing simulation with worst-case analysis. stars is a methodology for worst-case analysis of embedded systems. stars manipulates abstract representations of system components to obtain upper bounds on the number of various events in the system, as well as a bound on the response time. vcc is a commercial discrete event simulator, that can be used both for functional and performance verification. we describe an extension of vcc to facilitate stars. the extension allows the user to specify abstract representations of vcc modules. these abstractions are used by stars, but their validity can also be checked by vcc simulation. we also propose a mostly automatic procedure to generate these abstractions. finally, we illustrate on an example how stars can be combined with simulation to find bugs that would be hard to find by simulation alone.
statistical timing analysis for intra-die process variations with spatial correlations. process variations have become a critical issue in performanceverification of high-performance designs. we present a new, statisticaltiming analysis method that accounts for inter- and intra-dieprocess variations and their spatial correlations. since statisticaltiming analysis has an exponential run time complexity, we proposea method whereby a statistical bound on the probability distributionfunction of the exact circuit delay is computed with linear run time.first, we develop a model for representing inter- and intra-die variationsand their spatial correlations. using this model, we thenshow how gate delays and arrival times can be represented as a sumof components, such that the correlation information betweenarrival times and gate delays is preserved. we then show howarrival times are propagated and merged in the circuit to obtain anarrival time distribution that is an upper bound on the distributionof the exact circuit delay. we prove the correctness of the bound andalso show how the bound can be improved by propagating multiplearrival times. the proposed algorithms were implemented andtested on a set of benchmark circuits under several process variationscenarios. the results were compared with monte carlo simulationand show an accuracy of 3.32% on average over all test cases.
worst-case analysis of discrete systems. we propose a methodology for worst-case analysis of systems with discrete observable signals. the methodology can be used to verify different properties of systems such as power consumption, timing performance or resource utilization. we also propose an application of the methodology to timing analysis of embedded systems implemented on a single processor. the analysis provides a bound on the response time of such systems. it is typically very efficient, because it does not require a state space search.
statistical clock skew analysis considering intra-die process variations. with shrinking cycle times, clock skew has become an increasinglydifficult and important problem for high performance designs.traditionally, clock skew has been analyzed using case-files whichcannot model intra-die process variations and hence result in a veryoptimistic skew analysis. in this paper, we present a statistical skewanalysis method to model intra-die process variations. we firstpresent a formal model of the statistical clock skew problem and thenpropose an algorithm which is based on propagation of joint probabilitydistribution functions in a bottom up fashion in a clock tree.the analysis accounts for topological correlations between pathdelays and has linear run time with the size of the clock tree. theproposed method was tested on several large clock tree circuits,including a clock tree from a large industrial high-performancemicroprocessor. the results are compared with monte carlo simulationfor accuracy comparison and demonstrate the need for statisticalanalysis of clock skew.
iterative algorithms for formal verification of embedded real-time systems. most embedded real-time systems consist of many concurrent components operating at significantly different speeds. thus, an algorithm for formal verification of such systems must efficiently deal with a large number of states and large ratios of timing constants. we present such an algorithm based on timed automata, a model where a finite state system is augmented with time measuring devices called timers. we also present a semi-decision procedure for an extended model where timers can be decremented. this extension allows describing behaviors that are not expressible by timed automata, for example interrupts in a real-time operating system.
accurate estimation and modeling of total chip leakage considering inter- & intra-die process variations. in this paper we propose an accurate estimation and modeling of total circuit leakage distribution, considering both inter- and intra-die variations (variation in l, t/sub ox/ and random dopant fluctuation). since, the total leakage in a circuit depends on leakage in a transistor, integration of transistors in a logic gate, and the gate topology in a circuit block, we model the total circuit leakage distribution at all levels of circuit design, while taking the different correlations among transistors, logic gates, circuit topology, and input vectors into account. the proposed model accurately estimates both statistical information (mean and variance) and the shape of the leakage distribution. we have verified the model using monte carlo simulation using devices of 50nm effective length and analyzed the results to enumerate the effect of different process parameters on individual components of total leakage.
modeling non-slicing floorplans with binary trees. several novel topological representations of non-slicing floor-plans [2] have been more recently proposed, providing new ideas and techniques for solving block placement problems and other related layout applications. among these topological representations, ordered trees exhibit a lower redundancy and, therefore, a provable smaller search space, which makes them the best topological candidate for solving general block placement problems. starting from the early eighties, binary trees have been widely used to represent slicing floorplans [7]. this paper shows that binary trees can efficiently model non-slicing floorplans as well, as there is a one-to-one mapping between the sets of binary and ordered trees representing the floorplan. moreover, this paper shows that binary trees exhibiting a certain property can be used to represent block placement configurations with symmetry constraints, which is very useful when dealing with device-level placement problems for analog layout. as the number of these trees is proven to be smaller than the number of symmetric-feasible sequence-pairs [1], using binary trees is better than using either sequence-pairs or o-trees when solving analog placement problems. a comparative evaluation, substantiating these theoretical results, has been carried out by providing alternative optimization engines to a placement tool operating in an industrial environment.
hierarchical performance macromodels of feasible regions for synthesis of analog and rf circuits. accurate performance modeling is essential for its usage in a circuit synthesis flow. only a small fraction of the entire design space is occupied by designs with meaningful behavior and performance. in this work, we have focussed on modeling these feasible regions accurately in contrast with modeling the entire design space. macromodels for the feasible regions were built hierarchically until the desired accuracy was achieved. an accuracy driven synthesis methodology is proposed to guide the identification of the feasible regions and dynamically enhance the performance of the macromodels. dynamic performance modeling ensures true convergence of our synthesis approach as opposed to existing static macromodel based techniques. we applied the proposed methodology for modeling and synthesis of several analog and rf circuits and the results demonstrate that our approach yields highly accurate design solutions in a much smaller time compared to simulation based approaches.
speeding up technology-independent timing optimization by network partitioning. technology-independent timing optimization is an important problem in logic synthesis. although many promising techniques have been proposed in the past, unfortunately they are quite slow and thus impractical for large networks. in this paper, we propose depart, a delay-based partitioner-cum-optimizer, which purports to solve this problem. given a combinational logic network that is to be optimized for timing, depart divides it into sub-networks using timing information and a constraint on the maximum number of gates allowed in a single sub-network. these sub-networks are then dispatched, one by one, to a standard timing optimizer. the optimized sub-networks are re-glued, generating an optimized network. the challenge is how to partition the original network into sub-networks so that the final solution quality after partitioning and optimization is comparable to that from the timing optimizer. we propose a partitioning technique that is timing-driven and is simple yet effective. we compare depart with speed_up, a state-of-the-art timing optimization tool, and with various partitioning techniques such as min-cut based and region growing, on a suite of large industrial and iscas circuits. on more than half of the benchmarks, depart yields run-time improvements of 20 to 450 times over a normal invocation of speed_up (the overall average improvement being 8 times), without compromising the solution quality much. min-cut and region growing partitioning schemes, not being timing-driven, perform poorly in terms of the final circuit delay.
dataflow-driven memory allocation for multi-dimensional signal processing systems. memory cost is responsible for a large amount of the chip and/or board area of customized video and image processing systems. in this paper, a novel background memory allocation and assignment technique is presented. it is intended for a behavioural algorithm specification, where the procedural ordering of the memory related operations is not yet fully fixed. instead of the more restricted classical scheduling-based explorations, starting from procedurally interpreted specifications in terms of loops, a novel optimization approach&mdash;driven by data flow analysis&mdash;is proposed. employing the estimated silicon area as a steering cost, this allocation/assignment technique yields one or (optionally) several distributed (multi-port) memory architecture(s) with fully-determined characteristics, complying with a given clock cycle budget for read/write operations. moreover, our approach can accurately deal with complex multi-dimensional signals by means of a polyhedral data-flow analysis operating with groups of scalars.
an architecture and a wrapper synthesis approach for multi-clock latency-insensitive systems. this paper presents an architecture and a wrapper synthesis approach for the design of multi-clock systems-on-chips. we build upon the initial work on multi-clock latency-insensitive systems by singh and theobald (2004), and provide a detailed system architecture with the following capabilities and benefits: (i) modules arc stalled only when needed, thereby avoiding unnecessary stalling, (ii) adequate metastability resolution is provided, (iii) handshake interfaces between modules are high-performance and low-latency, i.e., capable of transferring data packets on every clock cycle, (iv) ip cores with large clock distribution delays are correctly handled, and (v) an automated approach is provided for wrapper synthesis from formal specifications. for wrapper synthesis, we have developed an automated tool which accepts interface specifications in a high-level language (component wrapper language, or cwl), and automatically produces gate-level implementations of wrapper circuitry that will correctly and efficiently stall the synchronous modules depending on the availability of i/o channels. an optimization is introduced to reduce the cost of the wrapper circuitry by eliminating "busy waiting." a small set of benchmark examples is also proposed, and synthesis results for the tool are promising.
sequential synthesis using s1s. we present a mathematical framework for analyzing the synthesis of interacting finite state systems. the logic s1s is used to derive simple, rigorous, and constructive solutions to problems in sequential synthesis. we obtain exact and approximate sets of permissible fsm network behavior, and address the issue of fsm realizability. this approach is also applied to synthesizing systems with fairness and timed systems.
flute: fast lookup table based wirelength estimation technique. wirelength estimation is an important tool to guide the design optimization process in early design stages. in this paper, we present a wirelength estimation technique called flute. our technique is based on pre-computed lookup table to make wirelength estimation very fast and very accurate for low degree nets. we show experimentally that for flute, rmst, and hpwl, the average error in wirelength are 0.72%, 4.23%, and -8.71%, respectively, and the normalized runtime are 1, 1.24, and 0.16, respectively.
fractional cut: improved recursive bisection placement. in this paper, we present improvements to recursive bisection basedplacement. in contrast to prior work, our horizontal cut lines arenot restricted to row boundaries; this avoids a "narrow region"problem. to support these new cut line positions, a dynamic programmingbased legalization algorithm has been developed. thecombination of these has improved the stability and lowered thewire lengths produced by our feng shui placement tool.on benchmarks derived from industry partitioning examples,our results are close to those of the annealing based tool dragon,while taking only a fraction of the run time. on synthetic benchmarks,our wire lengths are nearly 23% better than those of dragon.for both benchmark suites, our results are substantially better thanthose of the recursive bisection based tool capo and the analyticplacement tool kraftwerk.
efficient solution space exploration based on segment trees in analog placement with symmetry constraints. the traditional way of approaching devicelevel placement problems for analog layout is to explore a huge search space of absolute placement representations, where cells are allowed to illegally overlap during their moves [2, 7, 8]. this paper presents a novel analog placement technique operating on the set of binary tree representations of the layout [3], where the typical presence of an arbitrary number of symmetry groups of devices is directly taken into account during the exploration of the solution space. the efficiency of the novel approach is due to a data structure called segment tree, mainly used in computational geometry.
coupled analysis of electromigration reliability and performance in ulsi signal nets. in deep submicron vlsi circuits, interconnect reliability due to electromigration and thermal effects is fast becoming a serious design issue particularly for long signal lines. this paper presents for the first time a rigorous coupled analysis of ac electromigration that are prevalent in signal lines and thermal effects arising due to joule heating of the wires. the analysis is applied to study the effect of technology scaling using itrs data, wherein the effects of increasing interconnect (cu) resistivity with line dimensions and the effect of a finite barrier metal thickness have been included. finally, we have also quantified the reliability implications for minimum sized vias in optimally buffered signal nets. our analysis suggests that for the optimally buffered interconnects, while the maximum current density in the line remains limited by the performance, the current density in the vias exceeds the reliability limits and therefore requires careful consideration in the physical design process flow.
compact and complete test set generation for multiple stuck-faults. we propose a novel procedure for testing all multiple stuck-faults in a logic circuit using two complementary algorithms. the first algorithm finds pairs of input vectors to detect the occurrence of target single stuck-faults independent of the occurrence of other faults. the second uses a sophisticated branch and bound procedure to complete the test set generation on the faults undetected by the first algorithm. the technique is complete and applies to all circuits. experimental results presented in this paper demonstrate that compact and complete test sets can be quickly generated for standard benchmark circuits.
timing analysis in presence of power supply and ground voltage variations. given the sensitivity of circuit delay to supply and ground voltagevalues, static timing analysis (sta) must take into account supplyvoltage variations. existing sta techniques allow one to verifythe timing at different process corners which effectively only considers cases where all the supplies are low or all are high. cases of mismatch between the supplies of driver and load are not considered. in practice, supply voltages are neither totally independentnor totally dependent. in this work, we consider the supply andground nodes of a logic gate to be either totally independent variables, or to be directly tied or connected to those of some other gate(s) in the circuit. we also assume that the exact supplyvoltage values are not known exactly, but that only upper/lowerbounds on them are known. in this framework, we propose newtiming models for logic gates and identify the worst-case voltagecon gurations for individual gates and for simple paths. we thengive an sta technique that provides the worst-case circuit delaytaking supply variations into account.
track assignment: a desirable intermediate step between global routing and detailed routing. routing is one of the most complex stages in the back-end design process. simple routing algorithms based on two stages of global routing and detailed routing do not offer appropriate opportunities to address problems arising from signal delay, cross-talk and process constraints. an intermediate stage of track assignment between global and detailed routing proves to be an ideal place to address these problems. with this stage it is possible to use global routing information to efficiently address these problems and to aid the detailed router in achieving the wiring completions. in this paper we formulate routing as a three stage process; global routing, track assignment and detailed routing. we describe the intermediate track assignment problem and suggest an efficient heuristic for its solution. we introduce cost metrics to model basic effects arising from connectivity. we discuss extensions to include signal integrity and process constraints. we propose a heuristic based on weighted bipartite matching as a core routine. to improve its performance additional heuristics based on lookahead and segment splitting are also suggested. experimental results are given to highlight the efficacy of track assignment stage in routing process.
m-trie: an efficient approach to on-chip logic minimization. boolean logic minimization is being increasingly applied to new applications which demands very fast and frequent minimization services. these applications typically offer very limited computing and memory resources rendering the traditional logic minimizers ineffective. we present a new approximate logic minimization algorithm based on ternary trie. we compare its performance with espresso-ii and rocm logic minimizers for routing table compaction and demonstrate that it is 100 to 1000 times faster and can run with a data memory as little as 16kb. it is also found that proposed approach can support up to 25000 incremental updates per seconds positioning itself as an ideal on-chip logic minimization algorithm.
complementary use of runtime validation and model checking. the increasing gap between design complexity and compute power for verification necessitates radically new solutions to meet the verification challenges for future generations of hardware designs. increasingly it will not be possible to completely validate hardware prior to fabrication. we will need to reconcile ourselves to the fact that hardware, like software, will be shipped with bugs. however, this can be acceptable with appropriate mechanisms for runtime validation that detect bugs and recover from them when needed. this paper takes a significant step in examining runtime validation as part of the verification methodology. it examines the strengths and weaknesses of runtime validation and how it may be used to complement model checking in a hybrid methodology. we consider the use of on-chip hardware for detecting bugs using hardware assertions. these assertions may be used for validating abstractions and assumptions for use in offline model checking. hardware based assertions monitor properties at runtime and do not suffer from the state explosion problem. offline model checking is used to validate globally distributed properties where runtime error detection has limitations in monitoring and responding to signals separated by many clock cycles. in this case the hardware based runtime validated abstractions and assumptions help in reducing the state space for model checking. our ideas are demonstrated on a highly concurrent, yet simple to understand token sharing protocol, as well as a fairly complex cache coherence system.
analysis of substrate thermal gradient effects on optimal buffer insertion. this paper studies the effects of the substrate thermal gradients on the buffer insertion techniques. using a non-uniform temperature-dependent distributed rc interconnect delay model, the buffer insertion problem is analyzed and design guidelines are provided to ensure the near-optimality of the signal performance in the presence of the thermal gradients. in addition, the effect of temperature-dependent driver resistance on the buffer insertion is studied. experimental results show that neglecting thermal gradients in the substrate and the interconnect lines can result in non-optimal solutions when using standard buffer insertion techniques and that these effects intensify with technology scaling.
shilpa: a high-level synthesis system for self-timed circuits. shilpa is a system for the high-level synthesis of self-timed circuits. it takes behavioral descriptions in a process+functional language called hopcp and produces a netlist for the actel field-programmable gate array (fpga), supported by the viewlogic tools. hopcp descriptions are initially translated into an intermediate form based on hypergraphs called hfgs. shilpa then applies action refinement, which is a technique for transforming hfgs into asynchronous hardware by a series of graph-based transformation rules. action refinement is characterized by incremental resource allocation and control decomposition. the major contributions of the proposed work are given
hierarchical interconnect circuit models. the increasing size of integrated systems combined with deep submicron physical modeling details creates an explosion in rlc interconnect modeling complexity of unmanageable proportions. interconnect extraction tools employ hierarchy to manage complexity, but this hierarchy is discarded via eliminating far away coupling terms when the equivalent rlc circuits are formed. the increasing dominance of capacitance coupling along with the emergence of on-chip inductance, however, makes the composite effect of far-away couplings increasingly evident. even if newly enforced design rules and practices will ultimately obviate the need for modeling these couplings for design verification, some approximation of the "exact" solution is required to validate these rules. this paper proposes an efficient hierarchical equivalent circuit representation of interconnect parasitics that utilizes the efficient hierarchical long-distance modeling already existing within extractors. results from a prototype simulator based on these hierarchical models demonstrates the simulation inaccuracy incurred when the far-away coupling terms are ignored. such a form of interconnect modeling may provide the key to hierarchical modeling of electro-magnetic interactions between large components on future gigascale systems.
caliber: a software pipelining algorithm for clustered embedded vliw processors. in this paper we describe a software pipelining framework, caliber (cluster aware load balancing retiming algorithm), suitable for compilers targeting clustered embedded vliw processors. caliber can be effectively used by embedded system designers to explore different code optimization alternatives, i.e., can assist the generation of high-quality customized retiming solutions for desired program memory size and throughput requirements, while minimizing register pressure. an extensive set of experimental results is presented, considering several representative benchmark loop kernels and a wide variety of clustered datapath configurations, demonstrating that our algorithm compares favorably with one of the best state-of-the-art algorithms, achieving up to 50% improvement in performance and up to 47% improvement in register requirements.
electromagnetic parasitic extraction via a multipole method with hierarchical refinement. the increasing interconnect density and operating frequencies of system-on-a-chip (soc) designs necessitates extraction of parasitic electromagnetic couplings beyond the localized confines of functional design blocks. in addition, soc design styles and gridless variable-width routing make it increasingly difficult to use precharacterized library shapes for parasitic extraction. a comprehensive capacitance and inductance extraction solution requires a hierarchical data representation and fast runtime algorithms. we illustrate through examples that both the multipole method and hierarchical refinement, which are the two most successful approaches for parasitic extraction to date, work efficiently only under certain, limiting conditions. to improve this situation we present an approach which combines the best of both methods into a concurrent multipole refinement representation of the electromagnetic interaction which is efficient for arbitrary interconnect configurations. we use a generalized formulation of electromagnetic interactions to exploit the similarities in capacitance and inductance extraction for greater efficiency.
design verification via simulation and automatic test pattern generation. we present a simulation-based method for combinational design verification that aims at complete coverage of specified design errors using conventional atpg tools. the error models used in prior research are examined and reduced to four types: gate substitution errors (gses), gate count errors (gces), input count errors (ices), and wrong input errors (wies). conditions are derived for a gate to be completely testable for gses; these conditions lead to small test sets for gses. near-minimal test sets are also derived for gces. we analyze redundancy in design errors and relate this to single stuck-line (ssl) redundancy. we show how to map all the foregoing error types into ssl faults, and describe an extensive set of experiments to evaluate the proposed method. our experiments demonstrate that high coverage of the modeled design errors can be achieved with small test sets.
pessimism reduction in crosstalk noise aware sta. high performance circuits are facing increasingly severe signal integrity problems due to crosstalk noise and crosstalk noise awareness has become an integral part of static timing analysis (sta). existing crosstalk noise aware sta methods compute noise induced delay uncertainty on a net by net basis and in a pessimistic way, without considering the overlap bounds of the victim and aggressor timing windows and realistic delay impact on early and late signal arrival times. since crosstalk induced delay on individual nets contribute cumulatively on data and clock paths, even small amounts of pessimism in computation can add up to produce several unrealistic timing violations. unlike glitch noise analysis where noise often attenuates during propagation, quality of delay noise analysis is severely affected by any pessimism in noise estimation and can unnecessarily cost valuable silicon and design resources for fixing unreal violations. in this paper, we propose two temporal techniques to reduce pessimism in crosstalk noise aware sta. the first method, "effective delay noise", is a net based method where the exact overlap points of victim and aggressor timing windows are considered to obtain the part of delay noise that actually impacts early and late signal arrival times. the second method, "path based delay noise", is a path based method where the reduced arrival uncertainty of the nets of a given path are utilized for pessimism reduction. we also propose a novel "uncertainty propagation" technique as part of the second method, which results in an iteration free crosstalk noise aware sta of the path with significantly reduced pessimism. the two techniques are combined in a proposed methodology that is compatible with existing industrial static timing analyzers with very little computational overhead compared to the traditional noise aware sta and a significant improvement in eliminating unreal violations. the proposed techniques resulted in 77% reduction of worst case negative slack and 57% reduction in the number of failing paths in the setup analysis of a 90nm industrial design.
numerical integration algorithms and asymptotic waveform evaluation (awe). an intuitive relationship between numerical integration algorithms and awe is established. a small number of data points generated during a brief fixed timestep numerical integration of linear(ized) circuits are used to form sampled waveform integration, correction and extrapolation (swice) models. this method preserves the efficiency of the awe technique, while increasing the accuracy and generality. the strengths of such an approach are illustrated from a theoretical view, as well as with practical examples
physical and reduced-order dynamic analysis of mems. in this paper, we first present an efficient physical level simulationmethod for the dynamic analysis of electrostatic micro-electro-mechanicalsystems (mems). this method is then used to analyzemems dynamics. stiffness hardening or softening of mem structureshas been shown to depend both on the applied voltage andthe geometry. the existence of multiple resonant peaks in the frequencyresponse diagram has been presented. we have shown thata dc bias along with an appropriate ac bias can give fast switchingat a considerably less peak power requirement. finally, a reducedorder model has been developed based on karhunen-loèvedecomposition for the dynamic simulation of mems. reduced ordermodels are cheap in terms of memory and computational timeand are needed to perform fast and efficient system-level compositecircuit and micro-mechanical simulations.
constraint satisfaction for relative location assignment and scheduling. tight data-and timing constraints are imposed by communication and multimedia applications. the architecture for the embedded processor imply resource constraints. instead of random-access registers, relative location storages or rotating register files are used to exploit the available parallelism of resources by means of reducing the initiation interval in pipelined schedules. therefore, the compiler or synthesis tool must deal with the difficult tasks of scheduling of operations and location assignment of values while respecting all the constraints including the storage file capacity. this paper presents a method that handles constraints of relative location storages during scheduling together with timing and resource constraints. the characteristics of the coloring of conflict graphs, representing the relative overlap of value instances, are analyzed in order to identify the bottlenecks for location assignment with the aim of serializing their lifetimes. this is done with pairs of loop instances of values until it can be guaranteed that all constraints will be satisfied. experiments show that high quality schedules for kernels and inner loops can be efficiently obtained.
cycle time and slack optimization for vlsi-chips. we consider the problem of finding an optimal clock schedule, i.e. optimal arrival times for clock signals at latches of a vlsi chip. we describe a general model which includes all previously considered models. then we show how to optimize the cycle time and optimally balance slacks on data paths and on clocktree paths.the problem of finding a clock schedule with the optimum cycle time was solved before, either by linear programming or by binary search, using a test for negative circuits in a digraph as a subroutine. we show for the first time that a direct combinatorial algorithm solves this problem optimally. incidentally, this yields a new efficient method for timing analysis with transparent latches.moreover, we extend this algorithm to the slack balancing problem: to make the chip less sensitive to routing detours, process variations and manufacturing skew it is desirable to have as few critical paths as possible. we show how to find the clock schedule with minimum number of critical paths (optimum slack distribution) in a well-defined sense. rather than fixed clock arrival times we show how to obtain as large as possible intervals for the clock arrival times. this can be considered as slack on clocktree paths. indeed, we can find the global optimum of simultaneous optimization of slacks on all data paths and clocktree paths.all the above is done by very efficient network optimization algorithms, based on parametric shortest paths. our computational results with recent ibm processor chips show that the number of critical paths decreases dramatically, in addition to a considerable improvement of the cycle time. the running times are reasonable even for the largest designs.
post-verification debugging of hierarchical designs. as vlsi designs grow in complexity and size, errors become more frequent and difficult to track. recent developments have automated most of the verification tasks but debugging still remains a resource-intensive, manually conducted procedure. this paper bridges this gap as it develops robust automated debugging methodologies that complement verification processes. unlike prior debugging techniques, the proposed one exploits the hierarchical nature of modern designs to improve the performance and quality of debugging. it also formulates the problem in terms of quantified boolean formula satisfiability to obtain dramatic reduction in memory requirements, which allows for debugging of large designs. extensive experiments conducted on industrial and benchmark designs confirm the efficiency and practicality of the proposed approach.
debugging sequential circuits using boolean satisfiability. logic debugging of today's complex sequential circuits is an important problem. in this paper, a logic debugging methodology for multiple errors in sequential circuits with no state equivalence is developed. the proposed approach reduces the problem of debugging to an instance of boolean satisfiability. this formulation takes advantage of modern boolean satisfiability solvers that handle large circuits in a computationally efficient manner. an extensive suite of experiments with large sequential circuits confirm the robustness and efficiency of the proposed approach. the results further suggest that boolean satisfiability provides an effective platform for sequential logic debugging.
precomputation-based sequential logic optimization for low power. we address the problem of optimizing logic-level sequential circuits for low power. we present a powerful sequential logic optimization method that is based on selectively precomputing the output logic values of the circuit one clock cycle before they are required, and using the precomputed values to reduce internal switching activity in the succeeding clock cycle. we present two different precomputation architectures which exploit this observation.we present an automatic method of synthesizing precomputational logic so as to achieve maximal reductions in power dissipation. we present experimental results on various sequential circuits. up to 75% reductions in average switching activity and power dissipation are possible with marginal increases in circuit area and delay.
automatic gate-level synthesis of speed-independent circuits. a cad tool for the synthesis of asynchronous control circuits using basic gates such as and gates and or gates is presented. the synthesized circuits are speed-independent-that is, they work correctly regardless of individual gate delays. synthesis results for a variety of specifications taken from industry and previously published examples are presented. the speed-independent circuits are compared with those non-speed-independent circuits synthesized using previously described algorithms, in which delay elements are added to remove circuit hazards. these synthesis results show that the new circuits are on average approximately 25% faster with an area penalty of only 15%. this work demonstrates that direct synthesis of gate-level speed-independent circuits is not only feasible, but also produces robust and relatively efficient circuits compared to those synthesized with timing constraints
estimation and bounding of energy consumption in burst-mode control circuits. this paper describes two techniques to quantify energy consumption of burst-mode asynchronous (clock-less) control circuits. the circuit specifications considered are extended burst-mode specifications, and the implementations are multi-level logic implementations whose outputs are guaranteed to be free of any voltage glitches (hazards). both techniques use stochastic analysis to combine a small number of simulations in order to quantify average energy per external signal transition. the first technique uses n-valued simulation to derive mathematically tight upper and lower bounds of energy consumption. using this technique we bound the effect of hazards under all possible operating conditions and environments for a given circuit. additionally, to drive synthesis tools for low-power, we propose a second technique that uses fixed-delay simulation to derive a realistic estimate of energy consumption within our derived upper and lower bounds. we demonstrate the feasibility of both these techniques on a variety of burst-mode control circuits used in an industrial-quality chip. our preliminary results indicate that less than 5% of the power of typical multi-level burst-mode circuits can be attributed to hazards.
hierarchical partitioning. partitioning of digital circuits has become a key problem area during the last five years. benefits from new technologies like multi-chip-modules or logic emulation strongly depend on partitioning results. most published approaches are based on abstract graph models constructed from flat netlists, which consider only connectivity information. the approach presented in this paper uses information on design hierarchy in order to improve partitioning results and reduce problem complexity. designs up to 150k gates have been successfully partitioned by descending and ascending the hierarchy. compared to a standard k-way iterative improvement partitioning approach results are improved by up to 65% and runtimes are decreased by up to 99%.
faster sat and smaller bdds via common function structure. the increasing popularity of sat and bdd techniques in verification and synthesis encourages the search for additional speed-ups. since typical sat and bdd algorithms are exponential in the worst-case, the structure of real-world instances is a natural source of improvements. while sat and bdd techniques are often presented as mutually exclusive alternatives, our work points out that both can be improved via the use of the same structural properties of instances. our proposed methods are based on efficient problem partitioning and can be easily applied as pre-processing with arbitrary sat solvers and bdd packages without source code modifications.finding a better variable-ordering is a well recognized problem for both sat solvers and bdd packages. currently, all leading edge variable-ordering algorithms are dynamic, in the sense that they are invoked many times in the course of the "host" algorithm that solves sat or manipulates bdds. examples include the dlcs ordering for sat solvers and variable-sifting during bdd manipulations. in this work we propose a universal variable-ordering mince (min cut etc.) that pre-processes a given boolean formula in cnf. mince is completely independent from target algorithms and outperforms both dlcs for sat and variable sifting for bdds. we argue that mince tends to capture structural properties of boolean functions arising from real-world applications. our contribution is validated on the iscas circuits and the dimacs benchmarks. empirically, our technique often outperforms existing techniques by a factor of two or more. our results motivate search for stronger dynamic ordering heuristics and combined static/dynamic techniques.
performance efficiency of context-flow system-on-chip platform. recent efforts in adapting computer networks into system-on-chip(soc), or network-on-chip, present a setback to the traditionalcomputer systems for the lack of effective programming model,while not taking full advantage of the almost unlimited on-chipbandwidth. in this paper, we propose a new programming model,called context-flow, that is simple, safe, highly parallelizable yettransparent to the underlying architectural details. an soc platformarchitecture is then designed to support this programmingmodel, while fully exploiting the physical proximity between theprocessing elements. we demonstrate the performance efficiencyof this architecture over bus based and packet-switch based networksby two case studies using a multi-processor architecture simulator.
generic ilp versus specialized 0-1 ilp: an update. optimized solvers for the boolean satisfiability (sat) problem have many applications in areas such as hardware and software verification, fpga routing, planning, etc. further uses are complicated by the need to express "counting constraints" in conjunctive normal form (cnf). expressing such constraints by pure cnf leads to more complex sat instances. alternatively, those constraints can be handled by integer linear programming (ilp), but generic ilp solvers may ignore the boolean nature of 0--1 variables. therefore specialized 0--1 ilp solvers extend sat solvers to handle these so-called "pseudo-boolean" constraints.this work provides an update on the on-going competition between generic ilp techniques and specialized 0--1 ilp techniques. to make a fair comparison, we generalize recent ideas for fast sat-solving to more general 0--1 ilp problems that may include counting constraints and optimization. another aspect of our comparison is evaluation on 0--1 ilp benchmarks that originate in electronic design automation (eda), but that cannot be directly solved by a sat solver. specifically, we solve instances of the max-sat and max-ones optimization problems which seek to maximize the number of satisfied clauses and the "true" values over all satisfying assignments, respectively. those problems have straightforward applications to sat-based routing and are additionally important due to reductions from max-cut, max-clique, and min vertex cover. our experimental results show that specialized 0--1 techniques tend to outperform generic ilp techniques on boolean optimization problems as well as on general eda sat problems.
is wire tapering worthwhile? wire sizing and buffer insertion/sizing are critical optimizations in deep submicron design. the past years have seen several studies of buffer insertion, wire sizing, and their simultaneous optimization. when wiring long interconnect, tapering, i.e., reducing the wire width as the distance from the driver increases, has proven effective. however, tapering is not widely utilized in industry since it is difficult to integrate into a complete routing methodology. this work examines the benefits of wire sizing with tapering when combined with buffer insertion. we perform several experiments with actual ibm technologies. results indicate that wire tapering reduces delay typically by less than 5% compared to uniform wire sizing, when buffers can be inserted. consequently, we suggest that it may not be worthwhile to maintain a routing methodology that supports wire tapering.
accurate estimation of global buffer delay within a floorplan. closed formed expressions for buffered interconnect delay approximation have been around for some time. however, previous approaches assume that buffers are free to be placed anywhere. in practice, designs frequently have large blocks that make the ideal buffer insertion solution unrealizable. the theory of otten (1998) is extended to show how one can model the blocks into a simple delay estimation technique that applies both to two-pin and to multi-pin nets. even though the formula uses one buffer type, it shows remarkable accuracy in predicting delay when compared to an optimal realizable buffer insertion solution. potential applications include wire planning, timing analysis during floorplanning or global routing. our experiments show that our approach accurately predicts delay when compared to constructing a realizable buffer insertion with multiple buffer types.
a general framework for vertex orderings, with applications to netlist clustering. we present a general framework for the construction of vertex orderings for netlist clustering. our window algorithm constructs an ordering by iteratively adding the vertex with highest attraction to the existing ordering. variant choices for the attraction function allow our framework to subsume many graph traversals and clustering objectives from the literature. the dp-rp method of [3] is then applied to optimally split the ordering into a k-way clustering. our approach is adaptable to use-specified cluster size constraints. experimental results for clustering and multi-way partitioning are encouraging.
an assembly-level execution-time model for pipelined architectures. the aim of this work is to provide an elegant and accurate static execution timing model for 32-bit microprocessor instruction sets, covering also inter-instruction effects. such effects depend on the processor state and the pipeline behavior, and are related to the dynamic execution of assembly code. the paper proposes a mathematical model of the delays deriving from instruction dependencies and gives a statistical characterization of such timing overheads. the model has been validated on a commercial architecture, the intel486, by means of timing analysis of a set of benchmarks, obtaining an error within 5%. this model can be seamlessly integrated with a static energy consumption model in order to obtain precise software power and energy estimations.
minimum-buffered routing of non-critical nets for slew rate and reliability control. in high-speed digital vlsi design, bounding the load capacitance at gate outputs is a well-known methodology to improve coupling noise immunity, reduce degradation of signal transition edges, and reduce delay uncertainty due to coupling noise. bounding load capacitance also improves reliability with respect to hot-carrier oxide breakdown and ac self-heating in interconnects, and guarantees bounded input rise/fall times at buffers and sinks.this paper introduces a new minimum-buffer routing problem (mbrp) formulation which requires that the capacitive load of each buffer, and of the source driver, be upper-bounded by a given constant. our contributions include the following.&bull; we give linear-time algorithms for optimal buffering of a given routing tree with a single (inverting or non-inverting) buffer type.&bull; for simultaneous routing and buffering with a single non-inverting buffer type, we give a factor 2(1 + &epsilon;) approximation algorithm and prove that no algorithm can guarantee a factor smaller than 2 unless p=np. for the case of a single inverting buffer type, we give a factor 4(1 + &epsilon;) approximation algorithm.&bull; we give local-improvement and clustering based mbrp heuristics with improved practical performance, and present a comprehensive experimental study comparing the runtime/quality tradeoffs of the proposed mbrp heuristics on test cases extracted from recent industrial designs.
free space management for cut-based placement. ip blocks and large macro cells are increasingly prevalent in physical design, actually causing an increase in the available free space for the dust logic. we observe that top-down placement based on recursive bisection with multilevel partitioning performs poorly on these porous designs. however, analytic solvers have the ability to find the natural distribution of cells in the layout. consequently, we propose an enhancement to cut-based placement called analytic constraint generation (acg). acg utilizes an analytic engine to set constraints for the multi-level partitioner. we show that for real industry designs, acg significantly improves the performance of cut-based placement, as implemented within a state-of-the-art industrial placer.
fast power estimation for deterministic input streams. the power dissipated by digital systems under realistic input stimuli is not accurately described by a single average value, but by a waveform that shows how power consumption varies over time as the system responds to the inputs. we face the problem of obtaining accurate power waveforms for combinational and sequential circuits under typical usage patterns. we propose a multi level simulation engine that achieves high accuracy in estimating the average power as well as the time domain power waveform with high computational efficiency.
reuse of design objects in cad frameworks. the reuse of well-tested and optimized design objects is an important aspect for decreasing design times, increasing design quality, and improving the predictability of designs. reuse spans from the selecting cells from a library up to adapting already designed objects.in this paper, we present a new model for reusing design objects in cad frameworks. based on experiences in other disciplines, mainly in software engineering and case-based reasoning, we developed a feature-based model to describe design objects and their similarities. our model considers generic modules as well as multi-functional units. we discuss the relationships of the model to design process and to the configuration hierarchy of complex design objects. we examined our model with the prototype system rodeo.
function unit specialization through code analysis. many previous attempts at asip synthesis have employed template matching techniques to target function units to application code, or directly design new units to extract maximum performance. this paper presents an entirely new approach to specializing hardware for application specific needs. in our framework of a parameterized vliw processor, we use a post-modulo scheduling analysis to reduce the allocated hardware resources while increasing the code's performance. initial results indicate significant savings in area, as well as optimizations to increase fir filter code performance 200% to 300%.
weibull based analytical waveform model. current cmos technologies are characterized by interconnectlines with increased relative resistance w.r.t. driver outputresistance. designs generate signal waveshapes that are verydifficult to model using a single parameter model such as thetransition time. in this paper, we present a simple and robustparameter analytical expression for waveform modeling based onthe weibull cumulative distribution function. the weibull modelaccurately captures the variety of waveshapes without introducingsignificant runtime overhead and produces results with less than5% error. we also present a fast and simple algorithm to convertwaveforms obtained by circuit simulation to the weibull model. amethodology for characterizing gates for the new model is alsopresented. simulation results for many single and multiple inputgates show errors well below 5%. our model can be used in amixed environment where some signals may still be characterizedby a single parameter.
modeling unbuffered latches for timing analysis. unbuffered latches are often used in high-performance designs with custom timing flows. adding these circuits to a standard library enables improved designs without blowing the library size. we observe a high potential frequency gain (up to 16%) for smaller power consumption. accurate models for static timing analysis are required to reach a good point on the safety to performance trade-off. we are proposing a complete modeling methodology that can fit in a standard timing analysis flow. an accurate n-model is presented for the input impedance of an unbuffered latch with less than 2% error. we also present a new setup criteria required for these latches. we also show that more advanced waveform models are required to model the output. a weibull waveform model proves to be effective in this case.
efficient use of large don't cares in high-level and logic synthesis. this paper describes optimization techniques using don't-care conditions that span the domain of high-level and logic synthesis. the following three issues are discussed: 1) how to describe and extract don't-care conditions from high-level descriptions; 2) how to pass don't-care conditions from high-level to logic synthesis; and 3) how to optimize the logic using don't-care conditions. efficient techniques are given for these three problems which allow the use of large don't-care sets. results from several examples demonstrate that these techniques are very effective for both area and delay minimization.
zamlog: a parallel algorithm for fault simulation based on zambezi. we present a new multiprocessor sequential circuit fault simulator, zamlog, based on a novel uniprocessor simulator, zambezi. both the fault and test sets are partitioned for multiprocessor simulation. the parallelization technique, designed to preserve the efficiency of zambezi, is simple to implement and has low communication requirements. experimental results indicate that zamlog can obtain speedups of up to 95. the speedups obtained and the scalability are between 3 and 10 times better than any reported in the literature. furthermore, the speed-ups obtained are with respect to a uniprocessor algorithm which is superior, by an average of 40%, to those used to gauge the speed-ups of previous parallel systems.
the a to z of socs. the exploding complexity of new chips and the ever decreasing time-to-market window are forcing fundamental changes in the way systems are designed. the advent of systems-on-chip (soc) based on pre-designed intellectual-property (ip) cores has become an absolute necessity for embedded systems companies to remain competitive. designing an soc, however, is extremely complex, as it encompasses a range of difficult problems in hardware and software design. this paper explains a wide range of soc issues including market drivers and trends, technology and integration aspects, early architecture definition, methodology, hardware and software design and verification techniques.
low-power programmable routing circuitry for fpgas. we propose two new fpga routing switch designs that are programmable to operate in three different modes: high-speed, low-power or sleep. high-speed mode provides similar power and performance to a traditional routing switch. in low-power mode, speed is curtailed in order to reduce power consumption. our first switch design reduces leakage power consumption by 36-40% in low-power vs. high-speed mode (on average); dynamic power is reduced by up to 28%. leakage power in sleep mode is 61% lower than in high-speed mode. a second switch design offers a 36% smaller area overhead and reduces leakage by 28-30% in low-power vs. high-speed mode. the proposed switch designs require only minor changes to a traditional routing switch, making them easy to incorporate into current fpga interconnect. the applicability of the new switches is motivated through an analysis of timing slack in industrial fpga designs. specifically, we show that a considerable fraction of routing switches may be slowed down (operate in low-power mode), without impacting overall design performance.
improving coverage analysis and test generation for large designs. state space techniques have proven to be useful for measuring and improving the coverage of test vectors that are used during functional validation via simulation. by comparing the state and edge coverage provided by tests with that which is possible in the design's state graph, the designer can estimate how well tested the design is and identify areas that need better testing. unfortunately, for many interesting designs, the full state graph may be too large to fully explore, or if it is explorable, the resulting coverage may be so low as to provide limited feedback. several techniques have been proposed that identify and work with an interesting subset of the design's state machines, but they still require computing the full state graph before projecting it. in this paper we discuss projection directed state exploration, in which a projection from the full graph is found while exploring only the relevant portion of the full graph. even with this limited exploration, bdd size blowup is still a problem. to deal with this, we have also developed several interactive tools that provide feedback to the designer, and allow them to add hints to help with the exploration.
simultaneous communication and processor voltage scaling for dynamic and leakage energy reduction in time-constrained systems. we propose a new technique for the combined voltage scaling of processors and communication links, taking into account dynamic as well as leakage power consumption. the voltage scaling technique achieves energy efficiency by simultaneously scaling the supply and body bias voltages in the case of processors and buses with repeaters, while energy efficiency on fat wires is achieved through dynamic voltage swing scaling. we also introduce a set of accurate communication models for the energy estimation of voltage scalable embedded systems. in particular, we demonstrate that voltage scaling of bus repeaters and dynamic adaption of the voltage swing on fat wires can significantly influence the system's energy consumption. experimental results, conducted on numerous generated benchmarks and a real-life example, demonstrate that substantial energy savings can be achieved with the proposed techniques.
computing the entire active area/power consumption versus delay trade-off curve for gate sizing with a piecewise linear simulator. the gate sizing problem is the problem of finding load drive capabilities for all gates in a given boolean network such, that a given delay limit is kept, and the necessary cost in terms of active area usage and/or power consumption is minimal. this paper describes a way to obtain the entire cost versus delay trade-off curve of a combinational logic circuit in an efficient way. every point on the resulting curve is the global optimum of the corresponding gate sizing problem. the problem is solved by mapping it onto piecewise linear models in such a way, that a piecewise linear (circuit) simulator can do the job. it is shown that this setup is very efficient, and can produce trade-off curves for large circuits (thousands of gates) in a few minutes. benchmark results for the entire set of mcnc '91 two-level examples are given.
equivalent design representations and transformations for interactive scheduling. it is pointed out that high-level synthesis (hls) requires more designer interaction to better meet the needs of experienced designers. however, attempts to create a highly interactive synthesis process are hampered by incompatibility of various representations used during synthesis. to overcome this problem, equivalent representations are needed, as well as equivalence-preserving synthesis transformations. the structured finite state machine (sfsm) design model for scheduled behavior is presented, its equivalence to the control data flow graph (cdfg) model is shown, and primitive behavior-preserving transformations for scheduling are defined. this model and these transformations have been integrated into the bif interactive environment to permit manual rescheduling of a design
efficient orthonormality testing for synthesis with pass-transistor selectors. this paper presents the mapping problem for pass transistor selector mapping, which has not been addressed before. pass transistor synthesis is potentially important for semi- or full-custom design techniques, which are increasingly attracting attention. pass transistors have the advantage that fewer transistors are needed, and that circuits with high fanin and small delay can be constructed. technology mapping approaches in the existing literature cannot handle these selectors, due to the restriction of 1-hot encoding of the control signals. we present a new algorithm to address this problem, which is based on the novel idea of a general boolean oracle. our oracle is based on atpg techniques, and compared to bdds, the oracle has the advantage that failure to complete only affects optimization locally, and does not hinder optimization elsewhere in the logic. a limitation of bdds is that it is difficult to complete the algorithm if a bdd grows too large. the experimental results show up to 82% improvement in transistor count for the mcnc combinatorial multi-level examples.
analytical macromodeling for high-level power estimation. this paper present a new macromodeling technique for high-level power estimation. our technique is based on a parameterizable analytical model that relies exclusively on statistical information of the circuit's primary inputs. during estimation, the statistics of the required metrics are extracted from the input stream, and a power estimate is obtained by evaluating a model function that has been characterized in advance. our model yields power estimates within seconds, because it does not rely on the statistics of the circuit's primary outputs and, consequently, does not perform any simulation during estimation. moreover, it achieves better accuracy than previous macromodeling approaches by taking into account both spatial and temporal correlations in the input stream.in experiments with the iscas-85 combinational circuits, the average absolute relative error of our power macromodeling technique was at most 1.8%. the worst-case error was at most 12.8%. for a ripple-carry adder family, in comparison with power estimates that were obtained using spice, the average absolute and worst-case errors of our model's estimates were at most 5.1% and 19.8%, respectively.in addition to power dissipation, our macromodeling technique can be used to estimate the statistics of a circuit's primary outputs with very low average errors. it is thus suitable for power estimation in core-based systems with pre-characterized blocks. once the metrics of the primary inputs are known, the power dissipation of the entire system can be estimated by simply propagating this information through the blocks using their corresponding model functions.
a new built-in self-test approach for digital-to-analog and analog-to-digital converters. this paper proposes a test approach and circuitry suitable for built-in self-test (bist) of digital-to-analog (d/a) and analog-to-digital (a/d) converters. offset, gain, linearity and differential linearity errors are tested without using test equipment. the proposed bist structure decreases the test cost and test time. the bist circuitry has been designed to d/a and a/d converters using cmos 1.2 &mgr;m technology. by only a minor modification the test structure would be able to localize the fail situation. the small value of area overhead (aoh), the simplicity and efficiency of the proposed bist architecture seem to be promising for manufacturing.
design space exploration for a umts front-end exploiting analog platforms. universal mobile telecommunication system (umts) front end design is challenging because of the need to optimize power while satisfying a very high dynamic range requirement. dealing with this design problem at the transistor level does not allow exploring efficiently the design space, while using behavioral models does not allow taking into consideration important second-order effects. we present an extension of the platform-based design methodology originally developed for digital systems to the analog domain to conjugate the need of higher levels of abstraction to deal with complexity as well as the one of capturing enough of the actual circuit-level characteristics to deal with second order effects. we show how this methodology applied to the umts front-end design yields power savings as large as 47% versus an original hand optimized design.
a signature based approach to regularity extraction. regularity extraction is an important step in the design flow of datapath-dominated circuits. this paper outlines a new method that automatically extracts regular structures from the netlist. the method is general enough to handle two types of designs: designs with structured cluster information for a portion of the datapath components that are identified at the hdl level; and designs with no such structured cluster information. the method analyzes the circuit connectivity and uses signature based approaches to recognize regularity.
efficient analog platform characterization through analog constraint graphs. we propose a scheme for improving the efficiency of the characterization process for system-level models of analog circuits within the analog platform based design paradigm. we leverage designer knowledge to map basic functional requirements of the circuit into circuit parameters relations so that the sampling space can be significantly reduced. a set of equalities and inequalities in the circuit parameters is used to represent the constraints. a feasible parameter space lies at the intersection of the sets of design parameters that satisfy equalities and inequalities, defining a manifold in the parameter space. we introduce a bipartite graph representation denoted analog constraint graphs (acg) to represent these constraints. acgs are instrumental for obtaining a random configuration generator that samples configurations in the manifold. the sampler is automatically translated into executable code to fit the characterization framework starting from a mathematical description of constraints. results show that the automatically generated samplers are comparable in terms of code efficiency with hand-written ones. furthermore, a heuristics to generate uniformly distributed configuration enabled by the tools is presented and applied to a complex adc design, yielding a reduction in power consumption by more than 28%.
efficient ltl compilation for sat-based model checking. this work describes an algorithm of automata construction for ltl safety properties, suitable for bounded model checking. existing automata construction methods are tailored to bdd-based symbolic model checking. the novelty of our approach is that we construct deterministic automata, unlike the standard approach, which constructs nondeterministic automata. we show that the proposed method has significant advantages for bounded model checking over traditional methods.
how to bridge the abstraction gap in system level modeling and design. as more and more processors and subsystems are integrated in a single system, the verification bottleneck is driving designers away from rtl and rtl-like strategies for verification and design to higher abstraction levels. increasing system complexity at the other hand requires much faster simulation and analysis tools. this is leading to new standards and tools around transaction level modeling. languages such as systemc and systemverilog are rich in behavioral and structural constructs which enable modeling designs at different levels of abstraction without imposing a top-down or bottom-up design flow. in fact, most design flows are iterative and modules at different levels of abstractions have to be considered. a more abstract model is very useful to increase simulation speed and to improve formal verification. systemc and systemverilog stress the importance of verification support for complex socs including improvement for hardware verification as well as for the verification of hardware dependent software. in todays design flows the software development can often only start after the hardware is available. this causes unacceptable delays for the software development. the idea of transaction level modeling (tlm) is to provide in an early phase of the hardware development transaction level models of the hardware. based on these tlms a fast enough simulation environment is the basis for the development of hardware and hardware dependent software. the presumption is to run these transaction level models at several tens or some hundreds of thousand transactions per second which should be fast enough for system level modeling and verification.
ficom: a framework for incremental consistency maintenance in multi-representation, structural vlsi databases. a framework for vlsi design databases which supports fine-grained incremental consistency maintenance between different views of a design is presented. the framework provides for structural views of a design such as logic or circuit schematic, symbolic layout, and physical layout, and supports representation of geometric design rule constraints between design objects. a prototype interactive design system which provides a user interface to three structural view types (gate and circuit schematics, and symbolic layouts) is presented. features of the prototype system are automatic propagation of incremental operations between views and high-speed online generation and evaluation of geometric design rule constraints
high-level synthesis: an essential ingredient for designing complex asics. it is common wisdom that synthesizing hardware from higher-level descriptions than verilog incurs a performance penalty. the case study here shows that this need not be the case. if the higher-level language has suitable semantics, it is possible to synthesize hardware that is competitive with hand-written verilog rtl. differences in the hardware quality are dominated by architecture differences and, therefore, it is more important to explore multiple hardware architectures. this exploration is not practical without quality synthesis from higher-level languages.
design and cad challenges in sub-90nm cmos technologies. this paper discusses design challenges of scaled cmos circuits insub-90nm technologies for high-performance digital applications.to continue scaling of the cmos devices deep into sub-90nm tech-nologies,fully depleted soi, strained-si on sige, finfets withdouble gate, and even further, three-dimensional circuits will be uti-lizedto design high-performance circuits. we will discuss uniquedesign aspects and issues resulting from this scaling such as gate-to-body tunneling, self-heating, reliability issues, and process vari-ations.as the scaling approaches various physical limits, new soidesign issues such as vt modulation due to leakage, low-voltageimpact ionization, and higher v{t,lin} to maintain adequate v{t,sat},continue to surface.with an eye towards the future, design andcad issues related to sub-65nm device structures such as doublegate finfet will be discussed.
system level design and verification using a synchronous language. synchronous languages such as esterel, lustre, signal, andothers were originally developed for safety-critical embedded software and compiled into c. they have recently been extended to hardware with new language features and compilers to rtl. contrary to traditional hdl languages (verilog, vhdl) and recent system-level languages (systemc, system verilog), they have well defined formal semantics,which facilitate bug avoidance using correct-by-constructioncompilation and verification techniques.the tutorial will demonstrate what the synchronous language offers for the modeling, design, analysis and implementation of systems that comprise hardware and software.it will be based on esterel. esterel models have proved tobe useful for rapid design space exploration and verificationat system level, without resorting to detailed implementation and slow bit-level event-based simulation. we show how to model control-dominated ip blocks at a higher levelof abstraction and how to use the target c code or rtl inconjunction with other system-level tools. case studies include examples of design space exploration by synthesizing equivalent hardware or software from the same esterel description, with formal verification of safety properties such as bus protocol conformance. we conclude with a review of future research directions.
efficient breadth-first manipulation of binary decision diagrams. we propose new techniques for efficient breadth-first iterative manipulation of robdds. breadth-first iterative robdd manipulation can potentially reduce the total elapsed time by multiple orders of magnitude compared to the conventional depth-first recursive algorithms when the memory requirement exceeds the available physical memory. however, the breadth-first manipulation algorithms proposed so far have had a large enough overhead associated with them to make them impractical. our techniques are geared towards minimizing the overhead without sacrificing the speed up potential. experimental results indicate considerable success in that regard.
the disjunctive decomposition of logic functions. we present an algorithm for extracting a disjunctive decomposition from the bdd representation of a logic function f. the output of the algorithm is a multiple-level netlist exposing the hierarchical decomposition structure of the function. the algorithm has theoretical quadratic complexity in the size of the input bdd. experimentally, we were able to decompose most synthesis benchmarks in less than one second of cpu time, and to report on the decomposability of several complex iscas combinational benchmarks. we found the final netlist to be often close to the output of more complex dedicated optimization tools.
exploiting multi-cycle false paths in the performance optimization of sequential circuits. it is shown how the notion of false paths, traditionally defined for combinational logic circuits, can be extended to the sequential context by considering the operation of the circuit over multiple clock-cycles. multicycle false paths can be removed from the circuit using techniques similar to those proposed for combinational logic circuits. this observation offers techniques to improve the performance of sequential logic circuits. a preliminary implementation of an algorithm that uses these ideas shows significant performance improvement on some typical benchmark circuits at a very modest area overhead
directional bias and non-uniformity in fpga global routing architectures. this paper investigates the effect of the prefabricated routing track distribution on the area-efficiency of fpgas. the first question we address is whether horizontal and vertical channels should contain the same number of tracks (capacity), or if there is a density advantage with a directional bias. secondly, should the channels have a uniform capacity, or is there an advantage when capacities vary from channel to channel? the key result is that the most area-efficient global routing architecture is one with uniform (or very nearly uniform) channel capacities across the entire chip in both the horizontal and vertical directions. several non-uniform and directionally-biased architectures, however, are fairly area-efficient provided that appropriate choices are made for the pin positions on the logic blocks and the logic array aspect ratio.
formalizing designer's preferences for multiattribute optimization with application to leakage-delay tradeoffs. traditional single-attribute optimization problems force a designer to choose either power or delay as the objective function and minimize it with constraints on other attributes. however this approach does not provide the designer with enough freedom to incorporate tradeoffs between various attributes such as leakage and delay. in this paper we present a utility theoretic approach for the joint optimization of leakage and delay. this provides a general framework for quantifying a designer's preferences for tradeoffs between leakage and delay. we show that energy-delay product (edp) is an element of a larger class of such utility functions. the resulting multi-attribute optimization problem is modeled as a convex gate sizing problem that is solved using geometric programming. the resulting solution is a design point that is optimal with respect to the designer's preferences.
using complete-1-distinguishability for fsm equivalence checking. this article introduces the notion of a complete-1-distinguishability (c-1-d) property for simplifying equivalence checking of finite state machines (fsms). when a specification machine has the c-1-d property, the traversal of the product machine can be eliminated. instead, a much simpler check suffices. the check consists of first obtaining a 1-equivalence mapping between the individually reachable states of the specification and the implementation machines, and then checking that it is a bisimulation relation. the c-1-d property can be used directly for specification machines on which it naturally holds---a condition that has not been exploited thus far in fsm verification. we also show how this property can be enforced on an arbitrary fsm by exposing some of its latch outputs as pseudo-primary outputs during synthesis and verification. in this sense, our synthesis/verification methodology provides another point in the trade-off curve between constraints-on-synthesis versus complexity-of-verification. practical experiences with this methodology have resulted in success with several examples for which it is not possible to complete verification using existing implicit state space traversal techniques.
estimation of signal arrival times in the presence of delay noise. delay due to capacitive coupling of interconnects has become an important reliability issue in the design of nanometer circuits. in this paper we present a probabilistic approach towards analyzing the impact of capacitive coupling noise on signal delay. the variation in the delay is due to the variation in the relative arrival times of the aggressors and the victim. we derive expressions for the moments of the victim voltage in the presence of noise. from these we compute estimates of the earliest and latest possible arrival times of the victim. we compare the analytical results with monte carlo simulations using spice. even though the analytical calculations are 200 times faster than the monte carlo simulations, the differences in the estimates of the mean and standard deviation of the arrival time is no more than 2.8%. in addition, the width of the timing intervals using the proposed approach is reduced by as much as 48% with a confidence level of 0.984. that is 98.4% of the monte carlo simulations result in an arrival time that falls within the derived interval which is 48% shorter.
fast functional simulation using branching programs. abstract: this paper addresses the problem of speeding up functional (delay-independent) logic simulation for synchronous digital systems. the problem needs very little new motivation-cycle-based functional simulation is the largest consumer of computing cycles in system design. most existing simulators for this task can he classified as being either event driven or levelized compiled-code, with the levelized compiled code simulators generally being considered faster for this task. an alternative technique, based on evaluation using branching programs, was suggested about a decade ago in the context of switch level functional simulation. however, this had very limited application since it could not handle the large circuits encountered in practice. this paper resurrects the basic idea present this technique and provides significant modifications that enable its application to contemporary industrial strength circuits. we present experimental results that demonstrate up to a 10x speedup over levelized compiled code simulation for a large suite of benchmark circuits as well as for industrial examples with over 40.000 gates.
au: timing analysis under uncertainty. due to excessive reduction in the gate length, dopant concentrationsand the oxide thickness, even the slightest of variations inthese quantities can result in significant variations in the performanceof a device. this has resulted in a need for efficient andaccurate techniques for performing statistical analysis of circuits.in this paper we propose a methodology based on bayesian networksfor computing the exact probability distribution of the delayof a circuit. in case of large circuits where it is not possible tocompute the exact distribution, we propose methods to reduce theproblem size and get a tight lower bound on the exact distribution.
analytical approach to custom datapath design. this paper addresses the problem of layout design automation of datapath cells. we present a novel approach to transistor placement problem for custom datapath designs and demonstrate that it can be applied to practical designs. our approach is based on an analytical model which employs a mixed integer linear programming (milp) technique. the novelty and originality of the method is the efficient management of the complexity of the underlying mathematical model. our prototype tool automatically handles transistor merging, folding, and intra-cell component sharing.
provably correct high-level timing analysis without path sensitization. this paper addresses the problem of true delay estimation during high level design. the existing delay estimation techniques either estimate the topological delay of the circuit which may be pessimistic, or use gate-level timing analysis for calculating the true delay, which may be prohibitively expensive.we show that the paths in the implementation of a behavioral specification can be partitioned into two sets, sp and up. while the paths in sp can affect the delay of the circuit, the paths in up cannot. consequently, the true delay of the resulting circuit can be computed by just measuring the topological delay of the paths in sp, eliminating the need for the computationally intensive process of path sensitization. experimental results show that high-level true delay estimation can be done very fast, even when gate-level true delay estimation becomes computationally infeasible. the high-level delay estimates are verified by comparing with delay estimates obtained by gate-level timing analysis on the actual implementation.
an optimal chip compaction method based on shortest path algorithm with automatic jog insertion. a one-dimensional compaction method for layout patterns including rectilinear macrocells on any number of layers is presented. the algorithm is based on the shortest path search on a constraint graph. it generates an optimal layout pattern in the smallest area by introducing effective jogs in o (n log n) time, where n is the number of line segments of the input pattern and inserted jogs. the jogs are inserted by means of an enhanced plane-sweep method developed in the field of computational geometry. performance data of an experimental program show its efficiency
effects of global interconnect optimizations on performance estimation of deep submicron design. in this paper, we quantify the impact of global interconnect optimization techniques that address such design objectives as delay, peak noise, delay uncertainty due to noise, power, and cost. in doing so, we develop a new system-performance simulation model as a set of studies within the marco gsrc technology extrapolation (gtx) system. we model a typical point-to-point global interconnect and focus on accurate assessment of both circuit and design technology with respect to such issues as inductance, signal line shielding, dynamic delay, buffer placement uncertainty and repeater staggering. we demonstrate, for example, that optimal wire sizing models need to consider inductive effects -- and that use of more accurate {-1,3} worst-case capacitive coupling noise switch factors substantially increases peak noise estimates compared to traditional {0,2} bounds. we also find that optimal repeater sizes are significantly smaller than conventional models would suggest, especially when considering energy-delay issues.
circuit power estimation using pattern recognition techniques. this paper proposes a circuit power estimation method using bayesian inference and neural networks. based on statistical distribution of circuit leakage power and switching energy, the entire state and transition space of a circuit are classified using neural networks into a limited few classes that represent different power consumption average values. this technique enables efficient table-lookup of circuit power of the entire state and transition space. theoretical basis of bayesian inference, feature extraction for neural networks of circuit leakage power and switching energy are discussed. experiments on a wide range of circuit topologies demonstrated the robustness of the proposed method for estimating circuit leakage power of all possible states and switching energy of all possible transitions.
sisma: a statistical simulator for mismatch analysis of mos ics. this paper presents a simulator for the statistical analysis of mos integrated circuits a ected by mismatch e ect. the tool is based on a rigorous formulation of circuit equations including random current sources to take into account technological tolerances. the simulator requires a simulation time of several orders of magnitude lower than that required by montecarlo analysis, while ensuring a good accuracy.
parameterized rtl power models for combinational soft macros. we propose a new rtl power macromodel that is suitable for re-configurable, synthesizable soft-macros. the model is parameterized with respect to the input data size (i.e., bit-width), and can be automatically scaled with respect to different technology libraries and/or synthesis options. scalability is obtained through a single additional characterizations run, and does not require the disclosure of any intellectual property. the model is derived from empirical analysis of the sensitivity of power on input statistics, input data size and technology. the experiments prove that, with limited approximation, it is possible to de-couple the effects on power of these three factors. the proposed solution is innovative, since no previous macromodel supports automatic technology scaling, and yields estimation errors within 15%.
a multi-harmonic probe technique for computing oscillator steady states. we present a novel method for finding periodic steady states of general classes of oscillators robustly. the new method, which we term the multi-harmonic probe (mhp) technique, generalizes the well-known technique of augmenting harmonic balance (hb) for oscillators using an external probe. by using non-sinusoidal periodic probes, mhp enhances the applicability of the standard probe method (which uses purely sinusoidal probes) to broader classes of oscillators. we thus obtain a general and robust method for the periodic steady state of any kind of oscillator. results on lc and ring oscillator circuits are presented that testify to the efficacy of our approach.
parameterized model order reduction of nonlinear dynamical systems. in this paper we present a parameterized reduction technique for non-linear systems. our approach combines an existing non-parameterized trajectory piecewise linear method for non-linear systems, with an existing moment matching parameterized technique for linear systems. results and comparisons are presented for two examples: an analog non-linear circuit, and a mem switch.
fault dictionary compaction by output sequence removal. fault dictionary compaction has been accomplished in the past by removing responses on individual output pins for specific test vectors. in contrast to the previous work, we present techniques for eliminating entire sequences of outputs and for efficiently storing the remaining output sequences. experimental results on the iscas 85 and iscas 89 benchmark circuits show that the sizes of dictionaries proposed are substantially smaller than the full fault dictionary, while the dictionaries retain most or all of the diagnostic capability of the full fault dictionary.
integrated fault diagnosis targeting reduced simulation. integrated fault diagnosis techniques attempt to overcome the limitations associated with static (pre-computed information usage) and dynamic (run-time analysis) techniques by using a limited amount of pre-computed information and coupling this with simulation at diagnosis time, for rapid fault diagnosis. a significant problem with previous integrated techniques is that the pre-computed information is not targeted specifically toward reducing the run-time costs. we present a new approach to integrated fault diagnosis, by specifically creating the precomputed information to provide later savings in the simulation costs at diagnosis time. experimental results on the iscas 85 and iscas 89 circuits illustrate the savings achieved by this technique.
a statistical study of the effectiveness of bist jitter measurement techniques. this paper describes a statistical study of the effectiveness of state-of-the-art built-in-self-test (bist) jitter measurement techniques. many bist solutions under-sample the signal under test, estimating the jitter in a system based upon a subset of the total number of clock edges. in this paper, we explore how under-sampling affects the accuracy of jitter measurements, and demonstrate a technique for estimating the actual jitter using a gaussian distribution estimation. our theoretical results were verified through a simulation study and comparison to experimental data collected from a 400 mhz phase-locked loop supplied by an industry sponsor.
extension of the asymptotic waveform evaluation technique with the method of characteristics. a problem inherent in methods for simulating distributed elements with the asymptotic waveform evaluation (awe) technique is that they use complex exponentials to approximate pure delays in the time responses of transmission lines. the aproximation can lead to spurious ringing in the simulation results. this problem can be overcome within the context of a spice-based simulator. the generalized method of characteristics is used to derive an equivalent circuit model for a system of coupled lines. this allows the pure delay to be factored out; awe can then be used to approximate the characteristic admittance, as well as the propagation functions of the lines. the awe approximation can be simulated efficiently within a modified version of spice. examples are presented to demonstrate that this technique is both accurate and faster than other methods
exhaustive simulation need not require an exponential number of tests. while simulation is today the most common form of verification, one disadvantage is the excessive number of tests needed for complete coverage. however, the number of tests may be substantially reduced if test case generation is combined with a structural analysis. the resulting set of test cases for exhaustive simulation may be smaller than exponential, which might make exhaustive simulation feasible. even if the set of test cases is still too large, choosing tests from this reduced set results in better coverage than otherwise
be careful with don't cares. abstract: it is commonly expected that any correct implementation can replace its specification inside a larger design without violating the correctness of the whole design. this property (called replaceability) is automatically satisfied in the absence of don't cares because "correctness" by definition implies that specification and implementation compute the identical function. however don't cares allow an implementation to compute a different function, and thus make it difficult to ensure replaceability. whether this problem occurs depends on the exact meaning of "don't care" and the associated definition of "correctness". we will consider three meanings of "don't care" and for each give conditions under which correct implementations may replace their specifications.
incremental synthesis. a small change in the input to logic synthesis may cause a large change in the output implementation. this is undesirable if a designer has some investment in the old implementation and does not want it perturbed more than necessary. we describe a method that solves this problem by reusing gates from the old implementation, and restricting synthesis to the modified portions only.
inaccuracies in power estimation during logic synthesis. this paper studies the confidence with which power can be estimated at various levels of design abstraction. we report the results of experiments designed to identify and evaluate the sources of inaccuracies in gate-level power estimation. in particular, we are interested in power estimation during logic synthesis. factors that may invalidate or diminish the accuracy of power estimates include optimization, technology mapping, transistor sizing, placement and wiring, and choice of input stimuli.
eta: electrical-level timing analysis. a timing analyzer which performs timing analysis considering electrical-level details such as input signal slope, gate input distinction, charge sharing, and interconnect, while also taking into account such high-level concerns as path sensitization, is described. to achieve the greatest efficiency, eta operates in two phases: (1) logic and delay precharacterization, and (2) longest path analysis. during the precharacterization phase, each gate is analyzed to get its boolean function and its load at the transistor level. during the longest path analysis phase, paths from each primary input are enumerated and examined separately. each potentially longest path is tested for sensitizability at the gate level until a sensitizable longest path is found. the circuit examples given demonstrate the importance of an accurate delay calculation in correctly finding the longest statistically sensitizable path
compatible observability don't cares revisited. codcs stand for compatible observability don't cares. we first examine the definition of compatibility and when a set of codcs is compatible. we then discuss savoj's codc computation for propagating codcs from a node's output to its fanins, and show by example, that the results can depend on the current implementation of the node. then we generalize the computation so that the result is independent of the implementation at the node. the codcs propagated by this computation are proved to be maximal in some sense. local don't cares (ldcs) are codcs of a node, pre-imaged to the primary inputs and then imaged and projected to the local fanins of the node. ldcs combine codcs with sdcs (satisfiability don't cares), but only the codc part is propagated to the fanin network. another form of local don't cares, propagates both the codc and sdc parts to the fanin network. both are shown to be compatible in some sense, but conservative. we give a method for updating both kinds of local don't cares incrementally when other nodes in the network are changed.
resource sharing in hierarchical synthesis. this paper presents a new approach to hierarchical high-level synthesis with respect to internal register-transfer structures of complex components. entire subdesigns can efficiently be used as complex components at a higher hierarchical level of the design. after synthesis, the calculated schedule of each subdesign is added to its register-transfer component model. this enables the sharing of unused subcomponents across different hierarchical levels of the design. especially, subcomponents of autonomous components, with a separate controller, can also be shared. as a result, the presented methodology offers a high degree of optimization to hierarchically specified designs.
methods for true power minimization. this paper presents methods for efficient power minimization at circuit and micro-architectural levels. the potential energy savings are strongly related to the energy profile of a circuit. these savings are obtained by using gate sizing, supply voltage, and threshold voltage optimization, to minimize energy consumption subject to a delay constraint. the true power minimization is achieved when the energy reduction potentials of all tuning variables are balanced. we derive the sensitivity of energy to delay for each of the tuning variables connecting its energy saving potential to the physical properties of the circuit. this helps to develop understanding of optimization performance and identify the most efficient techniques for energy reduction. the optimizations are applied to some examples that span typical circuit topologies including inverter chains, sram decoders, and adders. at a delay of 20% larger than the minimum, energy savings of 40% to 70% are possible, indicating that achieving peak performance is expensive in terms of energy. energy savings of about 50% can be achieved without delay penalty with the balancing of sizes, supplies, and thresholds.
binary decision diagrams and beyond: enabling technologies for formal verification. ordered binary decision diagrams (obdds) have found widespread use in cad applications such as formal verification, logic synthesis, and test generation. obdds represent boolean functions in a form that is both canonical and compact for many practical cases. they can be generated and manipulated by efficient graph algorithms. researchers have found that many tasks can be expressed as series of operations on boolean functions, making them candidates for obdd-based methods. the success of obdds has inspired efforts to improve their efficiency and to expand their range of applicability. techniques have been discovered to make the representation more compact and to represent other classes of functions. this has led to improved performance on existing obdd applications, as well as enabled new classes of problems to be solved. this paper provides an overview of the state of the art in graph-based function representations. we focus on several recent advances of particular importance for formal verification and other cad applications.
verifying properties of hardware and software by predicate abstraction and model checking. this tutorial describes automatic techniques for formally verifying hardware and software by creating boolean abstractions of the underlying unbounded system state variables.
logic synthesis for large pass transistor circuits. pass transistor logic (ptl) can be a promising alternative to static cmos for deep sub-micron design. in this work, we motivate the need for cad algorithms for ptl circuit design and propose decomposed bdds as a suitable logic level representation for synthesis of ptl networks. decomposed bdds can represent large, arbitrary functions as a multi-stage circuit and can exploit the natural, efficient mapping of a bdd to ptl. a comprehensive synthesis flow based on decomposed bdds is outlined for ptl design. we show that the proposed approach allows us to make logic-level optimizations similar to the traditional multi- level network based synthesis flow for static cmos, and also makes possible optimizations with a direct impact on area, delay and power of the final circuit implementation which do not have any equivalent in the traditional approach. we also present a set of heuristical algorithms to synthesize ptl circuits optimized for area, delay and power which are key to the proposed synthesis flow. experimental results on iscas benchmark circuits show that our technique yields ptl circuits with substantial improvements over static cmos designs. in addition, to the best of our knowledge this is the first time ptl circuits have been synthesized for the entire iscas benchmark set.
adaptive methods for netlist partitioning. an algorithm that remains in use at the core of many partitioning systems is the kernighan-lin algorithm and a variant the fidducia-matheysses (fm) algorithm. to understand the fm algorithm we applied principles of data engineering where visualization and statistical analysis are used to analyze the run-time behavior. we identified two improvements to the algorithm which, without clustering or an improved heuristic function, bring the performance of the algorithm near that of more sophisticated algorithms. one improvement is based on the observation, explored empirically, that the full passes in the fm algorithm appear comparable to a stochastic local restart in the search. we motivate this observation with a discussion of recent improvements in monte carlo markov chain methods in statistics. the other improvement is based on the observation that when an fm-like algorithm is run 20 times and the best run chosen, the performance trace of the algorithm on earlier runs is useful data for learning when to abort a later run. these improvements, implemented with a simple adaptive scheme, are orthogonal to techniques used in state-of-the-art implementations, and should therefore be applicable to other vlsi optimization algorithms.
efficient boolean function matching. efficient algorithms for performing the matching step in technology mapping are proposed. the main result is an algorithm for matching under input negations that takes time polynomial in the size of the bdds representing the functions to be matched. this algorithm is the basis for efficient methods for matching under permutations, bridging and constant inputs. a simple mapper based on the algorithms was implemented and tested on a suite of combinational circuits. using the actel type 1 mother cell, the mapper required an average of 8.5% fewer cells than mispga. when integrated into a more sophisticated technology mapper, the matching algorithms could provide even better performance
mcpower: a monte carlo approach to power estimation. an alternative technique for power estimation that combines the accuracy of simulation-based techniques with the speed of the probabilistic technique is investigated. the resulting method is statistical in nature; it consists of applying randomly-generated input patterns to the circuit and monitoring, with a simulator, the resulting power value. this is continued until a value of power is obtained with a desired accuracy, at a specified confidence level. the algorithm and experimental results are presented and the superiority of this approach is discussed
optimization of critical paths in circuits with level-sensitive latches. a simple extension of the critical path method is presented which allows more accurate optimization of circuits with level-sensitive latches. the extended formulation provides a sufficient set of constraints to ensure that, when all slacks are non-negative, the corresponding circuit will be free of late signal timing problems. cycle stealing is directly permitted by the formulation. however, moderate restrictions may be necessary to ensure that the timing constraint graph is acyclic. forcing the constraint graph to be acyclic allows a broad range of existing optimization algorithms to be easily extended to better optimize circuits with level-sensitive latches. we describe the extension of two such algorithms, both of which attempt to solve the problem of selecting parts from a library to minimize area subject to a cycle time constraint.
identification of critical paths in circuits with level-sensitive latches. an approach to timing verification of circuits with level-sensitive latches which focuses on the critical paths that constrain the operating speed of these circuits is described. the timing model used has been referred to as the `smo model' (sakallah, mudge and olukotun, 1990). three types of critical paths (long, short and loops) can arise in the smo formulation; verifying their timing is sufficient to ensure correct operation. an algorithm for identifying these paths is presented, and its relationship to other approaches to solving the smo model equations is discussed. finally, results which demonstrate the algorithm on circuits from the iscas89 benchmark suite are presented
new channel segmentation model and associated routing algorithm for high performance fpgas. in the model considered, a channel is partitioned into several regions and each region consists of tracks of equal length segments, but segment length is varied uniformly across the regions. each region is allocated a certain number of tracks. the segments are arranged in a staggered fashion. in order to make optimum use of the model, a routing algorithm is developed. the key feature of the routing algorithm is the assignment of the nets to the appropriate tracks by delay computation and delay matching techniques. experimental results show that the model and the algorithm improve the longest net delay by as much as 75.16% and the average net delay by 48.28% as compared to the conventional uniformly segmented model
molecular electronics: devices, systems and tools for gigagate, gigabit chips. new electronics technologies are emerging which may carry us beyond the limits of lithographic processing down to molecular-scale feature sizes. devices and interconnects can be made from a variety of molecules and materials including bistable and switchable organic molecules, carbon nanotubes, and, single-crystal semiconductor nanowires. they can be self-assembled into organized structures and attached onto lithographic substrates. this tutorial reviews emerging molecular-scale electronics technology for cad and system designers and highlights where iccad research can help support this technology.
improved reachability analysis of large finite state machines. bdd-based symbolic traversals are the state-of-the-art technique for reachability analysis of finite state machines. they are currently limited to medium-small circuits for two reasons: peak bdd size during image computation and bdd explosion for representing state sets. starting from these limits, this paper presents an optimized traversal technique particularly oriented to the exact exploration of the state space of large machines. this is possible thanks to: 1) temporary simplification of a finite state machine by removing some of its state elements, 2) a "divide-and-conquer" approach based on state set decomposition. an effective use of secondary memory allows us to store relevant portions of bdds and to regularize access to memory, resulting in less page faults. experimental results show that this approach is particularly effective on the larger iscas'89 and iscas'89-addendum'93 circuits.
boolean constrained encoding: a new formulation and a case study. this paper provides a new, generalized approach to the problem of encoding information as vectors of binary digits. we furnish a formal definition for the boolean constrained encoding problem, and show that this definition encompasses many particular encoding problems found in vlsi design, at various description abstraction levels. our approach can capture equivalence and/or compatibility classes in the original symbol set to encode, by allowing symbols codes to be cubes of a boolean space, instead of the usual minterms. besides, we introduce a unified framework to represent encoding constraints which is more general than previous efforts. the framework is based upon a new definition of the pseudo-dichotomy concept, and is adequate to guide the solution of encoding problems through the satisfaction of constraints extracted from the original problem statement. an encoding problem case study is presented, the state assignment of synchronous finite state machines with the simultaneous consideration of state minimization. the practical comparison with well-established approaches to solve this problem in two separate steps, shows that our solution is competitive with other published results. however, the case study is primarily intended to show the feasibility of the boolean constrained encoding problem formulation.
timing verification of sequential domino circuits. two methods are presented for static timing verification of sequential circuits implemented as a mix of static and domino logic. constraints for proper operation of domino gates are derived. an important observation is that input signals to domino gates may start changing near the end of the evaluate phase. the first method models domino gates explicitly, similar to latches. the second method treats domino gates only during pre- and post-processing steps. this method is shown to be more conservative, but easier to compute.
synthesis using sequential functional modules (sfms). this paper presents a new method used in our rtl-synthesis tool to perform technology mapping with sequential functional modules (sfms) such as counters, accumulators, shift-registers, or rotators from any target or macro library. if the library contains sfms, the method automatically recognizes them. if an rtl design contains patterns that can be implemented on sfms, the method maps them to the sfms found in the target library. this mapping reduces the design time by leveraging the library developer' s effort, leads to more regular and often smaller and faster designs, and helps to reduce timing and routing problems at later stages of the design process.
sequential redundancy identification using recursive learning. a sequential redundancy identification procedure is presented. based on uncontrollability analysis and recursive learning techniques, this procedure identifies c-cycle redundancies in large circuits, without simplifying assumptions or state transition information. the proposed procedure can identify redundant faults which require conflicting assignments on multiple lines. in this sense, it is a generalization of fires, a state-of-the-art redundancy identification algorithm. a modification of the proposed procedure is also presented for identifying untestable faults. experimental results on iscas benchmarks demonstrate that these two procedures can efficiently identify a large portion of c-cycle redundant and untestable faults.
non-linear quantification scheduling in image computation. computing the set of states reachable in one step from a given set of states, i.e. image computation, is a crucial step in several symbolic verification algorithms, including model checking and reachability analysis. so far, the best methods for quantification scheduling in image computation, with a conjunctively partitioned transition relation, have been restricted to a linear schedule. this results in a loss of flexibility during image computation. we view image computation as a problem of constructing an optimal parse tree for the image set. the optimality of a parse tree is defined by the largest bdd that is encountered during the computation of the tree. we present dynamic and static versions of a new algorithm, varscore, which exploits the flexibility offered by the parse tree approach to the image computation. we show by extensive experimentation that our techniques outperform the best known techniques so far.
switch-factor based loop rlc modeling for efficient timing analysis. timing uncertainty caused by inductive and capacitivecoupling is one of the major bottlenecks in timing analysis. in thispaper, we propose an effective loop rlc modeling technique toefficiently decouple lines with both inductive and capacitivecoupling. we generalize the rlc decoupling problem based ontransmission line theory and a switch-factor, which is the voltageratio between two nets. this switch-factor is also known as themiller factor and is widely used to model capacitive coupling.the proposed modeling technique can be directly applied to partialrlc netlists extracted using existing parasitic extraction toolswithout advance knowledge of the return path. the new modelaccurately captures the impact of neighboring switching activitywhen it significantly affects the size of current return loop. asdemonstrated in our experiments, the new model accuratelypredicts both upper and lower delay bounds as a function ofneighboring switching patterns. therefore, this approach can beeasily implemented into existing timing analysis flows such asmax-timing and min-timing analysis. finally, we apply the newmodeling approach to a range of activities across the designprocess including timing optimization, static timing analysis, highfrequency clock design, and data-bus wire planning.
a methodology for correct-by-construction latency insensitive design. in deep sub-micron (dsm) designs, performance will depend critically on the latency of long wires. we propose a new synthesis methodology for synchronous systems that makes the design functionally insensitive to the latency of long wires. given a synchronous specification of a design, we generate a functionaly equivalent synchronous implementation that can tolerate arbitrary communication latency between latches. by using latches we can break a long wire in short segments which can be traversed while meeting a single clock cycle constraint. the overall goal is to obtain a design that is robust with respect to delays of long wires, in a shorter time by reducing the multiple iterations between logical and physical design, and with performance that is optimized with respect to the speed of the single components of the design. in this paper we describe the details of the proposed methodology as well as report on the latency insensitive design of pdlx, an out-of-order microprocessor with speculative-execution.
acv: an arithmetic circuit verifier. based on a hierarchical verification methodology, we present an arithmetic circuit verifier acv, in which circuits expressed in a hardware description language, also called acv, are symbolically verified using binary decision diagrams for boolean functions and multiplicative binary moment diagrams (*bmds) for word-level functions. a circuit is described in acv as a hierarchy of modules. each module has a structural definition as an interconnection of logic gates and other modules. modules may also have functional descriptions, declaring the numeric encodings of the inputs and outputs, as well as specifying their functionality in terms of arithmetic expressions. verification then proceeds recursively, proving that each module in the hierarchy having a functional description, including the top-level one, realizes its specification. the language and the verifier contain additional enhancements for overcoming some of the difficulties in applying *bmd-based verification to circuits computing functions such as division and square root. acv has successfully verified a number of circuits, implementing such functions as multiplication, division, and square root, with word sizes up to 256 bits.
ilp models for the synthesis of asynchronous control circuits. a new technique for the logic synthesis of asynchronous circuits is presented. it is based on the structural theory of petri nets and integer linear programming. the techniqueis capable of checking implementability conditions, such as,complete state coding, and deriving a gate netlist to implement the specified behavior. this technique can synthesize specifications with few thousands of transitions in the petrinet, providing a speed-up of several orders of magnitudewith regard to other existing techniques.
phdd: an efficient graph representation for floating point circuit verification. data structures such as *bmds, hdds, and k*bmds provide compact representations for functions which map boolean vectors into integer values, but not floating point values. in this paper, we propose a new data structure, called multiplicative power hybrid decision diagrams (*phdds), to provide a compact representation for functions that map boolean vectors into integer or floating point values. the size of the graph to represent the ieee floating point encoding is linear with the word size. the complexity of floating point multiplication grows linearly with the word size. the complexity of floating point addition grows exponentially with the size of the exponent part, but linearly with the size of the mantissa part. we applied *phdds to verify integer multipliers and floating point multipliers before the rounding stage, based on a hierarchical verification approach. for integer multipliers, our results are at least 6 times faster than *bmds. previous attempts at verifying floating point multipliers required manual intervention. we verified floating point multipliers before the rounding stage automatically.
daomap: a depth-optimal area optimization mapping algorithm for fpga designs. in this work we study the technology mapping problem for fpga architectures to minimize chip area, or the total number of lookup tables (luts) of the mapped design, under the chip performance constraint. this is a well-studied topic and a very difficult task (np-hard). the contributions of this work are as follows: (i) we consider the potential node duplications during the cut enumeration/generation procedure so the mapping costs encoded in the cuts drive the area-optimization objective more effectively; (ii) after the timing constraint is determined, we will relax the non-critical paths by searching the solution space considering both local and global optimality information to minimize mapping area; (iii) an iterative cut selection procedure is carried out that further explores and perturbs the solution space to improve solution quality. we guarantee optimal mapping depth under the unit delay model. experimental results show that our mapping algorithm, named daomap, produces significant quality and runtime improvements. compared to the state-of-the-art depth-optimal, area minimization mapping algorithm cutmap (cong and hwan, 1995), daomap is 16.02% better on area and runs 24.2x faster on average when both algorithms are mapping to fpgas using luts of five inputs. luts of other inputs are also used for comparisons.
the y-architecture for on-chip interconnect: analysis and methodology. the y-architecture for on-chip interconnect is based on pervasiveuse of 0-, 120-, and 240-degree oriented semi-global and globalwiring. its use of three uniform directions exploits on-chip routingresources more efficiently than traditional manhattan wiring architecture.this paper gives in-depth analysis of deployment issues associatedwith the y-architecture. our contributions are as follows:(1) we analyze communication capability (throughput of meshes)for different interconnect architectures using a multi-commodityflow approach and a rentian communication model. throughput ofthe y-architecture is largely improved compared to the manhattanarchitecture, and is close to the throughput of the x-architecture.(2) we propose a symmetrical y clock tree structure with bettertotal wire length compared to both h and x clock tree structures,and better path length compared to the h tree. (3) we discuss powerdistribution under the y-architecture, and give analytical and spicesimulation results showing that the power network in y-architecturecan achieve 8.5% less ir drop than an equally-resourced power networkin manhattan architecture. (4) we propose the use of via tunnelsand banks of via tunnels as a technique for improving routabilityfor manhattan and y-architectures.
a general dispersive multiconductor transmission line model for interconnect simulation in spice. although numerous methods have been proposed for interconnect simulation, no single model exists for all kind of transmission line problems. this paper presents a new, single, general dispersive coupled uniform/nonuniform transmission line model which can be used for interconnect simulation in spice. the mathematical model is based on the use of chebyshev polynomials for the representation of the spatial variation of the transmission-line voltages and currents. a simple collocation procedure is used to obtain a matrix representation of the transmission line equations with matrix coefficients that are first polynomials in s, and in which terminal transmission-line voltages and currents appear explicitly. thus, the model is compatible with both the spice's numerical integration algorithm and the modified nodal analysis formalism.
imf: interconnect-driven multilevel floorplanning for large-scale building-module designs. we present in this paper, a new interconnect-driven multilevel floorplanning, called imf, to handle large-scale building-module designs. unlike the traditional multilevel framework that adopts the "v-cycle" framework: bottom-up coarsening followed by top-down uncoarsening, in contrast, imf works in the "/spl lambda/-cycle" manner: top-down uncoarsening (partitioning) followed by bottom-up coarsening (merging). the top-down partitioning stage iteratively partitions the floorplan region based on mm-cut bipartitioning with exact net-weight modeling to reduce the number of global interconnections and thus the total wirelength. then, the bottom-up merging stage iteratively applies fixed-outline floorplanning using simulated annealing for all regions and merges two neighboring regions recursively. we also propose an accelerative fixed-outline floorplanning (aff) to speed up wirelength minimization under the outline constraint. experimental results show that imf consistently obtains the best floorplanning results with the smallest wirelength for large-scale building-module designs, compared with all publicly available floorplanners. in particular, imf scales very well as the circuit size increases. the /spl lambda/-cycle multilevel framework outperforms the v-cycle one in the optimization of global circuit effects, such as interconnection and crosstalk optimization, since the /spl lambda/-cycle framework considers the global configuration first and then processes down to local ones level by level and thus the global effects can be handled at earlier stages. the /spl lambda/-cycle multilevel framework is general and thus can be readily applied to other problems.
partial simulation-driven atpg for detection and diagnosis of faults in analog circuits. in this paper, we propose a novel fault-oriented test generation methodology for detection and isolation of faults in analog circuits. given the description of the circuit-under-test, the proposed test generator computes the optimal transient test stimuli in order to detect and isolate a given set of faults. it also computes the optimal set of test nodes to probe at, and the time instants to make measurements. the test generation program accommodates the effects introduced by component tolerances and measurement inaccuracy, and can be tailored to fit the signal generation capabilities of a hardware tester. experimental results show that the proposed technique can be applied to generate transient tests for both linear and non-linear analog circuits of moderate complexity in reasonably less cpu time. this will significantly impact the test development costs for an analog circuit and will decrease the time-to-market of a product. finally, the short duration and the easy-to-apply feature of the test stimuli will lead to significant reduction in production test costs.
fast and exact simultaneous gate and wire sizing by lagrangian relaxation. this paper considers simultaneous gate and wire sizing for general vlsi circuits under the elmore delay model. we present a fast and exact algorithm which can minimize total area subject to maximum delay bound. the algorithm can be easily modified to give exact algorithms for optimizing several other objectives (e.g. minimizing maximum delay or minimizing total area subject to arrival time specifications at all inputs and outputs). no previous algorithm for simultaneous gate and wire sizing can guarantee exact solutions for general circuits. our algorithm is an iterative one with a guarantee on convergence to global optimal solutions. it is based on lagrangian relaxation and "one-gate/wire-at-a-time" local optimizations, and is extremely economical and fast. for example, we can optimize a circuit with 13824 gates and wires in about 13 minutes using under 12 mb memory on an ibm rs/6000 workstation.
test scheduling for core-based systems. we present optimal solutions to the test scheduling problem for core-based systems. we show that test scheduling is equivalent to the m-processor open-shop scheduling problem and is therefore np-complete. however, a commonly-encountered instance of this problem (m = 2) can be solved in polynomial time. for the general case (m > 2), we present a mixed-integer linear programming (milp) model for optimal scheduling and apply it to a representative core-based system using an milp solver. we also extend the milp model to allow optimal test set selection from a set of alternatives. finally, we present an efficient heuristic algorithm for handling larger systems for which the milp model may be infeasible.
reducing structural bias in technology mapping. technology mapping based on dag-covering suffers from the problem of structural bias: the structure of the mapped netlist depends strongly on the subject graph. in this paper we present a new mapper aimed at mitigating structural bias. it is based on a simplified cut-based boolean matching algorithm, and using the speed afforded by this simplification we explore two ideas to reduce structural bias. the first, called lossless synthesis, leverages recent advances in structure-based combinational equivalence checking to combine the different networks seen during technology independent synthesis into a single network with choices in a scalable manner. we show how cut based mapping extends naturally to handle such networks with choices. the second idea is to combine several library gates into a single gate (called a supergate) in order to make the matching process less local. we show how supergates help address the structural bias problem, and how they fit naturally into the cut-based boolean matching scheme. an implementation based on these ideas significantly outperforms state-of-the-art mappers in terms of delay, area and run-time on academic and industrial benchmarks.
a cocktail approach on random access scan toward low power and high efficiency test. scan design, providing a good test solution to sequential circuits, suffers large data volume, long test time and high test power problem. recently, the random access scan (ras) scheme offers a solution to alleviate the above problems (baik et al., 2004). in this paper, based on ras, a cocktail scan scheme is proposed and demonstrated to improve the test efficiency significantly. the scheme adopts a two-phase approach, firstly by using a cycle random scan test with a few random seed patterns to test the dut and secondly, by using the ras mechanism to test the circuit. due to employment of a revised process and several strategies, namely, test response abundant, constrained static compaction, and bit propagation before test vector dropping, it is very effective in reducing bit flipping and test data volume, consequently, the test application time and power. experimental results show that the scheme can achieve 86% reduction in test data volume and 10 times of speedup in test application time.
eliminating wire crossings for molecular quantum-dot cellular automata implementation. when exploring computing elements made from technologies other than cmos, it is imperative to investigate the effects of physical implementation constraints. this paper focuses on molecular quantum-dot cellular automata circuits. for these circuits, it is very difficult for chemists to fabricate wire crossings (at least in the near future). a novel technique is introduced to remove wire crossings in a given circuit to facilitate the self assembly of real circuits - thus providing meaningful and functional design targets for both physical and computer scientists. the technique eliminates all wire crossings with minimal logic gate/node duplications. experimental results based on existing qca circuits and other benchmarks are quite encouraging, and suggest that further investigation is needed.
approximate algorithms for time separation of events. we describe a polynomial-time approximate algorithm for computing minimum and maximum time separations between all pairs of events in systems specified by acyclic timing constraint graphs. even for acyclic graphs, the problem is np-complete. we propose finding an approximate solution by first approximating the non-convex feasible space with a suitable convex ``envelope'', and then solving the problem efficiently in the approximate convex space. unlike previous works, our algorithm can handle both min and max-type timing constraints in the same system, and has a computational complexity that is polynomial in the number of events. although the computed separations are conservative in the worst-case, experiments indicate that our results are highly accurate in practice.
validation coverage analysis for complex digital designs. in interactive behavioral synthesis, the designer can control the design process at every stage, including modifying the schedule of the design to improve its performance. in this paper, we present a methodology for performance optimization in interactive behavioral synthesis. also proposed are several quality metrics and hints that can assist the user in utilizing the proposed methodology. when the user is optimizing the performance of the design, one important decision is the selection of a clock period. to facilitate clock selection by the user, we have developed an algorithm to estimate the effect of different clock periods on the execution time of the design. we have tested our methodology on several benchmarks. the experimental results support the proposed methodology by demonstrating an average improvement of 46.2% in design performance.
an efficient, bus-layout based method for early diagnosis of bussed driver shorts in printed circuit boards. this paper presents a new, layout-based approach to board-level shorts diagnosis for bussed drivers, with the goal of early repair of interconnect shorts so as to minimize (a) fault masking during opens testing and (b) driver abuse. this approach leads to an early diagnosis of more than 96% of shorts and simplifies the subsequent rest for opens considerably. besides, this approach improves the production yield and field survivability of boards.
multilevel optimization for large-scale circuit placement. we have designed and implemented a new class of fast and highly scalable placement algorithms that directly handle complex constraints and achieve total wirelengths comparable to the state of the art. our approach exploits recent advances in (i) multilevel methods for hierarchical computation, (ii) interior-point methods for nonconvex nonlinear programming, and (iii) the fast multipole method for the order n evaluation of sums over the n (n - 1)/2 pairwise interactions of n components. significant adaptation of these methods for the placement problem is required, and we have therefore developed a set of customized discrete algorithms for clustering, declustering, slot assignment, and local refinement with which the continuous algorithms are naturally combined. preliminary test runs on benchmark circuits with up to 184,000 cells produce total wirelengths within approximately 5-10% of those of gordian-l [1] in less than one tenth the run time. such an ultra-fast placement engine is badly needed for timing convergence of the synthesis and layout phases of integrated circuit design.
characteristic faults and spectral information for logic bist. we present a new method of built-in-self-test (bist) for sequential circuits and system-on-a-chip (soc) using characteristic faults and circuitspecific spectral information in the form of one or more hadamard coefficients. the hadamard coefficients are extracted from the test sequences for a small set of characteristic faults of the circuit. by extracting a few characteristic faults from the circuit, we show that detection of these characteristic faults is sufficient in detecting a vast majority of the remaining faults in the circuit. the small number of characteristic faults allows us to reduce the coefficients necessary for bist. state relaxation is performed on the compacted test sequences to reduce the spectral noise further. since we are targeting only a very small number of characteristic faults, the execution times for computing the spectra are greatly reduced. our experimental results show that our new method can achieve high bist coverage with both lower computational efforts and storage, with very few characteristic faults.
an enhanced multilevel algorithm for circuit placement. this paper presents several important enhancements to therecently published multilevel placement package mpl.the improvements include (i) unconstrained quadratic relaxation on small, noncontiguous subproblems at every level of the hierarchy; (ii) improved interpolation (declustering)based on techniques from algebraic multigrid (amg), and(iii) iterated v-cycles with additional geometric informationfor aggregation in subsequent v-cycles. the enhanced version of mpl, named mpl2, improves the total wirelength result by about 12% compared to the original version. the attractive scalability properties of the mpl run time have beenlargely retained, and the overall run time remains very competitive. compared to gordian-l-domino on uniform-cell-size ibm/ispd98 benchmarks, a speed-up of well over8x on large circuits (¿ 100,000 cells or nets) is obtainedalong with an average improvement in total wirelength ofabout 2%. compared to dragon [32] on the same benchmarks, a speed-up of about 5x is obtained at the cost ofabout 4% increased wirelength. on the recently publishedpeko synthetic benchmarks, mpl2 generates surprisinglyhigh-quality placements - roughly 60% closer to the optimal than those produced by capo 8.5 and dragon - inrun time about twice as long as capo's and about 1/10th of dragon's.
goldengate: a fast and accurate bridging fault simulator under a hybrid logic/iddq testing environment. in this paper we describe goldengate-a bridging fault simulator for cell-based digital vlsi circuits with the following features: 1. it targets both combinational and sequential circuits. 2. it simulates general (routing, adjacency, and intra-cell) realistic bridging faults efficiently through a table-based scheme. the pre-computed table contains accurate cell output voltage and i/sub ddq/ values obtained through electrical-level simulations. 3. it simulates both feedback and nonfeedback bridging faults (bfs) efficiently through a cycling event-driven technique. 4. it allows mixed voltage and i/sub ddq/ simulation to support a fully hybrid test scheme where mixed logic and i/sub ddq/ sensings are allowed. the experimental results show that goldengate is both accurate and fast.
hierarchical partitioning for field-programmable systems. this paper presents a new recursive bipartitioning algorithm for a hierarchical field-programmable system. it draws new insights into relating the quality of the bipartitioning algorithm to circuit structures by the use of the partitioning tree (hagen et al., 1994). the final algorithm proposed not only forms the basis for the partitioning solution of a 1-million gate field programmable system (lewis et al., 1997) but can also be applied to general vlsi or multiple-fpga partitioning problems.
nocee: energy macro-model extraction methodology for network on chip routers. in this paper we present nocee, a fast and accurate method for extracting energy models for packet-switched network on chip (noc) routers. linear regression is used to model the relationship between events occurring in the noc and energy consumption. the resulting models are cycle accurate and can be applied to different technology libraries. we verify the individual router estimation models with many different synthetically generated traffic patterns and data inputs. characterization of a small library takes about two hours. the mean absolute energy estimation error of the resultant models is 5% (10% max) against a complete gate level simulation. we also apply this method to a number of complete nocs with inputs extracted from synthetic application traces and compare our estimated results to the gate level power simulations (mean absolute error is 5%). our estimation methodology has been integrated with commercial logic synthesis flow and power estimation tools (synopsys design compiler and primepower), allowing application across different designs. the extracted models show the different trends across various parameterizations of network on chip routers and have been integrated into an architecture exploration framework.
simultaneous gate sizing and fanout optimization. this paper describes an algorithm for simultaneous gate sizing and fanout optimization along the timing-critical paths in a circuit. first, a continuous-variable delay model that captures both sizing and buffering effects is presented. next, the optimization problem is formulated as a non-convex mathematical program. to manage the problem size, only a small number of critical paths are considered simultaneously. the mathematical program is solved by a non-linear programming package. finally, a design flow based on iterative selection and optimization of the k most critical paths in the circuit is proposed. experimental results show that the proposed flow reduces the circuit delay by an average of 9.2% compared to conventional flows that separate gate sizing from fanout optimization.
practical considerations in rlck crosstalk analysis for digital integrated circuits. inductance and inductive crosstalk has become an important new concern for on-chip wires in deep-submicron integrated circuits. recent advances in extractors to include inductance make possible the extraction of coupled rlck interconnect networks from large, complex on-chip layouts. in this paper, we describe the techniques we use in a commercial static noise analysis tool to analyze crosstalk noise due to fully-coupled rlck networks extracted from layout. notable are the approaches we use to filter and lump aggressor couplings, as well as the techniques used to handle degeneracies in the modified nodel analysis (mna) formulation. furthermore, the nonmonotonicity of interconnect responses in the presence of inductance require additional "sensitizations" in searching the possible switching events inducing the worst-case noise. comparisons with silicon indicate the need to include the substrate in the extracted models in certain cases.
code restructuring for improving cache performance of mpsocs. one of the critical goals in code optimization for mpsoc architectures is to minimize the number of off-chip memory accesses. this is because such accesses can be extremely costly from both performance and power angles. while conventional data locality optimization techniques can be used for improving data access pattern of each processor independently, such techniques usually do not consider locality for shared data. this paper proposes a strategy that reduces the number of off-chip references due to shared data. it achieves this goal by restructuring a parallelized application code in such a fashion that a given data block is accessed by parallel processors within the same time frame, so that its reuse is maximized while it is in the on-chip memory space. this tends to minimize the number of off-chip references since the accesses to a given data block are clustered within a short period of time during execution. our approach employs a polyhedral tool that helps us isolate computations that manipulate a given data block.
area and power reduction of embedded dsp systems using instruction compression and re-configurable encoding. in this paper, we propose a reconfiguration mechanism that allows multiple instruction compression to reduce both code size, which in turn reduces the cost, and (instruction fetch) power, which enhances the battery lifetime, two key considerations in embedded dsp systems. we enhance texas instruments dsp core tms320c27x to incorporate this mechanism and evaluate the improvements on code size and instruction fetch energy using real life embedded control application programs. we show that even with minimal hardware overhead, we can improve code size by over 10% and instruction fetch energy by over 40%.
runtime integrity checking for inter-object connections. ensuring integrity of heap resident data is critical for many embedded systems. ever-scaling process technology combined with power-saving techniques employed in embedded systems is increasing vulnerability of such systems to hardware-related errors such as soft errors. while such errors are transient and do not harm the architecture, they can corrupt data. in this study, we explore solutions to the inter-object connectivity problem in heap memory of java-based embedded environments. our objective is to ensure that the connections between the objects are consistent. in particular, we want to detect the cases where an inter-object link disappears or points to a wrong object. to address this problem, we propose a rule based approach, where the application programmer expresses the important connectivity rules to be satisfied using a special rule language, and a modified jvm (java virtual machine) checks these rules at runtime.
a power aware system level interconnect design methodology for latency-insensitive systems. latency-insensitive interconnects require first-in-first-out buffers (fifo) for flow-control and storage. interconnect delays are not scaling in proportion to the clock period and hence multiple stages of fifos will be needed for high performance interconnects. fifos in the interconnect are a significant contributor to the total power consumption. in this work, we propose a design methodology to synthesize a low power interconnect channel containing series connected fifos for latency-insensitive systems. our approach is the first to consider and simultaneously optimize the channel clock frequency, voltage and the fifo sizes to minimize the power consumption. for small problem size, we show that our approach finds solutions which are close to optimal. the power aware interconnect channel synthesis is affected by the system parameters like the data production rate and data consumption rate. the choice of optimal channel clock frequency, voltage and fifo sizes can lead to power savings as high as 77.7%, 83.6% and 87% for a 3 stage, 4 stage and a 5 stage channel respectively.
multilevel expansion-based vlsi placement with blockages. the rapid growth of system-on-chip designs makes it a necessity for physical design tools to efficiently handle the coexistence of large intellectual property (ip) blocks and small standard cells in a single design. in this work, we present an efficient expansion-based placer to address standard-cell placement problem in the presence of blockages induced by pre-placed ip blocks. expansion refers to the process during which cells are gradually distributed over a specified region. we implement expansion in a new placer by enhancing a quadratic placement technique based on fixed-point addition originally presented by b. hu and m. marek-sadowska (2003), where fixed points were defined as dimensionless pseudo cells, and were deliberately introduced into the circuit to pull cells from one location to another. the new placer not only produces very competitive placement results over multiple sets of public-domain benchmarks with conventional rectangle-like chip boundary, but also efficiently handles the existence of blockages. especially, we develop three expansion strategies and use them under different blockage settings.
congestion minimization during placement without estimation. this paper presents a new congestion minimization technique for standard cell global placement. the most distinct feature of this approach is that it does not follow the traditional "estimate-then-eliminate" strategy. instead, it avoids the excessive usage of routing resources by the "local" nets so that more routing resources are available for the uncertain "global" nets. the experimental results show that our new technique, sparse, achieves better routability than the traditional total wire length (bounding box) guided placers, which had been shown to deliver the best routability results among the placers optimizing different cost functions [2]. another feature of sparse is the capability of allocating white space implicitly. sparse exploits the well known empirical rent's rule and is able to improve the routability even more in the presence of white space. compared to the most recent academic routability-driven placer dragon[8], sparse is able to produce solutions with equal or better routability.
hyper-lp: a system for power minimization using architectural transformations. an automated high-level synthesis system, hyper-lp, for minimizing power consumption in application-specific datapath-intensive cmos circuits using a variety of architectural and computational transformations is presented. the sources of power consumption are reviewed, and the effects of architectural transformations on the various power components are presented. the synthesis environment consists of high-level estimation of power consumption, a library of transformation primitives (local and global), and heuristic/probabilistic optimization search mechanisms for fast and efficient scanning of the design space. examples with varying degree of computational complexity and structures are optimized and synthesized. the results indicate that an order of magnitude reduction in power can be achieved over current-day design methodologies while maintaining the system throughput; in some cases, this can be accomplished while preserving or reducing the implementation area
high-level scheduling model and control synthesis for a broad range of design applications. this paper presents a versatile scheduling model and an efficient control synthesis methodology which enables architectural (high-level) design/synthesis systems to seamlessly support a broad range of architectural design applications from datapath-dominated digital signal processing (dsp) to micro-processors/controllers and control-dominated peripherals, utilizing multi-phase clocking schemes, multiple threading, data-dependent delays, pipelining, and combinations of the above. the work presented in this paper is an enabling technology for high-level synthesis to go beyond traditional datapath-dominated dsp applications and to start becoming a viable and cost-effective design methodology for commodity ics such as micro-processors/controllers and control-dominated peripherals.
cdma/fdma-interconnects for future ulsi communications. future inter- and intra-ulsi interconnect systems demand extremely high data rates as well as bidirectional multi-i/o concurrent service, reconfigurable computing/processing architecture, and total compatibility with mainstream silicon soc (system-on-chip) and sip (system-in-package) technologies. in this talk, we review recent advances in cdma and fdma interconnect schemes that promise to meet all of the above system requirements. the physical transmission line is no longer limited to a direct-coupled metal wire. rather, it can be accomplished via either wired or wireless mediums through capacitor couplers that reduce the baseband noise and dc power consumption. these new advances in interconnect schemes would fundamentally alter the paradigm of ulsi data communications and enable the design of next generation computing/processing systems.
towards true crosstalk noise analysis. accurate noise analysis is currently of significant concern to high-performance designs, and the number of signals susceptible to noise effects will certainly increase in smaller process geometries. our approach uses a combination of temporal and functional information to eliminate false transition combinations and thereby overcome insufficiencies in static noise analysis. a similar idea arises in timing analysis where functional and timing information is used to eliminate false paths. the goal of our work is to develop an algorithm, software tool, and noise analysis flow that provide an accurate and conservative approach to noise analysis. in particular, this paper proposes an approach to identifying a pair of vectors that exercises the maximum crosstalk noise.
simulation-based bug trace minimization with bmc-based refinement. finding the cause of a bug can be one of the most time-consuming activities in design verification. this is particularly true in the case of bugs discovered in the context of a random simulation- based methodology, where bug traces, or counter-examples, may contain several hundred thousand cycles. in this work we propose butramin, a bug trace minimizer. butramin considers a bug trace produced by a random simulator or a semi-formal verification software and produces an equivalent trace of shorter length. butramin applies a range of minimization techniques, deploying both simulation-based and formal methods, with the objective of producing highly reduced traces that still expose the original bug. we evaluated butramin on a range of designs, including the publicly available picojava microprocessor. our experiments show that in most cases butramin is able to reduce traces to a small fraction of their initial size, in terms of cycle length and signals involved.
miller factor for gate-level coupling delay calculation. in coupling delay computation, a miller factor of more than 2x may be necessary to account for active coupling capacitance when modeling the delay of deep submicron circuitry in the presence of active coupling capacitance. we propose an efficient method to estimate this factor such that the delay response of a decoupling circuit model can emulate the original coupling circuit. under the assumptions of zero initial voltage, equal charge transfer, and 0.5vdd as the switching threshold voltage, an upper bound of 3x for maximum delay and a lower bound of -1x for minimum delay can be proven. efficient newton-raphson iteration is also proposed as a technique for computing the miller factor or effective capacitance. this result is highly applicable to crosstalk coupling delay calculation in deep submicron gate-level static timing analysis. detailed analysis and approximation are presented. spice simulations are demonstrated to show high correlation with these approximations.
induction-based gate-level verification of multipliers. we propose a method based on unrolling the inductive definition of binary number multiplication to verify gate-level implementations of multipliers. the induction steps successively reduce the size of the multiplier under verification. through induction, the verification of an n-bit multiplier is decomposed into n equivalence checking problems. the resulting equivalence checking problems could be significantly sped up by simple structural analysis. this method could be generalized to the verification of more general arithmetic circuits and the equivalence checking of complex data-path.
switching window computation for static timing analysis in presence of crosstalk noise. crosstalk effect is crucial for timing analysis in very deep submicron design. in this paper, we present and compare multiple scheduling algorithms to compute switching windows for static timing analysis in presence of crosstalk noise. we also introduce an efficient technique to evaluate the worst case alignment of multiple aggressors.
synthesis for multiple input wires replacement of a gate for wiring consideration. the alternative wire technique attempts to replace a target wire by another wire without charging the logic functionality. in this paper, we propose two new transformations of replacing wires. one transformation simultaneously replaces multiple input wires of a gate by a new set of input wires and the other performs gate decompostion during the alternative wire process. to accomplish such complex transformations, we discuss some theoretical foundations for replacing multiple wires. understanding how wires/gates can be replaced by other wires/gates allows us to speedup the process tremendously.
refining switching window by time slots for crosstalk noise calculation. for crosstalk noise calculation, computing switching windows of a net helps us identify noise sources accurately. traditional approaches use a single continuous switching window for a net. under this model, signal switching is assumed to happen any time within the window. although conservative and sound, this model can result in too much pessimism since in reality the exact timing of signal switching is determined by a path delay up to the net, i.e. the underlying circuit structure does not always allow signal switching at arbitrary time within the continuous switching window. to address this inherent inaccuracy of the continuous switching window, we propose a refinement of the traditional approaches, where signal switching is characterized by a set of discontinuous switching windows instead of a single continuous window. each continuous switching window is divided into multiple windows, called time slots, and the signal switching activity of each slot is analyzed separately to calculate the maximum noise with more accuracy. by controlling the size of a time slot we can trade off accuracy and runtime, which makes this approach highly scalable. we have confirmed by experiments on industrial circuits that up to 90% of the noise violations detected by the traditional approach can be unreal.
array composition and decomposition for optimizing embedded applications. optimizing array accesses is extremely critical in embedded computingas many embedded applications make use of arrays (in formof images, video frames, etc). previous research considered bothloop and data transformations for improving array accesses. however,data transformations considered were mostly limited to lineardata transformations and array interleaving. in this paper, we introducetwo data transformations: array decomposition (breaking upa large array into multiple smaller arrays) and array composition(combining multiple small arrays into a single large array). thispaper discusses that it is feasible to implement these optimizationswithin an optimizing compiler.
using constraint geometry to determine maximum rate pipeline clocking. geometric knowledge of the shape of the feasible region formed by pulse width, setup, and hold constraints is used directly by an efficient (cubic complexity) algorithm, gpipe, to determine the maximum rate for single-phase clocking of a given pipeline. the pipeline model uses level-sensitive latches as synchronizers and can allow wave pipelining. gpipe is also used to explore the effect of removing nonsynchronizing and/or synchronizing latches on the maximum clock speed of the pipeline. a simple test shows which latches, if any, to remove in order to guarantee no decrease, and permit a possible increase, in the clock rate
the associative-skew clock routing problem. we introduce the associative skew clock routing problem, which seeks a clock routing tree such that zero skew is preserved only within identified groups of sinks. the associative skew problem is easier to address within current eda frameworks than useful-skew (skew-scheduling) approaches, and defines an interesting tradeoff between the traditional zero-skew clock routing problem (one sink group) and the steiner minimum tree problem (n sink groups). we present a set of heuristic building blocks, including an efficient and optimal method of merging two zero-skew trees such that zero skew is preserved within the sink sets of each tree. finally, we list a number of open issues for research and practical application.
fast boolean optimization by rewiring. this paper presents a very efficient boolean logic optimization method. the boolean optimization is achieved by adding and removing redundant wires in a circuit. our algorithm applies the reasoning of automatic test pattern generation (atpg) which can detect redundancy efficiently. during the atpg process, mandatory assignments are assignments which must be satisfied. our algorithm analyzes different characteristics of mandatory assignments during the atpg process. new theoretical results based on the analysis are presented which lead to significant performance improvements. the fast run time and the excellent scaling to large problems make our boolean optimization method practical for industrial applications. experiments show that the optimization results are comparable to those of kunz and pradhan (1994) while the run time is two orders of magnitude faster (average 126x speed up). furthermore, we report optimization results for several large examples, which were previously thought to be too large to be handled by boolean optimization methods.
a coloring approach to the structural diagnosis of interconnects. this paper presents a new approach for diagnosing stuck-at and short faults in interconnects whose layouts are known. this structural approach exploits different graph coloring and coding techniques to generate a test set with no aliasing and confounding. the conditions for aliasing and confounding are analyzed with respect to the size and number of the shorts in the fault set. the characteristics of unbalanced/balanced codes for encoding the colors in the vector generation process for interconnect diagnosis are discussed and proved using a novel algebra. an algorithm for diagnosis is then presented.
supreme: substrate and power-delivery reluctance-enhanced macromodel evaluation. the recent demand for system-on-chip rf mixed-signal designand aggressive supply-voltage reduction require chip-level accurateanalysis of both the substrate and power delivery systems.together with the rising frequency, low-k dielectric, copper interconnects,and high conductivity substrate, the inductance effectsraised serious concern recently.however, the increasing designcomplexity creates tremendous challenges for chip-level power-deliverysubstrate co-analysis.in this paper, we propose a noveland efficient reluctance-based passive model order reduction techniqueto serve these tasks.our work, supreme(substrate andpower-delivery reluctance-enhanced macromodel evaluation) notonly greatly reduces the computational complexity of previousreluctance-based model order algorithms but is also capable ofhandling large number of noise sources efficiently.to facilitatethe analysis of inductive substrate return paths and evaluate thehigh-frequency substrate coupling effects, we derive a novel rlkcsubstrate model from maxwell's equations for the first time.experimentalresults demonstrate the superior runtime and accuracyof supreme compared to the traditional mna-based simulation.
single-pass redundancy addition and removal. redundancy-addition-and-removal is a rewiring technique which for a given target wire wt finds a redundant alternative wire wa. addition of wa makes wt redundant and hence removable without changing the overall circuit functionality. incremental logic restructuring based on this technique has been used in many applications. however, the search for valid alternative wires requires trial-and-error redundancy testing of a potentially large set of candidate wires. in this paper, we study the fundamental theory behind this technique and propose a new reasoning scheme which directly identifies alternative wires without performing trial-and-error tests. experimental results show up to 15 times speedup in comparison to the best techniques in literature.
inductwise: inductance-wise interconnect simulator and extractor. we develop a robust, efficient, and accurate tool, which integrates inductance extraction and simulation, called inductwise. this paper advances the state-of-the-art inductance extraction and simulation techniques and contains two major parts. in the first part, inductwise extractor, we discover the recently proposed inductance matrix sparsification algorithm, the k-method[1], albeit its great benefits of efficiency, has a major flaw on the stability. we provide both a counter example and a remedy for it. a window section algorithm is also presented to preserve the accuracy of the sparsification method. the second part, inductwise simulator, demonstrates great efficiency of integrating the nodal analysis formulation with the improved k-method. experimental results show that inductwise has over 250x speedup compared to spice3. the proposed sparsification algorithm accelerates the simulator another 175x and speeds up the extractor 23.4x within 0.1% of error. inductwise can extract and simulate an 118k-conductor rkc circuit within 18 minutes. it has been well tested and released on the web for public usage. (http://vlsi.ece.wisc.edu/inductwise.htm)
atpg-based logic synthesis: an overview. the ultimate goal of logic synthesis is to explore implementation flexibility toward meeting design targets, such as area, power, and delay. traditionally, such flexibility is expressed using "don't cares" and we seek the best implementation that does not violate them. however, the calculation and storing of don't care information is cpu and memory-intensive. in this paper, we give an overview of logic synthesis approaches based on techniques developed for automatic test pattern generation (atpg). instead of calculating and storing don't cares explicitly, atpg-based logic synthesis techniques calculate the flexibility implicitly. low cpu and memory usage make those techniques applicable for practical industrial circuits. also, the basic atpg-based logic level operations create predictable, small layout perturbations, making an ideal foundation for efficient physical synthesis. theoretical results show that an efficient, yet simple add-a-wire-and-remove-a-wire operation covers all possible complex logic transformations.
generalized fdtd-adi: an unconditionally stable full-wave maxwell's equations solver for vlsi interconnect modeling. the finite-difference time-domain (fdtd) method of solving the full-wave maxwell's equations has been recently extended to provide accurate and numerically stable operation for time steps exceeding the courant limit. the elimination of an upper bound on the size of the time step was achieved using an alternating-implicit direction (adi) time-stepping scheme. this greatly increases the computational efficiency of the fdtd method for classes of problems where the cell size of the three-dimensional space lattice is constrained to be much smaller than the shortest wavelength in the source spectrum. one such class of problems is the analysis of high-speed vlsi interconnects where full-wave methods are often needed for the accurate analysis of parasitic electromagnetic wave phenomena. in this paper, we present an enhanced fdtd-adi formulation which permits the modeling of realistic lossy materials such as semiconductor substrates and metal conductors as well as artificial lossy materials needed for perfectly matched layer (pml) absorbing boundary conditions. simulations using our generalized fdtd-adi formulation are presented to demonstrate the accuracy and extent to which the computational burden is reduced by the adi scheme.
perturb and simplify: multi-level boolean network optimizer. in this paper, we discuss the problem of optimizing a multi-level logic combinational boolean network. our techniques apply a sequence of local perturbations and modifications of the network which are guided by the automatic test pattern generation atpg based reasoning. in particular, we propose several new ways in which one or more redundant gates or wires can be added to a network. we show how to identify gates which are good candidates for local functionality change. furthermore, we discuss the problem of adding and removing two wires, none of which alone is redundant, but when jointly added/removed they do not affect functionality of the network. we also address the problem of efficient redundancy computation which allows to eliminate many unnecessary redundancy tests. we have performed experiments on mcnc benchmarks and compared the results to those of misii and rambo. experimental results are very encouraging.
overall consideration of scan design and test generation. a complete system which takes the test generation algorithm, the scan cell selection strategy and the structure of the scan chain into account is proposed. it is totally different from the traditional approaches which try to enhance the ability of the individual subject. the goal of this research is to reduce the extra costs caused by the scan design, especially the test application time. experimental results show that the overall consideration of scan design and test generation can speed up test generation and greatly reduce the amount of test application time
post-placement rewiring and rebuffering by exhaustive search for functional symmetries. separate optimizations of logic and layout have been thoroughly studied in the past and are well documented for common benchmarks. however, to be competitive, modern circuit optimizations must use physical and logic information simultaneously. in this work, we propose new algorithms for rewiring and rebuffering - a post-placement optimization that reconnects pins of a given netlist without changing the logic function and gate locations. these techniques are compatible with separate layout and logic optimizations, and appear independent of them. in particular, when the new optimization is applied before or after detailed placement, it approximately doubles the improvement in wirelength. our contributions are based on exhaustive search for functional symmetries in sub-circuits consisting of several gates. our graph-based symmetry finding is more comprehensive than previously known algorithms - it detects permutational and phase-shift symmetries on multiple input and output wires, as well as hybrid symmetries, creating more opportunities for rewiring and rebuffering.
integrating loop and data optimizations for locality within a constraint network based framework. in the context of data-intensive embedded applications, there have been two complementary approaches to data locality problem: restructuring code and restructuring data layout. conceivably, an integrated approach that combines these two can generate much better results than each individual approach. however, there is an inherent difficulty in optimizing both data layout and loop access pattern simultaneously under a unified setting. this difficulty occurs due to the fact that a given data structure can be accessed by different loop nests of the application, and each such loop nest can demand a different memory layout transformation for the said data structure. this results in a coupling problem, where the behaviors of two (or more) loop nests are coupled to each other as a result of data sharing between them. in this paper, we present a constraint network (cn) based formulation of the integrated loop-data optimization problem. we present two alternate solutions to the data locality problem with our cn based formulation and discuss the pros and cons of each scheme. the first solution is a pure backtracking based one, whereas the second one improves upon the first one by employing three additional optimizations, including backjumping.
an iterative gate sizing approach with accurate delay evaluation. this paper introduces a new gate sizing approach with accurate delay evaluation. the approach solves gate sizing problems by iterating local sizing results from linear programming within small variable ranges of gate sizes. in each iterative step, variable ranges of gate sizes are updated according to the result from a previous step. solutions with accurate delay evaluation which consider input signal slopes and separately evaluate rising and falling delays are obtained after several iterative steps. a speedup technique is used to pick out gates actually involved in each local sizing step so as to reduce cpu time. experiments on sample circuits show that our approach can provide solutions with smaller circuit area than conventional approaches for the same circuit delay or provide solutions under tight delay constraints where conventional approaches can not reach. moreover, our approach is faster than the conventional approaches for most circuits, especially under loose delay constraints.
statistical timing analysis considering spatial correlations using a single pert-like traversal. we present an efficient statistical timing analysis algorithm thatpredicts the probability distribution of the circuit delay while incorporatingthe effects of spatial correlations of intra-die parametervariations, using a method based on principal component analysis.the method uses a pert-like circuit graph traversal, and hasa run-time that is linear in the number of gates and interconnects,as well as the number of grid partitions used to model spatial correlations.on average, the mean and standard deviation valuescomputed by our method have errors of 0.2% and 0.9%, respectively,in comparison with a monte carlo simulation.
a new global routing algorithm for fpgas. as in traditional asic technologies, fpga routing usually consists of two steps: global routing and detailed routing. unlike existing fpga detailed routers, which can take full advantage of the special structures of the programmable routing resources, fpga global routing algorithms still greatly resemble their counterparts in the traditional asic technologies. in particular, the routing congestion information of a switch block essentially is still measured by the numbers of available rows and columns in the switch block. since the internal architecture of a switch block decides what can route through the block, the traditional measure of routing capacity is no longer accurate. in this paper, we present an accurate measure of switch block routing capacity. our new measure considers the exact positions of the switches inside a switch block. experiments with a global router based on these ideas show an average improvement of 38% in the channel width required to route some benchmark circuits using a popular switch block, compared with an algorithm based on the traditional methods for congestion control.
wire reconnections based on implication flow graph. global flow optimization (gfo) can perform the fanout/fanin wire re-connections by modeling the problem of the wire reconnections by a flow graph and then solving the problem using the maxflow-mincut algorithm on the flow graph. however, the flow graph cannot fully characterize the wire re-connections which causes gfo to lose optimality on several obvious cases. in addition, we find that the fanin re-connection can have more optimization power than the fanout re-connection but requires more sophisticated modeling. in this paper, we re-formulate the problem of the fanout/fanin re-connections by a new graph called the implication flow graph. we show that the problem of wire re-connections on the implication flow graph is np complete and also propose an efficient heuristic on the new graph. our experimental results are very exciting.
a wire-length minimization algorithm for single-layer layouts. the authors consider a steiner tree s interconnecting a set n of terminals. the minimizing length of s can be shown to be equivalent to the traditional (np-hard) steiner tree problem. an exact polynomial-time algorithm for minimizing the length of s when operations on s are limited is presented. these operations are called topology preserving transformations (tpts). based on the notion of tpt, an exact algorithm for minimizing the total length of a single-layer layout involving a set of multi-terminal nets and a collection of obstacles is proposed. the algorithm has been used to find a minimum length single-layer layout. the algorithm was also applied to find a steiner tree interconnecting a net n of terminals. the idea is to find a minimum spanning tree t of n. then, generate k steiner trees by randomly flipping edges of t to both its upper- and lower-l-shaped configurations. then, a topology preserving transformation is applied to each steiner tree. the best of them is selected as the final steiner tree. on the average, 9.4% improvement over the mst length has been reported
behavioral synthesis for testability. a synthesis for testability approach is presented. in this approach test points or flip-flops to be used in test point insertion or partial scan to enhance circuit testability are selected. the selection is based on circuit behavioral information rather than low level structural description. this allows test point insertion or partial scan usage on circuits described as interconnections of high level modules. test statement insertion is also proposed as an alternative to test point insertion and to partial scan. the major advantage of using test statement insertion is a lower pin count and lower test application time overhead than test point insertion and partial scan. the tool has been implemented in a computer program
provably good algorithm for low power consumption with dual supply voltages. dual-voltage approach emerges as an effective and practical technique for power reduction. in this paper we explore the power optimization with dual supply voltages under the given timing constraints. by analyzing the relations among the timing slack, delay and power consumption in a given circuit, we relate the voltage-scaling power optimization to maximal-weighted-independent-set (mwis) problem which is polynomial-time solvable on transitive graph. then we develop a provably good lower-bound algorithm based on mwis to generate the lower bound of power consumption. also, we propose a fast approach to predict the optimum supply voltages. the maximum power reduction is obtained by using the modified lower-bound algorithm with optimum voltages. experimental results show that the resulting lower bound is tight for most circuits and that the estimated optimum supply voltage is exactly, or very close to, the best choice of actual voltages.
layer assignment for high-performance multi-chip modules. in this paper, we present a layer assignment method for high-performance multi-chip module environments. in contrast with treating global routing and layer assignment separately, our method assigns nets to layers while considering preferable global routing topologies simultaneously. we take transmission line effects into account to avoid noise in high-speed circuit packages. the problem is formulated as a quadratic boolean programming problem and an algorithm is presented to solve the problem after linearization. our method is applied to a set of benchmark circuits to demonstrate the effectiveness.
signal integrity optimization on the pad assignment for high-speed vlsi design. in this paper, an efficient method is proposed to effectively minimize both simultaneous switching noise and crosstalk that are inevitably caused by package inductance and capacitance during the design of high-speed/high-bandwidth circuits. due to its efficiency, our algorithm can be incorporated into existing circuit floorplanning and placement schemes for the co-design of vlsi and packaging. for a set of industrial circuits/packages tested in our experiment, on the average, our method achieves a 16.8% reduction of total electrical noise when compared with the conventional design rule of thumb popularly used by circuit designers.
response shaper: a novel technique to enhance unknown tolerance for output response compaction. the presence of unknown values in the simulation result is a key barrier to effective output response compaction in practice. this paper proposes a simple circuit module, called a response shaper, to reshape the scan-out responses before feeding them to a space compactor. along with the proposed reshaping algorithm, response shapers can help the space compactor to reduce the number of undetectable modeled and unmodeled faults in the presence of unknown values. moreover, the proposed compaction scheme is atpg-independent and its hardware requirement is pattern-independent. in our experiments, we use a simple xor compactor as the space compactor to evaluate the effectiveness of the response shaper. the results show that the number of undetectable faults and unobservable scan-out responses can be significantly reduced in comparison with the results of a convolutional compactor. the number of the extra scan-in bits required for the control signals of the response shapers is only a small fraction of the total test data volume. also, its hardware overhead is acceptable and the runtime of the reshaping algorithm is scalable for large industrial designs.
hisim: hierarchical interconnect-centric circuit simulator. to ensure the power and signal integrity of modern vlsi circuits, it is crucial to analyze huge amount of nonlinear devices together with enormous interconnect and even substrate parasitics to achieve the required accuracy. neither traditional circuit simulation engines such as spice nor switch-level timing analysis algorithms are equipped to handle such a tremendous challenge in both efficiency and accuracy. we establish a solid framework that simultaneously takes advantage of a hierarchical nonlinear circuit simulation algorithm and an advanced large-scale linear circuit simulation method using a new predictor-corrector algorithm. under solid convergence and stability guarantees, our simulator, hisim, a hierarchical interconnect-centric circuit simulator, is capable of handling the post-layout rlkc power and signal integrity analysis task efficiently and accurately. experimental results demonstrate over 180x speed up over the conventional flat simulation method with spice-level accuracy.
a clustering- and probability-based approach for time-multiplexed fpga partitioning. improving logic density by time-sharing, time-multiplexed fpgas (tmfpgas) have become an important research topic for reconfigurable computing. due to the precedence and capacity constraints in tmfpgas, the clustering and partitioning problems for tmfpgas are different from the traditional ones. in this paper, we propose a two-phase hierarchical approach to solve the partitioning problem for tmfpgas. with the precedence and capacity considerations for both phases, the first phase clusters nodes to reduce the problem size, and the second phase applies a probability-based iterative-improvement approach to minimize cut cost. experimental results based on the xilinx tmfpga architecture show that our algorithm significantly outperforms previous works.
semi-analytical techniques for substrate characterization in the design of mixed-signal ics. a number of methods are presented for highly efficient calculation of substrate current transport. a three-dimensional green function based substrate representation, in combination with the use of the fast fourier transform, significantly speeds up the computation of sensitivities with respect to all parameters associated with a given architecture. substrate sensitivity analysis is used in a number of physical optimization tools, such as placement and trend analysis for the estimation of the impact of technology migration and/or layout re-design.
generalized constraint generation in the presence of non-deterministic parasitics. in a constraint-driven layout synthesis environment, parasitic constraints are generated and implemented in each phase of the design process to meet a given set of performance specifications. the success of the synthesis phase depends in great part on the effectiveness and the generality of the constraint generation process. none of the existing approaches to the constraint generation problem however are suitable for a number of parasitic effects in active and passive devices due to non-deterministic process variations. to address this problem a novel methodology is proposed based on the separation of all variables associated with non-deterministic parasitics, thus allowing the translation of the problem into an equivalent one in which conventional constrained optimization techniques can be used. the requirements of the method are a well-defined set of statistical properties for all parasitics and a reasonable degree of linearity of the performance measures relevant to design.
potential slack: an effective metric of combinational circuit performance. this paper proposes the concept of potential slack and show it is an effective metric of combinational circuit performance. we provide several methods for estimating potential slack and prove one (a maximal-independent-set based algorithm) in particular works best. experiments in gate sizing show that potential slack provides 100% correct prediction for circuit area optimization. we also explore the role of potential slack in timing-driven placement.
copyright protection of designs based on multi source ips. this paper addresses the copyright protection problem of integrated circuits designed with blocks which are originated from multiple design sources. the process consists of two phases. first, a compact signature is generated from every block independently and made public. utilizing such signatures, a design can be decomposed into its original building blocks, regardless of multiple hierarchies. then, a map of all the blocks can be built, thus allowing to reconstruct the original copyright dependencies. the proposed methodology can be used by foundries to verify that designs submitted for fabrication contain blocks traceable to a legal source of intellectual property. the verification process is also useful to intellectual property providers and integrators, as it reduces the likelihood of infringement, thus ultimately minimizing the risk of litigation.
a sliding window scheme for accurate clock mesh analysis. mesh architectures are used for distributing critical global signals on a chip such as clock and power/ground. the inherent redundancy created by loops present in the mesh smooths out undesirable variations between signal nodes spatially distributed over the chip. however, one outstanding problem with mesh architectures is the difficulty in analyzing them with sufficient accuracy. in this paper, we present a new sliding window-based scheme to analyze the latency in clock meshes. we show that for small meshes, our scheme comes within 1% of the spice simulation of the complete mesh with respect to clock latency. our scheme is ideally suited for distributed- or grid-computing. we show large design instances where spice could not finish, whereas our scheme could complete the analysis in less than 2 hours.
raft191486: a novel program for rapid-fire test and diagnosis of digital logic for marginal delays and delay faults. the problem of delay fault-testing and detection of chips with marginal performance has become even more critical than before due to advancing clock speeds. in this paper, a methodology for detection of marginal digital circuits and diagnosis of gate delay failures is developed. a new test application methodology is proposed in which test vectors may be applied to digital combinational circuits at intervals smaller than the critical path delay of the circuit and signal waveform analysis is used to interpret the test results. the resulting tests are called rapid fire tests (for raft) and allow classification of circuits from &ldquo;good&rdquo; to &ldquo;bad&rdquo; along a continuous scale.
timing macro-modeling of ip blocks with crosstalk. with the increase of design complexities and the decrease of minimal feature sizes, ip reuse is becoming a common practice while crosstalk is becoming a critical issue that must be considered. this work presents two macro-models for specifying the timing behaviors of combinational hard ip blocks with crosstalk effects. the gray-box model keeps a coupling graph and lists the conditions on relative input arrival time combinations for couplings not to take effect. the black-box model stores the output response windows for a basic set of relative input arrival time combinations, and computes the output arrival time for any given input arrival time combination through the union of some combinations in the basic set. both macro-models are conservative, and can greatly reduce the pessimism existing in the conventional "pin-to-pin" model. this is the first work to deal with timing macro-modeling of combinational hard ip blocks with the consideration of crosstalk effects.
a new incremental placement algorithm and its application to congestion-aware divisor extraction. this work presents two contributions. the first is an incremental placement algorithm for placement-aware logic synthesis along with a proof of optimality. the algorithm can efficiently compute the optimum location for a newly introduced node in a network that minimizes the incremental increase in the total half-perimeter wire-length of the network. the algorithm can be applied in a variety of placement-aware optimization contexts. the second contribution is a specific application of this algorithm to placement-aware common divisor extraction. we evaluate the effectiveness of the proposed extraction procedure by using it in an otherwise non-placement-aware flow with two different final placers. the first flow uses an industrial congestion-driven placer and results in an average reduction of 21% in congestion as measured by the global router. the second flow uses an academic wire-length-driven placer and results in an average reduction of 11% for a tool-specific measure of congestion estimated from the placement. our experiments also reveal a rather surprising phenomenon: in many cases the attempt to minimize the wire-length results in fewer literals after extraction than with a conventional literal-driven approach.
clock schedule verification under process variations. with aggressive scaling down of feature sizes in vlsi fabrication, process variations have become a critical issue in designs, especially for high-performance ics. usually having level-sensitive latches for their speed, high-performance ic designs need to verify the clock schedules. with process variations, the verification needs to compute the probability of correct clocking. because of complex statistical correlations, traditional iterative approaches are difficult to get accurate results. instead, a statistical checking of the structural conditions for correct clocking is proposed, where the central problem is to compute the probability of having a positive cycle in a graph with random edge weights. the proposed method only traverses the graph once to avoid the correlations among iterations, and it considers not only data delay variations but also clock skew variations. experimental results showed that the proposed approach has an error of 0.14% on average in comparisons with the monte carlo simulations.
efficient algorithms for buffer insertion in general circuits based on network flow. with shrinking vlsi feature sizes and increasing overall chip areas, buffering has emerged as an effective solution to the problem of growing interconnect delays in modern designs. the problem of buffer insertion in a single net has been the focus of most previous researches. however, efficient algorithms for buffer insertion in whole circuits are generally needed. in this paper, we relate the timing constrained minimal buffer insertion problem to the min-cost flow dual problem, and propose two algorithms based on min-cost flow and min-cut techniques, respectively, to solve it in combinational circuits. we compare our approaches to a traditional approach based on lagrangian relaxation. experimental results demonstrate that our approaches are efficient and effective. on the average, our approaches achieve 45% and 39% reduction, respectively, on the number of buffers inserted in comparison to the traditional approach.
optimal non-uniform wire-sizing under the elmore delay model. we consider non-uniform wire-sizing for general routing trees under the elmore delay model. three minimization objectives are studied: (1) total weighted sink-delays; (2) total area subject to sink-delay bounds; and (3) maximum sink delay. we first present an algorithm nwsa-wd for minimizing total weighted sink-delays based on iteratively applying the wire-sizing formula. we show that nwsa-wd always converges to an optimal wire-sizing solution. based on nwsa-wd and the lagrangian relaxation technique, we obtained two algorithms nwsa-db and nwsa-md which can optimally solve the other two minimization objectives. experimental results show that our algorithms are efficient both in terms of runtime and storage. for example, nwsa-wd, with linear runtime and storage, can solve a 6201-wire segment routing-tree problem using about 1.5-second runtime and 1.3-mb memory on an ibm rs/6000 workstation.
integrated floorplanning and interconnect planning. the vlsi fabrication has entered the deep sub-micron era and communication between different components has significantly increased. interconnect delay has become the dominant factor in total circuit delay. as a result, it is necessary to start interconnect planning as early as possible. in this paper, we propose a method to combine interconnect planning with floorplanning. our approach is based on the wong-liu floorplanning algorithm. when the positions, orientations, and shapes of the cells are decided, the pin positions and routing of the interconnects are decided as well. we use a multi-stage simulated annealing approach in which different interconnect planning methods are used in different ranges of temperatures to reduce running time. a temperature adjustment scheme is designed to give smooth transitions between different stages of simulated annealing. experimental results show that our approach performs well.
test generation for delay faults in non-scan and partial scan sequential circuits. a recently proposed transition fault model for sequential circuits is considered. in this fault model, a transition fault is characterized by the fault site, the fault type and the fault size. it was observed that neither a comprehensive functional verification sequence nor a sequence with a high stuck-at fault coverage gives a high transition fault coverage for sequential circuits. deterministic test generation for delay faults is required to raise the coverage to a reasonable level. here, a test generation algorithm for this fault model is presented. with the use of a fault injection technique, tests for transition faults can be generated by using a stuck-at fault test generation algorithm with some modifications. the test generator datest has been integrated with a sequential circuit delay fault simulator, tfsim. experimental results for iscas-89 benchmark circuits and some designs are presented. for partial scan circuits, a test application scheme for detecting transition faults is described. modifications on test generation and fault simulation algorithms required for partial scan circuits are presented. experimental results are presented
risa: accurate and efficient placement routability modeling. the prevalence of net list synthesis tools raises great concern on routability of cell placement created with state-of-the-art placement techniques. in this paper, an accurate and efficient placement routability modeling technique is proposed and incorporated into the prevailing simulated annealing approach. this accurate and efficient modeling is based on the supply versus demand analysis of routing resource over an array of regions on a chip. vertical and horizontal routability is analyzed separately due to the bias of routing resource in multiple-metal-layer asic designs. a special technique on net bounding box partitioning is also proposed and critical to the accuracy of this modeling at the presence of mega cells, which tend to cause local routing congestion. by incorporating this efficient modeling into the cost function of simulated annealing, experiments conducted on small to large industrial designs indicate that placement routability evaluated with a global router is greatly improved as a result of the proposed accurate modeling.
synthesis of cmos domino circuits for charge sharing alleviation. the charge sharing (cs) problem is one of notorious noise problems in domino circuits design and test. in this paper, this problem is thoroughly investigated by considering circuit topology and circuit function. the sensitivity of each domino gate to the cs problem is represented by the concept of cs-vulnerability. a method to derive the cs-vulnerability and the test pattern for each domino gate is suggested. we also propose a transistor reordering method to dramatically reduce the cs-vulnerabilities for all domino gates, so that the cs problem can be alleviated. simulation results demonstrate that our transistor reordering method can efficiently reduce the cs-vulnerabilities for most of domino circuits.
fault emulation: a new approach to fault grading. in this paper, we propose a method of using an fpga-based emulation system for fault grading. the real-time simulation capability of a hardware emulator could significantly improve the run-time of fault grading, which is one of the most resource-intensive tasks in the design process. a serial fault emulation algorithm is employed and enhanced by two speed-up techniques. first, a set of independent faults can be emulated in parallel. second, simultaneous injection of multiple dependent faults is also possible by adding extra supporting circuitry. because the reconfiguration time spent on mapping the numerous faulty circuits into the fpga boards could be the bottleneck of the whole process, using extra logic for injecting a large number of faults per configuration can reduce the number of reconfigurations, and thus, significantly improve the efficiency. some modeling issues that are unique in the fault emulation environment are also addressed. the performance estimation indicates that this approach could be several orders of magnitude faster than the existing software approaches for large designs.
an efficient method for hot-spot identification in ulsi circuits. in this paper, we present a method to efficiently identify the onchip hot spots in ulsi circuits. a set of mathematical formulae were derived in analytical forms so that local temperature information can be fetched quickly. these formulae were based on the green's function and error function approximation, and the resulting equations were further simplified to a tractable level by asserting different constraints. experimental result shows that this method is able to accurately locate the hot spots with little time complexity. it is particularly useful for temperature-driven circuit macro placement in early chip design phase, for which a large number of design iterations is needed and simulation efficiency is much required.
circuit partitioning with logic perturbation. traditionally, the circuit partitioning problem is done by first modeling a circuit as a graph and then partitioning is performed on the modeling graph. using the concept of alternative wires, we propose an efficient method that is able to preserve a local optimal solution in the graph domain while a different graph, representing the same circuit, is generated. when a conventional graph partitioning technique reaches a local optimal solution, our proposed technique generates a different graph that is logically equivalent to the original circuit, and that has equal or better partitioning solution. faced with a different graph which is newly generated, together with a currently good partitioning solution, a conventional graph partitioning technique may then escape from the local optimum and continue searching for better solutions in a different graph domain. the proposed technique can be combined with almost any graph partitioner. experiments show encouraging results.
floorplan design for multi-million gate fpgas. modern fpgas have multi-millions of gates and future generations of fpga will be even more complex. this means floorplanning tools will soon be extremely important for the physical design of fpgas. due to the heterogeneous logic and routing resources on an fpga, fpga floorplanning is very different from the traditional floorplanning for asics. this work presents the first fpga floorplanning algorithm targeted for fpgas with heterogeneous resources (e.g., xilinx's spartan3 chips consisting of columns of clbs, ram blocks, and multiplier blocks). our algorithm can generate floor-plans for xilinx's xc3s5000 architecture (largest of the spartan3 family) in a few minutes.
fame: a fault-pattern based memory failure analysis framework. a memory failure analysis framework is developed-the failureanalyzer for memories (fame). the fame integrates the memoryerror catch and analysis (meca) system and the memory defect diagnostics(mdd) system. the fault-type based diagnostics approachused by meca can improve the efficiency of the test and diagnosticalgorithms. the fault-pattern based diagnostics approach used bymdd further improves the defect identification capability. the famealso comes with a powerful viewer for inspecting the failure patternsand fault patterns. it provides an easy way to narrow down the potentialcause of failures and identify possible defects more accuratelyduring the memory product development and yield ramp-up stage.an experiment has been done on an industrial case, demonstratingvery accurate results in a much shorter time as compared with theconventional way.
stable multiway circuit partitioning for eco. we propose a new stable multiway partitioning algorithm,where stability is defined as an additional quality of a partitioningsolution. the stability of a partitioning algorithm isan important criterion for a partitioning based placement toachieve timing closure through the repetition of the placementprocedure [invited talk: important placement considerations for modern vlsi chips]. given a previous partitioning result p*on an original netlist hypergraph h* and a partially modifiednetlist hypergraph h, a new cost function with similarityfactor is defined to produce a new partition p on hwhich is similar to the original partition p*. the proposedalgorithm is the first approach that quantifies the degree ofsimilarity of a current partition to the original partition usingsimilarity cost. our goal is to build a new partition ina relatively short run time, whose cut quality is not muchdegraded from that of the original partition p* while it preservesas much of the previous groupings in p* as possible.the proposed partitioner is especially beneficial to engineeringchange order (eco) applications, where partial modificationsof a netlist are handled by the incremental methodologyin a design iteration cycle. our approach helps ecoplacers maximize the incremental capability since the portionsto be re-placed are minimized. experimental resultsshow that the proposed algorithm achieves a high qualitypartition comparable to a state-of-the-art multilevel partitionerhmetis [multilevel k-way hypergraph partitioning], while many portions of the groupings in the previous partition are preserved in the current partition.the tradeoff between similarity and cut quality with respectto a varying similarity coefficient is also shown.
diagnosis of realistic bridging faults with single stuck-at information. abstract: precise failure analysis requires accurate fault diagnosis. a previously proposed method for diagnosing bridging faults using single stuck-at dictionaries was applied only to small circuits, produced large and imprecise diagnoses, and did not take into account the byzantine generals problem for bridging faults. we analyze the original technique and improve it by introducing the concepts of match restriction, match requirement, and failure recovery. our new technique, which requires no information other than that used by standard stuck-at methods, produces diagnoses that are an order of magnitude smaller than those produced by the original technique and produces many fewer misleading diagnoses than that of traditional stuck-at diagnosis.
inside: instruction selection/identification & design exploration for extensible processors. this paper presents the inside system that rapidly searchesthe design space for extensible processors, given area and performance constraints of an embedded application, while minimizing the design turn-around-time. our system consists ofa) a methodology to determine which code segments are mostsuited for implementation as a set of extensible instructions,b) a heuristic algorithm to select pre-configured extensibleprocessors as well as extensible instructions (library), and c)an estimation tool which rapidly estimates the performance ofan application on a generated extensible processor. by selecting the right combination of a processor core plus extensible instructions, we achieve a performance increase on average of 2.03x (up to 7x) compared to the base processor core at aminimum hardware overhead of 25% on average.
a quantitative study and estimation models for extensible instructions in embedded processors. designing extensible instructions is a computationally complex task, due to the large design space each instruction is exposed to. one method of speeding up the design cycle is to characterize instructions and estimate their peculiarities during a design exploration. in this paper, we study and derive three estimation models for extensible instructions: area overhead, latency, and power consumption under a wide range of customization parameters. system decomposition and regression analysis are used as the underlying methods to characterize and analyze extensible instructions. we verify our estimation models using automatically and manually generated extensible instructions, plus extensible instructions used in large real-world applications. the mean absolute error of our estimation models arc as small as: 3.4% (6.7% max.) for area overhead, 5.9% (9.4% max.) for latency, and 4.2% (7.2% max.) for power consumption, compared to estimation through the time consuming synthesis and simulation steps using commercial tools. our estimation models achieve an average speedup of three orders of magnitude over the commercial tools and thus enable us to conduct a fast and extensive design space exploration that would otherwise not be possible. the estimation models are integrated into our extensible processor tool suite.
compact modeling and spice-based simulation for electrothermal analysis of multilevel ulsi interconnects. this paper presents both compact analytical models and fast spice based 3-d electro-thermal simulation methodology to characterize thermal effects due to joule heating in high performance cu/low-k interconnects under steady-state and transient stress conditions. the results demonstrate excellent agreement with experimental data and those using finite element (fe) thermal simulations (ansys). the effect of vias, as additional heat sinking paths to alleviate the temp erature rise in the metal wires, is included in our analysis to provide more accurate and realistic thermal diagnosis. it shows that the effectiveness of vias in reducing the temperature rise in interconnects is highly dependent on the via separation and the dielectric materials used. the analytical model is then applied to estimate the temperature distribution in multi-level interconnects. in addition, we discuss the possibility that, under the impact of thermal effects, the performance improvement expected from the use of low-k dielectric materials may be degraded. furthermore, thermal coupling between wires is evaluated and found to be significant. finally, the impact of metal wire aspect ratio on interconnect thermal characteristics is discussed.
random pattern testable logic synthesis. previous procedures for synthesis of testable logic guarantee that all faults in the synthesized circuits are detectable. however, the detectability of many faults in these circuits can be very low leading to poor random pattern testability. a new procedure to perform logic synthesis that synthesizes random pattern testable multilevel circuits is proposed. experimental results show that the circuits synthesized by the proposed procedure tstfx are significantly more random pattern testable and smaller than those synthesized using its counterpart fast_extract (fx) in sis. the proposed synthesis procedure design circuits that require only simple random pattern generators in built-in self-test, thereby obviating the need for complex bist circuitry.
bist tpg for faults in system backplanes. a built-in self-test (bist) methodology to test system backplanes by using bist functionality in each of its constituent boards is presented. since the configurations of systems change frequently, at the system level, the proposed methodology employs a simple test schedule which can be easily changed whenever the system configuration is changed. since the boards used in such systems are designed for use in a wide variety of systems, the proposed methodology defines the test objectives to be achieved by a board's bist circuit in terms of the board's edge pin connections, independent of the configurations of the systems in which the board may be used. it is shown that the combination of the proposed test schedule and the availability, on each board in the system, of any bist circuit that satisfies the proposed test objectives, guarantees safe testing of faults in backplanes. a programmable test architecture and an algorithm to program the architecture to obtain bist that satisfies the test objectives is also presented. finally, the applicability and effectiveness of the methodology is demonstrated via its application to multiple configurations of an example system that uses a vme backplane.
fast and efficient phase conflict detection and correction in standard-cell layouts. alternating-aperture phase shift masking (aapsm), a form of strong resolution enhancement technology (ret) is used to image critical features on the polysilicon layer at smaller technology nodes. this technology imposes additional constraints on the layouts beyond traditional design rules. of particular note is the requirement that all critical features be flanked by opposite-phase shifters, while the shifters obey minimum width and spacing requirements. a layout is called phase-assignable if it satisfies this requirement. phase conflicts between shifters have to be removed to enable the use of aapsm for layouts that air not phase-assignable. previous work has sought to detect a suitable set of phase conflicts to be removed, as well as correct them as well as correct them. this paper has two key contributions: (1) a new computationally efficient approach to detect a minimal set of phase conflicts, which when corrected produces a phase-assignable layout; (2) a novel layout modification scheme for correcting these phase conflicts in standard-cell blocks. unlike previous formulations of this problem, the proposed solution for the conflict detection problem does not frame it as a graph bipartization problem. instead, a simpler and more computationally efficient reduction is proposed. this simplification greatly improves the runtime, while maintaining the same improvements ill the quality of results. an average runtime speedup of 5.9/spl times/ is achieved using the new flow. a new layout modification scheme for correcting phase conflicts in large standard-cell blocks is also proposed. the proposed layout modification scheme can handle all phase conflicts in large standard-cell blocks with small increases in area. our experiments show that the percentage area increase for making typical standard-cell blocks phase-assignable ranges from 3.4-9.1%.
a comparative study of design for testability methods using high-level and gate-level descriptions. a comparative study of a gate-level test generator and a high-level test generator by benchmarking them on a common suite of circuits is presented. based on the examination of the results dft techniques that use high-level circuit information are proposed. the results obtained after partial scan selection by a high-level dft tool are compared with results obtained by a gate-level partial scan tool. this detailed comparative study demonstrates that a dft tool can make a more effective selection of partial scan flip-flops by exploiting the high-level circuit information, and by accurately predicting the hard-to-test areas of a circuit
automatic compositional minimization in ctl model checking. a method for reducing the complexity of ctl model checking on a system of interacting finite state machines is described. the method consists essentially of reducing each component machine with respect to the property to be verified, and then verifying the property on the composition of the reduced components. the procedure is fully automatic and produces an exact result. the potential of the approach is assessed on real-world examples, and the method is demonstrated on a circuit
fast flip-chip power grid analysis via locality and grid shells. full-chip power grid analysis is time consuming. several techniques have been proposed to tackle the problem but typically they deal with the power grid as a whole or partition at unnatural boundaries. using a locality effect under flip-chip packaging, we propose a natural partitioning approach based on overlapping power grid "shells". the technique makes more efficient any previous simulation techniques that are polynomial in grid size. it is also parallelizable and therefore extremely fast. using complete partitions gives no loss of accuracy compared to a full matrix solution, while lesser partitions are conservative for droop and current. results on a recent pentium/spl reg/ microprocessor design show excellent speed and accuracy.
minimizing the number of test configurations for fpgas. fpga test cost can be greatly reduced by minimizing the number of test configurations. a test technique is presented for fpgas with multiplexer-based routing architectures in which multiple logical paths through each multiplexer is enabled instead of only one path. it is shown that for xilinx virtex-ii and spartan-3 fpgas only 8 test configurations are required to achieve 100% stuck-at, pip stuck-on, and pip stuck-off fault coverage.
taco: temperature aware clock-tree optimization. in this paper, an efficient linear time algorithm taco is proposed for the first time to minimize the worst case clock skew in the presence of on-chip thermal variation. taco, while tries to minimize the worst case clock skew, also attempts to minimize the clock tree wirelength by building up merging diamonds in a bottom-up manner. as an output, taco provides balanced merging points and the modified clock routing paths to minimize the worst case clock skew under thermal variation. experimental results on a set of standard benchmarks show 50-70% skew reduction with less than 0.6% wirelength overhead.
incremental placement for timing optimization. an incremental timing driven placement algorithm is presented.we introduce a fast path-based analytical approach for timingimprovement. our method achieves timing optimization byreducing the enclosing bounding boxes of selected nets oncritical paths. furthermore, this technique tries to minimizemodifications to the initial placement while improving the delayof the circuit incrementally. two contributions of this work are1) efficient conversion of a path-based timing minimizationproblem to a geometric net-constraint problem and 2) minimalmodification of a placement to improve timing. our techniquecan take an initial placement from any algorithm and improvetiming iteratively. the experiments show that the proposedapproach is very efficient.
frame-based dynamic voltage and frequency scaling for a mpeg decoder. this paper describes a dynamic voltage and frequency scaling (dvfs) technique for mpeg decoding to reduce the energy consumption while maintaining a quality of servic(qos) constraint. the computational workload for an incoming frame is predicted using a frame-based history so that the processor voltage and frequency can be scaled to provide the exact amount of computing power needed to decode the frame. more precisely, the required decoding time for each frame is separated into two parts: a frame-dependent (fd) part and a frame-independent (fi) part. the fd part varies greatly according to the type of the incoming frame whereas the fi part remains constant regardless of the frame type. in the dvfs scheme presented in this paper the fi part is used to compensate for the prediction error that may occur during the fd part such that a significant amount of energy can be saved while meeting the frame rate requirement. the proposed dvfs algorithm has been implemented on a strongarm-1110 based evaluation board. measurement results demonstrate a higher than 50% cpu energy saving as a result of dvfs.
dynamic voltage and frequency scaling under a precise energy model considering variable and fixed components of the system power dissipation. this work presents a dynamic voltage and frequency scaling (dvfs) technique that minimizes the total system energy consumption for performing a task while satisfying a given execution time constraint. we first show that in order to guarantee minimum energy for task execution by using dvfs it is essential to divide the system power into active and standby power components. next, we present a new dvfs technique, which considers not only the active power, but also the standby component of the system power. this is in sharp contrast with previous dvfs techniques, which only consider the active power component. we have implemented the proposed dvfs technique on the bitsyx platform - an intel pxa255-based platform manufactured by ads inc., and report detailed power measurements on this platform. these measurements show that, compared to conventional dvfs techniques, an additional system energy saving of up to 18% can be achieved while satisfying the user-specified timing constraints.
parametric yield maximization using gate sizing based on efficient statistical power and delay gradient computation. with the increased significance of leakage power and performance variability, the yield of a design is becoming constrained both by power and performance limits, thereby significantly complicating circuit optimization. in this paper, we propose a new optimization method for yield optimization under simultaneous leakage power and performance limits. the optimization approach uses a novel leakage power and performance analysis that is statistical in nature and considers the correlation between leakage power and performance to enable accurate computation of circuit yield under power and delay limits. we then propose a new heuristic approach to incrementally compute the gradient of yield with respect to gate sizes in the circuit with high efficiency and accuracy. we then show how this gradient information can be effectively used by a non-linear optimizer to perform yield optimization. we consider both inter-die and intra-die variations with correlated and random components. the proposed approach is implemented and tested and we demonstrate up to 40% yield improvement compared to a deterministically optimized circuit.
control generation for embedded systems based on composition of modal processes. in traditional distributed embedded system designs, control information is often replicated across several processes and kept coherent by application-specific mechanisms. consequently, processes cannot be reused in a new system without tailoring the code to deal with the new system's control information. the modal process framework [5] provides a high-level way to specify the coherence of replicated control information independently of the behavior of the processes. thus multiple processes can be composed without internal tailoring and without suffering from errors common in lower-level specification styles. this paper first describes a kernel-language representation for the high-level composition operators; it also presents a synthesis algorithm for the mode manager, the runtime code that maintains control information coherence within and between distributed processors.
interface co-synthesis techniques for embedded systems. abstract: a key aspect of the synthesis of embedded systems is the automatic integration of system components. this entails the derivation of both the hardware and software interfaces that will bind these elements together and permit them to communicate correctly and efficiently. without the automatic synthesis of these interfaces, designers are not able to fully simulate and evaluate their systems. frequently, they are discouraged from exploring the design space of different hardware/software partitions because practical concerns mandate minimizing changes late in the design cycle, thus leading to more costly implementations than necessary. this paper presents a set of techniques that form the basis of a comprehensive solution to the synthesis of hardware/software interfaces. software drivers and glue logic are generated to connect processors to peripheral devices, hardware co-processors, or communication interfaces while meeting bandwidth and performance requirements. we use as examples a set of devices that communicate over an infrared local communications network (highlighting a video wrist-watch display) to explain our techniques and the need for design space exploration tools for embedded systems.
energy-efficient platform designs for real-world wireless sensing applications. real-world wireless sensing applications demand system platforms with a wide range of size, cost, power consumption, connectivity, performance, and flexibility requirements. these goals cannot be achieved without understanding the nature of the sensing functions in the first place, which can be classified into passive vs. active sensing, event detection vs. data acquisition, and real-time monitoring vs. data logging. this paper discusses platform design techniques for supporting these design goals through the trade-offs of sensing devices, wireless interfaces, and computation and control units. we also cover power subsystem design for supply-aware optimizations, including load/supply matching, power defragmentation in multi-supply systems, and use of supercapacitors. to evaluate these system platforms, we describe an emulation-based benchmarking methodology to quantify fitness metrics.
statistical estimation of sequential circuit activity. abstract: in this paper, we present a monte carlo based technique to estimate signal activity at the internal nodes of sequential logic circuits. the technique takes spatial and temporal correlations of logic signals into consideration. the monte carlo based techniques that have been proposed for combinational circuits can not be directly applied to sequential circuits due to the initial transient problem. the proposed approach deals with this problem by gaining insight from markov chain theory. experimental results show that the error (%) of estimated activity of individual nodes is within 3% in comparison to that of long run simulation results.
estimation of circuit activity considering signal correlations and simultaneous switching. this paper presents accurate estimation of signal activity at the internal nodes of cmos combinational logic circuits. the methodology is based on stochastic model of logic signals and takes correlations and simultaneous switching of signals at logic gate inputs into consideration. in combinational logic synthesis, in order to minimize spurious transitions due to finite propagation delays, it is crucial to balance all signal paths and to reduce the logic depth. as a result of balancing delays through different paths, the inputs to logic gates may switch at approximately the same time. we have developed and implemented an technique to calculate signal probability and switching activity of the cmos combinational logic circuits. experimental results show that if simultaneous switching is not considered the switching activities of the internal nodes can be off by more than 100% compared to simulation based techniques. in contrast, our technique is on the average within 2% of logic simulation results.
efficient reduced-order modeling for the transient simulation of three-dimensional interconnect. abstract: multipole-accelerated surface-volume methods have proved to be very efficient techniques for delay and cross-talk simulation of three-dimensional integrated circuit interconnect. however, to be efficiently combined with transistor circuitry in a spice-level simulation, reduced-order models which have accurate low-frequency behavior must be constructed. asymptotic waveform evaluation (awe) or pade-via-lanczos (pvl) algorithms can not be used directly to construct the reduced-order models from the surface-volume formulation, because the formulation generates dense matrices which are too expensive to factor. in this paper we describe a two-level approach to efficiently generating reduced-order models with accurate low frequency behavior. first, reduced-order models which match taylor series terms at s=/spl infin/ are efficiently generated from the surface-volume formulation using an arnoldi method, and then these fairly high-order models are used to efficiently construct lower-order models which snatch taylor series terms at s=0. examples are given to demonstrate the accuracy of the resultant low-order model.
technology mapping for field-programmable gate arrays using integer programming. we show that the fpga technology mapping problem can be efficiently implemented as a mixed integer linear programming (milp) problem which generates truly optimal mappings. the milp approach can handle a wide variety of fpga logic block architectures. we present a compact milp formulation for logic blocks based on lookup tables (luts) multiplexers. we also show that the milp formulation can be easily modified to modified to optimize area, delay, or a combination of both. we demonstrate that moderately large benchmark circuits can be mapped in a reasonable time using the milp approach directly. for larger circuits, we propose a technique of partitioning a circuit prior to mapping, which drastically reduces the computation time with little or no loss in optimality.
a new approach to simultaneous buffer insertion and wire sizing. in this paper, we present a completely new approach to the problem of delay minimization by simultaneous buffer insertion and wire sizing for a wire. we show that the problem can be formulated as a convex quadratic program, which is known to be solvable in polynomial time. nevertheless, we explore some special properties of our problem and derive an optimal and very efficient algorithm to solve the resulting program. given m buffers and a set of n discrete choices of wire width, the running time of our algorithm is o(mn^2) and is independent of the wire length in practice. for example, an instance of 100 buffers and 100 choices of wire width can be solved in 3 seconds. besides, our formulation is so versatile that it is easy to consider other objectives like wire area or power dissipation, or to add constraints to the solution. also, wire capacitance lookup tables, or very general wire capacitance models which can capture area capacitance, fringing capacitance, coupling capacitance, etc. can be used.
retiming with interconnect and gate delay. in this paper, we study the problem of retiming of sequential circuitswith both interconnect and gate delay. most retiming algorithms haveassumed ideal conditions for the non-logical portions of the datapaths, which are not sufficiently accurate to be used in high performancecircuits today. in our modeling, we assume that the delay ofa wire is directly proportional to its length. this assumption is reasonablesince the quadratic component of a wire delay is significantlysmaller than its linear component when the more accurate elmore delaymodel is used. a simple experiment is conducted to illustrate thevalidity of this assumption. we present two approaches to solve thisproblem, both of which have polynomial time complexity. the firstone can compute the optimal clock period while the second one isan improvement over the first one in terms of practical applicability.the second approach gives solutions very close to the optimal (0.13%more than the optimal on average) but in a much shorter runtime.a circuit with more than 22k gates and 32k wires can be optimallyretimed in 83.56 seconds by a pc with an 1.8ghz intel xeon processor.
delay and area optimization for compact placement by gate resizing and relocation. in this paper, we first present an efficient algorithm for the gate sizing problem. then we propose an algorithm which performs delay and area optimization for a given compact placement by resizing and relocating cells in the circuit layout. since the gate sizing procedure is embedded within the placement adjustment process, interconnect capacitance information is included in the gate size selection process. as a result, the algorithm is able to obtain superior solutions.
dynamic power management using adaptive learning tree. dynamic power management (dpm) is a technique to reduce power consumption of electronic systems by selectively shutting down idle components. the quality of the shutdown control algorithm (power management policy) mostly depends on the knowledge of user behavior, which in many in many cases is initially unknown or non-stationary. for this reason, dpm policies should be capable of adapting to changes in user behavior. in this paper, we present a novel dpm scheme based on idle period clustering and adaptive learning trees. we also provide a design guide for applying our technique to components with multiple sleep states. experimental results show that our technique outperforms other advanced dpm schemes as well as simple time-out policies. the proposed approach shows little deviation of efficiency for various workloads having different characteristics, while other policies show that their efficiency changes drastically depending on the trace data characteristics. furthermore, experimental evidence indicates that our workload learning algorithm is stable and has fast convergence.
skew sensitivity minimization of buffered clock tree. given a topology of clock tree and a library of buffers, we propose an efficient skew sensitivity minimization algorithm using dynamic programming approach. our algorithm finds the optimum buffer sizes, its insertion levels in the clock tree, and optimum wire widths to minimize the skew sensitivity under manufacturing variations. careful fine tuning by shifting buffer locations at the last stage preserves the minimum skew sensitivity property and reduces the interconnect length. for a given clock tree of n points and a library of s different buffer sizes, the run time of the presented algorithm is o(log3n&bull;s2).experimental results show a significant reduction of clock skews ranging from 87 times to 144 times compared to the clock skews before applying the proposed algorithm. we also observe a further reduction of the propagation delay of clock signals as a result of applying the proposed skew sensitivity algorithm.
an algorithm for synthesis of system-level interface circuits. we describe an algorithm for the synthesis and optimization of interface circuits for embedded system components such as microprocessors, memory asic, and network subsystems with fixed interfaces. the algorithm accepts the timing characteristics of two system components as input, and generates a combinational interface (glue logic) circuit. the algorithm consists of two parts. in the first part, we determine the direct pin-to-pin connections in the interface circuit employing a 0/1 ilp formulation to minimize wiring area and dynamic power consumption. in the second part, we determine logic subcircuits in the interface circuit, utilizing the timing diagrams of the system components. the proposed algorithm has been implemented in a software package synterface. experimental results are presented to demonstrate the effectiveness of the algorithm.
expected current distributions for cmos circuits. the analysis of cmos vlsi circuit switching current has become an increasingly important and difficult task from both a vlsi design and simulation software perspective. this paper presents a new static switching current estimation algorithm based on the idea of "expected current distributions" (ecds). unlike previous "expected waveform" approaches, ecds model not only the expected value of switching current waveforms over all time, but also the variances and covariances of all waveform segments as well. this extra information allows a switching current wave form to be modeled by a random process with both first and second order ensemble statistics. this specification provides the power spectral density of the switching current and allows the use of traditional frequency domain noise analysis to simulate the behavior of the switching current in the electrical supply network. an ecd simulation procedure is described and results are presented for the iscas85 combinational benchmark circuits. estimated quantities include total average and rms vdd current, the autocorrelation function of the total vdd current waveform and per-gate average and rms vdd currents. the results show speedups of up to 100x and good agreement with respect to figures obtained using dynamic logic simulation and statistical mean estimation.
efficient canonical form for boolean matching of complex functions in large libraries. a new algorithm is developed which transforms the truth table or implicant table of a boolean function into a canonical form under any permutation of inputs. the algorithm is used for boolean matching for large libraries that contain cells with large numbers of inputs and implicants. the minimum cost canonical form is used as a unique identifier for searching for the cell in the library. the search time is nearly constant if a hash table is used for storing the cells' canonical representations in the library. experimental results on more than 100,000 gates confirm the validity and feasible run-time of the algorithm.
hybrid decision diagrams. abstract: functions that map boolean vectors into the integers are important for the design and verification of arithmetic circuits. mtbdds and bmds have been proposed for representing this class of functions. we discuss the relationship between these methods and describe a generalization called hybrid decision diagrams which is often much more concise. we show how to implement arithmetic operations efficiently for hybrid decision diagrams. in practice, this is one of the main limitations of bmds since performing arithmetic operations on functions expressed in this notation can be very expensive. in order to extend symbolic model checking algorithms to handle arithmetic properties, it is essential to be able to compute the bdd for the set of variable assignments that satisfy an arithmetic relation. in our paper, we give an efficient algorithm for this purpose. moreover, we prove that for the class of linear expressions, the time complexity of our algorithm is linear in the number of variables.
concurrent flip-flop and repeater insertion for high performance integrated circuits. for many years, cmos process scaling has allowed a steady increase in the operating frequency and integration density of integrated circuits. only recently, however, have we reached a point where it takes several clock cycles for global signals to traverse a complex digital system such as a modern microprocessor. thus, interconnect latency must be taken into account in current and future design tools at the architectural as well as synthesis level. to this purpose, this work proposes a new latency-aware technique for the performance-driven concurrent insertion of flip-flops and repeaters in vlsi circuits. overwhelming evidence showing an exponential increase in the number of pipelined interconnects with process scaling, for high-performance microprocessors as well as high-end asics, is also presented. this increase indicates a radical change in current design methodologies to cope with this new emerging problem.
dynamic scheduling and synchronization synthesis of concurrent digital systems under system-level constraints. we present in this paper a novel control synthesis technique for system-level specifications that are better described as a set of concurrent synchronous descriptions, their synchronizations and constraints. the proposed synthesis technique considers the degrees of freedom introduced by the concurrent models and by the environment in order to satisfy the design constraints.synthesis is divided in two phases. in the first phase, the original specification is translated into an algebraic system, for which complex control-flow constraints and quantifiers of the design are determined. this algebraic system is then analyzed and the design space of the specification is represented by a finite-state machine, from which a set of boolean formulas is generated and manipulated in order to obtain a solution. this method contrasts with usual high-level synthesis methods in that it can handle arbitrarily complex control-flow structures, concurrency and synchronization by allowing the scheduling of the operations to change dynamically over time.
a convex programming approach to positive real rational approximation. as system integration evolves and tighter design constraints must be met, it becomes necessary to account for the non-ideal behavior of all the elements in a system. certain devices common in high-frequency integrated circuit applications, such as spiral inductors, saw filters, etc, are often described and studied in the frequency domain. models take the form of frequency domain data obtained through measurement or through physical simulation. usually the available data is sampled, incomplete, noisy, and covers only a finite range of the spectrum.in this paper we present a methodology for generating guaranteed passive time-domain models of frequency-described subsystems. the methodology presented is based on convex programming based algorithms for fixed denominator system identification. the algorithm is guaranteed to produce a passive system model that is optimal in the sense of having minimum weighted square error in the frequency band of interest over all models with a prescribed set of system poles. an incremental-fitting reformulation of the problem is also introduced that trades optimality for efficiency while still guaranteeing passivity. results of the application of the proposed methodologies to the modeling of a variety of subsystems are presented and discussed.
optimization based passive constrained fitting. verification of contemporary integrated circuits requires accurate modeling of high-frequency effects in all passive component sub-systems. often, descriptions of those subsystems are only available in the frequency-domain. in this paper, we propose a simple, scalar, constrained-passive rational approximation scheme that incorporates a grid-based test for strict positive realness. in contrast to similar recent work based on convex optimization and the positive real lemma, the methodology is potentially more efficient, since it does not introduce a quadratic number of auxiliary variables, is potentially more accurate, since pole locations can be re-adjusted during the optimization, but possibly less reliable, since it relies on the solution of optimization problems that are not convex. there-fore, because of the use of local constrained non-convex optimization, the generation of feasible initial guesses is also considered.
an optimal technology mapping algorithm for delay optimization in lookup-table based fpga designs. presents a polynomial time technology mapping algorithm, called flow-map, that optimally solves the lookup-table (lut)-based field-programmable gate array (fpga) technology mapping problem for depth minimization for general boolean networks. this theoretical breakthrough makes a sharp contrast with the fact that the conventional technology mapping problem in library-based designs is np-hard. a key step in flow-map is to compute a minimum height k-feasible cut in a network, solved by network flow computation. the algorithm also effectively minimizes the number of luts by maximizing the volume of each cut and by several postprocessing operations. the flow-map algorithm was tested on a a set of benchmarks and achieved reductions of both the network depth and the number of luts in mapping solutions as compared with previous algorithms
architectural synthesis integrated with global placement for multi-cycle communication. multiple clock cycles are needed to cross the global interconnectsfor multi-gigahertz designs in nanometer technologies. forsynchronous design, this requires the consideration of multi-cycleon-chip communication at the high level. in this paper, we presenta new architectural synthesis system integrated with globalplacement, named mcas (multi-cycle architectural synthesis),on top of the recently-proposed regular distributed register(rdr) micro-architecture. the rdr architecture provides aregular synthesis platform for supporting multi-cyclecommunication. novel architectural synthesis algorithms thatintegrate high-level synthesis with global placement have beendeveloped in mcas, including scheduling-driven placement anddistributed controller generation, etc. experimental results showthat our methodology can achieve a clock period improvement of31% and a total latency improvement of 24% on averagecompared to the conventional architectural synthesis flow.
an implicit connection graph maze routing algorithm for eco routing. eco routing is a very important design capability in advanced ic, mcm and pcb designs when additional routings need to be made at the latter stage of the physical design. eco is difficult in two aspects: first, there are a large number of existing interconnects which become obstacles in the region. a hierarchical approach is not applicable in this situation, and we need to search a large, congested region thoroughly. second, advances in circuit designs require variable width and variable spacing on interconnects. thus, a gridless routing algorithm is needed. in this paper, we propose to use an implicit representation of a non-uniform grid graph for gridless maze routing algorithm. a novel slit-tree plus interval-tree data structure is developed, combined with a cache structure, to support efficient queries into the connection graph. our experiments show that this data structure is very small in memory usage while very fast in answering maze expansion related queries. this make the framework very useful in the eco type of routing.
multilevel approach to full-chip gridless routing. this paper presents a novel gridless detailed routing approach based on multilevel optimization. the multilevel framework with recursive coarsening and refinement in a "v-shaped" flow allows efficient scaling of our gridless detailed router to very large designs. the downward pass of recursive coarsening builds the representations of routing regions at different levels, while the upward pass of iterative refinement allows a gradual convergence to a globally optimized solution. the use of a multicommodity flow-based routing algorithm for the initial routing at the coarsest level and a modified maze algorithm for the refinement at each level considerably improves the quality of gridless routing results. compared with the recently published gridless detailed routing algorithm using wire planning [1], our multilevel gridless routing algorithm is 3&times; to 75&times; faster. we also compared our multilevel framework with a recently developed three-level routing approach [1] and a traditional hierarchical routing approach. our multilevel algorithm generates better detailed routing results with higher completion rates. to our knowledge, this is the first time that multilevel optimization has been applied to ic routing.
optimal wiresizing for interconnects with multiple sources. the optimal wiresizing problem for nets with multiple sources is studied under the distributed elmore delay model. we decompose such a net into a source subtree (sst) and a set of loading subtrees (lsts), and show the optimal wiresizing solution satisfies a number of interesting properties, including: the lst separability, the lst monotone property, the sst local monotone property and the general dominance property. furthermore, we study the optimal wiresizing problem using a variable grid and reveal the bundled refinement property. these properties lead to efficient algorithms to compute the lower and upper bounds of the optimal solutions. experiment results on nets from an intel processor layout show an interconnect delay reduction of up to 35.9\% when compared to the minimum-width solution. in addition, the algorithm based on a variable grid yields a speedup of two orders of magnitude without loss of accuracy, when compared with the fixed grid based methods.
an efficient approach to simultaneous transistor and interconnect sizing. in this paper, we study the simultaneous transistor and interconnect sizing (stis) problem. we define a class of optimization problems as ch-posynomial programs and reveal a general dominance property for all ch-posynomial programs. we show that the stis problems under a number of transistor delay models are ch-posynomial programs and propose an efficient and near-optimal stis algorithm based on the dominance property. when used to solve the simultaneous driver/buffer and wire sizing problem for real designs, it reduces the maximum delay by up to 16.1%, and more significantly, reduces the power consumption by a factor of 1.63x, when compared with the original designs. when used to solve the transistor sizing problem, it achieves a smooth area-delay trade-off. moreover, the algorithm optimizes a clock net of 367 drivers/buffers and 59304 /spl mu/m-long wire in 120 seconds, and a 32-bit adder with 1026 transistors in 66 seconds on a sparc-5 workstation.
global interconnect sizing and spacing with consideration of coupling capacitance. the paper presents an efficient approach to perform global interconnect sizing and spacing (giss) for multiple nets to minimize interconnect delays with consideration of coupling capacitance, in addition to area and fringing capacitances. we introduce the formulation of symmetric and asymmetric wire sizing and spacing. we prove two important results on the symmetric and asymmetric effective fringing properties which lead to a very effective bound computation algorithm to compute the upper and lower bounds of the optimal wire sizing and spacing solution for all nets under consideration. our experiments show that in most cases the upper and lower bounds meet quickly after a few iterations and we actually obtain the optimal solution. to our knowledge, this is the first in depth study of global wire sizing and spacing for multiple nets with consideration of coupling capacitance. experimental results show that our giss solutions lead to substantially better delay reduction than existing single net wire sizing solutions without consideration of coupling capacitance.
architecture and compilation for data bandwidth improvement in configurable embedded processors. many commercially available embedded processors are capable of extending their base instruction set for a specific domain of applications. while steady progress has been made in the tools and methodologies of automatic instruction set extension for configurable processors, recent study has shown that the limited data bandwidth available in the core processor (e.g., the number of simultaneous accesses to the register file) becomes a serious performance bottleneck. in this paper, we propose a new low-cost architectural extension and associated compilation techniques to address the data bandwidth problem. specifically, we embed a single control bit in the instruction op-codes to selectively copy the execution results to a set of hash-mapped shadow registers in the write-back stage. this can efficiently reduce the communication overhead due to data transfers between the core processor and the custom logic. we also present a novel simultaneous global shadow register binding with a hash function generation algorithm to take full advantage of the extension. the application of our approach leads to a nearly-optimal performance speedup (within 2% of the ideal speedup).
simultaneous driver and wire sizing for performance and power optimization. in this paper, we study the simultaneous driver and wire sizing (sdws) problem under two objective functions: (i) delay minimization only, or (ii) combined delay and power dissipation minimization. we present general formulations of the sdws problem under these two objectives based on the distributed elmore delay model with consideration of both capacitive power dissipation and short-circuit power dissipation. we show several interesting properties of the optimal sdws solutions under the two objectives, including an important result (theorem 3) which reveals the relationship between driver sizing and optimal wire sizing. these results lead to polynomial time algorithms for computing the lower and upper bounds of optimal sdws solutions under the two objectives, and efficient algorithms for computing optimal sdws solutions under the two objectives. we have implemented these algorithms and compared them with existing design methods for driver sizing only or independent driver and wire sizing. accurate spice simulations shows that our methods reduce the delay by up to 11%&ndash;47% and power dissipation by 26%&ndash;63% compared with existing design methods.
interconnect layout optimization under higher-order rlc model. studies the interconnect layout optimization problem under a higher-order rlc model to optimize not just the delay but also the waveform for rlc circuits with non-monotone signal response. we propose a unified approach that considers topology optimization, wire-sizing optimization and waveform optimization simultaneously. our algorithm considers a large class of routing topologies, ranging from shortest-path steiner trees to bounded-radius steiner trees and steiner routings. we construct a set of required-arrival-time steiner (rats) trees, providing a smooth trade-off among signal delay, waveform and routing area. using a new incremental moment computation algorithm, we interleave topology construction with moment computation to facilitate accurate delay calculation and evaluation of waveform quality. experimental results show that our algorithm is able to construct a set of topologies providing a smooth trade-off among signal delay, signal settling time, voltage overshoot and routing cost.
bounded-skew clock and steiner routing under elmore delay. we study the minimum-cost bounded-skew routing tree problem under the elmore delay model. we present two approaches to construct bounded-skew routing trees: (i) the boundary merging and embedding (bme) method which utilizes merging points that are restricted to the boundaries of merging regions, and (ii) the interior merging and embedding (ime) algorithm which employs a sampling strategy and dynamic programming to consider merging points that are interior to, rather than on the boundary of, the merging regions. our new algorithms allow accurate control of elmore delay skew, and show the utility of merging points inside merging regions.
buffer block planning for interconnect-driven floorplanning. this paper studies buffer block planning for interconnect-driven floorplanning in deep submicron designs. we first introduce the concept of feasible region (fr) for buffer insertion, and derive closed-form formula for fr. we observe that the fr for a buffer is quite large in general even under fairly tight delay constraint. therefore, fr gives us a lot of flexibility to plan for buffer locations. we then develop an effective buffer block planning (bbp) algorithm to perform buffer clustering such that the overall chip area and the buffer block number can be minimized. to the best of our knowledge, this is the first in-depth study on buffer planning for interconnect-driven floorplanning with both area and delay consideration.
large-scale circuit placement: gap and promise. placement is one of the most important steps in the rtl-to-gdsii synthesis process, as it directly defines the interconnects, which have become the bottleneck in circuit andsystem performance in deep submicron technologies. theplacement problem has been studied extensively in the past30 years. however, recent studies show that existing placement solutions are surprisingly far from optimal. the first part of this tutorial summarizes results from recent optimality and scalability studies of existing placement tools. thesestudies show that the results of leading placement tools fromboth industry and academia may be up to 50% to 150% awayfrom optimal in total wirelength. if such a gap can be closed,the corresponding performance improvement will be equivalent to several technology-generation advancements. thesecond part of the tutorial highlights the recent progress onlarge-scale circuit placement, including techniques for wirelength minimization, routability optimization, and performance optimization.
physical planning with retiming. in this paper, we propose a unified approach to partitioning, floorplanning, and retiming for effective and efficient performance optimization. the integration enables the partitioner to exploit more realistic geometric delay model provided by the underlying floorplan. simultaneous consideration of partitioning and retiming under the geometric delay model enables us to hide global interconnect latency effectively by repositioning ff along long wires. under the proposed geometric embedding based performance driven partitioning problem, our geo algorithm performs multi-level top-down partitioning while determining the location of the partitions. we adopt the concept of sequential arrival time [14] and develop sequential required time in our retiming based timing analysis engine. geo performs cluster-move based iterative improvement on top of multi-level cluster hierarchy [4], where the gain function obtained from the timing analysis is based on the minimization of cutsize, wirelength, and sequential slack. in our comparison to (i) state-of-the-art partitioner hmetis [9] followed by retiming [11] and simulated annealing based slicing floorplanning [15], and (ii) state-of-the-art simultaneous partitioning with retiming hpm [7] followed by floorplanning [15], geo obtains 35% and 23% better delay results while maintaining comparable cutsize, wirelength, and runtime results.
a new enhanced spfd rewiring algorithm. this paper presents an in-depth study of the theory and algorithms for the spfd-based (set of pairs of functions to be distinguished) rewiring, and explores the flexibility in the spfd computation. our contributions are in the following two areas: (1) we present a theorem and a related algorithm for more precise characterization of feasible spfd-based rewiring. extensive experimental results show that for lut-based fpgas, the rewiring ability of our new algorithm is 70% higher than spfd-based local rewiring algorithms (spfd-lr) [19][21] and 18% higher than the recently developed spfd-based global rewiring algorithm (spfd-gr)[20]. (2) in order to achieve more rewiring ability on certain selected wires used in various optimizations, we study the impact of using different atomic spfd pair assignment methods during the spfd-based rewiring. we develop several heuristic atomic spfd pair assignment methods for area or delay minimization and show that they lead to 10% more selected rewiring ability than the random (or arbitrary) assignment methods. when combining (1) and (2) together, we can achieve 38.1% higher general rewiring ability.
large scale circuit partitioning with loose/stable net removal and signal flow based clustering. in this paper, we present an efficient iterative improvement based partitioning (iip) algorithm called lsr/mffs, that combines signal flow based maximum fanout free subgraph (mffs) clustering algorithm with loose and stable net removal (lsr) partitioning algorithm. the mffs algorithm generalizes existing mffc decomposition method from combinational circuits to general sequential circuits in order to handle cycles naturally. we also study the properties of the nets that straddle the cutline carefully, and introduce the concepts of the loose and stable nets as well as effective ways to remove them out of the cutset. the lsr/mffs algorithm first applies lsr algorithm to clustered netlist generated by mffs algorithm for global-level cutsize optimization and then declusters netlist for further cutsize refinement. as a result, the lsr/mffs algorithm has achieved the best cutsize result among all the bipartitioning algorithms published in the literatures with very promising runtime performance. in particular, it outperforms the recent state-of-the-art iip algorithms la3-cdip, clip-propf, strawman, hmetis-fm, and mlc by 17.4%, 12.1%, 5.9%, 3.1%, and 1.9%, respectively. it also outperforms the state-of-the-art non-iip algorithms paraboli, fbb, and panza by 32.0%, 21.4%, and 1.4%, respectively.
multi-way vlsi circuit partitioning based on dual net representation. in this paper, we study the area-balanced multi-way partitioning problem of vlsi circuits based on a new dual netlist representation named the hybrid dual netlist (hdn). given a netlist, we first compute a k-way partition of the nets based on the hdn representation, and then transform a k-way net partition into a k-way module partitioning solution. the main contribution of our work is the formulation and solution of the k-way module contention (k-mc) problem, which determines the best assignment of the modules in contention to partitions, while maintaining user-specified area requirements, when we transform the net partition into a module partition. under a natural definition of binding factor between nets and modules, and preference function between partitions and modules, we show that the k-mc problem can be reduced to a min-cost max-flow problem. we present efficient solutions to the k-mc problem based on network flow computation. extensive experimental results show that our algorithm consistently outperforms the conventional k-fm partitioning algorithm by a significant margin.
interconnect design for deep submicron ics. in this paper, we study the interconnect layout optimization problem under a higher-order rlc model to optimize not just delay, but also waveform for rlc circuits with non-monotone signal response. we propose a unified approach that considers topology optimization, wiresizing optimization, and waveform optimization simultaneously. our algorithm considers a large class of routing topologies, ranging from shortest-path steiner trees to bounded-radius steiner trees and steiner routings. we construct a set of required-arrival-time steiner trees or rats-trees, providing a smooth trade-off among signal delay, waveform, and routing area. using a new incremental moment computation algorithm, we interleave topology construction with moment computation to facilitate accurate delay calculation and evaluation of waveform quality. experimental results show that our algorithm is able to construct a set of topologies providing a smooth trade-off among signal delay, signal settling time, voltage overshoot, and routing cost.
robust mixed-size placement under tight white-space constraints. a novel and very simple correct-by-construction top-down methodology for high-utilization mixed-size placement is presented. the polarbear algorithm combines recursive cut-size-driven partitioning with fast and scalable legalization of every placement subproblem generated by every partitioning. the feedback provided by the legalizer at all stages of partitioning improves final placement quality significantly on standard ibm benchmarks and dramatically on low-white-space adaptations of them. compared to feng shui 5.1 and capo 9.3, polarbear is the only tool that can consistently find high-quality placements for benchmarks with less than 5% white space. with white space at 5%, polarbear beats capo 9.3 by 10% in average total wirelength while feng shui 5.1 frequently fails to find legal placements altogether. with 20% white space, polarbear still beats capo 9.3 by 1% and feng shui 5.1 by 1% in average total wirelength, in comparable run times.
optimality and stability study of timing-driven placement algorithms. this work studies the optimality and stability of timing-drivenplacement algorithms. the contributions of this work include twoparts: 1) we develop an algorithm for generating synthetic examples with known optimal delay for timing driven placement(t-peko). the examples generated by our algorithm can closelymatch the characteristics of real circuits. 2) using these syntheticexamples with known optimal solutions, we studied the optimalityof several timing-driven placement algorithms for fpgas by comparing their solutions with the optimal solutions, and their stability by varying the number of longest paths in the examples. our study shows that with a single longest path, the delay produced by these algorithms is from 10% to 18% longer than the optima on the average, and from 34% to 53% longer in the worst case. furthermore, their solution quality deteriorates as the number of longest paths increases. for examples with more than 5 longest paths, their delay is from 23% to 35% longer than the optima on the average, and is from 41% to 48% longer in the worst case.
a thermal-driven floorplanning algorithm for 3d ics. as the technology progresses, interconnect delays have become bottlenecks of chip performance. 3d integrated circuits are proposed as one way to address this problem. however, thermal problem is a critical challenge for 3d ic circuit design. we propose a thermal-driven 3d floorplanning algorithm. our contributions include: (1) a new 3d floorplan representation, cba and new interlayer local operations to more efficiently exploit the solution space; (2) an efficient thermal-driven 3d floorplanning algorithm with an integrated compact resistive network thermal model (cba-t); (3) two fast thermal-driven 3d floorplanning algorithms using two different thermal models with different runtime and quality (cba-t-fast and cba-t-hybrid). our experiments show that the proposed 3d floorplan algorithm with cba representation can reduce the wirelength by 29% compared with a recent published result from (hsiu et al., 2004). in addition, compared to a nonthermal-driven 3d floorplanning algorithm, the thermal-driven 3d floorplanning algorithm can reduce the maximum on-chip temperature by 56%.
an enhanced multilevel routing system. in this paper, we present several novel techniques that make the recently published multilevel routing scheme [19] more effective and complete. our contributions include: (1) resource reservation for local nets during the coarsening process, (2) congestion-driven, graph-based steiner tree construction during the initial routing and the refinement process and (3) multi-iteration refinement considering the congestion history. the experiments show that each of these techniques helps to improve the completion rate considerately. compared to [19], the new routing system reduces the number of failed nets by 2&times; to 18&times;, with less than 50% increase in runtime in most cases.
thermal via planning for 3-d ics. heat dissipation is one of the most serious challenges in 3-d ic designs. one effective way of reducing circuit temperature is to introduce thermal through-the-silicon (tts) vias. in this paper, we extended the tts-via planning in a multilevel routing framework by cong and zhang (2005), but use a much enhanced tts-via planning algorithm. we formulate the tts-via minimization problem with temperature constraints as a constrained nonlinear programming problem (nlp) based on the thermal resistive model and develop an efficient heuristic algorithm, named m-advp, which solves a sequence of simplified via planning subproblems in alternating direction in a multilevel framework. the vertical via distribution is formulated as a convex programming problem, and the horizontal via planning is based on two efficient techniques: path counting and heat propagation. experimental results show that the m-advp algorithm is more than 200/spl times/ faster than the direct solution to the npl formulation for via planning with very similar solution quality (within 1% of ts-vias count). however, compared to a recent work of multilevel ts-via planning algorithm based on temperature profiling (cong and zhang, 2005), our algorithm can reduce the total ts-via number by over 68% for the same required temperature with similar runtime.
optimization of custom mos circuits by transistor sizing. optimization of a circuit by transistor sizing is often a slow, tedious and iterative manual process which relies on designer intuition. circuit simulation is carried out in the inner loop of this tuning procedure. automating the transistor sizing process is an important step towards being able to rapidly design high-performance, custom circuits. jiffytune is a new circuit optimization tool that automates the tuning task. delay, rise/fall time, area and power targets are accommodated. each (weighted) target can be either a constraint or an objective function. minimax optimization is supported. transistors can be ratioed and similar structures grouped to ensure regular layouts. bounds on transistor widths are supported. jiffytune uses lancelot, a large-scale nonlinear optimization package with an augmented lagrangian formulation. simple bounds are handled explicitly and trust region methods are applied to minimize a composite objective function. in the inner loop of the optimization, the fast circuit simulator specs is used to evaluate the circuit. specs is unique in its ability to efficiently provide time-domain sensitivities, thereby enabling gradient-based optimization. both the adjoint and direct methods of sensitivity computation have been implemented in specs. to assist the user, interfaces in the cadence and sled design systems have been constructed. these interfaces automate the specification of the optimization task, the running of the optimizer and the back-annotation of the results on to the circuit schematic. jiffytune has been used to tune over 100 circuits for a custom, high-performance microprocessor that makes use of dynamic logic circuits. circuits with over 250 tunable transistors have been successfully optimized. automatic circuit tuning has been found to facilitate design re-use. the designers' focus shifts from solving the optimization problem to specifying it correctly and completely. this paper describes the algorithms of jiffytune, the environment in which it is used and presents a case study of the application of jiffytune to individual circuits of the microprocessor.
circuit optimization via adjoint lagrangians. the circuit tuning problem is best approached by means of gradient-based nonlinear optimization algorithms. for large circuits, gradient computation can be the bottleneck in the optimization procedure. traditionally, when the number of measurements is large relative to the number of tunable parameters, the direct method is used to repeatedly solve the associated sensitivity circuit to obtain all the necessary gradients. likewise, when the parameters outnumber the measurements, the adjoint method is employed to solve the adjoint circuit repeatedly for each measurement to compute the sensitivities. in this paper, we propose the adjoint lagrangian method, which computes all the gradients necessary for augmented-lagrangian-based optimization in a single adjoint analysis. after the nominal simulation of the circuit has been carried out, the gradients of the merit function are expressed as the gradients of a weighted sum of circuit measurements. the weights are dependent on the nominal solution and on optimizer quantities such as lagrange multipliers. by suitably choosing the excitations of the adjoint circuit, the gradients of the merit function are computed via a single adjoint analysis, irrespective of the number of measurements and the number of parameters of the optimization. this procedure requires close integration between the nonlinear optimization software and the circuit simulation program. the adjoint lagrangian formulation has been implemented in the jiffytune tool which optimizes delay, area, slew (transition time) and power measurements by adjusting transistor widths and wire sizes. speedups of over 35x have been realized in the gradient computation procedure by using the adjoint lagrangian formulation, leading to speedups of up to 2.5x in the overall optimization procedure. perhaps more importantly, these speedups have rendered feasible the tuning of large circuits. a circuit with 6,900 transistors was optimized in under two hours of cpu time.
automatic netlist extraction for measurement-based characterization of off-chip interconnect. an approach is presented for modeling board level, package-level, and mcm substrate-level interconnect circuitry based an measured time domain refectometry data. the time-domain scattering parameters of a multiport system are used to extract a spice netlist which uses standard elements to match the behavior of the device up to a user-specified cutoff frequency. linear or nonlinear circuits may be connected to the model ports, and the entire circuit simulated in a standard circuit simulator. two-port and four-port example microstrip circuits are characterized, and the simulation results are compared with measured data. delay, reflection transmission, and crosstalk are accurately modeled in each case.
synthesis of asynchronous control circuits with automatically generated relative timing assumptions. this paper describes a method of synthesis of asynchronous circuits with relative timing. asynchronous communication between gates and modules typically utilizes handshakes to ensure functionality. relative timing assumptions in the form &ldquo;event a occurs before event b&rdquo; can be used to remove redundant handshakes and associated logic. this paper presents a method for automatic generation of relative timing assumptions from the untimed specification. these assumptions can be used for area and delay optimization of the circuit. a set of relative timing constraints sufficient for the correct operation of the circuit is back-annotated to the designer. experimental results for control circuits of a prototype ia32 instruction length decoding and steering unit called rappid (&ldquo;revolving asynchronous pentium&reg; processor instruction decoder&rdquo;) shows significant improvements in area and delay over speed-independent circuits.
decomposition and technology mapping of speed-independent circuits using boolean relations. presents a new technique for the decomposition and technology mapping of speed-independent circuits. an initial circuit implementation is obtained in the form of a netlist of complex gates, which may not be available in the design library. the proposed method iteratively performs boolean decomposition of each such gate f into a two-input combinational or sequential gate g, which is available in the library, and two gates h/sub 1/ and h/sub 2/, which are simpler than f, while preserving the original behavior and speed-independence of the circuit. to extract functions for h/sub 1/ and h/sub 2/, the method uses boolean relations, as opposed to the less powerful algebraic factorization approach used in previous methods. after logic decomposition, overall library matching and optimization is carried out. logic resynthesis, performed after speed-independent signal insertion for h/sub 1/ and h/sub 2/, allows for the sharing of decomposed logic. overall, this method is more general than existing techniques based on restricted decomposition architectures, and thereby leads to better results in technology mapping.
synthesizing petri nets from state-based models. this paper presents a method to synthesize labeled petri nets from state-based models. although state-based models (such as finite state machines) are a powerful formalism to describe the behavior of sequential systems, they cannot explicitly express the notions of concurrency, causality and conflict. petri nets can naturally capture these notions. the proposed method in based on deriving an elementary transition system (ets) from a specification model. previous work has shown that for any ets there exists a petri net with minimum transition count (one transition for each label) with a reachability graph isomorphic to the original ets. this paper presents the first known approach to obtain an ets from a non-elementary ts and derive a place-irredundant petri net. furthermore, by imposing constraints on the synthesis method, different classes of petri nets can be derived from the same reachability graph (pure, free choice, unique choice). this method has been implemented and efficiently applied in different frameworks: petri net composition, synthesis of petri nets from asynchronous circuits, and resynthesis of petri nets.
observability analysis of embedded software for coverage-directed validation. the most common approach to checking correctness of a hardware or software design is to verify that a description of the design has the proper behavior as elicited by a series of input stimuli. in the case of software, the program is simply run with the appropriate inputs, and in the case of hardware, its description written in a hardware description language (hdl) is simulated with the appropriate input vectors. in coverage-directed validation, coverage metrics are defined that quantitatively measure the degree of verification coverage of the design.motivated by recent work on observability-based coverage metrics for models described in a hardware description language, we develop a method that computes an observability-based code coverage metric for embedded software written in a high-level programming language. given a set of input vectors, our metric indicates the instructions that had no effect on the output. an assignment that was not relevant to generate the output value cannot be considered as being covered. results show that our method offers a significantly more accurate assessment of design verification coverage than statement coverage. existing coverage methods for hardware can be used with our method to build a verification methodology for mixed hardware/software or embedded systems.
synthesis of customized loop caches for core-based embedded systems. embedded system programs tend to spend much time in small loops. introducing a very small loop cache into the instruction memory hierarchy has thus been shown to substantially reduce instruction fetch energy. however, loop caches come in many sizes and variations -- using the configuration best on the average may actually result in worsened energy for a specific program. we therefore introduce a loop cache exploration tool that analyzes a particular program's profile, rapidly explores the possible configurations, and generates the configuration with the greatest power savings. we introduce a simulation-based approach and show the good energy savings that a customized loop cache yields. we also introduce a fast estimation-based approach that obtains nearly the same results in seconds rather than tens of minutes or hours.
incremental cad. comprehensive study of incremental algorithms and solutions in the context of cad tool development is an open area of research with a great deal of potential. incremental algorithms for synthesis and layout are needed when design undergoes local or incremental change. often these local changes are made to react to local change in the design, correct local errors or to make local improvements in one or more of the design quality metrics. in this paper we outline fundamental problems in incremental logic synthesis and physical design. preliminary solutions to a subset of these problems will be outlined.
a sum-over-paths impulse-response moment-extraction algorithm for ic-interconnect networks: verification, coupled rc lines. we have created a stochastic impulse-response (ir) moment-extractionalgorithm for rc circuit networks. it employs anewly discovered feynman sum-over-paths postulate. fullparallelism has been preserved. numerical verification resultsfor coupled rc lines confirmed rapid convergence. we believethis algorithm may find useful application in massively coupledelectrical systems, such as those encountered in high-enddigital-ic interconnects.
a high-level design and optimization tool for analog rf receiver front-ends. this paper presents a high-level analysis and optimization tool for the design of analog rf receiver front-ends, which takes all design parameters and all aspects of performance degradation (noise, distortion, self-mixing...) into account. the simulations are performed in the spectral domain with a behavioral model library for the rf building blocks. the tool allows to explore alternative rf receiver topologies as well as to investigate design trade-offs within each topology. by having integrated the performance analysis routine within a simulated annealing optimization loop, the tool can also perform an optimal high-level synthesis of a given topology towards a specific application. it then determines the optimal specifications for the rf building blocks such that the required receiver signal quality is met while the overall power and/or area consumption is minimized.
fault modeling and simulation for crosstalk in system-on-chip interconnects. system-on-chips (socs) using ultra deep sub-micron (dsm) technologies and ghz clock frequencies have been predicted by the 1997 sia road map. recent studies [3,4], as well as experiments reported in this paper, show significant crosstalk effects in long on-chip interconnects of ghz dsm chips. recognizing the importance of high-speed, reliable interconnects in ghz socs, we address in this paper the problem of testing for glitch and delay errors caused by crosstalk in buses and interconnects between components of a soc.since it is not possible to explicitly test for all the possible process variations and defects that can lead to crosstalk errors in soc interconnects, we present an abstract model, maximum aggressor (ma) fault model, and its test requirements. the attractiveness of the model is that it can abstract crosstalk defects in interconnects with a linear number of faults, while the corresponding ma tests provide complete coverage for all physical level defects related to cross-coupling capacitance between the interconnects. a spice-level fault simulation methodology is presented which allows simulation of a small subset of the potentially exponential number of defects. the simulation methodology also enables validation of the proposed fault model and the resulting test set.
simulation-based automatic generation of signomial and posynomial performance models for analog integrated circuit sizing. this paper presents a method to automatically generate posynomial response surface models for the performance parameters of analog integrated circuits. the posynomial models enable the use of efficient geometric programming techniques for circuit sizing and optimization. to avoid manual derivation of approximate symbolic equations and subsequent casting to posynomial format, techniques from design of experiments and response surface modeling in combination with spice simulations are used to generate signomial and posynomial models in an automatic way. attention is paid to estimating the relative 'goodness-of-fit' of the generated models. experimental results allow to assess both the quality of the generated models as well as the strengths and the limitations of the presented approach.
a multiple-dominance switch-level model for simulation of short faults. short faults in cmos networks frequently give rise to intermediate node voltages. an efficient local algorithm is presented for event-driven switch-level simulation of cmos networks in which intermediate signal values are common. the proposed model allows multiple dominant signals associated with the state of a node. the strength of several logical low and high signal contributions can thereby be taken into account when the logic state of a node is computed, which means that intermediate voltages can be handled more accurately. to demonstrate the usefulness of the multiple-dominance model in fault simulations, a new fault simulation algorithm is presented. various common transistor-level fault types were simulated, and the results show that the number of discrepancies from electrical-level simulations is significantly reduced at a low computational cost.
virtual screening: a step towards a sparse partial inductance matrix. we extend the partial inductance concept by replacing the magnetic interaction between open filaments i and j by that between filament j and a (finite) closed loop, formed by connecting the endpoints of a filament pair (i-i&prime;). the secondary filament i' is constructed by radial projection of filament i onto a cylindrical shell around filament j. we show that, although individual partial inductance values are modified, the inductive behaviour of the full circuit is invariant. mutual inductances of distant filaments are particularly reduced, because the far field of a conductor loop falls off much faster than that of a single filament. therefore, it is expected that subsequent removal of such transformed off-diagonal elements from the partial inductance matrix has less effect on the overall inductive properties, so our method provides a tool to enhance robustness under matrix sparsification. we call our method &ldquo;virtual screening&rdquo;, because the screening filaments {i&prime;} are not physically present. symmetry of the inductance matrix is preserved for orthogonal networks only.we also present an extension of our method to a more general class of shells. this allows a detailed comparison of the virtual screening method and the &ldquo;potential shift-truncate method&rdquo;, introduced with spherical equipotential shells [krauter et al. iccad'95] and extended to ellipsoidal equipotential shells recently [beattie et al. iedm'98]. we find strong similarities, but also differences. an interesting result is the fact that the virtual screening method with tubular shells applied to orthogonal networks can be interpreted as a generalization of the potential shift-truncate method to non-equipotential shells, which also implies that preservation of stability is guaranteed.some numerical results, sustaining the ideas behind our method, conclude the paper.
techniques for including dielectrics when extracting passive low-order models of high speed interconnect. interconnect structures including dielectrics can be modeled by an integral equation method using volume currents and surface charges for the conductors, and volume polarization currents and surface charges for the dielectrics. in this paper we describe a mesh analysis approach for computing the discretized currents in both the conductors and the dielectrics. we then show that this fully mesh-based formulation can be cast into a form using provably positive semidefinite matrices, making for easy application of krylovsubspace based model-reduction schemes to generate accurate guaranteed passive reduced-order models. several printed circuit board examples are given to demonstrate the effectiveness of the strategy.
proximity templates for modeling of skin and proximity effects on packages and high frequency interconnect. modeling the exponentially varying current distributions in conductor interiors associated with high frequency interconnect behavior causes a rapid increase in the computation time and memory required even by recently developed fast electromagnetic analysis programs. in this paper we describe a procedure to generate numerically a set of basis functions which efficiently represent conductor current variation, and thus improving solver efficiency. the method is based on solving a sequence of template problems, and is easily generalized to arbitrary conductor cross-sections. results are presented to demonstrate that the numerically computed basis functions are seven to twenty times more efficient than the commonly used piece-wise constant basis functions.
formal verification coverage: computing the coverage gap between temporal specifications. existing methods for formal verification coverage compare a given specification with a given implementation, and evaluate the coverage gap in terms of quantitative metrics. we consider a new problem, namely to compare two formal temporal specifications and to find a set of additional temporal properties that close the coverage gap between the two specifications. in this paper we present: (1) the problem definition and motivation, (2) a methodology for computing the coverage gap between specifications, and (3) a methodology for representing the coverage gap as a collection of temporal properties that preserve the syntactic structure of the target specification.
a unified approach to topology generation and area optimization of general floorplans. in this paper, it is shown that for any rectangularly dualizable graph, a feasible topology can be obtained by using only either straight or z-cutlines recursively within a bounding rectangle. given an adjacency graph, a potential topology, which may be nonslicible and is likely to yield an optimally sized floorplan, is produced first in a top-down fashion using heuristic search in and-or graphs. the advantage of this technique is fourfold : (i) accelerates top-down search phase, (ii) generates a floorplan with minimal number of nonslice cores, (iii) ensures safe routing order without addition of pseudo-modules, and (iv) solves the bottom-up algorithm efficiently for optimal sizing of general floorplans in the second phase.
variability inspired implementation selection problem. given a directed acyclic graph and different possible implementations for each node, the implementation selection problem (isp) selects the appropriate implementation for each node such that a given global design objective is optimized, isp is a generic formulation that is explicitly or implicitly solved in several design automation problems like leakage optimization using dual v/sub th/, gate sizing, etc. an implementation of a node results in an associated delay and perhaps cost for the node. in the presence of different sources of uncertainty and fabrication variability, fixed estimates of delays and costs of a node are extremely erroneous. we investigate a probabilistic approach to solve isp by considering probability density functions for delays and costs of a node. we propose a dynamic-programming based approach in a probabilistic sense and introduce effective pruning criteria when dealing with probability distributions for identifying co-optimal solution at each stage. a case study of leakage optimization using dual v/sub th/ is presented where we show the effectiveness of a probabilistic approach considering v/sub th/ variability over a traditional deterministic one.
hybrid cmos/nanoelectronic digital circuits: devices, architectures, and design automation. physics offers several active devices with nanometer-scale footprint, that can be best used in combination with a cmos subsystem. such hybrid circuits offer the potential for high defect tolerance combined with unparalleled performance. in this tutorial, we highlight key issues and architectural alternatives for this promising technology and outline the challenges posed by the hybrid circuits pose for design automation.
propersyn: a portable parallel algorithm for logic synthesis. an algorithm based on the transduction method and implemented in the propercad environment is described. the parallel propersyn algorithm attempts to make the execution time manageably small. the algorithm uses an asynchronous message driven computing model with no synchronizing barriers, and hence it is scalable to a larger number of processors. also, the algorithm is portable across a wide variety parallel machines. experimental results on various parallel machines are presented. the algorithm is built around a well-defined sequential algorithm interface such that there can be benefits from future expansion of the sequential algorithm
efficient circuit partitioning to extend cycle simulation beyond synchronous circuits. cycle simulation techniques, such as levelized compiled code, can ordinarily be applied only to synchronous designs. they usually cannot be applied to designs containing circuit features like combinational paths, multiple clock domains, generated clocks, asynchronous resets, and transparent latches. this paper presents a novel partitioning algorithm that partitions a non-cycle-simulatable circuit containing these features into sub-circuits that can be cycle simulated. cycle simulation techniques can be applied to the individual sub-circuits, and the whole collection of sub-circuits can be simulated together using conventional co-simulation techniques. empirical results demonstrate that this approach brings the benefits of cycle simulation to circuits that were previously impossible to cycle simulate. the partitioning algorithm requires time and space linear in the size of the circuit, and in practice is very fast. we also discuss how the key ideas presented here can be applied to accelerate hdl simulation.
noise analysis for optical fiber communication systems. the optical fiber transmission links form the backbone of the communicationsinfrastructure. almost all of voice and data (internet) traffic is routed throughterrestrial and submarine optical fiber links, connecting the world together. invention of the optical amplifiers (oas) and wavelength-division multiplexing(wdm) technology enabled very high capacity optical fiber communicationlinks that run for thousands of kilometers without any electronic repeaters, butat the same time brought many design challenges. as electronic amplifiers do,oas add noise to the signal they amplify. in the design of an optical fibercommunication link, the prediction of the deterioration the information signalsexperience due to the nonlinearity of the optical fiber and the optical noise generated by the oas is essential. in this paper, we first present a short overviewof optical fiber communication systems and the challenges that faces one froma modeling, analysis and design perspective. then, we describe novel formulations and computational techniques for the analysis of the interplay between theinformation signals and the optical noise due to the fiber nonlinearity as theypropagate together along the fiber link. our formulations are similar, in spirit,to the linear(ized), time-varying formulations for noise analysis in analog/rfelectronic circuits. we then investigate signal-noise mixing due to optical fibernonlinearities using the techniques developed. finally, we discuss the use ofthe generated results in the performance evaluation of communication links,and comment on system design implications.
modelling and analysis of communication circuit performance using markov chains and efficient graph representations. in high-speed data networks, the bit-error-rate specification on the system can be very stringent, i.e., 10-14. at such error rates, it is not feasible to evaluate the performance of a design using straightforward, simulation based, approaches. nevertheless performance prediction before actual hardware is built is essential for the design process.this work introduces a stochastic model and an analysis-based, non-monte-carlo method for performance evaluation of digital data communication circuits. the analyzed circuit is modeled by a number of interacting finite state machines with inputs described as functions on a markov chain state-space. the composition of these elements results in a typically very large markov chain. system performance measures, such as probability of bit errors and rate of synchronization loss, can be evaluated by solving linear problems involving the large markov chain's transition probability matrix. this paper first describes a dedicated multi-grid method used to solve these very large linear problems. the principal bottleneck in such an approach is the size of the markov chain state-space, which grows exponentially with system complexity. the second part of this paper introduces a novel, graph based, data structure capable of efficiently storing and manipulating transition probability matrices for several million state markov chains. the methods are illustrated on a real industrial clock-recovery circuit design.
modeling and simulation of the interference due to digital switching in mixed-signal ics. the paper introduces a methodology for the evaluation of the interference noise, caused by digital switching activity, in sensitive circuits of a mixed-digital-analog chip. the digital switching activity is modeled stochastically as functions defined on markov chains. the actual interference signal is obtained through the modulation of this discrete stochastic signal with real current injection patterns stored a priori in a pre-characterized library. the interference noise results from the propagations of these continuous stochastic signals through the linear network that models the chip power grid, substrate and relevant package parasitics. the interference noise power spectral density is computed by linear frequency-domain analysis. the methodology is implemented using advanced numerical techniques capable of tackling very large problems.
computing phase noise eigenfunctions directly from steady-state jacobian matrices. the main effort in oscillator phase noise calculation lies in computing a vector function called the perturbation projection vector (ppv). current techniques for ppv calculation use time domain numerics to generate the system's monodromy matrix, followed by full or partial eigenanalysis. we present a superior method that finds the ppv using only a single linear solution of the oscillator's time- or frequency-domain steady-state jacobian matrix. the new method is better suited for existing tools with fast harmonic balance or shooting capabilities, and also more accurate than explicit eigenanalysis. a key advantage is that it dispenses with the need to select the correct one-eigenfunction from amongst a potentially large set of choices, an issue that explicit eigencalculation based methods have to face.
time-domain non-monte carlo noise simulation for nonlinear dynamic circuits with arbitrary excitations. a new, time-domain, non-monte carlo method for computer simulation of electrical noise in nonlinear dynamic circuits with arbitrary excitations is presented. this time-domain noise simulation method is based on the results from the theory of stochastic differential equations. the noise simulation method is general in the sense that any nonlinear dynamic circuit with any kind of excitation, which can be simulated by the transient analysis routine in a circuit simulator, can simulated by our noise simulator in time-domain to produce the noise variances and covariances of circuit variables as a function of time, provided that noise models for the devices in the circuit are available. noise correlations between circuit variables at different time points can also be calculated. previous work on computer simulation of noise in integrated circuits is reviewed with comparisons to our method. shot, thermal and flicker noise models for integrated-circuit devices, in the context of our time-domain noise simulation method, are described. the implementation of this noise simulation method in a circuit simulator (spice) is described. two examples of noise simulation (a cmos ring-oscillator and a bjt active mixer) are given.
buffer insertion under process variations for delay minimization. this paper considers the buffer insertion problem under process variations. with continued technology scaling, it is necessary to model the physical parameters to be random variables. one approach to the buffer insertion problem under variations is to use the mean values of these parameters and solve the problem using traditional buffer insertion techniques for delay minimization. another approach is to find a buffer insertion solution using a new method that can handle the probability distributions. thus, the performance can be optimized with some yield constraint. in this paper, we present both analytical and experimental results to show that the two approaches give almost identical solutions. in other words, the more expensive statistical methods are not needed for the buffer insertion in delay minimization problem.
an observability-based code coverage metric for functional simulation. functional simulation is the most widely used method for design verification. at various levels of abstraction, e.g., behavioral, register-transfer level and gate level, the designer simulates the design using a large number of vectors attempting to debug and verify the design. a major problem with functional simulation is the lack of good metrics and tools to evaluate the quality of a set of functional vectors. metrics used currently are based on instruction counts and are quite simplistic. designers are forced to use ad-hoc methods to terminate functional simulation, e.g. cpu time limitations. we propose a new metric for measuring the extent of design verification provided by a set of functional simulation vectors. this metric is universal, and can be used uniformly for all designs. our metric computes observability information to determine whether effects of errors that are activated by the program stimuli can be observed at the circuit outputs. we provide preliminary experimental evidence that supports the validity of the proposed metric. we believe that using this metric in design verification will result in higher-quality functional checking. tests and improved correctness
verification of asynchronous interface circuits with bounded wire delays. the problem of verifying that the gate-level implementation of an asynchronous circuit, with given or extracted bounds on wire and gate delays, is equivalent to a specification of the asynchronous circuit behavior described as a classical flow table, under the fundamental mode of operation, is considered. a procedure for extracting the complete set of possible flow tables from a gate-level description of an asynchronous circuit under the bounded wire delay model is given. given an extracted flow table and the initial flow table specification, procedures for constructing a product flow table so as to check for machine equivalence are discussed
analytical fault modeling and static test generation for analog ics. static tests are key in reducing the current high cost of testing analog and mixed-signal ics. a new dc test generation technique for detecting catastrophic failures in this class of circuits is presented. to include the effect of tolerance of parameters during testing, the test generation problem is formulated as a minimax optimization problem, and solved iteratively as successive linear programming problems. an analytical fault modeling technique, based on manufacturing defect statistics is used to derive the fault list for the test generation. using the technique presented here an efficient static test set for analog and mixed-signal ics can be constructed, reducing both the test time and the packaging cost.
dynamic test signal design for analog ics. in this paper we present an approach to construct dynamic test signals for analog circuits. using the integral measure for characterizing time-domain signals, we extend the minmax formulation of the static test problem to the dynamic case. a sub-optimal solution strategy, similar to dynamic programming methods is used to construct the test waveforms. the approach presented here may be used to construct input signals for an on-chip test scheme or for the selection of an external stimulus applied through an arbitrary waveform generator.
efficient and accurate transient simulation in charge-voltage plane. transient simulation has traditionally been performed in current- voltage plane (with current and voltage as variables) for verification of integrated circuits and systems. this paper introduces techniques for efficient and accurate transient simulation in charge-voltage plane (with charge and voltage as variables). for integrated circuits, both simulation cost and overhead to increase accuracy are drastically reduced by performing simulations in charge-voltage plane. adaptively controlled explicit simulation in charge-voltage plane is used to demonstrate the feasibility of the approach. solution of circuit equations in charge-voltage plane is 10-20 times more efficient than in current-voltage plane. furthermore, simulation accuracy can be increased at an incremental cost. as a result, aces in charge-voltage plane provides speedups of 300x-5000x or more over traditional circuit simulators with little or no loss in circuit timing accuracy.
efficient coupled noise estimation for on-chip interconnects. noise analysis and avoidance is an increasingly critical step in deep submicron design. ever increasing requirements on performance have led to widespread use of dynamic logic circuit families and its other derivatives. these aggressive circuit families trade off noise margin for timing performance making them more susceptible to noise failure and increasing the need for noise analysis. currently, noise analysis is performed either through circuit or timing simulation or through model order reduction. these techniques in use are still inefficient for analyzing massive amount of interconnect data found in present day integrated circuits. this paper presents efficient techniques for estimation of coupled noise in on-chip interconnects. this noise estimation metric is an upper bound for rc circuits, being similar in spirit to elmore delay in timing analysis. such an efficient noise metric is especially useful for noise criticality pruning and physical design based noise avoidance techniques.
how to efficiently capture on-chip inductance effects: introducing a new circuit element k. on-chip inductance extraction and analysis is becoming increasing critical. inductance extraction can be difficult, cumbersome and impractical on large designs as inductance depends on the current return path -- which is typically unknown prior to extracting and simulating the circuit model. in this paper, we propose a new circuit element, k, to model inductance effects, at the same time being easier to extract and analyze. k is defined as inverse of partial inductance matrix l, and has locality and sparsity normally associated with a capacitance matrix. we propose to capture inductance effects by directly extracting and simulating k, instead of partial inductance, leading to much more efficient procedure which is amenable to full chip extraction. this proposed approach has been verified through several simulation results.
block-based static timing analysis with uncertainty. static timing analysis is a critical step in design of any digitalintegrated circuit. technology and design trends have ledto significant increase in environmental and process variationswhich need to be incorporated in static timing analysis.this paper presents a new, efficient and accurate block-basedstatic timing analysis technique considering uncertainty.this new method is more efficient as its modelsarrival times as cumulative density functions (cdfs) anddelays as probability functions (pdfs). computationallysimple expression are presented for basic static timing operations.the techniques are valid for any form of the probabilitydistribution, though the use piecewise linear modelingof cdfs is highlighted in this paper. reconvergent fanoutsare handled using a new technique that avoids path tracing.variable accuracy timing analysis can be performed byvarying the modeling accuracy of the piecewise linearmodel. regular and statistical timing on different parts ofthe circuit can be incorporated into a single timing analysisrun. accuracy and efficiency of the proposed method is demonstratedfor various iscas benchmark circuits.
realizable reduction for rc interconnect circuits. interconnect reduction is an important step in the design and analysis of complex interconnects found in present-day integrated circuits. this paper presents techniques for obtaining realizable and accurate reduced models for two-port and multi-port rc circuits. the proposed method is also particularly suitable for interconnect reduction for nonlinear circuit simulation and for interconnect post-processing in a parasitic extractor. the method has two limitations. first, it only considers the first few moments of the transfer function; however, that is accurate enough for rc circuits. second, the amount of interconnect reduction is topology dependent. although, most on-chip interconnect topologies are well suited for the method proposed. accuracy and efficiency of the proposed method is demonstrated for various realistic examples.
performance analysis of a system of communicating processes. efficient exploration of the system design space necessitates fast and accurate performance estimation as opposed to the computationally prohibitive alternative of exhaustive simulation. the paper addresses the issue of worst case performance analysis of a system described as a set of concurrent communicating processes. we show that the synchronization overhead associated with inter process communication can contribute significantly to the overall system performance. application of existing performance analysis techniques, which target single process descriptions, lead to inaccurate performance estimates as the synchronization overhead is not accounted for. we present perc, a fast and accurate worst case performance analysis technique which analyzes inter process communication, and accounts for synchronization overhead while computing the worst case performance estimate of a given system implementation. application of perc to example systems described as multiple communicating processes shows the ability of the proposed method to accurately estimate the worst case performance of the system implementation.
a controller-based design-for-testability technique for controller-data path circuits. this paper investigates the effect of the controller on the testability of sequential circuits composed of controllers and data paths. it is shown that even when both the controller and the data path parts are individually 100\% testable, the composite circuit may not be easily testable by gate-level sequential atpg. analysis shows that a primary problem in test pattern generation of combined controller-data path circuits is the correlation of control signals due to implications imposed by the controller specification. a design-for-testability technique is developed to re-design the controller such that the implications which may produce conflicts during test pattern generation are eliminated. the dft technique involves adding extra control vectors to the controller. experimental results show the ability of the controller dft technique to produce highly testable controller-data path circuits, with nominal hardware overhead.
non-scan design-for-testability of rt-level data paths. this paper presents a non-scan design-for-testability technique applicable to register-transfer (rt) level data path circuits, which are usually very hard-to-test due to the presence of complex loop structures. we develop a new testability measure, and utilize the rt-level structure of the data path, for cost-effective re-design of the circuit to make it easily testable, without having to either scan any flip-flop or breakloops directly. the non-scan dft technique was applied to several data path circuits. experimental results demonstrate the feasibility of producing non-scan testable data paths, which can be tested at-speed. the hardware overhead and the test application time required for the non-scan designs is significantly lower than the corresponding partial scan designs.
performance optimization of sequential circuits by eliminating retiming bottlenecks. a method to improve the effectiveness of retiming by transforming the sequential circuit is proposed. bottlenecks which prevent retiming to achieve a desired clock period are identified. conditions to eliminate the retiming bottlenecks are derived. these conditions are satisfied by a process of identifying subcircuits and satisfying a set of timing constraints on the subcircuits. the transformed circuit, which satisfies the timing constraints, can be retimed to achieve the desired clock period. if the original circuit has its initial state specified, the method always generates the final circuit with an equivalent initial state. experimental results on a variety of sequential benchmark circuits demonstrate significant performance improvement
fast timing simulation of transient faults in digital circuits. transient fault simulation is an important verification activity for circuits used in critical applications since such faults account for over 80% of all system failures. this paper presents a timing level transient fault simulator that bridges the gap between electrical and gate-level transient fault simulators. a generic mos circuit primitive and analytical solutions of node differential equations are used to perform transistor level simulation with accurate mos-fet models. the transient fault is modeled by a piecewise quadratic injected current waveform; this retains the electrical nature of the transient fault and provides spice-like accuracy. detailed comparisons with spice3 show the accuracy of this technique and speedups of two orders of magnitude are observed for circuits containing up to 2000 transistors. latched error distributions of the benchmark circuits are also provided.
fast and accurate timing simulation with regionwise quadratic models of mos i-v characteristics. this paper presents a technique called regionwise quadratic (rwq) modeling that allows highly accurate mos models, as well as measured i-v data, to be used in fast timing simulation. this technique significantly increases the accuracy of fast timing simulation while maintaining efficiency by permitting analytical solutions of node equations. a fast timing simulator using these rwq models has been implemented. several examples of rwq modeling are provided, and comparisons of simulation results with spice3 are shown to demonstrate accuracy and efficiency. speedups of two to three orders of magnitude for circuits containing up to 2000 transistors are observed.
algorithm for achieving minimum energy consumption in cmos circuits using multiple supply and threshold voltages at the module level. this paper proposes an optimum methodology forassigning supply and threshold voltages to modules in a cmoscircuit such that the overall energy consumption is minimizedfor a given delay constraint. the modules of the circuit shouldhave large enough gate depths such that the delay and energypenalties of the level shifters connecting them are negligible.both static and dynamic energy are considered in theoptimization. energy savings of up to 48% have been achievedon various example circuits. the first step in the optimizationfinds optimum supply and threshold voltages for each modulein the circuit. if the circuit has a large number of modules, thisstep might yield a correspondingly large number of differentsupply and threshold voltages for minimum energyconsumption. since having a large number of different supplyand threshold voltages on an ic is not feasible in currenttechnologies, an additional step clusters the multiple voltagesobtained from the first step into a fixed number of supply andthreshold voltages (for example, 2 different supply voltagesand 2 different threshold voltages). in addition to theapplication of this method to circuit optimization, it can also beapplied to a wide range of problems with delay constraints,such as software tasks running on a dynamically variable v{dd}and v{th} processor.
mogac: a multiobjective genetic algorithm for the co-synthesis of hardware-software embedded systems. in this paper, we present a hardware-software co-synthesis system, called mogac, that partitions and schedules embedded system specifications consisting of multiple periodic task graphs. mogac synthesizes real-time heterogeneous distributed architectures using an adaptive multiobjective genetic algorithm that can escape local minima. price and power consumption are optimized while hard real-time constraints are met. mogac places no limit on the number of hardware or software processing elements in the architectures it synthesizes. our general model for bus and point-to-point communication links allows a number of link types to be used in an architecture. application-specific integrated circuits consisting of multiple processing elements are modeled. heuristics are used to tackle multi-rate systems, as well as systems containing task graphs whose hyperperiods are large relative to their periods. the application of a multiobjective optimization strategy allows a single co-synthesis run to produce multiple designs which trade off different architectural features. experimental results indicate that mogac has advantages over previous work in terms of solution quality and running time.
efficient crosstalk noise modeling using aggressor and tree reductions. this paper describes a fast method to estimate crosstalk noise in the presence of multiple aggressor nets for use in physical design automation tools. since noise estimation is often part of the innerloop of optimization algorithms, very efficient closed-form solutions are needed. previous approaches have typically used simple lumped 3--4 node circuit templates. one aggressor net is modeled at a time assuming that the coupling capacitances to all quiet aggressor nets are grounded. they also model the load from interconnect branches as a lumped capacitor and use a dominant pole approximation to solve the template circuit. while these approximations allow for very fast analysis, they result in significant underestimation of the noise. in this paper, we propose a new and more comprehensive fast noise estimation model. we use a 6 node template circuit and propose a novel reduction technique for modeling quiet aggressor nets based on the concept of coupling point admittance. we also propose a reduction method to replace tree branches with effective capacitors which models the effect of resistive shielding. finally, we propose a new double pole approach to solve the template circuit. we tested the proposed method on noiseprone interconnects from an industrial high performance processor. our results show a worst-case error of 7.8% and an average error of 2.7%, while allowing for very fast analysis.
stratified random sampling for power estimation. in this paper, we propose a statistical power evaluation framework at the rt-level. we first discuss the power macro-modeling formulation, and then propose a simple random sampling technique to alleviate the the overhead of macro-modeling during rtl simulation. next, we describe a regression estimator to reduce the error of the macro-modeling approach. experimental results indicate that the execution time of the simple random sampling combined with power macro-modeling is 50 x lower than that of conventional macro-modeling while the percentage error of regression estimation combined with power macro-modeling is 16 x lower than that of conventional macro-modeling. hence, we provide the designer with options to either improve the accuracy or the execution time when using power macro-modeling in the context of rtl simulation.
accurate net models for placement improvement by network flow methods. an efficient iterative improvement procedure for row based cell placement is described. special emphasis is placed on the objective function used to model net lengths. it is shown that minimizing the net length estimated with the net model also minimizes the half perimeter of a rectangle enclosing all pins of a net. contrary to the half perimeter the new objective function permits computation of costs for assigning cells to locations independently for all cells to be placed simultaneously. this provides the algorithm an important advantage compared to other iterative improvement techniques: many cells can be placed simultaneously by formulating placement as a network flow problem. the algorithm is superior to timber-wolfsc 5.4, which minimizes the half perimeter
provably good global buffering using an available buffer block plan. to implement high-performance global interconnect without impacting the performance of existing blocks, the use of buffer blocks is increasingly popular in structured-custom and block-based asic/soc methodologies. recent works by cong et al. [6] and tang and wong [25] give algorithms to solve the buffer block planning problem. in this paper we address the problem of how to perform buffering of global nets given an existing buffer block plan. assuming as in [6, 25] that global nets have been already decomposed into two-pin connections, we give a provably good algorithm based on a recent approach of garg and k&ouml;nemann [8] and fleischer [7]. our method routes connections using available buffer blocks, such that required upper and lower bounds on buffer intervals -- as well as wirelength upper bounds per connection -- are satisfied. unlike [6, 25], our model allows more than one buffer to be inserted into any given connection. in addition, our algorithm observes buffer parity constraints, i.e., it will choose to use an inverter or a buffer (= co-located pair of inverters) according to source and destination signal parity. the algorithm outperforms previous approaches [6] and has been validated on top-level layouts extracted from a recent high-end microprocessor design.
latency-guided on-chip bus network design. deep submicron technology scaling has two major ramifications on the design process. first, reduced feature size significantly increases wire delay, thus resulting in critical paths being dominated by global interconnect rather than gate delays. second, ultra high level of integration mandates design of systems-on-chip that encompass numerous intra-synchronous blocks with decreased functional granularity and increased communication demands. to address these issues we have developed an on-chip bus network design methodology and corresponding set of tools which, for the first time, close the synthesis loop between system and physical design. the approach has three components: a communication profiler, a bus network designer, and a fast approximate floorplanner. the communication profiler collects run-time information about the traffic between system cores. the bus network design component optimizes the bus network structure by coordinating information from the other two components. the floorplanner aims at creating a feasible floorplan and to communicate information about the most constrained parts of the network.
frequency domain simulation of high-q oscillators with homotopy methods. an algorithm for the robust and efficient simulation of high-q oscillators using the harmonic balance method is presented. globally convergent homotopy methods are combined with the harmonic balance method for high-q oscillator simulation. various homotopy options are evaluated leading to an algorithm that is applicable to a wide variety of oscillator circuits.
kauffman networks: analysis and applications. a kauffman network is an abstract model of gene regulatory networks. each gene is represented by a vertex. an edge from one vertex to another implies that the former gene regulates the latter. statistical features of kauffman networks match the characteristics of living cells. the number of cycles in the network's state space, called attractors, corresponds to the number of different cell types. the attractor's length corresponds to the cell cycle time. the sensitivity of attractors to different kinds of disturbances, modeled by changing a network connection, the state of a vertex, or the associated function, reflects the stability of the cell to damage, mutations and virus attacks. in order to evaluate attractors, their number and lengths have to be computed. this problem is the major open problem related to kauffman networks. available algorithms can only handle networks with less than a hundred vertices. the number of genes in a cell is often larger. in this paper, we present a set of efficient algorithms for computing attractors in large kauffman networks. the resulting software package is hoped to be of assistance in understanding the principles of gene interactions and discovering a computing scheme operating on these principles.
guiding cnf-sat search via efficient constraint partitioning. contemporary techniques to identify a good variable order for sat rely on identifying minimum tree-width decompositions. however, the problem of finding a minimal width tree decomposition for an arbitrary graph is np complete. the available tools and methods are impractical, as they cannot handle large and hard-to-solve cnf-sat instances. this work proposes a hypergraph partitioning based constraint decomposition technique as an alternative to contemporary methods. we model the cnf-sat problem on a hypergraph and apply min-cut based bi-partitioning. clause-variable statistics across the partitions are analyzed to further decompose the problem, iteratively. the resulting tree-like decomposition provides a variable order for guiding cnf-sat search. experiments demonstrate that our partitioning procedure is fast, scalable and the derived variable order results in significant increase in performance of the sat engine.
vlsi circuit partitioning by cluster-removal using iterative improvement techniques. move-based iterative improvement partitioning methods such as the fiduccia-mattheyses (fm) algorithm and krishnamurthy's look-ahead (la) algorithm are widely used in vlsi cad applications largely due to their time efficiency and ease of implementation. this class of algorithms is of the "local improvement" type. they generate relatively high quality results for small and medium size circuits. however, as vlsi circuits become larger, these algorithms are not so effective on them as direct partitioning tools. we propose new iterative-improvement methods that select cells to move with a view to moving clusters that straddle the two subsets of a partition into one of the subsets. the new algorithms significantly improve partition quality while preserving the advantage of time efficiency. experimental results on 25 medium to large size acm/sigda benchmark circuits show up to 70% improvement over fm in cutsize, with an average of per-circuit percent improvements of about 25%, and a total cut improvement of about 35%. they also outperform the recent placement-based partitioning tool paraboli and the spectral partitioner melo by about 17% and 23%, respectively, with less cpu time. this demonstrates the potential of iterative improvement algorithms in dealing with the increasing complexity of modern vlsi circuitry.
efficient incremental rerouting for fault reconfiguration in field programmable gate arrays. the ability to reconfigure around manufacturing defects and operational faults increases fpga chip yield, reduces system downtime and maintenance in field operation, and increases reliabilities of mission- and life-critical systems. the fault reconfiguration technique discussed in this work use the principle of node covering in which reconfiguration is achieved by constructing replacement chains of cells from faulty cells to spare/unused ones. a key issue in such reconfiguration is efficient incremental rerouting in the fpga. previous methods for node-covering based reconfiguration are &ldquo;static&rdquo; in the sense that extra interconnects are added a-priori as part of the initial circuit routing so that a specific fault pattern (e.g., one fault per row) can be tolerated [1]. this, however, results in worst-case track overheads and also in an inflexibility to tolerate other realistic fault patterns. in this paper, we develop dynamic reconfiguration and incremental rerouting techniques that are fault specific. in this approach, the fpga is initially routed without any extra interconnects for reconfiguration. when faults occur, the routed nets have to be minimally perturbed to allow these interconnects to be inserted &ldquo;on-the-fly&rdquo; for reconfiguration. these requirements are addressed in our minimally incremental rerouting technique conv_t-dag, which uses a cost-directed depth-first search strategy. we prove several results that establishes the near-optimality of conv_t-dag in terms of track overhead. to the best of our knowledge, this is the first time that an incremental rerouting technique has been developed for fpgas. for several benchmark circuits, the static approach to tolerating one fault per row resulted in a 43% to 34% track overhead. using the dynamic reconfiguration approach and conv_t-dag results in an average overhead of only 16%&mdash;an improvement of more than 50%. over all circuits, the reconfiguration time per fault ranges from 16.8 to 72.9 secs. simulation of smaller fault sets of one to four faults show very small track overheads ranging from 1.75% to 4.49%. conv_t-dag can also be used for interconnect fault tolerance.
partitioning around roadblocks: tackling constraints with intermediate relaxations. constraint satisfaction during partitioning and placement of vlsi circuits is an important problem, and effective techniques to address it lead to high-quality physical design solutions. this problem has, however, been cursorily treated in previous partitioning and placement research. our work presented here addresses the balance-ratio constraint, and is a crucial first step to an effective solution to the general constraint-satisfaction problem. in current iterative-improvement mincut partitioners, the balance-ratio constraint is tackled by disallowing moves that violate it. these methods can lead to sub-optimal solutions since the process is biased against the movement of large cells and clusters of cells. we present techniques for an informed relaxation process that attempts to estimate whether relaxing the constraint temporarily will ultimately benefit the mincut objective. if so, then a violating move is allowed, otherwise it is disallowed. the violations are corrected in future moves so that the final solution satisfies the given constraint. on a set of acm/sigda proud benchmark circuits with actual cell sizes, we obtained up to 38% and an average of 14.5% better cutsizes with as little as 13% time overhead using our techniques compared to the standard method of not allowing any relaxation.
system software techniques for low-power operation in wireless sensor networks. the operation of wireless sensor networks is fundamentally constrained by available energy sources. the underlying hardware determines the power draw of each possible mode of operation. system software attempts maximize the use of the lowest possible modes of each of the subsystems. this tutorial paper describes the system software techniques used at several levels. at the application sensing level, this includes duty-cycling, sensor hierarchy, and aggregation. at the communication level, it includes low-power listening, communication scheduling, piggybacking, post-hoc synchronization, and power-aware routing. at the node os level, it includes event driven execution with split-phase operation and cooperative power management interfaces. at the lowest level, it includes management of primary and secondary energy storage devices coupled with intelligent charge transfer scheduling. all of these aspects must be integrated in a systematic software framework.
computer-aided design for dna self-assembly: process and applications. cad plays a fundamental role in both top-down and bottom-up system fabrication. this paper presents a bottom-up circuit patterning process based on dna self-assembly. the process is described in terms of the design tool requirements and the new opportunities that self-assembly creates for circuit designers. the paper also connects recent demonstrations of addressable self-assembly to applications in computer architecture and system design.
optimization of hierarchical designs using partitioning and resynthesis. this paper explores the influence of optimization along the boundary between hierarchically described components. a novel technique called repartitioning combines partitioning and sequential resynthesis of the design under various quality measures. it is applied to various digital circuits which consist of a controller and a datapath. the outcome of this effort is a versatile, parametrizable resynthesis tool which preserves this hierarchy. due to the cost measures, an average improvement ranging between 5% and 15% was obtained.
fast transient power and noise estimation for vlsi circuits. today's digital design systems are running out of steam, when it comes to meeting the challenges presented by simultaneous switching, power consumption and reliabilty constraints emerging in vlsi circuits. in this paper a new technique to accurately estimate the transient behavior of large cmos cell-based circuits in a reasonable amount of time is presented. gate-level simulations and a consistent modeling methodology are employed to compute the time-domain waveforms for signal voltages, supply currents, power consumption and &dgr;&igr; noise on power lines. this can be done for circuit blocks and complete designs by our new tool powtim, which adds spice-like capabilities to digital design standards.
an analytical method for finding the maximum crosstalk in lossless-coupled transmission lines. the crosstalk in a system containing n(n&ges;2) lossless microstrip transmission lines is formulated as a linear function in time. the maximum crosstalk is computed by evaluating the crosstalk at certain breakpoints in time. the technique also provides the pattern (rising or falling) of input voltages and their relative delays for which the maximum crosstalk occurs. this pattern is usually determined by the system parameters. since the maximum crosstalk determines the faulty vs fault-free operation, the pattern found could be used for testing integrated logic circuits during the design stage
a block rational arnoldi algorithm for multipoint passive model-order reduction of multiport rlc networks. recent work in the area of model-order reduction for rlc interconnect networks has been focused on building reduced-order models that preserve the circuit-theoretic properties of the network, such as stability, passivity, and synthesizability. passivity is the one circuit-theoretic property that is vital for the successful simulation of a large circuit netlist containing reduced-order models of its interconnect networks. non-passive reduced-order models may lead to instabilities even if they are themselves stable. in this paper, we address the problem of guaranteeing the accuracy and passivity of reduced-order models of multiport rlc networks at any finite number of expansion points. the novel passivity-preserving model-order reduction scheme is a block version of the rational arnoldi algorithm. the scheme reduces to that of the prima algorithm when applied to a single expansion point at zero frequency. although the treatment of this paper is restricted to expansion points that are on the negative real axis, it is shown that the resulting passive reduced-order model is superior in accuracy to the one that would result from expanding the original model around a single point. nyquist plots are used to illustrate both the passivity and the accuracy of the reduced-order models.
a hierarchical decomposition methodology for multistage clock circuits. this paper describes a novel methodology to automate the design of the interconnect distribution for multistage clock circuits. we introduce two key ideas. first, a hierarchical decomposition of the layout divides the problem into a set of local steiner-wired latch clusters (to minimize and balance local capacitance) fed globally by a balanced binary tree (to maximize performance). second, we recast the global clock distribution problem as a simultaneous optimization of clock topology, clock segment routing, wiresizing, and buffering. the hierarchical decomposition reduces the problem complexity and allows use of more aggressive optimization techniques. integration of the geometric and electrical optimizations likewise allows more aggressive performance goals. experiments with an industrial design comprising over 16,000 latches demonstrate the efficiency of the approach: a complete clock distribution solution met a 200mhz cycle time specification with only 310ps of skew, met strict current density constraints, exhibited good delay matching across uniform wire width and device variations, and was completed in under 10 cpu hours.
replication for logic bipartitioning. logic replication, the duplication of logic in order to limit communication between partitions, is an effective part of a complete partitioning solution. in this paper we seek a better understanding of the important issues in logic replication. by developing new optimizations to existing algorithms we are able to significantly improve the quality of these techniques, achieving up to 12.5% better results than the best existing replication techniques. when integrated into our already state-of-the-art partitioner, we improve overall cutsizes by 37.8%, while requiring the duplication of at most 7% of the logic.
embedded program timing analysis based on path clustering and architecture classification. formal program running time verification is an important issue in system design required for performance optimization under "first-time-right" design constraints and for real-time system verification. simulation based approaches or simple instruction counting are not appropriate and risky for more complex architectures in particular with data dependent execution paths. formal analysis techniques have suffered from loose timing bounds leading to significant performance penalties when strictly adhered to. we present an approach which combines simulation and formal techniques in a safe way to improve analysis precision and tighten the timing bounds. using a set of processor parameters, it is adaptable to arbitrary processor architectures. the results show an unprecedented analysis precision allowing to reduce performance overhead for provably correct system or interface timing.
transmission line design of clock trees. we investigate appropriate regimes for transmission line propagation of signals on digital integrated circuits. we start from exact solutions to the transmission line equations proposed by davis and meindl. we make appropriate modifications due to finite rise time. they affect the delay calculation and hypothesis pertaining the constancy of the electromagnetic parameters. we study these effects in detail. to find the domain of physical variables where transmission line behavior is feasible, we pose the problem as a nonlinear minimization problem in a space spanned by two continuous variables, with four parameters. from the resulting solutions and employing monotonicity properties of the functional we extract regimes of validity. these regimes of validity happen to be commensurate with what is reachable and doable with todays leading technologies. we complete this study with a qualitative analysis of driver insertion in the presence of transmission lines. the resulting configurations are suitable for the development of an improved clock design discipline.
attractor-repeller approach for global placement. traditionally, analytic placement used linear or quadratic wirelength objective functions. minimizing either formulation attracts cells sharing common signals (nets) together. the result is a placement with a great deal of overlap among the cells. to reduce cell overlap, the methodology iterates between global optimization and repartitioning of the placement area. in this work, we added new attractive and repulsive forces to the traditional formulation so that overlap among cells is diminished without repartitioning the placement area. the superiority of our approach stems from the fact that our new formulations are convex and no hard constraints are required. a preliminary version of the new placement method is tested using a set of mcnc benchmarks1 and, on average, the new method achieved 3.96% and 7.6% reduction in wirelength and cpu time compared to timberwolf v7.0 in hierarchical mode [10].
a router for symmetrical fpgas based on exact routing density evaluation. this paper presents a new performance and routability driven routing algorithm for symmetrical array based field-programmable gate arrays (fpgas). a key contribution of our work is to overcome one essential limitation of the previous routing algorithms: inaccurate estimations of routing density which were too general for symmetrical fpgas. to this end, we derive an exact routing density calculation that is based on a precise analysis of the structure (switch block) of symmetrical fpgas, and utilize it consistently in global and detailed routings. with an introduction of the proposed accurate routing metrics, we design a new routing algorithm called a cost-effective net-decomposition based routing which is fast, and yet produces remarkable routing results in terms of both routability and path/net delays. we performed an extensive experiment to show the effectiveness of our algorithm based on the proposed cost metrics.
voltage-drop-constrained optimization of power distribution network based on reliable maximum current estimates. the problem of optimum design of tree-shaped power distribution networks with respect to the voltage drop effect is addressed in this paper. an approach for the width adjustment of the power lines supplying the circuit's major functional blocks is formulated, so that the network occupies the minimum possible area under specific voltage drop constraints at all blocks. the optimization approach is based on precise maximum current estimates derived by statistical means from recent advances in the field of extreme value theory. experimental tests include the design of power grid for a choice of different topologies and voltage drop tolerances in a typical benchmark circuit.
binary time-frame expansion. this paper introduces a new method for performing time-frame expansion based on writing the number of time frames in terms of powers of two. in the proposed method, the behavior of a circuit for t time frames, where n 0 ⪣t < n is modeled by unrolling the circuit 20, 21, 22, ..., 2(log n &minus;1) times and combining them. this formulation of the problem makes it possible to prune the search space quickly when the problem is infeasible. to show the advantage of this method, we have used it to model the state justification problem and solve the problem using a sat-solver. experimental results show several orders of magnitude speedup for some non-trivial infeasible problems. furthermore, in most cases the cpu time requirement grows linearly in terms of the number of time frames.
general models for optimum arbitrary-dimension fpga switch box designs. an fpga switch box is said to be hyper-universal if it is routable for all possible surrounding multi-pin net topologies satisfying the routing resource constraints. it is desirable to design hyper-universal switch boxes with the minimum number of switches. a previous work, universal switch module, considered such a design problem concerning 2-pin net routings around a single fpga switch box. however, as most nets are multi-pin nets in practice, it is imperative to study the problem that involves multi-pin nets. in this paper, we provide a new view of global routings and formulate the most general &kappa;-sided switch box design problem into an optimum &kappa;-partite graph design problem. applying a powerful decomposition theorem of global routings, we prove that, for a fixed &kappa;, the number of switches in an optimum &kappa;-sided switch box with w terminals on each side is o (w), by constructing some hyper-universal switch boxes with o(w) switches. furthermore, we obtain optimum, hyper-universal 2-sided and 3-sided switch boxes, and propose hyper-universal 4-sided switch boxes with less than 6.7w switches, which is very close to the lower bound 6w obtained for pure 2-pin net models in [5].
a routing algorithm for flip-chip design. the flip-chip package gives the highest chip density of any packaging method to support the pad-limited application-specific integrated circuit (asic) designs. in this paper, we propose the first router for the flip-chip package in the literature. the router can redistribute nets from wire-bonding pads to bump pads and then route each of them. the router adopts a two-stage technique of global routing followed by detailed routing. in global routing, we use the network flow algorithm to solve the assignment problem from the wire-bonding pads to the bump pads, and then create the global routing path for each net. the detailed routing consists of three stages, cross point assignment, net ordering determination, and track assignment, to complete the routing. experimental results based on seven real designs from the industry demonstrate that the router can reduce the total wirelength by 10.2%, the critical wirelength by 13.4%, and the signal skews by 13.9%, compared with a heuristic algorithm currently used in industry.
fast, accurate static analysis for fixed-point finite-precision effects in dsp designs. translating digital signal processing (dsp) software intoits finite-precision hardware implementation is often a time-consumingtask. we describe a new static analysis techniquethat can accurately analyze finite-precision effects arisingfrom fixed-point implementations of dsp algorithms.the technique is based on recent interval representation methodsfrom affine arithmetic, and the use of new probabilisticbounds. the resulting numerical error estimates are comparableto detailed statistical simulation, but achieve speedupsof four to five orders of magnitude by avoiding actual bit-truesimulation. we show error analysis results on both feedforward and feedback dsp kernels.
simultaneous functional-unit binding and floorplanning. as device feature size decreases, interconnection delay becomes the dominating factor of system performance. thus it is important that accurate physical information is used during high level synthesis. in this paper, we consider the problem of simultaneously performing functional-unit binding and floorplanning. experimental results indicate that our approach to combine binding and floorplanning is superior to the traditional approach of separating the two tasks.
a hierarchical functional structuring and partitioning approach for multiple-fpga implementations. in this paper, we present a new synthesis and partitioning approach for multiple-fpga implementations from register-transfer-level (rtl) netlists. our approach bridges the gap between rtl/logic synthesis and physical partitioning by finely tuning logic implementations suited for multiple-fpga systems. we propose a hierarchical functional structuring and partitioning method which fully exploits the design structural hierarchy by decomposing rtl components into sets of logic sub-functions. this allows the partitioner to place portions of components into fpga partitions. experimental results on a number of benchmarks and industrial designs show that our approach achieves significant improvements in clb and io-pin utilizations of fpgas compared to that produced using a traditional multiple-fpga partitioning method.
hardware/software co-testing of embedded memories in complex socs. a novel approach for testing embedded memories in complexsystems-on-a-chip (socs) is presented. the proposedsolution aims to balance the usage of the existing on-chipresources and dedicated design for test (dft) hardwaresuch that the functional power constraints are not exceededduring test while trading-off the testing time againstdft area and performance overhead. the suitability ofsoftware-centric and hardware-centric approaches for embeddedmemory testing is examined and to combine the advantagesof both directions, a new built-in self-test (bist)-basedmethod, called hardware/software co-testing, is introduced.the proposed solution is programmable, scalableand guarantees low routing overhead.
local search for final placement in vlsi design. a new heuristic is presented for the general cell placement problem where the objective is to minimize total bounding box netlength. the heuristic is based on the guided local search (gls) metaheuristic. gls modifies the objective function in a constructive way to escape local minima. previous attempts to use local search on final (or detailed) placement problems have often failed as the neighborhood quickly becomes too excessive for large circuits. nevertheless, by combining gls with fast local search it is possible to focus the search on appropriate sub-neighborhoods, thus reducing the time complexity considerably.comprehensive computational experiments with the developed algorithm are reported on small, medium and large industrial circuits, and for standard cell and general cell variants of the problem. the experiments demonstrate that the developed algorithm is able to improve the estimated routing length of large-sized general cell layouts with as much as 20 percent.the general nature of the proposed method makes it easy to incorporate other goals, such as routability and timing constraints, into the objective function. current layout algorithms use a feedback approach in which a placement is evaluated by performing (partial) routing and timing analysis; the output of this analysis is then used to construct an improved placement. this iterative nature of the design process calls for placement algorithms that take an existing placement and construct an improved placement that resembles the original one, but in which the information from the routing/timing analysis is taken into account.
system partitioning to maximize sleep time. abstract: partitioning of a system to maximize exploitable sleep time for low-power synthesis is discussed. the motivation is to deactivate the memory refresh circuitry, apply power down or disable the clock signals during the inactive periods of operation of circuit elements, and thus minimize the power consumption. since it is impractical to have a separate set of control signals for each circuit element (otherwise, the control itself would consume a lot of power), it is advisable to partition a circuit based on the activity patterns of its elements so that the partitions can be switched into sleep mode for long periods of time. in this paper, we formulate this partitioning problem and show that it is np-hard. we present geo-part, a geometric partitioning heuristic for this problem. an efficient implementation of geo-part using segment tree data structure is discussed. experimental results are encouraging.
timing uncertainty analysis for time-of-flight systems. time-of-flight synchronization is a new digital design methodology that eliminates all latching devices, allowing higher clock rates than alternative timing schemes. synchronization is accomplished by precisely balancing connection delays. many effective pipeline stages are created by pipelining combinational logic, similar in concept to wave pipelining but differing in several respects. due to the unique flow-through nature of circuits and to the need for pulse-mode operation, time-of-flight design exposes interesting new areas for cad timing analysis. this paper discusses how static propagation delay uncertainty limits the clock period for time-of-flight circuits built with opto-electronic devices. we present algorithms for placing a minimum set of clock gates to restore timing in feedback loops that implement memory and for propagating delay uncertainty through a circuit graph. a mixed integer program determining the minimum feasible clock period subject to pulse width and arrival time constraints is discussed. algorithms are implemented in xhatch, a time-of-flight cad package.
sparse and efficient reduced order modeling of linear subcircuits with large number of terminals. in the process of designing state-of-the art vlsi circuit we often encounter large but highly structured linear subcircuits with large number of terminals. classical examples are power supply networks, clock distribution networks, large data buses, etc. various applications would benefit from efficient high level models of such networks. unfortunately the existing model-order-reduction algorithms are not adapted to handle more than a few tens of terminals. this talk introduces recmor, an algorithm for the computation of reduced order models of structured linear circuits with numerous i/o ports. the algorithm exploits certain regularities of the subcircuit response that are typical in numerous applications of interest. when these regularities are present, the normally dense matrix-transfer function of the subcircuit contains sub-blocks that in some sense are significantly low rank and can be compactly modeled by the recently introduced svdmor algorithm. the new recmor algorithm decomposes the large matrix-transfer function recursively, and applies svdmor compression adaptively to the sub-blocks of the transfer function. the result is a reduced order model that is sparse, efficient, and directly usable as an efficient substitute of the subcircuit in circuit simulations. the method is illustrated on several circuit examples.
automatic differentiation in circuit simulation and device modeling. automatic differentiation as a technique for accurate and reliable computation of partial derivatives in device models used by circuit simulation is introduced. the requirements for derivative computations in several simulation algorithms are reviewed, and two automatic differentiation methods are discussed. the application of automatic differentiation to circuit simulation and device modeling is demonstrated through several circuit analysis examples
computation of circuit waveform envelopes using an efficient, matrix-decomposed harmonic balance algorithm. in this paper we introduce a novel algorithm for numerically computing the "slow" dynamics (envelope) of circuits in which a "fast" varying carrier signal is also present. the algorithm proceeds at the rate of the slow behavior and its computational cost is fairly insensitive to the rate of the fast signals. the envelope computation problem is formulated as a differential-algebraic system of equations (daes) in terms of frequency-domain quantities (e.g. amplitudes and phases) that capture the fast varying behavior of the circuit. the solution of this dae represents the "slow" variation of these quantities, i.e., the envelope. the efficiency of this method is the result of using the most appropriate method for each of the circuit modes: harmonic balance for the fast behavior and time-domain integration of daes for the slow behavior. the paper describes the theoretical foundations of the algorithm and presents several circuit analysis examples.
measurement and modeling of mos transistor current mismatch in analog ic's. this paper presents a new methodology for measuring mos transistor current mismatch and a new transistor current mismatch model. the new methodology is based on extracting the mismatch information from a fully functional circuit rather than on probing individual devices; this extraction leads to more efficient and more accurate mismatch measurement. the new model characterizes the total mismatch as a sum of two components, one systematic and the other random. for our process, we attribute nearly half of the mismatch to the systematic component, which we model as a linear gradient across the die. furthermore, we present a new model for the random component of the mismatch which is 60% more accurate, on average, than existing models.
testing of analog systems using behavioral models and optimal experimental design techniques. this paper describes a new cad algorithm which performs automatic test pattern generation (atpg) for a general class of analog systems, namely those circuits which can be efficiently modeled as an additive combination of user-defined basis functions. the algorithm is based on the statistical technique of i-optimal experimental design, in which test vectors are chosen to be maximally independent so that circuit performance will be characterized as accurately as possible in the presence of measurement noise and model inaccuracies. this technique allows analog systems to be characterized more accurately and more efficiently, thereby significantly reducing system test time and hence total manufacturing cost.
hierarchical statistical characterization of mixed-signal circuits using behavioral modeling. a methodology for hierarchical statistical circuit characterization which does not rely upon circuit-level monte carlo simulation is presented. the methodology uses principal component analysis, response surface methodology, and statistics to directly calculate the statistical distributions of higher-level parameters from the distributions of lower-level parameters. we have used the methodology to characterize a folded cascode operational amplifier and a phase-locked loop. this methodology permits the statistical characterization of large analog and mixed-signal systems, many of which are extremely time-consuming or impossible to characterize using existing methods.
statistical verification of power grids considering process-induced leakage current variations. transistor threshold voltages (v{th}) have been reduced as partof on-going technology scaling. the smaller v{th} values featureincreased variations due to underlying process variations, witha strong within-die component. correspondingly, given the exponential dependence of leakage on v{th}, circuit leakage currentsare increasing significantly and have strong within-die statistical variations.with these leakage currents loading the powergrid, the grid develops correspondingly large statistical voltagedrops. this leakage-induced voltage drop is an unavoidable background level of noise on the grid. any additional non-leakagecurrents due to circuit activity will lead to voltage drop which isto be added to this background noise. we propose a techniquefor checking whether the statistical voltage drop on every node iswithin user-specified bounds, given user-specified statistics of theleakage currents.
an exact algorithm for the maximal sharing of partial terms in multiple constant multiplications. in this paper, we propose an exact algorithm that maximizes the sharing of partial terms in multiple constant multiplication (mcm) operations. we model this problem as a boolean network that covers all possible partial terms which may be used to generate the set of coefficients in the mcm instance. the pis to this network are shifted versions of the mcm input. an and gate represents an adder or a subtracter, i.e., an and gate generates a new partial term. all partial terms that have the same numerical value are ored together. there is a single output which is an /spl and/ over all the coefficients in the mcm. we cast this problem into a 0-1 integer linear programming (ilp) problem by requiring that the output is asserted while minimizing the total number of and gates that evaluate to one. a sat-based solver is used to obtain the exact solution. we argue that for many real problems the size of the problem is within the capabilities of current sat solvers. we present results using binary, csd and msd representations. two main conclusions can be drawn from the results. one is that, in many cases, existing heuristics perform well, computing the best solution, or one close to it. the other is that the flexibility of the msd representation does not have a significant impact in the solution obtained.
global signaling over lossy transmission lines. we describe an interconnect scheme based on lossy transmission lines, compare this scheme with traditional bus based links, and present performance data. unlike some other schemes there is no requirement for up-conversion, equalization, or special metal processing. in preliminary work, we have measured data rates of 14 gbps (limited by test equipment) over a 7.2 mm interconnection, implemented in 0.18 /spl mu/m cmos. for active links signaling over a single serial link, is more power efficient than over traditional parallel buses, does not require repeaters and is less affected by noise and coupling.
a tutorial on logic synthesis for lookup-table based fpgas. discusses combinational logic synthesis for fpgas that use lookup tables (luts). issues that differentiate lut synthesis from conventional logic synthesis are emphasized. the ability of a k-input lut to implement any boolean function of k variables differentiates the synthesis of lut circuits from that for conventional asic technologies. the major different occurs during the technology mapping phase of logic synthesis. for values of k greater than 3, the larger number of functions that can be implemented by a k-input lut makes it impractical to use a conventional library-based technology mapping. however, the completeness of the set of functions that can be implemented by a lut eliminates the need for a library of separate functions. in addition, this completeness can be leveraged to optimize the final circuit
daisy: a simulation-based high-level synthesis tool for delta-sigma modulators. an integrated tool called daisy (delta-sigma analysis and synthesis) is presented for the high-level synthesis of &delta;&sigma; modulators. the approach determines both the optimum modulator topology and the required building block specifications, such that the system specifications -- mainly accuracy and signal bandwidth -- are satisfied at the lowest possible power consumption. a genetic-based differential evolution algorithm is used in combination with a fast dedicated behavioral simulator that includes the major nonidealities of the building blocks to realistically analyze and optimize the modulator performance. experimental results illustrate the effectiveness of the approach. also, an overview of optimized topologies as a function of the modulator specifications for a wide range of values shows the capabilities and performance range covered by the tool.
sprim: structure-preserving reduced-order interconnect macromodeling. in recent years, order-reduction techniques based on krylov subspaces have become the methods of choice for generating macromodels of large multi-port rlc circuits. a widely-used method of this type is prima. its main features are provably passive reduced-order models and a moment-matching property. on the other hand, prima does not preserve other structures, such as reciprocity or the block structure of the circuit matrices, inherent to rlc circuits, which makes it harder to synthesize the prima models as actual circuits. moreover, the prima models match only half as many moments as optimal, but non-passive, moment-matching techniques such as sympvl. in this paper, we propose the reduction technique sprim that overcomes these disadvantages of prima. in particular, sprim generates provably passive and reciprocal macromodels of multi-port rlc circuits, and the sprim models match twice as many moments as the corresponding prima models obtained with identical computational work. numerical results are reported that illustrate the higher accuracy of sprim vs. prima.
efficient small-signal circuit analysis and sensitivity computations with the pvl algorithm. we describe the application of the pvl algorithm to the small-signal analysis of circuits, including sensitivity computations. the pvl algorithm is based on the efficient computation of the pade&acute; approximation of the network transfer function via the lanczos process. the numerical stability of the algorithm permits the accurate computation of the pade&acute; approximation over any given frequency range. we extend the algorithm to compute sensitivities of network transfer functions, their poles, and zeros, with respect to arbitrary circuit parameters, with minimal additional computational cost, and we present numerical examples.
reduced-order modeling of large passive linear circuits by means of the sypvl algorithm. lucent technologiesthis paper discusses the analysis of large linear electrical networks consisting of passive components, such as resistors, capacitors, inductors, and transformers. such networks admit a symmetric formulation of their circuit equations. we introduce sypvl, an efficient and numerically stable algorithm for the computation of reduced-order models of large, linear, passive networks. sypvl represents the specialization of the more general pvl algorithm, to symmetric problems. besides the gain in efficiency over pvl, sypvl also preserves the symmetry of the problem, and, as a consequence, can often guarantee the stability of the resulting reduced-order models. moreover, these reduced-order models can be synthesized as actual physical circuits, thus facilitating compatibility with existing analysis tools. the application of sypvl is illustrated with two interconnect-analysis examples.
symbolic hazard-free minimization and encoding of asynchronous finite state machines. this paper presents an automated method for the synthesis of multiple-input-change (mic) asynchronous state machines. asynchronous state machine design is subtle since, unlike synchronous synthesis, logic must be implemented without hazards, and state codes must be chosen carefully to avoid critical races. we formulate and solve an optimal hazard-free and critical race-free encoding problem for a class of mic asynchronous state machines called burst-mode. analogous to a paradigm successfully used for the optimal encoding of synchronous machines, the problem is formulated as an input encoding problem. implementations are targeted to sum-of-product realizations. we believe this is the first general method for the optimal encoding of hazard-free mic asynchronous state machines under a generalized fundamental mode of operation. results indicate that improved solutions are produced, ranging up to 17% improvement.
optimist: state minimization for optimal 2-level logic implementation. we present a novel method for state minimization of incompletely-specified finite state machines. where classic methods simply minimize the number of states, ours directly addresses the implementation's logic complexity, and produces an exactly optimal implementation under input encoding. the method incorporates optimal ``state mapping'', i.e., the process of reducing the symbolic next-state relation which results from state splitting to an optimal conforming symbolic function. further, it offers a number of convenient sites for applying heuristics to reduce time and space complexity, and is amenable to implementation based on implicit representations. although our method currently makes use of an input encoding model, we believe it can be extended smoothly to encompass output encoding as well.
optimista: state minimization of asynchronous fsms for optimum output logic. the optimal state minimization problem is to select a reduced state machine having the best logic implementation over all possible state reductions and encodings. a recent algorithm, optimist [3], was the first general solution to this problem for synchronous fsms. in this paper, we present the first solution for asynchronous fsms.this paper makes two contributions. first, we introduce optimista, a new algorithm which guarantees optimum 2-level output logic for asynchronous fsms. in asynchronous machines, output logic is often critical: it usually determines the machine latency. the algorithm is formulated as a binate constraint satisfaction problem, which is solved using a binate solver. the second contribution is a novel alternative result: the unreduced machine itself can be used directly to obtain minimum-cardinality output logic.thus, this paper presents two approaches: using optimista, which simultaneously performs state and logic minimization; or using no state reduction (if output logic cardinality is of sole interest). extensions for literal optimization, targetted to multi-level logic, are also proposed.
simultaneous short-path and long-path timing optimization for fpgas. this work presents the routing cost valleys (rcv) algorithm - the first published algorithm that simultaneously optimizes all short- and long-path timing constraints in a field-programmable gate array (fpga). rcv is comprised of a new slack allocation algorithm that produces both minimum and maximum delay budgets for each circuit connection, and a new router that strives to meet and, if possible, surpass these connection delay constraints. rcv achieves excellent results. on a set of 100 large circuits, rcv improves both long-path and short-path timing slack significantly vs. an earlier computer-aided design (cad) system that focuses solely on long-path timing. even with no short-path timing constraints, rcv improves the clock speed of circuits by 3.9% on average. finally, rcv is able to meet timing on all 72 peripheral component interconnect (pci) cores tested, while an earlier algorithm fails to achieve timing on all 72 cores.
model reduction for dc solution of large nonlinear circuits. a new algorithm based on model reduction using krylov subspace technique is proposed to compute the dc solution of large nonlinear circuits. the proposed method combines continuation methods with model reduction techniques. thus it enables the application of the continuation methods to an equivalent reduced-order set of nonlinear equations instead of the original system. this results in a significant reduction in the computational expense as the size of the reduced equations is much less than that of the original system.the reduced order system is obtained by projecting the set of nonlinear equations, whose solution represents the dc operating point, into a subspace of a much lower dimension. it is also shown that the both the reduced-order system and the original system share the first q derivatives w.r.t. the circuit variable used to parameterize the family of the solution trajectories generated by the continuation method.
timing distribution in vhdl behavioral models. a cad tool, timespec, developed for solving the timing distribution problem of allocating realistic delays to the internal primitives (rtl models) of a digital device by using the linear programming approach is described. the inconsistencies in the manufacturer's specifications are also detected and corrected. timespec allows the use of embedded timing in behavioral vhdl models, and thus the end-to-end delays for all paths in the digital device are made available. an interface is provided with an x windows based graphical tool, the modeler's assistant, which allows enumeration of all the input-to-output paths in the device. thus a cad tool is made available to system or chip designers/modelers for building accurate and synthesizable vhdl models
efficient sat-based unbounded symbolic model checking using circuit cofactoring. we describe an efficient approach for sat-based quantifier elimination that significantly improves the performance of pre-image and fixed-point computation in sat-based unbounded symbolic model checking (umc). the proposed method captures a larger set of new states per sat-based enumeration step during quantifier elimination, in comparison to previous approaches. the novelty of our approach is in the use of circuit-based cofactoring to capture a large set of states, and in the use of a functional hashing based simplified circuit graph to represent the captured states. we also propose a number of heuristics to further enlarge the state set represented per enumeration, thereby reducing the number of enumeration steps. we have implemented our techniques in a sat-based umc framework where we show the effectiveness of sat-based existential quantification on public benchmarks, and on a number of large industry designs that were hard to model check using purely bdd-based techniques. we show several orders of improvement in time and space using our approach over previous cnf-based approaches. we also present controlled experiments to demonstrate the role of several heuristics proposed in the paper. importantly, we were able to prove using our method the correctness of a safety property in an industry design that could not be proved using other known approaches.
clock distribution design and verification for powerpc microprocessors. with the increase of clock speeds, clock skew has become a significant part of the cycle time of high speed microprocessors. while many clocktree routing techniques promise zero or minimal skew, algorithm assumptions or our design methodology constraints often prevent a single approach from being suitable for the entire clock design. in this paper we describe a collection of strategies that are applied at various levels of design to yield clock distribution networks of acceptable skew for the two different clock design styles used by powerpc processors. we also describe a static timing based approach for analyzing the clock network to detect the various clock violations of interest.
exact and heuristic approaches to input vector control for leakage power reduction. we present two approaches to leakage power minimization in static cmos circuits by means of input vector control (ivc). we model leakage effects using pseudo-boolean functions. these are incorporated into an optimal integer linear programming model called vg-ilp that analyzes leakage variation with respect to a circuit's input vectors. a heuristic mixed-integer linear programming (mlp) method is also presented which has several advantages: it is faster, its accuracy can be quickly estimated, and trade-offs between runtime and optimality can easily be made. the proposed methods are used to generate a large set of experimental results on leakage reduction. it is shown that average leakage currents are usually 1.25 times the minimum, confirming the effectiveness of ivc. the heuristic mlp approach is much faster than exact ilp, while finding input vectors whose power consumption is only a few percent from the optimum.
minimum crosstalk switchbox routing. as technology advances, interconnection wires are placed in closer proximity. consequently, reduction of crosstalks between interconnection wires becomes an important consideration in vlsi design. in this paper, we study the gridded switchbox routing problems with the objectives of satisfying crosstalk constraints and minimizing the total crosstalk in the nets. we propose a new approach to the problems which utilizes existing switchbox routing algorithms and improves upon the routing results by re-assigning the horizontal and vertical wire segments to rows and columns, respectively, in an interative fashion. this approach can also be applied to the channel routing problem with crosstalk constraints. a novel mixed ilp formulation and effective procedures for reducing the number of variables and constraints in the mixed ilp formulation are then presented. the experimental results are encouraging.
optimal shape function for a bi-directional wire under elmore delay model. in this paper, we determine the optimal shape function for a bi-directional wire under the elmore delay model. given a bi-directional wire of length l, let f(x) be the width of the wire at position x, 0\leq x \leq l. let t_{dr} be the right-to-left delay. let t_{dl} be the left-to-right delay. let t_{bd}=\alpha t_{dr}+\beta t_{dl} be the total weighted delay where \alpha\geq 0 and \beta\geq 0 are given weights such that \alpha+\beta=1. we determine f(x) so that t_{bd} is minimized. our study shows that, if \alpha=\beta, the optimal shape function is f(x)=c, for some constant c; if \alpha\neq \beta, the optimal shape function can be expressed in terms of the lambert's w function as f(x)=-\frac{c_f}{2c_0}(\frac{1}{w(-ae^{-bx})}+1), where c_f is the unit length fringing capacitance, c_0 is the unit area capacitance, a and b are constants in terms of the given circuit parameters. if \alpha=0 or \beta=0, our result gives the optimal shape function for a uni-directional wire.
simultaneous analytic area and power optimization for repeater insertion. we present an analytic formula for repeater insertion in globalinterconnects that simultaneously minimizes silicon device areaand power dissipation for a given performance ¿{crit}/k where ¿{crit}is the minimum possible delay along a global interconnect, withrepeaters inserted, and 0
library-less synthesis for static cmos combinational logic circuits. traditional synthesis techniques optimize cmos circuits in two phases: i) logic minimization and ii) library mapping phase. typically, the structures and the sizes of the gates in the library are chosen to yield good synthesis results over many blocks or even for an entire chip. consequently this approach precludes an optimal design of individual blocks which may need custom structures. the authors present a new transistor level technique that optimizes cmos circuits both structurally and size-wise. the technique is independent of a library and hence can explore a design space much larger than that possible due to gate level optimization. results demonstrate a significant improvement in circuit performance of the resynthesized circuits.
optimal synthesis of multichip architectures. a global optimization approach to high level synthesis of vlsi multichip architectures is presented. optimal application-specific architectures are synthesized to minimize latency given constraints on chip area, i/o pin count and interchip communication delays. a mathematical integer programming (ip) model for simultaneously partitioning, scheduling, and allocating hardware (functional units, i/o pins, and interchip buses) is formulated. by exploiting the problem structure (using polyhedral theory), the size of the search space is decreased and a new variable selection strategy is introduced based on the branch and bound algorithm. multichip optimal architectures for several examples are synthesized in practical cpu times. execution times are comparable to those for previous heuristic approaches. there are, however, significant improvements in optimal schedules and allocations of multichips
dsp address optimization using a minimum cost circulation technique. this paper presents a new approach to solving the dsp address assignment problem. a minimum cost circulation approach is used to efficiently generate high performance addressing code in polynomial time. addressing code size improvements of up to 7 times are obtained, accounting for up to 1.6 times improvement in code size and performance of compiler-generated dsp code. results also show that memory layout has a small effect on code size and performance when optimal addressing is used. this research is important for industry since this value-added technique can improve code size, power dissipation and performance, without increasing cost.
transform domain techniques for efficient extraction of substrate parasitics. a semi-analytical technique for computation of the frequency- behavior of silicon substrates is demonstrated. the technique uses a boundary element approach, that utilizes the complex substrate green function and the two-dimensional fast fourier transform. the resultant dense system matrix is sparsified by application of orthogonal transform operators on the matrix representing the system. three transform operators are evaluated for this purpose - the discrete cosine transform (dct), the discrete wavelet transform (dwt) and the discrete hadamard transform (dht). the application of any one of these operators provides a rigorous sparsification technique, which significantly reduces the computation time. the green function is computed in the two layers at the top of the substrate. this is done so that contacts in the oxide layer can be included in the substrate model, along with contacts in the silicon substrate. hence, substrate loss terms in metal interconnect lines and in line-to- line interaction models, can be evaluated using this technique. extraction of a simple circuit-simulator compatible model from frequency-domain data is discussed.
analyzing software influences on substrate noise: an adc perspective. substrate noise affects the performance of mixed signal integrated circuits. power supply (di/dt) noise is the dominant source of substrate noise. there have been various attempts at the circuit and software levels to estimate this noise. software-level noise estimation is especially important, as designing noise tolerant circuits for all circumstances may be prohibitively expensive. in this paper, we propose a new software approach for estimating di/dt noise and incorporate it into a power simulator in order to investigate the influence of software on substrate noise. as a case study, we investigate how an analog-to-digital converter (adc) can be designed to adapt its resolution in the presence of substrate noise generated by a embedded processor core. the proposed strategies prevent unexpected adc performance degradations.
a unified theory of timing budget management. this work presents a theoretical framework that optimally solves many open problems in time budgeting. our approach unifies a large class of existing time-management paradigms. examples include time budgeting for maximizing total weighted delay relaxation, minimizing the maximum relaxation and min-skew time budget distribution. we show that many of the time management problems can be transformed into a min-cost flow instance that can be optimally and efficiently solved through well-known combinatorial techniques. experiments include mapping of several designs, which are implemented using parameterized coregen ip cores, on xilinx fpga devices. different time budgeting policies have been applied during the mapping stage. our time management techniques always improved the area requirement of the implemented testbenches compared to a widely-used path-based method. we also compared the maximum budgeting and fairness in delay budget assignments. our experimental results show that an average improvement of 19% in area can be achieved when fairness and maximum budgeting policies are combined, compared to pure maximum budgeting.
formal derivation of optimal active shielding for low-power on-chip buses. passive shielding has been used to reduce capacitive coupling effects of adjacent bus lines by inserting passive ground or power lines (shields) between the bus lines. active shielding is another shielding technique, in which the shield is allowed to switch depending on the switching pattern of its adjacent bus lines. this work formally derives the optimal active shielding logic function for minimum power dissipation. it is also shown that this optimal active shielding architecture depends on the ratio of coupling to ground capacitance (/spl gamma/ = c/sub c//c/sub g/). optimal active shielding is shown to provide up to 25% reduction in bus power dissipation compared to conventional passive shielding. a sub-optimal active shielding architecture with simpler hardware is also proposed. simulation results show that using the sub-optimal shielding architecture leads to less than 6% bus power penalty compared to the optimal active shielding logic circuit.
serial-link bus: a low-power on-chip bus architecture. as technology scales, the shrinking wire width increases the interconnect resistivity, while the decreasing interconnect spacing significantly increases the coupling capacitance. this paper proposes reducing the number of bus lines of the conventional parallel-line bus (plb) architecture by multiplexing each m-bits onto a single line. this bus architecture, the serial-link bus (slb), transforms an n-bit conventional plb into an n/m-line (serial link) bus. the advantage of slbs is that they have fewer lines, and if the bus width is kept the same, slbs will have a larger line pitch. increasing the line width has a twofold reduction effect on the line resistance; as the resistivity of sub-100 nm wires drops significantly, the line width increases. also, increasing the line width and spacing reduces the coupling capacitance between adjacent lines, but increases the line-to-ground capacitance. thus, an optimum degree of multiplexing mopt and an optimum width to pitch ratio ηopt exist, which minimizes the bus energy dissipation and maximizes the bus throughput per unit area. the optimum degree of multiplexing and optimum width-to-pitch ratio for maximum throughput per unit area and minimum energy dissipation for the 25-130-nm technologies was determined in this paper. also, an encoding technique was proposed and implemented to reduce the switch activity penalty due to serialization. hspice simulations show that for the same throughput per unit area as conventional parallel-line data buses, the slb architecture reduces the energy dissipation by up to 31% for a 64-bit bus implemented in an intermediate metal layer of a 50-nm technology, and a reduction of 53% is projected for a 25-nm technology.
cache optimization for embedded processor cores: an analytical approach. embedded microprocessor cores are increasingly beingused in embedded and mobile devices. the softwarerunning on these embedded microprocessor cores is often apriori known, thus, there is an opportunity for customizingthe cache subsystem for improved performance. in thiswork, we propose an efficient algorithm to directly computecache parameters satisfying desired performance criteria.our approach avoids simulation and exhaustiveexploration, and, instead, relies on an exact algorithmicapproach. we demonstrate the feasibility of our algorithmby applying it to a large number of embedded systembenchmarks.
a design for testability technique for rtl circuits using control/data flow extraction. in this paper, we present a technique for extracting functional (control/data flow) information from register transfer level (rtl) controller/data path circuits and illustrate its use in design for hierarchical testability of these circuits. this testing procedure and design for testability (dft) technique is general enough to handle rtl control flow intensive circuits like protocol handlers as well as data flow intensive circuits like digital filters. it makes the combined controller-data path highly testable and does not require any external behavioral information. this scheme has the advantages of low area/delay/power overheads (average of 3.2%, 0.9% and 4.1%, respectively, for benchmarks), high fault coverage (over 99% for most cases), very low test generation times (because it is independent of bit-width), and the advantage of at-speed testing. experiments show a 2-to-4 (1-to-3) orders of magnitude test generation time advantage over an efficient gate-level sequential test generator (combinational test generator that assumes full scan).
fault detection and input stimulus determination for the testing of analog integrated circuits based on power-supply current monitoring. a new method for the testing and fault detection of analog integrated circuits is presented. time-domain testing followed by spectral analysis of the power-supply current is used to detect both dc and ac faults. spectral analysis is applied since the tolerances on the circuit parameters make a direct comparison of waveforms impossible. for the fault detection a probabilistic decision rule is proposed based on a multivariate statistical analysis. since no extra testing pin is needed and the on-line calculation effort is small, the method can be used for wafer-probe testing as well as final production testing. in addition, a methodology for the selection of the input stimulus is presented that improves the test-ability. examples demonstrate the efficiency and the effectiveness of the algorithms.
interface and cache power exploration for core-based embedded system design. minimizing power consumption is of paramount importance during the design of embedded (mobile computing) systems that come as systems-on-a-chip, since interdependencies of design characteristics like power, performance, and area for various system parts (cores) become increasingly influential. in this scenario, interfaces play a key role since they allow one to control/exploit these interdependencies with the aim to meet design constraints like power. in this paper, we present the first comprehensive approach to explore this impact. we consider a whole system comprising a cpu, caches, a main memory and interfaces between those cores and demonstrate the high impact that an adequate adaptation between core parameters and interface parameters in terms of power consumption has. we especially found that cache parameters and bus configurations of cache buses have a significant impact in this respect. in addition, we made the important observation that optimizing for performance no longer implies that power is optimized as well in deep submicron technologies. instead, we found out that especially for newer technologies, the relative interface power contribution increases, leading to scenarios where we obtain a real power/performance tradeoff. in summary, our explorations unveiled not yet investigated interdependencies that represent the first step towards future efforts to optimize/adapt interfaces and caches in core-based systems for low power designs.
system-level exploration for pareto-optimal configurations in parameterized systems-on-a-chip. in this work, we provide a technique for efficiently exploring the configuration space of a parameterized system-on-a-chip (soc) architecture to find all pareto-optimal configurations. these configurations represent the range of meaningful power and performance tradeoffs that are obtainable by adjusting parameter values for a fixed application mapped onto the soc architecture. our approach extensively prunes the potentially large configuration space by taking advantage of parameter dependencies. we have successfully incorporated our technique into the parameterized soc tuning environment (platune) and applied it to a number of applications.
test generation for bridging faults in cmos ics based on current monitoring versus signal propagation. bridge-type defects play a dominant role in state-of-the-art cmos technologies. this paper describes a combined functional and overcurrent-based test generation approach for cmos circuits, which is optionally based on layout information. comparative results for benchmark circuits are given to demonstrate the feasibility of voltage-based versus iddq-based testing.
false-noise analysis using logic implications. cross-coupled noise analysis has become a critical concern in today's vlsi designs. typically, noise analysis makes an assumption that all aggressing nets can simultaneously switch in the same direction. this creates a worst-case noise pulse on the victim net that often leads to false noise violations. in this paper, we present a new approach that uses logic implications to identify the maximum set of aggressor nets that can inject noise simultaneously under the logic constraints of the circuit. we propose an approach to efficiently generate logic implications from a transistor-level description and propagate them in the circuit using robdd representations and a newly proposed laterial propagation method. we then show that the problem of finding the worst case logically feasible noise can be represented as a maximum weighted independent set problem and show how to efficiently solve it. initially, we restrict our discussion to zero-delay implications, which are valid for glitch-free circuits and then extend our approach to timed implications. the proposed approaches were implemented in an industrial noise analysis tool and results are shown for a number of industrial test cases. we demonstrate that a significant reduction in the number of noise failures can be obtained from considering the logic implications as proposed in this paper, underscoring the need for false-noise analysis.
delay noise pessimism reduction by logic correlations. high-performance digital circuits are facing increasingly severe signal integrity problems due to crosstalk noise and therefore the state-of-the-art static timing analysis (sta) methods consider crosstalk-induced delay variation. current noise-aware sta methods compute noise-induced delay uncertainty for each net independently and annotate appropriate delay changes of nets onto data paths and associated clock paths to determine timing violations. since delay changes in individual nets contribute cumulatively to delay changes of paths, even small amounts of pessimism in noise computation of nets can add up to produce large timing violations for paths, which may be unrealistic. unlike glitch noise analysis where noise often attenuates during propagation, quality of delay noise analysis is severely affected by any pessimism in noise estimation and can unnecessarily cost valuable silicon and design resources for fixing unreal violations. in this paper, we propose a method to reduce pessimism in noise-aware sta by considering signal correlations of all nets associated with an entire timing path simultaneously, in a path-based approach. we first present an exact algorithm based on the branch-and-bound technique and then extend it with several heuristic techniques so that very large industrial designs can be analyzed efficiently. these techniques, which are implemented in an industrial crosstalk noise analysis tool, show as much as 75% reduction in the computed path delay variations.
negative thinking by incremental problem solving: application to unate covering. we introduce a new technique to solve exactly a discrete optimization problem, based on the paradigm of "negative" thinking. the motivation is that when searching the space of solutions, often a good solution is reached quickly and then improved only a few times before the optimum is found: hence most of the solution space is explored to certify optimality, but it does not yield any improvement of the cost function. so it is quite natural for an algorithm to be "skeptical" about the chance to improve the current best solution. for illustration we have applied our approach to the unate covering problem. we designed a procedure, raiser, implementing a negative thinking search, which is incorporated into a common branch-and-bound procedure. raiser is invoked at a node of the search tree which is deep enough to justify negative thinking. raiser tries to detect a hard core of the matrix corresponding to the node by augmenting an independent set of rows in order to increase incrementally the cost of the minimum solutions covering the matrix. eventually either raiser prunes the subtree rooted at the node (having found a lower bound equal or greater than the current best solution) or returns a new solution that becomes the current best one. experiments show that our program, aura, outperforms both espresso and our enhancement of espresso using coudert's limit lower bound. it is always faster and in the most difficult examples either has a running time better by up to two orders of magnitude, or the other programs fail to finish due to timeout or spaceout. the package scherzo is faster on some examples and loses on others, due to a less powerful pruning strategy of the search space, partially mitigated by a more effective computation of the maximal independent set.
a fast and robust exact algorithm for face embedding. we present a new matrix formulation of the face hypercube embedding problem that motivates the design of an efficient search strategy to find an encoding that satisfies all faces of minimum length. increasing dimensions of the boolean space are explored; for a given dimension constraints are satisfied one at a time. the following features help to reduce the nodes of the solution space that must be explored: candidate cubes instead of candidate codes are generated, cubes yielding symmetric solutions are not generated, a smaller sufficient set of solutions (producing basic sections) is explored, necessary conditions help discard unsuitable candidate cubes, early detection that a partial solution cannot be extended to be a global solution prunes infeasible portions of the search tree. we have implemented a prototype package minsk based on the previous ideas and run experiments to evaluate it. the experiments show that minsk is faster and solves more problems than any available algorithm. moreover, minsk is a robust algorithm, while most of the proposed alternatives are not. besides most problems of the complete mcnc benchmark suite, other solved examples include an important set of decoder plas coming from the design of microprocessor instruction sets.
the impact of the nanoscale on computing systems. nanoscale technologies provide both challenges and opportunities. we show that the issues and potential solutions facing designers are technology independent and arise mainly from shrinking device sizes and an increase in the number of devices available. we explore how it is possible to use some of the devices that will be available to help ease design complexity as well as overcome process related challenges such as limited layout freedom, increased defect densities, timing constraints, and power dissipation.
factoring logic functions using graph partitioning. algorithmic logic synthesis is usually carried out in two stages, the independent stage where logic minimization is performed on the boolean equations with no regard to physical properties and the dependent stage where mapping to a physical cell library is done. the independent stage includes logic operations like decomposition, extraction, factoring, substitution and elimination. these operations are done with some kind of division (boolean, algebraic), with the goal being to obtain a logically equivalent factored form which minimizes the number of literals.in this paper, we present an algorithm for factoring that uses graph partitioning rather than division. central to our approach is to combine this with the use of special classes of boolean functions, such as read-once functions, to devise new combinatorial algorithms for logic minimization. our method has been implemented in the sis environment, and an empirical evaluation indicates that we usually get significantly better results than algebraic factoring and are quite competitive with boolean factoring but with lower computation costs.
robust optimization based backtrace method for analog circuits. in this paper, we propose a new robust approach to signal backtrace for efficiently testing embedded analog modules in a large system. the proposed signal backtrace method is formulated as a solution to a multi-point boundary value problem (bvp), with constraints on the output state and the input. this error constraint minimizes large spurious deviations in the input signal and the corvergence problems that arise if multiple solutions exist or if the desired signal does not exist in the feasible signal space. as an additional attractive advantage, this formulation preserves the core iteration structure of a spice-like simulator without modifications, greatly easing implementation.
on adaptive diagnostic test generation. adaptive diagnosis, a paradigm for diagnosis, is defined. a system based on this paradigm, for i_{ddq} measurement based diagnosis of bridging faults, is reported. experimental evaluation of the system shows it to be substantially superior to existing systems, especially for larger circuits.
storage assignment during high-level synthesis for configurable architectures. modern, high performance configurable architectures integrate on-chip, distributed block ram modules to provide ample data storage. synthesizing applications to these complex systems requires an effective and efficient approach to conduct data partitioning and storage assignment. in this paper, we present a data and iteration space partitioning solution that focuses on minimizing remote memory accesses or, equivalently, maximizing the local computation. using the same code but different data partitionings, we can achieve faster clock frequencies, without increasing the number of cycles, by simply minimizing global memory accesses. other optimization techniques like scalar replacement, prefetching and buffer insertion can further minimize remote accesses and lead to average 4.8/spl times/ speedup in overall runtime.
design of heterogeneous ics for mobile and personal communication systems. mobile and personal communication systems form key market areas for the electronics industry of the nineties. stringent requirements in terms of flexibility, performance and power dissipation, are driving the development of integrated circuits into the direction of heterogeneous single-chip solutions. new ic architectures are emerging which contain the core of a powerful programmable processor, complemented with dedicated hardware, memory and interface structures. in this tutorial we will discuss the real-life design of a heterogeneous ic for an industrial telecom application: a reconfigurable mobile terminal for satellite communication. based on this practical design experience, we will subsequently discuss a methodology for the design of heterogeneous ics. design steps that will be addressed include: system specification and refinement, data path and communication synthesis, and code generation for embedded processor cores.
direct transistor-level layout for digital blocks. we present a complete transistor-level layout flow, from logic netlist to final shapes, for blocks of combinational logic up to a few thousand transistors in size. the direct transistor-level attack easily accommodates the demands for careful custom sizing necessary in high-speed design, and is also significantly denser than a comparable cell-based layout. the key algorithmic innovations are (a) early identification of essential diffusion-merged mos device groups called clusters, but (b) deferred binding of clusters to a specific shape-level layout until the very end of a multi-phase placement strategy. a global placer arranges uncommitted clusters; a detailed placer optimizes clusters at shape level for density and for overall routability. a commercial router completes the flow. experiments comparing to a commercial standard cell-level layout flow show that, when flattened to transistors, our tool consistently achieves 100% routed layouts that average 23% less area.
efficient thermal placement of standard cells in 3d ics using a force directed approach. as the technology node progresses, thermal problems arebecoming more prominent especially in the developingtechnology of three-dimensional (3d) integrated circuits. thethermal placement method presented in this paper uses an iterativeforce-directed approach in which thermal forces direct cells awayfrom areas of high temperature. finite element analysis (fea) isused to calculate temperatures efficiently during each iteration.benchmark circuits produce thermal placements with both lowertemperatures and thermal gradients while wirelength is minimally affected.
addressing the timing closure problem by integrating logic optimization and placement. timing closure problems occur when timing estimates computed during logic synthesis do not match with timing estimates computed from the layout of the circuit. in such a situation, logic synthesis and layout synthesis are iterated until the estimates match. the number of such iterations is becoming larger as technology scales. timing closure problems occur mainly due to the difficulty in accurately predicting interconnect delay during logic synthesis.in this paper, we present an algorithm that integrates logic synthesis and global placement to address the timing closure problem. we introduce technology independent algorithms as well as technology dependent algorithms. our technology independent algorithms are based on the notion of "wire-planning". all these algorithms interleave their logic operations with local and incremental/full global placement, in order to maintain a consistent placement while the algorithm is run. we show that by integrating logic synthesis and placement, we avoid the need to predict interconnect delay during logic synthesis. we demonstrate that our scheme significantly enhances the predictability of wire delays, thereby solving the timing closure problem. this is the main result of our paper. our results also show that our algorithms result in a significant reduction in total circuit delay. in addition, our technology independent algorithms result in a significant circuit area reduction.
new methods for speeding up computation of newton updates in harmonic balance. a new adaptive approach to solving large dimension harmonic balance (hb) problems is presented. the method is based on adjusting the order of the equation system according to the degree of nonlinearity of each node in the circuit. a block-diagonal preconditioner is used to construct an algorithm for order reducing during the iterative hb process.
counterexample-guided choice of projections in approximate symbolic model checking. bdd-based symbolic techniques of approximate reachability analysis based on decomposing the circuit into a collection of overlapping sub-machines (also referred to as overlapping projections) have been recently proposed. computing a superset of the reachable states in this fashion is susceptible to false negatives. searching for real counterexamples in such an approximate space is liable to failure. in this paper, the "hybridization effect" induced by the choice of projections is identified as the cause for the failure. a heuristic based on hamming distance is proposed to improve the choice of projections, that reduces the hybridization effect and facilitates either a genuine counterexample or proof of the property. the ideas are evaluated on a real large design example from the pci interface unit in the magic chip of the stanford flash multiprocessor.
the sizing rules method for analog integrated circuit design. this paper presents the sizing rules method for analog cmos circuit design that consists of: first, the development of a hierarchical library of transistor pair groups as basic building blocks for analog cmos circuits; second, the derivation of a hierarchical generic list of constraints that must be satisfied to guarantee the function of each block and its reliability with respect to physical effects; and third, the development of an automatic recognition of building blocks in a circuit schematic. the sizing rules method efficiently captures design knowledge on the technology-specific level of transistor pair groups. this reduces the preparatory modeling effort for analog circuit synthesis. results of industrial applications to circuit sizing, design centering, response surface modeling and analog placement show the significance of the sizing rules method. sizing rules especially make sure that automatic circuit sizing and design centering lead to technically meaningful and robust results.
e-proofs: a cmos bridging fault simulator. the problem of bridging fault simulation under the conventional voltage testing environment is considered. a method to provide electrical-level simulation accuracy, without paying the associated performance penalties, is proposed. a three-level simulation model is used, balancing the tradeoffs among gate-level, switch-level, and electrical-level simulation. large memory overheads are avoided by localizing the fault, and by performing electrical-level simulation only in the area around the fault. this approach is sufficiently flexible to model feedback faults, bicmos circuits, stuck-open faults, and any fault that can be described with a circuit netlist. tests were run on several iscas combinational and sequential benchmark circuits, using realistic cells and transistor parameters; results show that accurate simulations can be performed in reasonable time
a delay model for logic synthesis of continuously-sized networks. abstract: we present a new delay model for use in logic synthesis. a traditional model treats the area of a library cell as constant and makes the cell's delay a linear function of load. out model is based on a different, but equally fundamental linearity in the equation relating area, delay, and load: namely, we may keep a cell's delay constantly making its area a linear function of load. this allows us to technology map using a library with continuous device sizing, satisfies certain electrical noise and power constraints, and in certain cases is computationally simpler than a traditional model. we give results to support these claims. a companion paper uses the computational simplicity to explore a wide search space of algebraic factorings in a mapped network.
optimal latch mapping and retiming within a tree. we propose a technology mapping algorithm that takes existing structural technology-mapping algorithms based on dynamic programming and extends them to retime pipelined circuits. if the circuit to be mapped has a tree structure, our algorithm generates an optimal solution compatible with that structure. the algorithm takes into account gate delays and capacitive loads as latches are moved across the logic. it also supports latches with embedded logic: i.e., cells that combine a d latch with a combinational gate at little extra cost in latch delay.
mist: an algorithm for memory miss traffic management. cache misses represent a major bottleneck in embedded systems performance. traditionally, compilers optimistically treated all memory accesses as cache hits, relying on the memory controller to account for longer miss delays. however, the memory controller has only a local view of the program, and is not able to efficiently hide the latency of these memory operations. our compiler technique actively manages cache misses, and performs global miss traffic optimizations, to better hide the latency of the memory operations. our memory-aware compiler scheduled several benchmarks on the tic6211 processor architecture with a direct mapped cache, and generated an average of 61.6% improvement over the best schedule of the traditional (memory-transparent) optimizing compiler, demonstrating the utility of our miss traffic optimization approach.
efficient manipulation algorithms for linearly transformed bdds. binary decision diagrams (bdds) are the state-of-the-art data structure in vlsi cad. but due to their ordering restriction only exponential sized bdds exist for many functions of practical relevance. linear transformations (lts) have been proposed as a new concept to minimize the size of bdds and it is known that in some cases even an exponential reduction can be obtained.in addition to a small representation, the efficient manipulation of a data structure is also important. in this paper we present polynomial time manipulation algorithms that can be used for linearly transformed bdds (lt-bdds) analogously to bdds. for some operations, like synthesis algorithms based on ite, it turns out that the techniques known from bdds can be directly transferred, while for other operations, like quantification and cofactor computation, completely different algorithms have to be used. experimental results are given to show the efficiency of the approach.
iterative abstraction using sat-based bmc with proof analysis. resolution-based proof analysis techniques have been proposedrecently to identify a sufficient set of reasons for unsatisfiabilityderived by a cnf-based sat solver. we have adapted thesetechniques to work with a hybrid sat solver. we use the proofanalysis technique with sat-based bmc, in order to generateuseful abstract models. our abstraction procedure is usediteratively in a top-down framework, starting from the concretedesign, where we apply bmc on increasingly more abstractmodels. we apply various sat-based and bdd-basedverification methods on these abstract models, in order to obtainproofs of correctness, or to perform deeper searches forcounterexamples. we demonstrate the effectiveness of ourprototype implementation on several large industry designs.
width minimization of two-dimensional cmos cells using integer programming. we address the problem of cmos cell width minimization in the general two-dimensional (2-d) layout style and propose a novel technique based on integer linear programming (ilp) to solve it exactly. we formulate a 0-1 ilp model whose solution minimizes cell width along with the routing complexity across the diffusion rows. we present experimental results that evaluate the performance of two ilp solvers that have very different solution methods, and assess the effect of the number of rows on cell width. run-times for optimal layouts are in seconds for cells with up to 20 transistors. for larger cells, we propose a practical circuit pre-processing scheme that dramatically reduces the run time with little or no loss in optimality.
formal methods for dynamic power management. dynamic power management or dpm refers to the problem ofjudicious application of various low power techniques based onruntime conditions in an embedded system to minimize the totalenergy consumption.to be effective, often such decisions takeinto account the operating conditions and the system-level designgoals.dpm has been a subject of intense research in thepast decade driven by the need for low power in modern embeddeddevices.we present an overview of the formal methods thathave been explored in solving the system-level dpm problem.we show how formal reasoning frameworks can potentially unifyapparently disparate dpm techniques.
manufacturing-aware physical design. ultra-deep submicron manufacturability impacts physicaldesign (pd) through complex layout rules and large guardbands for process variability; this creates new requirements for new manufacturing-aware pd technologies. the firstpart of this tutorial reviews pd complications and methodology changes - notably in the detailed routing arena - that arise from subwavelength lithography and deep-submicronmanufacturing (antennas, metal planarization and mask-wafer mismatch). process variations and their sources are taxonomized for modeling and simulation. a framework ofdesign for cost and value is described. the second part covers yield-constrained optimizations in pd, especially "beyond corners" approaches that escape today's pessimistic or even incorrect corner-based approaches. statistical timingand noise analyses enable optimization of parametric yieldand reliability. yield-aware cell libraries and "analog" design rules (as opposed to "digital", 0/1 rules) can help designers explore yield-cost tradeoffs, especially for low-volumeparts. we then examine performance impact-limited fill insertion which goes beyond mere capacitance rules. modeling, objectives, and filling strategies are discussed. finally,we discuss current and near-term prospects for the overall design-to-manufacturing pd methodology. key aspects include better integrations with analysis and manufacturing interfaces, as well as cost-benefit tradeoffs for "regular"layout structures that are likely beyond 90nm, cost optimizations for low-volume production, and the role of robust and/or stochastic optimization in pd.
layout-aware scan chain synthesis for improved path delay fault coverage. path delay fault testing becomes increasingly important due tohigher clock rates and higher process variability caused by shrinkinggeometries. achieving high-coverage path delay fault testingrequires the application of scan justified test vector pairs, coupledwith careful ordering of the scan flip-flops and/or insertion ofdummy flip-flops in the scan chain. previous works on scan synthesisfor path delay fault testing using scan shifting have focusedexclusively on maximizing fault coverage and/or minimizing thenumber of dummy flip-flops, but have disregarded the scan wirelengthoverhead. in this paper we consider both dummy flip-flopand wirelength costs, and focus on post-layout formulations thatcapture the achievable tradeoffs between these costs and delay faultcoverage in scan chain synthesis.
towards formal verification of analog designs. we show how model checking methods developed for hybrid dynamic systems may be usefully applied for analog circuit verification. finite-state abstractions of the continuous analog behavior are automatically constructed using polyhedral outer approximations to the flows of the underlying continuous differential and difference equations. in contrast to previous approaches, we do not discretize the entire continuous state space, and our abstraction captures the relevant behaviors for verification in terms of the transitions between "states" (regions of the continuous state space) as a finite state machine in the hybrid system model. the approach is illustrated for two circuits, a standard oscillator benchmark, and a much larger and more realistic delta-sigma (ai) modulator.
constrained multivariable optimization of transmission lines with general topologies. the design of system level interconnects to meet signal integrity objectives is a challenging problem. this paper formulates the transmission line synthesis problem as a constrained multi-dimensional optimization of the complete net, taking into account factors like loading conditions on the line, loss in the line and rise-time of the input signal. different design variables such as width or resistivity of the interconnect, resistive source or far-end termination, etc. can all be considered concurrently. the termination metric is based upon forcing the impulse response waveform to be symmetric using the first three exact moments of the distributed system. an efficient means to trade-off between signal rise-time and ringing is presented and no time-domain simulations are needed. several examples are presented to demonstrate the efficacy of the proposed methodology.
test pattern generation based on arithmetic operations. existing built-in self test (bist) strategies require the use of specialized test pattern generation hardware which introduces significant area overhead and performance degradation. in this paper, we propose a novel method for implementing test pattern generators based on adders widely available in data-path architectures and digital signal processing circuits. test patterns are generated by continuously accumulating a constant value and their quality is evaluated in terms of the pseudo-exhaustive state coverage on subspaces of contiguous bits. this new test generation scheme, along with the recently introduced accumulator-based compaction scheme facilitates a bist strategy for high performance datapath architectures that uses the functionality of existing hardware, is entirely integrated with the circuit under test, and results in at-speed testing with no performance degradation and area overhead.
acyclic modeling of combinational loops. this paper presents a method to convert gate-level combinational loop into an acyclic circuit, if the combinational loop is not oscillatory. combinational loops breach design methodologies, because they can involve undesirable circuit behavior and can possibly lead to oscillations based on the external stimuli to the loops. however, for designs compiled using automated synthesis-compiler, these loops are very likely to appear in the generated gate-level designs. we present a modeling of combinational loops as state holding elements and break non oscillatory loops using a level sensitive latch. apart from modeling combinational loops consisting of gates, the algorithm also converts the loops through design latches. the increase in design area, due to the loop conversion, has an upper bound of twice the size of the original feedback path. however, in case of multiply nested feedback paths, each path is treated separately. unlike previous work that converts cyclic combinational logic where the feedback is not exercised, this paper presents an algorithm to identify the stateful "latch" behavior in a class of feedback logic (non-oscillatory, monotonic). a conversion algorithm replaces such feedback logic by an equivalent circuit comprising explicit latches and acyclic combinational logic. the replacement circuit has an identical behavior as the original stateful feedback logic.
partition-based decision heuristics for image computation using sat and bdds. methods based on boolean satisfiability (sat) typically use a conjunctive normal form (cnf) representation of the boolean formula, and exploit the structure of the given problem through use of various decision heuristics and implication methods. in this paper, we propose a new decision heuristic based on separator-set induced partitioning of the underlying cnf graph. it targets those variables whose choice generates clause partitions with disjoint variable supports. this can potentially improve performance of sat applications by decomposing the problem dynamically within the search. in the context of a recently proposed image computation method combining sat and bdds, this results in simpler bdd subproblems. we provide algorithms for cnf partitioning -- one based on a clause-variable dependency matrix, and another based on standard hypergraph partitioning techniques, and also for the use of partitioning information in decision heuristics for sat. we demonstrate the effectiveness of our proposed partition-based heuristic with practical results for reachability analysis of benchmark sequential circuits.
a high-level interconnect power model for design space exploration. in this paper, we present a high-level power model toestimate the power consumption in semi-global and global interconnects.such interconnects are used for communications between logic modules,clock distribution networks, and power supply rails. the main purposeof our model is to set forward a simple methodology to efficiently obtainfirst-order estimates of interconnect power in early stages of the designprocess. hence, the objective is to provide designers and/or high-leveldesign automation tools with a way to quickly explore the design spaceand weed out architectures whose interconnect power requirements donot meet the allocated power budget. in addition to switching power,which includes inter-wire coupling, our model also considers power dueto vias and repeaters. our experimental results show that in comparisonto an accurate low-level model, the error in our method in estimatingtotal switching power is only 6% (while the speedup is three-to-fourorders of magnitude), and an estimate of the numbers of vias (hence, viapower) is within 3% agreement of that obtained for designs synthesizedby commercial tools. furthermore, we develop a probabilistic segmentlength distribution model for cases in which rent's rule is inadequate. byanalyzing the netlists of a set of complex designs, we have been able tovalidate our segment length distribution model. the novelty of this worklies in the introduction of a high-level interconnect modeling methodologyin which it is possible to efficiently compute all the major sources ofpower consumption in interconnects and hence, enable interconnect-aware,high-level design space exploration.
gate sizing using incremental parameterized statistical timing analysis. as technology scales into the sub-90 nm domain, manufacturing variations become an increasingly significant portion of circuit delay. as a result, delays must be modeled as statistical distributions during both analysis and optimization. this paper uses incremental, parametric statistical static timing analysis (ssta) to perform gate sizing with a required yield target. both correlated and uncorrelated process parameters are considered by using a first-order linear delay model with fitted process sensitivities. the fitted sensitivities are verified to be accurate with circuit simulations. statistical information in the form of criticality probabilities are used to actively guide the optimization process which reduces run-time and improves area and performance. the gate sizing results show a significant improvement in worst slack at 99.86% yield over deterministic optimization.
re-encoding sequential circuits to reduce power dissipation. we present a fully implicit encoding algorithm for minimization of average power dissipation in sequential circuits, based on the reduction of the average number of bit changes per state transition.we have studied two novel schemes for this purpose, one based on recursive weighted non-bipartite matching, and one on recursive minicut bi-partitioning. we employ adds (algebraic decision diagrams) to computate the transition probabilities, to measure the potential area saving, and in the encoding algorithms themselves.our experiments show the effectiveness of our method in reducing power dissipation for large sequential designs.
a symbolic algorithm for maximum flow in 0-1 networks. we present an algorithm for finding the maximum flow in a 0-1 network. the algorithm is symbolic and does not require explicit enumeration of the nodes and edges of the network. therefore, it can handle much larger graphs than it was previously possible (more than 10^36 edges). the main idea is to trace (implicitly) sets of edge-disjoint augmenting paths. disjointness is enforced by solving an edge matching problem for each layer of the network with the help of newly defined priority functions.
a new approach to effective circuit clustering. it is pointed out that the complexity of next-generation vlsi systems will exceed the capabilities of top-down layout synthesis algorithms, particularly in netlist partitioning and module placement. bottom-up clustering is needed to condense the netlist so that the problem size becomes tractable to existing optimization methods. here, the ds quality measure, a general metric for evaluation of clustering algorithms, is established. the dc metric in turn motivates the rw-st algorithm, a self-tuning clustering method based on random walks in the circuit netlist. rw-st efficiently captures a globally good circuit clustering. when incorporated within a two-phase iterative fiduccia-mattheyses partitioning strategy, the rw-st clustering method improves bisection width by an average of 17% over previous matching-based methods
a system for synthesizing optimized fpga hardware from matlab. efficient high level design tools that can map behavioral descriptions to fpga architectures are one of the key requirements to fully leverage fpga for high throughput computations and meet time-to-market pressures. we present a compiler that takes as input algorithms described in matlab and generates rtl vhdl. the rtl vhdl then can be mapped to fpgas using existing commercial tools. the input application is mapped to multiple fpgas by parallelizing the application and embedding communication and synchronization primitives automatically. our compiler infers the minimum number of bits required to represent the variable through a precision analysis framework. the compiler can leverage optimized ip cores to enhance the hardware generated. the compiler also exploits parallelism in the input algorithm by pipelining in the presence of resource constraints. we demonstrate the utility of the compiler by synthesizing hardware for a couple of signal/image processing algorithms and comparing them with manually designed hardware.
efficient construction of binary moment diagrams for verifying arithmetic circuits. bdd-based approaches cannot handle some arithmetic functions such as multiplication efficiently, while binary moment diagrams proposed by bryant and chen provide compact representations for those functions. they reported a bmd-based polynomial-time algorithm for verifying multipliers. this approach requires high-level information such as specifications to subcomponents. this paper presents a new technique called backward construction which can construct bmds directly from circuit descriptions without any high-level information. the experiments show that the computation time for verifying for n-bit multipliers is approximately n^4. we have successfully verified 64-bit multipliers of several type in 3-6 hours with 40 mbyte of memory on sparcstation10/51. this result outperforms previous bdd-based approaches for verifying multipliers.
deterministic test pattern generation techniques for sequential circuits. this paper presents new test generation techniques for improving the average-case performance of the iterative logic array based deterministic sequential circuit test generation algorithms. to be able to assess the effectiveness of the proposed techniques, we have developed a new atpg system for sequential circuits, called atoms, and we have incorporated these techniques into the test generator. atoms achieved very high fault coverages in a short amount of time for the iscas89 sequential benchmark circuits, demonstrating the effectiveness of these techniques on the test generation performance.
wirelength optimization by optimal block orientation. rectangular cells can be flipped in place along either horizontal or vertical axis without changing the area of a layout. during floorplanning, both the location and orientation of cells are determined. however, the complexity of the floorplanning process usually means that the wirelength is not minimum. this paper proposes a technique for wirelength minimization based on in-place flipping of cells that can be applied to any floorplan style consisting of rectangular blocks or sub-blocks. instead of conventional search procedures, a boolean symbolic approach is proposed to generate flip-optimal floorplans. experimental results show that it can effectively reduce the wirelength of current state of the art approaches, at no cost in area and with modest runtimes.
vlsi placement using uncertain costs. many objective functions used to evaluate placement quality contain uncertain parameters. while these values (e.g., channel width, cell area, wire length, and circuit delay) can be estimated, they cannot be precisely known until the layout is finished or sometimes until the chip is fabricated. as a result, current automatic placement algorithms must use `expected'' values in their objective functions providing one possible estimate of placement nquality. an algorithm that uses the full range of potential values when computing placement cost can yield a more credible prediction of placement quality and reveal more about the structure of optimal configurations. in this paper, we propose an interval-based approach to modeling uncertainty in automatic placement algorithms. we illustrate our methodology by implementing an interval branch-and-bound placement algorithm. using this example, we demonstrate how interval operators can be used to compute bounds on placement cost and to determine minimum-cost configurations. we also test the performance of our algorithm and analyze the results.
diagnosis of interconnect faults in cluster-based fpga architectures. fault diagnosis has particular importance in the context of field programmable gate arrays (fpgas) because faults can be avoided by reconfiguration at almost no real cost. cluster-based fpga architectures, in which several logic blocks are grouped together into a coarse-grained logic block, are rapidly becoming the architecture of choice for major fpga manufacturers. the high density interconnect found within clusters greatly complicates the problem of fpga diagnosis. we propose a technique for the testing and diagnosis of cluster-based fpga architectures. we present a hierarchical approach to define a set of fpga configurations in which each fault is detectable, and each fault pair is differentiable. the cornerstone of this work is the concise expression of the distinguishing conditions of each fault pair. experimental results demonstrate that nearly 100% fault coverage and diagnostic resolution are achieved with a low number of test configurations.
identification of unsettable flip-flops for partial scan and faster atpg. state justification is a time-consuming operation in test generation for sequential circuits. in this paper, we present a technique to rapidly identify state elements (hip-hops) that are either difficult to set or unsettable. this is achieved by performing test generation on certain transformed circuits to identify state elements that are not settable to specific logic values. two applications that benefit from this identification are sequential circuit test generation and partial scan design. the knowledge of the state space is shown to be useful in creating early backtracks in deterministic test generation. partial scan selection is also shown to benefit from the knowledge of the difficult-to-set hip-hops. experiments on the iscas89 circuits are presented to show the reduction in time for test generation and the improvements in the testability of the resulting partial scan circuits.
equivalent waveform propagation for static timing analysis. this paper proposes a scheme that captures diverse input waveformsof cmos gates for static timing analysis. conventionallythe latest arrival time and transition time are calculated from thetimings when a transient waveform goes across pre-determinedreference voltages. however, this method cannot accurately considerthe impact of waveform shape on gate delay, when crosstalk-inducednon-monotonic waveforms or inductance-dominant stepwisewaveforms are injected. we propose a new timing analysisscheme called "equivalent waveform propagation". the proposedscheme calculates the equivalent waveform that makes the outputwaveform close to the actual waveform, and uses the equivalentwaveform for timing calculation. the proposed scheme can copewith various waveforms affected by resistive shielding, crosstalknoise, wire inductance etc. in this paper, we devise a method tocalculate equivalent waveform. the proposed calculation methodis compatible with conventional methods in gate delay library andcharacterization, and hence our method is easy to be implementedwith conventional static timing analysis tools.
timing analysis considering spatial power/ground level variation. spatial power/ground level variation causes power/ground level mismatch between driver and receiver, and the mismatch affects gate propagation delay. this paper proposes a timing analysis method based on a concept called “pg level equalization” which is compatible with conventional sta frameworks. we equalize the power/ground levels of driver and receiver. the charging/discharging current variation due to equalization is compensated by replacing output load. we present an implementation method of the proposed concept, and demonstrate that the proposed method works well for multiple-input gates and rc load model.
optimal buffered routing path constructions for single and multiple clock domain systems. shrinking process geometries and the increasing use of ip components in soc designs give rise to new problems in routing and buffer insertion. a particular concern is that cross-chip routing will require multiple clock cycles. another is the integration of independently clocked components. this paper explores simultaneous routing and buffer insertion in the context of single and multiple clock domains. we present optimal and efficient polynomial algorithms that can be used to estimate communication overhead for interconnect and resource planning in single and multi-clock domain systems. experimental results verify the correctness and practicality of our approach.
regularity extraction via clan-based structural circuit decomposition. identifying repeating structural regularities in circuits allows the minimization of synthesis, optimization, and layout efforts. we introduce in this paper a novel method for identifying a set of repeating circuit structures, referred to as templates, and we report on using an efficient binate cover solver to select an appropriate subset of templates with which to cover the circuit. our approach is comprised of three steps. first, the circuit graph is decomposed in a hierarchical inclusion parse tree using a clan-based decomposition algorithm. this algorithm discovers clans, grouping of nodes in the circuit graph that have a natural affinity towards each other. second, the parse tree nodes are classified into equivalence classes. such classes represent templates suitable for circuit covering. the final step consists of using a binate cover solver to find an appropriate cover. the cover will consist of instantiated templates and gates that cannot be covered by any templates. we describe the results of applying this algorithm to several circuits, and show that the algorithm is effective in extracting structural regularity.
configuration bitstream compression for dynamically reconfigurable fpgas. field programmable gate arrays (fpgas) holds the possibility of dynamic reconfiguration. the key advantages of dynamic reconfiguration are the ability to rapidly adapt to dynamic changes and better utilization of the programmable hardware resources for multiple applications. however, with the advent of multi-million gate equivalent fpgas, configuration time is increasingly becoming a concern. high reconfiguration cost can potentially wipe out any gains from dynamic reconfiguration. one solution to alleviate this problem is to exploit the high levels of redundancy in the configuration bitstream by compression. in this paper, we propose a novel configuration compression technique that exploits redundancies both within a configuration's bitstream as well as between bitstreams of multiple configurations. by maximizing reuse, our results show that the proposed technique performs 26.5-75.8% better than the previously proposed techniques. to the best of our knowledge, ours is the first work that performs inter-configuration compression.
variability in sub-100nm sram designs. many components of variability become larger percentage design factors with decreasing feature size. hence, the small transistors in sram cells are particularly sensitive to these variations. the sram cell transistors in sub-100-nm designs may contain fewer than 100 channel dopant atoms. to achieve a robust design with such variability, one must enhance the normal static-noise-margin and write-trip-point analysis, often with monte carlo simulations using statistical transistor models including the process and mismatch fluctuations. similar challenges exist for the sense amplifiers normally used with sram arrays. except with very low speed designs, yield to speed can be substantially reduced by variations between nominally matched sense amplifier transistors as well as by the variability resulting in a very worst memory cell low read current. this also increases the hazards of delay timing with dummy paths and dummy cells and increases the need for at-speed testing prior to repair.
a formal approach to nonlinear analog circuit verification. this contribution presents an approach to nonlinear dynamic analog circuit verification. the input-output behavior of two systems is analyzed to check whether they are functionally similar. the algorithm compares the implicit nonlinear state space descriptions of the two systems on the same or on different levels of abstraction by sampling the state spaces and by building a nonlinear one-to-one mapping of the state spaces. some examples demonstrate the feasibility of our approach.
interconnect yield model for manufacturability prediction in synthesis of standard cell based designs. a sound ic design methodology must be supported by adequate manufacturability assessment tools. these tools should assist a designer in predicting ic manufacturing cost in as early a design stage as possible. in this paper a yield model is proposed that takes as input a standard cell netlist and produces as output a yield estimate without performing placement and routing. this yield model has been successfully used to predict the interconnect yield of standard cell designs that were implemented with two place and route tools. the proposed yield model can be used as a crucial component in the objective function of a circuit synthesis tool as well as in technology mapping optimization.
java as a specification language for hardware-software systems. the specification language is a critical component of the hardware-software co-design process since it is used for functional validation and as a starting point for hardware- software partitioning and co-synthesis. this paper pro poses the java programming language as a specification language for hardware-software systems. java has several characteristics that make it suitable for system specification. however, static control and dataflow analysis of java programs is problematic because java classes are dynamically linked. this paper provides a general solution to the problem of statically analyzing java programs using a technique that pre-allocates most class instances and aggressively resolve memory aliasing using global analysis. the output of our analysis is a control dataflow graph for the input specification. our results for sample designs show that the analysis can extract fine to coarse-grained concurrency for subsequent hardware-software partitioning and co-synthesis steps of the hardware-software co- design process to exploit.
jmtp: an architecture for exploiting concurrency in embedded java applications with real-time considerations. using java in embedded systems is plagued by problems of limited runtime performance and unpredictable runtime behavior. the java multi-threaded processor (jmtp) provides solutions to these problems. the jmtp architecture is a single chip containing an off-the-shelf general purpose processor core coupled with an array of java thread processors (jtps). performance can be improved using this architecture by exploiting coarse-grained parallelism in the application. these performance improvements are achieved with relatively small hardware costs. runtime predictability is improved by implementing a subset of the java virtual machine (jvm) specification in the jtp and trimming away complexity without excessively restricting the java code a jtp can handle. moreover, the jmtp architecture incorporates hardware to adaptively manage shared jmtp resources in order to satisfy jtp thread timing constraints or provide an early warning for a timing violation. this is an important feature for applications with quality-of-service demands. in addition to the hardware architecture, we describe a software framework that analyzes a java application for expressed and implicit coarse-grained concurrent threads to execute on jtps. this framework identifies the optimal mapping of an application to a jmtp with an arbitrary number of jtps. we have tested this framework on a variety of applications including idea encryption with different jtp configurations and confirmed that the algorithm was able to obtain desired results in each case.
clock scheduling and clocktree construction for high performance asics. in this paper we present a new method for clock schedulingand clocktree construction that improves the performance ofhigh-end asics significantly.first, we compute a clock schedule that yields the optimumcycle time and the best possible clock distribution with respectto early and late mode; in particular the number of criticaltests is minimized. second, individual arrival time intervalsare computed for all endpoints of the clocktree. finally, weconstruct a clocktree that realizes arrival times within theseintervals and exploits positive slacks to save power consumption.we demonstrate the superiority of our method to previousapproaches by experimental results on industrial asics withup to 194 000 registers and more than 160 clock domains. weimproved the clock frequencies by 5-28% up to 1.033 ghz (in hardware).
pattern generation for a deterministic bist scheme. recently a deterministic built-in self-test scheme has been presented based on reseeding of multiple-polynomial linear feedback shift registers. this scheme encodes deterministic test sets at distinctly lower costs than previously known approaches. in this paper it is shown how this scheme can be supported during test pattern generation. the presented atpg algorithm generates test sets which can be encoded very efficiently. experiments show that the area required for synthesizing a bist scheme that encodes these patterns is significantly less than the area needed for storing a compact test set. furthermore, it is demonstrated that the proposed approach of combining atpg and bist synthesis leads to a considerably reduced hardware overhead compared to encoding a conventionally generated test set.
an efficient procedure for the synthesis of fast self-testable controller structures. the bist implementation of a conventionally synthesized controller in most cases requires the integration of an additional register only for test purposes. this leads to some serious drawbacks concerning the fault coverage, the system speed and the area overhead. a synthesis technique is presented which uses the additional test register also to implement the system function by supporting self-testable pipeline-like controller structures. it will be shown, that if the need of two different registers in the final structure is already taken into account during synthesis, then the overall number of flipflops can be reduced, and the fault coverage and system speed can be enhanced. the presented algorithm constructs realizations of a given finite state machine specification which can be trivially implemented by a self-testable structure. the efficiency of the procedure is ensured by a very precise characterization of the space of suitable realizations, which avoids the computational overhead of previously published algorithms.
statistical timing analysis with two-sided constraints. based on a timing yield model, a statistical static timing analysis technique is proposed. this technique preserves existing methodology by selecting a "device file setting" that takes into account within-die statistical variations, and with which to run traditional static timing analysis in order to meet the desired yield. using process-specific "generic paths" representing critical paths in a given process technology, our approach can be used early in the design process, most importantly during the pre-placement phase. within-die variations are taken care of using a simple model that assumes positive correlation, which leads to upper and lower bounds on the timing yield. our approach also handles both setup and hold timing constraints.
a single-path-oriented fault-effect propagation in digital circuits considering multiple-path sensitization. various satisfiability problems in combinational logic blocks as, for example, test pattern generation, verification, and netlist optimization, can be solved efficiently by exploiting the fundamental concepts of propagation and justification. therefore, fault effect propagation gains further importance. for the first time, we provide the theoretical background for a single path oriented fault effect propagation considering both single and multiple path sensitization. we call this approach spop. furthermore, we formulate necessary and sufficient sensitization conditions for spop. from these conditions the best suited algebra for propagation can be derived. experimental results for stuck--at test pattern generation demonstrate that the new approach is orthogonal to d--frontier based methods. we achieve substantial improvements with respect to test pattern generation time and quality.
adaptation of partitioning and high-level synthesis in hardware/software co-synthesis. previously, we had presented the system cosyma for hardware/software co-synthesis of small embedded controllers. target system of cosyma is a core processor with application specific co-processors. the system speedup for standard programs compared to a single 33mhz risc processor solution with fast, single cycle access ram was typically less than 2 due to restrictions in high-level co-processor synthesis, and incorrectly estimated back end tool performance, such as hardware synthesis, compiler optimization and communication optimization. meanwhile, a high-level synthesis tool for high-performance co-processors in co-synthesis has been developed. this paper explains the requirements and the main features of the high-level synthesis sytem and its integration into cosyma. the results show a speedup of 10 in most cases. compared to the speedup, the co-processor size is very small.
formal specification and verification of a dataflow processor array. we describe the formal specification and verification of the vgi parallel dsp chip [1], which contains 64 compute processors with ~30k gates in each processor. our effort coincided in time with the &ldquo;informal&rdquo; verification stage of the chip. by interacting with the designers, we produced an abstract but executable specification of the design which embodies the programmer's view of the system. given the size of the design, an automatic check that even one of the 64 processors satisfies its specification is well beyond the scope of current verification tools. however, the check can be decomposed using assume-guarantee reasoning. for vgi, the implementation and specification operate at different time scales: several steps of the implementation correspond to a single step in the specification. we generalized both the assume-guarantee method and our model checker mocha to allow compositional verification for such applications. we used our proof rule to decompose the verification problem of the vgi chip into smaller proof obligations that were discharged automatically by mocha. using our formal approach, we uncovered and fixed subtle bugs that were unknown to the designers.
decomposing refinement proofs using assume-guarantee reasoning. model-checking algorithms can be used to verify, formally and automatically, if a low-level description of a design conforms with a high-level description. however, for designs with very large state spaces, prior to the application of an algorithm, the refinement-checking task needs to be decomposed into subtasks of manageable complexity. it is natural to decompose the task following the component structure of the design. however, an individual component often does not satisfy its requirements unless the component is put into the right context, which constrains the inputs to the component. thus, in order to verify each component individually, we need to make assumptions about its inputs, which are provided by the other components of the design. this reasoning is circular: component a is verified under the assumption that context b behaves correctly, and symmetrically, b is verified assuming the correctness of a. the assume-guarantee paradigm provides a systematic theory and methodology for ensuring the soundness of the circular style of postulating and discharging assumptions in component-based reasoning.we give a tutorial introduction to the assume-guarantee paradigm for decomposing refinement-checking tasks. to illustrate the method, we step in detail through the formal verification of a processor pipeline against an instruction set architecture. in this example, the verification of a three-stage pipeline is broken up into three subtasks, one for each stage of the pipeline.
sigma: a simulator for segment delay faults. lucent technologieswe propose an efficient combinational circuit simulation technique for the recently proposed segment delay fault model. after simulation of a vector pair, activated segments are traced using a depth-first search. a segment numbering scheme finds the number of faults to be simulated. a labeling technique generates edge labels to compute a unique label for each segment fault. the use of labels avoids explicit storing of fault lists and allows efficient access to previously detected segment faults. experimental results demonstrate several advantages of the segment delay fault model. first, the total number of faults remains manageable for small segment lengths. second, many segments, not included in any robustly testable path fault, may have robust segment delay fault tests. generating tests for such segments may increase the delay defect coverage.
fast identification of untestable delay faults using implications. we propose a novel algorithm to rapidly identify untestable delay faults using pre-computed static logic implications. our fault-independent analysis identifies large sets of untestable faults, if any, without enumerating them. the cardinalities of these sets are obtained by using a counting algorithm that has quadratic complexity in the number of lines. since our method is based on an incomplete set of logic implications, it gives only a lower bound of the number of untestable faults. a post-processing step can list the untestable faults, if desired. targeting untestable delay faults for test generation by an automatic test pattern generation (atpg) tool can be avoided. the method works on the segment delay fault model and its special case, the path delay fault model, to identify robustly untestable, non-robustly untestable, and functionally unsensitizable delay faults. results on benchmark circuits show that many delay faults are identified as untestable in a very short time. for the benchmark circuit c6288, our algorithm identified 1.978 x 10^20 functionally unsensitizable path faults in 3 cpu seconds.
improved interconnect sharing by identity operation insertion. this paper presents an approach to reduce interconnect cost by insertion of identity operations in a cdfg. other than previous approaches, it is based on systematic pattern analysis and automated transformation selection. the cost function controlling transformation selection is derived with statistical experiments and is optimized using practical benchmarks. the results show significantly reduced interconnect cost for most register architectures and application examples.
design of pipeline analog-to-digital converters via geometric programming. in this paper we present a method for the design of analog-todigital converters (adcs). this method computes the sizes of the different components (transistors, capacitors, etc.) in a predefined adc topology so that the design specifications are met in the desired process technology.the method is based on formulating the adc design constraints such as specifications on power, signal-to-noise ratio (snr), area, and sampling frequency in special convex form in terms of the component sizes of the adc and intermediate design variables. more specifically, we cast the problem of sizing the components of the adc as a geometric program. therefore, all design constraints are formulated as posynomial inequality or monomial equality constraints. very efficient numerical algorithms are then used to solve the resulting geometric program and to compute the component sizes of an adc that meets the desired specifications. the synthesis method is fast, and determines the globally optimal design; in particular the final solution is completely independent of the starting point (which can even be infeasible), and infeasible specifications are unambiguously detected.this paper introduces the concept of hierarchical problem formulation within a geometric programming framework. this modular formulation allows a high re-use of the adc posynomial model.
design and optimization of lc oscillators. we present a method for optimizing and automating component and transistor sizing for cmos lc oscillators. we observe that the performance measures can be formulated as posynomial functions of the design variables. as a result, the lc oscillator design problems can be posed as a geometric program, a special type of optimization problem for which very efficient global optimization methods have recently been developed. the synthesis method is therefore fast, and determines the globally optimal design; in particular the final solution is completely independent of the starting point (which can even be infeasible), and infeasible specifications are unambiguously detected. we can rapidly compute globally optimal trade-off curves between competing objectives such as phase noise and power.
energy efficient address assignment through minimized memory row switching. data transfer intensive applications consume a significant amount of energy in memory access. the selection of a memory location from a memory array involves driving row and column select lines. a signal transition on a row select line often consumes significantly more energy than a transition on a column select line. in order to exploit this difference in energy consumption of row and column select lines, we propose a novel address assignment methodology that aims to minimize high energy row transitions by assigning spatially and temporally local data items to the same row. the problem of energy efficient address assignment has been formulated as a multi-way graph partitioning problem and solved with a heuristic. our experiments demonstrate that our methodology achieves row transition counts very close to the optimum and that the methodology can, for some examples, reduce row transition count by 40--70% over row major mapping. moreover, we also demonstrate that our methodology is capable of handling access sequences with over 15 million accesses in moderate time.
model reduction of variable-geometry interconnects using variational spectrally-weighted balanced truncation. this paper presents a spectrally-weighted balanced truncation technique for rlc interconnects, a technique needed when the interconnect circuit parameters change as a result of variations in the manufacturing process. the salient features of this algorithm are the inclusion of parameter variations in the rlc interconnect, the guaranteed stability of the reduced transfer function, and the availability of provable frequency-weighted error bounds for the reduced-order system. this paper shows that the balanced truncation technique is an effective model-order reduction technique when variations in the circuit parameters are taken into consideration. experimental results show that the new variational spectrally-weighted balanced truncation attains, on average, 20% more accuracy than the variational krylov-subspace-based model-order reduction techniques while the run-time is also, on average, 5% faster.
lazy group sifting for efficient symbolic state traversal of fsms. this paper proposes lazy group sifting for dynamic variable re-ordering during state traversal. the proposed method relaxes the idea of pairwise grouping of present state variables and their corresponding next state variables. this is done to produce better variable orderings during image computation without causing bdd size blowup in the substitution of next state variables with present state variables at the end of image computation. experimental results show that our approach is more robust in state traversal than the approaches that either unconditionally group variable pairs or never group them.
boom - a heuristic boolean minimizer. we present a two-level boolean minimization tool (boom) based on a new implicant generation paradigm. in contrast to all previous minimization methods, where the implicants are generated bottom-up, the proposed method uses a top-down approach. thus instead of increasing the dimensionality of implicants by omitting literals from their terms, the dimension of a term is gradually decreased by adding new literals. unlike most other minimization tools like espresso, boom doesn't use the definition of the function to be minimized as a basis for the solution, thus the original coverage influences the solution only indirectly through the number of literals used.most minimization methods use two basic phases introduced by quine-mccluskey, known as prime implicant (pi) generation and the covering problem solution. some more modern methods, like espresso, combine these two phases, reducing the number of pis to be processed. this approach is also used in boom, the search for new literals to be included into a term aims at maximum coverage of the output function.the function to be minimized is defined by its on-set and off-set, listed in a truth table. thus the don't care set, often representing the dominant part of the truth table, need not be specified explicitly. the proposed minimization method is efficient above all for functions with a large number of input variables while only few care terms are defined.the minimization procedure is very fast, hence if the first solution does not meet the requirements, it can be improved in an iterative manner. the method has been tested on several different kinds of problems, like the mcnc standard benchmarks or larger problems generated randomly.
a fast crosstalk- and performance-driven multilevel routing system. in this paper, we propose a novel framework for fast multilevelrouting considering crosstalk and performance optimization. to handlethe crosstalk minimization problem, we incorporate an intermediatestage of layer/track assignment into the multilevel routing framework.for performance-driven routing, we propose a novel minimum-radiusminimum-cost spanning-tree (mrmcst) heuristic for global routing.compared with the state-of-the-art multilevel routing, the experimentalresults show that our approach achieved a 6.7x runtime speedup, reducedthe respective maximum and average crosstalk (coupling length)by about 30% and 24%, reduced the respective maximum and averagedelay by about 15% and 5%, and resulted in fewer failed nets.
interconnect scaling implications for cad. interconnect scaling to deep submicron processes presents many challenges to today's cad flows. a recent analysis by sylvester and keutzer examined the behavior of average length wires under scaling, and controversially concluded that current cad tools are adequate for future module-level designs. in our work, we show that average length wire scaling is sensitive to the technology assumptions, although the change in their behavior is small under all reasonable scaling assumptions. however, examining only average length wires is optimistic, since long wires are the ones that primarily cause cad tool exceptions. in a module of fixed complexity, under both optimistic and pessimistic scaling assumptions, the number of long wires will increase slowly with scaling. more importantly, as the overall die capacity grows exponentially, the number of modules and thus the total number of wires in a design, will also increase exponentially. thus, if the design team size and per-designer workload is to remain relatively constant, future cad tools will need to handle long wires much better than current tools to reduce the percentage of wires that require designer intervention.
smart simulation using collaborative formal and simulation engines. we present ketchum, a tool that was developed to improve the productivity of simulation-based functional verification by providing two capabilities: (1) automatic test generation and (2) unreachability analysis. given a set of "interesting" signals in the design under test (dut), automatic test generation creates input stimuli that drive the dut through as many different combinations (called coverage states) of these signals as possible to thoroughly exercise the dut. unreachability analysis identifies as many unreachable coverage states as possible.ketchum differs from the previous published results for several reasons. first, ketchum provides 10x higher capacity than previous published results. the higher capacity is achieved by carefully orchestrating simulation and multiple formal methods including symbolic simulation, sat-based bmc, symbolic fixpoint computation and automatic abstraction. second, ketchum performs not only automatic test generation but also unreachability analysis, which enables the test generation effort to be focused on coverage states that are not unreachable. third, the backbone of ketchum is an off-the-shelf commercial simulator. it enables ketchum to reach deep states of the design quickly and supports simulation monitors through the standard api of the simulator during test generation.we applied ketchum to several industrial designs, including the picojava microprocessor from sun and the dw8051 microcontroller from synopsys and obtained very promising results. the experiments show that ketchum can (1) handle design blocks containing more than 4500 latches and 170k gates, (2) reach up to 6x more coverage states than random simulation and (3) identify a majority of the unreachable coverage states.
synthesis of operation-centric hardware descriptions. most hardware description frameworks, whether schematic or textual, use cooperating finite state machines (cfsm) as the underlying abstraction. in the cfsm framework, a designer explicitly manages the concurrency by scheduling the exact cycle-by-cycle interactions between multiple concurrent state machines. design mistakes are common in coordinating interactions between two state machines because transitions in different state machines are not semantically coupled. it is also difficult to modify one state machine without considering its interaction with the rest of the system.this paper presents a method for hardware synthesis from an "operation centric" description, where the behavior of a system is described as a collection of "atomic" operations in the form of rules. typically, a rule is defined by a predicate condition and an effect on the state of the system. the atomicity requirement simplifies the task of hardware description by permitting the designer to formulate each rule as if the rest of the system is static.an implementation can execute several rules concurrently in a clock cycle, provided some sequential execution of those rules can reproduce the behavior of the concurrent execution. in fact, detecting and scheduling valid concurrent execution of rules is the central issue in hardware synthesis from operation-centric descriptions. the result of this paper shows that an operation-centric framework offers significant reduction in design time, without loss in implementation quality.
a methodology for the design of application specific instruction set processors (asip) using the machine description language lisa. the development of application specific instruction set processors (asip) is currently the exclusive domain of the semiconductor houses and core vendors. this is due to the fact that building such an architecture is a difficult task that requires expertise knowledge in different domains: application software development tools, processor hardware implementation, and system integration and verification. this paper presents a retargetable framework for asip design which is based on machine descriptions in the lisa language. from that, software development tools can be automatically generated including hll c-compiler, assembler, linker, simulator and debugger frontend. moreover, synthesizable hdl code can be derived which can then be processed by standard synthesis tools. implementation results for a low-power asip for dvb-t acquisition and tracking algorithms designed with the presented methodology will be given.
corner block list: an effective and efficient topological representation of non-slicing floorplan. in this paper, a corner block list -- a new efficient topological representation for non-slicing floorplan is proposed with applications to vlsi floorplan and building block placement. given a corner block list, it takes only linear time to construct the floorplan. unlike the o-tree structure, which determines the exact floorplan based on given block sizes, corner block list defines the floorplan independent of the block sizes. thus, the structure is better suited for floorplan optimization with various size configurations of each block. based on this new structure and the simulated annealing technique, an efficient floorplan algorithm is given. soft blocks and the aspect ratio of the chip are taken into account in the simulated annealing process. the experimental results demonstrate the algorithm is quite promising.
bus optimization for low-power data path synthesis based on network flow method. sub-micron feature sizes have resulted in a considerable portion of power to be dissipated on the buses, causing an increased attention on savings for power at the behavioral level and rt level of design. this paper addresses the problem of minimizing power dissipated in switching of the buses in data path synthesis. unlike the previous approaches in which minimization of the power consumed in buses has not been considered until operation scheduling is completed, our approach integrates the bus binding problem into scheduling to exploit the impact of scheduling on reduction of power dissipated on the buses more fully and effectively. we accomplish this by formulating the problem into a flow problem in a network, and devising an efficient algorithm which iteratively finds maximum flow of minimum cost solutions in the network. experimental results on a number of benchmark problems show that given resource and global timing constraints our designs are 22% power-efficient over the designs produced by a random-move based solution, and 18% power-efficient over the designs by a clock-step based optimal solution.
power optimization in disk-based real-time application specific systems. while numerous power optimization techniques have been proposed at all levels of design process abstractions for electronic components, until now, power minimization in mixed mechanical-electronic subsystems, such as disks, has not been addressed. we propose a conceptually simple, but realistic power consumption model for disk drives. we present heuristics for optimization of power consumption in several common hard real-time disk-based design systems. we show how to coordinate task scheduling and disk data assignment, in order to minimize power consumption in both electronic and mechanical components of used disks. extensive experimental results indicate significant power reduction.
throughput optimization of general non-linear computations. this paper addresses an optimal technique for throughput optimization of general non-linear data flow computations using a set of transformations. throughput is widely recognized as the most important design metric of the modern dsp and communication applications. numerous approaches have been proposed for throughput optimization, but most was restricted to limited classes of computations. they have limited effectiveness when applied to large complex non-linear dsp and communication computations. the new technique is used as an optimization engine in a divide-and-conquer global approach for throughput optimization. we demonstrate the effectiveness of the new technique on numerous real-life non-linear designs.
power optimization using divide-and-conquer techniques for minimization of the number of operations. we develop an approach to minimizing power consumption of portable wireless dsp applications using a set of compilation and architectural techniques. the key technical innovation is a novel divide-and-conquer compilation technique to minimize the number of operations for general dsp computations. our technique optimizes not only a significantly wider set of computations than the previously published techniques, but also outperforms (or performs at least as well as other techniques) on all examples. along the architectural dimension, we investigate coordinated impact of compilation techniques on the number of processors which provide optimal trade-off between cost and power. we demonstrate that proper compilation techniques can significantly reduce power with bounded hardware cost. the effectiveness of all techniques and algorithms is documented on numerous real-life designs.
a novel dimension reduction technique for the capacitance extraction of 3d vlsi interconnects. in this paper, we present a new capacitance extraction method named dimension reduction technique (drt) for 3d vlsi interconnects. the drt converts a complex 3d problem into a series of cascading simple 2d problems. each 3d problem is solved separately, so we can choose the most efficient method according to the arrangement of conductors. more importantly, it is very easy to obtain the analytical solutions of 2d problem in many layers such as the pure dielectric layers and the layers with parallel signal lines. therefore, the domain that has to be analyzed numerically is minimized. this leads to the drastic reduction of the computing time and memory needs. we have used the drt to extract the capacitances of multilayered and multiconductor cross-overs, bends, via with signal lines and open-end. the results are in good agreement with those of ansoft's spicelink and mit's fastcap, but the computing time and memory size used by the drt are several even tens times less than those used by spicelink and fastcap.
factoring and eliminating common subexpressions in polynomial expressions. polynomial expressions are used to compute a wide variety of mathematical functions commonly found in signal processing and graphics applications, which provide good opportunities for optimization. however existing compiler techniques for reducing code complexity such as common subexpression elimination and value numbering are targeted towards general purpose applications and are unable to fully optimize these expressions. this work presents algorithms to reduce the number of operations to compute a set of polynomial expression by factoring and eliminating common subexpressions. these algorithms are based on the algebraic techniques for multi-level logic synthesis. experimental results on a set of benchmark applications with polynomial expressions showed an average of 42.5% reduction in the number of multiplications and 39.6% reduction in the number of clock cycles for computation of these expressions on the arm processor core, compared to common subexpression elimination.
effects of delay models on peak power estimation of vlsi sequential circuits. previous work has shown that maximum switching density at a given node is extremely sensitive to a slight change in the delay at that node. however, when estimating the peak power for the entire circuit, the powers estimated must not be as sensitive to a slight variation or inaccuracy in the assumed gate delays because computing the exact gate delays for every gate in the circuit during simulation is expensive. thus, we would like to use the simplest delay model possible to reduce the execution time for estimating power, while making sure that it provides an accurate estimate, i.e., that the peak powers estimated will not vary due to a variation in the gate delays. results for four delay models are reported for the iscas85 combinational benchmark circuits, iscas89 sequential benchmark circuits, and several synthesized circuits.
synchronous equivalence for embedded systems: a tool for design exploration. this paper presents a new protocol for parallel and distributed simulation of vlsi systems. it is novel in two aspects: first, it combines optimistic and conservative synchronization methods, allowing processes to self-adapt for maximal utilization of concurrency. second, it does not require any application-dependent information like lookahead, which in many cases is unknown, zero, or difficult to automatically obtain from a design in a hardware description language. all these features make it very convenient and practical, extending the class of applications to at least all vhdl circuits, including delta cycle. the proposed protocol has been implemented and used for vhdl simulation. experimental results on several large vhdl circuits (between 1411 and 14704 processes) have shown promising linear speedups. we also observed that the dynamic synchronization, in which processes automatically adapt to optimistic or conservative behavior, follows closely or finds a very good configuration. this protocol may have a string impact for mixed-signal circuit simulation, where digital parts may be optimistic and heavy-state analog parts, conservative.
a vectorless estimation of maximum instantaneous current for sequential circuits. both the ir drop and em problems require accurate analysis of maximum instantaneous current (mic) on the power supply bus. we propose a vectorless approach to deriving a tight upper bound on mic. we first characterize different types of signal correlation which may cause the mic estimation to lose accuracy. we next propose theorems to identify gates which switch mutually exclusively, taking into account correlation across sequential elements (flip-flops). note that previous research of this topic addressed on combinational circuits only. after obtaining the information of mutually exclusive switching, we then apply a graph algorithm to obtain an upper bound on mic. in average, our results on sequential benchmarks are 212% tighter than those from imax and 129% tighter than those from pie based on h. kriplani et al. (1995).
statistical sampling and regression analysis for rt-level power evaluation. in this paper, we propose a statistical power evaluation framework at the rt-level. we first discuss the power macro-modeling formulation, and then propose a simple random sampling technique to alleviate the the overhead of macro-modeling during rtl simulation. next, we describe a regression estimator to reduce the error of the macro-modeling approach. experimental results indicate that the execution time of the simple random sampling combined with power macro-modeling is 50 x lower than that of conventional macro-modeling while the percentage error of regression estimation combined with power macro-modeling is 16 x lower than that of conventional macro-modeling. hence, we provide the designer with options to either improve the accuracy or the execution time when using power macro-modeling in the context of rtl simulation.
enhancing high-level control-flow for improved testability. in this study, we present a controllability measure for high-level circuit descriptions and a high-level synthesis-for-testability technique. unlike many recent studies in the area of high-level synthesis for testability that focus on improving the testability of data paths, the objective of our approach is to improve the testability of synthesized circuits by enhancing the controllability of the control flow. experimental results on several high-level synthesis benchmarks show that when this approach is used prior to logic synthesis, a shorter atpg time, a smaller test set, and better fault coverage and atpg efficiency are often achieved. implementation of this technique requires minimal logic and performance overheads and allows test vectors to be applied at clock-speed.
a precorrected-fft method for simulating on-chip inductance. the simulation of on-chip inductance using peec-based circuit analysis methods often requires the solution of a subproblem where an extracted inductance matrix must be multiplied by a current vector, an operation with a high computational cost. this paper presents a highly accurate technique, based on a precorrected-fft approach, that speeds up this calculation. instead of computing the inductance matrix explicitly, the method exploits the properties of the inductance calculation procedure while implicitly considering the effects of all of the inductors in the layout. an optimized implementation of the method has been applied to accurately simulate large industrial circuits with up to 121,000 inductors and nearly 7 billion mutual inductive couplings in about 20 minutes. techniques for trading off the cpu time with the accuracy using different approximation orders and grid constructions are also illustrated. comparisons with a block diagonal sparsification method in terms of accuracy, memory and speed demonstrate that our method is an excellent approach for simulating on-chip inductance in a large circuit.
efficient generation of monitor circuits for gste assertion graphs. generalized symbolic trajectory evaluation (gste) is a powerful,new method for formal verification that combines the industrially-provenscalability and capacity of classical symbolic trajectoryevaluation with the expressive power of temporal-logic modelchecking. gste was originally developed at intel and hasbeen used successfully on intel's next-generation microprocessors.however, the supporting algorithms and tools for gste are stillrelatively immature.gste specifications are given as assertion graphs, an extensionof ¿-automata. this paper presents a linear-time, linear-size translationfrom gste assertion graphs into monitor circuits, which canbe used with dynamic verification both as a quick "sanity check" ofthe specification before effort is invested in abstraction and formalverification, and also as means to reuse gste specifications withother validations methods. we present experimental results usingreal gste assertion graphs for real industrial circuits, showing thatthe circuit construction procedure is efficient in practice and that themonitor circuits impose minimal simulation overhead.
application-specific buffer space allocation for networks-on-chip router design. we present a system-level buffer planning algorithm that can be used to customize the router design in networks-on-chip (nocs). more precisely, given the traffic characteristics of the target application and the buffering space budget, our algorithm automatically assigns the buffer depth for each input channel, in different routers across the chip, to match the communication pattern, such that the overall performance is maximized. this is in deep contrast with the uniform assignment of buffering resources (currently used in noc design) which can significantly degrade the overall system performance. for instance, for a complex audio/video application, about 85% savings in buffering resources can be achieved by smart buffer allocation using our algorithm without any reduction in performance.
optimum loading dispersion for high-speed tree-type decision circuitry. with increasing density and capacity due to technology scaling, augmenting data (especially in semiconductor memories) burden selection circuitry with exponentially growing capacitive loads. this tendency violates stringent timing requirements.this work ameliorates the situation for k-stage tree-type decision circuitry. we show that for a k-stage binary decision tree, there always exists an optimum solution such that, after the select-signal arrangement, the worst case loading among select signals equals a lower bound. our proposed procedure not only provides an optimum solution but also minimizes the loading variance. the worst case loading can be reduced up to nearly k/2 times, thus speeding up and saving power up to k/2 times or so for the select signal with the heaviest loading. in contrast, excluding one unit-loading select signal, the empirical variance of the remaining (k - 1) signals is always less than 1 instead of diverging. hence, our approach, for timing-driven layout synthesis, is competent to design high-performance tree-type decision circuitry with more accurate timing and power prediction. in addition, by the presented approach, we can have the alternative of optimizing either for k-stage or for (k-1)-stage, meanwhile possibly minimizing the other. our algorithm, also, can easily be extended for a general k-stage decision tree with r descendants per node, not restricted to a binary tree; the resultant worst case loading could be quite close to the lower bound and reduced up to nearly k(r - 1)/r times.
a timing-constrained algorithm for simultaneous global routing of multiple nets. in this paper, we propose a new approach for vlsi interconnect global routing that can optimize both congestion and delay, which are often competing objectives. our approach provides a general framework that may use any single-net routing algorithm and any delay model in global routing. it is based on the observation that there are several routing topology flexibilities under timing constraints. these flexibilities are exploited for congestion reduction through a network flow based hierarchical bisection and assignment process. experimental results on benchmark circuits are quite promising.
on breakable cyclic definitions. in the course of hardware system design or real-time process control, high-level specifications may contain simultaneous definitions of concurrent modules whose information flow forms cyclic dependencies without the separation of state-holding elements. the temporal behavior of these cyclic definitions may be meant to be combinational rather than sequential. most prior approaches to analyzing cyclic combinational circuits were built upon the formulation of ternary-valued simulation at the circuit level. this work shows the limitation of this formulation and investigates, at the functional level, the most general condition where cyclic definitions are semantically combinational. it turns out that the prior formulation is a special case of our treatment. our result admits strictly more flexible high-level specifications. furthermore, it allows a higher-level analysis of combinationality, and, thus, no costly synthesis of a high-level description into a circuit netlist before combinationality analysis can be performed. with our formulation, when the target is software implementations, combinational cycles need not be broken as long as the execution of the underlying system obeys a sequencing execution rule. for hardware implementations, combinational cycles are broken and replaced with acyclic equivalents at the functional level to avoid malfunctioning in the final physical realization.
fast-yet-accurate pvt simulation by combined direct and iterative methods. the operations and performances of deep-submicron integrated circuits are affected significantly by the variations of process parameters, power supply voltages and operating temperatures. circuit simulation for all the combinations of process-voltage-temperature (pvt) conditions, known as pvt simulation, is emerging as a must not only for analog and rf circuit designs, but also for the designs of digital library cells and critical paths. with the number of pvt conditions in the range of hundreds and even thousands, existing solution of invoking a simulator repeatedly for all these pvt conditions is becoming extremely time consuming. this paper presents a new simulation approach capable of simulating hundreds and thousands pvt corners with the computational cost comparable to or even less than that of a few corner simulations, yet with the same simulation accuracy and robustness. the proposed approach is based on the combination of the lu-factorization based direct method and krylov subspace based iterative methods to explore the common characteristics shared by a circuit under all pvt corners. the key novelty is a systematic method that uses as few lu based direct solving as possible for underlying linearized systems, and then solves the rest of linearized systems across the entire pvt linear system space using krylov subspace based iterative methods with preconditioners computed from those lu factors.
forward model checking techniques oriented to buggy designs. forward model checking is an efficient symbolic model checking method for verifying realistic properties of sequential circuits and protocols. in this paper, we present the techniques that modify the order of state traversal on forward model checking, and that dramatically improve average cpu time for finding design errors. a failing property has to be checked again and again to analyze the bug until it is corrected. the techniques, therefore, can have significant impacts on actual verification tasks. we use a modified regular/omega-regular expression to represent a set of illegal state transition sequences of an fsm. it makes the problem clear and gives us a sense of depth-first traversal, not on the state space, but on the property.
approaching the maximum energy saving on embedded systems with multiple voltages. dynamic voltage scaling (dvs) is arguably the most effectiveenergy reduction technique. the multiple-voltage dvs systems,which can operate only at pre-determined discrete voltages, arepractical and have been well studied. however, one importantunsolved problem is how many levels and at which values shouldvoltages be implemented on a multiple-voltage dvs system toachieve the maximum energy saving. we refer this as the voltageset-up problem. in this paper, (1) we derive analytical solutionsfor dual-voltage system. (2) for the general case that does nothave analytic solutions, we develop efficient numerical methods.(3) we demonstrate how to apply the proposed algorithms onsystem design. (4) interestingly, the experimental results suggestthat the multiple-voltage dvs system, when the voltages are setup properly, can reach dvs techniqueýs full potential in energysaving. specifically, on the design of an ad hoc application-specificsystem and the design of the mpeg video encoder, wefind that the best single-voltage systems consume 150% and 20%more energy than the tight theoretical lower bounds, respectively.however, our approach gives dual-, 3-, and 4-voltage dvs systemsettings that are only 17.6%, 4.9%, and 2.6% for the ad hocsystem, and 4.0%, 1.1%, and 0.2% for the mpeg video encoder,over the same lower bounds.
automatic test program generation for pipelined processors. simulation-based verification has both advantages and disadvantages compared with formal verification. our demand is to find a practical way to verify actual microprocessors. this paper presents an efficient test program generation method for simulation-based verification using techniques developed for formal verification. our test program generator enumerates all reachable states of a processor pipeline and generates instruction sequences for every reachable test care. the program covers complicated test cases that are difficult to cover with random instructions and impossible to cover with conventional test program generation methods. our test program generator also works for larger microprocessor designs than formal verifiers have done.
ctl model checking based on forward state traversal. we present a ctl model checking algorithm based mainly on forward state traversal, which can check many realistic ctl properties without doing backward state traversal. this algorithm is effective in many situations where backward state traversal is more expensive than forward state traversal. we combine it with bdd-based state traversal techniques using partitioned transition relations. experimental results show that our method can verify actual ctl properties of large industrial models which cannot be handled by conventional model checkers.
generating instruction sets and microarchitectures from applications. the design of application-specific instruction set processor(asip) system includes at least three interdependent tasks: microarchitecture design, instruction set design, and instruction set mapping for the application. we present a method that unifies these three design problems with a single formulation: a modified scheduling/allocation problem with an integrated instruction formation process. micro-operations (mops) representing the application are scheduled into time steps. instructions are formed and hardware resources are allocated during the scheduling process. the assembly code for the given application is obtained automatically at the end of the scheduling process. this approach considers mop parallelism, instruction field encoding, delay load/store/branch, conditional execution of mops and the retargetability to various architecture templates. experiments are presented to show the power and limitation of our approach. performance improvement over our previous work is significant.
metamorphosis: state assignment by retiming and re-encoding. this paper presents metamorphosis -- a novel technique for optimal state assignment targeting multi-level logic implementations. we present an elegant matrix formulation and a graph partitioning based synthesis technique which permits both bit-constrained and unconstrained encoding of a symbolic finite state machine (fsm) represented initially with a one-hot code. optimal state encoding is achieved by controlled retiming/re-encoding and resynthesis of the symbolic fsm. the synthesis is guided directly by the cost function (optimization criterion) rather than speculative estimates of the encoding heuristics on the final design cost. the technique is illustrated through performance driven synthesis of fsm and extensions to handle other cost metrics is outlined.
compatible class encoding in roth-karp decomposition for two-output lut architecture. roth-karp decomposition is one of the most popular techniques for lut-based fpga technology mapping because it can decompose a node into nodes with fewer numbers of fanins. in this paper, we show how to formulate the compatible class encoding problem in roth-karp decomposition as a symbolic-output encoding problem in order to exploit the feature of the two-output lut architecture. based on this formulation, we also develop an encoding algorithm to minimize the number of lut's required to implement the logic circuit. experimental results show that our encoding algorithm can produce promising results in the logic synthesis environment for the two-output lut architecture.
an iterative area/performance trade-off algorithm for lut-based fpga technology mapping. in this paper, we propose an iterative area/performance trade-off algorithm for lut-based fpga technology mapping. first, it finds an area-optimized performance-considered initial network by a modified area optimization technique. then, an iterative algorithm consisting of several resynthesizing techniques is applied to trade the area for the performance in the network gracefully. experimental results show that this approach can provide a complete set of mapping solutions from the area-optimized one to the performance-optimized one for the given design. furthermore, these two extreme solutions, the area-optimized one and the performance-optimized one, produced by our algorithm outperform the results of most existing algorithms. therefore, our algorithm is very useful for the timing driven fpga synthesis.
phantom redundancy: a high-level synthesis approach for manufacturability. abstract: phantom redundancy, an area-efficient technique for fabrication-time reconfigurability is presented. phantom redundancy adds extra interconnect so as to render the resulting microarchitecture reconfigurable in the presence of any (single) functional unit failure. the proposed technique yields partially good chips in addition to perfect chips. a genetic algorithm is used to incorporate phantom redundancy constraints into microarchitecture synthesis. the algorithm minimizes tire performance degradation due to any faulty functional unit of the resulting microarchitecture. the effectiveness of the technique is illustrated on benchmark examples.
clock period minimization of non-zero clock skew circuits. it is known that the clock skew can be exploited as a manageableresource to improve the circuit performance. however, due to thelimitation of race condition, the optimal clock skew schedulingdoes not achieve the lower bound of the clock period. in thispaper, we propose a polynomial time complexity algorithm, whichincorporates optimal clock skew scheduling and delay insertion,for the synthesis of non-zero clock skew circuits. the mainadvantages of our algorithm include two parts. first, it guaranteesto achieve the lower bound of the clock period. secondly, it alsotries to minimize the required inserted delays under the lowerbound of the clock period. experimental data shows that, eventhough we only use the buffers in a standard cell library toimplement the delay insertion, our approach still works well.
power efficiency of voltage scaling in multiple clock, multiple voltage cores. due to increasing clock speeds, increasing design sizes and shrinking technologies, it is becoming more and more challenging to distribute a single global clock throughout a chip. in this paper we study the effect of using a globally asynchronous locally synchronous (gals) organization for a superscalar, out-of-order processor, both in terms of power and performance. to this end, we propose a novel modeling and simulation environment for multiple clock cores with static or dynamically variable voltages for each synchronous block. using this design exploration environment we were able to assess the power/performance tradeoffs available for multiple clock, single voltage (mcsv), as well as multiple clock, dynamic voltage (mcdv) cores. our results show that mcsv processors are 10% more power efficient when compared to single-clock single voltage designs with a performance penalty of about 10%. by exploiting the flexibility of independent dynamic voltage scaling the various clock domains, the power efficiency of gals designs can be improved by 12% on average, and up to 20% more in select cases. the power efficiency of mcdv cores becomes comparable with the one of single clock, dynamic voltage (scdv) cores, while being up to 8% better in some cases. our results show that mcdv cores consume 22% less power at an average 12% performance loss.
improving the proportion of at-speed tests in scan bist. a method to select the lengths of functional sequences in a bist scheme for scan designs is proposed in this paper. a functional sequence is a sequence of primary input vectors applied when the circuit operates as a sequential circuit, without using scan. these sequences can be applied at-speed, i.e., at the normal circuit clock speed. the objectives set for choosing the lengths of the functional sequences are to increase the number of vectors applied at-speed, and to reduce the number of settings of functional sequence lengths, without compromising the fault coverage achieved. the experimental results presented demonstrate that compared to earlier methods, the proposed method achieves the above objectives while also achieving higher fault coverages for most of the benchmark circuits considered.
satori - a fast sequential sat engine for circuits. we describe the design and implementation of satori - a fast sequentialjustification engine based on state-of-the-art sat and atpg techniques.we present several novel techniques that propel satori to ademonstrable 10x improvement over a commercial engine. traditionalsequential justification based on atpg or, on a bounded model of thesequential circuit using sat, has diverging strengths and weaknesses. inthis paper, we contrast these techniques and describe how their strengthsare combined in satori. we use conflict-based learning in each time-frameand illegal state learning across time-frames. this enables bothcombinational and sequential back-jumping. we experimentally analyzethe main features of satori by comparing satori's performanceagainst a state-of-the-art sat solver - zchaff using a boundedmodel, and a commercial sequential atpg engine performing justification.additional results are presented for satori versus the commercialatpg engine and vis on iscas ý89 and itc'99 benchmark circuitsfor an application to assertion checking.
achieving fast and exact hazard-free logic minimization of extended burst-mode gc finite state machines. this paper presents a new approach to two-level hazard-free logic minimization in the context of extended burst-mode finite state machine synthesis targeting generalized c-elements (gc). no currently available minimizers for literal-exact two-level hazard-free logic minimization of extended burst-mode gc controllers can handle large circuits without synthesis times ranging up over thousands of seconds. even existing heuristic approaches take too much time when iterative exploration over a large design space is required and do not yield minimum results. the logic minimization approach presented in this paper is based on state graph exploration in conjunction with single-cube cover algorithms, an approach that has not been considered for minimization of extended burst-mode finite state machines previously. our algorithm achieves very fast logic minimization by introducing compacted state graphs and cover tables and an efficient single-cube cover algorithm for single-output minimization. our exact logic minimizer finds minimal number of literal solutions to all currently available benchmarks, in less than one second on a 333 mhz microprocessor -- more than three orders of magnitude faster than existing literal exact methods, and over an order of magnitude faster than existing heuristic methods for the largest benchmarks. this includes a benchmark that has never been possible to solve exactly in number of literals before.
high-level synthesis of distributed logic-memory architectures. with the increasing cost of global communication on-chip, high-performance designs for data-intensive applications require architectures that distribute hardware resources (computing logic, memories, interconnect, etc.) throughout a chip, while restricting computations and communications to geographic proximities. in this paper, we present a methodology for high-level synthesis (hls) of distributed logic-memory architectures, i.e., architectures that have logic and memory distributed across several partitions in a chip. conventional hls tools are capable of extracting parallelism from a behavior for architectures that assume a monolithic controller/datapath communicating with a memory or memory hierarchy. this work provides techniques to extend the synthesis frontier to more general architectures that can extract both coarse- and fine-grained parallelism from data accesses and computations in a synergistic manner. our methodology selects many possible ways of organizing data and computations, carefully examines the trade-offs (i.e., communication overheads, synchronization costs, area overheads) in choosing one solution over another, and utilizes conventional hls techniques for intermediate steps.we have evaluated the proposed framework on several benchmarks by generating register-transfer level (rtl) implementations using an existing commercial hls tool with and without our enhancements, and by subjecting the resulting rtl circuits to logic synthesis and layout. the results show that circuits designed as distributed logic-memory architectures using our framework achieve significant (upto, 5.31x average of 3.45x) performance improvements over well-optimized conventional designs with small area overheads (upto 19.3%, 15.1% on average).
a formal basis for design process planning and management. in this paper we present a design formalism that allows for a complete and general characterization of design disciplines and for a unified representation of arbitrarily complex design processes. this formalism has been used as the basis for the development of several prototype cad meta-tools that offer effective design process planning and management services.
synthesis of heterogeneous distributed architectures for memory-intensive applications. memory-intensive applications present unique challenges to an asicdesigner in terms of the choice of memory organization, memory size requirements,bandwidth and access latencies, etc. the high potential of single-chip distributed logic-memory architectures in addressing many of these issues has been recognized ingeneral-purpose computing, and more recently in asic design. however, such architectureswill be adopted widely by designers only when general techniques and toolsfor efficient high-level synthesis (hls) of multi-partitioned asics become available.the techniques presented in this paper are motivated by the fact that many memory-intensiveapplications exhibit irregular array data access patterns (due to conditionalsin loop nests, etc.). synthesis should, therefore, be capable of determining a partitionedarchitecture, wherein array data and computations may have to be heterogeneouslydistributed for achieving the best performance speedup. furthermore, the synthesismethodology should not be restricted by the nature of array index functions (affine orotherwise) in a behavior. therefore, our methodology employs simulation to provideinformation about the access patterns of array data references in a behavior, which isused by the rest of our analysis. we use a combination of clustering and min-cut stylepartitioning techniques to partition the behavior into sub-behaviors while consideringvarious factors including data access locality, balanced workloads, inter-partitioncommunication, etc. finally, we also employ an iterative improvement strategy to determinethe best way of distributing array data into physical memory in each partition.our experiments with several benchmark applications show that the proposed techniquescan yield partitioned architectures that can achieve upto 2.2x performancespeed-up over conventional hls solutions, while achieving upto 1.6x performancespeedup over the best homogeneous partitioning solution feasible.
lower bound on latency for vliw asip datapaths. traditional lower bound estimates on latency for dataflow graphs assume no data transfer delays. while such approaches can generate tight lower bounds for datapaths with a centralized register file, the results may be uninformative for datapaths with distributed register file structures that are characteristic of vliw asips. in this paper we propose a latency bound that accounts for such data transfer delays. the novelty of our approach lies in construction the "window dependency graph" and bounds associated with the problem which capture delay penalties due to operation serialization and/or data moves among distributed register files. through a set of benchmark examples, we show that the bound is competitive with state-of-the-art approaches. moreover, our experiments show that the approach can aid an iterative improvement algorithm in determining good functional unit assignment ?-- a key step in code generation for vliw asips.
high-level synthesis using computation-unit integrated memories. high-level synthesis (hls) of memory-intensive applications has featured several innovations in terms of enhancements made to the basic memory organization and data layout. however, increasing performance and energy demands faced by application-specific integrated circuits (asic) are forcing designers to alter the fundamental architectural template of the hls output, namely, a controller-datapath associated with a memory subsystem (monolithic, banked, etc.). we propose an architectural template for the hls output that consists of a controller-datapath circuit associated with a memory subsystem into which computation units have been integrated. the enhanced memory subsystem is called computation-unit integrated memory (cim). a cim offers higher memory bandwidth (relative to what is offered through the system bus) to computation units present locally within it and reduces the overall communication between the memory subsystem and the controller-datapath, thus providing a template highly suitable for deriving efficient implementations of memory-intensive applications. this work addresses the challenge of providing an automatic synthesis framework for a cim-based architecture. our framework can analyze the various trade-offs involved in selecting suitable operations in a behavior for execution using a cim and generate a high-performance, low-overhead implementation. experiments with several behaviors indicate that an average performance improvement of 1.88/spl times/ (a maximum of 2.63/spl times/) is possible with very low area overheads. the energy-delay product improves by an average of 2.1/spl times/ (maximum of 3.4/spl times/).
exploring performance tradeoffs for clustered vliw asips. vliw asips provide an attractive solution for increasingly pervasive real-time multimedia and signal processing embedded applications. in this paper we propose an algorithm to support trade-off exploration during the early phases of the design/specialization of vliw asips with clustered datapaths. for purposes of an early exploration step, we define a parameterized family of clustered datapaths d(m,n), where m and n denote interconnect capacity and cluster capacity constraints on the family. given a kernel, the proposed algorithm explores the space of feasible clustered datapaths and returns: a datapath configuration; a binding and scheduling for the operations; and a corresponding estimate for the best achievable latency over the specified family. moreover, we show how the parameters m and n, as well as a target latency optionally specified by the designer, can be used to effectively explore trade-offs among delay, power/energy, and latency. extensive empirical evidence is provided showing that the proposed approach is strikingly effective at attacking this complex optimization problem.
analysis and evaluation of a hybrid interconnect structure for fpgas. in this paper, a cluster-based fpga is proposed. the proposed fpga has a hybrid interconnect structure which takes advantages of both mesh and tree topologies. we analyze the area and performance of proposed fpga in terms of the needed switches by comparing with those of conventional fpgas. we evaluate the proposed architecture on a series of benchmark designs. the experimental results show that the proposed model can significantly reduce the routing area, achieve high performance and admit more implementations of various designs at the price of a modest increase of switches required for that architecture.
efficient partitioning and analysis of digital cmos-circuits. a library independent method for the partitioning and analysis of switch-level cmos circuits is presented. this method is superior to the existing methods for extraction, because it is able to recognize cmos tristate drivers connected to a bus individually. moreover, it can improve the state-of-the-art algorithms for the determination of unidirectional signal flow, because its functional analysis is able to recognize groups of transistors which always constitute signal sources. the local functional analysis of the partitions is improved by the exclusion of impossible paths. additionally, the recognition of fully complementary gates allows the improvement of existing algorithms for signal flow analysis
mongrel: hybrid techniques for standard cell placement. we give an overview of a standard-cell placer mongrel. the prototype tool adopts a middle-down methodology in which a grid is imposed over the layout area and cells are assigned to bins forming a global placement. the optimization technique applied in this phase is based on the relaxation-based local search (rbls) framework in which a combinatorial search mechanism is driven by an analytical engine. this enables a more global view of the problem and results in complex modifications of the placement in a single search "move". details of this approach including a novel placement legalization procedure are presented. when a global placement has converged, a detailed placement is formed and further optimized by the proposed optimal interleaving technique. experimental results are presented and are quite promising, demonstrating that there is significant room for improvement in state of the art placement.
physical placement driven by sequential timing analysis. traditional timing-driven placement considers only combinational delays and does not take into account the potential of subsequent sequential optimization steps. as a result, the potential of re-balancing path delays through post-placement applications of clock skew scheduling and in-place retiming cannot be fully realized. in this paper we describe a new placement algorithm that is based on a tight integration of sequential timing analysis in the inner loop of an analytic solver. instead of minimizing the maximum path delay, our approach minimizes the maximum mean delay on any circuit loop, thus enabling the full optimization potential of clock skew scheduling and in-place retiming. we present two versions of the new algorithm: one approximates sequential criticality and weights wires accordingly (cong and lim, 2000), the other extends this with the inclusion of explicit wire-length constraints for loops that limit the final clock period. our algorithms are implemented using a hybrid, gordlan-style sequence of analytical placement steps interleaved with cell partitioning (kleinhans et al., 1988). our experiments on a set of large industrial designs demonstrate that the presented placement algorithm can minimize the contribution of interconnection delays to the clock period on average by 23.5% compared to a solution based on combinational delays.
accurate delay computation for noisy waveform shapes. in this paper we present a new gate delay model for accurate modeling of difficult waveform shapes, such as those resulting from coupling capacitance noise, inductive ringing and resistive shielding. our modeling approach uses a process of time shifting and time stretching of a set of so-called base-waveforms. these base-waveforms are selected from a large set of noisy waveform shapes that occur in interconnect structures with coupling and other types of noise, such that the delay error across all considered waveforms is minimized. depending on the desired accuracy one or more base-waveforms can be used. this method is also used to model the gate output waveforms allowing for closure, in terms of the used base-waveforms across a circuit library. we show that the determination of the optimal set of base-waveforms under such input-to-output closure is exponential in complexity. we, therefore, propose an heuristic approach that maps the problem to the unate covering problem for which efficient solution methods are available. the new delay model can be applied in a timing analysis program with minor changes. we present results that demonstrate the accuracy of the new delay model for waveforms perturbed with noise for a large set of waveform shapes.
software-assisted cache replacement mechanisms for embedded systems. we address the problem of improving cache predictability and performance in embedded systems through the use of software-assisted replacement mechanisms. these mechanisms require additional software controlled state information that affects the cache replacement decision. software instructions allow a program to kill a particular cache element, i.e., effectively make the element the least recently used element, or keep that cache element, i.e., the element will never be evicted.we prove basic theorems that provide conditions under which kill and keep instructions can be inserted into program code, such that the resulting performance is guaranteed to be as good as or better than the original program run using the standard lru policy. we developed a compiler algorithm based on the theoretical results that, given an arbitrary program, determines when to perform software-assisted replacement, i.e., when to insert either a kill or keep instruction. empirical evidence is provided that shows that performance and predictability (worst-case performance) can be improved for many programs.
fast simulation of vlsi interconnects. this work introduces an efficient and accurate interconnect simulation technique. a new formulation for typical vlsi interconnect structures is proposed which, in addition to providing a compact set of modeling equations, also offers a potential for exploiting sparsity at the simulation level. simulations show that our approach can achieve 50 /spl times/ improvement in computation time and memory over inductwise (which in turn has been shown to be 400 /spl times/ faster than spice) while preserving simulation accuracy.
on interactions between routing and detailed placement. the main goal of this work is to develop deeper insights into viable placement-level optimization of routing. two primary contributions are made. first, an experimental framework in which the viability of predictive models of routing congestion for optimization during detailed placement can be evaluated, is developed. the main criteria of consideration in these experiments is how (un)reliably various models from the literature detect routing hot-spots. we conclude that such models appear to be too unreliable for detailed placement optimization. second, motivated by the first result, we present a unified combinatorial framework in which cell placement and exact routing structures are captured and optimized; the framework relies on the trunk-decomposition of global routing structures and optimization is performed by a generalized optimal interleaving algorithm (hur and lillis, 2000). a proof of concept implementation of this framework is studied in the fpga domain. the technique can reduce the number of channels at maximum density by almost 45% on average with maximum reduction of 68% for optimized global routing.
a predictive system shutdown method for energy saving of event-driven computation. we present a system-level power management technique for power saving of event-driven applications. we present a new predictive system shutdown method to exploit sleep mode operations for power saving. we use an exponential-average approach to predict the upcoming idle period. we introduce two mechanisms, prediction-miss correction and pre-wakeup, to improve the hit ratio and to reduce the delay overhead. experiments on four different event-driven applications show that our proposed method achieves high hit ratios in a wide range of delay overheads, which results in a high degree of power saving with low delay penalties.
an integrated algorithm for combined placement and libraryless technology mapping. this paper presents a new solution for combining technology mapping with placement, coupling the two into one phase. the original aspects of our work are the use of libraryless mapping and a state space search mechanism that is used to find the best solution. several heuristics are presented for speeding up the search. comparisons with a more conventional approach show that these strategies provide improvements of about 20%, with reasonable cpu times, on benchmark circuits.
cash: a novel "clock as shield" design methodology for noise immune precharge-evaluate logic. in gigascale integrated circuits (gsi), interconnects are expected to play a more dominant role in circuit performance than transistor cells. the circuit performance is affected by signal integrity as cross-talk becomes more significant with the scaling of feature sizes. many attempts have been made to improve noise immunity, but all require the sacrifice of speed as a trade-off, especially in dynamic circuits. avoiding noise problems while maintaining the desired speed would involve increased wire spacing or extensive shielding, both of which are unfavorable due to demands for high density and a relatively higher cost of wires in current process technologies. we propose a novel methodology in which clock lines are used as shielding wires to reduce cross-talk effects in domino circuits, thereby minimizing the possibility of functional failures. in addition, this method provides another benefit: a small buffer size is required for driving a long interconnect for iso-noise immunity. since clock lines, which are always required in domino circuits, are used to shield signal lines, speed penalty and area overhead which are drawbacks of previous work can be avoided. this design methodology cash (clock as shielding) demonstrates the superiority over conventional methods. hspice simulations on a 2-input domino and gate and 4 and 8-bit full adders designed in cash show higher noise immunity over conventional design.
hardware/software managed scratchpad memory for embedded system. we propose a methodology for energy reduction and performance improvement. the target system comprises of an instruction scratchpad memory instead of an instruction cache. highly utilized code segments are copied into the scratchpad memory, and are executed from the scratchpad. the copying of code segments from main memory to the scratchpad is performed during runtime. a custom hardware controller is used to manage the copying process. the hardware controller is activated by strategically placed custom instructions within the executing program. these custom instructions inform the hardware controller when to copy during program execution. novel heuristic algorithms are implemented to determine locations within the program to insert these custom instructions, as well as to choose the best sets of code segments to be copied to the scratchpad memory. for a set of realistic benchmarks, experimental results indicate the method uses 50.7% lower energy (on average) and improves performance by 53.2% (on average) when compared to a traditional cache system which is identical in size. cache systems compared had sizes ranging from 256 to 16k bytes and associativities ranging from 1 to 32.
multi-level network optimization for low power. this paper describes a procedure for minimizing the power consumption in a boolean network under the zero delay model. power is minimized by modifying the function of each intermediate node in the network such that the power consumption of the node is decreased without increasing the power consumption of the other nodes in the network. a formal analysis of how changes in the switching activity of an intermediate node affect the switching activity of other nodes in the networks is given first. using this analysis, a procedure for calculating the set of compatible power don't cares for each node in the network is presented. finally it is shown how these don't cares are used to optimize the network for low power. these techniques have been implemented and results show an average of 10% improvement in total power consumption of the network compared to the results generated by the conventional network optimization techniques.
two-level logic minimization for low power. abstract: we study the problem of two-level logic minimization for low power in static cmos circuits. we start by defining power prime implicants (ppis) which identify the set of all implicants that are sufficient and necessary for obtaining a minimum power solution. we then provide an efficient algorithm for generating the set of all ppis of a function. the set of all ppis is then used in a minimum covering problem to find the best power solution. the feasibility of generating the set of all ppis and the increased complexity of solving the minimum covering problem are analyzed by deriving an upper bound on the expected number of ppis which shows it to be linearly proportional to the number of prime implicants of the function. the results of our experiments are then used to draw conclusions on the effectiveness of low power two-level logic minimization.
a metal and via maskset programmable vlsi design methodology using plas. in recent times there has been a substantial increase in the cost and complexity of fabricating a vlsi chip. the lithography masks themselves can cost between /spl epsi/ and /spl ges/. it is conjectured that due to these increasing costs, the number of asic starts in the last few years has declined. we address this problem by using an array of dynamic plas which require only metal and via mask customization in order to implement a new design. this would allow several similar-sized designs to share the same base set of masks (right up to the metal layers) and only have different metal and via masks. we have implemented our methodology for both combinational and sequential designs, and demonstrate that our approach strikes a reasonable compromise between asic and field programmable design methodologies in terms of placed-and-routed area and delay. our method has a 2.89/spl times/ (3.58/spl times/) delay overhead and a 4.96/spl times/ (3.44/spl times/) area overhead compared to standard cells for combinational (sequential) designs.
test generation for acyclic sequential circuits with hold registers. we present a method of test generation for acyclic sequential circuits with hold registers. a complete (100% fault efficiency) test sequence for an acyclic sequential circuit can be obtained by applying a combinational test generator to all the maximal time-expansion models (tems) of the circuit. we propose a class of acyclic sequential circuits for which the number of maximal tems is one, i.e, the maximum tem exists. for a circuit in the class, test generation can be performed by using only the maximum tem.the proposed class of sequential circuits with the maximum tem properly includes several known classes of acyclic sequential circuits such as balanced structures and acyclic sequential circuits without hold registers for which test generation can be also performed by using a combinational test generator. therefore, in general, the hardware overhead for partial scan based on the proposed structure is smaller than that based on balanced or acyclic sequential structure without hold registers.
schematic-based lumped parameterized behavioral modeling for suspended mems. schematic-based lumped parameterized behavioral modeling and simulation methodologies have become available since the emergence of analog hdls. they greatly ease iterative hierarchical multi-domain simulation, which is critical to the design of mems. nodas is one of such tools, with models written in veriloga and simulation performed within the cadence framework.this paper focuses on several key modeling issues in nodas, including schematic representation, element communication, linear, nonlinear and multi-domain modeling, and extensibility to new physical effects, processes and physical domains. a nonlinear beam model and an electrostatic gap model are discussed as examples. simulation comparison to finite element analyses and experimental data verifies the accuracy of the models and validates the simulation methodology.
simulation coverage enhancement using test stimulus transformations. this paper introduces the concept of abstract state exploration histories to a simulation environment, and present a test stimulus transformation (tst) technique to improve simulation coverage. state exploration histories are adapted from reachability analysis in formal verification. in tst, an aggressively abstracted state exploration history is maintained during simulation. while this history is being collected, test stimuli from an existing test bench are transformed on-the-fly to explore new scenarios that are not in the history. the results showed that 3-fold increase in transition coverage for a cache coherence controller, and 10 times faster coverage convergence for a mpeg2 decoder can be achieved.
a game theoretic approach to dynamic energy minimization in wireless transceivers. adaptive transceivers can significantly reduce the energyconsumption of a mobile, battery-powered node by capturing real-timechanges in the communication channel. this paper proposes agame-theoretic solution to the optimization of the energy consumptionin wireless transceivers. this is accomplished by dynamicallyadapting the modulation level of the transmitter modulator and theerror correction aptitude of the receiver decoder with respect tochannel conditions subject to specified average bit-error-rate andthroughput constraints. experimental results demonstrate energysavings of up to 15%.
a cache-defect-aware code placement algorithm for improving the performance of processors. yield improvement through exploiting fault-free sections of defective chips is a well-known technique (koren and singh (1990) and stapper et al. (1980)). the idea is to partition the circuitry of a chip in a way that fault-free sections can function independently. many fault tolerant techniques for improving the yield of processors with a cache memory have been proposed. in this paper, we propose a defect-aware code placement technique which offsets the performance degradation of a processor with a defective cache memory. to the best of our knowledge, this is the first compiler-based technique which offsets the performance degradation due to cache defects. experiments demonstrate that the technique can compensate the performance degradation even when 5% of cache lines are faulty. in some cases the technique was able to offset the impact even in presence of 25% faulty cache-lines.
a new algorithm for the binate covering problem and its application to the minimization of boolean relations. the binate covering problem (bcp) is the problem of finding a minimum cost assignment to variables that is a solution of a boolean equation f=1. it is a generalization of the set covering (or unate covering) problem, where f is positive unate, and is generally given as a table with rows corresponding to the set elements and the columns corresponding to the subsets. previous methods have considered the case when f is given as a product-of-sum formula or as a binary decision diagram (bdd). a branch-and-bound algorithm for the bcp that assumes f is expressed as the conjunction of multiple bdds is presented. the bcp solver that has been implemented can be applied to several problems, including exact minimization of boolean relations, for which results are presented. it has been possible to solve large, difficult problems (up to 4692 variables) which could not be solved by the product of sum based method
efficient model order reduction via multi-node moment matching. the new concept of multi-node moment matching (mmm) is introduced in this paper. the mmm technique simultaneously matches the moments at several nodes of a circuit using explicit moment matching around s=0. as compared to the well-known single-point moment matching (smm) techniques (such as awe), mmm has several advantages. first, the number of moments required by mmm is significantly lower than smm for a reduced order model of the same accuracy, which directly translates into computational efficiency. this higher computational efficiency of mmm as compared to smm increases with the number of inputs to the circuit. second, mmm has much better numerical stability as compared to smm. this characteristic allows mmm to calculate an arbitrarily high order approximation of a linear system, achieving the required accuracy for systems with complex responses. finally, mmm is highly suitable for parallel processing techniques especially for higher order approximations while smm has to calculate the moments sequentially and cannot be adapted to parallel processing techniques.
low power system scheduling and synthesis. many scheduling techniques have been presented recently which exploit dynamic voltage scaling (dvs) and dynamic power management (dpm) for both uniprocessors and distributed systems, as well as both real-time and non-real-time systems. while such techniques are power-aware and aim at extending battery lifetimes for portable systems, they need to be augmented to make them battery-aware as well. we will survey such power-aware and battery-aware scheduling algorithms. also, system synthesis algorithms for real-time systems-on-a-chip (socs), distributed and wireless client-server embedded systems, etc., have begun optimizing power consumption in addition to system price. we will survey such algorithms as well, and point out some open problems.
computation of signal threshold crossing times directly from higher order moments. this work introduces a simple method for calculating the times at which any signal crosses a pre-specified threshold voltage (e.g. 10%, 20%, 50%, etc.) directly from the moments. the method can use higher order moments to asymptotically improve the accuracy of the estimated crossing times. this technique bypasses the steps involved in calculating poles and residues to obtain time-domain information. once q moments are calculated, only 2q multiplications and (q-i) additions are required to determine any threshold crossing time at a certain node. moreover, this technique avoids other problems such as pole instability. several orders of approximations are presented for different threshold crossing times depending on the number of moments involved. for example, the worst case error of a first to a seventh order (single to seven moments) approximation of 50% rc delay is 1650%, 192.26%, 11.31%, 3.37%, 2.57%, 2.56%, and 1.43%, respectively. if the whole waveform is required it can be easily determined by interpolation between different threshold crossing points. the presented technique works for rc circuits for both step and nonstep inputs, including piecewise linear waveforms.
efficient statistical capacitance variability modeling with orthogonal principle factor analysis. due to the ever-increasing complexity of vlsi designs and ic process technologies, the mismatch between a circuit fabricated on the wafer and the one designed in the layout tool grows ever larger. therefore, characterizing and modeling process variations of interconnect geometry has become an integral part of analysis and optimization of modern vlsi designs. in this paper, we present a systematic methodology to develop a closed form capacitance model, which accurately captures the nonlinear relationship between parasitic capacitances and dominant global/local process variation parameters. the explicit capacitance representation applies the orthogonal principle factor analysis to greatly reduce the number of random variables associated with modeling conductor surface fluctuations while preserving the dominant sources of variations, and consequently the variational capacitance model can be efficiently utilized by statistical model order reduction and timing analysis tools. experimental results demonstrate that the proposed method exhibits over 100/spl times/ speedup compared with monte carlo simulation while having the advantage of generating explicit variational parasitic capacitance models of high order accuracy.
repeater insertion in tree structured inductive interconnect. the effects of inductance on repeater insertion in rlc trees is the focus of this paper. an algorithm is introduced to insert and size repeaters within an rlc tree to optimize a variety of possible cost functions such as minimizing the maximum path delay, the skew between branches, or a combination of area, power, and delay. the algorithm has a complexity proportional to the square of the number of possible repeater positions, permitting a repeater solution to be chosen that is close to the global minimum. the repeater insertion algorithm is used to insert repeaters within several copper-based interconnect trees to minimize the maximum path delay based on both an rc model and an rlc model. the two buffering solutions are compared using the as/x dynamic circuit simulator. it is shown that as inductance effects increase, the area and power consumed by the inserted repeaters to minimize the path delays of an rlc tree decreases. by including inductance in the repeater insertion methodology, the interconnect is modeled more accurately as compared to an rc model, permitting average savings in area, power, and delay of 40.8%, 15.6%, and 6.7%, respectively, for a variety of copper-based interconnect trees from a 0.25 &mgr;m cmos technology. the average savings in area, power, and delay increases to 62.2%, 57.2%, and 9.4%, respectively, when using five times faster devices with the same interconnect trees.
don't cares and multi-valued logic network minimization. we address optimizing multi-valued (mv) logic functions in a multi-level combinational logic network. each node in the network, called an mv-node, has multi-valued inputs and single multi-valued output. the notion of don't cares used in binary logic is generalized to multi-valued logic. it contains two types of flexibility: incomplete specification and non-determinism. we generalize the computation of observability don't cares for a multi-valued function node. methods are given to compute (a) the maximum set of observability don't cares, and (b) the compatible set of observability don't cares for each mv-node. we give a recursive image computation to transform the don't cares into the space of local inputs of the node to be minimized. the methods are applied to some experimental multi-valued networks, and demonstrate reduction in the size of the tables that represent multi-valued logic functions.
module selection and data format conversion for cost-optimal dsp synthesis. in high level synthesis each node of a synchronous dataflow graph (dfg) is scheduled to a specific time and allocated to a processor. in this paper we present new integer linear programming (ilp) models which generate a blocked schedule for a dfg with implicit retiming, pipelining, and unfolding while performing module selection and data format conversion. a blocked schedule is a schedule which overlaps multiple iterations of the dfg to guarantee a minimum number of processors. component modules are selected from a library of processors to minimize cost. furthermore, we include data format converters between processors of different data formats. in addition, we minimize the unfolding factor of the blocked schedule.
sensitivity analysis of iterative design processes. as design processes continue to increase in complexity, it is important to base process improvements on quantitative analysis. in this paper we develop an analytical approach to analyze sequential design processes using sensitivity analysis. two applications illustrate this approach, one involving a pareto analysis of an asic design process and the other an optimization of a software design process to determine the lower bound of the process completion time.
efficient validity checking for processor verification. we describe an efficient validity checker for the quantifier-free logic of equality with uninterpreted functions. this logic is well suited for verifying microprocessor control circuitry since it allows the abstraction of datapath values and operations. our validity checker uses special data structures to speed up case splitting, and powerful heuristics to reduce the number of case splits needed. in addition, we present experimental results and show that this implementation has enabled the automatic verification of an actual high-level microprocessor description.
timing-driven partial scan. we present a partial scan approach, which aims at reducing both area overhead and performance degradation caused by test logic. given a target speed and an initial design that meets the target, the algorithm selects a minimum set of scan flip-flops, if they exist, that (1) will break all sequential cycles and (2) will not violate the performance requirement after the scan logic is added. if such a set does not exist, the algorithm will find a set of scan flip-flops in which (1) all sequential cycles are broken and (2) the total area increase caused by the scan logic and the subsequent performance optimization to meet the target speed is minimized.experimental results on some of the iscas'89 sequential circuits are presented as well as comparisons between the new method and the existing methods. for circuits synthesized by automatic synthesis tools, we suggest a new design flow, which selects/inserts the partial scan logic after area optimization, but before performance optimization. for meeting both performance and testability requirements, the new design flow tends to produce designs with less area increase than the traditional design flow, which considers testability and adds test logic after performance optimization.this work represents an important concept for considering the three major design parameters, namely, performance, area, and testability, together during the synthesis phase for obtaining the right partial scan solution.
a fast and memory-efficient diagnostic fault simulation for sequential circuits. in this paper, a fast and memory-efficient diagnostic fault simulator for sequential circuits is proposed. in it, a two-level optimization technique is developed and used to prompt the processing speed. in the first high level, an efficient list, which stores the indistinguishable faults so far for each fault during simulation, and the list maintaining algorithm are applied, thus the number of diagnostic comparisons is minimized. in the second low level, a bit-parallel comparison is developed to speed up the comparing process. therefore, the different diagnostic measure reports for a given test set can be generated very quickly. in addition, the simulator is extended to diagnose the single stuck-at device fault. experimental results show that this diagnostic simulator achieves a significant speedup compared to previous methods.
condition graphs for high-quality behavioral synthesis. identifying mutual exclusiveness between operators during behavioral synthesis is important in order to reduce the required number of control steps or hardware resources. to improve the quality of the synthesis result, we propose a representation, the condition graph, and an algorithm for identification of mutually exclusive operators. previous research efforts have concentrated on identifying mutual exclusiveness by examining language constructs such as if-then-else statements. thus, their results heavily depend on the description styles. the proposed approach can produce results independent of description styles and identify more mutually exclusive operators than any previous approaches. the condition graph and the proposed algorithm can be used in any scheduling or binding algorithms. experimental results on several benchmarks have shown the efficiency of the proposed representation and algorithm.
direct synthesis of timed asynchronous circuits. this paper presents a new method to synthesize timed asynchronous circuits directly from the specification without generating a state graph. the synthesis procedure begins with a deterministic graph specification with timing constraints. a timing analysis extracts the timed concurrency and timed causality relations between any two signal transitions. then, a hazard-free implementation of the specification is synthesized by analyzing precedence graphs which are constructed by using the timed concurrency and timed causality relations. the major result of this work is that the method does not suffer from the state explosion problem, achieves significant reductions in synthesis time, and generates synthesized circuits that have nearly the same area as compared to previous timed circuit methods. in particular, this paper shows that a timed circuit &mdash; not containing circuit hazards under given timing constraints &mdash; can be found by using the relations between signal transitions of the specification. moreover, the relations can be efficiently found using a heuristic timing analysis algorithm. by allowing significantly larger designs to be synthesized, this work is a step towards the development of high-level synthesis tools for system level asynchronous circuits.
a new algorithm for the design of stable higher order single loop sigma delta analog-to-digital converters. abstract: this paper presents a new algorithm to attain optimized network scaling in single loop, 1 bit sigma delta analog 1d digital converters (sd adc) of order three or more. the algorithm is based on a novel mathematical description of stability and performance criteria of the sd adc and on the application of nonlinear interactive optimization techniques. the feasibility of the new algorithm has been confirmed in practical implementations. the method brings new insight on the correlation between system stability, performance, system order and the choice of the network scaling. our method is extendible to cascaded sd as well as sd based on filter topologies.
maximum independent sets on transitive graphs and their applications in testing and cad. we present a polynomial time algorithm that finds the maximum weighted independent set of a transitive graph. the studied problem finds applications in a variety of vlsi contexts, including path delay fault testing, scheduling in high level synthesis and channel routing in physical design automation. the algorithm has been implemented and incorporated in a cad tool for path delay fault testing. we experimentally verify its impact in the latter context.
copy detection for intellectual property protection of vlsi designs. we give the first study of copy detection techniques for vlsi cad applications; these techniques are complementary to previous watermarking-based ip protection methods in finding and proving improper use of design ip. after reviewing related literature (notably in the text processing domain), we propose a generic methodology for copy detection based on determining basic elements within structural representations of solutions (ips), calculating (context-independent) signatures for such elements, and performing fast comparisons to identify potential violators of ip rights. we give example implementations of this methodology in the domains of scheduling, graph coloring and gate-level layout; experimental results show the effectiveness of our copy detection schemes as well as the low overhead of implementation. we remark on open research areas, notably the potentially deep and complementary interaction between watermarking and copy detection.
non-tree routing for reliability and yield improvement. we propose to introduce redundant interconnects for manufacturing yield and reliability improvement. by introducing redundant interconnects, the potential for open faults is reduced at the cost of increased potential for short faults; overall, manufacturing yield and fault tolerance can be improved. we focus on a post-processing, tree augmentation approach which can be easily integrated in current physical design flows. our contributions are as follows:&bull; we formulate the problem as a variant of the classical 2-edge-connectivity augmentation problem in which we take into account such practical issues as wirelength increase budget, routing obstacles, and use of steiner points.&bull; we show that an optimum solution can always be found on the hanan grid defined by the terminals and the corners of the feasible routing region.&bull; we give a compact integer program formulation which, for up to 100 terminal nets, is solved in practical runtime by the commercial optimization package cplex.&bull; we give a well-scaling greedy algorithm which has practical runtime up to 1,000 terminals, and comes on the average within 1--2% of the optimum computed by cplex.&bull; we give a comprehensive experimental study comparing the solution quality and runtime of our methods with the best reported methods for 2-edge-connectivity augmentation, including a sophisticated heuristic based on minimum-weight branchings [9] and a recent genetic algorithm [14].experiments on randomly generated and industry testcases show that our greedy augmentation method achieves significant increase in reliability (as measured by the percentage of biconnected tree edges) with very small increase in wirelength. for example, on 1,000 terminal nets the average percentage of biconnected tree edges is 34.19% for a wire-length increase of only 1%, and 87.73% for a wirelength increase of 20%. spice simulations on industry routed nets show that non-tree routing has the additional benefit of reducing maximum sink delay by an average of 28.26% compared to steiner routing, and by an average of 3.72% compared to timing optimized routing. spice simulations further imply that non-tree routing has smaller delay variation due to process variability.
on mismatches between incremental optimizers and instance perturbations in physical design tools. the incremental, "construct by correction" design methodology has become widespread in constraint-dominated dsm design. we study the problem of eco for physical design domains in the general context of incremental optimization. we observe that an incremental design methodology is typically built from a full optimizer that generates a solution for an initial instance, and an incremental optimizer that generates a sequence of solutions corresponding to a sequence of perturbed instances. our hypothesis is that in practice, there can be a mismatch between the strength of the incremental optimizer and the magnitude of the perturbation between successive instances. when such a mismatch occurs, the solution quality will degrade -- perhaps to the point where the incremental optimizer should be replaced by the full optimizer. we document this phenomenon for three distinct domains -- partitioning, placement and routing -- using leading industry and academic tools. our experiments show that current cad tools may not be correctly designed for eco-dominated design processes. thus, compatibility between optimizer and instance perturbation merits attention both as a research question and as a matter of industry design practice.
analytical delay models for vlsi interconnects under ramp input. elmore delay has been widely used as an analytical estimate of interconnect delays in the performance-driven synthesis and layout of vlsi routing topologies. however, for typical rlc interconnections with ramp input, elmore delay can deviate by up to 100% or more from spice-computed delay since it is independent of rise time of the input ramp signal. we develop new analytical delay models based on the first and second moments of the interconnect transfer function when the input is a ramp signal with finite rise time. delay estimates using our first moment based analytical models are within 4% of spice-computed delay, and models based on both first and second moments are within 2.3% of spice, across a wide range of interconnect parameter values. evaluation of our analytical models is several orders of magnitude faster than simulation using spice. we also describe extensions of our approach for estimation of source-sink delays in arbitrary interconnect trees.
evaluation of placement techniques for dna probe array layout. dna probe arrays have emerged as a core genomic technology thatenables cost-effective gene expression monitoring, mutation detection,single nucleotide polymorphism analysis and other genomicanalyses. dna chips are manufactured through a highly scalableprocess, very large-scale immobilized polymer synthesis (vl-sips),that combines photolithographic technologies adapted fromthe semiconductor industry with combinatorial chemistry. commerciallyavailable dna chips contain more than a half millionprobes and are expected to exceed one hundred million probes inthe next generation. this paper is one of the first attempts to applyvlsi cad methods to the problem of probe placement in dnachips, where the main objective is to minimize total border cost(i.e., the number of nucleotide mismatches between adjacent sites).we make the following contributions. first, we propose severalpartitioning-based algorithms for dna probe placement thatimprove solution quality by over 4% compared to best previouslyknown methods. second, we give a simple in-place probe re-embeddingalgorithm with solution quality better than previous"chessboard" and batched greedy algorithms. third, we experimentallyevaluate scalability and suboptimality of existing and newlyproposed probe placement algorithms. interestingly, we find thatdna placement algorithms appear to have better suboptimalityproperties than those recently reported for vlsi placement algorithms.
intrinsic shortest path length: a new, accurate a priori wirelength estimator. a priori wirelength estimation is concerned with predicting various wirelength characteristics before placement. in this work we propose a novel, accurate estimator of net lengths. we observe that in "good" placements, the length of a net is very strongly correlated with the numbers of nets in the shortest paths connecting node pairs of the net, when each shortest path is computed under the restriction that the net itself does not exist. we refer to this as the net's intrinsic shortest path length (ispl). using ispl as a wirelength estimator has several advantages: (1) it transparently handles multi-pin nets and is a strong predictor of their length; (2) it strongly correlates with the average netlist wirelength; (3) it has a distribution that is similar to that of wirelength; and (4) it acts as a good predictor for individual net lengths. based on ispls, we characterize vlsi netlists with a single value and develop an intuitive, empirical link between our proposed value and the rent parameter. we also analytically model the relationship between ispl and wirelength, and use ispls in two practical applications: a priori total wirelength estimation and a priori global interconnect prediction.
architecture and details of a high quality, large-scale analytical placer. modern design requirements have brought additional complexities to netlists and layouts. millions of components, whitespace resources, and fixed/movable blocks are just a few to mention in the list of complexities. with these complexities in mind, placers are faced with the burden of finding an arrangement of placeable objects under strict wirelength, timing, and power constraints. in this paper we describe the architecture and novel details of our high quality, large-scale analytical placer. the performance of our placer has been recently recognized in the recent ispd-2005 placement contest, and in this paper we disclose many of the technical details that we believe are key factors to its performance. we describe (i) a new clustering architecture, (ii) a dynamically adaptive analytical solver, and (iii) better legalization schemes and novel detailed placement methods. we also provide extensive experimental results on a number of benchmark sets. on average, our results are better than the best published results by 3%, 14%, and 6% for the ibm ispd '04, iccad '04, and ispd '05 benchmark sets respectively. one of the goals of this paper is to also provide enough details to enable possible future replication of our methods.
low-cost single-layer clock trees with exact zero elmore delay skew. we give the first single-layer clock tree construction with exact zero skew according to the elmore delay model. the previous linear-planar-dme method guarantees a planar solution under the linear delay model. in this paper, we use a linear-planar-dme variant connection topology to construct a low-cost zero skew tree (zst) according to the elmore delay model. while a linear-delay zst is trivially converted to an elmore-delay zst by &ldquo;detouring&rdquo; wires, the key idea is to defer this detouring as much as possible to reduce tree cost. costs of our planar zst solutions are comparable to those of the best previous non-planar zst solutions, and substantially improve over previous planar clock routing methods.
an analytic placer for mixed-size placement and timing-driven placement. we extend the aplace wirelength-driven standard-cell analytic placement framework of a.a. kennings and i.l. markov (2002) to address timing-driven and mixed-size ("boulders and dust") placement. compared with timing-driven industry tools, evaluated by commercial detailed routing and sta, we achieve an average of 8.4% reduction in cycle time and 7.5% reduction in wirelength for a set of six industry testcases. for mixed-size placement, we achieve an average of 4% wirelength reduction on ispd02 mixed-size placement benchmarks compared to results of the leading-edge solver, feng shui (v2.4) (khatkhate et al., 2004). we are currently evaluating our placer on industry testcases that combine the challenges of timing constraints, large instance sizes, and embedded blocks (both fixed and unfixed).
on identifying don't care inputs of test patterns for combinational circuits. given a test set for stuck-at faults, some of primary input values may be changed to opposite logic values without losing fault coverage. we can regard such input values as don't care (x). in this paper, we propose a method for identifying x inputs of test vectors in a given test set. while there are many combinations of x inputs in the test set generally, the proposed method finds one including x inputs as many as possible, by using fault simulation and procedures similar to implication and justification of atpg algorithms. experimental results for iscas benchmark circuits show that approximately 66% of inputs of un-compacted test sets could be x in average. even for compacted test sets, the method found that approximately 47% of inputs are x. finally, we discuss how logic values are reassigned to the identified x inputs where several applications exist to make test vectors more desirable.
hardware/software partitioning for multi-function systems. we are interested in optimizing the design of multi-function embedded systems that run a pre-specified set of applications, such as multi-standard audio/video codecs and multi-system phones. such systems usually have stringent performance constraints and tend to have mixed hardware-software implementations. the current state of the art in the hardware/software codesign of such systems is to design for each application separately. this often leads to application-specific sub-optimal decisions and inconsistent mappings of common nodes in different applications. we use these as the guiding principles to formulate, as a codesign problem, the design and synthesis of an efficient hardware-software implementation for a multi-function embedded system. our solution methodology is to first identify nodes that represent similar functionality across different applications. such "common" nodes are characterized by several metrics. these metrics are quantified and used by a hardware/software partitioning tool to map common nodes to the same resource as far as possible. we demonstrate how this is achieved by modifying a traditional partitioning algorithm (gclp) used to partition single applications. the overall result of the system-level partitioning process is (1) a hardware or software mapping and (2) a schedule for execution for each node within the application set. on an example set consisting of three video applications, we show that the solution obtained by the use of our method is 38% smaller than that obtained when each application is considered independently.
lru-seq: a novel replacement policy for transition energy reduction in instruction caches. leakage energy will be the major energy consumer in futuredeep sub-micron designs. especially the memory sub-systemof future socs will be negatively affected by this trend. inorder to reduce the leakage energy, memory banks are transitionedto a low-energy state when possible. this transitionitself costs some energy which is termed as the transition energy.in this paper we present, as the first approach of its kind,a novel energy saving replacement policy called lru-seq forinstruction caches. evaluation of the policy on various architecturesin a system-level environment has shown that upto23% energy savings can be obtained. considering the negligiblehardware impact, lru-seq offers a viable choice foran energy saving policy.
mixed signal dft: a concise overview. practical mixed-signal dft solutions are presentedwith an emphasis on performance, cost, and testcoverage.special consideration is given to thepossible dft techniques for phase-locked loops(plls) with associated implications on testcoverage, performance, cost, and time to market.an introduction to practical dft techniques fordata converters (a/d and d/a) follow.anoverview of ieee p1149.4 analog test bus standardconcludes the embedded tutorial.
interconnect parasitic extraction in the digital ic design methodology. accurate interconnect analysis has become essential not only for post-layout verification but also for synthesis. this tutorial explores interconnect analysis and extraction methodology on three levels: coarse extraction to guide synthesis, detailed extraction for full-chip analysis, and full 3d analysis for critical nets. we will also describe the electrical issues caused by parasitics and how they have, and will be, influenced by changing technology. the importance of model order reduction will be described as well as methodologies at the synthesis stage for avoiding parasitic problems.
fastpep: a fast parasitic extraction program for complex three-dimensional geometries. in this paper we describe a computationally efficient approach to generating reduced-order models from peec-based three-dimensional electromagnetic analysis programs. it is shown that a recycled multipole-accelerated approach applied to recent model order reduction techniques requires nearly two orders of magnitude fewer floating point operations than direct techniques thus allowing the analysis of larger, more complex three-dimensional geometries.
efficient techniques for inductance extraction of complex 3-d geometries. the combination of a mesh analysis equation formulation technique with a preconditioned gmres matrix solution algorithm to accelerate the determination of inductances of complex three-dimensional structures is described. addition of the preconditioner to gmres can reduce the cost of solution to m2 operations compared to m 2 for direct inversion. results from fasthenry, a 3-d inductance extraction program, demonstrate that the iterative approach can accelerate solution times by more than an order of magnitude
highly accurate fast methods for extraction and sparsification of substrate coupling based on low-rank approximation. more aggressive design practices have created renewed interest in techniques for analyzing substrate coupling problems. most previous work has focused primarily on faster techniques for extracting coupling resistances, but has offered little help for reducing the resulting resistance matrix, whose number of nonzero entries grows quadratically with the number of contacts. wavelet-like methods have been applied to sparsifying the resistance matrix representing the substrate coupling, but the accuracy of the method is very sensitive to the particulars of the contact layout. in this paper we show that for the substrate problem it is possible to improve considerably on the wavelet-like methods by making use of the algorithmic structure common to the fast multipole and wavelet-like algorithms, but making judicious use of low-rank approximations. the approach, motivated by the hierarchical svd algorithm, can achieve more than an order of magnitude better accuracy for commensurate sparsity, or can achieve much better sparsity at commensurate accuracy, when compared to the wavelet-like algorithm.
2d data locality: definition, abstraction, and application. data locality has been a central theme in the compiler optimization world for a long time. most of the prior compiler techniques try to optimize data locality in a one-dimensional linear address space. however, there are many problems out there where the domain for data locality can be two or higher dimensional. for example, in a 2d mesh network environment, each node has connections with its four neighbors, and therefore, the data locality can potentially be exploited in two dimensions from a given processor's viewpoint. because of this, maximizing the number of communications with any of four neighbors (instead of other nodes) helps improve performance. similar examples can be given from the areas of embedded sensor processing and 3d systems as well. in this application domain, we make two specific contributions. first, we show how array data of a loop-intensive application can be mapped onto a 2d mesh so that the communication distances between the nodes are reduced. second, we discuss how code restructuring through loop transformation can help us achieve better data locality in the 2d space.
banked scratch-pad memory management for reducing leakage energy consumption. current trends indicate that leakage energy consumption will be an important concern in upcoming process technologies. we propose a compiler-based leakage energy optimization strategy for on-chip scratch-pad memories (spms). the idea is to divide spm into banks and use compiler-guided data layout optimization and data migration to maximize spm bank idleness, thereby increasing the chances of placing banks into low-power (low-leakage) state.
improving memory energy using access pattern classification. in this paper, we propose a data-driven strategy to optimize the memory energy consumption in a banked memory system. our compiler-based strategy modifies the original execution order of loop iterations in array-dominated applications to increase the length of the time period(s) in which memory banks are idle (i.e., not accessed by any loop iteration). to achieve this, it first classifies loop iterations according to their bank access patterns and then, with the help of a polyhedral tool, tries to bring the iterations with similar bank access patterns close together. increasing the idle periods of memory banks brings two major benefits; first, it allows us to place more memory banks into low-power operating modes, and second, it enables us to use a more aggressive (i.e., more energy saving) operating mode for a given bank. our strategy has been evaluated using seven array-dominated applications on both a cacheless system and a system with cache memory. our results indicate that the strategy is very successful in reducing the memory system energy, and improves the memory energy by as much as 34% on the average.
delay bounded buffered tree construction for timing driven floorplanning. as devices and lines shrink into the deep submicron range, the propagation delay of signals can be effectively improved by repowering the signals using intermediate buffers placed within the routing trees. almost no existing timing driven floorplanning and placement approaches consider the option of buffer insertion. as such, they may exclude solutions, particularly early in the design process, with smaller overall area and better routability. in this paper, we propose a new methodology in which buffered trees are used to estimate wire delay during floorplanning and placement. instead of treating delay as one of the objectives, as done by the majority of previous work, we formulate the problem in terms of delay bounded buffered trees (dbb-tree). the dbb formulation is as follows: given a net and delay bounds on critical sinks, construct a tree with intermediate buffers inserted to minimize both the total wiring length and the number of buffers while satisfying the given delay bounds. based on the elmore delay model, we propose an efficient algorithm to construct a dbb spanning tree for use during floorplanning and placement. experimental results show that the algorithm is very effective. using buffer insertion at the floorplanning and placement stage yields significantly better solutions in terms of both chip area and total wire length.
fir filter synthesis algorithms for minimizing the delay and the number of adders. as the complexity of digital filters is dominated by the number of multiplications, many works have focused on minimizing the complexity of multiplier blocks that compute the constant coefficient multiplications required in filters. although the complexity of multiplier blocks is significantly reduced by using efficient techniques such as decomposing multiplications into simple operations and sharing common subexpressions, previous works have not considered the delay of multiplier blocks which is a critical factor in the design of complex filters. in this paper, we present new algorithms to minimize the complexity of multiplier blocks under the given delay constraints. by analyzing multiplier blocks in view of delay, three delay reduction methods are proposed and combined into previous algorithms. since the proposed algorithms can generate multiplier blocks that meet the specified delay, a trade-off between delay and hardware complexity is enabled by changing the delay constraints. experimental results show that the proposed algorithms can reduce the delay of multiplier blocks at the cost of a little increase of complexity.
subthreshold leakage modeling and reduction techniques. as technology scales, subthreshold leakage currents grow exponentially and become an increasingly large component of total power dissipation. cad tools to help model and manage subthreshold leakage currents will be needed for developing ultra low power and high performance integrated circuits. this paper gives an overview of current research to control leakage currents, with an emphasis on areas where cad improvements will be needed. the first part of the paper explores techniques to model subthreshold leakage currents at the device, circuit, and system levels. next, circuit techniques such as source biasing, dual vt partitioning, mtcmos, and vtcmos are described. these techniques reduce leakage currents during standby states and minimize power consumption. this paper also explores ways to reduce total active power by limiting leakage currents and optimally trading off between dynamic and leakage power components.
a novel clock distribution and dynamic de-skewing methodology. in present day vlsi ics, intra-die processing variations are becoming harder to control, resulting in a large skew in the clock signals at the end of the clock distribution network. we describe a buffered h-tree technique to distribute the clock signal and to de-skew a clock network. the clock shielding wires (which are connected to gnd in normal operation) are, in de-skewing mode, used to selectively return the clock signal for de-skewing, and for serial communication with the clock distribution sites for skew adjustment. our forward and return clock networks are buffered, with identically sized and co-located wires and buffers. this results in both these networks exhibiting identical delay characteristics in the presence of intra-die process variations. unlike existing approaches, our method utilizes a single phase detection circuit, and can achieve a very low maximum chip-level clock skew. this skew value is not dependent on the resolution of the phase detector. further, our technique can be applied dynamically, either at boot time or periodically during the operation of the ic, as necessary. additionally, our buffered h-tree enables us to implement efficient clock gating by allowing the user to turn off clocks in the distribution network itself, thus disabling entire sections of the clock network. we demonstrate the utility of our technique on a 6-level h-tree clock distribution network. in a clock distribution network which is initially skewed by up to 300ps, our technique can de-skew signals to within 4ps of each other. we show that the total wiring area of our clock distribution and de-skewing methodology is about 35% higher than a traditional h-tree (which does not have a deskewing functionality), while the active logic area overhead is about 25%. the power consumption of our network is 5% lower than that of a traditional h-tree network with no de-skewing functionality.
ies3: a fast integral equation solver for efficient 3-dimensional extraction. integral equation techniques are often used to extract models of integrated circuit structures. this extraction involves solving a dense system of linear equations, and using direct solution methods is prohibitive for large problems. in this paper, we present ies/sup 3/ (pronounced "ice cube"), a fast integral equation solver for three-dimensional problems with arbitrary kernels. extraction methods based on ies/sup 3/ are substantially more efficient than existing multipole-based approaches.
efficient time-domain simulation of frequency-dependent elements. we describe an efficient algorithm for the time-domain simulation of elements described by causal impulse responses. the computational bottleneck in the simulation of such elements is the need to compute convolutions at each time point. hence, direct approaches for the simulation of such elements require time o(n^2), where n is the length of the simulation. we apply ideas from approximation theory to reduce this complexity to o(n \log n) while maintaining double-precision accuracy. the only restriction imposed by our method is that the impulse response h(t) gets ``smoother'' as t goes to infinity. essentially all physically reasonable impulse responses have this characteristic. the ideas presented can also be applied to time-domain simulation of elements described in the frequency domain, including those characterized by measured data. in this paper, we demonstrate the efficiency of the algorithm by applying it to the simulation of lossy transmission lines.
logical effort based technology mapping. we propose a new approach to library-based technology mapping, based on the method of logical effort. our algorithm is close to optimal for fanout-free circuits, and is extended to solve the load-distribution problem for circuits with fanout. on average, benchmark circuits mapped using our approach are 25.39% faster than the solutions obtained from sis.
definition and solution of the memory packing problem for field-programmable systems. this paper defines a new optimization problem that arises in the use of a field-programmable system (fps). an fps consists of a set of field-programmable gate arrays and memories, and is used both for emulation of asics and computation. in both cases the application circuits will include a set of memories which may not match the number and aspect ratio of the physical memories available on the fps. this can often require that the physical memories be time-multiplexed to implement the required memories, in a circuit we call a memory organizer.we give a precise definition of the packing optimization problem and present an algorithm for its solution. the algorithm has been implemented in a cad tool that automatically produces a memory organizer circuit ready for synthesis by a commercial fpga tool set.
sub-90nm technologies: challenges and opportunities for cad. future high performance microprocessor design with technology scaling beyond 90nm will pose two major challenges: (1) energy and power, and (2) parameter variations. design practice will have to change from deterministic design to probabilistic and statistical design. this paper discusses circuit techniques and design automation opportunities to overcome the challenges.
an empirical model for accurate estimation of routing delay in fpgas. we present an empirical routing delay model for estimating interconnection delays in fpgas. we assume that the routing delay is a function of interplc distances, circuit size, fanout of the net and routing congestion in the channel. we performed extensive simulations of various circuits to generate a sufficiently large dataset. our method estimates delays by reading the average value tables and interpolating the values, if necessary. we present a rigorous statistical justification of this delay model. our results show that our method predicts the delays within 20% of actual and it far outperforms all other existing techniques.
an "effective" capacitance based delay metric for rc interconnect. efficient, yet accurate delay estimation for rc interconnect is required for the optimization loop of timing-driven physical design tools. for many applications, the elmore delay metric [4] has been widely used due to its efficiency and ease of use. however, it is well known that the elmore metric can have significant error since it ignores the resistive shielding of down-stream capacitance. we present a new interconnect metric called ecm that accounts for this resistive shielding by computing an effective capacitance to model the downstream capacitance. ecm can also be computed with the same complexity as the elmore delay and does not require the computation of moments. experiments show that ecm is significantly more accurate than elmore delay and is competitive with other metrics that use multiple moments.
analytical modeling of crosstalk noise waveforms using weibull function. to analyze the failure of a cmos circuit due to glitches induced by capacitive crosstalk, noise immunity curves (a.k.a. noise rejection curve) must be characterized. however, noise waveform models currently used for characterization such as ideal triangle and trapezoid can underestimate the propagated noise pulse by over 20% and result in missed violations. we provide an analytical solution to fit any given crosstalk noise waveform to a weibull function, which can generate identical propagated glitch heights compared to spice, resulting in accurate noise immunity curves.
predictable routing. predictable routing is the concept of using prespecified patterns to route a net. by doing this, we allow an more accurate prediction mechanism for metrics such as congestion and wirelength earlier in the design flow. additionally, we can better plan the routes, insert buffers and perform wire sizing earlier. with comparable routing quality, we show that we can predictably route up to 80% of a selected subset of nets. also, we introduce methods for finding a group of nets which can be predictably routed.
instruction generation for hybrid reconfigurable systems. in this work, we present an algorithm for simultaneous template generation and matching. the algorithm profiles the graph and iteratively contracts edges to create the templates. the algorithm is general and can be applied to any type of graph, including directed graphs and hypergraphs. we discuss how to target the algorithm towards the novel problem of instruction generation and selection for a hybrid (re)configurable systems. in particular, we target the strategically programmable system, which embeds complex computational units like alus, ip blocks, etc. into a configurable fabric. we argue that an essential compilation step for these systems is instruction generation, as it is needed to specify the functionality of the embedded computational units. additionally, instruction generation can be used to create soft macros -- tightly sequenced pre-specified operations placed in the configurable fabric.
a robust cell-level crosstalk delay change analysis. in this work we present a robust and efficient methodology for crosstalk-induced delay change analysis for asic design styles. the approach employs optimization methods to search for worst aggressor alignment, and it computes crosstalk induced delay change on each stage considering an impact on downstream logic. computational efficiency is achieved using pre-characterized current models for drivers and compact macromodels for interconnect. the proposed methodology has been implemented in a commercial noise analysis tool. experimental results obtained on industrial designs demonstrate high accuracy and reduced pessimism of the proposed methodology.
delay budgeting for a timing-closure-driven design method. in this paper, we present an rtl delay-budgeting approach for a timing-closure-driven design method. we formulate the delay-budgeting problem into the lagrange-multipliers-based slack distribution problem. we present two algorithms, namely the balanced slack distribution algorithm and the at-based (area-time) slack distribution algorithm, to solve the problem. we also present a timing-closure-driven design flow by integrating commercial synthesis/layout tools with the proposed algorithms. we have demonstrated the viability of the proposed rtl delay-budgeting method. the results show that without an accurate at-characteristic projection of modules the balanced slack distribution algorithm will be a good choice for delay budgeting at rtl.
variational analysis of large power grids by exploring statistical sampling sharing and spatial locality. we propose a parametric random walk algorithm to facilitate a feasible evaluation of a few critical network nodes under the influence of a large number of variation sources in a power grid. by combining statistical sampling sharing with random walks, we devise an efficient localized sensitivity analysis for large power distribution networks such that the analysis can be conducted without solving the complete network. we further show that this sampling-based parametric analysis can be extended from the first order sensitivity analysis to a more accurate second order analysis. by exploiting the natural spatial locality inherent in our algorithm formulation, the second order parametric analysis can be conducted very efficiently even for a large number of global and local variation sources. the proposed approach is demonstrated by analyzing large power grids under the influence of process and current loading variations to which the application of the standard brutal-force circuit simulation becomes completely infeasible. our results have demonstrated the superior performance of the proposed algorithm both in terms of accuracy and runtime.
the feasibility of on-chip interconnection using antennas. the feasibility of integrating antennas and required circuits to form wireless interconnects in foundry digital cmos technologies has been demonstrated. the key challenges including the effects of metal structures associated with integrated circuits, heat removal, packaging, and interaction of transmitted and received signals with nearby circuits appear to be manageable. besides, on-chip interconnection, this technology can potentially be applied for implementation of true single chip radio and radar, interchip communication systems, rfid tags and others.
analysis and optimization of substrate noise coupling in single-chip rf transceiver design. the relentless move toward single chip integration of rf, analog and digital blocks results in significant noise coupling effects that can degrade performance and hence, should be controlled. in this paper, we propose a practical methodology that uses a suite of commercial tools in combination with a high-speed extractor based on an innovative semi-analytical method to deal with noise coupling problems, and enable rf designers to achieve a first silicon-success of their chips. the integration of the methodology in a typical rf design flow is illustrated and its successful application to achieve a single-chip integration of a transceiver demonstrated.
stable and efficient reduction of substrate model networks using congruence transforms. parasitic analog-digital noise coupling has been identified as a key issue facing designers of mixed-signal integrated circuits. in particular, signal cross talk through the common chip substrate has become increasingly problematic. this paper demonstrates a new methodology for developing simulation, synthesis, and verification models to analyze the global electrical behavior of the non-ideal semiconductor substrate. rc substrate network models, which are generated via a triangular discretization method, are accurately approximated for subsequent analysis by an efficient reduction algorithm. this algorithm utilizes the well-conditioned lanczos process to formulate pade approximations of the network port admittance. congruence transformations are employed to ensure stability, and to create reduced networks which are easily realizable with spice-compatible rc elements. for validation, the strategy has been successfully applied to several mixed-signal circuit examples.
incremental partitioning-based vectorless power grid verification. to ensure reliable performance of a chip, design verification of the power grid is of critical importance. this paper builds on previous work that models the working behavior of the circuit in terms of abstracted current constraints and solves for worst-case voltage drop on the grid as a linear program. the main motivation is to allow the efficient verification of local power grid sections or blocks, enabling incremental design analysis of the grid. this approach substantially improves the computational time by reducing the problem size and the constraint set and replacing them by black box macromodels. this increase the capacity of the solver to handle industrial sized grids.
standby power optimization via transistor sizing and dual threshold voltage assignment. this paper presents a novel enumerative approach, with provable and efficient pruning techniques, for dual threshold voltage (vt) assignment at the transistor level. since the use of low vt may entail a substantial increase in leakage power, we formulate the problem as one of combined optimization for leakage-delay tradeoffs under vt optimization and sizing. based on an analysis of the effects of these two transforms on the delay and leakage, we justify a two-step procedure for performing this optimization. results are presented on the iscas85 benchmark suite favorably comparing our approach with an existing sensitivity-based optimizer.
clock skew scheduling for improved reliability via quadratic programming. this paper considers the problem of determining an optimal clock skew schedule for a synchronous vlsi circuit. a novel formulation of clock skew scheduling as a constrained quadratic programming (qp) problem is introduced. the concept of a permissible range, or a valid interval, for the clock skew of each local data path is key to this qp approach. from a reliability perspective, the ideal clock schedule corresponds to each clock skew within the circuit being at the center of the respective permissible range. however, this ideal clock schedule is not practically implementable because of limitations imposed by the connectivity among the registers within the circuit. to evaluate the reliability, a quadratic cost function is introduced as the euclidean distance between the ideal schedule and a given practically feasible clock schedule. this cost function is the minimization objective of the described algorithms for the solution of the previously mentioned quadratic program. furthermore, the work described here substantially differs from previous research in that it permits complete control over specific clock signal delays or skews within the circuit. specifically, the algorithms described here can be employed to obtain results with explicitly specified target values of important clock delays/skews with a circuit, such as for example, the clock delays/skews for i/o registers. an additional benefit is a potential reduction in clock period of up to 10%. an efficient mathematical algorithm is derived for the solution of the qp problem with &ogr;(r3) run time complexity and &ogr;(r2) storage complexity, where r is the number of registers in the circuit. the algorithm is implemented as a c++ program and demonstrated on the iscas'89 suite of benchmark circuits as well as on a number of industrial circuits. the work described here yields additional insights into the correlation between circuit structure and circuit timing by characterizing the degree to which specific signal paths limit the overall performance and reliability of a circuit. this information is directly applicable to logic and architectural synthesis.
symbolic debugging scheme for optimized hardware and software. symbolic debuggers are system development tools that can accelerate the validation speed of behavioral specifications by allowing a user to interact with an executing code at the source level. in response to a user query, the debugger retrieves the value of a source variable in a manner consistent with respect to the source statement where execution has halted. however, when a behavioral specification has been optimized using transformations, values of variables may be inaccessible in the run-time state.we have developed a set of techniques that, given a behavioral specification cdfg, enforce computation of a selected subset vcut of user variables such that (i) all other variables v &isin; cdfg can be computed from vcut and (ii) this enforcement has minimal impact on the optimization potential of the computation. the implementation of the new debugging approach poses several optimization tasks. we have formulated the optimization tasks and developed heuristics to solve them. the effectiveness of the approach has been demonstrated on a set of benchmark designs.
zero skew clock routing in multiple-clock synchronous systems. a clock routing algorithm for two-phase clock systems is presented. the algorithm, which minimizes both intraclock skew and interclock skew, has been implemented on sparc 1+ in c and has been tested on several industrial benchmarks as well as on randomly generated examples. in particular, the result was tested for a 267 synchronous component circuit at clock rates of 100 mhz. it is significant that this is the first ever result which deals with multiple clock routing with zero skew
static verification of test vectors for ir drop failure. atpg tools generate test vectors assuming zero delay model forlogic gates.in reality, however, gates have finite rise and falldelays that are dependent on process, voltage, and temperaturevariations across different dies on a wafer and within a die.a testengineer must verify the vectors for timing correctness before theyare handed off to the product engineer.currently, validation oftests is done using dynamic simulation of the circuit using the testvectors.a test vector is invalidated if it cannot reliably distinguishbetween a good and a faulty circuit under the signal placement andobservation error window of the tester equipment.since structuraltests can result in much more switching activity in the circuit thanwhat is estimated during normal functioning, the ir drop in thepower & ground lines can be significant, adversely impacting pathdelays.as a result, the validation performed by simulation can beerror prone.oversizing the power rails to address this problemimpacts the yield.we therefore propose the verification of testvectors for ir drop failure and present a flow for identifyingfailing vectors.attempting to address this verification in dynamicsimulation will force the use of circuit simulation or mixed-levelsimulation techniques, which are expensive in terms of run time.we discuss a static approach to validate the test vectors for failurein the presence of ir drop problems.
efficient mixed-domain analysis of electrostatic mems. we present efficient computational methods for scattered point and meshless analysis of electrostatic microelectromechanical systems (mems). electrostatic mems are governed by coupled mechanical and electrostatic energy domains. a self-consistent analysis of electrostatic mems is implemented by combining a finite cloud method based interior mechanical analysis with a boundary cloud method based exterior electrostatic analysis. lagrangian descriptions are used for both mechanical and electrostatic analyses. meshless finite cloud and boundary cloud methods combined with fast algorithms and lagrangian descriptions are flexible, efficient and attractive alternatives compared to conventional finite element/boundary element methods for self-consistent electromechanical analysis. numerical results are presented for an electrostatic comb drive device.
a probabilistic approach to buffer insertion. this work presents a formal probabilistic approach for solving optimizationproblems in design automation. prediction accuracy isvery low especially at high levels of design flow. this can be attributedmainly to unawareness of low level layout information andvariability in fabrication process. hence a traditional deterministicdesign automation approach where each cost function is representedas a fixed value becomes obsolete. a new approach is gainingattention in which the cost functions are representedas probability distributions and the optimization criteriais probabilistic too. this design optimization philosophy is demonstratedthrough the classic buffer insertion problem. formally,we capture wirelengths as probability distributions (as compared tothe traditional approach which considers wirelength as fixed values)and present several strategies for optimizing the probabilisticcriteria. during the course of this work many problems are provedto be np-complete. comparisons are made with the van-ginneken"optimal under fixed wire-length" algorithm. results show that thevan-ginneken approach generated delay distributions at the root ofthe fanout wiring tree which had large probability (0.91 in the worstcase and 0.55 on average) of violating the delay constraint. ouralgorithms could achieve 100% probability of satisfying the delayconstraint with similar buffer penalty. although this work considerswirelength prediction inaccuracies, our probabilistic strategy couldbe extended trivially to consider fabrication variability in wire parasitics.
hybrid techniques for electrostatic analysis of nanowires. we propose an efficient approach, namely the hybrid bie/poisson/schrodinger approach, for electrostatic analysis of nanowires. in this approach, the interior and the exterior domain electrostatics are described by poisson's equation (or poisson's equation coupled with schrodinger's equation when quantum-mechanical effects are dominant) and the boundary integral formulation of the potential equation, respectively. we employ a meshless finite cloud method and a boundary cloud method to solve the coupled equations self-consistently. the proposed approach significantly reduces the computational cost and provides a higher accuracy of the solution.
efficient statistical timing analysis through error budgeting. we propose a technique for optimizing the runtime in statistical timing analysis. given a global acceptable error budget at the primary output which signifies the difference in the area of the accurate and approximate timing cdfs, we propose a formulation of budgeting this global error across all nodes in the circuit. this node error budget is used to simplify the computation of arrival time cdfs at each node using approximations. this simplification reduces the runtime of statistical timing analysis. we investigate two ways of exploiting this node error budget, firstly through piecewise linear approximation (see ibid., a. devgan and c. kashyap, 2003) and secondly though hierarchical quadratic approximation. experimental results on iscas/mcnc benchmarks show that our approach is at most 3 times faster than accurate statistical timing analysis and had a very small error. we also found quadratic piecewise approximation to be more accurate than linear approximation but at lesser gains in runtime.
accurate power estimation for large sequential circuits. a power estimation approach is presented in which blocks of consecutive vectors are selected at random from a user-supplied realistic input vector set and the circuit is simulated for each block starting from an unknown state. this leads to two (upper and lower) bounds on the desired power value which can be quite tight (under 10% difference between the two in many cases). as a result, the power dissipation is obtained by simulating only a fraction of the potentially very large vector set.
leakage control through fine-grained placement and sizing of sleep transistors. leakage power is increasingly gaining importance with technology scaling. multi-threshold cmos (mtcmos) technology has become a popular technique for standby power reduction. sleep transistor insertion in circuits is an effective application of mtcmos technology for reducing leakage power. in this work we present a fine grained approach where each gate in the circuit is provided an independent sleep transistor. key advantages of this approach include better circuit slack utilization and improvements in signal integrity (which is a major disadvantage in clustering based approaches). to this end, we propose an optimal polynomial time fine grained sleep transistor sizing algorithm. we also prove the selective sleep transistor placement problem as np-complete and propose an effective heuristic. finally, in order to reduce the sleep transistor area penalty (which might get high since clustering is not performed), we propose a placement area constrained sleep transistor sizing formulation. our experiments show that on an average the sleep transistor placement and optimal sizing algorithm gave 69.7% and 59.0% savings in leakage power as compared to the conventional fixed delay penalty algorithms for 5 and 7% circuit slowdown respectively. moreover the post placement area penalty was less than 5% which is comparable to clustering schemes according to mohab anis et al. (2003).
integrating program transformations in the memory-based synthesis of image and video algorithms. in this paper we discuss the interaction and integration of two important program transformations in high-level synthesis&mdash;tree height reduction and redundant memory-access elimination. intuitively, these program transformations do not interfere with one another as they optimize different operations in the program graph and different resources in the synthesized system. however, we demonstrate that integration of the two tasks is necessary to better utilize available resources. our approach involves the use of a &ldquo;meta-transformation&rdquo; to guide transformation application as possibilities arise. results observed on several image and video benchmarks demonstrate that transformation integration increases performance through better resource utilization.
decomposition of timed decision tables and its use in presynthesis optimizations. presynthesis optimizations transform a behavioral hdl description into an optimized hdl description that results in improved synthesis results. we introduce the decomposition of timed decision tables (tdt), a tabular model of system behavior. the tdt decomposition is based on the kernel extraction algorithm. by experimenting using named benchmarks, we demonstrate how tdt decomposition can be used in presynthesis optimizations.
theoretical framework for compositional sequential hardware equivalence verification in presence of design constraints. we are interested in sequential hardware equivalence (or alignability equivalence) verification of synchronous sequential circuits as stated in c. pixley (1992). to cope with large industrial designs, the circuits must be divided into smaller subcircuits and verified separately. furthermore, in order to succeed in verifying the subcircuits, design constraints must be added to the subcircuits. these constraints mimic "essential" behavior of the subcircuit environment. in this work, we extend the classical alignability theory in the presence of design constraints, and prove a compositionality result allowing inferring alignability of the circuits from alignability of the subcircuits. as a result, we build a divide and conquer framework for alignability verification. this framework is successfully used on intel designs.
multigrid-like technique for power grid analysis. modern sub-micron vlsi designs include huge power grids that are required to distribute large amounts of current, at increasingly lower voltages. the resulting voltage drop on the grid reduces noise margin and increases gate delay, resulting in a serious performance impact. checking the integrity of the supply voltage using traditional circuit simulation is not practical, for reasons of time and memory complexity. we propose a novel multigrid-like technique for the analysis of power grids. the grid is reduced to a coarser structure, and the solution is mapped back to the original grid. experimental results show that the proposed method is very efficient as well as suitable for both dc and transient analysis of power grids.
cross-talk immune vlsi design using a network of plas embedded in a regular layout fabric. we present a vlsi design methodology to address the cross-talk problem, which is becoming increasingly important in deep sub-micron (dsm) ic design. in our approach, we implement the logic netlist in the form of a network of medium sized plas. we utilize two regular layout "fabrics" in our methodology, one for areas where pla logic is implemented, and another for routing regions between such logic blocks. we show that a single pla implemented in the first fabric style is not only cross-talk immune, but also about 2&times; smaller and faster than a traditional standard cell based implementation of the same logic. the second fabric, utilized in the routing region between individual plas, is also highly cross-talk immune. additionally, in this fabric, power and ground signals are essentially "pre-routed" all over the die.our synthesis flow involves decomposing the design into a network of plas, each of which has a bounded width and height. the number of inputs and outputs of each pla are flexible as long as the resulting pla width is bounded. we perform folding of plas to achieve better logic density. routing is performed using 2, 3, 4, 5 and 6 routing layers. state-of-the-art commercial routing tools are utilized for the experiments involving the use of 3, 4, 5 and 6 routing layers.we have implemented the entire design flow using these ideas. our scheme results in a reduction in the cross-talk between signal wires of between one and two orders of magnitude. as a result, for a 0.1&mu;m process, the delay variation due to cross-talk dramatically drops from 2.47:1 to 1.02:1. additionally, our methodology results in circuits that are extremely fast and dense, with a timing improvement of about 15% and an overall area penalty of about 3% compared to standard cells. the regular arrangement of metal conductors in our scheme results in low and highly predictable inductive and capacitive parasitics, resulting in highly predictable designs. the crosstalk immunity, high speed, low area overhead and high predictability of our methodology indicate that it is a strong candidate as the preferred design methodology in the dsm era.
assignment of global memory elements for multi-process vhdl specifications. a method for the synthesis of the global memory structure for a behavioral vhdl specification which consists of several concurrent processes is described. the global memory cells may be implemented as separate registers or rams. emphasis was laid on the minimization of both the area demand and timing demand due to access conflicts. the vhdl description is modeled as a petri net. the cases of this petri net are regarded as possible states of the system. the conflicts are then estimated on the basis of the probabilities that the system is in a certain state. finally the global signals are combined to larger memory structures by a clustering algorithm which is guided by both a decrease in area cost and possible conflicts
bit-level arithmetic optimization for carry-save additions. this paper addresses the bit-level optimization of carry-save adder (csa) arrays when the operands are of unequal wordlength (such as in some datapaths in digital signal processing circuits). we first show that by relaxing the carry-save representation to allow for more than two signals per bit position, we gain flexibility in the bit-level implementation of csa arrays that can be exploited to achieve a more efficient design. we then propose algorithms to optimize a single adder array at the bit-level. in addition, we proposed a heuristic to optimize a series of adder arrays that might occur in a datapath. we have applied our algorithms to the optimization of high-speed digital fir filters and have achieved 15% to 30% savings (weighted cost) in the overall filter implementation array in comparison to the standard carry-save implementation.
asf: a practical simulation-based methodology for the synthesis of custom analog circuits. this paper describes asf, a novel cell-level analog synthesis framework that can size and bias a given circuit topology subject to a set of performance objectives and a manufacturing process. to manage complexity and time-to-market, soc designs require a high level of automation and reuse. digital methodologies are inapplicable to analog ip, which relies on tight control of low-level device and circuit properties that vary widely across manufacturing processes. this analog synthesis solution automates these tedious, technology specific aspects of analog design. unlike previously proposed approaches, asf extends the prevalent "schematic and spice" methodology used to design analog and mixed-signal circuits. asf is topology and technology independent and can be easily integrated into a commercial schematic capture design environment. furthermore, asf employs a novel numerical optimization formulation that incorporates classical downhill techniques into stochastic search. asf consistently produces results comparable to expert manual design with 10x fewer candidate solution evaluations than previously published approaches that rely on traditional stochastic optimization methods.
generating sparse partial inductance matrices with guaranteed stability. this paper proposes a definition of magnetic vector potential that can be used to evaluate sparse partial inductance matrices. unlike the commonly applied procedure of discarding the smallest matrix terms, the proposed approach maintains accuracy at middle and high frequencies and is guaranteed to be positive definite for any degree of sparsity (thereby producing stable circuit solutions). while the proposed technique is strictly based upon potential theory (i.e. the invariance of potential differences on the zero potential reference choice), the technique is, nevertheless, presented and discussed in both circuit and magnetic terms. the conventional and the proposed sparse formulation techniques are contrasted in terms of eigenvalues and circuit simulation results on practical examples.
memory binding for performance optimization of control-flow intensive behaviors. this paper presents a memory binding algorithm for behaviors that are characterized by the presence of conditionals and deeply-nested loops that access memory extensively through arrays. unlike previous works, this algorithm examines the effects of branch probabilities and allocation constraints. first, we demonstrate, through examples, the importance of incorporating branch probabilities and allocation constraint information when searching for a performance-efficient memory binding. we also show the interdependence of these two factors and how varying one without considering the other may greatly affect the performance of the behavior. second, we introduce a memory binding algorithm that has the ability to examine numerous bindings by employing an efficient performance estimation procedure. the estimation procedure exploits locality of execution, which is an inherent characteristic of target behaviors. this enables the performance estimation technique to look at the global impact of the different bindings, given the allocation constraints.we tested our algorithm using a number of benchmarks from the parallel computing domain. a series of experiments demonstrates the algorithm's ability to produce bindings that optimize performance, meet memory allocation constraints, and adapt to different resource constraints and branch probabilities. results show that the algorithm requires 37% fewer memories with a performance loss of only 0.3% when compared to a parallel memory architecture. when compared to the best of a series of random memory bindings, the algorithm improves schedule performance by 21%.
generalized symmetries in boolean functions. in this paper we take a fresh look at the notion of symmetries in boolean functions. our studies are motivated by the fact that the classical characterization of symmetries based on invariance under variable swaps is a special case of a more general invariance based on unrestricted variable permutations. we propose a generalization of classical symmetry that allows for the simultaneous swap of ordered and unordered groups of variables, and show that it captures more of a function's invariant permutations without undue computational requirements. we apply the new symmetry definition to analyze a large set of benchmark circuits and provide extensive data showing the existence of substantial symmetries in those circuits. specific case studies of several of these benchmarks reveal additional insights about their functional structure and how it might be related to their circuit structure.
pipeline optimization for asynchronous circuits: complexity analysis and an efficient optimal algorithm. this paper addresses the problem of identifying the minimal pipelining needed in an asynchronous circuit (e.g., number/size of pipeline stages/latches required) to satisfy a given performance constraint, thereby implicitly minimizing area and power for a given performance. in contrast to the somewhat analogous problem of retiming in the synchronous domain, we first show that the basic pipeline optimization problem for asynchronous circuits is np-complete. this paper then presents an efficient branch and bound algorithm that can find the optimal pipeline configuration for moderately-sized problems. our experimental results on a few scalable system models demonstrate that our novel branch and bound solver can find the optimal pipeline configuration for models that have up to 235 possible pipeline configurations.
resynthesis of multi-level circuits under tight constraints using symbolic optimization. we apply recently introduced constructive multi-level synthesis in the resynthesis loop targeting convergence of industrial designs. the incremental ability of the resynthesis approach allows more predictable circuit implementations while allowing their aggressive optimization. the approach is based on a very general symbolic decomposition template for logic synthesis that uses information-theoretical properties of a function to infer its decomposition patterns (rather than more conventional measures such as literal counts). using this template the decomposition is done in a boolean domain unrestricted by the representation of a function, enabling superior implementation choices driven by additional technological constraints. the symbolic optimization is applied in resynthesis of industrial circuits which have tight timing constraints yielding their much improved timing properties.
leakage power optimization techniques for ultra deep sub-micron multi-level caches. on-chip l1 and l2 caches represent a sizeable fraction of the totalpower consumption of microprocessors. in deep sub-micron technology,the subthreshold leakage power is becoming the dominantfraction of the total power consumption of those caches. in thispaper, we present optimization techniques to reduce the leakagepower of on-chip caches assuming that there are multiple thresholdvoltages, vth's, available. first, we show a cache leakage optimizationtechnique that examines the trade-off between access timeand leakage power by assigning distinct vth's to each of the fourmain cache components - address bus drivers, data bus drivers,decoders, and sram cell arrays with sense-amps. second, we showoptimization techniques to reduce the leakage power of l1 and l2on-chip caches without affecting the average memory access time.the key results are: 1) 2 vth's are enough to minimize leakage in asingle cache; 2) if l1 size is fixed, increasing the l2 size can resultin much lower leakage without reducing average memory accesstime; 3) if l2 size is fixed, reducing l1 size can result in lower leakagewithout loss of the average memory access time; and 4) smallerl1 and larger l2 caches than are typical in today's processorsresult in significant leakage and dynamic power reduction withoutaffecting the average memory access time.
coupling-driven signal encoding scheme for low-power interface design. coupling effects between on-chip interconnects must be addressed in ultra deep submicron vlsi and system-on-a-chip (soc) designs. a new low-power bus encoding scheme is proposed to minimize coupled switchings which dominate the on-chip bus power consumption. the coupling-driven bus invert method use slim encoder and decoder architecture to minimize the hardware overhead. experimental results indicate that our encoding methods save effective switchings as much as 30% in an 8-bit bus with one-cycle redundancy.
a novel methodology for statistical parameter extraction. ic manufacturing process variations are typically expressed in terms of joint probability density function (jpdf's) or as worst case combinations/corners of the device model parameters. however, since device models can only provide approximations to actual device behavior, the difference between the two being the modeling error, only a part of the measured variation in device behavior can be modeled using device model parameter variations and the remaining appears as modeling error variation. in this paper, we present a novel statistical parameter extraction methodology that accounts for the effect of modeling error on device model parameter statistics and can be used to quantify the statistical suitability of conventional mos device models.
awe macromodels of vlsi interconnect for circuit simulation. the results of linear asymptotic waveform evaluation (awe) and of nonlinear circuit simulation are combined for the purpose of efficiently incorporating accurate interconnect information in the overall circuit description. a simple macromodel based on the y-parameter description of a complex interconnect network is discussed. the model makes possible the reduction of large, stiff interconnect configurations into compact representations that pose minimal problems to conventional circuit simulation techniques. the macromodel can be incorporated directly into a conventional circuit simulation with no modification of the original simulation software. the techniques are suitable for development as a software library that can be used to enhance existing simulators so that they can handle large vlsi interconnect configurations very efficiently. in addition, the ability to handle elements at the port level makes approach extremely attractive for any linear(ized) macromodels or for application such as mixed-mode simulation
adjustable width linear combinational scan vector decompression. a new scheme for combinational linear expansion isproposed for decompression of scan vectors. it has thecapability to adjust the width of the linear expansion each clockcycle. this eliminates the requirement that every scan bit-slicebe in the output space of the linear decompressor. depending onhow specified the current bit-slice is, the decompressor may loadall scan chains or may load only a subset of the scan chains.this provides the nice feature that any scan vector can begenerated using the proposed scheme regardless of the numberor distribution of the specified bits. thus, the proposed schemeallows the use of any atpg procedure without any constraints.moreover, it allows greater compression to be achieved thanfixed width expansion techniques since the ratio of the number ofscan chains to the number of tester channels can be scaled muchlarger. a procedure for designing and optimizing the adjustablewidth decompression hardware and obtaining the compresseddata is described. experimental data indicates that the proposedscheme is simple yet very effective.
behavior-to-placed rtl synthesis with performance-driven placement. interconnect delay should be considered together with computation delay during architectural synthesis in order to achieve timing closure in deep submicrometer technology. in this paper, we propose an architectural synthesis technique for distributed-register architecture, which separates interconnect delay for data transfer from component delay for computation. the technique incorporates performance-driven placement into the architectural synthesis to minimize performance overhead due to interconnect delay. experimental results show that our methodology achieves performance improvement of up to 60% and 22% on the average.
checking consistency of c and verilog using predicate abstraction and induction. it is common practice to write c models of circuits due to the greater simulation efficiency. once the c program satisfies the requirements, the circuit is designed in a hardware description language (hdl) such as verilog. it is therefore highly desirable to automatically perform a correspondence check between the c model and a circuit given in hdl. we present an algorithm that checks consistency between an ansi-c program and a circuit given in verilog using predicate abstraction. the algorithm exploits the fact that the c program and the circuit share many basic predicates. in contrast to existing tools that perform predicate abstraction, our approach is sat-based and allows all ansi-c and verilog operators in the predicates. we report experimental results on an out-of-order risc processor. we compare the performance of the new technique to bounded model checking (bmc).
automatic translation of behavioral testbench for fully accelerated simulation. this work presents the automated process of translating behavioral testbench into synthesizable one for the hardware-accelerated simulation. testbench is mainly implemented in unsynthesizable hdl description such as time delay, event control, non-static loops and sequential statements. nonetheless, fpga-based accelerator is limited to synthesizable design. to apply hardware acceleration to behavioral testbench, the proposed method automatically translates testbench into equivalent hardware by emulating the standard simulation reference model. by mapping testbench into hardware accelerator to be merged with the design under verification, we can accelerate behavioral testbench and remove the communication overhead between the software simulator and hardware accelerator. our experiments demonstrated that the simulation time is reduced by a factor of about 1000 as compared to the conventional hardware accelerated simulation.
static scheduling of multi-domain memories for functional verification. over the past decade both the quantity and complexity of available on-chip memory resources have increased dramatically. in order to ensure accurate asic behavior, both logic functions and memory resources must be successfully verified before fabrication. often, the functional verification of contemporary asic memory is complicated by the presence of multiple design clocks that operate asynchronously to each other. the presence of multiple clock domains presents significant challenges for large parallel verification systems such as parallel simulators and logic emulators that model both design logic and memory. specifically, multiple asynchronous design clocks make it difficult to verify that design hold times are met during memory model execution and causality along memory data/control paths is preserved during signal communication. in this paper, we describe new scheduling heuristics for memory-based designs with multiple asynchronous clock domains that are mapped to parallel verification systems. our scheduling approach scales to an unlimited number of clock domains and converges quickly to a feasible solution if one exists. it is shown that when our technique is applied to an fpga-based emulator containing 48mb of sram, evaluation fidelity is maintained and increased verification performance is achieved for large, memory-intensive circuits with multiple asynchronous clock domains.
a timing-driven data path layout synthesis with integer programming. we propose an efficient data path synthesis algorithm which generates bit-sliced layouts. since data path circuits have special characteristics which are different from those of random logic circuits, the dedicated synthesis system is required for efficient layouts. our main goal in the data path synthesis is to satisfy the timing constraints of circuits as well as to reduce layout areas. timing-driven placement and over-the-cell routing techniques are developed to generate data path modules. also, signal interfaces between bit-slices are carefully considered to further reduce layout areas. our synthesis techniques take advantage of the common characteristics of data path structures under timing constraints and applies mixed integer linear programming approach to solve the problem. the superior results from our data path synthesis system are demonstrated through comparison with the layout results with the simulated annealing technique.
metrics for structural logic synthesis. routability or wiring congestion in a vlsi chip is becoming increasingly important as chip complexity increases. congestion has a significant impact on performance, yield and chip area. although advances in placement algorithms have attempted to alleviate this problem, the inherent structure of the logic netlist has a significant impact on the routability irrespective of the placement algorithm used. placement algorithms find optimal assignment of locations to the logic and do not have the ability to change the netlist structure. significant decisions regarding the circuit structure are made early in synthesis such as during the technology independent logic optimization step. optimizations in this step use literal count as a metric for optimization and do not adequately capture the intrinsic entanglement of the netlist. two circuits with identical literal counts may have significantly different congestion characteristics post placement. in this paper, we motivate that a property of the network structure called adhesion can make a significant contribution to routing congestion. we then provide a metric to measure this property. we also show that adhesion as measured by this metric can be used in addition to literal counts to estimate and optimize post routing congestion early in the design flow.
dynamic transition relation simplification for bounded property checking. bounded model checking (bmc) is an incomplete property checking method that is based on a finite unfolding of the transition relation to disprove the correctness of a set of properties or to prove them for a limited execution length from the initial states. current bmc techniques repeatedly concatenate the original transition relation to unfold the circuit with increasing depths. in this paper we present a method that is based on a dual unfolding scheme. the first unfolding is non-initialized and progressively simplifies concatenated frames of the transition relation. the tail of the simplified frames is then applied in the second unfolding, which starts from the initial state and checks the properties. we use a circuit graph representation for all functions and perform simplification by merging vertices that are functionally equivalent under given input constraints. in the noninitialized unfolding, previous time frames progressively tighten these constraints thus leading to an asymptotic simplification of the transition relation. as a side benefit, our method can find inductive invariants constructively by detecting when vertices are functionally equivalent across time frames. this information is then used to further simplify the transition relation and, in some cases, prove unbounded correctness of properties. our experiments using industrial property checking problems demonstrate that the presented method significantly improves the efficiency of bmc.
heterogeneous built-in resiliency of application specific programmable processors. using the flexibility provided by multiple functionalities we have developed a new approach for permanent fault-tolerance: heterogeneous built-in-resiliency (hbir). hbir processor synthesis imposes several unique tasks on the synthesis process: (i) latency determination targeting k-unit fault-tolerance, (ii) application-to-faulty-unit matching and (iii) hbir scheduling and assignment algorithms. we address each of them and demonstrate the effectiveness of the overall approach, the synthesis algorithms, and software implementations on a number of designs.
timing analysis in high-level synthesis. a comprehensive timing model for behavioral-level specifications and algorithms for timing analysis in high-level synthesis is described. it is based on a timing network which models the data flow as well as the control flow in the behavioral input specification. the delay values for the network modules are created by invoking the same logic synthesis procedure applied after behavioral synthesis. the timing network is built only once for a given behavioral description. several parameters are used to explore different scheduling possibilities as well as different optimization modes (area, delay), without changing the network. the use of the timing model in conjunction with a path-based scheduling algorithm is presented. results for several benchmarks attested to the accuracy of this approach
micro-preemption synthesis: an enabling mechanism for multi-task vlsi systems. task preemption is a critical enabling mechanism in multi-task vlsi systems. on preemption, data in the register files must be preserved in order for the task to be resumed. this entails extra memory to preserve the context and additional clock cycles to save and restore the context. in this paper, we present techniques and algorithms to incorporate micro-preemption constraints during multi-task vlsi system synthesis. specifically, we have developed: (i) algorithms to insert and refine preemption points in scheduled task graphs subject to preemption latency constraints. (ii) techniques to minimize the context switch overhead by considering the dedicated registers required to save the state of a task on preemption and the shared registers required to save the remaining values in the tasks. (iii) a controller based scheme to preclude preemption related performance degradation. the effectiveness of all approaches, algorithms, and software implementations is demonstrated on real examples.
timing-safe false path removal for combinational modules. a combinational module is a combinational circuit that can be used under any arrival time condition at the primary inputs. an intellectual property (ip) module, if combinational, is one such example. the false-path-aware delay characterization of a combinational module without disclosing its internal structural detail is crucial for accurate timing analysis of ip-based designs.this paper addresses three related issues on delay characterization of combinational modules. we first introduce a new notion called timing-safe replaceability as a way of comparing the timing characteristics of two combinational modules formally. this notion allows us to determine whether a new module is a safe replacement of an original module under any surrounding environment with respect to timing. second, we consider false path detection of combinational modules. although false path detection is essential in accurate delay modeling, we argue that the conventional definition of false paths such as floating mode analysis is not appropriate for defining the falsity of a path for a combinational module since the falsity is relative to an arrival time condition. a new definition of false paths, termed strongly false paths, is introduced to resolve this issue. strongly false paths are those paths that are guaranteed to be false under any arrival time condition, and thus uniquely defined independent of arrival time conditions. finally, we propose a new algorithm that removes strongly false paths from a combinational module by a circuit transformation. we prove that the resulting circuit is a timing-safe replacement of the original.
implication graph based domino logic synthesis. in this paper, we present a new approach to the problem of inverter elimination in domino logic synthesis. a small piece of static cmos logic is introduced to the circuit to avoid significant area penalty resulting from duplication. to maximize the domino logic part and to minimize the static cmos logic part, a generalized atpg based logic transformation is proposed to eliminate or relocate a target inverter. based on the new concept of dominating set of mandatory assignment (dsma) and the corresponding implication graph, we propose algorithms to identify a minimum candidate set for a target inverter. experimental results show that logic transformation based on implication graph can reduce transistor counts by 25% and power delay product by 25% on average.
probabilistic state space search. this paper describes a probabilistic approach to state space search. the presented method applies a ranking of the design states according to their probability of reaching a given target state based on a random walk model. this ranking can be used to prioritize an explicit or partial symbolic state exploration to find a trajectory from a set of initial states to a set of target states. a symbolic technique for estimating the reachability probability is described which implements a smooth trade-off between accuracy and computing effort. the presented probabilistic state space search complements incomplete verification methods which are specialized in finding errors in large designs.
techniques for improving the accuracy of geometric-programming based analog circuit design optimization. we present techniques for improving the accuracy of geometric-programming (gp) based analog circuit design optimization. we describe major sources of discrepancies between the results from optimization and simulation, and propose several methods to reduce the error. device modeling based on convex piecewise-linear (pwl) function fitting is introduced to create accurate active and passive device models. we also show that in selected cases gp can enable nonconvex constraints such as bias constraints using monotonicity, which help reduce the error. lastly, we suggest a simple method to take the modeling error into account in gp optimization, which results in a robust design over the inherent errors in gp device models. two-stage operational amplifier and on-chip spiral inductor designs are given as examples to demonstrate the presented ideas.
rectification method for lookup-table type fpga's. a method to rectify lookup-table-type field-programmable gate array (fpga) designs is presented. instead of changing the netlist, only the functionality realized by lookup tables in a chip is modified and the netlist is retained so that there is no change in the delay of the chip. the problem is formalized using characteristic functions, and a redesign technique based on boolean relations is presented
a redesign technique for combinational circuits based on gate reconnections. in this paper, we consider a redesign technique applicable to combinational circuits implemented with gate-array or standard-cell technology, where we rectify an existing circuit only by reconnecting gates on the circuit with all the gate types unchanged. this constraint allows us to reuse the original placement as is, thereby speeding up the total time needed for a redesign. we formulate this problem as a boolean-constraint problem and give a bdd-based algorithm to check the feasibility of redesign.
fast test application technique without fast scan clocks. built-in self-test (bist) schemes need to set the state of the circuit under test (cut) for each test vector applied. the two primary techniques by which the state is set are test-per-scan and test-per-clock. in a test-per-scan scheme, circuit states are set using one or more scan chains. several scan cycles are required to apply a single test vector. in very large circuits, the time to apply each test vector may be quite high. the direct option of reducing test time with a fast scan clock is difficult to realize in practice. in a test-per-clock scheme, all circuit flip-flops are loaded in parallel. a new test vector can be applied in each cycle. the area overhead incurred in accessing each storage element directly is quite significant. we propose a new broadcast bist (b2ist) scheme as a compromise between the two approaches. b2ist uses time-division multiplexing (tdm) to load multiple storage elements in a broadcast group in a single clock cycle, but through only a single scan data input. based on our b2ist simulation, we compare the layout overhead and performance of b2ist with that of traditional bist schemes on iscas benchmark circuits. thus, b2ist can achieve the performance of a test-per-clock scheme, but only incur the overhead of a test-per-scan scheme.
approximate timing analysis of combinational circuits under the xbd0 model. this paper is concerned with approximate delay computation algorithms for combinational circuits. as a result of intensive research in the early 90's efficient tools exist which can analyze circuits of thousands of gates in a few minutes or even in seconds for many cases. however, the computation time of these tools is not so predictable since the internal engine of the analysis is either a sat solver or a modified atpg algorithm, both of which are just heuristic algorithms for an np-complete problem. although they are highly tuned for cad applications, there exists a class of problem instances which exhibits the worst-case exponential cpu time behavior. in the context of timing analysis, circuits with a high amount of reconvergence, e.g. c6288 of the iscas benchmark suite, are known to be difficult to analyze under sophisticated delay models even with state-of-the-art techniques. for example [mcgeer93] could not complete the analysis of c6288 under the mapped delay model. to make timing analysis of such corner case circuits feasible we propose an approximate computation scheme to the timing analysis problem as an extension to the exact analysis method proposed in [mcgeer93]. sensitization conditions are conservatively approximated in a selective fashion so that the size of sat problems solved during analysis is controlled. experimental results show that the approximation technique is effective in reducing the total analysis time without losing accuracy for the case where the exact approach takes much time or cannot complete.
folding of logic functions and its application to look up table compaction. the paper describes the folding method of logic functions to reduce the size of memories for keeping the functions. the folding is based on the relation of fractions of logic functions. we show that the fractions of the full adder function have the bit-wise not relation and the bit-wise or relation, and that the memory size becomes half (8-bit). we propose a new 3--1 lut with the folding mechanisms whcih can implement a full adder with one lut. a fast carry propagation line is introduced for a multi-bit addition. the folding and fast carry propagation mechanisms are shown to be useful to implement other multi-bit operations and general 4 input functions without extra hardware resources. the paper shows the reduction of the area consumption when using our luts compared to the case using 4--1 luts on several benchmark circuits.
precise timing verification of logic circuits under combined delay model. a combined delay model to manipulate the variance of the delay time of logic elements and a timing verification method based on the theory of regular expressions are presented. emphasis is placed on the hazard detection problem and the verification of asynchronous circuits. the effectiveness of the method with medium sized circuits including about 100 elements is shown
atpg for noise-induced switch failures in domino logic. domino circuits have been used in most modern high-performance microprocessordesigns because of their high speed, low transistor-count andhazard-free operation. however, with technology scaling, domino circuitsare increasingly susceptible to switch failures due to various noise sourcesthat include crosstalk, charge sharing and leakage. to test for such failuresin a manufactured chip, we describe a test pattern generation methodologythat generates specific test patterns to target such failures. these testpatterns activate noise from multiple sources such that their combined effectcauses a switch failure at a domino gate output. in addition, the testpatterns propagate the resulting error to an observable output within theduration of the circuit's clock cycle. the methodology has been implementedand validated using a domino multiplier circuit.
finfets for nanoscale cmos digital integrated circuits. suppression of leakage current and reduction in device-to-device variability are key challenges for sub-45nm cmos technologies. nonclassical transistor structures such as the finfet are likely necessary to meet transistor performance requirements in the sub-20nm gate length regime. this paper presents an overview of finfet technology and describes how it can be used to improve the performance, standby power consumption, and variability in nanoscale-cmos digital ics.
a scheduling method by stepwise expansion in high-level synthesis. a fast heuristic method for the scheduling problem that minimizes hardware costs of functional units, registers, and buses on the basis of an integer linear programming (ilp) model is proposed. in the method, the total computation time can be greatly reduced compared to the general ilp method, since the number of the integer variables which appear in the ilp formulation is reduced by introducing a stepwise expansion approach. results obtained for a practical scheduling problem indicate that the computation time of the proposed method is linear to the number of the control steps, and optimal or near-optimal solutions can be found
a zero-skew clock routing scheme for vlsi circuits. a clock routing scheme that guarantees a zero-skew routing result is proposed. it is shown that the time complexity for the algorithm can be reduced to o(n2 log n) by using the modified voronoi diagram to structure the algorithm. l-shaped pairing and h-flipping operations are introduced to further reduce the clock wire length. extensions are made to the algorithm for use in building-block layout and zero skew is also achieved. significant reduction in total clock wire lengths is observed
techniques for crosstalk avoidance in the physical design of high-performance digital systems. interconnect performance does not scale well into deep submicron dimensions, and the rising number of analog effects erodes the digital abstraction necessary for high levels of integration. in particular, crosstalk is an analog phenomenon of increasing relevance. to cope with the increasingly analog nature of high-performance digital system design, we propose using a constraint-driven methodology. in this paper we describe new constraint generation ideas incorporating digital sensitivity. in constraint-driven synthesis, we show that a fundamental subproblem of crosstalk channel routing, coupling-constrained graph levelization (ccl), is np-complete, and develop a novel heuristic algorithm. to demonstrate the viability of our methodology, we introduce a gridless crosstalk-avoiding channel router as an example of a robust and truly constraint-driven synthesis tool.
driving toward higher iddq test quality for sequential circuits: a generalized fault model and its atpg. we propose a generalized stuck-at fault model for sequential circuits under the selective iddq test strategy. the proposed fault model makes a pessimistic assumption on the boolean fault effects when the fault is activated. we show that by using the proposed fault model, test sequences of higher quality can be generated and/or selected. we further propose a test vector generation and selection method for this fault model. we present results to illustrate that a high fault coverage for the proposed fault model can be achieved by a small test set under the selective iddq test environment.
efficient harmonic balance simulation using multi-level frequency decomposition. efficient harmonic balance (hb) simulation provides a useful tool for the design of rf and microwave integrated circuits. for practical circuits that can contain strong nonlinearities, however, hb problems cannot be solved reliably or efficiently using conventional techniques. various preconditioning techniques have been proposed to facilitate a robust and efficient analysis based on krylov subspace linear solvers. in this work we introduce a multi-level frequency domain preconditioner based on a hierarchical frequency decomposition approach. at each newton iteration, we recursively solve a set of smaller problems to provide an effective preconditioner for the large linearized hb problem. compared to the standard single-level block diagonal preconditioner, our experiments indicate that our approach provides a more robust, memory efficient solution while offering a 2-9/spl times/ speedup for several strongly nonlinear hb problems in our experiments.
digital sensitivity: predicting signal interaction using functional analysis. maintaining signal integrity in digital systems is becoming increasingly difficult due to the rising number of analog effects seen in deep submicron design. one such effect, the signal crosstalk problem, is now a serious design concern. signals which couple electrically may not affect system behavior because of timing or function in the digital domain. if we can isolate observable coupling effects then we can constrain layout synthesis to eliminate them. in this paper, we find that it is possible to predict signal interaction by signal functionality alone, leading to a significant amount of robust switching isolation, independent of parasitics introduced by layout or semiconductor process. we introduce techniques to predict signal interaction using functional sensitivity analysis. in general sequential networks we find that significant switching isolation can be extracted with efficient sensitivity analysis algorithms, thus giving promise to the goal of synthesizing layout free from crosstalk effects.
transistor-level timing analysis using embedded simulation. a high accuracy system for transistor-level static timing analysis is presented. accurate static timing verification requires that individual gate and interconnect delays be accurately calculated. at the sub-micron level, calculating gate and interconnect delays using delay models can result in reduced accuracy. instead, the proposed method calculates delays through numerical integration using an embedded circuit simulator. it takes into account short circuit current and carefully chooses the set of conditions that results in a tight upper bound of the worst case delay for each gate. similar repeating transistor configurations of gates in the circuit are automatically identified and a novel interpolation based caching scheme quickly computes gate delays from the delays of similar gates. a tight object code level integration with a commercial high speed transistor-level circuit simulator allows efficient invocation of the simulation.
simulation methods for rf integrated circuits. the principles employed in the development of modern rf simulators are introduced and the various techniques currently in use, or expected to be in use in the next few years, are surveyed. frequency and time domain techniques are presented and contrasted, as are steady state and envelope techniques and large and small signal techniques.
application-driven synthesis of core-based systems. we developed a new hierarchical modular approach for synthesis of area-minimal core-based data-intensive systems. the optimization approach employs a novel global least-constraining most-constrained heuristic to minimize the instruction cache misses for a given application, instruction cache size and organization. based on this performance optimization technique, we constructed a strategy to search for a minimal-area processor core, and an instruction and data cache which satisfy the performance characteristics of a set of target applications. the synthesis platform integrates the existing modeling, profiling, and simulation tools with the developed system-level synthesis tools. the effectiveness of the approach is demonstrated on a variety of modern real-life multimedia and communication applications.
hazard-non-increasing gate-level optimization algorithms. hazard-non-increasing optimization algorithms, optimizations on gate-level logic without introduction of any further static nor dynamic hazards, are presented. proofs are given for general theoretical results on hazard-non-increasing transformations which serve as the basis for these algorithms. the algorithms substantially augment the set of proven hazard-non-increasing optimization techniques in the literature. these algorithms are useful for hazard-free implementations of asynchronous designs
a quantitative approach to functional debugging. we introduce a novel cut-based debugging paradigm. it coordinates design emulation and simulation and enables fast transition from one to another. emulation or functional implementation is used for fast application execution; simulation provides complete design observability and controllability. the implementation of the new debugging approach poses several cad tasks. we formulate the optimization tasks and develop constraint-based heuristics to solve them. effectiveness of the approach is demonstrated on a set of designs.
hyhope: a fast fault simulator with efficient simulation of hypertrophic faults. in sequential circuit fault simulation, the hypertrophic faults, which result from lengthened initialization sequence in the faulty circuits, usually produce a large number of fault events during simulation and require excessive gate evaluations. these faults degrade the performance of fault simulators attempting to simulate them exactly. in this paper, an exact simulation algorithm is developed to identify the hypertropic faults and to minimize their effects during the fault simulation. the simulator hyhope based on this algorithm shows that the average speedup ratio over hope 1.1 is 1.57 for iscas89 benchmark circuits. furthermore, the result indicates the performance of hyhope is close to the approximate simulator in which faults are simply dropped when they become potentially detected.
localized watermarking: methodology and application to operation scheduling. this paper addresses the copyright protection problem of integrated circuits designed with blocks which are originated from multiple design sources. the process consists of two phases. first, a compact signature is generated from every block independently and made public. utilizing such signatures, a design can be decomposed into its original building blocks, regardless of multiple hierarchies. then, a map of all the blocks can be built, thus allowing to reconstruct the original copyright dependencies. the proposed methodology can be used by foundries to verify that designs submitted for fabrication contain blocks traceable to a legal source of intellectual property. the verification process is also useful to intellectual property providers and integrators, as it reduces the likelihood of infringement, thus ultimately minimizing the risk of litigation.
optimal p/n width ratio selection for standard cell libraries. the effectiveness of logic synthesis to satisfy increasingly tight timing constraints in deep-submicron high-performance circuits heavily depends on the range and variety of logic gates available in the standard cell library. primarily, research in the design of high-performance standard cell libraries has been focused on drive strength selection of various logic gates. since cmos logic circuit delays not only depend on the drive strength of each gate but also on its p/n width ratio, it is crucial to provide good p/n width ratios for cach cell. the main contribution of this paper is the development of a theoretical framework through which library designers can determine &ldquo;optimal&rdquo; p/n width ratio for each logic gate in their high-performance standard cell library. this theoretical framework utilizes new gate delay models that explicitly represent the dependence of delay on p/n width ratio and load. these delay models yield highly accurate delay for cmos gates in a 0.12&mgr;m leff deep-submicron technology.
a novel net weighting algorithm for timing-driven placement. net weighting for timing-driven placement has been very popular in industry and academia. it has various advantages such as low complexity, high flexibility and ease of implementation. existing net weighting algorithms, however, are often ad-hoc. there is generally no known good net weighting algorithms. in this paper, we present a novel net weighting algorithm based on the concept of path-counting, and apply it in timing-driven fpga placement application. theoretically this is the first ever known accurate, all-path counting algorithm. experimental data shows that compared with the weighting algorithm used in state-of-the-art fpga placement package vpr[1], this new algorithm can achieve the longest path delay reduction of up to 38.8%, 15.6% on average with no runtime overhead and only a 4.1% increase in total wirelength.
silca: fast-yet-accurate time-domain simulation of vlsi circuits with strong parasitic coupling effects. we propose a new circuit analysis method, namelysemi-implicit linear-centric analysis (silca), for efficientspice-accurate transient simulation of deep-submicron vlsicircuits with strong parasitic coupling effects introduced byinterconnect lines, common substrate, power/ground networks, etc.silca is based on two linear-centric techniques. first, a new semi-implicititerative numerical integration scheme is developed, whichapplies dynamic time step control accounting for stiff systems andmeanwhile keeps constant equivalent conductance forcapacitor/inductor companion models. its convergence and stabilityproperties are characterized. second, to achieve constant linearizedconductance for nonlinear devices during nonlinear iterationprocess, a successive variable chord method is introduced as analternative of the newton-raphson method and the rank-one updatetechnique is implemented for fast lu factorization. with thesetechniques, silca reduces the number and cost of required lufactorizations dramatically. experimental results on substrate andpower/ground networks have demonstrated that silca yieldsspice-like accuracy with an over 80x reduction in lufactorization cost, and an about 20x overall cpu time speedup overspice3 for circuits with tens of thousands elements, and theefficiency increases further with the size of a circuit.
partial scan delay fault testing of asynchronous circuits. asynchronous circuits operate correctly only under timing assumptions. hence testing those circuits for delay faults is crucial. this paper describes a three-step method to detect possible delay faults in a sequential asynchronous circuit. the delays that are to be tested must be provided by the synthesis system. by using this information a set of paths in the circuit that must be tested is identified (step 1). for these paths the circuit is made acyclic by inserting at least one scan latch in every cycle (step 2). then test patterns are generated for these paths (step 3). these test patterns consist of setup and initialization vectors and the final test vector. we provide effective procedures to solve both the initialization and the test pattern generation problem. the latter problem is solved by reduction to a classical problem of stuck-at test pattern generation for a related combinational circuit. finally, a heuristic is proposed to determine which state variables must become part of a scan chain, or for which input variables the positive and negative phase must be driven independently in test mode. experimental results shows that a high level of path delay fault testability can be achieved with partial scan.
fault simulation of interconnect opens in digital cmos circuits. we describe a highly accurate but efficient fault simulator for interconnect opens, based on characterizing the standard cell library with spice; using transistor charge equations for the site of the open; using logic simulation for the rest of the circuit; taking four different factors, that can affect the voltage of an open, into account; and considering the oscillation and sequential behavior potential of opens. a novel test technique based on controlling the die surface voltage is also described. we present our simulation results of iscas85 layouts using stuck-at and iddq test sets.
efficient computation of small abstraction refinements. in the abstraction refinement approach to model checking, the discovery of spurious counterexamples in the current abstract model triggers its refinement. the proof - produced by a sat solver - that the abstract counterexamples cannot be concretized can be used to identify the circuit elements or predicates that should be added to the model. it is common, however, for the refinements thus computed to be highly redundant. a costly minimization phase is therefore often needed to prevent excessive growth of the abstract model. in this work we show how to modify the search strategy of a sat solver so that it generates refinements that are close to minimal, thus greatly reducing the time required for their minimization.
automated data dependency size estimation with a partially fixed execution ordering. for data dominated applications, the system level design trajectory should first focus on finding a good data transfer and storage solution. since no realization details are available at this level, estimates are needed to guide the designer. this paper presents an algorithm for automated estimation of strict upper and lower bounds on the individual data dependency sizes in high level application code given a partially fixed execution ordering. previous work has either not taken execution ordering into account at all, resulting in large overestimates, or required a fully specified ordering which is usually not available at this high level. the usefulness of the methodology is illustrated on representative application demonstrators.
multi-level logic optimization by implication analysis. this paper proposes a new approach to multi-level logic optimization based on atpg (automatic test pattern generation). previous atpg-based methods for logic minimization suffered from the limitation that they were quite restricted in the set of possible circuit transformations. we show that the atpg-based method presented here allows (in principle) the transformation of a given combinational network c into an arbitrary, structurally different but functionally equivalent combinational network c'. furthermore, powerful heuristics are presented in order to decide what network manipulations are promising for minimizing the circuit. by identifying indirect implications between signals in the circuit, transformations can be derived which are &ldquo;good&rdquo; candidates for the minimization of the circuit. in particular, it is shown that recursive learning can derive &ldquo;good&rdquo; boolean divisors justifying the effort to attempt a boolean division. for 9 out of 10 iscas-85 benchmark circuits our tool hannibal obtains smaller circuits than the well-known synthesis system sis.
concurrent d-algorithm on reconfigurable hardware. in this paper, a new approach for generating test vectors that detects faults in combinational circuits is introduced. the approach is based on automatically designing a circuit which implements the d-algorithm, an automatic test pattern generation (atpg) algorithm, specialized for the combinational circuit. our approach exploits fine-grain parallelism by performing the following in three clock cycles: direct backward/forward implications, conflict checking, selecting next gate to propagate fault or to justify a line, decisions on gate inputs, loading the state of the circuit after backup. in this paper, we show the feasibility of this approach in terms of speed, and how it compares with software based techniques.
fast methods for simulation of biomolecule electrostatics. computer simulation is an important tool for improving our understanding of biomolecule electrostatics, in part to aid in drug design. however, the numerical techniques used in these simulation tools do not exploit fast solver approaches widely used in analyzing integrated circuit interconnects. in this paper we describe one popular formulation used to analyze biomolecule electrostatics, present an integral formulation of the problem, and apply the precorrected-fft method to accelerate the solution of the integral equations.
a methodology for verifying memory access protocols in behavioral synthesis. memory is one of the most important components to be optimized in the several phases of the synthesis process. in behavioral synthesis, a memory is viewed as an abstract construct which hides the detail implementations of the memory. consequently, for a vendor's memory, behavioral synthesis should create a clean model of the memory wrapper which abstracts the properties of the memory that are required to interface to the rest of the circuit. however, this wrapping process invariably demands the verification problem of the memory access protocols in order to be safely used in behavioral synthesis environment. in this paper, we propose a systematic methodology of verifying the correctness of the memory wrapper. specifically, we analyze the complexity of the problem, and derive an effective solution which is not only practically efficient but also highly reliable. for designers who use memories as design components in behavioral synthesis, automating our solution shortens the verification time significantly in contrast of simulating memory accesses in the context of full design, which is a quite complex and time-consuming process, especially for designs with many memory access operations.
hardware/software co-synthesis with memory hierarchies. this paper introduces the first hardware/software co-synthesis algorithm of distributed real-time systems that optimize the memory hierarchy along with the rest of the architecture. memory hierarchies (caches) are essential for modern embedded cores to obtain high performance. they also represent a significant portion of the cost, size and power consumption of many embedded systems. our algorithm synthesizes a set of real-time tasks with data dependencies onto a heterogeneous multiprocessor architecture that meets the performance constraints with minimized cost. unlike previous work in co-synthesis, our algorithm not only synthesizes the hardware and software portions of the applications, but also the memory hierarchies. it chooses cache sizes and allocates tasks to caches as part of co-synthesis. the algorithm is built upon a task-level performance model for memory hierarchies. experimental results, including examples from the literature and results on real-life examples such as an mpeg-2 encoder, show that our algorithm is efficient, and compared with existing algorithms, it can reduce the overall cost of the synthesized system.
regularity driven logic synthesis. we present a new and innovative logic synthesis approach using regularity information of a design to selectively apply transformations and globally guide the synthesis process.since traditional logic synthesis applies transformations without consideration of global design characteristics such as regularity and dataflow, it destroys a substantial amount of regular structures. in addition, due to the non-incremental nature of most logic transformations, synthesis relies vastly on the computationally expensive concept of trial and error application of transformations, a time-consuming process in the synthesis of large designs.the proposed approach addresses both shortcomings of traditional logic synthesis and describes a mechanism to speed up logic synthesis and preserve regularity. it selectively applies transformations to places with similar characteristics and to the same stage of a regular structure, introducing a notion of dataflow-aware synthesis.preservation of regular structures has tremendous advantages to the following physical design stages. it yields high-density layouts, shorter wiring length and improved delay. in addition, the layout becomes more predictable at an earlier design stage.
embedded tutorial: formal equivalence checking between system-level models and rtl. a rigorous system-level model (slm) for a hardware design project is extremely important, often critical. such a functional model not only defines the architect's ideas but also builds a precise foundation for both hardware designers and verification engineers. the key uses of slms are: architecture validation; performance modeling and architectural trade-off; platforms for software development and verification; and functional reference model. in this tutorial, we discuss how to formally verify sequential equivalence between slms and rtl, for both timed and untimed models. first, we provide a formal definition of the sequential equivalence. then we discuss various formal verification technology that enables such practice in real designs.
design/process learning from electrical test. modern design-for-test (dft) practices not only simplify test generation but also make it much easier to diagnose problems uncovered in electrical test. in fact, many diagnostics steps can be automated enough to enable batch processing of large quantities of fail data captured during production test. hidden in these fail data is very valuable information about the product design, manufacturing process, and interactions between the two. the embedded tutorial provides an overview of some of the analysis methods that are being used and/or prototyped in the industry, as well as the underlying data sharing between the design and manufacturing areas that is required for and enabled by the analyses.
optimization and control of and for low-power, high-speed cmos design. it is essential to control vdd and vth for low-power, high-speed cmos design. in this paper, it is shown that these two parameters can be controlled by designers as objectives of design optimization to find better trade-offs between power and speed. quantitative analysis of trade-offs between power and speed is presented. some of the popular circuit techniques and design examples to control vdd and vth are introduced. a simple theory to compute optimum multiple vdd's and vth's is described. scaling scenarios of variable and/or multiple vdd's and vth's is discussed to show future technology directions.
verifying hardware in its software context. we describe a method for verifying hardware whose correct behavior depends upon its software interface. it is presumed that the hardware is presented as a synchronous rtl model whereas the software is presented as an asynchronous abstraction. our methodology incorporates partial order reduction on the software side, and localization reduction, to deal with the computational complexity of the verification. the partial order reduction is implemented as a constraint on the transition relation of a synchronous transformation of the software model. the reduced transformed model then may be verified using a verification algorithm whose scope is purely synchronous models, without modification. thus, independent of the interface verification problem, this gives a general method for combining partial order reduction with symbolic model-checking.
performance optimization of latency insensitive systems through buffer queue sizing of communication channels. this paper proposes for latency insensitive systems a performanceoptimization technique called channel buffer queue sizing, whichis performed after relay station insertion in the physical designstage. it can be shown that proper queue sizing can reduce or evencompletely avoid the performance loss due to imbalanced relaystations insertion in reconvergent paths. moreover, the problemof queue sizing and placement of the additional buffers for maximumperformance is formulated and studied to properly allocateavailable chip areas in the layout to communication channels. analgorithm based on mixed integer linear programming is proposed.experimental results show that queue sizing is effective in improvingthe performance of latency insensitive systems even under tightarea constraints. moreover, the proposed algorithm is sufficientlyefficient in obtaining the optimal solution for systems of practicalsizes.
samba-bus: a high performance bus architecture for system-on-chips. a high performance communication architecture, samba-bus, isproposed in this paper. in samba-bus, multiple compatible bustransactions can be performed simultaneously with only a singlebus access grant from the bus arbiter. experimental results showthat, compared with a traditional bus architecture, the samba-busarchitecture can have up to 3.5 times improvement in the effectivebandwidth, and up to 15 times reduction in the average communicationlatency. in addition, the performance of samba-bus architectureis affected only slightly by arbitration latency, because bustransactions can be performed without waiting for the bus accessgrant from the arbiter. this feature is desirable in soc designs withlarge numbers of modules and long communication delay betweenmodules and the bus arbiter.
congestion aware layout driven logic synthesis. in this paper, we present novel algorithms that effectively combine physical layout and early logic synthesis to improve overall design quality. in addition, we employ partitioning and clustering algorithms to achieve faster turn around times.with the increasing complexity of designs, the traditional separation of logic and physical design leads to sub-optimal results as the cost functions employed during logic synthesis do not accurately represent physical design information. while this problem has been addressed extensively, the existing solutions apply only simple synthesis transforms during physical layout and are generally unable to reverse decisions made during logic minimization and technology mapping, that have a major negative impact on circuit structure.in our novel approach, we propose congestion aware algorithms for layout driven decomposition and technology mapping, two of the steps that affect congestion the most during logic synthesis, to effectively decrease wire length and improve congestion. in addition, to improve design turn-around-time and handle large designs, we present an approach in which synthesis partitioning and placement clustering co-exist, reflecting the different characteristics of logical and physical domain.
projection-based performance modeling for inter/intra-die variations. large-scale process fluctuations in nano-scale ic technologies suggest applying high-order (e.g., quadratic) response surface models to capture the circuit performance variations. fitting such models requires significantly more simulation samples and solving much larger linear equations. in this paper, we propose a novel projection-based extraction approach, probe, to efficiently create quadratic response surface models and capture both inter-die and intra-die variations with affordable computation cost. probe applies a novel projection scheme to reduce the response surface modeling cost (i.e., both the required number of samples and the linear equation size) and make the modeling problem tractable even for large problem sizes. in addition, a new implicit power iteration algorithm is developed to find the optimal projection space and solve for the unknown model coefficients. several circuit examples from both digital and analog circuit modeling applications demonstrate that probe can generate accurate response surface models while achieving up to 12/spl times/ speedup compared with the traditional methods.
prop: a recursive paradigm for area-efficient and performance oriented partitioning of large fpga netlists. in this paper, we introduce a new recursive partitioning paradigm prop which combines (p)artitioning, (r)eplication, (o)ptimization, to be followed by another recursion of (p)artitioning, etc. we measure the quality of partitions in terms of total device cost, logic and terminal utilization, and critical path delay. traditionally, the minimum lower bound into which a given netlist can be partitioned is determined by disregarding the logic interconnect while distributing the logic nodes into a minimum number of devices. prop paradigm challenges this assumption by demonstrating feasible partitions of some large netlists such that the number of device partitions is smaller than minimum lower bounds postulated initially. overall, we report consistent reductions in the total number of partitions for a wide range of combinational and sequential circuit benchmarks while, on the average, reducing critical path delay as well.
a hybrid approach to nonlinear macromodel generation for time-varying analog circuits. modeling frequency-dependent nonlinear characteristics of complexanalog blocks and subsystems is critical for enabling efficientverification of mixed-signal system designs. recent progress hasbeen made for constructing such macromodels, however, their accuracyand/or efficiency can break down for certain problems, particularlythose with high-q filtering. in this paper we explore a novelhybrid approach for generating accurate analog macromodels fortime-varying weakly nonlinear circuits. the combined benefits ofnonlinear padé approximations and pruning by exploitation of thesystem's internal structure allows us to construct nonlinear circuitmodels that are accurate for wide input frequency ranges, and therebycapable of modeling systems with sharp frequency selectivity.such components are widely encountered in analog signal processingand rf applications. the efficacy of the proposed approach isdemonstrated by the modeling of large time-varying nonlinear circuitsthat are commonly found in these application areas.
combinational equivalence checking through function transformation. circuits can be simplified for combinational equivalence checking by transforming internal functions, while preserving their ranges. in this paper, we investigate how to effiectively apply the idea to improve equivalence checking. we propose new heuristics to identify groups of nets in a cut, and elaborate detailed aspects of the new equivalence checking method. with a given miter, we identify a group of nets in a cut and transform the function of each net into a more compact representation with less variables. these new compact parametric representations preserve the range of nets as well as of the cut. this transformation significantly reduces the size of intermediate bdds and enables the verification to be conclusive for many designs which state-of-the-art equivalence checkers fail to verify. iterative groupings and transformations are performed until no grouping is possible for a cut. then we proceed to the next cut and continue until the compare point is reached. our experimental results show the effiectiveness of our strategy and new grouping heuristics on the new method.
asymptotic probability extraction for non-normal distributions of circuit performance. while process variations are becoming more significant with each new ic technology generation, they are often modeled via linear regression models so that the resulting performance variations can be captured via normal distributions. nonlinear (e.g. quadratic) response surface models can be utilized to capture larger scale process variations; however, such models result in non-normal distributions for circuit performance which are difficult to capture since the distribution model is unknown. in this paper we propose an asymptotic probability extraction method, apex, for estimating the unknown random distribution when using nonlinear response surface modeling. apex first uses a binomial moment evaluation to efficiently compute the high order moments of the unknown distribution, and then applies moment matching to approximate the characteristic function of the random circuit performance by an efficient rational function. a simple statistical timing example and an analog circuit example demonstrate that apex can provide better accuracy than monte carlo simulation with 10 samples and achieve orders of magnitude more efficiency. we also show the error incurred by the popular normal modeling assumption using standard ic technologies.
formulae and applications of interconnect estimation considering shield insertion and net ordering. it has been shown recently that simultaneous shield insertion and net ordering (called sino/r as only random shields are used) provides an area-efficient solution to reduce the rlc noise. in this paper, we first develop simple formulae with errors less than 10% to estimate the number of shields in the min-area sino/r solution. in order to accommodate pre-routed p/g wires that also serve as shields, we then formulate two new sino problems: sino/spr and sino/upg, and propose effective and efficient two-phase algorithms to solve them. compared to the existing dense wiring fabric scheme, the resulting sino/spr and sino/upg schemes maintain the regularity of the p/g structure, have negligible penalty on noise and delay variation, and reduce the total routing area by up to 42% and 36%, respectively. further, we develop various pre-layout estimation formulae for shielding areas and optimal p/g structures under different routing styles. these formulae can be readily used to guide global routing and high-level design decisions.
performance estimation of embedded software with instruction cache modeling. embedded systems generally interact with the outside world. thus, some real-time constraints may be imposed on the system design. verification of these constraints requires computing a tight upper bound on the worst case execution time (wcet) of a hardware/software system. the problem of bounding wcet is particularly difficult on modern processors, which use cache-based memory systems that vary memory access time significantly. this must be accurately modeled in order to tightly bound wcet. existing approaches either search all possible program paths, an intractable problem, or they use pessimistic assumptions to limit the search space. in this paper we present a far more effective and accurate method for modeling instruction cache activity and computing a tight bound on wcet. it is implemented in the program \texttt{cinderella}. we present some preliminary results of using this tool on sample embedded programs.
efficient full-chip thermal modeling and analysis. the ever-increasing power consumption and packaging density of integrated systems creates on-chip temperatures and gradients that can have a substantial impact on performance and reliability. while it is conceptually understood that a thermal equivalent circuit can be constructed to characterize the temperature gradients across the chip, direct and iterative solutions of the corresponding 3d equations are often intractable for a full-chip analysis. multigrid accelerated iterative methods can be applied to solve the equivalent circuit problem that is provably symmetric positive definite; however, explicitly building the matrix problem is intractable for most full-chip problems. in this work we present a multigrid iterative approach for the full-chip thermal analysis which does not require explicit construction of the equivalent circuit matrix. we propose specific multigrid treatments to cope with the strong anisotropy of the full-chip thermal problem that is created by the vast difference in material thermal properties and chip geometries. importantly, we demonstrate that only with careful thermal modeling assumptions and appropriate choices for grid hierarchy, multigrid operators and smoothing steps across grid points, can we accurately and efficiently analyze a full-chip thermal problem. experimental results demonstrate the efficacy of the proposed multigrid methodology. our prototyped thermal simulator is able to solve a steady-state problem with more than 10 million unknowns in 125 cpu seconds with a peak memory usage of 231 mega bytes.
a probabilistic timing approach to hot-carrier effect estimation. an approach for estimating hot-carrier induced degradation in mos transistor circuits is presented. the approach uses probabilistic timing simulation techniques to estimate the cumulative effects of all possible inputs on hot-carrier effect (hce) degradation in each transistor in the circuit in a single run rather than using exhaustive or monte carlo simulations. the approach has been implemented in a general-purpose simulator and tested on a number of typical examples and benchmarks
managing power and performance for system-on-chip designs using voltage islands. this paper discusses voltage islands, a system architecture and chip implementation methodology, that can be used to dramatically reduce active and static power consumption for system-on-chip (soc) designs. as technology scales for increased circuit density and performance, the need to reduce power consumption increases in significance as designers strive to utilize the advancing silicon capabilities. the consumer product market further drives the need to minimize chip power consumption.effective use of voltage islands for meeting soc power and performance requirements, while meeting time to market (tat) demands, requires novel approaches throughout the design flow as well as special circuit components and chip powering structures. this paper outlines methods being used today to design voltage islands in a rapid-tat product development environment, and discusses the need for industry eda advances to create an industry-wide voltage island design capability.
efficient exploration of the soc communication architecture design space. in this paper, we present a methodology and efficient algorithms for the design of high-performance system-on-chip communication architectures. our methodology automatically and optimally maps the various communications between system components onto a target communication architecture template that can consist of an arbitrary interconnection of shared or dedicated channels. in addition, our techniques simultaneously configure the communication protocols of each channel in the architecture in order to optimize system performance.we motivate the need for systematic exploration of the communication architecture design space, and highlight the issues involved through illustrative examples. we present a methodology and algorithms that address these issues, including the size and complexity of the design space. we present experimental results on example systems, including a cell forwarding unit of an atm switch, that demonstrate the benefits of using the proposed techniques. experimental results indicate that our techniques are successful in achieving significant improvements in system performance over conventional communication architectures (observed speedups over typical architectures such as single shared buses averaged 53%). moreover, we demonstrate that our design space exploration methodology and optimization algorithms are efficient (low cpu times), underlining their usefulness as part of any system design flow.
adapative error protection for energy efficiency. with dramatic scaling in feature sizes, noise resilience is becomingone of the most important design parameters, similar to performanceand energy efficiency. noise resilience is particularly problematicin long on-chip buses of complex single chip systems suchas on-chip multiprocessors. while one might opt to employ a verypowerful error protection scheme, this may not be very energy efficientas noise behavior typically varies over time. in this paper, wepropose an adaptive error protection scheme for energy efficiency,where the type of the coding scheme is modulated dynamically.the idea behind this strategy is to monitor the dynamic variationsin noise behavior and use the least powerful (and hence the mostenergy efficient) error protection scheme required to maintain theerror rates below a pre-set threshold. our detailed experimental resultsobtained through simulation show that this adaptive strategyachieves the same level of error protection as the most powerfulstrategy experimented, without experiencing the latter's energy inefficiency.based on our results, we recommend system designersto adopt adaptive protection schemes in environments where bothenergy and reliability are important.
fast performance analysis of bus-based system-on-chip communication architectures. this paper addresses the problem of efficient and accurate performance analysis to drive the exploration and design of bus-based system-on-chip (soc) communication architectures. our technique fills a gap in existing techniques for system-level performance analysis, which are either too slow to use in an iterative communication architecture design framework (e.g., simulation of the complete system), or are not accurate enough to drive the design of the communication architecture (e.g., techniques that perform a &ldquo;static&rdquo; analysis of the system performance). the proposed system-level performance analysis technique consists of (i) initial co-simulation performed after iiw/sw partitioning and mapping, with the communication between components modeled in an abstract manner (e.g., as events or data transfers), (ii) extraction of abstracted symbolic traces, represented as a bus and synchronization event (bse) graph, that captures the activity of the various system components and their communication over time, and (iii) manipulation of the bse graph using the bus parameters, to derive the behavior of the system accounting for effects of the bus architecture. we present experimental results on several example systems, including a tcp/ip network interface card sub-system. the results indicate that our performance estimation technique is over two orders of magnitude faster than performing a complete system simulation, while being very accurate (within 2.2% of performance estimates derived from accurate hw/sw co-simulation).
efficient model reduction of interconnect via approximate system gramians. krylov-subspace based methods for generating low-order models of complicated interconnect are extremely effective, but there is no optimality theory for the resulting models. alternatively, methods based on truncating a balanced realization (tbr), in which the observability and controllability gramians have been diagonalized, do have an optimality property but are too computationally expensive to use on complicated problems. in this paper we present a method for computing reduced-order models of interconnect by projection via the orthogonalized union of the approximate dominant eigenspaces of the system's controllability and observability gramians. the approximate dominant eigenspaces are obtained efficiently using an iterative lyapunov equation solver, vector adi, which requires only linear matrix-vector solves. a spiral inductor and a transmission line example are used to demonstrate that the new method accurately approximates the tbr results and gives much more accurate wideband models than krylov subspace-based moment matching methods.
interval-valued reduced order statistical interconnect modeling. we show how recent advances in the handling of correlated interval representations of range uncertainty can be used to predict the impact of statistical manufacturing variations on linear interconnect. we represent correlated statistical variations in rlc parameters as sets of correlated intervals, and show how classical model order reduction methods - awe and prima - can be re-targeted to compute interval-valued, rather than scalar-valued reductions. by applying a statistical interpretation and sampling to the resulting compact interval-valued model, we can efficiently estimate the impact of variations on the original circuit. results show the technique can predict mean delay with errors between 5-10%, for correlated rlc parameter variations up to 35%.
performance-centering optimization for system-level analog design exploration. in this paper we propose a novel analog design optimization methodology to address two key aspects of top-down system-level design: (1) how to optimally compare and select analog system architectures in the early phases of design; and (2) how to hierarchically propagate performance specifications from system level to circuit level to enable independent circuit block design. importantly, due to the inaccuracy of early-stage system-level models, and the increasing magnitude of process and environmental variations, the system-level exploration must leave sufficient design margin to ensure a successful late-stage implementation. therefore, instead of minimizing a design objective function, and thereby converging on a constraint boundary, we apply a novel performance centering optimization. our proposed methodology centers the analog design in the performance space, and maximizes the distance to all constraint boundaries. we demonstrate that this early-stage design margin, which is measured by the volume of the inscribed ellipsoid lying inside the performance constraints, provides an excellent quality measure for comparing different system architectures. the efficacy of our performance centering approach is shown for analog design examples, including a complete clock data recovery system design and implementation.
routability-driven placement and white space allocation. we present a congestion-driven placement flow. first, we consider in the global placement stage the routing demand to replace cells in order to avoid congested regions. then we allocate appropriate amounts of white space into different regions of the chip according to the congestion map. finally, a detailed placer is applied to legalize placements while preserving the distributions of white space. experimental results show that our placement flow can achieve the best routability with the shortest routed wirelength among all publicly available placement tools. moreover, our white space allocation approach can significantly improve the routabilities of placements generated by other placement tools.
power-optimal simultaneous buffer insertion/sizing and wire sizing. this paper studies the problems of minimizing power dissipationof an interconnect wire by simultaneously considering buffer insertion/sizing and wire sizing (bisws). we consider two cases, namely minimizing power dissipation with optimal delay constraints, and minimizing power dissipation with a given delay penalty.we derive closed form optimal solutions for both cases. theseclosed form solutions can be used to efficiently estimate the powerdissipation in the early stages of the vlsi designs. we observe thatthe power dissipation can be much different even with the sameoptimal delay.
automated oscillator macromodelling techniques for capturing amplitude variations and injection locking. we present a method for extracting comprehensive amplitude and phase macromodels of oscillators from their circuit descriptions. the macromodels are based on combining a scalar, nonlinear phase equation with a small linear time-varying system to capture slowly-dying amplitude variations. the comprehensive macromodels are able to correctly predict oscillator response in the presence of interference at far lower computational cost than that of full spice-level simulation. we also present an efficient numerical method for capturing injection locking in oscillators, thereby improving on the classic technique of adler (1946) in terms of accuracy and applicability to any kind of oscillator. we demonstrate the proposed techniques on lc and ring oscillators, comparing results from the macromodels against full spice-like simulation. numerical experiments demonstrate speed tips of orders of magnitude, while retaining excellent accuracy.
vdd programmability to reduce fpga interconnect power. power is an increasingly important design constraint for fpgas in nanometer technologies. because interconnect power is dominant in fpgas, we design vdd-programmable interconnect fabric to reduce fpga interconnect power. there are three vdd states for interconnect switches: high vdd, low vdd and power-gating. we develop a simple design flow to apply high vdd to critical paths and low vdd to non-critical paths and to power gate unused interconnect switches. we carry out a highly quantitative study by placing and routing benchmark circuits in 100 nm technology to illustrate the power saving. compared to single-vdd fpgas with optimized but nonprogrammable vdd level for the same target clock frequency, our new fpga fabric on average reduces interconnect power by 56.51% and total fpga power by 50.55%. due to the highly low utilization rate of routing switches, majority of the power reduction is achieved by power gating unused routing buffers. in contrast, recent work that considers vdd programmability only for logic fabric reduces total fpga power merely by 14.29%. to the best of our knowledge, it is the first in-depth study on vdd programmability for fpga interconnect power reduction.
whirlpool plas: a regular logic structure and their synthesis. a regular circuit structure called a whirlpool pla (wpla) is proposed. it is suitable for the implementation of finite state machines as well as combinational logic. a wpla is logically a four-level boolean nor network. by arranging the four logic arrays in a cycle, a compact layout is achieved. doppio-espresso, a four-level logic minimization algorithm is developed for wpla synthesis. no technology mapping, placement or routing is necessary for the wpla. area and delay trade-off is absent, because these two goals are usually compatible in wpla synthesis.
wavesched: a novel scheduling technique for control-flow intensive behavioral descriptions. in this paper, we present a novel scheduling algorithm targeted towards minimizing the average execution time of control-flow intensive behavioral descriptions. our algorithm uses a cdfg model, which preserves the parallelism inherent in the application. it explores previously unexplored regions of the solution space by its ability to overlap the schedules of independent iterative constructs, whose bodies share resources. it also incorporates well known optimization techniques like loop unrolling in a natural fashion. this is made possible by a general loop-handling technique, which we have devised. application of the algorithm to several common benchmarks demonstrates up to 4.8-fold improvement in expected schedule length over existing scheduling algorithms, without paying a price in terms of the best- and worst-case schedule lengths required to execute the behavioral description (in fact, frequently, the best/worst-case schedule lengths are also better for our algorithm).
parameterized interconnect order reduction with explicit-and-implicit multi-parameter moment matching for inter/intra-die variations. in this paper we propose a novel parameterized interconnect order reduction algorithm, core, to efficiently capture both inter-die and intra-die variations. core applies a two-step explicit-and-implicit scheme for multiparameter moment matching. as such, core can match significantly more moments than other traditional techniques using the same model size. in addition, a recursive arnoldi algorithm is proposed to quickly construct the krylov subspace that is required for parameterized order reduction. applying the recursive arnoldi algorithm significantly reduces the computation cost for model generation. several rc and rlc interconnect examples demonstrate that core can provide up to 10/spl times/ better modeling accuracy than other traditional techniques, while achieving smaller model complexity (i.e. size). it follows that these interconnect models generated by core can provide more accurate simulation result with cheaper simulation cost, when they are utilized for gate-interconnect co-simulation.
selecting partial scan flip-flops for circuit partitioning. this paper presents a new method of selecting scan flip-flops (ffs) in partial scan designs of sequential circuits. scan ffs are chosen so that the whole circuit can be partitioned into many small subcircuits which can be dealt with separately by a test pattern generator. this permits easy automatic test pattern generation for arbitrarily large sequential circuits. algorithms of selecting scan ffs to allow such partitioning and of scheduling tests for subcircuits are given. experimental results show that the proposed method makes it possible to generate test patterns for extra large sequential circuits which previous approaches cannot deal with.
behavioral modeling of analog circuits by wavelet collocation method. in this paper, we develop a wavelet collocation method with nonlinear companding for behavioral modeling of analog circuits. to construct the behavioral models, the circuit is first partitioned into building blocks and the input-output function of each block is then approximated by wavelets. as the blocks are mathematically represented by sets of simple wavelet basis functions, the computation cost for the behavioral simulation is significantly reduced. the proposed method presents several merits compared with those conventional techniques. first, the algorithm for expanding input-output functions by wavelets is a general-purpose approach, which can be applied in automatically modeling of different analog circuit blocks with different structures. second, both the small signal effect and the large signal effect are modeled in a unified formulation, which eases the process of modeling and simulation. third, a nonlinear companding method is developed to control the modeling error distribution. to demonstrate the promising features of the proposed method, a 4th order switched-current filter is employed to build the behavioral model.
valid clocking in wavepipelined circuits. an analysis of valid clock rates in wavepipelined circuits using a technique called timed boolean functions is presented. it is shown that the valid intervals for the clock period can be disconnected. thus, it is insufficient to known only the minimum valid clock period in guaranteeing proper operation of pipelined circuits. analytic expressions for the valid clock intervals in terms of both topological delay and two-vector longest and shortest delays are provided. also uncertainties arising from manufacturing are taken into account. some potential difficulties in computing the exact valid clock intervals are illustrated by demonstrating discontinuity and nonmonotonicity of the harmonic number h(&tau;) (the number of valid simultaneous data waves allowed) as a function of the clock period &tau;
leakage power modeling and reduction with data retention. in this paper, we study leakage power reduction using power gating in the forms of the virtual power/ground rails clamp (vrc) and multi-threshold cmos (mtcmos) techniques. we apply power gating to two circuit types: memory-based units and datapath components. using a microarchitecture-level power simulator, as well as power and timing models derived from detailed circuit designs, we further study leakage power modeling and reduction at the system level for modern high-performance vliw processors. we show that the leakage power can be over 40% of the total power for such processors. moreover, we propose time-out scheduling of vrc to reduce power up to 85.65% for l2 cache. this power savings results in close to 1/3 total power dissipation for the vliw processors we study.
statistical based link insertion for robust clock network design. we present a statistical based non-tree clock distribution construction algorithm that starts with a tree and incrementally insert cross links, such that the skew variation of the final clock network is within a certain confidence interval under variations in wire width. monte carlo simulations show that the robustness of the final clock network can be significantly improved with a small increase in wire length.
capturing time-of-flight delay for transient analysis based on scattering parameter macromodel. the delay associated with transmission line networks consists of the exponentially charging time and a pure propagation delay. this propagation delay, so called time-of-flight delay, is particularly evident in long lines. when the time-of-flight is comparable to the input rise-time, it is difficult to capture the time-of-flight with a finite sum of exponentials. therefore the time-of-flight must be captured explicitly from the transfer function of the circuit. in this paper, we give a precise definition of the time-of-flight together with some basic properties, and present an efficient method to capture the time-of-flight for general interconnect networks. based on our scattering parameter macromodel, we can easily capture the time-of-flight during the network reduction while using lower order model to evaluate the charging delay. by capturing the time-of-flight delay, the accuracy of system responses can be greatly improved without significantly increasing computing time.
on the interaction between power-aware fpga cad algorithms. as field-programmable gate array (fpga) power consumptioncontinues to increase, lower power fpga circuitry, architectures,and computer-aided design (cad) tools need to be developed.before designing low-power fpga circuitry, architectures, orcad tools, we must first determine where the biggest savings (interms of energy dissipation) are to be made and whether thesesavings are cumulative. in this paper, we focus on fpga cadtools. specifically, we describe a new power-aware cad flow forfpgas that was developed to answer the above questions.estimating energy using very detailed post-route power and delaymodels, we determine the energy savings obtained by our power-awaretechnology mapping, clustering, placement, and routingalgorithms and investigate how the savings behave when thealgorithms are applied concurrently. the individual savings of thepower-aware technology-mapping, clustering, placement, androuting algorithms were 7.6%, 12.6%, 3.0%, and 2.6%respectively. the majority of the overall savings were achievedduring the technology mapping and clustering stages of the power-awarefpga cad flow. in addition, the savings were mostlycumulative when the individual power-aware cad algorithmswere applied concurrently with an overall energy reduction of 22.6%.
partitioning and reduction of rc interconnect networks based on scattering parameter macromodels. this paper presents a linear time algorithm to reduce a large rc interconnect network into subnetworks which are approximated with lower order equivalent rc circuits. the number of rc elements can be reduced between 50% and 90%. instead of increasing approximation order for a network with large number of ports which will result in inefficiency at best and ill-conditioned matrices at worst, we partition the original network into several subnetworks, each of which is approximated by lower order model. the reduced circuits are guaranteed to be stable. the experiment results show that the number of circuit elements in a reduced network is o(n) for typical clock networks, where n is the number of external ports. the simulation time can be reduced by two to three orders of magnitude while the response of the reduced circuits is within five percent of that of the original circuits.
the design and optimization of soc test solutions. we propose an integrated technique for extensive optimization of the final test solution for system-on-chip using simulated annealing. the produced results from the technique are a minimized test schedule fulfilling test conflicts under test power constraints and an optimized design of the test access mechanism. we have implemented the proposed algorithm and performed experiments with several benchmarks and industrial designs to show the usefulness and efficiency of our technique.
actif: a high-level power estimation tool for analog continuous-time-filters. a tool is presented that gives a high-level estimation of the power consumed by an analog continuous-time ota-c filter when given only high-level input parameters such as dynamic range and signal swing. when used in combination with estimators for other building blocks (adc's, dac's, mixers,...) a truly high-level analog system exploration becomes feasible such as needed for architectural exploration of telecom systems. in literature only fundamental relations exist for analog filters, that predict the power with an error of orders of magnitude, which makes them hard to use in real system design. actif combines existing filter synthesis methods with new behavioral models for transconductance stages in a novel way to obtain an optimized high-level yet accurate power estimation. to verify the presented approach, two recently published design examples are compared with the results from actif.
instruction selection using binate covering for code size optimization. we address the problem of instruction selection in code generation for embedded dsp microprocessors. such processors have highly irregular data-paths, and conventional code generation methods typically result in inefficient code. instruction selection can be formulated as directed acyclic graph (dag) covering. conventional methods for instruction selection use heuristics that break up the dag into a forest of trees and then cover them independently. this breakup can result in suboptimal solutions for the original dag. alternatively, the dag covering problem can be formulated as a binate covering problem, and solved exactly or heuristically using branch-and-bound methods. we show that optimal instruction selection on a dag in the case of accumulator-based architectures requires a partial scheduling of nodes in the dag, and we augment the binate covering formulation to minimize spills and reloads. we show how the irregular data transfer costs of typical dsp data-paths can be modeled in the binate covering formulation.
full-chip interconnect power estimation and simulation considering concurrent repeater and flip-flop insertion. in this paper, we study the full-chip interconnect power modeling.we show that repeater insertion is no longer sufficient toachieve the target frequencies specified by itrs, and develop concurrentrepeater and ff insertion schemes. considering structuralinterconnects, layer assignment and concurrent repeater andff insertion for delay specification, we develop a cycle-accuratemicroarchitecture-level interconnect power simulation. the simulationreduces the over-estimation by up to 2:46x compared topower estimation based on purely stochastic interconnects and fixedswitching factor. furthermore, we show that interconnect pipelininghas a lower ipc but can improve throughput by up to 2.03x.this indicates that the traditional design flow optimizing ipc andclock frequency separately may no longer be valid.
backend cad flows for "restrictive design rules". to meet challenges of deep-subwavelength technologies (particularly 130 nm and following), lithography has come to rely increasingly on data processes such as shape fill, optical proximity correction, and rets like altpsm. for emerging technologies (65 nm and following) the computation cost and complexity of these techniques are themselves becoming bottlenecks in the design-silicon flow. this has motivated the recent calls for restrictive design rules such as fixed width/pitch/orientation of gate-forming polysilicon features. we have been exploring how design might take advantage of these restrictions, and present some preliminary ideas for how we might reduce the computational cost throughout the back end of the design flow through the post-tapeout data processes while improving quality of results: the reliability of opc/ret algorithms and the accuracy of models of manufactured products. we also believe that the underlying technology, including simulation and analysis, may be applicable to a variety of approaches to design for manufacturability (dfm).
cad computation for manufacturability: can we save vlsi technology from itself? every 18 to 24 months, the areal density of vlsi doubles and the predicted date for the end of cmos scaling is pushed out approximately 18 to 24 months. this rate of growth has been controlled mainly by the increasing capabilities of lithographic patterning. however, the rate of improvement of lithography systems in key physical parameters such as illumination wavelength has begun to slow. to make up the shortfall, lithography has increasingly turned to using cad tools to transform the geometric shapes in designs into shapes on photomasks which have been compensated for systematic pattern-distorting effects. as the requirements for this compensation grow, however, it becomes increasingly difficult to hide in post-tapeout data preparation, and must be considered in back-end design tools and methodologies. we describe a number of the challenges to lithographic patterning, highlighting the factors that limit "physical scaling" and introduce the layout-to-mask shape transformations that compensate for these limitations. we describe the implementation of these transformations in general-purpose and specialized cad tools, pointing out challenges like growth of computation effort. finally, we describe how limitations of post-tapeout compensation drive the need for "litho-aware" physical design tools, showing examples in cell design, place-and-route, and layout migration.
register assignment through resource classification for asip microcode generation. application specific instruction-set processors (asips) offer designers the ability for high-speed data and control processing with the added flexibility needed for late design specifications, accommodation of design errors, and product evolution. however, code generation for asips is a complex problem and new techniques are needed for its success. the register assignment task can be a critical phase, since often in asips, the number and functionality of available registers is limited, as the designer has opted for simplicity, speed, and low area. intelligent use of register files is critical to the program execution time, program memory usage and data memory usage. this paper describes a methodology utilizing register classes as a basis for assignment for a particular style of asip architectures. the approach gives preference to special purpose registers which are the scarce resources. this naturally leads to the objectives of high speed and low program memory usage. the approach has been implemented in a system called codesyn and used on custom asip architectures.
circuit simulation of nanotechnology devices with non-monotonic i-v characteristics. as research begins to explore potential nanotechnologiesfor future post-cmos integrated systems, modeling andsimulation environments must be developed that canaccommodate the corresponding problem complexity and non-traditionaldevice characteristics. this paper describes a circuit-levelsimulator that can accommodate an important class ofnanotechnology devices that are characterized by non-monotonici-v characteristics. employing adaptively controlledexplicit integration method (aces) and piecewise linear (pwl)device models, the proposed approach effectively overcomesthe convergence problems and multiple equilibrium pointsolution problems caused by the negative differentialresistance (ndr) regions in such device i-v functions.importantly, the aces approach can address the circuit sizeproblem when partitioning is included, and providecompatibility with simple i-v device model tables, therebyavoiding the need for analytical device models that rarely areavailable for nanotechnology devices.
system level design with spade: an m-jpeg case study. in this paper we present and evaluate the spade (system level performance analysis and design space exploration) methodology through an illustrative case study. spade is a method and tool for architecture exploration of heterogeneous signal processing systems. in this case study we start from an m-jpeg application and use spade to evaluate alternative multi-processor architectures for implementing this application. spade follows the y-chart paradigm for system level design; application and architecture are modeled separately and mapped onto each other in an explicit design step. spade permits architectures to be modeled at an abstract level using a library of generic building blocks, thereby reducing the cost of model construction and simulation. the case study shows that spade supports efficient exploration of candidate architectures; models can be easily constructed, modified and simulated in order to quickly evaluate alternative system implementations.
optimal wire sizing and buffer insertion for low power and a generalized delay model. we present efficient, optimal algorithms for timing optimization by discrete wire sizing and buffer insertion. our algorithms are able to minimize dynamic power dissipation subject to given timing constraints. in addition, we compute the complete power-delay tradeoff curve for added flexibility. we extend our algorithm to take into account the effect of signal slew on buffer delay which can contribute substantially to overall delay. the effectiveness of these methods is demonstrated experimentally.
power grid transient simulation in linear time based on transmission-line-modeling alternating-direction-implicit method. the soaring clocking frequency and integration density demand robust and stable power delivery to support tens of millions of transistors switching. to ensure the design quality of power delivery, extensive transient power grid simulations need to be performed during design process. however, the traditional circuit simulation engines are not scaled as well as the complexity of power delivery, as a result, it often takes a long runtime and huge memory requirement to simulate a medium size power grid circuit. in this paper, we develop and present a new efficient transient simulation algorithm for power distribution. the proposed algorithm, tlm-adi (transmission-line-modeling alternating-direction-implicit), first models the power delivery structure as transmission line mesh structure, then solves the transient mna matrices by the alternating-direction-implicit method. the proposed algorithm, with linear runtime and memory requirement, is also unconditionally stable which ensures that the time-step is not limited by any stability requirement. extensive experimental results show that the proposed algorithm is not only orders of magnitude faster than spice but also extremely memory saving and accurate.
flip-flop insertion with shifted-phase clocks for fpga power reduction. although the lut (look-up table) size of fpgas has been optimized for general applications, complicated designs may contain a large number of cascaded luts between flip-flops. this results in unwanted glitch propagation along the luts, and wastes power. this paper proposes a flip-flop insertion, we propose insertion of new flip-flops between adjacent existing flip-flops to minimize glitch propagation and power loss. each new flip-flop is timed by a phase-shifted clock with the phase calculated from the delays of luts and routing paths. this is different from traditional retiming methods that use the original clock or an 180-degree clock for the new flip-flops, and thus alters the original pipeline structure and synchronization. we start from a post-layout design, retiming its clock frequency and timing behavior. multiple flip-flop insertion is an np-complete problem because each new flip-flop affects the delays in the design. we have devised a glitch generation and propagation model for lut-based fpgas that take account of path delays while supporting reasonable complexity. we propose effective heuristics for flip-flop insertion and clock phase selection. full-chip measurements, including all the overheads associated with the inserted flip-flops, show that our approach shows up to 38% of the total dynamic power. we have analyzed our scheme, showing the mechanics of clock assignment and glitch minimization, and the sources of power reduction.
efficient instruction encoding for automatic instruction set design of configurable asips. application-specific instructions can significantly improve the performance, energy, and code size of configurable processors. a common approach used in the design of such instructions is to convert application-specific operation patterns into new complex instructions. however, processors with a fixed instruction bitwidth cannot accommodate all the potentially interesting operation patterns, due to the limited code space afforded by the fixed instruction bitwidth. we present a novel instruction set synthesis technique that employs an efficient instruction encoding method to achieve maximal performance improvement. we build a library of complex instructions with various encoding alternatives and select the best set of complex instructions while satisfying the instruction bitwidth constraint. we formulate the problem using integer linear programming and also present an effective heuristic algorithm. experimental results using our technique generate instruction sets that show improvements of up to 38% over the native instruction set for several realistic benchmark applications running on a typical embedded risc processor.
challenges in power-ground integrity. with the advance of semiconductor manufacturing, eda, and vlsi design technologies, circuits with increasingly higher speed are being integrated at an increasingly higher density. this trend causes correspondingly larger voltage fluctuations in the on-chip power distribution network due to ir-drop, l di/dt noise, or lc resonance. therefore, power-ground integrity becomes a serious challenge in designing future high-performance circuits. in this paper, we will introduce power-ground integrity, addressing its importance, verification methodology, and problem solution.
an efficient statistical analysis methodology and its application to high-density drams. in this work, a new approach for the statistical worst case of full-chip circuit performance and parametric yield prediction, using both the modified-principal component analysis (mpca) and the gradient method (gm), is proposed and verified. this method enables designers not only to predict the standard deviations of circuit performances but also track the circuit performances associated with the process shift by measuring e-tests. this new method is validated experimentally during the development and production of high density drams. our contributions to statistical circuit design are as follows: 1) a method for directly generating a parametrized model associated with electrical test data 2) the first application to high density drams using the true statistical method
a novel framework for multilevel routing considering routability and performance. we propose in this paper a novel framework for multilevel routing considering both routability and performance. the two-stage multilevel framework consists of coarsening followed by uncoarsening. unlike the previous multilevel routing, we integrate global routing, detailed routing, and resource estimation together at each level of the framework, leading to more accurate routing resource estimation during coarsening and thus facilitating the solution refinement during uncoarsening. further, the exact routing information obtained at each level makes our framework more flexible in dealing with various routing objectives (such as crosstalk, power, etc). experimental results show that our approach obtains significantly better routing solutions than previous works. for example, for a set of 11 commonly used benchmark circuits, our approach achieves 100% routing completion for all circuits while the previous multilevel routing, the three-level routing, and the hierarchical routing can complete routing for only 3, 0, 3 circuits, respectively. in particular, the number of routing layers used by our router is even smaller. we also have performed experiments on timing-driven routing. the results are also very promising.
a min-cost flow based detailed router for fpgas. routing for fpgas has been a very challenging problem dueto the limitation of routing resources. although the fpgarouting problem has been researched extensively, most algorithms route one net at a time, and it can cause the net-ordering problem.in this paper, we present a detailed routing algorithm forfpgas based on min-cost flow computations. using themin-cost flow approach, our algorithm routes all the netsconnected to a common logic module simultaneously. ateach stage of the network flow computation, we guaranteeoptimal result in terms of routability and delay cost. for further improvement, we adopt an iterative re nement scheme based on the lagrangian relaxation technique. the lagrangian relaxation approach transforms the routing problem into a sequence of lagrangian subproblems. at each iteration of the algorithm, lagrangian subproblems are solvedby our min-cost flow based routing algorithm. any violationof congestion constraints is reflected in the value of corresponding lagrangian multiplier. the lagrangian multipliers are incorporated into the cost of each routing rosource nodeand guide the router.because our min-cost flow based algorithm minimizes costfunction while it maximizes the flow, our algorithm findscongestion-free routing solutions with minimum total delay.comparison with vpr router shows that our router usesless or equal number of routing tracks with smaller criticalpath delay as well as total routing delay.
synthesis of hazard-free multi-level logic under multiple-input changes from binary decision diagrams. we describe a new method for directly synthesizing a hazard-free multilevel logic implementation from a given logic specification. the method is based on free/ordered binary decision diagrams (bdd's), and is naturally applicable to multiple-output logic functions. given an incompletely-specified (multiple-output) boolean function, the method produces a multilevel logic network that is hazard-free for a specified set of multiple-input changes. we assume an arbitrary (unbounded) gate and wire delay model under a pure delay (pd) assumption, we permit multiple-input changes, and we consider both static and dynamic hazards. this problem is generally regarded as a difficult problem and it has important applications in the field of asynchronous design. the method has been automated and applied to a number of examples. the results we have obtained are very promising.
dynamical identification of critical paths for iterative gate sizing. since only sensitizable paths contribute to the delay of a circuit, false paths must be excluded in optimizing the delay of the circuit. just identifying false paths in the first place is not sufficient since during iterative optimization process, false paths may become sensitizable, and sensitizable paths false. in this paper, we examine cases for false path becoming sensitizable and sensitizable becoming false. based on these conditions, we adopt a so-called loose sensitization criterion which is used to develop an algorithm for dynamically identification of sensitizable paths. by combining gate sizing and dynamically identification of sensitizable paths, an efficient performance optimization tool is developed. results on a set of circuits from iscas benchmark set demonstrate that our tool is indeed very effective in reducing circuit delay with less number of gate sized as compared with other methods.
cost-free scan: a low-overhead scan path design methodology. conventional scan design imposes considerable area and delay overhead by using larger scan flip-flops and additional scan wires without utilizing the functionality of the combinational logic. we propose a novel low-overhead scan design methodology, called cost-free scan, which exploits the controllability of primary inputs to establish scan paths through the combinational logic. the methodology aims at reducing scan overhead by (1) analyzing the circuit to determine all the cost-free scan flip-flops, and (2) selecting the best primary input vector to establish the maximum number of cost-free scan flip-flops on the scan chain. significant reduction in the scan overhead is achieved on iscas89 benchmarks, where in full scan environment, as many as 89% of the total flip-flops are found cost-free scannable, while in partial scan environment, reduction can be as high as 97% in scan flip-flops needed to break sequential loops.
silent: serialized low energy transmission coding for on-chip interconnection networks. on-chip source-synchronous serial communication has many advantages over multi-bit parallel communication in the aspects of skew, crosstalk area cost, wiring difficulty, and clock synchronization. however, the serial wire tends to dissipate more energy than parallel bus due to the bit multiplexing. we propose a coding method to reduce the transmission energy of the serial communication by minimizing the number of transitions on the serial wire. we demonstrate the significant energy saving in a multimedia application, 3d graphics. we also apply the coding technique to a cmos soc implementation which integrates various processing units with packet switched on-chip networks.
a cell-based power estimation in cmos combinational circuits. in this paper we present a power dissipation model considering the charging/discharging of capacitance at the gate output node as well as internal nodes, and capacitance feedthrough effect. based on the model, a cell-based power estimation (cbpe) method is developed to estimate the power dissipation in cmos combinational circuits. in our technique, we first construct a modified state transition graph called stgpe to model the power consumption behavior of a logic gate. then, according to the input signal probabilities and transition densities of the logic gate, we perform an efficient method to estimate the expected activity number of each edge in the stgpe. finally, the energy consumption of a logic gate is calculated by summing the energy consumptions of each edge in stgpe. for a set of benchmark circuits, experimental results show that the power dissipation estimated by cbpe is on average within 10-percent errors as compared to the exact spice simulation while the cpu time is more than two order-of-magnitudes faster.
aesthetic routing for transistor schematics. a heuristic routing approach for generating transistor schematic diagrams is presented. the method consists of two steps: global routing and channel routing. the global routing step partitions and routes the interconnections, into three levels of abstraction with domain knowledge. it forms desirable intra-block routing styles and local connection patterns, and achieves a reduction of net bends and lengths. channel routing minimizes net crossovers by applying decycling and ordering techniques achieving nonoverlapping routing with a small number of net crossovers
universal logic gate for fpga design. in this paper the problem of selecting an appropriate programmable cell structure for fpga architecture design is addressed. the cells studied here can be configured to the desired functionality by applying input permutation, negation, bridging or constant assignment, or output negation. a general methodology to determine logic description of such cells, which are capable of being configured to a given set of functions is described.experimental results suggest that the new cell behaves as well as the actel 2 cell in terms of logic power but requires substantially less area and wiring overhead.
on the signal bounding problem in timing analysis. in this paper, we study the propagation of slew dependent bounding signals and the corresponding slew problem in static timing analysis. the selection of slew from the latest arriving signal, a commonly used strategy, may violate the rule of monotonic delay. several methods for generating bounding signals to overcome this difficulty are described. the accuracy and monotonicity of each method is analyzed. these methods can be easily implemented in a static timer to improve the accuracy.
throughput-driven ic communication fabric synthesis. as the scale of system integration continues to grow, the on-chip communication becomes the ultimate bottleneck of system performance and the primary determinant of system architecture. in this paper we propose a throughput-driven synthesis methodology for on-chip communication fabrics based on optimized bus models. compared with traditional delay-driven, wire-by-wire planning methods, the throughput-driven methodology provides a feasible and accurate system-level solution to address delay and congestion problems simultaneously during earlyphase design planning. unlike the conventional methods which are based on rather inaccurate rc models and simplistic delay metrics, in our methodology the communication fabrics are characterized in terms of realistic partial element equivalent circuits (peec) extracted from the multi-layer interconnects and transistor level transient analysis via spice-like tools. the characterized models facilitate a flexible interconnect fabric optimization engine that can be embedded into a system planner for throughput-driven synthesis. furthermore, engineering trade-offs considering repeater area and interconnect power consumption are further considered as part of this methodology.
techniques for improving the efficiency of sequential circuit test generation. new techniques are presented in this paper to improve the efficiency of a test generation procedure for synchronous sequential circuits. these techniques aid the test generation procedure by reducing the search space, carrying out non-chronological backtracking, and reusing the test generation effort. they have been integrated into an existing sequential test generation system mix to constitute a new system, named mix-plus. the experimental results for the iscas-89 and addendum-93 benchmark circuits demonstrate the effectiveness of these techniques in improving the fault coverage and test generation efficiency.
tearing based automatic abstraction for ctl model checking. in this paper we present the tearing paradigm as a way to automatically abstract behavior to obtain upper and lower bound approximations of a reactive system. we present algorithms that exploit the bounds to perform conservative ectl and actl model checking. we also give an algorithm for false negative (or false positive) resolution for verification based on a theory of a lattice of approximations. we show that there exists a bipartition of the lattice set based on positive versus negative verification results. our resolution methods are based on determining a pseudo-optimal shortest path from a given, possibly coarse but tractable approximation, to a nearest point on the contour separating one set of the bipartition from the other.
a power modeling and characterization method for the cmos standard cell library. in this paper, we propose power consumption models for complex gates and transmission gates, which are extended from the model of basic gates proposed in [1]. we also describe an accurate power characterization method for cmos standard cell libraries which accounts for the effects of input slew rate, output loading, and logic state dependencies. the characterization methodology separates the power consumption of a cell into three components, e.g., capacitive feedthrough power, short-circuit power, and dynamic power. for each component, power equation is derived from spice simulation results where the netlist is extracted from cell's layout. experimental results on a set of iscas'85 benchmark circuits show that the power estimation based on our power modeling and characterization provides within 7% error of spice simulation on average while the cpu time consumed is more than two orders of magnitude less.
a power modeling and characterization method for macrocells using structure information. to characterize a macrocell, a general method is to store the power consumption of all possible transition events at primary inputs in the lookup tables. though this approach is very accurate, the lookup tables could be huge for the macrocells with many inputs. in this paper, we present a new power modeling method which takes advantage of the structure information of macrocells and selects minimum number of primary inputs or internal nodes in a macrocell as state variables to build a state transition graph (stg). those state variables can completely model the transitions of all internal nodes and the primary outputs. by carefully deleting some state variables, we further introduce an incomplete power modeling technique which can simplify the stg without losing much accuracy. in addition, we exploit the property of the compatible patterns of a macrocell to further reduce the number of edges in the corresponding stg. experimental results show that our modeling techniques can provide spice-like accuracy and can reduce the size of the lookup table significantly comparing to the general approach.
the reproducing placement problem with applications. we study a new placement problem: the reproducing placement problem (rpp). in each phase a module (or gate) is decomposed into two (or more) simpler modules. the goal is to find a &ldquo;good&rdquo; placement in each phase. the problem, being iterative in nature, requires an iterative algorithm. the problem finds applications in several gate-level placement problems, e.g., in layout-driven logic synthesis.we introduce the notion of minimum floating steiner trees (mfst). we employ an mfst algorithm as a central step in solving the rpp. a hanan-like theorem is established for the mfst problem and two approximation algorithms are proposed. experiments on commonly employed benchmarks verify the effectiveness of the proposed technique.
an algorithm to reduce test application time in full scan designs. an algorithm for generating a test with fewer test clocks for full scan designs by using combinational and sequential test generation algorithms adaptively is presented. heuristics combining tests measures and scan strategies are introduced. the algorithm, `test application time reduction for full scan designs' (tarf), is implemented and tested on a set of iscas sequential benchmark circuits. the results show that tarf achieves the same test coverage as combinational test generators but with fewer test clocks
comparing models of computation. we give a denotational framework (a meta model) within which certain properties of models of computation can be understood and compared. it describes concurrent processes as sets of possible behaviors. compositions of processes are given as intersections of their behaviors. the interaction between processes is through signals, which are collections of events. each event is a value-tag pair, where the tags can come from a partially ordered or totally ordered set. timed models are where the set of tags is totally ordered. synchronous events share the same tag, and synchronous signals contain events with the same set of tags. synchronous systems contain synchronous signals. strict causality (in timed systems) and continuity (in untimed systems) ensure determinacy under certain technical conditions. the framework is used to compare certain essential features of various models of computation, including kahn process networks, dataflow, sequential processes, concurrent sequential processes with rendezvous, petri nets, and discrete-event systems.
synthesis of concurrent system interface modules with automatic protocol conversion generation. we describe a new high-level compiler called integral for designing system interface modules. the input is a high-level concurrent algorithmic specification that can model complex concurrent control flow, logical and arithmetic computations, abstract communication, and low-level behavior. for abstract communication between two communicating modules that obey different i/o protocols, the necessary protocol conversion behaviors are automatically synthesized using a petri net theoretic approach. we present a synthesis trajectory that can synthesize the necessary hardware resources, control circuitry, and protocol conversion behaviors for implementing system interface modules.
process-variation-tolerant clock skew minimization. in this paper, we propose a novel hierarchical multiple-merge zero skew clock routing algorithm. the routing results produced by our approach will have zero skew in the nominal case and minimal skew increase in the presence of worst process variations. in order to construct such a clock routing, we formulate the linear placement with maximum spread problem and provide an o(nmin{n,p}lognlogp) algorithm for optimally solving this problem, where n is the number of cells to be placed and p is the maximum spread. experimental results show that our algorithm can indeed reduce the skew in various manufacturing variations effectively.
clustering for processing rate optimization. clustering (or partitioning) is a crucial step between logic synthesis and physical design in the layout of a large scale design. a design verified at the logic synthesis level may have timing closure problems at post-layout stages due to the emergence of multiple-clock-period interconnects. consequently, a trade-off between clock frequency and throughput may be needed to meet the design requirements. in this paper, we find that the processing rate, defined as the product of frequency and throughput, of a sequential system is upper bounded by the reciprocal of its maximum cycle ratio, which is only dependent on the clustering. we formulate the problem of processing rate optimization as seeking an optimal clustering with the minimal maximum-cycle-ratio in a general graph, and present an iterative algorithm to solve it. since our algorithm avoids binary search and is essentially incremental, it has the potential of being combined with other optimization techniques. experimental results validate the efficiency of our algorithm.
a timing analysis algorithm for circuits with level-sensitive latches. for a logic design with level-sensitive latches, we need to validate timing signal paths which may flush through several latches. we developed efficient algorithms based on the modified shortest and longest path method. the computational complexity of our algorithm is generally better than that of known algorithms in the literature. the implementation (cyclopss) has been applied to an industrial chip to verify the clock schedules.
retiming for wire pipelining in system-on-chip. at the integration scale of system-on-chips (socs), the conflicts between communication and computation will become prominent even on a chip. a big fraction of system time willshift from computation to communication. in synchronoussystems, a large amount of communication time is spent onmultiple-clock period wires. in this paper, we explore retimingto pipeline long interconnect wires in soc designs. behaviorally,it means that both computation and communicationare rescheduled for parallelism. the retiming is applied to anetlist of macro-blocks, where the internal structures may notbe changed and ip- ops may not be able to be inserted onsome wire segments. this problem is different from that on agate level netlist and is formulated as a wire retiming problem.theoretical treatment and a polynomial time algorithmare presented in the paper. experimental results showed thebenefits and effectiveness of our approach.
an effective methodology for functional pipelining. the problem of scheduling a loop in a pipelined fashion such that the iteration time (turnaround time) is minimized, given a loop behavior, a target initiation interval, and resource constraints, is considered. the iteration time is an important quality measure of a data path design because of its direct correlation with both the storage and the control costs. the scheduler starts with performing as-soon-as-possible-pipelined (asapp) scheduling without regard to the resource constraint. it then resolves the resource constraint violations, if there are any, by repeatedly rescheduling some operations
optimal wire retiming without binary search. the problem of retiming over a netlist of macro-blocks to achieve the minimal clock period, where the block internal structures may not be changed and flip-flops may not be inserted on some wire segments, is called the optimal wire retiming problem. to the best of our knowledge, there is no polynomial-time approach to solve it and the existence of such an approach is still an open question. we present a brand new algorithm that solves the optimal wire retiming problem with polynomial-time worst case complexity. since the new algorithm avoids binary search and is essentially incremental, it has the potential of being combined with other optimization techniques. experimental results show that the new algorithm is very efficient in practice.
behavioral synthesis for easy testability in data path scheduling. a data path scheduling algorithm to improve testability without assuming any particular test strategy is presented. a scheduling heuristic for easy testability, based on previous work on data path allocation for testability, is introduced. a mobility path scheduling algorithm to implement this heuristic while also minimizing area is developed. experimental results on benchmark and example circuits show high fault coverage, short test generation time, and little or no area overhead
trade-off between latch and flop for min-period sequential circuit designs with crosstalk. latches are extensively used in high-performance sequential circuit designs to achieve high frequencies because of their good performance and time borrowing feature. however, the amount of timing uncertainty due to crosstalk accumulated through latches could be larger than the benefit gained by time borrowing. in this paper, we show that the trade-off between a latch and a flop can be leveraged in a sequential circuit design with crosstalk, so that the clock period is minimized by selecting a configuration of mixed latches and flops. a circular time representation is proposed to make coupling detection easier and more efficient. experiments on our heuristic algorithm for finding an optimal configuration of mixed latches and flops showed promising results.
a path-based methodology for post-silicon timing validation. this work presents a novel path-based methodology for post-silicon timing validation. in timing validation, the objective is to decide if the timing behavior observed from the silicon is consistent with that predicted by the timing model. at the core of our path-based methodology, we propose a framework to obtain the post-silicon path ranking from observing silicon timing behavior. then, the consistency is determined by comparing the post-silicon path ranking and the pre-silicon path ranking calculated based on the timing model. our post-silicon ranking methodology consists of two approaches: ranking optimization and path filtering. we discuss the applications of both approaches and their impacts on the path ranking results. for experiments, we utilize a statistical timing simulator that was developed in the past to derive chip samples and we demonstrate the feasibility of our methodology using benchmark circuits.
simulation of digital circuits in the presence of uncertainty. current extended value set dynamic timing analyzers are not sophisticated enough to detect the subtle timing relationships upon which timing-critical systems depend, and exhaustive simulation achieves very accurate results but at tremendous computational cost. mtv is a simulator that strikes a balance between accuracy and efficiency.mtv is more accurate than other extended value set simulators because it respects the ordering of events. it is more efficient than exhaustive simulators because it efficiently simulates overlapping events and requires only a single waveform to represent a signal. features of mtv include: elimination of common ambiguity, symbolic delays, correlated delays, and sophisticated algorithms to detect ordered events. this paper concludes with simulation results from the iscas85 benchmark suite.
design of robust test criteria in analog testing. test design of analog circuits based on statistical methods for decision making is a topic of growing interest. the major problem of such statistical approaches with respect to industrial applicability concerns the confidence with which the determined test criteria can be applied in production testing. this mainly refers to the consideration of measurement noise, to the selected measurements, as well as to the required training and validation samples. these crucial topics are addressed in this paper. on exploiting experience from the statistical design of analog circuits and from pattern recognition methods, efficient solutions to these problems are provided. a very robust test design is achieved by systematically considering measurement noise, by selecting most significant measurements, and by using most meaningful samples. moreover, parametric as well as catastrophic faults are covered on application of digital testing methods.
logic decomposition during technology mapping. a problem in technology mapping is that quality of the final implementation depends significantly on the initially provided circuit structure. to resolve this problem, conventional techniques iteratively but separately apply technology independent transformations and technology mapping.in this paper, we propose a procedure which performs logic decomposition and technology mapping simultaneously. we show that the procedure effectively explores all possible algebraic decompositions. it finds an optimal tree implementation over all the circuit structures examined, while the run time is typically logarithmic in the number of decompositions.
design based analog testing by characteristic observation inference. in this paper, a new approach to analog test design based on the circuit design process, called characteristic observation inference (coi), is presented. in many situations, it is prohibitive to directly verify the circuit specifications due to the test equipment costs. our approach considers a given universal set of reasonable input stimuli and measurements that can be performed with the given test equipment. from this universal set, a minimal number of measurements is automatically selected that represent a set of observations characterizing the state of the circuit under test with respect to parametric faults. a parametric fault model is introduced which is related to the individual circuit specifications. for each given circuit specification, a corresponding test inference criterion is computed, based on logistic discrimination analysis. by applying these criteria, the satisfaction or violation of the given circuit specifications can be inferred from the observations of the circuit under test. the coi method applied to a complex operational amplifier yields very encouraging simulated results with respect to parametric faults as well as to catastrophic faults.
basic concepts for an hdl reverse engineering tool-set. designer's productivity has become the key-factor of the development of electronic systems. an increasing application of design data reuse is widely recognized as a promising technique to master future design complexities. since the intellectual property of a design is more and more kept in software-like hardware description languages (hdl), successful reuse depends on the availability of suitable hdl reverse engineering tools. this paper introduces new concepts for an integrated hdl reverse engineering tool-set and presents an implemented evaluation prototype for vhdl designs. starting from an arbitrary collection of hdl source code files, several graphical and textual views on the design description are automatically generated. the tool-set provides novel hypertext techniques, expressive graphical code representations, a user-defined level of abstraction, and interactive configuration mechanisms in order to facilitate the analysis, adoption and upgrade of existing hdl designs.
path selection and pattern generation for dynamic timing analysis considering power supply noise effects. noise effects such as power supply and crosstalk can significantly affect the performance of deep submicron designs. these delay effects are highly input pattern dependent. existing path selection and timing analysis techniques cannot capture the effects of noise on cell/interconnect delays. therefore, the selected critical paths may not be the longest paths and predicted circuit performance might not reflect the worst-case circuit delay. in this paper, we propose a path selection technique that can consider power supply noise effects on the propagation delays. next, for the selected critical paths, we propose a pattern generation technique for dynamic timing analysis such that the patterns produce the worst-case power supply noise effects on the delays of these paths. our experimental results demonstrate the difference in estimated circuit performance for the case when power supply noise effects are considered vs. when these effects are ignored. thus, they validate the need for considering power supply noise effects on delays during path selection and dynamic timing analysis.
clock tree synthesis for multi-chip modules. while designing interconnect for mcm's, one must take into consideration the distributed rlc effects, due to which signals may display nonmonotonic behavior and substantial ringing. this paper considers the problem of designing clock trees for mcm's. a fully distributed rlc model is utilized for awe-based analysis and synthesis, and appropriate measures are taken to ensure adequate signal damping and for buffer insertion to satisfy constraints on the clock signal slew rate. experimental results, verified by spice simulations, show that this method can be used to build clock trees with near-zero skews.
on theoretical and practical considerations of path selection for delay fault testing. in current industrial practice, critical path selection is an indispensable step for ac delay test and timing validation. traditionally, this step relies on the construction of a set of worse-case paths based upon discrete timing models. the assumption of discrete timing models can be invalidated by delay effects in the deep sub-micron domain, where timing defects and process variation are statistical in nature. in this paper, we study the problem of optimizing critical path selection, under both fixed delay and statistical delay assumptions. with a novel problem formulation and new theoretical results, we prove that the problem in both cases are computationally intractable. we then discuss practical heuristics and their theoretical performance bounds, and demonstrate that among all heuristics under consideration, only one is theoretically feasible. finally, we provide consistent experimental results based upon defect-injected simulation using an efficient statistical timing analysis framework.
analog circuit sizing based on formal methods using affine arithmetic. we present a novel approach to optimization-based variation-tolerant analog circuit sizing. using formal methods based on affine arithmetic, we calculate guaranteed bounds on the worst-case behavior and deterministically find the global optimum of the sizing problem by means of branch-and-bound optimization. to solve the nonlinear circuit equations with parameter variations, we define a novel affine-arithmetic newton operator that gives a significant improvement in computational efficiency over an implementation using interval arithmetic. the calculation of guaranteed worst-case bounds and the global optimization are demonstrated by a prototype implementation.
cad challenges in multimedia computing. abstract: this tutorial surveys the present and future of multimedia computing systems and outlines new challenges for cad presented by these systems. multimedia computing is a challenging domain for several reasons: it requires both high computation rates and memory bandwidth; it is a multirate computing problem; and requires low-cost implementations for high-volume markets. as a result, the design of multimedia computing systems introduces new challenges for cad at all levels of abstraction, ranging from layout to system design. after surveying the nature of the multimedia computing problem, we examine two experiences in multimedia computer design from a cad perspective: the design of vlsi systems-on-chips for multimedia: and the successive refinement of an application from software to a high-volume chip using advanced cad synthesis tools.
spider: simultaneous post-layout ir-drop and metal density enhancement with redundant fill. this paper presents spider, a novel methodology that advantageously utilizes metal fill to simultaneously fulfil metal density requirements and reduce ir-drop of the power distribution network. this is achieved through the addition of partially redundant connections between metal fills and power meshes. our technique is especially significant for 90nm process technology or below because (1) metal fill must now be done as part of the ic implementation flow due to its increasing impact on timing, (2) the tolerance for ir drop is tightening due to voltage scaling, and the increasingly conservative power mesh design to address ir-drop is adding significant burden on the available routing resources, (3) ir-drop is getting worse due to increasing design sizes, and (4) the large degree of design uncertainty demands irdrop repair capabilities that can be applied after routing is completed. spider addresses all these issues practically with little or no cost. experimental results further demonstrated the robustness and effectiveness of our approach: spider achieves an average ir-drop reduction of 62.2% in 16 designs of various sizes.
an efficient method for improving the quality of per-test fault diagnosis. per-test fault diagnosis methodology has been shown to be an effective one for the identification of complex defects. we improve a recent per-test technique by applying additional diagnosis on the outputs of the circuit. the new method brings in more evidence to support the true failures, hence improves the diagnostic quality. we show that this method can very well address several problems in previous work.
what is the limit of energy saving by dynamic voltage scaling? dynamic voltage scaling (dvs) is a technique that varies the supply voltage and clock frequency based on the computation load to provide desired performance with the minimal amount of energy consumption. it has been demonstrated as one of the most effective low power system design techniques, in particular for real time systems. previously, there are works on both ends of the dvs systems: the ideal variable voltage system which can change its voltage with no physical constraints, and the multiple voltage system which has a number of discrete voltages available simultaneously. in this paper, we study the dvs systems between these two extreme cases. we consider systems that can vary the operating voltage dynamically under various real-life physical constraints. based on the system's different behavior during voltage transition, we define the feasible dvs system and the practical dvs system. we build mathematical model to analyze the potential of dvs on energy saving for these different systems. finally, we simulate the behavior of a secure wireless communication networks with dvs systems. the results show that dvs results in energy reduction from 36% to 79%, and the real life dvs systems can be very close to the ideal system in energy saving.
algorithms for address assignment in dsp code generation. this paper presents dsp code optimization techniques, which originate from dedicated memory address generation hardware. we define a generic model of dsp address generation units. based on this model, we present efficient heuristics for computing memory layouts for program variables, which optimize utilization of parallel address generation units. improvements and generalizations of previous work are described, and the efficacy of the proposed algorithms is demonstrated through experimental evaluation.
energy optimization of distributed embedded processors by combined data compression and functional partitioning. transmitting compressed data can reduce inter-processor communicationtraffic and create new opportunities for dvs (dynamicvoltage scaling) in distributed embedded systems. however, datacompression alone may not be effective unless coordinated withfunctional partitioning. this paper presents a dynamic programmingtechnique that combines compression and functional partitioningto minimize energy on multiple voltage-scalable processorsrunning pipelined data-regular applications under performance constraints.our algorithm computes the optimal functional partitioning,cpu speed for each node, and their respective compression ratios.we validate the algorithm's effectiveness on a real distributedembedded system running an image processing algorithm.
function inlining under code size constraints for embedded processors. function inlining is a compiler optimization that generally increases performance at the expense of larger code size. however, current inlining techniques do not meet the special demands in the design of embedded systems, since they are based on simple heuristics, and they generate code of unpredictable size. this paper presents a novel approach to function inlining in c compilers for embedded processors, which aims a maximum program speedup under a global limit on code size. the core of this approach is a branch-and-bound algorithm which allows to quickly explore the large search space. in an application study we show how this algorithm can be applied to maximize the execution speed of an application under a given code size constraint.
optimizing mode transition sequences in idle intervals for component-level and system-level energy minimization. new embedded systems offer rich power management features in the form of multiple operational and nonoperational power modes. while they offer mechanisms for better energy efficiency, they also complicate power management decisions in the presence of realtime constraints. a traditional dynamic power management techniques based on localized break-even-time analysis with simple on/off power controls often yield suboptimal if not incorrect results globally. to address these problems, this work presents two core algorithms for reducing idle energy consumption at the component level and system level. the first algorithm discovers the optimal sequence for mode transition over multiple power modes under timing constraints. it assists the second algorithm that performs a sophisticated global search strategy to aggressively explore system-wide energy savings by correctly interpreting the constraints across all subsystems. experimental results show that in an embedded radio system where idle energy cost matches or exceeds the active energy consumption, our technique can further reduce the idle energy by 50-70%, which translates into 30-50% of overall system energy compared to existing techniques.
verifying correct pipeline implementation for microprocessors. we introduce a general, automatic verification technique for pipelined designs. the technique is based on a scalable, formal methodology for analyzing pipelines. the key advantages to our technique are: it specifically targets pipeline control, making it more efficient; it requires no explicit specification, since it compares hardware against itself; it can be used within the broader framework of hierarchical verification; and, it can be easily extended to handle certain "complex" pipelined structures.
a behavioral signal path modeling methodology for qualitative insight in and efficient sizing of cmos opamps. this paper describes a new modeling methodology that allows to derive systematically behavioral signal path models of operational amplifiers. combined with symbolic simulation, these models provide high qualitative insight in the small-signal functioning of a circuit. the behavioral signal path model provides compact interpretable expressions for the poles and zeros that constitute the signal path. these expressions show which design parameters have dominant influence on the position of a pole/zero and thus enable a designer to control a manual interactive sizing process. the methodology consists of the application of a sequence of abstractions, so that one gradually progresses from a full device to a full behavior circuit representation. during this translation, qualitative insight and design requirements are obtained. the methodology is implemented in an open tool called \eftoef. the behavioral signal path model is also used for optimization based sizing in order to achieve pole placement in an efficient way. for optimization based sizing, a new strategy for hierarchical penalty function composition is proposed, which allows sequential pruning of the design space. combined with an operating point driven \dc formulation and local minimax optimization, a fast sizing method is obtained which can be used for interactive design space exploration. experimental results of both modeling and sizing are shown.
efficient performance estimation for general real-time task systems. the paper presents a novel approach to compute tight upper bounds on the processor utilization independent of the implementation for general real-time systems where tasks are composed of subtasks and precedence constraints may exist among subtasks of the same task. we formulate the problem as a set of linear programming (lp) problems. observations are made to reduce the number of lp problem instances required to be solved, which greatly improves the computation time of the utilization bounds. furthermore, additional constraints are allowed to be included under certain circumstances to improve the quality of the bounds.
a delay metric for rc circuits based on the weibull distribution. physical design optimizations such as placement, interconnect synthesis, oorplanning, and routing require fast and accurate analysis of rc networks. because of its simple close form and fast evaluation, the elmore delay metric has been widely adopted. the recently proposed delay metrics primo and h-gamma match the rst three circuit moments to the probability density function of a gamma statistical distribution. although these methods demonstrate impressive accuracy compared to other delay metrics, their implementations tend to be challenging. as an alternative to matching to the gamma distribution, we propose to match the rst two circuit moments to a weibull distribution. the result is a new delay metric called weibull based delay (wed). the primary advantages of wed over primo and h-gamma are its efciency and ease of implementation. experiments show that wed is robust and has satisfactory accuracies at both near and far-end nodes.
compiler-directed voltage scaling on communication links for reducing power consumption. reducing power consumption of communication networks is an important optimization goal in many application domains, ranging from large-scale simulation codes to embedded multi-media applications. most of the prior efforts on network power optimization are hardware-based schemes. these schemes are predictive by definition as they control communication link status based on the observations made in the past. since prediction may not be very accurate most of the time, these approaches can result in overheads in terms of both performance and power. this paper proposes a compiler driven approach to communication link voltage management. in this approach, an optimizing compiler analyzes the application code and extracts the data communication pattern among parallel processors. this information along with network topology is used for identifying the link access patterns. these patterns and the inherent data dependence information of the underlying code help the compiler decide the optimum voltages/frequencies to be used for communication links at a given time frame. our focus in this work is on loop-intensive codes which frequently appear in data intensive video and image processing. we exploit the regularity in data accesses of these codes to abstract out their inter-processor communication patterns, which in turn enable us select the most appropriate voltage/frequency level to employ for each communication link at any time.
a gradient method on the initial partition of fiduccia-mattheyses algorithm. in this paper, a fiduccia-mattheyses (fm) algorithm incorporating a novel initial partition generating method is proposed. the proposed algorithm applies to both bipartitioning and multi-way partitioning problems with or without replication. the initial partition generating method is based on a gradient decent algorithm. on partitioning without replication, our algorithm achieves an average of 17% improvement over the analytical method, paraboli, on bipartitioning, 10% better than primal-dual method on 4-way partitioning and 51% better than net-based method. on partitioning allowing replication, our algorithm achieves an average of 23% improvement over the directed fiduccia-mattheyses algorithm on replication graph (fmrg) method on bipartitioning.
improving scratch-pad memory reliability through compiler-guided data block duplication. recent trends in embedded computing indicates an increasing use of scratch-pad memories (spms) as on-chip store for instructions and data. an important characteristic of these memory components is that they are managed by software, instead of hardware. ever-scaling process technology and employment of several power-saving techniques in embedded systems (e.g., voltage scaling) make these systems particularly vulnerable to soft errors and other transient errors. therefore, it is very important in practice to consider the impact of soft errors in spms. while it is possible to employ classical memory protection mechanisms such as parity checks and ecc, each of these has its drawbacks. specifically, a pure parity-based protection cannot correct any errors, and eccs can be an overkill in the normal operation state when no soft error is experienced. this paper proposes an alternate approach to protect spms against soft errors. the proposed approach is based on data block duplication under compiler control. more specifically, an optimizing compiler duplicates data blocks within the spm and protects each data block by parity if such a duplication does not hurt performance. the goal of this scheme is to provide only parity protection for data blocks (and reduce the overheads at runtime when no error occurs) but correct errors using the duplicate (when an error occurs in the primary copy), provided that the duplicate is not corrupted.
cama: a multi-valued satisfiability solver. this paper presents the multi-valued sat solver cama. camageneralizes the recently developed speed-up techniques usedin state-of-the-art binary sat solvers, such as the two-literal-watching scheme for boolean constraint propagation (bcp), conflict-based learning with identifying the first unique implication point (uip), and non-chronological back-tracking. in addition, a novel minimum value set (mvs) technique is introduced for improving the efficiency of conflict-based learning. by analyzing the conflict clauses, mvs can potentially prune conflictingspace that has not been searched before. two different decisionheuristics are discussed and evaluated. finally the performanceof cama is compared with chaff using on a one-hot-encodingscheme. the experimental results show that, for mv-sat problemswith large variable domains, cama outperforms chaff.
comprehensive frequency-dependent substrate noise analysis using boundary element methods. we present a comprehensive methodology for the electrodynamic modeling of substrate noise coupling. a new and efficient method is introduced for the calculation of the green's function that can accommodate arbitrary substrate doping profiles and thus facilitate substrate noise analysis using boundary element methods. in addition to a discussion of the application of the method and its validation in the context of substrate transfer resistance extraction, preliminary results from its application to frequency-dependent substrate noise modeling are presented also.
diagnosis of small-signal parameters for broadband amplifiers through s-parameter measurements and sensitivity-guided evolutionary search. with increasing uncertainties in the modeling and processing of semiconductor devices, it is essential that the sources of failures be identified once the devices are manufactured. we present a methodology to diagnose the problems in broadband amplifiers by determining the most important small signal parameters of the internal transistors. we use an evolutionary algorithm specifically designed to mimic the expected errors to ensure fast convergence to the correct solution. sensitivity analysis is used to determine the set of the most impactful small signal parameters and to guide the evolutionary search. experimental results indicate the proposed algorithm determines the parameters accurately and it scales well in terms of accuracy and computation time.
robust analog/rf circuit design with projection-based posynomial modeling. we propose a robust analog design tool (road) for post-tuning analog/rf circuits. starting from an initial design derived from hand analysis or analog circuit synthesis based on simplified models, road extracts accurate posynomial performance models via transistor-level simulation and optimizes the circuit by geometric programming. importantly, road sets up all design constraints to include large-scale process variations to facilitate the tradeoff between yield and performance. a novel convex formulation of the robust design problem is utilized to improve the optimization efficiency and to produce a solution that is superior to other local tuning methods. in addition, a novel projection-based approach for posynomial fitting is used to facilitate scaling to large problem sizes. a new implicit power iteration algorithm is proposed to find the optimal projection space and extract the posynomial coefficients with robust convergence. the efficacy of road is demonstrated on several circuit examples.
a markov chain sequence generator for power macromodeling. in this paper, we present a novel sequence generator based on a markov chain model. specifically, we formulate the problem of generating a sequence of vectors with given average input probability p, average transition density d, and spatial correlation s as a transition matrix computation problem, in which the matrix elements are subject to constraints derived from the specified statistics. we also give a practical heuristic that computes such a matrix and generates a sequence of l n-bit vectors in o(nl + n2) time. derived from a strongly mixing markov chain, our generator yields binary vector sequences with accurate statistics, high uniformity, and high randomness. experimental results show that our sequence generator can cover more than 99% of the parameter space. sequences of 2,000 48-bit vectors are generated in less than 0.05 seconds, with average deviations of the signal statistics p, d, and s equal to 1.6%, 1.8%, and 2.8%, respectively.our generator enables the detailed study of power macromodeling. using our tool and the iscas-85 benchmark circuits, we have assessed the sensitivity of power dissipation to the three input statistics p, d, and s. our investigation reveals that power is most sensitive to transition density, while only occasionally exhibiting high sensitivity to signal probability and spatial correlation. our experiments also show that input signal imbalance can cause estimation errors as high as 100% in extreme cases, although errors are usually within 25%.
synthesis methodology for built-in at-speed testing. we discuss a new synthesis flow, which offers the ability to do easy delay testing almost free in terms of its impact on speed and area compared to corresponding implementations with standard cells. the methodology uses matched delays in pre-charged plas and bundled routing to produce a completion signal, which is guaranteed to lie on all critical paths. we give a nondelay testing method for ensuring matched delays are correct, i.e. that all completion signals arrive after their corresponding data signals. the design margins of the matched delays can be small since they are internal to the plas, which are regular structures and therefore more predictable.
fast thermal simulation for architecture level dynamic thermal management. as power density increases exponentially, runtime regulation of operating temperature by dynamic thermal managements becomes necessary. this paper proposes a novel approach to the thermal analysis at chip architecture level for efficient dynamic thermal management. our new approach is based on the observation that the power consumption of architecture level modules in microprocessors running typical workloads presents strong nature of periodicity. such a feature can be exploited by fast spectrum analysis in frequency domain for computing steady state response. to obtain the transient temperature changes due to initial condition and constant power inputs, numerically stable moment matching approach is carried out. the total transient responses is the addition of the two simulation results. the resulting fast thermal analysis algorithm leads to at least 10/spl times/-100/spl times/ speedup over traditional integration-based transient analysis with small accuracy loss.
linear decomposition algorithm for vlsi design applications. we propose a unified solution to both linear placement and partitioning. our approach combines the well-known eigenvector optimization method with the recursive max-flow min-cut method. a linearized eigenvector method is proposed to improve the linear placement. a hypergraph maxflow algorithm is then adopted to efficiently find the max-flow min-cut. in our unified approach, the max-flow min-cut provides an optimal ordered partition subject to the given seeds and the eigenvector placement provides heuristic information for seed selection. experimental results on mcnc benchmarks show that our approach is superior to other methods for both linear placement and partitioning problems. on average, our approach yields an improvement of 45.1% over eigenvector approach in terms of total wire length, and yields an improvement of 26.9% over paraboli in terms of cut size.
defining statistical sensitivity for timing optimization of logic circuits with large-scale process and environmental variations. the large-scale process and environmental variations for today's nanoscale ics are requiring statistical approaches for timing analysis and optimization. significant research has been recently focused on developing new statistical timing analysis algorithms, but often without consideration for how one should interpret the statistical timing results for optimization. in this paper (li et al., 2005) we demonstrate why the traditional concepts of slack and critical path become ineffective under large-scale variations, and we propose a novel sensitivity-based metric to assess the "criticality" of each path and/or arc in the statistical timing graph. we define the statistical sensitivities for both paths and arcs, and theoretically prove that our path sensitivity is equivalent to the probability that a path is critical, and our arc sensitivity is equivalent to the probability that an arc sits on the critical path. an efficient algorithm with incremental analysis capability is described for fast sensitivity computation that has a linear runtime complexity in circuit size. the efficacy of the proposed sensitivity analysis is demonstrated on both standard benchmark circuits and large industry examples.
a framework for designing reusable analog circuits. recent analog design tools have started to allow designers to archivenot only the sized schematics but also some of the objectives thatthe circuit is trying to achieve. this paper first describes star(schematic tool for analog reuse), a system that captures designer'sknowledge as part of the archival circuit representation,and then describes how this system can be used to create portabledesign modules. creating portable analog modules require morethan just the optimization criteria for the cell. it must also includethe constraints on the cellýs environment (for proper operation), andhow these constraints should scale with technology. furthermore,the system must help the designer in the current task of creatingthe design, since it is rare that a designer thinks about creating ipfor someone else. we demonstrate the capability and utility of thissystem by examining the reuse of a phase-locked loop.
improving over-the-cell channel routing in standard cell design. the first stage of over-the-cell routing in the horizontally connected vertically connected (hcvc) model is formulated as followings: given two rows of terminals, find a planar routing to connect a subset of nets (with weights) on each row of terminals using a fixed number of tracks to maximize the total weight. this problem is called the two row fixed height planar routing (tfpr) problem [cpl93]. the complexity of the tfpr problem was unknown up to now. an approximation algorithm for the tfpr problem was presented in [cpl93]. in this paper we present a o(n2*h2) time algorithm to solve the tfpr problem optimally, where n is the number of terminals and h is the height of the standard cells. our algorithm can be used to improve the performance of several over-the-cell channel routers including the ones in [cpl93] and [hss93].
an efficient method for terminal reduction of interconnect circuits considering delay variations. this paper proposes a novel method to efficiently reduce the terminal number of general linear interconnect circuits with a large number of input and/or output terminals considering delay variations. our new algorithm is motivated by the fact that vlsi interconnect circuits have many similar terminals in terms of their timing and delay metrics due to their closeness in structure or due to mathematic approximation using meshing in finite difference or finite element scheme during the extraction process. by allowing some delay tolerance or variations, we can reduce many similar terminals and keep a small number of representative terminals. after terminal reduction, traditional model order reduction methods can achieve more compact models and improve simulation efficiency. the new method, termmerg, is based on the moments of the circuits as the metrics for the timing or delay. it then employs singular value decomposition (svd) method to determine the optimum number of clusters based on the low-rank approximation. after this, the k-means clustering algorithm is used to cluster the moments of the terminals into different clusters. experimental results on a number of real industry interconnect circuits demonstrate the effectiveness of the proposed method.
a graph theoretic optimal algorithm for schedule compression in time-multiplexed fpga partitioning. this paper presents an optimal algorithm to solve the schedule compression problem, which is an open problem proposed by trimberger [1] for time-multiplexed fpga partitioning. time-multiplexed fpgas have the potential to dramatically improve logic density by time-sharing logic. schedule compression is an important step in partitioning for time-multiplexed fpgas [1,4,9,10] and can greatly influence the quality of the partitioning solution. we exactly solve the schedule compression problem by converting it to a constrained min-max path problem. we further extend our algorithm to minimize the communication cost during schedule compression. experiments show that our optimal algorithm outperforms the existing heuristics and runs very efficiently.
fast 3-d inductance extraction in lossy multi-layer substrate. a mixed potential integral equation (mpie) technique combined with fast multi-layer green's functions and gaussian jacobi high order techniques is used to compute the 3-d frequency dependent inductances and resistances in lossy multi-layered substrate. compared to fasthenry, a multipole-accelerated 3-d inductance extraction program, the algorithm presented here is more accurate and faster for lossy multilayer structures due to two reasons. first, substrate and optional ground plane's lose and coupling effect are efficiently modeled by multilayer green's functions, while the green's functions are efficiently calculated via window-based acceleration technique. second, gaussian jacobi-based high order techniques are used to capture the singularity of the current distribution at metal edges, leading to significant reduction of problem size and speed-up of computation.
an algorithmic approach for generic parallel adders. binary addition is the most fundamental and frequentlyused operation. a well-designed adder should be fast andsatisfy the application requirements. we propose an algorithmicapproach to generate an irregular parallel-prefix adder, whichhas minimal delay for a given profile of input signals. it cancover different topologies such as ripple-carry, carry-skip andcarry-select adders. compared with kogge-stone and brent-kungadders, the results of the proposed approach have thesmallest output delay.
systematic design for power minimization of pipelined analog-to-digital converters. in this paper a general method to design a pipelined adc withminimum power consumption is presented. by expressing the totalpower consumption and the total input-referred noise of theconverter as functions of the capacitor values and the resolutions ofthe converter stages, an optimization algorithm is employed tocalculate the optimum values of these parameters, which lead tominimum power consumption while a specific noise requirement issatisfied. to determine the bias current values of operationalamplifiers an optimal choice for settling and slewing timeparameters is proposed. a practical design example is presented toshow the effectiveness of the proposed methodology.
concurrent logic restructuring and placement for timing closure. in this paper, an algorithm for simultaneous logic restructuring and placement is presented. this algorithm first constructs a set of super-cells along the critical paths and then generates the set of non-inferior re-mapping solutions for each supercell. the best mapping and placement solutions for all super-cells are obtained by solving a generalized geometric programming (ggp) problem. the process of identifying and optimizing the critical paths is iterated until timing closure is achieved. experimental results on a set of mcnc benchmarks demonstrate the effectiveness of our algorithm.
an exact solution to simultaneous technology mapping and linear placement problem. in this paper, we present an optimal algorithm for solving the simultaneous technology mapping and linear placement problem for tree-structured circuits with the objective of minimizing the post-layout area. the proposed algorithm relies on generation of gate-area versus cut-width curves using a dynamic programming approach. a novel design flow, which extends this algorithm to minimize the circuit delay and handle general dag structures, is also presented. experimental results on mcnc benchmarks are reported.
interconnect lifetime prediction under dynamic stress for reliability-aware design. thermal effects are becoming a limiting factor in high-performance circuit design due to the strong temperature-dependence of leakage power, circuit performance, ic package cost and reliability. while many interconnect reliability models assume a constant temperature, this paper presents a physics-based model for estimating interconnect lifetime for any time-varying temperature/current profile. this model is verified with numerical solutions. with this model, we show that designers may be more aggressive with the temperature profiles that are allowed on a chip. in fact, our model reveals that when the temperature magnitude variation is small, average temperature (instead of worst-case temperature) can be used to accurately predict interconnect lifetime, allowing for significant design margin reclamation in reliability-aware design. even when the variation of temperature magnitude is large, our model shows that using the maximum temperature is still too conservative for interconnect lifetime prediction. therefore, our model not only increases the accuracy of reliability estimates, but also enables designers to consider more aggressive designs. this model is similarly useful for temperature-aware dynamic runtime management.
abilbo: analog built-in block observer. this paper presents a novel multifunctional test structure called analog built-in block observer (abilbo). this structure is based on analog integrators and achieves analog scan, test frequency generation and test response compaction. a high fault coverage was obtained by using a discrete switched-capacitor abilbo for testing a biquad filter. the abilbo area overhead and performance penalty can be very low if functional and testing circuitry are shared. this is typically the case of high order filters based on a cascade of biquads.
accurate interconnect modeling: towards multi-million transistor chips as microwave circuits. in this tutorial we discuss concepts and techniques for the accurate and efficient modeling and extraction of interconnect parasitics in vlsi designs. due to increasing operating frequencies, microwave-like effects will become important. therefore stronger demands are put on extraction and verification tools. we indicate the state-of-the-art for capacitance, resistance and substrate resistance extraction and discuss some open problems. we also discuss several model reduction techniques as well as issues related to simulation and implementation in a cad system.
distributed simulation of vlsi systems via lookahead-free self-adaptive optimistic and conservative synchronization. this paper presents a new protocol for parallel and distributed simulation of vlsi systems. it is novel in two aspects: first, it combines optimistic and conservative synchronization methods, allowing processes to self-adapt for maximal utilization of concurrency. second, it does not require any application-dependent information like lookahead, which in many cases is unknown, zero, or difficult to automatically obtain from a design in a hardware description language. all these features make it very convenient and practical, extending the class of applications to at least all vhdl circuits, including delta cycle. the proposed protocol has been implemented and used for vhdl simulation. experimental results on several large vhdl circuits (between 1411 and 14704 processes) have shown promising linear speedups. we also observed that the dynamic synchronization, in which processes automatically adapt to optimistic or conservative behavior, follows closely or finds a very good configuration. this protocol may have a string impact for mixed-signal circuit simulation, where digital parts may be optimistic and heavy-state analog parts, conservative.
a super-scheduler for embedded reconfigurable systems. emerging reconfigurable systems attain high peformance with embedded optimized cores. for mapping designs on such special architectures, synthesis tools, that are aware of the special capabilities of the underlying architecture are necessary. in this paper we are proposing an algorithm to perform simultaneous scheduling and binding, targeting embedded reconfigurable systems. our algorithm differs from traditional scheduling methods in its capability of efficiently utilizing embedded blocks within the reconfigurable system. our algorithm can be used to implement several other scheduling techniques, such as asap, alap, and list scheduling. hence we refer to it as a super-scheduler. our algorithm is a path-based scheduling algorithm. at each step, an individual path from the input dfg is scheduled. our experiments with several dfg's extracted from mediabench suit indicate promising results. our scheduler presents capability to perform the trade-off between maximally utilizing the high-performance embedded blocks and exploiting parallelism in the schedule.
power-conscious joint scheduling of periodic task graphs and aperiodic tasks in distributed real-time embedded systems. in this paper, we present a power-conscious algorithm for jointly scheduling multi-rate periodic task graphs and aperiodic tasks in distributed real-time embedded systems. while the periodic task graphs have hard deadlines, the aperiodic tasks can have either hard or soft deadlines. periodic task graphs are first scheduled statically. slots are created in this static schedule to accommodate hard aperiodic tasks. soft aperiodic tasks are scheduled dynamically with an on-line scheduler. flexibility is introduced into the static schedule and optimized to allow the on-line scheduler to make dynamic modifications to the static schedule. this helps minimize the response times of soft aperiodic tasks through both resource reclaiming and slack stealing. of course, the validity of the static schedule is maintained. the on-line scheduler also employs dynamic voltage scaling and power management to obtain a power-efficient schedule. experimental results show that the flexibility introduced into the static schedule helps improve the response times of soft aperiodic tasks by up to 43%. dynamic voltage scaling and power management reduce power by up to 68%. the scheme in which the static schedule is allowed to be flexible achieves up to 32% more power saving compared to the scheme in which no flexibility is allowed, when both schemes are power-conscious. our work gives an average architecture price saving of 30% over a previous approach for embedded system architectures synthesized with execution slots for hard aperiodic tasks present.
netbench: a benchmarking suite for network processors. in this study we introduce netbench, a benchmarking suite for network processors. netbench contains a total of 9 applications that are representative of commercial applications for network processors. these applications are from all levels of packet processing; small, low-level code fragments as well as large application level programs are included in the suite.using simplescalar simulator we study the netbench programs in detail and characterize the network processor workloads. we also compare key characteristics such as instructions per cycle, instruction distribution, branch prediction accuracy, and cache behavior with the programs from mediabench. although the aimed architectures are similar for mediabench and netbench suites, we show that these workloads have significantly different characteristics. hence a separate benchmarking suite for network processors is a necessity. finally, we present performance measurements from intel ixp1200 network processor to show how netbench can be utilized.
computational geometry based placement migration. placement migration is a critical step to address a variety of post-placement design closure issues, such as timing, routing congestion, signal integrity, and heat distribution. to fix a design problem, one would like to perturb the design as little as possible while preserving the integrity of the original placement. this work presents a novel computational geometry based placement migration method, and a new stability metric to more accurately measure the "similarity" between two placements. it has two stages, a bin-based spreading at coarse scale and a delaunay triangulation based spreading at finer grain. it has clear advantage over conventional legalization algorithms such that the neighborhood characteristics of the original placement are preserved. thus, the placement migration is much more stable, which is important to maintain. applying this technique to placement legalization demonstrates significant improvements in wire length and stability compared to other popular legalization algorithms.
a partitioning algorithm for system-level synthesis. the partitioning/scheduling/allocation algorithm developed for the capsys method is presented. the aim of this project is to define a tool able to automatically design dedicated and embedded vliw architectures for large and complex applications. it inherits a sizable knowledge-pool from the wider field of parallel processors, vliw compiler design and high-level synthesis. emphasis is placed on constraints of such a system synthesis approach and more especially on the particularity of the partitioning step. the proposed solution implements a software/hardware approach based on the list-scheduling heuristic
a layout dependent full-chip copper electroplating topography model. in this paper, a layout dependent full-chip electroplating (ecp) topography model is developed based on the additive nature of the physics of the ep process. two layout attributes: layout density, and feature perimeter sum are used to compute the post-ecp topography. under a unified mechanism, two output variables representing the final topography: the array height and the step height are modeled simultaneously. using the proposed model long-range effects of the ecp process can be incorporated easily as well. the simulation results of our model were verified with test structure experimental data published in the literature and are presented in this paper. the results show that the errors are less than 5%. this model is not limited to the regular test structures; it can also be used for any practical design. the results of such partial application are shown here as well. our proposed ecp model can be used to model systematic variations caused by an ecp process or by a chemical mechanical planarization (cmp) process. the potential applications of this model include: layout design evaluation for catastrophic failure prevention; yield aware design (design for manufacturability), and variation- aware timing analysis.
a sequential quadratic programming approach to concurrent gate and wire sizing. with an ever-increasing portion of the delay in high- speed cmos chips attributable to the interconnect, interconnect-circuit design automation continues to grow in importance. by transforming the gate and multilayer wire sizing problem into a convex programming problem for the elmore delay approximation, we demonstrate the efficacy of a sequential quadratic programming (sqp) solution method. for cases where accuracy greater than that provided by the elmore delay approximation is required, we apply sqp to the gate and wire sizing problem with more accurate delay models. since efficient calculation of sensitivities is of paramount importance during sqp, we describe an approach for efficient computation of the accurate delay sensitivities.
coupling-aware high-level interconnect synthesis for low power. ultra deep submicron (udsm) technology and system-on-chip (soc) have resulted in a considerable portion of power dissipated on buses, in which the major sources of the power dissipation are (1) the transition activities on the signal lines and (2) the coupling capacitances of the lines. however, there has been no easy way of optimizing (1) and (2) simultaneously at an early stage of the synthesis process. in this paper, we propose a new (on-chip) bus synthesis algorithm to minimize the total sum of (1) and (2) in the microarchitecture synthesis. specifically, unlike the previous approaches in which (1) and (2) are minimized sequentially without any interaction between them, or only one of them is minimized, we, given a scheduled dataflow graph to be synthesized, minimize (1) and (2) simultaneously by formulating and solving the two important issues in an integrated fashion: binding data transfers to buses and determining a (physical) order of signal lines in each bus, both of which are the most critical factors that affect the results of (1) and (2). experimental results on a number of benchmark problems show that the proposed integrated low-power bus synthesis algorithm reduces power consumption by 24.8%, 40.3% and 18.1% on average over those in [12] (for minimizing (1) only), [1] (for (2) only) and [12, 1] (for (1) and then (2)), respectively.
an integrated data path optimization for low power based on network flow method. we propose an effective algorithm for power optimization in behavioral synthesis. in previous work, it has been shown that several hardware allocation/binding problems for power optimization can be formulated as network flow problems and be solved optimally. however, in these formulations, a fixed schedule was assumed. in such context, one key problem is: given an optimal network flow solution to a hardware allocation/binding problem for a schedule, how to generate a new optimal network flow solution rapidly for a local change of the schedule. to this end, from a comprehensive analysis of the relation between network structure and flow computation, we devise a two-step procedure: (step 1) max-flow computation step which finds a valid (maximum) flow solution while retaining the previous (maximum flow of minimum cost) solution as much as possible; (step 2) min-cost computation step which incrementally refines the flow solution obtained in step 1, using the concept of finding a negative cost cycle in the residual graph for the flow. the proposed algorithm can be applied effectively to several important high-level data path optimization problems (e.g., allocations/bindings of functional units, registers, buses, and memory ports) when we have the freedom to choose a schedule that will minimize power consumption. experimental results (for bus synthesis) on benchmark problems show that our designs are 5.2% more power-efficient over the best known results, which is due to (a) exploitation of the effect of scheduling and (b) optimal binding for every schedule instance. furthermore, our algorithm is about 2.8 times faster in run time over the full network flow based (optimal) bus synthesis algorithm, which is due to (c) our novel (two-step) mechanism which utilize the previous flow solution to reduce redundant flow computations.
interval-valued statistical modeling of oxide chemical-mechanical polishing. technology-oriented tools provide the raw data needed to optimize the fabrication process itself, and to predict problematic variational impacts on silicon design. unfortunately, even in these physics-oriented tools, statistically uncertain quantities appear as crucial inputs. to date, monte carlo techniques have been the dominant solution method. we suggest an alternative in which uncertainties are represented as correlated intervals, and interval-valued computations replace the standard scalar operations in the numerical algorithm for the tool. we use an oxide chemical-mechanical polishing tool as an example, and show how to "retrofit" workable statistical models on top of the original algorithm. accuracies to within /spl sim/1-10% of monte carlo simulation, and speedups of /spl sim/10-100x can be achieved, depending on whether we choose a formulation which emphasizes accuracy, or efficiency.
a methodology for improved circuit simulation efficiency via topology-based variable accuracy device modeling. a general and efficient preprocessing algorithm which can increase circuit simulation efficiency is discussed. the algorithm identifies significant devices based upon circuit topology. device model complexity and error tolerances are varied based upon device significance which results in a reduction in the required model evaluation time
verification of systems containing counters. it is pointed out that systems containing counters have very large and deep state spaces, and the verification of properties on these systems can be very expensive in terms of memory space and computation time. a technique for automatically reducing the state space associated with the system on which some properties that can express both safeness and fairness constraints have to be proved is presented. in particular, a set of conditions upon which some counters can be reduced to three-state, nondeterministic machines is given. the controllers can be simplified by removing the redundancy induced by their interaction with the counter, so that the verification tasks can be more easily performed
a statistical optimization-based approach for automated sizing of analog cells. this paper presents a cad tool for automated sizing of analog cells using statistical optimization in a simulation based approach. a nonlinear penalty-like approach is proposed to define a cost function from the performance specifications. also, a group of heuristics is proposed to increase the probability of reaching the global minimum as well as to reduce cpu time during the optimization process. the proposed tool sizes complex analog cells starting from scratch, within reasonable cpu times (approximately 1 hour for a fully differential opamp with 51 transistors), requiring no designer interaction, and using accurate transistor models to support the design choices. tool operation and feasibility is demonstrated via experimental measurements from a working cmos prototype of a folded-cascode amplifier.
power minimization using system-level partitioning of applications with quality of service requirements. design systems to provide various quality of service (qos) guarantees has received a lot of attentions due to the increasing popularity of real-time multimedia and wireless communication applications. meanwhile, low power consumption is always one of the goals for system design, especially for battery-operated systems. with the design trend of integrating multiple processor cores and memory on a single chip, we address the problem of how to partition a set of applications among processors, such that all the individual qos requirements are met and the total energy consumption is minimized. we exploit the advantages provided by the variable voltage design methodology to choose the voltage for each application on the same processor optimally for this purpose. we also discuss how to partition applications among the processors to achieve the same goal. we formulate the problem on an abstract qos model and present how to allocate resources (e.g., cpu time) and determine the voltage profile for every single processor. experiments on media benchmarks have also been studied.
a cad framework for co-design and analysis of cmos-set hybrid integrated circuits. this paper introduces a cad framework for co-simulation ofhybrid circuits containing cmos and set (single electrontransistor) devices. an improved analytical model for set is alsoformulated and shown to be applicable in both digital and analogdomains. particularly, the extension of the recent mib model forsingle/multi gate symmetric/asymmetric device for a wide range ofdrain to source voltage and temperature is addressed. circuit levelco-simulations are successfully performed by implementing theset analytical model in analog hardware description language(ahdl) of a professional circuit simulator smartspice.validation at device and circuit level is carried out by monte-carlosimulations. some novel functionality hybrid cmos-setcircuit characteristics: (i) set neuron (ii) multiple valued logiccircuit and (iii) a new negative differential resistance (ndr)circuit, are also predicted by the proposed set model andanalyzed using the new hybrid simulator.
on the optimization power of redundancy addition and removal techniques for sequential circuits. this paper attempts to determine the capabilities of existing redundancy addition and removal (srar) techniques for logic optimization of sequential circuits. to this purpose, we compare this method with the retiming and resynthesis (rar) techniques. for the rar case the set of possible transformations has been established by relating them to stg transformations by other authors. following these works, we first formally demonstrate that logic transformations provided by rar are covered by srar as well. then we also show that srar is able to identify transformations that cannot be found by rar. this way we prove the higher potential of the sequential redundancy addition and removal over the retiming and resynthesis techniques.
minimum area retiming with equivalent initial states. traditional minimum area retiming algorithms attempt to achieve their prescribed objective with no regard to maintaining the initial state of the system. this issue is important for circuits such as controllers, and our work addresses this problem. the procedure described generates bounds on the retiming variables that guarantee an equivalent initial state after retiming. a number of possible sets of bounds can be derived, and each set is used to solve a minimum area retiming problem that is set up as a 0/1 mixed integer linear program, using a new technique that models the maximal sharing of flip-flops at latch outputs. the best solution is found through enumeration of these sets, terminated on achievement of a calculated lower bound. experimental results show that after a small number of enumerations, optimal or near-optimal results are achievable.
synthesis of multiplier-less fir filters with minimum number of additions. abstract: in this paper we present optimizing transformations to minimize the number of additions+subtractions in both the direct form (/spl sigma/ a/sub i/x/sub n-i/ based) and its transposed form (multiple constant multiplication based) implementation of fir filters. these transformations are based on the iterative elimination of 2-bit common subexpressions in the coefficients binary representations. we give detailed description of the algorithms and present results for eight low pass fir filters with the number of coefficients ranging from 16 to 128. the results show upto 35% reduction in the number of additions+subtractions to implement /spl sigma/ a/sub i/x/sub n-i/ based fir filter structures and upto 38% reduction to implement mcm based structures.
an optimal algorithm for area minimization of slicing floorplans. the traditional algorithm of stockmeyer for area minimization of slicing floorplans has time (and space) complexity o(n^2) in the worst case, or o(n\log n) for balanced slicing. for more than a decade, it is considered the best possible. in this paper, we present a new algorithm of worst-case time (and space) complexity o(n\log n), where n is the total number of realizations for the basic blocks, regardless whether the slicing is balanced or not. we also prove \omega(n\log n) is the lower bound on the time complexity of any area minimization algorithm. therefore, the new algorithm not only finds the optimal realization, but also has an optimal running time.
a logic simulation engine based on a modified data flow architecture. an optimum application-specific data flow architecture for accelerating the standard event driven logic simulation is developed. a conservative distributed simulation algorithm which minimizes the use of null messages is also developed, along with a pseudodynamic data flow architecture to implement this distributed algorithm efficiently. a comparison of the standard event driven algorithm-based data flow accelerator to the distributed simulation algorithm-based accelerator is made on several benchmark circuits. the distributed simulation algorithm on the specialized data flow accelerator outperforms the standard event driven algorithm based data flow accelerator by a factor of three in most cases
board-level multi-terminal net routing for fpga-based logic emulation. we consider a board-level routing problem applicable to fpga-based logic emulation systems such as the realizer system [3] and the enterprise emulation system [5] manufactured by quickturn systems. optimal algorithms have been proposed for the case where all nets are two-terminal nets [10,11]. in this paper, we show how multi-terminal nets can be handled by decomposition into two-terminal nets. we show that the multi-terminal net decomposition problem can be modelled as a bounded-degree hypergraph-to-graph transformation problem where hyperedges are transformed to spanning trees. a network flow-based algorithm that solves both problems is proposed. it determines if there is a feasible decomposition and gives one whenever such a decomposition exists.
minimum replication min-cut partitioning. logic replication has been shown to be very effective in reducing the number of cut nets in partitioned circuits. liu et al. considered the circuit partitioning problem with logic replication for separating two given nodes and presented an algorithm to determine a partitioning of the minimum possible cut size. in general, there are many possible partitioning solutions with the minimum cut size and the difference of their required amounts of replication can be significant. since there is a size constraint on each component of the partitioning in practice, it is desirable to also minimize the amount of replication. in this paper, we present a network-flow based algorithm to determine an optimum replication min-cut partitioning that requires minimum replication. and we show that the algorithm can be generalized to separate two given subsets of nodes and determine an optimum partitioning of the minimum possible cut size using the least possible amount of replication. we also show that our algorithm can be used to improve the solutions produced by any heuristic replication min-cut partitioning algorithm by reducing the cut size and shrinking the replication set.
generation of bdds from hardware algorithm descriptions. we propose a new method for generating bdds from hardware algorithm descriptions written in a programming language. our system can deal with control structures, such as conditional branches (if-then-else) and data dependent loops (while-end). once bdds are generated, we can immediately check the equivalence of two different algorithm descriptions just by comparing bdds. this method can also be applied to verification between algorithm-level and gate-level designs. another interesting application is to synthesize loop-free logic circuits from algorithm descriptions. we show the experimental results for some practical examples, such as greatest common divisor (gcd) calculation. although our method has a limitation in size of problems, it is very practical and useful for actual design verification.
built-in self-test and fault diagnosis of fully differential analogue circuits. an approach to the test and diagnosis of fully differential analogue circuits is described in this paper. the test approach is based on off-line monitoring via an analogue bist observer the inputs of the operational amplifiers in the circuit. the analogue bist can detect both hard and soft faults. diagnosis resolution is improved by also monitoring the outputs of the operational amplifiers. faulty components can then be located and the actual defective value of a faulty passive component determined.
design for manufacturability in submicron domain. key characteristics of newly emerging ic technologies render the traditional concept of die size minimization and traditional "design rules" insufficient to handle the design-manufacturing interface. this tutorial surveys the design and process characteristics relevant to the manufacturability of submicron ics. the discussion also covers analysis of design for manufacturability (dfm) trade-offs. yield and cost models needed to analyze these trade-offs are explained as well.
idap: a tool for high level power estimation of custom array structures. while array structures are a significant source of power dissipation,there is a lack of accurate high-level power estimatorsthat account for varying array circuit implementationstyles. we present a methodology and a tool, the implementationdependent array power (idap) estimator, that modelpower dissipation in sram based arrays accurately basedon a high-level description of the array, parameterized bythe array operations, the implementation styles, and varioustechnology dependent parameters. the methodologyis generic and the idap tool has been validated on industrialdesigns across a wide variety of array implementationsin the e500 processor core. for these industrial designs,idap generates high-level estimates for dynamic power dissipationthat are highly accurate with an error margin ofless than 22.2% of detailed (layout extracted) spice simulations.
simplification of non-deterministic multi-valued networks. we discuss the simplification of non-deterministic mv networks and their internal nodes using internal flexibilities. given the network structure and its external specification, the flexibility at a node is derived as a non-deterministic mv relation. this flexibility is used to simplify the node representation and enhance the effect of boolean resubstitution. we show that the flexibility derived is maximum. the proposed approach has been implemented and tested in mvsis [16]. experimental results show that it performs well on a variety of mv and binary benchmarks.
a theory of non-deterministic networks. both non-determinism and multi-level networks compactlycharacterize the flexibility allowed in implementing a circuit.a theory for representing and manipulating non-deterministic(nd) multi-level networks is developed. the theory supports allthe network manipulations commonly applied to deterministicbinary networks, such as node minimization, elimination, anddecomposition. it is shown that an nd network's behavior can beinterpreted in three ways, all of which coincide when the networkis deterministic. operations performed on an nd network areanalyzed under each interpretation for changes in a network'sbehavior. modifications of a few operations are given which mustbe used to guarantee that a network's behavior does not violateits external specification. these modifications depend on whichbehavior is being used and the location of related non-determinism.this theory has been implemented in a system,mvsis. we provide comparisons among the uses of the various behaviors.
a new heuristic for rectilinear steiner trees. the minimum rectilinear steiner tree (rst) problem is one of the fundamental problems in the field of electronic design automation. the problem is np-hard, and much work has been devoted to designing good heuristics and approximation algorithms; to date, the champion in solution quality among rst heuristics is the batched iterated 1-steiner (bi1s) heuristic of kahng and robins. in a recent development, exact rst algorithms have witnessed spectacular progress: the new release of the geosteiner code of warme, winter, and zachariasen has average running time comparable to that of the fastest available bi1s implementation, due to robins. we are thus faced with the paradoxical situation that an exact algorithm for an np-hard problem is competitive in speed with a state-of-the-art heuristic for the problem.the main contribution of this paper is a new rst heuristic, which has at its core a recent 3/2 approximation algorithm of rajagopalan and vazirani for the metric steiner tree problem on quasi-bipartite graphs&mdash;these are graphs that do not contain edges connecting paris of steiner vertices. the rv algorithm is built around the linear programming relaxation of a sophisticated integer program formulation, called the bidirected cut relaxation. our heuristic achieves a good running time by combining an efficient implementation of the rv algorithm with simple, but powerful geometric reductions.experiments conducted on both random and real vlsi instances show that the new rst heuristic runs significantly faster than robins' implementation of bi1s and than the geosteiner code. moreover, the new heuristic typically gives higher-quality solutions than bi1s.
an output encoding problem and a solution technique. we present a new output encoding problem as follows: given a specification table, such as a truth table or a finite state machine state table, where some of the outputs are specified in terms of 1's, 0's and don't cares, and others are specified symbolically, and assuming that the minimum number of bits are used to encode the symbolic outputs (ceiling(log_2_(n)) bits for n symbolic outputs), determine a binary code for each symbol of the symbolically specified output column such that the total number of output functions to be implemented after encoding the symbolic outputs and compacting the columns is minimum. there are several applications of this output encoding problem, one of which is to reduce the area overhead while implementing scan or pseudo-random bist in a circuit with one-hot signals. we develop an exact algorithm to solve the above problem and present experimental data to validate the claim that our encoding strategy helps to reduce the area of a synthesized circuit.
time domain analysis of nonuniform frequency dependent high-speed interconnects. a method based on numerical inversion of the laplace transform for the transient analysis of nonuniform high-speed interconnects in lsi/vlsi circuits is described. the interconnects are treated as lossy multiconductor nonuniform frequency dependent transmission lines. an algorithm for overcoming the inherent initial value instability encountered while numerically integrating transmission line equations is described. the method is directly compatible with the piecewise decomposition technique (pdt) and can be extended to interconnect networks with nonlinear terminations. further speed up can be achieved by using parallel processors. examples and comparisons with published results are presented
schedulability analysis of multiprocessor real-time applications with stochastic task execution times. this paper presents an approach to the analysis of task sets implemented on multiprocessor systems, when the task execution times are specified as generalized probability distributions. because of the extreme complexity of the problem, an exact solution is practically impossible to be obtained even for toy examples. therefore, our methodology is based on approximating the generalized probability distributions of execution times by coxian distributions of exponentials. thus, we transform the generalized semi-markov process, corresponding to the initial problem, into a continuous markov chain (ctmc) which, however, is extremely large and, hence, most often is impossible to be stored in memory. we have elaborated a solution which allows to generate and analyze the ctmc in an efficient way, such that only a small part has to be stored at a given time. several experiments investigate the impact of various parameters on complexity, in terms of time and memory, as well as the trade-offs regarding the accuracy of generated results.
system-level routing of mixed-signal asics in wren. techniques for global and detailed routing of the macrocell-style analog core of a mixed-signal asic are discussed. a comparatively simple geometric model of the problem is combined with an aggressive simulated annealing formulation that selects paths while accommodating numerous signal-integrity constraints. experimental results demonstrate that it is critical to attack such constraints both globally (system-level) and locally (channel-level) to meet designer-specified performance targets
verification of executable pipelined machines with bit-level interfaces. we show how to verify pipelined machine models with bit-level interfaces by using a combination of deductive reasoning and decision procedures. while decision procedures such as those implemented in uclid can be used to verify pipelined machines, the models are at the term level: they abstract away the datapath, require the use of numerous abstractions, implement a small subset of the instruction set, and are far from executable. in contrast, we focus on verifying executable machines with bit-level interfaces. such proofs have previously required substantial expert guidance and the use of deductive reasoning engines. we show that by integrating uclid with the acl2 theorem proving system, we can use acl2 to reduce the proof that an executable, bit-level machine refines its instruction set architecture to a proof that a term level abstraction of the bit-level machine refines the instruction set architecture, which is then handled automatically by uclid. in this way, we exploit the strengths of acl2 and uclid to prove theorems that are not possible to even state using uclid and that would require prohibitively more effort using just acl2.
a complete compositional reasoning framework for the efficient verification of pipelined machines. we present a compositional reasoning framework based on refinement for verifying that pipelined machines satisfy the same safety and liveness properties as their instruction set architectures. our framework consists of a set of convenient, easily-applicable, and complete compositional proof rules. we show that our framework greatly extends the applicability of decision procedures by verifying a complex, deeply pipelined machine that state-of-the-art tools cannot currently handle. we discuss how our framework can be added to the design cycle and highlight what arguably is the most important benefit of our approach over current methods, that the counterexamples generated are much simpler, as bugs are isolated to a particular step in the composition proof.
unified complete mosfet model for analysis of digital and analog circuits. in this paper, we describe the complete mosfet model developed for circuit simulations. the model describes all transistor characteristics as functions of surface potentials, which are calculated iteratively at each applied voltage under the charge-sheet approximation. the key idea of this development is to put as much physics as possible into the equations describing the surface potentials. since the model includes both the drift and the diffusion contributions, a single equation is valid from the subthreshold to the saturation regions. the unified treatment of our model allows all transistor characteristics to be calculated without any nonphysical fitting parameters. additionally the calculation time is drastically reduced in comparison with a conventional piece-wise model.
simulation and sensitivity analysis of transmission line circuits by the characteristics method. in this paper we use the method of characteristics to derive a new simulation model of lossy transmission lines, and we present the sensitivity analysis in the time-domain. the simulation model is as fast as the recursive convolution model based on moment matching and pade' approximation, but does not have the stability problem. the sensitivity analysis model is particularly useful for transmission line circuits containing nonlinear elements, and is believed to be the first time- domain model. both the simulation and sensitivity analysis models are applicable to uniform and nonuniform transmission lines with arbitrary nonzero initial states. also we show that any nonlinear circuit element has a very simple linear model in sensitivity analysis. furthermore, we demonstrate that for any circuits, the modified nodal admittance(mna) matrices in simulation and in sensitivity analysis equations are the same, therefore no lu decomposition is needed in sensitivity analysis. the contributions in this paper have been implemented into a general-purpose program cssc(circuit simulation and sensitivity analysis with characteristics) which shows excellent accuracy and efficiency in both simulation and sensitivity analysis of transmission line circuits.
a force-directed macro-cell placer. in this paper we present a novel force-directed placement algorithm, which is used to solve macro-cell placement problems. a new wire model replaces the traditional clique model and makes possible early awareness of routing congestion. issues such as cell orientation, overlap elimination, and pad positioning are also considered. experiments show satisfactory performance and fast run time.
transformational partitioning for co-design of multiprocessor systems. this paper presents the underlying methodology of cosmos, an interactive approach for hardware/software co-design capable of handling multiprocessor systems and distributed architectures. the approach covers the co-design process through a set of user guided transformations allowing semi-automatic partitioning. the transformations are based on a powerful set of primitives for functional partitioning, structural reorganization and communication transformation. it leads to a fast transformation of a system-level specification into an architecture with a short design time and fast exploration of design space. the application of this approach is illustrated using several design examples starting from a system-level specification given in sdl to a distributed hardware/software architecture described in c/vhdl. we show that the use of transformational approach allows: application of the expertise of the designer during partitioning ; - the user to understand the results of the co-design process ; the process to take into account partial existing solutions ; - large design space exploration ; the designer to start from a very high-level specification language of the system to be designed.
a force-directed maze router. a new routing algorithm is presented. it is based on a multiple star net model, force-directed placement and maze searching techniques. the algorithm inherits the power of maze routing in that it is able to route complex layouts with various obstructions. the large memory requirement of the conventional maze algorithm is alleviated through successive net refinement, which constrains the maze searching to small regions. the algorithm shows advantages in routing designs with complicated layout obstructions.
application-driven processor design exploration for power-performance trade-off analysis. this paper presents an efficient design exploration environment for high-end core processors. the heart of the proposed design exploration framework is a two-level simulation engine that combines detailed simulation for critical portions of the code with fast profiling for the rest. our two-level simulation methodology relies on the inherent clustered structure of application programs and is completely general and applicable to any microarchitectural power/performance simulation engine. the proposed simulation methodology is 3-17x faster, while being sufficiently accurate (within 5%) when compared to the fully detailed simulator. the design exploration environment is able to vary different microarchitectural configurations and find the optimal one as far as energyxdelay product is concerned in a matter of minutes. the parameters that are found to affect drastically the core processor power/performance metrics are issue width, instruction window size, and pipeline depth, along with correlated clock frequency. for very high-end configurations for which balanced pipelining may not be possible, opportunities for running faster stages at lower voltage exist. in such cases, by using up to 3 voltage levels, the energyxdelay product is reduced by 23-30% when compared to the single voltage implementation.
noise analysis of phase-locked loops. this work addresses the problem of noise analysis of phase locked loops (plls). the problem is formulated as a stochastic differential equation and is solved in presence of circuit white noise sources yielding the spectrum of the pll output. specifically, the effect of loop filter characteristics, phase-frequency detector and phase noise of the open loop voltage controlled oscillator (vco) on the pll output spectrum is quantified. these results are derived using a full nonlinear analysis of the vco in the feedback loop and cannot be predicted using traditional linear analyses or the phase noise analysis of open loop oscillators. the computed spectrum matches well with measured results, specifically, the shape of the output spectrum matches very well with measured pll output spectra reported in the literature for different kinds of loop filters and phase detectors. the pll output spectrum computation only requires the phase noise of the vco, loop filter and phase detector noise, phase detector gain and loop filter transfer function and does not require the transient simulation of the entire pll which can be very expensive. the noise analysis technique is illustrated with some examples.
architectural-level synthesis of digital microfluidics-based biochips. microfluidics-based biochips offer a promising platform for massively parallel dna analysis, automated drug discovery, and real-time biomolecular recognition. current techniques for full-custom design of droplet-based "digital" biochips do not scale well for concurrent assays and for next-generation system-on-chip (soc) designs that are expected to include fluidic components. we propose a system design methodology that attempts to apply classical architectural-level synthesis techniques to the design of digital microfluidics-based biochips. we first develop an optimal scheduling strategy based on integer linear programming. since the scheduling problem is np-complete, we also develop two heuristic techniques that scale well for large problem instances. a clinical diagnostic procedure, namely multiplexed in-vitro diagnostics on human physiological fluids, is used to evaluate the proposed method.
switching activity analysis considering spatiotemporal correlations. this work presents techniques for computing the switching activities of all circuit nodes under pseudorandom or biased input sequences and assuming a zero delay mode of operation. complex spatiotemporal correlations among the circuit inputs and internal nodes are considered by using a lag-one markov chain model. evaluations of the model and a comparative analysis presented for benchmark circuits demonstrates the accuracy and the practicality of the method. the results presented in this paper are useful in power estimation and low power design.
steady-state analysis of voltage and current controlled oscillators. this paper introduces the problem of finding the steady-state and the numerical value of the controlling voltage or current for oscillators where the frequency of oscillation is known beforehand. these situations are very common when the oscillator is part of a phase-locked loop (pll). in plls, the reference frequency as well as the divide ratios are known at the time of design. therefore the desired frequency of the voltage (current) controlled oscillator is known but not the controlling voltage (current). we formulate this problem as the solution of an appropriate nonlinear equation. we present robust and efficient numerical techniques for solving this nonlinear equation both in time and frequency domain. we demonstrate using experimental results that this technique is at par with classical methods of calculating oscillator steady-state and period of oscillation for a given control voltage. we show that compared to a search-based approach to calculating the desired control voltage or current, our direct method is a order of magnitude faster for the same accuracy.
post-route optimization for improved yield using a rubber-band wiring model. this paper presents a unique approach to improve yield given a routed layout. currently after routing has been completed and compacted, it generally proceeds to verification without further modifications. however, to improve manufacturability, we introduce a concept called even wire distribution, a key element of the surf physical design tool. to alleviate congestion, we first move vias and wires torwards less dense areas in a manner which preserves the existing wiring paths. depending on locally available area, we then increase wire spacing to reduce defect sensitivity, without changing the area of the design. carafe, an inductive fault analysis tool is used to evaluate the new layout.
system-level power/performance analysis of portable multimedia systems communicating over wireless channels. this paper presents a new methodology for system-level power and performance analysis of wireless multimedia systems. more precisely, we introduce an analytical approach based on concurrent processes modeled as stochastic automata networks (sans) that can be effectively used to integrate power and performance metrics in system-level design. we show that 1) under various input traces and wireless channel conditions, the average-case behavior of a multimedia system consisting of a video encoder/decoder pair is characterized by very different probability distributions and power consumption values and 2) in order to identify the best trade-off between power and performance figures, one must take into consideration the entire environment (i.e., encoder, decoder, and channel) for which the system is being designed. compared to using simulation, our analytical technique reduces the time needed to find the steady-state behavior by orders of magnitude, with some limited loss in accuracy compared to the exact solution. we illustrate the potential of our methodology using the mpeg-2 video as the driver application.
sequential optimisation without state space exploration. we propose an algorithm for area optimization of sequential circuits through redundancy removal. the algorithm finds compatible redundancies by implying values over nets in the circuit. the potentially exponential cost of state space traversal is avoided and the redundancies found can all be removed at once. the optimized circuit is a safe delayed replacement of the original circuit. the algorithm computes a set of compatible sequential redundancies and simplifies the circuit by propagating them through the circuit. we demonstrate the efficacy of the algorithm even for large circuits through experimental results on benchmark circuits.
fault-tolerant techniques for ambient intelligent distributed systems. ambient intelligent systems provide an unexplored hardware platformfor executing distributed applications under strict energy constraints.these systems must respond quickly to changes in userbehavior or environmental conditions and must provide high availabilityand fault-tolerance under given quality constraints. thesesystems will necessitate fault-tolerance to be built into applications.one way to provide such fault-tolerance is to employ the use of redundancy.hundreds of computational devices will be available indeeply networked ambient intelligent systems, providing opportunitiesto exploit node redundancy to increase application lifetime orimprove quality of results if it drops below a threshold. pre-copyingwith remote execution is proposed as a novel, alternative techniqueof code migration to enhance system lifetime for ambient intelligentsystems. self-management of the system is considered in two differentscenarios: applications that tolerate graceful quality degradationand applications with single-point failures. the proposed techniquecan be part of a design methodology for prolonging the lifetime ofa wide range of applications under various types of faults, despitescarce energy resources.
noise analysis of non-autonomous radio frequency circuits. in this paper we consider the important problem of noise analysis of non-autonomous nonlinear rf circuits in presence of input signal phase noise. we formulate this problem as a stochastic differential equation and solve it in the presence of circuit white noise sources. we show that the output noise of a nonlinear non-autonomous circuit, driven by a periodic input signal with phase noise, is stationary and not cyclostationary (as would be predicted by traditional analyses). we also show that effect of input signal phase noise is to act as additional white noise source. this result is derived using a full nonlinear analysis of the problem and cannot be predicted by traditional linear analysis based techniques. input signal phase noise can be an important portion of the overall output noise of the non-autonomous circuit. in our opinion, existing analyses have not considered this effect in a rigorous manner. we also relate this solution to results of the existing nonlinear time domain and frequency domain methods of noise analysis and point out the modifications required for the present techniques. we illustrate our technique using an example.
hybrid structured clock network construction. this paper hierarchically constructs a hybrid mesh/tree clock network structure consisting of overlying zero-skew clock meshes, with underlying zero-skew clock trees originating from the mesh nodes. we propose a mesh construction procedure, which guarantees zero skew under the elmore delay model, using a simple and efficient linear programming formulation. buffers are inserted to reduce the transition time (or rise time). as a post-processing step, wire width optimization under an accurate higher-order delay metric is performed to further minimize the transition time and propagation delay/skew. experimental results show that the hybrid mesh/tree construction scheme can provide smaller propagation delay and transition time than a comparable clock tree.
a realistic variable voltage scheduling model for real-time applications. voltage scheduling is indispensable for exploiting the benefit of variable voltage processors. though extensive research has been done in this area, current processor limitations such as transition overhead and voltage level discretization are often considered insignificant and are typically ignored. we show that for hard, real-time applications, disregarding such details can lead to sub-optimal or even invalid results. we propose two algorithms that guarantee valid solutions. the first is a greedy yet simple approach, while the second is more complex but significantly reduces energy consumption under certain conditions. through experimental results on both real and randomly generated systems, we show the effectiveness of both algorithms, and explore what conditions make it beneficial to use the complex algorithm over the basic one.
combined dynamic voltage scaling and adaptive body biasing for lower power microprocessors under dynamic workloads. dynamic voltage scaling (dvs) reduces the power consumption of processors when peak performance is unnecessary. however, the achievable power savings by dvs alone is becoming limited as leakage power increases. in this paper, we show how the simultaneous use of adaptive body biasing (abb) and dvs can be used to reduce power in high-performance processors. analytical models of the leakage current, dynamic power, and frequency as functions of supply voltage and body bias are derived and verified with spice simulation. we then show how to determine the correct trade-off between supply voltage and body bias for a given clock frequency and duration of operation. the usefulness of our approach is evaluated on real workloads obtained using real-time monitoring of processor utilization for four applications. the results demonstrate that application of simultaneous dvs and abb results in an average energy reduction of 48% over dvs alone.
the circuit design of the synergistic processor element of a cell processor. a 32b 4-way simd dual-issue synergistic processor element of a cell processor is developed with 20.9 million transistors in 14.8mm/sup 2/ using a 90nm soi technology. cmos static gates implement the majority of the logic. dynamic circuits are used in critical areas, occupying 19% of the nonsram area. isa, microarchitecture and physical implementation are tightly coupled to achieve a compact and power efficient design. correct operation has been observed up to 5.6ghz at 1.4v supply and 56/spl deg/c.
detection of multiple transitions in delay fault test of sparc64 microprocessor. this work presents a new non-robust delay fault test generation method for the purpose of screening delay defects of microprocessors with fewer test vectors. it is important to reduce the number of test vectors in order to reduce test time, memory usage in the tester, and the overall testing cost. by paying attention to the constraints of off-path inputs in a non-robust test, we made it possible to generate a pair of test vectors to detect multiple delay faults based on the traditional dynamic compaction technique. delay fault test based on our method is applied to sparc64 microprocessor with 1.3 ghz clock for screening delay defects, and we achieved 90% coverage with 3,567 test vectors. the comparison results also show that the robust test is not practical for the screening purpose, since it needs more than three times the number of test vectors as compared to the non-robust test.
dynamic voltage scaling for the schedulability of jitter-constrained real-time embedded systems. jitter is a critical problem for the design of both distributed embedded systems and real-time control systems. this work considers meeting the completion jitter constraints of a set of independent, periodic, hard real-time tasks scheduled according to a preemptive fixed-priority scheme. control over completion jitter is achieved by judiciously applying dynamic voltage scaling (dvs). through simulation, the proposed method is shown to be an effective tool to meet jitter constraints on a variety of systems.
a new approach for factorizing fsm's. exact factors as defined in [2], if present in an fsm can result in most effective way of factorization. however, it has been found that most of the fsm's are not exact factorizable. in this paper, we have suggested a method of making fsm's exact factorizable by minor changes in the next state space while maintaining the functionality of the fsm. we have also developed a new combined state assignment algorithm for state encoding of factored and factoring fsm's. experimental results on mcnc benchmark examples, after running misii on the original fsm, factored fsm and factoring fsm have shown a reduction of 40% in the worst case signal delay through the circuit in a multilevel implementation. the total number of literals, on an average is the same after factorization as that obtained by running misii on the original fsm. for two-level implementation, our method has been able to factorize benchmark fsm's with a 14% average increase in overall areas, while the areas of combinational components of factored and factoring fsm's have been found to be significantly less than the area of the combinational component of the original fsm.
new methods for parallel pattern fast fault simulation for synchronous sequential circuits. the authors present combined, a super fast fault simulator for synchronous sequential circuits. combined is based on coupling a parallel pattern simulator with a non-parallel simulator. combined runs substantialy faster on iscas-89 benchmark circuits than a state-of-the-art single fault propagation simulator
bit-level scheduling of heterogeneous behavioural specifications. this paper presents a heuristic scheduling algorithm for heterogeneous specifications, those formed by operations of different types and widths. the algorithm extracts the common operative kernel of the operations, and binds afterwards operations to cycles with the aim of distributing uniformly the number of bits calculated per cycle. in consequence, operations may be fragmented and executed during a set of non-necessarily consecutive cycles, and over a set of several linked simple hardware resources. the proposed algorithm, in combination with allocation algorithms able to guarantee bit-level reuse of hardware resources, obtains considerably smaller datapaths than the ones proposed by conventional synthesis algorithms. in the datapaths produced the type, number, and width of the hardware resources are independent of the type, number, and width of the specification operations and variables.
fredkin/toffoli templates for reversible logic synthesis. reversible logic has applications in quantum computing, lowpower cmos, nanotechnology, optical computing, and dnacomputing. the most common reversible gates are the toffoli gate and the fredkin gate. our synthesis algorithm first finds a cascade of toffoli and fredkin gates with no back-tracking and minimal look-ahead. next we apply transformations that reduce the size of the circuit. transformations are accomplished via template matching. the basis for atemplate is a network with m gates that realizes the identity function. if a sequence in the network to be synthesized matches more than half of a template, then a transformationthat reduces the gate count can be applied. in this paper weshow that toffoli and fredkin gates behave in a similar manner. therefore, some gates in the templates may not needto be specified-they can match a toffoli or a fredkin gate.we formalize this by introducing the box gate. all templateswith less than six gates are enumerated and classified. wesynthesize all three input, three output reversible functionsand compare our results to those obtained previously.
fastmag: a 3-d magnetostatic inductance extraction program for structures with permeable materials. in this paper we present a fast and efficient program for extraction of the frequency dependent inductance of structures with permeable materials. the program, fastmag, uses a magnetic surface charge formulation, efficient techniques for evaluating the required integrals, and a preconditioned gmres method to solve the resulting linear system. results from examples are presented to demonstrate the accuracy and versatility of the fastmag program.
scheduling and binding bounds for rt-level symbolic execution. generalizes alap (as late as possible) bounds for the exact scheduling problem on a pre-defined data path. conventional bounds are inapplicable because of the possible requirement of re-computing operands for minimal schedule length. efficient techniques are presented for constructing the new bounds which are sensitive to point-to-point delays via transitive memory units. an efficient operand mapping bound is also described. based on these two bounds, time improvement factors of 50 have demonstrated in exact scheduling results.
reducing pessimism in rlc delay estimation using an accurate analytical frequency dependent model for inductance. the increasing demand for high performance ics and system on chip necessitates reliable methodologies for reducing pessimism in chip design. in this paper, we investigate how the frequency dependence of loop self inductance affects the rlc delay. we show that the pessimism in the estimation of rlc propagation delay could be as high as 30% if the frequency dependence of inductance is not considered properly. as a means of efficiently computing less pessimistic rlc delay values, we present an analytical model of frequency dependent loop self inductance that can be applied to model a wide range of real design scenarios. we demonstrate that our approach is computationally efficient and produces accurate and realistic (less pessimistic) delay values that lead to significantly improved system performance.
re-engineering of timing constrained placements for regular architectures. abstract: in a typical design flow, the design may be altered slightly several times after the initial design cycle according to minor changes in the design specification either as a result of design debugging or as a result of changes in engineering requirements. these modifications are usually local and are referred to as engineering changes. in this paper we study the problem of timing driven placement re-engineering: the problem of altering the placement of a circuit to incorporate engineering changes without degrading the timing performance of the circuit. we focus on the re-engineering problem for regular architectures such as fpgas and gate arrays. our algorithms exploit the locality of the re-engineering design changes and use the current placement to generate the new placement for the altered circuit. our experiments on the xilinx 3000 fpga architecture demonstrate the effectiveness of our algorithm in handling engineering changes efficiently.
compression-relaxation: a new approach to performance driven placement for regular architectures. we present a new iterative algorithm for performance driven placement applicable to regular architectures such as fpgas. our algorithm has two phases in each iteration: a compression phase and a relaxation phase. we employ a novel compression strategy based on the longest path tree of a cone for improving the timing performance of a given placement. compression might cause a feasible placement to become infeasible. the concept of a slack neighborhood graph is introduced and is used in the relaxation phase to transform an infeasible placement to a feasible one using a mincost flow formulation. our analytical results regarding the bounds on delay increase during relaxation are validated by the rapid convergence of our algorithm on benchmark circuits. we obtain placements that have 13% less critical path delay (on the average) than those generated by the xilinx automatic place and route tool (apr) on technology mapped mcnc benchmark circuits with significantly less cpu time than apr.
least fixpoint approximations for reachability analysis. the knowledge of the reachable states of a sequential circuit can dramatically speed up optimization and model checking. however, since exact reachability analysis may be intractable, approximate techniques are often preferable. cho et al. presented the machine-by-machine (mbm) and frame-by-frame (fbf) methods to perform approximate fsm traversal. fbf produces tighter upper bounds than mbm; however, it usually takes much more time and it may have convergence problems. in this paper, we show that there exists a class of methods&mdash;least fixpoint approximations&mdash;that compute the same results as rfbf (reached fbf, one of the fbf methods). we show that one member of this class, which we call least fixpoint mbm (lmbm), is as efficient as mbm, but provably more accurate. therefore, the trade-off that existed between mbm and rfbf has been eliminated. lmbm can compute rfbf-quality approximations for all the large iscas-89 benchmark circuits in a total of less than 9000 seconds.
real time analysis and priority scheduler generation for hardware-software systems with a synthesized run-time system. we present a tool, called clara, that performs real-time analysis and priority assignment for software tasks in a mixed hardware-software system with a custom run-time scheduler. we start from a system described in tasks/threads consisting of hardware specified in verilog and software specified in c. we obtain the worst case execution time for each individual task. then, based on the control flow of the application, clara uses a dynamic programmming algorithm to automatically find optimal priorities for the software tasks assuming no interrupts. assuming the set of software tasks runs on a microprocessor in a target architecture using a template we provide for the priority scheduler and interrupt code, clara then finds the worst case execution time for the application with interrupts allowed. thus, this tool brings real-time analysis to a system level for a particular run-time system. clara helps a designer minimize the worst case execution time of a mixed hardware-software application.
event driven simulation without loops or conditionals. the past several years have seen much research in event driven logic simulation[1]. various logic and delay models have been explored[2]. most simulation research has focused on improving simulation performance. new approaches to both compiled and event driven simulation have been explored[3,4,5].the internal operations of event-driven simulators can be divided into two categories, scheduling, and gate simulation. much effort has been focused on reducing the cost of scheduling[3,4,5]. there has also been effort to reduce the cost of gate simulation[6,7]. it has also been shown that explicit computation of gate outputs is unnecessary, as long as event-propagation is computed correctly[7].even though research has reduced the complexity of both scheduling and gate simulation, it is still necessary to test for event propagation and cancellation, and it is necessary to perform some computations during gate simulation.this paper will show that none of these computations are necessary. most computations are devoted testing internal states and computing new internal states. in our technique, subroutine addresses are used to maintain states. this permits the elimination of all state-testing and state-computation code. our technique is significantly faster than conventional event-driven simulation[1]. unlike earlier methods[7], our approach can easily be extended to any logic model or any delay model.
a novel design methodology for high performance and low power digital filters. presents novel design methodologies which can be used to dramatically reduce the complexity of parallel implementations of digital fir filters. these approaches are also applicable to iir filters. two ideas are presented. first, we remove the redundant computation by using a graph-theoretic framework in which we find the optimal re-ordering of computations for maximal computation sharing. second, we present the novel approach of searching for a quantization which improves the computation sharing when the frequency-domain transfer function is allowed to deviate within given bounds. a simple search scheme is presented and it is shown that, by appropriate perturbation of the filter coefficients, one can dramatically reduce the number of adders required in the filter implementation. using these approaches, on an average, less than one adder per coefficient is required, in contrast to a full-width multiplier. hence, the presented methodologies are a useful compliment to the existing design approaches of high-performance and low-power digital filters for future mobile computing and communication systems
the inversion algorithm for digital simulation. the inversion algorithm is an event-driven algorithm, whose performance rivals or exceeds that of levelized compiled code simulation, even at activity rates of 50% or more. the inversion algorithm has several unique features, the most remarkable of which is the size of the run-time code. the basic algorithm can be implemented using no more than a page of run-time code, although in practice it is more efficient to provide several different variations of the basic algorithm. the run-time code is independent of the circuit under test, so the algorithm can be implemented either as a compiled code or an interpreted simulator with little variation in performance. because of the small size of the run-time code, the run-time portions of the inversion algorithm can be implemented in assembly language for peak efficiency, and still be retargeted for new platforms with little effort.
design automation issues for biofluidic microchips. biotechnologists have started to exploit the ic industry's planar microfabrication technology. the state of the art in planar biofluidic microdevices is reviewed as a way of introducing biochip design issues. as with transistor ics, design aids that span the entire iccad program from modeling and simulation to synthesis and physical design are needed to address these issues. hierarchical design representations, modeling abstractions, and algorithms pertaining to biochip design will be reviewed. potential future challenges will be identified to motivate how the iccad community can contribute to this emerging area.
an efficient and robust technique for tracking amplitude and frequency envelopes in oscillators. envelope-following methods face special challenges when applied to oscillators because of their fundamental property of dynamically-changing frequencies. in this paper, we present a novel and robust approach for oscillator envelope following. our method combines, unifies and extends ideas from two prior oscillator envelope-following approaches, petzold's method and the wampde. our technique uses two extra system unknowns, as well as two extra "phase condition" equations, to track quantities related to dynamical frequency/time-period changes. these advances confer significant robustness without appreciable computational overhead. we validate our method on lc, ring and crystal oscillators, predicting frequency and amplitude modulations as well as transient startup envelopes accurately. speedups of 1-2 orders of magnitude are obtained over traditional alternatives.
a general s-domain hierarchical network reduction algorithm. this paper presents an efficient method to reduce complexities ofa linear network in s-domain. the new method works on circuitmatrices directly and reduces the circuit complexities by eliminatingsubcircuits in a hierarchical way. the resulting admittancesin the reduced networks are kept as rational functions of s withreduced order. some theoretical results are characterized for thepresence of common factors coming from the suppression of subcircuits.a novel common factor removal (de-cancellation) strategybased on a graph-based hierarchical subcircuit reduction processis proposed. the resulting reduction algorithm is applicableto any linear circuits in s-domain. the stability of the reduced systemis enforced by applying the hurwitz polynomial approximation.the reduced systems can be used for fast s-domain analysisand for time domain waveform evaluation. experimental resultson both linear analog circuits and rlc circuits, and comparisonwith spice in s-domain analysis are also provided.
synthesis of manufacturable analog circuits. we describe a synthesis system that takes operating range constraints and inter- and intra-circuit parametric manufacturing variations into account while designing a sized and biased analog circuit. previous approaches to cad for analog circuit synthesis have concentrated on nominal analog circuit design, and subsequent optimization of these circuits for statistical fluctuations and operating point ranges. our approach simultaneously synthesizes and optimizes for operating and manufacturing variations by mapping the circuit design problem into an infinite programming problem and solving it using an annealing within annealing formulation. we present circuits designed by this integrated synthesis system, and show that they indeed meet their operating range and parametric manufacturing constraints.
a symbolic simulation-based methodology for generating black-box timing models of custom macrocells. we present a methodology for generating black-box timing models for full-custom transistor-level cmos circuits. our approach utilizes transistor-level ternary symbolic timing simulation to explore the input arrival time space and determine the input arrival time windows that result in proper operation. this approach integrates symbolic timing simulation into existing static timing analysis flows and allows automated modelling of the timing behavior of aggressive full-custom circuit design styles.
on testable multipliers for fixed-width data path architectures. the usage of multipliers in the increasingly demanding fixed-width data path architectures poses serious testability problems. their truncated outputs not only degrade the fault observability, but the output responses of multipliers are inadequate to completely test functional blocks that are driven by them. in this paper, we propose a new design for testability scheme to improve the overall testability of data paths. the methodology takes into account the truncated least significant bits of the product in the test mode to increase the variety of patterns at the output of a multiplier. the proposed techniques are part of the arithmetic built-in self test methodology and can be incorporated with a minimal performance degradation and area overhead.
symbolic functional and timing verification of transistor-level circuits. we introduce a new method of verifying the timing of custom cmos circuits. due to the exponential number of patterns required, traditional simulation methods are unable to exhaustively verify a medium-sized modern logic block. static analysis can handle much larger circuits but is not robust with respect to variations from standard circuit structures. our approach applies symbolic simulation to analyze a circuit over all input combinations without these limitations. we present a prototype simulator (sirsim) and experimental results. we also discuss using sirsim to verify an industrial design which previously required a special-purpose verification methodology.
statistical design and optimization of sram cell for yield enhancement. we have analyzed and modeled the failure probabilities of sram cells due to process parameter variations. a method to predict the yield of a memory chip based on the cell failure probability is proposed. the developed method is used in an early stage of a design cycle to minimize memory failure probability by statistically sizing of sram cell.
fast discrete function evaluation using decision diagrams. abstract: an approach for fast discrete function evaluation based on multi-valued decision diagrams (mdd) is proposed. the mdd for a logic function is translated into a table on, which function evaluation is performed by a sequence of address lookups. the value of a function for a given input assignment is obtained with at most one lookup per input. the main application is to cycle-based logic simulation of digital circuits, where the principal difference from other logic simulators is that only values of the output and latch ports are computed. theoretically, decision-diagram based function evaluation offers orders-of-magnitude potential speedup over traditional logic simulation methods. in practice, memory bandwidth becomes the dominant consideration on large designs. we describe techniques to optimize usage of the memory hierarchy.
rectangle-packing-based module placement. the first and the most critical stage in vlsi layout design is the placement, the background of which is the rectangle packing problem: given many rectangular modules of arbitrary size, place them without overlapping on a layer in the smallest bounding rectangle. since the variety of the packing is infinite (two- dimensionally continuous) many, the key issue for successful optimization is in the introduction of a p-admissible solution space, which is a finite set of solutions at least one of which is optimal. this paper proposes such a solution space where each packing is represented by a pair of module name sequences. searching this space by simulated annealing, hundreds of modules could be successfully packed as demonstrated. combining a conventional wiring method, the biggest mcnc benchmark ami49 is challenged.
adaptive designs for power and thermal optimization. a processor designed to continuously monitor environmental conditions, such as its own power consumption, temperature, and operating frequency, has the potential to dynamically optimize its operating point for maximal power efficiency in real time. the implementation of montecito's power and thermal control system (foxton), which is nearing production, provides a basis for discussing opportunities for increasing power efficiency and robustness.
layout-driven area-constrained timing optimization by net buffering. with the advent of deep sub-micron technologies, interconnect loads and delays are becoming significant, and layout-driven synthesis has become the need of the day. however, given the tight constraints imposed by the layout (e.g., area availability, congestion), only those synthesis transforms can be made layout-driven that are local and layout-friendly. examples of such transforms are net buffering, gate resizing, and gate replication.in this paper, we address the problem of minimizing the delay of a mapped, roughly placed, and globally-routed design by buffer insertion and/or deletion without violating the local area constraints imposed by the layout and without overloading any buffer/cell pins. we believe this is the one of the most fundamental problems in layout-driven buffer optimization. to the best of our knowledge, no technique has been published to date that solves this problem. the concept of local (or block) area constraints we use in this paper is more powerful than that of the total design area traditionally-used in logic synthesis.our main contributions are the following: 1. we propose an exact, layout-driven net buffering algorithm to minimize the delay of an extended net under the area constraint of each block in the design. 2. we propose a simple yet effective scheme for applying the single-net algorithm to an entire design. 3. we apply our technique successfully on three real, large, industrial designs. the largest design (172k gates and 211k nets) could be optimized in about 20 minutes. the technique is remarkably effective when the available area in the design is small: it generates 6-9 times better delay improvements than the unconstrained delay minimization technique [8] modified to handle area constraints. over an entire range of available areas, it gives about 115% better delay improvements.
wta: waveform-based timing analysis for deep submicron circuits. existing static timing analyzers make several assumptions about circuits, implicitly trading off accuracy for speed. in this paper we examine the validity of these assumptions, notably the slope approximation to waveforms, single-input transitions, and the choice of a propagating signal based on a single voltage-time point. we provide data on static cmos gates that show delays obtained in this way can be optimistic by more than 30%. we propose a new approach, waveform-based timing analysis that employs a state-of-the-art circuit simulator as the underlying delay modeler. we show that such an approach can achieve more accurate delays than slope-based timing analyzers at a computation cost that still allows iterations between design modification and delay analysis.
oscillator-ac: restoring rigour to linearized small-signal analysis of oscillators. standard small-signal analysis methods for circuits break down for oscillators because small input perturbations result in arbitrarily large output changes, thus invalidating fundamental assumptions for small-signal analysis. in this paper, we propose a novel oscillator-ac (oac) approach remedying this situation, thus restoring validity and rigour to small-signal analysis of oscillators. our approach centers around a novel, general equation formulation for circuits that we term the gempde. a key feature of our approach is to solve for bivariate frequency variables with the help of novel augmenting phase condition equations. our gempde-based small-signal analysis provides both amplitude and frequency characteristics in a unified manner and is applicable to any kind of oscillator described by differential equations. we obtain speedups of 1-2 orders of magnitude over the transient simulation approach commonly used today by designers for oscillator perturbation analysis. we also demonstrate and explain how our linearization approach captures the inherently nonlinear phenomenon of injection locking in oscillators.
code placement with selective cache activity minimization for embedded real-time software design. many embedded system designs usually impose (hard)read-time constraints on tasks. thus, computing a tight upper boundof the worst case execution time (wcet) of a software is a criticallyimportant, but difficult task. the difficulty arises particularlywhen the code is executed on processors with cache-based memorysystems. in this paper, we propose a new code placement techniqueunder cache activity consideration for real-time software design.specifically, unlike the previous approaches which have triedto minimize total cache misses, which is not necessarily the bestway to meet all timing constraints of tasks, we minimizes the cachemisses in a selective way for tasks according to the degree of tightness(or urgency) of their timing constraints. based on a concept ofselective cache activity minimization, we propose a new approachwhich solves the code placement problem in two steps: (step 1) wetransform the code placement problem into so called an interval selectionproblem, which then we formulate into a 0-1 integer linearprogramming (ilp); (step 2) we apply an efficient approximationalgorithm, called code-map, to solve the exact code placementformulation obtained in step.
performance optimization under rise and fall parameters. typically, cell parameters such as the pin-to-pin intrinsic delays, load-dependent coefficients, and input pin capacitances have different values for rising and falling signals. the performance optimization algorithms, however, assume a single value for each parameter. no work has been done to study the impact of separate rise and fall values on the complexity of optimization. in this paper, we take the first step towards understanding this impact. we pick two problems that have polynomial-time complexities if a single value for each cell parameter is assumed. the first problem is that of buffer insertion on a fixed topology net to maximize the required time at the source of the net. the second is the gate resizing problem (and the more general technology mapping problem) for minimizing the circuit delay under the simplest, load-independent delay model. we show that under separate rise and fall parameters, both these problems become np-complete. to the best of our knowledge, this is the first such result showing the effect of rise and fall parameters on the complexity of performance optimization problems. we then address the important question of devising a good practical algorithm for local fanout optimization.
on the global fanout optimization problem. fanout optimization is a fundamental problem in timing optimization. most of the research has focussed on the fanout optimization problem for a single net (or the local fanout optimization problem lfo). the real goal, however, is to optimize the delay through the entire circuit by fanout optimization. this is the global fanout optimization (gfo) problem. touati claims in his thesis [6] that visiting nets of the network in a reverse topological order (from primary outputs to inputs), applying the optimum lfo algorithm to each net, computing the new required time at the source and propagating the delay changes to the fanins yields a provably optimum solution to the gfo problem. this result implies that gfo is solvable in polynomial time if lfo is. in this paper, we show that that is not the case. we prove that gfo is np-complete even if there are a constant number of buffering choices at each net. we analyze touati's result and point out the flaw in his argument. we then present sufficient conditions for the optimality of the reverse topological algorithm.
delay and bus current evaluation in cmos logic circuits. an accurate and fast analytical technique for computing the delay and the maximum supply current in a cmos inverter is presented. it accounts for the effects of input slope, output load, transistor size, and short-circuit current. the accuracy is within 10% of the hspice level-3 model and the speed is more than three orders of magnitude faster than hspice. an extension of this technique is shown for the calculation of the delay and the maximum supply current of a chain of inverters, without recourse to integration. an efficient method for computing the total current waveform of the chain is also presented. the relative speed of computing the current waveform exceeds two orders of magnitude compared to hspice
code partitioning for synthesis of embedded applications with phantom. in a large class of embedded systems, dynamic multitasking using traditional os techniques is infeasible because of memory and processing overheads or lack of operating systems availability for the target embedded processor. serializing compilers have been proposed as an alternative solution, enabling a designer to develop multitasking applications without the need of os support. a serializing compiler is a source-to-source translator that takes a posix compliant multitasking c program as input and generates an equivalent, embedded processor independent, single-threaded ansi c program, to be compiled using the embedded processor-specific tool chain. such serializing compilers work by partitioning each task into blocks of code and synthesizing a scheduler that dynamically switches among these blocks. the quality of the compiled code in terms of multitasking overhead and task latency is highly dependent on the partitioning algorithm. in this work, we give our solution to the partitioning problem in the context of serializing compilers. we show that it is possible to provide the designer with a set of pareto-optimal solutions that trade off multitasking overhead for task latency.
soi transistor model for fast transient simulation. progress in semiconductor process technology has made soitransistors one of the most promising candidates for high performanceand low power designs. with smaller diffusion capacitances,soi transistors switch significantly faster than theirtraditional bulk mos counterparts and consume less power perswitching. however, design and simulation of soi mos circuits ismore challenging due to more complex behavior of an soi transistorinvolving floating body effects, delay dependence on history oftransistor switching, bipolar effect and others. this paper isdevoted to developing a fast table model of soi transistors, suitablefor use in fast transistor level simulators. we propose usingbody charge instead of body potential as an independent variableof the model to improve convergence of circuit simulation integrationalgorithm. soi transistor has one additional terminal comparedwith the bulk mosfet and hence requires larger tables tomodel. we propose a novel transformation to reduce number oftable dimensions and as a result to make the size of the tables reasonable.the paper also presents efficient implementation of oursoi transistor table model using piece-wise polynomial approximation,nonuniform grid discretization, and splitting the transistormodel into the model of its equilibrium and non equilibrium states.the effectiveness of the proposed model is demonstrated byemploying it in a fast transistor level simulator to simulate highperformance industrial soi microprocessor circuits.
performance-driven simultaneous place and route for island-style fpgas. abstract: sequential place and route tools for fpgas are inherently weak at addressing both wirability and timing optimizations. this is primarily due to the difficulty of accurately predicting wirability and delay during placement. a new performance-driven simultaneous placement/routing technique has been developed for island-style fpga designs. on a set of industrial designs for xilinx 4000-series fpgas, our scheme produces 100% routed designs with 8%-15% improvement in delay when compared to the xilinx xact5.0 place and route system.
power estimation techniques for integrated circuits. with the advent of portable and high-density microelectronic devices, the power dissipation of very large scale integrated (vlsi) circuits is becoming a critical concern. accurate and efficient power estimation during the design phase is required in order to meet the power specifications without a costly redesign process. recently, a variety of power estimation techniques have been proposed, most of which are based on: 1) the use of simplified delay models, and 2) modeling the long-term behavior of logic signals with probabilities. the array of available techniques differ in subtle ways in the assumptions that they make, the accuracy that they provide, and the kinds of circuits that they apply to. in this tutorial, i will survey the many power estimation techniques that have been recently proposed and, in an attempt to make sense of all the variety, i will try to explain the different assumptions on which these techniques are based, and the impact of these assumptions on their accuracy and speed.
module placement on bsg-structure and ic layout applications. a new method of packing the rectangles (modules) is presented with applications to ic layout design. it is based on the bounded-sliceline grid (bsg) structure. the bsg dissects the plane into rooms associated with binary relations ``right-to''and ``above'' such that any two rooms are uniquely in either relation. a packing is obtained through an assignment of modules on the bsg, followed by physical realization bsg-pack. a simulated annealing searches for a good packing of all packings by changing the assignments. experiments showed that hundreds of rectangles are easily packed in a small rectangle area (chip) with a quite good quality in area efficiency. a wide adaptability is demonstrated specific to ic layout design. remarkable examples are: the chip is not necessarily rectangle, l-shaped modules and modules which are allowed to partially overlap each other can be handled.
channel-driven global routing with consistent placement (extended abstract). a global router with its consistent placer is proposed which aims to control wire-densities of channels. the routing order of nets and their routes are decided according to the channel which is predicted to have the maximum wire-density. the placer distributes the nets evenly with respect to the virtual length (half perimeter of the bounding box). interesting features included are the interactive dynamic test to decide the form of predicting functions and the admissible region to consider the routing resources in placement stage. experiments reveal some interesting phenomena that smaller maximum wire-density is attained in spite of comparable total wire-density and that smaller maximum wire-length in spite of larger total wire-length.
amplification of ultrawideband signals. one of the main implementation challenges in the ultrawide-band(uwb) radio is the design of efficient amplifiers. the difficultyin amplifying an uwb signal stems from its bandwidth beinga large fraction of the amplifier gain-bandwidth product. this paperdescribes a methodology and the tradeoffs associated with thedesign of uwb amplifiers. the amplifiers are designed to minimizea new performance metric, which we refer to as the effectivenoise figure (nf). the effective nf measures the degradationcaused by the amplifier in the achievable receiver performance afterthe digital decoding process, which is ultimately the most relevantmeasure of performance.
reachability analysis using partitioned-robdds. in this paper, we address the problem of finite state machine (fsm) traversal, a key step in most sequential verification and synthesis algorithms. we propose the use of partitioned-robdds to reduce the memory explosion problem associated with symbolic state space exploration techniques. in our technique, the reachable state set is represented as a partitioned-robdd different partitions of the boolean space are allowed to have different variable orderings and only one partition needs to be in memory at any given time. we show the effectiveness of our approach on a set of iscas89 benchmark circuits. our techniques result in a significant reduction in total memory utilization. for a given memory limit, partitioned-robdd based method can complete traversal for many circuits for which monolithic robdds fail. for circuits where both partitioned-robdds as well as monolithic-robdds cannot complete traversal, partitioned-robdds can reach a significantly larger set of states.
static timing analysis for self resetting circuits. static timing analysis techniques are widely used to verify the timing behavior of large digital designs implemented predominantly in conventional static cmos. these techniques, however, are not sufficient to completely verify the dynamic circuit families now finding favor in high-performance designs. in this paper, we describe an approach that extends static timing analysis to a high-performance dynamic cmos logic family called self-resetting cmos. due to the circuit structure employed in srcmos, designs naturally decompose into a hierarchy of gates and macros; timing analysis must address and preferably exploit this hierarchy. at the gate level, three categories of constraints on pulse timing arise from considering the effects of pulse width, overlap, and collisions. timing analysis is performed at the macro level, by a) performing timing tests at macro boundaries and b) using macro-level delay models. we define various macro-level timing tests which ensure that fundamental gate-level timing constraints are satisfied. we extend the standard delay model to handle leading and trailing edges of signal pulses, across-chip variations, tracking of signals, and slow and fast operating conditions. we have developed an srcmos timing analyzer based on this approach; the analyzer was implemented as extensions to a standard static timing analysis program, thus facilitating its integration into an existing design system and methodology.
configuring multiple scan chains for minimum test time. the high test time for serial scan designs can be reduced by the use of multiple scan chains. the problem of optimally constructing multiple scan chains so as to minimize the overall test time is considered. rather than following the traditional practice of using equal length chains, the chains are allowed to be of different lengths; this can lead to lower test times. the main idea of this approach is to assign those scan elements that are more frequently accessed to shorter scan chains. given a design with n scan elements, and given that k scan chains are to be used for applying tests, an algorithm of complexity o(kn2) is presented for configuring the chains such that the overall test application time is minimized. by analyzing a range of circuit topologies, test time reductions as large as 40% over equal length chain configurations are demonstrated
low power logic synthesis for xor based circuits. an abundance of research efforts in low power logic synthesis have so far been focused on and/or or nand/nor based logic. a typical approach is to first generate an initial multi- level and/or or nand/nor representation of a boolean function. next, the representation is optimized in terms of power. however, there are major classes of circuits such as arithmetic functions which have sizable and/or representations but have very compact and/xor representations. for these functions and/or based optimization approach often yields poor results. in this paper, we put forth a paradigm for low power logic synthesis based on and/xor representations of boolean functions. specifically, we propose transforming a boolean function into a fixed polarity reed muller form that allows us to efficiently synthesize xor trees and and trees with provably minimum switching activity. preliminary experimental results show that we attain good power savings with negligible area overhead and often area reduction when compared to conventional and/xor based synthesis methods and the berkeley sis system.
a methodology for the computation of an upper bound on nose current spectrum of cmos switching activity. currents injected by cmos digital circuit blocks into the powergrid and into the substrate of a system-on-a-chip may affect reliabilityand performance of other sensitive circuit blocks. to verify thecorrect operation of the system, an upper bound for the spectrum ofthe noise current has to be provided with respect to all possible transitionsof the circuit inputs. the number of input transitions is exponentialin the number of circuit inputs. in this paper, we present anovel approach for the computation of the upper bound that avoidsthe untractable exhaustive exploration of the entire space. its computationalcomplexity is indeed linear in the number of gates. ourapproach requires cmos standard cell libraries to be characterizedfor injected noise current. in this paper, we also present an approachfor this characterization of cmos standard cells. experimental resultshave proven the accuracy of both the algorithm and the noisecurrent models used for the library characterization.
the care and feeding of your statistical static timer. the integrated circuit fabrication process has inevitable imperfections and fluctuations that had resulted in ever-growing systematic and random variations in the electrical parameters of active and passive devices fabricated as stated in s. nassif (2001). the impact of such variations on various aspects of chip performance has been the subject of numerous recent papers, and techniques for analyzing and dealing with such variability roadly labeled design for manufacturability (dfm) - are emerging from research laboratories to practical implementation and deployment, and several service companies are actively engaged in implementing and promoting dfm techniques amongst semiconductor design and manufacturing organizations.
efficient verification of hazard-freedom in gate-level timed asynchronous circuits. this paper presents an efficient method for verifying hazard freedomin timed asynchronous circuits. timed circuits are a classof asynchronous circuits that utilize explicit timing informationfor optimization throughout the entire design process. in asynchronouscircuits, correct operation requires that there are no hazardsin the circuit implementation. therefore, when designing anasynchronous circuit, each internal node and output of the circuitmust be verified for hazard-freedom to ensure correct operation.current verification algorithms for timed asynchronous circuits requirean explicit state exploration often resulting in state explosionfor even modest sized examples. the goal of this work isto abstract the behavior of internal nodes and utilize this informationto make a conservative determination of hazard-freedom foreach node in the circuit. experimental results indicate that thisapproach is substantially more efficient than existing timing verificationtools. these results also indicate that this method scaleswell for large examples. it is capable of analyzing circuits in lessthan a second that could not be previously analyzed. while thismethod is conservative in that some false hazards may be reported,our results indicate that the number of false hazards is small.
high-level area and power estimation for vlsi circuits. this paper addresses the problem of computing the area complexity of a multi-output combinational logic circuit, given only its functional description, i.e., boolean equations, where area complexity is measured in terms of the number of gates required for an optimal multi-level implementation of the combinational logic. the proposed area model is based on transforming the given multi-output boolean function description into an equivalent single-output function. the model is empirical, and results demonstrating its feasibility and utility are presented. also, a methodology for converting the gate count estimates, obtained from the area model, into capacitance estimates is presented. high-level power estimates based on the total capacitance estimates and average activity estimates are also presented.
placement driven retiming with a coupled edge timing model. retiming is a widely investigated technique for performance optimization. it performs powerful modifications on a circuit netlist. however, often it is not clear, whether the predicted performance improvement will still be valid after placement has been performed. this paper presents a new retiming algorithm using a highly accurate timing model taking into account the effect of retiming on capacitive loads of single wires as well as fanout systems. we propose the integration of retiming into a timing-driven standard cell placement environment based on simulated annealing. retiming is used as an optimization technique throughout the whole placement process. the experimental results show the benefit of the proposed approach. in comparison with the conventional design flow based on standard feas our approach achieved an improvement in cycle time of up to 34% and 17% on the average.
cell replication and redundancy elimination during placement for cycle time optimization. this paper presents a new timing driven approach for cell replication tailored to the practical needs of standard cell layout design. cell replication methods have been studied extensively in the context of generic partitioning problems. however, until now it has remained unclear what practical benefit can be obtained from this concept in a realistic environment for timing driven layout synthesis. therefore, this paper presents a timing driven cell replication procedure, demonstrates its incorporation into a standard cell placement and routing tool and examines its benefit on the final circuit performance in comparison with conventional gate or transistor sizing techniques. furthermore, we demonstrate that cell replication can deteriorate the stuck-at fault testability of circuits and show that stuck-at redundancy elimination must be integrated into the placement procedure. experimental results demonstrate the usefulness of the proposed methodology and suggest that cell replication should be an integral part of the physical design flow complementing traditional gate sizing techniques.
state transformation in event driven explicit simulation. this paper presents a general method for incorporating state transformation in event driven explicit simulation. one inherent assumption in this type of simulation algorithm is the state independence, which allows the algorithm to process the states independently in an event driven manner at the transistor level. numerical problems arise when an inappropriate state representation of the circuit, in which the states are not truly independent, is chosen. in principle, any similarity transformation of the state equation can be employed to transform the circuit into a more convenient state space for numerical solution. this paper develops a systematic scheme to derive an appropriate state transformation, and to incorporate the state transformulation in such a way to maintain the efficiency of event driven explicit simulation algorithms.
transient sensitivity computation for transistor level analysis and tuning. this paper presents a general method for computing transient sensitivities using both the direct and adjoint methods in event driven controlled explicit simulation algorithms that employ piecewise linear device models. this transient sensitivity capability is intended to be used in a simulation environment for transistor level analysis and tuning. results demonstrate the efficiency and accuracy of the proposed techniques. examples are also presented to illustrate how the transient sensitivity capability is used in timing characterization and circuit tuning.
transition-by-transition fsm traversal for reachability analysis in bounded model checking. in bounded model checking (bmc)-based verification flows lack of reachability constraints often leads to false negatives. at present, it is daily practice of a verification engineer to identify the missing reachability constraints by manually inspecting the design code and by analyzing counterexamples. this, unfortunately, requires a lot of effort and is prone to errors. we propose an algorithm to determine reachability constraints automatically. the proposed approach applies to a design style where the operation of the design is controlled by a main fsm which can easily be extracted from the rtl description of the circuit. the algorithm decomposes and analyzes the state space of the circuit by considering transitions of the main fsm. experimental results show that the proposed method can considerably reduce the manual work of verification engineers.
dynamic data-bit memory built-in self- repair. in modern socs, embedded memories occupythe largest part of the chip area and include an evenlarger amount of active devices. as memories aredesigned very tightly to the limits of the technology theyare more prone to failures than logic. thus, theyconcentrate the large majority of defects and affect circuityield dramatically. thus, built-in self-repair is gainingsignificant importance. this work presents a dynamicmemory built-in self-repair schemer acting on the data-bitlevel. it allows reducing the size of the repairable units,or in other words, it allows using a single spare unit forrepairing faults affecting several regular units. as aconsequence, it repairs multiple faults by means of lowhardware cost.
robust automated synthesis methodology for integrated spiral inductors with variability. in order to synthesize spiral inductor designs to meet stringent design requirements, fundamental trade-offs in the design space must be analyzed and exploited. in this paper, we develop a robust automated synthesis methodology to efficiently generate spiral inductor designs using multi-objective optimization techniques and surrogate functions to approximate pareto surfaces in the design space. using our synthesis methodology, we also demonstrate how to reduce the impact of process variation and other sources of modeling error on spiral inductors. our results indicate that our synthesis methodology efficiently optimizes inductor designs based on the application's design requirements with an improvement of up to 51% in key inductor design constraints while reducing the impact of process and model variations.
high capacity and automatic functional extraction tool for industrial vlsi circuit designs. in this paper we present an advanced functional extraction tool for automatic generation of high-level rtl from switch-level circuit netlist representation. the tool is called fev-extract and is part of a comprehensive formal equivalence verification (fev) system developed at intel to verify modern microprocessor designs. fev-extract employs a powerful hierarchical analysis procedure, and advanced and generic algorithms for automatic recognition of logical primitives, to cope with variety of circuit design styles and their complexity. logic equations are then extracted to generate a behavioral rtl model described in industrial standard hdl languages, to be used in the formal equivalence verification, logic simulation, synthesis and testability flows.
exact two-level minimization of hazard-free logic with multiple-input changes. a method for exact hazard-free logic minimization of boolean functions is described. given an incompletely specified boolean function, the method produces a minimal sum-of-products implementation which is hazard-free for a given set of multiple-input changes, if such a solution exists. the method is a constrained version of the quine-mccluskey algorithm. it has been automated and applied to a number of examples. results are compared with results of a comparable non-hazard-free method (espresso-exact). overhead due to hazard elimination is shown to be negligible
prima: passive reduced-order interconnect macromodeling algorithm. this paper describes prima, an algorithm for generating provably passive reduced order n-port models for rlc interconnect circuits. it is demonstrated that, in addition to requiring macromodel stability, macromodel passivity is needed to guarantee the overall circuit stability once the active and passive driver/load models are connected. prima extends the block arnoldi technique to include guaranteed passivity. moreover, it is empirically observed that the accuracy is superior to existing block arnoldi methods. while the same passivity extension is not possible for mpvl, we observed comparable accuracy in the frequency domain for all examples considered. additionally a path tracing algorithm is used to calculate the reduced order macromodel with the utmost efficiency for generalized rlc interconnects.
practical considerations for passive reduction of rlc circuits. krylov space methods initiated a new era for rlc circuit model order reduction. although theoretically well-founded, these algorithms can fail to produce useful results for some types of circuits. in particular, controlling accuracy and ensuring passivity are required to fully utilize these algorithms in practice. in this paper we propose a methodology for passive reduction of rlc circuits based on extensions of prima, that is both broad and practical. this work is made possible by uncovering the algebraic connections between this passive model order reduction algorithm and other krylov space methods. in addition, a convergence criteria based on an error measure for prima is presented as a first step towards intelligent order selection schemes. with these extensions and error criterion, examples demonstrate that accurate approximations are possible well into the rf frequency range even with expansions about s=0.
application-specific network-on-chip architecture customization via long-range link insertion. networks-on-chip (nocs) represent a promising solution to complex on-chip communication problems. the noc communication architectures considered so far are based on either completely regular or fully customized topologies. in this paper, we present a methodology to automatically synthesize an architecture where a few application-specific long-range links are inserted on top of a regular mesh network. this way, we can better exploit the benefits of both complete regularity and partial customization. indeed, our experimental results show that inserting application-specific long-range links significantly increases the critical traffic workload at which the network state transits from a free to a congested regime. this, in turn, results in a significant reduction in the average packet latency and a major improvement in the network achievable throughput.
fast seed computation for reseeding shift register in test pattern compression. solving a system of linear equations has been widely used to compute seeds for lfsr reseeding to compress test patterns. however, as chip size is growing, solving linear equations requires a large number of computations that is proportional to n3. this paper proposes a new scan chain architecture and algorithm so that the order of computation is proportional to the number of scan cells in a chip. the new architecture is a methodology change that does not require complex design-for-testability (dft) as proposed in the previous techniques. instead of solving linear equations, the proposed new seed computation algorithm topologically determines seeds for test vectors. the compression ratio might be slightly lower than the other approaches, but the proposed approach can handle larger designs in a reasonable amount of time. computation analysis shows that, for 1 million scan cell design, if we assume it takes 1 msec for the proposed technique to compute seeds, it would take more than 14 minutes for other techniques that solve linear equations.
comprehensive lower bound estimation from behavioral descriptions. in this paper, we present a comprehensive technique for lower bound estimation (lbe) of resources from behavioral descriptions. previous work has focused on lbe techniques that use very simple cost models which primarily focus on the functional unit resources. our cost model accounts for storage resources in addition to functional resources. our timing model uses a finer granularity that permits the modeling of functional unit, register and interconnect delays. we tested our lbe technique for both functional unit and storage requirements on several high-level synthesis benchmarks and observed near-optimal results.
a statistical gate-delay model considering intra-gate variability. this paper proposes a model for calculating statistical gate-delayvariation caused by intra-chip and inter-chip variability. as thevariation of individual gate delays directly influences the circuit-delayvariation, it is important to characterize each gate-delay variationaccurately. furthermore, as every transistor in a gate affectsthe transient characteristics of the gate, it is also necessary to considerthe intra-gate variability in the model of gate-delay variation.this effect is not captured in existing statistical delay analyses. theproposed model considers the intra-gate variability through the introductionof sensitivity constants. the accuracy of the model isevaluated, and some simulation results for circuit delay variationare presented.
buffered steiner tree construction with wire sizing for interconnect layout optimization. this paper presents an efficient algorithm for buffered steiner tree construction with wire sizing. given a source and n sinks of a signal net, with given positions and a required arrival time associated with each sink, the algorithm finds a steiner tree with buffer insertion and wire sizing so that the required arrival time (or timing slack) at the source is maximized. the unique contribution of our algorithm is that it performs steiner tree construction, buffer insertion, and wire sizing simultaneously with consideration of both critical delay and total capacitance minimization by combining the performance-driven a-tree construction and dynamic programming based buffer insertion and wire sizing, while tree construction and the other delay minimization techniques were carried out independently in the past. experimental results show the effectiveness of our approach.
an exact gate assignment algorithm for tree circuits under rise and fall delays. in most libraries, gate parameters such as the pin-to-pin intrinsic delays, load-dependent coefficients, and input pin capacitances have different values for rising and falling signals. the performance optimization algorithms, however, assume a single value for each parameter.it is known that under the load-independent delay model, the gate assignment (or resizing) problem is solvable in time polynomial in the circuit size when a single value is assumed for each parameter [5]. in the presence of different rise and fall parameter values, this problem was recently shown to be np-complete even for chain and tree topology circuits under the simple load-independent delay model [8]. in this paper, we propose a dynamic programming algorithm for solving this problem exactly in pseudo-polynomial time for tree circuits. more specifically, we show that the problem can be solved in time proportional to the size of the tree circuit, the number of choices available in the library for each gate, and the delay of the circuit. to the best of our knowledge, this is the first pseudo-polynomial exact algorithm for the gate assignment problem for trees in the presence of different rise and fall delays. we present a straightforward way of extending this algorithm to general directed acyclic graphs. we present experimental results on a set of benchmark problems using a standard commercial library and show that our algorithm generates provably optimum delays for 72 out of 76 circuits. we also compare our technique with two approaches traditionally used to solve this problem in the industry & academia and show that it is slightly better than these two. interestingly, both traditional approaches also yield delays not far from the optimum.
a flexibility aware budgeting for hierarchical flow timing closure. we present a new block budgeting algorithm which speeds up timing closure in timing driven hierarchical flows. after a brief description of the addressed flow, block budgeting challenges are detailed. then, we explain why existing budgeting approaches are not adapted to fulfil these challenges. a new block budgeting algorithm is proposed. in order to derive relevant block constraints, this algorithm analyzes the design flexibility. this flexibility aware budgeting (fab) approach is then compared to some previous ones. experiments based on commercial eda tools and real designs show up to 55 % reduction in hierarchical flow run time and lead to a good flow timing closure.
impact of systematic spatial intra-chip gate length variability on performance of high-speed digital circuits. using data collected from an actual state-of-the-art fabrication facility, we conducted a comprehensive characterization of an advanced 0.18&mu;m cmos process. the measured data revealed significant systematic, rather than random, spatial intra-chip variability of mos gate length, leading to large circuit path delay variation. the critical path value of a combinational logic block varies by as much as 17%, and the global skew is increased by 8%. thus, a significant timing error (&sim;25%) and performance loss takes place if variability is not properly addressed. we derive a model, which allows estimating performance degradation for the given circuit and process parameters. analysis shows that the spatial, rather than proximity-dependent, systematic lgate variability is the main cause of large circuit speed degradation. the degradation is worse for the circuits with a larger number of critical paths and shorter average logic depth. we propose a location-dependent timing analysis methodology that allows to mitigate the detrimental effects of lgate variability, and developed a tool linking the layout-dependent spatial information to circuit analysis. we discuss the details of the practical implementation of the methodology, and provide the guidelines for managing the design complexity.
moment-based power estimation in very deep submicron technologies. the significant power optimization possibilities in the early stagesof the design flow advice the use of energy evaluation techniquesat high levels of abstraction. with this aim, the present work addressesthe estimation of the energy consumption in very deep submicrontechnologies. using the characterization of the probabilitydensity function with a projection in an orthogonal polynomialbase, and a symbolic propagation mechanism, a technique is presentedto estimate the dynamic and static power consumption indigital systems. the proposed approach has been validated withcircuits and excitations from realistic applications. comparisonswith reference transistor and bit level simulations are reported inorder to asses the the accuracy of the technique.
length-matching routing for high-speed printed circuit boards. as the clock frequencies used in industrial applications increase,the timing requirements imposed on routing problems becometighter. so, it becomes important to route the nets within tight minimumand maximum length bounds. although the problem of routingnets to satisfy maximum length constraints is a well-studiedproblem, there exists no sophisticated algorithm in the literaturethat ensures that minimum length constraints are also satisfied. inthis paper, we propose a novel algorithm that effectively incorporatesthe min-max length constraints into the routing problem. ourapproach is to use a lagrangian relaxation framework to allocateextra routing resources around nets simultaneously during routingthem. we also propose a graph model that ensures that all theallocated routing resources can be used effectively for extendinglengths. our routing algorithm automatically prioritizes resourceallocation for shorter nets, and length minimization for longer netsso that all nets can satisfy their min-max length constraints. ourexperiments demonstrate that this algorithm is effective even in thecases where length constraints are tight, and the layout is dense.
simultaneous escape routing and layer assignment for dense pcbs. as die sizes are shrinking, and circuit complexities are increasing, the pcb routing problem becomes more and more challenging. traditional routing algorithms can not handle these challenges effectively, and many high-end designs in the industry require manual routing efforts. in this paper, we propose a problem decomposition that distinguishes routing within dense components from routing in the intermediate area. in particular, we propose an effective methodology to find the escape routing solution for multiple components simultaneously such that the number of crossings in the intermediate area is minimized. for this, we model the problem as a longest path with forbidden pairs (lpfp) problem, and propose two algorithms for it. the first is an exact polynomial-time algorithm that is guaranteed to find the maximal planar routing solution on one layer. the second is a randomized algorithm that has good scalability characteristics for large circuits. then we use these algorithms to assign the maximal subset of planar nets to each layer, and then distribute the remaining nets at the end. we demonstrate the effectiveness of these algorithms through experiments on industrial circuits.
a provably good algorithm for high performance bus routing. as the clock frequencies used in industrial applications increase, the timing requirements on routing problems become tighter, and current routing tools can not successfully handle these constraints any more. we focus on the high-performance single-layer bus routing problem, where the objective is to match the lengths of all nets belonging to each bus. an effective approach to solve this problem is to allocate extra routing resources around short nets during routing; and use those resources for length extension afterwards. we first propose a provably optimal algorithm for routing nets with min-area max-length constraints. then, we extend this algorithm to the case where minimum constraints are given as exact length bounds. we also prove that this algorithm is optimal within a constant factor. both algorithms proposed are also shown to be scalable for large circuits, since the respective time complexities are o(a) and o(a log a), where a is the area of the intermediate region between chips.
an escape routing framework for dense boards with high-speed design constraints. shrinking transistor sizes, increasing circuit complexities, and high clock frequencies bring new board routing challenges that cannot be handled effectively by traditional routing algorithms. many high-end designs in the industry today require manual routing efforts, which increases the design cycle times considerably. in this paper, we propose an escape routing algorithm to route nets within multiple dense components simultaneously so that the number of crossings in the intermediate area is minimized. we also show how to handle high-speed design constraints within the framework of this algorithm. experimental comparisons with a recently proposed algorithm (ozdal and wong, 2004) show that our algorithm reduces the via requirements of industrial test cases on average by 39%.
optimal routing algorithms for pin clusters in high-density multichip modules. optimal routing algorithms for pin clusters in high-density multichip modules as the circuit densities and transistor counts are increasing, the package routing problem is becoming more and more challenging. in this paper, we study an important routing problem encountered in typical high-end mcm designs: routing within dense pin clusters. pin clusters are often formed by pins that belong to the same functional unit or the same data bus, and can become bottlenecks in terms of overall routability. topically, these clusters have irregular shapes, which can be approximated with rectilinear convex boundaries. since such boundaries have often irregular shapes, a traditional escape routing algorithm may give unroutable solutions. in this paper, we study how the positions of escape terminals on a convex boundary affect the overall routability. for this purpose, we propose a set of necessary and sufficient conditions to model routability outside a rectilinear convex boundary. given an escape routing solution, we propose an optimal algorithm to select the maximal subset of nets that are routable outside the boundary. after that, we focus on an integrated approach to consider routability constraints (outside the boundary) during the actual escape routing algorithm. here, we propose an optimal algorithm to find the best escape routing solution that satisfies all routability constraints. our experiments demonstrate that we can reduce the number of layers by 17% on the average, by using this integrated methodology.
a local circuit topology for inductive parasitics. a novel circuit topology for inductive coupling between interconnecting wires is presented. the model is local, i.e., only coupling between neighboring wires is explicitly modeled. however, the topology accounts for long-range coupling by propagating the vector potential from one wire to the next. examples of model calibration, both directly from layout and as model-order reduction of a given inductance matrix, are presented for simple wiring structures.
analytic modeling of interconnects for deep sub-micron circuits. closed form equations for second order transfer functions of generalarbitrarily-coupled rc trees with multiple drivers are reported.the models allow precise delay and noise calculations for systemsof coupled interconnects with guaranteed stability, and representthe minimum complexity associated with this class of circuits. thesimplicity, accuracy and generality of the models make them suitablefor use in early delay and noise planning of global signals incomplex systems.
pseudo-random testing and signature analysis for mixed-signal circuits. in this paper, we address the problem of functional testing of mixed-signal circuits using pseudo-random patterns. by embedding the linear, time-invariant (lti) analog circuit between a digital-to-analog converter (dac) and an analog-to-digital converter (adc), we can model the analog and converter circuitry as a digital lti system and test it using the pseudo-random vectors. we give mathematical analysis and formulate the pseudo-random testing process as the linear transformation of a random process by the analog lti device under test (dut). we choose the first and the second moments of the transformed random process, which are closely related to the functionality of the dut, as the signatures for fault detection. we show that such signatures can be estimated by proper arithmetic operations on the output responses of the dut to the vectors generated by lfsrs. we illustrate and compare the effectiveness of several possible choices of signatures, through analysis and experimental results of several circuits, in terms of their fault detection capabilities and the testing hardware requirements.
a comprehensive fault macromodel for opamps. in this paper, a comprehensive macromodel for transistor level faults in an operational amplifier is developed. with the observation that faulty behavior at output may result from interfacing error in addition to the faulty component, parameters associated with input and output characteristics are incorporated. test generation and fault classification are addressed for stand-alone opamps. a high fault coverage is achieved by a proposed testing strategy. transistor level short/bridging faults are analyzed and classified into catastrophic faults and parametric faults. based on the macromodels for parametric faults, faults simulation is performed for an active filter. we found many parametric faults in the active filter cannot be detected by traditional functional testing. a dft scheme alone with a current testing strategy to improve fault coverage is proposed.
area minimization for general floorplans. two methods for the area minimization problem in floorplanning are presented. these methods can be viewed as generalizations of stockmeyer's algorithm in the sense that they reduce to stockmeyer's algorithm for floorplans that are slicing. the present methods can also be applied to general floorplans. compared with the branch-and-bound algorithm, which is enumerative in nature and does not have any nontrivial performance bound for general floorplans, these methods are probably better than exhaustive methods for all the floorplans studied
area minimization for hierarchical floorplans. two results are presented in this paper. first we settle the open problem on the complexity of the area minimization problem for hierarchical floorplans by showing it to be n p-complete. we then present a pseudo-polynomial area minimization algorithm for hierarchical floorplans of order-5. the algorithm is based on a new algorithm for determining the set of nonredundant realizations of a wheel. the new algorithm for wheels has time cost o(k2logk) and space cost o(k2) if each of the (five) blocks in a wheel has at mostkrealizations&mdash;a reduction by a factor of k in both costs in comparison with previous algorithms. the area minimization algorithm was implemented. our experimental results show that the algorithm is indeed very fast.
an efficient and effective detailed placement algorithm. in the past few years, there has been a lot of research in the area of global placement. in comparison, not much attention has been paid to the detailed placement problem. existing detailed placers either fail to improve upon the excellent solution quality enabled by good global placers or are very slow. to handle the above problems, we focus on the detailed placement problem. we present an efficient and effective detailed placement algorithm to handle the wirelength minimization problem. the main contributions of our work are: (1) an efficient global swap technique to identify a pair of cells that can be swapped to reduce wirelength; (2) a flow that combines the global swap technique with other heuristics to produce very good wirelength; (3) an efficient single-segment clustering technique to optimally shift cells within a segment to minimize wirelength. on legalized mpl5 global placements on the ibm standard-cell benchmarks, our detailed placer can achieve 19.0%, 13.2% and 0.5% more wirelength reduction compared to fengshui5.0, rowironing and domino respectively. correspondingly we are 3.6/spl times/ 2.8/spl times/ and 15/spl times/ faster. on the ispd05 benchmarks (gi-joon nam et al., 2005), we achieve 8.1% and 9.1% more wirelength reduction compared to fengshui5.0 and rowironing respectively. correspondingly we are 3.1/spl times/ and 2.3/spl times/ faster.
memory bank customization and assignment in behavioral synthesis. with increasing design complexity and chip area, on-chip memory has become an important component whose integration needs to be addressed during system design. modern embedded dram technology allows for large amounts of on-chip memory space. however, in order to utilize the available memory intelligently, the memory has to be appropriately customized for the specific application. we address the topic of incorporating the application-specific customization of memory bank configuration into behavioral synthesis. the strategy involves a partitioning of behavioral arrays into memory banks based on a cost function that estimates the performance implications. for a given candidate partition, we present a heuristic for determining the access sequence that minimizes page misses in a bank while respecting data dependences. the output of the exploration is a graph displaying the variation of delay and memory area with the bank configuration. our experiments on several memory-intensive examples confirm that the exploration results can provide critical feedback to the designer about the optimal memory configuration for a given application.
an energy-conscious algorithm for memory port allocation. multiport memories are extensively used in modern system designs because of the performance advantages they offer. the increased memory access throughput could lead to significantly faster schedules in behavioral synthesis. however, they also have an associated area and energy penalty. we describe a technique for mapping data accesses to multiport memories during behavioral synthesis that results in significantly better energy characteristics than an unoptimized multiport design. the technique consists of an initial colouring of the array access nodes in the data flow graph based on spatial locality, followed by attempts to consecutively access memory locations with the same colour on the same port. our experiments on several applications indicate a significant reduction in address bus switching activity, leading to an overall energy reduction over an unoptimized design, while still maintaining a performance advantage over a single-port solution.
exploiting off-chip memory access modes in high-level synthesis. memory-intensive behaviors often contain large arrays that are synthesized into off-chip memories. with the increasing gap between on-chip and off-chip memory access delays, it is imperative to exploit the efficient access mode features of modern-day memories (e.g., page-mode drams) in order to alleviate the memory bandwidth bottleneck. our work addresses this issue by: (a) modeling realistic off-chip memory access modes for high-level synthesis (hls), (b) presenting algorithms to infer applicability of hls with these memory access modes, and (c) transforming input behavior to provide further memory access optimizations during hls. we demonstrate the utility of our approach using a suite of memory-intensive benchmarks with a realistic dram library module. experimental results show a significant performance improvement (more than 40\%) as a result of our optimization techniques.
who are the variables in your neighborhood. dynamic reordering techniques have had considerable success in reducing the impact of the initial variable order on the size of decision diagrams. sifting, in particular, has emerged as a very good compromise between low cpu time requirements and high quality of results. sifting, however, has the absolute position of a variable as the primary objective, and only considers the relative positions of groups of variables indirectly. in this paper we propose an extension to sifting that may move groups of variables simultaneously to produce better results. variables are aggregated by checking whether they have a strong affinity to their neighbors. (hence the title.) our experiments show an average improvement in size of 11%. this improvement, coupled with the greater robustness of the algorithm, more than offsets the modest increase in cpu time that is sometimes incurred.
symmetry detection and dynamic variable ordering of decision diagrams. knowing that some variables are symmetric in a function has numerous applications; in particular, it can help produce better variable orders for binary decision diagrams (bdds) and related data structures (e.g., algebraic decision diagrams). it has been conjectured that there always exists an optimum order for a bbd wherein symmetric variables are contiguous. we propose a new algorithm for the detection of symmetries, based on dynamic reordering, and we study its interaction with the reordering algorithm itself. we show that combining sifting with an efficient symmetry check for contiguous variables results in the fastest symmetry detection algorithm reported to date and produces better variable orders for many bdds. the overhead on the sifting algorithm is negligible.
static timing analysis considering power supply variations. power supply integrity verification has become a key concern in high performance designs. in deep submicron technologies, power supply noise can significantly increase the circuit delay and lead to performance failures. traditional static timing analysis which applies worst-case voltage margins to compute circuit delay leads to a very conservative analysis because the worst-case drop is localized to a small area of the die. in this paper, we propose a new approach for analyzing the impact of power supply variations on circuit delay. the circuit delay maximization problem is formulated as a constrained non-linear optimization problem which takes both ir and ldi/dt drops into account the proposed approach does not require apriori knowledge of critical paths in the circuit and can be effectively incorporated in an existing static timing analysis framework. the proposed method has been implemented and tested on iscas85 benchmark circuits and compared with the traditional methods for computing worst-case circuit delay under supply variations.
vectorless analysis of supply noise induced delay variation. the impact of power supply integrity on a design has become acritical issue, not only for functional verification, but also for performanceverification. traditional analysis has typically applied a worstcase voltage drop at all points along a circuit path which leads to avery conservative analysis. we also show that in certain cases, thetraditional analysis can be optimistic, since it ignores the possibilityof voltage shifts between driver and receiver gates. in this paper, wepropose a new analysis approach for computing the maximum pathdelay under power supply fluctuations. our analysis is based on theuse of superposition, both spatially across different circuit blocks,and temporally in time. we first present an accurate model of pathdelay variations under supply drops, considering both the effect oflocal supply reduction at individual gates and voltage shifts betweendriver/receiver pairs. we then formulate the path delay maximizationproblem as a constrained linear optimization problem, consideringthe effect of both ir drop and ldi/dt drops. we show how correlationsbetween currents of different circuit blocks can be incorporatedin this formulation using linear constraints. the proposed methodswere implemented and tested on benchmark circuits, including anindustrial power supply grid and we demonstrate a significantimprovement in the worst-case path delay increase.
efficient diagnosis of path delay faults in digital logic circuits. a new methodology involving effect-cause analysis has been demonstrated for the diagnosis of path delay faults. we seek to provide an improved understanding of the methods introduced in [6], with the goal of devising efficient representations and algorithms for the diagnosis of path delay faults. results indicate that the diagnostic resolution obtained is very high and includes all possible causes of the observed delay faults.
a test synthesis technique using redundant register transfers. this paper presents a test synthesis technique for behavioral descriptions. the technique is guided by two testability metrics which quantify the controllability and observability of behavioral variables and structural signals. the method is based on utilizing redundant register transfers in the data path to produce a test behavior with better controllability and observability properties. this approach can avoid unnecessary insertions of test structures in the data path. a test scheme for conditional statements has been developed involving minimal changes in the controller. our experimental results show improvements in fault coverage at modest hardware overhead.
i-copes: fast instruction code placement for embedded systems to improve performance and energy efficiency. the ratio of cache hits to cache misses in a computer system is, to a large extent, responsible for its characteristics such as energy consumption and performance. in recent years energy efficiency has become one of the dominating design constraints, due to the rapid growth in market share for mobile computing/communication/internet devices.in this paper we present a novel fast constructive technique that relocates the instruction code in such a manner into the main memory that the cache is utilized more efficiently. the technique is applied as a pre-processing step, i.e. before the code is executed. it is applicable for embedded systems where the number and characteristics of tasks running on the system is know a priori. the technique does not impose any computational overhead to the system. as a result of applying our technique to a variety of real-world applications we measured (through simulation) that the number of cache misses drops significantly. further, this reduces the energy consumption of a whole system (cpu, caches, buses, main memory) by up to 65% at an only slightly increased memory size of 13% on average.
fast cycle-accurate behavioral simulation for pipelined processors using early pipeline evaluation. modeling and simulating pipelined processors in procedurallanguages such as c/c++ requires lots of cost in handlingconcurrent events, which hinders fast simulation. a number ofresearches on simulation have devised speed-up techniques toreduce the number of events. this paper presents a newsimulation approach developed to enhance the simulation ofpipelined processors. the proposed approach is based on earlypipeline evaluation that all the intermediate values of aninstruction are computed in advance, creating a future state for thenext instructions. the future state allows the next instructions tobe computed without considering data dependencies betweennearby instructions. we apply this concept to building a cycle-accurate simulator for a pipelined risc processor and achieve almost the same speed as the instruction-level simulator.
rtl sat simplification by boolean and interval arithmetic reasoning. we present a method that combines interval-arithmetic (ia) and boolean reasoning with structural hashing for simplifying sat problems on circuits expressed at the register-transfer level. we demonstrate that simple transformations based on interval-arithmetic operations can significantly reduce the complexity of the problem. we identify cases where the inherent over-approximations in ia operations can be reduced. we demonstrate that these techniques can significantly reduce rtl-sat instances in size and runtime.
convertibility verification and converter synthesis: two faces of the same coin. an essential problem in component-based design is how to compose components designed in isolation. several approaches have been proposed for specifying component interfaces that capture behavioral aspects such as interaction protocols, and for verifying interface compatibility. likewise, several approaches have been developed for synthesizing converters between incompatible protocols. in this paper, we introduce the notion of adaptability as the property that two interfaces have when they can be made compatible by communicating through a converter that meets specified requirements. we show that verifying adaptability and synthesizing an appropriate converter are two faces of the same coin: adaptability can be formalized and solved using a game-theoretic framework, and then the converter can be synthesized as a strategy that always wins the game. finally we show that this framework can be related to the rectification problem in trace theory.
push-up scheduling: optimal polynomial-time resource constrained scheduling for multi-dimensional applications. multi-dimensional computing applications, such as image processing and fluid dynamics, usually contain repetitive groups of operations represented by nested loops. the optimization of such loops, considering processing resource constraints, is required to improve their computational time. this study presents a new technique, called push-up scheduling, able to achieve the shortest possible schedule length in polynomial time. such technique transforms a multi-dimensional data flow graph representing the problem, while assigning the loop operations to a schedule table in such a way to occupy, legally, any empty spot. the algorithm runs in o(n|e|) time, where n is the number of dimensions of the problem, and |e| is the number of edges in the graph.
reducing cache misses by application-specific re-configurable indexing. the predictability of memory access patterns in embedded systems can be successfully exploited to devise effective application-specific cache optimizations. in this work, we propose an improved indexing scheme for direct-mapped caches, which drastically reduces the number of conflict misses by using application-specific information; the scheme is based on the selection of a subset of the address bits. with respect to similar approaches, our solution has two main strengths. first, it models the misses analytically by building a miss equation, and exploits a symbolic algorithm to compute the exact optimum solution (i.e., the subset of address bits to be used as cache index that minimizes conflict misses). second, we designed a re-configurable bit selector, which can be programmed at run-time to fit the optimal cache indexing to a given application. results show an average reduction of conflict misses of 24%, measured over a set of standard benchmarks, and for different cache configurations.
statistical behavioral modeling and characterization of a/d converters. this paper presents a method to characterize nyquist rate a/d converters based on the use of a first order statistical behavioral model. the proposed model is derived from a very basic statistical interpretation of the conversion operation which contemplates noise and statistical process variations effects on traditional converter parameters. both dc and dynamic converter parameters can be easily measured. the applicability of the proposed method is illustrated with two different examples. the first serves to show the possibility of deriving the statistical behavioral model from real measured data, and to prove the correctness of the model by comparing results to those obtained with traditional deterministic models. the second example illustrates the incorporation of the model in the mixed-signal simulator eldo [6]. the obtained results show that despite the model's simplicity, it is very efficient for quick and complete simulation of data converters.
compiler-based register name adjustment for low-power embedded processors. we present an algorithm for compiler-driven register name adjustmentwith the main goal of power minimization on instruction fetchand register file access. in most instruction set architecture (isa) designs,the register fields reside in fixed positions within the instructionencoding, hence forming streams of indices on the instruction bus andto the register file address decoder. the number of bit transitions inthese streams greatly determines the power consumption on the addressbus and the register file decoder. while general-purpose registersare semantically indistinguishable and hence interchangeable,the particular register indices do have a direct impact on power consumption.the algorithms presented in this paper address this powerminimization problem by reassigning/encoding the registers so thatthe bit transitions within the register index streams are minimized.
symbolic algebra and timing driven data-flow synthesis. the growing market of multi-media applications has required the development of complex asics with significant data-path portions. unfortunately, most high-level synthesis tools and methods cannot automatically synthesize data paths such that complex arithmetic library blocks are intelligently used. symbolic computer algebra has been previously used to automate mapping data flow into a minimal set of complex arithmetic components. in this paper, we present extensions to the previous methods in order to find the minimal critical path delay (cpd) mapping. a new algorithm is proposed that incorporates symbolic manipulations such as tree-height-reduction, factorization, expansion, and horner transformation. such manipulations are used as guidelines in initial library element selection. furthermore, we demonstrate how substitution can be used for multi-expression component sharing and critical path delay optimization.
simultaneous design and placement of multiplexed chemical processing systems on microchips. microchip structures represent an attractive platform for microscale chemical processing of fluidic systems. however, standardized design methods for these devices have not yet been developed. here we describe our work toward adapting traditional soc circuit design techniques for the synthesis of fully customized and multiplexed lab-on-a-chip (loc) devices. we discuss our formulation of the multiplex layout problem and present an approach for the design of microchip based electrophoretic separation systems. this work is extendable to systems incorporating mixing and reaction.
variational interconnect analysis via pmtbr. we demonstrate an algorithm for interconnect modeling in the presence of process variation based on extension of the truncated balanced realization model reduction algorithm to multi-dimensional, parameter varying systems. our scheme, based on a set of estimators of the variational tbr projection spaces, is simple to implement, contains embedded error estimators, and leads to nearly optimally sized models.
analog macromodeling using kernel methods. in this paper we explore the potential of using a general class offunctional representation techniques, kernel-based regression, inthe nonlinear model reduction problem. the kernel-based view-pointprovides a convenient computational framework for regression,unifying and extending the previously proposed polynomialand piecewise-linear reduction methods. furthermore, as many familiarmethods for linear system manipulation can be leveraged ina nonlinear context, kernels provide insight into how new, morepowerful, nonlinear modeling strategies can be constructed. wepresent an svd-like technique for automatic compression of non-linearmodels that allows systematic identification of model redundanciesand rigorous control of approximation error.
simulation approaches for strongly coupled interconnect systems. shrinking feature sizes and increasing speeds of operation make interconnect-related effects very relevant for current circuit verification methodologies. reliable and accurate system verification requires the full analysis of circuits together with the environment that surrounds them, including the common substrate, the packaging structures, and perhaps even board information. in this paper we discuss circuit-level simulation algorithms that enable the analysis of the impact of strongly coupled interconnect structures on nonlinear circuit operation, so as to allow reliable and accurate system verification.
a precorrected-fft method for capacitance extraction of complicated 3-d structures. in this paper we present a new approach to three-dimensional capacitance extraction based on a precorrected fft scheme. the approach is compared to the now commonly used multipole-accelerated algorithms for a variety of structures, and the new method is shown to have substantial performance and memory advantages.
coping with rc(l) interconnect design headaches. physical interconnect effects have a dominant impact on today's deep submicron ic designs. in this tutorial paper we will describe the technology trends which have brought about this interconnect dominance, then consider some of the modeling and analysis approximations available for both pre- and post-layout interconnect design. this coverage will not be an exhaustive summary, but one that is primarily focused on moment-based analysis techniques, from the elmore delay, to the more recent advances in moment-matching approximations, and the corresponding nonlinear driver/load interfaces. future modeling, analysis, and design challenges will be considered throughout this paper.
multi-level synthesis for safe replaceability. we describe the condition that a sequential digital design is a safe replacement for an existing design without making any assumptions about a known initial state of the design or about its environment. we formulate a safe replacement condition which guarantees that if an original design is replaced by a new design, the interacting environment cannot detect the change by observing the input-output behavior of the new design; conversely, if a replacement design does not satisfy our condition an environment can potentially detect the replacement (in this sense the replacement is potentially unsafe). our condition allows simplification of the state transition diagram of an original design. we use the safe replacement condition to derive a sequential resynthesis method for area reduction of gate-level designs. we have implemented our resynthesis algorithm and we report experimental results.
simulation based test generation for scan designs. we describe a simulation-based test generation procedure for scan designs. a test sequence generated by this procedure consists of a sequence of one or more primary input vectors embedded between a scan-in operation and a scan-out operation. we consider the set of faults that can be detected by test sequences of this form, compared to the case where scan is applied with every test vector. the proposed procedure constructs test sequences that traverse as many pairs of fault-free/faulty states as possible, and thus avoids the use of branch-and-bound test generation techniques. additional techniques are incorporated into this basic procedure to enhance its effectiveness.
on undetectable faults in partial scan circuits. we provide a definition of undetectable faults in partial scan circuits under a test application scheme where a test consists of primary input vectors applied at-speed between scan operations. we also provide sufficient conditions for a fault to be undetectable under this test application scheme. we present experimental results on finite-state machine benchmarks to demonstrate the effectiveness of these conditions in identifying undetectable faults.
on application of output masking to undetectable faults in synchronous sequential circuits with design-for-testability logic. design-for-testability (dft ) for synchronous sequentialcircuits causes redundant faults in the original circuit to bedetectable in the circuit with dft logic. it has beenargued that such faults should not be detected in order toavoid reducing the yield unnecessarily. one way to dealwith such faults is to mask (or ignore) their fault effectswhen they appear on the circuit outputs, without maskingthe detection of faults that need to be detected. to investigatethe extent to which this can be accomplished, wedescribe a procedure for masking the effects of redundantfaults of the original circuit under a given test set generatedfor the circuit with dft logic. the procedureattempts to maximize the number of redundant faults thatare masked while minimizing (or holding to zero) thenumber of other masked faults.
on the generation of small dictionaries for fault location. fault location based on a fault dictionary is considered. to justify the use of a precomputed dictionary in terms of computation time, the computational effort invested in computing a dictionary is first analyzed. the number of circuit diagnoses that need to be performed dynamically, without the use of precomputed knowledge, before the overall effort exceeds the effort of computing a dictionary, is studied. experimental results on iscas-85 circuits show that for relatively small numbers of diagnoses, a precomputed dictionary is more efficient. a method to derive small dictionaries without losing resolution of modeled faults is then proposed. methods to compact the resulting dictionary further, using compaction techniques generally applied to fault detection, are then described. experimental results to demonstrate the effectiveness of the methods are presented. internal observation points to increase the resolution of the test set are also considered
an efficient non-enumerative method to estimate path delay fault coverage. a method for estimating the coverage of path delay faults of a given test set, without enumerating paths, is proposed. the method is polynomial in the number of lines in the circuit, and thus allows circuits with large numbers of paths to be considered under the path delay fault model. several levels of approximation, with increasing accuracy and increasing polynomial complexity, are proposed. experimental results to show the effectiveness and accuracy of the estimate in evaluating the path delay fault coverage are presented. combining this nonenumerative estimation method with a test generation method for path delay faults would yield a cost effective method to consider path delay faults in large circuits, which are beyond the capabilities of existing test generation and fault simulation procedures that are based on enumeration of paths
on testing delay faults in macro-based combinational circuits. we consider the problem of testing for delay faults in macro-based circuits. macro-based circuits are obtained as a result of technology mapping. gate-level fault models cannot be used for such circuits, since the implementation of a macro may not have an accurate gate-level counterpart, or the macro implementation may not be known. two delay fault models are proposed for macro-based circuits. the first model is analogous to the gate-level gross delay fault model. the second model is analogous to the gate-level path delay fault model. we provide fault simulation procedures, and present experimental results.
on error correction in macro-based circuits. we consider the problem of correcting errors in a macro-based circuit. our formulation of the problem allows the correction of errors that arise both in the context of design error correction, before the circuit is realized, and in the context where a physical circuit needs to be corrected. two error classes are defined, namely, component errors and line errors. both single and multiple errors are considered. accurate correction procedures are given for single errors. heuristics are given for correcting multiple errors. experimental results are given to demonstrate the correction procedures presented.
functional test generation for delay faults in combinational circuits. we propose a functional fault model for delay faults in combinational circuits and describe a functional test generation procedure based on this model. the proposed method is most suitable when a gate-level description of the circuit-under-test, necessary for employing existing gate-level delay fault test generators, is not available or does not accurately describe the circuit. it is also suitable for generating tests in early design stages of a circuit, before a gate-level implementation is selected. in addition, it can potentially be employed to supplement conventional test generators for gate-level circuits to reduce the cost of handling large numbers of paths. a parameter called &dgr; is used to control the number of funtional faults targeted and thus the number of tests generated. if &dgr; is unlimited, the functional test set detects every robustly testable path delay fault in any gate-level implementation of the given ciruit. an appropriate subset of tests can be selected once the implentation is known. the test sets generated for various values of &dgr; are fault simulated on gate-level realizations to demonstrate their effectiveness. the experiments indicate that functional test sets may be able to identify functions whose realizations have low path delay fault coverage.
built-in test generation for synchronous sequential circuits. we consider the problem of built-in test generation for synchronous sequential circuits. the proposed scheme leaves the circuit flip-flops unmodified, and thus allows at-speed test application. we introduce a uniform, parametrized structure for test pattern generation. by matching the parameters of the test pattern generator to the circuit-under-test, high fault coverage is achieved. in many cases, the fault coverage is equal to the fault coverage that can be achieved by deterministic test sequences. we also investigate a method to minimize the size of the test pattern generator, and study its effectiveness alone and in conjunction with the insertion of test-points.
an approach for improving the levels of compaction achieved by vector omission. we describe a method referred to as sequence counting to improve on the levels of compaction achievable by vector omission based static compaction procedures. such procedures are used to reduce the lengths of test sequences for synchronous sequential circuits without reducing the fault coverage. the unique feature of the proposed approach is that test vectors omitted from the test sequence can be reintroduced at a later time. reintroducing of vectors helps reduce the compacted test sequence length beyond the length that can be achieved if vectors are omitted permanently. experimental results are presented to demonstrate the levels of compaction achieved by the sequence counting approach.
design-for-debugging of application specific designs. abstract: we address the problem of considering debugging requirements during high level synthesis by providing low-cost hardware support and scheduling and assignment methods for ensuring controllability and observability of the user specified variables. two key conceptually new design ideas that enable efficient debugging are developed: pipelining of debugging variables for improving their scheduling and assignment freedom and use of i/o buffers for improving resource utilization of i/o pins. the provably optimal bounds for the maximum cardinality of the set of controllable and observable variables for a given design specification are derived. a polynomial time complexity synthesis algorithm for achieving the bounds is developed. the minimization of hardware overhead gives rise to a combinatorial optimization problem which is solved using a non-greedy heuristic algorithm. the effectiveness of the proposed design-for-debugging approach is demonstrated on several examples.
algorithm selection: a quantitative computation-intensive optimization approach. given a set of specifications for a targeted application, algorithm selection refers to choosing the most suitable algorithm for a given goal, among several functionally equivalent algorithms. we demonstrate an extraordinary potential of algorithm selection for achieving high throughput, low cost, and low power implementations.we introduce an efficient technique for low-bound evaluation of the throughput and cost during algorithm selection and propose a relaxation-based heuristic for throughput optimization. we also present an algorithm for cost optimization using algorithm selection. the effectiveness of methodology and algorithms is illustrated using examples.
cost optimization in asic implementation of periodic hard-real time systems using behavioral synthesis techniques. abstract: modern applications are often defined as sets of several computational tasks. this paper presents a synthesis algorithm for asic implementations which realize multiple computational tasks under hard real-time deadlines. the algorithm analyzes constraints imposed by task sharing as well as the traditional datapath synthesis criteria. in particular we demonstrated an efficient technique to combine rate-monotonic scheduling, a widely used hard real-time systems scheduling discipline, with estimations and scheduling and allocation algorithms. matching the number of bits in tasks assigned to the same processor was the most important factor in obtaining good designs. we have demonstrated the effectiveness of our algorithms on several multiple-task examples.
verilat: verification using logic augmentation and transformations. this paper presents a new framework for formal logic verification. what is depicted here is fundamentally different from previous approaches. in earlier approaches, the circuit is either not changed during the verification process, as in obdd or implication-based methods, or the circuit is progressively reduced during verification. whereas in our approach, we actually enlarge the circuits by adding gates during the verification process. specifically introduced here is a new technique that transforms the reference circuit as well as the circuit to be verified, so that the similarity between the two is progressively enhanced. this requires addition of gates to the reference circuit and/or the circuit to be verified. in the process, we reduce the dissimilarity between the two circuits, which makes it easier to verify the circuits.
a parametric test method for analog components in integrated mixed-signal circuits. in this paper, we present a novel approach to use test stimuli generated by digital components of a mixed-signal circuit for testing its analog components. a wavelet transform is applied to the response signal of the device under test (dut). we will show, that in comparison to fourier transform or no transform at all, particular properties of this transformation are advantageous for mixed-signal test and especially built-in self test.we introduce a new method for test measurement selection based on a non-deterministic parametric fault model for analog circuits. this approach allows for noise and measurement error in testing. we show, how test quality can be optimized in the presented fault model. our test methodology is demonstrated on an analog cmos bandpass filter.
logic optimization by output phase assignment in dynamic logic synthesis. domino logic is one of the most popular dynamic circuit configurations for implementing high-performance logic designs. since domino logic is inherently noninverting, it presents a fundamental constraint of implementing logic functions without any intermediate inversions. removal of intermediate inverters requires logic duplication for generating both the negative and positive signal phases, which results in significant area overhead. this area overhead can be substantially reduced by selecting an optimal output phase assignment, which results in a minimum logic duplication penalty for obtaining inverter-free logic. in this paper, we present this previously unaddressed problem of output phase assignment for minimum area duplication in dynamic logic synthesis. we give both optimal and heuristic algorithms for minimizing logic duplication.
custom-optimized multiplierless implementations of dsp algorithms. linear dsp kernels such as transforms and filters are comprised exclusively of additions and multiplications by constants. these multiplications may be realized as networks of additions and wired shifts in hardware. the cost of such a "multiplierless" implementation is determined by the number of additions, which in turn depends on the value and precision of these constants. for a given transform or filter, the set of constants and their required precision is affected by algorithmic and implementation choices and hence provides a degree of freedom for optimization. in this work we present an automated method to generate, for a given linear transform, a minimum addition multiplierless implementation that satisfies a given quality constraint. the method combines automatic algorithm selection to improve numerical robustness and automatic search methods to minimize constant precisions in a chosen algorithm. we present experiments that show the trade-offs between cost and quality, including custom optimizations of the transforms used in jpeg image and mp3 audio decoders.
a chip-level electrostatic discharge simulation strategy. this work presents a chip-level charged device model (cdm) electrostatic discharge (esd) simulation method. the chip-level simulation is formulated as a dc analysis problem. a network reduction algorithm based on random walks is proposed for rapid analysis, and to support incremental design. a benchmark with a 2.3m-node v/sub dd/ net and 1000 i/o pads is checked in 13 minutes, and 10 re-simulations for incremental changes take a total of 9 minutes.
a hybrid linear equation solver and its application in quadratic placement. this paper presents a new hybrid linear equation solver for quadratic placement. the new solver is a combination of stochastic solver and iterative solver: it is proven in this paper that an approximate ldl factorization can be obtained from random walks, and used as a preconditioner for conjugate gradient solver. testing on real-life placement benchmarks shows a speedup of up to 7.1 times over traditional incomplete cholesky preconditioned conjugate gradient (iccg).
challenges and opportunities in broadband and wireless communication designs. communication designs form the fastest growing segment of the semiconductor market. both network processors and wireless chipsets have been attracting a great deal of research attention, financial resources and design efforts. however, further progress is limited by lack of adequate system methodologies and tools. our goal in this tutorial is to provide impetus for development of communication design techniques and tools.the first part addresses network processors (np) that we study from three viewpoints: application, architecture, and system software and compilation tools. in addition to summary of main issues and representative case studies, we identify main system design issues. the second part of the tutorial focuses on wireless design. the main emphasis is on platform-based design methodology that leverages on functional profiling, architecture exploration, and orthogonalization of concerns to facilitate low-power wireless communication systems. the highlight of the paper, an in-depth study of the state-of-the-art wireless design, picoradio, is used as explanatory design example.
specifying and verifying imprecise sequential datapaths by arithmetic transforms. we address verification of imprecise datapath circuits with sequential elements. using arithmetic transform (at) and its extensions, we verify the sequential datapath circuits with finite precision. an efficient formulation of the precision verification is presented as a polynomial maximization search over boolean inputs. using a branch-and-bound search for the precision error and the block-level composition of ats, we verify the approximated, rounded and truncated pipelined datapaths.
acceleration techniques for dynamic vector compaction. we present several techniques for accelerating dynamic vector compaction for combinational and sequential circuits. a key feature of all our techniques is that they significantly improve the computation times without adversely affecting the quality of test sets that can be derived using state-of-the-art compaction methods. our techniques are based on three key ideas: (1) identification of support sets, (2) target fault switching, and (3) use of dynamic equivalent and untestable fault analysis. all these techniques are useful in significantly reducing the number of faults that have to be considered by a test generator or a fault simulator in a dynamic vector compaction system. for fault simulation, support sets quickly identify a large subset of faults that are guaranteed to be undetectable by a given input sequence. for test generation, support sets identify a large subset of faults that are guaranteed to be undetectable by any extension of a partially specified test sequence. experimental results on iscas 89 benchmark circuits and large production vlsi circuits are included. for full scan designs, our acceleration techniques reduce the overall computation times by a factor of 2 to 3 without adversely affecting the quality (size) of the computed test sets or their fault coverages. the improvement factors obtained are higher for larger circuits. the acceleration techniques enabled the computation of compact test sets for large production circuits that the base test generation system was unable to process in more than 2 cpu days on a silicon graphics mips 4400 workstation. results for sequential circuits also show that our acceleration techniques significantly improve the computation times for dynamic vector compaction.
register-transfer level estimation techniques for switching activity and power consumption. we present techniques for estimating switching activity and power consumption in register-transfer level (rtl) circuits. previous work on this topic has ignored the presence of glitching activity at various data path and control signals, which can lead to significant underestimation of switching activity. for data path blocks that operate on word-level data, we construct piecewise linear models that capture the variation of output glitching activity and power consumption with various word-level parameters like mean, standard deviation, spatial and temporal correlations, and glitching activity at the block's inputs. for rtl blocks that operate on data that need not have an associated word-level value, we present accurate bit-level modeling techniques for glitching activity as well as power consumption. this allows us to perform accurate power estimation for control-flow intensive circuits, where most of the power consumed is dissipated in non-arithmetic components like multiplexers, registers, vector logic operators, etc. since the final implementation of the controller is not available during high-level design iterations, we develop techniques that estimate glitching activity at control signals using control expressions and partial delay information. experiments on example rtl designs resulted in power estimates that were within 7% of those produced by an inhouse power analysis tool on the final gate-level implementation.
an iterative improvement algorithm for low power data path synthesis. we address the problem of minimizing power consumption in behavioral synthesis of data-dominated circuits. the complex nature of power as a cost function implies that the effects of several behavioral synthesis tasks like module selection, clock selection, scheduling, and resource sharing on supply voltage and switched capacitance need to be considered simultaneously to fully derive the benefits of design space exploration at the behavior level. recent work has established the importance of behavioral synthesis in low power vlsi design. however, most of the algorithms that have been proposed separate these tasks and perform them sequentially, and are hence not able to explore the tradeoffs possible due to their interaction. we present an efficient algorithm for performing scheduling, clock selection, module selection, and resource allocation and assignment simultaneously with an aim of reducing the power consumption in the synthesized data path. the algorithm, which is based on an iterative improvement strategy, is capable of escaping local minima in its search for a low power solution. the algorithm considers diverse module libraries and complex scheduling constructs such as multicycling, chaining, and structural pipelining. we describe supply voltage and clock pruning strategies that significantly improve the efficiency of our algorithm by cutting down on the computational effort involved in exploring candidate supply voltages and clock periods that are unlikely to lead to the best solution. experimental results are reported to demonstrate the effectiveness of the algorithm. our techniques can be combined with other known methods of behavioral power optimization like data path replication and transformations, to result in a complete data path synthesis system for low power applications.
transient power management through high level synthesis. the use of nanometer technologies is making it increasingly important to consider transient characteristics of a circuit's power dissipation (e.g., peak power, and power gradient or differential) in addition to its average power consumption. current transient power analysis and reduction approaches are mostly at the transistor- and logic-levels. we argue that, as was the case with average power minimization, architectural solutions to transient power problems can complement and significantly extend the scope of lower-level techniques.in this work, we present a high-level synthesis approach to transient power management. we demonstrate how high-level synthesis can impact the cycle-by-cycle peak power and peak power differential for the synthesized implementation. further, we demonstrate that it is necessary to consider transient power metrics judiciously in order to minimize or avoid area and performance overheads. in order to alleviate the limits on parallelism imposed by peak power constraints, we propose a novel technique based on the selective insertion of data monitor operations in the behavioral description. we present enhanced scheduling algorithms that can accept constraints on transient power characteristics (in addition to the conventional resource and performance constraints). experimental results on several example designs obtained using a state-of-the-art commercial design flow and technology library indicate that high-level synthesis with transient power management results in significant benefits -- peak power reductions of up to 32% (average of 25%), and peak power differential reductions of up to 58% (average of 42%) -- with minimal performance overheads.
analytical bound for unwanted clock skew due to wire width variation. under modern vlsi technology, process variations greatly affectcircuit performance, especially clock skew which is very timingsensitive. unwanted skew due to process variation forms a bottleneckpreventing further improvement on clock frequency. impactfrom intra-chip interconnect variation is becoming remarkable andis difficult to be modeled efficiently due to its distributive nature.through wire shaping analysis, we establish an analytical boundfor the unwanted skew due to wire width variation which is thedominating factor among interconnect variations. experimental resultson benchmark circuits show that this bound is safer, tighterand computationally faster than similar existing approach.
generalized resource sharing. resource sharing is one of the main tasks in high-level synthesis, and although many algorithms have addressed the problem there are still several limitations which restrict the generality and applicability of current algorithms. most clique-partitioning-based algorithms use local and inaccurate cost-functions which result in inefficient results. this paper presents algorithms for the resource sharing problem on registers and functional units, and shows how they overcome the limitations of existing algorithms. the main characteristics of this work are: interleaved register and functional unit merging in a global clique partitioning based framework, accurate merging cost estimation, accurate interconnect cost estimation, relative control cost taken into account and efficient false loop elimination. the results obtained show significant improvements in the delay of designs, while also minimizing area, specially for large designs with many sharing possibilities.
an analytical high-level battery model for use in energy management of portable electronic systems. once the battery becomes fully discharged, a battery-powered portable electronic system goes off-line. therefore, it is important to take the battery behavior into account. a system designer needs an adequate high-level model in order to make battery-aware decisions that target maximization of the system's lifetime on-line. we propose such a model: it allows a designer to predict the battery time-to-failure for a given load and provides a cost metric for lifetime optimization algorithms. our model also allows for a tradeoff between the accuracy and the amount of computation performed. the quality of the proposed model is evaluated using a detailed low-level simulation of a lithium-ion electrochemical cell.
accurate layout area and delay modeling for system level design. the problem of estimating design quality measures to accurately reflect design tradeoffs and efficiently explore the design space is discussed. specifically, interest is centered on predicting the layout area and delay of a given structural rt level design. clearly, current rt level cost measures are highly simplified and do not reflect the real physical design. in order to establish a more realistic assessment of layout effects, a layout model which accurately and efficiently accounts for the effects of wiring and floorplanning on the area and performance layout of rt level designs is proposed. benchmarking has shown that this model is quite accurate
latency effects of system level power management algorithms. a power management algorithm for an embedded system reduces system level power dissipation by shutting off parts of the system when they are not being used and turning them back on when they are required. algorithms for this problem are online in nature since they must operate without knowledge of the arrival time or service requirements of future requests. in this paper, we present online algorithms to manage power for embedded systems. we perform an empirical analysis of these algorithms and give theoretical justification for the empirical results. effective power management strategies have an adverse impact on the latency of the system for which the strategy is designed. typically, the more aggressive the power management scheme, the greater the increase in the latency of the system. in this paper, we prove an upper bound on the additional latency of the system introduced by power management strategies. moreover, we show that this upper bound occurs each time the system is shutdown and hence is an important system design parameter.in addition, service time and latencies have an effect on power management strategies since they alter the length and occurrences of idle periods which. we study this phenomenon experimentally, by modeling the disk drive of a laptop computer as an embedded system. the results show that if service times of arriving requests are modeled, the relative performance of algorithms can change leading to non-adaptive algorithms performing better than adaptive ones. we compare the performance of adaptive and non-adaptive power management algorithms. in particular, our experimental results show that an "immediate" shutdown strategy that shuts down the system whenever it encounters an idle period performs surprising better than sophisticated adaptive algorithms suggested in the literature. we provide an analytical explanation for the effectiveness of power management strategies.
portable parallel test generation for sequential circuits. a parallel test generation algorithm, propertest, for sequential circuits that is portable across a range of mimd parallel architectures is discussed. it uses prioritized execution to ensure consistent speedups as the number of processors is increased. this consistency is achieved without loss of fault coverage with increase in the number of processors. this also permits the use of parallel processing to improve the fault coverage when the execution time is bounded. results on iscas 89 benchmark programs are provided on a shared memory machine, a message passing machine, and a network of workstations. propertest was run unchanged on these different architectures
test-model based hierarchical dft synthesis. with increasing design sizes and adoption of system on a chip (soc) methodology, design synthesis and test automation tools are hitting capacity and performance bottlenecks. currently, hierarchical synthesis flows for large designs lack complete designfor-test (dft) support. with this paper, we address a solution, involving the introduction of test models in a traditional dft synthesis flow, that we term hierarchical dft synthesis (hds). we discuss the use of core test language (ctl) based test models combined with physical and timing models to provide a complete flow for chip-level dft. in doing so we address some challenges the new flow presents such as design rule checking (drc), dft architecting and optimization. we describe methods to overcome these challenges thereby presenting a new methodology to handle complex next generation designs.
achievable bounds on signal transition activity. transitions on high capacitance busses in vlsi systems result in considerable system power dissipation. therefore, various coding schemes have been proposed in the literature to encode the input signal in order to reduce the number of transitions. in this paper we derive achievable lower and upper bounds on the expected signal transition activity. these bounds are derived via an information-theoretic approach in which symbols generated by a source (possibly correlated) with entropy rate h are coded with an average of r bits/symbol. these results are applied to, 1.) determine the activity reducing efficiency of different coding algorithms such as entropy coding, transition coding, and bus-invert coding, 2.) bound the error in entropy-based power estimation schemes, and 3.) determine the lower-bound on the power-delay product. two examples are provided where transition activity within 4% and 8% of the lower bound is achieved when blocks of 8 and 13 symbols respectively are coded at a time.
an integrated design flow for a via-configurable gate array. in this work we present a complete physical design flow for a via-configurable gate array (vcga). the vcga is an array of prefabricated logic blocks and fixed metal masks. the block consists of via-configurable functional cells and a via-decomposable flip-flop. an m1-m2 via mask is used to define the block's functionality. interconnects are customized using via masks. we developed a physical design flow for vcga, which integrates a set of effective techniques. here, we highlight the packing, cell-binding, and detailed-routing problems. we use our design flow to compare the vcga-based and standard-cell/fpga-based designs. experimental results show the efficiency of our flow.
via-configurable routing architectures and fast design mappability estimation for regular fabrics. in this paper, we describe a new via-configurable routing architecture which shows a much better throughput and performance than the previous structures. we demonstrate how to construct a single-via-mask fabric to reduce the mask cost further, and we analyze the penalties which it incurs. to solve the routability problem commonly existing in fabric-based designs, an efficient white-space allocation and an incremental cell movement scheme are suggested, which help to provide a fast design convergence and early prediction of circuit's mappability to a given fabric.
on the np-completeness of regular 2-d fpga routing architectures and a novel solution. several industrial fpga routing architectures have been shown to have no efficient routing algorithms (unless p=np). here, we further investigate if the intractability of the routing problem on a regular 2-d fpga routing architecture can be alleviated by adding routing switches. we show that on this routing architecture, even with a substantial increase in switching flexibility, a polynomial time, predictable routing algorithm is still not likely to exist, and there is no constant ratio bound of the detailed over global routing channel densities. we also show that a perfect routing is unachievable on this architecture even with near complete (maximum) switching flexibility.we also discuss a new, greedy routing architecture, that possesses predictable and other desired routing properties, yet requires fewer routing resources than regular architectures. this theoretical result may suggest an alternative approach in routing architecture designs.
a heuristic to determine low leakage sleep state vectors for cmos combinational circuits. input vector control has been used to minimize the leakage powerconsumption of a circuit in sleep state. in this paper, we presenta novel heuristic for determining a low leakage vector to beapplied to a circuit in sleep state. the heuristic is a greedy searchbased on the controllability of nodes in the circuit and uses thefunctional dependencies among cells in the circuit to guide thesearch. results on a set of iscas and mcnc benchmark circuitsshow that in all cases our heuristic returns a vector having aleakage within 5% of that of the vector obtained using an extensiverandom search, with orders of magnitude improvement incomputational speed.
frugal linear network-based test decompression for drastic test cost reductions. in this work we investigate an effective approach to construct a linear decompression network in the multiple scan chain architecture. a minimal pin architecture, complemented by negligible hardware overhead, is constructed by mathematically analysing test data relationships, delivering in turn drastic test reductions. the proposed network drives a large number of internal scan chains with a short input vector, thus allowing significant reductions in both test time and test volume. the proposed method constructs an inverter-interconnect based network by exploring the pairwise linear dependencies of the internal scan chain vectors, resulting in a very low cost network that is nonetheless capable of outperforming much costlier compression schemes. we propose an iterative algorithm to construct the network from an initial set of test cubes. the experimental data shows significant reductions in test time and test volume with no loss of fault coverage.
energy optimization for a two-device data flow chain. many applications running on today's portable devices use multiple power-consuming devices simultaneously, often in the form of a dataflow chain which involves transfer of data between devices through buffers. some of these devices have the ability to scale their performance and power simultaneously by tuning one of their parameters (generically called the device speed). we address the problem of minimizing the energy consumed by a two-device data flow chain by choosing the speed profiles of the two devices and the "cycle time" of the intermediate buffer. determining the speed profiles (functions of time) to minimize the energy functional, in general, requires variational techniques. however, based on certain observations about device power-speed relations and application performance constraints, we were able to solve the problem analytically in two steps - device characterization and cycle time optimization. the effectiveness of the technique was demonstrated for two practical applications of dataflow chains - cd recording and vcd playback with up to 45% and 64% energy improvements, respectively.
battery optimization vs energy optimization: which to choose and when? batteries are non-ideal energy sources - minimizing the energy consumption of a battery-powered system is not equivalent to maximizing its battery life. we propose an alternative interpretation of a previously proposed battery model, which indicates that the deviation from ideal behavior is due to the buildup of "unavailable charge" during the discharge process. previously, battery-aware task scheduling algorithms and power management policies have been developed, which try to reduce the unavailable charge at the end of a given workload. however, they do not account for the occurrence of rest periods (user enforced, naturally occurring, or due to finite load horizon), which are present in a variety of workloads. we first obtain an analytical bound on the recovery time of a battery as a function of the extent of recovery. then, we shown that the effect of the rest periods is to reduce the improvement of battery-charge optimizing techniques over traditional energy-optimizing techniques. under certain conditions, the policy that only minimizes energy consumption can actually achieve a longer battery lifetime than a battery-aware policy. a formal criterion based on the recovery time is proposed to choose between a candidate battery-aware policy and a candidate energy-aware policy. we also model the battery discharge process as a linear time invariant system and obtain the frequency response of a battery. this is then used to study the effect of task granularity on the improvement achieved by battery-aware task scheduling. it was observed that the response time of typical batteries are of the order of seconds to several minutes. this, along with the charge recovery effect, was seen to cause battery-aware task scheduling methods to become ineffective for both very fine-grained (less than 10 ms) and very coarse-grained (greater than 30 mm) task granularities.
system level verification of digital signal processing applications based on the polynomial abstraction technique. polynomial abstraction has been developed for data abstraction of sequential circuits, where the functionality can be expressed as polynomials. the method, based on the fundamental theorem of algebra, abstracts a possibly infinite domain of input values, into a much smaller and finite one, whose size is calculated according to the degree of the respective polynomial. the abstract model preserves the system's control and data properties, which can be verified by model checking. experiments show that our approach does not only allow an automatic verification, but also gives considerably better results than existing methods.
a framework for testing core-based systems-on-a-chip. available techniques for testing core-based systems-on-a-chip (socs) do not provide a systematic means for synthesising low-overhead test architectures and compact test solutions. in this paper, we provide a comprehensive framework that generates low-overhead compact test solutions for socs. first, we develop a common ground for addressing issues such as core test requirements, core access and test hardware additions. for this purpose, we introduce finite-state automata for modeling tests, transparency modes and test hardware behavior. in many cases, the tests repeat a basic set of test actions for different test data which can again be modeled using finite-state automata. while earlier work can derive a single symbolic test for a module in a register-transfer level (rtl) circuit as a finite-state automation, this work extends the methodology to the system level, and, additionally contributes a satisfiability-based solution to the problem of applying a sequence of tests phased in time. this problem is known to be a bottleneck in testability analysis not only at the system level, but also at the rtl. experimental results show that the system-level average area overhead for making socs testable with our method is only 4.4%, while achieving an average test application time reduction of 78.5% over recent approaches. at the same time, it provides 100% test coverage of the precomputed test sets/sequences of the embedded cores.
high-density reachability analysis. we address the problem of reachability analysis for large finite state systems. symbolic techniques have revolutionized reachability analysis but still have limitations in traversing large systems. we present techniques to improve the symbolic breadth-first traversal and compute a lower bound on the reachable states. we identify the problem as one of density during traversal and our techniques seek to improve the same. our results show a marked improvement on the existing breadth-first traversal methods.
multi-domain clock skew scheduling. the application of general clock skew scheduling is practicallylimited due to the difficulties in implementing a wide spectrum ofdedicated clock delays in a reliable manner. this results in a significantlimitation of the optimization potential. as an alternative,the application of multiple clocking domains with dedicatedphase shifts that are implemented by reliable, possibly expensivedesign structures can overcome these limitations and substantiallyincrease the implementable optimization potential of clock adjustments.in this paper we present an algorithm for constrained clockskew scheduling which computes for a given number of clockingdomains the optimal phase shifts for the domains and the assignmentof the individual registers to the domains. for the within-domainlatency values, the algorithm can assume a zero-skew clockdelivery or apply a user-provided upper bound. our experimentsdemonstrate that a constrained clock skew schedule using a fewclocking domains combined with small within-domain latency canreliably implement the full sequential optimization potential to dateonly possible with an unconstrained clock schedule.
modeling of ballistic carbon nanotube field effect transistors for efficient circuit simulation. carbon nanotube field-effect transistors (cnfets) arebeing extensively studied as possible successors to cmos.novel device structures have been fabricated and devicesimulators have been developed to estimate theirperformance in a sub 10nm transistor era. this paperpresents a novel method of circuit-compatible modeling ofcnfets in their ultimate performance limit. the model sodeveloped has been used to simulate arithmetic and logicblocks using hspice.
a circuit model for carbon nanotube interconnects: comparative study with cu interconnects for scaled technologies. semiconducting carbon nanotubes (cnt) have gained immense popularity as possible successors to silicon as the channel material for ultra high performance field effect transistors. on the other hand, their metallic counterparts have often been regarded as ideal interconnects for the future technology generations. owing to their high current densities and increased reliability, metallic-single walled cnts (swcnts) have been subjects of fundamental research both in theory as well as experiments. metallic cnts have been modeled for rf applications in (burke, 2003) using an lc model. we present an efficient circuit compatible rlc model for metallic sw cnts, and analyze the impact of sw cnts on the performance of ultra scaled digital vlsi design.
compactest-ii: a method to generate compact two-pattern test sets for combinational logic circuits. the problem of generating small (compact) test sets for single transition and cmos stuck-open faults in combinational logic circuits is considered. in addition, it is proposed that to generate test sets that cover a wide range of physical defects, a test set to detect faults of different models should be derived. specifically, the problem of generating small and comprehensive test sets is addressed by considering the cmos stuck-open and the single transition fault models together. a dynamic test compaction technique for two-pattern tests is proposed. the technique exploits the test compaction strategies developed for stuck-at faults, and performs dynamic test vector overlap to derive small test sets. experimental results for iscas-85 combinational circuits and fully scanned versions of iscas-89 sequential circuits are presented to illustrate the efficacy of the proposed test compaction technique
true crosstalk aware incremental placement with noise map. crosstalk noise has become an important issue as technology scales down for timing and signal integrity closure. existing works to fix crosstalk noise are mostly done at the routing or post routing stage, which may be too late. since placement determines the overall routing congestion, which correlates with the coupling capacitance, which in turn correlates with the crosstalk noise, placement shall be a good level to do early noise mitigation. the only existing work for the crosstalk aware placement (to our best knowledge) is by lou and chen (2004), which uses the coupling capacitance map to guide placement. however, crosstalk is determined not only by the coupling capacitance, but also by many other factors, such as the driver resistance of the victim net and the coupling location (near source vs near sink coupling) (cong et al., 2001). we introduce a concept of noise map which takes those factors into account. guided by this accurate noise map explicitly, we propose an incremental placement technique to mitigate noise without disturbing the global placement order. our incremental placement has two key steps, namely noise aware cell inflation and local refinement. experimental results on industrial circuits show that our approach is able to reduce the number of top noise nets by 25% and improve the timing (300ps on the worst slack), with no wire length penalty or cpu overhead. our incremental approach is also able to maintain the placement stability.
a trajectory piecewise-linear approach to model order reduction and fast simulation of nonlinear circuits and micromachined devices. in this paper we present an approach to the nonlinear model reduction based on representing the nonlinear system with a piecewise-linear system and then reducing each of the pieces with a krylov projection. however, rather than approximating the individual components as piecewise-linear and then composing hundreds of components to make a system with exponentially many different linear regions, we instead generate a small set of linearizations about the state trajectory which is the response to a 'training input'. computational results and performance data are presented for a nonlinear circuit and a micromachined fixed-fixed beam example. these examples demonstrate that the macromodels obtained with the proposed reduction algorithm are significantly more accurate than models obtained with linear or the recently developed quadratic reduction techniques. finally, it is shown that the proposed technique is computationally inexpensive, and that the models can be constructed 'on-the-fly', to accelerate simulation of the system response.
leopard: a logical effort-based fanout optimizer for area and delay. we present leopard, a fanout optimization algorithm based on the effort delay model for near-continuous size buffer libraries. our algorithm minimizes area under required timing and input capacitance constraints by finding the tree topology and assigning different gains to each buffer to minimize the total buffer area. experimental results show that the new algorithm achieves significant buffer area improvement compared to previous approaches.
co-synthesis of heterogeneous multiprocessor systems using arbitrated communication. we describe the first co-design technique aimed at heterogenous systems employing arbitrated communication. arbitrated system design is especially difficult because communication scheduling is directly tied to task allocation. the method provides a complete co-design&mdash;i.e. generation of a hardware configuration along with an allocation and schedule&mdash;for the execution of hard real-time data-dependent tasks. by using an actual scheduling analysis in the inner co-design loop, the method is readily able to address realistic system effects including various communication models like arbitration, as in pci-based systems.
metrics, techniques and recent developments in mixed-signal testing. this paper presents a tutorial on mixed-signal testing. our focus is on testing the analog portion of the mixed-signal device, as the digital portion is handled in the usual way. we begin by first outlining the role of test in a manufacturing environment, and its impact on product cost and quality. we look at the impact of manufacturing defects on the behavior of digital and analog circuits. subsequently, we argue that analog circuits require very different test methods than those presently used to test digital circuits. we then describe four common analog test methods and their measurement setups. we also describe how analog testing can be accomplished using digital sampling techniques. finally, we close this tutorial with a brief description of several developments presently underway on the design of testable mixed-signal circuits.
verification of delta-sigma converters using adaptive regression modeling. a new verification technique for &delta;&sigma; analog-to-digital converters (adc) is proposed. the adc is partitioned into functional blocks, and adaptive regression models for each partition are constructed using transistor-level simulation data. non-idealities in circuit behavior are captured by the adaptive regression technique from the collected data. the algorithms have been implemented in a simulation program arsim (adaptive regression simulator), which performs data sampling, model building, and simulation. experimental results using arsim are shown on a second-order &delta;&sigma; modulator, and they demonstrate the effectiveness of our technique as a fast and accurate approach for verifying &delta;&sigma; converters.
battery-aware power management based on markovian decision processes. this paper is concerned with the problem of maximizing capacity utilization of the battery power source in a portable electronic system under latency and loss rate constraints. first, a detailed stochastic model of a power-managed, battery-powered electronic system is presented. the model, which is based on the theories of continuous-time markovian decision processes and stochastic networks, captures two important characteristics of today's rechargeable battery cells, i.e., the current rate-capacity characteristic and the relaxation-induced recovery. next, the battery-aware dynamic power management problem is formulated as a policy optimization problem and solved exactly by using a linear programming approach. experimental results show that the proposed method outperforms existing heuristic methods for battery management by as much as 17% in terms of the average energy delivered per unit weight of battery cells.
hardware synthesis from guarded atomic actions with performance specifications. we present a new hardware synthesis methodology for guarded atomic actions (or rules), which satisfies performance-related scheduling specifications provided by the designer. the methodology is based on rule composition, and relies on the fact that a rule derived by the composition of two rules behaves as if the two rules were scheduled simultaneously. rule composition is a well understood transformation in the trs theoretical framework; however, previous rule composition approaches resulted in an explosion of the number of rules during synthesis, making them impractical for realistic designs. we avoid this problem through composition of conditional actions which generates one rule instead of 2/sup n/ rules when we combine n rules. we then show how this conditional composition of rules can be compiled into an efficient hardware structure which introduces new but derived interfaces in modules. we demonstrate the approach via a small circuit example (gcd) and then show its impact on the methodology to implement pipelined processors in bluespec. many ways of dealing with branches in pipelined processors or bypassing values can be expressed simply as different schedules. the results show improvements in performance over previous rule-based synthesis approaches as well as the ease of performance-related architectural exploration. in a somewhat surprising result, we show that simply by specifying a different schedule, one can automatically transform a single-issue processor pipeline into a superscalar pipeline.
cellular wave computers and cnn technology - a soc architecture with xk processors and sensor arrays. cellular wave computers and cellular nonlinear network (cnn) technology are discussed in this paper. it is a system-on-chip (soc) architecture with xk processors and sensor arrays. the architectural lessons from the trends in manufacturing billion component devices when crossing the threshold of 100 nm feature size will determine the architecture, the elementary instructions, and the type of algorithms needed, hence also the complexity of the solution.
power-delay modeling of dynamic cmos gates for circuit optimization. we present an accurate analytical expression to compute power and delay of domino cmos circuits from a detailed description of internal capacitor switching and discharging currents. the expression obtained accounts for the main effects in complex sub-micron gates like velocity saturation effects, body effect, device sizes and coupling capacitors. the energy-delay product is also evaluated and analyzed. results are compared to hspice simulations (level 50) for a 0.18&mu;m cmos technology.
design of dna origami. the generation of arbitrary patterns and shapes at very small scales is at the heart of our effort to miniaturize circuits and is fundamental to the development of nanotechnology. here i review a recently developed method for folding long single strands of dna into arbitrary two-dimensional shapes using a raster fill technique - 'scaffolded dna origami'. shapes up to 100 nanometers in diameter can be approximated with a resolution of 6 nanometers and decorated with patterns of roughly 200 binary pixels at the same resolution. experimentally verified by the creation of a dozen shapes and patterns, the method is easy, high yield, and lends itself well to automated design and manufacture. so far, cad tools for scaffolded dna origami are simple, require hand-design of the folding path, and are restricted to two dimensional designs. if the method gains wide acceptance, better cad tools will be required.
power estimation tool for sub-micron cmos vlsi circuits. accurate and fast time-domain current waveform simulation is important for the design of reliable cmos vlsi circuits. a detailed current model that resulted in a maximum of 10% deviation from the current waveforms as obtained by spice level 3 at peak values and 5% at the average current is presented. the current model accounts for short-channel effects, input risetimes, short-circuit and dynamic current, and circuit topology. moreover, the model produces piecewise linear current waveforms and can be incorporated in any switch-level simulator. using the models in an event driven simulator, a 3-4 orders of magnitude speedup relative to spice level 3 has been achieved. the results for current waveform accuracy are better than those obtained for previously published methods and in particular for complex cmos circuits
thermal simulation techniques for nanoscale transistors. thermal simulations are important for advanced electronic systems at multiple length scales. a major challenge involves electrothermal phenomena within nanoscale transistors, which exhibit nearly ballistic transport both for electrons and phonons. the thermal device behavior can influence both the mobility and the leakage currents. we discuss recent advances in modeling coupled electron-phonon transport in future nanoscale transistors. the solution techniques involve solving the boltzmann transport equation (bte) for both electrons and phonons. we present a practical method for coupling an electron monte carlo simulation with an analytic "split-flux" form of the phonon bte. we use this approach to model self-heating in a 20 nm quasi-ballistic n+/n/n+ silicon diode, and to investigate the role of hot electron and hot phonon transport.
convexfit: an optimal minimum-error convex fitting and smoothing algorithm with application to gate-sizing. convex optimization has gained popularity due to its capability to reach global optimum in a reasonable amount of time. convexity is often ensured by fitting the table data into analytically convex forms such as posynomials. however, fitting the look-up tables into the posynomial forms with minimum error itself may not be a convex optimization problem and hence excessive fitting errors may be introduced. in this paper, we propose to directly adjust the look-up table values into a numerically convex look-up table without explicit analytical form. we show that numerically "convexifying" the table data with minimum perturbation can be formulated as a convex semidefinite optimization problem and hence optimality can be reached in polynomial time. without an explicit form limitation, we find that the fitting error is significantly reduced while the convexity is still ensured. as a result, convex optimization algorithms can still be applied. furthermore, we also develop a "smoothing" algorithm to make the table data smooth and convex to facilitate the optimization process. results from extensive experiments on industrial cell libraries demonstrate that our method reduces 30/spl times/ fitting error over a well-developed posynomial fitting algorithm. its application to circuit tuning is also presented.
automatic test generation for linear digital systems with bi-level search using matrix transform methods. a hierarchial testing approach for linear state variable digital systems based on matrix manipulation and constrained low-level test generation is reported. feast (functional extractor and sequential test generator) operates at the high level, where the circuit is described as an interconnection of arithmetic modules. crest (constrained sequential test generator) operates at the low level description of the individual modules, and generates test sets satisfying constraints imposed by the high-level modules and their interconnection structure. the approach was found to perform better than automatic test generation at the gate level using existing algorithms for several large circuits
sat based solutions for consistency problems in formal property specifications for open systems. formal property verification is increasingly being adopted by designers for module level validation. the behavior of a module is typically expressed in terms of the behavioral guarantee of the module under assumptions on its environment. expressing such assume-guarantee properties correctly in a formal language is a nontrivial task and errors in the specification are not uncommon. in this paper we examine the main forms of specification errors for open systems, and present sat based algorithms for verifying the specification against such errors.
double-gate soi devices for low-power and high-performance applications. double-gate (dg) transistors have emerged as promising devices for nano-scale circuits due to their better scalability compared to bulk cmos. among the various types of dg devices, quasi-planar soi finfets are easier to manufacture compared to planar double-gate devices. dg devices with independent gates (separate contacts to back and front gates) have recently been developed. dg devices with symmetric and asymmetric gates have also been demonstrated. such device options have direct implications at the circuit level. independent control of front and back gate in dg devices can be effectively used to improve performance and reduce power in sub-50nm circuits. independent gate control can be used to merge parallel transistors in noncritical paths. this results in reduction in the effective switching capacitance and hence power dissipation. we show a variety of circuits in logic and memory that can benefit from independent gate operation of dg devices. as examples, we show the benefit of independent gate operation in circuits such as dynamic logic circuits, schmitt triggers, sense amplifiers, and sram cells. in addition to independent gate option, we also investigate the usefulness of asymmetric devices and the impact of width quantization and process variations on circuit design.
making fourier-envelope simulation robust. fourier-envelope algorithms are an important component of the mixed-signal/rf verification toolbox. in this paper, we address the unpredictability and lack of robustness that has been reported for these algorithms. we show that the problem stems from fast oscillations in envelopes that are expected to be slowly varying. we demonstrate that this is related to the fact that the envelope equations are always stiff, whether or not the underlying system is. we show that careful choice of envelope initial conditions is necessary to obtain useful solutions, and propose two techniques for finding good initial conditions. applying these, and solving the envelope equations with stiffly-stable numerical methods, we improve the robustness and reliability of fourier-envelope methods. we illustrate the new methods with a direct-downconversion mixer circuit.
a bipartition-codec architecture to reduce power in pipelined circuits. this paper proposes a new bipatition-codec architecture that may reduce power consumption of pipelined circuits. we treat each output value of a pipelined circuit as one state of a fsm. if the output of a pipelined circuit transit mainly among few states, we could partition the combinational portion of a pipelined circuit into two blocks: one that contains the few states of high activity is small and the other that contains the remainder of low activity is big. consequently, the state transitions will be confined to the small block in most of the time. then we replace the small block with a codec circuit, which consists of an encoder and a decoder, to reduce the internal switching activity of the block. the encoder minimizes the number of bit changes during state transitions thus the switching which propagates into decoder is reduced considerably. we present experimental results on several mcnc benchmarks and get up to 63.7% power savings by using our new architecture.
simulation-based techniques for dynamic test sequence compaction. simulation-based techniques for dynamic compaction of test sequences are proposed. the first technique uses a fault simulator to remove test vectors from the partially-specified test sequence generated by a deterministic test generator if the vectors are not needed to detect the target fault, considering that the circuit state may be known. the second technique uses genetic algorithms to fill the unspecified bits in the partially-specified test sequence in order to increase the number of faults detected by the sequence. significant reductions in test set sizes were observed for all benchmark circuits studied. fault coverages improved for many of the circuits, and execution times often dropped as well, since fewer faults had to be targeted by the computation-intensive deterministic test generator.
performance-driven read-after-write dependencies softening in high-level synthesis. conventional scheduling algorithms usually produce schedules whose cycle lengths are influenced by the operations latency. operations are assigned to one or several consecutive cycles (multicycle operators) and one operation cannot begin until all its predecessors have finished, except for operations chaining. this technique allows the execution in the same cycle of several data-dependent operations, being some bits of the chained operations calculated in parallel. chaining one operation to its predecessor requires the completion of both in the selected cycle. this paper presents a less restrictive technique based on the softening of the read-after-write dependencies among operations, which allows beginning the execution of one operation before the calculus of its predecessors has been completed. this becomes feasible when the execution of the predecessor has begun in the selected cycle or in a previous one, and even if it finishes in a posterior cycle. this design technique is applied before synthesis to transform behavioural specifications into new ones whose subsequent synthesis substantially improves circuit performance.
iterative [simulation-based genetics + deterministic techniques]= complete atpg0. simulation-based test vector generators require much less computer time than deterministic atpg but they generate longer test sequences and sometimes achieve lower fault coverage. this is due to the divergence in the search process. in this paper, we propose a correction technique for simulation-based atpg. this technique is based on identifying the diverging state and on computing a fault cluster (faults close to each other). a set of candidate faults from the cluster is targeted with a deterministic atpg and the resulting test sequence is used to restart the search process of the simulation-based technique. this above process is repeated until all faults are detected or proven to be redundant/untestable. the program implementing this approach has been used to generate tests with very high fault coverage, and runs about 10 times faster than traditional deterministic techniques with very good test quality in terms of test length and fault coverage.
what is the cost of delay insensitivity? deep submicron technology calls for new design techniques, in which wire and gate delays are accounted to have equal or nearly equal effect on circuit behaviour. asynchronous speed-independent (si) circuits, whose behaviour is only robust to gate delay variations, may be too optimistic. on the other hand, building circuits totally delay-insensitive (di), for both gates and wires, is impractical. the paper presents an approach for automated synthesis of globally di and locally si circuits. it is based on order relaxation, a simple graphical transformation of a circuit's behavioural specification, for which signal transition graph, an interpreted petri net, is used. the method is successfully tested on a set of benchmarks and a realistic design example. it proves effective showing average cost of di interfacing at about 40% for area and 20% for speed.
minimizing power across multiple technology and design levels. approaches to achieve low-power and high-speed vlsi's are described with the emphasis on techniques across multiple technology and design levels. to suppress the leakage current in a standby mode, boosted gate mos (bgmos) is effective, which is based on cooperation between technology level and circuit level. to reduce the power in an active mode, vdd-hopping and vth-hopping are promising, which are cooperative approaches between circuit and software. power consumed in interconnect system can be reduced by a cooperative approach between application and layout as in bus shuffling. other low-power design approaches are also discussed.
functional timing optimization. it is widely believed that any true (or sensitizable) critical path of length &ge; t must be sped up in order for a circuit to have a delay < t. in this paper i demonstrate that this notion is pessimistic. many true paths can never affect the delay of the circuit &mdash; whenever such a path propagates a signal, some other path that is at least as long also propagates a signal.the theory for a new classification of paths based on the impact on the circuit delay is presented and conditions are given under which a path (or a set of paths) must be sped up in order to improve the circuit delay. the conditions for the categorization are independent of the delays in the circuit and are valid for all delay assignments.this work indicates that the widely employed notions of true and false paths may be misleading both for timing optimization and delay analysis of logic circuits.
the impact of device parameter variations on the frequency and performance of vlsi chips. the distance-correlated (continuous) within-die (wid) process variations of transistor parameters appears to be approximately scaling with process generations. furthermore, shrinking clock cycles and the scaling of functional block dimensions in complex chips (e.g. cpus), cause a shortening of interconnect distances. these effects mitigate correlated variations' impact on delay changes across a die. temperature has a small effect, and supply distribution can be well-understood and designed. furthermore, uncorrelated (random) variations (e.g. rdf, & ler) currently have a small impact on speed-setting paths, and even multiplying their effect (as processes shrink), would not make them very significant. coupled with methods for estimating the shift in the maximum operating frequency (f/sub max/) of a die (due to variations), it is shown that variations will continue to have a small effect on product speeds through the mid-term future.
a scalable substrate noise coupling model for mixed-signal ics. a scalable macromodel for substrate noise coupling in heavily doped substrates has been developed. this model is simple since it requires only four parameters which can readily be extracted from a small number of device simulations or measurements. once these parameters have been determined the model can be used for any spacing between the injection and sensing contacts and for different contact geometries. the scalability of the model with separation and width provides insight into substrate coupling and optimization issues prior to and during the layout phase. the model is validated for a 2&mgr;m and a 0.5&mgr;m cmos process where it is shown that the simple model predicts the noise coupling accurately. measurements from a chip fabricated in a 0.5&mgr;m cmos process show good agreement with the model.
power exploration for embedded vliw architectures. in this paper, we propose a system-level power exploration methodology for embedded vliw architectures based on an instruction-level analysis. the instruction-level energy model targets a general pipeline scalar processor; several architectural parameters such as number and type of pipeline stages as well as average stall/latency cycles per instruction and inter-instruction effects are taken into account. the application of the proposed model to vliw processors results intractable from the point of view of both spatial and temporal complexity (which grow exponentially w.r.t. the number of possible operations in the isa). to reduce this complexity, the basic model has been extended by assuming that the energy associated with a long instruction is given by the sum of the energy associated with the single operations of the long instruction and the single pipeline stages. the instruction-level energy model has been applied to a simplified vliw architecture to demonstrate the validity of the proposed approach.1
time-constrained loop pipelining. this paper addresses the problem of time-constrained loop pipelining, i.e. given a fixed throughput, finding a schedule of a loop which minimizes resource requirements. this paper proposes a methodology, called tclp, based on dividing the problem into two simpler and independent tasks: retiming and scheduling. tclp explores different sets of resources, searching for a maximum resource utilization. this reduces area requirements. after a minimum set of resources has been found, the execution throughput is increased and the number of registers required by the loop schedule is reduced. tclp attempts to generate a schedule which minimizes cost in time and area (resources and registers). the results show that tclp obtains optimal schedules in most cases.
optimizing computations in a transposed direct form realization of floating-point lti-fir systems. the inherent computational redundancy in discrete-time lti-fir system response computations in digital signal processing have been exploited in a variety of ways to minimize the computational complexity. we present an improved algorithm-level computational optimization that uses sorted recursive differences between coefficients representing the system transfer function with a floating-point number representation to extract maximum benefits from this redundancy. it can be applied to any lti-fir system and there is no deterioration in accuracy compared to directly using the coefficients. the results for several practical fir systems show that there is a significant reduction in the computational complexity, hence power consumed, using this technique.
power vs. delay in gate sizing: conflicting objectives? abstract: the problem of sizing gates for power-delay tradeoffs is of great interest to designers. in this work, the theoretical basis for gate sizing under delay and power considerations is presented, and results on a practical implementation are presented. the dynamic power as well as the short-circuit power are modeled, using notions of delay and transition density, and the optimization problem is formulated using notions of convex programming. previous approaches have not modeled the short circuit power, and our experimental results show that the incorporation of this leads to counter-intuitive results where the minimum power circuit is not necessarily the minimum-sized circuit.
nrg: global and detailed placement. we present a new approach to the placement problem. the proposed approach consists of analyzing the input circuit and deciding on a two-dimensional global grid for that particular input. after determination of the grid size, the placement is carried out in three steps: global placement, detailed placement and final optimization. we will show that the output of the global placement can also serve as a fast and accurate predictor. current implementation is based on simulated annealing. we have put all algorithms together in a placement package called nrg (pronounced n-er-g). in addition to area minimization, nrg can perform timing-driven placement. experimental results are strong. we improve timberwolf's results (version 1.2, the commercial version which is suppose to be better than all university versions including version 7) by about 5%. our predictor can estimate the wirelength within 10-20% accuracy offering 2-20x speedup compared with the actual placement algorithm.
a novel geometric algorithm for fast wire-optimized floorplanning. as the size and complexity of vlsi circuits increase, the needfor faster floorplanning algorithms also grows.in this work weintroduce traffic, a new method for creating wire- and area-optimizedfloorplans.through the use of connectivity groupling,simple geometry, and efficient data structures, traffic achieveshigher result quality than simulated annealing (sa) in afraction of the time.this speed allows designers to explore alarge circuit design space in a reasonable amount of time,rapidly evaluate small changes to big circuits, and quicklyproduce initial solutions for other floorplanning algorithms.
speeding up pipelined circuits through a combination of gate sizing and clock skew optimization. abstract: an algorithm for unifying the techniques of gate sizing and clock skew optimization for acyclic pipelines is presented. in the design of circuits under very tight timing specifications, the area overhead of gate sizing can be considerable. the procedure utilizes the idea of cycle-borrowing using clock skew optimization to relax the stringency of the timing specification on the critical stages of the pipeline. experimental results verify that cycle-borrowing using sizing+skew results in a better overall area-delay tradeoff than with sizing alone.
simulated quenching: a new placement method for module generation. this paper addresses a placement method good for module generation. conventional partitioning based method can not guarantee the best quality in consecutive partitioning, even if it can find a sequence of the minimum partitioning of a circuit into two subcircuits. also, when size of cells varies very much, which is often seen in module generation as leaf cells, it is sometimes too strong constraint for them to get the minimum partitioning under ``partitioning into two similar size of subcircuits''. on the other hand, although conventional simulated annealing (sa) based method gives a better result, it requires extremely long computation time, since they do not employ any divide and conquer technique. it is the purpose of this paper to propose an algorithm which is based on sa method and employs the divide and conquer technique so that it gives better quality than partitioning based method and also it gives drastically faster computation time than sa method. as the first step, we applied this idea to the linear placement. our algorithm is based on sorting inside subgroups, and this subgroup generation is done by plural cut-lines with a constant pitch. this constant pitch will be decreased from sufficiently large value to small value gradually, and this decreasing schedule is similar to the cooling schedule of sa method. and also, since there is a variation of offset in applying cut-lines even with the same pitch value, we randomly select one of them like sa method chooses a pair of components to be switched at random. sorting inside subgroups is only a rearrangement depending on the connection between subgroups and is very fast. it is found that the total wiring length is improved about 10% compared to that of spectral method which was recognized to be the best (slpc2). also, computation time was dramatically reduced over the sa method.
logic synthesis for look-up table based fpgas using functional decomposition and support minimization. this paper presents a logic synthesis method for look-up table (lut) based field programmable gate arrays (fpgas). we determine functions to be mapped to luts by functional decomposition. we use not only disjunctive decomposition but also nondisjunctive decomposition. furthermore, we propose a new boolean resubstitution technique customized for an lut network synthesis. resubstitution is used to determine whether an existing function is useful to realize another function; thus, we can share the common function among two or more functions. the boolean resubstitution is effectively carried out by solving a support minimization problem for an incompletely specified function. we can also handle satisfiability don't cares of an lut network using the technique.
deadlock-free routing and component placement for irregular mesh-based networks-on-chip. routing is one of the most crucial key factors which decides over the success of noc architecture based systems or their failure. this paper uses well known principles from parallel computer architecture to develop a deadlock free highly adaptive routing algorithm for a 2d-mesh based network-on-chip (noc) architecture including oversized ip cores. the paper consists of a short introduction into related routing theories and then gives a detailed description of the developed routing scheme. the last part is dedicated to a new floorplanning method, which allows to generate high density layouts suitable for the presented routing algorithm.
towards support for design description languages in eda framework. we report on a new framework service for design tool encapsulation, based on an information model for design management. the new service uses generated language processors that perform import and export of design files to and from a design management database with the support of nested syntax specifications and extension language scripts. our prototype design environment is based on the nelsis cad framework and several tools from the synopsys high-level synthesis and simulation tool suite.
unit delay simulation with the inversion algorithm. the inversion algorithm is an event driven algorithm whose performance meets or exceeds that of levelized compiled code simulation, even when the activity rate is unrealistically high. existing implementations of the inversion algorithm are based on the zero delay model. this paper extends the algorithm to more realistic timing models. the main problems discussed in this paper are avoiding scheduling conflicts, and minimizing the amount of storage space. these problems are made considerably more difficult by the deletion of not gates and the collapsing of various connections. these optimizations transform the simulation into a multi-delay simulation under the transport delay model. a complete solution to the scheduling problem is presented under these conditions.
address generation for memories containing multiple arrays. this paper presents techniques for generating addresses for memories containing multiple arrays. because these techniques rely on the inversion or rearrangement of address bits, they are faster and require less hardware to compute than offset addition. use of these techniques can decrease effective access time to arrays and reduce address generation hardware. the primary drawback is that extra memory space is occasionally required by these techniques, but this extra memory space is on average only 4% and no worse than 25.2% of the utilized memory space. this amount of wasted address space is less than the amount required by similar techniques.
functional simulation using binary decision diagrams. in many verification techniques fast functional evaluation of a boolean network is needed. we investigate the idea of using binary decision diagrams (bdds) for functional simulation. the area-time trade-off that results from different minimization techniques of the bdd is discussed. we propose new minimization methods based on dynamic reordering that allow smaller representations with (nearly) no runtime penalty.
power-aware microsensor design. military microsensors are networked distributed embedded systems composed of a processor, a radio, and sensors used for personnel or vehicle detection. they are most often found in minefield replacement and perimeter security applications where size, weight, power, and cost requirements are quite challenging. in this paper, we discuss the different system design approaches used in microsensor systems and introduce a modular, scalable, power-aware microsensor architecture intended span the entire dynamic range required of these systems. we describe a reference implementation of this concept and results from field experiments.
theoretical and practical validation of combined bem/fem substrate resistance modeling. in mixed-signal designs, substrate noise originating from the digital part can seriously influence the functionality of the analog part. as such, accurately modeling the properties of the substrate as a noise-propagator is becoming ever more important. a model can be obtained through the finite element method (fem) or the boundary element method (bem). the fem performs a full 3d discretization of the substrate, which makes this method very accurate and flexible but also slow. the bem only discretizes the contact areas on the boundary of the substrate, which makes it less flexible, but significantly faster. a combination between bem and fem can be efficient when we need flexibility and speed at the same time. this paper briefly describes the bem and the fem and their combination, but mainly concentrates on the theoretical validation of the combined method and the experimental verification through implementation in the space layout to circuit extractor and comparison with commercial bem and fem tools.
embedded systems design for low energy consumption. this tutorial covers the circuit fundamentals of cmos circuits which contribute to the consumption of energy in portable products, as well as guidelines for the design of systems in order to reduce energy consumption and prolong battery life. circuit fundamentals will include a definition of terms, basic circuit elements, laws of operation, and basic circuit theory applying energy consumption. we will then present three major principles of energy reduction: reducing number of transitions, reducing the amount of switched capacitance, and reducing the operating voltage. several guidelines that can be applied during the system design process which utilize the three major principles.
on modeling top-down vlsi design. we present an improved data model that reflects the whole vlsi design process including bottom-up and top-down design phases. the kernel of the model is a static version concept that describes the convergence of a design. the design history which makes the semantics of most other version concepts, is modeled explicitly by additional object classes (entities types) but not by the version graph itself. top-down steps are modeled by splitting a design object into requirements and realizations. the composition hierarchy is expressed by a simple but powerful configuration method. design data of iterative refinement processes are managed efficiently by storing incremental data only.
lazy-expansion symbolic expression approximation in synap. a lazy-expansion technique for generating small approximate symbolic analog circuit analysis expressions is described. statistics for this technique as implemented in the symbolic analysis program synap are presented and show a two order-of-magnitude speed improvement (on larger circuits) as compared with traditional full-expansion techniques. this technique also allows larger circuits to be analyzed. methods used in synap for eliminating pole and zero movement at the design point and for handling variables representing device mismatches are also presented
test planning for the effective utilization of port-scalable testers for heterogeneous core-based socs. many socs contain embedded cores with different scan frequencies. to better meet the test requirements for such heterogeneous socs, leading tester companies have recently introduced port-scalable testers, which can simultaneously drive groups of channels at different data rates. however the number of tester channels available for scan testing is limited; therefore, a higher shift frequency can increase the test time for a core if the resulting test access architecture reduces the bitwidth used to access it. we present a scalable test planning technique that exploits port scalability of testers to reduce soc test time. we compare the proposed heuristic optimization method to two baseline methods based on prior work that use a single scan data rate for all the embedded cores.
tam optimization for mixed-signal socs using analog test wrappers. we present a new approach for tam optimization and testscheduling in the modular testing of mixed-signal socs. a testplanning approach for digital socs is extended to handle analogcores in a plug-and-play fashion. a test wrapper based on anadc/dac pair and a digital configuration circuit is designed foranalog cores such that these cores can be accessed through digitaltams. in this way, there is no dependence on an analog testbus and expensive mixed-signal testers. experimental results arepresented for several itc'02 soc test benchmarks to which threeanalog cores are added. the results show that the testing of analogcores can be interleaved with the testing of digital cores to reducethe overall testing time for a mixed-signal soc.
dynamic platform management for configurable platform-based system-on-chips. general-purpose system-on-chip platforms consistingof configurable components are emerging as an attractivealternative to traditional, customized solutions (e.g., asics,custom socs), owing to their flexibility, time-to-market advantage,and low engineering costs. however, the adoptionof such platforms in many high-volume markets (e.g, wirelesshandhelds) is limited by concerns about their performance andenergy-efficiency. this paper addresses the problemof enablingthe use of configurable platforms in domains where custom approacheshave traditionally been used. we introduce dynamicplatform management, a methodology for customizing a configurablegeneral-purpose platform at run-time, to help bridgethe performance and energy efficiency gap with custom approaches.the proposed technique uses a software layer that detectstime-varying processing requirements imposed by a set ofapplications, and dynamically optimizes architectural parametersand platform components. dynamic platform managementenables superior application performance, more efficient utilizationof platform resources, and improved energy efficiency,as compared to a statically optimized platform, without requiringany modifications to the underlying hardware.we illustrate dynamic platform management by applying itto the design of a dual-access umts/wlansecurity processingsystem, implemented on a general-purpose configurable platform.experiments demonstrate that, compared to a staticallyoptimized design (on the same platform), the proposed techniquesenable upto 33% improvements in security processingthroughput, while achieving 59% savings in energy consumption(on average).
a specified delay accomplishing clock router using multiple layers. clock routing to minimize the clock skew is very necessary to make high performance lsis. our clock routing method: (1) realizes the specified delay to each input terminal and provides a zero skew; (2) uses multiple routing layers for pin-to-pin routing; and (3) considers the delay arising from the resistance of a through-hole. experimental results show that the delay is within 1% error compared to the specified delay and the skew can be controlled within pico second order.
multi.objective hypergraph partitioning algorithms for cut and maximum subdomain degree minimization. in this paper we present a family of multi-objective hypergraphpartitioning algorithms based on the multilevel paradigm, whichare capable of producing solutions in which both the cut and themaximum subdomain degree are simultaneously minimized. thistype of partitionings are critical for existing and emerging applications in vlsi cad as they allow to both minimize and evenly distribute the interconnects across the physical devices. our experimental evaluation on the ispd98 benchmark show that ouralgorithms produce solutions that when compared against thoseproduced by hmetis have a maximum subdomain degree that isreduced by up to 35% while achieving comparable quality in terms of cut.
latch optimization in circuits generated from high-level descriptions. in a gate-level description of a finite state machine (\fsm), there is a tradeoff between the number of latches and the size of the logic implementing the next-state and output functions. typically, an initial implementation is generated via explicit state assignment or translation from a high-level language, and the tradeoff is subsequently only lightly explored. we efficiently explore good latch/logic tradeoffs for large designs generated from high-level specifications. we reduce the number of latches while controlling the logic size. we demonstrate the efficacy of our techniques on some large industrial examples.
optimal integration of inter-task and intra-task dynamic voltage scaling techniques for hard real-time applications. it is generally accepted that the dynamic voltage scaling (dvs) is one of the most effective techniques for energy minimization. according to the granularity of units to which voltage scaling is applied, the dvs problem can be divided into two subproblems: (i) inter-task dvs problem; and (ii) intra-task dvs problem. a lot of effective dvs techniques have addressed either one of the two subproblems, but none of them have attempted to solve both simultaneously, which is mainly due to an excessive computation complexity to solve it optimally. this work addresses this core issue, that is, can the combined problem be solved effectively and efficiently? more specifically, our work shows, for a set of inter-dependent tasks, that the combined dvs problem can be solved optimally in polynomial time. experimental results indicate that the proposed integrated dvs technique is able to reduce energy consumption by 10.6% on average over the results by (zhang et al., 2002 and seo et al., 2004) (i.e., a straightforward combination of two optimal inter- and intra task dvs techniques).
akord: transistor level and mixed transistor/gate level placement tool for digital data paths. this paper describes akord, a transistor level and mixed transistor/gate level placement tool. akord has unique layout capabilities that address the digital data path layout problem. in order to improve communication between the placement and routing steps, new post placement algorithms were developed: a device re-spacing procedure, an optimization procedure for gate contacts, and a procedure which reduces wire crossovers. akord supports dynamically: 1. transistor folding without usage of device libraries that contain variants of the same device; 2. device merging, including information about optimal transistor chain formation; and 3. well area minimization. experimental results show that the automated layouts are comparable to skilled manual layouts and that the computation times are quite modest.
exploiting level sensitive latches in wire pipelining. wire pipelining emerges as a new necessity for global wires due to increasing wire delay, shrinking clock period and growing chip size. existing approaches on wire pipelining are mostly based on edge triggered flip-flops. in this paper, we demonstrate the advantages of using level sensitive latches in terms of both latency and area cost. the input-output timing coupling and the strict short path constraint for latches demand additional design elaborations compared with flip-flops. new approaches are proposed in this work to solve these difficulties so that the advantages of latches can be fully utilized. in particular, a deferred delay padding technique is developed to correct short path violations with the minimal extra cost. these techniques are integrated with a dynamic programming based concurrent synchronous element and repeater insertion framework. experimental results confirm the advantages of using latches as well as effectiveness of our algorithms.
repeater insertion and wire sizing optimization for throughput-centric vlsi global interconnects. as technology advances towards billion transistor systems, the cost of complex wire networks will require area efficient wiring methodologies. this paper explores the tradeoffs between wire latency, throughput and area for deep submicron (dsm) interconnect technologies. from basic physical models, optimal wiring sizing for repeater networks are rigorously derived and compared to hspice simulations. key case studies from 250nm to 70nm technologies reveal that significant wire area reduction (20--50%) can be achieved with optimal wire sizing to maximize the throughput per unit wire area.
discrete vt assignment and gate sizing using a self-snapping continuous formulation. this paper presents a novel approach towards the simultaneous vt-assignment and gate-sizing problem. this inherently discrete problem is formulated as a continuous problem, allowing it to be solved using any of several widely available and highly efficient non-linear optimizers. we prove that, under our formulation, the optimal solution has discrete vts assigned to almost every gate, thus eliminating the need for a sophisticated snapping heuristic. we show that this technique performs dual-vt assignment and gate sizing in a very efficient manner. compared to a sensitivity based method, we achieve average leakage savings of 31% and average total power savings of 7.4% with very efficient runtimes.
macromodeling of analog circuits for hierarchical circuit design. hierarchy plays a significant role in the design of digital and analog circuits. at each level of the hierarchy it becomes essential to evaluate if a sub-block design is feasible and if so which design style is the best candidate for the particular problem. this paper proposes a general methodology for evaluating the feasibility and the performance of sub-blocks at all levels of the hierarchy. a modified simplicial approximation technique is used to generate the feasibility macromodel and a layered volume-slicing methodology with radial basis functions is used to generate the performance macromodel. however, due to lack of space, only details of the performance macromodeling techniques are included. macromodels are developed and verified for analog blocks at three different levels of hierarchy (current mirror, opamp, and a/d converter).
shaping interconnect for uniform current density. as the vlsi technology scaling down, the electromigration problem becomes one of the major concerns in high-performance ic design for both power network and signal interconnects. for a uniform width metal interconnect, the current flows through the driving point is much larger than that flows through the fan-out point since much of current bypasses to the ground through the parasitic capacitance. this causes the lifetime of driving point to be quite shorter than that of fan-out point due to electromigration. in order to avoid breakdown at the driving point, wire sizing is an effective solution. thus we present a wire shape, of which the current density as well as the lifetime is uniform along the wire. spice simulation results show the uniformity of current density of this wire shape. under the same current density bound, we demonstrate that chip area and power consumption are significantly reduced for this wire shape compared to the uniform width wire. the wire shape functions we derived are continuous. however, it is not necessary to ultra-accurately reproduce the continuous shape on the silicon, since we can round the continuous shape to the nearest available litho width and this will not degrade the uniformity of current density.
accurate cmos bridge fault modeling with neural network-based vhdl saboteurs. this paper presents a new bridge fault model that is based on a multiple layer feedforward neural network and implemented within the framework of a vhdl saboteur cell. empirical evidence and experimental results show that it satisfies a prescribed set of bridge fault model criteria better than existing approaches. the new model computes exact bridged node voltages and propagation delay times with due attention to surrounding circuit elements. this is significant since, with the exception of full analog simulation, no other technique attempts to model the delay effects of bridge defects. yet, compared to these analog simulations, the new approach is orders of magnitude faster and achieves reasonable accuracy; computing bridged node voltages with an average error near 0.006 volts and propagation delay times with an average error near 14 ps.
expanding the frequency range of awe via time shifting. the new technique of time shifted moment matching (tsmm) is introduced in this paper. the tsmm technique performs moment matching (for expansion around s = 0) on a time-shifted version of the original signal. as compared to other well-known techniques (such as awe by pillage and rohrer, 1990), tsmm offers distinct advantages. the 50% delay and rise time are determined with much more accuracy for a given approximation order. moreover, the solutions have significantly improved accuracy as compared to awe, especially for moderate to highly inductive signals. tsmm is able to achieve the approximation capability of pvl (feldmann and freund, 1995) and prima (odabasioglu et al., 1998) with much lower approximation order.
branch merge reduction of rlcm networks. in this paper we consider the problem of finding asmaller rlcm circuit that approximately replicates thebehavior (up to a certain frequency) of a given rlcm circuit.targeted at parasitic extractors for verification of vlsidesigns, the proposed algorithm uses a branch merge, nodeelimination methodology, with the choice of nodes forelimination being guided by time-constant criteria.reliable,accurate, easy to code, the algorithm works well for coupledbuses and clocks, strongly inductive networks, and low-losstransmission lines, as well as for lossy rlc networks.
ticer: realizable reduction of extracted rc circuits. time constant equilibration reduction (ticer) is a novel rc reduction method tailored for extract/reduce cad tools. geometry-minded extraction tools fracture nets into parasitics based on local changes in geometry. the resulting rc circuits can have a huge dynamic range of time-constants; by eliminating the extreme time-constants, ticer produces smaller, less-stiff rc networks. it produces realizable rc circuits; can retain original network topology; scales well to large networks (~107 nodes); preserves dc and ac behavior; handles resistor loops and floating capacitors; has controllable accuracy; operates in linear time on most nets.
equivalence verification of polynomial datapaths with fixed-size bit-vectors using finite ring algebra. this paper addresses the problem of equivalence verification of rtl descriptions. the focus is on datapath-oriented designs that implement polynomial computations over fixed-size bit-vectors. when the size (m) of the entire datapath is kept constant, fixed-size bit-vector arithmetic manifests itself as polynomial algebra over finite integer rings of residue classes z/sub 2//sup m/. the verification problem then reduces to that of checking equivalence of multi-variate polynomials over z/sub 2//sup m/. this paper exploits the concepts of polynomial reducibility over z/sub 2//sup m/ and derives an algorithmic procedure to transform a given polynomial into a unique canonical form modulo 2/sup m/. equivalence testing is then carried out by coefficient matching. experiments demonstrate the effectiveness of our approach over contemporary techniques.
recursive bipartitioning of bdds for performance driven synthesis of pass transistor logic circuits. in this paper, we address the problem of performance oriented synthesis of pass transistor logic (ptl) circuits using a binary decision diagram (bdd) decomposition technique. we transform the bdd decomposition problem into a recursive bipartitioning problem and solve the latter using a max-flow min-cut technique. we use the area and delay cost of the ptl implementation of the logic function to guide the bipartitioning scheme. using recursive bipartitioning and a one-hot multiplexer circuit, we show that our ptl implementation has logarithmic delay in the number of inputs, under certain assumptions. the experimental results on benchmark circuits are promising, since they show the significant delay reductions with small or no area overheads as compared to previous approaches.
on average power dissipation and random pattern testability of cmos combinational logic networks. the implications of the observation that the probability of the occurrence of a transition on a wire of a circuit affects both the average power dissipation and the random pattern testability of a circuit are investigated. it is shown that restructuring a logic circuit can significantly affect its average power dissipation. various methods for the synthesis of combinational logic networks are presented and the effect of different algorithms on the power dissipation of the circuit is demonstrated. the dual problem of improving the random pattern testability of logic circuits is emphasized. it is shown that modifying the signal probabilities can significantly affect the random pattern testability of a circuit
reversible logic circuit synthesis. reversible or information-lossless circuits have applications in digital signal processing, communication, computer graphics and cryptography. they are also a fundamental requirement in the emerging field of quantum computation. we investigate the synthesis of reversible circuits that employ a minimum number of gates and contain no redundant input-output line-pairs (temporary storage channels). we prove constructively that every even permutation can be implemented without temporary storage using not, cnot and toffoli gates. we describe an algorithm for the synthesis of optimal circuits and study the reversible functions on three wires, reporting distributions of circuit sizes. finally, in an application important to quantum computing, we synthesize oracle circuits for grover's search algorithm, and show a significant improvement over a previously proposed synthesis algorithm.
graph algorithms for clock schedule optimization. for performance-driven synthesis of sequential circuits, the optimal clocking problem is considered, and it is shown that it is reducible to a parametric shortest path problem. constraints are used that take into account both the short and long paths. the main contributions are efficient graph algorithms to solve the set of constraints necessary for correct clocking
efficient implementation of retiming. retiming is a technique for optimizing sequential circuits. it repositions the registers in a circuit leaving the combinational cells untouched. the objective of retiming is to find a circuit with the minimum number of registers for a specified clock period. more than ten years have elapsed since leiserson and saxe first presented a theoretical formulation to solve this problem for single-clock edge-triggered sequential circuits. their proposed algorithms have polynomial complexity; however naive implementations of these algorithms exhibit o(n3) time complexitiy and o(n2) space complexity when applied to digital circuits with n combinational cells. this renders retiming ineffective for circuits with more than 500 combinational cells. this paper addresses the implementation issues required to exploit the sparsity of circuit graphs to allow min-period retiming and constrained min-area retiming to be applied to circuits with as many as 10,000 combinational cells. we believe this is the first paper to address these issues and the first to report retiming results for large circuits.
body-voltage estimation in digital pd-soi circuits and its application to static timing analysis. we describe a technique for estimating the floating body potentials of partially-depleted silicon-on-insulator (pd-soi) circuits under steady switching activity and under initial activity after a long period of quiescence. the approach is based on a unique state diagram abstraction of the pd-soi fet that captures all of the essential device physics. this picture yields a simple analytic model of the body voltage which is used within the context of a prototype transistor-level static timing analysis engine. results are presented that demonstrate the accuracy of the analytic body-voltage model and the reduction in delay uncertainty possible with this technique.
noise in deep submicron digital design. as technology scales into the deep submicron regime, noise immunity is becoming a metric of comparable importance to area, timing, and power for the analysis and design of vlsi systems. this paper defines noise as it pertains to digital systems and addresses the technology trends which are bringing noise issues to the forefront. the noise sources which are plaguing digital systems are explained. a metric referred to as noise stability is defined, and a static noise analysis methodology based on this metric is introduced to demonstrate how noise can be analyzed systematically. analysis issues associated with on-chip interconnect are also considered. this paper concludes with a discussion of the device, ciruit, layout, and logic design issues associated with noise.
global harmony: coupled noise analysis for full-chip rc interconnect networks. noise is becoming one of the most important metrics in the design of vlsi systems, certainly of comparable importance to area, timing, and power. in this paper, we describe global harmony, a methodology for the analysis of coupling noise in the global interconnect of large vlsi chips, being developed for the design of high-performance microprocessors. the architecture of global harmony involves a careful combination of static noise analysis, static timing analysis, and reduced-order modelling techniques. we describe a reduced-order modelling approach that allows for passive multiport reduction of rc netlists as impedance macromodels while preserving the symmetry and sparsity of the state matrices for efficient storage. we describe how the macromodels are practically employed to perform coupling analysis and how timing constraints can be used to limit pessimism in the analysis.
full-chip, three-dimensional, shapes-based rlc extraction. in this paper, we report the development of the first commercial full-chip, three-dimensional, shapes-based, rlck extraction tool, developed as part of a university-industry collaboration. the technique of return-limited inductances is used to provide a sparse, frequency-independent inductance and resistance network with self-inductances that represent sensible "nominal" values in the absence of mutual coupling. mutual inductances are extracted for accurate noise analysis. the tool, assura rlcx, exploits high-capacity scan-band techniques and disk caching for inductance extraction as an extension to cadence's existing assura rcx extractor.
spin-test: automatic test pattern generation for speed-independent circuits. spin-test is a simulation-based gate-level atpg system for speed-independent circuits. its core engine is an a* search algorithm which employs an accurate fault simulator and an efficient cost function to guide a deterministic test pattern generation phase. a random test pattern generation phase is also available in order to improve run time. the key atpg challenge in speed-independent circuits is the generation of patterns that are valid independently of the relative timing and the order of arrival of signals. spin-test addresses this challenge by guaranteeing fault sensitization with hazard/race-free patterns and response observation that is not affected by oscillations or non-deterministic circuit states. experimental results on benchmark circuits demonstrate the efficiency of spin-test in terms of both high fault coverage and low test generation time.
symbolic analysis of large analog circuits with determinant decision diagrams. symbolic analog-circuit analysis has many applications, and is especially useful for analog synthesis and testability analysis. in this paper, we present a new approach to exact and canonical symbolic analysis by exploiting the sparsity and sharing of product terms. it consists of representing the symbolic determinant of a circuit matrix by a graph---called determinant decision diagram (ddd)---and performing symbolic analysis by graph manipulations. we showed that ddd construction and ddd-based symbolic analysis can be performed in time complexity proportional to the number of ddd vertices. we described a vertex ordering heuristic, and showed that the number of ddd vertices can be quite small --- usually orders-of-magnitude less than the number of product terms. the algorithm has been implemented. an order-of-magnitude improvement in both cpu time and memory usages over existing symbolic analyzers isaac and maple-v has been observed for large analog circuits.
software synthesis through task decomposition by dependency analysis. latency tolerance is one of main problems of software synthesis in the design of hardware-software mixed systems. this paper presents a methodology for speeding up systems through latency tolerance which is obtained by decomposition of tasks and generation of an efficient scheduler. the task decomposition process focuses on the dependency analysis of system i/o operations. scheduling of the decomposed tasks is performed in a mixed static and dynamic fashion. experimental results show the significance of our approach.
power optimization of real-time embedded systems on variable speed processors. power efficient design of real-time embedded systems based on programmable processors becomes more important as system functionality is increasingly realized through software. this paper presents a power optimization method for real-time embedded applications on a variable speed processor. the method combines off-line and on-line components. the off-line component determines the lowest possible maximum processor speed while guaranteeing deadlines of all tasks. the on-line component dynamically varies the processor speed or bring a processor into a power-down mode according to the status of task set in order to exploit execution time variations and idle intervals. experimental results show that the proposed method obtains a significant power reduction across several kinds of applications.
decomposition methods for library binding of speed-independent asynchronous designs. we describe methods for decomposing gates within a speed-independent asynchronous design. the decomposition step is an essential part of the library binding process, and is used both to increase the granularity of the design for higher quality mapping and to ensure that the design can be implemented. we present algorithms for simple hazard-free gate decomposition, and show results which indicate that we can decompose most of the gates in our benchmark set by this simple method. we then extend these algorithms to work for those cases in which no simple decomposition exists.
a coordinate-transformed arnoldi algorithm for generating guaranteed stable reduced-order models of rlc circuits. since the first papers on asymptotic waveform evaluation (awe), pade-based reduced order models have become standard for improving coupled circuit-interconnect simulation efficiency. such models can be accurately computed using bi-orthogonalization algorithms like pade via lanczos (pvl), but the resulting pade approximates can still be unstable even when generated from stable rlc circuits. for certain classes of rc circuits it has been shown that congruence transforms, like the arnoldi algorithm, can generate guaranteed stable and passive reduced-order models. in this paper we present a computationally efficient model-order reduction technique, the coordinate-transformed arnoldi algorithm, and show that this method generates arbitrarily accurate and guaranteed stable reduced-order models for rlc circuits. examples are presented which demonstrates the enhanced stability and efficiency of the new method.
a novel scan architecture for power-efficient, rapid test. scan-based testing methodologies remedy the testability problem of sequential circuits; yet they suffer from prolonged test time and excessive test power due to numerous shift operations. the high density of the unspecified bits in test data enables the utilization of the test response data captured in the scan chain for the generation of the subsequent test stimulus, thus reducing both test time and test data volume. the proposed scan-based test scheme accesses only a subset of scan cells for loading the subsequent test stimulus while freezing the remaining scan cells with the response data captured, thus decreasing the scan chain transitions during shift operations. the experimental results confirm the significant reductions in test application time, test data volume and test power achieved by the proposed scan-based testing methodology.
partial core encryption for performance-efficient test of socs. the isolation of a core through full i/o scan helps ease soc test challenges;yet the performance of high-speed socs is significantly hampered.we propose a partial core encryption methodology wherein thecore vendor unveils only a small part of the core logic, successfully satisfyingcore ip protection requirements. once the partially encryptedcores are merged into an soc, the system integrator performs test generationon the visible soc logic only, greatly reducing the test generationeffort expended. by utilizing the test data provided by the core vendoras well, the soc integrator can test the soc with no performancedegradation. we present an efficient fault analysis based core encryptionalgorithm which is guided by judiciously computed testability measures.the experimental results confirm the significantly high encryption levelsattained by the proposed encryption algorithm.
interface specification for reconfigurable components. this paper presents a way of encoding some kinds of dynamic reconfiguration behaviour in the interface portion of circuit descriptions. this has many advantages. the user of a reconfigurable circuit has some knowledge about the reconfigurable interface of the circuit. static analysis tools can make better decisions about how to schedule virtual hardware. and most importantly the compiler can automatically synthesize the required interface between reconfigurable portions of the system and the regular portions of the design. several existing models of dynamic reconfiguration from the literature are captured using our type system extension based on sum types. this is especially important in system-on-chip (soc) contexts where a reconfigurable ip block may have to communicate over a non-trivial ip bus like coreconnect&trade;.
incremental placement for layout driven optimizations on fpgas. this paper presents an algorithm to update the placement of logic elements when given an incremental netlist change. specifically, these algorithms are targeted to incrementally place logic elements created by layout-driven circuit restructuring techniques. the incremental placement engine assumes that the restructuring algorithms provide a list of new logic elements along with preferred locations for each of these new elements. it then tries to shift non-critical logic elements in the original placement out of the way to satisfy the preferred location requests. our algorithm considers modern fpga architectures with clustered logic blocksthat have numerous architectural constraints. experiments indicate that our technique produces results of extremely highquality.
statistical technology mapping for parametric yield. the increasing variability of process parameters leads to substantial parametric yield losses due to timing and leakage power constraints. leakage power is especially affected by variability because of its exponential dependence on the highly varying transistor channel length and threshold voltage. this paper describes the new technology mapping algorithm that performs library binding to maximize parametric yield limited both by timing and power constraints. this is the first work that rigorously treats variability in circuit leakage power and delay within logic synthesis. experiments show that moving the concerns about variability into logic synthesis is justified. the results on industrial and public benchmarks indicate that, on avenge, the reduction in stand-by power can be up to 26% and can be as high as 50% for some benchmarks. the reduction is purely due to a more effective decision-making of the mapping algorithm, and is achieved without a timing parametric yield loss. alternatively, the algorithm leads to the delay reduction of up to 17%, with a 10% avenge possible reduction across the benchmarks, for stringent leakage constraints at a fixed yield level. parametric yield at a fixed leakage target can also be substantially increased. in some examples, the statistical mapper leads to a 80% yield at the leakage value for which the deterministic mapper guaranteed only a 50% yield.
interconnect resource-aware placement for hierarchical fpgas. in this paper, we utilize rent's rule as an empirical measure for efficient clustering and placement of circuits on hierarchical fpgas. we show that careful matching of design complexity and architecture resources of hierarchical fpgas can have a positive impact on the overall device area. we propose a circuit placement algorithm based on rent's parameter and show that our clustering and placement techniques can improve the overall device routing area by as much as 21% for the same array size, when compared to a state-of-art fpga placement and routing tool.
extracting rtl models from transistor netlists. this paper addresses the problem of deriving a register-transfer level (rtl) model from a transistor-level circuit. using existing techniques, the transistor-level circuit is converted into a relation that describes the evolution of the signals in the circuit with respect to the simulator clock. this simulation relation is then manipulated to derive the stable behavior of the circuit. given this stable behavior and information about the clocking scheme, we determine if the circuit is combinational, asynchronous or synchronous. for combinational and synchronous circuits we derive an equivalent register-transfer level model. this development enables full-custom circuit designers to use tools that were till now available only to designers working at the gate-level. the algorithm has been successfully used to characterize several custom designs, as well as the entire at&t standard-cell library.
path delay estimation using power supply transient signals: a comparative study using fourier and wavelet analysis. transient signal analysis (tsa) is a parametric device testingtechnique based on the analysis of dynamic (transient) current(i{ddt}) drawn by the core logic from the power supply pads in acmos digital circuit. in previous work, we develop a test procedurethat can be used both to detect signal variations caused bydefects and to obtain delay information in defect free chips. phasespectra of transient signals obtained using discrete fourier transformare shown to track path delays of defect-free chips under awide range of process variations. however, in recent work, wewere able to demonstrate through simulation experiments incorporatingdeep submicron transistor models, a circuit design andpath sensitization scenario in which our existing tsa method isnot able to yield accurate predictions of path delays. more specifically,a circuit composed of two inverter chains constructed withwidely varying transistor sizes was shown to produce path delaysthat were weakly correlated across a set of worst case processmodels. in this paper, an alternative wavelet-based analysis ofi{ddt} waveforms is shown to improve the accuracy of predictingmultiple path delays under these conditions.
fast timing closure by interconnect criticality driven delay relaxation. due to decreasing transistor sizes and increasing clock frequency, interconnect delay is a dominant factor in achieving timing closure in deep sub-micron designs. techniques like wire pipelining and retiming can manage delay of timing critical wires. the latency of the system, however, limits the total pipelining in the design. new techniques are, thus, needed at synthesis stage to consider the effect of critical wires in the design. in this work, we propose a novel intuitive algorithm, critical edge reduction (cer) algorithm, which produces a maximal delay budgeting solution under fixed latency while minimizing the number of critical wires. we also present an in-depth analysis of trade-off between maximum budgeting and critical edge minimization. we implemented our design flow using a set of mediabench data paths on xilinx virtexe fpga devices. using our algorithm, the xilinx place and route tool achieved timing closure, on average, 2.8 times faster than using maximum budgeting. the resulting average clock period using cer algorithm outperforms the one using maximum budgeting by 6%.
the case for retiming with explicit reset circuitry. retiming is often used to optimize synchronous sequential circuits for area or delay or both. if the latches that are retimed have a hardware reset value, the initial state of the circuit must also be retimed, i.e. an initial state must be derived for the retimed circuit. previously, it has been suggested that this can be avoided if the hardware reset signals are represented explicitly. however, it was thought that this adds unnecessary area and restricts the space of possible retimings. in this paper we demonstrate that this is not the case. in addition, we show that this methodology does not require the restriction that all reset signals be asserted at the beginning of circuit operation--- a restriction that was imposed by existing algorithms for determining the retimed initial state. finally we show how our explicit reset (er) framework enables us to retime when some latches may be driven by different hardware resets, and some others may not have any hardware resets. we also consider the case where the resets are asynchronous. we expect these solutions to the "retimed initial state" problem to help increase the practical applicability of retiming.
energy efficient real-time scheduling. real-time scheduling on processors that support dynamic voltage and frequency scaling is analyzed. the slacked earliest deadling first (sedf) algorithm is proposed and it is shown that the algorithm is optimal in minimizing processor energy consumption and maximum lateness. an upper bound on the processor energy savings is also derived. real-time scheduling of periodic tasks is also analyzed and optimal voltage and frequency allocation for a given task set is determined that guarantees schedulability and minimizes energy consumption.
validation and test generation for oscillatory noise in vlsi interconnects. inductance of on-chip interconnects gives rise to signal overshoots and undershoots that can cause logic errors. by considering technology trends, we show that in 0.13 &mgr;m technology such noise in local interconnects embedded in combinational logic can exceed the threshold voltage. we show the impact of such noise on different kinds of circuits. the magnitude of this noise can increase due to process variations. we present an algorithm for generating vectors for validation and manufacturing test to detect logic-value errors caused by inductance induced oscillation. to faciliate the vector generation method, we have derived analytical expressions, as functions of rise and fall times for (i) the magnitude of overshoots and undershoots, and (ii) the settling time, i.e., the time required for the circuit response to settle to a bound close to the final value.
sequential spfds. spfds are a mechanism to express flexibility in boolean networks. introduced by yamashita et al. in the context of fpga synthesis [4], they were extended later to general combinational networks [2]. we introduce the concept of sequential spfds and provide an algorithm to compute them based on a partition of the state bits. the spfds of each component in the partition are used to generate equivalence classes of states. we provide a formal relation between the resulting state classification and the equivalence classes produced by classical state minimization of completely specified machines [6]. the spfds associated with the state bits can be applied for re-encoding the state space. for this, we give an algorithm to re-synthesize the sequential circuit using sequential spfds and the new state re-encoding.
topologically constrained logic synthesis. spfds, a mechanism for expressing flexibility during logic synthesis, were first introduced for fpga synthesis. they were then extended to general, combinational boolean networks and later the concept of sequential spfds was introduced. in this paper, we explore the idea of using spfds for functional decomposition. a new type of functional decomposition called topologically constrained decomposition is introduced. an algorithm is provided for solving this problem using spfds. preliminary experimental results are encouraging and indicate the feasibility of the approach. a scheme is also presented for generating instances of the topologically constrained decomposition problem.
statistical gate sizing for timing yield optimization. variability in the chip design process has been relatively increasing with technology scaling to smaller dimensions. using worst case analysis for circuit optimization severely over-constrains the system and results in solutions with excessive penalties. statistical timing analysis and optimization have consequently emerged as a refinement of the traditional static timing approach for circuit design optimization. in this paper, we propose a statistical gate sizing methodology for timing yield improvement. we build statistical models for gate delays from library characterizations at multiple process corners and operating conditions. statistical timing analysis is performed, which drives gate sizing for timing yield optimization. experimental results are reported for the iscas and mcnc benchmarks. in addition, we provide insight into statistical properties of gate delays for a given technology library which intuitively explains when and why statistical optimization improves over static timing optimization.
gate sizing for crosstalk reduction under timing constraints by lagrangian relaxation. this work presents a post-route, timing-constrained gate-sizing algorithm for crosstalk reduction. gate-sizing has emerged as a practical and feasible method to reduce crosstalk in deep sub-micron vlsi circuits. it is however critical to ensure that the timing constraints of the circuit are not violated after sizing. we present an iterative gate-sizing algorithm for crosstalk reduction based on lagrangian relaxation that optimizes area and power while ensuring that the given timing constraints are met. experimental results demonstrating the effectiveness of the algorithm are reported for the iscas benchmarks and other large circuits with comparisons to an alternative design methodology.
a unified framework for statistical timing analysis with coupling and multiple input switching. as technology scales to smaller dimensions, increasing process variations, coupling induced delay variations and multiple input switching effects make timing verification extremely challenging. in this paper, we establish a theoretical framework for statistical timing analysis with coupling and multiple input switching. we prove the convergence of our proposed iterative approach and discuss implementation issues under the assumption of a gaussian distribution for the parameters of variation. a statistical timer based on our proposed approach is developed and experimental results are presented for the is-cas benchmarks. we juxtapose our timer with a single pass, non iterative statistical timer that does not consider the mutual dependence of coupling with timing and another statistical timer that handles coupling deterministically. monte carlo simulations reveal a distinct gain (up to 24%) in accuracy by our approach in comparison to the others mentioned.
implicit treatment of substrate and power-ground losses in return-limited inductance extraction. full-wave analysis, based on rigorous solution of the differential or integral form of maxwell's equations, is too slow for all but the smallest designs. traditional on-chip extraction engines are, therefore, being pushed to extract inductance and provide accurate high-frequency interconnect modelling while maintaining computational efficiency and capacity. this paper describes further accuracy-improving enhancements to the commecial full-chip rlck extraction engine, assura rlcx[1], based on the return-limited inductance formulation. specifically, we incorporate substrate losses due to eddy currents and power-ground losses while, based on design-driven assumptions, avoiding explicit extraction of the power-ground and substrate. results are validated on small testcases where comparison with full-wave solution is practical.
delay fault coverage: a realistic metric and an estimation technique for distributed path delay faults. in this paper, we propose a new and realistic definition of delay fault coverage, based on the percentage of fabricated faulty chips which can be detected as faulty by a given test set. this metric takes into account the probability distribution of delay fault sizes caused by fabrication process effects, as opposed to previously defined metrics which have been based primarily on the percentage of faults tested. in addition to proposing a realistic delay fault coverage metric, we also present a computationally viable scheme for using this metric to estimate the coverage of any given test set for a class of path delay faults caused by distributed fabrication process variations. we use the results for the iscas'89 benchmark circuits to demonstrate wide discrepancies between distributed path delay fault coverage estimates for robust test sets obtained using our realistic definition, and the ones obtained by using the traditional notion of coverage as the percentage of paths tested.
timing analysis based on primitive path delay fault identification. we present a novel timing analysis mechanism which is based on identifying primitive path delay faults (primitive pdfs) in a circuit. we show that this approach gives the exact maximum delay of the circuit under the floating mode of operation assumption. our timing analysis approach provides a framework where component delay correlations and signal correlations arising from fabrication process, signal propagation, and signal interaction effects can be handled very accurately. under these effects, timing analysis using previously reported floating mode timing analyzers, e.g., viability, trued-f etc., is very pessimistic. our timing analysis approach based on primitive pdf identification is also more efficient than conventional floating mode path sensitization analysis mechanisms in situations where critical paths need to be re-identified due to component delay speedup (e.g., post-layout delay optimization). we demonstrate the applicability of our timing analysis approach for a variety of benchmark circuits, and demonstrate the pessimism of conventional floating mode timing analysis approaches in accounting for signal propagation effects.
extraction of circuit models for substrate cross-talk. an increasingly urgent topic for the realization of densely packed (mixed signal) integrated circuits is prevention of cross-talk via the substrate. this paper proposes a boundary element method (bem) for calculating an admittance matrix for the substrate in order to analyze the parasitic coupling during layout verification.in contrast with standard be methods, we propose a green's function which is specific to the domain and the problem. this allows minimal discretization and a direct extraction of circuit models for the cross-talk. the extraction can be combined with an efficient model reduction technique to obtain more simple, yet accurate models for the cross-talk. the complete extraction process has a linear time complexity and a constant memory usage. the method is fully implemented and integrated in an existing layout-to-circuit extractor.
a new surface integral formulation for wideband impedance extraction of 3-d structures. detailed electromagnetic analysis of three-dimensional structures in multi-layereddielectric media is critical for automatic generation of equivalentcircuit models for the interconnects and packages in rf or mixed signalintegrated circuits. in this paper we present a new wideband surface integralformulation that can be readily combined with the well-establishedlayered green's function techniques. in discretizing the formulation, wehave used the well-known rwg linear basis function to reduce the numberof unknowns. using a so-called loop-star basis transformation andthe frequency normalization, the accuracy at low frequencies has beenimproved substantially. several numerical examples are used to validatethe accuracy and robustness of this new formulation.
maze router without a grid map. it is pointed out that maze routers provide powerful and flexible routing algorithms, but require storage of information for every routing grid and layer. the number of these grids is often so large that routing programs either run out of memory or become very slow due to excessive paging. a data organization which, with certain modifications to the algorithm, reduces and possibly eliminates the entire grid map is presented. the router has been coded with a special data structure library
retiming with non-zero clock skew, variable register, and interconnect delay. a retiming algorithm is presented which includes the effects of variable register, clock distribution, and interconnect delay. these delay components are incorporated into retiming by assigning register electrical characteristics (recs) to each edge in the graph representation of the synchronous circuit. a matrix (called the sequential adjacency matrix or sam) is presented that contains all path delays. timing constraints for each data path are derived from this matrix. vertex lags are assigned ranges rather than single values as in standard retiming algorithms. the approach used in the proposed algorithm is to initialize these ranges with unbounded values and continuously tighten these ranges using localized timing constraints until an optimal solution is obtained. the algorithm is demonstrated on modified mcnc benchmark circuits and both increased clock frequencies and elimination of all race conditions are observed.
eda and the network. digital computer networks are playing an increasingly important role in the evaluation, distribution, integration and management of eda systems. tools, libraries, design data, and a variety of both design and manufacturing services are accessible today via networks. networks are also playing a central role in the integration of system design teams, teams that involve a variety of both business and technical disciplines as well as widely distributed geographical locations. throughout the history of eda, the architectures used to integrate and distribute computation and interaction have played a central role in the overall design methodology and so have had a major, indirect impact on the choice of the most effective tools, algorithms, and data structures. in this paper, a number of the factors involved in the choice of a suitable architecture for eda integration are reviewed and a number of ongoing developments and challenges are presented.
an automated technique for topology and route generation of application specific on-chip interconnection networks. network-on-chip (noc) has been proposed as a solution to the communication challenges of system-on-chip (soc) design in nanoscale technologies. application specific soc design offers the opportunity for incorporating custom noc architectures that are more suitable for a particular application, and do not necessarily conform to regular topologies. custom noc design in nanoscale technologies must address performance requirements, power consumption and physical layout considerations. this paper presents a novel three phase technique that i) generates a performance aware layout of the soc, ii) maps the cores of the soc to routers, and iii) generates a unique route for every trace that satisfies the performance and architectural constraints. we present an analysis of the quality of the results of the proposed technique by experimentation with realistic benchmarks.
improving soft-error tolerance of fpga configuration bits. soft errors that change configuration bits of an sram based fpga modify the functionality of the design. the proliferation of fpga devices in various critical applications makes it important to increase their immunity to soft errors. in this work, we propose the use of an asymmetric sram (asram) structure that is optimized for soft error immunity and leakage when storing a preferred value. the key to our approach is the observation that the configuration bitstream is composed of 87% of zeros across different designs. consequently, the use of asram cell optimized for storing a zero (asram-0) reduces the failure in time by 25% as compared to the original design. we also present an optimization that increases the number of zeros in the bitstream while preserving the functionality.
detailed layer assignment for mcm routing. a routing environment mode, called the k-mcm model, is developed to take into account the unique features of a multilayer multichip module (mcm) such as the availability of segmented vias, and the presence of two active or terminal-bearing layers. a detailed layer assignment problem is formulated on the k-mcm model. a fast heuristic algorithm for the layer assignment problem is proposed and experimental results on twelve test examples with net counts up to 842 are presented
performance analysis of carbon nanotube interconnects for vlsi applications. the work in this paper analyses the applicability of carbon nanotube (cnt) bundles as interconnects for vlsi circuits, while taking into account the practical limitations in this technology. a model is developed to calculate equivalent circuit parameters for a cnt-bundle interconnect based on interconnect geometry. using this model, the performance of cnt-bundle interconnects (at local, intermediate and global levels) is compared to copper wires of the future. it is shown that cnt bundles can outperform copper for long intermediate and global interconnects, and can be engineered to compete with copper for local level interconnects. the technological requirements necessary to make cnt bundles viable as future interconnects are also laid out.
timing driven gate duplication: complexity issues and algorithms. this paper addresses the issue of timing driven gate duplication for delay optimization. gate duplication has been used extensively for cutset minimization but the usefulness in minimizing the circuit delay has not been addressed. this paper studies the complexity issues in timing driven gate duplication and proposes an algorithm for solving the so called global gate duplication problem. delay improvements over highly optimized results from sis have been reported.
achieving design closure through delay relaxation parameter. current design automation methodologies are becoming incapableof achieving design closure especially in the presence of deep submicroneffects. this paper addresses the issue of design closure from ahigh level point of view. a new metric called delay relaxation parameter(drp) for rtl (register transfer level) designs is proposed. drpessentially captures the degree of delay relaxation that the design cantolerate without violating the clock constraint. this metric when optimizedresults in quicker design flow. algorithms to optimize drp areformulated and their optimality are investigated. experimental resultsare conducted using a state of the art design flow with synopsys designcompiler followed by cadence place and route. our approachof optimizing drp resulted in lesser design iterations and faster designclosure as compared to designs generated through synopsys behavioralcompiler and a representative academic design flow.
predictability: definition, ananlysis and optimization. predictability is the quantified from of accuracy. we propose a predictability driven design methodology. the novelty lies in defining and using the idea of predictability. in order to illustrate the basic concepts we focus on the low power binding problem. the binding problem for low power was solved in [3], [5], but in the presence of in-accuracies, their claims of optimality are imprecise. our experiments show that these inaccuracies could be as high as 33%. our methodology could improve this unpredictability to as low as 11% with minimal power penalty (7% on average).
a general framework for probabilistic low-power design space exploration considering process variation. increasing levels of process variation in current process technologies make it extremely important that design and process decisions be made while considering their impact. this work presents a convex optimization based approach to select supply and threshold voltages to minimize power dissipation in generic multi-vdd/vth cmos designs while considering process variation. we use this probabilistic approach to compare the optimization of different statistical parameters of power dissipation (e.g., mean or high percentile points), and quantify the impact of rising process variations on these power minimization techniques.
binding, allocation and floorplanning in low power high-level synthesis. this work is a contribution to high level synthesis for lowpower systems.while device feature size decreases, interconnectpower becomes a dominating factor.thus it is importantthat accurate physical information is used during high-level synthesis.we propose a new power optimisation algorithm for rt-levelnetlists.the optimisation performs simultaneously slicing-treestructure-based floorplanning and functional unit binding andallocation.since floorplanning, binding and allocation can use theinformation generated by the other step, the algorithm can greatlyoptimise the interconnect power.compared to interconnect unawarepower optimised circuits, it shows that interconnect powercan be reduced by an average of 41.2%, while reducing overallpower by 24.1% on an average.the functional unit power remainsnearly unchanged.these optimisations are not achieved atthe expense of area.
dynamic fault-tolerance and metrics for battery powered, failure-prone systems. emerging vlsi technologies and platforms are giving rise tosystems with inherently high potential for runtime failure.such failures range from intermittent electrical and mechanicalfailures at the system level, to device failures at the chip level.techniques to provide reliable computation in the presence offailures must do so while maintaining high performance, withan eye toward energy efficiency. when possible, they shouldmaximize battery lifetime in the face of battery discharge non-linearities. this paper introduces the concept of adaptive fault-tolerance management for failure-prone systems, and a classification of local algorithms for achieving system-wide reliability.in order to judge the efficacy of the proposed algorithmsfor dynamic fault-tolerance management, a set of metrics, forcharacterizing system behavior in terms of energy efficiency,reliability, computation performance and battery lifetime, ispresented. for an example platform employed in a realistic evaluation scenario, it is shown that system configurations with the best performance and lifetime are not necessarilythose with the best combination of performance, reliability,battery lifetime and average power consumption.
digital rf processor (drp/spl trade/) for cellular phones. rf circuits for multi-ghz frequencies have recently migrated to low-cost digital deep-submicron cmos processes. unfortunately, this process environment, which is optimized only for digital logic and sram memory, is extremely unfriendly for conventional analog and hf designs. we present fundamental techniques recently developed that transform the rf and analog circuit design complexity to digital domain for a wireless rf transceiver, so that it enjoys the benefits of digital approach, such as process node scaling and design automation. all-digital phase locked loop, all-digital control of phase and amplitude of a polar transmitter, and direct hf sampling techniques allow great flexibility in reconfigurable radio design. digital signal processing concepts are used to help relieve analog design complexity, allowing one to reduce cost and power consumption in a reconfigurable design environment. software layers are defined to enable these architectures to develop an efficient software defined radio. vhdl hardware description language is universally used throughout this soc. the ideas presented have been used in texas instruments to develop two generations of commercial digital rf processors: a single-chip bluetooth radio and a single-chip gsm radio.
analog performance space exploration by fourier-motzkin elimination with application to hierarchical sizing. analog performance space exploration identifies the range of feasible performance values of a given circuit topology. it is an extremely challenging task of great importance to topology selection and hierarchical sizing. in this paper, a novel technique for the efficient simulation-based exploration of high-dimensional performance spaces is presented. to this end, fundamental circuit design knowledge is described by constraint functions. based on a linearization of the latter and of the circuit performance functions, a description of the feasible performance range in the form of a polytope is derived. moreover, the approach is integrated into a hierarchical sizing method, where it propagates topological and technological constraints bottom-up. practical application results demonstrate the efficiency and usefulness of the new method.
initial sizing of analog integrated circuits by centering within topology-given implicit specification. we present a novel technique to automatically calculate an initialsizing of analog circuits that conforms to good design practice.the method is purely (dc) simulation-based and does not needsymbolic design equations or user design knowledge. it identifiesthe space of feasible design parameters based on implicit specifications, which arise from the circuit topology. a sizing centeredwithin this space is obtained by iteratively solving a maximum volume ellipsoid problem on approximations to the feasible parameter space. the result is well-suited as initial sizing because it safely satisfies all implicit specifications. experimental results demonstrate the efficiency and reliability of our method.
new decompilation techniques for binary-level co-processor generation. existing asips (application-specific instruction-set processors) and compiler-based co-processor synthesis approaches meet the increasing performance requirements of embedded applications while consuming less power than high-performance gigahertz microprocessors. however, existing approaches place restrictions on software languages and compilers. binary-level co-processor generation has previously been proposed as a complementary approach to reduce impact on tool restrictions, supporting all languages and compilers, at the cost of some decrease in performance. in a binary-level approach, decompilation recovers much of the high-level information, like loops and arrays, needed for effective synthesis, and in many cases yields hardware similar to that of a compiler-based approach. however, previous binary-level approaches have not considered the effects of software compiler optimizations on the resulting hardware. in this paper, we introduce two new decompilation techniques, strength promotion and loop rerolling, and show that they are necessary to synthesize an efficient custom hardware coprocessor from a binary in the presence of software compiler optimizations. in addition, unlike previous approaches, we show the robustness of binary-level co-processor generation by achieving order of magnitude speedups for binaries generated for three different instruction sets, mips, arm, and microblaze, using two different levels of compiler optimizations.
hardware/software partitioning of software binaries. partitioning an embedded system application among a microprocessor and custom hardware has been shown to improve the performance, power or energy of numerous examples. the advent of single-chip microprocessor/fpga platforms makes such partitioning even more attractive. previous partitioning approaches have partitioned sequential program source code, such as c or c++. we introduce a new approach that partitions at the software binary level. although source code partitioning is preferable from a purely technical viewpoint, binary-level partitioning provides several very practical benefits for commercial acceptance. we demonstrate that binary-level partitioning yields competitive speedup results compared to source-level partitioning, achieving an average speedup of 1.4 compared to 1.5 for eight benchmarks partitioned on a single-chip microprocessor/fpga device.
verification of integer multipliers on the arithmetic bit level. one of the most severe short-comings of currently available equivalence checkers is their inability to verify integer multipliers. in this paper, we present a bit level reverse-engineering technique that can be integrated into standard equivalence checking flows. we propose a boolean mapping algorithm that extracts a network of half adders from the gate netlist of an addition circuit. once the arithmetic bit level representation of the circuit is obtained, equivalence checking can be performed using simple arithmetic operations. experimental results show the promise of our approach.
record & play: a structural fixed point iteration for sequential circuit verification. this paper proposes a technique for sequential logic equivalence checking by a structural fixed point iteration. verification is performed by expanding the circuit into an iterative circuit array and by proving equivalence of each time frame by well-known combinational verification techniques. these exploit structural similarity between designs by local circuit transformations. starting from the initial state, for each time frame the performed circuit transformations are stored (recorded) in an instruction queue. in subsequent time frames the instruction queue is re-used (played) and updated when necessary. at some point the instruction queue does not need to be modified any more and is valid in all subsequent time frames. thus, a fixed point is reached and machine equivalence is proved by induction. experimental results show the great promise of this approach to verify circuits after resynthesis and retiming.
test register insertion with minimum hardware cost. implementing a built-in self-test by a "test per clock" scheme offers advantages concerning fault coverage, detection of delay faults, and test application time. such a scheme is implemented by test registers, for instance bilbos and cbilbos, which are inserted into the circuit structure at appropriate places. an algorithm is presented which is able to find the cost optimal placement of test registers for nearly all the iscas'89 sequential benchmark circuits, and a suboptimal solution with slightly higher costs is obtained for all the circuits within a few minutes of computing time. the algorithm can also be applied to the minimum feedback vertex set problem in partial scan design, and an optimal solution is found for all the benchmark circuits. the resulting self-testable circuits are analyzed. it is found that often cbilbos lead to a minimum hardware overhead and also simplify test scheduling and test control.
design-manufacturing interface for 0.13 micron and below. over the years, the increase in ic functionality has been achieved by a continuous drive towards smaller feature sizes. due to the decreasing dimensions of semiconductor structures, the sensitivity to critical design and manufacturing parameters has risen dramatically. vertical integration techniques and multi-level interconnect, which are becoming more common in modern technologies, have driven up the number of critical processing steps to several hundreds. these trends are expected to continue for the next several decades. the .13 micron technology is around the corner, as well as 300mm wafers. the increase in ic functionality has come with a skyrocketing capital spending (more than $2 billion per fabrication facility). moreover, the product life cycles for leading edge ic's have become very short (less than 2 years).
impulse response fault model and fault extraction for functional level analog circuit diagnosis. in this paper, a functional fault model for analog circuit diagnosis is proposed. a faulty module is modeled as a fault-free module in serial or in parallel with a fault module. to extract such a fault module, we adopt an iterative deconvolution technique to deconvolute the impulse response of the fault module from the faulty response. the test results show that with such a fault model and fault extraction technique the diagnostic resolution is improved significantly due to the separation of the fault and the system function. moreover, such a fault model allows single-module fault tables to be applied to the diagnosis of a multi-module system.
metrology for analog module testing using analog testability bus. in this paper, we propose a method to generate high quality test waveform on chip to avoid the parasitic effects in an analog testability bus test environment. for the test response analysis, we derive an extraction methodology to remove the parasitic effects and obtain the intrinsic response of the cut. the test results show that the algorithm is robust such that the intrinsic responses remain the same regardless of the small variation in the test waveforms. with the concept of intrinsic responses, we are able to use a single library for the testing and diagnosis of multiple instantiation of an analog module.
fast analysis and optimization of power/ground networks. this paper presents an efficient method for optimizing power/ground (p/g) networks. it proposes a structured skeleton that is intermediate to the conventional method that uses full meshes (which are hard to analyze efficiently), and tree-structured p/g networks (which provide poor performance). as an example, we consider a p/g network structure modeled as an overlying mesh with underlying trees originating from the mesh, which eases the task of analysis with acceptable performance sacrifices. a fast and efficient event-driven p/g network simulator is proposed, which hierarchically simulates the p/g network with an adaptation of prima to handle non-zero initial conditions. an adjoint network that incorporates the variable topology of the original p/g network, as elements switch in and out of the network, is constructed to calculate the transient adjoint sensitivity over multiple intervals. these are used to drive a sensitivity-based heuristic optimization method. experimental results show that this procedure can be used to efficiently optimize large networks.
sapor: second-order arnoldi method for passive order reduction of rcs circuits. the recently-introduced susceptance element exhibits many prominent features in modeling the on-chip magnetic couplings. for an rcs circuit, it is better to be formulated as a second-order system. therefore, corresponding mor (model-order reduction) techniques for second-order systems are desired to efficiently deal with the ever-increasing circuit scale and to preserve essential model properties. we first review the existing mor methods for rcs circuits, such as enor and smor, and discuss several key issues related to numerical stability and accuracy of the methods. then, a technique, sapor (second-order arnoldi method for passive order reduction), is proposed to effectively address these issues. based on an implementation of a generalized second-order arnoldi method, sapor is numerically stable and efficient. meanwhile, the reduced-order system also guarantees passivity.
memory bank and register allocation in software synthesis for asips. an architectural feature commonly found in digital signal processors (dsps) is multiple data-memory banks. this feature increases memory bandwidth by permitting multiple memory accesses to occur in parallel when the referenced variables belong to different memory banks and the registers involved are allocated according to a strict set of conditions. unfortunately, current compiler technology is unable to take advantage of the potential increase in parallelism offered by such architectures. consequently, most application software for dsp systems is hand-written -- a very time-consuming task.we present an algorithm which attempts to maximize the benefit of this architectural feature. while previous approaches have decoupled the phases of register allocation and memory bank assignment, our algorithm performs these two phases simultaneously. experimental results demonstrate that our algorithm substantially improves the code quality of many compiler-generated and even hand-written programs.
reconfigurable machine and its application to logic diagnosis. it is pointed out that in the reconfigurable machine (rm) highly flexible architecture combining field-programmable gate arrays (fpgas) with rams supports a wide range of applications. since its gate-level programmability allows implementation of various kinds of parallel processing techniques, rm provides a performance comparable to that of existing special-purpose engines. a reconfigurable machine prototype (rmp) has been built as the first prototype incorporating five fpga and four sram memory banks. rmp has been applied to logic diagnosis and a logic simulator. the concept of rm may be the best solution to the trade-offs between general-purpose and special-purpose machines. rm will be a hardware platform accelerating a wide range of applications, and also offering an interesting problem in high-level synthesis
design of system interface modules. a design methodology and high-level synthesis techniques for integrating hardware modules into a system are presented. the interface between modules, which can obey arbitrary protocols, is generated from a high-level specification developed especially for describing intermodule communication. central to the design methodology are libraries which contain system-level module generators and a strategy to capture the protocol and timing information necessary for interface synthesis. the main impact of this work is raising the interface design abstraction and reducing the effort required from a designer to produce a system using various ic technologies
crosstalk fault detection by dynamic idd. undesired capacitive crosstalk between signals is expected to be a significant concern in deep submicron circuits. new test techniques are needed for these crosstalk faults since they may cause unacceptable performance degradation. we analyze the impact of crosstalk faults on a circuit's power dissipation. crosstalk faults can be detected by monitoring the dynamic supply current. the test method is based on a recently developed dynamic idd test metric, the energy consumption ratio (ecr). ecr-based test has been shown to be effective at tolerating the impact of process variations. in this paper, we apply a ecr-based test method called ecr-vdd test to detect the crosstalk faults. the effectiveness of the method is demonstrated by simulation results.
synthesis of custom processors based on extensible platforms. efficiency and flexibility are critical, but often conflicting, design goals in embedded system design. the recent emergence of extensible processors promises a favorable tradeoff between efficiency and flexibility, while keeping design turnaround times short. current extensible processor design flows automate several tedious tasks, but typically require designers to manually select the parts of the program that are to be implemented as custom instructions.in this work, we describe an automatic methodology to select custom instructions to augment an extensible processor, in order to maximize its efficiency for a given application program. we demonstrate that the number of custom instruction candidates grows rapidly with program size, leading to a large design space, and that the quality (speedup) of custom instructions varies significantly across this space, motivating the need for the proposed flow. our methodology features cost functions to guide the custom instruction selection process, as well as static and dynamic pruning techniques to eliminate inferior parts of the design space from consideration. further, we employ a two-stage process, wherein a limited number of promising instruction candidates are first selected, and then evaluated in more detail through cycle-accurate instruction set simulation and synthesis of the corresponding hardware, to identify the custom instruction combinations that result in the highest program speedup or maximize speedup under a given area constraint.we have evaluated the proposed techniques using a state-of-the-art extensible processor platform, in the context of a commercial design flow. experiments with several benchmark programs indicate that custom processors synthesized using automatic custom instruction selection can result in large improvements in performance (upto 5.4x, average of 3.4x), energy (upto 4.5x, average of 3.2x), and energy-delay product (upto 24.2x, average of 12.6x), while speeding up the design process significantly.
a scalable application-specific processor synthesis methodology. custom processors based on application-specific ordomain-specific instruction sets are gaining popularity, and areoften used to implement critical architectural blocks in complex system-on-chips. while several advances have been madein custom processor architectures, tools, and design methodologies, designers are still required to manually perform somecritical tasks, such as selection of the custom instructions bestsuited to the given application and design constraints.we present a scalable methodology for the synthesis of acustom processor from an embedded software program. a keyfeature of the proposed methodology is its scalability, whichis achieved by exploiting the structured, hierarchical natureof large software programs. we motivate the need for such amethodology, and describe the algorithms used for the criticalsteps, including hardware resource budgeting, local optimizations, and global exploration. our methodology utilizes the concept of "soft" instruction templates, which can be adapted by adding operations to them or deleting operations from them at any time during the design space exploration process, allowing for global design decisions to be interleaved with fine-grained optimizations.we have integrated our methodology in an open source compiler, and verified it using a commercial extensible processor. experiments with several benchmarks indicate that ourmethodology can effectively tackle large programs. it resultedin the synthesis of high-quality custom processors that demonstrated an average speedup of 2.61x and a maximum speedupof 6.32x. the cpu times required for custom processor synthesis were quite small, indicating that the proposed techniquescan be applied to embedded software programs of significantcomplexity.
a loosely coupled parallel algorithm for standard cell placement. we present a loosely coupled parallel algorithm for the placement of standard cell integrated circuits. our algorithm is a derivative of simulated annealing. the implementation of our algorithm is targeted towards networks of unix workstations. this is the very first reported parallel algorithm for standard cell placement which yields as good or better placement results than its serial version. in addition, it is the first parallel placement algorithm reported which offers nearly linear speedup, in terms of the number of processors (workstations) used, over the serial version. despite using the rather slow local area network as the only means of interprocessor communication, the processor utilization is quite high, up to 98% for 2 processors and 90% for 6 processors. the new parallel algorithm has yielded the best overall results ever reported for the set of mcnc standard cell benchmark circuits.
marsh: min-area retiming with setup and hold constraints. this paper describes a polynomial time algorithm for min-area retiming for edge-triggered circuits to handle both setup and hold constraints. given a circuit g and a target clock period c, our algorithm either outputs a retimed version of g satisfying setup and hold constraints or reports that such a solution is not possible, in &ogr;(|v3|log|v|log(|v|c)) steps, where |v| corresponds to number of gates in the circuit and c is equal to the number of registers in the circuit. this is the first polynomial time algorithm ever reported for min-area retiming with constraints on both long and short-paths. an alternative problem formulation that takes practical issues in to consideration and lowers the problem complexity is also developed. both the problem formulations have many parallels with the original formulation of long-path only retiming by leiserson and saxe and all the speed improvements that have been obtained on that technique are likely to be valid for improving the performance of the technique described in this paper.
mosaic: a tile-based datapath layout generator. it is pointed out that mosaic achieves a routing technique based on bus patterns preplaced all over the leaf cell and joins these segments based on module schematic information. with this routing technique, a high layout density can be achieved. the layout density of the 120-mhz micro-processor datapath module was 10000-20000 transistors/mm2 in 0.5-&mu;m three-metal bicmos technology. leaf cells are not used only in one module design, but are reusable across multiple module designs. only 100 kinds of leaf cells were needed for 300 module designs
hardware scheduling for dynamic adaptability using external profiling and hardware threading. while performance, area, and power constraints have been thedriving force in designing current communication-enabled embeddedsystems, post-fabrication and run-time adaptability is now required.two dominant configurable hardware platforms are processorsand fpgas. however, for compute-intensive applications,neither platform delivers the needed performance at the desiredlow power. the need thus arises for custom, application-specificconfigurable (asc) hardware.this paper addresses the optimization of asc hardware. ourtarget application areas are multimedia and communication wherean incoming packet (task) is processed independently of otherpackets. we innovatively utilize two concepts: external profilingand hardware threading. we utilize an m/m/c queueing model toprofile task arrival patterns and show how profiling guides designdecisions. we introduce the novel concept of hardware threadingwhich allows on-the-fly borrowing of unutilized hardware, thusmaximizing task-level parallelism, to either boost performance orto lower power consumption. we present a scheduling algorithmthat synthesizes a hardware-threaded architecture, and discuss experimentalresults that illustrate adaptability to different workloads,and performance/power trade-offs.
generalized network flow techniques for dynamic voltage scaling in hard real-time systems. energy consumption is an important performance parameter forportable and wireless embedded systems. however, energy consumptionmust be carefully balanced with real-time responsivenessin hard real-time systems. we present an optimal offline dynamicvoltage scaling (dvs) scheme for dynamic power management insuch systems. a generalized network flow model for the uniprocessordvs problem is developed and solved optimally using an efficientnetwork flow algorithm. the proposed method outperformsexisting dvs schemes for several popular embedded processorswhere the number of processor speeds is limited to a few values.the gnf model provides theoretical lower bounds on energy consumptionusing dvs in hard real-time systems.
incremental formal design verification. language containment is a method for design verification that involves checking if the behavior of the system to be verified is a subset of the behavior of the specifications (properties or requirements), which it has to meet. if this check fails, language containment returns a subset of &ldquo;fair&rdquo; states involved in behavior that the system exhibits but the specification does not. current techniques for language containment do not take advantage of the fact that the process of design is incremental; namely that the designer repeatedly modifies and re-verifies his/her design. this results in unnecessary and cumbersome computation. we present a method, which successively modifies the latest result of verification each time the design is modified. our incremental algorithm translates changes made by the designer to an addition or subtraction of edges, states or constraints (on acceptable behavior) from the transition behavior or specification of the problem. next, these changes are used to update the set of &ldquo;fair&rdquo; states previously computed. this incremental algorithm is superior to the current techniques for language containment; a conclusion supported by the experimental results presented in this paper.
fast field solver-programs for thermal and electrostatic analysis of microsystem elements. to solve the problem of fast thermal and electrostatic simulation of microsystem elements two different field solver tools have been developed at tub. the us-thermanal program is capable for the fast steady state and dynamic simulation of suspended multi-layered microsystem structures, while the 2d-sunred program is the first version of a general field solver program, based on an original method, the successive network reduction. this program offers a very fast and accurate substitute of fem programs for the solution of the poisson equation, e.g. solving a 32000 grid problem in about 6 minutes on a 586 pc. application examples show the usability of the tools.
verifying clock schedules. timing verification and optimization have been formulated as mathematical programming problems. the computational aspects of using such a formulation for verifying clock schedules are considered. the formulation can have multiple solutions, and these extraneous solutions can cause previously published algorithms to produce incorrect or misleading results. the conditions under which multiple solutions exist are characterized, and it is shown that even when the solution is unique, the running times of these previous algorithms can be unbounded. by contrast, a simple polynomial time algorithm for clock schedule verification is exhibited. the algorithm was implemented and used to check the timing of all the circuits in the iscas-89 benchmark suite. observed running times are linear in circuit size and quite practical
sat based atpg using fast justification and propagation in the implication graph. in this paper we present new methods for fast justification and propagation in the implication graph (ig) which is the core data structure of our sat based implication engine. as the ig model represents all information on the implemented logic function as well as the topology of a circuit, the proposed techniques inherit all advantages of both general sat based and structure based approaches to justification, propagation, and implication. these three fundamental boolean problems are the main tasks to be performed during automatic test pattern generation (atpg) such that the proposed algorithms are incorporated into our atpg tool tip which is built on top of the implication engine.working exclusively in the ig, the complex functional operations of justification, propagation, and implication reduce to significantly simpler graph algorithms. they are easily extended to exploit bit-parallel techniques. as the ig is automatically generated for arbitrary logics the algorithms remain applicable independent of the required logic. this allows processing of various fault models using the same engine. that is, the presented ig based methods offer a complete and versatile framework for rapid development of new atpg tools that target emerging fault models such as cross-talk, delay or bridging faults. tip currently handles stuck-at as well as various delay fault models. furthermore, the proposed methods are used within tools for boolean equivalence checking, optimization of netlists, timing analysis or retiming (reset state computation).in order to demonstrate the performance of ig based atpg, i.e. justification and propagation in the ig, we provide experimental results for stuck-at and path delay fault models. they show that tip outperforms the state-of-the-art in sat based and structure based atpg.
a sat-based implication engine for efficient atpg, equivalence checking, and optimization of netlists. the paper presents a flexible and efficient approach to evaluating implications as well as deriving indirect implications in logic circuits. evaluation and derivation of implications are essential in atpg, equivalence checking, and netlist optimization. contrary to other methods, the approach is based on a graph model of a circuit's clause description called implication graph. it combines both the flexibility of sat-based techniques and high efficiency of structure based methods. as the proposed algorithms operate only on the implication graph, they are independent of the chosen logic. evaluation of implications and computation of indirect implications are performed by simple and efficient graph algorithms. experimental results for various applications relying on implication demonstrate the effectiveness of the approach.
a statistical approach to estimate the dynamic non-linearity parameters of pipeline adcs. a fully-analytical approach to estimate the statistics ofdynamic non-linearity parameters of pipeline analog-to-digitalconverters (adcs) in the presence of circuit non-idealitiesincluding capacitance mismatches and non-idealopamps is presented. these parameters include the spurious-freedynamic range (sfdr) and the signal to noise-and-distortionratio (sndr). the simple closed-form formulasfor sfdr and sndr presented here are useful for designautomation of highly-linear pipeline adcs in order toextract the required values for the circuit-level specificationsof the sub-blocks of converters. behavioral simulations arepresented to show the accuracy of the proposed equations.
a mapping algorithm for defect-tolerance of reconfigurable nano-architectures. self-assembled nano-fabrication processes yield regular and reconfigurable devices. however, defect densities in this emerging nanotechnology are higher than those in conventional lithography-based vlsi. in this paper, we present a defect-tolerant design flow to minimize customized post-fabrication design efforts to be performed per chip. we also present a greedy o(n log n) mapping algorithm which makes the connection between defect-unaware design steps and the final defect-aware step. experiments show that the results obtained by this algorithm are very close to the exact solutions.
low power state assignment targeting two-and multi-level logic implementations. the problem of minimizing power consumption during the state encoding of a finite state machine is considered. a new power cost model for state encoding is proposed and encoding techniques that minimize this power cost for two- and multi-level logic implementations are described. these techniques are compared with those which minimize area or the switching activity at the present state bits. experimental results show significant improvements.
clock-tree routing realizing a clock-schedule for semi-synchronous circuits. it is known that the clock-period can be shorter than the maximum of signal-delays between registers if the clock arrival time to each register is properly scheduled. the algorithm to design an optimal clock-schedule was given. in this paper, we propose a clock-tree routing algorithm that realizes a given clock-schedule using the elmore-delay model. following the deferred-merge-embedding (dme) framework, the algorithm generates a topology of the clock-tree and determines the locations and sizes of intermediate buffers simultaneously. the experimental results show that this method constructs clock-trees with moderate wire length compared with that of zero-skew clock-trees.
statistical timing analysis driven post-silicon-tunable clock-tree synthesis. process variations cause significant timing uncertainty and yield degradation in deep sub-micron technologies. a solution to counter timing uncertainty is post-silicon clock tuning. existing design approaches for post-silicon-tunable (pst) clock-tree synthesis usually insert a pst clock buffer for each flip-flop or put pst clock buffers across an entire level of a clock-tree. this can cause significant over-design and long tuning time. in this paper, we propose to insert pst clock buffers at both internal and leaf nodes of a clock-tree and use a bottom-up algorithm to reduce the number of candidate pst clock buffer locations. we then provide two statistical-timing-driven optimization algorithms to reduce the hardware cost of a pst clock-tree. experimental results on iscas89 benchmark circuits show that our algorithms achieve up to a 90% area or a 90% number of tunable clock buffer reductions compared to existing design methods.
algorithm level re-computing - a register transfer level concurrent error detection technique. in this paper we propose two algorithm-level time redundancy based concurrent error detection (ced) schemes that exploit diversity in a register transfer (rt) level implementation. rt level diversity can be achieved either by changing the operation-to-operator allocation (allocation diversity) or by shifting the operands before re-computation (data diversity). by enabling a fault to affect the normal result and the re-computed result in two different ways, rt level diversity yields good ced capability with low area overhead. we used synopsys behavior complier (bc) to implement the technique.
adaptive cut line selection in min-cut placement for large scale sea-of-gates arrays. we present a new min-cut based placement algorithm for large scale sea-of-gates arrays. in the past all such algorithms used a fixed cut line sequence that is determined before min-cut partitioning is performed. in our approach, we adaptively select a next partitioning pattern based on the current parameter value; we then perform the corresponding min-cut partitionings and measure a new parameter value. we repeat this process until all cut lines are processed. as a parameter, we introduce a new global objective function based on wire congestions on cut lines. we establish a close relation between this function and cut line sequences. this relation is used to develop an innovative method of adaptively determining a cut line sequence so as to minimize this global function. with this adaptive selection of cut lines along with a new cluster-based min-cut partitioning technique, our algorithm can produce, in a short time and at a low cost, final placement results that achieve the 100% completion of wiring on chips of fixed sizes. this has led to its successful production use, having generated more than 400 cmos sea-of-gates array chips.
worst-case analysis to obtain stable read/write dc margin of high density 6t-sram-array with local vth variability. 6t-sram cells in the sub-100 nm cmos generation are now being exposed to a fatal risk that originates from large local vth variability (/spl sigma//sub v/spl i.bar/local/). to achieve high-yield sram arrays in presence of random /spl sigma//sub v/spl i.bar/local/ component, we propose worst-case analysis that determines the boundary of the stable vth region for the sram read/write dc margin (vth curve). applying this to our original 65 nm spice model, we demonstrate typical behavior of the vth curve and show new criteria for discussing sram array stability with vth variability.
performance optimization using separator sets. in this paper, we propose a new method to optimize a performance of a very large circuit. we find the best set of local transformations to be applied to the circuit, by inserting &ldquo;padding nodes&rdquo; on non-critical edges of the circuit, and calculating separator sets of the circuit using separator sets. our method is robust for very large circuits, because its memory usage and calculation time are linear and polynomial order with the size of the circuit.according to our experimental results, our method has accomplished all circuits, while k. j. singh's selection function method has aborted with three large circuits because of memory overflow. the results also shows our method has a comparable capability in delay optimization to singh's method.
switching activity analysis using boolean approximation method. this paper presents a novel algorithm to estimate the signal probability and switching activity at all nodes in a combinational logic circuit under a zero-delay model without constructing global bdds. by using taylor expansion technique, the first-order signal correlation effects due to reconvergent fan-out nodes are taken into account. high accuracy is achieved by considering the dependency of the signal probability and switching activity on each primary input. high speed is also achieved by using the incremental approach for probability calculation. our approach is able to handle large circuits, since it does not need to construct global bdds for the probability calculation. the analysis of the time complexity and the experimental results show the running time of our approach to be about 100 times shorter than that of the most accurate approach previously proposed and that our approach has comparable accuracy. the error of the total power estimation is about 0.5% on average.
lp based cell selection with constraints of timing, area, and power consumption. this paper presents a new lp based optimal cell selection method. optimal cell selection is a useful tool for final tuning of lsi designs. it replaces drivabilities of cells, adjusting timing, area, and power constraints. using the latest and earliest arrival times, it can handle both setup and hold time constraints. we also make an efficient initial basis, which speeds up a simplex lp solver by 5 times without any relaxations nor approximations. from experimental results, it reduces the clock cycle of a manual designed 13k-transistor chip by 17% without any increase of area.
layout-driven resource sharing in high-level synthesis. in deep submicron (dsm) technology, the interconnects are equally as or more important than the logic gates. in particular, to achieve timing closure in dsm technology, it is very necessary and critical to consider the interconnect delay at an early stage of the synthesis process. it has been known that resource sharing in high-level synthesis is one of the major synthesis tasks which greatly affect the final synthesis/layout results. in this paper, we propose a new layout-driven resource sharing approach to overcome some of the limitations of the previous works in which the effects of layout on the synthesis have never been taken into account or considered in local and limited ways, or whose computation time is excessively large. the proposed approach consists of two steps: (step 1) we relax the integrated resource sharing and placement into an efficient linear programming (lp) formulation based on the concept of discretizing placement space; (step 2) we derive a feasible solution from the solution obtained in step 1. then, we employ an iterative mechanism based on the two steps to tightly integrate resource sharing and placement tasks so that the slack time violation due to interconnect delay (determined by placement) as well as logic delay (determined by resource sharing) should be minimized. from experiments using a set of benchmark designs, it is shown that the approach is effective, and efficient, completely removing the slack time violation produced by conventional methods.
optimal allocation of carry-save-adders in arithmetic optimization. carry-save-adder(csa) is one of the most widely used schemes for fast arithmetic in industry. this paper provides a solution to the problem of finding an optimal-timing allocation of csas. specifically, we present a polynomial time algorithm which finds an optimal-timing csa allocation for a given arithmetic expression. in addition, we extend our result for csa allocation to the problem of optimizing arithmetic expressions across the boundary of design hierarchy by introducing a new concept, called auxiliary ports. our algorithm can be used to carry out the csa allocation step optimally and automatically, and this can be done within the context of a standard hdl synthesis environment.
a new algorithm for routing tree construction with buffer insertion and wire sizing under obstacle constraints. buffer insertion and wire sizing are critical in deep submicron vlsi design. this paper studies the problem of constructing routing trees with simultaneous buffer insertion and wire sizing in the presence of routing and buffer obstacles. no previous algorithms consider all these factors simultaneously. previous dynamic programming based algorithm is first extended to solve the problem. however, with the size of routing graph increasing and with wire sizing taken into account, the time and space requirement increases enormously. then a new approach is proposed to formulate the problem as a series of graph problems. the routing tree solution is obtained by finding shortest paths in a series of graphs. in the new approach, wire sizing can be handled almost without any additional time and space requirement. moreover, the time and space requirement is only polynomial in terms of the size of routing graph. our algorithm differs from traditional dynamic programming, and is capable of addressing the problem of inverter insertion and sink polarity. both theoretical and experimental results show that the graph-based algorithm outperforms the dp-based algorithm by a large margin. we also propose a hierarchical approach to construct routing tree for a large number of sinks.
dynamic compilation for energy adaptation. while previous compiler research indicates that significant improvements in energy efficiency may be possible if properly optimized code is used, the energy constraints under which a given application code should be optimized may not always be available at compile-time. more importantly, these constraints may change dynamically during the course of execution. in this work, we present a dynamic recompilation/linking framework using which the energy behavior of a given application can be optimized while the application is being executed. our preliminary experiments indicate that large energy gains are possible through dynamic code recompilation/linking at the expense of a relatively small increase in execution time.
a simulation-based method for the verification of shared memory in multiprocessor systems. as processor architectural complexity increases, greater effort must be focused on functional verification of the chip as a component of the system. multiprocessor verification presents a particular challenge in terms of both difficulty and importance. while formal methods have made significant progress in the validation of coherence protocols, these methods are not always practical to apply to the structural implementation of a complex microprocessor. this paper describes a simulation-based approach to modeling and checking the shared-memory properties of the alpha architecture by using a directed acyclic graph to represent memory-access orderings. the resulting tool is integrated with a simulation model of an alpha implementation, allowing the user to verify aspects of the implementation with respect to the overall architectural specification. both an implementation-independent and an implementation-specific version of the tool are discussed.
delay optimal partitioning targeting low power vlsi circuits. abstract: in this paper, a delay optimal clustering/partitioning algorithm for minimizing the power dissipation of a circuit is proposed. traditional approaches for delay optimal partitioning are based on lawler's clustering algorithm that makes no attempt to explore alternative partitioning solutions that have the same delay but better power implementations. our algorithm provides a formal mechanism which implicitly enumerates alternate partitionings and selects a partitioning that has the same delay but less power dissipation. for tree circuits, the proposed algorithm produces delay and power optimal partitioning whereas for non-tree circuits it produces delay optimal partitioning with significantly improved power dissipation.
test generation for primitive path delay faults in combinational circuits. this paper presents a method of identifying primitive path-delay faults in combinational circuits, and deriving robust tests for all robustly testable primitive faults. it uses the concept of sensitizing cubes to reduce the search space. this approach helps identify faults that cannot be part of any primitive fault, and avoids attempting test generation for them. sensitization conditions determined for primitive fault identification are also used in test generation, reducing test generation effort. experimental results on some of the iscas'85 and mcnc'91 benchmark circuits indicate that they contain a fair number of primitive multiple path delay faults which must be tested.
on the difference between two widely publicized methods for analyzing oscillator phase behavior. this paper describes the similarities and differences between two widely publicized methods for analyzing oscillator phase behavior. the methods were presented in [3] and [6]. it is pointed out that both methods are almost alike. while the one in [3] can be shown to be, mathematically, more exact, the approximate method in [6] is somewhat simpler, facilitating its use for purposes of analysis and design. in this paper, we show that, for stationary input noise sources, both methods produce equal results for the oscillator's phase noise behavior. however, when considering injection locking, it is shown that both methods yield different results, with the approximation in [6] being unable to predict the locking behavior. in general, when the input signal causing the oscillator phase perturbations is non-stationary, the exact model produces the correct results while results obtained using approximate model break down.
a generalized method for computing oscillator phase noise spectra. this paper presents a generalized semi-analytic method for computingoscillator phase noise spectra, including the details veryclose to the oscillation frequency. the starting point is a generalrelation between an oscillator's output power spectral density andthe characteristics of the input noise processes. for weak inputnoise processes that vary sufficiently fast over time, this relation reducesto an analytic expression. for cases that do not satisfy theseconditions, the relation is, in part, evaluated numerically. this isaccomplished using techniques for exponential data fitting. the resultingmethod is able to compute oscillator phase noise spectra fora wide range of input noise characteristics.
activity-driven clock design for low power circuits. in this paper we investigate activity-driven clock trees to reduce the dynamic power consumption of synchronous digital cmos circuits. sections of an activity-driven clock tree can be turned on/off by gating the clock signals during the active/idle times of the clocked elements. we propose a method of obtaining the switching activity patterns of the clocked circuits during the high level design process. we formulate three novel activity-driven problems. the objective of these problems is to minimize system's dynamic power consumption. we propose an approximation algorithm based on recursive matching to solve the clock tree construction problem. we solve the gate insertion problems with an exact algorithm employing the dynamic programming paradigm. finally, we present experimental results that verify the effectiveness of our approach. our work in this paper is a step in understanding how high level decisions (e.g. behavioral design) can affect a low level design (e.g. clock design).
clock period constrained minimal buffer insertion in clock trees. in this paper we investigate the problem of computing a lower bound on the number of buffers required when given a maximum clock frequency and a predefined clock tree. using generalized properties of published cmos timing models, we formulate a novel non-linear and a simplified linear buffer insertion problem. we solve the latter optimally with an o(n) algorithm. the basic formulation and algorithm are extended to include a skew upper bound constraint. using these algorithms we propose further algorithmic extensions that allow area and phase delay tradeoffs. our results are verified using spice3e2 simulations with mcnc mosis 2.0&mgr; models and parameters. experiments show our buffer insertion algorithms can be used effectively for high-speed clock designs.
estimation of maximum transition counts at internal nodes in cmos vlsi circuits. in combinational logic circuits, a single switching event on the primary inputs may give rise to multiple switchings at the internal nodes. this glitching effect is caused primarily by unequal delay paths and results in increased power consumption and decreased device reliability. in this paper, we present a new algorithm to estimate the maximum number of transitions at internal nodes in combinational cmos vlsi circuits. unlike exhaustive simulation, our algorithm is based on the technique of propagating uncertainty waveforms throughout the circuit and using these waveforms to count the maximum switching activity at every node. our approach guarantees a tight upper bound on the number of transitions which is necessary to assess the minimum circuit reliability lifetime and maximum power dissipation.
optimization of a fully integrated low power cmos gps receiver. this paper describes an optimization technique able to optimize a complete wireless receiver architecture in a reasonable amount of time. the optimizer alternates between spice level optimizations of simple building blocks and a full architecture optimization of the whole based on accurate models of the building blocks. the models of the building blocks are interpolated over the data points acquired in the spice level simulations. the optimizer technique has been applied to the optimization of an architecture for a gps receiver. the optimal design has been implemented in a standard 0.25&mu;m cmos process.
gate sizing using lagrangian relaxation combined with a fast gradient-based pre-processing step. in this paper, we present forge, an optimal algorithm for gate sizing using the elmore delay model. the algorithm utilizes lagrangian relaxation with a fast gradient-based pre-processing step that provides an effective set of initial lagrange multipliers. compared to the previous lagrangian-based approach, forge is considerably faster and does not have the inefficiencies due to difficult-to-determine initial conditions and constant factors. we compared the two algorithms on 30 benchmark designs, on a sun ultrasparc-60 workstation. on average forge is 200 times faster than the previously published algorithm. we then improved forge by incorporating a slew-rate-based convex delay model, which handles distinct rise and fall gate delays. we show that forge is 15 times faster, on average, than the amps transistor-sizing tool from synopsys, while achieving the same delay targets and using similar total transistor area.
a layout-aware synthesis methodology for rf circuits. in this paper a layout-aware rf synthesis methodology is presented. the methodology combines the power of a differential evolution algorithm with cost function response modeling and integrated layout generation to synthesize rf circuits efficiently, taking into account all layout parasitics during the circuit optimization. the proposed approach has successfully been applied to the design of a high-performance downconverter mixer circuit, proving the effectiveness of the implemented design methodology.
optimal wire and transistor sizing for circuits with non-tree topology. conventional methods for optimal sizing of wires and transistors use linear rc circuit models and the elmore delay as a measure of signal delay. if the rc circuit has a tree topology the sizing problem reduces to a convex optimization problem which can be solved using geometric programming. the tree topology restriction precludes the use of these methods in several sizing problems of significant importance to high-performance deep submicron design including, for example, circuits with loops of resistors, e.g., clock distribution meshes, and circuits with coupling capacitors, e.g., buses with crosstalk between the lines. the paper proposes a new optimization method which can be used to address these problems. the method uses the dominant time constant as a measure of signal propagation delay in an rc circuit, instead of elmore delay. using this measure, sizing of any rc circuit can be cast as a convex optimization problem which can be solved using the recently developed efficient interior-point methods for semidefinite programming. the method is applied to two important sizing problems --- sizing of clock meshes, and sizing of buses in the presence of crosstalk.
hermes: lut fpga technology mapping algorithm for area minimization with optimum depth. this work presents hermes, a depth-optimal lut based fpga mapping algorithm. the presented algorithm is based on a new strategy for finding luts allowing to find a good lut in a significantly shorter time compared to the previous methods. the quality of results is improved by enabling lut re-implementation and by introducing a cost function which encourages input sharing among luts. the experimental results show that, on average, the presented algorithm computes 15.5% and 3.5% smaller lut mappings compared to the ones obtained by flowmap and cutmap, respectively, using two orders of magnitude less cpu time. the speed of hermes makes it suitable for running in an incremental manner during logic synthesis.
folding a stack of equal width components. we consider two versions of the problem of folding a stack of equal width components. in both versions, when a stack is folded, a routing penalty is incurred at the fold. in one version, the height of the folded layout is given and we are to minimize width. in the other, the width of the folded layout is given and its height is to be minimized.
hero: hierarchical emc-constrained routing. the authors point out that, in order to perform the design of printed circuit boards as time- and cost-efficiently as possible, electromagnetic compatability (emc) phenomena have to be taken into account during layout synthesis. the emc router hero offers a robust framework for incorporating emc constraints and cost criteria into routing. using hero, it will not be possible to obtain a completely failsafe layout, in general. however, experimental results for typical boards prove that a great number of emc problems can be avoided during layout synthesis and that the effects of emc phenomena can be reduced substantially. detailed reports of emc design rule violations provide effective input to the succeeding emc verification phase. violations of emc design rules are mainly caused by an inappropriate placement. therefore, it seems to be of great promise to combine hierarchical placement methods with this approach for hierarchical routing
cloning techniques for hierarchical compaction. a method for efficiently performing hierarchical compaction in the presence of over the cell routing (otcr) is described. by treating the otcr objects as part of the cells they overlap, the amount of interaction between cells in the hierarchy is reduced. this method eliminates the need to make all objects within a cell that interact with otcr into ports. an explosion in the complexity of the problem that needs to be solved via linear programming (lp) is thus avoided. computation is shifted away from lp and into the graph domain where efficient and accurate solution methods have been demonstrated
communication-aware task scheduling and voltage selection for total systems energy minimization. in this paper, we present an interprocessor communication-aware task scheduling algorithm applicable to a multiprocessor system executing an application with dependent tasks. our algorithm takes the application task graph and the architecture graph as inputs,assigns the tasks to processors and then schedules them. as main theoreticalcontribution, the algorithm we propose reduces the overallsystems energy by (i) reducing the total interprocessor communicationand (ii) executing certain cycles at a lower voltage level. experimentalresults show that by tuning the parameter for communicationawareness, a schedule using our algorithm can reduce upto 80%interprocessor communication in a complex video/audio application(compared to a schedule which is only voltage-selection aware) withoutlosing much in the number of cycles executed at lower voltage.
test generation for comprehensive testing of linear analog circuits using transient response sampling. the problem of testing analog components continues to be the bottleneck in reducing the time-to-market of mixed-signal ics. in this paper, we present a test generation algorithm for implicit functional testing of linear analog circuits using transient response sampling. each specification of the circuit under test (cut) imposes bounds on individual parametric deviations under the single fault assumption. these bounds are mapped on to "acceptable" ranges of measurements of the transient response of the cut at various sample points using time domain sensitivity calculations. any circuit that "passes" the applied test is also guaranteed to meet its specifications. the simplicity of the test waveform, reduced test generation time and test time show that this testing method is a good alternative to existing testing schemes.
a more reliable reduction algorithm for behavioral model extraction. in this paper we are concerned with developing more reliable model reduction algorithms. we have focused on less common, but real, examples that fail to be effectively reduced by almost all of the currently popular model reduction methods. the failure of these popular methods is due to the fact that they all separately examine controllability and observability. we then present a new method based on several modifications and extensions of the recently developed aisiad algorithm. the modified aisaid method is demonstrated on a wide variety of examples, including electrical interconnect, micromachined devices, and heat flow to show that the method is reliable. our modified aisaid method is either nearly equivalent or far superior to any of the other reduction methods suitable for large scale problems.
on mask layout partitioning for electron projection lithography. electron projection lithography (epl) is a leading candidate for next generation lithography (ngl) in vlsi production. the membrane mask used in epl is divided into sub-fields by struts for structural support. a layout must be partitioned into these sub-fields on mask and then stitched back together by the epl tool on wafer. to minimize possible stitching errors, partitioning of a mask layout should minimize cuts of layout features in the overlapping area between two adjacent sub-fields. this paper presents the first formulation of the mask layout partitioning problem for epl as a graph problem. the graph formulation is optimally solved with a shortest path approach. two other techniques are also presented to speed up computation. experimental runs on data from a real industry design show excellent results.
a video driver system designed using a top-down, constraint-driven methodology. to accelerate the design cycle for analog and mixed-signal systems, we have proposed a top-down, constraint-driven design methodology. the key idea of the proposed methodology is hierarchically propagating constraints from performance specifications to layout. consequently, it is essential to provide the necessary tools and techniques enabling the efficient constraint propagation. to illustrate the applicability of the proposed methodology to the design of larger systems, we present in this paper the complete design flow for a video driver system. critical advantages of the methodology illustrated with this design example include avoiding costly low level re-designs and getting working silicon parts from the first run. following our approach, a jitter constraint is imposed at the system level and then is propagated hierarchically to the circuit blocks and layout, using behavioral modeling and simulation. experimental results are presented from working fabricated parts.
damocles: an observer-based approach to design tracking. the first phase of damocles, which involves developing a data management system subset of an entire design tracking system using the observer approach, is described. the designer is provided with a cockpit data management view of the project, without changing the way in which design groups do data management. the observer approach creates a cockpit view for the designer without changing the current point-task view. the cockpit view presents a designer with a design state perspective consisting of an object-oriented view of design data, tool flow and methodology information, history and audit trail information, etc. the designer can use the cockpit view to get the larger picture about project progress as and when the designer chooses. this view is extracted from the traditional designer environment by damocles while the designer is working through the point-task view
power analysis of embedded software: a first step towards software power minimization. embedded computer systems are characterized by the presence of a dedicated processor and the software that runs on it. power constraints are increasingly becoming the critical component of the design specification of these systems. at present, however, power analysis tools can only be applied at the lower levels of the design&mdash;the circuit or gate level. it is either impractical or impossible to use the lower level tools to estimate the power cost of the software component of the system. this paper describes the first systematic attempt to model this power cost. a power analysis technique is developed that has been applied to two commercial microprocessors&mdash;intel 486dx2 and fujitsu sparclite 934. this technique can be employed to evaluate the power cost of embedded software and also be used to search the design space in software power optimization.
efficient iterative time preconditioners for harmonic balance rf circuit simulation. efficient iterative time preconditioners for krylov-basedharmonic balance circuit simulators are proposed.some numerical experiments assess theirperformance relative to the well-known block-diagonalfrequency preconditioner and the previouslyproposed time preconditioners.
a simultaneous technology mapping, placement, and global routing algorithm for field-programmable gate arrays. technology mapping algorithms for lut (look up table) based fpgas have been proposed to transfer a boolean network into logic-blocks. however, since those algorithms take no layout information into account, they do not always lead to excellent results. in this paper, a simultaneous technology mapping, placement and global routing algorithm for fpgas, maple, is presented. mapleis an extended version of a simultaneous placement and global routing algorithm for fpgas, which is based on recursive partition of layout regions and block sets. maple inherits its basic processes and executes the technology mapping simultaneously in each recursive process. therefore, the mapping can be done with the placement and global routing information. experimental results for some benchmark circuits demonstrate its efficiency and effectiveness.
adaptive sampling and modeling of analog circuit performance parameters with pseudo-cubic splines. many approaches to analog performance parameter macro modeling have been investigated by the research community. these models are typically derived from discrete data obtained from circuit simulation using numerous input combinations of component sizes for a given circuit topology. the simulations are computationally intensive, therefore it is advantageous to reduce the number of simulations necessary to build an accurate macro model. we present a new algorithm for adaptively sampling multi-dimensional black box functions based on duchon pseudo-cubic splines. the splines readily and accurately model high dimensional functions based on discrete unstructured data and require no tuning of parameters as seen in many other interpolation methods. the adaptive sampler, in conjunction with pseudo-cubic splines, is used to accurately model various analog performance parameters for an operational amplifier topology using fewer sample points than traditional gridded and quasi-random sampling methodologies.
a deductive technique for diagnosis of bridging faults. a deductive technique is presented that uses voltage testing for the diagnosis of single bridging faults between two gate input or output lines and is applicable to combinational or full-scan sequential circuits. for defects in this class of faults the method is accurate by construction while making no assumptions about the logic-level wired-and/or behavior. a path-trace procedure starting from failing outputs deduces potential lines associated with the bridge and eliminates certain faults. the information obtained from the path-trace from failing outputs is combined using an intersection graph to make further deductions. the intersection graph implicitly represents all candidate faults, thereby obviating the need to enumerate faults and hence allowing the exploration of the space of all faults. the above procedures are performed dynamically and a reduced intersection graph is maintained to reduce memory and simulation time. no dictionary or fault simulation is required. results are provided for all large iscas89 benchmark circuits. for the largest benchmark circuit, the procedure reduces the space of all bridging faults, which is of the order of 10^9 to a few hundred faults on the average in about 30 seconds of execution time.
practical techniques to reduce skew and its variations in buffered clock networks. clock skew is becoming increasingly difficult to control due to variations. link based non-tree clock distribution is a cost-effective technique for reducing clock skew variations. however, previous works based on this technique were limited to unbuffered clock networks and neglected spatial correlations in the experimental validation. in this work, we overcome these shortcomings and make the link based non-tree approach feasible for realistic designs. the short circuit risk and multi-driver delay issues in buffered non-tree clock networks are investigated. our approach is validated with spice based monte carlo simulations, considering spatial correlations among variations. the experimental results show that our approach can reduce the maximal skew by 47%, improve the skew yield from 15% to 73% on average with a decrease on the total wire and buffer capacitance.
subtract: a program for the efficient evaluation of substrate parasitics in integrated circuits. algorithms for the efficient evaluation of substrate parasitics in mixed-signal integrated circuits have been developed and incorporated in an extraction tool for substrate parasitics, subtract. using a preprocessed, polynomial- based boundary element method, subtract enables the parasitic extraction process to be completely technology independent, allowing for fast evaluation. additionally, techniques to accelerate the iterative solution of the resulting impedance matrix have been developed and employed to further improve the speed advantages that this method offers. the preprocessed boundary element method is more efficient than finite-difference schemes and orders of magnitude faster than general boundary element methods using a direct evaluation of green's function. results of employing subtract to the design and verification of a mixed-signal a/d converter ic are described.
logic synthesis techniques for reduced area implementation of multilevel circuits with concurrent error detection. this paper presents new logic synthesis techniques for generating multilevel circuits with concurrent error detection based on a parity-check code scheme that can detect all errors caused by single stuck-at faults. these synthesis techniques fully automate the design process and allow for a better quality result than previous methods thereby reducing the cost of concurrent error detection. an algorithm is described for selecting a good parity-check code for encoding the outputs of a circuit. once the code has been chosen, a new procedure called structure-constrained logic optimization is used to minimize the area of the circuit as much as possible while still using a circuit structure that ensures that single stuck-at faults cannot produce undetected errors. the implementation that is generated is path fault secure and when augmented by a checker forms a self-checking circuit. results indicate that self-checking multilevel circuits can be generated which require significantly less area than using duplication.
ust/dme: a clock tree router for general skew constraints. in this paper, we propose new approaches for solving the useful-skew tree (ust) routing problem [17]: clock routing subject to general skew constraints. the clock layout synthesis engine of our ust algorithms is based on the deferred-merge embedding (dme) paradigm for zero-skew tree [5; 1] and bounded-skew tree [8; 2] routings; hence, the names ust/dme and greedy-ust/dme for our algorithms. they simultaneously perform skew scheduling and tree routing such that each local skew range is incrementally refined to a skew value that minimizes the wirelength during the bottom-up merging phase of dme. the resulting skew schedule is not only feasible, but is also best for routing in terms of wirelength. the experimental results show very encouraging improvement over the previous bst/dme algorithm on three iscas89 benchmarks under general skew constraints in terms of total wirelength.
jitter-tolerant clock routing in two-phase synchronous systems. due to process, manufacturing and system operating conditions in a real environment, clock jitter is inevitable. in the presence of jitter, zero or near-zero skew are not really safe for reliable clock operations. appropriate skew or useful skew can serve as a safety margin to guard against clock jitter. in two-phase clocking, the nonoverlapping interval of two-phase clocks provides an additional degree of freedom to improve either the clock tree cost or jitter-tolerance. we construct a two-phase jitter-tolerant useful-skew tree (jt-ust) such that the susceptibility to clock jitter and the clock tree cost is minimized. following the deferred-merge embedding (dme) framework, we use a simulated annealing approach to explore the routing topologies and embeddings. experimental results have shown 63% to 100% reduction of jitter-prone sink pairs over previous clock routing methods while having very comparable clock tree costs.
physics-based compact modeling for nonclassical cmos. physics-based compact modeling, as opposed to the conventional empirical approach, is emphasized for nanoscale nonclassical cmos. ufdg, a physics-based compact model for generic double-gate mosfets with ultra-thin bodies, is overviewed, and its applications to double- and (multiple) independent-gate finfet device and circuit design are demonstrated.
efficiency improvements for force-directed scheduling. force-directed scheduling is a technique which schedules operations under time constraints in order to achieve schedules with a minimum number of resources. the worst case time complexity of the algorithm is cubic in the number of operations. this is due to the computation of the changes in the distribution functions needed for the force calculations. an incremental way to compute the changes in the distribution functions, based on gradual time-frame reduction, is presented. this reduces the time complexity of the algorithm to quadratic in the number of operations, without any loss in effectiveness or generality of the algorithm. implementations show a substantial cpu-time reduction of force-directed scheduling, which is illustrated by means of some industrially relevant examples
predicting the performance of synchronous discrete event simulation systems. in this paper we propose a model to predict the performance of synchronous discrete event simulation. the model considers parameters including the number of active objects per cycle, event execution granularity and communication cost. we derive a single formula that predicts the performance of synchronous simulation.we have benchmarked several vhdl circuits on sgi origin 2000. the benchmark results show that the prediction model explains more than 90% of parallel simulation execution time. we also measure the effect of computation granularity over performance. the benchmark results show that although higher granularity can have better speedup because of dominance of computation over communication, the computational granularity cannot overshadow the inherent synchronization cost. this model can be used to predict the speed-up expected for synchronous simulation, and to decide whether it is worthwhile to use synchronous simulation before actually implementing it.
relaxation-based harmonic balance technique for semiconductor device simulation. harmonic and intermodulation distortion effects play an important role in numerous analog applications, particularly in such areas as wireless communication systems. in this paper, we present a two-dimensional harmonic balance semiconductor device simulator which accurately models these nonlinear effects at the physical (drift-diffusion) level. the simulator is based on stanford university's pisces code, and supports the full range of physical models and features present in the time-domain version of the program. a modified block gauss-seidel-newton nonlinear relaxation scheme is developed to efficiently handle the extremely large size of two-dimensional harmonic balance semiconductor device simulation problems.
a yield improvement methodology using pre- and post-silicon statistical clock scheduling. in deep sub-micron technologies, process variations can cause significant path delay and clock skew uncertainties thereby lead to timing failure and yield loss. in this paper, we propose a comprehensive clock scheduling methodology that improves timing and yield through both pre-silicon clock scheduling and post-silicon clock tuning. first, an optimal clock scheduling algorithm has been developed to allocate the slack for each path according to its timing uncertainty. to balance the skew that can be caused by process variations, programmable delay elements are inserted at the clock inputs of a small set of flip-flops on the timing critical paths. a delay-fault testing scheme combined with linear programming is used to identify and eliminate timing violations in the manufactured chips. experimental results show that our methodology achieves substantial yield improvement over a traditional clock scheduling algorithm in many of the iscas89 benchmark circuits, and obtain an average yield improvement of 13.6%.
a search-based bump-and-refit approach to incremental routing for eco applications in fpgas. incremental physical cad is encountered frequently in the so-called engineering change order (eco) process in which design changes are made typically late in the design process in order to correct logical and/or technological problems in the circuit. as far as routing is concerned, in order to capitalize on the enormous resources and time already spent on routing the circuit, and to meet time-to-market requirements, it is desirable to re-route only the eco-affected portion of the circuit, while minimizing any routing changes in the much larger unaffected part of the circuit. incremental re-routing also needs to be fast and to effectively use available routing resources. in this paper, we develop a complete incremental routing methodology for fpgas using a novel approach called bump and refit (b&r); b&r was initially proposed in [4] in the much simpler context of extending some nets by a segment (for the purpose of fault tolerance) for fpgas with simple i-to-i switchboxes. here we significantly extend this concept to global and detailed incremental routing for fpgas with complex switchboxes such as those in lucent's orca and xilinx's virtex series. we also introduce new concepts such as b&r cost estimation during global routing, and determination of the optimal subnet set to bump for each bumped net, which we obtain using an efficient dynamic programming formulation. the basic b&r idea in our algorithms is to re-arrange some portions of some existing nets on other tracks within their current channels to find valid routings for the incrementally changed circuit without requiring any extra routing resources (i.e., completely unused tracks), and with little effect on the electrical properties of existing nets.we have developed optimal and near-optimal algorithms (called subsec_b&r and subnet_b&r, respectively) to find incremental routing solutions using the b&r paradigm in complex fpgas. we implemented these algorithms for lucent's orca-2c fpga, and compared our algorithms to two recent incremental routing techniques, standard and rip-up&reroute, and to lucent's a_par routing tool. experimental results show that our incremental routers perform very well for eco applications. firstly, b&r is 10 to 20 times faster than complete re-routing using a_par. further, the b&r incremental routers are nearly 27% faster and the new nets have nearly 10% smaller lengths than in previous incremental techniques. also, the b&r routers do not change either the lengths or topologies of existing nets, a significant advantage in eco applications, in contrast to rip-up&reroute which increases the length of ripped up nets by an average of 8.75% to 13.6%.
weighted control scheduling. this paper describes a practical technique for the optimal scheduling of control dominated systems minimizing the weighted average latency over all control branches. such a weighted metric is crucial for control dependent scheduling to accommodate practical architectural goals. in contrast to most weighting mechanisms, a nonbayesian probabilistic measure is used to avoid assumptions of branch independence. the underlying scheduling model allows general fsm-based models for operations, captures several forms of speculative execution and scales well with increasing control complexity.
improved use of the carry-save representation for the synthesis of complex arithmetic circuits. the increasing importance of datapath circuits in complex systems-on-chip calls for special arithmetic optimisations. the goal is to achieve automatically the handcrafted results which escape classic logic optimisations. some work has been done in the recent years to infer the use of the carry-save representation in the synthesis of arithmetic circuits. yet, many cases of practical interest cannot be handled due to the scattering of logic operations among the arithmetic ones - especially in arithmetic computations which are originally described at the bit level in high-level languages such as c. we therefore introduce an algorithm to restructure dataflow graphs so that they can be synthesized in high-quality arithmetic circuits, close, to those that an expert designer would conceive. on typical embedded software benchmarks which could be advantageously implemented with hardware accelerators, our technique always reduces tangibly the critical path by up to 46% and generally achieves the quality of manual implementations. in many cases, our algorithm also manages to reduce the cell area by up to 10-20%.
bus encoding to prevent crosstalk delay. the propagation delay across long on-chip buses is increasingly becoming a limiting factor in high-speed designs. crosstalk between adjacent wires on the bus may create a significant portion of this delay. placing a shield wire between each signal wire alleviates the crosstalk problem but doubles the area used by the bus, an unacceptable consequence when the bus is routed using scarce top-level metal resources. instead, we propose to employ data encoding to eliminate crosstalk delay within a bus. this paper presents a rigorous analysis of the theory behind "self-shielding codes", and gives the fundamental theoretical limits on the performance of codes with and without memory. specifically, we find that a 32-bit bus can be encoded with 40 wires using a code with memory or 46 wires with a memoryless code, in comparison to the 63 wires required with simple shielding.
hierarchical timing analysis using conditional delays. we present a novel method to perform timing analysis of hierarchical circuits. it is based on the representation of circuit modules by conditional delay matrices (cdms) which combine module delays with event propagation conditions. the cdm model is independent of module complexity and allows automatic identification of false paths. we exploit hierarchy information to perform efficient delay computation. the effectiveness of the method is demonstrated on a high-level model of the iscas-85 circuit c6288, which is difficult to analyze using traditional approaches. the method has been implemented in a symbolic timing analysis program called cat. the application of cat to carry-skip adders shows that hierarchical timing analysis is faster by an order of magnitude than gate-level analysis.
an approximate timing analysis method for datapath circuits. we present a novel timing analysis method acd that computes an approximate value for the delay of datapath circuits. based on the conditional delay matrix (cdm) formalism we introduced earlier, the acd method exploits the fact that most datapath signals are directed by a small set of control inputs. the signal propagation conditions are restricted to a set of predefined control inputs, which results in significant reductions in the size of the conditions as well as computation time. we have implemented acd and experimented with reverse-engineered high-level versions of the iscas-85 benchmarks. our results demonstrate up to three orders of magnitude speedup in computation time over exact methods, with little or no loss in accuracy.
deep submicron defect detection with the energy consumption ratio. advances in technology and increasing integration are expected to degrade the effectiveness of iddq test. total leakage currents per ic are expected to be very large, making it difficult to detect the impact of a single defect (t.w. williams et al., 1996; m. sachdev, 1997). test methods which detect faults by monitoring the dynamic supply current have been suggested as one alternative. almost all the dynamic current techniques proposed in the literature are adversely affected by the impact of process variations. many are also susceptible to timing and magnitude errors in measurement. the energy consumption ratio (ecr) is a new dynamic current-based test metric (b. vinnakota et al., 1998), that addresses some of these problems. ecr-based test offers several advantages over other dynamic test methods and the iddq test such as tolerance to process variations, reduced test process complexity and a proven ability to detect faults that escape other techniques. the ecr has been validated through extensive simulation and through application to a 50k gate sub-micron biomedical ic (w. jiang and b. vinnakota, 1999). our contributions are directed towards further validating the real quality of the ecr
perfect-balance planar clock routing with minimal path-length. the design of high speed digital vlsi circuits prefers that the clock net is routed on the metal layer with the smallest rc delay. this strategy not only avoids the difficulties of having different electrical parameters on different layers, but also eliminates the delay and attenuation of the clock signal through vias. the clock phase-delay is also decreased. in this paper, we present a novel algorithm, based on hierarchical max-min optimization, to construct a planar clock tree which can be embedded on a single metal layer. the clock tree achieves equal path length---the length of the path from the clock source to each clock terminal is exactly the same. in addition, the path length from the source to clock terminals is minimized. some examples including industrial benchmarks have been tested and the results are promising. we further optimize the geometry of the clock tree to minimize both the skew and path delay of the clock signal while maintaining the planarity of the clock network. some premilinary results are promising which achieve near zero skew by using spice simulation.(supersedes ucsc-crl-92-12)
symbolic pointer analysis. one of the bottlenecks in the recent movement of hardware synthesis from behavioral c programs is the difficulty in reasoning about runtime pointer values at compile time. the pointer analysis problem has been investigated in the compiler community for two decades, which has yielded efficient, polynomial time algorithms for context-insensitive analysis. however, at the accuracy level for which hardware synthesis is desired, namely context and flow sensitive analysis, the time and space complexity of the best algorithms reported grow exponentially with program size. in this paper, we present our first step towards a new analysis technology which potentially leads to almost-linear time complexity and sub-linear space complexity algorithm even for the most accurate analysis. the key idea that contributes to this efficiency is to implicitly encode the pointer-to relation in the boolean domain, thereby capturing the procedure transfer function completely, compactly and canonically. this represents a wide departure from the traditional techniques, all of which explicitly capture pointer-to relation using variations of point-to graph, which have to be re-evaluated for different calling contexts. experiments for our first flow-insensitive algorithm on common benchmarks show promising result.
optimization techniques for high-performance digital circuits. the relentless push for high performance in custom digital circuits has led to renewed emphasis on circuit optimization or tuning. the parameters of the optimization are typically transistor and interconnect sizes. the design metrics are not just delay, transition times, power and area, but also signal integrity and manufacturability. this tutorial paper discusses some of the recently proposed methods of circuit optimization, with an emphasis on practical application and methodology impact. circuit optimization techniques fall into three broad categories. the first is dynamic tuning, based on time-domain simulation of the underlying circuit, typically combined with adjoint sensitivity computation. these methods are accurate but require the specification of input signals, and are best applied to small data-flow circuits and "cross-sections" of larger circuits. efficient sensitivity computation renders feasible the tuning of circuits with a few thousand transistors. second, static tuners employ static timing analysis to evaluate the performance of the circuit. all paths through the logic are simultaneously tuned, and no input vectors are required. large control macros are best tuned by these methods. however, in the context of deep submicron custom design, the inaccuracy of the delay models employed by these methods often limits their utility. aggressive dynamic or static tuning can push a circuit into a precipitous corner of the manufacturing process space, which is a problem addressed by the third class of circuit optimization tools, statistical tuners. statistical techniques are used to enhance manufacturability or maximize yield. in addition to surveying the above techniques, topics such as the use of state-of-the-art nonlinear optimization methods and special considerations for interconnect sizing, clock tree optimization and noise-aware tuning will be briefly considered.
post global routing crosstalk risk estimation and reduction. previous approaches for crosstalk synthesis often fail to achieve satisfactory results due to limited routing flexibility. furthermore, the risk tolerance bounds partitioning problem critical for constrained optimization has not been adequately addressed. this paper presents the first approach for crosstalk risk estimation and reduction at the global (instead of detailed) routing level. it quantitatively defines and estimates the risk of each routing region using a graph-based optimization approach and globally adjusts routes of nets for risk reduction. at the end of the entire optimization process, a risk-free global routing solution is obtained together with partitions of nets' risk tolerance bounds which reflect the crosstalk situation of the chip. the proposed approach has been implemented and tested on cbl/ncsu benchmarks and the experimental results are very promising.
timing-driven placement for heterogeneous field programmable gate array. in this paper, a new timing-driven placement algorithm is proposed to handle complicated placement requirements inherent in fpgas with heterogeneous resources (dedicated logic block, memory block). the new algorithm employs a multi-layer density system with each layer modeling a drastically different architectural resource. by introducing the multi-layer density system, a heterogeneous placement task is translated to a set of homogeneous ones, with each of them being handled at a different density layer. we also present a new iterative timing optimization scheme which is seamlessly integrated in the placement process. the tight interaction between the placement and timing optimization produces superior timing results for industrial designs.
formulation of static circuit optimization with reduced size, degeneracy and redundancy by timing graph manipulation. static circuit optimization implies sizing of transistors and wires on a static timing basis, taking into account all paths through a circuit. previous methods of formulating static circuit optimization produce problem statements that are very large and contain inherent redundancy and degeneracy. in this paper, a method of manipulating the timing formulation is presented which produces a dramatically more compact optimization problem, and reduces redundancy and degeneracy. the circuit optimization is therefore more efficient and effective. numerical results to demonstrate these improvements are presented.
a unified signal transition graph model for asynchronous control circuit synthesis. both low-level (analysis-oriented) and high-level (specification-oriented) models for asynchronous circuits and the environment where they operate, together with strong equivalence results between the properties at the low levels, are described. one interesting side result is the precise characterization of classical static and dynamic hazards in terms of the model. consequently the designer can check the specification and directly decide if the behavior of any implementation will depend, e.g., on the delays of the signals described by such specification
solving the minimum-cost satisfiability problem using sat based branch-and-bound search. boolean satisfiability (sat) has seen many successful applications in various fields, such as electronic design automation (eda) and artificial intelligence (ai). however, in some cases it may be required/preferable to use variations of the general sat problem. in this paper we consider one important variation, the minimum-cost satisfiability problem (mincostsat). mincostsat is a sat problem which minimizes the cost of the satisfying assignment. mincostsat has various applications, e.g. automatic test pattern generation (atpg), fpga routing, ai planning, etc. this problem has been tackled before - first by covering algorithms, e.g. scherzo [3], and more recently by sat based algorithms, e.g. bsolo [16]. however the sat algorithms they are based on are not the current generation of highly efficient solvers. the solvers in this generation, e.g. chaff [20], minisat [5] etc., incorporate several new advances, e.g. two literal watching based boolean constraint propagation, that have delivered order of magnitude speedups. we first point out the challenges in using this class of solvers for the mincostsat problem and then present techniques to overcome these challenges. the resulting solver mincostchaff shows order of magnitude improvement over several current best known branch-and-bound solvers for a large class of problems, ranging from minimum test pattern generation, bounded model checking in eda to graph coloring and planning in ai.
hybrid floorplanning based on partial clustering and module restructuring. in this paper, we propose a hybrid floorplanning methodology. two hierarchical strategies for avoiding local optima during iterative improvement are proposed: (1) partial clustering, and (2) module restructuring. these strategies work for localizing nets connecting small modules in small regions, and conceal such small modules and their nets during the iterative improvement phase. this method is successful in reducing both area and wire length in addition to reducing the computational time required for optimization. although our method only searches slicing floorplans, the results are superior to the results obtained even with non-slicing floorplans. we applied our method to the largest mcnc floorplan benchmark example, ami49, and industrial data. for the ami49 benchmark, we obtained results superior to any published results for both estimated area and routing results.
clock skew optimization for ground bounce control. high speed synchronous digital systems require large switching currents to facilitate rapid signal transitions. these large currents create voltage drops on the power distribution network and necessitate expensive chip packaging with a large number of supply pins. in this paper we propose a novel technique to reduce the dynamic transient current drawn from the supply pins. our approach is based on sub-dividing the synchronous clocking into multiple sub-clocks with relative skew. this spreads the computation across the entire clock cycle instead of largely occurring at the beginning. timing constraints must also be obeyed, so that no races or timing errors are introduced. we propose an exact algorithm based on integer linear programming to solve this problem. we have used our method in the design of a 5ghz ecl encoder chip to achieve a factor of two reduction in ground bounce, as shown by hspice simulations. we also obtained order-of-magnitude improvements in ground bounce on benchmarks laid out in sub-micron cmos technology. the approach potentially leads to significant reductions in packaging costs.
a new method to express functional permissibilities for lut based fpgas and its applications. this paper presents a new method to express functional permissibilities for look-up table (lut) based field programmable gate arrays (fpgas). the method represents functional permissibilities by using sets of pairs of functions, not by incompletely specified functions. it makes good use of the properties of luts such that their internal logics can be freely changed. the permissibilities expressed by the proposed method have the desired property that at many points of a network they can be simultaneously treated. applications of the proposed method are also presented; a method to optimize networks and a method to remove connections that are obstacles at the routing step. preliminary experimental results are given to show the effectiveness of our proposed method.
mixed-size placement via line search. we describe a remarkably simple yet very effective line search technique for cell placement. our method "corrects" errors in force scaling by sampling different force weights in each iteration of placement and selecting the best candidate placements based on an objective function. our technique is not only very fast, but it does away with the need for the ad hoc scaling that has plagued prior force-directed methods. we describe the implementation of our method within a multilevel flow and show that it can achieve good wire lengths with competitive run-times compared to other academic tools. specifically, we produce placements with 12% and 15% better hpwl than fengshui 5.0 and capo 9.1, respectively, on the iccad04 mixed-size benchmarks, while presenting run-times that are 37% faster than capo 9.1.
engineering details of a stable force-directed placer. analytic placement methods that simultaneously minimize wire length and spread cells are receiving renewed attention from both academia and industry. we describe the implementation details of a force-directed placer, fdp. specifically, we provide: (1) a description of efficient force computation for spreading cells; (2) an illustration of numerical instability in these methods and a means by which these instabilities are avoided; (3) spread metrics for measuring cell distribution throughout the placement region; and (4) a complementary technique which aids in directly minimizing hpwl. we present results comparing our analytic placer to other academic tools for both standard cell and mixed-size designs. compared to kraftwerk and capo 8.7, our tool produces results with an average improvement of 9% and 3%, respectively.
combined dynamic voltage scaling and adaptive body biasing for heterogeneous distributed real-time embedded systems. dynamic voltage scaling (dvs) is a powerful technique for reducingdynamic power consumption in a computing system. however, astechnology feature size continues to scale, leakage power is increasing and willlimit power savings obtained by dvs alone. previous system-level real-timescheduling approaches use dvs alone to optimize power consumption withoutconsidering leakage power. to overcome this limitation, we propose a newscheduling algorithm that combines dvs and adaptive body biasing (abb)to simultaneously optimize both dynamic power consumption and leakagepower consumption for real-time distributed embedded systems. first, wederive an analytical expression to determine the optimal supply voltage andbody bias voltage under a given clock frequency. based on this expression, wecompute the optimal energy consumption at a given clock frequency and analyzethe tradeoff between energy consumption and execution time for a set oftasks with precedence relationships and real-time constraints. we then proposea scheduling algorithm to reduce total power consumption under givenreal-time constraints. this algorithm also considers variations in power consumptionof different tasks and characteristics of different voltage-scalableprocessing elements (pes) to maximize power reduction. experimental resultsshow that the average power reduction of our technique with respect todvs alone is 34.7%, while the average saving compared to no voltage scalingis 68.3% for the 0.07µm technology.
generalized matching from theory to application. we present a novel approach for post-mapping optimization. we exploit the concept of generalised matching, a technique that finds symbolically all possible matching assignments of library cells to a multi-output network specified by a boolean relation. several objectives are targeted: area minimization under delay constraints; power minimization under delay constraints; and unconstrained delay minimization. we describe the theory of generalized matching and the algorithmic optimization required for its efficient and robust implementation. a tool based on generalized matching has been implemented and tested on large examples of the mcnc'91 benchmark suite. we obtain sizable improvements in: speed (6% in average, up to 20.7%); area under speed constraints (13.7% an average, up to 29.5%); and power under speed constraints (22.3% in average, up to 38.1%).
optimized power-delay curve generation for standard cell ics. an effective way to compare logic techniques, logic families, or cell libraries is by means of power (or area) versus delay plots, since the efficiency of achieving a particular delay is of crucial significance. in this paper we describe a method of producing an optimized power versus delay curve for a combinational circuit. we then describe a method for comparing the relative merits of a set of power versus delay curves for a circuit, each generated with a different cell library. our results indicate that very few combinational functions need to be in a cell library, at most 11. the power-delay points achieved by design compiler from synopsys using the state-of-the-art artisan sage-x library compare unfavorably to our approach. in terms of minimum energy-delay product, our approach is superior by 79% on average. our approach yields the same delay points with a 107% savings in power consumption, on average. we also show that the specified vdd for a process technology should only be used for the absolute fastest implementations of a circuit.
hurwitz stable reduced order modelling for rlc interconnect trees. we present a new relizable reduced order modeling technique for rlc interconnect trees. both lumped and distributed wire models can be used with this technique. provable stability is achieved by using hurwitz polynomials. moment computation process is avoided but moments can still be matched implicitly. in experiments, the proposed hurwitz three-pole model can accurately and efficiently capture inductive effect for both near end and far end nodes.
timing-driven placement using design hierarchy guided constraint generation. design hierarchy plays an important role in timing-driven placement for large circuits. in this paper, we present a new methodology for delay budgeting based timing-driven placement. a novel slack assignment approach is described as well as its application on delay budgeting with design hierarchy information. the proposed timing-driven placement flow is implemented into a placement tool named dragon (timing-driven mode), and evaluated using an industrial place and route flow. compared to cadence qplace, timing-driven dragon generates placement results with shorter clock cycle and better routability.
efficient finite-difference method for quasi-periodic steady-state and small signal analyses. this paper discusses a finite-difference mixed frequency-time (mft) method for the quasi-periodic steady-state analysis and introduces the quasi-periodic small signal analysis. a new approach for solving the huge nonlinear system the mft finite difference method generates from practical circuits is given, which makes efficient frequency-sweeping quasi-periodic small-signal analysis possible. the new efficient solving technique works well with the krylovsubspace recycling or reuse [4], which can not be achieved with existing techniques. in addition, this paper gives a way to calculate the quasi-periodic fourier integration weights, necessary in the adjoint mft small-signal analyses, and a way to calculate quasi-periodic large-signal fourier spectrum that is more efficient than existing methods. numerical examples also show that the finite-difference mft method can be significantly more accurate than shooting-newton mft method and the new preconditioning technique is more efficient.
multi-level logic optimization of fsm networks. current approaches to compute and exploit the flexibility of a component in an fsm network are all at the symbolic level. conventionally, exploitation of this flexibility relies on state minimizers for incompletely specified fsms (isfsms) or pseudo non-deterministic fsms (pndfsm's). however, state-of-the art state minimizers cannot handle large isfsms or pndfsms. in addition, these exploitation techniques are at the symbolic level, not directly at the net-list logic level. we present a general approach to exploit exact or approximate flexibility directly at the net-list logic level, and we demonstrate that many sequential logic optimization techniques can be applied in exploitation. moreover, we propose a new procedure for input don't care sequences. as a result, both computation and exploitation of input don't care sequences in larger fsm networks can be made efficient and effective. finally, we give preliminary results on some artificially constructed fsm networks. preliminary results indicate that our approach can be effective in reducing the size of a component of an fsm network
gste through a case study. generalized symbolic trajectory evaluation (gste) [17, 18, 19] is a very significant extension of ste that has the power to verify all &omega;-regular properties but at the same time preserves the benefits of the original ste [16]. it also extends the symbolic quaternary model used by ste to support seamless model refinement for efficiency and accuracy trade-off in gste model checking. in this paper, we present a case study on fifo verification to illustrate the strength of gste and demonstrate its methodology in specifying and verifying large scale designs.
stochastic analysis of interconnect performance in the presence of process variations. deformations in interconnect due to process variations can lead to significant performance degradation in deep sub-micron circuits. timing analyzers attempt to capture the effects of variation on delay with simplified models. the timing verification of rc or rlc networks requires the substitution of such simplified models with spatial stochastic processes that capture the random nature of process variations. the present work proposes a new and viable method to compute the stochastic response of interconnects. the technique models the stochastic response in an infinite dimensional hilbert space in terms of orthogonal polynomial expansions. a finite representation is obtained by using the galerkin approach of minimizing the hilbert space norm of the residual error. the key advance of the proposed method is that it provides a functional representation of the response of the system in terms of the random variables that represent the process variations. the proposed algorithm has been implemented in a procedure called opera, results from opera simulations on commercial design test cases match well with those from the classical monte carlo spice simulations and from perturbation methods. additionally opera shows good computational efficiency: speedup factor of 60 has been observed over monte carlo spice simulations.
noise margin analysis for dynamic logic circuits. we consider the problem of noise margin analysis for dynamic logic circuits. because such circuits operate in multiple phases, their noise immunity is also time varying. we formulate noise margin analysis as a non-linear optimization problem where we find the smallest disturbance waveform that results in a qualitative change in the behavior of the circuit. we present a practical method for solving these optimization problems based on deriving a sensitivity matrix for the small-signal response of the circuit. we use our approach to compare the robustness of static cmos gates, self-resetting domino, and output prediction logic.
the compositional far side of image computation. symbolic image computation is the most fundamental computationin bdd-based sequential system optimization and formal verification.in this paper, we explore the use of over-approximationand bdd minimization with donýt cares during image computation.our new method, based on the partitioned representation ofthe transition relation, consists of three phases: first, the model istreated as a set of loosely coupled components, and over-approximateimages are computed to minimize the transition relation ofeach component. a refined overall image is then computed usingthe simplified transition relation. finally, the exact image isobtained by a clipping operation that recovers all previous over-approximations.since bdd minimization employs constraints on thenext-state variables of the transition relation, instead of the customaryconstraints on the present-state variables, we call the resultingmethod far side image computation.the new method can be implemented on top of any image computationalgorithm that is based on the partitioned transition relation.(for example, iwls95, mlp, and fine-grain.)we demonstrate the effectiveness of our approach by experimentson models ranging from easy to hard: the new method wins significantlyover the best known algorithms so far in both cpu timeand memory usage, especially on the hard models.
rlc interconnect delay estimation via moments of amplitude and phase response. a new category of moments&mdash;amplitude and phase moments (ap moments) are introduced for rlc interconnect delay estimation. we show that there are tight relationships between ap moments, circuit moments and central moments. the first order ap moment represents the elmore delay while the higher order ap moments can be used to represent the error between the elmore delay and the exact 50% delay from the view of gain and phase-shift variation. with the help of the physical meaning revealed by the ap moments, a closed-form 50% delay model&mdash;ap delay model is proposed for rlc interconnect delay estimation in terms of the first four ap moments. we also propose a new two-pole model (ap two-pole model) by matching the first two phase moments of the transfer function. the ap two-pole model can be used for more generally timing parameters estimation. the input signal's impact on delay estimation can be incorporated into these two delay models by simply combining the input signal's ap moments with the transfer function's ap moments. in our experiments these two models show significant accuracy improvement over the elmore delay model.
the chebyshev expansion based passive model for distributed interconnect networks. a new chebyshev expansion based model for distributed interconnect networks is presented in this paper. unlike the moment methods, this new model is optimal and it does not require the knowledge of expansion points. an automatic order selection scheme is also included in the new model. by using the integrated congruence transform, we guarantee the passivity of the new model for distributed interconnect networks. because of the orthogonality of chebyshev polynomials, the modified gram-schmidt algorithm can be simplified. in the experimental examples, the new model is found to be accurate and efficient.
congestion reduction during placement based on integer programming. this paper presents a novel method to reduce routing congestion during placement stage. the proposed approach is used as a post-processing step in placement. congestion reduction is based on local improvement on the existing layout. however, the approach has a global view of the congestion over the entire design. it uses integer linear programming (ilp) to formulate the conflicts between multiple congested regions, and performs local improvement according to the solution of ilp. experiments show that the proposed approach can effectively reduce the total overflow of global routing result. the short running time of the algorithm indicates good scalability on large designs.
frosty: a fast hierarchy extractor for industrial cmos circuits. this paper presents frosty, a computer programfor automatically extracting the hierarchy of a large-scale digitalcmos circuit from its transistor-level netlist description and alibrary of subcircuits. to handle the complexity of industrialcircuits, frosty combines traditional structural recognition andpattern matching methods into a two-step extraction process.first, gate structures based on channel-connected-components arerecognized from a circuit netlist and library subcircuits. thenannotated graphs representing the connectivity and properties ofgate structures are constructed. comparing to transistor-levelnetlists, these graphs are much smaller in size, moredistinguishable in structure, and are thus more suitable forlabeling based pattern matching. an efficient pattern matchingalgorithm is applied to extract the circuit hierarchy from thesecondensed circuit graphs. frosty has been demonstrated to beorders of magnitude faster than the best known extractionprogram subgemini, capable of extracting the entire hierarchy ofindustrial designs with several hundred thousand transistors in afew minutes on a sun workstation. further frosty is scale withthe size of a circuit.
efficient network flow based min-cut balanced partitioning. we consider the problem of bipartitioning a circuit into two balanced components that minimizes the number of crossing nets. previously, the kernighan and lin type (k&l) heuristics, the simulated annealing approach, and the spectral method were given to solve the problem. however, network flow techniques were overlooked as a viable approach to min-cut balanced bipartition to due its high complexity. in this paper we propose a balanced bipartition heuristic based on repeated max-flow min-cut techniques, and give an efficient implementation that has the same asymptotic time complexity as that of one max-flow computation. we implemented our heuristic algorithm in a package called fbb. the experimental results demonstrate that fbb outperforms the k&l heuristics and the spectral method in terms of the number of crossing nets, and the efficient implementation makes it possible to partition large, circuit instances with reasonable runtime. for example, the average elapsed time for bipartitioning a circuit s35932 of almost 20k gates is less than 20 minutes.
redi: an efficient fault oriented procedure to identify redundant faults in combinational logic circuits. in this work, a new and effective procedure, called redi, to efficiently identify redundant single stuck-at faults in combinational logic circuits is proposed. the method is fault oriented and uses sensitizability of partial paths to determine redundant faults. it uses only implications and hence may not determine all the redundant faults of a circuit. however, experimental results presented on benchmark circuits show that the procedure identifies nearly all the redundant faults in most of the benchmark circuits. the key features of redi that make it efficient are: partial path sensitization, blockage learning, dynamic branch ordering and fault grouping. experimental results on benchmark circuits demonstrate the efficiency of the proposed procedure in identifying redundant faults in combinational logic circuits.
edge-map: optimal performance driven technology mapping for iterative lut based fpga designs. we consider the problem of performance driven lookup-table (lut) based technology mapping for fp-gas using a general delay model. in the general delay model, each interconnection edge has a weight representing the delay of the interconnection. this model is particularly useful when combined with an iterative re-technology mapping process where the actual delays of the placed and routed circuit are fed-back to the technology mapping phase to improve the mapping based on the more realistic delay estimation. well-known technology mappers such as flowmap and chortle-d only minimize the number of levels in the technology mapped circuit and hence are not suitable for such an iterative re-technology mapping process. recently, mather and liu in [ml94] studied the performance driven technology mapping problem using the general delay model and presented an effective heuristic algorithm for the problem. in this paper, we present an efficient technology mapping algorithm that achieves provably optimal delay in the technology mapped circuit using the general delay model. our algorithm is a non-trivial generalization of flowmap. a key problem in our algorithm is to compute a k-feasible network cut such that the circuit delay on every cut edge is upper-bounded by a specific value. we implemented our algorithm in a lut based fpga technology mapping package called edge-map, and tested edge-map on a set of benchmark circuits.
rtl power optimization with gate-level accuracy. traditional rtl power optimization techniques committransformations at the rtl based on the estimation of area, delayand power. however, because of inadequate power and delayinformation, the power optimization transformations applied atthe rtl may cause unexpected results after synthesis, such asworsened delay or increased power dissipation. our solution tothis problem is to divide rtl power optimization into two steps,namely rtl exploration and gate-level commitment. during rtlexploration phase potential candidates for applying some specificrtl transformation are identified where high level informationpermits faster and more effective analysis. these candidates aresimply "marked" on the netlist. then during the gate-levelcommitment phase when accurate power and delay information isavailable, the final decision of whether accepting or rejecting thecandidate is made to achieve the best power and delay trade-offs.
new algorithms for min-cut replication in partitioned circuits. abstract: hwang and el gamal (1992, 1995) formulated the min-cut replication problem, which is to determine min-cut replication sets for the components of a k-way partition such that the cut size of the partition is minimized after the replication. they gave an optimal algorithm for finding min-cut replication sets for a k-way partitioned digraph. however, their optimal min-cut replication algorithm does not guarantee min-cut replication sets of minimum sizes. furthermore, their algorithm is not optimal for hypergraphs. in this paper, we optimally solve the min-area min-cut replication problem on digraphs, which is to find min-cut replication sets with the minimum sizes. more importantly, we give an optimal solution to the hypergraph min-area min-cut replication problem using a much smaller flow network model. we implemented our algorithms in a package called hyper-mamc, and interfaced hyper-mamc to the tapir package. on average, hyper-mamc produces 57.3% fewer cut nets and runs much faster than mo-rep in the tapir package, on the same initial partitions of a set of mcnc partition93 benchmark circuits.
cosmos: a continuous optimization approach for maximum power estimation of cmos circuits. maximum instantaneous power in vlsi circuits has a great impact on circuit's reliability and the design of power and ground lines. to synthesize highly reliable systems, accurate estimates of maximum power must be obtained in various design phases. unfortunately, determining the input patterns to induce the maximum current (power) is essentially a combinatorial optimization problem. even for circuits with small number of primary inputs (pi's), it is cpu time intensive to conduct exhaustive search in the input vector space. the only feasible way is to find good upper and lower bounds of the maximum power, and to make the gap between these two bounds as narrow as possible. in this paper, we present a continuous optimization approach to efficiently generate tight lower bounds of the maximum instantaneous power for cmos circuits. in our approach, each primary input (pi) of the circuit is allowed to assume any real number between 0 and 1. maximum power estimation for cmos circuits is then transformed into a continuous optimization problem, in which a smooth function is maximized over a unit hypercube in the euclidean space. the continuous problem can be solved efficiently to generate good lower bounds of the maximum power. our experiments with iscas and mcnc benchmark circuits demonstrate the superiority of this approach. for all the circuits tested, the mean value of the ratio "cpu time of the continuous optimization approach divided by cpu time of the simulation-based technique" is equal to 0.41. for 60% of the circuits tested, our approach gives a better estimate (1.16 times larger, on an average) than the simulation-based technique does. compared to the atpg-based technique, the continuous optimization approach generates a tighter lower bound (1.19 times larger, on an average) of maximum power for 60% of all the circuits tested.
conflict driven techniques for improving deterministic test pattern generation. this work presents several new techniques for enhancing the performance of deterministic test pattern generation for vlsi circuits. the techniques introduced are called dynamic decision ordering, conflict driven recursive learning and conflict learning. an important feature shared by all these techniques is that they are triggered by the occurrence of a conflict in the generation of tests. hence, they are not active all the time nor for all the faults. this feature allows the atpg system that uses these techniques to resolve hard-to-resolve faults with far fewer backtracks and leaves the system as efficient as before in the absence of conflicts. we have incorporated these techniques into a commercial d-algorithm based atpg tool. the experimental results on full scan versions of itc'99 benchmark circuits demonstrate an improvement of the atpg system both in the number of aborted faults and in test generation time.
data path placement with regularity. as more data processing functions are integrated into systems-on-chip, data path is becoming a critical part of the whole vlsi design. however, traditional physical design methodology can not satisfy the data path performance requirement because it has no knowledge of the data path bit-sliced structure. in this paper, an abstract physical model (apm) is proposed to extract bit-slice regularity information from data flow graph (dfg) and it is used for interconnect and congestion planning. a two step heuristic algorithm is introduced to optimize the linear placement of apm to satisfy both the wire length and routing track budget.
thermal-induced leakage power optimization by redundant resource allocation. traditionally, at early design stages, leakage power is associated with the number of transistors in a design. hence, intuitively an implementation with minimum resource usage would be best for low leakage. such an allocation would generally be followed by switching optimal resource binding to achieve a low power design. this treatment of leakage power is unaware of operating conditions such as temperature. in this paper, we propose a technique to reduce the total leakage power of a design by identifying the optimal number of resources during allocation and binding. we demonstrate that, contrary to the general tendency to minimize the number of resources, the best solution can actually be achieved if a certain degree of redundancy is allowed. this is due to the fact that leakage is strongly dependent on the on-chip temperature profile. distributing activity over a higher number of resources can reduce power density, remove potential hotspots and subsequently minimize thermal induced leakage. on the other hand, using an arbitrarily high number of resources will not yield the best solution. in this paper, we show that there is a power density, hence, temperature, at which the total leakage power will reach its optimal value. such an optimal resource number can be a better starting point for the subsequent switching-driven low power binding. we also present a high-level power density-aware leakage model. based on the estimates by this model, we optimize the total leakage power by 53.8% on average compared to the minimum resource binding, and 35.7% on average compared to a temperature-aware resource binding technique.
on compacting test response data containing unknown values. the design of a test response compactor called a block compactoris given. block compactors belong to a new class of compactorscalled finite memory compactors. different from spacecompactors, finite memory compactors contain memory elements.also unlike time compactors, finite memory compactors havefinite impulse response. these properties give finite memorycompactors the ability to achieve higher compaction ratios thanspace compactors and still be able to tolerate unknown values intest responses. the proposed block compactors, as an instance offinite memory compactors generate a signature of response data inseveral scan cycles. results presented on several industrial designsshow that block compactors provide better test quality and higherdata compaction than earlier works on test response compactors.
a probabilistic multicommodity-flow solution to circuit clustering problems. circuit clustering, which plays a fundamental role in hierarchical designs, is discussed. identifying strongly connected components in the circuits can significantly reduce the complexity of the design and improve the performance of the design process. however, there has not been a clear objective function for circuit clustering. a clustering metric based on the random graph model and the ratio cust concept is presented. a probabilistic, multicommodity flow based algorithm is proposed and tested under the clustering metric. experimental results show that this algorithm generates promising results with respect to the proposed metric. extensions and directions for future work are also proposed
multi-million gate fpga physical design challenges. the recent past has seen a tremendous increase in the size ofdesign circuits that can be implemented in a single fpga. theselarge design sizes significantly impact cycle time due to designautomation software runtimes and an increased number ofperformance based iterations. new fpga physical designapproaches need to be utilized to alleviate some of theseproblems. hierarchical approaches to divide and conquer thedesign, early estimation tools for design exploration, andphysical optimizations are some of the key methodologies thathave to be introduced in the fpga physical design tools. thispaper will investigate the loss/benefit in quality of results due tohierarchical approaches and compare and contrast some of thedesign automation problem formulations and solutions neededfor fpgas versus known standard cell asic approaches.
minimum-area sequential budgeting for fpga. the constraint-based approach to timing-driven placementrequires delay budgeting to define the delay upper bounds for nets.while most of the previous delay-budgeting works have beenfocused on optimizing combinational circuits, the work in [delay budgeting in sequential circuit with application on fpga placement]introduces sequential budgeting, which combines budgeting andretiming to optimize sequential circuits better. however, theformulation in [delay budgeting in sequential circuit with application on fpga placement] does not consider flip-flop (ff) minimization,which is important in practical applications. here, we propose anew sequential budgeting algorithm, c-sbgt, that not onlycontrols the ff count, but also can be solved more efficientlycompared to [delay budgeting in sequential circuit with application on fpga placement]. our formulation has fewer constraints than [delay budgeting in sequential circuit with application on fpga placement] and the procedure to realize retiming is also simpler. ourexperiments show that our new min-area sequential budgetingalgorithm produces a good trade-off between the area andbudgeting optimization goals, as well as improving the timingof previous sequential budgeting method by 12%.
system-level power and thermal modeling and analysis by orthogonal polynomial based response surface approach (oprs). this paper proposes a new statistical response surface based power estimation technique. the new approach is able to include a number of parameters such as multiple vdd, multiple vth and gate sizing parameters. it has both deterministic ability and statistical ability. the deterministic ability allows the new model to provide optimal design parameters for power reduction. the statistical ability can be used to model the process variation impact on power.
timing-aware power noise reduction in layout. in this paper, we propose a timing-aware power-noise reduction technique. our approach consists of prediction and correction steps. before placement, we estimate the power noise of each cell considering switching frequency of cells which, after placement, will most likely be in the neighborhood. if a frequently switching cell has neighbors which switch infrequently, it is unlikely that this cell will suffer from a power noise problem. based on the cell power noise estimation, we add decap padding to each cell. then we invoke a standard cell placement tool and perform power grid analysis. we eliminate the power grid noise by gate sizing. our technique can reallocate decaps to improve power noise, power consumption, and timing. the gate sizing is based on the sequence of linear programs (slp) formulation, and it can be solved efficiently. experimental results show that our techniques can effectively reduce power noise and meet timing constraints.
test and diagnosis of fault logic blocks in fpgas. since field programmable gate arrays (fpgas) are reprogrammable, faults in them can be easily tolerated once fault sites are located. in this paper we present a method for the testing and diagnosis of faults in fpgas. the proposed method imposes no hardware overhead, and requires minimal support from external test equipments. test time depends only on the number of faults, and is independent of the chip size. with the help of this technique, chips with faults can still be used. as a result, the chip yield can be improved and chip cost is reduced. experimental results are given to show the feasibility of this method.
communication synthesis for distributed embedded systems. abstract: communication synthesis is an essential step in hardware-software co-synthesis: many embedded systems use custom communication topologies and the communication links are often a significant part of the system cost. this paper describes new techniques for the analysis and synthesis of the communication requirements of embedded systems during co-synthesis. our analysis algorithm derives delay bounds on communication in the system given an allocation of messages to links. this analysis algorithm is used by our synthesis algorithm to choose the required communication links in the system and assign interprocess communication to the links. experimental results show that our algorithm finds good communication architectures in small amounts of cpu time.
a wide frequency range surface integral formulation for 3-d rlc extraction. a new surface integral formulation and discretization approach for computing electromagnetoquasistatic impedance of general conductors is described. the key advantages of the formulation is that it avoids volume discretization of the conductors and the substrate, and a single discretization is accurate over the entire frequency range. computational results from an on-chip inductor, a connector and a transmission line are used to show that the formulation is accurate and is &ldquo;acceleration&rdquo; ready. that is, the results demonstrate that an efficiently computed preconditioner insures rapid iterative method convergence and tests with projection show the required kernels can be approximated easily using a coarse grid.
solution of parallel language equations for logic synthesis. the problem of designing a component that combined with a known part of a system, conforms to a given overall specification arises in several applications ranging from logic synthesis to the design of discrete controllers. we cast the problem as solving abstract equations over languages. language equations can be defined with respect to several language composition operators such as synchronous composition, &bull;, and parallel composition, &diams;; conformity can be checked by language containment. in this paper we address parallel language equations.parallel composition arises in the context of modeling delay-insensitive processes and their environments. the parallel composition operator models an exchange protocol by which an input is followed by an output after a finite exchange of internal signals. it abstracts a system with two components with a single message in transit, such that at each instance either the components exchange messages or one of them communicates with its environment, which submits the next external input to the system only after the system has produced an external output in response to the previous input.we study the most general solutions of the language equation a &diams; x &sube; c, and define the language operators needed to express them. then we specialize such equations to languages associated with important classes of automata used for modeling systems, e.g., regular languages and fsm languages. in particular, for a &diams; x &sube; c, we give algorithms for computing: the largest fsm language solution, the largest complete solution, and the largest solution whose composition with a yields a complete fsm language. we solve also fsm equations under bounded parallel composition.in this paper, we give concrete algorithms for computing such solutions, and state and prove their correctness.
multi-level logic optimization for low power using local logic transformations. in this paper we present an efficient technique to reduce the switching activity in a cmos combinational logic network based on local logic transformations. these transformations consist of adding redundant connections or gates so as to reduce the switching activity. simple and efficient procedures, based on logic implication, for identifying the sources and targets of the redundant connections are presented. additionally, procedures that permit the designer to tradeoff power and delay after the transformations are described. results of experiments on the mcnc benchmark circuits are given. the results indicate that significant reduction of the switching activities of a cmos combinational circuit can be achieved with a very low area overhead and low computational cost.
passive synthesis of compact frequency-dependent interconnect models via quadrature spectral rules. in this paper, we present a reduced order modeling methodology,based on the utilization of optimal non-uniform grids generatedby gaussian spectral rules, for the direct passive synthesis ofspice-compatible modeling of multi-conductor interconnectstructures. the algorithm is based on a padé-chebyshevapproximation of the frequency-dependent input impedancematrix of the passive interconnect system. the synthesized circuitis represented as the concatenation of a number of non-uniformsections of passive lumped coupled circuits. however, contrary tothe popular uniform segmentation-based distributed circuitmodels for interconnects, where 10 to 15 segments per minimumwavelength are needed for multi-ghz accuracy, the proposedmodel is "optimal" in the sense that highly-accurate responses canbe obtained with a number of segments per minimum wavelengthbarely exceeding the nyquist limit of 2. this high accuracy stemsfrom the super-exponential convergence of the padé-chebyshevapproximation of the input impedance of the transmission-linemodel of the interconnect, and results in the synthesis of mnastamps for the interconnect structure with five to ten timesreduction in the number of state variables compared to uniformgrids. moreover, the passivity of the generated spice-compatiblemulti-port models is guaranteed through the use ofpassive equivalent circuits for the representation of the frequency-dependent,per-unit-length series impedance and shunt admittancematrices of the interconnect.
an algorithm for power estimation in switched-capacitor circuits. a number of low-power designs, such as those for mobile communication equipment, contain switched-capacitor circuits. in such designs it is important to be able to estimate the power dissipated by the switched-capacitor portion of the circuit. this paper describes an algorithm for the computation of statistical information about the power dissipated in a switched-capacitor circuit when corresponding statistical information about the inputs to the circuit is known. ordinary circuit simulators are not suited for this task, because they can only compute the power dissipated by the circuit for one specific set of input signals. the algorithm does not require monte-carlo analyses, and it accounts for correlation among the inputs. to demonstrate the algorithm's performance, numerical results obtained on a number of sample switched-capacitor circuits are reported.
dragon2000: standard-cell placement tool for large industry circuits. in this paper, we develop a new standard cell placement tool, dragon2000, to solve large scale placement problem effectively. a top-down hierarchical approach is used in dragon2000. state-of-the-art partitioning tools are tightly integrated with wirelength minimization techniques to achieve superior performance. we argue that net-cut minimization is a good and important shortcut to solve the large scale placement problem. experimental results show that minimizing net-cut is more important than greedily obtain a wirelength optimal placement at intermediate hierarchical levels. we run dragon2000 on recently released large benchmark suite ispd98 as well as mcnc circuits. for circuits which have more than 100k cells, comparing to itools1.4.0, dragon2000 can produce slightly better placement results (1.4%) while spending much less amount of time (2&times; speedup). this is also the first published placement result on the publicly available large industrial circuits.
the maximum set of permissible behaviors for fsm networks. for systems of interacting finite state machines (fsm''s), manual designs sometimes use information derived from the other components to optimize one of them. an associated problem is to find the set of permissible sequential functionalities that can be implemented at a component while preserving the behavior of the total system. most conventional approaches attempt to find such a set using th notion of don''t care sequences, but in general, the complete set of permissible finite state machines are difficult to compute. as a result, only small subsets are derived and used in designing interacting components. however, there is no knowledge of how much optimality is lost using these subsets. this paper proposes a method for computing and representing the complete set of permissible finite state machines. we show that the complete set can be computed and represented by a single non-deterministic finite state machine, called the e-machine. the computation is different from any based on don''t care sequences. the transition relation of the e-machine is obtained by a fixed point computation. the procedure has been implemented and initial experimental results are given.
vlsi timing simulation with selective dynamic regionization. accurate timing simulations are crucial to the design of mos vlsi circuits, but can take prohibitively large amounts of time. this paper describes dynamic regionization techniques applied to an event based simulator for mos timing simulation that have proven to be more efficient and as accurate as the static reorganization method. the mos network is first statically partitioned into groups of strongly coupled nodes called regions. big regions are then incrementally and dynamically partitioned into and replaced by subregions. subregions are treated just like normal regions in the event based simulation process. this simulator has been used to verify the timing and functionality of several large vlsi chips. performance is 3 to 7 times faster than a static regionalization method.
single-layer fanout routing and routability analysis for ball grid arrays. fanout routing for ball grid array(bga) packages becomes non-trivial when the i/o pin count increases. with large number of i/os, the number of i/os we can put on a package is not always limited by the available area but sometimes by the ability to fan them out on the next level of interconnect---the pcb or mcm substrate. this paper is the first to consider this problem and offers an efficient algorithm (evenfanout) to solve it. evenfanout generates the optimal uniform distribution of wires. another important contribution is that we analyzed the relationship between pin pitch and the routability of fanout so that the package designer can choose an optimal pitch for maximum routability. knowing this relationship, we know whether a fanout routing is routable or not before it is routed. this is implemented in the package early analysis and routing tool (peart) for rapid development of ball grid array packages.
an adaptive two-level management for the flash translation layer in embedded systems. while the capacity of flash-memory storage systems keeps increasing significantly, effective and efficient management of flash-memory space has become a critical design issue! different granularities in space management impose different management costs and mapping efficiency. in this paper, we explore an address translation mechanism that can dynamically and adaptively switch between two granularities in the mapping of logical block addresses into physical block addresses in flash memory management. the objective is to provide good performance in address mapping and space utilization and, at the same time, to have the memory space requirements, and the garbage collection overhead under proper management. the experimental results show that the proposed adaptive mechanism could provide significant performance improvement over the well-known coarsegrained management mechanism nftl (nand flash translation layer) over realistic workloads.
interchangeable pin routing with application to package layout. many practical routing problems such as bga, pga, pin redistribution and test fixture routing involve routing with interchangeable pins. these routing problems, especially package layout, is becoming more difficult to do manually due to increasing speed and i/o. currently, no commercial or university router is available for this task. in this paper, we unify these different problems as instances of interchangeable pin routing (ipr) problem. we show that this problem is np-complete. we formulate the problem as flows in a routing network on a triangulation instead of grids and developed a min-cost max-flow heuristic considering only the most important cuts in the design. the heuristic is extended to multiple layers and handles prerouted nets. it can accommodate all-angle, octilinear or rectilinear metric. experiments showed that the heuristic is very effective on most practical examples. it successfully routed an industry design with 4000 interchangeable pins without manual intervention.
on per-test fault diagnosis using the x-fault model. this work proposes a new per-test fault diagnosis method based on the x-fault model. the x-fault model represents all possible behaviors of a physical defect or defects in a gate and/or on its fanout branches by using different x symbols on the fanout branches. a novel technique is proposed for analyzing the relation between observed and simulated responses to extract diagnostic information and to score the results of diagnosis. experimental results show the effectiveness of our method.
approximate symbolic analysis of large analog integrated circuits. this paper describes a unified approach to the approximate symbolic analysis of large linearized analog circuits. it combines two new approximation-during-computation strategies with a variation of the classical two-graph tree enumeration method. the first strategy is to generate common trees of the two-graphs, and therefore the product terms in the symbolic network function, in the decreasing order of magnitude. the second approximation strategy is the sensitivity-based simplification of two-graphs, which excludes from the two-graphs many circuit elements that have little effect on the network function being derived. our approach is therefore able to symbolically analyze much larger analog integrated circuits than previously reported, using complete small signal models for the semiconductor devices. we show accurate yet reasonably sized symbolic network functions for integrated circuits with up to 39 transistors whereas previous approaches were limited to less than 15.
area optimization of multi-functional processing units. functions executed by a multifunctional processing unit (pu) correspond to clusters of operations in the specification, which are represented as signal flow graphs (sfgs). because of high-throughput demands, the operations of each sfg are executed in parallel. since operations for only one of the sfgs are executed at a given time, operations belonging to different sfgs can be executed on the same operator. here, the most important part of the mapping of several sfgs onto one pu, which is the assignment of the sfgs operations to the pu's operators, given a number of allocated operators, is considered. the problem is to find an operator assignment that minimizes the silicon area that is occupied by the pu's interconnection consisting of multiplexers and wires. an approach based on local search algorithms such as iterative improvement and simulated annealing is presented. although these algorithms are known to be generally applicable, it is shown that detailed knowledge of the operator assignment problem is required to obtain good results within acceptable cpu time limits for large problem instances
simplifying boolean constraint solving for random simulation-vector generation. we present an algorithm for simplifying the solution of conjunctive boolean constraints of state and input variables, in the context of constrained random vector generation using bdds. the basis of our approach is extraction of "hold-constraints" from constraint system. hold-constraints are deterministic and trivially resolvable; in addition, they can be used to simplify the original constraints as well as refine the conjunctive partition. experiments demonstrate significant reduction in the time and space needed for constructing the conjunction bdds, and the time spent in vector generation during simulation.
a framework for constrained functional verification. we describe a framework for constrained simulation-vector generationin an industry setting. the framework consists of two keycomponents: the constraint compiler and the vector generator. theconstraint compiler employs various techniques, including prioritization,partitioning, extraction, and decomposition, to minimize theinternal representation of the constraints, and thus the complexityof constraint solving. the vector generator then uses the compileddata together with input biasing to generate random simulation vectors.constraints and input biases are treated in a unified manner inthe vector generator. although there are many alternative ways ofgenerating vectors from constraints, the framework uniquely suits apractical constrained verification environment because of its abilityto handle complicated constraints and its seamless treatment of constraintsand biases. we illustrate the effectiveness of the frameworkwith real examples from commercial designs.
modeling design constraints and biasing in simulation using bdds. constraining and input biasing are frequently used techniques in functional verification methodologies based on randomized simulation generation. constraints confine the simulation to a legal input space, while input biasing, which can be considered as a probabilistic constraint, makes it easier to cover interesting &ldquo;corner&rdquo; cases. in this paper, we propose to use constraints and biasing to form a simulation environment instead of using an explicit testbench in hierarchical functional verification. both constraints and input biasing can depend on the state of the design and thus are very expressive in modeling the environment. we present a novel method that unifies the handling of constraints and biasing via the use of binary decision diagrams (bdds). the distribution of input vectors under the effect of constraints and input biasing are determined by what we refer to as the constrained probabilities. a bdd representing the constraints is first built, then an algorithm is applied to bias the branching probabilities in the bdd. during simulation, this annotated bdd is used to generate input vectors whose distribution match their predetermined constrained probabilities. the simulation generation is a one-pass process, i.e., no backtracking or retry is needed. also, we describe a partitioning method to minimize the size of bdds used in simulation generation. our techniques were used in the verification of a set of commercial designs; experimental results demonstrated their effectiveness.
temporal floorplanning using the t-tree formulation. improving logic capacity by time-sharing, dynamically reconfigurable fpgas are employed to handle designs of high complexity and functionality. we model each task as a 3d-box and deal with the temporal floorplanning/placement problem for dynamically reconfigurable fpga architectures. we present a tree-based data structure, called t-trees, to represent the spatial and temporal relations among tasks. each node in a t-tree has at most three children which represent the dimensional relationship among tasks. for the t-tree, we develop an efficient packing method and derive the condition to ensure the satisfaction of precedence constraints which model the temporal ordering among tasks induced by the execution of dynamically reconfigurable fpgas. experimental results show that our tree-based formulation can achieve significantly better solution quality with less execution time than the most recent state-of-the-art work.
automatic synthesis of 3d asynchronous state machines. an automatic synthesis tool (3d) for designing asynchronous controllers from burst-mode specifications, a class of specifications allowing multiple input change fundamental mode operation, is described. an algorithm for constructing a three-dimensional next-state table, a heuristic for encoding states, and a procedure for generating necessary constraints for exact logic minimization are presented. the effectiveness of the 3d implementation and the synthesis procedure on numerous designs including a large realistic example (asynchronous data transfer protocol of the scsi bus controller) is demonstrated. the latency (input to output delay) and the cycle time (time required for the circuit to stabilize after the excitation) for all benchmark designs using a 0.8-&mu;m cmos standard cell library are estimated
an enhanced flow model for constraint handling in hierarchical multi-view design environments. in this paper we present an enhanced design flow model that increases the capabilities of a cad framework to support design activities on hierarchical multi-view design descriptions. this flow model offers new constructs for the configuration of complex design constraints in terms of conditions on the hierarchical multi-view structure of a design. the design flow management system enforces these constraints and uses them to inform the designer more effectively about the validity of verification results and the executability of tools. this helps to make the design process less error prone and to improve productivity. our solution is original in that we introduce the notions of design hierarchy and equivalence in a design flow model. we thereby bridge a gap between the areas of data management and design flow management. strong points of our solution are its simplicity and the seamless integration with existing flow management concepts.
fast balanced stochastic truncation via a quadratic extension of the alternating direction implicit iteration. balanced truncation (bt) model order reduction (mor) is known for its superior accuracy and computable error bounds. balanced stochastic truncation (bst) is a particular bt procedure that provides a general, structure-independent mor framework to preserve both passivity and stability of original models. its application toward large scale systems, however, has been limited by the complexity of solving large size continuous time algebraic riccati equations (cares). this paper introduces a novel quadratic extension of the alternating direction implicit (adi) iteration, called qadi, that efficiently solves a care. a cholesky factor variant of qadi, called cfqadi, further exploits low rank matrices and and produces solution in factor form that greatly accelerates bst. remarkable efficiency of the proposed bst/(cf)qadi integration is demonstrated with numerical examples.
performance-driven synthesis of asynchronous controllers. we examine the implications of a new hazard-free combinational logic synthesis method, which generates multiplexor trees from binary decision diagrams (bdds)&mdash;representations of logic functions factored recursively with respect to input variables&mdash;on extended burst-mode asynchronous synthesis. first, the use of the bdd-based synthesis reduces the constraints on state minimization and assignment, which reduces the number of additional state variables required in many cases. second, in cases where conditional signals are sampled, it eliminates the need for state variable changes preceding output changes, which reduces overall input to output latency. third, selection variables can easily be ordered to minimize the latency on a user-specified path, which is important for optimizing the performance of systems that use asynchronous components. we present extensive evaluations showing that, with only minimal optimization, the bbd-based synthesis gives comparable results in area with our previous exact two-level synthesis method. we also give a detailed example of the specified path optimization.
fpga device and architecture evaluation considering process variations. process variations in nanometer technologies are becoming an important issue for cutting-edge fpgas with a multi-million gate capacity. considering both die-to-die and within-die variations in effective channel length, threshold voltage, and gate oxide thickness, we first develop closed-form models of leakage and timing variations at the fpga chip level. experiments show that our models are within 3% from monte carlo simulation, and the leakage and delay variations can be up to 3/spl times/ and 1.9/spl times/, respectively. we then derive analytical yield models considering both leakage and timing variations, and use such models to evaluate fpga device and architecture under process variations. compared to the architecture similar to a commercial fpga and device setting from itrs roadmap, device tuning alone improves leakage yield by 39% and architecture and device co-optimization increases leakage yield by 73%. we also show that lut size 4 gives the highest leakage yield, lut size 7 gives the highest timing yield, but lut size 5 achieves the maximum combined leakage and timing yield. to the best of our knowledge, this is the first in-depth study on fpga device and architecture co-evaluation considering process variations.
scalable compositional minimization via static analysis. state-equivalence based reduction techniques, e.g. bisimulation minimization, can be used to reduce a state transition system to facilitate subsequent verification tasks. however, the complexity of computing the set of equivalent state pairs often exceeds that of performing symbolic property checking on the original system. we introduce a fully-automated efficient compositional minimization approach which requires only static analysis. key to our approach is a heuristic algorithm that identifies components with high reduction potential in a bit-level netlist. we next inject combinational logic which restricts the component's inputs to selected representatives of symbolically-computed equivalence classes thereof. finally, we use existing transformations to synergistically exploit the dramatic netlist reductions enabled by these input filters. experiments confirm that our technique is able to efficiently yield substantial reductions on large industrial netlists.
wire-length prediction using statistical techniques. we address the classic wire-length estimation problem and propose a new statistical wire-length estimation approach that captures the probability distribution function of net lengths after placement and before routing. the wire-length prediction model was developed using a combination of parametric and non-parametric statistical techniques. the model predicts not only the length of the net using input parameters extracted from the floorplan of a design, but also probability distributions that a net with given characteristics obtained after placement will have a particular length. the model is validated using both learn-and-test and resubstitution techniques. the model can be used for a variety of purposes, including the generation of a large number of statistically sound and therefore realistic instances of designs. we applied the net models to the probabilistic buffer insertion problem and obtained substantial improvement in net delay after routing.
general framework for removal of clock network pessimism. the paper presents a simple yet powerful general theoretical framework and efficient implementation for removal of clock network timing pessimism. we address pessimism in static timing analysis (sta) tools caused by considering delay variation along common segments of clock paths. the sta tools compute setup (hold) timing slack based on conservative combinations of late (early) launching and early (late) capturing arrival times. to avoid exponential-time path-based analysis the sta tools use both early and late arrival times on gates common to both launching and capturing paths. it is impossible in real circuit and is observed as the clock network pessimism in sta. our approach supports any kind of delay variation though the typical causes of the pessimism are process, voltage, and temperature on-chip variation, and reconvergence in clock network. we propose a new theoretical framework that allows to apply known graph algorithms instead of time consuming forward and backward multi-pass tracing algorithms and heuristics that are limited to some network topologies [4]. the new graph-based framework supports clock networks of virtually any size and type, e.g., tree, mesh, hybrid, clock gating, chains of multipliers and dividers, loops in such chains, etc. the implementation based on the proposed framework has proven its strength in a commercial sign-off static timing analyzer and thus is helping hundreds of designers to achieve faster clock speeds of their chips.
paras: system-level concurrent partitioning and scheduling. partitioning for the asic designs is examined and the interaction between high-level synthesis and partitioning is studied and incorporated in the solution. four algorithms (called paras) which can exploit this interaction by solving the scheduling and partitioning problems concurrently are presented. paras maximizes the overall performance of the final design and considers different chip configurations and communication structures. experiments, conducted with specifications ranging in size from few to hundreds of operations, demonstrate the success of this approach.
a technology-independent cad tool for esd protection device extraction: esdextractor. the challenges for developing an esd (electro-static discharge) layout extractor originate from unconventional layout patterns of esd protection devices, parasitic esd device extraction and device count reduction. this paper reports a new technology-independent layout extractor, esdextractor, which is capable of extracting all types of esd devices and answers the demands for esd design verification. general methodology to extract both intentional and parasitic esd devices, specific algorithms and implementation methods for efficiencyenhancement are presented, followed by a design example.
a probabilistic constructive approach to optimization problems. we propose a new optimization paradigm for solving intractable combinatorial problems. the technique, named probabilistic constructive (pc), combines the advantages of both constructive and probabilistic algorithms. the constructive aspect provides relatively short runtime and makes the technique amenable for the inclusion of insights through heuristic rules. the probabilistic nature facilitates a flexible trade-off between runtime and the quality of solution.in addition to presenting the generic technique, we apply it to the maximal independent set problem. extensive experimentation indicates that the new approach provides very attractive trade-offs between the quality of the solution and runtime, often outperforming the best previously published approaches.
a high efficiency full-chip thermal simulation algorithm. thermal simulation has become increasingly important in chip design, especially in the nanometer regime, where the on-chip hot spots severely degrade the performance and reliability of the circuit and increase the leakage power. in this paper, we present a highly efficient and accurate thermal simulation algorithm that is capable of performing full-chip temperature calculations at the cell level. the algorithm is a combination of several important numerical techniques including the green function method, the discrete cosine transform (dct), and the frequency domain computations. experimental results show that our algorithm can achieve orders of magnitude speedup compared with previous green function based algorithms while maintaining the same accuracy.
gate-level simulation of digital circuits using multi-valued boolean algebras. this paper describes an algorithm for the simulation of gate-level logic. multiple logic levels are used to describe the state of each node. each state corresponds to a different voltage level, and the number of levels to be used for a simulation is user-defined. this feature simplifies considerably the interface between a digital and an analog simulator. a dc solver is incorporated to find the initial operating point of a circuit before a transient analysis begins. this solver has the capability of finding the operating point of gates located in feedback loops. for transient analysis, a gate delay model that takes into account the slope of the input waveforms is used. the performance of the algorithm is demonstrated by simulations of a number of benchmark circuits.
statistical critical path analysis considering correlations. critical path analysis is always an important task in timing verification. for todays nanometer ic technologies, process variations have a significant impact on circuit performance. the variability can change the criticality of long paths (gattiker et al., 2002). therefore, statistical approaches should be incorporated in critical path analysis. in this paper, we present two novel techniques that can efficiently evaluate path criticality under statistical non-linear delay models. they are integrated into a block-based statistical timing tool with the capability of handling arbitrary correlations from manufacturing process dependence and also path sharing. experiments on iscas85 benchmarks as well as industrial circuits prove both accuracy and efficiency of these techniques.
efficient solution of systems of boolean equations. this paper describes an algorithm for the efficient solution of large systems of boolean equations. the algorithm exploits the fact that, in some cases, the composition operation of boolean functions represented by bdd's can be performed in a very efficient manner. thus, the algorithm tries to eliminate as many variables and equations as possible through function composition. when the system can no longer be reduced in this way, the elimination process is continued through the use of shannon decomposition. numerical results show that the performance of this algorithm is significantly superior to that of a previous algorithm proposed by the authors.
energy-aware fault tolerance in fixed-priority real-time embedded systems. we investigate an integrated approach to fault tolerance anddynamic power management in real-time embedded systems. faulttolerance is achieved via checkpointing and power management iscarried out using dynamic voltage scaling (dvs). we presentfeasibility-of-scheduling tests for checkpointing schemes for aconstant processor speed as well as for variable processor speeds.dvs is then carried out on the basis of these feasibility analyses.experimental results show that compared to fault-obliviousmethods, the proposed approach significantly reduces powerconsumption and guarantees timely task completion in the presence of faults.
soft self-synchronising codes for self-calibrating communication. self-calibrating designs are gaining momentum in both the computation and communication worlds. instead of relying on the worst-case characterisation of design parameters, self calibrating systems determine autonomously the boundary of correct behaviour, and set design parameters accordingly. we focus on the communication task. we model errors due to over-aggressive operation and derive a channel model. we show that self-synchronising codes achieve completely reliable communication over this channel model, and study a known example, ledr (level encoded 2-phase dual-rail), which is an improvement of the well-known dual-rail code. then, we introduce a family of coding schemes which are a generalisation of ledr, and study their performance over our channel model. we observe that the wiring overhead can be significantly reduced at the expense of a limited loss in reliability. finally, we extend our channel model to include additive noise, and show that in this more general situation a specific instance of our coding scheme has similar or better performance than ledr, at a smaller wiring overhead.
gradual relaxation techniques with applications to behavioral synthesis. heuristics are widely used for solving computational intractablesynthesis problems. however, until now, there has been limitedeffort to systematically develop heuristics that can be applied to avariety of synthesis tasks. we focus on development of generaloptimization principles so that they can be applied to a wide rangeof synthesis problems. in particular, we propose a new way torealize the most constraining principle where at each step wegradually relax the constraints on the most constrained elementsof the solution. this basic optimization mechanism is augmentedwith several new heuristic principles: minimal freedom reduction,negative thinking, calibration, simultaneous step consideration,and probabilistic modeling.we have successfully applied these optimization principles to anumber of common behavioral synthesis tasks. specifically, wedemonstrate a systematic way to develop optimization algorithmsfor maximum independent set, time-constrained scheduling, andsoft real-time system scheduling. the effectiveness of theapproach and algorithms is validated on extensive real-lifebenchmarks.
a data flow fault coverage metric for validation of behavioral hdl descriptions. behavioral hdl descriptions are commonly used to capture the high-level functionality of a hardware circuit for simulation and synthesis. the manual process of creating a behavioral description is error prone, so significant effort must be made to verify the correctness of behavioral descriptions. simulation-based validation and formal verification are both techniques used to verify correctness. we investigate validation because formal verification techniques are frequently intractable for large designs. the first step toward a behavioral validation technique is the development of a validation fault coverage metric which can be used to evaluate the likelihood of design defect detection with a given test sequence.we propose a validation fault coverage metric which is based on an analysis of the control data flow description associated with the behavior. the proposed metric identifies a subset of paths through the data flow which must be traversed during testing to detect faults. the proposed metric is a tractable compromise between the statement coverage metric which requires only that each statement be executed, and the path coverage metric which requires that all data flow paths be executed. data flow paths are identified based on the relative code locations of definitions and uses of variables which may be assigned incorrectly due to a design error. we propose an efficient method to compute all data flow paths which must be traversed, and we generate coverage results for several benchmark vhdl circuits for comparison to other approaches.
area minimization of power distribution network using efficient nonlinear programming techniques. this paper deals with area minimization of power distribution network for vlsis. a new algorithm based on efficient nonlinear programming techniques is presented to solve this problem. the experiment results prove that this algorithm has achieved the objects that minimize the area of power/ground networks with higher speed.
partial bist insertion to eliminate data correlation. a new partial bist insertion approach based on eliminating data correlation to improve pseudo-random testability is presented. data correlation causes the circuit to be in a subset of the states more or less frequently, which leads to low fault coverage in pseudo-random test. one important cause of correlation is reconvergent fanout. incorporating bist test flip-flops into reconvergent paths will break correlation, however, breaking all reconvergent fanout is unnecessary since some reconvergent fanout results in negligible correlation. we introduce a metric to determine the degree of correlation caused by a set of reconvergent fanout paths. we use this metric to identify problematic reconvergent fanout which must be broken through partial bist insertion. we provide an algorithm to break high correlation reconvergent paths. our algorithm provides high fault coverage while selecting fewer bist flip-flops than required using loop breaking techniques. experimental results produced using our algorithm rank on average among the top 11.6% of all possible solutions with the same number of flip-flops.
an efficient multi-view design model for real-time interactive synthesis. an efficient multiview design model for real-time interactive synthesis of behavioral descriptions into layout data is described. a hybrid data structure which combines all of the design data needed throughout multiple levels of abstraction, including behavior, structure, and floorplan, into a single unified view is presented. a detailed time and space complexity analysis of the proposed design model is also given, showing that it provides fast updating capabilities for incremental design changes but does not require an exorbitant amount of memory space. these features make this design model ideal for user-controlled synthesis systems that support incremental design and redesign tasks. furthermore, the simplicity of the data structure allows easy implementation, maintenance, and extensibility
conflict driven learning in a quantified boolean satisfiability solver. within the verification community, there has been a recent increase in interest in quantified boolean formula evaluation (qbf) as many interesting sequential circuit verification problems can be formulated as qbf instances. a closely related research area to qbf is boolean satisfiability (sat). recent advances in sat research have resulted in some very efficient sat solvers. one of the critical techniques employed in these solvers is conflict driven learning. in this paper, we adapt conflict driven learning for application in a qbf setting. we show that conflict driven learning can be regarded as a resolution process on the clauses. we prove that under certain conditions, tautology clauses obtained from resolution in qbf also obey the rules for implication and conflicts of regular (non-tautology) clauses; and therefore they can be treated as regular clauses and used in future search. we have implemented this idea in a new qbf solver called quaffle and our initial experiments show that conflict driven learning can greatly speed up the solution process for most of the benchmarks we tested.
error catch and analysis for semiconductor memories using march tests. we present an error catch and analysis (eca) system for semiconductor memories. the system consists of a test algorithm generator called tags, a fault simulator called ram-ses, and an error analyzer (era). we use tags to generate a set of test algorithms of different lengths and diagnostic resolutions for the memory under test, and use ramses to generate the march dictionary for each test algorithm. with the march dictionaries, era is able to support march algorithms for easy diagnosis of faulty rams. legacy test algorithms also can be reused. when integrated with a ram tester, our eca system can generate ram bitmaps that are similar to the ram layout. the bitmaps provide detail information about the error locations and faults causing the errors. based on the information, diagnosis of the ram chips for yield and reliability improvement can be done more easily.
incremental deductive & inductive reasoning for sat-based bounded model checking. bounded model checking (bmc) based on boolean satisfiability (sat) methods has recently gained popularity as a viable alternative to bdd-based techniques for verifying large designs. this work proposes a number of conceptually simple, but extremely effective, optimizations for enhancing the performance of sat-based bmc flows. the key ideas include: (1) a novel idea to combine sat-based inductive reasoning and bmc; (2) clever orchestration of variable ordering and learned information in an incremental framework for bmc; and (3) bmc-specific ordering strategies for the sat solver. our experiments, conducted on a wide range of industrial designs, show that the proposed optimizations consistently provide between 1-2 orders of magnitude speedup and can be extremely useful in enhancing the efficacy of typical sat-bmc tools.
post-placement voltage island generation under performance requirement. high power consumption not only leads to short battery life for handheld devices, but also causes on-chip thermal and reliability problems in general. as power consumption is proportional to the square of supply voltage, reducing supply voltage can significantly reduce power consumption. multi-supply voltage (msv) has previously been introduced to provide finer-grain power and performance trade-off. in this work we propose a methodology on top of a set of algorithms to exploit non-trivial voltage island boundaries for optimal power versus design cost trade-off under performance requirement. our algorithms are efficient, robust and error-bounded, and can be flexibly tuned to optimize for various design objectives (e.g., minimal power within a given number of voltage islands, or minimal fragmentation in voltage islands within a given power bound) depending on the design requirement. our experiment on real industry designs shows a ten-fold improvement of our method over current logical-boundary based industry approach.
stochastic wire-length and delay distribution of 3-dimensional circuits. 3-d technology promises higher integration density and lower interconnection complexity and delay. at present, however, not much work on circuit applications has been done due to lack of insight into 3-d circuit architecture and performance. in this paper, we investigate the interconnect distributions of 3-d circuits. we divide the 3-d interconnects into horizontal wires and vertical wires and derive their wire-length distributions, respectively. based on the stochastic wire-length distributions, we calculate 3-d circuit interconnect delay distribution. we show that 3-d structures effectively reduce the number of long delay nets, significantly reduce the number of repeaters needed, and dramatically improve the performance. with 3-d structures, a circuit can work at a much higher clock rate (double, even triple) than with 2-d. however, we also show that the impacts of vertical wires on chip area and interconnect delay may limit the number of device layers that we can integrate.
dicer: distributed and cost-effective redundancy for variation tolerance. increasingly prominent variational effects impose imminent threat to the progress of vlsi technology. this work explores redundancy, which is a well-known fault tolerance technique, for variation tolerance. it is observed that delay variability can be reduced by making redundant paths distributed or less correlated. based on this observation, a gate splitting methodology is proposed for achieving distributed redundancy. we show how to avoid short circuit and estimate delay in dual-driver nets which are caused by gate splitting. a spin-off gate placement heuristic is developed to minimize redundancy cost. monte carlo simulation results on benchmark circuits show that our method can improve timing yield from 59% to 72% with only 03% increase on cell area and 2.2% increase on wirelength on average.
a soft error rate analysis (sera) methodology. we present a soft error rate analysis (sera) methodology for combinational and memory circuits. sera is based on a modeling and analysis-based approach that employs a judicious mix of probability theory, circuit simulation, graph theory and fault simulation. sera achieves five orders of magnitude speed-up over monte carlo based simulation approaches with less than 5% error. dependence of soft error rate (ser) of combinational circuits on supply voltage, clock period, latching window, circuit topology, and input vector values are explicitly captured and studied for a typical 0.18 /spl mu/m cmos process. results show that the ser of logic is a much stronger function of timing parameters than the supply voltage. also, an "ser peaking" phenomenon in multipliers is observed where the center bits have an ser that is in order of magnitude greater than that of lsbs and msbs.
dynamic range estimation for nonlinear systems. it has been widely recognized that the dynamic range information of an application can be exploited to reduce the datapath bitwidth of either processors or asics, and therefore the overall circuit area, delay and power consumption. while recent advances in analytical dynamic range estimation can deliver results accurate enough to account for both spatial and temporal correlation, the reported methods are only valid for linear systems. in this paper, we use a powerful mathematical tool, called polynomial chaos, which enables not only the orthogonal decomposition of random processes, but also the propagation of random processes through nonlinear systems with difficult constructs such as multiplications, divisions and conditionals. we show that when applied to interesting nonlinear applications such as adaptive filters, polynomial filters and rational filters, this method can produce complete, accurate statistics of each internal variable, thereby allowing the synthesis of bitwidth with the desired tradeoff between circuit performance and signal-to-noise ratio.
architectural partitioning of control memory for application specific programmable processors. abstract: because of programmability of application specific programmable processors (aspps), microcode-based control is effectively used to drive aspp datapaths for different applications. in aspps, each application needs a separate microprogram resulting in large microcode memory. this paper proposes a distributed microcode memory model in which only distinct microcodes are stored in each separate memory module to save memory area. a hierarchical clustering approach is also proposed for the design of this distributed microcode memory. experimental results indicate this approach is especially well suited for aspp microcode memory design because of the existence of repetitive microcodes across multiple behaviors.
bit-flipping bist. a scan-based bist scheme is presented which guarantees complete fault coverage with very low hardware overhead. a probabilistic analysis shows that the output of an lfsr which feeds a scan path has to be modified only at a few bits in order to transform the random patterns into a complete test set. these modifications may be implemented by a bit-flipping function which has the lfsr-state as an input, and flips the value shifted into the scan path at certain times. a procedure is described for synthesizing the additional bit-flipping circuitry, and the experimental results indicate that this mixed-mode bist scheme requires less hardware for complete fault coverage than all the other scan-based bist approaches published so far.
synthesis of reusable dsp cores based on multiple behaviors. design with cores has become popular recently because it can decrease the design time and ease the complexity of the design process. this paper presents a new method for the design of dsp cores based on multiple behaviors. this method uses redesign technique based on reallocation transformations to extract those rtl components in an initial rtl structure which are highly reusable and uses them to construct a dsp core. experimental results are provided to illustrate the high reusability of core, extracted from given behaviors, when it accommodates new behaviors.
using a distributed rectangle bin-packing approach for core-based soc test scheduling with power constraints. we present a new algorithm to co-optimize test scheduling andwrapper design under power constraints for core-based socs(system on chip). core testing solutions are generated as a set ofwrapper designs, each represented by a rectangle with width equalto the test time and height equal to the number of tam (testaccess mechanism) wires used. the test-scheduling problem withpower constraints is formulated as the distributed rectangle bin-packingproblem, which allows wrapper pins to be assigned to non-consecutivesoc pins. the generalized problem for multiple-tamsis solved by global optimization using evolutionary strategy and thesequence-pair representation. experiments on itcý02 benchmarksare very encouraging.
frequency domain analysis of switching noise on power supply network. in this paper, we propose an approach for the analysis of power supply noise in the frequency domain for power/ground (p/g) networks of tree topologies. we model the p/g network as a linear time invariant (lti) pseudo-distributed rlc network and the gates (or cells) as time-varying current sources. voltage fluctuation caused by the switching events is calculated based on the effective impedances seen by the corresponding current sources and the spatial correlation between the nodes of the power network. superposition is applied to the lti system to obtain the overall noise spectrum at any node of the power supply network. inverse fast fourier transformation (ifft) is then performed on the frequency domain noise spectrum to obtain the time domain noise waveform. the proposed algorithm has a complexity of o(n2). experimental results show that our approach can produce accurate noise waveforms.
eco algorithms for removing overlaps between power rails and signal wires. design eco commonly happens in industry due to constraints or target changes from manufacturing, marketing, reliability, or performance. at each step, designers usually want to modify the existing solution incrementally and keep the design as close as possible to the existing one. in this paper, we address the pso (power rail - signal wire overlap) problem which solves overlaps between power rails and signal wires due to the changes in power rail design on the top layer of a multiple layer routing region. pso problems are frequently caused by changes from power delivery system or package design. the new routing solution satisfies the following constraints: 1) keep the routing of power rails in the new design unchanged. 2) only the routing of the top two layers is changed. 3) horizontal (vertical) signal wire segments on the top layer can only move up/down (left/right). at the same time, the new routing solution keeps the routing pattern unchanged. this requires: a) if one end point of a horizontal (vertical) wire segment on the top layer is a fixed pin, this segment can not move. b) if vertical (horizontal) projections of two horizontal (vertical) signal wire segments have overlaps, then the up/down (left/right) relationship should not be changed. c) if two horizontal (vertical) segments belonging to different nets are on the same track, their left/right (up/down) relationship should not be changed as long as the two segments still exist in the new solution. 4) for each signal wire segment, the deviation (i.e., the difference between its new position and the old one) should not exceed the user-defined allowable deviation bound. different bounds can be set on different segments. we propose two algorithms to solve the pso problem. both algorithms guarantee to find a feasible solution as long as one exists. one is faster, while the other makes effort to minimize the total deviation as well as the max deviation. according to time and quality requirements, users can choose an appropriate algorithm to solve the problem. for a set of industrial test circuits, we were able to remove all overlaps between power rails and signal wires with minimal wire deviation.
an algorithm for simultaneous pin assignment and routing. macro-block pin assignment and routing are important tasks in physical design planning. existing algorithms for these problems can be classified into two categories: 1) a two-step approach where pin assignment is followed by routing, and 2) a net-by-net approach where pin assignment and routing for a single net are performed simultaneously. none of the existing algorithms is "exact" in the sense that the algorithm may fail to route all nets even though a feasible solution exists. this remains to be true even if only 2-pin nets between two blocks are concerned. in this paper, we present the first polynomial-time exact algorithm for simultaneous pin assignment and routing for 2-pin nets from one block (source block) to all other blocks. in addition to finding a feasible solution whenever one exists, it guarantees to find a pin-assignment/routing solution with minimum cost &alpha; &middot; w + &beta; &middot; v, where w is the total wirelength and v is the total number of vias. our algorithm has various applications: 1) it is suitable in eco (engineering change order) situations where a designer wants to incrementally modify the existing solution instead of redoing everything after a design change. 2) given any pin assignment and routing solution obtained by any existing method, our algorithm can be used to increase the number of routed nets and reduce the routing cost. furthermore, it provides an efficient algorithm for the pin assignment and routing problem of all blocks. the method is applicable to both global and detailed routing with arbitrary routing obstacles on multiple layers. experimental results demonstrate its efficiency and effectiveness.
timing-driven partitioning for two-phase domino and mixed static/domino implementations. domino logic is a high-performance circuit configuration that is usually embedded in static logic environment and tightly coupled with the clocking scheme. in this paper, the timing-driven partitioning algorithms that partition a logic network between (1) static and domino implementations, and (2) the phases of a two-phase clock, are provided. in addition, an efficient static mapping algorithm is described.
bus-driven floorplanning. in this paper, we present an integrated approach to floorplanningand bus planning, i.e., bus-driven floorplanning (bdf). we are givena set of circuit blocks and the bus specifications (i.e., the net list ofblocks for the buses). a feasible bdf solution is a placement ofall circuit blocks such that each bus can be realized as a rectangularstrip (horizontal or vertical) going through all the blocks connectedby the bus. the objective is to determine a feasible bdf solutionthat minimizes floorplan area and total bus area. our approachis based upon the sequence-pair floorplan representation. after acareful analysis of the relationship between bus ordering and blockordering in the floorplan represented by a sequence pair, we derivefeasibility conditions on sequence pairs that give feasible bdfsolutions. experimental results demonstrate the efficiency and effectivenessof our algorithm.
robust and passive model order reduction for circuits containing susceptance elements. numerous approaches have been proposed to address the overwhelming modeling problems that result from the emergence of magnetic coupling as a dominant performance factor for icsand packaging. firstly, model order reduction (mor) methods have been extended to robustly capture very high frequency behaviors for large rlc systems via methods such as prima[8] with guaranteed passivity. in addition, new models of the magnetic couplings in terms of susceptance (inverse of inductance) have shown great promise for robust sparsification of otherwise intractable inductance coupling-matrix problems [3--5]. however, model order reduction via prima for circuits that include susceptance elements does not guarantee passivity. moreover, susceptance elements are incompatible with the path tracing algorithms that provide the fundamental runtime efficiency of rice [10]. in this paper a novel mor algorithm, smor, is proposed as an extension of enor [11] which exploits the matrix properties of susceptance-based circuits for runtime efficiency, and provides for a numerically stable, provably passive mor using a new or-thonormalization strategy.
an efficient approach for moment-matching simulation of linear subnetworks with measured or tabulated data. this paper describes a new moment-generation algorithm for efficient simulation of linear subnetworks characterized by measured or tabulated data using moment-matching techniques. the subnetwork moments are computed by performing an integration in time-domain on the measured data. the proposed technique is more accurate as it relies on integration as compared to the previously published approaches which depend on the differentiation of measured data in frequency-domain for computation of moments. using the new moment-generation technique, the cfh (complex frequency hopping) algorithm has been extended to handle measured subnetworks. also a generalized stencil for measured data for inclusion in circuit simulators and to facilitate efficient moment-generation has been presented. examples and comparison with conventional simulations are provided. the method is accurate while it is faster than the conventional approach by 1 to 2 orders of magnitude.
implicit enumeration of strongly connected components. this paper presents a bdd-based implicit algorithm to compute all maximal strongly connected components of directed graphs. the algorithm iteratively applies reachability analysis and sequentially identifies sccs. experiments suggest that the algorithm dramatically outperforms the only existing implicit method which must compute the transitive closure of the adjacency-matrix of the graphs.
interconnect-aware high-level synthesis for low power. interconnects (wires, buffers, clock distribution networks, multiplexers and busses) consume a significant fraction of total circuit power. in this work, we demonstrate the importance of optimizing on-chip interconnects for power during high-level synthesis. we present a methodology to integrate interconnect power optimization into high-level synthesis. our binding algorithm not only reduces power consumption in functional units and registers in the resultant register-transfer level (rtl) architecture, but also optimizes interconnects for power. we take physical design information into account for this purpose. to estimate interconnect power consumption accurately for deep sub-micron (dsm) technologies, wire coupling capacitance is taken into consideration. we observed that there is significant spurious (i.e., unnecessary) switching activity in the interconnects and propose techniques to reduce it. compared to interconnect-unaware power-optimized circuits, our experimental results show that interconnect power can be reduced by 53.1% on an average, while reducing overall power by an average of 26.8% with 0.5% area overhead. compared to area-optimized circuits, the interconnect power reduction is 72.9% and overall power reduction is 56.0% with 44.4% area overhead.
post global routing rlc crosstalk budgeting. existing layout optimization methods often assume a set of interconnects with given rlc crosstalk bounds in a routing region. rlc crosstalk bound partitioning is critical for effectively applying these methods at the full-chip level. in this paper, we develop an optimal crosstalk budgeting scheme based on linear programming (lp) formulation, and apply it to shield insertion and net ordering at the full-chip level. experiment results show that compared to the best alternative approach, the lp based method reduces the total routing area by up to 7.61% and also uses less runtime. to the best of our knowledge, this is the first in-depth work that studies the rlc crosstalk budgeting problem.
a twisted bundle layout structure for minimizing inductive coupling noise. in this paper, we propose a novel twisted-bundle layout structure for minimizing inductive coupling noise. in this structure, we create several routing regions and re-order the routing of nets in each of these routing regions. the purpose is to create complementary and opposite current loops in the twisted-bundle layout structure, such that the magnetic fluxes arising from any signal net within a twisted group cancel each other in the current loop of a net of interest. the effectiveness of the twisted-bundle structure in minimizing coupling inductance has been verified by the application of fasthenry extraction on a 16-bit bus structure. we achieve about two orders of magnitude reduction in inductive coupling. spice simulations also show that the 16-bit twisted-bundle bus structure is able to maintain high signal integrity at high frequency of operation.
a trade-off oriented placement tool. high quality placement results are always produced at the cost ofsignificant runtimes. in this paper, we study the trade-offbetween the overall quality and the runtime for standard-cellplacement problems. we implemented and studied a class ofschemes to achieve the runtime vs. quality trade-off. wedeveloped a new trade-off oriented placement tool (toop)which is controlled by decision trees. toop can adjust itselfbased on user's requests and netlist properties. compared tocadence qplace, even the fastest mode of toop (lowest quality)can produce placements with similar or better layout. toop alsoshows much stronger ability to produce routable placement whencompared to capo.
on-chip interconnect modeling by wire duplication. in this paper, we present a novel wire duplication-based interconnect modeling technique. the proposed modeling technique exploits the sparsity of the l&minus;1 matrix, where l is the inductance matrix, and constructs a sparse and stable equivalent rlc circuit by windowing the original inductance matrix. the model avoids matrix inversions. most important, it is more accurate and more efficient than many existing techniques.
power estimation for cycle-accurate functional descriptions of hardware. cycle-accurate functional descriptions (cafd) are being widely adopted in integrated circuit (ic) design flows. power estimation can potentially benefit from the inherent increase in simulation efficiency of cycle-based functional simulation. currently, most approaches to hardware power estimation operate at the register-transfer level (rtl), or lower levels of design abstraction. attempts at power estimation for functional descriptions have suffered from poor accuracy because the design decisions performed during their synthesis lead to an unavoidable, large uncertainty in any power estimate that is based solely on the functional description. we propose a methodology for cafd power estimation that combines the accuracy achieved by power estimation at the structural rtl with the efficiency of cycle-accurate functional simulation. we achieve this goal by viewing a cafd as an abstraction of a specific, known rtl implementation that is synthesized from it. we identify correlations between a cafd and its rtl implementation, and "back-annotate" information into the cafd solely for the purpose of power estimation. the resulting rtl-aware cafd contains a layer of code that instantiates virtual placeholders for rtl components, and maps values of cafd variables into the rtl components' inputs/outputs, thus enabling efficient and accurate power estimation. power estimation is performed in our methodology by simply co-simulating the rtl-aware cafd with a simulatable power model library that contains power macro-models for each rtl component. we present techniques to further improve the speed of cafd power estimation, through the use of control state-based adaptive power sampling. we have implemented and evaluated the proposed techniques in the context of a commercial c-based hardware design flow. experiments with a number of large industrial designs (up to 1 million gates) demonstrate that the proposed methodology achieves accuracy very close to rtl power estimation with two-to-three orders of magnitude speedup in estimation times.
post routing performance optimization via multi-link insertion and non-uniform wiresizing. most existing performance-driven and clock routing algorithms construct optimal routing topology for each net individually without considering its routability on the chip, so they can not guarantee performance after all nets are routed. this paper proposes a new approach for post routing performance optimization via multi-link insertion and non-uniform wiresizing, which improves the performance of a net topology obtained from a global routing solution. unlike previous approaches, it can achieve reduction in both maximum delay and skew to satisfy user specified constraints and minimizes the routing resource consumed. during optimization, the topology of the net is kept routable. experiments show that link insertion and wiresizing can improve net performance significantly, and among all approaches, multi-link insertion and wiresizing achieves the best performance and area efficiency.
fast algorithms for ir drop analysis in large power grid. due to the extremely large size of power grids, ir drop analysis has become a computationally challenging problem both in terms of runtime and memory usage. although ir drop analysis can be naturally formulated as the problem of solving a linear system, the system is too large to be solved by existing linear solvers. in this paper, we present two iterative algorithms based on node-by-node traversals and row-by-row traversals of the power grid, respectively. our algorithms are extremely fast and guarantee convergence to the exact solutions. in fact, they can be considered as efficient implementations of the classical successive over relaxation iterative method for solving linear systems. our methods take full advantage of the special structure of the power grid. experimental results show that our algorithms out-perform the random-walk-based algorithm which is the best known method today. for a 16-million node problem, our row-based algorithm took 26.47 minutes while the random-walk-based algorithm took 19.6 hours. our row-based algorithm produced an exact solution while the random walk produced a solution with maximum error of 5.7 mv.
a fast wavelet collocation method for high-speed vlsi circuit simulation. this paper presents a fast wavelet collocation method (fwcm) for high- speed circuit simulation. the fwcm has the following properties: (1) it works in the time domain, so that the circuit nonlinearity can be handled, and the accuracy of the result can be well controlled, unlike the method working in the frequency domain where the numerical error may get uncontrolled during the inverse laplace transform; (2) the wavelet property of localization in both time and frequency domains makes a uniform approximation possible, which is generally not found in the time marching methods; (3) it is very effective in treating the singularities often developed in high-speed ics due to the property of the wavelets; (4) calculation of derivatives at all collocation points is optimal and takes o(n\log n), where n is the number of collocation points; (5) an adaptive scheme exists; and (6) it has an o(h^4) convergence rate while the most existing methods only have an o(h^2) convergence rate, where h is the step length. numerical experiments further demonstrated the promising features of fwcm in high-speed ic simulation.
cost-effective radiation hardening technique for combinational logic. a radiation hardening technique for combinational logic circuits is described. the key idea is to exploit the asymmetric logical masking probabilities of gates, hardening gates that have the lowest logical masking probability to achieve cost-effective tradeoffs between overhead and soft error failure rate reduction. the technique, which decouples the physical from the logical aspects of soft error susceptibility of a gate, uses a gate (transistor) sizing technique that is both efficient and accurate (in comparison to spice). a full set of experimental results demonstrate the cost-effective tradeoffs that can be achieved.
an optimal algorithm for river routing with crosstalk constraints. with the increasing density of vlsi circuits, the interconnection wires are getting packed even closer. this has increased the effect of interaction between these wires on circuit performance and hence, the importance of controlling crosstalk. in this paper, we consider river routing with crosstalk constraints. given the positions of the pins in a single-layer routing channel and the maximum tolerable crosstalk between each pair of nets, we give a polynomial time algorithm to decide whether there is a feasible river routing solution and produce one with minimum crosstalk whenever the problem is feasible.
an exact gate decomposition algorithm for low-power technology mapping. with the remarkable growth of portable application and the increasing frequency and integration density, power is being given comparable weight to speed and area in ic designs. in technology mapping, how decomposition is done can have a significant impact on the power dissipation of the final implementation. in the literature, only heuristic algorithms are given for the low-power gate decomposition problem. in this paper, we prove many properties an optimal decomposition tree must have. based on these optimality properties, we design an efficient exact algorithm to solve the low-power gate decomposition problem. moreover, the exact algorithm can be easily modified to a heuristic algorithm which performs much better than the known heuristics.
improving the efficiency of static timing analysis with false paths. we improve the efficiency of static timing analysis when false paths are considered. the efficiency of timing analysis is critical for the performance driven optimization program because timing analysis is invoked heavily in the inner loop. however, when false paths are dealt in timing analysis, a large number of tags need to be created and propagated, and thus deteriorated the efficiency. in this paper, we minimize the number of the tags through a biclique covering approach, which iteratively removes a tag if the false path information in the tag is covered by the union of other tags. the produced tags remove the false path timing and guarantee to cover the true path timings. since the minimum biclique covering of the general bipartite graph is np complete, we use a minimal degree ordering approach to perform the biclique covering minimization. the experimental results show significant reduction on the number of tags.
thermal characterization and optimization in platform fpgas. increasing power densities in field programmable gate arrays (fpgas) have made them susceptible to thermal problems. the advent of platform fpgas has further exacerbated the problems by increasing the power density variations on the fpga fabric. therefore, we need to characterize the die temperature of platform fpgas. in this paper, we first estimate the temperature distribution within a virtex-4 fpga by feeding the block power numbers in an architecture-level temperature simulator calibrated to reflect a real fpga package. we analyze the impact of different hard-wired blocks on the temperature profile, and observe that they introduce intra-die variation in temperature of up to 20&deg;c. next, we evaluate the influence of placement on temperature. our experiments indicate a decrease in peak temperature by changing the placement of hard blocks, especially the high-speed transceivers. we further propose an iterative placement technique to reduce the peak temperature, and apply it on real designs. finally, we propose alternate organizations of the hard blocks in the fpga fabric to reduce temperature.
optimal sizing of high-speed clock networks based on distributed rc and lossy transmission line models. we have proposed an efficient measure to reduce the clock skew by assigning the clock network with variable branch widths. this measure has long been used for ``h'''' clock tree. this paper formulates the optimal sizing of a general clock network as an optimization problem which minimizes the clock skew in a feasible set of widths. this feasible set of branch widths is decided by the process technology and routing resources. the skew minimization problem is turned into a least-squares estimation problem, and a modified gauss-marquardt''s method is then used to determine the optimal widths of clock branches. this optimization method combines the best features of the methods based on taylor series and methods based on gradients. an efficient algorithm is also proposed that assigns the good initial widths especially for a clock tree which let the later optimization process converge much more quickly. our method is very flexible and can handle the general clock network including loops. the clock network can exhibit distributed rc and lossy transmission line behaviors. the method employs a scattering-parameters based delay macromodel to evaluate the timing of the clock network during the optimization process. the major objective of our sizing method is to minimize the skew, but as a by-product that the largest path delay is also reduced.
a new paradigm for low-power, variation-tolerant circuit synthesis using critical path isolation. design considerations for robustness with respect to variations and low power operations typically impose contradictory design requirements. low power design techniques such as voltage scaling, dual-vth etc. can have a large negative impact on parametric yield. in this paper, we propose a novel paradigm for low-power variationtolerant circuit design, which allows aggressive voltage scaling. the principal idea is to (a) isolate and predict the set of possible paths that may become critical under process variations, (b) ensure that they are activated rarely, and (c) avoid possible delay failures in the critical paths by dynamically switching to two-cycle operation (assuming all standard operations are single cycle), when they are activated. this allows us to operate the circuit at reduced supply voltage while achieving the required yield. simulation results on a set of benchmark circuits at 70nm process technology show average power reduction of 60% with less than 10% performance overhead and 18% overhead in die-area compared to conventional synthesis. application of the proposed methodology to pipelined design is also investigated.
improving the robustness of a surface integral formulation for wideband impendance extraction of 3d structures. in order for parasitic extraction of high-speed integrated circuit interconnect to be sufficiently efficient, and fit with model-order reduction techniques, a robust wideband surface integral formulation is essential. one recently developed surface integral formulation has shown promise, but was plagued with numerical difficulties of poorly understood origin. in this paper we show that one of that formulation's difficulties was related to the inaccuracy in the approach to evaluate integrals over discretization panels, and we present an accurate approach based on an adapted piecewise quadrature scheme. we also show that the condition number of the original system of integral equations can be reduced by differentiating one of the integral equations. computational results on a ring and a spiral inductor are used to show that the new quadrature scheme and the differentiated integral formulation improve accuracy and accelerate the convergence of iterative solution methods.
trunk decomposition based global routing optimization. we present global routing optimization methods which are not based on rip-up and re-route framework. in particular, the routing optimization is based on trunk decomposition [13] of the global routing. in this framework, the route of a net is decomposed into sets of wiring segments. by viewing a wiring segment as an "atomic object" of perturbation, we can efficiently evaluate the effect of routing tree perturbation. we propose two complementary routing optimization methods, namely segment partitioning and segment migration. these targeted optimizers can improve congestion related routing objectives by quickly shuffling wiring segments across different routing channels. our routing approach produces better results compared to rip-up and re-route method based router labyrinth [14] with average total overflow reduction of more than 88% while taking only 61% of runtime required by ripup and reroute phase of labyrinth. when applied to the output of labyrinth, the approach, on average, reduces the total overflow by more than 97% with complete overflow elimination for four circuits, while requiring additional runtime of just 33%. on a larger benchmark suite, the total overflow reduction of more than 86% is obtained, with complete overflow elimination for eight circuits, while requiring only 19% additional runtime.
generator-based verification. to prove system correctness, assumptions made in verifying a blockmust be cleared by verifying that the block's environment guaranteesthem. conversely, guarantees enforced by a block may be usedas assumptions for its environment. block level interface specificationsthus serve as both assumptions and guarantees in compositionalverification. traditionally, such specifications have beenrepresented as monitors or checkers. in this paper, we propose analternative representation using generators. novel algorithms arepresented for simulation and formal verification. we argue that forsimulation, representation as a generator can be more efficient thanas a checker - both asymptotically and practically. we also identifya subset of generators that can be efficiently handled using formaltechniques. experimental results are given for some benchmarkexamples and industrial case studies.
on the use of bloom filters for defect maps in nanocomputing. while the exact manufacturing process for nanoscale computing devices is uncertain, it is abundantly clear that future technology nodes will see an increase in defect rates. therefore, it is of paramount importance to construct new architectures and design methodologies that can tolerate large numbers of defects. defect maps are a necessity in the future design flows, and research on their practical construction is essential. in this work, we study the use of bloom filters as a data structure for defect maps. we show that bloom filters provide the right tradeoff between accuracy and space-efficiency. in particular, they can help simplify the nanosystem design flow by embedding defect information within the nanosystem delivered by the manufacturers. we develop a novel nanoscale memory design that uses this concept. it does not rely on a voting strategy, and utilizes the device redundancy more effectively than existing approaches.
a hierarchical modeling framework for on-chip communication architectures. the communication sub-system of complex ic systems is increasingly critical for achieving system performance. given this, it is important that the on-chip communication architecture should be included in any quantitative evaluation of system design during design space exploration. while there are several mature methodologies for the modeling and evaluation of architectures of processing elements, there is relatively little work done in modeling of an extensive range of on-chip communication architectures, and integrating this into a single modeling and simulation environment combining processing element and on-chip communication architectures. this paper describes a modeling framework with accompanying simulation tools that attempts to fill this gap. based on an analysis of a wide range of on-chip communication architectures, we describe how a specific hierarchical class library can be used to develop new on-chip communication architectures, or variants of existing ones with relatively little incremental effort. we demonstrate this through three case studies including two commercial on-chip bus systems and an on-chip packet switching network. here we show that through careful analysis and construction it is possible for the modeling environment to support the common features of these architectures as part of the library and permit instantiation of the individual architectures as variants of the library design. as part of this methodology we also show how different levels of abstraction of the model can be supported and viewed as different variants that can be used in an accuracy versus simulation time trade-off.
verification of analog/mixed-signal circuits using labeled hybrid petri nets. system on a chip design results in the integration of digital, analog, and mixed-signal circuits on the same substrate which further complicates the already difficult validation problem. this paper presents a new model, labeled hybrid petri nets (lhpns), that is developed to be capable of modeling such a heterogeneous set of components. this paper also describes a compiler from vhdl-ams to lhpns. to support formal verification, this paper presents an efficient zone-based state space exploration algorithm for lhpns. this algorithm uses a process known as warping to allow zones to describe continuous variables that may be changing at variable rates. finally, this paper describes the application of this algorithm to a couple of analog/mixed-signal circuit examples.
the effects of energy management on reliability in real-time embedded systems. the slack time in real-time systems can be used by recovery schemes to increase system reliability as well as by frequency and voltage scaling techniques to save energy. moreover, the rate of transient faults (i.e., soft errors caused, for example, by cosmic ray radiations) also depends on system operating frequency and supply voltage. thus, there is an interesting trade-off between system reliability and energy consumption. this work first investigates the effects of frequency and voltage scaling on the fault rate and proposes two fault rate models based on previously published data. then, the effects of energy management on reliability are studied. our analysis results show that, energy management through frequency and voltage scaling could dramatically reduce system reliability, and ignoring the effects of energy management on the fault rate is too optimistic and may lead to unsatisfied system reliability.
an accurate sparse matrix based framework for statistical static timing analysis. statistical static timing analysis has received wide attention recently and emerged as a viable technique for manufacturability analysis. to be useful, however, it is important that the error introduced in ssta be significantly smaller than the manufacturing variations being modeled. achieving such accuracy requires careful attention to the delay models and to the algorithms applied. in this paper, we propose a new sparse-matrix based framework for accurate path-based ssta, motivated by the observation that the number of timing paths in practice is sub-quadratic based on a study of industrial circuits and the iscas89 benchmarks. our sparse-matrix based formulation has the following advantages: (a) it places no restrictions on process parameter distributions; (b) it embeds accurate polynomial-based delay model which takes into account slope propagation naturally; (c) it takes advantage of the matrix sparsity and high performance linear algebra for efficient implementation. our experimental results are very promising.
color permutation: an iterative algorithm for memory packing. it is predicted that 70% of the silicon real-estate will be occupied by memories in future system-on-chips. the minimization of on-chip memory hence becomes increasingly important for cost, performance and energy consumption. in this paper, we present a reasonably fast algorithm based on iterative improvement, which packs a large number of memory blocks into a minimum-size address space. the efficiency of the algorithm is achieved by two new techniques. first, in order to evaluate each solution in linear time, we propose a new algorithm based on the acyclic orientation of the memory conflict graph. second, we propose a novel representation of the solution which effectively compresses the potentially infinite solution space to a finite value of n!, where n is the number of vertices in th memory conflict graph. furthermore, if a near-optimal solution is satisfactory, this value can be dramatically reduced to &chi;!, where &chi;! is the chromatic number of the memory conflict graph. experiments show that consistent improvement over scalar method by 30% can be achieved.
information theoretic approach to address delay and reliability in long on-chip interconnects. with shrinking feature size and growing integration density in the deep sub-micron technologies, the global buses are fast becoming the "weakest-links" in vlsi design. they have large delays and are error-prone. especially, in system-on-chip (soc) designs, where parallel interconnects run over large distances, the effects of crosstalk are detrimental to the overall system performance due to the large delays and un-reliability involved. this paper presents an information theoretic approach to address delay and reliability in long interconnects. a framework to calculate the capacity of a physical wire is laid out herein. the results for 8-bit wide buses of varying lengths in 0.1&mu;m technology are also presented. the wires are modeled based on their calculated parasitic (r, l, c) values and the coupling (c, l) parameters. using this model, results are obtained for the data transfer capacity of long interconnects. it is seen that for wide buses, the signal delay distribution has a long tail, meaning that most signals arrive at the output much faster than the worst case delay. using communication-theory, these "good" signals arriving early can be used to predict/correct the "few" signals arriving late. further, results show that for every bus configuration, there exists an optimal frequency of transmission that will result in the maximum data transfer rate. also, this optimal frequency is higher than the pessimistic worst case delay based clock design.
fastsies: a fast stochastic integral equation solver for modeling the rough surface effect. in this paper we describe several novel sparsification techniques used in a fast stochastic integral equation solver to compute the mean value and the variance of capacitance of 3d interconnects with random surface roughness. with the combination of these numerical techniques, the computational cost has been reduced from o(n/sup 4/) to o(nlog/sup 2/(n)), where n is the number of panels used for the discretization of nominal smooth surfaces. numerical experiments show that the proposed numerical techniques are accurate and efficient.
designing application-specific networks on chips with floorplan information. with increasing communication demands of processor and memory cores in systems on chips (socs), scalable networks on chips (nocs) are needed to interconnect the cores. for the use of nocs to be feasible in today's industrial designs, a custom-tailored, application-specific noc that satisfies the design objectives and constraints of the targeted application domain is required. in this work, we present a design methodology that automates the synthesis of such application-specific noc architectures. we present a floorplan aware design method that considers the wiring complexity of the noc during the topology synthesis process. this leads to detecting timing violations on the noc links early in the design cycle and to have accurate power estimations of the interconnect. we incorporate mechanisms to prevent deadlocks during routing, which is critical for proper operation of nocs. we integrate the noc synthesis method with an existing design flow, automating noc synthesis, generation, simulation and physical design processes. we also present ways to ensure design convergence across the levels. experiments on several soc benchmarks are presented, which show that the synthesized topologies provide a large reduction in network power consumption (2.78x on average) and improvement in performance (1.59x on average) over the best mesh and mesh-based custom topologies. an actual layout of a multimedia soc with the noc designed using our methodology is presented, which shows that the designed noc supports the required frequency of operation (close to 900 mhz) without any timing violations. we could design the noc from input specifications to layout in 4 hours, a process that usually takes several weeks.
on channel segmentation design for row-based fpgas. the channel segmentation design problem for row-based field-programmable gate arrays (fpgas) is to design a segmented channel to maximize the probability of successful routing. an algorithm which takes an arbitrary net distribution and an integer k (specifying the maximum number of segments allowed in routing a net) as inputs, and automatically generates a segmented channel which is most suitable for k-segment channel routing is presented. the algorithm was tested extensively over various net distributions. an algorithm for segmented channel routing based on reducing the problem to the maximum independent set problem for undirected graphs is also presented
leakage power dependent temperature estimation to predict thermal runaway in finfet circuits. in this work we propose a methodology to self-consistently solve leakage power with temperature to predict thermal runaway. we target 28n m finfet based circuits as they are more prone to thermal runaway compared to bulk-mosfets. we generate thermal models for logic cells to self-consistently determine the temperature map of a circuit block. our proposed condition for thermal runaway shows the design trade off between the primary input (pi) activity of a circuit block, sub-threshold leakage at the room temperature and the thermal resistance of the package. we show that in finfet circuits, thermal runaway can occur at the itrs specified sub-threshold leakage (150na/&mu;m, highperformance) for a nominal pi activity of 0.5 and typical package thermal resistance.
a delay fault model for at-speed fault simulation and test generation. we describe a transition fault model, which is easy to simulate under test sequences that are applied at-speed, and provides a target for the generation of at-speed test sequences. at-speed test application allows a circuit to be tested under its normal operation conditions. however, fault simulation and test generation for the existing fault models become significantly more complex due to the need to handle faulty signal-transitions that span multiple clock cycles. the proposed fault model alleviates this shortcoming by introducing unspecified values into the faulty circuit when fault effects may occur. fault detection potentially occurs when an unspecified value reaches a primary output. due to the uncertainty that an unspecified value propagated to a primary output will be different from the fault free value, an inherent requirement in this model is that a fault would be potentially detected multiple times in order to increase the likelihood of detection. experimental results demonstrate that the model behaves as expected in terms of fault coverage and numbers of detections of target faults. a variation of an n-detection test generation procedure for stuck-at faults is used for generating test sequences under this model.
a stochastic integral equation method for modeling the rough surface effect on interconnect capacitance. in this work we describe a stochastic integral equation method for computing the mean value and the variance of capacitance of interconnects with random surface roughness. an ensemble average green's function is combined with a matrix neumann expansion to compute nominal capacitance and its variance. this method avoids the time-consuming monte carlo simulations and the discretization of rough surfaces. numerical experiments show that the results of the new method agree very well with monte carlo simulation results.
smt(): a step toward scalability in system verification. we describe a sat-based decision method for the underlying logic in many formal verification problems; i.e. the counter arithmetic logic with lambda expressions and uninterpreted functions (clu). this logic is well suited for equivalence checking of two versions of a hardware design or the input and output of a compiler and has been recently utilized in several model checkers. our method follows the general satisfiability modulo theories or smt(t) framework and combines a dpll-style sat solver with two theory solvers; one specific to equality and the other to separation inequality atoms within clu. by adopting a combined implication scheme, we coordinate the efforts among theory solvers, and by efficiently processing uninterpreted functions involved in conflicts, we considerably improve the effectiveness of sat learning and backtracking routines. finally, we empirically demonstrate the effectiveness of our smt(clu) procedure and compare its performance to recent solvers on a wide range of hardware verification benchmarks.
a simultaneous bus orientation and bused pin flipping algorithm. the orientation of a bus is defined as the direction from the least significant bit (lsb) to the most significant bit (msb). bused pin flipping is a property that allows several bused pins to flip without changing the system functionality. in this paper a simultaneous bus orientation and bused pin flipping algorithm is presented. the algorithm can be integrated into a bus-centric floorplanner targeting bus-rich designs such as microprocessors. experimental results show that a floorplanner enhanced by the algorithm produces high quality floorplans in terms of bus routing.
joint design-time and post-silicon minimization of parametric yield loss using adjustable robust optimization. parametric yield loss due to variability can be effectively reduced by both design-time optimization strategies and by adjusting circuit parameters to the realizations of variable parameters. the two levels of tuning operate within a single variability budget, and because their effectiveness depends on the magnitude and the spatial structure of variability their joint co-optimization is required. in this paper we develop a formal optimization algorithm for such co-optimization and link it to the control and measurement overhead via the formal notions of measurement and control complexity. we describe an optimization strategy that unifies design-time gate-level sizing and post-silicon adaptation using adaptive body bias at the chip level. the statistical formulation utilizes adjustable robust linear programming to derive the optimal policy for assigning body bias once the uncertain variables, such as gate length and threshold voltage, are known. computational tractability is achieved by restricting optimal body bias selection policy to be an affine function of uncertain variables. we demonstrate good run-time and show that 5-35% savings in leakage power across the benchmark circuits are possible. dependence of results on measurement and control complexity is studied and points of diminishing returns for both metrics are identified.
yield-aware analog integrated circuit optimization using geostatistics motivated performance modeling. automated circuit optimization is an important component of complex analog integrated circuit design. today's analog designs must be optimized not only for nominal performance but also for robustness in order to maintain a reasonable yield with highly scaled vlsi technologies. the complex nature of analog/mixed-signal systems, however, makes this yield-aware analog circuit optimization extremely difficult and costly. in this paper, we adopt a geostatistics motivated approach (i.e. kriging model) for efficient extraction of yield-aware pareto front performance models for analog circuits. an iterative search based optimization approach is proposed to efficiently seek optimal performance tradeoffs under yield constraints in high-dimensional design parameter and process variation spaces. our experiments confirm that the generated yield-aware pareto fronts are accurate and the optimization procedure is very efficient. the latter is achieved by the well controlled iterative update scheme in the presented techniques which avoids an excessive number of time consuming transistor-level simulations.
dynamic response time optimization for sdf graphs. synchronous data flow (sdf) is a well-known model of computation that is widely used in the control engineering and digital signal processing domains. existing scheduling methods are mainly static approaches that assume full knowledge of the environment, e.g. data arrival times. in a growing number of practical cases like internet multimedia applications there exists only partial knowledge of the environment, e.g. average data rates. here, only dynamic scheduling can yield optimal results. in this paper, we propose a new dynamic scheduling method that minimizes the maximal response time of the system. it is a generalization of a deadline revision method to allow treatment of data-dependent tasks using edf scheduling. the applicability and benefit of the new approach is shown using a real-world example.
using cad to shape experiments in molecular qca. this paper examines how circuits and systems made from molecular qca devices might function. our design constrain are "chemically reasonable" in that we consider the characteristics and dimensions of devices and scaffoldings (circuit boards to attach devices to) that have actually been fabricated (currently in isolation). we will show that not only is the work presented here a necessary first step for any work in qca cad, but also that by considering issues related to design can actually help shap shape experiments in the physical sciences for emerging, nano-scale devices. our work shows that circuits, scaffoldings, substrates, and devices must all be considered simultaneously. otherwise, there is a very real possibility that the devices and scaffoldings that are eventually manufactured will result in devices that only work in isolation. this work is especially timely as experimentalists are currently working to merge the different experimental tracks - i.e. to selectively place a qca device.
a case for cmos/nano co-design. the challenge of extending moore's law past the physical and economic barriers of present semiconductor technologies calls for novel nanoelectronic solutions. circuits composed of mixed silicon semiconductors and nanoelectronics can provide a means for gradually switching technology paradigms. we suggest a design methodology to accompany this concept. furthermore, we explore design tradeoffs for a nanoscale crossbar technology that supports cmos/nano co-design.
fast and accurate transaction level models using result oriented modeling. effcient communication modeling is a critical task in soc design and exploration. in particular, fast and accurate communication is needed to predict the performance of a system. recently, transaction level modeling (tlm) is used to speedup communication simulation at the cost of accuracy. this paper proposes a novel modeling technique called result oriented modeling (rom) which removes the accuracy drawback of tlm. using rom, models yield the same speed as their tlm counterparts, yet still are 100% accurate in timing. rom utilizes the fact that internal states in the communication channel are not observable by the caller. hence, rom omits the internal states entirely and optimistically predicts the end result. retroactively, the outcome is checked and, if necessary, corrective measures are taken to maintain the accuracy of the model. in this paper, we apply rom to the amba ahb bus architecture. our experimental results show that rom exhibits the same high simulation performance as traditional tlm, yet it retains the same accuracy as the bus functional model. thus, the proposed rom approach eliminates the speed/accuracy tradeoff exhibited by traditional tlm.
hybrid spectral/iterative partitioning. although spectral partitioning has been an active area of research, there are still many limitations which prevent its widespread use. these limitations include the inability to work directly with a hypergraph model, great difficulty in specifying design constraints, and the inability to specify arbitrary cost functions. none of those limitations are present in the commonly-used kernighan-lin/fiduccia-mattheyses (klfm) style iterative improvement heuristics. our current work focuses on developing a new multi-way, hybrid spectral/iterative hypergraph partitioning algorithm which combines the strengths of spectral partitioners and iterative improvement algorithms to create a new class of partitioners. we show how spectral information (the eigenvectors of a graph) can be incorporated into an iterative partitioning framework. we use spectral information to generate initial partitions, influence the selection of iterative improvement moves, and break out of local minima which may trap klfm improvement algorithms. our 3-way and 4-way partitioning results are better than the best published results, demonstrating the effectiveness of our new hybrid method.
fullwave volumetric maxwell solver using conduction modes. we present a gridless method for solving the interior problem for a set of conductors in an homogeneous dielectric, at sufficiently high frequencies, valid for conductor lengths that are not small compared to the minimum wavelength, and transverse dimensions that are large compared to the skin depth. for ic applications, we cover the regime 10--100 ghz and the inclusion of all relevant wire dimensions. we decompose the electromagnetic-field in terms of the eigenfunctions of the helmholtz equation for three dimensional current distributions inside the conductors. using a relatively small number of modes per conductor we obtain results comparable to filament or mesh decompositions using a much larger dimensionality for the resulting linear problem. the method is an extension to the fullwave regime of a method introduced in [1].
multi-level spectral hypergraph partitioning with arbitrary vertex sizes. this paper presents a new spectral partitioning formulation which directly incorporates vertex size information. the formulation results in a generalized eigenvalue problem, and this problem is reduced to the standard eigenvalue problem. experimental results show that incorporating vertex sizes into the eigenvalue calculation produces results that are 50% better than the standard formulation in terms of scaled ratio-cut cost, even when a kernighan-lin style iterative improvement algorithm taking into vertex sizes is applied as a post-processing step. the standard spectral partitioning formulation is impractical for use in multi-level partitioning schemes since it requires a contraction method that produces nearly-equal-size clusters. to evaluate the new method for use in multi-level partitioning, we combine the partitioner with a multi-level bottom-up clustering algorithm and iterative refinement. experimental results show that our new spectral algorithm is more effective than the standard spectral formulation and other partitioners in the multi-level partitioning of hypergraphs.
application-specific customization of parameterized fpga soft-core processors. soft-core microprocessors mapped onto field-programmable gate arrays (fpgas) represent an increasingly common embedded software implementation option. modern fpga soft-cores are parameterized to support application-specific customization, wherein pre-defined units, such as a multiplication unit or floating-point unit, may be included in the microprocessor architecture to speed up software execution at the expense of increased size. we introduce a methodology for fast applicationspecific customization of a parameterized fpga soft core, using synthesis and execution to obtain size and performance data in order to create a tool that can be used across a variety of tool platforms and fpga devices. as synthesizing a soft core takes tens of minutes, developing heuristics that execute in an acceptable time of an hour or two, yet find near-optimal results, is a challenge. we consider two approaches, one using a traditional cad approach that does an initial characterization using synthesis to create an abstract problem model and then explores the solution space using a knapsack algorithm, and the other using a synthesisin-the-loop exploration approach. we compare approaches for a variety of design constraints, on 11 eembc benchmarks, using an actual xilinx soft-core processor, and for two different commercial xilinx fpga devices. our results show that the approaches can generate a customized configuration exhibiting roughly 2x speedups over a base soft core, reaching within 4% of optimal in about 1.5 hours, including complete synthesis of the soft-core onto the fpga, compared to over 11 hours for exhaustive search. our results also show that including synthesisin-the-loop, compared to a traditional cad approach, improved speedups by an average of 20% when size constraints were tight. the approaches may also be applicable to soft-core processors targeted to asics in addition to fpgas.
an efficient method for statistical circuit simulation. the dynamic behavior of a vlsi circuit can be described by a system of differential-algebraic equations. when some circuit elements are affected by process variations, the dynamic behavior of the circuit will deviate from its nominal trajectory. monte-carlo-type random sampling methods are widely used to estimate the trajectory deviation. however they can be quite time-consuming when the dimension of the parameter space is large. this paper offers an alternative solution by casting the problem into the theoretic frame work of non-linear non-gaussian filtering. to estimate the mean and variance of the time-dependent circuit trajectory, we develop a method based on unscented transformation, which is an efficient bayesian analysis sampling technique. theoretically the method has linear runtime complexity. experimental results show that compared to traditional monte-carlo methods, the new method can achieve over 10x speedup with less than 2% error.
noise propagation and failure criteria for vlsi designs. noise analysis has become a critical concern in advanced chip designs. traditional methods suffer from two common issues. first, noise that is propagated through the driver of a net is combined with noise injected by capacitively coupled aggressor nets using linear summation. since this ignores the non-linear behavior of the driver gate the noise that develops on a net can be significantly underestimated. we therefore propose a new linear model that accurately combines propagated and injected noise on a net and which maintains the efficiency of linear simulation. after the propagated and injected noise are correctly combined on a victim net, it is necessary to determine if the noise can result in a functional failure. this is the second issue that we discuss in this paper. traditionally, noise failure criteria have been based on unity gain points of the dc or ac transfer curves. however, we will show that for digital designs, these approaches can result in a pessimistic analysis in some cases, while in other cases, they allow circuit operation that is extremely close to regions that are unstable and do not allow sufficient margin for error in the analysis. in this paper, we compare the effectiveness of the discussed noise failure criteria and also present a propagation based method, which is intended to overcome these drawbacks. the proposed methods were implemented in a noise analysis tool and we demonstrate results on industrial circuits.
online task-scheduling for fault-tolerant low-energy real-time systems. in this paper we investigate fault tolerance and dynamic voltage scaling (dvs) in hard real time systems. we present two low-complexity fault-aware scheduling algorithms that combine feasibility analysis of rate monotonic algorithm (rma) schedules and dvs-based frequency scaling using exact characterization of rma algorithm. these algorithms lay the foundation for highly efficient online schemes that minimize energy consumption by adapting dvs policies to runtime behavior of tasks and fault occurrences without violating the offline feasibility analysis. simulation results demonstrate energy savings of up to 60% over low-energy offline scheduling algorithms [22].
test of future system-on-chips. spurred by technology leading to the availability of millions of gates per chip, system-level integration is evolving as a new paradigm, allowing entire systems to be built on a single chip. being able to rapidly develop, manufacture, test, debug and verify complex socs is crucial for the continued success of the electronics industry. this growth is expected to continue full force at least for the next decade, while making possible the production of multimillion transistor chips. however, to make its production practical and cost effective, the industry road maps identify a number of major hurdles to be overcome. the key hurdle is related to test and diagnosis. this embedded tutorial analyzes these hurdles, relates them to the advancements in semiconductor technology and presents potential solutions to address them. these solutions are meant to ensure that test and diagnosis contribute to the overall growth of the soc industry and do not slow it down. this embedded tutorial in addition presents the state-of-the-art in system-level integration and addresses the strategies and current industrial practices in the test of system-on-chip. it discusses the requirements for test reuse in hierarchical design, such as embedded test strategies for individual cores, test access mechanisms, optimizing test resource partitioning, and embedded test management and integration at the system-on-chip level. processor cores being one of the most common cores embedded in a soc, issues related to self-testing embedded processor cores are addressed. future research challenges and opportunities are discussed in enabling testing of future socs which use deep submicron technologies.
system-wide energy minimization for real-time tasks: lower bound and approximation. we present a dynamic voltage scaling (dvs) technique that minimizes system-wide energy consumption for both periodic and sporadic tasks. it is known that a system consists of processors and a number of other components. energy-aware processors can be run in different speed levels; components like memory and i/o subsystems and network interface cards can be in a standby state when they are active, but idle. processor energy optimization solutions are not necessarily efficient from the perspective of systems. current system-wide energy optimization studies are often limited to periodic tasks with heuristics in getting approximated solutions. in this paper, we develop an exact dynamic programming algorithm for periodic tasks on processors with practical discrete speed levels. the algorithm determines the lower bound of energy expenditure in pseudopolynomial time. an approximation algorithm is proposed to provide performance guarantee with a given bound in polynomial running time. because of their time efficiency, both the optimization and approximation algorithms can be adapted for online scheduling of sporadic tasks with irregular task releases. we prove that system-wide energy optimization for sporadic tasks is np-hard in the strong sense. we develop (pseudo-) polynomial-time solutions by exploiting its inherent properties.
using functional independence conditions to optimize the performance of latency-insensitive systems. in latency-insensitive design shell modules are used to encapsulate system components (pearls) in order to interface them with the given latency-insensitive protocol and dynamically control their operations. in particular, a shell stalls a pearl whenever new valid data are not available on its input channels. we study how functional independence conditions (fic) can be applied to the performance optimization of a latency-insensitive system by avoiding unnecessary stalling of their pearls. we present a novel circuit design of a generic shell template that can exploit fics. we describe an automatic procedure for the logic synthesis of a fic-shell instance that is only based on the analysis of the logic structure of its corresponding pearl and does not require any input from the designers. we implemented the proposed technique within the logic synthesis tool abc and we use it to complete various experiments that demonstrate its performance benefits and limited overhead. in particular, we completed the semi-custom design of a system-on-chip (soc), an ultra-wideband baseband transmitter, using a state-of-the-art 90nm technology process. to the best of our knowledge this represents the first report on the complete latency-insensitive design of a real-world soc.
process and environmental variation impacts on asic timing. with each semiconductor process node, the impacts on performance of environmental and semiconductor process variations become a larger portion of the cycle time of the product. simple guard-banding for these effects leads to increased product development times and uncompetitive products. in addition, traditional static timing methodologies are unable to cope with the large number of permutations of process, voltage, and temperature corners created by these independent sources of variation. in this paper we will discuss the sources of variation; by introducing the concepts of systematic inter-die variation, systematic intra-die variation and intra-die random variation. we will show that by treating these forms of variations differently, we can achieve design closure with less guard-banding than traditional methods.
on bounding the delay of a critical path. process variations cause different behavior of timing-dependent effects across different chips. in this work, we analyze one example of timing-dependent effects, cross-coupling capacitance, and the complex problem space created by considering coupling and process variations together. the delay of a critical path under these conditions is difficult to bound for design and test. we develop a methodology that analyzes this complex space by decomposing the problem space along three dimensions: the aggressor space, test space, and sample space. for design, we utilize an obdd-based approach to prune the aggressor space based on logical constraints, which can be combined with a worst-case timing window simulator to prune based on both logical and timing constraints. after pruning, the reduced aggressor space can be used to derive a more accurate timing bound. solving the problems in the test and sample spaces is postponed to the post-silicon stage, where we propose a test selection methodology for bounding the delay of every sample. this methodology is based on probability density estimation and has a tradeoff between the number of tests to apply and the tightness of the delay bound obtained. experimental results based on benchmark examples are presented to show the effectiveness of the proposed methodology.
tip-opc: a new topological invariant paradigm for pixel based optical proximity correction. as the 193nm lithography is likely to be used for 45mm and even 32nm processes, much more stringent requirement will be posed on optical proximity correction (opc) technologies. currently, there are two opc approaches --- the model-based opc (mb-opc) and the inverse lithography technology (ilt). mb-opc generates masks which is less complex compared with il.t. but il.t produces much better results than mb-opc in terms of contour fidelity because ilt is a pixel based method. observing that mb-opc preserves the mask shape topologies which leads to a lower mask complexity, we combine the strengths of both methods --- the topology invariant property and the pixel based mask representation. to the best of our knowledge, it is the first time that this topological invariant pixel based opc (tip-opc) paradigm is proposed, which fills the critical hole of the opc landscape and potentially has many new applications. our technical novelty includes the lithography friendly mask topological invariant operations, the efficient fast fourier transform based cost function sensitivity computation and the tip-opc algorithm. the experimental results show that tip-opc can achieve much better post opc contours compared with mb-opc while maintaining the mask shape topologies.
automation in mixed-signal design: challenges and solutions in the wake of the nano era. the use of cmos nanometer technologies at 65 nm and below will pose serious challenges on the design of mixed-signal integrated systems in the very near future. rising design complexities, tightening time-to-market constraints, leakage power, increasing technology tolerances, and reducing supply voltages are key challenges that designers face. novel types of devices, new process materials and new reliability issues are next on the horizon. we discuss new design methodologies and eda tools that are being or need to be developed to address the problems of designing such mixed-signal integrated systems.
yield prediction for 3d capacitive interconnections. capacitive interconnections are very promising structures for high-speed and low-power signaling in 3d packages. since the performance of ac links, in terms of band-width and bit-error-rate (ber), depends on assembly and synchronization accuracy we performed a statistical analysis of assembly procedures and communication circuits. in this paper we present a yield prediction methodology for 3d capacitive links: starting from the analysis of communication circuits and ber measurements, we analyze stacking variability in order to predict reliability and performance. the proposed parametric yield analysis is demonstrated on a test-case, with constrained inter-electrode coupling and operating frequency.
a high-quality mixed-size analytical placer considering preplaced blocks and density constraints. in addition to wirelength, modern placers need to consider various constraints such as preplaced blocks and density. we propose a high-quality analytical placement algorithm considering wirelength, preplaced blocks, and density based on the log-sum-exp wirelength model proposed by naylor et al. [20] and the multilevel framework. to handle preplaced blocks, we use a two-stage smoothing technique, gaussian smoothing followed by level smoothing, to facilitate block spreading during global placement. the density is controlled by white-space re-allocation using partitioning and cut-line shifting during global placement and cell sliding during detailed placement. we further use the conjugate gradient method with dynamic step-size control to speed up the global placement and macro shifting to and better macro positions. experimental results show that our placer obtains the best published results.
a linear-time approach for static timing analysis covering all process corners. manufacturing process variations lead to circuit timing variability and a corresponding timing yield loss. traditional corner analysis consists of checking all process corners (combinations of process parameter extremes) to make sure that circuit timing constraints are met at all corners, typically by running static timing analysis (sta) at every corner. this approach is becoming too expensive due to the exponential increase in the number of corners with modern processes. as an alternative, we propose a linear-time approach for sta which covers all process corners in a single pass. our technique assumes a linear dependence of delay on process parameters and provides tight bounds on the worst-case circuit delay. it exhibits high accuracy (within 1-3%) in practice and, if the circuit has m gates and n relevant process parameters, the complexity of the algorithm is o(mn).
enhanced error vector magnitude (evm) measurements for testing wlan transceivers. as wireless lan devices become more prevalent in the consumer electronics market, there is an ever increasing pressure to reduce their overall cost. the test cost of such devices is an appreciable percentage of the overall cost, which typically results from the high number of specifications, the high number of distinct test set-ups and equipment pieces that need to be used, and the high cost of each test set-up. in this paper, we investigate the versatility of evm measurements to test the variable-envelope wlan (wireless local area networks) receiver and transmitter characteristics. the goal is to optimize evm test parameters (input data and test limits) and to reduce the number of specification measurements that require high test times and/or expensive test equipment. our analysis shows that enhanced evm measurements(optimized data sequence and limits, use of rms, scale, and phase error vector values) in conjunction with a set of simple path measurements (input-output impedances) can provide the desired fault coverage while eliminating lengthy spectrum mask and noise figure tests
a fast block structure preserving model order reduction for inverse inductance circuits. most existing rcl-1 circuit reductions stamp inverse inductance l-1 elements by a second-order nodal analysis (na). the na formulation uses nodal voltage variables and describes inductance by nodal susceptance. this leads to a singular matrix stamping in general. we introduce a new circuit stamping for rcl-1 circuits using branch vector potentials. the new circuit stamping results in a first-order circuit matrix that is semi-positive definite and non-singular. we call this as vectorpotential based nodal analysis (vna). it enables an accurate and passive reduction. in addition, to preserve the structure of state matrices such as sparsity and hierarchy, we represent the flat vna matrix in a bordered-block diagonal (bbd) form. this enables us to build and simulate the macromodel efficiently. in experiments performed on several test cases, our method achieves up to 15x faster modeling building time, up to 33x faster simulation time, and as much as 67x smaller waveform error compared to sapor, the best existing second order rcl-1 reduction method.
state re-encoding for peak current minimization. in a synchronous finite state machine (fsm), huge current peaks are often observed at the moment of state transition. previous low power state encoding algorithms focus on the reduction of switching activities of state registers (i.e., state bits). however, even though the switching state registers are the same, different combinations of switching directions still result in different peak currents. based on that observation, in this paper, we propose the first approach to re-encode an fsm by considering the switching directions of state registers in order to minimize the peak current caused by the state transition. experimental data consistently show that the peak current is reduced with no penalty.
post-routing redundant via insertion and line end extension with via density consideration. redundant via insertion and line end extension employed in the post-routing stage are two well known and highly recommended techniques to reduce yield loss due to via failure. however, if the amount of inserted redundant vias is not well controlled, it could violate via density rules and adversely worsen the yield and reliability of the design. in this paper, we first study the problem of redundant via insertion, and present two methods to accelerate a state-of-the-art approach (which is based on a maximum independent set (mis) formulation) to solve it. we then consider the problem of simultaneous redundant via insertion and line end extension. we formulate the problem as a maximum weighted independent set (mwis) problem and modify the accelerated mis-based approach to solve it. lastly, we investigate the problem of simultaneous redundant via insertion and line end extension subject to the maximum via density rule, and present a two-stage approach for it. in the first stage, we ignore the maximum via density rule, and enhance the mwis-based approach to find the set of regions which violate the maximum via density rule after performing simultaneous redundant via insertion and line end extension. in the second stage, excess redundant vias are removed from those violating regions such that after the removal, the maximum via density rule is met while the total amount of redundant vias removed is minimized. this density-aware redundant via removal problem is formulated as a set of zero-one integer linear programming (0-1 ilp) problems each of which can be solved independently without sacrificing the optimality. the superiorities of our approaches are all demonstrated through promising experimental results.
energy management for real-time embedded systems with reliability requirements. with the continued scaling of cmos technologies and reduced design margins, the reliability concerns induced by transient faults have become prominent. moreover, the popular energy management technique dynamic voltage and frequency scaling (dvfs) has been shown to have direct and negative effects on reliability. in this work, for a set of real-time tasks, we focus on the slack allocation problem to minimize their energy consumption while preserving the overall system reliability. building on our previous findings for a single real-time application where a recovery task was used to preserve reliability, we identify the problem of reliability-aware energy management for multiple tasks as np-hard and propose two polynomial-time heuristic schemes. we also investigate the effects of on-chip/off-chip workload decomposition on energy management, by considering a generalized power model. simulation results show that ordinary energy management schemes could lead to drastically decreased system reliability, while the proposed reliability-aware heuristic schemes are able to preserve the system reliability and obtain significant energy savings at the same time.
a gate delay model focusing on current fluctuation over wide-range of process and environmental variability. this paper proposes a gate delay model that is suitable for timing analysis considering wide-range process and environmental variability. the proposed model focuses on current variation and its impact on delay is considered by replacing output load. the proposed model is applicable for large variability with current model constructed by dc analysis whose cost is small. the proposed model can also be used both in statistical static timing analysis and in conventional corner-based static timing analysis. experimental results in a 90nm technology show that the gate delays of inverter, nand and nor are accurately estimated under gate length, threshold voltage, supply voltage and temperature fluctuation. we also verify that the proposed model can cope with slow input transition and rc output load. we demonstrate applicability to multiple-stage path delay and flip-flop delay, and show an application of sensitivity calculation for statistical timing analysis.
a timing dependent power estimation framework considering coupling. in this paper, we propose a timing dependent dynamic power estimation framework that considers the impact of coupling and glitches. we show that relative switching activities and times of coupled nets significantly affect dynamic power consumption, and neither should be ignored during power estimation. to capture the timing dependence, an approach to efficient representation and propagation of switching-window distributions through a circuit, considering coupling induced delay variations, is developed. based on the propagated switchingwindow distributions, power consumption in charging or discharging coupling capacitances is calculated, and accounted for in the total power. experimental results for the iscas'85 benchmarks demonstrate that ignoring the impact of timing dependent coupling on power can cause up to 59% error in coupling power estimation (up to 25% error in total power estimation).
nanowire addressing with randomized-contact decoders. methods for assembling crossbars from nanowires (nws) have been designed and implemented. methods for controlling individual nws within a crossbar have also been proposed, but implementation remains a challenge. a nw decoder is a device that controls many nws with, a much smaller number of lithographically produced mesoscale wires (mws). unlike traditional demultiplexers, all proposed nw decoders are assembled stochastically. in a randomized-contact decoder (rcd) [11], for example, field-effect transistors are randomly created at about half of the nw/mw junctions. in this paper, we tightly bound the number of mws required to produce a correctly functioning rcd with high probability. we show that the number of mws is logarithmic in the number of nws, even when errors occur. we also analyze the overhead associated with controlling a stochastically assembled decoder. as we explain, lithographically-produced control circuitry must store information regarding which mws control which nws. this requires more area than the mws themselves, but has received little attention elsewhere.
a unified non-rectangular device and circuit simulation model for timing and power. for 65nm and below devices, even after optical proximity correction (opc), the gate may still be non-rectangular. there are several limited works on the device and circuit characterizations for the post-opc non-ideal-shape wafer images, with significant impacts on timing and power. most of them, however, are based on the equivalent gate length models, which are different for timing and leakage, and thus hard to use for coherent circuit simulations. in this paper, we propose a unified post-litho device characterization model and circuit simulation for timing and power. to our best knowledge, this is the most accurate methodology for post-litho analysis, including timing, leakage and transient simulation. based on this method, the parameter extraction is also included in the model which was omitted by previous works. a post-litho model card is proposed for circuit simulation to combine these two techniques. our experimental results validate the new model.
improvements to combinational equivalence checking. the paper explores several ways to improve the speed and capacity of combinational equivalence checking based on boolean satisfiability (sat). state-of-the-art methods use simulation and bdd/sat sweeping on the input side (i.e. proving equivalence of some internal nodes in a topological order), interleaved with attempts to run sat on the output (i.e. proving equivalence of the output to constant 0). this paper improves on this method by (a) using more intelligent simulation, (b) using cnf-based sat with circuit-based decision heuristics, and (c) interleaving sat with low-effort logic synthesis. experimental results on public and industrial benchmarks demonstrate substantial reductions in runtime, compared to the current methods. in several cases, the new solver succeeded in solving previously unsolved problems.
application-independent defect-tolerant crossbar nano-architectures. defect tolerance is a major issue in nano computing. in this paper, an application-independent defect tolerant scheme for reconfigurable crossbar nano-architectures is presented. architectural features are developed to reliably connect local defect-free subsets of crossbars in order to generate a defect-free architecture. it is also shown how to further reduce the area overhead associated with this flow by relaxing some constraints on the defect-free subsets. experimental results show more than 9x reduction in the area overhead without any negative impact on the usability of modified defect-free subsets.
analog placement with symmetry and other placement constraints. in order to handle device matching in analog circuits, some pairs of modules are required to be placed symmetrically. this paper addresses this device-level placement problem for analog circuits and our approach can handle symmetry constraint and other placement constraints simultaneously. the problem of placing devices with symmetry constraint has been extensively studied but none of the previous works has considered symmetry constraint with other placement constraints simultaneously. instead of handling the constraints by having a penalty term in the cost function to penalize violations, a unified method is proposed that, by adjusting the edge weights in a pair of constraint graphs, can try to satisfy all the placement and symmetry constraints simultaneously in a candidate floorplan solution. the maximum distance of the modules in a symmetry group from the corresponding symmetry axis will be minimized in this weight adjusting step, in order to minimize the total packing area. we have compared our method with the most updated results on this problem [2] when there are only symmetry constraints and results show that our approach can give solutions of better quality, in an acceptable amount of run time. we will also demonstrate the effectiveness of our approach in handling different types of constraints simultaneously by testing on data sets with both symmetry and other placement constraints, and the results are very promising.
cmos-mems integration: why, how and what? cmos-mems integration can improve the performance of the mems (micro-electromechanical systems), allows for smaller packages and leads to a lower packaging and instrumentation cost. as argued in this article, processing mems above cmos is the most promising approach for cmos-mems integration, but it limits the thermal budget for mems processing. poly-sige provides the desired material properties for mems applications at significantly lower temperatures compared to poly-si. a case study of a cmos-integrated sige gyroscope will be presented.
performances improvement of fpga using novel multilevel hierarchical interconnection structure. this paper presents a new multilevel hierarchical fpga (mfpga) architecture that unifies two unidirectional programmable networks: a predictible downward network based on the butterfly-fat-tree topology, and an upward network using hierarchy. studies based on the rent's rule show that wiring and switch requirements in the mfpga grow slower than in traditional topologies. new tools are developed to place and route several benchmark circuits on this architecture. experimental results based on the mcnc benchmarks show that mfpga can implement circuits with an average gain of 40% in total area compared with mesh architecture.
soft error derating computation in sequential circuits. soft error tolerant design becomes more crucial due to exponential increase in the vulnerability of computer systems to soft errors. accurate estimation of soft error rate (ser), the probability of system failure due to soft errors, is a key factor in design of cost-effective soft error resilient systems. we present a very fast and accurate approach based on enhanced static timing analysis and signal probabilities to estimate the probability of latching an incorrect value in the system bistables (timing derating). experimental results and comparison with fault injections using timing accurate monte-carlo simulations show that the accuracy of our approach is within 1% while orders of magnitude faster.
robust system level design with analog platforms. an approach to robust system level mixed signal design is presented based on analog platforms. the bottom-up characterization phase of platform components provides accurate performance models that export architectural constraints to the system level. from the one side, performance models can be affected by residual errors and usually do not consider process variations and modeling uncertainties. conversely, behavioral models cannot match accurate circuit level simulations, so that during the mapping (exploration) process circuit configurations difficult to be realized may be obtained. we propose a methodology that extends techniques from optimization and design centering to system level analog design exploiting general, implicit architectural constraints to control the robustness of the solution. the approach allows quantitative extension of robust techniques to hierarchical designs. its effectiveness is illustrated with the design of a pipeline a/d converter and a umts receiver front-end.
cost-aware synthesis of asynchronous circuits based on partial acknowledgement. designing asynchronous circuits by reusing existing synchronous tools has become a promising solution to the problem of poor cad support in asynchronous world. a straightforward way is to structurally map the gates in a synchronous netlist to their functionally equivalent modules which use delay-insensitive codes. different trade-offs exist in previous methods between the overheads of the implementations and their robustness. the aim of this paper is to optimise the area of asynchronous circuits using partial acknowledgement concept. we employ this concept in two design flows, which are implemented in a software tool to evaluate the efficiency of the method. the benchmark results show the average reduction in area by 28% and in the number of inter-functional module wires that require timing verification by 67%, compared to ncl-x.
a novel framework for faster-than-at-speed delay test considering ir-drop effects. faster-than-at-speed test have been proposed to detect small delay defects. while these techniques increase the test frequency to reduce the positive slack of the path, they exacerbate the already well known issue of ir-drop during test. this may result in false identification of good chips to be faulty due to ir-drop rather than small delay defects. we present a case study of ir-drop effects due to faster-than-at-speed test. we propose a novel framework for pattern generation/application using any commercial no-timing atpg tool, to screen small delay defects and a technique to determine the optimal test frequency considering both performance degradation due to ir-drop effects and positive slack.
performance-oriented statistical parameter reduction of parameterized systems via reduced rank regression. process variations in modern vlsi technologies are growing in both magnitude and dimensionality. to assess performance variability, complex simulation and performance models parameterized in a high-dimensional process variation space are desired. however, the high parameter dimensionality, imposed by a large number of variation sources encountered in modern technologies, can introduce significant complexion in circuit analysis and may even render performance variability analysis completely intractable. we address the challenge brought by high-dimensional process variations via a new performance-oriented parameter dimension reduction technique. the basic premise behind our approach is that the dimensionality of performance variability is determined not only by the statistical characteristics of the underlying process variables, but also by the structural information imposed by a given design. using the powerful reduced rank regression (rrr) and its extension as a vehicle for variability modeling, we are able to systematically identify statistically significant reduced parameter sets and compute not only reduced-parameter but also reduced-parameter-order models that are far more efficient than what was possible before. for a variety of interconnect modeling problems, it is shown that the proposed parameter reduction technique can provide more than one order of magnitude reduction in parameter dimensionality. such parameter reduction immediately leads to reduced simulation cost in sampling-based performance analysis, and more importantly, highly efficient parameterized interconnect reduced order models. as a general parameter dimension reduction methodology, it is anticipated that the proposed technique is broadly applicable to a variety of statistical circuit modeling problems, thereby offering a useful framework for controlling the complexity of statistical circuit analysis.
design and cad challenges in 45nm cmos and beyond. with semiconductor industry's aggressive march towards 45nm cmos technology and introduction of new materials and device structures in sight for 32nm and 22nm nodes, it is crucial for the ic design and cad community to understand the challenges posed by these potential technology changes. this tutorial will focus on these challenges starting from front end of line (devices) to the back end of line (interconnects) and finally the impact on cad. we will discuss the impact of various device technology options/improvements, such as high-k, metal gate, low temperature operation, increased mobility and reduced variability, on the overall chip performance in the context of power-constrained technology optimization. this will show that power constraints limit, but do not eliminate, the performance improvements available from new technology. the integration issues related to low-k materials for interconnects in 45nm and beyond will be examined in the context of advanced ic design. ultra low-k materials, evolution of etch and chemical mechanical polishing (cmp), and techniques to limit damage during processing and their impact on design performance will be discussed in detail. these advanced device and interconnect structures and materials including 3d technology have tremendous impact on the direction of the cad industry. we will discuss the design methodology and cad implications of these imminent technology changes.
precise identification of the worst-case voltage drop conditions in power grid verification. identifying worst-case voltage drop conditions in every module supplied by the power grid is a crucial problem in modern ic design. in this paper we develop a novel methodology for power grid verification which is based on accurately constructing the space of current variations of the supplied modules and locating its precise points that yield the worst-case voltage drop conditions. the construction of the current space is performed via plain simulation and statistical extrapolation using results from extreme value theory. the method overcomes limitations of past methods which either relied on loosely bounding the worst-case voltage drop, or abstracted the current space in a vague and incomplete set of bound-type constraints. experimental results verify the potential of the proposed method to identify worst-case conditions and demonstrate the pessimism inherent in previous bound-type approaches.
a high-level compact pattern-dependent delay model for high-speed point-to-point interconnects. this work introduces an extended linear pattern-dependent model for high-level signal delay estimation in high-speed very deep submicron point-to-point interconnects. the proposed model accurately predicts the delay in both inductively and capacitively coupled lines for the complete set of the switching patterns and not only for capacitively coupled lines or worst-case delay as in previous works. we also consider process variations in the formulation of the model and propose a moment-based approach for the inclusion of variations. the accuracy of the model has been assessed by means of extensive experiments. moreover, we show how the model can be applied at high levels of abstraction in order to explore coding-based alternatives to improve throughput.
importance of volume discretization of single and coupled interconnects. this paper presents figures of merit and error formulae to determine which interconnects require volume discretization in the ghz range. most of the previous work focused mainly on efficient modeling of volume discretized interconnects using several integration and reduction techniques. however, little work has been done to characterize when using the simple dc model has an impact on critical circuit metrics such as delay, impedance ...etc. most of the previous work simply assumes that when skin depth becomes smaller than the wire cross section dimensions, volume discretization becomes essential. however, careful analysis in this paper shows that this assumption is invalid and a figure of merit is derived to characterize when volume discretization of single and coupled wires is required. this derived figure of merit is shown to depend solely on the interconnect dimensions and spacing and is independent of the type of the materials used or technology scaling.
near-term industrial perspective of analog cad. analog and mixed-signal cad looks like a nice success story: there's been significant research in building design automation tools since the late 80's, and commercial tools have been on the market for several years now. however, the majority of ams (analog/mixed-signal) designers still use manual design only, focused around the spice simulator. so why are designers not or slowly adopting these cad tools? this paper will present a reality check on the current state of the art of ams design tools for industrial usage.
fast wire length estimation by net bundling for block placement. the wire length estimation is the bottleneck of packing based block placers. to cope with this problem, we present a fast wire length estimation method in this paper. the key idea is to bundle the 2-pin nets between block pairs, and measure the wire length bundle by bundle, instead of net by net. previous bundling method [5] introduces a huge error which compromises the performance. we present an errorfree bundling approach which utilizes the piecewise linear wire length function of a pair of blocks. with the function implemented into a lookup table, the wire length can be computed promptly and precisely by binary search. furthermore, we show that 3-pin nets can also be bundled, resulting in a further speedup. the effectiveness of our method is verified by experiments.
tp-ppv: piecewise nonlinear, time-shifted oscillator macromodel extraction for fast, accurate pll simulation. we present a novel method for generating small, accurate pll macromodels that capture transient response and jitter performance with unprecedented accuracy, while offering large speedups. the method extracts and uses a highly accurate oscillator phase macromodel termed the tp-ppv macromodel. the core idea behind the novel extraction procedure is to combine concepts from strongly nonlinear trajectory piecewise macromodeling techniques together with ppv-based timeshifted nonlinear phase macromodels. as a result, tp-ppv generated macromodels offer excellent global as well as local fidelity. these properties are necessary for handing large excursions in pll control voltages during capture/lock in, e.g., hopping frequency synthesizers. we validate tp-ppv on a 5-stage interpolative ring vco based pll and compare results against full simulation, as well as against prior macromodels. we show that, unlike prior macromodels that only work well when the control voltage of the vco has small excursions, the tp-ppv macromodel provides near-perfect matches against full spicelevel simulation over a wide range of design scenarios, while achieving speedups of about three orders of magnitude.
efficient process-hotspot detection using range pattern matching. in current manufacturing processes, certain layout configurations are likely to have reduced yield and/or reliability due to increased susceptibility to stress effects or poor tolerance to certain processes like lithography. these problematic layout configurations need to be efficiently detected and eliminated from a design layout to enable better yield. in this paper, such layout configurations are called processhotspots and an efficient and scalable algorithm is proposed to detect such process-hotspots in a given layout. the concept of a range pattern is introduced and used to accurately and compactly represent these process-hotspots. this representation is flexible and can incorporate information about the deficiencies of available modeling and/or subsequent correction (for instance, mask synthesis) techniques. each range pattern can also be associated with a scoring mechanism to score the problem regions according to yield impact. a library of range patterns is being developed in collaboration with a fab. the proposed process-hotspot detection system assumes that process-hotspots are specified as a library of range patterns and determines all occurrences of any of these range patterns in a layout. it is fast and accurate and can be applied to large industrial layouts. unlike previous work, the proposed scheme can identify problems that cannot be efficiently modeled or corrected by subsequent mask synthesis techniques and can thereby complement existing work in that area. experimental results are quite promising and show that all locations that match a range pattern in a given layout can be found in a matter of minutes.
wire density driven global routing for cmp variation and timing. in this paper, we propose the first wire density driven global routing that considers cmp variation and timing. to enable cmp awareness during global routing, we propose a compact predictive cmp model with dummy fill, and validate it with extensive industry data. while wire density has some correlation and similarity to the conventional congestion metric, they are indeed different in the global routing context. therefore, wire density rather than congestion should be a unified metric to improve both cmp variation and timing. the proposed wire density driven global routing is implemented in a congestion-driven global router [5] for cmp and timing optimization. the new global router utilizes several novel techniques to reduce the wire density of cmp and timing hotspots. our experimental results are very encouraging. the proposed algorithm improves cmp variation and timing by over 7% with negligible overhead in wirelength and even slightly better routability, compared to the pure congestion-driven global router [5].
dynamic voltage and frequency management based on variable update intervals for frequency setting. an efficient adaptive method to perform dynamic voltage and frequency management (dvfm) for minimizing the energy consumption of microprocessor chips is presented. instead of using a fixed update interval, the proposed dvfm system makes use of adaptive update intervals for optimal frequency and voltage scheduling. the optimization enables the system to rapidly track the workload changes so as to meet soft real-time deadlines. the method, which is based on introducing the concept of an effective deadline, utilizes the correlation between consecutive values of the workload. in practice because the frequency and voltage update rates are dynamically set based on variable update interval lengths, voltage fluctuations on the power network are also minimized. the technique, which may be implemented by simple hardware and is completely transparent from the application, leads to power savings of up to 60% for highly correlated workloads compared to dvfm systems based on fixed update intervals.
platform-based resource binding using a distributed register-file microarchitecture. behavior synthesis and optimization beyond the register transfer level require an efficient utilization of the underlying platform features. this paper presents a platform-based resource-binding approach using a distributed register-file microarchitecture (drfm) that makes efficient use of distributed embedded memory blocks as register files in modern fpgas. a drfm contains multiple islands, each having a local register file, a functional unit pool and data-routing logic. compared with the traditional discrete-register counterpart, a drfm allows use of the platform-featured on-chip memory or register-file ip blocks to implement its local register files, and this results in substantial saving of multiplexing logic and global interconnects. drfm provides a useful architectural template and a direct optimization objective for minimizing inter-island connections for synthesis algorithms. based on drfm, we propose a novel binding algorithm focusing on the minimization of the inter-island connections. by applying our approach, significant reductions on multiplexors and global-interconnections are observed. on the xilinx virtex ii fpga platform, our experimental results show a 2x logic area reduction and a 7.8% performance improvement, compared with the traditional discrete-register-based approach.
fill for shallow trench isolation cmp. shallow trench isolation (sti) is the mainstream cmos isolation technology. it uses chemical mechanical polishing (cmp) to remove excess of deposited oxide and attain a planar surface for successive process steps. despite advances in sti cmp technology, pattern dependencies cause large post-cmp topography variation that can result in functional and parametric yield loss. fill insertion is used to reduce pattern variation and consequently decrease post-cmp topography variation. traditional fill insertion is rulebased and is used with reverse etchback to attain desired planarization quality. due to extra costs associated with reverse etchback, "single-step" sti cmp in which fill insertion suffices is desirable. to alleviate the failures caused by imperfect cmp, we focus on two objectives for fill insertion: oxide density variation minimization and nitride density maximization. a linear programming based optimization is used to calculate oxide densities that minimize oxide density variation. next a fill insertion methodology is presented that attains the calculated oxide density while maximizing the nitride density. averaged over the two large testcases, the oxide density variation is reduced by 63% and minimum nitride density increased by 79% compared to tiling-based fill insertion. to assess post-cmp planarization, we run cmp simulation on the layout filled with our approach and find the planarization window (time window in which polishing can be stopped) to increase by 17% and maximum final step height (maximum difference in post-cmp oxide thickness) to decrease by 9%.
information processing in nanoscale arrays: dna assembly, molecular devices, nano-array architectures. arrays of simple, nanoscale components are promising for future information processing circuitry. large arrays could provide high functionality by exploiting the nonlinear dynamics of locally connected components, while circumventing nanoscale power dissipation and interconnect limits. to realize such a paradigm shift, however, many new physical design and system-level issues must be addressed. here, i will describe 1) results on dna-directed assembly of components in 2d arrays, 2) the search for electrically active molecular components and 3) schemes for information processing in arrays of simple nanoscale components.
stable and compact inductance modeling of 3-d interconnect structures. recent successful techniques for the efficient simulation of largescale interconnect models rely on the sparsification of the inverse of the inductance matrix l. while there are several techniques for sparsifying l-1, the stability of these approximations for general interconnect structures has not been established, i.e., the sparsified reluctance and inductance matrices are not guaranteed to be positive-definite. in this paper, we present a novel technique for reluctance sparsification for general interconnect structures that enjoys several advantages: first, the resulting sparse approximation is guaranteed to be positive definite. second, the approximation is optimal, in a certain well-defined sense. third, owing to its computational efficiency and numerical stability, the algorithm is applicable for very large problem sizes. finally our approach yields a compact representation of both inductance and reluctance matrices for general cases.
factor cuts. enumeration of bounded size cuts is an important step in several logic synthesis algorithms such as technology mapping and re-writing. the standard algorithm does not scale beyond 6 or 7 inputs because it enumerates all cuts and there are too many of them. we address the enumeration problem by introducing the notion of cut factorization. in cut factorization, one enumerates global and local cuts (collectively called the factor cuts) of the network, and uses these to generate other cuts. depending on how global and local cuts are defined, one obtains different factorization schemes. in the first scheme, complete factorization, it is possible to generate any cut from factor cuts. however, complete factorization is expensive though less expensive than exhaustive enumeration. in the second scheme, partial factorization, there is no guarantee of generating all cuts from factor cuts. however, it is much faster, and produces good results. in this paper we also present two applications of factor cuts: lut mapping and macrocell mapping. in lut mapping, we find that considering only factor cuts guarantees depth optimality for most nodes in the network. for the remaining nodes, other cuts need to be generated from factor cuts and examined. in macrocell mapping, we focus on a particular 9-input macrocell, and use factor cuts as a heuristic method to improve depth by reducing structural bias. factor cuts are used to map the macrocell as a whole whenever possible instead of mapping its parts separately. in this context factor cuts enable a new quality-run-time tradeoff between mapping parts of the macrocell separately (poor quality), and mapping using all 9-input cuts (long run-time).
system-level process-driven variability analysis for single and multiple voltage-frequency island systems. the problem of determining bounds for application completion times running on generic systems comprised of single or multiple voltage-frequency islands (vfis) with arbitrary topologies is addressed in the context of manufacturing-driven variability. the approach provides an exact solution for the system-level timing yield in single clock, single voltage (ssv) and vfi systems with an underlying tree-based topology, and a tight upper bound for generic, non-tree based topologies. the results show that: (a) timing yield for overall source-to- sink completion time for generic systems can be modeled in an exact manner for both ssv and vfi systems; and (b) multiple vfi, latency-constrained systems can achieve 11--90% higher timing yield than their ssv counterparts. the results are proven formally and supported by experimental results on two embedded applications, namely software defined radio and mpeg2 encoder.
current path analysis for electrostatic discharge protection. the electrostatic discharge (esd) problem has become a challenging reliability issue in nanometer circuit design. high voltages resulted from esd might cause high current densities in a small device and burn it out, so on-chip protection circuits for ic pads are required. to reduce the design cost, the protection circuit should be added only for the ic pads with an esd current path, which arises the esd current path analysis problem. in this paper, we first introduce the analysis problem for esd protection in circuit design. we then model the circuit as a constrained graph, decompose esd connected components linked with the pads, and apply the breadth-first search (bfs) to identify the esd connected components in each constrained graph and thus the current paths. experimental results show that our algorithm can detect all esd paths very efficiently and economically. to our best knowledge, our algorithm is the first point tool available to the public for the esd analysis.
soft error reduction in combinational logic using gate resizing and flipflop selection. soft errors in logic are emerging as a significant reliability problem for vlsi designs. this paper presents novel circuit optimization techniques to mitigate soft error rates (ser) of combinational logic circuits. first, we propose a gate sizing algorithm that trades off ser reduction and area overhead. this approach first computes bounds on the maximum achievable ser reduction by resizing a gate. this bound is then used to prune the circuit graph, arriving at a smaller set of candidate gates on which we perform incremental sensitivity computations to determine the gates that are the largest contributors to circuit ser. second, we propose a flipflop selection method that uses slack information at each primary output node to determine the flipflop configuration that produces maximum ser savings. this approach uses an enhanced flipflop library that contains flipflops of varying temporal masking ability. third, we propose a unified, cooptimization approach combining flipflop selection with the gate sizing algorithm. the joint optimization algorithm produces larger ser reductions while incurring smaller circuit overhead than either technique taken in isolation. experimental results on a variety of benchmarks show ser reductions of 7.9x with gate sizing, 6.6x with flipflop assignment, and 28.2x for the combined optimization approach, with no delay penalties and area overheads within 5--6%. the runtimes for the optimization algorithms are on the order of 1--3 minutes.
design optimization for single-event upset robustness using simultaneous dual-vdd and sizing techniques. an optimization algorithm for the design of combinational circuits that are robust to single-event upsets (seus) is described. a simple, highly accurate model for the seu robustness of a logic gate is developed. this model -- in posynomial form -- is integrated with performance and power constraints into an optimization framework based on geometric programming for design space exploration. simulation results for design optimization using simultaneous dual- vdd and gate sizing techniques for the 70 nm process technology demonstrate the tradeoffs that can be achieved with this approach.
testing delay faults in asynchronous handshake circuits. as a class of asynchronous circuits, handshake circuits are designed to tolerate variation of gate delays. however, certain timing constraints, such as the bundled data assumption, are exploited in the single-rail implementation of these circuits in order to simplify them. therefore, any delay fault in the circuit may cause one of two problems, namely performance degradation or logic errors. to address the challenges incurred by the autonomous behavior of handshake circuits during at-speed test, we propose test methods for both types of delay faults based on a dft strategy which greatly simplifies the complexity of test generation. the efficiency of the proposed methodology is demonstrated through experimental results on several handshake circuits.
voltage island aware floorplanning for power and timing optimization. power consumption is a crucial concern in nanometer chip design. researchers have shown that multiple supply voltage (msv) is an effective method for power consumption reduction. the underlying idea behind msv is the trade-off between power saving and performance. in this paper, we present an effective voltage assignment technique based on dynamic programming. given a netlist without reconvergent fanouts, the dynamic programming can guarantee an optimal solution for the voltage assignment. we then generate a level shifter for each net that connects two blocks in different voltage domains, and perform power-network aware floorplanning for the msv design. experimental results show that our floorplanner is very effective in optimizing power consumption under timing constraints.
practical variation-aware interconnect delay and slew analysis for statistical timing verification. interconnects constitute a dominant source of circuit delay for modern chip designs. the variations of critical dimensions in modern vlsi technologies lead to variability in interconnect performance that must be fully accounted for in timing verification. however, handling a multitude of inter-die/intra-die variations and assessing their impacts on circuit performance can dramatically complicate the timing analysis. in this paper, a practical interconnect delay and slew analysis technique is presented to facilitate efficient evaluation of wire performance variability. by harnessing a collection of computationally efficient procedures and closed-form formulas, process and input signal variations are directly mapped into the variability of the output delay and slew. since our approach produces delay and slew expressions parameterized in the underlying process variations, it can be harnessed to enable statistical timing analysis while considering important statistical correlations. our experimental results have indicated that the presented analysis is accurate regardless of location of sink nodes and it is also robust over a wide range of process variations.
temperature-aware leakage minimization technique for real-time systems. in this paper, we study the interdependency between leakage energy and chip temperature in real-time systems. we observe that the temperature variation on chip has a large impact on the system's leakage energy. by incorporating the temperature information, we propose an online temperature-aware leakage minimization algorithm for real-time systems. the basic idea is to run tasks when the system is cool and the workload is high, and put the system into sleep when it is hot and the workload is light. this online algorithm has low run-time complexity and improve the leakage energy saving by 34% on average in both real life and artificial benchmarks over traditional dvs approaches. finally, our algorithm can be combined with existing dynamic voltage scaling methods to further improve the total energy efficiency.
conjoining soft-core fpga processors. soft-core programmable processors on field-programmable gate arrays (fpgas) can be custom synthesized to instantiate only those hardware units, such as multipliers and floating-point units, that an application requires to meet performance demands, thus minimizing soft-core size on the fpga. conjoining processors, meaning to share hardware units among two or more processors, can further reduce soft-core size, leaving more resources for other circuits such as custom coprocessors. using xilinx microblaze coprocessors and standard embedded system benchmarks, we show that conjoining two processors can provide 16% processor size reductions on average, with less than 1% cycle count overhead. we introduce an efficient dynamic-programming-based exploration method to find the best custom instantiation of hardware units, considering both standalone and conjoined options, for soft-core processors.
design automation for analog: the next generation of tool challenges. the decade of the 1990s saw the first wave of practical "post-spice" tools for analog designs. a range of synthesis, optimization, layout and modeling techniques made their way from academic prototypes to first-generation commercial offerings. we offer some pragmatic prognostications for what the next wave might (or, more bluntly, should) focus on next, as pressure to improve ams design productivity grows.
performance analysis of concurrent systems with early evaluation. early evaluation allows to execute operations when enough information at the inputs has been received to determine the value at the outputs. systems that can tolerate variable-latency units, such as latency-insensitive or asynchronous systems, can enhance their performance by using early evaluation. the most relevant example of a unit with early evaluation is the multiplexor: the output can be determined as soon as the information of the selected channel arrives, without waiting for the other channels. this paper analyzes the potential impact of early evaluation in concurrent systems. an analytical model, based on a petri net extension with early firing is proposed to estimate the performance. the reduction of the analytical model to a linear programming formulation for an efficient estimation of the upper bound for the system throughput is proposed. the results show the accuracy of the model and the benefits of early evaluation.
an optimal simultaneous diode/jumper insertion algorithm for antenna fixing. as technology enters the nanometer territory, the antenna effect plays an important role in determining the yield and reliability of a vlsi circuit. diode insertion and jumper insertion are the most effective techniques to fix the antenna effect. however, due to the increasing design complexity and the limited routing resource, applying diode or jumper insertion alone cannot achieve a high antenna fixing rate. in this paper, we give a polynomial-time antenna violation detection/fixing algorithm by simultaneous diode/jumper insertion with minimum cost, based on a minimum-cost networkflow formulation. experimental results show that our algorithm consistently achieves much higher antenna fixing rates than the state-of-the-art jumper insertion and diode insertion algorithms alone.
efficient boolean characteristic function for fast timed atpg. circuit timing analysis is important in various aspects of circuit optimization. the problem of finding input vectors achieving functional and temporal requirements is known as timed automatic test pattern generation (timed atpg). a timed atpg algorithm will return an input vector that satisfies functional and temporal requirements simultaneously when evaluated. several previous works use timed atpg as a core engine for solving problems related to timing analysis, such as crosstalk and maximum instantaneous current analysis. despite the usefulness of timed atpg, traditional timed atpg is slow and unscalable for large circuits. in this paper, we present a very efficient way for timed atpg. on average, our results are 8 times faster than the most recent work, and in some cases, up to 32 times faster.
uml for esl design: basic principles, tools, and applications. this paper starts with a brief introduction to the uml 2.0 and application-specific uml customizations via profiles. after a discussion of uml design tools with focus on eda support, we present a hw/sw co-design approach and demonstrate how hw architectures are described together with application sw in a unique uml based environment. using a dedicated profile providing support for systemc in uml, and a systemc wrapper for the simit instruction set simulator of a strongarm, an executable model of the complete architecture is generated which can be simulated by the systemc kernel. the physical layer of an 802.11a system is used as an application example.
optimal memoryless encoding for low power off-chip data buses. off-chip buses account for a significant portion of the total system power consumed in embedded systems. bus encoding schemes have been proposed to minimize power dissipation, but none has been demonstrated to be optimal with respect to any measure. in this paper, we give the first provably optimal and explicit (polynomial-time constructible) families of memoryless codes for minimizing bit transitions in off-chip buses. our results imply that having access to a clock does not make a memoryless encoding scheme that minimizes bit transitions more powerful.
post-placement voltage island generation. high power consumption will shorten battery life for handheld devices and cause thermal and reliability problems. one way to lower the dynamic power consumption is to reduce the supply voltage. multi-supply voltage (msv) is introduced to provide higher flexibility in controlling the power and performance trade-off in region-based msv, circuits are partitioned into "voltage islands" where each island occupies a contiguous physical space and operates at one supply voltage. in a very recent work [6], this supply voltage partitioning problem is addressed, and the input circuit is partitioned into a slicing structure with every voltage island rectangular in shape. this unnecessary restriction on the structure and island shapes has caused a significant degradation in the solution quality. in this paper, we propose a method to solove this voltage island generation problem without these restrictions. experimental results have shown that our approach is fast and can improve the solution quality significantly. in some data sets, only two voltage islands are needed to satisfy the same power consumption bound while the approach in [6] will generate nineteen.
handling inductance in early power grid verification. as part of integrated circuit design verification, one should check if the voltage drop on the power grid exceeds some critical threshold. one way to do this is by simulation, but that is computationally expensive and gets prohibitive for large circuits with a large variety of possible operational modes. another limitation of a simulation-based approach is that it requires complete knowledge of the logic circuitry drawing current from the grid, thus precluding grid verification early in the design process. in this paper, we model the grid as an rlc circuit and we propose three verification techniques that can be applied in the early stages of the design process. these techniques do not require exact knowledge of the circuit currents. instead, the currents drawn by the logic beneath the power grid are described by means of current constraints that capture the uncertainty about circuit details and activity. the first verification approach gives the exact worst-case voltage drop at every node of the grid, but it is slow. a second faster approach gives conservative bounds on the worst-case voltage drop at every node of the grid. the third approach is much faster; it is a conservative approach which simply checks if the grid voltage drop exceeds some pre-defined thresholds, without actually computing the worst-case voltage drop at every node.
optimizing yield in global routing. we present the first efficient approach to global routing that takes spacing-dependent costs into account and provably finds a near-optimum solution including these costs. we show that this algorithm can be used to optimize manufacturing yield. the core routine is a parallelized fully polynomial approximation scheme, scaling very well with the number of processors. we present results showing that our algorithm reduces the expected number of defects in wiring by more than 10 percent on state-of-the-art industrial chips.
timing model reduction for hierarchical timing analysis. in this paper, we propose a timing model reduction algorithm for hierarchical timing analysis based on a bicliquestar replacement technique. in hierarchical timing analysis, each functional block is characterized into an abstract timing model. the complexity of analysis is linear to the number of edges in the abstract timing model for timing propagation. we propose a biclique-star replacement technique to minimize the number of edges in the timing model. the experiments on industry test cases show that by allowing acceptable errors, the proposed algorithm can largely reduce the number of edges in the timing model.
a bitmask-based code compression technique for embedded systems. embedded systems are constrained by the available memory. code compression techniques address this issue by reducing the code size of application programs. dictionary-based code compression techniques are popular because they offer both good compression ratio and fast decompression scheme. recently proposed techniques [8, 9] improve standard dictionary-based compression by consideringmismatches. this paper makes two important contributions: i) it provides a cost-benefit analysis framework for improving the compression ratio by creating more matching patterns, and ii) it develops an efficient code compression technique using bitmasks to improve the compression ratio without introducing any decompression penalty. to demonstrate the usefulness of our approach we have used applications from various domains and compiled for a wide variety of architectures. our approach outperforms the existing dictionary-based techniques by an average of 15%, giving a compression ratio of 55% - 65%.
loop pipelining for high-throughput stream computation using self-timed rings. we present a technique for increasing the throughput of stream processing architectures by removing the bottlenecks caused by loop structures. we implement loops as self-timed pipelined rings that can operate on multiple data sets concurrently. our contribution includes a transformation algorithm which takes as input a high-level program and gives as output the structure of an optimized pipeline ring. our technique handles nested loops and is further enhanced by loop unrolling. simulations run on benchmark examples show a 1.3 to 4.9x speedup without unrolling and a 2.6 to 9.7x speedup with twofold loop unrolling.
dynamic power management using machine learning. dynamic power management (dpm) work proposed to date places inactive components into low power states using a single dpm policy. in contrast, we instead dynamically select among a set of dpm policies with a machine learning algorithm. we leverage the fact that different policies outperform each other under different workloads and devices. our algorithm adapts to changes in workloads and guarantees quick convergence to the best performing policy for each workload. we performed experiments with a policy set representing state of the art dpm policies on a hard disk drive and a wlan card. our results show that our algorithm adapts really well with changing device and workload characteristics and achieves an overall performance comparable to the best performing policy at any point of time.
exploring linear structures of critical path delay faults to reduce test efforts. it has been shown that the delay of a target path can be composed linearly of other path delays. if the later paths are robustly testable (with known delay values), the target path can then be validated through simple calculation. yet, no decomposition process is available to find paths that satisfy the above property. in this paper, given a set of target critical paths, we propose a two-stage method to find a set of robust-testable paths (with smaller number than the original set). the first stage constructs a necessary subset for critical robust paths, and the second stage identifies remaining functional sensitizable segments and their corresponding composing robust paths. the experiments show that a large percentage (several benchmarks close to 100%, 75% on average) of critical paths can be covered for most circuits. all paths and coverage are verified to match the best possible results. the data also indicate that the remaining hard-to-test (functional sensitizable) paths actually result from only a few tens of segments in the circuit (except for one circuit, s35932). dft technique can then be applied to these uncovered segments for full testability with small overheads.
mapping arbitrary logic functions into synchronous embedded memories for area reduction on fpgas. this work describes a new mapping technique, ram-map, that identifies parts of circuits that can be efficiently mapped into the synchronous embedded memories found on field programmable gate arrays (fpgas). previous techniques developed for mapping into asynchronous embedded memories cannot be used because modern fpgas do not have asynchronous embedded memories. after technology mapping, an area-prediction cost function is used to guide the selection of logic cones to be placed in embedded memories. extra logic is added to compensate for missing asynchronous functionality on the synchronous memories. experiments conducted on altera's stratix device family indicate that this embedded memory mapping technique can provide an average area reduction of 6.2% and up to 32.5% on a large set of industrial designs. a small architecture change that increases the size of the fpga fabric by 0.05% can increase the average area reduction to 14.1% and up to 59.1% on the same design set.
exploiting soft redundancy for error-resilient on-chip memory design. memory design is facing the upcoming challenges due to a combination of technology scaling and higher levels of integration and system complexity. in particular, memory circuits become vulnerable to transient (soft) errors caused by particle strikes and process spread. in this paper, we propose a new error-tolerance technique referred to as the soft redundancy for on-chip memory design. program runtime variations in memory spatial locality cause wasted memory spaces occupied by the irrelevant data. the proposed soft-redundancy allocated memory exploits these wasted memory spaces to achieve efficient memory access and effective error protection in a coherent manner. simulation results on the spec cpu2000 benchmarks demonstrate 73.7% average error protection coverage ratio on the 23 benchmarks, with average of 52% and 48.3% reduction in memory miss rate and bandwidth requirement, respectively, as compared to the existing techniques.
layer minimization of escape routing in area array packaging. we devise a central triangular sequence to minimize the escape routing layers in area array packaging. we use a network flow model to analyze the bottleneck of the routable pins. the triangular patterns are generated in a reverse order from the last to the first layer. we demonstrate that the triangular pin sequence maximizes the sum of escape pins in the accumulated layers and thus minimize the number of escape routing layers. a test case is presented to illustrate the approach.
fast decap allocation based on algebraic multigrid. decap (decoupling capacitor) is an effective technique for suppressing power supply noise. nevertheless, over-usage of decap usually causes excessive power dissipation. therefore, the total decap area needs to be minimized subject to power supply noise constraints. this is a complicated nonlinear optimization problem that may have as many as millions of variables. we propose an algebraic multigrid (amg) based method to handle the high complexity. an error compensation scheme is developed to compensate the accuracy loss during the amg reduction. a charge based back-mapping method and a few other techniques are suggested to further improve the computation efficiency. our method is flexible to use and can be easily integrated with other existing decap allocation works. when compared to several previous works, the results from our method are usually the closest to the optimum. our method also runs fast and can solve circuits with up to 1 million nodes in about 11 minutes. in addition, it has better scalability than the previous works.
thermal sensor allocation and placement for reconfigurable systems. temperature monitoring using thermal sensors is an essential tool for evaluating the thermal behavior and sustaining the reliable operation in high-performance and high-power systems. with current technology scaling and integration trends timely and accurate detection of localized heating will be evermore important. in this work, we address the creation of a resource efficient sensor infrastructure for computing systems that are of regular nature, such as logic array-based computing platforms. we propose algorithms to embed thermal sensors into a regular structure to minimize the number of sensors and determine sensor locations required to maintain a given accuracy in temperature sensing for a given design. our algorithms are tailored for minimal usage of thermal sensors to suit a variety of architectural conditions. for programmable logic arrays the highly application-specific usage of the hardware resources leads to unpredictable thermal profiles. as a result, post-manufacture instantiation of thermal sensors is desired, which in turn demands the use of native hardware resources, which can be scarce. we demonstrate that using our techniques the number of sensors required to monitor a set of hotspots is reduced by 75% on an average, across different sizes of logic arrays for different hotspot distributions compared to a uniform distribution of sensors throughout the fabrics.
leveraging protocol knowledge in slack matching. stalls, due to mis-matches in communication rates, are a major performance obstacle in pipelined circuits. if the rate of data production is faster than the rate of consumption, the resulting design performs slower than when the communication rate is matched. this can be remedied by inserting pipeline buffers (to temporarily hold data), allowing the producer to proceed if the consumer is not ready to accept data. the problem of deciding which channels need these buffers (and how many) for an arbitrary communication profile is called the slack matching problem; the optimal solution to this problem has been shown to be np-complete. in this paper, we present a heuristic that uses knowledge of the communication protocol to explicitly model these bottlenecks, and an iterative algorithm to progressively remove these bottlenecks by inserting buffers. we apply this algorithm to asynchronous circuits, and show that it naturally handles large designs with arbitrarily cyclic and acyclic topologies, which exhibit various types of control choice. the heuristic is efficient, achieving linear time complexity in practice, and produces solutions that (a) achieve up to 60% performance speedup on large media processing kernels, and (b) can either be verified to be optimal, or the approximation margin can be bounded.
a network-flow approach to timing-driven incremental placement for asics. we present a novel incremental placement methodology called flowplace for significantly reducing critical path delays of placed standard-cell circuits. flowplace includes: a) a timing-driven (td) analytical global placer tan that uses accurate delay functions and minimizes a combination of linear and quadratic objective functions; b) a network flow based detailed placer tif that has new and effective techniques for performing td incremental placement and satisfying rowlength (white space) constraints. we have obtained results on three sets of benchmarks: i) td versions of the ibm benchmark suite that we have constructed; ii) benchmarks used in td-dragon; iii) the faraday benchmarks. results show that starting with dragon-placed circuits, we are able to obtain up to 34% and an average of 18% improvement in critical path delays, at an average of 17.5% of the run-time of the dragon placer. starting with a state-of-the-art td placer td-dragon, for the td-dragon benchmarks we obtain up to about 10% and an average of 4.3% delay improvement with 12% of td-dragon's run times; this is significant as we are extracting performance improvements from a performanceoptimized layout. wire length deterioration on the average over all benchmark suites is less than 8%.
variability and yield improvement: rules, models, and characterization. yield and variability are becoming detractors for successful design in sub-90-nm process technologies. we consider the fundamental lithography and process issues that are driving variability and yield and the role of design rules in future processes. we examine the importance of layout-aware modeling and layout regularity, including advantages and cost. characterization structures for examining the electrical effects of device-level variability are discussed as well as circuit techniques for mitigating variability and yield challenges.
an analytical model for negative bias temperature instability. negative bias temperature instability (nbti) in pmos transistors has become a significant reliability concern in present day digital circuit design. with continued scaling, the effect of nbti has rapidly grown in prominence, forcing designers to resort to a pessimistic design style using guard-banding. since nbti is strongly dependent on the time for which the pmos device is stressed, different gates in a combinational circuit experience varying extents of delay degradation. this has necessitated a mechanism of quantizing the gate-delay degradation, to pave the way for improved design strategies. our work addresses this issue by providing a procedure for determining the amount of delay degradation of a circuit due to nbti. an analytical model for nbti is derived using the framework of the reaction-diffusion model, and a mathematical proof for the widely observed phenomenon of frequency independence is provided. simulations on iscas benchmarks under a 70nm technology show that nbti causes a delay degradation of about 8% in combinational logic based circuits after 10 years (&ap; 3 x 108s).
a statistical framework for post-silicon tuning through body bias clustering. adaptive body biasing (abb) is a powerful technique that allows post-silicon tuning of individual manufactured dies such that each die optimally meets the delay and power constraints. assigning individual bias control to each gate leads to severe overhead, rendering the method impractical. however, assigning a single bias control to all gates in the circuit prevents the method from compensating for intra-die variation and greatly reduces its effectiveness. in this paper, we propose a new variability-aware method that clusters gates at design time into a handful of carefully chosen independent body bias groups, which are then individually tuned post-silicon for each die. we show that this allows us to obtain near-optimal performance and power characteristics with minimal overhead. for each gate, we generate the probability distribution of its post-silicon ideal body bias voltage using an efficient sampling method. we then use these distributions and their correlations to drive a statistically-aware clustering technique. we study the physical design constraints and show how the area and wirelength overhead can be significantly limited using the proposed method. compared to a fixed design time based dual threshold voltage assignment method, we improve leakage power by 38-71% while simultaneously reducing the standard deviation of delay by 2-9x.
guaranteeing performance yield in high-level synthesis. meeting timing constraint is one of the most important issues for modern design automation tools. this situation is exacerbated with the existence of process variation. current high-level synthesis tools, performing task scheduling, resource allocation and binding, may result in unexpected performance discrepancy due to the ignorance of the impact of process variation, which requires a shift in the design paradigm, from today's deterministic design to statistical or probabilistic design. in this paper, we present a variation-aware performance yield-guaranteed high-level synthesis algorithm. the proposed approach integrates high-level synthesis and statistical static timing analysis into a simulated annealing engine to simultaneously explore solution space while meeting design objectives. our results show that the area reduction is in the average of 14% when 95% performance yield is imposed with the same total completion time constraint.
robust estimation of parametric yield under limited descriptions of uncertainty. reliable prediction of parametric yield for a specific design is difficult; a significant reason is the reliance of the yield estimation methods on the hard-to-measure distributional properties of the process data. existing methods are inadequate when dealing with real-life distributions of process and environmental parameters, and limited availability of parameter data during early design. this paper proposes a robust technique for full-chip parametric yield estimation; the proposed work is based on the rigorous notions of non-parametric robust statistics which permits estimation based on the knowledge of the range and the limited number of moments (e.g. mean and variance) of the parameter distributions. fully or partially specified process and environmental parameters can be described by robust representations, and used to estimate probabilistic bounds for leakage dissipation. the proposed approach is applied to estimating the chip-level parametric yield. the experimental results show that the robust estimation algorithm improves the total leakage estimate by 5-13% at the 99th percentile across distinct frequency bins, compared to using only the intervals of partially-specified parameters.
from single core to multi-core: preparing for a new exponential. in the past, processor design trends were dominated by increasingly complex feature sets, higher clock speeds, growing thermal envelopes and increasing power dissipation. recently, clock speeds have tapered and thermal and power dissipation envelopes have remained flat. however, the demand for increasing performance continues which has fueled the move to integrated multiple processor (multi-core) designs. this paper discusses this trend towards multi-core processor designs, the design challenges that accompany it and a view of the research required to support it.
un/dopack: re-clustering of large system-on-chip designs with interconnect variation for low-cost fpgas. fpga device area is dominated by interconnect, so low-cost fpga architectures often have reduced interconnect capacity. this limited routing capacity creates a hard channel width constraint that can make it difficult for cad tools to successfully map a circuit into these devices. instead of migrating a design to a high-cost, resource-rich architecture that is easier to route, we present a cheaper alternative: a fully automated cad flow (un/dopack) that finds local regions of high interconnect demand and reduces it by spreading out the logic in that region. this is done by introducing whitespace in the form of empty logic elements (les) within the configurable logic blocks (clbs) of the congested region. after spreading, the congested region occupies more routing channels and so obtains access to greater aggregate interconnect capacity. although this has the side effect of using more clbs, it has the advantage of lowering peak interconnect demands and making a previously-unroutable circuit routable. we also design a new set of synthetic benchmark circuits that model interconnect variation within a large design. using these benchmarks, we show that circuits with high interconnect variation require fpga devices to have large channel widths. however, since congestion of such circuits is localized, un/dopack is very good at reducing the peak demands of circuits with high interconnect variation. our results suggest that even for an average rent exponent of 0.62 (a modest value), a large variation of this exponent within a design will also require fpgas to have large channel widths. thus, it is crucial to study interconnect variation of benchmark circuits when designing lowcost fpgas. previous research studying interconnect properties focuses on average rent exponent values of each design, but we believe new work should study variation as well. for circuits with high interconnect variation, we demonstrate that channel widths can be reduced by up to ~40% with only ~10% increase in area.
energy budgeting for battery-powered sensors with a known task schedule. battery-powered wireless sensors are severely constrained by the amount of the available energy. a method for computing the energy budget per sensing task can be a valuable design aid for sensor network optimizations. this work presents such a method that computes the upper and lower bounds on the task energy budget for a sensor node that must remain operational over a specified lifetime, with a known task schedule. these bounds take into account nonlinear changes in the battery voltage, capacity loss at high discharge rates, charge recovery, and capacity fade over time. we also propose efficient approximations replacing expensive calculations of the battery voltage while computing the energy budget bounds.
a code refinement methodology for performance-improved synthesis from c. although many recent advances have been made in hardware synthesis techniques from software programming languages such as c, the performance of synthesized hardware commonly suffers due to the use of c constructs and coding practices that are not appropriate for hardware. most previous approaches to addressing this problem require drastic changes to coding practice. we present an approach that instead requires only minimal changes but yields significant speedups. in this approach, a software developer initially writes c code as they normally would, and then applies simple refinement guidelines to only the performance-critical code regions, which are the regions most likely to be synthesized to hardware. alternatively, if a designer is aware of performance-critical parts of the application, the guidelines could be followed during development. in this study, we analyze dozens of embedded benchmarks to determine the most common c coding practices that limit hardware performance, and introduce coding guidelines to make the code more amenable to synthesis. those guidelines typically require minimal coding effort, generally consisting of less than ten lines of code for each guideline. the guidelines typically represent modifications that require designer knowledge, making the guidelines difficult or impossible for synthesis tools to automate. we apply these guidelines to six benchmarks, resulting in average speedups of 3.5x compared to synthesis from the original code with a negligible software size and performance overhead.
studying a gals fpga architecture using a parameterized automatic design flow. routing delays dominate other delays in current fpga designs. we have proposed a novel globally asynchronous locally synchronous (gals) fpga architecture called the gapla to deal with this problem. in the gapla architecture, the fpga area is divided into locally synchronous blocks and the communications between them are through asynchronous i/o interfaces. an automatic design flow is developed for the gapla architecture. starting from behavioral description, a design is partitioned into smaller modules and fit to gapla synchronous blocks. the asynchronous communications between modules are then sytthesized. the cad flow is parameterized in modeling the gapla architecture. by manipulating the parameters, we could study different factors of the designed gapla arcitecturc. our experimental results show an average of 20% performance improvement could be achieved by the gapla architecture.
analytical modeling of sram dynamic stability. in this paper, for the first time, a theory for evaluating dynamic noise margins of sram cells is developed analytically. the results allow predicting the transient error susceptibility of an sram cell using a closed-form expression. the key innovation involves using the methods of nonlinear system theory in developing the model. it is shown that when a transient noise of given magnitude affects a sensitive node of a cell, the bi-stable, feedback-driven nature of the cell determines whether the noise will be suppressed or will evolve to eventually flip state. the specific formal and quantitative result is a closed-form expression that can be used to predict whether a cell flip will occur for a noise signal with specific characteristics, and for a given sram cell design. experiments show excellent match between the analytical prediction and the spice simulation results.
an efficient technique for synthesis and optimization of polynomials in gf(2). this paper presents an efficient technique for synthesis and optimization of polynomials over gf(2m), where m is a non-zero positive integer. the technique is based on a graph-based decomposition and factorization of polynomials over gf(2m), followed by efficient network factorization and optimization. a technique for efficiently computing coefficients over gf(pm), where p is a prime number, is first presented. the coefficients are stored as polynomial graphs over gf(pm). the synthesis and optimization is initiated from this graph based representation. the technique has been applied to minimize multipliers over all the 51 fields in gf(2k), k = 2...8 in 0.18 micron cmos technology with the help of the synopsys&reg; design compiler. it has also been applied to minimize combinational exponentiation circuits, and other multivariate bit- as well as word-level polynomials. the experimental results suggest that the proposed technique can reduce area, delay, and power by significant amount.
combinatorial algorithms for fast clock mesh optimization. we present a fast and efficient combinatorial algorithm to simultaneously identify the candidate locations as well as the sizes of the buffers driving a clock mesh. due to the high redundancy, a mesh architecture offers high tolerance towards variation in the clock skew. however, such a redundancy comes at the expense of mesh wire length and power dissipation. based on survivable network theory, we formulate the problem to reduce the clock mesh by retaining only those edges that are critical to maintain redundancy. such a formulation offers designer the option to trade-off between power and tolerance to process variations. experimental results indicate that our techniques can result in power savings up to 28% with less than 4% delay penalty.
runtime distribution-aware dynamic voltage scaling. we propose a new intra-task dynamic voltage scaling (dvs) method to capture an important fact of 'software runtime distribution' and integrate it into dvs effectively. specifically, the proposed method finds performance levels, for a given software runtime distribution, i.e. statistical profiling of execution cycles (neither the execution cycle of worst-case execution path nor the worst-case execution cycles of basic blocks), which leads to a 'minimal energy consumption while satisfying the given deadline constraints. experimental results report that the proposed method gives 19.2%~33.3% further energy reduction compared with the best-known methods for two industrial multimedia software programs, h.264 decoder and mpeg4 decoder.
a framework for statistical timing analysis using non-linear delay and slew models. in this paper we propose a framework for statistical static timing analysis (ssta) considering intra-die process variations. given a cell library, we propose an accurate method to characterize the gate and interconnect delay as well as slew as a function of underlying parameter variations. using these accurate delay models, we propose a method to perform ssta based on a quadratic delay and slew model. the method is based on efficient dimensionality reduction technique used for accurate computation of the max of two delay expansions. our results indicate less than 4% error in the variance of the delay models compared to spice monte carlo and less than 1% error in the variance of the circuit delay compared to monte carlo simulations.
template-based parasitic-aware optimization and retargeting of analog and rf integrated circuit layouts. parasitic effects are extremely significant for the performance of analog and rf integrated circuits. although layout retargeting for technology migration or specification update is able to preserve designers' intent, the associated layout parasitics cannot be guaranteed to meet the performance requirements. in this paper, we present a novel algorithm that performs parasitic-aware automatic layout retargeting for analog/rf integrated circuits. given parasitic resistance/capacitance bounds and matching constraints ensuring desired circuit performance, the algorithm creates a reduced-template-graph from original layouts and adds parasitic constraints. using a two-dimensional hybrid scheme of graph-based optimization and nonlinear programming, the nonlinear problem is solved effectively and efficiently. the algorithm has successfully retargeted operational amplifiers and an rf low-noise amplifier within minutes of cpu time.
automatic memory reductions for rtl model verification. we present several techniques for automatically reducing memories in rtl designs. this includes a new memory abstraction algorithm that allows us to greatly reduce the size of memories and a technique based on-term rewriting that further improves the abstraction. in contrast to previously proposed methods for abstracting memories of rtl designs, our methods are general---e.g., they allow us to arbitrarily and directly compare memories---and they are sound and complete---e.g., there are no false positives or negatives. in addition, the combination of our techniques allows us to automatically verify rtl pipelined machine designs beyond the reach of current state-of-the-art methods, as our experimental results show.
accelerating high-level bounded model checking. sat-based bounded model checking (bmc) has been found promising in finding deep bugs in industry designs and scaling well with design sizes. however, it has limitations due to requirement of finite data paths, inefficient translations and loss of high-level design information during the bmc problem formulation. these shortcomings inherent in boolean-level bmc can be avoided by using high-level bmc. we propose a novel framework for high-level bmc, which includes several techniques that extract high-level design information from efsm models to make the verification model "bmc friendly", and use it on-the-fly to simplify the bmc problem instances. such techniques overcome the inherent limitations of boolean-level bmc, while allowing integration of state-of-the-art techniques for bmc. in our controlled experiments we found signficant performance improvements achievable by the proposed techniques.
molecular organic electronic circuits. electronic energy disorder associated within amorphous and polycrystaline molecular organic thin film structures strongly affects the macroscopic observable behavior of organic field effect transistors (ofet) and poses practical challenges to implementing ofet circuits. it has been convenient to ignore the detailed physical processes associated with this disorder and model ofet behavior as equivalent to silicon fets, but such simplifications limit our ability to develop integrated circuit technology as they fail to predict the true integrated ofet behavior. this talk will highlight the evolution of the organic electronic circuit technology and the challenges that lay ahead, emphasizing the need for physically accurate models of device behavior as the cornerstone of any future circuit advancements.
simultaneous power and thermal integrity driven via stapling in 3d ics. the existing work on via-stapling in 3d integrated circuits optimizes power and thermal integrity separately and uses steadystate thermal analysis. this paper presents the first in-depth study on simultaneous power and thermal integrity driven viastapling in 3d design. the transient temperature and supply voltage violations are calculated by a structured and parameterized model reduction, which also generates parameterized temperature and voltage violation sensitivities with respect to the via pattern and density. using parameterized sensitivities, an efficient yet effective greedy optimization is presented to optimize power and thermal integrity simultaneously. experiments with two active device layers show that compared to sequential power and thermal optimization using steady-state thermal analysis, sequential optimization using transient thermal analysis reduces non-signal vias by on average 11.5%, and simultaneous optimization using transient thermal analysis reduces non-signal vias by on average 34%. the via reduction would be higher for the 3d design with more device layers.
faster, parametric trajectory-based macromodels via localized linear reductions. trajectory-based methods offer an attractive methodology for automated, on-demand generation of macromodels for custom circuits. these models are generated by sampling the state trajectory of a circuit as it simulates in the time domain, and building macromodels by reducing and interpolating among the linearizations created at a suitably spaced subset of the time points visited during training simulations. however, a weak point in conventional trajectory models is the reliance on a single, global reduction matrix for the state space. we develop a new, faster method that generates and weaves together a larger set of smaller localized linearizations for the trajectory samples. the method not only improves speedups to 30x over spice, but as a side benefit also provides a platform for parametric small-signal simulation of circuits with variational device/process parameters, at a speedup of roughly 200x over spice.
analysis and modeling of cd variation for statistical static timing. statistical static timing analysis (ssta) has become a key method for analyzing the effect of process variation in aggressively scaled cmos technologies. much research has focused on the modeling of spatial correlation in ssta. however, the vast majority of these works used artificially generated process data to test the proposed models. hence, it is difficult to determine the actual effectiveness of these methods, the conditions under which they are necessary, and whether they lead to a significant increase in accuracy that warrants their increased runtime and complexity. in this paper, we study 5 different correlation models and their associated ssta methods using 35420 critical dimension (cd) measurements that were extracted from 23 reticles on 5 wafers in a 130nm cmos process. based on the measured cd data, we analyze the correlation as a function of distance and generate 5 distinct correlation models, ranging from simple models which incorporate one or two variation components to more complex models that utilize principle component analysis and quad-trees. we then study the accuracy of the different models and compare their ssta results with the result of running sta directly on the extracted data. we also examine the trade-off between model accuracy and run time, as well as the impact of die size on model accuracy. we show that, especially for small dies (< 6.6mm x 5.7mm), the simple models provide comparable accuracy to that of the more complex ones, while incurring significantly less runtime and implementation difficulty. the results of this study demonstrate that correlation models for ssta must be carefully tested on actual process data and must be used judiciously.
verification through the principle of least astonishment. assessing the correctness of a digital design is a challenging task hampered by extremely large circuit netlists, counterintuitive property descriptions and ill-defined specifications. in this paper we propose a new verification methodology, inspired by the principle of least astonishment. the underlying idea is to provide an automatic assessment of what constitutes "common behavior" for a system, and use this to detect any anomaly in the design. deviant behavior is presented to the verification engineer through intuitive, compact diagrams which lend themselves to quick inspection for correctness. to enable this methodology we introduce inferno, a new tool which can analyze the results of a logic simulation trace and automatically extract high-level diagrams representing the design's transaction activity across any user-defined interface. in addition, inferno can automatically generate a checker module corresponding to a given transaction, suitable for use in a wide range of verification methodologies. we envision the deployment of inferno in a closed-loop constraint-random simulation methodology where any new transaction detected on the interface is presented to the user for analysis and, once deemed legal, it is merged into an "approved transactions" checker, which flags the detection of any new type of transactions. we provide a series of examples and experimental results to show the effectiveness of inferno and some of its possible uses.
from micro to nano: mems as an interface to the nano world. leveraging conventional microsystems technology, mems has become the technology of choice for a wide range of applications including inertial sensors for automotive, games, and consumer applications, projection displays or inkjet print heads. in support of recent efforts to shrink dimensions to the nanoscale, mems has established itself as a perfect technology for interaction with the nanoworld. we will describe initial results using mems to manipulate single molecules for medical diagnostics. this technology has the potential to turn complex laboratory procedures into procedures that are as simple as taking the temperature.
an electrothermally-aware full-chip substrate temperature gradient evaluation methodology for leakage dominant technologies with implications for power estimation and hot-spot management. as cmos technology scales into the nanometer regime, power dissipation and associated thermal concerns in high-performance ics due to on-chip hot-spots and thermal gradients are beginning to impact vlsi design. moreover, elevated substrate (junction or die) temperature strongly influences ic performance, reliability, and packaging/cooling cost. hence, accurate estimation of substrate thermal profiles is critical. this paper presents an accurate chip-level electrothermally-aware methodology for spatial silicon substrate temperature estimation. the methodology self-consistently incorporates various electrothermal couplings arising mainly due to the strong dependence of subthreshold leakage on temperature and also employs an accurate package thermal model, to account for inhomogeneous layers and non-cubic structure, which are not considered in traditional methods. the proposed methodology becomes increasingly effective as technology scales due to increasing leakage. furthermore, it is shown that considering realistic package thermal models not only improves the accuracy of estimating temperature distribution but also has significant implications for power estimation and hot-spot management.
carbon nanotubes for potential electronic and optoelectronic applications. carbon nanotubes (cnts) are novel quasi-one-dimensional materials with excellent electrical properties in addition to their remarkable mechanical strength, thermal conductivity and chemical inertness. moreover, semiconducting cnts are directgap semiconductors that directly absorb and emit light. this offers the possibility of developing a cnt-based electric and optoelectronic technology. [1]
prospects for emerging nanoelectronics in mainstream information processing systems. the international technology roadmap for semiconduc-tors (itrs) seeks to stimulate invention and research lead-ing to one or more new nanoelectronics technologies that may extend functional scaling of information processing substantially beyond "ultimately scaled" cmos. introduction of such new technologies is envisioned in two phases - first by extending the cmos platform via heterogeneous integration of new technologies and, later, via a replace-ment for cmos that would provide the equivalent of sev-eral more technology nodes beyond ultimate cmos. 1d charge state materials (nanotubes and nanowires) appear to be particularly attractive for the first phase. ferromagnetic or spin-based logic devices are under investigation for the second phase. some recent work in both of these areas will be presented.
technology migration techniques for simplified layouts with restrictive design rules. designs using simple geometric layout objects (such as points, sticks and rectangles) with restrictive design rules (rdrs) on each layout object (i.e., it must be placed on a set of grids subject to a set of ground rules) have been introduced as an approach to better enable design for manufacturability (dfm) in ultra-deep submicron designs[9]. in this paper, we study the problem of migrating the conventional shape-based layouts to the simplified layouts with rdr constraints. we present a migration flow which consists of two process steps: (1) conversion where shapes (such as polygons) are converted to simple geometric objects (such as sticks) while the topology is maintained, and (2) grid legalization for rdrs where the simple geometric objects are placed on grid subject to the given set of ground rules by using a novel legalization algorithm, the minimum perturbation-driven graph-based grid legalization(mp-ggl) algorithm. we demonstrate the effectiveness of the flow by successfully migrating a set of library cells in the conventional shape-based technology to the simplified layouts with rdr constraints.
decoupling capacitor planning and sizing for noise and leakage reduction. decoupling capacitor (decap) is a popular means to reduce power supply noise in integrated circuits. since the decaps are usually inserted in the whitespace of the device layer, decap management during the floorplanning stage is desirable. in this paper, we devise the effective decap distance model to analyze how functional blocks are affected by non-neighboring decaps. in addition, we propose a generalized network flow-based algorithm to allocate the whitespace to the blocks and determine the oxide thicknesses for the decaps to be implemented in the whitespace. experimental results show that our decap allocation and sizing methods can significantly reduce decap budget and leakage power with a small increase in area and wirelength when integrated into 2d and 3d floorplanners.
adaptive multi-domain thermal modeling and analysis for integrated circuit synthesis and design. chip-package thermal analysis is necessary for the design and synthesis of reliable, high-performance, low-power, compact integrated circuits (ics). many methods of ic thermal analysis suffer performance or accuracy problems that prevent use in ic synthesis and hinder use in architectural design. this article describes isac, a novel, fast, accurate thermal analysis system for use in ic synthesis and design. we present new, cooperative, temporal and spatial adaptation methods to dramatically accelerate accurate analysis. the proposed system unifies steady-state, time-domain, and frequency-domain analysis techniques. it is composed of our spatially-adaptive multigrid iterative solver, a new temporally and spatially adaptive asynchronous time marching solver, and a new spatially-adaptive frequency-domain moment matching solver. together, these cooperative adaptation and multi-domain analysis techniques allow the proposed system to efficiently solve the static, short time scale, and long time scale variants of the ic thermal analysis problem. experimental results demonstrate significant performance improvement over existing thermal analysis solutions. our spatial adaptation techniques bring a 21.6x -690.0x speedup over recently-published steady-state thermal analysis techniques. our unified spatial and temporal adaptation techniques, within our asynchronous time marching method, bring a 1,071x -1,890x speedup over other widely-used, time-domain thermal analysis techniques with less than 0.5% error. our spatial adaptation techniques enable the efficient use of our frequency-domain thermal analysis technique, which brings a 10x -100x speedup over the fastest-known time-domain technique, when used for long time scale thermal analysis. the thermal analysis system described in this article has been implemented as a c/c++ library that has been publicly released for free academic and personal use.
physical aware frequency selection for dynamic thermal management in multi-core systems. in order to maintain performance per watt in microprocessors, there is a shift towards the chip level multiprocessing paradigm. microprocessor manufacturers are experimenting with tens of cores, forecasting the arrival of hundreds of cores per single processor die in the near future. with such large-scale integration and increasing power densities, thermal management continues to be a significant design effort to maintain performance and reliability in modern process technologies. in this paper, we present two mechanisms to perform frequency scaling as part of dynamic frequency and voltage scaling (dvfs) to assist dynamic thermal management (dtm). our frequency selection algorithms incorporate the physical interaction of the cores on a large-scale system onto the emergency intervention mechanisms for temperature reduction of the hotspot, while aiming to minimize the performance impact of frequency scaling on the core that is in thermal emergency. our results show that our algorithm consistently succeeds in maximizing the operating frequency of the most critical core while successfully relieving the thermal emergency of the core. a comparison of our two alternative techniques reveals that our physical aware criticality-based algorithm results in 11.7% faster clock frequencies compared to our aggressive scaling algorithm. we also show that our technique is extremely fast and is suited for real time thermal management
a new rlc buffer insertion algorithm. most existing buffering algorithms neglect the impact of inductance on circuit performance, which causes large error in circuit analysis and optimization. even for the approaches considering inductance effects, their delay models are too simplistic to catch the actual performance. as delay-length dependence is approaching linear with inductance effect [1], fewer buffers are needed to reduce rlc delay. this motivates this work to propose a new algorithm for rlc buffer insertion. in this paper, a new buffer insertion algorithm considering inductance for intermediate and global interconnect is proposed, based on downstream impedance instead of traditional downstream capacitance. a new pruning technique that provides tremendous speedup and a new frequency estimation method that is very accurate in delay computation are also proposed. experiments on industrial netlists demonstrate that our new algorithm reduces the number of buffers up to 34.4% over the traditional van ginneken's algorithm that ignores inductance. our impedance delay estimation is very accurate compared to spice simulations, with only 10% error while the delay model used in the previous rlc algorithm has 20% error [2]. the accurate delay model not only reduces the number of buffers, but also brings high fidelity to the buffer solutions. incorporating slew constraints, the algorithm is accelerated by about 4x with only slight degradation in solution quality.
clock buffer polarity assignment for power noise reduction. power/ground noise is a major source of vlsi circuit timing variations. this work aims to reduce clock network induced power noise by assigning different signal polarities (opposite switchings) to clock buffers in an existing buffered clock tree. three assignment algorithms are proposed: (1) partitioning, (2) 2-coloring on minimum spanning tree and (3) recursive min-matching. a post-processing of clock buffer sizing is performed to achieve desired clock skew. spice based experimental results indicate that our techniques could reduce the average peak current and average delay variations by 44% and 54% respectively.
carbon nanotube transistor circuits: models and tools for design and performance optimization. in this paper, we describe the development of device models and tools for the design of new transistors such as the carbon nanotube transistor. an hspice model for enhancement mode nanotube transistor has been developed. it can be used for design of nanotube transistor circuits as well as to study performance benefits of the new transistor. a model of the carbon nanotube transistor with schottky barrier is presented. the model enables device design and performance optimization.
fast and robust quadratic placement combined with an exact linear net model. this paper presents a robust quadratic placement approach, which offers both high-quality placements and excellent computational efficiency. the additional force which distributes the modules on the chip in force-directed quadratic placement is separated into two forces: hold force and move force. both of these forces are determined without any heuristics. based on this novel systematic force implementation, we show that our iterative placement algorithm converges to an overlapfree placement. in addition, engineering change order (eco) is efficiently supported by our placer. to handle the important trade-off between cpu time and placement quality, a deterministic quality control is presented. in addition, a new linear net model is proposed, which accurately models the half-perimeter wirelength (hpwl) in the quadratic cost function of quadratic placement. hpwl in general is a linear metric for netlength and represents an efficient and common estimation for routed wirelength. compared with the classical clique net model, our linear net model reduces memory usage by 75%, cpu time by 23% and netlength by 8%, which is measured by the hpwl of all nets. using the ispd-2005 benchmark suite for comparison, our placer combined with the new linear net model has just 5.9% higher netlength but is 16x faster than aplace, which offers the best netlength in this benchmark. compared to capo, our placer has 9.2% lower netlength and is 5.4x faster. in the recent ispd-2006 placement contest, in which quality is mainly determined by netlength and cpu time, our placer together with the new net model produced excellent results.
network coding for routability improvement in vlsi. with the standard approach for establishing multicast connections over a network, network nodes are utilized to forward and duplicate the packets received over the incoming links. recently, there has been a significant interest in a novel paradigm of network coding. network coding generalizes the traditional routing approach by allowing the network nodes to generate new packets by performing algebraic operations on packets received over the incoming links. it has been shown that network coding can increase the throughput of multicast communication. in this paper, we explore the benefits of network coding for improving the routing characteristics of vlsi designs. we demonstrate that when data has to be routed across the ic, it is often beneficial to perform network coding. initial results demonstrate that network coding can result in a healthy reduction in wire length, wire area, interconnect power as well as the active area associated with the interconnects. this comes at a small delay penalty.
formal model of data reuse analysis for hierarchical memory organizations. in real-time data-dominated communication and multimedia processing applications, due to the manipulation of large sets of data, a multi-layer memory hierarchy is used to enhance the system performance and also to reduce the energy consumption. savings of dynamic energy can be obtained by accessing frequently used data from smaller memories rather than from large background memories. the optimization of the hierarchical memory architecture implies the addition of layers of smaller memories to which heavily used data can be copied. this paper presents a formal model for data reuse analysis which identifies those parts of arrays more intensely accessed, taking also into account the relative lifetimes of the signals. tested on a two-layer memory hierarchy, this model led to savings in the dynamic energy from 40% to over 70% relative to the energy used in the case of a flat memory design.
stepping forward with interpolants in unbounded model checking. this paper addresses sat-based unbounded model checking based on craig interpolants. this recently introduced methodology is often able to outperform bdds and other sat-based techniques on large verification instances. based on refutation proofs generated by sat solvers, interpolants provide compact circuit representations of state sets, and abstract away several details non relevant for proofs. we propose three main contributions, aimed at controlling interpolant size and traversal depth. first of all, we introduce interpolant-based dynamic abstraction to reduce the support of the computed interpolant. second, we propose new advances in interpolant compaction by redundancy removal. both techniques rely on an effective application of the incremental sat paradigm. finally, we also introduce interpolant computation exploiting circuit quantification, instead of sat refutation proofs. experimental results are specifically oriented to prove properties, rather than disproving them (bug hunting). they show how the methodology is able to extend the applicability of interpolant based model checking to larger and deeper verification instances.
a revisit to floorplan optimization by lagrangian relaxation. with the advent of deep sub-micron (dsm) era, floorplanning has become increasingly important in physical design process. in this paper we clarify a misunderstanding in using lagrangian relaxation for the minimum area floorplanning problem. we show that the problem is not convex and its optimal solution cannot be obtained by solving its lagrangian dual problem. we then propose a modified convex formulation and solve it using min-cost flow technique and trust region method. experimental results under module aspect ratio bound [0.5, 2.0] show that the running time of our floorplanner scales well with the problem size in mcnc benchmark. compared with the floorplanner in [27], our flooplanner is 9.5x faster for the largest case "ami49". it also generates a floorplan with smaller deadspace for almost all test cases. in addition, since the generated floorplan has an aspect ratio closer to 1, it is more friendly to packaging. our floorplanner is also amicable to including interconnect cost and other physical design metrics.
microarchitecture parameter selection to optimize system performance under process variation. design variability due to within-die and die-to-die process variations has the potential to significantly reduce the maximum operating frequency and the effective yield of high-performance microprocessors in future process technology generations. this variability manifests itself by increasing the number and criticality of long delay paths. to quantify this impact, we use an architectural process variation model that is appropriate for the analysis of system performance in the earlystages of the design process. we propose a method of selecting microarchitectural parameters to mitigate the frequency impact due to process variability for distinct structures, while minimizing ipc (instructions-per-cycle) loss. we propose an optimization procedure to be used for system-level design decisions, and we find that joint architecture and statistical timing analysis can be more advantageous than pure circuit level optimization. overall, the technique can improve the 90% yield frequency by about 14% with 3% ipc loss for a baseline machine with a 20fo4 logic depth per pipestage. this approach is sensitive to the selection of processor pipeline depth, and we demonstrate that machines with aggressive pipelines will experience greater challenges in coping with process variability.
cache miss clustering for banked memory systems. one of the previously-proposed techniques for reducing memory energy consumption is memory banking. the idea is to divide the memory space into multiple banks and place currently unused (idle) banks into a low-power operating mode. the prior studies -- both hardware and software domain - in memory energy optimization via low-power modes do not take the data cache behavior explicitly into account. as a consequence, the energy savings achieved by these techniques can be unpredictable due to dynamic cache behavior at runtime. the main contribution of this paper is a compiler optimization, called the bank-aware cache miss clustering, that increases idle durations of memory banks, and as a result, enables better exploitation of available low-power capabilities supported by the memory system. this is because clustering cache misses helps to cluster cache hits as well, and this in turn increases bank idleness. we implemented our cache miss clustering approach within a compilation framework and tested it using seven array-intensive application codes. our experiments show that cache miss clustering saves significant memory energy as a result of increased idle periods of memory banks.
a spectrally accurate integral equation solver for molecular surface electrostatics. electrostatic analysis of complicated molecular surfaces arises in a number of nanotechnology applications including: biomolecule design, carbon nanotube simulation, and molecular electron transport. molecular surfaces are typically smooth, without the corners common in electrical interconnect problems, and are candidates for methods with higher order convergence than that of the commonly used flat panel methods. in this paper we describe and demonstrate a spectrally accurate approach for analyzing molecular surfaces described by a collection of surface points. the method is a synthesis of several techniques, and starts by using least squares to fit a high order spherical harmonic surface representation to the given points. then this analytic representation is used to construct a differentiable map from the molecular suface to a cube, an orthogonal basis is generated on the rectangular cube surfaces, and a change of variables is used to desingularize the required integrals of products of basis functions and green's function. finally, an efficient method for solving the discretized system using a matrix-implicit scheme is described. the combined method is demonstrated on an analytically solvable sphere problem, capacitance calculation of complicated molecular surface, and a coupled poisson/poisson-boltzmann problem associated with a biomolecule. the results demonstrate that for a tolerance of 10-3 this new approach requires one to two orders of magnitude fewer unknowns than a flat panel method.
optimal useful clock skew scheduling in the presence of variations using robust ilp formulations. this paper exploits useful skew to improve system performance and robustness. we formulate a robust integer linear programming problem considering the interactions between data and clock paths on a microprocessor chip to improve clock frequency. the timing slack is optimized for each path to determine a clock schedule. the percentage of timing violations, obtained from a 1000 point monte carlo simulation, is higlighted as yield predictions and conveys the robustness of the clock schedule. the results show performance improvement of up to 9.747% with 20% yield and up to 6.682% with 100% yield. the novelty of the proposed method is its ability to tradeoff between performance improvement in frequency and robustness, via a single variable in the formulation.
parameterized model order reduction via a two-directional arnoldi process. this paper presents a multiparameter moment-matching based model order reduction technique for parameterized interconnect networks via a novel two-directional arnoldi process. it is referred to as a pimtap algorithm, which stands for parameterized interconnect macromodeling algorithm via a two-directional arnoldi process. pimtap inherits the advantages of previous multiparameter moment-matching algorithms and avoids their shortfalls. it is numerically stable and adaptive, and preserves the passivity of parameterized rlc networks.
optimal bus sequencing for escape routing in dense pcbs. the pcb routing problem has become so difficult that no commercial cad software can provide an automatic solution for high-end boards. existing algorithms for escape routing, an important step in pcb routing, are net-centric. directly applying these algorithms will result in mixing nets of different buses together. but in practice, it is preferred to bundle together nets in a bus. thus the bus-centric escape routing problem can be naturally divided into two subproblems: (1) finding a subset of buses that can be routed on the same layer without net mixings and crossings, which we refer to as the bus sequencing problem, and (2) finding the escape routing solutions for each chosen bus, which can be solved by a net-centric escape router. in this paper, we solve the bus sequencing problem. we introduce a new optimization problem called the longest common interval sequence (lcis) problem and model the bus sequencing problem as an lcis problem. by using dynamic programming and balanced search tree data structure, we present an lcis algorithm which can find an optimal solution in o(n log n) time. we also show that o(n log n) is a lower-bound for this problem and thus the time complexity of our algorithm is also the best possible.
a selective pattern-compression scheme for power and test-data reduction. this paper proposes a selective pattern-compression scheme to minimize both test power and test data volume during scan-based testing. the proposed scheme will selectively supply the test patterns either through the compressed scan chain whose scanned values will be decoded to the original scan cells, or directly through the original scan chain using minimum transition filling method. due to shorter length of a compressed scan chain, the potential switching activities and the required storage bits can be both reduced. furthermore, the proposed scheme also supports multiple scan chains. the experimental results demonstrate that, with few hardware overhead, the proposed scheme can achieve significant improvement in shift-in power reduction and large amount of test data volume reduction.
can nano-photonic silicon circuits become an intra-chip interconnect technology? surprisingly, nano-photonic silicon has already emerged as a commercial inter-chip optical communications technology. this was made possible by silicon-on-insulator (soi), technology, which integrates many of the optical communications components directly in silicon cmos chips. intel and luxtera have both announced > 10gb/sec optical modulators, integrated into silicon. all the other customarily required opto-electronic components; detectors, waveguides, splitters, couplers, filters, etc., are fully executed in cmos designs, as well. continuous wave optical power is provided from off-chip, just as dc power is currently provided from off-chip. the initial commercial applications are optical 10gb/s ethernet, infiniband, and other inter-chip, communications applications. the question to be addressed in this talk, is whether silicon nano-photonics can now make the final jump, to intra-chip optical interconnects?
engineering change using spare cells with constant insertion. in the vlsi design process, a design implementation often needs to be corrected because of new specifications or design constraint violations. this correction process is referred to as engineering change (ec). usually, an ec problem is resolved by using spare cells, which have been inserted into the unused spaces of a chip. in this paper, we propose an iterative method to generate feasible mapping solutions for an ec problem considering spare cells whose inputs may be tied to vdd or gnd, called constant insertion. applying constant insertion can increase a cell's flexibility in aspect of functionalities, so far-away spare cells need not be used just for some specific functionality. our experimental results show that the area in which there are enough spare cells for a mapping solution with constant insertion is only 82% of the area without constant insertion.
module assignment for pin-limited designs under the stacked-vdd paradigm. this paper addresses the module assignment problem in pin-limited designs under the stacked-vdd circuit paradigm. a partition-based algorithm is presented for efficiently assigning modules at the floorplanning level so as to reuse currents between the vdd domains, and minimize the power wasted during the operation of the circuit. experimental results on a dlx architecture show that compared with assigning modules to different vdd rails using a bin-packing technique, the circuit generated by our algorithm has 32% lower wasted power, on average. in addition, experiments on a 3d ic example show that our module assignment approach is equally effective in reducing the power waste in 3d ics.
sizing and placement of charge recycling transistors in mtcmos circuits. a downside of using multi-threshold cmos (mtcmos) technique for leakage reduction is the energy consumption during transitions between sleep and active modes. previously, a charge recycling (cr) mtcmos architecture was proposed to reduce the large amount of energy consumption that occurs during the mode transitions in power-gated circuits. considering the rc parasitics of the virtual ground and vdd lines, proper sizing and placement of charge-recycling transistors is key to achieving the maximum power saving. in this paper, we show that the sizing and placement problems of charge-recycling transistors in cr-mtcmos can be formulated as a linear programming problem, and hence, can be efficiently solved using standard mathematical programming packages. the proposed sizing and placement techniques allow us to employ the cr-mtcmos solution in large row-based standard cell layouts while achieving nearly the full potential of this power-gating architecture, i.e., we achieve 44% saving in switching energy due to the mode transition in cr-mtcmos compared to standard mtcmos.
probabilistic decision diagrams for exact probabilistic analysis. a decision diagram based framework is proposed for representing the probabilistic behavior of circuits with faulty gates. we introduce probabilistic decision diagrams (pdd) as an exact computational tool which along with vast expressive power holds many other useful properties such as space efficiency (on average) and efficient manipulation algorithms (polynomial in size.) an algorithm for constructing the pdd for a circuit is proposed. useful information about probabilistic behavior of the circuit (such as output error probability for arbitrary input probability distribution) can be directly extracted from the pdd representation. experimental results demonstrate the effectiveness and applicability of the proposed approach.
remote activation of ics for piracy prevention and digital right management. we introduce a remote activation scheme that aims to protect integrated circuits (ic) intellectual property (ip) against piracy. remote activation enables designers to lock each working ic and to then remotely enable it. the new method exploits inherent unclonable variability in modern manufacturing for unique identification (id) and integrated the ids into the circuit functionality. the objectives are realized by replication of a few states of the finite state machine (fsm) and adding control to the state transitions. on each chip, the added control signals are a function of the unique ids and are thus unclonable. on standard benchmark circuits, the experimental results show that the novel activation method is stable, unclonable, attack-resilient, while having a low overhead and a unique key for each ic.
combining static and dynamic defect-tolerance techniques for nanoscale memory systems. nanoscale technology promises dramatically increased device density, but also decreased reliability. with bit error rates projected to be as high as 10%, designing a usable nanoscale memory system poses a significant challenge. in particular, we need to bootstrap a sea of unreliable bits into contiguous address ranges which are preferably as large as 4k-byte virtual memory pages. we accomplish this bootstrapping through a combination of dynamic error correction codes within 32-bit blocks and a static defect map which tracks usability of these blocks. the key insight is that statically-determined defect locations can be much more powerful than dynamically correcting for unknown locations, but that defect maps are only practical at a coarse granularity. using a combination of bch error correction codes and a bloom-filter-based defect map, we achieve a memory efficiency of 60% and 13% for 4k-byte pages at 1% and 10% bit-error rates, respectively.
timing constraint-driven technology mapping for fpgas considering false paths and multi-clock domains. modern fpga chips contain multiple dedicated clocking networks, because nearly all real designs contain multiple clock domains. in this paper, we present an fpga technology mapping algorithm targeting designs with multi-clock domains such as those containing multi-clocks, multi-cycle paths, and false paths. we use timing constraints to handle these unique clocking issues. we work on timing constraint graphs and process multiple arrival/required times for each node in the gate-level netlist. we also recognize and process constraint conflicts efficiently. our algorithm produces a mapped circuit with the optimal mapping depth under timing constraints. to the best of our knowledge, this is the first fpga mapping algorithm working with multi-clock domains. experiments show that our algorithm is able to improve circuit performance by 16.8% on average after placement and routing for a set of benchmarks with multi-cycle paths, comparing to a previously published depth-optimal algorithm that does not consider multi-cycle paths.
counterflow pipelining: architectural support for preemption in asynchronous systems using anti-tokens. this paper introduces a novel approach to efficiently implement several useful architectural features in asynchronous application-specific ics (asics). these features include speculation, preemption, and eager evaluation, which have so far only been available on cpus, and have not been adequately investigated for custom asics. for the efficient implementation of the new architectural features, a radically new approach inspired by sproull's counterflow pipelines [7] is proposed. the key idea is to allow special commands, called anti-tokens, to be propagated in a direction opposite to that of data, allowing certain computations to be killed before they are completed, if their results are no longer required. the net impact is a significant improvement in the throughput of a certain class of systems---e.g., those involving conditional computation---where a bottleneck pipeline stage can often be preempted if its result is determined to be no longer needed. experimental results indicate that our approach can improve the system throughput by a factor of up to 2.2x, along with an energy savings of up to 27%.
optimal polynomial-time interprocedural register allocation for high-level synthesis and asip design. register allocation, in high-level synthesis and asip design, is the process of determining the number of registers to include in the resulting circuit or processor. the goal is to allocate the minimum number of registers such that no scalar variable is spilled to memory. previously, an optimal polynomial-time algorithm for this problem has been presented for individual procedures represented in static single assignment (ssa) form. this result is now extended to complete programs (or sub-programs), as long as: (1) each procedure is represented in ssa form; and (2) at every procedure call, all live variables are split at the call point. with this representation, it is possible to ensure that the interprocedural interference graph (iig) is chordal, and can therefore be colored optimally in polynomial time. an optimal coloring of the iig can be achieved by allocating registers for each procedure individually. previous work has shown that optimal register allocation in ssa form does not require an interference graph. optimal interprocedural register allocation, therefore, is achieved without constructing an interference graph, giving the optimal algorithm a significant runtime advantage over prior sub-optimal heuristics.
from molecular interactions to gates: a systematic approach. the continuous minituarization of integrated circuits may reach atomic scales in a couple of decades. some researchers have already built simple computation engines by manipulating individual atoms on metal surfaces. this paper presents a systematic approach to automate the design of logic gates using molecule cascades. temporal logic is used to characterize molecular interactions and specify the behavior of logic gates. model-checking techniques are used for the exploration of structures behaviorally equivalent to the logic gates. as an example, a complete library of combinational logic gates has been designed using a particular molecular system. this new approach provides a methodology to bridge the gap between physical chemists and computer scientists in seeking computational structures at atomic scales.
mosfet modeling for 45nm and beyond. compact mosfet models are a critical link between technology and design. the inexorable reduction in supply voltage and geometry to 45nm and below adds or emphasizes physical effects not important in the past, and so continues to expand the requirements for mosfet models. at and below 45nm, process variations, reliability, proximity effects, high-k gate materials, and non-classical device structures all challenge modeling. this tutorial presents fundamentals and evolution of compact mosfet models, and techniques to address the new challenges.
allocation cost minimization for periodic hard real-time tasks in energy-constrained dvs systems. energy-efficiency and power-awareness for electronic systems have been important design issues in hardware and software implementations. we consider the scheduling of periodic hard real-time tasks along with the allocation of processors under a given energy constraint. each processor type could be associated with its allocation cost. the objective of this work is to minimize the entire allocation cost of processors so that the timing and energy constraints are both satisfied. we develop approximation algorithms for processor types with continuous processor speeds or discrete processor speeds. the capability of the proposed algorithms was evaluated by a series of experiments, and it was shown that the proposed algorithms always derived solutions with system costs close to those of optimal solutions in the experiments.
automating post-silicon debugging and repair. modern ic designs have reached unparalleled levels of complexity, resulting in more and more bugs discovered after design tape-out however, so far only very few eda tools for post-silicon debugging have been reported in the literature. in this work we develop a methodology and new algorithms to automate this debugging process. key innovations in our technique include support for the physical constraints specific to post-silicon debugging and the ability to repair functional errors through subtle modifications of an existing layout. in addition, our proposed post-silicon debugging methodology (fogclear) can repair some electrical errors while preserving functional correctness. thus, by automating this traditionally manual debugging process, our contributions promise to reduce engineers' debugging effort. as our empirical results show, we can automatically repair more than 70% of our benchmark designs.
a new statistical max operation for propagating skewness in statistical timing analysis. statistical static timing analysis (ssta) is emerging as a solution for predicting the timing characteristics of digital circuits under process variability. for computing the statistical max of two arrival time probability distributions, existing analytical ssta approaches use the results given by clark in [8]. these analytical results are exact when the two operand arrival time distributions have jointly gaussian distributions. due to the nonlinear max operation, arrival time distributions are typically skewed. furthermore, nonlinear dependence of gate delays and non-gaussian process parameters also make the arrival time distributions asymmetric. therefore, for computing the max accurately, a new approach is required that accounts for the inherent skewness in arrival time distributions. in this work, we present analytical solution for computing the statistical max operation.1 first, the skewness in arrival time distribution is modeled by matching its first three moments to a so-called skewed normal distribution. then by extending clark's work to handle skewed normal distributions we derive analytical expressions for computing the moments of the max. we then show using initial simulations results that using a skewness based max operation has a significant potential to improve the accuracy of the statistical max operation in ssta while retaining its computational efficiency.
a hybrid scheme for compacting test responses with unknown values. this paper presents a hybrid compaction scheme for test responses containing unknown values, which consists of a space compactor and an unknown-blocking multiple input signature registers (misr). the proposed scheme guarantees no coverage loss for the modeled faults. the proposed hybrid scheme can also be tuned to observe any user-specified percentage of responses for controlling the coverage loss for un-modeled faults. the experimental results demonstrate that, in comparison with a space compactor or an unknown-blocking misr alone, the hybrid compaction scheme achieves a lower coverage loss without demanding more test-data volume. in addition, we propose a quantitative approach to estimate the required percentage of observable responses for the proposed scheme, directly based on a test-quality metric of un-modeled faults.
organic electronic device modeling at the nanoscale. electronic devices with nanoscale features (~ 100 nm or smaller) are becoming increasingly important in electronics technology. while nanoscale electronic devices comprise a variety of different material sets and structures, many of the nanoscale devices developed in the last decade employ organic materials. in this talk, we discuss the modeling of organic electronic thin film devices. in our approach, analysis of such devices begins on the molecular scale, and device level behavior is then derived from the combination of individual molecular properties and physical models of intermolecular interactions. we present a general purpose monte carlo simulator based on molecular-scale physical models and employ this simulator to analyze device behavior.
a design flow dedicated to multi-mode architectures for dsp applications. this paper addresses the design of multi-mode architectures for digital signal processing applications. we present a dedicated design flow and its associated high-level synthesis tool, named gaut. given a unified description of a set of time-wise mutually exclusive tasks and their associated throughput constraints, a single rtl hardware architecture optimized in area is generated. in order to reduce the register, steering logic (multiplexers) and controller (decoding logic) complexities, we propose a joint-scheduling algorithm which maximizes the similarities between control steps and specific binding approaches for both functional units and storage elements which maximize the similarities between the datapaths. we show through a set of test cases that our approach offers significant area saving relative to the state-of-the-art.
ppv-hb: harmonic balance for oscillator/pll phase macromodels. a unique feature of oscillators is that small but sustained external perturbations lead to unboundedly large changes in phase, thereby making standard harmonic balance (hb) inapplicable to realistic oscillator phase macromodels. in this paper, we rectify this situation by presenting a novel extension of hb that is capable of handling oscillator phase macromodels. key to the new method, termed ppv-hb, is a formulation that separates unboundedly increasing phase terms from the bounded, periodic components. ppv-hb can be used not only on individual oscillators, but it also enables the application of hb-like techniques for simulating system-level equation systems composed of higher-level macromodels of blocks. we validate ppv-hb on individual oscillators and a pll system, demonstrating excellent matches with transient simulation using phase macromodels. speedups of 1-2 orders of magnitude are obtained, over and above additional speedups of another 2-3 orders of magnitude that stem from using macromodels (as opposed to full circuit simulation).
novel wire density driven full-chip routing for cmp variation control. as nanometer technology advances, the post-cmp dielectric thickness variation control becomes crucial for manufacturing closure. to improve cmp quality, dummy feature filling is typically performed by foundries after the routing stage. however, filling dummy features may greatly degrade the interconnect performance and lead to explosion of mask data. it is thus desirable to consider wire-density uniformity during routing to minimize the side effects from aggressive post-layout dummy filling. in this paper, we present a new full-chip grid-based routing system considering wire density for reticle planarization enhancement. to fully consider wire distribution, the router applies a novel two-pass, top-down planarity-driven routing framework, which employs a new density critical area analysis based on voronoi diagrams and incorporates an intermediate stage of density-driven layer/track assignment based on incremental delaunay triangulation. experimental results show that our methods can achieve more balanced wire distribution than state-of-the-art works.
fastroute: a step to integrate global routing into placement. because of the increasing dominance of interconnect issues in advanced ic technology, placement has become a critical step in the ic design flow. to get accurate interconnect information during the placement process, it is desirable to incorporate global routing into it. however, previous global routers are computationally expensive. it is impractical to perform global routing repeatedly during placement. in this paper, we present an extremely fast and high-quality global router called fastroute. in traditional global routing approaches, congestion is not considered during steiner tree construction. so they have to rely on the time-consuming maze routing technique to eliminate routing congestion. different from traditional approaches, we proposed a congestion-driven steiner tree topology generation technique and an edge shifting technique to determine the good steiner tree topologies and steiner node positions. based on the congestion-driven steiner trees, we only need to apply maze routing to a small percentage of the two-pin nets once to obtain high quality global routing solutions. we also proposed a new cost function based on logistic function to direct the maze routing. experimental results show that fastroute generates less congested solutions in 132x and 64x faster runtimes than the state-of-the-art academic global routers labyrinth [1] and chi dispersion router [2], respectively. it is even faster than the highly-efficient congestion estimator fadglor [3]. the promising results make it possible to incorporate global routing directly into placement process without much runtime penalty. this could dramatically improve the placement solution quality. we believe this work will fundamentally change the way the eda community look at and make use of global routing in the whole design flow.
eco timing optimization using spare cells. we introduce in this paper a new problem of eco timing optimization using spare-cell rewiring and present the first work for this problem. spare-cell rewiring is a popular technique for incremental timing optimization and/or functional change after the placement stage. the spare-cell rewiring problem is very challenging because of its dynamic wiring cost nature for selecting a spare cell, while the existing related problems consider only static wiring cost. for the addressed problem, we present a framework of buffer insertion and gate sizing to handle it. in this framework, we present a dynamic programming algorithm considering the dynamic cost, called dynamic cost programming (dcp), for the eco timing optimization with spare cells. without loss of solution optimality, we further present an effective pruning method by selecting spare cells only inside an essential bounding polygon to reduce the solution space. the whole framework is integrated into a commercial design flow. experimental results based on five industry benchmarks show that our method is very effective and efficient in fixing the timing violations of eco paths.
algorithms for mis vector generation and pruning. ignoring the effect of simultaneous switching for logic gates causes silicon failures for high performance microprocessor designs. the main reason to omit this effect is the run time penalty and potential over-conservatism. run times are directly proportional to the vector sizes. efficient algorithms are presented that prune the multiple input switching (mis) vector set to a worst-case covering using a boolean logic abstraction of the gate. this non-physical representation reduces the vector size to approximately n vectors for an n-input gate. this is effectively the same vector set size as the optimal single input switching vector set. there are no errors for 88% the simulations using a monty-carlo coverage on a 90nm static library, and the magnitude of the errors are less than 5% on average.
skew aware polarity assignment in clock tree. in modern sequential vlsi designs, clock tree plays an important role in synchronizing different components in a chip. to reduce peak current and power/ground noises caused by clock network, assigning different signal polarities to clock buffers is proposed in previous work. althogh peak current and power/ground noises are minimized by signal polarities assignment, an assignment without timing information may increase the clock skew significantly. as a result, a timing-aware signal polarities assigning technique is necessary. in this paper, we propose a novel signal polarities assigning technique which can not only reduce peak current and power/ground noises simultaneously but also render the clock skew in control. the experimental result shows that the clock skew produced by our algorithm is 94% of original clock skew in average while the clock skew produced by three algorithms (partition, mst, matching) [5] are 235%, 272%, and 283%, respectively. moreover, our algorithm is as efficient as the three algorithms of [5] in reducing peak current and power/ground noises.
high-level synthesis challenges and solutions for a dynamically reconfigurable processor. a dynamically reconfigurable processor (drp) is designed to achieve high area efficiency by switching reconfigurable data paths dynamically. our drp architecture has a stand alone finite state machine and that switches "contexts" consisting of many operational and storage units in processing elements (pes) and wires between them. utilizing the resources not only in two spatial dimensions but also vertically (time-multiplexed) under accurate timing and area constraints imposes challenges for a high-level synthesizer for the drp. we describe a c-based behavioral synthesis method which features data path generation with clock speed optimization. this is achieved by including the overhead of selectors in the scheduling algorithm, and considering a wire delay at each pe level. a new technique is introduced to achieve high area efficiency. it works by effectively allocating multiple steps into the context. from the original highlevel synthesizer for application-specific integrated circuits, some of the basic rules such as operator and register sharing were completely changed due to the coarse grained and multi-context architecture. experimental results show that the generated data paths are highly parallelized and well balanced between contexts. the delay controllability enables the highest throughput point to be found more easily.
an efficient wake-up schedule during power mode transition considering spurious glitches phenomenon. during the power mode transition, a large surge current may lead to the malfunctions in a power-gating design. in this paper, we introduce several important properties of the surge current during the power mode transition for the distributed sleep transistor network (dstn) designs. based on these properties, we propose an accurate estimation of surge current and provide an efficient schedule on the dstn structure. our experiment achieved significantly better results than previous works---on average, 332 times wake-up time reduction and 35.48% less energy loss during the power mode transition.
decomposing image computation for symbolic reachability analysis using control flow information. the main challenge in bdd-based symbolic reachability analysis is represented by the sizes of the intermediate decision diagrams obtained during image computations. methods proposed to mitigate this problem fall broadly into two categories: search strategies that depart from breadth-first search, and efficient techniques for image computation. in this paper we present an algorithm that belongs to the latter category. it exploits define-use information along executable paths extracted from the control-flow graph of the model being analyzed; this information enables an effective constraining of the transition relation and a decomposition of the image computation process that often leads to much smaller intermediate bdds. our experiments confirm that this reduction in the size of the representation of state sets translates in significant decreases in cpu and memory requirements.
temperature aware microprocessor floorplanning considering application dependent power load. this paper studies microprocessor floorplanning considering thermal and throughput optimization. we first develop a stochastic heat diffusion model taking into account the application dependent power load for thermal analysis. then, we design the floorplanning algorithm based on this model. experimental results show that, compared with the deterministic heat diffusion model, our model obtains up to 3.2&deg;c reduction of the on-chip peak temperature, 1.25% reduction of the area, and 1.125x better cpi (cycles per instruction) performance, respectively. compared with temperature aware floorplanning in the hotspot tool set that ignores interconnect pipelining, our algorithm is up to 27x faster, reduces the peak temperature by up to 3&deg;c, and also reduces cpi significantly with a negligible area overhead.
increasing data-bandwidth to instruction-set extensions through register clustering. the conflicting requirements of performance and flexibility in today's embedded system market are forcing system designers to use more and more of the so called configurable or customizable processor cores. such processors tend to meet the demanding performance constraints by accommodating application specific instruction-set extensions (ises) which have, naturally, become a vital component of current processor customization flows. one major bottleneck in maximizing ise performance is the limitation on the data-bandwidth between the general purpose register(gpr) file and the ises. for improved performance, it is desirable to have a large data-bandwidth from the gprs to ises. however, the tight area constraints of modern embedded processors often restrict the gpr i/o of ises to save port area of the register files. this paper presents a novel approach to increase the gpr i/o of ises without significantly increasing the size of the gpr files. this is achieved by applying the concept of register clustering, common in many vliw architectures, to single-issue processors with high performance ises. such clustering often causes extra register moves in compiled code. this work also presents an algorithm to minimize such register moves. the benchmark results presented in this paper show that our solution can significantly reduce the area overhead of many-port gpr files without sacrificing the performance improvements through ises.
boxrouter 2.0: architecture and implementation of a hybrid and robust global router. in this paper, we present boxrouter 2.0, a hybrid and robust global router with discussion on its architecture and implementation. as high performance vlsi design becomes more interconnect-dominant, efficient congestion elimination in global routing is in greater demand. hence, we propose boxrouter 2.0 which has strong ability to improve routability and minimize the number of vias with blockages, while minimizing wirelength. boxrouter 2.0 is improved over [1], but can perform multi-layer routing with 2d global routing and layer assignment. our 2d global routing is equipped with two ideas: robust negotiation-based a* search for routing stability, and topology-aware wire ripup for flexibility. after 2d global routing, 2d-to-3d mapping is done by the layer assignment which is powered by progressive via/blockage-aware integer linear programming. experimental results show that boxrouter 2.0 has better routability with comparable wirelength than other routers on ispd07 benchmark, and it can complete (no overflow) ispd98 benchmark for the first time in the literature with the shortest wirelength.
scalable exploration of functional dependency by interpolation and incremental sat solving. functional dependency is concerned with rewriting a boolean function f as a function h over a set of base functions {g1, ..., gn}, i.e. f = h(g1, ..., gn). it plays an important role in many aspects of electronic design automation (eda), ranging from logic synthesis to formal verification. prior approaches to the exploration of functional dependency are based on binary decision diagrams (bdds), which may not be easily scalable to large designs. this paper proposes a novel reformulation that extensively exploits the capability of modern satisfiability (sat) solvers. thereby, functional dependency is detected effectively through incremental sat solving, and the dependency function h, if it exists, is obtained through craig interpolation. the main strengths of the proposed approach include: (1) fast detection of functional dependency with modest memory consumption and thus scalable to large designs, (2) a full capacity to handle a large set of base functions and thus discovering dependency whenever exists, and (3) potential application to large-scale logic optimization and verification reduction. experimental results show the proposed method is far superior to prior work and scales well in dealing with the largest iscas89 and itc99 benchmark circuits with up to 200k gates.
approximation algorithm for the temperature-aware scheduling problem. the paper addresses the problem of performance optimization for a set of periodic tasks with discrete voltage/frequency states under thermal constraints. we prove that the problem is np-hard, and present a pseudo-polynomial optimal algorithm and a fully polynomial time approximation technique (fptas) for the problem. the fptas technique is able to generate solutions in polynomial time that are guaranteed to be within a designer specified quality bound (qb) (say within 1% of the optimal). we evaluate our techniques by experimentation with multimedia and synthetic benchmarks mapped on the 70nm cmos technology processor. the experimental results demonstrate our techniques are able to match optimal solutions when qb is set at 5%, can generate solutions that are quite close to optimal (< 5%) even when qb is set at higher values (50%), and executes in few seconds (with qb > 25%) for large task sets with 120 nodes (while the optimal solution takes several hundred seconds). we also analyze the effect of different thermal parameters, such as the initial temperature, the final temperature and the thermal resistance.
performance and power evaluation of a 3d cmos/nanomaterial reconfigurable architecture. in this paper, we introduce a novel reconfigurable architecture, named 3d nfpga, which utilizes 3d integration techniques and new nanoscale materials synergistically. the proposed architecture is based on cmos-nano hybrid techniques that incorporate nanomaterials such as carbon nanotube bundles and nanowire crossbars into cmos fabrication process. using unique features of fpgas and a novel 3d stacking method enabled by the application of nanomaterials, 3d nfpga obtains a 4.5x footprint reduction compared to traditional cmos-based 2d fpgas. with a customized design automation flow, we evaluate the performance and power of 3d nfpga driven by the 20 largest mcnc benchmarks. results demonstrate that 3d nfpga is able to provide a performance gain of 2.6x with a small power overhead comparing to the cmos 2d fpga architecture.
cachecompress: a novel approach for test data compression with cache for ip embedded cores. in this paper, we propose a novel test data compression technique named cachecompress, which combines selective encoding and dynamic dictionary based encoding. depending on the number of specified bits, a test data word is either encoded in a single code word or as a lookup in the dictionary. explicit dictionary initialization is not required since the content of the dictionary is updated during testing. the dictionary itself only contains the most recently used patterns, thus it exhibits a behaviour similar to a cache. experiments show that our technique achieves higher compression ratio than other recent compression schemes while the dictionary size has been dramatically reduced.
run-time adaptive on-chip communication scheme. during run-time varying workloads and/or constraints in embedded systems require run-time adaptivity to provide a high degree of efficiency during any operation mode/scenario. design time decisions can often only cover certain scenarios and fail in efficiency when hard-to-predict system scenarios occur. we are presenting the first approach of an adaptive on-chip communication scheme. it provides an adaptive routing/path allocation algorithm to meet a required level of qos (guaranteed bandwidth). in our architecture adaptive runtime links are established by re-assigning buffer blocks on-demand. this adaptive buffer allocation scheme increases the buffer utilization and decreases the overall buffer use on an average of 42% in our case study analysis compared to a fixed buffer assignment strategy. the area overhead introduced by the adaptive scheme can be traded-off against the flexibility in order to select an available path and on-demand buffer allocation. we demonstrate the advantage by using various real world digital media applications and compare our approach to the state-of-the-art static on-chip communication schemes.
a self-adjusting clock tree architecture to cope with temperature variations. ensuring resilience against environmental variations is becoming one of the great challenges of chip design. in this paper, we propose a self adjusting clock tree architecture, sacta, to improve chip performance and reliability in the presence of on-chip temperature variations. sacta performs temperature dependent dynamic clock skew scheduling to prevent timing violations in a pipelined circuit. we present an automatic temperature adjustable skew buffer design, which enables the adaptive feature of sacta. furthermore, we propose an efficient and general optimization framework to determine the configuration of these special delay elements. experimental results show that a pipeline supported by sacta is able to prevent thermal induced timing violations within a significantly larger range of operating temperatures (enhancing the violation-free range by as much as 45&deg;c).
device-circuit co-optimization for mixed-mode circuit design via geometric programming. modern processing technologies offer a number of types of devices such as high-vt, low-vt, thick-oxide, etc. in addition to the nominal transistor in order to meet system performance and functional needs. while designers have leveraged these devices for mixed-signal design, a design framework is needed to guide designers in selecting the best set of devices. the same framework can enable device manufacturers decide which new devices to include in the suite of device offerings. this paper presents a design methodology that can quickly guide a designer in selecting the best set of devices for a given application, specifications, and circuit structure. the equation-based optimization framework based on geometric programming (gp) extends upon previous efforts that optimize sizing, biasing, and supply voltages. the paper first shows that convex piecewise-linear function fitting can effectively model for optimization all the types of devices offered by a 90nm cmos technology. additionally, we show the potential to model and include experimental devices such as a schottky tunneling source mosfet. second, the paper applies the model to an example circuit, a track-and-hold amplifier. the optimization and subsequent simulation illustrate the importance and amount of benefit from applying device selection.
estimation of delay test quality and its application to test generation. as a method to evaluate delay test quality of test patterns, sdqm (statistical delay quality model) has been proposed for transition faults. in order to derive better test quality by sdqm, the following two things are important: for each transition fault, (1) to find out the accurate length of the longest sensitizable paths along which the fault is activated and propagated, and (2) to generate a test pattern that detects the fault through as long paths as possible. in this paper, we propose a method to calculate the length of the potentially sensitizable longest path for detection of a transition fault. in addition, we develop a procedure to extract path information that helps high quality transition atpg. experimental results show that the proposed method not only derives more accurate sdql (statistical delay quality level) but also enhances the test quality of generated test patterns.
3d-staf: scalable temperature and leakage aware floorplanning for three-dimensional integrated circuits. thermal issues are a primary concern in the three-dimensional (3d) integrated circuit (ic) design. temperature, area, and wire length must be simultaneously optimized during 3d floorplanning, significantly increasing optimization complexity. most existing floorplanners use combinatorial stochastic optimization techniques, hampering performance and scalability when used for 3d floorplanning. in this work, we propose and evaluate a scalable, temperature-aware, force-directed floorplanner called 3d-staf. force-directed techniques, although efficient at reacting to physical information such as temperature gradients, must eventually eliminate overlap. this can cause significant displacement when used for heterogeneous blocks. to smooth the transition from an unconstrained 3d placement to a legalized, layer-assigned floorplan, we propose a three-stage force-directed optimization flow combined with new legalization techniques that eliminate white spaces and block overlapping during multi-layer floorplanning. a temperature-dependent leakage model is used within 3d-staf to permit optimization based on the feedback loop connecting thermal profile and leakage power consumption. 3d-staf has good performance that scales well for large problem instances. compared to recently published 3d floorplanning work, 3d-staf improves the area by 6%, wire length by 16%, via count by 22%, peak temperature by 6% while running nearly 4x faster on average.
finding linear building-blocks for rtl synthesis of polynomial datapaths with fixed-size bit-vectors. polynomial computations over fixed-size bit-vectors are found in many practical datapath designs. for efficient rtl synthesis, it is important to identify good decompositions of the polynomial into smaller/simpler units. symbolic computer algebra algorithms and tools have been used for this purpose. however, fixed-size (m) bit-vector arithmetic is polynomial algebra over the finite integer ring z2m, which is a non-unique factorization domain (non-ufd). while non-ufds provide an extra freedom to search for decompositions, they complicate polynomial manipulation as traditional division-based algorithms are inapplicable. this paper presents new mathematical concepts for polynomial decomposition over z2m, for rtl synthesis over fixed-size m-bit vectors. given a polynomial, we identify a specific set of linear expressions and compute the gr&ouml;bner bases of their ideal (over non-ufd z2m) using syzygies. this basis serves as good building-blocks for the given computation. a decomposition is identified by subsequent gr&ouml;bner basis reduction. experimental results demonstrate significant area savings due to our approach, as compared against contemporary datapath synthesis techniques.
an efficient method to identify critical gates under circuit aging. negative bias temperature instability (nbti) is the leading factor of circuit performance degradation. due to its complex dependence on operating conditions, especially signal probability, it is a tremendous challenge to accurately predict the degradation rate in reality. on the other hand, we demonstrate in this work that it is feasible to reliably predict the relative importance of gates under nbti. by identifying critical gates that are the most important ones for timing degradation, we will be able to effectively protect the circuit from aging, with the minimum design overhead. the proposed method is based on a new timing analysis framework that integrates a nbti-aware library. for each potential critical path, we prove that there exists a particular signal probability, which leads to the worst case of timing degradation. the search of such worst case signal probability provides a safe guardband for the degradation, yet avoiding overly pessimistic analysis. by applying this method to iscas and itc benchmark circuits at the 65nm node, we demonstrate that in average only 1% of total gates need to be protected in order to control the timing degradation within 10% in ten years. since this method only requires one-time analysis of each critical path, it is very efficient in computation. with the information of critical gates available, it further enables other resilient design techniques to mitigate circuit aging under nbti.
efficient vco phase macromodel generation considering statistical parametric variations. with the growing concern of process variability, parameterized circuit models are becoming increasingly important for circuit design and verification. although techniques exist to extract compact vco phase macromodels, a direct parametrization of vco macromodels over a large set of parametric variations not only results in highly complex models, but also leads to significantly high computational cost. in this paper, an efficient parameterized vco phase model generation technique is presented to capture the impacts of statistical parametric variations. the model extraction cost of our approach is significantly reduced by exploiting circuit-specific parameter dimension reduction, which effectively reduces the parameter space dimension over which the phase model needs to be extracted. the application of parameter reduction is facilitated by a novel and fast time-domain sampling technique that provides the essential statistical correlation data. our numerical experiments have shown that the proposed model generation approach is more efficient than brute-force parametric modeling while producing accurate parameterized phase models that can capture large range parametric variations.
compatibility path based binding algorithm for interconnect reduction in high level synthesis. this paper describes a register and functional unit (fu) binding algorithm in high level synthesis. our algorithm targets the reduction of multiplexer inputs. since multiplexers connect multiple inputs to fus or registers, the multiplexer count is a good indicator of the interconnect complexity. reducing the number of multiplexer inputs results in reducing interconnect cost. specifically, our algorithm constructs a weighted and ordered compatibility graph, and binds operations that form a long path in the graph together. as a result, operations with many flow dependencies and common inputs are bound to same fu, leading to a small number of fu inputs. in addition, the operation variables generated by a single fu are assigned to the same register so that connections between fus and registers are reduced. we have implemented our algorithm within a matlab to verilog conversion tool, and applied it to a suite of benchmark programs. our experimental results have shown that the proposed scheme achieves 11.8%, 43.6% and 58.8% multiplexer input count reduction on average over weighted bipartite matching algorithm, k-cofamily algorithm and left edge algorithm, respectively. to assess the impact on interconnect reduction, we have generated layouts of the circuits from our verilog description. it is shown that our approach delivers a 10.1% reduction in total wire-length of global interconnects with minor area overhead of register and fus in comparison to the best previously proposed scheme.
efficient multi-layer obstacle-avoiding rectilinear steiner tree construction. given a set of pins and a set of obstacles on routing layers, a multi-layer obstacle-avoiding rectilinear steiner minimal tree (ml-oarsmt) connects these pins by rectilinear edges within layers and vias between layers, and avoids running through any obstacle to construct a steiner tree with a minimal total cost. the ml-oarsmt problem is very important for many vlsi designs with pins being located in multiple routing layers that contain numerous routing obstacles incurred from ip blocks, power networks, prerouted nets, etc. therefore, it is desired to develop an effective algorithm for the ml-oarsmt problem. however, there is no existing work on the mloarsmt problem. in this paper, we first formulate the mloarsmt problem and identify key different properties of the problem from its single-layer counterpart. based on the multi-layer obstacle-avoiding spanning graph (ml-oasg), we present the first algorithm to solve the ml-oarsmt problem. our algorithm can guarantee an optimal solution for any 2-pin net and many higher-pin nets. experiments show that our algorithm results in 33% smaller total costs on average than a construction-by-correction heuristic which is widely used for steiner-tree construction in the recent literature.
untangling twisted nets for bus routing. previous works [1], [2] on pcb bus routing assume matched pin ordering for both sides. but in practice, the pin ordering might be mismatched and the nets become twisted. in this paper, we propose a preprocessing step to untangle such twisted nets. we also present an algorithm to solve this untangling problem. our algorithm produces an optimal single-detour routing scheme that rematches the pin ordering. by integrating our preprocessing step into the bus router in [2], we show that many routing problems that cannot be solved previously can now be solved with insignificant increase in runtime.
a novel synthesis algorithm for reversible circuits. in this paper, a new non-search based synthesis algorithm for reversible circuits is proposed. compared with the widely used search-based methods, our algorithm is guarantied to produce a result and can lead to a solution with much fewer steps. to evaluate the proposed method, several circuits taken from the literature are used. the experimental results corroborate the expected findings.
a geometric approach for early power grid verification using current constraints. the verification of power grids in modern integrated circuits must start at design time, where circuit information is unknown but could be specified or inferred from design or architectural considerations. this work builds on previously proposed techniques to deal with circuit uncertainty in the framework of linear current constraints, but proposes a cost-controlled solution, by following a geometric approach, and transforming a problem that requires as many linear programs as there are power grid nodes, to another involving a user-limited number of solutions of one linear system.
a methodology for fast and accurate yield factor estimation during global routing. in this paper, a novel and computationally efficient methodology to accurately estimate key yield factors during the global routing stage is presented. such an yield factor estimator at the global routing stage is essential since it can used to either get an early estimate of the final yield of the same design (i.e. the yield after applying the required sequence of detailed routing and post-routing yield optimizations) and/or to improve the final yield of the design by making the solution at the end of global routing more amenable to post-routing yield optimizations. the proposed yield factor estimator is inherently flexible and can easily be programmed to estimate during global routing a variety of key yield factors of the same design after a typical sequence of detailed routing and representative post-routing yield optimizations has been applied. examples are provided to show how the yield factor estimator can be used to predict short and open critical area and metal density after typical yield optimization solutions like wire-spreading, wire-widening and metal filling, respectively. experimental results presented in the paper show that the proposed yield factor estimator can predict final yield factor hotspots/values with a high degree of accuracy. the proposed estimator is also shown to be more suited for the purpose of yield factor estimation compared with typical metrics at the global routing stage like congestion.
timing optimization by restructuring long combinatorial paths. we present an implementation of an algorithm for constructing provably fast circuits for a class of boolean functions with input signals that have individual starting times. we show how to adapt this algorithm to logic optimization for timing correction at late stages of vlsi physical design and report experimental results on recent industrial chips. by restructuring long critical paths, our code achieves worst-slack improvements of up to several hundred picoseconds on top of traditional timing optimization techniques.
a fast and high-capacity electromagnetic solution for highspeed ic design. this paper proposes a fast and high-capacity electromagnetic solution, time-domain layered finite element reduction recovery (lafe-rr) method, for high-frequency modeling and simulation of large-scale on-chip circuits. this method rigorously reduces the matrix of a multilayer system to that of a single-layer one regardless of the original problem size. more important, the matrix reduction is achieved analytically, and hence the cpu and memory overheads are minimal. the recovery of solutions in all other layers involves only forward and backward substitution of matrices of single-layer size. the memory cost is also modest-requiring only the memory needed for the factorization of a single layer sparse matrix. the improved performance applies to any arbitrarily shaped multilayer structure. numerical and experimental results are presented to demonstrate the accuracy, efficiency, and capacity of the proposed method.
the coming of age of physical synthesis. physical synthesis, the integration of logic synthesis with physical design information, was born in the mid to late 1990s, which means it is about to enter its teenage years. today, physical synthesis tools are a major part of the eda industry, accounting for hundreds of millions of dollars in revenue. this work looks at how technology and design trends have affected physical synthesis over the last decade and also how physical synthesis will continue to evolve on its way to adulthood.
thermal-aware steiner routing for 3d stacked ics. in this paper, we present the first work on the steiner routing for 3d stacked ics. in the 3d steiner routing problem, the pins are located in multiple device layers, which makes it more general than its 2d counterpart. our algorithm consists of two steps: tree construction and tree refinement. our tree construction algorithm builds a delay-oriented steiner tree under a given thermal profile. we show that thermal-aware 3d tree construction involves the minimization of two-variable elmore delay function. in our tree refinement algorithm, we reposition the through-vias while preserving the original routing topology for further thermal optimization under performance constraint. we employ a novel scheme to relax the initial nlp formulation to ilp and consider all through-vias from all nets simultaneously. our related experiments show the effectiveness of our proposed solutions.
timing budgeting under arbitrary process variations. timing budgeting under process variations is an important step in a statistical optimization flow. we propose a novel formulation of the problem where budgets are statistical instead of deterministic as in existing works. this new formulation considers the changes of both the means and variances of delays, and thus can reduce the timing violation introduced by ignoring the changes of variances. we transform the problem to a linear programming problem using a robust optimization technique. our approach can be used in late-stage design where the detailed distribution information is known, and is most useful in early-stage design since our approach does not assume specific underlying distributions. in addition, with the help of block-level timing budgeting, our approach can reduce the timing pessimism. our approach is applied to the leakage power minimization problem. the results demonstrate that our approach can reduce timing violation from 690ps to ops, and the worst total leakage power by 17.50% on average.
a novel technique for incremental analysis of on-chip power distribution networks. we propose a novel and efficient incremental analysis technique for 'what-if analysis of on-chip power distribution networks (pdn). effect of local modifications to a pdn, including local topology changes, can be quickly analyzed without need for very expensive re-analysis of the entire modified network. we borrow ideas from a fictitious domain method that has been successfully used in solving partial differential equations arising from inhomogeneous problems in mechanics. the effect of local wiring modifications in several pdn regions is mimicked by applying fictitious currents at the boundaries of these regions in the original unmodified network. the fictitious currents are calculated from component sub-problems in a low-computation iterative procedure. the practicality of this method for use in what-if analysis is demonstrated with several large power networks from actual industrial designs. it analyzes a modified network with few million changes in a fraction of time it would take for a complete re-analysis.
fault-tolerant multi-level logic decoder for nanoscale crossbar memory arrays. several technologies with sub-lithographic features are targeting the fabrication of crossbar memories in which the nanowire decoder is playing a major role. in this paper, we suggest a way to reduce the decoder size and keep it defect tolerant by using multiple threshold voltages (vt), which is enabled by our underlying technology. we define two types of multi-valued decoders and model the defects they undergo due to the vt variation. multi-valued hot decoders yield better area saving than n-ary reflexive codes (nrc), and under severe conditions, nrc enables a non-vanishing part of the code space to recover. there are many combinations of decoder type and number of vt's yielding equal effective memory capacities. the optimal choice saves area up to 24%. we also show that the precision of the addressing voltages for decoders with unreliable vt's is a crucial parameter for the decoder design and permits large savings in memory area.
strategies for improving the parametric yield and profits of 3d ics. three-dimensional (3d) integrated circuits (ics) that integrate die with through-silicon vias (tsvs) promise to continue system and functionality scaling beyond the traditional geometric 2d device scaling. 3d integration also improves the performance of ics by reducing the communication time between different chip components through the use of short tsv-based vertical wires. this reduction is particularly attractive in processors where it is desirable to reduce the access time between the main logic die and the l2 cache or the main memory die. process variations in 2d ics lead to a drop in parametric yield (as measured by speed, leakage and sales profits), which forces manufacturers to speed bin their chips and to sell slow chips at reduced prices. in this paper we develop a model to quantify the impact of process variations on the parametric yield of 3d ics, and then we propose a number of integration strategies that use a graph-theoretic framework to maximize the performance, parametric yield and profits of 3d ics. comparing our proposed strategies to current yield-oblivious methods, it is demonstrated that it is possible to increase the number of 3d ics in the fastest speed bins by almost 2x, while simultaneously reducing the number of slow ics by 29.4%. this leads to an improvement in performance by up to 6.45% and an increase of about 12.48% in total sales revenue using up-to-date market price models.
incremental component implementation selection: enabling eco in compositional system synthesis. the component implementation selection problem (cisp) is to select the appropriate implementation for components of a design, such that the timing constraint is met and some global design objective is optimized. cisp is a generic problem that implicitly or explicitly appears in many stages of cad flow. in this paper, we present a methodology for quick and efficient updating of cisp solutions in face of incremental engineering changes. for a commonly-used formulation, we discuss necessary and sufficient conditions for optimality of a cisp solution based on which, we develop an algorithm that maintains both validity and optimality of a solution subject to incremental changes. we implemented our approach to incrementally update the threshold voltage assignment solution for a netlist going through engineering changes. on average, our method ran over 300 times faster than the "from-scratch" solver, while delivering the same results.
a methodology for timing model characterization for statistical static timing analysis. while the increasing need for addressing process variability in sub-90nm vlsi technologies has sparkled a large body of statistical timing and optimization research, the realization of these techniques heavily depends on the availability of timing models that feed the statistical timing analysis engine. to target at this critical but less explored territory, in this paper, we present numerical and statistical modeling techniques that are suitable for the underlying timing model characterization infrastructure of statistical timing analysis. our techniques are centered around the understanding that while the widening process variability calls for accurate non-first-order timing models, their deployment requires well-controlled characterization techniques to cope with the complexity and scalability. we present a methodology by which timing variabilities in interconnects and nonlinear gates are translated efficiently into quadratic timing models suitable for accurate statistical timing analysis. specific parameter reduction techniques are developed to control the characterization cost that is a function of number of variation sources. the proposed techniques are extensively demonstrated under the context of logic stage timing characterization involving interactions between logic gates and interconnects.
design, synthesis and evaluation of heterogeneous fpga with mixed luts and macro-gates. small gates, such as and2, xor2 and mux2, have been mixed with lookup tables (luts) inside the programmable logic block (plb) to reduce area and power and increase performance in fpgas. however, it is unclear whether incorporating macro-gates with wide inputs inside plbs is beneficial. in this paper, we first propose a methodology to extract a small set of logic functions that are able to implement a large portion of functions for given fpga applications. assuming that the extracted logic functions are implemented by macro-gates in plbs, we then develop a complete synthesis flow for such heterogeneous plbs with mixed luts and macro-gates. the flow includes a cut-based delay and area optimized technology mapping, a mixed binary integer and linear programming based area recovery algorithm to balance the resource utilization of macro-gates and luts for area-efficient packing, and a sat-based packing. we finally evaluate the proposed heterogeneous fpga using the newly developed flow and show that mixing lut and macro-gates, both with 6 inputs, improves performance by 16.5% and reduces logic area by 30% compared to using merely 6-input luts.
procrastination determination for periodic real-time tasks in leakage-aware dynamic voltage scaling systems. many computing systems have adopted the dynamic voltage scaling (dvs) technique to reduce energy consumption by slowing down operation speed. however, the longer a job executes, the more energy in leakage current the processor consumes for the job. to reduce the power/energy consumption from the leakage current, a processor can enter the dormant mode. existing research results for leakage-aware dvs scheduling perform procrastination of real-time jobs greedily so that the idle time can be aggregated as long as possible to turn off the processor. this paper proposes algorithms for the procrastination determination of periodic real-time tasks in uniprocessor systems. instead of greedy procrastination, the procrastination procedures are applied only when the evaluated energy consumption is less than not procrastination. evaluation results show that our proposed algorithms could derive energy-efficient solutions and outperform existing algorithms.
exploiting symmetry in sat-based boolean matching for heterogeneous fpga technology mapping. the boolean matching problem is a key procedure in technology mapping for heterogeneous field programmable gate arrays (fpga), and sat-based boolean matching (sat-bm) provides a highly flexible solution for various fpga architectures. however, the computational complexity of state-of-the-art sat-bm prohibits its application practically. in this paper we propose an efficient sat-bm algorithm by exploring function and architectural symmetries. while the most recent work obtained up to 13x speedup, we achieve up to 200x speedup, when both are compared to the original sat-bm algorithm.
the design and synthesis of a synchronous and distributed mac protocol for wireless network-on-chip. to bridge the widening gap between computation requirements and communication efficiency faced by gigascale heterogeneous socs in the upcoming ubiquitous era, a new on-chip communication system, dubbed wireless network-on-chip (wnoc), is introduced by using the recently developed cmos proximity wireless interconnection technology. in this paper, a synchronous and distributed medium access control (sd-mac) protocol is designed and implemented. tailored for wnoc, sd-mac employs a binary countdown approach to resolve channel contention between rf nodes. the receiver_select_sender mechanism and hidden terminal elimination scheme are proposed to increase the throughput and channel utilization of the system. our simulation study shows the promising performance of sd-mac in terms of throughput, latency, and network utilization. as a major component of simple and compact rf node design, a mac unit implements the proposed sdmac that guarantees correct operation of synchronized frames while keeping overhead low. the synthesis results demonstrate several attractive features such as high speed, low power consumption, nice scalability and low area cost.
data locality enhancement for cmps. as chip multiprocessors (cmps) are being increasingly used in embedded computing, optimizing data locality considering interprocessor interactions is becoming critical. to address this problem, this paper proposes a new abstraction called the interprocessor data reuse vector, which captures the reuse distance (in terms of loop iterations) between successive accesses to a given data element from different processors. based on this reuse vector, we then present a data locality optimization scheme. a unique characteristic of this scheme is that it allows application of different transformations to different processors of the cmp if this helps improve locality of data shared across processors. we automated our approach within an optimizing compiler and collected statistics using eight application codes. our results indicate that the proposed code restructuring is very effective in practice (about 9% savings in performance over a standard data locality optimizer).
an incremental learning framework for estimating signal controllability in unit-level verification. unit-level verification is a critical step to the success of full-chip functional verification for microprocessor designs. in the unit-level verification, a unit is first embedded in a complex software that emulates the behavior of surrounding units, and then a sequence of stimuli is applied to measure the functional coverage. in order to generate such a sequence, designers need to comprehend the relationship between boundaries at the unit under verification and at the inputs to the emulation software. however, figuring out this relationship can be very difficult. therefore, this paper proposes an incremental learning framework that incorporates an ordered-binary-decision-forest(obdf) algorithm, to automate estimating the controllability of unit-level signals and to provide full-chip level information for designers to govern these signals. mathematical analysis shows that the proposed obdf algorithm has lower model complexity and lower error variance than the previous algorithms. meanwhile, a commercial microprocessor core is also applied to demonstrate that controllability of input signals on the load/store unit in the microprocessor core can be estimated automatically and information about how to govern these signals can also be extracted successfully.
adaptive post-silicon tuning for analog circuits: concept, analysis and optimization. the well-known pelgrom model [14] has demonstrated that the variation between two devices on the same die due to random mismatch is inversely proportional to the square root of the device area: &sigma; ~ 1/sqrt(area). based on the pelgrom model, analog devices are sized to be large enough to average out random variations. importantly, with cmos scaling, variations due to random doping fluctuations are making it exceedingly difficult to control device mismatches by sizing alone; namely, the devices have to be made so large that the benefits of cmos scaling are not realized for analog and rf circuits. in this paper we propose a novel post-silicon tuning methodology to reduce random mismatches for analog circuits in sub-90nm cmos. a novel dynamic programming algorithm is incorporated into a fast monte carlo simulation flow for statistical analysis and optimization of the proposed tunable analog circuits. we apply the proposed post-silicon tuning methodology to several commonly-used analog circuit blocks. we demonstrate that with the post-silicon tuning, device mismatch exponentially decreases as area increases: &sigma; ~ exp(---&alpha;&middot;area).
a novel soc design methodology combining adaptive software and reconfigurable hardware. reconfigurable hardware is becoming a prominent component in a large variety of soc designs. reconfigurability allows for efficient hardware acceleration and virtually unlimited adaptability. on the other hand, overheads associated with reconfiguration and interfaces with the software component need to be evaluated carefully during the exploration phase. the aim of this paper is to identify the best trade-off considering application-specific features in software, which can lend itself to software-based acceleration and lead to a revision of the view that certain computationally intensive tasks can only be accelerated through hardware. in order to validate the effectiveness of our proposed techniques, we built an extensive development and experimental setup, bringing together the mlton-based programming environment and physical mapping of the software and hardware onto a real dynamically reconfigurable soc system.
clustering based pruning for statistical criticality computation under process variations. we present a new linear time technique to compute criticality information in a timing graph by dividing it into "zones". errors in using tightness probabilities for criticality computation are dealt with using a new clustering based pruning algorithm which greatly reduces the size of circuit-level cutsets. our clustering algorithm gives a 150x speedup compared to a pairwise pruning strategy in addition to ordering edges in a cutset to reduce errors due to clark's max formulation. the clustering based pruning strategy coupled with a localized sampling technique reduces errors to within 5% of monte carlo simulations with large speedups in runtime.
timing variation-aware high-level synthesis. the timing closure problem is one of the most important problems in the design automation. however, the rapid increase of the impact of the process variation on circuit timing makes the problem much more complicated and unpredictable to tackle in synthesis. this work addresses a new problem of high-level synthesis (hls) that effectively takes into account the timing variation. specifically, the work addresses the following four problem: (1) how can the statistical static timing analysis (ssta) used in logic synthesis be modified and applied to the delay and yield computation in hls? (2) how does the resource binding affect yield? (3) how does the scheduling affect yield? (4) how can scheduling and resource binding tasks be combined together to efficiently solve the problem with the objective of minimizing latency under yield constraint?
variation-aware performance verification using at-speed structural test and statistical timing. meeting the tight performance specifications mandated by the customer is critical for contract manufactured asics. to address this, at speed test has been employed to detect subtle delay failures in manufacturing. however, the increasing process spread in advanced nanometer asics poses considerable challenges to predicting hardware performance from timing models. performance verification in the presence of process variation is difficult because the critical path is no longer unique. different paths become frequency limiting in different process corners. in this paper, we present a novel variation-aware method based on statistical timing to select critical paths for structural test. node criticalities are computed to determine the probabilities of different circuit nodes being on the critical path across process variation. moreover, path delays are projected into different process corners using their linear delay function forms. experimental results for three multimillion gate asics demonstrate the effectiveness of our methods.
principle hessian direction based parameter reduction with process variation. as cmos technology enters the nanometer regime, the increasing process variation is bringing manifest impact on circuit performance. in this paper, we propose a principle hessian direction (phd) based parameter reduction approach. this new approach relies on the impact of each parameter on circuit performance to decide whether keeping or reducing the parameter. compared with the existing principle component analysis (pca) method, this performance based property provides us a significantly smaller set of parameters after reduction. the experimental results also support our conclusions. in all cases, an average of 53% of reduction is observed with less than 3% error in the mean value and less than 8% error in the variation.
unified adaptivity optimization of clock and logic signals. vlsi design is increasingly sensitive to variations which often degrade the parametric yield. post-silicon tuning techniques can compensate for specific variations on the die and thus significantly improve the yield. previous works on adaptivity optimization for post-silicon tuning focus on either logic signal tuning or clock signal tuning. this paper proposes the first unified adaptivity optimization on logical and clock signal tuning, which enables us to significantly save resource. in addition, it does not need any assumption on variation distributions. our unified optimization is based on a novel linear programming formulation which can be efficiently solved by an advanced robust linear programming technique. due to the discrete nature of the problem, the continuous solution obtained from linear programming is then efficiently discretized. this procedure involves binary search accelerated dynamic programming, batch based optimization, and latin hypercube sampling based fast simulation. our experimental results demonstrate that up to 50% area cost reduction can be obtained by the unified optimization compared to optimization on logic or clock alone. in addition, the proposed discretization approach significantly outperforms the alternatives in terms of solution quality and runtime.
estimation of statistical variation in temporal nbti degradation and its impact on lifetime circuit performance. negative bias temperature instability (nbti) in mosfets is one of the major reliability concerns in sub-100nm technologies. so far, studies of nbti and its impact on circuit performance have assumed an average behavior of the degradation process. however, in very short channel devices, finite number of si-h bonds in the channel can induce a statistical random variation of the degradation process. this results in significant random vt variations in pmos transistor. the nbti induced variation depends on operating temperature and the effective stress period for the specific device. in this paper, we analyze the impact of stochastic temporal nbti variations and propose a compact circuit level vt model. using the proposed model, we show how temporal vt variations can affect the lifetime performance of different circuit topologies including 6t sram cell and random combinational logic circuits.
checking equivalence of quantum circuits and states. among the post-cmos technologies currently under investigation, quantum computing (qc) holds a special place. qc offers not only extremely small size and low power, but also exponential speed-ups for important simulation and optimization problems. it also poses new cad problems that are similar to, but more challenging, than the related problems in classical (non-quantum) cad, such as determining if two states or circuits are functionally equivalent. while differences in classical states are easy to detect, quantum states, which are represented by complex-valued vectors, exhibit subtle differences leading to several notions of equivalence. this provides flexibility in optimizing quantum circuits, but leads to difficult new equivalence-checking issues for simulation and synthesis. we identify several different equivalence-checking problems and present algorithms for practical benchmarks, including quantum communication and search circuits, which are shown to be very fast and robust for hundreds of qubits.
mapping model with inter-array memory sharing for multidimensional signal processing. the storage requirements in data-intensive signal processing systems (including applications in video and image processing, artificial vision, medical imaging, real-time 3-d rendering, advanced audio and speech coding) have an important impact on both the system performance and the essential design parameters -- the overall power consumption and chip area. this is due to the significant amount of data that must be stored during the execution of the algorithmic specification, as well as due to the amount of data transfers to/from large, energy-consuming, off-chip data memories. this paper addresses the problem of efficiently mapping the multidimensional signals from the algorithmic specification of the system into the physical memory. different from all the previous mapping models that aim to optimize the memory sharing between the elements of a same array, creating separate windows in the physical memory for distinct arrays, this proposed mapping model is the first one to exploit the possibility of memory sharing between different arrays. as a consequence, this signal-to-memory mapping approach yields significant savings in the amount of data storage resulted after mapping.
device and architecture concurrent optimization for fpga transient soft error rate. late cmos scaling reduces device reliability, and existing work has studied the permanent ser (soft error rate) for configuration memory in fpga extensively. in this paper, we show that continuous cmos scaling dramatically increases the significance of fpga chip-level transient soft errors in circuit elements other than configuration memory, and transient ser can no longer be ignored. we then develop an efficient, yet accurate, transient ser evaluation method, called trace based methodology, considering logic, electrical and latch-window maskings. by collecting traces on logic probability and sensitivity and re-using these traces for different device settings, we finally perform device and architecture concurrent optimization considering hundreds of device and architecture combinations. compared to the commonly used fpga architecture and device settings, device and architecture concurrent optimization can reduce the transient ser by 2.8x and reduce the product of energy, delay and transient ser by 1.8x.
a general model for performance optimization of sequential systems. retiming, c-slow retiming and recycling are different transformations for the performance optimization of sequential circuits. for retiming and c-slow retiming, different models that provide exact solutions have already been proposed. an exact model for recycling was yet unknown. this paper presents a general formulation that covers the combination of the three schemes for performance optimization. it provides an exact model based on integer linear programming that resorts to the structural theory of marked graphs. a set of experiments has been designed to show the benefits in performance obtained by combining retiming and recycling. the results also show the applicability of the method in large circuits.
yield-driven near-threshold sram design. voltage scaling is desirable in sram to reduce energy consumption. however, commercial sram is prone to functional failures when vdd is scaled. several sram designs scale vdd to 200--300mv to minimize energy per access, but these designs do not consider sram robustness, limiting them to small arrays and sensor type applications. we examine the effects on area and energy for a differential 6t, single-ended 6t with power rail collapsing and an 8t bitcell as vdd is scaled and the bitcells are sized appropriately to maintain robustness. sram robustness is examined using importance sampling to reduce simulation runtime. at high voltages, the differential 6t bitcell is the smallest for the same failure rate, but the 8t bitcell is smaller when vdd is scaled below 450mv. for vdd below vth, bitcells must be sized greatly to retain robustness and large arrays become impractical. the differential 6t and 8t designs have the lowest dynamic energy consumption, and the single-ended 6t design has the lowest leakage. the supply voltage for minimum energy operation depends on cache configuration and can be well above vth for large caches with low dynamic activity.
multi-layer interconnect performance corners for variation-aware timing analysis. parasitic interconnect corner methods are known to be inaccurate. this paper explains the sources of their errors and shows that errors in excess of 22% can occur in the predicted corner delays of a multi-layer stage in the presence of process variations. it is shown that exhaustive corner search methods are infeasible in practice as they have an exponential complexity in terms of required spice simulations with respect to the number of layers a stage is routed through. this exponential complexity is reduced to a linear one with a new simulation-based search method with the aid of stage delay properties. the ideas behind the simulation-based methodology are shown to be expandable to an analytical-based multi-layer performance corner location methodology. the simulated best/worst case delays based on these analytical corners produce errors below 4% as compared to the exhaustive search simulation based method.
an efficient algorithm for time separation of events in concurrent systems. the time separation of events (tse) problem is that of finding the maximum and minimum separation between the times of occurrence of two events in a concurrent system. it has applications in the performance analysis, optimization and verification of concurrent digital systems. this paper introduces an efficient polynomial-time algorithm to give exact bounds on tse's for choice-free concurrent systems, whose operational semantics obey the max-causality rule. a choice-free concurrent system is modeled as a strongly-connected marked graph, where delays on operations are modeled as bounded intervals with unspecified distributions. while previous approaches handle acyclic systems only, or else require graph unfolding until a steady-state behavior is reached, the proposed approach directly identifies and evaluates the asymptotic steady-state behavior of a cyclic system via a graph-theoretical approach. as a result, the method has significantly lower computational complexity than previously-proposed solutions. a prototype cad tool has been developed to demonstrate the feasibility and efficacy of our method. a set of experiments have been performed on the tool as well as two existing tools, with noticeable improvement on runtime and accuracy for several examples.
efficient placement of distributed on-chip decoupling capacitors in nanoscale ics. decoupling capacitors are widely used to reduce power supply noise. on-chip decoupling capacitors have traditionally been allocated into the white space available on the die based on an unsystematic or ad hoc approach. in this way, large decoupling capacitors are often placed at a significant distance from the current load, compromising the signal integrity of the system. this issue of power delivery cannot be alleviated by simply increasing the size of the on-chip decoupling capacitors. to be effective, the on-chip decoupling capacitors should be placed physically close to the current loads. the area occupied by the on-chip decoupling capacitor, however, is directly proportional to the magnitude of the capacitor. the minimum impedance between the on-chip decoupling capacitor and the current load is therefore fundamentally affected by the magnitude of the capacitor. a distributed on-chip decoupling capacitor network is proposed in this paper. a system of distributed on-chip decoupling capacitors is shown to provide an efficient solution for providing the required on-chip decoupling capacitance under existing technology constraints. in a system of distributed on-chip decoupling capacitors, each capacitor is sized based on the parasitic impedance of the power distribution grid. various tradeoffs in a system of distributed on-chip decoupling capacitors are also discussed. related simulation results for typical values of on-chip parasitic resistance are also presented. an analytic solution is shown to provide accurate distributed system. the worst case error is 0.003% as compared to spice. techniques presented in this paper are applicable not only for current technologies, but also provide an efficient placement of the on-chip decoupling capacitors in future technology generations.
victim alignment in crosstalk aware timing analysis. modeling the effect of coupling noise on circuit delay is a key issue in static timing analysis (sta) and involves the "victim-aggressor alignment" problem. as delay-noise depends strongly on the skew between the victim-aggressor input transitions', it is not possible to apriori identify the victim input transition that results in the latest arrival time at the victim. several approaches that heuristically search for the worst-case victim-aggressor alignment have been proposed in literature. in this paper we present an analytical result that obviates the need to search for the worst-case victim input transition, thereby simplifying the victim-aggressor alignment problem significantly. using the properties of standard nonlinear cmos drivers, we show that regardless of the switching of the aggressors, the worst-case victim input transition is the one that switches at the latest point in its timing window. although this result has been empirically observed in the industry, to the best of our knowledge, this is the first work that provides a rigorous analysis and shows that the result holds for both linear and non-linear drivers. we also show that limiting the alignment of the victim to only the latest victim input transition can significantly reduce the runtime of existing heuristic techniques with no loss of accuracy.
efficient path delay test generation based on stuck-at test generation using checker circuitry. this paper proposes an approach to non-robust and functionally sensitizable path delay test generation through stuck-at test generation. in this approach, to generate two-pattern tests for path delay faults in a combinational circuit, checker circuitry is constructed which is composed of logic gates corresponding to the mandatory assignments for detecting the faults. this checker circuitry allows us to use any existing combinational stuck-at test generation tool. since today's stuck-at test generation tools reach a mature level, the proposed approach can efficiently solve the path delay test generation problem for combinational circuits. experimental results show that the approach can speed up path delay test generation and can improve fault efficiency. this paper also discusses how a scan circuit and the issues of over-testing and test power are handled in the proposed test generation framework.
variation-aware task allocation and scheduling for mpsoc. as technology scales, the delay uncertainty caused by process variations has become increasingly pronounced in deep submicron designs. as a result, a paradigm shift from deterministic to statistical design methodology at all levels of the design hierarchy is inevitable [1]. in this paper, we propose a variation-aware task allocation and scheduling algorithm for multiprocessor system-on-chip (mpsoc) architectures to mitigate the impact of parameter variations. a new design metric, called performance yield and defined as the probability of the assigned schedule meeting the predefined performance constraints, is used to guide the task allocation and scheduling procedure. an efficient yield computation method for task scheduling complements and significantly improves the effectiveness of the proposed variation-aware scheduling algorithm. experimental results show that our variation-aware scheduler achieves significant yield improvements. on average, 45% and 34% yield improvements over worst-case and nominal-case deterministic schedulers, respectively, can be obtained across the benchmarks by using the proposed variation-aware scheduler.
methodology for low power test pattern generation using activity threshold control logic. this paper proposes a new technique of power-aware test pattern generation, wherein the test mode power constraints are specified using pseudo hardware logic functions (referred to as power constraint circuits) that augment the target circuit fed to the atpg tool. the novelty of this approach is three-fold: (i) the atpg tool only sees the enhanced circuit. this influences the generation of the test cubes themselves, as against post-processing of these cubes for a given pattern. (ii) pattern generation can be driven to minimize test power according to a programmable switching activity threshold, and hence, is scalable. (iii) the same constraint circuit can also be effectively used for pattern filtering to isolate patterns which cause high switching activity. additionally, the proposed method does not require any changes to the pattern generation tool or process. this paper describes the methodology, together with techniques for realizing the hardware circuit and specifying thresholds. experimental results on various benchmark circuits (including an industrial design) are presented to show the effectiveness of this approach.
exploiting sti stress for performance. starting at the 65nm node, stress engineering to improve performance of transistors has been a major industry focus. an intrinsic stress source - shallow trench isolation - has not been fully utilized up to now for circuit performance improvement. in this paper, we present a new methodology that combines detailed placement and active-layer fill insertion to exploit sti stress for performance improvement. we perform process simulation of a production 65nm sti technology to generate mobility and delay impact models for sti stress. based on these models, we are able to perform sti stress-aware delay analysis of critical paths using spice. we then present our timing-driven optimization of sti stress in standard cell designs, using detailed placement perturbation to optimize pmos performance and active-layer fill insertion to optimize nmos performance. we assess our optimization on small designs implemented with a 65nm production cell library and a standard synthesis, place and route flow. our timing-driven optimization of sti stress impacts can improve clock frequency by between 7% to 11%. the frequency improvement through exploitation of sti stress comes at practically zero cost in terms of design area and wirelength.
fast exact toffoli network synthesis of reversible logic. the research in the field of reversible logic is motivated by its application in low-power design, optical computing and quantum computing. hence synthesis of reversible logic has become a very important research area in the last years. in this paper exact algorithms for the synthesis of generalized toffoli networks are considered. we present an improvement of an existing synthesis approach that is based on boolean satisfiability. furthermore, the principle limits of the original and the improved approach are shown. then, we propose a new method using problem specific knowledge during the synthesis process to overcome these limits. experimental results demonstrate improvements of the overall synthesis time up to four orders of magnitude.
architectural power models for sram and cam structures based on hybrid analytical/empirical techniques. the need to perform power analysis in the early stages of the design process has become critical as power has become a major design constraint. embedded and high-performance microprocessors incorporate large on-chip cache and similar sram-based or cam-based structures, and these components can consume a significant fraction of the total chip power. thus an accurate power modeling method for such structures is important in early architecture design studies. we present a unified architecture-level power modeling methodology for array structures which is highly-accurate, parameterizable, and technology scalable. we demonstrate the applicability of the model to different memory structures (srams and cams) and include leakage-variability in advanced technologies. the power modeling approach is validated against hspice power simulation results, and we show power estimation accuracy within 5% of detailed circuit simulations.
analog placement with common centroid constraints. in order to reduce parasitic mismatch in analog circuits, some groups of devices are required to share a common centroid while being placed. devices are split into smaller ones and placed with a common center point. we will address this problem of handling common centroid constraint in placement. a new representation called center-based corner block list (c-cbl) is proposed which is a natural extension of corner block list (cbl) [1] to represent a common centroid placement of a set of device pairs. c-cbl is complete and non-redundant in representing any common centroid mosaic packings with pairs of blocks to be matched. to address the same problem with an additional constraint that devices are required to be placed uniformly to average out the parasitic errors, a grid-based approach is proposed. experimental results show that both approaches are fast and promising, and have high scalability that even large data sets can be handled effectively.
high-performance routing at the nanometer scale. in this work we describe significant improvements to core routing technologies and outperform the best results from the ispd '07 global routing contest, as well as previous literature, in terms of route completion, runtime and total wirelength. in particular, our router, fgr, improves upon wirelengths produced by boxrouter and maizerouter in march 2007 by 9.9% and 8.4%, respectively. additionally, we reveal the mathematical basis of negotiated-congestion routing, offer comprehensive analysis of existing routing techniques and discuss several applications at the nanometer scale.
combinational and sequential mapping with priority cuts. an algorithm for technology mapping of combinational and sequential logic networks is proposed and applied to mapping into k-input lookup-tables (k-luts). the new algorithm avoids the hurdle of computing all k-input cuts while preserving the quality of the results, in terms of area and depth. the memory and runtime of the proposed algorithm are linear in circuit size and quite affordable even for large industrial designs. for example, computing a good quality 6-lut mapping of an aig with im nodes takes 150mb of ram and 1 minute on a typical laptop. an extension of the algorithm allows for sequential mapping, which searches the combined space of all possible mappings and retimings. this leads to an 18--22% improvement in depth with a 3--5% lut count penalty, compared to combinational mapping followed by retiming.
extending systems-on-chip to the third dimension: performance, cost and technological tradeoffs. because of the today's market demand for high-performance, high-density portable hand-held applications, electronic system design technology has shifted the focus from 2-d planar soc single-chip solutions to different alternative options as tiled silicon and single-level embedded modules as well as 3-d integration. among the various choices, finding an optimal solution for system implementation dealt usually with cost, performance and other technological trade-off analysis at the system conceptual level. it has been identified that the decisions made within the first 20% of the total design cycle time will ultimately result upto 80% of the final product cost. in this paper, we discuss appropriate and realistic metric for performance and cost trade-off analysis both at system conceptual level (up-front in the design phase) and at implementation phase for verification in the three-dimensional integration. in order to validate the methodology, two ubiquitous electronic systems are analyzed under various implementation schemes and discuss the pros and cons of each of them.
stochastic extended krylov subspace method for variational analysis of on-chip power grid networks. in this paper, we propose a novel stochastic method for analyzing the voltage drop variations of on-chip power grid networks with log-normal leakage current variations. the new method, called stoeks, applies hermite polynomial chaos (pc) to represent the random variables in both power grid networks and input leakage currents. but different from the existing hermit pc based stochastic simulation method, extended krylov subspace method (eks) is employed to compute variational responses using the augmented matrices consisting of the coefficients of hermite polynomials. our contribution lies in the combination of the statistical spectrum method with the extended krylov subspace method to fast solve the variational circuit equations for the first time. experimental results show that the proposed method is about two-order magnitude faster than the existing her-mite pc based simulation method and more order of magnitudes faster than monte carlo methods with marginal errors. stoeks also can analyze much larger circuits than the exiting hermit pc based methods.
efficient decoupling capacitance budgeting considering operation and process variations. this paper solves the variation-aware on-chip decoupling capacitance (decap) budgeting problem. unlike previous work assuming the worst-case current load, we develop a novel stochastic current model, which efficiently and accurately captures operation variation such as temporal correlation between clock cycles and logic-induced correlation between ports. the models also considers current variation due to process variation with spatial correlation. we then propose an iterative alternative programming algorithm to solve the decap budgeting problem under the stochastic current model. experiments using industrial examples show that compared with the baseline model which assumes maximum currents at all ports and under the same decap area constraint, the model considering temporal correlation reduces the noise by up to 5x, and the model considering both temporal and logic-induced correlations reduces the noise by up to 17x. compared with the model using deterministic process parameters, considering process variation (leff variation in this paper) reduces the mean noise by up to 4x and the 3&sigma; noise by up to 13x. while the existing stochastic optimization has been used mainly for process variation purpose, this paper to the best of our knowledge is the first in-depth study on stochastic optimization taking into account both operation and process variations for power network design. we convincingly show that considering operation variation is highly beneficial for power integrity optimization and this should be researched for optimizing signal and thermal integrity as well.
the fast methodology for high-speed soc/computer simulation. this paper describes the fast methodology that enables a single fpga to accelerate the performance of cycle-accurate computer system simulators modeling modern, realistic socs, embedded systems and standard desktop/laptop/server computer systems. the methodology partitions a simulator into (i) a functional model that simulates the functionality of the computer system and (ii) a predictive model that predicts performance and other metrics. the partitioning is crafted to map most of the parallel work onto a hardware-based predictive model, eliminating much of the complexity and difficulty of simulating parallel constructs on a sequential platform. fast conventions and libraries have been designed to make creating, modifying, using and measuring such simulators straightforward. we describe a prototype fast system: a full-system, rtl-level cycle-accurate-capable computer system simulator that executes the x86 isa, boots unmodified linux and executes unmodified x86 applications. the prototype runs two to three orders of magnitude faster than the fastest intel and amd rtl-level cycle-accurate x86 software-based simulators and about six to seven times faster than rtl simulation.
a nonlinear cell macromodel for digital applications. current source models have emerged as a promising technique for reducing digital cell netlists to a simpler electrical model for use in timing and other applications. the multiport current source model (mcsm) is one of the most general models in this class, which has been shown to handle multiple electrical effects including multiple-input switching (mis) events in timing. however, this new model is hampered by two major problems: port characterization runtime and accuracy across a range of complicated cells which are deployed in advanced microprocessor design such as complex combinational cells, muxes, and sequentials. in this paper we demonstrate a significant leap in modeling accuracy and characterization runtime over the mcsm model which effectively eliminates these remaining issues. the quality of the new approach is conclusively demonstrated on a comprehensive 45nm cell library currently in use. the new approach accurately models both complex combinational as well as, for the first time, sequential cells, and puts mcsms on the path for next generation gate level electrical analysis.
minimizing leakage power in sequential circuits by using mixed flip-flops. dual vt has been widely used to control leakage, while, at the same time, satisfying circuit performance. however, current approaches target the combinational circuits even though sequential elements, such as flip-flops and latches, contribute an appreciable proportion of the total leakage. the use of dual vt flip-flops is limited to circuits of large timing slack, because introducing high vt flip-flops in place of low vt ones yields abrupt change in timing. we propose mixed vt flip-flops, which are designed by using both low and high vt, but in different transistors. compared to low vt flip-flop, the mixed vt flip-flops exhibit increased delay, but either on setup time or on clock-to-q delay but not on both, while their leakage is greatly reduced. we extend the conventional sensitivity-based dual vt allocation algorithm to incorporate mixed vt flip-flops together with dual vt combinational gates. experimental results show that an average leakage saving of 31% is achieved, compared to the use of dual vt on combinational subcircuits alone. the leakage of the flip-flops themselves is cut by 57% on average.
practical method for obtaining a feasible integer solution in hierarchical layout optimization. layout optimization is a powerful technique for design migration, circuit performance tuning and design for manufacturing. in this paper, we study the problem of layout optimization for the hierarchical circuits in modern vlsi designs which essentially can be formulated as the integer linear programming(ilp) problem. existing approaches are either unable to handle hierarchy, inefficient or failing to provide the feasible integer solutions for large scale hierarchical layouts. we present a practical method, irls algorithm (iteratively rounding and lp solving) which consists of a proper rounding strategy based on the careful analysis of hierarchical layout constraints, to obtain a feasible integer solution in the constraint-based layout modification process, thus enabling efficient optimization for large scale hierarchical layouts, and specifically avoiding the need to use the general ilp solvers. experimental results demonstrate the efficiency and effectiveness of the irls algorithm. compared with the general ilp/milp solver, the irls algorithm can obtain decent results with much less runtime (speed-up ranging from 4,000x to 360,000x). compared with the two-step approach[2] on legalizing a set of large scale industry circuit layouts, the irls algorithm can provide much better solution (satisfying all abutment/alignment constraints that the two-step approach fails to meet).
impedance extraction for 3-d structures with multiple dielectrics using preconditioned boundary element method. in this paper, we present the first bem impedance extraction algorithm for multiple dielectrics. the effect of multiple dielectrics is significant and efficient modeling is challenging. however, previous bem algorithms, including fastimp and fastpep, assume uniform dielectric, thus causing considerable errors. the new algorithm introduces a circuit formulation which makes it possible to utilizes either multilayer green's function or equivalent charge method to extract impedance in multiple dielectrics. the novelty of the formulation is the reduction of the number of unknowns and the application of the hierarchical data structure. the hierarchical data structure permits efficient sparsification transformation and preconditioners to accelerate the linear equation solver. experimental results demonstrate that the new algorithm is accurate and efficient. for uniform dielectric problems, the new algorithm is one magnitude faster than fastimp, while its results differ from fastimp within 2%. for multiple dielectrics problems, its relative error with respect to hfss is below 3%.
stimulus generation for constrained random simulation. constrained random simulation is the main workhorse in today's hardware verification flows. it requires the random generation of input stimuli that obey a set of declaratively specified input constraints, which are then applied to validate given design properties by simulation. the efficiency of the overall flow depends critically on (1) the performance of the constraint solver and (2) the distribution of the generated solutions. in this paper we discuss the overall problem of efficient constraint solving for stimulus generation for mixed boolean/integer variable domains and propose a new hybrid solver based on markov-chain monte carlo methods with good performance and distribution.
operation chaining asynchronous pipelined circuits. we define operation chaining (op-chaining) as an optimization problem to determine the optimal pipeline depth for balancing performance against energy demands in pipelined asynchronous designs. since there are no clock period requirements, asynchronous pipeline stages can have non-uniform latencies. we exploit this fact to coalesce several stages together thereby saving power and area due to the elimination of control-path resources from the pipeline. the trade-off is potentially reduced pipeline parallelism. in this paper, we formally define this optimization as a graph covering problem, which finds sub-graphs that will be synthesized as an opchained pipeline stage. we then define the solution space for provably correct solutions and present an algorithm to efficiently search this space. the search technique partitions the graph based on post-dominator relationships to find sub-graphs that are potential op-chain candidates. we use knowledge of the global critical path (gcp) [13] to evaluate the performance impact of accepting a candidate sub-graph and formulate a heuristic cost function to model this trade-off. the algorithm has a quadratic-time complexity in the size of the dataflow graph. we have implemented this algorithm within an automated asynchronous synthesis toolchain [12]. experimental evidence from applying the algorithm on several media processing kernels reveals that the average energy-delay and energy-delay-area products improve by about 1.4x and 1.8x respectively, with a maximum improvement of 5x and 18x.
a novel intensity based optical proximity correction algorithm with speedup in lithography simulation. it is important to reduce the optical proximity correction (opc) runtime while maintaining a good result quality. in this paper, we obtain a better formula, which theoretically speeds up the widely used method, optimal coherent approximations (oca's), by a factor of 2x. we speed up the opc algorithm further by making it intensity based (ib-opc), because it requires much less intensity simulations than the conventional edge placement error (epe) based opc algorithms. in addition, the ib-opc algorithm, which uses the efficiently computed sensitivity information, converges faster than the epe based opc. our ib-opc experimental results show a runtime speedup of up to 15x with a comparable result quality as of the epe based opc.
low-overhead design technique for calibration of maximum frequency at multiple operating points. determination of maximum operating frequencies (fmax) during manufacturing test at different operating voltages is required to: (a) to ensure that, for a dynamic voltage and frequency scaling (dvfs) system, the adaptation hardware actually applies the correct operating frequency corresponding to a scaled supply and (b) to sort chips in different voltage-frequency (v-fmax)bins, so that chips at different bins can be used for different applications. existing speed binning approach requires extensive delay testing at all operating points with all possible frequencies, which increases test cost and test time significantly. in this paper, we propose a low-overhead solution for characterizing fmax of a circuit at different operating voltages that can eliminate the complex and expensive fmax calibration at multiple voltage points. the basic idea is to choose a small set of representative paths in a circuit based on their voltage sensitivity and dynamically configuring them into ring oscillator to compute the fmax. the proposed calibration mechanism is all-digital, robust to process variations, reasonably accurate (average 2.8% error) and incorporates minimal hardware overhead (average 1.7% delay, 3.5% area and 0.28% power overhead).
a robust finite-point based gate model considering process variations. this paper proposes a robust gate model based on a finite-point modeling scheme. with current source model (csm) framework, a robust, finite-point gate model is constructed. the new model depends on the selective points of i-v curves of gates. thus, it implicitly incorporates the variation related parameters into finite points. in addition, to provide good accuracy on output waveform, the new model creates the input and output capacitance elements as nonlinear dependency on input/output waveform and process variation parameters. experimental results show that the generated gate model has less than 3.7% error at mean, less than 6.2% error at variance and less than 5.8% at 90% percentile for cumulative density functions (cdfs).
mc-sim: an efficient simulation tool for mpsoc designs. the ability to integrate diverse components such as processor cores, memories, custom hardware blocks and complex network-on-chip (noc) communication frameworks onto a single chip has greatly increased the design space available for system-on-chip (soc) designers. efficient and accurate performance estimation tools are needed to assist the designer in making design decisions. in this paper, we present mc-sim, a heterogeneous multi-core simulator framework which is capable of accurately simulating a variety of processor, memory, noc configurations and application specific coprocessors. we also describe a methodology to automatically generate fast, cycle-true behavioral, c-based simulators for coprocessors using a high-level synthesis tool and integrate them with mc-sim, thus augmenting it with the capacity to simulate coprocessors. our c-based simulators provide on an average 45x improvement in simulation speed over that of rtl descriptions. we have used this framework to simulate a number of real-life applications such as the mpeg4 decoder and litho-simulation, and experimented with a number of design choices. our simulator framework is able to accurately model the performance of these applications (only 7% off the actual implementation) and allows us to explore the design space rapidly and achieve interesting design implementations
including inductance in static timing analysis. in this paper analytical expressions are derived for effective load capacitances of rlc interconnects to accurately estimate both the propagation delay and transition time at the output of a cmos gate. the new effective capacitance calculation technique poses no extra complexity as compared to the rc based approaches but can accommodate inductance. these new expressions are derived based on a generalized driving point admittance. the generalized driving point admittance takes inductance into consideration and hence accounts for the inductive shielding that in some cases can even exceed the resistive shielding in current technologies. another improvement in the new effective capacitance calculation method is the utilization of a more general waveform shape that accounts for the non-monotonic behavior due to inductance effects. it is shown throughout the paper that two effective capacitances are required for accurate estimation of the propagation delay and rise time with an rlc interconnect load. simulation results show that the error in propagation delays and rise times when neglecting inductance can be over 60% as compared to an rlc model in realistic interconnects. on the other hand, simulations show that the propagation delay and rise time maximum errors associated with the proposed approach are less than 10% as compared to spice.
frequency-aware ppv: a robust phase macromodel for accurate oscillator noise analysis. perturbation projection vector (ppv) is an established technique for oscillator phase noise analysis; however, the ppv method significantly loses accuracy when circuits have large time constants, resulting in over-estimation of oscillator phase noise. in this paper, we show the problem of the ppv phase equation that it ignores the dynamics of oscillator frequency responses, and propose an improved ppv technique: frequency-aware ppv (fw-ppv). using the fw-ppv technique, we derive analytical phase noise equations, which work accurately for all oscillators, especially for oscillators with large time constants. we apply the proposed technique on real oscillator circuits, and compare the results to cadence spectre rf. simulation results show that our method has better accuracy than previous approaches.
sparse and passive reduction of massively coupled large multiport interconnects. the large number of ports in an interconnect structure is a critical limiting factor when applying model-order reduction. this is due to the fact that the size of the reduced model grows rapidly with increasing the number of ports, leading to large and dense circuit matrices. to address this problem, a novel method based on transverse partitioning and waveform relaxation is proposed for passive model-order reduction of massively coupled large multiport interconnects. the new method effectively replaces the tightly coupled multiport reduced model with decoupled 2-port subcircuits. in addition to preserving the advantages of model-order reduction, the computational complexity of the new method grows only linearly with the number of lines.
the analysis of cyclic circuits with boolean satisfiability. the accepted wisdom is that combinational circuits must have acyclic (i.e., loop-free or feed-forward) topologies. and yet simple examples suggest that this need not be so. in previous work, we advocated the design of cyclic combinational circuits (i.e., circuits with loops or feedback paths). we proposed a synthesis methodology and demonstrated that it produces significant improvements in area and in delay. the analysis method that we used to validate cyclic circuits was based on binary decision diagrams. in this paper, we propose a much more efficient technique for analysis based on boolean satisfiability (sat).
a fast band-matching technique for interconnect inductance modeling. sparsification of the inverse of inductance matrix l has been widely used to facilitate the interconnect simulation. the band-matching proposed in [5] was proven to be stable and optimal. however, the technique in [5] exhibits a cubic computation complexity. in this paper, we reveal additional relationship between the entries in band-matching inductance matrices. we propose a fast technique that can calculate the entries in the band-matching approximation, in linear computational time. experiments show accurate results for proposed method with orders of magnitude improvement in computational time.
an efficient algorithm for statistical circuit optimization using lagrangian relaxation. due to the technology scaling down, process variation has become a crucial challenge on both interconnect delay and reliability. to handle the process variation, statistical optimization has emerged as a popular technique for yield improvement. as a relatively new technique, second-order conic programming (socp) has recently attracted very much attention in the literature for statistical circuit optimization. however, we observe significant limitations of socp in its flexibility, accuracy, and scalability for statistical circuit optimization, especially when interconnects are considered. we thus present in this paper an effective and efficient alternative for multi-constrained statistical circuit optimization by both gate and wire sizing using lagrangian relaxation (lr). compared with socp, experimental results show that our lr-based algorithm can achieve much better solution quality by reducing 21% area and obtain 560x speed-up over socp.
modeling, optimization and control of rotary traveling-wave oscillator. rotary traveling-wave oscillator (rtwo) is a recently proposed transmission-line approach for multi-gigahertz rate clock generation. rtwo has the characteristics of both conventional lc tank oscillator and ring oscillator. thus, it is difficult to be analyzed by a general-purpose method. this paper presents a systematic and efficient method for rtwo modeling and optimization. equations for frequency, power dissipation, die area, loop gain and phase noise are formulated in posynomial forms. the resulting optimization problem is relaxed to be a geometric programming (gp) and can be efficiently solved with a convex optimization solver. a novel scheme to control the rotation direction is also suggested for skew control. experimental results show that our method can rapidly compute the globally optimal trade-off and reduce the power by up to 85% for a 11.8 ghz rtwo design. compared to a recently reported low-power methodology, the proposed design scheme can save about 50% of die area and achieve lower power dissipation as well as faster rise/fall time.
on the numbers of variables to represent sparse logic functions. in an incompletely specified function f, don't care values can be chosen to minimize the number of variables to represent f. it is shown that, in incompletely specified functions with k 0's and k 1's, the probability that f can be represented with only p = 2[log2(k + 1)] variables is greater than e-1 = 0.36788. in the case of multiple-output functions, where only the outputs for k input combinations are specified, most functions can be represented with at most p = 2[log2(k+1)] -1 variables. experimental data is shown to support this. because of this property, an ip address table can be realized with a small amount of memory.
voltage island-driven floorplanning. energy efficiency has become one of the most important issues to be addressed in today's system-on-a-chip (soc) designs. one way to lower the power consumption is to reduce the supply voltage. multi-supply voltage (msv) is thus introduced to provide higher flexibility in controlling the power and performance trade-off. in region-based msv, circuits are partitioned into "voltage islands" where each island occupies a contiguous physical space and operates at one supply voltage. these tasks of island partitioning and voltage level assignments should be done simultaneously in the floorplanning process in order to take those important physical information into consideration. in this paper, we consider this core-based voltage island driven floorplanning problem including islands with power down mode, and propose a method to solve it. given a candidate floorplan solution represented by a normalized polish expression, we are able to obtain optimal voltage assignment and island partitioning (including islands with power down mode) simultaneously to minimize the total power consumption. simulated annealing is used as the basic searching engine. by using this approach, we can achieve significant power savings (up to 50%) for all data sets, without any significant increase in area and wire length. our floorplanner can also be extended to minimize the number of level shifters between different voltage islands and to simplify the power routing step by placing the islands in proximity to the corresponding power pins.
on the decreasing significance of large standard cells in technology mapping. technology scaling reduces gate delays while wire delays may increase. our work studies the interaction of this phenomenon with technology mapping and its impact on modern eda flows. in particular, we demonstrate that the use of larger standard cells increases the number of long wires and may undermine circuit delay optimization at 65nm and below. experiments with 130nm, 90nm, 65nm, and 45nm industrial cmos technology suggest that limiting the use of larger standard cells in technology mapping becomes more effective at 65nm and 45nm node, resulting in up to 12% improvement in critical path delay on large benchmark circuits.
enhancing design robustness with reliability-aware resynthesis and logic simulation. while circuit density and power efficiency increase with each major advance in ic technology, reliability with respect to soft errors tends to decrease. current solutions to this problem such as tmr require high area and power overhead. in this work, soft-error reliability is improved with minimal area overhead by careful, localized circuit restructuring. the key idea is to increase logic masking of errors by taking advantage of conditions already present in the circuit, such as observability don't-cares. we describe two circuit modification techniques to improve reliability: don't-care-based resynthesis and local rewriting. a key feature of these techniques is fast, on-the-fly estimation of soft error rate (ser) using our reliability evaluator anser. this tool is compared against prior ser evaluators and found to run orders of magnitude faster. we show empirically that our reliability-driven synthesis methods can reduce ser by 29--40% with only 5--13% area overhead.
network flow-based power optimization under timing constraints in msv-driven floorplanning. power consumption has become a crucial problem in modern circuit design. multiple supply voltage (msv) design is introduced to provide higher flexibility in controlling the power and performance tradeoff. one important requirement of msv design is that timing constraints of the circuit must be satisfied after voltage assignment of the cells. in this paper, we will show that the voltage assignment task on a given netlist can be formulated as a convex cost dual network flow problem and can be solved optimally in polynomial time using a cost-scaling algorithm when the delay choices of each module are continuous in the real or integer domain. we can make use of this approach to obtain a feasible voltage assignment solution in the general cases with power consumption approximating the minimum one. furthermore, we will propose a framework to optimize power consumption and physical layout of a circuit simultaneously during the floorplanning stage, by embedding this cost-scaling solver into a simulated annealing based floorplanner. this is effective in practice due to the short running time of the solver. we compared our approach with the latest work [9] on the same problem, and the experimental results show that, using our framework, significant improvement on power saving (18% less power cost on average) can be achieved in much less running time (7x faster on average) for all the test cases, which confirms the effectiveness of our approach.
an ilp algorithm for post-floorplanning voltage-island generation considering power-network planning. power optimization is a crucial concern for modern circuit designs. multiple supply voltages (msv's) provide an effective technique for the power optimization. this paper addresses the voltage-island generation problem for msv designs at the post-floorplanning stage. we first present a general formulation of this problem that considers level-shifter planning and power-network routing resources. without loss of solution quality, we propose an economical graph-based representation that needs only a linear number of nodes to the block number to model the block adjacency in a floorplan for the voltage-island generation. in contrast, previous works need a quadratic number of nodes. to tackle the addressed problem, we employ an ilp formulation which consists of (1) level-shifter aware wirelength estimation to capture the timing overhead, (2) voltage-island-clustering inequalities to avoid complicated constraint transformations, and (3) inequalities to capture the power-network routing-resource usage. compared with previous works, our algorithm can produce better voltage islands in terms of power-network routing resources. experimental results show that our algorithm can effectively reduce the power-network routing resource by up to 19.46% with a reasonable overhead of 4.03% more power consumption and using reasonable running time.
archer: a history-driven global routing algorithm. global routing is an important step in the physical design process. in this paper, we propose a new global routing algorithm archer, which resolves some of the most common problems with the state-of-the-art global routers. it is known that concurrent global routing algorithms are typically too expensive to be applied on today's large designs, which may contain up to a million nets. on the other hand, iterative rip-up and reroute (rnr) based algorithms are susceptible to getting stuck in local optimal solutions. in this paper, we propose an rnr-based global routing algorithm that guides the routing iterations out of local optima through effective usage of congestion histories. we also focus on the problem of how to enable a smooth trade-off between seemingly conflicting objectives of overflow and wirelength minimization. furthermore, we propose a lagrangian relaxation based bounded-length min-cost topology improvement algorithm that enables steiner trees to change dynamically for the purpose of congestion optimization. our experiments show that archer obtains congestion-free solutions for all circuits in the standard ispd98 benchmarks, which is the best result published so far. furthermore, it produces better results than the best results reported in the ispd-07 global routing contest in terms of routability. compared to fastroute [18, 19], which is the state-of-the-art rnr-based global routing algorithm, archer improves routability by 30%, and reduces the wirelengths by 32% on the average on ispd07 benchmarks.
bounding l2 gain system error generated by approximations of the nonlinear vector field. typical nonlinear model order reduction approaches need to address two issues: reducing the order of the model, and approximating the vector field. in this paper we focus exclusively on the second issue, and present results characterizing the repercussions at the system level of vector field approximations. the error assessment problem is formulated as the l2 gain upper bounding problem of a scaled feedback interconnection. applying the small gain theorem in the proposed setup, we prove that the l2 gain of the error system is upper bounded by the l2 gain of the vector field approximation error, provided it is small. in addition, the paper also presents a numerical procedure, based on the iqc/lmi approach, to perform the error estimation task with less conservatism. a numerical example is given in this paper to demonstrate the practical implications of the presented results.
sensitivity analysis for oscillators. this paper presents an analysis for calculating sensitivities of an oscillator's periodic steady-state and perturbation projection vector to design, process, or environmental parameters. a general continuous-time formulation is described. applications of the oscillator sensitivity analysis in design optimization and macromodeling are demonstrated through examples.
what can brain researchers learn from computer engineers and vice versa? the human brain is a network containing a hundred billion neurons, each communicating with several thousand others. as the wiring for neuronal communication draws on limited space and energy resources, evolution had to optimize their use. this principle of minimizing wiring costs, similar to that in computer design, explains many features of brain architecture, including placement and shape of many neurons. however, the shape of some neurons and their synaptic properties remained unexplained. this led us to the principle of maximization of brain's ability to store information. combination of the two principles provides a systematic view of brain architecture, necessary to explain brain function. it would be interesting to see whether advances in understanding brain function will make impact on computer design. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
parallel domain decomposition for simulation of large-scale power grids. this paper presents fully parallel domain decomposition (dd) techniques for efficient simulation of large-scale linear circuits such as power grids. dd techniques that use non-overlapping and overlapping partitioning of power grids are described in this paper. simulation results show that with the proposed parallel dd framework, existing linear circuit simulators can be extended to handle large-scale power grids. results for circuits with more than four million nodes indicate that parallel dd with lu factorization is most suitable for power grid simulation. however, for densely connected power grids, parallel dd with additive schwarz preconditioning offers maximum scalability and best performance.
analysis and optimization of power-gated ics with multiple power gating configurations. power gating is an efficient technique for reducing leakage power in electronic devices by disconnecting blocks idle for long periods of time from the power supply. disconnecting gated blocks causes changes in densities of currents flowing through a grid. even in dc conditions, current densities in some grid branches may increase for some gating configurations to the extent of violating electromigration (em) constraints. the existing dc methods for grid sizing optimize the grid area under voltage drop (ir) and em constraints for one configuration of circuit blocks connected to the grid. we show that these methods cannot be directly applied for optimizing power-gated grids. we analyze the effects of em and ir voltage drop in power grids with multiple power gating configurations. based on our analyses, we develop a grid sizing algorithm to satisfy all reliability constraints for all feasible gating configurations. our experimental results indicate that a grid initially sized for all blocks present may be modified to fulfill em and ir constraints for multiple gating schedules with only a small area increase.
exploiting hierarchy and structure to efficiently solve graph coloring as sat. many important eda problems can be formulated as graph coloring, which is a class of the constraint satisfaction problem (csp). this paper makes three contributions. first, we define new encodings for representing csps as equivalent boolean satisfiability (sat) problems: 1) a generalization of the log encoding by using ite trees to select the domain values of a csp variable, so that only conflict clauses are required; and 2) a simplified direct encoding, derived from the direct encoding (where each domain value of a csp variable is indexed by a unique boolean variable) by omitting one of the boolean variables and the at-least-one clause. second, we propose the use of hierarchical encodings that combine several simple encodings to index the domain values of csp variables, in order to produce sat formulas that depend on fewer boolean variables and are easier to solve. third, we study schemes for static ordering of the boolean variables in a conjunctive normal form (cnf) representation of a csp, based on the structure of the csp graph, such that the resulting variable order is used for the decisions made by a sat solver when evaluating the cnf. we compare 12 previously known sat encodings for csp with the two new encodings, as well as with 10 hybrid encodings. with symmetry-breaking constraints enforced, static variable ordering produced up to 2 orders of magnitude speedup. additionally exploiting hierarchical encodings resulted in another order of magnitude speedup.
simultaneous input vector selection and dual threshold voltage assignment for static leakage minimization. dual vt assignment and input vector control are two tightly coupled leakage reduction techniques. we study how to apply them effectively to a circuit to minimize the static leakage power. we argue that simply combining them in a serial fashion will not reach their full potential in leakage reduction. to show this, we propose a heuristic algorithm that integrates them into a single optimization loop by assigning the value for primary inputs and vt for logic gates simultaneously. our algorithm leverages the fact that both input vector and threshold voltage vt have great impact on a gate's leakage at standby mode and avoids to assign a gate both low vt and input vector that results high leakage. the selection of input vector and the assignment of vt are integrated seamlessly through the concepts of leakage observability, worst leakage state, and path factor. the proposed algorithm has a low run time complexity and achieves an average 15% leakage reduction on all the iscas and mcnc benchmarks over the serial combination of input vector selection and dual vt assignment.
bioroute: a network-flow based routing algorithm for digital microfluidic biochips. due to the recent advances in microfluidics, digital microfluidic biochips are expected to revolutionize laboratory procedures. one critical problem for biochip synthesis is the droplet routing problem. unlike traditional vlsi routing problems, in addition to routing path selection, the biochip routing problem needs to address the issue of scheduling droplets under the practical constraints imposed by the fluidic property and the timing restriction of the synthesis result. in this paper, we present the first network-flow based routing algorithm that can concurrently route a set of non-interfering nets for the droplet routing problem on biochips. we adopt a two-stage technique of global routing followed by detailed routing. in global routing, we first identify a set of non-interfering nets and then adopt the network-flow approach to generate optimal global-routing paths for the nets. in detailed routing, we present the first polynomial-time algorithm for simultaneous routing and scheduling using the global-routing paths with a negotiation-based routing scheme. the experimental results show the robustness and efficiency of our algorithm.
performance estimation and slack matching for pipelined asynchronous architectures with choice. this paper presents a fast analytical method for estimating the throughput of pipelined asynchronous systems, and then applies that method to develop a fast solution to the problem of pipelining "slack matching." the approach targets systems with hierarchical topologies, which typically result when high-level (block structured) language specifications are compiled into data-driven circuit implementations. a significant contribution is that our approach is the first to efficiently handle architectures with choice (i.e., the presence of conditional computation constructs such if-then-else and conditional loops). the key idea behind the fast speed of our analysis method is to exploit information about the hierarchy of a given block-structured system, thereby yielding a runtime that is linear in the number of pipeline stages. in contrast, existing approaches typically represent an entire system as a single petri net or marked graph, and then apply markov chain analysis or other state enumeration methods with costly runtimes. building upon our analysis approach, we introduce a novel solution to the problem of slack matching, i.e., determining optimal insertion of fifo stages into a pipelined design to improve performance. we present both an optimal solution using an milp formulation, and a fast heuristic algorithm that yielded optimal results for all of our examples.
the effect of process variation on device temperature in finfet circuits. with technology scaling, devices are increasingly prone to process variations. these variations cause a large spread in leakage power, since it is extremely sensitive to process variations, which in turn results in larger temperature variations across different dies. in this paper, we investigate the temperature variations in finfet circuits considering variations in following parameters (i) channel length and (ii) body thickness. we estimate temperature variation under process fluctuation by monte carlo simulation with thermal models to solve temperature and leakage power self-consistently. the results show that high activity circuits exhibit larger temperature variations since increased temperature increments leakage power and vice versa. it is also shown that under moderate process variation (3&sigma;=10% for channel length and body thickness) and a nominal primary input activity of 0.4, thermal runaway can occur in more than 15% of chips in 28nm finfet technology, severely degrading manufacturing yield.
compact modeling of variational waveforms. in ultra-deep sub-micron technologies, modeling waveform shapes correctly is essential for accurate timing and noise analysis. due to process and environmental variations, there is a need for a variational waveform model that is compact, efficient and accurate. the model should capture correlations due to common dependence on process parameters. this paper proposes a waveform model derived from basic transformations of a nominal waveform in the absence of variations. the transformations are parameterized by variational quantities that capture the sensitivity of the waveform to process parameters. the resulting waveform model works well with current-source models for static timing analysis. numerical results are presented to demonstrate the accuracy of the model both in capturing variational waveforms and in propagating waveforms through logic gates.
guaranteed stable projection-based model reduction for indefinite and unstable linear systems. in this work we present a stability-preserving projection framework for model reduction of linear systems. specifically, given one projection matrix (e.g. a right-projection matrix), we derive a set of linear constraints for the other projection matrix (e.g. the left-projection matrix) resulting in a projection framework that is guaranteed to generate a stable reduced model. several efficient techniques for solving the proposed system of constraints are presented, including an optimization problem formulation for finding the optimal stabilizing projection, and a formulation with computational complexity independent of the size of the original system. the resulting algorithms can create accurate stable and passive models of arbitrary indefinite systems at a significantly cheaper cost than existing methods such as balanced truncation. nevertheless, our algorithms integrate fully and effortlessly with most of the available standard model order reduction approaches for very large systems generated in vlsi applications (such as moment-matching methods, pod, or poor man's tbr), which can guarantee stability and passivity only in very specialized cases. our algorithms have been tested on a large variety of typical vlsi applications, including field-solver-extracted models of rf inductors for analog applications, power distribution grids for large vlsi digital integrated circuits, and mems devices for sensing and actuation applications. the results have been successfully compared to those from existing and much more expensive stabilizing reduction techniques.
a performance-driven qbf-based iterative logic array representation with applications to verification, debug and test. many cad for vlsi techniques use time-frame expansion, also known as the iterative logic array representation, to model the sequential behavior of a system. replicating industrial-size designs for many time-frames may impose impractically excessive memory requirements. this work proposes a performance-driven, succinct and parametrizable quantified boolean formula (qbf) satisfiability encoding and its hardware implementation for modeling sequential circuit behavior. this encoding is then applied to three notable cad problems, namely bounded model checking (bmc), sequential test generation and design debugging. extensive experiments on industrial circuits confirm outstanding run-time and memory gains compared to state-of-the-art techniques, promoting the use of qbf in cad for vlsi.
incremental learning approach and sat model for boolean matching with don't cares. in this paper, we will propose an incremental learning approach to solve boolean matching for incompletely specified functions. this approach can incrementally analyze current feasible partial mappings, detect and eliminate redundant manipulations in a proactive way. a new type of signature exploiting single variable symmetries is also given to reduce the searching space. moreover, a sat model of boolean matching will be proposed to handle large boolean functions. through the utilization of these novel mechanisms, a drastic improvement on the performance of our boolean matching algorithms are achieved. the experimental results demonstrate the effectiveness and efficiency of the proposed learning-based and sat-based boolean matching algorithms on many large benchmarking circuits.
accurate detection for process-hotspots with vias and incomplete specification. this paper introduces the concept of via range patterns and incompletely specified range patterns to represent new types of process-hotspots. via range patterns can represent process-hotspots containing vias that are a major source of lithography issues. an incompletely specified range pattern can accurately and succinctly represent a process-hotspot where any configuration of objects (that is unknown to the user apriori) can exist in some of its peripheral regions. these new types of range patterns cannot be accurately represented and/or detected using the concept of range patterns introduced in [7]. a new detection algorithm that can accurately detect these new types of patterns is also proposed. this is necessitated since the range pattern matching algorithm proposed earlier causes mismatches: it either misses true matches or reports false matches for these new kinds of patterns. theoretical results show that the proposed algorithm prevents the incorrect mis-match issues, while experimental results on fab provided process-hotspots show the algorithm is computationally efficient and practical for use on real industrial designs.
accurate energy breakeven time estimation for run-time power gating. run-time power gating (rtpg) is a recent technique, which aims at aggressively reducing leakage power consumption. energy breakeven time (ebt), or equivalent sleep time has been proposed as a critical figure of merit of rtpg. our research introduces the definition of average ebt in a run-time environment. we develop a method to estimate the average ebt for any given circuit block, considering the impact of circuit states. hspice simulation results on iscas85 benchmark circuits show that the average ebt model has on the average 1.8% error. the cad tool implemented based on the model can perform fast estimations with a speedup of 3000 x over hspice.
design methodology to trade off power, output quality and error resiliency: application to color interpolation filtering. power dissipation and tolerance to process variations pose conflicting design requirements. scaling of voltage is associated with larger variations, while vdd up-scaling or transistor up-sizing for process tolerance can be detrimental for power dissipation. however, for certain signal processing systems such as those used in color image processing, we noted that effective trade-offs can be achieved between vdd scaling, process tolerance and "output quality". in this paper we demonstrate how these tradeoffs can be effectively utilized in the development of novel low-power variation tolerant architectures for color interpolation. the proposed architecture supports a graceful degradation in the psnr (peak signal to noise ratio) under aggressive voltage scaling as well as extreme process variations in sub-70nm technologies. this is achieved by exploiting the fact that some computations are more important and contribute more to the psnr improvement compared to the others. the computations are mapped to the hardware in such a way that only the less important computations are affected by vdd-scaling and process variations. simulation results show that even at a scaled voltage of 60% of nominal vdd value, our design provides reasonable image psnr with 69% power savings.
selective shielding: a crosstalk-free bus encoding technique. with cmos process technology scaling to deep submicron level, propagation delay across long on-chip buses is becoming one of the main performance limiting factors in high-performance designs. propagation delay is very significant when adjacent wires are transitioning in opposite direction (i.e., crosstalk transitions) as compared to transitioning in the same direction. as crosstalk transitions have significant impact on propagation delay, several bus encoding techniques have been proposed in literature to eliminate such transitions. in this work, we propose a technique, namely, selective shielding, to eliminate crosstalk transitions. compared to the conventional shielding technique, our technique significantly reduces the number of extra wires. we give a lower bound on the number of wires required to encode n-bit data using the selective shielding technique. we show that our technique achieves better energy savings and requires less area as compared to the other techniques.
early planning for clock skew scheduling during register binding. design decisions made during high-level synthesis usually have great impacts on the later design stages. in this paper, we present a general framework, which plans for the clock skew scheduling in physical design stages during register binding in high-level synthesis. our proposed technique pursues the optimality of the native objective functions of the register binding problem. at the same time, it ensures not invalidating the subsequent clock skew scheduling for optimizing the clock period. we use the switching power as the native objective of our register binding problem. the problem is first formulated as a milp problem. an acceleration scheme based on the concept of weakly compatible edge set(wces) is proposed to speed up the milp solver to obtain the optimal solution. then, we present our heuristic algorithm to reduce the running time further. the experimental results show that on average our acceleration scheme can speed up the solver by 8.6 times, and our heuristic is 70 times faster than the solver with a 5.25% degradation of the native objective. the minimum and maximum degradation among our benchmark set are 0.82% and 12.2% respectively.
computation of minimal counterexamples by using black box techniques and symbolic methods. computing counterexamples is a crucial task for error diagnosis and debugging of sequential systems. if an implementation does not fulfill its specification, counterexamples are used to explain the error effect to the designer. in order to be understood by the designer, counterexamples should be simple, i.e. they should be as general as possible and assign values to a minimal number of input signals. here we use the concept of black boxes --- parts of the design with unknown behavior --- to mask out components for counterexample computation. by doing so, the resulting counterexample will argue about a reduced number of components in the system to facilitate the task of understanding and correcting the error. we introduce the notion of 'uniform counterexamples' to provide an exact formalization of simplified counterexamples arguing only about components which were not masked out. our computation of counterexamples is based on symbolic methods using aigs (and-inverter-graphs). experimental results using a vliw processor as a case study clearly demonstrate our capability of providing simplified counterexamples.
gate sizing by lagrangian relaxation revisited. in this paper, we formulate the generalized convex sizing (gcs) problem that unifies and generalizes the sizing problems. we revisit the approach to solve the sizing problem by lagrangian relaxation, point out several misunderstandings in the previous works, and extend the approach to handle general convex delay functions in the gcs problems. we identify a class of proper gcs problems whose objective functions in the simplified dual problem are differentiable and show many practical sizing problems, including the simultaneous sizing and clock skew optimization problem, are proper. we design an algorithm based on the method of feasible directions to solve proper gcs problems. the algorithm will provide evidences for infeasible gcs problems according to a condition derived by us. experimental results confirm the efficiency and the effectiveness of our algorithm when the elmore delay model is used.
thermalscope: multi-scale thermal analysis for nanometer-scale integrated circuits. thermal analysis has long been essential for designing reliable, high-performance, cost-effective integrated circuits (ics). increasing power densities are making this problem more important. characterizing the thermal profile of an ic quickly enough to allow feedback on the thermal effects of tentative design changes is a daunting problem, and its complexity is increasing. the move to nanoscale fabrication processes is increasing the importance of quantum thermal phenomena such as ballistic phonon transport. accurate thermal analysis of nanoscale ics containing hundreds of millions of devices requires characterization of thermal effects on length scales that vary by several orders of magnitude, from nanoscale quantum thermal effects to centimeter-scale cooling package impact. existing chip-package thermal analysis methods based on classical fourier heat transfer cannot capture nanoscale quantum thermal effects. however, accurate device-level modeling techniques, such as molecular dynamics methods, are far too slow for use in full-chip ic thermal analysis. in this work, we propose and develop thermalscope, a multi-scale thermal analysis method for nanoscale ic design. it unifies microscopic and macroscopic thermal physics modeling methods, i.e., the fourier and boltzmann transport modeling methods. moreover, it supports adaptive multi-resolution modeling. together, these ideas enable efficient and accurate characterization of nanoscale quantum heat transport as well as chip-package level heat flow. thermalscope is designed for full-chip thermal analysis of billion-transistor nanoscale ic designs, with accuracy at the scale of individual devices. thermalscope enables accurate characterization of temperature-related effects, such as variation in leakage power and delay. thermalscope has been implemented in software and used for full-chip thermal analysis and temperature-dependent leakage analysis of an ic design with more than 150 million transistors. it will be publicly released for free academic and personal use.
equalized interconnects for on-chip networks: modeling and optimization framework. this paper presents a modeling framework for fast design space exploration and optimization of equalized on-chip interconnects. the exploration is enabled by cross-layer modeling that connects the transistor and wire parameters to link performance, equalization coefficients, and architecture-friendly metrics (delay, energy-per-bit, and throughput density). appropriate models are derived to speed-up the search by more than two orders of magnitude and make a million point design space searchable in less than two hours on a standard machine. with this approach we are able to find the best link design for target throughput, power and area constraints, thus enabling the architectural optimization of energy-efficient on-chip networks. for the same latency and throughput density, equalized interconnects optimized using the new methodology have up to 10x better energy-efficiency than optimized repeater interconnects.
multi-layer global routing considering via and wire capacities. global routing for modern large-scale circuit designs has attracted much attention in the recent literature. most of the state-of-the-art academic global routers just work on a simplified routing congestion model that ignores the essential via capacity for routing through multiple metal layers. such a simplified model would easily cause fatal routability problems in subsequent detailed routing. to remedy this deficiency, we present in this paper a more effective congestion metric that considers both the in-tile nets and the residual via capacity for global routing. with this congestion metric, we develop a new global router that features two novel routing algorithms for congestion optimization, namely least-flexibility-first routing and multi-source multi-sink escaping-point routing. the least-flexibility-first routing processes the nets with the least flexibility first, facilitating a quick prediction of congestion hot spots for the subsequent nets. enjoying lower time complexity than traditional maze and a*-search routing, in particular, the linear-time escaping-point routing guarantees to find the optimal solution and achieves the theoretical lower-bound time complexity. experimental results show that our global router can achieve very high-quality routing solutions with more reasonable via usage, which can benefit and correctly guide subsequent detailed routing.
soft-edge flip-flops for improved timing yield: design and optimization. parameter variations cause high yield losses due to their large impact on circuit delay. in this paper, we propose the use of so-called soft-edge flip-flops as an effective way to mitigate these yield losses. soft-edge flip-flops have a small window of transparency (ranging from 0.25-3 fo4) instead of a hard edge, allowing limited cycle stealing on critical paths, and thus compensating for delay variations. by enabling time borrowing, soft-edge flip-flops allow random delay variations to average out across multiple logic stages. in addition, they address small amounts of delay imbalance between logic stages, further maximizing the frequency of operation. we develop a library of soft-edge flip-flops with varying amounts of softness. we show that the power and area overhead of soft-edge flip-flops grows directly with the amount of softness. we then propose a statistically aware flip-flop assignment algorithm that maximizes the gain in timing yield while minimizing the incurred power overhead. experimental results on a wide range of benchmark circuits show that the proposed approach improves the mean delay by 1.9--22.3% while simultaneously reducing the standard deviation of delay by 1.9--24.1% while increasing power by a small amount (0.3--2.8%).
monte-carlo driven stochastic optimization framework for handling fabrication variability. increasing effects of fabrication variability have inspired a growing interest in statistical techniques for design optimization. in this work, we propose a monte-carlo driven stochastic optimization framework that does not rely on the distribution of the varying parameters (unlike most other existing techniques). stochastic techniques like successive sample mean optimization (ssmo) and stochastic decomposition present a strong framework for solving linear programming formulations in which the parameters behave as random variables. we consider binning-yield loss (byl) as the optimization objective and show that we can get a provably optimal solution under a convex byl function. we apply this framework for the mtcmos sizing problem [21] using ssmo and stochastic decomposition techniques. the experimental results show that the solution obtained from stochastic decomposition based framework had 0% yield-loss, while the deterministic solution [21] had a 48% yield-loss.
variable domain transformation for linear pac analysis of mixed-signal systems. this paper describes a method to perform linear ac analysis on mixed-signal systems which appear strongly nonlinear in the voltage domain but are linear in other variable domains. common circuits like phase/delay-locked loops and duty-cycle correctors fall into this category, since they are designed to be linear with respect to phases, delays, and duty-cycles of the input and output clocks, respectively. the method uses variable domain translators to change the variables to which the ac perturbation is applied and from which the ac response is measured. by utilizing the efficient periodic ac (pac) analysis available in commercial rf simulators, the circuit's linear transfer function in the desired variable domain can be characterized without relying on extensive transient simulations. furthermore, the variable domain translators enable the circuits to be macromodeled as weakly-nonlinear systems in the chosen domain and then converted to voltage-domain models, instead of being modeled as strongly-nonlinear systems directly.
slot allocation using logical networks for tdm virtual-circuit configuration for network-on-chip. configuring time-division-multiplexing (tdm) virtual circuits (vcs) for network-on-chip must guarantee conflict freedom for overlapping vcs besides allocating sufficient time slots to them. these requirements are fulfilled in the slot allocation phase. in the paper, we define the concept of a logical network (ln). based on this concept, we develop and prove theorems that constitute sufficient and necessary conditions to establish conflict-free vcs. using these theorems, slot allocation for vcs becomes a procedure of computing lns and then assigning vcs to different lns. tdm vc configuration can thus be predictable and correct-by-construction. we have integrated this slot allocation method into our multi-node vc configuration program and applied the program to an industrial application.
analysis of large clock meshes via harmonic-weighted model order reduction and port sliding. clock meshes posses inherent low clock skews and excellent immunity to pvt variations, and have increasingly found their way to high-performance ic designs. however, analysis of such massively coupled networks is significantly hindered by the sheer size of the network and tight coupling between non-tree interconnects and large numbers of clock drivers. the presented harmonic-weighted model order reduction algorithm is motivated by the key observation of the steady-state operation of the clock networks, and its efficiency is facilitated by the locality analysis via port sliding. the scalability of the analysis is significantly improved by eliminating the need of computing infeasible multi-port passive reduced order interconnect models with large port count. and the overall task is decomposed into tractable and naturally parallelizable model generation and fft/inverse-fft operations, all on a per driver or per sink basis.
optimization-based framework for simultaneous circuit-and-system design-space exploration: a high-speed link example. connecting system-level performance models with circuit information has been a long-standing problem in analog/mixed-signal front-ends, like radios and high-speed links. high-speed links are particularly hard to analyze because of the complex interplay of device/circuit parasitics and channel filtering operation. in this paper we introduce optimization-based framework for link design-space exploration, connecting the link transmission quality and top-level filter settings with circuit power, sizing and biasing. we derive a special analytical discrete time representation that avoids the size explosion of the symbolic problem description improving the parsing and solver time by orders of magnitude and making this joint optimization possible in real-time. this robust and accurate problem formulation is derived in signomial form and is compatible with existing optimization approaches to circuit sizing. we demonstrate this optimization framework on a link design-space exploration example, investigating trade-offs between the transmit preemphasis and linear receiver equalizer and their impact on overall link power vs. data rate.
inductive equivalence checking under retiming and resynthesis. retiming and resynthesis are among the most important techniques for practical sequential circuit optimization. however, their applicability is much limited due to verification concerns. overcoming the verification bottleneck is a supreme task. this paper studies both the theoretical and practical aspects of inductive verification on the equivalence between circuits under retiming and resynthesis transformation. we study the completeness condition of the inductive approach to equivalence checking and show that prior work is only complete for circuits transformed under retiming or resynthesis, but not both. we overcome prior limitation and make complete the equivalence checking for circuits transformed up to retiming+resynthesis+retiming. the theoretical insights lead to a robust satisfiability formulation of verification under various retiming and resynthesis scenarios. experimental results demonstrate the scalability of the approach. several previously unverifiable circuits and unverifiable transformation scenarios can now be verified effectively.
formal verification at higher levels of abstraction. most formal verification tools on the market convert a high-level register transfer level (rtl) design into a bit-level model. algorithms that operate at the bit-level are unable to exploit the structure provided by the higher abstraction levels, and thus, are less scalable. this tutorial surveys recent advances in formal verification using high-level models. we present word-level verification with predicate abstraction and satisfiability modulo theories (smt) solvers. we then describe techniques for term-level modeling and ways to combine word-level and term-level approaches for scalable verification.
automated refinement checking of concurrent systems. stepwise refinement is at the core of many approaches to synthesis and optimization of hardware and software systems. for instance, it can be used to build a synthesis approach for digital circuits from high level specifications. it can also be used for post-synthesis modification such as in engineering change orders (ecos). therefore, checking if a system, modeled as a set of concurrent processes, is a refinement of another is of tremendous value. in this paper, we focus on concurrent systems modeled as communicating sequential processes (csp) and show their refinements can be validated using insights from translation validation, automated theorem proving and relational approaches to reasoning about programs. the novelty of our approach is that it handles infinite state spaces in a fully automated manner. we have implemented our refinement checking technique and have applied it to a variety of refinements. we present the details of our algorithm and experimental results. as an example, we were able to automatically check an infinite state space buffer refinement that cannot be checked by current state of the art tools such as fdr. we were also able to check the data part of an industrial case study on the ep2 system.
statistical analysis of rf circuits using combined circuit simulator-full wave field solver approach. as technologies continue to shrink in size, modeling the effect of process variations on circuit performance is assuming profound significance. process variations affect the on-chip performance of both active and passive components. this necessitates the inclusion of the effect of these variations on distributed interconnect structures in modeling overall circuit performance. in this work, first it is shown through field-solver simulations that larger process variations lead to non-gaussian pdfs (probability density functions) for the circuit equivalent parameters of distributed passives. next, a method for accurate statistical analysis of coupled circuit-em (electromagnetic) systems without computing the equivalent circuit parameters of em-modeled objects is demonstrated. this method also obviates the need to generate random variables representing the equivalent circuit parameters, from distributions which are correlated, non-gaussian and non-closed-form. the proposed approach relies on application of the response surface (rs) methodology to the y-parameters of both the circuit and the distributed structures independently and expressing the eventual performance measures through a suitable combination of the y-parameters. the eventual performance measures are expressed through a hierarchical approach in terms of the underlying gaussian random variables representing the process parameters. a rapid response surface monte carlo (rsmc) analysis on these derived response surfaces furnishes the pdfs and can also be used to predict the yield based on different qualifying criteria and objective functions.
intsim: a cad tool for optimization of multilevel interconnect networks. interconnect issues are becoming increasingly important for ulsi systems. intsim, an interconnect cad tool, has been developed to obtain pitches of different wiring levels and die size for circuit blocks or logic cores of microchips. it includes a methodology for co-optimization of signal, power and clock interconnects, and a newly derived stochastic wiring distribution that gives reduced error than prior work when compared to measured data. results of intsim are found to match well with actual data from an analyzed microprocessor. several case studies are conducted to show this cad tool's utility as a system level simulator: (i) wire resistivity increases due to size effects are projected to increase die size of a 22nm low power logic core by 30% and power by 7%. (ii) when compared to a 22nm low power logic core with copper interconnects, a similar logic core with carbon nanotube interconnects could reduce power by 25% and die area by 27%, or increase frequency by 15% and reduce die area by 11%. (iii) a future 22nm 8 ghz 96m gate logic core's power, die size and optimal multilevel interconnect architecture are predicted. a version of intsim with a graphical user interface is available for download from www.ece.gatech.edu/research/labs/gsigroup.
a frequency-domain technique for statistical timing analysis of clock meshes. we propose a frequency-domain modeling technique with applications on the statistical timing analysis of clock mesh/grid networks. using transmission lines to model clock mesh edges, we express the means and (co)variances of the sink arrival times as polynomial functions of the arrival times of the input signals and the wire widths of the mesh edges, with up to second order accuracy. experimental results show that the proposed frequency-domain statistical timing analysis technique is efficient and accurate. the relative mean error is less than 1% and relative variance error less than 3%.
hybrid cegar: combining variable hiding and predicate abstraction. variable hiding and predicate abstraction are two popular abstraction methods to obtain simplified models for model checking. although both methods have been used successfully in practice, no attempt has been made to combine them in counterexample guided abstraction refinement (cegar). in this paper, we propose a hybrid abstraction method that allows both visible variables and predicates to take advantages of their relative strengths. we use refinement based on weakest preconditions to add new predicates, and under certain conditions trade in the predicates for visible variables in the abstract model. we also present heuristics for improving the overall performance, based on static analysis to identify useful candidates for visible variables, and use of lazy constraints to find more effective unsatisfiable cores for refinement. we have implemented the proposed hybrid cegar procedure. our experiments on public benchmarks show that the new abstraction method frequently outperforms the better of the two existing abstraction methods.
large-scale atomistic approach to random-dopant-induced characteristic variability in nanoscale cmos digital and high-frequency integrated circuits. modeling of device variability is crucial for the accuracy of timing in circuits and systems, and the stability of high-frequency application. unfortunately, due to the randomness of dopant position in device, the fluctuation of device gate capacitance is nonlinear and hard to be modeled in current compact models. therefore, a large-scale statistically sound "atomistic" device/circuit coupled simulation approach is proposed to characterize the random-dopant-induced characteristic fluctuations in 16-nm-gate cmos integrated circuits concurrently capturing the discrete-dopant-number- and discrete-dopant-position-induced fluctuations. the variations of transition time of digital circuit (inverter, nand, and nor gates) and high-frequency characteristic of common-source amplifier are estimated. for the digital circuits, the function-dependent and circuit-topology-dependent characteristic fluctuations resulted from random nature of discrete dopants is for the first time discussed. this study provides an insight into random-dopant- induced intrinsic timing and high-frequency characteristic fluctuations. the accuracy of the simulation technique is confirmed by the use of experimentally calibrated transistor physical model.
efficient computation of current flow in signal wires for reliability analysis. electromigration (em) and self-heating are critical reliability concerns for metal wires in high performance designs. em reliability rules for a vlsi technology are typically expressed in terms of average, root-mean-square and peak current limits for each metal layer in the technology. to ensure em reliability of a design, current flowing through each wire segment in the design should not violate the em reliability rules. in this work, we present closed-from analytical models for efficient computation of average, root-mean-square and peak currents through any element in an arbitrary rc tree. the proposed models are validated against spice simulations for several rc nets extracted from an industrial asic design. the results show that the models exhibit very good accuracy with a mean error of only 3.1% in root-mean-square and 0.2% in average current estimation.
yield-aware hierarchical optimization of large analog integrated circuits. hierarchical optimization using building circuit block pareto performance models is an efficient and well established approach for optimizing the nominal performances of large analog circuits. however, the extension to yield-aware hierarchical methodology, as dictated by the need for safeguarding chip manufacturability in scaled technologies, is completely nontrivial. we address two fundamental difficulties in achieving such a methodology: yield-aware pareto performance characterization at the building block level and yield-aware system-level optimization problem formulation. it is shown that our approach is not only able to effectively capture the block performance trade-offs at different yield levels, but also correctly formulate the whole system yield and efficiently perform system-level optimization in presence of process variations. our approach extends the efficiency of hierarchical analog optimization, enjoyed for improving nominal circuit performances, to yield-aware optimization. our methodology is demonstrated by the hierarchical optimization of a phased locked loop (pll) consisting of multiple circuit blocks.
stabilizing schemes for piecewise-linear reduced order models via projection and weighting functions. in this paper we present several results concerning the stabilization of piecewise-linear reduced order models. we include proofs of internal and external stability for models whose system matrices possess special structures. we then introduce a new projection scheme, and a new set of weighting functions which allow us to extend some of these results to piecewise-linear systems comprised of arbitrary matrices, at least one of which is hurwitz. included are an algorithm for creating switching piecewise-linear reduced models comprised of globally exponentially stable systems, and stable simulation results for a system which produces unstable results when using the standard tpwl method.
pars: fast and near-optimal grid-based cell sizing for library-based design. we propose pars, a parallel and randomized tool which solves the discrete gate sizing (cell sizing) problem on a grid. pars is formulated based on an optimization framework known as nested partitions which uses parallelism and randomization from a novel perspective to better identify the optimization direction. it achieves nearoptimal solutions for minimizing total power and area subject to meeting a delay constraint. the embarrassingly-parallel nature of pars makes it highly efficient. we show small algorithm run-times, in at most minutes for circuits with over 47,000 cells. we make comparison with the optimal solution generated by a custom and parallel branch-and-bound algorithm. consequently, we are able to generate the optimal solution within hours. while the optimal algorithm uses up to 200 nodes in our grid, pars achieves its speedups and near-optimal solutions using only 20 nodes.
effective ir-drop reduction in at-speed scan testing using distribution-controlling x-identification. test data modification based on test relaxation and x-filling is the preferable approach for reducing excessive ir-drop in at-speed scan testing to avoid test-induced yield loss. however, none of the existing test relaxation methods can control the distribution of identified don't care bits (x-bits), thus adversely affecting the effectiveness of ir-drop reduction. in this paper, we propose a novel test relaxation method, called distribution-controlling x-identification (dc-xid), which controls the distribution of x-bits identified from a set of fully-specified test vectors for the purpose of effectively reducing ir-drop. experimental results on large industrial circuits demonstrate the effectiveness and practicality of the proposed method in reducing ir-drop, without any impact on fault coverage, test data volume, or test circuit size.
a statistical approach for full-chip gate-oxide reliability analysis. gate oxide breakdown is a key factor limiting the useful lifetime of an integrated circuit. unfortunately, the conventional approach for full chip oxide reliability analysis assumes a uniform oxide-thickness for all devices. in practice, however, gate-oxide thickness varies from die-to-die and within-die and as the precision of process control worsens an alternative reliability analysis approach is needed. in this work, we propose a statistical framework for chip level gate oxide reliability analysis while considering both die-to-die and within-die components of thickness variation. the thickness of each device is modeled as a distinct random variable and thus the full chip reliability estimation problem is defined on a huge sample space of several million devices. we observe that the full chip oxide reliability is independent of the relative location of the individual devices. this enables us to transform the problem such that the resulting representation can be expressed in terms of only two distinct random variables. using this transformation we present a computationally efficient and accurate approach for estimating the full chip reliability while considering spatial correlations of gate-oxide thickness. we show that, compared to monte carlo simulation, the proposed method incurs an error of only 1~6% while improving the runtime by around three orders.
correct-by-construction microarchitectural pipelining. this paper presents a method for correct-by-construction microarchitectural pipelining that handles cyclic systems with dependencies between iterations. our method combines previously known bypass and retiming transformations with a few transformations valid only for elastic systems with early evaluation (namely, empty fifo insertion, fifo capacity sizing, insertion of anti-tokens, and introducing early evaluation multiplexors). by converting the design to a synchronous elastic form and then applying this extended set of transformations, one can pipeline a functional specification with an automatically generated distributed controller that implements stalling logic resolving data hazards off the critical path of the design. we have developed an interactive toolkit for exploring elastic microarchitectural transformations. the method is illustrated by pipelining a few simple examples of instruction set architecture isa specifications.
comprehensive procedure for fast and accurate coupled oscillator network simulation. coupled oscillator networks occur in various domains such as biology, astrophysics and electronics. in this paper, we present a comprehensive procedure for rapid and accurate simulation of large coupled oscillator networks using widely accepted, fully-nonlinear perturbation projection vector (ppv) phase macromodels. we validate our method against full simulation of 20x20 coupled network of brusselator biochemical oscillator and obtain computational speedups of 170x over full simulation. furthermore, we apply the method to study self-organization phenomenon of brusselator under asymmetric coupling and time period variations.
efficient online computation of core speeds to maximize the throughput of thermally constrained multi-core processors. we address the problem of efficient online computation of the speeds of different cores of a multi-core processor to maximize the throughput (which is expressed as a weighted sum of the speeds), subject to an upper bound on the core temperatures. we first compute the solution for steady-state thermal conditions by solving a linear program. we then present two approaches to computing the transient speed curves for each core: (i) a local solution, which involves solving a linear program every time step (of about 10 ms), and (ii) a global solution, which computes the optimal speed curve over a large time window (of about 100 s) by solving a non-linear program. we showed that the local solution is insensitive to the weights assigned in the performance objective (hence the need for the global solution). this is because a reduction in the speed of a core can only reduce the temperature of the other cores over much larger time periods (of the order of several seconds). the local solution is then completely determined by the temperature constraint equations. we show that the constraint matrix exhibits a special property - it can be expressed as the sum of a diagonal matrix and a matrix with identical rows. this allows us to solve the multi-core thermal constraint equations analytically to determine the (temporally) local optimum speeds. further, we showed that due to this property, the steady-state speed solution selects a set of threads to operate at maximum temperature, and turns off all unused cores. hence, to ensure that all available threads are scheduled, we impose a "fairness" constraint. finally, we show how the open-loop speed control methods proposed above could be used together with a feedback controller to achieve robustness to model uncertainty.
diastolic arrays: throughput-driven reconfigurable computing. diastolic arrays are arrays of processing elements that communicate exclusively through first-in first-out (fifo) queues. fifo virtualization units enable relaxed timing of data transfers, and include hardware support to guarantee bandwidth and buffer space for all data transfers, which may follow composite paths through the network. we show that the architecture of diastolic arrays enables efficient synthesis from high-level specifications of communicating finite state machines so average throughput is maximized. preliminary results are presented on an h.264 decoding benchmark.
a capacitance solver for incremental variation-aware extraction. lithographic limitations and manufacturing uncertainties are resulting in fabricated shapes on wafer that are topologically equivalent, but geometrically different from the corresponding drawn shapes. while first-order sensitivity information can measure the change in pattern parasitics when the shape variations are small, there is still a need for a high-order algorithm that can extract parasitic variations incrementally in the presence of a large number of simultaneous shape variations. this paper proposes such an algorithm based on the well-known method of floating random walk (frw). specifically, we formalize the notion of random path sharing between several conductors undergoing shape perturbations and use it as a basis of a fast capacitance sensitivity extraction algorithm and a fast incremental variational capacitance extraction algorithm. the efficiency of these algorithms is further improved with a novel frw method for dealing with layered media. our numerical examples show a 10x speed up with respect to the boundary-element method adjoint or finite-difference sensitivity extraction, and more than 560x speed up with respect to a non-incremental frw method for a high-order variational extraction.
bsg-route: a length-matching router for general topology. length-matching routing is a very important issue for pcb routing. previous length-matching routers [1]--[3] all have assumptions on the routing topology whereas practical designs may be free of any topological constraint. in this paper, we propose a router that deals with general topology. unlike previous routers, our router does not impose any restriction on the routing topology. moreover, our router is gridless. its performance does not depend on the routing grid size of the input while routers in [1]--[3] do. this is a big advantage because modern pcb routing configurations usually imply huge routing grids. the novelty of this work is that we view the length-matching routing problem as an area assignment problem and use a placement structure, bounded-sliceline grid (bsg) [4], to help solving the problem. experimental results show that our router can handle practical designs that previous routers can't handle. for designs that they could handle, our router runs much faster. for example, in one of our data, we obtain the result in 88 seconds while the router in [3] takes more than one day.
architecting parallel programs. the current shift from sequential to multicore and manycore processors presents serious challenges to software developers. a significant part of the industrial and research communities believes that either a) they can squeak by or b) the right compiler, parallel language etc will save them. such ad hoc responses are likely to prove neither correct nor sustainable. to systematically find and exploit parallelism, and to achieve forward scalability --- that is, designs which efficiently scale to much larger numbers of cores --- will require re-architecting software applications such as eda. we believe that the key to re-architecting software is the use of design patterns and a pattern language. furthermore, structural patterns (aka architectural styles) and computational patterns (aka the thirteen dwarfs) are the key high-level design patterns. the patterns are then used to create programming frameworks that can be used to facilitate implementation of the software architecture. this tutorial presents the most recent research results by uc berkeley and intel. we will present our working pattern language and give examples on its use in eda and other application areas.
cad for displays! we take displays for granted in devices like our laptops, television, cell phones, and cars -to name a few places. the tft lcd processes in use now are as mature as cmos was 20 years ago, which is when we started seeing asic companies doing fabless chip design and investing heavily in cad. today, the display, as i believe i showed while working on the olpc, is really just an asic! why focus on the display? the display is the most expensive and power hungry component in your laptops, it can now be "taped out" just like an asic using standard tft lcd fabs, and -in the limit- the laptop or the cell phone will become just a display in which the electronics are integrated into. i believe that we are about to see a revolution in display design, with gradual subsumption of more and more of the cpu and motherboard electronics, to further drive down cost and power consumption. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
exact basic geometric operations on arbitrary angle polygons using only fixed size integer coordinates. as the semiconductor technology is scaling down to nanometer regime, accurate layout analysis requires operations with simulated contours of vlsi layouts which are non-rectilinear. the basic operations on non-rectilinear shapes include "intersection", "difference", "union", "find connected components" and "find boundary". whatever precision one would choose for the representation of vertices of shapes a and b the exact representation of, say, a&cap;b would require an even higher precision. consequently rounding of intermediate results of a chain of basic operations seems to be inevitable. the presence of rounding errors is unacceptable because the implementation of algorithms for all operations which involve topology, such as "find connected components", " find boundary", etc, becomes impossible or extremely complex we present a complete solution to the following problem: let a vlsi design or a simulated through a lithography process image of a vlsi design be given by a number of two-dimensional point sets. each point set consists of polygons with arbitrary (not necessarily 90&deg;) angles and with vertices on an integer grid. perform any amount of sequential basic operations so that: &bull; the resulting point sets are mathematically exact, that is no rounding errors are allowed. in particular the connectivity of the point sets remains intact, the boundaries remain undistorted and the statements like "a = (a \ b) &cup; (a &cap; b)", "(a \ b) is disjoint with b" and "a &cap; b &sub; a" always hold. &bull; the amount of time and memory per one basic geometric operation on elementary polygons (trapezoids) is constant. for example it would not be an acceptable solution to represent the vertices of the new shapes which appear as a result of the operations of intersection, difference, etc, by unlimited length rational numbers.
statistical modeling of metal-gate work-function variability in emerging device technologies and implications for circuit design. for the first time, a new source of random threshold voltage (vth) fluctuation in emerging metal-gate transistors is identified, analytically modeled and investigated for its device and circuit-level implications. the new source of variability, christened work-function variation (wfv), is caused by the dependency of metal work-function on the orientation of its grains. a statistical framework is developed, which enables estimation of the key parameters of work-function distribution by identifying the physical dimensions of the devices and properties of materials used in the fabrication. this paper offers three major contributions for process, device and circuit designers. first, the proposed model can be employed to identify suitable materials and fabrication processes that can reduce the impact of vth fluctuation due to wfv. for instance, four types of metal nitride gate materials (tin and tan for nmos and wn and mon for pmos devices) are studied and it is shown that tin and wn result in lower vth fluctuation. second, device engineers can benefit from the result of this work by evaluating the wfv level of various types of classical or non-classical metal-gate cmos transistors. as an example, it is shown that finfet transistors are less affected by wfv compared to fd-soi and bulk-si devices due to their larger gate area. third, circuit designers can utilize this model to investigate the impact of such a variation on the key performance and reliability parameters of the circuits. for instance, an sram cell is analyzed in the presence of vth fluctuations due to wfv and it is shown that such variations can result in considerable performance and reliability degradation.
silicon feedback to improve frequency of high-performance microprocessors: an overview. in modern high-performance microprocessors designed using advanced process technologies, the frequency of the part is often slower than what the static timing analysis tools predict before tape out. we give an overview of techniques used to observe the failing path on the tester, identify the dominant devices impacting the delay of the path, and learn from the failing path to fix other similar paths in the design. in particular, we describe a support vector machine based approach for learning from speedpaths observed in silicon.
pulse width allocation with clock skew scheduling for optimizing pulsed latch-based sequential circuits. pulsed latches, latches driven by a brief clock pulse, offer the convenience of flip-flop-like timing verification and optimization, while retaining superior design parameters of latches over flip-flops. but, pulsed latch-based design using a single pulse width has a limitation in reducing clock period. the limitation still exists even if clock skew scheduling is employed, since the amount of skew that can be assigned is practically limited due to process variations. the problem of allocating pulse width (out of discrete number of predefined widths) and scheduling clock skew (within prescribed upper bound) is formulated, for the first time, for optimizing pulsed latch-based sequential circuits. an allocation algorithm called pwcs_optimize is proposed to solve the problem. experiments with 65-nm technology demonstrate that small number of variety of pulse widths (up to 5) combined with clock skews (up to 10% of clock period) yield minimum clock period for many benchmark circuits. the design flow including pwcs_optimize, placement and routing, and synthesis of local and global clock trees is presented and assessed with example circuits.
process variation aware system-level task allocation using stochastic ordering of delay distributions. design variability due to within-die and die-to-die variations has potential to significantly reduce the maximum operating frequency and effective performance of the system in future process technology generations. when multiple cores in mpsoc have different delay distributions, the problem of assigning tasks to the cores become challenging. this paper targets system level task allocation to stochastically minimize the total execution time of an application on mpsoc under process variation. in this work, we first introduce stochastically optimal task allocation problem. we provide formal theorems of the optimality of the solution in simple scenarios. we extend our theoretical work for generic cases in normal distribution. the proposed techniques enable efficient computation of task allocation using non-stochastic analysis. we apply these techniques in allocating tasks in the embedded system benchmark suites on mpsoc. we show that deterministic solution for system-level task allocation on widely used benchmark topologies and distributions (normal distribution) is almost as good as the best probabilistic solution.
constraint graph-based macro placement for modern mixed-size circuit designs. in this paper, we propose a constraint graph-based macro placement algorithm that removes macro overlaps and optimizes macro positions for modern mixed-size circuit designs. improving over the constraint graph by working only on its essential edges without loss of the solution quality, our algorithm can search for high-quality macro placement solutions effectively and efficiently. instead of packing macros along chip boundaries like most recent previous work, our placer can determine a non-compacted macro placement by linear programming and placement region cost evaluation and handle various placement constraints/objectives. compared with various leading academic macro placers, our algorithm can consistently and significantly reduce the wirelengths for designs with different utilization rates, implying that our macro placer is robust and has very high quality.
more moore: foolish, feasible, or fundamentally different? moore's law has been a foundation of modern electronics, sustained primarily by scaling. but can this continue despite the serious problems of litho, variability, device physics, and cost? this panel looks at several possibilities. perhaps moore's law will muddle through, as it has so far, with a combination of tools, process, and design. but even if technically possible, moore's law is in practice driven by economics, and economics might turn against further scaling. also, we've all seen how performance of single cores has topped out, despite scaling. might this be a fundamental problem with planar technologies, prompting the need to go 3-d to get further performance increases? or might cmos itself give way to other technologies, allowing moore's law yet another respite? compare and contrast for yourself these four very different visions of the future of your job, your industry, and your personal gadgets.
a highly efficient optimization algorithm for pixel manipulation in inverse lithography technique. an efficient algorithm based on the pixel-based mask representation is proposed for fast synthesis of model-based inverse lithography technology (ilt) to improve the resolution and pattern fidelity in optical lithography. this new algorithm reduces n2 intensity computations to three (3) equivalent intensity computations per iteration, where n2 is the total number of pixels in a mask. this algorithm has been demonstrated using different critical dimensions (cds) and different mask technologies with incoherence and partial-coherence image models. this algorithm is about 60 times faster and more effective than the current gradient-based algorithm. the final image fidelity has quite a weak dependence on the initial condition. good fidelity images are achieved when cd is reduced to 45nm.
adjustment-based modeling for statistical static timing analysis with high dimension of variability. this paper presents an adjustment-based modeling framework for statistical static timing analysis (ssta) when the dimension of parameter variability is high. instead of building a complex model between the circuit timing and parameter variability, we build a model which adjusts an approximate variation-aware timing into an accurate one. the intuition is that it is simpler to build a model which adjusts an approximate estimate into an accurate one. it is also more efficient to obtain an approximate circuit timing model. the combination of these two observations makes the use of an adjustment-based model a good choice for ssta with high dimension of parameter variability. to build the adjustment model, we use a simulation-based approach, which is based on gaussian process. combined with intelligent sampling, we show that an adjustment-based model can more effectively capture the nonlinearity of the circuit timing with respect to parameter variability compared to polynomial modeling. we also show that with only 200 samples of the circuit timing and 42 independent parameter variations, adjustment-based modeling obtains higher accuracy than direct ssta using quadratic modeling.
module locking in biochemical synthesis. we are developing a framework for computation with biochemical reactions with a focus on synthesizing specific logical functionality, a task analogous to technology-independent logic synthesis. our method synthesizes biochemical reactions that compute output quantities of molecular types as a function of input quantities, either deterministically or probabilistically. an important constraint is the timing, captured in the relative rates of the biochemical reactions: all the outputs of a given phase must be produced before the next phase can begin consuming them as inputs. to achieve this synchronization, the reaction rates must sometimes be separated by orders of magnitude: some much faster than others, some much slower. this might be costly or infeasible given a specific library of biochemical reactions. in this paper, we describe a novel mechanism for locking the computation of biochemical modules - analogous to handshaking mechanisms in asynchronous circuit design. with locking, our method synthesizes robust computation that is nearly rate independent, requiring at most two speeds ("fast" and "slow"). the trade-off is with respect to the size of the solution: more reactions are needed. we characterize this trade-off for inter-and intra-module locking in general and for a variety of specific modules that we have designed. in particular, we discuss locking in detail for a stochastic module that implements probabilistic computation, producing different combinations of molecular types according to specified probability distributions.
efficient block-based parameterized timing analysis covering all potentially critical paths. in order for the results of timing analysis to be useful, they must provide insight and guidance on how the circuit may be improved so as to fix any reported timing problems. a limitation of many recent variability-aware timing analysis techniques is that, while they report delay distributions, or verify multiple corners, they do not provide the required guidance for re-design. we propose an efficient block-based parameterized timing analysis technique that can accurately capture circuit delay at every point in the parameter space, by reporting all paths that can become critical. using an efficient pruning algorithm, only those potentially critical paths are carried forward, while all other paths are discarded during propagation. this allows one to examine local robustness to parameters in different regions of the parameter space, not by considering differential sensitivity at a point (which would be useless in this context) but by knowledge of the paths that can become critical at nearby points in parameter space. we give a formal definition of this problem and propose a technique for solving it that improves on the state of the art, both in terms of theoretical computational complexity and in terms of run time on various test circuits.
post-silicon timing characterization by compressed sensing. we address post-silicon characterization of the unique gate delays and their timing distributions on each manufactured ic. our proposed approach is based upon the new theory of compressed sensing. the first step in performing timing measurements is to find the sensitizable paths by traditional testing methods. next, we show that the timing variations are sparse in the wavelet domain. the sparsity is exploited for estimation of the gate delays using the compressed sensing theory. this estimation method requires significantly less number of timing measurements compared to the case where the dependence between the gate delays is not directly integrated within the estimation framework. we discuss a number of applications for the new post-silicon timing characterization method. experimental results on benchmark circuits show that using compressed sensing theory can characterize the post-silicon variations with a mean accurately of 95% in the pertinent sparse basis.
sparse implicit projection (sip) for reduction of general many-terminal networks. this paper is concerned with model order reduction of large scale dynamic systems that have sparse matrix representations, particularly systems with large numbers of input/output "ports." we present an algorithm that combines the advantages of widely-used approaches such as prima and ticer but avoids many of the drawbacks of both. the resulting algorithm is capable of highorder rational approximation, exploits network sparsity, preserves passivity, can be extended to general non-symmetric systems, and can be applied to networks with hundreds or thousands of ports. we develop a common mathematical framework that can encompass all three algorithms, show mathematical relations between them, and point out certain special cases where they are equivalent. we show examples from analysis of industrial on-chip rc/rlc networks that demonstrate performance advantages of more than three orders of magnitude.
evaluation of voltage interpolation to address process variations. post-fabrication tuning provides a promising design approach to mitigate the performance and power overheads of process variation in advanced fabrication technologies. this paper explores design considerations and vlsi-cad support for a recently proposed postfabrication tuning knob called voltage interpolation. the paper discusses design tradeoffs between circuit tuning range and static power overheads that can be performed within the synthesis flow of the design process. the paper explores the scheme for a 64-core chip-multiprocessor machine using industrial-grade design blocks and shows that the scheme can be used to mitigate overhead arising from random and correlated within-die process variations. the analysis shows that the scheme can match the nominal delay target with a 10% power cost, or for the same power budget, incur only a 9% delay overhead after variations.
verifying external interrupts of embedded microprocessor in soc with on-chip bus. the microprocessor verification challenge becomes higher in the on-chip bus (ocb) than in the unit-level. especially for the external interrupts, since they interface with other ip components, they suffer from the complicated bus protocol and ip conflict problems. this paper proposes a automatic method to verify the microprocessor external interrupt behaviors on the ocb. the verification approach is based on the processor external interrupt verification tool (pevt) whose simulation environment is direct-connected memory. in this paper, we implement the pevt-soc and successfully verify two soc platforms, one academic microprocessor and one public domain microprocessor. an interesting bug appears that is impossible to be discovered in the memory bus and not easy to be identified on the ocb. the result shows that the pevt-soc effectively shortens the verification time regardless of the system complexity and can be easily migrated to different platforms/microprocessors. with little human effort, even an inexperience designer can generate extensive verification cases in a systematic way.
graphene nanoribbon fets: technology exploration and cad. graphene nanoribbon fets (gnrfets) have emerged as a promising candidate for nanoelectronics applications. this paper summarizes (i) current understanding and prospects for gnrfets as ultimately scaled, ideal ballistic transistors, (ii) physics-based modeling of gnrfets to support circuit design and cad, and (iii) variability and defects in gnrs and their impact on gnrfet circuit performance and reliability.
breaking the simulation barrier: sram evaluation through norm minimization. with process variation becoming a growing concern in deep submicron technologies, the ability to efficiently obtain an accurate estimate of failure probability of sram components is becoming a central issue. in this paper we present a general methodology for a fast and accurate evaluation of the failure probability of memory designs. the proposed statistical method, which we call importance sampling through norm minimization principle, reduces the variance of the estimator to produce quick estimates. it builds upon the importance sampling, while using a novel norm minimization principle inspired by the classical theory of large deviations. our method can be applied for a wide class of problems, and our illustrative examples are the data retention voltage and the read/write failure tradeoff for 6t sram in 32 nm technology. the method yields computational savings on the order of 10000x over the standard monte carlo approach in the context of failure probability estimation for sram considered in this paper.
transition-aware decoupling-capacitor allocation in power noise reduction. dynamic power noises may not only degrade the circuit performance but also reduce the noise margin which may result in the functional errors in integrated circuit. decoupling capacitor (decap) allocation is one of the most effective way in reducing serious dynamic power noises (hotspots). to allocate decap before placement, we observed that not only locations but also rising time of functional cells are required to accurately predict power noises. compared to a previous work which only takes neighborhood relation into consideration, our method is more efficient in reducing hotspots. furthermore, to reduce the hotspots after placement, instead of only using the empty space as proposed in the previous work, we move out cells in the area with serious power noise area (hot area). the obtained empty space can be used to accommodate decaps to further reduce the hotspots. the experimental result shows, compared to the previous work [1], our estimation function to allocate decap before placement is 23% better in reducing power noises. moreover, compared to a method which fills decaps to all remaining empty space, our cell move algorithm can almost eliminate all the remaining hot grid nodes and hot cells. in summary, compared to the original circuits (without decap), about 60% of hotspots can be removed using our prediction function before placement, and most of the remaining hotspots are removed by our cell moving step after placement.
lightweight secure pufs. to ensure security and robustness of the next generation of physically unclonable functions (pufs), we have developed a new methodology for puf design. our approach employs integration of three key principles: (i) inclusion of multiple delay lines for creation of each response bit; (ii) transformations and combination of the challenge bits; and (iii) combination of the outputs from multiple delay lines; to create modular, easy to parameterize, secure and reliable puf structures. statistical analysis of the new structure and its comparison with existing pufs indicates a significantly lower predictability, and higher resilience against circuit faults, reverse engineering and other security attacks.
system-level thermal aware design of applications with uncertain execution time. the paper introduces the problem of system-level thermal aware design of applications with uncertain run time on an embedded processor equipped with dynamic voltage/frequency scaling features. the problem takes as inputs a task sequence, cycle time distribution of each task, and processor thermal model. the solution specifies a voltage/frequency assignment to the tasks such that the expected latency is minimized subject to the probability that the peak temperature constraint is not violated is no less than a designer specified value. we prove that the problem is at least np-hard, and present optimal and (1 + &epsilon;) fully polynomial time approximation scheme as solutions. to the best of our knowledge, this paper is the first work that addresses the stochastic version of the system-level thermal-aware design problem. we evaluate the effectiveness of our techniques by experimenting with realistic and synthetic benchmarks.
reliable system design: models, metrics and design techniques. design of reliable systems meeting stringent quality, reliability, and availability requirements is becoming increasingly difficult in advanced technologies. the current design paradigm, which assumes that no gate or interconnect will ever operate incorrectly within the lifetime of a product, must change to cope with this situation. future systems must be designed with built-in mechanisms for failure tolerance, prediction, detection and recovery during normal system operation. this tutorial will focus on models and metrics for designing reliable systems, algorithms and tools for modeling and evaluating such systems, will discuss a broad spectrum of techniques for building such systems with support for concurrent error detection, failure prediction, error correction, recovery, and self-repair. complex interplay between power, performance and reliability requirements in future systems, and associated constraints will also be discussed.
simultaneous control of power/ground current, wakeup time and transistor overhead in power gated circuits. power gating in circuits is one of the effective technologies to allow low leakage and high performance operations. this work aims to analyze and establish the relations between the three important design parameters in power gated circuits: (i) the maximum current flowing from/to power/ground (ii) the wakeup (sleep to active mode transition) time delay and (iii) the number of sleep transistors. with the understanding of relations between the parameters, we propose solutions to the two problems: (1) finding logic clusters and their wakeup schedule to minimize the sleep transistor overhead under the constraints of wakeup time and peak current and (2) finding logic clusters and their wakeup schedule to minimize the wakeup time under the constraints of peak current and the number of sleep transistors. from an experimentation using iscas benchmarks, it is shown that our proposed technique is able to explore the search space, finding solutions with 65% ~ 77% reduced number of sleep transistors and 30% ~ 36% reduced wakeup time delay, compared to the results by the previous work.
on efficient monte carlo-based statistical static timing analysis of digital circuits. the monte-carlo (mc) technique is a well-known solution for statistical analysis. in contrast to probabilistic (non-monte carlo) statistical static timing analysis (ssta) techniques, which are typically derived from simple statistical or timing models, the mc-based ssta technique encompasses complicated timing and process variation models. however, a precise analysis that involves a traditional mc-based technique requires many timing simulation runs (1000s). in this paper, the behavior of the critical delay of digital circuits is investigated by using a legendre polynomial-based anova decomposition. the analysis verifies that the variance of the critical delay is mainly due to the pairwise interactions among the principal components (pcs) of the process parameters. based on this fact, recent progress on the mc-based ssta, through latin hypercube sampling (lhs), is also studied. it is shown that this technique is prone to inefficient critical delay variance and quantile estimating. inspired by the decomposition observations, an efficient algorithm is proposed which produces optimally low l2-discrepancy quasi-mc (qmc) samples which significantly improve the precision of critical delay statistical estimations, compared with that of the mc, lhs, and traditional qmc techniques.
characterization and modeling of graphene field-effect devices. the novel electronic properties of graphene, including a linear energy dispersion relation and purely two-dimensional structure, have led to intense research into possible applications of this material in nanoscale devices. in this paper, we review the unique electronic properties of graphene that give it the potential for high-frequency electronic applications. we then present the latest results on the current-voltage characteristics of top-gated graphene fets. these devices show unique characteristics related to the ambipolar nature of the graphene channel. in addition, the devices show very high saturation velocities, suggesting the possibility for superior high frequency performance. our initial devices have transconductances as high as 150 &mu;s/&mu;m despite low on-off current ratios, making the devices very suitable for analog/rf applications.
challenges at 45nm and beyond. design at 45nm technologies and below is a risky proposition because of the many design challenges involved: variability, leakage, verification complexity, poor analog device performance, etc. in this panel, experienced designers coming from different backgrounds talk about how they have overcome some of the design and cad challenges in 45nm, what cad challenges still exist and how the cad community can help.
area-i/o flip-chip routing for chip-package co-design. the area-i/o flip-chip package provides a high chip-density solution to the demand of more i/o's in vlsi designs; it can achieve smaller package size, shorter wirelength, and better signal and power integrity. in this paper, we introduce the routing problem for chip and package co-design and present the first work in the literature to handle the multiple re-distribution layer (rdl) routing problem for flip-chip designs, considering pin and layer assignment, total wirelength minimization, and chip-package co-design. our router adopts a two-stage technique of global routing followed by rdl routing. the global routing assigns each block port to a unique bump pad via an i/o pad and decides the rdl routing among i/o pads and bump pads. based on the minimum-cost maximum-flow algorithm, we can guarantee 100% rdl routing completion after the assignment and the optimal solution with the minimum wirelength. the rdl routing efficiently distributes the routing points between two adjacent bump pads and then generates a 100% routable sequence to complete the routing. experimental results based on 10 industry designs demonstrate that our router can achieve 100% routability and the optimal routing wirelength under reasonable cpu times, while related works cannot.
linear analysis of random process variability. this paper describes an alternate method to monte carlo for calculating circuit node voltage and branch current variances due to random process variability. recent results show that the complex models traditionally used to describe random process variations of a transistor can be replaced by a single independent current noise source with a variance dependent on the transistor's size and operating points. as a result, each transistor affected by random process variability can be modeled as a deterministic device in parallel with a current noise source. by replacing all the transistors in a circuit with this model, the spatial voltage variances of circuit nodes can be calculated through linear small-signal analysis. the idea is presented in this paper and a tool implemented for berkeley spice is described. the results of the variability spice tool match the results from monte carlo run in spectre, with an accuracy determined by the accuracy of the random process variability model. for example, the standard deviations computed by the tool are within a 5.0% accuracy of those calculated through measured silicon data which has a fitting error of 5.4%. the monte carlo method computes node variances in a time proportional to the number of circuit nodes and the number of iterations, whereas the computation time required by the variability tool is only a function of the number of circuit nodes. for large analog designs this results in a significant speed-up in the amount of time required to calculate circuit node variances.
integrated code and data placement in two-dimensional mesh based chip multiprocessors. as transistor sizes continue to shrink and the number of transistors per chip keeps increasing, chip multiprocessors (cmps) are becoming a promising alternative to remain on the current performance trajectory for both high-end systems and embedded systems. since future technologies offer the promise of being able to integrate billions of transistors on a chip, the prospects of having hundreds to thousands of processors on a single chip along with an underlying memory hierarchy and an interconnection system is entirely feasible. this paper proposes a compiler directed integrated code and data placement scheme for two-dimensional mesh based cmp architectures. the proposed approach uses a code-data affinity graph (cdag) to represent the relationship between loop iterations and array data and then assigns the sets of loop iterations to processing cores and sets of data blocks to on-chip memories. during the mapping process, the on-chip memory capacity and load imbalance across different cores and the topology of the noc are taken into account. in this paper, we present two variants of our approach: depth-first placement (dfp) and breadth-first placement (bfp), and compare them to three alternate code/data mapping schemes. the experimental evaluation shows that our cdag based placement schemes are very successful in practice, achieving average performance improvements of 19.9% (dfp) and 16.8% (bfp), and average energy improvements of 29.7% (dfp) and 27.8% (bfp).
integrated circuit design with nem relays. to overcome the energy-efficiency limitations imposed by finite sub-threshold slope in cmos transistors, this paper explores the design of integrated circuits based on nanoelectro-mechanical (nem) relays. a dynamical verilog-a model of the nem relay is described and correlated to device measurements. using this model we explore nem relay design strategies for digital logic and i/o that can significantly improve the energy efficiency of the whole vlsi system. by exploiting the low effective threshold voltage and zero leakage achievable with these relays, we show that nem relay-based adders can achieve an order of magnitude or more improvement in energy efficiency over cmos adders with ns-range delays and with no area penalty. by applying parallelism, this improvement in energy-efficiency can be achieved at higher throughputs as well, at the cost of increased area. similar improvements in high-speed i/o energy are also predicted by making use of the relays to implement highly energy-efficient digital-to-analog and analog-to-digital converters.
overlay aware interconnect and timing variation modeling for double patterning technology. as double patterning technology (dpt) becomes the only solution for 32-nm lithography process, we need to investigate how dpt affects the performance of a chip. in this paper, we present an efficient modeling of timing variation with overlay which is inevitable for dpt. our work makes it possible to analyze timing with overlay variables. since the variation of metal space caused by overlay results in coupling capacitance variation, we first model metal spacing variation with individual overlay sources. then, all overlay sources are considered to determine the worst timing with coupling capacitance variation. non-parallel pattern caused by overlay is converted to parallel one with equivalent spacing having the same delay to be applicable of a traditional rc extraction flow. to verify our work, we use identical interconnects having different positions and different layout decompositions. experimental result shows that the delay has a variation from 7.8% to 9.1% depending on their locations. the well decomposed structure shows only 2.7% delay variation.
multigrid on gpu: tackling power grid analysis on parallel simt platforms. the challenging task of analyzing on-chip power (ground) distribution networks with multi-million node complexity and beyond is key to today's large chip designs. for the first time, we show how to exploit recent massively parallel single-instruction multiple-thread (simt) based graphics processing unit (gpu) platforms to tackle power grid analysis with promising performance. several key enablers including gpu-specific algorithm design, circuit topology transformation, workload partitioning, performance tuning are embodied in our gpu-accelerated hybrid multigrid algorithm, gpuhmd, and its implementation. in particular, a proper interplay between algorithm design and simt architecture consideration is shown to be essential to achieve good runtime performance. different from the standard cpu based cad development, care must be taken to balance between computing and memory access, reduce random memory access patterns and simplify flow control to achieve efficiency on the gpu platform. extensive experiments on industrial and synthetic benchmarks have shown that the proposed gpuhmd engine can achieve 100x runtime speedup over a state-of-the-art direct solver and be more than 15x faster than the cpu based multigrid implementation. the dc analysis of a 1.6 million-node industrial power grid benchmark can be accurately solved in three seconds with less than 50mb memory on a commodity gpu. it is observed that the proposed approach scales favorably with the circuit complexity, at a rate about one second per million nodes.
delay-optimal simultaneous technology mapping and placement with applications to timing optimization. technology mapping and placement have significant impact on the delays in standard cell based very large scale integrated (vlsi) circuits. traditionally, these steps are applied separately to optimize delays, possibly since efficient algorithms that allow the simultaneous exploration of the mapping and placement solution spaces are unknown. in this paper, we present an exact polynomial time algorithm for delay-optimal placement of a tree and extend the same to simultaneous technology mapping and placement for optimal delay in the tree. we extend the algorithm by employing lagrangian relaxation technique, which assesses the timing criticality of paths beyond a tree, to optimize the delays in directed acyclic graphs (dags). experimental results on benchmark circuits in a 70 nm technology show that our algorithms improve timing significantly with remarkably less run-times compared to a competitive approach of iterative conventional timing driven mapping and multi-level placement.
algorithms for simultaneous consideration of multiple physical synthesis transforms for timing closure. we propose a post-placement physical synthesis algorithm that can apply multiple circuit synthesis and placement transforms on a placed circuit to improve the critical path delay under area constraints by simultaneously considering the benefits and costs of all transforms (as opposed to considering them sequentially after applying each transform). the circuit transforms we employ include, but are not limited to, incremental placement, two types of buffer insertion, cell resizing and cell replication. the problem is modeled as a min-cost network flow problem, in which nodes represent circuit transform options. by carefully determining the structure of the network graph and the cost of each arc, a set of near-optimal transform options can be obtained as those whose corresponding nodes in the network graph have the min-cost flow passing through them. we also tie the transform selection network graph to a detailed placement network graph with td arc costs for cell movements. this enables our algorithms to incorporate considerations of detailed placement cost for each synthesis transform along with the basic cost of applying the transform in the circuit. we have tested our algorithms on three sets of benchmarks under 3--10% area increase constraints, and obtained up to 48% and an average of 27.8% timing improvement. our average improvement is relatively 40% better (8.2% better by an absolute measure) than applying the same set of transforms in a good sequential order that is used in many current techniques. considering only synthesis transforms (no replacement), our technique is relatively 50% better than the sequential approach.
roadnoc: runtime observability for an adaptive network on chip architecture. hard-to-predict system behavior and/or reliability issues resulting from migrating to new technology nodes requires considering runtime adaptivity in future on-chip systems. runtime observability is a prerequisite for runtime adaptivity as it is providing necessary system information gathered on-the-fly. we are presenting the first comprehensive runtime observability infrastructure for an adaptive network on chip architecture which is flexible (e.g. in choosing the routing path), hardly intrusive, and requires little additional overhead (around 0.7% of the total link bandwidth). the hardware overhead is negligible, too, and is in fact less than the hardware savings due to resource multiplexing capabilities that are achieved through runtime observability/adaptivity. as an example, our on-demand buffer assignment scheme increases the buffer utilization and decreases the overall buffer requirements by an average of 42% (the buffer area amounts to about 60% of the entire router area [19]) in our case study analysis compared to a fixed buffer assignment scheme [7]. our runtime observability on an average also increases the connection success rate by 62% compared to the case without runtime observability for the applications from the e3s benchmark suite [6]. we show the advantages obtained through runtime observability and compare with state-of-the art communication-centric designs.
a novel sequential circuit optimization with clock gating logic. to save power consumption, it has been shown that the clock signal can be gated without changing the functionality under certain clock-gating conditions. we observe that the clock-gating conditions and the next-state function of a flip-flop (ff) are correlated and can be used for sequential optimization. we show that the implementation of the next-state function of any ff can be just an inverter if the clock signal is appropriately gated. by exploiting the flexibility between the clock-gating conditions and the next-state function, we propose an iterative optimization technique to minimize the overall timing.
verification of arithmetic datapaths using polynomial function models and congruence solving. this paper addresses the problem of solving finite word-length (bit-vector) arithmetic with applications to equivalence verification of arithmetic datapaths. arithmetic datapath designs perform a sequence of add, mult, shift, compare, concatenate, extract, etc., operations over bit-vectors. we show that such arithmetic operations can be modeled, as constraints, using a system of polynomial functions of the type f: z2n1 x z2n2 x &middot;&middot;&middot; x z2nd &rarr; z2m. this enables the use of modulo-arithmetic based decision procedures for solving such problems in one unified domain. we devise a decision procedure using newton's p-adic iteration to solve such arithmetic with composite moduli, while properly accounting for the word-sizes of the operands. we describe our implementation and show how the basic p-adic approach can be improved upon. experiments are performed over some communication and signal processing designs that perform non-linear and polynomial arithmetic over word-level inputs. results demonstrate the potential and limitations of our approach, when compared against sat-based approaches.
deterministic analog circuit placement using hierarchically bounded enumeration and enhanced shape functions. the analog placement algorithm plantage, presented in this paper, generates placements for analog circuits with comprehensive placement constraints. plantage is based on a hierarchically bounded enumeration of basic building blocks, using b*-trees. the practically relevant solution space is thereby enumerated quasi-complete. the sets of possible placements of the basic building blocks are represented and combined in a new efficient way, using enhanced shape functions. the result of plantage is the pareto front of placements with respect to different aspect ratios. the whole approach is deterministic, in contrast to existing analog placement algorithms.
importance sampled circuit learning ensembles for robust analog ic design. this paper presents iscles, a novel and robust analog design method that promises to scale with moore's law, by doing boosting-style importance sampling on digital-sized circuits to achieve the target analog behavior. iscles consists of: (1) a boosting algorithm developed specifically for circuit assembly; (2) an iscles-specific library of possible digital-sized circuit blocks; and (3) a recently-developed multi-topology sizing technique to automatically determine each block's topology and device sizes. iscles is demonstrated on design of a sinusoidal function generator and a flash a/d converter, showing promise to robustly scale with shrinking process geometries.
smoothed form of nonlinear phase macromodel for oscillators. this paper proposes an improvement to the well-known oscillator nonlinear phase macromodel based on floquet theory. a smoothed form of the nonlinear phase macromodel is derived by eliminating highly oscillatory terms in the macromodel, resulting in a significant speed-up in transient simulation. for an lc oscillator under sinusoidal excitation the new macromodel is equivalent to the adler model. numerical experiments confirm a considerable decrease of computational efforts. it is further shown that the new macromodel allows one to perform phase noise analysis of locked oscillators under arbitrary periodic injection.
power supply noise aware workload assignment for multi-core systems. as the industry moves from single- to multi-core processors, the challenges of how to reliably design and analyze power delivery for such systems also arise. we study various workload assignments to cores and their impact on the global power grid noise. we develop metrics to estimate the amount of noise propagated from core to core and propose a power supply noise aware workload assignment method. in our experiments, we show that performance loss can be significant if workload assignment is not properly made.
boolean factoring and decomposition of logic networks. this paper presents new methods for restructuring logic networks based on fast boolean techniques. the basis for these are 1) a cut-based view of a logic network, 2) exploiting the uniqueness and speed of disjoint-support decompositions, 3) a new heuristic for speeding these up, 4) extending these to general decompositions, and 5) limiting local transformations to functions with 16 or less inputs so that fast truth table manipulations can be used in all operations. boolean methods lessen the structural bias of algebraic methods, while still allowing for high speed and multiple iterations. experimental results on k-lut networks show an average additional reduction of 5.4% in lut count, while preserving delay, compared to heavily optimized versions of the same networks.
efficient and accurate eye diagram prediction for high speed signaling. this paper introduces an accumulative prediction method to predict the eye diagram for high speed signaling systems. we use the step responses of pull-up and pull-down to extract the worst-case eye diagram, including the eye height and jitter. furthermore, the method produces the input patterns of the worst-case intersymbol interference. the algorithm handles signals of either symmetric or asymmetric rise/fall time. experimental results demonstrate the accuracy and efficiency of the proposed method.
linear constraint graph for floorplan optimization with soft blocks. in this paper, we propose the linear constraint graph (lcg) as an efficient general floorplan representation. for n blocks, an lcg has at most 2n+3 vertices and at most 6n+2 edges. operations with direct geometric meanings are developed to perturb the lcgs. we apply the lcgs to the floorplan optimization with soft blocks to leverage its advantage in terms of the sizes of the graphs, which will improve the efficiency of solving a complex mathematical program in the inner loop of the optimization that decide the block shapes without introducing overlaps to the non-slicing floorplans. experimental results confirm that the lcgs are effective and efficient.
on capture power-aware test data compression for scan-based testing. large test data volume and high test power are two of the major concerns for the industry when testing large integrated circuits. with given test cubes in scan-based testing, the "don't-care" bits can be exploited for test data compression and/or test power reduction. prior work either targets only one of these two issues or considers to reduce test data volume and scan shift power together. in this paper, we propose a novel capture power-aware test compression scheme that is able to keep scan capture power under a safe limit with little loss in test compression ratio. experimental results on benchmark circuits demonstrate the efficacy of the proposed approach.
system-level power estimation using an on-chip bus performance monitoring unit. in this paper we propose an on-chip bus pmu which makes accurate estimates of system power consumption from a first-order linear power model by utilizing system-level activity information exchanged on the on-chip bus. it can easily be customized for different on-chip and off-chip memory devices, and is not dependent on a specific cpu core. we model memory devices using energy state machines, describe them in xml, and use that description automatic synthesis of the pmu. we compare the short-term accuracy of the proposed pmu with a cycle-accurate system-level power estimator, and assess its long-term accuracy with a real hardware prototype. experimental results show that the the power estimation deviates less than 5% from real measurements.
texture filter memory: a power-efficient and scalable texture memory architecture for mobile graphics processors. with increasing interest in sophisticated graphics capabilities in mobile systems, energy consumption of graphics hardware is becoming a major design concern in addition to the traditional performance enhancement criteria. among the different steps in the graphics processing pipeline, we have observed that memory accesses during texture mapping -- a highly memory intensive phase - contribute 30-40% of the energy consumed in typical embedded graphics processors. this makes the texture mapping subsystem an attractive candidate for energy optimization. we argue that a standard cache hierarchy, commonly used by researchers and commercial graphics processors for texture mapping, is wasteful of energy, and propose the texture filter memory, an energy efficient architecture that exploits locality and the relatively high degree of predictability in texture memory access patterns. our architecture consumes 75% lesser energy for texturing in a fixed function pipeline, incurring no performance overhead and a small area overhead over conventional texture mapping hardware.
nanolithography and cad challenges for 32nm/22nm and beyond. the semiconductor industry is stuck at 193nm lithography as the main workhorse for manufacturing integrated circuits of 45nm and most likely 32nm nodes. on one hand, many novel approaches are being developed to extend the 193nm lithography, including immersion, double patterning, and exotic resolution enhancement techniques. on the other hand, next generation lithography, in particular, extreme ultra violet lithography (euvl) is projected by itrs as the main contender for technology nodes at or below 22nm, though significant challenges still exist from both technology and economy aspects. this tutorial will cover key nanolithography and cad challenges with possible solutions for 32nm/22nm (and beyond?), from the underlying hardware/equipment perspectives (for double patterning, euv, and so on), to the computational lithography aspects (extreme ret, inverse lithography, pixelated mask, etc.), and to the key eda issues on nanolithofriendly layouts (e.g., double patterning compliance layout, and so on).
game-theoretic timing analysis. estimating the worst-case execution time (wcet) of tasks is a key step in the design of reliable real-time software and systems. in this paper, we present a new, game-theoretic approach to estimating wcet based on performing directed measurements on the target platform. we model the estimation problem as a game between our algorithm (player) and the environment of the program (adversary), where the player seeks to find the longest path through the program while the adversary sets environment parameters to thwart the player. we present both theoretical and experimental results demonstrating the utility of our approach. on the theoretical side, we prove that our algorithm can converge to find the longest path with high probability. experimental results indicate that our approach is competitive with an existing technique based on static analysis and integer programming. moreover, the approach can be easily applied to even complex hardware/software platforms.
minimizing the energy cost of throughput in a linear pipeline by opportunistic time borrowing. in this paper, we present a technique to optimize the energy-delay product of a synchronous linear pipeline circuit with dynamic error detection and correction capability running. the technique dynamically adjusts the supply voltage level and clock frequency of the design by exploiting slacks that are present in various stages of the pipeline. the key enabler is the utilization of soft-edge flip-flops to allow time borrowing between consecutive stages of the pipeline in order to provide the timing-critical stages with more time to complete their computations resulting in lower error probability. this raises the effective throughput of the pipeline for a fixed energy consumption level, or alternatively, lowers the energy consumption for the same effective throughput. we formulate the problem of optimally selecting the transparency window sizes of the soft-edge flip-flops and the frequency level of the pipeline circuit at different voltage levels so as to optimize the energy cost of the achieved throughput. experimental results show the efficacy of the problem formulation and solution technique.
sram dynamic stability: theory, variability and analysis. technology scaling in sub-100nm regime has significantly shrunk the sram stability margins in data retention, read and write operations. conventional static noise margins (snms) are unable to capture nonlinear cell dynamics and become inappropriate for state-of-the-art srams with shrinking access time and/or advanced dynamic read-write-assist circuits. using the insights gained from rigorous nonlinear system theory, we define the much needed sram dynamic noise margins (dnms). the newly defined dnms not only capture key sram nonlinear dynamical characteristics but also provide valuable design insights. furthermore, we show how system theory can be exploited to develop cad algorithms that can analyze sram dynamic stability characteristics three orders of magnitude faster than a brute-force approach while maintaining spice-level accuracy. we also demonstrate a parametric dynamic stability analysis approach suitable for low-probability cell failures, leading to three orders of magnitude runtime speedup for yield analysis under high-sigma parameter variations.
routing for chip-package-board co-design considering differential pairs. nanometer effects have complicated the designs of chips as well as packages and printed circuit boards (pcb's). in order to improve the performance, convergence, and signal integrity of the design, chip-package-board co-design is strongly recommended by industry. in this paper, we present the first routing algorithm in the literature for chip-package-board co-design with differential-pair considerations. our algorithm is based on linear programming and integer linear programming and guarantees to find an optimal solution for the addressed problem. it first creates globalrouting paths among chips, packages, and a pcb. without loss of the solution optimality, our routing formulation can reduce the numbers of integer variables (constraints) by 95% (99%) on average. then, any-angle routing is applied to complete the routing. experimental results based on five real industry designs show that our router can achieve 100% routability and the optimal global-routing wirelength and satisfy all differential-pair constraints, under reasonable cpu times, whereas recent related work results in much inferior solution quality.
proactive temperature balancing for low cost thermal management in mpsocs. designing thermal management strategies that reduce the impact of hot spots and on-die temperature variations at low performance cost is a very significant challenge for multiprocessor system-on-chips (mpsocs). in this work, we present a proactive mpsoc thermal management approach, which predicts the future temperature and adjusts the job allocation on the mpsoc to minimize the impact of thermal hot spots and temperature variations without degrading performance. in addition, we implement and compare several reactive and proactive management strategies, and demonstrate that our proactive temperature-aware mpsoc job allocation technique is able to dramatically reduce the adverse effects of temperature at very low performance cost. we show experimental results using a simulator as well as an implementation on an ultrasparc t1 system.
mute-aes: a multiprocessor architecture to prevent power analysis based side channel attack of the aes algorithm. side channel attack based upon the analysis of power traces is an effective way of obtaining the encryption key from secure processors. power traces can be used to detect bitflips which betray the secure key. balancing the bitflips with opposite bitflips have been proposed, by the use of opposite logic. this is an expensive solution, where the balancing processor continues to balance even when encryption is not carried out in the processor. we propose, for the first time, a multiprocessor algorithmic balancing technique to prevent power analysis of a processor executing an aes cryptographic program, a popular encryption standard for embedded systems. our technique uses a dual processor architecture where two processors execute the same program in parallel, but with complementary intermediate data, thus balancing the bitflips. the second processor works in conjunction with the first processor for balancing only when the aes encryption is performed, and both processors carry out independent tasks when no encryption is being performed. accessing the encryption key or the input data by the first processor begins the obfuscation by the second processor. to stop the encryption by the second processor, we use a novel signature detection technique, which detects the end of the encryption automatically. the multiprocessor balancing approach (muteaes) proposed here reduces performance by 0.42% and increases the size of the hardware by 2x (though reduces to 0.1% when no encryption is being performed). we show that differential power analysis (dpa) fails when our technique is applied to aes. we further illustrate, that by the use of this balancing strategy, the adversary is left with noise from the power profile with little useful information.
double patterning technology friendly detailed routing. double patterning technology (dpt) is a most likely lithography solution for 32/22nm technology nodes as of 2008 due to the delay of extreme ultra violet lithography. however, it should hurdle two challenges before being introduced to mass production, layout decomposition and overlay error. in this paper, we present the first detailed routing algorithm for dpt to improve layout decomposability and robustness against overlay error, by minimizing indecomposable wirelength and the number of stitches. experimental results show that the proposed approach improves the quality of layout significantly in terms of decomposability and the number of stitches with 3.6x speedup, compared with a current industrial dpt design flow.
a framework for predictive dynamic temperature management of microprocessor systems. the sustained push for performance, transistor count and instruction level parallelism has reached a point where ic thermal issues are at the forefront of design constraints. many of the current systems deploy dynamic voltage and frequency scaling (dvfs) to address thermal emergencies. dvfs has certain limitations in terms of response lag, scalability and being reactive. on the other hand, several hardware based control theoretic schemes have been proposed to deliver optimal performance, but such schemes come at high cost and lack flexibility and scalability. in this paper, we present an alternative thermal monitoring and management system that utilizes software and hardware components, based on virtual machine concept. the proposed scheme delivers targeted, localized, and preemptive thermal management at low cost, adapts well to a multitasking environment, while delivering maximum performance under thermal stress.
automated abstraction by incremental refinement in interpolant-based model checking. this paper addresses the field of unbounded model checking (umc) based on sat engines, where craig interpolants have recently gained wide acceptance as an automated abstraction technique. we start from the observation that interpolants can be quite effective on large verification instances. as they operate on sat-generated refutation proofs, interpolants are very good at automatically abstract facts that are not significant for proofs. in this work, we push forward the new idea of generating abstractions without resorting to sat proofs, and to accept (reject) abstractions whenever they (do not) fulfill given adequacy constraints. we propose an integrated approach smoothly combining the capabilities of interpolation with abstraction and over-approximation techniques, that do not directly derive from sat refutation proofs. the driving idea of this combination is to incrementally generate, by refinement, an abstract (over-approximate) image, built up from equivalences, implications, ternary and localization abstraction, then (eventually) from sat refutation proofs. experimental results, derived from the verification of hard problems, show the robustness of our approach.
pyramids: an efficient computational geometry-based approach for timing-driven placement. the purpose of global placement is to find non-overlapping locations for cells, typically while minimizing a wirelength objective. because of this objective, however, when more timing information about the design is known, some cells will inevitably be sub-optimally placed from a timing perspective. in this paper, we present two new techniques to incrementally improve placements by moving cells to their optimal timing locations. we call our approach pyramids, since it uses pyramid-shaped delay surfaces to solve for the optimal location, rather than running a more expensive linear programming solver. we show how to apply these techniques to timing-driven detailed placement and also for more accurate latestage incremental timing correction. experimental results validate the effectiveness of pyramids by showing significantly improved timing after an industrial placement algorithm. furthermore, compared to the linear programming solvers, the speedup of pyramids solver is 373x vs. clp and 448x vs. glpk.
embedded software verification: challenges and solutions. embedded software are becoming more and more pervasive in our lives, and many application domains have very high reliability requirements. ensuring high software quality while still maintaining software productivity is a challenging task. in order to address this challenge, more formal analysis and automated verification techniques are needed in addition to standard software testing. in this tutorial, we will showcase the important ideas and techniques of software formal verification, including static program analysis, program modeling and (bounded) model checking, and predicate abstraction refinement. we will emphasize some of the key techniques that have been successfully adopted by recent, industrial-strength software verification tools. in this tutorial, we will focus on detecting bugs in sequential programs written in c/c++ for portable devices as well as for general purpose platforms. the tutorial will be tailored to the iccad audience by emphasizing the use of decision procedures such as bdds, presburger arithmetic, bit-vector arithmetic, sat and smt solvers. many of these techniques have been used in the context of analyzing, optimizing, and verifying ic designs. by attending this tutorial, the audience will get a better understanding of the challenges and potential solutions of embedded software verification.
mixed-signal simulation challenges and solutions. the design of complex mixed-signal system-on-a-chip (soc) designer poses challenging requirements on the simulation design environment. the simulation platform has to include simulations at the behavioral, gate and transistor-level which have traditionally been done in separate environments. as the scaling trend continues, the designer needs additional accuracy and capacity, new capabilities such as efficient statistical simulation that takes into account layout dependent effects. in this panel we have representatives from the cad and design community discussing the challenges and current solutions available to the mixed-signal simulation challenge.
a succinct memory model for automated design debugging. in today's complex soc designs, verification and debugging are becoming ever more crucial and increasingly time-consuming tasks. the prevalence of embedded memories adds to the difficulty of the problem by exponentially increasing the statespace of the design. in this work, a novel memory model for design debugging is presented. it models memory succinctly by avoiding an explicit representation for each memory bit. the method uses the simulation of the erroneous design to guide the debugging process. this results in a parameterizable formal encoding that grows linearly with the erroneous trace length, significantly reducing the memory requirements of the debugging problem. in addition, the proposed model is extended to handle an arbitrary initial memory configuration, as well as non-cycle accurate output traces where only a final expected memory state is available for comparison. experiments on industrial designs show a 96% average reduction in memory usage along with a noticeable performance improvement compared to previous work.
placement based multiplier rewiring for cell-based designs. we present an algorithm for improving the performance of carry-save-adder (csa) style multipliers. based on placement information, the algorithm exploits the arithmetic equivalence in the csa multipliers and rewires to improve the slack of the multiplier.
decoupling capacitance allocation for timing with statistical noise model and timing analysis. this paper presents an allocation method of decoupling capacitance that explicitly considers timing. we have found and focused that decap does not necessarily improve a gate delay at all the switching timing within a cycle, and devised an efficient sensitivity calculation of timing to decap for decap allocation. the proposed method, which is based on a statistical noise modeling and timing analysis, accelerates the sensitivity calculation with an approximation and adjoint sensitivity analysis. experimental results show that the decap allocation based on the sensitivity analysis efficiently optimizes the worst-case circuit delay within a given decap budget. compared to the maximum decap placement, the delay improvement due to decap increases by 5% even while the total amount of decap is reduced to 40%.
statistical path selection for at-speed test. process variations make at-speed testing significantly more difficult. they cause subtle delay changes that are distributed rather than the localized nature of a traditional fault model. due to parametric variations, different paths can be critical in different parts of the process space, and the union of such paths must be tested to obtain good process space coverage. this paper proposes a novel branch-and-bound algorithm that elegantly and efficiently solves the hitherto open problem of statistical path tracing. the resulting paths are used for at-speed structural testing. a new test quality metric (tqm) is proposed and paths which maximize this metric are selected. after chip timing has been performed, the path selection procedure is extremely efficient. path selection for a multi-million gate chip design can be completed in a matter of seconds.
hybrid cmos-sttram non-volatile fpga: design challenges and optimization approaches. research efforts to develop a novel memory technology that combines the desired traits of non-volatility, high endurance, high speed and low power have resulted in the emergence of spin torque transfer-ram (sttram) as a promising next generation universal memory. however, the prospect of developing a non-volatile fpga framework with sttram exploiting its high integration density remains largely unexplored. in this paper, we propose a novel cmos-sttram hybrid fpga framework; identify the key design challenges; and propose optimization techniques at circuit, architecture and application mapping levels. simulation results show that a sttram based optimized fpga framework achieves an average improvement of 48.38% in area, 22.28% in delay and 16.1% in dynamic power for iscas benchmark circuits over a conventional cmos based fpga design.
power supply signal calibration techniques for improving detection resolution to hardware trojans. chip design and fabrication is becoming increasingly vulnerable to malicious activities and alternations with globalization. an adversary can introduce a trojan designed to disable and/or destroy a system at some future time (time bomb) or the trojan may serve to leak confidential information covertly to the adversary. this paper proposes a taxonomy for trojan classification and then describes a statistical approach for detecting hardware trojans that is based on the analysis of an ics power supply transient signals. a key component to improving the resolution of power analysis techniques to trojans is calibrating for process and test environment (pe) variations. the main focus of this research is on the evaluation of four signal calibration techniques, each designed to reduce the adverse impact of pe variations on our statistical trojan detection method.
fault tolerant placement and defect reconfiguration for nano-fpgas. when manufacturing nano-devices, defects are a certainty and reliability becomes a critical issue. until now, the most pervasive methods used to address reliability, involve injecting spare resources. however, these methods use predetermined spare placement that is not optimized for each netlist. this is the first work (to the best of our knowledge) that addresses the problem of fault tolerance for nano-fpgas at the placement stage; fault tolerant placements are generated that are amenable to fast defect reconfiguration through replacement of defective logic elements with spares. we propose a simulated-annealing based placement algorithm that produces placements with the objective of maximizing the chances of successful recovery from faults in logic elements within the circuit's timing constraints. in addition, our study of the fault reconfiguration problem shows it is np-complete, and we propose a fast scheme for achieving a good reconfiguration solution for a random or clustered fault map. experimental results show that these techniques can increase the probability of successful fault reconfiguration by 55% (compared to a uniform spare distribution scheme), without significantly degrading the circuit performance.
path-ro: a novel on-chip critical path delay measurement under process variations. as technology scales to 45nm and below, process variations will present significant impact on path delay. this trend makes the deviation between simulated path delay and actual path delay in a manufactured chip more significant. in this paper, we propose a new on-chip path delay measurement structure called path-based ring oscillator (path-ro). the proposed method creates an oscillator from a targeted path for which it is used to measure path delay on-chip under the impact of process variations. to alleviate accuracy degradation caused by the architecture itself, a high-accuracy calibration process is presented. through experimental results on path-ros inserted in itc'99 b19 benchmark, we obtain path delay distribution under different process variations. the accuracy and efficiency of path delay measurement using path-ro are also verified by comparing the results obtained from post-layout hspice simulations.
steel: a technique for stress-enhanced standard cell library design. mobility degradation and device scaling limitations have led process engineers to develop new techniques that introduce mechanical stress in mosfet channels, which results in enhanced carrier transport. new fabrication steps strive to increase carrier mobility which, consequently, increases both ion and ioff in cmos devices. however, most stress-enhancement techniques are dependent on layout parameters and their effects can be exploited within standard cell library design. in this work, we propose a new standard cell library design methodology that shares vdd and vss source/drain connections across standard cell boundaries. such sharing allows for increased channel stress in both the corresponding device as well as its neighboring devices. using an industrial 65nm process and standard cell library, we show that our standard cell design methodology can be seamlessly integrated into current, state-of-the-art digital ic design flows. the new shared source/drain technique improves critical path delay by 11% on average over a number of benchmarks for only a ~35% increase in leakage. further-more, stress-enhanced standard cell libraries offer a superior power/delay tradeoff compared to dual-vth across a wide range of operating points with reduced manufacturing costs. specifically, our stress-enhanced library (with a single vth) consumes ~2.5x less leakage than its dual-vth counterpart.
to sat or not to sat: ashenhurst decomposition in a large scale. functional decomposition is a fundamental operation in logic synthesis. prior bdd-based approaches to functional decomposition suffer from the memory explosion problem and do not scale well to large boolean functions. variable partitioning has to be specified a priori and often restricted to a few bound-set variables. moreover, non-disjoint decomposition requires substantial sophistication. this paper shows that, when ashenhurst decomposition (the simplest and preferable functional decomposition) is considered, both single and multiple-output decomposition can be formulated with satisfiability solving, craig interpolation, and functional dependency. variable partitioning can be automated and integrated into the decomposition process without the bound-set size restriction. the computation naturally extends to nondisjoint decomposition. experimental results show that the proposed method can effectively decompose functions with up to 300 input variables.
race analysis for systemc using model checking. systemc is a system-level modeling language that offers a wide range of features to describe concurrent systems at different levels of abstraction. the systemc standard permits simulators to implement a deterministic scheduling policy, which often hides concurrency-related design flaws. we present a novel compiler for systemc that integrates a formal and scalable race analysis. this analysis combines both classic static analysis and model checking techniques. the outcome of the analysis is not only valuable to diagnose the effect of race conditions, but can also be used to improve simulation performance dramatically. our compiler produces a simulator that uses the race analysis information at runtime to perform partial-order reduction, thereby eliminating context switches that do not affect the result of the simulation. experimental results show simulation speedups of one order of magnitude and better.
obstacle-avoiding rectilinear steiner tree construction. in today's vlsi designs, there can be many blockages in a routing region. the obstacle-avoiding rectilinear steiner minimum tree (oarsmt) problem has become an important problem in the physical design stage of vlsi circuits. this problem has attracted a lot of attentions in research and several approaches have been proposed to solve this problem effectively. in this paper, we will present a heuristic maze routing based approach to solve this oarsmt problem. it is commonly believed that maze routing based approaches can only handle small scale problems and there is a lack of an effective multi-terminal variant to handle multi-pin nets in practice. we will show in this paper that maze routing based approaches can also handle large scale oarsmt problems effectively. our approach is based on the searching process as in maze routing and can handle multi-pin nets very well in both solution quality, running time and memory space usage. we have compared our results with those of the previous works and can show that we can out-perform the best previous results on this problem [15] by giving an oarsmt with 2.01% less wire length on average and can make a 27.04% improvement in wire length in comparison with a lower bound of the optimal solution on average, while the running times are all very short and comparable to those in [15]. besides, due to the flexibility of maze routing, we can handle different kinds of obstacles with different convex or concave rectilinear shapes directly without a need to partition each blockage into a set of rectangular sub-blockages, which will increase the size of the problem.
impulse sensitivity function analysis of periodic circuits. this paper describes an efficient method to characterize the impulse sensitivity function (isf) of a periodic circuit via periodic ac (pac) analysis. the paper extends the application of isf from oscillators to other periodic circuits including flip-flops, latches, clocked comparators, and regenerative amplifiers, in order to characterize their important characteristics such as set-up and hold times, regeneration gain, metastability probability, and sampling aperture/bandwidth. recognizing that the generalized isf is a subset of a time-varying impulse response, the isf is efficiently computed based on periodic time-varying system analysis techniques. compared to the previous isf characterization method based on transient simulations, a speedup of ~5x is achieved.
constrained aggressor set selection for maximum coupling noise. in this paper, we consider the problem of selecting a set of aggressor nets that maximize crosstalk induced noise or delay pushout on a coupled victim net, under given logical constraints. we formulate the problem mathematically, and propose efficient lagrangian relaxation and network flow based approaches that guarantee an optimal solution. we also formulate and solve this problem while considering the noise susceptibility of the victim's receiving gate. experimental results show that the proposed approaches are run-time efficient by factors of up to 800x in comparison to an exhaustive search approach, and reduce timing pessimism by up to 36%.
using test data to improve ic quality and yield. the complexity of interactions in today's manufacturing processes makes test structures and experiments inadequate as sole drivers of yield-learning and design-for-manufacturing [dfm]. they must be driven by product impact. product-impact-oriented test-based learning provides insight into the nature of model-hardware mismatches and variability that exist on and impact real products. that insight can be used to drive both parametric and defect-oriented process actions and dfm.
layout decomposition for double patterning lithography. in double patterning lithography (dpl) layout decomposition for 45nm and below process nodes, two features must be assigned opposite colors (corresponding to different exposures) if their spacing is less than the minimum coloring spacing [11, 9, 5]. however, there exist pattern configurations for which pattern features separated by less than the minimum color spacing cannot be assigned different colors. in such cases, dpl requires that a layout feature be split into two parts. we address this problem using a layout decomposition algorithm that includes graph construction, conflict cycle detection, and node splitting processes. we evaluate our technique on both real-world and artificially generated testcases in 45nm technology. experimental results show that our proposed layout decomposition method effectively decomposes given layouts to satisfy the key goals of minimized line-ends and maximized overlap margin. there are no design rule violations in the final decomposed layout.
fbt: filled buffer technique to reduce code size for vliw processors. vliw processors provide higher performance and better efficiency etc. than risc processors in specific domains like multimedia applications etc. a disadvantage is the bloated code size of the compiled application code. therefore, reducing the application code size is a design key issue for vliw processors. in this paper we adapt a hardware-supported approach called "deflate" [12] which has been used before in data compression. it can significantly reduce the code size compared to state-of-the-art approaches for vliw processors as we will show within this work. in fact, we enhance the "deflate" algorithm by using a new technique called filled buffer technique which can be applied to any lempel-ziv family algorithms to improve compression ratio in average by more than 13% compared to the sole "deflate" algorithm. using our filled buffer technique in conjunction with "v2f" [15] improves the compression ratio by 10%. we have conducted evaluations using a representative set of benchmarks (from mediabench and mibench) and have applied our scheme to two vliw processors, namely tms320c62x and tms320c64x. we achieved allover compression ratios as low as 44% using the "deflate" algorithm (61% and 56% in average for tms320c62x and tms320c64x, respectively).
performance optimization of elastic systems using buffer resizing and buffer insertion. buffer resizing and buffer insertion are two transformation techniques for the performance optimization of elastic systems. different approaches for each technique have already been proposed in the literature. both techniques increase the storage capacity and can potentially contribute to improve the throughput of the system. each technique offers a different trade-off between area cost and latency. this paper presents a method that combines both techniques to achieve the maximum possible throughput while minimizing the cost of the implementation. the provided method is based on mixed integer linear programming. a set of experiments is designed to show the feasibility of the approach.
a low-overhead fault tolerance scheme for tsv-based 3d network on chip links. three-dimensional die stacking integration provides the ability to stack multiple layers of processed silicon with a large number of vertical interconnects. through silicon vias (tsvs) provide a promising area- and power-efficient way to support communication between different stack layers. unfortunately, low tsv yield significantly impacts design of three-dimensional die stacks with a large number of tsvs. this paper presents a defecttolerance technique for tsvs-based multi-bit links through an efficient and effective use of redundancy. this technique is ideally suited for three-dimensional network-on-chip (noc) links. simulation results demonstrate significant yield improvement, from 66% to 98%, with a low area cost (17% on a vertical link in a noc switch, which leads a modest 2.1% increase the total switch area) in 130nm technology, with minimal impact of vlsi design and test flows.
robust reconfigurable filter design using analytic variability quantification techniques. in this paper, we develop a variability-aware design methodology for reconfigurable filters used in multi-standard wireless systems. to model the impact of statistical circuit component variations on the predicted manufacturing yield, we implement several different analytic variability quantification techniques based on a double-sided implementation of the first and second order reliability methods (form and sorm), which provide several orders of magnitude improvement in computational complexity over statistical sampling methods. leveraging these efficient analytic variability quantification techniques, we employ an optimization approach using sequential quadratic programming to simultaneously determine the fixed and tunable/switchable circuit element values in an arbitrary-order canonical filter to improve the overall robustness of the filter design when statistical variations are present. the results indicate that reconfigurable filters and impedance matching networks designed using the proposed methodology meet the specified performance requirements with a 26% average absolute yield improvement over circuits designed using deterministic techniques.
context-sensitive static transistor-level ir analysis. with advances in semiconductor process technology, chip power density has dramatically increased, making power grid integrity a critical concern at all stages of the design process. given the inherent difficulty of capturing worst-case ir drops for all logic gates with dynamic vectors, a static flow is essential for verifying grid integrity on complex chip designs, especially microprocessors. a novel static transistor-level ir drop analysis flow which significantly reduces the conservatism of other static flows is presented. the key feature of this flow is a fast nand decision diagram (ndd) algorithm, a lightweight variant of a boolean decision diagram (bdd) with the capacity to effectively process device transition exclusions in a per logical-device, context-sensitive fashion, thereby radically reducing the conservatism typical of static analysis.
advancing supercomputer performance through interconnection topology synthesis. in today's many-core era, the interconnection networks have been the key factor that dominates the performance of a computer system. in this paper, we propose a design flow to discover the best topology in terms of the communication latency and physical constraints. first a set of representative candidate topologies are generated for the interconnection networks among computing chips; then an efficient multi-commodity flow algorithm is devised to evaluate the performance. the experiments show that the best topologies identified by our algorithm can achieve better average latency compared to the existing networks.
fastroute3.0: a fast and high quality global router based on virtual capacity. as an easily implemented approach, ripup and reroute has been employed by most of today's global routers, which iteratively applies maze routing to refine solution quality. but traditional maze routing is susceptible to get stuck at local optimal results. in this work, we will present a fast and high quality global router fastroute3.0, with the new technique named virtual capacity. virtual capacity is proposed to guide the global router at maze routing stage to achieve higher quality results in terms of overflow and runtime. during maze routing stage, virtual capacity works as a substitute for the real edge capacity in calculating the maze routing cost. there are two sub techniques included: (1) virtual capacity initialization, (2) virtual capacity update. before the maze routing stage, fastroute3.0 initializes the virtual capacity by subtracting the predicted overflow generated by adaptive congestion estimation (ace) from the real edge capacity. and in the following maze routing iterations, we further reduce the virtual capacity by the amount of existing overflow (edge usage minus real edge capacity) for the edges that are still congested. to avoid excessive "pushing-away" of routing wires, the virtual capacity is increased by a fixed percentage of the existing overflow if edge usage is smaller than real edge capacity. experimental results show that fastroute3.0 is highly proficient dealing with ispd98, ispd07 and ispd08 benchmark suites. the results outperform published ripup and reroute based academic global routers in both routability and runtime. in particular, (1) fastroute3.0 completes routing all the ispd98 benchmarks. (2) for ispd07 and ispd08 global routing contest benchmarks, it generates 12 out of 16 congestion free solutions. (3) the total runtime is enhanced greatly.
a new method to improve accuracy of leakage current estimation for transistors with non-rectangular gates due to sub-wavelength lithography effects. non-ideal pattern transfer from drawn circuit layout to manufactured nanometer transistors can severely affect electrical characteristics such as drive current, leakage current, and threshold voltage. obtaining accurate electrical models of non-rectangular transistors due to sub-wavelength lithography effects is indispensable for dfm-aware nanometer ic design. in this paper, tcad device simulations are utilized to quantify the accuracy of a standard equivalent gate length extraction approach for non-rectangular transistors. it is verified that threshold voltage and current density are non-uniform along the channel width due to narrow-width related edge effects, leading to significant inaccuracy in the sub-threshold region. a new egl extraction method utilizing location-dependent weighting factors and convex parameter extraction techniques is proposed to account for the current density non-uniformity. preliminary results verified by tcad simulations indicate that the accuracy of leakage current estimation for non-rectangular transistors can be significantly improved. the method is readily applicable to calibration with real silicon data.
parameterized transient thermal behavioral modeling for chip multiprocessors. in this paper, we propose a new architecture-level parameterized transient thermal behavioral modeling algorithm for emerging thermal related design and optimization problems for high-performance chip-multiprocessor (cmp) design. we propose a new approach, called parthermpof, to build the parameterized thermal performance models from the given architecture thermal and power information. the new method can include a number of parameters such as the locations of thermal sensors in a heat sink, different components (heat sink, heat spread, core, cache, etc.), thermal conductivity of heat sink materials, etc. the method consists of two steps: first, response surface method based on low-order polynomials is applied to build the parameterized models at each time point for all the given sampling nodes in the parameter space. second, an improved generalized pencil-of-function (gpof) method is employed to build the transfer-function based behavioral models for each time-varying coefficient of the polynomials generated in the first step. experimental results on a practical quad-core microprocessor show that the generated parameterized thermal model matchs the given data very well. parthermpof is very suitable for design space exploration and optimization where both time and system parameters need to be considered.
model reduction via projection onto nonlinear manifolds, with applications to analog circuits and biochemical systems. previous model order reduction methods fit into the framework of identifying the low-order linear subspace and using the linear projection to project the full state space into the low-order subspace. despite its simplicity, the macromodel might automatically include redundancies. in this paper, we present a model order reduction approach, named manimor, which extends the linear projection framework to a general nonlinear projection framework. the two key ideas of manimor are (1) it explicitly separates the construction of the low-order subspace and projection operation; (2) it constructs a nonlinear manifold which captures important system responses and defines the corresponding nonlinear projection operator. the low-order manifold subspace in manimor is identified by stitching together the low-order linear subspaces around a set of sample points on the manifold. after the manifold is determined, it is embedded into a global nonlinear coordinate system. the projection function is defined in a piece-wise linear manner, and the model evaluation is conducted directly in the manifold subspace using cheap matrix-vector product computations. as a result, a compact model is generated by precomputing all the functions and jacobians and storing them in a look-up table. we apply manimor on two analog circuits and a bio-chemical system to validate its correctness. extensive comparisons with the results of the full model and other macromodels are provided. experimental results show that manimor manages to obtain a huge reduction -- e.g., from 52 to 5 for the i/o buffer circuit and from 304 to 30 for yeast pheromone pathway system. this is less than half of the size of the tpwl model with the same accuracy. with great promise to capture important system responses, manimor presents a novel and powerful paradigm for nonlinear model reduction, and casts inspirations for further researches.
nthu-route 2.0: a fast and stable global router. we present in this paper a fast and stable global router called nthu-route 2.0 that improves the solution quality and runtime of a state-of-the-art router, nthu-route, by the following enhancements: (1) a new history based cost function, (2) new ordering methods for congested region identification and rip-up and reroute, and (3) two implementation techniques. the experimental results show that nthu-router 2.0 solves all ispd98 benchmarks with very good quality. moreover, it routes 7 of 8 ispd07 benchmarks without any overflow. in particular, for one of the ispd07 benchmarks which are thought to be difficult cases previously, nthu-route 2.0 can completely eliminate its total overflow. nthu-route 2.0 also successfully solves 12 of 16 ispd08 benchmarks without causing any overflow.
electrically driven optical proximity correction based on linear programming. conventional optical proximity correction (opc) tools aim to minimize edge placement errors (epe) due to the optical and resist process by moving mask edges. however, in low-k1 lithography, especially at 45nm and beyond, printing perfect polygons is practically impossible to achieve. in addition, prohibitively high mask complexity is incurred, leading to high mask cost. given the impossibility of perfect printing, we argue that aiming to reduce the error of electrical discrepancy between the ideal and the printed contours is a more reasonable strategy. in fact, we show that contours with non-minimal epe may result in closer match to the desired electrical performance. towards achieving this objective, we developed a new electrically driven opc (ed-opc) algorithm. the tool combines lithography simulation with accurate electrical modeling of resist contours to predict the on/off current through a transistor gate. the computation of mask edge movements is cast as a linear program based on optical and electrical sensitivities. the objective is to minimize the error in saturation current between printed and target shapes. this optimization is then solved with fast runtime. the results on industrial 45nm soi layouts using high-na immersion lithography models show up to a 5% improvement in accuracy of timing over conventional opc. this is achieved at less than 26% runtime overheads, while also lowering mask complexity by up to 43%. the results confirm that better timing accuracy can be achieved despite larger edge placement error.
guiding global placement with wire density. this paper presents an efficient technique for the estimation of the routed wirelength during global placement using the wire density of the net. the proposed method identifies congested regions of the chip and incorporates the model of the routed wirelength into the objective function in order to effectively alleviate these regions from congestion. the method is integrated in the analytical placement framework and the two-level structure improves the scalability of the placer and speeds up the algorithm. the proposed analytical placer provides the best-so-far average routed wirelength in the ibm version2 benchmark suite.
a voltage-frequency island aware energy optimization framework for networks-on-chip. in this paper, we present a partitioning, mapping, and routing optimization framework for energy-efficient vfi (voltage-frequency island) based network-on-chip. unlike the recent work [10] which only performs partitioning together with voltage-frequency assignment for a given mesh network layout, our framework consists of three key vfi-aware components, i.e., vfi-aware partitioning, vfi-aware mapping, and vfi-aware routing. thus our technique effectively reduces vfi overheads such as mixed clock fifos and voltage level converters by over 82% and energy consumption by over 9% compared with the previous state-of-art works [10].
on the modeling of resistance in graphene nanoribbon (gnr) for future interconnect applications. in this paper, we present a comprehensive model for the resistance in graphene nanoribbon (gnr) interconnects. we use the recent experimental and theoretical results to model the impact of stacking of graphene layers in multi-layer gnr interconnects. we compare the resistance of gnr interconnects with both single-walled carbon nanotube (swcnt) bundle interconnects and conventional copper interconnects. our simulation results demonstrate the performance superiority of multi-layer gnr interconnects over conventional copper interconnects at small widths (< 15 nm). consequently, multi-layer gnr interconnects demonstrate a great potential to replace conventioanl copper interconnects in future technologies.
synthesis from multi-cycle atomic actions as a solution to the timing closure problem. one solution to the timing closure problem is to perform infrequent operations in more than one cycle. despite simplicity of the solution statement, it is not easily considered because it requires changes in rtl, which, in turn, exacerbates the verification problem. we offer a timing closure solution guaranteed to preserve functional correctness of designs expressed using atomic actions or rules. we exploit the fact that the semantics of atomic actions are untimed, that is, the time to execute an action is not specified. the current hardware synthesis technique from atomic actions assumes that each rule takes one clock cycle to complete its computation. consequently, the rule with the longest combinational path determines the clock cycle of the entire design, often leading to needlessly slow circuits. we present a synthesis procedure for a system where the combinational circuits embodied in a rule can take multiple cycles without changing the semantics of the original design. we also present preliminary results based on an experimental compiler which uses the bluespec (bsv) compiler front end and generates verilog. the results show that the clock speed and the performance of circuits can be improved substantially by allowing slow paths to complete over multiple cycles. our technique is orthogonal to solutions based on multiple clock domains.
physical models for electron transport in graphene nanoribbons and their junctions. physics-based equivalent circuit models are presented for armchair and zigzag graphene nanoribbons (gnrs), and their conductances have been benchmarked against those of carbon nanotubes and copper wires. it is demonstrated that gnrs that have large coherence length behave like waveguides for electrons. this poses both challenges and opportunities for designing graphene nanoelectronic circuits.
practical, fast monte carlo statistical static timing analysis: why and how. statistical static timing analysis (ssta) has emerged as an essential tool for nanoscale designs. monte carlo methods are universally employed to validate the accuracy of the approximations made in all ssta tools, but monte carlo itself is never employed as a strategy for practical ssta. it is widely believed to be "too slow" -- despite an uncomfortable lack of rigorous studies to support this belief. we offer the first large-scale study to refute this belief. we synthesize recent results from fast quasi-monte carlo (qmc) deterministic sampling and efficient karhunen-lo&eacute;ve expansion (kle) models of spatial correlation to show that monte carlo ssta need not be slow. indeed, we show for the iscas89 circuits, a few hundred, well-chosen sample points can achieve errors within 5%, with no assumptions on gate models, wire models, or the core sta engine, with runtimes less than 90 s.
clock buffer polarity assignment combined with clock tree generation for power/ground noise minimization. a new approach to the problem of clock buffer polarity assignment for minimizing power/ground noise on the clock network is presented. the previous approaches solve the assignment problem in two separate steps: (step 1) generating a clock routing tree of minimum total wirelength, satisfying the clock skew constraint and then (step 2) inserting buffering elements with their polarities under the objective of minimizing power/ground noise while satisfying the clock skew constraint. yet, there is no easy way to predict the result of step 2 during step 1. in our approach, we place the primary importance on the cost of power/ground noise. consequently, we try to minimize the cost of power/ground noise first and then to construct a clock routing tree later while satisfying the clock skew constraint. through experimentation using several benchmark circuits, it is shown that this approach is quite effective and produces very good solutions, reducing the power/ground noise by 75% and the peak current by 26% at the expense of 5% wirelength overhead compared to that produced by the conventional approach.
design and optimization of a digital microfluidic biochip for protein crystallization. proteins crystallization is a commonly used technique for protein analysis and subsequent drug design. it predicts the three-dimensional arrangement of the constituent amino acids, which in turn indicates the specific biological function of a protein. protein crystallization experiments are typically carried out manually on multi-well plates in the laboratory. these experiments are slow, expensive, and error-prone. we present the design of a multi-well plate microfluidic biochip for protein crystallization; this biochip can transfer protein samples, prepare candidate solutions, and carry out crystallization automatically. to reduce the manufacturing cost of such devices, we present an efficient algorithm to generate a pin-assignment plan for the proposed design. the resulting biochip enables control of a large number of on-chip electrodes using only a small number of pins. based on the pin-constrained chip design, we present an efficient shuttle-passenger-like droplet manipulation method to achieve high-throughput and defect-tolerant well loading.
a polynomial time approximation scheme for timing constrained minimum cost layer assignment. as vlsi technology enters the nanoscale regime, interconnect delay becomes the bottleneck of circuit performance. compared to gate delays, wires are becoming increasingly resistive which makes it more difficult to propagate signals across the chip. however, more advanced technologies (65nm and 45nm) provide relief as the number of metal layers continues to increase. the wires on the upper metal layers are much less resistive and can be used to drive further and faster than on thin metals. this provides an entirely new dimension to the traditional wire sizing problem, namely, layer assignment for efficient timing closure. assigning all wires to thick metals improves timing, however, routability of the design may be hurt. the challenge is to assign minimal amount of wires to thick metals to meet timing constraints. in this paper, the minimum cost layer assignment problem is proven to be np-complete. as a theoretical solution for np-complete problems, a polynomial time approximation scheme is proposed. the new algorithm can approximate the optimal layer assignment solution by a factor of 1 + &epsilon; in o(m log log m &middot; n3/&epsilon;2) time for 0 < &epsilon; < 1, where n is the number of nodes in the tree and m is the number of routing layers. this work presents the first theoretical advance for the timing-driven minimum cost layer assignment problem. in addition to its theoretical guarantee, the new algorithm is highly practical. our experiments on 500 testcases demonstrate that the new algorithm can run 2x faster than the optimal dynamic programming algorithm with only 2% additional wire.
modeling and simulation for on-chip power grid networks by locally dominant krylov subspace method. fast analysis of power grid networks has been a challenging problem for many years. the huge size renders circuit simulation inefficient and the large number of inputs further limits the application of existing krylov-subspace macromodeling algorithms. however, strong locality has been observed that two nodes geometrically far have very small electrical impact on each other because of the exponential attenuation. however, no systematic approaches have been proposed to exploit such locality. in this paper, we propose a novel modeling and simulation scheme, which can automatically identify the dominant inputs for a given observed node in a power grid network. this enables us to build extremely compact models by projecting the system onto the locally dominant krylov subspace corresponding to those dominant inputs only. the resulting simulation can be very fast with the compact models if we only need to view the responses of a few nodes under many different inputs. experimental results show that the proposed method can have at least 100x speedup over spice-like simulations on a number of large power grid networks up to 1m nodes.
incorporating logic exclusivity (le) constraints in noise analysis using gain guided backtracking method. crosstalk noise becomes one of the critical issues gating design closure for nano-meter designs. pessimism in noise analysis can lead to significant additional time spent addressing false violations. taking logic correlation into consideration, noise analysis can reduce pessimism significantly by eliminating false noise signals [1]-[3][5]-[7][10]-[13]. eliminating the aggressors from the aggressor candidate set that can not switch simultaneously restricted by the logic exclusivity (le) relationship among them can save simulation time as well. the le problem, being proved as np-complete, is basically to determine the subset (possibly multiple equivalent subsets) of a given aggressor candidate set which has the largest combined weight out of all possible subsets governed by logic exclusivity constraints. this paper presents a new approach in resolving the le problem, which employs a gain guided backtrack search technique that does not require exhaustive search of all the binary paths to reach an optimal solution. we first prove that under certain conditions, if the gain at each level is non-negative, then the result will be optimal. based on this theorem, a new algorithm is developed. the experimental results demonstrate the efficiency and accuracy of this approach. the algorithm can quickly find the optimal solutions for most cases from industry designs and outperforms other methods.
process variability-aware transient fault modeling and analysis. due to reduction in device feature size and supply voltage, the sensitivity of digital systems to transient faults is increasing dramatically. as technology scales further, the increase in transistor integration capacity also leads to the increase in process and environmental variations. despite these difficulties, it is expected that systems remain reliable while delivering the required performance. reliability and variability are emerging as new design challenges, thus pointing to the importance of modeling and analysis of transient faults and variation sources for the purpose of guiding the design process. this work presents a symbolic approach to modeling the effect of transient faults in digital circuits in the presence of variability due to process manufacturing. the results show that using a nominal case and not including variability effects, can underestimate the ser by 5% for the 50% yield point and by 10% for the 90% yield point.
spm management using markov chain based data access prediction. leveraging the power of scratchpad memories (spms) available in most embedded systems today is crucial to extract maximum performance from application programs. while regular accesses like scalar values and array expressions with affine subscript functions have been tractable for compiler analysis (to be prefetched into spm), irregular accesses like pointer accesses and indexed array accesses have not been easily amenable for compiler analysis. this paper presents an spm management technique using markov chain based data access prediction for such irregular accesses. our approach takes advantage of inherent, but hidden reuse in data accesses made by irregular references. we have implemented our proposed approach using an optimizing compiler. in this paper, we also present a thorough comparison of our different dynamic prediction schemes with other spm management schemes. spm management using our approaches produces 12.7% to 28.5% improvements in performance across a range of applications with both regular and irregular access patterns, with an average improvement of 20.8%.
temperature aware task sequencing and voltage scaling. on-chip power density and temperature are rising exponentially with decreasing feature sizes. this alarming trend calls for temperature management at every level of system design. in this paper, we propose task sequencing as a powerful and complimentary mechanism to voltage scaling in improving the thermal profile of an embedded system executing a set of periodic heterogenous tasks under timing constraints. we first derive the peak temperature of a repeating task sequence analytically and develop a heuristic to construct the task sequence that minimizes the peak temperature. experimental evaluation shows that our task sequencing heuristic achieves peak temperature within 0.5&deg;c of the optimal solution and 7.47&deg;c lower, on an average, compared to the worst sequence for a large range of embedded task sets. we also propose an iterative algorithm that combines task sequencing with voltage scaling to further lower the peak temperature while satisfying the timing constraints. for embedded task sets, our combined task sequencing and voltage scaling approach achieves, on an average, 2.1&deg;c -- 6.94&deg;c reduction in peak temperature compared to voltage scaling alone.
hardware protection and authentication through netlist level obfuscation. hardware intellectual property (ip) cores have emerged as an integral part of modern system-on-chip (soc) designs. however, ip vendors are facing major challenges to protect hardware ips and to prevent revenue loss due to ip piracy. in this paper, we propose a novel design methodology for hardware ip protection and authentication using netlist level authentication. the proposed methodology can be integrated in the soc design and manufacturing flow to provide hardware protection to the ip vendors, the chip designer, and the system designer. simulation results on iscas-89 benchmark circuits show that we can achieve high levels of security through a well-formulated obfuscation scheme at less than 10% area overhead under delay constraint.
thermal-aware floorplanning for task migration enabled active sub-threshold leakage reduction. this paper presents a new approach to active sub-threshold leakage reduction using task migration. the main idea is to replicate a hot module in a design so as to actively migrate its computation at regular intervals, reducing the on-chip temperature and thereby the subthreshold leakage. we observe that choosing which blocks to migrate and their placement in a floorplan is a chicken-and-egg problem. to solve this, we propose a two step floorplanning methodology, wherein, given a base floorplan, we first choose the modules to replicate and then effectively utilize the deadspaces in it by exploiting the lateral conduction of heat in the floorplan to place a module's replica. with an optimized floorplan, using task migration we obtain an average savings of 29% in the active sub-threshold leakage at the expense of about 6% additional area.
a novel fixed-outline floorplanner with zero deadspace for hierarchical design. fixed-outline floorplanning, which enables hierarchical design, is considered more and more important nowadays. in this paper, a novel sa-based fixed-outline floorplanner with the optimal area utilization named saffoa is introduced to improve the total wirelength. the basic idea is to build and solve a group of four quadratic equations in four variables iteratively, which can handle the fixed-outline constraint of any aspect ratio. a new topological representation called ordered quadtree is then custom-made for this basic idea to facilitate its integration into sa iterations. after the fixed-outline constraint with 100% area utilization is achieved, we will solve the tradeoff between the chip area and wirelength and thus concentrate on the latter in sa process. experimental results show that the chip wirelength is decreased by about 16.8% and 8.6% on average, compared with two previous fixed-outline floorplanners on soft modules, which are both proved to be better than parquet. besides, our method is still competitive on the wirelength, even if compared with some leading-edge outline-free floorplanners. at last, local refinement is also adopted to guide the sa process and reshape soft modules to meet the constraint on their aspect ratios (ars). with its help, saffoa can still generate feasible floorplans with no deadspace under a strict ar constraint such as [0.5,2].
automated extraction of expert knowledge in analog topology selection and sizing. this paper presents a methodology for analog designers to maintain their insights into the relationship among performance specifications, topology choice, and sizing variables, despite those insights being constantly challenged by changing process nodes and new specs. the methodology is to take a data-mining perspective on a pareto optimal set of sized analog circuit topologies, then doing: extraction of a specs-to-topology decision tree; global nonlinear sensitivity analysis on topology and sizing variables; and determining analytical expressions of performance tradeoffs. these approaches are all complementary as they answer different designer questions. once the knowledge is extracted, it can be readily distributed to help other designers, without needing further synthesis. results are shown for operational amplifier design on a database containing thousands of pareto optimal designs across five objectives.
robust fpga resynthesis based on fault-tolerant boolean matching. we present fpga logic synthesis algorithms for stochastic fault rate reduction in the presence of both permanent and transient defects. we develop an algorithm for fault tolerant boolean matching (ftbm), which exploits the flexibility of the lut configuration to maximize the stochastic yield rate for a logic function. using ftbm, we propose a robust resynthesis algorithm (rose) which maximizes stochastic yield rate for an entire circuit. finally, we show that existing plb (programmable logic block) templates for area-aware boolean matching and logic resynthesis are not effective for fault tolerance, and propose a new robust template with path re-convergence. compared to the state-of-the-art academic technology mapper berkeley abc, rose using the proposed robust plb template reduces the fault rate by 25% with 1% fewer luts, and increases mtbf (mean time between failures) by 31%, while preserving the optimal logic depth.
maps: multi-algorithm parallel circuit simulation. the emergence of multi-core and many-core processors has introduced new opportunities and challenges to eda research and development. while the availability of increasing parallel computing power holds new promise to address many computing challenges in cad, the leverage of hardware parallelism can only be possible with a new generation of parallel cad applications. in this paper, we propose a novel multi-algorithm parallel circuit simulation approach (maps) and its multi-core implementation to expedite one of the most fundamental cad applications: transistor-level transient circuit simulation. maps starts multiple simulation algorithms in parallel for a given simulation task. by properly synchronizing these algorithms on-the-fly, we exploit the diversity in simulation algorithms to achieve possibly superlinear overall speedup in transient simulation. in addition, our unique multi-algorithm framework allows unique safe exploration of simulation methods that are conventionally discarded due to convergence concerns. as a coarse grained parallel simulation approach, the implementation of maps demands a minimum of parallel programming effort and allows for reuse of existing serial simulation codes.
scalable and scalably-verifiable sequential synthesis. this paper describes an efficient implementation of sequential synthesis that uses induction to detect and merge sequentially-equivalent nodes. state-encoding, scan chains, and test vectors are essentially preserved. moreover, the sequential synthesis results are sequentially verifiable using an independent inductive prover similar to that used for synthesis, with guaranteed completeness. experiments with this sequential synthesis show effectiveness. when applied to a set of 20 industrial benchmarks ranging up to 26k registers and up to 53k 6-luts, average reductions in register and area are 12.9% and 13.1% respectively while delay is reduced by 1.4%. when applied to the largest academic benchmarks, an average reduction in both registers and area is more than 30%. the associated sequential verification is also scalable and runs about 2x slower than synthesis. the implementation is available in the synthesis and verification system abc.
temperature-aware test scheduling for multiprocessor systems-on-chip. increasing power densities due to process scaling, combined with high switching activity and poor cooling environments during testing, have the potential to result in high integrated circuit (ic) temperatures. this has the potential to damage ics and cause good ics to be discarded due to temperature-induced timing faults. we first study the power impact of scan chain testing for the iscas89 benchmarks. we find that the scan-chain test power consumption is 1.6x higher for at-speed testing than normal operating power consumption. we conclude that if the testing frequency is less than half of the normal frequency, then the testing power consumption may in fact be lower. however, due to differences in the cooling environments, the peak die temperatures may still be higher. second, we present an optimal formulation for minimal-duration temperature-constrained test scheduling. our results improve on the test schedule time of the best existing algorithm by 10.8% on average for a packaged ic thermal environment. we also present an efficient heuristic that generally produces the same results as the optimal algorithm, while requiring little cpu time, even for large problem instances.
dynamic feature ordering for efficient registration. existing sequential feature-based registration algorithms involving search typically either select features randomly (eg. the ransac[8] approach) or assume a predefined, intuitive ordering for the features (e.g. based on size or resolution). this paper presents a formal framework for computing an ordering for features which maximizes search efficiency.features are ranked according to matching ambiguity measure, and an algorithm is proposed which couples the feature selection with the parameter estimation, resulting in a dynamic feature ordering. the analysis is extended to template features where the matching is non-discrete and a sample-refinement process is proposed.the framework is demonstrated effectively on the localization of a person in an image, using a kinematic model with template features. different priors are used on the model parameters and the results demonstrate nontrivial variations in the optimal feature hierarchy.
mixtures of dynamic textures. a dynamic texture is a linear dynamical system used to model a single video as a sample from a spatio-temporal stochastic process. in this work, we introduce the mixture of dynamic textures, which models a collection of videos consisting of different visual processes as samples from a set of dynamic textures. we derive the em algorithm for learning a mixture of dynamic textures, and relate the learning algorithm and the dynamic texture mixture model to previous works. finally, we demonstrate the applicability of the proposed model to problems that have traditionally been challenging for computer vision.
good continuation of general 2d visual features: dual harmonic models and computational inference. good continuation is a fundamental principle of perceptual organization that guides the grouping of parts based on how they should succeed one another within coherent wholes. despite the general language that was used by the gestalt psychologists in phrasing this principle, computational work has focused almost exclusively on the study of curve-like structures. here we offer, for the first time, a rigorous generalization of good continuation to arbitrary visual structures that can be abstracted as scalar functions over the image plane. the differential geometry of these structures dictates that their good continuation should be based both on their value and on the geometry of their levelsets, which yield a coupled system of equations solvable for a formal model. we exhibit the resulting computation on shading and intensity functions, demonstrating how it eliminates spurious measurements while preserving both regular structure and singularities. related implementations could be applied to color channels, motion magnitude, and disparity signals.
globally convergent autocalibration. existing autocalibration techniques use numerical optimizationalgorithms that are prone to the problem of localminima. to address this problem, we have developeda method where an interval branch-and-bound method isemployed for numerical minimization. thanks to the propertiesof interval analysis this method is guaranteed to convergeto the global solution with mathematical certainty andarbitrary accuracy, and the only input information it requiresfrom the user is a set of point correspondences anda search box. the cost function is based on the huang-faugerasconstraint of the fundamental matrix. a recentlyproposed interval extension based on bernstein polynomialforms has been investigated to speed up the search for thesolution. finally, some experimental results on syntheticimages are presented.
towards direct recovery of shape and motion parameters from image sequences. a novel procedure is presented to construct image-domainfilters (receptive fields) that directly recover localmotion and shape parameters. these receptive fields arederived from training on image deformations that best discriminatebetween different shape and motion parameters.beginning with the construction of 1-d receptive fieldsthat detect local surface shape and motion parameterswithin cross sections, we show how the recovered shape andmotion model parameters are sufficient to produce local estimatesof time to collision.in general, filter pairs (receptive fields) can be synthesizedto perform or detect specific image deformations. atthe heart of the method is the use of a matrix to representimage deformation correspondence between individual pixelsof two views of a surface. the image correspondencematrix can be decomposed using singular value decompositionto yield a pair of corresponding receptive fields thatdetect image changes due to the deformation of interest.
active fixation using attentional shifts, affine resampling, and multiresolution search. presents a new approach for fixing two cameras at a single location in a 3d scene. fixation requires the detection of binocular disparity for a single point of interest in the scene so that vergence control can reduce that disparity to zero. most existing systems use area-based matching, since feature-based matching is computationally prohibitive. unfortunately, the area-based approach does not perform well when confronted with steeply inclined surfaces, occlusions, repeating patterns or featureless image regions. the method presented in this paper utilizes attentional shifts and affine resampling to combat these problems. these are integrated with adaptive window-size control and coarse-to-fine correlation-based searching. the effectiveness of the approach for complex scenes is demonstrated with several stereo image pairs.
self-calibrating a stereo head: an error analysis in the neighbourhood of degenerate configurations. we show that the self-calibration of a stereo head from corresponding points in an image pair is in certain circumstances prone to considerable error. a novel error analysis reveals that the automated determination of relative orientation and focal length is adversely affected when the cameras verge inwards a similar amount, and when the principal point locations have a horizontal error. this analysis is facilitated by the adoption of closed-form solutions for self-calibration from previous work of the authors. it is also shown that estimation of the fundamental matrix associated with a stereo head image pair is improved when a domain-specific parameterization and associated computational techniques are adopted. experiments conducted with such image pairs suggest that, given cognisance of sensitive configurations and adoption of the revised method of fundamental matrix estimation, robust reconstructions are attainable. this is demonstrated on the problem of metrically reconstructing a scene from two pairs of images obtained by an uncalibrated stereo head undergoing unknown ground-plane motion.
depth discontinuities by pixel-to-pixel stereo. an algorithm to detect depth discontinuities from a stereo pair of images is presented. the algorithm matches individual pixels in corresponding scanline pairs while allowing occluded pixels to remain unmatched, then propagates the information between scanlines by means of a fast postprocessor. the algorithm handles large untextured regions, uses a measure of pixel dissimilarity that is insensitive to image sampling, and prunes bad search nodes to increase the speed of dynamic programming. the computation is relatively fast, taking about 1.5 microseconds per pixel per disparityon a workstation. approximate disparity maps and precise depth discontinuities (along both horizontal and vertical boundaries) are shown for five stereo images containing textured, untextured, fronto-parallel, and slanted objects.
split aperture imaging for high dynamic range. most imaging sensors have limited dynamic range and hence are sensitive to only a part of the illumination range present in a natural scene. the dynamic range can be improved by acquiring multiple images of the same scene under different exposure settings and then combining them. in this paper, we describe a camera design for simultaneously acquiring multiple images. the cross-section of the incoming beam from a scene point is partitioned into as many parts as the required number of images. this is done by splitting the aperture into multiple parts and directing the beam exiting from each in a different direction using an assembly of mirrors. a sensor is placed in the path of each beam and exposure of each sensor is controlled either by appropriately setting its exposure parameter, or by splitting the incoming beam unevenly. the resulting multiple exposure images are used to construct a high dynamic range image. we have implemented a video-rate camera based on this design and the results obtained are presented.
face recognition in the presence of multiple illumination sources. most existing face recognition algorithms work well for controlled images but are quite susceptible to changes in illumination and pose. this has led to the rise of analysis-by-synthesis approaches due to their inherent potential to handle these external factors. though these approaches work quite well, most of them assume that the face is illuminated by a single light source which is usually not true in realistic conditions. in this paper, we propose an algorithm to recognize faces illuminated by arbitrarily placed, multiple light sources. the algorithm does not need to know the number of light sources and works extremely well even while recognizing faces illuminated by different number of light sources. results using this algorithm are reported on multiple-illumination datasets generated from pie [10] and yale face database b [5]. we also highlight the importance of the hard non-linearity in the lambert¿s law which is often ignored, probably to linearize the estimation process.
a framework for modeling appearance change in image sequences. image "appearance" may change over time due to a variety of causes such as 1) object or camera motion; 2) generic photometric events including variations in illumination (e.g. shadows) and specular reflections; and 3) "iconic changes" which are specific to the objects being viewed and include complex occlusion events and changes in the material properties ofthe objects. we propose a general framework for representing and recovering these "appearance changes" in an image sequence as a "mixture" of different causes. the approach generalizes previous work on optical flow to provide a richer description of image events and more reliable estimates of image motion.
an algebraic approach to surface reconstruction from gradient fields. several important problems in computer vision such as shape from shading (sfs) and photometric stereo (ps) require reconstructing a surface from an estimated gradient field, which is usually non-integrable, i.e. have non-zero curl. we propose a purely algebraic approach to enforce integrability in discrete domain. we first show that enforcing integrability can be formulated as solving a single linear system ax = b over the image. in general, this system is under-determined. we show conditions under which the system can be solved and a method to get to those conditions based on graph theory. the proposed approach is non-iterative, has the important property of local errorconfinement and can be applied to several problems. results on sfs and ps demonstrate the applicability of our method.
tracking and recognizing rigid and non-rigid facial motions using local parametric models of image motion. this paper explores the use of local parametrized models of image motion for recovering and recognizing the non-rigid and articulated motion of human faces. parametric flow models (for example affine) are popular for estimating motion in rigid scenes. we observe that within local regions in space and time, such models not only accurately model non-rigid facial motions but also provide a concise description of the motion in terms of a small number of parameters. these parameters are intuitively related to the motion of facial features during facial expressions and we show how expressions such as anger, happiness, surprise, fear, disgust and sadness can be recognized from the local parametric motions in the presence of significant head motion. the motion tracking and expression recognition approach performs with high accuracy in extensive laboratory experiments involving 40 subjects as well as in television and movie sequences.
camera calibration using spheres: a semi-definite programming approach. vision algorithms utilizing camera networks with a commonfield of view are becoming increasingly feasible andimportant. calibration of such camera networks is a challengingand cumbersome task. the current approaches forcalibration using planes or a known 3d target may not befeasible as these objects may not be simultaneously visiblein all the cameras. in this paper, we present a new algorithmto calibrate cameras using occluding contours of spheres.in general, an occluding contour of a sphere projects to anellipse in the image. our algorithm uses the projection ofthe occluding contours of three spheres and solves for theintrinsic parameters and the locations of the spheres. theproblem is formulated in the dual space and the parametersare solved for optimally and efficiently using semi-definiteprogramming. the technique is flexible, accurate and easyto use. in addition, since the contour of a sphere is simultaneouslyvisible in all the cameras, our approach cangreatly simplify calibration of multiple cameras with a commonfield of view. experimental results from computer simulateddata and real world data, both for a single cameraand multiple cameras, are presented.
actions as space-time shapes. human action in video sequences can be seen as silhouettes of a moving torso and protruding limbs undergoing articulated motion. we regard human actions as three-dimensional shapes induced by the silhouettes in the space-time volume. we adopt a recent approach [9] for analyzing 2d shapes and generalize it to deal with volumetric space-time action shapes. our method utilizes properties of the solution to the poisson equation to extract space-time features such as local space-time saliency, action dynamics, shape structure and orientation. we show that these features are useful for action recognition, detection and clustering. the method is fast, does not require video alignment and is applicable in (but not limited to) many scenarios where the background is known. moreover, we demonstrate the robustness of our method to partial occlusions, non-rigid deformations, significant changes in scale and viewpoint, high irregularities in the performance of an action and low quality video.
detecting irregularities in images and in video. we address the problem of detecting irregularities in visual data, e.g., detecting suspicious behaviors in video sequences, or identifying salient patterns in images. the term "irregular" depends on the context in which the "regular" or "valid" are defined. yet, it is not realistic to expect explicit definition of all possible valid configurations for a given context. we pose the problem of determining the validity of visual data as a process of constructing a puzzle: we try to compose a new observed image region or a new video segment ("the query") using chunks of data ("pieces of puzzle") extracted from previous visual examples ("the database"). regions in the observed data which can be composed using large contiguous chunks of data from the database are considered very likely, whereas regions in the observed data which cannot be composed from the database (or can be composed, but only using small fragmented pieces) are regarded as unlikely/suspicious. the problem is posed as an inference process in a probabilistic graphical model. we show applications of this approach to identifying saliency in images and video, and for suspicious behavior recognition.
recovery and tracking of continuous 3d surfaces from stereo data using a deformable dual-mesh. we propose a novel method for continuous 3d depth recovery and tracking using calibrated stereo. the method integrates stereo correspondence, surface reconstruction and tracking by using a new single deformable dual mesh optimization, resulting in simplicity, robustness and efficiency.in order to combine stereo correspondence and structure recovery, the method introduces an external energy function defined for a 3d volume based on cross-correlation between the stereo pairs. the internal energy functional of the deformable dual mesh imposes smoothness on the surfaces and it serves as a communication tool between the two meshes. under the forces produced by the energy terms, the dual mesh deforms to recover and track the 3d surface.the newly introduced dual-mesh model, which is one of the main contributions of this paper, makes the system robust against local minima and yet it is efficient. a coarse-to-fine minimization approach makes the system even more efficient. tracking is achieved by using the recovered surface as an initial position for the next time frame. although the system can effectively utilize initial surface positions and disparity data, they are not needed for a successful operation, which makes this system applicable to a wide range of areas. we present the results of a number of experiments on stereo human face and cloud images, which proves that our new method is very effective.
a theoretical limit on the number of effective pixels that can be optically resolved on a non-planar subject. in normal imaging systems, the depth of field is inversely proportional to the lens aperture. if we assume the system is diffraction limited, then the maximum resolution (i.e. pixels per mm) is proportional to the lens aperture. thus there is a tradeoff between depth of field and resolution. this tradeoff creates an upper limit on the number of pixels that can be resolved on a non-planar subject. this paper presents the theoretical limit on the number of pixels. the derivations of the limit shows that the limit is only a function of the subject size and depth. the subject distance, focal length, and sensor size do not matter. for small subjects the limit is well below the capabilities of modern imaging systems. for example a subject 15cm wide and 10cm deep can only be imaged with 300,000 pixels even though sensors with 10 times that many pixels are readily available. the resulting limit has obvious applications in machine vision, particularly when specifying optics and imaging sensors. experimental results are provided to validate the main result of the paper.
a supervised learning framework for generic object detection in images. in recent years kernel principal component analysis (kernel pca) has gained much attention because of its ability to capture nonlinear image features, which are particularly important for encoding image structure. boosting has been established as a powerful learning algorithm that can be used for feature selection. in this paper we present a novel framework for object class detection that combines the feature reduction and feature selection abilities of kernel pca and adaboost respectively. the classifier obtained in this way is able to handle change in object appearance, illumination conditions, and surrounding clutter. a nonlinear subspace is learned for positive and negative object classes using kernel pca. features are derived by projecting example images onto the learned subspaces. base learners are modeled using bayes classifier. adaboost is then employed to discover the features that are most relevant for the object detection task at hand. the proposed method has been successfully tested on wide range of object classes (cars, airplanes, pedestrians, motorcycles, etc) using standard data sets and has shown remarkable performance. using a small training set, a classifier learned in this way was able to generalize the intra-class variation while still maintaining high detection rate. in most object categories we achieved detection rates of above 95% with minimal false alarm rates. we demonstrate the effectiveness of our approach in terms of absolute performance parameters and comparative performance against current state of the art approaches.
reconstructing complex surfaces from multiple stereo views. we present a framework for 3d surface reconstruction that can be used to model fully 3 dimensional scenes from an arbitrary number of stereo views. taken from vastly different viewpoints. this is a key step toward producing 3d world descriptions of complex scenes using stereo and is a very challenging problem: real world scenes tend to contain many 3d objects, they do not usually conform to the 2-1/2d assumption made by traditional algorithms, and one cannot take it for granted that the computed 3d points can easily be clustered into separate groups. by combining a particle based representation, robust fitting, and optimization of an image based objective function, we have been able to reconstruct surfaces without any a priori knowledge of their topology and in spite of the noisiness of the stereo data. our current implementation goes through three steps-initializing a set of particles from the input 3d data, optimizing their location, and finally grouping them into global surfaces. using several complex scenes containing multiple objects, we demonstrate its competence and ability to merge information and thus to go beyond what can be done with conventional stereo alone.
spectral gradient: a material descriptor invariant to geometry and incident illumination. the light reflected from a surface depends on the scene geometry, the incident illumination and the surface material. a novel methodology is presented which extracts reflectivity information of the various materials in the scene independent of incident light and scene geometry. a scene is captured under different narrow-band color filters and the spectral derivatives of the scene are computed. the resulting spectral derivatives form a spectral gradient at each pixel. this spectral gradient is a material descriptor which is invariant to scene geometry and incident illumination for smooth diffuse surfaces. spectral gradients can discriminate among smooth dielectrics with different reflectance properties independent of viewing conditions.
voxel carving for specular surfaces. we present an novel algorithm that reconstructs voxels of a general 3d specular surface from multiple images of a calibrated camera. a calibrated scene (i.e. points whose 3d coordinates are known) is reflected by the unknown specular surface onto the image plane of the camera. for every viewpoint, surface normals are associated to the voxels traversed by each projection ray formed by the reflection of a scene point. a decision process then discards voxels whose associated surface normals are not consistent with one another. the output of the algorithm is a collection of voxels and surface normals in 3d space, whose quality and size depend on user-set thresholds. the method has been tested on synthetic and real images. visual and quantified experimental results are presented.
epipole and fundamental matrix estimation using virtual parallax. the paper addresses the problem of computing the fundamental matrix which describes a geometric relationship between a pair of stereo images: the epipolar geometry. we propose a novel method based on virtual parallax. instead of computing directly the 3/spl times/3 fundamental matrix, we compute a homography with one epipole position, and show that this is equivalent to computing the fundamental matrix. simple equations are derived by reducing the number of parameters to estimate. as a consequence, we obtain an accurate fundamental matrix of rank two with a stable linear computation. experiments with simulated and real images validate our method and clearly show the improvement over existing methods.
seeing behind the scene: analysis of photometric properties of occluding edges by the reversed projection blurring model. this paper analyzes photometric properties of occluding edges and proves that (1) we can observe surface edges on the farther object located close to the occluding edge even if they are occluded by the nearer object, (2) the image of an occluding edge coincides with that of a surface edge on the nearer object if the brightness of the farther object is uniform around the occluding edge. first, we propose a blurring model named the reversed projection blurring model to analyze photometric properties of blurring phenomena of an occluding edge. using this model, the theoretical proof of the two properties mentioned above is given. finally, experimental results in real world environments demonstrate the validity of our blurring model as well as the observability of the photometric properties of occluding edges.
from projective to euclidean space under any practical situation, a criticism of self-calibration. for many practical applications it is important to relax the self-calibration conditions to allow for changing internal camera parameters (e.g. zooming/focusing ¿). classical techniques failed for such conditions. we present the available constraints that allow us to right a projective calibration to a euclidean one. meanwhile, we found that the estimations of the internal parameters were rather inaccurate. we discuss theoretically this difficulty and above all the resulting effect on the 3d reconstruction. in fact, we show that the uncertainty on the focal length estimation leads to a euclidean calibration up to a quasi anisotropic homothety whereas the error on the principal point can often be interpreted as a translation. hopefully, the calibration we come up with, is quite acceptable for reconstruction of models.
visual navigation using a single camera. we assess the usefulness of monocular recursive motion estimation techniques for vehicle navigation in the absence of a model for the environment. for this purpose we extend a recently proposed recursive motion estimator, the essential filter, to handle scale estimation. we examine experimentally the accuracy with which the motion and position of the vehicle may be computed on an 8000 frame indoors sequence. the issues of sampling time frequency and number of necessary features in the environment are addressed systematically.
an axis-based representation for recognition. we present a new axis-based shape representation scheme along with a matching framework to address the problem of generic shape recognition. the main idea is to define the relative spatial arrangement of local symmetry axes and their metric properties in a shape centered coordinate frame. the resulting descriptions are invariant to scale, rotation, small changes in viewpoint and articulations. symmetry points are extracted from a surface whose level curves roughly mimic the motion by curvature. by increasing the amount of smoothing on the evolving curve, only those symmetry axes that correspond to the most prominent parts of a shape are extracted. the representation does not suffer from the common instability problems of the traditional connected skeletons. it captures the perceptual qualities of shapes well. therefore finding the similarities and the differences among shapes becomes easier. the matching process gives highly successful results on a diverse database of 2d shapes.
3d photography on your desk. a simple and inexpenssive approach for extracting the three-dimentional shape of objects is presented. it is based on 'weak structured lighting'; it differs from other conventional structured lighting approaches in that it requires very little hardware besides the camera: a desk-lamp, a pencil and a checkerboard. the camera faces the object, which is illuminated by the desk-lamp. the user moves a pencil in front of the light source casting a moving shadow on the object. the 3d shape of the object is extracted from the spatial and temporal location of the observed shadow. experimental results are presented on three different scenes demonstrating that the error in reconstructing the surface is less than 1%.
multi-view surface reconstruction using polarization. a new technique for surface reconstruction is developed that uses polarization information from two views. one common problem arising from many multiple view techniques is that of finding correspondences between pixels on each image. in the new method, these correspondences are found by exploiting the spontaneous polarization of light caused by reflection to recover surface normals. these normals are then used to recover surface height. the similarity between reconstructed surface regions determines whether or not a pair of points correspond to each other. the technique is thus able to overcome the convex/concave ambiguity found in many single view techniques. because the technique relies on smooth surface regions to detect correspondences, rather than feature detection, it is applicable to objects normally inaccessible to stereo vision. also due to this fact, it is possible to remove noise without causing oversmoothing problems.
layered representation of motion video using robust maximum-likelihood estimation of mixture models and mdl encoding. representing and modeling the motion and spatial support of multiple objects and surfaces from motion video sequences is an important intermediate step towards dynamic image understanding. one such representation, called layered representation, has recently been proposed. although a number of algorithms have been developed for computing these representations, there has not been a consolidated effort into developing a precise mathematical formulation of the problem. this paper presents one such formulation based on maximum likelihood estimation (mle) of mixture models and the minimum description length (mdl) encoding principle. the three major issues in layered motion representation are: (i) how many motion models adequately describe image motion, (ii) what are the motion model parameters, and (iii) what is the spatial support layer for each motion model.
a theory of catadioptric image formation. conventional video cameras have limited fields of view which make them restrictive for certain applications in computational vision. a catadioptric sensor uses a combination of lenses and mirrors placed in a carefully arranged configuration to capture a much wider field of view. when designing a catadioptric sensor, the shape of the mirror(s) should ideally be selected to ensure that the complete catadioptric system has a single effective viewpoint. in this paper, we derive the complete class of single-lens single-mirror catadioptric sensors which have a single viewpoint and an expression for the spatial resolution of a catadioptric sensor in terms of the resolution of the camera used to construct it. we also include a preliminary analysis of thedefocus blur caused by the use of a curved mirror.
computing geodesics and minimal surfaces via graph cuts. geodesic active contours and graph cuts are two standard image segmentation techniques. we introduce a new segmentation method combining some of their benefits. our main intuition is that any cut on a graph embedded in some continuous space can be interpreted as a contour (in 2d) or a surface (in 3d). we show how to build a grid graph and set its edge weights so that the cost of cuts is arbitrarily close to the length (area) of the corresponding contours(surfaces) for any anisotropic riemannian metric. there are two interesting consequences of this technical result. first, graph cut algorithms can be used to find globally minimum geodesic contours (minimal surfaces in 3d) under arbitrary riemannian metric for a given set of boundary conditions. second, we show how to minimize metrication artifacts in existing graph-cut based methods in vision. theoretically speaking, our work provides an interesting link between several branches of mathematics - differential geometry, integral geometry, and combinatorial optimization. the main technical problem is solved using cauchy-crofton formula from integral geometry.
fast approximate energy minimization via graph cuts. many tasks in computer vision involve assigning a label (such as disparity) to every pixel. a common constraint is that the labels should vary smoothly almost everywhere while preserving sharp discontinuities that may exist, e.g., at object boundaries. these tasks are naturally stated in terms of energy minimization. in this paper, we consider a wide class of energies with various smoothness constraints. global minimization of these energy functions is np-hard even in the simplest discontinuity-preserving case. therefore, our focus is on efficient approximation algorithms. we present two algorithms based on graph cuts that efficiently find a local minimum with respect to two types of large moves, namely expansion moves and swap moves. these moves can simultaneously change the labels of arbitrarily large sets of pixels. in contrast, many standard algorithms (including simulated annealing) use small moves where only one pixel changes its label at a time. our expansion algorithm finds a labeling within a known factor of the global minimum, while our swap algorithm handles more general energy functions. both of these algorithms allow important cases of discontinuity preserving energies. we experimentally demonstrate the effectiveness of our approach for image restoration, stereo and motion. on real data with ground truth, we achieve 98 percent accuracy.
resolution-appropriate shape representation. we present a new type of "snake" in which the dimensionality of the shapes is scaled appropriately for the resolution of the images in which the shapes are embedded. we define shapes as an ordered list of control points and compute the principal components of the shapes in a prior training set. our energy function is based upon the mahalanobis distance of a given shape from the mean shape and on the mahalanobis distance of the image attributes from image attribute values extracted from the training set. we show that the derivative of this energy function with respect to the modal weights is reduced as the image resolution is reduced, and that the derivative of the energy scales with the variance associated with each mode. we exploit this property to determine the subset of the modes which are relevant at a particular level of image resolution, thereby reducing the dimensionality of the shapes. we implement a coarse-to-fine search procedure in the image and shape domains simultaneously, and demonstrate this procedure on the identification of anatomic structures in computed tomography images.
what does motion reveal about transparency? the perception of transparent objects from images is knownto be a very hard problem in vision. given a single image,it is difficult to even detect the presence of transparent objectsin the scene. in this paper, we explore what can be saidabout transparent objects by a moving observer. we showhow features that are imaged through a transparent objectbehave differently from those that are rigidly attached to thescene. we present a novel model-based approach to recoverthe shapes and the poses of transparent objects from knownmotion. the objects can be complex in that they may be composedof multiple layers with different refractive indices. wehave conducted numerous simulations to verify the practicalfeasibility of our algorithm. we have applied it to real scenesthat include transparent objects and recovered the shapes ofthe objects with high accuracy.
surface classification using conformal structures. 3d surface classification is a fundamental problem incomputer vision and computational geometry. surfaces canbe classified by different transformation groups. traditionalclassification methods mainly use topological transformationgroups and euclidean transformation groups. this paperintroduces a novel method to classify surfaces by conformaltransformation groups. conformal equivalent classis refiner than topological equivalent class and coarser thanisometric equivalent class, making it suitable for practicalclassification purposes. for general surfaces, the gradientfields of conformal maps form a vector space, which hasa natural structure invariant under conformal transformations.we present an algorithm to compute this conformalstructure, which can be represented as matrices, and use itto classify surfaces. the result is intrinsic to the geometry,invariant to triangulation and insensitive to resolution. tothe best of our knowledge, this is the first paper to classifysurfaces with arbitrary topologies by global conformal invariants.the method introduced here can also be used forsurface matching problems.
shadow puppetry. the mapping between 3d body poses and 2d shadows is fundamentally many-to-many and defeats regression methods, even with windowed context. we show how to learn a function between paths in the two systems, resolving ambiguities by integrating information over the entire length of a sequence.the basis of this function is a configurable and dynamical manifold that summarizes the target system's behavior. this manifold can be modeled from data with a hidden markov model having special topological properties that we obtain via entropy minimization. inference is then a matter of solving for the geodesic on the manifold that best explains the evidence in the cue sequence. we give a closed-form maximum a posteriori solution for geodesics through the learned density space, thereby obtaining optimal paths over the dynamical manifold.these methods give a completely general way to perform inference over time-series; in vision they support analysis, recognition, classification and synthesis of behaviors in linear time. we demonstrate with a prototype that infers 3d from monocular monochromatic sequences (e.g., back-subtractions), without using any articulatory body model. the framework readily accommodates multiple cameras and other sources of evidence such as optical flow or feature tracking.
scale-space from nonlinear filters. decomposition by extrema is put into the context of linear vision systems and scale-space. one dimensional discrete m- and n-sieves neither introduce new edges as the scale increases nor create new extrema. they share this property with diffusion based filters. furthermore m- and n-sieve algorithms are extremely fast with order complexity n. used to decompose an image, the resulting granularity is appropriate for pattern recognition.
shape recovery of 3d data obtained from a moving range sensor by using image sequences. for a large object, scanning from the air is one of the most efficient methods of obtaining 3d data. in the case of large cultural heritage objects, there are some difficulties in scanning with respect to safety and efficiency. to remedy these problems, we have been developing a novel 3d measurement system, the floating laser range sensor (flrs), in which a range sensor is suspended beneath a balloon. the obtained data, however, have some distortions due to sensor-movements during the scanning process. in this paper, we propose a method to recover 3d range data obtained by a moving laser range sensor. this method is applicable not only to our flrs, but also to a general moving range sensor. using image sequences from a video camera mounted on the flrs enables us to estimate the motion of the flrs without any physical sensors such as gyros or gps. in the first stage, the initial values of camera motion parameters are estimated by full-perspective factorization. the next stage refines camera motion parameters using the relationships between camera images and range data distortion. finally, by using the refined parameters, the distorted range data are recovered. in addition, our method is applicable with an uncalibrated video camera and range sensor system. we applied this method to an actual scanning project, and the results showed the effectiveness of our method.
efficient visual event detection using volumetric features. this paper studies the use of volumetric features as an alternative to popular local descriptor approaches for event detection in video sequences. motivated by the recent success of similar ideas in object detection on static images, we generalize the notion of 2d box features to 3d spatio-temporal volumetric features. this general framework enables us to do real-time video analysis. we construct a real-time event detector for each action of interest by learning a cascade of filters based on volumetric features thatefficiently scans video sequences in space and time. this event detector recognizes actions that are traditionally problematic for interest point methods ¿ such as smooth motions where insufficient space-time interest points are available. our experiments demonstrate that the technique accurately detects actions on real-world sequences and is robust to changes in viewpoint, scale and action speed. we also adapt our technique to the related task of human action classification and confirm that it achieves performance comparable to a current interest point based human activity recognizer on a standard database of human activities.
quasiconvex optimization for robust geometric reconstruction. geometric reconstruction problems in computer vision are often solved by minimizing a cost function that combines the reprojection errors in the 2d images. in this paper, we show that, for various geometric reconstruction problems, their reprojection error functions share a common and quasiconvex formulation. based on the quasiconvexity, we present a novel quasiconvex optimization framework in which the geometric reconstruction problems are formulated as a small number of small-scale convex programs that are ready to solve. our final reconstruction algorithm is simple and has intuitive geometric interpretation. in contrast to existing local minimization approaches, our algorithm is deterministic and guarantees a predefined accuracy of the minimization result.the quasiconvexity also provides an intuitive method to handle directional uncertainties and outliers in measurements. when there are outliers in the measurements, our method provides a mechanism to locate the global minimum of a robust error function. for large scale problems and when computational resources are constrained, we provide an efficient approximation that gives a good upper bound (but not global minimum) on the reconstruction error. we demonstrate the effectiveness of our algorithm by experiments on both synthetic and real data.
efficient learning of relational object class models. we present an efficient method for learning part-based object class models. the models include location and scale relations between parts, as well as part appearance. models are learnt from raw object and background images, represented as an unordered set of features extracted using an interest point detector. the object class is generatively modeled using a simple bayesian network with a central hidden node containing location and scale information, and nodes describing object parts. the model¿s parameters, however, are optimized to reduce a loss function which reflects training error, as in discriminative methods. specifically, the optimization is done using a boosting-like technique with complexity linear in the number of parts and the number of features per image. this efficiency allows our method to learn relational models with many parts and features, and leads to improved results when compared with other methods. extensive experimental results are described, using some common bench-mark datasets and three sets of newly collected data, showing the relative advantage of our method.
nonlinear manifold learning for visual speech recognition. a technique for representing and learning smooth nonlinear manifolds is presented and applied to several lip reading tasks. given a set of points drawn from a smooth manifold in an abstract feature space, the technique is capable of determining the structure of the surface and of finding the closest manifold point to a given query point. we use this technique to learn the "space of lips" in a visual speech recognition task. the learned manifold is used for tracking and extracting the lips, for interpolating between frames in an image sequence and for providing features for recognition. we describe a system based on hidden markov models and this learned lip manifold that significantly improves the performance of acoustic speech recognizers in degraded environments. we also present preliminary results on a purely visual lip reader.
graph partition by swendsen-wang cuts. vision tasks, such as segmentation, grouping, recognition, can be formulated as graph partition problems. the recent literature witnessed two popular graph cut algorithms: the ncut using spectral graph analysis and the minimum-cut using the maximum flow algorithm. this paper presents a third major approach by generalizing the swendsen-wang method- a well celebrated algorithm in statistical mechanics. our algorithm simulates ergodic, reversible markov chain jumps in the space of graph partitions to sample a posterior probability. at each step, the algorithm splits, merges, or re-groups a sizable subgraph, and achieves fast mixing at low temperature enabling a fast annealing procedure. experiments show it converges in 2-30seconds in a pc for image segmentation. this is 400 times faster than the single-site update gibbs sampler, and 20-40 times faster than the ddmcmc algorithm. the algorithm can optimize over the number of models and works for general forms of posterior probabilities, so it is more general than the existing graph cut approaches.
integrated spatial and frequency domain 2d motion segmentation and estimation. a video containing multiple objects in rotational and translational motion is analyzed through a combination of spatial and frequency domain representations. it is argued that the combined analysis can take advantage of the strengths of both representations. initial estimates of constant, as well as time-varying, translation and rotation velocities are obtained from frequency analysis. improved motion estimates and motion segmentation for the case of translation are achieved by integrating spatial and fourier domain information. for combined rotational and translational motions, the frequency representation is used for motion estimation, but only spatial information can be used to separate and extract the independently moving objects. the proposed algorithms are tested on synthetic and real videos.
incorporating visual knowledge representation in stereo reconstruction. in this paper, we present a two-layer generative model that incorporates generic middle-level visual knowledge for dense stereo reconstruction. the visual knowledge is represented by a dictionary of surface primitives including various categories of boundary discontinuities and junctions in parametric form. given a stereo pair, we first compute a primal sketch representation which decomposes the image into a structural part for object boundaries and high intensity contrast represented by a 2d sketch graph, and a structureless part represented by markov random field on pixels. then we label the sketch graph and compute the 3d sketch (like a wire-frame) by fitting the primitive dictionary to the sketch graph. the surfaces between the 3d sketches are filled in by computing the depth of the mrf model on the structureless part. these two levels interact closely since the mrf is used to propagate information between the primitives, and at the same time, the primitives act as boundary conditions for the mrf. the two processes maximize a bayesian posterior probability jointly. we propose anmcmc algorithm that simultaneously infers the 3d primitive types and parameters and estimates the depth of the scene. our experiments show that this representation can infer the depth map with sharp boundaries and junctions for textureless images, curve objects and free-form shapes.
self-calibration from image derivatives. this study investigates the problem of estimating the calibration parameters from image motion fields induced by a rigidly moving camera with unknown calibration parameters, where the image formation is modeled with a linear pinhole-camera model. the equations obtained show the flow to be clearly separated into a component due to the rotation and the calibration parameters. a set of parameters encoding the latter component are linearly related to the flow, and from these parameters the calibration can be determined. however, as for discrete motion, in the general case it is not possible, to decouple image measurements from two frames only into their translational and rotational component.geometrically, the ambiguity takes the form of a part of the rotational component being parallel to the translational component, and thus the scene can be reconstructed only up to a projective transformation. in general, for a full calibration at least four successiveimage frames are necessary with the 3d-rotation changing between the measurements.the geometric analysis gives rise to a direct self-calibration method that avoids computation of optical flow or point correspondences and uses only normal flow measurements. in this technique the direction of translation is estimated employing in a novel way smoothness constraints. then the calibration parameters are estimated from the rotational components of several flow fields using levenberg-marquardt parameter estimation, iterative in the calibration parameters only. the technique proposed does not require calibration objects in the scene or special camera motions and it also avoids the computation of exact correspondence. this makes it suitable for the calibration of active vision systems which have to acquire knowledge about their intrinsic parameters while they perform other tasks, or as a tool for analyzing image sequences in large video databases.
regular polygon detection. this paper describes a new robust regular polygon detector. the regular polygon transform is posed as a mixture of regular polygons in a five dimensional space. given the edge structure of an image, we derive the a posteriori probability for a mixture of regular polygons, and thus the probability density function for the appearance of a mixture of regular polygons. likely regular polygons can be isolated quickly by discretising and collapsing the search space into three dimensions. the remaining dimensions may be efficiently recovered subsequently using maximum likelihood at the locations of the most likely polygons in the subspace. this leads to an efficient algorithm. also the a posteriori formulation facilitates inclusion of additional a priori information leading to real-time application to road sign detection. the use of gradient information also reduces noise compared to existing approaches such as the generalised hough transform. results are presented for images with noise to show stability. the detector is also applied to two separate applications: real-time road sign detection for on-line driver assistance; and feature detection, recovering stable features in rectilinear environments.
paracatadioptric camera calibration using lines. paracatadioptric sensors combine a parabolic shaped mirrorand a camera inducing an orthographic projection.such a configuration provides a wide field of view whilekeeping a single effective viewpoint. previous work in centralcatadioptric sensors proved that a line projects into aconic curve and that three line images are enough to calibratethe system. however the estimation of the coniccurves where lines are mapped is hard to accomplish. ingeneral only a small arc of the conic is visible in the imageand conventional conic fitting techniques are unable to correctlyestimate the curve. the present work shows that a setof conic curves corresponds to paracatadioptric line imagesif, and only if, certain properties are verified. these propertiesare used to constraint the search space and correctlyestimate the curves. the accurate estimation of a minimumof three line images allows the complete calibration of theparacatadioptric camera. if the camera is skewless and theaspect ratio is known then the conic fitting problem is solvednaturally by an eigensystem. for the general situation theconic curves are estimated using non-linear optimization.
fundamental matrix for cameras with radial distortion. when deploying a heterogeneous camera network or when we use cheap zoom cameras like in cell-phones, it is not practical, if not impossible to off-line calibrate the radial distortion of each camera using reference objects. it is rather desirable to have an automatic procedure without strong assumptions about the scene. in this paper, we present a new algorithm for estimating the epipolar geometry of two views where the two views can be radially distorted with different distortion factors. it is the first algorithm in the literature solving the case of different distortion in the left and right view linearly and without assuming the existence of lines in the scene. points in the projective plane are lifted to a quadric in three-dimensional projective space. a radial distortion of the projective plane results to a matrix transformation in the space of lifted coordinates. the new epipolar constraint depends linearly on a 4x4 radial fundamental matrix which has 9 degrees of freedom. a complete algorithm is presented and tested on real imagery.
recognising panoramas. the problem considered in this paper is the fully asutomaticconstruction of panoramas.fundamentally, thisproblem requires recognition, as we need to know whichparts of the panorama join up.previous approaches haveused human input or restrictions on the image sequencefor the matching step.in this work we use object recognitiontechniques based on invariant local features to selectmatchings images, and a probabilistic model for verification.because of this our method is insensitive to the ordering, orientation, scale and illumination of the images.it is also insensitive to 'noise' images which are not partof the panorama at all, that is, it recognises panoramas.this suggests a useful application for photographers: thesystem takes as input the images on an entire flash card orfilm, recognises images that form part of a panorama, andstitches them with no user input whatsoever.
towards gauge invariant bundle adjustment: a solution based on gauge dependent damping. bundle ajustment is used to obtain accurate visual reconstructionsby minimizing the reprojection error. the coordinateframe ambiguity, or more generality the gauge freedoms,has been dealt with in different manners. it has oftenbeen reported that standard bundle adjustment algorithmswere not gauge invariant: two iterations within differentgauges can lead to geometrically very different results. surprisingly,most algorithms do not exploit gauge freedoms toimprove performances. we consider this issue. we analyzetheoretically the impact of the gauge on standard algorithms.we show that a sufficiently general damping matrixin levenberg-marquardt iteration can be used to implicitlyreproduce a gauge transformation. we show that if thedamping matrix is chosen such that the decrease in the reprojectionerror is maximized, then the iteration is gauge invariant.experimental results on simulated and real data showthat our gauge invariant bundle adjustment algorithm outperformsexisting ones in terms of stability.
optimum fiducials under weak perspective projection. we investigate how a given fixed number of points should be located in space so that the pose of a camera viewing them from unknown locations can be estimated with the greatest accuracy. we show that optimum solutions are obtained when the points form concentric complete regular polyhedra. for the case of optimal configurations we provide a worst-case error analysis and use it to analyze the effects of weak perspective approximation to true perspective viewing. comprehensive computer simulations validate the theoretical results.
multiple-view structure and motion from line correspondences. we address the problem of camera motion and structure reconstruction from line correspondences across multiple views, from initialization to final bundle adjustment. one of the main difficulties when dealing with line features is their algebraic representation. first, we consider the triangulation problem. based on pl&uuml;cker coordinates to represent the lines, we propose a maximum likelihood algorithm, relying on linearising the pl&uuml;cker constraint, and on a pl&uuml;cker correction procedure to compute the closest pl&uuml;cker coordinates to a given 6-vector. second, we consider the bundle adjustment problem. previous overparameterizations of 3d lines induce gauge freedoms and/or internal consistency constraints. we propose the orthonormal representation, which allows handy non-linear optimization of 3d lines using the minimum 4 parameters, within an unconstrained non-linear optimizer. we compare our algorithms to existing ones on simulated and real data.
towards ultimate motion estimation: combining highest accuracy with real-time performance. although variational methods are among the most accurate techniques for estimating the optical flow, they have not yet entered the field of real-time vision. main reason is the great popularity of standard numerical schemes that are easy to implement, however, at the expense of being too slow for real-time performance. in our paper we address this problem in two ways: (i) we present an improved version of the highly accurate technique of brox et al. [9]. thereby we show that a separate robustification of the constancy assumptions is very useful, in particular if the 1-norm is used as penalizer. as a result, a method is obtained that yields the lowest angular errors in the literature. (ii) we develop an efficient numerical scheme for the proposed approach that allows real-time performance for sequences of size 160 × 120. to this end, we combine two hierarchical strategies: a coarse-to-fine warping strategy as implementation of a fixed point iteration for a non-convex optimisation problem and a nonlinear full multigrid method ¿ a so called full approximation scheme (fas) ¿ for solving the highly nonlinear equation systems at each warping level. in the experimental section the advantage of the proposed approach becomes obvious: outperforming standard numerical schemes by two orders of magnitude frame rates of six high quality flow fields per second are obtained on a 3.06 ghz pentium4 pc.
model selection and surface merging in reconstruction algorithms. the problem of model selection is relevant to many areas of computer vision. model selection criteria have been used in the vision literature and many more have been proposed in statistics, but the relative strengths of these criteria have not been analyzed in vision. more importantly, suitable extensions to these criteria must be made to solve problems unique to computer vision. using the problem of surface reconstruction as our context, we analyze existing criteria using simulations and sensor data, introduce new criteria from statistics, develop novel criteria capable of handling unknown error distributions and outliers, and extendmodel selection criteria to apply to the surface merging problem. the new surface merging rules improve upon previous results, and work well even at small step heights (h = 3¿) and crease discontinuities. our results show that a bayesian criteria and its bootstrapped variant perform the best, although for time-sensitive applications, a variant of the akaike criterion may be a better choice. unfortunately, none of the criteria work reliably for small region sizes, implying that model selection and surface merging should be avoided unless the region size is sufficiently large.
separability of pose and expression in facial tracing and animation. we explore the application of facial tracking to automated re-animation. to this end, it is necessary to recover both head-pose and facial expression from the facial movement of a performer. however, both effects are coupled. this is a serious problem, which previous studies haven't fully considered. the solution to this interaction problem proposed here is to solve explicitly, at each timestep, for pose and expression variables. in principle this is a nonlinear inverse problem. however, appropriate parameterisation of pose in terms of affine transformations with parallax, and of expression in terms of key-frames, reduces the problem to a bilinear one. this can then be solved directly by singular value decomposition. thus actor-driven animation has b een implemented in real-time, at video field-rate, using two indy desktop workstations.
color recognition in outdoor images. the color associated with an object in machine vision images is not constant; under varying illuminating and viewing conditions (such as in outdoor images), the perceived color of an object can vary significantly, thus making color-based recognition difficult. existing methods in color-based recognition have been applied mostly to indoor and/or constrained imagery, but not to realistic outdoor data.this work analyzes the variation of object color in outdoor images with respect to existing models of day-light illumination and surface reflectance. two approaches for color recognition are then proposed: the first develops context-based models of daylight illumination and hybrid surface reflectance, and predicts the color of objects based on scene context. the secondmethod shows that object color can be nonparametrically "learned" through classification methods such as neural networks and multivariate decision trees. the methods have been successfully tested in domains such as road/highway scenes, off-road navigation and military target detection.
region tracking through image sequences. the paper describes an approach to the tracking of complex shapes through image sequences, that combines deformable region models and deformable contours. a deformable region model is presented: its optimisation is based on texture correlation and is constrained by the use of a motion model, such as rigid, affine or homographic. the use of texture information (versus edge information) noticeably improves the tracking performances of deformable models in the presence of texture. then the region contour is refined using an edge based deformable model in order to better deal with specularities, non planar objects and occlusions. the method is illustrated and validated by experimental results on real images.
electronically directed "focal" stereo. a key to developing computationally efficient stereo vision is the incorporation of intelligent control. stereo is most effective when it is able to "focus" its analysis on regions and details of a scene that are important to the task at hand, while avoiding less important regions and unnecessary detail. the paper describes two methods for electronically "focusing" stereo measurement through simple image pre-processing. the first allows measurement sensitivity to be adjusted. the second allows the shape of the 3d region in which measurements are gathered to be matched to the shape of surfaces in the scene.
lambertian reflectance and linear subspaces. we prove that the set of all reflectance functions (the mapping from surface normals to intensities) produced by lambertian objects under distant, isotropic lighting lies close to a 9d linear subspace. this implies that, in general, the set of images of a convex lambertian object obtained under a wide variety of lighting conditions can be approximated accurately by a low-dimensional linear subspace, explaining prior empirical results. we also provide a simple analytic characterization of this linear space. we obtain these results by representing lighting using spherical harmonics and describing the effects of lambertian materials as the analog of a convolution. these results allow us to construct algorithms for object recognition based on linear methods as well as algorithms that use convex optimization to enforce non-negative lighting functions. finally, we show a simple way to enforce non-negative lighting when the images of an object lie near a 4d linear space.
automatic tracking of human motion in indoor scenes across multiple synchronized video streams. this pap er presents a comprehensive framework for tracking moving humans in an indoor environment from sequences of synchronized monocular grayscale images captured from multiple fixed cameras. the proposed framework consists of three main modules: single view tracking (svt), multiple view transition tracking (mvtt), and automatic camera switching (acs). bayesian classification schemes based on motion analysis of human features are used to track (spatially and temporally) a subject image of interest between consecutive frames. the automatic camera switching module predicts the position of the subject along a spatial-temporal domain, and then selects the camera which provides the best view and requires the least switching to continue tracking. limited degrees of occlusion are tolerated within the system. tracking is based up on the images of upper human bodies captured from various viewing angles, and non-human moving objects are excluded using principal component analysis (pca). experimental results are presented to evaluate the performance of the tracking system.
recognition using region correspondences. recognition systems attempt to recover information about the identity of the observed objects and their location in the environment. a fundamental problem in recognition is the following. given a correspondence between some portions of an object model and some portions of an image, determine whether the image contains an instance of the object, and, in case it does, determine the transformation that relates the model to the image. the current approaches to this problem are divided into methods that use ``global'''' properties of the object (e.g., centroid and moments of inertia) and methods that use ``local'''' properties of the object (e.g., corners and line segments). global properties are sensitive to occlusion and, specifically, to self occlusion. local properties are difficult to locate reliably, and their matching involves intensive computation. a novel method for recognition that uses region information is presented. in our approach the model is divided into volumes, and the image is divided into regions. given a match between subsets of volumes and regions (without any explicit correspondence between different pieces of the regions) the alignment transformation is computed. the method applies to planar objects under similarity, affine, and projective transformations and to projections of 3-d objects undergoing affine and projective transformations. the new approach combines many of the advantages of the previous two approaches, while avoiding some of their pitfalls. like the global methods, our approach makes use of region information that reflects the true shape of the object. but like local methods, our approach can handle occlusion.
recognition of human body motion using phase space constraints. a new method for representing and recognizing human body movements is presented. the basic idea is to identify sets of constraints that are diagnostic of a movement: expressed using body-centered coordinates such as joint angles and in force only during a particular movement. assuming the availability of cartesian tracking data, we develop techniques for a representation of movements defined by space curves in subspaces of a "phase space." the phase space has axes of joint angles and torso location and attitude, and the axes of the subspaces are subsets of the axes of the phase space. using this representation we develop a system for learning new movements from ground truth data by searching for constraints. we then use the learned representation for recognizing movements in unsegmented data. we train and test the system on nine fundamental steps from classical ballet performed by two dancers; the system accurately recognizes the movements in the unsegmented stream of motion.
projective alignment with regions. we have recently proposed an approach to recognition that uses regions to determine the pose of objects while allowing for partial occlusion of the regions. regions introduce an attractive alternative to existing global and local approaches, since, unlike global features, they can handle occlusion and segmentation errors, and unlike local features they are not as sensitive to sensor errors, and they are easier to match. the region-based approach also uses image information directly, without the construction of intermediate representations, such as algebraic descriptions, which may be difficult to reliably compute. in this paper we further analyze properties of the method for planar objects undergoing projective transformations. in particular, we prove that three visible regions are sufficient to determine the transformation uniquely, and that for a large class of objects two regions are insufficient for this purpose. however, we show that when several regions are available the pose of the object can generally be recovered even when some or all regions are significantly occluded. our analysis is based on investigating the flow patterns of points under projective transformations in the presence of fixed points.
a caratheodory-fejer approach to robust multiframe tracking. a requirement common to most dynamic vision applicationsis the ability to track objects in a sequence of frames. thisproblem has been extensively studied in the past few years,leading to several techniques, such as unscented particlefilter based trackers, that exploit a combination of the (assumed)target dynamics, empirically learned noise distributionsand past position observations. while successful inmany scenarios, these trackers remain fragile to occlusionand model uncertainty in the target dynamics. as we showin this paper, these difficulties can be addressed by modelingthe dynamics of the target as an unknown operator thatsatisfies certain interpolation conditions. results from interpolationtheory can then be used to find this operator bysolving a convex optimization problem. as illustrated withseveral examples, combining this operator with kalman andupf techniques leads to both robustness improvement andcomputational complexity reduction.
when is it possible to identify 3d objects from single images using class constraints? one approach to recognizing objects seen from arbitrary viewpoint is by extracting invariant properties of the objects from single images. such properties are found in images of 3d objects only when the objects are constrained to belong to certain classes (e.g., bi;aterally symmetric objects). existing studies that follow this approach propose how to compute invariant representations for a handful of classes of objects. a fundmental question regarding the invariance approach is whether it can be applied to a wide range of classes. to answer this question it is essential to study the set of classes for which invariance exists. this paper introduces a new method for determining the existence of invariance for classes of objects together with the set of images from which these invariance can be computed. we developed algebraic tests that, given a class of objects undergoing affine projection, determine whether the objects in the class can be identified from single images. in addition, these tests allow us to determine the set of views of the objects which are degenerate. we apply these tests to several classes of objects and determine which of them is identifiable and which of their views are degenerate.
good continuations in digital image level lines. we propose a probabilistic algorithm able to detect the curves that are unexpectedy smooth in a set of digital curves. the only parameter is a false alarme rate, influencing the detection only by its logarithm. we experiment the good continuation criterion on image level lines. one of the conclusion is that, accordingly to gestalt theory, onecan detect egdes in a way that is widely independent of contrast. we also use the same kind of method to detect corners and junctions.
head-eye calibration. we deal with the calibration problem of an active head-eye system, which consists of a pair of cameras mounted on a head with 13 degrees of freedom. the aim of the calibration is to establish relative positions of different 3d systems: between camera and neck, eye and neck, etc., so that we can keep track of the camera position in a fixed (calibration) reference system as a function of the visual parameters of the head-eye system. we formulate the problem and propose both closed-form and nonlinear optimization approaches to solve it. experiments were carried out and comparison of results with other algorithms were made on both simulated and real data.
visual homing: surfing on the epipoles. we introduce a novel method for visual homing. using this method a robot can be sent to desired positions and orientations in 3-d space specified by single images taken from these positions. our method is based on recovering the epipolar geometry relating the current image taken by the robot and the target image. using the epipolar geometry, most of the parameters which specify the differences in position and orientation of the camera between the two images are recovered. however, since not all of the parameters can be recovered from two images, we have developed specific methods to bypass these missing parameters and resolve the ambiguities that exist. we present two homing algorithms for two standard projection models, weak and full perspective. our method determines the path of the robot on-line, the starting position of the robot is relatively not constrained, and a 3-d model of the environment is not required. the method is almost entirely memoryless, in the sense that at every step the path to the target position is determined independently of the previous path taken by the robot. because of this property the robot may be able, while moving toward the target, to perform auxiliary tasks or to avoid obstacles, without this impairing its ability to eventually reach the target position. we have performed simulations and real experiments which demonstrate the robustness of the method and that the algorithms always converge to the target pose.
a cylindrical surface model to rectify the bound document image. this article proposes a novel approach on how torectify the photo image of the bound document. thesurface of the document is modeled by a cylindricalsurface. by the geometry of camera image formation, theequations using the cue of directrixes to map the points onthe surface in the 3-d scene to the points on the imageplane are achieved. baselines of the horizontal text lineare extracted as projections of directrixes to estimate thebending extent of the surface, and then the images arerectified. the proposed method needs no auxiliary device.experimental results are presented to demonstrate thefeasibility and the application of the method.
3d object reconstruction from a single 2d line drawing without hidden lines. the human vision system can interpret a single 2d line drawing as a 3d object without much difficulty even if the hidden lines of the object are invisible. several reconstruction approaches have tried to emulate this ability, but they cannot recover the complete object if the hidden lines of the object are not shown. this paper proposes a novel approach for reconstructing complete 3d objects from line drawings without hidden lines. first, we develop some constraints and properties for the inference of the topology of the invisible edges and vertices of an object. then we present a reconstruction method based on perceptual symmetry and planarity of the object. we give a number of examples to demonstrate the ability of our approach.
iterative multi-step explicit camera calibration. perspective camera calibration has been in the last decades a research subject for a large group of researchers and as a result several camera calibration methodologies can be foundin the literature. however only a small number of those methods base their approaches on the use of monoplane calibration points to realize an explicit 3d camera calibration. to avoid the singularity obtained with the calibration equations when monoplane calibration points are used, this method computes the calibration parameters in a multi-step procedure and requires a first-guess solution for the intrinsic parameters. these parameters are updated and their accuracy increased through an iterative procedure. a stability analysis as a function of the pose of the camera is presented. camera pose view strategies for accurate camera orientation computation can be extracted from the pose view stability analysis.
real-time motion analysis with linear-programming. a method to compute motion models in real time from point-to-line correspondences using linear programming is presented. point-to-line correspondences are the most reliable motion measurements given the aperture effect, and it is shown how they can approximate other motion measurements as well.using an l1 error measure for image alignment based on point-to-line correspondences and minimizing this measure using linear programming, achieves results which are more robust than the commonly used l2 metric. while estimators based on l1 are not theoretically robust, experiments show that the proposed method is robust enough to allow accurate motion recovery in hundreds of consecutive frames. the entire computation is performed in real-time on a pc with no special hardware.
a model-based approach for automated feature extraction in fundus images. a new approach to automatically extract the main features in color fundus images are proposed in this paper. optic disk is localized by the principal component analysis (pca) and its shape is detected by a modified active shape model (asm). exudates are extracted by the combined region growing and edge detection. a fundus coordinate system is further set up based on the fovea localization to provide a better description of the features in fundus images. the success rates achieved are 99%, 94%, and 100% for disk localization, disk boundary detection, and fovea localization respectively. the sensitivity and specificity for exudate detection are 100% and 71%. the success of the proposed algorithms can be attributed to the utilization of the model-based methods.
active visual navigation using non-metric structure. demonstrates a method of using nonmetric visual information derived from an uncalibrated active vision system to navigate an autonomous vehicle through free-space regions detected in a cluttered environment. the structure of 3-space is recovered modulo an affine transformation using an uncalibrated active stereo head carried by the vehicle. the plane at infinity, necessary for recovering affine structure from projective structure, is found in a novel manner by making controlled rotations of the head. the structure is composed of 3d points obtained by detecting and matching image corners through the stereo image sequence. considerable care has been taken to ensure that the processing is reliable, robust and automatic. driveable regions are determined from the projection of the affine structure onto a plane parallel to the ground determined using projective constructs. two methods of negotiating the regions are explored. the first introduces metric information to allow control of a euclidean vehicle. the second uses visual servoing of the active head to navigate in the affinely described free-space regions.
large deformation diffeomorphic metric mapping of fiber orientations. this paper proposes a method to match diffusion tensor magnetic resonance images (dt-mri) through the large deformation diffeomorphic metric mapping of vector fields, focusing on the fiber orientations, considered as unit vector fields on the image volume. we study a suitable action of diffeomorphisms on such vector fields, and provide an extension of the large deformation diffeomorphic metric mapping framework to this type of dataset, resulting in optimizing for geodesics on the space of diffeomorphisms connecting two images. two different distance function of vector fields are considered. existence of the minimizers under smoothness assumptions on the compared vector fields is proved, and coarse to fine hierarchical strategies are detailed, to reduce both ambiguities and computation load. this is illustrated by numerical experiments on dt-mri heart and brain images.
learning geometric hashing functions for model-based object recognition. a major problem associated with geometric hashing and methods which have emerged from it is the non-uniform distribution of invariants over the hash space. this problem can affect the performance of the method significantly. finding a "good" geometric hash function which redistributes the invariants uniformly over the hash space is not easy. in this paper, a new approach is proposed for alleviating the above problem. it is based on the use of an "elastic hash table" which is implemented as a self-organizing feature map neural network (sofm-nn). in contrast to existing approaches which try to redistribute the invariants over the hash bins, we proceed oppositely, spreading the hash bins over the invariants. during training, the sofm-nn resembles an elastic net which deforms over the hash space. the objective of the deformation process is to spread more hash bins in hash space areas which are heavily occupied and less hash bins in lower density areas. the advantage of the proposed approach is that it is a process that adapts to the invariants through learning. hence, it makes absolutely no assumptions about the statistical characteristics of the invariants and the geometric hash function is actually computed through learning. furthermore, the well known "topology preserving" property of the sofm-nn guarantees that the computed geometric hash function should be well behaved. finally, the proposed approach is inherently parallelizable.
class-specific material categorisation. although a considerable amount of work has been published on material classification, relatively little of it studies situations with considerable variation within each class. many experiments use the exact same sample, or different patches from the same image, for training and test sets. thus, such studies are vulnerable to effectively recognising one particular sample of a material as opposed to the material category. in contrast, this paper places firm emphasis on the capability to generalise to previously unseen instances of materials. we adopt an appearance-based strategy, and conduct experiments on a new database which contains several samples of each of eleven material categories, imaged under a variety of pose, illumination and scale conditions. together, these sources of intra-class variation provide a stern challenge indeed for recognition. somewhat surprisingly, the difference in performance between various state-of-the-art texture descriptors proves rather small in this task. on the other hand, we clearly demonstrate that very significant gains can be achieved via different svm-based classification techniques. selecting appropriate kernel parameters proves crucial. this motivates a novel recognition scheme based on a decision tree. each node contains an svm to split one class from all others with a kernel parameter optimal for that particular node. hence, each decision is made using a different, optimal, class-specific metric. experiments show the superiority of this approach over several state-of-the-art classifiers.
using algebraic functions of views for indexing-based object recognition. current indexing-based approaches build the hash table using either a large number of reference views or 3d models. in this paper, we propose building the hash table using algebraic functions of views. during preprocessing, we consider groups of model points and we represent all the views (i.e., images) that they can produce in a hash table. these views are computed using algebraic functions of a small number of reference views which contain the group. fundamental to this procedure is a methodology based on singular value decomposition and interval arithmetic for estimating the ranges of values that the parameters of algebraic functions can assume. during recognition, scene groups are used to retrieve from the hash table the model groups that might have produced them. using algebraic functions of views for indexing-based recognition offers a number of advantages. first of all, the hash table can be built easier, without requiring 3d models or a large number of reference views. second, recognition does not rely on the similarities between new and reference views. third, verification becomes simpler. finally, the approach is more general and extendible.
recovering object surfaces from viewed changes in surface texture patterns. explores the reconstruction of object surfaces from viewed changes in surface texture patterns. our approach differs from those in the past in that instead of simply producing local estimates of the surface orientation, our algorithm recovers complete surfaces. past approaches only found the surface orientation locally and, therefore, did not take advantage of the surface integrability constraint. our algorithm does not assume that the surface texture pattern is isotropic, and it does not assume that the viewed surface is at some point fronto-parallel. furthermore, our algorithm has mechanisms for handling texture boundaries and, consequently, does not produce erratic results in the regions abutting these boundaries. results on real images are presented demonstrating the potential of our approach.
densities and maximum likelihood estimation of matching constraints. in this paper we present a theory for obtaining densities that are important for computer vision. as a result of the theory we compute the exact and novel density of the slope of a line fitted to image points. this density makes it possible to obtain confidence intervals for the slope or to make hypothesis testing about if two intersecting lines form a corner or not. the theory also lets us derive a novel technique for maximum likelihood estimation, that can be used for computing the fundamental matrix, conics, or any other constraint that can be expressed by polynomials of degree 2. we present exact and novel densities for the fundamental matrix and conic constraints, that are needed for the estimation. experiments show how the results can be used in practice to compute maximum likelihood estimates of the fundamental matrix. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
stereo in the presence of specular reflection. the problem of accurate depth estimation using stereo in the presence of specular reflection is addressed. specular reflection, a fundamental and ubiquitous reflection mechanism, is viewpoint dependent and can cause large intensity differences at corresponding points, resulting in significant depth errors. we analyze the physics of specular reflection and the geometry of stereopsis which led us to a relationship between stereo vergence, surface roughness, and the likelihood of a correct match. given a lower bound on surface roughness, an optimal binocular stereo configuration can be determined which maximizes precision in depth estimation despite specular reflection. however, surface roughness is difficult to estimate in unstructured environments. therefore, trinocular configurations, independent of surface roughness, are determined such that at each scene point visible to all sensors, at least one stereo pair can compute produce depth. we have developed a simple algorithm to reconstruct depth from the multiple stereo pairs.
multi-scale gesture recognition from time-varying contours. a novel method is introduced to recognize and estimate the scale of time-varying human gestures. it exploits the changes in contours along spatio-temporal directions. each contour is first parameterized as a 2d function of radius vs. cumulative contour length, and a 3d surface is composed from a sequence of such functions. in a two-phase recognition process, dynamic timewarping is employed to rule out significantly different gesture models, and then mutual information (mi) is applied for matching the remaining models. the system has been tested on 8 gestures performed by 5 subjects with varied time scales. the two-phase process is compared against exhaustively testing three similarity measures based upon mi, correlation, and nonparametric kernel density estimation. experimental results demonstrate that the exhaustive application of mi is the most robust with a recognition rate of 90.6%, however, the two-phase approach is much more computationally efficient with a comparable recognition rate of 90.0%.
finding correspondences of patches by means of affine transformations. in this paper we present a novel method for finding the optimal affine transformation for matching of images. the method requires no feature points, does not rely on normalization of images and can be tuned to highlight interesting parts in the images. furthermore, the method does not need any derivatives for obtaining the affine transformation and it has a computational cost proportional to n2 logn for n×n images.the problem of finding the optimal affine transformation is solved by an iterative algorithm. in each step a global optimization is performed by the use of fft. this global characteristic helps the algorithm from getting trapped in a local optimum. novel theoretical results are presented that show under what restrictions the algorithm can be expected to work properly.its intended primary use is for reconstruction problems in computer vision. these rely heavily on the establishment of point correspondences in the images. since the method makes no assumptions on the images it can be used when feature points are difficult to detect. experiments on real images are included and it is shown that the algorithm is robust and performs well even in difficult situations, with occlusions. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
shape parameter optimization for adaboosted active shape model. active shape model (asm) has been shown to be a powerful tool to aid the interpretation of images, especially in face alignment. asm local appearance model parameter estimation is based on the assumption that residuals between model fit and data have a gaussian distribution. moreover, to generate an allowable face shape, asm truncates coefficients of shape principal components into the bounds determined by eigenvalues. in this paper, an algorithm of modeling local appearances, called adaboosted asm, and a shape parameter optimization method are proposed. in the algorithm of modeling the local appearances, we describe our novel modeling method by using adaboosted histogram classifiers, in which the assumption of the gaussian distribution is not necessary. in the shape parameter optimization, we describe that there is an inadequacy on controlling shape parameters in asm, and our novel method on how to solve it. experimental results demonstrate that the adaboosted histogram classifiers improve robustness of landmark displacement greatly, and the shape parameter optimization solves the inadequacy problem of asm on shape constraint effectively.
3d shape reconstruction using volume intersection techniques. volume intersection algorithms are used to reconstruct incomplete objects from their silhouettes. an imagined light source is moved about the data and the cumulative amount of "light" seen at each point in space is interpreted as indicating the likelihood that the point is inside the object. the object data need not be uniformly distributed nor exclusively surface data. explicit distinction between noise, surface and interior data is avoided. the novel concept of a localised viewing region is introduced to overcome the inherent inability of volume intersection algorithms to reconstruct concave surfaces. algorithms for 2d pixel and3d voxel data are described and applied to 3d ultra-sound data.
a chromaticity space for specularity-, illumination color- and illumination pose-invariant 3-d object recognition. most of the recent color recognition/indexing approaches concentr ate on establishing invariance to illumination color to improve the utility of color recognition. however, other effects caused by illumination pose and specularity on three-dimensional object surfaces have not received notable attention. we present a chromaticity recognition method that discounts the effects of illumination pose, illumination color and specularity. it utilizes a chromaticity space based on log-ratio of sensor responses for illumination pose and color invariance. a model-based specularity detection/rejection algorithm can be used to improve the chromaticity recognition and illumination estimation for objects including specular reflections.
geodesic active contours. a novel scheme for the detection of object boundaries is presented. the technique is based on active contours deforming according to intrinsic geometric measures of the image. the evolving contours naturally split and merge, allowing the simultaneous detection of several objects and both interior and exterior boundaries. the proposed approach is based on the relation between active contours and the computation of geodesics or minimal distance curves. the minimal distance curve lays in a riemannian space whose metric as defined by the image content. this geodesic approach for object segmentation allows to connect classical "snakes" based on energy minimization and geometric active contours based on the theory of curve evolution. previous models of geometric active contours are improved as showed by a number of examples. formal results concerning existence, uniqueness, stability, and correctness of the evolution are presented as well.
fast object recognition in noisy images using simulated annealing. a fast simulated annealing algorithm is developed for automatic object recognition. the object recognition problem is addressed as the problem of best describing a match between a hypothesized object and an image. the normalized correlation coefficient is used as a measure of the match. templates are generated on-line during the search by transforming model images. simulated annealing reduces the search time by orders of magnitude with respect to an exhaustive search. the algorithm is applied to the problem of how landmarks, e.g., traffic signs, can be recognized by a navigating robot. we illustrate the performance of our algorithm with real-world images of complicated scenes with traffic signs. false positive matches occur only for templates with very small information content. to avoid false positive matches, we propose a method to select model images for robust object recognition by measuring the information content of the model images. the algorithm works well in noisy images for model images with high information content.
information-conserving object recognition. following the theory of statistical estimation, the problem of recognizing objects imaged in complex real-world scenes is examined from a parametric perspective. a scalar measure of an objects's complexity, which is invariant under affine transformation and changes in image noise level, is extracted from the object's fisher information. the volume of fisher information is shown to provide an overall statistical measure of the object's recognizability in a particular image, while the complexity provides an intrinsically physical measure that characterizes the object in any image. an information-conserving method is then developed for recognizing an object imaged in a complex scene. here the term information-conserving means that the method uses al the measured data pertinent to the object's recognizability, attains the theoretical lower bound on estimation error for any unbiased estimate, and therefore is statistically optimal. this method is then successfully applied to finding objects imaged in thousands of complex real-world scenes.
3d point distribution models of the cortical sulci. in this paper we present the first steps in the development of a statistical shape model, specifically a point distribution model (pdm), of the cortical surface of the brain. this will ultimately be used to locate, label, and describe the cortex, for visualisation, diagnosis, andquantification. in order to produce the model it was necessary to find and label the sulcal fissures on a series of mr images. due to the complexity of the surface, an automated method was developed to facilitate development of a full surface model. automating the marking process introduced the problem of identifying correspondences between examples, the knowledge of which is essential to the development of a pdm. various methods were investigated to solve this problem including simple point matching and more complex curve matching. each is outlined and discussed. the models obtained so far provide interesting insights into the shape and cortical pattern variations over a group of normal subjects.
face recognition from one example view. to create a pose-invariant face recognizer, one strategy is the view-based approach, which uses a set of real example views at different poses. but what if we only have one real view available, such as a scanned passport photo-can we still recognize faces under different poses? given one real view at a known pose, it is still possible to use the view-based approach by exploiting prior knowledge of faces to generate virtual views, or views of the face as seen from different poses. to represent prior knowledge, we use 2d example views of prototype faces under different rotations. we develop example-based techniques for applying the rotation seen in the prototypes to essentially "rotate" the single real view which is available. next, the combined set of one real and multiple virtual views is used as example views for a view-based, pose-invariant face recognizer. oar experiments suggest that among the techniques for expressing prior knowledge of faces, 2d example-based approaches should be considered alongside the more standard 3d modeling techniques.
on multi-feature integration for deformable boundary finding. precise segmentation of underlying objects in an image is very important especially for biomedical image analysis. we present an integrated approach for boundary finding using region and curvature information along with the gradient. unlike the previous methods, where smoothing is enforced by penalizing curvature, here the grey level curvature is used as an extra source of information. however, information fusion may not be useful unless used properly. to address that, we present results that highlight the pros and cons of using the various sources of information and indicate when one should get precedence over the others.
robust path-based spectral clustering with application to image segmentation. spectral clustering and path-based clustering are two recently developed clustering approaches that have delivered impressive results in a number of challenging clustering tasks. however, they are not robust enough against noise and outliers in the data. in this paper, based on m-estimation from robust statistics, we develop a robust path-based spectral clustering method by defining a robust path-based similarity measure for spectral clustering. our method is significantly more robust than spectral clustering and path-based clustering. we have performed experiments based on both synthetic and real-world data, comparing our method with some other methods. in particular, color images from the berkeley segmentation dataset and benchmark are used in the image segmentation experiments. experimental results show that our method consistently outperforms other methods due to its higher robustness.
unsupervised image classification with a hierarchical em algorithm. this work takes place in the context of hierarchical stochastic models for the resolution of discrete inverse problems from low level vision. some of these models lie on the nodes of a quad-tree which leads to non-iterative inference procedures. nevertheless, if they circumvent the algorithmic drawbacks of grid-based models (computational load and/or great dependence on the initialization), they admit modeling shortcomings (cumbersome and somehow artificial). we investigate a new hierarchical stochastic model which takes benefit from both the spatial and the hierarchical prior modelings. the independence graph is based on a tree which has been pollarded with the nodes at the coarsest resolution exhibiting a grid-based interaction structure. for this class of models, we address the critical problem of parameter estimation. to this end, we derive an em algorithm on the hybrid structure which mixes an exact em algorithm on each subtrees and a low cost gibbsian em algorithm on the coarse spatial grid. experiments on a synthetic image and on multi-spectral satellite images are reported.
image statistics based on diffeomorphic matching. we propose a new approach to deal with the first and second order statistics of a set of images. these statistics take into account the images characteristic deformations and their variations in intensity. the central algorithm is based on non-supervised diffeomorphic image matching (without landmarks or human intervention). as they convey the notion of the mean shape and colors of an object and the one of its common variations, such statistics of sets of images may be relevant in the context of object recognition, both in the segmentation of any of its representations and in the classification of them. the proposed approach has been tested on a small database of face images to compute a mean face and second order statistics. the results are very encouraging since, wheras the algorithm does not need any human intervention and is not specific to face image databases, the mean image looks like a real face and the characteristic modes of variation (deformation and intensity changes) are sensible.
designing spatially coherent minimizing flows for variational problems based on active contours. this paper tackles an important aspect of the variational problems involving active contours, which has been largely overlooked so far: the optimization by gradient flows. classically, the definition of a gradient depends directly on the choice of an inner product structure. this consideration is largely absent from the active contours literature. most authors, overtly or covertly, assume that the space of admissible deformations is ruled by the canonical l2 inner product. the classical gradient flows reported in the literature are relative to this particular choice. in this paper, we investigate the relevance of using other inner products, yielding other gradient descents, and some other minimizing flows not deriving from any inner product. in particular, we show how to induce different degrees of spatial coherence into the minimizing flow, in order to decrease the probability of getting trapped into irrelevant local minima. we show with some numerical experiments that the sensitivity of the active contours method to initial conditions, which seriously limits its applicability and its efficiency, is alleviated by our application-specific spatially coherent minimizing flows.
lighting normalization with generic intrinsic illumination subspace for face recognition. in this paper, we introduce the concept of intrinsic illumination subspace which is based on the intrinsic images. this intrinsic illumination subspace enables an analytic generation of the illumination images under varying lighting conditions. when objects of the same class are concerned, our method allows a class-based generic intrinsic illumination subspace to be constructed in advance. we propose a lighting normalization method based on the generic intrinsic illumination subspace, which is used as a bootstrap subspace for novel images. face recognition experiments are performed to demonstrate the effectiveness of our method.
using prior shape and intensity profile in medical image segmentation. in this note we present a coupled optimization model forboundary determination. one part of the model incorporatesa prior shape into a geometric active contour modelwith a fixed parameter. the second part determines the'best' parameter used in the first part by maximizing the mutualinformation of the image geometry between the priorand an aligned novel image over all the alignments, thatare the solutions of the first part corresponding to differentparameters. we also present an alternative method, whichgenerates an intensity model formed as the average of a setof aligned training images. experimental results on cardiacultrasound images are presented. these results indicatethat the proposed model provides close agreement withexpert traced borders, and the parameter determined in thismodel for one image can be used for images with similarproperties. the existence of a solution to the proposed minimizationproblem is also discussed.
learning effective image metrics from few pairwise examples. we present a new approach to learning image metrics. the main advantage of our method lies in a formulation that requires only a few pairwise examples. apparently, based on the little amount of side-information, it would take a very effective learning scheme to yield a useful image metric. our algorithm achieves this goal by addressing two key issues. first, we establish a global-local (glocal) image representation that induces two structure-meaningful vector spaces to respectively describe the global and the local image properties. second, we develop a metric optimization framework that finds an optimal bilinear transform to best explain the given side-information. we emphasize it is the glocal image representation that makes the use of bilinear transform more powerful. experimental results on classifications of face images and visual tracking are included to demonstrate the contributions of the proposed method.
robust regression with projection based m-estimators. the robust regression techniques in the ransac family arepopular today in computer vision, but their performance dependson a user supplied threshold. we eliminate this draw-backof ransac by reformulating another robust method,the m-estimator, as a projection pursuit optimization problem.the projection based pbm-estimator automatically derivesthe threshold from univariate kernel density estimates.nevertheless, the performance of the pbm-estimator equalsor exceeds that of ransac techniques tuned to the optimalthreshold, a value which is never available in practice.experiments were performed both with synthetic and realdata in the affine motion and fundamental matrix estimationtasks.
mutual information regularized bayesian framework for multiple image restoration. bayesian methods have been extensively used in various applications. however, there are two intrinsic issues rarely addressed, namely generalization and validity. in the context of multiple image restoration, we show that traditional bayesian methods are sensitive to model errors and cannot guarantee valid results satisfying the underlying prior knowledge, e.g. independent noise property. to improve the bayesian framework¿s generalization, we propose to explicitly enforce the validity of the result. independent noise prior is very important but largely under-utilized in previous literature. in this paper, we use mutual information (mi) to explicitly enforce the independence. efficient approximations based on taylor expansion are proposed to adapt mi into standard energy forms to regularize the bayesian methods. the new regularized bayesian framework effectively utilizes the traditional generative signal/noise models but is much more robust to various model errors, as demonstrated in experiments on some demanding imaging applications.
face detection by fuzzy pattern matching. the paper describes an approach to detect faces whose size and position are unknown in an image with a complex background. the candidates of faces are detected by finding out "face like" regions in the input image using the fuzzy pattern matching method. the perceptually uniform color space is used in our research in order to obtain reliable results. the skin color that is used to detect face like regions, is represented by a model developed by us called skin color distribution function. the skin color regions are then extracted by estimating a measure that describes how well the color of a pixel looks like the skin color for each pixel in the input image. the faces which appear in images are modeled as several 2 dimensional patterns. the face like regions are extracted by a fuzzy pattern matching approach using these face models. the face candidates are then verified by estimating how well the extracted facial features fit a face model which describes the geometrical relations among facial features.
calibration of a hybrid camera network. visual surveillance using a camera network has imposed new challenges to camera calibration. an essential problem is that a large number of cameras may not have a common field of view or even be synchronized well. we propose to use a hybrid camera network that consists of catadioptric and perspective cameras for a visual surveillance task. the relations between multiple views of a scene captured from different cameras can be then calibrated under the catadioptric camera's coordinate system. this paper addresses the important issue of how to calibrate the hybrid camera network. we calibrate the hybrid camera network in three steps. first, we calibrate the catadioptric camera using only the vanishing points. in order to reduce computational complexity, we calibrate the camera without the mirror first and then calibrate the catadioptric camera system. second, we determine 3d positions of some points usingas few as two spatial parallel lines and some equidistance points. finally, we calibrate other perspective cameras based on these known spatial points.
a bidirectional matching algorithm for deformable pattern detection with application to handwritten word retrieval. a bayesian framework for deformable pattern classification has been proposed in [1] with promising results for isolated handwritten character recognition. its performance, however, degrades significantly when it is applied to detect deformable patterns in complex scenes, where the amount of outliers due to other neighboring objects or the background is usually large. also, the fact that the associated evidence measure does not penalize models resting on white space results in a high false alarm rate.in this paper, another bayesian framework for deformable pattern detection is proposed. the framework possesses the intrinsic property of matching with only part of an image (segmentation) and its associated evidence measure can penalize white space implicitly. however, limited data exploration capability is the major trade-off. by properly combining the two frameworks, a new matching algorithm called bi-directional matching is proposed.this combined approach possesses the advantages of the two frameworks and gives robust results for non-rigid shape extraction. to evaluate the performance of the proposed approach, we have applied it to shape-based handwritten word retrieval. using a subset of the bb data-set in the cedar database, we can achieve a recall rate of 59% and a precision rate of 43%.
registration of multimodal fluorescein images sequence of the retina. in this study we present a y-feature extraction method for registering color and fluorescein angiograms of the retina. the registration of multimodal fluorescein imagery requires the identification of strong geometric features in the retinal images that are invariant across modalities and to temporal grey level variations due to the propagation of the dye in the vessels. the most informative features, invariant across the considered modalities, are the locations of vessels¿ ramification: the so-called y-features. we propose a y-feature extraction method based on the local classification of image gradient information and an articulated model. an appropriate cost function is proposed for fitting the model using a gradient-based approach. the fitted y-features are subsequently matched across the images for registering the color and fluorescein images. experimental results obtained on a large database validate the proposed method.
a model of figure-ground segregation from kinetic occlusion. the paper presents a model of image segmentation that can distinguish foreground from background purely on the basis of motion information. the main processing steps involved are: detection of motion boundaries, and analysis of figure ground relationship. the proposed model utilizes the observation that in kinetic occlusion, motion boundaries typically display mixture motion information, and foreground surfaces tend to move with motion boundaries. through distributed probabilistic modeling, these constraints can be embedded into computations with efficient network representations. the resulting networks use spatiotemporal gabor filters as front ends, and are suitable for parallel distributed processing. we demonstrate the application of the model in the decomposition of moving images into surfaces according to depth.
motion from the frontier of curved surfaces. the frontier of a curved surface is the envelope of contour generators showing the boundary, at least locally, of the visible region swept out under viewer motion. in general, the outlines of curved surfaces (apparent contours) from different viewpoints are generated by different contour generators on the surface and hence do not provide a constraint on viewer motion. we show that frontier points, however, have projections which correspond to a real point on the surface and can be used to constrain viewer motion by the epipolar constraint. we show how to recover viewer motion from frontier points for both continuous and discrete motion, calibrated and uncalibrated cameras. we present preliminary results of an iterative scheme to recover the epipolar line structure from real image sequences using only the outlines of curved surfaces. a statistical evaluation as also performed to estimate the stability of the solution.
surface geometry from cusps of apparent contours. it is known that the deformations of the apparent contours of a surface under perspective projection and viewer motion enable the recovery of the geometry of the surface, for example by utilising the epipolar parametrization. these methods break down with apparent contours that are singular i.e. with cusps. in this paper, we study this situation in detail and show how, nevertheless, the surface geometry (including the gauss curvature and mean curvature of the surface) can be recovered by following the cusps. indeed the formulae are much simpler in this case, and require lower spatio-temporal derivatives than in the general case of nonsingular apparent contours. we give a simulated example, and also show that following cusps does not by itself provide us with information on ego-motion.
improving laser triangulation sensors using polarization. we report a novel application of polarization based vision addressing the robustness of laser triangulation range sensors. such sensors are based on the accurate detection of a pattern of laser light projected onto a scene, usually a point or line. typical problems arise with highly specularly reflective surfaces, which can generate visible reflections of the light in various parts of the image. this can confuse the detection algorithms and lead to wrong range measurements. this paper demonstrates experimentally the feasibility of polarization based vision for disambiguating multiple specular inter reflections of the laser light. we concentrate on metal components as they have high interest for inspection in manufacturing, and show positive results with situations of various complexities.
background estimation as a labeling problem. we present a new background estimation algorithm that constructs the background of an image sequence with moving objects by copying areas from input frames. the background estimation problem is formulated as an optimal labeling problem in which the label at an output pixel is the frame number from which to copy the background color. the costs of assigning labels encourage seamless copying from regions that are stationary over a period of time in such a way that implied motion boundaries occur at intensity edges. this is accomplished without explicitly tracking the moving objects or computing optical flow. experiments demonstrate that our algorithm is effective in difficult areas where the background is visible for only a small fraction of time, and on inputs with both moving objects that are not always in motion and moving objects with textureless areas.
auxiliary variables for deformable models. we present a mathematical formulation for curve and surface reconstruction algorithms by introduction of auxiliary variables. for deformable models and templates, two step iterative algorithms have been often used where, at each iteration, the model is first locally deformed according to the potential data attraction and then globally smoothed. we show how these approaches can be interpreted as the introduction of auxiliary variables and the minimization of a two variables energy. this permits us to transform an implicit data constraint defined by a non convex potential into an explicit convex reconstruction problem. we show some mathematical properties and results on this new auxiliary problem, in particular when the potential is a function of the distance to the closest feature point. we then illustrate our approach for some deformable models and templates and image restoration.
the earth mover's distance under transformation sets. the earth mover's distance (emd) is a distance measure between distributions with applications in image retrieval and matching. we consider the problem of computing a transformation of one distribution which minimizes its emd to another.the applications discussed here include estimation of the size at which a color pattern occurs in an image, lighting-invariant object recognition, and point feature matching in stereo image pairs. we present a monotonically convergent iteration which can be applied to a large class of emd under transformation problems, although the iteration may converge to only a locally optimal transformation. we also provide algorithms that are guaranteed to compute a globally optimal transformation for a few specific problems, including some emd under translation problems.
tracking meteorological structures through curve matching using geodesic paths. this paper is concerned with the problem of tracking clouds structures like vortices in meteorological images. for this purpose we characterize the deformation between two successive occurrences, by matching their two boundary curves. our approach is based on the computation of the set of paths connecting the two curves to be matched. it minimizes a cost function which measures the local similarity of the two curves. these matching paths are obtained as geodesic curves on this cost surface. moreover our method allows to consider complex curves of arbitrary topologysince these curves are represented through an implicit function rather than through a parameterization. experimental results are given to illustrate the properties of themethod in processing synthetic and then meteorologic remotely-sensed data.
site model acquisition and extension from aerial images. a system has been developed to acquire, extend and refine 3d geometric site models from aerial imagery. this system hypothesizes potential building roofs in an image, automatically locates supporting geometric evidence in other images, and determines the precise shape and position of the new buildings via multiimage triangulation. model-to-image registration techniques are applied to align new, incoming images against the site model. model extension and refinement procedures are then performed to add previously unseen buildings and to improve the geometric accuracy of the existing 3d building models.
on-line selection of discriminative tracking features. this paper presents a method for evaluating multiple feature spaces while tracking, and for adjusting the set of features used to improve tracking performance. our hypothesisis that the features that best discriminate between object and background are also best for tracking the object. we develop an on-line feature selection mechanism based on the two-class variance ratio measure, applied to log likelihood distributions computed with respect to a given feature from samples of object and background pixels. this feature selection mechanism is embedded in a tracking system that adaptively selects the top-ranked discriminative features for tracking. examples are presented to illustrate how the method adapts to changing appearances of both tracked object and scene background.
mean shift analysis and applications. a non-parametric estimator of density gradient, the mean shift, is employed in the joint, spatial-range (value) domain of gray level and color images for discontinuity preserving filtering and image segmentation. properties of the mean shift are reviewed and its convergence on lattices is proven.the proposed filtering method associates with each pixel in the image the closest local mode in the density distribution of the joint domain. segmentation into a piecewise constant structure requires only one more step, fusion of the regions associated with nearby modes.the proposed technique has two parameters controlling the resolution in the spatial and range domains. since convergence is guaranteed, the technique does not require the intervention of the user to stop the filtering at the desired image quality. several examples, for gray and color images, show the versatility of the method and compare favorably with results described in the literature for the same images.
real-time obstacle avoidance using central flow divergence and peripheral flow. the lure of using motion vision as a fundamental element in the perception of space drives this effort to use flow features as the sole cues for robot mobility. real-time estimates of image flow and flow divergence provide the robot's sense of space. the robot steers down a conceptual corridor comparing left and right peripheral flows. large central flow divergence warns the robot of impending collisions at "dead ends." when this occurs, the robot turns around and resumes wandering. behavior is generated by directly using flow-based information in the 2d image sequence; no 3d reconstruction is attempted. active mechanical gate stabilization simplifies the visual interpretation problems by reducing camera rotation. by combining corridor following and dead-end deflection, the robot has wandered around the lab at 30 cm/s for as long as 20 minutes without collision. the ability to support this behavior in real-time with current equipment promises expanded capabilities as computational power increases in the future.
a multi-body factorization method for motion analysis. the structure from motion problem has been extensively studied in the field of computer vision. yet, the bulk of the existing work assumes that the scene contains only a single moving object. the more realistic case where an unknown number of objects move in the scene has received little attention, especially for its theoretical treatment. we present a new method for separating and recovering the motion and shape of multiple independently moving objects in a sequence of images. the method does not require prior knowledge of the number of objects, nor is dependent on any grouping of features into an object at the image level. for this purpose, we introduce a mathematical construct of object shapes, called the shape interaction matrix, which is invariant to both the object motions and the selection of coordinate systems. this invariant structure is computable solely from the observed trajectories of image features without grouping them into individual objects. once the structure is computed, it allows for segmenting features into objects by the process of transforming it into a canonical form, as well as recovering the shape and motion of each object.
manhattan world: compass direction from a single image by bayesian inference. when designing computer vision systems for the blind and visually impaired it is important to determine the orientation of the user relative to the scene. we observe that most indoor and outdoor (city) scenes are designed on a manhattan three-dimensional grid. this manhattan grid structure puts strong constraints on the intensity gradients in the image. we demonstrate an algorithm for detecting the orientation of the user in such scenes based on bayesian inference using statistics which we have learnt in this domain. our algorithm requires a single input image and does not involve pre-processing stages such as edge detection and hough grouping. we demonstrate strong experimental results on a range of indoor and outdoor images. we also show that estimating the grid structure makes it significantly easier to detect target objects which are not aligned with the grid.
variational space-time motion segmentation. we propose a variational method for segmenting imagesequences into spatio-temporal domains of homogeneousmotion. to this end, we formulate the problem of motionestimation in the framework of bayesian inference, using aprior which favors domain boundaries of minimal surfacearea. we derive a cost functional which depends on a surfacein space-time separating a set of motion regions, aswell as a set of vectors modeling the motion in each region.we propose a multiphase level set formulation of thisfunctional, in which the surface and the motion regions arerepresented implicitly by a vector-valued level set function.joint minimization of the proposed functional results in aneigenvalue problem for the motion model of each region andin a gradient descent evolution for the separating interface.numerical results on real-world sequences demonstratethat minimization of a single cost functional generates asegmentation of space-time into multiple motion regions.
single view metrology. we describe how 3d affine measurements may be computed from a single perspective view of a scene given only minimal geometric information determined from the image. this minimal information is typically the vanishing line of a reference plane, and a vanishing point for a direction not parallel to the plane. it is shown that affine scene structure may then be determined from the image, without knowledge of the camera's internal calibration (e.g. focal length), nor of the explicit relation between camera and world (pose).in particular, we show how to (i) compute the distance between planes parallel to the reference plane (up to a common scale factor)&semi; (ii) compute area and length ratios on any plane parallel to the reference plane&semi; (iii) determine the camera's location. simple geometric derivations are given for these results. we also develop an algebraic representation which unifies the three types of measurement and, amongst other advantages, permits a first order error propagation analysis to be performed, associating an uncertainty with each measurement.we demonstrate the technique for a variety of applications, including height measurements in forensic images and 3d graphical modelling from single images.
gaze manipulation for one-to-one teleconferencing. a new algorithm is proposed for novel view generation in one-to-one teleconferencing applications. given the video streams acquired by two cameras placed on either side of a computer monitor, the proposed algorithm synthesises images from a virtual camera in arbitrary position (typically located within the monitor) to facilitate eye contact. our technique is based on an improved, dynamic-programming, stereo algorithm for efficient novel-view generation. the two main contributions of this paper are: i) a new type of three-plane graph for dense-stereo dynamic-programming, that encourages correct occlusion labeling; ii) a compact geometric derivation for novel-view synthesis by direct projection of the minimum-cost surface. furthermore, this paper presents a novel algorithm for the temporal maintenance of a background model to enhance the rendering of occlusions and reduce temporal artefacts (flicker); and a cost aggregation algorithm that acts directly on our three-dimensional matching cost space. examples are given that demonstrate the robustness of the new algorithm to spatial and temporal artefacts for long stereo video streams. these include demonstrations of synthesis of cyclopean views of extended conversational sequences. we further demonstrate synthesis from a freely translating virtual camera.
learning-based hand sign recognition using shoslif-m. we present a self-organizing framework called the shoslif-m for learning and recognizing spatiotemporal events (or patterns) from intensity image sequences. the proposed framework consists of a multiclass, multivariate discriminant analysis to automatically select the most discriminating features (mdf), a space partition tree to achieve a logarithmic retrieval time complexity for a database of n items, and a general interpolation scheme to do view inference and generalization in the mdf space based on a small number of training samples. the system is tested to recognize 28 different hand signs. the experimental results show that the learned system can achieve a 96% recognition rate for test sequences that have not been used in the training phase.
better optical triangulation through spacetime analysis. the standard methods for extracting range data from optical triangulation scanners are accurate only for planar objects of uniform reflectance illuminated by an incoherent source. using these methods, curved surfaces, discontinuous surfaces, and surfaces of varying reflectance cause systematic distortions of the range data. coherent light sources such as lasers introduce speckle artifacts that further degrade the data. we present a new ranging method based on analyzing the time evolution of the structured light reflections. using our spacetime analysis, we can correct for each of these artifacts, thereby attaining significantly higher accuracy using existing technology. we present results that demonstrate the validity of our method using a commercial laser stripe triangulation scanner.
a stochastic filter for fluid motion tracking. in this paper we present a method for the tracking of fluid flows velocity fields. the technique we propose is formalized within sequential bayesian filter framework. the filter we propose here combines an itô diffusion process coming from a stochastic formulation of the vorticity-velocity form of navier-stokes equation and discrete measurements extracted from an image sequence. the resulting tracker provides robust and consistent estimations of instantaneous motion fields along the whole image sequence. in order to handle a state space of reasonable dimension for the stochastic filtering problem, we represent the motion field as a combination of adapted basis functions. the used basis functions ensue from a mollification of biot-savart integral and a discretization of the vorticity and divergence maps of the fluid vector field. the efficiency of the method is demonstrated on a long real world sequence showing a vortex launch at tip of airplane wing.
correlation model for 3d texture. while an exact definition of texture is somewhat elusive, texture can be qualitatively described as a distribution of color, albedo or local normal on a surface. in the literature, the word texture is often used to describe a color or albedo variation on a smooth surface. we refer to such texture as 2d texture.in real world scenes, texture is often due to surface height variations and can be termed 3d texture. because of local foreshortening and masking, oblique views of 3d texture are not simple transformations of the frontal view. consequently, texture representations such as the correlation function or power spectrum are also affected by local foreshortening and masking.this work presents a correlation model for a particular class of 3d textures. the model characterizes the spatial relationship among neighboring pixels in an image of 3d texture and the change of this spatial relationship with viewing direction.
object recognition in high clutter images using line features. we present an object recognition algorithm that uses model and image line features to locate complex objects in high clutter environments. finding correspondences between model and image features is the main challenge in most object recognition systems. in our approach, corresponding line features are determined by a three-stage process. the first stage generates a large number of approximate pose hypotheses from correspondences of one or two lines in the model and image. next, the pose hypotheses from the previous stage are quickly ranked by comparing local image neighborhoods to the corresponding local model neighborhoods. fast nearest neighbor and range search algorithms are used to implement a distance measure that is unaffected by clutter and partial occlusion. the ranking of pose hypotheses is invariant to changes in image scale, orientation, and partially invariant to affine distortion. finally, a robust pose estimation algorithmis applied for refinement and verification, starting from the few best approximate poses produced by the previous stages. experiments on real images demonstrate robust recognition of partially occluded objects in very high clutter environments.
error-tolerant visual planning of planar grasp. this paper describes an effcient method to calculate, from an image of an object,configurations of a two-fingered robot gripp er that form a "cage" to contain that object. closing the fingers on the object from these configurations is guaranteed to reach a given desired grasp. this builds on the visual grasping theory of blake, taylor and cox [1], which describes how to find optimal grasps. it extends the results of rimon and blake [10], which show how to construct such cages, in two ways. first, a more effcient algorithm for computing the cage is described. second, a further development deals with occlusion by solving thecaging problem within a restricted image window. the new methods greatly reduce the complexity of the visual caging problem, making it feasible in a real time computer vision system.
calibrating pan-tilt cameras in wide-area surveillance networks. pan-tilt cameras are often used as components of wide-area surveillance systems. it is necessary to calibrate these cameras in relation to one another in order to obtain a consistent representation of the entire space. existing methods for calibrating pan-tilt cameras have assumed an idealized model of camera mechanics. in addition, most methods have been calibrated using only asmall range of camera motion. this paper presents a method for calibrating pan-tilt cameras that introduces a more complete model of camera motion. pan and tilt rotations are modeled as occurring around arbitrary axes in space. in addition, the wide area surveillance system itself is used to build a large virtual calibration object, resulting in better calibration than would be possible with a single small calibration target. finally, the proposed enhancements are validated experimentally, with comparisons showing the improvement provided over more traditional methods.
recognizing human action efforts: an adaptive three-mode pca framework. we present a computational framework capable of labelingthe effort of an action corresponding to the perceivedlevel of exertion by the performer (low - high). the approachinitially factorizes examples (at different efforts) ofan action into its three-mode principal components to reducethe dimensionality. then a learning phase is introducedto compute expressive-feature weights to adjust themodel's estimation of effort to conform to given perceptuallabels for the examples. experiments are demonstrated recognizingthe efforts of a person carrying bags of differentweight and for multiple people walking at different paces.
brdf invariant stereo using light transport constancy. nearly all existing methods for stereo reconstruction assume that scene reflectance is lambertian, and make use of color constancy as a matching invariant. we introduce a new invariant for stereo reconstruction called light transport constancy, which allows completely arbitrary scene reflectance (brdfs). this invariant can be used to formulate a rank constraint on multiview stereo matching when the scene is observed in several lighting configurations. in addition, we show that this multiview constraint can be used with as few as two cameras and two lighting configurations. unlikely previous methods for brdf invariant stereo, light transport constancy does not require precisely configured or calibrated light sources, nor calibration objects in the scene. importantly, the new constraint can be used to provide brdf invariance to any existing stereo method, whenever appropriate lighting variation is available.
real-time simultaneous localisation and mapping with a single camera. ego-motion estimation for an agile single camera movingthrough general, unknown scenes becomes a much morechallenging problem when real-time performance is requiredrather than under the off-line processing conditionsunder which most successful structure from motion workhas been achieved. this task of estimating camera motionfrom measurements of a continuously expanding set of self-mappedvisual features is one of a class of problems knownas simultaneous localisation and mapping (slam) in therobotics community, and we argue that such real-time mappingresearch, despite rarely being camera-based, is morerelevant here than off-line structure from motion methodsdue to the more fundamental emphasis placed on propagationof uncertainty.we present a top-down bayesian framework for single-cameralocalisation via mapping of a sparse set of naturalfeatures using motion modelling and an information-guidedactive measurement strategy, in particular addressingthe difficult issue of real-time feature initialisation viaa factored sampling approach. real-time handling of uncertaintypermits robust localisation via the creating andactive measurement of a sparse map of landmarks such thatregions can be re-visited after periods of neglect and localisationcan continue through periods when few features arevisible. results are presented of real-time localisation fora hand-waved camera with very sparse prior scene knowledgeand all processing carried out on a desktop pc.
active search for real-time vision. in most cases when information is to be extracted from an image, there are priors available on the state of the world and therefore on the detailed measurements which will be obtained. while such priors are commonly combined with the actual measurements via bayes¿ rule to calculate posterior probability distributions on model parameters, their additional value in guiding efficient image processing has almost always been overlooked. priors tell us where to look for information in an image, how much computational effort we can expect to expend to extract it, and of how much utility to the task in hand it is likely to be. such considerations are of importance in all practical real-time vision systems, where the processing resources available at each frame in a sequence are strictly limited ¿ and it is exactly in high frame-rate real-time systems such as trackers where strong priors are most likely to be available. in this paper, we use shannon information theory to analyse the fundamental value of measurements using mutual information scores in absolute units of bits, specifically looking at the overwhelming case where uncertainty can be characterised by gaussian probability distributions. we then compare these measurement values with the computational cost of the image processing required to obtain them. this theory puts on a firm footing for the first time principles of ¿active search¿ for efficient guided image processing, in which candidate features of possibly different types can be compared and selected automatically for measurement.
adaptive shape evolution using blending. we propose a shape representation scheme which allows two shapes to be combined into a single model. the desired regions of the two shapes are selected, and then merged together forming a blended shape. for reconstruction, blending is incorporated into a deformable model framework. the model automatically adapts to the data, blending when necessary. hierarchical blending allows multiple blends of a shape to occur forming an evolution from the initial shape of a sphere to the final shape. blending also allows the insertion of a hole between arbitrary locations. the models used are globally defined, making the recovered shape a natural symbolic description. we present reconstruction experiments involving shapes of various topologies.
deformable model-based shape and motion analysis from images using motion residual error. we present a novel method for the shape and motion estimation of a deformable model using error residuals from model-based motion analysis. the motion of the model is first estimated using a model-based least squares method. using the residuals from the least squares solution, the non-rigid structure of the model can be better estimated by computing how changes in the shape of the model affect its motion parameterization. this method is implemented as a component in a deformable model-based framework that uses optical flow information and edges. this general model-based framework is applied to human face shape and motion estimation. we present experiments that demonstrate that this framework is a considerable improvement over a framework that uses only optical flow information and edges.
3d articulated models and multi-view tracking with silhouettes. we propose a method to estimate the motion of a person filmed by two or more fixed cameras. the novelty of our technique is its ability to cope with fast movements, self-occlusions and noisy images. our algorithms are based on the latest works on calibration and image segmentation developed in our lab. we compare the projections of a 3d model of a person on the images to the detected silhouettes of the person, and create forces that will move the 3d model towards the final estimation of the real pose. we developed a fast algorithm that computes the motion of the articulated 3d model. we show that our results are good, even if the cameras are not synchronized.
initialization of deformable models from 3d data. the robustness of shape recovery based on deformable models dep ends in general, on the relative difference of position and topology of the initial model with respect to the data: a close initialization with correct topology guaranties a proper recovery of the object. furthermore, the closeness of the initial model greatly influences the time of computation needed for the recovery. in this paper, we propose a method for initializing deformable models from range data or volumetric images. the prop osed method solves two distinct problems. first, we use the topological segmentation of volumetric images in order to recover the approximate topology of the object. second, we use an efficient mesh sampling algorithm to control the number of vertices of the initial model. the method takes into account missing data and outliers.
constraining human body tracking. our paper addresses the problem of enforcing constraintsin human body tracking. a projection technique is derivedto impose kinematic constraints on independent multi-bodymotion: we show that for small motions the multi-body articulatedmotion space can be approximated by a linearmanifold estimated directly from the previous body pose.we propose a learning approach to model non-linear constraints;we train a support vector classifier from motioncapture data to model the boundary of the space of validposes. linear and non-linear body pose constraints are enforcedby first projecting unconstrained motions onto thearticulated motion space and then optimizing to find pointson this linear manifold that lie within the non-linear constraintsurface modeled by the svm classifier.
avoiding the "streetlight effect": tracking by exploring likelihood modes. classic methods for bayesian inference effectively constrain search to lie within regions of significant probability of the temporal prior. this is efficient with an accurate dynamics model, but otherwise is prone to ignore significant peaks in the true posterior. a more accurate posterior estimate can be obtained by explicitly finding modes of the likelihood function and combining them with a weak temporal prior. in our approach modes are found using effi- cient example-based matching followed by local refinement to find peaks and estimate peak bandwidth. by reweighting these peaks according to the temporal prior we obtain an estimate of the full posterior model. we show comparative results on real and synthetic images in a high degree of freedom articulated tracking task.
a symmetric patch-based correspondence model for occlusion handling. occlusion is one of the challenging problems in stereo. in this paper, we solve the problem in a segment-based style. both images are segmented, and we propose a novel patch-based stereo algorithm that cuts the segments of one image using the segments of the other, and handles occlusion areas in a proper way. a symmetric graph-cuts optimization framework is used to find correspondence and occlusions simultaneously. the experimental results show superior performance of the proposed algorithm, especially on occlusions, untextured areas and discontinuities.
information theoretic focal length selection for real-time active 3-d object tracking. active object tracking, for example, in surveillance tasks, becomes more and more important these days. besides the tracking algorithms themselves methodologies have to be developed for reasonable active control of the degrees of freedom of all involved cameras. in this paper we present an information theoretic approach that allows the optimal selection of the focal lengths of two cameras during active 3-d object tracking. the selection is based on the uncertainty in the 3-d estimation. this allows us to resolve the trade-off between small and large focal length: in the former case, the chance is increased to keep the object in the field of view of the cameras. in the latter one, 3-d estimation becomes more reliable. also, more details are provided, for example for recognizing the objects.beyond a rigorous mathematical framework we present real-time experiments demonstrating that we gain an improvementin 3-d trajectory estimation by up to 42% in comparison with tracking using a fixed focal length.
tracking through singularities and discontinuities by random sampling. some issues in marker-less tracking of human body motion are addressed. extended kalman filters have commonly been applied to kinematic variables, to combine predictions consistent with plausible motion, with the incoming stream of visual measurements. kalman filtering is applicable only when the underlying distribution is approximately gaussian. often, this assumption proves remarkably robust.there are two pervasive circumstances under which the gaussianity assumption can break down. the first is kinematic singularity, and the second is at joint end-stops. failure of kalman filtering under these circumstance is illustrated.the non-gaussian nature of the distributions is demonstrated experimentally by means of monte-carlo simulation. random simulation - particle filtering or condensation -proves to provide a robust alternative algorithm for tracking that can also deal with these difficult conditions.
markov-based failure prediction for human motion analysis. this paper presents a new method of detecting andpredicting motion tracking failures with applications inhuman motion and gait analysis. we define a trackingfailure as an event and describe its temporal characteristicsusing a hidden markov model (hmm). thisstochastic model is trained using previous examples oftracking failures. we derive vector observations for thehmm using the noise covariance matrices characterizinga tracked, 3-d structural model of the human body. weshow a causal relationship between the conditional outputprobability of the hmm, as transformed using alogarithmic mapping function, and impending trackingfailures. results are illustrated on several multi-viewsequences of complex human motion.
active concept learning for image retrieval in dynamic databases. concept learning in content-based image retrieval (cbir) systems is a challenging task. this paper presents an active concept learning approach based on mixture model to deal with the two basic aspects of a database system: changing (image insertion or removal) nature of a database and user queries. to achieve concept learning, we develop a novel model selection method based on bayesian analysis that evaluates the consistency of hypothesized models with the available information. the analysis of exploitation vs. exploration in the search space helps to find optimal model efficiently. experimental results on corel database show the efficacy of our approach.
cosmos-a representation scheme for free-form surfaces. we address the problem of representing and recognizing arbitrarily curved 3d rigid objects when: the objects may vary in shape and complexity, and no restrictive assumptions are made about the types of surfaces on the object. we propose a new and general surface representation scheme for recognizing objects with free form (sculpted) surfaces from range data. in this scheme, an object is described concisely in terms of maximal surface patches of constant shape index. these maximal patches are mapped onto the unit sphere via their orientations, and aggregated via shape spectral functions. properties such as surface area, curvedness and connectivity that capture local and global information are also built into the representation. the scheme yields not only a meaningful and rich surface description useful for the recoverability of the object, but also a set of powerful indexing primitives for object matching. we demonstrate the generality and the effectiveness of our scheme using real range images of complex objects. we also present results on the categorization of object views based on a novel shape spectral matching technique.
dynamic texture segmentation. we address the problem of segmenting a sequence of imagesof natural scenes into disjoint regions that are characterizedby constant spatio-temporal statistics. we model thespatio-temporal dynamics in each region by gauss-markovmodels, and infer the model parameters as well as theboundary of the regions in a variational optimization framework.numerical results demonstrate that - in contrast topurely texture-based segmentation schemes - our method iseffective in segmenting regions that differ in their dynamicseven when spatial statistics are identical.
selection of scale-invariant parts for object class recognition. this paper introduces a novel method for constructingand selecting scale-invariant object parts. scale-invariantlocal descriptors are first grouped into basic parts. a classifieris then learned for each of these parts, and featureselection is used to determine the most discriminative ones.this approach allows robust part detection, and it is invariantunder scale change-that is, neither the training imagesnor the test images have to be normalized.the proposed method is evaluated in car detectiontasks with significant variations in viewing conditions, andpromising results are demonstrated. different local regions,classifiers and feature selection methods are quantitativelycompared. our evaluation shows that local invariantdescriptors are an appropriate representation for objectclasses such as cars, and it underlines the importance offeature selection.
self-calibration of a stereo rig using monocular epipolar geometry. this paper addresses the problem of self-calibration from one unknown motion of an uncalibrated stereo rig. unlike the existing methods for stereo rig self-calibration, which have been focused on applying the autocalibration paradigm using both motion and stereo correspondences, our method does not require the recovery of stereo correspondences. our method combines purely algebraic constraints with implicit geometric constraints. assuming that the rotational part of the stereo geometry has two unknown degrees of freedom (i.e., the third dof is roughly known), and that the principle point of each camera is known, we first show that the computation of the intrinsic and extrinsic parameters of the stereo rig can be recovered from the motion correspondences only, i.e., the monocular fundamental matrices. we then provide an initialization procedure for the proposed non-linear method. we provide an extensive performance study for the method in the presence of image noise. in addition, we study some of the aspects related to the 3d motion that govern the accuracy of the proposed self-calibration method. experiments conducted on synthetic and real data/images demonstrate the effectiveness and efficiency of the proposed method.
simultaneous facial action tracking and expression recognition using a particle filter. the recognition of facial gestures and expressions in image sequences is an important and challenging problem. most of the existing methods adopt the following paradigm. first, facial actions/features are retrieved from the images, and then facial expressions are recognized based on the retrieved temporal parameters. unlike this main stream, this paper introduces a new approach allowing the simultaneous recovery of facial actions and expression using a particle filter adopting multi-class dynamics that are conditioned on the expression. for each frame in the video sequence, our approach is split in two consecutive stages. in the first stage, the 3d head pose is recovered using a deterministic registration technique based on online appearance models. in the second stage, the facial actions as well as the facial expression are simultaneously recovered using the stochastic framework with mixed states. the proposed fast scheme is either as robust as existing ones or more robust with respect to many regards. experimental results show the feasibility and robustness of the proposed approach.
on optimal light configurations in photometric stereo. this paper develops new theory for the optimal placement of photometric stereo lighting in the presence of camera noise. we show that for three lights, any triplet of orthogonal light directions minimises the uncertainty in scaled normal computation. the assumptions are that the camera noise is additive and normally distributed, and uncertainty is defined as the expectation of squared distance of scaled normal to the ground truth. if the camera noise is of zero mean and variance ¿², the optimal (minimum) uncertainty in the scaled normal is 3¿². for case of n > 3 lights, we show that the minimum uncertainty is 9¿²/n, and identify sets of light configurations which reach this theoretical minimum.
can two specular pixels calibrate photometric stereo?. lambertian photometric stereo with unknown light source parameters is ambiguous. provided that the object imaged constitutes a surface, the ambiguity is represented by the group of generalised bas-relief (gbr) transformations. we show that this ambiguity is resolved when specularreflection is present in two images taken under two different light source directions. we identify all configurations of the two directional lights which are singular and show that they can easily be tested for. while previous work used optimisation algorithms to apply the constraints implied by the specular reflectance component, we have developed a linear algorithm to achieve this goal. our theory can be utilised to construct fast algorithms for automatic reconstruction of smooth glossy surfaces.
illumination-invariant color object recognition via compressed chromaticity histograms of color-channel-normalized images. several color object recognition methods that are based on image retrieval algorithms attempt to discount changes of illumination in order to increase performance when test image illumination conditions differ from those that obtained when the image database was created. here we extend the seminal method of swain and ballard to discount changing illumination.the new method is based on the first stage of the simplest color indexing method, which uses angular invariants between color image and edge image channels. that method first normalizes image channels, and then effectively discards much of the remaining information. here we adopt the color-normalization stage as an adequate color constancy step. further,we replace 3d color histograms by 2d chromaticity histograms. treating these as images, we implement the method in a compressed histogram-image domain using a combination of wavelet compression and discrete cosine transform (dct) to fully exploit the technique of low-pass filtering for efficiency. results are very encouraging, with substantially better performance than other methods tested. the method is also fast, in that the indexing process is entirely carried out in the compressed domain and uses a feature vector of only 36 or 72 values.
incremental discovery of object parts in video sequences. this paper addresses the problem of automatically discovering the rigid parts of an initially unknown moving deformable object in a monocular video sequence. the parts are first extracted through motion-based segmentation, using a time scale automatically chosen with the quantity of motion concept. tracking and reobservation reinforce these low-level segmentation results and further segmentation is performed only when and where no modeled parts can be tracked. central to the system is the modeler that minimizes the impacts of erroneous segmentations and departures in tracking. the sequential nature of the framework allows incremental modeling and segmentation of parts that need not simultaneously be visible or in motion, making it possible to circumvent the typical constraint of model initialization. the fundamental principles are strictly ensemblist and do not rely on any specific pdf. the interest of this framework is demonstrated on three types of video sequences including human and robot motion.
a multi-scale generative model for animate shapes and parts. this paper presents a multi-scale generative model for representing animate shapes and extracting meaningful parts of objects. the model assumes that animate shapes (2d simple closed curves) are formed by a linear superposition of a number of shape bases. these shapebases resemble the multi-scale gabor bases in image pyramid representation, are well localized in both spatial and frequency domains, and form an over-complete dictionary. this model is simpler than the popular b-spline representation since it does not engage a domainpartition. thus it eliminates the interference between adjacent b-spline bases, and becomes a true linear additive model. we pursue the bases by reconstructing the shape in a coarse-to-fine procedure through curve evolution. these shape bases are further organized ina tree-structure where the bases in each subtree sum up to an intuitive part of the object. to build probabilistic model for a class of objects, we propose a markov random field model at each level of the tree representation to account for the spatial relationship between bases. thus the final model integrates a markov tree (generative) model over scales and a markov random field over space. we adopt em-type algorithm for learning the meaningful parts for a shape class, and show some results on shape synthesis.
indexing visual representations through the complexity map. in differential geometry curves are characterized as mappings from an interval to the plane. in topology curves are characterized as a hausdorff space with certain countability properties. neither of these definitions captures the role that curves play in vision, however, in which curves can denote simple objects (such as a straight line), or complicated objects (such as a jumble of string). the difference between these situations is in part a measure of their complexity, and in part a measure of their dimensionality. note that the map defining such curves is unknown, as is the proper way to represent them. we propose a formal complexity theory of curves appropriate for computational vision in general, and for problems like separating straight lines from jumbles in particular. the theory is applied to the problem of perceptual grouping.
optimal polyline tracking for artery motion compensation in coronary angiography. we propose a novel solution to the problem of motion compensation of coronary angiographs. as the heart is beating, it is difficult for the physician to observe closely a particular point (e.g. stenosis) on the artery tree. we propose to rigidly compensate the sequence so that the area around the point of interest appears stable. this is a difficult problem because the arteries deform in a nonrigid manner and only their 2d x-ray projection is observed. also, the lack of features around the selected point makes the matching subject to the aperture problem. the algorithm automatically extracts a section of the artery of interest, models it as a polyline, andtracks it. the problem is formulated as an energy minimization problem which is solved using a shortest path in a graph algorithm. the motion compensated sequence can be obtained by translating every pixel so that the point of interest remains stable. we have applied this algorithm to many examples in two sets of angiography data and have obtained excellent results.
shape representation via harmonic embedding. we present a novel representation of shape for closedplanar contours explicitly designed to possess a linearstructure. this greatly simplifies linear operations suchas averaging, principal component analysis or differentiation in the space of shapes. the representation reliesupon embedding the contour on a subset of the space ofharmonic functions of which the original contour is thezero level set.
controlling model complexity in flow estimation. this paper describes a novel application of statisticallearning theory (slt) to control model complexity in flowestimation. slt provides analytical generalization boundssuitable for practical model selection from small and noisydata sets of image measurements (normal flow). the methodaddresses the aperture problem by using the penalized risk(ridge regression). we demonstrate an application of thismethod on both synthetic and real image sequences and useit for motion interpolation and extrapolation. our experimentalresults show that our approach compares favorablyagainst alternative model selection methods such as theakaike's final prediction error, schwartz's criterion, generalizedcross-validation, and shibata's model selector.
learning-based object detection in cardiac mr images. an automated method for left ventricle detection in mr cardiac images is presented. ventricle detection is the first step in a fully automated segmentation system used to compute volumetric information about the heart.our method is based on learning the gray level appearance of the ventricle by maximizing the discrimination between positive and negative examples in a training set. the main differences from previously reported methods are feature definition and solution to the optimization problem involved in the learning process.our method was trained on a set of 1,350 mr cardiac images from which 101,250 positive examples and 123,096 negative examples were generated. the detection results on a test set of 887 different images demonstrate an excellent performance: 98% detection rate, a false alarm rate of 0:05% of the number of windows analyzed (10 false alarms per image) and a detection time of 2 seconds per 256 × 256 image on a sun ultra 10 for an 8-scale search. the false alarms are eventually eliminated by a position/scale consistency check along all the images that represent the same anatomical slice.
learning to identify and track faces in image sequences. we address the problem of robust face identification in the presence of pose, lighting, and expression variation. previous approaches to the problem have assumed similar models of variation for each individual, estimated from pooled training data. we describe a method of updating a first order global estimate of identity by learning the class-specific correlation between the estimate and the residual variation during a sequence. this is integrated with an optimal tracking scheme, in which identity variation is decoupled from pose, lighting and expression variation. the method results in robust tracking and a more stable estimate of facial identity under changing conditions.
recognizing action at a distance. our goal is to recognize human actions at a distance,at resolutions where a whole person may be, say, 30 pixelstall. we introduce a novel motion descriptor based onoptical flow measurements in a spatio-temporal volume foreach stabilized human figure, and an associated similaritymeasure to be used in a nearest-neighbor framework. makinguse of noisy optical flow measurements is the key challenge,which is addressed by treating optical flow not asprecise pixel displacements, but rather as a spatial patternof noisy measurements which are carefully smoothed andaggregated to form our spatio-temporal motion descriptor.to classify the action being performed by a human figurein a query sequence, we retrieve nearest neighbor(s) from adatabase of stored, annotated video sequences. we can alsouse these retrieved exemplars to transfer 2d/3d skeletonsonto the figures in the query sequence, as well as two formsof data-based action synthesis "do as i do" and "do as isay". results are demonstrated on ballet, tennis as well asfootball datasets.
texture synthesis by non-parametric sampling. a non-parametric method for texture synthesis is proposed. the texture synthesis process grows a new image outward from an initial seed, one pixel at a time. a markov random field model is assumed, and the conditional distribution of a pixel given all its neighbors synthesized so far is estimated by querying the sample image and finding all similar neighborhoods. the degree of randomness is controlled by a single perceptually intuitive parameter. the method aims at preserving as much local structure as possible and produces good results for a wide variety of synthetic and real-world textures.
variational-based method to extract parametric shapes from images. in this paper, we propose a variational method to segment image objects, which have a given parametric shape based on a level-set formulation of the mumford-shah functional, and the shape parameters. we define an energy functional composed by two complementary terms. the first one detects object boundaries using a chan-vese-like method. the second term constrains the contour to find a shape compatible with the parametric shape. the segmentation of the object of interest is given by the minimum of our energy functional. this minimum is computed with the calculus of variation and the gradient descent method that provide a system of evolution equations solved with the well-known level set method. we focus in this paper on the parametric category of image linear objects. applications of the proposed model are presented on synthetic and real images.
nonmetric lens distortion calibration: closed-form solutions, robust estimation and model selection. this paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide angle lenses. while almost all existing nonmetric distortion calibration methods need user involvement in one form or another, we present an automatic approach based on the robust the-least-median-of-squares (lmeds) estimator. our approach is thus less sensitive to erroneous input data such as image curves that are mistakenly considered as projections of 3d linear segments. our approach uniquely uses fast, closed-form solutions to the distortion coefficients, which serve as an initial point for a non-linear optimization algorithm to straighten imaged lines. moreover we propose a method for distortion model selection based on geometrical inference. successful experiments to evaluate the performance of this approach on synthetic and real data are reported.
an automatic drowning detection surveillance system for challenging outdoor pool environments. automatically understanding events happening at a site is the ultimate goal of visual surveillance system. this paper investigates the challenges faced by automated surveillance systems operating in hostile conditions and demonstrates the developed algorithms via a system that detects water crises within highly dynamic aquatic environments. an efficient segmentation algorithm based on robust block-based background modeling and thresholding-with-hysteresis methodology enables swimmers to be reliably detected amid reflections, ripples, splashes and rapid lighting changes. partial occlusions are resolved using a markov random field framework that enhances the tracking capability of the system. visual indicators of water crises are identified based on professional knowledge of water crises detection, based on which a set of swimmer descriptors has been defined. through seamlessly fusing the extracted swimmer descriptors based on a novel functional link network, the system achieves promising results for water crises detection. the developed algorithms have been incorporated into a live system with robust performance for different hostile environments faced by an outdoor swimming pool.
feature hierarchies for object classification. the paper describes a method for automatically extracting informative feature hierarchies for object classification, and shows the advantage of the features constructed hierarchically over previous methods. the extraction process proceeds in a top-down manner: informative top-level fragments are extracted first, and by a repeated application of the same feature extraction process the classification fragments are broken down successively into their own optimal components. the hierarchical decomposition terminates with atomic features that cannot be usefully decomposed into simpler features. the entire hierarchy, the different features and sub-features, and their optimal parameters, are learned during a training phase using training examples. experimental comparisons show that these feature hierarchies are significantly more informative and better for classification compared with similar non-hierarchical features as well as previous methods for using feature hierarchies.
facial expression recognition using a dynamic model and motion energy. previous efforts at facial expression recognition have been based on the facial action coding system (facs), a representation developed in order to allow human psychologists to code expression from static facial "mugshots." we develop new more accurate representations for facial expression by building a video database of facial expressions and then probabilistically characterizing the facial muscle activation associated with each expression using a detailed physical model of the skin and muscles. this produces a muscle based representation of facial motion, which is then used to recognize facial expressions in two different ways. the first method uses the physics based model directly, by recognizing expressions through comparison of estimated muscle activations. the second method uses the physics based model to generate spatio temporal motion energy templates of the whole face for each different expression. these simple, biologically plausible motion energy "templates" are then used for recognition. both methods show substantially greater accuracy at expression recognition than has been previously achieved.
identifying individuals in video by combining "generative" and discriminative head models. the objective of this work is automatic detection and identification of individuals in unconstrained consumer video, given a minimal number of labelled faces as training data. whilst much work has been done on (mainly frontal) face detection and recognition, current methods are notsufficiently robust to deal with the wide variations in pose and appearance found in such video. these include variations in scale, illumination, expression, partial occlusion, motion blur, etc. we describe two areas of innovation: the first is to capture the 3-d appearance of the entire head, rather than just the face region, so that visual features such as the hairline can be exploited. the second is to combine discriminative and ¿generative¿ approaches for detection and recognition. images rendered using the head model are used to train a discriminative tree-structured classifier giving efficient detection and pose estimates over a very wide pose range with three degrees of freedom. subsequent verification of the identity is obtained using the head model in a ¿generative¿ framework. we demonstrate excellent performance in detecting and identifying three characters and their poses in a tv situation comedy.
transfer of fixation for an active stereo platform via affine structure recovery. this paper describes an algorithm for stereo tracking using 3d affine transfer of a body-centred fixation point. transfer is based on corners detected in the image and matched over time and in stereo. the paper presents a method of basing the transfer on all the available data, providing immunity to noise and poor conditioning. the paper also shows an implementation at video rates on a four axis active camera platform. graceful degradation in the presence of insufficient data and fixed latency tracking in parallel with the structure calculation provide robust performance. recovered trajectories are shown in an approximately euclidean frame while structure transfer is demonstrated by the evolution of the target's convex hull.
fast recognition of multi-view faces with feature selection. we propose a discriminative feature selection method utilizing support vector machines for the challenging task of multi-view face recognition. according to the statistical relationship between the two tasks, feature selection and multi-class classification, we integrate the two tasks into a single consistent framework and effectively realize the goal of discriminative feature selection. the classification process can be made faster without degrading the generalization performance through this discriminative feature selection method. on the umist multi-view face database, our experiments show that this discriminative feature selection method can speed up the multi-view face recognition process without degrading the correct rate and outperform the traditional kernel subspace methods.
probabilistic contour extraction using hierarchical shape representation. in this paper, we address the issue of extracting contour of the object with a specific shape. a hierarchical graphical model is proposed to represent shape variations. a complex shape is decomposed into several components which are described as principal component analysis (pca) based models in various levels. the hierarchical representation allows for chain-like conditional dependency within a single level and bidirectional communication between different levels. additionally, a sequential monte-carlo (smc) based inference algorithm that can explore the graphical structure is proposed to estimate the contour. the experiments performed on real-world hand and face images show that the proposed method is effective in combating occlusion and cluttered background. moreover, it is possible to isolate the localization error to an individual component of a shape attributed to the hierarchical representation.
on the geometry and algebra of the point and line correspondences between n images. we explore the geometric and algebraic relations that exist between correspondences of points and lines in an arbitrary number of images. we propose to use the formalism of the grassmann-cayley algebra as the simplest way to make both geometric and algebraic statements in a very synthetic and effective way (i.e. allowing actual computation if needed). we have a fairly complete picture of the situation in the case of points; there are only three types of algebraic relations which are satisfied by the coordinates of the images of a 3-d point: bilinear relations arising when we consider pairs of images among the n and which are the well-known epipolar constraints, trilinear relations arising when we consider triples of images among the n, and quadrilinear relations arising when we consider four-tuples of images among the n. in the case of lines, we show how the traditional perspective projection equation can be suitably generalized and that in the case of three images there exist two independent trilinear relations between the coordinates of the images of a 3-d line.
on exploiting occlusions in multiple-view geometry. occlusions are common place in man-made and natural environments; they often result in photometric features where a line terminates at an occluding boundary, resembling a "t". we show that the 2-d motion of such t-junctions in multiple views carries non-trivial information on the 3-d structure of the scene and its motion relative to the camera. we show how the constraint among multiple views of t-junctions can be used to reliably detect them and differentiate them from ordinary point features. finally, we propose an integrated algorithm to recursively and causally estimate structure and motion in the presence of t-junctions along with other point-features.
on the epipolar geometry of the crossed-slits projection. the crossed-slits (x-slits) camera is defined by two non-intersectingslits, which replace the pinhole in the commonperspective camera. each point in space is projected to theimage plane by a ray which passes through the point and thetwo slits. the x-slits projection model includes the pushb-roomcamera as a special case. in addition, it describesa certain class of panoramic images, which are generatedfrom sequences obtained by translating pinhole cameras.in this paper we develop the epipolar geometry of the x-slitsprojection model. we show an object which is similarto the fundamental matrix; our matrix, however, describesa quadratic relation between corresponding image points(using the veronese mapping). similarly the equivalent ofepipolar lines are conics in the image plane. unlike the pin-holecase, epipolar surfaces do not usually exist in the sensethat matching epipolar lines lie on a single surface; we analyzethe cases when epipolar surfaces exist, and characterizetheir properties. finally, we demonstrate the matchingof points in pairs of x-slits panoramic images.
realtime ibr with omnidirectional crossed-slits projection. the crossed-slits (x-slits) projection can be used to generate new views of a scene from a sequence of perspective images. compared with other image-based rendering (ibr) techniques, x-slits image generation is simple and requires a relatively small number of input images, which makes it suitable for realtime ibr. in this paper we extend this model to omnidirectional cameras and a circular slit. we show how it can be used for realtime image-based rendering of omnidirectional images, and how to optimize it for speed and quality. we analyze the inherent geometric distortions of the circular x-slits projection, and describe a normalization mechanism to reduce distortions, creating a realistic virtual environment. essentially the same mechanism is used to augment the x-slits images with artificial objects, when using standard graphics tools which assume perspective projection.
3d-2d projective registration of free-form curves and surfaces. some medical interventions require knowing the correspondence between an mri/ct pre-operative image and the actual position of the patient. examples occur in neurosurgery, radiotherapy, interventional radiology, but also in video surgery (laparoscopy). we present in this article three new techniques for performing this task without artificial markers. we find the 3d-2d projective transformation (composition of a rigid displacement and a perspective projection) which maps a 3d object onto a 2d image of this object. depending on the object model (curve or surface), and on the 2d image acquisition system (x-ray, video), the techniques are different but the framework is common. it does not depend on the initial relative positions of the objects and deals with the occlusions and the outliers. results are presented on real medical data to demonstrate the validity of our approach.
bayesian structural content abstraction for region-level image authentication. we present a hierarchical representation of image structure and use it for image content authentication. firstly, we model the image with the markov pixon random field. within the bayesian framework, the optimal label map and regional pixon map can be obtained, based on which wedefine an undirected graph, namely bayesian structural content abstraction (basca). this representation captures the spatial topology information of homogeneous regions as well as their finest scale and interactions. then, an efficient optimization scheme has been proposed to iteratively minimize the distance (or learning error) to all content-identical image samples generated by an acceptable operation setdefined by the user. in addition, we use the regional pixon map to remove spurious vertices and thus to establish a basca hierarchy naturally. the basca itself and its features can act as the signature of the protected image. our experimental results show that the proposed approach has much less false positive and comparable false negative probability compared with the existing methods
sectored snakes: evaluating learned-energy segmentations. we describe how to teach deformable models to maximize image segmentation correctness based on userspecified criteria, and we present a method for evaluating which criteria work best. we present sectored snakes, a formulation that demonstrably improves upon regular snakes.a traditional deformable model ("snake" in 2d) fails to find an object's boundary when the strongest nearby image edges are not the ones sought. but models can be trained to respond to other image features instead, by learning their probability distributions. the implementor must then decide on which of many image qualities to teach the model. to this end, we show how to evaluate the efficacy of any resulting deformable model, given a sampling of ground truth, a model of the range of shapes tried during optimization, and a measure of shape closeness.in the domain of abdominal ct images, we demonstrate such evaluation on a simple "sectoring" of a snake, in which intensity and perpendicular gradient are observed over equal-length segments. this speci.c set of qualities shows a measured improvement over an objective function that is uniform around the shape, and it follows naturally from examination of the latter's failures due to images variations around the organ boundary.
building a classification cascade for visual identification from one example. object identification (oid) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object¿s exact identity (e.g. bob¿s bmw). two special challenges characterize oid. (1) inter-class variation is often small (many cars look alike) and may be dwarfed by illumination or pose changes. (2) there may be many classes but few or just one positive "training" examples per class. due to (1), a solution must locate possibly subtle object-specific salient features (a door handle) while avoiding distracting ones (a specular highlight). however, (2) rules out direct techniques of feature selection. we describe an online algorithm that takes one model image from a known category and builds an efficient "same" vs. "different" classification cascade by predicting the most discriminative feature set for that object. our method not only estimates the saliency and scoring function for each candidate feature, but also models the dependency between features, building an ordered feature sequence unique to a specific model image, maximizing cumulative information content. learned stopping thresholds make the classifier very efficient. to make this possible, category-specific characteristics are learned automatically in an off-line training procedure from labeled image pairs of the category, without prior knowledge about the category. our method, using the same algorithm for both cars and faces, outperforms a wide variety of other methods.
discontinuity preserving stereo with small baseline multi-flash illumination. currently, sharp discontinuities in depth and partial occlusions in multiview imaging systems pose serious challenges for many dense correspondence algorithms. however, it is important for 3d reconstruction methods to preserve depth edges as they correspond to important shape features like silhouettes which are critical for understanding the structure of a scene. in this paper we show how active illumination algorithms can produce a rich set of feature maps that are useful in dense 3d reconstruction. we start by showing a method to compute a qualitative depth map from a single camera, which encodes object relative distances and can be used as a prior for stereo. in a multiview setup, we show that along with depth edges, binocular half-occluded pixels can also be explicitly and reliably labeled. to demonstrate the usefulness of these feature maps, we show how they can be used in two different algorithms for dense stereo correspondence. our experimental results show that our enhanced stereo algorithms are able to extract high quality, discontinuity preserving correspondence maps from scenes that are extremely challenging for conventional stereo methods.
global rigidity constraints in image displacement fields. image displacement fields-optical flow fields, stereo disparity fields, normal flow fields-due to rigid motion possess a global geometric structure which is independent of the scene in view. motion vectors of certain lengths and directions are constrained to lie on the imaging surface at particular loci whose location and form depends solely on the 3d motion parameters. if optical flow fields or stereo disparity fields are considered, then equal vectors are shown to lie on conic sections. similarly, for normal motion fields, equal vectors lie within regions whose boundaries also constitute conics. by studying various properties of these curves and regions and their relationships, a characterization of the structure of rigid motion fields is given. the goal of this paper is to introduce a concept underlying the global structure of image displacement fields. this concept gives rise to various constraints that could form the basis of algorithms for the recovery of visual information from multiple views.
which shape from motion?. in a practical situation, the rigid transformation relating different views is recovered with errors. in such a case, the recovered depth of the scene contains errors, and consequently a distorted version of visual space is computed. what then are meaningful shape representations that can be computed from the images? the result presented in this paper states that if the rigid transformation between different views is estimated in a way that gives rise to a minimum number of negative depth values, then at the center of the image affine shape can be correctly computed. this result is obtained by exploiting properties of the distortion function, developed in [1]. the distortion model turns out to be a very powerful tool in the analysis and design of 3d motion and shape estimation algorithms, and as a byproduct of our analysis we present a computational explanation of psychophysical results demonstrating human visual space distortion from motion information.
building qualitative event models automatically from visual input. we describ e an implemented technique for generating event models automatically based on qualitative reasoning and a statistical analysis of video input. using an existing tracking program which generates labelled contours for objects in every frame, the view from a fixed camera is partitioned into semantically relevant regions based on the paths followed by movingobjects. the paths are indexed with temporal information so objects moving along the same path at different speeds can be distinguished. using a notion of proximity based on the speed of the moving objects and qualitative spatial reasoning techniques, event models describing the behaviour of pairs of objects can be built, again using statistical methods. the system has been tested on a traffic domain and learns various event models expressed in the qualitative calculus which represent human observable events. the system can then be used to recognise subsequent selected event occurrences or unusual behaviours.
achieving a fitts law relationship for visual guided reaching. in order to take advantage of the top speed of manipulators, vision can not be tightly integrated into the motion control loop. past visual servo control systems have performed satisfactorily with this constraint, however it can be shown that the task execution time can be reduced if the vision system is de-coupled from the low level motor control system.for reaching, there is a trade-off between the accuracy of a motion and the time requir ed to execute a motion. in studies of human motor contr ol this trade-off is quantified by fitts law, a relationship between the motion time, the target distance, and the target width. these studies suggest that vision is not used tightly within the control loop, i.e. as a sensor that is servo-ed on, but rather vision is used to determine where the reaching target is and whether target has been reached successfully. through a simple robotic example we demonstrate that a similar trade off exists between motion accuracy and the motion execution time for visual guided robot reaching motions. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
color constancy in diagonal chromaticity space. simple constraints on the sets of possible surface reflectances and illuminants are exploited in a new color constancy algorithm that builds upon forsyth's (1990) theory of color constancy. the goal defined for a color constancy algorithm is to discount variations in the color and intensity of the incident illumination and thereby extract illumination-independent descriptors of surface colors from images. forsyth's method is based on two constraints: first, the surface colors under a canonical illuminant all fall within an established maximal convex gamut of possible colors and second that a diagonal matrix accurately maps colors between illuminants. these constraints taken together turn out to be very effective in solving for color constancy; however, other strong assumptions about the scenes are required for the method to work-the illumination must be uniform, the surfaces must be planar, and there can be no specularities. we show that these restrictions are necessary only because forsyth sets out to recover the intensity of descriptors. at the outset we abandon 3-dimensional descriptor recovery in favor of recovering only orientation (i.e. 2 dimensions). intensity information is factored out of the problem by mapping 3-dimensional (r, g, b) camera responses onto 2-dimensional chromaticities; specifically (r/b, g/b). we show that this "diagonal chromaticity space" has two important properties: first, gamut convexity is preserved and second illumination change is still described by a diagonal matrix. it follows that forsyth's algorithm can be directly applied to the recover chromaticity descriptors and from these the 3d descriptor orientations can be derived. the basic algorithm is then extended to include a maximal gamut constraint on the set of illuminants that is analogous to the gamut constraint on surface colors. the diagonal chromaticity space facilitates the expression of the illumination constraint in the algorithm. tests on real images show that the algorithm provides good color constancy.
color constancy under varying illumination. illumination is rarely constant in intensity or color throughout a scene. multiple light sources with different spectra-sun and sky, direct and interreflected light-are the norm. nonetheless, almost all color constancy algorithms assume that the spectrum of the incident illumination remains constant across the scene. we assume the converse, that illumination does vary, in developing a new algorithm for color constancy. rather than creating difficulties, varying illumination is in fact a very powerful constraint. indeed tests of our algorithm using real images of an office scene show excellent results.
colour by correlation: a simple, unifying approach to colour constancy. in this paper we consider the problem of color constancy; how given an image of a scene under an unknown illuminant can we recover an estimate of that light? rather than recovering a single estimate of the illuminant as many previous authors have done, in the first instance we recover a measure of the likelihood that each possible illuminant was the scene illuminant. we do this by correlating image colors with the colors that can occur under each of a set of possible lights. we then recover an estimate of the scene illuminant based on these likelihoods. computation is expressed and performed in a generic correlation framework which we develop in this paper. we develop a new probabilistic instantiation of this framework which delivers very good color constancy on synthetic and real images. we show that the proposed framework is rich enough to allow many existing algorithms to be expressed within it; e.g. the grey-world and gamut mapping algorithms. we explore too the relationship of these algorithms to other probabilistic and neural network approaches.
gamut constrained illuminant estimation. this paper presents a novel solution to the illuminant estimationproblem: the problem of how, given an image of ascene taken under an unknown illuminant, we can recoveran estimate of that light. the work is founded on previousgamut mapping solutions to the problem which solvefor a scene illuminant by determining the set of diagonalmappings which take image data captured under an unknownlight to a gamut of reference colours taken undera known light. unfortunately a diagonal model is not alwaysa valid model of illumination change and so previousapproaches sometimes return a null solution. in addition,previous methods are difficult to implement. we addressthese problems by recasting the problem as one ofilluminant classification: we define a prioria set of plausiblelights thus ensuring that a scene illuminant estimatewill always be found. a plausible light is represented bythe gamut of colours observable under it and the illuminantin an image is classified by determining the plausible lightwhose gamut is most consistent with the image data. weshow that this step (the main computational burden of thealgorithm) can be performed simply, quickly, and efficientlyby means of a non-negative least-squares optimisation. wereport results on a large set of real images which show thatit provides excellent illuminant estimation, outperformingprevious algorithms.
image-based rendering using image-based priors. given a set of images acquired from known viewpoints, wedescribe a method for synthesizing the image which wouldbe seen from a new viewpoint.in contrast to existing techniques,which explicity reconstruct the 3d geometry of thescene, we transform the problem to the reconstruction ofcolour rather than depth.this retains the benefits of geometricconstraints, but projects out the ambiquities in depthestimation which occur in textureless regions.on the other hand, regularization is still needed in orderto generate high-quality images.the paper's secondcontribution is to constrain the generated views to lie in thespace of images whose texture statistics are those of the inputimages.this amounts to a image-based prior on thereconstruction which regularizes the solution, yielding realisticsynthetic views.examples are given of new viewgeneration for cameras interpolated between the acquisitionviewpoints-which enables synthetic steadicam stabilizationof a sequence with a high level of realism.
fixed point probability field for complex occlusion handling. in this paper, we show that in a multi-camera context, we can effectively handle occlusions in real-time at each frame independently, even when the only available data comes from the binary output of a simple blob detector, and the number of present individuals is a priori unknown. we start from occupancy probability estimates in a top view and rely on a generative model to yield probability images to be compared with the actual input images. we then refine the estimates so that the probability images match the binary input images as well as possible. we demonstrate the quality of our results on several sequences involving complex occlusions.
camera calibration with known rotation. we address the problem of using external rotation informationwith uncalibrated video sequences. the main problemaddressed is, what is the benefit of the orientation infomationfor camera calibration? it is shown that in case ofa rotating camera the camera calibration problem is lineareven in the case that all intrinsic parameters vary. forarbitrarily moving cameras the calibration problem is alsolinear but underdetermined for the general case of varyingall intrinsic parameters. however, if certain constraints areapplied to the intrinsic parameters the camera calibrationcan be computed linearily. it is analyzed which constraintsare needed for camera calibration of freely moving cameras.furthermore we address the problem of aligning thecamera data with the rotation sensor data in time. we givean approach to align these data in case of a rotating camera.
fusion of multi-view silhouette cues using a space occupancy grid. in this paper, we investigate what can be inferred from several silhouette probability maps, in multi-camera environments. to this aim, we propose a new framework for multi-view silhouette cue fusion. this framework uses a space occupancy grid as a probabilistic 3d representation of scene contents. such a representation is of great interest for various computer vision applications in perception, or localization for instance. our main contribution is to introduce the occupancy grid concept, popular in the robotics community, for multi-camera environments. the idea is to consider each camera pixel as a statistical occupancy sensor. all pixel observations are then used jointly to infer where, and how likely, matter is present in the scene. as our results illustrate, this simple model has various advantages. most sources of uncertainty are explicitly modeled, and no premature decisions about pixel labeling occur, thus preserving pixel knowledge. consequently, optimal scene object localization, and robust volume reconstruction, can be achieved, with no constraint on camera placement and object visibility. in addition, this representation allows to improve silhouette extraction in images.
robust structure from motion and identified dynamics. this paper addresses robust recovery of structure and motion for rigid bodies in video sequences. for small interframe motion, feature appearance is commonly estimated according to the previous frame. however, in the case of occlusion or corrupt frames, the small inter-frame motion model fails. in this paper, we propose to use robustidentification techniques to estimate the motion dynamics based on a set of previous frames. these dynamics are then recursively used to robustly estimate object structure and motion and to predict the object appearance in future frames. results are tested for 3d reconstructions of rigid bodies in real and synthetic image sequences.
svm-based nonparametric discriminant analysis, an application to face detection. detecting the dominant normal directions to the decisionsurface is an established technique for feature selectionin high dimensional classification problems. several approacheshave been proposed to render this strategy moreamenable to practice, but they still show a number of importantshortcomings from a pragmatic point of view. this paperintroduces a novel such approach, which combines thenormal directions idea with support vector machine classifiers.the two make a natural and powerful match, as svsare located nearby, and fully describe the decision surfaces.the approach can be included elegantly into the training ofperformant classifiers from extensive datasets. the potentialis corroborated by experiments, both on synthetic andreal data, the latter on a face detection experiment. in thisexperiment we demonstrate how our approach can lead to asignificant reduction of cpu-time, with neglectable loss ofclassification performance.
bayesian decision theory, the maximum local mass estimate, and color constancy. vision algorithms are often developed in a bayesian framework. two estimators are commonly used: maximum a posteriori (map), and minimum mean squared error (mmse). we argue that neither is appropriate for perception problems. the map estimator makes insufficient use of structure in the posterior probability. the squared error penalty of the mmse estimator does not reflect typical penalties. we describe a new estimator, which we call maximum local mass (mlm) [10, 26, 65], which integrates the local probability density. the mlm method is sensitive to local structure of the posterior probability, which map is not. the new method uses an optimality criterion that is appropriate for perception tasks: it finds the most probable approximately correct answer. for the case of low observation noise, we provide an efficient approximation. we apply this new estimator to color constancy. an unknown illuminant falls on surfaces of unknown colors. we seek to estimate both the illuminant spectrum and the surface spectra from photosensor responses which depend on the product of the unknown spectra. in simulations, we show that the mlm method performs better than the map estimator, and better than two standard color constancy algorithms. the mlm method may prove useful in other vision problems as well.
learning low-level vision. we show a learning-based method for low-level vision problems{estimating scenes from images. we generate a synthetic world of scenes and their corresponding rendered images. we model that world with a markov network, learning the network parameters from the examples. bayesian belief propagation allows us to efficiently find a local maximum of the posterior probability for the scene, given the image. we call this approach vista{vision by image/scene training.we apply vista to the "super-resolution" problem (estimating high frequency details from a low-resolution image), showing good results. for the motion estimation problem, we show figure/ground discrimination, solution of the aperture problem, and filling-in arising from application of the same probabilistic machinery.
transformed component analysis: joint estimation of spatial transformations and image components. a simple, effective way to model images is to represent each input pattern by a linear combination of "component" vectors, where the amplitudes of the vectors are modulated to match the input. this approach includes principal component analysis, independent component analysis and factor analysis. in practice, images are subjected to randomly selected transformations of a known nature, such as translation and rotation. direct use of the above methods will lead to severely blurred components that tend to ignore the more interesting and useful structure. in previous work, we introduced a clustering algorithm that is invariant to transformations [1].in this paper, we propose a method called transformed component analysis, which incorporates a discrete, hidden variable that accounts for transformations and uses the expectation maximization algorithm to jointly extract components and normalize for transformations. we illustrate the algorithm using a shading problem, facial expression modeling and written digit recognition.
integrating representative and discriminative models for object category detection. category detection is a lively area of research. while categorization algorithms tend to agree in using local descriptors, they differ in the choice of the classifier, with some using generative models and others discriminative approaches. this paper presents a method for object category detection which integrates a generative model with a discriminative classifier. for each object category, we generate an appearance codebook, which becomes a common vocabulary for the generative and discriminative methods. given a query image, the generative part of the algorithm finds a set of hypotheses and estimates their support in location and scale. then, the discriminative part verifies each hypothesis on the same codebook activations. the new algorithm exploits the strengths of both original methods, minimizing their weaknesses. experiments on several databases show that our new approach performs better than its building blocks taken separately. moreover, experiments on two challenging multi-scale databases show that our new algorithm outperforms previously reported results.
efficient block noise removal based on nonlinear manifolds. the problem of block noise removal is considered. it is assumed that the original image is on or close to a sub-space of admissible images in the form of a low dimensional nonlinear manifold. we propose to use a close variant of the total variation regularizer for measuring block noise. based on this noise measure, we present an effective approach that reconstructs the original image in the presence of block noise. our main computational task is the solution of a quadratic programming problem, for which we propose a very efficient interior point method. the effectiveness and efficiency of our approach is demonstrated by an example.
polymorphic grouping for image segmentation. the paper describes a new approach to image segmentation. it accepts the inherent deficiencies occuring when extracting low-level features and when dealing with the complexity of real scenes. image segmentation therefore is understood as deriving a rich symbolic description useful for tasks such as stereo or object recognition in outdoor scenes. the approach is based on a polymorphic scheme for simultaneously extracting points, lines and segments in a topologically consistent manner, together with their mutual relations derived from the feature adjacency graph (fag) thereby performing several grouping steps which gradually use more and more specific domain knowledge to achieve an optimal image description. the heart of the approach is (1) a detailed analysis of the fag and (2) a robust estimation for validating the found geometric hypotheses. the analysis of the fag, derived from the exoskeleton of the features, allows to detect inconsistencies of the extracted features with the ideal image model, a cell-complex. the fag is used for finding hypotheses about incidence relations and geometric hypotheses, such as collinearity or parallelity, also between non-neighbored points and lines. the m-type robust estimation is used for simultaneously eliminating wrong hypotheses on geometric relationships. it uses a new argument for the weighting function.
combining color and geometry for the active, visual recognition of shadows. shadows are a frequent occurrence, but they cannot be infallibly recognized until a scene's geometry and lighting are known. we present a number of cues which together strongly suggest the identification of a shadow and which can be examined with low cost. the techniques are: a color image segmentation method that recovers single material surfaces as single image regions irregardless of the surface partially in shadow, a method to recover the penumbra and umbra of shadow; a method for determining whether some object could be obstructing a light source. the last cue requires the examination of well understood shadows in the scene. our observer is equipped with an extendable probe for casting its own shadows. actively obtained shadows allow the observer to experimentally determine the location of the light sources in the scene. the system has been tested both indoors and out.
texture segmentation by multiscale aggregation of filter responses and shape elements. texture segmentation is a difficult problem, as is apparentfrom camouflage pictures. a textured region can containtexture elements of various sizes, each of which can itselfbe textured. we approach this problem using a bottom-upaggregation framework that combines structural characteristicsof texture elements with filter responses. our processadaptively identifies the shape of texture elements and characterizethem by their size, aspect ratio, orientation, brightness,etc., and then uses various statistics of these propertiesto distinguish between different textures. at the sametime our process uses the statistics of filter responses tocharacterize textures. in our process the shape measuresand the filter responses crosstalk extensively. in addition,a top-down cleaning process is applied to avoid mixing thestatistics of neighboring segments. we tested our algorithmon real images and demonstrate that it can accurately segmentregions that contain challenging textures.
3d reconstruction with projective octrees and epipolar geometry. in this paper, the problem of generating a 3d octree-like structure with the help of epipolar geometry within a projective framework is addressed. after a brief introduction on the basics of octrees and epipolar geometry, the new concept called "projective octree" is introduced together with an algorithm for building this projective structure. finally, some results of the implementations are presented in the last section together with the conclusions and future work.
surface orientation and curvature from differential texture distortion. a unified differential geometric framework for estimation of local surface shape and orientation from projective texture distortion is proposed, based on a differential version of the texture stationarity assumption introduced by malik and rosenholtz. this framework allows the information content of the gradient of any texture descriptor defined in a local coordinate frame to be characterized in a very compact form. the analysis encompasses both full affine texture descriptors and the classical "texture gradients". for estimation of local surface orientation and curvature from uncertain observations of affine texture distortion, the proposed framework allows the dimensionality of the search space to be reduced from five to one.
when does a camera see rain? rain produces sharp intensity fluctuations in images and videos, which degrade the performance of outdoor vision systems. these intensity fluctuations depend on various factors, such as the camera parameters, the properties of rain, and the brightness of the scene. we show that the properties of rain ¿ its small drop size, high velocity, and low density ¿ make its visibility strongly dependent on camera parameters such as exposure time and depth of field. we show that these parameters can be selected so as to reduce or even remove the effects of rain without altering the appearance of the scene. conversely, the parameters of a camera can also be set to enhance the visual effects of rain. this can be used to develop an inexpensive and portable camera-based rain gauge that provides instantaneous rain rate measurements. the proposed methods serve to make vision algorithms more robust to rain without any necessity for post-processing. in addition, they can be used to control the visual effects of rain during the filming of movies.
accurate motion flow estimation with discontinuities. we address the problem of motion flow estimation for a scene with multiple moving objects, observed from a possibly moving camera. we take as input a (possibly sparse) noisy velocity field, as obtained from local matching, produce a set of motion boundaries, and identify pixels with different velocities in overlapping layers. for a fixed observer, these overlapping layers capture occlusion information. for a moving observer, further processing is required to segment independent objects and infer structure. unlike previous approaches, which generate layers by iteratively fitting data to a set of predefined parameters, we instead find boundaries first, then infer regions and address occlusion overlap relationships. all computational steps use a common framework of tensors to represent velocity information, together with saliency (confidence), and uncertainty. communication between sites is performed by convolution-like tensor voting. the scheme is non-iterative, and the only free parameter is the scale, related to neighborhood size. we illustrate the approach with results obtained from synthetic sequences and from real images. the quantitative results compare favorably with those of other methods, especially in the presence of occlusion
parameterized image varieties: a novel approach to the analysis and synthesis of image sequences. this paper addresses the problem of characterizing the space formed by all images of a rigid set of n points observed by a weak perspective or paraperspective camera. by taking explicitly into account the euclidean constraints associated with calibrated cameras, we showthat this space is a six-dimensional variety embedded in ir2n, and parameterize it using the image positions of three reference points. this parameterization is constructed vialinear least squares from point correspondences established across a sequence of images, and it is used to synthesize new pictures without any explicit three-dimensional model. degenerate scene and camera configurations are analyzed, and experiments with real image sequences are presented.
mean shift based clustering in high dimensions: a texture classification example. feature space analysis is the main module in many computer vision tasks. the most popular technique, k-means clustering, however, has two inherent limitations: the clusters are constrained to be spherically symmetric and their number has to be known a priori. in nonparametric clustering methods, like the one based on mean shift, these limitations are eliminated but the amount of computation becomes prohibitively large as the dimension of the space increases. we exploit a recently proposed approximation technique, locality-sensitive hashing (lsh), to reduce the computational complexity of adaptive mean shift. in our implementation of lsh the optimal parameters of the data structure are determined by a pilot learning procedure, and the partitions are data driven. as an application, the performance of mode and k-means based textons are compared in a texture classification study.
incorporating the torrance and sparrow model of reflectance in uncalibrated photometric stereo. under the lambertian reflectance model, uncalibrated photometricstereo with unknown light sources is inherentlyambiguous. in this paper, we consider the use of a moregeneral reflectance model, namely the torrance and sparrowmodel, in uncalibrated photometric stereo. we demonstratethat this can not only resolve the ambiguity when thelight sources are unknown, but can also result in more accuratesurface reconstructions and can capture the reflectanceproperties of a large number of non-lambertian surfaces.our method uses single light source images with unknownlighting and no knowledge about the parameters of the reflectancemodel. it can recover the 3-d shape of surfaces(up to the binary convex/concave ambiguity) together withtheir reflectance properties. we have successfully tested ouralgorithm on a variety of non-lambertian surfaces demonstratingthe effectiveness of our approach. in the case ofhuman faces, the estimated skin reflectance has been shownto closely resemble the measured skin reflectance reportedin the literature. we also demonstrate improved recognitionresults on 4050 images of 10 faces with variable lightingand viewpoint when the synthetic image-based representationsof the faces are generated using the surface reconstructionsand reflectance properties recovered while assumingthe extended reflectance model.
modeling bayesian estimation for deformable contours. a novel trainable snake model, called eigensnake, is presented in the bayesian framework. in the eigensnake, prior knowledge of a specific object shape, such as that of face outlines and facial features, is derived from a training set of the shape and incorporated into a bayesian snake model in the form of the prior distribution. further, a "shape space", which is constructed on the basis of a set of eigenvectors obtained from principle component analysis, is used to restrict and stabilize the search for the optimal solution. the effectiveness is demonstrated by experiments, which shows that the eigensnake produces more reliable and accurate results than existing models.
fragmentation in the vision of scenes. natural images are highly structured in their spatial configuration. where one would expect a different spatial distribution for every image, as each image has a different spatiallay out, we show that the spatial statistics of recorded images can be explained by a single process of sequential fragmentation. the observation by a resolution limited sensory system turns out to have a profound influence on the observed statistics of natural images. the power-law and normal distribution represent the extreme cases of sequential fragmentation. between these two extremes, spatial detail statistics deform from power-law to normal through the weibull type distribution as receptive field size increases relative to image detail size.
reflectance-based classification of color edges. we aim at using color information to classify the physicalnature of edges in video. to achieve physics-based edgeclassification, we first propose a novel approach to coloredge detection by automatic noise-adaptive thresholdingderived from sensor noise analysis. then, we present a taxonomyon color edge types. as a result, a parameter-freeedge classifier is obtained labeling color transitions intoone of the following types: (1) shadow-geometry, (2) highlightedges, (3) material edges. the proposed method isempirically verified on images showing complex real worldscenes.
image indexing using composite color and shape invariant features. new sets of color models are proposed for object recognition invariant to a change in view point, object geometry and illumination. further, computational methods are presented to combine color and shape invariants to produce a high-dimensional invariant feature set for discriminatory object recognition.experiments on a database of 500 images show that object recognition based on composite color and shape invariant features provides excellent recognition accuracy. furthermore, object recognition based on color invariants provides very high recognition accuracy whereas object recognition based entirely on shape invariants yields very poor discriminative power.the image database and the performance of the recognition scheme can be experienced within pictoseek on-line as part of the zomax system at: http://www.wins.uva.nl/research/isis/zomax/.
mirrors in motion: epipolar geometry and motion estimation. in this paper we consider the images taken from pairs ofparabolic catadioptric cameras separated by discrete motions.despite the nonlinearity of the projection model, theepipolar geometry arising from such a system, like the perspectivecase, can be encoded in a bilinear form, the catadioptricfundamental matrix. we show that all such matriceshave equal lorentzian singular values, and they definea nine-dimensional manifold in the space of 4 × 4 matrices.furthermore, this manifold can be identified with a quotientof two lie groups. we present a method to estimate a matrixin this space, so as to obtain an estimate of the motion.we show that the estimation procedures are robust to modestdeviations from the ideal assumptions.
optical flow and deformable objects. when a plane undergoes a deformation that can be represented by a planar linear vector field, the projected vector field on the image plane of an optical device is at most quadratic. this 2d motion field has one singular point, with eigenvalues identical to those of the singular point describing the deformation. as a consequence, the nature of the singular point of the deformation is a projective invariant. when the plane moves and experiences a linear deformation at the same time, the associated 2d motion field is still quadratic with at most 3 singular points. in the case of a normal rototranslation, i.e. when the angular velocity is normal to the plane, and of a linear deformation, the 2d motion field has at most one singular point and substantial information on the rigid motion and on the deformation can be recovered from it. experiments with simulated deformations and real deformable objects show that the proposed analysis can provide accurate results and information on more general 3d deformations.
on the local form and transitions of symmetry sets, medial axes, and shocks. in this paper we explore the local geometry of the medial axis (ma) and shocks (sh), and their structural changes under deformations, by viewing these symmetries as subsets of the symmetry set (ss) and present two results. first, we establish that the local form of the medial axis must generically be one of three cases, which we denote by the a notation explained below (here, it merely serves as a reference to sections of the paper): endpoints (a3), interior points (a12), and junctions (a13). the local form of shocks is a sub-classification of these points into six types. second, we address the (classical) instabilities of the ma, i.e., abrupt changes in the representation with a slight changes in shape, as when a new branch appears with slight protrusion. the identification of these &lsquo;transitions&rsquo; is clearly crucial in robust object recognition. we show that for the medial axis only two such instabilities are generically possible: (i) when four branches come together (a14), and (ii) when a new branch grows out of an existing one (a1a3). similarly, there are six cases of shock instabilities, derived as sub-classifications of the ma instabilities. we give an explicit example of a dent forming in an ellipse where many of the transitions described in the paper can be seen to appear.
affine invariant medial axis and skew symmetry. affine invariant medial axes and symmetry sets of planar shapes are intr oduced and studied in this paper. two different approaches are presented. the first one is based on affine invariant distances, and defines the symmetry set, a set containing the medial axis, as the closure of the locus of points on (at least) two affine normals and affine-equidistant from the corresponding points on the curve. the second approach is based on a affine bitangent conics. in this case the symmetry set is defined as the closure of the locus of centers of conics with (at least) three-point contact with two or more distinct points on the curve. this is equivalent to conic and curve having, at those points, the same affine tangent, or the same euclidean tangent and curvature. although the two analogous definitions for the classical euclidean symmetry set (medial axis) are equivalent, this is not the case for the affine group. we then show how to use the symmetry set to detect affine skew symmetry, proving that the contact based symmetry set is a straight line if and only if the given shape is the affine transformation of a symmetric object.
on the use of marginal statistics of subband images. a commonly used representation of a visual pattern is the set of marginal probability distributions of the output of a bank of filters (gaussian, laplacian, gabor etc...). this representation has been used effectively for a variety of vision tasks including texture classification, texture synthesis, object detection and image retrieval. this paper examines the ability of this representation to discriminate between an arbitrary pair of visual stimuli. examples of patterns are derived that provably possess the same marginal statistical properties, yet are "visually distinct." these results suggest the need for either employing a large and diverse filter bank or incorporating joint statistics in order to represent a large class of visual patterns.
ego-motion and omnidirectional cameras. recent research in image sensors has produced cameras with very large fields of view. an area of computer vision research which will benefit from this technology is the computation of camera motion (ego-motion) from a sequence of images. traditional cameras suffer from the problem that the direction of translation may lie outside of the field of view, making the computation of camera motion sensitive to noise. in this paper, we present a method for the recovery of ego-motion using omnidirectional cameras. noting the relationship between spherical projection and wide-angle imaging devices, we propose mapping the image velocity vectors to a sphere, using the jacobian of the transformation between the projection model of the camera and spherical projection. once the velocity vectors are mapped to a sphere, we show how existing ego-motion algorithms can be applied and present some experimental results. these results demonstrate the ability to compute ego-motion with omnidirectional cameras.
registration of multiple point sets using the em algorithm. in this paper we address the problem of global registration between multiple dimensional point patterns with a given correspondence. the actual overlapping is not necessarily between pairs. instead, it can be between any number of patterns. it is assumed that each pattern is a portion of an image of an unobserved object under a distinct rigid transformation. we derive an iterative solution for the problem of global registration of the patterns in order to reconstruct the original object.our solution is based on the em algorithm and it generalizes the well known solutions for the two-pattern case. we also suggest a very efficient method to implement the proposed algorithm. experimental results demonstrate the improved performance of the proposed method.
an efficient image similarity measure based on approximations of kl-divergence between two gaussian mixtures. in this work we present two new methods for approximating the kullback-liebler (kl) divergence between two mixtures of gaussians. the first method is based on matching between the gaussian elements of the two gaussian mixture densities. the second method is based on the unscented transform. the proposed methods are utilized for image retrieval tasks. continuous probabilistic image modeling based on mixtures of gaussians together with kl measure for image similarity, can be used for image retrieval tasks with remarkable performance. the efficiency and the performance of the kl approximation methods proposed are demonstrated on both simulated data and real image datasets. the experimental results indicate that our proposed approximations outperform previously suggested methods.
vignette and exposure calibration and compensation. we discuss calibration and removal of "vignetting" (radial falloff) and exposure (gain) variations from sequences of images. unique solutions for vignetting, exposure and scene radiances are possible when the response curve is known. when the response curve is unknown, an exponential ambiguity prevents us from recovering these parameters uniquely. however, the vignetting and exposure variations can nonetheless be removed from the images without resolving this ambiguity. applications include panoramic image mosaics, photometry for material reconstruction, image-based rendering, and preprocessing for correlation-based vision algorithms.
shape and spatially-varying brdfs from photometric stereo. this paper describes a photometric stereo method designed for surfaces with spatially-varying brdfs, including surfaces with both varying diffuse and specular properties. our method builds on the observation that most objects are composed of a small number of fundamental materials. this approach recovers not only the shape but also material brdfs and weight maps, yielding compelling results for a wide variety of objects. we also show examples of interactive lighting and editing operations made possible by our method.
a semi-supervised framework for mapping data to the intrinsic manifold. this paper presents a novel scheme for manifold learning. different from the previous work reducing data to euclidean space which cannot handle the looped manifold well, we map the scattered data to its intrinsic parameter manifold by semi-supervised learning. given a set of partially labeled points, the map to a specified parameter manifold is computed by an iterative neighborhood average method called anchor points diffusion procedure (apd). we explore this idea on the most frequently used close-formed manifolds, stiefel manifolds whose special cases include hyper sphere and orthogonal group. the experiments show that apd can recover the underlying intrinsic parameters of points on scattered data manifold successfully.
recognition of group activities using dynamic probabilistic networks. dynamic probabilistic networks (dpns) are exploitedfor modelling the temporal relationships among a set of differentobject temporal events in the scene for a coherentand robust scene-level behaviour interpretation. in particular,we develop a dynamically multi-linked hidden markovmodel (dml-hmm) to interpret group activities involvingmultiple objects captured in an outdoor scene. the model isbased on the discovery of salient dynamic interlinks amongmultiple temporal events using dpns. object temporalevents are detected and labelled using gaussian mixturemodels with automatic model order selection. a dml-hmmis built using schwarz's bayesian information criterionbased factorisation resulting in its topology being intrinsicallydetermined by the underlying causality and temporalorder among different object events. our experimentsdemonstrate that its performance on modelling group activitiesin a noisy outdoor scene is superior compared to thatof a multi-observation hidden markov model (mohmm),a parallel hidden markov model (pahmm) and a coupledhidden markov model (chmm).
fast stereo matching using reliability-based dynamic programming and consistency constraints. a method for solving binocular and multi-view stereomatching problems is presented in this paper. a weakconsistency constraint is proposed, which expresses thevisibility constraint in the image space. it can be provedthat the weak consistency constraint holds for scenes thatcan be represented by a set of 3d points. as well, alsoproposed is a new reliability measure for dynamicprogramming techniques, which evaluates the reliability ofa given match. a novel reliability-based dynamicprogramming algorithm is derived accordingly, which canselectively assign disparity values to pixels when thereliabilities of the corresponding matches exceed a giventhreshold. consistency constraints and the new reliability-baseddynamic programming algorithm can be combinedin an iterative approach. the experimental results showthat the iterative approach can produce dense (60~90%)and reliable (total error rate of 0.1~1.1%) matching forbinocular stereo datasets. it can also generate promisingdisparity maps for trinocular and multi-view stereodatasets.
applying the information bottleneck principle to unsupervised clustering of discrete and continuous image representations. in this paper we present a method for unsupervised clustering of image databases. the method is based on a recently introduced information-theoretic principle, the information bottleneck (ib) principle. image archives are clustered such that the mutual information between the clusters and the image content is maximally preserved. the ib principle is applied to both discrete and continuous image representations, using discrete image histograms and probabilistic continuous image modeling based on mixture of gaussian densities, respectively. experimental results demonstrate the performance of the proposed method forimage clustering on a large image database. several clustering algorithms derived from the ib principle are explored and compared.
recovery of epipolar geometry as a manifold fitting problem. the introduction of the joint image manifold allows to treatthe problem of recovering camera motion and epipolar geometryas the problem of fitting a manifold to the data measuredin a stereo pair. the manifold has a singularity andboundary, therefore care must be taken when fitting it.this paper reviews the notion of joint image manifold,and how previous motion recovery methods can be viewedin its context, and then offers a new fitting method, whichimproves upon previous results, especially when the extentof the data and/or the motion are small.
the pyramid match kernel: discriminative classification with sets of image features. discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. kernel-based classification methods can learn complex decision boundaries, but a kernel over unordered set inputs must somehow solve for correspondences ¿ generally a computationally expensive task that becomes impractical for large set sizes. we present a new fast kernel function which maps unordered feature sets to multi-resolution histograms and computes a weighted histogram intersection in this space. this "pyramid match" computation is linear in the number of features, and it implicitly finds correspondences based on the finest resolution histogram cell where a matched pair first appears. since the kernel does not penalize the presence of extra features, it is robust to clutter. we show the kernel function is positive-definite, making it valid for use in learning algorithms whose optimal solutions are guaranteed only for mercer kernels. we demonstrate our algorithm on object recognition tasks and show it to be accurate and dramatically faster than current approaches.
inferring 3d structure with a statistical image-based shape model. we present an image-based approach to infer 3d structureparameters using a probabilistic "shape+structure" model.the 3d shape of an object class is represented by setsof contours from silhouette views simultaneously observedfrom multiple calibrated cameras, while structural featuresof interest on the object are denoted by a number of 3d locations.a prior density over the multi-view shape and correspondingstructure is constructed with a mixture of probabilisticprincipal components analyzers. given a novelset of contours, we infer the unknown structure parametersfrom the new shape's bayesian reconstruction. modelmatching and parameter inference are done entirely in theimage domain and require no explicit 3d construction. ourshape model enables accurate estimation of structure despitesegmentation errors or missing views in the input silhouettes,and it works even with only a single input view.using a training set of thousands of pedestrian images generatedfrom a synthetic model, we can accurately infer the3d locations of 19 joints on the body based on observedsilhouette contours from real images.
probabilistic bilinear models for appearance-based vision. we present a probabilistic approach to learning objectrepresentations based on the "content and style" bilineargenerative model of tenenbaum and freeman. in contrastto their earlier svd-based approach, our approach modelsimages using particle filters. we maintain separate particlefilters to represent the content and style spaces, allowing usto define arbitrary weighting functions over the particles tohelp estimate the content/style densities. we combine thisapproach with a new em-based method for learning basisvectors that describe content-style mixing. using a particle-basedrepresentation permits good reconstruction despitereduced dimensionality, and increases storage capacity andcomputational efficiency. we describe how learning the distributionsusing particle filters allows us to efficiently computea probabilistic "novelty" term. our example applicationconsiders a dataset of faces under different lightingconditions. the system classifies faces of people it has seenbefore, and can identify previously unseen faces as new content.using a probabilistic definition of novelty in conjunctionwith learning content-style separability provides a crucialbuilding block for designing real-world, real-time objectrecognition systems.
towards a mathematical theory of primal sketch and sketchability. in this paper, we present a mathematical theory for marr'sprimal sketch. we first conduct a theoretical study ofthe descriptive markov random field model and the generativewavelet/sparse coding model from the perspectiveof entropy and complexity. the competition between thetwo types of models defines the concept of "sketchability",which divides image into texture and geometry. we then proposea primal sketch model that integrates the two modelsand, in addition, a gestalt field model for spatial organization.we also propose a sketching pursuit process that coordinatesthe competition between two pursuit algorithms:the matching pursuit [8] and the filter pursuit [12], that seekto explain the image by bases and filters respectively. themodel can be used to learn a dictionary of image primitives,or textons in julesz's language, for natural images.the primal sketch model is not only parsimonious for imagerepresentation, but produces meaningful sketches overa large number of generic images.
face surveillance. most of the research on face recognition addresses the match problem and it assumes a closed universe where there is no need for a reject ('false positive') option. the surveillance problem is addressed indirectly, if at all, through the match problem, where the size of the gallery rather than that of the probe set is very large. this paper addresses the proper surveillance problem where the size of the probe ('unknown image') set vs gallery ('known image') set is 450 vs 50 frontal images. we developed robust face id verification ('classification') and retrieval schemes based on hybrid classifiers and showed their feasibility using the feret face database. the hybrid classifier architecture consists of an ensemble of connectionist networks - radial basis functions (rbf) and inductive decision trees (dt). experimental results prove the feasibility of our approach and yield 97% accuracy using the probe and gallery sets specified above.
shading primitives: finding folds and shallow grooves. diffuse interreflections cause effects that make current theories of shape from shading unsatisfactory. we show that distant radiating surfaces produce radiosity effects at low spatial frequencies. this means that, if a shading pattern has a small region of support, unseen surfaces in the environment can only produce effects that vary slowly over the support region. it is therefore relatively easy to construct matching processes for such patterns that are robustto interreflections. we call regions with these patterns "shading primitives."folds and grooves on surfaces provide two examples of shading primitives; the shading pattern is relatively independent of surface shape at a fold or a groove, and the pattern is localised. we show that the pattern of shading can be predicted accurately by a simple model, and derive a matching process from this model. both groove and fold matchers are shown to work well on images of real scenes.
calibration-free visual control using projective invariance. much of the previous work on hand-eye coordination has emphasized the reconstructive aspects of vision. recently, techniques that avoid explicit reconstruction by placing visual feedback into a control loop have been developed. when properly defined, these methods lead to calibration insensitive hand-eye coordination. recent work on projective geometry as applied to vision is used to extend this paradigm in two ways. first, it is shown how results from projective geometry can be used to perform online calibration. second, results on projective invariance are used to define setpoints for visual control that are independent of viewing location. these ideas are illustrated through a number of examples and have been tested on an implemented system.
degenerate cases and closed-form solutions for camera calibration with one-dimensional objects. camera calibration with one-dimensional objects is based on an algebraic constraint on the image of the absolute conic. we will give an alternative derivation to this constraint, allowing a geometrical interpretation. from this we derive the degenerate cases, or critical motions, where the calibration algorithm will fail. we also show that constraints on the intrinsic parameters lead to simplified closed-form solutions and a reduced set of critical motions. a simulation and a real data experiment is performed to evaluate the accuracy of the calibration result for motions close to being critical.
on-line density-based appearance modeling for object tracking. object tracking is a challenging problems in real-time computer vision due to variations of lighting condition, pose, scale, and view-point over time. however, it is exceptionally difficult to model appearance with respect to all of those variations in advance; instead, on-line update algorithms are employed to adapt to these changes. we present a new on-line appearance modeling technique which is based on sequential density approximation. this technique provides accurate and compact representations using gaussian mixtures, in which the number of gaussians is automatically determined. this procedure is performed in linear time at each time step, which we prove by amortized analysis. features for each pixel and rectangular region are modeled together by the proposed sequential density approximation algorithm, and the target model is updated in scale robustly. we show the performance of our method by simulations and tracking in natural videos.
on optimizing template matching via performance characterization. template matching is a fundamental operator in computer vision and is widely used in feature tracking, motion estimation, image alignment, and mosaicing. under a certain parameterized warping model, the traditional template matching algorithm estimates the geometric warp parameters that minimize the ssd between the target and a warped template. the performance of the template matching can be characterized by deriving the distribution of warp parameter estimate as a function of the ideal template, the ideal warp parameters, and a given noise or perturbation model. in this paper, we assume a discretization of the warp parameter space and derive the theoretical expression for the probability mass function (pmf) of the parameter estimate. as the pmf is also a function of the template size, we can optimize the choice of the template or block size by determining the template/block size that gives the estimate with minimum entropy. experimental results illustrate the correctness of the theory. an experiment involving feature point tracking in face video is shown to illustrate the robustness of the algorithm in a real-world problem.
bottom-up/top-down image parsing by attribute graph grammar. in this paper, we present an attribute graph grammar for image parsing on scenes with man-made objects, such as buildings, hallways, kitchens, and living rooms. we choose one class of primitives ¿ 3d planar rectangles projected on images, and six graph grammar production rules. each production rule not only expands a node into its components, but also includes a number of equations that constrain the attributes of a parent node and those of its children. thus our graph grammar is context sensitive. the grammar rules are used recursively to produce a large number of objects and patterns in images and thus the whole graph grammar is a type of generative model. the inference algorithm integrates bottom-up rectangle detection which activates top-down prediction using the grammar rules. the final results are validated in a bayesian framework. the output of the inference is a hierarchical parsing graph with objects, surfaces, rectangles, and their spatial relations. in the inference, the acceptance of a grammar rule means a recognition of an object, and actions are taken to pass the attributes between a node and its parent through the constraint equations associated with this production rule. when an attribute is passed from a child node to a parent node, it is called bottom-up, and the opposite is called top-down.
determining reflectance and light position from a single image without distant illumination assumption. several techniques have been developed for recovering reflectance properties of real surfaces under unknown illumination conditions. however, in most cases, those techniques assume that the light sources are located at inifinity,which cannot be applied to, for example, photometric modeling of indoor environments. in this paper, we propose two methods to estimate the surface reflectance property of an object, as well as the position of a light source from a single image without the distant illumination assumption. given a color image of an object with specular reflection as an input, the first method estimates the light source position by fitting to the lambertian diffuse component, while separating the specular and diffuse components by using an iterative relaxation scheme. moreover, we extend the above method by using a single specular image as an input, thus removing its constraints on the diffuse reflectance property and the number of light sources. this method simultaneously recovers the reflectance properties and the light source positions by optimizing the linearity of a log-transformed torrance-sparrow model. by estimating the object's reflectance property and the light source position, we can freely generate synthetic images of the target object under arbitrary source directions and source-surface distances.
multiple light sources and reflectance property estimation based on a mixture of spherical distributions. in this paper, we propose a new method for simultaneously estimating the illumination of the scene and the reflectanceproperty of the object from a single image. we assume that the illumination consists of multiple point sources and the shape of the object is known. unlike previous methods, we will recover not only the direction and intensity of the light sources, but also the number of light sources and the specular reflection parameter of the object. first, we represent the illumination on the surface of a unit sphere as a finite mixture of von mises-fisher distributions by deriving a spherical specular reflection model. next, we estimate this mixture and the number of distributions. finally, using this result as initial estimates, we refine the estimates using the original specular reflection model. we can use the results to render the object under novel lighting conditions.
a linear method for reconstruction from lines and points. discusses the basic role of the trifocal tensor in scene reconstruction. this 3/spl times/3/spl times/3 tensor plays a role in the analysis of scenes from three views analogous to the role played by the fundamental matrix in the two-view case. in particular, the trifocal tensor maybe computed by a linear algorithm from a set of 13 line correspondences in three views. it is further shown in this paper to be essentially identical to a set of coefficients introduced by shashua (1994) to effect point transfer in the three-view case. this observation means that the 13-line algorithm may be extended to allow for the computation of the trifocal tensor given any mixture of sufficiently many line and point correspondences. from the trifocal tensor, the camera image matrices may be computed, and the scene may be reconstructed. for unrelated uncalibrated cameras, this reconstruction is unique up to projectivity. thus, projective reconstruction of a set of lines and points may be reconstructed linearly from three views.
in defence of the 8-point algorithm. the fundamental matrix is a basic tool in the analysis of scenes taken with two uncalibrated cameras, and the 8 point algorithm is a frequently cited method for computing the fundamental matrix from a set of 8 or more point matches. it has the advantage of simplicity of implementation. the prevailing view is, however, that it is extremely susceptible to noise and hence virtually useless for most purposes. the paper challenges that view, by showing that by preceding the algorithm with a very simple normalization (translation and scaling) of the coordinates of the matched points, results are obtained comparable with the best iterative algorithms. this improved performance is justified by theory and verified by extensive experiments on real images.
parameter-free radial distortion correction with centre of distortion estimation. we propose a method of simultaneously calibrating the radial distortion function of a camera alongwith the other internal calibration parameters. the method relies on the use of a planar (or alternatively non-planar) calibration grid, which is captured in several images. in this way, the determination of the radial distortion is an easy add-on to the popular calibration method proposed by zhang [17]. the method is entirely non-iterative, and hence is extremely rapid and immune from the problem of local minima. our method determines the radial distortion in a parameter-free way, not relying on any particular radial distortion model. this makes it applicable to a large range of cameras from narrow-angle to fish-eye lenses. the method also computes the centre of radial distortion, which we argue is important in obtaining optimal results. experiments show that this point may be significantly displaced from the centre of the image, or the principal point of the camera.
photo-consistent 3d fire by flame-sheet decomposition. this paper considers the problem of reconstructing visuallyrealistic 3d models of fire from a very small setof simultaneous views (even two). by modeling fire as asemi-transparent 3d density field, we show that fire reconstructionis equivalent to a severely under-constrained computerizedtomography problem, for which traditional methodsbreak down. our approach is based on the observationthat every pair of photographs of a semi-transparentscene defines a unique density field, called a flame sheet,that (1) concentrates all its density on one connected, semi-transparentsurface, (2) reproduces the two photos exactly,and (3) is the most spatially-coherent density field that doesso. from this observation, we reduce fire reconstruction tothe convex combination of sheet-like density fields, each ofwhich is derived from the flame sheet of two input photos.experimental results suggest that this method enables high-qualityview extrapolation without over-fitting artifacts.
segmented shape descriptions from 3-view stereo. we address the recovery of segmented, 3-d descriptions of an object from intensity images. we use three views of an object from slightly different viewpoints as our input. for each image we extract a hierarchy of groups based on proximity, parallelism and symmetry in a robust manner. the groups in the three images are matched by computing the epipolar geometry. for each set of matched groups from the three images, we then label the contours of the groups as "true" or "limb" edges. using the information about groups, the label associated with their contours and projective properties of subclasses of generalized cylinders, we infer the 3-d structure of these groups. the proposed method not only allows robust shape recovery but also produces segmented parts. our approach can also deal with groups generated as a result of texture or shadows on the object. we present results on real images of moderately complex objects.
statistical background subtraction for a mobile observer. statistical background modelling and subtraction has proved to be a popular and effective class of algorithms for segmenting independently moving foreground objects outfrom a static background, without requiring any a priori information of the properties of foreground objects. this paper presents two contributions on this topic, aimed towards robotics where an active head is mounted on a mobile vehicle. in periods when the vehicle's wheels are not driven, camera translation is virtually zero, and background subtraction techniques are applicable. parts of this work are also highly relevant to surveillance and video conferencing. the first part of the paper presents an efficient probabilistic framework for when the camera pans and tilts. a unified approach is developed for handling various sources of error, including motion blur, sub-pixel camera motion, mixed pixels at object boundaries, and also uncertainty in background stabilisation caused by noise, unmodelled radial distortion and small translations of the camera. the second contribution regards a bayesian approach to specifically incorporate uncertainty concerning whether the background has yet been uncovered by moving foreground objects. this is an important requirement during initialisation of a system. we cannot assume that a background model is available in advance since that would involve storing models for each possible position, in every room, of the robot's operating environment. instead the background model must be generated online, very possibly in the presence of moving objects.
sparse image coding using a 3d non-negative tensor factorization. we introduce an algorithm for a non-negative 3d tensor factorization for the purpose of establishing a local parts feature decomposition from an object class of images. in the past such a decomposition was obtained using non-negative matrix factorization (nmf) where images were vectorized before being factored by nmf. a tensor factorization (ntf) on the other hand preserves the 2d representations of images and provides a unique factorization (unlike nmf which is not unique). the resulting "factors" from the ntf factorization are both sparse (like with nmf) but also separable allowing efficient convolution with the test image. results show a superior decomposition to what an nmf can provide on all fronts ¿ degree of sparsity, lack of ghost residue due to invariant parts and efficiency of coding of around an order of magnitude better. experiments on using the local parts decomposition for face detection using svm and adaboost classifiers demonstrate that the recovered features are discriminatory and highly effective for classification.
neighborhood preserving embedding. recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. we consider the case where data is drawn from sampling a probability distribution that has support on or near a submanifold of euclidean space. in this paper, we propose a novel subspace learning algorithm called neighborhood preserving embedding (npe). different from principal component analysis (pca) which aims at preserving the global euclidean structure, npe aims at preserving the local neighborhood structure on the data manifold. therefore, npe is less sensitive to outliers than pca. also, comparing to the recently proposed manifold learning algorithms such as isomap and locally linear embedding, npe is defined everywhere, rather than only on the training data points. furthermore, npe may be conducted in the original space or in the reproducing kernel hilbert space into which data points are mapped. this gives rise to kernel npe. several experiments on face database demonstrate the effectiveness of our algorithm.
learning a locality preserving subspace for visual recognition. previous works have demonstrated that the face recognition performance can be improved significantly in low dimensional linear subspaces. conventionally, principal component analysis (pca) and linear discriminant analysis (lda) are considered effective in deriving such a face subspace. however, both of them effectively see only the euclidean structure of face space. in this paper, we propose a new approach to mapping face images into a sub-space obtained by locality preserving projections (lpp) for face analysis. we call this laplacian face approach. different from pca and lda, lpp finds an embedding that preserves local information, and obtains a face space that best detects the essential manifold structure. in this way, the unwanted variations resulting from changes in lighting, facial expression, and pose may be eliminated or reduced. we compare the proposed laplacian face approach with eigenface and fisherface methods on three test datasets. experimental results show that the proposed laplacianface approach provides a better representation and achieves lower error rates in face recognition.
wormholes in shape space: tracking through discontinuous changes in shape. existing object tracking algorithms generally use some form of local optimisation, assuming that an object's position and shape change smoothly over time. in some situations this assumption is not valid: the trackable shape of an object may change discontinuously, for example if it is the 2d silhouette of a 3d object.in this paper we propose a novel method for modelling temporal shape discontinuities explicitly. allowable shapes are represented as a union of (learned) bounded regions within a shape space. discontinuous shape changes are described in terms of transitions between these regions. transition probabilities are learned from training sequences and stored in a markov model. in this way we can create "wormholes" in shape space. tracking with such models is via an adaptation of the condensation algorithm.
natural image statistics for natural image segmentation. building on recent progress in modeling £lter responsestatistics of natural images we integrate a statistical modelinto a variational framework for image segmentation. incorporatedin a sound probabilistic distance measure themodel drives level sets toward meaningful segmentationsof complex textures and natural scenes. since each regioncomprises two model parameters only the approachis computationally ef£cient and enables the application ofvariational segmentation to a considerably larger class ofreal-world images. we validate the statistical basis of ourapproach on thousands of natural images and demonstratethat our model outperforms recent variational segmentationmethods based on second-order statistics.
learning non-negative sparse image codes by convex programming. example-based learning of codes that statistically encode general image classes is of vital importance for computational vision. recently, non-negative matrix factorization (nmf) was suggested to provide image codes that are both sparse and localized, in contrast to established non-local methods like pca. in this paper we adopt and generalize this approach to develop a novel learning framework that allows to efficiently compute sparsity-controlled invariant image codes by a well-defined sequence of convex conic programs. applying the corresponding parameter-free algorithm to various image classes results in semantically relevant and transformation-invariant image representations that are remarkably robust against noise and quantization.
real time pattern matching using projection kernels. a novel approach to pattern matching is presented, whichreduces time complexity by two orders of magnitude comparedto traditional approaches. the suggested approachuses an efficient projection scheme which bounds the distancebetween a pattern and an image window using veryfew operations. the projection framework is combined witha rejection scheme which allows rapid rejection of imagewindows that are distant from the pattern. experimentsshow that the approach is effective even under very noisyconditions. the approach described here can also be usedin classification schemes where the projection values serveas input features that are informative and fast to extract.
fast stereovision with subpixel-precision. a fast stereo algorithm based on aliasing effects of simple disparity estimators within a coherence-detection scheme is presented. the algorithm calculates dense disparity maps with subpixel-precision by performing local spatial filter operations and simple arithmetic transformations. performance similar to classical area-based approaches is achieved, but without the complicated hierarchical search structure typical for these approaches. the algorithm is completely parallel, the disparity values are calculated independently for each pixel. in addition, local validation counts for the disparity estimates and a fused cyclopean view of the scene are available within the proposed network structure for coherence-based stereo. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
reconstruction from image sequences by means of relative depths. the paper deals with the problem of reconstructing the locations of n points in space from m different images without camera calibration. it shows how these problems can be put into a similar theoretical framework. a new concept, the reduced fundamental matrix, is introduced. it contains just 4 parameters and can be used to predict locations of points in the images and to make reconstruction. we also introduce the concept of reduced fundamental tensor which describes the relations between points in 3 images. it has 15 components and depends on 9 parameters. necessary and sufficient conditions for a tensor to be a reduced fundamental tensor are derived. this framework can be generalised to a sequence of images. the dependencies between the different representations are investigated. furthermore a canonical form of the camera matrices in a sequence are presented.
bayesian clustering of optical flow fields. we present a method for unsupervised learning of classesof motions in video. we project optical flow fields to a complete,orthogonal, a-priori set of basis functions in a probabilisticfashion, which improves the estimation of the projectionsby incorporating uncertainties in the flows. we thencluster the projections using a mixture of feature-weightedgaussians over optical flow fields. the resulting modelextracts a concise probabilistic description of the majorclasses of optical flow present. the method is demonstratedon a video of a person's facial expressions.
3d shape recognition and reconstruction based on line element geometry. this paper presents a new method for the recognition and reconstruction of surfaces from 3d data. line element geometry, which generalizes both line geometry and the laguerre geometry of oriented planes, enables us to recognize a wide class of surfaces (spiral surfaces, cones, helical surfaces, rotational surfaces, cylinders, etc.) by fitting linear subspaces in an appropriate seven-dimensional image space. in combination with standard techniques such as pca and ransac, line element geometry is employed to effectively perform the segmentation of complex objects according to surface type. examples show applications in reverse engineering of cad models and testing mathematical hypotheses concerning the exponential growth of sea shells.
geometric context from a single image. many computer vision algorithms limit their performance by ignoring the underlying 3d geometric structure in the image. we show that we can estimate the coarse geometric properties of a scene by learning appearance-based models of geometric classes, even in cluttered natural scenes. geometric classes describe the 3d orientation of an image region with respect to the camera. we provide a multiple-hypothesis framework for robustly estimating scene structure from a single image and obtaining confidences for each geometric label. these confidences can then be used to improve the performance of many other applications. we provide a thorough quantitative evaluation of our algorithm on a set of outdoor images and demonstrate its usefulness in two applications: object detection and automatic single-view reconstruction.
combining generative models and fisher kernels for object recognition. learning models for detecting and classifying object categories is a challenging problem in machine vision. while discriminative approaches to learning and classification have, in principle, superior performance, generative approaches provide many useful features, one of which is the ability to naturally establish explicit correspondence between model components and scene features ¿ this, in turn, allows for the handling of missing data and unsupervised learning in clutter. we explore a hybrid generative/discriminativeapproach using ¿fisher kernels¿ [1] which retains most of the desirable properties of generative methods, while increasing the classification performance through a discriminative setting. furthermore, we demonstrate how this kernel framework can be used to combine different types of features and models into a single classifier. our experiments, conducted on a number of popular benchmarks, show strong performance improvements over the corresponding generative approach and are competitive with the best results reported in the literature.
a multi-scale hybrid linear model for lossy image representation. this paper introduces a simple and efficient representation for natural images. we partition an image into blocks and treat the blocks as vectors in a high-dimensional space. we then fit a piece-wise linear model (i.e. a union of affine subspaces) to the vectors at each down-sampling scale. we call this a multi-scale hybrid linear model of the image. the hybrid and hierarchical structure of this model allows us effectively to extract and exploit multi-modal correlations among the imagery data at different scales. it conceptually and computationally remedies limitations of many existing image representation methods that are based on either a fixed linear transformation (e.g. dct, wavelets), an adaptive uni-modal linear transformation (e.g. pca), or a multi-modal model at a single scale. we will justify both analytically and experimentally why and how such a simple multi-scale hybrid model is able to reduce simultaneously the model complexity and computational cost. despite a small overhead for the model, our results show that this new model gives more compact representations for a wide variety of natural images under a wide range of signal-to-noise ratio than many existing methods, including wavelets.
large-scale event detection using semi-hidden markov models. we present a new approach to recognizing events invideos.we first detect and track moving objects in thescene.based on the shape and motion properties ofthese objects, we infer probabilities of primitive eventsframe-by-frame by using bayesian networks.compositeevents, consisting of multiple primitive events, overextended periods of time are analyzed by using a hidden,semi-markov finite state model.this results in morereliable event segmentation compared to the use of standardhmms in noisy video sequences at the cost of someincrease in computational complexity.we describe ourapproach to reducing this complexity.we demonstratethe effectiveness of our algorithm using both real-worldand pertubed data.
self-calibration and euclidean reconstruction using motions of a stereo rig. this paper describes a method to upgrade projective reconstruction to affine and to metric reconstructions using rigid gener almotions of a stereo rig. we make clear the algebraic relationships between projective reconstruction, the plane at infinity (affine reconstruction), camera calibration, and metric reconstruction. we show that all the computations can be carried out using standard linear resolution methods and that these methods compare favorably with nonlinear optimization methods in the presence of gaussian noise. we carry out a theoretical error analysis which quantify the relative importance of the accuracies of projective-to-affine conversion and affine-to-euclidean conversion. experiments with real data are consistent with the theoretical error analysis and with a sensitivity analysis performed with simulated data.
object pose: links between paraperspective and perspective. d.f. dementhon and l.s. davis (1995) proposed a method for determining the pose of a 3d object with respect to a camera from 3d to 2d point correspondences. the method consists of iteratively improving the pose computed with a weak perspective camera model to converge at the limit, to a pose estimation computed with a perspective camera model. we show that the method of dementhon and davis can be extended to paraperspective. the iterative paraperspective pose algorithm that we describe in detail has interesting properties both in terms of speed and rate of convergence. moreover, we introduce a simple way of taking into account the orthogonality constraint associated with the rotation matrix and we define the optimal experimental setup to be used in the presence of camera calibration errors.
statistical learning, localization, and identification of objects. this work describes a statistical approach to deal with learning and recognition problems in the field of computer vision. an abstract theoretical framework is provided, which is suitable for automatic model generation from examples, identification, and localization of objects. both, the learning and localization stage are formalized as parameter estimation tasks. the statistical learning phase is unsupervised with respect to the matching of model and scene features. the general mathematical description yields algorithms which can even treat parameter estimation problems from projected data. the experiments show that this probabilistic approach is suitable for solving 2d and 3d object recognition problems using grey-level images. the method can also be applied to 3d image processing issues using range images, i.e. 3d input data.
vector boosting for rotation invariant multi-view face detection. in this paper, we propose a novel tree-structured multi-view face detector (mvfd), which adopts the coarse-to-fine strategy to divide the entire face space into smaller and smaller subspaces. for this purpose, a newly extended boosting algorithm named vector boosting is developed to train the predictors for the branching nodes of the tree that have multi-components outputs as vectors. our mvfd covers a large range of the face space, say, +/- 45° rotation in plane (rip) and +/- 90° rotation off plane (rop), and achieves high accuracy and amazing speed (about 40 ms per frame on a 320 × 240 video sequence) compared with previous published works. as a result, by simply rotating the detector 90°, 180° and 270°, a rotation invariant (360° rip) mvfd is implemented that achieves real time performance (11 fps on a 320 × 240video sequence) with high accuracy.
spatial color indexing and applications. we suggest the use of the color correlogram as a generic indexing tool to tackle various computer vision problems. correlograms were shown to be very effective for content-basedimage retrieval [4]. we adapt the correlogram to handle the problems of image subregion querying, object localization, object tracking, and cut detection. experimental results suggest that the color correlogram is much more effective than the histogram for these applications, with insignificant additional computational, storage, or processing cost. we also provide a technique to cut down the storage requirement of correlograms so that it is the same as that of histograms, with only negligible performance penalty compared to the original correlogram.
detecting changes in aerial views of man-made structures. many applications require detecting structural changes in a scene over a period of time. comparing intensity values of successive images is not effective as such changes don't necessarily reflect actual changes at a site but might be caused by changes in the view point, illumination and seasons. we take the approach of comparing a 3-d model of the site, prepared from previous images, with new images to infer significant changes. this task is difficult as the images and the models have very different levels of abstract representations. our approach consists of several steps: registering a site model to a new image, model validation to confirm the presence of model objects in the image; structural change detection seeks to resolve matching problems and indicate possibly changed structures; and finally updating models to reflect the changes. our system is able to detect missing (or mis-modeled) buildings, changes in model dimensions, and new buildings under some conditions.
relational histograms for shape indexing. this paper is concerned with the retrieval of images from large databases based on their shape similarity to a query image. our approach is based on two dimensional histograms that encode both the local and global geometric properties of the shapes. the pairwise attributes are the directed segment relative angle and directed relative position the novelty of the proposed approach is to simultaneously use the relational and structural constraints, derived from an adjacency graph, to gate histogram contributions. we investiguate the retrieval cap abilities of the method for various queries. we also investigate the robustness of the method to segmentation errors. we conclude that a relational histo gram of pairwise segment attributespresents a very efficient way of indexing into large databases. the optimal configuration is obtained when the local features are constructed from six neighbouring segments pairs. moreover, a sensitivity analysis reveals that segmentation errors do not affect the retrieval performances.
sensitivity analysis for object recognition from large structural libraries. this paper studies the structural sensitivity of line-pattern recognition using shape-graphs. we compare the recognition performance for four different algorithms. each algorithm uses a set of pair wise geometric attributes and a neighborhood graph to represent the structure of the line patterns. the first algorithm uses a pair-wise geometric histogram, the second uses a relational histogram on the edges of the shape graph, the third compares the set of attributes on the edges of the shape graph and the final algorithm compares the arrangement of line correspondences using graph-matching. the different algorithms are compared under line deletion, line addition, line fragmentation and line end-point measurement errors. it is the graph-matching algorithm which proves to be the most effective.
computing visual correspondence: incorporating the probability of a false match. we describe a method for computing visual correspondence which employs a formal model of the probability of a false match. this model estimates the chance that the best match for each point could have occurred at random. the model is effective at identifying points in one image for which there is no corresponding point in the other image, as occurs at depth boundaries in stereo and at motion boundaries in optical flow. more generally, the model can be used to identify points where the best match is of poor quality, as occurs in regions of uniform texture. we describe the similarity measure used in the method and present the formal model of a false match. we also show examples of using the method to compute stereo disparity.
outlier correction in image sequences for the affine camera. it is widely known that, for the affine camera model, both shape and motion can be factorized directly from the so-called image measurement matrix constructed from image point coordinates. the ability to extract both shape and motion from this matrix by a single svd operation makes this shape-from-motion approach attractive; however, it cannot deal with missing feature points and, in the presence of outliers, a direct svd to the matrix would yield highly unreliable shape and motion components. in this paper, we present an outlier correction scheme that iteratively updates the elements of the image measurement matrix. the magnitude and sign of the update to each element is dependent upon the residual robustly estimated in each iteration. the result is that outliers are corrected and retained, giving improved reconstruction and smaller reprojection errors. our iterative outlier correction scheme has been applied to both synthesized and real video sequences. the results obtained are remarkably good.
reconstructing the geometry of flowing water. we present a recording scheme, image formation model and reconstruction method that enables image-based modeling of flowing bodies of water from multi-video input data. the recorded water is dyed with a fluorescent chemical to measure the thickness of a column of water, which leads to an image formation model based on integrated emissivities along a viewing ray. this model allows for a photo-consistency based error measure for a weighted minimal surface, which is recovered using a pde obtained from the euler-lagrangian formulation of the problem. the resulting equation is solved using the level set method.
ensuring color consistency across multiple cameras. most multi-camera vision applications assume a single common color response for all cameras. however different cameras ¿ even of the same type ¿ can exhibit radically different color responses, and the differences can cause significant errors in scene interpretation. to address this problem we have developed a robust system aimed at inter-camera color consistency. our method consists of two phases: an iterative closed-loop calibration phase that searches for the per-camera hardware register settings that best balance linearity and dynamic range, followed by a refinement phase that computes the per-camera parametric values for an additional software-based color mapping.
closed-world tracking. a new approach to tracking weakly modeled objects in a semantically rich domain is presented. we define a closed-world as a space-time region of an image sequence in which the complete taxonomy of objects is known, and in which each pixel should be explained as belonging to one of those objects. given contextual object information, context-specific features can be dynamically selected as the basis for tracking. a context-specific feature is one that has been chosen based upon the context to maximize the chance of successful tracking between frames. our work is motivated by the goal of video annotation-the semi-automatic generation of symbolic descriptions of action taking place in a contextually-rich dynamic scene. we describe how contextual knowledge in the "football domain" can be applied to closed-world football player tracking and present the details of our implementation. we include tracking results based on hundreds of images that demonstrate the wide range of tracking situations the algorithm successfully handles as well as a few examples of where the algorithm fails.
finding people by sampling. we show how to use a sampling method to find sparsely clad people in static images. people are modeled as an assembly of nine cylindrical segments. segments are found using an em algorithm, and then assembled into hypotheses incrementally, using a learned likelihood model. each assembly step passes on a set of samples of its likelihood to the next; this yields effective pruning of the space of hypotheses. the collection of available nine-segment hypotheses is then represented by a set of equivalence classes, which yield an efficient pruning process. the posterior for the number of people is obtained from the class representatives. people are counted quite accurately in images of real scenes using an map estimate. we show the method allows top-down as well as bottom up reasoning. while the method can be overwhelmed by very large numbers of segments, we show that this problem can be avoided by quite simple pruning steps.
robust multi-sensor image alignment. this paper presents a method for alignment of images acquired by sensors of different modalities (e.g., eo and ir). the paper has two main contributions: (i) it identifies an appropriate image representation for multi-sensor alignment, i.e., a representation which emphasizes the common information between the two multi-sensor images, suppresses the non-common information, and is adequate for coarse-to-fine processing. (ii) it presents a new alignment technique, which applies global estimation to any choice of a local similarity measure. in particular, it is shown that when this registration technique is applied to the chosen image representation with a local-normalized-correlation similarity measure, it providesa new multi-sensor alignment algorithm which is robust to outliers, and applies to a wide variety of globally complex brightness transformations between the two images.our proposed image representation does not rely on sparse image features (e.g., edge, contour, or point features). it is continuous and does not eliminate the detailed variations within local image regions. our method naturally extends to coarse-to-fine processing, and applies even in situations when the multi-sensor signals are globally characterized by low statistical correlation.
mosaic based representations of video sequences and their applications. recently, there has been a growing interest in the use of mosaic images to represent the information contained in video sequences. the paper systematically investigates how to go beyond thinking of the mosaic simply as a visualization device, but rather as a basis for efficient representation of video sequences. we describe two different types of mosaics called the static and the dynamic mosaic that are suitable for different needs and scenarios. we discuss a series of extensions to these basic mosaics to provide representations at multiple spatial and temporal resolutions and to handle 3d scene information. we describe techniques for the basic elements of the mosaic construction process, namely alignment, integration, and residual analysis. we describe several applications of mosaic representations including video compression, enhancement, enhanced visualization, and other applications in video indexing, search, and manipulation.
a mixed-state condensation tracker with automatic model-switching. there is considerable interest in the computer vision community in representing and modelling motion. motion models are use d as predictors to increase the robustness and accuracy of visual trackers, and as classifiers for gesture recognition. this paper presents a significant development of random sampling methods to allow automatic switching between multiple motion models as a natural extension of the tracking process. the bayesian mixed-state framework is described in its generality, and the example of a bouncing ball is used to demonstrate that a mixed-state model can significantly improve tracking performance in heavy clutter. the relevance of the approach to the problem of gesture recognition is then investigated using a tracker which is able to follow the natural drawing action of a hand holding a pen, and switches state according to the hand's motion.
finding tree structures by grouping symmetries. the representation of objects in images as tree structures is of great interest to vision, as they can represent articulated objects such as people as well as other structured objects like arteries in human bodies, roads, circuit board patterns, etc. tree structures are often related to the symmetry axis representation of shapes, which captures their local symmetries. algorithms have been introduced to detect (i) open contours in images in quadratic time (ii) closed contours in images in cubic time, and (iii) tree structures from contours in quadratic time. the algorithms are based on dynamic programming and single source shortest path algorithms. however, in this paper, we show that the problem of finding tree structures in images in a principled manner is a much harder problem. we argue that the optimization problem of finding tree structures in images is essentially equivalent to a variant of the steiner tree problem, which is np-hard. nevertheless, an approximate polynomial-time algorithm for this problem exists: we apply a fast implementation of the goemans-williamson approximate algorithm to the problem of finding a tree representation after an image is transformed by a local symmetry mapping. examples of extracting tree structures from images illustrate the idea and applicability of the approximate method.
stochastic refinement of the visual hull to satisfy photometric and silhouette consistency constraints. an iterative method for reconstructing a 3d polygonalmesh and color texture map from multiple views of an objectis presented. in each iteration, the method first estimates atexture map given the current shape estimate. the texturemap and its associated residual error image are obtainedvia maximum a posteriori estimation and reprojection of themultiple views into texture space. next, the surface shape isadjusted to minimize residual error in texture space. thesurface is deformed towards a photometrically-consistentsolution via a series of 1d epipolar searches at randomlyselected surface points. the texture space formulation hasimproved computational complexity over standard image-basederror aproaches, and allows computation of the reprojectionerror and uncertainty for any point on the surface.moreover, shape adjustments can be constrained suchthat the recovered model's silhouette matches those of theinput images. experiments with real world imagery demonstratethe validity of the approach.
robust contour tracking in echocardiographic sequences. in this paper we present an evaluation of a robust visual image tracker on echocardiographic image sequences. we show how the tracking framework can be customised to define an appropriate shape-space that describes heart shape deformations that can be learnt from a training data set. we also investigate an energy-based temporal boundary enhancement method to improve image feature measurement. preliminary results are presented demonstrating tracking on real normal heart motion data sequences and synthesised and real abnormal heart motion data sequences. we conclude by discussing some of our current research efforts.
condensing image databases when retrieval is based on non-metric distances. one of the key problems in appearance-based-vision is understanding how to use a set of labeled images to classify new images. classification systems that can model human performance, or that use robust image matching methods, often make use of similarity judgments that are non-metric, but when the triangle inequality is not obeyed, most existing pattern recognition techniques are not applicable. we note that exemplar-based (or nearest-neighbor) methods can be applied naturally when using a wide class of non-metric similarity functions. the key issue, however, is to find methods for choosing good representatives of a class that accurately characterize it. we show that existing condensing techniques for finding class representatives are ill-suited to deal with non-metric dataspaces.we then focus on developing techniques for solving this problem, emphasizing two points: first, we show that the distance between two images is not a good measure of how well one image can represent another in non-metric spaces. instead, we use the vector correlation between the distances from each image to other previously seen images. second, we show that in non-metric spaces, boundary points are less significant for capturing the structure of a class than they are in euclidean spaces. we suggest that atypical points may be more important in describing classes. we demonstrate the importance of these ideas to learning thatgeneralizes from experience by improving performance using both synthetic and real images.
saliency maps and attention selection in scale and spatial coordinates: an information theoretic approach. information measures with respect to spatial locations and scales of objects in an image are important to image processing and interpretation. it allows us to focus attention on relevant data, saving effort and reducing false positives. in particular, the information content of a man-made scene is typically confined to a small set of scales. we devise a scale space based measure of image information. kullback contrasts between successive resolution lengths gives the differential information gain. experiments show that this measure gives a clear indication of characteristic lengths in a variety of real world images and is superior to power spectrum based measurements. decomposing the expected information gain into spatial coordinates gives us a saliency map for use by an attention selector. we combine the scale and spatial decompositions into a single information measure, giving both the spatial extent and scale range of interest. the information measure has an efficient implementation, and thus can be used routinely in early vision processing.
multimodal human computer interaction: a survey. in this paper, we review the major approaches to multimodal human-computer interaction, giving an overview of the field from a computer vision perspective. in particular, we focus on body, gesture, gaze, and affective interaction (facial expression recognition and emotion in audio). we discuss user and task modeling, and multimodal fusion, highlighting challenges, open issues, and emerging applications for multimodal human-computer interaction (mmhci) research.
tracking across multiple cameras with disjoint views. conventional tracking approaches assume proximity inspace, time and appearance of objects in successive observations.however, observations of objects are often widelyseparated in time and space when viewed from multiplenon-overlapping cameras. to address this problem, wepresent a novel approach for establishing object correspondenceacross non-overlapping cameras. our multi-cameratracking algorithm exploits the redundance in paths thatpeople and cars tend to follow, e.g. roads, walk-ways orcorridors, by using motion trends and appearance of objects,to establish correspondence. our system does notrequire any inter-camera calibration, instead the systemlearns the camera topology and path probabilities of objectsusing parzen windows, during a training phase. oncethe training is complete, correspondences are assigned usingthe maximum a posteriori (map) estimation framework.the learned parameters are updated with changing trajectorypatterns. experiments with real world videos are reported,which validate the proposed approach.
images as bags of pixels. we propose modeling images and related visual objects as bags of pixels or sets of vectors. for instance, gray scale images are modeled as a collection or bag of (x, y, i) pixel vectors. this representation implies a permutational invariance over the bag of pixels which is naturally handled by endowing each image with a permutation matrix. each matrix permits the image to span a manifold of multiple configurations, capturing the vector set's invariance to orderings or permutation transformations. permutation configurations are optimized while jointly modeling many images via maximum likelihood. the solution is a uniquely solvable convex program which computes correspondence simultaneously for all images (as opposed to traditional pairwise correspondence solutions). maximum likelihood performs a nonlinear dimensionality reduction, choosing permutations that compact the permuted image vectors into a volumetrically minimal subspace. this is highly suitable for principal components analysis which, when applied to the permutationally invariant bag of pixels representation, outperforms pca on appearance-based vectorization by orders of magnitude.furthermore, the bag of pixels subspace benefits from automatic correspondence estimation, giving rise to meaningful linear variations such as morphings, translations, and jointly spatio-textural image transformations. results are shown for several datasets.
shape gradients for histogram segmentation using active contours. we consider the problem of image segmentation using active contours through the minimization of an energy criterion involving both region and boundary functionals. these functionals are derived through a shape derivative approach instead of classical calculus of variation. the equations can be elegantly derived without converting the region integrals into boundary integrals. from the derivative, we deduce the evolution equation of an active contour that makes it evolve towards a minimum of the criterion. we focus more particularly on statistical features globally attached to the region and especially to the probability density functions of image features such as the color histogram of a region. a theoretical framework is set for the minimization of the distance between two histograms for matching or tracking purposes. an application of this framework to the segmentation of color histograms in video sequences is then proposed. we briefly describe our numerical scheme and show some experimental results.
qualitative probabilities for image interpretation. two basic problems in image interpretation are: a) determining which interpretations are the most plausible amongst many possibilities; and b) controlling the search for plausible interpretations. we address these issues using a bayesian approach, with the plausibility ordering and search pruning based on the posterior probabilities of interpretations. however, due to the need for detailed quantitative prior probabilities and the need to evaluate complex integrals over various conditional distributions, a full bayesian approach is currently impractical except in tightly constrained domains.to circumvent these difficulties we introduce the notion of qualitative probabilistic analysis. in particular, given spatial and contrast resolution parameters, we consider only the asymptotic order of the posterior probability for any interpretation as these resolutions are made finer. we introduce this approach for a simple card-world domain, and present computational results for blocks-world images.
globally optimal regions and boundaries. we propose a new form of energy functional for the segmentation of regions in images, and an efficient method for finding its global optima. the energy can have contributions from both the region and its boundary, thus combining the best features of region- and boundary-based approaches to segmentation. by transforming the region energy into a boundary energy, we can treat both contributions on an equal footing, and solve the global optimization problem as a minimum mean weight cycle problem on a directed graph. the simple, polynomial-time algorithm requires no initialization and is highly parallelizable
multi-modal tensor face for simultaneous super-resolution and recognition. face images of non-frontal views under poor illumination with low resolution reduce dramatically face recognition accuracy. this is evident most compellingly by the very low recognition rate of all existing face recognition systems when applied to live cctv camera input. in this paper, we present a bayesian framework to perform multi-modal (such as variations in viewpoint and illumination) face image super-resolution for recognition in tensor space. given a single modal low-resolution face image, we benefit from the multiple factor interactions of training tensor, and super-resolve its high-resolution reconstructions across different modalities for face recognition. instead of performing pixel-domain super-resolution and recognition independently as two separate sequential processes, we integrate the tasks of super-resolution and recognition by directly computing a maximum likelihood identity parameter vector in high-resolution tensor space for recognition. we show results from multi-modal super-resolution and face recognition experiments across different imaging modalities, using low-resolution images as testing inputs and demonstrate improved recognition rates over standard tensorface and eigenface representations.
image registration with global and local luminance alignment. inspired by tensor voting, we present luminance voting, a novel approach for image registration with global and local luminance alignment. the key to our modeless approach is the direct estimation of replacement function, by reducing the complex estimation problem to the robust 2d tensor voting in the corresponding voting spaces. no model for replacement function is assumed. luminance data are first encoded into 2d ball tensors. subject to the monotonic constraint only, we vote for an optimal replacement function by propagating the smoothness constraint using a dense tensor field. our method effectively infers missing curve segments and rejects image outliers without assuming any simplifying or complex curve model. the voted replacement functions are used in our iterative registration algorithm for computing the best warping matrix. unlike previous approaches, our robust method corrects exposure disparity even if the two overlapping images are initially misaligned. luminance voting is effective in correcting exposure difference, eliminating vignettes, and thus improving image registration. we present results on a variety of images.
eliminating structure and intensity misalignment in image stitching. the aim of this paper is to achieve seamless image stitching for eliminating obvious visual artifact caused by severe intensity discrepancy, image distortion and structure mis-alignment, given that the input images are globally registered. our approach is based on structure deformation and propagation while maintaining the overall appearance affinity of the result to the input images. this new approach is proven to be effective in solving the above problems, and has found applications in mosaic deghosting, image blending and intensity correction. our new method consists of the following main processes. first, salient features or structures are robustly detected and aligned along the optimal partitioning boundary between the input images. from these features, we derive sparse deformation vectors to uniformly encode the underlying structure and intensity misalignment. these sparse deformation cues will then be propagated robustly and smoothly into the interior of the target image by solving the associated laplace equations in the image gradient domain. we present convincing results to show that our method can handle significant structure and intensity misalignment in image stitching.
a robust algorithm for point set registration using mixture of gaussians. this paper proposes a novel and robust approach to the point set registration problem in the presence of large amounts of noise and outliers. each of the point sets is represented by a mixture of gaussians and the point set registration is treated as a problem of aligning the two mixtures. we derive a closed-form expression for the l¿ distance between two gaussian mixtures, which in turn leads to a computationally efficient registration algorithm. this new algorithm has an intuitive interpretation, is simple to implement and exhibits inherent statistical robustness. experimental results indicate that our algorithm achieves very good performance in terms of both robustness and accuracy.
detection of concentric circles for camera calibration. the geometry of plane-based calibration methods is well understood, but some user interaction is often needed in practice for feature detection. this paper presents a fully automatic calibration system that uses patterns of pairs of concentric circles. the key observation is to introduce a geometric method that constructs a sequence of points strictly convergent to the image of the circle center from an arbitrary point. the method automatically detects the points of the pattern features by the construction method, and identify them by invariants. it then takes advantage of homological constraints to consistently and optimally estimate the features in the image. the experiments demonstrate the robustness and the accuracy of the new method.
circular motion geometry by minimal 2 points in 4 images. this paper describes a new and simple method of recovering the geometry of uncalibrated circular motion or single axis motion using a minimal data set of 2 points in 4 images. this problem has been solved using non-minimal data either by computing the fundamental matrix and trifocal tensor in 3 images, or by fitting conics to tracked points in 5 images. our new method first computes a planar homography from a minimum of 2 points in 4 images. it is shown that two eigenvectors of this homography are the images of the circular points. then, other fixed image entities and rotation angles can be straightforwardly computed. the crux of the method lies in relating this planar homography from two different points to a homology naturally induced by corresponding points on different conic loci from a circular motion. the experiments on real image sequences demonstrate the simplicity, accuracy and robustness of the new method.
epitomic analysis of appearance and shape. we present novel simple appearance and shape models that we call epitomes. the epitome of an image is its miniature, condensed version containing the essence of the textural and shape properties of the image. as opposed to previously used simple image models, such as templates or basis functions, the size of the epitome is considerably smaller than the size of the image or object it represents, but the epitome still contains most constitute elements needed to reconstruct the image (fig. 1). a collection of images often shares an epitome, e.g., when images are a few consecutive frames from a video sequence, or when they are photographs of similar objects.a particular image in a collection is defined by its epitome and a smooth mapping from the epitome to the image pixels. when the epitomic representation is used within a hierarchical generative model, appropriate inference algorithms can be derived to extract the epitome from a single image or a collection of images and at the same time perform various inference tasks, such as image segmentation, motion estimation, object removal and super-resolution.
model-based matching of line drawings by linear combinations of prototypes. we describe a technique for finding pixelwise correspondences between two images by using models of objects of the same class to guide the search. the object models are "learned" from example images (also called prototypes) of an object class. the models consist of a linear combination of prototypes. the flow fields giving pixelwise correspondences between a base prototype and each of the other prototypes must be given. a novel image of an object of the same class is matched to a model by minimizing an error between the novel image and the current guess for the closest model image. currently, the algorithm applies to line drawings of objects. an extension to real grey level images is discussed.
multidimensional morphable models. we describe a flexible model for representing images of objects of a certain class, known a priori, such as faces, and introduce a new algorithm for matching it to a novel image and thereby performing image analysis. we call this model a multidimensional morphable model or just a morphable model. the morphable model is learned from example images (calledprototypes) of objects of a class. in this paper we introduce an effective stochastic gradient descent algorithm that automatically matches a model to a novel image by finding the parameters that minimize the error between the image generated by the model and the novelimage. two examples demonstrate the robustness and the broad range of applicability of the matching algorithm and the underlying morphable model. our approach can provide novel solutions to several vision tasks, including the computation of image correspondence, object verification, image synthesis and image compression.
layered active appearance models. active appearance models (aams) provide a framework for modeling the joint shape and texture of an image. an aam is a compact representation of both factors in a conditionally linear model. however, the standard aam framework does not handle images which have missing features, or allow modification of certain structures in the image while leaving neighboring ones undeformed. we introduce the layered active appearance model (laam), which allows for missing features, occlusion, substantial spatial rearrangement of features, and which provides a more general representation that extends the applicability of the active appearance model.
structure and motion estimation from dynamic silhouettes under perspective projection. addresses the problem of estimating the structure and motion of a smooth curved object from its silhouettes observed over time by a trinocular stereo rig under perspective projection. we first construct a model for the local structure along the silhouette for each frame in the temporal sequence. successive local models are then integrated into a global surface description by estimating the motion between successive time instants. the algorithm tracks certain surface features (parabolic points) and image features (silhouette inflections and frontier points) which are used to bootstrap the motion estimation process. the entire silhouette along with the reconstructed local structure are then used to refine the initial motion estimate. we have implemented the proposed approach and report results on real images.
high resolution terrain mapping using low altitude aerial stereo imagery. this paper presents an approach to build high resolutiondigital elevation maps from a sequence of unregistered lowaltitude stereovision image pairs. the approach first uses avisual motion estimation algorithm that determines the 3dmotions of the cameras between consecutive acquisitions,on the basis of visually detected and matched environmentfeatures. an extended kalman filter then estimates both the6 position parameters and the 3d positions of the memorizedfeatures as images are acquired. details are given onthe filter implementation and on the estimation of the uncertaintieson the feature observations and motion estimations.experimental results show that the precision of the methodenables to build spatially consistent very large maps.
creating efficient codebooks for visual recognition. visual codebook based quantization of robust appearance descriptors extracted from local image patches is an effective means of capturing image statistics for texture analysis and scene classification. codebooks are usually constructed by using a method such as k-means to cluster the descriptor vectors of patches sampled either densely (¿textons¿) or sparsely (¿bags of features¿ based on key-points or salience measures) from a set of training images. this works well for texture analysis in homogeneous images, but the images that arise in natural object recognition tasks have far less uniform statistics. we show that for dense sampling, k-means over-adapts to this, clustering centres almost exclusively around the densest few regions in descriptor space and thus failing to code other informative regions. this gives suboptimal codes that are no better than using randomly selected centres. we describe a scalable acceptance-radius based clusterer that generates better codebooks and study its performance on several image classification tasks. we also show that dense representations outperform equivalent keypoint based ones on these tasks and that svm or mutual information based feature selection starting from a dense codebook further improves the performance.
unsupervised non-parametric region segmentation using level sets. we present a novel non-parametric unsupervised segmentationalgorithm based on region competition [21];but implemented within a level sets framework [11]. thekey novelty of the algorithm is that it can solve n ¿ 2 classsegmentation problems using just one embedded surface;this is achieved by controlling the merging and splitting behaviourof the level sets according to a minimum descriptionlength (mdl) [6, 14] cost function. this is in contrastto n class region-based level set segmentation methods todate which operate by evolving multiple coupled embeddedsurfaces in parallel [3, 13, 20]. furthermore, it operates inan unsupervised manner; it is necessary neither to specifythe value of n nor the class models a-priori.we argue that the level sets methodology provides amore convenient framework for the implementation of theregion competition algorithm, which is conventionally implementedusing region membership arrays due to the lackof a intrinsic curve representation. finally, we generalisethe gaussian region model used in standard region competitionto the non-parametric case. the region boundary motionand merge equations become simple expressions containingcross-entropy and entropy terms.
multiple view geometry and the l-norm. this paper presents a new framework for solving geometric structure and motion problems based on l_¿ -norm. instead of using the common sum-of-squares cost-function, that is, thel_¿ -norm, the model-fitting errors are measured using the l_¿ -norm. unlike traditional methods based on l_¿, our framework allows for efficient computation of global estimates. we show that a variety of structure and motion problems, for example, triangulation, camera resectioning and homography estimation can be recast as a quasi-convex optimization problem within this framework. these problems can be efficiently solved using second order cone programming (socp) which is a standard technique in convex optimization. the proposed solutions have been validated on real data in different settings with small and large dimensions and with excellent performance.
multiview reconstruction of space curves. is the real problem in resolving correspondence using currentstereo algorithms the lack of the "right" matching criterion?in studying the related task of reconstructing three-dimensionalspace curves from their projections in multipleviews, we suggest that the problem is more basic: matchingand reconstruction are coupled, and so reconstruction algorithmsshould exploit this rather than assuming that matchingcan be successfully performed before reconstruction. torealize this coupling, a generative model of curves is introducedwhich has two key components: (i) a prior distributionof general space curves and (ii) an image formation modelwhich describes how 3d curves are projected onto the imageplane. a novel aspect of the image formation model is that ituses an exact description of the gradient field of a piecewiseconstant image. based on this forward model, a fully automaticalgorithm for solving the inverse problem is developedfor an arbitrary number of views. the resulting algorithmis robust to partial occlusion, deficiencies in image curveextraction and it does not rely on photometric information.the relative motion of the cameras is assumed to be given.several experiments are carried out on various realistic scenarios.in particular, we focus on scenes where traditionalcorrelation-based methods would fail.
globally optimal estimates for geometric reconstruction problems. we introduce a framework for computing statistically optimal estimates of geometric reconstruction problems. while traditional algorithms often suffer from either local minima or non-optimality - or a combination of both - we pursue the goal of achieving global solutions of the statistically optimal cost-function. our approach is based on a hierarchy of convex relaxations to solve non-convex optimization problems with polynomials. these convex relaxations generate a monotone sequence of lower bounds and we show how one can detect whether the global optimum is attained at a given relaxation. the technique is applied to a number of classical vision problems: triangulation, camera pose, homography estimation and last, but not least, epipolar geometry estimation. experimental validation on both synthetic and real data is provided. in practice, only a few relaxations are needed for attaining the global optimum.
using conic correspondence in two images to estimate the epipolar geometry. in this paper it is shown how corresponding conics in two images can be used to estimate the epipolar geometry in terms of the fundamental/essential matrix. the corresponding conics can be images of either planar conics or silhouettes of quadrics. it is shown that one conic correspondence gives two independent constraints on the fundamental matrix and a method to estimate the fundamental matrix from at least four corresponding conics is presented. furthermore, a new type of fundamental matrix for describing conic correspondences is introduced. finally, it is shown that the problem of estimating the fundamental matrix from 5 point correspondences and 1 conic correspondence in general has 10 different solutions. a method to calculate these solutions is also given together with an experimental validation.
3d human body model acquisition from multiple views. we present a novel motion-based approach for the part determination and shape estimation of a human's body parts. the novelty of the technique is that neither a prior model of the human body is employed nor prior body part segmentation is assumed. we present a human body part identification strategy (hbpis) that recovers all the body parts of a moving human based on the spatiotemporal analysis of its deforming silhouette. we formalize the process of simultaneous part determination and 2d shape estimation by employing the supervisory control theory of discrete event systems. in addition, in order to acquire the 3d shape of the body parts, we present a new algorithm which selectively integrates the (segmented by the hbpis) apparent contours, from three mutually orthogonal views. the effectiveness of the approach is demonstrated through a series of experiments, where a subject performs a set of movements according to a protocol that reveals the structure of the human body.
a robot system that observes and replicates grasping tasks. to alleviate the problem of overwhelming complexity in grasp synthesis and path planning associated with robot task planning, we adopt the approach of teaching the robot by demonstrating in front of it. the system has four components: the observation system, the grasping task recognition module, the task translator and the robot system. the observation system comprises an active multibaseline stereo system and a dataglove. the data stream recorded is then used to track object motion; this paper illustrates how complimentary sensory data can be used for this purpose. the data stream is also interpreted by the grasping task recognition module, which produces higher levels of abstraction to describe both the motion and actions taken in the task. the resulting information are provided to the task translator which creates commands for the robot system to replicate the observed task. in this paper we describe how these components work with special emphasis on the observation system. the robot system that we use to perform the grasping tasks comprises the puma 560 arm and the utah/mit hand.
a multibaseline stereo system with active illumination and real-time image acquisition. we describe our implementation of a parallel depth recovery scheme for a four-camera multibaseline stereo in a convergent configuration. our system is capable of image capture at video rate. this is critical in applications that require three-dimensional tracking. we obtain dense stereo depth data by projecting a light pattern of frequency modulated sinusoidally varying intensity onto the scene, thus increasing the local discriminability at each pixel and facilitating matches. in addition, we make most of the camera view areas by converging them at a volume of interest. results show that we are able to extract stereo depth data that are, on the average, less than 1 mm in error at distances between 1.5 to 3.5 m away from the cameras.
unsupervised parallel image classificiation using a hierarchical markovian model. the paper deals with the problem of unsupervised classification of images modeled by markov random fields (mrf). if the model parameters are known then we have various methods to solve the segmentation problem (simulated annealing, icm, etc...). however, when they are not known, the problem becomes more difficult. one has to estimate the hidden label field parameters from the only observable image. our approach consists of extending a recent iterative method of estimation, called iterative conditional estimation (ice) to a hierarchical markovian model. the idea resembles the estimation-maximization (em) algorithm as we recursively look at the maximum a posteriori (map) estimate of the label field given the estimated parameters then we look at the maximum likelihood (ml) estimate of the parameters given a tentative labeling obtained at the previous step. we propose unsupervised image classification algorithms using a hierarchical model. the only parameter supposed to be known is the number of regions, all the other parameters are estimated. the presented algorithms have been implemented on a connection machine cm200. comparative tests have been done on noisy synthetic and real images (remote sensing).
reliable recovery of piled box-like objects via parabolically deformable superquadrics. automatic unloading of piled box-like objects is undoubtedlyof great importance to the industry. in this contributiona system addressing this problem is described: weemploy a laser range finder for data acquisition, and globallydeformable superquadrics [2], [22] for object modeling.our technique is based on a hypothesis generation andrefinement scheme. the vertices of the piled objects are extractedand superquadric seeds are aligned at these vertices.the model parameter recovery task is decomposedinto two subproblems, each dealing with a subset of themodel's parameter set. both region and boundary based informationsources are used for parameter estimation. comparedto a widespread strategy for superquadric recovery[11], our method shows advantages in terms of robustnessand computational efficiency. in addition, our system exhibitsversatility with regard to existing industrial systems,since it can effectively deal with both neatly placed and jumbledconfigurations of objects
accurate, real-time, unadorned lip tracking. human speech is inherently multi-modal, consisting of both audio and visual components. recently researchers have shown that the incorporation of information about the position of the lips into acoustic speech recognisers enables robust recognition of noisy speech. in the case of hidden markov model-recognition, we show that his happens because the visual signal stabilises the alignment of states. it is also shown that unadorned lips, both the inner and outer contours, can be robustly tracked in real time on general-purpose workstations. to accomplish this, efficient algorithms are employed which contain three key components: shape models, motion models, and focused colour feature detectors ¿ all of which are learnt from examples.
consistent surface color for texturing large objects in outdoor scenes. color appearance of an object is significantly influenced by the color of the illumination. when the illumination color changes, the color appearance of the object will change accordingly, causing its appearance to be inconsistent. to arrive at color constancy, we have developed a physics-based method of estimating and removing the illumination color. in this paper, we focus on the use of this method to deal with outdoor scenes, since very few physics-based methods have successfully handled outdoor color constancy. our method is principally based on shadowed and non-shadowed regions. previously researchers have discovered that shadowed regions are illuminated by sky light, while non-shadowed regions are illuminated by a combination of sky light and sunlight. based on this difference of illumination, we estimate the illumination colors (both the sunlight and the sky light) and then remove them. to reliably estimate the illumination colors in outdoor scenes, we include the analysis of noise, since the presence of noise is inevitable in natural images. as a result, compared to existing methods, the proposed method is more effective and robust in handling outdoor scenes. in addition, the proposed method requires only a single input image, making it useful for many applications of computer vision.
recovering epipolar geometry by reactive tabu search. in this paper we propose a new approach to recovering epipolar geometry from a pair of uncalibrated images. we first detect the feature points. by minimizing a proposed cost function, we match the feature points, discard the outliers and recover the epipolar geometry in one step. experiments on real images show that this approach is effective and fast.
united snakes. since their debut in 1987, snakes (active contour models) have become a standard image analysis technique with several variants now in common use. we present a portable, reusable, software package called "united snakes". the package unites the most popular snake variants, including finite difference, b-spline, and hermite polynomial snakes within the mathematical framework of a general finite element formulation with a choice of shape functions. the package furthermore incorporates a recently proposed snake-like technique known as "livewire". we integrate snakes and livewire by introducing an effective method for imposing hard constraints on snakes. our experiments demonstrate that snakes and livewire have complementary strengths and that their union offers a more powerful tool for interactive image analysis, especially for medical imaging applications. united snakes is implemented in java as a javabean so that it can easily be integrated in end-user application systems.
annular symmetry operators: a method for locating and describing objects. we present a machine vision system in which segmentation is computed in conjunction with a structural description of objects in the scene. it is assumed that contrast edges capture all relevant object information. the principles which dictate how edge features are grouped to infer objects are based upon detecting symmetrical enclosing edge configurations. these are detected using annular operators applied at multiple scales to edge data which have been extracted at multiple scales from a gray level image. the subsequent grouping of symmetry points results in a set of parts which make it possible to identify the location of objects within an image. these parts are used as a basis for constructing coarse graph-based descriptors for the perceptually significant objects found in the scene. results are presented to illustrate the method's performance on several images.
uncalibrated motion capture exploiting articulated structure constraints. we present an algorithm for 3d reconstruction of dynamic articulated structures, such as humans, from uncalibrated multiple views. the reconstruction exploits constraints associated with a dynamic articulated structure, specifically the conservation over time of length between rotational joints. these constraints admit reconstruction of metric structure from at least two different images in each of two uncalibrated parallel projection cameras. as a by product, the calibration of the cameras can also be computed. the algorithm is based on a stratified approach, starting with affine reconstruction from factorization, followed by rectification to metric structure using the articulated structure constraints. the exploitation of these specific constraints admits reconstruction and self-calibration with fewer feature points and views compared to standard self-calibration. the method is extended to pairs of cameras that are zooming, where calibration of the cameras allows compensation for the changing scale factor in a scaled orthographic camera. results are presented in the form of stick figures and animated 3d reconstructions using pairs of sequences from broadcast television. the technique shows promise as a means of creating 3d animations of dynamic activities such as sports events.
dynamic measurement clustering to aid real time tracking. we present a technique for clustering measurements such that high-dimensional parameter estimation problems can be simplified. the key idea is to find rows of the measurement jacobian whose rank is significantly less than its width. such a set of rows gives a cluster of measurements which is affected only by a subset of the parameter space. this cluster can be used independently from other measurements to isolate parameter decisions. unlike static partitioning techniques, the method presented dynamically generates clusters at each step of the estimation. this achieves substantial computational reductions, even for problems which cannot be partitioned in the traditional sense. the technique is applied to the task of tracking camera motions in real-time and video sequences are used to compare the resulting system to previous methods.
passive photometric stereo from motion. we introduce an iterative algorithm for shape reconstruction from multiple images of a moving (lambertian) object illuminated by distant (and possibly time varying) lighting. starting with an initial piecewise linear surface, the algorithm iteratively estimates a new surface based on the previous surface estimate and the photometric information available from the input image sequence. during each iteration, standard photometric stereo techniques are applied to estimate the surface normals up to an unknown generalized bas-relief transform, and a new surface is computed by integrating the estimated normals. the algorithm essentially consists of a sequence of matrix factorizations (of intensity values) followed by minimization using gradient descent (integration of the normals). conceptually, the algorithm admits a clear geometric interpretation, which is used to provide a qualitative analysis of the algorithm¿s convergence. implementation-wise, it is straightforward, being based on several established photometric stereo and structure from motion algorithms. we demonstrate experimentally the effectiveness of our algorithm using several videos of hand-held objects moving in front of a fixed light and camera.
a level line selection approach for object boundary estimation. an energy model-based approach for estimating object boundaries is presented. we study a particular energy, which minimizer can be determined. the method estimates the unknown number of objects and draws object boundaries by selecting the "best" level lines computed from level sets of the original image. unlike previous standard methods, the proposed method does not require iteration for minimizing the energy. in addition, our segmentation algorithm combines anisotropic diffusion-based regularization with level line selection to extract smooth object boundaries. experimental results on 2d biomedical and meteorological images are reported.
an integrated framework for image segmentation and perceptual grouping. this paper presents an efficient algorithm for image segmentation and a framework for perceptual grouping. it makes an attempt to provide one way of combining bottom-up and top-down approaches. in image segmentation, it generalizes the swendsen-wang cut algorithm [1] (swc) to make both 2-way and m-way cuts, and includes topology change processes (graph repartitioning and boundary diffusion). the method directly works at a low temperature without using annealing. we show that it is much faster than the ddmcmc approach [12] and more robust than the swc method. the results are demonstrated on the berkeley data set [7]. in perceptual grouping, it integrates discriminative model learning/computing, a belief propagation algorithm (bp) [15] , and swc into a three-layer computing framework. these methods are realized as different levels of approximation to an "ideal" generative model. we demonstrate the algorithm on the problem of human body configuration.
probabilistic boosting-tree: learning discriminative models for classification, recognition, and clustering. in this paper, a new learning framework¿probabilistic boosting-tree (pbt), is proposed for learning two-class and multi-class discriminative models. in the learning stage, the probabilistic boosting-tree automatically constructs a tree in which each node combines a number of weak classifiers (evidence, knowledge) into a strong classifier (a conditional posterior probability). it approaches the target posterior distribution by data augmentation (tree expansion) through a divide-and-conquer strategy. in the testing stage, the conditional probability is computed at each tree node based on the learned classifier, which guides the probability propagation in its sub-trees. the top node of the tree therefore outputs the overall posterior probability by integrating the probabilities gathered from its sub-trees. also, clustering is naturally embedded in the learning phase and each sub-tree represents a cluster of certain level. the proposed framework is very general and it has interesting connections to a number of existing methods such as the a* algorithm, decision tree algorithms, generative models, and cascade approaches. in this paper, we show the applications of pbt for classification, detection, object recognition. we have also applied the framework in segmentation.
gradient flows and geometric active contour models. in this paper, we analyze the geometric active contour models discussed previously from a curve evolution point of view and propose some modifications based on gradient flows relative to certain new feature-based riemannian metrics. this leads to a novel snake paradigm in which the feature of interest may be considered to lie at the bottom of a potential well. thus the snake is attracted very naturally and efficiently to the desired feature. moreover, we consider some 3-d active surface models based on these ideas.
a practical single image based approach for estimating illumination distribution from shadows. this paper presents a practical method that estimates illumination distribution from shadows where the shadows are assumed to be cast on a textured, lambertian surface. previous methods usually require that the reflectance property of the surface be constant or uniform, or need an additional image to cancel out the effects of varying albedo of the textured surface. we deal with an estimation problem for which surface albedo information is not available. in this case, the estimation problem corresponds to an underdetermined one. we show that combination of regularization by correlation and some user-specified information can be a practical method for solving the problem. in addition, as an optimization tool for solving the problem, we develop a constrained non-negative quadratic programming (nnqp) technique into which not only regularization but also user-specified information are easily incorporated. we test and validate our method on both synthetic and real images and present some experimental results.
a representation of specular appearance. the appearance of an object can vary considerably with changes in illumination conditions. methods have been developed to describe these differences for diffuse reflection using the lambertian model, but little work has been done in characterizing specular appearance.towards a more comprehensive global reflectance descriptor, this paper focuses on a representation of specular appearance based on an approximate specular reflection model derived from torrance-sparrow. we propose that under certain illumination and surface conditions local specular structure can be expressed by the logarithms of three intensity-normalized photometric images. the total number of photometric images needed for representing global specular appearance depends on the object surface roughness, and we suggest an illumination planning method for determining the number of images. experimental results demonstrate the effectiveness of this logarithmic model as a specular descriptor.
visual correspondence using energy minimization and mutual information. we address visual correspondence problems without assuming that scene points have similar intensities in different views. this situation is common, usually due tonon-lambertian scenes or to differences between cameras. we use maximization of mutual information, apowerful technique for registering images that requiresno apriori model of the relationship between scene intensities in different views. however, it has provendifficult to use mutual information to compute densevisual correspondence. comparing fixed-size windowsvia mutual information suffers from the well-knownproblems of fixed windows, namely poor performanceat discontinuities and in low-texture regions. in thispaper, we show how to compute visual correspondenceusing mutual information without suffering from theseproblems. using a simple approximation, mutual information can be incorporated into the standard energyminimization framework used in early vision. the energy can then be efficiently minimized using graph cuts,which preserve discontinuities and handle low-textureregions. the resulting algorithm combines the accuratedisparity maps that come from graph cuts with the tolerance for intensity changes that comes from mutual information.
estimation of diffuse and specular appearance. to account for the variability of object appearance due to differences in illumination, attention has recently been focused on representing the set of images for all possible lighting conditions. approaches that address this problem have primarily focused on lighting differences for diffuse reflection using the lambertian model; however, specular reflections can additionally present considerable disparity in appearance.we present a method for representing illumination appearance for both diffuse and specular reflections for objects of uniform surface roughness using four photometric images. this approach uses separation of reflection components, extracts surface reflectances and roughness, and produces arbitrary lighting images without explicit computation of surface shape. experimental results demonstrate the validity of the proposed method for constructing diffuse and specular appearances.
fast vehicle detection with probabilistic feature grouping and its application to vehicle tracking. generating vehicle trajectories from video data is an important application of its (intelligent transportation systems). we introduce a new tracking approach which uses model-based 3-d vehicle detection and description algorithm. our vehicle detection and description algorithm is based on a probabilistic line feature grouping, and it is faster (by up to an order of magnitude) and more flexible than previous image-based algorithms. we present the system implementation and the vehicle detection and tracking results.
opaque document imaging: building images of inaccessible texts. this paper introduces a method for building a readable image of an opaque, rolled or folded text from a volumetric, penetrating scan. the problem is framed by localizing, constructing, and manipulating an image induced by a surface embedded in a 3d voxel space. there are two central contributions that lead to the demonstrated results. first is an energy-based texture formation algorithm, which is a function of voxel intensities and the geometry of the embedded surface. second is a regularization algorithm based on a constrained mapping of the embedded surface to a regularized image plane. the mapping preserves angles and lengths, which minimizes the distortion of text in the image. the experimental results show readable images derived from custom, high resolution (x-ray-based) ct scans of rolled papyrus and ink samples. these methods are significant for scholars seeking to study inaccessible texts, and may lead to viable techniques for scanning everyday opaque objects (books) without opening them.
dynamic stroke information analysis for video-based handwritten chinese character recognition. video-based handwritten character recognition(vcr) system is a new type of character recognitionsystem with many unique advantages over on-linecharacter recognition system. its main problem is toeffectively extract stroke dynamic information fromvideo data for character recognition. in this paper, wepropose a new stroke extraction algorithm throughdynamic stroke information analysis for a vcr system.the experimental results on over 3000 video charactersequences show that our system can extract the chinesecharacter stroke dynamic information similar to an on-line system.
physics-based 3d position analysis of a soccer ball from monocular image sequences. in this paper, we propose a method for locating 3d position of a soccor ball from monocular image sequence of soccor games. toward this goal, we adopted ground-model-to-image transformation together with physics-based approach that a ball follows the parabolic trajectory in the air. by using the transformation the heights of a ball can be easily calculated using simple triangular geometric relations given the start and the end position of the ball on the ground. here the heights of a ball are determined in terms of a player's height. even if the end position of a ball is not given on the ground due to kicking or heading of a falling ball before it touches the ground, the most probable trajectory can be determined by searching based on the physical fact taht the ball follows a parabolic trajectory in the air. we have tested and experimented with a real image sequence the results of which seem promising.
coupled space learning for image style transformation. in this paper, we present a new learning framework for image style transforms. considering that the images in different style representations constitute different vector spaces, we propose a novel framework called coupled space learning to learn the relations between different spaces and use them to infer the images from one style to another style. observing that for each style, only the components correlated to the space of the target style are useful for inference, we first develop the correlative component analysis to pursue the embedded hidden subspaces that best preserve the inter-space correlation information. then we develop the coupled bidirectional transform algorithm to estimate the transforms between the two embedded spaces, where the coupling between the forward transform and the backward transform is explicitly taken into account. to enhance the capability of modelling complex data, we further develop the coupled gaussian mixture model to generalize our framework to a mixture-model architecture. the effectiveness of the framework is demonstrated in the applications including face super-resolution and bidirectional portrait style transforms.
a segmentation algorithm for contrast-enhanced images. medical imaging often involves the injection of contrast agents and the subsequent analysis of tissue enhancement patterns. many important types of tissue have characteristic enhancement patterns; for example, in magnetic resonance (mr) mammography, malignancies exhibit a characteristic "wash out" temporal pattern, while in mr angiography, arteries, veins and parenchyma each have their own distinctive temporal signature. in such image sequences, there are substantial changes in intensities; however, this change is due primarily to the contrast agent rather than the motion of scene elements. as a result, the task of segmenting contrast-enhanced images poses interesting new challenges for computer vision. in this paper, we propose a new image segmentation algorithm for image sequences with contrast enhancement, using a model-based time series analysis of individual pixels. we use energy minimization via graph cuts to efficiently ensure spatial coherence. the energy is minimized in an expectation-maximization fashion that alternates between segmenting the image into a number of non-overlapping regions and finding the temporal profile parameters which best describe the behavior of each region. preliminary experiments on mr mammography and mr angiography studies show the algorithm's ability to find an accurate segmentation.
direct estimation of affine image deformations using visual front-end operations with automatic scale selection. this article deals with the problem of estimating deformations of brightness patterns using visual front-end operations. estimating such deformations constitutes an important subtask in several computer vision problems relating to image correspondence and shape estimation. the following subjects are treated: the problem of decomposing affine flow fields into simpler components is analysed in detail. a canonical parametrization is presented based on singular value decomposition, which naturally separates the rotationally invariant components of the flow field from the rotationally variant ones. a novel mechanism is presented for automatic selection of scale levels when estimating local affine deformations. this mechanism is expressed within a multiscale framework where disparity estimates are computed in a hierarchical coarse-to-fine manner and corrected using iterative techniques. then, deformation estimates are selected from the scales that minimize a certain normalized residual over scales. finally, the descriptors so obtained serve as initial data for computing refined estimates of the local deformations.
robotic control with partial visual information. we consider a class of control tasks, which rely from partial visual information in a robotic setting. these tasks are hard in the sense that at every given moment, the available information is insufficient for the control task. still, the amount of information collected throughout the control process is large and thus seems sufficient for carrying out the task.such situations commonly arise when the object is frequently occluded from one of the cameras in a stereo pair or when only one moving camera is available.we propose a generic contr ol rule for such tasks and characterize the conditions required for the success of the task. the analysis is based on the observation that mathematically, the behavior of such systems is related to a class of row-action (and pocs) optimization algorithms.in the second part of the paper we focus on one particular task from this class: position and orientation control with a single rotating camera. we show that this task may be carried out, in principle, for any camera movement, and suggest efficient control strategy and camera moving strategy. interestingly, it seems that the advisable control law is not consistent withsimple-minded intuition. we substantiate our claims by simulations and experiments on real data.
deformation invariant image matching. we propose a novel framework to build descriptors of local intensity that are invariant to general deformations. in this framework, an image is embedded as a 2d surface in 3d space, with intensity weighted relative to distance in x-y. we show that as this weight increases, geodesic distances on the embedded surface are less affected by image deformations. in the limit, distances are deformation invariant. we use geodesic sampling to get neighborhood samples for interest points, then use a geodesic-intensity histogram (gih) as a deformation invariant local descriptor. in addition to its invariance, the new descriptor automatically finds its support region. this means it can safely gather information from a large neighborhood to improve discriminability. furthermore, we propose a matching method for this descriptor that is invariant to affine lighting changes. we have tested this new descriptor on interest point matching for two data sets, one with synthetic deformation and lighting change, another with real non-affine deformations. our method shows promising matching results compared to several other approaches.
representation and self-similarity of shapes. representing shapes is a significant problem for vision systems that must recognize or classify objects. we derive a representation for a given shape by investigating its self-similarities, and constructing its shape axis(sa) and shape axis tree (sa-tree).we start with a shape, its boundary contour, and two different parameterizations for the contour. to measure its self-similarity we consider matching pairs of points (and their tangents) along the boundary contour, i.e., matching the two parameterizations. the matching, or self-similarity criteria may vary, e.g., co-circularity, parallelism, distance, region homogeneity. the loci of middle points of the pairing contour points are the shape axis and they can be grouped into a unique tree graph, the sa-tree. the shape axis for the co-circularity criteria is compared to the symmetry axis. an interpretation in terms of object parts is also presented.
towards a unified iu environment: coordination of existing iu tools with the iue. progress in the field of computer vision/image understanding (iu) has long been hampered by the lack of standard software environments for research and application development. the image understanding environment (iue) is being implemented to provide a freely-distributed standard software environment that is appropriate for a wide range of research and development activities. nevertheless, we recognize that the iue will not serve everyone's individual needs and that conversion to the iue could be an expensive process for many sites. therefore, we are investing significant effort to make the iue an open environment that can work in coordination with existing iu systems and tools. this paper introduces the work being performed at amerinex ai to address the processing and data representation factors involved in this coordination.
effciently solving dynamic markov random fields using graph cuts. in this paper we present a fast new fully dynamic algorithm for the st-mincut/max-flow problem. we show how this algorithm can be used to efficiently compute map estimates for dynamically changing mrf models of labelling problems in computer vision, such as image segmentation. specifically, given the solution of the max-flow problem on a graph, we show how to efficiently compute the maximum flow in a modified version of the graph. our experiments showed that the time taken by our algorithm is roughly proportional to the number of edges whose weights were different in the two graphs. we test the performance of our algorithmon one particular problem: the object-background segmentation problem for video and compare it with the best known st-mincut algorithm. the results show that the dynamic graph cut algorithm is much faster than its static counterpart and enables real time image segmentation. it should be noted that our method is generic and can be used to yield similar improvements in many other cases that involve dynamic change in the graph.
finding periodicity in space and time. an algorithm for simultaneous detection, segmentation, and characterization of spatiotemporal periodicity is presented. the use of periodicity templates is proposed to localize and characterize temporal activities. the templates not only indicate the presence and location of a periodic event, but also give an accurate quantitative periodicity measure. hence, they can be used as a new means of periodicity representation. the proposed algorithm can also be considered as a "periodicity filter" a low-level model of periodicity perception. the algorithm is computationally simple, and shown to be more robust than optical flow based techniques in the presence of noise. a variety of real-world examples are used to demonstrate the performance of the algorithm.
an expectation maximization approach to the synergy between image segmentation and object categorization. in this work we deal with the problem of modelling and exploiting the interaction between the processes of image segmentation and object categorization. we propose a novel framework to address this problem that is based on the combination of the expectation maximization (em) algorithm and generative models for object categories. using a concise formulation of the interaction between these two processes, segmentation is interpreted as the e step, assigning observations to models, whereas object detection/analysis is modelled as the m-step, fitting models to observations. we present in detail the segmentation and detection processes comprising the e and m steps and demonstrate results on the joint detection and segmentation of the object categories of faces and cars.
region segmentation via deformable model-guided split and merge. abstract an improved method for deformable shape-based image segmentation is described. image regions are merged together and/or split apart, based on their agreement with an a priori distribution on the global deformation parameters for a shape template. the quality of a candidate region merging is evaluated by a cost measure that includes: homogeneity of image properties within the combined region, degree of overlap with a deformed shape model, and a deformation likelihood term. perceptually-motivated criteria are used to determine where/how to split regions, based on the local shape properties of the region group''s bounding contour. a globally consistent interpretation is determined in part by the minimum description length principle. experiments show that the model-based splitting strategy yields a significant improvement in segmention over a method that uses merging alone.
3d pose estimation by fitting image gradients directly to polyhedral models. addresses the problem of pose estimation and tracking of vehicles in image sequences from traffic scenes recorded by a stationary camera. in a new algorithm, the vehicle pose is estimated by directly fitting image gradients to polyhedral vehicle models without an edge segment extraction process. the new approach is significantly more robust than approaches that rely on feature extraction because the new approach exploits more information from the image data. we can track vehicles that are partially occluded by textured objects, e.g. foliage, where classical approaches based on edge segment extraction fail. results from various experiments with real-world traffic scenes are presented.
meshfree particle method. many of the computer vision algorithms have been posed invarious forms of differential equations, derived from minimization of specific energy functionals, and the finite element representation and computation have become the de facto numerical strategies for solving these problems. however, for cases where domain mappings between numerical iterations or image frames involve large geometrical shape changes, such as deformable models for object segmentation and non rigid motion tracking, these strategies may exhibit considerable loss of accuracy when themesh elements become extremely skewed or compressed. we present a new computational paradigm, the meshfree particle method, where the object representation and the numerical calculation are purely based on the nodal points and do not require the meshing of the analysis domain. this meshfree strategy can naturally handle large deformation and domain discontinuity issues and achieve desired numerical accuracy through adaptive node and polynomial shape function refinement. we discuss in detail the element-free galerkin method, including the shape function construction using the moving least square approximation and the galerkin weak form formulation, and we demonstrate its applications to deformable model based segmentation and mechanically motivated left ventricular motion analysis.
what metrics can be approximated by geo-cuts, or global optimization of length/area and flux. in [3] we showed that graph cuts can find hyper-surfaces of globally minimal length (or area) under any riemannian metric. here we show that graph cuts on directed regular grids can approximate a significantly more general class of continuous non-symmetric metrics. using submodularity condition [1, 11], we obtain a tight characterization of graph-representable metrics. such "submodular" metrics have an elegant geometric interpretation via hyper-surface functionals combining length/area and flux. practically speaking, we extend "geo-cuts" algorithm [3] to a wider class of geometrically motivated hypersurface functionals and show how to globally optimize any combination of length/area and flux of a given vector field. the concept of flux was recently introduced into computer vision by [13] but it was mainly studied within variational framework so far. we are first to show that flux can be integrated into graph cuts as well. combining geometric concepts of flux and length/area within the global optimization framework of graph cuts allows principled discrete segmentation models and advances the state of the art for the graph cuts methods in vision. in particular, we address the "shrinking" problem of graph cuts, improve segmentation of long thin objects, and introduce useful shape constraints.
computing visual correspondence with occlusions via graph cuts. several new algorithms for visual correspondence based on graph cuts have recently been developed. while these methods give very strong results in practice, they do not handle occlusions properly. specifically, they treat the two input images asymmetrically, and they do not ensure that a pixel corresponds to at most one pixel in the other image. in this paper, we present two new methods which properly address occlusions, while preserving the advantages of graph cut algorithms. we give experimental results for stereo as well as motion, which demonstrate that our methods perform well both at detecting occlusions and computing disparities.
a new framework for approximate labeling via graph cuts. a new framework is presented that uses tools from duality theory of linear programming to derive graph-cut based combinatorial algorithms for approximating np-hard classification problems. the derived algorithms include ¿-expansion graph cut techniques merely as a special case, have guaranteed optimality properties even in cases where á-expansion techniques fail to do so and can provide very tight per-instance suboptimality bounds in all occasions.
gabor wavelets for 3-d object recognition. this paper presents a model-based object recognition approach that uses a hierarchical gabor wavelet representation. the key idea is to use magnitude, phase and frequency measures of gabor wavelet representation in an innovative flexible matching approach that can provide robust recognition. a gabor grid a topology-preserving map, efficiently encodes both signal energy and structural information of an object in a sparse multi-resolution representation. the gabor grid subsamples the gabor wavelet decomposition of an object model and is deformed to allow the indexed object model match with the image data. flexible matching between the model and the image minimizes a cost function based on local similarity and geometric distortion of the gabor grid. grid erosion and repairing is performed whenever a collapsed grid, due to object occlusion, is detected. the results on infrared imagery are presented. where objects undergo rotation, translation, scale, occlusion and aspect variations under changing environmental conditions.
multi-view aam fitting and camera calibration. in this paper we study the relationship between multiview active appearance model (aam) fitting and camera calibration. in the first part of the paper we propose an algorithm to calibrate the relative orientation of a set of n > 1 cameras by fitting an aam to sets of n images. in essence, we use the human face as a (non-rigid) calibration grid. our algorithm calibrates a set of 2 × 3 weak-perspective camera projection matrices, projections of the world coordinate system origin into the images, depths of the world coordinate system origin, and focal lengths. we demonstrate that the performance of this algorithm is comparable to a standard algorithm using a calibration grid. in the second part of the paper we show how calibrating the cameras improves the performance of multi-view aam fitting.
a multilevel banded graph cuts method for fast image segmentation. in the short time since publication of boykov and jolly¿s seminal paper [3], graph cuts have become well established as a leading method in 2d and 3d semi-automated image segmentation. although this approach is computationally feasible for many tasks, the memory overhead and supralinear time complexity of leading algorithms results in an excessive computational burden for high-resolution data. in this paper, we introduce a multilevel banded heuristic for computation of graph cuts that is motivated by the well-known narrow band algorithm in level set computation. we perform a number of numerical experiments to show that this heuristic drastically reduces both the running time and the memory consumption of graph cuts while producing nearly the same segmentation result as the conventional graph cuts. additionally, we are able to characterize the type of segmentation target for which our multilevel banded heuristic will yield different results from the conventional graph cuts. the proposed method has been applied to both 2d and 3d images with promising results.
integrated edge and junction detection with the boundary tensor. the boundaries of image regions necessarily consist of edges (in particular, step and roof edges), corners, and junctions. currently, different algorithms are used to detect each boundary type separately, but the integration of the results into a single boundary representation is difficult. therefore, a method for the simultaneous detection of all boundary types is needed. we propose to combine responses of suitable polar separable filters into what we will call the boundary tensor. the trace of this tensor is a measure of boundary strength, while the small eigenvalue and its difference to the large one represent corner / junction and edge strengths respectively. we prove that the edge strength measure behaves like a rotationally invariant quadrature filter. a number of examples demonstrate the properties of the new method and illustrate its application to image segmentation.
is levenberg-marquardt the most efficient optimization algorithm for implementing bundle adjustment?. in order to obtain optimal 3d structure and viewing parameter estimates, bundle adjustment is often used as the last step of feature-based structure and motion estimation algorithms. bundle adjustment involves the formulation of a large scale, yet sparse minimization problem, which is traditionally solved using a sparse variant of the levenberg- marquardt optimization algorithm that avoids storing and operating on zero entries. this paper argues that considerable computational benefits can be gained by substituting the sparse levenberg-marquardt algorithm in the implementation of bundle adjustment with a sparse variant of powell¿s dog leg non-linear least squares technique. detailed comparative experimental results provide strong evidence supporting this claim.
shapelets correlated with surface normals produce surfaces. this paper addresses the problem of deducing the surface shape of an object given just the surface normals. many shape measurement algorithms such as shape from shading and shape from texture only return the surface normals of an object, often with an ambiguity of ¿ in the surface tilt. the surface shape has to be inferred from these normals, typically via some integration process. however, reconstruction through the integration of surface gradients is sensitive to noise and the choice of integration paths across the surface. in addition, existing techniques cannot accommodate ambiguities in tilt. this paper presents a new approach to the reconstruction of surfaces from surface normals using basis functions, referred to here as shapelets. the surface gradients of the shapelets are correlated with the gradients of the surface and the correlations summed to form the reconstruction. this results in a simple reconstruction process that is very robust to noise. where there is an ambiguity of ¿ in the surface tilt, reconstructions of reduced quality are still possible up to a positive/negative shape ambiguity. intriguingly, some form of reconstruction is also possible using just slant information.
appearance modeling under geometric context. we propose a unified framework based on a general definition of geometric transform (get) for modeling appearance. get represents the appearance by applying designed functionals over certain geometric sets. we show that image warping, radon transform, trace transform, etc. are special cases of our definition. moreover, three different types of gets are designed to handle deformation, articulation and occlusion and applied to fingerprinting the appearance inside a contour. they include the contour-driven get, the feature curve based get and selecting functionals to model the appearance inside the convex hull of the contour. a multi-resolution representation that combines both shape and appearance information is also proposed. we apply our approach to image synthesis and object recognition. the proposed approach produces promising results when applied to fingerprinting the appearance of human and body parts despite the challenges due to articulated motion and deformations.
combining gradient and albedo data for rotation invariant classification of 3d surface texture. we present a new texture classification scheme whichis invariant to surface-rotation. many textureclassification approaches have been presented in the pastthat are image-rotation invariant, however, imagerotation is not necessarily the same as surface rotation.we have therefore developed a classifier that usesinvariants that are derived from surface properties ratherthan image properties. previously we developed ascheme that used surface gradient (normal) fieldsestimated using photometric stereo. in this paper weaugment these data with albedo information and an alsoemploy an additional feature set: the radial spectrum.we used 30 real textures to test the new classifier. aclassification accuracy of 91% was achieved whenalbedo and gradient 1d polar and radial features werecombined. the best performance was also achieved byusing 2d albedo and gradient spectra. the classificationaccuracy is 99%.
bayesian autocalibration for surveillance. in the context of visual surveillance of human activity, knowledge about a camera¿s internal and external parameters is useful, as it allows for the establishment of a connection between image and world measurements. unfortunately, calibration information is rarely available and difficult to obtain after a surveillance system has been installed. in this paper a method for camera autocalibration based on information gathered by tracking people is developed. it brings two main contributions: first, we show how a foot-to-head plane homology can be used to obtain the calibration parameters and then we show an approach how to efficiently estimate initial parameter estimates from measurements; second, we present a bayesian solution to the calibration problem that can elegantly handle measurement uncertainties, outliers, as well as prior information. it is shown how the full posterior distribution of calibration parameters given the measurements can be estimated, which allows making statements about the accuracy of both the calibration parameters and the measurements involving them.
independent 3d motion detection using residual parallax normal flow fields. this paper considers a specific problem of visual perception of motion, namely the problem of visual detection of independent 3d motion. most of the existing techniques for solving this problem rely on restrictive assumptions about the environment, the observer's motion, or both. moreover, they are based on the computation of a dense optical flow field, which amounts to solving the ill-posed correspondence problem. in this work, independent motion detection is formulated as a problem of robust parameter estimation applied to the visual input acquired by a rigidly moving observer. the proposed method automatically selects a planar surface in the scene and the residual planar parallax normal flow field with respect to the motion of this surface is computed at two successive time instants. the two resulting normal flow field are then combined in a linear model. the parameters of this model are related to the parameters of self-motion (ego-motion) and their robust estimation leads to a segmentation of the scene based on 3d motion. the method avoids a complete solution to the correspondence problem by selectively matching subsets of image points and by employing normal flow fields. experimental results demonstratethe effectiveness of the proposed method in detecting independent motion in scenes with large depth variations and unrestrited observer motion.
a task driven 3d object recognition system using bayesian networks. in this paper we propose a general framework to build a task oriented 3d object recognition system for cad based vision (cbv). features from 3d space curves representing the object's rims provide sufficient information to allow identification and pose estimation of industrial cad models. however, features relying on differential surface properties tend to be very vulnerable with respect to noise. to model the statistical behavior of the data we introduce bayesian netswhich model the relationship between objects and observable features. furthermore, task oriented selection of the optimal action to reduce the uncertainty of recognition results is incorporated into the bayesian nets. this enables the integration of intelligent recognition strategies depending on the already acquired evidence into a robust, and effcient, 3d cad based recognition system.
object recognition from local scale-invariant features. an object recognition system has been developed that uses a new class of local image features. the features are invariant to image scaling, translation, and rotation, and partially invariant to illumination changes and affine or 3d projection.these features share similar properties with neurons in inferior temporal cortex that are used for object recognition in primate vision. features are efficiently detected through a staged filtering approach that identifies stable points in scale space. image keys are created that allow for local geometric deformations by representing blurred image gradients in multiple orientation planes and at multiple scales.the keys are used as input to a nearest-neighbor indexing method that identifies candidate object matches. final verification of each match is achieved by finding a low-residual least-squares solution for the unknown model parameters. experimental results show that robust object recognition can be achieved in cluttered partially-occluded images with a computation time of under 2 seconds.
texture segmentation and shape in the same image. uniformly textured surfaces in 3d scenes provide important cues for image understanding. texture can be used for both segmentation and for 3d shape inference. unfortunately, virtually all current algorithms are based on assumptions that make it impossible to do texture segmentation and shape-from-texture in the same image. texture segmentation algorithms rely on an absence of 3d effects that tend to distort the texture. shape-from-texture algorithms depend on these effects, relying instead on the texture being already segmented. to really understand texture in images, texture segmentation and shape-from-texture must be viewed as a combined problem to be solved simultaneously. we present a solution to this problem with a region-growing algorithm that explicitly accounts for perspective distortions of otherwise uniform texture. we use the image spectrogram to compute local surface normals, which are in turn used to "frontalize" the texture. these frontalized texture patches are then subjected to a region-growing algorithm based on similarity in the local frequency domain and a minimum description length criteria. we show results of our algorithm on real texture images taken in the lab and outdoors.
vision based hand modeling and tracking for virtual teleconferencing and telecollaboration. the authors present a hand model that simultaneously satisfies both the synthesis and analysis requirements of model based compression. the model can be fitted to any person's hand and can be done using a single camera. once the model is fitted to a real human hand, it is then used in several tracking scenarios in order to verify its effectiveness. with successful tracking achieved, the model is ready to be incorporated into a virtual environment or model based compression scheme such as sign language communication over telephone lines or virtual teleconferences over computer networks at very low bit rates and at very high image quality.
reflectance function estimation and shape recovery from image sequence of a rotating object. we describe a technique for surface recovery of a rotating object illuminated under a collinear light source (where the light source lies on or near the optical axis). we show that the surface reflectance function can be directly estimated from the image sequence without any assumption on the reflectance property of the object surface. from the image sequence, the 3d locations of some singular surface points are calculated and their brightness values are extracted for the estimation of the reflectance function. we also show that the surface can be recovered by using shading information in two images of the rotating object. iteratively using the first-order taylor series approximation and the estimated reflectance function, the depth and orientation of the surface can be recovered simultaneously. the experimental results on real image sequences of both matte and specular surfaces demonstrate that the technique is feasible and robust.
discriminative random fields: a discriminative framework for contextual interaction in classification. in this work we present discriminative random fields(drfs), a discriminative framework for the classification ofimage regions by incorporating neighborhood interactionsin the labels as well as the observed data. the discriminativerandom fields offer several advantages over the conventionalmarkov random field (mrf) framework. first,the drfs allow to relax the strong assumption of conditionalindependence of the observed data generally used inthe mrf framework for tractability. this assumption is toorestrictive for a large number of applications in vision. second,the drfs derive their classification power by exploitingthe probabilistic discriminative models instead of thegenerative models used in the mrf framework. finally, allthe parameters in the drf model are estimated simultaneouslyfrom the training data unlike the mrf frameworkwhere likelihood parameters are usually learned separatelyfrom the field parameters. we illustrate the advantages ofthe drfs over the mrf framework in an application ofman-made structure detection in natural images taken fromthe corel database.
a hierarchical field framework for unified context-based classification. we present a two-layer hierarchical formulation to exploit different levels of contextual information in images for robust classification. each layer is modeled as a conditional field that allows one to capture arbitrary observation-dependent label interactions. the proposed framework has two main advantages. first, it encodes both the short-range interactions (e.g., pixelwise label smoothing) as well as the long-range interactions (e.g., relative configurations of objects or regions) in a tractable manner. second, the formulation is general enough to be applied to different domains ranging from pixelwise image labeling to contextual object detection. the parameters of the model are learned using a sequential maximum-likelihood approximation. the benefits of the proposed framework are demonstrated on four different datasets and comparison results are presented.
an integrated stereo-based approach to automatic vehicle guidance. proposes a new approach for vision-based longitudinal and lateral vehicle control. the novel feature of this approach is the use of binocular vision. we integrate two modules consisting of a new, domain-specific, efficient binocular stereo algorithm, and a lane marker detection algorithm, and show that the integration results in a improved performance for each of the modules. longitudinal control is supported by detecting and measuring the distances to leading vehicles using binocular stereo. the knowledge of the camera geometry with respect to the locally planar road is used to map the images of the road plane in the two camera views into alignment. this allows us to separate image features into those lying in the road plane, e.g. lane markers, and those due to other objects which are dynamically integrated into an obstacle map. therefore, in contrast with the previous work, we can cope with the difficulties arising from occlusion of lane markers by other vehicles. the detection and measurement of the lane markers provides us with the positional parameters and the road curvature which are needed for lateral vehicle control. moreover, this information is also used to update the camera geometry with respect to the road, therefore allowing us to cope with the problem of vibrations and road inclination to obtain consistent results from binocular stereo.
learning layered motion segmentation of video. we present an unsupervised approach for learning a layered representation of a scene from a video for motion segmentation. our method is applicable to any video containing piecewise parametric motion. the learnt model is a composition of layers, which consist of one or more segments. the shape of each segment is represented using a binary matte and its appearance is given by the rgb value for each point belonging to the matte. included in the model are the effects of image projection, lighting, and motion blur. furthermore, spatial continuity is explicitly modeled resulting in contiguous segments. unlike previous approaches, our method does not use reference frame(s) for initialization. the two main contributions of our method are: (i) a novel algorithm for obtaining the initial estimate of the model by dividing the scene into rigidly moving components using efficient loopy belief propagation; and (ii) refining the initial estimate using ¿ β-swap and ¿-expansion algorithms, which guarantee a strong local minima. results are presented on several classes of objects with different types of camera motion, e.g. videos of a human walking shot with static or translating cameras. we compare our method with the state of the art and demonstrate significant improvements.
affine surface reconstruction by purposive viewpoint control. we present an approach for building an affine representation of an unknown curved object viewed under orthographic projection from images of its occluding contour. it is based on the observation that the projection of a point on a curved, featureless surface can be computed along a special viewing direction that does not belong to the point's tangent plane. we show that by circumnavigating the object on the tangent plane of selected surface points, we can (1) compute two orthogonal projections of every point projecting to the occluding contour during this motion, and (2) compute the affine coordinates of these points. our approach demonstrates that affine shape of curved objects can be computed directly, i.e., without euclidean calibration or image velocity and acceleration measurements.
edge-based rich representation for vehicle classification. in this paper we propose an approach to vehicle classification under a mid-field surveillance framework. we develop a repeatable and discriminative feature based on edge points and modified sift descriptors, and introduce a rich representation for object classes. experimental results show the proposed approach is promising for vehicle classification in surveillance videos despite great challenges such as limited image size and quality and large intra-class variations. comparisons demonstrate the proposed approach outperforms other methods.
geometric invariants and applications under catadioptric camera model. this paper presents geometric invariants of points and their applications under central catadioptric camera model. although the image has severe distortions under the model, we establish some accurate projective geometric invariants of scene points and their image points. these invariants, being functions of principal point, are useful, from which a method for calibrating the camera principal point and a method for recovering planar scene structures are proposed. the main advantage of using these invariants for plane reconstruction is that neither camera motion nor the intrinsic parameters, except for the principal point, is needed. the theoretical correctness of the established invariants and robustness of the proposed methods are demonstrated by experiments. in addition, our results are found to be applicable to some more general camera models other than the catadioptric one.
a theory of refractive and specular 3d shape by light-path triangulation. we investigate the feasibility of reconstructing an arbitrarily-shaped specular scene (refractive or mirror-like) from one or more viewpoints. by reducing shape recovery to the problem of reconstructing individual 3d light paths that cross the image plane, we obtain three key results. first, we show how to compute the depth map of a specular scene from a single viewpoint, when the scene redirects incoming light just once. second, for scenes where incoming light undergoes two refractions or reflections, we show that three viewpoints are sufficient to enable reconstruction in the general case. third, we show that it is impossible to reconstruct individual light paths when light is redirected more than twice. our analysis assumes that, for every point on the image plane, we know at least one 3d point on its light path. this leads to reconstruction algorithms that rely on an "environment matting" procedure to establish pixel-to-point correspondences along a light path. preliminary results for a variety of scenes (mirror, glass, etc.) are also presented.
euclidean reconstruction and reprojection up to subgroups. the necessary and sufficient conditions for being able to estimate scene structure, motion and camera calibration from a sequence of images are very rarely satisfied in practice. what exactly can be estimated in sequences of practical importance, when such conditions are not satisfied? in this paper we give a complete answer to this question. for every camera motion that fails to meet the conditions, we give explicit formulas for the ambiguities in the reconstructed scene, motion and calibration. such a characterization is crucial both for designing robust estimation algorithms (that do not try to recover parameters that cannot be recovered), and for generating novel views of the scene by controlling the vantage point. to this end, we characterize explicitly all the vantage points that give rise to a valid euclidean reprojection regardless of the ambiguity in the reconstruction. we also characterize vantage points that generate views that are altogether invariant to the ambiguity. all the results are presented using simple notation that involves no tensors nor complex projective geometry, and should be accessible with basic background in linear algebra.
a theory of shape by space carving. in this paper we consider the problem of computing the 3d shape of an unknown, arbitrarily-shaped scene from multiple photographs taken at known but arbitrarily-distributed viewpoints. by studying the equivalence class of all 3d shapes that reproduce the input photographs, we prove the existence of a special member of this class, the photo hull, that (1) can be computed directly from photographs of the scene, and (2) subsumes all other members of this class. we then give a provably-correct algorithm, called space carving, for computing this shape and present experimental results on complex real-world scenes. the approach is designed to (1) capture photorealistic shapes that accurately model scene appearance from a wide range of viewpoints, and (2) account for the complex interactions between occlusion, parallax, shading, and their view-dependent effects on scene-appearance.
a probabilistic contour discriminant for object localisation. a method of localising objects in images is proposed. possible configurations are evaluated using the contour discriminant, a likelihood ratio which is derived from a probabilistic model of the feature detection process. we treat each step in this process probabilistically, including the occurrence of clutter features, and derive the observation densities for both correct "target" configurations and incorrect "clutter" configurations. the contour discriminant distinguishes target objects from the background even in heavy clutter, making only the most general assumptions about the form that clutter might take. the method generates samples stochastically to avoid the cost of processing an entire image, and promises to be particularly suited to the task of initialising contour trackers based on sampling methods.
hierarchical statistical models for the fusion of multiresolution image data. this paper presents a class of nonlinear hierarchical algorithms for the fusion of multiresolution image data in low-level vision. the approach combines nonlinear causal markov models defined on hierarchical graph structures, with standard bayesian estimation theory. two random processes defined on simple hierarchical graphs (quadtrees or "ternary graphs") are introduced to represent the multiresolution observations at hand and the hidden labels to be estimated. an optimal algorithm (inspired from the viterbi algorithm) is developed to compute the bayesian estimates on the hierarchical graph structures. estimates are obtained within two passes on the graph structure. this algorithm is non-iterative and yields a per pixel computational complexity which is independent of image size. this approach is compared to the multiscale algorithm proposed by (bouman et al., 1994) for single-resolution image segmentation (that we have extended for multiresolution data fusion).
a probabilistic exclusion principle for tracking multiple objects. tracking multiple targets is a challenging problem, especially when the targets are &ldquo;identical&rdquo;, in the sense that the same model is used to describe each target. in this case, simply instantiating several independent 1-body trackers is not an adequate solution, because the independent trackers tend to coalesce onto the best-fitting target. this paper presents an observation density for tracking which solves this problem by exhibiting a probabilistic exclusion principle. exclusion arises naturally from a systematic derivation of the observation density, without relying on heuristics. another important contribution of the paper is the presentation of partitioned sampling, a new sampling method for multiple object tracking. partitioned sampling avoids the high computational load associated with fully coupled trackers, while retaining the desirable properties of coupling.
morphological corner detection. this paper presents a new operater for corner detection. this operator uses a variant of the morphological closing operator, which we have called asymmetrical closing. it consists of the successive application of different morphological transformations using different structuring elements. each of these structuring elements used to probe the image under study is tuned to affect corners of different orientation and brightness. we found that this kind of approach, based on brightness comparisons, leads to better quality results than others and is achieved at a lower computational cost.
removal of translation bias when using subspace methods. given estimates of the motion field (optic flow) from an image sequence, it is possible to recover translational direction, ~ t , using a variety of techniques. one such technique, known as "subspace methods," generates constraints which are perpendicular to ~ t , so that two distinct constraints allow a solution for ~ t . in practice many constraints are used in a least-squares solution, but it has been observed that the recovered estimates for ~ t are biased towards the optical axis. while the cause of the bias is well known, previous attempts to remove it have been awed. this paper outlines a new method which removes the bias. the technique is simple to apply and computationally efficient.
beyond trees: common-factor models for 2d human pose recovery. tree structured models have been widely used for determining the pose of a human body, from either 2d or 3d data. while such models can effectively represent the kinematic constraints of the skeletal structure, they do not capture additional constraints such as coordination of the limbs. tree structured models thus miss an important source of information about human body pose, as limb coordination is necessary for balance while standing, walking, or running, as well as being evident in other activities such as dancing and throwing. in this paper we consider the use of undirected graphical models that augment a tree structure with latent variables in order to account for coordination between limbs. we refer to these as common-factor models, since they are constructed by using factor analysis to identify additional correlations in limb position that are not accounted for by the kinematic tree structure. these common-factor models have an underlying tree structure and thus a variant of the standard viterbi algorithm for a tree can be applied for efficient estimation. we present some experimental results contrasting common-factor models with tree models, and quantify the improvement in pose estimation for 2d image data.
surface reflectance modeling of real objects with interreflections. in mixed reality, especially in augmented virtuality which virtualizes real objects, it is important to estimate object surface reflectance properties to render the objects under arbitrary illumination conditions. though several methods have been explored to estimate the surface reflectance properties, it is still difficult to estimate surface reflectance parameters faithfully for complex objects which have non-uniform surface reflectance properties and exhibitinter reflections. this paper describes a new method for densely estimating non-uniform surface reflectance properties of real objects constructed of convex and concave surfaces with interreflections. we use registered range and surface color texture images obtained by a laser range finder. experiments show the usefulness of the proposed method.
a unified approach to coding and interpreting face images. face images are difficult to interpret because they are highly variable. sources of variability include individual appearance, 3d pose, facial expression and lighting. we describe a compact parametrised model of facial appearance which takes into account all these sources of variability. the model represents both shape and grey-level appearance and is created by performing a statistical analysis over a training set of face images. a robust multi-resolution search algorithm is used to fit the model to faces in new images. this allows the main facial features to be located and a set of shape and grey-level appearance parameters to be recovered. a good approximation to a given face can be reconstructed using less than 100 of these parameters. this representation can be used for tasks such as image coding, person identification, pose recovery, gender recognition and expression recognition. the system performs well on all the tasks listed above.
minimum risk distance measure for object recognition. the optimal distance measure for a given discrimination task under the nearest neighbor framework has been shown to be the likelihood that a pair of measurements have different class labels [5]. for implementation and efficiency considerations, the optimal distance measure was approximated by combining more elementary distance measures defined on simple feature spaces. in this paper, we address two important issues that arise in practice for such an approach:(a) what form should the elementary distance measure in each feature space take? we motivate the need to use the optimal distance measure in simple feature spaces as the elementary distance measures; such distance measures have the desirable property that they are invariant to distance-respecting transformations. (b) how do we combine the elementary distance measures? we present the precise statistical assumptions under which a linear logistic model holds exactly. we benchmark our model with three other methods on a challenging face discrimination task and show that our approach is competitive with the state of the art.
periodic motion detection and segmentation via approximate sequence alignment. a method for defecting and segmenting periodic motion is presented. we exploit periodicity as a cite and detect periodic motion in complex scenes where common methods for rnotion segmentation are likely to fail. we note that periodic motion detection can be seen as an approximate case of sequence alignment where an image sequence is matched to itself over one or more periods of time. to use this observation, we first consider alignment of two video sequences obtained by independently moving cameras. under assumption of constant translation, the fundamental matrices and the homographies are shown to be time-linear matrix functions. these dynamic quantities can be estimated by matching corresponding space-time points with similar local motion and shape. for periodic motion, we match corresponding points across periods and develop a ransac procedure to simultaneously estimate the period and the dynamic geometric transformations between periodic views. using this method, we demonstrate detection and segmentation of human periodic motion in complex scenes with non-rigid backgrounds, moving camera and motion parallax.
segmentation of salient closed contours from real images. using a saliency measure based on the global property of contour closure, we have developed a method that reliably segments out salient contours bounding unknown objects from real edge images. the measure also incorporates the gestalt principles of proximity and smooth continuity that previous methods have exploited. unlike previous measures, we incorporate contour closure by finding the eigen-solution associated with a stochastic process that models the distribution of contours passing through edges in the scene. the segmentation algorithm utilizes the saliency measure to identify multiple closed contours by finding strongly- connected components on an induced graph. the determination of strongly connected components is a direct consequence of the property of closure. we report for the first time, results on large real images for which segmentation takes an average of about 10 secs per object on a general-purpose workstation. the segmentation is made efficient for such large images by exploiting the inherent symmetry in the task.
space-time interest points. local image features or interest points provide compact and abstract representations of patterns in an image. in this paper, we propose to extend the notion of spatial interest points into the spatio-temporal domain and show how the resulting features often reflect interesting events that can be used for a compact representation of video data as well as for its interpretation. to detect spatio-temporal events, we build on the idea of the harris and f&ouml;rstner interest point operators and detect local structures in space-time where the image values have significant local variations in both space and time. we then estimate the spatio-temporal extents of the detected events and compute their scale-invariant spatio-temporal descriptors. using such descriptors, we classify events and construct video representation in terms of labeled space-time points. for the problem of human motion analysis, we illustrate how the proposed method allows for detection of walking people in scenes with occlusions and dynamic back-grounds.
geotensity: combining motion and lighting for 3d surface reconstruction. this paper is about automatically reconstructing the full 3d surface of an object observed in motion by a single static camera. we introduce the geotensity constraint that governs the relationship between four images of a moving object under fairly general lighting conditions. we show that it is possible in theory to solve for 3d surface structure for both the case of a single point light source and a pair of point light sources and propose that a solution exists for an arbitrary number point light sources. the surface may or may not be textured. we then give an example of automatic surface reconstruction of a face under a point light source. the geotensity constraint provides the theoretical foundation for the full automatic 3d reconstruction of lambertian objects using a single fixed camera and arbitrary unknown object motion under arbitrary lighting conditions.
textons, contours and regions: cue integration in image segmentation. this paper makes two contributions. it provides (1) an operational definition of textons, the putative elementary units of texture perception, and (2) an algorithm for partitioning the image into disjoint regions of coherent bright-ness and texture, where boundaries of regions are defined by peaks in contour orientation energy and differences in texton densities across the contour.julesz introduced the term texton, analogous to a phoneme in speech recognition, but did not provide an operational definition for gray-level images. here we re-invent textons as frequently co-occurring combinations of oriented linear filter outputs. these can be learned using a k-means approach. by mapping each pixel to its nearest texton, the image can be analyzed into texton channels, each of which is a point set where discrete techniques such as voronoi diagrams become applicable.local histograms of texton frequencies can be used with a x2 test for significant differences to find texture boundaries. natural images contain both textured and untextured regions, so we combine this cue with that of the presence of peaks of contour energy derived from outputs of odd- and even-symmetric oriented gaussian derivative filters. each of these cues has a domain of applicability, so to facilitate cue combination we introduce a gating operator based on a statistical test for isotropy of delaunay neighbors. having obtained a local measure of how likely two nearby pixels are to belong to the same region, we use the spectral graph theoretic framework of normalized cuts to find partitions of the image into regions of coherent texture and brightness. experimental results on a wide range of images are shown.
the local projective shape of smooth surfaces and their outlines. this paper examines projectively invariant local properties of smooth curves and surfaces. oriented projective differential geometry is proposed as a theoretical framework for establishing such invariants and describing the local shape of surfaces and their outlines. this framework is applied to two problems: a projective proof of koenderink's famous characterization of convexities, concavities, and inflections of apparent contours; and the determination of the relative orientation of rim tangents at frontier points.
affine-invariant local descriptors and neighborhood statistics for texture recognition. this paper presents a framework for texture recognitionbased on local affine-invariant descriptors and their spatiallayout. at modeling time, a generative model of localdescriptors is learned from sample images using the em algorithm.the em framework allows the incorporation ofunsegmented multi-texture images into the training set. thesecond modeling step consists of gathering co-occurrencestatistics of neighboring descriptors. at recognition time,initial probabilities computed from the generative modelare refined using a relaxation step that incorporates co-occurrencestatistics. performance is evaluated on imagesof an indoor scene and pictures of wild animals.
determining wet surfaces from dry. wet surfaces are ubiquitous in our visual experience. autonomous machines with vision systems will need to identify wet surfaces from dry. wet surfaces (especially rough, absorbent ones) appear darker when wet. this paper presents the lekner and dorf (1988) model for describing the darkening caused by wetting. we explain how to use this optics model to transform intensity values of a region of an image to make that region appear wet. we also show how the model can be reversed in order to make a wet part of an image appear dry. it is also shown that this technique can be used to identify wet regions. this identification is contrasted with darkening caused by shadows. comparisons of the gray-level histograms of these real images show the validity of this approach for distinguishing wet surfaces from dry.
a maximum entropy framework for part-based texture and object recognition. this paper presents a probabilistic part-based approach for texture and object recognition. textures are represented using a part dictionary found by quantizing the appearance of scale- or affine-invariant keypoints. object classes are represented using a dictionary of composite semi-local parts, or groups of neighboring keypoints with stable and distinctive appearance and geometric layout. a discriminative maximum entropy framework is used to learn the posterior distribution of the class label given the occurrences of parts from the dictionary in the training set. experiments on two texture and two object databases demonstrate the effectiveness of this framework for visual classification.
a real-time algorithm for medical shape recovery. in this paper, we present a shape recovery technique in 2d and 3d with specific applications in visualizing and measuring anatomical shapes from medical images. this algorithm models extremely corrugated structures like the brain, is topologically adaptable, is robust, and runs in o(n logn) time where n is the total number of points in the domain. our two-stage technique is based on the level set shape recovery scheme introduced in [11, 12, 4] and the fast march ing method in [19] for computing solutions to static hamilton-jacobi equations.
learning pedestrian models for silhouette refinement. we present a model-based method for accurate extraction ofpedestrian silhouettes from video sequences. our approachis based on two assumptions, 1) there is a common appearanceto all pedestrians, and 2) each individual looks likehim/herself over a short amount of time. these assumptionsallow us to learn pedestrian models that encompassboth a pedestrian population appearance and the individualappearance variations. using our models, we are ableto produce pedestrian silhouettes that have fewer noise pixelsand missing parts. we apply our silhouette extractionapproach to the nist gait data set and show that under thegait recognition task, our model-based sulhouettes resultin much higher recognition rates than silhouettes directlyextracted from background subtraction, or any non-model-basedsmoothing schemes.
shape recovery using dynamic subdivision surfaces. a new dynamic subdivision surface model is proposed for shape recovery from 3d data sets. the model inherits the attractive properties of the catmull-clark subdivision scheme and is set in a physics-based modeling paradigm. unlike other existing methods, our model does not require a parameterized input mesh to recover shapes of arbitrary topology, allows direct manipulation of the limit surface via application of forces and provides a fast, robust, and hierarchical approach to recover complex shapes from 3d data with very few degrees of freedom (contr ol vertic es). we provide an analytic formulation and introduce the physical quantities required to develop the dynamic subdivision surface model which can be deformed by applying forces synthesized from the data. our experiments demonstrate that this new dynamic model has a promising future in shape recovery from volume and range data sets.
a bilinear illumination model for robust face recognition. we present a technique to generate an illumination subspace for arbitrary 3d faces based on the statistics of measured illuminations under variable lighting conditions from many subjects. a bilinear model based on the higher-order singular value decomposition is used to create a compact illumination subspace given arbitrary shape parameters from a parametric 3d face model. using a fitting procedure based on minimizing the distance of the input image to the dynamically changing illumination subspace, we reconstruct a shape-specific illumination subspace from a single photograph. we use the reconstructed illumination subspace in various face recognition experiments with variable lighting conditions and obtain accuracies which are very competitive with previous methods that require specific training sessions or multiple images of the subject.
stereo depth estimation: a confidence interval approach. we describe an estimation technique which, given a measurement of the depth of a target from a wide-field-of-view (wfov) stereo camera pair, produces a minimax risk fixed-size confidence interval estimate for the target depth. this work constitutes the first application to the computer vision domain of optimal fixed-size confidence-interval decision theory. the approach is evaluated in terms of theoretical capture probability and empirical capture frequency during actual experiments with a target on an optical bench. the method is compared to several other procedures including the kalman filter. the minimax approach is found to dominate all the other methods in performance. in particular, for the minimax approach, a very close agreement is achieved between theoretical capture probability and empirical capture frequency. this allows performance to be accurately predicted, greatly facilitating the system design, and delineating the tasks that may be performed with a given system.
pims and invariant parts for shape recognition. we present completely new very powerful solutions to two fundamental problems central to computer vision. 1. given data sets representing c objects to be stored in a database, and given a new data set for an object, determine the object in the database that is most like the object measured. we solve this problem through use of pims ("polynomial interpolated measures"), which is a new representation integrating implicit polynomial curves and surfaces, explicit polynomials, and discrete data sets which may be sparse. the method provides high accuracy at low computational cost. 2. given noisy 2d data along a curve (or 3d data along a surface), decompose the data into patches such that new data taken along affine transformations or euclidean transformations of the curve (or surface) can be decomposed into correponding patches. then recognition of complex or partially occluded objects can be done in terms of invariantly determined patches. we briefly outline a low computational cost image-database indexing-system based on this representation for objects having complex shape-geometry.
bayesian fusion of color and texture segmentations. in many applications one would like to use information from both color and texture features in order to segment an image. we propose a novel technique to combine "soft" segmentations computed for two or more features independently. our algorithm merges models according to a maximum descriptiveness criterion, and allows to choose any number of classes for the final grouping. this technique also allows to improve the quality of supervised classification based on one feature (e.g. color) by merging information from unsupervised segmentation based on another feature (e.g., texture.)
independent component analysis of textures. a common method for texture representation is to use the marginal probability densities over the outputs of a set of multi-orientation, multi-scale filters as a description of the texture. we propose a technique, based on independent components analysis, for choosing the set of filters that yield the most informative marginals, meaning that the product over the marginals most closely approximates the joint probability density function of the filter outputs. the algorithm is implemented using a steerable filter space. experiments involving both texture classification and synthesis show that compared to principal components analysis, ica provides superior performance for modeling of natural and synthetic textures.
a spectral technique for correspondence problems using pairwise constraints. we present an efficient spectral method for finding consistent correspondences between two sets of features. we build the adjacency matrix m of a graph whose nodes represent the potential correspondences and the weights on the links represent pairwise agreements between potential correspondences. correct assignments are likely to establish links among each other and thus form a strongly connected cluster. incorrect correspondences establish links with the other correspondences only accidentally, so they are unlikely to belong to strongly connected clusters. we recover the correct assignments based on how strongly they belong to the main cluster of m, by using the principal eigenvector ofm and imposing the mapping constraints required by the overall correspondence mapping (one-to-one or one-to-many). the experimental evaluation shows that our method is robust to outliers, accurate in terms of matching rate, while being much faster than existing methods.
recognizing surfaces using three-dimensional textons. we study the recognition of surfaces made from different materials such as concrete, rug, marble or leather on the basis of their textural appearance. such natural textures arise from spatial variation of two surface attributes: (1) reflectance and (2) surface normal. in this paper, we provide a unified model to address both these aspects of natural texture. the main idea is to construct a vocabulary of prototype tiny surface patches with associated local geometric and photometric properties. we call these 3d textons. examples might be ridges, grooves, spots or stripes or combinations thereof. associated with each texton is an appearance vector, which characterizes the local irradiance distribution, represented as a set of linear gaussian derivative filter outputs, under different lighting and viewing conditions.given a large collection of images of different materials, a clustering approach is used to acquire a small (on the order of 100) 3d texton vocabulary. given a few (1 to 4) images of any material, it can be characterized using these textons. we demonstrate the application of this representation for recognition of the material viewed under novel lighting and viewing conditions.
control in a 3d reconstruction system using selective perception. this paper presents a control structure for general purpose image understanding that addresses both the high level of uncertainty in local hypotheses and the computational complexity of image interpretation. the control of vision algorithms is performed by an independent subsystem that uses bayesian networks and utility theory to compute the marginal value of information provided by alternative operators and selects the ones with the highest value.we have implemented and tested this control structure with several aerial image data-sets. the results show that the knowledge base used by the system can be acquired using standard learning techniques and that the value-driven approach to the selection of vision algorithms leads to performance gains. moreover, the modular system architecture simplifies the addition of both control knowledge and new vision algorithms.
adaptive enhancement of cardiac magnetic resonance (cmr) images. this paper presents a wavelet-based framework for enhancing the coherent structures attributable to the target organ in cardiac magnetic resonance (mr) images. previous approaches focus on the rician nature of noise in magnitude mr images. image noise is but only one of the confounding factors that obscure the anatomical structures of the target organ. this paper models the image noise in a magnitude mr image in terms of two noise classes which occur over different ranges of signal intensity. an adaptive enhancement scheme is developed to achieve simultaneous attenuation of the effects of these factors and improvement in image contrast.
a probabilistic framework for edge detection and scale selection. we devise a statistical framework for edge detection by performing a statistical analysis of zero crossings of the second derivative of an image. this analysis enables us to estimate at each pixel of an image the probability that an edge passes through the pixel. we present a statistical analysis of the lindeberg operators that we use to compute image derivatives. we also introduce a confidence probability that tells us how reliable the edge probability is, given the image's noise level and the operator's scale. combining the edge and confidence probabilities leads to a probabilistic scale selection algorithm. we present the results of experiments on natural images.
unsupervised improvement of visual detectors using co-training. one significant challenge in the construction of visualdetection systems is the acquisition of sufficient labeleddata. this paper describes a new technique for trainingvisual detectors which requires only a small quantity of labeleddata, and then uses unlabeled data to improve performanceover time. unsupervised improvement is based onthe co-training framework of blum and mitchell, in whichtwo disparate classifiers are trained simultaneously. unlabeledexamples which are confidently labeled by one classifierare added, with labels, to the training set of the otherclassifier. experiments are presented on the realistic task ofautomobile detection in roadway surveillance video. in thisapplication, co-training reduces the false positive rate by afactor of 2 to 11 from the classifier trained with labeled dataalone.
learning how to inpaint from global image statistics. inpainting is the problem of filling-in holes in images. considerable progress has been made by techniques that use the immediate boundary of the hole and some prior information on images to solve this problem. these algorithms successfully solve the local inpainting problem but they must, by definition, give the same completion to any two holes that have the same boundary, even when the rest of the image is vastly different. in this paper we address a different, more global inpainting problem. how can we use the rest of the image in order to learn how to inpaint? we approach this problem from the context of statistical learning. given a training image we build an exponential family distribution over images that is based on the histograms of local features. we then use this image specific distribution to in paint the hole by finding the most probable image given the boundary and the distribution. the optimization is done using loopy belief propagation. we show that our method can successfully complete holes while taking into account the specific image statistics. in particular it can give vastly different completions even when the local neighborhoods are identical.
randomized ransac with sequential probability ratio test. a randomized model verification strategy for ransac is presented. the proposed method finds, like ransac, a solution that is optimal with user-controllable probability n. a provably optimal model verification strategy is designed for the situation when the contamination of data by outliers is known, i.e. the algorithm is the fastest possible (on average) of all randomized ransac algorithms guaranteeing 1 - n confidence in the solution. the derivation of the optimality property is based on wald¿s theory of sequential decision making. the r-ransac with sprt, which does not require the a priori knowledge of the fraction of outliers and has results close to the optimal strategy, is introduced. we show experimentally that on standard test data the method is 2 to 10 times faster than the standard ransac and up to 4 times faster than previously published methods.
on representation and matching of multi-coloured objects. a new representation for objects with multiple colours-the colour adjacency graph (cag)-is proposed. each node of the cag represents a single chromatic component of the image defined as a set of pixels forming a unimodal cluster in the chromatic scattergram. edges encode information about adjacency of colour components and their reflectance ratio. the cag is related to both the histogram and region adjacency graph representations. it is shown to be preserving and combining the best features of these two approaches while avoiding their drawbacks. the proposed approach is tested on a range of difficult object recognition and localisation problems involving complex imagery of non-rigid 3d objects under varied viewing conditions with excellent results.
surface reconstruction by integrating 3d and 2d data of multiple views. surface representation is needed for almost all modelingand visualization applications, but unfortunately, 3d datafrom a passive vision system are often insufficient for a traditionalsurface reconstruction technique that is designedfor densely scanned 3d point data. in this paper, we developa new method for surface reconstruction by combiningboth 3d data and 2d image information. the silhouetteinformation extracted from 2d images can also be integratedas an option if it is available. the new methodis a variational approach with a new functional integrating3d stereo data with 2d image information. this givesa more robust approach than existing methods using onlypure 2d information or 3d stereo data. we also propose abounded regularization method to implement efficiently thesurface evolution by level-set methods. the properties ofthe algorithms are discussed, proved for some cases, andempirically demonstrated through intensive experiments onreal sequences.
automatic recognition of human facial expressions. the paper presents a new idea for detecting an unknown human face in input imagery and recognizing his/her facial expression represented in the deformation of the two dimensional net, called potential net. the method deals with the facial information, faceness and expressions, as an overall pattern of the net activated by edges in a single input image of face, rather than from changes in the shape of the facial organs or their geometrical relationships. we build models of facial expressions from the deformation patterns in the potential net for face images in the training set of different expressions and then project them into emotion space. expression of an unknown subject can be recognized from the projection of the net for the image into the emotion space. the potential net is further used to model the common human face. the mosaic method representing energy in the net is used as a template for finding candidates for the face area and the candidates are verified their faceness by projecting them into emotion space in order to select the finalist. precise location of the face is determined by the histogram analysis of vertical and horizontal projections of edges.
kernel-based multifactor analysis for image synthesis and recognition. in many vision problems, the appearances of the observed images, e.g. the human facial images, are often influenced by multiple underlying factors. in this paper, a kernel-based factorization framework is proposed to analyze a multifactor dataset. specifically, we perform n-mode singular value decomposition (n-mode svd) in a higher dimensional feature space instead of the input space by using kernel approaches. given an input sample, its specific underlying factors which may be all absent in the training set can be extracted and translated from one sample to another by using kernel-based ¿translation¿. therefore our framework is suitable for tasks of new image synthesis and underlying factor recognition. we demonstrate the capabilities of our framework on ensembles of facial images subjected to different person identities, view-points and illuminations with high-quality synthetic faces and high face recognition accuracy.
ambiguity in reconstruction from images of six points. let s be a set of six points in space, let \psi be any hyperboloid of one sheet containing s, and let i be a sequence of images of s taken by an uncalibrated camera moving over \psi. then reconstruction from i is subject to a three way ambiguity which is unbroken as long as the optical centre of the camera remains on \psi.let p be an image of s taken from a point on \psi. the images "near" p define a tangent space which splits into a direct sum w_p\oplus n_p\oplus f_p, where wp corresponds to images near p for which the ambiguity is maintained, np corresponds to images for which the ambiguity is broken and fp corresponds to images which are physically impossible.
a recursive filter for phase velocity assisted shape-based tracking of cardiac non-rigid motion. a framework for tracking pointwise periodic non-rigid motion of the heart's left ventricular (lv) wall is presented which incorporates information from two different magnetic resonance imaging (mri) techniques. new developments in phase-contrast cine mr imaging have produced spatial maps of instantaneous velocity that heave proven accuracy within the myocardium, or wall, of the heart. this information is combined with shape-based matching techniques to provide improved estimates of trajectories, especially in regions where shape information is limited. these raw trajectories act as input to a recursive least squares (rls) filter which applies the constraints of temporal periodicity and spatial smoothness for the final estimate. the results of the rls filter are compared with the motion of actual implanted markers. comparisons are also made between exclusively shape-based filtered and phase-contrast enhanced trajectory estimates using both phantom and actual canine heart mr images.
topologically adaptable snakes. the paper presents a typologically adaptable snakes model for image segmentation and object representation. the model is embedded in the framework of domain subdivision using simplicial decomposition. this framework extends the geometric and topological adaptability of snakes while retaining all of the features of traditional snakes, such as user interaction, and overcoming many of the limitations of traditional snakes. by superposing a simplicial grid over the image domain and using this grid to iteratively reparameterize the deforming snakes model, the model is able to flow into complex shapes, even shapes with significant protrusions or branches, and to dynamically change topology as necessitated by the data. snakes can be created and can split into multiple parts or seamlessly merge into other snakes. the model can also be easily converted to and from the traditional parametric snakes model representation. we apply a 2d model to various synthetic and real images in order to segment objects with complicated shapes and topologies.
multiple-cue illumination estimation in textured scenes. in this paper, we present a method that integrates cuesfrom shading, shadow and specular reflections for estimatingdirectional illumination in a textured scene. textureposes a problem for lighting estimation, since texture edgescan be mistaken for changes in illumination condition, andunknown variations in albedo make reflectance model fittinginpractical. unlike previous works which all assumeknown or uniform reflectance, our method can deal with theeffects of textures by capitalizing on physical consistenciesthat exist among the lighting cues. since scene textures donot exhibit such coherence, we use this property to minimizethe influence of texture on illumination direction estimation.for the recovered light source directions, a technique forestimating their intensities in the presence of texture is alsoproposed.
a unifying framework for structure and motion recovery from image sequences. the paper proposes a statistical framework that enables 3d structure and motion to be computed optimally from an image sequence, on the assumption that feature measurement errors are independent and gaussian distributed. the analysis and results demonstrate that computing both camera/scene motion and 3d structure is essential to computing either with any accuracy. having computed optimal estimates of structure and motion over a small number of initial images, a recursive version of the algorithm (previously reported) recomputes sub optimal estimates given new image data. the algorithm is designed explicitly for real time implementation, and the complexity is proportional to the number of tracked features. 3d projective, affine and euclidean models of structure and motion recovery have been implemented, incorporating both point and line features into the computation. the framework can handle any feature type and camera model that may be encapsulated as a projection equation from scene to image.
rigidity checking of 3d point correspondences under perspective projection. an algorithm is described which rapidly verifies the potential rigidity of three dimensional point correspondences from a pair of two dimensional views under perspective projection. the output of the algorithm is a simple yes or no answer to the question ``could these corresponding points from two views be the projection of a rigid configuration?'''' potential applications include 3d object recognition from a single previous view and correspondence matching for stereo or motion over widely separated views. our analysis begins with the observation that it is often the case that two views cannot provide an accurate structure-from-motion estimate because of ambiguity and ill- conditioning. however, it is argued that an accurate yes/no answer to the rigidity question is possible and experimental results support this assertion with as few as six pairs of corresponding points over a wide range of scene structures and viewing geometries. rigidity checking verifies point correspondences by using 3d recovery equations as a matching condition. the proposed algorithm improves upon other methods that fall under this approach because it works with as few as six corresponding points under full perspective projection, handles correspondences from widely separated views, makes full use of the disparity of the correspondences, and is integrated with a linear algorithm for 3d recovery due to kontsevich. the rigidity decision is based on the residual error of an integrated pair of linear and nonlinear structure-from-motion estimators. results are given for experiments with synthetic and real image data. a complete implementation of this algorithm is being made publicly available.
a generative/discriminative learning algorithm for image classification. we have developed a two-phase generative/discriminative learning procedure for the recognition of classes of objects and concepts in outdoor scenes. our method uses both multiple types of object features and context within the image. the generative phase normalizes the description length of images, which can have an arbitrary number of extracted features of each type. in the discriminative phase, a classifier learns which images, as represented by this fixed-length description, contain the target object. we have tested the approach by comparing it to several other approaches in the literature and by experimenting with several different data sets and combinations of features. our results, using color, texture, and structure features, show a significant improvement over previously published results in image retrieval. using salient region features, we are competitive with recent results in object recognition.
local features for object class recognition. in this paper we compare the performance of local detectors and descriptors in the context of object class recognition. recently, many detectors / descriptors have been evaluated in the context of matching as well as invariance to viewpoint changes [20]. however, it is unclear if these results can be generalized to categorization problems, which require different properties of features. we evaluate 5state-of-the-art scale invariant region detectors and 5 descriptors. local features are computed for 20 object classes and clustered using hierarchical agglomerative clustering. we measure the quality of appearance clusters and location distributions using entropy as well as precision. we also measure how the clusters generalize from training set to novel test data. our results indicate that extended sift descriptors [22] computed on hessian-laplace [20] regions perform best. second score is obtained by salient regions [11]. the results also show that these two detectors provide complementary features. the new detectors/descriptorssignificantly improve the performance of a state-of-the art recognition approach [16] in pedestrian detection task.
globally optimal solutions for energy minimization in stereo vision using reweighted belief propagation. a wide range of low level vision problems have been formulated in terms of finding the most probable assignment of a markov random field (or equivalently the lowest energy configuration). perhaps the most successful example is stereo vision. for the stereo problem, it has been shown that finding the global optimum is np hard but good results have been obtained using a number of approximate optimization algorithms. in this paper we show that for standard benchmark stereo pairs, the global optimum can be found in about 30 minutes using a variant of the belief propagation (bp) algorithm. we extend previous theoretical results on reweighted belief propagation to account for possible ties in the beliefs and using these results we obtain easily checkable conditions that guarantee that the bp disparities are the global optima. we verify experimentally that these conditions are typically met for the standard benchmark stereo pairs and discuss the implications of our results for further progress in stereo.
a multigrid approach for hierarchical motion estimation. this paper focuses on the estimation of the apparent motion field between two consecutive frames in an image sequence. the approach developed here is a trade-off between methods based on global parameterized flow models and local dense optic flow estimators.the method relies on an adaptive multigrid minimization approach. in addition to accelerated convergence toward good estimates, it allows to mix different parameterizations of the estimate relative to adaptive partitions of the image.the performances of the resulting algorithms are demonstrated in the difficult context of a non-convex energy. experimental results on real world meteosat sequences are presented.
using specularities for recognition. recognition systems have generally treated specular highlightsas noise. we show how to use these highlights asa positive source of information that improves recognitionof shiny objects. this also enables us to recognize verychallenging shiny transparent objects, such as wine glasses.specifically, we show how to find highlights that are consistentwith an hypothesized pose of an object of known 3dshape. we do this using only a qualitative description ofhighlight formation that is consistent with most models ofspecular reflection, so no specific knowledge of an object'sreflectance properties is needed. we first present a methodthat finds highlights produced by a dominant compact lightsource, whose position is roughly known. we then show howto estimate the lighting automatically for objects whose reflectionis part specular and part lambertian. we demonstratethis method for two classes of objects. first, we showthat specular information alone can suffice to identify objectswith no lambertian reflectance, such as transparentwine glasses. second, we use our complete system to recognizeshiny objects, such as pottery.
a general framework for object detection. this paper presents a general trainable framework for object detection in static images of cluttered scenes. the detection technique we develop is based on a wavelet representation of an object class derived from a statistical analysis of the class instances. by learning an object class in terms of a subset of an overcomplete dictionary of wavelet basis functions, we derive a compact representation of an object class which is used as an input to a support vector machine classifier. this representation overcomes both the problem of in-class variability and provides a low false detection rate in unconstrained environments.we demonstr ate the capabilities of the technique in two domains whose inherent information content differs significantly. the first system is face detection and the second is the domain of people which, in contrast to faces, vary greatly in color, texture, and patterns. unlike previous approaches, this system learns from examples and does not rely on any a priori (hand-crafted) models or motion-based segmentation. the paper also presents a motion-based extension to enhance the performance of the detection algorithm over video sequences. the results presented here suggest that this architecture may well be quite general.
detection of multiple, partially occluded humans in a single image by bayesian combination of edgelet part detectors. this paper proposes a method for human detection in crowded scene from static images. an individual human is modeled as an assembly of natural body parts. we introduce edgelet features, which are a new type of silhouette oriented features. part detectors, based on these features, are learned by a boosting method. responses of part detectors are combined to form a joint likelihood model that includes cases of multiple, possibly inter-occluded humans. the human detection problem is formulated as maximum a posteriori (map) estimation. we show results on a commonly used previous dataset as well as new data-sets that could not be processed by earlier methods.
a pattern classification approach to dynamical object detection. current systems for object detection in video sequences rely on explicit dynamical models like kalman filters or hidden markov models. there is significant overhead needed in the development of such systems as well as the a priori assumption that the object dynamics can be described with such a dynamical model. this paper describes a new pattern classification technique for object detection in video sequences that uses a rich, over complete dictionary of wavelet features to describe an object class. unlike previous work where a small subset of features was selected from the dictionary, this system does no feature selection and learns the model in the full 1,326 dimensional feature space. comparisons using different sized sets of several types of features are given. we extend this representation into the time domain without assuming any explicit model of dynamics. this data driven approach produces a model of the physical structure and short-time dynamical characteristics of people from a training set of examples; no assumptions are made about the motion of people, just that short sequences characterize their dynamics sufficiently for the purposes of detection. one of the main benefits of this approach is that transient false positives are reduced. this technique compares favorably with the static detection approach and could be applied to other object classes. we also present a real-time version of one of our static people detection systems.
joint haar-like features for face detection. in this paper, we propose a new distinctive feature, called joint haar-like feature, for detecting faces in images. this is based on co-occurrence of multiple haar-like features. feature co-occurrence, which captures the structural similarities within the face class, makes it possible to construct an effective classifier. the joint haar-like feature can be calculated very fast and has robustness against addition of noise and change in illumination. a face detector is learned by stagewise selection of the joint haar-like features using adaboost. a small number of distinctive features achieve both computational efficiency and accuracy. experimental results with 5,676 face images and 30,000 nonface images show that our detector yields higher classification performance than viola and jones¿ detector, which uses a single feature for each weak classifier. given the same number of features, our method reduces the error by 37%. our detector is 2.6 times as fast as viola and jones¿ detector to achieve the same performance.
a pde-based level-set approach for detection and tracking of moving objects. this papers pr esents a framework for detecting and tracking moving objects in a sequence of images. using a statistical approach, where the inter-frame difference is modeled by a mixture of two laplacian or gaussian distributions, and an energy minimization based approach, we reformulate the motion detection and tracking problem as a front propagation problem. the euler-lagrange equation of the designed energy functional is first derived and the flow minimizing the energy is then obtained. following the work by caselles et al [cks95],and malladi et al [msv95, msv93], the contours to be detected and tracked are modeled as geodesic active contours evolving toward the minimum of the designed energy, under the influence of internal and external image dependent forces. using the level set formulation scheme of osher and sethian [os88] complex curves can be detected and tracked and topological changes for the evolving curves are naturally managed. to reduce the computational cost required by a direct implementation of the formulation scheme of osher and sethian [os88], a new approach exploiting aspects from the classical narrow band [as95] and fast marching [set96] methods is proposed and favorably compared to them. in order to further reduce the cpu time, a multi-scale approach has also been considered. very promising experimental results are provided using real video sequences.
task-oriented generation of visual sensing strategies. in vision-guided robotic operations, vision is used for extracting necessary information for achieving the task. since visual sensing is usually performed with limited resources, visual sensing strategies should be planned so that only necessary information is obtained efficiently. this paper describes a method of systematically generating visual sensing strategies based on knowledge of the task to be performed. the generation of the appropriate visual sensing strategy entails knowing what information to extract, where to get it, and how to get it. this is facilitated by the knowledge of the task, which describes what objects are involved in the operation, and how they are assembled. our method has been implemented using a laser range finder as the sensor. experimental results show the feasibility of the method, and point out the importance of task-oriented evaluation of visual sensing strategies.
polarization-based transparent surface modeling from two views. in this paper, we propose a novel method to recover thesurface shape of transparent objects. the degree of polarizationof the light reflected from the object surface dependson the reflection angle which, in turn, depends on the object'ssurface normal; thus, by measuring the degree of polarization,we are able to calculate the surface normal of theobject. however, degree of polarization and surface normaldoes not correspond one-to-one, making us to analyze twopolarization images taken from two different view in orderto solve the ambiguity. a parabolic curve will be a strongclue to correspond a point in one image to a point in theother image, where both points represent the same point onobject surface. by comparing the degree of polarization atsuch corresponding points, the true surface normal can bedetermined.
geodesic active regions for supervised texture segmentation. this paper presents a novel variational method for supervised texture segmentation. the textured feature space is generated by filtering the given textured images using isotropic and anisotropic filters, and analyzing their responses as multi-component conditional probability density functions.the texture segmentation is obtained by unifying region and boundary-based information as an improved geodesic active contour model. the defined objective function is minimized using a gradient-descent method where a level set approach is used to implement the obtained pde.according to this pde, the curve propagation towards the final solution is guided by boundary and region-based segmentation forces, and is constrained by a regularity force. the level set implementation is performed using a fast front propagation algorithm where topological changes are naturally handled. the performance of our method is demonstrated on a variety of synthetic and real textured frames.
polarization-based inverse rendering from a single view. this paper presents a method to estimate geometrical,photometrical, and environmental information of a single-viewedobject in one integrated framework under fixed viewingposition and fixed illumination direction. these threetypes of information are important to render a photorealisticimage of a real object. photometrical information representsthe texture and the surface roughness of an object,while geometrical and environmental information representthe 3d shape of an object and the illumination distribution,respectively. the proposed method estimates the 3d shapeby computing the surface normal from polarization data,calculates the texture of the object from the diffuse only reflectioncomponent, determines the illumination directionsfrom the position of the brightest intensity in the specularreflection component, and finally computes the surfaceroughness of the object by using the estimated illuminationdistribution.
gradient vector flow fast geodesic active contours. abstract--in this paper, we propose an edge-driven bidirectional geometric flow for boundary extraction. to this end, we combine the geodesic active contour flow [check end of sentence] and the gradient vector flow external force for snakes [check end of sentence]. the resulting motion equation is considered within a level set formulation [check end of sentence], can deal with topological changes and important shape deformations. an efficient numerical schema is used for the flow implementation that exhibits robust behavior and has fast convergence rate [check end of sentence], [check end of sentence]. promising results on real and synthetic images demonstrate the potentials of the flow.
principal manifolds and bayesian subspaces for visual recognition. we investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. three techniques: principal component analysis (pca), independent component analysis (ica) and nonlinear pca (nlpca) are examined and tested in a visual recognition experiment using a large gallery of facial images from the "feret" database. we compare the recognition performance of a nearest-neighbor matching rule with each principal manifold representation to that of a maximum a posteriori (map) matching rule using a bayesian similarity measure derived from probabilistic subspaces and demonstrate the superiority of the latter.
shape and appearance repair for incomplete point surfaces. this paper presents a new surface content completion framework that can restore both shape and appearance from scanned, incomplete point set inputs. first, the geometric holes can be robustly identified from noisy and defective data sets without the need of any normal or orientation information, using the method of active deformable models. the geometry and texture information of the holes can then be determined either automatically from the models¿ context, or semi-automatically with minimal users¿ intervention. the central idea for this repair process is to establish a quantitative similarity measurement among local surface patches based on their local parameterizations and curvature computation. the geometry and texture information of each hole can be completed by warping the candidate region and gluing it to the hole. the displacement for the alignment process is computed by solving a poisson equation in 2d. our experiments show that the unified framework, founded upon the techniques of deformable models, local parameterization, and pde modeling, can provide a robust and elegant solution for content completion of defective, complex point surfaces.
probabilistic visual learning for object detection. we present an unsupervised technique for visual learning which is based on density estimation in high-dimensional spaces using an eigenspace decomposition. two types of density estimates are derived for modeling the training data: a multivariate gaussian (for a unimodal distributions) and a multivariate mixture-of-gaussians model (for multimodal distributions). these probability densities are then used to formulate a maximum-likelihood estimation framework for visual search and target detection for automatic object recognition. this learning technique is tested in experiments with modeling and subsequent detection of human faces and non-rigid objects such as hands.
a curvature-based approach to contour motion estimation. we present a novel method of velocity field estimation for points on moving contours in an image sequence. the method determines the corresponding point in the next image frame by considering curvature changes at each point on a contour. in previous methods, there are errors in estimation for the points which have low curvature variations since those methods compute the solutions by approximatingthe normal component of optical flow. the proposed method computes optical flow vectors of contour points by minimizing the curvature changes. as a first step, snakes are used to locate smooth curves in 2d imagery. then, the extracted curves are tracked continuously. we excluded the rearranging process in snakes and allowed the snaxel distance to vary. each point on a contour has a unique corresponding point in thenext frame. experimental results showed that the proposed method computes accurate optical flow vectors for various moving contours.
volumetric deformable models with parameter functions: a new approach to the 3d motion analysis of the lv from mri-spamm. we present a new method for analyzing the 3d motion of the heart's left ventricle (lv) from tagged magnetic resonance imaging (mri) data. our technique is based on the development of a new class of volumetric physics-based deformable models whose parameters are functions and can capture the local shape variation of an object. these parameters require no complex post-processing in order to be used by a physician. these volumetric models allow the accurate estimation of the shape and motion of the inner and outer walls of the lv as well as within the walls. we also present a new technique for calculating forces exerted by tagged mri data to material points of the deformable model. furthermore, by plotting the variations over time of the extracted lv model parameters from normal heart data we are able to quantitatively analyze and compare the epicardial and endocardial motion.
background modeling and subtraction of dynamic scenes. background modeling and subtraction is a core componentin motion analysis. the central idea behind such moduleis to create a probabilistic representation of the staticscene that is compared with the current input to performsubtraction. such approach is efficient when the scene to bemodeled refers to a static structure with limited perturbation.in this paper, we address the problem of modeling dynamicscenes where the assumption of a static backgroundis not valid. waving trees, beaches, escalators, naturalscenes with rain or snow are examples. inspired by the workproposed in [4], we propose an on-line auto-regressivemodel to capture and predict the behavior of such scenes.towards detection of events we introduce a new metric thatis based on a state-driven comparison between the predictionand the actual frame. promising results demonstratethe potentials of the proposed framework.
cluster-based segmentation of natural scenes. in cluster-based segmentation pixels are mapped into various feature-spaces whereupon they are subjected to a grouping-algorithm. in this paper we develop a robust and versatile non-parametric clustering algorithm that is able to handle the unbalanced and irregular clusters encountered in such segmentation- applications.the strength of our approach lies in the definition and use of two cluster-validity indices that are independent of the cluster-topology. by combining them, an excellent clustering can be identified, and experiments confirm that the associated clusters do indeed correspond to perceptually salient image-regions.
shape extraction for curves using geometry-driven diffusion and functional optimization. in this paper we show how both geometry-driven diffusion and optimization of the mumford-shah functional can be used to develop a type of curve-evolution that is able to preserve salient features of closed curves (such as corners and straight line segments), while simultaneously suppressing noise and irrelevant details. the idea is to characterize the curve by means of its angle-function (i.e. the angle between the tangent and a fixed axis) and to apply the appropriate dynamics to this one-dimensional representation. we show how constrained evolution equations can be used to keep the corresponding curve closed at all times.
evaluation of features detectors and descriptors based on 3d objects. we explore the performance of a number of popular feature detectors and descriptors in matching 3d object features across viewpoints and lighting conditions. to this end we design a method, based on intersecting epipolar constraints, for providing ground truth correspondence automatically. these correspondences are based purely on geometric information, and do not rely on the choice of a specific feature appearance descriptor. we test detector-descriptor combinations on a database of 100 objects viewed from 144 calibrated viewpoints under three different lighting conditions. we find that the combination of hessian-affine feature finder and sift features is most robust to viewpoint change. harris-affine combined with sift and hessian-affine combined with shape context descriptors were best respectively for lighting change and change in camera focal length. we also find that no detector-descriptor combination performs well with viewpoint changes of more than 25---30¿.
a bayesian approach for shadow extraction from a single image. this paper addresses the problem of shadow extraction from a single image of a complex natural scene. no simplifying assumption on the camera and the light source other than the lambertian assumption is used. our method is unique because it is capable of translating very rough user-supplied hints into the effective likelihood and prior functions for our bayesian optimization. the likelihood function requires a decent estimation of the shadowless image, which is obtained by solving the associated poisson equation. our bayesian framework allows for the optimal extraction of smooth shadows while preserving texture appearance under the extracted shadow. thus our technique can be applied to shadow removal, producing some best results to date compared with the current state-of-the-art techniques using a single input image. we propose related applications in shadow compositing and image repair using our bayesian technique.
integration of conditionally dependent object features for robust figure/background segmentation. we propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and position of the target. robustness is achieved by the integration of appearance and geometric object features and by their description using particle filters. previous approaches assume independence of the object cues or apply the particle filter formulation to only one of the features, and assume a smooth change in the rest, which can prove is very limiting, especially when the state of some features needs to be updated using other cues or when their dynamics follow non-linear and unpredictable paths. our technique offers a general framework to model the probabilistic relationship between features. the proposed method is analytically justified and applied to develop a robust tracking system that adapts online and simultaneously the colorspace where the image points are represented, the color distributions, and the contour of the object. results with synthetic data and real video sequences demonstrate the robustness and versatility of our method.
dominant sets and hierarchical clustering. dominant sets are a new graph-theoretic concept that has proven to be relevant in partitional (flat) clustering as well as image segmentation problems. however, in many computer vision applications, such as the organization of an image database, it is important to provide the data to be clustered with a hierarchical organization, and it is not clear how to do this within the dominant set framework. in this paper we address precisely this problem, and present a simple and elegant solution to it. to this end, we consider a family of (continuous) quadratic programs which contain a parameterized regularization term that controls the global shape of the energy landscape. when the regularization parameter is zero the local solutions are known to be in one-to-one correspondence with dominant sets, but when it is positive an interesting picture emerges. we determine bounds for the regularization parameter that allow us to exclude from the set of local solutions those inducing clusters of size smaller than a prescribed threshold. this suggests a new (divisive) hierarchical approach to clustering, which is based on the idea of properly varying the regularization parameter during the clustering process. straight forward dynamics from evolutionary game theory are used to locate the solutions of the quadratic programs at each level of the hierarchy. we apply the proposed framework to the problem of organizing a shape database. experiments with three different similarity matrices (and databases) reported in the literature have been conducted, and the results confirm the effectiveness of our approach.
guiding model search using segmentation. in this paper we show how a segmentation as preprocessing paradigm can be used to improve the efficiency and accuracy of model search in an image. we operationalize this idea using an over-segmentation of an image into superpixels. the problem domain we explore is human body pose estimation from still images. the superpixels prove useful in two ways. first, we restrict the joint positions in our human body model to lie at centers of superpixels, which reduces the size of the model search space. in addition, accurate support masks for computing features on half-limbs of the body model are obtained by using agglomerations of superpixels as half-limb segments. we present results on a challenging dataset of people in sports news images.
dynamic refraction stereo. in this paper we consider the problem of reconstructing the 3d position and surface normal of points on an unknown, arbitrarily-shaped refractive surface. we show that two viewpoints are sufficient to solve this problem in the general case, even if the refractive index is unknown. the key requirements are (1) knowledge of a function that maps each point on the two image planes to a known 3d point that refracts to it, and (2) light is refracted only once. we apply this result to the problem of reconstructing the time-varying surface of a liquid from patterns placed below it. to do this, we introduce a novel "stereo matching" criterion called refractive disparity, appropriate for refractive scenes, and develop an optimization-based algorithm for individually reconstructing the position and normal of each point projecting to a pixel in the input views. results on reconstructing a variety of complex, deforming liquid surfaces suggest that our technique can yield detailed reconstructions that capture the dynamic behavior of free-flowing liquids.
a unified factorization algorithm for points, line segments and planes with uncertainty models. in this paper we present a unified factorization algorithm for recovering structure and motion from image sequences by using point features, line segments and planes. this new formulation is based on directional uncertainty model for features. points and line segments are both described by the same probabilistic models and so can be recovered in the same way. prior information on the coplanarity of features is shown to fit naturally into the new factorization formulation and provides additional constraints for the shape recovery. this formulation leads to a weighted least squares motion and shape recovery problem which is solved by an efficient quasi-linear algorithm. the statistical uncertainty model also enables us to recover uncertainty estimates for the reconstructed three dimensional feature locations.
determining facial expressions in real-time. we suggest an approach to describing and tracking the deformation of facial features. we concentrate on the mouth since its shape is important in detecting emotion. however, we believe that our system could be extended to deal with other facial features. in our system, the mouth is described by a valley contour which is based between the lips. this contour is shown to exist independently of illumination, viewpoint, identity, and expression. we present a real time mouth tracking system that follows this valley. it is shown to be robust to changes in identity, illumination and viewpoint. a simple classification algorithm was found to be sufficient to discriminate between 5 different mouth shapes, with a 100% recognition rate.
robust tracking with spatio-velocity snakes: kalman filtering approach. using results from robust kalman filtering, we present a new kalman filter-based snake model for tracking of nonrigid objects in combined spatio-velocity space. the proposed model is the stochastic version of the velocity snake which is an active contour model for combined tracking of position and velocity of nonrigid boundaries. the proposed model uses image gradient and optical flow measurements along the contour as system measurements. an optical-flow based measurement error is used to detect and reject image measurements which correspond to image clutter or to other objects. the method was applied to object tracking ofboth rigid and nonrigid objects, resulting in good tracking results and robustness to image clutter, occlusions and numerical noise.
objective image fusion performance characterisation. image fusion as a way of combining multiple image signals into a single fused image has in recent years been extensively researched for a variety of multisensor applications. choosing an optimal fusion approach for each application from the plethora of algorithms available however, remains a largely open issue. a small number of metrics proposed so far provide only a rough, numerical estimate of fusion performance with limited understanding of the relative merits of different fusion schemes. this paper proposes a method for comprehensive, objective, image fusion performance characterisation using a fusion evaluation framework based on gradient information representation. the method provides an in-depth analysis of fusion performance by quantifying: information contributions by each sensor, fusion gain, fusion information loss and fusion artifacts (artificial information created). it is demonstrated on the evaluation of an extensive dataset of multisensor images fused with a wide range of established image fusion algorithms. the results demonstrate and quantify a number of well known issues concerning the performance of these schemes and provide a useful insight into a number of more subtle yet important fusion performance effects not immediately accessible to an observer.
automatic generation of grbf networks for visual learning. learning can often be viewed as the problem of mapping from an input space to an output space. examples of these mappings are used to construct a continuous function that approximates given data and generalizes for intermediate instances. generalized radial basis function (grbf) networks are used to formulate this approximating function. a novel method is introduced to construct an optimal grbf network for a given mapping and error bound using the integral wavelet transform. simple one-dimensional examples are used to demonstrate how the optimal network is superior to one constructed using standard ad hoc optimization techniques. the paper concludes with an application of optimal grbf networks to object recognition and pose estimation. the results of this application are favorable.
combining image regions and human activity for indirect object recognition in indoor wide-angle views. traditional methods of object recognition are reliant on shape and so are very difficult to apply in cluttered, wide-angle and low-detail views such as surveillance scenes. to address this, a method of indirect object recognition is proposed, where human activity is used to infer both the location and identity of objects. no shape analysis is necessary. the concept is dubbed ¿interaction signatures¿, since the premise is that a human will interact with objects in ways characteristic of the function of that object ¿ for example, a person sits in a chair and drinks from a cup. the human-centred approach means that recognition is possible in low-detail views and is largely invariant to the shape of objects within the same functional class. this paper implements a bayesian network for classifying region patches with object labels, building upon our previous work in automatically segmenting and recognising a human¿s interactions with the objects. experiments show that interaction signatures can successfully find and label objects in low-detail views and are equally effective at recognising test objects that differ markedly in appearance from the training objects.
n-dimensional probablility density function transfer and its application to colour transfer. this article proposes an original method to estimate a continuous transformation that maps one n-dimensional distribution to another. the method is iterative, non-linear, and is shown to converge. only 1d marginal distributions are used in the estimation process, hence involving low computation costs. as an illustration this mapping is applied to colour transfer between two images of different contents. the paper also serves as a central focal point for collecting together the research activity in this area and relating it to the important problem of automated colour grading.
a shape-based segmentation approach: an improved technique using level sets. we propose a novel approach for shape-based segmentation based on a specially designed level set function format. this format permits us to better control the process of object registration which is an important part in the shapebased segmentation framework. the method depends on a set of training shapes used to build a parametric shape model. the color is taken into consideration besides the shape prior information. the shape model is fitted to the image volume by registration through an energy minimization problem. the approach overcomes the conventional methods problems like point correspondences and weighing coefficients tuning of the partial differential equations (pde's). also it is suitable for multi-dimensional data and computationally efficient. results of extracting the 2d star fish and the brain ventricles in 3d demonstrate theefficiency of the approach.
efficient model-based 3d tracking of deformable objects. efficient incremental image alignment is a topic of renewed interest in the computer vision community because of its applications in model fitting and model-based object tracking. successful compositional procedures for aligning 2d and 3d models under weak-perspective imaging conditions have already been proposed. here we present a mixed compositional and additive algorithm which is applicable to the full projective camera case.
image spaces and video trajectories: using isomap to explore video sequences. dimensionality reduction techniques seek to representa set of images as a set of points in a low dimensionalspace.here we explore a video representation thatconsiders a video as two parts - a space of possibleimages and a trajectory through that space.the non-lineardimensionality reduction technique of isomap,gives, for many interesting scenes, a very low dimensionalrepresentation of the space of possible images.analysis of the shape of the video trajectory throughthese image spaces gives new tools for video analysis.experiments with natural video sequences illustratemethods for the very different tasts of classifyingvideo clips and temporal super-resolution.
recognizing 3d objects using photometric invariant. we describe an efficient algorithm for recognizing 3d objects by combining photometric, and geometric invariants. a photometric property is derived, that is invariant to the changes of illumination and to relative object motion with respect to the camera and/or the lighting source in 3d space. we argue that conventional color constancy algorithms can not be used in the recognition of 3d objects. further we show recognition does not require a full constancy of colors, rather, it only needs something that remains unchanged under the varying light conditions and poses of the objects. combining the derived color invariant and the spatial constraints on the object surfaces, we identify corresponding positions in the model and the data space coordinates, using centroid invariance of corresponding groups of feature positions. tests are given to show the stability and efficiency of our approach to 3d object recognition.
bias-corrected optical flow estimation for road vehicle tracking. model-based vehicle tracking in traffic image sequences can be made more robust by matching expected displacementrates of vehicle surface points to optical flow (of) vectors computed from an image sequence. the capability to track vehicles uninterruptedly in thismanner over extended image sequences results in the ability to investigate even small errors in of estimation. it turns out that the of magnitudes are systematically underestimated. the ¿ albeit small ¿ bias can be corrected by analyzing the influence of explicitly modeled grey value noise on the precision of of values estimated by means of the neighborhood sampling method.
self-calibration and metric reconstruction in spite of varying and unknown internal camera parameters. in this paper the feasibility of self-calibration in the presence of varying internal camera parameters is under investigation. a self-calibration method is presented which efficiently deals with all kinds of constraints on the internal camera parameters. within this framework a practical method is proposed which can retrieve metric reconstruction from image sequences obtained with uncalibrated zooming/focusing cameras. the feasibility of the approach is illustrated on real and synthetic examples.
mesh optimization using an inconsistency detection template. we propose a new technique for optimizing a triangular mesh for polyhedral representation of the scene in a video stream. we introduce a specially designed template that can effectively detect color and texture discontinuities. using real images, we demonstrate that our method is superior to existing methods.
structure and semi-fluid motion analysis of stereoscopic satellite images for cloud tracking. time-varying multispectral observations of clouds from meteorological satellites are used to estimate cloud-top heights (structure) and cloud winds (semi-fluid motion). stereo image pairs over several time steps were acquired by two geostationary satellites with synchronized scanning instruments. cloud-top height estimation from these image pairs is performed using an improved automatic stereo analysis algorithm on a massively parallel maspar computer with 16 k processors. a new category of motion behavior known as semi-fluid motion is described for modeling cloud motions and an automatic algorithm for extracting semi-fluid motion is developed to track cloud winds. the time sequential dense estimates of cloud-top height depth maps in conjunction with intensity data are used to estimate local semi-fluid motion parameters for cloud tracking. both stereo disparities and motion correspondences are estimated to sub-pixel accuracy. the interactive image spreadsheet (iiss) is a new versatile visualization tool that was enhanced to analyze and visualize the results of the stereo analysis and semi-fluid motion estimation algorithms. experimental results using time-varying data of the visible channel from two satellites in geosynchronous orbit is presented for the hurricane frederic.
structured light in scattering media. virtually all structured light methods assume that the scene and the sources are immersed in pure air and that light is neither scattered nor absorbed. recently, however, structured lighting has found growing application in underwater and aerial imaging, where scattering effects cannot be ignored. in this paper, we present a comprehensive analysis of two representative methods - light stripe range scanning and photometric stereo - in the presence of scattering. for both methods, we derive physical models for the appearances of a surface immersed in a scattering medium. based on these models, we present results on (a) the condition for object detectability in light striping and (b) the number of sources required for photometric stereo. in both cases, we demonstrate that while traditional methods fail when scattering is significant, our methods accurately recover the scene (depths, normals, albedos) as well as the properties of the medium. these results are in turn used to restore the appearances of scenes as if they were captured in clear air. although we have focused on light striping and photometric stereo, our approach can also be extended to other methods such as grid coding, gated and active polarization imaging.
results using random field models for the segmentation of color images of natural scenes. we present results using a markov random field color texture model for the unsupervised segmentation of images of outdoor scenes. the color random field model describes textured regions in terms of spatial interaction within color bands and between different color bands. the model is used by a segmentation algorithm based on agglomerative hierarchical clustering. at the heart of the clustering is a step wise optimal merging process that at each iteration maximizes a global performance functional. the test for stopping the clustering is based on changes in the likelihood of the image. we provide experimental results that demonstrate the performance of the segmentation algorithm on color images of natural scenes. most of the processing during segmentation is local making the algorithm amenable to high performance parallel implementation.
a class of photometric invariants: separating material from shape and illumination. we derive a new class of photometric invariants that can beused for a variety of vision tasks including lighting invariantmaterial segmentation, change detection and tracking, aswell as material invariant shape recognition. the key ideais the formulation of a scene radiance model for the class of"separable" brdfs, that can be decomposed into materialrelated terms and object shape and lighting related terms.all the proposed invariants are simple rational functions ofthe appearance parameters (say, material or shape and lighting).the invariants in this class differ from one another in thenumber and type of image measurements they require. mostof the invariants in this class need changes in illumination orobject position between image acquisitions. the invariantscan handle large changes in lighting which pose problems formost existing vision algorithms. we demonstrate the power ofthese invariants using scenes with complex shapes, materials,textures, shadows and specularities.
constructing virtual worlds using dense stereo. we present virtualized reality, a technique to create virtual worlds out of dynamic events using densely distributed stereo views. the intensity image and depth map for each camera view at each time instant are combined to form a visible surface model. immersive interaction with the virtualized event is possible using a dense collection of such models. additionally, acomplete surface model of each instant can be built by merging the depth maps from different cameras into a common volumetric space. the corresponding model is compatible with traditional virtual models and can be interacted with immersively using standard tools. because both vsms and csms are fully three-dimensional, virtualized models can also be combined and modi.ed to build larger, more complex environments, an important capability for many non-trivial applications. we present results from 3d dome, our facility to create virtualized models.
how to deal with point correspondences and tangential velocities in the level set framework. in this paper, we overcome a major drawback of the levelset framework: the lack of point correspondences. we maintainexplicit backward correspondences from the evolvinginterface to the initial one by advecting the initial point coordinateswith the same speed as the level set function. ourmethod leads to a system of coupled eulerian partial differentialequations. we show in a variety of numerical experimentsthat it can handle both normal and tangential velocities,large deformations, shocks, rarefactions and topologicalchanges. applications are many in computer vision andelsewhere since our method can upgrade virtually any levelset evolution. we complement our work with the design ofnon zero tangential velocities that preserve the relative areaof interface patches; this feature may be crucial in such applicationsas computational geometry, grid generation orunfolding of the organs' surfaces, e.g. brain, in medicalimaging.
adaptive dynamic range imaging: optical control of pixel exposures over space and time. this paper presents a new approach to imaging thatsignificantly enhances the dynamic range of a camera.the key idea is to adapt the exposure of each pixel onthe image detector, based on the radiance value of thecorresponding scene point. this adaptation is done inthe optical domain, that is, during image formation. inpractice, this is achieved using a spatial light modulatorwhose transmittance can be varied with high resolutionover space and time. a real-time control algorithm isdeveloped that uses acquired images to automaticallyadjust the transmittance function of the spatial modulator. each captured image and its corresponding transmittance function are used to compute a very high dynamic range image that is linear in scene radiance.we have implemented a video-rate adaptive dynamicrange camera that consists of a color ccd detector anda controllable liquid crystal light modulator. experiments have been conducted in scenarios with complexand harsh lighting conditions. the results indicate thatadaptive imaging can have a significant impact on visionapplications such as monitoring, tracking, recognition,and navigation.
variational stereovision and 3d scene flow estimation with statistical similarity measures. we present a common variational framework for dense depth recovery and dense three-dimensional motion field estimation from multiple video sequences, which is robustto camera spectral sensitivity differences and illumination changes. for this purpose, we first show that both problems reduce to a generic image matching problem after backprojecting the input images onto suitable surfaces. we then solve this matching problem in the case of statistical similarity criteria that can handle frequently occurring non-affine image intensities dependencies. our method leads to an efficient and elegant implementation based on fast recursive filters. we obtain good results on real images.
vision in bad weather. current vision systems are designed to perform in clear weather. needless to say, in any outdoor application, there is no escape from &ldquo;bad&rdquo; weather. ultimately, computer vision systems must include mechanisms that enable them to function (even if somewhat less reliably) in the presence of haze, fog, rain, hail and snow. we begin by studying the visual manifestations of different weather conditions. for this, we draw on what is already known about atmospheric optics. next, we identify effects caused by bad weather that can be turned to our advantage. since the atmosphere modulates the information carried from a scene point to the observer it can be viewed as a mechanism of visual information coding. based on this observation, we develop models and methods for recovering pertinent scene properties, such as three-dimensional structure, from images taken under poor weather conditions
shadow flow: a recursive method to learn moving cast shadows. we present a novel algorithm to detect and remove cast shadows in a video sequence by taking advantage of the statistical prevalence of the shadowed regions over the object regions. we model shadows using multivariate gaussians. we apply a weak classifier as a pre-filter.we project shadow models into a quantized color space to update a shadow flow function. we use shadow flow, background models, and current frame to determine the shadow and object regions. this method has several advantages: it does not require a color space transformation. we pose the problem in the rgb color space, and we can carry out the same analysis in other cartesian spaces as well. it is data-driven and adapts to the changing shadow conditions. in other words, accuracy of our method is not limited by the preset values. furthermore, it does not assume any 3d models for the target objects or tracking of the cast shadows between frames. our results show that the detection performance is superior than the benchmark method.
real-time focus range sensor. structures of dynamic scenes can only be recovered using a real-time range sensor. depth-from-defocus offers a direct solution to fast and dense range estimation. it is computationally efficient as it circumvents the correspondence problem faced by stereo and feature tracking in structure-from-motion. however, accurate depth estimation requires theoretical and practical solutions to a variety of problems including the recovery of textureless surfaces, precise blur estimation, and magnification variations caused by defocusing. both textured and textureless surfaces are recovered using an illumination pattern that is projected via the same optical path used to acquire images. the illumination pattern is optimized to ensure maximum accuracy and spatial resolution in the computed depth. the relative blurring in two images is computed using a narrow-band linear operator that is designed by considering all the optical, sensing and computational elements of the depth-from-defocus system. defocus-invariant magnification is achieved by the use of an additional aperture in the imaging optics. a prototype focus range sensor has been developed that produces up to 512/spl times/480 depth estimates at 30 hz with an accuracy better than 0.3%. several experimental results are included to demonstrate the performance of the sensor.
comparing curved-surface range image segmenters. this work focuses on creating a framework for objectively evaluating the performance of range image segmentation algorithms. the algorithms are evaluated in terms of correct segmentation, over- and under- segmentation, missed and noise regions. a set of images with ground truth was created for this work. the images were captured using a structured light scanner. images used in the evaluation contain planar, spherical, cylindrical, toroidal andconical surface patches. the different surface patches in each image were manually identified to establish ground truth for performance evaluation. two segmentation algorithms from the literature are compared.
improved sub-pixel stereo correspondences through symmetric refinement. most dense stereo correspondence algorithms start by establishing discrete pixel matches and later refine these matches to sub-pixel precision. traditional sub-pixel refinement methods attempt to determine the precise location of points, in the secondary image, that correspond to discrete positions in the reference image. we show that this strategy can lead to a systematic bias associated with the violation of the general symmetry of matching cost functions. this bias produces random or coherent noise in the final reconstruction, but can be avoided by refining both image coordinates simultaneously, in a symmetric way. we demonstrate that the symmetric sub-pixel refinement strategy results in more accurate correspondences by avoiding bias while preserving detail.
"perspective shape from shading" and viscosity solutions. this article proposes a solution of the lambertian shapefrom shading (sfs) problem in the case of a pinhole cameramodel (performing a perspective projection). our approachis based upon the notion of viscosity solutions of hamilton-jacobiequations. this approach allows us to naturallydeal with nonsmooth solutions and provides a mathematicalframework for proving correctness of our algorithms.our work extends previous work in the area in three aspects.first, it models the camera as a pinhole whereasmost authors assume an orthographic projection (see [15]for a panorama of the sfs problem up to 1989 and [29, 17]for a recent survey), thereby extending the applicability ofshape from shading methods to more realistic images. inparticular it extends the work of [24] and [26]. second, byadapting the brightness equation to the perspective problem,we obtain a new partial differential equation (pde).results about the existence and uniqueness of its solutionare also obtained. third, it allows us to come up with a newapproximation scheme and a new algorithm for computingnumerical approximations of the "continuous" solution aswell as a proof of their convergence toward that solution.
a cubist approach to object recognition. we describe an appearance-based object recognition system using a keyed, multi-level context representation reminiscent of certain aspects of cubist art. specifically, we utilize distinctive intermediate-level features in this case automatically extracted 2-dboundary fragments, as keys, which are then verified within a local context, and assembled within a loose global context to evoke an overall percept. this system demonstrates good recognition of a variety of 3-d shapes, ranging from sports cars and fighter planes to snakes and lizards with full orthographic invariance. we report the results of large-scale tests, involving over 2000 separate test images, that evaluate performance with increasing number of items inthe database, in the presence of clutter, background change, and occlusion, and also the results of some generic classification experiments where the system is tested on objects never previously seen or modeled. to our knowledge, the results we report are the best in the literature for full-sphere tests of general shapes with occlusion and clutter resistance.
detecting rotational symmetries. we present an algorithm for detecting multiple rotational symmetries in natural images. given an image, its gradient magnitude field is computed, and information from the gradients is spread using a diffusion process in the form of a gradient vector flow (gvf) field. we construct a graph whose nodes correspond to pixels in the image, connecting points that are likely to be rotated versions of one another. the n-cycles present in the graph are made to vote for c_n symmetries, their votes being weighted by the errors in transformation between gvf in the neighborhood of the voting points, and the irregularity of the n-sided polygons formed by the voters. the votes are accumulated at the centroids of possible rotational symmetries, generating a confidence map for each order of symmetry. we tested the method with several natural images.
stereo with mirrors. in this paper, we propose the use of mirrors and a single camera for computational stereo. when compared to conventional stereo systems that use two cameras, our method has a number of significant advantages such as wide field of view, single viewpoint projection, identical camera parameters and ease of calibration. we propose four stereo systems that use a single camera pointed towards planar, ellipsoidal, hyperboloidal, and paraboloidal mirrors. in each case, we present a derivation of the epipolar constraints. next, we attempt to understand what can be seen by each system and formalize the notion of field of view. we conclude with two experiments to obtain 3-d structure. in the first we use a pair of planar mirrors, and in the second a pair of paraboloidal mirrors. the results of our experiments demonstrate the viability of stereo using mirrors.
wide baseline stereo matching. the objective of this work is to enlarge the class of camera motions for which epipolar geometry and image correspondences can be computed automatically. this facilitates matching between quite disparate views ¿ wide baseline stereo.two extensions are made to the current small baseline algorithms: first, and most importantly, a viewpoint invariant measure is developed for assessing the affinity of corner neighbourhoods over image pairs; second, algorithms are given for generating putative corner matches between image pairs using local homographies. two novel infrastructure developments are also described, the automatic generation of local homographies, and the combination of possibly conflicting sets of matches prior to ransac estimation.the wide baseline matching algorithm is demonstrated on a number of image pairs with varying relative motion, and for different scene types. all processing is automatic.
measuring convexity for figure/ground separation. in human perception, convex surfaces have a strong tendency to be perceived as the "figure". convexity has a stronger influence on figural organization than other global shape properties, such as symmetry ([9]). and yet, there has been very little work on convexity properties in computer vision.we present a model for figure/ground segregation which exhibits a preference for convex regions as the figure (i.e., the foreground). the model also shows a preference for smaller regions to be selected as figures, which is also known to hold for human visual perception (e.g., koffka [11]). the model is based on the machinery of markov random fields/random walks/diffusion processes, so that the global shape properties are obtained via local and stochastic computations. experimental results demonstrate that our model performs well on ambiguous figure/ground displays which were not captured before. in particular, in ambiguous displays where neither region is strictly convex, the model shows preference to the "more convex" region, thus offering a continuous measure of convexity in agreement with human perception.
reading between the lines: a method for extracting dynamic 3d with texture. a method is presented that extracts the 3d shape of objects, together with the surface texture. both shape and tecture are obtained from a single image. the underlying principle is based on an active technique. a high resolution pattern is projected onto the object and the deformations as observed by a single camera yield the 3rd dimension. furthermore, the surface texture is extracted from the same image. because the whole procedure is based on a single image, a frame-by-frame reconstruction of a video taken with the pattern projected throughout, yields 3dshape dynamics. the paper sketches the complete system but focuses on the problem of extraction.
eye design in the plenoptic space of light rays. natural eye designs are optimized with regard to the tasksthe eye-carrying organism has to perform for survival. thisoptimization has been performed by the process of naturalevolution over many millions of years. every eye capturesa subset of the space of light rays. the information containedin this subset and the accuracy to which the eye canextract the necessary information determines an upper limiton how well an organism can perform a given task. in thiswork we propose a new methodology for camera design. byinterpreting eyes as sample patterns in light ray space wecan phrase the problem of eye design in a signal processingframework. this allows us to develop mathematical criteriafor optimal eye design, which in turn enables us to build thebest eye for a given task without the trial and error phase ofnatural evolution. the principle is evaluated on the task of3d ego-motion estimation.
an enhanced correlation-based method for stereo correspondence with sub-pixel accuracy. the invariance of the similarity measure in photometric distortions as well as its capability in producing sub-pixel accuracy are two desired and often required features in most stereo vision applications. in this paper we propose a new correlation-based measure which incorporates both mentioned requirements. specifically, by using an appropriate interpolation scheme in the candidate windows of the matching image, and using the classical zero mean normalized cross correlation function, we introduce a suitable measure. although the proposed measure is a non-linear function of the sub-pixel displacement parameter, its maximization results in a closed form solution, resulting in reduced complexity for its use in matching techniques. application of the proposed measure in a number of benchmark stereo pair images reveals its superiority over existing correlation-based techniques used for sub-pixel accuracy.
automatic video summarization by graph modeling. we propose a unified approach for summarization based on the analysis of video structures and video highlights. our approach emphasizes both the content balance and perceptual quality of a summary. normalized cut algorithm is employed to globally and optimally partition a video into clusters. a motion attention model based on human perception is employed to compute the perceptual quality of shots and clusters. the clusters, together with the computed attention values, form a temporal graph similar to markov chain that inherently describes the evolution and perceptual importance of video clusters. in our application, the flow of a temporal graph is utilized to group similar clusters into scenes, while the attention values are used as guidelines to select appropriate sub-shots in scenes for summarization.
multiscale annealing for real-time unsupervised texture segmentation. we derive real-time global optimization algorithms for several clustering optimization methods used in unsupervised texture segmentation. speed is achieved by exploiting the topological relation of features to design a multiscale optimization technique, while accuracy and global optimization properties are provided by a deterministic annealing method. coarse grained cost functions are derived for both central and sparse pairwise clustering, where the problem of coarsening sparse random graphs is solved by the concept of structured randomization. annealing schedules and coarse-to-fine optimization are tightly coupled by a statistical convergence criterion derived from computational learning theory. the algorithms are benchmarked on brodatz-like micro-texture mondrians. results are presented for an autonomous robotics application.
surface reconstruction: gncs and mfa. the reconstruction of noise corrupted surfaces can be inferred by methodologies such as bayesian estimation and minimum description length. both of these imply a formulation where the reconstruction minimizes a functional. often this functional is non convex and the minimum cannot be found by simple gradient methods. the paper concerns functionals with quadratic data term, criteria for such functionals to be convex, and the variational approach of minimizing non convex functionals. initial convexity of the approximating functional is considered to be a critical point. two fully automatic methods of generating convex functionals are presented. they are based on gaussian convolution and are compared to the blake-zisserman graduated non convexity (gnc) (a. blake, a. zisserman, 1987) and g.l. bilbro et al. (1992) and d. geiger and f. girosi's (1991) mean field annealing (mfa) of the weak membrane.
structure from motion using sequential monte carlo methods. in this paper, the structure from motion (sfm) problem is addressed using sequential monte carlo methods. a new sfm algorithm based on random sampling is derived to estimate the posterior distributions of camera motion and scene structure for the perspective projection camera model. experimental results show that challenging issues in solving the sfm problem, due to erroneous feature tracking, feature occlusion, motion/structure ambiguity, mixed-domain sequences, mismatched features, and independently moving objects, can be well modeled and effectively addressed using the proposed method.
basic gray level aura matrices: theory and its application to texture synthesis. in this paper, we present a new mathematical framework for modeling texture images using independent basic gray level aura matrices (bglams). we prove that independent bglams are the basis of gray level aura matrices (glams), and that an image can be uniquely represented by its independent bglams. we propose a new bglam distance measure for automatically evaluating synthesis results w.r.t. input textures to determine if the output is a successful synthesis of the input. for the application to texture synthesis, we present a new algorithm to synthesize textures by sampling only the independent bglams of an input texture. with respect to synthesis of textures and evaluation of the results, the performance of our approach is extensively evaluated and compared with symmetric glams that are used in existing techniques and with gray level cooccurrence matrices (glcms). experimental results have shown that (1) our approach significantly outperforms both symmetric glams and glcms; (2) the new bglam distance measure has the ability to evaluate synthesis results, which can be used to automate the conventional visual inspection process for determining whether or not the output texture is a successful synthesis of the input; and (3) a broad range of textures can be faithfully synthesized using independent bglams and the synthesis results are comparable to existing techniques.
three dimensional mr brain segmentation. in mr brain images, segmentation using intensity values is severely limited owing to field inhomogeneities, susceptibility artifacts and partial volume effects. edge based segmentation methods suffer from spurious edges and gaps in boundaries. a method is presented which combines the advantages of edge based and region based segmentation. first a multiscale image representation is constructed which favors intra-tissue diffusion over inter-tissue diffusion by exploiting local contrast. subsequently a multiscale linking model (the hyperstack) is used to group voxels into a number of segments. this facilitates segmentation of grey matter, white matter and cerebrospinal fluid with minimal user interaction. using a supervised segmentation technique and mr simulations of a brain phantom as validation it is shown that the errors are in the order of or smaller than reported in literature.
phenomenological eigenfunctions for image irradiance. we present a framework for calculating low-dimensional bases to represent image irradiance from surfaces with isotropic reflectance under arbitrary illumination. by representing the illumination and the bidirectional reflectance distribution function (brdf) in frequency space, a model for the image irradiance is derived. this model is then reduced in dimensionality by analytically constructing the principal component basis for all images given the variations in both the illumination and the surface material. the principal component basis are constructed in such a way that all the symmetries (helmholtz reciprocity and isotropy) of the brdf are preserved in the basis functions. using the framework we calculate a basis using a database of natural illumination and the curet database containing brdfs of real world surface materials.
face recognition by stepwise nonparametric margin maximum criterion. linear discriminant analysis (lda) is a popular feature extraction technique in face recognition. however, it often suffers from the small sample size problem when dealing with the high dimensional data. moreover, while lda is guaranteed to find the best directions when each class has a gaussian density with a common covariance matrix, it can fail if the class densities are more general. in this paper, a new nonparametric linear feature extraction method, step-wise nonparametric margin maximum criterion(snmmc), is proposed to find the most discriminant directions, which does not assume that the class densities belong to any particular parametric family and does not depend on the non-singularity of the within-class scatter matrix either. on three datasets from att and feret face databases, our experimental results demonstrate that snmmc outperforms other methods and is robust to variations of pose, illumination and expression.
using eye reflections for face recognition under varying illumination. face recognition under varying illumination remains a challenging problem. much progress has been made toward a solution through methods that require multiple gallery images of each subject under varying illumination. yet for many applications, this requirement is too severe. in this paper, we propose a novel method that requires only a single gallery image per subject taken under unknown lighting. the method builds upon two contributions. we first estimate the lighting from its reflection in the eyes. this allows us to explicitly recover the illumination in the single gallery images as well as the probe image. next, we exploit the local linearity of face appearance variation across different people. we represent the gallery images as locally linear montages of images of many different faces taken under the same lighting (bootstrap images). then, we transfer the estimated combination of bootstrap images to synthesize each subject¿s face under the probe lighting to accomplish recognition. finally, we show through tests on the cmu pie database that we can achieve better recognition results using our lighting estimation method and locally linear montages than the current state-of-the-art.
real-time interactively distributed multi-object tracking using a magnetic-inertia potential model. this paper breaks with the common practice of using a joint state space representation and performing the joint data association in multi-object tracking. instead, we present an interactively distributed framework with linear complexity for real-time applications. when objects do not interact on each other, our approach performs like multiple independent trackers. when the objects are in close proximity or present occlusions, we propose a magnetic-inertia potential model to handle the "error merge" and "labelling" problems in a particle filtering framework. specifically, we propose to model the interactive likelihood densities by a "gravitation" and "magnetic" repulsion scheme and relax the common first-order markov chain assumption by using an "inertia" markov chain. our model represents the cumulative effect of virtual physical forces that objects undergo while interacting with others. it implicitly handles the "error merge" and "labelling" problems and thus solves the difficult object occlusion and data association problems using an innovative scheme. our preliminary work has demonstrated that the proposed approach is far superior to existing methods not only in robustness but also in speed.
invariant of a pair of non-coplanar conies in space: definition, geometric interpretation and computation. the joint invariants of a pair of coplanar conics has been widely used in recent vision literature. in this paper, the algebraic invariant of a pair of non-coplanar conics in space is concerned. the algebraic invariant of a pair of non-coplanar conics is first derived from the invariant algebra of a pair of quaternary quadratic forms by using the dual representation of space conics. then, this algebraic invariant is geometrically interpreted in terms of cross-ratios. finally, an analytical procedure for projective reconstruction of a space conic from two uncalibrated images is developed and the correspondence conditions of the conics between two views are also explicited.
linear n>=4-point pose determination. the determination of the position and the orientation of the camera from the known correspondences of the reference points and the image points is known as the problem of pose estimation in computer vision or space resection in photogrammetry. it is well known that using 3 corresponding points has at most 4 solutions. less appears to be known about the cases of 4 and 5 points. in this paper, we describe linear solutions that always give the unique solution to 4-point and 5-point pose determination for the reference points not lying on the critical confogurations. the same linear method can also be extended to any n ¿ 5 points.the robustness and accuracy of the method are experimented both on simulated and real images.
preemptive ransac for live structure and motion estimation. a system capable of performing robust live ego-motion estimation for perspective cameras is presented. the system is powered by random sample consensus with preemptive scoring of the motion hypotheses. a general statement of the problem of efficient preemptive scoring is given. then a theoretical investigation of preemptive scoring under a simple inlier-outlier model is performed. a practical preemption scheme is proposed and it is shown that the preemption is powerful enough to enable robust live structure and motion estimation.
non-parametric self-calibration. in this paper we develop a theory of non-parametric self-calibration. recently, schemes have been devised for non-parametric laboratory calibration, but not for self-calibration. we allow an arbitrary warp to model the intrinsic mapping, with the only restriction that the camera is central and that the intrinsic mapping has a well-defined non-singular matrix derivative at a finite number of points under study. we give a number of theoretical results, both forinfinitesimal motion and finite motion, for a finite number of observations and when observing motion over a dense image, for rotation and translation. our main result is that through observing the flow induced by three instantaneous rotations at a finite number of points of the distorted image, we can perform projective reconstruction of those image points on the undistorted image. we present some results with synthetic and real data.
recovering photometric properties of multiple strongly-reflective, partially-transparent surfaces from a single image. this paper introduces a method to recover photometric parameters of a set of 3d surfaces from a single image with significant global-illumination effects such as inter-reflections and transparencies. since this problem is ambiguous for arbitrary unknown scenes, our formulation assumes that the scene consists of a small set of photometrically homogeneous surfaces with known 3d shapes, illuminated by known light sources. we show that under these conditions, the system of non-linear equations that defines how the image is formed may be factorized into a vector composed only of products of some photometric parameters, and a matrix, whose elements depend non-linearly on both the known illumination, the known 3d shapes and the remaining photometric parameters. this factorization leads to an efficient optimization-based algorithm to compute all unknown photometric parameters from a single input image. experiments with real data show that this algorithm is more stable and efficient than simpler alternatives.
detecting kinetic occlusion. visual motion boundaries provide a powerful cue for the perceptual organization of scenes. motion boundaries are present when surfaces in motion occlude one another. conventional approaches to motion analysis have relied on assumptions of data conservation and smoothness, which has made analysis of motion boundaries difficult. we show that a common source of motion boundary, kinetic occlusion, can be detected using spatiotemporal junction analysis. junction analysis is accomplished by utilizing distributed representations of motion used in models of human visual motion sensing. by detecting changes in the direction of motion in these representations, spatiotemporal junctions are detected in a manner which differentiates accretion from deletion. we demonstrate successful occlusion detection on spatiotemporal imagery containing occluding surfaces in motion.
the catchment feature model for multimodal language analysis. the catchment feature model (cfm) addresses two questions in multimodal interaction: how do we bridge video and audio processing with the realities of human multimodal communication, and how information from the different modes may be fused. we discuss the need for our model, motivate the cfm from psycholinguistic research, and present the model. in contrast to 'whole gesture' recognition, the cfm applies a feature decomposition approach that facilitates cross-modal fusion at the level of discourse planning and conceptualization. we present our experimental framework for cfm-based research, and cite three concrete examples of catchment features (cf), and propose new directions of multimodal research based on the model.
learning dynamical models using expectation-maximisation. tracking with deformable contours in a filtering frame-work requir esa dynamical model for prediction. for any given application, tracking is improved by having an accurate model, learned from training data. we develop a method for learning dynamical models from training sequences, explicitly taking account of the fact that training data are noisy measurements and not true states. by introducing an "augmented-state smoothing filter" , we show how the technique of expectation-maximisation can be applied to this problem, and show that the resulting algorithm produces more robust and accurate tracking.
modeling scenes with local descriptors and latent aspects. we present a new approach to model visual scenes in image collections, based on local invariant features and probabilistic latent space models. our formulation provides answers to three open questions:(1) whether the invariant local features are suitable for scene (rather than object) classification; (2) whether unsupervised latent space models can be used for feature extraction in the classification task; and (3) whether the latent space formulation can discover visual co-occurrence patterns, motivating novel approaches for image organization and segmentation. using a 9500-image dataset, our approach is validated on each of these issues. first, we show with extensive experiments on binary and multi-class scene classification tasks, that a bag-of-visterm representation, derived from local invariant descriptors, consistently outperforms state-of-the-art approaches. second, we show that probabilistic latent semantic analysis (plsa) generates a compact scene representation, discriminative for accurate classification, and significantly more robust when less training data are available. third, we have exploited the ability of plsa to automatically extract visually meaningful aspects, to propose new algorithms for aspect-based image ranking and context-sensitive image segmentation.
a snake for model-based segmentation. despite the promising results of numerous applications, the hitherto proposed snake techniques share some common problems: snake attraction by spurious edge points, snake degeneration (shrinking and flattening), convergence and stability of the deformation process, snake initialization and local determination of the parameters of elasticity. we argue here that these problems can be solved only when all the snake aspects are considered. the snakes proposed here implement a new potential field and external force in order to provide a deformation convergence, attraction by both near and far edges as well as snake behaviour selective according to the edge orientation. furthermore, we conclude that in the case of model-based segmentation, the internal force should include structural information about the expected snake shape. experiments using this kind of snakes for segmenting bones in complex hand radiographs show a significant improvement.
learning and inference in parametric switching linear dynamical systems. we introduce parametric switching linear dynamic systems (p-slds) for learning and interpretation of parametrized motion, i.e., motion that exhibits systematic temporal and spatial variations. our motivating example is the honeybee dance: bees communicate the orientation and distance to food sources through the dance angles and waggle lengths of their stylized dances. switching linear dynamic systems (slds) are a compelling way to model such complex motions. however, slds does not provide a means to quantify systematic variations in the motion. previously, wilson ¿ bobick presented parametric hmms [21], an extension to hmms with which they successfully interpreted human gestures. inspired by their work, we similarly extend the standard slds model to obtain parametric slds. we introduce additional global parameters that represent systematic variations in the motion, and present general expectation-maximization (em) methods for learning and inference. in the learning phase, p-slds learns canonical slds model from data. in the inference phase, p-slds simultaneously quantifies the global parameters and labels the data. we apply these methods to the automatic interpretation of honey-bee dances, and present both qualitative and quantitative experimental results on actual bee-tracks collected from noisy video data.
a graph cut algorithm for generalized image deconvolution. the goal of deconvolution is to recover an image x from its convolution with a known blurring function. this is equivalent to inverting the linear system y = hx. in this paper we consider the generalized problem where the system matrix h is an arbitrary non-negative matrix. linear inverse problems can be solved by adding a regularization term to impose spatial smoothness. to avoid oversmoothing, the regularization term must preserve discontinuities; this results in a particularly challenging energy minimization problem. where h is diagonal, as occurs in image denoising, the energy function can be solved by techniques such as graph cuts, which have proven to be very effective for problems in early vision. when h is non-diagonal, however, the data cost for a pixel to have a intensity depends on the hypothesized intensities of nearby pixels, so existing graph cut methods cannot be applied. this paper shows how to use graph cuts to obtain a discontinuity-preserving solution to a linear inverse system with an arbitrary non-negative system matrix. we use a dynamically chosen approximation to the energy which can be minimized by graph cuts; minimizing this approximation also decreases the original energy. experimental results are shown for mri reconstruction from fourier data.
higher order statistical learning for vehicle detection in images. the paper describes a scheme for detecting vehicles in images. the proposed method approximately models the unknown distribution of the images of vehicles by learning higher order statistics (hos) information of the `vehicle class' from sample images. given a test image, statistical information about the background is learnt `on the y'. an hos-based decision measure then classifies test patterns as vehicles or otherwise.when tested on real images of aerial views of vehicular activity, the method gives good results even on complicated scenes. it does not require any a priori information about the site. however, it is amenable to augmentation with contextual information. the method can serve as an important step towards building an automated roadway monitoring system.
obstacle detection using projective invariant and vanishing lines. this paper presents a novel method for detecting vehicles as obstacles in various road scenes using a single on-board camera. vehicles are detected by testing whether the motion of a set of three horizontal line segments, which are always on the vehicles, satisfies the motion constraint of the ground plane or that of the surface plane of the vehicles. the motion constraint of each plane is derived from the projective invariant combined with the vanishing line of the plane that is a prior knowledge of road scenes. the proposed method is implemented into a newly developed on-board lsi. experimental results for real road scenes under various conditions show the effectiveness of the proposed method.
optimal recovery of depth from defocused images using an mrf model. a map-mrf based scheme is proposed for recovering the depth and the focused image of a scene from two defocused images. the space-variant blur parameter and the focused image of the scene are both modeled as mrfs and their map estimates are obtained using simulated annealing. the performance of the proposed scheme is tested on both synthetic as well as real data and the estimates of the depth are found to be better than that of the existing window-based technique.
autocalibration of a projector-screen-camera system: theory and algorithm for screen-to-camera homography estimation. this paper deals with the autocalibration of a systemthat consists of a planar screen, multiple projectors, and acamera. in the system, either multiple projectors or a singlemoving projector projects patterns on a screen while a stationarycamera placed in front of the screen takes images ofthe patterns. we treat the case in which the patterns that theprojectors project toward space are assumed to be known(i.e., the projectors are calibrated), whereas poses of theprojectors are unknown. under these conditions, we considerthe problem of estimating screen-to-camera homographyfrom the images alone. this is intended for cases wherethere is no clue on the screen surface that enables directestimation of the screen-to-camera homography. one applicationis a 6dof input device; poses of a multi-beamprojector freely moving in space are computed from the imagesof beam spots on the screen. the primary contributionof the paper is theoretical results on the uniqueness of solutionsand a noniterative algorithm for the problem. theeffectiveness of the method is shown by experimental resultson synthetic as well as on real images.
finding faces in photographs. two new schemes are presented for finding human faces in a photograph. the first scheme approximates the unknown distributions of the face and the face-like manifolds using higher order statistics (hos). an hos-based data clustering algorithm is also proposed. in the second scheme, the face to non-face and non-face to face transitions are learnt using a hidden markov model (hmm). the hmm parameters are estimated corresponding to a given photograph and the faces are located by examining the optimal state sequence of the hmm. experimental results are presented on the performance of both the schemes.
fast and accurate self-calibration. this paper describes new techniques for self calibration and for recovering the motion from a projective reconstruction when the calibration is known. we show that our approach deals with the ambiguities in self calibration produced by special motions. we extend our techniques to deal with varying calibration parameters. in passing, we prove convergence for the iterative projective reconstruction algorithm of sturm/triggs and berthilsson/heyden/sparr.
using temporal coherence to build models of animals. this paper describes a system that can build appearance models of animals automatically from a video sequence of the relevant animal with no explicit supervisory information. the video sequence need not have any form of special background. animals are modeled as a 2d kinematic chain of rectangular segments, where the number of segments and the topology of the chain are unknown. the system detects possible segments, clusters segments whose appearance is coherent over time, and then builds a spatial model of such segment clusters. the resulting representation of the spatial configuration of the animal in each frame can be seen either as a track - in which case the system described should be viewed as a generalized tracker, that is capable of modeling objects while tracking them - or as the source of an appearance model which can be used to build detectors for the particular animal. this is because knowing a video sequence is temporally coherent - i.e. that a particular animal is present through the sequence - is a strong supervisory signal. the method is shown to be successful as a tracker on video sequences of real scenes showing three different animals. for the same reason it is successful as a tracker, the method results in detectors that can be used to find each animal fairly reliably within the corel collection of images.
new algorithms for two-frame structure from motion. we describe two new algorithms for two frame structure from motion from tracked point features. one is the first fast algorithm for computing an exact least squares estimate. it exploits our observation that the rotationally invariant least squares error can be written in a simple form that depends just on the motion. the other is essentially as accurate as the least squares estimate and is more efficient, probably faster, and potentially more robust than previous algorithms of comparable accuracy. we also analyze theoretically the accuracy of the optical flow approximation to the least squares error.
a bayesian network framework for relational shape matching. a bayesian network formulation for relational shapematching is presented. the main advantage of the relationalshape matching approach is the obviation ofthe non-rigid spatial mappings used by recent non-rigidmatching approaches. the basic variables that need tobe estimated in the relational shape matching objectivefunction are the global rotation and scale and the localdisplacements and correspondences. the new bethefree energy approach is used to estimate the pairwisecorrespondences between links of the template graphsand the data. the resulting framework is useful inboth registration and recognition contexts. results areshown on hand-drawn templates and on 2d transverset1-weighted mr images.
a theory of specular surface geometry. a theoretical framework is introduced for the perception of specular surface geometry. when an observer moves in three-dimensional space, real scene features, such as surface markings, remain stationary with respect to the surfaces they belong to. in contrast, a virtual feature, which is the specular reflection of a real feature, travels on the surface. based on the notion of caustics, a novel feature classification algorithm is developed that distinguishes real and virtual features from their image trajectories that result from observer motion. next, using support functions of curves, a closed-form relation is derived between the image trajectory of a virtual feature and the geometry of the specular surface it travels on. it is shown that in the 2d case where camera motion and the surface profile are coplanar, the profile is uniquely recovered by tracking just two unknown virtual features. finally, these results are generalized to the case of arbitrary 3d surface profiles that are travelled by virtual features when camera motion is not confined to a plane. an algorithm is developed that uniquely recovers 3d surface profiles using a single virtual feature tracked from the occluding boundary of the object. all theoretical derivations and proposed algorithms are substantiated by experiments.
object indexing using an iconic sparse distributed memory. a general-purpose object indexing technique is described that combines the virtues of principal component analysis with the favorable matching properties of high-dimensional spaces to achieve high-precision recognition. an object is represented by a set of high-dimensional iconic feature vectors comprised of the responses of derivatives of gaussian filters at a range of orientations and scales. since these filters can be shown to form the eigenvectors of arbitrary images containing both natural and man-made structures, they are well-suited for indexing in disparate domains. the indexing algorithm uses an active vision system in conjunction with a modified form of kanerva's (1988, 1993) sparse distributed memory which facilitates interpolation between views and provides a convenient platform for learning the association between an object's appearance and its identity. the robustness of the indexing method was experimentally confirmed by subjecting the method to a range of viewing conditions and the accuracy was verified using a well-known model database containing a number of complex 3d objects under varying pose.
view-invariant alignment and matching of video sequences. in this paper, we propose a novel method to establish temporalcorrespondence between the frames of two videos. 3d epipolargeometry is used to eliminate the distortion generated bythe projection from 3d to 2d. although the fundamental matrixcontains the extrinsic property of the projective geometrybetween views, it is sensitive to noise. therefore, wepropose the use of a rank constraint of corresponding pointsin two views to measure the similarity between trajectories.this rank constraint shows more robustness and avoids computationof the fundamental matrix. a dynamic programmingapproach using the similarity measurement is proposed to findthe non-linear time-warping function for videos containinghuman activities. in this way, videos of different individualstaken at different times and from distinct viewpoints canbe synchronized. a temporal pyramid of trajectories is appliedto improve the accuracy of the view-invariant dynamictime-warping approach. we show various applications of thisapproach such as video synthesis, human action recognition,and computer aider training. compared to state-of-the-arttechniques, our method shows a great improvement.
on the equivalence of common approaches to lighting insensitive recognition. lighting variation is commonly handled by methods invariant to additive and multiplicative changes in image intensity. it has been demonstrated that comparing images using the direction of the gradient can produce broader insensitivity to changes in lighting conditions, even for 3d scenes. we analyze two common approaches to image comparison that are invariant, normalized correlation using small correlation windows, and comparison based on a large set of oriented difference of gaussian filters. we show analytically that these methods calculate a monotonic (cosine) function of the gradient direction difference and hence are equivalent to the direction of gradient method. our analysis is supported with experiments on both synthetic and real scenes.
prior-based segmentation by projective registration and level sets. object detection and segmentation can be facilitated by the availability of a reference object. however, accounting for possible transformations between the different object views, as part of the segmentation process, remains a challenge. recent works address this problem by using comprehensive training data. other approaches are applicable only to limited object classes or can only accommodate similarity transformations. we suggest a novel variational approach to prior-based segmentation, which accounts for planar projective transformation, using a single reference object. the prior shape is registered concurrently with the segmentation process, without point correspondence. the algorithm detects the object of interest and correctly extracts its boundaries. the homography between the two object views is accurately recovered as well. extending the chan-vese level set framework, we propose a region-based segmentation functional that includes explicit representation of the projective homography between the prior shape and the shape to segment. the formulation is derived from two-view geometry. segmentation of a variety of objects is demonstrated and the recovered transformation is verified.
segmentation of hybrid motions via hybrid quadratic surface analysis. in this paper, we investigate the mathematical problem underlying segmentation of hybrid motions: given a series of tracked feature correspondences between two (perspective) images, we seek to segment and estimate multiple motions, possibly of different types (e.g., affine, epipolar, and homography). in order to accomplish this task, we cast the problem into a more general mathematical framework of segmenting data samples drawn from a mixture of linear subspaces and quadratic surfaces. the result is a novel algorithm called hybrid quadratic surface analysis (hqsa). hqsa uses both the derivatives and hessians of fitting poly-nomials for the data to separate linear data samples from quadratic data samples. these derivatives and hessians also lead to important necessary conditions, based on the so-called mutual contraction subspace, to separate data samples on different quadratic surfaces. the algebraic solution we derive is non-iterative and numerically stable. it tolerates moderate noise and can be used in conjunction with outlier removal techniques. we show how to solve the hybrid motion segmentation problem using hqsa, and demonstrate its performance on simulated data with noise and on real perspective images.
retrieving images by appearance. a system to retrieve images using a description of the image intensity surface is presented. gaussian derivative filters at several scales are applied to the image and low order 2d differential invariants are computed. the resulting multi-scale representation is indexed for rapid retrieval. queries are designed by the users from an example image by selecting appropriate regions. the invariant vectors corresponding to these regions are matched with the database counter-parts both in feature and coordinate space. this yields a match score per image. images are sorted by the match score and displayed. experiments conducted with over 1500 images of objects embedded in arbitrary backgrounds are described. it is observed that images similar in appearance and whose viewpoint is within small view variations of the query can be retrieved with an average precision1 of 56%.
an ensemble prior of image structure for cross-modal inference. in cross-modal inference, we estimate complete fields from noisy and missing observations of one sensory modality using structure found in another sensory modality. this inference problem occurs in several areas including texture reconstruction and reconstruction of geophysical fields. we propose a method for cross-modal inference that simultaneously learns shape recipes between two modalities and estimates missing information by using a prior on image structure gleaned from the alternate modality. in the absence of a physical basis for representing image priors, we use a statistical one that represents correlations in differential features. this is done efficiently using a perturbation sampling scheme. using just one example of the alternate modality, we produce a factorized ensemble representation of feature correlations that yields efficient solutions to large-sized spatial inference problems. we demonstrate the utility of this approach on cross-modal inference with depth and spectral data.
model-based tracking of self-occluding articulated objects. computer sensing of hand and limb motion is an important problem for applications in human computer interaction and computer graphics. we describe a framework for local trading of self occluding motion, in which one part of an object obstructs the visibility of another. our approach uses a kinematic model to predict occlusions and windowed templates to track partially occluded objects. we present offline 3d tracking results for hand motion with significant self occlusion.
agent orientated annotation in model based visual surveillance. the paper presents an agent based surveillance system for use in monitoring scenes involving both pedestrians and vehicles. the surveillance system supplies textual descriptions for the dynamic activity occurring in the 3d world. these are derived by means of dynamic andprobabilistic inference based on geometric information provided by a vision system that tracks vehicles and pedestrians. the symbolic scene annotation is given at two major levels of description: the object level and the interobject level. at object level, each tracked object(pedestrian or vehicle) is assigned a behaviour agent which uses a bayesian network to infer the fundamental features of the objects' trajectory, and continuously updates its textual description. the inter-object interaction level is interpreted by a situation agent which is created dynamically when two objects are in close proximity.
recovering human body configurations using pairwise constraints between parts. the goal of this work is to recover human bodyconfigurations from static images. without assuming a priori knowledge of scale, pose or appearance, this problem is extremely challenging and demands the use of all possible sources of information. we develop a framework which can incorporate arbitrary pairwise constraints between body parts, such as scale compatibility, relative position, symmetry of clothing and smooth contour connections between parts. we detect candidate body parts from bottom-up using parallelism, and use various pairwise configuration constraints to assemble them together into body configurations. to find the most probable configuration, we solve an integer quadratic programming problem with a standard technique using linear approximations. approximate iqp allows us to incorporate much more information than the traditional dynamic programming and remains computationally efficient. 15 hand-labeled images are used to train the low-level part detector and learn the pairwise constraints. we show test results on a variety of images.
scale-invariant contour completion using conditional random fields. we present a model of curvilinear grouping using piece-wise linear representations of contours and a conditional random field to capture continuity and the frequency of different junction types. potential completions are generated by building a constrained delaunay triangulation (cdt) over the set of contours found by a local edge detector. maximum likelihood parameters for the model are learned from human labeled groundtruth. using held out test data, we measure how the model, by incorporating continuity structure, improves boundary detection over the local edge detector. we also compare performance with a baseline local classifier that operates on pairs of edgels. both algorithms consistently dominate the low-level boundary detector at all thresholds. to our knowledge, this is the first time that curvilinear continuity has been shown quantitatively useful for a large variety of natural images. better boundary detection has immediate application in the problem of object detection and recognition.
learning a classification model for segmentation. we propose a two-class classification model for grouping. human segmented natural images are used as positive examples. negative examples of grouping are constructed by randomly matching human segmentations and images. in a preprocessing stage an image is over segmented into superpixels. we define a variety of features derived from the classical gestalt cues, including contour, texture, brightness and good continuation. information-theoretic analysis is applied to evaluate the power of these grouping cues. we train a linear classifier to combine these features. to demonstrate the power of the classification model, a simple algorithm is used to randomly search for good segmentations. results are shown on a wide range of images.
a cluster-based statistical model for object detection. this paper presents an approach to object detection which is based on recent work in statistical models for texture synthesis and recognition (heeger and bergen 1995, de bonet and viola 1998, zhu et al. 1998, simoncelli and portilla 1998). our method follows the texture recognition work of de bonet and viola. we use feature vectors which capture the joint occurrence of local features at multiple resolutions. the distribution of feature vectors for a set of training images of an object class is estimated by clustering the data and then forming a mixture of gaussian model. the mixture model is further refined by determining which clusters are the most discriminative for the class and retaining only those clusters. after the model is learned, test images are classified by computing the likelihood of their feature vectors with respect to the model. we present promising results in applying our technique to face detection and car detection.
weakly-calibrated stereo perception for rover navigation. presents a vision system for autonomous navigation based on stereo perception without 3d reconstruction. this approach uses weakly calibrated stereo images, i.e. images for which only the epipolar geometry is known. the vision system first rectifies the images, matches selected points between the two images, and then computes the relative elevation of the points relative to a reference plane as well as the images of their projections on this plane. we have integrated this vision module into a complete navigation system. in this system, the relative elevation is used as a shape indicator in order to compute appropriate steering directions everytime a new stereo pair is processed. we have conducted initial experiments in unstructured, outdoor environments with an wheeled rover.
vehicle identification between non-overlapping cameras without direct feature matching. we propose a novel method for identifying road vehicles between two non-overlapping cameras. the problem is formulated as a same-different classification problem: probability of two vehicle images from two distinct cameras being from the same vehicle or from different vehicles. the key idea is to compute the probability without matching the two vehicle images directly, which is a process vulnerable to drastic appearance and aspect changes. we represent each vehicle image as an embedding amongst representative exemplars of vehicles within the same camera. the embedding is computed as a vector each of whose components is a non-metric distance for a vehicle to an exemplar. the non-metric distances are computed using robust matching of oriented edge images. a set of truthed training examples of same-different vehicle pairings across the two cameras is used to learn a classifier that encodes the probability distributions. a pair of the embeddings representing two vehicles across two cameras are then used to compute the same-different probability. in order for the vehicle exemplars to be representative for both cameras, we also propose a method for jointly selection of corresponding exemplars using the training data. experiments on observations of over 400 vehicles under drastically illumination and camera conditions demonstrate promising results.
behaviour understanding in video: a combined method. in this paper we develop a system for human behaviour recognition in video sequences. human behaviour is modelled as a stochastic sequence of actions. actions are described by a feature vector comprising both trajectory information (position and velocity), and a set of local motion descriptors. action recognition is achieved via probabilistic search of image feature databases representing previously seen actions. a hmm which encodes the rules of the scene is used to smooth sequences of actions. high-level behaviour recognition is achieved by computing the likelihood that a set of predefined hidden markov models explains the current action sequence. thus, human actions and behaviour are represented using a hierarchy of abstraction: from simple actions, to actions with spatio-temporal context, to action sequences and finally general behaviours. while the upper levels all use (parametric) bayes networks and belief propagation, the lowest level uses non-parametric sampling from a previously learned database of actions. the combined method represents a general framework for human behaviour modelling. in this paper we demonstrate the results chiefly on broadcast tennis sequences for automated video annotation.
face recognition with mrc-boosting. in this paper, a novel classification algorithm called mrc-boosting is proposed. through aggregating maximal-rejection-classifier features under boosting framework, this algorithm can deal with complicated two-class classification problem, especially for the category called target detection problem where a target class should be discriminated from the surrounding clutter class. mrc-boosting is efficient since unlike many other boosting based algorithms, at each iteration the optimal feature is computed in closed-form, with neither exhaustive search nor time-consuming numerical optimization. furthermore, a variant of mrc-boosting is derived and applied to face recognition. this variant mrc-boosting algorithm is able to utilize large amount of training samples efficiently, overcoming the difficulty faced by other algorithms like adaboost. the effectiveness of the proposed algorithm is validated by face recognition experiments on cmu-pie database.
a non-iterative greedy algorithm for multi-frame point correspondence. this paper presents a framework for finding point correspondences in monocular image sequences over multiple frames.the general problem of multi-frame point correspondence is np hard for three or more frames. a polynomial time algorithm for a restriction of this problem is presented, and is used as the basis of proposed greedy algorithm for the general problem. the greedy nature of the proposed algorithm allows it to be used in real time systems for tracking and surveillance etc. in addition, the proposed algorithm deals with the problems of occlusion, missed detections, and false positives, by using a single non-iterative greedy optimization scheme, and hence, reduces the complexity of the overall algorithm as compared to most existing approaches, where multiple heuristics are used for the same purpose.while most greedy algorithms for point tracking do not allow for entry and exit of points from the scene, this is not a limitation for the proposed algorithm. experiments with real and synthetic data show that the proposed algorithm outperforms the existing techniques and is applicable in more general settings.
integrating the effects of motion, illumination and structure in video sequences. most work in computer vision has concentrated on studying the individual effects of motion and illumination on a 3d object. in this paper, we present a theory for combining the effects of motion, illumination, 3d structure, albedo, and camera parameters in a sequence of images obtained by a perspective camera. we show that the set of all lambertian reflectance functions of a moving object, illuminated by arbitrarily distant light sources, lies "close" to a bilinear subspace consisting of nine illumination variables and six motion variables. this result implies that, given an arbitrary video sequence, it is possible to recover the 3d structure, motion and illumination conditions simultaneously using the bilinear subspace formulation. the derivation is based on the intuitive notion that, given an illumination direction, the images of a moving surface cannot change suddenly over a short time period. we experimentally compare the images obtained using our theory with ground truth data and show that the difference is small and acceptable. we also provide experimental results on real data by synthesizing video sequences of a 3d face with various combinations of motion and illumination directions.
edit distance from graph spectra. this paper is concerned with computing graph edit distance. one of the criticisms that can be leveled at existing methods for computing graph edit distance is that it lacks the formality and rigour of the computation of string edit distance. hence, our aim is to convert graphs to string sequences so that standard string edit distance techniques can be used. to do this we use graph spectral seriation method to convert the adjacency matrix into a string or sequence order. we pose the problem of graph-matching as maximum aposteriori probability alignment of the seriation sequences for pairs of graphs. this treatment leads to an expression for the edit costs. we compute the edit distance by finding the sequence of string edit operations which minimise the cost of the path traversing the edit lattice. the edit costs are defined in terms of the a posteriori probability of visiting a site on the lattice. we demonstrate the method with results on a data-set of delaunay graphs.
phase field models and higher-order active contours. the representation and modelling of regions is an important topic in computer vision. in this paper, we represent a region via a level set of a ¿phase field¿ function. the function is not constrained, e.g. to be a distance function; nevertheless, phase field energies equivalent to classical active contour energies can be defined. they represent an advantageous alternative to other methods: a linear representation space; ease of implementation (a pde with no reinitialization); neutral initialization; greater topological freedom. we extend the basic phase field model with terms that reproduce ¿higher-order active contour¿ energies, a powerful way of including prior geometric knowledge in the active contour framework via nonlocal interactions between contour points. in addition to the above advantages, the phase field greatly simplifies the analysis and implementation of the higher-order terms. we define a phase field model that favours regions composed of thin arms meeting at junctions, combine this with image terms, and apply the model to the extraction of line networks from remote sensing images.
automatic registration of 3-d ultrasound images. one of the most promising applications of 3-d ultrasound lies in the visualisation and volume estimation of internal 3-d structures. unfortunately, artifacts and speckle make automatic analysis of the data difficult. in this paper we investigate the use of 3-d spatial compounding to improve data quality, and find that accurate registration is the key. a correlation-based registration technique is applied to 3-d ultrasound data acquired from in-vivo examinations of a human gall bladder. we find that the registration technique performs well, and visualisation and segmentation of the compounded data are clearly improved.
trilinearity of three perspective views and its associated tensor. it has been established that certain trilinear forms of three perspective views give rise to a tensor of 27 intrinsic coefficients. we show in this paper that a permutation of the the trilinear coefficients produces three homography matrices (projective transformations of planes) of three distinct intrinsic planes, respectively. this, in turn, yields the result that 3d invariants are recovered directly-simply by appropriate arrangement of the tensor's coefficients. on a secondary level, we show new relations between fundamental matrix, epipoles, euclidean structure and the trilinear tensor. on the practical side, the new results extend the existing envelope of methods of 3d recovery from 2d views-for example, new linear methods that cut through the epipolar geometry, and new methods for computing epipolar geometry using redundancy available across many views.
object tracking across multiple independently moving aerial cameras. a camera mounted on an aerial vehicle provides an excellent means for monitoring large areas of a scene. utilizing several such cameras on different aerial vehicles allows further flexibility, in terms of increased visual scope and in the pursuit of multiple targets. in this paper, we address the problem of tracking objects across multiple moving airborne cameras. since the cameras are moving and often widely separated, direct appearance-based or proximity-based constraints cannot be used. instead, we exploit geometric constraints on the relationship between the motion of each object across cameras, to test multiple correspondence hypotheses, without assuming any prior calibration information. we propose a statistically and geometrically meaningful means of evaluating a hypothesized correspondence between two observations in different cameras. second, since multiple cameras exist, ensuring coherency in correspondence, i.e. transitive closure is maintained between more than two cameras, is an essential requirement. to ensure such coherency we pose the problem of object tracking across cameras as a k-dimensional matching and use an approximation to find the maximum likelihood assignment of correspondence. third, we show that as a result of tracking objects across the cameras, a concurrent visualization of multiple aerial video streams is possible. results are shown on a number of real and controlled scenarios with multiple objects observed by multiple cameras, validating our qualitative models.
efficient, robust and accurate fitting of a 3d morphable model. 3d morphable models, as a means to generate images of a class of objects and to analyze them, have become increasingly popular. the problematic part of this frameworkis the registration of the model to an image, a.k.a. the fitting. the characteristic features of a fitting algorithm are its efficiency, robustness, accuracy and automation. many accurate algorithms based on gradient descent techniques exist which are unfortunately short on the other features. recently, an efficient algorithm called inverse compositional image alignment (icia) algorithm, able to fit 2d images, was introduced. in this paper, we extent this algorithm to fit 3d morphable models using a novel mathematical notation which facilitates the formulation of the fitting problem. this formulation enables us to avoid a simplification so far used in the icia, being as efficient and leading to improved fitting precision. additionally, the algorithm is robust without sacrificing its efficiency and accuracy, thereby conforming to three of the four characteristics of a good fitting algorithm.
exploring the space of a human action. one of the fundamental challenges of recognizing actions is accounting for the variability that arises when arbitrary cameras capture humans performing actions. in this paper, we explicitly identify three important sources of variability: (1) viewpoint, (2) execution rate, and (3) anthropometry of actors, and propose a model of human actions that allows us to investigate all three. our hypothesis is that the variability associated with the execution of an action can be closely approximated by a linear combination of action bases in joint spatio-temporal space. we demonstrate that such a model bounds the rank of a matrix of image measurements and that this bound can be used to achieve recognition of actions based only on imaged data. a test employing principal angles between subspaces that is robust to statistical fluctuations in measurement data is presented to find the membership of an instance of an action. the algorithm is applied to recognize several actions, and promising results have been obtained.
unsupervised image translation. an interesting and potentially useful vision/graphics task is to render an input image in an enhanced form or also in an unusual style; for example with increased sharpness or with some artistic qualities. in previous work [10, 5],researchers showed that by estimating the mapping from an input image to a registered (aligned) image of the same scene in a different style or resolution, the mapping could be used to render a new input image in that style or resolution. frequently a registered pair is not available, but instead the user may have only a source image of an unrelated scene that contains the desired style. in this case, the task of inferring the output image is much more difficult since the algorithm must both infer correspondences between features in the input image and the source image, and infer the unknown mapping between the images. we describe a bayesian technique for inferring the most likely output image. the prior on the output image p ( x )is a patch-based markov random field obtained from the source image. the likelihood of the input p ( y|x )is a bayesian network that can represent different rendering styles. we describe a computationally efficient, probabilistic inference and learning algorithm for inferring the most likely output image and learning the rendering style. we also show that current techniques for image restoration or reconstruction proposed in the vision literature (e.g., image super-resolution or de-noising) and image-based non-photorealistic rendering could be seen as special cases of our model. we demonstrate our technique using several tasks, including rendering a photograph in the artistic style of an unrelated scene, de-noising, and texture transfer.
fast global kernel density mode seeking with application to localisation and tracking. we address the problem of seeking the global mode of a density function using the mean shift algorithm. mean shift, like other gradient ascent optimisation methods, is susceptible to local maxima, and hence often fails to find the desired global maximum. in this work, we propose a multi-bandwidth mean shift procedure that alleviates this problem, which we term annealed mean shift, as it shares similarities with the annealed importance sampling procedure. the bandwidth of the algorithm plays the same role as the temperature in annealing. we observe that the over-smoothed density function with a sufficiently large bandwidth is uni-modal. using a continuation principle, the influence of the global peak in the density function is introduced gradually. in this way the global maximum is more reliably located. generally, the price of this annealing-like procedure is that more iterations are required. since it is imperative that the computation complexity is minimal in real-time applications such as visual tracking. we propose an accelerated version of the mean shift algorithm. compared with the conventional mean shift algorithm, the accelerated mean shift can significantly decrease the number of iterations required for convergence. the proposed algorithm is applied to the problems of visual tracking and object localisation. we empirically show on various data sets that the proposed algorithm can reliably find the true object location when the starting position of mean shift is far away from the global maximum, in contrast with the conventional mean shift algorithm that will usually get trapped in a spurious local maximum.
learning and inferring image segmentations using the gbp typical cut algorithm. significant progress in image segmentation has beenmade by viewing the problem in the framework of graphpartitioning. in particular, spectral clustering methods suchas "normalized cuts" (ncuts) can efficiently calculate goodsegmentations using eigenvector calculations. however,spectral methods when applied to images with local connectivityoften oversegment homogenous regions. more importantly,they lack a straightforward probabilistic interpretationwhich makes it difficult to automatically set parametersusing training data.in this paper we revisit the typical cut criterion proposedin [1, 5]. we show that computing the typical cut isequivalent to performing inference in an undirected graphicalmodel. this equivalence allows us to use the powerfulmachinery of graphical models for learning and inferringimage segmentations. for inferring segmentations weshow that the generalized belief propagation (gbp) algorithmcan give excellent results with a runtime that is usuallyfaster than the ncut eigensolver. for learning segmentationswe derive a maximum likelihood learning algorithmto learn affinity matrices from labelled datasets. we illustrateboth learning and inference on challenging real andsynthetic images.
thresholding for change detection. image differencing is used for many applications involving change detection. although it is usually followed by a thresholding operation to isolate regions of change there are few methods available in the literature specific to (and appropriate for) change detection. we describe four different methods for selecting thresholds that work on very different principles. either the noise or the signal is modelled, and the model covers either the spatial or intensity distribution characteristics. the methods are: 1/ a normal model is used for the noise intensity distribution, 2/ signal intensities are tested by making local intensity distribution comparisons in the two image frames (i.e. the difference map is not used), 3/ the spatial properties of the noise are modelled by a poisson distribution, and 4/ the spatial properties of the signal are modelled as a stable number of regions (or stable euler number).
motion segmentation and tracking using normalized cuts. we propose a motion segmentation algorithm that aims to break a scene into its most prominent moving groups. a weighted graph is constructed on the image sequence by connecting pixels that are in the spatiotemporal neighborhood of each other. at each pixel, we define motion profile vectors which capture the probability distrobution of the image velocity. the distance between motion profiles is used to assign a weight on the graph edges. using normalized cuts we find the most salient partitions of the spaciotemporal graph formed by the image sequence. for segmenting long image sequences, we have developed a recursive update procedure that incorporates knowledge of segmentation in previous frames for efficiently finding the group correspondence in the new frame.
fusing points and lines for high performance tracking. this paper addresses the problem of real-time 3d model-based tracking by combining point-based and edge-based tracking systems. we present a careful analysis of the properties of these two sensor systems and show that this leads to some non-trivial design choices that collectively yield extremely high performance. in particular, we present a method for integrating the two systems and robustly combining the pose estimates they produce. further we show how on-line learning can be used to improve the performance of feature tracking. finally, to aid real-time performance, we introduce the fast feature detector which can perform full-frame feature detection at 400hz. the combination of these techniques results in a system which is capable of tracking average prediction errors of 200 pixels. this level of robustness allows us to track very rapid motions, such as 50.camera shake at 6hz.
a model-based integrated approach to track myocardial deformation using displacement and velocity constraints. accurate estimation of heart wall dense field motion and deformation could help to better understand the physiological processes associated with ischemic heart diseases, and to provide significant improvement in patient treatment. we present a new method of estimating left ventricular deformation which integrates instantaneous velocity information obtained within the mid-wall region with shape information found on the boundaries of the left ventricle. velocity information is obtained from phase contrast magnetic resonance images, and boundary information is obtained from shape-based motion tracking of the endo- and cardial boundaries. the integration takes place within a continuum biomechanical heart model which is embedded in a finite element framework. we also employ a feedback mechanism to improve tracking accuracy. the integration of the two disparate but complementary sources overcomes some of the limitations of previous work in the field which concentrates on motion estimation from a single image-derived source.
on the spatial statistics of optical flow. we develop a method for learning the spatial statistics of optical flow fields from a novel training database. training flow fields are constructed using range images of natural scenes and 3d camera motions recovered from hand-held and car-mounted video sequences. a detailed analysis of optical flow statistics in natural scenes is presented and machine learning methods are developed to learn a markov random field model of optical flow. the prior probability of a flow field is formulated as a field-of-experts model that captures the higher order spatial statistics in overlapping patches and is trained using contrastive divergence. this new optical flow prior is compared with previous robust priors and is incorporated into a recent, accurate algorithm for dense optical flow computation. experiments with natural and synthetic sequences illustrate how the learned optical flow prior quantitatively improves flow accuracy and how it captures the rich spatial structure found in natural scene motion.
learning non-generative grammatical models for document analysis. we present a general approach for the hierarchical segmentation and labeling of document layout structures. this approach models document layout as a grammar and performs a global search for the optimal parse based on a grammatical cost function. our contribution is to utilize machine learning to discriminatively select features and set all parameters in the parsing process. therefore, and unlike many other approaches for layout analysis, ours can easily adapt itself to a variety of document analysis problems. one need only specify the page grammar and provide a set of correctly labeled pages. we apply this technique to two document image analysis tasks: page layout structure extraction and mathematical expression interpretation. experiments demonstrate that the learned grammars can be used to extract the document structure in 57 files from the uwiii document image database. we also show that the same framework can be used to automatically interpret printed mathematical expressions so as to recreate the original latex.
linear multi-view reconstruction of points, lines, planes and cameras using a reference plane. this paper presents a new linear method for reconstructingsimultaneously 3d features (points, lines and planes)and cameras from many perspective views by solving a singlelinear system. it assumes that a real or virtual referenceplane is visible in all views. we call it the direct referenceplane (drp) method. it is well known that the projection relationshipbetween uncalibrated cameras and 3d featuresis non-linear in the absence of a reference plane. with aknown reference plane, points and cameras have a linearrelationship, as shown in [16]. the main contribution ofthis paper is that lines and cameras, as well as, planes andcameras also have a linear relationship. consequently, all3d features and all cameras can be reconstructed simultaneouslyfrom a single linear system, which handles missingimage measurements naturally. a further contribution is anextensive experimental comparison, using real data, of differentreference plane and non-reference plane reconstructionmethods. for difficult reference plane scenarios, withpoint or line features, the drp method is superior to allcompared methods. finally, an extensive list of referenceplane scenarios is presented, which shows the wide applicabilityof the drp method.
probabilistic 3d object recognition. a probabilistic 3d object recognition algorithm is presented. in order to guide the recognition process the probability that match hypotheses between image features and model features are correct is computed. a model is developed which uses the probabilistic peaking effect of measured angles and ratios of lengths by tracing iso angle and iso ratio curves on the viewing sphere. the model also accounts for various types of uncertainty in the input such as incomplete and inexact edge detection. for each match hypothesis the pose of the object and the pose uncertainty which is due to the uncertainty in vertex position are recovered. this is used to find sets of hypotheses which reinforce each other by matching features of the same object with compatible uncertainty subsets. a probabalistic expression is used to rank these hypothesis sets. the hypothesis sets with the highest rank are output. the algorithm has been fully implemented, and tested on real images.
a comparison of projective reconstruction methods for pairs of views. recently, different approaches for uncalibrated stereo have been suggested which permit projective reconstruction from multiple views. these use weak calibration which is represented by the epipolar geometry, and so no knowledge of the intrinsic or extrinsic camera parameters is required. we consider projective reconstructions from pairs of views, and compare a number of the available methods. consequently we conclude which methods are most likely to be of use in applications that are dependent on 3d uncalibrated reconstructions.
non-negative lighting and specular object recognition. recognition of specular objects is particularly difficult because their appearance is much more sensitive to lighting changes than that of lambertian objects. we consider an approach in which we use a 3d model to deduce the lighting that best matches the model to the image. in this case, an important constraint is that incident lighting should be non-negative everywhere. in this paper, we propose a new method to enforce this constraint and explore its usefulness in specular object recognition, using the spherical harmonic representation of lighting. the method follows from a novel extension of szego¿s eigenvalue distribution theorem to spherical harmonics, and uses semidefinite programming to perform a constrained optimization. the new method is faster as well as more accurate than previous methods. experiments on both synthetic and real data indicate that the constraint can improve recognition of specular objects by better separating the correct and incorrect models.
universal mosaicing using pipe projection. video mosaicing is commonly used to increase the visual field of view by pasting together many video frames. existing mosaicing methods are effective only in very limited cases where the image motion is almost a uniform translation or the camera performs a pure pan. forward camera motion or camera zoom are very problematic for traditional mosaicing.a mosaicing methodology to allow image mosaicing in the most general cases is presented, where frames in the video sequence are transformed such that the optical flow becomes parallel. this transformation is an oblique projection of the image into a "viewing pipe" whose central axis is the trajectory of the camera.the "pipe projection" enables to define high-quality mosaicing even for the most challenging cases of forward motion and of zoom. in addition, view interpolation, generating dense intermediate views, is used to overcome parallax effects.
view-based object matching. we introduce a novel view-based object representation, called the saliency map graph (smg), which captures the salient regions of an object view at multiple scales using a wavelet transform. this compact representation is highly invariant to translation, rotation (image and depth), and scaling, and offers the locality of representation required for occluded object recognition. to compare two saliency map graphs, we introduce two graph similarity algorithms. the first computes the topological similarity between two smg's, providing a coarse-level matching of two graphs. the second computes the geometrical similarity betweentwo smg's, providing a fine-level matching of two graphs. we test and compare these two algorithms on a large database of model object views.
a maximum-flow formulation of the n-camera stereo correspondence problem. this paper describes a new algorithm for solving the n-camera stereo correspondence problem by transforming it into a maximum-flow problem. once solved, the minimum-cut associated to the maximum-flow yields a disparity surface for the whole image at once. this global approach to stereo analysis provides a more accurate and coherent depth map than the traditional line-by-line stereo. moreover, the optimality of the depth surface is guaranteed and can be shown to be a generalization of the dynamic programming approach that is widely used in standard stereo. results show improved depth estimation as well as better handling of depth discontinuities. while the worst case running time is o(n2d2 log(nd)), the observed average running time is o(n1.2d1.3) for an image size of n pixels and depth resolution d.
contour-based learning for object detection. we present a novel categorical object detection scheme that uses only local contour-based features. a two-stage, partially supervised learning architecture is proposed: a rudimentary detector is learned from a very small set of segmented images and applied to a larger training set of un-segmented images; the second stage bootstraps these detections to learn an improved classifier while explicitly training against clutter. the detectors are learned with a boosting algorithm which creates a location-sensitive classifier using a discriminative set of features from a randomly chosen dictionary of contour fragments. we present results that are very competitive with other state-of-the-art object detection schemes and show robustness to object articulations, clutter, and occlusion. our major contributions are the application of boosted local contour-based features for object detection in a partially supervised learning framework, and an efficient new boosting procedure for simultaneously selecting features and estimating per-feature parameters.
an integral approach to free-formed object modeling. presents a new approach to free-formed object modeling from multiple range images. in most conventional approaches, successive views are registered sequentially. in contrast to the sequential approaches, we propose an integral approach which reconstructs statistically optimal object models by simultaneously aggregating all data from multiple views into a weighted least-squares (wls) formulation. the integral approach has two components. first, a global resampling algorithm constructs partial representations of the object from individual views so that correspondences can be established among different views. the global resampling algorithm is based on the spherical attribute image (sai) previously introduced in the context of object representation and recognition. second, a weighted least-squares algorithm integrates resampled partial representations of multiple views, using the technique of principal component analysis with missing data (pcamd). experiments using real range images show that our approach is robust against noise and mismatches, and generates accurate object models.
texture-based image retrieval without segmentation. image segmentation is not only hard and unnecessary for texture-based image retrieval, but can even be harmful. images of either individual or multiple textures are best described by distributions of spatial frequency descriptors, rather than single descriptor vectors over pre-segmented regions.a retrieval method based on the earth movers distance with an appropriate ground distance is shown to handle both complete and partial multi-textured queries. as an illustration, different images of the same type of animal are easily retrieved together. at the same time, animals with subtly different coats, like cheetahs and leopards, are properly distinguished.
a metric for distributions with applications to image databases. we introduce a new distance between two distributions that we call the earth mover's distance (emd), which reflects the minimal amount of work that must be performed to transform one distribution into the other by moving "distribution mass" around. this is a special case of the transportation problem from linear optimization, for which efficient algorithms are available. the emd also allows for partial matching. when used to compare distributions thathave the same overall mass, the emd is a true metric, and has easy-to-compute lower bounds. in this paper we focus on applications to image databases, especially color and texture. we use the emd to exhibit the structure of color-distribution and texture spaces by means of multi-dimensional scaling displays. we also propose a novel approach to the problem of navigating through a collection of color images, which leads to a new paradigm for image database search.
construction and refinement of panoramic mosaics with global and local alignment. this paper presents techniques for constructing full view panoramic mosaics from sequences of images. our representation associates a rotation matrix (and optionally a focal length) with each input image, rather than explicitly projecting all of the images onto a common surface (e.g., a cylinder). in order to reduce accumulated registration errors, we apply global alignment (block adjustment) to the whole sequence of images, which results in an optimal image mosaic (in the least-squares sense). to compensate for small amounts of motion parallax introduced by translations of the camera and other unmodeled distortions, we develop a local alignment (deghosting) technique which warps each image based on the results of pairwise local image registrations. by combining both global and local alignment, we significantly improve the quality of our image mosaics, thereby enabling the creation of full view panoramic mosaics with hand-held cameras.
locating objects using the hausdorff distance. the hausdorff distance is a measure defined between two point sets representing a model and an image. in the past, it has been used to search images for instances of a model that has been translated or translated and scaled by finding transformations that bring a large number of model features close to image features, and vice versa. the hausdorff distance is reliable even when the image contains multiple objects, noise, spurious features, and occlusions. we apply it to the task of locating an affine transformation of a model in an image; this corresponds to determining the pose of a planar object that has undergone weak perspective projection. we develop a rasterised approach to the search and a number of techniques that allow us to quickly locate all transformations of the model that satisfy two quality criteria; we can also quickly locate only the best transformation. we discuss an implementation of this approach, and present some examples of its use.
rigid and articulated motion seen with an uncalibrated stereo rig. this paper establishes a link between uncalibrated stereo vision and the motion of rigid and articulated bodies. the variation in the projective reconstruction of a dynamic scene over time allows an uncalibrated stereo rig to be used as a faithful motion capturing device.we introduce an original theoretical framework - projective kinematics - which allows rigid and articulated motion to be represented within the transformation group of projective space. corresponding projective velocities are defined in the tangent space. most importantly, these projective motions inherit the lie-group structure of the displacement group.these theoretical results lead immediately to non-metric formulations of visual serving, tracking, motion capturing and motion synthesis systems, that no longer require the metric geometry of a stereo camera or of the articulated body to be known. we report on such a non-metric formulation of a visual serving system and present simulated experimental results.
fast texture-based tracking and delineation using texture entropy. we propose a fast texture-segmentation approach to the problem of 2-d and 3-d model-based contour tracking, which is suitable for real-time or interactive applications. our approach relies on detecting texture boundaries in the direction normal to the contour boundaries and on using a hidden markov model to link these boundary points in the other direction. the probabilities that appear in this computation closely relate to texture entropy and kullback-leibler divergence, a property we use to compute and update dynamic texture models. we demonstrate results both in the context of interactive 2-d delineation and fast 3-d tracking.
multiperspective projection and collineation. we present theories of multiperspective projection and collineation. given an arbitrary multiperspective imaging system that captures smoothly varying set of rays, we show how to map the rays onto a 2d ray manifold embedded in a 4d linear vector space. the characteristics of this imaging system, such as its projection, collineation, and image distortions can be analyzed by studying the 2-d tangent planes of this ray manifold. these tangent planes correspond to the recently proposed general linear camera (glc) model. in this paper, we study the imaging process of the glcs. we show the glc imaging process can be broken down into two separate stages: the mapping of 3d geometry to rays and the sampling of those rays over an image plane. we derive a closed-form solution to projecting 3d points in a scene to rays in a glc. a glc image is created by sampling these rays over an image plane. we develop a notion of glc collineation analogous to pinhole cameras. glc collineation describes the transformation between the images of a single glc due to changes in sampling and image plane selection. we show that general glc collineations can be characterized by a quartic (4th order) rational function. glc projection and collineation provides a basis for developing new computer vision algorithms suitable for analyzing a wider range of imaging systems than current methods, based on simple pinhole projection models, permit.
a new paradigm for recognizing 3-d object shapes from range data. most of the work on 3-d object recognition from rangedata has used an alignment-verification approach in whicha specific 3-d object is matched to an exact instance of thesame object in a scene. this approach has been successfullyused in industrial machine vision, but it is not capable ofdealing with the complexities of recognizing classes of similarobjects. this paper undertakes this task by proposingand testing a component-based methodology encompassingthree main ingredients: 1) a new way of learning and extractingshape-class components from surface shape information;2) a new shape representation called a symbolicsurface signature that summarizes the geometric relationshipsamong components; and 3) an abstract representationof shape classes formed by a hierarchy of classifiersthat learn object-class parts and their spatial relationshipsfrom examples.
the hamilton-jacobi skeleton. the eikonal equation and variants of it are of significant interest for problems in computer vision and image processing. it is the basis for continuous versions of mathematical morphology, stereo, shape-from-shading and for recent dynamic theories of shape. its numerical simulation can be delicate, owing to the formation of singularities in the evolving front, and is typically based on level set methods. however, there are more classical approaches rooted in hamiltonian physics, which have received little consideration in computer vision.in this paper we first introduce a new algorithm for simulating the eikonal equation, which offers a number of computational and conceptual advantages over the earlier methods when it comes to shock tracking. next, we introduce a very efficient algorithm for shock detection, where the key idea is to measure the net outward flux of a vector field per unit volume, and to detect locations where a conservation of energy principle is violated. we illustrate the approach with several numerical examples including skeletons of complex 2d and 3d shapes.
fast intensity-based 2d-3d image registration of clinical data using light fields. registration of a preoperative ct (3d) image to one or more x-ray projection (2d) images, a special case of the pose estimation problem, has been attempted in a variety of ways with varying degrees of success. recently, there has been a great deal of interest in intensity-based methods. one of the drawbacks to such methods is the need to create digitally reconstructed radiographs (drrs) at each step of the optimization process. drrs are typically generated by ray casting, an operation that requires o(n3) time, where we assume that n is approximately the size (in voxels) of one side of the drr as well as one side of the ct volume. we address this issue by extending light field rendering techniques from the computer graphics community to generate drrs instead of conventional rendered images. using light fields allows most of the computation to be performed in a preprocessing step; after this precomputation, very accurate drrs can be generated in o(n2) time. another important issue for 2d-3d registration algorithms is validation. previously reported 2d-3d registration algorithms were validated using synthetic data or phantoms but not clinical data. we present an intensity-based 2d-3d registration system that generates drrs using light fields; we validate its performance using clinical data with a known gold standard transformation.
shock graphs and shape matching. we have been developing a theory for the generic representation of 2-d shape, where structural descriptions are derived from the shocks "singularities" of a curve evolution process, acting on bounding contours. we now apply the theory to the problem of shape matching. the shocks are organized into a directed, acyclic shock graph, and complexity is managed by attending to the most significant "central" shape components first. the space of all such graphs is highly structured and can be characterized by the rules of a shock graph grammar. the grammar permits a reduction of a shock graph to a unique rooted shock tree. we introduce a novel tree matching algorithm which finds the best set of corresponding nodes between two shock trees in polynomial time. using a diverse database of shapes, we demonstrate our system's performance under articulation, occlusion, and changes in viewpoint.
corner detection in textured color images. corner models in the literature have lagged behind edge models with respect to color and shading. we use both a region model, based on distributions of pixel colors, and an edge model, which removes false positives, to perform corner detection on color images whose regions contain texture. we show results on a variety of natural images at different scales that highlight the problems that occur when boundaries between regions have curvature.
hyperbolic "smoothing" of shapes. we have been developing a theory of generic 2-d shape based on a reaction-diffusion model from mathematical physics. the description of a shape is derived from the singularities of a curve evolution process driven by the reaction (hyperbolic) term. the diffusion (parabolic) term is related to smoothing and shape simplification. however, the unification of the two is problematic, because the slightest amount of diffusion dominates and prevents the formation of generic first-order shocks. the technical issue is whether it is possible to smooth a shape, in any sense, without destroying the shocks. we now report a constructive solution to this problem, by embedding the smoothing term in a global metric against which a purely hyperbolic evolution is performed from the initial curve. this is a new flow for shape, that extends the advantages of the original one. specific metrics are developed, which lead to a natural hierarchy of shape features, analogous to the simplification one might perceive when viewing an object from increasing distances. we illustrate our new flow with a variety of examples.
visual speech recognition with loosely synchronized feature streams. we present an approach to detecting and recognizing spoken isolated phrases based solely on visual input. we adopt an architecture that first employs discriminative detection of visual speech and articulatory features, and then performs recognition using a model that accounts for the loose synchronization of the feature streams. discriminative classifiers detect the subclass of lip appearance corresponding to the presence of speech, and further decompose it into features corresponding to the physical components of articulatory production. these components often evolve in a semi-independent fashion, and conventional viseme-based approaches to recognition fail to capture the resulting co-articulation effects. we present a novel dynamic bayesian network with a multi-stream structure and observations consisting of articulatory feature classifier scores, which can model varying degrees of co-articulation in a principled way. we evaluate our visual-only recognition system on a command utterance task. we show comparative results on lip detection and speech/nonspeech classification, as well as recognition performance against several baseline systems.
egomotion estimation using log-polar images. we address the problem of egomotion estimation of a monocular observer moving with arbitrary translation and rotation in an unknown environment, using log-polar images.the method we propose is uniquely based on the spatio-temporal image derivatives, or the normal flow. thus, we avoid computing the complete optical flow field, which is an ill-posed problem due to the aperture problem. we use a search paradigm based on geometric properties of the normal flow field, and consider a family of search subspaces to estimate the egomotion parameters. these algorithms are particularly well-suited for the log-polar image geometry, as we use a selection of special normal flow vectors with simple representation in logpolar coordinates. this approach highlights the close coupling between algorithmic aspects and the sensor geometry (retina physiology), often found in nature.finally, we present and discuss a set of experiments, for various kinds of camera motions, which show encouraging results.
visual routines for autonomous driving. the paper describes visual routines based on models of color and shape, as well as crucial issues involving the sche duling of such routines. the visual routines are developed in a unique platform. the view from a car driving in a simulated world is fed into a datacube pipeline video processor. the use of this simulation provides a flexible environment from which to set crucial image processing parameters of the individual routines. in addition to the simulations are also tested in similar images generated by driving in the real world, to assure the generalizability of the simulation.
learning and evaluating visual features for pose estimation. we present a method for learning a set of visual landmarks which are useful for pose estimation. the landmark learning mechanism is designed to be applicable to a wide range of environments, and generalized for different approaches to computing a pose estimate. initially, each landmark is detected as a local extreme of a measure of distinctiveness and represented by a principal components encoding which is exploited for matching. attributes of the observed landmarks can be parameterized using a generic parameterization method and then evaluated in terms of their utility for pose estimation. we present experimental evidence that demonstrates the utility of the method.
dense shape reconstruction of a moving object under arbitrary, unknown lighting. we present a method for shape reconstruction from severalimages of a moving object. the reconstruction is dense(up to image resolution). the method assumes that themotion is known, e.g., by tracking a small number of featurepoints on the object. the object is assumed lambertian(completely matte), light sources should not be veryclose to the object but otherwise arbitrary, and no knowledgeof lighting conditions is required. an object changesits appearance significantly when it changes its orientationrelative to light sources, causing violation of the commonbrightness constancy assumption. while a lot of effort isdevoted to deal with this violation, we demonstrate howto exploit it to recover 3d structure from 2d images. wepropose a new correspondence measure that enables pointmatching across views of a moving object. the method hasbeen tested both on computer simulated examples and on areal object.
coupled lighting direction and shape estimation from single images. this paper presents a new method for the simultaneous estimation of lighting direction and shape from shading. the method estimates the shape and the lighting direction using a two step iterative process. we assume an initial (possibly incorrect) estimate of the lighting position. a stiff deformable model is then fitted to the image, assuming this lighting position. next, a least-squares estimate of the lighting position is derived from the model using the levenberg-marquart method.the two steps - model fitting and lighting-position estimation - are iterated. once the light direction has converged to a stable solution the deformable model stiffness is lowered and the model fits accurately given the lighting model. in addition, we show how the method can be used with either orthographic or perspective projection assumptions. in a variety of experiments on real and synthetic data, the method is robust to errors both to the initial light position and shape estimates.
a two-stage robust statistical method for temporal registration from features of various type. a model registration system capable of tracking an object, the model of which is known, in an image sequence is presented. it integrates tracking, pose determination and updating of the visible features. the which handles various features (points, lines and free-form curves) in a very robust way and is able to give a correct estimate of the pose even when tracking errorsoccur. the reliability of the system is shown on an augmented reality project.
bilinear voting. a geometric-vision approach to solve bilinear problems in general, and the color constancy and illuminant estimation problem in particular, is presented in this paper. we show a general framework, based on ideas from the generalized (probabilistic) hough transform, to estimate the unknown variables in the bilinear form. in the case of illuminant and reflectance estimation in natural images, each image pixel "votes" for possible illuminants (or reflectance), and the estimation is based on cumulative votes. in the general case, the voting is for the parameters of the bilinear model. the framework is natural for the introduction of physical constraints. for the case of illuminant estimation, we briefly show the relation of this work with previous algorithms for color constancy, and present examples.
steerable wedge filters. steerable filters, as developed by freeman and adelson (1991), are a class of rotation-invariant linear operators that may be used to analyze local orientation patterns in imagery. the most common examples of such operators are directional derivatives of gaussians and their 2d hilbert transforms. the inherent symmetry of these filters produces an orientation response that is periodic with period /spl pi/, even when the underlying image structure does not have such symmetry. this problem may be alleviated by reconsidering the full class of steerable filters. we develop a family of even- and odd-symmetric steerable filters that have a spatially asymmetric "wedge-like" shape and are optimally localized in their orientation response. unlike the original steerable filters, these filters are not based on directional derivatives and the hilbert transform relationship is imposed on their angular components. we demonstrate the ability of these filters to properly represent oriented structures.
regression based bandwidth selection for segmentation using parzen windows. we consider the problem of segmentation of images that can be modelled as piecewise continuous signals having unknown, non-stationary statistics. we propose a solution to this problem which first uses a regression framework to estimate the image pdf, and then mean-shift to find the modes of this pdf. the segmentation follows from mode identification wherein pixel clusters or image segments are identified with unique modes of the multi-modal pdf. each pixel is mapped to a mode using a convergent, iterative process. the effectiveness of the approach depends upon the accuracy of the (implicit) estimate of the underlying multi-modal density function and thus on the bandwidth parameters used for its estimate using parzen windows. automatic selection of bandwidth parameters is a desired feature of the algorithm. we show that the proposed regression-based model admits a realistic framework to automatically choose bandwidth parameters which minimizes a global error criterion. we validate the theory presented with results on real images.
separating transparent layers of repetitive dynamic behaviors. in this paper we present an approach for separating two transparent layers of complex non-rigid scene dynamics. the dynamics in one of the layers is assumed to be repetitive, while the other can have any arbitrary dynamics. such repetitive dynamics includes, among other, human actions in video (e.g., a walking person), or a repetitive musical tune in audio signals. we use a global-to-local space-time alignment approach to detect and align the repetitive behavior. once aligned, a median operator applied to space-time derivatives is used to recover the intrinsic repeating behavior, and separate it from the other transparent layer. we show results on synthetic and real video sequences. in addition, we show the applicability of our approach to separating mixed audio signals (from a single source).
multi-view reconstruction using photo-consistency and exact silhouette constraints: a maximum-flow formulation. this paper describes a novel approach for reconstructing a closed continuous surface of an object from multiple calibrated color images and silhouettes. any accurate reconstruction must satisfy (1) photo-consistency and (2) silhouette consistency constraints. most existing techniques treat these cues identically in optimization frameworks where silhouette constraints are traded off against photo-consistency and smoothness priors. our approach strictly enforces silhouette constraints, while optimizing photo-consistency and smoothness in a global graph-cut framework. we transform the reconstruction problem into computing max-flow/mincut in a geometric graph, where any cut corresponds to a surface satisfying exact silhouette constraints (its silhouettes should exactly coincide with those of the visual hull); a minimum cut is the most photo-consistent surface amongst them. our graph-cut formulation is based on the rim mesh, (the combinatorial arrangement of rims or contour generators from many views) which can be computed directly from the silhouettes. unlike other methods, our approach enforces silhouette constraints without introducing a bias near the visual hull boundary and also recovers the rim curves. results are presented for synthetic and real datasets.
affine reconstruction of curved surfaces from uncalibrated views of apparent contours. in this paper, we show that even if the camera is uncalibrated, and its translational motion is unknown, curved surfaces can be reconstructed from their apparent contours up to a 3d affine ambiguity. furthermore, we show that even if the reconstruction is non-metric (non-euclidean), we can still extract useful information for many computer vision applications just from the apparent contours.we first show that if the camera undergoes pure translation (unknown direction and magnitude), the epipolar geometry can be recovered from the apparent contours without using any search or optimisation process. the extracted epipolar geometry is next used for reconstructing curved surfaces from the deformations of the apparent contours viewed from uncalibrated cameras. the result is applied to distinguishing curved surfaces from fixed features in images. it is also shown that the time-to-contact to the curved surfaces can be computed from simple measurements of the apparent contours. the proposed method is implemented and tested on real images of curved surfaces.
discovering objects and their localization in images. we seek to discover the object categories depicted in a set of unlabelled images. we achieve this using a model developed in the statistical text literature: probabilistic latent semantic analysis (plsa). in text analysis this is used to discover topics in a corpus using the bag-of-words document representation. here we treat object categories as topics, so that an image containing instances of several categories is modeled as a mixture of topics. the model is applied to images by using a visual analogue of a word, formed by vector quantizing sift-like region descriptors. the topic discovery approach successfully translates to the visual domain: for a small set of objects, we show that both the object categories and their approximate spatial layout are found without supervision. performance of this unsupervised method is compared to the supervised approach of fergus et al. [8] on a set of unseen images containing only one object per image. we also extend the bag-of-words vocabulary to include ¿doublets¿ which encode spatially local co-occurring regions. it is demonstrated that this extended vocabulary gives a cleaner image segmentation. finally, theclassification and segmentation methods are applied to a set of images containing multiple objects per image. these results demonstrate that we can successfully build object class models from an unsupervised analysis of images.
appearance sampling for obtaining a set of basis images for variable illumination. previous studies have demonstrated that the appearance ofan object under varying illumination conditions can be representedby a low-dimensional linear subspace. a set ofbasis images spanning such a linear subspace can be obtainedby applying the principal component analysis (pca)for a large number of images taken under different lightingconditions. while the approaches based on pca havebeen used successfully for object recognition under varyingillumination conditions, little is known about how many imageswould be required in order to obtain the basis imagescorrectly. in this study, we present a novel method for analyticallyobtaining a set of basis images of an object forarbitrary illumination from input images of the object takenunder a point light source. the main contribution of ourwork is that we show that a set of lighting directions canbe determined for sampling images of an object dependingon the spectrum of the object's brdf in the angularfrequency domain such that a set of harmonic images canbe obtained analytically based on the sampling theorem onspherical harmonics. in addition, unlike the previously proposedtechniques based on spherical harmonics, our methoddoes not require the 3d shape and reflectance properties ofan object used for rendering harmonics images of the objectsynthetically.
video google: a text retrieval approach to object matching in videos. we describe an approach to object and scene retrievalwhich searches for and localizes all the occurrences of auser outlined object in a video. the object is represented bya set of viewpoint invariant region descriptors so that recognitioncan proceed successfully despite changes in viewpoint,illumination and partial occlusion. the temporalcontinuity of the video within a shot is used to track theregions in order to reject unstable regions and reduce theeffects of noise in the descriptors.the analogy with text retrieval is in the implementationwhere matches on descriptors are pre-computed (using vectorquantization), and inverted file systems and documentrankings are used. the result is that retrieval is immediate,returning a ranked list of key frames/shots in the manner ofgoogle.the method is illustrated for matching on two full lengthfeature films.
using extended light sources for modeling object appearance under varying illumination. in this study, we demonstrate the effectiveness of using extended light sources for modeling the appearance of an object for varying illumination. extended light sources have a radiance distribution that is similar to that of the gaussian function and have the potential of functioning as a low-pass filter when the appearance of an object is sampled under them. this enables us to obtain a set of basis images of an object for variable illumination from input images of the object taken under those light sources without suffering aliasing caused by insufficient sampling of its appearance. furthermore, extended light sources are useful in terms of reducing high contrast in image intensities due to specular and diffuse reflection components. this helps us observe both specular and diffuse reflection components of an object in the same image taken with a single shutter speed. we have tested our proposed approach based on extended light sources with objects of complex appearance that are generally difficult to model using image-based modeling techniques.
weighted and robust incremental method for subspace learning. visual learning is expected to be a continuous and robustprocess, which treats input images and pixels selectively.in this paper we present a method for subspace learning,which takes these considerations into account. wepresent an incremental method, which sequentially updatesthe principal subspace considering weighted influence ofindividual images as well as individual pixels within an image.this approach is further extended to enable determinationof consistencies in the input data and imputation of thevalues in inconsistent pixels using the previously acquiredknowledge, resulting in a novel incremental, weighted androbust method for subspace learning.
perceptual organization in an interactive sketch editing application. the paper shows how techniques from computational vision can be deployed to support interactive sketch editing. while conventional computer supported drawing tools give users access to visible marks or image objects at a single level of abstraction, a human user's visual system rapidly constructs complex groupings and associations among image elements according to his or her immediate purposes. we have been exploring perceptually supported sketch editors in which computer vision algorithms run continuously, behind the scenes, to afford users efficient access to emergent visual objects in a drawing. we employ a flexible image interpretation architecture based on token grouping in a multiscale blackboard data structure. this organization supports multiple perceptual interpretations of line drawing data, domain specific knowledge bases for interpreting visual structures, and natural gesture based selection of visual objects.
conditional random fields for contextual human motion recognition. we present algorithms for recognizing human motion in monocular video sequences, based on discriminative conditional random field (crf) and maximum entropy markov models (memm). existing approaches to this problem typically use generative (joint) structures like the hidden markov model (hmm). therefore they have to make simplifying, often unrealistic assumptions on the conditional independence of observations given the motion class labels and cannot accommodate overlapping features or long term contextual dependencies in the observation sequence. in contrast, conditional models like the crfs seamlessly represent contextual dependencies, support efficient, exact inference using dynamic programming, and their parameters can be trained using convex optimization. we introduce conditional graphical models as complementary tools for human motion recognition and present an extensive set of experiments that show how these typically outperform hmms in classifying not only diverse human activities like walking, jumping, running, picking or dancing, but also for discriminating among subtle motion styles like normal walk and wander walk.
asset-2: real-time motion segmentation and shape tracking. the paper describes how image sequences taken by a moving video camera may be processed to detect and track moving objects against a moving background in real-time. the motion segmentation and shape tracking system as known as asset-2-a scene segmenter establishing tracking, version 2. motion is found by tracking image features, and segmentation is based on first-order (i.e., six parameter) flow fields. shape tracking is performed using two dimensional radial map representation. the system runs in real-time, and is accurate and reliable. it requires no camera calibration and no knowledge of the camera's motion.
fast pose estimation with parameter-sensitive hashing. example-based methods are effective for parameter estimationproblems when the underlying system is simple orthe dimensionality of the input is low. for complex andhigh-dimensional problems such as pose estimation, thenumber of required examples and the computational complexityrapidly become prohibitively high. we introduce anew algorithm that learns a set of hashing functions that efficientlyindex examples in a way relevant to a particularestimation task. our algorithm extends locality-sensitivehashing, a recently developed method to find approximateneighbors in time sublinear in the number of examples. thismethod depends critically on the choice of hash functions;we show how to find the set of hash functions that are optimallyrelevant to a particular estimation problem. experimentsdemonstrate that the resulting algorithm, which wecall parameter-sensitive hashing, can rapidly and accuratelyestimate the articulated pose of human figures from alarge database of example images.
computing map trajectories by representing, propagating and combining pdfs over groups. this paper addresses the problem of computing the trajectoryof a camera from sparse positional measurementsthat have been obtained from visual localisation, and densedifferential measurements from odometry or inertial sensors.a fast method is presented for fusing these two sourcesof information to obtain the maximum a posteriori estimateof the trajectory. a formalism is introduced for representingprobability density functions over euclidean transformations,and it is shown how these density functions can bepropagated along the data sequence and how multiple estimatesof a transformation can be combined. a three-passalgorithm is described which makes use of these results toyield the trajectory of the camera.simulation results are presented which are validatedagainst a physical analogue of the vision problem, and resultsare then shown from sequences of approximately 1,800frames captured from a video camera mounted on a go-kart.several of these frames are processed using computer visionto obtain estimates of the position of the go-kart. the algorithmfuses these estimates with odometry from the entiresequence in 150 ms to obtain the trajectory of the kart.
image statistics and anisotropic diffusion. many sensing techniques and image processing applicationsare characterized by noisy, or corrupted, image data.anisotropic diffusion is a popular, and theoretically wellunderstood, technique for denoising such images. diffusionapproaches however require the selection of an "edgestopping" function, the definition of which is typically adhoc. we exploit and extend recent work on the statisticsof natural images to define principled edge stopping functionsfor different types of imagery. we consider a varietyof anisotropic diffusion schemes and note that they computespatial derivatives at fixed scales from which we estimatethe appropriate algorithm-specific image statistics. goingbeyond traditional work on image statistics, we also modelthe statistics of the eigenvalues of the local structure tensor.novel edge-stopping functions are derived from these imagestatistics giving a principled way of formulating anisotropicdiffusion problems in which all edge-stopping parametersare learned from training data.
recovering facial shape and albedo using a statistical model of surface normal direction. this paper describes how facial shape can be modelled using a statistical model that captures variations in surface normal direction. to construct this model we make use of the azimuthal equidistant projection to map surface normals from the unit sphere to points on a local tangent plane. the variations in surface normal direction are captured using the covariance matrix for the projected point positions. this allows us to model variations in face shape using a standard point distribution model. we train the model on fields of surface normals extracted from range data and show how to fit the model to intensity data using constraints on the surface normal direction provided by lambert¿s law. we demonstrate that this process yields accurate facial shape recovery and allows an estimate of the albedo map to be made from single, real world face images.
the optimal axial interval in estimating depth from defocus. we analyze the effect of perturbations on the estimation of depth from defocus (dfd) implemented by changing the focus setting (e.g., axially moving the sensor). the analysis yields the optimal change of focus setting, and the spatial frequencies for which estimation is most robust. for stable estimation at all spatial frequencies, the change in focus setting should be less than twice the depth of field. for the most robust estimation in the highest spatial frequencies the axial interval should be equal to the depth of field.
resolving hand over face occlusion. the ability to segment or track the hand is an important problem in computer vision. while various solutions have been proposed, many methods do not work against complex or cluttered backgrounds. solving these cases is essential to solving many problems in the domain of computer vision such as, human-computer interaction (hci), surveillance, and virtual reality (i.e., augmented desks). this paper presents a method to segment the hand over complex backgrounds, such as the face. the similar colors and texture of the hand and face make the problem particularly challenging. the method is not restricted to only segmenting hands across faces and uses no knowledge of hands. our method is based on the underlying concept of an image force field. in this representation change is measured through how particles move through the field. each individual image location consists of a vector value which is a nonlinear combination of the remaining pixels in the image. we introduce and develop a novel physics-based feature that is able to measure regional structure in the image thus avoiding the problem of local pixel-based analysis, which breaks down under our conditions. the regional image structure changes in the occluded region during occlusion, while elsewhere the regional structure remains relatively constant. we model the regional image structure at all image locations over time using a mixture of gaussians (mog) to detect the occluded region in the image. we have tested the method on a number of sequences demonstrating the versatility of the proposed approach.
separation of transparent layers using focus. consider situations where the depth at each point in the scene is multi-valued, due to the presence of a virtual image semi-reflected by a transparent surface. the semi-reflected image is linearly superimposed on the image of the object that is behind the transparent surface. a novel approach is proposed for the recovery of the superimposed layers. by searching for the images in which either of the objects (layers) is focused, the transparent areas are detected and an estimate of the depth map of each layer is obtained. as a result of the focusing, an initial separation of the layers is achieved. the separation is enhanced via mutual blurring of the perturbing components in the images, based on the depths estimate and the parameters of the imaging system.
temporalboost for event recognition. this paper contributes a new boosting paradigm to achieve detection of events in video. previous boosting paradigms in vision focus on single frame detection and do not scale to video events. thus new concepts need to be introduced to address questions such as determining if an event has occurred, localizing the event, handling same action performed at different speeds, incorporating previous classifier responses into current decision, using temporal consistency of data to aid detection and recognition. the proposed method has the capability to improve weak classifiers by allowing them to use previous history in evaluating the current frame. a learning mechanism built into the boosting paradigm is also given which allows event level decisions to be made. this is contrasted with previous work in boosting which uses limited higher level temporal reasoning and essentially makes object detection decisions at the frame level. our approach makes extensive use of temporal continuity of video at the classifier and detector levels. we also introduce a relevant set of activity features. features are evaluated at multiple zoom levels to improve detection. we show results for a system that is able to recognize 11 actions.
a theory of multiplexed illumination. imaging of objects under variable lighting directions is animportant and frequent practice in computer vision andimage-based rendering. we introduce an approach that significantlyimproves the quality of such images. traditionalmethods for acquiring images under variable illuminationdirections use only a single light source per acquired image.in contrast, our approach is based on a multiplexing principle,in which multiple light sources illuminate the objectsimultaneously from different directions. thus, the objectirradiance is much higher. the acquired images are thencomputationally demultiplexed. the number of image acquisitionsis the same as in the single-source method. theapproach is useful for imaging dim object areas. we givethe optimal code by which the illumination should be multiplexedto obtain the highest quality output. for n imagescorresponding to n light sources, the noise is reduced by\sqrt n/2 relative to the signal. this noise reduction translatesto a faster acquisition time or an increase in density of illuminationdirection samples. it also enables one to use lightingwith high directional resolution using practical setups,as we demonstrate in our experiments.
dynamic rigid motion estimation from weak perspective. "weak perspective" represents a simplified projection model that approximates the imaging process when the scene is viewed under a small viewing angle and its depth relief is small relative to its distance from the viewer. we study how to generate dynamic models for estimating rigid 3d motion from weak perspective. a crucial feature in dynamic visual motion estimation is to decouple structure from motion in the estimation model. the reasons are both geometric-to achieve global observability of the model-and practical, for a structure independent motion estimator allows us to deal with occlusions and appearance of new features in a principled way. it is also possible to push the decoupling even further, and isolate the motion parameters that are affected by the so called "bas relief ambiguity" from the ones that are not. we present a novel method for reducing the order of the estimator by decoupling portions of the state space from the time evolution of the measurement constraint. we use this method to construct an estimator of full rigid motion (modulo a scaling factor) on a six dimensional state space, an approximate estimator for a four dimensional subset of the motion space, and a reduced filter with only two states. the latter two are immune to the bas relief ambiguity. we compare strengths and weaknesses of each of the schemes on real and synthetic image sequences.
polarization-based decorrelation of transparent layers: the inclination angle of an invisible surface. when a transparent surface is present between an observer and an object, an image reflected by the surface may be superimposed on the image of the observed object. we present a new approach to recover the scenes (layers) and to classify which is the reflected/transmitted one, based on imaging through a polarizing filter at two orientations. estimates of the separate layers are obtained by weighted pixel-wise differences of these images, inverting the image formation process. however, the weights depend on the angle of incidence, hence on the inclination of the transparent (invisible) surface. this angle is estimated by seeking the angle-value which (through the weights) leads to decorrelation of the estimated layers. experimental results, obtained using real photos of actual objects, demonstrate the success of angle estimation and consequent layer separation and labeling. the method is shown to be superior to earlier methods where only raw optical data was used.
tales of shape and radiance in multi-view stereo. to what extent can three-dimensional shape and radiancebe inferred from a collection of images? can the two be estimatedseparately while retaining optimality? how shouldthe optimality criterion be computed? when is it necessaryto employ an explicit model of the reflectance properties ofa scene? in this paper we introduce a separation principlefor shape and radiance estimation that applies to lambertianscenes and holds for any choice of norm. when thescene is not lambertian, however, shape cannot be decoupledfrom radiance, and therefore matching image-to-imageis not possible directly. we employ a rank constraint onthe radiance tensor, which is commonly used in computergraphics, and construct a novel cost functional whose minimizationleads to an estimate of both shape and radiancefor non-lambertian objects, which we validate experimentally.
transinformation for active object recognition. this article develops an analogy between object recognition and the transmission of information through a channel based on the statistical representation of the appearances of 3d objects. this analogy provides a means to quantitatively evaluate the contribution of individual receptive field vectors, and to predict the performance of the object recognition process. transinformation also provides a quantitative measure of the discrimination provided by each viewpoint, thus permitting the determination of the most discriminant viewpoints. as an application, the article develops an active object recognition algorithm which is able to resolve ambiguities inherent in a single-view recognition algorithm.
the beltrami flow over implicit manifolds. in many medical computer vision tasks the relevant data isattached to a specific tissue such as the colon or the cortex.this situation calls for regularization techniques whichare defined over surfaces.we introduce in this paper thebeltrami flow over implicit manifolds.this new regularizationtechnique overcomes the over-smoothing of the l2flow and the staircasing effects of the l1 flow, that wererecently suggested via the harmonic map methods.the keyof our approach is first to clarify the link between the intrinsic polyakov action and the implicit harmonic energyfunctional and then use the geometrical understanding ofthe beltrami flow to generalize it to images on implicitlydefined non flat surfaces.it is shown that once again thebeltrami flow interpolates between the l2 and l1 flows onnon-flat surfaces.the implementation scheme of this flowis presented and various experimental results obtained on aset of various real images illustrate the performances of theapproach as well as the differences with the harmonic mapflows.this extension of the beltrami flow to the case of nonflat surfaces opens new perspectives in the regularization ofnoisy data defined on manifolds.
comparing and evaluating interest points. many computer vision tasks rely on feature extraction. inter est points are such features. this paper shows that interest points are geometrically stable under different transformations and have high information content (distinctiveness). these two properties make interest points very successful in the context of image matching. to measure these two properties quantitatively, we introduce two evaluation criteria: repeatability rate and information content.the quality of the interest points depends on the detector used. in this paper several detectors are compared according to the criteria specified above. we determine which detector gives the best results and show that it satisfies the criteria well.
monocular perception of biological motion - detection and labeling. computer perception of biological motion is key to developing convenient and powerful human-computer inter-faces. successful body tracking algorithms have been developed; however, initialization is done by hand.we propose a method for detecting a moving human body and for labeling its parts automatically. it is based on maximizing the joint probability density function (pdf) of the position and velocity of the body parts. the pdf is estimated from training data. dynamic programming is used for calculating efficiently the best global labeling on an approximation of the pdf. the computational cost is on the order of n 4 where n is the number of features detected.we explore the performance of our method with experiments carried on a variety of periodic and non-periodic body motions viewed monocularly for a total of approximately 30,000 frames. point-markers were strapped to the joints of the subject for facilitating image analysis. we find an average of 2.3% labeling error; the experiments also suggest a high degree of viewpoint-invariance.
a model-based vehicle segmentation method for tracking. our goal is to detect and track moving vehicles on a road observed from cameras placed on poles or buildings. inter-vehicle occlusion is significant under these conditions and traditional blob tracking methods will be unable to separate the vehicles in the merged blobs. we use vehicle shape models, in addition to camera calibration and ground plane knowledge, to detect, track and classify moving vehicles in presence of occlusion. we use a 2-stage approach. in the first stage, hypothesis for vehicle types, positions and orientations are formed by a coarse search, which is then refined by a data driven markov chain monte carlo (ddmcmc) process. we show results and evaluations on some real urban traffic video sequence using three types of vehicle models.
computing ritz approximations of primary images. ritz vectors approximate eigenvectors that are a common choice for primary images in content based indexing. they can be computed efficiently even when the images are accessed through slow communication such as the internet. we develop an algorithm that computes ritz vectors in one pass through the images. when iterated, the algorithm can recover the exact eigenvectors. in applications to image indexing and learning it may be necessary to compute primary images for indexing many sub-categories of the image set the proposed algorithm can compute these additional primary images "offline", without the image data much more costly even when access to the images is inexpensive.
manifold clustering. manifold learning has become a vital tool in data driven methods for interpretation of video, motion capture, and handwritten character data when they lie on a low dimensional, non-linear manifold. this work extends manifold learning to classify and parameterize unlabeled data which lie on multiple, intersecting manifolds. this approach significantly increases the domain to which manifold learning methods can be applied, allowing parameterization of example manifolds such as figure eights and intersecting paths which are quite common in natural data sets. this approach introduces several technical contributions which may be of broader interest, including node-weighted multi-dimensional scaling and a fast algorithm for weighted low-rank approximation for rank-one weight matrices. we show examples for intersecting manifolds of mixed topology and dimension and demonstrations on human motion capture data.
indexing images by trees of visual content. an unsupervised algorithm for arranging an image database as a binary tree is described. tree nodes are associated with image subsets, maintaining the property that the similarity among the images associated with the children of a node is higher than the similarity among the images associated with the parent node. experiments with datasets of hundreds and thousands of images show that shallow trees can produce clustering into "meaningful" classes. visual-content search trees can be used to automate image retrieval by content, orhelp a human to interactively search for images.
limitations of markov random fields as models of textured images of real surfaces. we investigate to what extent textures can be distinguished using conditional markov fields and small samples. we establish that the least square (ls) estimator is the only reasonable choice for this task and we prove its asymptotic consistency and normality for a general class of random fields that include gaussian markov fields as a special case. the performance of this estimator when applied to textured images of real surfaces is poor if small boxes are used (20/spl times/20 or less). we investigate the nature of this problem by comparing the behavior predicted by the rigorous theory to the one that has been experimentally observed. our analysis reveal that 20/spl times/20 samples contain enough information to distinguish between the textures in our experiments and that the poor performance mentioned above should be attributed to the fact that conditional markov fields do not provide accurate models for textured images of many real surfaces. a more general model that exploits more efficiently the information contained in small samples is also suggested.
utilizing scatter for pixel subspace selection. measures of scatter are used in statistical pattern recognition to identify and select important features, computed as linear combinations of the given features. examples include principal components and linear discriminants. the classic computational procedures require eigenvector decomposition of large matrices, and in the case of images they are only practical for identifying a low dimensional feature subspace.we investigate the case in which the selected features are required to be a subset of the given features. it is shown that the same scatter measures used in the general case can also be used in this discrete selection case, but the computational procedure no longer involves matrix eigenvector decomposition.instead, the selection of pixels that optimize scatter measures can be accomplished by a very simple and efficient discrete optimization technique that runs in linear time regardless of the subspace size. applications to clustering and content based indexing are discussed.
active blobs. a new region-based approach to nonrigid motion tracking is described. shape is defined in terms of a deformable triangular mesh that captures object shape plus a color texture map that captures object appearance. photometric variations are also modeled. nonrigid shape registration and motion tracking are achieved by posing the problem as an energy-based, robust minimization procedure. the approach provides robustness to occlusions, wrinkles, shadows, and specular highlights. the formulation is tailored to take advantage of texture mapping hardware available in many workstations, pc's, and game consoles. this enablesnonrigid tracking at speeds approaching video rate.
convex grouping combining boundary and region information. convexity is an important geometric property of many natural and man-made structures. prior research has shown that it is imperative to many perceptual-organization and image-understanding tasks. this paper presents a new grouping method for detecting convex structures from noisy images in a globally optimal fashion. particularly, this method combines both region and boundary information: the detected structural boundary is closed and well aligned with detected edges while the enclosed region has good intensity homogeneity. we introduce a ratio-form cost function for measuring the structural desirability, which avoids a possible bias to detect small structures. a new fragment-pruning algorithm is developed to achieve the structural convexity. the proposed method can also be extended to detect open boundaries, which correspond to the structures that are partially cropped by the image perimeter, and incorporate a human-computer interaction for detecting a convex boundary around a specified point. we test the proposed method on a set of real images and compare it with the jacobs¿ convex-grouping method.
complete scene structure from four point correspondences. a technique is presented for computing 3d scene structure from point and line features in monocular image sequences. unlike previous methods, the technique guarantees the completeness of the recovered scene, ensuring that every scene feature that is detected in each image is reconstructed. the approach relies on the presence of four or more reference features whose correspondences are known in all the images. under an orthographic or affine camera model, the parallax of the reference features provides constraints that simplify the recovery of the rest of the visible scene. an efficient recursive algorithm is described that uses a unified framework for point and line features. the algorithm integrates the tasks of feature correspondence and structure recovery, ensuring that all reconstructible features are tracked. in addition, the algorithm is immune to outliers and feature drift, two weaknesses of existing structure from motion techniques. experimental results are presented for real images.
model-based multiple view reconstruction of people. this paper presents a framework to reconstruct a scenecaptured in multiple camera views based on a prior modelof the scene geometry. the framework is applied to thecapture of animated models of people. a multiple camerastudio is used to simultaneously capture a moving personfrom multiple viewpoints. a humanoid computer graphicsmodel is animated to match the pose at each time frame.constrained optimisation is then used to recover the multipleview correspondence from silhouette, stereo and featurecues, updating the geometry and appearance of the model.the key contribution of this paper is a model-based computervision framework for the reconstruction of shape andappearance from multiple views. this is compared to currentmodel-free approaches for multiple view scene capture.the technique demonstrates improved scene reconstructionin the presence of visual ambiguities and providesthe means to capture a dynamic scene with a consistentmodel that is instrumented with an animation structure toedit the scene dynamics or to synthesise new content.
plenoptic image editing. this paper presents a new class of interactive image editing operations designed to maintain consistency between multiple images of a physical 3d scene. the distinguishing feature of these operations is that edits to any one image propagate automatically to all other images asif the (unknown) 3d scene had itself been modified. the modified scene can then be viewed interactively from any other camera viewpoint and under different scene illuminations. the approach is useful first as a power-assist that enables a user to quickly modify many images by editing just a few, and second as a means for constructing and editing image-based scene representations by manipulating a set of photographs. the approach works by extending operations like image painting, scissoring, and morphing so that they alter a scene's generalized plenoptic function in a physically-consistent way, thereby affecting scene appearance from all viewpoints simultaneously. a key element in realizing these operations is a new volumetric decomposition technique for reconstructing an scene's plenoptic function from an incomplete set of camera viewpoints.
spherical matching for temporal correspondence of non-rigid surfaces. this paper introduces spherical matching to estimate dense temporal correspondence of non-rigid surfaces with genus-zero topology. the spherical domain gives a consistent 2d parameterisation of non-rigid surfaces for matching. non-rigid 3d surface correspondence is formulated as the recovery of a bijective mapping between two surfaces in the 2d domain. formulating matching as a 2d bijection guarantees a continuous one-to-one surface correspondence without overfolding. this overcomes limitations of direct estimation of non-rigid surface correspondence in the 3d domain. a multiple resolution coarse-to-fine algorithm is introduced to robustly estimate the dense correspondence which minimises the disparity in shape and appearance between two surfaces. spherical matching is applied to derive the temporal correspondence between non-rigid surfaces reconstructed at successive frames from multiple view video sequences of people. dense surface correspondence is recovered across complete motion sequences for both textured and uniform regions, without the requirement for a prior model of human shape or kinematic structure for tracking.
a theory of inverse light transport. in this paper we consider the problem of computing and removing interreflections in photographs of real scenes. towards this end, we introduce the problem of inverse light transport ¿ given a photograph of an unknown scene, decompose it into a sum of n-bounce images, where each image records the contribution of light that bounces exactly n times before reaching the camera. we prove the existence of a set of interreflection cancelation operators that enable computing each n-bounce image by multiplying the photograph by a matrix. this matrix is derived from a set of "impulse images" obtained by probing the scene with a narrow beam of light. the operators work under unknown and arbitrary illumination, and exist for scenes that have arbitrary spatially-varying brdfs. we derive a closed-form expression for these operators in the lambertian case and present experiments with textured and untextured lambertian scenes that confirm our theory¿s predictions.
minimally-supervised classification using multiple observation sets. this paper discusses building complex classifiers from a single labeled example and vast number of unlabeled observation sets, each derived from observation of a single processor object. when data can be measured by observation, it is often plentiful and it is often possible to make more than one observation of the state of a process or object. this paper discusses how to exploit the variability across such sets of observations of the same object to estimate class labels for unlabeled examples given a minimal number of labeled examples. in contrast to similar semi-supervised classification procedures that define the likelihood that two observations share a label as a function of the embedded distance between the two observations, this method uses the naive bayes estimate of how often the two observations did result from the same observed process. exploiting this additional source of information in an iterative estimation procedure can generalize complex classification models from single labeled observations. some examples involving classification of tracked objects in a low-dimensional feature space given thousands of unlabeled observation sets are used to illustrate the effectiveness of this method.
optimal subpixel matching of contour chains and segments. this paper introduces a new general purpose algorithm that allows the optimal geometric match between contours to be determined, that is the transformation yielding a minimal deformation is obtained. the algorithm relies only on the geometric properties of the contours and does not call for any other constraint, so that it is particularly suitable when no parameterization of title deformation is available or desirable. contour deformation is explicitly incorporated in the computation, allowing for a thorough use of all geometric information available. moreover, no discretization is involved in the computation, resulting in two main advantages: first, the algorithm is robust to differences in the segmentation of contours and allows the matching of polygonal approximations of contours with very little loss of precision, second, subpixel precision matching can be achieved.
spectral partitioning for structure from motion. we propose a spectral partitioning approach for large-scaleoptimization problems, specifically structure from motion.in structure from motion, partitioning methods reduce theproblem into smaller and better conditioned subproblemswhich can be efficiently optimized.our partitioning methoduses only the hessian of the reprojection error and its eigenvector.we show that partitioned systems that preserve theeigenvectors corresponding to small eigenvalues result inlower residual error when optimized.we create partitionsby clustering the entries of the eigenvectors of the hessiancorresponding to small eigenvalues.this is a more generaltechnique than relying on domain knowledge and heuristicssuch as bottom-up structure from motion approaches.simultaneously,it takes advantage of more information thangeneric matrix partitioning algorithms.
efficiently registering video into panoramic mosaics. we present an automatic and efficient method to register and stitch thousands of video frames into a large panoramic mosaic. our method preserves the robustness and accuracy of image stitchers that match all pairs of images while utilizing the ordering information provided by video. we reduce the cost of searching for matches between video frames by adaptively identifying key frames based on the amount of image-to-image overlap. key frames are matched to all other key frames, but intermediate video frames are only matched to temporally neighboring key frames and intermediate frames. image orientations can be estimated from this sparse set of matches in time quadratic to cubic in the number of key frames but only linear in the number of intermediate frames. additionally, the matches between pairs of images are compressed by replacing measurements within small windows in the image with a single representative measurement. we show that this approach substantially reduces the time required to estimate the image orientations with minimal loss of accuracy. finally, we demonstrate both the efficiency and quality of our results by registering several long video sequences.
subpixel-precise extraction of watersheds. an approach to extract watersheds and watercourses, as well as their corresponding valleys and hills, from images with subpixel precision is proposed. the critical points of the terrain are essential as the starting points for the construction of these separatrices. they are extracted efficiently with subpixel precision using an approach based on derivatives of gaussian filters. the separatrices are extracted by integrating their defining differential equation.finally, the hills and valleys are constructed by an efficient graph search algorithm. examples show the quality of the results that can be achieved with the proposed approach.
accurate internal camera calibration using rotation, with analysis of sources of error. describes a simple and accurate method for internal camera calibration based on tracking image features through a sequence of images while the camera undergoes pure rotation. a special calibration object is not required and the method can therefore be used both for laboratory calibration and for self calibration in autonomous robots. experimental results with real images show that focal length and aspect ratio can be found to within 0.15 percent, and lens distortion error can be reduced to a fraction of a pixel. the location of the principal point and the location of the center of radial distortion can each be found to within a few pixels. we perform a simple analysis to show to what extent the various technical details affect the accuracy of the results. we show that having pure rotation is important if the features are derived from objects close to the camera. in the basic method accurate angle measurement is important. the need to accurately measure the angles can be eliminated by rotating the camera through a complete circle while taking an overlapping sequence of images and using the constraint that the sum of the angles must equal 960 degrees.
filtering using a tree-based estimator. within this paper a new framework for bayesian tracking ispresented, which approximates the posterior distribution atmultiple resolutions. we propose a tree-based representationof the distribution, where the leaves define a partition ofthe state space with piecewise constant density. the advantageof this representation is that regions with low probabilitymass can be rapidly discarded in a hierarchical search,and the distribution can be approximated to arbitrary precision.we demonstrate the effectiveness of the technique byusing it for tracking 3d articulated and non-rigid motionin front of cluttered background. more specifically, we areinterested in estimating the joint angles, position and orientationof a 3d hand model in order to drive an avatar.
robot aerobics: four easy steps to a more flexible calibration. presents a method for calibrating intrinsic and extrinsic camera parameters. this algorithm can easily be modified by other users to suit their particular calibration needs, without requiring a high-precision calibration target or complicated linear algebra. the algorithm uses controlled motions and a single light source to simulate calibration targets in convenient 3d locations. these convenient calibration targets enable us to simplify the calibration algorithm and gather dense data for lens distortion. dense data makes the distortion correction more accurate than traditional low-order polynomial fits, and allows us to calibrate wide-angle lenses (
expected performance of robust estimators near discontinuities. in extracting a polynomial surface patch near an intensity or range discontinuity, a robust estimator must tolerate not only the truly random bad data ("random outliers"), but also the coherently structured points ("pseudo outliers") that belong to a different surface. to characterize the performance of least median of squares, m estimators, hough transforms, ransac, and minpran on data containing both random and pseudo outliers, we develop two analytical measures, "pseudo outlier bias" and "pseudo outlier breakdown". using these measures, we find that each robust estimator has surprisingly poor performance, even under the best possible circumstances, implying that present estimators should be used with care and new estimators should be developed.
how hard is 3-view triangulation really? we present a solution for optimal triangulation in three views. the solution is guaranteed to find the optimal solution because it computes all the stationary points of the (maximum likelihood) objective function. internally, the solution is found by computing roots of multi-variate polynomial equations, directly solving the conditions for stationarity. the solver makes use of standard methods from computational commutative algebra to convert the root-finding problem into a 47 × 47 non-symmetric eigen-problem. although there are in general 47 roots, counting both real and complex ones, the number of real roots is usually much smaller. we also show experimentally that the number of stationary points that are local minima and lie in front of each camera is small but does depend on the scene geometry.
dense matching of multiple wide-baseline views. this paper describes a pde-based method for densedepth extraction from multiple wide-baseline images. emphasislies on the usage of only a small amount of images.the integration of these multiple wide-baseline views isguided by the relative confidence that the system has in thematching to different views. this weighting is fine-grainedin that it is determined for every pixel at every iteration.reliable information spreads fast at the expense of less reliabledata, both in terms of spatial communications withina view and in terms of information exchange between theviews. changes in intensity between images can be handledin a similar fine grained fashion.
segmentation and range sensing using a moving-aperture lens. the use of a novel motorized lens to perform segmentation of image sequences is presented in this paper. the lens has the effect of introducing small, repeating movements of the camera center so that objects appear to translate in the image by an amount that depends on the distance from the plane of focus. for a stationary scene, optical flow magnitudes are therefore directly related to three-dimensional object distance from the observer. we describe a segmentation procedure that exploits these controlled observer movements and present experimental results that demonstrate the successful extraction of objects at different depths. potential applications of our approach include image compositing, teleconferencing, and range estimation.
learning hierarchical models of scenes, objects, and parts. we describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. the model is based on a set of parts which describe the expected appearance and position, in an object centered coordinate frame, of features detected by a low-level interest operator. each object category then has its own distribution over these parts, which are shared between objects. we learn the parameters of this model via a gibbs sampler which uses the graphical model¿s structure to analytically average over many parameters. applied to a database of images of isolated objects, the sharing of parts among objects improves detection accuracy when few training examples are available. we also extend this hierarchical framework to scenes containing multiple objects.
object localization by bayesian correlation. maximization of cross-correlation is a commonly used principle for intensity-based object localization that gives a single estimate of location. however, to facilitate sequential inference (eg over time or scale) and to allow the representation of ambiguity, it is desirable to represent an entire probability distribution for object location. although the cross-correlation itself (or some function of it) has sometimes been treated as a probability distribution, this is not generally justifiable.bayesian correlation achieves a consistent probabilistic treatment by combining several developments. the first is the interpretation of correlation matching functions in probabilistic terms, as observation likelihoods. second, probability distributions of filter-bank responses are learned from training examples. inescapably, response-learning also demands statistical modeling of background intensities, and there are links here with image coding and independent component analysis. lastly, multi-scale processing is achieved, in a bayesian context, by means of a new algorithm, layered sampling, for which asymptotic properties are derived.
automatic model construction, pose estimation, and object recognition from photographs using triangular splines. this paper proposes a method for automatically constructing triangular g1 spline models of complex three-dimensional objects from a few registered photographs. these models are used for pose estimation from monocular silhouette data and they form the basis for a simple recognition strategy. the proposed approach is demonstrated by several experiments.
recognition of 3d free-form objects using segment-based stereo vision. we propose a new method to recognize 3d free-form objects from their apparent contours. it is the extension of our established method to recognize objects with fixed edges. object models are compared with 3d boundaries which are extracted by segment-based stereo vision. based on the local shapes of the boundaries, candidate transformations are generated. the candidates are verified and adjusted based on the whole shapes of the boundaries. themodels are built from all-around range data of the objects. experimental results show the effectiveness of the method.
video input driven animation (vida). there are many challenges associated with the integration of synthetic and real imagery. one particularly difficult problem is the automatic extraction of salient parameters of natural phenomena in real video footage for subsequent application to synthetic objects. can we ensure that the hair and clothing of a synthetic actor placed in a meadow of swaying grass will move consistently with the wind that moved that grass? the video footage can be seen as a controller for the motion of synthetic features, a concept we call video input driven animation (vida). we propose a schema that analyzes an input video sequence, extracts parameters from the motion of objects in the video, and uses this information to drive the motion of synthetic objects. to validate the principles of vida, we approximate the inverse problem to harmonic oscillation, which we use to extract parameters of wind and of regular water waves. we observe the effect of wind on a tree in a video, estimate wind speed parameters from its motion, and then use this to make synthetic objects move. we also extract water elevation parameters from the observed motion of boats and apply the resulting water waves to synthetic boats.
geometric and photometric restoration of distorted documents. we present a system to restore the 2d content printed on distorted documents. our system works by acquiring a 3d scan of the document¿s surface together with a high-resolution image. using the 3d surface information and the 2d image, we can ameliorate unwanted surface distortion and effects from non-uniform illumination. our system can process arbitrary geometric distortions, not requiring any pre-assumed parametric models for the document¿s geometry. the illumination correction uses the 3d shape to distinguish content edges from illumination edges to recover the 2d content¿s reflectance image while making no assumptions about light sources and their positions. results are shown for real objects, demonstrating a complete framework capable of restoring geometric and photometric artifacts on distorted documents.
bi-directional tracking using trajectory segment analysis. in this paper, we present a novel approach to keyframe-based tracking, called bi-directional tracking. given two object templates in the beginning and ending keyframes, the bi-directional tracker outputs the map (maximum a posterior) solution of the whole state sequence of the target object in the bayesian framework. first, a number of 3d trajectory segments of the object are extracted from the input video, using a novel trajectory segment analysis. second, these disconnected trajectory segments due to occlusion are linked by a number of inferred occlusion segments. last, the map solution is obtained by trajectory optimization in a coarse-to-fine manner. experimental results show the robustness of our approach with respect to sudden motion, ambiguity, and short and long periods of occlusion.
more-than-topology-preserving flows for active contours and polygons. active contour and active polygon models have been used widely for image segmentation. in some applications, the topology of the object(s) to be detected from an image is known a priori, despite an unknown complex geometry, and it is important that the active contour or polygon maintain the desired topology. in this work, we construct a novel geometric flow that can be added to image based evolutions of active contours and polygons so that the topology of the initial contour or polygon is preserved. indeed, the proposed geometric flow ensures more than just correct topology; it ensures that the active contour or polygon is, in some sense, kept far away from a topology change. smoothness properties similar to curvature flow are also guaranteed by the proposed geometric flow. the proposed topology preserving geometric flow is the gradient flow arising from an energy that is based on electrostatic principles. the evolution of a single point on the contour depends on all other points of the contour, which is different from traditional curve evolutions in computer vision literature.
prediction error as a quality metric for motion and stereo. this paper presents a new methodology for evaluating the quality of motion estimation and stereo correspondence algorithms. motivated by applications such as novel view generation and motion-compensated compression, we suggest that the ability to predict new views or frames is a natural metric for evaluating such algorithms.our new metric has several advantages over comparing algorithm outputs to true motions or depths. first of all, it does not require the knowledge of ground truth data, which may be difficult or laborious to obtain. second, it more closely matches the ultimate requirements of the application, which are typically tolerant of errors in uniform color regions, but very sensitive to isolated pixel errors or disocclusion errors.in the paper, we develop a number of error metrics based on this paradigm, including forward and inverse prediction errors, residual motion error, and local motion-compensated prediction error. we show results on a number of widely used motion and stereo sequences, many of which do not have associated ground truth data.
stereo matching with transparency and matting. this paper formulates and solves a new variant of the stereo correspondence problem: simultaneously recovering the disparities, true colors, and opacities of visible surface elements. this problem arises in newer applications of stereo reconstruction, such as view interpolation and the layering of real imagery with synthetic graphics for special effects and virtual studio applications. while this problem is intrinsically more difficult than traditional stereo correspondence, where only the disparities are being recovered, it provides a principled way of dealing with commonly occuring problems such as occlusions and the handling of mixed (foreground/background) pixels near depth discontinuities. it also provides a novel means for separating foreground and background objects (matting) without the use of a special blue screen. we formulate the problem as the recovery of colors and opacities in a generalized 3-d (x, y, d) disparity space, and solve the problem using a combination of initial evidence aggregation followed by iterative energy minimization.
motion estimation with quadtree splines. this paper presents a motion estimation algorithm based on a new multiresolution representation, the quadtree spline. this representation describes the motion field as a collection of smoothly connected patches of varying size, where the patch size is automatically adapted to the complexity of the underlying motion. the topology of the patches is determined by a quadtree data structure, and both split and merge techniques are developed for estimating this spatial subdivision. the quadtree spline is implemented using another novel representation, the adaptive hierarchical basis spline, and combines the advantages of adaptively-sized correlation windows with the speedups obtained with hierarchical basis preconditioners. results are presented on some standard motion sequences.
a geometric criterion for shape-based non-rigid correspondence. a geometric criterion is developed for establishing shape based non rigid correspondence between plane curves. unlike previous efforts, the criterion does not use rigid invariants of shape. instead, shapes are compared non rigidly from the vantage point of the correspondence. geometric invariants are proposed for curves whose shapes can be exactly matched by a non rigid correspondence. the invariants are based on angular deviations of convex and concave segments of the curves. examples of correspondences between curves obtained from medical images are provided.
separating reflection components of textured surfaces using a single image. the presence of highlights, which in dielectric inhomogeneousobjects are linear combination of specular and diffusereflection components, is inevitable. a number of methodshave been developed to separate these reflection components.to our knowledge, all methods that use a singleinput image require explicit color segmentation to deal withmulticolored surfaces. unfortunately, for complex texturedimages, current color segmentation algorithms are stillproblematic to segment correctly. consequently, a methodwithout explicit color segmentation becomes indispensable,and this paper presents such a method. the method is basedsolely on colors, particularly chromaticity, without requiringany geometrical parameter information. one of the basicideas is to compare the intensity logarithmic differentiationof specular-free images and input images iteratively.the specular-free image is a pseudo-code of diffuse componentsthat can be generated by shifting a pixel's intensityand chromaticity nonlinearly while retaining its hue. allprocesses in the method are done locally, involving a maximumof only two pixels. the experimental results on naturalimages show that the proposed method is accurate and robustunder known scene illumination chromaticity. unlikethe existing methods that use a single image, our methodis effective for textured objects with complex multicoloredscenes.
highlight removal by illumination-constrained inpainting. we present a single-image highlight removal method that incorporates illumination-based constraints into image inpainting. unlike occluded image regions filled by traditional inpainting, highlight pixels contain some useful information for guiding the inpainting process. constraints provided by observed pixel colors, highlight color analysis and illumination color uniformity are employed in our method to improve estimation of the underlying diffuse color. the inclusion of these illumination constraints allows for better recovery of shading and textures by inpainting. experimental results are given to demonstrate the performance of our method.
common pattern discovery using earth mover's distance and local flow maximization. in this paper, we present a novel segmentation-insensitive approach for mining common patterns from 2 images. we develop an algorithm using the earth movers distance (emd) framework, unary and adaptive neighborhood color similarity. we then propose a novel local flow maximization approach to provide the best estimation of location and scale of the common pattern. this is achieved by performing an iterative optimization in search of the most stable flows¿ centroid. common pattern discovery isdifficult owing to the huge search space and problem domain. we intend to solve this problem by reducing the search space through identifying the location and a reduced spatial space for common pattern discovery. experimental results justify the effectiveness and the potential of the approach.
integrated surface, curve and junction inference from sparse 3-d data sets. we are interested in descriptions of 3-d data sets, as obtained from stereo or a 3-d digitizer. we therefore consider as input a sparse set of points, possibly associated with orientation information. in this paper, we address the problem of inferring integrated high-level descriptionssuch as surfaces, curves, and junctions from a sparse point set. while the method described in [5], [6] provides excellent results for smooth structures, it only detects discontinuities, but does not localize them. for precise localization, we propose a non-iterative cooperative algorithm in which surfaces, curves, and junctions work together: initial estimates are computed based on [5], [6], where each point in the given sparse and possibly noisy point set is convolved with a predefined vector mask to produce dense saliency maps. these maps serve as input to our novel maximal surface and curve marching algorithms for initial surface and curve extraction. refinement of initial estimates is achieved by hybrid voting using excitatory and inhibitory fields for inferring reliable and natural extension so that surface/curve and curve/junction discontinuities are preserved. results on several synthetic as well as real data sets are presented.
direction diffusion. in a number of disciplines, directional data provides a fundamental source of information. a novel framework for isotropic and anisotropic diffusion of directions is presented in this paper. the framework can be applied both to regularize directional data and to obtain multi-scale representations of it. the basic idea is to apply and extend results from the theory of harmonic maps in liquid crystals.this theory deals with the regularization of vectorial data, while satisfying the unit norm constraint of directional data. we show the corresponding variational and partial differential equations formulations for isotropic diffusion, obtained from an l2 norm, and edge preserving diffusion, obtained from an l1 norm.in contrast with previous approaches, the framework is valid for directions in any dimensions, supports non-smooth data, and gives both isotropic and anisotropic formulations. we present a number of theoretical results, open questions, and examples for gradient vectors, optical flow, and color images.
face sketch synthesis and recognition. in this paper, we propose a novel face photo retrievalsystem using sketch drawings. by transforming a photoimage into a sketch, we reduce the difference betweenphoto and sketch significantly, thus allow effectivematching between the two. to improve the synthesisperformance, we separate shape and texture informationin a face photo, and conduct transformation on themrespectively. finally a bayesian classifier is used torecognize the probing sketch from the synthesizedpseudo-sketches. experiments on a data set containing606 people clearly demonstrate the efficacy of thealgorithm.
photometric stereo under perspective projection. photometric stereo is a fundamental approach in computer vision. at its core lies a set of image irradiance equations each taken with a different illumination. the vast majority of studies in this field have assumed orthography as the projection model. this paper re-examines the basic set of equations of photometric stereo, under an assumption of perspective projection. we show that the resulting system is linear (as is the case under the orthographic model; nevertheless, the unknowns are different in the perspective case). we then suggest a simple reconstruction algorithm based on the perspective formulae, and compare it to its orthographic counterpart on synthetic as well as real images. this algorithm obtained lower error rates than the orthographic one in all of the error measures. these findings strengthen the hypothesis that a more realistic set of assumptions, the perspective one, improves reconstruction significantly.
a new perspective [on] shape-from-shading. shape-from-shading (sfs) is a fundamental problem incomputer vision. the vast majority of research in this fieldhave assumed orthography as its projection model. thispaper re-examines the basis of sfs, the image irradianceequation, under an assumption of perspective projection.the paper also shows that the perspective image irradianceequation depends merely on the natural logarithm of thedepth function (and not on the depth function itself), and assuch it is invariant to scale changes of the depth function.we then suggest a simple reconstruction algorithm basedon the perspective formula, and compare it to existing orthographicsfs algorithms. this simple algorithm obtainedlower error rates than legacy sfs algorithms, and equatedwith and sometimes surpassed state-of-the-art algorithms.these findings lend support to the assumption that transitionto a more realistic set of assumptions improves reconstructionsignificantly.
non-orthogonal binary subspace and its applications in computer vision. this paper presents a novel approach that represents an image or a set of images using a non-orthogonal binary subspace (nbs) spanned by box-like base vectors. these base vectors possess the property that the inner product operation with them can be computed very efficiently. we investigate the optimized orthogonal matching pursuit method for finding the best nbs base vectors. it is demonstrated in this paper how the nbs based expansion can be applied to speed up several common computer vision algorithms, including normalized cross correlation (ncc), sum of squared difference (ssd) matching, appearance subspace projection and subspace-based object recognition. promising experimental results on facial and natural images are demonstrated in this paper.
comparison of graph cuts with belief propagation for stereo, using identical mrf parameters. recent stereo algorithms have achieved impressive resultsby modelling the disparity image as a markov randomfield (mrf). an important component of an mrf-basedapproach is the inference algorithm used to find the mostlikely setting of each node in the mrf. algorithms havebeen proposed which use graph cuts or belief propagationfor inference. these stereo algorithms differ in both theinference algorithm used and the formulation of the mrf.it is unknown whether to attribute the responsibility for differencesin performance to the mrf or the inference algorithm.we address this through controlled experiments bycomparing the belief propagation algorithm and the graphcuts algorithm on the same mrf's, which have been createdfor calculating stereo disparities. we find that the labellingsproduced by the two algorithms are comparable.the solutions produced by graph cuts have a lower energythan those produced with belief propagation, but this doesnot necessarily lead to increased performance relative tothe ground-truth.
local symmetries of shapes in arbitrary dimension. motivated by a need to define an object-centered reference system determined by the most salient characteristics of the shape, many methods have been proposed, all of which directly or indirectly involve an axis about which the shape is locally symmetric. recently, a function v, called "the edge strength function", has been successfully used to determine efficiently the axes of local symmetries of 2-d shapes. the level curves of v are interpreted as succesively smoother versions of the initial shape boundary. the local minima of the absolute gradient \left\| {\nabla v} \right\| along the level curves of v are shown to be a robust criterion for determining the shape skeleton. more generally, at an extremal point of \left\| {\nabla v} \right\| along a level curve, the level curve is locally symmetric with respect to the gradient vector \nabla v. that is, at such a point, the level curve is approximately a conic section whose one of the principal axes coincides with the gradient vector. thus, the locus ofthe extremal points of \left\| {\nabla v} \right\| along the level curves determines the axes of local symmetries of the shape. in this paper, we extend this method to shapes of arbitrary dimension.
modelling shapes with uncertainties: higher order polynomials, variable bandwidth kernels and non parametric density estimation. in this paper, we introduce a new technique for shape modelling in the space of implicit polynomials. registration consists of recovering an optimal one-to-one transformation of a higher order polynomial along with uncertainties measures that are determined according to the covariance matrix of the correspondences at the zero isosurface. in the modelling phase, these measures are used to weight the importance of the training samples phase according to a variable bandwidth non-parametric density estimation process. the selection of the most appropriate kernels to represent the training set is done through the maximum likelihood criterion. excellent results for patterns of digits, related with the registration and the modelling aspects of our approach demonstrate the potentials of our method.
curve and surface smoothing without shrinkage. for a number of computational purposes, including visualization of scientific data and registration of multimodal medical data, smooth curves must be approximated by polygonal curves, and surfaces by polyhedral surfaces. an inherent problem of these approximation algorithms is that the resulting curves and surfaces appear faceted. boundary-following and iso-surface construction algorithms are typical examples. to reduce the apparent faceting, smoothing methods are used. in this paper, we introduce a new method for smoothing piecewise linear shapes of arbitrary dimension and topology. this new method is in fact a linear low-pass filter that removes high-curvature variations, and does not produce shrinkage. its computational complexity is linear in the number of edges or faces of the shape, and the required storage is linear in the number of vertices.
estimating the tensor of curvature of a surface from a polyhedral approximation. estimating principal curvatures and principal directions of a surface from a polyhedral approximation with a large number of small faces, such as those produced by iso-surface construction algorithms, has become a basic step in many computer vision algorithms, particularly in those targeted at medical applications. we describe a method to estimate the tensor of curvature of a surface at the vertices of a polyhedral approximation. principal curvatures and principal directions are obtained by computing in closed form the eigenvalues and eigenvectors of certain 3/spl times/3 symmetric matrices defined by integral formulas, and closely related to the matrix representation of the tensor of curvature. the resulting algorithm is linear, both in time and in space, as a function of the number of vertices and faces of the polyhedral surface.
surface reconstruction from feature based stereo. this paper describes an approach to recovering surface models of complex scenes from the quasi-sparse data returned by a feature based stereo system. the method can be used to merge stereo results obtained from different viewpoints into a single coherent surface mesh. the technique proceeds by exploiting the free space theorem which provides a principled mechanism for reasoning about the structure of the scene based on quasi-sparse correspondences in multiple image. effective methods for overcoming the difficulties posed by missing features and outliers are discussed. results obtained by applying this approach to actual images are presented.
image segmentation by reaction-diffusion bubbles. figure-ground segmentation is a fundamental problem in computer vision. the main difficulty is the integration of low-level, pixel-based local image features to obtain global object-based descriptions. active contours in the form of snakes, balloons, and level-set modeling techniques have been proposed that satisfactorily address this question for certain applications. however, these methods require manual initialization, do not always perform well near sharp protrusions or indentations, or often cross gaps. we propose an approach inspired by these methods and a shock-based representation of shape in terms of parts, protrusions, and bends. since initially it is not clear where the objects or their parts are, parts are hypothesized in the form of fourth order shocks randomly initialized in homogeneous areas of images. these shocks then form evolving contours, or bubbles, which grow, shrink, merge, split and disappear to capture the objects in the image. in the homogeneous areas of the image bubbles deform by a reaction-diffusion process. in the inhomogeneous areas, indicated by differential properties computed from low-level processes such as edge-detection, texture, optical-flow and stereo, etc., bubbles do not deform. as such, the randomly initialized bubbles integrate low-level information and, in the process, segment the figures from the ground.
symmetry maps of free-form curve segments via wave propagation. this paper presents an approach for computing the symmetries (skeletons) of an edge map consisting of a collection of curve segments. this approach is a combination of analytic computations in the style of computational geometry and discrete propagations on a grid in the style of the numerical solutions of pde's. specifically, waves from each of the initial curve segments are initialized and propagated as a discrete wavefront along discrete directions. in addition, to avoid error built up due to the discrete nature of propagation, shockwaves are detected and explicitly propagated along a secondary dynamic grid. the propagation of shockwaves, integrated with the propagation of the wavefront along discrete directions, leads to an exact simulation of propagation by the eikonal equation. the resulting symmetries are simply the collection of shockwaves formed in this process which can be manipulated locally, exactly, and efficiently under local changes in an edge map (gap completion, removal of spurious elements, etc). the ability to express grouping operations in the language of symmetry maps makes it an appropriate intermediate representation between low-level edge maps and high level object hypotheses.
design of multi-parameter steerable functions using cascade basis reduction. a new cascade basis reduction method of computing the optimal least-squares set of basis functions to steer a given function is presented. the method combines the lie group-theoretic and the singular value decomposition approaches such that their respective strengthscomplement each other. since the lie group-theoretic approach is used, the set of basis and steering functions computed can be expressed in analytic form. because the singular value decomposition method is used, this set of basis and steering functions is optimal in the least-squares sense. most importantly, the computational complexity in designing basis functions for transformation groups with large numbers of parameters is significantly reduced. the efficiency of the cascade basis reduction method is demonstrated by designing a set of basis functions to steer a gabor function under the four-parameter linear transformation group.
segmentating cortical gray matter for functional mri visualization. we describe a system that is being used to segment gray matter and create connected cortical representations from mri. the method exploits knowledge of the anatomy of the cortex and incorporates structural constraints into the segmentation. first, the white matterand csf regions in the mr volume are segmented using some novel techniques of posterior anisotropic diffusion. then, the user selects the cortical white matter component of interest, and its structure is verified by checking for cavities and handles. after this, a connected representation of the gray matter is created by a constrained growing-out from the white matter boundary. because the connectivity is computed, the segmentation can be used as input to several methods of visualizing the spatial pattern of cortical activity within gray matter. in our case, the connected representation of gray matter is used to create a representation of theflattened cortex. then, fmri measurements are over-laid on the flattened representation, yielding a representation of the volumetric data within a single image.
animat vision: active vision in artificial animals. we propose and demonstrate a new paradigm for active vision research that draws upon recent advances in the fields of artificial life and computer graphics. a software alternative to the prevailing hardware vision mindset, animat vision prescribes artificial animals, or animats, situated in physics-based virtual worlds as autonomous virtual robots possessing active perception systems. to be operative in its world, an animat must autonomously control its eyes and muscle-actuated body, applying computer vision algorithms to continuously analyze the retinal image streams acquired by its eyes in order to locomote purposefully through its world. we describe an initial animat vision implementation within lifelike artificial fishes inhabiting a physics-based, virtual marine world. emulating the appearance, motion, and behavior of real fishes in their natural habitats, these animats are capable of spatially nonuniform retinal imaging, foveation, retinal image stabilization, color object recognition, and perceptually-guided navigation. these capabilities allow them to pursue moving targets such as fellow artificial fishes. animat vision offers a fertile approach to the development, implementation, and evaluation of computational theories that profess sensorimotor competence for animal or robotic situated agents.
shape classifer based on generalized probabilistic descent method with hidden markov descriptor. the goal of this paper is to present a weighted likelihood discriminant for minimum error shape classification. different from traditional maximum likelihood (ml) methods, in which classification is based on probabilities from independent individual class models as is the case for general hidden markov model (hmm) methods, proposed method utilizes information from all classes to minimize classification error. the proposed approach uses a hmm for shape curvature as its 2-d shape descriptor. in this contribution we introduce a weighted likelihood discriminant function and present a minimum error classification strategy based on generalized probabilistic descent (gpd) method. we believe our sound theory based implementation reduces classification error by combining hmm with gpd theory. we show comparative results obtained with our approach and classic ml classification alongwith fourier descriptor and zernike moments based classification for fighter planes and vehicle shapes.
multi-view geometry of 1d radial cameras and its application to omnidirectional camera calibration. we study the multi-view geometry of 1d radial cameras. a broad a class of both central and non-central cameras, such as fish-eye and catadioptric cameras, can be reduced to 1d radial cameras under the assumption of known center of radial distortion. for cameras in general configuration, we introduce a quadrifocal tensor that can be computed linearly from 15 or more features seen in four views. from this tensor a metric reconstruction of the 1d cameras as well as the observed features can be obtained. in a second phase this reconstruction can then be used as a calibration object to estimate a non-parametric non-central model for the cameras. we study some degenerate cases, including pure rotation. in the case of a purely rotating camera we obtain a trifocal tensor that can be estimated linearly from 7 points in three views. this allows us to obtain a metric reconstruction of the plane at infinity. next, we use the plane at infinity as a calibration device to non-parametrically estimate the radial distortion. we demonstrate the results of our approach on real and synthetic images.
shape from symmetry. we describe a technique for reconstructing probable occluded surfaces from 3-d range images. the technique exploits the fact that many objects possess shape symmetries that can be recognized even from partial 3-d views. our approach identifies probable symmetries and uses them to extend the partial 3-d shape model into the occluded space. to accommodate objects consisting of multiple parts, we describe a technique for segmenting objects into parts characterized by different symmetries. results are provided for a real-world database of 3-d range images of common objects, acquired through an active stereo rig.
recovering 3d motion of multiple objects using adaptive hough transform. presents a method to determine the 3d motion of multiple objects from two perspective views. in our method, segmentation is determined based on a 3d rigidity constraint. we divide the input image into overlapping patches, and for each sample of the translation parameter space, we compute the rotation parameters of patches using a least-squares fit. every patch votes for a sample in the translation and rotation parameter space. for a patch containing multiple motions, we use an m-estimator to compute rotation parameters of a dominant motion. we use the adaptive hough transform to refine the relevant parameter space in a "coarse-to-fine" fashion. applications of the proposed method to both synthetic and real images are demonstrated with promising results.
inference of non-overlapping camera network topology by measuring statistical dependence. we present an approach for inferring the topology of a camera network by measuring statistical dependence between observations in different cameras. two cameras are considered connected if objects seen departing in one camera are seen arriving in the other. this is captured by the degree of statistical dependence between the cameras. the nature of dependence is characterized by the distribution of observation transformations between cameras, such as departure to arrival transition times, and color appearance. we show how to measure statistical dependence when the correspondence between observations in different cameras is unknown. this is accomplished by non-parametric estimates of statistical dependence and bayesian integration of the unknown correspondence. our approach generalizes previous work which assumed restricted parametric transition distributions and only implicitly dealt with unknown correspondence. results are shown on simulated and real data. we also describe a technique for learning the absolute locations of the cameras with global positioning system (gps) side information.
computation of coherent optical flow by using multiple constraints. the optical flow constitutes one of the most widely adopted representations to define and characterize the evolution of image features over time. in order to compute the velocity field, it is necessary to define a set of constraints on the temporal change of image features. we consider the implications in using multiple constraints arising from multiple data points. the first step is the analysis of differential constraints and how they can be applied, locally, to compute the image velocity. this analysis allows to relate each constraint to a particular gray level pattern. this approach is extended to multiple image points, allowing also the characterization of the temporal behaviour of the image features and to detect erroneous measurements due to occlusions, depth discontinuities or shadows. several experiments are presented from real image sequences.
machine learning and multiscale methods in the identification of bivalve larvae. this paper describes a novel application of support vector machines and multiscale texture and color invariants to a problem in biological oceanography: the identification of 6 species of bivalve larvae. our data consists of polarized color images of scallop and other bivalve larvae (between 2 and 17 days old) collected from the ocean by a shipboard optical imaging system of our design. larvae of scallops, clams, and oysters are small (100 microns) with few distinguishing features when observed under standard light microscopy. however, the use of polarized light with a full wave retardation plate produces a vivid color, bi-refringence pattern. the patterns display very subtle differences between species, often not discernable to human observers. we show that a soft-margin support vector machine with gaussian rbf kernel is a good discriminator on a feature set extracted from gabor wavelet transforms and color distribution angles of each image. by constraining the gabor center frequencies to be low, the resulting system can attain classification accuracy in excess of 90% for vertically oriented images, and in excess of 80% for randomly oriented images.
entropy-of-likelihood feature selection for image correspondence. feature points for image correspondence are often selectedaccording to subjective criteria (e.g. edge density,nostrils). in this paper, we present a general, non-subjectivecriterion for selecting informative feature points, based onthe correspondence model itself. we describe the approachwithin the framework of the bayesian markov random field(mrf) model, where the degree of feature point informationis encoded by the entropy of the likelihood term. we proposethat feature selection according to minimum entropy-of-likelihood (eol) is less likely to lead to correspondence ambiguity, thus improving the optimization process in termsof speed and quality of solution. experimental resultsdemonstrate the criterion's ability to select optimal featurespoints in a wide variety of image contexts (e.g. objects,faces). comparison with the automatic kanade-lucas-tomasifeature selection criterion shows correspondence tobe significantly faster with feature points selected accordingto minimum eol in difficult correspondence problems.
bilateral filtering for gray and color images. bilateral filtering smooths images while preserving edges, by means of a nonlinear combination of nearby image values. the method is noniterative, local, and simple. it combines gray levels or colors based on both their geometric closeness and their photometric similarity, and prefers near values to distant values in both domain and range. in contrast with filters that operate on the three bands of a color image separately, a bilateral filter can enforce the perceptual metric underlying the cie-lab color space, and smooth colors and preserve edges in a way that is tuned to human perception. also, in contrast with standard filtering, bilateral filtering produces no phantom colors along edges in color images, and reduces phantom colors where they appear in the original image.
3d tracking = classification + interpolation. hand gestures are examples of fast and complex motions.computers fail to track these in fast video, but sleight ofhand fools humans as well: what happens too quickly wejust cannot see. we show a 3d tracker for these types ofmotions that relies on the recognition of familiar configurationsin 2d images (classification), and fills the gapsin-between (interpolation). we illustrate this idea with experimentson hand motions similar to finger spelling. thepenalty for a recognition failure is often small: if two configurationsare confused, they are often similar to eachother, and the illusion works well enough, for instance, todrive a graphics animation of the moving hand. we contributeadvances in both feature design and classifier training:our image features are invariant to image scale, translation,and rotation, and we propose a classification methodthat combines vqpca with discrimination trees.
an integrated bayesian approach to layer extraction from image sequences. this paper describes a bayesian approach for modeling 3d scenes as a collection of approximately planar layers that are arbitrarily positioned and oriented in the scene. in contrast to much of the previous work on layer-based motion modeling, which computes layered descriptions of 2d image motion, our work leads to a 3d description of the scene. there are two contributions within the paper. the first is to formulate the prior assumptions about the layers and scene within a bayesian decision making framework which is used to automatically determine the number of layers and the assignment of individual pixels to layers. the second is algorithmic. in order to achieve the optimization, a bayesian version of ransac is developed with which to initialize the segmentation. then, a generalized expectation maximization method is used to find the map solution.
robust computation and parametrization of multiple view relations. a new method is presented for robustly estimating multiple view relations from image point correspondences. there are three new contributions, the first is a general purpose method of parametrizing these relations using point correspondences. the second contribution is the formulation of a common maximum likelihood estimate (mle) for each of the multiple view relations. the parametrization facilitates a constrained optimization to obtain the mle. the third contribution is a new robust algorithm, mlesac, for obtaining the point correspondences.the method is general and its use is illustrated for the estimation of fundamental matrices, image to image homographics and quadratic transformations.results are given for both synthetic and real images. it is demonstrated that the method gives results equal or superior to previous approaches.
robust detection of degenerate configurations for the fundamental matrix. new methods are reported for the detection of multiple solutions (degeneracy) when estimating the fundamental matrix, with specific emphasis on robustness in the presence of data contamination (outliers). the fundamental matrix can be used as a first step in the recovery of structure from motion. if the set of correspondences is degenerate then this structure cannot be accurately recovered and many solutions will explain the data equally well. it is essential that we are alerted to such eventualities. however, current feature matchers are very prone to mismatching, giving a high rate of contamination within the data. such contamination can make a degenerate data set appear non degenerate, thus the need for robust methods becomes apparent. the paper presents such methods with a particular emphasis on providing a method that will work on real imagery and with an automated (non perfect) feature detector and matcher. it is demonstrated that proper modelling of degeneracy in the presence of outliers enables the detection of outliers which would otherwise be missed. results using real image sequences are presented. all processing, point matching, degeneracy detection and outlier detection is automatic.
context-based vision system for place and object recognition. while navigating in an environment, a vision system has to be able to recognize where it is and what the main objects in the scene are. in this paper we present a context-based vision system for place and object recognition. the goal is to identify familiar locations (e.g., office 610, conference room 941, main street), to categorize new environments (office, corridor, street) and to use that information to provide contextual priors for object recognition (e.g., tables are more likely in an office than a street). we present a low-dimensional global image representation that provides relevant information for place recognition and categorization, and show how such contextual information introduces strong priors that simplify object recognition. we have trained the system to recognize over 60 locations (indoors and outdoors) and to suggest the presence and locations of more than 20 different object types. the algorithm has been integrated into a mobile system that provides real-time feedback to the user.
semantic organization of scenes using discriminant structural templates. in this paper, we present a procedure for organizing real world scenes along semantic axes. the approach is based on the output energies of linear discriminant filters that take into account, or not, spatial information.we introduce three semantic axes along which pictures are ordered. the main semantic axis computes the degree of naturalness of a scene. then, urban pictures are evaluated according to their degree of verticalness and natural scenes, according to their degree of openness. we observe the emergence of typical scene categories such as beach, mountain, skyscrapers, city center, etc., along the axes.
matching constraints and the joint image. the paper studies the geometry of multi image perspective projection and the matching constraints that this induces on image measurements. the combined image projections define a 3d joint image subspace of the space of combined homogeneous image coordinates. this is a complete projective replica of the 3d world in image coordinates. its location encodes the imaging geometry and is captured by the 4 index joint image grassmannian tensor. projective reconstruction in the joint image is a canonical process requiring only a simple rescaling of image coordinates. reconstruction in world coordinates amounts to a choice of basis in the joint image. the matching constraints are multilinear tensorial equations in image coordinates that tell whether tokens in different images could be the projections of a single world token. for 2d images of 3d points there are exactly three basic types: the epipolar constraint, a. shashua's (1995) trilinear one, and a new quadrilinear 4 image one. for images of lines, r. hartley's (1994) trilinear constraint is the only type. the coefficients of the matching constraints are tensors built directly from the joint image grassmannian. their complex algebraic interdependency is captured by quadratic structural simplicity constraints on the grassmannian.
variational frameworks for dt-mri estimation, regularization and visualization. we address three crucial issues encountered in dt-mri (diffusion tensor magnetic resonance imaging) : diffusion tensor estimation, regularization and fiber bundle visualization. we first review related algorithms existing in the literature and propose then alternative variational formalisms that lead to new and improved schemes, thanks to the preservation of important tensor constraints (positivity, symmetry). we illustrate how our complete dt-mri processing pipeline can be successfully used to construct and draw fiber bundles in the white matter of the brain, from a set of noisy raw mri images.
image parsing: unifying segmentation, detection, and recognition. we propose a general framework for parsing images into regions and objects. in this framework, the detection and recognition of objects proceed simultaneously with image segmentation in a competitive and cooperative manner. we illustrate our approach on natural images of complex city scenes where the objects of primary interest are faces and text. this method makes use of bottom-up proposals combined with top-down generative models using the data driven markov chain monte carlo (ddmcmc) algorithm which is guaranteed to converge to the optimal estimate asymptotically. more precisely, we define generative models for faces, text, and generic regions- e.g. shading, texture, and clutter. these models are activated by bottom-up proposals. the proposals for faces and text are learnt using a probabilistic version of adaboost. the ddmcmc combines reversible jump and diffusion dynamics to enable the generative models to explain the input images in a competitive and cooperative manner. our experiments illustrate the advantages and importance of combining bottom-up and top-down models and of performing segmentation and object detection/recognition simultaneously.
simultaneous multiple 3d motion estimation via mode finding on lie groups. we propose a new method to estimate multiple rigid motions from noisy 3d point correspondences in the presence of outliers. the method does not require prior specification of number of motion groups and estimates all the motion parameters simultaneously. we start with generating samples from the rigid motion distribution. the motion parameters are then estimated via mode finding operations on the sampled distribution. since rigid motions do not lie on a vector space, classical statistical methods can not be used for mode finding. we develop a mean shift algorithm which estimates modes of the sampled distribution using the lie group structure of the rigid motions. we also show that proposed mean shift algorithm is general and can be applied to any distribution having a matrix lie group structure. experimental results on synthetic and real image data demonstrate the superior performance of the algorithm.
state space construction for behavior acquisition in multi agent environments with vision and action. this paper proposes a method which estimates the relationships between learner's behaviors and other agents' ones in the environment through interactions (observation and action) using the method of system identification. in order to identify the model of each agent, akaike's information criterion is applied to the results of canonical variate analysis for the relationship between the observed data in terms of action and future observation. next, reinforcement learning based on the estimated state vectors is performed to obtain the optimal behavior. the proposed method is applied to a soccer playing situation, where a rolling ball and other moving agents are well modeled and the learner's behaviors are successfully acquired by the method. computer simulations and real experiments are shown and a discussion is given.
plane-based calibration algorithm for multi-camera systems via factorization of homography matrices. a new calibration algorithm for multi-camera systemsusing a planar reference pattern is proposed. the algorithmis an extension of sturm-maybank-zhang style plane-basedcalibration technique for use with multiple cameras. rigiddisplacements between the cameras are recovered as well asthe intrinsic parameters only by capturing with the camerasa model plane with known reference points placed at threeor more locations. thus the algorithm yields a simple calibrationmeans for stereo vision systems with an arbitrarynumber of cameras while maintaining the handiness andflexibility of the original method. the algorithm is based onfactorization of homography matrices between the modeland image planes into the camera and plane parameters.to compensate for the indetermination of scaling factors,each homography matrix is rescaled by a double eigenvalueof a planar homology defined by two views and two modelplanes. the obtained parameters are finally refined by anon-linear maximum likelihood estimation (mle) process.the validity of the proposed technique was verified throughsimulation and experiments with real data.
towards an active visual observer. we present a binocular active vision system that can attend to and fixate a moving target. our system has an open and expandable design and it forms the first steps of a long term effort towards developing an active observer using vision to interact with the environment, in particular capable of figure-ground segmentation. we also present partial real-time implementations of this system and show their performance in real-world situations together with motor control. in pursuit we particularly focus on occlusions of other targets, both stationary and moving, and integrate three cues, ego-motion, target motion and target disparity, to obtain an overall robust behavior. an active vision system must be open, expandable, and operate with whatever data are available momentarily. it must also be equipped with means and methods to direct and change its attention. this system is therefore equipped with motion detection for changing attention and pursuit for maintaining attention, both of which run concurrently.
priors for people tracking from small training sets. we advocate the use of scaled gaussian process latent variable models (sgplvm) to learn prior models of 3d human pose for 3d people tracking. the sgplvm simultaneously optimizes a low-dimensional embedding of the high-dimensional pose data and a density function that both gives higher probability to points close to training data and provides a nonlinear probabilistic mapping from the low-dimensional latent space to the full-dimensional pose space. the sgplvm is a natural choice when only small amounts of training data are available. we demonstrate our approach with two distinct motions, golfing and walking. we show that the sgplvm sufficiently constrains the problem such that tracking can be accomplished with straighforward deterministic optimization.
grouping based on projective geometry constraints and uncertainty. the process of grouping and subsequently recognising objects in cluttered images is one laden with difficulties, however, results can be greatly enhanced if the inherent uncertainty of image-features is taken into account. this paper shows that starting with the individual edgel's uncertainty it is possible to calculate covariance-information for all derived quantities. this information can be used to choose between competing algorithms, selecting the one that produces the more reliable results, but also as an aid during the recognition process. the consequent application of error-propagation leads to a new formulation for the calculation of the cross-ratio, which is both robust and efficient in dealing with measured lines, and does notrequire knowledge about the vanishing point. extensive monte-carlo simulations as well as the application to images of cluttered street-scenes demonstrate the robustness and suitability of the approach.
flux maximizing geometric flows. several geometric active contour models have been proposed for segmentation in computer vision and image analysis. the essential idea is to evolve a curve (in 2d) or a surface (in 3d) under constraints from image forces so that it clings to features of interest in an intensity image. recent variations on this theme take into account properties of enclosed regions and allow for multiple curves or surfaces to be simultaneously represented. however, it is still unclear how to apply these techniques to images of narrow elongated structures, such as blood vessels, where intensity contrast may be low and reliable region statistics cannot be computed. to address this problem, we derive the gradient flows which maximize the rate of increase of flux of an appropriate vector field through a curve (in 2d) or a surface (in 3d). the key idea is to exploit the direction of the vector field along with its magnitude. the calculations lead to a simple and elegant interpretation which is essentially parameter free and has the same form in both dimensions. we illustrate its advantages with several level-set-based segmentations of 2d and 3d angiography images of blood vessels.
kalmansac: robust filtering by consensus. we propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. while the optimal (maximum-likelihood) solution has doubly exponential complexity due to the combinatorial explosion of possible choices of inliers, we exploit the structure of the problem to design a sampling-based algorithm that has constant complexity. we derive our algorithm from the equations of the optimal filter, which makes our approximation explicit. our work is motivated by real-time tracking and the estimation of structure from motion (sfm). we test our algorithm for on-line outlier rejection both for tracking and for sfm. we show that our approach can tolerate a large proportion of outliers, whereas previous causal robust statistical inference methods failed with less than half as many. our work can be thought of as the extension of random sample consensus algorithms to dynamic data, or as the implementation of pseudo-bayesian filtering algorithms in a sampling framework.
features for recognition: viewpoint invariance for non-planar scenes. most current local feature detectors/descriptors implicitly assume that the scene is (locally) planar, an assumption that is violated at surface discontinuities. we show that this restriction is, at least in theory, unnecessary, as one can construct local features that are viewpoint-invariant for generic non-planar scenes. however, we show that any such feature necessarily sacrifices shape information, in the sense of being non shape-discriminative. finally, we show that if viewpoint is factored out as part of the matching process, rather than explicitly in the representation, then shape is discriminative indeed. we illustrate our theoretical results empirically by showing that, even for simple scenes, current affine descriptors fail where even a naive 3-d viewpoint invariant succeeds in matching.
three-dimensional scene flow. just as optical flow is the two-dimensional motion of points in an image, scene flow is the three-dimensional motion of points in the world. the fundamental difficulty with optical flow is that only the normal flow can be computed directly from the image measurements, without some form of smoothing or regularization. in this paper, we begin by showing that the same fundamental limitation applies to scene flow; however, many cameras are used to image the scene. there are then two choices when computing scene flow: 1) perform the regularization in the images or 2) perform the regularization on the surface of the object in the scene. in this paper, we choose to compute scene flow using regularization in the images. we describe three algorithms, the first two for computing scene flow from optical flows and the third for constraining scene structure from the inconsistencies in multiple optical flows.
snake pedals: geometric models with physics-based control. in this paper, we introduce a novel geometric shape modeling scheme which allows for representation of global and local shape characteristics of an object. geometric models are traditionally well suited for representing global shapes but not the local details. however, in this paper we propose a powerful geometric shape modeling scheme which allows for the representation of global shap es with local detail and permits model shaping as well as topological changes via physics-based control.the proposed modeling scheme consists of representing shapes by pedal curves and surfaces ¿ pedal curves/surfaces are the loci of the foot of perpendiculars to the tangents of a fixed curve/surface from a fixed point called the pedal point. by varying the location of the pedal point, one can synthesize a large class of shapes which exhibit both local and glob al deformations. we introduce physics-based control for shaping these geometric models by letting the pedal point vary and use a dynamic spline to represent the position of this varying pedal point. the model dubbed as a "snake pedal" allows for interactive manipulation via forces applied to the snake. we demonstrate the applicability of this modeling scheme via examples of shape synthesis and shape estimation from real image data.
maintaining multi-modality through mixture tracking. in recent years particle filters have become a tremendouslypopular tool to perform tracking for non-linearand/or non-gaussian models. this is due to their simplicity,generality and success over a wide range of challengingapplications. particle filters, and monte carlo methodsin general, are however poor at consistently maintainingthe multi-modality of the target distributions that may arisedue to ambiguity or the presence of multiple objects. toaddress this shortcoming this paper proposes to model thetarget distribution as a non-parametric mixture model, andpresents the general tracking recursion in this case. it isshown how a monte carlo implementation of the generalrecursion leads to a mixture of particle filters that interactonly in the computation of the mixture weights, thus leadingto an efficient numerical algorithm, where all the resultspertaining to standard particle filters apply. the ability ofthe new method to maintain posterior multi-modality is illustratedon a synthetic example and a real world trackingproblem involving the tracking of football players in a videosequence.
finding the epipole from uncalibrated optical flow. this paper presents a novel method for determining the location of the instantaneous epipole in a sequence of images acquired by an uncalibrated camera and containing a single, rigid motion (e.g., the camera moves in a static environment). the method uses the full perspective camera model and requires the estimation of the optical flow at a minimum of six image locations. the key observation is that the optical flow equations can be written in terms of the epipole in a strikingly simple form if the translation and rotational flow components are not separated as done usually. the epipole location can then be obtained as the minimum of a least-square residual function asdsociated to the computed optical flow. we report and discuss initial experiments on both synthetic and real data and illustrate possible developments of this method towards the use of uncalibrated optical flow for 3-d motion and structure reconstruction.
object recognition with informative features and linear classification. in this paper we show that efficient object recognition canbe obtained by combining informative features with linear classification. the results demonstrate the superiority of informative class-specific features, as compared with generic type features such as wavelets, for the task of object recognition. we show that information rich features can reach optimal performance with simple linear separation rules, while generic feature based classifiers require more complex classification schemes. this is significant because efficient and optimal methods have been developed for spaces that allow linear separation. to compare different strategies for feature extraction, we trained and compared classifiers working in feature spaces of the same low dimensionality, using two feature types (image fragments vs. wavelets) and two classification rules (linear hyperplane and a bayesian network). the results show that by maximizing the individual information of the features, it is possible to obtain efficient classification by a simple linear separating rule, aswell as more efficient learning.
motion analysis with a camera with unknown, and possibly varying intrinsic parameters. in the present paper we address the problem of computing structure and motion, given a set point correspondences in a monocular image sequence, considering small motions when the camera is not calibrated. we first set the equations defining the calibration, rigid motion and scene structure. we then review the motion equation, the structure from equation and the depth evolution equation, including the particular case of planar structures, considering a discrete displacement between two frames. a step further, we develop the first order expansion of these equations and analyse the observability of the related infinitesimal quantities. it is shown that we obtain a complete correspondence between these equations and the equation derived in the discrete case. however, in the case of infinitesimal displacements, the projection of the translation (focus of expansion or epipole) is clearly separated from the rotational component of the motion. this is an important advantage of the present approach. using this last property, we propose a mechanism of image stabilization in which the rotational disparity is iteratively canceled. this allows a better estimation of the focus of expansion, and simplifies different aspects of the analysis of the equations: structure from motion equation, analysis of ambiguity, geometrical interpretation of the motion equation.
invariant-based recognition of complex curved 3d objects from image contours. to recognize three-dimensional objects bounded by smooth curved surfaces from monocular image contours, viewpoint-dependent image features must be related to object geometry. contour bitangents and inflections along with associated parallel tangents points are the projection of surface points that lie on the occluding contour for a five-parameter family of scaled orthographic projection viewpoints. an invariant representation can be computed from these image features and seen for modeling and recognizing objects. modeling is achieved by moving an object in front of a camera to obtain a curve of possible invariants. the relative camera-object motion is not required, and 3d models are not utilized. at recognition time, invariants computed from a single image are used to index the model database. using the matched features, independent qualitative and quantitative verification procedures eliminate potential false matches. examples from an implementation are presented.
robust real-time face detection. this paper describes a face detection framework that is capable of processing images extremely rapidly while achieving high detection rates. there are three key contributions. the first is the introduction of a new image representation called the &ldquo;integral image&rdquo; which allows the features used by our detector to be computed very quickly. the second is a simple and efficient classifier which is built using the adaboost learning algorithm (freund and schapire, 1995) to select a small number of critical visual features from a very large set of potential features. the third contribution is a method for combining classifiers in a &ldquo;cascade&rdquo; which allows background regions of the image to be quickly discarded while spending more computation on promising face-like regions. a set of experiments in the domain of face detection is presented. the system yields face detection performance comparable to the best previous systems (sung and poggio, 1998; rowley et al., 1998; schneiderman and kanade, 2000; roth et al., 2000). implemented on a conventional desktop, face detection proceeds at 15 frames per second.
detecting pedestrians using patterns of motion and appearance. this paper describes a pedestrian detection system that integratesimage intensity information with motion information.we use a detection style algorithm that scans a detectorover two consecutive frames of a video sequence. thedetector is trained (using adaboost) to take advantage ofboth motion and appearance information to detect a walkingperson. past approaches have built detectors based onmotion information or detectors based on appearance information,but ours is the first to combine both sources ofinformation in a single detector. the implementation describedruns at about 4 frames/second, detects pedestriansat very small scales (as small as 20x15 pixels), and has avery low false positive rate.our approach builds on the detection work of viola andjones. novel contributions of this paper include: i) developmentof a representation of image motion which is extremelyefficient, and ii) implementation of a state of theart pedestrian detection system which operates on low resolutionimages under difficult conditions (such as rain andsnow).
alignment by maximization of mutual information . a new information-theoretic approach is presented for finding the pose of an object in an image. the technique does not require information about the surface properties of the object, besides its shape, and is robust with respect to variations of illumination. in our derivation, few assumptions are made about the nature of the imaging process. as a result, the algorithms are quite general and can foreseeably be used in a wide variety of imaging situations. experiments are presented that demonstrate the approach in registering magnetic resonance images, aligning a complex 3d object model to real scenes including clutter and occlusion, tracking a human head in a video sequence and aligning a view-based 2d object model to real images. the method is based on a formulation of the mutual information between the model and the image. as applied in this paper, the technique is intensity-based, rather than feature-based. it works well in domains where edge or gradient-magnitude based methods have difficulty, yet it is more robust then traditional correlation. additionally, it has an efficient implementation that is based on stochastic approximation.
using frontier points to recover shape, reflectance and illumunation. we describe a method to recover the surface reflectance and the 3-d shape of a non-lambertian object as well as illumination, from a collection of images. it is based on the so-called frontier points, which are extracted from the outlines of an object. frontier points provide 3-d locations on the object surface where the surface normal is known. this information is exploited to infer the surface reflectance of the object and the light distribution of the scene both under varying illumination and fixed vantage point, and under varying vantage point and fixed illumination. we also show how to apply frontier points for shape recovery in photometric stereo. the effectiveness of frontier points for recovering reflectance, illumination and shape is confirmed by a number of experiments on both real and synthetic data.
asl recognition based on a coupling between hmms and 3d motion analysis. we present a framework for recognizing isolated and continuous american sign language (asl) sentences from three-dimensional data. the data are obtained by using physics-based three-dimensional tracking methods and then presented as input to hidden markov models (hmms) for recognition. to improve recognition performance, we model context-dependent hmms and present a novel method of coupling three-dimensional computer vision methods and hmms by temporally segmenting the data stream with vision methods. we then use the geometric properties of the segments to constrain the hmm framework for recognition. we show in experiments with a 53 sign vocabulary that three-dimensional features outperform two-dimensional features in recognition performance. furthermore, we demonstrate that context-dependent modeling and the coupling of vision methods and hmms improve the accuracy of continuous asl recognition.
shape from shading with interreflections under proximal light source: 3d shape reconstruction of unfolded book surface from a scanner image. we address the problem to recover the 3d shape of an unfolded book surface from the shading information in a scanner image. from a technical point of view, this shape from shading problem in real world environments is characterized by (1) proximal light source, (2) interreflections, (3) moving light source, (4) specular reflection, and (5) nonuniform albedo distribution. taking all these factors into account, we first formulate the problem based on an iterative nonlinear optimization scheme. then we introduce piecewise polynomial models of the 3d shape. image restoration experiments for a real book surface demonstrated that geometric and photometric distortions are almost completely removed by the proposed method.
recognition with local features: the kernel recipe. recent developments in computer vision have shown that local features can provide efficient representations suitable for robust object recognition. support vector machines have been established as powerful learning algorithms with good generalization capabilities. in this paper, we combine these two approaches and propose a general kernel method for recognition with local features. we show that the proposed kernel satisfies the mercer condition and that it is suitable for many established local feature frameworks. large-scale recognition results are presented on three different databases, which demonstrate that svms with the proposed kernel perform better than standard matching techniques on local features. in addition, experiments on noisy and occluded images show that local feature representations significantly outperform global approaches.
facial expression decomposition. in this paper, we propose a novel approach for facialexpression decomposition - higher-order singular valuedecomposition (hosvd), a natural generalization ofmatrix svd. we learn the expression subspace and personsubspace from a corpus of images showing seven basicfacial expressions, rather than resort to expert-coded facialexpression parameters as in [3]. we propose a simultaneousface and facial expression recognition algorithm,which can classify the given image into one of the sevenbasic facial expression categories, and then other facialexpressions of the new person can be synthesized using thelearned expression subspace model. the contributions ofthis work lie mainly in two aspects. first, we propose a newhosvd based approach to model the mapping betweenpersons and expressions, used for facial expression synthesisfor a new person. second, we realize simultaneous faceand facial expression recognition as a result of facialexpression decomposition. experimental results are presentedthat illustrate the capability of the person subspaceand expression subspace in both synthesis and recognitiontasks. as a quantitative measure of the quality of synthesis,we propose using gradient minimum square error (gmse)which measures the gradient difference between the originaland synthesized images.
region correspondence by inexact attributed planar graph matching. an efficient graph matching approach is proposed for finding region correspondence between two images of the same scene but taken from different viewpoints. regions and their relations in an image are represented with region adjacency graph (rag), which is a kind of attributed planar graph. the problem to find an optimal region correspondence, which matches the regions in two images with maximal similarity in region features and region relations, is formulated into the problem to find the optimal inexact matching between two rags. the properties specific to planar graph and that of the region adjacency relations are utilized to invent an efficient algorithm to solve the problem. experimental results on various kinds of images show the effectiveness of the method.
learning models for predicting recognition performance. this paper addresses one of the fundamental problems encountered in performance prediction for object recognition. in particular we address the problems related to estimation of small gallery size that can give good error estimates and their confidences on large probe sets and populations. we use a generalized two-dimensional prediction model that integrates a hypergeometric probability distribution model with a binomial model explicitly and considers the distortion problem in large populations. we incorporate learning in the prediction process in order to find the optimal small gallery size and to improve its performance. the chernoff and chebychev inequalities are used as a guide to obtain the small gallery size. during the prediction we use the expectation-maximum (em) algorithm to learn the match score and the non-match score distributions (the number of components, their weights, means and covariances) that are represented as gaussian mixtures. by learning we find the optimal size of small gallery and at the same time provide the upper bound and the lower bound for the prediction on large populations. results are shown using real-world databases.
perceptual scale space and its applications. in this paper, we study a perceptual scale space by constructing a so-called sketch pyramid which augments the gaussian and laplacian pyramid representations in traditional image scale space theory. each level of this sketch pyramid is a generic attributed graph ¿ called the primal sketch which is inferred from the corresponding image at the same level of the gaussian pyramid. when images are viewed at increasing resolutions, more details are revealed. this corresponds to perceptual transitions which are represented by topological changes in the sketch graph in terms of a graph grammar. we compute the sketch or perceptual pyramid by bayesian inference upwards-downwards the pyramid using markov chain monte carlo reversible jumps. we show two example applications of this perceptual scale space: (1) motion tracking of objects over scales, and (2) adaptive image displays which can efficiently show a large high-resolution image in a small screen (of a pda for example) through a selective tour of its image pyramid. other potential applications include super-resolution and multi-resolution object recognition.
an iterative optimization approach for unified image segmentation and matting. separating a foreground object from the background in a static image involves determining both full and partial pixel coverages, also known as extracting a matte. previous approaches require the input image to be pre-segmented into three regions: foreground, background and unknown, which is called a trimap. partial opacity values are then computed only for pixels inside the unknown region. this pre-segmentation based approach fails for images with large portions of semi-transparent foreground where the trimap is difficult to create even manually. in this paper we combine the segmentation and matting problem together and propose a unified optimization approach based on belief propagation. we iteratively estimate the opacity value for every pixel in the image, based on a small sample of foreground and background pixels marked by the user. experimental results show that compared with previous approaches, our method is more efficient to extract high quality mattes for foregrounds with significant semi-transparent regions.
mutual information-based 3d surface matching with applications to face recognition and brain mapping. face recognition and many medical imaging applications require the computation of dense correspondence vector fields that match one surface with another. in brain imaging, surface-based registration is useful for tracking brain change, and for creating statistical shape models of anatomy. based on surface correspondences, metrics can also be designed to measure differences in facial geometry and expressions. to avoid the need for a large set of manually-defined landmarks to constrain these surface correspondences, we developed an algorithm to automate the matching of surface features. it extends the mutual information method to automatically match general 3d surfaces (including surfaces with a branching topology). we use diffeomorphic flows to optimally align the riemann surface structures of two surfaces. first, we use holomorphic1-forms to induce consistent conformal grids on both surfaces. high genus surfaces are mapped to a set of rectangles in the euclidean plane, and closed genus-zero surfaces are mapped to the sphere. next, we compute stable geometric features (mean curvature and conformal factor) and pull them back as scalar fields onto the 2d parameter domains. mutual information is used as a cost functional to drive a fluid flow in the parameter domain that optimally aligns these surface features. a diffeomorphic surface-to-surface mapping is then recovered that matches surfaces in 3d. lastly, we present a spectral method that ensures that the grids induced on the target surface remain conformal when pulled through the correspondence field. using the chain rule, we express the gradient of the mutual information between surfaces in the conformal basis of the source surface. this finite-dimensional linear space generates all conformal reparameterizations of the surface. illustrative experiments apply the method to face recognition and to the registration of brain structures, such as the hippocampus in 3d mri scans, a key step in understanding brain shape alterations in alzheimer¿s disease and schizophrenia.
a novel approach for texture shape recovery. in vision and graphics, there is a sustained interest incapturing accurate 3d shape with various scanning devices.however, the resulting geometric representation isonly part of the story. surface texture of real objects isalso an important component of the representation and fine-scalesurface geometry such as surface markings, roughness,and imprints, are essential in highly realistic renderingand accurate prediction. we present a novel approachfor measuring the fine-scale surface shape of specular surfacesusing a curved mirror to view multiple angles in asingle image. a distinguishing aspect of our method is thatit is designed for specular surfaces, unlike many methods(e.g. laser scanning) which cannot handle highly specularobjects. also, the spatial resolution is very high so that itcan resolve very small surface details that are beyond theresolution of standard devices. furthermore, our approachincorporates the simultaneous use of a bidirectional texturemeasurement method, so that spatially varying bidirectionalreflectance is measured at the same time as surfaceshape.
retrieval with knowledge-driven kernel design: an approach to improving svm-based cbir with relevance feedback. the performance of svm-based image retrieval is often constrained by the scarcity of training samples. the total number of image samples labelled by users in a retrieval session is very limited, and these small number of labelled samples cannot effectively represent the true distributions of positive and negative image classes, especially for the negative image class. this paper proposes a novel approach to deal with this problem. instead of treating it as a problem, the mere existence of the small number of labelled images and their desired distribution in the kernel space is considered as prior knowledge from image retrieval to aid the design of the kernel used by svms. this is achieved by maximizing a criterion, such as one based on scatter matrices, through gradient-based search methods, incurring very little computational overhead to real-time retrieval process. experimental results on two benchmark image databases demonstrate the improved retrieval performance by the dynamically designed kernel and hence the effectiveness of the proposed approach for svm based image retrieval.
surface parameterization using riemann surface structure. we propose a general method that parameterizes general surfaces with complex (possible branching) topology using riemann surface structure. rather than evolve the surface geometry to a plane or sphere, we instead use the fact that all orientable surfaces are riemann surfaces and admit conformal structures, which induce special curvilinear coordinate systems on the surfaces. we can then automatically partition the surface using a critical graph that connects zero points in the global conformal structure on the surface. the trajectories of iso-parametric curves canonically partition a surface into patches. each of these patches is either a topological disk or a cylinder and can be conformally mapped to a parallelogram by integrating a holomorphic 1-form defined on the surface. the resulting surface subdivision and the parameterizations of the components are intrinsic and stable. for surfaces with similar topology and geometry, we show that the parameterization results are consistent and the subdivided surfaces can be matched to each other using constrained harmonic maps. the surface similarity can be measured by direct computation of distance between each pair of corresponding points on two surfaces. to illustrate the technique, we computed conformal structures for anatomical surfaces in mri scans of the brain and human face surfaces. we found that the resulting parameterizations were consistent across subjects, even for branching structures such as the ventricles, which are otherwise difficult to parameterize. our method provides a surface-based framework for statistical comparison of surfaces and for generating grids on surfaces for pde-based signal processing.
high resolution tracking of non-rigid 3d motion of densely sampled data using harmonic maps. we present a novel fully automatic method for high resolution, non-rigid dense 3d point tracking. high quality dense point clouds of non-rigid geometry moving at video speeds are acquired using a phase-shifting structured light ranging technique. to use such data for the temporal study of subtle motions such as those seen in facial expressions, an efficient non-rigid 3d motion tracking algorithm is needed to establish inter-frame correspondences. the novelty of this paper is the development of an algorithmic framework for 3d tracking that unifies tracking of intensity and geometric features, using harmonic maps with added feature correspondence constraints. while the previous uses of harmonic maps provided only global alignment, the proposed introduction of interior feature constraints guarantees that non-rigid deformations will be accurately tracked as well. the harmonic map between two topological disks is a diffeomorphism with minimal stretching energy and bounded angle distortion. the map is stable, insensitive to resolution changes and is robust to noise. due to the strong implicit and explicit smoothness constraints imposed by the algorithm and the high-resolution data, the resultingregistration/deformation field is smooth, continuous and gives dense one-to-one inter-frame correspondences. our method is validated through a series of experiments demonstrating its accuracy and efficiency.
landmark-based shape deformation with topology-preserving constraints. this paper presents a novel approach for landmark-basedshape deformation, in which fitting error and shapedifference are formulated into a support vector machine(svm) regression problem. to well describe nonrigid shapedeformation, this paper measures the shape difference usinga thin-plate spline model. the proposed approach iscapable of preserving the topology of the template shape inthe deformation. this property is achieved by inserting aset of additional points and imposing a set of linear equalityand/or inequality constraints. the underlying optimizationproblem is solved using a quadratic programming algorithm.the proposed method has been tested using practicaldata in the context of shape-based image segmentation.some relevant practical issues, such as missing detectedlandmarks and selection of the regularization parameter arealso briefly discussed.
error analysis of pure rotation-based self-calibration. abstract--self-calibration using pure rotation is a well-known technique and has been shown to be a reliable means for recovering intrinsic camera parameters. however, in practice, it is virtually impossible to ensure that the camera motion for this type of self-calibration is a pure rotation. in this paper, we present an error analysis of recovered intrinsic camera parameters due to the presence of translation. we derived closed-form error expressions for a single pair of images with nondegenerate motion; for multiple rotations for which there are no closed-form solutions, analysis was done through repeated experiments. among others, we show that translation-independent solutions do exist under certain practical conditions. our analysis can be used to help choose the least error-prone approach (if multiple approaches exist) for a given set of conditions.
3d shape and motion analysis from image blur and smear: a unified approach. this paper addresses 3d shape recovery and motion estimation using a realistic camera model with an aperture and a shutter. the spatial blur and temporal smear effects induced by the camera's finite aperture and shutter speed are used for inferring both the shape and motion of the imaged objects
separating reflections in human iris images for illumination estimation. a method is presented for separating corneal reflections in an image of human irises to estimate illumination from the surrounding scene. previous techniques for reflection separation have demonstrated success in only limited cases, such as for uniform colored lighting and simple object textures, so they are not applicable to irises which exhibit intricate textures and complicated reflections of the environment. to make this problem feasible, we present a method that capitalizes on physical characteristics of human irises to obtain an illumination estimate that encompasses the prominent light contributors in the scene. results of this algorithm are presented for eyes of different colors, including light colored eyes for which reflection separation is necessary to determine a valid illumination estimate.
fusion of static and dynamic body biometrics for gait recognition. human identification at a distance has recently gainedgrowing interest from computer vision researchers. thispaper aims to propose a visual recognition algorithmbased upon fusion of static and dynamic body biometrics.for each sequence involving a walking figure, posechanges of the segmented moving silhouettes arerepresented as an associated sequence of complex vectorconfigurations, and are then analyzed using the procrustesshape analysis method to obtain a compact appearancerepresentation, called static information of body. also, amodel-based approach is presented under a condensationframework to track the walker and to recover joint-angletrajectories of lower limbs, called dynamic information ofgait. both static and dynamic cues are respectively used forrecognition using the nearest exemplar classifier. they arealso effectively fused on decision level using differentcombination rules to improve the performance of bothidentification and verification. experimental results on adataset including 20 subjects demonstrate the validity ofthe proposed algorithm.
variable bandwidth qmdpe and its application in robust optical flow estimation. robust estimators, such as least median of squared (lmeds) residuals, m-estimators, the least trimmed squares (lts) etc., have been employed to estimate optical flow from image sequences in recent years. however, these robust estimators have a breakdown point of no more than 50%. in this paper, we propose a novel robust estimator, called variable bandwidth quick maximum density power estimator (vbqmdpe),which can tolerate more than 50% outliers. we apply the novel proposed estimator to robust optical flow estimation. our method yields better results than most other recently proposed methods, and it has the potential to better handle multiple motion effects.
eye gaze estimation from a single image of one eye. in this paper, we present a novel approach, called the"one-circle" algorithm, for measuring the eye gaze using a monocular image that zooms in on only one eye of a person. observing that the iris contour is a circle, we estimate the normal direction of this iris circle, considered as the eye gaze, from its elliptical image. from basic projective geometry, an ellipse can be back-projected into space onto two circles of different orientations. however, by using an anthropometric property of the eyeball, the correct solution can be disambiguated. this allows us to obtain a higher resolution image of the iris with a zoom-in camera and thereby achieving higher accuracies in the estimation. the robustness of our gaze determination approach was verified statistically by the extensive experiments on synthetic and real image data. the two key contributions in this paper are that we show the possibility of finding the unique eye gaze direction from a single image of one eye and that one can obtain better accuracy as a consequence of this.
unified subspace analysis for face recognition. we propose a face difference model that decomposesface difference into three components, intrinsicdifference, transformation difference, and noise. usingthe face difference model and a detailed subspace analysison the three components we develop a unified frameworkfor subspace analysis. using this framework we discoverthe inherent relationship among different subspacemethods and their unique contributions to the extractionof discriminating information from the face difference.this eventually leads to the construction of a 3dparameter space that uses three subspace dimensions asaxis. within this parameter space, we develop a unifiedsubspace analysis method that achieves better recognitionperformance than the standard subspace methods on over2000 face images from the feret database.
joint region tracking with switching hypothesized measurements. this paper proposes a switching hypothesized measurements (shm) model supporting multimodal probability distributions and presents the application ofthe model in handling potential variability in visual environments when tracking multiple objects jointly. for a set of occlusion hypotheses, a frame is measured once under each hypothesis, resulting in a set of measurements at each time instant. a computationally efficient shm filter is derived for online joint region tracking. both occlusion relationships and states of the objects are recursively estimated from the history of hypothesized measurements. the reference image is updated adaptively to deal with appearance changes of the objects. the shm model is generally applicable to various dynamic processes with multiple alternative measurement methods.
patch based blind image super resolution. in this paper, a novel method for learning based image super resolution (sr) is presented. the basic idea is to bridge the gap between a set of low resolution (lr) images and the corresponding high resolution (hr) image using both the sr reconstruction constraint and a patch based image synthesis constraint in a general probabilistic framework. we show that in this framework, the estimation of the lr image formation parameters is straightforward. the whole framework is implemented via an annealed gibbs sampling method. experiments on sr on both single image and image sequence input show that the proposed method provides an automatic and stable way to compute super-resolution and the achieved result is encouraging for both synthetic and real lr images.
cumulative residual entropy, a new measure of information & its application to image alignment. in this paper we use the cumulative distribution of a random variable to define the information content in it and use it to develop a novel measure of information that parallels shannon entropy, which we dub cumulative residual entropy (cre). the key features of cre may be summarized as, (1)its definition is valid in both the continuous and discrete domains,(2) it is mathematically more general than the shannon entropy and (3) its computation from sample data is easy and these computations converge asymptotically to the true values. we define the cross-cre (ccre) between two random variables and apply it to solve the uni- & multi-modal image alignment problem for parameterized (rigid, affine and projective) transformations. the key strengths of the ccre over using the now popular mutual information method (based on shannon's entropy) are that the former has significantly larger noise immunity and a much larger convergence range over the field of parameterized transformations. these strengths of ccre are demonstrated via experiments on synthesized and real image data.
modeling textured motion : particle, wave and sketch. in this paper, we present a generative model for textured motion phenomena, such as falling snow, wavy river and dancing grass, etc. firstly, we represent an image as a linear superposition of image bases selected from a generic and over-complete dictionary. the dictionary contains gabor bases for point/particle elements and fourier bases for wave-elements. these bases compete to explain the input images. the transform from a raw image to a base or a token representation leads to large dimension reduction. secondly, we introduce a unified motion equation to characterize the motion of these bases and the interactions between waves and particles, e.g. a ball floating on water. we use statistical learning algorithm to identify the structure of moving objects and their trajectories automatically. then novel sequences can be synthesized easily from the motion and image models. thirdly, we replace the dictionary of gabor and fourier bases with symbolic sketches (also bases). with the same image and motion model, we can render realistic and stylish cartoon animation. in our view, cartoon and sketch are symbolic visualization of the inner representation for visual perception. the success of the cartoon animation, in turn, suggests that our image and motion models capture the essence of visual perception of textured motion.
rigid body segmentation and shape description from dense optical flow under weak perspective. we present an algorithm for identifying and tracking independently moving rigid objects from optical flow. the proposed method uses the fact that each distinct object has a unique epipolar constraint associated with its motion. this is in contrast to using local optical flow information for segmentation. thus motion discontinuities based on self-occlusion are distinguished from those due to separate objects. the use of epipolar geometry allows for the determination of individual motion parameters for each object as well as the recovery of relative depth for each point on the object. the segmentation problem is formulated as a scene partitioning problem and a statistic-based algorithm which uses only nearest neighbor interactions and a finite number of iterations is developed. a kalman filter based approach is used for tracking motion parameters with time. the algorithm assumes an affine camera where perspective effects are limited to changes in overall scale. no camera calibration parameters are required.
intensity and feature based stereo matching by disparity parametrization. in this paper, we propose a new solution to the stereo correspondence problem by including features in intensity based matching. the features we use are intensity gradients in both the x and y directions of the left and the deformed right images. although a uniform smoothness constraint is still used, it is never-the-less applied only to non-feature regions. to avoid local minima in function minimization, we propose to parameterize the disparity function by hierarchical gaussians. a simple stochastic gradient method is used to estimate the gaussian weights. experiments with various real stereo images show robust performances.
color edge detection by photometric quasi-invariants. photometric invariance is used in many computer vision applications.the advantage of photometric invariance is therobustness against shadows, shading, and illumination conditions.however, the drawbacks of photometric invarianceis the loss of discriminative power and the inherent instabilitiescaused by the non-linear transformations to computethe invariants.in this paper, we propose a new class of derivativeswhich we refer to as photometric quasi-invariants. thesequasi-invariants share with full invariants the nice propertythat they are robust against photometric edges, such asshadows or specular edges. further, these quasi-invariantsdo not have the inherent instabilities of full photometric invariants.we will apply these quasi-invariant derivativesin the context of photometric invariant edge detection andclassification. experiments show that the quasi-invariantderivatives are stable and they significantly outperform thefull invariant derivatives in discriminative power.
segmentation using eigenvectors: a unifying view. automatic grouping and segmentation of images remains a challenging problem in computer vision. recently, a number of authors have demonstrated good performance on this task using methods that are based on eigenvectors of the affinity matrix. these approaches are extremely attractive in that they are based on simple eigen-decomposition algorithms whose stability is well understood. nevertheless, the use of eigen-decompositions in the context of segmentation is far from well understood.in this paper we give a unified treatment of these algorithms, and show the close connections between them while highlighting their distinguishing features. we then prove results on eigenvectors of block matrices that allow us to analyze the performance of these algorithms in simple grouping settings. finally, we use our analysis to motivate a variation on the existing methods that combines aspects from different eigenvector segmentation algorithms. we illustrate our analysis with results on real and synthetic images.
capturing subtle facial motions in 3d face tracking. facial motions produce not only facial feature points motions,but also subtle appearance changes such as wrinklesand shading changes. these subtle changes are importantyet difficult issues for both analysis (tracking) and synthesis(animation). previous approaches were mostly basedon models learned from extensive training appearance examples.however, the space of all possible facial motionappearance is huge. thus, it is not feasible to collect samplescovering all possible variations due to lighting conditions,individualities, and head poses. therefore, it is difficultto adapt such models to new conditions. in this paper,we present an adaptive technique for analyzing subtle facialappearance changes. we propose a new ratio-imagebased appearance feature, which is independent of a person'sface albedo. this feature is used to track face appearancevariations based on exemplars. to adapt the exemplarappearance model to new people and lighting conditions,we develop an online em-based algorithm. experimentsshow that the proposed method improves classification resultsin a facial expression recognition task, where a varietyof people and lighting conditions are involved.
combinatorial constraints on multiple projections of a set of points. multiple projections of a scene cannot be arbitrary, the allowedconfigurations being given by matching constraints.this paper presents new matching constraints on multipleprojections of a rigid point set by uncalibrated cameras, obtainedby formulation in the oriented projective rather thanprojective geometry. they follow from consistency of orientationsof camera rays and from the fact that the scene is theaffine rather that projective space. for their non-parametricnature, we call them combinatorial. the constraints are derivedin a unified theoretical framework using the theory oforiented matroids. for example, we present constraints on4 point correspondences for 2d camera resectioning, on 3correspondences in two 1d cameras, and on 4 correspondencesin two 2d cameras.
rendering real-world objects using view interpolation. presents a new approach to rendering arbitrary views of real-world 3d objects of complex shapes. we propose to represent an object by a sparse set of corresponding 2d views, and to construct any other view as a combination of these reference views. we show that this combination can be linear, assuming proximity of the views, and we suggest how the visibility of constructed points can be determined. our approach makes it possible to avoid difficult 3d reconstruction, assuming only rendering is required. moreover, almost no calibration of views is needed. we present preliminary results on real objects, indicating that the approach is feasible.
space-time scene manifolds. the space of images is known to be a non-linear sub-space that is difficult to model. this paper derives an algorithm that walks within this space. we seek a manifold through the video volume that is constrained to lie locally in this space. every local neighborhood within the manifold resembles some image patch. we call this the scene manifold because the solution traces the scene outline. for a broad class of inputs the problem can be posed as finding the shortest path in a graph and can thus be solved efficiently to produce the globally optimal solution. constraining appearance rather than geometry gives rise to numerous new capabilities. here we demonstrate the usefulness of this approach by posing the well-studied problem of mosaicing in a new way. instead of treating it as geometrical alignment, we pose it as an appearance optimization. since the manifold is constrained to lie in the space of valid image patches, the resulting mosaic is guaranteed to have the least distortions possible. any small part of it can be seen in some image even though the manifold spans the whole video. thus it can deal seamlessly with both static and dynamic scenes, with or without 3d parallax. essentially, the method simultaneously solves two problems that have been solved only separately until now: alignment and mosaicing.
consensus surfaces for modeling 3d objects from multiple range images. in this paper, we present a robust method for creating a triangulated surface mesh from multiple range images. our method merges a set of range images into a volumeteric implicit-surface representation which is converted to a surface mesh using a variant of the marching-cubes algorithm. unlike previous techniques based on implicit-surface representations, our method estimates the signed distance to the object surface by finding a consensus of locally coherent observations of the surface. we call this method the consensus-surface algorithm. this algorithm effectively eliminates many of the troublesome effects of noise and extraneous surface observations without sacrificing the accuracy of the resulting surface. we utilize octrees to represent volumetric implicit surfaces ¿ effectively reducing the computation and memory requirements of the volumetric representation without sacrificing accuracy of the resulting surface. we present results which demonstrate that our consensus-surface algorithm can construct accurate geometric models from rather noisy input range date.
algorithms for implicit deformable models. this paper presents a framework for implicit deformable models and a pair of new algorithms for solving the nonlinear partial differential equations that result from this framework. implicit models offer a useful alternative to parametric models, particularly when dealing with the deformation of higher-dimensional objects. the basic expressions for the evolution of implicit models are relatively straightforward; they follow as a direct consequence of the chain rule for differentiation. more challenging, however, is the development of algorithms that are stable and efficient. the first algorithm is a viscosity approximation which gives solutions over a dense set in the range, providing a means of calculating the solutions of embedded families of contours simultaneously. the second algorithm incorporates sparse solutions for a discrete set of contours. this sparse-field method requires a fraction of the computation compared to the first but offers solutions only for a finite number of contours. results from 3d medical data as well as video images are shown.
scene modeling based on constraint system decomposition techniques. we present a new approach to 3d scene modeling basedon geometric constraints. contrary to the existing methods,we can quickly obtain 3d scene models that respectthe given constraints exactly. our system can describe alarge variety of linear and non-linear constraints in a flexibleway.to deal with the constraints, we decided to exploit theproperties of the gpdof algorithm developed in the constraintprogramming community [12]. the approach isbased on a dictionary of so-called r-methods, based on theoremsof geometry, which can solve a subset of geometricconstraints in a very efficient way. gpdof is used to find,in polynomial-time, a reduced parameterization of a scene,and to decompose the equation system, induced by constraints,into a sequence of r-methods. we have validatedour approach in reconstructing, from images, 3d modelsof buildings based on linear and quadratic geometric constraints.
closing the loop on multiple motions. we describe a number of advances in the analysis of road scenes when the scene contains multiple moving objects and is observed by a single nonsteerable camera mounted on the front of a vehicle. our structure from motion approach to scene segmentation derives front the observed motions of independently moving objects and requires no prior knowledge. we describe a hierarchy of camera models for the analysis of the scene, the simpler models handle degeneracies that occur in the more complex models. the major technical contribution is the recursive computation of feature clusters, which are fed forward over time. this closed loop feature tracking generates extended feature trajectories which significantly improve the discriminating power of scene segmentation.
a quantitative analysis of view degeneracy and its use for active focal length control. we quantify the observation by kender and freudenstein (1987) that degenerate views occupy a significant fraction of the viewing sphere surrounding an object. this demonstrates that systems for recognition must explicitly account for the possibility of view degeneracy. we show that view degeneracy cannot be detected from a single camera viewpoint. as a result, systems designed to recognize objects from a single arbitrary viewpoint must be able to function in spite of possible undetected degeneracies, or else operate with imaging parameters that cause acceptably low probabilities of degeneracy. to address this need, we give a prescription for active control of focal length that allows a principled tradeoff between the camera field of view and probability of view degeneracy.
a sparse probabilistic learning algorithm for real-time tracking. this paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. recently avidan [1] has shown that object recognizers using kernel-svms can be elegantly adapted to localization by means of spatial perturbation of the svm, using optic flow. whereas avidan's svm applies to each frame of a video independently of other frames, the benefits of temporal fusion of data are well known. this issue is addressed here by using a fully probabilistic 'relevance vector machine' (rvm) to generate observations with gaussian distributions that can be fused over time. to improve performance further, rather than adapting a recognizer, webuild a localizer directly using the regression form of the rvm. a classification svm is used in tandem, for object verification, and this provides the capability of automatic initialization and recovery. the approach is demonstrated in real-time face and vehicle tracking systems. the 'sparsity' of the rvms means that only a fraction of cpu time is required to track at frame rate. tracker output is demonstrated in a camera management task in which zoom and pan are controlled inresponse to speaker/vehicle position and orientation, over an extended period. the advantages of temporal fusion inthis system are demonstrated.
stochastic completion fields: a neural model of illusory contour shape and salience. we describe an algorithm and representation level theory of illusory contour shape and salience. unlike previous theories, our model is derived from a single assumption-namely, that the prior probability distribution of boundary completion shape can be modeled by a random walk in a lattice whose points are positions and orientations in the image plane (i.e. the space which one can reasonably assume is represented by neurons of the mammalian visual cortex). our model does not employ numerical relaxation or other explicit minimization, but instead relies on the fact that the probability that a particle following a random walk will pass through a given position and orientation on a path joining two boundary fragments can be computed directly as the product of two vector-field convolutions. we show that for the random walk we define, the maximum likelihood paths are curves of least energy, that is, on average, random walks follow paths commonly assumed to model the shape of illusory contours. a computer model is demonstrated on numerous illusory contour stimuli from the literature.
recognition and interpretation of parametric gesture. a new method for the representation, recognition, and interpretation of parameterized gesture is presented. by parameterized gesture we mean gestures that exhibit a meaniful variation; one example is a point gesture where the important parameter is the 2-dimnesional direction. our approach is to extend the standard hidden markov model method of gesture recognition by including a global parametric variation in the output probabilities of the states of the hmm. using a linear model to derive the theory, we formulate an expectation-maximization (em) method for training the parametric hmm. during testing, the parametric hmm simultaneously recognizes the gesture and estimates the quantifying parameters. using visually-derived and directly measured 3-dimensional hand position measurements as input, we present results on two different movements ¿ a size gesture and a point gesture ¿ and show robustness with respect to noise in the input features.
relational matching with dynamic graph structures. the paper describes a novel approach to relational matching problems in machine vision. rather than matching static scene descriptions, the approach adopts an active representation of the data to be matched. this representation is iteratively reconfigured to increase its degree of topological congruency with the model relational structure in a reconstructive matching process. the active reconfiguration of relational structures is controlled by a map update process. the final restored graph representation is optimal in the sense that it has maximum a posteriori probability with respect to the available attributes for the objects under match. the benefits of the technique are demonstrated experimentally on the matching of cluttered synthetic aperture radar data to a model in the form of a digital map. the operational limits of the method are established in a simulation study.
object categorization by learned universal visual dictionary. this paper presents a new algorithm for the automatic recognition of object classes from images (categorization). compact and yet discriminative appearance-based object class models are automatically learned from a set of training images. the method is simple and extremely fast, making it suitable for many applications such as semantic image retrieval, web search, and interactive image editing. itclassifies a region according to the proportions of different visual words (clusters in feature space). the specific visual words and the typical proportions in each object are learned from a segmented training set. the main contribution of this paper is two fold: i) an optimally compact visual dictionary is learned by pair-wise merging of visual words from an initially large dictionary. the final visual words are described by gmms. ii) a novel statistical measure of discrimination is proposed which is optimized by each merge operation. high classification accuracy is demonstrated for nine object classes on photographs of real objects viewed under general lighting conditions, poses and viewpoints. the set of test images used for validation comprise: i) photographs acquired by us, ii) images from the web and iii) images from the recently released pascal dataset. the proposed algorithm performs well on both texture-rich objects (e.g. grass, sky, trees) and structure-rich ones (e.g. cars, bikes, planes).
locus: learning object classes with unsupervised segmentation. we address the problem of learning object class models and object segmentations from unannotated images. we introduce locus (learning object classes with unsupervised segmentation) which uses a generative probabilistic model to combine bottom-up cues of color and edge with top-down cues of shape and pose. a key aspect of this model is that the object appearance is allowed to vary from image to image, allowing for significant within-class variation. by iteratively updating the belief in the object¿s position, size, segmentation and pose, locus avoids making hard decisions about any of these quantities and so allows for each to be refined at any stage. we show that locus successfully learns an object class model from unlabeled images, whilst also giving segmentation accuracies that rival existing supervised methods. finally, we demonstrate simultaneous recognition and segmentation in novel images using the learned models for a number of object classes, as well as unsupervised object discovery and tracking in video.
feature selection for unsupervised and supervised inference: the emergence of sparsity in a weighted-based approach. the problem of selecting a subset of relevant features in a potentially overwhelming quantity of data is classic and found in many branches of science including - examples in computer vision, text processing and more recently bio-informatics are abundant. in this work we present a definition of '"relevancy" based on spectral properties of the affinity (or laplacian) of the features' measurement matrix. the feature selection process is then based on a continuous ranking of the features defined by a least-squares optimization process. a remarkable property of the feature relevance function is that sparse solutions for the ranking values naturally emerge as a result of a "biased non-negativity" of a key matrix in the process. as a result, a simple least-squares optimization process converges onto a sparse solution, i.e., a selection of a subset of features which form a local maxima over the relevance function. the feature selection algorithm can be embedded in both unsupervised and supervised inference problems and empirical evidence show that the feature selections typically achieve high accuracy even when only a small fraction of the features are relevant.
3d surface topography from intensity images. the paper demonstrates how a new shape from shading scheme can be used to extract topographic information from 2d intensity imagery. the shape-from-shading scheme has two novel ingredients. firstly, it uses a geometric update procedure which allows the image irradiance equation to be satisfied as a hard constraint. this not only improves the data closeness of the recovered needle-map, but also removes the necessity for extensive parameter tuning. secondly, we use curvature information to impose topographic constraints on the recovered needle-map. the topographic information is captured using the shape index of j.j. koenderink and a.j. van doorn (1995) and consistency is imposed using a robust error function. we show that the new shape-from-shading scheme leads to a meaningful topographic labelling of 3d surface structures
8-point algorithm revisited: factorized 8-point algorithm. in this paper, a novel algorithm for the fundamental matrix estimation, called factorized 8-point algorithm, is presented. the factorized 8-point algorithm is composed of three steps: (1) the measurement matrix in the traditional 8-point algorithm is decomposed into two factor matrices; (2) by introducing some auxiliary variables, a new linear minimization problem is formed, where every element of its associated measurement matrix is simply either a measurement datum or a constant; (3) the fundamental matrix is determined by solving this minimization problem by a least squares method. like the traditional 8-point algorithm and hartley¿s normalized 8-point algorithm, the factorized8-point algorithm is also completely linear. but unlike the normalized 8-point algorithm, the factorized 8-point algorithm does not need any pre-normalization step. since every element of the measurement matrix in the factorized8-point algorithm is a measurement datum or a constant, no amplification of measurement error is involved; the factorized 8-point algorithm can boost effectively the robustness of the estimation. large numbers of experiments show that the factorized 8-point algorithm consistently outperforms the traditional 8-point algorithm. in addition, although the factorized 8-point algorithm is specially designed for fundamental matrix estimation, its basic principle can be generalized to other estimation problems in computer vision, such as camera projection matrix estimation, homography estimation, focus of expansion estimation, and trifocal tensor estimation.
tracking articulated body by dynamic markov network. a new method for visual tracking of articulated objectsis presented. analyzing articulated motion is challengingbecause the dimensionality increase potentially demandstremendous increase of computation. to ease this problem,we propose an approach that analyzes subparts locallywhile reinforcing the structural constraints at the meantime. the computational model of the proposed approachis based on a dynamic markov network, a generative modelwhich characterizes the dynamics and the image observationsof each individual subpart as well as the motion constraintsamong different subparts. probabilistic variationalanalysis of the model reveals a mean field approximationto the posterior densities of each subparts given visual evidence,and provides a computationally efficient way forsuch a difficult bayesian inference problem. in addition,we design mean field monte carlo (mfmc) algorithms, inwhich a set of low dimensional particle filters interact witheach other and solve the high dimensional problem collaboratively.extensive experiments on tracking human bodyparts demonstrate the effectiveness, significance and computationalefficiency of the proposed method.
optical flow estimation using wavelet motion model. a motion estimation algorithm using wavelet approximation as an optical flow model has been developed to estimate accurate dense optical flow from an image sequence. this wavelet motion model is particularly useful in estimating optical flows with large displacement. traditional pyramid methods which use the coarse-to-fine image pyramid by image burring in estimating optical flow often produce incorrect results when the coarse-level estimates contain large errors that cannot be corrected at the subsequent finer levels. this happens when regions of low texture become flat or certain patterns result in spatial aliasing due to imageblurring. our method, in contrast, uses large-to-small full-resolution regions without blurring images, and simultaneously optimizes the coarser and finer parts of optical flow so that the large and small motion can be estimated correctly. we compare results obtained by using our method with those obtained by using one of the leading optical flow methods, the szeliski pyramid spline-based method. the experiments include cases of small displacement (less than4 pixels under 128 × 128 image size or equivalent displacement under other image sizes), and those of large displacement (10 pixels). while both methods produce comparableresults when the displacements are small, our method out performs pyramid spline-based method when the displacements are large.
equivalence of julesz and gibbs texture ensembles. research on texture has been pursued along two different lines. the first line of research, pioneered by julesz (1962), seeks the essential ingredients in terms of features and statistics in human texture perception. this leads us to a mathematical definition of texture as a julesz ensemble. a julesz ensemble is the maximum set of images that share the same value of some basic feature statistics as the image \math, or equivalently it is a uniform distribution on this set. the second line of research studies statistical models, in particular, markov random field (mrf) and frame models (zhu, wu, and mumford 1997), to characterize texture patterns locally.in this article, we bridge the two lines by the fundamental principle of equivalence of ensembles in statistical mechanics (gibbs, 1902). we prove that 1). the conditional probability of an arbitrary image patch given its environment, under the julesz ensemble or the uniform model, is inevitably a frame (mrf) model, and 2). the limit of the frame (mrf) model, which we called the gibbs ensemble, is equivalent to a julesz ensemble as \math. thus the advantages of the two methodologies can be fully utilized.
visual learning given sparse data of unknown complexity. this study addresses the problem of unsupervised visual learning. it examines existing popular model order selection criteria before proposes two novel criteria for improving visual learning given sparse data and without any knowledge about model complexity. in particular, a rectified bayesian information criterion (bicr) and a completed likelihood akaike¿s information criterion (cl-aic) are formulated to estimate the optimal model order (complexity) for learning the dynamic structure of a visual scene. both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from very small to large. extensive experiments on learning a dynamic scene structure are carried out to demonstrate the effectiveness of bicr and cl-aic, compared to that of bic [15], aic [1], icl [3] and a mml based criterion [7].
video behaviour profiling and abnormality detection without manual labelling. a novel framework is developed for automatic behaviour profiling and abnormality sampling/detection without any manual labelling of the training dataset. natural grouping of behaviour patterns is discovered through unsupervised model selection and feature selection on the eigen-vectors of a normalised affinity matrix. our experiments demonstrate that a behaviour model trained using an unlabelled dataset is superior to those trained using the same but labelled dataset in detecting abnormality from an unseen video.
uncalibrated perspective reconstruction of deformable structures. reconstruction of 3d structures from uncalibrated image sequences has a wealthy history. most work has been focused on rigid objects or static scenes. this paper studies the problem of perspective reconstruction of deformable structures such as dynamic scenes from an uncalibrated image sequence. the task requires decomposing the image measurements into a composition of three factors: 3d deformable structures, rigid rotations and translations, and intrinsic camera parameters. we develop a factorization algorithm that consists of two steps. in the first step we recover the projective depths iteratively using the sub-space constraints embedded in the image measurements of the deformable structures. in the second step, we scale the image measurements by the reconstructed projective depths. we then extend the linear closed-form solution for weakperspective reconstruction [23] to factorize the scaled measurements and simultaneously reconstruct the deformable shapes and underlying shape model, the rigid motions, and the varying camera parameters such as focal lengths. the accuracy and robustness of the proposed method is demonstrated quantitatively on synthetic data and qualitatively on real image sequences.
two-frame wide baseline matching. this paper describes a novel approach to automatically recover corresponding feature points and epipolar geometry over two wide baseline frames. our contributions consist of several aspects: first, the use of an affine invariant feature, edge-corner, is introduced to provide a robust and consistent matching primitives. second, based on svd decomposition of affine matrix, the affine matching space between two corners can be approximately divided into two independent spaces by rotation angle and scaling factor. employing this property, a two-stage affine matching algorithm is designed to obtain robust matches over two frames. third, using the epipolar geometry estimated by these matches, more corresponding feature points are determined. based on these robust correspondences, the fundamental matrix is refined, and a series of virtual views of the scene are synthesized. finally, several experiments are presented to illustrate that a number of robust correspondences can be stably determined for two wide baseline images under significant camera motions with illumination changes, occlusions, and self-similarities. after testing a number of examples and comparing with the existing methods, the experimental results strongly demonstrate that our matching method outperforms the state-of-art algorithms for all of the test cases.
boosting chain learning for object detection. a general classification framework, called boostingchain, is proposed for learning boosting cascade. in thisframework, a "chain" structure is introduced to integratehistorical knowledge into successive boosting learning.moreover, a linear optimization scheme is proposed toaddress the problems of redundancy in boosting learningand threshold adjusting in cascade coupling. by thismeans, the resulting classifier consists of fewer weakclassifiers yet achieves lower error rates than boostingcascade in both training and test. experimentalcomparisons of boosting chain and boosting cascade areprovided through a face detection problem. thepromising results clearly demonstrate the effectivenessmade by boosting chain.
automatic 3d face modeling from video. in this paper, we develop an efficient technique for fully automatic recovery of accurate 3d face shape from videos captured by a low cost camera. the method is designed to work with a short video containing a face rotating from frontal view to profile view. the whole approach consists of three components. first, automatic initialization is performed in the first frame with approximately frontal face. then, to handle the case of low quality image captured by low cost camera, the 2d feature matching, head poses and underlying 3d face shape are estimated and refined iteratively in an efficient way based on image sequence segmentation. finally, to take advantage of the sparse structure of the proposed algorithm, sparse bundle adjustment technique is further employed to speed up the computation. we demonstrate the accuracy and robustness of the algorithm using a set of experiments.
hypergeometric filters for optical flow and affine matching. this paper proposes new "hypergeometric" filters for the problem of image matching under the translational and affine model. this new set of filters has the following advantages: (1) high-precision registration of two images under the translational and affine model. because the window effects are eliminated, we are able to achieve superb performance in both translational and affine matching. (2) affine matching without exhaustive search or image warping. due to the recursiveness of the filters in the spatial domain, we are able to analytically express the relation between filter outputs and the six affine parameters. this analytical relation enables us to directly compute these affine parameters. (3) generality. the approach we demonstrate here can be applied to a broad class of matching problems, as long as the transformation between the two image patches can be mathematically represented in the frequency domain.
tracking articulated hand motion with eigen dynamics analysis. this paper introduces the concept of eigen-dynamics andproposes an eigen dynamics analysis (eda) method to learnthe dynamics of natural hand motion from labelled sets ofmotion captured with a data glove. the result is parameterizedwith a high-order stochastic linear dynamic system(lds) consisting of five lower-order lds. each correspondingto one eigen-dynamics. based on the eda model, weconstruct a dynamic bayesian network (dbn) to analyzethe generative process of a image sequence of natural handmotion. using the dbn, a hand tracking system is implemented.experiments on both synthesized and real-worlddata demonstrate the robustness and effectiveness of thesetechniques.
parameterized modeling and recognition of activities. a framework for modeling and recognition of temporal activities is proposed. the modeling of sets of exemplar activities is achieved by parameterizing their representation in the form of principal components. recognition of spatio-temporal variants of modeled activities is achieved by parameterizing the search in the space of admissible transformations that the activities can undergo. experiments on recognition of articulated and deformable object motion from image motion parameters are presented.
okapi-chamfer matching for articulated object recognition. recent years have witnessed the rise of many effective text information retrieval systems. by treating local visual features as terms, training images as documents and input images as queries, we formulate the problem of object recognition into that of text retrieval. our formulation opens up the opportunity to integrate some powerful text retrieval tools with computer vision techniques. in this paper, we propose to improve the efficiency of articulated object recognition by an okapi-chamfer matching algorithm. the algorithm is based on the inverted index technique. the inverted index is a widely used way to effectively organize a collection of text documents. with the inverted index, only documents that contain query terms are accessed and used for matching. to enable inverted indexing in an image database, we build a lexicon of local visual features by clustering the features extracted from the training images. given a query image, we extract visual features and quantize them based on the lexicon, and then look up the inverted index to identify the subset of training images with non-zero matching score. to evaluate the matching scores in the subset, we combined the modified okapi weighting formula with the chamfer distance. the performance of the okapi-chamfer matching algorithm is evaluated on a hand posture recognition system. we test the system with both synthesized and real world images. quantitative results demonstrate the accuracy and efficiency of our system.
detection, analysis and matching of hair. we develop computational models for measuring hair appearance for comparing different people. the models and methods developed have applications to person recognition and face image indexing. an automatic hair detection algorithm is described and results reported. a multidimensional representation of hair appearance is presented and computational algorithms are described. results on a dataset of 524 subjects are reported. identification of people using hair attributes is compared to eigenface-based recognition along with a joint, eigenface-hair based identification.
a background layer model for object tracking through occlusion. motion layer estimation has recently emerged as apromising object tracking method. in this paper, we extendprevious research on layer-based tracker by introducingthe concept of background occluding layers and explicitlyinferring depth ordering of foreground layers. thebackground occluding layers lie in front of, behind, and inbetween foreground layers. each pixel in the backgroundregions belongs to one of these layers and occludes all theforeground layers behind it. together with the foregroundordering, the complete information necessary for reliablytracking objects through occlusion is included in ourrepresentation. an map estimation framework isdeveloped to simultaneously update the motion layerparameters, the ordering parameters, and the backgroundoccluding layers. experimental results show that undervarious conditions with occlusion, including situationswith moving objects undergoing complex motions orhaving complex interactions, our tracking algorithm isable to handle many difficult tracking tasks reliably.
learned temporal models of image motion. an approach for learning and estimating temporal-flow models from image sequences is proposed. the temporal-flow models are represented as a set of orthogonal temporal-flow bases that are learned using principal component analysis of instantaneous flow measurements. spatial constraints on the temporal-flow are also developed for modeling the motion of regions in rigid and coordinated motion. the performance of these models is demonstrated on several long image sequences of rigid and articulated bodies in motion.
learning a sparse, corner-based representation for time-varying background modeling. time-varying phenomenon, such as ripples on water, trees waving in the wind and illumination changes, produces false motions, which significantly compromises the performance of an outdoor-surveillance system. in this paper, we propose a corner-based background model to effectively detect moving-objects in challenging dynamic scenes. specifically, the method follows a three-step process. first, we detect feature points using a harris corner detector and represent them as sift-like descriptors. second, we dynamically learn a background model and classify each extracted feature as either a background or a foreground feature. last, a "lucas-kanade" feature tracker is integrated into this framework to differentiate motion-consistent foreground objects from background objects with random or repetitive motion. the key insight of our work is that a collection of sift-like features can effectively represent the environment and account for variations caused by natural effects with dynamic movements. features that do not correspond to the background must therefore correspond to foreground moving objects. our method is computational efficient and works in real-time. experiments on challenging video clips demonstrate that the proposed method achieves a higher accuracy in detecting the foreground objects than the existing methods.
region competition: unifying snakes, region growing, energy/bayes/mdl for multi-band image segmentation. we present a novel statistical and variational approach to image segmentation based on a new algorithm named region competition. this algorithm is derived by minimizing a generalized bayes/mdl (minimum description length) criterion using the variational principle. we show that existing techniques in early vision such as, snake/balloon models, region growing, and bayes/mdl are addressing different aspects of the same problem and they can be unified within a common statistical framework which combines their advantages. we analyze how to optimize the precision of the resulting boundary location by studying the statistical properties of the region competition algorithm and discuss what are good initial conditions for the algorithm. our method is generalized to color and texture segmentation and is demonstrated on grey level images, color images and texture images.
free-form surface registration using surface signatures. this paper introduces a new free-form surface representation scheme for the purpose of fast and accurate registration and matching. accurate registration of surfaces is a common task in computer vision. the proposed representation scheme captures the surface curvature information, seen from certain points and produces images, called surface signatures, at these points. matching signatures of different surfaces enables the recovery of the transformation parameters between these surfaces. we propose to use template matching to compare the signature images. to enable partial matching, another criterion, the overlap ratio, is used. this representation scheme can be used as a global representation of the surface as well as a local one and performs near real-time registration. we show that the signature representation can be used to match objects in 3-d scenes in the presence of clutter and occlusion. applications presented include free-form object matching, multimodal medical volumes registration and dental teeth reconstruction from intra-oral images.
grade: gibbs reaction and diffusion equation. recently there have been increasing interest in using nonlinear pdes for applications in computer vision and image processing, in this paper, we propose a general statistical framework for designing a new class of pdes. for a given applications, a markov random field model p(i) is learned according to the minimax entropy principle studied in [25] [26], so that p(i) should characterize the ensemble of images in our application. p(i) is a gibbs distribution whose energy terms can be divided into two categories. subsequently the partial differential equations given by gradient descent on the gibbs potential are essentially reaction-diffusion equations, where the energy terms in one category produce anisotropic diffusion while the inverted energy terms in the second category produce reaction associated with pattern formation. we call this new class of pdes the gibbs reaction and diffusion equations ¿ grade and we demonstrate experiments where grade are used for texture pattern formation, denoising, image enhancements, and clutter removal.
ranking prior likelihood distributions for bayesian shape localization framework. in this paper, we formulate the shape localization problem in the bayesian framework. in the learning stage, we propose the constrained rank boost approach to model the likelihood of local features associated with the keypoints of an object, like face, while preserve the prior ranking order between the ground truth position of a keypoint and its neighbors; in the inferring stage, a simple efficient iterative algorithm is proposed to uncover the map shape by locally modeling the likelihood distribution around each key point via our proposed variational locally weighted learning (vlwl) method. our proposed framework has the following benefits: 1) compared to the classical pca models, the likelihood presented by the ranking prior likelihood model has more discriminating power as to the optimal position and its neighbors, especially in the problem with ambiguity between the optimal positions and their neighbors; 2) the vlwl method guarantees that the posterior probability of the derived shape increases monotonously; and 3) the above two methods are both based on accurate probability formulation, which spontaneously leads to a robust confidence measure for the discovered shape. moreover, we present a theoretical analysis for the convergence of the constrained rank-boost. extensive experiments compared with the active shape models demonstrate the accuracy, robustness, and stability of our proposed framework.
automatically labeling video data using multi-class active learning. labeling video data is an essential prerequisite for many vision applications that depend on training data, such as visual information retrieval, object recognition, and human activity modeling. however, manually creating labels is not only time-consuming but also subject to human errors, and eventually, becomes impossible for a very large amount of data (e.g. 24/7 surveillance video). to minimize the human effort in labeling, we propose a unified multi-class active learning approach for automatically labeling video data. the contributions of this paper include extending active learning from binary classes to multiple classes and evaluating several practical sample selection strategies. the experimental results show that the proposed approach works effectively even with a significantly reduced amount of labeled data. the best sample selection strategy can achieve more than a 50% error reduction over random sample selection.
forms: a flexible object recognition and modelling system. we briefly describe a generic statistical framework for representing the shapes of animate objects using principal component analysis and stochastic shape grammars. such a representation scheme gives a formalism for solving the inverse problem-object recognition. then we show: how these representations can be extracted from 2d silhouettes by a novel method for skeleton extraction and shape segmentation; how a similarity metric can be defined on this shape space; and how we can perform recognition in a bottom up/top down loop. the system is demonstrated to be stable in the presence of noise, the absence of parts, the presence of additional parts, and considerable variations in articulation and viewpoint. successful categorization is demonstrated on a dataset of seventeen categories of animate objects.
fast multiple object tracking via a hierarchical particle filter. a very efficient and robust visual object tracking algorithm based on the particle filter is presented. the method characterizes the tracked objects using color and edge orientation histogram features. while the use of more features and samples can improve the robustness, the computational load required by the particle filter increases. to accelerate the algorithm while retaining robustness we adopt several enhancements in the algorithm. the first is the use of integral images [34] for efficiently computing the color features and edge orientation histograms, which allows a large amount of particles and a better description of the targets. next, the observation likelihood based on multiple features is computed in a coarse-to-fine manner, which allows the computation to quickly focus on the more promising regions. quasi-random sampling of the particles allows the filter to achieve a higher convergence rate. the resulting tracking algorithm maintains multiple hypotheses and offers robustness against clutter or short period occlusions. experimental results demonstrate the efficiency and effectiveness of the algorithm for single and multiple object tracking.
binocular helmholtz stereopsis. helmholtz stereopsis has been introduced recently as a surfacereconstruction technique that does not assume a modelof surface reflectance. in the reported formulation, correspondencewas established using a rank constraint, necessitatingat least three viewpoints and three pairs of images.here, it is revealed that the fundamental helmholtz stereopsisconstraint defines a nonlinear partial differential equation,which can be solved using only two images. it is shownthat, unlike conventional stereo, binocular helmholtz stereopsisis able to establish correspondence (and thereby recoversurface depth) for objects having an arbitrary andunknown brdf and in textureless regions (i.e., regions ofconstant or slowly varying brdf). an implementation andexperimental results validate the method for specular surfaceswith and without texture.
improved fast gauss transform and efficient kernel density estimation. evaluating sums of multivariate gaussians is a common computational task in computer vision and pattern recognition, including in the general and powerful kernel density estimation technique. the quadratic computational complexity of the summation is a significant barrier to the scalability of this algorithm to practical applications. the fast gauss transform (fgt) has successfully accelerated the kernel density estimation to linear running time for low-dimensional problems. unfortunately, the cost of a direct extension of the fgt to higher-dimensional problems grows exponentially with dimension, making it impractical for dimensions above 3. we develop an improved fast gauss transform to efficiently estimate sums of gaussians in higher dimensions, where a new multivariate expansion scheme and an adaptive space subdivision technique dramatically improve the performance. the improved fgt has been applied to the mean shift algorithm achieving linear computational complexity. experimental results demonstrate the efficiency and effectiveness of our algorithm.
passive depth from defocus using a spatial domain approach. this paper presents an algorithm for a dense computation of the difference in blur between two images. the two images are acquired by varying the intrinsic parameters of the camera.the image formation system is assumed to be passive. estimation of depth from the blur difference is straigh-forward. the algorithm is based on a local image decomposition technique using the hermite polynomial basis. we show that any coefficient of the hermite polynomial computed using the more blurred image is a function of the partial derivatives of the other image and the blur difference. hence, the blur difference can be computed by resolving a system of equations. all computations required are local and carried out in the spatial domain.an algorithm is presented for estimation of the blur in 1d and 2d cases and its behavior is studied for constant images, step edges, line edges and junctions. the algorithm is tested using synthetic and real images. the results obtained are very encouraging. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
hilbert functions and applications to the estimation of subspace arrangements. this paper develops a new mathematical framework for studying the subspace-segmentation problem. we examine some important algebraic properties of subspace arrangements that are closely related to the subspace-segmentation problem. more specifically, we introduce an important class of invariants given by the hilbert functions. we show that there exist rich relations between subspace arrangements and their corresponding hilbert functions. we propose a new subspace-segmentation algorithm, and showcase two applications to demonstrate how the new theoretical revelation may solve subspace segmentation and model selection problems under less restrictive conditions with improved results.
class-based grouping in perspective images. in any object recognition system a major and primary task is to associate those image features, within an image of a complex scene, that arise from an individual object. the key idea here is that a geometric class defined in 3d induces relationships in the image which must hold between points on the image outline (the perspective projection of the object). the resulting image constraints enable both identification and grouping of image features belonging to objects of that class. the classes include surfaces of revolution, canal surfaces (pipes) and polyhedra. recognition proceeds by first recognising an object as belonging to one of the classes (for example a surface of revolution) and subsequently identifying the object (for example as a particular vase). this differs from conventional object recognition systems where recognition is generally targetted at particular objects. these classes also support the computation of 3d invariant descriptions including symmetry axes, canonical coordinate frames and projective signatures. the constraints and grouping methods are viewpoint invariant, and proceed with no information on object pose. we demonstrate the effectiveness of this class-based grouping on real, cluttered scenes using grouping algorithms developed for rotationally symmetric surfaces, canal-surfaces and polyhedra.
counting people in crowds with a real-time network of simple image sensors. estimating the number of people in a crowded environment is a central task in civilian surveillance. most vision-based counting techniques depend on detecting individuals in order to count, an unrealistic proposition in crowded settings. we propose an alternative approach that directly estimates the number of people. in our system, groups of image sensors segment foreground objects from the background, aggregate the resulting silhouettes over a network, and compute a planar projection of the scene's visual hull. we introduce a geometric algorithm that calculates bounds on the number of persons in each region of the projection, after phantom regions have been eliminated. the computational requirements scale well with the number of sensors and the number of people, and only limited amounts of data are transmitted over the network. because of these properties, our system runs in real-time and can be deployed as an untethered wireless sensor network. we describe the major components of our system, and report preliminary experiments with our first prototype implementation.
consistent segmentation for optical flow estimation. in this paper, we propose a method for jointly computing optical flow and segmentating video while accounting for mixed pixels (matting). our method is based on statistical modeling of an image pair using constraints on appearance and motion. segments are viewed as overlapping regions with fractional (á) contributions. bidirectional motion is estimated based on spatial coherence and similarity of segment colors. our model is extended to video by chaining the pairwise models to produce a joint probability distribution to be maximized. to make the problem more tractable, we factorize the posterior distribution and iteratively minimize its parts. we demonstrate our method on frame interpolation.
schwarz representation for matching and similarity analysis. this paper presents a novel multiscale representation of one-dimensional signal based on complex analysis. we show that a signal and its derivative at different scales can be represented by one analytic function defined on the unit disc in the complex plane, which is called the schwarz representation of a signal. this representation is applied to the matching problem. using the theory of analytic functions, we are able to define the inverse of a signal. the matching function between two signals can be defined as the composition of one signal's schwarz representation and another signal's inverse. the matching function determined bythis method has a group structure and is close-formed.
dealing with textureless regions and specular highlights - a progressive space carving scheme using a novel photo-consistency measure. we present two extensions to the space carving framework. the first is a progressive scheme to better reconstruct surfaces lacking sufficient textures. the second is a novel photo-consistency measure that is valid for both specular and diffuse surfaces, under unknown lighting conditions.
exact eye contact with virtual humans. this paper describes a simple yet effective method for achieving accurate, believable eye contact between humans and computer-generated characters, which to the author's knowledge is demonstrated here for the first time. a prototype system provides a high-fidelity stereoscopic head-tracked virtual environment, within which the user can engage in eye contact with a near-photorealistic virtual human model. the system does not require eye tracking. the paper describes design and implementation details, and reports qualitative positive feedback from initial testers.
geometric segmentation of perspective images based on symmetry groups. symmetry is an effective geometric cue to facilitate conventionalsegmentation techniques on images of man-madeenvironment. based on three fundamental principles thatsummarize the relations between symmetry and perspectiveimaging, namely, structure from symmetry, symmetry hypothesistesting, and global symmetry testing, we developa prototype system which is able to automatically segmentsymmetric objects in space from single 2-d perspective images.the result of such a segmentation is a hierarchy ofgeometric primitives, called symmetry cells and complexes,whose 3-d structure and pose are fully recovered. such ageometrically meaningful segmentation may greatly facilitateapplications such as feature matching and robot navigation.
vision-based projected tabletop interface for finger interactions. we designed and implemented a vision-based projected table-top interface for finger interaction. the system offers a simple and quick setup and economic design. the projection onto the tabletop provides more comfortable and direct viewing for users, and more natural, intuitive yet flexible interaction than classical or tangible interfaces. homography calibration techniques are used to provide geometrically compensated projections on the tabletop. a robust finger tracking algorithm is proposed to enable accurate and efficient interactions using this interface. two applications have been implemented based on this interface.
learning the probability of correspondences without ground truth. we present a quality assessment procedure for correspondence estimation based on geometric coherence rather than ground truth. the procedure can be used for performance evaluation of correspondence extraction schemes developed by researchers, as well as for online learning and adaptation aimed at better system performance. a very important aspect of the proposed procedure is that it considers uncertainty in the correspondence extraction, and encourages the evaluated methods to deal correctly with uncertainty. other important strengths of the procedure are that it does not use any manual work, and that it does not put any strong constraints on the scene, but rather relies on geometric coherence in the motion. thanks to these strengths, it can therefore be used with large amounts of real, potentially application specific data, or even data acquired during system operation. in the evaluation the correspondence extractor is handled as a black box producing a probability distribution for the local motion vector between a pair of image patches. the procedure is therefore quite general. we are making the evaluation procedure available for public use.
combined support vector machines and hidden markov models for modeling facial action temporal dynamics. the analysis of facial expression temporal dynamics is of great importance for many real-world applications. being able to automatically analyse facial muscle actions (action units, aus) in terms of recognising their neutral, onset, apex and offset phases would greatly benefit application areas as diverse as medicine, gaming and security. the base system in this paper uses support vector machines (svms) and a set of simple geometrical features derived from automatically detected and tracked facial feature point data to segment a facial action into its temporal phases. we propose here two methods to improve on this base system in terms of classification accuracy. the first technique describes the original time-independent set of features over a period of time using polynomial parametrisation. the second technique replaces the svm with a hybrid svm/hidden markov model (hmm) classifier to model time in the classifier. our results show that both techniques contribute to an improved classification accuracy. modeling the temporal dynamics by the hybrid svm-hmm classifier attained a statistically significant increase of recall and precision by 4.5% and 7.0%, respectively.
is ica significantly better than pca for face recognition?. the standard pca was always used as baseline algorithm to evaluate ica-based face recognition systems in the previous research. in this paper, we examine the two architectures of ica for image representation and find that ica architecture i involves a pca process by vertically centering (pca i), while ica architecture ii involves a whitened pca process by horizontally centering (pca ii). so, it is reasonable to use these two pca versions as baseline algorithms to revaluate the ica-based face recognition systems. the experiments were performed on the feret face database. the experimental results show there is no significant performance differences between ica architecture i (ii) and pca i (ii), although ica architecture ii significantly outperforms the standard pca. it can be concluded that the performance of ica strongly depends on its involved pca process. the pure ica projection has little effect on the performance of face recognition.
an artificial imagination for interactive search. in this paper we take a look at the predominant form of human computer interaction as used in image retrieval, called interactive search, and discuss a new approach called artificial imagination. this approach addresses two of the grand challenges in this field as identified by the research community: reducing the amount of iterations before the user is satisfied and the small sample problem. artificial imagination will deepen the level of interaction with the user by giving the computer the ability to think along by synthesizing ('imagining') example images that ideally match all or parts of the picture the user has in mind. we discuss two methods of how to synthesize new images, of which the evolutionary synthesis approach receives our main focus.
assessing accuracy factors in deformable 2d/3d medical image registration using a statistical pelvis model. deformable 2d-3d medical image registration is anessential technique in computer integrated surgery (cis)to fuse 3d pre-operative data with 2d intra-operativedata. several factors may affect the accuracy of 2d-3dregistration, including the number of 2d views, the anglebetween views, the view angle relative to anatomical objects,the co-registration error between views, the imagenoise, and the image distortion. in this paper, we investigateand assess the relationship between these factors andthe accuracy of 2d-3d registration. we proposed a deformable2d-3d registration method based on a statisticalmodel. we conducted experiments using a hemi-pelvismodel and simulated x-ray images. some discussions areprovided on how to improve the accuracy of 2d-3d registrationbased on our assessment.
a system for hybrid vision- and sound-based interaction with distal and proximal targets on wall-sized, high-resolution tiled displays. when interacting with wall-sized, high-resolution tiled displays, users typically stand or move in front of it rather than sit at fixed locations. using a mouse to interact can be inconvenient in this context, as it must be carried around and often requires a surface to be used. even for devices that work in mid-air, accuracy when trying to hit small or distal targets becomes an issue. ideally, the user should not need devices to interact with applications on the display wall. we have developed a hybrid vision- and sound-based system for device-free interaction with software running on a 7×4 tile 220-inch display wall. the system comprises three components that together enable interaction with both distal and proximal targets: (i) a camera determines the direction in which a user is pointing, allowing distal targets to be selected. the direction is determined using edge detection followed by applying the hough transform. (ii) using four microphones, a user double-snapping his fingers is detected and located, before the selected target is moved to the location of the snap. this is implemented using correlation and multilateration. (iii) 16 cameras detect objects (fingers, hands) in front of the display wall. the 1d positions of detected objects are then used to triangulate object positions, enabling touch-free multi-point interaction with proximal content. the system is used on the display wall in three contexts to (i) move and interact with windows from a traditional desktop interface, (ii) interact with a whiteboard-style application, and (iii) play two games.
object detection in aerial imagery based on enhanced semi-supervised learning. object detection in aerial imagery has been well studied in computer vision for years. however, given the complexity of large variations of the appearance of the object and the background in a typical aerial image, a robust and efficient detection is still considered as an open and challenging problem. in this paper, we present the enhanced semi-supervised learning (esl) framework and apply this framework to revising an object detection methodology we have developed in a previous effort. theoretic analysis and experimental evaluation using the uci machine learning repository clearly indicate the superiority of the esl framework. the performance evaluations of the revised object detection methodology against the original one clearly demonstrate the promise and superiority of this approach.
interactive feedback for video tracking using a hybrid maximum likelihood similarity measure. in this article, we present an object tracking system which allows interactive user feedback to improve the accuracy of the tracking process in real-time video. in addition, we describe the hybrid maximum likelihood similarity, which integrates traditional metrics with the maximum likelihood estimated metric. the hybrid similarity measure is used to improve the dynamic relevance feedback process between the human user and the objects detected by our system.
automatic generation of robot program code: learning from perceptual data. we propose a novel appr oach to programa robot by demonstrating the task multiple number of times in front of a vision system. here we integrate human dexterity with sensory data using computer vision techniques in a single platform. a simultaneous feature detection and tracking framework is used to track various features (finger tips and the wrist joint). a kalman filter does the tracking by predicting the tentative feature location and a hos-based data clustering algorithm extracts the feature. color information of the features are used for establishing correspondences. a fast, efficient and robust algorithm for the vision system thus developed process a binocular video sequence to obtain the trajectories and the orientation information of the end effector. the concept of a trajectory bundle is introduced to avoid singularities and to obtain an optimal path.
multiple cue integrated action detection. we present an action recognition scheme that integrates multiple modality of cues that include shape, motion and depth to recognize human gesture in the video sequences. in the proposed approach we extend classification framework that is commonly used in 2d object recognition to 3d spatio-temporal space for recognizing actions. specifically, a boosting-based classifier is used that learns spatio-temporal features specific to target actions where features are obtained from temporal patterns of shape contour, optical flow and depth changes occuring at local body parts. the individual features exhibit different strength and sensitivity depending on many factors that include action, underlying body parts and background. in the current method, the multiple cues of different modalities are combined optimally by fisher linear discriminant to form a strong feature that preserve strength of individual cues. in the experiment, we apply the integrated action classifier on a set of target actions and evaluate its performance by comparing with single cue-based cases and present qualitative analysis of performance gain.
conformal metrics and true "gradient flows" for curves. we wish to endow the manifold m of smooth curves in ¿¿ with a riemannian metric that allows us to treat continuous morphs (homotopies) between two curves c¿ and c¿ as trajectories with computable lengths which are independent of the parameterization or representation of the two curves (and the curves making up the morph between them). we may then define the distance between the two curves using the trajectory of minimal length (geodesic) between them, assuming such a minimizing trajectory exists. at first we attempt to utilize the metric structure implied rather unanimously by the past twenty years or so of shape optimization literature in computer vision. this metric arises as the unique metric which validates the common references to a wide variety of contour evolution models in the literature as "gradient flows" to various formulated energy functionals. surprisingly, this implied metric yields a pathological and useless notion of distance between curves. in this paper, we show how this metric can be minimally modified using conformal factors the depend upon a curve¿s total arclength. a nice property of these new conformal metrics is that all active contour models that have been called "gradient flows" in the past will constitute true gradient flows with respect to these new metrics under specfic time reparameterizations.
human-computer intelligent interaction: a survey. human-computer interaction (hci) is one of the foremost challenges of our society. new paradigms for interacting with computers are being developed which will define the 21st century and enable the world to communicate and interact effortlessly and intuitively. in this short survey, we explain the major research clusters comprising the state of the art, and indicate promising future research directions.
stereoscopic segmentation. we cast the problem of multiframe stereo reconstruction of a smooth surface as the global region segmentation of a collection of images of the scene. dually, the problem of segmenting multiple calibrated images of an object becomes that of estimating the solid shape that gives rise to such images. we assume that the radiance of the scene results in piecewise homogeneous image statistics. this simplifying assumption covers lambertian scenes with constant albedo as well as fine homogeneous textures, which are known challenges to stereo algorithms based on local correspondence. we pose the segmentation problem within a variational framework, and use fast level set methods to find the optimal solution numerically. our algorithm does not work in the presence of strong photometric features, where traditional reconstruction algorithms do. it enjoys significant robustness to noise under the assumptiong it is designed for.
non-intrusive physiological monitoring for automated stress detection in human-computer interaction. affective computing, one of the frontiers of human-computer interaction studies, seeks to provide computers with the capability to react appropriately to a user's affective states. in order to achieve the required on-line assessment of those affective states, we propose to extract features from physiological signals from the user (blood volume pulse, galvanic skin response, skin temperature and pupil diameter), which can be processed by learning pattern recognition systems to classify the user's affective state. an initial implementation of our proposed system was set up to address the detection of "stress" states in a computer user. a computer-based "paced stroop test" was designed to act as a stimulus to elicit emotional stress in the subject. signal processing techniques were applied to the physiological signals monitored to extract features used by three learning algorithms: naïve bayes, decision tree and support vector machine to classify relaxed vs. stressed states.
a statistical approach to snakes for bimodal and trimodal imagery. in this paper, we describe a new region-based approach to active contours for segmenting images composed of two or three types of regions characterizable by a given statistic. the essential idea is to derive curve evolutions which separate two or more values of a predetermined set of statistics computed over geometrically determined subsets of the image. both global and local image information is used to evolve the active contour. image derivatives, however, are avoided, thereby giving rise to a further degree of noise robustness compared to most edge-based snake algorithms.
pose and gaze estimation in multi-camera networks for non-restrictive hci. multi-camera networks offer potentials for a variety of novel human-centric applications through provisioning of rich visual information. in this paper, face orientation analysis and posture analysis are combined as components of a human-centered interface systemthat allows the user's intentions and region of interest to be estimated without requiring carried or wearable sensors. in pose estimation, image observations at the cameras are first locally reduced to parametrical descriptions, and particle swarm optimization (pso) is then used for optimization of the kinematics chain of the 3d human model. in face analysis, a discrete-time linear dynamical system (lds), based on kinematics of the head, combines the local estimates of the user's gaze angle produced by the cameras and employs spatiotemporal filters to correct any inconsistencies. knowing the intention and the region of interest of the user facilitates further interpretation of human behavior, which is the key to non-restrictive and intuitive human-centered interfaces. applications in assisted living, speaker tracking, and gaming can benefit from such unobtrusive interfaces.
recognizing human actions in videos acquired by uncalibrated moving cameras. most work in action recognition deals with sequences acquired by stationary cameras with fixed viewpoints. due to the camera motion, the trajectories of the body parts contain not only the motion of the performing actor but also the motion of the camera. in addition to the camera motion, different viewpoints of the same action in different environments result in different trajectories, which can not be matched using standard approaches. in order to handle these problems, we propose to use the multi-view geometry between two actions. however, well known epipolar geometry of the static scenes where the cameras are stationary is not suitable for our task. thus, we propose to extend the standard epipolar geometry to the geometry of dynamic scenes where the cameras are moving. we demonstrate the versatility of the proposed geometric approach for recognition of actions in a number of challenging sequences.
peye: toward a visual motion based perceptual interface for mobile devices. we present the architecture and algorithm design of a visual motion based perceptual interface for mobile devices with cameras. in addition to motion vector, we use the term "visual motion" to be any dynamic changes on consecutive image frames. in the lower architectural hierarchy, visual motion events are defined by identifying distinctive motion patterns. in the higher hierarchy, these visual events are used for interacting with user applications. we present an approach to context aware motion vector estimation to better tradeoff between speed and accuracy. it switches among a set of motion estimation algorithms of different speeds and precisions based on system context such as computation load and battery level. for example, when the cpu is heavily loaded or the battery level is low, we switch to a fast but less accurate algorithm, and vice versa. moreover, to obtain more accurate motion vectors, we propose to adapt the search center of fast block matching methods based on previous motion vectors. both quantitative evaluation of algorithms and subjective usability study are conducted. it is demonstrated that the proposed approach is very robust yet efficient.
reinforcement learning for combining relevance feedback techniques. relevance feedback (rf) is an interactive process which refines the retrievals by utilizing user's feedback history. most researchers strive to develop new rf techniques and ignore the advantages of existing ones. in this paper, we propose an image relevance reinforcement learning (irrl) model for integrating existing rf techniques. various integration schemes are presented and a long-term shared memory is used to exploit the retrieval experience from multiple users. also, a concept digesting method is proposed to reduce the complexity of storage demand. the experimental results manifest that the integration of multiple rf approaches gives better retrieval performance than using one rf technique alone, and that the sharing of relevance knowledge between multiple query sessions also provides significant contributions for improvement. further, the storage demand is significantly reduced by the concept digesting technique. this shows the scalability of the proposed model against a growing-size database.
large lexicon detection of sign language. this paper presents an approach to large lexicon sign recognition that does not require tracking. this overcomes the issues of how to accurately track the hands through self occlusion in unconstrained video, instead opting to take a detection strategy, where patterns of motion are identified. it is demonstrated that detection can be achieved with only minor loss of accuracy compared to a perfectly tracked sequence using coloured gloves. the approach uses two levels of classification. in the first, a set of viseme classifiers detects the presence of sub-sign units of activity. the second level then assembles visemes into word level sign using markov chains. the system is able to cope with a large lexicon and is more expandable than traditional word level approaches. using as few as 5 training examples the proposed system has classification rates as high as 74.3% on a randomly selected 164 sign vocabulary performing at a comparable level to other tracking based systems.
real-time automatic kinematic model building for optical motion capture using a markov random field. we present a completely autonomous algorithm for the real-time creation of a moving subject's kinematic model from optical motion capture data and with no a priori information. our approach solves marker tracking, the building of the kinematic model, and the tracking of the body simultaneously. the novelty lies in doing so through a unifying markov random field framework, which allows the kinematic model to be built incrementally and in real-time. we validate the potential of this method through experiments in which the system is able to accurately track the movement of the human body without an a priori model, as well as through experiments on synthetic data.
catadioptric camera calibration using geometric invariants. central catadioptric cameras are imaging devices thatuse mirrors to enhance the field of view while preservinga single effective viewpoint. in this paper, we propose anovel method for the calibration of central catadioptriccameras using geometric invariants. lines in space areprojected into conics in the catadioptric image plane aswell as spheres in space. we proved that the projection ofa line can provide three invariants whereas the projectionof a sphere can provide two. from these invariants,constraint equations for the intrinsic parameters ofcatadioptric camera are derived. therefore, there are twovariants of this novel method. the first one uses theprojections of lines and the second one uses theprojections of spheres. in general, the projections of twolines or three spheres are sufficient to achieve thecatadioptric camera calibration. one importantobservation in this paper is that the method based on theprojections of spheres is more robust and has higheraccuracy than that using the projections of lines. theperformances of our method are demonstrated by theresults of simulations and experiments with real images.
detecting salient motion by accumulating directionally-consistent flow. motion detection can play an important role in many vision tasks. yet image motion can arise from "uninteresting" events as well as interesting ones. in this paper, salient motion is defined as motion that is likely to result from a typical surveillance target (e.g., a person or vehicle traveling with a sense of direction through a scene) as opposed to other distracting motions (e.g., the scintillation of specularities on water, the oscillation of vegetation in the wind).we propose an algorithm for detecting this salient motion that is based on intermediate-stage vision integration of optical flow. empirical results are presented that illustrate the applicability of the proposed methods to real-world video. unlike many motion detection schemes, no knowledge about expected object size or shape is necessary for rejecting the distracting motion.
linear approaches to camera calibration from sphere images or active intrinsic calibration using vanishing points. spherical objects and vanish points are often used for camera calibration. an occluding contour of a sphere is projected to a conic in the perspective image, and using a moving active camera, the trajectory of a vanishing point in the perspective images is also a conic when the camera is rotated about a fixed 3d axis whereas the translation of the camera is arbitrary. in fact, the problems of camera calibration using conics from spheres or vanishing points can be described by same mathematic representations. two linear approaches to the problems are proposed in this paper: one based on the geometric interpretation of the relation between image conics and the image of the absolute conic, and the other using the special structure of the problems in algebra. only three such conics are needed for the two linear approaches, and the minimum number for previous nonlinear optimization methods is also three. all five intrinsic parameters are recovered linearly without making assumptions, such as, zero-skew or unitary aspect ratio which are often used in previous methods. the two linear algorithms have been tested in extensive experiments with respect to noise sensitivity and also made comparisons with recent calibration techniques.
drowsy driver detection through facial movement analysis. the advance of computing technology has provided the means for building intelligent vehicle systems. drowsy driver detection system is one of the potential applications of intelligent vehicle systems. previous approaches to drowsiness detection primarily make preassumptions about the relevant behavior, focusing on blink rate, eye closure, and yawning. here we employ machine learning to datamine actual human behavior during drowsiness episodes. automatic classifiers for 30 facial actions from the facial action coding system were developed using machine learning on a separate database of spontaneous expressions. these facial actions include blinking and yawn motions, as well as a number of other facial movements. in addition, head motion was collected through automatic eye tracking and an accelerometer. these measures were passed to learning-based classifiers such as adaboost and multinomial ridge regression. the system was able to predict sleep and crash episodes during a driving computer game with 96% accuracy within subjects and above 90% accuracy across subjects. this is the highest prediction rate reported to date for detecting real drowsiness. moreover, the analysis revealed new information about human behavior during drowsy driving.
utilization of stereo disparity and optical flow information for human interaction. to attain smooth human interaction, we propose a system which simultaneously utilizes the stereo disparity and optical flow information of real-time stereo gray multiresolution images to recognize objects and gestures. for real-time calculation of the disparity and optical flow information of a stereo image, the system first creates pyramid images by utilizing a gaussian filter. the system then determines the disparity and optical flow of a low density image and extracts regions in front of a certain depth. the three foremost regions are recognized by higher order local auto-correlation features and a linear discriminant analysis. with this process, the system recognizes the face and hand signs of users, which are displayed foremost, and roughly recognizes novements within the region in real-time. with this framework, the system can discriminate the face of a user, can monitor the basic movements of the user, can smoothly learn a presented object by users, and can communicate with users from hand signs learned in advance.
multiclass spectral clustering. we propose a principled account on multiclass spectral clustering. given a discrete clustering formulation, we first solve a relaxed continuous optimization problem by eigen-decomposition. we clarify the role of eigenvectors as a generator of all optimal solutions through orthonormal transforms. we then solve an optimal discretization problem, which seeks a discrete solution closest to the continuous optima. the discretization is efficiently computed in an iterative fashion using singular value decomposition and non-maximum suppression. the resulting discrete solutions are nearly global-optimal. our method is robust to random initialization and converges faster than other clustering methods. experiments on real image segmentation are reported.
nonparametric modelling and tracking with -gng. in this paper we address the correspondence problem, with its application to nonrigid tracking and unsupervised modelling, as a nonparametric, active-linking topology learning problem. unlike existing soft competitive learning methods, active growing neural gas (a-gng) has both global and local properties which allows part of the network to reconfigure while tracking. in addition, a-gng uses a number of features (e.g. topographic product, local grey-level and map transformation) so that the topological relations are preserved and nodes correspondences are retained between tracked configurations. experimental results in a sequence of hand gestures and artificial data have shown the superiority of our proposed method over the original gng.
visual motion estimation and prediction: a probabilistic network model for temporal coherence. we develop a theory for the temporal integration of visual motion motivated by psychophysical experiments. the theory proposes that input data are temporally grouped and used to predict and estimate motion flows in the image sequences. our theory is expressed in terms of the bayesian generalization [10] of standard kalman filtering which allows us to solve temporal grouping in conjunction with prediction and estimation. as demonstrated for tracking isolated contours [12], the bayesian formulation is superior to approaches which use data association as a first stage followed by conventional kalman filtering. our computer simulations demonstrate that our theory qualitatively accounts for several psychophysical experiments on motion occlusion and motion outliers [15], [20].
signfinder: using color to detect, localize and identify informational signs. we describe an approach to detecting, locating and normalizing road signs. the approach will apply provided: (i) the signs have stereotypical boundary shapes (i.e. rectangular, or hexagonal ¿ of course, we allow for these shapes to be distorted by projection to unknown viewpoint), (ii) the writingon the sign has one uniform color and the rest of the sign has a second uniform color (we allow for the color of the illuminant to be unknown). we show that the approach works even under significant illuminant color changes, viewpoint direction, shadowing, and occlusion. this work is part of a project intended to help people who are blind, or whose sight is impaired.
a unifying approach to hard and probabilistic clustering. we derive the clustering problem from first principles showing that the goal of achieving a probabilistic, or "hard", multi class clustering result is equivalent to the algebraic problem of a completely positive factorization under a doubly stochastic constraint. we show that spectral clustering, normalized cuts, kernel k-means and the various normalizations of the associated affinity matrix are particular instances and approximations of this general principle. we propose an efficient algorithm for achieving a completely positive factorization and extend the basic clustering scheme to situations where partial label information is available.
real time body pose tracking in an immersive training environment. we describe a visual communication application for a dark, theaterlike interactive virtual simulation training environment. our system visually estimates and tracks the body position, orientation and the arm-pointing direction of the trainee. this system uses a near-ir camera array to capture images of the trainee from different angles in the dim-lighted theater. image features like silhouettes and intermediate silhouette body axis points are then segmented and extracted from image backgrounds. 3d body shape information such as 3d body skeleton points and visual hulls can be reconstructed from these 2d features in multiple calibrated images. we proposed a particle-filtering based method that fits an articulated body model to the observed image features. currently we focus on the arm-pointing gesture of either limb. from the fitted articulated model we can derive the position on the screen the user is pointing to. we use current graphic hardware to accelerate the processing speed so the system is able to work in real-time. the system serves as part of multi-modal user-input device in the interactive simulation.
multi-view subspace constraints on homographies. the motion of a planar surface between two camera views induces a homography. the homography depends on the camera intrinsic and extrinsic parameters, as well as on the 3d plane parameters. while camera parameters vary across different views, the plane geometry remains the same. based on this fact, we derive linear subspace constraints on the relative motion of multiple (\math) planes across multiple views.the paper has three main contributions: (i) we show that the collection of all "relative homographies" of a pair of planes (homologies) across multiple views, spans a 4-dimensional linear subspace. (ii) we show how this constraint can be extended to the case of multiple planes across multiple views. (iii) we suggest two potential application areas which can benefit from these constraints: (a) the accuracy of homography estimation can be improved by enforcing the multi-view subspace constraints. (b) violations of these multi-view constraints can be used as a cue for moving object detection. all the results derived in this paper are true for uncalibrated cameras.
image based regression using boosting method. we present a general algorithm of image based regression that is applicable to many vision problems. the proposed regressor that targets a multiple-output setting is learned using boosting method. we formulate a multiple-output regression problem in such a way that overfitting is decreased and an analytic solution is admitted. because we represent the image via a set of highly redundant haar-like features that can be evaluated very quickly and select relevant features through boosting to absorb the knowledge of the training data, during testing we require no storage of the training data and evaluate the regression function almost in no time. we also propose an efficient training algorithm that breaks the computational bottleneck in the greedy feature selection process. we validate the efficiency of the proposed regressor using three challenging tasks of age estimation, tumor detection, and endocardial wall localization and achieve the best performance with a dramatic speed, e.g., more than 1000 times faster than conventional data-driven techniques such as support vector regressor in the experiment of endo-cardial wall localization.
squaring the circles in panoramas. pictures taken by a rotating camera cover the viewing sphere surrounding the center of rotation. having a set of images registered and blended on the sphere what is left to be done, in order to obtain a flat panorama, is projecting the spherical image onto a picture plane. this step is unfortunately not obvious ¿ the surface of the sphere may not be flattened onto a page without some form of distortion. the objective of this paper is discussing the difficulties and opportunities that are connected to the projection from viewing sphere to image plane. we first explore a number of alternatives to the commonly used linear perspective projection. these are ¿global¿ projections and do not depend on image content. we then show that multiple projections may coexist successfully in the same mosaic: these projections are chosen locally and depend on what is present in the pictures. we show that such multi-view projections can produce more compelling results than the global projections.
progressive surface reconstruction from images using a local prior. this paper introduces a new method for surface reconstruction from multiple calibrated images. the primary contribution of this work is the notion of local prior to combine the flexibility of the carving approach with the accuracy of graph-cut optimization. a progressive refinement scheme is used to recover the topology and reason the visibility of the object. within each voxel, a detailed surface patch is optimally reconstructed using a graph-cut method. the advantage of this technique is its ability to handle complex shape similarly to level sets while enjoying a higher precision. compared to carving techniques, the addressed problem is well-posed, and the produced surface does not suffer from aliasing. in addition, our approach seamlessly handles complete and partial reconstructions: if the scene is only partially visible, the process naturally produces an open surface; otherwise, if the scene is fully visible, it creates a complete shape. these properties are demonstrated on real image sequences.
a general framework for temporal video scene segmentation. videos are composed of many shots caused by different camera operations, e.g., on/off operations and switching between cameras. one important goal in video analysis is to group the shots into temporal scenes, such that all the shots in a single scene are related to a particular physical setting, an on-going action or a theme. in this paper, we present a general framework for temporal scene segmentation for various video types. the proposed method is formulated in a statistical fashion and uses the markov chain monte carlo (mcmc) technique to determine the boundaries between video scenes. in this approach, an arbitrary number of scene boundaries are randomly initialized and automatically updated using two types of updates: diffuse and jumps. the posterior probability on the number of scenes and their boundary locations is computed based on the model priors and the data likelihood. the updates of the model parameters are controlled by the hypothesis ratio test in the mcmc process. the proposed framework has been experimented on two types of videos, home videos and feature films, and accurate results have been obtained.
estimating motion and structure from correspondences of line segments between two perspective images. presents an algorithm for determining 3d motion and structure from correspondences of line segments between two perspective images. to our knowledge, the paper is the first investigation of use of line segments in motion and structure from motion. classical methods use their geometric abstraction, namely straight lines, but then three images are necessary for the motion and structure determination process. we show that two views are in general sufficient when we use line segments. the assumption we use is that two matched line segments contain the projection of a common part of the corresponding line segment in space. indeed this is what we use to match line segments between different views. both synthetic and real data have been used to test the proposed algorithm, and excellent results have been obtained with real data containing a relatively large set of line segments. the results are comparable with those obtained using stereo calibration.
understanding the relationship between the optimization criteria in two-view motion analysis. the three best known criteria in two-view motion analysis are based, respectively, on the distances between points and their corresponding epipolar lines, on the gradient-weighted epipolar errors, and on the distances between points and the reprojections of their reconstructed points. the last one has a better statistical interpretation, but is, however, much slower than the first two. in this paper, we show that the last two criteria are equivalent when the epipoles are at infinity, and differ from each other only a little even when the epipoles are in the image. the first two criteria are equivalent only when the epipoles are at infinity and when the observed object has the same scale in the two images. this suggests that the second criterion is sufficient in practice because of its computational efficiency. the resultis valid for both calibrated and uncalibrated images.
modeling geometric structure and illumination variation of a scene from real images. we present in this paper a system which automatically builds, from real images, a scene model containing both 3d geometric information of the scene structure and its photometric information under various illumination conditions. the geometric structure is recovered from images taken from distinct viewpoints. structure-from-motion and correlation-based stereo techniques are used to match pixels between images of different viewpoints and to reconstruct the scene in 3d space. the photometric property is extracted from images taken under different illumination conditions (orientation, position and intensity of the light sources). this is achieved by computing a low-dimensional linear space of the spatio-illumination volume, and is represented by a set of basis images. the model that has been built can be used to create realistic renderings from different viewpoints and illumination conditions. applications include object recognition, virtual reality and product advertisement.
shape and motion under varying illumination: unifying structure from motion, photometric stereo, and multi-view stereo. this paper presents an algorithm for computing optical flow,shape, motion, lighting, and albedo from an image sequenceof a rigidly-moving lambertian object under distant illumination.the problem is formulated in a manner that subsumesstructure from motion, multi-view stereo, and photometricstereo as special cases. the algorithm utilizes bothspatial and temporal intensity variation as cues: the formerconstrains flow and the latter constrains surface orientation;combining both cues enables dense reconstruction ofboth textured and texture-less surfaces. the algorithm worksby iteratively estimating affine camera parameters, illumination,shape, and albedo in an alternating fashion. results aredemonstrated on videos of hand-held objects moving in frontof a fixed light and camera.
bayesian body localization using mixture of nonlinear shape models. we present a 2dmodel-based approach to localizing human body in images viewed from arbitrary and unknown angles. the central component is a statistical shape representation of the nonrigid and articulated body contours, where a non-linear deformation is decomposed based on the concept of parts. several image cues are combined to relate the body configuration to the observed image, with self-occlusion explicitly treated. to accommodate large viewpoint changes, a mixture of view-dependent models is employed. inference is done by direct sampling of the posterior mixture, using sequential monte carlo (smc) simulation enhanced with annealing and kernel move. the fitting method is independent of the number of mixture components, and does not require the preselection of a "correct" viewpoint. the models were trained on a large number of interactively labeled gait images. preliminary tests demonstrated the feasibility of the proposed approach.
tracking objects using density matching and shape priors. we present a novel method for tracking objects by combiningdensity matching with shape priors. density matchingis a tracking method which operates by maximizing thebhattacharyya similarity measure between the photometricdistribution from an estimated image region and a modelphotometric distribution. such trackers can be expressed aspde-based curve evolutions, which can be implemented usinglevel sets. shape priors can be combined with this level-setimplementation of density matching by representing theshape priors as a series of level sets; a variational approachallows for a natural, parametrization-independentshape term to be derived. experimental results on real imagesequences are shown.
euclidean structure from uncalibrated images using fuzzy domain knowledge: application to facial images synthesis. use of uncalibrated images has found many applications such as image synthesis. however, it is not easy to specify the desired position of the new image in projective or af.ne space. this paper proposes to recover euclidean structure from uncalibrated images using domain knowledge such as distances and angles. the knowledge we have is usually about an object category, but not very precise for the particular object being considered. the variation (fuzziness) is modeled as a gaussian variable. six types of common knowledge are formulated. once we have a euclidean description, the task to specify the desired position in euclidean space becomes trivial. the proposed technique is then applied to synthesis of new facial images. a number of dif.culties existing in image synthesis are identified and solved. for example, we propose to use edge points to deal with occlusion.
facial expression understanding in image sequences using dynamic and active visual information fusion. this paper explores the use of multisensory information fusiontechnique with dynamic bayesian networks (dbns)for modeling and understanding the temporal behaviors offacial expressions in image sequences. our approach tothe facial expression understanding lies in a probabilisticframework by integrating the dbns with the facial actionunits (aus) from psychological view. the dbns provide acoherent and unified hierarchical probabilistic frameworkto represent spatial and temporal information related to facialexpressions, and to actively select the most informativevisual cues from the available information to minimize theambiguity in recognition. the recognition of facial expressionsis accomplished by fusing not only from the currentvisual observations, but also from the previous visual evidences.consequently, the recognition becomes more robustand accurate through modeling the temporal behavior of facialexpressions. experimental results demonstrate that ourapproach is more admissible for facial expression analysisin image sequences.
local gabor binary pattern histogram sequence (lgbphs): a novel non-statistical model for face representation and recognition. for years, researchers in face recognition area have been representing and recognizing faces based on subspace discriminant analysis or statistical learning. nevertheless, these approaches are always suffering from the generalizability problem. this paper proposes a novel non-statistics based face representation approach, local gabor binary pattern histogram sequence (lgbphs), in which training procedure is unnecessary to construct the face model, so that the generalizability problem is naturally avoided. in this approach, a face image is modeled as a "histogram sequence" by concatenating the histograms of all the local regions of all the local gabor magnitude binary pattern maps. for recognition, histogram intersection is used to measure the similarity of different lgbphses and the nearest neighborhood is exploited for final classification. additionally, we have further proposed to assign different weights for each histogram piece when measuring two lgbphses. our experimental results on ar and feret face database show the validity of the proposed approach especially for partially occluded face images, and more impressively, we have achieved the best result on feret face database.
a probabilistic semantic model for image annotation and multi-modal image retrieva. this paper addresses automatic image annotation problem and its application to multi-modal image retrieval. the contribution of our work is three-fold. (1) we propose a probabilistic semantic model in which the visual features and the textual words are connected via a hidden layer which constitutes the semantic concepts to be discovered to explicitly exploit the synergy among the modalities. (2) the association of visual features and textual words is determined in a bayesian framework such that the confidence of the association can be provided. (3) extensive evaluation on a large-scale, visually and semantically diverse image collection crawled from web is reported to evaluate the prototype system based on the model. in the proposed probabilistic model, a hidden concept layer which connects the visual feature and the word layer is discovered by fitting a generative model to the training image and annotation words through an expectation-maximization (em) based iterative learning procedure. the evaluation of the prototype system on 17,000 images and 7,736 automatically extracted annotation words from crawled web pages for multi-modal image retrieval has indicated that the proposed semantic model and the developed bayesian framework are superior to a state-of-the-art peer system in the literature.
closely coupled object detection and segmentation. we propose a closely coupled object detection and segmentation algorithm for enhancing both processes in a cooperative and iterative manner. figure-ground segmentation reduces the effect of background clutter on template matching; the matched template provides shape constraints on segmentation. more precisely, we estimate the probability of each pixel belonging to the foreground by a weighted sum of the estimates based on shape and color alone. the weight on the shape-based estimate is related to the probability that a familiar object is present and is updated dynamically so that we enforce shape constraints only where the object is present. experiments on detecting people in images of cluttered scenes demonstrate that the proposed algorithm improves both segmentation and detection. more accurate object boundaries are extracted; higher object detection rates and lower false alarm rates are achieved than performing the two processes separately or sequentially.
robust point matching for two-dimensional nonrigid shapes. recently, nonrigid shape matching has received more and more attention. for nonrigid shapes, most neighboring points cannot mow independently under deformation due to physical constraints. furthermore, the rough structure of a shape should be preserved under deformation, otherwise even people cannot match shapes reliably. therefore, though the absolute distance between two points may change sign@cantl>;, the neighborhood of a point is well preserved in general. based on this observation, we formulate point matching as a graph matching problem. each point is a node in the graph, and two nodes are connected by an edge if their euclidean distance is less than a threshold. the optimal match between two graphs is the one that maximizes the number of matched edges. the shape context distance is used to initialize the graph matching, followed by relaxation labeling for rejnement. nonrigid deformation is overcome by bringing one shape closer 10 the other in each iteration using deformation parameters estimated from the current point correspondence. experiments demonstrate the effectiveness of our approach: it outperforms the shape context and tps-rpm algorithms under nonrigid deformation and noise on a public data set.
shape and model from specular motion. this work investigates visual characteristics of specular surfaces during rotation, and gives approaches to qualitatively identify and quantitatively recover shapes of these surfaces. continuous images are taken when an object rotates. we look at specularly reflected patterns on the surfaces and their motion in the epis parallel to the rotation plane, from which estimation of each surface point and construction of the object model are carried out. we find very simple and direct methods to fulfill this objective; linear equations for multiple lights illumination, and a 1st-order differential equation for single light illumination. the motion of specular reflection has nice global characteristics in epi. the surface types range from very shiny metal surfaces to surfaces with only week specular reflectance. we give both simulation and experiments on real objects.
acquiring 3d object models from specular motion using circular lights illumination. this work recovers 3d graphics models of objects with specular surfaces. an object is routed and continuous images of it are taken. circular lights that generate cones of rays are used to illuminate the rotating object. when the lights are properly set, each point on the object can be highlighted during the rotation. the shape for each rotational plane is measured independently using its corresponding epipolar palne image. a 3d graphics model is subsequently reconstructed by combining shapes at different rotational planes. computing a shape is simple and requires only the motion of the highlight on each rotation plane. results not obtained before are given in the 3d shape recovery experiments on real objects.
object tracking using deformable templates. we propose a novel method for object tracking using prototype-based deformable template models. to track an object in an image sequence, we use a criterion which combines two terms: the deviation of the object shape from its shape in the previous frame, and the fidelity ofthe detected shape to the input image. shape and gradient information are used to track the object. we have also used the consistency between corresponding object regions throughout the sequence to help in tracking the object of interest. inter-frame motion is also used to track the boundary of moving objects. we have applied the algorithm to a number of image sequences from different sources. the inherent structure in the deformable template, together with region, motion, and image gradient cues, make the algorithm relatively insensitive to the adverse effects of weak image features and moderate partial occlusion.
segmenting foreground objects from a dynamic textured background via a robust kalman filter. the algorithm presented in this paper aims to segment the foreground objects in video (e.g., people) given time-varying, textured backgrounds. examples of time-varying backgrounds include waves on water, clouds moving, trees waving in the wind, automobile traffic, moving crowds, escalators, etc. we have developed a novel foreground-background segmentation algorithm that explicitly accounts for the non-stationary nature and clutter-like appearance of many dynamic textures. the dynamic texture is modeled byan autoregressive moving average model (arma). a robust kalman filter algorithm iteratively estimates the intrinsic appearance of the dynamic texture, as well as the regions of the foreground objects. preliminary experiments with this method have demonstrated promising results.
conditional feature sensitivity: a unifying view on active recognition and feature selection. the objective of active recognition is to iteratively collectthe next "best" measurements (e.g., camera angles orviewpoints), to maximally reduce ambiguities in recognition.however, existing work largely overlooked featureinteraction issues. feature selection, on the other hand,focuses on the selection of a subset of measurements for agiven classification task, but is not context sensitive (i.e.,the decision does not depend on the current input). thispaper proposes a unified perspective through conditionalfeature sensitivity analysis, taking into account both currentcontext and feature interactions. based on differentrepresentations of the contextual uncertainties, we presentthree treatment models and exploit their joint power fordealing with complex feature interactions. synthetic examplesare used to systematically test the validity of theproposed models. a practical application in medical domainis illustrated using an echocardiography databasewith more than 2000 video segments with both subjective(from experts) and objective validations.
robust estimation of albedo for illumination-invariant matching and shape recovery. we present a nonstationary stochastic filtering framework for the task of albedo estimation from a single image. there are several approaches in the literature for albedo estimation, but few include the errors in estimates of surface normals and light source direction to improve the albedo estimate. the proposed approach effectively utilizes the error statistics of surface normals and illumination direction for robust estimation of albedo, for images illuminated by single and multiple light sources. the albedo estimate obtained is subsequently used to generate albedo-free normalized images for recovering the shape of an object. traditional shape-from-shading (sfs) approaches often assume constant/piecewise constant albedo and known light source direction to recover the underlying shape. using the estimated albedo, the general problem of estimating the shape of an object with varying albedo map and unknown illumination source is reduced to one that can be handled by traditional sfs approaches. experimental results are provided to show the effectiveness of the approach and its application to illumination-invariant matching and shape recovery. the estimated albedo maps are compared with the ground truth. the maps are used as illumination-invariant signatures for the task of face recognition across illumination variations. the recognition results obtained compare well with the current state-of-the-art approaches. impressive shape recovery results are obtained using images downloaded from the web with little control over imaging conditions. the recovered shapes are also used to synthesize novel views under novel illumination conditions.
rectified surface mosaics. we approach mosaicing as a camera tracking problem within a known parameterized surface. from a video of a camera moving within a surface, we compute a mosaic representing the texture of that surface, flattened onto a planar image. our approach works by defining a warp between images as a function of surface geometry and camera pose. globally optimizing this warp to maximize alignment across all frames determines the camera trajectory, and the corresponding flattened mosaic image. in contrast to previous mosaicing methods which assume planar or distant scenes, or controlled camera motion, our approach enables mosaicing in cases where the camera moves unpredictably through proximal surfaces, such as in medical endoscopy applications.
efficient generic calibration method for general cameras with single centre of projection. generic camera calibration is a non-parametric calibration technique that is applicable to any type of vision sensor. however, the standard generic calibration method was developed such that both central and non-central cameras can be calibrated within the same framework. consequently, existing parametric calibration techniques cannot be applied for the common case of cameras with a single centre of projection (e.g. pinhole, fisheye, hyperboloidal catadioptric). this paper proposes improvements to the standard generic calibration method for central cameras that reduce its complexity, and improve its accuracy and robustness. improvements are achieved by taking advantage of the geometric constraints resulting from a single centre of projection in order to enable the application of established pinhole calibration techniques. input data for the algorithm is acquired using active grids, the performance of which is characterised. a novel linear estimation stage is proposed that enables a well established pinhole calibration technique to be used to estimate the camera centre and initial grid poses. the proposed solution is shown to be more accurate than the linear estimation stage of the standard method. a linear alternative to the existing polynomial method for estimating the pose of additional grids used in the calibration is demonstrated and evaluated. distortion correction experiments are conducted with real data for both an omnidirectional camera and a fisheye camera using the standard and proposed methods. motion reconstruction experiments are also undertaken for the omnidirectional camera. results show the accuracy and robustness of the proposed method to be improved over those of the standard method.
population shape regression from random design data. regression analysis is a powerful tool for the study of changes in a dependent variable as a function of an independent regressor variable, and in particular it is applicable to the study of anatomical growth and shape change. when the underlying process can be modeled by parameters in a euclidean space, classical regression techniques (hardle, applied nonparametric regression, 1990; wand and jones, kernel smoothing, 1995) are applicable and have been studied extensively. however, recent work suggests that attempts to describe anatomical shapes using flat euclidean spaces undermines our ability to represent natural biological variability (fletcher et al., ieee trans. med. imaging 23(8), 995---1005, 2004; grenander and miller, q. appl. math. 56(4), 617---694, 1998).in this paper we develop a method for regression analysis of general, manifold-valued data. specifically, we extend nadaraya-watson kernel regression by recasting the regression problem in terms of fréchet expectation. although this method is quite general, our driving problem is the study anatomical shape change as a function of age from random design image data.we demonstrate our method by analyzing shape change in the brain from a random design dataset of mr images of 97 healthy adults ranging in age from 20 to 79 years. to study the small scale changes in anatomy, we use the infinite dimensional manifold of diffeomorphic transformations, with an associated metric. we regress a representative anatomical shape, as a function of age, from this population.
limits of learning-based superresolution algorithms. learning-based superresolution (sr) is a popular sr technique that uses application dependent priors to infer the missing details in low resolution images (lris). however, their performance still deteriorates quickly when the magnification factor is only moderately large. this leads us to an important problem: "do limits of learning-based sr algorithms exist?" this paper is the first attempt to shed some light on this problem when the sr algorithms are designed for general natural images. we first define an expected risk for the sr algorithms that is based on the root mean squared error between the superresolved images and the ground truth images. then utilizing the statistics of general natural images, we derive a closed form estimate of the lower bound of the expected risk. the lower bound only involves the covariance matrix and the mean vector of the high resolution images (hris) and hence can be computed by sampling real images. we also investigate the sufficient number of samples to guarantee an accurate estimate of the lower bound. by computing the curve of the lower bound w.r.t. the magnification factor, we could estimate the limits of learning-based sr algorithms, at which the lower bound of the expected risk exceeds a relatively large threshold. we perform experiments to validate our theory. and based on our observations we conjecture that the limits may be independent of the size of either the lris or the hris.
estimation of the epipole using optical flow at antipodal points. we present algorithms for estimating the epipole or direction of translation of a moving camera. we use constraints arising from two points that are antipodal on the image sphere in order to decouple rotation from translation. one pair of antipodal points constrains the epipole to lie on a plane, and two such pairs will correspondingly give two planes. the intersection of these two planes is an estimate of the epipole. this means we require image motion measurements at two pairs of antipodal points to obtain an estimate. two classes of algorithms are possible and we present two simple yet extremely robust algorithms representative of each class. these are shown to have comparable accuracy with the state of the art when tested in simulation under noise and with real image sequences.
hierarchical ensemble of global and local classifiers for face recognition. in the literature of psychophysics and neurophysiology, many studies have shown that both global and local features are crucial for face representation and recognition. this paper proposes a novel face recognition method which exploits both global and local discriminative features. in this method, global features are extracted from the whole face images by keeping the low-frequency coefficients of fourier transform, which we believe encodes the holistic facial information, such as facial contour. for local feature extraction, gabor wavelets are exploited considering their biological relevance. after that, fisher's linear discriminant (fld) is separately applied to the global fourier features and each local patch of gabor features. thus, multiple fld classifiers are obtained, each embodying different facial evidences for face recognition. finally, all these classifiers are combined to form a hierarchical ensemble classifier. we evaluate the proposed method using two large-scale face databases: feret and frgc version 2.0. experiments show that the results of our method are impressively better than the best known results with the same evaluation protocol.
unsupervised clustering of symbol strings and context recognition. the representation of information based on symbolstrings has been applied to the recognition of context. aframework for approaching the context recognition problemhas been described and interpreted in terms of symbolstring recognition. the symbol string clustering map(scm) is introduced as an efficient algorithm for the unsupervisedclustering and recognition of symbol string data.the scm can be implemented in an on line manner usinga computationally simple similarity measure based ona weighted average. it is shown how measured sensor datacan be processed by the scm algorithm to learn, representand distinguish different user contexts without any user input.
a thorough experimental study of datasets for frequent itemsets. the discovery of frequent patterns is a famous problem in data mining. while plenty of algorithms have been proposed during the last decade, only a few contributions have tried to understand the influence of datasets on the algorithms behavior. being able to explain why certain algorithms are likely to perform very well or very poorly on some datasets is still an open question. in this setting, we describe a thorough experimental study of datasets with respect to frequent itemsets. we study the distribution of frequent itemsets with respect to itemsets size together with the distribution of three concise representations: frequent closed, frequent free and frequent essential itemsets. for each of them, we also study the distribution of their positive and negative borders whenever possible. from this analysis, we exhibit a new characterization of datasets and some invariants allowing to better predict the behavior of well known algorithms. the main perspective of this work is to devise adaptive algorithms with respect to dataset characteristics.
mining online users? access records for web business intelligence. this paper discusses about how business intelligence on awebsite could be obtained from users' access recordsinstead of web logs of "hits". users' access records arecaptured by implementing an access-control (ac)architectural model on the website. this model requiresusers to register their profiles in an exchange of apassword; and thereafter they have to login before gainingaccess to certain resources on the website. the links tothe resources on the website have been modified such thata record of information about the access would berecorded in the database when clicked. this way, data-miningcan be performed on a relatively clean set ofaccess records about the users. hence, a good deal ofbusiness intelligence about the users' behaviors,preferences and about the popularities of the resources(products) on the website can be gained. in this paper, wealso discussed how the business intelligence acquired, inturn, can be used to provide e-crm for the users.
a parameterless method for efficiently discovering clusters of arbitrary shape in large datasets. clustering is the problem of grouping data based on similarityand consists of maximizing the intra-group similaritywhile minimizing the inter-group similarity. the problem ofclustering data sets is also known as unsupervised classification,since no class labels are given. however, all exist-ingclustering algorithms require some parameters to steerthe clustering process, such as the famous k for the numberof expected clusters, which constitutes a supervision ofa sort. we present in this paper a new, efficient, fast andscalable clustering algorithm that clusters over a range ofresolutions and finds a potential optimum clustering withoutrequiring any parameter input. our experiments showthat our algorithm outperforms most existing clustering algorithmsin quality and speed for large data sets.
links between kleinberg's hubs and authorities, correspondence analysis, and markov chains. in this work, we show that kleinberg's hubs and authoritiesmodel is closely related to both correspondence analysis,a well-known multivariate statistical technique, and aparticular markov chain model of navigation through theweb. the only difference between correspondence analysisand kleinberg's method is the use of the average value ofthe hubs (authorities) scores for computing the authorities(hubs) scores, instead of the sum for kleinberg's method.we also show that correspondence analysis and our markovmodel are related to salsa, a variant of kleinberg's model.
test-cost sensitive naive bayes classification. inductive learning techniques such as the naive bayes and decision tree algorithms have been extended in the past to handle different types of costs mainly by distinguishing different costs of classification errors. however, it is an equally important issue to consider how to handle the test costs associated with querying the missing values in a test case. when the value of an attribute is missing in a test case, it may or may not be worthwhile to take the effort to obtain its missing value, depending on how much the value will result in a potential gain in the classification accuracy. in this paper, we show how to obtain a test-cost sensitive naive bayes classifier (csnb) by including a test strategy which determines how unknown attributes are selected to perform test on in order to minimize the sum of the mis-classification costs and test costs. we propose and evaluate several potential test strategies including one that allows several tests to be done at once. we empirically evaluate the csnb method, and show that it compares favorably with its decision tree counterpart.
empirical comparison of various reinforcement learning strategies for sequential targeted marketing. we empirically evaluate the performance of various re-inforcementlearning methods in applications to sequentialtargeted marketing. in particular, we propose and evaluatea progression of reinforcement learning methods, rangingfrom the "direct" or "batch" methods to "indirect" or"simulation based" methods, and those that we call "semi-direct"methods that fall between them. we conduct a num-berof controlled experiments to evaluate the performanceof these competing methods. our results indicate that whilethe indirect methods can perform better in a situation inwhich nearly perfect modeling is possible, under the morerealistic situations in which the system's modeling parametershave restricted attention, the indirect methods' performancetend to degrade. we also show that semi-directmethods are effective in reducing the amount of computationnecessary to attain a given level of performance, andoften result in more profitable policies.
modeling multiple time series for anomaly detection. our goal is to generate comprehensible and accurate models from multiple time series for anomaly detection. the models need to produce anomaly scores in an online manner for real-life monitoring tasks. we introduce three algorithms that work in a constructed feature space and evaluate them with a real data set from the nasa shuttle program. our offline and online evaluations indicate that our algorithms can be more accurate than two existing algorithms.
a rule evaluation support method with learning models based on objective rule evaluation indexes. in this paper, we present a novel rule evaluation support method for post-processing of mined results with rule evaluation models based on objective indexes. post-processing of mined results is one of the key issues to make a data mining process successfully. however, it is difficult for human experts to evaluate many thousands of rules from a large dataset with noises completely. to reduce the costs of rule evaluation procedures, we have developed the rule evaluation support method with rule evaluation models, which are obtained with objective rule evaluation indexes and evaluations of a human expert for each rule. since the method is needed more accurate rule evaluation models, we have compared learning algorithms to construct rule evaluation models with the actual meningitis data mining result and actual rule sets from uci datasets. then we show the availability of our adaptive rule evaluation support method.
mining high utility itemsets. traditional association rule mining algorithms onlygenerate a large number of highly frequent rules, butthese rules do not provide useful answers for what thehigh utility rules are. in this work, we develop a novelidea of top-k objective-directed data mining, which focuseson mining the top-k high utility closed patterns thatdirectly support a given business objective. to associationmining, we add the concept of utility to capture highly desirablestatistical patterns and present a level-wise item-setmining algorithm. with both positive and negativeutilities, the anti-monotone pruning strategy in apriorialgorithm no longer holds. in response, we develop a newpruning strategy based on utilities that allow pruning oflow utility itemsets to be done by means of a weaker butanti-monotonic condition. our experimental results showthat our algorithm does not require a user specifiedminimum utility and hence is effective in practice.
investigative profiling with computer forensic log data and association rules. investigative profiling is an important activity in computerforensics that can narrow the search for one or morecomputer perpetrators. data mining is a technique that hasproduced good results in providing insight into large volumesof data. this paper describes how the associationrule data mining technique may be employed to generateprofiles from log data and the methodology used for the interpretationof the resulting rule sets. the process relies onbackground knowledge in the form of concept hierarchiesand beliefs, commonly available from, or attainable by, thecomputer forensic investigative team. results obtained withthe profiling system has identified irregularities in computerlogs.
distributed web mining using bayesian networks from multiple data streams. we present a collective approach to mine bayesian net-works from distributed heterogenous web-log data streams. in this approach we first learn a local bayesian network at each site using the local data. then each site identifies the observations that are most likely to be evidence of coupling between local and non-local variables and transmits asub-set of these observations to a central site. another bayesian network is learnt at the central site using the data transmittedfrom the local site. the local and central bayesian networks are combined to obtain a collective bayesian net-work, that models the entire data. we applied this techniqueto mine multiple data streams where data centralization is difficult because of large response time and scalability issues.experimental results and theoretical justification that demonstrate the feasibility of our approach are presented.
handling generalized cost functions in the partitioning optimization problem through sequential binary programming. this paper proposes a framework for cost-sensitive classification under a generalized cost function. by combining decision trees with sequential binary programming, we can handle unequal misclassification costs, constrained classification, and complex objective functions that other methods cannot. our approach has two main contributions. first, it provides a new method for cost-sensitive classification that outperforms a traditional, accuracy-based method and some current cost-sensitive approaches. second, and more important, our approach can handle a generalized cost function, instead of the simpler misclassification cost matrix to which other approaches are limited.
learning with progressive transductive support vector machine. support vector machine (svm) is a new learningmethod developed in recent years based on thefoundations of statistical learning theory. by taking atransductive approach instead of an inductive one insupport vector classifiers, the test set can be used as anadditional source of information about margins. intuitively,we would expect transductive learning to yieldimprovements when the training sets are small or whenthere is a significant deviation between the training andworking set subsamples of the total population. in thispaper, a progressive transductive support vector machineis addressed to extend joachims' transductive svm tohandle different class distributions. it solves the problemof having to estimate the ratio of positive/negativeexamples from the working set. the experimental resultsshow that the algorithm is very promising.
online hierarchical clustering in a data warehouse environment. many important industrial applications rely on data mining methods to uncover patterns and trends in large data warehouse environments. since a data warehouse is typically updated periodically in a batch mode, the mined patterns have to be updated as well. this requires not only accuracy from data mining methods but also fast availability of up-to-date knowledge, particularly in the presence of a heavy update load. to cope with this problem, we propose the use of online data mining algorithms which permanently store the discovered knowledge in suitable data structures and enable an efficient adaptation of these structures after insertions and deletions on the raw data. in this paper, we demonstrate how hierarchical clustering methods can be reformulated as online algorithms based on the hierarchical clustering method optics, using a density estimator for data grouping. we also discuss how this algorithmic schema can be specialized for efficient online single-link clustering. a broad experimental evaluation demonstrates that the efficiency is superior with significant speed-up factors even for large bulk insertions and deletions.
sequential pattern mining in multiple streams. in this paper, we deal with mining sequential patterns in multiple data streams. building on a state-of-the-art sequential pattern mining algorithm prefixspan for mining transaction databases, we propose mile¹, an efficient algorithm to facilitate the mining process. mile recursively utilizes the knowledge of existing patterns to avoid redundant data scanning, and can therefore effectively speed up the new patterns' discovery process. another unique feature of mile is that it can incorporate some prior knowledge of the data distribution in data streams into the mining process to further improve the performance. extensive empirical results show thatmile is significantly faster than prefixspan. as mile consumes more memory than prefixspan, we also present a solution to balance the memory usage and time efficiency in memory constrained environments.
emailsift: email classification based on structure and content. in this paper we propose a novel approach that uses structure as well as the content of emails in a folder for email classification. our approach is based on the premise that representative — common and recurring — structures/patterns can be extracted from a pre-classified email folder and the same can be used effectively for classifying incoming emails. a number of factors that influence representative structure extraction and the classification are analyzed conceptually and validated experimentally. in our approach, the notion of inexact graph match is leveraged for deriving structures that provide coverage for characterizing folder contents. extensive experimentation validate the selection of parameters and the effectiveness of our approach for email classification.
incremental mining of frequent xml query pattern. recently, the discovering of frequent xml query patterns gains its focus due to its many applications in xml data management, and several algorithms have been proposed to discover frequent query patterns using the frequent structure mining techniques. in this paper we consider the problem of incremental mining of frequent xml query patterns. we propose a novel method to minimize the i/o and computation requirements for handling incremental updates.
mining chains of relations. traditional data mining applications consider the problem of mining a single relation between two attributes. for example, in a scientific bibliography database, authors are related to papers, and we may be interested in discovering association rules between authors. however, in real life, we often have multiple attributes related though chains of relations. for example, authors write papers, and papers concern one or more topics. mining such relational chains poses additional challenges. in this paper we consider the following problem: given a chain of two relationsr₁(a, p) and r₂(p, t) we want to find selectors for the objects in t such that the projected relation between a and p satisfies a specific property. the motivation for our approach is that a given property might not hold on the whole dataset, but it might hold when projecting the data on a selector set. we discuss various algorithms and we examine the conditions under which the apriori technique can be used. we experimentally demonstrate the effectiveness of our methods.
a hypergraph based clustering algorithm for spatial data sets. clustering is a discovery process in data mining an can be used to group together the objects of a database into meaningful subclasses which serve as the foundation for other data analysis techniques.in this paper, we focus on dealing with a set of spatial data. for the spatial data, the clustering problem becomes that of finding the densely populate regions of the space and thus grouping these regions into clusters such that the intracluster similarity is maximized and theintercluster similarity is minimized. we develop a novel hierarchical clustering algorithm that uses a hypergraph to represent a set of spatial data. this hypergraph is initially constructed from the delaunay triangulation graph of the data set and can correctly capture the relationships among sets of data points. two phases are developed for the proposed clustering algorithm to find the clusters in the data set.we evaluate our hierarchical clustering algorithm with some spatial data sets in which contain clusters of different sizes, shapes, densities, and noise. experimental results on these data sets are very encouraging.
an empirical bayes approach to detect anomalies in dynamic multidimensional arrays. we consider the problem of detecting anomalies in data that arise as multidimensional arrays with each dimension corresponding to the levels of a categorical variable. in typical data mining applications, the number of cells in such arrays are usually large. our primary focus is detecting anomalies by comparing information at the current time to historical data. naive approaches advocated in the process control literature do not work well in this scenario due to the multiple testing problem - performing multiple statistical tests on the same data produce excessive number of false positives. we use an empirical bayes method which works by fitting a two component gaussian mixture to deviations at current time. the approach is scalable to problems that involve monitoring massive number of cells and fast enough to be potentially useful in many streaming scenarios. we show the superiority of the method relative to a naive "per component error rate" procedure through simulation. a novel feature of our technique is the ability to suppress deviations that are merely the consequence of sharp changes in the marginal distributions. this research was motivated by the need to extract critical application information and business intelligence from the daily logs that accompany large-scale spoken dialog systems deployed by at&t. we illustrate our method on one such system.
spam filtering using a markov random field model with variable weighting schemas. in this paper we present a markov random field model based approach to filter spam. our approach examines the importance of the neighborhood relationship (mrf cliques) among words in an email message for the purpose of spam classification. we propose and test several different theoretical bases for weighting schemes among corresponding neighborhood windows. our results demonstrate that unexpected side effects depending on the neighborhood window size may have larger accuracy impact than the neighborhood relationship effects of the markov random field.
on effective conceptual indexing and similarity search in text data. similarity search in text has proven to be an interesting problem from the qualitative perspective because of inherent redundancies and ambiguities in textual descriptions. the methods used in search engines in order to retrieve documents most similar to user-defined sets of keywords are not applicable to targets which are medium to large size documents, because of even greater noise effects stemming from the presence of a large number of words unrelated to the overall topic in the document. the inverted representation is the dominant method for indexing text, but it is not as suitable for document-to-document similarity search, as for short user-queries. one way of improving the quality of similarity search is latent semantic indexing (lsi), which maps the documents from the original set of words to a concept space. u fortunately, lsi maps the data into a domain in which it is not possible to provide effectiveindexing techniques. in this paper, we investigate new ways of providing conceptual search among documents bycreating a representation in terms of conceptual word-chains. this technique also allows effective indexing techniques so that similarity queries ca be performed on large collectionsof documents by accessing a small amount of data. we demonstrate that our scheme outperforms standard textual similarity search o the inverted representation both in terms of quality a d search efficiency.
moment: maintaining closed frequent itemsets over a stream sliding window. this paper considers the problem of mining closed frequent itemsets over a sliding window using limited memory space. we design a synopsis data structure to monitor transactions in the sliding window so that we can output the current closed frequent itemsets at any time. due to time and memory constraints, the synopsis data structure cannot monitor all possible itemsets. however, monitoring only frequent itemsets will make it impossible to detect new itemsets when they become frequent. in this paper, we introduce a compact data structure, the closed enumeration tree (cet), to maintain a dynamically selected set of itemsets over a sliding-window. the selected itemsets consist of a boundary between closed frequent itemsets and the rest of the itemsets. concept drifts in a data stream are reflected by boundary movements in the cet. in other words, a status change of any itemset (e.g., from non-frequent to frequent) must occur through the boundary. because the boundary is relatively stable, the cost of mining closed frequent itemsets over a sliding window is dramatically reduced to that of mining transactions that can possibly cause boundary movements in the cet. our experiments show that our algorithm performs much better than previous approaches.
a preference model for structured supervised learning tasks. the preference model introduced in this paper gives a natural framework and a principled solution for a broad class of supervised learning problems with structured predictions, such as predicting orders (label and instance ranking), and predicting rates (classification and ordinal regression). we show how all these problems can be cast as linear problems in an augmented space, and we propose an on-line method to efficiently solve them. experiments on an ordinal regression task confirm the effectiveness of the approach.
indexing and mining free trees. tree structures are used extensively in domains such ascomputational biology, pattern recognition, computer networks,and so on. in this paper, we present an indexing techniquefor free trees and apply this indexing technique to theproblem of mining frequent subtrees. we first define a novelrepresentation, the canonical form, for rooted trees and extendthe definition to free trees. we also introduce anotherconcept, the canonical string, as a simpler representationfor free trees in their canonical forms. we then apply ourtree indexing technique to the frequent subtree mining problemand present freetreeminer, a computationally efficientalgorithm that discovers all frequently occurring subtreesin a database of free trees. we study the performance andthe scalability of our algorithms through extensive experimentsbased on both synthetic data and datasets from tworeal applications: a dataset of chemical compounds and adataset of internet multicast trees.
integrating fuzziness into olap for multidimensional fuzzy association rules mining. this paper contributes to the ongoing research onmultidimensional online association rules mining byproposing a general architecture that utilizes a fuzzy datacube for knowledge discovery. three different methods areintroduced to mine fuzzy association rules in the constructedfuzzy data cube, namely single dimension, multidimensionaland hybrid association rules mining. experimental resultsobtained for each of the three methods on the adult data ofthe united states census in 2000 show their effectiveness andapplicability.
efficient determination of dynamic split points in a decision tree. we consider the problem of choosing split points forcontinuous predictor variables in a decision tree. previousapproaches to this problem typically either (1) discretize the continuous predictor values prior to learning or (2) apply a dynamic method that considers all possible split points for each potential split. in this paper, we describe anumber of alternative approaches that generate a smallnumber of candidate split points dynamically with littleoverhead. we argue that these approaches are preferable to pre-discretization, and provide experimental evidence that they yield probabilistic decision trees with the same prediction accuracy as the traditional dynamic approach.furthermore, because the time to grow a decision tree isproportional to the number of split points evaluated, our approach is significantly faster than the traditional dynamic approach.
using emerging patterns and decision trees in rare-class classification. the problem of classifying rarely occurring cases is faced in many real life applications. the scarcity of the rare cases makes it difficult to classify them correctly using traditional classifiers. in this paper, we propose a new approach to use emerging patterns (eps) and decision trees (dts) in rare-class classification (epdt). eps are those itemsets whose supports in one class are significantly higher than their supports in the other classes. epdt employs the power of eps to improve the quality of rare-case classification. to achieve this aim, we first introduce the idea of generating new non-existing rare-class instances, and then we over-sample the most important rare-class instances. our experiments show that epdt outperforms many classification methods.
efficient splitting rules based on the probabilities of pre-assigned intervals. this paper describes new methods for classification in orderto find an optimal tree. unlike the current splitting rules that areprovided by searching all threshold values, this paper proposes thesplitting rules that are based on the probabilities of pre-assignedintervals.
discovering similar patterns for characterising time series in a medical domain. in this article, we describe the process of discovering similar patterns in time series and creating reference models for population groups in a medical domain, and particularly in the field of physiotherapy, using data mining techniques on a set of isokinetic data. the discovered knowledge was evaluated against the expertise of a physician specialized in isokinetic techniques, and applied in the i4 (intelligent interpretation of isokinetic information) project developed in conjunction with the spanish national center for sports research and sciences for muscular diagnosis and rehabilitation, injury prevention, training evaluation and planning, etc., of elite athletes and ordinary people.
an adaptive learning approach for noisy data streams. two critical challenges typically associated with mining data streams are concept drift and data contamination. to address these challenges, we seek learning techniques and models that are robust to noise and can adapt to changes in timely fashion. we approach the stream-mining problem using a statistical estimation framework, and propose a fast and robust discriminative model for learning noisy data streams. we build an ensemble of classifiers to achieve timely adaptation by weighting classifiers in a way that maximizes the likelihood of the data. we further employ robust statistical techniques to alleviate the problem of noise sensitivity. experimental results on both synthetic and real-life data sets demonstrate the effectiveness of this new model learning approach.
discovery of functional relationships in multi-relational data using inductive logic programming. ilp systems have been largely applied to datamining classification tasks with a considerable success. the use of ilp systems in regression tasks has been far less successful. current systems have very limited numerical reasoning capabilities, which limits the application of ilp to discovery of functional relationships of numeric nature. this paper proposes improvements in numerical reasoning capabilities of ilp systems for dealing with regression tasks. it proposes the use of statistical-based techniques like model validation and model selection to improve noise handling and it introduces a new search stopping criterium based on the pac method to evaluate learning performance. we have found these extensions essential to improve on results over machine learning and statistical-based algorithms used in the empirical evaluation study.
towards automatic generation of query taxonomy: a hierarchical query clustering approach. previous works on automatic query clustering most generatea flat, un-nested partition of query terms. in this work,we are pursuing to organize query terms into a hierarchicalstructure and construct a query taxonomy in an automaticway. the proposed approach is designed based on a hierarchicalagglomerative clustering algorithm to hierarchicallygroup similar queries and generate the cluster hierarchiesby a novel cluster partition technique. the search processesof real-world search engines are combined to obtain highlyranked web documents as the feature source for each queryterm. preliminary experiments show that the proposed approachis effective to obtain thesaurus information for queryterms, and is also feasible to construct a query taxonomywhich provides a basis for in-depth analysis of users' searchinterests and domain-specific vocabulary on a larger scale.
efficient multidimensional quantitative hypotheses generation. finding local interrelations (hypotheses) among attributeswithin very large databases of high dimensionalityis an acute problem for many databases and data miningapplications. these include, dependency modeling, clusteringlarge databases, correlation and link analysis.traditional statistical methods are concerned with the corroborationof (a set of) hypotheses on a given body ofdata. testing all of the hypotheses that can be generatedfrom a database with millions of records and dozens offields is clearly infeasible. generating, on the other hand,a set of the most "promising" hypotheses (to be corroborated)requires much intuition and ingenuity.in this paper we present an efficient method for rankingthe multidimensional hypotheses using image processingof data visualization. in the heart of the method lies theuse of visualization techniques and image processing ideasto rank subsets of attributes according to the relation betweenthem in the databases. some of the scalability issuesare solved by concise generalized histograms and by usingan efficient on-line computation of clustering around amedian with only five additional memory words. in additionto presenting our algorithmic methodology, we demonstrateits efficiency and performance by applying it to realcensus data sets, as well as synthetic data sets.
evolutionary time series segmentation for stock data mining. stock data in the form of multiple time series aredifficult to process, analyze and mine. however, when theycan be transformed into meaningful symbols like technicalpatterns, it becomes an easier task. most recent work ontime series queries only concentrates on how to identify agiven pattern from a time series. researchers do notconsider the problem of identifying a suitable set of timepoints for segmenting the time series in accordance with agiven set of pattern templates (e.g., a set of technicalpatterns for stock analysis). on the other hand, using fixedlength segmentation is a primitive approach to thisproblem; hence, a dynamic approach (with highcontrollability) is preferred so that the time series can besegmented flexibly and effectively according to the needs ofthe users and the applications. in view of the facts that sucha segmentation problem is an optimization problem andevolutionary computation is an appropriate tool to solve it,we propose an evolutionary time series segmentationalgorithm. this approach allows a sizeable set of stockpatterns to be generated for mining or query. in addition,defining the similarity between time series (or time seriessegments) is of fundamental importance in fitnesscomputation. by identifying the perceptually importantpoints directly from the time domain, time series segmentsand templates of different lengths can be compared andintuitive pattern matching can be carried out in an effectiveand efficient manner. encouraging experimental results arereported from tests that segment the time series of selectedhong kong stocks.
analyzing high-dimensional data by subspace validity. we are proposing a novel method that makes it possibleto analyze high dimensional data with arbitrary shapedprojected clusters and high noise levels. at the core of ourmethod lies the idea of subspace validity. we map the datain a way that allows us to test the quality of subspaces usingstatistical tests. experimental results, both on synthetic andreal data sets, demonstrate the potential of our method.
scalable multi-relational association mining. we propose the new radar technique for multi-relational data mining. this permits the mining of very large collections and provides a new technique for discovering multi-relational associations. results show that radar is reliable and scalable for mining a large yeast homology collection, and that it does not have the main-memory scalability constraints of the farmer and warmr tools.
objective and subjective algorithms for grouping association rules. we propose two algorithms for grouping and summarizingassociation rules. the first algorithm recursively groupsrules according to the structure of the rules and generatesa tree of clusters as a result. the second algorithm groupsthe rules according to the semantic distance between therules by making use of an autometically tagged semantictree-structured network of items. we provide a case study inwhich the proposed algorithms are evaluated. the resultsshow that our grouping methods are effective and producegood grouping results.
fast pnn-based clustering using k-nearest neighbor graph. search for nearest neighbor is the main source ofcomputation in most clustering algorithms. we proposethe use of nearest neighbor graph for reducing thenumber of candidates. the number of distancecalculations per search can be reduced from o(n) to o(k)where n is the number of clusters, and k is the number ofneighbors in the graph. we apply the proposed schemewithin agglomerative clustering algorithm known as thepnn algorithm.
using functional pca for cardiac motion exploration. principal component analysis (pca) [14, 6] is a maintool in multivariate data analysis. its paradigms are alsoused in the karhunen-loeve decomposition [5], a standardtool in image processing. extensions of pca to the frameworkof functional data have been proposed. the analy-sisprovided by the functional pca seems to be a powerfultool to find principal sources of variability in curves or images,but it fails in providing us with easy interpretationsin the case of multifunctional data. guide lines aiming atspot information from the outputs of pca applied to functionalswith values in space of continuous functions upona bounded domain are proposed. an application to cardiacmotion analysis illustrates the complexity of the multi-functionalframework and the results provided by functionalpca. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
knowledge discovery from diagrammatically represented data. knowledge discover from diagrammatic data can be facilitated by a language that permits queries on such data.such a language (diagrammatic sql) is being developed to expedite the development of an autonomous artificially intelligent agent with a capacity to deal with diagrammatic information.this language is described and examples of how it can be used to facilitatediagrammatic data mining are detaled
an evaluation of approaches to classification rule selection. in this paper a number of classification rule evaluation measures are considered. in particular the authors review the use of a variety of selection techniques used to order classification rules contained in a classifier, and a number of mechanisms used to classify unseen data. the authors demonstrate that rule ordering founded on the size of antecedent works well given certain conditions.
integrating e-commerce and data mining: architecture and challenges. we show that the e-commerce domain can provide all the right ingredients for successful data mining. we describe an integrate architecture for supporting this integration. thearchitecture can dramatically reduce the pre-processing, cleaning, and data understanding effort often documented to take 80%of the time in knowledge discovery projects. we emphasize the need for data collection at the application server layer (not the web server)in order to support logging of data and metadata that is essential to the discovery process. we describe the datatransformation bridges require from the transaction processing systems an customer event streams (e.g.,clickstreams) to the data warehouse. we detail the mining workbench, which needs to provide multiple views of the data through reporting, data mining algorithms, visualization, and olap. we conclude with a set of challenges.
obtaining best parameter values for accurate classification. in this paper we examine the effect that the choice of support and confidence thresholds has on the accuracy of classifiers obtained by classification association rule mining. we show that accuracy can almost always be improved by a suitable choice of threshold values, and we describe a method for finding the best values. we present results that demonstrate this approach can obtain higher accuracy without the need for coverage analysis of the training data. keywords: classification, association rule mining.
text document categorization by term association. a good text classifier is a classifier that efficiently categorizeslarge sets of text documents in a reasonable timeframe and with an acceptable accuracy, and that providesclassification rules that are human readable for possiblefine-tuning. if the training of the classifier is also quick,this could become in some application domains a good assetfor the classifier. many techniques and algorithms forautomatic text categorization have been devised. accordingto published literature, some are more accurate than others,and some provide more interpretable classification modelsthan others. however, none can combine all the beneficialproperties enumerated above. in this paper, we present anovel approach for automatic text categorization that borrowsfrom market basket analysis techniques using associationrule mining in the data-mining field. we focus on twomajor problems: (1) finding the best term association rulesin a textual database by generating and pruning; and (2)using the rules to build a text classifier. our text categorizationmethod proves to be efficient and effective, and experimentson well-known collections show that the classifierperforms well. in addition, training as well as classificationare both fast and the generated rules are human readable.
t-trees, vertical partitioning and distributed association rule mining. in this paper we consider a technique (data-vp) fordistributed (and parallel) association rule mining thatmakes use of a vertical partitioning technique to distributethe input data amongst processors. the proposed verticalpartitioning is facilitated by a novel compressed set enumerationtree data structure (the t-tree), and an associatedmining algorithm (apriori-t), that allows for computationallyeffective distributed/parallel arm when compared withexisting approaches.
efficient subsequence matching in time series databases under time and amplitude transformations. subsequence matching in large time series databases hasattracted a lot of interest and many methods have been proposedthat cope with this problem in an adequate extend.however, locating subsequence matches of arbitrary length,under time and amplitude transformations, has received farless attention and is still an open problem. in this paperwe present an efficient algorithm for variable-length subsequencematching under transformations that guaranteesno false dismissals. further, this algorithm uses a novelsimilarity criterion for determining similarity under amplitudetransformations in a most efficient way. finally, ouralgorithm has been tested in various experiments on realdata, resulting in a running time improvement of one orderof magnitude compared to the naive approach.
unsupervised segmentation of categorical time series into episodes. this paper describes an unsupervised algorithm forsegmenting categorical time series into episodes. thevoting-experts algorithm first collects statistics aboutthe frequency and boundary entropy of ngrams, then passesa window over the series and has two "expert methods" decidewhere in the window boundaries should be drawn. thealgorithm successfully segments text into words in four languages.the algorithm also segments time series of robotsensor data into subsequences that represent episodes inthe life of the robot. we claim that voting-expertsfinds meaningful episodes in categorical time series becauseit exploits two statistical characteristics of meaningfulepisodes.
attribute measurement policies for time and cost sensitive classification. attribute measurement is an important component of classification algorithms, which could limit their applicability in realtime settings. the time taken to assign a value to an unknown attribute may reduce the overall utility of the final result. we identify three different costs that must be considered, including a time sensitive utility function. we model this attribute measurement problem as a markov decision process (mdp), and build a policy to control this process using ao* heuristic search. the results offer a cost-effective approach to attribute measurement and classification for a variety of realtime applications.
speed-up iterative frequent itemset mining with constraint changes. mining of frequent itemsets is a fundamental datamining task. past research has proposed many efficientalgorithms for the purpose. recent work also highlightedthe importance of using constraints to focus the miningprocess to mine only those relevant itemsets. in practice,data mining is often an interactive and iterative process.the user typically changes constraints and runs the miningalgorithm many times before satisfied with the finalresults. this interactive process is very time consuming.existing mining algorithms are unable to take advantageof this iterative process to use previous mining results tospeed up the current mining process. this results inenormous waste in time and in computation. in this paper,we propose an efficient technique to utilize previousmining results to improve the efficiency of current miningwhen constraints are changed. we first introduce theconcept of tree boundary to summarize the usefulinformation available from previous mining. we then showthat the tree boundary provides an effective and efficientframework for the new mining. the proposed techniquehas been implemented in the contexts of two existingfrequent itemset mining algorithms, fp-tree and treeprojection. experiment results on both synthetic and real-lifedatasets show that the proposed approach achievesdramatic saving in computation.
online algorithms for mining semi-structured data stream. in this paper, we study an online data mining problemfrom streams of semi-structured data such as xml data.modeling semi-structured data and patterns as labeled orderedtrees, we present an online algorithm streamt thatreceives fragments of an unseen possibly infinite semi-structureddata in the document order through a datastream, and can return the current set of frequent patternsimmediately on request at any time. a crucial part of our algorithmis the incremental maintenance of the occurrencesof possibly frequent patterns using a tree sweeping technique.we give modifications of the algorithm to other on-linemining model. we present theoretical and empiricalanalyses to evaluate the performance of the algorithm.
mining frequent closed patterns in microarray data. microarray data typically contains a large number of columns and a small number of rows, which poses a great challenge for existing frequent (closed) pattern mining algorithms that discover patterns in item enumeration space. in this paper, we propose two new algorithms that explore the row enumeration space to mine frequent closed patterns. several experiments on real-life gene expression data show that the new algorithms are faster than existing algorithms, including closet, charm, closet+ and carpenter.
detection of significant sets of episodes in event sequences. we present a method for a reliable detection of "unusual" sets of episodes in the form of many pattern sequences, scanned simultaneously for an occurrence as a subsequence in a large event stream within a window of size w. we also investigate the important special case of all permutations of the same sequence, which models the situation where the order of events in an episode does not matter, e.g., when events correspond to purchased market basket items. in order to build a reliable monitoring system we compare obtained measurements to a reference model which in our case is a probabilistic model (bernoulli or markov). we first present a precise analysis that leads to a construction of a threshold. the difficulties of carrying out a probabilistic analysis for an arbitrary set of patterns, stems from the possible simultaneous occurrence of many members of the set as subsequences in the same window, the fact that the different patterns typically do have common symbols or common subsequences or possibly common prefixes, and that they may have different lengths. we also report on extensive experimental results, carried out on the wal-mart transactions database, that show a remarkable agreement with our theoretical analysis. this paper is an extension of our previous work in [reliable detection of episodes in event sequences] where we laid out foundation for the problem of the reliable detection of an "unusual" episodes, but did not consider more than one episode scanned simultaneously for an occurrence.
optimal projections of high dimensional data. in this paper, we compare two artificial neuralnetwork algorithms for performing exploratoryprojection pursuit, a statistical technique forinvestigating data by projecting it onto lower dimensionalmanifolds. the neural networks are extensions of anetwork which performs principal component analysis.we illustrate the technique on artificial data beforeapplying it to real data.
blocking anonymity threats raised by frequent itemset mining. in this paper we study when the disclosure of datamining results represents, per se, a threat to the anonymity of the individuals recorded in the analyzed database. the novelty of our approach is that we focus on an objective definition of privacy compliance of patterns without any reference to a preconceived knowledge of what is sensitive and what is not, on the basis of the rather intuitive and realistic constraint that the anonymity of individuals should be guaranteed. in particular, the problem addressed here arises from the possibility of inferring from the output of frequent itemset mining (i.e., a set of itemsets with support larger than a threshold ó), the existence of patterns with very low support (smaller than an anonymity threshold k)[3]. in the following we develop a simple methodology to block such inference opportunities by introducing distortion on the dangerous patterns.
identifying markov blankets with decision tree induction. the markov blanket of a target variable is theminimum conditioning set of variables that makes thetarget independent of all other variables. markovblankets inform feature selection, aid in causal discoveryand serve as a basis for scalable methods of constructingbayesian networks. this paper applies decision treeinduction to the task of markov blanket identification.notably, we compare (a) c5.0, a widely used algorithmfor decision rule induction, (b) c5c, which post-processesc5.0's rule set to retain the most frequentlyreferenced variables and (c) pc, a standard method forbayesian network induction. c5c performs as well as orbetter than c5.0 and pc across a number of data sets.our modest variation of an inexpensive, accurate, off-the-shelfinduction engine mitigates the need for specializedprocedures, and establishes baseline performance againstwhich specialized algorithms can be compared.
classification with degree of membership: a fuzzy approach. algorithms adopt either a decision tree based approach or an approach that requires users to provide some user-specifiedthresholds to guide the search for interesting rules. in this paper, we propose a new approach based on the use of an objective interestingness measure todistinguish interesting rules from uninteresting ones. using linguistic terms to represent the revealed regularities and exceptions, this approach s especially useful when the discovered rules are presented to human experts for examination because of the affinity with thehuman knowledge representation. the use of fuzzy technique allows the predict on of attribute values to be associated with degree of membership. our approach s, therefore, able to deal with the cases that an object can belong to more than one class. for example, a person can suffer from cold and fever to certain extent at the same time. furthermore, our approach is more resilient to noise and missing data values because of the use of fuzzy technique. to evaluate the performance of our approach, we tested it using several real-life databases. the experimental results show that it can be very effective at data mining tasks. in fact, when compared to popular data mining algorithms, our approach can be better ableto uncover useful rules hidden in databases.
on feature selection through clustering. we study an algorithm for feature selection that clusters attributes using a special metric and then makes use of the dendrogram of the resulting cluster hierarchy to choose the most relevant attributes. the main interest of our technique resides in the improved understanding of the structure of the analyzed data and of the relative importance of the attributes for the selection process.
adaptive clustering: obtaining better clusters using feedback and past experience. adaptive clustering uses external feedback to improve cluster quality; past experience serves to speed up execution time. an adaptive clustering environment is proposed that uses q-learning to learn the reward values of successive data clusterings. adaptive clustering supports the reuse of clusterings by memorizing what worked well in the past. it has the capability of exploring multiple paths in parallel when searching for good clusters. in a case study, we apply adaptive clustering to instance-based learning relying on a distance function modification approach. a distance function adaptation scheme that uses external feedback is proposed and compared with other distance function learning approaches. experimental results indicate that the use of adaptive clustering leads to significant improvements of instance-based learning techniques, such as k-nearest neighbor classifiers. moreover, as a by-product a new instance-based learning technique is introduced that classifies examples by solely using cluster representatives; this technique shows high promise in our experimental evaluation.
heuristic optimization for decentralized frequent itemset counting. the choices for mining of decentralized data are numerous, and we have developed techniques to enumerate andoptimize decentralized frequent itemset counting. in thispaper, we introduce our heuristic approach to improve theperformance of such techniques developed in ways similarto query processing in database systems. we also describeempirical results that validate our heuristic techniques.
a fast algorithm for computing hypergraph transversals and its application in mining emerging patterns. computing the minimal transversals of a hypergraph isan important problem in computer science that has significantapplications in data mining. in this paper, we present anew algorithm for computing hypergraph transversals andhighlight their close connection to an important class ofpatterns known as emerging patterns. we evaluate our techniqueon a number of large datasets and show that it out-performsprevious approaches by a factor of 9-29 times.
generating an informative cover for association rules. mining association rules may generate a large numbersof rules making the results hard to analyze manually.pasquier et al. have discussed the generation of guigues-duquenne-luxenburger basis (gd-l basis). using a similarapproach, we introduce a new rule of inference anddefine the notion of association rules cover as a minimalset of rules that are non-redundant with respect to this newrule of inference. our experimental results (obtained usingboth synthetic and real data sets) show that our coversare smaller than the gd-l basis and they are computed intime that is comparable to the classic apriori algorithm forgenerating rules.
provably fast training algorithms for support vector machines. support vector machines are a family of data analysis algorithms, based on convex quadratic programming. we focus on their use for classification that case the svm algorithms work by maximizing the margin of a classifying hyperplane in a feature space. the feature space is handled by means of kernels f the problems are formulated in dual form. random sampling techniques successfully used for similar problems are studied here. the main contribute onis a random zed algorithm for training svms for which we can formally prove an upper bound on the expected running time that is quasilinear on the number of data points. to ourknowledge, this is the first algorithm for training svms in dual formulation and with kernels for which such a quasi-linear time bound has been formally proved.
inexact field learning: an approach to induce high quality rules from low quality data. to avoid low quality problem caused by low quality data, this paper introduces an inexactfield learning approach which derives rules by working on the fields of attributes with respect to classes, rather than on individual point values of attributes. the experimental results show that field learning achieved a higher prediction accuracy rate on new unseen test cases which is particularly true when the learning is performed on large low qualitydata.
a lazy approach to pruning classification rules. associative classification is a promising technique forthe generation of highly precise classifiers. previous workspropose several clever techniques to prune the huge set ofgenerated rules, with the twofold aim of selecting a smallset of high quality rules, and reducing the chance of overfitting.in this paper, we argue that pruning should be reducedto a minimum and that the availability of a large rule basemay improve the precision of the classifier, without affectingits performance. in l3 (live and let live), a new algorithmfor associative classification, a lazy pruning technique iterativelydiscards all rules that only yield wrong case classifications.classification is performed in two steps. initially, ruleswhich have already correctly classified at least one trainingcase, sorted by confidence, are considered. if the caseis still unclassified, the remaining rules (unused during thetraining phase) are considered, again sorted by confidence.extensive experiments on 26 databases from the ucimachine learning database repository show that l3 improvesthe classification precision with respect to previousapproaches.
clustering on demand for multiple data streams. in the data stream environment, the patterns generated by the mining techniques are usually distinct at different time because of the evolution of data. in order to deal with various types of multiple data streams and to support flexible mining requirements, we devise in this paper a clustering on demand framework, abbreviated as cod framework, to dynamically cluster multiple data streams. while providing a general framework of clustering on multiple data streams, the cod framework has two major features, namely one data scan for online statistics collection and compact multi-resolution approximations, which are designed to address, respectively, the time and the space constraints in a data stream environment. furthermore, with the multi-resolution approximations of data streams, flexible clustering demands can be supported.
detecting patterns of appliances from total load data using a dynamic programming approach. nonintrusive appliance load monitoring (nialm) systems require sufficient accurate total load data to separate the load into its major appliances. the most available solutions separate the whole electric energy consumption based on the measurement of all three voltages and currents. aside from the cost for special measuring devices, the intrusion into the local installation is the main problem for reaching a high market distribution. the use of standard digital electricity meters could avoid this problem but the loss of information of the measured data has to be compensated by more intelligent algorithms and implemented rules to disaggregate the total load trace of only the active power measurements. the paper presents a new nialm approach to analyse data, collected form a standard digital electricity meter. to disaggregate the consumption of the entire active power into its major electrical end uses, an algorithm consisting of clustering methods, a genetic algorithm and a dynamic programming approach is presented. the genetic algorithm is used to combine frequently occuring events to create hypothetical finite state machines to model detectable appliances. the time series of each finite state machine is optimized using a dynamic programming method similar to the viterbi algorithm.
feature selection for clustering - a filter solution. processing applications with a large number of dimensionshas been a challenge to the kdd community. featureselection, an effective dimensionality reduction technique,is an essential pre-processing method to remove noisy features.in the literature there are only a few methods proposedfor feature selection for clustering. and, almost all ofthose methods are wrapper' techniques that require a clusteringalgorithm to evaluate the candidate feature subsets.the wrapper approach is largely unsuitable in real-worldapplications due to its heavy reliance on clustering algorithmsthat require parameters such as number of clusters,and due to lack of suitable clustering criteria to evaluateclustering in different subspaces. in this paper we proposea filter' method that is independent of any clustering algorithm.the proposed method is based on the observationthat data with clusters has very different point-to-point distancehistogram than that of data without clusters. usingthis we propose an entropy measure that is low if data hasdistinct clusters and high otherwise. the entropy measure issuitable for selecting the most important subset of featuresbecause it is invariant with number of dimensions, and isaffected only by the quality of clustering. extensive performanceevaluation over synthetic, benchmark, and realdatasets shows its effectiveness.
mining relevant text from unlabelled documents. automatic classification of documents is an importantarea of research with many applications in the fields of documentsearching, forensics and others. methods to performclassification of text rely on the existence of a sample of documentswhose class labels are known. however, in manysituations, obtaining this sample may not be an easy (oreven possible) task. in this paper we focus on the classificationof unlabelled documents into two classes: relevant andirrelevant, given a topic of interest. by dividing the set ofdocuments into buckets (for instance, answers returned bydifferent search engines), and using association rule miningto find common sets of words among the buckets, we can efficientlyobtain a sample of documents that has a large percentageof relevant ones. this sample can be used to trainmodels to classify the entire set of documents. we prove, viaexperimentation, that our method is capable of filtering relevantdocuments even in adverse conditions where the percentageof irrelevant documents in the buckets is relativelyhigh.
efficient yet accurate clustering. in this paper we show that most hierarchical agglomerativeclustering (hac)algorithms follow a 90-10 rule where roughly 90%iterations from the beginning merge cluster pairs with dissimilarity less than 10%of the maximumdissimilarity. we propose two algorithms - 2-phase andnested - based on partially overlapping partitioning (pop).to handle high-dimensional data efficiently, we propose a tree structure particularly suitable for pop. extensive experimentsshow that the proposed algorithms reduce the time andmemory requirement of existing hac algorithms significantly without compromising in accuracy.
classifier fusion using shared sampling distribution for boosting. we present a new framework for classifier fusion that uses a shared sampling distribution for obtaining a weighted classifier ensemble. the weight update process is self regularizing as subsequent classifiers trained on the disjoint views rectify the bias introduced by any classifier in preceding iterations. we provide theoretical guarantees that our approach indeed provides results which are better than the case when boosting is performed separately on different views. the results are shown to outperform other classifier fusion strategies on a well known texture image database.
mining frequent spatio-temporal sequential patterns. many applications track the movement of mobile objects, which can be represented as sequences of timestamped locations. given such a spatio-temporal series, we study the problem of discovering sequential patterns, which are routes frequently followed by the object. sequential pattern mining algorithms for transaction data are not directly applicable for this setting. the challenges to address are (i) the fuzziness of locations in patterns, and (ii) the identification of non-explicit pattern instances. in this paper, we define pattern elements as spatial regions around frequent line segments. our method first transforms the original sequence into a list of sequence segments, and detects frequent regions in a heuristic way. then, we propose algorithms to find patterns by employing a newly proposed substring tree structure and improving apriori technique. a performance evaluation demonstrates the effectiveness and efficiency of our approach.
using rough sets theory and database operations to construct a good ensemble of classifiers for data mining applications. in this paper we present a new approach to construct a good ensemble of classifiers using rough sets theory and database operations. ensembles of classifiers is formulated precisely within the framework of rough sets theory and constructed very efficiently by using set-oriented database operations. our method first computes a set of reductswhich include all the indispensable attributes required for the decision categories. for each reduct, a reduct table is generated by removing those attributes which are not in the reduct. next, a novel rule induction algorithm is used to compute the maximal generalized rules for each reducttable and a set of reduct classifiers is formed based on thecorresponding reducts. the distinctive features of our method as compared to other methods of constructing ensembles of classifiers are:(1) present a theoretical model to explain the mechanism of constructing ensemble of classifiers, (2) each reduct is a minimum subset of attributes, has the same classification ability as the entire attributes,(3)ea h reduct classifier constructed from the corresponding reduct has a minimal set of classification rules, and is as accurate andcomplete as possible and at the same time as diverse as possible from the other classifiers, (4)the test indicates that the number of classifiers used to improve the accuracy is muchless than other methods
subspace selection for clustering high-dimensional data. in high-dimensional feature spaces traditional clustering algorithms tend to break down in terms of efficiency and quality. nevertheless, the data sets often contain clusters which are hidden in various subspaces of the original feature space. in this paper, we present a feature selection technique called surfing (subspaces relevant for clustering) that finds all subspaces interesting for clustering and sorts them by relevance. the sorting is based on a quality criterion for the interestingness of a subspace using the k-nearest neighbor distances of the objects. as our method is more or less parameterless, it addresses the unsupervised notion of the data mining task "clustering" in a best possible way. a broad evaluation based on synthetic and real-world data sets demonstrates that surfing is suitable to find all relevant subspaces in high dimensional, sparse data sets and produces better results than comparative methods.
towards simple, easy-to-understand, yet accurate classifiers. we design a method for weighting linear support vectormachine classifiers or random hyperplanes, to obtain classifierswhose accuracy is comparable to the accuracy of anon-linear support vector machine classifier, and whose resultscan be readily visualized. we conduct a simulationstudy to examine how our weighted linear classifiers behavein the presence of known structure. the results show thatthe weighted linear classifiers might perform well comparedto the non-linear support vector machine classifiers, whilethey are more readily interpretable than the non-linear classifiers.
mining a set of coregulated rna sequences. post-transcriptional regulation, though less studied, isan important research topic in bioinformatics. in a set ofpost-transcriptionally coregulated rnas, the basepair interactionscan organize the molecules into domains andprovide a framework for functional interactions. their consensusmotifs may represent the binding sites of rna regulatoryproteins. unlike dna motifs, rna motifs are moreconserved in structures than in sequences. knowing thestructural motifs can help us better understand the regulationactivities. in this paper, we propose a novel data miningapproach to rna secondary structure prediction. todemonstrate the performance of our new approach, we firsttested it on the same data sets previously used and publishedin literature. secondly, to show the flexibility of ournew approach, we also tested it on a data set that containspseudoknot motifs that most current systems cannot identify.
improving automatic query classification via semi-supervised learning. accurate topical classification of user queries allows for increased effectiveness and efficiency in general-purpose web search systems. such classification becomes critical if the system is to return results not just from a general web collection but from topic-specific back-end databases as well. maintaining sufficient classification recall is very difficult as web queries are typically short, yielding few features per query. this feature sparseness coupled with the high query volumes typical for a large-scale search service makes manual and supervised learning approaches alone insufficient. we use an application of computational linguistics to develop an approach for mining the vast amount of unlabeled data in web query logs to improve automatic topical web query classification. we show that our approach in combination with manual matching and supervised learning allows us to classify a substantially larger proportion of queries than any single technique. we examine the performance of each approach on a real web query stream and show that our combined method accurately classifies 46% of queries, outperforming the recall of best single approach by nearly 20%, with a 7% improvement in overall effectiveness.
extraction techniques for mining services from web sources. the web has established itself as the dominantmedium for doing electronic commerce. consequentlythe number of service providers, bothlarge and small, advertising their services on theweb continues to proliferate. in this paper we describenew extraction algorithms for mining servicedirectories from web pages. we develop anovel propagation technique for identifying andaccumulating all of the attributes related to a serviceentity in a web page. we provide experimentalresults of the effectiveness of our extractiontechniques by mining a database of veterinarianservice providers from web sources.
neighborgram clustering interactive exploration of cluster neighborhoods. we describe an interactive way to generate a set of clustersfor a given data set. the clustering is done by constructinglocal histograms, which can then be used to visualize,select, and fine-tune potential cluster candidates.the accompanying algorithmcan also generate clusters automatically,allowing for an automatic or semi-automaticclustering process where the user only occasionally interactswith the algorithm. we illustrate the ability to automaticallyidentify and visualize clusters using nci's aidsantiviral screen data set.
findings from a practical project concerning web usage mining. in a practical project a statistical analysis of the weblog files of the domain www.volkswagen.de was carriedout by using the crisp-dm procedure. for the preprocessingphase, more profound findings could be gainedthan are usually described in many studies. since the aimwas to deduce significant statements while measuring theeffect, tests of significance for e-metrics were used inaddition to the commonly described procedure.
who links to whom: mining linkage between web sites. previous studies of the web graph structure have focused on the graph structure at the level of individual pages. in actuality the web is a hierarchically nested graph, with domains, hosts and web sites introducing intermediate levels of affiliation and administrativecontrol. to better understand the growth of the web we need to understand its macro-structure, in terms of the linkage between web sites. in this paper e approximate this by studying the graph of the linkage between hosts on the web. this as done based on snapshots of the web taken by google in oct 1999,aug 2000 and jun 2001.the connectivity between hosts is represented by a directed graph, with hosts as nodes and weighted edges representingthe count of hyperlinks between pages on the corresponding hosts. we demonstrate how such a "hostgraph" an be used to study connectivity properties of hosts and domains over time, anddiscuss a modified "copy model" too explain observed link eight distributions as a function of subgraph size. we discuss changes in the web over time in the size and connectivity of web sites and country domains. we also describe a data mining application of the hostgraph: a related host finding algorithm which achieves a precision of 0.65 at rank 3.
a new algorithm for learning parameters of a bayesian network from distributed data. we present a novel approach for learning parametersof a bayesian network from distributed heterogeneousdataset. in this case, the whole dataset is distributedin several sites and each site contains observations fora different subset of features. the new method usesthe collective learning approach proposed in our earlierwork and substantially reduces the computational andtransmission overhead. theoretical analysis is givenand experimental results are provided to illustrate theaccuracy and efficiency of our method.
pairwise symmetry decomposition method for generalized covariance analysis. we propose a new theoretical framework for generalizing the traditional notion of covariance. first, we discuss the role of pairwise cross-cumulants by introducing a cluster expansion technique for the cumulant generating function. next, we introduce a novel concept of symmetry decomposition of probability density functions according to the c_4v group. by utilizing the irreducible representations, generalized covariances are explicitly defined, and their utility is demonstrated using an analytically solvable model.
vivo: visual vocabulary construction for mining biomedical images. given a large collection of medical images of several conditions and treatments, how can we succinctly describe the characteristics of each setting? for example, given a large collection of retinal images from several different experimental conditions (normal, detached, reattached, etc.), how can data mining help biologists focus on important regions in the images or on the differences between different experimental conditions? if the images were text documents, we could find the main terms and concepts for each condition by existing ir methods (e.g., tf/idf and lsi). we propose something analogous, but for the much more challenging case of an image collection: we propose to automatically develop a visual vocabulary by breaking images into n × n tiles and deriving key tiles ("vivos") for each image and condition. we experiment with numerous domain-independent ways of extracting features from tiles (color histograms, textures, etc.), and several ways of choosing characteristic tiles (pca, ica). we perform experiments on two disparate biomedical datasets. the quantitative measure of success is classification accuracy: our "vivos" achieve high classification accuracy (up to 83% for a nine-class problem on feline retinal images). more importantly, qualitatively, our "vivos" do an excellent job as "visual vocabulary terms": they have biological meaning, as corroborated by domain experts; they help spot characteristic regions of images, exactly like text vocabulary terms do for documents; and they highlight the differences between pairs of images.
webspade: a parallel sequence mining algorithm to analyze web log data. enterprise-class web sites receive a large amountof traffic, from both registered and anonymous users.data warehouses are built to store and help analyze the click streams within this traffic to providecompanies with valuable insights into the behaviorof their customers. this article proposes a parallelsequence mining algorithm, webspade, to analyzethe click streams found in site web logs. in this process, raw web logs are first cleaned and inserted intoa data warehouse. the click streams are then minedby webspade. an innovative web-based front-endis used to visualize and query the sequence miningresults. the webspade algorithm is currently usedby verizon to analyze the daily traffic of the verizon.com web site.
semi-supervised mixture of kernels via lpboost methods. we propose an algorithmto construct classification models with a mixture of kernels from labeled and unlabeled data. the derived classifier is a mixture of models, each based on one kernel choice from a library of kernels. the sparse-favoring 1-norm regularization method is employed to restrict the complexity of mixture models and to achieve the sparsity of solutions. by modifying the column generation boosting algorithm lpboost to a more general linear programming formulation, we are able to efficiently solve mixture-of-kernel problems and automatically select kernel basis functions centered at labeled data as well as unlabeled data. the effectiveness of the proposed approach is proved by experimental results on benchmark datasets.
kernel-density-based clustering of time series subsequences using a continuous random-walk noise model. noise levels in time series subsequence data are typically very high, and properties of the noise differ from those of white noise. the proposed algorithm incorporates a continuous random-walk noise model into kernel-density-based clustering. evaluation is done by testing to what extent the resulting clusters are predictive of the process that generated the time series. it is shown that the new algorithm not only outperforms partitioning techniques that lead to trivial and unsatisfactory results under the given quality measure, but also improves upon other density-based algorithms. the results suggest that the noise elimination properties of kernel-density-based clustering algorithms can be of significant value for the use of clustering in preprocessing of data.
a levelwise search algorithm for interesting subspace clusters. we present a levelwise search algorithm for finding subspace clusters in high dimensional data satisfying various properties besides the commonly used minimum density property. a set of such properties are summarized and a user can choose any of these properties. a lattice is built with all the discovered clusters which enables further analysis and discovery of useful knowledge about the clusters and their inter-relationships.
frequent sub-structure-based approaches for classifying chemical compounds. in this paper we study the problem of classifying chemical compounddatasets. we present a sub-structure-based classificationalgorithm that decouples the sub-structure discovery processfrom the classification model construction and uses frequentsubgraph discovery algorithms to find all topological and geometricsub-structures present in the dataset. the advantage ofour approach is that during classification model construction, allrelevant sub-structures are available allowing the classifier tointelligently select the most discriminating ones. the computationalscalability is ensured by the use of highly efficient frequentsubgraph discovery algorithms coupled with aggressive featureselection. our experimental evaluation on eight different classificationproblems shows that our approach is computationallyscalable and on the average, outperforms existing schemes by10% to 35%.
multi-view clustering. we consider clustering problems in which the available attributes can be split into two independent subsets, such that either subset suffices for learning. example applications of this multi-view setting include clustering of web pages which have an intrinsic view (the pages themselves) and an extrinsic view (e.g., anchor texts of inbound hyperlinks); multi-view learning has so far been studied in the context of classification. we develop and study partitioning and agglomerative, hierarchical multi-view clustering algorithms for text data. we find empirically that the multi-view versions of k-means and em greatly improve on their single-view counterparts. by contrast, we obtain negative results for agglomerative hierarchical multi-view clustering. our analysis explains this surprising phenomenon.
information theoretic clustering of sparse co-occurrence data. a novel approach to clustering co-occurrence data posesit as an optimization problem in information theory whichminimizes the resulting loss in mutual information. a divisiveclustering algorithm that monotonically reduces thisloss function was recently proposed. in this paper we showthat sparse high-dimensional data presents special challengeswhich can result in the algorithm getting stuck atpoor local minima. we propose two solutions to this problem:(a) a "prior" to overcome infinite relative entropy valuesas in the supervised naive bayes algorithm, and (b)local search to escape local minima. finally, we combinethese solutions to get a robust algorithm that is computationallyefficient. we present experimental results to showthat the proposed method is effective in clustering documentcollections and outperforms previous information-theoreticclustering approaches.
adaptive product normalization: using online learning for record linkage in comparison shopping. the problem of record linkage focuses on determining whether two object descriptions refer to the same underlying entity. addressing this problem effectively has many practical applications, e.g., elimination of duplicate records in databases and citation matching for scholarly articles. in this paper, we consider a new domain where the record linkage problem is manifested: internet comparison shopping. we address the resulting linkage setting that requires learning a similarity function between record pairs from streaming data. the learned similarity function is subsequently used in clustering to determine which records are co-referent and should be linked. we present an online machine learning method for addressing this problem, where a composite similarity function based on a linear combination of basis functions is learned incrementally. we illustrate the efficacy of this approach on several real-world datasets from an internet comparison shopping site, and show that our method is able to effectively learn various distance functions for product data with differing characteristics. we also provide experimental results that show the importance of considering multiple performance measures in record linkage evaluation.
iterative clustering of high dimensional text data augmented by local search. the k-means algorithm with cosine similarity, alsoknown as the spherical k-means algorithm, is a popularmethod for clustering document collections. however,spherical k-means can often yield qualitatively poor results,especially when cluster sizes are small, say 25-30 documentsper cluster, where it tends to get stuck at a localmaximum far away from the optimal solution. in this paper,we present a local search procedure, which we call"first-variation" that refines a given clustering by incrementallymoving data points between clusters, thus achievinga higher objective function value. an enhancement offirst variation allows a chain of such moves in a kernighan-linfashion and leads to a better local maximum. combiningthe enhanced first-variation with spherical k-meansyields a powerful "ping-pong" strategy that often qualitativelyimproves k-means clustering and is computationallyefficient. we present several experimental results to high-lightthe improvement achieved by our proposed algorithmin clustering high-dimensional and sparse text data.
better rules, few features: a semantic approach to selecting features from text. the choice of features used to represent a domain has a profound effect on the quality of the model produced; yet, few researchers have investigated the relationship between the features used to represent text and the quality of the final model. we explored this relationship formedical texts by comparing association rules based on features with three different semantic levels: (1) words (2) manually assigned keywords and (3) automatically selected medical concepts. our preliminary findings indicate that bi-directional association rules based onconcepts or keywords are more plausible and more useful than those based on word features. the concept and keyword representations also required 90% fewer features than the word representation. this drastic dimensionality reduction suggests that this approach is well suited to large textual corpus of medical text, such as parts of the web.
cluster merging and splitting in hierarchical clustering algorithms. hierarchical clustering constructs a hierarchy of clusterseither repeatedly mer in two smaller clusters into alarger one or splittin a larger cluster into smaller ones. the crucial step is how to best select the next cluster(s)to split or merge. here we provide a comprehensiveanalysis of selection methods and propose several newmethods. we perform extensive clustering experimentsto test 8 selection methods, and ?nd that the averagesimilarity is the best method in divisive clustering andminmax linkage is the best in agglomerativecluster balance is a key factor to achieve goodperformance. we also introduce the concept of objective function saturation and clustering target distanceto effectively assess the quality of clustering.
a user-driven and quality-oriented visualization for mining association rules. on account of the enormous amounts of rules that canbe produced by data mining algorithms, knowledgevalidation is one of the most problematic steps in anassociation rule discovery process.in order to findrelevant knowledge for decision-making, the user needs toreally rummage through the rules.visualization can bevery beneficial to support him/her in this task byimproving the intelligibility of the large rule sets andenabling the user to navigate inside them.in this article,we propose to answer the association rule validationproblem by designing a human-centered visualizationmethod for the rule rummaging task.this new approachbased on a specific rummaging model relies on ruleinterestingness measures and on interactive rule subsetfocusing and mining.we have implemented ourrepresentation by developing a first experimentalprototype called arvis.
a biobjective model to select features with good classification quality and low cost. in this paper we address a multi-group classification problem in which we want to take into account, together with the generalization ability, cots associated with the features. this cost is not limited to an economical payment, but can also refer to risk, computational effort, space requirements, etc. in order to get a good generalization ability, we use support vector machines (svm) as the basic mechanism by considering the maximization of the margin. we formulate the problem as a biobjective mixed integer problem, for which pareto optimal solutions can be obtained.
convex hull ensemble machine. we propose a new ensemble algorithm called "convexhull ensemble machine (chem)." chem in hilbert spaceis developed first and it is modified to regression and clas-sificationproblems. empirical studies show that in classi-ficationproblems chem has similar prediction accuracyas adaboost, but chem is much more robust to outputnoise. in regression problems, chem works competitivelywith other ensemble methods such as gradient boost andbagging.
using information-theoretic measures to assess association rule interestingness. assessing rules with interestingness measures is the cornerstone of successful applications of association rule discovery. however, there exists no information-theoretic measure which is adapted to the semantics of association rules. in this article, we present the directed information ratio (dir), a new rule interestingness measure which is based on information theory. dir is specially designed for association rules, and in particular it differentiates two opposite rules a → b and a → \mathop b\limits^ - . moreover, to our knowledge, dir is the only rule interestingness measure which rejects both independence and (what we call) equilibrium, i.e. it discards both the rules whose antecedent and consequent are negatively correlated, and the rules which have more counter-examples than examples. experimental studies show that dir is a very filtering measure, which is useful for association rule post-processing.
a min-max cut algorithm for graph partitioning and data clustering. an important application of graph partitioning is data clustering using a graph model - the pairwise similarities between all data objects form a weighted graph adjacency matrix that contains all necessary information for clustering. here we propose a new algorithm for graph partition with an objective function that follows the min-max clustering principle. the relaxed version of the optimization of the min-max cut objective function leads to the fiedler vector in spectral graph partition. theoretical analyses of min-max cut indicate that it leads to balanced partitions, and lower bonds are derived. the min-max cut algorithm is tested on news-group datasets and is found to outperform other current popular partitioning/clustering methods. the linkage-based refinements in the algorithm further improve the quality of clustering substantially. we also demonstrate that the linearized search order based on linkage differential is better than that based on the fiedler vector, providing another effectivepartition method.
text classification by boosting weak learners based on terms and concepts. document representations for text classification are typically based on the classical bag-of-words paradigm. this approach comes with deficiencies that motivate the integration of features on a higher semantic level than single words. in this paper we propose an enhancement of the classical document representation through concepts extracted from background knowledge. boosting is used for actual classification. experimental evaluations on two well known text corpora support our approach through consistent improvement of the results.
adaptive dimension reduction for clustering high dimensional data. it is well-known that for high dimensional data clustering, standard algorithms such as em and the k -meansare often trapped in local minimum. many initializationmethods were proposed to tackle this problem, but withonly limited success. in this paper we propose newapproach to resolve this problem by repeated dimension reductions such that k-means or em are performedonly in very low dimensions.cluster membership is utilized as a bridge between the reduced dimensional sub-space and the original space, providing flexibility andease of implementation. clustering analysis performedon highly overlapped gaussians, dna gene expressionprofiles and internet newsgroups demonstrate the effectiveness of the proposed algorithm.
high performance data mining using the nearest neighbor join. the similarity join has become an important database primitiveto support similarity search and data mining. a similarity joincombines two sets of complex objects such that the result containsall pairs of similar objects. well-known are two types of thesimilarity join, the distance range join where the user defines adistance threshold for the join, and the closest point query ork-distance join which retrieves the k most similar pairs. in thispaper, we investigate an important, third similarity join operationcalled k-nearest neighbor join which combines each point ofone point set with its k nearest neighbors in the other set. it hasbeen shown that many standard algorithms of knowledge discoveryin databases (kdd) such as k-means and k-medoid clustering,nearest neighbor classification, data cleansing, postprocessingof sampling-based data mining etc. can be implementedon top of the k-nn join operation to achieve performance improvementswithout affecting the quality of the result of these algorithms.we propose a new algorithm to compute the k-nearestneighbor join using the multipage index (mux), a specialized indexstructure for the similarity join. to reduce both cpu and i/ocost, we develop optimal loading and processing strategies.
incremental support vector machine construction. svms suffer from the problem of large memory requirement and cpu time when trained in batch mode on large data sets. we overcome these limitations, and at the same time make svms suitable for learning with data streams, by constructing incremental learning algorithms.we first introduce and compare different incremental learning techniques, and show that they are capable of producing performance results similar to the batch algorithm, and in some cases superior condensation properties. we then consider the problem of training svms using stream data. our objective is to maintain an updated representation of recent batches of data. we apply incremental schemes to the problem and show that their accuracy is comparable to the batch algorithm.
density connected clustering with local subspace preferences. many clustering algorithms tend to break down in high-dimensional feature spaces, because the clusters often exist only in specific subspaces (attribute subsets) of the original feature space. therefore, the task of projected clustering (or subspace clustering) has been defined recently. as a novel solution to tackle this problem, we propose the concept of local subspace preferences, which captures the main directions of high point density. using this concept we adopt density-based clustering to cope with high-dimensional data. in particular, we achieve the following advantages over existing approaches: our proposed method has a determinate result, does not depend on the order of processing, is robust against noise, performs only one single scan over the database, and is linear in the number of dimensions. a broad experimental evaluation shows that our approach yields results of significantly better quality than recent work on clustering high-dimensional data.
extensible markov model. a markov chain is a popular data modeling tool. this paper presents a variation of markov chain, namely extensible markov model (emm). by providing a dynamically adjustable structure, emm overcomes the problems caused by the static nature of the traditional markov chain. therefore, emms are particularly well suited to model spatiotemporal data such as network traffic, environmental data, weather data, and automobile traffic. performance studies using emms for spatiotemporal prediction problems show the advantages of this approach.
significance tests for patterns in continuous data. in this paper we consider the question of uncertainty of detected patterns in data mining. in particular, we develop statistical tests for patterns found in continuous data, indicating the significance of these patterns in terms of the probability that they have occurred by chance. we examine the performance of these tests on patterns detected in several large data sets, including a data set describing the locations of earthquakes in california and another describing flow cytometry measurements on phytoplankton.
modal-style operators in qualitative data analysis. we explore the usage of the modal possibility operator (andits dual necessity operator) in qualitative data analysis, andshow that it - quite literally - complements the derivationoperator of formal concept analysis; we also propose a newgeneralization of the rough set approximation operators. asan example for the applicability of the concepts we investigatethe morse data set which has been frequently studiedin multidimensional scaling procedures.
examiner: optimized level-wise frequent pattern mining with monotone constraint. the key point of this paper is that, in frequent patternmining, the most appropriate way of exploiting monotoneconstraints in conjunction with frequency is to use them inorder to reduce the problem input together with the searchspace. following this intuition, we introduce examiner, alevel-wise algorithm which exploits the real synergy of anti-monotoneand monotone constraints: the total benefit isgreater than the sum of the two individual benefits. examinergeneralizes the basic idea of the preprocessing algorithmexante, embedding such ideas at all levels ofan apriori-like computation. the resulting algorithm is thegeneralization of the apriori algorithm when a conjunctionof monotone constraints is conjoined to the frequency anti-monotoneconstraint. experimental results confirm that thisis, so far, the most efficient way of attacking the computationalproblem in analysis.
using representative-based clustering for nearest neighbor dataset editing. the goal of dataset editing in instance-based learning is to remove objects from a training set in order to increase the accuracy of a classifier. for example, wilson editing removes training examples that are misclassified by a nearest neighbor classifier so as to smooth the shape of the resulting decision boundaries. this paper revolves around the use of representative-based clustering algorithms for nearest neighbor dataset editing. we term this approach supervised clustering editing. the main idea is to replace a dataset by a set of cluster prototypes. a novel clustering approach called supervised clustering is introduced for this purpose. our empirical evaluation using eight uci datasets shows that both wilson and supervised clustering editing improve accuracy on more than 50% of the datasets tested. however, supervised clustering editing achieves four times higher compression rates than wilson editing.
on closed constrained frequent pattern mining. constrained frequent patterns and closed frequent patterns are two paradigms aimed at reducing the set of extracted patterns to a smaller, more interesting, subset. although a lot of work has been done with both these paradigms, there is still confusion around the mining problem obtained by joining closed and constrained frequent patterns in a unique framework. in this paper we shed light on this problem by providing a formal definition and a thorough characterization. wealso study computational issues and show how to combine the most recent results in both paradigms, providing a very efficient algorithm which exploits the two requirements (satisfying constraints and being closed) together at mining time in order to reduce the computation as much as possible.
usage-based pagerank for web personalization. recommendation algorithms aim at proposing "next" pages to a user based on her current visit and the past users' navigational patterns. in the vast majority of related algorithms, only the usage data are used to produce recommendations, whereas the structural properties of the web graph are ignored. we claim that taking also into account the web structure and using link analysis algorithms ameliorates the quality of recommendations. in this paper we present upr, a novel personalization algorithm which combines usage data and link analysis techniques for ranking and recommending web pages to the end user. using the web site's structure and its usage data we produce personalized navigational graph synopses (prng) to be used for applying upr and produce personalized recommendations. experimental results show that the accuracy of the recommendations is superior to pure usage-based approaches.
mining molecular fragments: finding relevant substructures of molecules. we present an algorithm to find fragments in a setof molecules that help to discriminate between differentclasses of, for instance, activity in a drug discovery context.instead of carrying out a brute-force search, our methodgenerates fragments by embedding them in all appropriatemolecules in parallel and prunes the search tree based ona local order of the atoms and bonds, which results in substantiallyfaster search by eliminating the need for frequent,computationally expensive reembeddings and by suppressingredundant search. we prove the usefulness of our algorithmby demonstrating the discovery of activity-relatedgroups of chemical compounds in the well-known nationalcancer institute's hiv-screening dataset.
bifold constraint-based mining by simultaneous monotone and anti-monotone checking. mining for frequent itemsets can generate an overwhelming number of patterns, often exceeding the size of the original transactional database. one way to deal with this issue is to set filters and interestingness measures. others advocate the use of constraints to apply to the patterns, either on the form of the patterns or on descriptors of the items in the patterns. however, typically the filtering of patterns based on these constraints is done as a post-processing phase. filtering the patterns post-mining adds a significant overhead, still suffers from the sheer size of the pattern set and loses the opportunity to exploit those constraints. in this paper we propose an approach that allows the efficientmining of frequent itemsets patterns, while pushing simultaneously both monotone and anti-monotone constraints during and at different strategic stages of the mining process. our implementation shows a significant improvement when considering the constraints early and a better performance over dualminer which also considers both types of constraints.
shortest-path kernels on graphs. data mining algorithms are facing the challenge to deal with an increasing number of complex objects. for graph data, a whole toolbox of data mining algorithms becomes available by defining a kernel function on instances of graphs. graph kernels based on walks, subtrees and cycles in graphs have been proposed so far. as a general problem, these kernels are either computationally expensive or limited in their expressiveness. we try to overcome this problem by defining expressive graph kernels which are based on paths. as the computation of all paths and longest paths in a graph is np-hard, we propose graph kernels based on shortest paths. these kernels are computable in polynomial time, retain expressivity and are still positive definite. in experiments on classification of graph models of proteins, our shortest-path kernels show significantly higher classificationaccuracy than walk-based kernels.
telecommunications strategic marketing - kdd and economic modeling. the italian deregulation process of telecommunications market in the last years has produced a largeeconomic impact since it has altered equilibriums thatwere established for a long time. in this framework, wenotice a strong need for adequate tools to analyze themarket and its trends and, at the same time, a lack ofspecific solutions within the scientific literature, due tothe new technical challenges issued by the problem.in particular, in the context of building a decisionsupport system (dss) for the strategic marketing unit oftelecom italia (ti) we have devised a newmethodology to profitably combine most powerful toolsfrom kdd and economic sciences. we have tested ourapproach by analyzing the residential telecommunicationsmarket demand in italy during the transition from amonopolistic structure to an oligopolistic one.in this paper, we first address the state of the art indss design, then we describe the proposed methodologyand its application in the case study.
ensembles of cascading trees. we introduce a new method, called cs4, to constructcommittees of decision trees for classification. the methodconsiders different top-ranked features as the root nodes ofmember trees. this idea is particularly suitable for dealingwith high-dimensional bio-medical data as top-ranked featuresin this type of data usually possess similar merits forclassification. to make a decision, the committee combinesthe power of individual trees in a weighted manner. unlikebagging or boosting which uses bootstrapped trainingdata, our method builds all the member trees of a committeeusing exactly the same set of training data. we have testedthese ideas on uci data sets as well as recent bio-medicaldata sets of gene expression or proteomic profiles that areusually described by more than 10,000 features. all the experimentalresults show that our method is efficient and thatthe classification performance are superior to c4.5 familyalgorithms.
efficient density-based clustering of complex objects. nowadays data mining in large databases of complex objects from scientific, engineering or multimedia applications is getting more and more important. in many different application domains complex object representations along with complex distance functions are used for measuring the similarity between objects. often not only these complex distance measures are available but also simpler distance functions which can be computed much more efficiently. traditionally, the well known concept of multi-step query processing which is based on exact and lower-bounding approximative distance functions is used independently of data mining algorithms. in this paper, we will demonstrate how the paradigm of multi-step query processing can be integrated into the two density-based clustering algorithms dbscan and optics resulting in a considerable efficiency boost. our approach tries to confine itself to ¿-range queries on the simple distance functions and carries out complex distance computations only at that stage of the clustering algorithm where they are compulsory to compute the correct clustering result. in a broad experimental evaluation based on real-world test data sets, we demonstrate that our approach accelerates the generation of flat and hierarchical density-based clusterings by more than one order of magnitude.
optimized disjunctive association rules via sampling. the problem of finding optimized support associationrules for a single numerical attribute, where the optimizedregion is a union of k disjoint intervals from the range ofthe attribute, is investigated. the first polynomial timealgorithm for the problem of finding such a region maximizingsupport and meeting a minimum cumulative confidencethreshold is given. because the algorithm is notpractical, an ostensibly easier, more constrained versionof the problem is considered. experiments demonstratethat the best extant algorithm for the constrained versionhas significant performance degradation on both a syntheticmodel of patterned data and on real world data sets.running the algorithm on a small random sample is proposedas a means of obtaining near optimal results withhigh probability. theoretical bounds on sufficient samplesize to achieve a given performance level are proved, andrapid convergence on synthetic and real-world data is validatedexperimentally.
matching in frequent tree discovery. various definitions and frameworks for discovering frequent trees in forests have been developed recently. at the heart of these frameworks lies the notion of matching, which determines when a pattern tree matches a tree in a data set. we introduce a novel notion of tree matching for use in frequent tree mining and we show that it generalizes the framework of zaki while still being more specific than that of termier et al. furthermore, we show how zaki's treeminerv algorithm can be adapted towards our notion of tree matching. experiments show the promise of the approach.
warp: time warping for periodicity detection. periodicity mining is used for predicting trends in time series data. periodicity detection is an essential process in periodicity mining to discover potential periodicity rates. existing periodicity detection algorithms do not take into account the presence of noise, which is inevitable in almost every real-world time series data. in this paper, we tackle the problem of periodicity detection in the presence of noise. we propose a new periodicity detection algorithm that deals efficiently with all types of noise. based on time warping, the proposed algorithm warps (extends or shrinks) the time axis at various locations to optimally remove the noise. experimental results show that the proposed algorithm out-performs the existing periodicity detection algorithms in terms of noise resiliency.
segment-based injection attacks against collaborative filtering recommender systems. significant vulnerabilities have recently been identi- fied in collaborative filtering recommender systems. researchers have shown that attackers can manipulate a system's recommendations by injecting biased profiles into it. in this paper, we examine attacks that concentrate on a targeted set of users with similar tastes, biasing the system's responses to these users. we show that such attacks are both pragmatically reasonable and also highly effective against both user-based and item-based algorithms. as a result, an attacker can mount such a "segmented" attack with little knowledge of the specific system being targeted and with strong likelihood of success.
summarization - compressing data into an informative representation. in this paper, we formulate the problem of summarization of a dataset of transactions with categorical attributes as an optimization problem involving two objective functions - compaction gain and information loss. we propose metrics to characterize the output of any summarization algorithm. we investigate two approaches to address this problem. the first approach is an adaptation of clustering and the second approach makes use of frequent itemsets from the association analysis domain. we illustrate one application of summarization in the field of network data where we show how our technique can be effectively used to summarize network traffic into a compact but meaningful representation. specifically, we evaluate our proposed algorithms on the 1998 darpa off-line intrusion detection evaluation data and network data generated by skaion corp for the arda information assurance program.
preprocessing opportunities in optimal numerical range partitioning. we show that only the segment borders have to be taken into account as cut point candidates in searching for theoptimal multisplit of a numerical value range with respect to convex attribute evaluation functions. segment borders can be found efficiently in a linear-time preprocessing step. with training set error, which is not strictly convex, the data can be preprocessed into an even smaller number of cut point candidates, called alternations, when striving for the optimal partition. we show that no segment borders(resp. alternations) can be overlooked with strictly convex functions (resp. training set error) without risking to lose optimality. our experiments show that while in real-world domainssignificant reduction in the number of cut point candidates can be obtained for training set error, the number of segment borders is usually not much lower than that of boundary points.
mining general temporal association rules for items with different exhibition periods. in this paper, we explore a new model of mining generaltemporal association rules from large databases wherethe exhibition periods of the items are allowed to be differentfrom one to another. note that in this new model,the downward closure property which all prior apriori-basedalgorithms relied upon to attain good efficiency isno longer valid. as a result, how to efficiently generatecandidate itemsets form large databases has become themajor challenge. to address this issue, we develop an efficientalgorithm, referred to as algorithm spf (standingfor segmented progressive filter) in this paper. the basicidea behind spf is to first segment the database into sub-databasesin such a way that items in each sub-databasewill have either the common starting time or the commonending time. then, for each sub-database, spf progressivelyfilters candidate 2-itemsets with cumulative filteringthresholds either forward or backward in time. this featureallows spf of adopting the scan reduction techniqueby generating all candidate k-itemsets (k >2) from candidate2-itemsets directly. the experimental results show thatalgorithm spf significantly outperforms other schemeswhich are extended from prior methods in terms of the executiontime and scalability.
an improved categorization of classifier's sensitivity on sample selection bias. a recent paper categorizes classifier learning algorithms according to their sensitivity to a common type of sample selection bias where the chance of an example being selected into the training sample depends on its feature vector x but not (directly) on its class label y. a classifier learner is categorized as "local" if it is insensitive to this type of sample selection bias, otherwise, it is considered "global". in that paper, the true model is not clearly distinguished from the model that the algorithm outputs. in their discussion of bayesian classifiers, logistic regression and hard-margin svms, the true model (or the model that generates the true class label for every example) is implicitly assumed to be contained in the model space of the learner, and the true class probabilities and model estimated class probabilities are assumed to asymptotically converge as the training data set size increases. however, in the discussion of naive bayes, decision trees and soft-margin svms, the model space is assumed not to contain the true model, and these three algorithms are instead argued to be "global learners". we argue that most classifier learners may or may not be affected by sample selection bias; this depends on the dataset as well as the heuristics or inductive bias implied by the learning algorithm and their appropriateness to the particular dataset.
creating ensembles of classifiers. ensembles of classifiers offer promise in increasing overall classification accuracy. the availability of extremely large datasets has opened avenues for application of distributed and/or parallel learning to efficiently learn models of them. in this paper, distributed learningis done by training classifiers on disjoint subsets of the data. we examine a random partitioning method to create disjoint subsets and propose a more intelligent way of partitioning into disjointsubsets using clustering. it was observed that the intelligent method of partitioning generally performs better than random partitioning for our datasets. in both methods a significant gain in accuracy may be obtained by applying bagging to each of the disjoint subsets, creating multiple diverse classifiers. the significance of our finding is that a partition strategy for even small/moderate sized datasets when combined with bagging can yield better performancethan applying a single learner using the entire dataset.
effective estimation of posterior probabilities: explaining the accuracy of randomized decision tree approaches. there has been increasing number of independently proposed randomization methods in different stages of decision tree construction to build multiple trees. randomized decision tree methods have been reported to be significantly more accurate than widely-accepted single decision trees, although the training procedure of some methods incorporates a surprisingly random factor and therefore opposes the generally accepted idea of employing gain functions to choose optimum features at each node and compute a single tree that fits the data. one important question that is not well understood yet is the reason behind the high accuracy. we provide an insight based on posterior probability estimations. we first establish the relationship between effective posterior probability estimation and effective loss reduction. we argue that randomized decision tree methods effectively approximate the true probability distribution using the decision tree hypothesis space. we conduct experiments using both synthetic and real-world datasets under both 0-1 and cost-sensitive loss functions.
making subsequence time series clustering meaningful. recently, the startling claim was made that sequential time series clustering is meaningless. this has important consequences for a significant amount of work in the literature, since such a claim invalidates this work's contribution. in this paper, we show that sequential time series clustering is not meaningless, and that the problem highlighted in these works stem from their use of the euclidean distance metric as the distance measure in the subsequence vector space. as a solution, we consider quite a general class of time series, and propose a regime based on two types of similarity that can exist between subsequence vectors, which give rise naturally to an alternative distance measure to euclidean distance in the subsequence vector space. we show that, using this alternative distance measure, sequential time series clustering can indeed be meaningful. we repeat a key experiment in the work on which the "meaningless" claim was based, and show that our method leads to a successful clustering outcome.
decision tree evolution using limited number of labeled data items from drifting data streams. most previously proposed mining methods on data streams make an unrealistic assumption that "labelled" data stream is readily available and can be mined at anytime. however, in most real-world problems, labelled data streams are rarely immediately available. due to this reason, models are reconstructed only when labelled data become available periodically. this passive stream mining model has several drawbacks. we propose a new concept of demand-driven active data mining. in active mining, the loss of the model is either continuously guessed without using any true class labels or estimated, whenever necessary, from a small number of instances whose actual class labels are verified by paying an affordable cost. when the estimated loss is more than a tolerable threshold, the model evolves by using a small number of instances with verified true class labels. previous work on active mining concentrates on error guess and estimation. in this paper, we discuss several approaches on decision tree evolution.
a computational framework for taxonomic research: diagnosing body shape within fish species complexes. it is estimated that ninety percent of the world's species have yet to be discovered and described. the main reason for the slow pace of new species description is that the science of taxonomy, as traditionally practiced, can be very laborious. to formally describe a new species, taxonomists have to manually gather and analyze data from large numbers of specimens, often from broad geographic areas, and identify the smallest subset of external body characters that uniquely diagnoses the new species as distinct from all its known relatives. in this paper, we use an automated feature selection and classification approach to address the taxonomic impediment in new species discovery. the experiments on a taxonomic problem involving species of suckers in the genus carpiodes demonstrate promising results.
using artificial anomalies to detect unknown and known network intrusions. intrusion detection systems (idss) must be capable of detecting new and unknown attacks, or anomalies. we study the problem of building detection models for both pure anomaly detection and combined misuse and anomaly detection (i.e., detection of both known and unknown intrusions). we show the necessity of artificial anomalies by discussing the failure to use conventional inductive learning methods to detect anomalies. we propose an algorithm to generate artificial anomalies to coerce the inductive learner into discovering an accurate boundary between known classes (normal connections and known intrusions) and anomalies. empirical studies show that our pure anomaly-detection model trained using normal and artificial anomalies is capable of detecting more than 77% of all unknown intrusion classes with more than 50% accuracy per intrusion class. the combined misuse and anomaly-detection models are as accurate as a pure misuse detection model in detecting known intrusions and are capable of detecting at least 50% of unknown intrusion classes with accuracy measurements between 75 and 100% per class.
labeling unclustered categorical data into clusters based on the important attribute values. sampling has been recognized as an important technique to improve the efficiency of clustering. however, with sampling applied, those points which are not sampled will not have their labels. although there is a straightforward approach in the numerical domain, the problem of how to allocate those unlabeled data points into proper clusters remains as a challenging issue in the categorical domain. in this paper, a mechanism named maximal resemblance data labeling (abbreviated as mardl) is proposed to allocate each unlabeled data point into the corresponding appropriate cluster based on the novel categorical clustering representative, namely, node importance representative(abbreviated as nir), which represents clusters by the importance of attribute values. mardl has two advantages: (1) mardl exhibits high execution efficiency; (2) after each unlabeled data is allocated into the proper cluster, mardl preserves clustering characteristics, i.e., high intra-cluster similarity and low inter-cluster similarity. mardl is empirically validated via real and synthetic data sets, and is shown to be not only more efficient than prior methods but also attaining results of better quality.
progressive modeling. presently, inductive learning is still performed in a frustratingbatch process. the user has little interaction withthe system and no control over the final accuracy and trainingtime. if the accuracy of the produced model is too low,all the computing resources are misspent. in this paper, wepropose a progressive modeling framework. in progressivemodeling, the learning algorithm estimates online both theaccuracy of the final model and remaining training time. ifthe estimated accuracy is far below expectation, the usercan terminate training prior to completion without wastingfurther resources. if the user chooses to complete the learningprocess, progressive modeling will compute a modelwith expected accuracy in expected time. we describe oneimplementation of progressive modeling using ensemble ofclassifiers.
icon-based visualization of large high-dimensional datasets. high dimensional data visualization is critical todata analysts since it gives a direct view of originaldata. we present a method to visualize large amount ofhigh dimensional data. we divide dimensions of datainto several groups. then, we use one icon to represent each group, and associate visual properties of eachicon with dimensions in each group. a high dimensional data record will be represented by multiple different types of icons located in the same position. furthermore, we use summary icons to display local detailsof viewer's interests and the whole data set at meantime. we show its effectiveness and efficiency through a case study on a real large data set.
is random model better? on its accuracy and efficiency. inductive learning searches an optimal hypothesis thatminimizes a given loss function. it is usually assumed thatthe simplest hypothesis that fits the data is the best approximateto an optimal hypothesis. since finding the simplesthypothesis is np-hard for most representations, we generallyemploy various heuristics to search its closest match.computing these heuristics incurs significant cost, makinglearning inefficient and unscalable for large dataset. in thesame time, it is still questionable if the simplest hypothesisis indeed the closest approximate to the optimal model.recent success of combining multiple models, such as bagging,boosting and meta-learning, has greatly improved theaccuracy of the simplest hypothesis, providing a strong argumentagainst the optimality of the simplest hypothesis.however, computing these combined hypotheses incurs significantlyhigher cost. in this paper, we first advert that aslong as the error of a hypothesis on each example is withina range dictated by a given loss function, it can still be optimal.contrary to common beliefs, we propose a completelyrandom decision tree algorithm that achieves much higheraccuracy than the single best hypothesis and is comparableto boosted or bagged multiple best hypotheses. the advantageof multiple random tree is its training efficiency aswell as minimal memory requirement.
validating and refining clusters via visual rendering. the automatic clustering algorithms are known towork well in dealing with clusters of regular shapes, e.g.compact spherical/elongated shapes, but may incur highererror rates when dealing with arbitrarily shaped clusters.although some efforts have been devoted to addressingthe problem of skewed datasets, the problem of handlingclusters with irregular shapes is still in its infancy,especially in terms of dimensionality of the datasets andthe precision of the clustering results considered. notsurprisingly, the statistical indices works ineffective invalidating clusters of irregular shapes, too. in this paper,we address the problem of clustering and validatingarbitrarily shaped clusters with a visual framework(vista). the main idea of the vista approach is tocapitalize on the power of visualization and interactivefeedbacks to encourage domain experts to participate inthe clustering revision and clustering validation process.
using rule sets to maximize roc performance. rules are commonly use for classification because they are modular, intelligible and easy to learn. existing work in classification rule learning assumes the goal is to produce categorical classifications to maximize classification accuracy. recent work in machine learning has pointed out the limitations of classification accuracy: when class distributions are skewed, or error costs are unequal, an accuracy maximizing rule set can perform poorly. amore flexible use of a rule set is to produce instance scores indicating the likelihood that an instance belongs to a given class. with such an ability, we can apply rulesets effectively whendistributions are skewed or error costs are unequal. this paper empirically investigates different strategies for evaluating rule sets when the goal is to maximize the scoring (roc)performance.
privacy preserving data classification with rotation perturbation. data perturbation techniques are one of the most popular models for privacy preserving data mining [3, 1]. it is especially convenient for applications where the data owners need to export/publish the privacy-sensitive data. a data perturbation procedure can be simply described as follows. before the data owner publishes the data, they randomly change the data in certain way to disguise the sensitive information while preserving the particular data property that is critical for building the data models. several perturbation techniques have been proposed recently, among which the most typical ones are randomization approach [3] and condensation approach [1].
the anatomy of a hierarchical clustering engine for web-page, news and book snippets. in this paper, we investigate the web snippet hierarchical clustering problem in its full extent by devising an algorithmic solution, and a software prototype called snaket (accessible at http://roquefort.di.unipi.it/), that: (1) draws the snippets from 16 web search engines, the amazon collection of books a9.com, the news of google news and the blogs of blogline; (2) builds the clusters on-the-fly (ephemeral clustering) in response to a user query without adopting any pre-defined organization in categories; (3) labels the clusters with sentences of variable length, drawn from the snippets and possibly missing some terms, provided they are not too many;
association rules enhanced classification of underwater acoustic signal. classification of underwater acoustic signal is one ofthe important fields of pattern recognition. inspired bythe experience of training man experts in sonar, wepropose a two-phase training algorithm to exploit theassociation rules to reveal the understandable intrinsicrules contributing to correct classification in the knownmisclassification datasets in this paper. preliminaryexperimental results demonstrate the potential ofclassification association rules to enhance the accuracyof classification of underwater acoustic signals.
communication efficient construction of decision trees over heterogeneously distributed data. we present an algorithm designed to efficiently construct a decision tree over heterogeneously distributed data without centralizing. we compare our algorithm against a standard centralized decision tree implementation in terms of accuracy as well as the communication complexity. our experimental results show that by using only 20% of the communication cost necessary to centralize the data we can achieve trees with accuracy at least 80% of the trees produced by the centralized version.
fast frequent string mining using suffix arrays. we present a method to mine strings that are frequent in one database and infrequent in another. the method uses suffix- and lcp-arrays that can be computed extremely fast and space efficiently, and further exhibit a good locality behavior. experiments with several biologically relevant data sets show that our approach outperforms existing methods in terms of time and space.
a synchronization based algorithm for discovering ellipsoidal clusters in large datasets. this paper introduces a new scalable approach to clusteringbased on synchronization of pulse-coupled oscillators. eachdata point is represented by an integrate-and-fire oscillator, and the interaction between oscillators is defined according to the relative similarity between the points. the set of oscillators will self-organize into stable phase-locked subgroups. our approach proceeds by loading only a subset of the data and allowing it to self-organize. groups ofsynchronized oscillators are then summarized and purged from memory. we show that our method is robust, scales linearly, and can determine the number of clusters. the proposedapproach is empirically evaluated with several synthetic data sets and is used to segment large color images.
privacy-preserving frequent pattern mining across private databases. privacy consideration has much significance in the application of data mining. it is very important that the privacy of individual parties will not be exposed when data mining techniques are applied to a large collection of data about the parties. in many scenarios such as data warehousing or data integration, data from the different parties form a many-to-many schema. this paper addresses the problem of privacy-preserving frequent pattern mining in such a schema across two dimension sites. we assume that sites are not trusted and they are semi-honest. our method is based on the concept of semi-join and does not involve data encryption which is used in most previous work. experiments are conducted to study the efficiency of the proposed models.
functional trees for classification. the design of algorithms that explore multiple representation languages and explore different search space has an intuitive appeal.in this context of classification problems, algorithmsthat generate multivariate trees are able to explore multiplerepresentation languages by using decision test based on acombination of attributes.the same applies to models threesalgorithms, in regression domains, but using linear models atleaf nodes.in this paper we study where to use combinations of attributes in decision tree learning.we present an algorithm for multivariate tree learning that combines a univariate decision tree with a discriminant function by means of constructiveinduction.this algorithm is able to use decision nodes with multivariate tests, and leaf nodes that predict a class using adiscrimnant. multivariate decision nodes are built when growing the tree, while functional leaves are built when pruning the tree.functional trees can be seen as a generalization of multivariate trees.our algorithm was compared against to its components and two simplified versions using 30 benchmark datasets. the experimental evaluation shows that our algorithm has clear advantages with respect to the generalization ability and model sizes at statistically significant.
cole: a cooperative data mining approach and its application to early diabetes detection. we present cole, a cooperative data mining approach for discovering hybrid knowledge. it employs multiple different data mining algorithms, and combines results from them to enhance the mined knowledge. for our medical application area, we analyse several focusing strategies that allowed us to gain medically significant results.
feature selection for building cost-effective data stream classifiers. a stream classifier is a decision model that assigns a class label to a data stream, based on its arriving data. various features of the stream can be used in the classifier, each of which may have different relevance to the classification task and different cost in obtaining its value. as time passes by, some less costly features may become more relevant, but the time needed for decision may be considered as a cost. a challenge is how to balance the different costs when building a cost-effective classifier. this paper proposes a new feature selection strategy that extends the traditional relief algorithm in two aspects: (1) estimate the classification cost associated with each feature, and (2) order all the features with a score that combines both cost estimation and classification relevance. a classifier is then built with the selected features using a traditional classification method. experimental results show that classifiers constructed with this strategy are indeed cost effective.
mining generalized association rules for sequential and path data. while association rules for set data se and describe relations between parts of set valued objects completely, association rules for sequential data are restricted by specific interpretations of the subsequence relation: contiguous subsequences describe localfeatures of a sequence valued object, noncontiguous subsequences its global features. we model both types of features with generalized subsequences that describe local deviations by wildcards, and present a new algorithm of apriori type for mining all generalized subsequences with prescribed minim m support from a given database of sequences. furthermore we show that the givenalgorithm automatically takes into account an eventually underlying graph structure, i.e., is applicable to path data also.
a tight upper bound on the number of candidate patterns. in the context of mining for frequent patterns using the standard level wise algorithm, the following question arises: given the current level and the current set of frequentpatterns, what is the maximal number of candidate patterns that can be generated on the next level? we answer this question by providing a tight upper bound, derived from a combinatorial result from the sixties by kruskal andkatona. our result is useful to educe the number of databasescans.
esrs: a case selection algorithm using extended similarity-based rough sets. a case selection algorithm selects representative casesfrom a large data set for future case-based reasoningtasks. this paper proposes the esrs algorithm, based onextended similarity-based rough set theory, which selectsa reasonable number of the representative cases whilemaintaining satisfactory classification accuracy. it alsocan handle noise and inconsistent data. experimentalresults on synthetic and real sets of cases showed that itspredictive accuracy is similar to that of well-knownmachine learning systems on standard data sets, while ithas the advantage of being applicable to any data setwhere a similarity function can be defined.
a scalable collaborative filtering framework based on co-clustering. collaborative filtering-based recommender systems have become extremely popular in recent years due to the increase in web-based activities such as e-commerce and online content distribution. current collaborative filtering (cf) techniques such as correlation and svd based methods provide good accuracy, but are computationally expensive and can be deployed only in static off-line settings. however, a number of practical scenarios require dynamic real-time collaborative filtering that can allow new users, items and ratings to enter the system at a rapid rate. in this paper, we consider a novel cf approach based on a recently proposed weighted co-clustering algorithm [1] that involves simultaneous clustering of users and items. we design incremental and parallel versions of the co-clustering algorithm and use it to build an efficient real-time cf framework. empirical evaluation demonstrates that our approach provides an accuracy comparable to that of the correlation and matrix factorization based approaches at a much lower computational cost.
a machine learning approach to improve congestion control over wireless computer networks. in this paper, we present the application of machine learning techniques to the improvement of the congestion control of tcp in wired/wireless networks. tcp is sub-optimal in hybrid wired/wireless networks because it reacts in the same way to losses due to congestion and losses due to link errors. we thus propose to use machine learning techniques to build automatically a loss classifier from a database obtained by simulations of random network topologies. several machine learning algorithms are compared for this task and the best method for this application turns out to be decision tree boosting. it outperforms ad hoc classifiers proposed in the networking literature.
combining labeled and unlabeled data for text classification with a large number of categories. we develop a framework to incorporate unlabeled data in the error-correcting output coding (ecoc)setup by decomposing multiclass problems into multiple binary problems and then use co-training to learn the individual binary classification problems. we show that our method isespecially useful for classification tasks involving a large number of categories where co-training doesn't perform very well by itself and when combined with ecoc, outperforms several other algorithms that combine labeled and unlabeled data for text classification in terms of accuracy, precision-recall tradeoff, and efficiency.
using text mining to infer semantic attributes for retail data mining. current data mining techniques usually do not have amechanism to automatically infer semantic features inherentin the data being "mined". the semantics are eitherinjected in the initial stages (by feature construction) or byinterpreting the results produced by the algorithms. bothof these techniques have proved effective but require a lotof human effort. in many domains, semantic informationis implicitly available and can be extracted automaticallyto improve data mining systems. in this paper, we present acase study of a system that is trained to extract semantic featuresfor apparel products and populate a knowledge basewith these products and features. we show that semanticfeatures of these items can be successfully extracted by applyingtext learning techniques to the descriptions obtainedfrom websites of retailers. we also describe several applicationsof such a knowledge base of product semantics that wehave built including recommender systems and competitiveintelligence tools and provide evidence that our approachcan successfully build a knowledge base with accurate factswhich can then be used to create profiles of individual customers,groups of customers, or entire retail stores.
loaded: link-based outlier and anomaly detection in evolving data sets. in this paper, we present loaded, an algorithm for outlier detection in evolving data sets containing both continuous and categorical attributes. loaded is a tunable algorithm, wherein one can trade off computation for accuracy so that domain-specific response times are achieved. experimental results show that loaded provides very good detection and false positive rates, which are several times better than those of existing distance-based schemes.
an algorithm for in-core frequent itemset mining on streaming data. frequent itemset mining is a core data mining operation and has been extensively studied over the last decade. this paper takes a new approach for this problem and makes two major contributions. first, we present a one pass algorithm for frequent itemset mining, which has deterministic bounds on the accuracy, and does not require any out-of-core summary structure. second, because our one pass algorithm does not produce any false negatives, it can be easily extended to a two pass accurate algorithm. our two pass algorithm is very memory efficient, and allows mining of datasets with large number of distinct items and/or very low support levels. our detailed experimental evaluation on synthetic and real datasets shows the following. first, our one pass algorithm is very accurate in practice. second, our algorithm requires significantly lower memory than manku and motwani's one pass algorithm and the multi-pass apriori algorithm. our two pass algorithm outperforms apriori and fp-tree when the number of distinct items is large and/or support levels are very low. in other cases, it is quite competitive, with possible exception of cases where the average length of frequent itemsets is quite high.
dependency derivation in industrial process data. in many industrial processes, finding dependencies and the creation of dependency graphs can increase the understanding of the system significantly. this knowledge can then be used for further optimization and variable selection. most of the measured attributes in these cases come in the form of time series. there are several ways of determining correlation between series, most of them suffering from specific problems when applied to real-world data. here, awell performing measure based on the mutual information rate is derived and discussed with results from both synthetic and real data.
scalable model-based clustering by working on data summaries. the scalability problem in data mining involves the developmentof methods for handling large databases withlimited computational resources. in this paper, we presenta two-phase scalable model-based clustering framework:first, a large data set is summed up into sub-clusters; then,clusters are directly generated from the summary statisticsof sub-clusters by a specifically designed expectation-maximization(em) algorithm. taking example for gaussianmixture models, we establish a provably convergentem algorithm, emads, which embodies cardinality, mean,and covariance information of each sub-cluster explicitly.combining with different data summarization procedures,emads is used to construct two clustering systems:gemads and bemads. the experimental results demonstratethat they run several orders of magnitude faster thanthe classic em algorithm with little loss of accuracy. theygenerate significantly better results than other model-basedclustering systems using similar computational resources.
svd based term suggestion and ranking system. in this paper, we consider the application of the singular value decomposition (svd) to a search term suggestion system in a pay-for-performance search market. we propose a novel positive and negative refinement method based on orthogonal subspace projections. we demonstrate that svd subspace-based methods: 1) expand coverage by reordering the results, and 2) enhance the clustered structure of the data. the numerical experiments reported in this paper were performed on overture's pay-per-performance search market data.
on evaluating performance of classifiers for rare classes. predicting rare classes effectively is an important problem.the definition of effective classifier, embodied in theclassifier evaluation metric, is however very subjective, dependenton the application domain. in this paper, a widevariety of point-metrics are put into a common analyticalcontext defined by the recall and precision of the target rareclass. this enables us to compare various metrics in an objective,domain-independent manner. we judge their suitabilityfor the rare class problems along the dimensions oflearning difficulty and levels of rarity. this yields manyvaluable insights. in order to address the goal of achievingbetter recall and precision, we also propose a way ofcomparing classifiers directly based on the relationships betweenrecall and precision values. it resorts to a compositepoint-metric only when recall-precision based comparisonsyield conflicting results.
text classification with evolving label-sets. we introduce the evolving label-set problem encountered in building real-world text classification systems. this problem arises when a text classification system trained on a label-set encounters documents of unseen classes at deployment time. we design a class-detector module that monitors unlabeled data, detects new classes, and suggests them to the administrator for inclusion in the label-set. we propose abstractions that group together tokens under human understandable concepts and provide a mechanism of assigning importance to unseen terms. we present generative algorithms leveraging the notion of support of documents in a model for (1) selecting documents of proposed new classes, and (2) automatically triggering detection of new classes. experiments on three real world taxonomies show that our methods select new class documents with high precision, and trigger emergence of new classes with low false-positive and false-negative rates.
evaluating boosting algorithms to classify rare classes: comparison and improvements. classification of rare vents has many important data mining applications. boosting is a promising meta-techniquethat improves the classification performance of any weak classifier. so far, no systematic study has been conducted to evaluate how boosting performs for the task of mining rare classes. in this paper, we evaluate three existing categories of boosting algorithms from the single viewpoint of how they update the example weights in eachiteration, and discuss their possible effect on recall andprecision of the rare class. we propose enhanced algorithms in two of the categories, and justify their choice of weightupdating parameters theoretically. using some specially designed synthetic datasets, we compare the capability of all the algorithms from the rare class perspective. theresults support our qualitative analysis, and also indicate that our enhancements bring an extra capability for achieving better balance between recall and precision in mining rareclasses.
non-redundant data clustering. data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. in practice this discovery process should avoid redundancies with existing knowledge about class structures or groupings, and reveal novel, previously unknown aspects of the data. in order to deal with this problem, we present an extension of the information bottleneck framework, called coordinated conditional information bottleneck, which takes negative relevance information into account by maximizing a conditional mutual information score subject to constraints. algorithmically, one can apply an alternating optimization scheme that can be used in conjunction with different types of numeric and non-numeric attributes. we present experimental results for applications in text mining and computer vision.
a formal model for user preference. personalization and recommendation systems requireformalized model for user preference. this paper presentsthe formal model of preference including positivepreference and negative preference. for rare events, weapply the probability of random occurrence in order toreduce noise effects caused by data sparseness. paretodistribution is adopted for the random occurrenceprobability. we also present the method for combininginformation of joint feature variables in different sizes bydynamic weighting using random occurrence probability.
fast and exact out-of-core k-means clustering. clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. k-means requires several passes on the entire dataset, which can make it very expensive for large disk-resident datasets. in view of this, a lot of work has been done on various approximate versions of k-means, which require only one or a small number of passes on the entire dataset. in this paper, we present a new algorithm which typically requires only one or a small numberof passes on the entire dataset, and provably produces the same cluster centers as reported by the original k-means algorithm. the algorithm uses sampling to create initial cluster centers, and then takes one or more passes over the entire dataset to adjust these cluster centers. we provide theoretical analysis to show that the cluster centers thus reported are the same as the ones computed by the original k-means algorithm. experimental results from a number of real and synthetic datasets show speedup between a factor of 2 and 4.5, as compared to k-means.
an agglomerative hierarchical clustering using partial maximum array and incremental similarity computation method. as the tractable amount of data is growing in computer science area, fast clustering algorithm is being required because traditional clustering algorithms are not so feasible for very large and high dimensional data. many studies have been reported for clustering of large database, but most of them circumvent this problem by using the approximation method to result in thedeterioration of accuracy. in this paper, we propose a new clustering algorithm by means of partial maximum array, which can realize the agglomerative hierarchical clustering with the same accuracy to the brute-force algorithm and has o(n 2 ) time complexity. and we alsopresent the incremental method of similarity computation which substitutes the scalar calculation for the time-consuming calculation of vector similarity. the experimental results show that clustering becomes significantly fast for large and high dimensional data.
efficiently mining maximal frequent itemsets. we present genmax, a backtrack search based algorithm for mining maximal frequent itemsets. genmax uses a number of optimizations to prune the search space.it usesa novel technique called progressive focusing to perform maximality checking, and diffset propagation to perform fast frequency computation. systematic experimental comparison with previous work indicates that different methods have varying strengths and weaknesses based on dataset characteristics. we found genmax to be a highly efficient method to mine the exact set of maximal patterns.
stability of feature selection algorithms. with the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. strangely, despite extensive work on the stability of learning algorithms, the stability of feature selection algorithms has been relatively neglected. this study is an attempt to fill that gap by quantifying the sensitivity of feature selection algorithms to variations in the training set. we assess the stability of feature selection algorithms based on the stability of the feature preferences that they express in the form of weights-scores, ranks, or a selected feature subset. we examine a number of measures to quantify the stability of feature preferences and propose an empirical way to estimate them. we perform a series of experiments with several feature selection algorithms on a set of proteomics datasets. the experiments allow us to explore the merits of each stability measure and create stability profiles of the feature selection algorithms. finally we show how stability profiles can support the choice of a feature selection algorithm.
mining frequent itemsets from secondary memory. mining frequent itemsets is at the core of mining association rules, and is by now quite well understood algorithmically for main memory databases. in this paper, we investigate approaches to mining frequent itemsets when the database or the data structures used in the mining are too large to fit in main memory. experimental results show that our techniques reduce the required disk accesses by orders of magnitude, and enable truly scalable data mining.
distance measures for effective clustering of arima time-series. many environmental and socioeconomic time-series data can be adequately modeled using auto-regressiveintegrated moving average (arima) models. we call such time-series arima time-series. we consider the problem of clustering arima time-series. we propose the use of the linear predictive coding (lpc) cepstrum of time-series for clustering arima time-series, by using the euclideandistance between the lpc cepstra of two time-series as their dissimilarity measure. we demonstrate that lpc cepstral coefficients have the desire features for accurate clustering and efficient indexing of arima time-series. for example, few lpc cepstral coefficients are sufficient in order todiscriminate between time-series that are modeled by different arima models. in fact this approach requires fewer coefficients than traditional approaches, such as dft and dwt. the proposed distance measure can be use for measuring the similarity between different arima models as well.we cluster arima time-series using the partition around medoids method with various similarity measures. we present experimental results demonstrating that using the proposed measure we achieve significantly betterclusterings of arima time-series data as compared to clusterings obtained by using other traditional similaritymeasures, such as dft, dwt, pca, etc. experiments wereperformed both on simulated as well as real data.
the diasdem framework for converting domain-specific texts into xml documents with data mining techniques. modern organizations are accumulating huge volumesof textual documents. to turn archives into valuable know-ledge sources, textual content must become explicit andqueryable. semantic tagging with markup languages suchas xml satisfies both requirements. we thus introduce thediasdem* framework for extra ting semantics from structural text units (e.g., sentences), assigning xml tags to them and deriving a flat xml dtd for the archive. diasdem focuses on archives characterized by a peculiar terminologyand by an implicit structure such as court filings and company reports. in the knowledge discovery phase, text units are iteratively clustered by similarity of their content. eachiteration outputs clusters satisfying a set of quality criteria.text units contained in these clusters are tagged with semi-automatically determined luster labels and xml tags respectively. additionally, extracted named entities (e.g.,per-sons) serve as attributes of xml tags. we apply the frame-work in a case study on the german commercial register.
learning from order examples. we advocate a new learning task that deals with ordersof items, and we call this the learning from order examples(loe) task. the aim of the task is to acquire the rule thatis used for estimating the proper order of a given unordereditem set. the rule is acquired from training examples thatare ordered item sets. we present several solution methodsfor this task, and evaluate the performance and the characteristicsof these methods based on the experimental resultsof tests using both artificial data and realistic data.
a bayesian framework for regularized svm parameter estimation. the support vector machine (svm) is considered here in the context of pattern classification. the emphasis is on the soft margin classifier which uses regularization to handle non-separable learning samples. we present an svm parameter estimation algorithm that first identifies a subset of the learning samples that we call the support set and then determines not only the weights of the classifier but also the hyperparameter that controls the influence of the regularizing penalty term on basis thereof. we provide numerical results using several data sets from the public domain.
filling-in missing objects in orders. filling-in techniques are important, since missing values frequently appear in real data. such techniques have been established for categorical or numerical values. though lists of ordered objects are widely used as representational forms (e.g., web search results, best-seller lists), filling-in techniques for orders have received little attention. we therefore propose a simple but effective technique to fill-in missing objects in orders. we built this technique into our collaborative filtering system.
an algebraic approach to data mining: some examples. in this paper, we introduce an algebraic approach tothe foundations of data mining. our approach is basedupon two algebras of functions defined over a commonstate space x and a pairing between them.one algebra is an algebra of state space observations, and the other is an algebra of labeled sets ofstates.we interpret h as the algebraic encoding of the dataand the pairing as the misclassification rate when theclassifer f is applied to the set of states x.in this paper, we give a realization theorem givingconditions on formal series of data sets built from dthat imply there is a realization involving a state spacex, a classifier f \in r and a set of labeled states x \in r_0that yield this series.
supervised ordering - an empirical survey. ordered lists of objects are widely used as representational forms. such ordered objects include web search results or bestseller lists. in spite of their importance, methods of processing orders have received little attention. however, research concerning orders has recently become common; in particular, researchers have developed various methods for the task of supervised ordering to acquire functions for object sorting from example orders. here, we give a unified view of these methods and our new one, and empirically survey their merits and demerits.
the rough set approach to association rule mining. in transaction processing, an association is said to existbetween two sets of items when a transaction containingone set is likely to also contain the other. in informationretrieval, an association between two sets of keywords occurswhen they co-occur in a document. similarly, in datamining, an association occurs when one attribute set occurstogether with another. as the number of such associationsmay be large, maximal association rules are sought, e.g.,feldman et al (1997, 1998).rough set theory is a successful tool for data mining. byusing this theory, rules similar to maximal associations canbe found. however, we show that the rough set approach todiscovering knowledge is much simpler than the maximalassociation method.
svm based models for predicting foreign currency exchange rates. support vector machine (svm) has appeared as a powerfultool for forecasting forex market and demonstrated betterperformance over other methods, e.g., neural network orarima based model. svm-based forecasting modelnecessitates the selection of appropriate kernel function andvalues of free parameters: regularization parameter and \varepsilon-insensitive loss function. in this paper, we investigate the effectof different kernel functions, namely, linear, polynomial, radialbasis and spline on prediction error measured by several widelyused performance metrics. the effect of regularizationparameter is also studied. the prediction of six different foreigncurrency exchange rates against australian dollar has beenperformed and analyzed. some interesting results are presented.
predicting distribution of a new forest disease using one-class svms. in california, a newly discovered virulent pathogen(phytophthora ramorum) has killed thousands of nativeoak trees. mapping the potential distribution of thepathogen is essential for decision makers to assess therisk of the pathogen and aid in preventing its furtherspread. most methods used to map potential ranges ofspecies (e.g. multivariate or logistic regression) requireboth presence and absence data, the latter of which is notalways feasibly collected. in this study, we present theone-class support vector machine (svm) to predict thepotential distribution of sudden oak death in california.the model was developed using presence data collectedthroughout the state, and tested for accuracy using a 5-fold cross-validation approach. the model performedwell, and provided 91% predicted accuracy. we believeone-class svm when coupled with geographicalinformation systems (gis) will become a very usefulmethod to deal with presence-only data in ecologicalanalysis over a range of scales.
categorization and keyword identification of unlabeled documents. in this paper we first propose a global unsupervised feature selection approach for text, based on frequent itemset mining. as a result, each document is represented as a set of words that co-occur frequently in the given corpus of documents. we then introduce a locally adaptive clustering algorithm, designed to estimate (local) word relevance and, simultaneously, to group the documents. we present experimental results to demonstrate the feasibility of our approach. furthermore, the analysis of the weights credited to terms provides evidence that the identified keywords can guide the process of label assignment to clusters. we take into consideration both spam email filtering and general classification datasets. our analysis of the distribution of weights in the two cases provides insights on how the spam problem distinguishes from the general classification case.
understanding helicoverpa armigera pest population dynamics related to chickpea crop using neural networks. insect pests are a major cause of crop loss globally. pestmanagement will be effective and efficient if we canpredict the occurrence of peak activities of a given pest.research efforts are going on to understand the pestdynamics by applying analytical and other techniques onpest surveillance data sets. in this study we make an effortto understand pest population dynamics using neuralnetworks by analyzing pest surveillance data set ofhelicoverpa armigera or pod borer on chickpea (cicerarietinum l.) crop. the results show that neural networkmethod successfully predicts the pest attack incidences forone week in advance.
generation of attribute value taxonomies from data for data-driven construction of accurate and compact classifiers. attribute value taxonomies (avt) have been shown to be useful in constructing compact, robust, and comprehensible classifiers. however, in many application domains, human-designed avts are unavailable. we introduce avt-learner, an algorithm for automated construction of attribute value taxonomies from data. avt-learner uses hierarchical agglomerative clustering (hac) to cluster attribute values based on the distribution of classes that co-occur with the values. we describe experiments on uci data sets that compare the performance of avt-nbl (an avt-guided naive bayes learner) with that of the standard naive bayes learner (nbl) applied to the original data set. our results show that the avts generated by avt-learner are competitive with human-generated avts (in cases where such avts are available). avt-nbl using avts generated by avt-learner achieves classification accuracies that are comparable to or higher than those obtained by nbl; and the resulting classifiers are significantly more compact than those generated by nbl.
a scalable algorithm for clustering sequential data. in recent years, we have seen an enormous growth in the amount of available commercial and scientific data. data from domains such as protein sequences, retail transactions, intrusion detection, and web-logs have an inherent sequential nature. clustering of such data sets is usefulfor various purposes. for example, clustering of sequences from commercialdata sets may help marketer identify different customer groups based upon their purchasing patterns. grouping protein sequences that share similar structure helps in identifying sequences with similar functionality. over the years, many methods have been developed for clustering objects according to their similarity. however these methods tend to have a computational complexity that is at least quadratic on the number of sequences. in this paperwe present an entirely different approach to sequence clustering that does not require an all-against-all analysis and uses a nearlinear complexity k-means based clustering algorithm. our experiments using data sets derived from sequences of purchasing transactions and protein sequences show that this approach is scalable and leads to reasonably good clusters.
semi-supervised mixture-of-experts classification. we introduce a mixture-of-experts technique that is a generalization of mixture modeling techniques previously suggested for semi-supervised learning. we apply the bias-variance decomposition to semi-supervised classification and use the decomposition to study the effects from adding unlabeled data when learning a mixture model. our empirical results indicate that the biggest gain from adding unlabeled data comes from the reduction of the model variance, whereas the behavior of the bias error term heavily depends on the correctness of the underlying model assumptions.
reliable detection of episodes in event sequences. suppose one wants to detect "bad" or "suspicious" subsequencesin event sequences.whether an observed patternof activity (in the form of a particular subsequence) is significantand should be a cause for alarm, depends on howlikely it is to occur fortuitously.a long enough sequenceof observed events will almost certainly contain any subsequence,and setting thresholds for alarm is an important issuein a monitoring system that seeks to avoid false alarms.suppose a long sequence t of observed events contains asuspicious subsequence pattern s within it, where the suspicioussubsequence s consists of m events and spans a windowof size w within t.we address the fundamental problem:is a certain number of occurrences of a particular subsequenceunlikely to be fortuitous (i.e., indicative of suspiciousactivity)?if the probability of fortuitous occurrencesis high and an automated monitoring system flags it as suspiciousanyway, then such a system will suffer from generatingtoo many false alarms.this paper quantifies the probabilityof such an s occuring in t within a window of sizew, the number of distinct windows containing s as a subsequence,the expected number of such occurrences, its variance,and establishes its limiting distribution that allows toset up an alarm threshold so that the probability of falsealarms is very small.we report on experiments confirmingthe theory and showing that we can detect bad subsequenceswith low false alarm rate.
orthogonal decision trees. this paper introduces orthogonal decision trees that offer an effective way to construct a redundancy-free, accurate, and meaningful representation of large decision-tree-ensembles often created by popular techniques such as bagging, boosting, random forests and many distributed and data stream mining algorithms. orthogonal decision trees are functionally orthogonal to each other and they correspond to the principal components of the underlying function space. this paper offers a technique to construct such trees based on eigen-analysis of the ensemble and offers experimental results to document the performance of orthogonal trees on grounds of accuracy and model complexity.
unimodal segmentation of sequences. we study the problem of segmenting a sequence into k pieces so that the resulting segmentation satisfies monotonicity or unimodality constraints. unimodal functions can be used to model phenomena in which a measured variable first increases to a certain level and then decreases. we combine a well-known unimodal regression algorithm with a simple dynamic-programming approach to obtain an optimal quadratic-time algorithm for the problem of unimodal k-segmentation. in addition, we describe a more efficient greedy-merging heuristic that is experimentally shown to give solutions very close to the optimal. as a concrete application of our algorithms, we describe two methods for testing if a sequence behaves unimodally or not. our experimental evaluation shows that our algorithms and the proposed unimodality tests give very intuitive results.
on the privacy preserving properties of random data perturbation techniques. privacy is becoming an increasingly important issue inmany data mining applications. this has triggered the developmentof many privacy-preserving data mining techniques.a large fraction of them use randomized data distortiontechniques to mask the data for preserving the privacyof sensitive data. this methodology attempts to hidethe sensitive data by randomly modifying the data values oftenusing additive noise. this paper questions the utility ofthe random value distortion technique in privacy preservation.the paper notes that random objects (particularly randommatrices) have "predictable" structures in the spectraldomain and it develops a random matrix-based spectral filteringtechnique to retrieve original data from the datasetdistorted by adding random values. the paper presents thetheoretical foundation of this filtering method and extensiveexperimental results to demonstrate that in many cases randomdata distortion preserve very little data privacy. thepaper also points out possible avenues for the developmentof new privacy-preserving data mining techniques like exploitingmultiplicative and colored noise for preserving privacyin data mining applications.
a framework for semi-supervised learning based on subjective and objective clustering criteria. in this paper, we propose a semi-supervised framework for learning a weighted euclidean subspace, where the best clustering can be achieved. our approach capitalizes on user-constraints and the quality of intermediate clustering results in terms of its structural properties. it uses the clustering algorithm and the validity measure as parameters.
mining decision trees from data streams in a mobile environment. this paper presents a novel fourier analysis-based technique toaggregate, communicate, and visualize decision trees in a mobile environment. fourier representation of a decision tree has several useful properties that are particularly useful for mining continuous data streams from small mobile computing devices. this paper presents algorithms to compute the fourier spectrum of a decision tree and the vice versa. it offers a framework to aggregate decision trees in their fourier representations. it a so describes atouch-pad/ticker-based approach to visualize decision trees using their fourier spectrum and an implementation for pdas..
clustering validity assessment: finding the optimal partitioning of a data set. clustering s a mostly unsupervised procedure and the majority of the clustering algorithms depend on certain assumptions in order to define the subgroups present in a data set. as a consequence, in most applications the resulting clustering scheme requires some sort ofevaluation as regards its validity. in this paper we present a clustering validity procedure,which evaluates the results of clustering algorithms on data sets. we define a validity index, s_dbw, based on well-defined clustering criteria enabling the selection of the optimal input parameters' values for a clustering algorithm that result in the best partitioning of a data set.we evaluate the reliability of our index both theoretically and experimentally, considering three representative clustering algorithms ran on synthetic and real data sets. also, we carried out an evaluation study to compare s_dbw performance with other known validity indices.our approach performed favorably in all cases, even in those that other indices failed to indicate the correct partitions in a data set.
gradual model generator for single-pass clustering. we present an algorithm for generating a mixture model from a data set by converting the data into a model. the method is applicable when only part of the data fits in the main memory at the same time. the generated model is a gaussian mixture model but the algorithm can be adapted to other types of models, too. the user cannot specify the size of the generated model. we also introduce a post-processing method, which can reduce the size of the model without using the original data. this will result in a more compact model with fewer components, but with approximately the same representation accuracy as the original model. our comparisons show that the algorithm produces good results and is quite efficient. the whole process requires only 0.5-10% of the time spent by the expectation-maximization algorithm.
comparing pure parallel ensemble creation techniques against bagging. we experimentally evaluate randomization-based approachesto creating an ensemble of decision-tree classifiers.unlike methods related to boosting, all of the eightapproaches considered here create each classifier in an ensembleindependently of the other classifiers. experimentswere performed on 28 publicly available datasets, usingc4.5 release 8 as the base classifier. while each of the otherseven approaches has some strengths, we find that none ofthem is consistently more accurate than standard baggingwhen tested for statistical significance.
facilitating fuzzy association rules mining by using multi-objective genetic algorithms for automated clustering. in this paper, we propose an automated clustering methodbased on multi-objective genetic algorithms (ga); the aim ofthis method is to automatically cluster values of a givenquantitative attribute to obtain large number of largeitemsets in low duration (time). we compare the proposedmulti-objective ga-based approach with cure-basedapproach. in addition to the autonomous specification offuzzy sets, experimental results showed that the proposedautomated clustering exhibits good performance overcure-based approach in terms of runtime as well as thenumber of large itemsets and interesting association rules.
phrase-based document similarity based on an index graph model. document clustering techniques mostly rely on singleterm analysis of the document data set, such as the vectorspace model. to better capture the structure of documents,the underlying data model should be able to represent thephrases in the document as well as single terms. we presenta novel data model, the document index graph, which indexesweb documents based on phrases, rather than singleterms only. the semi-structured web documents helpin identifying potential phrases that when matched withother documents indicate strong similarity between the documents.the document index graph captures this informa-tion,and finding significant matching phrases between documentsbecomes easy and efficient with such model. thesimilarity between documents is based on both single termweights and matching phrases weights. the combined similaritiesare used with standard document clustering techniquesto test their effect on the clustering quality. experimentalresults show that our phrase-based similarity, combinedwith single-term similarity measures, enhances webdocument clustering quality significantly.
query-driven support pattern discovery for classification learning. we propose a novel query-driven lazy learning algorithm which attempts to discover useful local patterns, called support patterns, for classifying a given query. the learning is customized to the query to avoid the horizon effect. we show that this query-driven learning algorithm can guarantee to discover all support patterns with perfect expected accuracy in polynomial time. the experimental results on benchmark data sets also demonstrate that our learning algorithm really has prominent learning performance.
pixelmaps: a new visual data mining approach for analyzing large spatial data sets. pixelmaps are a new pixel-oriented visual data miningtechnique for large spatial datasets. they combine kernel-density-based clustering with pixel-oriented displays to emphasizeclusters while avoiding overlap in locally densepoint sets on maps. because a full evaluation of densityfunctions is prohibitively expensive, we also propose an efficientapproximation, fast-pixelmap, based on a synthesisof the quadtree and gridfile data structures.
mining top-k frequent closed patterns without minimum support. in this paper, we propose a new mining task: mining top-kfrequent closed patterns of length no less than min_l, wherek is the desired number of frequent closed patterns to bemined, and min _l is the minimal length of each pattern.an efficient algorithm, called tfp, is developed for mining such patterns without minimum support. two methods, closed_node_count and descendant_sum are proposedto effiectively raise support threshold and prune fp-tree bothduring and after the construction of fp-tree. during themining process, a novel top-down and bottom-up combinedfp-tree mining strategy is developed to speed-up support-raising and closed frequent pattern discovering. in addition,a fast hash-based closed pattern verification scheme has beenemployed to check efficiently if a potential closed pattern isreally closed.our performance study shows that in most cases, tfpoutperforms closet and charm, two efficient frequentclosed pattern mining algorithms, even when both are running with the best tuned min_support. furthermore, themethod can be extended to generate association rules andto incorporate user-specified constraints. thus we concludethat for frequent pattern mining, mining top-k frequent closedpatterns without min support is more preferable than thetraditional min_support-based mining.
an online algorithm for segmenting time series. in recent years, there has been an explosion of interest in mining time series databases. as with most computer science problems, representation of the data is the key to efficient and effective solutions. one of the most commonly used representations is piecewise linear approximation. this representation has been used by various researchers to support clustering, classification, indexing and association rule mining of t me series data. a variety of algorithms have been proposed to obtain this representation, with several algorithms having been independently rediscovered several times. in this paper, we undertake the first extensive review and empirical comparison of all proposed techniques. we show that allthese algorithms have fatal flaws from a data mining perspective. we introduce a novel algorithm that we empirically show to be super or to all others n the literature.
discovering representative episodal association rules from event sequences using frequent closed episode sets and event constraints. discovering association rules from time-series data is an important data mining problem. the number of potential rules grows quickly as the number of items in the antecedent grows. it is therefore difficult for an expert to analyze the rules and identify the useful. an approach for generating representative association rules for transactions that uses only a subset of the set of frequent itemsets called frequent closed itemsets was presented in [6 ]. we employ formalconcept analysis to develop the notion of frequent closed episodes. the concept of representative association rules is formalized in the context of event sequences. applying constraints to target highly significant rules further reduces the number of rules. our approach results in a significant reduction of the number of rules generated, while maintaining the minimum set of relevant association rules and retaining the ability to generate the entire set of association rules with respect to the given constraints. we show how our method can be used to discover associations in a drought risk management decision support system and use multiple climatology datasets related to automated weather stations1
hot sax: efficiently finding the most unusual time series subsequence. in this work, we introduce the new problem of finding time series discords. time series discords are subsequences of a longer time series that are maximally different to all the rest of the time series subsequences. they thus capture the sense of the most unusual subsequence within a time series. time series discords have many uses for data mining, including improving the quality of clustering, data cleaning, summarization, and anomaly detection. as we will show, discords are particularly attractive as anomaly detectors because they only require one intuitive parameter (the length of the subsequence) unlike most anomaly detection algorithms that typically require many parameters. we evaluate our work with a comprehensive set of experiments. in particular, we demonstrate the utility of discords with objective experiments on domains as diverse as space shuttle telemetry monitoring, medicine, surveillance, and industry, and we demonstrate the effectiveness of our discord discovery algorithm with more than one million experiments, on 82 different datasets from diverse domains.
automatic topic identification using webpage clustering. grouping webpage into distinct topics is one way to organize the large amount of retrieved information on the web. in this paper, we report that based on similaritymetric which incorporates textual information, hyperlinkstructure and co-citation relations, an unsupervised clustering method can automatically and effectively identify relevant topics, a shown in experiments on several retrieved sets of webpages. the clustering method is a state-of-art spectral graph partitioning method based on normalized cutcriterion first developed for image segmentation.
clustering of time series subsequences is meaningless: implications for previous and future research. time series data is perhaps the most frequently encountered typeof data examined by the data mining community. clustering isperhaps the most frequently used data mining algorithm, beinguseful in it's own right as an exploratory technique, and also as asubroutine in more complex data mining algorithms such as rulediscovery, indexing, summarization, anomaly detection, andclassification. given these two facts, it is hardly surprising thattime series clustering has attracted much attention. the data to beclustered can be in one of two formats: many individual timeseries, or a single time series, from which individual time seriesare extracted with a sliding window. given the recent explosion ofinterest in streaming data and online algorithms, the latter casehas received much attention.in this work we make an amazing claim. clustering of streamingtime series is completely meaningless. more concretely, clustersextracted from streaming time series are forced to obey a certainconstraint that is pathologically unlikely to be satisfied by anydataset, and because of this, the clusters extracted by anyclustering algorithm are essentially random. while this constraintcan be intuitively demonstrated with a simple illustration and issimple to prove, it has never appeared in the literature.we can justify calling our claim surprising, since it invalidatesthe contribution of dozens of previously published papers. we willjustify our claim with a theorem, illustrative examples, and acomprehensive set of experiments on reimplementations ofprevious work.
improving home automation by discovering regularly occurring device usage patterns. the data stream captured by recording inhabitant-deviceinteractions in an environment can be mined todiscover significant patterns, which an intelligent agentcould use to automate device interactions. however, thisknowledge discovery problem is complicated by severalchallenges, such as excessive noise in the data, data thatdoes not naturally exist as transactions, a need tooperate in real time, and a domain where frequency maynot be the best discriminator. in this paper, we propose anovel data mining technique that addresses thesechallenges and discovers regularly-occurringinteractions with a smart home. we also discuss a casestudy that shows the data mining technique can improvethe accuracy of two prediction algorithms, thusdemonstrating multiple uses for a home automationsystem. finally, we present an analysis of the algorithmand results obtained using inhabitant interactions.
feature-based prediction of unknown preferences for nearest-neighbor collaborative filtering. recommendation systems analyze user preferences and recommend items to a user by predicting the user's preference for those items.among various kinds of recommendation methods, collaborative filtering (cf) has been widely used and successfully applied to practical applications.however, collaborative filtering has two inherent problems: data sparseness and the cold-start problems.in this paper, we propose a method of integrating additional feature information of users and items into cf to overcome the difficulties caused by sparseness and improve the accuracy of recommendation. several experimental results that show the effectiveness of the proposed method are also presented.
amiot: induced ordered tree mining in tree-structured databases. frequent subtree mining has become increasingly important in recent years. in this paper, we present amiot algorithm to discover all frequent ordered subtrees in a tree-structured database. in order to avoid the generation of infrequent candidate trees, we propose the techniques such as right-and-left tree join and serial tree extension. proposed methods enumerate only the candidate trees with high probability of being frequent without any duplications. the experiments on synthetic dataset and xml database show that amiot reduces redundant candidate trees and outperforms freqt algorithm by up to five times in execution time.
aine: an immunological approach to data mining. an investigation has been undertaken to repeat previous work on an artificial immune system for data analysis called aine (artificial immune network).the previous work was limited to testing the algorithm on relatively small data sets. the aim of this investigation is two fold,firstly to corroborate the results presented in previous work and secondly, to test the algorithm on a larger and more complex data set. a new re-implementation of aine is then described and differences in behaviour are identified and explained. it is argued that the behaviourseen in the new implementation is more accurate than that seen in previous work and an in-depth analysis of the algorithm structure is undertaken in order to confirm theseobservations. the algorithm is also tested on new data and the results of this are presented. comparisons are draw with other similar techniques for data mining and it is argued that aine is an effective data-mining algorithm.
dependencies between transcription factor binding sites: comparison between ica, nmf, plsa and frequent sets. gene expression of eucaryotes is regulated through transcription factors, which are molecules able to attach to the binding sites in the dna sequence. these binding sites are small pieces of dna usually found upstream from the gene they regulate. as the binding sites play an important role in the gene expression, it is of interest to find out their characteristics. in this paper we look for dependencies and independencies between these binding sites using independent component analysis (ica), non-negative matrix factorization (nmf), probabilistic latent semantic analysis (plsa) and the method of frequent sets. the data used are human gene upstream regions and possible binding sites listed in a biological database. also, results on the baker's yeast (s.cerevisiae) upstream regions are briefly discussed for comparison. ica, nmf and plsa are latent variable methods that decompose the observed data into smaller components. of these, ica and nmf were originally aimed for continuous data. we show that these methods can be successfully used on discrete dna data as well. plsa and the method of frequent sets were created for discrete data sets. the above methods reveal partially overlapping sets of possible binding sites such that the binding sites within a set are dependent of each other. the methods of frequent sets and nmf give a good overview of the most common data structures, whereas using ica and plsa we find large sets that are surprisingly frequent. that is, sets of very frequently occurring possible binding sites can be found near hundreds or thousands of genes; also interesting but less frequent ones co-occur surprisingly often.
orthogonal neighborhood preserving projections. orthogonal neighborhood preserving projections (onpp) is a linear dimensionality reduction technique which attempts to preserve both the intrinsic neighborhood geometry of the data samples and the global geometry. the proposed technique constructs a weighted data graph where the weights are constructed in a data-driven fashion, similarly to locally linear embedding (lle). a major difference with the standard lle where the mapping between the input and the reduced spaces is implicit, is that onpp employs an explicit linear mapping between the two. as a result, and in contrast with lle, handling new data samples becomes straightforward, as this amounts to a simple linear transformation. onpp shares some of the properties of locality preserving projections (lpp). both onpp and lpp rely on a k-nearest neighbor graph in order to capture the data topology. however, our algorithm inherits the characteristics of lle in preserving the structure of local neighborhoods, while lpp aims at preserving only locality without specifically aiming at preserving the geometric structure. this feature makes onpp an effective method for data visualization. we provide ample experimental evidence to demonstrate the advantageous characteristics of onpp, using well known synthetic test cases as well as real life data from computational biology and computer vision.
focused community discovery. we present a new approach to community discovery. community discovery usually partitions the graph into communities or clusters. focused community discovery allows the searcher to specify start points of interest, and find the community of those points. focused search allows for a much more scalable algorithm in which the time depends only on the size of the community, and not on the number of nodes in the graph, and so is scalable to arbitrarily large graphs. furthermore, our algorithm is robust to imperfect data, such as extra or missing edges in the graph. we show the effectiveness of our algorithm using both synthetic graphs and on the real-life livejournal friends graph, a publicly-available social network consisting of over two million users and 13 million edges.
higher-order web link analysis using multilinear algebra. linear algebra is a powerful and proven tool in web search. techniques, such as the pagerank algorithm of brin and page and the hits algorithm of kleinberg, score web pages based on the principal eigenvector (or singular vector) of a particular non-negative matrix that captures the hyperlink structure of the web graph. we propose and test a new methodology that uses multilinear algebra to elicit more information from a higher-order representation of the hyperlink graph. we start by labeling the edges in our graph with the anchor text of the hyperlinks so that the associated linear algebra representation is a sparse, three-way tensor. the first two dimensions of the tensor represent the web pages while the third dimension adds the anchor text. we then use the rank-1 factors of a multilinear parafac tensor decomposition, which are akin to singular vectors of the svd, to automatically identify topics in the collection along with the associated authoritative web pages.
time series segmentation for context recognition in mobile devices. recognizing the context of se is important in making mobile devices as simple to use as possible. finding out what the user's situation is can help the device andunderlying service in providing an adaptive and personalized user interface. the device can infer parts of the context of the user from sensor data: the mobile device can includesensors for acceleration, noise level, luminosity, humidity, etc. in this paper we consider context recognition by unsupervisedsegmentation of time series produced by sensors.dynamic programming can be used to find segments that minimize the intra-segment variances. while this method produces optimal solutions, it is too slow for long sequencesof data. we present and analyze randomized variations of the algorithm. one of them, global iterative replacement or gir, gives approximately optimal results in a fraction of the time required by dynamic programming. wedemonstrate the se of time series segmentation in contextrecognition for mobile phone applications.
dynamic weighted majority: a new ensemble method for tracking concept drift. algorithms for tracking concept drift are important formany applications. we present a general method basedon the weighted majority algorithm for using any on-linelearner for concept drift. dynamic weighted majority(dwm) maintains an ensemble of base learners, predictsusing a weighted-majority vote of these "experts",and dynamically creates and deletes experts in response tochanges in performance. we empirically evaluated two experimentalsystems based on the method using incrementalnaive bayes and incremental tree inducer (iti) as experts.for the sake of comparison, we also included blum's implementationof weighted majority. on the stagger conceptsand on the sea concepts, results suggest that the ensemblemethod learns drifting concepts almost as well as the basealgorithms learn each concept individually. indeed, we reportthe best overall results for these problems to date.
suppressing data sets to prevent discovery of association rules. enterprises have been collecting data for many reasons including better customer relationship management, and high-level decision making. public safety was another motivation for large-scale data collection efforts initiated by government agencies. however, such widespread data collection efforts coupled with powerful data analysis tools raised concerns about privacy. this is due to the fact that collected data may contain confidential information. one method to ensure privacy is to selectively hide confidential information from the data sets to be disclosed. in this paper, we focus on hiding confidential correlations. we introduce a heuristic to reduce the information loss and propose a blocking method that prevents discovery of confidential correlations while preserving the usefulness of the data set.
making logistic regression a core data mining tool with tr-irls. binary classification is a core data mining task. for large datasets or real-time applications, desirable classifiersare accurate, fast, and need no parameter tuning. we present a simple implementation of logistic regression that meets these requirements. a combination of regularization, truncated newton methods, and iteratively re-weighted least squares make it faster and more accurate than modern svm implementations, and relatively insensitive to parameters. it is robust to linear dependencies and some scaling problems, making most data preprocessing unnecessary.
indiscernibility degree of objects for evaluating simplicity of knowledge in the clustering procedure. this paper presents a new, rough sets-based clusteringmethod that enables evaluation of simplicity of classification knowledge during the clustering procedure. the method iteratively refines equivalence relations so that they become more simple set of relations that give adequately coarse classification to the objects. at each step ofiteration, importance of the equivalence relation is evaluated on the basis of the newly introduced measure, indiscernibility degree. an indiscernibility degree is defined as a ratio of equivalence relations that classify the two objects into the same equivalence class. if an equivalence relation hasability to discern the two objects that have high indiscernibility degree, it is considered to perform too fine classification and then modified to regard them as indiscernible objects. the refinement is repeated decreasing the threshold level ofindiscernibility degree, and finally simple clusters can beobtained. experimental results on the artificial data showed that iterative refinement of equivalence relation lead tosuccessful generation of coarse clusters that can be representedby simple knowledge.
recognition of common areas in a web page using visual information: a possible application in a page classification. extracting and processing information from webpages is an important task in many areas likeconstructing search engines, information retrieval, anddata mining from the web. common approach in theextraction process is to represent a page as a "bag ofwords" and then to perform additional processing onsuch a flat representation. in this paper we propose anew, hierarchical representation that includes browserscreen coordinates for every html object in a page.using visual information one is able to define heuristicsfor the recognition of common page areas such asheader, left and right menu, footer and center of a page.we show in initial experiments that using our heuristicsdefined objects are recognized properly in 73% of cases.finally, we show that a naive bayes classifier, takinginto account the proposed representation, clearlyoutperforms the same classifier using only informationabout the content of documents.
mining similar temporal patterns in long time-series data and its application to medicine. data mining in time-series medical databases has beenreceiving considerable attention since it provides a way ofrevealing useful information hidden in the database; forexample relationships between temporal course of examinationresults and onset time of diseases. this paperpresents a new method for finding similar patterns in temporalsequences. the method is a hybridization of phase-constraintmultiscale matching and rough clustering. multiscalematching enables us cross-scale comparison of thesequences, namely, it enable us to compare temporal patternsby partially changing observation scales. rough clusteringenable us to construct interpretable clusters of thesequences even if their similarities are given as relativesimilarities. we combine these methods and cluster the sequencesaccording to multiscale similarity of patterns. experimentalresults on the chronic hepatitis dataset showedthat clusters demonstrating interesting temporal patternswere successfully discovered.
text mining for a clear picture of defect reports: a praxis report. we applied the text mining categorization technology,in the publicly available, ibm enterprise informationportal v8.1 to more than 15,000 customer reported,product problem records. we used a proven softwarequality category set to categorize these problem recordsinto different areas of interest. our intent was to developa clear picture of potential areas for quality improvementin each of the software products reviewed, and to providethis information to development's management.the paper presents the benefits that can be gained fromcategorizing problem records, as well as the limitations.
wavelet based uxo detection. the detection and classification of unexploded ordnance(uxo) is considered a multi-dimensional pattern recognitionproblem. standard techniques in solving multi-dimensionaldetection and classification problems involveusing large sets of templates or libraries. this paper showsthat by using wavelet transformation a single library willallow a particular class of ordnance to be classified over arange of depths.
effective and efficient distributed model-based clustering. in many companies data is distributed among several sites, i.e. each site generates its own data and manages its own data repository. analyzing and mining these distributed sources requires distributed data mining techniques to find global patterns representing the complete information. the transmission of the entire local data set is often unacceptable because of performance considerations, privacy and security aspects, and bandwidth constraints. traditional data mining algorithms, demanding access to complete data, are not appropriate for distributed applications. thus, there is a need for distributed data mining algorithms in order to analyze and discover new knowledge in distributed environments. one of the most important data mining tasks is clustering which aims at detecting groups of similar data objects. in this paper, we propose a distributed model-based clustering algorithm that uses em for detecting local models in terms of mixtures of gaussian distributions. we propose an efficient and effective algorithm for deriving and merging these local gaussian distributions to generate a meaningful global model. in a broad experimental evaluation we show that our framework is scalable in a highly distributed environment.
ensemble modeling through multiplicative adjustment of class probability. we develop a new concept for aggregating items of evidencefor class probability estimation. in naïve bayes, eachfeature contributes an independent multiplicative factor tothe estimated class probability. we modify this model to includean exponent in each factor in order to introduce fea-tureimportance. these exponents are chosen to maximizethe accuracy of estimated class probabilities on the trainingdata. for naïve bayes, this modification accomplishes morethan what feature selection can. more generally, since theindividual features can be the outputs of separate probabilitymodels, this yields a new ensemble modeling approach,which we call apm (adjusted probability model), alongwith a regularized version called apmr.
a generic framework for efficient subspace clustering of high-dimensional data. subspace clustering has been investigated extensively since traditional clustering algorithms often fail to detect meaningful clusters in high-dimensional data spaces. many recently proposed subspace clustering methods suffer from two severe problems: first, the algorithms typically scale exponentially with the data dimensionality and/or the subspace dimensionality of the clusters. second, for performance reasons, many algorithms use a global density threshold for clustering, which is quite questionable since clusters in subspaces of significantly different dimensionality will most likely exhibt significantly varying densities. in this paper, we propose a generic framework to overcome these limitations. our framework is based on an efficient filter-refinement architecture that scales at most quadratic w.r.t. the data dimensionality and the dimensionality of the subspace clusters. it can be applied to any clustering notions including notions that are based on a local density threshold. a broad experimental evaluation on synthetic and real-world data empirically shows that our method achieves a significant gain of runtime and quality in comparison to state-of-the-art subspace clustering algorithms.
mining coverage-based fuzzy rules by evolutional computation. in this paper, we propose a novel mining approach based on the genetic process and an evaluation mechanism to automatically construct an effective fuzzy rule base. the proposed approach consists of three phases: fuzzy-rule generating, fuzzy-rule encoding and fuzzy-ruleevolution. in the fuzzy-rule generating phase, a number of fuzzy rules are randomly generated. in the fuzzy-rule encoding phase, all the rules generated are translated into fixed-length bit strings to form an initial population. in the fuzzy-rule evolution phase, genetic operations andcredit assignment are applied at the rule level. the proposed mining approach chooses good individuals in the population for mating, gradually creating better offspring fuzzy rules. a concise and compact fuzzy rule base is thus constructed effectively without human expertintervention.
hierarchical density-based clustering of uncertain data. the hierarchical density-based clustering algorithm optics has proven to help the user to get an overview over large data sets. when using optics for analyzing uncertain data which naturally occur in many emerging application areas, e.g. location based services, or sensor databases, the similarity between uncertain objects has to be expressed by one numerical distance value. based on such single-valued distance functions optics, like other standard data mining algorithms, can work without any changes. in this paper, we propose to express the similarity between two fuzzy objects by distance probability functions which assign a probability value to each possible distance value. contrary to the traditional approach, we do not extract aggregated values from the fuzzy distance functions but enhance optics so that it can exploit the full information provided by these functions. the resulting algorithm foptics helps the user to get an overview over a large set of fuzzy objects.
effectiveness of information extraction, multi-relational, and semi-supervised learning for predicting functional properties of genes. we focus on the problem of predicting functional propertiesof the proteins corresponding to genes in the yeastgenome. our goal is to study the effectiveness of approachesthat utilize all data sources that are availablein this problem setting, including unlabeled and relationaldata, and abstracts of research papers. we study transductionand co-training for using unlabeled data. we investigatea propositionalization approach which uses relationalgene interaction data. we study the benefit of informationextraction for utilizing a collection of scientific abstracts.the studied tasks are kdd cup tasks of 2001 and 2002.the solutions which we describe achieved the highest scorefor task 2 in 2001, the fourth rank for task 3 in 2001, thehighest score for one of the two subtasks and the third placefor the overall task 2 in 2002.
ontologies improve text document clustering. text document clustering plays an important role in providingintuitive navigation and browsing mechanisms by organizinglarge sets of documents into a small number ofmeaningful clusters. the bag of words representation usedfor these clustering methods is often unsatisfactory as it ignoresrelationships between important terms that do not co-occurliterally. in order to deal with the problem, we integratecore ontologies as background knowledge into theprocess of clustering text documents. our experimentalevaluations compare clustering techniques based on pre-categorizationsof texts from reuters newsfeeds and on asmaller domain of an elearning course about java. in theexperiments, improvements of results by background knowledgecompared to a baseline without background knowledgecan be shown in many interesting combinations.
concise representation of frequent patterns based on disjunction-free generators. many data mining problems require the discover of frequent patterns in order to be solved.frequent itemsets are useful in the discover of association rules, episode rules, sequential patterns and clusters. the number of frequent itemsets is usually huge. therefore, it is important to work out concise representations of frequent itemsets. in the paper, we describe three basic loassless representations of frequent patters in a uniform wayand offer a new lossless representation of frequent patterns based on disjunction-free generators. the new representation is more concisethan two of the basic representations and more efficiently computablethan the third representation. we propose an algorithm for the determining the new representation.
evolutionary algorithms for clustering gene-expression data. this work deals with the problem of automatically finding optimal partitions in bioinformatics datasets. we propose incremental improvements for a clustering genetic algorithm (cga), culminating in the evolutionary algorithm for clustering (eac). the cga and its modified versions are evaluated in five gene-expression datasets, showing that the proposed eac is a promising tool for clustering gene-expression data.
probabilistic noise identification and data cleaning. real world data is never as perfect as we would like itto be and can often suffer from corruptions that may impactinterpretations of the data, models created from thedata, and decisions made based on the data.one approachto this problem is to identify and remove records that containcorruptions.unfortunately, if only certain fields in arecord have been corrupted then usable, uncorrupted datawill be lost.in this paper we present lens, an approach foridentifying corrupted fields and using the remaining non-corruptedfields for subsequent modeling and analysis.ourapproach uses the data to learn a probabilistic model containingthree components: a generative model of the cleanrecords, a generative model of the noise values, and a probabilisticmodel of the corruption process.we provide an algorithmfor the unsupervised discovery of such models andempirically evaluate both its performance at detecting corruptedfields and, as one example application, the resultingimprovement this gives to a classifier.
the hybrid poisson aspect model for personalized shopping recommendation. predicting an individual customer's likelihood of purchasinga specific item forms the basis of many marketingactivities, such as personalized shopping recommendation.collaborative filtering and association rule miningcan be applied to this problem, but in retail supermarkets,the problem becomes particularly challenging because ofthe sparsity and skewness of transaction data. this paperpresents hypam(hybrid poisson aspect model), a newprobabilistic graphical model that combines a poisson mixturewith a latent aspect class model to model customers'shopping behavior. we empirically compare hypam withtwo well-known recommenders, grouplens (a correlation-basedmethod), and ibm smartpad (association rules andcosine similarity). experimental results show that hypamoutperforms the other recommenders by a large margin fortwo real-world retail supermarkets, ranking most of actualpurchases in the top ten percent of the most likely purchaseditems. we also present a new visualization method, rankplot, to evaluate the quality of recommendations.
tractable group detection on large link data sets. discovering underlying structure from co-occurrencedata is an important task in a variety of fields, including:insurance, intelligence, criminal investigation, epidemiology,human resources, and marketing.previously kubicaet. al. presented the group detection algorithm (gda) - analgorithm for finding underlying groupings of entities fromco-occurrence data.this algorithm is based on a probabilisticgenerative model and produces coherent groups thatare consistent with prior knowledge.unfortunately, the optimizationused in gda is slow, potentially making it infeasiblefor many large data sets.to this end, we present k-groups - an algorithm that uses an approach similar tothat of k-means to significantly acclerate the discovery ofgroups while retaining gda's probabilistic model.we comparethe performance of gda and k-groups on a variety ofdata, showing that k-groups' sacrifice in solution quality issignificantly offset by its increase in speed.
mining ratio rules via principal sparse non-negative matrix factorization. association rules are traditionally designed to capture statistical relationship among itemsets in a given database. to additionally capture the quantitative association knowledge, f.korn et al recently proposed a paradigm named ratio rules for quantifiable data mining. however, their approach is mainly based on principle component analysis (pca) and as a result, it cannot guarantee that the ratio coefficient is non-negative. this may lead to serious problems in the rules' application. in this paper, we propose a new method, called principal sparse non-negative matrix factorization (psnmf), for learning the associations between itemsets in the form of ratio rules. in addition, we provide a support measurement to weigh the importance of each rule for the entire dataset.
transduction and typicalness for quality assessment of individual classifications in machine learning and data mining. in the past machine learning algorithms have been successfully used in many problems, and are emerging as valuable data analysis tools. however, their serious practical use is affected by the fact, that more often than not, they cannot produce reliable and unbiased assessments of their predictions' quality. in last years, several approaches for estimating reliability or confidence of individual classifiers have emerged, many of them building upon the algorithmic theory of randomness, such as (historically ordered) transduction-based confidence estimation, typicalness-based confidence estimation, and transductive reliability estimation. unfortunately, they all have weaknesses: either they are tightly bound with particular learning algorithms, or the interpretation of reliability estimations is not always consistent with statistical confidence levels. in the paper we propose a joint approach that compensates the mentioned weaknesses by integrating typicalness-based confidence estimation and transductive reliability estimation into joint confidence machine. the resulting confidence machine produces confidence values in the statistical sense (e.g., a confidence level of 95% means that in 95% the predicted class is also a true class), as well as provides us with a general principle that is independent of to the particular underlying classifier we perform a series of tests with several different machine learning algorithms in several problem domains. we compare our results with that of a proprietary tcm-nn method as well as with kernel density estimation. we show that the proposed method significantly outperforms density estimation methods, and how it may be used to improve their performance.
efficient mining of frequent subgraphs in the presence of isomorphism. frequent subgraph mining is an active research topic inthe data mining community. a graph is a general modelto represent data and has been used in many domains likecheminformatics and bioinformatics. mining patterns fromgraph databases is challenging since graph related operations,such as subgraph testing, generally have higher timecomplexity than the corresponding operations on itemsets,sequences, and trees, which have been studied extensively.in this paper, we propose a novel frequent subgraph miningalgorithm: ffsm, which employs a vertical search schemewithin an algebraic graph framework we have developedto reduce the number of redundant candidates proposed.our empirical study on synthetic and real datasets demonstratesthat ffsm achieves a substantial performance gainover the current start-of-the-art subgraph mining algorithmgspan.
semi-supervised clustering with metric learning using relative comparisons. semi-supervised clustering algorithms partition a given data set using limited supervision from the user. in this paper, we propose a clustering algorithmthat uses supervision in terms of relative comparisons, viz., is closer to than to . the success of a clustering algorithm also depends on the kind of dissimilarity measure. the proposed clustering algorithm learns the underlying dissimilarity measure while finding compact clusters in the given data set. through our experimental studies on high-dimensional textual data sets, we demonstrate that the proposed algorithm achieves higher accuracy than the algorithms using pairwise constraints for supervision.
discovery of interesting association rules from livelink web log data. we present our experience in mining web usage patternsfrom a large collection of livelink log data. livelink is aweb-based product of open text, which provides automaticmanagement and retrieval of different types of informationobjects over an intranet or extranet. we report our experiencein preprocessing raw log data and post-processing themining results for finding interesting rules. in particular,we compare and evaluate a number of rule interestingnessmeasures and find that two of the measures that have notbeen used in association rule learning work very well.
mining the smallest association rule set for predictions. mining transaction databases for association rules usually generates a large number of rules, most of which are unnecessary when used for subsequent prediction. in this paper we define a rule set for a given transaction database that is much smaller than the association rule set but makes the same predictions as the association rule set by the confidence priority. we call this subset the informative rule set. the informative rule set is not constrained to particular target items; and it is smaller than the non-redundant association rule set. we present an algorithm to directly generate the informative rule set, i.e., without generating all frequentitemsets first, and that accesses the database less often than other unconstrained direct methods. we show experimentally that the informative rule set is much smaller than boththe association rule set and the non-redundant association rule set, and that it can be generated more efficiently.
mining temporal patterns without predefined time windows. this paper proposes algorithms for discovering temporal patterns without predefined time windows.the problem of discovering temporal patterns is divided into two sub-tasks: (1) using "cheap statistics" for dependence testing and candidates removal (2) identifying the temporal relationships between dependent event types.the dependence problem is formulated as the problem of comparing two probability distributions and is solved using a technique reminiscent of the distance methods used in spatial point process, while the latter problem is solved using an approach based on chi-squared tests.experiments are conducted to evalaute the effectiveness and scalability of the proposed methods.
mass spectrum labeling: theory and practice. we introduce the problem of labeling a particle's mass spectrum with the substances it contains, and develop several formal representations of the problem, taking into account practical complications such as unknown compounds and noise. this task is currently a bottle-neck in analyzing data from a new generation of instruments for real-time environmental monitoring.
on learning asymmetric dissimilarity measures. many practical applications require that distance measures to be asymmetric and context-sensitive. we introduce context-sensitive learnable asymmetric dissimilarity (clad) measures, which are defined to be a weighted sum of a fixed number of dissimilarity measures where the associated weights depend on the point from which the dissimilarity is measured. the parameters used in defining the measure capture the global relationships among the features. we provide an algorithm to learn the dissimilarity measure automatically from a set of user specified comparisons in the form "x is closer to y than to z," and study its performance. the experimental results show that the proposed algorithm outperforms other approaches due to the context sensitive nature of the clad measures.
partial ensemble classifiers selection for better ranking. ranking is an important task in data mining and knowledge discovery. we propose a novel approach called pecs algorithm to improve the overall ranking performance of a given ensemble. we formally analyse the sufficient and necessary condition under whichpecs algorithm can effectively improve ensemble ranking performance. the experiments with real-world data sets show that this new approach achieves significant improvements in ranking over the original bagging and adaboost ensembles.
a personalized music filtering system based on melody style classification. with the growth of digital music, the personalized musicfiltering system is helpful for users. melody style is one ofthe music features to represent user's music preference. inthis paper, we present a personalized content-based musicfiltering system to support music recommendation based onuser's preference of melody style. we propose the multitypemelody style classification approach to recommend themusic objects. the system learns the user preference bymining the melody patterns from the music access behaviorof the user. a two-way melody preference classifier istherefore constructed for each user. music recommendationis made through this melody preference classifier.performance evaluation shows that the filtering effect of theproposed approach meets user's preference.
comparing naive bayes, decision trees, and svm with auc and accuracy. predictive accuracy has often been used as the mainand often only evaluation criterion for the predictive performanceof classification or data mining algorithms. inrecent years, the area under the roc (receiver operatingcharacteristics) curve, or simply auc, has been proposedas an alternative single-number measure for evaluating performanceof learning algorithms. in our previous work, weproved that auc is, in general, a better measure (definedprecisely) than accuracy. many popular data mining algorithmsshould then be re-evaluated in terms of auc. forexample, it is well accepted that naive bayes and decisiontrees are very similar in accuracy. how do they compare inauc? also, how does the recently developed svm (supportvector machine) compare to traditional learning algorithmsin accuracy and auc? we will answer these questions inthis paper. our conclusions will provide important guide-linesin data mining applications on real-world datasets.
frequent subgraph discovery. as data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the requirement of these domains. an alternate way of modeling the objects in these data sets is to use graphs. within that model, the problem of finding frequent patterns becomes that of discovering subgraphs that occur frequently over the entire set of graphs. in this paper we present a computationally efficient algorithm for finding all frequent subgraphs in large graph databases. we evaluated the performance of the algorithm by experiments with synthetic datasets as well as a chemical compound dataset. the empirical results show that our algorithm scales linearly with the number of input transactions and it is able to discover frequent subgraphs from a set of graph transactions reasonably fast, even though we have to deal with computationally hard problems such as canonical labeling of graphs and subgraph isomorphism which are not necessary for traditional frequent itemset discovery.
feature selection via supervised model construction. relieff is a feature mining technique, which has been successfully used in data mining applications.however, relieff is sensitive to the definition of relevance that is used in its implementation and when handling a large data set, it is computationally expensive.this paper presents an optimisation (feature selection via supervised model construction) for data transformation and starter selection, and evaluates its effectiveness with c4.5.experiments indicate that the proposed method gave improvement of computation efficiency whilst maintaining classification accuracy of trial data sets.
discovering frequent geometric subgraphs. as data mining techniques are being increasingly appliedto non-traditional domains, existing approaches forfinding frequent itemsets cannot be used as they cannotmodel the requirement of these domains. an alternate wayof modeling the objects in these data sets, is to use a graphto model the database objects. within that model, the problemof finding frequent patterns becomes that of discoveringsubgraphs that occur frequently over the entire set ofgraphs. in this paper we present a computationally efficientalgorithm for finding frequent geometric subgraphs ina large collection of geometric graphs. our algorithm isable to discover geometric subgraphs that can be rotation,scaling and translation invariant, and it can accommodateinherent errors on the coordinates of the vertices. our experimentalresults show that our algorithms requires relativelylittle time, can accommodate low support values, andscales linearly on the number of transactions.
mining generalized association rules using pruning techniques. the goal of the paper is to mine generalizedassociation rules using pruning techniques. given a largetransaction database and a hierarchical taxonomy tree ofthe items, we try to find the association rules between theitems at different levels in the taxonomy tree under theassumption that original frequent itemsets and associationrules have already been generated beforehand. in theproposed algorithm gmar, we use join methods andpruning techniques to generate new generalizedassociation rules. through several comprehensiveexperiments, we find that the gmar algorithm is muchbetter than basic and cumulate algorithms.
grew-a scalable frequent subgraph discovery algorithm. existing algorithms that mine graph datasets to discover patterns corresponding to frequently occurring subgraphs can operate efficiently on graphs that are sparse, contain a large number of relatively small connected components, have vertices with low and bounded degrees, and contain well-labeled vertices and edges. however, for graphs that do not share these characteristics, these algorithms become highly unscalable. in this paper we present a heuristic algorithm called grew to overcome the limitations of existing complete or heuristic frequent subgraph discovery algorithms. grew is designed to operate on a large graph and to find patterns corresponding to connected subgraphs that have a large number of vertex-disjoint embeddings. our experimental evaluation shows that grew is efficient, can scale to very large graphs, and find non-trivial patterns.
association analysis with one scan of databases. mining frequent patterns with an fp-tree avoids costlycandidate generation and repeatedly occurrence frequencychecking against the support threshold. it thereforeachieves better performance and efficiency than apriori-likealgorithms. however, the database still needs tobe scanned twice to get the fp-tree. this can be verytime-consuming when new data are added to an existingdatabase because two scans may be needed for not only thenew data but also the existing data. this paper presentsa new data structure p-tree, pattern tree, and a new technique,which can get the p-tree through only one scan of thedatabase and can obtain the corresponding fp-tree with aspecified support threshold. updating a p-tree with newdata needs one scan of the new data only, and the existingdata do not need to be re-scanned.
statistical considerations in learning from data. in this paper we focus on statistics. classical statistics and bayesian statistics are both employed in data mining. both have advantages but both also have severe limitations in this context. we point out some of these limitations as well as s me of the advantages. the fact that we may need to take account of evidence both internal and external to the data set presents a difficulty for classical statistics. the need to incorporate an objective measure of reliability creates a difficulty for bayesian statistics.we outline an approach to uncertainty that promises to capture the best of both worlds by incorporating both background knowledge and objectivity.
triple jump acceleration for the em algorithm. this paper presents the triple jump framework for accelerating the em algorithm and other bound optimization methods. the idea is to extrapolate the third search point based on the previous two search points found by regular em. as the convergence rate of regular em becomes slower, the distance of the triple jump will be longer, and thus provide higher speedup for data sets where em converges slowly. experimental results show that the triple jump framework significantly outperforms em and other acceleration methods of em for a variety of probabilistic models, especially when the data set is sparse. the results also show that the triple jump framework is particularly effective for cluster models.
predicting density-based spatial clusters over time. most of existing clustering algorithms are designed to discover snapshot clusters that reflect only the current status of a database. snapshot clusters do not reveal the fact that clusters may either persist over a period of time, or slowly fade away as other clusters may gradually develop. predicting dynamic cluster evolutions and their occurring periods are important because this information can guide users to prepare appropriate actions toward the right areas during the right time for the most effective results. in this paper we developed a simple but effective approach in predicting the future distance among object pairs. objects that will be close in distance over different periods of time are then processed to discover density-based clusters that may occur or change over time.
hierarchy-regularized latent semantic indexing. organizing textual documents into a hierarchical taxonomy is a common practice in knowledge management. beside textual features, the hierarchical structure of directories reflect additional and important knowledge annotated by experts. it is generally desired to incorporate this information into text mining processes. in this paper, we propose hierarchy-regularized latent semantic indexing, which encodes the hierarchy into a similarity graph of documents and then formulates an optimization problem mapping each document into a low dimensional vector space. the new feature space preserves the intrinsic structure of the original taxonomy and thus provides a meaningful basis for various learning tasks like visualization and classification. our approach employs the information about class proximity and class specificity, and can naturally cope with multi-labeled documents. our empirical studies show very encouraging results on two real-world data sets, the new reuters (rcv1) benchmark and the swissprot protein database.
subject classification in the oxford english dictionary. the oxford english dictionary is a valuable source of lexical information and a rich testing ground for mining highly structured text.each entry is organized into a hierarchy of senses, which include definitions, labels and cited quotations.subject labels distinguish the subject classification of a sense, for example they signal how a word may be used in anthropology, music or computing.unfortunately subject labeling in the dictionary is incomplete. to overcome thisincompleteness, we attempt to classify the senses (i.e., definitions) in the dictionary by their subjects, using thecitations as an information guide.we report on four different approaches: k nearest neighbors, a standard classification technique; term weighting, an information retrieval method dealing with text; naïve bayes, a probabilistic method; and expectation maximization, an iterative probabilistic method.experimental performance of these methods is compared based on standard classification metrics.
a dynamic adaptive self-organising hybrid model for text clustering. clustering by document concepts is a powerful way ofretrieving information from a large number of documents.this task in general does not make any assumption on thedata distribution. in this paper, for this task we propose anew competitive self-organising (som) model, namelythe dynamic adaptive self-organising hybrid model(dash). the features of dash are a dynamic structure,hierarchical clustering, non-stationary data learning andparameter self-adjustment. all features are data-oriented:dash adjusts its behaviour not only by modifying itsparameters but also by an adaptive structure. thehierarchical growing architecture is a useful facility forsuch a competitive neural model which is designed fortext clustering. in this paper, we have presented a newtype of self-organising dynamic growing neural networkwhich can deal with the non-uniform data distributionand the non-stationary data sets and represent the innerdata structure by a hierarchical view.
partial elastic matching of time series. we consider the problem of elastic matching of time series. we propose an algorithm that determines a subsequence of a target time series that best matches a query series. in the proposed algorithm we map the problem of the best matching subsequence to the problem of a cheapest path in a dag (directed acyclic graph). the proposed approach allows us to also compute the optimal scale and translation of time series values, which is a nontrivial problem in the case of subsequence matching.
an efficient fuzzy c-means clustering algorithm. the fuzzy c-means (fcm) algorithm is commonly used for clustering.the performance of the fcm algorithm depends on the selection of the initial cluster center and/or the initial membership value.if a good initial cluster center that is close to the actual final clustercenter can be found, the fcm algorithm will converge very quickly and the processing time can be drastically.in this paper, we propose a novel algorithm for efficient clustering.this algorithm is a modified fcm called the psfcm algorithm, which significantly reduces the computation timerequired to partition a dataset into desired cluster.we find the actual cluster center by using a simplified set of the original complete dataset.it refines the initial value of the fcm algorithm to speed up the convergence time.our experiments show that the proposed psfcm algorithm isalgorithm.we also demonstrate that the quality of the proposed psfcm algorithm is the same as the fcm algorithm.
tree-structured partitioning based on splitting histograms of distances. we propose a novel clustering algorithm that is similar in spiritto classification trees. the data is recursively split using a criterionthat applies a discrete curve evolution method to the histogramof distances. the algorithm can be depicted throughtree diagrams with triple splits. leaf nodes represent eitherclusters or sets of observations that can not yet be clearly assignedto a cluster. after constructing the tree, unclassified datapoints are mapped to their closest clusters. the algorithm hasseveral advantages. first, it deals effectively with observationsthat can not be unambiguously assigned to a cluster by allowinga "margin of error". second, it automatically determinesthe number of clusters; apart from the margin of error the useronly needs to specify the minimal cluster size but not the numberof clusters. third, it is linear with respect to the number ofdata points and thus suitable for very large data sets. experimentsinvolving both simulated and real data from differentdomains show that the proposed method is effective and efficient.
mining generalized substructures from a set of labeled graphs. the problem of mining frequent itemsets in transactional data has been studied frequently and has yielded several algorithms that can find the itemsets within a limited amount of time. some of them can derive "generalized" frequent itemsets consisting of items at any level of a taxonomy. recently, several approaches have been proposed to mine frequent substructures (patterns) from a set of labeled graphs. the graph mining approaches are easily extended to mine generalized patterns where some vertices and/or edges have labels at any level of a taxonomy of the labels by extending the definition of "subgraph". however, the extended method outputs a massive set of the patterns most of which are over-generalized, which causes computation explosion. in this paper, an efficient and novel method is proposed to discover all frequent patterns which are not over-generalized from labeled graphs, when taxonomies on vertex and edge labels are available.
adapting classification rule induction to subgroup discovery. rule learning is typically used for solving classificationand prediction tasks. however, learning of classificationrules can be adapted also to subgroup discovery. this papershows how this can be achieved by modifying the coveringalgorithm and the search heuristic, performing probabilisticclassification of instances, and using an appropriatemeasure for evaluating the results of subgroup discovery.experimental evaluation of the cn2-sd subgroup discoveryalgorithm on 17 uci data sets demonstrates substantialreduction of the number of induced rules, increased rulecoverage and rule significance, as well as slight improvementsin terms of the area under the roc curve.
mining significant pairs of patterns from graph structures with class labels. in recent years, the problem of mining association rulesover frequent itemsets in transactional data has been frequentlystudied and yielded several algorithms that can findassociation rules within a limited amount of time. alsomore complex patterns have been considered such as orderedtrees, unordered trees, or labeled graphs. althoughsome approaches can efficiently derive all frequent subgraphsfrom a massive dataset of graphs, a subgraph orsubtree that is mathematically defined is not necessarily abetter knowledge representation. in this paper, we proposean efficient approach to discover significant rules to classifypositive and negative graph examples by estimating atight upper bound on the statistical metric. this approachabandons unimportant rules earlier in the computations,and thereby accelerates the overall performance. the performancehas been evaluated using real world datasets, andthe efficiency and effect of our approach has been confirmedwith respect to the amount of data and the computation time.
localized prediction of continuous target variables using hierarchical clustering. in this paper, we propose a novel technique for the efficientprediction of multiple continuous target variablesfrom high-dimensional and heterogeneous data sets usinga hierarchical clustering approach. the proposed approachconsists of three phases applied recursively:partitioning, localization and prediction. in thepartitioning step, similar target variables are groupedtogether by a clustering algorithm. in the localizationstep, a classification model is used to predict which groupof target variables is of particular interest. if theidentified group of target variables still contains a largenumber of target variables, the partitioning andlocalization steps are repeated recursively and theidentified group is further split into subgroups with moresimilar target variables. when the number of targetvariables per identified subgroup is sufficiently small, thethird step predicts target variables using localized predictionmodels built from only those data records thatcorrespond to the particular subgroup. experimentsperformed on the problem of damage prediction incomplex mechanical structures indicate that ourproposed hierarchical approach is computationally moreefficient and more accurate than straightforward methodsof predicting each target variable individually orsimultaneously using global prediction models.
fuzzy data mining: effect of fuzzy discretization. when we generate association rules, continuous attributes have to be discretized into intervals while our knowledge representation is not always based on such discretiztion.forexample, we usually use some linguistic terms (e.g., young, middle age, and old) for dividing our ages into somefuzzy categories.in this paper, we describe the extraction of linguistic association rules and examine the performanceof extracted rules.first we modify the definitions of the two basic measures (i.e., confidence and support) ofassociation rules for extracting linguistic association rules. the main difference between standard and linguistics association rules is the discretiztion of continuous attributes. we divide the domain interval of each attribute into some fuzzy discretiztion with standard on-fuzzy discretiztion through computer simulations on a pattern classificationproblem with many continuous attributes.the classification performance of extracted rules on unseen test patterns is examined under various conditions.simulation results show that linguistic association rules with rule weights have highgeneralization ability even when the domain of each continuous attribute is homogeneously partitioned.
clugo: a clustering algorithm for automated functional annotations based on gene ontology. we address the issue of providing highly informative and comprehensive annotations using information revealed by the structured vocabularies of gene ontology (go). for a target, a set of candidate terms for inferring target properties is collected and form a unique distribution on the go directed acyclic graph (dag). we propose a novel ontology-based clustering algorithm — clugo, which considers go hierarchical characteristics and the clustering of term distributions. by identifying significant groups in the distributions, clugo assigns comprehensive and correct annotations for a target. according to the results of experiments with automated sequence functional annotations, clugo represents a considerable improvement over our previous work — gomit in terms of recall while maintaining a similar level of precision. we conclude that given a go candidate term distribution, clugo is an efficient ontology-based clustering algorithm for selecting comprehensive and correct annotations.
extracting frequent subsequences from a single long data sequence: a novel anti-monotonic measure and a simple on-line algorithm. in this paper, we study frequent-subsequence extraction from a single very-long data-sequence. first we propose a novel frequency measure, called the total frequency, for counting multiple occurrences of a sequential pattern in a single data sequence. the total frequency is anti-monotonic, and makes it possible to count up pattern occurrences without duplication. moreover the total frequency has a good property for implementation based on the dynamic programming strategy. second we give a simple on-line algorithm for a specialized subsequence extraction problem, i.e., a problem with the infinite window-length. this specialized problem is considered to be a relaxation of the general-case problem, thus this fast on-line algorithm is important from the view of practical applications.
comine: efficient mining of correlated patterns. association rule mining often generates a huge numberof rules, but a majority of them either are redundantor don not reflect the tue correlation relationship amongdata objects.in this paper, we re-examine this problemand show that two interesting measures, all_confidence(denoted as \alpha) and coherence (denoted as \gamma), both disclosegenuine correlation relationships and can be computedefficiently.moreover, we propose two interestingalgorithms, comine(\alpha) and comine(\gamma), based onextensions of a pattern-growth methodology.our performancestudy shows that the comine algorithms havehigh performance in comparison with their apriori-basedcounterpart algorithms.
ad hoc association rule mining as sql3 queries. although there have been several encouraging attempts at developing methods for data mining using sql, simplicity and efficiency still remain significant impediments for furtherdevelopment. in this paper, we propose a significantly new approach and show that any object relational database can be mined for association rules without any restructuring orpreprocessing using only basic sql3 constructs and functions, and hence no additional machineries are necessary. in particular, we show that the cost of computing associationrules for a given database does not depend on support and confidence thresholds. more precisely, the set of large items can be computed using one simple join query and anaggregation once the set of all possible meets (least fix point) of item set patterns in the input table is known. the principal focus of this paper is to demonstrate that several sql3expressions exists for the mining of association rules.
finding maximal frequent itemsets over online data streams adaptively. due to the characteristics of a data stream, it is very important to confine the memory usage of a data mining process regardless of the amount of information generated in the data stream. for this purpose, this paper proposes a cp-tree (compressed-prefix tree)that can be effectively used in finding either frequent or maximal frequent itemsets over an online data stream. unlike a prefix tree, a node of a cp-tree can maintain the information of several itemsets together. based on this characteristic, the size of a cp-tree can be flexibly controlled by merging or splitting nodes. in this paper, a mining method employing a cp-tree is proposed and an adaptive memory utilization scheme is also presented in order to maximize the mining accuracy of the proposed method for confined memory space at all times. finally, the performance of the proposed method is analyzed by a series of experiments to identify its various characteristics.
implementation of a least fixpoint operator for fast mining of relational databases. recent research has focused on computing large item sets for association rule mining using sql3 least fixpoint computation, and by exploiting the monotonic nature of the sql3 aggregate functions such as sum and create view recursive constructs.such approaches allow us to view mining as an ad hoc querying exercise and treat the efficiency issue as an optimization problem.in this paper, we present a recursive implementation of a recently proposed least fixpoint operator for computing large item sets from object-relational databases.we present experimental evidence to show that our implementation compares well with several well-regarded and contemporary algorithms for large item set generation.
on mining general temporal association rules in a publication database. in this paper, we explore a new problem of mining general temporal association rules in publication databases. in essence, a publication database is a set of transactions where each transaction t is a set of items of which each item contains an individual exhibition period. the current model of association rule mining is not able to handle the publication database due to the following fundamental problems, i.e., (1) lack of consideration of the exhibition period of each individual item; (2) lack of an equitable support counting basis for each item. to remedy this, we propose an innovative algorithm progressive-partition-miner (abbreviatedly as ppm) to discover general temporal association rules in a publication database. the basic idea ofppm is to first partition the publication database in light of exhibition periods of items and then progressively accumulate the occurrence count of each candidate 2-itemset based on the intrinsic partitioning characteristics. algorithm ppm is also designed to employ a filtering threshold in each partition to early prune out those cumulatively infrequent 2-itemsets. explicitly, the execution time of ppm is, in orders of magnitude, smaller than those required by the schemes which are directly extended from existing methods.
fs: a random walk based free-form spatial scan statistic for anomalous window detection. often, it is required to identify anomalous windows over a spatial region that reflect unusual rate of occurrence of a specific event of interest. a spatial scan statistic essentially considers a scan window, and identifies anomalous windows by moving the scan window in the region. while spatial scan statistic has been successful, earlier proposals suffer from two limitations: (i) they resrict the scan window to be of a regular shape (e.g., circle, rectangle, cylinder). however, the region of anomaly, in general, is not necessarily of a regular shape. (ii) they take into account autocorrelation among spatial data, but not spatial heterogeneity. as a result, they often result in inaccurate anomalous windows. to address these limitations, we propose a random walk based free-form spatial scan statistic (fs³). application of fs³ on real datasets has shown that it can identify more refined anomalous windows with better likelihood ratio of it being an anomaly, than those identified by earlier spatial scan statistic approaches.
preparations for semantics-based xml mining. xml allows users to define elements using arbitrary words and organize them in a nested structure. these features of xml offer both challenges and opportunities in information retrieval, document management, and data mining. in this paper,we propose a new methodology for preparing xml documents for quantitative determination of similarity between xml documents by taking account of xml semantics (i.e.,meanings of the elements andnested structures of xml documents).accurate quantitative determination of similarity between xml documents provides an important basis for a variety of applications of xml document mining and processing. experiments with xml documents show that ourmethodology provides a 50-100%improvement in determining similarity, over the traditional vector-space model that considers only term-frequency and 100% accuracy in identifying the category of each document from an on-line bookstore.
the computational complexity of high-dimensional correlation search. there is a growing awareness that the popular support metric (often used to guide search in market-basket analysis) is not appropriate for use in every association mining application. support measures only the frequency of co-occurrence of a set of events when determining which pat-terns to report back to the user. it incorporates no rigorous statistical notion of surprise or interest, and many of the patterns deemed interesting by the support metric are uninteresting to the user.however, a positive aspect of support is that search using support is very efficient. the question we address in this paper is: can we retain this efficiency if we move beyond support, and to other, more rigorous metrics? we consider the computational implications of incorporating simple expectation into the data mining task. it turns out that many variations on the problem which incorporate more rigorous tests of dependence (or independence) result in np-hard problem definitions.
dynamic daily-living patterns and association analyses in tele-care systems. tele-care systems aim to carry out intelligent analyses of a person's wellbeing using data about their daily activities. this is a very challenging task because the massive dataset is likely to be erroneous, possibly with misleading sections due to noise or missing values. furthermore, the interpretation of the data is highly sensitive to the lifestyle of the monitored person and the environment in which they interact. in our tele-care project, sensor-network domain knowledge is used to overcome the difficulties of monitoring long-term wellbeing with an imperfect data source. in addition, a fuzzy association analysis is leveraged to implement a dynamic and flexible analysis over individual- and environment-dependent data.
mining minimal distinguishing subsequence patterns with gap constraints. discovering contrasts between collections of data is an important task in data mining. in this paper, we introduce a new type of contrast pattern, called a minimal distinguishing subsequence (mds). an mds is a minimal subsequence that occurs frequently in one class of sequences and infrequently in sequences of another class. it is a natural way of representing strong and succinct contrast information between two sequential datasets and can be useful in applicationssuch as protein comparison, document comparison and building sequential classification models. mining mds patterns is a challenging task and is significantly different from mining contrasts between relational/transactional data. one particularly important type of constraint that can be integrated into the mining process is the gap constraint. we present an efficient algorithm called consgapminer (contrast sequences with gap miner), to mine all mdss satisfying a minimum and maximum gap constraint, plus a maximum length constraint. it employs highly efficient bitset and boolean operations, for powerful gap-based pruning within a prefix growth framework. a performance evaluation with both sparse and dense datasets, demonstrates the scalability of consgapminer and shows its ability to mine patterns from high dimensional datasets at low supports.
an algebra for inductive query evaluation. inductive queries are queries that generate pattern sets.this paper studies properties of boolean inductive queries,i.e. queries that are boolean expressions over monotonicand anti-monotonic constraints. more specifically, we introduceand study algebraic operations on the answer setsof such queries and show how these can be used for constructingand optimizing query plans. special attention isdevoted to the dimension of the queries, i.e. the minimumnumber of version spaces needed to represent the answersets. the framework has been implemented for the patterndomain of strings and experimentally validated.
considering both intra-pattern and inter-pattern anomalies for intrusion detection. various approaches have been proposed to discoverpatterns from system call trails of unix processes tobetter model application behavior. however, thesetechniques only consider relationship between systemcalls (or system audit events). in this paper, we firstrefine the definition of maximal patterns given in [8] andprovide a pattern extraction algorithm to identify suchmaximal patterns. we then add one additional dimensionto the problem domain by also taking into considerationthe overlap relationship between patterns. we argue thatan execution path of an application is usually not anarbitrary combination of various patterns; but rather,they overlap each other in some specific order. suchoverlap relationship characterizes the normal behavior ofthe application. finally, a novel pattern matchingmodule is proposed to detect intrusions based on bothintra-pattern and inter-pattern anomalies. we test thisidea using the data sets obtained from the university ofnew mexico. the experimental results indicate that ourscheme detect significantly more anomalies than thescheme presented in [8] while maintaining a very lowfalse alarm rate.
an optimal linear time algorithm for quasi-monotonic segmentation. monotonicity is a simple yet significant qualitative characteristic. we consider the problem of segmenting an array in up to k segments. we want segments to be as monotonic as possible and to alternate signs. we propose a quality metric for this problem, present an optimal linear time algorithm based on novel formalism, and compare experimentally its performance to a linear time top-down regression algorithm. we show that our algorithm is faster and more accurate. applications include pattern recognition and qualitative modeling.
divide and prosper: comparing models of customer behavior from populations to individuals. this paper compares customer segmentation, 1-to-1, and aggregate marketing approaches across a broad range of experimental settings, including multiple segmentation levels, marketing datasets, dependent variables, and different types of classifiers, segmentation techniques, and predictive measures. our experimental results show that, overall, 1-to-1 modeling significantly outperforms the aggregate approach among high-volume customers and is never worse than aggregate approach among low-volume customers. moreover, the best segmentation techniques tend to outperform 1-to-1 modeling among low-volume customers.
cantree: a tree structure for efficient incremental mining of frequent patterns. since its introduction, frequent-pattern mining has been the subject of numerous studies, including incremental updating. many existing incremental mining algorithms are apriori-based, which are not easily adoptable to fp-tree based frequent-pattern mining. in this paper, we propose a novel tree structure, called cantree (canonical-order tree), that captures the content of the transaction database and orders tree nodes according to some canonical order. by exploiting its nice properties, the cantree can be easily maintained when database transactions are inserted, deleted, and/or modified. for example, the cantree does not require adjustment, merging, and/or splitting of tree nodes during maintenance. no rescan of the entire updated database or reconstruction of a new tree is needed for incremental updating. experimental results show the effectiveness of our cantree.
mining ontological knowledge from domain-specific text documents. traditional text mining systems employ shallow parsing techniques and focus on concept extraction and taxonomic relation extraction. this paper presents a novel system called crctol for mining rich semantic knowledge in the form of ontology from domain-specific text documents. by using a full text parsing technique and incorporating both statistical and lexico-syntactic methods, the knowledge extracted by our system is more concise and contains a richer semantics compared with alternative systems. we conduct a case study wherein crctol extracts ontological knowledge, specifically key concepts and semantic relations, from a terrorism domain text collection. quantitative evaluation, by comparing with a state-of-the-art ontology learning system known as text-to-onto, has shown that crctol produces much better precision and recall for both concept and relation extraction, especially from sentences with complex structures.
mining patterns that respond to actions. data mining focuses on patterns that summarize the data. in this paper, we focus on mining patterns that could change the state by responding to opportunities of actions.
linear causal model discovery using the mml criterion. determining the causal structure of a domain is a keytask in the area of data mining and knowledge discovery.the algorithm proposed by wallace et al. [15] hasdemonstrated its strong ability in discovering linear causalmodels from given data sets. however, some experimentsshowed that this algorithm experienced difficulty in discoveringlinear relations with small deviation, and it occasion-allygives a negative message length, which should not beallowed. in this paper, a more efficient and precise mml encodingscheme is proposed to describe the model structureand the nodes in a linear causal model. the estimation ofdifferent parameters is also derived. empirical results showthat the new algorithm outperformed the previous mml-basedalgorithm in terms of both speed and precision.
learning instance greedily cloning naive bayes for ranking. naive bayes (simply nb) [12] has been widely used in machine learning and data mining as a simple and effective classification algorithm. since its conditional independence assumption is rarely true, researchers have made a substantial amount of effort to improve naive bayes. the related research work can be broadly divided into two approaches: eager learning and lazy learning, depending on when the major computation occurs. different from eager approach, the key idea for extending naive bayes from the lazy approach is to learn a naive bayes for each testing example. in recent years, some lazy extensions of naive bayes have been proposed. for example, snnb [18], lwnb [7], and lbr [19]. all are aiming at improving the classification accuracy of naive bayes. in many real-world machine learning and data mining applications, however, an accurate ranking is more desirable than an accurate classification. responding to this fact, we present a lazy learning algorithm called instance greedily cloning naive bayes (simply igcnb) in this paper. our motivation is to improve naive bayes' ranking performance measured by auc [4, 14]. we experimentally tested our algorithm, using the whole 36 uci datasets recommended by weka [1], and compared it to c4.4 [16], nb [12], snnb [18] and lwnb [7]. the experimental results show that our algorithm outperforms all the other algorithms used to compare significantly in yielding accurate ranking.
mining production data with neural network & cart. this paper presents the preliminary results of a datamining study of a production line involving hundreds ofvariables related to mechanical, chemical, electrical andmagnetic processes involved in manufacturing coatedglass. the study was performed using two nonlinear,nonparametric approaches, namely neural network andcart, to model the relationship between the qualities ofthe coating and machine readings. furthermore, neuralnetwork sensitivity analysis and cart variable rankingswere used to gain insight into the coating process. ourinitial results show the promise of data mining techniquesto improve the production.
cmar: accurate and efficient classification based on multiple class-association rules. previous studies propose that associative classification has high classification accuracy and strong flexibility at handling unstructured data. however, it still suffers from the huge set of mined rules and sometimes biased classification or overfitting since the classificationis based on only single high-confidence rule. in this study, we propose new associative classification method, cmar, i.e., classification based on multiple association rules. the method extends an efficient frequent pattern mining method, fp-growth ,constructs classdistribution-associated fp-tree, and mines large database efficiently. moreover, it applies cr-tree structure to store and retrieve mined association rulesefficiently, and prunes rules effectively based on confidence, correlation and database coverage. the classification is performed based on weighted x2 analysis using multiple strong association rules. our extensive experiments on 26 databases from uci machine learning database repository show that cmar is consistent, highly effective at classificationof various kinds of databases and has better average classificationaccuracy in comparison with cba and c4.5.moreover,our performancestudy shows that the method is highly efficient and scalable in comparison with other reported associative classification methods.
classifying biomedical citations without labeled training examples. in this paper we introduce a novel technique for classifying text citations without labeled training examples. we first utilize the search results of a general search engine as original training data. we then proposed a mutually reinforcing learning algorithm (mrl) to mine the classification knowledge and to "clean" the training data. with the help of a set of established domain-specific ontological terms or keywords, the mrl mining step derives the relevant classification knowledge. the mrl cleaning step then builds a naive bayes classifier based on the mined classification knowledge and tries to clean the training set. the mrl algorithm is iteratively applied until a clean training set is obtained. we show the effectiveness of the proposed technique in the classification of biomedical citations from a large medical literature database.
mining image features for efficient query processing. the number of feature required to depict an image can be very large. using all features simultaneously to measure image similarity and to learn image query-concepts can suffer from the problem of dimensionality curse ,which degrades both search accuracy and search peed. regarding search accuracy, the presence of irrelevant features with respect to a query can contaminate similarity measurement, and hence decrease both the recall and precision of thatquery. to remedy this problem, we present a mining method that learns online user query concept and identities important features quickly. regarding search speed, the presence of a large number of feature can low down query-concept learning and indexing performance. we propose a divide-and-conquer method that divides the concept-learning task into g subtasks to achieve speedup. we notice that a task must be divided carefully, or search accuracy maysuffer. we thus propose a genetic-based mining algorithm to discover good feature groupings. through analysis and mining result, we observe that organizing image features in a multi-resolution manner, and minimizing intra-group feature correlation, can peed up query-concept learning substantially while maintaining high search accuracy.
improving medical/biological data classification performance by wavelet preprocessing. many real-world datasets contain noise and noisecould degrade the performances of learning algorithms.motivated from the success of wavelet denoisingtechniques in image data, we explore a generalsolution to alleviate the effect of noisy databy wavelet preprocessing for medical/biological dataclassification. our experiments are divided into twocategories: one is of different classification algorithmson a specific database (ecoli [6]) and the other isof a specific classification algorithm (decision tree)on different databases. the experiment results showthat the wavelet denoising of noisy data is able to improvethe accuracies of those classification methods,if the localities of the attributes are strong enough.
adaptive and resource-aware mining of frequent sets. the performance of an algorithm that mines frequent sets from transactional databases may severely depend on the specific features of the data being analyzed. moreover, some architectural characteristics of the computational platform used - e.g. the available main memory - can dramatically change its runtime behavior. in this paper we present dci (direct count & intersect), an efficient algorithm for discovering frequent sets from large databases. due to the multiple heuristics strategies adopted, dci can adapt its behavior not only to the features of the specific computing platform, but also to the features of the datasetbeing mined, so that it results very effective in mining both short and long patterns from sparse and dense datasets. finally we also discuss the parallelization strategies adopted in the design of pardci, a distributed and multi-threaded implementation of dci.
evolutionary structure learning algorithm for bayesian network and penalized mutual information metric. this paper formulates the problem of learning bayesian network structures from data as determining the structure that best approximates the probability distribution indicated by the data. a new metric, penalized mutual information metric, is proposed, and a evolutionary algorithm is designed to search for the best structure among alternatives. the experimental results show that this approach is reliable and promising.
solving the fragmentation problem of decision trees by discovering boundary emerging patterns. the single coverage constraint discourages a decisiontree to contain many significant rules. the loss of significantrules leads to a loss in accuracy. on the other hand, thefragmentation problem causes a decision tree to contain toomany minor rules. the presence of minor rules decreasesaccuracy. we propose to use emerging patterns to solvethese problems. in our approach, many globally significantrules can be discovered. extensive experimental results ongene expression datasets show that our approach are moreaccurate than single c4.5 trees, and are also better thanbagged or boosted c4.5 trees.
spatial interest pixels (sips): useful low-level features of visual media data. visual media data such as an image is the raw data representationfor many important applications. the biggestchallenge in using visual media data comes from the extremelyhigh dimensionality. we present a comparativestudy on spatial interest pixels (sips), including eight-way(a novel sip miner), harris, and lucas-kanade, whose extractionis considered as an important step in reducing thedimensionality of visual media data. with extensive casestudies, we have shown the usefulness of sips as the low-levelfeatures of visual media data. a class-preserving dimensionreduction algorithm (using gsvd) is applied tofurther reduce the dimension of feature vectors based onsips. the experiments showed its superiority over pca.
multi-stage classification. while much research has focused on methods for evaluating and maximizing the accuracy of classifiers either individually or in ensembles, little effort has been devoted to analyzing how classifiers are typically deployed in practice. in many domains, classifiers are used as part of a multi-stage process that increases accuracy at the expense of more data collection and/or more processing resources as the likelihood of a positive class label increases. this paper systematically explores the tradeoffs inherent in constructing these multi-stage classifiers from a series of increasingly accurate and expensive individual classifiers, considering a variety of metrics such as accuracy, cost/benefit ratio, and lift. it suggests architectures appropriate for both independent instances and for highly linked data.
direct interesting rule generation. an association rule generation algorithm usually generatestoo many rules including a lot of uninteresting ones.many interestingness criteria are proposed to prune thoseuninteresting rules. however, they work in post-pruningprocess and hence do not improve the rule generation ef£ciency. in this paper, we discuss properties of informativerule set and conclude that the informative rule set includesall interesting rules measured by many commonly used interestingnesscriteria, and that rules excluded by the informativerule set are forwardly prunable, i.e. they can be removedin the rule generation process instead of post pruning.based on these properties, we propose a direct interestingrule generation algorithm, dig, to directly generateinteresting rules de£ned by any of 12 interestingness criteriadiscussed in this paper. we further show experimentallythat dig is faster and uses less memory than apriori.
mining frequent itemsets in distributed and dynamic databases. traditional methods for frequent itemset mining typicallyassume that data is centralized and static. such methods imposeexcessive communication overhead when data is distributed,and they waste computational resources when datais dynamic. in this paper we present what we believe to bethe first unified approach that overcomes these assumptions.our approach makes use of parallel and incremental techniquesto generate frequent itemsets in the presence of dataupdates without examining the entire database, and imposesminimal communication overhead when mining distributeddatabases. further, our approach is able to generate bothlocal and global frequent itemsets. this ability permits ourapproach to identify high-contrast frequent itemsets, whichallows one to examine how the data is skewed over differentsites.
interpretations of association rules by granular computing. this paper presents interpretations for associationrules. it first introduces pawlak's method, and thecorresponding algorithm of finding decision rules (a kindof association rules). it then uses extended random sets topresent a new algorithm of finding interesting rules. itproves that the new algorithm is faster than pawlak'salgorithm. the extended random sets are easily to includemore than one criterion for determining interesting rules.they also provide two measures for dealing withuncertainties in association rules.
metric rule generation with septic shock patient data. in this contribution we present an application of metric rule generation in the domain of medical research. we consider intensive car unit patients developing a septic shockduring their stay at the hospital. to analyse the patient data, rule generation is embedded in a medical data mining cycle. for rule generation, we improve an architecture basedon a growing trapezoidal basis function network.
using discriminant analysis for multi-class classification. discriminant analysis is known to learn discriminativefeature transformations. this paper studies its use in multi-classclassification problems. the performance is tested ona large collection of benchmark datasets.
intersection based generalization rules for the analysis of symbolic septic shock patient data. in intensive care units much data is irregularly recorded.here, we consider the analysis of symbolic septic shock patientdata. we show that it could be worth consideringthe generalization paradigm (individual cases generalizedto more general rules) instead of the association paradigm(combining single attributes) when considering very individualcases (e.g. patients) and when expecting longer rulesthan shorter ones. we present an algorithm for rule generationand classification based on heuristically generatedset-based intersections. we demonstrate the usefulness ofour algorithm by analysing our septic shock patient data.
applications of data mining in hydrology. long-term range streamflow forecast plays an invaluable role in water resources planning andmanagement. in this study, the potential applicability and limitations of the time series forecasting approach using neural network with the multiresolution learning paradigm (nnmlp) are investigated. the predictedlongterm range streamflows using the nnmlp are compared with the observations. the results show that the time series forecasting approach of nnmlp has good predicting skill. the nnmlp requires only historicalstreamflow information. the time series forecasting approach of nnmlp has great potential for being used alone in regions with limited available information, and for being combined with other approaches to improve long-term range streamflow forecasts.
lpminer: an algorithm for finding frequent itemsets using length-decreasing support constraint. over the years, a variety of algorithms or finding frequentitemsets in very large transaction databases have been developed. the key feature in most to these algorithms is that they use a constant support constraint to control the inherently exponential complexity of the problem. in general, itemsets that contain only a few items will tend to be interesting if they have a high support, whereas long itemsets can still be interesting even if their support is relatively small. ideally, we desire to have an algorithm that finds all the frequent itemsets whose support decreases as a function of their length. in this paper we present an algorithm called lpminer, that finds all itemsets that satisfy a length-decreasing support constraint. our experimental evaluation shows that lpminer is up to two orders of magnitude faster than the fp-growth algorithm or finding itemsets at a constant support constraint, and that its runtime increasesgradually as the average length of the transactions (and the discovered itemsets) increases.
attribute (feature) completion - the theory of attributes from data mining prospect. a "correct" selection of attributes (features) is vital indata mining. as a first step, this paper constructs all possibleattributes of a given relation. the results are basedon the observations that each relation is isomorphic to aunique abstract relation, called canonical model. the completeset of attributes of the canonical model is, then, constructed.any attribute of a relation can be interpreted (viaisomorphism) from such a complete set.
slpminer: an algorithm for finding frequent sequential patterns using length-decreasing support constraint. over the years, a variety of algorithms for finding frequentsequential patterns in very large sequential databaseshave been developed. the key feature in most of these algorithmsis that they use a constant support constraint tocontrol the inherently exponential complexity of the problem.in general, patterns that contain only a few items willtend to be interesting if they have a high support, whereaslong patterns can still be interesting even if their supportis relatively small. ideally, we desire to have an algorithmthat finds all the frequent patterns whose support decreasesas a function of their length. in this paper we present an algorithmcalled slpminer, that finds all sequential patternsthat satisfy a length-decreasing support constraint. our experimentalevaluation shows that slpminer achieves up totwo orders of magnitude of speedup by effectively exploitingthe length-decreasing support constraint, and that itsruntime increases gradually as the average length of the sequences(and the discovered frequent patterns) increases.
mining associations by linear inequalities. the main theorem is: generalized associations of a relational table can be found by a finite set of linear inequalities within polynomial time. it is derived from the following three results, which were established in icdm0'02 and are re-developed here. they are (1) isomorphic theorem: isomorphic relations have isomorphic patterns. such an isomorphism classifies relational tables into isomorphic classes. (2) a variant of the classical bitmaps indexes uniquely exists in each isomorphic class. we take it as the canonical model of the class. (3) all possible attributes/features can be generated by a generalized procedure of the classical aog (attribute oriented generalization). then, (4) the main theorem for canonical model is established. by isomorphism theorem, we had the final result (5).
process diagnosis via electrical-wafer-sorting maps classification. the commonality analysis is a proven tool for fault detection in semiconductor manufacturing. this methodology extracts subsets of production lots from all the available data. then, data mining techniques are used only on the selected data. this approach loses part of the available information and does not discriminate among the lots. the new methodology performance the automatic classificationof the electrical wafer test maps in order to identify the classes of failure present in the production lots. subsequently, the proposed procedure uses the process history of each wafer to create a list of the root cause candidates. this methodology is the core of the software tool acid which is currently used for process diagnosis at the agrate site of the st microelectronics. a real analysis is presented.
unsupervised link discovery in multi-relational data via rarity analysis. a significant portion of knowledge discovery and datamining research focuses on finding patterns of interest indata. once a pattern is found, it can be used to recognizesatisfying instances. the new area of link discoveryrequires a complementary approach, since patterns ofinterest might not yet be known or might have too fewexamples to be learnable. this paper presents anunsupervised link discovery method aimed at discoveringunusual, interestingly linked entities in multi-relationaldatasets. various notions of rarity are introduced tomeasure the "interestingness" of sets of paths andentities. these measurements have been implemented andapplied to a real-world bibliographic dataset where theygive very promising results.
finding representative set from massive data. in the information age, data is pervasive. in some applications, data explosion is a significant phenomenon. the massive data volume poses challenges to both human users and computers. in this project, we propose a new model for identifying representative set from a large database. a representative set is a special subset of the original dataset, which has three main characteristics: it is significantly smaller in size compared to the original dataset. it captures the most information from the original dataset compared to other subsets of the same size. it has low redundancy among the representatives it contains. we use information-theoretic measures such as mutual information and relative entropy to measure the representativeness of the representative set. we first design a greedy algorithm and then present a heuristic algorithm that delivers much better performance. we run experiments on two real datasets and evaluate the effectiveness of our representative set in terms of coverage and accuracy. the experiments show that our representative set attains expected characteristics and captures information more efficiently.
improving the reliability of decision tree and naive bayes learners. the c4.5 decision tree and naive bayes learners are known to produce unreliable probability forecasts. we have used simple binning and laplace transform techniques to improve the reliability of these learners and compare their effectiveness with that of the newly developed venn probability machine (vpm) meta-learner. we assess improvements in reliability using loss functions, receiver operator characteristic (roc) curves and empirical reliability curves (erc). the vpm outperforms the simple techniques to improve reliability, although at the cost of increased computational intensity and slight increase in error rate. these trade-offs are discussed.
mmss: multi-modal story-oriented video summarization. we propose multi-modal story-oriented video summarization (mmss) which, unlike previous works that use fine-tuned, domain-specific heuristics, provides a domain-independent, graph-based framework. mmss uncovers correlation between information of different modalities which gives meaningful story-oriented news video summaries. mmss can also be applied for video retrieval, giving performance that matches the best traditional retrieval techniques (okapi and lsi), with no fine-tuned heuristics such as tf/idf.
mining optimal actions for profitable crm. data mining has been applied to crm (customer relationshipmanagement) in many industries witha limitedsuccess.most data mining tools can only discover customer modelsor profiles (such as customers who are likely attritors andcustomers who are loyal), but not actions that would improvecustomer relationship (such as changing attritors toloyal customers). we describe a novel algorithm that suggestsactions to change customers from an undesired status(such as attritors) to a desired one (such as loyal). our algorithmtakes into account the cost of actions, and further,it attempts to maximize the expected net profit. to our bestknowledge, no data mining algorithms or tools today can accomplishthis important task in crm. the algorithm is implemented,with many advanced features, in a specializedand highly effective data mining software called proactivesolution.
parameter-free spatial data mining using mdl. consider spatial data consisting of a set of binary features taking values over a collection of spatial extents (grid cells). we propose a method that simultaneously finds spatial correlation and feature co-occurrence patterns, without any parameters. in particular, we employ the minimum description length (mdl) principle coupled with a natural way of compressing regions. this defines what "good" means: a feature co-occurrence pattern is good, if it helps us better compress the set of locations for these features. conversely, a spatial correlation is good, if it helps us better compress the set of features in the corresponding region. our approach is scalable for large datasets (both number of locations and of features). we evaluate our method on both real and synthetic datasets.
predicting software escalations with maximum roi. enterprise software venders often have to release software products before all reported defects are corrected, and a small number of these reported defects will be escalated by customers whose businesses are seriously impacted. escalated defects must be quickly resolved at a high cost by the software vendors. the total costs can be even greater, including loss of reputation, satisfaction, loyalty, and repeat revenue. in this paper, we develop an escalation prediction (ep) system to mine historic defect report data and predict the escalation risk of current defect reports for maximum roi (return on investment). more specifically, we first describe a simple and general framework to convert the maximum roi problem to cost-sensitive learning. we then apply and compare several best-known cost-sensitive learning approaches for ep. the ep system has produced promising results, and has been deployed in the product group of an enterprise software vendor. conclusions drawn from this study also provide guidelines for mining imbalanced datasets and cost-sensitive learning.
discovering frequent arrangements of temporal intervals. in this paper we study a new problem in temporal pattern mining: discovering frequent arrangements of temporal intervals. we assume that the database consists of sequences of events, where an event occurs during a time-interval. the goal is to mine arrangements of event intervals that appear frequently in the database. there are many applications where these type of patterns can be useful, including data network, scientific, and financial applications. efficient methods to find frequent arrangements of temporal intervals using both breadth first and depth first search techniques are described. the performance of the proposed algorithms is evaluated and compared with other approaches on real datasets (american sign language streams and network data) and large synthetic datasets.
improving text classification using local latent semantic indexing. latent semantic indexing (lsi) has been shown to be extremely useful in information retrieval, but it is not an optimal representation for text classification. it always drops the text classification performance when being applied to the whole training set (global lsi) because this completely unsupervised method ignores class discrimination while only concentrating on representation. some local lsi methods have been proposed to improve the classification by utilizing class discrimination information. however, their performance improvements over original term vectors are still very limited. in this paper, we propose a new local lsi method called "local relevancy weighted lsi" to improve text classification by performing a separate single value decomposition (svd) on the transformed local region of each class. experimental results show that our method is much better than global lsi and traditional local lsi methods on classification within a much smaller lsi dimension.
inference of protein-protein interactions by unlikely profile pair. we note that a set of statistically "unusual" protein-profilepairs in experimentally determined database ofprotein-protein interactions can typify protein-proteininteractions, and propose a novel method calledpicupp that sifts such protein-profile pairs using astatistical simulation. it is demonstrated that unusualpfam and interpro profile pairs can be extracted fromthe dip database using a bootstrapping approach. weparticularly illustrate that such protein-profile pairs canbe used for predicting putative pairs of interactingproteins. their prediction accuracies are around 86%and 90% when interpro and pfam profiles are used,respectively at 75% confidence level.
building text classifiers using positive and unlabeled examples. this paper studies the problem of building text classifiersusing positive and unlabeled examples. the key feature ofthis problem is that there is no negative example forlearning. recently, a few techniques for solving thisproblem were proposed in the literature. these techniquesare based on the same idea, which builds a classifier intwo steps. each existing technique uses a different methodfor each step. in this paper, we first introduce some newmethods for the two steps, and perform a comprehensiveevaluation of all possible combinations of methods of thetwo steps. we then propose a more principled approachto solving the problem based on a biased formulation ofsvm, and show experimentally that it is more accuratethan the existing techniques.
efficient nonlinear dimension reduction for clustered data using kernel functions. in this paper, we propose a nonlinear feature extractionmethod which is based on centroids and kernel functions.the dimension reducing nonlinear transformation isobtained by implicitly mapping the input data into a featurespace using a kernel function, and then finding a linearmapping based on an orthonormal basis of centroids in thefeature space that maximally separates the between-classrelationship. the proposed method utilizes an efficient algorithmto compute an orthonormal basis of centroids in thefeature space transformed by a kernel function and achievesdramatic computational savings. the experimental resultsdemonstrate that our method is capable of extracting non-linearfeatures effectively so that competitive performanceof classification can be obtained in the reduced dimensionalspace.
analyzing the interestingness of association rules from the temporal dimension. rule discovery is one of the central tasks of data mining. existing research has produced many algorithms for the purpose. these algorithms, however, often generate too manyrules. in the past few years, rule interestingness techniques were proposed to help the user find interesting rules. these techniques typically employ the dataset as a whole to mine rules, and then filter and/or rank the discovered rules in various ways. in this paper, we argue that this is insufficient. these techniques are unable to answer a question that is of criticalimportance to the application of rules, i.e., can the rules be trusted? in practice, the users are always concerned with the question. they want to know whether the rules indeed represent some true and stable (or reliable)underlying relationships in the domain. if a rule is not stable, does it show any systematic pattern such as a trend? before any rule can be used, these questions must be answered. this paper proposes a technique to use statistical methods to analyze rules from the temporal dimension to answer these questions. experimental results show that the proposed technique is very effective.
a comparative study of linear and nonlinear feature extraction methods. this paper presents theoretical relationships among several generalized lda algorithms and proposes computationally efficient approaches for them utilizing the relationships. generalized lda algorithms are extended nonlinearly by kernel methods resulting in nonlinear discriminant analysis. performances and computational complexities of these linear and nonlinear discriminant analysis algorithms are compared.
mining approximate frequent itemsets from noisy data. frequent itemset mining is a popular and important first step in analyzing data sets across a broad range of applications. the traditional, "exact" approach for finding frequent itemsets requires that every item in the itemset occurs in each supporting transaction. however, real data is typically subject to noise, and in the presence of such noise, traditional itemset mining may fail to detect relevant itemsets, particularly those large itemsets that are more vulnerable to noise. in this paper we propose approximate frequent itemsets (afi), as a noise-tolerant itemset model. in addition to the usual requirement for sufficiently many supporting transactions, the afi model places constraints on the fraction of errors permitted in each item column and the fraction of errors permitted in a supporting transaction. taken together, these constraints winnow out the approximate itemsets that exhibit systematic errors. in the context of a simple noise model, we demonstrate that afi is better at recovering underlying data patterns, while identifying fewer spurious patterns than either the exact frequent itemset approach or the existing error tolerant itemset approach of yang et al. [11].
a new implementation technique for fast spectral based document retrieval systems. the traditional methods of spectral text retrieval(fds,cds) create an index of spatial data and convert thedata to its spectral form at query time. we present a newmethod of implementing and querying an index containingspectral data which will conserve the high precision performanceof the spectral methods, reduce the time needed toresolve the query, and maintain an acceptable size for theindex. this is done by taking advantage of the propertiesof the discrete cosine transform and by applying ideas fromvector space document ranking methods.
revealing true subspace clusters in high dimensions. subspace clustering is one of the best approaches for discovering meaningful clusters in high dimensional space. one cluster in high dimensional space may be transcribed into multiple distinct maximal clusters by projecting onto different subspaces. a direct consequence of clustering independently in each subspace is an overwhelmingly large set of overlapping clusters which may be significantly similar. to reveal the true underlying clusters, we propose a similarity measurement of the overlapping clusters. we adopt the model of gaussian tailed hyper-rectangles to capture the distribution of any subspace cluster. a set of experiments on a synthetic dataset demonstrates the effectiveness of our approach. application to real gene expression data also reveals impressive meta-clusters expected by biologists.
hybrid pre-query term expansion using latent semantic analysis. latent semantic retrieval methods (unlike vector space methods) take the document and query vectors and map them into a topic space to cluster related terms and documents. this produces a more precise retrieval but also a long query time. we present a new method of document retrieval which allows us to process the latent semantic information into a hybrid latent semantic-vector space query mapping. this mapping automatically expands the users query based on the latent semantic information in the document set. this expanded query is processed using a fast vector space method. since we have the latent semantic data in a mapping, we are able to store and retrieve vector information in the same fast manner that the vector space method offers. multiple mappings are combined to produce hybrid latent semantic retrieval which provide precision results 5% greater than the vector space method and fast query times.
op-cluster: clustering by tendency in high dimensional space. clustering is the process of grouping a set of objects intoclasses of similar objects. because of unknownness of thehidden patterns in the data sets, the definition of similarityis very subtle. until recently, similarity measures are typicallybased on distances, e.g euclidean distance and cosinedistance. in this paper, we propose a flexible yet powerfulclustering model, namely op-cluster (order preservingcluster). under this new model, two objects are similaron a subset of dimensions if the values of these twoobjects induce the same relative order of those dimensions.such a cluster might arise when the expression levels of (co-regulated)genes can rise or fall synchronously in responseto a sequence of environment stimuli. hence, discovery ofop-cluster is essential in revealing significant gene regulatorynetworks. a deterministic algorithm is designed andimplemented to discover all the significant op-clusters. aset of extensive experiments has been done on several realbiological data sets to demonstrate its effectiveness and efficiencyin detecting co-regulated patterns.
efficient progressive sampling for association rules. in data mining, sampling has often been suggested as aneffective tool to reduce the size of the dataset operated atsome cost to accuracy. however, this loss to accuracy isoften difficult to measure and characterize since the exactnature of the learning curve (accuracy vs. sample size) isparameter and data dependent, i.e., we do not know aprioriwhat sample size is needed to achieve a desired accuracyon a particular dataset for a particular set of parameters.in this article we propose the use of progressive sampling todetermine the required sample size for association rule mining.we first show that a naive application of progressivesampling is not very efficient for association rule mining.we then present a refinement based on equivalence classes,that seems to work extremely well in practice and is able toconverge to the desired sample size very quickly and veryaccurately. an additional novelty of our approach is thedefinition of a support-sensitive, interactive measure of accuracyacross progressive samples.
rpcl-based local pca algorithm. mining local structure is important in data analysis.gaussian mixture is able to describe local structurethrough the covariance matrices, but when used on high dimensional data, fitly specifying such a large number of d(d + 1)=2 free elements in each covariance matrix is difficult. in this paper, by constraining the covariance matrixin decomposed orthonormal form, we propos a local pcaalgorithm to tackle this problem in help of rpcl competitivelearning, which can automatically determine the number of local structure.
efficient discovery of common substructures in macromolecules. biological macromolecules play a fundamental role indisease; therefore, they are of great interest to fields such aspharmacology and chemical genomics. yet due to macromolecules'complexity, development of effective techniquesfor elucidating structure-function macromolecular relationshipshas been ill explored. previous techniques have eitherfocused on sequence analysis, which only approximatesstructure-function relationships, or on small coor-dinatedatasets, which does not scale to large datasets orhandle noise. we present a novel scalable approach toefficiently discover macromolecule substructures based onthree-dimensional coordinate data, without domain-specificknowledge. the approach combines structure-based frequentpattern discovery with search space reduction andcoordinate noise handling. we analyze computational performancecompared to traditional approaches, validate thatour approach can discover meaningful substructures innoisy macromolecule data by automated discovery of primaryand secondary protein structures, and show that ourtechnique is superior to sequence-based approaches at determiningstructural, and thus functional, similarity be-tweenproteins.
text representation: from vector to tensor. in this paper, we propose a text representation model, tensor space model (tsm), which models the text by multilinear algebraic high-order tensor instead of the traditional vector. supported by techniques of multilinear algebra, tsm offers a potent mathematical framework for analyzing the multifactor structures. tsm is further supported by certain introduced particular operations and presented tools, such as the high-order singular value decomposition (hosvd) for dimension reduction and other applications. experimental results on the 20 newsgroups dataset show that tsm is constantly better than vsm for text classification.
protecting sensitive knowledge by data sanitization. in this paper, we address the problem of protecting somesensitive knowledge in transactional databases. the challengeis on protecting actionable knowledge for strategicdecisions, but at the same time not losing the great benefitof association rule mining. to accomplish that, we introducea new, efficient one-scan algorithm that meets privacyprotection and accuracy in association rule mining, withoutputting at risk the effectiveness of the data mining per se.
learning conditional independence tree for ranking. accurate ranking is desired in many real-world data mining applications. traditional learning algorithms, however, aim only at high classification accuracy. it has been observed that both traditional decision trees and naive bayes produce good classification accuracy but poor probability estimates. in this paper, we use a new model, conditional independence tree (citree), which is a combination of decision tree and naive bayes and more suitable for ranking and more learnable in practice. we propose a novel algorithm for learning citree for ranking, and the experiments show that the citree algorithm outperforms the state-of-the-art decision tree learning algorithm c4.4 and naive bayes significantly in yielding accurate rankings. our work provides an effective data mining algorithm for applications in which an accurate ranking is required.
closing the loop: an agenda- and justification-based framework for selecting the next discovery task to perform. we propose and evaluate an agenda-and justification-basedarchitecture for discovery systems that selects the next tasks to perform. this framework has manydesirable properties: (1) it facilitates the encoding of general discovery strategies using a variety of backgroundknowledge, (2) t reasons about the appropriateness of the tasks being considered, and (3) it tailors its behavior toward a user 's interests. a prototype discovery program called hamb demonstrates that both reasons andestimates of interestingness contribute to performance in the domains of protein crystallization and patient rehabilitation.
peruse: an unsupervised algorithm for finding recurrig patterns in time series. this paper describes peruse, an unsupervised algorithm for finding recurring patterns in time series.it was initially developed and tested with sensor data from a mobile robot, i.e. noisy, re-valued, multivariate time series with variable intervals between observations.the pattern discovery problem is decomposed into two sub-problems: (1) a supervised learning problem in which a teacher provised exemplars of patterns and labels time series according to whether they contain the patterns; (2)an un supervised learning problem in which the time series are used to generate an approximation to the teacher.experimental results show that peruse can discover patterns in audio data corresponding to qualitatively distinct outcomes of taking actions.
sparse kernel least squares classifier. in this paper, we propose a new learning algorithm for constructing kernel least squares classifier. the new algorithm adopts a recursive learning way and a novel two-step sparsification procedure is incorporated into learning phase. these two most importantfeatures not only provide a feasible approach for large-scale problems as it is not necessary to store the entire kernel matrix, but also produce a very sparse model with fast training and testing time. experimental results on a number of data classification problems are presented to demonstrate the competitiveness of new proposed algorithm.
mining motifs in massive time series databases. the problem of efficiently locating previously knownpatterns in a time series database (i.e., query by content) hasreceived much attention and may now largely be regardedas a solved problem. however, from a knowledge discoveryviewpoint, a more interesting problem is the enumeration ofpreviously unknown, frequently occurring patterns. we callsuch patterns "motifs", because of their close analogy totheir discrete counterparts in computation biology. anefficient motif discovery algorithm for time series would beuseful as a tool for summarizing and visualizing massivetime series databases. in addition it could be used as asubroutine in various other data mining tasks, including thediscovery of association rules, clustering and classification.in this work we carefully motivate, then introduce, a non-trivialdefinition of time series motifs. we propose anefficient algorithm to discover them, and we demonstrate theutility and efficiency of our approach on several real worlddatasets.
parsing without a grammar: making sense of unknown file formats. the thousands of specialized structured file formats inuse today present a substantial barrier to freely exchanginginformation between applications programs. we considerthe problem of deducing such basic features as thewhitespace characters, bracketing delimiter symbols, andself-delimiter characters of a given file format from one ormore example files. we demonstrate that for sufficientlylarge example files, we can typically identify the basic featuresof interest.
sequence modeling with mixtures of conditional maximum entropy distributions. we present a novel approach to modeling sequences usingmixtures of conditional maximum entropy (maxent) distributions.our method generalizes the mixture of first-ordermarkov models by including the "long-term" dependenciesin model components.the "long-term" dependenciesare represented by the frequently used in the naturallanguage processing (nlp) domain probabilistic triggersor rules (suc as "a occured k positions back" \longrightarrow"the current symbol is b" with probability p).the maxentframework is then used to create a coherent global probabilisticmodel from all selected triggers.in this paper, weenhance this formalism by using probabilistic mixtures withmaxent models as components, thus representing hidden orunobserved effects in the data.we demonstrate how ourmixture of conditional maxent models can be learned fromdata using the generalized em algorithm that scales linearlyin the dimensions of the data and the number of mixturecomponents.we present empirical results on the simulatedand real-world data sets and demonstrate that theproposed approach enables us to create better quality modelsthan the mixtures of first-order markov models and resistoverfitting and curse of dimensionality that would inevitablypresent themselves for the higher order markov models.
combining multiple clusterings by soft correspondence. combining multiple clusterings arises in various important data mining scenarios. however, finding a consensus clustering from multiple clusterings is a challenging task because there is no explicit correspondence between the classes from different clusterings. we present a new framework based on soft correspondence to directly address the correspondence problem in combining multiple clusterings. under this framework, we propose a novel algorithm that iteratively computes the consensus clustering and correspondence matrices using multiplicative updating rules. this algorithm provides a final consensus clustering as well as correspondence matrices that gives intuitive interpretation of the relations between the consensus clustering and each clustering from clustering ensembles. extensive experimental evaluations also demonstrate the effectiveness and potential of this framework as well as the algorithm for discovering a consensus clustering from multiple clusterings.
experimentation and self learning in continuous database marketing. we present a method for continuous database marketingthat identifies target customers for a number of marketingoffers using predictive models. the algorithm thenselects the appropriate offer for the customer. experimentaldesign principles are encapsulated to capturemore information that will be used to monitor and refinethe predictive models. the updated predictive models arethen used for the next round of marketing offers.
reviewing relief and its extensions: a new approach for estimating attributes considering high-correlated features. relief algorithm [4], [5] and its extensions [8], [9]are some of the most known filter methods for estimatingthe quality of attributes in classification problems dealingwith both dependent and independent features. thesemethods attend to find all meaningful features for eachproblem (both weakly and strongly ones [6]) so they areusually employed like a first stage for detecting irrelevantattributes. nevertheless, in this paper we checked thatrelief-family algorithms present some importantlimitations that could distort the selection of the finalfeatures' subset, specially in the presence of high-correlatedattributes. to overcome these difficulties, anew approach has been developed (wacsa algorithm),which performance and validity are verified on well-knowndata sets.
on computing condensed frequent pattern bases. frequent pattern mining has been studied extensively.however, the effectiveness and efficiency of this mining isoften limited, since the number of frequent patterns generatedis often too large. in many applications it is sufficientto generate and examine only frequent patterns with supportfrequency in close-enough approximation instead of in fullprecision. such a compact but close-enough frequent patternbase is called a condensed frequent patterns-base.in this paper, we propose and examine several alternativesat the design, representation, and implementation ofsuch condensed frequent pattern-bases. a few algorithmsfor computing such pattern-bases are proposed. their effectivenessat pattern compression and their efficient computationmethods are investigated. a systematic performancestudy is conducted on different kinds of databases,which demonstrates the effectiveness and efficiency of ourapproach at handling frequent pattern mining in largedatabases.
parallel algorithms for distance-based and density-based outliers. an outlier is an observation that deviates so much from other observations as to arouse suspicion that it was generated by a different mechanism. outlier detection has many applications, such as data cleaning, fraud detection and network intrusion. the existence of outliers can indicate individuals or groups that exhibit a behavior that is very different from most of the individuals of the dataset. in this paper we design two parallel algorithms, the first one is for finding out distance-based outliers based on nested loops along with randomization and the use of a pruning rule. the second parallel algorithm is for detecting density-based local outliers. in both cases data parallelism is used. we show that both algorithms reach near linear speedup. our algorithms are tested on four real-world datasets coming from the machine learning database repository at the uci.
h-mine: hyper-structure mining of frequent patterns in large databases. methods for efficient mining of frequent patterns have been studied extensively by many researchers. however, the previously proposed methods still encounter someperformance bottlenecks when mining databases with different data characteristics, such as dense vs. sparse, long vs. short patterns, memory-based vs. disk-based, etc.in this study, we propose a simple and novel hyper-linkeddata structure, h-struct , and a new mining algorithm, h-mine ,which takes advantage of this data structure anddynamically adjusts links in the mining process. a distinct feature of this method is that it has very limitedand precisely predictable space overhead and runs really fast in memory-based setting. moreover, it ca be scaled up to very large databases by database partitioning, and whenthe data set becomes dense,(conditional)fp-trees can be constructed dynamically as part of the mining process. our study shows that h-mine has high performance in various kinds of data, outperforms the previously developedalgorithms in different settings, and is highly scalable in mining large databases. this study also proposes a new datamining methodology, space-preserving mining ,which mayhave strong impact in the future development of efficient and scalable data mining methods.
algorithms for spatial outlier detection. a spatial outlier is a spatially referenced object whosenon-spatial attribute values are significantly different fromthe values of its neighborhood. identification of spatial outlierscan lead to the discovery of unexpected, interesting,and useful spatial patterns for further analysis. one drawbackof existing methods is that normal objects tend to befalsely detected as spatial outliers when their neighborhoodcontains true spatial outliers. in this paper, we proposea suite of spatial outlier detection algorithms to overcomethis disadvantage. we formulate the spatial outlier detectionproblem in a general way and design algorithms whichcan accurately detect spatial outliers. in addition, usinga real-world census data set, we demonstrate that our approachescan not only avoid detecting false spatial outliersbut also find true spatial outliers ignored by existing methods.
efficiently mining frequent closed partial orders. mining ordering information from sequence data is an important data mining task. sequential pattern mining [1] can be regarded as mining frequent segments of total orders from sequence data. however, sequential patterns are often insufficient to concisely capture the general ordering information.
anchor text mining for translation of web queries. this paper presents an approach to automatically extracting translations of web query terms through mining of web anchor texts and link structures. one of the existing difficulties in cross-language information retrieval (clir)and web search is the lack of the appropriate translations of new terminology and proper names. such a difficult problem can be effectively alleviated by our proposed approach, and the resource of anchor texts in the web is proven a valuable corpus for this kind of term translation.
maple: a fast algorithm for maximal pattern-based clustering. pattern-based clustering is important in many applications,such as dna micro-array data analysis, automaticrecommendation systems and target marketing systems.however, pattern-based clustering in large databasesis challenging. on the one hand, there can be a huge numberof clusters and many of them can be redundant and thusmake the pattern-based clustering ineffective. on the otherhand, the previous proposed methods may not be efficient orscalable in mining large databases.in this paper, we study the problem of maximal pattern-basedclustering. redundant clusters are avoided completelyby mining only the maximal pattern-based clusters.maple, an efficient and scalable mining algorithm is developed.it conducts a depth-first, divide-and-conquer searchand prunes unnecessary branches smartly. our extensiveperformance study on both synthetic data sets and real datasets shows that maximal pattern-based clustering is effective.it reduces the number of clusters substantially. moreover,maple is more efficient and scalable than the previouslyproposed pattern-based clustering methods in mininglarge databases.
bit reduction support vector machine. support vector machines are very accurate classifiers and have been widely used in many applications. however, the training and to a lesser extent prediction time of support vector machines on very large data sets can be very long. this paper presents a fast compression method to scale up support vector machines to large data sets. a simple bit reduction method is applied to reduce the cardinality of the data by weighting representative examples. we then develop support vector machines which may be trained on weighted data. experiments indicate that the bit reduction support vector machine produces a significant reduction in the time required for both training and prediction with minimum loss in accuracy. it is also shown to be more accurate than random sampling, when the data is not over-compressed.
schism: a new approach for interesting subspace mining. high-dimensional data pose challenges to traditional clustering algorithms due to their inherent sparsity and data tend to cluster in different and possibly overlapping subspaces of the entire feature space. finding such subspaces is called subspace mining. we present schism, a new algorithm for mining interesting subspaces, using the notions of support and chernoff-hoeffding bounds. we use a vertical representation of the dataset, and use a depth-first search with backtracking to find maximal interesting subspaces. we test our algorithm on a number of high-dimensional synthetic and real datasets to test its effectiveness.
mining mutually dependent patterns. in some domains, such as isolating problems in computer net-worksand discovering stock market irregularities, there is more interest inpatterns consisting of infrequent, but highly correlated items rather thanpatterns that occur frequently (as defined by minsup, the minimum supportlevel). herein, we describe the m-pattern, a new pattern that is definedin terms of minp, the minimum probability of mutual dependence of itemsin the pattern. we show that all infrequent m-pattern can be discovered byan efficient algorithm that makes use of: (a) a linear algorithm to qualifyan m-pattern; (b) an effective technique for candidate pruning based on anecessary condition for the presence of an m-pattern; and (c) a level-wisesearch for m-pattern discovery (which is possible because m-patterns aredownward closed). further, we consider frequent m-patterns, which aredefined in terms of both minp and minsup. using synthetic data, we studythe scalability of our algorithm. then, we apply our algorithm to data froma production computer network both to show the m-patterns present andto contrast with frequent patterns. we show that when minp_0, our algorithmis equivalent to finding frequent patterns. however, with a larger minp, our algorithm yields a modest number of highly correlated items, which makes it possible to mine for infrequent but highly correlated item-sets. to date, many actionable m-patterns have been discovered in production systems.
automatic web page classification in a dynamic and hierarchical way. automatic classification of web pages is an effectiveway to deal with the difficulty of retrieving informationfrom the internet. although there are many automaticclassification algorithms and systems that have beenproposed, most of them ignore the conflict between thefixed number of categories and the growing number ofweb pages going into the system. they also requiresearching through all existing categories to make anyclassification. we propose a dynamic and hierarchicalclassification system that is capable of adding newcategories as required, organizing the web pages into atree structure, and classifying web pages by searchingthrough only one path of the tree structure. our testresults show that our proposed single-path searchtechnique reduces the search complexity and increasesthe accuracy by 6% comparing to related algorithms. ourdynamic-category expansion technique also achievessatisfying results on adding new categories into oursystem as required.
progressive and interactive analysis of event data using event miner. exploring large data sets typically involves activities that iteratebetween data selection and data analysis, in which insights obtainedfrom analysis result in new data selection. further, data analysis needs touse a combination of analysis techniques: data summarization, mining algorithmsand visualization. this interweaving of functions arises both fromthe semantics of what the analyst hopes to achieve and from scalability requirementsfor dealing with large data volumes. we refer to such a processas a progressive analysis. herein is described a tool, event miner, that integratesdata selection, mining and visualization for progressive analysis oftemporal, categorical data. we discuss a data model and architecture. weillustrate how our tool can be used for complex mining tasks such as findingpatterns not occurring on monday. further, we discuss the novel visualizationemployed, such as visualizing categorical data and the results of datamining. also, we discuss the extension of the existing mining frameworkneeded to mine temporal events with multiple attributes. throughout, weillustrate the capabilities of event miner by applying it to event data fromlarge computer networks.
structure search and stability enhancement of bayesian networks. learning bayesian network structure from large-scale datasets, without any expert-specified ordering of variables, remainsa difficult problem. we propose systematic improvements toautomatically learn bayesian network structure from data. (1)we propose a linear parent search method to generate candidategraph. (2) we propose a comprehensive approach to eliminatecycles using minimal likelihood loss, a short cycle first heuristic,and a cut-edge repairing. (3) we propose structure perturbationto assess the stability of the network and a stability-improvementmethod to refine the network structure. the algorithms are easyto implement and efficient for large networks. experimental resultson two data sets show that our new approach outperformsexisting methods.
finding constrained frequent episodes using minimal occurrences. recurrent combinations of events within an event sequence, known as episodes, oftenreveal useful information. most of the proposed episode mining algorithms adopt an apriori-like approach that generates candidates and then calculates their support levels. obviously, such an approach is computationally expensive. moreover, those algorithms are capable ofhandling only a limited range of constraints. in this paper, we introduce two miningalgorithms - episode prefix tree (ept) and position pairs set (pps) - based on a prefix-growth approach to overcome the above limitations. both algorithms push constraints systematically into the mining process. performance study shows that the proposed algorithms run considerably faster than minepi.
a transaction-based neighbourhood-driven approach to quantifying interestingness of association rules. in this paper, we present a data-driven approach for ranking association rules (ars) based on interestingness. the occurrence of unrelated or weakly related item-pairs in an ar is interesting. in the retail market-basket context, items may be related through various relationships arising due to mutual interaction, 'substitutability' and 'complementarity.' item-relatedness is a composite of these relationships. we introduce three relatedness measures for capturing relatedness between item-pairs. these measures use the concept of function embedding to appropriately weigh the relatedness contributions due tocomplementarity and substitutability between items. we propose an interestingness coefficient by combining the three relatedness measures. we compare this with two objective measures of interestingness and show the intuitiveness of the proposed interestingness coefficient.
an adaptive density-based clustering algorithm for spatial database with noise. clustering spatial data has various applications. several clustering algorithms have been proposed to cluster objects in spatial databases. spatial object distribution has significant effect on the results of clustering. few of current algorithms consider the distribution of objects while processing clusters. in this paper, we propose an adaptive density-based clustering algorithm, adbc, which uses a novel adaptive strategy for neighbor selection based on spatial object distribution to improve clustering accuracy. we perform a series of experiments on simulated data sets and real data sets. a comparison with dbscan and optics shows the superiority of our new approach.
exploiting unlabeled data for improving accuracy of predictive data mining. predictive data mining typically relies on labeled datawithout exploiting a much larger amount of availableunlabeled data. the goal of this paper is to show thatusing unlabeled data can be beneficial in a range ofimportant prediction problems and therefore should be anintegral part of the learning process. given an unlabeleddataset representative of the underlying distribution and ak-class labeled sample that might be biased, ourapproach is to learn k contrast classifiers each trained todiscriminate a certain class of labeled data from theunlabeled population. we illustrate that contrastclassifiers can be useful in one-class classification, outlierdetection, density estimation, and learning from biaseddata. the advantages of the proposed approach aredemonstrated by an extensive evaluation on synthetic datafollowed by real-life bioinformatics applications for (1)ranking pubmed articles by their relevance to proteindisorder and (2) cost-effective enlargement of adisordered protein database.
visually mining web user clickpaths. as powerful as clickpath mining methods can be, theyoften lead to huge incomprehensible and non-interestingresult sets. our clickpath mining practice at msn wasfaced with challenges of keeping analysts closer to thedata exploration process, revealing powerful insight fromclickpath mining that business owners can directly actupon. these challenges stressed the importance of aninteractive and visual representation of clickpath miningresults. most products today that can perform clickpathvisualization do so by presenting massive cross-weavingweb graphs. we present a new type of clickpathvisualization which focuses only on clickpaths of interest,simplifying the visualization space while still retaining thesame degree of mineable knowledge in the data. we alsodescribe visualization techniques we have used toenhance the detection of interesting clickpath patternsfrom data, and provide a real-life case study that hasbenefited from the use of our implemented clickpathvisualizer pave.
farm: a framework for exploring mining spaces with multiple attributes. mining for frequent itemsets typically involves a preprocessing step in which data with multiple attributes are grouped into transactions, and item are defined based on attribute values. we have observed that such fixed attribute mining can severely constrain the pattern that are discovered. herein, we introduce mining paces, a new framework for mining multi-attribute data that include the discovery of transaction and item definition (with the exploitation of taxonomies and functional dependenciesif they are available).we prove that special downward closure properties (or anti-monotonic property) hold for mining paces, aresult that allows us to construct efficient algorithms for mining pattern without the constraint of fixed attribute mining. we apply our algorithm to real world data collected from a production computer network. the result how that by exploiting the special kind of downward closure in mining paces, execution times for mining can be reduced by a factor of three to four.
learning rules for anomaly detection of hostile network traffic. we introduce an algorithm called lerad that learnsrules for finding rare events in nominal time-series datawith long range dependencies. we use lerad to findanomalies in network packets and tcp sessions to detectnovel intrusions. we evaluated lerad on the 1999darpa/lincoln laboratory intrusion detection evaluationdata set and on traffic collected in a universitydepartmental server environment.
user-directed exploration of mining space with multiple attributes. there has been a growing interest in mining frequentitemsets in relational data with multiple attributes. a keystep in this approach is to select a set of attributes thatgroup data into transactions and a separate set of attributesthat labels data into items. unsupervised and unrestrictedmining, however, is stymied by the combinatorial complexityand the quantity of patterns as the number of attributesgrows. in this paper, we focus on leveraging the semanticsof the underlying data for mining frequent itemsets. forinstance, there are usually taxonomies in the data schemaand functional dependencies among the attributes. domainknowledge and user preferences often have the potentialto significantly reduce the exponentially growing miningspace. these observations motivate the design of a user-directeddata mining framework that allows such domainknowledge to guide the mining process and control the miningstrategy. we show examples of tremendous reductionin computation by using domain knowledge in mining relationaldata with multiple attributes.
an algorithm for the exact computation of the centroid of higher dimensional polyhedra and its application to kernel machines. the support vector machine (svm) solution correspondsto the centre of the largest sphere inscribed in versionspace. alternative approaches like bayesian pointmachines (bpm) and analytic centre machines have suggestedthat the generalization performance can be furtherenhanced by considering other possible centres of versionspace like the centroid (centre of mass) or the analytic centre.we present an algorithm to compute exactly the centroidof higher dimensional polyhedra, then derive approximationalgorithms to build a new learning machine whoseperformance is comparable to bpm. we also show that forregular kernel matrices (gaussian kernels for example), thesvm solution can be obtained by solving a linear system ofequalities.
the representative basis for association rules. we define the concept of the representative basic for interesting association rules, and an inference system which is purely qualitative. the representative basis is unique, and minimal with respect to (wrt) the inference system. on the representative basis, the inference system is correct and complete. experimental results show that the number of rule in the representative basis is significantly reduced wrt the number of rules generated by other existing approaches.
probabilistic user behavior models. we present a mixture model based approach for learningindividualized behavior models for the web users. weinvestigate the use of maximum entropy and markov mixturemodels for generating probabilistic behavior models.we first build a global behavior model for the entire populationand then personalize this global model for the existingusers by assigning each user individual componentweights for the mixture model. we then use these individualweights to group the users into behavior model clusters.we show that the clusters generated in this manner areinterpretable and able to represent dominant behavior patterns.we conduct offline experiments on around two monthsworth of data from citeseer, an online digital library forcomputer science research papers currently storing morethan 470,000 documents. we show that both maximum entropyand markov based personal user behavior modelsare strong predictive models. we also show that maximumentropy based mixture model outperforms markov mixturemodels in recognizing complex user behavior patterns.
regulatory element discovery using tree-structured models. computational discovery of transcriptional regulatoryregions in dna sequences provides an efficient way tobroaden our understanding of how cellular processes arecontrolled. in this paper, we formulate the regulatoryelement discovery problem in the regression frameworkwith regulatory regions treated as predictor variables andgene expression levels as responses. we use regressiontree models to identify structural relationships betweenpredictors and responses. the regression treemethodology is extended to handle multiple responsesfrom different experiments by modifying the split function.we apply this method to two data sets of the yeastsaccharomyces cerevisiae. the method successfullyidentifies most of regulatory motifs that are known tocontrol gene transcription under the given experimentalconditions. our method also suggests several putativemotifs that can present novel regulatory motifs.
spatial clustering of chimpanzee locations for neighborhood identification. since 1960, the chimpanzees (pan troglodytes) of gombe national park, tanzania, have been studied by behavioral ecologists, including jane goodall. data have been collected for more than 40 years and are being analyzed by researchers in order to increase our understanding of the social structure of chimpanzees. in this paper, we consider the following question of interest to behavioral ecologists — "does clustering exist among female chimpanzees in terms of their spatial locations?" the analysis of this question will help behavioral ecologists to learn about the space use and the social interactions between female chimpanzees. the data collected for this analysis are marked spatial point patterns over the park. current spatial clustering methods lack the ability to handle such marked point patterns directly. this paper presents a novel application of spatial point pattern analysis and data mining techniques to the ecological problem of clustering female chimpanzees. we found that ripley's k-function provides a powerful statistical tool for evaluating clustering behavior among spatial point patterns. we then proposed two clustering approaches for marked point patterns using the k-function. experimental results using the proposed clustering methods provide significant insight into the dynamics of female chimpanzee space use and into the overall social stucture of the species. in addition, the proposed methods can be extended to also include temporal information.
privacy-preserving collaborative filtering using randomized perturbation techniques. collaborative filtering (cf) techniques are becomingincreasingly popular with the evolution of the internet. toconduct collaborative filtering, data from customers areneeded. however, collecting high quality data from customersis not an easy task because many customers areso concerned about their privacy that they might decide togive false information. we propose a randomized perturbation(rp) technique to protect users' privacy while stillproducing accurate recommendations.
estimation of false negatives in classification. in many classification problems such as spam detection and network intrusion, a large number of unlabeled test instances are predicted negative by the classifier. however, the high costsas well as time constraints on an expert's time prevent further analysis of the "predicted false" class instances in order to segregate the false negatives from the true negatives. a systematic method is thus required to obtain an estimate of the number of false negatives. a capture-recapture based method can be used to obtain an ml-estimate of false negatives when two or more independent classifiers are available. in the case for which independence does not hold, we can apply log-linear models to obtain an estimate of false negatives. however, as shown in this paper, lesser the dependencies among the classifiers, better is the estimate obtained for false negatives. thus, ideally independent classifiers should be used to estimate the false negatives in an unlabeled dataset. experimental results on the spam dataset from the uci machine learning repository are presented.
statistical relational learning for document mining. a major obstacle to fully integrated deployment of manydata mining algorithms is the assumption that data sitsin a single table, even though most real-world databaseshave complex relational structures. we propose an integratedapproach to statistical modeling from relationaldatabases. we structure the search space based on "refinementgraphs", which are widely used in inductive logic programmingfor learning logic descriptions. the use of statisticsallows us to extend the search space to include richerset of features, including many which are not boolean.search and model selection are integrated into a single process,allowing information criteria native to the statisticalmodel, for example logistic regression, to make feature selectiondecisions in a step-wise manner. we present experimentalresults for the task of predicting where scientific paperswill be published based on relational data taken fromciteseer. our approach results in classification accuraciessuperior to those achieved when using classical "flat" features.the resulting classifier can be used to recommendwhere to publish articles.
a new algorithm for finding minimal sample uniques for use in statistical disclosure assessment. we present suda2, a recursive algorithm for finding minimal sample uniques (msus). suda2 uses a novel method for representing the search space formsus and new observations about the properties ofmsus to prune and traverse this space. experimental comparisons with previous work demonstrate that suda2 is not only several orders of magnitude faster but is also capable of identifying the boundaries of the search space, enabling datasets of larger numbers of columns than before to be addressed.
a fast algorithm to cluster high dimensional basket data. clustering is a data mining problem that has received significant attention by the database community. data set size, dimensionality and sparsity have been identified as aspectsthat make clustering more difficult. this work introduces a fast algorithm to cluster large binary data sets where data points have high dimensionality and most o their coordinates are zero. this is the case with basket data transactions containing items, that can be represented as sparse binary vectors with very high dimensionality. an experimental section shows performance, advantages and limitations of the proposed approach.
aligning boundary in kernel space for learning imbalanced dataset. an imbalanced training dataset poses serious problem for many real-world supervised learning tasks. in this paper, we propose a kernel-boundary-alignment algorithm, which considers training-data imbalance as prior information to augment svms to improve class-prediction accuracy. using a simple example, we first show that svms can suffer from high incidences of false negatives when the training instances of the target class are heavily outnumbered by the training instances of a non-target class. the remedy we propose is to adjust the class boundary by modifying the kernel matrix, according to the imbalanced data distribution. through theoretical analysis backed by empirical study, we show that our kernel-boundary-alignment algorithm works effectively on several datasets.
learning automatic acquisition of subcategorization frames using bayesian inference and support vector machines. learning bayesian belief network (bbn) from corpora and support vector machines (svm) have been applied to the automatic acquisition of verb subcategorization frames for modern greek.we are incorporating minimal linguistic resources, i.e. basic morphological tagging and phrase chunking, to demonstrate that verb subcategorization, which is of great significance for developing robust natural language human computer interaction systems, could be achieved using large corpora, without having any general-purpose syntactic parser at all.
svm and graphical algorithms: a cooperative approach. we present a cooperative approach using both support vector machine (svm) algorithms and visualization methods. svm are widely used today and often give high quality results, but they are used as "black-box" (it is very difficult to explain the obtained results) and cannot treat easily very large datasets. we have developed graphical methods to help the user to evaluate and explain the svm results. the first method is a graphical representation of the separating frontier quality, it is then linked with other visualization tools to help the user explaining svm results. the information provided by these graphical methods is also used for svm parameter tuning, they are then used together with automatic algorithms to deal with very large datasets on standard computers. we present an evaluation of our approach with the uci and the kent ridge bio-medical data sets.
zigzag: a new algorithm for mining large inclusion dependencies in database. in the relational model, inclusion dependencies (inds)convey many information on data semantics. they generalizeforeign keys, which are very popular constraints inpractice. however, one seldom knows the set of satisfiedinds in a database. the ind discovery problem in existingdatabases can be formulated as a data-mining problem.we underline in this article that the exploration of ind expressionsfrom most general (smallest) inds to most specific(largest) inds does not succeed whenever large indshave to be discovered. to cope with this problem, we introducea new algorithm, called zigzag , which combinesthe strength of levelwise algorithms (to find out some smallestinds) with an optimistic criteria to jump more or lessto largest inds. preliminary tests, on synthetic databases,are presented and commented on. it is worth noting that themain result of this paper is general enough to be appliedto other data-mining problems, such as maximal frequentitemsets mining.
semantic role parsing: adding semantic structure to unstructured text. there is a ever-growing need to add structure in the formof semantic markup to the huge amounts of unstructured textdata now available. we present the technique of shallow semanticparsing, the process of assigning a simple who didwhat to whom, etc., structure to sentences in text, as auseful tool in achieving this goal. we formulate the semanticparsing problem as a classification problem using supportvector machines. using a hand-labeled training setand a set of features drawn from earlier work together withsome feature enhancements, we demonstrate a system thatperforms better than all other published results on shallowsemantic parsing.
alternate representation of distance matrices for characterization of protein structure. the most suitable method for the automated classification of protein structures remains an open problem in computational biology. in order to classify a protein structure with any accuracy, an effective representation must be chosen. here we present two methods of representing protein structure. one involves representing the distances between the cá atoms of a protein as a two-dimensional matrix and creating a model of the resulting surface with zernike polynomials. the second uses a wavelet-based approach. we convert the distances between a protein's cα atoms into a one-dimensional signal which is then decomposed using a discrete wavelet transformation. using the zernike co-efficients and the approximation coefficients of the wavelet decomposition as feature vectors, we test the effectiveness of our representation with two different classifiers on a dataset of more than 600 proteins taken from the 27 most-populated scop folds. we find that the wavelet decomposition greatly outperforms the zernike model.with the wavelet representation, we achieve an accuracy of approximately 56%, roughly 12% higher than results reported on a similar, but less-challenging dataset. in addition, we can couple our structure-based feature vectors with several sequence-based properties to increase accuracy another 5-7%. finally, we use a multi-stage classification strategy on the combined features to increase performance to 78%, an improvement in accuracy of more than 15-20% and 34% over the highest reported sequence-based and structure-based classification results, respectively.
clump: a scalable and robust framework for structure discovery. we introduce a robust and efficient framework called clump (clustering using multiple prototypes) for unsupervised discovery of structure in data. clump relies on finding multiple prototypes that summarize the data. clustering the prototypes enables our algorithm to scale up to extremely large and high-dimensional domains such as text data. other desirable properties include robustness to noise and parameter choices. in this paper, we describe the approach in detail, characterize its performance on a variety of datasets, and compare it to some existing model selection approaches.
training support vector machines using gilbert's algorithm. support vector machines are classifiers designed around the computation of an optimal separating hyperplane. this hyperplane is typically obtained by solving a constrained quadratic programming problem, but may also be located by solving a nearest point problem. gilbert's algorithm can be used to solve this nearest point problem but is unreasonably slow. in this paper we present a modified version of gilbert's algorithm for the fast computation of the support vector machine hyperplane. we then compare our algorithm with the nearest point algorithm and with sequential minimal optimization.
a theory of inductive query answering. we introduce the boolean inductive query evaluationproblem, which is concerned with answering inductivequeries that are arbitrary boolean expressions over monotonicand anti-monotonic predicates. secondly, we developa decomposition theory for inductive query evaluation inwhich a boolean query q is reformulated into k sub-queriesq_i= q_a\wedge q_mthat are the conjunction of a monotonicand an anti-monotonic predicate. the solution to each sub-querycan be represented using a version space. we investigatehow the number of version spaces k needed to answerthe query can be minimized. thirdly, for the pattern domainof strings, we show how the version spaces can berepresented using a novel data structure, called the versionspace tree, and can be computed using a variant of the famousapriori algorithm. finally, we present some experi-mentsthat validate the approach.
a graph-ranking algorithm for geo-referencing documents. this paper presents an application of pagerank for assigning documents with a corresponding geographical scope. we describe the technique in detail, together with its theoretical formulation. experimental results are promising, comparing favorably with previous proposals.
mining significant associations in large scale text corpora. mining large-scale text corpora is an essential step in extractingthe key themes in a corpus. we motivate a quanti-tativemeasure for significant associations through the distributionsof pairs and triplets of co-occurring words. weconsider the algorithmic problem of efficiently enumerat-ingsuch significant associations and present pruning algorithmsfor these problems, with theoretical as well as empiricalanalyses. our algorithms make use of two novel miningmethods: (1) matrix mining, and (2) shortened documents.we present evidence from a diverse set of documents that ourmeasure does in fact elicit interesting co-occurrences.
correlation preserving discretization. discretization is a crucial preprocessing primitive for a variety of data warehousing and mining tasks. in this article we present a novel pca-based unsupervised algorithm for the discretization of continuous attributes in multivariate datasets. the algorithm leverages the underlying correlation structure in the dataset to obtain the discrete intervals, and ensures that the inherent correlations are preserved. the approach also extends easily to datasets containing missing values. we demonstrate the efficacy of the approach on real datasets and as a preprocessing step for both classification and frequent itemset mining tasks. we also show that the intervals are meaningful and can uncover hidden patterns in data.
neural analysis of mobile radio access network. the self-organizing map (som) is an efficient tool for visualization and clustering of multidimensional data. it transforms the input vectors on two-dimensional grid of prototype vectors and orders them. the ordered prototype vectors are easier to visualize and explore than the original data. mobile networks produce a huge amount of spatio-temporaldata. the data consists of parameters of base stations (bs)and quality information of calls. there are two alternatives in starting the data analysis. we can build either a general one-cell-model trained using state vectors from all cells, or a model of the network using state vectors with parameters from all mobile cells. in both methods,further analysis is needed to understand the reasons for various operational states of the entire network.
mining semantic networks for knowledge discovery. this paper addresses the problem of mining a class ofsemantic networks, called concept frame graphs (cfg's),for knowledge discovery from text. this new representationis motivated by the need to capture richer text content sothat non-trivial mining tasks can be performed. we firstdefine the cfg representation and then describe a rule-basedalgorithm for constructing a cfg from text documents.treating the cfg as a networked knowledge base,we propose new methods for text mining. on a specific taskof discovering the top companies in an area, we observe thatour approach leads to simpler content mining algorithms,once the cfg has been constructed. moreover, exploitingthe network structure of cfg results in significant improvementsin precision and recall.
active feature-value acquisition for classifier induction. many induction problems include missing data that can be acquired at a cost. for building accurate predictive models, acquiring complete information for all instances is often expensive or unnecessary, while acquiring information for a random subset of instances may not be most effective. active feature-value acquisition tries to reduce the cost of achieving a desired model accuracy by identifying instances for which obtaining complete information is most informative. we present an approach in which instances are selected for acquisition based on the current model's accuracy and its confidence in the prediction. experimental results demonstrate that our approach can induce accurate models using substantially fewer feature-value acquisitions as compared to alternative policies.
rdf: a density-based outlier detection method using vertical data representation. outlier detection can lead to discovering unexpected and interesting knowledge, which is critical important to some areas such as monitoring of criminal activities in electronic commerce, credit card fraud, etc. in this paper, we developed an efficient density-based outlier detection method for large datasets. our contributions are: a) we introduce a relative density factor (rdf); b) based on rdf, we propose an rdf-based outlier detection method which can efficiently prune the data points which are deep in clusters, and detect outliers only within the remaining small subset of the data; c) the performance of our method is further improved by means of a vertical data representation, p-trees. we tested our method with nhl and nba data. our method shows an order of magnitude speed improvement compared to the contemporary approaches.
privacy-sensitive bayesian network parameter learning. this paper considers the problem of learning the parameters of a bayesian network, assuming the structure of the network is given, from a privacy-sensitive dataset that is distributed between multiple parties. for a binary-valued dataset, we show that the count information required to estimate the conditional probabilities in a bayesian network can be obtained as a solution to a set of linear equations involving some inner product between the relevantdifferent feature vectors. we consider a random projection-based method that was proposed elsewhere to securely compute the inner product (with a modified implementation of that method).
discovery of association rules in tabular data. in this paper we address the problem of finding all association rules in tabular data. an algorithm, ara, for finding rules, that satisfy clearly specified constraints, in tabular data is presented. ara is based on the dense miner algorithm but includes an additional constraintand an improved method of calculating support. ara is tested and compared with our implementation of dense miner ;it is conclude that ara is usually more efficient than dense miner and is often considerably more so.we also consider the potential for modifying the constraints used in ara in order to find more generalrules.
toward xml-based knowledge discovery systems. inductive databases are intended to be general purposedatabases in which both source data and mined patterns canbe represented, retrieved and manipulated; however, theheterogeneity of models for mined patterns makes difficult torealize them. in this paper, we explore the feasibility of usingxml as the unifying framework for inductive databases,introducing a suitable data model called xdm (xml fordata mining). xdm is designed to describe source rawdata, heterogeneous mined patterns and data mining statements,so that they can be stored inside a unique xml-basedinductive database.
theory and applications of attribute decomposition. this paper examines the attribute decomposition approach with simple bayesian combination for dealing with classi£cation problems that contain high number ofattributes and moderate numbers of records. according to the attribute decomposition approach, the set of input attributes is automatically decomposed into several subsets. classi£cation model is built for each subset, then all the models are combined using simple bayesian combination.this paper presents theoretical and practical foundation for the attribute decomposition approach. a greedyprocedure, called d-ifn, is developed to decompose the input attributes set into subsets and build a classi£cation model for each subset separately. the results achieved in theempirical comparison testing with well-known classi£cationmethods (like c4.5)indicate the superiority of the decomposition approach.
privacy-preserving distributed clustering using generative models. we present a framework for clustering distributed datain unsupervised and semi-supervised scenarios, taking intoaccount privacy requirements and communication costs.rather than sharing parts of the original or perturbed data,we instead transmit the parameters of suitable generativemodels built at each local data site to a central location.we mathematically show that the best representative of allthe data is a certain "mean" model, and empirically showthat this model can be approximated quite well by generatingartificial samples from the underlying distributions usingmarkov chain monte carlo techniques, and then fittinga combined global model with a chosen parametric form tothese samples. we also propose a new measure that quantifiesprivacy based on information theoretic concepts, andshow that decreasing privacy leads to a higher quality of thecombined model and vice versa. we provide empirical resultson different data types to highlight the generality of ourframework. the results show that high quality distributedclustering can be achieved with little privacy loss and lowcommunication cost.
flexpat: flexible extraction of sequential patterns. this paper addresses sequential data mining, a sub-area of data mining where the data to be analyzed is organized in sequences. in many problem domains a natural ordering exists over data. examples of sequential databases (sdbs) include: (a)collections of temporal data sequences, such as chronologicalseries of daily stock indices or multimedia data (sound, music, video..); and (b) macromolecule banks, where aminoacid or proteic sequences are represented as strings.in a sdb it is often valuable to detect regularities through one or several sequences. in particular, finding exact or approximate repetitions of segments ca be utilized directly (e.g.for determining the biochemical activity of a protein region) or indirectly, e.g. for prediction in finance. to this end, we present concepts and an algorithm for automatically extracting sequential patterns from a sequential database. such a patter is defined as a group of significantly similar segments from one or several sequences. appropriate functions for measuringsimilarity between sequence segments are proposed, generalizing the edit distance framework. there is a trade off here between flexibility, particularly in sequence data representation and in associated similarity metrics, and computational efficiency. wedesigned the flexpat algorithm to satisfactorily cope with this trade-off. flexpat's complexity is in practice lesser than quadratic in the total length of the sdb analyzed, while allowinghigh flexibility. some experimental results obtained with flexpat on music data are presented and commented.
change profiles. in this paper we introduce a generalization of associationrules: change profiles. we analyze their properties, describetheir relationship to other structures in pattern discoveryand sketch their possible applications. we studyhow the frequent patterns can be clustered based on theirchange profiles and propose methods for approximating thefrequencies of the patterns from the approximate changeprofiles and bounding the intervals where the frequencies ofthe patterns are guaranteed to be. we evaluate empiricallythe methods for estimating the frequencies and the stabilityof their frequency estimates under different kinds of noise.
integrating customer value considerations into predictive modeling. the success of prediction models for business purposesshould not be measured by their accuracy only. theirevaluation should also take into account the higherimportance of precise prediction for "valuable"customers. we illustrate this idea through the example ofchurn modeling in telecommunications, where it isobviously much more important to identify potentialchurn among valuable customers. we discuss, boththeoretically and empirically, the optimal use of"customer value" data in the model training, modelevaluation and scoring stages. our main conclusion isthat a non-trivial approach of using "decayed" value-weightsfor training is usually preferable to the twoobvious approaches of either using non-decayed customervalues as weights or ignoring them.
o-cluster: scalable clustering of large high dimensional data sets. clustering large data sets of high dimensionality hasalways been a challenge for clustering algorithms. manyrecently developed clustering algorithms have attemptedto address either handling data sets with a very largenumber of records and/or with a very high number ofdimensions. this paper provides a discussion of theadvantages and limitations of existing algorithms whenthey operate on very large multidimensional data sets. tosimultaneously overcome both the "curse ofdimensionality" and the scalability problems associatedwith large amounts of data, we propose a new clusteringalgorithm called o-cluster. o-cluster combines a novelactive sampling technique with an axis-parallelpartitioning strategy to identify continuous areas of highdensity in the input space. the method operates on alimited memory buffer and requires at most a single scanthrough the data. we demonstrate the high quality of theobtained clustering solutions, their robustness to noise,and o-cluster's excellent scalability.
ranking-based evaluation of regression models. we suggest the use of ranking-based evaluation measures for regression models, as a complement to the commonly used residual-based evaluation. we argue that in some cases, such as the case study we present, ranking can be the main underlying goal in building a regression model, and ranking performance is the correct evaluation metric. however, even when ranking is not the contextually correct performance metric, the measures we explore still have significant advantages: they are robust against extreme outliers in the evaluation set; and they are interpretable. the two measures we consider correspond closely to non-parametric correlation coefficients commonly used in data analysis (spearman's ρ and kendall's τ); and they both have interesting graphical representations, which, similarly to roc curves, offer useful "partial" model performance views, in addition to a one-number summary in the area under the curve. we illustrate our methods on a case study of evaluating it wallet size estimation models for ibm's customers.
a heterogeneous field matching method for record linkage. record linkage is the process of determining that two records refer to the same entity. a key subprocess is evaluating how well the individual fields, or attributes, of the records match each other. one approach to matching fields is to use hand-written domain-specific rules. this "expert systems" approach may result in good performance for specific applications, but it is not scalable. this paper describes a new machine learning approach that creates expert-like rules for field matching. in our approach, the relationship between two field values is described by a set of heterogeneous transformations. previous machine learning methods used simple models to evaluate the distance between two fields. however, our approach enables more sophisticated relationships to be modeled, which better capture the complex domain specific, common-sense phenomena that humans use to judge similarity. we compare our approach to methods that rely on simpler homogeneous models in several domains. by modeling more complex relationships we produce more accurate results.
quantitative association rules based on half-spaces: an optimization approach. we tackle the problem of finding association rules for quantitative data. whereas most of the previous approaches operate on hyperrectangles, we propose a representation based on half-spaces. consequently, the left-hand side and right-hand side of an association rule does not contain a conjunction of items or intervals, but a weighted sum of variables tested against a threshold. since the downward closure property does not hold for such rules, we propose an optimization setting for finding locally optimal rules. a simple gradient descent algorithm optimizes a parameterized score function, where iterations optimizing the first separating hyperplane alternate with iterations optimizing the second. experiments with two real-world data sets show that the approach finds non-random patterns and scales up well. we therefore propose quantitative association rules based on half-spaces as an interesting new class of patterns with a high potential for applications.
employing discrete bayes error rate for discretization and feature selection. the tasks of discretization and feature selection are frequentlyused to improve classification accuracy. in this paper,we use discrete approximation of bayes error rate toperform discretization on the features. the discretizationprocedure targets minimization of bayes error rate withineach partition. a class-pair discriminatory measure can bedefined on discretized partitions which forms the basis offeature selection algorithm. small value of this measure fora class-pair indicates that the class-pair in considerationis confusing and the features which distinguish them wellshould be chosen first. a video classification problem ona large database is considered for showing the comparisonof a classifier using our discretization and feature selectiontasks with svm, neural network classifier, decision treesand k-nearest neighbor classifier
incremental learning with support vector machines. support vector machines (svms) have become a popular tool for machine learning with large amounts of high dimensional data. in this paper an approach for incremental learning with support vector machines is presented, that improves the existing approach of [3 ]. also, some insight into the interpretability of support vectors s given.
using sequential and non-sequential patterns in predictive web usage mining tasks. we describe an efficient framework for web personalizationbased on sequential and non-sequential pattern discov-eryfrom usage data. our experimental results performedon real usage data indicate that more restrictive patterns,such as contiguous sequential patterns (e.g., frequent navigationalpaths) are more suitable for predictive tasks, suchas web prefetching, which involve predicting which item isaccessed next by a user), while less constrained patterns,such as frequent itemsets or general sequential patterns aremore effective alternatives in the context of web personalizationand recommender systems.
on a capacity control using boolean kernels for the learning of boolean functions. this paper concerns the classification task discrete attribute spaces, but consider the task in a more fundamental framework: the learning of boolean functions.the purpose of this paper is to present a new learning algorithm for boolean functions called boolean kernel classifier (bkc) employing capacity control using boolean kernels.bkc uses support vector machines (svms) as learning engines and boolean kernels are primarily used for running svms in feature spaces spanned by conjunctions of boolean literals.however, another inportant role of boolean kernels is to appropriately control the size of its hypothesis space to avoid overfitting.after applying a svm to learn a classifier f in a feature space h induced by a boolean kernel f k of f onto a subspace hk of h spanned by conjunctions with length at most k, bkc can determine the smallest k such that f k is as accurate as f and learn another f' in hk expected to have lower error for unseen data.by an empirical study on learning of randomly generated boolean functions, it is shown that the capacity control is effective, and bkc outperforms c4.5 and naive bayes classifiers.
feature selection algorithms: a survey and experimental evaluation. in view of the substantial number of existing feature selection algorithms, the need arises to count on criteria that enables to adequately decide which algorithm to us in certain situations.this work assess the performance of several fundamental algorithms found in the literature in a controlled scenario.a scoring measure ranks the algorithms by taking into account the amount of relevance, irrelevance and redundance on sample data sets.this measure computer the degree of matching between the output given by the algorithm and the know optimal solution.sample size effects are also studied.
interestingness preprocessing. as the size of databases increases, the number of rules mined from them also increases, often to a extent that overwhelms users. to address this problem, an important part of the kdd process is dedicated to determining which of these patterns is interesting. in this paper we define the interestingness preprocessing step, and introduce a new framework for interestingness analysis. in asimilar fashion to data-preprocessing, this preprocessing should always be applied prior to interestingness processing. a strictrequirement, and the biggest challenge, in defining interestingness preprocessing techniques is that the preprocessing will not eliminate any potentially interesting patterns. that is, the preprocessing methods must be domain-,task-and user-independent. this property differentiates the preprocessing methods from existing interestingness criteria, and, since they can be applied automatically, makes them very useful. this generic nature also makes them rare: preprocessing methods are very challenging to define.we also define in this paper the first two preprocessing techniques, and present the empirical results of applying them to six databases. the results indicate that interestingness preprocessing step is very powerful: in most cases, an average of half the rules mined were eliminated by the application of the two interestingness preprocessing techniques. these results are particularly significant since no user-interaction is required to achieve them.
multivariate supervised discretization, a neighborhood graph approach. we present a new discretization method in the contextof supervised learning. this method entitled hyperclusterfinder is characterized by its supervised and polytheticbehavior. the method is based on the notion of clustersand processes in two steps. first, a neighborhood graphconstruction from the learning database allows discoveringhomogenous clusters. second, the minimal and maximalvalues of each cluster are transferred to each dimension inorder to define some boundaries to cut the continuous attributein a set of intervals. the discretization abilities ofthis method are illustrated by some examples, in particular,processing the xor problem.
exploring interestingness through clustering: a framework. determining interestingness is a notoriously difficultproblem: it is subjective and elusive to capture. it is alsobecoming an increasingly more important problem in kddas the number of mined patterns increases. in this work weintroduce and investigate a framework for association ruleclustering that enables automating much of the laboriousmanual effort normally involved in the exploration and understandingof interestingness. clustering is ideally suitedfor this task; it is the unsupervised organization of patternsinto groups, so that patterns in the same group are moresimilar to each other than to patterns in other groups. wealso define a data-driven inferred labeling of these clusters,the ancestor coverage, which provides an intuitive, conciserepresentation of the clusters.
automatically mining result records from search engine response pages. usually, web applications such as deep web crawlers, metasearch engines, and other web mining systems need to extract information displayed in the form of result records on response pages returned by search engines in response to submitted queries. extracting such records is challenging as search engines are heterogeneous in displaying their records. in addition, response pages returned by many search engines include other noisy content such as advertisements, suggestion links, etc., which make the extraction task even more complicated. in this paper, we propose a highly effective and efficient algorithm for automatically mining result records from search engine response pages.
on incorporating subjective interestingness into the mining process. subjective interestingness is at the heart of thesuccessful discovery of association rules. to determine what is subjectively interesting, users' domainknowledge must be applied. [7] introduced an approach that requires very little domain knowledgeand inter action to eliminate the majority of therules that are subjectively not interesting. in thispaper we investigate how this approach can be incorporated into the mining process, the benefits anddisadvantages of doing so, and examine the resultsof its application to real databases.
complex spatial relationships. this paper describes the need for mining complex relationshipsin spatial data. complex relationships are definedas those involving two or more of: multi-feature colocation,self-colocation, one-to-many relationships, self-exclusionand multi-feature exclusion. we demonstrate that even inthe mining of simple relationships, knowledge of complexrelationships is necessary to accurately calculate the significanceof results. we implement a representation of spatialdata such that it contains known 'weak-monotonic' properties,which are exploited for the efficient mining of complexrelationships, and discuss the strengths and limitations ofthis representation.
data analysis and mining in ordered information tables. many real world problems deal with ordering objects instead of classifying objects, although majority of research in machine learning and data mining has been focused on the latter. for modeling ordering problems, we generalize the notion of information tables to ordered information tables by adding order relations on attribute values. the problem of mining ordering rules is formulated as findingassociation between orderings of attribute values and the overall ordering of objects. an ordering rules ay state that "if the value of an object x on an attribute a is ordered ahead of the value of another object y on the same attribute, then x is ordered ahead of y" for mining ordering rules, we first transform an ordered information table into a binaryinformation, and then apply any standard machine learning and data mining algorithms. as an illustration, we analyze in detail maclean's universities ranking for the year 2000.
the eq framework for learning equivalence classes of bayesian networks. this paper proposes a theoretical and an algorithmic framework for the analysis and the design of efficient learning algorithms which explore the space of equivalence classes of bayesian network structures.this framework is composed of a generic learning model which uses essential graphs and more general partially directed graphs i order to represent the equivalence classes evaluated during search, operational characterizations of these graphs, processing procedures and formulas for directly calculating their score.the experimental results of the algorithms designed within this framework show that the space of equivalence classes may be explored efficiently and with better results than the classical search in the space of bayesian network structures.
mining constrained association rules to predict heart disease. this work describes our experiences on discovering association rules in medical data to predict heart disease. we focus on two aspects in this work: mapping medical data toa transaction format suitable for mining association rules and identifying useful constraints. based on these aspects we introduce an improved algorithm to discover constrainedassociation rules. we present an experimental sectionexplaining several interesting discovered rules.
bayesian data mining on the web with b-course. b-course is a free 1 web-based bayesian data mining service. this service allows the users to analyze their own data for multivariate probabilistic dependencies represented as bayesian network models. in addition to this, b-course also offers facilities for inferring certain type of causal dependencies from the data. the software is especially suitable for educational purposes as the tutorial style user-friendly interface intertwines the steps in the data analysiswith support material that gives an informal introduction to the bayesian approach adopted. nevertheless, although the analysis methods, modeling assumptions and restrictionsare totally transparent to the user, this transparency is not achieved at the expense of analysis power: with the restrictions stated in the support material, b-course is a powerful analysis tool exploiting several theoretically elaborate results developed recently in the fields of bayesian and causal modeling.
evaluating attraction in spatial point patterns with an application in the field of cultural history. spatial collocation rules are often useful for describing dependencies between spatial features. still, the commonly used criteria for the interestingness of the rules and the selected neighbourhood constraints for spatial objects may be too rough for capturing the essentials of such dependencies. we demonstrate the difficulties with concrete examples on a large place-name data set. we propose a technique based on simple density estimation for assessing the interestingness with different neighbouring constraints.
tecno-streams: tracking evolving clusters in noisy data streams with a scalable immune system learning model. artificial immune system (ais) models hold many promises inthe field of unsupervised learning. however, existing models arenot scalable, which makes them of limited use in data mining. wepropose a new ais based clustering approach (tecno-streams)that addresses the weaknesses of current ais models. comparedto existing ais based techniques, our approach exhibits superiorlearning abilities, while at the same time, requiring low memoryand computational costs. like the natural immune system, thestrongest advantage of immune based learning compared to otherapproaches is expected to be its ease of adaptation to the dynamicenvironment that characterizes several applications, particularlyin mining data streams. we illustrate the ability of the proposedapproach in detecting clusters in noisy data sets, and in miningevolving user profiles from web clickstream data in a single pass.tecno-streams adheres to all the requirements of clusteringdata streams: compactness of representation, fast incremental processingof new data points, and clear and fast identification of outliers.
a clustering method for very large mixed data sets. in the developed countries, especially over the last decade, there has been an explosive growth in the capability to generate, collect and use very large data sets. the objects of these data sets could be simultaneously described by quantitative and qualitative attributes. at present, algorithms able to process either very large data sets (in metric spaces) or mixed(qualitative and quantitative) incomplete data (missing value) sets have been developed, but not for very large mixed incomplete data sets. in this paper we introduce a new clustering method named glc+to process very large mixed incomplete data sets in order to obtain apartition in connected sets.
dependency networks for relational data. instance independence is a critical assumption of traditional machine learning methods contradicted by many relational datasets. for example, in scientific literature datasets there are dependencies among the references of a paper. recent work on graphical models for relational data has demonstrated significant performance gains for models that exploit the dependencies among instances. in this paper, we present relational dependency networks (rdns), a new form of graphical model capable of reasoning with such dependencies in a relational setting. we describe the details of rdn models and outline their strengths, most notably the ability to learn and reason with cyclic relational dependencies. we present rdn models learned on a number of real-world datasets, and evaluate the models in a classification context, showing significant performance improvements. in addition, we use synthetic data to evaluate the quality of model learning and inference procedures.
leveraging relational autocorrelation with latent group models. the presence of autocorrelation provides a strong motivation for using relational learning and inference techniques. autocorrelation is a statistical dependence between the values of the same variable on related entities and is a nearly ubiquitous characteristic of relational data sets. recent research has explored the use of collective inference techniques to exploit this phenomenon. these techniques achieve significant performance gains by modeling observed correlations among class labels of related instances, but the models fail to capture a frequent cause of autocorrelation - the presence of underlying groups that influence the attributes on a set of entities. we propose a latent group model (lgm) for relational data, which discovers and exploits the hidden structures responsible for the observed autocorrelation among class labels. modeling the latent group structure improves model performance, increases inference efficiency, and enhances our understanding of the datasets. we evaluate performance on three relational classification tasks and show that lgm outperforms models that ignore latent group structure, particularly when there is little information with which to seed inference.
compound classification models for recommender systems. recommender systems recommend products to customers based on ratings or past customer behavior. without any information about attributes of the products or customers involved, the problem has been tackled most successfully by a nearest neighbor method called collaborative filtering in the context, while additional efforts invested in building classification models did not pay off and did not increase the quality. therefore, classification methods have mainly been used in conjunction with product or customer attributes. starting from a view on the plain recommendation task without attributes as a multi-class classification problem, we investigate two particularities, its autocorrelation structure as well as the absence of re-occurring items (repeat buying). we adapt the standard generic reductions 1-vs-rest and 1-vs-1 of multi-class problems to a set of binary classification problems to these particularities and thereby provide a generic compound classifier for recommender systems. we evaluate a particular specialization thereof using linear support vector machines as member classifiers on movielens data and show that it outperforms state-of-the-artmethods, i.e., item-based collaborative filtering.
simple estimators for relational bayesian classifiers. in this paper we present the relational bayesianclassifier (rbc), a modification of the simple bayesianclassifier (sbc) for relational data. there exist severalbayesian classifiers that learn predictive models ofrelational data, but each uses a different estimationtechnique for modeling heterogeneous sets of attributevalues. the effects of data characteristics on estimationhave not been explored. we consider four simpleestimation techniques and evaluate them on three real-worlddata sets. the estimator that assumes each multisetvalue is independently drawn from the same distribution(indepval) achieves the best empirical results. weexamine bias and variance tradeoffs over a range of datasets and show that indepval's ability to model moremultiset information results in lower bias estimates andcontributes to its superior performance.
on the tractability of rule discovery from distributed data. this paper analyses the tractability of rule selection for supervised learning in distributed scenarios. the selection of rules is usually guided by a utility measure such as predictive accuracy or weighted relative accuracy. a common strategy to tackle rule selection from distributed data is to evaluate rules locally on each dataset. while this works well for homogeneously distributed data, this work proves limitations of this strategy if distributions are allowed to deviate. the identification of those subsets for which local and global distributions deviate, poses a learning task of its own, which is shown to be at least as complex as discovering the globally best rules from local data.
mining association rules from stars. association rule mining is an important data mining problem.it is found to be useful for conventional relational data.however, previous work had mostly targeted on mining a single table.in real life, a database is typically made up of multiple table and one important case is where some of the tables form a star schema.that tables typically correspond to entity sets and joining the tables in a star schema gives relationship amoung entity sets which can be very interesting information.hence mining on the join result is an important problem.based on characteristics of the star schema we propose an efficient algorithm for mining association rules on the joinresult but without actually performing the join opertation.we show that this approach can significantly out-perform the join-then-mine approach even when the latter adopts a fastest known mining algorithm.
a high-performance distributed algorithm for mining association rules. we present a new distributed association rule mining(d-arm) algorithm that demonstrates superlinear speedupwith the number of computing nodes. the algorithm isthe first d-arm algorithm to perform a single scan overthe database. as such, its performance is unmatched byany previous algorithm. scale-up experiments over standard synthetic benchmarks demonstrate stable run time regardless of the number of computers. theoretical analysisreveals a tighter bound on error probability than the oneshown in the corresponding sequential algorithm.
visualizing association mining results through hierarchical clusters. we propose a new methodology for visualizing association mining results. inter-item distances are computed from combinations of item set supports. the new distances retain a simple pairwise structure, and are consistent with important frequently occurring item sets. thus standard tools of visualization, e.g. hierarchical clustering dendrograms can still be applied, while the distance information upon which they are based is richer. our approach is applicable to general association mining applications, as well as applications involving information spaces modeled by directed graphs, e.g. the web. in the context of collections of hypertext documents, the inter-document distances capture the information inherent in a collection's link structure, a for of link mining. we demonstrate our methodology with document sets extracted fro the science citation index, applying a metric that measures consistency between clusters and frequent itemsets.
impact studies and sensitivity analysis in medical data mining with roc-based genetic learning. roc curves have been used for a fair comparison of machinelearning algorithms since the late 90's. accordingly,the area under the roc curve (auc) is nowadays considereda relevant learning criterion, accommodating imbalanceddata, misclassification costs and noisy data.this paper shows how a genetic algorithm-based optimizationof the auc criterion can be exploited for impactstudies and sensitivity analysis.the approach is illustrated on the atherosclerosis identificationproblem, pkdd 2002 challenge.
an experimental comparison of supervised and unsupervised approaches to text summarization. the paper presents a direct comparison of supervised and unsupervised approaches to text summarization. as a representative supervised method, we use the c4.5 decision tree algorithm, extended with the minimum description length principle (mdl), and compare it against several unsupervised methods. it is found that a particular un-supervised method based on an extension of the k-means clustering algorithm, performs equal to and in some cases superior to the decision tree based method.
exploring the parameter state space of stacking. ensemble learning schemes are a new field in data mining.while current research concentrates mainly on improvingthe performance of single learning algorithms, an alternativeis to combine learners with different biases. stackingis the best-known such scheme which tries to combine learners'predictions or confidences via another learning algorithm.however, the adoption of stacking into the data mining communityis hampered by its large parameter space, consistingmainly of other learning algorithms: (1) the set of learning algorithmsto combine, (2) the meta-learner responsible for thecombining and (3) the type of meta-data to use: confidencesor predictions. none of these parameters are obvious choices.furthermore, little is known about the relation between parametersettings and performance of stacking. by exploring all ofstacking's parameter settings and their interdependencies, weintend make stacking a suitable choice for mainstream datamining applications.
efficient data mining for maximal frequent subtrees. a new type of tree mining is defined in this paper,which uncovers maximal frequent induced subtrees from adatabase of unordered labeled trees. a novel algorithm,pathjoin, is proposed. the algorithm uses a compact datastructure, fst-forest, which compresses the trees and stillkeeps the original tree structure. pathjoin generates candidatesubtrees by joining the frequent paths in fst-forest.such candidate subtree generation is localized and thussubstantially reduces the number of candidate subtrees. experimentswith synthetic data sets show that the algorithmis effective and efficient.
evaluating the utility of statistical phrases and latent semantic indexing for text classification. the term-based vector space model is a prominenttechnique to retrieve textual information. in this paper weexamine the usefulness of phrases as terms in vector-baseddocument classification. we focus on statistical techniquesto extract both adjacent and window phrases fromdocuments. we discover that the positive effect of addingphrase terms is very limited, if we have already achievedgood performance using single-word terms, even whensvd/lsi is used as dimensionality reduction method.
cluster cores-based clustering for high dimensional data. we propose a new approach to clustering high dimensional data based on a novel notion of cluster cores, instead of on nearest neighbors. a cluster core is a fairly dense group with a maximal number of pairwise similar objects. it represents the core of a cluster, as all objects in a cluster are with a great degree attracted to it. as a result, building clusters from cluster cores achieves high accuracy. other major characteristics of the approach include: (1) it uses a semantics-based similarity measure. (2) it does not incur the curse of dimensionality and is scalable linearly with the dimensionality of data. (3) it outperforms the well-known clustering algorithm, rock, with both lower time complexity and higher accuracy.
objective-oriented utility-based association mining. the necessity to develop methods for discovering associationpatterns to increase business utility of an enterprisehas long been recognized in data mining community.this requires modeling specific association patterns thatare both statistically (based on support and confidence) andsemantically (based on objective utility) relating to a givenobjective that a user wants to achieve or is interested in.however, we notice that no such a general model has beenreported in the literature. traditional association miningfocuses on deriving correlations among a set of items andtheir association rules like diaper ¿ beer only tell us thata pattern like fdiaperg is statistically related to an itemlike beer. in this paper, we present a new approach, calledobjective-oriented utility-based association (ooa)mining,to modeling such association patterns that are explicitlyrelating to a user's objective and its utility. due to its focuson a user's objective and the use of objective utility as keysemantic information to measure the usefulness of associationpatterns, ooa mining differs significantly from existingapproaches such as the existing constraint-based associationmining. we formally define ooa mining and developan algorithm for mining ooa rules. the algorithm is anenhancement to apriori with specific mechanisms for handlingobjective utility. we prove that the utility constraint isneither monotone nor anti-monotone nor succinct nor convertibleand present a novel pruning strategy based on theutility constraint to improve the efficiency of ooa mining.
face recognition using landmark-based bidimensional regression. this paper studies how biologically meaningful landmarks extracted from face images can be exploited for face recognition using the bidimensional regression. incorporating the correlation statistics of landmarks, this paper also proposes a new approach called eigenvalue weighted bidimensional regression. complex principal component analysis is used for computing eigenvalues and removing correlation among landmarks. we evaluate our approach using two standard face databases: the purdue ar and the nist feret. experimental results show that the bidimensional regression is an efficient method to exploit geometry information of face images.
k-d decision tree: an accelerated and memory efficient nearest neighbor classifier. most nearest neighbor (nn) classifiers employ nn searchalgorithms for the acceleration. however, nnclassification does not always require the nn search.based on this idea, we propose a novel algorithm namedk-d decision tree (kddt). since kddt uses voronoicondensed prototypes, it is less memory consuming thannaive nn classifiers. we have confirmed that kddt ismuch faster than nn search based classifiers through thecomparative experiment (from 9 to 369 times faster).
a self-organizing map with expanding force for data clustering and visualization. the self-organizing map (som) is a powerful tool in theexploratory phase of data mining. however, due to the dimensional conflict, the neighborhood preservation cannotalways lead to perfect topology preservation. in this paper, we establish an expanding som (esom) to detect andpreserve better topology correspondence between the twospaces. our experiment results demonstrate that the esomconstructs better mappings than the classic som in terms ofboth the topological and the quantization errors. furthermore, clustering results generated by the esom are moreaccurate than those by the som.
learning functional dependency networks based on genetic programming. bayesian network (bn) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. but bn can handle discrete values only; it cannot handle continuous, interval and ordinal ones, which must be converted to discrete values and the order information is lost. thus, bn tends to have higher network complexity and lower understandability. in this paper, we present a novel dependency network which can handle discrete, continuous, interval and ordinal values through functions; it has lower network complexity and stronger expressive power; it can represent any kind of relationships; and it can incorporate a-priori knowledge though user-defined functions. we also propose a novel genetic programming (gp) to learn dependency networks. the novel gp does not use any knowledge-guided nor application-oriented operator, thus it is robust and easy to replicate. the experimental results demonstrate that the novel gp can successfully discover the target novel dependency networks, which have the highest accuracy and the lowest network complexity.
instability of classifiers on categorical data. in this paper we study the local behaviour of arbitrary classifiers using the instability of that classifier in a data point. moreover, we introduce two algorithms. the first to find highly unstable points, the second to find islands of stability.
mining patterns of change in remote sensing image databases. remote sensing image databases are the fastest growing archives of spatial information. however, we still have a limited capacity for extracting information from large remote sensing image databases. there are currently very few techniques for image data mining and information extraction in large image data sets, and thus we are failing to exploit our large remote sensing data archives. this paper proposes a methodology to provide guidance for mining remote sensing image databases. the basic idea is to use domain concepts to build generic description of patterns in remote sensing images, and then use structural approaches to identify such patterns in images. we illustrate our proposal with a case study for detecting land use patterns in amazonia from inpe's remote sensing image database.
document clustering and cluster topic extraction in multilingual corpora. a statistics-based approach for clustering documents and for extracting cluster topics is described. relevant (meaningful) expressions (res) automatically extracted from corpora are used as clustering base features. these features are transformed and its number is strongly reduced in order to obtain a small set of document classificationfeatures. this is achieved on the basis of principalcomponents analysis. model-based clustering analysis finds thebest number of clusters. then, the most important res are extracted from each cluster and taken as document cluster topics.
metric incremental clustering of nominal data. we present an algorithm for clustering nominal data that is based on a metric on the set of partitions of a finite set of objects; this metric is defined starting from a lower valuation of the lattice of partitions. the proposed algorithm seeks to determine a clustering partition such that the total distance between this partition and the partitions determined by the attributes of the objects has a local minimum. the resulting clustering is quite stable relative to the ordering of the objects.
pruning social networks using structural properties and descriptive attributes. scale is often an issue with understanding and making sense of large social networks. here we investigate methods for pruning social networks by determining the most relevant relationships. we measure importance in terms of predictive accuracy on a set of target attributes of the social network. our goal is to create a pruned network that models only the most informative affiliations and relationships. we present methods for pruning networks based on both structural properties and descriptive attributes demonstrate it on a network of nasdaq and nyse businesses and on a bibliographic network.
closeminer: discovering frequent closed itemsets using frequent closed tidsets. complete set of itemsets can be grouped into non-overlapping clusters identified by closed tidsets. each cluster has only one closed itemset and is the superset of all itemsets with the same support. number of closed itemsets is identical to the number of clusters. therefore, the problem of discovering closed itemsets can be considered as the problem of clustering the complete set of itemsets by closed tidsets. in this paper, we present closeminer, a new algorithm for discovering all frequent closed itemsets by grouping the complete set of itemsets into non-overlapping clusters identified by closed tidsets. an extensive experimental evaluation on a number of real and synthetic databases shows that closeminer outperforms apriori and charm.
a simple knn algorithm for text categorization. text categoriztion (also called text classification) is the process of identifying the class to which a text document belongs. this paper proposes to use a simple non-weighted feature knn algorithm for text caegoriztion. we propose to use a feature selection method that finds the relevant features for the learning task at hand using feature interaction (based on word interdependencies).
optimizing constraint-based mining by automatically relaxing constraints. in constraint-based mining, the monotone and anti-monotone properties are exploited to reduce the search space. even if a constraint has not such suitable properties, existing algorithms can be re-used thanks to an approximation, called relaxation. in this paper, we automatically compute monotone relaxations of primitive-based constraints. first, we show that the latter are a superclass of combinations of both kinds of monotone constraints. second, we add two operators to detect the properties of monotonicity of such constraints. finally, we define relaxing operators to obtain monotone relaxations of them.
probabilistic principal surfaces for yeast gene microarray data mining. the recent technological advances are producing huge data sets in almost all fields of scientific research, from astronomy to genetics. although each research field often requires ad-hoc, fine tuned, procedures to properly exploit all the available information inherently present in the data, there is an urgent need for a new generation of general computational theories and tools capable to boost most human activities of data analysis. here we propose probabilistic principal surfaces (pps) as an effective high-d data visualization and clustering tool for data mining applications, emphasizing its flexibility and generality of use in data-rich field. in order to better illustrate the potentialities of the method, we also provide a real world case-study by discussing the use of pps for the analysis of yeast gene expression levels from microarray chips.
generalizing the notion of confidence. in this paper, we explore extending association analysis to non-traditional types of patterns and non-binary data by generalizing the notion of confidence. the key idea is to regard confidence as a measure of the extent to which the strength of one association pattern provides information about the strength of another. this approach provides a framework that encompasses the traditional concept of confidence as a special case and can be used as the basis for designing a variety of new confidence measures. besides discussing such confidence measures, we provide examples that illustrate the potential usefulness of a generalized notion of confidence. in particular, we describe an approach to defining confidence for error tolerant itemsets that preserves the interpretation of confidence as a conditional probability and derive a confidence measure for continuous data that agrees with the standard confidence measure when applied to binary transaction data.
measuring real-time predictive models. in this paper we examine the problem of comparing real-time predictive models and propose a number of measures for selecting the best model, based on a combination of accuracy, timeliness, and cost. we apply the measure to the real-time attrition problem.
svm feature selection for classification of spect images of alzheimer's disease using spatial information. alzheimer's disease is the most frequent type of dementia for elderly patients. due to aging populations the occurrence of this disease will increase in the next years. early diagnosis is crucial to be able to develop more powerful treatments. brain perfusion changes can be a marker for alzheimer's disease. in this article we study the use of spect perfusion imaging for the diagnosis of alzheimer's disease differentiating between images from healthy subjects and images from alzheimer's disease patients. our classification approach is based on a linear programming formulation similar to the 1-norm support vector machines. in contrastwith other linear hyperplane-based methods that perform simultaneous feature selection and classification, our proposed formulation incorporates proximity information about the features and generates a classifier that does not just select the most relevant voxels but the most relevant "areas" for classification resulting in more robust classifiersthat are better suitable for interpretation. this approach is compared with the classical fisher linear discriminant (fld) classifier as well as with statistical parametric mapping (spm). we tested our method on data from four european institutions. our method achieved sensitivity of 84.4% at 90.9% specificity, this is considerable better the human experts. our method also outperformed the fld and spm techniques. we conclude that our approach has the potential to be a useful help for clinicians.
evolutionary gabor filter optimization with application to vehicle detection. despite the considerable amount of research work on the applicationof gabor filters in pattern classification, their design and selectionhave been mostly done on a trial and error basis. existing techniques areeither only suitable for a small number of filters or less problem-oriented.a systematic and general evolutionary gabor filter optimization (egfo)approach that yields a more optimal, problem-specific, set of filters is proposedin this study. the egfo approach unifies filter design with filter selectionby integrating genetic algorithms (gas) with an incremental clusteringapproach. specifically, filter design is performed using gas, a globaloptimization approach that encodes the parameters of the gabor filters ina chromosome and uses genetic operators to optimize them. filter selectionis performed by grouping together filters having similar characteristics(i.e., similar parameters) using incremental clustering in the parameterspace. each group of filters is represented by a single filter whose parameterscorrespond to the average parameters of the filters in the group. thisstep eliminates redundant filters, leading to a compact, optimized set of filters.the average filters are evaluated using an application-oriented fitnesscriterion based on support vector machines (svms). to demonstrate theeffectiveness of the proposed framework, we have considered the challengingproblem of vehicle detection from gray-scale images. our experimentalresults illustrate that the set of gabor filters, specifically optimized for theproblem of vehicle detection, yield better performance than using traditionalfilter banks.
on local spatial outliers. we propose a measure, spatial local outlier measure (slom) which captures the local behaviour of datum in their spatial neighborhood. with the help of slom we are able to discern local spatial outliers which are usually missed by global techniques like "three standard deviations away from the mean". furthermore the measure takes into account the local stability around a data point and supresses the reporting of outliers in highly unstable areas, where data is too heterogeneous and the notion of outliers is not meaningful. we prove several properties of slom and report experiments on synthetic and real data sets which show that our approach is novel and scalable to large data sets.
supervised latent semantic indexing for document categorization. latent semantic indexing (lsi) is a successful technology in information retrieval (ir) which attempts to explore the latent semantics implied by a query or a document through representing them in a dimension-reduced space. however, lsi is not optimal for document categorization tasks because it aims to find the most representative features for document representation rather than the most discriminative ones. in this paper, we propose supervised lsi (slsi) which selects the most discriminative basis vectors using the training data iteratively. the extracted vectors are then used to project the documents into a reduced dimensional space for better classification. experimental evaluations show that the slsi approach leads to dramatic dimension reduction while achieving good classification results.
hierarchical text classification and evaluation. hierarchical classification refers to assigning of one or more suitable categories from a hierarchical category space to a document. while previous work in hierarchical classification focused on virtual category trees where documents are assigned only to the leaf categories, we propose atop-down level-based classification method that can classify documents to both leaf and internal categories. as the standard performance measures assume independence between categories, they have not considered the documents incorrectly classified into categories that are similar or not far from the correct ones in the category tree. we therefore propose the category-similarity measures and distance-based measures to consider the degree of misclassification in measuring the classification performance. an experiment has been carried out to measure the performance four proposed hierarchical classification method. the results showed that our method performs well for reuters text collection when enough training documents are given andthe new measures have indeed considered the contributions of misclassified documents.
introducing uncertainty into pattern discovery in temporal event sequences. pattern discovery in temporal event sequences is of greatimportance in many application domains, such as telecommunicationnetwork fault analysis. in reality, not every typeof event has an accurate timestamp. some of them, definedas inaccurate events in this paper, may only have an intervalas possible time of occurrence. the existence of inaccurateevents may cause uncertainty in event ordering. thetraditional support model cannot deal with this uncertainty,which would cause some interesting patterns to be missing.in this paper, a new concept, precise support, is introducedto evaluate the probability of a pattern contained in a sequence.based on this new metric, we define the uncertaintymodel and present an algorithm to discover interesting patternsin the sequence database that has one type of inaccurateevent. in our model, the number of types of inaccurateevents can be extended to k readily, however, at a cost ofincreasing computational complexity.
neighborhood formation and anomaly detection in bipartite graphs. many real applications can be modeled using bipartite graphs, such as users vs. files in a p2p system, traders vs. stocks in a financial trading system, conferences vs. authors in a scientific publication network, and so on. we introduce two operations on bipartite graphs: 1) identifying similar nodes (neighborhood formation), and 2) finding abnormal nodes (anomaly detection). and we propose algorithms to compute the neighborhood for each node using random walk with restarts and graph partitioning; we also propose algorithms to identify abnormal nodes, using neighborhood information. we evaluate the quality of neighborhoods based on semantics of the datasets, and we also measure the performance of the anomaly detection algorithm with manually injected anomalies. both effectiveness and efficiency of the methods are confirmed by experiments on several real datasets.
a border-based approach for hiding sensitive frequent itemsets. sharing data among organizations often leads to mutual benefit. recent technology in data mining has enabled efficientextraction of knowledge from large databases. this, however, increases risks of disclosing the sensitive knowledge when the database is released to other parties. to address this privacy issue, one may sanitize the original database so that the sensitive knowledge is hidden. the challenge is to minimize the side effect on the quality of the sanitized database so that non-sensitive knowledge can still be mined. in this paper, we study such a problem in the context of hiding sensitive frequent itemsets by judiciously modifying the transactions in the database. to preserve the non-sensitive frequent itemsets, we propose a border-based approach to efficiently evaluate the impact of any modification to the database during the hiding process. the quality of database can be well maintained by greedily selecting the modifications with minimal side effect. experiments results are also reported to show the effectiveness of the proposed approach.
detecting interesting exceptions from medical test data with visual summarization. in this paper, we propose a method which visualizes irregularmulti-dimensional time-series data as a sequence ofprobabilistic prototypes for detecting exceptions from medicaltest data. conventional visualization methods often requireiterative analysis and considerable skill thus are nottotally supported by a wide range of medical experts. ourprototypelines displays summarized information based ona probabilistic mixture model by using hue only thus is consideredto exhibit novelty. the effectiveness of the summarizationis pursued mainly through use of a novel informationcriterion. we report our endeavor with chronic hepatitisdata, especially discoveries of interesting exceptions bya non-expert and an untrained expert.
x-mhmm: an efficient algorithm for training mixtures of hmms when the number of mixtures is unknown. in this paper we consider sequence clustering problems and propose an algorithm for the estimation of the number of clusters based on the x-means algorithm. the sequences are modeled using mixtures of hidden markov models. by means of experiments with synthetic data we analyze the proposed algorithm. this algorithm proved to be both computationally efficient and capable of providing accurate estimates of the number of clusters. some results of experiments with real-world web-log data are also given.
a random walk through human associations. letting one's thoughts wander is not simply an arbitrary or rambling process. it can better be described as "associative thinking", where a complex chain of associative thoughts and ideas are linked. it is our contention that this seemingly chaotic process can be modeled by a random walk in a weighted directed graph. furthermore, is it possible to predict mathematically the "steady state" of such a process, to determine where such wandering is leading. the random walk process uses rules of association, defined by the local confidence gain (lcg) interestingness measure. extracted concepts are used as nodes of a directed graph. the associative "forces" between any two concepts (measured by lcg) are used to weigh the edges connecting the nodes that create a graph of associations. it is common, yet not trivial, for people to look for data about a subject without knowing its exact nomenclature (for example, finding the name of a disease just by knowing its symptoms). random walk in association graphs can discover highly informative phrases that can be used for query expansion in a way that better expresses the user's initial search goals. a different usage is to create a user profile representing his current interests. we used a modified version of the turing test to show that the random walk process discovers association rules that conform to a human associations generating process. by constructing the user associations we were able to build a profile representing the user's "line of thoughts". the suggested algorithm can be used in any database and can implement the ranking measures of other association rules.
mining the web to discover the meanings of an ambiguous word. in information retrieval and text mining, informationon word senses is usually taken from dictionaries or lexicaldatabases that have been prepared by lexicographers.in this paper we propose an automatic method for wordsense induction, i.e. for the discovery of a set of sensedescriptors to a given ambiguous word. the approach isbased on the statistics of word co-occurrence as derivedfrom web pages. the underlying assumption is that thesenses of an ambiguous word are best described by termsthat, although bearing a strong association to this word,are mutually exclusive, i.e. whose association strengthwithin the retrieved web pages is as weak as possible.measuring association strength is based upon a novelconfidence gain approach that relates the observed co-occurrencefrequency for two sense descriptor candidatesto an average co-occurrence frequency for pairs of arbitrarywords. the proposed approach is fully unsupervisedand takes into account the contemporary meanings ofwords, as reflected in texts from the internet. our resultsare evaluated using a list of ambiguous words commonlyreferred to in the literature.
bias analysis in text classification for highly skewed data. feature selection is often applied to high-dimensional data as a preprocessing step in text classification. when dealing with highly skewed data, we observe that typical feature selection metrics like information gain or chi-squared are biased toward selecting features for the minor class, and the metric of bi-normal separation can select features for both minor and major classes. in this work, we investigate how these feature selection metrics impact on the performance of frequently used classifiers such as decision trees, na¨ýve bayes, and support vector machines via bias analysis for highly skewed data. three types of biases are metric bias, class bias, and classifier bias. extensive experiments are designed to understand how these biases can be employed in concert and efficiently to achieve good classificationperformance. we report our findings and present recommended approaches to text classification based on bias analysis and the empirical study.
supervised tensor learning. this paper aims to take general tensors as inputs for supervised learning. a supervised tensor learning (stl) framework is established for convex optimization based learning techniques such as support vector machines (svm) and minimax probability machines (mpm). within the stl framework, many conventional learning machines can be generalized to take n^th-order tensors as inputs. we also study the applications of tensors to learning machine design and feature extraction by linear discriminant analysis (lda). our method for tensor based feature extraction is named the tenor rank-one discriminant analysis (tr1da). these generalized algorithms have several advantages: 1) reduce the curse of dimension problem in machine learning and data mining; 2) avoid the failure to converge; and 3) achieve better separation between the different categories of samples. as an example, we generalize mpm to its stl version, which is named the tensor mpm (tmpm). tmpm learns a series of tensor projections iteratively. it is then evaluated against the original mpm. our experiments on a binary classification problem show that tmpm significantly outperforms the original mpm.
applying noise handling techniques to genomic data: a case study. osteogenesis imperfecta (oi) is a genetic collagenousdisease associated with mutations in one or both of thegenes colia1 and colia2. there are at least four knownphenotypes of oi, of which type ii is the severest and oftenlethal. we identified three approaches to noise handling,namely, robust algorithms, filtering, and polishing,and evaluated their effectiveness when applied to the problemof classifying the disease oi based on a data set ofamino acid sequences and associated information of pointmutations of colia1. preliminary results suggest that eachnoise handling mechanism can be useful under different circumstances.filtering is stable across all cases. pruningwith robust c4.5 increased the classification accuracy insome cases, and polishing gave rise to some additional improvementin classifying the lethal oi phenotype.
on the mining of substitution rules for statistically dependent items. in this paper, a new mining capability, called mining ofsubstitution rules, is explored. a substitution refers to thechoice made by a customer to replace the purchase of someitems with that of others. the process of mining substitutionrules can be decomposed into two procedures. the first procedureis to identify concrete itemsets among a large numberof frequent itemsets, where a concrete itemset is a frequentitemset whose items are statistically dependent. thesecond procedure is then on the substitution rule generation.two concrete itemsets x and y form a substitutionrule, denoted by x \triangleright y to mean that x is a substitute for y,if and only if (1) x and y are negatively correlated and (2)the negative association rule x \to \overline y exists. in this paper,we derive theoretical properties for the model of substitutionrule mining. then, in light of these properties, algorithmsrm (standing for substitution rule mining) is designedand implemented to discover the substitution rulesefficiently while attaining good statistical significance. empiricalstudies are performed to evaluate the performance ofalgorithm srm proposed. it is shown that algorithm srmproduces substitution rules of very high quality.
a hybrid data-mining approach in genomics and text structures. we introduce a genetic sequence identifier based on ahierarchical system using fuzzy and classic (crisp) neuralnetworks. the system is based on a set of predictors andon a decision network. the prediction of the structure ofthe genes is addressed using a new method and tools,involving the sequence of distances between bases andneuro-fuzzy predictors. the method and system have beensuccessful in predicting genomic sequences and textstructures.
treefinder: a first step towards xml data mining. in this paper, we consider the problem of searching fre-quenttrees from a collection of tree-structured data model-ingxml data. the treef inder algorithm aims at findingtrees, such that their exact or perturbed copies are frequentin a collection of labelled trees.to cope with complexity issues, treef inder is correctbut not complete: it finds a subset of the actually frequenttrees. the default of completeness is experimentally inves-tigatedon artificial medium size datasets; it is shown thattreefinderreaches completeness or falls short to it for arange of experimental settings.
dryade: a new approach for discovering closed frequent trees in heterogeneous tree databases. in this paper we present a novel algorithm for discovering tree patterns in a tree database. this algorithm uses a relaxed tree inclusion definition, making the problem more complex (checking tree inclusion is np-complete), but allowing to mine highly heterogeneous databases. to obtain good performances, our dryade algorithm discovers only closed frequent tree patterns.
efficient mining of high branching factor attribute trees. in this paper, we present a new tree mining algorithm, dryadeparent, based on the hooking principle first introduced in dryade [9]. in the experiments, we demonstrate that the branching factor and depth of the frequent patterns to find are key factor of complexity for tree mining algorithms. we show that dryadeparent outperforms the current fastest algorithm, cmtreeminer, by orders of magnitude on datasets where the frequent patterns have a high branching factor.
mmac: a new multi-class, multi-label associative classification approach. building fast and accurate classifiers for large-scale databases is an important task in data mining. there is growing evidence that integrating classification and association rule mining together can produce more efficient and accurate classifiers than traditional classification techniques. in this paper, the problem of producing rules with multiple labels is investigated. we propose a new associative classification approach called multi-class, multi-label associative classification (mmac). this paper also presents three measures for evaluating the accuracy of data mining classification approaches to a wide range of traditional and multi-label classification problems. results for 28 different datasets show that the mmac approach is an accurate and effective classification technique, highly competitive and scalable in comparison with other classification approaches.
learning bayesian networks from incomplete data based on emi method. currently, there are few efficient methods in practice forlearning bayesian networks from incomplete data, whichaffects their use in real world data mining applications.this paper presents a general-duty method that estimatesthe (conditional) mutual information directly from incompletedatasets, emi. emi starts by computing the intervalestimates of a joint probability of a variable set, which areobtained from the possible completions of the incompletedataset. and then computes a point estimate via a convexcombination of the extreme points, with weights dependingon the assumed pattern of missing data. finally, based onthese point estimates, emi gets the estimated (conditional)mutual information. this paper also applies emi to the dependencyanalysis based learning algorithm by j. cheng soas to efficiently learn bns with incomplete data. the experimentalresults on asia and alarm networks show that emibased algorithm is much more efficient than two search&scoring based algorithms, sem and em-ea algorithms. interms of accuracy, emi based algorithm is more accuratethan sem algorithm, and comparable with em-ea algorithm.
incremental learning of bayesian networks with hidden variables. in this paper, an incremental method for learning bayesian networks based on evolutionary computing, iema, is put forward. iema introduces the evolutionary algorithm and em algorithm into the process of incremental learning, can not only avoid getting into local maxima, but also incrementally learn bayesian networks with high accuracy in presence of missing values andhidden variables. in addition, we improved the incremental learning process by friedman et al. the experimental results verified the validity of iema. in terms of storage cost, iema is comparable with the incremental learning method of friedman et al, while it is ore accurate.
model stability: a key factor in determining whether an algorithm produces an optimal model from a matching distribution. this paper investigates the factors leading to producingsuboptimal models when training and test class distributions(or misclassification costs) are matched. our resultshows that model stability plays a key role in determiningwhether the algorithm produces an optimal modelfrom a matching distribution (cost). the performance differencebetween a model trained from the matching distribution(cost) and the optimal model generally increases asthe degree of model stability decreases. the practical implicationof our result is that one should only follow theconventional wisdom of using a training class distribution(cost) that matches the test class distribution (cost) to traina classifier if the learning algorithm is known to be stable.
combining multiple weak clusterings. a data set can be clustered in many ways dependingon the clustering algorithm employed, parameter settingsused and other factors. can multiple clusterings becombined so that the final partitioning of data providesbetter clustering? the answer depends on the quality ofclusterings to be combined as well as the properties of thefusion method. first, we introduce a unifiedrepresentation for multiple clusterings and formulate thecorresponding categorical clustering problem. as aresult, we show that the consensus function is related tothe classical intra-class variance criterion using thegeneralized mutual information definition. second, weshow the efficacy of combining partitions generated byweak clustering algorithms that use data projections andrandom data splits. a simple explanatory model is offeredfor the behavior of combinations of such weak clusteringcomponents. we analyze the combination accuracy as afunction of parameters controlling the power andresolution of component partitions as well as the learningdynamics vs. the number of clusterings involved. finally,some empirical studies compare the effectiveness ofseveral consensus functions.
analysis of consensus partition in cluster ensemble. in combination of multiple partitions, one is usually interested in deriving a consensus solution with a quality better than that of given partitions. several recent studies have empirically demonstrated improved accuracy of clustering ensembles on a number of artificial and real-world data sets. unlike certain multiple supervised classifier systems, convergence properties of unsupervised clustering ensembles remain unknown for conventional combination schemes. in this paper we present formal arguments on the effectiveness of cluster ensemble from two perspectives. the first is based on a stochastic partition generation model related to re-labeling and consensus function with plurality voting. the second is to study the property of the "mean" partition of an ensemble with respect to a metric on the space of all possible partitions. in both the cases, the consensus solution can be shown to converge to a true underlying clustering solution as the number of partitions in the ensemble increases. this paper provides a rigorous justification for the use of cluster ensemble.
anomaly intrusion detection using multi-objective genetic fuzzy system and agent-based evolutionary computation framework. in this paper, we present a multi-objective genetic fuzzy system for anomaly intrusion detection. the proposed system extracts accurate and interpretable fuzzy rule-based knowledge from network data using an agent-based evolutionary computation framework. the experimental results on kdd-cup99 intrusion detection benchmark data demonstrate that our system can achieve high detection rate for intrusion attacks and low false positive rate for normal network traffic.
enhancing techniques for efficient topic hierarchy integration. in this paper, we study the problem of integrating documentsfrom different sources into a comprehensive topic hierarchy.our objective is to develop efficient techniques thatimprove the accuracy of traditional categorization methodsby incorporating categorization information providedby data sources into categorization process. notice thatin the world-wide web, categorization information is oftenavailable from information sources. we present severalenhancing techniques that use categorization informationto enhance traditional methods such as naive bayes andsupport vector machines. experiment on collections fromopenfind and yam, and google and yahoo!, well-knownpopular web sites in taiwan and usa, respectively, showsthat our techniques significantly improve the classificationaccuracy from, for example, 55% to 66% for naive bayes,and from 57% to 67% for svm for the data set collectedfrom yam and openfind.
mining associated implication networks: computational intermarket analysis. current attempts to analyze international financialmarkets include the use of financial technical analysis anddata mining techniques. in this paper, we propose a newapproach that incorporates implication networks andassociation rules to form an associated network structure.the proposed approach explicitly addresses the issue oflocal vs. global influences between financial markets.
mining frequent closed itemsets with the frequent pattern list. the mining of the complete set of frequent itemsets willlead to a huge number of itemsets. fortunately, thisproblem can be reduced to the mining of frequent closeditemsets (fcis), which results in a much smaller number ofitemsets. the approaches to mining frequent closeditemsets can be categorized into two groups: those withcandidate generation and those without. in this paper, wepropose an approach to mining frequent closed itemsetswithout candidate generation: with a data structure calledthe frequent pattern list (fpl). we designed thealgorithm fplc -mining to mine the frequent closeditemsets (fcis). experimental result shows that our methodis faster than the previously existing ones.
visualization of rule's similarity using multidimensional scaling. one of the most important problems with rule inductionmethods is that it is very difficult for domain experts to checkmillions of rules generated from large datasets. the discoveryfrom these rules requires deep interpretation from domainknowledge. although several solutions have been proposedin the studies on data mining and knowledge discovery,these studies are not focused on similarities betweenrules obtained. when one rule r1 has reasonable featuresand the other rule r2 with high similarity to r1 includes unexpectedfactors, the relations between these rules will becomea trigger to the discovery of knowledge. in this paper,we propose a visualization approach to show the similarrelations between rules based on multidimensional scaling,which assign a two-dimensional cartesian coordinateto each data point from the information about similiariesbetween this data and others data. we evaluated this methodon two medical data sets, whose experimental results showthat knowledge useful for domain experts could be found.
pattern discovery based on rule induction and taxonomy generation. one of the most important problems with rule inductionmethods is that they cannot extract rules, which plausiblyrepresent experts' decision processes. in this paper,the characteristics of experts' rules are closely examinedand a new approach to extract plausible rules is introduced,which consists of the following three procedures. first, thecharacterization of decision attributes (given classes) is extractedfrom databases and the concept hierarchy for givenclasses is calculated. second, based on the hierarchy, rulesfor each hierarchical level are induced from data. then, foreach given class, rules for all the hierarchical levels are integratedinto one rule.
a greedy algorithm for selecting models in ensembles. we are interested in ensembles of models built over k data sets. common approaches are either to combine models by vote averaging, or to build a meta-model on the outputs of the local models. in this paper, we consider the model assignment approach, in which a meta-model selects one of the local statistical models for scoring. we introduce an algorithm called greedy data labeling (gdl) that improves the initial data partition by reallocating some data, so that when each model is built on its local data subset, the resulting hierarchical system has minimal error. we present evidence that model assignment may in certain situations be more natural than traditional ensemble learning, and if enhanced by gdl, it often outperforms traditional ensembles.
tsp: mining top-k closed sequential patterns. sequential pattern mining has been studied extensivelyin data mining community.most previous studies requirethe specification of a minimum support threshold to performthe mining.however, it is difficult for users to providean appropriate threshold in practice.to overcomethis difficulty, we propose an alternative task: mining top-kfrequent closed sequential patterns of length no less thanmin_l, where k is the desired number of closed sequentialpatterns to be mined, and min_l is the minimum length ofeach pattern.we mine closed patterns since they are compactrepresentations of frequent patterns.we developed an efficient algorithm, called tsp, whichmakes use of the length constraint and the properties of top-kclosed sequential patterns to perform dynamic support-raisingand projected database-pruning.our extensive performancestudy shows that tsp outperforms the closed sequentialpattern mining algorithm even when the latter isrunning with the best tuned minimum support threshold.
privacy-preserving outlier detection. outlier detection can lead to the discovery of truly unexpected knowledge in many areas such as electronic commerce, credit card fraud and especially national security. we look at the problem of finding outliers in large distributed databases where privacy/security concerns restrict the sharing of data. both homogeneous and heterogeneous distribution of data is considered. we propose techniques to detect outliers in such scenarios while giving formal guarantees on the amount of information disclosed.
computing frequent graph patterns from semistructured data. whereas data mining in structured data focuses on frequentdata values, in semi-structured and graph data theemphasis is on frequent labels and common topologies.here, the structure of the data is just as important as its content.we study the problem of discovering typical patterns ofgraph data. the discovered patterns can be useful for manyapplications, including: compact representation of sourceinformation and a road-map for browsing and querying informationsources. difficulties arise in the discovery taskfrom the complexity of some of the required sub-tasks, suchas sub-graph isomorphism. this paper proposes a new algorithmfor mining graph data, based on a novel definitionof support. empirical evidence shows practical, as well astheoretical, advantages of our approach.
estimating the number of segments in time series data using permutation tests. segmentation is a popular technique for discoveringstructure in time series data. we address the largely openproblem of estimating the number of segments that can bereliably discovered. we introduce a novel method for theproblem, called pete. pete is based on permutation testing.the problem is an instance of model (dimension) selection.the proposed method analyzes the possible overfitof a model to the available data rather than uses a termfor penalizing model complexity. in this respect the approachis more similar to cross-validation than regulariza-tionbased techniques (e.g., aic, bic, mdl, mml). further,the method produces a p value for each increase in thenumber of segments. this gives the user an overview of thestatistical significance of the segmentations. we evaluatethe performance of the proposed method using both syntheticand real time series data. the experiments show thatpermutation testing gives realistic results about the numberof reliably identifiable segments and that it compares favorablywith the monte carlo cross-validation (mccv) andcommonly used bic criteria.
active sampling for feature selection. in knowledge discovery applications, where new featuresare to be added, an acquisition policy can help select thefeatures to be acquired based on their relevance and thecost of extraction. this can be posed as a feature selectionproblem where the feature values are not known in advance.we propose a technique to actively sample the featurevalues with the ultimate goal of choosing between alternativecandidate features with minimum sampling cost.our heuristic algorithm is based on extracting candidatefeatures in a region of the instance space where the featurevalue is likely to alter our knowledge the most. an experimentalevaluation on a standard database shows that it ispossible outperform a random subsampling policy in termsof the accuracy in feature selection.
mining web data to create online navigation recommendations. a system to provide online navigation recommendation for web visitors is introduced. we call visitor the anonymous user, i.e., when only data about her/his browsing behavior (web logs) are available. we first apply clustering techniques over a large sample of web data. next, from thesignificant patterns that are discovered, a set of rules about how to use them is created. finally, comparing the current web visitor session with the patterns, online navigation recommendations are proposed using the mentioned rules. the system was tested using data from a real web site, showing its effectiveness.
combining the web content and usage mining to understand the visitor behavior in a web site. a web site is a semi structured collection of differentkinds of data, whose motivation is show relevant informationto visitor and by this way capture her/his attention.understand the specifics preferences that define the visitorbehavior in a web site, is a complex task. an approximationis suppose that it depend the content, navigationsequence and time spent in each page visited. these variablescan be extracted from the web log files and the website itself, using web usage and content mining respectively.combining the describe variables, a similarity measureamong visitor sessions is introduced and used in a clusteringalgorithm, which identifies groups of similar sessions,allowing the analysis of visitors behavior.in order to prove the methodology's effectiveness, it wasapplied in a certain web site, showing the benefits of thedescribed approach.
web cartography for online state promotion: an algorithm for clustering web resources. this paper presents an approach of web cartography to be used in the context of online site promotion.the overall objective is to provide users with handy maps offering information about candidate sites for the creation of hyperlinks that enable a large flow of targeted visitors.two main types of data must be considered; texts and hyperlinks.we propose to exploit the latter to construct a relevant corpus on which semantic as well as graph analysis can be applied.the stress is put on theclustering of web resources based on the link network,which makes it possible to highlight groups of strongly connected sites which are of the utmost interest for our application.to tackle the site graph partitioning problem, we turn to a promising iterative approach initially developedin the context of computer-aided design.it uses spectral decomposition of the laplacian matrix to embed theconsidered graph in a geometric space where efficientmethods can be applied.an algorithm that was adaptedfrom an existing one implements the method.experimentswere conductedon a real application case concerning the promotion of a site dealing with cognac.we present the obtained map as well as leads to exploit it.
alpha galois lattices. in many applications there is a need to represent a large number of data by clustering them in a hierarchy of classes. our basic representation is a galois lattice, a structure that exhaustively represents the whole set of concepts that are distinguishable given the instance set and the representation language. what we propose here is a method to reduce the size of the lattice, and thus simplify our view of the data, while conserving its formal structure and exhaustivity. for that purpose we use a preliminary partition of the instance set, representing the association of a "type" to each instance. by redefining the notion of extent of a term in order to cope, to a certain degree (denoted as ¿), with this partition, we define a particular family of galois lattices denoted as alpha galois lattices. we also discuss the related implication rules defined as inclusion of such ¿-extents.
class decomposition via clustering: a new framework for low-variance classifiers. we propose a pre-processing step to classification thatapplies a clustering algorithm to the training set to discoverlocal patterns in the attribute or input space. wedemonstrate how this knowledge can be exploited to enhancethe predictive accuracy of simple classifiers. our focusis mainly on classifiers characterized by high bias butlow variance (e.g., linear classifiers); these classifiers experiencedifficulty in delineating class boundaries over theinput space when a class distributes in complex ways. decomposingclasses into clusters makes the new class distributioneasier to approximate and provides a viable way toreduce bias while limiting the growth in variance. experimentalresults on real-world domains show an advantagein predictive accuracy when clustering is used as a pre-processingstep to classification.
predicting rare events in temporal domains. temporal data mining aims at finding patterns in historicaldata. our work proposes an approach to extract temporalpatterns from data to predict the occurrence of targetevents, such as computer attacks on host networks, or fraudulenttransactions in financial institutions. our problemformulation exhibits two major challenges: 1) we assumeevents being characterized by categorical features and displayinguneven inter-arrival times; such an assumption fallsoutside the scope of classical time-series analysis, 2) weassume target events are highly infrequent; predictive techniquesmust deal with the class-imbalance problem. we pro-posean efficient algorithm that tackles the challenges aboveby transforming the event prediction problem into a searchfor all frequent eventsets preceding target events. the classimbalance problem is overcome by a search for patterns onthe minority class exclusively; the discrimination power ofpatterns is then validated against other classes. patternsare then combined into a rule-based model for prediction.our experimental analysis indicates the types of event sequenceswhere target events can be accurately predicted.
bootstrapping rule induction. most rule learning systems posit hard decision boundariesfor continuous attributes and point estimates of ruleaccuracy, with no measures of variance, which may seemarbitrary to a domain expert. these hard boundaries/pointschange with small perturbations to the training data. moreover,rule induction typically produces a large number ofrules that must be filtered and interpreted by an analyst.this paper describes a method of combining rules over multiplebootstrap replications of rule induction so as to reducethe total number of rules presented to an analyst and to providemeasures of variance to continuous attribute decisionboundaries and accuracy-point estimates. the method isillustrated with perioperative data.
interactive visualization and navigation in large data collections using the hyperbolic space. we propose the combination of two recently introducedmethods for the interactive visual data mining of largecollections of data. both, hyperbolic multi-dimensionalscaling (hmds) and hyperbolic self-organizing maps(hsom) employ the extraordinary advantages of the hyperbolicplane (h2): (i) the underlying space grows exponentiallywith its radius around each point - ideal for embeddinghigh-dimensional (or hierarchical) data; (ii) thepoincaré model of the ih2 exhibits a fish-eye perspectivewith a focus area and a context preserving surrounding; (iii)the mouse binding of focus-transfer allows intuitive interactivenavigation.the hmds approach extends multi-dimensional scalingand generates a spatial embedding of the data representingtheir dissimilarity structure as faithfully as possible. itis very suitable for interactive browsing of data object collections,but calls for batch precomputation for larger collectionsizes.the hsom is an extension of kohonen's self-organizingmap and generates a partitioning of the data collection assignedto an ih2 tessellating grid. while the algorithm'scomplexity is linear in the collection size, the data browsingis rigidly bound to the underlying grid.by integrating the two approaches we gain the synergetic effectof adding advantages of both. and the hybrid architectureuses consistently the ih2 visualization and navigationconcept. we present the successfully application to a textmining example involving the reuters-21578 text corpus.
alpha-surface and its application to mining protein data. given a finite set of points in three dimensional euclidean space r3, the subset that forms its surface could bedifferent when observed in different levels of details. in thispaper, we introduce a notion called a-surface. we presentan algorithm that extracts the a-surface from a finite set ofpoints in r3. we apply the algorithm to extracting the a-surfaces of proteins and discover patterns from these surface structures, using the pattern discovery algorithm wedeveloped earlier. we then use these patterns to classify theproteins. experimental results show the good performanceof the proposed approach.
delta b+ tree: indexing 3d point sets for pattern discovery. three-dimensional point sets can be used to representdata in different domains. given a database of 3d pointsets, pattern discovery looks for similar subsets that occurin multiple point sets. geometric hashing proved to be aneffective technique in discovering patterns in 3d point sets.however, there are also known shortcomings. we proposea new indexing technique called \delta b+trees. it is an extensionof b+-trees that stores point triplet information. itovercomes the shortcomings of the geometric hashing technique.we introduce four different ways of constructing thekey from a triplet. we give analytical comparison betweenthe new index structure and the geometric hashing technique.we also conduct experiments on both synthetic dataand real data to evaluate the performance.
classification through maximizing density. this paper presents a novel method for classification, which makes use of the models builtby the lattice machine (lm) [1,3 ]. the lm approximates data resulting in, as a model of data, a set of hyper tuples that are equilabelled, supported and maximal . the method presentedin this paper uses the lm model of data to classify new data with a view to maximising the density of the model. experiments show that this method, when used with the lm, outperforms the c2 algorithm in [3 ] and it is comparable to the c5.0 classification algorithm.
template-based privacy preservation in classification problems. in this paper, we present a template-based privacy preservation to protect against the threats caused by data mining abilities. the problem has dual goals: preserve the information for a wanted classification analysis and limit the usefulness of unwanted sensitive inferences that may be derived from the data. sensitive inferences are specified by a set of "privacy templates". each template specifies the sensitive information to be protected, a set of identifying attributes, and the maximum association between the two. we show that suppressing the domain values is an effective way to eliminate sensitive inferences. for a large data set, finding an optimal suppression is hard, since it requires optimization over all suppressions. we present an approximate but scalable solution. we demonstrate the effectiveness of this approach on real life data sets.
maintenance of sequential patterns for record deletion. in the past, we proposed an incremental mining algorithm for maintenance of sequential patterns based on the concept of pre-large sequences as new records were inserted. in this paper, we attempt to apply the concept of pre-large sequences to maintain sequentialpatterns as records are deleted. pre-large sequences are defined by a lower support threshold and an upper support threshold. they act as buffers to avoid the movements of sequential patterns directly from large to small and vice-versa. our proposed algorithm does notrequire rescanning original databases until the accumulative amount of deleted customer sequences exceeds a safety bound, which depends on database size. as databases grow larger, the numbers of deleted customer sequences allowed before database rescanningis required also grow. the proposed approach is thus efficient for a large database.
maintenance of sequential patterns for record modification using pre-large sequences. in the past, we proposed incremental miningalgorithms for maintenance of sequential patterns basedon the concept of pre-large sequences as records wereinserted or deleted. although maintenance of sequentialpatterns for record modification can be performed byusage of the deletion procedure and then the insertionprocedure, twice computation time of a single procedureis needed. in this paper, we thus attempt to apply theconcept of pre-large sequences to maintain sequentialpatterns as records are modified. the proposed algorithmdoes not require rescanning original databases until theaccumulative amount of modified customer sequencesexceeds a safety bound derived by pre-large concept. asdatabases grow larger, the numbers of modified customersequences allowed before database rescanning isrequired also grow.
an immune neural network used for classification. based on analyzing the immune phenomena in nature and utilizing performances of ann, a novel network model, i.e., an immune neural network (inn), is proposed which integrates the immune mechanism and the function of neural information processing. the learning algorithm of inn is mainly about the selection of an excitation function and an adaptive algorithm of the network.
summary: efficiently summarizing transactions for clustering. frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. in recent years, several studies have also extended its applicationto the transaction (or document) classification and clustering. however, most of the frequent-itemset based clustering algorithms need to first mine a large intermediate set of frequent itemsets in order to identify a subset of the most promising ones that can be used for clustering. in this paper, we study how to directly find a subset of high quality frequent itemsets that can be used as a concise summary of the transaction database and to clusterthe categorical data. by exploring some properties of the subset of itemsets that we are interested in, we proposed several search space pruning methods and designed an efficient algorithm called summary. our empirical results have shown that summary runs very fast even when the minimum support is extremely low and scales very well with respect to the database size, and surprisingly, as a pure frequent itemset mining algorithm it is very effectivein clustering the categorical data and smmarizing the dense transaction databases.
mining associations by pattern structure in large relational tables. association rule mining aims at discovering patternswhose support is beyond a given threshold. mining patternscomposed of items described by an arbitrary subset ofattributes in a large relational table represents a new challengeand has various practical applications, including theevent management systems that motivated this work. theattribute combinations that define the items in a pattern providethe structural information of the pattern. current associationalgorithms do not make full use of the structuralinformation of the patterns: the information is either lostafter it is encoded with attribute values, or is constrainedby a given hierarchy or taxonomy. pattern structures conveyimportant knowledge about the patterns. in this paper,we present a novel architecture that organizes the miningspace based on pattern structures. by exploiting the inter-relationshipsamong pattern structures, execution times formining can be reduced significantly. this advantage isdemonstrated by our experiments using both synthetic andreal-life datasets.
comparison of lazy bayesian rule and tree-augmented bayesian learning. the naive bayes classifier is widely used in interactiveapplications due to its computational efficiency, direct theoreticalbase, and competitive accuracy. however, its attributeindependence assumption can result in sub-optimalaccuracy. a number of techniques have explored simple relaxationsof the attribute independence assumption in or-derto increase accuracy. among these, the lazy bayesianrule () and the tree-augmented naive bayes ()have demonstrated strong prediction accuracy. however,their relative performance has never been evaluated. thispaper compares and contrasts these two techniques, findingthat they have comparable accuracy and hence shouldbe selected according to computational profile. lbr is desirablewhen small numbers of objects are to be classifiedwhile tan is desirable when large numbers of objects areto be classified.
approximate inverse frequent itemset mining: privacy, complexity, and approximation. in order to generate synthetic basket datasets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket datasets. the characteristics that could be used for this purpose include the frequent itemsets and association rules. the problem of generating synthetic basket datasets from frequent itemsets is generally referred to as inverse frequent itemset mining. in this paper, we show that the problem of approximate inverse frequent itemset mining is np-complete. then we propose and analyze an approximate algorithm for approximate inverse frequent itemset mining, and discuss privacy issues related to the synthetic basket dataset. in particular, we propose an approximate algorithm to determine the privacy leakage in a synthetic basket dataset.
on reducing classifier granularity in mining concept-drifting data streams. many applications use classification models on streaming data to detect actionable alerts. due to concept drifts in the underlying data, how to maintain a model's up-to-dateness has become one of the most challenging tasks in mining data streams. state of the art approaches, including both the incrementally updated classifiers and the ensemble classifiers, have proved that model update is a very costly process. in this paper, we introduce the concept of model granularity. we show that reducing model granularity will reduce model update cost. indeed, models of fine granularity enable us to efficiently pinpoint local components in the model that are affected by the concept drift. it also enables us to derive new components that can easily integrate with the model to reflect the current data distribution, thus avoiding expensive updates on a global scale. experiments on real and synthetic data show that our approach is able to maintain good prediction accuracy at a fraction of model updating cost of state of the art approaches.
ssdt: a scalable subspace-splitting classifier for biased data. decision trees are one of the most extensively used data mining models. recently, a number of efficient, scalable algorithms for constructing decision trees on large disk-resident dataset have been introduced. in this paper, we study the problem of learning scalable decision trees from datasets with biased class distribution. our objective is to build decision trees that are ore concise and oreinterpretable while maintaining the scalability of the model.to achieve this, our approach searches for subspace clusters of data cases of the biased class to enable multivariate splittings based on weighted distances to such clusters. in orderto build concise and interpretable models, other approaches including multivariate decision trees and association rules, often introduce scalability and performance issues. the ssdt algorithm we present achieves the objective without loss in efficiency, scalability, and accuracy.
bottom-up generalization: a data mining solution to privacy protection. the well-known privacy-preserved data mining modifies existing data mining techniques to randomized data. in this paper, we investigate data mining as a technique for masking data, therefore, termed data mining based privacy protection. this approach incorporates partially the requirement of a targeted data mining task into the process of masking data so that essential structure is preserved in the masked data. the idea is simple but novel: we explore the data generalization concept from data mining as a way to hide detailed information, rather than discover trends and patterns. once the data is masked, standard data mining techniques can be applied without modification. our work demonstrated another positive use of data mining technology: not only can it discover useful patterns, but also mask private information. we consider the following privacy problem: a data holder wants to release a version of datafor building classification models, but wants to protect against linking the released data to an external source for inferring sensitive information. we adapt an iterative bottom-up generalization from data mining to generalize the data. the generalized data remains useful to classification but becomes difficult to link to other sources. the generalization space is specified by a hierarchical structure of generalizations. a key is identifying the best generalization to climb up the hierarchy at each iteration. enumerating all candidate generalizations is impractical. we present a scalable solution that examines at most one generalization in each iteration for each attribute involved in the linking.
concept tree based clustering visualization with shaded similarity matrices. one of the problems with existing clustering methods isthat the interpretation of clusters may be difficult. two differentapproaches have been used to solve this problem:conceptual clustering in machine learning and clusteringvisualization in statistics and graphics. the purpose of thispaper is to investigate the benefits of combining clusteringvisualization and conceptual clustering to obtain bettercluster interpretations. in our research we have combinedconcept trees for conceptual clustering with shaded similaritymatrices for visualization. experimentation shows thatthe two interpretation approaches can complement eachother to help us understand data better.
meta-patterns: revealing hidden periodic patterns. discovery of periodic patterns in time series data has become an active research area with many applications. these patterns can be hierarchical in nature, where higher level pattern may consist of repetitions of lower level patterns.unfortunately, the presence of noise m y prevent these higher level patterns from being recognized in the sense that two portions (of data sequence) that support the same (high level) pattern may have different layouts of occurrences of basic symbols. there may not exist any common representation in terms of raw symbol combinations; and hence such (high level) pattern may not be expressed by any previous model (defined on raw symbols or symbol combinations) and would not be properly recognized by any existing method. in this paper, we propose novel model, namely meta-pattern, to capture these high level patterns. as more flexible model, the number of potential meta-patterns could be very large. a substantial difficulty lies on how to identify the proper pattern candidates. however, the well-known apriori property is not able to provide sufficient pruning power. a new property, namely component location property, is identified and used to conduct the candidate generation so that an efficient computation-based mining algorithm can be developed. last but not least, we apply our algorithm to some real and synthetic sequences and some interesting patterns are discovered.
a bernoulli relational model for nonlinear embedding. the notion of relations is extremely important in mathematics. in this paper, we use relations to describe the embedding problem and propose a novel stochastic relational model for nonlinear embedding. given some relation among points in a high-dimensional space, we start from preserving the same relation in a low embedded space and model the relation as probabilistic distributions over these two spaces, respectively. we illustrate that the stochastic neighbor embedding and the gaussian process latent variable model can be derived from our relational model. moreover we devise a new stochastic embedding model and refer to it as bernoulli relational embedding (bre). bre's ability in nonlinear dimensionality reduction is illustrated on a set of synthetic data and collections of bitmaps of handwritten digits and face images.
mining quantitative frequent itemsets using adaptive density-based subspace clustering. a novel approach to subspace clustering is proposed to exhaustively and efficiently mine quantitative frequent itemsets (qfis) from massive transaction data¹. for the computational tractability, our approach introduces adaptive density-based and apriori-like algorithm. its outstanding performance is shown through numerical experiments.
atomic wedgie: efficient query filtering for streaming times series. in many applications it is desirable to monitor a streaming time series for predefined patterns. in domains as diverse as the monitoring of space telemetry, patient intensive care data, and insect populations, where data streams at a high rate and the number of predefined patterns is large, it may be impossible for the comparison algorithm to keep up. we propose a novel technique that exploits the commonality among the predefined patterns to allow monitoring at higher bandwidths, while maintaining a guarantee of no false dismissals. our approach is based on the widely used envelope-based lower bounding technique. extensive experiments demonstrate that our approach achieves tremendous improvements in performance in the offline case, and significant improvements in the fastest possible arrival rate of the data stream that can be processed with guaranteed no false dismissal.
using boosting to simplify classification models. ensemble classification techniques such as bagging ,boosting and arcingalgorithms have been shown to lead to reduced classification error on unseencases and seem immune t the problem of overfitting. several explanations forthe reduction in generalisation error have been presented, with authors morerecently defining and applying diagnostics such as edge and margin [4,9,10 ].these measures pr vide insight into the behaviour of ensemble classifiers but can they be exploited further?
an incremental approach to building a cluster hierarchy. in this paper we present a novel incremental hierarchicalclustering (ihc) algorithm. our approach aims to constructa hierarchy that satisfies the homogeneity and themonotonicity properties. working in a bottom-up fashion,a new instance is placed in the hierarchy and a sequence ofhierarchy restructuring process is performed only in regionsthat have been affected by the presence of the new instance.the experimental results on a variety of domains demonstratethat our algorithm is not sensitive to input ordering,can produce a quality cluster hierarchy, and is efficient interms of its computational time.
a comparative study of rnn for outlier detection in data mining. we have proposed replicator neural networks (rnns)for outlier detection [8]. here we compare rnn for outlierdetection with three other methods using both publiclyavailable statistical datasets (generally small) and datamining datasets (generally much larger and generally realdata). the smaller datasets provide insights into the relativestrengths and weaknesses of rnns. the larger datasetsparticularly test scalability and practicality of application.
center-based indexing for nearest neighbors search. the paper addresses the problem of indexing data forthe k nearest neighbors (k-nn) search. it presents a tree-basedtop-down indexing method that uses an iterative k-meansalgorithm for tree node splitting and combines threedifferent search pruning criteria from bst, ght and gnatinto one. the experiments show that the presented indexingtree accelerates the k-nn searching up to several thousandstimes in case of large data sets.
association rule mining in peer-to-peer systems. we extend the problem of association rule mining -a key data mining problem - to systems in which thedatabase is partitioned among a very large number ofcomputers that are dispersed over a wide area. such computing systems include grid computing platforms, federated database systems, and peer-to-peer computing environments. the scale of these systems poses several difficulties, such as the impracticality of global communications and global synchronization, dynamic topology changes ofthe network, on-the-fly data updates, the need to share resources with other applications, and the frequent failureand recovery of resources.we present an algorithm by which every node in thesystem can reach the exact solution, as if it were giventhe combined database. the algorithm is entirely asynchronous, imposes very little communication overhead,transparently tolerates network topology changes andnode failures, and quickly adjusts to changes in the dataas they occur. simulation of up to 10,000 nodes show thatthe algorithm is local: all rules, except for those whoseconfidence is about equal to the confidence threshold, arediscovered using information gathered from a very smallvicinity, whose size is independent of the size of the system.
mpis: maximal-profit item selection with cross-selling considerations. in the literature of data mining, many different algorithmsfor association rule mining have been proposed. however,there is relatively little study on how association rules can aidin more specific targets. in this paper, one of the applicationsfor association rules - maximal-profit item selection with cross-selling effect (mpis) problem - is investigated. the problemis about selecting a subset of items which can give the maximalprofit with the consideration of cross-selling. we provethat a simple version of this problem is np-hard. we proposea new approach to the problem with the consideration of theloss rule - a kind of association rule to model the cross-sellingeffect. we show that the problem can be transformed to aquadratic programming problem. in case quadratic programmingis not applicable, we also propose a heuristic approach.experiments are conducted to show that both of the proposedmethods are highly effective and efficient.
adapting information extraction knowledge for unseen web sites. we propose a wrapper adaptation framework which aimsat adapting a learned wrapper to an unseen web site. it significantlyreduces human effort in constructing wrappers.our framework makes use of extraction rules previously discoveredfrom a particular site to seek potential training ex-amplecandidates for an unseen site. rule generalizationand text categorization are employed for finding suitable examplecandidates. another feature of our approach is thatit makes use of the previously discovered lexicon to classifygood training examples automatically for the new site. weconducted extensive experiments to evaluate the quality ofthe extraction performance and the adaptability of our approach.
a probabilistic approach for adapting information extraction wrappers and discovering new attributes. we develop a probabilistic framework for adapting information extraction wrappers with new attribute discovery. wrapper adaptation aims at automatically adapting a previously learned wrapper from the source web site to a new unseen site for information extraction. one unique characteristic of our framework is that it can discover new or previously unseen attributes as well as headers from the new site. it is based on a generative model for the generation of text fragments related to attribute items and formatting data in a web page. to solve the wrapper adaptation problem, we consider two kinds of information from the source web site. the first kind of information is the extraction knowledge contained in the previously learned wrapper from the source web site. the second kind of information is the previously extracted or collected items. we employ a bayesian learning approach to automatically select a set of training examples for adapting a wrapper for the new unseen site. to solve the new attribute discovery problem, we develop a model which analyzes the surrounding text fragments of the attributes in the new unseen site. a bayesian learning method is developed to discover the new attributes and their headers. em technique is employed in both bayesian learning models. we conducted extensive experiments from a number of real-world web sites to demonstrate the effectiveness of our framework.
hot item mining and summarization from multiple auction web sites. online auction web sites are fast changing, highly dynamic, and complex as they involve tremendous sellers and potential buyers, as well as a huge amount of items listed for bidding. we develop a two-phase framework which aims at mining and summarizing hot items from multiple auctionweb sites to assist decision making. the objective of the first phase is to automatically extract the product features and product feature values of the items from the descriptions provided by the sellers. we design a hmm-based learning method to train an extended hmm model which can adapt to the unseen web page from which the information is extracted. the goal of the second phase is to discover and summarize the hot items based on the extracted information. we formulate the hot item mining task as a semi-supervised learning problem and employ the graph mincuts algorithm to accomplish this task. the summary of the hot items is then generated by considering the frequency and the position of the product features being mentioned in the descriptions. we have conducted extensive experiments from several real-world auction web sites to demonstrate the effectiveness of our framework.
a hybrid approach to discover bayesian networks from databases using evolutionary programming. this paper describes a novel data mining approach thatemploys evolutionary programming to discover knowledgerepresented in bayesian networks. there are two differentapproaches to the network learning problem. the first oneuses dependency analysis, while the second one searchesgood network structures according to a metric. unfortu-nately,both approaches have their own drawbacks. thus,we propose a novel hybrid algorithm of the two approaches,which consists of two phases, namely, the conditional inde-pendence(ci) test and the search phases. a new opera-toris introduced to further enhance the search efficiency.we conduct a number of experiments and compare the hy-bridalgorithm with our previous algorithm, mdlep [18],which uses ep for network learning. the empirical resultsillustrate that the new approach has better performance.we apply the approach to a data sets of direct marketingand compare the performance of the evolved bayesian net-worksobtained by the new algorithm with the models gen-eratedby other methods. in the comparison, the inducedbayesian networks produced by the new algorithm outper-formthe other models.
merging interface schemas on the deep web via clustering aggregation. we consider the problem of integrating a large number of interface schemas over the deep web, the scale of the problem and the diversity of the sources present serious challenges to the conventional manual or rule-based approaches to schema integration. to address these challenges, we propose a novel formulation of schema integration as an optimization problem, with the objective of maximally satisfying the constraints given by individual schemas. since the optimization problem can be shown to be np-complete, we develop a novel approximation algorithm lmax, which builds the unified schema via recursive applications of clustering aggregation. we further extend lmax to handle the irregularities frequently occurring among the interface schemas. extensive evaluation on real-world data sets shows the effectiveness of our approach.
using category-based adherence to cluster market-basket data. in this paper, we devise an efficient algorithm for clusteringmarket-basket data. different from those of the traditionaldata, the features of market-basket data are knownto be of high dimensionality, sparsity, and with massive out-liers.without explicitly considering the presence of the tax-onomy,most prior efforts on clustering market-basket datacan be viewed as dealing with items in the leaf level of thetaxonomy tree. clustering transactions across different levelsof the taxonomy is of great importance for marketingstrategies as well as for the result representation of the clusteringtechniques for market-basket data. in view of thefeatures of market-basket data, we devise in this paper anovel measurement, called the category-based adherence,and utilize this measurement to perform the clustering. thedistance of an item to a given cluster is defined as the numberof links between this item and its nearest large node inthe taxonomy tree where a large node is an item (i.e., leaf)or a category (i.e., internal) node whose occurrence countexceeds a given threshold. the category-based adherenceof a transaction to a cluster is then defined as the averagedistance of the items in this transaction to that cluster.with this category-based adherence measurement, wedevelop an efficient clustering algorithm, called algorithmcba (standing for category-based adherence), for market-basketdata with the objective to minimize the category-basedadherence. a validation model based on informationgain (ig) is also devised to assess the quality of clusteringfor market-basket data. as validated by both real and syntheticdatasets, it is shown by our experimental results, withthe taxonomy information, algorithm cba devised in thispaper significantly outperforms the prior works in both theexecution efficiency and the clustering quality for market-basketdata.
mining strong affinity association patterns in data sets with skewed support distribution. existing association-rule mining algorithms often relyon the support-based pruning strategy to prune its combinatorialsearch space. this strategy is not quite effectivefor data sets with skewed support distributions because theytend to generate many spurious patterns involving itemsfrom different support levels or miss potentially interestinglow-support patterns. to overcome these problems, we proposethe concept of hyperclique pattern, which uses an objectivemeasure called h-confidence to identify strong affinitypatterns. we also introduce the novel concept of cross-supportproperty for eliminating patterns involving itemswith substantially different support levels. our experimentalresults demonstrate the effectiveness of this method forfinding patterns in dense data sets even at very low supportthresholds, where most of the existing algorithms wouldbreak down. finally, hyperclique patterns also show greatpromise for clustering items in high dimensional space.
clustering item data sets with association-taxonomy similarity. we explore in this paper the efficient clustering of itemdata. different from those of the traditional data, the featuresof item data are known to be of high dimensionalityand sparsity. in view of the features of item data, we devisein this paper a novel measurement, called the association-taxonomysimilarity, and utilize this measurement to performthe clustering. with this association-taxonomy similaritymeasurement, we develop an efficient clustering algorithm,called algorithm at (standing for association-taxonomy),for item data. two validation indexes basedon association and taxonomy properties are also devised toassess the quality of clustering for item data. as validatedby the real dataset, it is shown by our experimental resultsthat algorithm at devised in this paper significantly outperformsthe prior works in the clustering quality as measuredby the validation indexes, indicating the usefulness ofassociation-taxonomy similarity in item data clustering.
mixtures of arma models for model-based time series clustering. clustering problems are central to many knowledge discoveryand data mining tasks. however, most existing clusteringmethods can only work with fixed-dimensional representationsof data patterns. in this paper, we study the clusteringof data patterns that are represented as sequencesor time series possibly of different lengths. we propose amodel-based approach to this problem using mixtures of autoregressivemoving average (arma) models. we derive anexpectation-maximization (em) algorithm for learning themixing coefficients as well as the parameters of the componentmodels. experiments were conducted on simulatedand real datasets. results show that our method comparesfavorably with another method recently proposed by othersfor similar time series clustering problems.
cost-sensitive learning by cost-proportionate example weighting. we propose and evaluate a family of methods for convertingclassifier learning algorithms and classification theoryinto cost-sensitive algorithms and theory. the proposedconversion is based on cost-proportionate weighting of thetraining examples, which can be realized either by feedingthe weights to the classification algorithm (as often done inboosting), or by careful subsampling. we give some theoreticalperformance guarantees on the proposed methods,as well as empirical evidence that they are practical alternativesto existing approaches. in particular, we proposecosting, a method based on cost-proportionate rejectionsampling and ensemble aggregation, which achievesexcellent predictive performance on two publicly availabledatasets, while drastically reducing the computation requiredby other methods.
from path tree to frequent patterns: a framework for mining frequent patterns. in this paper, we propose a new framework for miningfrequent patterns from large transactional databases. thecore of the framework is of a novel coded prefix-path treewith two representations, namely, a memory-based prefix-pathtree and a disk-based prefix-path tree. the disk-basedprefix-path tree is simple in its data structure yet rich ininformation contained, and is small in size. the memory-basedprefix-path tree is simple and compact. upon thememory-based prefix-path tree, a new depth-first frequentpattern discovery algorithm, called p p-mine, is proposedin this paper that outperforms fp-growth significantly. thememory-based prefix-path tree can be stored on disk usinga disk-based prefix-path tree with assistance of the new codingscheme. we present efficient loading algorithms to loadthe minimal required disk-based prefix-path tree into mainmemory. our technique is to push constraints into the loadingprocess, which has not been well studied yet.
fast parallel association rule mining without candidacy generation. in this paper we introduce a new parallel algorithm mlfpt (multiple local frequent pattern tree) [11] for parallel mining of frequent patterns, based on fp-growth mining, that uses only two full i/o scans of the database, eliminating the need for generating the candidate items and distributing the work fairly among processors. we have devised partitioning strategies at different stages of the mining process to achieve near optimal balancing between processors.we have successfully tested our algorithm on datasets larger than 50 million transactions.
irc: an iterative reinforcement categorization algorithm for interrelated web objects. most existing categorization algorithms deal with homogeneous web data objects, and consider interrelated objects as additional features when taking the interrelationships withother types of objects into account. however, focusing on any single aspects of these interrelationships and objects will not fully reveal their true categories. in this paper, wepropose a novel categorization algorithm, the iterative reinforcement categorization algorithm (irc), to exploit the full interrelationships between the heterogeneous objects on the web.irc attempts to classify the interrelated web objects by iterative reinforcement between individual classification results of different types via the interrelationships. experiments on a clickthrough log dataset from msn search engine show that, with the f1 measures, irc achieves a 26.4% improvement over a pure content-based classification method, a 21% improvement over a query metadata-based method, and a 16.4% improvement over a virtual document-based method. furthermore, our experiments show that irc converges rapidly.
clustering spatial data when facing physical constraints. clustering spatial data is a well-known problem that hasbeen extensively studied to find hidden patterns or meaningfulsub-groups and has many applications such as satelliteimagery, geographic information systems, medical imageanalysis, etc. although many methods have been proposedin the literature, very few have considered constraintssuch that physical obstacles and bridges linking clustersmay have significant consequences on the effectiveness ofthe clustering. taking into account these constraints duringthe clustering process is costly, and the effective modeling ofthe constraints is of paramount importance for good performance.in this paper, we define the clustering problem in thepresence of constraints - obstacles and crossings - and investigateits efficiency and effectiveness for large databases.in addition, we introduce a new approach to model theseconstraints to prune the search space and reduce the numberof polygons to test during clustering. the algorithmdbcluc we present detects clusters of arbitrary shape andis insensitive to noise and the input order. its average runningcomplexity is o(nlogn) where n is the number of dataobjects.
discriminatively trained markov model for sequence classification. in this paper, we propose a discriminative counterpart of the directed markov models of order k - 1, or mm(k-1) for sequence classification. mm(k-1) models capture dependencies among neighboring elements of a sequence. the parameters of the classifiers are initialized to based on the maximum likelihood estimates for their generative counterparts. we derive gradient based update equations for the parameters of the sequence classifiers in order to maximize the conditional likelihood function. results of our experiments with data sets drawn from biological sequence classification (specifically protein function and subcellular localization) and text classification applications show that the discriminatively trained sequence classifiers outperform their generative counterparts, confirming the benefits of discriminative training when the primary objective is classification.our experiments also show that the discriminatively trained mm(k - 1) sequence classifiers are competitive with the computationally much more expensive support vector machines trained using k-gram representations of sequences.
cbc: clustering based text classification requiring minimal labeled data. semi-supervised learning methods construct classifiersusing both labeled and unlabeled training data samples.while unlabeled data samples can help to improve theaccuracy of trained models to certain extent, existingmethods still face difficulties when labeled data is notsufficient and biased against the underlying datadistribution. in this paper, we present a clustering basedclassification (cbc) approach. using this approach,training data, including both the labeled and unlabeleddata, is first clustered with the guidance of the labeleddata. some of unlabeled data samples are then labeledbased on the clusters obtained. discriminative classifierscan subsequently be trained with the expanded labeleddataset. the effectiveness of the proposed method isjustified analytically. our experimental resultsdemonstrated that cbc outperforms existing algorithmswhen the size of labeled dataset is very small.
gspan: graph-based substructure pattern mining. we investigate new approaches for frequent graph-basedpattern mining in graph datasets and propose a novel algorithmcalled gspan (graph-based substructure pattern mining),which discovers frequent substructures without candidategeneration. gspan builds a new lexicographic orderamong graphs, and maps each graph to a unique minimumdfs code as its canonical label. based on this lexico-graphicorder, gspan adopts the depth-first search strategyto mine frequent connected subgraphs efficiently. our performancestudy shows that gspan substantially outperformsprevious algorithms, sometimes by an order of magnitude.
a comparison of stacking with meta decision trees to bagging, boosting, and stacking with other methods. abstract. meta decision trees (mts) are a method for combining multiple classifiers. we present an integration of the algorithm mlc4.5 for learning mts into the weka data mining suite. we compare classifier ensembles combined with mdts to bagged and boosted decision trees, and to classifier ensembles combined with other methods: voting and stacking with three different meta-level classifiers (ordinary decision trees, naive bayes, and multi-response linear regression -mlr).
mining case bases for action recommendation. corporations and institutions are often interested inderiving marketing strategies from corporate data andproviding informed advice for their customers oremployees. for example, a financial institution mayderive marketing strategies for turning their reluctantcustomers into active ones and a telecommunicationscompany may plan actions to stop their valuablecustomers from leaving. in data mining terms, theseadvice and action plans are aimed at convertingindividuals from an undesirable class to a desirable one,or to help devising a direct-marketing plan in order toincrease the profit for the institution. in this paper, wepresent an approach to use role models' for generatingsuch advice and plans. these role models are typicalcases that form a case base and can be used forcustomer advice generation. for each new customerseeking advice, a nearest-neighbor algorithm is used tofind a cost-effective and highly probable plan forswitching a customer to the most desirable role models.in this paper, we explore the tradeoff among time, spaceand quality of computation in this case-based reasoningframework. we demonstrate the effectiveness of themethods through empirical results.
mining surveillance video for independent motion detection. this paper addresses the special applications of datamining techniques in homeland defense. the problemtargeted, which is frequently encountered in military/intelligence surveillance, is to mine a massive surveillancevideo database automatically collected to retrieve theshots containing independently moving targets. a novelsolution to this problem is presented in this paper, whichoffers a completely qualitative approach to solving for theautomatic independent motion detection problem directlyfrom the compressed surveillance video in a faster thanrealtime mining performance. this approach is based onthe linear system consistency analysis, and consequentlyis called qls. sincetheqls approach only focuses onwhat exactly is necessary to compute a solution, it savesthe computation to a minimum and achieves the efficacy tothe maximum. evaluations from real data show that qlsdelivers effective mining performance at the achieved efficiency.
mining plans for customer-class transformation. we consider the problem of mining high-utility plansfrom historical plan databases that can be used to transformcustomers from one class to other, more desirable classes.traditional data mining algorithms are focused on findingfrequent sequences. but high frequency may not imply lowcosts and high benefits. traditional markov decision process(mdp) algorithms are designed to address this issueby bringing in the concept of utility, but these algorithmsare also known to be expensive to execute. in this paper,we present a novel algorithm auplan which automaticallygenerates sequential plans with high utility by combiningdata mining and ai planning. these high-utility plans couldbe used to convert groups of customers from less desirablestates to more desirable ones. our algorithm adapts theapriori algorithm by considering the concepts of plans andutilities. we show through empirical studies that planningusing our integrated algorithm produces high-utility plansefficiently.
regression clustering. complex distribution in real-world data is oftenmodeled by a mixture of simpler distributions. clusteringis one of the tools to reveal the structure of this mixture.the same is true to the datasets with chosen responsevariables that people run regression on. withoutseparating the clusters with very different responseproperties, the residue error of the regression is large.input variable selection could also be misguided to ahigher complexity by the mixture. in regressionclustering (rc), k (>1) regression functions are appliedto the dataset simultaneously which guide the clusteringof the dataset into k subsets each with a simplerdistribution matching its guiding function. each functionis regressed on its own subset of data with a muchsmaller residue error. both the regressions and theclustering optimize a common objective function. wepresent a rc algorithm based on k-harmonic meansclustering algorithm and compare it with other existingrc algorithms based on k-means and em.
on precision and recall of multi-attribute data extraction from semistructured sources. machine learning techniques for data extraction fromsemistructured sources exhibit different precision and recallcharacteristics. however to date the formal relationship betweenlearning algorithms and their impact on these twometrics remains unexplored. this paper proposes a formalizationof precision and recall of extraction and investigatesthe complexity-theoretic aspects of learning algorithms formulti-attribute data extraction based on this formalism. weshow that there is a tradeoff between precision/recall of extractionand computational efficiency and present experimentalresults to demonstrate the practical utility of theseconcepts in designing scalable data extraction algorithmsfor improving recall without compromising on precision.
a polygonal line algorithm based nonlinear feature extraction method. we propose a polygonal line based principal curve algorithm for nonlinear feature extraction, in which the nonlinearities among the multivariable data can be described by a set of local linear models. the proposed algorithm integrates the linear pca approach with the polygonal line algorithm to represent complicated nonlinear data structure. statistical redundancy elimination for high dimensional data is also discussed for describing the underlying principal curves without much loss of information among the original data sets. the polygonal line algorithm can produce robust and accurate nonlinear curve estimation for different multivariate data types, and it is helpful in reducing the computation complexity for existing principal curve approaches when the sample size is large.
segmenting customer transactions using a pattern-based clustering approach. grouping customer transactions into categories helpsunderstand customers better. the marketing literaturehas concentrated on identifying important segmentationvariables (e.g. customer loyalty) and on using clusteringand mixture models for segmentation. the data miningliterature has provided various clustering algorithms forsegmentation. in this paper we investigate using"pattern-based" clustering approaches to groupingcustomer transactions. we argue that there are clustersin transaction data based on natural behavioral patterns,and present a new technique, yaca, that groupstransactions such that itemsets generated from eachcluster, while similar to each other, are different fromones generated from others. we present experimentalresults from user-centric web usage data thatdemonstrates that yaca generates a highly effectiveclustering of transactions.
learning rules from highly unbalanced data sets. this paper presents a simple and effective rule learning algorithm for highly unbalanced data sets. by using the small size of the minority class to its advantage this algorithm can conduct an almost exhaustive search for patterns within the known fraudulent cases. this algorithm was designed for and successfully applied to a law enforcement problem, which involves discovering common patterns of fraudulent transactions.
on the stationarity of multivariate time series for correlation-based data analysis. multivariate time series (mts) data sets are common in various multimedia, medical and financial application domains. these applications perform several data-analysis operations on large number of mts data sets such as similarity searches, feature-subset-selection, clustering and classifications. correlation-based techniques, such as principal component analysis (pca), have proven to improve the efficiency of many of the above-mentioned data-analysis operations on mts, which implies that the correlation coefficientsconcisely represent the original mts data. however, if the statistical properties (e.g., variance) of mts data change over time dimension, i.e., mts data is non-stationary, the correlation coefficients are not stable. in this paper, we propose to utilize the stationarity of the mts data sets, in order to represent the original mts data more stably, as well as concisely with the correlation coefficients. that is, before performing any correlation-based data analysis, we first executes the stationarity test to decide whether the mts data is stationary or not, i.e., whether the correlation is stable or not. subsequently, for a non-stationary mts data set, we difference it to render the data set stationary. even though our approach is general, to focus the discussion we describe our approach within the context of our previously proposed technique for mts similarity search. in order to show the validity of our approach, we performed several experiments on four real-world data sets. the results show that the performance of our similarity search technique have significantly improved in terms of precision/recall.
visualizing global manifold based on distributed local data abstractions. mining distributed data for global knowledge is getting more attention recently. the problem is especially challenging when data sharing is prohibited due to local constraints like limited bandwidth and data privacy. in this paper, we investigate how to derive the embedded manifold (as a 2-d map)for a horizontally partitioned data set, where data cannot be shared among the partitions directly. we propose a model-based approach which computes hierarchical local data abstractions, aggregates the abstractions, and finally learns a global generative model — generative topographic mapping (gtm) based on the aggregated data abstraction. we applied the proposed method to two benchmarking data sets and demonstrated that the accuracy of the derived manifold can effectively be controlled by adjusting the data granularity level of the adopted local abstraction.
agile: a general approach to detect transitions in evolving data streams. in many applications such as e-commerce, system diagnosis and telecommunication services, data arrives in streams at a high speed. it is common that the underlying process generating the stream may change over time, either as a result of the fundamental evolution or in response to some external stimulus. detecting these changes is a very challenging problem of great practical importance. the overall volume of the stream usually far exceeds the available main memory and access to the data stream is typically performed via a linear scan in ascending order of the indices of the records. in this paper, we propose a novel approach, agile, to monitor streaming data and to detect distinguishable transitions of the underlying processes. agile has many advantages over the traditional hidden markov model, e.g., agile only requires one scan of the data.
infominer+: mining partial periodic patterns with gap penalties. in this paper, we focus on mining periodic patterns allowing some degreeof imperfection in the form of random replacement from a perfectperiodic pattern. information gain was proposed to identify patternswith events of vastly different occurrence frequencies and adjust forthe deviation from a pattern. however, it does not take any penaltyif there exists some gap between the pattern occurrences. in manyapplications, e.g., bio-informatics, it is important to identify subsequencesthat a pattern repeats perfectly (or near perfectly). as a solution,we extend the information gain measure to include a penaltyfor gaps between pattern occurrences. we call this measure as generalizedinformation gain. furthermore, we want to find subsequences' such that for a pattern p , the generalized information gain of pin s' is high. this is particularly useful in locating repeats in dnasequences. in this paper, we developed an effective mining algorithm,infominer+, to simultaneously mine significant patterns and the as-sociatedsubsequences.
mining california vital statistics data. vital statistics data offer a fertile ground for data mining. in this paper, we discuss the results of a data-mining project on the causes of death aspect of the vital statistics data in the state of california. a data-mining tool called cubist is used to build predictive models out of two million cases over a nine-year period. the objective of our study is to discover knowledge (trends, correlations or patterns) that may not be gleaned through standard techniques. the generated predictive models allow pertinent state agencies to gain insight into various aspects of the death rates in the state of california, to predict health issues related to the causes of death, to offer an aid to decision or policy-making process and to provide useful information services to the customers. the results obtained in our study contain valuable new information.
postprocessing decision trees to extract actionable knowledge. most data mining algorithms and tools stop at discoveredcustomer models, producing distribution informationon customer profiles. such techniques, when applied to industrialproblems such as customer relationship management(crm), are useful in pointing out customers who arelikely attritors and customers who are loyal, but they requirehuman experts to postprocess the mined information manually.most of the postprocessing techniques have been limitedto producing visualization results and interestingnessranking, but they do not directly suggest actions that wouldlead to an increase the objective function such as profit. inthis paper, we present a novel algorithm that suggest actionsto change customers from an undesired status (suchas attritors) to a desired one (such as loyal) while maximizingobjective function: the expected net profit. we developthese algorithms under resource constraints that areabound in reality. the contribution of the work is in takingthe output from an existing mature technique (decisiontrees, for example), and producing novel, actionable knowledgethrough automatic postprocessing.
a comparison study on algorithms for incremental update of frequent sequences. the problem of mining frequent sequences is to extractfrequently occurring subsequences in a sequence database.algorithms on this mining problem include gsp, mfs, andspade. the problem of incremental update of frequent sequencesis to keep track of the set of frequent sequences asthe underlying database changes. previous studies have extendedthe traditional algorithms to efficiently solve the up-dateproblem. these incremental algorithms include ism,gsp+and mfs+. each incremental algorithm has its owncharacteristics and they have been studied and evaluatedseparately under different scenarios. this paper presentsa comprehensive study on the relative performance of theincremental algorithms as well as their non-incrementalcounterparts. our goal is to provide guidelines on thechoice of an algorithm for solving the incremental updateproblem given the various characteristics of a sequencedatabase.
fd_mine: discovering functional dependencies in a database using equivalences. the discovery of fds from databases has recentlybecome a significant research problem. in this paper, wepropose a new algorithm, called fd_mine. fd_minetakes advantage of the rich theory of fds to reduce boththe size of the dataset and the number of fds to bechecked by using discovered equivalences. we show thatthe pruning does not lead to loss of information.experiments on 15 uci datasets show that fd_mine canprune more candidates than previous methods.
dimensionality reduction using kernel pooled local discriminant information. we study the use of kernel subspace methods for learninglow-dimensional representations for classification. we proposea kernel pooled local discriminant subspace methodand compare it against several competing techniques: generalizedfisher discriminant analysis (gda) and kernelprincipal components analysis (kpca) in classificationproblems. we evaluate the classification performance ofthe nearest-neighbor rule with each subspace representation.the experimental results demonstrate the efficacy ofthe kernel pooled local subspace method and the potentialfor substantial improvements over competing methods suchas kpca in some classification problems.
speculative markov blanket discovery for optimal feature selection. in this paper we address the problem of learning the markov blanket of a quantity from data in an efficient manner. markov blanket discovery can be used in the feature selection problem to find an optimal set of features for classificationtasks, and is a frequently-used preprocessing phase in data mining, especially for high-dimensional domains. our contribution is a novel algorithm for the induction of markov blankets from data, called fast-iamb, that employs a heuristic to quickly recover the markov blanket. empirical results show that fast-iamb performs in many cases faster and more reliably than existing algorithms without adversely affecting the accuracy of the recovered markov blankets.
discriminant analysis: a unified approach. linear discriminant analysis (lda) as a dimension reduction method is widely used in data mining and machine learning. it however suffers from the small sample size (sss) problem when data dimensionality is greater than the sample size. many modified methods have been proposed to address some aspect of this difficulty from a particular viewpoint. a comprehensive framework that provides a complete solution to the sss problem is still missing. in this paper, we provide a unified approach to lda, and investigate the sss problem in the framework of statistical learning theory. in such a unified approach, our analysis results in a deeper understanding of lda. we demonstrate that lda (and its nonlinear extension) belongs to the same framework where powerful classifiers such as support vector machines (svms) are formulated. in addition, this approach allows us to establish an error bound for lda. finally our experiments validate our theoretical analysis results.
a new optimization criterion for generalized discriminant analysis on undersampled problems. a new optimization criterion for discriminant analysis ispresented. the new criterion extends the optimization criteriaof the classical linear discriminant analysis (lda) byintroducing the pseudo-inverse when the scatter matricesare singular. it is applicable regardless of the relative sizesof the data dimension and sample size, overcoming a limitationof the classical lda. recently, a new algorithm calledlda/gsvd for structure-preserving dimension reductionhas been introduced, which extends the classical lda tovery high-dimensional undersampled problems by using thegeneralized singular value decomposition (gsvd). the solutionfrom the lda/gsvd algorithm is a special case of thesolution for our generalized criterion in this paper, which isalso based on gsvd.we also present an approximate solution for our gsvd-basedsolution, which reduces computational complexity byfinding sub-clusters of each cluster, and using their centroidsto capture the structure of each cluster. this reducedproblem yields much smaller matrices of which the gsvdcan be applied efficiently. experiments on text data, withup to 7000 dimensions, show that the approximation algorithmproduces results that are close to those produced bythe exact algorithm.
learning weighted naive bayes with accurate ranking. naive bayes is one of most effective classification algorithms. in many applications, however, a ranking of examples are more desirable than just classification. how to extend naive bayes to improve its ranking performance is an interesting and useful question in practice. weighted naive bayes is an extension of naive bayes, in which attributes have different weights. this paper investigates how to learn a weighted naive bayes with accurate ranking from data, or more precisely, how to learn the weights of a weighted naive bayes to produce accurate ranking. we explore various methods: the gain ratio method, the hill climbing method, and the markov chain monte carlo method, the hill climbing method combined with the gain ratio method, and the markov chain monte carlo method combined with the gain ratio method. our experiments show that a weighted naive bayes trained to produce accurate ranking outperforms naive bayes.
an efficient data mining technique for discovering interesting sequential patterns. mining sequential patterns is to discover sequentialpurchasing behaviors of most customers from a largeamount of customer transactions. in this paper, a datamining language is presented. from the data mininglanguage, use s can specify the interested items and thecriteria of the sequential patterns to be discovered. also,an efficient data mining technique is proposed to ext actthe sequential patterns according to the uses` requests.
bagging with adaptive costs. ensemble methods have proved to be highly effective in improving the performance of base learners under most circumstances. in this paper, we propose a new algorithm that combines the merits of some existing techniques, namely bagging, arcing and stacking. the basic structure of the algorithm resembles bagging. however, the misclassification cost of each training point is repeatedly adjusted according to its observed out-of-bag vote margin. in this way, the method gains the advantage of arcing - building the classifier the ensemble needs - without fixating on potentially noisy points. computational experiments show that this algorithm performs consistently better than bagging and arcing with linear and nonlinear base classifiers. in view of the characteristics of bacing, a hybrid ensemble learning strategy, which combines bagging and different versions of bacing, is proposed and studied empirically.
sentiment analyzer: extracting sentiments about a given topic using natural language processing techniques. we present sentiment analyzer (sa) that extracts sentiment(or opinion) about a subject from online text documents.instead of classifying the sentiment of an entire documentabout a subject, sa detects all references to the givensubject, and determines sentiment in each of the referencesusing natural language processing (nlp) techniques. oursentiment analysis consists of 1) a topic specific featureterm extraction, 2) sentiment extraction, and 3) (subject,sentiment) association by relationship analysis. sa utilizestwo linguistic resources for the analysis: the sentiment lexiconand the sentiment pattern database. the performanceof the algorithms was verified on online product review articles("digital camera" and "music" reviews), and moregeneral documents including general webpages and newsarticles.
sharing classifiers among ensembles from related problem domains. a classification ensemble is a group of classifiers that all solve the same prediction problem in different ways. it is well-known that combining the predictions of classifiers within the same problem domain using techniques like bagging or boosting often improves the performance. this research shows that sharing classifiers among different but closely related problem domains can also be helpful. in addition, a semi-definite programming based ensemble pruning method is implemented in order to optimize the selection of a subset of classifiers for each problem domain. computational results on a catalog dataset indicate that the ensembles resulting from sharing classifiers among different product categories generally have larger aucs than those ensembles trained only on their own categories. the pruning algorithm not only prevents the occasional decrease of effectiveness caused by conflicting concepts among the problem domains, but also provides a better understanding of the problem domains and their relationships.
mining genes in dna using genescout. in this paper, we present a new system, calledgenescout, for predicting gene structures in vertebrate genomicdna. the system contains specially designed hiddenmarkov models (hmms) for detecting functional sites includingprotein-translation start sites, mrna splicing junctiondonor and acceptor sites, etc. our main hypothesisis that, given a vertebrate genomic dna sequence s, it isalways possible to construct a directed acyclic graph gsuch that the path for the actual coding region of s is inthe set of all paths on g. thus, the gene detection problemis reduced to that of analyzing the paths in the graphg. a dynamic programming algorithm is used to find theoptimal path in g. the proposed system is trained usingan expectation-maximization (em) algorithm and its performanceon vertebrate gene prediction is evaluated usingthe 10-way cross-validation method. experimental resultsshow the good performance of the proposed system and itscomplementarity to a widely used gene detection system.
learning through changes: an empirical study of dynamic behaviors of probability estimation trees. in practice, learning from data is often hampered by the limited training examples. in this paper, as the size of training data varies, we empirically investigate several probability estimation tree algorithms over eighteen binary classification problems. nine metrics are used to evaluate their performances. our aggregated results show that ensemble trees consistently outperform single trees. confusion factor trees(cft) register poor calibration even as training size increases, which shows that cfts are potentially biased if data sets have small noise. we also provide analysis on the observed performance of the tree algorithms.
integrating hidden markov models and spectral analysis for sensory time series clustering. we present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. the sensory time-series data present new challenges to data mining, including uneven sequence lengths, multi-dimensionality and high levels of noise. we adopt a principled approach, by first transforming all the data into an equal-length vector form while keeping as much temporal information as we can, and then applying dimensionality and noise reduction techniques such as spectral clustering to the transformed data. experimental evaluation on synthetic and real data shows that our proposed approach outperforms standard model-based clustering algorithms for time series data.
detecting patterns of change using enhanced parallel coordinates visualization. analyzing data to find trends, correlations, and stablepatterns is an important problem for many industrialapplications. in this paper, we propose a new techniquebased on parallel coordinates visualization. previous workon parallel coordinates methods has shown that they areeffective only when variables that are correlated and/orshow similar patterns are displayed adjacently. althoughcurrent parallel coordinates tools allow the user tomanually rearrange the order of variables, this process isvery time-consuming when the number of variables islarge. automated assistance is needed. this paperproposes an edit-distance based technique to rearrangevariables so that interesting patterns can be easilydetected. our system, v-miner, includes both automatedmethods for visualizing common patterns and a query toolthat enables the user to describe specific target patterns tobe mined/displayed by the system. following an overviewof the system, a case study is presented to explain howmotorola engineers have used v-miner to identifysignificant patterns in their product test and design data.
frequent-pattern based iterative projected clustering. irrelevant attributes add noise to high dimensional clustersand make traditional clustering techniques inappropriate.projected clustering algorithms have been proposed to findthe clusters in hidden subspaces. we realize the analogy betweenmining frequent itemsets and discovering the relevantsubspace for a given cluster. we propose a methodology forfinding projected clusters by mining frequent itemsets andpresent heuristics that improve its quality. our techniquesare evaluated with synthetic and real data; they are scalableand discover projected clusters accurately.
a visual data mining framework for convenient identification of useful knowledge. data mining algorithms usually generate a large number of rules, which may not always be useful to human users. in this project, we propose a novel visual data-mining framework, called opportunity map, to identify useful and actionable knowledge quickly and easily from the discovered rules. the framework is inspired by the house of quality from quality function deployment (qfd) in quality engineering. it associates discovered rules, related summarized data and data distributions with the application objective using an interactive matrix. combined with drill down visualization, integrated visualization of data distribution bars and rules, visualization of trend behaviors, and comparative analysis, the opportunity map allows users to analyze rules and data at different levels of detail and quickly identify the actionable knowledge and opportunities. the proposed framework represents a systematic and flexible approach to rule analysis. applications of the system to large-scale data sets from our industrial partner have yielded promising results.
demand forecasting by the neural network with discrete fourier transform. this paper proposes a new demand forecastingmethod using the neural network and fourier transform.in this method, time series data of sales resultsconsidered as a combination of frequency aretransformed into several frequency data. they areidentified from objective indexes that consist of productproperties or economic indicators and so forth. thismethod is efficient for demand forecasting aimed at newproducts that have no historical data.
adaptive parallel sentences mining from web bilingual news collection. in this paper a robust, adaptive approach for miningparallel sentences from a bilingual comparable newscollection is described. sentence length models andlexicon-based models are combined under a maximumlikelihood criterion. specific models are proposed to handleinsertions and deletions that are frequent in bilingualdata collected from the web. the proposed approach isadaptive, updating the translation lexicon iteratively usingthe mined parallel data to get better vocabulary coverageand translation probability parameter estimation.experiments are carried out on 10 years of xinhuabilingual news collection. using the mined data, we getsignificant improvement in word-to-word alignment accuracyin machine translation modeling.
a join-less approach for co-location pattern mining: a summary of results. spatial co-location patterns represent the subsets of features whose instances are frequently located together in geographic space. co-location pattern discovery presents challenges since the instances of spatial features are embedded in a continuous space and share a variety of spatial relationships. a large fraction of the computation time is devoted to identifying the instances of co-location patterns. we propose a novel join-less approach for co-location pattern mining, which materializes spatial neighbor relationships with no loss of co-location instances and reduces the computational cost of identifying the instances. the join-less co-location mining algorithm is efficient since it uses an instance-lookup scheme instead of an expensive spatial or instance join operation for identifying co-location instances. the experimental evaluations show the join-less algorithm performs more efficiently than a current join-based algorithm and is scalable in dense spatial datasets.
on active learning for data acquisition. many applications are characterized by having naturallyincomplete data on customers - where data on only somefixed set of local variables is gathered. however, having amore complete picture can help build better models. thenaïve solution to this problem - acquiring complete datafor all customers - is often impractical due to the costs ofdoing so. a possible alternative is to acquire completedata for "some" customers and to use this to improve themodels built. the data acquisition problem is determininghow many, and which, customers to acquire additionaldata from. in this paper we suggest using active learningbased approaches for the data acquisition problem. inparticular, we present initial methods for data acquisitionand evaluate these methods experimentally on web usagedata and uci datasets. results show that the methodsperform well and indicate that active learning basedmethods for data acquisition can be a promising area fordata mining research.
example-based robust outlier detection in high dimensional datasets. detecting outliers is an important problem. most of its applications typically possess high dimensional datasets. in high dimensional space, the data becomes sparse which implies that every object can be regarded as an outlier from the point of view of similarity. furthermore, a fundamental issue is that the notion of which objects are outliers typically varies between users, problem domains or, even, datasets. in this paper, we present a novel robust solution which detects high dimensional outliers based on user examples and tolerates incorrect inputs. it studies the behavior of projections of such a few examples, to discover further objects that are outstanding in the projection where many examples are outlying. our experiments on both real and synthetic datasets demonstrate the ability of the proposed method to detect outliers corresponding to the user examples.
general mc: estimating boundary of positive class from small positive data. single-class classification (scc) seeks to distinguishone class of data from the universal set of multiple classes.we propose a scc method called general mc that estimatesan accurate classification boundary of positive classfrom small positive data using the distribution of unlabeleddata. our theoretical and empirical analyses show that,as long as the distribution of unlabeled data is not highlyskewed in the feature space, general mc significantly outperformsother recent scc methods when the positive dataset is highly under-sampled.
a feature selection framework for text filtering. this paper presents a new framework for local featureselection in text filtering. in this framework, a feature setis constructed per category by first selecting a set of termshighly indicative of membership (positive set) and anotherset of terms highly indicative of non-membership (negativeset), and then combining these two sets. this feature selectionframework not only unifies several standard featureselection methods, but also facilitates the proposal of a newmethod that optimally combines the positive and negativesets. the experimental comparison between the proposedmethod and standard methods was conducted on six featureselection metrics: chi-square, correlation coefficient, oddsratio, gss coefficient and two proposed variants of odds ratioand gss coefficient: or-square and gss-square respectively.the results show that the proposed feature selectionmethod improves text filtering performance.
heterogeneous learner for web page classification. classification of an interesting class of web pages (e.g.,personal homepages, resume pages) has been an interestingproblem. typical machine learning algorithms for thisproblem require two classes of data for training: positiveand negative training examples. however, in applicationto web page classification, gathering an unbiased sampleof negative examples appears to be difficult. we proposea heterogeneous learning framework for classifying webpages, which (1) eliminates the need for negative trainingdata, and (2) increases classification accuracy by using twoheterogeneous learners. our framework uses two heterogeneouslearners - a decision list and a linear separatorwhich complement each other - to eliminate the need fornegative training data in the training phase and to increasethe accuracy in the testing phase. our results show that ourheterogeneous framework achieves high accuracy withoutrequiring negative training data; it enhances the accuracyof linear separators by reducing the errors on "low-margindata". that is, it classifies more accurately while requiringless human efforts in training.
relational peculiarity oriented data mining. peculiarity rules are a new type of interesting rules which can be discovered by searching the relevance among peculiar data. a main task of mining peculiarity rules is the identification of peculiarity. traditional methods of finding peculiar data are attribute-based approaches. this paper extends peculiarity oriented mining to relational peculiarity oriented mining. peculiar data are identified on record level, and peculiar rules are mined and explained in a relational mining framework. the results from preliminary experiments show that relational peculiarity oriented mining is very effective.
scalable construction of topic directory with nonparametric closed termset mining. a topic directory, e.g., yahoo directory, provides a view of a document set at different levelsof abstraction and is ideal for the interactive exploration and visualization of the document set. we present a method that dynamically generates a topic directory from a document set usinga frequent closed termset mining algorithm. our method shows experimental results of equal quality to recent document clustering methods and has additional benefits such as automatic generation of topic labels and determination of a clustering parameter.
the relationships among various nonnegative matrix factorization methods for clustering. the nonnegative matrix factorization (nmf) has been shown recently to be useful for clustering and various extensions and variations of nmf have been proposed recently. despite significant research progress in this area, few attempts have been made to establish the connections between various factorization methods while highlighting their differences. in this paper we aim to provide a comprehensive study on matrix factorization for clustering. in particular, we present an overview and summary on various matrix factorization algorithms and theoretically analyze the relationships among them. experiments are also conducted to empirically evaluate and compare various factorization methods. in addition, our study also answers several previously unaddressed yet important questions for matrix factorizations including the interpretation and normalization of cluster posterior and the benefits and evaluation of simultaneous clustering. we expect our study would provide good insights on matrix factorization research for clustering.
a k-nn associated fuzzy evidential reasoning classifier with adaptive neighbor selection. the paper presents a fuzzy evidential reasoning algorithmin light of the dempster-shafer evidence theory andthe k-nearest neighbor algorithm for pattern classification.given an input pattern to be classified, each of its k nearestneighbors is viewed as an evidence source, in terms ofa fuzzy evidence structure. the distance between the inputpattern and each of its k nearest neighbors is usedfor mass determination while the contextual information ofthe nearest neighbor in the training sample space is formulatedby a fuzzy set in determining a fuzzy focal element.therefore, pooling evidence provided by neighbors is realizedby a fuzzy evidential reasoning, where feature selectionis further considered through ranking and adaptive combinationof neighbors. a fast implementation scheme of thefuzzy evidential reasoning is also developed. experimentalresults of classifying multi-channel remote sensing imageshave shown that the proposed approach outperforms the k-nearestneighbor (k-nn) algorithm [1], the fuzzy k-nearestneighbor (f-knn) algorithm [2], the evidence-theoretic k-nearestneighbor (e-knn) algorithm [3], and the fuzzy ex-tendedversion of e-knn (fe-knn) [4], in terms of theclassification accuracy and insensitivity to the number kof nearest neighbors.
cost-guided class noise handling for effective cost-sensitive learning. recent research in machine learning, data mining and related areas has produced a wide variety of algorithms for cost-sensitive (cs) classification, where instead of maximizing the classification accuracy, minimizing the misclassification cost becomes the objective. however, these methods assume that training sets do not contain significant noise, which is rarely the case in real-world environments. in this paper, we systematically study the impacts of class noise on cs learning, and propose a cost-guided class noise handling algorithm to identify noise for effective cs learning. we call it cost-guided iterative classification filter (cicf), because it seamlessly integrates costs and an existing classification filter for noise identification. instead of putting equal weights to handle noise in all classes in existing efforts, cicf puts more emphasis on expensive classes, which makes it especially successful in dealing with datasets with a large cost-ratio. experimental results and comparative studies from real-world datasets indicate that the existence of noise may seriously corrupt the performance of cs classifiers, and by adopting the proposed cicf algorithm, we can significantly reduce the misclassification cost of a cs classifier in noisy environments.
dynamic classifier selection for effective mining from noisy data streams. recently, mining from data streams has become an important and challenging task for many real-world applications such as credit card fraud protection and sensor networking. one popular solution is to separate stream data into chunks, learn a base classifier from each chunk, and then integrate all base classifiers for effective classification. in this paper, we propose a new dynamic classifier selection (dcs) mechanism to integrate base classifiers for effective mining from data streams. the proposed algorithm dynamically selects a single "best" classifier to classify each test instance at run time. our scheme uses statistical information from attribute values, and uses each attribute to partition the evaluation set into disjoint subsets, followed by a procedure that evaluates the classification accuracy of each base classifier on these subsets. given a test instance, its attribute values determine the subsets that the similar instances in the evaluation set have constructed, and the classifier with the highest classification accuracy on those subsets is selected to classify the test instance. experimental results and comparative studies demonstrate the efficiency and efficacy of our method. such a dcs scheme appears to be promising in mining data streams with dramatic concept drifting or with a significant amount of noise, where the base classifiers are likely conflictive or have low confidence.
efficient text classification by weighted proximal svm. in this paper, we present an algorithm that can classify large-scale text data with high classification quality and fast training speed. our method is based on a novel extension of the proximal svm mode [3]. previous studies on proximal svm have focused on classification for low dimensional data and did not consider the unbalanced data cases. such methods will meet difficulties when classifying unbalanced and high dimensional data sets such as text documents. in this work, we extend the original proximal svm by learning a weight for each training error. we show that the classification algorithm based on this model is capable of handling high dimensional and unbalanced data. in the experiments, we compare our method with the original proximal svm (as a special case of our algorithm) and the standard svm (such as svm light) on the recently published rcv1-v2 dataset. the results show that our proposed method had comparable classification quality with the standard svm. at the same time, both the time and memory consumption of our method are less than that of the standard svm.
ctc - correlating tree patterns for classification. we present ctc, a new approach to structural classification. it uses the predictive power of tree patterns correlating with the class values, combining state-of-the-art tree mining with sophisticated pruning techniques to find the k most discriminative pattern in a dataset. in contrast to existing methods, ctc uses no heuristics and the only parameters to be chosen by the user are the maximum size of the rule set and a single, statistically well founded cut-off value. the experiments show that ctc classifiers achieve good accuracies while the induced models are smaller than those of existing approaches, facilitating comprehensibility.
a pattern decomposition (pd) algorithm for finding all frequent patterns in large datasets. efficient algorithms to mine frequent patterns are crucial to many tasks in data mining. since the apriori algorithm was proposed in 1994, there have been several methods proposed to improve its performance. however, most still adopt its candidate set generation-and-testapproach. we propose a pattern decomposition (pd) algorithm that can significantly reduce the size of the dataset on each pass making it more efficient to mine frequent patterns in a large dataset. the proposed algorithm avoids the costly process of candidate set generation and saves time by reducing dataset. our empirical evaluation shows that the algorithmoutperforms apriori by one order of magnitude and is faster than fp-tree. further, pd is more scalable than both apriori and fp-tree.
smartminer: a depth first algorithm guided by tail information for mining maximal frequent itemsets. maximal frequent itemsets (mfi) are crucial to manytasks in data mining. since the maxminer algorithm firstintroduced enumeration trees for mining mfi in 1998,several methods have been proposed to use depth firstsearch to improve performance. to further improve theperformance of mining mfi, we proposed a techniquethat takes advantage of the information gathered fromprevious steps to discover new mfi. more specifically,our algorithm called smartminer gathers and passes tailinformation and uses a heuristic select function whichuses the tail information to select the next node toexplore. compared with mafia and genmax, smartminergenerates a smaller search tree, requires a smallernumber of support counting, and does not requiresuperset checking. using the datasets mushroom andconnect, our experimental study reveals that smartminergenerates the same mfi as mafia and genmax, but yieldsan order of magnitude improvement in speed.
hierarchical classification by expected utility maximization. hierarchical classification refers to an extension of the standard classification problem, in which labels must be chosen from a class hierarchy. in this paper, we look at hierarchical classification from an information retrieval point of view. more specifically, we consider a scenario in which a user searches a document in a topic hierarchy. this scenario gives rise to the problem of predicting an optimal entry point, that is, a topic node in which the user starts searching. the usefulness of a corresponding prediction strongly depends on the search behavior of the user, which becomes relevant if the document is not immediately found in the predicted node. typically, users tend to browse the hierarchy in a top-down manner, i.e., they look at a few more specific subcategories but usually refuse exploring completely different branches of the search tree. from a classification point of view, this means that a prediction should be evaluated, not solely on the basis of its correctness, but rather by judging its usefulness against the background of the user behavior. the idea of this paper is to formalize hierarchical classification within a decision-theoretic framework which allows for modeling this usefulness in terms of a user-specific utility function. the prediction problem thus becomes a problem of expected utility maximization. apart from its theoretical appeal, we provide first empirical results showing that the approach performs well in practice.
regularized least absolute deviations regression and an efficient algorithm for parameter tuning. linear regression is one of the most important and widely used techniques for data analysis. however, sometimes people are not satisfied with it because of the following two limitations: 1) its results are sensitive to outliers, so when the error terms are not normally distributed, especially when they have heavy-tailed distributions, linear regression often works badly; 2) its estimated coefficients tend to have high variance, although their bias is low. to reduce the influence of outliers, robust regression models were developed. least absolute deviation (lad) regression is one of them. lad minimizes the mean absolute errors, instead of mean squared errors, so its results are more robust. to address the second limitation, shrinkage methods were proposed, which add a penalty on the size of the coefficients. the lasso is one of these methods and it uses the l1-norm penalty, which not only reduces the prediction error and the variance of estimated coefficients, but also provides an automatic feature selection function. in this paper, we propose the regularized least absolute deviation (rlad) regression model, which combines the nice features of the lad and the lasso together. the rlad is a regularization method, whose objective function has the form of "loss + penalty." the "loss" is the sum of the absolute deviations and the "penalty" is the l1-norm of the coefficient vector. furthermore, to facilitate parameter tuning, we develop an efficient algorithm which can solve the entire regularization path in one pass. simulations with various settings are performed to demonstrate its performance. finally, we apply the algorithm to solve the image reconstruction problem and find interesting results.
cominer: an effective algorithm for mining competitors from the web. this paper attempts to accomplish a novel task of mining competitive information with respect to an entity (such as a company, product, person) from the web. an algorithm called "cominer" is proposed, which first extracts a set of comparative candidates of the input entity and then ranks them according to the comparability, and finally extracts the competitive fields. the experimental results show that the proposed algorithm drafts a complete picture of competitive relation of a given entity effectively.
turning clusters into patterns: rectangle-based discriminative data description. the ultimate goal of data mining is to extract knowledge from massive data. knowledge is ideally represented as human-comprehensible patterns from which end-users can gain intuitions and insights. yet not all data mining methods produce such readily understandable knowledge, e.g., most clustering algorithms output sets of points as clusters. in this paper, we perform a systematic study of cluster description that generates interpretable patterns from clusters. we introduce and analyze novel description formats leading to more expressive power, motivate and define novel description problems specifying different trade-offs between interpretability and accuracy. we also present effective heuristic algorithms together with their empirical evaluations.
object identification with constraints. object identification aims at identifying different representations of the same object based on noisy attributes such as descriptions of the same product in different online shops or references to the same paper in different publications. numerous solutions have been proposed for solving this task, almost all of them based on similarity functions of a pair of objects. although today the similarity functions are learned from a set of labeled training data, the structural information given by the labeled data is not used. by formulating a generic model for object identification we show how almost any proposed identification model can easily be extended for satisfying structural constraints. therefore we propose a model that uses structural information given as pairwise constraints to guide collective decisions about object identification in addition to a learned similarity measure. we show with empirical experiments on public and on real-life data that combining both structural information and attribute-based similarity enormously increases the overall performance for object identification tasks.
deploying approaches for pattern refinement in text mining. text mining is the technique that helps users find useful information from a large amount of digital text documents on the web or databases. instead of the keyword-based approach which is typically used in this field, the pattern-based model containing frequent sequential patterns is employed to perform the same concept of tasks. however, how to effectively use these discovered patterns is still a big challenge. in this study, we propose two approaches based on the use of pattern deploying strategies. the performance of the pattern deploying algorithms for text mining is investigated on the reuters dataset rcv1 and the results show that the effectiveness is improved by using our proposed pattern refinement approaches.
rule-based platform for web user profiling. this paper discusses a research project: rule-based web user profiling platform. in this platform, usage data are encoded as a sequence of events, each of which represents an action performed by a user on a web service at a given time. an event template is proposed to define event models for different web services. the platform is rule-based. rules define profile metrics and determine how to compute profile metrics from usage events. a prototype of the platform was implemented and was applied to generate profiles from page view events. the major contribution of the work is the rule-based approach to user profiling. it is the rules and the event template that provide the flexibility to allow the platform to be configured for different web services.
high-performance unsupervised relation extraction from large corpora. we present uries -- an unsupervised relation identification and extraction system. the system automatically identifies interesting binary relations between entities in the input corpus, and then proceeds to extract a large number of instances of these relations. the system discovers relations by clustering frequently co-occuring pairs of entities, based on the contexts in which they appear. its complex pattern-based representation of the contexts allows the clustering step to achieve very high precision, sufficient for the clusters to perform as sets of seeds for bootstrapping a high-recall relation extraction process. in a series of experiments we demonstrate the successful performance of uries and compare it to the two existing systems -- a weakly supervised high-recall web relation extraction system called sres, and an unsupervised relation identification system that uses a simpler bag-of-words representation of contexts. the experiments show that uries performs comparably to sres, but without any supervision, and that such performance is due to the power of its complex contexts representation and to its novel candidate selection method.
improving nearest neighbor classifier using tabu search and ensemble distance metrics. the nearest-neighbor (nn) classifier has long been used in pattern recognition, exploratory data analysis, and data mining problems. a vital consideration in obtaining good results with this technique is the choice of distance function, and correspondingly which features to consider when computing distances between samples. in this paper, a new ensemble technique is proposed to improve the performance of nn classifier. the proposed approach combines multiple nn classifiers, where each classifier uses a different distance function and potentially a different set of features (feature vector). these feature vectors are determined for each distance metric using simple voting scheme incorporated in tabu search (ts). the proposed ensemble classifier with different distance metrics and different feature vectors (ts-df/nn) is evaluated using various benchmark data sets from uci machine learning repository. results have indicated a significant increase in the performance when compared with various well-known classifiers. furthermore, the proposed ensemble method is also compared with ensemble classifier using different distance metrics but with same feature vector (with or without feature selection (fs)).
high quality, efficient hierarchical document clustering using closed interesting itemsets. high dimensionality remains a significant challenge for document clustering. recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to improve the efficiency of hierarchical document clustering. in this paper, we introduce the notion of "closed interesting" itemsets (i.e. closed itemsets with high interestingness). we provide heuristics such as "super item" to efficiently mine these itemsets and show that they provide significant dimensionality reduction over closed frequent itemsets. using "closed interesting" itemsets, we propose a new, sub-linearly scalable, hierarchical document clustering method that outperforms state of the art agglomerative, partitioning and frequent-itemset based methods both in terms of clustering quality and runtime performance, without requiring dataset specific parameter tuning. we evaluate twenty interestingness measures and show that when used to generate "closed interesting" itemsets, and to select parent nodes, mutual information, added value, yule's q and chi- square offer best clustering performance.
saxually explicit images: finding unusual shapes. over the past three decades, there has been a great deal of research on shape analysis, focusing mostly on shape indexing, clustering, and classification. in this work, we introduce the new problem of finding shape discords, the most unusual shapes in a collection. we motivate the problem by considering the utility of shape discords in diverse domains including zoology, anthropology, and medicine. while the brute force search algorithm has quadratic time complexity, we avoid this by using locality-sensitive hashing to estimate similarity between shapes which enables us to reorder the search more efficiently. an extensive experimental evaluation demonstrates that our approach can speed up computation by three to four orders of magnitude.
plagiarism detection in arxiv. we describe a large-scale application of methods for finding plagiarism in research document collections. the methods are applied to a collection of 284,834 documents collected by arxiv.org over a 14 year period, covering a few different research disciplines. the methodology effi- ciently detects a variety of problematic author behaviors, and heuristics are developed to reduce the number of false positives. the methods are also efficient enough to imple- ment as a real-time submission screen for a collection many times larger.
semantic kernels for text classification based on topological measures of feature similarity. in this paper we propose a new approach to the design of semantic smoothing kernels for text classification. these kernels implicitly encode a superconcept expansion in a semantic network using well-known measures of term similarity. the experimental evaluation on two different datasets indicates that our approach consistently improves performance in situations of little training data and data sparseness.
an interactive semantic video mining and retrieval platform--application in transportation surveillance video for incident detection. understanding and retrieving videos based on their semantic contents is an important research topic in multimedia data mining and has found various real-world applications. most existing video analysis techniques focus on the low level visual features of video data. however, there is a "semantic gap" between the machine-readable features and the high level human concepts i.e. human understanding of the video content. in this paper, an interactive platform for semantic video mining and retrieval is proposed using relevance feedback (rf), a popular technique in the area of content-based image retrieval (cbir). by tracking semantic objects in a video and then modeling spatio-temporal events based on object trajectories and object interactions, the proposed interactive learning algorithm in the platform is able to mine the spatio-temporal data extracted from the video. an iterative learning process is involved in the proposed platform, which is guided by the user's response to the retrieved results. although the proposed video retrieval platform is intended for general use and can be tailored to many applications, we focus on its application in traffic surveillance video database retrieval to demonstrate the design details. the effectiveness of the algorithm is demonstrated by our experiments on real-life traffic surveillance videos.
solution path for semi-supervised classification with manifold regularization. with very low extra computational cost, the entire solution path can be computed for various learning algorithms like support vector classification (svc) and support vector regression (svr). in this paper, we extend this promising approach to semi-supervised learning algorithms. in particular, we consider finding the solution path for the laplacian support vector machine (lapsvm) which is a semi-supervised classification model based on manifold regularization. one advantage of the this algorithm is that the coefficient path is piecewise linear with respect to the regularization parameter, hence its computational complexity is quadratic in the number of labeled examples.
a simple yet effective data clustering algorithm. in this paper, we use a simple concept based on k-reverse nearest neighbor digraphs, to develop a framework record for clustering and outlier detection. we developed three algorithms - (i) record algorithm (requires one parameter), (ii) agglomerative record algorithm (no parameters required) and (iii) stability-based record algorithm( no parameters required). our experimental results with published datasets, synthetic and real-life datasets show that record not only handles noisy data, but also identifies the relevant clusters. our results are as good as (if not better than) the results got from other algorithms.
coala: a novel approach for the extraction of an alternate clustering of high quality and high dissimilarity. cluster analysis has long been a fundamental task in data mining and machine learning. however, traditional clustering methods concentrate on producing a single solution, even though multiple alternative clusterings may exist. it is thus difficult for the user to validate whether the given solution is in fact appropriate, particularly for large and complex datasets. in this paper we explore the critical requirements for systematically finding a new clustering, given that an already known clustering is available and we also propose a novel algorithm, coala, to discover this new clustering. our approach is driven by two important factors; dissimilarity and quality. these are especially important for finding a new clustering which is highly informative about the underlying structure of data, but is at the same time distinctively different from the provided clustering. we undertake an experimental analysis and show that our method is able to outperform existing techniques, for both synthetic and real datasets.
optimal segmentation using tree models. sequence data are abundant in application areas such as computational biology, environmental sciences, and telecommunications. many real-life sequences have a strong segmental structure, with segments of different complexities. in this paper we study the description of sequence segments using variable length markov chains (vlmcs), also known as tree models. we discover the segment boundaries of a sequence and at the same time we compute a vlmc for each segment. we use the bayesian information criterion (bic) and a variant of the minimum description length (mdl) principle that uses the krichevsky-trofimov (kt) code length to select the number of segments of a sequence. on dna data the method selects segments that closely correspond to the annotated regions of the genes.
local correlation tracking in time series. we address the problem of capturing and tracking local correlations among time evolving time series. our approach is based on comparing the local auto-covariance matrices (via their spectral decompositions) of each series and generalizes the notion of linear cross-correlation. in this way, it is possible to concisely capture a wide variety of local patterns or trends. our method produces a general similarity score, which evolves over time, and accurately reflects the changing relationships. finally, it can also be estimated incrementally, in a streaming setting. we demonstrate its usefulness, robustness and efficiency on a wide range of real datasets.
identifying follow-correlation itemset-pairs. an association rule a\to b is useful to predict that b will likely occur when a occurs. this is a classical association rule. in real world applications, such as bioinformatics and medical research, there are many follow correlations between itemsets a and b: b likely occurs n times after a occurred m times, wrote to \le a^m , b^n \ge. we refer to this follow-correlation as p3.1 itemset-pairs because \le a^3 , b^1\ge like that in example 2 should be uninterested in association analysis. this paper designs an efficient algorithm for identifying p3.1 itemset-pairs in sequential data. we experimentally evaluate our approach, and demonstrate that the proposed approach is efficient and promising.
large scale detection of irregularities in accounting data. in recent years, there have been several large accounting frauds where a company's financial results have been intentionally misrepresented by billions of dollars. in response, regulatory bodies have mandated that auditors perform analytics on detailed financial data with the intent of discovering such misstatements. for a large auditing firm, this may mean analyzing millions of records from thousands of clients. this paper proposes techniques for automatic analysis of company general ledgers on such a large scale, identifying irregularities - which may indicate fraud or just honest errors - for additional review by auditors. these techniques have been implemented in a prototype system, called sherlock, which combines aspects of both outlier detection and classification. in developing sherlock, we faced three major challenges: developing an efficient process for obtaining data from many heterogeneous sources, training classifiers with only positive and unlabeled examples, and presenting information to auditors in an easily interpretable manner. in this paper, we describe how we addressed these challenges over the past two years and report on experiments evaluating sherlock.
applying data mining to pseudo-relevance feedback for high performance text retrieval. in this paper, we investigate the use of data mining, in particular the text classification and co-training techniques, to identify more relevant passages based on a small set of labeled passages obtained from the blind feedback of a retrieval system. the data mining results are used to expand query terms and to re-estimate some of the parameters used in a probabilistic weighting function. we evaluate the data mining based feedback method on the trec hard data set. the results show that data mining can be successfully applied to improve the text retrieval performance. we report our experimental findings in detail.
automatic single-organ segmentation in computed tomography images. in this paper, we propose a hybrid approach for automatic single-organ segmentation in computed tomography (ct) data. the approach consists of three stages: first, a probability image of the organ of interest is obtained by applying a binary classification model obtained using pixel-based texture features; second, an adaptive split-and-merge segmentation algorithm is applied on the organ probability image to remove the noise introduced by the misclassified pixels; and third, the segmented organ's boundaries from the previous stage are iteratively refined using a region growing algorithm. while we applied our approach for liver segmentation in 2-d ct images, a challenging and important task in many medical applications, the proposed approach can be applied for the segmentation of any other organ in ct images. moreover, the proposed approach can be extended to perform automatic multiple organ segmentation and to build context-sensitive reporting tools for computer-aided diagnosis applications.
probabilistic segmentation and analysis of horizontal cells. because images of neurons show interweaved processes from multiple cells, it is hard to determine which pixels belong to each cell, and consequently to analyze the images automatically. to manage these difficulties, we introduce probabilistic segmentation, in which each pixel is assigned a probability of belonging to each cell instead of being categorically assigned to one cell. we propose a randomized algorithm for probabilistic segmentation. the algorithm is based on repeated, intensity-weighted random walks on the image, and leads to improved segmentation quality. analysis and mining techniques can utilize the more nuanced and complete information that the probabilistic segmentation yields about an image. such techniques can then compute probabilistic values, which indicate the level of confidence that can be placed in them.
mixed-drove spatio-temporal co-occurence pattern mining: a summary of results. mixed-drove spatio-temporal co-occurrence patterns (mdcops) represent subsets of object-types that are located together in space and time. discovering mdcops is an important problem with many applications such as identifying tactics in battlefields, games, and predator-prey interactions. however, mining mdcops is computationally very expensive because the interest measures are computationally complex, datasets are larger due to the archival history, and the set of candidate patterns is exponential in the number of object-types. we propose a monotonic composite interest measure for discovering mdcops and a novel mdcop mining algorithm. analytical and experimental results show that the proposed algorithm is correct and complete. results also show the proposed method is computationally more efficient than naïve alternatives.
dirichlet aspect weighting: a generalized em algorithm for integrating external data fields with semantically structured queries by using gradient projection method. in this paper we address the problem of document retrieval with semantically structured queries - queries where each term has a tagged field label. we introduce dirichlet aspect weighting model which integrates terms from external databases into the query language model in a bayesian learning framework. for this model, the dirichlet prior distribution is governed by parameters which depend on the number of fields in the external databases. this model needs additional examples to be augmented to the semantically structured query. these examples are obtained using pseudo relevance feedback. we formulate a loglikelihood function for the dirichlet aspect weighting model and maximize it using a novel generalized em algorithm. comparison of the results of dirichlet aspect weighting model on trec 2005 genomics track dataset with baseline methods using pseudo relevance feedback, while incorporating terms from external databases shows an improvement.
manifold clustering of shapes. shape clustering can significantly facilitate the automatic labeling of objects present in image collections. for example, it could outline the existing groups of pathological cells in a bank of cyto-images; the groups of species on photographs collected from certain aerials; or the groups of objects observed on surveillance scenes from an office building. here we demonstrate that a nonlinear projection algorithm such as isomap can attract together shapes of similar objects, suggesting the existence of isometry between the shape space and a low dimensional nonlinear embedding. whenever there is a relatively small amount of noise in the data, the projection forms compact, convex clusters that can easily be learned by a subsequent partitioning scheme. we further propose a modification of the isomap projection based on the concept of degree-bounded minimum spanning trees. the proposed approach is demonstrated to move apart bridged clusters and to alleviate the effect of noise in the data.
an efficient reference-based approach to outlier detection in large datasets. a bottleneck to detecting distance and density based outliers is that a nearest-neighbor search is required for each of the data points, resulting in a quadratic number of pairwise distance evaluations. in this paper, we propose a new method that uses the relative degree of density with respect to a fixed set of reference points to approximate the degree of density defined in terms of nearest neighbors of a data point. the running time of our algorithm based on this approximation is o(r_n log n) where n is the size of dataset and r is the number of reference points. candidate outliers are ranked based on the outlier score assigned to each data point. theoretical analysis and empirical studies show that our method is effective, efficient, and highly scalable to very large datasets.
exploratory mining in cube space. data mining has evolved as a new discipline at the intersection of several existing areas, including database systems, machine learning, optimization, and statistics. an important question is whether the field has matured to the point where it has originated substantial new problems and techniques that distinguish it fromits parent disciplines. in this paper, we discuss a class of new problems and techniques that show great promise for exploratory mining, while synthesizing and generalizing ideas from the parent disciplines. while the class of problems we discuss is broad, there is a common underlying objective-to look beyond a single data mining step (e.g., data summarization or model construction) and address the combined process of data selection and transformation, parameter and algorithm selection, and model construction. the fundamental difficulty lies in the large space of alternative choices at each step, and good solutions must provide a natural framework for managing this complexity. we regard this as a grand challenge for datamining, and see the ideas in this paper as promising initial steps towards a rigorous exploratory framework that supports the entire process.
adaptive blocking: learning to scale up record linkage. many data mining tasks require computing similarity between pairs of objects. pairwise similarity computations are particularly important in record linkage systems, as well as in clustering and schema mapping algorithms. because the number of object pairs grows quadratically with the size of the dataset, computing similarity between all pairs is impractical and becomes prohibitive for large datasets and complex similarity functions. blocking methods alleviate this problem by efficiently selecting approximately similar object pairs for subsequent distance computations, leaving out the remaining pairs as dissimilar. previously proposed blocking methods require manually constructing an index-based similarity function or selecting a set of predicates, followed by hand-tuning of parameters. in this paper, we introduce an adaptive framework for automatically learning blocking functions that are efficient and accurate. we describe two predicate-based formulations of learnable blocking functions and provide learning algorithms for training them. the effectiveness of the proposed techniques is demonstrated on real and simulated datasets, on which they prove to be more accurate than non-adaptive blocking methods.
meta clustering. clustering is ill-defined. unlike supervised learning where labels lead to crisp performance criteria such as accuracy and squared error, clustering quality depends on how the clusters will be used. devising clustering criteria that capture what users need is difficult. most clustering algorithms search for optimal clusterings based on a pre-specified clustering criterion. our approach differs. we search for many alternate clusterings of the data, and then allow users to select the clustering(s) that best fit their needs. meta clustering first finds a variety of clusterings and then clusters this diverse set of clusterings so that users must only examine a small number of qualitatively different clusterings. we present methods for automatically generating a diverse set of alternate clusterings, as well as methods for grouping clusterings into meta clusters. we evaluate meta clustering on four test problems and two case studies. surprisingly, clusterings that would be of most interest to users often are not very compact clusterings.
an experimental investigation of graph kernels on a collaborative recommendation task. this work presents a systematic comparison between seven kernels (or similarity matrices) on a graph, namely the exponential diffusion kernel, the laplacian diffusion kernel, the von neumann kernel, the regularized laplacian kernel, the commute time kernel, and finally the markov diffusion kernel and the cross-entropy diffusion matrix -- both introduced in this paper -- on a collaborative recommendation task involving a database. the database is viewed as a graph where elements are represented as nodes and relations as links between nodes. from this graph, seven kernels are computed, leading to a set of meaningful proximity measures between nodes, allowing to answer questions about the structure of the graph under investigation; in particular, recommend items to users. crossvalidation results indicate that a simple nearest-neighbours rule based on the similarity measure provided by the regularized laplacian, the markov diffusion and the commute time kernels performs best. we therefore recommend the use of the commute time kernel for computing similarities between elements of a database, for two reasons: (1) it has a nice appealing interpretation in terms of random walks and (2) no parameter needs to be adjusted.
adding semantics to email clustering. this paper presents a novel algorithm to cluster emails according to their contents and the sentence styles of their subject lines. in our algorithm, natural language processing techniques and frequent itemset mining techniques are utilized to automatically generate meaningful generalized sentence patterns (gsps) from subjects of emails. then we put forward a novel unsupervised approach which treats gsps as pseudo class labels and conduct email clustering in a supervised manner, although no human labeling is involved. our proposed algorithm is not only expected to improve the clustering performance, it can also provide meaningful descriptions of the resulted clusters by the gsps. experimental results on open dataset (enron email dataset) and a personal email dataset collected by ourselves demonstrate that the proposed algorithm outperforms the k-means algorithm in terms of the popular measurement f1. furthermore, the cluster naming readability is improved by 68.5% on the personal email dataset.
pattern mining in frequent dynamic subgraphs. graph-structured data is becoming increasingly abundant in many application domains. graph mining aims at finding interesting patterns within this data that represent novel knowledge. while current data mining deals with static graphs that do not change over time, coming years will see the advent of an increasing number of time series of graphs. in this article, we investigate how pattern mining on static graphs can be extended to time series of graphs. in particular, we are considering dynamic graphs with edge insertions and edge deletions over time. we define frequency in this setting and provide algorithmic solutions for finding frequent dynamic subgraph patterns. existing subgraph mining algorithms can be easily integrated into our framework to make them handle dynamic graphs. experimental results on real-world data confirm the practical feasibility of our approach.
mining correlation between motifs and gene expression. one of the major challenges in the post-genomic era is to determine all dna-binding transcription factors (tfs) and their regulatory binding sites (motifs) within the genomes. to discover the relationship between the motifs and changes in gene expression, we propose a new algorithm, co-miner (correlation miner). correlation rules are generated based on the expression profiles of genes with significant expression change through the time course of gene expression. thus, we may consider the change in gene expression to be causatively associated with the transcription binding sites in the upstream sequences. in addition, we introduce partition and constraint pushing techniques to improve the performance and demonstrate their effectiveness by our experiments. by applying co-miner to a yeast dataset, the relationships between motifs and gene expression revealed by co-miner are confirmed in the literature.
intelligent icons: integrating lite-weight data mining and visualization into gui operating systems. the vast majority of visualization tools introduced so far are specialized pieces of software that run explicitly on a particular dataset at a particular time for a particular purpose. in this work we introduce a novel framework for allowing visualization to take place in the background of normal day-to-day operation of any gui based operation system. our system works by replacing the standard file icons with automatically created icons that reflect the contents of the files in a principled way. we call such icons intelligent icons. the utility of intelligent icons is further enhanced by arranging them in a way that reflects their similarity/differences. we demonstrate the utility of our approach on diverse applications.
discover bayesian networks from incomplete data using a hybrid evolutionary algorithm. this paper proposes a novel hybrid approach for learning bayesian networks from incomplete data in the presence of missing values, which combines an evolutionary algorithm with the traditional expectation-maximization (em) algorithm. the new algorithm can overcome the problem of getting stuck in sub-optimal solutions which occurs in most existing learning algorithms. the experimental results on the data sets generated from several benchmark networks illustrate that the new algorithm has better performance than some state-of-the-art algorithms. we also apply the approach to a data set of direct marketing and compare the performance of the discovered bayesian networks obtained by the new algorithm with the networks generated by other methods. in the comparison, the bayesian networks learned by the new algorithm outperform other networks.
who thinks who knows who? socio-cognitive analysis of email networks. interpersonal interaction plays an important role in organizational dynamics, and understanding these interaction networks is a key issue for any organization, since these can be tapped to facilitate various organizational processes. however, the approaches of collecting data about them using surveys/interviews are fraught with problems of scalability, logistics and reporting biases, especially since such surveys may be perceived to be intrusive. widespread use of computer networks for organizational communication provides a unique opportunity to overcome these difficulties and automatically map the organizational networks with a high degree of detail and accuracy. this paper describes an effective and scalable approach for modeling organizational networks by tapping into an organization's email communication. the approach models communication between actors as non-stationary bernoulli trials and bayesian inference is used for estimating model parameters over time. this approach is useful for sociocognitive analysis (who knows who knows who) of organizational communication networks. using this approach, novel measures for analysis of (i) closeness between actors' perceptions about such organizational networks (agreement), (ii) divergence of an actor's perceptions about organizational network from reality (misperception) are explained. using the enron email data, we show that these techniques provide sociologists with a new tool to understand organizational networks.
probabilistic enhanced mapping with the generative tabular model. visualization of the massive datasets needs new methods which are able to quickly and easily reveal their contents. the projection of the data cloud is an interesting paradigm in spite of its difficulty to be explored when data plots are too numerous. so we study a new way to show a bi-dimensional projection from a multidimensional data cloud: our generative model constructs a tabular view of the projected cloud. we are able to show the high densities areas by their non equidistributed discretization. this approach is an alternative to the self-organizing map when a projection does already exist. the resulting pixel views of a dataset are illustrated by projecting a data sample of real images: it becomes possible to observe how are laid out the class labels or the frequencies of a group of modalities without being lost because of a zoom enlarging change for instance. the conclusion gives perspectives to this original promising point of view to get a readable projection for a statistical data analysis of large data samples.
star-structured high-order heterogeneous data co-clustering based on consistent information theory. heterogeneous object co-clustering has become an important research topic in data mining. in early years of this research, people mainly worked on two types of heterogeneous data (denoted by pair-wise co-clustering); while recently more and more attention was paid to multiple types of heterogeneous data (denoted by highorder co-clustering). in this paper, we studied the highorder co-clustering of objects with star-structured interrelationship, i.e., there is a central type of objects that connects the other types of objects. actually, this case could be a very good model for many real-world applications, such as the co-clustering of web images, their low-level visual features, and the surrounding text. we used a tripartite graph to represent the interrelationships among different objects, and proposed a consistent information theory which generates an effective algorithm to obtain the co-clusters of different types of objects. experiments on a web image show that our proposed algorithm is a better choice compared with previous work on heterogeneous object co-clustering.
temporal data mining in dynamic feature spaces. many interesting real-world applications for temporal data mining are hindered by concept drift. one particular form of concept drift is characterized by changes to the underlying feature space. seemingly little has been done in this area. this paper presents fae, an incremental ensemble approach to mining data subject to such concept drift. empirical results on large data streams demonstrate promise.
data mining methods for modeling gene expression regulation and their applications. understanding gene expression regulation at both transcriptional and post-transcriptional levels is critical for elucidation of the mechanism of stress tolerance in plants and important for understanding and diagnosis of human diseases. with the advent of high throughput gene expression profiling techniques, a huge amount of gene expression data on various organisms has been collected. such a wealth of biological data has provided excellent opportunities to elucidating transcriptional regulation mechanisms using machine learning and data mining approaches.
mining for tree-query associations in a graph. new applications of data mining, such as in biology, bioinformatics, or sociology, are faced with large datasets structured as graphs. we present an efficient algorithm for mining associations between tree queries in a large graph. tree queries are powerful tree-shaped patterns featuring existential variables and data constants. our algorithm applies the theory of conjunctive database queries to make the generation of association rules efficient. we propose a practical, database-oriented implementation in sql, and show that the approach works in practice through experiments on data about food webs, protein interactions, and citation analysis.
on the use of structure and sequence-based features for protein classification and retrieval. the need to retrieve or classify proteins using structure or sequence-based similarity underlies many biomedical applications. in drug discovery, researchers search for proteins that share specific chemical properties as sources for new treatment. with folding simulations, similar intermediate structures might be indicative of a common folding pathway. here we present two normalized, stand-alone representations of proteins that enable fast and efficient object retrieval based on sequence or structure. to create our sequence-based representation, we take the profiles returned by the psi-blast alignment algorithm and create a normalized summary using a discrete wavelet transform. for our structural representation, we transform each 3d structure into a normalized 2d distance matrix and apply a 2d wavelet decomposition to generate our descriptor. we also create a hybrid representation by concatenating together the above descriptors. we evaluate the generality of our models by using them as indices for database retrieval experiments as well as feature vectors for classification. we find that our methods provide excellent performance when compared with the state-of-the-art for each task. our results show that the sequence-based representation is generally superior to the structure-based representation and that in the classification context, the hybrid strategy affords a significant improvement over sequence or structure.
a data mining approach for capacity building of stakeholders in integrated flood management. new approaches to managing flood events are increasingly of more relevance due to recent widespread floods and the presumed changes in the climate. these approaches fall under the integrated flood management (ifm) banner and focus not only on flood prevention, but on flood resilience. this paper introduces an application (floreto) for ifm that utilizes the data mining approach, in a web based three tier system, devoted to the capacity building of stakeholders as a micro-scale resilience strategy of ifm. the intelligent models, which constitute the business logic in floreto, are used to match the input parameters or design criteria, describing properties prone to flooding, to technically justifiable flood mitigation measures. datasets from the german city of kellinghusen were collected and intelligent models were built. satisfactory results have been obtained, which shows the promise of this data mining approach and opens the door for its application for ifm in other regions.
opening the black box of feature extraction: incorporating visualization into high-dimensional data mining processes. feature extraction techniques have been used to handle high-dimensional data and experimental studies often show improved classification accuracies. unfortunately very few studies provide concrete evidences on the effectiveness of these feature extraction techniques and they largely remain to be black boxes. in this study, we design and implement a visualization prototype system that allows users to look into the classification processes, explore the links among the original and extracted features in different classifiers, examine why and how an instance is correctly or incorrectly classified. we demonstrate the prototype's capabilities by combining a feature extraction method based on hierarchical feature space clustering with j48 decision tree classifiers and perform experiments on a real hyperspectral remote sensing image dataset.
belief propagation in large, highly connected graphs for 3d part-based object recognition. we describe a part-based object-recognition framework, specialized to mining complex 3d objects from detailed 3d images. objects are modeled as a collection of parts together with a pairwise potential function. an efficient inference algorithm -- based on belief propagation (bp) -- finds the optimal layout of parts, given some input image. we introduce aggbp, a message aggregation scheme for bp, in which groups of messages are approximated as a single message. for objects consisting of n parts, we reduce cpu time and memory requirements from o( n^2 ) to o(n). we apply aggbp on synthetic data as well as a real-world task identifying protein fragments in three-dimensional images. these experiments show that our improvements result in minimal loss in accuracy in significantly less time.
social capital in friendship-event networks. in this paper, we examine a particular form of social network which we call a friendship-event network. a friendship-event network captures both the friendship relationship among a set of actors, and also the organizer and participation relationships of actors in a series of events. within these networks, we formulate the notion of social capital based on the actor-organizer friendship relationship and the notion of benefit, based on event participation. we investigate appropriate definitions for the social capital of both a single actor and a collection of actors. we ground these definitions in a real-world example of academic collaboration networks, where the actors are researchers, the friendships are collaborations, the events are conferences, the organizers are program committee members and the participants are conference authors. we show that our definitions of capital and benefit capture interesting qualitative properties of event series. in addition, we show that social capital is a better publication predictor than publication history.
geometrically inspired itemset mining. in our geometric view, an itemset is a vector (itemvector) in the space of transactions. linear and potentially non-linear transformations can be applied to the itemvectors before mining patterns. aggregation functions and interestingness measures can be applied to the transformed vectors and pushed inside the mining process. we show that interesting itemset mining can be carried out by instantiating four abstract functions: a transformation (g), an algebraic aggregation operator () and measures (f and f). for frequent itemset mining (fim), g and f are identity transformations,is intersection and f is the cardinality. based on this geometric view we present a novel algorithm that uses space linear in the number of 1-itemsets to mine all interesting itemsets in a single pass over the data, with no candidate generation. it scales (roughly) linearly in running time with the number of interesting itemsets. fim experiments show that it outperforms fpgrowth on realistic datasets above a small support threshold (0.29% and 1.2% in our experiments) .
finding "who is talking to whom" in voip networks via progressive stream clustering. technologies that use the internet network to deliver voice communications have the potential to reduce costs and improve access to communications services around the world. however, these new technologies pose several challenges in terms of confidentiality of the conversations and anonymity of the conversing parties. call authentication and encryption techniques provide a way to protect confidentiality, while anonymity is typically preserved by an anonymizing service (anonymous call). this work studies the feasibility of revealing pairs of anonymous and encrypted conversing parties (caller/callee pair of streams) by exploiting the vulnerabilities inherent to voip systems. in particular, by exploiting the aperiodic inter-departure time of voip packets, we can trivialize each voip stream into a binary time-series. we first define a simple yet intuitive metric to gauge the correlation between two voip binary streams. then we propose an effective technique that progressively pairs conversing parties with high accuracy and in a limited amount of time. our metric and method are justified analytically and validated by experiments on a very large standard corpus of conversational speech. we obtain impressively high pairing accuracy that reaches 97% after 5 minutes of voice conversations.
a novel method for detecting outlying subspaces in high-dimensional databases using genetic algorithm. detecting outlying subspaces is a relatively new research problem in outlier-ness analysis for high-dimensional data. an outlying subspace for a given data point p is the subspace in which p is an outlier. outlying subspace detection can facilitate a better characterization process for the detected outliers. it can also enable outlier mining for highdimensional data to be performed more accurately and efficiently. in this paper, we proposed a new method using genetic algorithm paradigm for searching outlying subspaces efficiently. we developed a technique for efficiently computing the lower and upper bounds of the distance between a given point and its kth nearest neighbor in each possible subspace. these bounds are used to speed up the fitness evaluation of the designed genetic algorithm for outlying subspace detection. we also proposed a random sampling technique to further reduce the computation of the genetic algorithm. the optimal number of sampling data is specified to ensure the accuracy of the result. we show that the proposed method is efficient and effective in handling outlying subspace detection problem by a set of experiments conducted on both synthetic and real-life datasets.
query-sensitive similarity measure for content-based image retrieval. similarity measure is one of the keys of a high-performance content-based image retrieval (cbir) system. given a pair of images, existing similarity measures usually produce a static and constant similarity score. however, an image can usually be perceived with different meanings and therefore, the similarity between the same pair of images may change when the concept being queried changes. this paper proposes a query-sensitive similarity measure, qsim, which takes the concept being queried into account in measuring image similarities, by exploiting the query image as well as the images labeled by user in the relevance feedback process. experimental comparisons to state-of-the-art techniques show that qsim has superior performance.
forecasting skewed biased stochastic ozone days: analyses and solutions. much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. recently, we have been approached by texas commission on environmental quality (tceq) to help them build highly accurate ozone level alarm forecasting models for the houston area, where these technical difficulties come together in one single problem. key characteristics of this problem that are challenging and interesting include: 1) the dataset is sparse (72 features, and 2% or 5% positives depending on the criteria of "ozone days"), 2) evolving over time from year to year, 3) limited in collected data size (7 years or around 2500 data entries), 4) contains a large number of irrelevant features, 5) is biased in terms of "sample selection bias", and 6) the true model is stochastic as a function of measurable factors. besides solving a difficult application problem, this dataset offers a unique opportunity to explore new and existing data mining techniques, and to provide experience and guidance for similar problems. our main technical focus addresses on how to estimate reliable probability given both sample selection bias and a large number of irrelevant features, and how to choose the most reliable decision threshold to predict the unknown future with different distribution. on the application side, the prediction accuracy of our approach is 20% higher in recall (correctly detects 1 to 3 more ozone days, depending on the year) and 10% higher in precision (15 to 30 fewer false alarm days per year) than state-of-the-art methods used by air quality control scientists, and these results are significant for tceq.
multi-tier granule mining for representations of multidimensional association rules. it is a big challenge to promise the quality of multidimensional association mining. the essential issue is how to represent meaningful multidimensional association rules efficiently. currently we have not found satisfactory approaches for solving this challenge because of the complicated correlation between attributes. multi-tier granule mining is an initiative for solving this challenging issue. it divides attributes into some tiers and then compresses the large multidimensional database into granules at each tier. it also builds association mappings to illustrate the correlation between tiers. in this way, the meaningful association rules can be justified according to these association mappings.
incremental mining of frequent query patterns from xml queries for caching. existing studies for mining frequent xml query patterns mainly introduce a straightforward candidate generate-and-test strategy and compute frequencies of candidate query patterns from scratch periodically by checking the entire transaction database, which consists of xml query patterns transformed from user queries. however, it is nontrivial to maintain such discovered frequent patterns in real xml databases because there may incur frequent updates that may not only invalidate some existing frequent query patterns but also generate some new frequent ones. accordingly, existing proposals are inefficient for the evolution of the transaction database. to address these problems, this paper presents an efficient algorithm ips-fxqpminer for mining frequent xml query patterns without candidate maintenance and costly tree-containment checking. we transform xml queries into sequences through a oneto- one mapping and then mine the frequent sequences to generate frequent xml query patterns. more importantly, based on ips-fxqpminer, an efficient incremental algorithm, incre-fxqpminer is proposed to incrementally mine frequent xml query patterns, which can minimize the i/o and computation requirements for handling incremental updates. our experimental study on various real-life datasets demonstrates the efficiency and scalability of our algorithms over previous known alternatives.
delta-tolerance closed frequent itemsets. in this paper, we study an inherent problem of mining frequent itemsets (fis): the number of fis mined is often too large. the large number of fis not only affects the mining performance, but also severely thwarts the application of fi mining. in the literature, closed fis (cfis) and maximal fis (mfis) are proposed as concise representations of fis. however, the number of cfis is still too large in many cases, while mfis lose information about the frequency of the fis. to address this problem, we relax the restrictive definition of cfis and propose the \delta-tolerance cfis (\delta- tcfis). mining \delta-tcfis recursively removes all subsets of a \delta-tcfi that fall within a frequency distance bounded by \delta. we propose two algorithms, cfi2tcfi and minetcfi, to mine \delta-tcfis. cfi2tcfi achieves very high accuracy on the estimated frequency of the recovered fis but is less efficient when the number of cfis is large, since it is based on cfi mining. minetcfi is significantly faster and consumes less memory than the algorithms of the state-of-the-art concise representations of fis, while the accuracy of minetcfi is only slightly lower than that of cfi2tcfi.
data mining approaches to criminal career analysis. narrative reports and criminal records are stored digitally across individual police departments, enabling the collection of this data to compile a nation-wide database of criminals and the crimes they committed. the compilation of this data through the last years presents new possibilities of analyzing criminal activity through time. augmenting the traditional, more socially oriented, approach of behavioral study of these criminals and traditional statistics, data mining methods like clustering and prediction enable police forces to get a clearer picture of criminal careers. this allows officers to recognize crucial spots in changing criminal behaviour and deploy resources to prevent these careers from unfolding. four important factors play a role in the analysis of criminal careers: crime nature, frequency, duration and severity. we describe a tool that extracts these from the database and creates digital profiles for all offenders. it compares all individuals on these profiles by a new distance measure and clusters them accordingly. this method yields a visual clustering of these criminal careers and enables the identification of classes of criminals. the proposed method allows for several user-defined parameters.
a novel scalable algorithm for supervised subspace learning. subspace learning approaches aim to discover important statistical distribution on lower dimensions for high dimensional data. methods such as principal component analysis (pca) do not make use of the class information, and linear discriminant analysis (lda) could not be performed efficiently in a scalable way. in this paper, we propose a novel highly scalable supervised subspace learning algorithm called as supervised kampong measure (skm). it assigns data points as close as possible to their corresponding class mean, simultaneously assigns data points to be as far as possible from the other class means in the transformed lower dimensional subspace. theoretical derivation shows that our algorithm is not limited by the number of classes or the singularity problem faced by lda. furthermore, our algorithm can be executed in an incremental manner in which learning is done in an online fashion as data streams are received. experimental results on several datasets, including a very large text data set rcv1, show the outstanding performance of our proposed algorithm on classification problems as compared to pca, lda and a popular feature selection approach, information gain (ig).
constructing ensembles for better ranking. we propose a novel algorithm, rankde, to build an ensemble using an extra artificial dataset. rankde aims at improving the overall ranking performance, which is crucial in many machine learning applications. this algorithm constructs artificial datasets that are diverse with the current training dataset in terms of ranking. we conduct experiments with real-world data sets to compare rankde with some traditional and state-of-the-art ensembling algorithms of bagging, adaboost, decorate and rankboost in terms of ranking. the experiments showthat rankdeoutperforms bagging, decorate, adaboost, and rankboost when limited data is available. when enough training data is available, it is competitive with decorate and adaboost
graphrank: statistical modeling and mining of significant subgraphs in the feature space. we propose a technique for evaluating the statistical significance of frequent subgraphs in a database. a graph is represented by a feature vector that is a histogram over a set of basis elements. the set of basis elements is chosen based on domain knowledge and consists generally of vertices, edges, or small graphs. a given subgraph is transformed to a feature vector and the significance of the subgraph is computed by considering the significance of occurrence of the corresponding vector. the probability of occurrence of the vector in a random vector is computed based on the prior probability of the basis elements. this is then used to obtain a probability distribution on the support of the vector in a database of random vectors. the statistical significance of the vector/subgraph is then defined as the p-value of its observed support. we develop efficient methods for computing p-values and lower bounds. a simplified model is further proposed to improve the efficiency. we also address the problem of feature vector mining, a generalization of itemset mining where counts are associated with items and the goal is to find significant sub-vectors. we present an algorithm that explores closed frequent sub-vectors to find significant ones. experimental results show that the proposed techniques are effective, efficient, and useful for ranking frequent subgraphs by their statistical significance.
diverse topic phrase extraction through latent semantic analysis. we propose a novel algorithm for extracting diverse topic phrases in order to provide summary for large corpora. previous works often ignore the importance of diversity and thus extract phrases crowded on some hot topics while failing to cover other less obvious but important topics. we solve this problem through document re-weighting and phrase diversification by using latent semantic analysis (lsa). experiments on various datasets show that our new algorithm can improve relevance as well as diversity over different topics for topic phrase extraction problems.
secure distributed k-anonymous pattern mining. privacy-preserving data mining is an important area that studies privacy issues of data mining. when the goal is to share data mining results, two privacy-related problems may arise. the first one is how to compute the data-mining results among several parties without sharing the data. cryptography-based primitives are the basic tool used to develop ad-hoc secure multi-party computation protocols that share information as less as possible during the computation under different adversary models. the second one is how to produce data mining results that provably do not contain threats to the anonymity of individuals. the concept of k-anonymity has been used to discover anonymity-preserving frequent patterns, and centralized algorithms have been developed. in this paper and for the first time, we study how to produce anonymity-preserving data mining results in a distributed environment. we present two privacy-preserving strategies and show their feasibility through experimental analysis.
a balanced ensemble approach to weighting classifiers for text classification. this paper studies the problem of constructing an effective heterogeneous ensemble classifier for text classification. one major challenge of this problem is to formulate a good combination function, which combines the decisions of the individual classifiers in the ensemble. we show that the classification performance is affected by three weight components and they should be included in deriving an effective combination function. they are: (1) global effectiveness, which measures the effectiveness of a member classifier in classifying a set of unseen documents; (2) local effectiveness, which measures the effectiveness of a member classifier in classifying the particular domain of an unseen document; and (3) decision confidence, which describes how confident a classifier is when making a decision when classifying a specific unseen document. we propose a new balanced combination function, called dynamic classifier weighting (dcw), that incorporates the afore-mentioned three components. the empirical study demonstrates that the new combination function is highly effective for text classification.
stagger: periodicity mining of data streams using expanding sliding windows. sensor devices are becoming ubiquitous, especially in measurement and monitoring applications. because of the real-time, append-only and semi-infinite natures of the generated sensor data streams, an online incremental approach is a necessity for mining stream data types. in this paper, we propose stagger: a one-pass, online and incremental algorithm for mining periodic patterns in data streams. stagger does not require that the user pre-specify the periodicity rate of the data. instead, stagger discovers the potential periodicity rates. stagger maintains multiple expanding sliding windows staggered over the stream, where computations are shared among the multiple overlapping windows. small-length sliding windows are imperative for early and real-time output, yet are limited to discover short periodicity rates. as streamed data arrives continuously, the sliding windows expand in length in order to cover the whole stream. larger-length sliding windows are able to discover longer periodicity rates. stagger incrementally maintains a tree-like data structure for the frequent periodic patterns of each discovered potential periodicity rate. in contrast to the fourier/wavelet-based approaches used for discovering periodicity rates, stagger not only discovers a wider, more accurate set of periodicities, but also discovers the periodic patterns themselves. in fact, experimental results with real and synthetic data sets show that stagger outperforms fourier/wavelet-based approaches by an order of magnitude in terms of the accuracy of the discovered periodicity rates. moreover, realdata experiments demonstrate the practicality of the discovered periodic patterns.
semi-supervised kernel regression. insufficiency of training data is a major obstacle in machine learning and data mining applications. many different semi-supervised learning algorithms have been proposed to tackle this difficulty by leveraging a large amount of unlabeled data. however, most of them focus on semi-supervised classification. in this paper we propose a semi-supervised regression algorithm named semi-supervised kernel regression (sskr). while classical kernel regression is only based on labeled examples, our approach extends it to all observed examples using a weighting factor to modulate the effect of unlabeled examples. experimental results prove that sskr significantly outperforms traditional kernel regression and graph-based semi-supervised regression methods.
using an ensemble of one-class svm classifiers to harden payload-based anomaly detection systems. unsupervised or unlabeled learning approaches for network anomaly detection have been recently proposed. in particular, recent work on unlabeled anomaly detection focused on high speed classification based on simple payload statistics. for example, payl, an anomaly ids, measures the occurrence frequency in the payload of n-grams. a simple model of normal traffic is then constructed according to this description of the packets' content. it has been demonstrated that anomaly detectors based on payload statistics can be "evaded" by mimicry attacks using byte substitution and padding techniques. in this paper we propose a new approach to construct high speed payload-based anomaly ids intended to be accurate and hard to evade. we propose a new technique to extract the features from the payload. we use a feature clustering algorithm originally proposed for text classification problems to reduce the dimensionality of the feature space. accuracy and hardness of evasion are obtained by constructing our anomaly-based ids using an ensemble of one-class svm classifiers that work on different feature spaces.
mining maximal quasi-bicliques to co-cluster stocks and financial ratios for value investment. we introduce an unsupervised process to co-cluster groups of stocks and financial ratios, so that investors can gain more insight on how they are correlated. our idea for the co-clustering is based on a graph concept called maximal quasi-bicliques, which can tolerate erroneous or/and missing information that are common in the stock and financial ratio data. compared to previous works, our maximal quasi-bicliques require the errors to be evenly distributed, which enable us to capture more meaningful co-clusters. we develop a new algorithm that can efficiently enumerate maximal quasi-bicliques from an undirected graph. the concept of maximal quasi-bicliques is domain-independent; it can be extended to perform co-clustering on any set of data that are modeled by graphs.
cosmic: conceptually specified multi-instance clusters. recently, more and more applications represent data objects as sets of feature vectors or multi-instance objects. in this paper, we propose cosmic, a method for deriving concept lattices from multi-instance data based on hierarchical density-based clustering. the found concepts correspond to groups or clusters of multi-instance objects having similar instances in common. we demonstrate that cosmic outperforms compared methods with respect to efficiency and cluster quality and is capable to extract interesting patterns in multi-instance data sets.
a feature selection and evaluation scheme for computer virus detection. anti-virus systems traditionally use signatures to detect malicious executables, but signatures are over-fitted features that are of little use in machine learning. other more heuristic methods seek to utilize more general features, with some degree of success. in this paper, we present a data mining approach that conducts an exhaustive feature search on a set of computer viruses and strives to obviate over-fitting. we also evaluate the predictive power of a classifier by taking into account dependence relationships that exist between viruses, and we show that our classifier yields high detection rates and can be expected to perform as well in real-world conditions.
discovering partial orders in binary data. we approach the problem of discovering interesting orders in data. in many applications, it is more important to find interesting partial orders since there is often no clear ordering between certain sets of elements. furthermore, a partial order is more robust against partially erroneous data. we present the notion of fundamental partial orders (fpo), and argue that any partial order that satisfies this property is an interesting partial order. to mine such partial orders, we present a two-stage methodology that first finds an interesting total order, and then discovers a partial order satisfying fpo using this total order. to illustrate, we focus on {0, 1} data. this is an important problem with many applications, e.g., in paleontology, where we chronologically order fossil sites by minimizing lazarus counts. we present the experimental results of our method on paleontological data, and show that it outperforms existing approaches. the techniques developed here are general and can be abstracted for mining partial orders in any setting.
biclustering protein complex interactions with a biclique finding algorithm. biclustering has many applications in text mining, web clickstream mining, and bioinformatics. when data entries are binary, the tightest biclusters become bicliques. we propose a flexible and highly efficient algorithm to compute bicliques. we first generalize the motzkin-straus formalism for computing the maximal clique from l_1 constraint to l_p constraint, which enables us to provide a generalized motzkin-straus formalism for computing maximal-edge bicliques. by adjusting parameters, the algorithm can favor biclusters with more rows less columns, or vice verse, thus increasing the flexibility of the targeted biclusters. we then propose an algorithmto solve the generalized motzkin- straus optimization problem. the algorithm is provably convergent and has a computational complexity of o(|e|) where |e| is the number of edges. using this algorithm, we bicluster the yeast protein complex interaction network. we find that biclustering protein complexes at the protein level does not clearly reflect the functional linkage among protein complexes in many cases, while biclustering at protein domain level can reveal many underlying linkages. we show several new biologically significant results.
entity resolution with markov logic. entity resolution is the problem of determining which records in a database refer to the same entities, and is a crucial and expensive step in the data mining process. interest in it has grown rapidly in recent years, and many approaches have been proposed. however, they tend to address only isolated aspects of the problem, and are often ad hoc. this paper proposes a well-founded, integrated solution to the entity resolution problem based on markov logic. markov logic combines first-order logic and probabilistic graphical models by attaching weights to first-order formulas, and viewing them as templates for features of markov networks. we show how a number of previous approaches can be formulated and seamlessly combined in markov logic, and how the resulting learning and inference problems can be solved efficiently. experiments on two citation databases show the utility of this approach, and evaluate the contribution of the different components.
global and componentwise extrapolation for accelerating data mining from large incomplete data sets with the em algorithm. the expectation-maximization (em) algorithm is one of the most popular algorithms for data mining from incomplete data. however, when applied to large data sets with a large proportion of missing data, the em algorithm may converge slowly. the triple jump extrapolation method can effectively accelerate the em algorithm by substantially reducing the number of iterations required for em to converge. there are two options for the triple jump method, global extrapolation (tjem) and componentwise extrapolation (ctjem). we tried these two methods for a variety of probabilistic models and found that in general, global extraplolation yields a better performance, but there are cases where componentwise extrapolation yields very high speedup. in this paper, we investigate when componentwise extrapolation should be preferred. we conclude that, when the jacobian of the em mapping is diagonal or block diagonal, ctjem should be preferred. we show how to determine whether a jacobian is diagonal or block diagonal and experimentally confirm our claim. in particular, we show that ctjem is especially effective for the semi-supervised bayesian classifier model given a highly sparse data set.
latent dirichlet co-clustering. we present a generative model for simultaneously clustering documents and terms. our model is a four-level hierarchical bayesian model, in which each document is modeled as a random mixture of document topics , where each topic is a distribution over some segments of the text. each of these segments in the document can be modeled as a mixture of word topics where each topic is a distribution over words. we present efficient approximate inference techniques based on markov chain monte carlo method and a moment-matching algorithm for empirical bayes parameter estimation. we report results in document modeling, document and term clustering, comparing to other topic models, clustering and co-clustering algorithms including latent dirichlet allocation (lda), model-based overlapping clustering (moc), model-based overlapping co-clustering (mocc) and information-theoretic co-clustering (itcc).
adaptive parallel graph mining for cmp architectures. mining graph data is an increasingly popular challenge, which has practical applications in many areas, including molecular substructure discovery, web link analysis, fraud detection, and social network analysis. the problem statement is to enumerate all subgraphs occurring in at least \sigmagraphs of a database, where \sigmais a user specified parameter. chip multiprocessors (cmps) provide true parallel processing, and are expected to become the de facto standard for commodity computing. in this work, building on the state-of-the-art, we propose an efficient approach to parallelize such algorithms for cmps. we show that an algorithm which adapts its behavior based on the runtime state of the system can improve system utilization and lower execution times. most notably, we incorporate dynamic state management to allow memory consumption to vary based on availability. we evaluate our techniques on current day shared memory systems (smps) and expect similar performance for cmps. we demonstrate excellent speedup, 27- fold on 32 processors for several real world datasets. additionally, we show our dynamic techniques afford this scalability while consuming up to 35% less memory than static techniques.
co-clustering documents and words using bipartite isoperimetric graph partitioning. in this paper, we present a novel graph theoretic approach to the problem of document-word co-clustering. in our approach, documents and words are modeled as the two vertices of a bipartite graph. we then propose isoperimetric co-clustering algorithm (ica) - a new method for partitioning the document-word bipartite graph. ica requires a simple solution to a sparse system of linear equations instead of the eigenvalue or svd problem in the popular spectral co-clustering approach. our extensive experiments performed on publicly available datasets demonstrate the advantages of ica over spectral approach in terms of the quality, efficiency and stability in partitioning the document-word bipartite graph.
comparison of descriptor spaces for chemical compound retrieval and classification. in recent years the development of computational techniques that build models to correctly assign chemical compounds to various classes or to retrieve potential drug-like compounds has been an active area of research. many of the best-performing techniques for these tasks utilize a descriptor-based representation of the compound that captures various aspects of the underlying molecular graph's topology. in this paper we compare different set of descriptors that are currently used for chemical compound classification. in this process, we also introduce four different descriptors derived from all connected fragments present in the molecular graphs. in addition, we introduce an extension to existing vector-based kernel functions to take into account the length of the fragments present in the descriptors. we experimentally evaluate the performance of the previously introduced and the new descriptors in the context of svm-based classification and ranked-retrieval on 28 classification and retrieval problems derived from 18 datasets. our experiments show that for both these tasks, the new descriptors consistently and statistically outperform previously developed schemes based on the widely used fingerprint- and maccs keys-based descriptors, as well as recently introduced descriptors obtained by mining and analyzing the structure of the molecular graphs.
cluster based core vector machine. core vector machine(cvm) is suitable for efficient large-scale pattern classification. in this paper, a method for improving the performance of cvm with gaussian kernel function irrespective of the orderings of patterns belonging to different classes within the data set is proposed. this method employs a selective sampling based training of cvm using a novel kernel based scalable hierarchical clustering algorithm. empirical studies made on synthetic and real world data sets show that the proposed strategy performs well on large data sets.
efficient clustering of uncertain data. we study the problem of clustering data objects whose locations are uncertain. a data object is represented by an uncertainty region over which a probability density function (pdf) is defined. one method to cluster uncertain objects of this sort is to apply the uk-means algorithm, which is based on the traditional k-means algorithm. in uk-means, an object is assigned to the cluster whose representative has the smallest expected distance to the object. for arbitrary pdf, calculating the expected distance between an object and a cluster representative requires expensive integration computation. we study various pruning methods to avoid such expensive expected distance calculation.
relational ensemble classification. relational classification aims at including relations among entities, for example taking relations between documents such as a common author or citations into account. however, considering more than one relation can further improve classification accuracy. in this paper we introduce a new approach to make use of several relations as well as both relations and attributes for classification using ensemble methods. to accomplish this, we present a generic relational ensemble model, that can use different relational and local classifiers as components. furthermore, we discuss solutions for several problems concerning relational data such as heterogeneity, sparsity, and multiple relations. finally, we provide empirical evidence, that our relational ensemble methods outperform existing relational classification methods, even rather complex models such as relational probability trees (rpts), relational dependency networks (rdns) and relational bayesian classifiers (rbcs).
detection of interdomain routing anomalies based on higher-order path analysis. anomalous interdomain border gateway protocol (bgp) events including misconfigurations, attacks and large-scale power failures often affect the global routing infrastructure. thus, the ability to detect and categorize such events is extremely useful. in this article we present a novel anomaly detection technique for bgp that distinguishes between different anomalies in bgp traffic. this technique is termed higher order path analysis (hopa) and focuses on the discovery of patterns in higher order paths in supervised learning datasets. our results demonstrate that not only worm events but also different types of worms as well as blackout events are cleanly separable and can be classified in real time based on our incremental approach. this novel approach to supervised learning has potential applications in cybersecurity/forensics and text/data mining in general.
discovery of collocation episodes in spatiotemporal data. given a collection of trajectories of moving objects with different types (e.g., pumas, deers, vultures, etc.), we introduce the problem of discovering collocation episodes in them (e.g., if a puma is moving near a deer, then a vulture is also going to move close to the same deer with high probability within the next 3 minutes). collocation episodes catch the inter-movement regularities among different types of objects. we formally define the problem of mining collocation episodes and propose two scaleable algorithms for its efficient solution. we empirically evaluate the performance of the proposed methods using synthetically generated data that emulate real-world object movements.
linear and non-linear dimensional reduction via class representatives for text classification. we address the problem of building fast and effective text classification tools. we describe a "representatives methodology" related to feature extraction and illustrate its performance using as vehicles a centroid based method and a method based on clustered lsi that were recently proposed as useful tools for low rank matrix approximation and cost effective alternatives to lsi. the methodology is very flexible, providing the means for accelerating existing algorithms. it is also combined with kernel techniques to enable the analysis of data for which linear techniques are insufficient. numerous classification examples indicate that the proposed technique is effective and efficient with an overall performance superior than existing linear and nonlinear lsi-based approaches.
comparisons of k-anonymization and randomization schemes under linking attacks. recently k-anonymity has gained popularity as a privacy quantification against linking attacks, in which attackers try to identify a record with values of some identifying attributes. if attacks succeed, the identity of the record will be revealed and potential confidential information contained in other attributes of the record will be disclosed. k-anonymity counters this attack by requiring that each record must be indistinguishable from at least k -1 other records with respect to the identifying attributes. randomization can also be used for protection against linking attacks. in this paper, we compare the performance of k-anonymization and randomization schemes under linking attacks. we present a new privacy definition that can be applied to both k-anonymization and randomization. we compare these two schemes in terms of both utility and risks of privacy disclosure, and we promote to use r-u confidentiality map for such comparisons. we also compare various randomization schemes.
the pdd framework for detecting categories of peculiar data. peculiar data are objects that are relatively few in number and significantly different from the other objects in a data set. in this paper, we propose the pdd framework for detecting multiple categories of peculiar data. this framework provides an extensible set of perspectives for viewing data, currently including viewing data as a set of records, attributes, frequencies, intervals, sequences, or sequences of changes. by using these six views of the data, multiple categories of peculiar data can be detected to reveal different aspects of the data. for each view, the framework provides an extensible set of peculiarity measures to detect outliers and other kinds of peculiar data. the pdd framework has been implemented for oracle and access. experiments are reported for data sets concerning regina weather and nhl hockey.
discovering unrevealed properties of probability estimation trees: on algorithm selection and performance explanation. there has been increasing interest to design better probability estimation trees, or pets, for ranking and probability estimation. capable of generating class membership probabilities, pets have been shown to be highly accurate and flexible for many difficult problems, such as cost-sensitive learning and matching skewed distributions. there are a large number of pet algorithms available, and about ten of them are well-known. this large number provides an advantage, but it also creates confusion in practice. one would ask "given a new dataset, which algorithm to choose and what performance to expect and not to expect? what are the reasons to explain either good or bad performance under different situations?" in this paper, we systematically, for the first time, answer these important questions by conducting a large-scale empirical comparison of five popular pets by examining their auc, mse and error rate "learning curves" (instead of training-test split based cross-validation). using the maximum auc achieved by any of the evaluated probability estimation tree algorithms, we demonstrate that the preference of a probability estimation tree on different evaluation metrics can be accurately characterized by the "signal-noise separability" of the dataset, as well as some other observable statistics of the dataset explained further in the paper. moreover, in order to understand their relative performance, many important and previously unrevealed properties of each pet's mechanism and heuristics are analyzed and evaluated. importantly, a practical guide for choosing the most appropriate pet algorithm given a new data mining problem is provided.
newscats: a news categorization and trading system. newscats is an automated text categorization (atc) prototype using a hand-made thesaurus to forecast intraday stock price trends from information contained in press releases. due to a unique labeling approach and by carefully selecting the appropriate training data news- cats achieves a performance which is clearly superior to other atc prototypes used for stock price trend forecasting. in this paper we describe the architecture, training, and testing of newscats as well as the results of an extensive robustness analysis.
adaptive kernel principal component analysis with unsupervised learning of kernels. choosing an appropriate kernel is one of the key problems in kernel-based methods. most existing kernel selection methods require that the class labels of the training examples are known. in this paper, we propose an adaptive kernel selection method for kernel principal component analysis, which can effectively learn the kernels when the class labels of the training examples are not available. by iteratively optimizing a novel criterion, the proposed method can achieve nonlinear feature extraction and unsupervised kernel learning simultaneously. moreover, a noniterative approximate algorithm is developed. the effectiveness of the proposed algorithms are validated on uci datasets and the coil-20 object recognition database.
rapid identification of column heterogeneity. data quality is a serious concern in every data management application, and a variety of quality measures have been proposed, e.g., accuracy, freshness and completeness, to capture common sources of data quality degradation. we identify and focus attention on a novel measure, column heterogeneity, that seeks to quantify the data quality problems that can arise when merging data from different sources. we identify desiderata that a column heterogeneity measure should intuitively satisfy, and describe our technique to quantify database column heterogeneity based on using a novel combination of cluster entropy and soft clustering. finally, we present detailed experimental results, using diverse data sets of different types, to demonstrate that our approach provides a robust mechanism for identifying and quantifying database column heterogeneity.
accelerating newton optimization for log-linear models through feature redundancy. log-linear models are widely used for labeling feature vectors and graphical models, typically to estimate robust conditional distributions in presence of a large number of potentially redundant features. limited-memory quasi-newton methods like lbfgs or blmvm are optimization workhorses for such applications, and most of the training time is spent computing the objective and gradient for the optimizer. we propose a simple technique to speed up the training optimization by clustering features dynamically, and interleaving the standard optimizer with another, coarse-grained, faster optimizer that uses far fewer variables. experiments with logistic regression training for text classification and conditional random field (crf) training for information extraction show promising speed-ups between 2× and 9× without any systematic or significant degradation in the quality of the estimated models.
recommendation on item graphs. a novel scheme for item-based recommendation is proposed in this paper. in our framework, the items are described by an undirected weighted graph g = (v, e). v is the node set which is identical to the item set, and e is the edge set. associate with each edge e_ij \ine is a weight w_ij \geqslant0, which represents similarity between items i and j. without the loss of generality, we assume that any user's ratings to the items should be sufficiently smooth with respect to the intrinsic structure of the items, i.e., a user should give similar ratings to similar items. a simple algorithm is presented to achieve such a "smooth" solution. encouraging experimental results are provided to show the effectiveness of our method.
direct marketing when there are voluntary buyers. in traditional direct marketing, the implicit assumption is that customers will only purchase the product if they are contacted. in real business environments, however, there are "voluntary buyers," who will still make the purchase in the absence of a contact. while no direct promotion is needed for voluntary buyers, the traditional response-driven paradigm tends to target such customers. this paper presents "influential marketing," targeting only those whose purchase decisions can be positively influenced, i.e. buyers who are non-voluntary. our novel, practical solution to this problem gives promising results.
getting the most out of ensemble selection. we investigate four previously unexplored aspects of ensemble selection, a procedure for building ensembles of classifiers. first we test whether adjusting model predictions to put them on a canonical scale makes the ensembles more effective. second, we explore the performance of ensemble selection when different amounts of data are available for ensemble hillclimbing. third, we quantify the benefit of ensemble selection's ability to optimize to arbitrary metrics. fourth, we study the performance impact of pruning the number of models available for ensemble selection. based on our results we present improved ensemble selection methods that double the benefit of the original method.
the influence of class imbalance on cost-sensitive learning: an empirical study. in real-world applications the number of examples in one class may overwhelm the other class, but the primary interest is usually on the minor class. cost-sensitive learning has been deeded as a good solution to these class-imbalanced tasks, yet it is not clear how does the class-imbalance affect cost-sensitive classifiers. this paper presents an empirical study using 38 data sets, which discloses that class-imbalance often affects the performance of cost-sensitive classifiers: when the misclassification costs are not seriously unequal, cost-sensitive classifiers generally favor natural class distribution although it might be imbalanced; while when misclassification costs are seriously unequal, a balanced class distribution is more favorable.
fast random walk with restart and its applications. how closely related are two nodes in a graph? how to compute this score quickly, on huge, disk-resident, real graphs? random walk with restart (rwr) provides a good relevance score between two nodes in a weighted graph, and it has been successfully used in numerous settings, like automatic captioning of images, generalizations to the "connection subgraphs", personalized pagerank, and many more. however, the straightforward implementations of rwr do not scale for large graphs, requiring either quadratic space and cubic pre-computation time, or slow response time on queries. we propose fast solutions to this problem. the heart of our approach is to exploit two important properties shared by many real graphs: (a) linear correlations and (b) blockwise, community-like structure. we exploit the linearity by using low-rank matrix approximation, and the community structure by graph partitioning, followed by the sherman- morrison lemma for matrix inversion. experimental results on the corel image and the dblp dabasets demonstrate that our proposed methods achieve significant savings over the straightforward implementations: they can save several orders of magnitude in pre-computation and storage cost, and they achieve up to 150x speed up with 90%+ quality preservation.
gradual cube: customize profile on mobile olap. olap is supported by more and more environment as a powerful analysis tool. with the rapid development of mobile and wireless technologies, users wish to enjoy the olap service on these devices. however, there are many issues on mobile olap against the traditional ones, e.g. the transmission bottleneck, unstable network connection, etc. moreover, the mobile device owners have raised increasing requirements to customize the service such as transmitting the data on demand or asap to support their activities. all these challenges provide new chances for olap. in this paper, a new mechanism gradual cube is proposed to face such challenges. it can reduce the transmission data size, provide customized transmission strategy and enable users to conduct off-line browsing. we assume the users' precision requirement follows some distribution so that three methods, namely random, optimal and heuristic, are developed to customize the transmission plan. the experiments show that such methods are both effective and efficient.
boosting kernel models for regression. this paper proposes a general boosting framework for combining multiple kernel models in the context of both classification and regression problems. our main approach is built on the idea of gradient boosting together with a new regularization scheme and aims at reducing the cubic com- plexity of training kernel models. we focus mainly on using the proposed boosting framework to combine kernel ridge regression (krr) models for regression tasks. numerical experiments on four large-scale data sets have shown that boosting multiple small krr models is superior to training a single large krr model on both improving generalization performance and reducing computational requirements.
on the lower bound of local optimums in k-means algorithm. the k-means algorithm is a popular clustering method used in many different fields of computer science, such as data mining, machine learning and information retrieval. however, the k-means algorithm is very likely to converge to some local optimum which is much worse than the desired global optimal solution. to overcome this problem, current k-means algorithm and its variants usually run many times with different initial centers to avoid being trapped in local optimums that are of unacceptable quality. in this paper, we propose an efficient method to compute a lower bound on the cost of the local optimum from the current center set. after every k-means iteration, k-means algorithm can halt the procedure if the lower bound of the cost at the future local optimum is worse than the best solution that has already been computed so far. although such a lower bound computation incurs some extra time consumption in the iterations, extensive experiments on both synthetic and real data sets show that this method can greatly prune the unnecessary iterations and improve the efficiency of the algorithm in most of the data sets, especially with high dimensionality and large k.
dimension reduction for supervised ordering. ordered lists of objects are widely used as representational forms. such ordered objects include web search results and best-seller lists. techniques for processing such ordinal data are being developed, particularly methods for a supervised ordering task: i.e., learning functions used to sort objects from sample orders. in this article, we propose two dimension reduction methods specifically designed to improve prediction performance in a supervised ordering task.
boosting for learning multiple classes with imbalanced class distribution. classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which assume a relatively balanced class distribution and equal misclassification costs. this learning difficulty attracts a lot of research interests. most efforts concentrate on bi-class problems. however, bi-class is not the only scenario where the class imbalance problem prevails. reported solutions for bi-class applications are not applicable to multi-class problems. in this paper, we develop a cost-sensitive boosting algorithm to improve the classification performance of imbalanced data involving multiple classes. one barrier of applying the cost-sensitive boosting algorithm to the imbalanced data is that the cost matrix is often unavailable for a problem domain. to solve this problem, we apply genetic algorithm to search the optimum cost setup of each class. empirical tests show that the proposed cost-sensitive boosting algorithm improves the classification performances of imbalanced data sets significantly.
bitspade: a lattice-based sequential pattern mining algorithm using bitmap representation. sequential pattern mining allows to discover temporal relationship between items within a database. the patterns can then be used to generate association rules. when the databases are very large, the execution speed and the memory usage of the mining algorithm become critical parameters. previous research has focused on either one of the two parameters. in this paper, we present bitspade, a novel algorithm that combines the best features of spam, one of the fastest algorithm, and spade, one of the most memory efficient algorithm. moreover, we introduce a new pruning strategy that enables bitspade to reach high performances. experimental evaluations showed that bitspade ensures an efficient tradeoff between speed and memory usage by outperforming spade by both speed and memory usage factors more than 3.4 and spam by a memory consumption factor up to more than an order of magnitude.
fast relevance discovery in time series. in this paper, we propose to model time series from a new angle: state transition points. when fluctuation of values in a time series crosses a certain point, it may trigger state transition in the system, which may lead to abrupt changes in many other time series. the concept of state transition points is essential in understanding the behavior of the time series and the behavior of the system. the new measure is robust and is capable of discovering correlations that pearson's coefficient cannot reveal. we propose efficient algorithms to identify state transition points and to compute correlation between two time series. we also introduce some triangular inequalities to efficiently find highly correlated time series among many time series.
cluster ranking with an application to mining mailbox networks. we initiate the study of a new clustering framework, called cluster ranking. rather than simply partitioning a network into clusters, a cluster ranking algorithm also orders the clusters by their strength. to this end, we introduce a novel strength measure for clusters&#x2014;the integrated cohesion&#x2014;which is applicable to arbitrary weighted networks. we then present a new cluster ranking algorithm, called c-rank. we provide extensive theoretical and empirical analysis of c-rank and show that it is likely to have high precision and recall. a main component of c-rank is a heuristic algorithm for finding sparse vertex separators. at the core of this algorithm is a new connection between vertex betweenness and multicommodity flow. our experiments focus on mining mailbox networks. a mailbox network is an egocentric social network, consisting of contacts with whom an individual exchanges email. edges between contacts represent the frequency of their co&#x2013;occurrence on message headers. c-rank is well suited to mine such networks, since they are abundant with overlapping communities of highly variable strengths. we demonstrate the effectiveness of c-rank on the enron data set, consisting of 130 mailbox networks.
window-based tensor analysis on high-dimensional and multi-aspect streams. data stream values are often associated with multiple aspects. for example, each value from environmental sensors may have an associated type (e.g., temperature, humidity, etc) as well as location. aside from timestamp, type and location are the two additional aspects. how to model such streams? how to simultaneously find patterns within and across the multiple aspects? how to do it incrementally in a streaming fashion? in this paper, all these problems are addressed through a general data model, tensor streams, and an effective algorithmic framework, window-based tensor analysis (wta). two variations of wta, independent-window tensor analysis (iw) and moving-window tensor analysis (mw), are presented and evaluated extensively on real datasets. finally, we illustrate one important application, multi-aspect correlation analysis (maca), which uses wta and we demonstrate its effectiveness on an environmental monitoring application.
p3c: a robust projected clustering algorithm. projected clustering has emerged as a possible solution to the challenges associated with clustering in high dimensional data. a projected cluster is a subset of points together with a subset of attributes, such that the cluster points project onto a small range of values in each of these attributes, and are uniformly distributed in the remaining attributes. existing algorithms for projected clustering rely on parameters whose appropriate values are difficult to set by the user, or are unable to identify projected clusters with few relevant attributes. in this paper, we present a robust algorithm for projected clustering that can effectively discover projected clusters in the data while minimizing the number of parameters required as input. in contrast to all previous approaches, our algorithm can discover, under very general conditions, the true number of projected clusters. we show through an extensive experimental evaluation that our algorithm: (1) significantly outperforms existing algorithms for projected clustering in terms of accuracy; (2) is effective in detecting very low-dimensional projected clusters embedded in high dimensional spaces; (3) is effective in detecting clusters with varying orientation in their relevant subspaces; (4) is scalable with respect to large data sets and high number of dimensions.
on trajectory representation for scientific features. in this article, we present trajectory representation algorithms for tangible features found in temporally varying scientific datasets. rather than modeling the features as points, we take attributes like shape and extent of the feature into account. our contention is that these attributes play an important role in understanding the temporal evolution and interactions among features. the proposed representation scheme is based on motion and shape parameters including linear velocity, angular velocity, etc. we use these parameters to segment the trajectory instead of relying on the geometry of the trajectory. we evaluate our algorithms on real datasets originating from different domains. we show the accuracy of the motion and shape parameter estimation by reconstructing the trajectories with high accuracy. finally, we present performance and scalability results.
exploratory under-sampling for class-imbalance learning. under-sampling is a class-imbalance learning method which uses only a subset of major class examples and thus is very efficient. the main deficiency is that many major class examples are ignored. we propose two algorithms to overcome the deficiency. easyensemble samples several subsets from the major class, trains a learner using each of them, and combines the outputs of those learners. balancecascade is similar to easyensemble except that it removes correctly classified major class examples of trained learners from further consideration. experiments show that both of the proposed algorithms have better auc scores than many existing class-imbalance learning methods. moreover, they have approximately the same training time as that of under-sampling, which trains significantly faster than other methods.
searching for pattern rules. we address the problem of finding a set of pattern rules, from a transaction dataset given a statistical metric. a new data structure, called an incrementally counting suffix tree (icst), is proposed for online computation of estimates of the support of any pattern or itemset. using an icst, our approach directly generates a set of pattern rules by a single scan of the whole dataset in partitions without the generation of frequent itemsets. non-redundant rules can be found by removing redundancies from the pattern rules. the ppmcr algorithm first finds pattern rules and then non-redundant rules by generating valid candidates while traversing the icst. experimental results show that the ppmcr algorithm can be used for efficiently mining fewer non-redundant rules.
dstree: a tree structure for the mining of frequent sets from data streams. with advances in technology, a flood of data can be produced in many applications such as sensor networks and web click streams. this calls for efficient techniques for extracting useful information from streams of data. in this paper, we propose a novel tree structure, called dstree (data stream tree), that captures important data from the streams. by exploiting its nice properties, the dstree can be easily maintained andmined for frequent itemsets as well as various other patterns like constrained itemsets.
decision trees for functional variables. classification problems with functionally structured in- put variables arise naturally in many applications. in a clinical domain, for example, input variables could include a time series of blood pressure measurements. in a financial setting, different time series of stock returns might serve as predictors. in an archaeological application, the 2-d pro- file of an artifact may serve as a key input variable. in such domains, accuracy of the classifier is not the only reason- able goal to strive for; classifiers that provide easily inter- pretable results are also of value. in this work, we present an intuitive scheme for extending decision trees to handle functional input variables. our results show that such deci- sion trees are both accurate and readily interpretable.
trias - an algorithm for mining iceberg tri-lattices. in this paper, we present the foundations for mining frequent tri-concepts, which extend the notion of closed itemsets to three-dimensional data to allow for mining folk-sonomies. we provide a formal definition of the problem, and present an efficient algorithm for its solution as well as experimental results on a large real-world example.
ac-close: efficiently mining approximate closed itemsets by core pattern recovery. recent studies have proposed methods to discover approximate frequent itemsets in the presence of random noise. by relaxing the rigid requirement of exact frequent pattern mining, some interesting patterns, which would previously be fragmented by exact pattern mining methods due to the random noise or measurement error, are successfully recovered. unfortunately, a large number of "uninteresting" candidates are explored as well during the mining process, as a result of the relaxed pattern mining methodology. this severely slows down the mining process. even worse, it is hard for an end user to distinguish the recovered interesting patterns from these uninteresting ones. in this paper, we propose an efficient algorithm ac-close to recover the approximate closed itemsets from "core patterns". by focusing on the so-called core patterns, integrated with a top-down mining and several effective pruning strategies, the algorithm narrows down the search space to those potentially interesting ones. experimental results show that ac-close substantially outperforms the previously proposed method in terms of efficiency, while delivers a similar set of interesting recovered patterns.
subjectivity categorization of weblog with part-of-speech based smoothing. experts from different domains try to mine users' comments on weblogs for different reasons such as politics or commerce. all these needs necessitate automatically distinguishing subjective weblog contents from objective ones, namely subjectivity categorization. since weblogs contain various topics from different domains, limited training data can hardly cover all the topics and "unseen words" becomes a serious problem for categorization tasks. in this paper, part-of-speech (pos) based smoothing is proposed to alleviate the "unseen words" problem. in conjunction with a naïve bayes model constructed from limited training data, the probability of an unseen word in a new domain can be well smoothed by the probability of its pos result. empirical studies on five datasets show that our approach consistently outperforms the basic naïve bayes with laplace smoothing. in a cross-domain experiment, our approach achieves 22.0% improvement in macro f1 and 24.4% in micro f1 over basic naïve bayes. these verify that pos based smoothing can indeed benefit subjectivity categorization, especially in the cases with a large number of unseen words.
what is the dimension of your binary data? many 0/1 datasets have a very large number of variables; however, they are sparse and the dependency structure of the variables is simpler than the number of variables would suggest. defining the effective dimensionality of such a dataset is a nontrivial problem. we consider the problem of defining a robust measure of dimension for 0/1 datasets, and show that the basic idea of fractal dimension can be adapted for binary data. however, as such the fractal dimension is difficult to interpret. hence we introduce the concept of normalized fractal dimension. for a dataset d, its normalized fractal dimension counts the number of independent columns needed to achieve the unnormalized fractal dimension of d. the normalized fractal dimension measures the degree of dependency structure of the data. we study the properties of the normalized fractal dimension and discuss its computation. we give empirical results on the normalized fractal dimension, comparing it against pca.
entropy-based concept shift detection. when monitoring sensory data (e.g., from a wearable device) the context oftentimes changes abruptly: people move from one situation (e.g., working quietly in their office) to another (e.g., being interrupted by one's manager). these context changes can be treated like concept shifts, since the underlying data generator (the concept) changes while moving from one context situation to another. we present an entropy based measure for data streams that is suitable to detect concept shifts in a reliable, noise-resistant, fast, and computationally efficient way. we assess the entropy measure under different concept shift conditions. to support our claims we illustrate the concept shift behavior of the stream entropy. we also present a simple algorithm control approach to show how useful and reliable the information obtained by the entropy measure is compared to a ensemble learner as well as an experimentally inferred upper limit. our analysis is based on three large synthetic data sets representing real, virtual, and a combination of both concept drifts under different noise conditions (up to 50%). last but not least, we demonstrate the usefulness of the entropy based measure context switch indication in a real world application in the context-awareness/wearable computing domain.
improving personalization solutions through optimal segmentation of customer bases. on the web, where the search costs are low and the competition is just a mouse click away, it is crucial to segment the customers intelligently in order to offer more personalized products and services to them. traditionally, customer segmentation is achieved using statistics-based methods that compute a set of statistics from the customer data and group customers into segments by applying distance-based clustering algorithms in the space of these statistics. in this paper, we present a direct grouping based approach to computing customer segments that groups customers in terms of optimally combining transactional data of several customers to build a predictive model of customer behavior for each group. we consider customer segmentation as a combinatorial optimization problem of finding the best partitioning of the customer base into disjoint groups and show that finding an optimal customer partition is np-hard. we propose several suboptimal direct grouping segmentation methods, empirically compares them against traditional statistics-based hierarchical and affinity propagation based segmentation, and 1-to-1 methods across multiple experimental conditions. we show that the best direct grouping method builds mostly small sized customer segments and significantly dominates the statistics-based and 1-to-1 approaches across most of the experimental conditions, while still being computationally tractable.
a framework for regional association rule mining in spatial datasets. the immense explosion of geographically referenced data calls for efficient discovery of spatial knowledge. one of the special challenges for spatial data mining is that information is usually not uniformly distributed in spatial datasets. consequently, the discovery of regional knowledge is of fundamental importance for spatial data mining. this paper centers on discovering regional association rules in spatial datasets. in particular, we introduce a novel framework to mine regional association rules relying on a given class structure. a reward-based regional discovery methodology is introduced, and a divisive, grid-based supervised clustering algorithm is presented that identifies interesting subregions in spatial datasets. then, an integrated approach is discussed to systematically mine regional rules. the proposed framework is evaluated in a real-world case study that identifies spatial risk patterns from arsenic in the texas water supply.
mining complex time-series data by learning markovian models. in this paper, we propose a novel and general approach for time-series data mining. as an alternative to traditional ways of designing specific algorithm to mine certain kind of pattern directly from the data, our approach extracts the temporal structure of the time-series data by learning markovian models, and then uses well established methods to efficiently mine a wide variety of patterns from the topology graph of the learned models. we consolidate the approach by explaining the use of some well-known markovian models on mining several kinds of patterns. we then present a novel high-order hidden markov model, the variable-length hidden markov model (vlhmm), which combines the advantages of well-known markovian models and has the superiority in both efficiency and accuracy. therefore, it can mine a much wider variety of patterns than each of prior markovian models. we demonstrate the power of vlhmm by mining four kinds of interesting patterns from 3d motion capture data, which is typical for the high-dimensionality and complex dynamics.
top-cop: mining top-k strongly correlated pairs in large databases. recently, there has been considerable interest in computing strongly correlated pairs in large databases. most previous studies require the specification of a minimum correlation threshold to perform the computation. however, it may be difficult for users to provide an appropriate threshold in practice, since different data sets typically have different characteristics. to this end, we propose an alternative task: mining the top-k strongly correlated pairs. in this paper, we identify a 2-d monotone property of an upper bound of pearson's correlation coefficient and develop an efficient algorithm, called top-cop to exploit this property to effectively prune many pairs even without computing their correlation coefficients. our experimental results show that the top-cop algorithm can be orders of magnitude faster than brute-force alternatives for mining the top-k strongly correlated pairs.
keyphrase extraction using semantic networks structure analysis. keyphrases play a key role in text indexing, summarization and categorization. however, most of the existing keyphrase extraction approaches require human-labeled training sets. in this paper, we propose an automatic keyphrase extraction algorithm, which can be used in both supervised and unsupervised tasks. this algorithm treats each document as a semantic network. structural dynamics of the network are used to extract keyphrases (key nodes) unsupervised. experiments demonstrate the proposed algorithm averagely improves 50% in effectiveness and 30% in efficiency in unsupervised tasks and performs comparatively with supervised extractors. moreover, by applying this algorithm to supervised tasks, we develop a classifier with an overall accuracy up to 80%.
mining maximal generalized frequent geographic patterns with knowledge constraints. in frequent geographic pattern mining a large amount of patterns is well known a priori. this paper presents a novel approach for mining frequent geographic patterns without associations that are previously known as non-interesting. geographic dependences are eliminated during the frequent set generation using prior knowledge. after the dependence elimination maximal generalized frequent sets are computed to remove redundant frequent sets. experimental results show a significant reduction of both the number of frequent sets and the computational time for mining maximal frequent geographic patterns.
resource management for networked classifiers in distributed stream mining systems. networks of classifiers are capturing the attention of system and algorithmic researchers because they offer improved accuracy over single model classifiers, can be distributed over a network of servers for improved scalability, and can be adapted to available system resources. this work provides a principled approach for the optimized allocation of system resources across a networked chain of classifiers. we begin with an illustrative example of how complex classification tasks can be decomposed into a network of binary classifiers. we formally define a global performance metric by recursively collapsing the chain of classifiers into one combined classifier. the performance metric trades off the end-to-end probabilities of detection and false alarm, both of which depend on the resources allocated to each individual classifier. we formulate the optimization problem and present optimal resource allocation results for both simulated and state-of-the-art classifier chains operating on telephony data.
mining generalized graph patterns based on user examples. there has been a lot of recent interest in mining patterns from graphs. often, the exact structure of the patterns of interest is not known. this happens, for example, when molecular structures are mined to discover fragments useful as features in chemical compound classification task, or when web sites are mined to discover sets of web pages representing logical documents. such patterns are often generated from a few small subgraphs (cores), according to certain generalization rules (grs). we call such patterns "generalized patterns"(gps). while being structurally different, gps often perform the same function in the network. previously proposed approaches to mining gps either assumed that the cores and the grs are given, or that all interesting gps are frequent. these are strong assumptions, which often do not hold in practical applications. in this paper, we propose an approach to mining gps that is free from the above assumptions. given a small number of gps selected by the user, our algorithm discovers all gps similar to the user examples. first, a machine learning-style approach is used to find the cores. second, generalizations of the cores in the graph are computed to identify gps. evaluation on synthetic data, generated using real cores and grs from biological and web domains, demonstrates effectiveness of our approach.
corrective classification: classifier ensembling with corrective and diverse base learners. empirical studies on supervised learning have shown that ensembling methods lead to a model superior to the one built from a single learner under many circumstances [1], especially when learning from imperfect, such as biased or noise infected, information sources. in this paper, we provide a novel corrective classification (c2) design, which incorporates error detection, data cleansing and bootstrap sampling to construct base learners that constitute the classifier ensemble. the essential goal is to reduce noise impacts and eventually enhance the learners built from noise corrupted data. we further analyze the importance of both the accuracy and diversity of base learners in ensembling, in order to shed some light on the mechanism under which c2 works. experimental comparisons will demonstrate that c2 is not only superior to the learner built from the original noisy sources, but also more reliable than bagging [2] or the aggressive classifier ensemble (ace) [3], which are two degenerate components/variants of c2.
minimum enclosing spheres formulations for support vector ordinal regression. we present two new support vector approaches for ordinal regression. these approaches find the concentric spheres with minimum volume that contain most of the training samples. both approaches guarantee that the radii of the spheres are properly ordered at the optimal solution. the size of the optimization problem is linear in the number of training samples. the popularsmo algorithm is adapted to solve the resulting optimization problem. numerical experiments on some real-world data sets verify the usefulness of our approaches for data mining.
personalization in context: does context matter when building personalized customer models? the idea that context is important when predicting customer behavior has been maintained by scholars in marketing and data mining. however, no systematic study measuring how much the contextual information really matters in building customer models in personalization applications have been done before. in this paper, we address this problem. to this aim, we collected data containing rich contextual information by developing a special-purpose browser to help users to navigate a well-known e-commerce retail portal and purchase products on its site. the experimental results show that context does matter for the case of modeling behavior of individual customers. the granularity of contextual information also matters, and the effect of contextual information gets diluted during the process of aggregating customers' data.
bregman bubble clustering: a robust, scalable framework for locating multiple, dense regions in data. in traditional clustering, every data point is assigned to at least one cluster. on the other extreme, one class clustering algorithms proposed recently identify a single dense cluster and consider the rest of the data as irrelevant. however, in many problems, the relevant data forms multiple natural clusters. in this paper, we introduce the notion of bregman bubbles and propose bregman bubble clustering (bbc) that seeks k dense bregman bubbles in the data. we also present a corresponding generative model, soft bbc, and show several connections with bregman clustering, and with a one class clustering algorithm. empirical results on various datasets show the effectiveness of our method.
loci: load shedding through class-preserving data acquisition. an avalanche of data available in the stream form is overstretching our data analyzing ability. in this paper, we propose a novel load shedding method that enables fast and accurate stream data classification. we transform input data so that its class information concentrates on a few features, and we introduce a progressive classifier that makes prediction with partial input. we take advantage of stream data's temporal locality . for example, readings from a temperature sensor usually do not change dramatically over a short period of time . for load shedding. we first show that temporal locality of the original data is preserved by our transform, then we utilize positive and negative knowledge about the data (which is of much smaller size than the data itself) for classification. we employ both analytical and empirical analysis to demonstrate the advantage of our approach.
lazy associative classification. decision tree classifiers perform a greedy search for rules by heuristically selecting the most promising features. such greedy (local) search may discard important rules. associative classifiers, on the other hand, perform a global search for rules satisfying some quality constraints (i.e., minimum support). this global search, however, may generate a large number of rules. further, many of these rules may be useless during classification, and worst, important rules may never be mined. lazy (non-eager) associative classification overcomes this problem by focusing on the features of the given test instance, increasing the chance of generating more rules that are useful for classifying the test instance. in this paper we assess the performance of lazy associative classification. first we demonstrate that an associative classifier performs no worse than the corresponding decision tree classifier. also we demonstrate that lazy classifiers outperform the corresponding eager ones. our claims are empirically confirmed by an extensive set of experimental results. we show that our proposed lazy associative classifier is responsible for an error rate reduction of approximately 10% when compared against its eager counterpart, and for a reduction of 20% when compared against a decision tree classifier. a simple caching mechanism makes lazy associative classification fast, and thus improvements in the execution time are also observed.
how bayesians debug. manual debugging is expensive. and the high cost has motivated extensive research on automated fault lo- calization in both software engineering and data mining communities. fault localization aims at automatically locating likely fault locations, and hence assists manual debugging. a number of fault localization algorithms have been developed in recent years, which prove effec- tive when multiple failing and passing cases are avail- able. however, we notice what is more commonly en- countered in practice is the two-sample debugging prob- lem, where only one failing and one passing cases are available. this problem has been either overlooked or insufficiently tackled in previous studies. in this paper, we develop a new fault localization al- gorithm, named bayesdebug, which simulates some manual debugging principles through a bayesian ap- proach. different from existing approaches that base fault analysis on multiple passing and failing cases, bayesdebug only requires one passing and one failing cases. we reason about why bayesdebug fits the two- sample debugging problem and why other approaches do not. finally, an experiment with a real-world program grep-2.2 is conducted, which exemplifies the effective- ness of bayesdebug.
converting output scores from outlier detection algorithms into probability estimates. current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. we argue that converting the scores into well-calibrated probability estimates is more favorable for several reasons. first, the probability estimates allow us to select the appropriate threshold for declaring outliers using a bayesian risk model. second, the probability estimates obtained from individual models can be aggregated to build an ensemble outlier detection framework. in this paper, we present two methods for transforming outlier scores into probabilities. the first approach assumes that the posterior probabilities follow a logistic sigmoid function and learns the parameters of the function from the distribution of outlier scores. the second approach models the score distributions as a mixture of exponential and gaussian probability functions and calculates the posterior probabilites via the bayes' rule. we evaluated the efficacy of both methods in the context of threshold selection and ensemble outlier detection. we also show that the calibration accuracy improves with the aid of some labeled examples.
margin: maximal frequent subgraph mining. the exponential number of possible subgraphsmakes the problem of frequent subgraph mining a challenge. the set of maximal frequent subgraphs is much smaller to that of the set of frequent subgraphs, thus providing ample scope for pruning. margin is a maximal subgraph mining algorithm that moves among promising nodes of the search space along the "border" of the infrequent and frequent subgraphs. this drastically reduces the number of candidate patterns considered in the search space. experimental results validate the efficiency and utility of the technique proposed.
cluster analysis of time-series medical data based on the trajectory representation and multiscale comparison techniques. this paper presents a cluster analysis method for multi-dimensional time-series data on clinical laboratory examinatios. our method represents the time series of test results as trajectories in multidimensional space, and compares their structural similarity by using the multiscale comparison technique. it enables us to find the part-to-part correspondences between two trajectories, taking into account the relationships between different tests. the resultant dissimilarity can be further used with clustering algorithms for finding the groups of similar cases. the method was applied to the cluster analysis of albumin-platelet data in the chronic hepatitis dataset. the results denonstrated that it could form interesting groups of cases that have high correspondence to the fibrotic stages.
speedup clustering with hierarchical ranking. many clustering algorithms in particular hierarchical clustering algorithms do not scale-up well for large data-sets especially when using an expensive distance function. in this paper, we propose a novel approach to perform approximate clustering with high accuracy. we introduce the concept of a pairwise hierarchical ranking to efficiently determine close neighbors for every data object. empirical results on synthetic and real-life data show a speedup of up to two orders of magnitude over optics while maintaining a high accuracy and up to one order of magnitude over the previously proposed data bubbles method, which also tries to speedup optics by trading accuracy for speed.
a parameterized probabilistic model of network evolution for supervised link prediction. we introduce a new approach to the problem of link prediction for network structured domains, such as the web, social networks, and biological networks. our approach is based on the topological features of network structures, not on the node features. we present a novel parameterized probabilistic model of network evolution and derive an efficient incremental learning algorithm for such models, which is then used to predict links among the nodes. we show some promising experimental results using biological network data sets.
improving grouped-entity resolution using quasi-cliques. the entity resolution (er) problem, which identifies duplicate entities that refer to the same real world entity, is essential in many applications. in this paper, in particular, we focus on resolving entities that contain a group of related elements in them (e.g., an author entity with a list of citations, a singer entity with song list, or an intermediate result by group by sql query). such entities, named as grouped-entities, frequently occur in many applications. the previous approaches toward grouped-entity resolution often rely on textual similarity, and produce a large number of false positives. as a complementing technique, in this paper, we present our experience of applying a recently proposed graph mining technique, quasi-clique, atop conventional er solutions. our approach exploits contextual information mined from the group of elements per entity in addition to syntactic similarity. extensive experiments verify that our proposal improves precision and recall up to 83% when used together with a variety of existing er solutions, but never worsens them.
integrating features from different sources for music information retrieval. efficient and intelligent music information retrieval is a very important topic of the 21st century. with the ultimate goal of building personal music information retrieval systems, this paper studies the problem of identifying "similar" artists using both lyrics and acoustic data. in this paper, we present a clustering algorithm that integrates features from both sources to perform bimodal learning. the algorithm is tested on a data set consisting of 570 songs from 53 albums of 41 artists using artist similarity provided by all music guide. experimental results show that the accuracy of artist similarity classifiers can be significantly improved and that artist similarity can be efficiently identified.
semantic smoothing for model-based document clustering. a document is often full of class-independent "general" words and short of class-specific 'core" words, which leads to the difficulty of document clustering. we argue that both problems will be relieved after suitable smoothing of document models in agglomerative approaches and of cluster models in partitional approaches, and hence improve clustering quality. to the best of our knowledge, most model-based clustering approaches use laplacian smoothing to prevent zero probability while most similarity-based approaches employ the heuristic tf*idf scheme to discount the effect of "general" words. inspired by a series of statistical translation language model for text retrieval, we propose in this paper a novel smoothing method referred to as context-sensitive semantic smoothing for document clustering purpose. the comparative experiment on three datasets shows that model-based clustering approaches with semantic smoothing is effective in improving cluster quality.
anytime classification using the nearest neighbor algorithm with applications to stream mining. for many real world problems we must perform classification under widely varying amounts of computational resources. for example, if asked to classify an instance taken from a bursty stream, we may have from milliseconds to minutes to return a class prediction. for such problems an anytime algorithm may be especially useful. in this work we show how we can convert the ubiquitous nearest neighbor classifier into an anytime algorithm that can produce an instant classification, or if given the luxury of additional time, can utilize the extra time to increase classification accuracy. we demonstrate the utility of our approach with a comprehensive set of experiments on data from diverse domains.
stability region based expectation maximization for model-based clustering. in spite of the initialization problem, the expectation- maximization (em) algorithm is widely used for estimating the parameters in several data mining related tasks. most popular model-based clustering techniques might yield poor clusters if the parameters are not initialized properly. to reduce the sensitivity of initial points, a novel algorithm for learning mixture models from multivariate data is introduced in this paper. the proposed algorithm takes advantage of trust-tech (transformation under stability-retaining equilibra characterization) to compute neighborhood local maxima on likelihood surface using stability regions. basically, our method coalesces the advantages of the traditional em with that of the dynamic and geometric characteristics of the stability regions of the corresponding nonlinear dynamical system of the log-likelihood function. two phases namely, the em phase and the stability region phase, are repeated alternatively in the parameter space to achieve improvements in the maximum likelihood. though applied to gaussian mixtures in this paper, our technique can be easily generalized to any other parametric finite mixture model. the algorithm has been tested on both synthetic and real datasets and the improvements in the performance compared to other approaches are demonstrated. the robustness with respect to initialization is also illustrated experimentally.
similarity of temporal query logs based on arima model. a challenging issue faced by modern information retrieval is that of determining and satisfying users' requirements relying only on very short text queries. in this paper, we propose an algorithm to find out related queries based on auto-regressive integrated moving average (arima) model. first, we select and estimate arima model of the temporal query logs. and then each query is denoted by a sequence of coefficients. we use the correlation of arima coefficients as the similarity measurement. we call it as the arima temporal similarity (arima ts). this similarity describes how strongly two time series are linearly related. on the other hand, the arima model could also be treated as a dimensionality reduction procedure. it can save storage space for a large database of the query logs. in addition, arima model could be used as a tool to predict the trend of a query. the experimental results on two query logs of msn search engine 1 demonstrate that the proposed approach can achieve better similarity measurement efficiently.
enhancing text clustering using concept-based mining model. most of text mining techniques are based on word and/or phrase analysis of the text. the statistical analysis of a term (word or phrase) frequency captures the importance of the term within a document. however, to achieve a more accurate analysis, the underlying mining technique should indicate terms that capture the semantics of the text from which the importance of a term in a sentence and in the document can be derived. a new concept-based mining model that relies on the analysis of both the sentence and the document, rather than, the traditional analysis of the document dataset only is introduced. the proposed mining model consists of a concept-based analysis of terms and a concept-based similarity measure. the term which contributes to the sentence semantics is analyzed with respect to its importance at the sentence and document levels. the model can efficiently find significant matching terms, either words or phrases, of the documents according to the semantics of the text. the similarity between documents relies on a new concept-based similarity measure which is applied to the matching terms between documents. experiments using the proposed concept-based term analysis and similarity measure in text clustering are conducted. experimental results demonstrate that the newly developed concept-based mining model enhances the clustering quality of sets of documents substantially.
distances and (indefinite) kernels for sets of objects. the main disadvantage of most existing set kernels is that they are based on averaging, which might be inappropriate for problems where only specific elements of the two sets should determine the overall similarity. in this paper we propose a class of kernels for sets of vectors directly exploiting set distance measures and, hence, incorporating various semantics into set kernels and lending the power of regularization to learning in structural domains where natural distance functions exist. these kernels belong to two groups: (i) kernels in the proximity space induced by set distances and (ii) set distance substitution kernels (non-psd in general). we report experimental results which show that our kernels compare favorably with kernels based on averaging and achieve results similar to other state-of-the-art methods. at the same time our kernels systematically improve over the naive way of exploiting distances.
latent friend mining from blog data. the rapid growth of blog (also known as "weblog") data provides a rich resource for social community mining. in this paper, we put forward a novel research problem of mining the latent friends of bloggers based on the contents of their blog entries. latent friends are defined in this paper as people who share the similar topic distribution in their blogs. these people may not actually know each other, but they have the interest and potential to find each other out. three approaches are designed for latent friend detection. the first one, called cosine similarity-based method, determines the similarity between bloggers by calculating the cosine similarity between the contents of the blogs. the second approach, known as topic-based method, is based on the discovery of latent topics using a latent topic model and then calculating the similarity at the topic level. the third one is two-level similarity-based, which is conducted in two stages. in the first stage, an existing topic hierarchy is exploited to build a topic distribution for a blogger. then, in the second stage, a detailed similarity comparison is conducted for bloggers that are close in interest to each other which are discovered in the first stage. our experimental results show that both the topic-based and two-level similarity-based methods work well, and the last approach performs much better than the first two. in this paper, we give a detailed analysis of the advantages and disadvantages of different approaches.
frequent closed itemset mining using prefix graphs with an efficient flow-based pruning strategy. this paper presents pgminer, a novel graph-based algorithm for mining frequent closed itemsets. our approach consists of constructing a prefix graph structure and decomposing the database to variable length bit vectors, which are assigned to nodes of the graph. the main advantage of this representation is that the bit vectors at each node are relatively shorter than those produced by existing vertical mining methods. this facilitates fast frequency counting of itemsets via intersection operations. we also devise several internode and intra-node pruning strategies to substantially reduce the combinatorial search space. unlike other existing approaches, we do not need to store in memory the entire set of closed itemsets that have been mined so far in order to check whether a candidate itemset is closed. this dramatically reduces the memory usage of our algorithm, especially for low support thresholds. our experiments using synthetic and real-world data sets show that pgminer outperforms existing mining algorithms by as much as an order of magnitude and is scalable to very large databases.
mining latent associations of objects using a typed mixture model--a case study on expert/expertise mining. this paper studies the problem of discovering latent associations among objects in text documents. specifically, given two sets of objects and various types of co-occurrence data concerning the objects existing in texts, we aim to discover the hidden or latent associative relationships between the two sets of objects. existing methods are not directly applicable as they are unable to consider all this information. for example, the probabilistic mixture model called separable mixture model (smm) proposed by hofmann can use only one type of co-occurrences to mine latent associations. this paper proposes a more general probabilistic mixture model called the typed separable mixture model (tsmm), which is able to use all types of co-occurrences within a single framework. experimental results based on the expert/expertise mining task show that tsmm outperforms smm significantly.
boosting the feature space: text classification for unstructured data on the web. the issue of seeking efficient and effective methods for classifying unstructured text in large document corpora has received much attention in recent years. traditional document representation like bag-of-words encodes documents as feature vectors, which usually leads to sparse feature spaces with large dimensionality, thus making it hard to achieve high classification accuracies. this paper addresses the problem of classifying unstructured documents on the web. a classification approach is proposed that utilizes traditional feature reduction techniques along with a collaborative filtering method for augmenting document feature spaces. the method produces feature spaces with an order of magnitude less features compared with a baseline bag-of-words feature selection method. experiments on both real-world data and benchmark corpus indicate that our approach improves classification accuracy over the traditional methods for both support vector machines and adaboost classifiers.
an information theoretic approach to detection of minority subsets in database. detection of rare and exceptional occurrences in large-scale databases have become an important practice in the field of knowledge discovery and information retrieval. many databases include large amount of noise or irrelevant data, whose distribution often overlaps with the subsets of exceptional data containing useful knowledge. this paper addresses the problem of finding a small subset of "minority" data whose distribution overlaps with, but are exceptional to or inconsistent with that of the majority of the database. in such a case, conventional distance-based or density-based approaches in outlier detection are ineffective due to their dependence on the structure of the majority or the prerequisite of critical parameters. we formalize the task as an estimation of a model of the minority subset which provides a simple description of the subset and yet maintains divergence from that of the majority. this estimation is formalized as a minimization problem using an information theoretic framework of rate distortion theory. we further introduce conditions of the majority to derive an objective function which factorizes the property of the minority and dependence to the structure of the majority. the proposed method shows improvements from conventional approaches in artificial data and a promising result in document retrieval problem.
fast on-line kernel learning for trees. kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. however kernels for structures usually are too computational demanding to be applied to complex learning algorithms, e.g. support vector machines. consequently, in order to apply kernels to large amount of structured data, we need fast on-line algorithms along with an efficiency optimization of kernel-based computations. in this paper, we optimize this computation by representing set of trees by minimal direct acyclic graphs (dags) allowing us i) to reduce the storage requirements and ii) to speed up the evaluation on large number of trees as it can be done 'one-shot' by computing kernels over dags. the experiments on predicate argument subtrees from propbank data show that substantial computational savings can be obtained for the perceptron algorithm.
learning to use a learned model: a two-stage approach to classification. association rule-based classifiers have recently emerged as competitive classification systems. however, there are still deficiencies that hinder their performance. one defi- ciency is the use of rules in the classification stage. current systems assign classes to new objects based on the best rule applied or on some predefined scoring of multiple rules. in this paper we propose a new technique where the system automatically learns how to use the rules. we achieve this by developing a two-stage classification model. first, we use association rule mining to discover classification rules. second, we employ another learning algorithm to learn how to use these rules in the prediction process. our two-stage approach outperforms c4.5 and ripper on the uci datasets in our study, and outperforms other rule-learning methods on more than half the datasets. the versatility of our method is also demonstrated by applying it to text classification, where it equals the performance of the best known systems for this task, svms.
bayesian state space modeling approach for measuring the effectiveness of marketing activities and baseline sales from pos data. analysis of point of sales (pos) data is an important research area of marketing science and knowledge discovery, which may enable marketing managers to attain the effective marketing activities. to measure the effectiveness of marketing activities and baseline sales, we develop the multivariate time series modeling method in the framework of a general state space model. a multivariate poisson model and a multivariate correlated auto-regressive model are used for a system model and an observation model. the bayesian approach via markov chain monte carlo (mcmc) algorithm is employed for estimating model parameters. to evaluate the goodness of the estimated models, the bayesian predictive information criterion is utilized. the proposed model is evaluated with its application to actual pos data.
detecting link spam using temporal information. how to effectively protect against spam on search ranking results is an important issue for contemporary web search engines. this paper addresses the problem of combating one major type of web spam: 'link spam.' most of the previous work on anti link spam managed to make use of one snapshot of web data to detect spam, and thus it did not take advantage of the fact that link spam tends to result in drastic changes of links in a short time period. to overcome the shortcoming, this paper proposes using temporal information on links in detection of link spam, as well as other information. specifically, it defines temporal features such as in-link growth rate (igr) and in-link death rate (idr) in a spam classification model (i.e., svm). experimental results on web domain graph data show that link spam can be successfully detected with the proposed method.
confident identification of relevant objects based on nonlinear rescaling method and transductive inference. we present a novel machine learning algorithm to identify relevant objects from a large amount of data. this approach is driven by linear discrimination based on nonlinear rescaling (nr) method and transductive inference. the nr algorithm for linear discrimination (nrld) computes both the primal and the dual approximation at each step. the dual variables associated with the given labeled dataset provide important information about the objects in the data-set and play the key role in ordering these objects. a confidence score based on a transductive inference procedure using nrld is used to rank and identify the relevant objects from a pool of unlabeled data. experimental results on an unbalanced protein data-set for the drug target prioritization and identification problem are used to illustrate the feasibility of the proposed identification algorithm.
lazy bagging for classifying imbalanced data. in this paper, we propose a lazy bagging (lb) design, which builds bootstrap replicate bags based on the characteristics of the test instances. upon receiving a test instance ik, lb will trim bootstrap bags by taking ik's nearest neighbors in the training set into consideration. our hypothesis is that an unlabeled instance's nearest neighbors provide valuable information for learners to refine their local decision boundaries for classifying this instance. by taking full advantage of ik's nearest neighbors, the base learners are able to receive less bias and variance in classifying ik. this strategy is beneficial for classifying imbalanced data because refining local decision boundaries can help a learner reduce its inherent bias towards the majority class and improve its performance on minority class examples. our experimental results will confirm that lb outperforms c4.5 and tb in terms of reducing classification error, and most importantly this error reduction is largely contributed from lb's improvement on minority class examples. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
efficient algorithms for mining significant substructures in graphs with quality guarantees. graphs have become popular for modeling scientific data in recent years. as a result, techniques for mining graphs are extremely important for understanding inherent data and domain characteristics. one such exploratory mining paradigm is the k-mst (minimum spanning tree over k vertices) problem that can be used to discover significant local substructures. in this paper, we present an efficient approximation algorithm for the k-mst problem in large graphs. the algorithm has an o (k) approximation ratio and o (n log n + m log m log k + nk2 log k) running time, where n and m are the number of vertices and edges respectively. experimental results on synthetic graphs and protein interaction networks show that the algorithm is scalable to large graphs and useful for discovering biological pathways. the highlight of the algorithm is that it offers both analytical guarantees and empirical evidence of good running time and quality.
finding predictive runs with laps. we present an extension to the lasso [6] for binary classification problems with ordered attributes. inspired by the fused lasso [5] and the group lasso [7, 3] models, we aim to both discover and model runs (contiguous subgroups of the variables) that are highly predictive. we call the extended model laps (the lasso with attribute partition search). such problems commonly arise in financial and medical domains, where predictors are time series variables, for example. this paper outlines the formulation of the problem, an algorithm to obtain the model coefficients and experiments showing applicability to practical problems of this type.
mining frequent itemsets in a stream. we study the problem of finding frequent itemsets in a continuous stream of transactions. the current frequency of an itemset in a stream is defined as its maximal frequency over all possible windows in the stream from any point in the past until the current state that satisfy a minimal length constraint. properties of this new measure are studied and an incremental algorithm that allows, at any time, to immediately produce the current frequencies of all frequent itemsets is proposed. experimental and theoretical analysis show that the space requirements for the algorithm are extremely small for many realistic data distributions.
extracting product comparisons from discussion boards. in recent years, product discussion forums have become a rich environment in which consumers and potential adopters exchange views and information. researchers and practitioners are starting to extract user sentiment about products from user product reviews. users often compare different products, stating which they like better and why. extracting information about product comparisons offers a number of challenges; recognizing and normalizing entities (products) in the informal language of blogs and discussion groups require different techniques than those used for entity extraction in the more formal text of newspapers and scientific articles. we present a case study in extracting information about comparisons between running shoes and between cars, describe an effective methodology, and show how it produces insight into how consumers view the running shoe and car markets.
dusc: dimensionality unbiased subspace clustering. to gain insight into today's large data resources, data mining provides automatic aggregation techniques. clustering aims at grouping data such that objects within groups are similar while objects in different groups are dissimilar. in scenarios with many attributes or with noise, clusters are often hidden in subspaces of the data and do not show up in the full dimensional space. for these applications, subspace clustering methods aim at detecting clusters in any subspace. existing subspace clustering approaches fall prey to an effect we call dimensionality bias. as dimensionality of subspaces varies, approaches which do not take this effect into account fail to separate clusters from noise. we give a formal definition of dimensionality bias and analyze consequences for subspace clustering. a dimensionality unbiased subspace clustering (dusc) definition based on statistical foundations is proposed. in thorough experiments on synthetic and real world data, we show that our approach outperforms existing subspace clustering algorithms.
block-iterative algorithms for non-negative matrix approximation. in this paper we present new algorithms for non-negative matrix approximation (nma), commonly known as the nmf problem. our methods improve upon the well-known methods of lee \& seung~\cite{lee00} for both the frobenius norm as well the kullback-leibler divergence versions of the problem. for the latter problem, our results are especially interesting because it seems to have witnessed much lesser algorithmic progress as compared to the frobenius norm nma problem. our algorithms are based on a particular \textbf {block-iterative} acceleration technique for em, which preserves the multiplicative nature of the updates and also ensures monotonicity. furthermore, our algorithms also naturally apply to the bregman-divergence nma algorithms of~\cite{suv.nips}. experimentally, we show that our algorithms outperform the traditional lee/seung approach most of the time.
cross-mining binary and numerical attributes. we consider the problem of relating itemsets mined on binary attributes of a data set to numerical attributes of the same data. an example is biogeographical data, where the numerical attributes correspond to environmental variables and the binary attributes encode the presence or absence of species in different environments. from the viewpoint of itemset mining, the task is to select a small collection of interesting itemsets using the numerical attributes; from the viewpoint of the numerical attributes, the task is to constrain the search for local patterns (e.g. clusters) using the binary attributes. we give a formal definition of the problem, discuss it theoretically, give a simple constant-factor approximation algorithm, and show by experiments on biogeographical data that the algorithm can capture interesting patterns that would not have been found using either itemset mining or clustering alone.
efficient kernel discriminant analysis via spectral regression. linear discriminant analysis (lda) has been a popular method for extracting features which preserve class separability. the projection vectors are commonly obtained by maximizing the between class covariance and simultaneously minimizing the within class covariance. lda can be performed either in the original input space or in the reproducing kernel hilbert space (rkhs) into which data points are mapped, which leads to kernel discriminant analysis (kda). when the data are highly nonlinear distributed, kda can achieve better performance than lda. however, computing the projective functions in kda involves eigen-decomposition of kernel matrix, which is very expensive when a large number of training samples exist. in this paper, we present a new algorithm for kernel discriminant analysis, called spectral regression kernel discriminant analysis (srkda). by using spectral graph analysis, srkda casts discriminant analysis into a regression framework which facilitates both efficient computation and the use of regularization techniques. specifically, srkda only needs to solve a set of regularized regression problems and there is no eigenvector computation involved, which is a huge save of computational cost. our computational analysis shows that srkda is 27 times faster than the ordinary kda. moreover, the new formulation makes it very easy to develop incremental version of the algorithm which can fully utilize the computational results of the existing training samples. experiments on face recognition demonstrate the effectiveness and efficiency of the proposed algorithm.
improving knowledge discovery in document collections through combining text retrieval and link analysis techniques. in this paper, we present concept chain queries (ccq), a special case of text mining in document collections focusing on detecting links between two topics across text documents. we interpret such a query as finding the most meaningful evidence trails across documents that connect these two topics. we propose to use link-analysis techniques over the extracted features provided by information extraction engine for finding new knowledge. a graphical text representation and mining model is proposed which combines information retrieval, association mining and link analysis techniques. we present experiments on different datasets that demonstrate the effectiveness of our algorithm. specifically, the algorithm generates ranked concept chains and evidence trails where the key terms representing significant relationships between topics are ranked high1.
the chosen few: on identifying valuable patterns. constrained pattern mining extracts patterns based on their individual merit. usually this results in far more patterns than a human expert or a machine learning technique could make use of. often different patterns or combinations of patterns cover a similar subset of the examples, thus being redundant and not carrying any new information. to remove the redundant information contained in such pattern sets, we propose a general heuristic approach for selecting a small subset of patterns. we identify several selection techniques for use in this general algorithm and evaluate those on several data sets. the results show that the technique succeeds in severely reducing the number of patterns, while at the same time apparently retaining much of the original information. additionally the experiments show that reducing the pattern set indeed improves the quality of classification results. both results show that the approach is very well suited for the goals we aim at.
change-point detection in time-series data based on subspace identification. in this paper, we propose series of algorithms for detecting change points in time-series data based on subspace identification, meaning a geometric approach for estimating linear state-space models behind time-series data. our algorithms are derived from the principle that the subspace spanned by the columns of an observability matrix and the one spanned by the subsequences of time-series data are approximately equivalent. in this paper, we derive an batchtype algorithm applicable to ordinary time-series data, i.e. consisting of only output series, and then introduce the online version of the algorithm and the extension to be available with input-output time-series data. we illustrate the effectiveness of our algorithms with comparative experiments using some artificial and real datasets.
using burstiness to improve clustering of topics in news streams. specialists who analyze online news have a hard time separating the wheat from the chaff. moreover, automatic data-mining techniques like clustering of news streams into topical groups can fully recover the underlying true class labels of data if and only if all classes are well separated. in reality, especially for news streams, this is clearly not the case. the question to ask is thus this: if we cannot recover the full c classes by clustering, what is the largest k \le c clusters we can find that best resemble the k underlying classes? using the intuition that bursty topics are more likely to correspond to important events that are of interest to analysts, we propose several new bursty vector space models (b-vsm) for representing a news document. b-vsm takes into account the burstiness (across the full corpus and whole duration) of each constituent word in a document at the time of publication. we benchmarked our b-vsm against the classical tfidf-vsm on the task of clustering a collection of news stream articles with known topic labels. experimental results show that b-vsm was able to find the burstiest clusters/topics. further, it also significantly improved the recall and precision for the top k clusters/topics.
mining statistical information of frequent fault-tolerant patterns in transactional databases. constraints applied on classic frequent patterns are too strict and may cause interesting patterns to be missed. hence, researchers have proposed to mine a more relaxed version of frequent patterns, where transactions are allowed to miss some items in the itemset they support. patterns exhibiting such "faults" are called frequent fault-tolerant patterns (fft-patterns) if they are significant in number. in this paper, the term "pattern" is distinguished from "itemset" as referring to a pair (tidset × itemset). unlike classical frequent patterns, the number of fftpatterns grows exponentially not only with the number of items, but also with the number of transactions. since the latter may reach millions, mining fft-patterns by enumerating them becomes infeasible. hence, the challenge is to represent fft-patterns concisely without losing any useful information. to address this, we draw on the observation that, in transactional databases, the transactions themselves are not important from the data mining point-ofview; i.e. researchers are interested in finding itemsets contained in lots of transactions, rather than in the transactions per se. therefore, we propose to mine only the frequent itemsets along with the statistical information of the supporting transaction sets, rather than enumerate entire fftpatterns. then we present our approach the bias framework, consisting of backtracking algorithm, integer linear programming (ilp) constraints, and aggregation statistics to solve this problem. algorithms under this framework not only increase the efficiency of the fft-patterns mining process by more than an order of magnitude, but also provide a more comprehensive analysis of fft-patterns.
on appropriate assumptions to mine data streams: analysis and practice. recent years have witnessed an increasing number of studies in stream mining, which aim at building an accurate model for continuously arriving data. somehow most existing work makes the implicit assumption that the training data and the yet-to-come testing data are always sampled from the "same distribution”, and yet this "same distribution” evolves over time. we demonstrate that this may not be true, and one actually may never know either "how” or "when” the distribution changes. thus, a model that fits well on the observed distribution can have unsatisfactory accuracy on the incoming data. practically, one can just assume the bare minimum that learning from observed data is better than both random guessing and always predicting exactly the same class label. importantly, we formally and experimentally demonstrate the robustness of a model averaging and simple voting-based framework for data streams, particularly when incoming data "continuously follows significantly different” distributions. on a real streaming data, this framework reduces the expected error of baseline models by 60%, and remains the most accurate compared to those baseline models.
can the content of public news be used to forecast abnormal stock market behaviour? a popular theory of markets is that they are efficient: all available information is deemed to provide an accurate valuation of an asset at any time. in this paper, we consider how the content of marketrelated news articles contributes to such information. specifically, we mine news articles for terms of interest, and quantify this degree of interest. we then incorporate this measure into traditional models for market index volatility with a view to forecasting whether the incidence of interesting news is correlated with a shock in the index, and thus if the information can be captured to value the underlying asset. we illustrate the methodology on stock market indices for the usa, the uk, and australia.
a pairwise covariance-preserving projection method for dimension reduction. dimension reduction is critical in many areas of pattern classification and machine learning and many discriminant analysis algorithms have been proposed. in this paper, a pairwise covariance-preserving projection method (pcpm) is proposed for dimension reduction. pcpm maximizes the class discrimination and also preserves approximately the pairwise class covariances. the optimization involved in pcpm can be solved directly by eigenvalues decomposition. our theoretical and empirical analysis reveals the relationship between pcpm and linear discriminant analysis (lda), sliced average variance estimator (save), heteroscedastic discriminant analysis (hda) and covariance preserving projection method (cpm). pcpm can utilize class mean and class covariance information at the same time. furthermore, pairwise weight scheme can be incorporated naturally with the pairwise summarization form. the proposed methods are evaluated by both synthetic and real-world datasets.
preserving privacy through data generation. many databases will not or can not be disclosed without strong guarantees that no sensitive information can be extracted. to address this concern several data perturbation techniques have been proposed. however, it has been shown that either sensitive information can still be extracted from the perturbed data with little prior knowledge, or that many patterns are lost. in this paper we show that generating new data is an inherently safer alternative. we present a data generator based on the models obtained by the mdlbased krimp [12] algorithm. these are accurate representations of the data distributions and can thus be used to generate data with the same characteristics as the original data. experimental results show a very large patternsimilarity between the generated and the original data, ensuring that viable conclusions can be drawn from the anonymised data. furthermore, anonymity is guaranteed for suited databases and the quality privacy trade-off can be balanced explicitly.
efficient discovery of frequent approximate sequential patterns. we propose an efficient algorithm for mining frequent approximate sequential patterns under the hamming distance model. our algorithm gains its efficiency by adopting a "break-down-and-build-up" methodology. the "breakdown" is based on the observation that all occurrences of a frequent pattern can be classified into groups, which we call strands. we developed efficient algorithms to quickly mine out all strands by iterative growth. in the "build-up" stage, these strands are grouped up to form the support sets from which all approximate patterns would be identified. a salient feature of our algorithm is its ability to grow the frequent patterns by iteratively assembling building blocks of significant sizes in a local search fashion. by avoiding incremental growth and global search, we achieve greater efficiency without losing the completeness of the mining result. our experimental studies demonstrate that our algorithm is efficient in mining globally repeating approximate sequential patterns that would have been missed by existing methods.
mining interpretable human strategies: a case study. this paper focuses on mining human strategies by observing their actions. our application domain is an hci study aimed at discovering general strategies used by software users and understanding how such strategies relate to gender and success. we cast this as a sequential pattern discovery problem, where user strategies are manifested as sequential patterns. problematically, we found that the patterns discovered by standard algorithms were difficult to interpret and provided limited information about high-level strategies. to help interpret the patterns and extract general strategies, we examined multiple ways of clustering the patterns into meaningful groups, which collectively led to interesting findings about user behavior both in terms of gender differences and problem-solving success. as a real-world application of data mining techniques, our work led to the discovery of new strategic patterns that are linked to user success and had not been revealed in more than nine years of manual empirical work. as a case study, our work highlights important research directions for making data mining more accessible to non-experts.
disk aware discord discovery: finding unusual time series in terabyte sized datasets. the problem of finding unusual time series has recently attracted much attention, and several promising methods are now in the literature. however, virtually all proposed methods assume that the data reside in main memory. for many real-world problems this is not be the case. for example, in astronomy, multi-terabyte time series datasets are the norm. most current algorithms faced with data which cannot fit in main memory resort to multiple scans of the disk/tape and are thus intractable. in this work we show how one particular definition of unusual time series, the time series discord, can be discovered with a disk aware algorithm. the proposed algorithm is exact and requires only two linear scans of the disk with a tiny buffer of main memory. furthermore, it is very simple to implement. we use the algorithm to provide further evidence of the effectiveness of the discord definition in areas as diverse as astronomy, web query mining, video surveillance, etc., and show the efficiency of our method on datasets which are many orders of magnitude larger than anything else attempted in the literature.
incorporating user provided constraints into document clustering. document clustering without any prior knowledge or background information is a challenging problem. in this paper, we propose ss-nmf: a semi-supervised nonnegative matrix factorization framework for document clustering. in ss-nmf, users are able to provide supervision for document clustering in terms of pairwise constraints on a few documents specifying whether they "must" or "cannot" be clustered together. through an iterative algorithm, we perform symmetric tri-factorization of the documentdocument similarity matrix to infer the document clusters. theoretically, we show that ss-nmf provides a general framework for semi-supervised clustering and that existing approaches can be considered as special cases of ss-nmf. through extensive experiments conducted on publicly available data sets, we demonstrate the superior performance of ss-nmf for clustering documents.
a support vector approach to censored targets. censored targets, such as the time to events in survival analysis, can generally be represented by intervals on the real line. in this paper, we propose a novel support vector technique (named svcr) for regression on censored targets. svcr inherits the strengths of support vector methods, such as a globally optimal solution by convex programming, fast training speed and strong generalization capacity. in contrast to ranking approaches to survival analysis, our approach is able not only to achieve superior ordering performance, but also to predict the survival time very well. experiments show a significant performance improvement when the majority of the training data is censored. experimental results on several survival analysis datasets demonstrate that svcr is very competitive against classical survival analysis models.
supervised learning by training on aggregate outputs. supervised learning is a classic data mining problem where one wishes to be be able to predict an output value associated with a particular input vector. we present a new twist on this classic problem where, instead of having the training set contain an individual output value for each input vector, the output values in the training set are only given in aggregate over a number of input vectors. this new problem arose from a particular need in learning on mass spectrometry data, but could easily apply to situations when data has been aggregated in order to maintain privacy. we provide a formal description of this new problem for both classification and regression. we then examine how k-nearest neighbor, neural networks, and support vector machines can be adapted for this problem.
cocktail ensemble for regression. this paper is motivated to improve the performance of individual ensembles using a hybrid mechanism in the regression setting. based on an error-ambiguity decomposition, we formally analyze the optimal linear combination of two base ensembles, which is then extended to multiple individual ensembles via pairwise combinations. the cocktail ensemble approach is proposed based on this analysis. experiments over a broad range of data sets show that the proposed approach outperforms the individual ensembles, two other methods of ensemble combination, and two stateof-the-art regression approaches.
how much noise is too much: a study in automatic text classification. noise is a stark reality in real life data. especially in the domain of text analytics, it has a significant impact as data cleaning forms a very large part of the data processing cycle. noisy unstructured text is common in informal settings such as on-line chat, sms, email, newsgroups and blogs, automatically transcribed text from speech, and automatically recognized text from printed or handwritten material. gigabytes of such data is being generated everyday on the internet, in contact centers, and on mobile phones. researchers have looked at various text mining issues such as pre-processing and cleaning noisy text, information extraction, rule learning, and classification for noisy text. this paper focuses on the issues faced by automatic text classifiers in analyzing noisy documents coming from various sources. the goal of this paper is to bring out and study the effect of different kinds of noise on automatic text classification. does the nature of such text warrant moving beyond traditional text classification techniques? we present detailed experimental results with simulated noise on the reuters21578 and 20-newsgroups benchmark datasets. we present interesting results on real-life noisy datasets from various crm domains.
topical n-grams: phrase and topic discovery, with an application to information retrieval. most topic models, such as latent dirichlet allocation, rely on the bag-of-words assumption. however, word order and phrases are often critical to capturing the meaning of text in many text mining tasks. this paper presents topical n-grams, a topic model that discovers topics as well as topical phrases. the probabilistic model generates words in their textual order by, for each word, first sampling a topic, then sampling its status as a unigram or bigram, and then sampling the word from a topic-specific unigram or bigram distribution. thus our model can model "white house" as a special meaning phrase in the `politics' topic, but not in the `real estate' topic. successive bigrams form longer phrases. we present experiments showing meaningful phrases and more interpretable topics from the nips data and improved information retrieval performance on a trec collection.
consensus clusterings. in this paper we address the problem of combining multiple clusterings without access to the underlying features of the data. this process is known in the literature as clustering ensembles, clustering aggregation, or consensus clustering. consensus clustering yields a stable and robust final clustering that is in agreement with multiple clusterings. we find that an iterative em-like method is remarkably effective for this problem. we present an iterative algorithm and its variations for finding clustering consensus. an extensive empirical study compares our proposed algorithms with eleven other consensus clustering methods on four data sets using three different clustering performance metrics. the experimental results show that the new ensemble clustering methods produce clusterings that are as good as, and often better than, these other methods.
spectral regression: a unified approach for sparse subspace learning. recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, information retrieval, and pattern recognition. some popular methods include principal component analysis (pca), linear discriminant analysis (lda) and locality preserving projection (lpp). however, a disadvantage of all these approaches is that the learned projective functions are linear combinations of all the original features, thus it is often difficult to interpret the results. in this paper, we propose a novel dimensionality reduction framework, called unified sparse subspace learning (ussl), for learning sparse projections. ussl casts the problem of learning the projective functions into a regression framework, which facilitates the use of different kinds of regularizers. by using a l1-norm regularizer (lasso), the sparse projections can be efficiently computed. experimental results on real world classification and clustering problems demonstrate the effectiveness of our method.
data discretization unification. data discretization is defined as a process of converting continuous data attribute values into a finite set of intervals with minimal loss of information. in this paper, we prove that discretization methods based on informational theoretical complexity and the methods based on statistical measures of data dependency are asymptotically equivalent. furthermore, we define a notion of generalized entropy and prove that discretization methods based on minimal description length principle, gini index, aic, bic, and pearson&#x2019;s x 2 and g 2 statistics are all derivable from the generalized entropy function. we design a dynamic programming algorithm that guarantees the best discretization based on the generalized entropy notion. furthermore, we conducted an extensive performance evaluation of our method for several publicly available data sets. our results show that our method delivers on the average 31% less classification errors than many previously known discretization methods.
temporal analysis of semantic graphs using asalsan. asalsan is a new algorithm for computing three-way dedicom, which is a linear algebra model for analyzing intrinsically asymmetric relationships, such as trade among nations or the exchange of emails among individuals, that incorporates a third mode of the data, such as time. asalsan is unique because it enables computing the three-way dedicom model on large, sparse data. a nonnegative version of asalsan is described as well. when we apply these techniques to adjacency arrays arising from directed graphs with edges labeled by time, we obtain a smaller graph on latent semantic dimensions and gain additional information about their changing relationships over time. we demonstrate these techniques on international trade data and the enron email corpus to uncover latent components and their transient behavior. the mixture of roles assigned to individuals by asalsan showed strong correspondence with known job classifications and revealed the patterns of communication between these roles. changes in the communication pattern over time, e.g., between top executives and the legal department, were also apparent in the solutions.
discovering temporal communities from social network documents. this paper studies the discovery of communities from social network documents produced over time, addressing the discovery of temporal trends in community memberships. we first formulate static community discovery at a single time period as a tripartite graph partitioning problem. then we propose to discover the temporal communities by threading the statically derived communities in different time periods using a new constrained partitioning algorithm, which partitions graphs based on topology as well as prior information regarding vertex membership. we evaluate the proposed approach on synthetic datasets and a real-world dataset prepared from the citeseer.
optimizing frequency queries for data mining applications. data mining algorithms use various trie and bitmap-based representations to optimize the support (i.e., frequency) counting performance. in this paper, we compare the memory requirements and support counting performance of fp tree, and compressed patricia trie against several novel variants of vertical bit vectors. first, borrowing ideas from the vldb domain, we compress vertical bit vectors using wah encoding. second, we evaluate the gray code rankbased transaction reordering scheme, and show that in practice, simple lexicographic ordering, obtained by applying lsb radix sort, outperforms this scheme. led by these results, we propose hdo, a novel hamming-distance-based greedy transaction reordering scheme, and ahdo, a linear-time approximation to hdo. we present results of experiments performed on 15 common datasets with varying degrees of sparseness, and show that hdoreordered, wah encoded bit vectors can take as little as 5% of the uncompressed space, while ahdo achieves similar compression on sparse datasets. finally, with results from over a billion database and data mining style frequency query executions, we show that bitmap-based approaches result in up to hundreds of times faster support counting, and hdo-wah encoded bitmaps offer the best space-time tradeoff.
training conditional random fields by periodic step size adaptation for large-scale text mining. for applications with consecutive incoming training examples, on-line learning has the potential to achieve a likelihood as high as off-line learning without scanning all available training examples and usually has a much smaller memory footprint. to train crfs on-line, this paper presents the periodic step size adaptation (psa) method to dynamically adjust the learning rates in stochastic gradient descent. we applied our method to three large scale text mining tasks. experimental results show that psa outperforms the best off-line algorithm, l-bfgs, by many hundred times, and outperforms the best on-line algorithm, smd, by an order of magnitude in terms of the number of passes required to scan the training data set.
latent dirichlet conditional naive-bayes models. in spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where each data point only has a few non-zero observations. in this paper, we introduce conditional naive-bayes (cnb) models, which generalize naive-bayes mixture models to naturally handle sparsity by conditioning the model on observed features. further, we present latent dirichlet conditional naive-bayes (ld-cnb) models, which constitute a family of powerful hierarchical bayesian models for latent structure discovery from sparse data. the proposed family of models are quite general and can work with arbitrary regular exponential family conditional distributions. we present a variational inference based em algorithm for learning along with special case analyses for gaussian and discrete distributions. the efficacy of the proposed models are demonstrated by extensive experiments on a wide variety of different datasets.
dynamic micro targeting: fitness-based approach to predicting individual preferences. it is crucial to segment customers intelligently in order to offer more targeted and personalized products and services. traditionally, customer segmentation is achieved using statistics-based methods that compute a set of statistics from the customer data and group customers into segments by applying clustering algorithms. recent research proposed a direct grouping-based approach that combines customers into segments by optimally combining transactional data of several customers and building a data mining model of customer behavior for each group. this paper proposes a new micro targeting method that builds predictive models of customer behavior not on the segments of customers but rather on the customer-product groups. this micro-targeting method is more general than the previously considered direct grouping method. we empirically show that it significantly outperforms the direct grouping and statistics-based segmentation methods across multiple experimental conditions and that it generates predominately small-sized segments, thus providing additional support for the micro-targeting approach to personalization. index terms: customer segmentation, marketing application, personalization, micro targeting, customer profiles
a text classification framework with a local feature ranking for learning social networks. in this paper, a text classifier framework with a feature ranking scheme is proposed to extract social structures from text data. it is assumed that only a small subset of relations between the individuals in a community is known. with this assumption, the social network extraction is translated into a classification problem. the relations between two individuals are represented by merging their document vectors and the given relations are used as labels of training data. by this transformation, a text classifier such as rocchio is used for learning the unknown relations. we show that there is a link between the intrinsic sparsity of social networks and class imbalance. furthermore, we show that feature ranking methods usually fail in problem with unbalanced data. in order to deal with this deficiency and re-balance the unbalanced social data, a local feature ranking method, which is called reverse discrimination, is proposed.
predicting blogging behavior using temporal and social networks. modeling the behavior of bloggers is an important problem with various applications in recommender systems, targeted advertising, and event detection. in this paper, we propose three models by combining content, temporal, social dimensions: the general blogging-behavior model, the profile-based blogging-behavior model and the socialnetwork and profile-based blogging-behavior model. the models are based on two regression techniques: extreme learning machine (elm), and modified general regression neural network (mgrnn). we choose one of the largest blogs, a political blog, dailykos 1, for our empirical evaluation. experiments show that the social network and profile-based blogging behavior model with elm regression techniques produce good results for the most active bloggers and can be used to predict blogging behavior.
web site recommendation using http traffic. collaborative filtering (cf) is widely used in web recommender systems, while most existing cf applications focus on transactions or page views within a single site. in this paper, we build a recommender system prototype, which suggests web sites to users, by collecting browsing events at routers without neither user nor website effort. 100 million http flows, involving 11, 327 websites, are converted to user-site ratings using access frequency as the implicit rating metric. with this rating dataset, we evaluate six cf algorithms including one proposed algorithm based on ip address locality. our experiments show that the recommendation from k nearest neighbors (rknn ) performs the best by 50% p@10 (precision of top 10) and 53% p@5 (precision of top 5). although the precision is far from ideal, our preliminary results suggest the potential value of such a centralized web site recommender system.
trend motif: a graph mining approach for analysis of dynamic complex networks. complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. until recently, studies of complex networks have mainly focused on their network topology. however, in many real world applications, the edges and vertices have associated attributes that are frequently represented as vertex or edge weights. furthermore, these weights are often not static, instead changing with time and forming a time series. hence, to fully understand the dynamics of the complex network, we have to consider both network topology and related time series data. in this work, we propose a motif mining approach to identify trend motifs for such purposes. simply stated, a trend motif describes a recurring subgraph where each of its vertices or edges displays similar dynamics over a userdefined period. given this, each trend motif occurrence can help reveal significant events in a complex system; frequent trend motifs may aid in uncovering dynamic rules of change for the system, and the distribution of trend motifs may characterize the global dynamics of the system. here, we have developed efficient mining algorithms to extract trend motifs. our experimental validation using three disparate empirical datasets, ranging from the stock market, world trade, to a protein interaction network, has demonstrated the efficiency and effectiveness of our approach.
solving consensus and semi-supervised clustering problems using nonnegative matrix factorization. consensus clustering and semi-supervised clustering are important extensions of the standard clustering paradigm. consensus clustering (also known as aggregation of clustering) can improve clustering robustness, deal with distributed and heterogeneous data sources and make use of multiple clustering criteria. semi-supervised clustering can integrate various forms of background knowledge into clustering. in this paper, we show how consensus and semi-supervised clustering can be formulated within the framework of nonnegative matrix factorization (nmf). we show that this framework yields nmf-based algorithms that are: (1) extremely simple to implement; (2) provably correct and provably convergent. we conduct a wide range of comparative experiments that demonstrate the effectiveness of this nmf-based approach.
bandit-based algorithms for budgeted learning. we explore the problem of budgeted machine learning, in which the learning algorithm has free access to the training examples' labels but has to pay for each attribute that is specified. this learning model is appropriate in many areas, including medical applications. we present new algorithms for choosing which attributes to purchase of which examples in the budgeted learning model based on algorithms for the multi-armed bandit problem. all of our approaches outperformed the current state of the art. furthermore, we present a new means for selecting an example to purchase after the attribute is selected, instead of selecting an example uniformly at random, which is typically done. our new example selection method improved performance of all the algorithms we tested, both ours and those in the literature.
multilevel belief propagation for fast inference on markov random fields. graph-based inference plays an important role in many mining and learning tasks. among all the solvers for this problem, belief propagation (bp) provides a general and efficient way to derive approximate solutions. however, for large scale graphs the computational cost of bp is still demanding. in this paper, we propose a multilevel algorithm to accelerate belief propagation on markov random fields (mrf). first, we coarsen the original graph to get a smaller one. then, bp is applied on the new graph to get a coarse result. finally the coarse solution is efficiently refined back to derive the original solution. unlike traditional multiresolution approaches, our method features adaptive coarsening and efficient refinement. the above process can be recursively applied to reduce the computational cost remarkably. we theoretically justify the feasibility of our method on gaussian mrfs, and empirically show that it is also effectual on discrete mrfs. the effectiveness of our method is verified in experiments on various inference tasks.
active learning from data streams. in this paper, we address a new research problem on active learning from data streams where data volumes grow continuously and labeling all data is considered expensive and impractical. the objective is to label a small portion of stream data from which a model is derived to predict newly arrived instances as accurate as possible. in order to tackle the challenges raised by data streams' dynamic nature, we propose a classifier ensembling based active learning framework which selectively labels instances from data streams to build an accurate classifier. a minimal variance principle is introduced to guide instance labeling from data streams. in addition, a weight updating rule is derived to ensure that our instance labeling process can adaptively adjust to dynamic drifting concepts in the data. experimental results on synthetic and real-world data demonstrate the performances of the proposed efforts in comparison with other simple approaches. *
depth-based novelty detection and its application to taxonomic research. it is estimated that less than 10 percent of the world's species have been described, yet species are being lost daily due to human destruction of natural habitats. the job of describing the earth's remaining species is exacerbated by the shrinking number of practicing taxonomists and the very slow pace of traditional taxonomic research. in this article, we tackle, from a novelty detection perspective, one of the most important and challenging research objectives in taxonomy new species identification. we propose a unique and efficient novelty detection framework based on statistical depth functions. statistical depth functions provide from the "deepest" point a "center-outward ordering" of multidimensional data. in this sense, they can detect observations that appear extreme relative to the rest of the observations, i.e., novelty. of the various statistical depths, the spatial depth is especially appealing because of its computational efficiency and mathematical tractability. we propose a novel statistical depth, the kernelized spatial depth (ksd) that generalizes the spatial depth via positive definite kernels. by choosing a proper kernel, the ksd can capture the local structure of a data set while the spatial depth fails. observations with depth values less than a threshold are declared as novel. the proposed algorithm is simple in structure: the threshold is the only one parameter for a given kernel. we give an upper bound on the false alarm probability of a depth-based detector, which can be used to determine the threshold. experimental study demonstrates its excellent potential in new species discovery.
parallel mining of frequent closed patterns: harnessing modern computer architectures. inspired by emerging multi-core computer architectures, in this paper we present mt closed, a multi-threaded algorithm for frequent closed itemset mining (fcim). to the best of our knowledge, this is the first fcim parallel algorithm proposed so far. we studied how different duplicate checking techniques, typical of fcim algorithms, may affect this parallelization. we showed that only one of them allows to decompose the global fcim problem into independent tasks that can be executed in any order, and thus in parallel. finally we show how mt closed efficiently harness modern cpus. we designed and tested several parallelization paradigms by investigating static/dynamic decomposition and scheduling of tasks, thus showing its scalability w.r.t. to the number of cpus. we analyzed the cache friendliness of the algorithm. finally, we provided additional speed-up by introducing simd extensions.
statistical learning algorithm for tree similarity. tree edit distance is one of the most frequently used distance measures for comparing trees. when using the tree edit distance, we need to determine the cost of each operation, but this is a labor-intensive and highly skilled task. this paper proposes an algorithm for learning the costs of tree edit operations from training data consisting of pairs of similar trees. to formalize the cost learning problem, we define a probabilistic model for tree alignment that is a variant of tree edit distance. then, the parameters of the model are estimated using the expectation maximization (em) technique. in this paper, we develop an algorithm for parameter learning that is polynomial in time (o(mn2d6)) and space (o(n2d4)) where n, d, and m represent the size of the trees, the maximum degree of trees, and the number of training pairs of trees, respectively.
efficient data sampling in heterogeneous peer-to-peer networks. performing data-mining tasks such as clustering, classification, and prediction on large datasets is an arduous task and, many times, it is an infeasible task given current hardware limitations. the distributed nature of peer-to-peer databases further complicates this issue by introducing an access overhead cost in addition to the cost of sending individual tuples over the network. we propose a two-level sampling approach focusing on peer-to-peer databases for maximizing sample quality given a user-defined communication budget. given that individual peers may have varying cardinality we propose an algorithm for determining the optimal sample rate (the percentage of tuples to sample from a peer) for each peer. we do this by analyzing the variance of individual peers, ultimately minimizing the total variance of the entire sample. by performing local optimization of individual peer sample rates we maximize approximation accuracy of the samples. we also offer several techniques for sampling in peer-to-peer databases given various amounts of known and unknown information about the network and its peers.
lightweight distributed trust propagation. using mobile devices, such as smart phones, people may create and distribute different types of digital content (e.g., photos, videos). one of the problems is that digital content, being easy to create and replicate, may likely swamp users rather than informing them. to avoid that, users may organize content producers that they know and trust in a web of trust. users may then reason about this web of trust to form opinions about content producers with whom they have never interacted before. these opinions will then determine whether content is accepted. the process of forming opinions is called trust propagation. we design a mechanism for mobile devices that effectively propagates trust and that is lightweight and distributed (as opposed to previous work that focuses on centralized propagation). this mechanism uses a graph-based learning technique. we evaluate the effectiveness (predictive accuracy) of this mechanism against a large real-world data set. we also evaluate the computational cost of a j2me implementation on a mobile phone.
social network extraction of academic researchers. this paper addresses the issue of extraction of an academic researcher social network. by researcher social network extraction, we are aimed at finding, extracting, and fusing the `semantic'-based profiling information of a researcher from the web. previously, social network extraction was often undertaken separately in an ad-hoc fashion. this paper first gives a formalization of the entire problem. specifically, it identifies the `relevant documents' from the web by a classifier. it then proposes a unified approach to perform the researcher profiling using conditional random fields (crf). it integrates publications from the existing bibliography datasets. in the integration, it proposes a constraints-based probabilistic model to name disambiguation. experimental results on an online system show that the unified approach to researcher profiling significantly outperforms the baseline methods of using rule learning or classification. experimental results also indicate that our method to name disambiguation performs better than the baseline method using unsupervised learning. the methods have been applied to expert finding. experiments show that the accuracy of expert finding can be significantly improved by using the proposed methods.
mechanism design for clustering aggregation by selfish systems. we propose a market mechanism that can be implemented on clustering aggregation problem among selfish systems, which tend to lie about their correct clustering during aggregation process. our study is the preliminary step toward the development of robust distributed data mining among selfish systems.
scalable collaborative filtering with jointly derived neighborhood interpolation weights. recommender systems based on collaborative filtering predict user preferences for products or services by learning past user-item relationships. a predominant approach to collaborative filtering is neighborhood based (" k-nearest neighbors"), where a user-item preference rating is interpolated from ratings of similar items and/or users. we enhance the neighborhood-based approach leading to substantial improvement of prediction accuracy, without a meaningful increase in running time. first, we remove certain so-called "global effects" from the data to make the ratings more comparable, thereby improving interpolation accuracy. second, we show how to simultaneously derive interpolation weights for all nearest neighbors, unlike previous approaches where each weight is computed separately. by globally solving a suitable optimization problem, this simultaneous interpolation accounts for the many interactions between neighbors leading to improved accuracy. our method is very fast in practice, generating a prediction in about 0.2 milliseconds. importantly, it does not require training many parameters or a lengthy preprocessing, making it very practical for large scale applications. finally, we show how to apply these methods to the perceivably much slower user-oriented approach. to this end, we suggest a novel scheme for low dimensional embedding of the users. we evaluate these methods on the netflix dataset, where they deliver significantly better results than the commercial netflix cinematch recommender system.
exploration of link structure and community-based node roles in network analysis. communities are nodes in a network that are grouped together based on a common set of properties. while the communities and link structures are often thought to be in alignment, it may not be the case when the communities are defined using other external criterion. in this paper we provide a new way to measure the alignment. we also provide a new metric that can be used to estimate the number of communities to which a node is attached. this metric, along with degree, is used to assign a communitybased role to nodes. we demonstrate the usefulness of the community-based node roles by applying them to the influence maximization problem.
document transformation for multi-label feature selection in text categorization. feature selection on multi-label documents for automatic text categorization is an under-explored research area. this paper presents a systematic document transformation framework, whereby the multi-label documents are transformed into single-label documents before applying standard feature selection algorithms, to solve the multi-label feature selection problem. under this framework, we undertake a comparative study on four intuitive document transformation approaches and propose a novel approach called entropy-based label assignment (ela), which assigns the labels weights to a multi-label document based on label entropy. three standard feature selection algorithms are utilized for evaluating the document transformation approaches in order to verify its impact on multi-class text categorization problems. using a svm classifier and two multi-label evaluation benchmark text collections, we show that the choice of document transformation approaches can significantly influence the performance of multi-class categorization and that our proposed document transformation approach ela can achieve better performance than all other approaches.
a generalization of proximity functions for k-means. k-means is a widely used partitional clustering method. a large amount of effort has been made on finding better proximity (distance) functions for k-means. however, the common characteristics of proximity functions remain unknown. to this end, in this paper, we show that all proximity functions that fit k-means clustering can be generalized as k-means distance, which can be derived by a differentiable convex function. a general proof of sufficient and necessary conditions for k-means distance functions is also provided. in addition, we reveal that k-means has a general uniformization effect; that is, k-means tends to produce clusters with relatively balanced cluster sizes. this uniformization effect of k-means exists regardless of proximity functions. finally, we have conducted extensive experiments on various real-world data sets, and the results show the evidence of the uniformization effect. also, we observed that external clustering validation measures, such as entropy and variance of information (vi), have difficulty in measuring clustering quality if data have skewed distributions on class sizes.
recommendation via query centered random walk on k-partite graph. this paper presents an algorithm for recommending items using a diverse set of features. the items are recommended by performing a random walk on the k-partite graph constructed from the heterogenous features. to support personalized recommendation, the random walk must be initiated separately for each user, which is computationally demanding given the massive size of the graph. to overcome this problem, we apply multi-way clustering to group together the highly correlated nodes. a recommendation is then made by traversing the subgraph induced by clusters associated with a user's interest. our experimental results on real data sets demonstrate the efficacy of the proposed algorithm.
binary matrix factorization with applications. an interesting problem in nonnegative matrix factorization (nmf) is to factorize the matrix x which is of some specific class, for example, binary matrix. in this paper, we extend the standard nmf to binary matrix factorization (bmf for short): given a binary matrix x , we want to factorize x into two binary matrices w ,h (thus conserving the most important integer property of the objective matrix x ) satisfying x wh. two algorithms are studied and compared. these methods rely on a fundamental boundedness property of nmf which we propose and prove. this new property also provides a natural normalization scheme that eliminates the bias of factor matrices. experiments on both synthetic and real world datasets are conducted to show the competency and effectiveness of bmf.
weighted additive criterion for linear dimension reduction. linear discriminant analysis (lda) for dimension reduction has been applied to a wide variety of face recognition tasks. however, it has two major problems. first, it suffers from the small sample size problem when dimensionality is greater than the sample size. second, it creates subspaces that favor well separated classes over those that are not. in this paper, we propose a simple weighted criterion for linear dimension reduction that addresses the above two problems associated with lda. in addition, there are well established numerical procedures such as semi-definite programming for efficiently computing the proposed criterion. we demonstrate the efficacy of our proposal and compare it against other competing techniques using a number of examples.
a cascaded approach to biomedical named entity recognition using a unified model. we propose a cascaded approach for extracting biomedical named entities from text documents using a unified model. previous works often ignore the high computational cost incurred by a single-phase approach. we alleviate this problem by dividing the named entity extraction task into a segmentation task and a classification task, reducing the computational cost by an order of magnitude. a unified model, which we term "maximum-entropy margin-based" (memb), is used in both tasks. the memb model considers the error between a correct and an incorrect output during training and helps improve the performance of extracting sparse entity types that occur in biomedical literature. we report experimental evaluations on the genia corpus available from the bionlp/nlpba (2004) shared task, which demonstrate the state-of-the-art performance achieved by the proposed approach.
using significant, positively associated and relatively class correlated rules for associative classification of imbalanced datasets. the application of association rule mining to classification has led to a new family of classifiers which are often referred to as "associative classifiers (acs)". an advantage of acs is that they are rule-based and thus lend themselves to an easier interpretation. rule-based classifiers can play a very important role in applications such as medical diagnosis and fraud detection where "imbalanced data sets" are the norm and not the exception. the focus of this paper is to extend and modify acs for classification on imbalanced data sets using only statistical techniques. we combine the use of statistically significant rules with a new measure, the class correlation ratio ( ccr), to build an ac which we call sparccc. experiments show that in terms of classification quality, sparccc performs comparably on balanced datasets and outperforms other ac techniques on imbalanced data sets. it also has a significantly smaller rule base and is much more computationally efficient.
language-independent set expansion of named entities using the web. set expansion refers to expanding a given partial set of objects into a more complete set. a well-known example system that does set expansion using the web is google sets. in this paper, we propose a novel method for expanding sets of named entities. the approach can be applied to semi-structured documents written in any markup language and in any human language. we present experimental results on 36 benchmark sets in three languages, showing that our system is superior to google sets in terms of mean average precision.
on meta-learning rule learning heuristics. the goal of this paper is to investigate to what extent a rule learning heuristic can be learned from experience. to that end, we let a rule learner learn a large number of rules and record their performance on the test set. subsequently, we train regression algorithms on predicting the test set performance of a rule from its training set characteristics. we investigate several variations of this basic scenario, including the question whether it is better to predict the performance of the candidate rule itself or of the resulting final rule. our experiments on a number of independent evaluation sets show that the learned heuristics outperform standard rule learning heuristics. we also analyze their behavior in coverage space.
understanding discrete classifiers with a case study in gene prediction. the requirement that the models resulting from data mining should be understandable is an uncontroversial requirement. in the data mining literature, however, it plays hardly any role, if at all. in practice, though, understandability is often even more important than, e.g., accuracy. understandability does not mean that models should be simple. it means that one should be able to understand the predictions of models. in this paper we introduce tools to understand arbitrary classifiers defined on discrete data. more in particular, we introduce explanations that provide insight at a local level. they explain why a classifier classifies a data point as it does. for global insight, we introduce attribute weights. the higher the weight of an attribute, the more often it is decisive in the classification of a data point. to illustrate our tools, we describe a case study in the prediction of small genes. this is a notoriously hard problem in bioinformatics.
origami: mining representative orthogonal graph patterns. in this paper, we introduce the concept of -orthogonal patterns to mine a representative set of graph patterns. intuitively, two graph patterns are -orthogonal if their similarity is bounded above by . each -orthogonal pattern is also a representative for those patterns that are at least similar to it. given user defined , [0, 1], the goal is to mine an -orthogonal, -representative set that minimizes the set of unrepresented patterns. we present origami, an effective algorithm for mining the set of representative orthogonal patterns. origami first uses a randomized algorithm to randomly traverse the pattern space, seeking previously unexplored regions, to return a set of maximal patterns. origami then extracts an orthogonal, -representative set from the mined maximal patterns. we show the effectiveness of our algorithm on a number of real and synthetic datasets. in particular, we show that our method is able to extract high quality patterns even in cases where existing enumerative graph mining methods fail to do so.
structure-based statistical features and multivariate time series clustering. we propose a new method for clustering multivariate time series. a univariate time series can be represented by a fixed-length vector whose components are statistical features of the time series, capturing the global structure. these descriptive vectors, one for each component of the multivariate time series, are concatenated, before being clustered using a standard fast clustering algorithm such as k-means or hierarchical clustering. such statistical feature extraction also serves as a dimension-reduction procedure for multivariate time series. we demonstrate the effectiveness and simplicity of our proposed method by clustering human motion sequences: dynamic and high-dimensional multivariate time series. the proposed method based on univariate time series structure and statistical metrics provides a novel, yet simple and flexible way to cluster multivariate time series data efficiently with promising accuracy. the success of our method on the case study suggests that clustering may be a valuable addition to the tools available for human motion pattern recognition research.
rule cubes for causal investigations. with the complexity of modern vehicles tremendously increasing, quality engineers play a key role within today's automotive industry. field data analysis supports corrective actions in development, production and after sales support. we decompose the requirements and show that association rules, being a popular approach to generating explanative models, still exhibit shortcomings. recently proposed interactive rule cubes are a promising alternative. we extend this work by introducing a way of intuitively visualizing and meaningfully ranking them. moreover, we present methods to interactively factorize a problem and validate hypotheses by ranking patterns based on expectations, and by browsing a cube-based network of related influences. all this is currently in use as an interactive tool for warranty data analysis in the automotive industry. a real-world case study shows how engineers successfully use it in identifying root causes of quality issues.
non-redundant multi-view clustering via orthogonalization. typical clustering algorithms output a single clustering of the data. however, in real world applications, data can often be interpreted in many different ways; data can have different groupings that are reasonable and interesting from different perspectives. this is especially true for high-dimensional data, where different feature subspaces may reveal different structures of the data. why commit to one clustering solution while all these alternative clustering views might be interesting to the user. in this paper, we propose a new clustering paradigm for explorative data analysis: find all non-redundant clustering views of the data, where data points of one cluster can belong to different clusters in other views. we present a framework to solve this problem and suggest two approaches within this framework: (1) orthogonal clustering, and (2) clustering in orthogonal subspaces. in essence, both approaches find alternative ways to partition the data by projecting it to a space that is orthogonal to our current solution. the first approach seeks orthogonality in the cluster space, while the second approach seeks orthogonality in the feature space. we test our framework on both synthetic and high-dimensional benchmark data sets, and the results show that indeed our approaches were able to discover varied solutions that are interesting and meaningful. keywords: multi-view clustering, non-redundant clustering, orthogonalization
analyzing and detecting review spam. mining of opinions from product reviews, forum posts and blogs is an important research topic with many applications. however, existing research has been focused on extraction, classification and summarization of opinions from these sources. an important issue that has not been studied so far is the opinion spam or the trustworthiness of online opinions. in this paper, we study this issue in the context of product reviews. to our knowledge, there is still no published study on this topic, although web page spam and email spam have been investigated extensively. we will see that review spam is quite different from web page spam and email spam, and thus requires different detection techniques. based on the analysis of 5.8 million reviews and 2.14 million reviewers from amazon.com, we show that review spam is widespread. in this paper, we first present a categorization of spam reviews and then propose several techniques to detect them.
detecting subdimensional motifs: an efficient algorithm for generalized multivariate pattern discovery. discovering recurring patterns in time series data is a fundamental problem for temporal data mining. this paper addresses the problem of locating subdimensional motifs in real-valued, multivariate time series, which requires the simultaneous discovery of sets of recurring patterns along with the corresponding relevant dimensions. while many approaches to motif discovery have been developed, most are restricted to categorical data, univariate time series, or multivariate data in which the temporal patterns span all of the dimensions. in this paper, we present an expected linear-time algorithm that addresses a generalization of multivariate pattern discovery in which each motif may span only a subset of the dimensions. to validate our algorithm, we discuss its theoretical properties and empirically evaluate it using several data sets including synthetic data and motion capture data collected by an on-body inertial sensor.
optimal subsequence bijection. we consider the problem of elastic matching of sequences of real numbers. since both a query and a target sequence may be noisy, i.e., contain some outlier elements, it is desirable to exclude the outlier elements from matching in order to obtain a robust matching performance. moreover, in many applications like shape alignment or stereo correspondence it is also desirable to have a one-to-one and onto correspondence (bijection) between the remaining elements. we propose an algorithm that determines the optimal subsequence bijection (osb) of a query and target sequence. the osb is efficiently computed since we map the problem's solution to a cheapest path in a dag (directed acyclic graph). we obtained excellent results on standard benchmark time series datasets. we compared osb to dynamic time warping (dtw) with and without warping window. we do not claim that osb is always superior to dtw. however, our results demonstrate that skipping outlier elements as done by osb can significantly improve matching results for many real datasets. moreover, osb is particularly suitable for partial matching. we applied it to the object recognition problem when only parts of contours are given. we obtained sequences representing shapes by representing object contours as sequences of curvatures.
a novel criterion for onset detection: differential information redundancy with application to human movement initiation. a new detection criterion based on the change in the marginal information redundancy is presented. by establishing a link with information theory we are able to give an intuitive interpretation of our criterion. the usefulness of the new criterion is demonstrated for a case study of human movement initiation detection from force and torque signals in activity of daily living tasks. using the new criterion, we achieve a performance that is more in agreement with expert decisions compared with traditional thresholding techniques and the advanced wavelet-based detector and energy detectors.
an efficient spectral algorithm for network community discovery and its applications to biological and social networks. automatic discovery of community structures in complex networks is a fundamental task in many disciplines, including social science, engineering, and biology. recently, a quantitative measure called modularity (q) has been proposed to effectively assess the quality of community structures. several community discovery algorithms have since been developed based on the optimization of q. however, this optimization problem is np-hard, and the existing algorithms have a low accuracy or are computationally expensive. in this paper, we present an efficient spectral algorithm for modularity optimization. when tested on a large number of synthetic or real-world networks, and compared to the existing algorithms, our method is efficient and and has a high accuracy. in addition, we have successfully applied our algorithm to detect interesting and meaningful community structures from real-world networks in different domains, including biology, medicine and social science. due to space limitation, results of these applications are presented in a complete version of the paper available on our website (http://cse.wustl.edu/~jruan/).
connections between mining frequent itemsets and learning generative models. frequent itemsets mining is a popular framework for pattern discovery. in this framework, given a database of customer transactions, the task is to unearth all patterns in the form of sets of items appearing in a sizable number of transactions. we present a class of models called itemset generating models (or igms) that can be used to formally connect the process of frequent itemsets discovery with the learning of generative models. igms are specified using simple probability mass functions (over the space of transactions), peaked at specific sets of items and uniform everywhere else. under such a connection, it is possible to rigorously associate higher frequency patterns with generative models that have greater data likelihoods. this enables a generative model-learning interpretation of frequent itemsets mining. more importantly, it facilitates a statistical significance test which prescribes the minimum frequency needed for a pattern to be considered interesting. we illustrate the effectiveness of our analysis through experiments on standard benchmark data sets.
local probabilistic models for link prediction. one of the core tasks in social network analysis is to predict the formation of links (i.e. various types of relationships) over time. previous research has generally represented the social network in the form of a graph and has leveraged topological and semantic measures of similarity between two nodes to evaluate the probability of link formation. here we introduce a novel local probabilistic graphical model method that can scale to large graphs to estimate the joint co-occurrence probability of two nodes. such a probability measure captures information that is not captured by either topological measures or measures of semantic similarity, which are the dominant measures used for link prediction. we demonstrate the effectiveness of the co-occurrence probability feature by using it both in isolation and in combination with other topological and semantic features for predicting co-authorship collaborations on three real datasets.
sampling for sequential pattern mining: from static databases to data streams. sequential pattern mining is an active field in the domain of knowledge discovery. recently, with the constant progress in hardware technologies, real-world databases tend to grow larger and the hypothesis that a database can be loaded into main-memory for sequential pattern mining purpose is no longer valid. furthermore, the new model of data as a continuous and potentially infinite flow, known as data stream model, call for a pre-processing step to ease the mining operations. since the database size is the most influential factor for mining algorithms we examine the use of sampling over static databases to get approximate mining results with an upper bound on the error rate. moreover, we extend these sampling analysis and present an algorithm based on reservoir sampling to cope with sequential pattern mining over data streams. we demonstrate with empirical results that our sampling methods are efficient and that sequence mining remains accurate over static databases and data streams.
gapprox: mining frequent approximate patterns from a massive network. recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the web, demanding powerful data mining methods. due to inherent noise or data diversity, it is crucial to address the issue of approximation, if one wants to mine patterns that are potentially interesting with tolerable variations. in this paper, we investigate the problem of mining frequent approximate patterns from a massive network and propose a method called gapprox. gapprox not only finds approximate network patterns, which is the key for many knowledge discovery applications on structural data, but also enriches the library of graph mining methodologies by introducing several novel techniques such as: (1) a complete and redundancy-free strategy to explore the new pattern space faced by gapprox; and (2) transform "frequent in an approximate sense" into an anti-monotonic constraint so that it can be pushed deep into the mining process. systematic empirical studies on both real and synthetic data sets show that frequent approximate patterns mined from the worm protein-protein interaction network are biologically interesting and gapprox is both effective and efficient.
a computational approach to style in american poetry. we develop a quantitative method to assess the style of american poems and to visualize a collection of poems in relation to one another. qualitative poetry criticism helped guide our development of metrics that analyze various orthographic, syntactic, and phonemic features. these features are used to discover comprehensive stylistic information from a poem's multi-layered latent structure, and to compute distances between poems in this space. visualizations provide ready access to the analytical components. we demonstrate our method on several collections of poetry, showing that it better delineates poetry style than the traditional word-occurrence features that are used in typical text analysis algorithms. our method has potential applications to academic research of texts, to research of the intuitive personal response to poetry, and to making recommendations to readers based on their favorite poems.
locally constrained support vector clustering. support vector clustering transforms the data into a high dimensional feature space, where a decision function is computed. in the original space, the function outlines the boundaries of higher density regions, naturally splitting the data into individual clusters. the method, however, though theoretically sound, has certain drawbacks which make it not so appealing to the practitioner. namely, it is unstable in the presence of outliers and it is hard to control the number of clusters that it identifies. parametrizing the algorithm incorrectly in noisy settings, can either disguise some objectively present clusters in the data, or can identify a large number of small and nonintuitive clusters. here, we explore the properties of the data in small regions building a mixture of factor analyzers. the obtained information is used to regularize the complexity of the outlined cluster boundaries, by assigning suitable weighting to each example. the approach is demonstrated to be less susceptible to noise and to outline better interpretable clusters than support vector clustering alone.
estmax: tracing maximal frequent itemsets over online data streams. in general, the number of frequent itemsets in a data set is very large. in order to represent them in more compact notation, closed or maximal frequent itemsets (mfis) are used. however, the characteristics of a data stream make such a task be more difficult. for this purpose, this paper proposes a method called estmax that can trace the set of mfis over a data stream. the proposed method maintains the set of frequent itemsets by a prefix tree and extracts all of mfis without any additional superset/subset checking mechanism. upon processing a newly generated transaction, its longest matched frequent itemsets are marked in a prefix tree as candidates for mfis. at the same time, if any subset of these newly marked itemsets has been already marked as a candidate mfi, it is cleared as well. by employing this additional step, it is possible to extract the set of mfis at any moment. the performance of the proposed method is comparatively analyzed by a series of experiments to identify its various characteristics.
finding cohesive clusters for analyzing knowledge communities. documents and authors can be clustered into "knowledge communities" based on the overlap in the papers they cite. we introduce a new clustering algorithm, streemer, which finds cohesive foreground clusters embedded in a diffuse background, and use it to identify knowledge communities as foreground clusters of papers which share common citations. to analyze the evolution of these communities over time, we build predictive models with features based on the citation structure, the vocabulary of the papers, and the affiliations and prestige of the authors. findings include that scientific knowledge communities tend to grow more rapidly if their publications build on diverse information and if they use a narrow vocabulary.
zonal co-location pattern discovery with dynamic parameters. zonal co-location patterns represent subsets of featuretypes that are frequently located in a subset of space (i.e., zone). discovering zonal spatial co-location patterns is an important problem with many applications in areas such as ecology, public health, and homeland defense. however, discovering these patterns with dynamic parameters (i.e., repeated specification of zone and interest measure values according to user preferences) is computationally complex due to the repetitive mining process. also, the set of candidate patterns is exponential in the number of feature types, and spatial datasets are huge. previous studies have focused on discovering global spatial co-location patterns with a fixed interest measure threshold. in this paper, we propose an indexing structure for co-location patterns and propose algorithms (zoloc-miner) to discover zonal colocation patterns efficiently for dynamic parameters. extensive experimental evaluation shows our proposed approaches are scalable, efficient, and outperform na¨ive alternatives.
prism: a primal-encoding approach for frequent sequence mining. sequence mining is one of the fundamental data mining tasks. in this paper we present a novel approach called prism, for mining frequent sequences. prism utilizes a vertical approach for enumeration and support counting, based on the novel notion of prime block encoding, which in turn is based on prime factorization theory. via an extensive evaluation on both synthetic and real datasets, we show that prism outperforms popular sequence mining methods like spade [10], prefixspan [6] and spam [2], by an order of magnitude or more.
succinct matrix approximation and efficient k-nn classification. this work reveals that instead of the polynomial bounds in previous literatures there exists a sharper bound of exponential form for the l2 norm of an arbitrary shaped random matrix. based on the newly elaborated bound, a nonuniform sampling method is presented to succinctly approximate a matrix with a sparse binary one, and thus relieves the computation loads of k-nn classifier in both time and storage. the method is also pass-efficient because sampling and quantizing are combined together in a single step and the whole process can be completed within one pass over the input matrix. in the evaluations on compression ratio and reconstruction error, the sampling method exhibits impressive capability in providing succinct and tight approximations for the input matrices. the most significant finding in the classification experiment is that the k-nn classifier based on the approximation can even outperform the standard one. this provides another strong evidence for the claim that our method is especially capable in capturing intrinsic characteristics.
incremental subspace clustering over multiple data streams. data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. subspace clustering can discover clusters of objects in different subspaces. however, traditional subspace clustering algorithms for static data sets are not readily used for incremental clustering, and is very expensive for frequent re-clustering over dynamically changing stream data. in this paper, we present an efficient incremental subspace clustering algorithm for multiple streams over sliding windows. our algorithm detects all the -cc-clusters, which capture the coherent changing patterns among a set of streams over a set of time points. -cc-clusters are incrementally generated by traversing a directed acyclic graph pdag. we propose efficient insertion and deletion operations to update the pdag dynamically. in addition, effective pruning techniques are applied to reduce the search space. experiments on real data sets demonstrate the performance of our algorithm.
bayesian folding-in with dirichlet kernels for plsi. probabilistic latent semantic indexing (plsi) represents documents of a collection as mixture proportions of latent topics, which are learned from the collection by an expectation maximization (em) algorithm. new documents or queries need to be folded into the latent topic space by a simplified version of the em-algorithm. during plsifolding-in of a new document, the topic mixtures of the known documents are ignored. this may lead to a suboptimal model of the extended collection. our new approach incorporates the topic mixtures of the known documents in a bayesian way during foldingin. that knowledge is modeled as prior distribution over the topic simplex using a kernel density estimate of dirichlet kernels. we demonstrate the advantages of the new bayesian folding-in using real text data.
a semantic kernel for semi-structured documents. natural language processing has emerged as an active field of research in the machine learning community. several methods based on statistical information have been proposed. however, with the linguistic complexity of the texts, semantic-based approaches have been investigated. in this paper, we propose a semantic kernel for semistructured biomedical documents. the semantic meanings of words are extracted using the umls framework. the kernel, with a svm classifier, has been applied to a text categorization task on a medical corpus of free text documents. the results have shown that the semantic kernel outperforms the linear kernel and the naive bayes classifier. moreover, this kernel was ranked in the top ten of the best algorithms among 44 classification methods at the 2007 cmc medical nlp international challenge.
community learning by graph approximation. learning communities from a graph is an important problem in many domains. different types of communities can be generalized as link-pattern based communities. in this paper, we propose a general model based on graph approximation to learn link-pattern based community structures from a graph. the model generalizes the traditional graph partitioning approaches and is applicable to learning various community structures. under this model, we derive a family of algorithms which are flexible to learn various community structures and easy to incorporate the prior knowledge of the community structures. experimental evaluation and theoretical analysis show the effectiveness and great potential of the proposed model and algorithms.
detecting fractures in classifier performance. a fundamental tenet assumed by many classification algorithms is the presumption that both training and testing samples are drawn from the same distribution of data this is the stationary distribution assumption. this entails that the past is strongly indicative of the future. however, in real world applications, many factors may alter the one true model responsible for generating the data distribution both significantly and subtly. in circumstances violating the stationary distribution assumption, traditional validation schemes such as ten-folds and hold-out become poor performance predictors and classifier rankers. thus, it becomes critical to discover the fracture points in classifier performance by discovering the divergence between populations. in this paper, we implement a comprehensive evaluation framework to identify bias, enabling selection of a "correct" classifier given the sample bias. to thoroughly evaluate the performance of classifiers within biased distributions, we consider the following three scenarios: missing completely at random (akin to stationary); missing at random; and missing not at random. the latter reflects the canonical sample selection bias problem.
co-ranking authors and documents in a heterogeneous network. recent graph-theoretic approaches have demonstrated remarkable successes for ranking networked entities, but most of their applications are limited to homogeneous networks such as the network of citations between publications. this paper proposes a novel method for co-ranking authors and their publications using several networks: the social network connecting the authors, the citation network connecting the publications, as well as the authorship network that ties the previous two together. the new co-ranking framework is based on coupling two random walks, that separately rank authors and documents following the pagerank paradigm. as a result, improved rankings of documents and their authors depend on each other in a mutually reinforcing way, thus taking advantage of the additional information implicit in the heterogeneous network of authors and documents.
transitional patterns and their significant milestones. mining frequent patterns in transaction databases has been studied extensively in data mining research. however, most of the existing frequent pattern mining algorithms do not consider the time stamps associated with the transactions. in this paper, we extend the existing frequent pattern mining framework to take into account the time stamp of each transaction and discover patterns whose frequency dramatically changes over time. we define a new type of patterns, called transitional patterns, to capture the dynamic behavior of frequent patterns in a transaction database. transitional patterns include both positive and negative transitional patterns. their frequencies increase/decrease dramatically at some time points of a transaction database. we introduce the concept of significant milestones for a transitional pattern, which are time points at which the frequency of the pattern changes most significantly. moreover, we develop an algorithm to mine from a transaction database the set of transitional patterns along with their significant milestones. our experimental studies on real-world databases illustrate that mining positive and negative transitional patterns is highly promising as a practical and useful approach to discovering novel and interesting knowledge from large databases.
failure prediction in ibm bluegene/l event logs. frequent failures are becoming a serious concern to the community of high-end computing, especially when the applications and the underlying systems rapidly grow in size and complexity. in order to develop effective fault-tolerant strategies, there is a critical need to predict failure events. to this end, we have collected detailed event logs from ibm bluegene/l, which has 128k processors, and is currently the fastest supercomputer in the world. in this study, we first show how the event records can be converted into a data set that is appropriate for running classification techniques. then we apply classifiers on the data, including ripper (a rule-based classifier), support vector machines (svms), a traditional nearest neighbor method, and a customized nearest neighbor method. we show that the customized nearest neighbor approach can outperform ripper and svms in terms of both coverage and precision. the results suggest that the customized nearest neighbor approach can be used to alleviate the impact of failures.
sample selection for maximal diversity. the problem of selecting a sample subset sufficient to preserve diversity arises in many applications. one example is in the design of recombinant inbred lines (ril) for genetic association studies. in this context, genetic diversity is measured by how many alleles are retained in the resulting inbred strains. ril panels that are derived from more than two parental strains, such as the collaborative cross [2, 14], present a particular challenge with regard to which of the many existing lab mouse strains should be included in the initial breeding funnel in order to maximize allele retention. a similar problem occurs in the study of customer reviews when selecting a subset of products with a maximal diversity in reviews. diversity in this case implies the presence of a set of products having both positive and negative ranks for each customer. in this paper, we demonstrate that selecting an optimal diversity subset is an np-complete problem via reduction to set cover. this reduction is sufficiently tight that greedy approximations to the set cover problem directly apply to maximizing diversity. we then suggest a slightly modified subset selection problem in which an initial greedy diversity solution is used to effectively prune an exhaustive search for all diversity subsets bounded from below by a specified coverage threshold. extensive experiments on real datasets are performed to demonstrate the effectiveness and efficiency of our approach.
semi-supervised document clustering via active learning with pairwise constraints. this paper investigates a framework that discovers pairwise constraints for semi-supervised text document clustering. an active learning approach is proposed to select informative document pairs for obtaining user feedbacks. a gain directed document pair selection method that measures how much we can learn by revealing the relationships between pairs of documents is designed. three different models, namely, uncertainty model, generation error model, and objective function model are proposed. language modeling is investigated for representing clusters in the semi-supervised document clustering approach.
improving text classification by using encyclopedia knowledge. the exponential growth of text documents available on the internet has created an urgent need for accurate, fast, and general purpose text classification algorithms. however, the "bag of words" representation used for these classification methods is often unsatisfactory as it ignores relationships between important terms that do not co-occur literally. in order to deal with this problem, we integrate background knowledge in our application: wikipedia into the process of classifying text documents. the experimental evaluation on reuters newsfeeds and several other corpus shows that our classification results with encyclopedia knowledge are much better than the baseline "bag of words" methods.
high-speed function approximation. we address a new learning problem where the goal is to build a predictive model that minimizes prediction time (the time taken to make a prediction) subject to a constraint on model accuracy. our solution is a generic framework that leverages existing data mining algorithms without requiring any modifications to these algorithms. we show a first application of our framework to a combustion simulation problem. our experimental evaluation shows significant improvements over existing methods; prediction time typically is improved by a factor between 2 and 6.
maximum entropy based significance of itemsets. we consider the problem of defining the significance of an itemset. we say that the itemset is significant if we are surprised by its frequency when compared to the frequencies of its sub-itemsets. in other words, we estimate the frequency of the itemset from the frequencies of its sub-itemsets and compute the deviation between the real value and the estimate. for the estimation we use maximum entropy and for measuring the deviation we use kullback-leibler divergence. a major advantage compared to the previous methods is that we are able to use richer models whereas the previous approaches only measure the deviation from the independence model. we show that our measure of significance goes to zero for derivable itemsets and that we can use the rank as a statistical test. our empirical results demonstrate that for our real datasets the independence assumption is too strong but applying more flexible models leads to good results.
computing correlation anomaly scores using stochastic nearest neighbors. this paper addresses the task of change analysis of correlated multi-sensor systems. the goal of change analysis is to compute the anomaly score of each sensor when we know that the system has some potential difference from a reference state. examples include validating the proper performance of various car sensors in the automobile industry. we solve this problem based on a neighborhood preservation principle -if the system is working normally, the neighborhood graph of each sensor is almost invariant against the fluctuations of experimental conditions. here a neighborhood graph is defined based on the correlation between sensor signals. with the notion of stochastic neighborhood, our method is capable of robustly computing the anomaly score of each sensor under conditions that are hard to be detected by other naive methods.
noise modeling with associative corruption rules. this paper presents an active learning approach to the problem of systematic noise inference and noise elimination, specifically the inference of associated corruption (ac) rules. ac rules are defined to simulate a common noise formation process in real-world data, in which the occurrence of an error on one attribute is dependent on several other attribute values. our approach consists of two algorithms, associative corruption forward (acf) and associative corruption backward (acb). algorithm acf is proposed for noise inference, and acb is designed for noise elimination. the experimental results show that the acf algorithm can infer the noise formation correctly, and acb indeed enhances the data quality for supervised learning.
local word bag model for text categorization. many text processing applications adopted the bag of words (bow) model representation of documents, in which each document is represented as a vector of weighted terms or n-grams, and then cosine distance between two vectors is used as the similarity measurement. although the great success in information retrieval and text categorization, the conventional bow model ignores the detailed local text information, i.e. the co-occurrence pattern of words at sentence or paragraph level. in this paper, we propose a novel approach to represent a document as a set of local tf-idf vectors, or what we called local word bags (lwb). by encapsulating local information distributed around a document into multiple lwbs, we can measure the similarity of two documents via the partial match of their corresponding local bags. to perform the matching efficiently, we introduce the local word bag kernel (lwb kernel), a variant of vgpyramid match kernel. the new kernel enables the discriminative machine learning methods like svm to compute the partial matching between two sets of lwbs in linear time after an one time hierarchical clustering procedure over all local bags at the initialization stage. experiments on real world datasets demonstrate the effectiveness of our new approach.
clustering needles in a haystack: an information theoretic analysis of minority and outlier detection. identifying atypical objects is one of the traditional topics in machine learning. recently, novel approaches, e.g., minority detection and one-class clustering, have explored further to identify clusters of atypical objects which strongly contrast from the rest of the data in terms of their distribution or density. this paper analyzes such tasks from an information theoretic perspective. based on information bottleneck formalization, these tasks interpret to increasing the averaged atypicalness of the clusters while reducing the complexity of the clustering. this formalization yields a unifying view of the new approaches as well as the classic outlier detection. we also present a scalable minimization algorithm which exploits the localized form of the cost function over individual clusters. the proposed algorithm is evaluated using simulated datasets and a text classification benchmark, in comparison with an existing method.
general averaged divergence analysis. subspace selection is a powerful tool in data mining. an important subspace method is the fisher rao linear discriminant analysis (lda), which has been successfully applied in many fields such as biometrics, bioinformatics, and multimedia retrieval. however, lda has a critical drawback: the projection to a subspace tends to merge those classes that are close together in the original feature space. if the separated classes are sampled from gaussian distributions, all with identical covariance matrices, then lda maximizes the mean value of the kullback leibler (kl) divergences between the different classes. we generalize this point of view to obtain a framework for choosing a subspace by 1) generalizing the kl divergence to the bregman divergence and 2) generalizing the arithmetic mean to a general mean. the framework is named the general averaged divergence analysis (gada). under this gada framework, a geometric mean divergence analysis (gmda) method based on the geometric mean is studied. a large number of experiments based on synthetic data show that our method significantly outperforms lda and several representative lda extensions.
unsupervised face annotation by mining the web. searching for images of people is an essential task for image and video search engines. however, current search engines have limited capabilities for this task since they rely on text associated with images and video, and such text is likely to return many irrelevant results. we propose a method for retrieving relevant faces of one person by learning the visual consistency among results retrieved from text correlation-based search engines. the method consists of two steps. in the first step, each candidate face obtained from a text-based search engine is ranked with a score that measures the distribution of visual similarities among the faces. faces that are possibly very relevant or irrelevant are ranked at the top or bottom of the list, respectively. the second step improves this ranking by treating this problem as a classification problem in which input faces are classified as ’person-x’ or ’non-person-x’; and the faces are re-ranked according to their relevant score inferred from the classifier’s probability output. to train this classifier, we use a bagging-based framework to combine results from multiple weak classifiers trained using different subsets. these training subsets are extracted and labeled automatically from the rank list produced from the classifier trained from the previous step. in this way, the accuracy of the ranked list increases after a number of iterations. experimental results on various face sets retrieved from captions of news photos show that the retrieval performance improved after each iteration, with the final performance being higher than those of the existing algorithms.
a randomized approach for approximating the number of frequent sets. we investigate the problem of counting the number of frequent (item)sets---a problem known to be intractable in terms of an exact polynomial time computation. in this paper, we show that it is in general also hard to approximate. subsequently, a randomized counting algorithm is developed using the markov chain monte carlo method. while for general inputs an exponential running time is needed in order to guarantee a certain approximation bound, we empirically show that the algorithm still has the desired accuracy on real-world datasets when its running time is capped polynomially.
iterative subgraph mining for principal component analysis. graph mining methods enumerate frequent subgraphs efficiently, but they are not necessarily good features for machine learning due to high correlation among features. thus it makes sense to perform principal component analysis to reducethe dimensionality and create decorrelated features. we present a novel iterative mining algorithm that captures informative patterns corresponding to major entries of top principal components. it repeatedly callsweighted substructure mining where example weights are updated in each iteration. the lanczos algorithm, a standard algorithm of eigen decomposition, is employed to update the weights. in experiments, our patterns are shown to approximate the principal components obtained by frequent mining.
redsom: relative density visualization of temporal changes in cluster structures using self-organizing maps. we introduce a self-organizing map (som) based visualization method that compares cluster structures in temporal datasets using relative density som (redsom) visualization. our method, combined with a distance matrix-based visualization, is capable of visually identifying emerging clusters, disappearing clusters, enlarging clusters, contracting clusters, the shifting of cluster centroids, and changes in cluster density. for example, when a region in a som becomes significantly more dense compared to an earlier som, and well separated from other regions, then the new region can be said to represent a new cluster. the capabilities of redsom are demonstrated using synthetic datasets, as well as real-life datasets from the world bank and the australian taxation office. the results on the real-life datasets demonstrate that changes identified interactively can be related to actual changes. the identification of such cluster changes is important in many contexts, including the exploration of changes in population behavior in the context of compliance and fraud in taxation.
robust time-referenced segmentation of moving object trajectories. trajectory segmentation is the process of partitioning a given trajectory into a small number of homogeneous segments w.r.t. some criteria. conventional segmentation techniques only focus on the spatial features of the movement and could lead to spatially homogeneous segments but with presumably dissimilar temporal structures. furthermore, trajectories could be over-segmented in the presence of outliers. in this paper, we propose a family of three trajectory segmentation methods that takes into account both geospatial and temporal structures of movement for the segmentation and is also robust with respect to time-referenced spatial outliers. the effectiveness of our methods is empirically demonstrated over three real-world datasets.
text mining in radiology reports. medical text mining has gained increasing interest in recent years. radiology reports contain rich information describing radiologist’s observations on the patient’s medical conditions in the associated medical images. however, as most reports are in free text format, the valuable information contained in those reports cannot be easily accessed and used, unless proper text mining has been applied. in this paper, we propose a text mining system to extract and use the information in radiology reports. the system consists of three main modules: a medical finding extractor, a report and image retriever, and a text-assisted image feature extractor. in evaluation, the overall precision and recall for medical finding extraction are 95.5% and 87.9% respectively, and for all modifiers of the medical findings 88.2% and 82.8% respectively. the overall result of report and image retrieval module and text-assisted image feature extraction module is satisfactory to radiologists.
a shrinkage approach for modeling non-stationary relational autocorrelation. recent research has shown that collective classification in relational data often exhibit significant performance gains over conventional approaches that classify instances individually. this is primarily due to the presence of autocorrelation in relational datasets, meaning that the class labels of related entities are correlated and inferences about one instance can be used to improve inferences about linked instances. statistical relational learning techniques exploit relational autocorrelation by modeling global autocorrelation dependencies under the assumption that the level of autocorrelation is stationary throughout the dataset. to date, there has been no work examining the appropriateness of this stationarity assumption. in this paper, we examine two real-world datasets and show that there is significant variance in the autocorrelation dependencies throughout the relational data graphs. we develop a shrinkage technique for modeling this non-stationary autocorrelation and show that it achieves significant accuracy gains over competing techniques that model either local or global autocorrelation dependencies in isolation.
isolation forest. most existing model-based approaches to anomaly detection construct a profile of normal instances, then identify instances that do not conform to the normal profile as anomalies. this paper proposes a fundamentally different model-based method that explicitly isolates anomalies instead of profiles normal points. to our best knowledge, the concept of isolation has not been explored in current literature. the use of isolation enables the proposed method, iforest, to exploit sub-sampling to an extent that is not feasible in existing methods, creating an algorithm which has a linear time complexity with a low constant and a low memory requirement. our empirical evaluation shows that iforest performs favourably to orca, a near-linear time complexity distance-based method, lof and random forests in terms of auc and processing time, and especially in large data sets. iforest also works well in high dimensional problems which have a large number of irrelevant attributes, and in situations where training set does not contain any anomalies.
inlier-based outlier detection via direct density ratio estimation. we propose a new statistical approach to the problem of inlier-based outlier detection, i.e.,finding outliers in the test set based on the training set consisting only of inliers. our key idea is to use the ratio of training and test data densities as an outlier score; we estimate the ratio directly in a semi-parametric fashion without going through density estimation. thus our approach is expected to have better performance in high-dimensional problems. furthermore, the applied algorithm for density ratio estimation is equipped with a natural cross-validation procedure, allowing us to objectively optimize the value of tuning parameters such as the regularization parameter and the kernel width. the algorithm offers a closed-form solution as well as a closed-form formula for the leave-one-out error. thanks to this, the proposed outlier detection me thod is computationally very efficient and is scalable to massive datasets. simulations with benchmark and real-world datasets illustrate the usefulness of the proposed approach.
overlapping matrix pattern visualization: a hypergraph approach. in this work, we study a visual data mining problem: given a set of discovered overlapping submatrices of interest, how can we order the rows and columns of the data matrix to best display these submatrices and their relationships? we find this problem can be converted to the hypergraph ordering problem, which generalizes the traditional minimal linear arrangement (or graph ordering) problem and then we are able to prove the np-hardness of this problem. we propose a novel iterative algorithm which utilize the existing graph ordering algorithm to solve the optimal visualization problem. this algorithm can always converge to a local minimum. the detailed experimental evaluation using a set of publicly available transactional datasets demonstrates the effectiveness and efficiency of the proposed algorithm.
experimental evaluation of the value of structure: how to efficiently exploit interdependencies in sequence labeling. many problems in natural language processing, information extraction or bioinformatics consist in predicting a label for each element of a sequence of observations. the sequence of labels generally presents multiple dependencies that restrict the possible labels the elements can take. therefore, relations between labels intuitively provide information valuable for the prediction. several approaches have been proposed to take advantage of this additional information. however, experimental results show that taking relations into account does not always improve prediction performances, while it significantly increases the computational cost of both learning and prediction. in this work, we aim at both explaining these surprising results and proposing a simple but computationnaly efficient approach for labeling sequences.
a conservative feature subset selection algorithm with missing data. this paper introduces a novel conservative feature subset selection method with incomplete data sets. the method is conservative in the sense that it selects the minimal subset of features that renders the rest of the features independent of the target (the class variable) without making any assumption about the missing data mechanism. this is achieved in the context of determining the markov blanket of the target that reflects the worst-case assumption about the missing data mechanism, including the case when data is not missing at random. an application of the method on synthetic incomplete data is carried out to illustrate its practical relevance. the method is compared against state-of-the-art approaches such as the {expectation maximization} (em) algorithm and the available case technique.
multi-label classification using ensembles of pruned sets. this paper presents a pruned sets method (ps) for multi-label classification. it is centred on the concept of treating sets of labels as single labels. this allows the classification process to inherently take into account correlations between labels. by pruning these sets, ps focuses only on the most important correlations, which reduces complexity and improves accuracy. by combining pruned sets in an ensemble scheme (eps), new label sets can be formed to adapt to irregular or complex data. the results from experimental evaluation on a variety of multi-label datasets show that [e]ps can achieve better performance and train much faster than other multi-label methods.
why stacked models perform effective collective classification. collective classification techniques jointly infer all class labels of a relational data set, using the inferences about one class label to influence inferences about related class labels. kou and cohen recently introduced an efficient relational model based on stacking that, despite its simplicity, has equivalent accuracy to more sophisticated joint inference approaches. using experiments on both real and synthetic data, we show that the primary cause for the performance of the stacked model is the reduction in bias from learning the stacked model on inferred labels rather than true labels. the reduction in variance due to conditional inference also contributes to the effect but it is not as strong. in addition, we show that the performance of the joint inference and stacked learners can be attributed to an implicit weighting of local and relational features at learning time.
stream sequential pattern mining with precise error bounds. sequential pattern mining is an interesting data mining problem with many real-world applications. this problem has been studied extensively in static databases. however, in recent years, emerging applications have introduced a new form of data called data stream. in a data stream, new elements are generated continuously. this poses additional constraints on the methods used for mining such data: memory usage is restricted, the infinitely flowing original dataset cannot be scanned multiple times, and current results should be available on demand.this paper introduces two effective methods for mining sequential patterns from data streams: the ss-be method and the ss-mb method. the proposed methods break the stream into batches and only process each batch once. the two methods use different pruning strategies that restrict the memory usage but can still guarantee that all true sequential patterns are output at the end of any batch. both algorithms scale linearly in execution time as the number of sequences grows, making them effective methods for sequential pattern mining in data streams. the experimental results also show that our methods are very accurate in that only a small fraction of the patterns that are output are false positives. even for these false positives, ss-be guarantees that their true support is above a pre-defined threshold.
space efficient string mining under frequency constraints. let $\db_1$ and $\db_2$ be two databases (i.e. multisets) of $d$ strings, over an alphabet $\sigma$, with overall length $n$. we study the problem of mining discriminative patterns between $\db_1$ and $\db_2$ --- e.g., patterns that are frequent in one database but not in the other, emerging patterns, or patterns satisfying other frequency-related constraints. using the algorithmic framework by hui (cpm 1992), one can solve several variants of this problem in the optimal linear time with the aid of suffix trees or suffix arrays. this stands in high contrast to other pattern domains such as itemsets or subgraphs, where super-linear lower bounds are known. however, the space requirement of existing solutions is $o(n \log n)$ bits, which is not optimal for $|\sigma
comparative evaluation of anomaly detection techniques for sequence data. we present a comparative evaluation of a large number of anomaly detection techniques on a variety of publicly available as well as artificially generated data sets. many of these are existing techniques while some are slight variants and/or adaptations of traditional anomaly detection techniques to sequence data.
semi-supervised learning from general unlabeled data. we consider the problem of semi-supervised learning (ssl) from general unlabeled data, which may contain irrelevant samples. within the binary setting, our model manages to better utilize the information from unlabeled data by formulating them as a three-class ($-1,+1, 0$) mixture, where class $0$ represents the irrelevant data. this distinguishes our work from the traditional ssl problem where unlabeled data are assumed to contain relevant samples only, either $+1$ or $-1$, which are forced to be the same as the given labeled samples. this work is also different from another family of popular models, universum learning (universum means "irrelevant" data), in that the universum need not to be specified beforehand. one significant contribution of our proposed framework is that such irrelevant samples can be automatically detected from the available unlabeled data, even though they are mixed with relevant data. this hence presents a general ssl framework that does not force "clean" unlabeled data.more importantly, we formulate this general learning framework as a semi-definite programming problem, making it solvable in polynomial time. a series of experiments demonstrate that the proposed framework can outperform the traditional ssl on both synthetic and real data.
similarity learning for nearest neighbor classification. in this paper, we propose an algorithm for learning a general class of similarity measures for knn classification. this class encompasses, among others, the standard cosine measure, as well as the dice and jaccard coefficients. the algorithm we propose is an extension of the voted perceptron algorithm and allows one to learn different types of similarity functions (either based on diagonal, symmetric or asymmetric similarity matrices). the results we obtained show that learning similarity measures yields significant improvements on several collections, for two prediction rules: the standard knn rule, which was our primary goal, and a symmetric version of it.
active learning of equivalence relations by minimizing the expected loss using constraint inference. selecting promising queries is the key to effective active learning. in this paper, we investigate selection techniques for the task of learning an equivalence relation where the queries are about pairs of objects. as the target relation satisfies the axioms of transitivity, from one queried pair additional constraints can be inferred. we derive both the upper and lower bound on the number of queries needed to converge to the optimal solution. besides restricting the set of possible solutions, constraints can be used as training data for learning a similarity measure. for selecting queries that result in a large number of meaningful constraints, we present an approximative optimal selection technique that greedily minimizes the expected loss in each round of active learning. this technique makes use of inference of expected constraints. besides the theoretical results, an extensive evaluation for the application of record linkage shows empirically that the proposed selection method leads to both interesting and a high number of constraints.
efficient discovery of statistically significant association rules. searching statistically significant association rules is an important but neglected problem. traditional association rules do not capture the idea of statistical dependence and the resulting rules can be spurious, while the most significant rules may be missing. this leads to erroneous models and predictions which often become expensive.the problem is computationally very difficult, because the significance is not a monotonic property. however, in this paper we prove several other properties, which can be used for pruning the search space. the properties are implemented in the statapriori algorithm, which searches statistically significant, non-redundant association rules. based on both theoretical and empirical observations, the resulting rules are very accurate compared to traditional association rules. in addition, statapriori can work with extremely low frequencies, thus finding new interesting rules.
pseudolikelihood em for within-network relational learning. in this work, we study the problem of \emph{within-network} relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to predict the classes of unlabeled instances in the same graph. we categorize recent work in statistical relational learning into three alternative approaches for this setting: disjoint learning with disjoint inference, disjoint learning with collective inference, and collective learning with collective inference. models from each of these categories has been employed previously in different settings, but to our knowledge there has been no systematic comparison of models from all three categories. in this paper, we develop a novel pseudolikelihood em method that facilitates more general \emph{collective learning} and \emph{collective inference} on partially labeled relational networks. we then compare this method to competing methods from the other categories on both synthetic and real-world data. we show that collective learning and inference with the pseudolikelihood em approach achieves significantly higher accuracy than the other types of models when there are a moderate number of labeled examples in the data graph.
rtm: laws and a recursive generator for weighted time-evolving graphs. how do real, weighted graphs change over time? what patterns, if any, do they obey? earlier studies focus on unweighted graphs, and, with few exceptions, they focus on static snapshots. here, we report patterns we discover on several real, weighted, time-evolving graphs. the reported patterns can help in detecting anomalies in natural graphs, in making link prediction and in providing more criteria for evaluation of synthetic graph generators. we further propose an intuitive and easy way to construct weighted, time-evolving graphs. in fact, we prove that our generator will produce graphs which obey many patterns and laws observed to date. we also provide empirical evidence to support our claims.
start globally, optimize locally, predict globally: improving performance on imbalanced data. class imbalance is a ubiquitous problem in supervised learning and has gained wide-scale attention in the literature. perhaps the most prevalent solution is to applysampling to training data in order improve classifier performance. the typical approach will apply uniform levels of sampling globally. however, we believe that datais typically multi-modal, which suggests sampling shouldbe treated locally rather than globally. it is the purposeof this paper to propose a framework which first identifies meaningful regions of data and then proceeds to findoptimal sampling levels within each. this paper demonstrates that a global classifier trained on data locally sampled produces superior rank-orderings on a wide range ofreal-world and artificial datasets as compared to contemporary global sampling methods.
spotting significant changing subgraphs in evolving graphs. graphs are popularly used to model structural relationships between objects. in many application domains such as social networks, sensor networks and telecommunication, graphs evolve over time. in this paper, we study a new problem of discovering the subgraphs that exhibit significant changes in evolving graphs. this problem is challenging since it is hard to define changing regions that are closely related to the actual changes (i.e., additions/deletions of edges/nodes) in graphs. we formalize the problem, and design an efficient algorithm that is able to identify the changing subgraphs incrementally. our experimental results on real datasets show that our solution is very efficient and the resultant subgraphs are of high quality.
inscy: indexing subspace clusters with in-process-removal of redundancy. subspace clustering aims at detecting clusters in any subspace projection of a high dimensional space. as the number of projections is exponential in the number of dimensions, efficiency is crucial. moreover, the resulting subspace clusters are often highly redundant, i.e. many clusters are detected multiply in several projections. we propose a novel index for efficient subspace clustering in a novel depth-first processing with in-process-removal of redundant clusters for better pruning. thorough experiments on real and synthetic data show that inscy yields substantial efficiency and quality improvements.
a novel method of combined feature extraction for recognition. multimodal recognition is an emerging technique to overcome the non-robustness of the unimodal recognition in real applications. canonical correlation analysis (cca) has been employed as a powerful tool for feature fusion in the realization of such multimodal system. however, cca is the unsupervised feature extraction and it does not utilize the class information of the samples, resulting in the constraint of the recognition performance. in this paper, the class information is incorporated into the framework of cca for combined feature extraction, and a novel method of combined feature extraction for multimodal recognition, called discriminative canonical correlation analysis (dcca), is proposed. the experiments show that dcca outperforms some related methods of both unimodal recognition and multimodal recognition.
nonparametric monotone classification with moca. we describe a monotone classification algorithm called moca that attemptsto minimize the mean absolute prediction error for classification problems with ordered class labels.we first find a monotone classifier with minimum l1 loss on the training sample, and then use a simpleinterpolation scheme to predict the class labels for attribute vectors not present in the training data.we compare moca to the ordinal stochastic dominance learner (osdl), on artificial as well asreal data sets. we show that moca often outperforms osdl with respect to mean absolute prediction error.
efficient feature selection in the presence of multiple feature classes. we present an information theoretic approach to feature selection when the data possesses feature classes. feature classes are pervasive in real data. for example, in gene expression data, the genes which serve as features may be divided into classes based on their membership in gene families or pathways. when doing word sense disambiguation or named entity extraction, features fall into classes including adjacent words, their parts of speech, and the topic and venue of the document the word is in. when predictive features occur predominantly in a small number of feature classes, our information theoretic approach significantly improves feature selection. experiments on real and synthetic data demonstrate substantial improvement in predictive accuracy over the standard $l_0$ penalty-based stepwise and stream wise feature selection methods as well as over lasso and elastic nets, all of which are oblivious to the existence of feature classes.
cleansing noisy data streams. in this paper, we identify a new research problem on cleansing noisy data streams which contain incorrectly labeled training examples. the objective is to accurately identify and remove mislabeled data, such that the prediction models built from the cleansed streams can be more accurate than the ones trained from the raw noisy streams. for this purpose, we first use bias-variance decomposition to derive a maximum variance margin (mvm) principle for stream data cleansing. following this principle, we further propose a local and global filtering (lgf) framework to combine the strength of local noise filtering (within one single data chunk) and global noise filtering (across a number of adjacent data chunks) to identify erroneous data. experimental results on six data streams (including two real-world data streams) demonstrate that lgf significantly outperforms simple methods in identifying noisy examples.
scalable tensor decompositions for multi-aspect data mining. modern applications such as internet traffic, telecommunication records, and large-scale social networks generate massive amounts of data with multiple aspects and high dimensionalities. tensors (i.e., multi-way arrays) provide a natural representation for such data. consequently, tensor decompositions such as tucker become important tools for summarization and analysis.one major challenge is how to deal with high-dimensional, sparse data. in other words, how do we compute decompositions of tensors where most of the entries of the tensor are zero. specialized techniques are needed for computing the tucker decompositions for sparse tensors because standard algorithms do not account for the sparsity of the data. as a result, a surprising phenomenon is observed by practitioners: despite the fact that there is enough memory to store both the input tensors and the factorized output tensors, memory overflows occur during the tensor factorization process. to address this intermediate blowup problem, we propose memory-efficient tucker (met). based on the available memory, met adaptively selects the right execution strategy during the decomposition. we provide quantitative and qualitative evaluation of met on real tensors. it achieves over 1000x space reduction without sacrificing speed; it also allows us to work with much larger tensors that were too big to handle before. finally, we demonstrate a data mining case-study using met.
non-negative matrix factorization on manifold. recently non-negative matrix factorization (nmf) has received a lot of attentions in information retrieval, computer vision and pattern recognition. nmf aims to find two non-negative matrices whose product can well approximate the original matrix. the sizes of these two matrices are usually smaller than the original matrix. this results in a compressed version of the original data matrix. the solution of nmf yields a natural parts-based representation for the data. when nmf is applied for data representation, a major disadvantage is that it fails to consider the geometric structure in the data. in this paper, we develop a graph based approach for parts-based data representation in order to overcome this limitation. we construct an affinity graph to encode the geometrical information and seek a matrix factorization which respects the graph structure. we demonstrate the success of this novel algorithm by applying it on real world problems.
xcrawl: a high-recall crawling method for web mining. web mining systems exploit the redundancy of data published on the web to automatically extract information from existing web documents. the first step in the information extraction process is thus to locate within a limited period of time as many web pages as possible that contain relevant information, a task which is commonly accomplished by applying focused crawling techniques. the performance of such a crawler can be measured by its "recall", i.e. the percentage of documents found and identified as relevant compared to the number of existing documents. a higher recall value implies that more redundant data is available, which in turn leads to better results in the subsequent fact extraction phase. in this paper, we propose xcrawl, a new focused crawling method which outperforms state-of-the-art approaches with respect to recall values achievable within a given period of time. this method is based on a new combination of ideas and techniques used to identify and exploit navigational structures of websites, such as hierarchies, lists or maps. in addition, automatic query generation is applied to rapidly collect web sources containing target documents. the proposed crawling technique was inspired by the requirements of a web mining system developed to extract product and service descriptions and was evaluated in different application scenarios. comparisons with existing focused crawling techniques reveal that the new crawling method leads to a significant increase in recall whilst maintaining precision.
tefe: a time-efficient approach to feature extraction. with the rapid evolution of internet applications, people all over the world are sharing pictures, videos and audios online, and thus, content-based analysis is often demanded. test efficiency is crucial to the success of online information processing. one obstacle to high-speed testing is the time cost of feature extraction for test objects, particularly for objects with complex representation such as images, videos and audios. in this paper, we study the problem of reducing test time cost by extracting cheap but sufficient features. we propose the tefe (time-efficient feature extraction) approach, which balances between the test accuracy and test time cost by extracting a proper subset of features for each test object. in the implementation, tefe trains a sequence of support vector machines and classifies each test object cascadingly. empirical study shows that tefe is time efficient while holding a classification accuracy close to that of using all features. it also shows that the test time is linearly adjustable in tefe.
what sperner family concept class is easy to be enumerated? we study the problem of enumerating concepts in a sperner family concept class using subconcept queries, which is a general problem including maximal frequent itemset mining as its instance. though even the theoretically best known algorithm needs quasi-polynomial time to solve this problem in the worst case, there exist practically fast algorithms for this problem. this is because many instances of this problem in real world have low complexity in some measures. in this paper, we characterize the complexity of sperner family concept class by the vc dimension of its intersection closure and its characteristic dimension, and analyze the worst case time complexity on the enumeration problem of its concepts in terms of the vc dimension. we also showed that the vc dimension of real data used in data mining is actually small by calculating the vc dimension of some real datasets using a new algorithm closely related to the introduced two measures, which does not only solve the problem but also let us know the vc dimension of the intersection closure of the target concept class.
maximum margin clustering with pairwise constraints. maximum margin clustering (mmc), which extends the theory of support vector machine to unsupervised learning, has been attracting considerable attention recently. the existing approaches mainly focus on reducing the computational complexity of mmc. the accuracy of these methods, however, has not always been guaranteed. in this paper, we propose to incorporate additional side-information, which is in the form of pairwise constraints, into mmc to further improve its performance. a set of pairwise loss functions are introduced into the clustering objective function which effectively penalize the violation of the given constraints. we show that the resulting optimization problem can be easily solved via constrained concave-convex procedure (cccp). moreover, for constrained multi-class mmc, we present an efficient cutting-plane algorithm to solve the sub-problem in each iteration of cccp. the experiments demonstrate that the pairwise constrained mmc algorithms considerably outperform the unconstrained mmc algorithms and two other clustering algorithms that exploit the same type of side-information.
metropolis algorithms for representative subgraph sampling. while data mining in chemoinformatics studied graph data with dozens of nodes, systems biology and the internet are now generating graph data with thousands and millions of nodes. hence data mining faces the algorithmic challenge of coping with this significant increase in graph size: classic algorithms for data analysis are often too expensive and too slow on large graphs. while one strategy to overcome this problem is to design novel efficient algorithms, the other is to 'reduce' the size of the large graph by sampling. this is the scope of this paper: we will present novel metropolis algorithms for sampling a 'representative' small subgraph from the original large graph, with 'representative' describing the requirement that the sample shall preserve crucial graph properties of the original graph. in our experiments, we improve over the pioneering work of leskovec and faloutsos (kdd 2006), by producing representative subgraph samples that are both smaller and of higher quality than those produced by other methods from the literature.
one-class collaborative filtering. many applications of collaborative filtering (cf), such as news item recommendation and bookmark recommendation, are most naturally thought of as one-class collaborative filtering (occf) problems. in these problems, the training data usually consist simply of binary data reflecting a user's action or inaction, such as page visitation in the case of news item recommendation or webpage bookmarking in the bookmarking scenario. usually this kind of data are extremely sparse (a small fraction are positive examples), therefore ambiguity arises in the interpretation of the non-positive examples. negative examples and unlabeled positive examples are mixed together and we are typically unable to distinguish them. for example, we cannot really attribute a user not bookmarking a page to a lack of interest or lack of awareness of the page. previous research addressing this one-class problem only considered it as a classification task. in this paper, we consider the one-class problem under the cf setting. we propose two frameworks to tackle occf. one is based on weighted low rank approximation; the other is based on negative example sampling. the experimental results show that our approaches significantly outperform the baselines.
document-word co-regularization for semi-supervised sentiment analysis. the goal of sentiment prediction is to automatically identify whether a given piece of text expresses positive or negative opinion towards a topic of interest. one can pose sentiment prediction as a standard text categorization problem, but gathering labeled data turns out to be a bottleneck. fortunately, background knowledge is often available in the form of prior information about the sentiment polarity of words in a lexicon. moreover, in many applications abundant unlabeled data is also available. in this paper, we propose a novel semi-supervised sentiment prediction algorithm that utilizes lexical prior knowledge in conjunction with unlabeled examples. our method is based on joint sentiment analysis of documents and words based on a bipartite graph representation of the data. we present an empirical study on a diverse collection of sentiment prediction problems which confirms that our semi-supervised lexical models significantly outperform purely supervised and competing semi-supervised techniques.
discovering significant patterns in multi-stream sequences. discovering significant patterns in synchronized multi-stream sequences also known as multi-attribute event sequences (multi-sequences), is an important problem in many domains, including monitoring systems and information retrieval. in this paper we propose a new approach for assessing significance of multi-stream patterns in multi-attribute event sequences. in experiments on physiological multi-stream data we show applicability of our method.
clustering documents with active learning using wikipedia. wikipedia has been applied as a background knowledge base to various text mining problems, but very few attempts have been made to utilize it for document clustering. in this paper we propose to exploit the semantic knowledge in wikipedia for clustering, enabling the automatic grouping of documents with similar themes. although clustering is intrinsically unsupervised, recent research has shown that incorporating supervision improves clustering performance, even when limited supervision is provided. the approach presented in this paper applies supervision using active learning. we first utilize wikipedia to create a concept-based representation of a text document, with each concept associated to a wikipedia article. we then exploit the semantic relatedness between wikipedia concepts to find pair-wise instance-level constraints for supervised clustering, guiding clustering towards the direction indicated by the constraints. we test our approach on three standard text document datasets. empirical results show that our basic document representation strategy yields comparable performance to previous attempts; and adding constraints improves clustering performance further by up to 20%.
frequent subgraph retrieval in geometric graph databases. discovery of knowledge from geometric graph databases is of particular importance in chemistry and biology, because chemical compounds and proteins are represented as graphs with 3d geometric coordinates. in such applications, scientists are not interested in the statistics of the whole database. instead they need information about a novel drug candidate or protein at hand, represented as a query graph. we propose a polynomial-delay algorithm for geometric frequent subgraph retrieval. it enumerates all subgraphs of a single given query graph which are frequent geometric $\epsilon$-subgraphs under the entire class of rigid geometric transformations in a database. by using geometric$\epsilon$-subgraphs, we achieve tolerance against variations in geometry. we compare the proposed algorithm to gspan on chemical compound data, and we show that for a given minimum support the total number of frequent patterns is substantially limited by requiring geometric matching. although the computation time per pattern is larger than for non-geometric graph mining,the total time is within a reasonable level even for small minimum support.
scaling up classifiers to cloud computers. as the size of available datasets has grown from megabytes to gigabytes and now into terabytes, machine learning algorithms and computing infrastructures have continuously evolved in an effort to keep pace. but at large scales, mining for useful patterns still presents challenges in terms of data management as well as computation. these issues can be addressed by dividing both data and computation to build ensembles of classifiers in a distributed fashion, but trade-offs in cost, performance, and accuracy must be considered when designing or selecting an appropriate architecture. in this paper, we present an abstraction for scalable data mining that allows us to explore these trade-offs. data and computation are distributed to a computing cloud with minimal effort from the user, and multiple models for data management are available depending on the workload and system configuration. we demonstrate the performance and scalability characteristics of our ensembles using a wide variety of datasets and algorithms on a condor-based pool with chirp to handle the storage.
measuring proximity on graphs with side information. this paper studies how to incorporate side information (such as users' feedback) in measuring node proximity on large graphs. our method (prosin) is motivated by the well-studied random walk with restart (rwr). the basic idea behind prosin is to leverage side information to refine the graph structure so that the random walk is biased towards/away from some specific zones on the graph. our case studies demonstrate that prosin is well-suited in a variety of applications, including neighborhood search, center-piece subgraphs, and image caption. given the potential computational complexity of prosin, we also propose a fast algorithm (fast-prosin) that exploits the smoothness of the graph structures with/without side information. our experimental evaluation shows that fast-prosin achieves significant speedups (up to 49x) over straightforward implementations.
clustering geospatial objects via hidden markov random fields. this paper addresses the problem of clustering objects located and correlated geographically and containing multiple attributes. for the clustering problem, it is necessary to consider both the similarities of the attributes and the spatial dependencies of the objects. a new clustering framework using hidden markov random fields (hmrfs) and gaussian distributions and new potential models of hmrfs for irregularly located geospatial objects are proposed in this paper. experimental results for systematic data and two real-world data showed the availability of the proposed algorithms.
boosting relational sequence alignments. the task of aligning sequences arises in many applications. classical dynamic programming approaches require the explicit state enumeration in the reward model. this is often impractical: the number of states grows very quickly with the number of domain objects and relations among these objects. relational sequence alignment aims at exploiting symbolic structure to avoid the full enumeration. this comes at the expense of a more complex reward model selection problem: virtually infinitely many abstraction levels have to be explored. in this paper, we apply gradient-based boosting to leverage this problem. specifically, we show how to reduce the learning problem to a series of relational regressions problems. the main benefit of this is that interactions between states variables are introduced only as needed, so that the potentially infinite search space is not explicitly considered. as our experimental results show, this boosting approach can significantly improve upon established results in challenging applications.
anti-monotonic overlap-graph support measures. in graph mining, a frequency measure is anti-monotonic if the frequency of a pattern never exceeds the frequency of a subpattern. the efficiency and correctness of most graph pattern miners relies critically on this property. we study the case where the dataset is a single graph. vanetik, gudes and shimony already gave sufficient and necessary conditions for anti-monotonicity of measures depending only on the edge-overlaps between the intances of the pattern in a labeled graph. we extend these results to homomorphisms, isomorphisms and homeomorphisms on both labeled and unlabeled, directed and undirected graphs, for vertex and edge overlap. we show a set of reductions between the different morphisms that preserve overlap. we also prove that the popular maximum independent set measure assigns the minimal possible meaningful frequency, introduce a new measure based on the minimum clique partition that assigns the maximum possible meaningful frequency and introduce a new measure sandwiched between the former two based on the poly-time computable lovasz theta-function.
disco: distributed co-clustering with map-reduce: a case study towards petabyte-scale end-to-end mining. huge datasets are becoming prevalent; even as researchers, we now routinely have to work with datasets that are up to a few terabytes in size. interesting real-world applications produce huge volumes of messy data. the mining process involves several steps, starting from pre-processing the raw data to estimating the final models. as data become more abundant, scalable and easy-to-use tools for distributed processing are also emerging. among those, map-reduce has been widely embraced by both academia and industry. in database terms, map-reduce is a simple yet powerful execution engine, which can be complemented with other data storage and management components, as necessary. in this paper we describe our experiences and findings in applying map-reduce, from raw data to final models, on an important mining task. in particular, we focus on co-clustering, which has been studied in many applications such as text mining, collaborative filtering, bio-informatics, graph mining. we propose the distributed co-clustering (disco) framework, which introduces practical approaches for distributed data pre-processing, and co-clustering. we develop disco using hadoop, an open source map-reduce implementation. we show that disco can scale well and efficiently process and analyze extremely large datasets (up to several hundreds of gigabytes) on commodity hardware.
prediction of skin penetration using machine learning methods. improving predictions of the skin permeability coefficient is a difficult problem. it is also an important issue with the increasing use of skin patches as a means of drug delivery. in this work, we apply k-nearest-neighbour regression, single layer networks, mixture of experts and gaussian processes to predict the permeability coefficient. we obtain a considerable improvement over the quantitative structure-activity relationship (qsars) predictors. we show that using five features, which are molecular weight, solubility parameter, lipophilicity, the number of hydrogen bonding acceptor and donor groups, can produce better predictions than the one using only lipophilicity and the molecular weight. the gaussian process regression with five compound features gives the best performance in this work.
a novel language-model-based approach for image object mining and re-ranking. one leading framework for image object mining is the bag-of-words (bow) approach. the idea is to encode an image as a collection of visual words of the quantized local patches. objects in the image can then be retrieved through inferring the semantic topics associated with the set of visual words. however, the visual bow mining framework is apt to suffer from the so-called term-mismatch problem (a.k.a. vocabulary problem). this is caused by the poverty of query information, and consequently becomes an obstacle to deal with synonymy (i.e., different visual words for describing the same object). in this paper, we propose a novel language-model-based approach with pseudo-relevance feedback for addressing the vocabulary problem in visual bow mining. we employ the pseudo positive images produced in response to the original query as a set of “cues” to gradually refine the query language model. unlike traditional approaches that only ruggedly append feedback information into the original query, the proposed approach reconstructs the query language model with finer granularities so that the query concepts can be captured more accurately. the proposed approach is experimentally evaluated using two different types of image object databases. our algorithms are shown to bring significant improvement in the retrieval accuracy over a non-feedback baseline, and achieve better performance than conventional feedback approaches.
bayesian co-clustering. in recent years, co-clustering has emerged as a powerful data mining tool that can analyze dyadic data connecting two entities. however, almost all existing co-clustering techniques are partitional, and allow individual rows and columns of a data matrix to belong to only one cluster. several current applications, such as recommendation systems and market basket analysis, can substantially benefit from a mixed membership of rows and columns. in this paper, we present bayesian co-clustering (bcc) models, that allow a mixed membership in row and column clusters. bcc maintains separate dirichlet priors for rows and columns over the mixed membership and assumes each observation to be generated by an exponential family distribution corresponding to its row and column clusters. we propose a fast variational algorithm for inference and parameter estimation. the model is designed to naturally handle sparse matrices as the inference is done only based on the non-missing entries. in addition to finding a co-cluster structure in observations, the model outputs a low dimensional co-embedding, and accurately predicts missing values in the original matrix. we demonstrate the efficacy of the model through experiments on both simulated and real data.
balancing spectral clustering for segmenting spatio-temporal observations of multi-agent systems. we examine the application of spectral clustering for breaking up the behavior of a multi-agent system in space and time into smaller, independent elements. we cluster observations of individualentities in order to identify significant changes in the parameter space (like spatial position)and detect temporal alterations of behavior within the same framework. data is also influenced byknowledge about important events. clusters are pre-processed at each step of the iterative subdivision to make the algorithm invariant against spatial scaling, rotation, replay speed andvarying sampling frequency. a method is presented to balance spatial and temporal segmentation based on the expected group size. we demonstrate our results by analyzing the outcomes of acomputer game.
seqstream: mining closed sequential patterns over stream sliding windows. previous studies have shown mining closed patterns provides more benefits than mining the complete set of frequent patterns, since closed pattern mining leads to more compact results and more efficient algorithms. it is quite useful in a data stream environment where memory and computation power are major concerns. this paper studies the problem of mining closed sequential patterns over data stream sliding windows. a synopsis structure ist (inverse closed sequence tree) is designed to keep inverse closed sequential patterns in current window. an efficient algorithm seqstream is developed to mine closed sequential patterns in stream windows incrementally, and various novel strategies are adopted in seqstream to prune search space aggressively. extensive experiments on both real and synthetic data sets show that seqstream outperforms prefixspan, clospan and bide by a factor of about one to two orders of magnitude.
on locally linear classification by pairwise coupling. locally linear classification by pairwise coupling addresses a nonlinear classification problem by three basic phases: decompose the classes of complex concepts into linearly separable subclasses, learn a linear classifier for each pair, and combine pairwise classifiers into a single classifier. a number of methods have been proposed in this framework. however, these methods have two major deficiencies: 1) lack of systematic evaluation of this framework; 2) naive application of clustering algorithms to generate subclasses. this paper proves the equivalence between three popular combination schemas under general settings, defines several global criterion functions for measuring the goodness of subclasses, and presents a supervised greedy clustering algorithm to optimize the proposed criterion functions. extensive experiments were conducted to validate the effectiveness of the proposed techniques.
interpreting pet scans by structured patient data: a data mining case study in dementia research. one of the goals of medical research in the area of dementia is to correlate images of the brain with other variables, for instance, demographic information or outcomes of clinical tests. the usual approach is to select a subset of patients based on such variables and analyze the images associated with those patients. in this paper, we apply data mining techniques to take the opposite approach: we start with the images and explain the differences and commonalities in terms of the other variables. in the first step, we cluster pet scans of patients to form groups sharing similar features in brain metabolism. to the best of our knowledge, it is the first time ever that clustering is applied to whole pet scans. in the second step, we explain the clusters by relating them to non-image variables. to do so, we employ rsd, an algorithm for relational subgroup discovery, with the cluster membership of patients as target variable. our results enable interesting interpretations of differences in brain metabolism in terms of demographic and clinical variables. the approach was implemented and tested on an exceptionally large pre-existing data collection of patients with different types of dementia. it comprises 10 gb of image data from 454 pet scans, and 42 variables from psychological and demographical data organized in 11 relations of a relational database. we believe that explaining medical images in terms of other variables (patient records, demographic information, etc.) is a challenging new and rewarding area for data mining research.
text cube: computing ir measures for multidimensional text database analysis. since jim gray introduced the concept of ”data cube” in 1997, data cube, associated with online analytical processing (olap), has become a driving engine in data warehouse industry. because the boom of internet has given rise to an ever increasing amount of text data associated with other multidimensional information, it is natural to propose a data cube model that integrates the power of traditional olap and ir techniques for text. in this paper, we propose a text-cube model on multidimensional text database and study effective olap over such data. two kinds of hierarchies are distinguishable inside: dimensional hierarchy and term hierarchy. by incorporating these hierarchies, we conduct systematic studies on efficient text-cube implementation, olap execution and query processing. our performance study shows the high promise of our methods.
clustering uncertain data using voronoi diagrams. we study the problem of clustering uncertain objects whose locations are described by probability density functions (pdf). we show that the uk-means algorithm, which generalises the k-means algorithm to handle uncertain objects, is very inefficient. the inefficiency comes from the fact that uk-means computes expected distances (ed) between objects and cluster representatives. for arbitrary pdf's, expected distances are computed by numerical integrations, which are costly operations. we propose pruning techniques that are based on voronoi diagrams to reduce the number of expected distance calculation. these techniques are analytically proven to be more effective than the basic bounding-box-based technique previous known in the literature. we conduct experiments to evaluate the effectiveness of our pruning techniques and to show that our techniques significantly outperform previous methods.
scs: a new similarity measure for categorical sequences. measuring the similarity between categorical sequences is a fundamental process in many data mining applications. a key issue is to extract and make use of significant features hidden behind the chronological and structural dependencies found in these sequences. almost all existing algorithms designed to perform this task are based on the matching of patterns in chronological order, but such sequences often have similar structural features in chronologically different positions. in this paper we propose scs, a novel method for measuring the similarity between categorical sequences, based on an original pattern matching scheme that makes it possible to capture chronological and non-chronological dependencies. scs captures significant patterns that represent the natural structure of sequences, and reduces the influence of those representing noise. it constitutes an effective approach for measuring the similarity of data such as biological sequences, natural language texts and financial transactions. to show its effectiveness, we have tested scs extensively on a range of datasets, and compared the results with those obtained by various mainstream algorithms.
direct zero-norm optimization for feature selection. zero-norm, defined as the number of non-zero elements in a vector, is an ideal quantity for feature selection. however, minimization of zero-norm is generally regarded as a combinatorially difficult optimization problem. in contrast to previous methods that usually optimize a surrogate of zero-norm, we propose a direct optimizationmethod to achieve zero-norm for feature selection in this paper. based on expectation maximization (em), this method boils down to solving a sequence of quadratic programming problems and hence can be practically optimized in polynomial time. we show that the proposed optimization technique has a nice bayesian interpretation and converges to the true zero norm asymptotically, provided that agood starting point is given. following the scheme of our proposed zero-norm, we even show that an arbitrary-norm based support vector machine can be achieved in polynomial time. a series of experiments demonstrate that our proposed em based zero-norm outperforms other state-of-the-art methods for feature selection on biological microarray data and uci data, in terms of both the accuracy and the learning efficiency.
support vector regression for censored data (svrc): a novel tool for survival analysis. a crucial challenge in predictive modeling for survival analysis is managing censored observations in the data. the cox proportional hazards model is the standard tool for the analysis of continuous censored survival data. we propose a novel machine learning algorithm, support vector regression for censored data (svrc) for improved analysis of medical survival data. svrc leverages the high-dimensional capabilities of traditional svr while adapting it for use with censored data through a modified asymmetric loss/penalty function which allows censored (left and right censored) data to be processed. we applied the new algorithm to predict the recurrence and disease progression of prostate cancer, breast cancer and lung cancer. compared with the traditional cox model, svrc achieves significant improvement in overall accuracy as well as in the ability to identify high-risk and low-risk patient populations.
mining large networks with subgraph counting. the problem of mining frequent patterns in networks has many applications, including analysis of complex networks, clustering of graphs, finding communities in social networks, and indexing of graphical and biological databases. despite this wealth of applications, the current state of the art lacks algorithmic tools for counting the number of subgraphs contained in a large network. in this paper we develop data-stream algorithms that approximate the number of all subgraphs of three and four vertices in directed and undirected networks. we use the frequency of occurrence of all subgraphs to prove their significance in order to characterize different kinds of networks: we achieve very good precision in clustering networks with similar structure. the significance of our method is supported by the fact that such high precision cannot be achieved when performing clustering based on simpler topological properties, such as degree, assortativity, and eigenvector distributions. we have also tested our techniques using swap randomization.
exploiting local and global invariants for the management of large scale information systems. this paper presents a data oriented approach to modeling the complex computing systems, in which an ensemble of correlation models are discovered to represent the system status. if the discovered correlations can continually hold under different user scenarios and workloads, they are regarded as invariants of the information system. in our previous work, we have developed an algorithm to automatically search the invariants between any pair of system attributes, which we call local invariants. however that method is unable to deal with the high order dependency models due to the combinatorial explosion of search space. in this paper we use bayesian regression technique to discover those high order correlation models, called global invariants. we treat each attribute as a response variable in turn and express its dependency with the other attributes in a regression model. by adding the prior constraint of laplacian distribution to the regression coefficients, we can find the solution in which only the correlated attributes with respect to the response have nonzero regression coefficients. after that we further consider the temporal dependencies of those extracted attributes by incorporating their past observations. we also provide a confidence metric and a validation procedure to measure the reliability of learned models. if the model does not break down in the validation, it is regarded as a true invariant of the system. experimental results on a real wireless networking system show that the discovered invariants can be used to effectively detect system failures as well as provide valuable information about the failure source.
collaborative filtering for implicit feedback datasets. a common task of recommender systems is to improve customer experience through personalized recommendations based on prior implicit feedback. these systems passively track different sorts of user behavior, such as purchase history, watching habits and browsing activity, in order to model user preferences. unlike the much more extensively researched explicit feedback, we do not have any direct input from the users regarding their preferences. in particular, we lack substantial evidence on which products consumer dislike. in this work we identify unique properties of implicit feedback datasets. we propose treating the data as indication of positive and negative preference associated with vastly varying confidence levels. this leads to a factor model which is especially tailored for implicit feedback recommenders. we also suggest a scalable optimization procedure, which scales linearly with the data size. the algorithm is used successfully within a recommender system for television shows. it compares favorably with well tuned implementations of other known methods. in addition, we offer a novel way to give explanations to recommendations given by this factor model.
collective latent dirichlet allocation. in this paper, we propose a new variant of latent dirichlet allocation (lda): collective lda (c-lda), for multiple corpora modeling. c-lda combines multiple corpora during learning such that it can transfer knowledge from one corpus to another; meanwhile it keeps a discriminative node which represents the corpus id to constrain the learned topics in each corpus. compared with lda locally applied to the target corpus, c-lda results in refined topic-word distribution, while compared with applying lda globally and straightforwardly to the combined corpus, c-lda keeps each topic only for one corpus. we demonstrate that c-lda has improved performance with these advantages by experiments on several benchmark document data sets.
alert detection in system logs. we present nodeinfo, an unsupervised algorithm for anomaly detection in system logs. we demonstrate nodeinfo's effectiveness on data from four of the world's most powerful supercomputers: using logs representing over 746 million processor-hours, in which anomalous events called alerts were manually tagged for scoring, we aim to automatically identify the regions of the log containing those alerts. we formalize the alert detection task in these terms, describe how nodeinfo uses the information entropy of message terms to identify alerts, and present an online version of this algorithm, which is now in production use. this is the first work to investigate alert detection on (several) publicly-available supercomputer system logs, thereby providing a reproducible performance baseline.
temporal-relational classifiers for prediction in evolving domains. many relational domains contain temporal information and dynamics that are important to model (e.g., social networks, protein networks). however, past work in relational learning has focused primarily on modeling static "snapshots" of the data and has largely ignored the temporal dimension of these data. in this work, we extend relational techniques to temporally-evolving domains and outline a representational framework that is capable of modeling both temporal and relational dependencies in the data. we develop efficient learning and inference techniques within the framework by considering a restricted set of temporal-relational dependencies and using parameter-tying methods to generalize across relationships and entities. more specifically, we model dynamic relational data with a two-phase process, first summarizing the temporal-relational information with kernel smoothing, and then moderating attribute dependencies with the summarized relational information. we develop a number of novel temporal-relational models using the framework and then show that the current approaches to modeling static relational data are special cases within the framework. we compare the new models to the competing static relational methods on three real-world datasets and show that the temporal-relational models consistently outperform the relational models that ignore temporal information - achieving significant reductions in error ranging from 15% to 70%.
on-line lda: adaptive topic models for mining text streams with applications to topic detection and tracking. this paper presents online topic model (olda), a topic model that automatically captures the thematic patterns and identifies emerging topics of text streams and their changes over time. our approach allows the topic modeling framework, specifically the latent dirichlet allocation (lda) model, to work in an online fashion such that it incrementally builds an up-to-date model (mixture of topics per document and mixture of words per topic) when a new document (or a set of documents) appears. a solution based on the empirical bayes method is proposed. the idea is to incrementally update the current model according to the information inferred from the new stream of data with no need to access previous data. the dynamics of the proposed approach also provide an efficient mean to track the topics over time and detect the emerging topics in real time. our method is evaluated both qualitatively and quantitatively using benchmark datasets. in our experiments, the olda has discovered interesting patterns by just analyzing a fraction of data at a time. our tests also prove the ability of olda to align the topics across the epochs with which the evolution of the topics over time is captured. the olda is also comparable to, and sometimes better than, the original lda in predicting the likelihood of unseen documents.
comparison of cluster representations from partial second- to full fourth-order cross moments for data stream clustering. under seven external clustering evaluation measures, a comparison is made for cluster representations from the partial second order to the fourth order in data stream clustering. two external clustering evaluation measures, purity and cross entropy, adopted for data stream clustering performance evaluation in the past, penalize the performance of an algorithm when each hypothesized cluster contains points in different target classes or true clusters, while ignoring the issue of points in a target class falling into different hypothesized clusters. the seven measures will address both sides of the clustering performance. the represented geometry by the partial second-order statistics of a cluster is non-oblique ellipsoidal and cannot describe the orientation, asymmetry, or peakedness of a cluster. the higher-order cluster representation presented in this paper introduces the third and fourth cross moments, enabling the cluster geometry to be beyond an ellipsoid. the higher-order statistics allow two clusters with different representations to merge into a multivariate normal cluster, using normality tests based on multivariate skewness and kurtosis. the clustering performance under the seven external clustering evaluation measures with a synthetic and two real data streams demonstrates the effectiveness of the higher-order cluster representations.
a generative probabilistic model for multi-label classification. traditional discriminative classification method makes little attempt to reveal the probabilistic structure and the correlation within both input and output spaces. in the scenario of multi-label classification, most of the classifiers simply assume the predefined classes are independently distributed, which would definitely hinder the classification performance when there are intrinsic correlations between the classes. in this article, we propose a generative probabilistic model, the correlated labeling model (col model), to formulate the correlation between different classes. the col model is presented to capture the correlation between classes and the underlying structures via the latent random variables in a supervised manner. we develop a variational procedure to approximate the posterior distribution and employ the em algorithm for the empirical bayes parameter estimation. in our evaluations, the proposed model achieved promising results on various data sets.
finding alternative clusterings using constraints. the aim of data mining is to find novel and actionable insights. however, most algorithms typically just find a single explanation of the data even though alternatives could exist. in this work, we explore a general purpose approach to find an alternative clustering of the data with the aid of must-link and cannot-link constraints. this problem has received little attention in the literature and since our approach can be incorporated into the many clustering algorithms that use a distance function, compares favorably with existing work.
releasing the svm classifier with privacy-preservation. support vector machine (svm) is a widely used tool in classification problem. svm solves a quadratic optimization problem to decide which instances of training dataset are support vectors, i.e., the necessarily informative instances to form the classifier. the support vectors are intact tuples taken from the training dataset. releasing the svm classifier to public use or shipping the svm classifier to clients will disclose the private content of support vectors, violating the privacy-preservation requirement in some legal or commercial reasons. to the best of our knowledge, there has not been work extending the notion of privacy-preservation to releasing the svm classifier. in this paper, we propose an approximation approach which post-processes the svm classifier to protect the private content of support vectors. this approach is designed for the commonly used gaussian radial basis function kernel. by applying this post-processor on the svm classifier, the resulted privacy-preserving svm classifier can be publicly released without exposing the private content of support vectors and is able to provide comparable classification accuracy to the original svm classifier.
learning by propagability. in this paper, we present a novel feature extraction framework, called learning by propagability. the whole learning process is driven by the philosophy that the data labels and optimal feature representation can constitute a harmonic system, namely, the data labels are invariant with respect to the propagation on the similarity-graph constructed by the optimal feature representation. based on this philosophy, a unified formulation for learning by propagability is proposed for both supervised and semi-supervised configurations. specifically, this formulation offers the semi-supervised learning two characteristics: 1) unlike conventional semi-supervised learning algorithms which mostly include at least two parameters, this formulation is parameter-free; and 2) the formulation unifies the label propagation and optimal representation pursuing, and thus the label propagation is enhanced by benefiting from the graph constructed with the derived optimal representation instead of the original representation. extensive experiments on uci toy data, handwritten digit recognition, and face recognition all validate the effectiveness of our proposed learning framework compared with the state-of-the-art methods for feature extraction and semi-supervised learning.
unsupervised cross-domain learning by interaction information co-clustering. in real-world data mining applications, one often has access to multiple datasets that are relevant to the task at hand. however, learning from such datasets can be difficult as they are often drawn from different domains, i.e., not identically distributed or differ in class or feature sets. in this paper, we consider the problem of learning the class structures %, unique and shared, of related domains in an unsupervised manner. its setting generalizes that of information filtering and novelty detection applications which addresses both known and unknown classes. we propose a co-clustering framework for estimating and adapting the class structures of two related domains, {enabling the analyses of shared and unique classes.} we define an objective function using interaction information to take account of the divergence between the corresponding clusters of respective domains. we present an iterative algorithm which alternates object and feature clustering and converges to a local minimum of the objective function. we present empirical results using text benchmarks, comparing the proposed algorithm and combinations of conventional approaches in problems of partitioning documents and detecting unknown topics.
modeling and predicting the helpfulness of online reviews. online reviews provide a valuable resource for potential customers to make purchase decisions. however, the sheer volume of available reviews as well as the large variations in the review quality present a big impediment to the effective use of the reviews, as the most helpful reviews may be buried in the large amount of low quality reviews. the goal of this paper is to develop models and algorithms for predicting the helpfulness of reviews, which provides the basis for discovering the most helpful reviews for given products. we first show that the helpfulness of a review depends on three important factors: the reviewer’s expertise, the writing style of the review, and the timeliness of the review. based on the analysis of those factors, we present a nonlinear regression model for helpfulness prediction. our empirical study on the imdb movie reviews dataset demonstrates that the proposed approach is highly effective.
a probability model for projective clustering on high dimensional data. clustering high dimensional data is a big challenge in data mining due to the curse of dimensionality. to solve this problem, projective clustering has been defined as an extension of traditional clustering that seeks to find projected clusters in subsets of dimensions of a data space. in this paper, the problem of modeling projected clusters is first discussed, and an extended gaussian model is proposed. second, a general objective criterion used with $k$-means type projective clustering is presented based on the model. finally, the expressions to learn model parameters are derived and then used in a new algorithm named fpc to perform fuzzy clustering on high dimensional data. the experimental results on document clustering show the effectiveness of the proposed clustering model.
filling in the blanks - krimp minimisation for missing data. many data sets are incomplete. for correct analysis of such data, one can either use algorithms that are designed to handle missing data or use imputation. imputation has the benefit that it allows for any type of data analysis. obviously, this can only lead to proper conclusions if the provided data completion is both highly accurate and maintains all statistics of the original data. in this paper, we present three data completion methods that are built on the mdl-based {\sc krimp} algorithm. here, we also follow the mdl principle, i.e. the completed database that can be compressed best, is the best completion because it adheres best to the patterns in the data. by using local patterns, as opposed to a global model, krimp captures the structure of the data in detail. experiments show that both in terms of accuracy and expected differences of any marginal, better data reconstructions are provided than the state of the art, structural em.
supervised inductive learning with lotka-volterra derived models. we present a classification algorithm built on our adaptation of the generalized lotka-volterra model, well-known in mathematical ecology. the training algorithm itself consists only of computing several scalars, per each training vector, using a single global user parameter and then solving a linear system of equations. construction of the system matrix is driven by our model and based on kernel functions. the model allows an interesting point of view of kernels' role in the inductive learning process. we describe the model through axiomatic postulates. finally, we present the results of the preliminary validation experiments.
latent dirichlet allocation and singular value decomposition based multi-document summarization. multi-document summarization deals with computing a summary for a set of related articles such that they give the user a general view about the events. one of the objectives is that the sentences should cover the different events in the documents with the information covered in as few sentences as possible. latent dirichlet allocation can breakdown these documents into different topics or events. however to reduce the common information content the sentences of the summary need to be orthogonal to each other since orthogonal vectors have the lowest possible similarity and correlation between them. singular value decompositions used to get the orthogonal representations of vectors and representing sentences as vectors, we can get the sentences that are orthogonal to each other in the lda mixture model weighted term domain. thus using lda we find the different topics in the documents and using svd we find the sentences that best represent these topics. finally we present the evaluation of the algorithms on the duc2002 corpus multi-document summarization tasks using the rouge evaluator to evaluate the summaries. compared to duc 2002 winners, our algorithms gave significantly better rouge-1 recall measures.
cost-sensitive parsimonious linear regression. we examine linear regression problems where some features may only be observable at a cost (e.g., in medical domains where features may correspond to diagnostic tests that take time and costs money). this can be important in the context of data mining, in order to obtain the best predictions from the data on a limited cost budget. we define a parsimonious linear regression objective criterion that jointly minimizes prediction error and feature cost. we modify least angle regression algorithms commonly used for sparse linear regression to produce the parlir algorithm, whichnot only provides an efficient and parsimonious solution as we demonstrate empirically, but it also provides formal guarantees that we prove theoretically.
organic pie charts. we present a new visualization of the distance and cluster structure of high dimensional data. it is particularly well suited for analysis tasks of users unfamiliar with complex data analysis techniques as it builds on the well known concept of pie charts. the non-linear projection capabilities of emergent self-organizing maps (esom) are used to generate a topology-preserving ordering of the data points on a circle. the distance structure within the high dimensional space is visualized on the circle analogously to the u-matrix method for two-dimensional som. the resulting display resembles pie charts but has an organic structure that naturally emerges from the data. pie segments correspond to groups of similar data points. boundaries between segments represent low density regions with larger distances among neighboring points in the high dimensional space. the representation of distances in the form of a periodic sequence of values makes time series segmentation applicable to automated clustering of the data that is in sync with the visualization. we discuss the usefulness of the method on a variety of data sets to demonstrate the applicability in applications such as document analysis or customer segmentation.
graph olap: towards online analytical processing on graphs. olap (on-line analytical processing) is an important notion in data analysis. recently, more and more graph or networked data sources come into being. there exists a similar need to deploy graph analysis from different perspectives and with multiple granularities. however, traditional olap technology cannot handle such demands because it does not consider the links among individual data tuples. in this paper, we develop a novel graph olap framework, which presents a multi-dimensional and multi-level view over graphs. the contributions of this work are two-fold. first, starting from basic definitions, i.e., what are dimensions and measures in the graph olap scenario, we develop a conceptual framework for data cubes on graphs. we also look into different semantics of olap operations, and classify the framework into two major subcases: informational olap and topological olap. then, with more emphasis on informational olap (topological olap will be covered in a future study due to the lack of space), we show how a graph cube can be materialized by calculating a special kind of measure called aggregated graph and how to implement it efficiently. this includes both full materialization and partial materialization where constraints are enforced to obtain an iceberg cube. we can see that the aggregated graphs, which depend on the graph properties of underlying networks, are much harder to compute than their traditional olap counterparts, due to the increased structural complexity of data. empirical studies show insightful results on real datasets and demonstrate the efficiency of our proposed optimizations.
learning on weighted hypergraphs to integrate protein interactions and gene expressions for cancer outcome prediction. building reliable predictive models from multiple complementary genomic data for cancer study is a crucial step towards successful cancer treatment and a full understanding of the underlying biological principles. to tackle this challenging data integration problem, we propose a hypergraph-based learning algorithm called hypergene to integrate microarray gene expressions and protein-protein interactions for cancer outcome prediction and biomarker identification. hypergene is a robust two-step iterative method that alternatively finds the optimal outcome prediction and the optimal weighting of the marker genes guided by a protein-protein interaction network. under the hypothesis that cancer-related genes tend to interact with each other, the hypergene algorithm uses a protein-protein interaction network as prior knowledge by imposing a consistent weighting of interacting genes. our experimental results on two large-scale breast cancer gene expression datasets show that hypergene utilizing a curated protein-protein interaction network achieves significantly improved cancer outcome prediction. moreover, hypergene can also retrieve many known cancer genes as highly weighted marker genes.
evolutionary clustering by hierarchical dirichlet process with hidden markov state. this paper studies evolutionary clustering, which is a recently hot topic with many important applications, noticeably in social network analysis. in this paper, based on the recent literature on hierarchical dirichlet process (hdp) and hidden markov model (hmm), we have developed a statistical model hdp-htm that combines hdp with a hierarchical transition matrix (htm) based on the proposed infinite hierarchical hidden markov state model (ih$^2$ms) as an effective solution to this problem. the hdp-htm model substantially advances the literature on evolutionary clustering in the sense that not only it performs better than the existing literature, but more importantly it is capable of automatically learning the cluster numbers and structures and at the same time explicitly addresses the correspondence issue during the evolution. extensive evaluations have demonstrated the effectiveness and promise of this solution against the state-of-the-art literature.
a practical approach to classify evolving data streams: training with limited amount of labeled data. recent approaches in classifying evolving data streams are based on supervised learning algorithms, which can be trained with labeled data only. manual labeling of data is both costly and time consuming. therefore, in a real streaming environment, where huge volumes of data appear at a high speed, labeled data may be very scarce. thus, only a limited amount of training data may be available for building the classification models, leading to poorly trained classifiers. we apply a novel technique to overcome this problem by building a classification model from a training set having both unlabeled and a small amount of labeled instances. this model is built as micro-clusters using semisupervised clustering technique and classification is performed with κ-nearest neighbor algorithm. an ensemble of these models is used to classify the unlabeled data. empirical evaluation on both synthetic data and real botnet traffic reveals that our approach, using only a small amount of labeled data for training, outperforms state-of-the-art stream classification algorithms that use twenty times more labeled data than our approach.
discovering flow anomalies: a sweet approach. given a percentage-threshold and readings from a pair of consecutive upstream and downstream sensors, flow anomaly discovery identifies dominant time intervals where the fraction of time instants of significantly mis-matched sensor readings exceed the given percentage-threshold. discovering flow anomalies (fa) is an important problem in environmental flow monitoring networks and early warning detection systems for water quality problems. however, mining fas is computationally expensive because of the large (potentially infinite) number of time instants of measurement and potentially long delays due to stagnant (e.g. lakes) or slow moving (e.g. wetland) water bodies between consecutive sensors. traditional outlier detection methods (e.g. t-test) are suited for detecting transient fas (i.e., time instants of significant mis-matches across consecutive sensors) and cannot detect persistent fas (i.e., long variable time-windows with a high fraction of time instant transient fas) due to a lack of a pre-defined window size. in contrast, we propose a smart window enumeration and evaluation of persistence-thresholds (sweet) method to efficiently explore the search space of all possible window lengths. computation overhead is brought down significantly by restricting the start and end points of a window to coincide with transient fas, using a smart counter and efficient pruning techniques. experimental evaluation using a real dataset shows our proposed approach outperforms naıve alternatives.
border sampling through coupling markov chain monte carlo. recently, progressive border sampling (pbs) was proposed for sample selection in supervised learning by progressively learning an augmented full border from small labeled datasets. however, this quadratic learning algorithm is inapplicable to large datasets. in this paper, we incorporate the pbs to a state of the art technique called coupling markov chain monte carlo (cmcmc) in an attempt to scale the original algorithm up on large labeled datasets. the cmcmc can produce an exact sample while a naive strategy for markov chain monte carlo cannot guarantee the convergence to a stationary distribution. the resulting cmcmc-pbs algorithm is thus proposed for border sampling on large datasets. cmcmc-pbs exhibits several remarkable characteristics: linear time complexity, learner-independence, and a consistent convergence to an optimal sample from the original training sets by learning from their subsamples. our experimental results on the 33 either small or large labeled datasets from the ucikdd repository and a nuclear security application show that our new approach outperforms many previous sampling techniques for sample selection.
a topic modeling approach and its integration into the random walk framework for academic search. in this paper, we propose a unified topic modeling approach and its integration into the random walk framework for academic search. specifically, we present a topic model for simultaneously modeling papers, authors, and publication venues. we combine the proposed topic model into the random walk framework. experimental results show that our proposed approach for academic search significantly outperforms the baseline methods of using bm25 and language model, and those of using the existing topic models (including plsi, lda, and the at model).
dirichlet process based evolutionary clustering. evolutionary clustering has emerged as an important research topic in recent literature of data mining, and solutions to this problem have found a wide spectrum of applications, particularly in social network analysis. in this paper, based on the recent literature on dirichlet processes, we have developed two different and specific models as solutions to this problem: dpchain and hdp-evo. both models substantially advance the literature on evolutionary clustering in the sense that not only they both perform better than the existing literature, but more importantly they are capable of automatically learning the cluster numbers and structures during the evolution. extensive evaluations have demonstrated the effectiveness and promise of these models against the state-of-the-art literature.
time sensitive ranking with application to publication search. link-based ranking has contributed significantly to the success of web search. pagerank and hits are the best known link-based ranking algorithms. these algorithms do not consider an important dimension, the temporal dimension. they favor older pages because these pages have many in-links accumulated over time. bringing new and quality pages to the users is important because most users want the latest information. existing remedies to pagerank are mostly heuristic approaches. this paper investigates the temporal aspect of ranking with application to publication search, and proposes a principled method based on the stationary probability distribution of the markov chain. the proposed techniques are evaluated empirically using a large collection of high energy particle physics publication. the results show that the proposed methods are highly effective.
improving collaborative filtering recommendations using external data. this paper describes an approach for incorporating externally specified aggregate ratings information into certain types of collaborative filtering (cf) methods. for a statistical model-based cf approach, we formally showed that this additional aggregated information provides more accurate recommendations of individual items to individual users. furthermore, theoretical insights gained from the analysis of this model-based method suggested a way to incorporate aggregate information into the heuristic item-based cf method. both the model-based and the heuristic item-based cf methods were empirically tested on several datasets, and the experiments uniformly confirmed that the aggregate rating information indeed improves cf recommendations. these results also show the power of theory by demonstrating how the insights gained from theoretical developments can shed light on proper selection of good heuristic methods. we also showed the way to introduce scalability and parallelization into the estimation procedure and reported the running time for steps of the estimation procedure for large datasets.
generalized framework for syntax-based relation mining. supervised approaches to data mining are particularly appealing as they allow for the extraction of complex relations from data objects. in order to facilitate their application in different areas, ranging from protein to protein interaction in bioinformatics to text mining in computational linguistics research, a modular and general mining framework is needed. the major constraint to the generalization process concerns the feature design for the description of relational data. in this paper, we present a machine learning framework for the automatic mining of relations, where the target objects are structurally organized in a tree. object types are generalized by means of the use of roles, whereas the relation properties are described by means of the underlying tree structure. the latter is encoded in the learning algorithm thanks to kernel methods for structured data, which represent structures in terms of their all possible subparts. this approach can be applied to any kind of data disregarding their very nature. experiments with support vector machines on two text mining datasets for relation extraction, i.e. the propbank and framenet corpora, show both that our approach is general, and that it reaches state-of-the-art accuracy.
iterative set expansion of named entities using the web. set expansion refers to expanding a partial set of "seed" objects into a more complete set. one system that does set expansion is seal (set expander for any language), which expands entities automatically by utilizing resources from the web in a language independent fashion. in a previous study, seal showed good set expansion performance using three seed entities; however, when given a larger set of seeds (e.g., ten), seal's expansion method performs poorly. in this paper, we present iterative seal (iseal), which allows a user to provide many seeds. briefly, iseal makes several calls to seal, each call using a small number of seeds. we also show that iseal can be used in a "bootstrapping" manner, where each call to seal uses a mixture of user-provided and self-generated seeds. we show that the bootstrapping version of iseal obtains better results than seal even when using fewer user-provided seeds. in addition, we compare the performance of various ranking algorithms used in iseal, and show that the choice of ranking method has a small effect on performance when all seeds are user-provided, but a large effect when iseal is bootstrapped. in particular, we show that random walk with restart is nearly as good as bayesian sets with user-provided seeds, and performs best with bootstrapped seeds.
a non-parametric semi-supervised discretization method. semi-supervised classification methods aim to exploit labelled and unlabelled examples to train a predictive model. most of these approaches make assumptions on the distribution of classes. this article first proposes a new semi-supervised discretization method which adopts very low informative prior on data. this method discretizes the numerical domain of a continuous input variable, while keeping the information relative to the prediction of classes. then, an in-depth comparison of this semi-supervised method with the original supervised modl approach is presented. we demonstrate that the semi-supervised approach is asymptotically equivalent to the supervised approach, improved with a post-optimizationof the intervals bounds location.
a robust discriminative term weighting based linear discriminant method for text classification. text classification is widely used in applications ranging from e-mail filtering to review classification. many of these applications demand that the classification method be efficient and robust, yet produce accurate categorizations by using the terms in the documents only. we present a supervised text classification method based on discriminative term weighting, discrimination information pooling, and linear discrimination. terms in the documents are assigned weights according to the discrimination information they provide for one category over the others. these weights also serve to partition the terms into two sets. a linear opinion pool is adopted for combining the discrimination information provided by each set of terms yielding a two-dimensional feature space. subsequently, a linear discriminant function is learned to categorize the documents in the feature space. we provide intuitive and empirical evidence of the robustness of our method with three term weighting strategies. experimental results are presented for data sets from three different application areas. the results show that our method's accuracy is higher than other popular methods, especially when there is a distribution shift from training to testing sets. moreover, our method is simple yet robust to different application domains and small training set sizes.
mining periodic behavior in dynamic social networks. social interactions that occur regularly typically correspond to significant yet often infrequent and hard to detect interaction patterns. to identify such regular behavior, we propose a new mining problem of finding periodic or near periodic subgraphs in dynamic social networks. we analyze the computational complexity of theproblem, showing that, unlike any of the related subgraph mining problems, it is polynomial. we propose a practical, efficient and scalable algorithm to find such subgraphs that takes imperfect periodicity into account. we demonstrate the applicability of our approach on severalreal-world networks and extract meaningful and interesting periodic interaction patterns.
variance minimization least squares support vector machines for time series analysis. here we propose a novel machine learning method for time series forecasting which is based on the widely-used least squares support vector machine (ls-svm) approach. the objective function of our method contains a weighted variance minimization part as well. this modification makes the method more efficient in time series forecasting, as this paper will show. the proposed method is a generalization of the well-known ls-svm algorithm. it has similar advantages like the applicability of the kernel-trick, it has a linear and unique solution, and a short computational time, but can perform better in certain scenarios. the main purpose of this paper is to introduce the novel variance minimization least squares support vector machine (vmls-svm) method and to show its superiority through experimental results using standard benchmark time series prediction datasets.
graph-based rare category detection. rare category detection is the task of identifying examples from rare classes in an unlabeled data set. it is an open challenge in machine learning and plays key roles in real applications such as financial fraud detection, network intrusion detection, astronomy, spam image detection, etc. in this paper, we develop a new graph-based method for rare category detection named grade. it makes use of the global similarity matrix motivated by the manifold ranking algorithm, which results in more compact clusters for the minority classes; by selecting examples from the regions where probability density changes the most, it relaxes the assumption that the majority classes and the minority classes are separable. furthermore, when detailed information about the data set is not available, we develop a modified version of grade named grade-li, which only needs an upper bound on the proportion of each minority class as input. besides working with data with structured features, both grade and grade-li can also work with graph data, which can not be handled by existing rare category detection methods. experimental results on both synthetic and real data sets demonstrate the effectiveness of the grade and grade-li algorithms.
nearest neighbour classifiers for streaming data with delayed labelling. we study streaming data where the true labels come with a delay. the question is whether the online nearest neighbour classifier (ib2 and ib3 here) should employ the unlabelled data. three strategies are examined: do-nothing, replace and forget. experiments with 28 data sets show that ib2 benefits from unlabelled data, while ib3 does not.
maximum margin embedding. we propose a new dimensionality reduction method called maximum margin embedding (mme), which targets to projecting data samples into the most discriminative subspace, where clusters are most well-separated. specifically, mme projects input patterns onto the normal of the maximum margin separating hyperplanes. as a result, mme only depends on the geometry of the optimal decision boundary and not on the distribution of those data points lying further away from this boundary. technically, mme is formulated as an integer programming problem and we propose a cutting plane algorithm to solve it. moreover, we prove theoretically that the computational time of mme scales linearly with the dataset size. experimental results on both toy and real world datasets demonstrate the effectiveness of mme.
a hierarchical algorithm for clustering uncertain data via an information-theoretic approach. in recent years there has been a growing interest in clustering uncertain data. in contrast to traditional, "sharp" data representation models, uncertain data objects can be represented in terms of an uncertainty region over which a probability density function (pdf) is defined. in this context, the focus has been mainly on partitional and density-based approaches, whereas hierarchical clustering schemes have drawn less attention.we propose a centroid-linkage-based agglomerative hierarchical algorithm for clustering uncertain objects, named u-ahc. the cluster merging criterion is based on an information-theoretic measure to compute the distance between cluster prototypes. these prototypes are represented as mixture densities that summarize the pdfs of all the uncertain objects in the clusters. experiments have shown that our method outperforms state-of-the-art clustering algorithms from an accuracy viewpoint while achieving reasonably good efficiency.
sequence mining automata: a new technique for mining frequent sequences under regular expressions. in this paper we study the problem of mining frequent sequences satisfying a given regular expression. previous approaches to solve this problem were focusing on its search space, pushing (in some way) the given regular expression to prune unpromising candidate patterns. on the contrary, we focus completely on the given input data and regular expression. we introduce sequence mining automata ($sma$), a specialized kind of petri net that while reading input sequences, it produces for each sequence all and only the patterns contained in the sequence and that satisfy the given regular expression. based on this automaton, we develop a family of algorithms. our thorough experimentation on different datasets and application domains confirms that in many cases our methods outperform the current state of the art of frequent sequence mining algorithms using regular expressions (in some cases of orders of magnitude).
estimating aggregates over multiple sets. many datasets, including market basket data, text or hypertext documents, and measurement data collected in different nodes or time periods, are modeled as a collection of sets over a ground set of (weighted) items. we consider the problem of estimating basic aggregates such as the weight or selectivity of a subpopulation of the items. we extend classic summarization techniques based on sampling to this scenario when we have multiple sets and selection predicates based on membership in particular sets.
enhancing the stability of spectral ordering with sparsification and partial supervision: application to paleontological data. recent studies have demonstrated the prospects of data mining algorithms for addressing the task of seriation in paleontological data (i.e. the age-based ordering of the sites of excavation). a prominent approach is spectral ordering that computes a similarity measure between the sites and orders them such that similar sites become adjacent and dissimilar sites are placed far apart. in the paleontological domain, the similarity measure is based on the mammal genera whose remains are retrieved at each site of excavation. although spectral ordering achieves good performance in the seriation task, it ignores the background knowledge that is naturally present in the domain, as paleontologists can derive the ages of the sites of excavation within some accuracy. on the other hand, the age information is uncertain, so the best approach would be to combine the background knowledge with the information on mammal co-occurrences. motivated by this kind of partial supervision we propose a novel semi-supervised spectral ordering algorithm. our algorithm modifies the laplacian matrix used in spectral ordering, such that domain knowledge of the ordering is taken into account. also, it performs feature selection (sparsification) by discarding features that contribute most to the unwanted variability of the data in bootstrap sampling. the theoretical properties of the proposed algorithm are thoroughly analyzed and it is demonstrated that the proposed framework enhances the stability of the spectral ordering output and induces computational gains.
computational discovery of motifs using hierarchical clustering techniques. discovery of motifs plays a key role in understanding gene regulation in organisms. existing tools for motif discovery demonstrate some weaknesses in dealing with reliability and scalability. therefore, development of advanced algorithms for resolving this problem will be useful. this paper aims to develop data mining techniques for discovering motifs. a mismatch based hierarchical clustering algorithm is proposed in this paper, where three heuristic rules for classifying clusters and a post-processing for ranking and refining the clusters are employed in the algorithm. our algorithm is evaluated using two sets of dna sequences with comparisons. results demonstrate that the proposed techniques in this paper outperform meme, alignace and sombrero for most of the testing datasets.
paired learners for concept drift. to cope with concept drift, we paired a stable online learner with a reactive one. a stable learner predicts based on all of its experience, whereas are active learner predicts based on its experience over a short, recent window of time. the method of paired learning uses differences in accuracy between the two learners over this window to determine when to replace the current stable learner, since the stable learner performs worse than does there active learner when the target concept changes. while the method uses the reactive learner as an indicator of drift, it uses the stable learner to predict, since the stable learner performs better than does the reactive learner when acquiring target concept. experimental results support these assertions. we evaluated the method by making direct comparisons to dynamic weighted majority, accuracy weighted ensemble, and streaming ensemble algorithm (sea) using two synthetic problems, the stagger concepts and the sea concepts, and three real-world data sets: meeting scheduling, electricity prediction, and malware detection. results suggest that, on these problems, paired learners outperformed or performed comparably to methods more costly in time and space.
inference analysis in privacy-preserving data re-publishing. privacy-preserving data re-publishing (ppdr) deals with publishing microdata in dynamic scenarios. due to privacy concerns, data must be disguised before being published. research in privacy-preserving data publishing (ppdp) has proposed many such methods on static data. in ppdr, multiple appeared records can be used to infer private information of other records. therefore, inference channels exist among different releases. to understand the privacy property of data re-publishing, we need to analyze the impact of these inference channels. previous studies show such analysis when data are updated or disguised in special ways, however, no general method has been proposed. using the maximum entropy modeling method, we have developed a general solution. our method can conduct inference analysis when data are arbitrarily updated or arbitrarily disguised using either generalization or bucketization, two most common data disguise methods in ppdr. through analysis and experiments, we demonstrate the advantage and the effectiveness of our method.
sparcl: efficient and effective shape-based clustering. clustering is one of the fundamental data mining tasks. many different clustering paradigms have been developed over the years, which include partitional, hierarchical, mixture model based, density-based, spectral, subspace, and so on. the focus of this paper is on full-dimensional, arbitrary shaped clusters. existing methods for this problem suffer either in terms of the memory or time complexity (quadratic or even cubic). this shortcoming has restricted these algorithms to datasets of moderate sizes. in this paper we propose sparcl, a simple and scalable algorithm for finding clusters with arbitrary shapes and sizes, and it has linear space and time complexity. sparcl consists of two stages -- the first stage runs a carefully initialized version of the kmeans algorithm to generate many small seed clusters. the second stage iteratively merges the generated clusters to obtain the final shape-based clusters. experiments were conducted on a variety of datasets to highlight the effectiveness, efficiency, and scalability of our approach. on the large datasets sparcl is an order of magnitude faster than the best existing approaches.
classifying high-dimensional text and web data using very short patterns. in this paper, we propose the "democratic classifier", a simple pattern-based classification algorithm that uses very short patterns for classification, and does not rely on the minimum support threshold. borrowing ideas from democracy, our training phase allows each training instance to vote for an equal number of candidate size-2 patterns. the training instances select patterns by effectively balancing between local, class, and global significance of patterns. the selected patterns are simultaneously added to the model for all applicable classes and a novel power law based weighing scheme adjusts their weights with respect of each class. results of experiments performed on 121 common text and web datasets show that our algorithm almost always outperforms state of the art classification algorithms, without any parameter tuning. on 100 real-life web datasets, the average absolute classification accuracy improvement was as great as 9.4% over svm, harmony, c4.5 and knn. also, our algorithm ran about 3.5 times faster than the fastest existing pattern-based classification algorithm.
sparse maximum margin logistic regression for credit scoring. the objective of credit scoring model is to categorizethe applicants as either accepted or rejected debtors prior to granting credit. a modified logistic loss function is proposed which can approximate hinge loss and therefore the resulting model, maximum margin logistic regression (mmlr), has the classification capability of support vector machine (svm) with low computational cost. finally, to classify credit applicants, an efficient algorithm is also described for mmlr based on epsilon-boosting which can provide sparse estimation of coefficients for better stability and interpretability.
a non-parametric approach to pair-wise dynamic topic correlation detection. we introduce dynamic correlated topic models (dctm) for analyzing discrete data over time. this model is inspired by the hierarchical gaussian process latent variable models (gp-lvm). dctm is essentially a non-linear dimension reduction technique which is capable of (1) detecting topic evolution within a document corpus,(2) discovering topic correlations between document corpora, and (3) monitoring topic and correlation trends dynamically. unlike generative aspect models such like lda, dctm demonstrates a much faster converging rate with better model fitting to the data. we empirically assess our approach using 268,231 scientific documents, from the year 1988 to 2005. posterior inferences suggest that dctm is useful for capturing topic and correlation dynamics, as well as predicting their trends.
multi-space-mapped svms for multi-class classification. in svms-based multiple classification, it is not always possible to find an appropriate kernel function to map all the classes from different distribution functions into a feature space where they are linearly separable from each other. this is even worse if the number of classes is very large. as a result, the classification accuracy is not as good as expected. in order to improve the performance of svms-based multi-classifiers, this paper proposes a method, named multi-space-mapped svms, to map the classes into different feature spaces and then classify them. the proposed method reduces the requirements for the kernel function. substantial experiments have been conducted on one-against-all, one-against-one, fsvm, ddag algorithms and our algorithm using six uci data sets. the statistical results show that the proposed method has a higher probability of finding appropriate kernel functions than traditional methods and outperforms others.
deck: detecting events from web click-through data. in the past few years there has been increased research interest in detecting previously unidentified events from web resources. our focus in this paper is to detect events from the click-through data generated by web search engines. existing event detection algorithms, which mainly study the news archive data, cannot be employed directly because of the following two unique features of click-through data: 1) the information provided by click-through data is quite limited; 2) not every query issued to a web search engine corresponds to an event in the real world. in this paper, we address this problem by proposing an effective algorithm which detects events from click-through data deck. we firstly transform click-through data to the 2d polar space by considering the semantic dimension and temporal dimension of queries. robust subspace estimation is performed to detect subspaces such that each subspace consists of queries of similar semantics. next, we prune uninteresting subspaces which do not contain queries corresponding to real events by simultaneously considering the respective distribution of queries along the semantic dimension and the temporal dimension in each subspace. finally, events are detected from interesting subspaces using a nonparametric clustering technique. compared with an existing approach, our experimental results based on real-life data have shown that the proposed approach is more accurate and effective in detecting real events from click-through data.
rbnbc: repeat based naive bayes classifier for biological sequences. in this paper, we present rbnbc, a repeat based naive bayes classifier of bio-sequences that uses maximal frequent subsequences as features. rbnbc's design is based on generic ideas that can apply to other domains where the data is organized as collections of sequences. specifically, rbnbc uses a novel formulation of naive bayes that incorporates repeated occurrences of subsequences within each sequence. our extensive experiments on two collections of protein families show that it performs as well as existing state-of-the-art probabilistic classifiers for bio-sequences. this is surprising as it is a pure data mining based generic classifier that does not require domain-specific background knowledge. we note that domain-specific ideas could further increase its performance.
nonnegative matrix factorization for combinatorial optimization: spectral clustering, graph matching, and clique finding. nonnegative matrix factorization (nmf) is a versatile model for data clustering. in this paper, we propose several nmf inspired algorithms to solve different data mining problems. they include (1) multi-way normalized cut spectral clustering, (2) graph matching of both undirected and directed graphs, and (3) maximal clique finding on both graphs and bipartite graphs. key features of these algorithms are (a) they are extremely simple to implement; and (b) they are provably convergent. we conduct experiments to demonstrate the effectiveness of these new algorithms. we also derive a new spectral bound for the size of maximal edge bicliques as a byproduct of our approach.
learning bayesian networks: a map criterion for joint selection of model structure and parameter. for learning bayesian network (bn) structures, it has become common practice to use the bayesian dirichlet (bd) scoring criterion. in contrast to most other scoring metrics that functionally can be interpreted as regularized maximum likelihood criteria, the bd metric cannot be considered as such. the functional dissimilarity of the bd metric compared to other metrics is an obstacle from an analytical point of view; this is for instance becomes clear in the context of the structural em algorithm for learning bns from incomplete data. also, it is not easy to pin-point why exactly and to what extend regularization is taken care of by applying the bd metric. we introduce a bayesian scoring criterion that is closely related to the bd metric, but solves the obvious disadvantages of the bd metric. we arrive at this result by using the same basic assumptions as for the bd metric, but in contrast to the bd metric, where focus is on learning the model structure only, we aim at learning the most probable bn pair jointly, i.e., model structure and the parameter are selected as a pair. this approach yields a scoring metric that has the functional form of a regularized maximum likelihood metric. we perform experiments, and show that this map bn metric also yields better results than the bic and bd metrics on independent test data.
transductive component analysis. in this paper, we study semi-supervised linear dimensionality reduction. beyond conventional supervised methods which merely consider labeled instances, the semi-supervised scheme allows to leverage abundant and ample unlabeled instances into learning so as to achieve better generalization performance. under semi-supervised settings, our objective is to learn a smooth as well as discriminative subspace and linear dimensionality reduction is thus achieved by mapping all samples into the subspace. specifically, we present the transductive component analysis (tca) algorithm to generate such a subspace founded on a graph-theoretic framework.considering tca is non-orthogonal, we further present the orthogonal transductive component analysis (otca) algorithm to iteratively produce a series of orthogonal basis vectors. otca has better discriminating power than tca. experiments carried out on synthetic and real-world datasets by otca show a clear improvement over the results of representative dimensionality reduction algorithms.
wifisviz: effective visualization of frequent itemsets. frequent itemset mining plays an essential role in the mining of many different patterns. most existing frequent itemset mining algorithms return the mined results--namely, frequent itemsets--in the form of textual lists. however, the use of visual representation can enhance the user understanding of the inherent relations in a collection of frequent itemsets. in this paper, we propose an effective visualizer, called wifisviz, to display the mined frequent itemsets. wifisviz provides users with an overview and details about the itemsets. moreover, this visualizer is also equipped with several interactive features for effective visualization of the frequent itemsets mined from various real-life applications.
spatiotemporal relational probability trees: an introduction. we introduce spatiotemporal relational probability trees (srpts), probability estimation trees for relational data that can vary in both space and time. the srpt algorithm addresses the exponential increase in search complexity through sampling. we validate the srpt using a simulated data set and we empirically demonstrate the srpt algorithm on two real-world data sets.
fast and memory efficient mining of high utility itemsets in data streams. efficient mining of high utility itemsets has become one of the most interesting data mining tasks with broad applications. in this paper, we proposed two efficient one-pass algorithms, mhui-bit and mhui-tid, for mining high utility itemsets from data streams within a transaction-sensitive sliding window. two effective representations of item information and an extended lexicographical tree-based summary data structure are developed to improve the efficiency of mining high utility itemsets. experimental results show that the proposed algorithms outperform than the existing algorithms for mining high utility itemsets from data streams.
m3miml: a maximum margin method for multi-instance multi-label learning. multi-instance multi-label learning (miml) deals with the problem where each training example is associated with not only multiple instances but also multiple class labels. previous miml algorithms work by identifying its equivalence in degenerated versions of multi-instance multi-label learning. however, useful information encoded in training examples may get lost during the identification process. in this paper, a maximum margin method is proposed for miml which directly exploits the connections between instances and labels. the learning task is formulated as a quadratic programming (qp) problem and implemented in its dual form. applications to scene classification and text categorization show that the proposed approach achieves superior performance over existing miml methods.
learning the latent semantic space for ranking in text retrieval. subspace learning techniques for text analysis, such as latent semantic indexing (lsi), have been widely studied in the past decade. however, to our best knowledge, no previous study has leveraged the rank information for subspace learning in ranking tasks. in this paper, we propose a novel algorithm, called learning latent semantics for ranking (llsr), to seek the optimal latent semantic space tailored to the ranking tasks. we first present a dual explanation for the classical latent semantic indexing (lsi) algorithm, namely learning the so-called latent semantic space (lss) to encode the data information. then, to handle the increasing amount of training data for the practical ranking tasks, we propose a novel objective function to derive the optimal lss for ranking. experimental results on two smart sub-collections and a trec dataset show that llsr effectively improves the ranking performance compared with the classical lsi algorithm and ranking without subspace learning.
fast counting of triangles in large real networks without counting: algorithms and laws. triangles are important for real world social networks, lying at the heart of the clustering coefficient and of the transitivity ratio. however, straight-forward and even approximate counting algorithms can be slow, trying to execute or approximate the equivalent of a 3-way database join. in this paper, we provide two algorithms, the eigen triangle for counting the total number of triangles in a graph, and the eigen triangle local algorithm that gives the count of triangles that contain a desired node. additional contributions include the following:(a) we show that both algorithms achieve excellent accuracy, with up to ~1000x faster execution time, on several, real graphs and (b) we discover two new power laws (degree-triangle and triangle participation laws) with surprising properties.
quantitative association analysis using tree hierarchies. association analysis arises in many important applications such as bioinformatics and business intelligence. given a large collection of measurements over a set of samples, association analysis aims to find dependencies of target variables to subsets of measurements. most previous algorithms adopt a two-stage approach; they first group samples based on the similarity in the subset of measurements, and then they examine the association between these groups and the specified target variables without considering the inter-group similarities or alternative groupings. this can lead to cases where the strength of association depends significantly on arbitrary clustering choices. in this paper, we propose a tree-based method for quantitative association analysis. tree hierarchies derived from sample similarities represent many possible sample groupings. they also provide a natural way to incorporate domain knowledge such as ontologies and to identify and remove outliers. given a tree hierarchy, our association analysis evaluates all possible groupings and selects the one with strongest association to the target variable. we introduce an efficient algorithm, treeqa, to systematically explore the search-space of all possible groupings in a set of input trees, with integrated permutation tests. experimental results show that treeqa is able to handlelarge-scale association analysis very efficiently and is more effective and robust in association analysis than previous methods.
formal models for expert finding on dblp bibliography data. finding relevant experts in a specific field is often crucial for consulting, both in industry and in academia. the aim of this paper is to address the expert-finding task in a real world academic field. we present three models for expert finding based on the large-scale dblp bibliography and google scholar for data supplementation. the first, a novel weighted language model, models an expert candidate based on the relevance and importance of associated documents by introducing a document prior probability, and achieves much better results than the basic language model. the second, a topic-based model, represents each candidate as a weighted sum of multiple topics, whilst the third, a hybrid model, combines the language model and the topic-based model. we evaluate our system using a benchmark dataset based on human relevance judgments of how well the expertise of proposed experts matches a query topic. evaluation results show that our hybrid model outperforms other models in nearly all metrics.
finding good itemsets by packing data. the problem of selecting small groups of itemsets that represent the data well has recently gained a lot of attention. we approach the problem by searching for the itemsets that compress the data efficiently. as a compression technique we use decision trees combined with a refined version of mdl. more formally, assuming that the items are ordered, we create a decision tree for each item that may only depend on the previous items. our approach allows us to find complex interactions between the attributes, not just co-occurrences of 1s. further, we present a link between the itemsets and the decision trees and use this link to export the itemsets from the decision trees. in this paper we present two algorithms. the first one is a simple greedy approach that builds a family of itemsets directly from data. the second one, given a collection of candidate itemsets, selects a small subset of these itemsets. our experiments show that these approaches result in compact and high quality descriptions of the data.
toward faster nonnegative matrix factorization: a new algorithm and comparisons. nonnegative matrix factorization (nmf) is a dimension reduction method that has been widely used for various tasks including text mining, pattern analysis, clustering, and cancer class discovery. the mathematical formulation for nmf appears as a non-convex optimization problem, and various types of algorithms have been devised to solve the problem. the alternating nonnegative least squares (anls) framework is a block coordinate descent approach for solving nmf, which was recently shown to be theoretically sound and empirically efficient. in this paper, we present a novel algorithm for nmf based on the anls framework. our new algorithm builds upon the block principal pivoting method for the nonnegativity constrained least squares problem that overcomes some limitations of active set methods. we introduce ideas to efficiently extend the block principal pivoting method within the context of nmf computation. our algorithm inherits the convergence theory of the anls framework and can easily be extended to other constrained nmf formulations. comparisons of algorithms using datasets that are from real life applications as well as those artificially generated show that the proposed new algorithm outperforms existing ones in computational speed.
a joint matrix factorization approach to unsupervised action categorization. in this paper, a novel unsupervised approach to mining categories from action video sequences is presented. this approach consists of two modules: action representation and learning model. videos are regarded as spatially distributed dynamic pixel time series, which are quantized into pixel prototypes. after replacing the pixel time eries with their corresponding prototype labels, the video sequences are compressed into 2d action matrices. we put these matrices together to form an multi-action tensor, and propose the joint matrix factorization method to simultaneously cluster the pixel prototypes into pixel signatures, and matrices into action classes. the approach is tested on public and popular weizmann data set, and promising results are achieved.
a fast method to mine frequent subsequences from graph sequence data. in recent years, the mining of a complete set of frequent subgraphs from labeled graph data has been extensively studied.however, to our best knowledge, almost no methods have been proposed to find frequent subsequences of graphs from a set of graph sequences. in this paper, we define a novel class of graph subsequences by introducing axiomatic rules of graph transformation, their admissibility constraints and a union graph. then we propose an efficient approach named "gtrace'' to enumerate frequent transformation subsequences (ftss) of graphs from a given set of graph sequences. its fundamental performance has been evaluated by using artificial datasets, and its practicality has been confirmed through the experiments using real world datasets.
a recommendation system for preconditioned iterative solvers. preconditioned iterative methods are often used to solve very large sparse systems of linear systems that arise in many scientific and engineering applications. the performance and robustness of these solvers is extremely sensitive to the choice of multiple preconditioner and solver parameters. users of iterative methods often encounter an overwhelming number of combinations of choices for solvers, matrix preprocessing steps, preconditioners, and their parameters. the lack of a unified theoretical analysis of preconditioners coupled with limited knowledge of their interaction with linear systems makes it highly challenging for practitioners to choose good solver configurations. in this paper, we propose a novel, multi-stage learning based methodology for determining the best solver configurations to optimize the desired performance behavior for any given linear system. empirical results over real performance data for the hypre iterative solver package demonstrate the efficacy and flexibility of the proposed approach.
mining order-preserving submatrices from data with repeated measurements. order-preserving submatrices (opsm's) have been shown useful in capturing concurrent patterns in data when the relative magnitudes of data items are more important than their absolute values. to cope with data noise, repeated experiments are often conducted to collect multiple measurements. we propose and study a more robust version of opsm, where each data item is represented by a set of values obtained from replicated experiments. we call the new problem opsm-rm (opsm with repeated measurements). we define opsm-rm based on a number of practical requirements. we discuss the computational challenges of opsm-rm and propose a generic mining algorithm. we further propose a series of techniques to speed up two time-dominating components of the algorithm. we clearly show the effectiveness of our methods through a series of experiments conducted on real microarray data.
predicting future decision trees from evolving data. recognizing and analyzing change is an important human virtue because it enables us to anticipate future scenarios and thus allows us to act pro-actively. one approach to understand change within a domain is to analyze how modelsand patterns evolve. knowing how a model changes over time is suggesting to ask: can we use this knowledge to learn a model in anticipation, such that it better reflects the near-future characteristics of an evolving domain? in this paper we provide an answer to this question by presenting an algorithm which predicts future decision trees based ona model of change. in particular, this algorithm encompasses a novel approach to change mining which is based on analyzing the changes of the decisions made during model learning. the proposed approach can also be applied to other types of classifiers and thus provides a basis for future research. we present our first experimental results which show that anticipated decision trees have the potential to outperform trees learned on the most recent data.
clustering distributed time series in sensor networks. event detection is a critical task in sensor networks, especially for environmental monitoring applications. traditional solutions to event detection are based on analyzing one-shot data points, which might incur a high false alarm rate because sensor data is inherently unreliable and noisy. to address this issue, we proposea novel distributed single-pass incremental clustering (dsic) technique to cluster the time series obtained at sensor nodes based on their underlying trends. in order to achieve scalability and energy-efficiency, our dsic technique uses a hierarchical structure of sensor networks as the underlying infrastructure. the algorithm first compresses the time series produced at individual sensor nodes into a compact representation using haar wavelettransform, and then, based on dynamic time warping distances, hierarchically groups the approximate time series into a global clustering model in an incremental manner. experimental results on both real data and synthetic data demonstrate that our dsic algorithm is accurate, energy-efficient and robust with respect tonetwork topology changes.
tofa: trace oriented feature analysis in text categorization. dimension reduction for large-scale text data is attracting much attention lately due to the rapid growth of world wide web. we can consider dimension reduction algorithms in two categories: feature extraction and feature selection. an important problem remains: it has been difficult to integrate these two algorithm categories into a single framework, making it difficult to reap the benefit of both. in this paper, we formulate the two algorithm categories through a unified optimization framework. under this framework, we develop a novel feature selection algorithm called trace oriented feature analysis (tofa). the novel objective function of tofa is a unified framework that integrates many prominent feature extraction algorithms such as unsupervised principal component analysis and supervised maximum margin criterion are special cases of it. thus tofa can process not only supervised problem but also unsupervised and semi-supervised problems. experimental results on real text datasets demonstrate the effectiveness and efficiency of tofa.
web mining for understanding stories through graph visualisation. rich information spaces (like the web or scientific publications) are full of "stories": sets of statements that evolve over time, manifested as, for example, collections of newspaper articles reporting events relating to an evolving crime investigation, sets of news articles and blog posts accompanying the development of a political election campaign, or sequences of scientific papers on a topic. in this paper, we propose a method and a visualisation tool for mapping and interacting with such stories. in contrast to existing approaches, our method concentrates on relational information and on local patterns rather than on the occurrence of individual concepts and global models. in addition, we present an evaluation framework. a real-life case study is used to illustrate and evaluate the method and tool.
multiplicative mixture models for overlapping clustering. the problem of overlapping clustering, where a point is allowed to belong to multiple clusters, is becoming increasingly important in a variety of applications. in this paper, we present an overlapping clustering algorithm based on multiplicative mixture models. we analyze a general setting where each component of the multiplicative mixture is from an exponential family, and present an efficient alternating maximization algorithm to learn the model and infer overlapping clusters. we also show that when each component is assumed to be a gaussian, we can apply the kernel trick leading to non-linear cluster separators and obtain better clustering quality. the efficacy of the proposed algorithms is demonstrated usingexperiments on both uci benchmark datasets and a microarray gene expression dataset.
anomaly detection support vector machine and its application to fault diagnosis. we address the issue of classification problems in the following situation: test data include data belonging to unlearned classes. to address this issue, most previous works have taken two-stage strategies where unclear data are detected using an anomaly detection algorithm in the first stage while the rest of data are classified into learned classes using a classification algorithm in the second stage. in this study, we propose anomaly detection support vector machine (adsvm) which unifies classification and anomaly detection. adsvm is unique in comparison with the previous work in that it addresses the two problems simultaneously. we also propose a multiclass extension of adsvm that uses a pairwise voting strategy. we empirically present that adsvm outperforms two-stage algorithms in application to an real automobile fault dataset, as well as to uci benchmark datasets.
hirel: an incremental clustering algorithm for relational datasets. traditional clustering approaches usually analyze static datasets in which objects are kept unchanged after being processed, but many practical datasets are dynamically modified which means some previously learned patterns have to be updated accordingly. re-clustering the whole dataset from scratch is not a good choice due to the frequent data modifications and the limited out-of-service time, so the development of incremental clustering approaches is highly desirable. besides that, propositional clustering algorithms are not suitable for relational datasets because of their quadratic computational complexity. in this paper, we propose an incremental clustering algorithm that requires only one pass of the relational dataset. the utilization of the representative objects and the balanced search tree greatly accelerate the learning procedure. experimental results prove the effectiveness of our algorithm.
graph-based iterative hybrid feature selection. when the number of labeled examples is limited, traditional supervised feature selection techniques often fail due to sample selection bias or unrepresentative sample problem. to solve this, semi-supervised feature selection techniques exploit the statistical information of both labeled and unlabeled examples in the same time. however, the results of semi-supervised feature selection can be at times unsatisfactory, and the culprit is on how to effectively use the unlabeled data. quite different from both supervised and semi-supervised feature selection, we propose a “hybrid”framework based on graph models. we first apply supervised methods to select a small set of most critical features from the labeled data. importantly, these initial features might otherwise be missed when selection is performed onthe labeled and unlabeled examples simultaneously. next,this initial feature set is expanded and corrected with the use of unlabeled data. we formally analyze why the expected performance of the hybrid framework is better than both supervised and semi-supervised feature selection. experimental results demonstrate that the proposed method outperforms both traditional supervised and state-of-the-art semisupervised feature selection algorithms by at least 10% inaccuracy on a number of text and biomedical problems with thousands of features to choose from. software and dataset is available from the authors.
publishing sensitive transactions for itemset utility. we consider the problem of publishing sensitive transaction data with privacy preservation. high dimensionality of transaction data poses unique challenges on data privacy and data utility. on one hand, re-identification attacks tend to use a subset of items that infrequently occur in transactions, called moles. on the other hand, data mining applications typically depend on subsets of items that frequently occur in transactions, called nuggets. thus the problem is how to eliminate all moles while retaining nuggets as much as possible. a challenge is that moles and nuggets are multi-dimensional with exponential growth and are tangled together by shared items. we present a novel and scalable solution to this problem. the novelty lies in a compact border data structure that eliminates the need of generating all moles and nuggets.
using wikipedia for co-clustering based cross-domain text classification. traditional approaches to document classification requires labeled data in order to construct reliable and accurate classifiers. unfortunately, labeled data are seldom available, and often too expensive to obtain. given a learning task for which training data are not available, abundant labeled data may exist for a different but related domain. one would like to use the related labeled data as auxiliary information to accomplish the classification task in the target domain. recently, the paradigm of transfer learning has been introduced to enable effective learning strategies when auxiliary data obey a different probability distribution. a co-clustering based classification algorithm has been previously proposed to tackle cross-domain text classification. in this work, we extend the idea underlying this approach by making the latent semantic relationship between the two domains explicit. this goal is achieved with the use of wikipedia. as a result, the pathway that allows to propagate labels between the two domains not only captures common words, but also semantic concepts based on the content of documents. we empirically demonstrate the efficacy of our semantic-based approach to cross-domain classification using a variety of real data.
an efficient rectification method for trinocular stereovision. this paper presents an efficient and intuitive algorithm of the epipolar line rectification to trinocular stereo pairs with triangular configuration of the cameras. given the perspective projection matrices of each camera, the transformation matrices are computed by determining the new camera coordinate system in affine space and imposing some constraints on the remaining freedom degrees. the proposed method is able to make matching points lie on the identical row or column on the three images in affine coordinates.
efficient cross-validation of the complete two stages in kfd classifier formulation. this paper presents an efficient evaluation algorithm for cross-validating the two-stage approach of kfd classifiers. the proposed algorithm is of the same complexity level as the existing indirect efficient cross-validation methods but it is more reliable since it is direct and constitutes exact crossvalidation for the kfd classifier formulation. simulations demonstrate that the proposed algorithm is almost as fast as the existing fast indirect evaluation algorithm and the twostage cross-validation selects better models on most of the thirteen benchmark data sets.
ear recognition by means of a rotation invariant descriptor. iannarelli's studies showed that ear shape can be considered a biometric identifier able to authenticate people as well as more established biometrics like face or voice, for instance. however, very few researches can be found in literature about ear recognition. in most cases techniques already working in other biometric fields, such as pca (principal component analysis), are applied to ear.eigen-ears provide high recognition rate only in closely controlled conditions. indeed, even a slight amount of rotation can cause a significant drop in system performance and in unattended systems rotations occur very frequently. in this paper, we propose the use of a rotation invariant descriptor, namely gfd (generic fourier descriptor), to extract meaningful features from ear images. this descriptor results to be quite robust to both ear rotations and illumination changes. experimental results confirm the superiority of this approach evencompared to eigen-ears.
novel mathematical model for enhanced fisher's linear discriminant and its application to face recognition. in this paper, a novel mathematical model for enhanced fisher's linear discriminant is proposed, and it will be referred as efld in the following discussion. efld has two main advantages: first, it takes both the within-class scatter and the between-class scatter into account as fld dose; second, it could adaptively distinguish different variables of sample vector according to their scale in statistics. the features extracted by efld are much reliable for classification. according to the experiments on harvard face database and orl face database, efld outperforms some famous algorithms (pca, fld and ica) against large variation in lighting direction, variation in pose and facial expression. efld also has another potential contribution to classifying algorithms: there have been a number of classifying algorithms which need fld to extract classifiable features, some new algorithms could be proposed by replacing fld by efld in algorithms which use fld to extract features.
a probabilistic framework for joint head tracking and pose estimation. head tracking and pose estimation are usually considered as two sequential and separate problems: pose is estimated on the head patch provided by a tracking module. however, precision in head pose estimation is dependent on tracking accuracy which itself could benefit from the head orientation knowledge. therefore, this work considers head tracking and pose estimation as two coupled problems in a probabilistic setting. head pose models are learned and incorporated into a mixed-state particle filter framework for joint head tracking and pose estimation. experimental results on real sequences show the effectiveness of the method in estimating more stable and accurate pose values.
3d face recognition using normal sphere and general fourier descriptor. today, face figures among the most promising biometrics, allowing to identify people without requiring any physical contact. in this research field, 3d provides a significant improvement in recognition performances, but the existing approaches show limitations dealing with pose variations; indeed 3d face surfaces need to be aligned before the matching operation. this paper proposes an approach that overcomes this limitation by projecting the 3d shape information onto the 2d surface of a normal sphere, while a rotation invariant descriptor is used to extract key features from this surface. in addition, using a 2d descriptor reduces the computing time that is a typical drawback of 3d methods. experimentations have been conducted on a property face dataset, to assess the robustness of the method with respect to a large set of facial expression and pose variations.
a hybrid hmm-based speech recognizer using kernel-based discriminants as acoustic models. in this paper we propose a novel order-recursive training algorithm for kernel-based discriminants which is computationally efficient. we integrate this method in a hybrid hmm-based speech recognition system by translating the outputs of the kernel-based classifier into class-conditional probabilities and using them instead of gaussian mixtures as production probabilities of a hmm-based decoder for speech recognition. the performance of the described hybrid structure is demonstrated on the darpa resource management (rm1) corpus.
estimation of dynamic light changes in outdoor scenes without the use of calibration objects. the the work presented in this paper explores how dynamical light parameters in an outdoor environment can be estimated for use in a real-time augmented reality (ar) system. a method using existing inverse rendering techniques is used to acquire diffuse surface reflectances in an offline procedure. the reflectances are used in an on-line procedure to estimate the illumination parameters of an outdoor scene. the method presented reduces the light estimation problem of outdoor scenes to a modified phong shading model with two unknown parameters, which can be determined through the use of a linear equations system. the work presented provides an elegant method for estimating dynamically changing illumination parameters without the need for a calibration object in the scene.
appearance factorization based facial expression recognition and synthesis. facial expression interpretation, recognition and analysis is a key issue in visual communication and man to machine interaction. in this paper, we address the issues of facial expression recognition and synthesis and compare the proposed bilinear factorization based representations with previously investigated methods such as linear discriminant analysis and linear regression. we conclude that bilinear factorization outperforms these techniques in terms of correct recognition rates and synthesis photorealism especially when the number of training samples is restrained.
motion capture based on color error maps in a distributed collaborative environment. in this paper a composite framework for collaborative working is presented. the framework includes real-time motion tracking based on computer vision from standard webcams situated at different locations, data transmission and real-time animation of 3d avatars in a virtual world. motion tracking is obtained without using markers, with weak constraints on users' clothes and environment lighting. it is based on a model fitting process that compares the 2d processed images supplied by cameras with a set of artificially generated views of a human model.
combining dichotomizers for map field classification. a new method for combining dichotomizers like svms is proposed for classifying multi-class pattern fields. the novelty lies in the estimation of the styleconstrained posterior field class probabilities from the frequencies of the training patterns in the regions of the feature space engendered by the pairwise decision boundaries of the dichotomizers. we show that on simulated data, this non-parametric field classifier is nearly optimal. on scanned printed digits, its accuracy is comparable to that of state-of-the-art style classifiers.
a robust block-based image watermarking scheme using fast hadamard transform and singular value decomposition. we present a new approach for transparent and high rate embedding of watermarks into digital images using fast hadamard transform (fht) and singular value decomposition (svd). the proposed algorithm consists of three main steps: dividing the cover image into small blocks, applying the fht to each block, and distributing the singular values of the visual watermark image over the transformed cover blocks. the main attractive features of this approach are simplicity, flexibility in data embedding capacity, and real-time implementation. the experimental results show the much improved performance of the proposed method in comparison with existing techniques, and also its robustness against the most common attacks.
comparative classifier aggregation. comparative neural networks are a new kind of neural networks that can be used to compare two or more items given a set of context features. they compare two items at a time indicating the one that matches the context features better. consequently, any sorting algorithm, coupled with such a neural comparator, can sort any set of items. although applications include ink segmentation (for handwriting recognition purposes) and web page ranking, our emphasis on this paper is on classifier aggregation and, in particular, the integration of our standard handwriting recognizers with a user personalization database that consists of user samples.
modelling crowd scenes for event detection. this work presents an automatic technique for detection of abnormal events in crowds. crowd behaviour is difficult to predict and might not be easily semantically translated. moreover it is difficulty to track individuals in the crowd using state of the art tracking algorithms. therefore we characterise crowd behaviour by observing the crowd optical flow and use unsupervised feature extraction to encode normal crowd behaviour. the unsupervised feature extraction applies spectral clustering to find the optimal number of models to represent normal motion patterns. the motion models are hmms to cope with the variable number of motion samples that might be present in each observation window. the results on simulated crowds demonstrate the effectiveness of the approach for detecting crowd emergency scenarios.
a new hierarchical image segmentation method. image segmentation is a popular topic in computer vision and image processing. as a region-based approach, the mumford and shah (ms) model is a powerful and robust segmentation technique as compared to local based methods. however, there are also some difficulties with the ms model. in this paper, we present a piecewise linear approximation for the ms model to adapt to the image intensities distribution inside the segmented regions. we also modify the ms model to detect roof edges. because the ms functional is not convex, the result is often trapped in a local minimum and depends on the initial conditions. to overcome this problem, we present a new hierarchical strategy that takes into account both the local information at the pixel level and the global information of the ms model. the results indicate that our approach is effective in many applications.
automatic/interactive interpretation of color map images. in this paper, a combined automatic/interactive technology and algorithms for interpretation of color maps is proposed. main stages of technology are: color image binarization, binary image vectorization and vectorized image object interpretation. special scheme for automatic image vectorization as well as automatic object recognition techniques performed under operator control are proposed. practical experience in realising this technology is shown.
image renaissance using discrete optimization. in this paper we propose a novel technique to image completion that addresses image renaissance through a graph-based matching process. to this end, a number of candidate seeds with content similar to the one of the area to be inpainted are considered. they are selected through a particle filter method and then positioned over the missing area. markov random fields are used to formalize inpainting as a labeling estimation problem while a combinatorial approach is used to recover the optimal partition of patches that completes the missing area with the á-expansion process. promising results in image and texture completion demonstrate the potentials of the proposed method.
thresholding video images for text detection. thresholdging video images is very challenging due to the fact that image background generally has low resolution and is also more complicated and highly distorted than document images. as a result, thresholding methods that work well for document images may not work effectively for video images in some applications. this paper investigates the issue of thresholding video images for text detection and further develops a relative entropy-based thresholding approach that can effectively extract text from complicated video images. in order to demonstrate its performance a comparative study is conducted among the proposedthresholding method and several thresholding techniques which are widely used for document and gray scale images. the experimental results show that thresholdging video images is far more difficult than thresholding document images and simple histogram-based methods generally do not perform well.
from cell image segmentation to differential diagnosis of thyroid cancer. an approach for cytologic diagnosis of thyroid cancer with the help of automatic morphometry is proposed. this approach is based on a developed computer analyser of images that is aimed at: automated processing and binarization of colour images; automatic raster-to-vector transformation and formation of biological objects; morphometric assessment of biological objects by quantitative parameters characterizing the changes of cell nuclei; building of anexpert system to aid the diagnosis of thyroid cancer.
hidden markov models for optical flow analysis in crowds. this paper presents an event detector for emergencies in crowds. assuming a single camera and a dense crowd we rely on optical flow instead of tracking statistics as a feature to extract information from the crowd video data. the optical flow features are encoded with hidden markov models to allow for the detection of emergency or abnormal events in the crowd. in order to increase the detection sensitivity a local modelling approach is used. the results with simulated crowds show the effectiveness of the proposed approach on detecting abnormalities in dense crowds.
the mean shift algorithm and the unified framework. this paper considers two classes of algorithms for the representation of data points using centroids: the unified framework and the mean shift algorithm. the relationship between both approaches is presented showing that the mean shift algorithm fits within the unified framework being equivalent to snake with cohen potential. however it does not use competitive learning as the other methods considered in the unified framework. the advantages of both types of techniques are exemplified through examples.
correlation based image defect detection. the defect inspection that used image sensing such as automated pattern inspection is a useful solution to automatize the visual check, not limit to factory automation field. mostly such defect inspection is using the models of defect that described by primitive features. this paper proposes a new defect detection method that is the non-model based approach. in this approach, the method extracts the image description rule from local regions.it is useful for the defect inspection problems that cannot prepare a defect model such as scratch or superimpose detection, texture image analysis, etc. in the experiment, i tried the defect detection to the landscape picture which several types of superimpose were added. from these results, it was confirmed that the proposed method has high ability to detect the defected regions independently with the texture type.furthermore, i attempted the application to a scene image.therefrom, the possibility to apply the figure-ground separation of the image understanding basic problem was confirmed.
interacting active rectangles for estimation of intervertebral disk orientation. this paper presents a fast and efficient method to determine intervertebral disk orientation in a magnetic resonance (mr) image of the spine. the algorithm originates from active contour theory and enforces a shape constraint to avoid leaks through weak or non-existent boundaries. the method represents a vertebra as a rectangle, modeled as a semi-affine transformation applied to the unit square. a regional flow integrated along the rectangle's perimeter updates the rectangle's transformation to achieve the segmentation. further constraints are added so that adjacent rectangles have similar orientation and scale. the orientation of a disk is then inferred from its adjacent vertebrae. experiments show that the method is fast and effective in detecting the correct intervertebral disk orientation, which is used for transverse image planning.
enhancement of annual rings on industrial ct images of logs. many researchers have shown the ability of x-ray computer tomography (ct) of acquiring knowledge about the internal structure of logs. contrarily to medical ct scanners, industrial ct scanners should satisfy more extreme constraints (in terms of speed, duty cycle, radiation safety, reconstruction circle and aperture size) in order to be used in a sawmill environment. all these factors lower the quality of industrial ct images while automatic methods for analyzing data are required. to ensure good performances and robustness, an automatic system should adapt to the quality of the input images. this paper focuses on an algorithm which can adaptively improve the contrast of the ridge and valley structure of annual rings in ct images of wooden logs. we also show that this algorithm does not only help in segmenting annual rings but also gives with little adaptation a good approximation of the localization of the pith.
integration of an on-line handwriting recognition system in a smart phone device. this paper presents the evolving of our academic development to a technology driven application: the integration of an unconstraint cursive on-line handwritten characters into a smart phone device. the ultimate goal of this work is to implement an accuracy handwritingrecognizer into mobile devices with limited computing and memory resources. a hierarchical fuzzy modeling is used to obtain a compact and robust knowledge representation and the decision process is based on an adapted fuzzy inference system to reduce computing without decreasing the peiformances. we describe in this paper the basic architecture of the recognition system called "resifcar", its practical adaptation to the mobile device constraintsand the recognition rates both on cursive isolated letters (91.9%) and on isolated digits (92.3%) in a writer independent context based on 100 different writers.
a bayesian approach for 3d models retrieval based on characteristic views. the management of big databases of three-dimensional models (used in cad applications, visualization, games, etc.) is a very important domain. the ability to characterize and easily retrieve models are a key issues for the designers and the final users. in this frame, two main approaches exist: search by example of a three-dimensional model, and search by a 2d view. in this paper we focus on the characterization of a 3d model by a set of views (called characteristic views), and on the indexing process of these models with a bayesian probabilistic approach using the characteristic views. we illustrate our results using a collection of three-dimensional models supplied by renault group.
reliability index of optical flow that considers error margin of matches and stabilizes camera movement estimation. a reliability index that evaluates the quality of optical flow is needed because the accuracy of estimation of camera movement or the shape of the environment depends on the accuracy of optical flow. a reliability index using spatial brightness gradient information has already been proposed, and its effectiveness has been confirmed. in this paper, we proposes a reliability index that considers the error margin of matches in addition to the spatial brightness gradient information. the result of experiments showed that considering the error margin of matches increases the performance of the reliability index. it was also found that the camera movement can be estimated from optical flow in a synthetic image to which the camera movement was known beforehand. then, it was confirmed that rejecting using the reliability index improves the accuracy of estimation. moreover, in an experiment in witch changing of noise was added to the image sequence, it was shown that moderate noise stabilized the movement estimation.
flexible text recovery from degraded typewritten historical documents. the conversion of large collections of historical typewritten documents into digital libraries and archives is met with significant challenges that standard recognition techniques cannot address. the condition and individual nature of characters in these degraded documents necessitate a departure from existing thresholding approaches. this paper presents a flexible approach designed to overcome the difficulties presented by such documents by flexibly analysing each individual character and cautiously repairing it. the main sources of ocr errors are successfully addressed and reliable corrective actions are taken.
uncalibrated visual servoing from projective reconstruction of control values. the visual servoing technique has been studied extensively as a robust method for navigating robots toward goal positions and orientations reliably. unfortunately, the existing visual servoing methods require the calibration of cameras and robots, which is time-consuming. thus, in this paper, we propose a visual servoing method which does not require the calibration of cameras and robots. in particular, we show that we can navigate uncalibrated robots to goal positions properly by using the projective reconstruction based on the abstract projection of control values.
a markov random field approach to microarray image gridding. the paper reports a novel approach for the problem of automatic gridding in microarray images. the solution is modeled as a bayesian random field with a gibbs prior possibly containing first order cliques (1-clique). on the contrary of previously published contributions, this paper does not assume second order cliques, instead it relies on a two step procedure to locate microarray spots. first a set of guide spots are used to interpolate a reference grid. the final grid is then produced by an a-posteriori maximization which takes into account the reference rectangular grid and local deformations. the algorithm is completely automatic and no human intervention is required, the only critical parameter being the range of the radius of the guide spots.
towards robust voxel-coloring: handling camera calibration errors and partial emptiness of surface voxels. in this paper, we present two new methods to reduce the effects of camera calibration errors and partial emptiness of surface voxels on voxel-coloring. both of these sources of error introduce outlier pixels in voxel projections in the input images and thus result in over-carving of the reconstructed 3d scene. the existing methods to handle these errors are either insufficient or too complex. our proposed methods are simple and can be incorporated into existing voxel-coloring algorithms easily. our experimental results show that the methods proposed in this paper have the ability to improve the results of existing algorithms.
modification table form generation system based on the form recognition. as there exist large number of both printed and electronical documents of table form, it is very important to provide their handling system. the system should provide capability of generating, modifying or filling in to the form only with logical manipulation. in this paper, we propose a system which can extract the structure of the form, and modify it logically without considering layout information, and finally generate modified form layout. the system is based on our table form analysis method and table form representation language (tfml). experimental results show that the system can generate practical layouts for the modified documents.
robust facet model for application to speckle noise removal. in this paper, a robust facet model is developed, and applied to speckle noise removal in syntehetic aperture radar (sar) images. the parameters of a facet model is usually estimated by a least-squares (ls) method under the gaussian assumption. in many applications, such as speckle removal in sar images, the noise process is not gaussian, and conventional estimators do not work. a robust estimation algorithm is developed, and applied to remove speckle noise in synthetic aperture images. conventional adaptive filtering approaches in speckle filtering smoothes the image selectively depending on the details of underlying textures, and tend to blur details after speckle removal. in the proposed approach, the image is assumed to be composed of structural and stochastic components, and the stochastic component is modeled by a robust facet model. the proposed method is applied to real synthetic aperture images to demonstrate the validity and effectiveness of the algorithm.
neural networks vs logistic regression: a comparative study on a large data set. neural networks and logistic regression have been among the most widely used ai technique in applications of pattern classification.much has been discussed about if there is any significant difference in between them but much less has been actually done with real-world applications data (large scale) to help settle this matter, with a few exceptions.this paper presents a performance comparison between these two techniques on the market application of credit risk assessment, making use of a large database from an outstanding credit bureau and financial institution (a sample of 180,000 examples).the comparison was carried out through a 30-fold stratified cross-validation process to define the confidence intervals for the performance evaluation. several metrics were applied both on the optimal decision point and along the continuous output domain.the statistical tests showed that multilayer perceptrons perform better than logistic regression at 95% confidence level, for all the metrics used.
detection of 3d-flow by characteristic of convex-concave and color. this paper describes a method for detecting 3dflow of an arbitrary point on a free-form surface from time series range images obtained by a stereovision system. the approach that positively uses surface shape data obtained from the range images is examined. especially, it proposes height-color- histogram (hch) that integrates local convexconcave shape and color texture information on the surface as feature value used for correspondence point search between frames. hch makes the feature of an object part integrate shape and color texture information. in this paper, first, the method of generating hch is explained, and effectiveness is considered. finally, it is shown that 3d-flows detection about an arbitrary point on free-form surface is possible by the proposal technique with quasi-realtime.
a system identification approach for video-based face recognition. the paper poses video-to-video face recognition as a dynamical system identification and classification problem. video-to-video means that both gallery and probe consists of videos. we model a moving face as a linear dynamical system whose appearance changes with pose. an autoregressive and moving average (arma) model is used to represent such a system. the choice of arma model is based on its ability to take care of the change in appearance while modeling the dynamics of pose, expression etc. recognition is performed using the concept of subspace angles to compute distances between probe and gallery video sequences. the results obtained are very promising given the extent of pose, expression and illumination variation in the video data used for experiments.
detection of faces of various directions in complex backgrounds. this paper describes the detection of faces in complex backgrounds where their sizes, positions and directions are arbitrary. we detect the faces by extracting face components such as eyes, a mouth and so on. we first extract face features and then calculate their likelihoods as each face component. second we detect the face features which satisfy geometrical relations of the face. in order to reduce the number of combinations of all labels for all features, we determine face candidate regions using generalized hough transform and then apply a relaxation method to each candidate region.
real-time localization in outdoor environments using stereo vision and inexpensive gps. we describe a real-time, low-cost system to localize a mobile robot in outdoor environments. our system relies on stereo vision to robustly estimate frame-to-frame motion in real time (also known as visual odometry). the motion estimation problem is formulated efficiently in the disparity space and results in accurate and robust estimates of the motion even for a small-baseline configuration. our system uses inertial measurements to fill in motion estimates when visual odometry fails. this incremental motion is then fused with a low-cost gps sensor using a kalman filter to prevent long-term drifts. experimental results are presented for outdoor localization in moderately sized environments (\geqslant 100 meters)
face set classification using maximally probable mutual modes. in this paper we consider face recognition from sets of face images and, in particular, recognition invariance to illumination. the main contribution is an algorithm based on the novel concept of maximally probable mutual modes (mmpm). specifically: (i) we discuss and derive a local manifold illumination invariant and (ii) show how the invariant naturally leads to a formulation of "common modes" of two face appearance distributions. recognition is then performed by finding the most probable mode, which is shown to be an eigenvalue problem. the effectiveness of the proposed method is demonstrated empirically on a challenging database containing the total of 700 video sequences of 100 individuals.
hmm-based human action recognition using multiview image sequences. in this paper, we present a novel method for human action recognition from any arbitrary view image sequence that uses the cartesian component of optical flow velocity and human body silhouette feature vector information. we use principal component analysis (pca) to reduce the higher dimensional silhouette feature space into lower dimensional feature space. the action region in an image frame represents q-dimensional optical flow feature vector and r-dimensional silhouette feature vector. we represent each action using a set of hidden markov models and we model each action for any viewing direction by using the combined (q + r)-dimensional features at any instant of time. we perform experiments of the proposed method by using ku gesture database and manually captured data. experimental results of different actions from any viewing direction are correctly classified by our method, which indicate the robustness of our view-independent method.
an efficient method to detect facial fiducial points for face recognition. in this paper a completely automatic face recognition system is presented. it consists of two main modules: in the first, the facial fiducial points are localized, and in the second the face is characterized applying a bank of gabor filters in correspondence to the found fiducial points. this method is an evolution of the one we have presented in [a face recognition system based on local feature analysis]: the fiducial point estimation is more efficient and self-correcting, and the face characterization modified.
colour-based model pruning for efficient arg object recognition. in this paper we address the problem of object recognition from 2d views. a new approach is proposed which combines the recognition systems based on attribute relational graph matching (arg) [2 ] and the multimodal neighbourhood signature (mns) [7 ] method. in the new system we use the mns method as a pre-matching stage to prune the number of model candidates. the arg method then identifies the best model among the candidates through a relaxation labelling process. the results of experiments show a considerable gain in the arg matching speed. interestingly, as a result of the reduction in the entropy of labelling by a virtue model pruning, the recognition rate for extreme object views also improves.
a face recognition system dealing with expression variant faces. in this paper we present the generalization of the automatic face recognition system, presented in [2], making it able to deal with different expressions and the presence of spectacles. the system behavior is measured on the frgc 1.0 and the xm2vts databases, addressing some of the current challenges highlighted by phillips and others [7]. we set up experiments having in the gallery, for each subject, both one still image and multi-still images with different expressions. besides, we investigate how the image resolution affects the performances and test the scalability of the system doubling the gallery size.
robust object segmentation using graph cut with object and background seed estimation. in this paper we propose a new robust way of extracting accurate human silhouettes indoors with an active stereo camera. we first infer the parts of object and background areas of high confidence by fusing color, stereo matching information and image segmentation methods. then the inferred areas(seeds) are incorporated in a graph cut. the experimental results were presented with image sequences taken with pan-tilt stereo camera. our proposed algorithms were evaluated with respect to the ground truth data. we proved that our algorithms can outperform other methods that are based on either color/contrast or stereo/contrast principles alone.
a new set of topology preserving removal operations in the 3d space. a new set of 3x3x3 topology preserving removal operations is introduced to compute the surface skeleton of a 3d object. we show that this set of operations can be appropriately employed in a parallel process withoutcreating disconnections, cavities, tunnels and vanishing of object components.
face recognition based on the appearance of local regions. recently, we proposed a novel facial representation for face recognition based on local binary pattern (lbp) features. we obtained excellent results when dividing the face images into several regions from which the lbp features are extracted and concatenated into an enhanced feature vector as a face descriptor. however, it was unclear whether the obtained results were due to the use of local regions (instead of a holistic approach) or to the discriminative power of lbp. in this work, we investigated this issue by adopting and comparing four different texture features when using the appearances of local regions. the experimental results clearly showed and confirmed the validity of using lbp for face description.
supervised nonparametric information theoretic classification. in this paper, supervised nonparametric information theoretic classification (itc) is introduced. its principle relies on the likelihood of a data sample of transmitting its class label to data points in its vicinity. itc's learning rule is linked to the concept of information potential and the approach is validated on ripley's data set. we show that itc may outperform classical classification algorithms, such as probabilistic neural networks and support vector machines.
the new focal point localization algorithm for fingerprint registration. the new algorithm of unique point localization for fingerprint registration is proposed. the focal point, an average center of curvature of fingerprint, is the unique and reliable reference point, suitable for fingerprint registration. in this paper, the new approach demonstrates fast and reliable reference point. moreover, the focal point can be located even it is out of original fingerprint boundary and singularity is not exist.
a subspace approach to face detection with support vector machines. we present a subspace approach to face detection with support vector machine (svms). a linear svm classifier is trained as a filter to produce a subspace in which a non-linear svm classifier with gaussian kernel is trained for face detection. this makes training easier and results in a very efficient face detection algorithm. experimental results demonstrate their promising performance compared with some well-known existing detectors.
a comparative study of several modeling approaches for large vocabulary offline recognition of handwritten chinese characters. in this paper, we compare three representative modeling approaches, namely the multiple-prototype-based template matching approach, the subspace approach and the continuous density hidden markov model approach for large vocabulary offline recognition of handwritten chinese characters. on a task of classification of 4616 handwritten chinese characters, we evaluate and compare the strength and weakness of individual approaches in terms of the classification accuracy, the memory requirement and the computational complexity. we offer recommendations for practitioners on how to make intelligent use of these modeling approaches for different purposes in different applications.
binocular hand tracking and reconstruction based on 2d shape matching. this paper presents a method for real-time 3d hand tracking in images acquired by a calibrated, possibly moving stereoscopic rig. the proposed method consists of a collection of techniques that enable the modeling and detection of hands, their temporal association in image sequences, the establishment of hand correspondences between stereo images and the 3d reconstruction of their contours. building upon our previous research on color-based, 2d skin-color tracking, the 3d hand tracker is developed through the coupling of the results of two 2d skin-color trackers that run independently on the two video streams acquired by a stereoscopic system. the proposed method runs in real time on a conventional pentium 4 processor when operating on 320x240 images. representative experimental results are also presented.
a perceptual shape descriptor. in this study, we present the two dimensional object silhouette by a one dimensional descriptor, which preserves the perceptual structure of its shape. the proposed descriptor is based on the moments of the angles between the bearings of a point on the boundary, in a set of neighborhood systems. at each point on the boundary, the angle between a pair of bearings is calculated to extract the topological information of the boundary in a given locality. the proposed method does not use any heuristic rule or empirical threshold value in the shape representation. the similarity between the patterns is measured by elastic matching of thedescriptors. the proposed shape descriptor is tested on dataset of mpeg 7 core experiments shape-1. the experiments show better results than the previous studies reported in the literature.
plane rectification using a circle and points from a single view. this paper presents a new method for planar rectification. the pattern used here contains one circle and two points with known distances to the circle. partial rectification is introduced to calculate the trace of the mapping centers from each distance constraint. the algorithm is derived by discovering three fixed points during a matrix transformation. complex coordinates are used to simplify this problem. our experiments demonstrate that this method achieves good performance.
recognition of off-line handwritten arabic words using hidden markov model approach. hidden markov models (hmm) have been used with some success in recognizing printed arabic words. in this paper, a complete scheme for totally unconstrained arabic handwritten word recognition based on a model discriminant hmm is presented. a complete system able to classify arabic-handwritten words of one hundred different writers is proposed and discussed. the system first attempts to remove some of variation in the images that do not affect the identity of the handwritten word. next, the system codes the skeleton and edge of the word so that feature information about the lines in the skeleton is extracted. then a classification process based on the hmm approach is used. the output is a word in the dictionary. a detailed experiment is carried out and successful recognition results are reported.
a fusion methodology based on dempster-shafer evidence theory for two biometric applications. different features carry more or less rich and varied pieces of information to characterize a pattern. the fusion of these different sources of information can provide an opportunity to develop more efficient biometric system compared when using a feature vector. thus a new automatic fusion methodology using different sources of information (different feature sets) is presented here. dempster-shafer evidence theory is employed for this purpose. for performance evaluation significqntly large data sets of the biometric sources signature and hand shqpe are used. the results on combining different feature vectors compared to a single vector with our approach prove the importance of a fusion process.
introducing termination probabilities to hmm. hmm is very well suited to model sequential patterns. this paper introduces a new parameter, the termination probability, to hmm. the new parameter provides a better initialization for the backward variable during the training and evaluation phases. this improves the discriminatory power of hmm by allowing the system to judge the input observation sequence based on where it is completed. experimental results show the improvement achieved by this parameter.
texture classification using curvelet statistical and co-occurrence features. texture classification has long been an important research topic in image processing. now a days classification based on wavelet transform is being very popular. wavelets are very effective in representing objects with isolated point singularities, but failed to represent line singularities. recently, ridgelet transform which deal effectively with line singularities in 2-d is introduced. but images often contain curves rather than straight lines, so curvelet transform is designed to handle it. it allows representing edges and other singularities along lines in a more efficient way when compared with other transforms. in this paper, the issue of texture classification based on curvelet transform has been analyzed. curvelet statistical features (csfs) and curvelet co-occurrence features (ccfs) are derived from the sub-bands of the curvelet decomposition and are used for classification. experimental results show that this approach allows obtaining high degree of success rate in classification.
efficient estimation of pen trajectory from off-line handwritten words. this paper presents an easy and efficient method to estimate the pen trajectory based on minimizing the pen movement. given start and end vertices, the complexity of the proposed algorithm is linear. in addition, the algorithm clearly identifies alternatives that do not affect the overall length of the pen trajectory, making enough room for other criteria, e.g. vision rules, to be applied.
rejection strategies and confidence measures for a k- nn classifier in an ocr task. in handwritten character recognition, the rejection of extraneous patterns, like image noise, strokes or corrections, can improve significantly the practical usefulness of a system. in this paper, a combination of two confidence measures defi ned for a k-nearest neighbors classifier is proposed. experiments are presented comparing the performance of the same system with and without the new rejection rules.
learning to imitate human movement to adapt to environmental changes. a model for learning human movement is proposed. the learning model generates plausible trajectories of limbs that mimic the human movement. the learning model is able to generalize these trajectories over extrinsic constraints. these constraints result from the space of start and end configuration of the human body and task-specific constraints such as obstacle avoidance. this generalization is a step forward from existing systems that can learn single gestures only. such a model is needed to develop humanoid robots that move in a human-like way in reaction to diverse changes in their environment. the model proposed to accomplish this uses a combination of principal component analysis (pca) and a special type of a topological map called the dynamic cell structure (dcs) network. experiments on a kinematic chain of 3 joints show that this model is able to successfully generalize movement using a few training samples for both free movement and obstacle avoidance.
off-line signature verification based on the modified direction feature. signature identification and verification has been a topic of interest and importance for many years in the area of biometrics. in this paper we present an effective method to perform off-line signature verification and identification. to commence the process, the signature's contour is first determined from its binary representation. unique structural features are subsequently extracted from the signature's contour through the use of a novel combination of the modified direction feature (mdf) in conjunction with additional distinguishing features to train and test two neural network-based classifiers. a resilient back propagation neural network and a radial basis function neural network were compared. using a publicly available database of 2106 signatures containing 936 genuine and 1170 forgeries, we obtained a verification rate of 91.12%.
learning mixtures of offline and online features for handwritten stroke recognition. in this paper we propose a novel scheme to combine offline and online features of handwritten strokes. the stateof- the-art methods in handwritten stroke recognition have used a pre-determined combination of these features, which is not optimal in all situations. the proposed model addresses this issue by learning mixtures of offline and online characteristics from a set of exemplars. each stroke is represented as a probabilistic sequence of substrokes with varying compositions of these features. the model adapts to any stroke and chooses the feature composition that best characterizes it. the superiority of the method is demonstrated on handwritten numeral and character strokes.
differential epipolar constraint in mobile robot egomotion estimation. the estimation of camera egomotion is a well established problem in computer vision. many approaches have been proposed based on both the discrete and the differential epipolar constraint. the discrete case is mainly used in self-calibrated stereoscopic systems, whereas the differential case deals with an unique moving camera. this article surveys several methods for mobile robot egomotion estimation covering more than 0.5 million samples using synthetic data. results from real data are also given. the surveyed algorithms have been programmed and are available on the internet:http://eia.udg.es/-armangue/research.
modeling shape and topology of 3d images of biological specimens. this paper presents an efficient way of representing the geometry and topology of 3d images of biological specimens derived from electron microscopy. a vector quantization algorithm is used in order to select a reduced set of interior points that best approximates the probability density function of the original volumetric data. object's geometry and topology are obtained from the point set by the use of the alpha shapes theory.
3d modeling from turntable sequences using dense stereo carving and multi-view consistency. this paper addresses the problem of reconstructing a 3-d model, with texture, from a sequence of images of the object taken from a turntable. previous approaches have successfully solved the problem either using active interaction techniques, like the laser pen in immersion's lightscribe commercial system or directly relying on objects texture (not implemented commercially). in contrast, we present a general methodology, which combines silhouette carving with dense stereo and multi-view consistency. it functions even in the presence of highlights or lack of texture. results are presented on real objects with the above-mentioned characteristics.
compressed spatio-temporal descriptors for video matching and retrieval. the contents of a video can be described in terms of appearance and motion of the scenes. in this paper, we propose a compressed spatio-temporal descriptor that is suitable for video matching and retrieval tasks. we use a modified wavelet based compression technique that exploits the temporal redundancy of the data using optical flow. in order to achieve a compact flow representation, a spline based technique is used. the optical flow field gives the directions along which the gray levels have regular variations in time. wavelet decomposition along these directions results in fewer coefficients and thus higher compression. we demonstrate that the wavelet coefficients and flow parameters can be efficiently used for 1) video retrieval and matching, and 2) calculating spatio-temporal similarity between articulated objects. the results are demonstrated on several sequences.
trains of keypoints for 3d object recognition. this paper presents a 3d object recognition method that exploits the spatio-temporal coherence of image sequences to capture the object most relevant features. we start from an image sequence that describes the object's visual appearance from different view points. we extract local features (sift) and track them over the sequence. the tracked interest points form trains of features that are used to build a vocabulary for the object. training images are represented with respect to that vocabulary and an svm classifier is trained to recognize the object. we present very promising results on a dataset of 11 objects. tests are performed under varying illumination, scale, and scene clutter.
perception planning for an exploration task of a 3d environment. the incremental recovery of the 3d model of a closed environment is a complex task as it involves several functions: 3d acquisition, data registration and fusion, construction of a 3d triangular mesh or other representations. the sensor must be placed in several positions so that the resulting model is complete (no unseen areas) and has the required resolution. this paper presents a method devoted to the selection of the next best view for a sensor used for 3d modelling of an environment; the objective is to minimise the number of acquisitions and optimise the quality of the final model. from the current sensor position, an optimal next view is selected by the use of utility functions computed for some possible solutions; the method combines exhaustive search and hill climbing optimisation. thanks to a simulation, results are presented for a synthetic environment, using a virtual 3d sensor on a 5 degrees of freedom robot.
estimating fibre twist and aspect ratios in 3d voxel volumes. aspect ratios and twist measures can help us characterise paper fibre properties. such measures, that need volume data, are presented here. to test the developed methods, simulated voxel volumes of fibr es were created by defining each fibr e as a spline curve with an elliptical cross sectional shape and a constant twist per length unit. this allows us to directly compare the measurements from the voxel volume to the properties of the original spline fibres. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
analysis of ramp discontinuity model for multiscale image segmentation. this paper presents an algorithm for multiscale image segmentation. towards this, it proposes a new region model, that of a homogenous region surrounded by ramp discontinuities (a scenario usually encountered in real images). this paper presents the analysis of this model, leading to a robust algorithm for detection of ramp discontinuities in the image, and finally segmentation of the image at different photometric scales. the algorithm is further specialized for detecting very thin regions. the final segmentation algorithm can detect regions in the image, with varying photometric scales, sizes and arbitrary geometric properties. the properties of the algorithm are experimentally verified on synthetic and real images.
spatial-variant image filtering based on bidimensional empirical mode decomposition. this paper presents a fully automatic spatialvariant approach for image filtering and representation based on bidimensional empirical mode decomposition (bemd). unlike traditional filtering strategies which demonstrate poor performance for multicomponent, non-stationary images, the proposed method adaptively tracks the local characteristics of image intensities. in this paper, we first describe our own bemd algorithm and use it to decompose gray level images into a finite number of spatial frequency components, called intrinsic mode functions (imf). then based on the statistical properties of the imfs, features can be extracted. the idea is to group certain adjacent modes together to realize image filtering. experiments on natural multipartite images have indicated the effectiveness of our approach.
new experiments on icp-based 3d face recognition and authentication. in this paper, we discuss new experiments on face recognition and authentication based on dimensional surface matching. while most of existing methods use facial intensity images, a newest ones focus on introducing depth information to surmount some of classical face recognition problems such as pose, illumination, and facial expression variations. the presented matching algorithm is based on icp (iterative closest point) that provides perfectly the posture of presented probe. in addition, the similarity metric is given by spatial deviation between the overlapped parts in matched surfaces. the general paradigm consists in building a full 3d face gallery using a laser-based scanner (the off-line phase). at the on-line phase, identification or verification, only one captured 2.5d face model is performed with the whole set of 3d faces from the gallery or compared to the 3d face model of the genuine, respectively. this probe model can be acquired from arbitrary viewpoint, with arbitrary facial expressions, and under arbitrary lighting conditions.a new multi-view registered 3d face database, including these variations, is developed within biosecure workshop 2005 in order to perform significant experiments.
curvature scale space corner detector with adaptive threshold and dynamic region of support. corners play an important role in object identification methods used in machine vision and image processing systems. single-scale feature detection finds it hard to detect both fine and coarse features at the same time. on the other hand, multi-scale feature detection is inherently able to solve this problem. this paper proposes an improved multi-scale corner detector with dynamic region of support, which is based on curvature scale space (css) technique. the proposed detector first uses an adaptive local curvature threshold instead of a single global threshold as in the original and enhanced css methods. second, the angles of corner candidates are checked in a dynamic region of support for eliminating falsely detected corners. the proposed method has been evaluated over a number of images and compared with some popular corner detectors. the results showed that the proposed method offers a robust and effective solution to images containing widely different size features.
monnet: monitoring pedestrians with a network of loosely-coupled cameras. monnet is a visual surveillance system for tracking pedestrians over extended premises. the monnet system is composed of intelligent nodes, which exchange information on the individually tracked pedestrians in an asynchronous manner. each node in monnet builds an appearance model for every observed pedestrian and compares it with models received from other nodes. the compact appearance models based on colour cues and face biometrics are stored locally on each node. the system is dynamically reconfigurable since its design allows for adding/removing nodes in a simple manner, comparable to the 'plug and play' technology. monnet also contains an optional 'observer' node for interactive data visualization. this node displays a user interface which allows a human operator to observe and to interact in real-time with the distributed tracking process. monnet was extensively tested with and without user input, and it is able to function correctly in both modes.
fast support vector machine classification using linear svms. we propose a classification method based on a decision tree whose nodes consist of linear support vector machines (svms). each node defines a decision hyperplane that classifies part of the feature space. for large classification problems (with many support vectors (svs)) it has the advantage that the classification time does not depend on the number of svs. here, the classification of a new sample can be calculated by the dot product with the orthogonal vector of each hyperplane. the number of nodes in the tree has shown to be much smaller than the number of svs in a non-linear svm, thus, a significant speedup in classification time can be achieved. for non-linear separable problems, the trivial solution (zero vector) of a linear svm is analyzed and a new formulation of the optimization problem is given to avoid it.
incremental pca or on-line visual learning and recognition. the methods for visual learning that compute a space of eigenvectors by principal component analysis (pca) traditionally require a batch computation step. since this leads to potential problems when dealing with large sets of images, several incremental methods for the computation of the eigenvectors have been introduced. however, such learning cannot be considered as an on-line process, since all the images are retained until the final step of computation of space of eigenvectors, when their coefficients in this subspace are computed. in this paper we propose a method that allows for simultaneous learning and recognition. we show that we can keep only the coefficients of the learned images and discard the actual images and still are able to build a model of appearance that is fast to compute and open-ended. we performed extensive experimental testing which showed that the recognition rate and reconstruction accuracy are comparable to those obtained by the batch method.
segmentation and typography extraction in document images using geodesic active regions. this paper is addressed to the problem of typography extraction in document images. for that, we propose the use of robust textural image processing methods (gabor filtering and the geodesic active regions model) instead of the classical document image processing techniques (physical segmentation and logical labeling) which work at a pixel level and are very sensitive to a lot of parameters such as: noise, skewing... we show, on a few examples, that our method is generic enough to cope with a lot of recurrent problems in the field of document processing.
morse homology descriptor for shape characterization. in this paper, we propose a new topological method for shape description that is suitable for any multi-dimensional data set that can be modelled as a manifold.the description is obtained for all pairs (m, f), where m is a closed smooth manifold and f a morse function defined on m.more precisely, we characterize the topology of all pairs of lower level sets (m_y, m_x) of f, where m_a = f^{-1} ((-¿, a]), for all a ¿ r.classical morse theory is used to establish a link between the topology of a pair of lower level sets of f and its critical points lying between the two levels.
light: local invariant generalized hough transform. in this paper, we present a novel method for 2d shape extraction based on the hough transform. the method is applicable under similarity transformations while maintaining the dimensionality of the problem as that of the original ght. this is possible due to the use of a set of fourier based descriptors which remain invariant under translation, scale and rotation. in contrast with other invariants used in the same context, the descriptors we present here are local, and therefore our method is specially tolerant to noise and occlusion. experimental results are presented demonstrating performance on highly occluded scenes and showing significantly superior performance of our method, related to the ght, in the presence of global unmodelled deformations.
image-based rendering of synthetic diffuse objects in natural scenes. we present a method for solving the global illumination problem for synthetic diffuse objects. the approach generates realistic shading for applications where a synthetic object is to be inserted in a natural scene. using only a few images of the surroundings of the object, we first build an environment map for representing the ambient light. we then model the global illumination integral using chebyshev polynomials. we show that due to the orthogonality of 2d chebyshev moments, the global illumination integral can reduce to the inner product of two vectors, representing the irradiance and the bidirectional reflectance distribution function (brdf). the chebyshev moments of these two functions are computed off-line and stored in the memory. the rendering of the object in the scene then becomes a simple problem of computing the inner product of the two vectors for each point.
image classification from generalized image distance features: application to detection of interstitial disease in chest radiographs. one of the most important tasks in medical image analysis is to detect the absence or presence of disease in an image, without having precise delineations of pathology available for training. a novel method is proposed to solve such a classification task, based on a generalized representation of an image derived from local per-pixel features. from this representation, differences between images can be computed, and these can be used to classify the image requiring knowledge of only global image labels for training. it is shown how to construct multiple representations of one image to get multiple classification opinions and combine them to smooth over errors of individual classifiers. the performance of the method is evaluated on the detection of interstitial lung disease on standard chest radiographs. the best result is obtained for the combining classification scheme yielding an area under the roc curve of 0.955.
approximating high dimensional probability distributions. we present an approach to estimating high dimensional discrete probability distributions with decomposable graphical models. starting with the independence assumption we add edges and thus gradually increase the complexity of our model. bounded by the minimum description length principle we are able to produce highly accurate models without overfitting. we discuss the properties and benefits of this approach in an experimental evaluation and compare it to the well studied chow-liu algorithm.
finding rule groups to classify high dimensional gene expression datasets. microarray data provides quantitative information about the transcription profile of cells. to analyze microarray datasets, methodology of machine learning has increasingly attracted bioinformatics researchers. some approaches of machine learning are widely used to classify and mine biological datasets. however, many gene expression datasets are extremely high dimensionality, traditional machine learning methods can not be applied effectively and efficiently. this paper proposes a robust algorithm to find out rule groups to classify gene expression datasets. unlike the most classification algorithms, which select dimensions (genes) heuristically to form rules groups to identify classes such as cancerous and normal tissues, our algorithm guarantees finding out best-k dimensions (genes), which are most discriminative to classify samples in different classes, to form rule groups for the classification of expression datasets. our experiments show that the rule groups obtained by our algorithm have higher accuracy than that of other classification approaches.
ethiopic character recognition using direction field tensor. many languages in ethiopia use a unique alphabet called ethiopic for writing. however, there is no ocr system developed to date. in an effort to develop automatic recognition of ethiopic script, a novel system is designed by applying structural and syntactic techniques. the recognition system is developed by extracting primitive structural features and their spatial relationships. a special tree structure is used to represent the spatial relationship of primitive structures. for each character, a unique string pattern is generated from the tree and recognition is achieved by matching the string against a stored knowledge base of the alphabet. to implement the recognition system, we use direction field tensor as a tool for character segmentation, and extraction of structural features and their spatial relationships. experimental results are reported.
image interpolation by high dimensional projection based on subspace method. this paper presents a new image interpolation technique for image cracking such as telop character occlusion or picture deterioration. the landscape picture and texture pattern or other natural scenes contain the behavior of the autocorrelation pattern, and a method of image interpolation based on the autocorrelation pattern has been established. this method extracts many local regions from a piece of image and generates a subspace by the image vectors. the subspace limits the freedom of the image description at the local region by the hyperplane restriction in the image vector space. this paper explains for an image interpolation method based on eigen-space and explains the expansion using kernel non-linear projection.
a computational algebraic topology approach for optical flow. this paper proposes an alternative to partial differential equations (pdes) for the solution of the optical flow problem. the problem is modeled using the heat transfer process. instead of using pdes, we propose to use the global equation of heat conservation. we use a computational algebraic topology-based image model which allows us to encode some underlying physical laws by linking a global value on a domain with values on its boundary. the numerical scheme is derived in a straightforward way from the problem modeled and provides a physical explanation of each solving step. experimental results are presented.
anomaly detection for video surveillance applications. we investigate the problem of anomaly detection for video surveillance applications. in our approach, we use a compression-based similarity measure to determine similarity between images in a video sequence. images that are sufficiently dissimilar are deemed anomalous and stored to be compared against subsequent images in the sequence. the goal of our research is two-fold; in addition to detecting anomalous images, the issue of heavy computational and storage resource demands is addressed.
lie algebra template tracking. visual cues are often very difficult to track. we use an effective least squares estimation of the lie algebra parameters to find the affine transformation involved in a visual region tracking. these parameters represent the geodesics of the optimal transformation orbit. our experiments validate the effectiveness of the method.
improving seismic horizon matching by ordinal measures. many processing and interpretation tasks of seismic images are based on cross-correlation (cc) as a measure of similarity of reflection patterns. although cc has several advantages over other correlation methods, it is very sensitive to nonlinear intensity variations or single outliers, which are however characteristic for seismic data. we show for the example of horizon matching across faults, that more robust ordinal measures can perform better, especially in case of poor data quality.
geometric neurocomputing for pattern recognition and pose estimation. this paper presents a geometric neurocomputing approach for 3d pose recognition using the framework of the geometric clifford algebras. the type of geometric problems like pattern recognition and 3d pose recognition can be very efficiently handled using geometric neural networks. our experimental part shows the application of generalized clifford moments for pattern recognition and 3d pose estimation of rigid objects using visual information captured by a trinocular head.
online learning of discriminative patterns from unlimited sequences of candidates. recent research in object recognition has demonstrated the advantages of representing objects and scenes through localized patterns such as small image templates. in this paper we study the selection of patterns in the framework of extended supervised online learning, where not only new examples but also new candidate patterns become available over time. we propose an algorithm that maintains a pool of discriminative patterns and improves the quality of the pool in a disciplined manner over time. the proposed algorithm is not tied to any specific pattern type or data domain. we evaluate the method on several object detection tasks.
visual recognition of similar gestures. naturalness and effectiveness of gesture-based communication strongly depend on the success of gesture recognition. however, confusion in classification increases when considering gestures with similar evolutions. given that neither typical motion-based features, nor hidden markov models are capable to distinguish accurately among them, it is common to consider only gestures that require different forms of execution. in this paper, we present empirical evidence showing that, in addition to motion, posture information significantly increases classification rates, even with similar gestures. moreover, for recognition, we propose dynamic naive bayesian classifiers. in comparison to hidden markov models, these models require less iterations of the em algorithm for training, while keeping competitive classification rates. the proposed system was evaluated considering 9 classes of similar gestures, showing a significant increase in performance by integrating motion and posture attributes.
an accurate discrete fourier transform for image processing. the classical method of numerically computing the fourier transform of digitized functions in one or in d-dimensions is the so-called discrete fourier transform (dft), efficiently implemented as fast fourier transform (fft) algorithms. in many cases the dft is not an adequate approximation of the continuous fourier transform. the method presented in this contribution provides accurate approximations of the continuous fourier transform with similar time complexity. the assumption of signal periodicity is no longer posed and allows to compute numerical fourier transforms in a broader domain of frequency than the usual half-period of thedft. in image processing this behavior is highly welcomed since it allows to obtain the fourier transform of an image without the usual interferences of the periodicity of the classical dft. the mathematical method is developed and numerical examples are presented.
a unified system for segmentation and tracking of face and hands in sign language recognition. this paper presents a unified system for segmentation and tracking of face and hands in a sign language recognition using a single camera. unlike much related work that uses colour gloves, we detect skin by combining 3 useful features: colour, motion and position. these features together, represent the skin colour pixels that are more likely to be foreground pixels and are within a predicted position range. we extend the previous research in occlusion detection to handle occlusion between any of the skin objects using a kalman filter based algorithm. the tracking improves the segmentation by reducing the search space and the segmentation enhances the overall tracking process. the algorithm is tested on several video sequences from a standard database and can provide a very low error rate.
interactive tools for pattern discovery. real-world pattern recognition problems contain rich context that must be taken into account in solution development. beyond the core classification tasks, there are several common challenges including the need to correlate non-comparable groups of variables while preserving data proximity relationships within each group, visualization of data geometry, rapid trial of many methodological alternatives, and integration with existing infrastructure. we explore the effective methods and tools to meet with these challenges. we describe a graphical software, mirage, as an experiment to address such concerns.
geometric approach for pose detection of moving human heads. this paper presents the detection of 3d pose of moving humans heads. the contribution of this work is the conjunction of an effective preprocessing method and a strong estimation kalman technique which uses less noise sensitive 3d line observations. the procedure involves the detection of the target face in any type of background using color histograms. to outline the face we use a minimization algorithm for the determination of its tangent directions. face 3d lines are coded in terms of motors (dual quaternions) which are used by a motor extended kalman filter for the estimation of the 3d pose of the head through time.
real time tracking for 3d realistic lip animation. this article deals with facial segmentation and liptracking with feedback control for real-time animation of a synthetic 3d face model. classical approaches consist in two successive steps : video analysis then synthesis. we want to build a global analysis/synthesis processing loop, where the image analysis needs the 3d synthesis and conversely. for that, we fit a generic 3d-face model on the speaker's face in our analysis algorithm for using synthesis information (like 3d information or face shape). this approach is inspired from control systems theory with feedback loops. the contribution of the paper is to use simple image processing techniques on available data, but to improve segmentation through the feedback loop. moreover, we propose a robust lip corners tracking based on estimation motion algorithm. the speaker is only asked to be in front of the camera with the mouth closed at the beginning of the video session (neutral position). this allows to do a quick initialisation step in order to fit the 3d-face model. results show that real-time (30hz) and robust performances are achievable under real-world conditions, which are two key issues for face and lip tracking applications.
kmod - a tw o-parameter svm kernel for pattern recognition. it has been shown that support vector machine theory optimizes a smoothness functional hypothesis through kernel application. we present kmod a two - parameter svm kernel with distinctive properties of good discrimination between patterns while reserving the data neighborhood information. in classification problems the experiments we carried out on the breast cancer benchmark produced better performance than rbf kernel and some stat e of the art classifiers. as well it also generated favorable results when subjected to a 10-class problem of recognizing handwritten digits in th e nist database .
blind super-resolution using a learning-based approach. the super-resolution of a single image of unknown point-spread-function (psf) is addressedby extending a learning framework using blind deconvolution with an uncertainty around the resulting psf. results indicate success in refining the estimate of the psf as well as to restoring the image. a novel disparity measure is also proposed to quantify the results.
speech music discrimination using class-specific features. in this paper the application of the class-specific features approach to classification is demonstrated for the problem of discriminating between speech and music. feature extraction is class-specific and can therefore be tailored to each class meaning that segment size, model orders and the type of features used can be different for the classes. the performance of the discriminator is evaluated and an example of how classification is possible without training is given.
probabilistic matching of image- to model-features for real-time object tracking. background clutter produces a difficult problem for edge matching within model-based object tracking approaches. the solution of matching all possible candidate image features with themodel features is computationally infeasible for real-time tracking. it is proposed to draw probabilistic samples of candidate sets based on measures for local topological constraints. line features are constraint by parallel and junction constraints. continuous measures are used for evaluation of the match of the features sets to avoid thresholds. this approach limits the number of matchings and processing time increases linearly with the number of features. experiments show the correct selection among multiple candidates for different scenarios.
morphological tagging approach in document analysis of invoices. in this paper a morphological tagging approach for document image invoice analysis is described. tokens close by their morphology and confirmed in their location within different similar contexts make apparent some parts of speech representative of the structure elements. this bottom up approach avoids the use of an priori knowledge provided that there are redundant and frequent contexts in the text. the approach is applied on the invoice body text roughly recognized by ocr and automatically segmented. the method makes possible the detection of the invoice articles and their different fields. the regularity of the article composition and its redundancy in the invoice is a good help for its structure. the recognition rate of 276 invoices and 1704 articles, is over than 91.02% for articles and 92.56% for fields.
neural network-based proper names extraction in fax images. in this paper, we are interested in the sender's name extraction in fax cover pages through a machine learning scheme. for this purpose, two analysis methods are implemented to work in parallel. the first one is based on image document analysis (ocr recognition, physical block selection), the other on text analysis (word feature extraction, local grammar rules). our main contribution consisted in introducing a neural network to find an optimal combination of the two approaches. tests carried on real fax images show that the neural network improves performance compared to an empirical combination function and to each method used separately.
a unified camera calibration using geometry and blur of feature points. although a lot of camera calibration methods have been proposed so far, most of them deal with the pinhole camera model, which neglects the defocus effects introduced by real lens systems. in this paper, we present a unified camera calibration method which determines both internal and external camera parameters from several blurred edges detected in a single image. first, we show the calibration procedure using our thin lens based camera model. then, we describe how to determine the position and the width of blurred features in an image. experiments have been done with real images and those results have shown the validity of our method.
medical image compression: study of the influence of noise on the jpeg 2000 compression performance. in this paper the eficiency of the jpeg 2ooo scheme combined with a complementary denoising process is analyzed on simulated and real denial ortho-pantomographic images, where the simulation images are perturbed by poisson noise. the case of dental radiography is investigated, because radiographic images are a combinatron between the relevant signal and a significant amount of acquisition noise, which is per definition not compressible. the noise behaves generally close to poisson statistics, which generally affects the compression rformance. the denoising process is supported by monte carlo noise modeling, which is introduced in the jpeg 2000 compression scheme to improve the compression ebciency of the medicul images in terms of compression ratio and image qualip f t f i selected images are denoised and the compression ratio, using lossless and lossy jpeg 2000, is reported and evaluated.
shape representation using concavity graphs. in this paper, a new graph data structure for 2-d shape representation is proposed. the new structure is called a concavity graph, and is an evolution from the already known "concavity tree". even though a concavity graph bears a fundamental resemblance to a concavity tree, the former is able to describe the shape of multiple objects in an image and their spatial configuration, and is hence inherently more complex.the aim of concavity graphs is two-fold: first we want to analyze the patterns in a multi-object image in a way that will (1) provide better representation of their shapes, and (2) convey useful information about how they "interact" together. second, we want our analysis technique to facilitate similarity matching between two images. this paper introduces the new structure and outlines how it can be used for shape representation as well as similarity matching.
multiple object tracking using local pca. tracking multiple interacting objects represents a challenging area in computer vision. the tracking problem in general can be formulated as the task of recovering the spatio-temporal trajectories for an unknown number of objects appearing and disappearing at arbitrary times. observations are noisy, their origin is unknown, generated by true detections or false alarms. data association and the estimation of object states are two crucial tasks to be solved in this context. this work describes a novel, computationally efficient tracking approach to generate consistent trajectories. first, trajectory segments are created by analyzing the spatio-temporal data distribution using local principal component analysis. subsequently, linking between trajectory segments is carried out relying on spatial proximity and kinematic smoothness constraints. tracking results are demonstrated in the context of human tracking and compared to results of a frame-to-frame-based tracking approach.
shape retrieval using concavity trees. concavity trees are well-known abstract structures. this paper proposes a new shape-based image retrieval method based on concavity trees. the proposed method has two main components. the first is an efficient (in terms of space and time) contour-based concavity tree extraction algorithm. the second component is a recursive concavity-tree matching algorithmthat returns a distance between two trees. we demonstrate that concavity trees are able to boost the retrieval performance of two feature sets by at least 15% when tested on a database of 625 silhoutte images.
binary image transformation using two-dimensional chaotic maps. we present an algorithm for binary image transformation using chaotic maps. because of its random-like behavior, chaos is a good candidate for encryption. we show that a two-dimensional discrete time dynamical system with one positive lyapunov exponent allows the transformation of the image in an unpredictable manner. the suggested algorithm acts on the pixel position, where the diffusion property resulting from the sensitivity to the initial states is used to accomplish the transformation in a random-like way. the suggested algorithm uses three types of keys: initial state, external parameters and the number of iterations. using the so-called henon map as an example, we show that the algorithm produces almost uncorrelated images even when the keys are slightly changed, making it an attractive and fast method for image encryption.
non-isotropic regularization of the correspondence space in stereo-vision. the correspondence problem in stereo vision is notoriously difficult. inany approaches a noisy solution is extracted fro the correspondence space. various sophisticated regularization techniques are applied then on this noisy solution. we study here the possibility to denoise the correspondence/correlation space before extracting the solution, by a non-linear and non-isotropic scheme. we showthat this methods preserves edges (depth discontinuities) welland overcomes some of the problems encountered in previous approaches.
filtering with gray-code kernels. in this paper we introduce a family of filter kernels - the gray-code kernels (gck) and demonstrate their use in image analysis. filtering an image with a sequence of gray-code kernels is highly efficient and requires only 2 operations per pixel for each filter kernel, independent of the size or dimension of the kernel. we show that the family of kernels is large and includes the walsh-hadamard kernels amongst others. the gck can also be used to approximate arbitrary kernels since a sequence of gck can form a complete representation. the efficiency of computation using a sequence of gck filters can be exploited for various real-time applications, such as, pattern detection, feature extraction, texture analysis, and more.
learning bayesian network classifiers for credit scoring using markov chain monte carlo search. in this paper, we will evaluate the power and usefulness of bayesian network classifiers (probabilistic networks) for credit scoring. various types of bayesian network classifiers will be evaluated and contrasted including unrestricted bayesian network classifiers learned using markov chain monte carlo (mcmc) search. the experiments will be carried out on three real life credit scoring data sets. it will be shown that mcmc bayesian network classifiers have a very good performance and by using the markov blanket concept, a natural form of feature selection is obtained, which results in parsimonious and powerful models for financial credit scoring.
eye tracking using markov models. we propose an eye detection and tracking method based on color and geometrical features of the human face using a monocular camera. in this method a decision is made on whether the eyes are closed or not and, using a markov chain framework to model temporal evolution, the subject's gaze is determined. the method can successfully track facial features even while the head assumes various poses, so long as the nostrils are visible to the camera. we compare our method with recently proposed techniques and results show that it provides more accurate tracking and robustness to variations in view of the face. a procedure for detecting tracking errors is employed to recover the loss of feature points in case of occlusion or very fast head movement. the method may be used in monitoring a driver's alertness and detecting drowsiness, and also in applications requiring non-contact human computer interaction.
ebem: an entropy-based em algorithm for gaussian mixture models. in this paper we address the problem of estimating the parameters of a gaussian mixture model. although the em algorithm yields the maximum-likelihood solution it requires a careful initialization of the parameters and the optimal number of kernels in the mixture may be unknown beforehand. we propose a criterion based on the entropy of the pdf (probability density function) associated to each kernel to measure the quality of a given mixture model. a novel method for estimating shannon entropy based on entropic spanning graphs is developed and a modification of the classical em algorithm to find the optimal number of kernels in the mixture is presented. we test our algorithm in probability density estimation, pattern recognition and color image segmentation.
improving evidential quality of surveillance imagery through active face tracking. we report on a system for automatically obtaining high-resolution images of surveillance targets. the system, beginning from a framed target, uses the presence of faces as a cue to initiate a real-time active face tracking process. using a single pan-tilt-zoom (ptz) camera, the system tracks the target while zooming in for a closeup image of the face. the system tracks feature points on a target face, and a simple yet reliable control strategy is used in conjunction with robust target localization to guide a ptz camera to a facial closeup of the target. we report on experiments with our system in real surveillance environments.
granulometric analysis of document images. we report on new form of multivariate granulometries based on rectangles of varying size and aspect ratio. these granulometries are used for describing visual similarity between document images. rectangular granulometries are used to probe the layout structure of document images, and the rectangular size distributions derived from them are used as descriptors for each image. feature selection is used to reduce the dimensionality and redundancy of thesize distributions, while preserving the essence of the visual appearance of a document. experimental results indicate that rectangular size distributions are an effective way tocharacterize visual similarity of document images, and provide insightful interpretation of classification results in the original image space.
vertebra edge detection using polar signature. in this paper we propose a new method of vertebrae segmentation in medical images. x-ray images of the spinal columns are analysed in order to extract a closed contour for each vertebra. to achieve this goal, we proceed by steps: the starting one is a segmentation approach based on the selection of each vertebra region. we use these regions information to identify each individual vertebra by its contour. for this task, we propose a polar signature representation of the contour using the image gradient of each region. lastly, an edge closing method exploiting polynomial fitting is used. we use the resulting extracted contours to determine vertebral mobility. for this, we proceed by the extraction of some parameters characterizing each vertebra, related to their form, position and orientation.
steerable kernels for arbitrarily-sampled spaces. this paper describes a procedure for generating steerable kernels corresponding to general image mappings (e.g. non-rigid transformations) for arbitrary image tesselations.
the chain-rule processor: optimal classification through signal processing. the chain-rule processor is a method of constructing an optimal bayes classifier from a bank of processors. each processor is a feature extractor designed to separate the given class from a class-dependent reference hypothesis, thereby avoiding the curse of dimensionality. this work builds upon prior work in optimal classifier design using class-specific features. the chain-rule processor is an improvement that recursively applies the pdf projection theorem.
object manipulation using fuzzy logic and geometric algebra. in this paper we present a method for object manipulation using a barrett hand and algorithms which involve fuzzy logic and conformal geometric algebra. the paper explains how we relate these two mathematical systems in order to implement algorithms for geometric computing under uncertainty. in the experimental part we show a task of visually-guided smooth grasping of real 3d objects.
hmms with explicit state duration applied to handwritten arabic word recognition. this paper describes an off-line segmentation-free handwritten arabic words recognition system. the described system uses discrete hmms with explicit state duration of various kinds (gauss, poisson and gamma) for the word classification purpose. after preprocessing, the word image is analyzed from right to left in order to extract from it a sequence of feature vectors. then, vector quantization is applied to this sequence and its output is submitted to a hmms classifier based on a likelihood criterion for identifying the word using the viterbi algorithm. several experiments were performed using the ifn/enit benchmark database, they showed, on the one hand, a substantial improvement in the recognition rate when hmms with explicit state duration of either discrete or continuous distribution are used instead of classical hmms (i.e. with implicit state duration), on the other hand, the gamma distribution for the state duration, that have given the best recognition rate (91.23 % in top 2), seems more suitable for the hmms based modeling of arabic handwriting..
a goal-oriented verification-based approach for target text line extraction from a document image captured by a pen scanner. in this paper, we present a goal-oriented verification-based approach for target text line extraction from a document image captured by a pen scanner. given a binary image, a series of processing steps are invoked adaptively, guided by the text line verification result in the preceding step. each step adopts a strategy that is most effective for dealing with the problem concerned. consequently, the target text line can be extracted in a more efficient and reliable way depending on the nature of the captured image. the effectiveness of the above approach is confirmed by a benchmark test.
underline detection and removal in a document image using multiple strategies. this paper presents a novel three-module approach for underline detection and removal in chinese/english ocr. the detection module uses strategies of connected component analysis and bottom edge analysis. the removal module uses different methods for different kinds of underlines. the disambiguation module is effected via recognition confidence comparison for reducing the risk of removing wrongly doubtful underlines. our approach can deal with untouched, touched, broken and slightly curved underlines. in a benchmark test using single text line images extracted from uw-i database and images captured by c-pen, we demonstrate that our approach has little negative effect on pure-text images, and can detect and remove reliably underlines in text line images with underlines.
a study of nonlinear shape normalization for online handwritten chinese character recognition: dot density vs. line density equalization. nonlinear shape normalization (nsn) approaches based on line density equalization have been the most popular choice for both offline and online handwritten chinese character recognition (hccr). however, in a recent study of using 8-directional features for online hccr, we discovered that an nsn approach based on dot density equalization achieved a much better performance than that of an nsn approach based on line density equalization. in this paper, we present the details of the nsn approaches we studied for online hccr, and report the comparative experimental results using an in-house developed chinese handwriting corpus as well as the popular nakayosi and kuchibue japanese character databases. we also present an improved nsn approach based on the equalization of dot densities derived from blurred character image that can be used for offline hccr.
a novel eye location algorithm based on radial symmetry transform. a novel and robust eye location algorithm is proposed in this paper. the algorithm is based on a low level, context free generalized symmetry transform. once the regions of interest are detected, characteristics of eyes can be used to improve detection results. the algorithm is tested using 1460 face images of the bioid database and 2730 images of the banca database. a fully automatic face verification system has also been developed using this eye location algorithm. the system was one of the top performers in the 2004 international face verification competition.
detection-assisted initialization, adaptation and fusion of body region trackers for robust multiperson tracking. in this paper, we present a system for simultaneous tracking of multiple persons in a smartroom using multiple cameras. robust person tracks are created, continuously adapted, and deleted by fusing cues from foreground segmentation maps and various appearance-based object detectors. tracking is performed using color histograms which are automatically filtered and adaptated based on local image characteristics. tracks from the various 2d views are merged to 3d position estimates by an intelligent fusion algorithm based on triangulation error reduction. the approach allows to robustly track moving, standing or sitting persons in cluttered environments and to successfully recover lost tracks at any point in the room. we also introduce a new set of metrics to measure multiple object tracking performance. our system reaches a high tracking accuracy with average position errors of less than 17cm.
graph matching using spectral embedding and alignment. this paper describes how graph-spectral methods can be used to transform the node correspondence problem into one of point-set alignment. we commence by using the isomap algorithm to embed the nodes of a graph in a low-dimensional euclidean space. with the nodes in the graph transformed to points in a metric space, we can recast the problem of graph-matching into that of aligning the points. here we use a variant of the scott and longuet-higgins algorithm to find point correspondences. we experiment with the resulting algorithmon a number of real-world problems.
real-time 3d articulated pose tracking using particle filters interacting through belief propagation. this article proposes a new statistical model for fast 3d articulated body tracking, similar to the loose-limbed model, but where inter-frame coherence is taken into account by using the previous marginal probability of each limb as prior information. belief propagation is used to estimate the current marginal for each limb. all probability distribution are represented as sums of weighted samples. the resulting algorithm corresponds to a set of particle filters, one for each limb, where the weight of each sample, after the standard evaluation, is recalculated by taking into account the interactions between limbs. applied to upper-body tracking in disparity and color images, the resulting algorithm estimates the body pose in quasi real-time (12hz).
a pattern recognition scheme for distributed denial of service (ddos) attacks in wireless sensor networks. we define distinct attack patterns depicting distributed denial of service (ddos) attacks against target nodes within wireless sensor networks for three most commonly used network topologies. we propose a graph neuron (gn)-based, decentralized pattern recognition scheme for attack detection. the scheme does analysis of internal traffic flow of the network for ddos attack patterns. we stipulate that the attack patterns depend on both the current energy levels, as well as the energy consumption rates of individual target nodes. the results of varying pattern update rates on the pattern recognition accuracies for the three network topologies are included in the end to test the effectiveness of our implementation.
generic detection of multi-part objects. a method is proposed to detect multi-part man-made or natural objects in complex images. it consists in first extracting simple curves and straight lines from the edge map. then, a search tree is expanded by selecting and ordering the segmented primitives on the basis of generic local and global grouping criteria. the set of partial contours provided by the parallel search are combined into more complex forms. global scores produce a sorted list of potential object silhouettes.
interaction-centric modelling for interactive virtual worlds: the apia approach. conceptual modelling studies the different abstraction methods of the real world. the conception and the execution of virtual worlds depend strongly of the type of conceptual models. existing modelling methods such as object-oriented modelling are not appropriated when the main concern is the dynamic reusability and interoperability. such a reusability and interoperability must be free of any human intervention. this paper presents a new paradigm named interaction-centric modelling (icm) that increases reusability and interoperability of virtual entities and behaviours.
2d grey-level skeleton computation: a discrete 3d approach. a discrete 3d binary approach to compute the skeleton in 2d grey-level images is presented. the 2d grey-level input image is converted to a 3d binary image and the top surface of the foreground is identified. this discrete surface then undergoes skeletonization. the obtained 3d curve skeleton is pruned, before being projected back to a 2d grey-level image. this is suitably post-processed, since the projection may cause spurious loops and thickening. this algorithm can find applications in optical character recognition and document analysis or in other situations where shape analysis by skeletons is desired. an important property of the suggested method is that no hard segmentation into foreground and background is needed prior to the skeletonization.
multiresolution spatial partitioning for shape representation. in this paper, an original solution for shape representation is proposed which relies on a spatial partitioning approach. the representation selects a discrete set of reference points with respect to which a relationship matrix is computed, accounting for the spatial distribution of shape pixels. this is accomplished at different levels of resolution by a tree based representation. depending on the number of points, coarse to fine region and boundary shape information are captured. properties of the representation are discussed and assessed through an experimental evaluation on a set of sample shapes.
modeling spatial relationships between 3d objects. in this paper, we propose an original modeling technique which enables quantitative non-symbolic representation and comparison of the mutual spatial positioning of extended entities in a 3d space. the representation accounts for the overall distribution of relationships among the individual points of two objects. properties of the model are expounded to develop an efficient computation technique and to motivate and assess a metric of similarity for quantitative comparison of spatial relationships between object pairs. experiments compare the proposed approach against two different solutions.
principal flow for tubular objects with non-circular cross-sections. various anatomical objects are tubular in shape. these structures can be modeled by describing their curvilinear path and the cross-sectional shape along the path. however, most research on tubular object segmentation has focused on vascular systems, and often assumes a circular cross-section. these techniques are not readily applicable to anatomy such as the cochlea, which has a non-circular cross-sectional shape. we present the principal flow filter, which calculates the flow vector (tangential to the path) in a local region of a tubular object with a non-circular cross-section. it can be used to extract the centerline orientation and thus incrementally track along the tube. we present results from generated data with a variety of cross-sectional shapes. the filter is shown to rapidly and robustly converge to the true orientation. we also analyse a ct scan of a human cochlea, with promising results.
extraction of resource descriptors for distributed content based image retrieval. content based retrieval from distributed libraries raises new and challenging issues with respect to retrieval from a single repository. in particular, an effective management of distributed libraries develops upon three main processes: resource description (extraction of descriptors that qualify the content of a given archive), resource selection (given a user query, select the resources that contain relevant documents) and results merging (organize and present items returned by individual libraries). so far, these issues have been mainly addressed for text archives. in this paper, we propose a novel approach to the extraction and verificationof resource descriptions for distributed collections of images.
pca for gender estimation: which eigenvectors contribute? a pruning schema is applied to multi-layer perceptron (mlp) gender classifier.mlp uses eigenvector coefficients of the face space created by principal component analysis (pca). we show that pruning improves the initial mlp performance by preserving the most effective input while eliminating most of the units and connections. pruning is also used as tool to monitor which eigenvectors contribute to gender estimation. in addition, by usage of feret face database, we test the pca approach on gender estimation task in bigger setting than the previous experiments.
partitioning of 3d meshes using reeb gra. in this paper, a model is proposed for partitioning of 3d objects based on reeb-graphs. the model is motivated by perceptual principles and supports identification of the main protrusions of an object. experimental results are presented to demonstrate the effectiveness of the proposed solution with respect to ground-truth data represented by manually segmented objects.
subpixel alignment of mri data under cartesian and log-polar sampling. magnetic resonance imaging (mri) allows numerous fourier domain sampling schemes such as cartesian and non-cartesian trajectories (e.g. polar, circular, and spherical). on the other hand, it provides directly the fourier spectrum of the field of view (fov) in the corresponding sampling scheme. motivated by these characteristic features of mri, we have developed a new scheme for direct fourier domain registration of mri data based on the phase difference matrix. we derive the exact relationship between the continuous and the discrete fourier phase-difference for cartesian or polar sampling schemes, and demonstrate that in each case the discrete phase diffence is a 2d sawtooth signal. subpixel alignment under rotation, translation and scale variation is then established simply by counting the number of cycles of the sawtooth signal. the problem is formulated as an over-determined system of equations, and is solved by imposing a regularity constraint, using the method of generalized cross validation (gcv).
a template-matching approach for protein surface clustering. surface-based techniques for protein comparison and classification typically require a compact surface representation, capable of effectively condensing its description. in this paper we propose an original template-matching algorithm for multi-feature surface clustering in the biochemical context. the effectiveness of our clustering algorithm in capturing surface similarities is then discussed within a larger framework for protein classification based on surface comparison, with the support of tests performed on a dataset including 25 proteins.
object-based and event-based semantic video adaptation. semantic video adaptation allows to transmit video content with different viewing quality, depending on the relevance of the content from the user's viewpoint. to this end, an automatic annotation subsystem must be employed that automatically detect relevant objects and events in the video stream. in this paper we present a composite framework that is made of an automatic annotation engine and a semantics-based adaptation module. three new different compression solutions are proposed that work at the object or event level. their performance is compared according to a new measure that takes into account the user's satisfaction and the effects on it of the errors in the annotation module.
early feature stream integration versus decision level combination in a multiple classifier system for text line recognition. this paper compares two different methods to combine feature streams to improve the performance of offline handwritten text line recognition systems. in both methods a pixel-based and a geometric feature stream are combined. the first method integrates the feature streams at an early stage whereas in the second method a combination step at the decision level is applied. in the experiments, the early integration approach outperforms the decision level combination as well as recognisers built from the individual feature streams.
switching particle filters for efficient real-time visual tracking. particle filtering is an approach to bayesian estimation of intractable posterior distributions from time series signals distributed by non-gaussian noise. a couple of variant particle filters have been proposed to approximate bayesian computation with finite particles. however, the performance of such algorithms has not been fully evaluated under circumstances specific to real-time vision systems. in this article, we focus on two filters: condensation and auxiliary particle filter (apf). we show their contrasting characteristics in terms of accuracy and robustness. we then propose a novel filtering scheme that switches these filters, according to a simple criterion, for realizing more robust and accurate real-time visual tracking. the eectiveness of our scheme is demonstrated by real visual tracking experiments. we also show that our simple switching method significantly helps online learning of the target dynamics, which greatly improves tracking accuracy.
mining for implications in medical data. accruing patients for clinical trials has been a tedious and time consuming task for clinicians. it requires extensive knowledge of the specific criteria for all available clinical trials. through interviews with clinicians, implications were discovered which reduced the number of required questions/answers to determine eligibility. after gathering and recording data on past breast cancer patients, the answers to the questions asked by an expert system were extracted. an association rule learner, was used to generate implication rules such as: male => not pregnant. it was determined that all current implication rules could be recovered with 100% confidence. further searching for additional rules resulted in the discovery of several which provided an improvement in the clinical ease of use of the webbased clinical trial assignment expert system.
corner detection using support vector machines. a support vector machine based algorithm for corner detection is presented. it is based on computing the direction of maximum gray-level change for each edge pixel in an image, and then representing the edge pixel by a four dimensional feature vector constituted by the count of other edge pixels lying in a window centred about and having each of the possible four directions as their direction of maximum local gray-level change. a support vector machine is designed using this feature vectors and the support vectors, representing critical points in a classification problem, correspond to the corner points. the algorithm is straightforward and does not involve computation of complex differential geometric operators. it has implicit learning capability resulting in good performance for a wide range of images.
a comparison of pixel, edge andwavelet features for face detection using a semi-naive bayesian classifier. henry schneiderman at carnegie mellon university developed a face detection algorithm based upon a semi-naive bayesian classifier and 5/3 linear phase wavelets. this paper explores the relative value of these wavelet features compared to simpler pixel and edge features. experiments suggest edge features are superior for highly controlled lighting, while pixel features are better and more stable for uncontrolled lighting. tests use the notre dame face data collected in fall 2003 and spring 2004 and use over 400, 000 face and non-face test image chips.
rule extraction from support vector machines: measuring the explanation capability using the area under the roc curve. recently, the area of rule extraction from support vector machines (svms) has been explored. one important indication of the success of a rule extraction method is the performance of extracted rules as compared to the original svm. in this paper, we describe the use of the area under the receiver operating characteristics (roc) curve (auc) to assess the quality of rules extracted from an svm. in particular, we directly compare auc to the more commonly used measures of accuracy and fidelity and show that auc is both a more reliable and meaningful measure to use.
age-related skin analysis by capacitance images. the skin surface characterization has a great importance for dermatologists as well as for cosmetic scientists in order to evaluate the effectiveness of medical or cosmetic treatments. skin topography characterization has been faced by using profilometers and skin replicas to achieve some measurements related to either skin 3d profile or wrinkles. so far, no in vivo measurements regarding skin topography changes have been achieved to evaluate skin ageing. this work describes how a portable capacitive device, normally used for fingerprint acquisition, can be utilized to achieve measures of skin ageing routinely. the capacitive images give a high resolution representation of skin topography, in terms of wrinkles and cells. in this work we have addressed the latter: cells have been segmented using the watershed approach and a feature related to their area distribution has been generated. accurate experiments accomplished in vivo show how the feature we conceived is linearly related to skin ageing.
comparing rank-inducing scoring systems. several methods for comparing rankings are available. these rankings are generally performed on the basis of some scores available for each item. we suggest that it may be better to compare the underlying scores themselves. to this effect, a metric has been provided which is equivalent to comparing the scores after fusing with another set of scores, making it theoretically interesting. this metric is a generalization of kendall distance. in the present article, we assume the distribution of the scores to be fused with to be unknown. some characteristics of the proposed methodology are studied and preliminary experimental results are reported.
graph classification using genetic algorithm and graph probing application to symbol recognition. we present in this paper a graph classification approach using genetic algorithm and a fast dissimilarity measure between graphs called graph probing. the approach consists in the learning of a set of synthetic graph prototypes which are used for a 1nn classification step. some experiments are performed on real data sets, representing 10 symbols. these tests demonstrate the interest to produce prototypes instead of finding representatives which simply belong to the data set.
individual recognition by kinematic-based gait analysis. current gait recognition approaches only consider individuals walking frontoparallel to the image plane. this makes them inapplicable for recognizing individuals walking from different angles with respect to the image plane. in this paper, we propose a kinematic-based approach to recognize individuals by gait. the proposed approach eastimates 3d human walking parameters by performing a least squares fit of the 3d kinematic model to the 2d silhouette extracted from a monocular image sequence. a genetic algorithm is used for feature selection from the estimated parameters, and the individuals are then recognized from the feature vectors using a nearest neighbor method. experimental results show that the proposed approach achieves good performance in recognizing individuals walking from different angles with respect to the image plane.
face recognition from face profile using dynamic time warping. most of the current profile recognition algorithms depend on the correct detection of fiducial points and the determination of relationships among these fiducial points. unfortunately, some features such as concave nose, protruding lips, flat chin, etc., make detection of such points difficult and unreliable. also, the number and position of fiducial points vary when expression changes even for the same person. in this paper, a curvature-based matching approach is presented, which does not require the extraction of all the fiducial points, but uses information contained in the profile. the scale space filtering is used to smooth the profile and then the curvature of the filtered profile is computed. using the curvature value, the fiducial points, such as nasion and throat can be reliably extracted using a fast and simple method. then a dynamic time warping method is applied to match the face profile portion from nasion to throat based on the curvature value. experiments are performed on two profile face image databases. recognition rates and conclusion are presented and discussed.
an fpga-based architecture for real time image feature extraction. we propose a novel fpga-based architecture for the extraction of four texture features using gray level cooccurrence matrix (glcm) analysis. these features are angular second moment, correlation, inverse difference moment, and entropy. the proposed architecture consists of a hardware and a software module. the hardware module is implemented on xilinx virtex-e v2000 fpga using vhdl. it calculates many glcms and glcm integer features in parallel. the software retrieves the feature vectors calculated in hardware and performs complementary computations. the architecture was evaluated using standard grayscale images and video clips. the results show that it can be efficiently used in realtime pattern recognition applications.
robust playfield segmentation using map adaptation. a vital task in sports video annotation is to detect and segment areas of the playfield. this is an important first step in player or ball tracking and detecting the location of the play on the playfield. in this paper we present a technique using statistical models, gaussian mixture models (gmms) and maximum a posteriori (map) adaptation. this involves first creating a generic model of the playfield colour and then using unsupervised map adaptation to adapt this model to the colour of the playfield in each game. this technique provides a robust and accurate segmentation of the playfield. to demonstrate the robustness of the method we tested it on a number of different sports that have grass playfields, rugby, soccer and field hockey.
image representation and retrieval using support vector machine and fuzzy c-means clustering based semantical spaces. this paper presents a learning based framework for content-based image retrieval to bridge the gap between low-level image features and high-level semantic information presented in the images on semantically organized collections. both supervised (probabilistic multi-class support vector machine) and unsupervised (fuzzy c-means clustering) learning based techniques are investigated to associate global mpeg-7 based color and edge features with their high-level semantical and/or visual categories. it represents images in a successive semantic level of information abstraction based on confidence or membership scores obtained from the learning algorithms. a fusion-based similarity matching function is employed on these new image representations to rank and retrieve most similar images compared to a query image. experimental results on a generic image database with manually assigned semantic categories and on a medical image database with different modalities and examined body parts demonstrate the effectiveness of the proposed approach compared to the commonly used euclidean distance measure on mpeg-7 based descriptors.
modular neural networks for seismic tomography. we propose in this paper a modular approach for the problem of traveltime inversion or seismic tomography. this problem consists in the inference of the velocity of wave propagation in the subsurface after an explosion has been produced at the surface, relying on such waves' traveltimes. these traveltimes are recorded by several receivers on the surface. in the present work, we consider data synthetically generated, thanks to the use of a particular "earth-model". an earth-model is a multilayered media in which each layer is homogeneous, that is, the seismic wave's propagation velocity in each layer is constant, and each layer's thickness is different. we compare, on these synthetic data, a multilayer perceptron (mlp) to a modular neural architecture. we show that the modular approach is better suited for theinversion problem stated, and study the experimental conditions in which the potential of this approach is optimally exploited.
image representation and retrieval using support vector machine and fuzzy c-means clustering based semantical spaces. this paper presents a learning based framework for content-based image retrieval to bridge the gap between low-level image features and high-level semantic information presented in the images on semantically organized collections. both supervised (probabilistic multi-class support vector machine) and unsupervised (fuzzy c-means clustering) learning based techniques are investigated to associate global mpeg-7 based color and edge features with their high-level semantical and/or visual categories. it represents images in a successive semantic level of information abstraction based on confidence or membership scores obtained from the learning algorithms. a fusion-based similarity matching function is employed on these new image representations to rank and retrieve most similar images compared to a query image. experimental results on a generic image database with manually assigned semantic categories and on a medical image database with different modalities and examined body parts demonstrate the effectiveness of the proposed approach compared to the commonly used euclidean distance measure on mpeg-7 based descriptors.
approximate fingerprint matching using kd-tree. fast and robust fingerprint matching is a challenging task today in fingerprint-based biometric systems. a fingerprint matching algorithm compares two given fingerprints and returns either a degree of similarity or a binary decision. minutiae-based fingerprint matching is the most well-known and widely used method [handbook of fingerprint recognition]. this paper reveals a new technique of fingerprint matching, using an efficient data structure, combining the minutiae representation with the individual usefulness of each minutia, to make the matching more powerful. experimental results exhibit the strength of this method.
anti-personnel mine detection and classification using gpr image. the automated anti-personnel mine (apm) detection and classification is currently a broad issue. the detection success depends on the feature selection that we obtain from the sensors. ground penetrating radar (gpr) is one of the established sensors for detecting buried apm. in this paper, we introduce a method which improves the accuracy of detecting apm by using gpr imaging. this method adopts a segmentation technique for feature extraction and neural network as a pattern classifier. a seeded region growing algorithm is applied as region based segmentation for pattern construction following the median filtering and threshold of the original gpr image. a feed forward neural network (ffnn) with backpropagation training is employed for classifying the patterns. the ffnn takes the patterns (apm signature) that are constructed from each salient region and generate the classification. this method significantly improves accuracy in the detection and classification of apm.
dtm generation from lidar data using skewness balancing. light detection and ranging (lidar) data for terrain and land surveying has contributed to many environmental, engineering and civil applications. however, the analysis of digital surface models (dsms) from complex lidar data is still challenging. commonly, the first task to investigate lidar data point clouds is to separate ground and object points as a preparatory step for further object classification. in this paper, the authors present a novel unsupervised segmentation algorithm - skewness balancing - to separate object and ground points efficiently from high resolution lidar point clouds by exploiting statistical moments. the results presented in this paper have shown its robustness and its potential for commercial applications.
object localization using input/output recursive neural networks. localizing objects in images is a dificult task and represents the first step to the solution of the object recognition problem. this paper presents a novel approach to the localization problem based on recursive neural networks (rnns). in particulal; a recursive learning paradigm is proposed to process directed acyclic graphs with labeled edges, and to realize mappings between graphs which are isomorph, i.e. that share the same topology of the links. the rnn model, that assumes a graph-based representation of images, uses a state transition function that depends on the edge labels and is independent from both the number and the order of the children of each node. moreover, the presence of targets attached to the internal nodes guarantees a fast learning, particularly sensitive to the local features of the graph. some preliminary experiments, carried out on artijcial images created using the coil collection, are reported, showing very promising results.
foveated online 3d visualization. spatially varying sensing (foveation) was first used as a means for image compression in our past research [1]. in this report we extend previous work by us to address the advantages of foveation in improving the performance of interactive 3d visualization over bandwidth limitedchannels, such as the internet. we develop an algorithm that is implemented in java3d. the method combines foveating jpeg texture files with level-of-detail representation in java3d. applications of the work include model based coding following the synthetic-natural hybrid (snhc) paradigm in mpeg-4 to electronic commerce with 3d visualization of merchandise. experimental results are presented to validate our approach.
distributed retrieval of wavelet images using bandwidth monitoring. limitations on the bandwidth to a server makes the retrieval of a large-size high-resolution image, even compressed, very time-consuming. to speed up this process we replace the retrieval process from a single server with the retrieval from multiple servers, i.e., simultaneously retrieving different part of an image from multiple server sites. in this paper, we present a block-based distributed retrieval strategy for images compressed by the embedded zerotree of wavelet coefficients (ezw) algorithm. the experimental results validate that block-based distributed retrieval is an efficient strategy to speed up downloading.
multi-user natural interaction system based on real-time hand tracking and gesture recognition. we present a computer vision based system that enables multiple people to interact naturally with a large display table using their own bare-hand gestures. the display presents and supports a particular multimedia application that can be used at the same time even by remote users. finally we describe two different applications designed for didactic and entertainment scenarios.
a new lda-based method for face recognition. linear discriminant analysis (lda) is a feature extraction technique for classification. in this paper, we propose a new lda-based method that can overcome the drawback existed in the traditional lda methods. it redefines the between-class scatter by adding a weight function according to the between-class distance, which helps to separate the classes as much as possible. at the same time, it projects the between-class scatter into the null space of the within-class scatter that contains the most discriminant information. hence, the transformationmatrix composed with the eigenvectors corresponding to the largest eigenvalues of the transferred between-class scatter can maximize the fisher criteria. experimental results show our method achieves better performance in comparison with the traditional lda methods.
fast, illumination insensitive face detection based on multilinear techniques and curvature features. this paper brings together two recent developments in image analysis. we consider a new mathematical framework that provides illumination invariant descriptors for face detection. towards fast learning and processing, we understand images and the corresponding feature maps as multilinear entities and apply higher order classifiers for image analysis and object detection. experimental results underline that this approach indeed provides quick training, fast runtime and robust performance across a variety of illumination conditions.
recognizing faces with expressions: within-class space and between-class space. in this paper, we propose a novel technique for expression invariant face recognition, which is different from eigenfaces method from two aspects: the first is that instead of applying principal component analysis (pca) on the pixel domain to obtain eigenfaces, we train eigen-motion by applying pca on motion vectors getting from the training face images with expression variations; the second is to consider the reconstructed errors of a test image in two spaces: the between-class eigenmotion sub-space and the within-class eigenmotion subspace, whichare used as the classification rule, in contrast to the traditional methods such as euclidean distance or mahalanobis distance in one subs pace. experimental results show that this method performs better than eigenfaces method in the presence offacial expression variations.
benefits of separable, multilinear discriminant classification. this paper presents an empirical investigation of the merits of tensor-based discriminant classification for visual object detection. first, we briefly discuss 2d separable discriminant analysis for grey value image analysis. then, we contrast this tensorial approach with classical linear discriminant analysis. our findings on a standard data set for object detection in natural environments show that, for the task of image analysis, tensor-based discriminant classifiers perform very robust. they learn and run faster and also generalize better than conventional techniques based on vectorial representations of the data.
benefits of separable, multilinear discriminant classification. this paper presents an empirical investigation of the merits of tensor-based discriminant classification for visual object detection. first, we briefly discuss 2d separable discriminant analysis for grey value image analysis. then, we contrast this tensorial approach with classical linear discriminant analysis. our findings on a standard data set for object detection in natural environments show that, for the task of image analysis, tensor-based discriminant classifiers perform very robust. they learn and run faster and also generalize better than conventional techniques based on vectorial representations of the data.
lightsphere: fast lighting compensation for matching a 2d image to a 3d model. we describe a fast object recognition method that identifies 2d color image queries among a set of 3d models. it is fast enough for searching a very large database. the main application is face recognition, for which we report very good accuracy over a wide range of pose and lighting conditions. we make weaker assumptions about both lighting and reflectance than are usual. we avoid finding eigenvectors or solving systems of equations. instead, we use the query to estimate a specialization of the brdf to the fixed lighting and pose of the query. in a single image pass, we compute a lookup table for re-rendering, which represents expectation values for the action of the light via the brdf. this yields a similarity measure of the consistency between model and query under the regularity assumptions. we report recognition results on a data set of 42 3d face models and 1764 query images, comprising 7 poses and 6 lighting conditions. the recognition accuracy is indistinguishable from much slower methods, methods which make stronger assumptions about the brdf and lighting.
a fast binary-image comparison method with local-dissimilarity quantification. image similarity measure is widely used in image processing. for binary images that are not composed of a single shape, a local comparison is interesting but the features are usely poor (color) or difficult to extract (texture, forms). we present a new binary image comparison method that uses a windowed hausdorff distance in a pixel-adaptive way. it enables to quantify the local dissimilarities and to give their spatial distribution which greatly improve the dissimilarity information. combined with a support vector machine classifier, this method is successfully tested on an medieval-impression database.
applying compiler techniques to diagram recognition. compiler techniques are effective and efficient in processing textual programming languages. these techniques can be adapted to recognition and processing of two-dimensional languages (diagrams). already, grammars and parsers have been used in a variety of diagram-recognition and diagram-processing tasks. here we explore the use of two other compiler techniques in pattern recognition systems. the first is compiler-style use of trees and tree transformation. the second is a multi-pass control structure, with a clear separation between layout, lexical, syntactic, and semantic analysis. our proposal is illustrated on a case study involving recognition of hand-drawn mathematics notation.
finding highly frequented paths in video sequences. we propose a novel algorithm to find highly frequented paths of motion trajectories obtained from video sequences. this is achieved by representing the motion trajectories in the scene as sequences of prototypes obtained by a combined vector quantization and growing neural gas algorithm. in contrast to existing methods, the proposed algorithm can be applied to data sets containing motion trajectories of varying length. the algorithm does not assume an a priori fixed number of prototypes. we demonstrate results on surveillance video sequences of cars driving on a highway and pedestrians walking in a major railway station.
using attention for video segmentation. in this paper we propose an original approach to partitioning of a video into shots based on a foveated representation of the video.the proposed scheme aims at detecting both abrupt and gradual transitions between shots using a single technique, rather than a set of dedicated methods. results on videos of various content types are reported and validate the proposed approach.
bayesian pot-assembly from fragments as problems in perceptual-grouping and geometric-learning. a heretofore unsolved problem of great archaeological importance is the automatic assembly of pots made on a wheel from the hundreds (or thousands) of sherds found at an excavation site. an approach is presented to the automatic estimation of mathematical models of such pots from 3d measurements of sherds. a bayesian approach is formulated beginning with a description of the complete set of geometric parameters that determine the distribution of the sherd measurement data. matching of fragments and aligning them geometrically into configurations is based on matching break-curves (curves on a pot surface separating fragments), estimated axis and profile curve pairs for individual fragments and configurations of fragments, and a number of features of groups of break-curves. pot assembly is a bottom-up maximum likelihood performance-based search. experiments are illustrated on pots which were broken for the purpose, and on sherds from an archaeological dig located in petra, jordan. the performance measure can also be an aposteriori probability, and many other types of information can be included, e.g., pot wall thickness, surface color, patterns on the surface, etc. this can also be viewed as the problem of learning a geometric object from an unorganized set of free-form fragments of the object and of clutter, or as a problem of perceptual grouping.
inference of moving forms via belief propagation. in this paper we address the issue of how form and motion can be integrated in order to provide suitable information to attentively track multiple moving objects. such integration is designed in a bayesian framework, and a belief propagation technique is exploited to perform coherent form/motion labelling of regions of the observed scene.
3d object reconstruction from non-parallel cross-sections. we propose a 3d object reconstruction algorithm from non-parallel object cross-sections. the algorithm is based on two-dimensional morphological morphing, affine transform and cubic spline interpolation. the algorithm is developed for processing 3d freehand ultrasound data.
iris individuality: a partial iris model. biometrics-based personal authentication systems are becoming popular with increased demand on security. a biometrics is expected to have significant amount of discriminatory information in representing uniqueness of a person. this discriminatory information about the biometric is loosely defined as the individuality. even though some individuality studies have been carried out for fingerprints, face and handwriting, formal analysis of iris individuality has not been carried out. in this paper, we propose a partial model for iris individuality and show its usefulness in predicting the empirical performance results.
an evaluation of error confidence interval estimation methods. reporting the accuracy performance of pattern recognition systems (e.g., biometrics id system) is a controversial issue and perhaps an issue that is not well understood [an introduction to evaluating biometric systems, confidence interval and test size estimation for biometric data]. this work focuses on the research issues related to the oft used confidence interval metric for performance evaluation. using a biometric (fingerprint) authentication system, we estimate the false reject rates and false accept rates of the system using a real fingerprint dataset. we also estimate confidence intervals of these error rates using a number of parametric (e.g., see [confidence interval and test size estimation for biometric data]) and non-parametric (e.g., bootstrapping [1, 3, 6]) methods. we attempt to assess the accuracy of the confidence intervals based on estimate and verify strategy applied to repetitive random train/test splits of the dataset. our experiments objectively verify the hypothesis that the traditional bootstrap and parametric estimate methods are not very effective in estimating the confidence intervals and magnitude of interdependence among data may be one of the reasons for their ineffective estimates. further, wedemonstrate that the resampling the subsets of the data samples (inspired from moving block bootstrap [moving blocks jackknife and bootstrap capture weak dependence]) may be one way of replicating interdependence among the data; the bootstrapping methods using such subset resampling may indeed improve the accuracy of the estimates. irrespective of the method of estimation, the results show that the (1 - ¿) 100% confidence intervals empirically estimated from the training set capture significantly smaller than(1 - ¿) fraction of the estimates obtained from the test set.
patterns of co-linear equidistant letter sequences and verses. it has been shown ([4], [3]) that equidistant letter sequence (els) pairs in the book of genesis (g) form more compact geometric patterns on the surface of a cylinder than is expected at random. this phenomenon has been demonstrated in g for specific lists of biographical data. we extend these results and show that: 1. the compactness phenomenon holds for triplets of elements where two elements are words, taken from a lexicon derived from all the words in the pentateuch, which form co-linear elss, and the third element is a verse in the text that contains two words with the same meanings as the first two elements respectively. 2. this phenomenon manifests itself in the entire hebrew pentateuch.
patterns of co-linear equidistant letter sequences and verses. it has been shown ([4], [3]) that equidistant letter sequence (els) pairs in the book of genesis (g) form more compact geometric patterns on the surface of a cylinder than is expected at random. this phenomenon has been demonstrated in g for specific lists of biographical data. we extend these results and show that: 1. the compactness phenomenon holds for triplets of elements where two elements are words, taken from a lexicon derived from all the words in the pentateuch, which form co-linear elss, and the third element is a verse in the text that contains two words with the same meanings as the first two elements respectively. 2. this phenomenon manifests itself in the entire hebrew pentateuch.
on the equivalence of local-mode finding, robust estimation and mean-shift analysis as used in early vision tasks. in this paper we show the equivalence of three techniques used in image processing: local-mode finding, robust-estimation and mean-shift analysis. the computational common element in all these image operators is the spatial-tonal normalized convolution, an image operator that generalizes the bilateral filter.
fuzzy border distance transforms and their use in 2d skeletonization. segmentation is always a difficult task in image analysis. in this paper, we propose a solution to computing distance transforms in images with fuzzy object borders. the difference from a standard distance transform is in the initialisation, which takes the fuzziness of the border into account. as an example of its usefulness, the new fuzzy border distance transform is used in skeletonization.
object and scene classification: what does a supervised approach provide us?. given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). we achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. we use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. experimental results are shown and evaluated to prove the validity of our proposal. object recognition performance is compared to the approaches of he et al. [3] and mart´ý et al. [6] using their own datasets. furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one.
introduction to the concept of structural hmm: application to mining customers' preferences in automotive design. we have introduced in this paper the concept of structural hidden markov models (shmm's). this new paradigm adds the syntactical (or structural) component to the traditional hmm's. shmm's introduce relationships between the visible observations of a sequence. these observations are related because they are viewed as evidences of a same conclusion in a rule of inference. we have applied this novel concept to predict customer's preferences for automotive designs. shmmhas outperformed both the k-nearest neighbors and the neural network classifiers with an additional 12% increase in accuracy.
protein fold recognition using a structural hidden markov model. protein fold recognition has been the focus of computational biologists for many years. in order to map a protein primary structure to its correct 3d fold, we introduce in this paper a machine learning paradigm that we entitled "structural hidden markov model" (shmm). we show how the concept of shmm can efficiently use the protein secondary structure during the fold recognition task. experimental results showed that the shmmoutperforms the svm with a 6% improvement in the average accuracy. however, because in this application the two classifiers are not correlated, therefore their combination based on the highest rank criterion boosted the shmm average accuracy with 10%.
object recognition from 3d blurred images. this paper presents a novel approach for 3d object recognition and classification. the originality of this approach is the combination of statistical reasoning, feature learning and expertise knowledge from the application. it is based on 2d processing of images alternating with 3d validation of class characteristics for recognition. classification is based on iterative refinement of hypotheses. an application is presented for pollen grain observed with lightmicroscopy for allergy prevention.
region segmentation and matching in stereo images. in this paper, we propose a new method to simultaneously achieve segmentation and dense matching in a pair of stereo images. in constrast to conventional methods that are based on similarity or correlation techniques, this method is based on geometry and uses correlations only on a limited number of key points. stemming from the observation that our environment is abundant in planes, this method focuses on segmentation and matching of planes in an observed scene. neither prior knowledge about the scene nor camera calibration are needed. using two uncalibrated images as inputs, the method starts with a rough identification of a potential plane, defined by three points only. based on these three points, a plane homography is then calculated and, used for validation. starting from a seed region defined by the original three points, the method grows the current region by successive move/confirmation steps until occlusions and/or surface discontinuity occur. in this case, the homography-based mapping of points between the two images will fail. this failure is detected by the correlation, used in the confirmation process. in particular, this method grows a region even across different colors as long as the region is planar. experiments on real images validated our method and showed its capability and performance.
gaussian energy functions for registration without correspondences. a new criterion based on gaussian fields is introduced and applied to the task of automatic rigid registration of point-sets. the method defines a simple energy function, which is always differentiable and convex in a large neighborhood of the alignment parameters; allowing for the use of powerful standard optimization techniques. we show that the size of the region of convergence can be extended so that no close initialization is needed, thus overcoming local convergence problems of iterative closest point algorithms. furthermore, the gaussian energy function can be evaluated with linear complexity using the fast gauss transform, which permits efficient implementation of the registration algorithm. analysis through several experimental results on real world datasets shows the practicality and points out the limits of the approach.
a k-means-based algorithm for projective clustering. in this paper, a new algorithm for projective clustering is proposed. the algorithm consists of two phases. the first phase performs attribute relevance analysis by detecting dense regions in each attribute, thereby allowing irrelevant attributes and outliers to be captured and eliminated. starting from the results of the first phase, the second phase aims to uncover clusters in different subspaces. the clustering process is based on the k-means algorithm, with the computation of distance restricted to subsets of attributes where object values are dense.
a powreful finite mixture model based on the generalized dirichlet distribution: unsupervised learning and applications. this paper presents a new finite mixture model based on a generalization of the dirichlet distribution. for the estimation of the parameters of this mixture we use a gem (generalized expectation maximization) algorithm based on a newton-raphson step. the experimental results involve the comparison of the performance of gaussian and generalized dirichlet mixtures in the classification of several pattern-recognition data sets.
application of rigid motion geometry to film restoration. film restoration involves locating the position of artifacts and replacing the "missing" portion of the film (obscured by the artifact) with pixels that had been lost. computer vision research has recently developed many techniques for constraining and predicting parts of a scene based upon the assumption of rigid motion. in this paper, we show how the constraints can help identify artifacts as well as how the prediction can be used to replace the artifact with natural looking portions of the scene. these techniques can be superior, when the rigid motion assumption is valid, to other techniques for film restoration.
content based image retrieval using gradient color fields. this paper presents a content based system retrieval that uses gradient color fields as features. these features take into account both contour curvature and colors found in adjacent regions. this approach is dual from color region based methods. it allows a simple description of images using a coarse understandable sketch, which preserves rich information with a small amount of storage. this representation allows different type of queries such as: statistical or structural, global or partial and contour based. these features have been tested, using different modes on a very large image database from broadcast television. results obtained from our system is presented and discussed.
coarse visual registration from closed-contour neighborhood descriptor. this article introduces an innovative visual coarseregistration process suitable for textureless objects. because our framework is industrial, the process is designed for metallic, complex objects containing multiple bores and repetitive patterns. this technique is based on a local shape descriptor, invariant under affine transform, which characterizes the neighborhood of a closed contour. the affine invariance is exploited in the learning stage to produce a lightweight model: for an automobile cylinder head, a learning viewsphere with twelve viewpoints is sufficient. moreover, during the learning stage, this descriptor is combined to a 2d/3d pattern, concept likewise presented in this article. once associated, the 2d/3d information wealth of this descriptor allows a pose estimation from a single match between two descriptors. this ability is exploited to obtain efficiently a great number of coarse pose hypothesis. a pose hypothesis classification method is proposed to select the best-ones. an evaluation on a cylinder head and a binding beam confirms both the robustness and the precision of the process.
face verification system architecture using smart cards. a smart card based face verification system is proposed in which the feature extraction and decision making is performed on the card. such an architecture has many privacy and security benefits. as smart cards are limited computational platforms, the face verification algorithms have to be adapted to limit the facial image representations. this minimises the information needed to be sent to the card and lessens the computational load of the template matching. studies performed on the banca and xm2vts databases demonstrate that by limiting these representations the verification performance of the system is not degraded and that the proposed architecture is a viable one.
incorporating temporal context with content for classifying image collections. semantic scene classification is an open problem in image understanding, especially when information purely from image content (i.e., pixels) is employed. however, in applications involving image collections, surrounding images give each image a temporal context. we present a probabilistic approach to scene classification, capable of integrating both image content and temporal context. elapsed time between images can be derived from the timestamps recorded by digital cameras. our temporal context model is trained to exploit the stronger dependence between images captured within a short period of time, indicated by the elapsed time. we demonstrate the efficacy of our approach by applying it to the problem of indoor-outdoor scene classification and achieving significant gains in accuracy. the probabilistic temporal context model can be applied to other scene classification problems.
photo classification by integrating image content and camera metadata. despite years of research, semantic classification of unconstrained photos is still an open problem. existing systems have only used features derived from the image content. however, exif metadata recorded by the camera provides cues independent of the scene content that can be exploited to improve classification accuracy. using the problem of indoor-outdoor classification as an example, analysis of metadata statistics for each class revealed that exposure time, flash use, and subject distance are salient cues. we use a bayesian network to integrate heterogeneous (content-based and metadata) cues in a robust fashion. based on extensive experimental results, we make two observations: (1) adding metadata to content-based cues gives highest accuracies; and (2) metadata cues alone can outperform content-based cues alone for certain applications, leading to a system with high performance, yet requiring very little computational overhead. the benefit of incorporating metadata cues can be expected to generalize to other scene classification problems.
fuzzy point of view combination for contextual shape recognition: application to on-line graphic gesture recognition. in this paper, we focus on the explicit use of the spatial context of strokes in the recognition process of graphic gestures. we dispose of two sources of knowledge on the samples: their shape which is a classical one and their spatial context. the proposed method is based on three different points of view to exploit optimally these two sources of knowledge to perform the recognition. the first point of view uses the spatial context to filter the possible classes and then uses the shape to discriminate the remaining classes. the second one reverses the roles of the sources of knowledge. the third one uses them jointly. the underlying idea is that each point of view suits to one of the three case of source reliability. the challenge is to automatically compose the points of view and to combine them to build a system performing contextual shape recognition without any prior information on the targeted domain.
a survey of approaches to three-dimensional face recognition. the vast majority of face recognition research has focused on the use of two-dimensional intensity images, and is covered in existing survey papers. this survey focuses on face recognition using three-dimensional data, either alone or in combination with two-dimensional intensity images. challenges involved in developing more accurate three-dimensional face recognition are identified.
perceptual organization in range data: robust detection of low order surfaces in heavy clutter. we consider the problem of detecting manmade objects in range data in the presence of extensive clutter. such situations arise in, for example, the detection of small structures or vehicles beneath a leaf canopy in range data collected from an airborne platform. this problem calls for an extremely robust detection scheme, and it should be fast. since most manufactured objects comprise large low-order piecewise smooth surfaces (often planes), we focus on detecting locally planar surfaces. we propose a novel technique we call distribution weighted histograms (dwh), which exploits the inherent geometric distributions of man-made objects versus the random occlusions such as those due to an overhanging leaf canopy. the dwh algorithm performs well under heavy occlusion while being computationally inexpensive (linear complexity). we present extensive experimental results.
multiscale surface organization and description for free form bject recognition. we introduce an efficient, robust means to obtain reliable surface descriptions, suitable for free form object recognition, at multiple scales from range data. mean and gaussian curvatures are use to segment the surface into four saliency classes of based on curvature consistency as evaluated in a robust multivoting scheme. contiguous regions consistent in both mean and gaussian curvature are identified as the most homogeneous segments, followed by those consistent in mean curvature but not gaussian curvature, followed by those consistent in gaussian curvature only. segments at each level of the hierarchy are extracted in the order of size, large to small, such that the most salient features of the surface are recovered first. this has potential for efficient object recognition by stopping once a just sufficient description is extracted.
sample size estimation using the receiver operating characteristic curve. in this paper we describe two related approaches to estimating the sample sizes required to statistically compare the performance of two classifiers: acceptable failure rates (afr) and the area under the receiver operating characteristic (roc) curve (auc). in particular, we consider rare event detection problems, where the prior class probabilities are highly skewed, and measure performance at a specific operating point and for the whole roc curve. it is shown that the use of auc as a performance measure is preferable to afr as it requires a smaller data set to demonstrate superiority of one classifier over another.
color image coding based on embedded wavelet zerotree and scalar quantization. with the continuous expansion of multimedia applications and the blossoming demand for efficiently storing and transmitting visual information, the needs and requirements of image compression have became increasingly vital. to address this need in the specific area of still image encoding, a new standard jpeg2000 is being designed. our paper deals with color image coding using discrete wavelets transform, color embedded zerotree wavelet (cezw) and combining scalar quantification and adaptive huffman coding. the results are compared to jpeg2000 performances using the java implementation.
comparing normalization and adaptation techniques for on-line handwriting recognition. in this paper a writer-independent on-line handwriting recognition system is described comparing the influence of handwriting normalization and adaptation techniques on the recognition performance. our hidden markov model (hmm) - based recognition system for unconstrained german script can be adapted to the writing style of a new writer using different adaptation techniques whereas the impact of preprocessing to normalize the pen-trajectory is examined. the performance of the resulting writer-dependent system increases significantly, even if only a few words are available for adaptation. so this approach is also applicable for on-line systems in hand-held computers such as pdas. in addition, the developed normalization techniques are helpful to improve completely writer independent systems. this paper presents the performance comparison of three different adaptation techniques either in a supervised or an unsupervised mode, in combination with appropriate normalization methods, with the availability of different amounts of adaptation dta ranging from only 6 words up to 100 words per writer.
cast shadow removing in foreground segmentation. in this paper, we focus on the problem of foreground segmentation in outdoor environment with a static tv camera. our application context is the visual surveillance of archeological sites. in this context the main aim is to detect the presence of people and to recognize their gestures in order to individuate the illegal actions. in this paper we concentrate solely on the primary step of moving object detection. in particular, the system should be able of recovering the true shape of the moving objects in order to allow to a classifier to discriminate a people from any other moving object as car and animals. moreover, the system should not be sensitive to changes in lighting, weather, number of people, etc., and it is required to work autonomously for long periods of time. a main problem in analyzing real outdoor daylight scenes is to deal with shadows cast by moving objects such as vehicles or pedestrians. cast shadows are often detected as a part of the moving objects since they move in the same way. when the detected objects contain shadows, large errors may occur with respect their recognition. in this paper a new approach for cast shadow removing is proposed. our idea is to detect shadow points as points that are static for a short temporal sequence and that are characterized by a photometric gain, with respect the reference background image, that is lower than unit and that we estimate for each new image through an optimization approach.
robust factorisation with uncertainty ana. this paper proposes how the classic factorisation algorithm for affine reconstruction can be extended to be robust to outliers and proposes how the uncertainty analysis can be performed in this case. the robust estimation approach elaborated here is based on the iteratively reweighted least-squares but the use of other robust methods is also discussed. moreover, the uncertainty analysis presented in this paper could be similarly used in a ransac or lmeds extension of the factorisation algorithm. the experiments verify that the proposed approach is reliable and able to give to consistent estimates and uncertainty measure for affine structure and motion.
robust alignment of transmission electron microscope tilt series. in this paper, we propose a novel method for automatic, feature-based alignment of transmission electron microscope images that is needed for computing 3d reconstructions in electron tomography. the proposed method, termed as trifocal alignment, is more accurate than the previous markerless methods. the key components of this work are (1) a reliable multiresolution algorithm for matching feature points between images, (2) a robust, maximumlikelihood- based estimator for determining the trifocal constraint, needed for validating the correctness of the matches, (3) a robust, large scale optimisation framework to compute the alignment parameters from hundreds of thousands of feature point measurements from a couple of hundred images. the experiments show for the first time that by the proposed feature-based alignment approach the accuracy level of the fiducial marker alignment can be achieved.
recognition of gestures in the context of speech. the scope of this paper is the interpretation of a user's intention via a video camera and a speech recognizer. in comparison to previous work which only takes into account gesture recognition, we demonstrate that by including speech, system comprehension increases. for the gesture recognition, the user must wear a colored glove, then we extract the velocity of the center of gravity of the hand. a hidden markov model (hmm) is learned for each gesturethat we want to recognize. in a dynamic action, to know if a gesture has been performed or not, we implement a threshold model below which the gesture is not detected. the off line tests for gesture recognition have a success rate exceeding 85% for each gesture. the combination of speech and gestures is realized using bayesian theory.
automatic acquisition of context models and its application to video surveillance. this paper addresses the problem of automatically acquiring context models from data. context and human behavior are represented using a state model, called situation model. this model consists of different layers referring to entities, filters, roles, relations, situation and situation relationship. we propose a framework for the automatic acquisition of these different layers. in particular, this paper proposes a novel generic situation acquisition algorithm. the algorithm is also successfully applied to a video surveillance task and is evaluated by the public caviar video database. the results are encouraging.
gmm-based svm for face recognition. a new face recognition algorithm is presented. it supposes that a video sequence of a person is available both at enrollment and test time. during enrollment, a client gaussian mixture model (gmm) is adapted from a world gmm using eigenface features extracted from each frame of the video. then, a support vector machine (svm) is used to find a decision border between the client gmm and pseudoimpostors gmms. at test time, a gmm is adapted from the test video and a decision is taken using the previously learned client svm. this algorithm brings a 3.5% equal error rate (eer) improvement over the biosecure reference system on the pooled protocol of the banca database.
unsupervised clustering of text entities in heterogeneous grey level documents. this paper presents a new method of functional classification of text blocks on a document. it is based on texture analysis and unsupervised classification. texture is used here to define different classes of text blocks in the document and to direct a possible way of exploration from the most eye-catching data to the less significant text block. the typographicai properties of blocks are characterized by two main discriminating primitives: the complexity of the text draw ing and the structural relief of the block. this analysis is the starting point of ahree-classes categorization into functional families (main headings, sub-headings and text paragraphs). each block of text is described and classified through a labeling process based on a 3d-feature space using the two previous features (complexity and structural relief) and athird one among pattern primitives, blocks size and location in the document. this method allows a first approach to a global context-free classification of documents.
recognition of building roof facets by merging aerial images and 3d lidar data in a hierarchical segmentation framework. we investigate in this paper an original methodology for detecting roof facets through the fusion of aerial images and lidar data (3d point cloud). based on a hierarchical segmentation of the image, we define a cost function that manages the merging order of regions. it depends on both radiometric similarities of two neighbouring regions as well as on extracted information from lidar data. considering that lidar data have been filtered into points belonging either to ground or non-ground classes, we define semantic and geometric rules in the binary merging process. building roof facets are finally detected by selecting a level of generallity for representing roof building components. some remarks are given concerning the reliability of the integration of lidar and image data. reconstructed roof facets are finally shown onto complex buildings.
paper to pda. a system is described for the automatic analysis of a document image into atomic fragments (e.g. word images) that can be reconstructed or "reflowed" onto a display device of arbitrary size, depth, and aspect ratio. the main intent is to allow scans and other page-image documents to be viewed effectively on a limited-resolution hand-held computing device, without any errors and losses due to ocr and retype-setting. the methods of image analysis and representation are described.
fusion of frequency and spatial domain information for motion analysis. this paper presents an approach to the analysis of multiple motions in video, which combines frequency and spatial domain information in a new manner. the tasks of interest are finding the number of moving objects, velocity estimation, object tracking, and motion segmentation. we propose a novel, hybrid approach, which avoids problems of spatial domain methods, like sensitivity to illumination changes or great computational cost, but also uses spatial information for precise object localization. experiments with synthetic and real sequences, show both the possibilities and limitations of this approach.
spatial and fourier error minimization for motion estimation and segmentation. we present a new approach to motion estimation by minimizing the squared error in both the spatial and frequency domains and we show that the spatially global nature of ft leads to a motion estimation error that is much lower than that obtained via spatial motion estimation. on the other hand, spatial analysis is useful for accurate segmentation. we describe a novel, hybrid approach combining the above two estimates of motion and segmentation. we examine the robustness of minimizing the error terms in both domains, both theoretically and experimentally. experiments with real and synthetic sequences demonstrate the capabilities of the proposed algorithm.
generalizing inverse compositional image alignment. the inverse compositional (ic) approach to image alignment uses characteristics of the alignment problem to improve optimization speed. while a number of authors have noted its usefulness, to date it has only been explored for least-squares type image difference measures using gauss- newton optimization schemes. we extend the ic approach to general difference measures, and a wider class of optimization approaches, with specific development for normalized correlation and mutual information using the bfgs optimizer. we present alignment experiments on image pairs of several different classes that demonstrate performance improvements for the general case.
efficient calculation of the complete optimal classification set. feature and structure selection is an important part of many classification problems. in previous papers, an approach called basis pursuit classification has been proposed which poses feature selection as a regularization problem using a 1-norm to measure parameter complexity. in addition, a complete optimal parameter set, here called the locus, can be calculated which contains every optimal collection of sparse features as a function of the regularization parameter. this paper considers how to iteratively calculate the parameter locus using a set of rank-1 inverse matrix updates. the algorithm is tested on both artificial and real data and it is shown that the computational cost is reduced from a cubed to a squared problem in the number of features.
image analysis through local information measures. the properties of local image statistics are analyzed in a classic information theoretic setting. local spatiochromatic image elements are projected into a space in which constituent components are independent by way of independent component analysis, allowing a fast and tractable means of considering the joint likelihood of such statistics. observation of this likelihood allows inferences to be made regarding the informativeness of a particular set of statistics. this operation is shown to illuminate a number of perceptually important image properties, allowing figure-ground segmentation, removal of common or expected image elements, and prediction of regions of interest.
image segmentation by shape particle filtering. statistical appearance models are valuable tools in medical image segmentation. current methods elegantly incorporate global shape and appearance, but can not cope with local appearance variations and rely on an assumption of gaussian gray value distribution. furthermore, initialization near the optimal solution is required. we propose a shape inference method that is based on pixel classification, so that local and non-linear intensity variations are dealt with naturally, while a global shape model ensures a consistent segmentation. optimization by stochastic sampling removes the need for accurate initialization. the method is demonstrated on vertebra segmentation in spine radiographs. segmentation errors are below 2 mm in 88 out of 91 cases, with an average error of 1.4 mm.
scratch detection via underdamped harmonic motion. this paper presents sdho (scratch detection via harmonic oscillator), a generalized model to detect line scratches on digital images. the line scratch profile is now a solution of a second order homogeneous differential equation, depending exclusively on the width and the brightness of the scratch. this method performs noticeably better than the other existing techniques with a lower computing time.
fast removal of line scratches in old movies. in this paper a fast algorithmfor removing line scratches in old movies is presented. it is strongly based on exploiting the defect visibility in the image. to this aim the weber's law can be applied to coefficients of an over-complete wavelet representation of the degraded image. the intensity of the defect, which is represented as a light diffraction effect, is then attenuated in the vertical and approximation sub-bands till the minimum threshold of visibility is reached. the experimental results are very satisfying: the image is completely recovered without local artefacts or annoying smoothing effects.
video structuring, indexing and retrieval based on global motion wavelet coefficients. this paper describes an approach for video structuring and indexing. it relies on motion wavelet coefficients directly estimated from image sequence. these coefficients provide a multiscale characterization of optical flow . they allow to define dominant and local motion descriptors, respectively related to camera and object displacements. we use dominant motion descriptors to perform a temporal segmentation of the sequence. shots extracted are characterized in term of dominant motion properties and indexed by using descriptors related to local motion content. these operations allow to retrieve shots, by example queries, according to only dynamic content of the scene and not camera displacements.
interactive road extraction with pixel force fields. pixel force field (pff) is a novel image representation where at each pixel a two-dimensional vector is defined for representing interaction of pixels. the vector is oriented to the center of the region composed of pixels having the same qualitative property, such as color and gray-scale level. using the pixel force field and improved live-wire segmentation technique the task of interactive road extraction from remote sensing images is solved.
application of non-negative and local non negative matrix factorization to facial expression recognition. in this paper two image representation approaches called non-negative matrix factorization (nmf) and local non-negative matrix factorization (lnmf) have been applied to two facial databases for recognizing six basic facial expressions. a principal component analysis (pca) approach was performed as well for facial expression recognition for comparison purposes. we found that, for the first database, lnmf outperforms both pca and nmf, while nmf produces the poorest recognition performance. results are approximately the same for the second database, with slightly performance improvement on behalf of nmf.
performance driven facial animation using illumination independent appearance-based tracking. we introduce a procedure to estimate human face high level animation parameters from a marker-less image sequence in presence of strong illumination changes. we use an efficient appearance-based tracker to stabilise face images and estimate illumination variation. this is achieved by using an appearance model composed by two independent linear subspaces modelling face deformation and illumination changes respectively. the system is very simple to train and is able to re-animate a 3d face model in real-time.
view-based dynamic object recognition based on human perception. psychophysical studies have shown that humans actively exploit temporal information such as contiguity of images in object recognition. we have recently developed a recognition system which uses temporal contiguity to learn extensible representations of objects on-line. the system performs well both on real-world and synthetic data and shows robustness under illumination changes. in this paper, we present results which compare the proposed representation against simple image-based representations of the same complexity using minkowski minimum distance classifiers and support vector machine classifiers. recognition results for all classifiers show large improvements with incorporated temporal information.
robot navigation by panoramic vision and attention guided fetaures. in visual-based robot navigation, panoramic vision emerges as a very attractive candidate for solving the localization task. unfortunately, current systems rely on specific feature selection processes that do not cover the requirements of general purpose robots. in order to fulfill new requirements of robot versatility and robustness to environmental changes, we propose in this paper to perform the feature selection of a panoramic vision system by means of the saliency-based model of visual attention, a model known for its universality. the first part of the paper describes a localization system combining panoramic vision and visual attention. the second part presents a series of indoor localization experiments using panoramic vision and attention guided feature detection. the results show the feasibility of the approach and illustrate some of its capabilities.
scene classification from dense disparity maps in indoor environments. we present our approach for scene classification in dense disparity maps from a binocular stereo system. the classification result is used for tracking and navigation purposes. the presented system is capable of foreground-background separation classifying room structures. the 3d model of the scene is derived directly from the disparity image. this approach is used for initial target selection and scene classification in mobile navigation. it is used on our mobile system for target tracking, but can also be used for localization as described in this paper.we describe the basic principles of our object detection and classification using disparity information from a binocular stereo system. the theoretical derivation is supported by results from the binocular stereo sensor system on our mobile robot.
extraction and clustering of motion trajectories in video. a system is described that tracks moving objects in a video dataset so as to extract a representation of the objects' 3d trajectories. the system then finds hierarchical clusters of similar trajectories in the video dataset. objects' motion trajectories are extracted via an ekf formulation that provides each object's 3d trajectory up to a constant factor. to increase accuracy when occlusions occur, multiple tracking hypotheses are followed. for trajectory-based clustering and retrieval, a modified version of edit distance, called longest common subsequence is employed. similarities are computed between projections of trajectories on coordinate axes. trajectories are grouped based, using an agglomerative clustering algorithm. to check the validity of the approach, experiments using real data were performed.
omnidirectional stereo vision with a hiperbolic double lobed mirror. this paper presents a compact panoramic stereo vision system based on a double lobed mirror with hyperbolic profile. as hyperbolic mirrors ensure a single viewpoint the incident light rays are easily found from the points of the image. the geometry of the double lobed mirror naturally ensures matched epipolar lines in the two images of the scene. these two properties make the double lobed mirror especially suitable for panoramic stereo vision because range estimation becomes simple and fast. this is a great advantage for real-time applications. the proposed mirror is useful for mobile robot navigation, surveillance, and machine vision where fast and real-time calculations are needed.
a unified formulation of invariant point pattern matching. we present a unified framework for modeling and solving invariant point pattern matching problems. invariant features are encoded as potentials in a probabilistic graphical model. by using a specific kind of graph topology, different types of invariant matching models can be implemented via tree-width selection. models with tree-widths 1, 2, 3 and 4 implement translation, similarity, affine and projective invariant point matching, respectively. the optimal match is then found by exploiting the markov structure of the graph through the generalized distributive law in a dynamic programming setting. in the absence of noise in the point coordinates, the solutions found are optimal. our early experiments suggest the approach is robust to outliers and moderate noise.
a comparison of junction tree and relaxation algorithms for point matching using different distance metrics. we have developed a polynomial time optimal method for a class of attributed graph matching problems using the junction tree algorithm from graphical models.in this paper we compare this method with standard probabilistic relaxation labelling using different forms of point metrics and under different levels of additive noise.results show that, no matter which of the metrics is applied, our technique is more effective than probabilistic relaxation labeling for large graph sizes.for small graph sizes, our technique is still preferable for two of the metrics, while for the third one both techniques perform similarly.
context enhancement of nighttime surveillance by image fusion. in this paper, we propose a novel method of automatically combining images of a scene at different time intervals by image fusion. all the important information of the original low quality nighttime images is combined with the context from a high quality image of the daytime at the same viewpoint. the fused image contains a comprehensive description of the scene which is more useful for human visual and machine perception. experimental results show that the proposed method is robust and effective.
an efficient radical-based algorithm for stroke-order-free online kanji character recognition. this paper investigates improvements of an online handwriting stroke-order analysis algorithm - cube search, based on cube graph stroke-order generation model and dynamic programming (dp). by dividing character into radicals, the model is decomposed into intra-radical graphs and an inter-radical graph. this decomposition considerably reduces the time complexity of stroke-order search dp. experimental results showed an significant improvements in operational speed. additionally, recognition accuracy was also improved by prohibiting unnatural stroke-order.
offline cursive character challenge: a new benchmark for machine learning and pattern recognition algorithms.. cursive character recognition is a challenging task due to high variability and intrinsic ambiguity of cursive letters. this paper presents c-cube (cursive character challenge), a new public-domain cursive character database. ccube contains 57293 cursive characters manually extracted from cursive handwritten words, including both upper and lower case versions of each letter. the database can be downoloaded from the web and it provides predefined experimental protocols in order to compare rigorously the results obtained by different researchers.
recognition of free-form objects in dense range data using local features. this article describes a system for recognizing free-form 3d objects in dense range data employing local features and object-centered geometric models. local features are extracted from range images and object models using curvature analysis, and variability in feature size is accommodated by decomposition of features into sub-features. shape indices and other attributes provide a basis for correspondence between compatible image and model features and subfeatures, as well as pruning of invalid correcpondences. a verification step provides a final ranking of object identity and pose hypotheses. the evaluation system contained 10 free-form objects and was tested using 10 range images with two objects from the database in each image. comments address strengths of the proposed technique as well as areas for future improvement.
experiments in transform-based range image compression. range images (depth maps) are seeing increased usage in a variety of application areas including entertainment, industrial automation, inspection, remote sensing, and military tactical planning. as the corpus of range imagery increases in size and the need to communicate such images over fixed-bandwidth channels increases, the compression of range data deservesinvestigation. since the geometry encoded by range sensors is inherently "low-bandwidth", transform-based techniques seem appropriate for investigation in this context. this paper reports on experiments with a popular zerotree-based image codec (the spiht algorithm developed by said and pearlman) and its application to the compression of range imagery. experiments suggest that compression rates of 1 bit/pixel and below are achievable with minimal impact on fidelity.
reliable and fast eye finding in close-up images. this paper describes a method for quickly and robustly localizing the iris and pupil boundaries of a human eye in close-up images. such an algorithm can be critical for iris identification, or for applications that must determine the subject's gaze direction, e.g., human-computer interaction or driver attentiveness determination. a multiresolution coarse-to-fine search approach is used, seeking to maximize gradient strengths and uniformities measured across rays radiating from a candidate iris or pupil's central point. an empirical evaluation of 670 eye images, both with and without glasses, resulted in a 98% localization accuracy. the algorithm has also shown robustness to weak illumination and most specular reflections (e.g., at eyewear and cornea), simplifying system component requirements. rapid execution is achieved on a 750 mhz desktop processor.
challenges for data mining in distributed sensor networks. the way of collecting sensor data will face a revolution when the newly developing technology of distributed sensor networks becomes fully functional and widely available. smart sensors will acquire full interconnection capabilities with similar devices, so that run-time data aggregation, parallel computing, and distributed hypothesis formation will become reality with off-the-sheif components and sensor boards. this revolution started around ten years ago, and now hardware and network are converging on the jirst convincing solutions. exploring and exploiting this paradigm are a renovated challenge for the pattern recognition and data mining community. this paper attempts a survey on state-of-the-art of wireless sensor technology, with an eye on data-related problems and technological limits. although the possibilities seem promising, the today limited computational resources of individual nodes hamper the elaboration of data with recent, computationallyintensive algorithms. new software paradigms must be developed, both creating new techniques or adapting, for network computing, old algorithms of earlier ages of computing.
most minutiae-based matching algorithms confront. most minutiae-based matching algorithms confront with the challenge of missing and fake minutiae, and especially the non-linear distortion. many efforts have been made to cope with these problems while relatively slow improvements achieved. in this paper, we proposed a novel minutiae-based matching scheme which introduced a concept of compatibility to the minutiae triangle structures. and based on the compatibility, we further adopted a relaxation process to adjust the similarity matrix of the minutiae triangle cells between the query and template images. to reduce the effect of non-linear distortion evidently, an extended searching step independent of any linear models was proposed. results obtained on the fvc2004 b1_a show that the proposed algorithm overcomes the influence of missing and fake minutiae, and meanwhile decreases the time cost of matching saliently.
simple calibration without metric information using an isoceles trapezoid. this paper addresses the problem of calibrating a pin-hole camera from images of an isoceles trapezoid. assuming a unit aspect ratio and zero skew, we introduce a novel and simple camera calibration approach. the key features of the proposed technique are its simplicity and the lack of need for 3d coordinate information about the calibrating object - i.e. the isosceles trapezoid. by ultilizing the symmetry of such trapezoid, we show that one can obtain both the internal and the external camera parameters. to demonstrate the effectiveness of the algorithm, we present the processing results on synthetic and real images, and compare our results to zhang's flexible calibration method.
automatic morphological detection of otolith nucleus. this paper deals with the analysis of otolith images for fish ageing issues. we present a new and well-founded approach for the automatic detection of the nucleus within otolith images. this topic is of key interest since the knowledge of the location of the otolith nucleus is required to achieve further processing (2d ring segmentation, age and growth estimation,...). using morphological features within an a contrario framework, we develop a robust parameterless scheme. its efficiency is demonstrated by an evaluation carried out for a set of several hundred of plaice otoliths.
synthesizing reflections of inserted objects. the aim of reflection synthesis of inserted objects is to generate reflections which would be seen by the same camera capturing the target scene and be reflected by the true reflective media in the target scene. this problem is inherently difficult because we are typically given only several, sometimes even just one, views of the target scene. in this paper, we explore the geometric constraints to synthesize geometrically correct reflections. we also demonstrate how to constraint the synthesized reflections to be photometrically consistent with those in the original target views. the proposed method, therefore, advances the current imagebased compositing techniques one step further toward the scenes with variations in both lighting conditions and viewpoints. we demonstrate our approach for real scenes.
nonlinear manifold clustering by dimensionality. because of variable dependence, high dimensional data typically have much lower intrinsic dimensionality than the number of its variables. hence high dimensional data can be expected to lie in (nonlinear) lower dimensional manifold. in this paper, we describe a nonlinear manifold clustering algorithm. by connecting data vectors with their neighbors in feature space, we construct a neighborhood graph from given set data vectors. furthermore, geometrical invariance, namely dimensionality, are extracted from the neighborhood of vectors, and used to facilitate the clustering procedure. in addition, we discuss a latent model for data cluster descriptions and an em algorithm to find such descriptions. preliminary experiments illustrate that this new algorithm can be used to explore the nonlinear structure of data.
online structure based chinese character pre-classification. in this paper, an online structural recognition (olsr) system for chinese characters is proposed. a pre-classification scheme based on this olsr is applied to improve the performance of a pure statistical pattern matching (spm) based chinese character recognition engine. the experimental result shows that the pre-classifier not only reduces the overall recognition time but also improves the online recognition accuracy
new rht-based ellipsoid recovery method. a new method that enables randomized hough transform (rht)-based recovery of ellipsoid parameters from a collection of 3d points is presented. the approach is attractive since it can alleviate the traditional hough transform's disadvantages of large computation time and memory usage—in particular for the ellipsoid detection's highdimensional parameter space. the new method uses two rht-based stages, first exploiting shape to enable recovery of position and then exploiting eigen analysis to recover the remaining parameters (of shape and orientation). experimental results on synthetic and real data are also presented.
breast mass segmentation based on information theory. in this study, an information based algorithm, called c-shells based deterministic annealing (csda), is proposed for breast mass segmentation on digital mammograms. csda recasts the fuzzy clustering concept into the probability framework and offers two improved features over existing clustering algorithms. first, it is a global minimization algorithm through mass constrained deterministic annealing rather than a local minimization method in the original fuzzy c-shells (fcs) approach. second, the prototype in this algorithm is shell, which is more effective in segmentation with compact or hollow spherical shells compared to the standard deterministic annealing (da) algorithm. experimental results show that the information based csda clustering algorithm is a promising image segmentation technique for digital mammographic mass detection.
self-calibration using constant camera motion. this paper investigates using constant inter-frame motion for self-calibration from an image sequence of an object rotating around a single axis with varying camera internal parameters. our approach is based on the facts that in many commercial systems rotation angles are often controlled by an electromechanical system, and the inter-frame essential matrices are invariant if the rotation angles are constant but not necessarily known. it is shown that recovering camera internal parameters is possible by making use of the equivalence of essential matrices, which relate the unknown calibration matrices to the fundamental matrices computed from the point correspondences. experimental results on both synthetic and real sequences are presented to determine the accuracy and the robustness of the proposed algorithm.
camera motion quantification and alignment. we propose a method to synchronize video sequences of distinct scenes captured by cameras undergoing similar motions. for the general camera motion and 3d scene, the camera ego-motions are featured by fundamental ratios obtained from the fundamental matrices. in the case of pure translation, translational magnitude features is used. these extracted features are invariant to the camera internal parameters, and therefore can be computed without recovering camera trajectories along the image sequences. consequently, the alignment problem reduces to matching sets of feature vectors, obtained without any knowledge of other sequences. experimental results demonstrate the accuracy and applications of the proposed method.
concurrent segmentation and recognition with shape-driven fast marching methods. we present a variational framework that integrates the statistical boundary shape models into a level set system that is capable of both segmenting and recognizing objects. since we aim to recognize objects, we trace the active contour and stop it near real object boundaries while inspecting the shape of the contour instead of enforcing the contour to get a priori shape. we get the location of character boundaries and character labels at the system output. we developed a promising local front stopping scheme based on both image and shape information for fast marching systems. a new object boundary shape signature model, based on directional gauss gradient filter responses, is also proposed. the character recognition system that employs the new boundary shape descriptor outperforms the other systems, based on well-known boundary signatures such as centroid distance, curvature etc.
synthetic fingerprint-database generation. this work complements our previous efforts in generating realistic fingerprint images for test purposes. the main variability which characterizes the acquisition of a fingerprint through an on-line sensor is modeled and a sequence of steps is defined to derive a series of impressions from the same master-fingerprint. this allows large fingerprint databases to be randomly generated according to some given parameters. the experimental results validate our technique and prove that it can be very useful for performance evaluation, learning and testing in fingerprint-based systems.
robust appearance-based object recognition using a fully connected markov random field. this paper presents a new kernel method for appearance-based object recognition, highly robust to noise and occlusion. it consists of a fully connected markov random field that integrates results of spin glass theory with gibbs probability distributions via nonlinear kernel mapping. we call this model spin glass-markov random field. we present theoretical analysis and several experiments that show its effectiveness and robustness to noise and occlusion. we obtain in both cases excellent results. particularly, we achieve a recognition rate above 93% with just 40% of visible portion of the object.
object categorization via local kernels. this paper considers the problem of multi-object categorization. we present an algorithm that combines support vector machines with local features via a new class of mercer kernels. this class of kernels allows us to perform scalar products on feature vectors consisting of local descriptors, computed around interest points (like corners); these feature vectors are generally of different lengths for different images. the resulting framework is able to recognize multi-object categories in different settings, from lab-controlled to real-world scenes. we present several experiments, on different databases, and we benchmark our results with state-of-the-art algorithms for categorization, achieving excellent results.
texture recognition through modal analysis of spectral peak patterns. in this paper we investigate how texture recognition can be achieved through the modal analysis of the pattern of peaks in the spectral density function. we commence from a texture characterisation which is based on the positions of peaks in the power spectrum. our aim is to use the modal structure of the pattern of peaks to perform texture retrieval from an image data-base. we explore two different approaches to the problem. first, we use a variant of the shapiro and brady method to perform recognition by comparing the modal structure of the proximity matrix for peak cluster centres. second, we perform latent semantic indexing on vectors representing the polar distribution of frequency peaks. we provide and experimental evaluation of these two methods on a data-base of fabric and wrapping paper patterns.
a learning model for multiple-prototype classification of strings. an iterative learning method to update labeled string prototypes for a 1-nearest prototype (1-np) classification is introduced. given a (typically reduced) set of initial string prototypes and a training set, it iteratively updates prototypes to better discriminate training samples. the update rule, which is based on the edit distance, adjusts a prototype by removing those local differences which are both frequent with respect to same-class closer training strings and infrequent with respect to different-class closer training strings. closer training strings are defined by unsupervised clustering. the process continues until prototypes converge. its main innovation is to provide a non-random local update rule to "move" a string prototype towards a number of string samples. a series of learning/classification experiments show a better 1-np performance of the updated prototypes with respect to the initial ones, that were originally selected to guarantee a good classification.
pruning local feature correspondences using shape context. we propose a novel approach to improve the distinctiveness of local image features without significantly affecting their robustness with respect to image deformations. local image features have proven to be successful in computer vision tasks involving partial occlusion, background noise, and various types of image deformations. however, the relatively high number of outliers that have to be rejected from the correspondences set, formed during the search for similar features, still plagues this approach. the task of rejecting outliers is usually based on estimating the global spatial transform suffered by the features in the correspondences set. this presents two problems: i) it cannot properly deal with non-rigid objects, and ii) it is sensitive to a high number of outliers. here, we address these problems by combining typical local features [multi-scale phase-based local features, object recognition from local scale-invariant features] with shape context [shape matching and object recognition using shape contexts]. a performance evaluation shows that this new semi-local feature generally provides higher distinctiveness and robustness to image deformations, thus potentially increasing the inlier/outlier ratio in the correspondences set. also, we show that in wide baseline stereo matching, and non-rigid motion applications, the use of the novel semi-local feature not only provides robustness to non-rigid deformations, but also produces a higher inlier/outlier ratio than the standard hough clustering of the global spatial transform of parameters.
a method for detecting artificial objects in natural environments. in this paper we will present a method for automatic detection of man-made objects in digital images representing natural environments. this method is based on statistical distribution of texture patterns in the image. this distribution is computed using zipf's law. the image is divided into sub-frames and zipf's distribution is computed for each sub-frame. then the surfaces under zipf's plots of the different sub-frames are compared in order to determine which sub-frame will contain an object. the sensitivity of this detection method to image resolution is also examined
compressed image quality evaluation using power law models. this paper presents a compressed image quality measure based on the properties of zipf law, which is a power-law model adapted from linguistic analysis. it describes the frequency distribution of image patterns, and can be used to put into evidence image details which are affected by compression. two image quality evaluation measures based on zipf law have been proposed and tested, one designed to be used on jpeg images and the other on jpeg2000 images. these measures have also been used with the tabu search algorithm for automatic compression optimization..
a combined bayesian markovian approach for behaviour recognition. numerous techniques exist which can be used for the task of behavioural analysis and recognition. common amongst these are bayesian networks and hidden markov models. although these techniques are extremely powerful and well developed, both have important limitations. by fusing these techniques together to form bayes-markov chains, the advantages of both techniques can be preserved, while reducing their limitations. the bayes-markov technique forms the basis of a common, flexible framework for supplementing markov chains with additional features. this results in improved user output, and aids in the rapid development of flexible and efficient behaviour recognition systems.
bayes information criterion for tikhonov regularization with linear constraints: application to spectral data estimation. spectral data estimation is an ill-posed problem, since (i) it is difficult to collect sufficient linear independent data and (ii) due to the integral nature of solid-state light sensors, camera outputs do not depend continuously on input signals. to solve these problems, most methods rely on exact a priori knowledge to reduce the problem's complexity (solution space). in this paper a new algorithm is introduced which does not require a priori information. the method is build upon a new extension of the bayes information criterion for ill-posed estimation problems, that is able to extract this information from the input data. the proposed solution is quite general and can readily be applied to other ill-posed problems, which are common in computer vision and image processing.
wavelet-based multiresolution stereo vision. an efficient wavelet-based multiresolution approach to the stereo vision problem is presented. a cost function is defined and iteratively minimized. the minimization is performed on the images' representation in the wavelet space. we employ the theory of representation of operators in spaces spanned by scaling functions and thereby take advantage of a simplified approximation of differentiation. examples illustrate the advantages afforded by the applicationof our algorithm over correlation-based methods.
implementation of a modular real-time feature-based architecture applied to visual face tracking. this paper presents a modular real-time feature-based visual tracking architecture where each feature of an object is tracked by one module. a data fusion stage collects the information from various modules exploiting the relationship among features to achieve robust detection and visual tracking. this architecture takes advantage of the temporal and spatial information available in a video stream. its effectiveness is demonstrated in a face tracking system that uses eyes and lips as features. in the architecture implementation, each module has a pre-processing stage that reduces the number of image regions that are candidates for eyes and lips. support vector machines are then used in the classification process, whereas a combination of kalman filters and template matching is used for tracking. the geometric relation between features is used in the data fusion stage to combine the information from different modules to improve tracking.
combining data-closeness and fourier domain integrability constraints in shape-from-shading. this paper describes a shape-from-shading algorithm that combines constraint on data-closeness from lambert's law and fourier domain integrability. the data closeness is ensured by constraining surface normals to fall on an irradiance cone, whose axis points in the light source direction and whose apex angle varies with iteration number. the integrability is ensured by projecting the non-integrable set of surface normals to the nearest integrable one by globally minimizing the distance among them in the fourier domain. the combination of both data-closeness and integrability constraints is aimed to overcome the problem of high dependency on the image irradiances. experimental results prove that the new method recovers needle maps that are both smooth and integrable and improves height surface stability.
a simple coupled statistical model for 3d face shape recovery. we focus on the problem of developing coupled statistical models that can be used to recover surface height from brightness images of faces. our approach consists on using a simple model that assumes that the height eigenmodes are identical to the intensity eigenmodes. we recover the height function directly from the best-fit intensity parameters. as a result the computations involve only a straightforward matrix-vector multiplication. experiments show that this method generate accurate height surfaces from out-of training intensity images.
a facial statistical model from complex numbers. in this paper we explore the use of complex numbers as means of representing angular statistics for surface normal data. our aim is to use the representation to construct a statistical model that can be used to describe the variations in fields of surface normals. we focus on the problem of representing facial shape. the fields of surface normals used to train the model are furnished by range images. we compare the complex representation with one based on angles, and demonstrate the advantages of the new method. once trained, we illustrate how the model can be fitted to brightness images by searching for the set of parameters that both satisfy lambert's law and minimize the integrability error.
efficient model selection for kernel logistic regression. kernel logistic regression models, like their linear counterparts, can be trained using the efficient iteratively re-weighted least-squares (irwls) algorithm. this approach suggests an approximate leave-one-out cross-validation estimator based on an existing method for exact leave-one-out cross-validation of least-squares models. results compiled over seven benchmark datasets are presented for kernel logistic regression with model selection procedures based on both conventional k-fold and approximate leave-one-out cross-validation criteria, demonstrating the proposed approach to be viable.
generic real-time tracking method on semi-dynamic scenes. this paper describes a tracking method capable of following multiple targets for a generic scene in real-time. the tracker has no a priori knowledge of the objects and does not know how many objects will be present in the scene. the tracker uses straight-forward techniques to extract, identify and track the targets within the image sequence.
integrating local and global features in automatic fingerprint verification. this paper presents a new approach for combining local and global recognition schemes for automatic fingerprint verification (afv), by using matched local features as the reference axis for generating global features. in our specific implementation, minutia-based and shape-basedtechniques were combined. the first one matches local features (minutiae) by a point-pattern matching algorithm. the second one generates global features (shape signatures) by using the matched minutiae as its frame of reference. shape signatures are then digitised to form afeature vector describing the fingerprint. finally, a lvq neural network was trained to match the fingerprints by using the difference of a pair of feature vectors. the experimental results show that the integrated system significantly outperforms the minutiae-based system in terms ofclassification accuracy and stability. this makes the new approach a promising solution for biometric applications.
trainable table location in document images. we describe an approach for table location in document images. the documents are described by means of a hierarchical representation that is based on the mxy tree. thepresence of a table is hypothesized by searching parallel lines in the mxy tree of the page. this hypothesis is afterwards verified by locating perpendicular lines or white spaces in the region included between the parallel lines. lastly,located tables can be merged on the basis of proximity and similarity criteria.the use of an optimization method,that relies on the definition of an appropriate table location index, allows us to identify the optimal values of thresholds involved in the algorithm. in this way the algorithm can be adapted to recognize tables with different features by maximizing the performance on an appropriate training set.the algorithm has been evaluated on two data-sets containing more than 1500 pages, and comparing its results with the tables identified by two commercial ocrs.
face recognition by using discriminative common vectors. in face recognition tasks, the dimension of the sample space is typically larger than the number of the samples in the training set. as a consequence, the within-class scatter matrix is singular and the linear discriminant analysis (lda) method cannot be applied directly. this problem is also known as the "small sample size" problem. in this paper, we propose a new face recognition method based on the discriminative common vectors for the small sample size case. the discriminative common vectors representing the people in the face database were found by using the null space of the within-class scatter matrix. then, these vectors were used for classification of new faces. test results show that the proposed method is superior to other methods in terms of accuracy, efficiency, and numerical stability.
automatic detection of planar contours from uncalibrated images. the present paper describes an original technique developed for detecting and matching unknown planar structures between a pair of uncalibrated images. problems related to bad segmentation or to occlusion are automatically solved in most cases. the match process works hierarchically on pertinent point which provide local consistency and on contours which ensure the global consistency. after match, contours are splited into planar contour accordingto collineations. tests made over different pairs of images demonstrate the efficiency of our approach.
unsupervised evaluation of image segmentation application to multi-spectral images. we present in this article a study of some unsupervised evaluation criteria of an image segmentation result. the goal of this work is to be able to automatically choose the parameters of a segmentation method best fitted for an image or to fusion different segmentation results. we compared six unsupervised evaluation criteria on a database composed of 100 synthetic gray-level images segmented by four methods. vinet's measure is used as an objective function to compare the behavior of the different criteria. we finally apply these criteria to evaluate segmentation results of multi-components images. we present in this article some experimental results of evaluation of gray-level and multi-components natural images.
a novel human gait recognition method by segmenting and extracting the region variance feature. existing methods of gait recognition suffer from some shortcomings, which are discussed at the beginning of the full paper. in order to suppress these shortcomings as much as possible, we proposed a new automatic gait recognition approach based on the region variance feature. firstly, the binary silhouette of a walking person is detected from each frame of the monocular image sequences. then we divide the two dimensional silhouette of the walker into three regions (head region, trunk region and legs region). next, the variance features of these regions are extracted respectively. together with the ratio of the silhouette's height and width, the gait signature vectors are constructed to identify different subjects. finally, similarity measurement based on the gait cycles and nn and knn classifiers are carried out to recognize the different subjects. experimental results show that the proposed novel method is very effective and correct recognition rates are over 92% and 97% on ucsd and cmu database, respectively.
enhancing edit distance on real sequences filters using histogram distance on fixed reference ordering. distance functions are the main tools to measure similarity of two sequences and to search the closest sequences to given query sequence. several well known distance functions, however, have asymptotical time complexity of o(mn) which cannot be fully afforded by systems that deal with large volumes of data. these distance functions, including edit distance on real sequences (edr) [5], have pruning methods to reduce execution time by dismissing false candidates as early as possible. in this paper, we propose the histogram distance on fixed reference (hdfr) ordering, with various reference histogram construction methods, to improve the filtering power of the pruning methods in edr. experiments show that a decrease in edr execution time is observed after hdfr is applied. while we base our experiments on edr, hdfr can also be applied to other distance functions with appropriate pruning methods.
towards correlation-based matching algorithms that are robust near occlusions. in the context of computer vision, matching can be done using correlation measures. this paper presents new algorithms that use two correlation measures: the zero mean normalised cross-correlation, zncc, and the smooth median absolute deviation, smad. while zncc is efficient in non-occluded areas and non-robust near occlusions, smad is non-efficient in non-occluded areas and robust near occlusions. the aim is to use the advantages of zncc and smad to deal with the problem of occlusions and to obtain dense disparity maps. the experimental results show that these algorithms are better than zncc-based algorithm and smad-based algorithm.
detecting rare events in video using semantic primitives with hmm. we present a new approach for recognizing rare events in aerial video. we use the framework of hidden markov models (hmms) to represent the spatio-temporal relations between objects and uncertainty in observations, where the data observables are semantic spatial primitives encoded based on prior knowledge about the events of interest. events are observed as a sequence of binarized distance relations among the objects participating in the event. this avoids directly modeling the temporal trajectories of continuous observables, which is difficult when training data is scarce. the approach enables better generalization to other scenes for which little or no training data may be available. we demonstrate the effectiveness of our approach using real aerial video and simulated data.
event recognition with fragmented object tracks. complete and accurate video tracking is very difficult to achieve in practice due to long occlusions, traffic clutter, shadows and appearance changes. in this paper, we study the feasibility of event recognition when object tracks are fragmented. by changing the lock score threshold controlling track termination, different levels of track fragmentation are generated. the effect on event recognition is revealed by examining the event model match score as a function of lock score threshold. using a dynamic bayesian network to model events, it is shown that event recognition actually improves with greater track fragmentation, assuming fragmented tracks for the same object are linked together. the improvement continues up to a point when it is more likely to be offset by other errors such as those caused by frequent object reinitialization. the study is conducted on busy scenes of airplane servicing activities where long tracking gaps occur intermittently.
multiplierless fast dct algorithms with minimal approximation errors. the approximation method proposed in this paper converts each constant in a dct algorithm into a minimum number of signed digits. then any multiplication in the transform can be turned into a number of add-and-shift operations on an integer value. with this technique, any fast dct algorithm can be made multiplierless. to reduce the algorithm complexity and the word length requirement, we developed an effective algorithm for converting any constant into a signed digits string with minimum number of non-zero signed digits and a reduced word length. the approximation errors of different constants could affect differently the mse of the approximated algorithm. the simple strategy is to assign more digits to those constants whose errors are more sensitive to the mse of the algorithm whose complexity will however increase when the total number of digits assigned to the constants becomes larger. this paper devised an efficient algorithm to find an optimized signed digits configuration for minimizing the mse of the algorithm with a specified complexity. experiment results show that lee's fast dct algorithm approximated by the proposed method can be used to reconstruct images with high visual quality in terms of psnr.
extending the depth of field in a compound-eye imaging system with super-resolution reconstruction. optical device miniaturization is highly desirable in many applications. direct down-scaling of traditional imaging system is one approach, but the extent to which it can be minimized is limited by the effect of diffraction. compound-eye imaging system, which utilizes multiple microlenses in image capture is a promising alternative. in this paper, we explore the possibility of an incorporation of phase masks in such a system to extend the depth of field. simulation experiments are conducted to verify the feasibility of the system.
pose estimation for multiple camera systems. pose estimation of a multiple camera system (mcs) is usually achieved by either solving the pnp problem or finding the least-squared-error rigid transformation between two 3d point sets. these methods employ partial information of an mcs, in which only a small number of features in one or two cameras can be utilized. to overcome this limitation, we propose a new pose estimation method for an mcs that uses complete information of an mcs. in our method, we treat the mcs as a single generalized camera [a general imaging model and a method for finding its parameters][using many cameras as one] and formulate this problem in a least-squared manner. an iterative algorithm is proposed for solving the least-squared problem. from the experimental results, it shows that the proposed method is accurate for pose estimation of mcs.
discriminative descriptor-based observation model for visual tracking. varying illumination and partial occlusion are two main difficulties in visual tracking. existing methods based on appearance information cannot solve these problems effectively since appearance is sensitive to lighting and the appearances under occlusions are quite different. in this paper, we propose a descriptor-based dynamic tracking approach that can track objects under partial occlusions and varying illumination. instead of global appearance, an object is represented by a set of invariant feature descriptors that are generated from local regions around some salient points. by integrating the local descriptor information into the observation model, our method is effective under varying illumination and partial occlusions.
an intelligent bulletin board system with real-time vision-based interaction using head pose estimation. a bulletin board is a place where people can read announcements, posters or leave public messages. however, traditional bulletin board certainly have several disadvantages such like without real-time interaction with users and monotonous. this paper presents an intelligent bulletin board system (ibbs), which allows a user to real-time interact with it without any additional auxiliaries. at first, a real-time front-view face detection using harr-like features is used to decide when ibbs should wake up and become interactive with the user. after system initialization, we keep on finding some feature points within the detected face area. then we estimate the orientation of user's head via pyramidal lucas-kanade optical flow tracking. compared to the traditional bulletin board system, our system has more flexibility. with the comparison to other non-vision-based input devices such like gloves or markers, our system offers a simple, useful and economical solution for the real-time interaction between the user and computer.
physics-based fusion of multispectral data for improved face recognition. a novel physics-based fusion of multispectral images within the visual spectra is proposed for the purpose of improving face recognition under constant or varying illumination. spectral images are fused according to the physics properties of the imaging system, including illumination, spectral response of the camera, and spectral reflectance of skin. the fused image is given as a probe to the recognition software faceit® which compares it to a gallery of images. the identification performance of our physics-based fusion method is compared to the performance of principle component analysis and average fusion methods. the results show that the proposed fusion yields a higher identification rate. a method of illumination adjustment is proposed when the probe and gallery images are acquired under different illumination conditions. the results show that the identification rate is higher than that of unadjusted gray-level images.
detecting deformable objects with flexible shape priors. we address the problem of detecting objcts/shapes with large deformation and articulation in cluttered images. the approach requires a shape prior that describes the approximated outline and articulation property of a given model. while dynamic programming is often used in solving shape detection, our focus is on formulating a more effective energy function to evaluate the optimality of a matching between the shape prior and image features. for efficiency, the detection via optimization is carried out over a non-uniform elastic grid based on referencing the edge information. experimental results are included to illustrate our method.
applying a hybrid method to handwritten character recognition. in this paper, we propose a new prototype learning/matching method that can be combined with support vector machines (svm) in pattern recognition. this hybrid method has the following merits. one, the learning algorithm for constructing prototypes determines both the number and the location of prototypes. this algorithm terminates within a finite number of iterations and assures that each training sample matches in class types with the nearest prototype. two, svm can be used to process top-rank candidates obtained by the prototype learning/matching method so as to save time in both training and testing processes. we apply our method to recognizing handwritten numerals and handwritten chinese/hiragana characters.experiment results show that the hybrid method saves great amount of training and testing time in large-scale tasks and achieves comparable accuracy rates to those achieved by using svm solely. our results also show that the hybrid method performs better than the nearest neighbour method.
an iterative bayesian approach for digital matting. this paper proposes a new iterative approach for digital image matting. it combines pre-segmentation and matting into an unified approach and extracts good matte iteratively within a well-defined bayesian framework based on a few user strokes on foreground and background regions. this method does not need a well specified trimap, which refers to a pre-segmented image with definitely foreground, definitely background and unknown regions, and can therefore efficiently handle the images, in which the trimap is very hard to create even manually. experimental results show that, compared with previous approaches, our method is more convenient and robust especially for images with large amount of holes or with foreground objects containing large portion of semi-transparent parts.
non stationary bayesian image restoration. in this paper we propose a new iterative bayesian non stationary image restoration algorithm. the main novelty of this approach is the introduction of a hierarchical non stationary image prior. based on this prior and the generative graphical model for the observations, bayesian inference is performed integrating out the hidden variables. an interesting byproduct of this approach is the justification, using a bayesian framework, of previous non stationary image restoration formulations that were based on heuristic arguments. numerical experiments are provided that demonstrate the advantages of the proposed non stationary approach as compared with stationary approaches.
a fibre bundle model of surfaces and its generalization. a fibre bundle model of shapes is proposed to describe a surface as a local direct product of a base curve and a fibre curve. with fibre curves as 1-parameter groups, this model is efficient in both synthesis and recognition. in fact, the 1-parameter groups can be uniquely determined by finite, e.g. six invariants of their lie algebras. besides the surfaces can be fastly generated by elementary function without numerical integration error. this model is then extended to fibres defined by high order ode.
defect detection in low-contrast glass substrates using anisotropic diffusion. in this research, we propose an anisotropic diffusion scheme to detect defects in low-contrast surface images and, especially, aim at glass substrates used in tft-lcds (thin film transistor-liquid crystal displays). in a sensed glass substrate, the gray levels of defects and background are hardly distinguishable and result in a low-contrast image. therefore, thresholding and edge detection techniques cannot be applied to detect subtle defects in the glass substrates surface. the proposed diffusion method in this paper can simultaneously carry out the smoothing and sharpening operations. it adaptively triggers the smoothing process in faultless areas to make the background uniform, and performs the sharpening process in defective areas to enhance anomalies. experimental results from a number of glass substrate samples including backlight panels and lcd glass substrates have shown the efficacy of the proposed diffusion scheme in low-contrast surface inspection.
a kernel-based discrimination framework for solving hypothesis testing problems with application to speaker verification. real-word applications often involve a binary hypothesis testing problem with one of the two hypotheses ill-defined and hard to be characterized precisely by a single measure. in this paper, we develop a framework that integrates multiple hypothesis testing measures into a unified decision basis, and apply kernel-based classification techniques, namely, kernel fisher discriminant (kfd) and support vector machine (svm), to optimize the integration. experiments conducted on speaker verification demonstrate the superiority of our approaches over the predominant approaches.
a robust region-based multiscale image fusion scheme for mis-registration problem of thermal and visible images. in this paper, a region based multiscale image fusion based on discrete wavelet frame (dwf) is proposed to combine information from thermal and visible images. because of the fusion result of thermal and visible image may then allow both detection and imperceptible localization of the target in thermal image with respect to the discernible background provided by visible image. additionally, the objective is to decrease the misregistration problem of these images which is actually exists in practice. the concept of discrete wavelet frame, which leads to translation invariant, can solve this problem. in our experiments, the preprocessing procedure of these source images is approached. it includes enhancement and registration based on object matching. experimental results show that the proposed fusion scheme provides more robust when mis-registration distortion exists for the source images.
learning and extracting edges from images by a modified hopfield neural network. this paper introduced a modified unsupetvised hopfield network that can learn the underlying process in an edge detection task from grey level images. after the learning phase, the network peiformance is tested to ensure that it can detect only the significant edges andthat it can generalise other images.
real time tracking with occlusion and illumination variations. the authors present a robust real time object tracking by image processing. a planar model defined by a center and few interest points of the object is used. this model choice allows to be robust to light variations and partial occlusions and a particle filter based tracker allows to recover from total occlusion of the object during a few seconds. this algorithm works at 15hz on a personal computer under linux and is robust concerning both geometrical aspects as planar rotation and scale modification.real experimentations prove the validity of the method for outdoor applications like vehicule tracking for adaptive cruise control.
a two-stage outlier rejection strategy for numerical field extraction in handwritten documents. in this article, we propose a segmentation-driven recognition system which aims at extracting numerical fields from handwritten documents. we show that a crucial point of the system is the rejection ability of the handwritten numeral classifier. therefore, we propose a simple two-stage outlier rejection strategy, and we show the benefit of this strategy on the numerical field extraction results.
local representation of 3d free-form contours for pose estimation. in this paper we present a new representation for 3d free-form contours in the conformal geometric algebra g4,1. this new representation allows to extract local geometrical feature information which is used to solve the correspondence problem for pose estimation applications. under perspective projection, local features are extracted from a projected contour segment and compared with image features obtained from the monogenic signal. we tested our approach using synthetical and real data for several pose estimation algorithms.
automatic sleep apnoea detection using measures of amplitude and heart rate variability from the electrocardiogram. a method for the automatic processing of the electrocardiogram (ecg) for the detection of disordered breathing associated with obstructive sleep apnoea is presented. the method provides a minute-by-minute analysis of night-time single lead ecg recordings. anindependently validated database of 35 ecg recordings acquired from normal subjects and subjects with obstructive and mixed sleep apnoea, each of approximately eight hours in duration, was used throughout the study. a wide variety of features based on heart beat intervals and an electrocardiogram derived respiratory signal were considered. classifiers based on linear and quadratic discriminants were used. results show that a 90% success rate in correctly identifying one-minute segments containing disordered breathing is achievable.
media content and type selection from always-on wearable video. a system is described for summarizing head-mounted or hand-carried "always-on" video. the example used is a tourist walking around a historic city with friends and family. the summary consists of a mixture of stills, panoramas and video clips. the system identifies both the scenes to appear in the summary and the media type used to represent them. as there are few shot boundaries in this class of video, the decisions are based on the system's classification of the user's behaviour demonstrated by the motion of the camera, and motion in the scene.
m-estimator based robust kernels for support vector machines. in this paper, we propose m-estimator based robust kernels for support vector machine. the main motivation for our proposed kernels is that the sum of squared difference in the widely used gaussian radial basis function kernels is not robust to outlier or noise. in addition, inspired by using a robust loss function in support vector machine regression to control training error [learning with kernels - support vector machines, regularization, optimzation and be-yond] and the idea of robust template matching with m-estimator [fast algorithm for robust template matching with m-estimators], we apply m-estimator techniques to gaussian radial basis functions and form a new class of robust kernels for support vector machines. we test our proposed kernels in several classification benchmark datasets and experimental results show that svm with proposed kernels are better than svm with gaussian radial basis function kernels.
an application of robust template matching to user location on wireless infrastructure. instead of using conventional template matching with the sum of squared distance (ssd) for signal strength matching to provide user location on wireless infrastructure[radar: an in-building rf based user location and tracking system], we propose the use of robust template matching methods [fast algorithm for robust template matching with m-estimators] for providing robust user location. our method expects and handles the noisy data common within a wireless setting, and provides the user with relevant information as to the reliability of their location within the system. in our experiments, we compare our method with conventional ssd based and sum of absolute difference (sad) based template matching and a state of the art method, support vector machines [the nature of statistical learning theory]. our experimental results show that some of robust template matching methods can outperform compared methods very much.
noise variance adaptive sea for motion estimation: a two-stage schema. in a practical video encoder, a video sequence obtained from a ccd camera inevitably conveys noise, which degrades not only image quality but also coding efficiency. based on the statistic analysis of noise signal,a noise variance adaptive two-stage successive elimination algorithm(nva-sea) for block motion estimation is presented. simulation results demonstrate that the proposed algorithm can get close performance to the full search, while the computation time has been significantly reduced.
3d free-form object recognition in range images using local surface patches. this paper introduces an integrated local surface descriptor for surface representation and 3d object recognition. a local surface descriptor is characterized by its centroid, its local surface type and a 2d histogram. the 2d histogram shows the frequency of occurrence of shape index values vs. the angles between the normal of reference feature point and that of its neighbors. instead of calculating local surface descriptors for all the 3d surface points, they are calculated only for feature points that are in areas with large shape variation. in order to speed up the retrieval of surface descriptors and to deal with a large set of objects, the local surface patches of models are indexed into a hash table. given a set of test local surface patches, votes are cast for models containing similar surface descriptors. based on potential corresponding local surface patches candidate models are hypothesized. verification is performed by running the iterative closest point (icp) algorithm to align models with the test data for the most likely models occurring in a scene. experimental results with real range data are presented to demonstrate and compare the effectiveness and efficiency of the proposed approach with the spin image and the spherical spin image representations.
human ear detection from side face range images. ear detection is an important part of an ear recognition system. in this paper we address human ear detection from side face range images. we introduce a simple and effective method to detect ears, which has two stages: offline model template building and on-line detection. the model template is represented by an averaged histogram of shape index. the on-line detection is a four-step process: step edge detection and thresholding, image dilation, connect-component labeling and template matching. experiment results with real ear images are presented to demonstrate the effectiveness of our approach.
invariant texture classification using ridgelet packets. in this paper, we propose a novel rotation invariant texture classification technique by using ridgelet packets. ridgelet packets provide many orthonormal bases that can effectively capture directional features present in textures. the fourier transform is good at eliminating the texture orientation differences. by combining these two tools, a very efficient rotation invariant texture classification technique is created. experimental results show that the proposed method achieves very high classification rates and it outperforms two state-of-the-art methods for rotation invariant texture classification under both noise-free and noisy environments.
function dot product kernels for support vector machine. a new family of kernels for support vector machine is proposed by taking the dot product of two function vectors. these kernels are proved to be admissible support vector kernels, and the dot product function in the kernels can be selected as the polynomial, the gaussian radial basis function, the exponential radial basis function, the wavelet function, the autocorrelation wavelet function, the probability function, etc. experiments show the feasibility of the proposed kernels for pattern recognition. the dual-tree complex wavelet is used to extract invariant features for recognizing similar handwritten numerals, and the recognition rate is about 99.50% for a training data set of 800 samples and a testing data set of 400 samples. it is also possible to apply the proposed kernels to function regression.
global-to-local non-rigid shape registration. non-rigid shape registration is an important issue in computer vision. in this paper we propose a novel globalto- local procedure for aligning non-rigid shapes. the global similarity transformation is obtained based on the corresponding pairs found by matching shape context descriptors. the local deformation is performed within an optimization formulation, in which the bending energy of thin plate spline transformation is incorporated as a regularization term to keep the structure of the model shape preserved under the shape deformation. the optimization procedure drives the initial global registration towards the target shape that results in the one-to-one correspondence between the model and target shape. experimental results demonstrate the effectiveness of the proposed approach.
invariant ridgelet-fourier descriptor for pattern recognition. in this paper, we present a novel descriptor for feature extraction by using a combination of ridgelets and fourier transform. we have successfully implemented ridgelets on the circular disk containing the pattern and applied fourier transform on the resulting ridgelet coefficients to extract rotation-invariant features for pattern recognition. the descriptor is very robust to gaussian noise even when the noise level is high. experimental results show that the new descriptor is a very good choice for pattern recognition.
discriminative distance measures for image matching. we propose a framework incorporating aspects of image classification to aid the matching of a reference image to target images. the framework involves an image representation based on a set of feature vectors, and a parametric distance measure on any two such vector sets. the distance measure may be optimized to provide maximum discrimination between the matching target images and the background images, when compared to the reference image. preliminary results indicate that the new distance measure performs substantially better than the traditional ssd and the bhattacharyya histogram measures in classification and tracking tasks.
improvement of bidirectional recurrent neural network for learning long-term dependencies. bidirectional recurrent neural network (brnn) is a non-causal generalization of recurrent neural networks (rnns). due to the problem of vanishing gradients, brnn cannot learn long-term dependencies efficiently with gradient descent. to tackle the long-term dependency problem, we propose segmented-memory recurrent neural network (smrnn) and develop a bidirectional segmented-memory recurrent neural network(bsmrnn). we test the performance of bsmrnn on the problem of information latching. our experimental results show that bsmrnn outperforms brnn on long-term dependency problems.
new efficient octree construction from multiple object silhouettes with construction quality control. in this paper, we propose an octree construction method with a new subdivision strategy which is governed by the degree of overlapping between each generated octant and the object. the specification of a maximum level of subdivision required in the conventional method is not needed. we introduce "grey-grey" and "grey-black" nodes based on a construction quality measure. the construction quality is measured by the maximum 2d projection error of the projected octant image with respective to the object silhouette in all views. only those octants which are "grey-grey" nodes will be subdivided. furthermore, we present a fast computation of the 2d projection and a new intersection test to reduce the computer processing time. computer simulations are conducted to show that the new method outperforms the conventional method in terms of memory space and computation time subject to the same level of construction quality.
a comparison of texture features based on svm and som. experimental results of texture features derived from gabor and other four wavelet transforms classified and clustered based on support vector machine (svms) and self-organizing maps (soms) are reported in this paper. a comparison of svm and som in texture classification is illustrated. the results show that these texture sets with appropriate classifiers perform reasonably well.
nighttime vehicle detection for driver assistance and autonomous vehicles. this study presents an effective method for detecting vehicles in front of the camera-assisted car during nighttime driving. the proposed method detects vehicles based on detecting and locating vehicle headlights and taillights using techniques of image segmentation and pattern analysis. first, to effectively extract bright objects of interest, a segmentation process based on automatic multilevel thresholding is applied on the grabbed road-scene images. then the extracted bright objects are processed by a rule-based procedure, to identify the vehicles by locating and analyzing their vehicle light patterns, and estimate their distances to the camera-assisted car. experimental results demonstrate the effectiveness of the proposed method on detecting vehicles at night.
resampling for face detection by self-adaptive genetic algorithm. over the past ten years, face detection has been thoroughly studied in computer vision research for its interesting applications. however, all of the state-of-the-art statistical methods suffer from the data collection for training a classifier. this paper presents a self-adaptive genetic algorithm (ga)-based method to swell face database through re-sampling from the existing faces. the basic idea is that a face is composed of a limited components set, and the ga can simulate the procedure of heredity. this simulation can also cover the variations of faces in different lighting conditions, poses, accessories, and quality conditions. to verify the generalization capability of the proposed method, we also use the expanded database to train an adaboost-based face detector and test it on the mit+cmu frontal face test set. the experimental results show that the data collection can be efficiently speeded up by the proposed methods.
a robust algorithm of principal curve detection. in this paper, we present a new method for the detection of principal curves in complicated feature images. based on the criteria of the shortest path of curves and directional deviation of paths, principal curve detection is carried out in graph domain. dfs searching scheme is adopted in exploration of a graph network. the motivation of this research is to find road boundaries and house contours from printed map images. by extensive experiments, the algorithm has shown good efficiency and robustness with real map images. the technique described in this paper can also be used in other applications, such as in character recognition, to separate characters from other unwanted document components that overlap with the characters.
yuv correction for multi-view video compression. a luminance and color correction algorithm for multi-view video compression is proposed in this paper. due to the dissimilar radiometric characteristics of different cameras and the variation of lighting conditions, significant luminance and color discrepancies among different camera views often exist in multi-view video sequences. these variations may cause the wrong disparity matching and result in the degradation of coding efficiency. to elevate the multiview video coding efficiency, a discrepancy model of different views based on modulation and translation parameters is proposed, and the discrepancies among different views are compensated before disparitymatching. the optimization of compensation parameters is discussed, and histogram matching method is used to mitigate the computational load. experimental results on both visual quality and coding efficiency have verified the validity and robustness of the proposed method.
automatic segmentation of lung fields from radiographic images of sars patients using a new graph cuts algorithm. this paper proposes an approach to the segmentation of lung fields in the severe acute respiratory syndrome (sars) infected radiographic images, which is the first step towards a computer-aided diagnosis system. to overcome the segmentation difficulty of highly atypical property of sars in the lung images, our algorithm first uses morphological operations to obtain the initial estimation of the regions where the lung boundaries lie in, and then applies a new graphbased optimization method to find the interested regions. the theoretical analysis shows that our approach is resistant to boundary discontinuity, noise, and large patches that affect the boundary search. experimental results are given to demonstrate the good performance of our algorithm.
a moving object tracked by a mobile robot with real-time obstacles avoidance capacity. this paper describes a robotic application that tracks a moving object by utilizing a mobile robot with multiple sensors. the robotic platform uses a visual camera to sense the movement of the desired object and a range sensor to help the robot detect and then avoid obstacles in real time while continuing to track and follow the desired object. in terms of real-time obstacle avoidance capacity, this paper also presents a modified potential field algorithm called dynamic goal potential field algorithm (dgpf) for this robotic application specifically. experimental results show that the robotic and intelligent system can fulfill the requirements of tracking an object and avoiding obstacles simultaneously when the object is moving.
lbt based low complexity image compression method. the lapped biorthogonal transform (lbt) based low complexity and low memory image compression method is proposed in this paper. lbt costs 46% computation as the discrete wavelet based (dwt), and only buffers 1/15 data that dwt does. by analyzing the distribution of the coefficients of lbt, the quantized set partition codec is used in our method. in coding process no context information is needed, and no complicated data structure, such as list, is used, which is low memory and low computation. the compression results on many standard test images show that, using the same coding method, lbt based one performs better than dwt based, with higher psnr and less distortion. we also find that lbt based method is especially fit to images with more details, such as high resolution satellite images. after all, our method is suitable to portable devices and real time processing.
a universal method for single character type recognition. character image contains not only the character information, but also the type information. the character's type information denotes the various category of the character, such as the font families, handwritten or printed, to what language the character belongs, etc. most of the existent methods for character type recognition are carried out on a group of characters belonging to the same category, and all these methods concentrate on their own specific field. in this paper, a novel universal method for character type recognition is proposed, which is based on a single unknown character and can be used in various fields. we employ a wavelet transform on the character image and extract wavelet features from the transformed image, which are used by a mqdf classifier. compared with existent methods, our method is much more flexible, robust and effective.
boundary correction for total variation regularized l^1 function with applications to image decomposition and segmentation. the total variation model with l^1 norm fidelity term (tvl^1) has been proposed to serve as an effective cartoontexture image decomposition tool because of its unique scale-dependent decomposition ability. nevertheless, one of its largely overlooked limitations is its inability to perfectly retain the original contours of the selected patterns when the fidelity term is not sufficiently weighted. in this paper, we propose a boundary correction method to refine the contours of extracted patterns under such circumstances. a scale-driven image segmentation algorithm extended from the boundary correction method is presented as an application. experimental results demonstrate that our works overcome the drawbacks of existing tv-l^1 model and provide an alternative segmentation method.
fast semi-local alignment for dn sequence database search. given a query dn sequence, our goal is to find in the dn sequence database all the sequence segments that are similar to the query. in this paper we present a string-to-signal transform technique that can transform a dn sequence into a four-channel signal. without considering gaps, the edit distance between two dn sequences can be calculated as the sum of absolute difference (sad) between their corresponding four-channel signals. the algorithm proposed in this paper can then be applied to speed up the process of searching for the desired sequence segments that yield small sads. in addition to efficiency, this algorithmguarantees the optimal search. that is, all the sequence segments that are similar enough to the query can be found without any miss.
segmentation of human body parts using deformable triangulation. this paper presents a new segmentation algorithm to segment a body posture into different body parts using the technique of triangulation. for well analyzing each posture, we first propose a triangulation-based method to triangulate it to different triangle meshes. then, we use a depth-first search scheme to find a spanning tree as its skeleton feature from the set of triangulation meshes. the triangulation-based scheme to extract important skeleton features has more robustness and effectiveness than other silhouette-based approaches. then, different body parts can be roughly extracted by removing all the branching points from the spanning tree. a model-driven technique is then proposed for more accurately segmenting a human body into semantic parts. this technique uses the concept of gaussian mixture model (gmm) to model different visual properties of different body parts. then, a suitable segmentation scheme can be driven by classifying these models using their skeletons. experimental results have proved that the proposed method is robust, accurate, and powerful in body part segmentation.
the application of a convolution neural network on face and license plate detection. in this paper, two detectors, one for face and the other for license plates, are proposed, both based on a modified convolutional neural network(cnn) verifier. in our proposed verifier, a single feature map and a fully connected mlp were trained by examples to classify the possible candidates. pyramid-based localization techniques were applied to fuse the candidates and to identify the regions of faces or license plates. in addition, geometrical rules filtered out false alarms in license plate detection. some experimental results are given to show the effectiveness of the approach. keywords: face detection, license plate detection, convolution neural network, feature map.
planar metric rectification by algebraically estimating the image of the absolute conic. a new metric rectification method for planar homography is proposed based on a closed form algebraic solution of the image of the absolute conic on the image plane.our solution allows shape measurement to be made directly on the image plane without explicitly computing the homography matrix or recoreringing the rectified image.we show that the invariance property of the relationship between the circular points and the absolute conic under projective transformation can effectively do planar metric rectification.in this approach, the image of the absolute conic is solved algebraically to achieve metric rectification based only on the vanishing line and the image of one arbitrary circle on the world plane extracted automatically from the image plane.the process of conic solving introduces no errors and the performance of the method is mainly dependent on the robustness of the straight line and ellipse fitting processes.the fitting scheme suggested in the paper is robust and give good results in most cases.
tooth contour extraction for matching dental radiographs. in dental biometrics [dental biometrics: human identification using dental radiographs] [matching of dental x-ray images for human identification], the contours of teeth in dental radiographs are utilized for human identification. however, in many images, the contours of teeth are fuzzy and only partially visible. to extract the contours from these images, we propose a method based on the active contour models [snakes: active contour models]. a new dynamic energy is proposed for the directional snake to discriminate boundaries of adjacent teeth. matching result shows the contours extracted with this method perform better than traditional methods.
robust nonlinear dimensionality reduction for manifold learning. this paper proposes an effective preprocessing procedure for current manifold learning algorithms, such as lle and isomap, in order to make the reconstruction more robust to noise and outliers. given a set of noisy data sampled from an underlying manifold, we first detect outliers by histogram analysis of the neighborhood distances of data points. the linear error-in-variables (eiv) model is then applied in each region to compute the locally smoothed values of data. finally a number of locally smoothed values of each sample are combined together to obtain the global estimate of its noise-free coordinates. the fusion process is weighted by the fitness of eiv model in each region to account for the variation of curvatures of the manifold. experimental results demonstrate that our preprocessing procedure enables the current manifold learning algorithms to achieve more robust and accurate reconstruction of nonlinear manifolds.
fault detection in distributed systems by representative subspace mapping. the high dimensionality of system observation, together with the frequent changes of system normal behavior resulting from workload variations, makes fault detection very difficult in distributed computing systems. this paper addresses these issues by proposing a novel statistical technique, the principal canonical correlation analysis (pcca), and applying it to monitor the system in a supervised manner. given a set of input variables u and system measurements x, pcca extracts a subspace x(1) from x that is not only highly correlated with the input u, but also a significant representative of the whole distribution of x. such property of pcca, which combines the strengths of both pca and cca, is beneficial to the fault detection task. experimental results from a real e-commerce system based on the multi-tiered j2ee architecture demonstrate the effectiveness of pcca.
albedo recovery using a photometric stereo approach. this paper describes a method for the estimation of surface reflectance values using a photometric stereo approach. evaluations show that surfaces rendered with reflectance values calculated by the proposed method have more realistic appearances than those with constant albedo.
illumination and expression invariant face recognition with one sample image. most face recognition approaches either assume constant lighting condition or standard facial expressions, thus cannot deal with both kinds of variations simultaneously. this problem becomes more serious in applications when only one sample images per class is available. in this paper, we present a linear pattern classification algorithm, adaptive principal component analysis (apca), which first applies pca to construct a subspace for image representation; then warps the subspace according to the within-class co-variance and between-class covariance of samples to improve class separability. this technique performed well under variations in lighting conditions. to produce insensitivity to expressions, we rotate the subspace before warping in order to enhance the representativeness of features. this method is evaluated on the asian face image database. experiments show that apca outperforms pca and other methods in terms of accuracy, robustness and generalization ability.
in this paper, an approach for deaf-people. this paper presents the design and implementation of a fingertip writing interface which recognizes the moving trajectory of the user's fingertip into alphabets and numerals. the processes are divided into tracking and recognition. for the fingertip tracking process, the interface employees techniques including background subtraction, skincolor modeling, finger extraction, fingertip positioning and kalman filter prediction. to recognize the fingertip trajectories, four types of features are defined for recognition with hidden markov models. according to our performance evaluation, the writing interface achieves an accuracy rate of 98% for fingertip tracking and reaches a recognition accuracy as high as 93% for alphabets and numerals, demonstrating its potential to serve as a feasible human-machine interface of natural modality.
probabilistic tracking with adaptive feature selection. we propose a color-based tracking framework that infers alternately an object's configuration and good color features via particle filtering. the tracker adaptively selects discriminative color features that well distinguish foregrounds from backgrounds. the effectiveness of a feature is weighted by the kullback-leibler observation model, which measures dissimilarities between the color histograms of foregrounds and backgrounds. experimental results show that the probabilistic tracker with adaptive feature selection is resilient to lighting changes and background distractions.
video scene extraction using mosaic technique. scene extraction is the first step toward semantic understanding of the video. this paper presents an effective approach to video scene extraction based on the analysis of background images. our approach exploits the fact that shots belonging to one particular scene often have similar background. although part of the video frame is covered by foreground objects, background scene still can be reconstructed by mosaic technique. the proposed scene extraction algorithm consists of two main components: the determination of shot similarity measure and shot grouping process. in our approach, several low-level visual features are integrated to compute the similarity measure between two shots. on the other hand, highlevel knowledge in cinematography is used to guide the shot grouping process. experimental results show that our approach is promising and outperforms some existing technique.
integration of gibbs prior models and deformable models for 3d medical image segmentation. this paper proposes a new methodology for 3d medical image segmentation based on the integration of 3d deformable and markov random field models. our method makes use of markov random field theory to build gibbs prior models for the 3d medical image with arbitrary initial parameters to estimate the organ boundary. then we use a 3d deformable model to fit the estimated boundary under the influence of gradient information in the initial 3d image and the balloon force. the result of the deformable model fit is used to update the gibbs prior model parameters, such as the gradient threshold of a boundary. based on the updated parameters we restart the gibbs prior models. by integrating these processes recursively we achieve an automated segmentation of the initial 3d images. our segmentation solution greatly reduces the time for 3d segmentation process and is capable of getting out of local minim. results of the method are presented for several examples, including som mri images with significant amount of noise.
a new off-line signature verification method based on graph. a graph matching approach to off-line signature verification is presented. each of the signature images being compared is represented as a point set, which includes the local extremas of various types along the signature contours. graph matching involves a deformation measure and a mapping function between point sets. multiresolution signature features, as computed by gradient, structural and concavity features, are used to measure local correspondence. deformation and similarity scores are combined to make the final decision. the method performs better than previous off-line methods and is comparable to that of on-line systems.
model based object recognition by robust information fusion. given a set of 3d model features and their 2d image, model based object recognition determines the correspondences between those features and hence computes the pose of the object. to achieve good recognition results, a novel approach based on robust information fusion is put forward in this paper. in this algorithm, the property of probabilistic peaking effect is employed to generate sets of hypothesized matches between model and image points. the correct hypotheses are obtained by searching for clusters among projections of predefined 3d reference points using the pose implied by each hypothesis. to assure the robustness of clustering, a new data fusion technique that is based on the nonparametric mode search method, mean shift, is proposed. the uncertainty information of the hypotheses is also incorporated into the fusion process to adaptively determine the bandwidth of the mean shift procedure. experimental results demonstrating the satisfactory performance of this algorithm are presented.
modification of the adaboost-based detector for partially occluded faces. while face detection seems a solved problem under general conditions, most state-of-the-art systems degrade rapidly when faces are partially occluded by other objects. this paper presents a solution to detect partially occluded faces by reasonably modifying the adaboost-based face detector. our basic idea is that the weak classifiers in the adaboost-based face detector, each corresponding to a haar-like feature, are inherently a patch-based model. therefore, one can divide the whole face region into multiple patches, and map those weak classifiers to the patches. the weak classifiers belonging to each patch are re-formed to be a new classifier to determine if it is a valid face patch-without occlusion. finally, we combine all of the valid face patches by assigning the patches with different weights to make the final decision whether the input subwindow is a face. the experimental results show that the proposed method is promising for the detection of occluded faces.
simultaneous segmentation and registration for functional mr images. a simultaneous segmentation and registration model is proposed for functional mr (fmr) image alignment that is significant for minimizing motion artifacts on fmri data analysis. due to t_2^* weighted signal loss and decreased resolution, in fmr images, the images can't be aligned reliably by only using image information. our approach uses the shape of a contour pre-segmented in a high resolution image to find the unknown contour in each of the time series images, and the spatial transform that maps the interface to the given contour. this is achieved by minimizing an energy functional depending on the information of the image gradient and the shape of interest, so that the boundary of the object can be captured either by higher gradient or by the prior knowledge of its shape. in the meantime, the registration is achieved by the transformation determined in shape matching. the model has been tested both on synthetic data and fmr brain image data. the experimental results showed the effectiveness of this model in feature determination and time series image registration. the existence of the solution to the proposed model is also discussed.
texture segmentation using independent component analysis of gabor features. this paper proposes a novel method for texture segmentation using independent component analysis (ica) of gabor features (called icag). it has three distinguished aspects. (1) gabor wavelets transformation first produces distinct textural features characterized by spatial locality, scale and orientation selectivity. (2) principal component analysis (pca) then reduces the dimensionality of these features and ica finally derives independent features for texture segmentation. (3) two different frameworks for ica are discussed. framework i regards pixels as random variables and represents them as a column vector by re-shaping all the transformed images row-by-row, while framework ii treats the statistical features, viz. the mean and standard deviation of image, as random variables. the statistical features of all the transformed images construct a column vector. comparative experiment results among icag, gabor wavelets and ica indicate that icag provides the best performance and framework ii is more efficient and applicable for texture segmentation.
isomap based on the image euclidean distance. scientists find that the human perception is based on the similarity on the manifold of data set. isometric feature mapping (isomap) is one of the representative techniques of manifold. it is intuitive, well understood and produces reasonable mapping results. however, if the input data for manifold learning are corrupted with noises, the isomap algorithm is topologically unstable. in this paper, we present an improved manifold learning method when the input data are images—the image euclidean distance based isomap (imisomap), in which we use a new distance for images called image euclidean distance (imed). experimental results demonstrate a consistent performance improvement of the algorithm imisomap over the traditional isomap based on euclidean distance.
blind image steganalysis based on statistical analysis of empirical matrix. in this paper, a novel steganalysis method based on statistical analysis of empirical matrix (em) is proposed to detect the presence of hidden message in an image. the projection histogram ..ph.. of em is used to extract features composed of two parts: the moments of ph and the moments of the characteristic function of ph. also, features extracted from prediction-error image [7] are included to enhance performance. svm is utilized as classifier. a test database is constructed, based on which a detailed test for different categories of features and a comparison with methods in prior arts are conducted. experiments show that the features we proposed are more effective than prior arts and our steganalysis method could blindly detect the presence of data hiding for various embedding schemes with high performance.
exploiting high dimensional video features using layered gaussian mixture models. analysis of video data usually requires training classifiers in high dimensional feature spaces. this paper proposes a layered gaussian mixture model (lgmm) to exploit high dimensional features for classifying various shots in video. lgmm decomposes a high dimensional feature space by building a pyramid structure and estimating the distribution of local partitions in each layer using gaussian mixtures from the bottom of the pyramid to the top. we reduce the dimension of features in each local region at a lower layer by projecting them onto the estimated gaussian components. these projected feature vectors are then used to estimate the gaussian mixture models at a upper layer. the final dimension of the feature is adjustable by choosing the number of gaussians at the top layer of the pyramid. we demonstrate the proposed method using motion features to classify video shots. the proposed method is independent from low level features and can be extended to other classification tasks.
a new adaptive diffusion equation for image noise removal and feature preservation. anisotropic diffusion can remove noise to some extent in image processing. however the contradiction between diffusion and preservation still exists. in this paper, a new nonlinear diffusion model for image noise removal and feature preservation is presented. this model treats inhomogeneity region and image feature adaptively by discontinuity measure and local gradient information. a well balance between diffusion and preservation is also made in this new diffusion method. experiments results show that the proposed method has high performance compared to other literature methods and is an ideal edge-preserving filtering method. in addition, we use block-based noise estimation to estimate deviation in diffusion equation.
inter-subspace distance: a new method for face recognition with multiple samples. in this paper, we develop a systematic method that can cope with multiple images simultaneously for face recognition. the proposed method, referred to as inter-subspace distance, employs the minimal distance between the two subspaces formed by training and test images, respectively. the advantages of our method are that it can use temporal information (image sequences) and multiple sampling (in scales or spatial positions) for face recognition. in addition, our method can ease the burdens of face detection by dealing with inaccuracies of positions and scales of the detected faces.
edge detection and texture segmentation based on independent component analysis. in this paper, we present a new feature extraction technique based on independent component analysis (ica). we use ica to learn the basis functions of natural images and then the basis functions are used as pattern templates for feature detections. the succesful applications of the proposed method to edge detection and texture segmentation are demonstrated.
deformable model based data compression for gesture recognition. we aim at recognizing a set of dance gestures from contemporary ballet. our input data are motion trajectories followed by the joints of a dancing body provided by a motion-capture system. it is obvious that direct use of the original signals is unreliable and expensive. therefore, we propose a suitable tool for nonuniform sub-sampling of spatio-temporal signals. the key of our approach is the use of a deformable model to provide a compact and efficient representation of motion trajectories.
a complementary ordering method for class imbalanced problem. we propose a method called asymmetric bagging with vector complementary ordering (abvco) to handle the class imbalanced problem. the proposed approach is not dependent on artificially generated data or re-weighted data. it can avoid the synthesis of classifiers that favor the majority class. the method is applied to multi-modal biometric authentication for further raising the fusion classifier performances.
periodic human motion description for sports video databases. many different visual features can be used for analysis and annotation of sports video material. here we present a periodic motion feature descriptor that can discriminate between different sports types that contain periodic motion. the experimental results, using video material from the 1992 barcelona olympic games, show that the proposed periodic motion descriptor can successfully classify four sports types: sprint, long-distance running, hurdling and canoeing.
bit-pairing codification for binary pattern projection system. in a previous work, we proposed a new binary-light projection mechanism that had a much reduced system size that made it particularly suitable for 3d shape inspection of semiconductor products. the inspection speed of the mechanism was governed by the number of required images which also equaled the number of shiftings of the grating. in this paper we address how inspection speed could be gained, i.e., how the number of required images could be reduced, by the incorporation of two neighboring bits in the codification of each scene element. we provide an optimal design of such a codification strategy. a solution to the shifting strategy optimization is also proposed that is applicable to any given binary patterns. theoretical analysis and real image experiments are presented to illustrate the workability of the solutions.
a trainable hierarchical hidden markov tree model for color image annotation. in this paper we consider how to annotate or label regions of grey-level or multispectral images based upon known labels and a set of interacting hierarchical doubly stochastic processes. the proposed model extends current work on the use of hierarchical markovian models for image processing using multiscale representations. in this paper we explore a new objective up-down algorithm whereby the spatio-spectral context of specific image region signatures are encoded via different types of trainable support kernels for the upward and downward operations.
a prototypes-embedded genetic k-means algorithm. this paper presents a genetic algorithm (ga) for kmeans clustering. instead of the widely applied stringof- group-numbers encoding, we encode the prototypes of the clusters into the chromosomes. the crossover operator is designed to exchange prototypes between two chromosomes. the one-step k-means algorithm is used as the mutation operator. hence, the proposed ga is called the prototypes-embedded genetic k-means algorithm (pgka). with the inherent evolution process of evolutionary algorithms, pgka has superior performance than the classical k-means algorithm, while comparing to other ga-based approaches, pgka is more efficient and suitable for large scale data sets.
texture classification using kernel independent component analysi. we propose a novel method, kernel independent component analysis (kica), for texture features extraction. the texture images are first mapped into a higher-dimensional implicit feature space. then a set of nonlinear basis functions are learned using kica. the feature vectors are obtained by projected the texture images onto the basis functions. comparison experiments between kica and the other two classic methods: gabor filters and ica, are performed. the results indicate that the kica is an efficient approach for texture classification.
fingerprint enhancement with dyadic scale-space. fingerprint enhancement is a critical step in fingerprint identification. most of the existing enhancement uses a set of contextual filters to enhance fingerprint. the main drawback of these methods is these contextual filters based on the local information of the fingerprint, such as ridge width, orientation, curvature et al. these information are unreliable in the areas corrupted by the noise. this paper introduces the scale space theory in the computer vision to enhance the fingerprint. in the enhancement process, decompose fingerprint into a series of images and organize the images by finer to coarser scheme. thus a globe and integrate interpretation is available and it enable us to get rid of the influence of noise to the largest extent. experiments show our algorithm is fast and has excellent performance.
multi-view sampling for relevance feedback in image retrieval. labelling is a boring task for users in relevance feedback. how to maximumly reduce the labelling is crucial for relevance feedback algorithms. in spirited by active learning and co-testing, we proposed a co-svm algorithm to improve the efficiency and effectiveness of selective sampling in image retrieval. in co-svm, color and texture are looked as sufficient and uncorrelated views of an image. svm classifier is learned in color and texture feature subspaces, respectively. then the two classifiers are used to classify the unlabelled data. these unlabelled samples that disagree in the two classifiers are chose to label. the experimental results show that the proposed algorithm is beneficial to image retrieval.
boosted gabor features applied to vehicle detection. robust vehicle detection is a challenging task given vehicles with different types, and sizes, and at different distances. this paper proposes a boosted gabor features (bgf) approach for vehicle detection. the two main conventional gabor filter design approaches are a filter bank design approach with fixed parameters even for different applications and a learning approach. in contrast, the parameters of our boosted gabor filters, learned from examples, differ from application to application. moreover, our boosted approach optimizes the filter parameters for every image sub-window, and the boosted filters have a large response for sub-windows containing a part of a vehicle resulting in a greatly improved performance in vehicle detection. our vehicle detection has two basic phases in which we build a multi-resolution hypothesis-validation structure. in the vehicle hypothesis generation phase, hypothesis lists are generated for three rois with different resolutions using horizontal and vertical edges ,and following that, a hypothesis list for the whole image is obtained by combining these three lists. in the subsequent hypothesis validation phase, we validate the vehicle hypothesis list by inputting the boosted gabor feature vector into the support vector machine. in the context of vehicle detection, the resulting system yields detection rates comparable to the best previous systems while achieving a 20 frames per second real-time performance on a pentium(r)4 cpu 2.4ghz.
perceptual distance normalization for appearance detection. in this paper we develop a novel contrast-invariant appearance detection model. the goal is to classify object-specific images (e.g. face images) from generic background patches. the novel contribution of this paper is the design of a perceptual distortion measure for comparing the appearance of an object to its reconstruction from the principal subspace. we demonstrate our approach on two different datasets: separating eyes from non-eyes and classifying faces from non-faces. on the eye database, for a true detection rate of 95% we demonstrate a nine-fold improvement in the false positive rates over a previously reported detection model [robust contrast-invariant eigendetection]. we also compare our detector model with a svm classifier.
finding region correspondences for wide baseline stereo. this study addresses the problem of finding correspondences for wide baseline stereo. texture has traditionally been utilised as a single-image cue for 3d shape reconstruction (shape-from-texture); at the same time, its role in multiview scene reconstruction has been very limited. in stereo image matching, repetitive patterns are usually considered as disturbing factor since they tend to produce multiple peaks of correlation, which results in matching ambiguity. we argue that presence and proper analysis of distinct, compact periodic texture areas can facilitate wide baseline matching by providing periodic distinguished regions (pdrs) that efficiently constrain the search for correspondences. we demonstrate how pdrs can be used to find a few initial correspondences in a wide baseline stereo pair and to establish precise correspondences for building the epipolar geometry. experimental results for various wide baseline stereo pairs are shown.
the trimmed iterative closest point algorithm. the problem of geometric alignment of two roughly preregistered, partially overlapping, rigid, noisy 3d point sets is considered. a new natural and simple, robustified extension of the popular iterative closest point (icp) algorithm [1] is presented, called the trimmed icp (tricp). the new algorithm is based on the consistent use of the least trimmed squares (lts) approach in all phases of the operation. convergence is proved and an efficient implementation is discussed. tricp is fast, applicable to overlaps under 50%, robust to erroneous measurements and shape defects, and has easy-to-set parameters. icp is a specialcase of tricp when the overlap parameter is 100%. results of testing the new algorithm are shown.
a rival penalized em algorithm towards maximizing weighted likelihood for density mixture clustering with automatic model selection. how to determine the number of clusters is an intractable problem in clustering analysis. in this paper, we propose a new learning paradigm named maximum weighted likelihood (mwl), in which the weights are designable. accordingly, we develop a novel rival penalized expectation-maximization (rpem) algorithm, whose intrinsic rival penalization mechanism enables the redundant densities in the mixture to be gradually faded out during the learning. hence, the rpem can automatically select an appropriate number of densities in density mixture clustering. the experiments have shown the promising results.
semantic retrieval by spatial relationships. a novel spatial representation of image objects is presented for efficient image retrieval based on spatial relationships. using our new representation, fast indexing and matching of images by spatial relationships can be accomplished. our approach takes care of the special requirements for content-based image retrieval (cbir) as compared to existing spatial representation schemes. experiments demonstrated the feasibility of semantic spatial retrieval using the proposed spatial representation in cbir.
does eigenpalm work? a system and evaluation perspective. recently, there are keen interests in eigenpalm, which, collectively, refers to those methods that extract palmprint features directly from the appearance by means of principal component analysis (pca) for (dis)similarity matching. encouraging results have been reported with the use of eigenpalm. however, we find a different story under a system and evaluation perspective. in this paper, we would like to introduce three issues that should be considered: the effects of templates from two different sessions, the effects of identical twins and the effects of unseen subjects. they are missing in the previous studies of eigenpalm.
multiple objects tracking with multiple hypotheses graph representation. we present a novel multi-object tracking algorithm based on multiple hypotheses about the trajectories of the objects. our work is inspired by reid's multiple hypothesis tracking algorithm which is an optimal solution to the motion correspondence that occurs in multi-object tracking. unfortunately, the exponential growth of the hypotheses tree precludes practical applications. to restrict this growth, many approximations relying on a series of clustering and pruning operations have been proposed. the decisions for these operations are based solely on previous observations and are not guided by observations in later frames. we show that due to multiple splits and merges, relying solely on previous observations to guide these operations may inadvertently eliminate the correct hypothesis. consequently, this leads to poor tracking performance. to overcome this problem, we determine the validity of a hypothesis by exploiting information in later frames and relating them to previous observations. experimental results demonstrate the robustness and efficiency of our approach.
classification of line and character pixels on raster maps using discrete cosine transformation coefficients and support vector machine. raster maps are widely available on the internet. valuable information such as street lines and labels, however, are all hidden in the raster format. to utilize the information, it is important to recognize the line and character pixels for further processing. this paper presents a novel algorithm using 2-d discrete cosine transformation (dct) coefficients and support vector machines (svm) to classify the pixels of lines and characters on raster maps. the experiment results show that our algorithm achieves 98% precision and 85% recall in classifying the line pixels and 83% precision and 96% recall in classifying the character pixels on a variety of raster map sources.
skin color detection in low bit-rate 3-d multiwavelet-based videos. there is a growing thrust of studies on exploring applications of multiwavelets in image compression, denoising and recognition. for compression, multiple scaling functions and multiple wavelets provide more flexible approximation of the original signal at high compression ratio than a comparable single scaling function and single wavelet, leading to potential improvement in detection of some features even in low bit-rate videos. this paper presents a study on detection of human skin colors in low bit-rate videos as a performance evaluation of low bit-rate videos encoded using spatio-temporal 3-d multiwavelets.
fingerprint representation using localized texture features. fingerprint representations can be broadly divided into three categories: image level, texture features and minu- tiae features. both image based and texture based repre- sentations require accurate alignment before comparison. this presents a problem since accurate registration of fin- gerprints is challenging. on the other hand, minutiae based matchers are invariant to changes in orientation and posi- tion, but completely ignore the rich visual content in the image. in this paper, we present a localized texture based representation scheme that relies solely on visual content for identification and at the same time does not require ab- solute alignment. we outline techniques to efficiently com- pute these features and also propose an algorithm to per- form identification based on these features. our experimen- tal evaluations over database of several sizes show that the proposed features are both accurate and scalable.
an embedded real-time vision system for 24-hour indoor/outdoor car-counting applications. we describe an embedded vision system, which integrates a web-cam quality cmos imaging chip with a risc processor, to perform real-time car-counting functions in the indoor and outdoor environment. the challenge of this application, especially for the outdoor environment, is to develop vision algorithms for day and night, and during the light-transition periods (i.e., dawn and dusk). the vision system also needs to accommodate a tremendous range of illumination change (from sunny summer to snowy winter). finally we report briefly the result of an outdoor system we deployed in germany since june 2003. the entire system consists of a network of 13 embedded vision systems covering a parking facility over 1 square kilometer. the vision-network has been in daily use for the employee parking guidance.
matching interest points using affine invariant concentric circles. we present a new method to perform reliable matching between different images. this method finds complete region correspondences between concentric circles and the corresponding projected ellipses centered on interest points. it matches interest points exploiting all the available luminance information in the regions under affine transformation. experiments have been conducted on many different data sets to compare our approach to two sift-based local descriptors. the results show the new method is more effective in natural scenes without distinctive texture patterns. it also offers increased robustness to partial visibility, object rotation in depth, and viewpoint angle change.
a time warping based approach for video copy detection. the proliferation of digital video urges the need of video copy detection for content and rights management. an efjcient video copy detection technique should be able to deal with spatiotemporal variations (e.g., changes in brightness or frame rates), and lower down the computation cost. m i l e most studies put more emphases on spatial variations, less effort is made for temporal variations and computation cost. to address the above issues, we propose a time warping based approach for video copy detection. a time warping matching algorithm is used to deal with video temporal variations. to reduce matching times, a fast pltering method to generate key parries and select candidate clips from video is presented. our experiments demonstrate promising results of the proposed approach.
a script matching algorithm for oriental characters on pdas. recently growth of pen-computers and personal digital assistants has made electronic ink a first-class object. one of the most important problems under this model is to search ink data at previously stored pen-strokes. in this paper we proposed and implemented a matching algorithm of write-dependant ink search for oriental characters, especially mixed korean with chinese characters. our algorithm is very simple guaranteeing the performance of the matching time for the mobile computer which has limitations of hardware. various experiments showed matching rate over 98% for only the korean scripts and 94% for the data mixed korean with chinese scripts.
extending dynamic range of two color images under different exposures. we present a method of extending the dynamic range of an picture with two different exposure images. since pictures under different exposure times show different scene dynamic ranges, if we make use of the visible information of each different exposure image, we can recover a high dynamic range image which contains what cannot be visualized by an auto-exposure time. in this method, we did not follow the ordinary fusion methods which were based on multi-layered or radiance map based approach of multiple images. instead, we used the filling method of undesirable regions of an auto-exposure picture, preserving its overall image quality. our filling method uses the gradient information of the visible regions and recovers the saturated regions by the energy minimization approach. the results show that our fusion method is simple and practical to make a hdr image, if we have two proper exposure images.
a novel virus infection clustering for flower images identification. computer-aided flower identification is a very useful tool for plant species identification aspect. in this paper, a study was made on a development of content based image retrieval system to characterize flower images efficiently. in this system, a novel virus infection clustering is proposed to cluster the image database to improve the searching efficiency. experimental results show that the developed system can yield promising results for flower image retrieval.
optimal global mosaic generation from retinal images. we present a method to construct a mosaic from multiple color and fluorescein retinal images. a set of images taken from different views at different times is difficult to register sequentially due to variations in color and intensity across images. we propose a method to register images globally in order to minimize the registration error and to find optimal registration pairs. the reference frame that gives the minimum registration error is found by the floyd- warshall's all-pairs shortest path algorithm, and all other images are registered to this reference frame using an affine transformation model. we present experimental results to validate the proposed method.
a noise robust front-end for speech recognition using hough transform and cumulative distribution mapping. this paper describes a novel and noise robust frontend that employs the use of hough transform for simultaneous frequency and temporal masking, together with cumulative distribution mapping of cepstral coefficients, for noisy speech recognition. recognition experiments on the aurora ii connected digits database have revealed that the proposed frontend achieves an average digit recognition accuracy of 83.67%. compared with the recognition results obtained by using the etsi standard mel-cepstral front-end, this accuracy represents a relative error rate reduction of around 58%.
face alignment using segmentation and a combined aam in a ptz camera. in this paper, we propose a novel framework for face alignment based on the active appearance model (aam) in surveillance systems with pan-tilt-zoom (ptz) cameras. the aam converges poorly in face images which are affected by illumination factors, cluttered backgrounds and status of the camera. to search for robust face model parameters, we propose a robust aam fitting method based on segmenting faces and combining person-specific and generic models to achieve accurate face alignment. we segment faces using histogram back-projection and a skin color histogram, which is updated using a skin mask extracted by the aam. for robust face recognition, we combined generic and person-specific models with a slight reduction in processing time. the extracted aam parameters are as accurate as those when using the person-specific model and can be used as features for face recognition. empirical experiments show that our proposed method extracts very accurate face parameters and is not sensitive to initial shapes.
feature extraction for bank note classification using wavelet transform. in this paper, we investigate an approach to feature extraction for bank note classification by exploiting the potential of wavelet transform. in the proposed method, high spatial frequency coefficients taken from the wavelet domain are examined to extract features. we first perform edge detection on bill images to facilitate the wavelet feature extraction. the construction of feature vectors is then conducted by thresholding and counting of wavelet coefficients. the proposed feature extraction method can be applied to classifying any kind of bank note. however, in this paper we examine korean won bills of 1000, 5000 and 10000 won types. experimental results with a set of 10,800 bill images show that the proposed feature extraction method provides a correct classification rate of 99% even by using the euclidean minimum distance matching as classifier.
a model-based approach for rigid object recognition. most object recognition systems require large databases of real images for classifier training. to collect real images for this purpose is a difficult and expensive process. this paper introduces a unified framework based on the creation and use of synthetic images for training various classifiers to achieve recognition of real-world objects. a 3d model of the object (i.e. trolley in this case) is constructed from a minimum of two photographs. the constructed 3d model is used to automatically generate the relevant synthetic images that are subsequently used to train the adaboost and support vector machine-based recognition systems. experimental results obtained are very encouraging suggesting that synthetically generated images generated by our approach can augment the real training samples used in current recognition systems.
the generalized condensed nearest neighbor rule as a data reduction method. in this paper, we propose a new data reduction algorithm that iteratively selects some samples and ignores others that can be absorbed, or represented, by those selected. this algorithm differs from the condensed nearest neighbor (cnn) rule in its employment of a strong absorption criterion, in contrast to the weak criterion employed by cnn; hence, it is called the generalized cnn (gcnn) algorithm. the new criterion allows gcnn to incorporate cnn as a special case, and can achieve consistency, or asymptotic bayes-risk efficiency, under certain conditions. gcnn, moreover, can yield significantly better accuracy than other instance- based data reduction methods. we demonstrate the last claim through experiments on five datasets, some of which contain a very large number of samples.
iris recognition with multi-scale edge-type matching. in this paper, we propose a novel descriptor which characterizes an iris pattern with multi-scale step/ridge edgetype (et) maps. the et maps are determined with the derivative of gaussian (dog) and the laplacian of gaussian (log) filters. there are two major advantages of our approach. first, both the feature extraction and the pattern classification are simple and efficient. the iris pattern classification is accomplished by et matching. the matching of each et flag can be regarded as a weak classifier and the final decision is based on the vote of each weak classifier. second, the number of free filter parameters is only three, and hence they can be easily determined. furthermore, we propose a method for designing the parameters of the filters with the genetic algorithm. the experimental results show that our approach can achieve a recognition rate of 99.98% which is comparable to that of the gabor filter approach.
boosting and structure learning in dynamic bayesian networks for audio-visual speaker detection. bayesian networks are an attractive modeling tool for human sensing, as they combine an intuitive graphical representation with efficient algorithms for inference and learning. earlier work has demonstrated that boosted parameter learning could be used to improve the performance of bayesian network classifiers for complex multi-modal inference problems such as speaker detection. in speaker detection, the goal is to use video and audio cues to infer when a person is speaking to a user interface. in this paper we introduce a new boosted structure learning algorithm based on adaboost. given labeled data, our algorithm modifiesboth the network structure and parameters so as to improve classification accuracy. we compare its performance to both standard structure learning and boosted parameterlearning on a fixed structure. we present results for speaker detection and for the uci "chess" dataset.
note on feature selection for polyp detection in ct colonography. in this paper we describe a computer aided detection (cad) algorithm for robust detection of polyps in computed tomography (ct) colonography. the devised algorithm identifies suspicious polyp candidate surfaces using the surface normal intersection, hough transform, 3d histogram analysis, region growing and a convexity test. from these detected surfaces we extract statistical and morphological features in order to evaluate if the surface in question is a polyp or fold. in order to devise the optimal classification scheme the performance of two different classifiers are evaluated when the algorithm is applied to synthetic and real patient data. the experimental results indicate that the overall polyp detection performance shows sensitivity higher than 92% for polyps larger than 5mm with an average of 4.7 to 6.0 false positives per dataset.
epipolar geometry estimation via ransac benefits from the oriented epipolar constraint. the efficiency of epipolar geometry estimation by ransac is improved by exploiting the oriented epipolar constraint. performance evaluation shows that the enhancement brings up to a two-fold speed-up. the orientation test is simple to implement, is universally applicable and takes negligible fraction of time compared with epipolar geometry computation.
physics-based extraction of intrinsic images from a single image. a technique for extracting intrinsic images, including the reflectance and illumination images, from a single color image is presented. the technique first convolves the input image with a prescribed set of derivative filters. the pixels of filtered images are then classified into reflectance-related or illumination-related based on a set of chromatic characteristics of pixels calculated from the input image. chromatic characteristics of pixels are defined by a photometric reflectance model based on the kubelka-munk color theory. from the classification results of the filtered images, the intrinsic images of the input image can be computed. real images have been utilized in our experiments. the results have indicated that the proposed technique can effectively extract the intrinsic images from a single image.
improvement in range segmentation parameters tuning. a great effort has been done during last years to improve range image segmentation results. the efficacy of the algorithms is affected by the parameters tuning.in this work two well-known search techniques have been applied to this task: genetic algorithms and simulated annealing. these techniques are adopted in cascade: the former to obtain a rough seed point set and the latter to have a more precise refinement of suitable solutions.we addressed our efforts towards the range segmenter proposed by the university of bern, that seems to be the best in term of versatility, being able to segment planar and curved surfaces, and in term of speed and quality of the performed segmentations.
ontodoc: an ontology-based query system for digital libraries. the decreasing cost and the increasing availability of new technologies is enabling people to create their own digital libraries. one of the main topic in personal digital libraries is allowing people to select interesting information among all the different digital formats available today (pdf, html, tiff, etc.). moreover the increasing availability of these on-line libraries, as well as the advent of the so called semantic web [weaving the web], is raising the demand for converting paper documents into digital, possibly semantically annotated, documents. these motivations drove us to design a new system which could enable the user to interact and query documents independently from the digital formats in which they are represented. in order to achieve this independence from the format we consider all the digital documents contained in a digital library as images. our system tries to automatically detect the layout of the digital documents and recognize the geometric regions of interest. all the extracted information is then encoded with respect to a reference ontology, so that the user can query his digital library by typing free text or browsing the ontology.
contour features for colposcopic image classification by artificial neural networks. this article presents colposcopic image classification based on contour parameters used in a comparison study of different artificial neural networks and the k-nearest neighbors reference method. in this study, significant image data bases are used (283 samples) from which a set of original parameters is extracted to characterize the attribute of contour. more precisely, wequantify the notion of sharp contours vs blurred contours in computing spatial parameters based on the number of small regions near boundaries of objects and frequency parameters based on power spectrum of lines cutting these boundaries. experimental results show thefeasibility of this study and the efficiency of the set of parameters since 95.8% of contour image set has been correctly classified.
feature fusion for image texture segmentation. a design-based method to fuse gabor filter and grey level co-occurrence probability (glcp) features for improved texture recognition is presented. feature space separability and unsupervised image segmentation are used for testing. the fused features are robust with respect to the curse of dimensionality and additive noise. feature reduction methods are typically detrimental to the segmentation performance. overall, the fused features are a definite improvement over non-fused features and are advocated in texture analysis applications.
texture segmentation comparison using grey level co-occurrence probabilities and markov random fields. the discrimination ability of texture features derived from gaussian markov random fields (gmrfs) and grey level co-occurrence probabilities (glcps) are compared and contrasted. more specifically, the role of window size in feature consistency and separability as well as the role of multiple textures within a window are investigated. glcps are demonstrated to have improved discrimination ability relative to mrfs with decreasing window size, an important concept when performing image segmentation. on the other hand, glcps are more sensitive to texture boundary confusion than gmrfs.
visually significant dynamics for watershed segmentation. the watershed transform is a powerful tool for segmentation once we can deal with oversegmentation. to solve the oversegmentation problem, hierarchical approaches are considered in order to retain the most significant regions of the image at different scales. the dynamics of the regional minima have been used to build this hierarchy. in this paper we present a new measure for computing the dynamics of the minima based on human perception of shapes. the described technique solves the major drawbacks of the hierarchical segmentations based on contrast dynamics or volume dynamics.
handwritten syriac character recognition using order structure invariance. this paper demonstrates how order structure invariance may be used for matching handwritten characters in which non-rigid deformation is tolerated and a training set is not required. we make two contributions. first we show how how to define and use order structure invariants together with local object features. second, we show how recognition by alignment can be accomplished on a sparse set of points by matching order structure invariants. we evaluate the method on the problem of recognising handwritten syriac characters obtained from historical documents. experiments indicate that the method tolerates the variations found in real handwriting while having high discrimination power. the method is potentially applicable to cursive scripts similar to syriac such as aramaic and arabic.
a systematic design procedure for scalable near-circular laplacian of gaussian operators. in low-level image processing tasks, the circularity of an operator has been shown to be an important factor affecting its accuracy as circular differential edge operators are effective in minimising the angular error in the estimation of image gradient direction. we present a general approach to the computation of scalable near-circular low-level laplacian image processing operators that is based on the finite element method. we use gaussian basis functions, together with a virtual finite element mesh, to illustrate the design of operators that are scalable to near-circular neighbourhoods through the use of an explicit scale parameter. the general design technique may be applied to a range of operators. here we illustrate the approach by discussing the implementation of a laplacian operator, and we evaluate our approach by presenting comparative results with the laplacian of gaussian operators.
relaxation labeling processes for protein secondary structure prediction. the prediction of protein secondary structure is a classical problem in bioinformatics, and in the past few years several machine learning techniques have been proposed to attack it. from an abstract pattern recognition viewpoint, the problem can be formulated as a (continuous) consistent labeling problem, whereby one has to assign symbolic labels to a set of objects by taking into account potential constraints between nearby objects. motivated by this observation, in this paper we propose a new approach to the problem based on (optimally trained) relaxation labeling algorithms, a well-known class of iterative procedures that aim at reducing labeling ambiguities and achieving global consistency through a parallel exploitation of local information. preliminary experiments performed on standard benchmark data confirm the effectiveness of the approach as compared to standard state-of-the-art machine learning predictors.
vessel segmentation in 2d-projection images using a supervised linear hysteresis classifier. 2d projection imaging is a widely used procedure for vessel visualization. for the subsequent analysis of the vasculature, precise measurements of e.g. vessel area, vessel length or the number of vessel segments are needed. to achieve these goals vessel enhancement and segmentation are required. while there are already many vasculature specific vessel segmentation algorithms, we describe in this contribution a more general supervised segmentation method which includes a feature extraction step followed by feature selection and segmentation based on the hysteresis classification paradigm. the method was tested on retina photographies. the rates of false positives and correct classifications were comparable with dedicated methods on similar data sets while it needed less time for both training and providing a segmentation result.
shape metamorphism using p-laplacian equation. we present a new approach for shape metamorphism, which is a process of gradually changing a source shape (known) through intermediate shapes (unknown) into a target shape (known).the problem, when represented with implicit scalar function, is under-constrained, and regularization is needed.using the p-laplacian equation (ple), we generalize a series of regularization terms based on the gradient of the implicit function, and we show that the present methods lack additional constraints for a more stable solution. the novelty of our approach is in the deployment of a new regularization term when p ¿ ¿ which leads to the infinite laplacian equation (ile).we show that ile minimizes the supremum of the gradient and prove that it is optimal for metamorphism since intermediate solutions are equally distributed along their normal direction.application of the proposed algorithm for 2d and 3d objects are demonstrated.
transformation invariance in hand shape recognition. in hand shape recognition, transformation invariance is key for successful recognition. we propose a system that is invariant to small scale, translation and shape variations. this is achieved by using a-priori knowledge to create a transformation subspace for each hand shape. transformation subspaces are created by performing principal component analysis (pca) on images produced using computer animation. a method to increase the efficiency of the system is outlined. this is achieved using a technique of grouping subspaces based on their origin and then organising them into a hierarchical decision tree. we compare the accuracy of this technique with that of the tangent distance technique and display the results.
a novel two-layer pca/mda scheme for hand posture recognition. principle component analysis (pca) and multiple discriminant analysis (mda) have long been used for the appearance-based hand posture recognition. in this paper, we propose a novel pca/mda scheme for hand posture recognition. unlike other pca/mda schemes, the pca layer acts as a crude classification. since posture alone cannot provide sufficient discriminating information, each input pattern will be given a likelihood of being in the nodes of pca layers, instead of a strict division. based on the expectation-maximization (em) algorithm, we introduce three methods to estimate the parameters for this crude classification during training. the experiments on a 110-sign vocabulary show a significant improvement compared with the global pca/mda.
a new method to compute the distortion vector field from two images. in this paper, we present a new method to compute the distortion vector field from two images. the aim of this study is to characterize the distortion between to images. several methods are based on optical flow techniques. however they are sensitive to image noise and grey-levelvariations between the two images. our method is based on distance transforms. images must be passed over twice before computing the distance transform and the distortion vector field simultaneously. pixels are characterized by the displacement from the nearest feature element (surface for grey-level images). 3x3x3 chamfer masks are used for grey-level images. the relative weights of spatial versus grey-level displacements are considered. experimental resultsare analyzed for both synthetic and natural images.
selecting canonical views for view-based 3-d object recognition. given a collection of sets of 2-d views of 3-d objects and a similarity measure between them, we present a method for summarizing the sets using a small subset called a bounded canonical set (bcs), whose members best represent the members of the original set. this means that members of the bcs are as dissimilar from each other as possible, while at the same time being as similar as possible to the non-bcs members. this paper will extend our earlier work on computing canonical sets [approximation of canonical sets and their application to 2d view simplification] in several ways: by omitting the need for a multi-objective optimization, by allowing the imposition of cardinality constraints, and by introducing a total similarity function. we evaluate the applicability of bcs to view selection in a view-based object recognition environment.
dissimilarity measures in color spaces. a problem of both theoretical and practical importance in image processing is to compare two color images, taking into account the eventual diversities due to translation, or color variations. the aim of this paper is to study the behavior of dissimilarity measures in different color spaces. five color spaces (rgb, hsi, hsv, cielab, cie-luv) are studied. properties of the dissimilarity measures are compared in terms of sensitivity to radiometric variations, spatial shifts and shape distortions. we compare the results with those obtained by subjective testing.
fast extraction of tubular and tree 3d surfaces with front propagation methods. we present a new fast approach for surface segmentation of thin structures, like vessels and vascular trees, based on fast marching and level sets methods. fast marching allows segmentation of tubular structures inflating a "long balloon" from a user given single point. however, when the tubular shape is rather long, the front propagation may blow up through the boundary of the desired shape close to the starting point. our contribution is focused on a way to go on front propagation only on the actually moving front and freezing other points. we demonstrate the ability to build a fast and accurate segmentation for those tubular and tree structures. we also develop a useful stopping criterion for the causal front propagation. we illustrate our algorithms by applications on the segmentation of vessels in 3d medical images.
homotopy-based estimation of depth cues in spatial domain. this paper presents a homotopy-based algorithm for a cooperative and simultaneous estimation of defocus blur and spatial shifts (2d motion, stereo disparities and/or zooming disparities) in the spatial domain. these cues are estimated from two images of the same scene acquired by a camera evolving in time and/or space and for which the intrinsic parameters are known. we show that these depth cues can be directly computed by resolving a system of equations is embedded in a family of systems using a homotopy method. the results confirm that the use of homotopies reduces approximation errors and thus leads to a denser and more accurate estimation of depth cues.
detecting rotational symmetry under affine projection. a new method is presented for detecting planar rotational symmetry under affine projection. the method can deal with partial occlusion and is able to detect multiple rotationally symmetric surfaces in complex backgrounds. the order of rotational symmetry can be estimated, and if it is greater than two, the tilt and orientation of the rotationally symmetric surface can be found and the symmetric region segmented. local features robust to local affine distortion are matched to obtain pairs of features. each feature pair hypothesises a set of centres of rotation for different tilts and orientations and the centres of rotation that are close to each other are grouped together to find the dominant rotational symmetries in the image. the method is posed independently of a specific feature detector and descriptor. results are presented on natural images.
classification error rate for quantitative evaluation of content-based image retrieval systems. a major problem in the field of content-based image retrieval is the lack of a common performance measure which allows the researcher to compare different image retrieval systems in a quantitative and objective manner. we analyze different proposed performance evaluation measures, select an appropriate one, and give quantitative results for four different, freely available image retrieval tasks using combinations of features. this work gives a concrete starting point for the comparison of content-based image retrieval systems. an appropriate performance measure and a set of databases are proposed and results for different retrieval methods are given.
automatic visual recognition of armed robbery. we propose a method by which to analyze silhouettes and recognize a classic holdup position of armed robbery. in such a situation, one actor levels his or her arm while another actor raises his or her arm(s) into the air. the core of this algorithm is skeleton analysis. we attempt recognition by fir st segmenting the skeleton of the silhouette into separate pieces of the body, then identifying the positions of the arms. we show that our algorithm correctly utilizes skeletons to identify parts of the human body and recognize these holdup positions.
analysis of abnormality in endoscopic images using combined hsi color space and watershed segmentation. in this paper, a method for detecting possible presence of abnormality in the endoscopic images is presented. the pre-processed endoscopic color images are segmented in the hsi color space. the pixels in the input color image corresponding to the segmented image are extracted for further processing. this image is smoothened using average filter and converted into grayscale image. its inverse transform is obtained for further processing and extended minima is imposed on the processed image using morphological reconstruction. then the morphological watershed segmentation is carried out on this image and the number of regions is counted and is compared with the threshold value. if the number of regions is more than the threshold value, then the output image is an indicative of possible presence of abnormality in the image.
on the performance of wavelets for handwritten numerals recognition. this paper validates a recognition system using bi-dimensional wavelet transforms as feature extractor and investigates the relevance of each subband image in the recognition process. an experiment to verify the efficiency of the wavelets was performed omitting the feature extraction step. results show that information about the relevant image features are evenly distributed in all subband images of wavelet coefficients and that wavelets are promising feature extractors. numerals from the nist database were used for evaluation of the systems tested.
skew detection in binary image documents based on image dilation and region labeling approach. in this paper we propose a new and efficient method for estimation of skew angle in a binary document image, based on image dilation and region labeling technique. the input document is dilated by using structuring element as line whose length is fixed experimentally and the region labeling technique is applied using depth first search. orientation angle is calculated for all the labeled regions, the average of all orientation angles is considered as the skew angle of the document. the experimental results show that better accuracy of estimation could be achieved using this approach since it is based on orientation angles of all the text lines of the underlying document and is the minimum variance unbiased estimator of the true skew angle. the novelty of the proposed method is that, it is robust for machine printed document of any size/font, multi-column layouts and documents containing graphics, pictures, charts, tables etc.
diagnosis and treatment of film tear in degraded archived media. a common form of degradation in archived film is film tear. this is caused by the physical ripping of the film. tear causes displacement of a region of the degraded frame and the loss of image data. as of yet no method of automatically treating film tear has been proposed. this paper outlines an algorithm to automatically detect and restore torn frames. tear detection is facilitated by the presence of a large edge feature, unlikely to be caused by other forms of degradation, in the torn frame. restoration is achieved by estimating the regional displacement and recovering missing image data.
script identification based on morphological reconstruction in document images. in this paper, the study of script identification based on morphological reconstruction for printed document images is carried out. the system is developed by using 609-scanned document images representing english, hindi, kannada, and urdu scripts. the system developed includes a feature extractor and a classifier. the feature extractor consists of two stages. in the first stage, the morphological erosion and opening by reconstruction is carried out on a document image in horizontal, vertical, right and left diagonal directions using the line structuring element. the length of the structuring element is fixed, based on the average height of all the connected components of an image. in the next stage, average pixel distribution is found in these resulting images. a nearest neighbor analysis is used to classify the new documents. accuracy of classification averaged 97% across the four scripts. the method shows robustness with respect to noise, font sizes and styles.
image segmentation through energy minimization based subspace fusion. in this paper we present an image segmentation technique that fuses contributions from multiple feature subspaces using an energy minimization approach. for each subspace, we compute a per-pixel quality measure and perform a partitioning through the standard normalized cut algorithm [normalized cuts and image segmentation]. to fuse the subspaces into a final segmentation, we compute a subspace label for every pixel. the labeling is computed through the graph-cut energy minimization framework proposed by [fast approximate energy minimization via graph cuts]. finally, we combine the initial subspace segmentation with the subspace labels obtained from the energy minimization to yield the final segmentation. we have implemented the algorithm and provide results for both synthetic and real images.
automatic adjustment of discriminant adaptive nearest neighbor. k-nearest neighbors relies on the definition of a global metric. in contrast, discriminant adaptive nearest neighbor (dann) computes a different metric at each query point based on a local linear discriminant analysis. in this paper, we propose a technique to automatically adjust the hyper-parameters in dann by the optimization of two quality criteria. the first one measures the quality of discrimination, while the second one maximizes the local class homogeneity. we use a bayesian formulation to prevent overfitting.
video motion estimation using prediction based hybrid approach. motion estimation is important for compression of video sequences. in this paper a new block motion estimation algorithm proposed. in the proposed method, the motion vector of previous frame are used to predict the initial motion vector and the search direction. the extent of search region is determined by predicted motion vector and motion vectors of four casual neighbours in the current frame. results shows significant speed-up compared to existing ones.
speech driven facial animation using a hidden markov coarticulation model. we present a hierarchical image based facial model which is driven from speech. it incorporates a novel modelling and synthesis algorithm for learning and producing coarticulated mouth animation we demonstrate using the hierarchical model how animation of the entire face may be created solely from animations of the mouth and how colour may be reincorporated and reproduced compactly without explicitly being modelled. we then consider and evaluate methods of merging animations from several different facial areas for delivery of output.
hierarchical, generic to specific multi-class object recognition. early vision systems could perform specific object recognition reasonably well but did not fare as well on identifying natural object classes. recent advances have led to systems that can learn a representation for different object classes and achieve good generic object class recognition. however, these systems are generally unable to perform the fine distinctions required for specific object identification. it seems that the two approaches are in contrast with each other. we propose a system that addresses the problems of generic class recognition as well as specific object recognition in the same framework. our system also possesses the property of graceful degradation, i.e., if it is unable to recognize an object as a dog, it recognizes it at least as a quadruped and so on. we automatically learn a hierarchy of the classes from the training data, progressing from the most generic class labels to the most specific object labels. this hierarchy is used during recognition. one important benefit of the hierarchical organization of the classes is that the number of comparisons performed for every input does not increase linearly with the number of classes added.
kernel procrustes. in this work we introduce a new methodology to build a kernel matrix from a collection of kernels. the key idea is to build an unique kernel that eliminates spurious differences between kernels. we propose a method based on the procrustes problems that uses the alternating projections method to minimize a certain error measure. the resulting kernel will be used for classification purposes using support vector machines (svms). the proposed method has been successfully evaluated against alternative kernel combination techniques.
orientation difference statistics for texture description. this paper presents a new approach for the description of directional textures based on the study of their orientation and coherence fields. we apply the feature-based interaction maps to the characterization of an orientation field. the features are extracted from orientation spatial difference histograms. the representation of a feature, as a function of the spacing vector used to compute the spatial statistics, yields a 2-d interaction map which can be used to assess the structural layout of texture. orientation-based interaction maps are exercised on original and distorted brodatz textures. the results show the relevance and the robustness of the approach for the description of directional textures.
onset detection through maximal redundancy detection. we propose a criterion, called maximal redundancy', for onset detection in time series. the concept redundancy is adopted from information theory and indicates how well a signal locally can be explained by an underlying model. it is shown that a local maximum in the redundancy is a good indicator for an onset. it is proven that 'maximal redundancy' detection is a statistical asymptotically optimal detector for ar processes. it also accounts for potentially non-gaussian time series and non- gaussian innovations in the ar processes. several applications are shown where the new criterion has been successfully applied.
spectral characterization of orientation data along curvilinear structures. this paper lies within the scope of texture analysis. we focus on anisotropic textures and propose an approach to measure the ripple of texture patterns. it assumes that the patterns are represented by some characteristic curves called generatrices (i.e. edges, level curves). two steps are involved. the first one deals with the estimation of the orientation along the generatrices. the second step consists in computing the power spectrum of the generatrix orientation. the global texture ripple is captured by the ripple spectrum which is computed by cumulating the orientation spectra of all individual generatrix. the approach is exercised on synthetic textures and on composite material images.
a 'no panacea theorem' for multiple classifier combination. we introduce the 'no panacea theorem' for classifier combination in the two-classifier, two-class case. it states that if the combination function is continuous and diverse, there exists a situation in which the combination algorithm will always give very bad performance. thus, there is no optimal algorithm, suitable in all situations. from this theorem, we see that the probability density functions (pdf's) play an important role in the performance of combination algorithms, so studying the pdf's becomes the first step in finding a good algorithm.
towards shape from shading under realistic photographic conditions. this paper describes a new modeling of the shape from shading problem taking perspective projection into account, and proposes a method of resolution for the new equation. an application is proposed, which consists in correcting the defects of photographs of skew i.e., non flat, documents.
a global solution to the sfs problem using b-spline surface and simulated annealing. this paper restates the shape from shading problem regarding both surface modeling and optimization. we combine the use of a b-spline as 3d model for the scene surface and the use of stochastic optimization, through simulated annealing. the proposed method overcomes successfully the main difficulties usually encountered in shape from shading. experiments are presented on both synthetic and real images.
did the great masters use optical projections while painting? perspective comparison of paintings and photographs of renaissance chandeliers. recently it has been claimed that as early as 1420 some european artists constructed their paintings by optically projecting images onto their supports (canvas, oak panel, etc.) and then tracing or painting over these projections. because projected images obey the laws of perspective, a powerful test of this claim centers on analyzing the geometric accuracy of key renaissance paintings. this paper investigates new techniques for analyzing the perspective accuracy of paintings. notably, we focus on a portion of a painting central to the debate of the theory: the chandelier in jan van eyck's "portrait of arnolfini and his wife." despite the high level of visual realism of the painting, the technique proposed here highlights large geometric inaccuracies that are very hard to explain as arising from the optical projection route. the contribution of this paper is two fold: i) we present a projective geometry-based technique for detecting and measuring geometric inaccuracies in paintings, and ii) we demonstrate that in the arnolfini portrait the source of those inaccuracies lies in the imaging process, as opposed to the manufacturing of the actual chandelier. the results presented in this paper cast serious doubts on the validity of the claim that optical tools were employed in painting the arnolfini portrait.
on-line adaptive background modelling for audio surveillance. in this paper, we investigate the problem of automatic audio surveillance. this aspect of the surveillance, which extends the more investigated area of video surveillance, can be very informative to solve many problems in real situations. similarly to video surveillance, also in this case it is necessary to build a background (bg) model, so that it is immediate to discover foreground (fg) events. to this end, we first introduce the concepts of audio bg and fg in an automated surveillance scenario. subsequently, we propose a novel audio bg system able to build in real time an adaptive model of the audio scene bg, and to promptly detect unexpected fg auditory events. the method is based on the probabilistic modelling of the audio data stream using separate sets of adaptive gaussian mixture models, working on the audio frequency spectrum. this approach is also characterized by the use of only one microphone and on-line functioning, so that it can be directly used in real situations, also to support a video surveillance system. preliminary results show the effectiveness of the approach to discover different fg audio situations.
adaptive feature integration for segmentation of 3d data by unsupervised density estimation. in this paper, a novel unsupervised approach for the segmentation of unorganized 3d points sets is proposed. the method derives by the mean shift clustering paradigm devoted to separate the modes of a multimodal density by using a kernel-based technique. here, the attention is focused on the selection of the kernel bandwidth which typically strongly affects the level of accuracy of the segmentation results. in particular, a set of geometric features is computed from each 3d point of the given data. this set is projected onto a number of independent sub-spaces, each one associated to a different estimated feature, and overall forming a joint multidimensional (feature) space. in this space, we propose a method for selecting the best multidimensional kernel bandwidth in an automatic fashion, based on stability criteria. the final kernel considers each sub-space in an adaptive way in relation to the discrimination power of each feature, leading to accurate results when dealing with different types of 3d data.
an interactive trajectory synthesizer to study outlier patterns in handwriting recognition and signature verification. a software tool has been developed to simulate complex pen tip trajectories and their corresponding velocity profiles based on the kinematic theory of rapid human movements and its lognormal model. the set of equations used to generate the various signals is shortly introduced. the application interface and the functionalities of the main modules are schematized and described. finally typical simulations results are presented in the context of an interactive comparative analysis of on-line signature data.
relightning of facial video. we present a novel method to relight video sequences given known surface shape and illumanation. the method preserves fine visual details.. it requires single videoframes, approximate 3d shape and standard studio illumanation only, making it applicable in studio production. the technique is demonstrated for relightning video sequences of faces.
adaptative markov random fields for omnidirectional vision. images obtained with catadioptric sensors contain significant deformations which prevent the direct use of classical image treatments. thus, markov random fields (mrf) whose usefulness is now obvious for projective image processing, can not be used directly on catadioptric images because of the inadequacy of the neighborhood. in this paper, we propose to define a new neighborhood for mrf by using the equivalence theorem developed for central catadioptric sensors. we show the importance of this adaptation for a motion detection application.
spatial color component matching of images. color and color neighborhood statistics have been used extensively in image matching and retrieval. however, the effective incorporation of color layout information remains a challenging issue. in this paper we present a novel method for color layout based image matching called spatial color component matching (sccm). first perceptually dominant colors are extracted from an image and are back-projected to segment the image into various areas. then, each dominant color area, depending on its size, is segmented into a number of spatial units using a multilevel graph partitioning algorithm. each unit is described in terms of its colorand a set of spatial attributes to form a spatial color component (scc). all scc's form a list that summarizes the color layout information in an image. the distance between two images is then defined by the minimum distance mapping between the two corresponding scc lists. the algorithm has been evaluated using an image database of wall paper patterns and another database of natural images. it has been judged by human subjects to be highly effective in both cases.
building the topological tree by recursive fcm color clustering. in this paper we define a topological tree (tt) as a knowledge representation method that aims to describe important visual and spatial features of image regions, namely the color similarity, the inclusion and the spatial adjacency. the topological tree exhibits some interesting properties that can be exploited to extract knowledge from images for information retrieval, image understanding and diagnosis purposes. examples of applications in dermatology are described. the tt can be constructed after segmentation, by computing the spatial relationships of regions or can be generated directly during the segmentation: to this aim we present a novel recursive fuzzy c-means (fcm) clustering algorithm based on the principal component analysis of the color space. the recursive fcm proves to be effective for underlining the adjacency and inclusion property of regions.
unsupervised image segmentation using a simple mrf model with a new implementation scheme. a markov random field (mrf) model with a new implementation scheme is proposed for unsupervised image segmentation based on image features. the traditional two-component mrf model for segmentation requires training data to estimate necessary model parameters and is thus unsuitable for unsupervised segmentation. the new mrf model overcomes this problem by introducing a function-based weighting parameter between the two components. this new mrf model is able to automatically estimate model parameters and is demonstrated to produce more accurate image segmentations than the traditional model using a variety of imagery.
probabilistic people tracking for occlusion handling. this work presents a novel people tracking approach, able to cope with frequent shape changes and large occlusions. in particular, the tracks are described by means of probabilistic masks and appearance models. occlusions due to other tracks or due to background objects and false occlusions are discriminated. the tracking system is general enough to be applied with any motion segmentation module, it can track people interacting each other and it maintains the pixel assignment to track even with large occlusions. at the same time, the update model is very reactive, so as to cope with sudden body motion and silhouette's shape changes. due to its robustness, it has been used in many experiments of people behavior control in indoor situations.
probability table compression using distributional clustering for scanning n-tuple classifiers. a method for compressing tables of probability distributions using distributional clustering is presented and applied to shrink the look-up tables of a scanning n-tuple handwritten character recognizer. lossy compression is realized by clustering n-tuples that are observed to induce similar class probability distributions. a new distance metric called "weighted mean kl divergence" is introduced to assess similarity and account for the cumulative effect of merging two distributions. after compression, cluster membership is rebalanced in an annealing-like process. the proposed method is evaluated on three isolated-character subsets of the unipen database. compression ratios in excess of 2000:1 are demonstrated for 5-tuple classifiers.
feature extraction methods applied to the clustering of electrocardiographic signals. a comparative study. in this paper, a method to automatically extract the main information from a long-term electrocardiographic signal is presented. this method is based on techniques of pattern recognition applied to speech processing, like dynamic time warping, and trace segmentation. in order to fulfill this objective, a clustering process is applied to the set of beats present within the electrocardiographic signal. from each group obtained, one beat is taken as representative of all the beats in that cluster.since the discrete sequences of beat features can have different length, the clustering process takes place in a pseudo-metric space, and the dissimilarity measure is calculated using dynamic programming. due to the same reason, the clustering algorithm employed is thekmedians, including some optimizations to reduce the computational cost. an experimental comparative study, using four different feature extraction methods, linear, and non-linear temporal alignment of sequences, is performed using labeled registers from the mit database.
some pattern recognition challenges in data-intensive astronomy. we review some of the recent developments and challenges posed by the data analysis in modern digital sky surveys, which are representative of the information-rich astronomy in the context of virtual observatory. illustrative examples include the problems of an automated star-galaxy classification in complex and heterogeneous panoramic imaging data sets, and an automated, iterative, dynamical classification of transient events detected in synoptic sky surveys. these problems offer good opportunities for productive collaborations between astronomers and applied computer scientists and statisticians, and are representative of the kind of challenges now present in all data-intensive fields. we discuss briefly some emergent types of scalable scientific data analysis systems with a broad applicability.
support vector machines for face recognition with two-layer generated virtual data. this paper presents support vector machines (svm) for few samples-based face recognition with two-layer artificially generated virtual training data. the few samples cannot express all the conditions of the test data. thus, we generalize the samples and the feature data to other conditions according to the distribution. first, correspond to the original face images, by locating the eyes center on the face images and facemask template; second is to the feature vectors, we get the feature data by principal component analysis to the face images, then use linear interpolate and extrapolate methods to generate new data. after all the data drawn, use svm to train and test. in the ict-ycnc face database, the proposed system obtains competitive results, and shows the methods are available.
an iris image synthesis method based on pca and super-resolution. it is very important for the performance evaluation of iris recognition algorithms to construct very large iris databases. however, limited by the real conditions, there are no very large common iris databases now. in this paper, an iris image synthesis method based on principal component analysis (pca) and super-resolution is proposed. the iris recognition algorithm based on pca is first introduced and then, iris image synthesis method is presented. the synthesis method first constructs coarse iris images with the given coefficients. then, synthesized iris images are enhanced using super-resolution. through controlling the coefficients, we can create many iris images with specified classes. extensive experiments show that the synthesized iris images have satisfactory cluster and the synthesized iris databases can be very large.
skin color detection through estimation and conversion of illuminant color using sclera region of eye under varying illumination. the skin color in an image captured by a camera undergoes variation as the illumination changes. therefore, the skin color detection based only on a static model often decreases the detection rate. for enhancing the robust skin color detection using a static model, the illuminant color estimated from images captured under various illumination conditions is converted to a canonical illuminant. this paper first estimates the illuminant color from the pixels in the sclera region of the eyes and then converts it to a canonical color for robust skin color detection. experimental results show that the skin color detection using the proposed method increases the detection rate especially for the images taken in the low or high correlated color temperature of the illumination.
robust tracking of multiple people in crowds using laser range scanners. laser based people tracking systems have been developed for mobile robotic or intelligent surveillance areas. existing systems rely on laser point clustering to extract object locations. however, in a crowded environment, laser points of different objects are often interlaced and undistinguishable and can not provide reliable features. this paper presents a novel and robust laser-based tracking method for people in crowds. firstly, we propose a stable feature extraction method based on accumulated distribution of successive laser frames. then a robust tracking filter is proposed based on the combination of independent bayesian filter and sampling based data association filter. evaluations with real data show that the proposed method is robust and effective. it achieves a significant improvement compared with existing trackers.
feature extraction for the analysis of gait and human motion. in this work we introduce a new model-based approach towards the 3-d tracking and extraction of gait patterns in human motion. we suggest the use of a hierarchical, structural model of the human body with a novel derivation of system dynamics from hard and soft kinematic constraints. the hard constraints place physical limitations on possible model configurations while the soft constraints represent probabilistic distributions learned from previous examples of human motion. using the parameters of the structural and dynamic models, we derive a methodology for extracting a number of gait variables at both coarse and fine resolutions with coincident robustness and precision. in particular, we demonstrate an ability to accurately measure gait velocity, stance width, stride length, arm swing, cadence, and stance times from multi-view, video sequences of human movement captured in a complex home environment.
estimating the optimal quantization parameter in h.264. the quantization parameter (qp) has a very important impact on the compression rate in h.264. in this paper we show that in order to achieve efficient rate-control coding a good estimate for the initial qp parameter is necessary. an extensive altering of this value, to keep the required bitrate, results in significant fluctuation of the image quality and decreases the average quality of the whole coded sequence. we propose a simple and fast method to decide the starting value for qp for each part of the video sequence. experimental results show stabilized image quality and significant gain in psnr.
object detection in video via particle filters. we propose an object detection method using particle filters. our approach estimates the probability of object presence in the current image given the history of observations up to current time. to do so, object presence is modelled by a two-state markov chain, and the problem is translated into sequential bayesian estimation which can be solved by particle filters. the observation density, required by the particle filter is based on selected discriminative haar-like features that were introduced by viola and jones [7] for object detection in static images. we illustrate the approach on the problem of face detection. experiments on real video sequences show the feasability of the approach.
nearest neighbor ensemble. recent empirical work has shown that combining predictors can lead to significant reduction in generalization error. the individual predictors (weak learners) can be very simple, such as two terminal-node trees; it is the aggregating scheme that gives them the power of increasing prediction accuracy. unfortunately, many combining methods do not improve nearest neighbor (nn) classifiers at all. this is because nn methods are very robust with respect to variations of a data set. in contrast, they are sensitive to input features. we exploit the instability of nn classifiers with respect to different choices of features to generate an effective and diverse set of nn classifiers with possibly uncorrelated errors. interestingly, the approach takes advantage of the high dimensionality of the data. the experimental results show that our technique offers significant performance improvements with respect to competitive methods.
detection of microcalcifications clusters in mammograms through ts-mrf segmentation and svm-based classification. at present, mammography is the only not invasive diagnostic technique allowing the diagnosis of a breast cancer at a very early stage. a visual clue of such disease particularly significant is the presence of clusters of microcalcifications. reliable methods for an automatic detection of such clusters are very difficult to accomplish because of the small size of the microcalcifications and of the poor quality of the digital mammograms. a method designed for this task is described. the mammograms are firstly segmented by means of the tree structured markov random field algorithm which extracts the elementary homogeneous regions of interest on the image. such regions are then submitted to a further analysis (based both on heuristic rules and support vector classification) in order to reduce the false positives. the approach has been successfully tested on a standard database of 40 mammographic images, publicly available.
classification of textures distorted by waterwaves. in this paper, we approach the novel problem of classifying images of underwater textures as observed from outside the water. our main contribution is to combine a geometric distortion removal algorithm with a texture classification method to solve the problem of classifying images of submerged textures when the water is disturbed by waves. we show that by modeling the separate types of distortion, we can extract enough texture information to correctly classify textures using spatial statistical measurements on the texton representations. we evaluate our algorithm on both natural and artificial textures acquired in our laboratory. results are promising and show the feasibility of our algorithm.
a ball detection algorithm for real soccer image sequences. a large number of methods for circle detection has been studied in the last years for numerous image processing applications. the application domain considered in this paper is the soccer game. to identify the ball in soccer images is very important in order to evaluate the goal event. this domain is challenging as a great number of problems has to be managed, such as occlusions, shadows, objects similar to the ball, real time processing. aim of this work is to present the results of a number of experiments obtained by using a modified version of the directional circle hough transform. different lighting conditions have been considered since they introduce strong modifications on the appearance of the ball in the image: when the image sequences are taken with natural light the ball appears as a spherical cap then the search of the ball has been modified in order to manage those situations. a large number of experiments has been carried out showing that the proposed method obtains an high detection score.
discriminant features for model-based image databases. a challenging topic in content-based image retrieval is to determine the discriminant features that improve classification performance.an approach to learn concepts is by estimating mixture model for image databases using em algorithm; however, this approach is impractical to be implemented for large databases due to the high dimensionality of the feature space.based on the over-splitting nature of our em algorithm and the bayesian analysis of the multiple users' labelling information derived from their relevance feedbacks, we propose a probabilistic mda to find the discriminating features, and integrate it with the em framework.the experimental results on corel images show the effectiveness of concept learning with the probabilistic mda, and the improvement of the retrieval performance.
an algorithm for real time eye detection in face images. the problem of eye detection in face images is very important for a large number of applications ranging from face recognition to gaze tracking. in this paper we propose a new algorithm for eyes detection that uses iris geometrical information for determining in the whole image the region candidate to contain an eye, and then the symmetry for selecting the couple of eyes. the novelty of this work is that the algorithm works on complex images without constraints on the background, skin color segmentation and so on. different experiments, carried out on images of subjects with different eyes colors, some of them wearing glasses, demonstrate the effectiveness and robustness of the proposed algorithm.
gesture segmentation from a video sequence using greedy similarity measure. we propose a novel method of greedy similarity measure to segment long spatial-temporal video sequences. firstly, a principal curve of motion region along frames of a video sequence is constructed to represent trajectory. then from the constructed principal curves of trajectories of predefined gestures, hmms are applied to modeling them. for a long input video sequence, greedy similarity measure is established to automatically segment it into gestures along with gesture recognition, where true breakpoints of its principal curve are found by maximizing the joint probability of two successive candidate segments conditioned on the gesture models obtained from hmms. the method is flexible, of high accuracy, and robust to noise due to the exploitation of principal curves, the combination of two successive candidate segments, and the simultaneous recognition. experiments including comparison with two established methods demonstrate the effectiveness of the proposed method.
a framework for grid-based image retrieval. in this paper we present a grid-based framework for image retrieval. in order to represent the intricate composition of images, the grid-based approach partitions each image into blocks from which a feature representation is derived from the local low-level content. since the background often dominates the subject in the foreground, a special query selection method was developed. it combines the salient region-of-interest/query-by-exampleparadigm with coarse segmentation to remove the irrelevant background regions. the proposed search method looks for similar features across all block positions and at several scales. existing local grid-based methods are constrained by searching for objects in the same position as the query object. using this framework, the spatial constraint can be eliminated, and steps toward scale invariance can be taken. promising results show that the grid-based method performs better than global search.
a computational framework for automatic determination of morphological parameters of proximal femur from intraoperative fluoroscopic images. determination of morphological parameters of proximal femur using different image modalities is discussed. in this paper, a computational framework based on particle filter is proposed for automatic determination of morphological parameters of proximal femur from intraoperative fluoroscopic images. in this framework, the proximal femur is decomposed into three constrained components: (1) femoral head, (2) femoral neck, and (3) femoral shaft. each component is represented by a set of parameters describing its three-dimensional (3d) spatial position and 3d geometrical shape. particle filter based inference is then used to estimate those parameters from the acquired fluoroscopic images. the constraints between different components are modeled by a single directional rational network to improve the efficiency and robustness of the proposed approach. we report the initial quantitative and qualitative evaluation results on a plastic femur, which indicate the validity of our approach.
utilizing information theoretic diversity for svm active learn. incrementally learning from a large number of unlabeled examples continues to be an active area of research in pattern recognition. active learning has made great strides in recent years to address this problem, taking advantage of svms to develop robust learning systems. recently, diversity sampling for svm active learning has garnered much attention. in this work we propose a fundamentally motivated view of diversity for svm active learning based on an information-theoretic diversity measure. comparative testing on a database from the small-sample learning problem of image retrieval is done and thoughts for future work are presented.
3d segmentation by maximally stable volumes (msvs). this paper introduces an efficient 3d segmentation concept, which is based on extending the well-known maximally stable extremal region (mser) detector to the third dimension. the extension allows the detection of stable 3d regions, which we call the maximally stable volumes (msvs). we present a very efficient way to detect the msvs in quasi-linear time by analysis of the component tree. two applications - 3d segmentation within simulated mr brain images and analysis of the 3d fiber network within digitized paper samples - show that reasonably good segmentation results are achieved with low computational effort.
a kernel fractional-step nonlinear discriminant analysis for pattern recognition. feature extraction is one of the most significant and fundamental problems in pattern recognition (pr). this paper introduces a novel kernel fractional-step nonlinear discriminant analysis (kf-nda) for feature extraction in pr. it not only overcomes the limitation of failing for a nonlinear problem in the direct fractional-step linear discriminant analysis (df-lda), but also improves the generalization ability of traditional kernel nonlinear discriminant analysis (k-nda). it is then applied to an experiment on face recognition, and the results demonstrate that this method is more effective than the existing methods.
online appearance-based face and facial feature tracking. we propose a simple framework that utilizes online appearance models for 3d face and facial feature tracking with a deformable model. adapting the geometrical parameters for each frame adopts a steepest ascent method in the observation likelihood using a local exhaustive and directed search in the parameter space. the observation likelihood is based on the current appearance and the registered images. the developed framework is straightforward and has the following advantages. first, it does not require any a priori statistical facial texture. second, it does not require any a priori transition model for the 3d motion. video sequences featuring large head motions, large facial animations, and external illumination variations are successfully tracked, which demonstrate the efficiency of the developed framework.
integrating emd and gradient for generating primal sketch of natural images. primal sketch performs an important role in early vision. in this paper, we propose a novel method to obtain the primal sketch of natural images by integrating empirical mode decomposition (emd) techniques and image gradient. 2d emd approach can decompose the image into a finite number of intrinsic mode functions (imf), and each one represents the original image in a different scale, with the 1st imf representing the finest scale. to enhance the information represented by the imf, we multiply the 1st imf by the image gradient. this enhanced imf highlights intensity changes in the image. by linking all the maximal points in the enhanced imf, we obtain a primal sketch of the original image. compared with the existed primal sketch extraction methods, our method is fully driven by the image data, and it needs neither to choose filters nor to learn the image bases. the experiment results show that our method is fast and effective.
facial expression recognition using auto-regressive models. in this paper, we address the analysis and recognition of facial expressions in continuous videos. we introduce a view- and texture-independent approach that exploits the temporal facial action parameters estimated by an appearance-based 3d face tracker. the facial expression recognition is carried out using learned dynamical models based on auto-regressive processes. these learned models can also be utilized for the synthesis and prediction tasks. experiments demonstrated the effectiveness of the developed method.
integrating automatic and interactive brain tumor segmentation. this paper integrates automatic segmentation based on supervised learning with an interactive multi-scale watershed segmentation method. the combined method automatically provides an initial segmentation that applies the building blocks that the user can use in the interactive method. thereby the two approaches are seamlessly integrated and the combined method can be used on the full range of problems from very easy to very difficult segmentation tasks resulting in different levels of interaction needed. the method is evaluated for segmentation of brain tumors.
structural flow smoothing for shape interpolation. this paper presents a comparative study of robust diffusion algorithms when used for smoothing structural fields applied in volumetric image interpolation. the input data consists of a set of parallel and equidistant slices which are considered sparsely located along a central axis. the structural flows are constructed using the dual directional block matching algorithm (dbma). two vectorial flows are modelled in both directions along the central axis, using the correlation between blocks of pixels from successive slices. as with most block matching algorithms, this method is susceptible to noise and the resulting vector fields contain outliers. a methodology that combines diffusion and robust statistics in order to smooth the dual structural flow is proposed. consequently, new slices are interpolated in between the existing slices, according to the smoothed vector fields. the set of algorithms is applied in volumetric medical images.
a multi-cameras 3d volumetric method for outdoor scenes : a road traffic monitoring application. this paper deals with the issue of using multi-cameras for road traffic monitoring. the aim is to remove the classic monocular ambiguities and to retrieve the objects' height. an efficient and simple calibration method is presented. it relies on the geometric constraints of the road. a high speed matching procedure is introduced. it is based on an altitude planar decomposition of the road scene. the method naturally achieves two tasks due to altitudes sampling. match and reconstruction become simultaneous. finally, experimental results are presented.
sector-based diffusion filtering. in this paper, we propose a new approach devoted to the denoising and the enhancing of strongly oriented 3-d images. in particular, the paper focuses on seismic data composed of a stack of layers disturbed by noise and broken by faults. the denoising of those data is a preprocessing used to improve the detection of the faults. our method is based on an anisotropic forward and backward diffusion scheme, which takes advantage of the computation of a "regional" orientation. this approach allows the recovering of the plan which is tangent to the current layer and the corresponding normal direction. then the diffusion goes forward along the layer in order to smooth the noise, and backward along the normal to separate the layers.
metric mixtures for mutual information (m^3 i) tracking. a new method for updating the template in a feature tracking application is presented, which has minimal memory and processing overhead. the proposed method is an expectation maximisation inspired approach based on modelling the variable appearance of a template using a gaussian mixture model in a discrete metric space, termed the m^3 i tracker for short.the proposed technique is compared to various other techniques in several experiments, where it performs robustly. several comparison methods are outperformed. in addition to robust template tracking it has wider applications to advanced techniques such as aams and deformable templates.
image template matching using mutual information and np-windows. a non-parametric (np) sampling method is introduced for obtaining the joint distribution of a pair of images. this method based on np windowing and is equivalent to sampling the images at infinite resolution. unlike existing methods, arbitrary selection of kernels is not required and the spatial structure of images is used. np windowing is applied to a registration application where the mutual information (mi) between a reference image and a warped template is maximised with respect to the warp parameters. in comparisons against the current state of the art mi registration methods np windowing yielded excellent results with lower bias and improved convergence rates.
implementing image applications on fpgas. the cameron project has developed a language and compiler for mapping image-based applications to field programmable gate arrays (fpgas). this paper tests this technology on several applications and finds that fpgas are between 8 and 800 times faster than comparable pentiums for image based tasks.
real-timehumanmotion sensingbased on vision-based inverse kinematics for interactive applications. vision-based human motion sensing has a strong merit that it does not impose any physical restrictions on humans, which provides a natural way of measuring human motion. however, its real-time processing is not easy to realize, because a human body has a high degrees of freedom, whose vision-based analysis is not simple and is usually time consuming. here, we have developed a method in which human postures are analyzed from a limited number of visual cues. it is a combination of numerical analysis of inverse kinematics and visual search. our method is based on a general framework of inverse kinematics, and, therefore, we can use relatively complex human figure model, which can generates natural human motion. in our experimental studies, we show that our implemented system works in real-time on a pc-cluster.
spectral sound gap filling. we present a new method for automatically filling in gaps of textural sounds. our approach is to transform the signal to the time-frequency space, fill in the gap, and apply the inverse transform to reconstruct the result. the complex spectrogram of the signal is partitioned into separate overlapping frequency bands. each band is fragmented by segmentation of the time-frequency space and a partition of the spectrogram in time, and filled in with complex fragments by example. we demonstrate our method by filling in gaps of various types of textural sounds.
person-on-person violence detection in video data. we address the problem of detecting human violence in video, such as fist fighting , kicking, hitting with objects, etc. to detect violence we rely on motion trajectory information and on orientation information of a person's limbs. we define an acceleration measure vector (amv) composed of direction and magnitude of motion and we define jerk to be the temporal derivative of amv. we present results from several data sequences involving multiple types of violent activities.
signal discrimination using a support vector machine for genetic syndrome diagnosis. in this study, a support vector machine (svm) classifies real world data of cytogenetic signals measured from fluorescence in-situ hybridization (fish) images in order to diagnose genetic syndromes. the study implements the svm structural risk minimization concept in searching for the optimal setting of the classifier kernel and parameters. we propose thresholding the distance of tested patterns from the svm separating hyperplane as a way of rejecting a percentage of the miss-classified patterns thereby allowing reduction of the expected risk. results show accurate performance of the svm in classifying fish signals in comparison to other state-of-the-art machine learning classifiers, indicating the potential of an svm-based genetic diagnosis system.
recognizing interaction activities using dynamic bayesian network. activity recognition is significant in intelligent surveillance. in this paper, we present a novel approach to the recognition of interacting activities based on dynamic bayesian network (dbn). in this approach the features representing the object motion are divided into two classes: global features and local features, which are at two different spatial scales. global features describe object motion at a large spatial scale and relations between objects or between the object and environment, and local ones represent the motion details of objects of interest. we propose a new dbn model structure with state duration to model human interacting activities. this dbn model structure combines the global features with local ones harmoniously. the effectiveness of this novel approach is demonstrated by experiment.
reflectance estimation from motion under complex illumination. in this paper, we propose a method for recovering the reflectance properties of a moving lambertian object from an image sequence of the object taken by a fixed camera under unknown, complex illumination. our proposed method is based on the spherical-harmonic representation of lambertian reflectance under arbitrary illumination. then, by combining the geometry reconstructed by shape-from-motion (sfm), we recover the albedo of the object and the illumination distribution only from the image sequence of the moving object. the proposed method enables us to synthesize realistic images of the object in arbitrary poses under arbitrary lighting conditions by using reconstructed shape and albedo. we conducted a number of experiments by using both synthetic and real images to confirm the effectiveness of our proposed method.
robust detection of people in thermal imagery. we present a new contour analysis technique to detect people in thermal imagery. background-subtraction is first used to identify local regions-of-interest. gradient information within each region is then combined into a contour saliency map. to extract contour fragments, a watershed-based selection algorithm is used. a path-constrained a* search is employed to complete any broken contours, from which silhouettes are formed. results using thermal video sequences demonstrate the capability of the approach to robustly detect people across a wider range of environmental conditions than is possible with standard approaches.
fast tone mapping for high dynamic range images. we present a fast, effective and flexible tone reproduction method that preserves visibility and contrast impression of high dynamic range scenes in low dynamic range reproduction devices. a single parameter controls the visibility and contrast in a simple and elegant manner and at interactive speed. the new method is simple to use and is computationally highly efficient. experiments show that the technique produces good results on a variety of high dynamic range images. the method can also be used to enhance ordinary low dynamic range digital images.
analysis and recognition of walking movements. we present an approach for recognizing human walking movements using low-level motion regularities and constraints. biomechanical features for classification are automatically extracted from video sequences of walkers. a multiplicative classification rule using statistical distances is then used to determine whether an unknown motion is consistent with normal walking patterns. recognition results are shown distinguishing walking examples across multiple speeds from other non-walking locomotions.
on the classification of temporal lobe epilepsy using mr image appearance. classification of neurological diseases based on image characteristics often requires extensive modeling and use intervention. while other techniques concentrate on specific structures, the novelty of the method presented here resides in its analysis of the grey-level appearance of large, non-specific volumes of interest (voi) from t1 mri data. no manual intervention is required other than the selection of the voi. this work presents the methodological framework and preliminary results towards our aim of classifying normal subjects and patients with temporal lobe epilepsy (tle) within the medial temporal lobe. for this purpose, principal components analysis is performed on a set of normal subjects for the creation of a multi-dimensional space representative of a normal population. new data for normal and tle subjects are proposed in this space, under the assumption that the distributions of the projections are not identical and can be used for classification. it is shown that linear discriminant analysis of the eigencoordinates of the projected data can beused to classify normals vs tle with a 70% accuracy based on only 10 eigenvectors. this results can go up to 100% if all eigenvectors defining the grey-level space are used.
transforming static ct in gated pet/ct studies to multiple respiratory phases. discrepancy between ct and pet data due to motion in pet/ct studies is a significant problem. pet is acquired over a period of time whereas ct is static. thus attenuation correction of pet data with ct leads to wrong quantification and can result in wrong diagnosis and treatment. a solution based on respiratory gating and optical flow algorithms is presented. a combined local-global optical flow algorithm is used for motion estimation on pet data, the static ct is then transformed to different phases of the respiratory cycle. corresponding pet and ct data is thus obtained for better attenuation correction. the results are verified on both software phantom and real patient data.
structural graph matching with polynomial bounds on memory and on worst-case effort. a new method of structural graph matching is introduced and compared against an existing method and against the maximum common subgraph. the method is approximate with polynomial bounds on both memory and on the worst-case compute effort. methods work on arbitrary types of graphs and tests with strongly regular graphs are included. no node or edge colors are needed in the methods; the common subgraph is extracted based in structural comparisons only. monte carlo trials are benchmarked with 100% additional (clutter) nodes. results are shown to be typically within 1-2 nodes of the maximum common subgraph. over 7500 test trials are reported with graphs up to 100 nodes.
structural matching via optimal basis graphs. the 'basis graph' approach to structural matching uses a fixed set of small (4 node) graphs to characterize local structure. we compute mapping probabilities by first finding the probability of a basis graph being an induced subgraph of the input graph. the similarity of these probabilities is used to compare nodes of the input graphs. the method permits common subgraphs to be identified without the use of any node or edge coloring. we report on an improved, simpler, version of the algorithm, which has also been optimized. performance is compared with the lerp method, which is based on length-r paths. both methods are approximate with polynomial bounds on both memory and on the worst-case compute effort. these methods work on arbitrary types of undirected graphs, and tests with strongly regular graphs are included. monte carlo test trials (3000+) included up to 100% additional (noise) nodes.
an area-based alignment method for 3d urban models. the alignment method refers to the idea of superposing a model onto an image. the problem is separated in two parts, i) first find a possible transformation of the model on the image ii) then validate this transformation by aligning the model onto the image.we propose an extension of the traditional alignment method in order to deal with complex objects sustained by projective mappings. much of the work is focalized on how to cope with spurious data as long as processing time is not becoming too excessive. moreover, the robustness and simplicity of the approach make it appealing for a broader class of objects, not necessarily urban parts.
combined use of partial least squares regression and neural network for diagnosis tasks. this paper deals with a diagnosis system, based on a combined use of partial least squares regression (pls) and neural network (nn). an application concerning the french railway track/vehicle transmission system illustrates this approach. it will be shown that a reliable selection of a reduced set of relevant descriptors is made by the pls regression. moreover, the projection of the data on the first pls plane allows to highlight trajectories of the evolution of the system state between different classes. the modeling of the process state is performed by a multilayer nn. in this case, the pls algorithm provides also a suitable approach to initialize the nn weights and to determine the optimal number of hidden nodes.
regularity and complexity of human electroencephalogram dynamics: applications to diagnosis of alzheimers disease. in this paper, we evaluate the complexity and regularity of human electroencephalogram (eeg) dynamics using approximate entropy (apen), and the results are used to distinguish alzheimer's disease (ad) patients from healthy subjects. from the 10-channel eeg time series recordings of 20 healthy subjects and 14 ad patients with closed eyes, our analysis has shown that ad patients have lower apen values than healthy subjects. these results support the previous hypothesis that greater regularity corresponds to greater component autonomy and isolation in many complex systems. we believe that our effort provides a valuable complementary framework to the classical eeg analysis, and it could help revealing the complexity of the human brain functions.
fast polygonal approximation of digital curves. in this paper, we have extended the approach defined in [segmentation of discrete curves into fuzzy segments, segmentation of discrete curvesinto fuzzy segments, extented version] to a multiorder analysis. the approach is based on the arithmetical definition of discrete lines [géométrie discrète, calculs en nombre entiers et algorithmique] with variable thickness. we provide a framework to analyse a digital curve at different levels of thickness. the extremities points of a segment provided at a high resolution are tracked at lower resolution in order to refine their locations. the high resolution level is automatically defined from the stability of the number of segments between two consecutive levels. the method is threshold-free and automatically provides a partitioning of a digital curve into its meaningful parts.
principal component analysis for online handwritten character recognition. in this paper, principal component analysis (pca) is applied to the problem of online handwritten character recognition in the tamil script. the input is a temporally ordered sequence of (x,y) pen coordinates corresponding to an isolated character obtained from a digitizer. the input is converted into a feature vector of constant dimensions following smoothing and normalization. pca is used to find the basis vectors of each class subspace and the orthogonal distance to the subspaces used for classification. pre-clustering of the training data and modification of distance measure are explored to overcome some common problems in the traditional subspace method. in empirical evaluation, these pca-based classification schemes are found to compare favorably with nearest neighbour classification.
the characterization of classification problems by classifier disagreements. in this paper we try to characterize a set of classification problems. for this, we use the disagreement between a set of standard classifiers. the disagreement patterns do not only point towards different types of classification problems, but also indicate the novelty and the usefulness of a classifier with respect to a setof classification problems and classifiers. some experiments show when known classification problems become unknown after changing their feature size or their training set size.
object tracking by the mean-shift of regional color distribution combined with the particle-filter algorithm. this paper presents a method for tracking a person in a video sequence in real time. in this method the profile of color distribution characterises target's feature. it is invariant for rotation and scale changes. it's also robust to non-rigidity and partial occlusion of the target. we employ the mean-shift algorithm to track the target and to reduce the computational cost. moreover, we incorporate the particle-filter into it to cope with a temporal occlusion of the target, and largely reduce the computational cost of the original particle-filter. experiments show the availability of this method.
features for printed document image analysis. this paper presents features for text/non-text area separation in printed document images. it firstly introduces entropic discrimination (i.e., a simple separation using only one feature). then, a brief recall on existing texture and geometric discriminant parameters proposed in previous research is done. several of them are statistically examined.
an information theoretic approach for active and effective object recognitions. this paper describes the strategy of optimal action selection for recognition of the observed object among those registered in the image data base from an information theoretic point of view. the goal is to reduce the number and effort of the recognition steps to reach the final decision of the recognition. we have chosen an information theoretic framework, motivated by the fact that sensored image data is not noiseless or ideal, nor can the effect of a certain action be completely determined in advance. we present the strategy of the recognition process, and then, the results of the feasibility study by experiments.
human behavior recognition with generic exponential family duration modeling in the hidden semi-markov model. the ability to learn and recognize human activities of daily living (adls) is important in building pervasive and smart environments. in this paper, we tackle this problem using the hidden semi-markov model. we discuss the stateof- the-art duration modeling choices and then address a large class of exponential family distributions to model state durations. inference and learning are efficiently addressed by providing a graphical representation for the model in terms of a dynamic bayesian network (dbn). we investigate both discrete and continuous distributions from the exponential family (poisson and inverse gaussian respectively) for the problem of learning and recognizing adls. a full comparison between the exponential family duration models and other existing models including the traditional multinomial and the new coxian are also presented. our work thus completes a thorough investigation into the aspect of duration modeling and its application to human activities recognition in a real-world smart home surveillance scenario.
augmented reality through real-time tracking of video sequences using a panoramic view. we propose a 2d approach for augmented reality (ar) applications where the real scene is modelled as a static panorama. we adapted a sparse tracking method based on homographies to track the orientation and zooming parameters of the camera during a video sequence. ar scenarii (synthetic object insertion, real object or character extraction) can be performed in arbitrary static environments (from wide outdoor scenes to virtually augmented desktops or conference rooms).
robust segmentation of hidden layers in video sequences. in this paper, we propose a novel and robust method for extracting motion layers in video sequences. taking advantage of temporal continuity, our framework considers both the visible and the hidden parts of each layer in order to increase robustness. moreover, the hidden parts of the layers are recovered, which could be of great help in many high level vision tasks. modeling the problem as a labeling task, we state it in a mrf-optimization framework and solve it with a graph-cut algorithm. both synthetic and real video sequences show a visible layers extraction comparable to the one usually performed by state of the art methods, as well as a novel and successful segmentation of hidden layers.
hidden markov models for couples of letters applied to handwriting recognition. this paper deals with handwritten word recognition using hidden markov models (hmm) and presents a new solution to cope with problems of segmentation resulting from image preprocessing. this first step involves cutting an image of an isolated word into letters or pieces of letters called graphems. it builds a sequence of small images described by features which are the input of hmm. the image segmentation usually produces errors and lowers the results obtained by a recognition system based on a set of hmm models corresponding to the twenty-six letters of the alphabet. this paper proposes to extend the alphabet with models of couples of letters which are often badly segmeented.
estimating the stretching characteristics of fiber bundles in microscopic images. collagen fiber bundles are important constituent parts of biological soft tissues, such as tendons, blood vessels and skin.the single collagen fibers within a bundle have a certain crimp that determines the bundle's stretching characteristic, which is of particular interest in mechanobiology. a thorough understanding of the complex interrelations between mechanical factors and the associated biological responses may help to improve diagnostics, which allow disease and injury to be treated earlier. we present a method to obtain the relative stretching characteristics (rsc) of collagen (fibrous) bundles based on the analysis of microscopic tissue images. we show, how the orientation statistics of local orientations in a bundle can be directly related to the rsc. the von mises distribution (vmd) - a circular probability distribution - is used to describe the 2d orientation statistics. the k parameter of the vmd is used to obtain the mean stretching and the probability density function (pdf) of the bundles' rsc is identified.
adaptive and smart interface for vcr remote control using hand gestures. this paper describes an adaptive and smart interface and shows its successful application for vcr remote control using hand gestures. the interface is capable of learning the user's operational habits and can offer self-help, aka wizard mode of operation; it can then monitorthe user's gestures and maintain constant vigilance in an attempt to assist her through feedback using video display and/or loud-speaker. the availability of users' profiles is used in an adaptive fashion to enhance human-computer interactions and to make them intelligent, i.e., causal. the smart interface is suitable for handicapped users and it can be used for security purposes too.
on-line handwriting recognition based on bigram co-occurrences. we propose a handwriting recognition method that utilizes the n-gram statistics of the english language. it is based on the linguistic property that very few pairs of english words share exactly the same letter bigrams. this property is exploited to bring context to the recognitionstage and to avoid segmentation. the recognition is based on detecting bigram co-occurrences. even with naive features and a limited reference set, it recognizes over 45% of lexicon words that it has never seen before in handwritten form.
local straightness: a contrast independent statistical edge measure for color and gray level images. most existing methods for edge detection rely on contrast dependent thresholds. we show that a local measurement defined by the ratio of the smallest to the largest eigenvalue of the second moment matrix of filter kernels, can be used to separate smooth, low curvature curves and straight lines from noise, independent of contrast, in both color and gray level images. this is done without applying a threshold to the gradient magnitude. the edge images are defined as zero crossings in the gradient direction. the covariance matrix can easily be computed for both gray level images and color images. further we show the potentiality of such a measure by integrating it with the hough transform to extract long straight lines in noisy color images. the method is shown to successfully extract consistent line features from color images of a scene, captured under drastically different lightening conditions.
canonical skeletons for shape matching. skeletal representations of 2-d shape, including shock graphs, have become increasingly popular for shape matching and object recognition. however, it is well known that skeletal structure can be unstable under minor boundary deformation, part articulation, and minor shape deformation (due to, for example, small changes in viewpoint). as a result, two very similar shapes may yield two significantly different skeletal representations which, in turn, will induce a large matching distance. such instability occurs both at external branches as well as internal branches of the skeleton. we present a framework for the structural simplification of a shape's skeleton which balances, in an optimization framework, the desire to reduce a skeleton's complexity by minimizing the number of branches, with the desire to maximize the skeleton's ability to accurately reconstruct the original shape. this optimization yields a canonical skeleton whose increased stability yields significantly improved recognition performance.
specular free spectral imaging using orthogonal subspace projection. specularity is an important issue in computer vision. many algorithms have been proposed to remove highlights for color images. however, to our knowledge, no work has been done so far which specifically handles highlights in spectral imaging. in this paper, we introduce a specular invariant representation for hyperspectral images based on the dichromatic model and orthogonal subspace projection. it is a simple one step algorithm which only involves pixellevel operations, thus it does not require any segmentation. nor does it require any pre/postprocessing or explicit spectral normalization. importantly, unlike the previous methods for color images, it can be theoretically extended to handle highlights caused by multicolored illuminations. experimental results demonstrate the effectiveness of our algorithm.
a strongly coupled architecture for contextual object and scene identification. the context-centered approach to object detection and recognition is based on the intuition that the contextual information of real-world scenes provides relevant information for these tasks. this intuition is supported by psychophysical experiments in human scene perception and visual search, which provide evidence that the human visual system uses the relationship between the environment and the objects to facilitate object recognition. here we use a probabilistic model to investigate the possible interactions between object class hypotheses and scene class hypotheses in a visual system. the architecture of the model is based on separate modules interacting with each other via feedforward and feedback connections. a competitive-priors structure is used to implement the feedback connections.
kalman filtering for robust identification of face images with varying expressions and lighting conditions. we propose a novel algorithm for the identification of faces from image samples. the algorithm uses the kalman filter to identify significant face features. we employ the kalmanfaces approach on a database of face images that show a variety of different expressions and were recorded under varying lighting conditions. kalmanfaces show robustness against distortion and outperform the classic eigenfaces approach in terms of identification performance and algorithm speed.
improvement of prediction accuracy using discretization and voting classifier. there are many examples of classification algorithms developed so far for data analysis, pattern recognition, scene analysis and learning from graphical models. being motivated by the works of a number of researchers, here i have tried to improve the prediction accuracy by first discretizing the real world dataset and then applying a voting classifier on the discretized dataset. in this work, continuous dataset from the raw real world dataset having missing attribute values have been generated and discretized the dataset using spid 3 algorithm. then naïve-bayesian classifier has been implemented to apply it on the continuous and discretized dataset. finally, an ensemble learner (ada-boost algorithm) has been developed where the naïve bayesian classifier has been used as the base learner of the ensemble. the extensive empirical results over the twenty real world datasets show that the prediction accuracy can be increased by the joint performance of discretization and voting classifier.
robust image registration based on markov-gibbs appearance model. a new approach to align an image of a textured object with a given prototype is proposed. visual appearance of the images, after equalizing their signals, is modeled with a markov-gibbs random field with pairwise interaction. similarity to the prototype is measured by a gibbs energy of signal co-occurrences in a characteristic subset of pixel pairs derived automatically from the prototype. an object is aligned by an affine transformation maximizing the similarity by using an automatic initialization followed by gradient search. experiments confirm that our approach aligns complex objects better than popular conventional algorithms.
probabilistic modeling of blood vessels for segmenting mra images. a new physically justified adaptive probabilistic model of blood vessels on magnetic resonance angiography (mra) images is proposed. the model accounts for both laminar (for normal subjects) and turbulent blood flow (in abnormal cases like anemia or stenosis) and results in a fast algorithm for extracting a 3d cerebrovascular system from the mra data. experiments with real data sets confirm the high accuracy of the proposed approach.
a framework for automatic segmentation of lung nodules from low dose chest ct scans. to accurately separate each pulmonary nodule from its background in a low dose computer tomography (ldct) chest image, two new adaptive probability models of the visual appearance of small 2d and large 3d pulmonary nodules are jointly used to control the evolution of the deformable model. the appearance prior is modeled with a translation and rotation invariant markov-gibbs random field of voxel intensities with pairwise interaction. the model is analytically identified from a set of training nodule images with normalized intensity ranges. both the nodules and their background in each current multi-modal chest image are also modeled with a linear combination of discrete gaussians that closely approximate the empirical marginal probability distribution of voxel intensities. experiments with real ldct chest images confirm the high accuracy of the proposed approach.
image analysis of renal dce mri for the detection of acute renal rejection. acute rejection is the most common reason of graft failure after kidney transplantation, and early detection is crucial to survive the transplanted kidney function. in this paper we introduce a new approach for the automatic classification of normal and acute rejection transplants from dynamic contrast enhanced magnetic resonance imaging (dce-mri). the proposed algorithm consists of three main steps; the first step isolates the kidney from the surrounding anatomical structures. in the second step, a novel nonrigid-registration algorithm is employed to account for the motion of the kidney due to patient breathing, and finally, the perfusion curves that show the transportation of the contrast agent into the tissue are obtained from the cortex and used in the classification of normal and acute rejection transplants. applications of the proposed approach yield promising results.
wide baseline matching through homographic transformation. this paper discusses the wide baseline matching problem where the camera parameters are known up to an error factor and the ground surface is considered planar. junctions of different shapes and orientations are detected. homographic correlation, an invariant measure to projective transformation, is utilized using reconstructed planes made of detected junctions. two variants of homographic correlation are proposed showing that this approach outperforms non-homographic correlation.
physically motivated reconstruction of fiberscopic images. flexible endoscopes are applied in modern techniques for technical inspection as well as medical diagnostic and therapy in keyhole-surgery-scenarios. their characteristic bendable image conductor consists of a limited number of coated fibers. an optical fiber consists of a core surrounded by a cladding layer. this configuration leads to imaging artifacts, called comb structures. they have a negative impact on further image processing steps, like feature detection and tracking. the intensity distribution of a cross-section of a fiber is usually modeled by a two-dimensional gaussian. we propose a preprocessing algorithm which exploits this physical property to remove the comb structure while retaining the image content. the proposed approach effectively removes of fiberscopic comb structure in real-time. it is adaptive to arbitrary endoscope and sensor combinations. the results give prospect of a large field of possible applications both for visual optimization in the clinical environment and for further digital imaging tasks.
a parallel pipelined implementation of loco-i for jpeg-ls. we describe n2c-ex, a parallel, pipelined version of a modified loco-i lossless compression algorithm used within the jpeg-ls coding scheme. this version takes into account the sequential nature of the original loco-i algorithm due to the use of context statistics in coding the residual errors of the predictive phase and uses three pipelines to carry out concurrently the encoding on independent pixels extracted from the serial stream of incoming data.
graph matching using interference of coined quantum walks. in this paper we consider how coined quantum walks can be applied to exact graph matching. the matching problem is abstracted using an auxiliary structure that connects pairs of vertices from the graphs to be matched by way of auxiliary vertices. we locate matches using coined quantum walks on this structure. we have tested the algorithm on graphs derived from the nci molecule database and found it to significantly reduce the space of possible matchings thereby allowing the graphs to be matched directly. we also perform a sensitivity analysis on the algorithm in order to examine its behaviour in the presence of noise.
an experimental comparison between consistency-based and adaptive prototype replacement schemes. an empirical characterization of a family of condensing algorithms for the 1-nn rule with regard to the different learning vector quantization schemes is presented. in particular, generalized prototype merging based on consistency on one hand and adaptive placement of a prespecified number of prototypes on the other, are considered. both families of methods have advantages and drawbacks. basically, lvq methods tend to be more robust and efficient butthey strongly depend on initialization and parameter setting while consistency-based merging methods have no initialization and parameter setting but tend to be very dependent on the particular training data.
a bayesian framework for robust human detection and occlusion handling using human shape model. one challenging aspect of automated surveillance for real environments is the occurrences of various difficult scenarios brought about by practical unconstrained settings. in this paper, we address foreground detection for automated surveillance under the following challenging situations: i) foregrounds being partially hidden due to close similarities to the background, and ii) foregrounds representing multiple objects being inseparable, forming a large contiguous blob due to occlusion. to build a robust system, we present a new foreground detection framework based on bayesian formulation, comprising both bottom-up and top-down approaches. we first propose a region-based background subtraction and a localized spatial segmentation scheme as the bottom-up steps for foreground detection. we then incorporate a human shape model as the top-down step for foreground validation and occlusion handling. segmentation is obtained when a maximum posteriori value is found, corresponding to the best description about foregrounds given by the approach. such integration of bottom-up and top-down approaches leads directly to more robust performance in handling challenging situations within hostile real environments. promising results are obtained when the algorithm is tested on real video sequences captured from a live surveillance system that operates at a public outdoor swimming pool.
panoramic stereo reconstruction using non-svp optics. omni-directional sensors are useful in obtaining a 360^o field of view with a single lens camera. omni-directional stereo imaging systems can be constructed using a single camera and a mirror consisting of two concentric, radially symmetric lobes. if the central camera-mirror axis is vertical, a stereo image containing imagery from all azimuth directions from two viewpoints can be captured within one image. a vertically oriented catadioptric optical system that employs a mirror with a radial profile other than parabolic or hyperbolic cannot maintain the straightness of non-vertical lines. however, non-parabolic or hyperbolic mirror profiles are desirable for resolution distribution, sensor size, and cost. these mirror shapes, including spherical mirrors, are said to be non-central or non-single view-point (svp); without a virtual perspective point, they pose new feature extraction challenges. the projection of straight lines in the world do not map to straight lines on the pixel array for non-svp panoramic images, nor in the general case map to any conventional conic. a method for processing the imagery from a panoramic non-svp catadioptric stereo sensor to reconstruct a 3d model of polyhedral objects with horizontal and vertical line edges is introduced. horizontal line segments are extracted using the panoramic hough transform and vertical line segments are recognized as straight radial lines. these segments, and closed shapes they form, are matched between the two lobe views to estimate position in three-dimensions. a novel hough transform technique is described, and practical considerations for its successful use are explored. four general weaknesses with hough transform techniques in general are identified, and solutions to address them in each case are given. details of a complete system using the panoramic hough transform are given to demonstrate where this transform must be supplemented with other methods for robust operation. issues of reconstruction accuracy are addressed, and experimental results with synthetic and real images are presented.
automatic detection of relevant head gestures in american sign language communication. an automated system for detection of head movements is described. the goal is to label relevant head gestures in video of american sign language (asl) communication. in the system, a 3d head tracker recovers head rotation and translation parameters from monocular video. relevant head gestures are then detected by analyzing the length and frequency of the motion signal's peaks and valleys. each parameter is analyzed independently, due to the fact that a number of relevant head movements in asl are associated with major changes around one rotational axis. no explicit training of the system is necessary. currently, the system can detect "head shakes." in experimental evaluation, classification performance is compared against ground-truth labels obtained from asl linguists. initial results are promising, as the system matches the linguists' labels in a significant number of cases.
robustness and specificity in object detection. in this paper we discuss the role of robustness to geometric conformity versus specificity in machine learning. the key observation made here is that object variation due to appearance and due to geometric deformation are often, for good reasons, intermixed in typical object detection applications. in the paper we consider a whole range of differently specific object detectors. it is shown that such detectors vary in their robustness to geometric deformation and also their specificity. such detectors can then be used in a cascade, where coarse detectors operate on a less-specific and more robust scale. this makes it possible to use coarse sampling of the space of geometric transformations. further on more-specific and less robust detectors are used. this requires as input the detections at a coarser scale combined with an optimization search step. in the paper it is also discussed how such detectors can automatically be obtained from a coarsely defined database of ground truth.
tracking soccer players using the graph representation. in this work, we consider the problem of tracking soccer players during a game by using multiple cameras. the main goal consists in finding the position of the players on the pitch at each instance of time. the occlusion is treated by splitting segmented blobs and the tracking is performed using a graph representation, where nodes correspond to the blobs obtained by image segmentation and edges represent the distance between the blobs.
bijective image registration using thin-plate splines.. image registration is the process of geometrically aligning two or more images. in this paper we describe a method for registering pairs of images based on thin-plate spline mappings. the proposed algorithm minimizes the difference in gray-level intensity over bijective deformations. by using quadratic sufficient constraints for bijectivity and a least squares formulation this optimization problem can be addressed using quadratic programming and a modified gauss-newton method. this approach also results in a very computationally efficient algorithm. example results from the algorithm on three different types of images are also presented.
non-linear reflectance model for bidirectional texture function synthesis. a rough texture modelling involves a huge image data-set - the bidirectional texture function (btf). this 6-dimensional function depends on planar texture coordinates as well as on view and illumination angles. we propose a new non-linear reflectance model, based on a lafortune reflectance model improvement, which restores all btf database images independently for each view position and herewith significantly reduces stored btf data size. the extension consists in introducing several spectral parameters for each btf image which are linearly estimated in the second estimation step according to the original data. the model parameters are computed for every surface reflectance field contained in the original bft data. this technique allows btf data compression by the ratio 1:15 while the synthesised images are almost indiscernible from the originals. the method is universal, and easily implementable in a graphical hardware for purpose of real-time btf rendering.
maximizing validity in 2d motion analysis. classifying and analyzing human motion from a video is relatively common in many areas. since the motion is carried out in 3d space, the 2d projection provided by a video is somewhat limiting. the question we are investigating in this article is how much information is actually lost when going from 3d to 2d and how this information loss depends on factors, such as viewpoint and tracking errors that inevitably will occur if the 2d sequences are analysed automatically.
fast synthesis of dynamic colour textures. textural appearance of many real word materials is not static but shows progress in time. if such a progress is spatially and temporally homogeneous these materials can be represented by means of dynamic texture (dt). dt modelling is a challenging problem which can add new quality into computer graphics applications. we propose a novel hybrid method for colour dts modelling. the method is based on eigen-analysis of dt images and subsequent preprocessing and modelling of temporal interpolation eigencoefficients using a causal auto-regressive model. the proposed method shows good performance for most of the tested dts, which depends mainly on the properties of the original sequence. moreover, this method compresses significantly the original data and enables extremely fast synthesis of artificial sequence, which can be easily performed by means of contemporary graphics hardware.
prescient paper: multimedia document creation with document image matching. a system is described for creating paper documents that show images of presentation slides and bar codes that point to a multimedia recording of a presentation that has not yet occurred. an image-matching algorithm applied after a presentation determines when each slide was displayed. these time-stamps map the bar codes onto commands that control a multimedia player. we describe the system infrastructure that allows us to prepare such prescient documents and the document image-matching algorithm that enables the mapping of bar codes onto the times when slides were displayed. this provides a multimedia annotation tool that requires no electronic device at capture time.
ecoc-one: a novel coding and decoding strategy. error correcting output codes (ecoc) represent a classification technique that allows a successful extension of binary classifiers to address the multiclass problem. in this paper, we propose a novel technique called ecoc-one to improve an initial ecoc configuration by including new dichotomies guided by the confusion matrix over exclusive training subsets. in this way, the initial coding represented by an optimal decision tree is extended adding binary classifiers forming a network. since not all dichotomies have the same relevance, a weighted methodology is included. moreover, to decode we introduce a new distance to attenuate the error accumulated by zeros in the ecocone matrix. we compare our strategy to other well-known ecoc coding strategies on the uci data set achieving very promising results.
error-less colour correctio. colour correction is the problem of mapping device dependent rgbs to standard cie xyzs. traditionally it is solved for by an error minimising one-to-one linear transform. however this problem is ill-posed. there exist multiple reflectances, known as metamers, which induce the same rgb but different xyzs (and vice versa). in this paper we propose that this ill-posedness might be viewed positively. indeed, that it leads to an error-less transform for colour correction. we propose that a mapping is error-less if it takes an rgb to an xyz such that there exists a real reflectance spectrum which integrates to this rgb-xyz pair. we show how we can solve for a mapping which satisfies this error-less criterion. as in previous studies, we seek a linear transform that is error-less. we show that we can solve for such a transform by quadratic programming. experiments demonstrate 3 important results. first, that a linear least squares transform is not error-less. specifically, saturated rgb-xyz pairs do not correspond to a plausible reflectance. second, there exists a linear transform that is error-less. finally, that the best error-less transform performs almost as well as least-squares, but substantially better for saturated colours. it is possible to map rgb to xyz with zero error.
forest extension of error correcting output codes and boosted landmarks. in this paper, we introduce a robust novel approach for detecting objects category in cluttered scenes by generating boosted contextual descriptors of landmarks. in particular, our method avoids the need of image segmentation, being at the same time invariant to scale, global illumination, occlusions and to small affine transformations. once detected the object category, we address the problem of multiclass recognition where a battery of classifiers is trained able to capture the shared properties between the object descriptors across classes. a natural way to address the multiclass problem is using the error correcting output codes technique. we extend the ecoc technique proposing a methodology to construct a forest of decision trees that are included in the ecoc framework. we present very promising results on standard databases: uci database and caltech database as well as in a real image problem.
perceptual grouping for contour extraction. this paper describes an algorithm that efficiently groups line segments into perceptually salient contours in complex images. a measure of affinity between pairs of lines is used to guide group formation and limit the branching factor of the contour search procedure. the extracted contours are ranked, and presented as a contour hierarchy. our algorithm is able to extract salient contours in the presence of texture, clutter, and repetitive or ambiguous image structure. we show experimental results on a complex line-set.
radon space and adaboost for pose estimation. in this paper, we present a new approach to camera pose estimation from single shot images in known environment. such a method comprises two stages, a learning step and an inference stage where given a new image we recover the exact camera position. lines that are recovered in the radon space consist of our feature space. such features are associated with [adaboost] learners that capture the wide image feature spectrum of a given 3d line. such a framework is used through inference for pose estimation. given a new image, we extract features which are consistent with the ones learnt, and then we associate such features with a number of lines in the 3d plane that are pruned through the use of geometric constraints. once correspondence between lines has been established, pose estimation is done in a straightforward fashion. encouraging experimental results based on a real case demonstrate the potentials of our method.
scene recovery from many randomly distributed single pixel cameras. this paper examines two scene recovery problems arising when interpreting data from massive numbers of randomly distributed single pixel cameras. assuming that the camera positions and orientations are approximately known, the paper shows that both distant and nearby scenes can be reconstructed, and analyzes how recovery performance varies with sensor parameters.
cross validation and segment support for stereo belief propagati. typically, algorithms for generating stereo disparity maps have been developed to minimise the energy equation of a single image. this paper proposes a method for implementing cross validation in a belief propagation optimisation. when tested using the middlebury online stereo evaluation, the cross validation improves upon the results of standard belief propagation. furthermore, it has been shown that regions of homogeneous colour within the images can be used for enforcing the so-called "segment constraint". developing from this, segment support is introduced to boost belief between pixels of the same image region and improve propagation into textureless regions.
an empirical model for saturation and capacity in classifier spaces. when assessing reported classification results based on selection of members from a database (e.g. a face database), one would like to know what is an achievable classification rate, given the noise level, dimensionality of the feature set and number of classes in the database. as best we can tell, no general results exist for this question, although many classification rates appear in different papers. this paper presents an empirical formula for map classification that links the number of discriminable classes to the error rate, dimensionality of the feature data and the feature noise level.
automated visual identification of characters in situation comedies. the objectives of the work described in this paper are simply stated: given examples of a particular person and an unlabelled video, we wish to find every instance of that person in the video and in others. this is an extremely difficult problem because of the many sources of variation in the person's appearance. we present a two stage approach. a 3-d ellipsoid approximation of the person's head is used to train a set of generative parts-based 'constellation' models which propose candidate detections in an image. the detected parts are then used to align the model, and the detections verified by global appearance. novel aspects of the approach include the minimal supervision required and the generalization across a wide range of pose. we demonstrate results of detecting three characters in a tv situation comedy.
fast exhaustive robust matching. this work presents a fast exhaustive robust matching technique for aligning translated images. the key idea is to express a robust matching surface function in terms of correlation operations. speed is obtained from computing correlations in the frequency domain. different sized images and arbitrary shapes may be matched. the method outputs a matching surface representing the quality of match at each translatory position. experimental results of a comparison with the standard method of phase correlation are shown.
improving cut detection in mpeg videos by gop-oriented frame difference normalization. the detection of abrupt shot changes ("cuts") in videos is a basic step in video content analysis. many cut detection algorithms based on histogram differences have been proposed in the literature, and it has been shown for the mpeg (moving picture experts group) domain that using small sub-images, namely approximated dc-frames, is sufficient to achieve very good detection results. in this paper, the characteristics of histogram based difference measurements of mpeg (dc-)frames are analyzed and an effective technique is presented to enhance the performance of cut detection algorithms, called "gop-oriented frame difference normalization" (gop: group of pictures). experimental results for the mpeg-7 video test set will be presented to demonstrate the benefits of our proposal. furthermore, the proposed method is not limited to a particular algorithm but it is applicable to an entire class of cut detection algorithms.
fast face detection with precise pose estimation. we present a fast algorithm for face detection and precise pose estimation. our detection scheme is based on a tree-structured hierarchy of face vs.background classifiers combined with a lazy evaluation strategy which concentrates computation on ambiguous areas of the image. the hierarchy corresponds to successive partitions of the pose parameter space, and thereby provides, at no additional cost, a fine estimate of the 2d pose of detected faces.
estimation of arbitrary camera motion in mpeg videos. several algorithms have been proposed to solve the problem of camera motion estimation in digital videos. however, the distinction between translation along the x-axis (y-axis) and rotation around the y-axis (x-axis) has only rarely been considered, and no approach of this kind is known to us for the mpeg domain. in this paper, we present such an algorithm for camera motion estimation in mpeg videos. for performance reasons it is reasonable to extract motion vectors directly from the compressed stream. however, since motion vectors are optimal with respect to compression, they often do not model real motion adequately and can thus be considered as "outliers" with respect to camera motion estimation. consequently, an outlier removal algorithm is incorporated into our approach to solve this problem. furthermore, we have investigated the minimum number of motion vectors required to obtain satisfactory results. comprehensive experiments with 32 video clips demonstrate the performance of the proposed approach.
using texture-based symbolic features for medical image representation. at present time the internet has become a major source of information and a powerful didactic tool. furthermore, the development of digital equipment, allows to acquire and store large quantities of medical data, including images. in the context of the cismef on-line health-catalogue, our work is centered on the automatic categorization of medical images according to their visual content, for further indexation and retrieval tasks. the aim of the present study is to assess the performance of a new image symbolic descriptor for medical modality, anatomic region and view angle image categorization. this descriptor is issued from the unsupervised partition of statistical and texture image subblock representations. a medical image database of 10322 images from 33 classes was ground-truthed by a domain expert. despite the complexity and variability of medical images, the compact symbolic representation approach proposed in this paper achieves high recognition rates. thus, using knn classifiers, we obtain an average precision of 83% and a top performance of 91.19%.
text detection from natural scene images: towards a system for visually impaired persons. we propose a system that reads the text encountered in natural scenes with the aim to provide assistance to the visually impaired persons. this paper describes the system design and evaluates several character extraction methods. automatic text recognition from natural images receives a growing attention because of potential applications in image retrieval, robotics and intelligent transport system. camera-based document analysis becomes a real possibility with the increasing resolution and availability of digital cameras. however, in the case of a blind person, finding the text region is the first important problem that must be addressed, because it cannot be assumed that the acquired image contains only characters. at first, our system tries to find in the image areas with small characters. then it zooms into the found areas to retake higher resolution images necessary for character recognition. in the present paper, we propose four character-extraction methods based on connected components. we tested the effectiveness of our methods on the icdar 2003 robust reading competition data. the performance of the different methods depends on character size. in the data, bigger characters are more prevalent and the most effective extraction method proves to be the sequence: sobel edge detection, otsu binarization, connected component extraction and rule-based connected component filtering.
a smale-like decomposition for discrete scalar fields. in this paper, we address the problem of representing the structure of the topology of a d-dimensional scalar field as a basis for constructing a multiresolution representation of the structure of such a field. to this aim, we define a discrete decomposition of a triangulated d-dimensional domain, on whose vertices the values of the field are given. we extend a smale decomposition, defined by thom and smale for differentiable functions, to the discrete case, to what we call a smale-like decomposition. we introduce the notion of discrete gradient vector field, which indicates the growth of the scalar field and matches with our decomposition. we sketch an algorithm for building a smale-like decomposition and a graph-based representation of this decomposition. we present results for the case of two-dimensional fields.
invariants to convolution with circularly symmetric psf. we introduce a new class of moment-based features invariant to rotation and to convolution with an unknown point-spread function having circular symmetry. unlike the invariants published earlier, they comprise both even and odd order moments, which increases their discrimination power and robustness.
automatic fish age estimation from otolith images using statistical learning. in this paper, we investigate the use of statistical learning techniques for fish age estimation from otolith images. the core of this study lies in the definition of relevant image-related features. we rely on the characterization of a 1d signal summing up the image content within a predefined area of interest. fish age estimation is then viewed as a multi-class classification issue using neural networks and svms. a procedure based on demodulation and remodulation of fish growth patterns is used to improve the generalization properties of the trained classifiers. we also investigate the combination of additional biological and shape features to the image-related ones. the performances are evaluated for a database of several hundred of plaice otoliths.
content-based image retrieval using fourier descriptors on a logo database. a system that enables the pictorial specification of queries in an image database is described. the queries are comprised of rectangle, polygon, ellipse, and b-spline shapes. the queries specify which shapes should appear in the target image as well as spatial constraints on thedistance between them and their relative position. the retrieval process makes use of an abstraction of the contour of the shape which is invariant against translation, scale, rotation, and starting point that is based on the use of fourier descriptors. these abstractions are used in a system to locate logos in an image database. the utility of this approach is illustrated using some sample queries.
face recognition from video using active appearance model segmentation. face recognition from video can be improved if good face segmentation of the subject under test is achieved. many video based face recognition rely on simple background modeling and coarse alignment strategies for segmentation. this work presents a face recognition from video framework based on using active appearance models (aam) to achieve accurate face segmentation and consistent shape free representation across a video sequence. the segmentation provided by the aam can be effectively normalized (morphed) to a mean shape. the resulting subimage can then be delivered to conventional face recognition from video algorithms for robust classification. we present preliminary results on a dataset of 17 individuals and outline the problems encountered in this approach.
hierarchical object indexing and sequential learning. this work is about scene interpretation in the sense of detecting and localizing instances from multiple object classes. we concentrate on object indexing: generate an over-complete interpretation - a list with extra detections but none missed. pruning such an index to a final interpretation involves a global, often intensive, contextual analysis. we propose a tree-structured hierarchy as a framework for indexing; each node represents a subset of interpretations. this unifies object representation, scene parsing, and sequential learning (modifying the hierarchy as new samples, poses and classes are encountered). then we specialize to learning - designing and refining a binary classifier at each node of the hierarchy dedicated to the corresponding subset of interpretations. the whole procedure is illustrated by experiments in reading license plates.
edge model based segmentation. segmentation is an important operation in image analysis. it is employed to extract interested objects from an image under test. much research work has been performed and the optimal graph theoretic approach to data clustering is one of the promising methods. however, when the image size is large, the graph size will be very large. as a result the graph becomes complex and its processing is computation demanding. in this paper, we propose to simplify the problem by pre-segmenting the image under test using an edge model before applying the optimal graph theoretic approach to data clustering. the experimental results show that the proposed method can efficiently segments an image with satisfactory results.
the using of thermal images of palm-dorsa vein-patterns for biometric verification. a novel personal verification method using the thermal images of palm-dorsa vein-patterns is presented in this paper. the characteristics of the proposed method are that no prior knowledge about the objects is necessary and the parameters can be set automatically. in our work, an infrared (ir) camera is adopted as the input device to capture the thermal images of palm-dorsa. according to the heat conduction law (the fourier law), multiple features can be extracted from each feature points of the vein-patterns (fpvps). multiresolution representations of images with fpvps are obtained using multiple multiresolution filters (mrfs) that extract the dominant points by filtering miscellaneous features for each fpvp. a hierarchical integrating function is then applied to integrate multiple features and multiresolution representations. we also introduce a logical and reasonable method to select a trained threshold for verification. the experimental results demonstrate that our proposed approach is valid and effective for vein-pattern verification.
combining null space-based gabor features for face recognition. we propose a novel face recognition strategy combining various discriminating gabor features in multi-scales and multi-orientations. a bank of well-chosen gabor filters is applied on the image to construct a group of feature vectors, and then the null space-based lda (nlda) is performed simultaneously on each orientation channel and the original image to give 5 component classifier outputs, which are then combined to increase the final recognition rate. experimental results on the feret database demonstrate the effectiveness and flexibility of our proposed method.
laser stripe peak detector for 3d scanners. a fir filter approach. the accuracy of a 3d reconstruction using laser scanners is significantly determined by the detection of the laser stripe. since the energy pattern of such a stripe corresponds to a gaussian profile, it makes sense to detect the point of maximum light intensity (or peak) by computing the zero-crossing point of the first derivative of such gaussian profile. however, because noise is present in every physical process, such as electronic image formation, it is not sensitive to perform the derivative of the image of the stripe in almost any situation, unless a previous filtering stage is done. considering that stripe scanning is an inherently row-parallel process, every row of a given image must be processed independently in order to compute its corresponding peak position in the row. this paper reports on the use of digital filtering techniques in order to cope with the scanning of different surfaces with different optical properties and different noise levels, leading to the proposal of a more accurate numerical peak detector, even at very low signal-to-noise ratios.
using statistical shape priors in geodesic active contours for robust object detection. a novel statistical shape prior model based on level set representations is proposed in this paper for robust object detection by geodesic active contours. this prior model is able to accommodate multiple shape states of objects. the level set representations (signed distance map) of the shapes are considered to form distinct clusters in a low dimensional feature subspace and a gaussian mixture model (gmm) is employed to fit the feature distribution in the subspace. a bayesian classifier is used to assign the currently detected object to the most similar shape cluster. a shape prior is then constructed from the statistical properties of that cluster and is used to drive the geodesic active contour curve towards it in the subsequent evolution. experiments demonstrate the effectiveness of our shape prior model.
improvement of ica based probability density estimation for pattern recognition. probability density function (pdf) estimation is a fundamentally important problem for statistical pattern recognition. independent component analysis (ica) can be applied to the feature vectors so that the pdf estimation of a high dimensional vector can be converted to the pdf estimation of several 1-dimensional variables. but in practice we find that this pdf is in poor generalization ability for pattern classification because of the implied noise. so this paper proposes an improvement of ica based pdf estimation method. a latent variable model is built to separate the noise from the feature vector so that the pattern information and the noise can be dealt with respectively. based on the latent variable model, a modified ica based pdf is deduced. the validity of our proposed method is demonstrated by the experiments of off-line handwritten numeral recognition.
event classification for automatic visual-based surveillance of parking lots. in this paper, a visual-based surveillance system for real-time event detection and classification in parking lots is presented. the focus is on the high-level part of the system, i.e., the event recognition (er) module, which is able to analyze two kinds of events (i.e., simple and composite events) that occur in the observed scene. simple events are represented by single moving objects, e.g., vehicles, pedestrians, etc. while a composite event is represented by a set of temporally consecutive simple events, e.g., people exiting a car just entered in the parking area. an adaptive high order neural tree (ahnt) is applied for recognizing both objects and complex events.
a novel approach to automatically extracting basic units from chinese sign language. in sign language recognition, using subwords instead of whole signs as basic units will scale well with increasing vocabulary size. however, there are no subwords defined in the signs' lexical forms. how to automatically extract subwords is a challenging issue. in this paper, a novel approach is proposed to automatically extract these subwords from chinese sign language(csl). signs can be broken down into several segments using hidden markov models in which each state represents one segment. temporal clustering algorithm is presented to extract subwords from these segments. the 238 subwords are automatically extracted from 5113 signs, and they can be used as the basic units for large vocabulary csl recognition with good performance.
real-time range imaging for dynamic scenes using colour-edge based structured light. a novel real time 3d-data acquisition system for highly dynamic scenes is presented. it is based on colour coded structured light using a single projection pattern. existing systems utilising this approach are usually limited to scenes with neural surfaces or not very robust. the presented system overcomes these shortcomings by using an innovative approach for recognising the projected pattern based on colour edges. the low-cost system is integrated using off-the-shelf components only. experimental results are presented including a report on the successful use of the system with a 3d gesture recognition application.
learning sample subspace with application to face detection. in this paper, we present a novel maximum correlation sample subspace method and apply it to human face detection [detecting face in images: a survey] in still images. the algorithm starts by projecting all the training samples onto each sample and selects the sample with the largest accumulated projection as the first subspace base vector. after a base vector is selected, all other samples are made orthogonal to the current base vector and which is in turn used to form the training samples for learning the next base vector. each subspace base is created by a one-pass process and therefore the method is computationally very efficient. these bases form a transform and we use it to derive discriminative features for face detection by training a support vector machine classifier. we perform testing on both cmu and mit face detection image data sets. extensive experiments demonstrate that our results are comparable to those published in state of the art literature.
ica filters for lighting invariant face recognition. the use of ica (independent component analysis) for the construction of filters for lighting invariant face recognition will be investigated. ica is used to provide filters which are applied as a pre-processing step to a low dimensional pca subspace representation of the databases. test faces imaged under varying illumination from a face database are classified using a support vector classifier. the ica pre-filter recognition results are compared against those using log (laplacian of gaussian) filter of various spatial resolutions and no pre-filtering. the ica pre-filters are shown to be very effective at selectively reducing the effect of illumination variance in object and face recognition without the need for tuning the filters to the orientations and spatial resolutions present in the images.
car/non-car classification in an informative sample subspace. in this paper, we present a method for data classification with application to car/non-car objects. we first developed a sample based car/non-car maximal mutual information low dimensional subspace. we then trained a support vector machine (svm) in this subspace for the detection of cars. using publicly available standard training and testing data sets, we demonstrated that our car detector gave very competitive performances.
a comparison of pca and ica for object recognition under varying illumination. an experiment is performed to evaluate the ability of two different subspace methods to recognize objects under different illumination conditions. principal component analysis (pca) and independent component analysis (ica) are compared for classifying 25 different objects with varying degrees of specularity under different illumination. each object was sampled under three widely different lighting conditions to form a set of training images used to createsubspaces with dimensions ranging from 10 to 30 basis vectors. the efficacy of ica and pca to correctly classify the objects was tested using two test images for each object under unique lighting conditions not included in the training set. the results were also determined when the images were pre-filtered with a laplacian of gaussian (log) filter. results show that ica techniques show promise for object recognition under varying illumination conditions.
combinatorial surface integration. graph-spectral surface integration techniques construct an integration path assuming that the surface contains a path along which the integration error is minimal. this paper presents a generalisation that uses minimum spanning trees of the weighted grid graph of surface normals, which scales with no need for surface segmentation. the problem of choosing an integration path is reduced to defining a local weight function. the method is assessed at weighting human face surface normals with geometric and information-theoretic functions of local support.
detection and recognition of lung abnormalities using deformable templates. automatic detection and recognition of lung cancer during mass screening of spiral computer tomographic (ct) chest scans is one of most important problems of todays medical image analysis. we propose an algorithm for isolating lung abnormalities (nodules) from arteries, veins, bronchi, and bronchioles after all these objects have been already separated from the surrounding anatomical structures. the separation is presented elsewhere, and this paper focuses on nodule detection using deformable 3d and 2d templates describing typical geometry and gray level distribution within the nodules of the same type. the detection combines normalized cross-correlation template matching by genetic optimization and bayesian post-classification. experiments with 200 spiral low dose ct (ldct) scans confirm the accuracy of our approach.
motion features from lip movement for person authentication. this paper describes a new motion based feature extraction technique for speaker identification using orientation estimation in 2d manifolds. the motion is estimated by computing the components of the structure tensor from which normal flows are extracted. by projecting the 3d spatiotemporal data to 2-d planes we obtain projection coefficients which we use to evaluate the 3-d orientations of brightness patterns in tv like image sequences. this corresponds to the solutions of simple matrix eigenvalue problems in 2d, affording increased computational efficiency. an implementation based on joint lip movements and speech is presented along with experiments which confirm the theory, exhibiting a recognition rate of 98% on the publicly available xm2vts database.
a low-dimensional illumination space representation of human faces for arbitrary lighting conditions. in this paper, a method for low-dimensional illumination space representation (ldisr) of human faces is proposed. the method can not only synthesize a virtual face image when given lighting condition but also estimate lighting conditions when given a face image. the ldisr is based on the observation that 9 basis point light resources can represent almost arbitrary lighting conditions for face recognition application and different human faces have the similar ldisr. the advantage of ldisr is that it can be trained on images of one human face and can be used for all human faces. the experiments on image reconstruction indicated the efficiency of ldisr.
a similarity measure based on hausdorff distance for human face recognition. a similarity measure based on hausdorff distance (smbhd) for face recognition is proposed in this paper. different from the conventional hausdorff distance based measures, the proposed measure can provide not only the dissimilarity information but also the similarity information of two objects to compare them. the added similarity information can especially better the discriminating capability of an object recognition system for similar objects such as faces with variant lighting condition and facial expression. in order to evaluate the performance of a face recognition system using the proposed similarity measure based on hausdorff distance (smbhd), the face images included in the ar, orl, and yale face databases have been used. the experimental results show that the system has a better performance than the systems based on conventional hausdorff distance measures and the eigenfaces approaches.
rigorous accuracy bounds for calibrated stereo reconstruction. we deal with the problem of obtaining rigorous bounds to the position of 3-d points computed by stereo triangulation when both the camera matrix and the image points are affected by uncertainty. by "rigorous bounds" we mean that the true unknown 3-d points are guaranteed to lie within the given intervals. to this end we first model the calibration process by assuming a bounded error in the localization of the reference points in the image, then we narrow the entries of the camera matrix. finally, we apply triangulation and obtain cuboids that bound points coordinates. we concentrated two state-of-the art methods for the solution of linear system of equations, namely intlab's and shary's methods. empirical comparison shows that the latter always provides sharper error bounds, in this application.
large scale feature selection using modified random mutation hill climbing. feature selection is a critical component of many pattern recognition applications. there are two distinct mechanisms for feature selection, namely the wrapper methods and the filter methods. the filter methods are generally considered inferior to the wrapper method, however wrapper methods are computationally more demanding than filter methods. one of the popular methods for wrapper-based feature selection is random mutation hill climbing. it performs a random search over the feature space to derive the optimal set of features. we will describe two enhancements to this algorithm, one that will improve its convergence time, and the other that will allow us to bias the results towards either higher accuracy or lower final feature space dimensionality. we will apply the algorithm to a real-world massive-scale feature selection problem involving the image classification problem associated with suppressing automobile airbags for children. we will provide classification results on an image database of nearly 4,000 images that indicate the advantages of the proposed method.
a new approach for relevance feedback through positive and negative samples. relevance feedback has recently emerged as a solution to the problem of providing an effective response to a similarity query in an images retrieval system based on low-level information such as color, texture and shape features. this paper describes an approach for learning an optimal similarity metric based on the analysis of relevant and non-relevant information given by the user during the feedback process. a positive and a negative space are determined as an approximation of the examples given by the user. the relevant region is represented by a kl subspace of positive examples and is iteratively updated at each feedback iteration. the non-relevant region is modeled by a mkl space, which better characterizes the variety of negative examples, which very likely could belong to more than one class. the search process is, then, formulated as a classification problem, based on the calculation of the minimal distance to the relevant or non-relevant region.
reward-punishment editing. in this work a novel editing technique is proposed. the basic idea of the algorithm is to reward patterns that contribute to a correct classification and to punish those that provide a wrong one. reward-punishment is performed according to two criteria: the former operates at very local level while the latter analyses the training set at coarser scales in a multi-resolution fashion. a score is calculated for each pattern according to the two criteria and patterns whose score is lower than a predefined threshold are edited out. experiments carried out on two difficult classification problems show the superiority of this method with respect to other well known approaches.
a wrapper-based approach to image segmentation and classification. the traditional processing flow of segmentation followed by classification in computer vision assumes that the segmentation is able to successfully extract the object of interest. this is extremely difficult without any prior knowledge about the object that is being extracted from the scene. we propose a method of segmentation that uses the classification subsystem as an integral part of the segmentation, which will provide contextual information regarding the objects to be segmented. we note that traditional segmentation can then be viewed as a filter operating on the image independently of the classifier, much like the filter methods for feature selection. our motivation for integrating segmentation and classification follows the wrapper methods of feature selection. in the wrapper methods for feature selection, the classifier is an integral part of the selection process and serves as the metric to decide the best feature set. in the same way, we wrap the segmentation and classification together, and use the classification accuracy as the metric to determine the best segmentation. we show the performance of wrapper-based segmentation on real-world and complex images of automotive vehicle occupants.
rotation-invariant neoperceptron. approaches based on local features and descriptors are increasingly used for the task of object recognition due to their robustness with regard to occlusions and geometrical deformations of objects. in this paper we present a local feature based, rotation-invariant neoperceptron. by extending the weight-sharing properties of convolutional neural networks to orientations, we obtain a neural network that is inherently robust to object rotations, while still being capable to learn optimally discriminant features from training data. the performance of the network is evaluated on a facial expression database and compared to a standard neoperceptron as well as to the scale invariant feature transform (sift), a-state-of-the-art local descriptor. the results confirm the validity of our approach.
natural, salient image patches for robot localization. this paper addresses a major problem in mobile robot localization.in most approaches to simultaneous localization and mapping (slam) only line and point features are used which easily lead to ambiguities in loop-closing and global relocalization.in this work we propose to use natural, salient image patches as additional high discriminative landmarks to aid in unclear localization scenarios which might occur in modern highly symmetric indoor environments.a new method of landmark extraction is presented as well as a matching method for storing and retrieving the landmarks in a location database.
content analysis in document images: a scale space approach. with the growing interest in automatic transformation of paper document to its electronic version, geometrical and logical structures have become an active research area for a decade. nowadays, kernel scale space has been widely adopted as the most promising multi-scale image document analysis method. yet still, traditional methods using scale space approach has its limitations: they are useful mostly on character extraction and they carry alarge computational load. in view of these limitations, this paper proposes a new approach using scale space in order to analyse the composite document content. in the proposed method, scale space transform is used to decompose an image into different scaled objects where the scale value is used for detecting progressively finer objects: text, line drawing, logo, and image, with encouraging results on real-life data.
learning pairwise similarity for data clustering. each clustering algorithm induces a similarity between given data points, according to the underlying clustering criteria. given the large number of available clustering techniques, one is faced with the following questions: (a) which measure of similarity should be used in a given clustering problem? (b) should the same similarity measure be used throughout the d-dimensional feature space? in other words, are the underlying clusters in given data of similar shape? our goal is to learn the pairwise similarity between points in order to facilitate a proper partitioning of the data without the a priori knowledge of k, the number of clusters, and of the shape of these clusters. we explore a clustering ensemble approach combined with cluster stability criteria to selectively learn the similarity from a collection of different clustering algorithms with various parameter configurations.
coarse detection and fine color description for region-based image queries. in content-based image retrieval systems, region-based queries allow more precise search than global ones. the user can retrieve similar regions of interest regardless their background in images.the definition of regions in thousands of generic images is a difficult key point, since it should not need user interaction for each image, and nevertheless be as close as possibleto regions of interest (to the user).in this paper we fir st present a technique of unsupervised coarse detection of regions which improves their visual specificity . the segmentation scheme is based on the classification of local distributions of quantized colors (ldqc). the competitive agglomeration (ca) classification algorithm, which has the advantage to automatically determine the optimal number of classes, is used.the second key point is the region description which must be finer for regions than for images. we present a region descriptor of fine color variability: the adaptive distribution of color shades (adcs). this color description is finer and more accurate than existing region color descrip-tors.
simple shadow remova. given the location of shadows, how can we obtain highquality shadow-free images? several methods have been proposed so far, but they either introduce artifacts or can be difficult to implement. we propose here a simple method that results in virtually error and shadow-free images in a very short time. our approach is based on the insight that shadow regions differ from their shadow-free counterparts by a single scaling factor. we derive a robust method to obtain that factor. we show that for complex scenes - containing many disjointed shadow regions- our new method is faster and more robust than others previously published. the method delivers good performance on a variety of outdoor images.
3d shape reconstruction of template models using genetic algorithms. we present in this communication a method, which enables to fit a 3d object defined by a functional representation (frep) to a dataset of 3d points on its surface. a parametric frep model sketching the point-set is fitted to the point-set. the best fitted parameters of the model are obtained by using a genetic algorithm, well known for its interesting properties in non-linear optimization. the efficiency of the approach is illustrated for reverse engineering applications.
school level recognition from children's drawings and writings. this paper presents part of a work aiming at building a tool for the detection of graphomotor difficulties involving disorders in the writing of children. we have defined an experimental protocol, containing exercises, like copying figures or writing sentences under different conditions. it allows to measure simple aspects of graphomotor skill up to complex ones. a great number of features were obtained from on-line children productions. we focus here on the method we used to select low-level features that can describe the automation level of graphic activity. it is based on hierarchical clustering of features and a sequential forward selection. every exercise is represented by two relevant features at least. we show that, in most cases, the selected features allow to recognize the school level of children having a regular schooling but to discriminate children with scholar difficulties as well.
discontinuity-based simplification of free form surface from a range image. this paper improves an existing method for more accurate simplification of free form surface represented as dense points. the main improvement lies in two aspects: one is the introduction of a novel transformation of curvatures, the other is to propose sampling points using both curvature information and curvature variation information. the experimental results based on real images show that the original object surface has been better approximated and the majority of the surface discontinuities have been better preserved with considerably few sampled (5%) data points.
condensation tracking through a hough space. recent work has shown tracking groups of lines throughthe parameter space represented by a hough accumulatorarray to be efficient and insensitive to both occlusion andchanges in illumination. previous methods [object tracking througha hough space, tracking in a hough space with an extended kalman filter]have, however, been less robust in the presence of distractions. distractions are a challenge to trackers of all types, but the problem is heightened in the hough-based approach as short collinear segments give the same response as an equal length connected line. we describe the application of the condensation algorithm to tracking peaks through a hough accumulator array, producing a tracking technique that is efficient and robust under illumination changes, occlusion and distractions.
segmentation and denoising via an adaptive threshold mumford-shah-like functional. this paper introduces an adaptive threshold algorithm based on variational methods which generalizes the mumford-shah and chan-vese functionals. it assumes a piecewise smooth model of the image and a closed contour, realized as the zero level set of a function. this functional is built upon an adaptive threshold surface coupled with the smoothed image. the algorithm uses the image boundaries found during the process of calculating the adaptive threshold surface to also smooth the image while preserving object boundaries, thus also improving the thresholding result. the resulting adaptive threshold surface provides a good approximation of the illumination function and thus can also be used to flatten the image. this method provides good smoothing results even in cases where the image can't be segmented using adaptive thresholding techniques.
membershipmap: data transformation based on membership aggregation. we propose a new data-driven transformation that facilitates many data mining, interpretation, and analysis tasks. our approach, called membershipmap, strives to extract the underlying sub-concepts of each raw attribute, and uses the orthogonal union of these sub-concepts to define a new space. the sub-concept soft labels of each point in the original space determine the position of that point in the new space. since sub-concept labels are prone to uncertainty inherent in the original data and in the initial extraction process, a combination of labeling schemes that are based on different measures of uncertainty will be presented. in particular, we introduce the crispmap, softmap, and possibilisticmap. we show that the membershipmap can be used as a flexible pre-processing tool to support such tasks as: sampling, data cleaning, and outlier detection.
p-channels: robust multivariate m-estimation of large datasets. in this paper we introduce a new technique that allows to estimate modes of a high-dimensional probability density function with linear time-complexity in the number of dimensions and the number of samples. the method can be implemented in an order-independent incremental way, such that the space-complexity is linear in the number of dimensions and the number of modes. the number of required samples to get reliable estimates depends linearly on the number of dimensions even if we replace the assumption of independent stochastic variables with the weaker assumption of data clustered in submanifolds. these submanifolds need not to be known, but smoothness assumptions are made. the new technique is based on representing data in what we call p-channels.
projection and visualization based on synchronization of coupled oscillators. this paper introduces a tool for mapping high dimensional data to a low-dimensional space by combining concepts from clustering and synchronization of pulse-coupled oscillators. each data point is represented by an integrate-and-fire oscillator which is characterized by a phase variable. using an appropriate coupling function, we show that the relative values of the phases evolve to reflect the proximity of the data in the original space. as a result, the oscillators phases could be used as a 1-d representation of the original space. to generate a 2-d phase space, we apply the synchronization procedure twice with different resolution parameters or different distance measures. the proposed approach is used to visualize the classical iris data and two collection of images.
fingerprint indexing using ridge invariants. indexing large fingerprint databases is an important and challenging problem. in this paper, an invariant-based fingerprint indexing scheme is proposed. minutia and surrounding ridges are combined to form a substructure. the invariants describe binary relations between substructures. experimental results on fvc2002 database demonstrate the validity of the proposed algorithm.
building a multi-modal thesaurus from annotated images. we propose an unsupervised approach to learn associations between low-level visual features and keywords. we assume that a collection of images is available and that each image is globally annotated. the objective is to extract representative visual profiles that correspond to frequent homogeneous regions, and to associate them with keywords. these labeled profiles would be used to build a multi-modal thesaurus that could serve as a foundation for hybrid navigation and search algorithms. our approach has two main steps. first, each image is coarsely segmented into regions, and visual features are extracted from each region. second, the regions are categorized using a novel algorithm that performs clustering and feature weighting simultaneously. as a result, we obtain clusters of regions that share subsets of relevant features. representatives from each cluster and their relevant visual and textual features would be used to build a thesaurus. the proposed approach is validated using a collection of 1169 images.
fingerprint representation and matching in ridge coordinate system. fingerprints are generally represented and analyzed in cartesian or polar coordinates. in this paper, however, fingerprints are represented and analyzed in a novel coordinate system, called ridge coordinate system (rcs), which is based on a ridge and an oriented point on the ridge. using rcss based on lots of ridges, we obtain a robust representation scheme of the ridge (skeleton) image of a fingerprint. based on this representation, an alignment-based fingerprint matching algorithm is proposed. experimental results on fvc2002 demonstrate the validity of the proposed algorithm.
recognizing emphysema- a neural network approach. an accurate and fully automatic method for detecting and quantifying emphysema in ct-images is presented. the method is based on an image preprocessing step followed by a neural network classifier trained to separate true emphysema from artifacts. the proposed approach is shown to be superior to an established method when applied on real patient data.
chinese handwriting recognition using hidden markov models. hidden markov model (hmm) has been applied to the problem of machine recognition of chinese handwriting. the character image is segmented into a number of local regions and feature vectors of these regions are extracted. the feature vectors are then used to get the observations for the hmm. the states of the hmm are to reflect the characteristic space structures of the character and its identities are obtained through the training samples usingsome algorithms. two kinds of hmm are built and two more simple nearest neighbor classifiers (nn) based on the vector quantification process in the discrete hmm are employed. the combination of the classifiers is presented. five kinds of features used to get the observations have been tried and three algorithms are adopted to determine the training process. the experimental result indicates the promising prospect of this approach.
pay attention when selecting features. in this paper, we propose a new, hierarchical approach to landmark selection for simultaneous robot localization and mapping based on visual sensors: a biologically motivated attention system finds salient regions of interest (rois) in images, and within these regions, harris corners are detected. this combines the advantages of the rois (reducing complexity, enabling good redetactability of regions) with the advantages of the harris corners (high stability). reducing complexity is important to meet real-time requirements and stability of features is essential to compute the depth of landmarks from structure from motion with a small baseline. we show that the number of landmarks is highly reduced compared to all harris corners while maintaining the stability of features for the mapping task.
a novel fingerprint matching scheme based on local structure compatibility. most minutiae-based matching algorithms confront with the challenge of missing and fake minutiae, and especially the non-linear distortion. many efforts have been made to cope with these problems while relatively slow improvements achieved. in this paper, we proposed a novel minutiae-based matching scheme which introduced a concept of compatibility to the minutiae triangle structures. and based on the compatibility, we further adopted a relaxation process to adjust the similarity matrix of the minutiae triangle cells between the query and template images. to reduce the effect of non-linear distortion evidently, an extended searching step independent of any linear models was proposed. results obtained on the fvc2004 b1_a show that the proposed algorithm overcomes the influence of missing and fake minutiae, and meanwhile decreases the time cost of matching saliently.
automatic segmentation of the knee bones using 3d active shape models. this paper presents an automated segmentation approach for mr images of the knee bones. the bones are the first stage of a segmentation system for the knee, primarily aimed at the automated segmentation of the cartilages. the segmentation is performed using 3d active shape models (asm), which are initialized using an affine registration to an atlas. the 3d asms of the bones are created automatically using a point distribution model optimization scheme. the accuracy and robustness of the segmentation approach was experimentally validated using an mr database of fat suppressed spoiled gradient recall images.
iris localization with dual coarse-to-fine strategy. iris-based personal recognition is highly dependent on the accurate iris localization. in this paper, an effective and efficient iris localization algorithm is proposed to overcome the drawback of the traditional localization methods which are time-consuming and sensitive to the occlusion caused by eyelids and eyelashes. the coarse-to-fine strategy is deployed in both the inner boundary localization and the outer boundary localization. in the coarse localization of the inner boundary, the lower contour of the pupil is introduced to estimate the parameters of the pupil since it is stable even when the iris image is seriously occluded. while in the coarse localization of the outer boundary, the average intensity signals on both sides of the pupil are utilized to estimate the parameters of the sclera after the fine localization of the inner boundary. in the fine stage, the hough transform is adopted to localize both boundaries precisely with the gradient information. experimental results indicate that the proposed method is more effective and efficient.
confidence guided progressive search and fast match techniques for high performance chinese/english ocr. in the past several years, we've been developing a high performance ocr engine for machine printed chinese/english documents. in this paper, we present two innovative techniques that contribute to the high efficiency in recognition of the mixed chinese/english text line. they are (1) a progressive search strategy based on character verification, and (2) a tree-based fast match technique with a confidence-guided adaptive stopping mechanism. the efficacy of the proposed techniques is confirmed by experiments in a benchmark test.
object recognition using local information content. object identification from local information has recently been investigated with respect to its potential for robust recognition, e.g., in case of partial object occlusions, scale variation, noise, and background clutter in detection tasks. this work contributes to this research by a thorough analysis of the discriminative power of local appearance patterns and by proposing to exploit local information content for object representation and recognition. in a first processing stage, we localize discriminative regions in the object views from a posterior entropy measure, and then derive object models from selected discriminative local patterns. object recognition is then applied to test patterns with associated low entropy using an efficient voting process. the method is evaluated by various degrees of partial occlusion and gaussian image noise, resulting in highly robust recognition even in the presence of severe occlusion effects.
a statistical assembled model for segmentation of entire 3d vasculature. we introduce a novel statistical deformable model called samtus for the segmentation of soft tissue tubular structures. the model is composed of an assembly of statistically deformable tubular segments whereby the junctions of the tubular branches are used as landmarks for constructing the underlying point distribution model. the flexibility of samtus is governed by two independent statistical models that describe the axis variation (statistical axis model, or sam) and the cross-sectional radius variation (statistical surface model, or ssm) respectively. we also propose a samtus based segmentation algorithm for an entire tubular structure. the approach has been applied to the segmentation of the three-dimensional vasculature of zebrafish embryo. the efficiency and robustness of this method is evaluated through quantification results on both sectional level and volumetric level.
boosted band ratio feature selection for hyperspectral image classification. band ratios have many useful applications in hyperspectral image analysis. while optimal ratios have been chosen empirically in previous research, we propose a principled algorithm for the automatic selection of ratios directly from data. first, a robust method is used to estimate the kullback-leibler divergence (kld) between different sample distributions and evaluate the optimality of individual ratio features. then, the boosting framework is adopted to select multiple ratio features iteratively. multiclass classification is handled by using a pairwise classification framework. the algorithm can also be applied to the selection of discriminant bands. experimental results on both simple material identification and complex land cover classification demonstrate the potential of this ratio selection algorithm.
self-validated and spatially coherent clustering with net-structured mrf and graph cuts. self-validation and efficient global optimization are two important objectives for feature space clustering. the gibbs energy minimization of markov random field (mrf) provides a general framework for the clustering problem. however, the large computational burdenmakes mostmrfbased methods cannot efficiently achieve these two targets simultaneously. in this paper, we propose a fast clustering approach which is self-validated and guarantees stepwise global optimum. we use the net-structured mrf (ns-mrf) to model the feature space and present an iterative cluster evolution algorithm. for each iteration, the cluster evolving is chosen from three hypotheses, i.e., cluster remaining, cluster merging or cluster splitting, in terms of energy minimization. graph cuts are used to obtain the optimal binary splitting while taking spatial coherence into account. we terminate the evolution process when the whole energy of ns-mrf stops decreasing, thus solve the validation problem. we also provide experimental results and compare our approach with the state of arts.
a novel segmentation and recognition algorithm for chinese handwritten address character strings. this paper presents a new method for segmenting and recognizing chinese handwritten address character strings. first, a dissection algorithm is applied to over-segment string image into radical series so that the correct segmentation could be achieved by merging those radicals according to the correct merging path. then, the method synthesizes layout analysis, isolated character classifier and bigram language model to find the best merging path and the best recognition result. the classifier used in this paper will give every isolated character image ten recognition candidates, each with corresponding recognition confidence. the parameter of bi-gram model is obtained from address database which contains more than one hundred thousand address items. in experiments on 946 mail images, the proposed method achieves correct rate of 87.2 percent.
vision-based preceding vehicle detection and tracking. this paper presents a preceding vehicle detection and tracking system by using support vector machine- based particle filtering (svmpf). svmpf integrates the support vector machine (svm) score with sampling weights. the sample weights, which are used to construct a probability distribution of samples, are measured by the svm score. once the vehicle is detected and tracked, it changes to svm tracking mode which is simpler than the previous svmpf mode. in the experiments, we demonstrate that our system can track the preceding vehicles under different whether conditions.
a clustering-based algorithm for extracting the centerlines of 2d and 3d objects. this paper presents a new algorithm for extracting the centerlines of 2d and 3d objects, based on clustering. the algorithm computes the centerline from all points of the object in order to remain faithful to the structure of the shape. the idea is to cluster a data set constituted of the points composing the object and their relative distance transforms. the centerline is derived from the set of computed clusters. the proposed method is accurate and robust to noisy boundaries.
content-based image retrieval using gabor-zernike features. content-based image retrieval (cbir) is an important research area for manipulating large amount of image databases and archives. extraction of invariant features is the basis of cbir. this paper focuses on the problem of texture and shape feature extractions. we investigate texture feature and shape feature for cbir by successfully combining the gabor filters and zernike moments (gf+zm). gf is used for texture feature extraction and zm extracts shape features. comprehensive performance evaluation of our method is based on three different databases: face database, fingerprint database, and mpeg-7 shape database. the experimental results demonstrate that gf+zm presents robustness to all of the three databases with the best average retrieval rate while the gf and zm are limited for certain databases. gf is effective for face database and fingerprint database but is weak for mpeg-7 shape database. zm achieves high retrieval rate for face database and mpeg-7 shape database but gives relatively low retrieval rate for fingerprint database.
mixture clustering using multidimensional histograms for skin detection. mixture models are frequently used to fit skin color distributions in various color spaces. however, the high computational cost of the conventional em algorithm makes it intractable for large data sets. in this paper, we propose a novel algorithm for estimating the parameters of mixture models. multidimensional histograms are incorporated into the em framework to group neighboring datapoints and reduce the size of the data set. we adopt this method to build gaussian mixture models of skin color and compare the performance of models with different number of components. further experiments on synthetic data show the efficiency of our method as a general approach to data clustering.
improved 3d head reconstruction system based on combining shape-from-silhouette with two-stage stereo algorithm. in this paper we present a quality improvement algorithm for the system, which models a human head. we have already proposed and applied the hybrid algorithm combining shape-from-silhouette with active stereo to our product of 3d head reconstruction system. our system is characterized by the ability of the reconstruction of the whole shape and texture of the human head, even the black hair parts, while other existing systems cannot do it. feature-based stereo algorithm adopted into our current system is the fast and robust approach. however, the depth data may be sparse and the accuracy depends on how accurate the edge detection is. on the other hand, area-based stereo algorithms generally provide dense depth data and can apply subpixel estimation, but it is comparatively time-consuming and may be inaccurate influenced by the difference of how to reflect the object in each image. to overcome these problems for improving our system practicably, we propose a novel two-stage stereo algorithm. in our algorithm, first, we adopt feature-based approach to get the depth data robustly. next, an interpolation of the depth data is performed to predict the depth data at the unestimated pixels on the edge. finally applying area-based approach and subpixel estimation refine the depth data. in this paper, we describe our hybrid modeling algorithm and two-stage stereo algorithm with some experimental results.
a method for crack detection on a concrete structure. recently, interest in automatic crack detection on concrete structure images for non-destructive inspection has been increasing. in general, there are various noises such as irregularly illuminated conditions, shading, blemishes and divots in the concrete images. these lead to difficulties for automatic crack detection. this paper presents two pre-processings in order to remove such noises for crack detection. first, slight variations like irregularly illuminated conditions and shading are removed from concrete images by the subtraction pre-processing with the smoothed image. secondly, a line filter based on the hessian matrix is used to emphasize line structures associated with cracks. finally, thresholding processing is used to separate cracks from background. the performance of the proposed method is evaluated by roc analysis with 50 real images. the experimental results show that the proposed method is effective for detecting cracks on noisy concrete images.
using multiple graphics cards as a general purpose parallel computer : applications to computer vision. pattern recognition and computer vision tasks are computationally intensive, repetitive, and often exceed the capabilities of the cpu, leaving little time for higher level tasks. we present a novel computer architecture which uses multiple, commodity computer graphics devices to perform pattern recognition and computer vision tasks many times faster than the cpu. this is a parallel computing architecture that is quickly and easily constructed from readily available hardware. it is based on parallel processing done on multiple graphics processing units (gpus). an eigenspace image recognition approach is implemented on this parallel graphics architecture. this paper discusses methods of mapping computer vision algorithms to run efficiently on multiple graphics devices to maximally utilize the underlying graphics hardware. the additional memory and memory bandwidth provided by the graphics hardware provided for significant speedup of the eigenspace approach. we show that graphics devices parallelize well and provide significant speedup over a cpu implementation, providing an immediately constructible low cost architecture well suited for pattern recognition and computer vision.
spine posture estimation method from human images using 3d spine model - computation of the rough approximation of the physical forces working on vertebral bodies. this paper describes a method for estimating a human spine posture from human images using a human spine model that is possible to compute the rough approximation of the physical forces working on vertebral bodies. the spine posture estimation model is composed of the vertebral bodies, each of which is modeled as a rigid body, and the intervertebral discs that are modeled as springs. our method uses the positions of the neck and waist in addition to the positions of the head, torso, and arms estimated from the actual human images. the spine model is deformed so as to locate the top and the bottom vertebrae of the spine model to the estimated neck and waist positions. according to the experiments based on one real mr image dataset of one subject person, our methods estimated the positions of the vertebrae within positional shifts of about 6.3 mm and the rotational variation of about 3.1 degrees. we also confirmed the methods calculated the reasonable estimation of the physical forces working on the vertebral body.
object localization/segmentation using generic shape priors. generally object segmentation is an ill-posed problem. approaches that use only plain image information will often fail. to overcome these limitations, prior knowledge (like information of the object contour) can be added to the segmentation process. in this paper, we present a novel generic shape model. we use the expertise from the field of object class recognition, namely a boundary-fragment- model (bfm) as prior knowledge for our level set segmentation approach. commonly, shape models need synthetically generated or pre-segmented training sets that are usually trained on one specific object or a small group of objects. with our new approach we are able to train shape models for whole categories, which makes the segmentation method much more flexible. additionally we overcome the difficulty of the correct initialization and reduce the segmentation effort. experimental results demonstrate the excellent performance of our method on different types of objects (categories).
object recognition using segmentation for feature detection. a new method is presented to learn object categories from unlabeled and unsegmented images for generic object recognition. we assume that each object can be characterized by a set of typical regions, and use a new segmentation method - "similarity-measure segmentation" - to split the images into regions of interest. this approach may also deliver segments, which are split into several disconnected parts, which turns out to be a powerful description of local similarities. several textural features are calculated for each region, which are used to learn object categories with boosting. we demonstrate the flexibility and power of our method by excellent results on various datasets. in comparison, our recognition results are significantly higher than results published in related work.
differentiating between many similar features using relational information in space and scale. we present an approach for differentiating between large numbers of similar feature points. the approach employs a learning strategy which utilizes mutual information to yield relational information or structure between feature points. it learns an ordered list of jumps in space and scale which is used for differentiation. to test the viability and potential of the approach, two datasets containing faces and objects were used.
missing microarray data estimation based on projection onto convex sets method. dna microarrays have gained widespread uses in biological studies. missing values in a microarray experiment must be estimated before further analysis. in this paper, we propose a projection onto convex sets based algorithm to incorporate all a priori knowledge about missing values into the estimation process. two convex sets applicable to all microarray datasets are constructed based on singular value decomposition (svd). in addition, in the two most popular missing value estimation methods knnimpute and svdimpute, there is a trade-off whether to use a specific group of genes for the missing value estimation or to use all genes. our algorithm can provide an optimal combination of these two strategies. experiments show our algorithm can achieve a reduction of 16% to 20% error than the knnimpute and svdimpute methods.
detecting periodically expressed genes based on time-frequency analysis and l-curve method. in microarray experiments, gene expression profiles are often affected by biological properties, such as synchronization loss, and show some non-stationarity. worse still, the microarray data usually suffers from missing values. the conventional spectrum-based methods, when used to identify a subset of genes that are periodically expressed, are degraded by these factors. in this paper, we use the wigner-ville distribution analysis and l-curve method for detection of periodically expressed genes. we provide a graphical exploratory device for assessment of the presence of periodically expressed genes. then, we identify the subset of genes actually involved in the cell cycle using the l-curve method. the experiments on several widely used datasets show that our algorithm can effectively reduce the effect of non-stationarity and missing values problems.
microarray missing data imputation based on a set theoretic framework and biological constraints. gene expressions measured using microarrays usually suffer from the missing value problem. existing missing value imputation algorithms have some limitations. for example, some algorithms have good performance only when strong local correlation exists in data while some provide the best estimate when data is dominated by a global structure. in addition, these algorithms do not take into account many biological constraints in the imputation procedure. in this paper, we propose a set theoretic framework for missing data imputation. we design our algorithm by taking into consideration the biological characteristic of the data and exploit the local correlation and the global correlation structure adaptively. experiments show that our algorithm can achieve a significant reduction of error compared with existing methods.
single camera stereo using planar parallel plate. a system of using a planar parallel plate to achieve single camera stereo has been proposed by nishimoto and shirai[a feature-based stereo model using small disparities]. their work was based onan assumption that the optical axis of the camera was equally displaced by a tilted planar plate with two fixed tilt angles. such assumption is invalid in general. in this paper, we propose a general framework to more accurately model such a single camera system using a planar parallel plate and to deal with arbitrary orientation of the plate. our model has no limitation on the fov of the camera. the proposed framework includes: a mathematical formulation to calculate the displacement of scene points; a plate calibration method to determine the plate intrinsic parameters as well as its extrinsic pose, and a generalized correspondence method which is capable of dealing with arbitrary number of images captured from different plate poses; experimental result is included to validate the proposed framework.
dining activity analysis using a hidden markov model. we describe an algorithm for dining activity analysis in a nursing home. based on several features, including motion vectors and distance between moving regions in the subspace of an individual person, a hidden markov model is proposed to characterize different stages in dining activities with certain temporal order. using hmm model, we are able to identify the start (and ending) of individual dining events with high accuracy and low false positive rate. this approach could be successful in assisting caregivers in assessments of resident's activity levels over time.
an ensemble classifier learning approach to roc optimization. an ensemble learning framework is proposed to optimize the receiver operating characteristic (roc) curve corresponding to a given classifier. the proposed ensemble maximal figure-ofmerit (e-mfom) learning framework meets four key requirements desirable for roc optimization, namely: (1) each classifier in the ensemble can be learned with any specified performance metric for any given classifier design; (2) such a classifier is discriminative in nature and attempts to optimize a particular operating point on the roc curve of the classifier; (3) an ensemble approximation to the overall behavior of the roc curve can be established by sampling a set of operating points; and (4) ensemble decision rules can be formulated by grouping these sampled classifiers with a uniform scoring function. we evaluate the proposed framework using 3 testing databases, the reuters and two uci sets. our experimental results clearly show that e-mfom learning outperforms the state-of-the-art algorithms using wilcoxon-mann-whitney rank statistics.
indexing with musical events and its application to content-based music identification. in this paper a musical event based indexing approach is proposed and its application to content-based music identification is studied. the events, which function as term words used in text retrieval or basic speech units in speech recognition, are inferred using an unsupervised learning algorithm. its differences with the existing methods are in that the learned low-level musicology knowledge and model selection technique are exploited to extract musical events. our experimental analyses on a task of music identification demonstrate that the proposed indexing method is efficient, compact and robust. using a collection of 20-second query segments on the evaluation set, the equal error rate reaches 1.57%. for applications that demand fewer false alarms, we could operate the system at a reduced false acceptance rate of 0.57% while increasing the false rejection rate to 4.58%.
boosting in random subspaces for face recognition. boosting is an excellent machine learning algorithm. in this paper, we propose a novel boosting method boosting in random subspaces. instead of boosting in original feature space, whose dimensionality is usually very high, multiple feature subspaces with lower dimensionality are randomly generated, and boosting is carried out in each random subspace. then the trained classifiers are further combined with simple fusion method. compared with boosting in original feature space, there are two advantages. the first is that the computation complexity of training is reduced, which is obvious. the second is that fusion further improves accuracy, which is verified by our extensive experiments on feret database.
face recognition using most discriminative local and global features. numerous studies in psychophysics and neurophysiological literatures have shown that both local and global features are important for representing and recognizing face. in this paper, a face recognition method, using local and global multi-resolution discriminative information, is proposed. first, face is represented by multi-scale and multiorientation gabor features. then adaboost is employed to learn local feature classifier, and lda (linear discriminant analysis) is used to extract global discriminative information. finally, their recognition results are fused. we evaluate both score and rank based combination schemes on feret and xm2vts face databases. experimental results demonstrate that almost all combination methods improve recognition rates and the best fusion method achieves 99% rank-1 recognition rate on feret fb probe set.
identification of embedded mathematical expressions in scanned documents. efficient extraction of mathematical expressions is considered as an important pre-processing step to apply existing ocr systems to convert scientific papers into their electronic format. in this correspondence, a technique for extracting embedded (or in-line) expressions has been presented. the proposed method for expression extraction initially invokes an existing ocr to recognize the input document. several features including word n-grams (a statistical analysis of a corpus of scientific documents reveals that the word level n-gram profile for sentences containing embedded expressions is quite different from that of the sentences without any expression) are computed on sentence level to spot sentences containing expressions. expression zones are pin pointed by exploiting ocr inability to handle expressions and by using some common typographical aspects followed in typing mathematical expressions. experimental results on a considerable size of dataset show high efficiency of the proposed technique.
lossless compression of textual images: a study on indic script documents. this paper presents a method for lossless compression of indian language textual images. the study is an extension of the previously developed pattern matching and substitution (pm&s)-based method for lossy compression of similar images. here an efficient method for residue coding is proposed and its performance is compared with ccitt gr-iv and jbig. a set of 20 text images for two most popular indic scripts, namely devanagari (hindi) and bengali, is used in the experiment. it is noted that the best results is achieved by pm&s-based approach followed by lzw-based residue coding. this combined scheme gives lossless compression ratio1 of about 37.9.
a multiple-classifier system for recognition of printed mathematical symbols. this paper deals with recognition of printed mathematical symbols. a group of classifiers arranged hierarchically is used to achieve robust recognition of the large number of symbols appearing in expressions. the classifier used at the top level employs stroke-based classification technique to recognize some of the frequently occurring symbols. the second level uses three classifiers to recognize the rest of the expression symbols. different combination techniques have been attempted to integrate the second level classifiers to achieve high recognition accuracy. experiment shows that the proposed approach is quite robust for recognition of a large number of symbols appearing in various expressions.
improvement of ocr accuracy by similar character pair discrimination: an approach based on artificial immune system. artificial immune system (ais) based classification approach is relatively new in the field of pattern recognition (pr). this paper explores this paradigm in the context of a frequently occurring pr problem, namely discrimination of similar shaped character pairs. the problem has been studied in the context of improving the recognition accuracy of ocr (optical character recognition) systems that often make mistakes to properly classify the confusion pairs. a set of binary classifiers is designed following immune principles to achieve pair-wise discrimination. the performance of the proposed approach has been investigated in detail and compared with classification schemes like nearest neighbor and support vector machines (svm)-based approach.
online handwritten indian script recognition: a human motor function based framework. this paper presents the online handwriting recognition for indian scripts. the primary concern of the approach is the modeling of human motor functionality while writing characters. this is achieved by looking at the whole pen trajectory where the time evaluation of the pen coordinates plays a crucial role. a low complexity classifier has been designed and the proposed similarity measure appears to be quite robust against wide variations in writing styles.initially, the approach has been applied for online recognition of handwritten characters in devnagari and bangla, the two major indian scripts. a test on a dataset of considerable size shows promising recognition rates namely, 97.29% for devnagari and 96.34% for bangla.
summarization of jbig2 compressed indian language textual images. this paper presents a method for automatic summarization of jbig2 coded textual images without optical character recognition (ocr). compressed images are partially (less than 10% of the uncompressed image size) decompressed and text lines and words are marked. a few features are computed at each sentence level. based on the feature values sentences are then marked as a summary sentence or not. the system finally generates a set of sentences as summary. in addition, sentences are ranked within the summary. experiment considers indian language text images. test results show a sentence selection efficiency of about 56% when judged against summarization generated by human. a nonparametric (distribution-free) rank statistic shows a correlation coefficient of 0.28 as a measure of the (minimum) strength of the associations between sentence ranking by machine and human.
object-based image retrieval using active nets. in this work, extraction of relevant objects from images and their matching for retrieval is proposed. objects are represented by using a two dimensional deformable structure referred to as active net, capable to adapt to relevant image regions according to chromatic and edge information. in particular, this representation allows a joint description of color, shape and structural information of extracted objects. a similarity measure between active nets is also defined and validated in a set of retrieval experiments on the eth-80 objects database.
performance of the kullback-leibler information gain for predicting image fidelity. this paper presents a new method for characterizing information of a compressed image relative to the original one. we show how the kullback-leibler information gain is based on three basic postulates which are natural for image processing and thus desirable. as an example of the proposed measure, we analyze the effects of lossy compression on the identification of breast cancer microcalcifications. we also show the comparative results of the kullback-leibler information gain and various quantitative measures for predicting image fidelity in the sense of diagnostic usefulness.
improving texture pattern recognition by integration of multiple texture feature extraction methods. this paper proposes a pixel-based texture classifier that integrates multiple texture feature extraction methods in order to identify the regions of an input image that belong to a given set of texture patterns. experimental results with textured images of outdoor scenes show that the proposed technique yields lower classification errors than widely recognized texture classifiers based on specific families of texture methods.
estimation of distance to planar surfaces and type of material with infrared sensors. this paper proposes a new technique for computing the distance to an unknown planar surface and, at the same time, estimating the material of the surface through the use of low-cost infrared sensors. previous approaches to this problem require more costly ultrasound systems as a complement or, alternatively, an exhaustive training process that records the sensor response corresponding to known materials measured at different predefined distances. experimental results with an off-the-shelf infrared sensor mounted on a mobile robot are presented.
fusion of global and local information for object detection. this paper presents a framework for fusing together global and local information in images to form a powerful object detection system. we begin by describing two detection algorithms. the first algorithm uses independent component analysis (ica) to derive an image representation that captures global information in the input data. the second algorithm uses a part-based representation that relies on local properties of the data. the strengths of the two detection algorithms are then combined to form a more powerful detector. the approach is evaluated on a database of real-world images containing side views of cars. the combineddetector gives distinctly superior performance than each of the individual detectors, achieving a high detection accuracy of 94% on this difficult test set.
hybrid off-line cursive handwriting word recognition. in this paper, we present an off-line cursive word handwriting recognition methodology. this is based on an additive fusion resulted after a novel combination of two different modes of word image normalization and robust hybrid feature extraction. we employ two types of features in a hybrid fashion. the first one, divides the word image into a set of zones and calculates the density of the character pixels in each zone. in the second type of features, we calculate the area that is formed from the projections of the upper and lower profile of the word. the performance of the proposed methodology is demonstrated after testing with the reference iam cursive handwriting database.
perspective pose estimation from uncertain omnidirectional image data. omnidirectional vision is highly beneficial for robot navigation. we present a novel perspective pose estimation for omnidirectional vision involving a parabolic central catadioptric sensor using small data sets. we incorporate an appropriate and approved stochastic method to deal with uncertainties in the data. our approach is robust in that it is more accurate than recent methods while using less precise hardware without rigorous calibration.
split and merge data association filter for dense multi-target tracking. bayesian target tracking methods consist in filtering successive measurements coming from a detector. in the presence of clutter or multiple targets, the filter must be coupled with an association procedure. classical bayesian multi-target tracking methods rely on the hypothesis that a target can generate at most one measurement per scan and that a measurement originates from at most one target. when tracking a high number of deformable sources, the previous assumptions are often not met, leading existing methods to fail. here, we propose an algorithm which allows to perform the tracking in the cases when a single target generates several measurements or several targets generate a single measurement. the novel idea presented in this paper is the introduction of a set that we call virtual measurement set which supersedes and extends the set of measurements. this set is chosen to optimally fit the set of predicted measurements at each time step. this is done in two stages : i) a set of feasible joint association events is built from virtual measurements that are created by successively splitting and merging real measurements; ii) the joint probability is maximized over all feasible joint association events. the method has been tested on microscopy image sequences which typically contains densely moving objects and gives satisfactory preliminary results.
genre-based search through biomedical images. we exploit the retrieval of visual information from biomedical scientific publication databases. therefore, we consider the use of domain specific genres to automatically subdivide large image databases into smaller, consistent parts. combination with latent semantic indexing onthe picture captions allows for efficient retrieval of images in specific categories. we demonstrate our approach on a large collection of images with captions from the elsevier brain research publications. initial result demonstrate the power of the proposed combination.
effect of noise on model selection criteria in visual applications. in this paper, the effect of noise level on the performance of a large number of existing model selection criteria for two important computer vision applications (motion and range segmentation) has been investigated. the results of our experiments show that although the performance of all model selection criteria deteriorates by increasing the level of noise, the surface selection criterion (ssc) remains the criterion of choice for different noise levels.
the model selection criteria as merging criteria. a comparative study of a wide range of different model selection criteria for merging 3d range data is presented. first, we measure and compared the success rate of every criterion in detecting step and crease discontinuities in 3d range data followed by measuring the performance in merging non-existent discontinuities. as a conclusion, we have recommended a small group of criteria that are suitable for all cases.
incremental vehicle 3-d modeling from video. in this paper, we present a new model-based approach for building 3-d models of vehicles from color video provided by a traffic surveillance camera. we incrementally build 3d models using a clustering technique. geometrical relations based on 3d generic vehicle model map 2d features to 3d. the 3d features are then adaptively clustered over the frame sequence to incrementally generate the 3d model of the vehicle. results are shown for both simulated and real traffic video. they are evaluated by a new structural performance measure underscoring usefulness of incremental learning.
a psychological adaptive model for video analysis. extracting key-frames is the first step for efficient content-based indexing, browsing and retrieval of the video data in commercial movies. most of the existing research deals with "how to extract representative frames?" however the unaddressed question is "how many key-frames are required to represent a video shot properly?" generally, the user defines this number a priori or some heuristic methods are used. in this paper, we propose a psychological model, which computes this number adaptively and online, from variation of visual features in a video-shot. we incorporate it with an iterative key-frame selection method to automatically select the key-frames. we compare the results of this method with two other well-known approaches, based on a novel effectiveness measure that scores each approach based on its representational power. movie-clips of varying complexity are used to underscore the success of the proposed model in real-time.
nearest-prototype relevance feedback for content based image retrieval. effective retrieval of images from databases can be attained by adopting relevance feedback mechanisms. the vast majority of such mechanisms that have been proposed so far are based on modifying either the query point, or the feature space, or the similarity measure, so that the average similarity between pairs of relevant images is as minimum as possible. in this paper, a relevance feedback technique based on the nearest-neighbor rule is proposed. for each image of the database, a relevance score is computed as the ratio between the distances from the nearest non-relevant and relevant images respectively. relevance is thus related to "local" properties of the images rather than to the estimation of global properties. reported results on the corel dataset show that the proposed mechanism allows attaining large improvements in retrieval precision compared to other mechanisms.
constructing visual taxonomies by shape. we investigate the use of statistical shape measures for segmented image regions to construct taxonomies of visual similarity. it is demonstrated that without the use of a priori knowledge, cluster analysis can be used to impose structure on heterogeneous image data sets. we develop visual taxonomies to accomplish moderate classification tasks, and provide a framework for more powerful, open-ended analysis of large data sets. the power of this method is demonstrated using a visual taxonomy of textual data, which is shown to be efficient in an mdl context.
a general framework for agglomerative hierarchical clustering algorithms. this paper presents a general framework for agglomerative hierarchical clustering based on graphs. different hierarchical agglomerative clustering algorithms can be obtained from this framework, by specifying an inter-cluster similarity measure, a subgraph of the â-similarity graph, and a cover routine. we also describe two methods obtained from this framework called hierarchical compact algorithm and hierarchical star algorithm. these algorithms have been evaluated using standard document collections. the experimental results show that our methods are faster and obtain smaller hierarchies than traditional hierarchical algorithms while achieving a similar clustering quality.
expectation-maximization for a linear combination of gaussians. we propose a modified expectation-maximization algorithm that approximates an empirical probability density function of scalar data with a linear combination of gaussians (lcg). due to both positive and negative components, the lcg approximates inter-class transitions more accurately than a conventional mixture of only positive gaussians. experiments in segmenting multi-modal medical images show the proposed lcg-approximation results in more adequate region borders.
to frame or not to frame in probabilistic texture modelling? the maximum entropy principle is a cornerstone of frame (filters, random fields, and maximum entropy) model considered at times as a first-ever step towards a universal theory of texture modelling or even as "the inevitable texture model". this paper disputes such opinions. that a wealth of exponential families of probability distributions is deduced from the me principle is well known for decades. the me property by itself in no way leads to an adequate probabilistic description, and to model a particular texture, specific limitations have to be imposed on signal statistics. frequency distributions of outputs from a bank of linear filters (the second frame's cornerstone) are hardly the only choice outperforming all other alternatives. the paper points also to other hidden drawbacks of frame.
accuracy of the regularised dynamic programming stereo. binocular stereo is an ill-posed problem that has to be regularised with respect to partial occlusions and homogeneous textures for obtaining a unique solution. we analyse typical errors of the dynamic programming stereo based on a probabilistic regularisation of partial occlusions. experiments show that the reconstruction is accurate until occlusions do not prevail over the binocularly visible terrain.
concurrent stereo under photometric image distortions. we have improved our concurrent stereo matching (csm) algorithm, which abandons the search for 'best' matches and determine matches that lie within admissible ranges using a noise model. we estimate photometric deviations between corresponding regions of stereo pairs with photometric transformations and mismatched or occluded regions. we allow for global, disparity dependent contrast and offset (gain and dark noise) distortions as well as multiple outliers. noise is estimated for each pixel at each disparity level and the csm framework applied. outliers are eliminated with a statistical model and likely matching volumes identified. then, starting in the foreground, the volumes are explored to select mutually consistent optical surfaces. finally, local, not global, surface continuity and visibility constraints are applied to generate a disparity map. this approach compares well with other matching algorithms: the more realistic matching model allows for signal contrast and offset variations over the whole image.
pixel position regression - application to medical image segmentation. pixel position regression (ppr), an automatic supervised method for image segmentation, is presented. the method uses a set of corresponding points indicated in each train image. for each point in this set, the mean position in all train images is determined. by warping the set of corresponding points to their mean positions, one can associate with each position in each train image a reference position. ppr estimates the reference position from a rich set of local image features through k-nearest-neighbor regression. the deformation field thus obtained determines the segmentation. it is demonstrated that the deformation field estimate can be improved by (weighted) blurring and more sophisticated methods such as global modeling of the deformation field through principal component analysis and iterated regression. the method is evaluated on a set of chest radio-graphs in which the lung fields, heart and clavicles are segmented.
image denoising with k-nearest neighbor and support vector regression. denoising is an important application of image processing, especially for medical image data. these images tend to be very noisy when a low radiation dose, less harmful to the patient, is used for acquisition. for computed tomography (ct) data, it is possible to simulate realistic low dose images from the raw scanner data. we use this data to construct a supervised denoising system, that learns an optimal mapping from input features to denoised voxel values. as input features we use several general filters and the output of existing standard noise reduction filters, notably non-linear diffusion schemes. after feature selection, these are mapped to the denoised values by k-nearest neighbor and support vector regression. the resulting regression denoising systems are shown to perform significantly better than non-linear diffusion schemes, gaussian smoothing and median filtering in experiments on ct chest scans.
text detection in images based on unsupervised classification of high-frequency wavelet coefficients. text localization and recognition in images is important for searching information in digital photo archives, video databases and web sites. however, since text is often printed against a complex background, it is often difficult to detect. in this paper, a robust text localization approach is presented, which can automatically detect horizontally aligned text with different sizes, fonts, colors and languages. first, a wavelet transform is applied to the image and the distribution of high-frequency wavelet coefficients is considered to statistically characterize text and non-text areas. then, the k-means algorithm is used to classify text areas in the image. the detected text areas undergo a projection analysis in order to refine their localization. finally, a binary segmented text image is generated, to be used as input to an ocr engine. the detection performance of our approach is demonstrated by presenting experimental results for a set of video frames taken from the mpeg-7 video test set.
learning optimal classifier through fuzzy recognition rate maximization. the adjustment of the metric (features weighting) and the optimisation of the position of prototypes in the feature space are two of most important problems in minimum distance classifiers. this paper presents a new method to deal with these two problems based on the maximisation of a fuzzy recognition rate functional. the functional is a result of an easy to understand mathematical formulation. experimental results on the recognition of binary cursive characters and gray-level container code characters follow. a comparison with the standard lvq method is also made and discussed for the cursive character case.
comparative analysis of decision-level fusion algorithms for 3d face recognition. 3d shape-based face recognition algorithms can be improved by using decision-level fusion algorithms. in this work, we present a comparative analysis of various fusion algorithms, and also propose novel ones. the contributions of the paper can be summarized as: i) a through analysis of several decision-level fusion algorithms, ii) a dynamically estimated reliability-assisted fusion schemes, and iii) a novel implementation of lda-based cascaded serial fusion algorithm. experiments conducted on the 3d_rma dataset confirm that serial fusion offers the best solution, and dynamic calculation of reliability estimates improves the accuracy of the standard fusion schemes.
comparing optimal bounding ellipsoid and support vector machine active learning. in this paper we propose two active learning algorithms combining statistical active learning methods based on svm and optimal bounding algorithms (obe) of adaptive system identification. we unify svm and obe by demonstrating the similarities and representing svm in an obe interpretation. samples are judiciously selected based on a volume measure provided by obe using both simple heuristic and greedy optimal strategies. preliminary experiments illustrate the effectiveness of the proposed algorithms as compared to similar methods.
finding regions of interest in document images by planar hmm. we present a new stochastic approach based on planar hidden markov models (phmm) for finding regions of interest (roi) in document images. the main advantage of the proposed approach is that no explicit rules characterizing the rois have to be defined. instead, the phmm learns to find the rois based on training data which show examples of document images together with the rois. the method has been tested on the task of finding the legal amount in real check images.
estimation of 3d motion from stereo images- differential and discrete formulations. in this paper we analyze the problem of motion estimation from a sequence of stereo images. we formulate both the differential and discrete approaches of two methods. the differential approach uses differential optical flow whereas the discrete approaches uses feature correspondences. we use both methods to compute, first, the 3d velocity in the z direction and, second, the complete motion parameters. the methods were extensively tested using synthetic images as well as real images and several conclusions are drawn from the results. we point out the critical factors for the methods. the real images are used without any illumination control of the scene in order to analyze the behavior of the methods in strongly noisy environments and low resolution depth maps.
rigid motion estimation from non-central catadioptric images. this paper addresses the problem of rigid motion estimation and 3d reconstruction in vision systems where it is possible to recover the incident direction from image points. such systems include pinhole cameras and catadioptric cameras. given two images of the same scene acquired from two positions, the transformation is estimated by means of an iterative process. the estimation process aims at having corresponding incident rays intersecting at the same 3d point. geometrical relationships are derived to support the estimation method. experiments with real images are presented.
motion estimation using dynamic programming with selective path search. a novel dynamic programming-based motion estimation algorithm is presented in this paper. during matching cost calculation, the algorithm selectively keeps the cost values for the best n candidates only. the required memory space is therefore considerably reduced. in addition, a new path searching approach is applied. when searching for the optimal path from pixel p, the algorithm considers both the nearby candidates and the best n candidates at pixel p-1. as a result, better estimations can be produced around motion boundaries. the experimental results show that the motions estimated through considering all the candidates are only slightly better than those estimated through selectively considering a small number of candidates, even though the former approach requires significantly more computational time and memory space.
multi-resolution genetic algorithm and its application in motion estimation. many computer vision problems can be formulated into optimization problems. in this paper, we propose a multi-resolution genetic algorithm, which can be applied to solving many of these problems. the motion estimation problem is used as a vehicle for demonstration. a matching-based estimator is proposed through setting up a proper fitness evaluation function and letting the multi-resolution genetic algorithm do the global searching. the results show that the proposed estimator is robust and can produce consistent velocities for real image sequences.
disparity flow estimation using orthogonal reliability-based dynamic programming. disparity flow depicts the 3d motion of a scene in disparity space of a given view and can be considered as view-dependent scene flow. the disparity flow map of a given view is a 2d array of 3d vectors that depicts the 3d motion observed at different pixel locations. estimating 3d motion in form of disparity flow map limits all computations in the 2d image space and converts the 3d motion estimation problem into a 2d labeling problem. a novel algorithm is presented in this paper for disparity flow estimation using the orthogonal reliability-based dynamic programming technique. experimental results using captured stereo sequences show that the new algorithm can generate dense and smooth 3d motion for dynamic scenes.
robust algorithm for pupil-glint vector detection in a video-oculography eyetracking system. this paper presents a robust real time algorithm for an eye tracking system employing the well-known bright-pupil technique that performs an effective detection of the pupil and glint positions in the image. the accuracy in the processing is essential if a good determination of the eye gaze is desired. this algorithm is competent for unconstrained images and presents an unmatchable behaviour for users using glasses. the algorithm employs mostly commands from matrox imaging library (mil) that present a wide sort of functions for image processing and pattern recognition.
pose correction and subject-specific features for face authentication. in this paper, we present a face authentication system that can be broken down in three stages. prior to feature extraction, a pose correction step is applied, so that frontal face images are synthesized through the use of flexible shape models and thin plate splines warping. once the pre-processing is completed, a set of subject-specific key points is located in face images by means of a two-layer strategy. in the first level, locations are chosen from lines that depict facial structure, and gabor features (jets) are extracted at these positions. in the second step, we evaluate these jets as individual classifiers over a training dataset, so that only the subset of points whose jets are good at discriminating between clients and imposters are preserved.
fast dichotomic multiple search algorithm for shortest cirular path. circular shortest path algorithms for polar objects segmentation have been proposed in [1, 11, 10] to address discrete case and extended in [2] to the continuous domain for closed global optimal geodesic calculation. the best method up to date relies on a branch and bound approach and runs in o(u1.6v) on average while o(u2v) in worst case for a u × v discrete trellis warped in the direction of v. we propose an new algorithm called dichotomic multiple search (dms) which finds the global minimum with a o(ulog2(u)v) worst case scenario complexity. our algorithm relies on the fact that two minimal paths never cross more than once. this allows to sequentially partition the trellis in a dichotomic manner. each computed circular minimal path with chosen starting point allows cutting the trellis into two sub trellis. the algorithm is then recursively applied on each sub trellis. application to object segmentation is presented.
combining svm classifiers for handwritten digit recognition. in this paper, we investigate the advantages and weaknesses of various decision fusion schemes using statistical and rule-based reasoning. the cooperation schemes are applied on two svm (support vector machine) classifiers performing classification task on two feature families referenced as structural and statistical features. the obtained results show that it is difficult to exceed the recognition rate of a single classifier applied strightforwardly on both feature families as one set. the rule based cooperation schemes enable an easy and efficient implementation of various rejection criteria. on the other hand, the statistical cooperation schemes provide higher recognition rates and offer possibility for fine-tuning of the recognition versuses the reliability tradeoff.
an efficient three-stage classifier for handwritten digit recognition. this paper proposes an efficient three-stage classifier for handwritten digit recognition based on nn (neural network) and svm (support vector machine) classifiers. the classification is performed by 2 nns and one svm. the first nn is designed to provide a low misclassification rate using a strong rejection criterion. it is applied on a small set of easy to extract features. rejected patterns are forwarded to the second nn that uses additional, more complex features, and utilizes a well-balanced rejection criterion. finally, rejected patterns from the second nn are forwarded to an optimized svm that considers only the "top k" classes as ranked by the nn. this way a very fast svm classification is obtained without sacrificing the classifier accuracy. the obtained recognition rate is among the best on the mnist database and the classification time is much better compared to the single svm applied on the same feature set.
graph matching using random walks. in this paper we propose a graph matching algorithm which uses random walks to compute topological features for each node, in order to identify candidate pairs of corresponding nodes in the two graphs. the algorithm automatically adapts the number of topological features required to determine the exact match among the nodes. even if the proposed technique is not guaranteed to provide an exact solution for all graphs, the experiments on a benchmark dataset show that it can outperform other state of the art algorithms with respect to the computational requirements. in fact, the proposed algorithm is polynomial in the number of graph nodes.
bayesian imitation of human behavior in interactive computer games. modern interactive computer games provide the ability to objectively record complex human behavior, offering a variety of interesting challenges to the pattern-recognition community. such recordings often represent a multiplexing of long-term strategy, mid-term tactics and short-term reactions, in addition to the more low-level details of the player's movements. in this paper, we describe our work in the field of imitation learning; more specifically, we present a mature, bayesian-based approach to the extraction of both the strategic behavior and movement patterns of a human player, and their use in realizing a cloned artificial agent. we then describe a set of experiments demonstrating the effectiveness of our model.
robust extraction of planar and quadric surfaces from range images. we present a new range image segmentation algorithm based on the extraction of planar and general quadric surfaces, which is of great relevance in man-made environments, built largely of low-order surfaces. we describe how our robust estimator can effectively reject erroneous surface hypotheses, while identifying points describing a general quadric surface, by means of an improved approximation to the true geometric distance between each point and the surface. we present thorough experimental results with quantitative evaluation against ground truth.
ocrgrid : a platform for distributed and cooperative ocr systems. developing an ocr (optical character recognition/ reader) system requires expertise in various fields of researches, and the fact has been recognized as an obstacle to expanding the range of ocr applications, improving the recognition accuracy, and to providing end users with better ocr applications and services. this paper proposes a platform for distributed and cooperative ocr systems, called "ocrgrid," that allows end users to search for and use ocr servers over networks. we discuss the potential of the platform, useful applications, and problems that need to be addressed. this paper also introduces a toolkit for realizing web-based ocrs and an implementation of the character recognition based on the majority logic.
character pattern extraction from colorful documents with complex backgrounds. today there are lots of documents in which text characters are printed on colored and/or complex backgrounds. we previously proposed a character pattern extraction method by which character paterns can be extracted from grayscale document images with comlex background. the method has unique, advantageous properties; it is capable of extracting very small characters and is tolerant of shadings of images. however, the method did not work well for some color documents since it lacks the ability of discriminating color difference. this paper proposes an enhanced version of the method, which utilizes the local color segmentation and the region growing. the experimental results have shown that the new method yields much better results for color magazine covers without sacrificing the performance of extracting small character patterns. the method is tolerant of shadings of images as well.
screen pattern removal for character pattern extraction from high-resolution color document images. screen pattern used in offset-printed documents has been one of great obstacles in developing document recognition systems that handle color documents. this paper proposes a selective smoothing method for filtering the screen patterns/noise in high-resolution color document images. experimental results show that the method yields significant improvements in character pattern extraction.
line detection and texture characterization of network patterns. this paper describes a complete approach to detect, localize and describe network patterns. such texture is automatically detected with gaussian derivative kernels and fisher linear discriminant analysis; line closure and thinning is provided by morphological masking and line luminance profile fitting provides width estimation. detection results on dermatological images are reported and discussed.
color calibration for a dermatological video camera system. in this work we describe a technique to calibrate images for skin analysis in dermatology. using a common reference we correct non-uniform illumination effects, give an estimation of the gamma correction, produce a xyz conversion matrix. the final result is then reverted to a non standard rgb color space, built from the instrument images. in this way different instruments behave uniformly allowing colorimetric characterization, while improving the results of common algorithms. the proposed techniques should be the initial support for a distributed framework where dermatological images can be consistently compared.
entropy estimation and multiscale processing in meteorological satellite images. a new model for the multiscale characterization of turbulence and chaotic information in digital images is presented. the model is applied to infrared satellite images for the determination of specific areas inside the clouds. these images are difficult to manipulate however due to their intrinsically chaotic character, consequence of the extreme turbulent regime of the atmospheric flow . in this paper we briefly review some known techniques for processing suchdata and we will justify the necessity of multiscale methods to extract the relevant features. in the theory presented herein, one main attribute is determined for every image: the most singular manifold (msm, of fractal nature), characterizing the sharpest changes in graylevel values. we will see that the most important set (from the statistical point of view) is that which both contains the sharpest transitions (msm) and maximizes the local entropy. for that reason, images can be reconstructed to a good quality from the value of the gradient over that set of maximal information. the results are interpreted according to their relevance for determining meteorological features.
propagating segmented regions during a camera saccade. in this paper, we present a method for propagating segmentation information across a saccade for a foveating camera. in particular, we take a region of interest from a wide-angle, low-fidelity image and propagate its segmentation information to a zoomed, high-fidelity image containing that region. our method uses normalized greyscale templates to estimate the change in translation and magnification required to transform the segmented region. this process is particularly useful for systems whose segmentation methods rely on prior images, such as motion or difference segmentation, because the segmentation methods cannot be simply be rerun to obtain a segmentation in the high-fidelity images.
location and recognition of flashlight projections for visual interfaces. we consider the location and recognition of flashlight projections given the image sequence supplied by a fixed camera monitoring a physical surface. a quotient method extracts a description of the flashlight projection that is independent of the reflectance of the illuminated surface. the information recovered is used to recognise individual flashlights and trigger audiovisual events in response to users' actions. a demonstration application, an interactive poster, is described and directions for future work identified.
probabilistic models for generating, modelling and matching image categories. in this paper we present a probabilistic and continuous framework for supervised image category modelling and matching as well as unsupervised clustering of image space into image categories. a generalized gmm-kl framework is described in which each image or image-set (category) is represented as a gaussian mixture distribution and images (categories) are compared and matched via a probabilistic measure of similarity between distributions. image-to-category matching is investigated and unsupervised clustering of a random image set into visually coherent image categories is demonstrated.
a subspace approach to texture modelling by using gaussian mixtures. assuming local and shift-invariant texture properties we describe the statistical dependencies between pixels by a joint probability density of gray-levels within a suitably chosen observation window. we estimate the unknown multivariate density in the form of a gaussian mixture of product components from data obtained by shifting the observation window. obviously, the size of the window should be large to capture the low-frequency properties of textures but, on the other hand, the increasing dimension of the estimated mixture may become prohibitive. by considering a subspace approach based on a structural mixture model we can increase the size of the observation window while keeping the computational complexity in reasonable bounds.
on the use of anthropometry in the invariant analysis of human actions. in this paper, we propose a novel approach to matching human actions using semantic correspondence between human bodies with an eye towards invariant analysis of activity. the correspondences are used to provide geometric constraints between multiple anatomical landmarks (e.g. hands, shoulders and feet) to match actions performed from different viewpoints and in different environments. the fact that the human body has certain anthropometric proportion allows innovative use of the machinery of epipolar geometry to provide constraints to accurately analyze actions performed by different people leading to some interesting results. temporally invariant matching is performed, using non-linear time warping, to ensure that similar actions performed at different rates are accurately matched as well. thus, the proposed algorithm guarantees that both temporal and view invariance is maintained in matching. we demonstrate the versatility of our algorithm in a number of challenging sequences and applications.
robust omniview-based probabilistic self-localization for mobile robots in large maze-like environments. this paper extends our previous work on omniview-based monte carlo localization. it presents a number of improvements addressing challenges arising from the characteristics of the given real-world application, the self-localization of a mobile robot in a regularly structured, maze-like and populated operation area, a home store. the contribution of this paper can be summarized as follows: we introduce a more specific extraction of color-based appearance features and propose a novel selective observation comparison method to determine the similarity between expected and actual observation allowing a better handling of severe occlusions or disturbances. moreover, we present the results of a series of localization experiments studying the impact of the appearance-feature extraction and the observation comparison on the localization accuracy. our improved approach can successfully demonstrate its omniview-based localization capabilities for a demanding, large operation area - a home store with a size up to 100 × 60^2. to the best of our knowledge, this is the most complex operation area that has been studied experimentally so far using appearance-based localization techniques.
a clustering approach to corner point analysis in hand drawn images. drawing tasks are used widely within neuropsychology for the assessment and monitoring of a variety of conditions. automated assessment of these tasks improves their repeatability and accuracy in use alongside a reduction in trained therapist resource loading. using images fromtest responses collected in an assessment of the condition of visuo-spatial neglect, this paper presents a method utilising a standard corner detection routine (susan) to establish the presence and location of corner points within an image of a drawn geometric shape. it is demonstrated that by applying a series of standard clustering systems to these located corners, the accuracy in terms of number and spatial position of corner points found assessed against actual corner position is improved.
activity discovery from surveillance videos. multi-agent interactions often result in mutual occlusion sequences which constitute a visual signature for the event. we define six qualitative occlusion primitives based on the persistence hypothesis (objects continue to exist even when hidden from view): isolated, occlude with foreground, occlude by background, disappear, enter and exit. variable length temporal sequences of occlusion primitives are shown to be useful features for categorizing many classes of semantically significant events. occlusion primitive labels depend on agent positions in the image, which are determined by combining foreground blob tracking and image motion. no prior knowledge of domain or camera calibration is necessary. new foreground blobs are identified as putative agents which may undergo occlusions, split into multiple agents, merge back again, etc. transition sequences are mined to identify semantic categories (e.g. people disembarking from a vehicle involve a series of splits). occlusion features alone may be useful for distinguishing some broad categories of interaction states, and together with features such as agent shape and motion histories, these form a rich signature for different event types that can be classified without camera calibration or any environment/ agent/action model priors.
a bimodal face and body gesture database for automatic analysis of human nonverbal affective behavior. to be able to develop and test robust affective multimodal systems, researchers need access to novel databases containing representative samples of human multi-modal expressive behavior. the creation of such databases requires a major effort in the definition of representative behaviors, the choice of expressive modalities, and the collection and labeling of large amount of data. at present, public databases only exist for single expressive modalities such as facial expression analysis. there also exist a number of gesture databases of static and dynamic hand postures and dynamic hand gestures. however, there is not a readily available database combining affective face and body information in a genuine bimodal manner. accordingly, in this paper, we present a bimodal database recorded by two highresolution cameras simultaneously for use in automatic analysis of human nonverbal affective behavior.
perceptual audio watermarking by learning in wavelet domain. conventional blind watermark (wm) decoding schemes use correlation-based decision rules because of their simplicity. drawback of the correlator decoders is their performance relies on the decision threshold. existence of an undesirable correlation between the wm data embedded through a secret key and the host signal makes the decision threshold specification harder, especially in noisy channels. to overcome this drawback, we propose a svm-based decoding scheme which is capable of learning the embedded wm data in wavelet domain. it is shown that both decoding and detection performance of the introduced wm extraction technique outperforms state-of-the-art correlation-based schemes. test results demonstrate that learning in the wavelet domain improves robustness to attacks while reducing complexity.
an evaluation of ensemble methods in handwritten word recognition based on feature selection. handwritten text recognition is one of the most difficult problems in the field of pattern recognition. the combination of multiple classifiers has been proven to be able to increase the recognition rate in difficult problems when compared to single classifiers. in this paper several novel methods for the creation of classifier ensembles are compared where the individual classifiers use different feature subsets. the methods are evaluated in the context of handwritten word recognition, using a hidden markov model recognizer as basic classifier.
multi-modality image registration using mutual information based on gradient vector flow. similarity measure plays a critical role in image registration. mutual information (mi) has been proved to be a promising measure used widely in multi-modality image registration. however, mutual information only takes statistical information into consideration, while spatial information is not even considered. in this paper, a novel approach is proposed to incorporate spatial information into mi through gradient vector flow (gvf). mutual information now is calculated from the gvf-intensity (gvfi) map of the original images instead of their intensity values. multimodality brain image registration was performed to test the accuracy and robustness of the proposed method. experimental results showed that the success rate of our method is higher than that of traditional mi-based registration.
inspecting ingredients of starches in starch-noodle based on image processing and pattern recognition. inspecting what sort of starch in commercial starchnoodles is important to international trade, food safety and protecting consumer benefit. at present, the inspection of components of starches in starch-noodle mainly relies on sensory perception, and which is fallibility or trustless. because the microstructure pattern of starches in starchnoodles depends mainly on a kind or blend of starches from which the starch-noodle was made, this paper presents an approach to classify the starch-noodles by using computer system automatically based on recognizing the microstructure pattern of the starches and components in starch-noodle. the method consists of three step: 1) take the micrograph of starch-noodles with scanning electron microscopy and preprocessing. 2) extract features of fractal geometry and gray-level co-occurrence from micrograph. 3) distinguish a sort of starch-noodles by using these combined features as input vector of artificial neural networks. the experiments has been conducted with starch-noodles of mungbean blending pachyrhizus, and the experimental results show that the method is practicable and effective.
learning and inference of 3d human poses from gaussian mixture modeled silhouettes. in this paper, we present a learning and inference framework for 3d human pose recovery using silhouettes represented by gaussian mixtures. a bayesian mixture of experts is learnt to conduct multimodal pose regression. the major contribution of this paper is the use of gaussian mixtures as silhouette shape descriptor and kullback-leibler divergence (kld) for silhouette distance and kernel computation. using gaussian mixtures and kld makes the learning and inference robust to errors in silhouettes extraction. it also allows likelihood evaluation of different pose estimates. this is done by computing the similarity of the observed silhouette and the predicted silhouettes by a generic body model onto the image plane. the system was trained with silhouettes rendered using animation software driven by motion capture data. experimental results using both synthetic and real image silhouettes illustrate the usefulness of the proposed framework.
planar motion of a parabolic catadioptric camera. camera motion is said to be planar if the direction of translation is perpendicular to the axis of rotation. a parabolic catadioptric camera is a camera realizing the orthogonal projection of rays reflected on a parabolic mirror. in this paper we consider the planar motion of a parabolic catadioptric camera, especially the motion restricted to a plane perpendicular to the optical axis, a common case in mobile robots working in urban environments. we begin by deriving the catadioptric fundamental matrix for such a motion and the intrinsic degrees of freedom in this matrix which turn out to be 8. we show that the camera intrinsics and the 3d motion can be recovered from the fundamental matrix. we derive the necessary and sufficient condition for a fundamental matrix to be induced by a planar motion. based on the additional constraint for a planar motion, we present an algorithm to compute epipolar geometry and recover the camera parameters and motion.
texture edge detection using multi-resolution features and som. texture boundaries or edges are useful information for segmenting a texture image. we propose a texture edge detection algorithm using a bank of 1-d multi-channel, multiresolution filters and self organizing map (som). 2-d filtering smears the effect of an edge in all directions, and hence we used 1-d filtering that will only smear the edge in the direction of filtering. som reduces the dimension of a feature vector by producing a 1-d map which plots the similarities of data by grouping similar items together. the output of som is processed to obtain the texture edge map. the proposed methodology is tested on simulated as well as natural texture images and produces satisfactory results.
classifiers for motion. in this paper, we present a supervised learning based approach for sub-pixel motion estimation. the novelty of this work is the learning based method itself which tries to learn the shifts from a large training database. integer pixel shift is sub-divided and discretized to levels in both the horizontal and vertical direction. we pose the problem of motion estimation in a polar coordinate system. shift estimation in the x and y direction has been posed as a problem of estimating r and è. the ordinal property of r has been used, and consequently, we employ a ranking based approach for estimating r. for è estimation we employ multi-class classification techniques. we demonstrate how very simplistic features can be used to differentiate between different subpixel shifts.
a method of image recognition based on the fusion of reduced invariant representations: mathematical substantiation. it is proposed an approach to solution of image recognition problems based on the following principal thesises: a) images are represented by multiple partial models widely used in pattern recognition ¿ feature sets; b) algorithms are multiple classifiers: each algorithm use its own data ¿ some partial image model; c) there are two kinds of fusion ¿ data (partial models) fusion and algorithm fusion; d) fusion processes of both kinds are implemented by algebraic techniques in the framework of descriptive theory of image analysis. the specific aspects of the proposed approach: a) a partial image model (a feature set) includes only image invariants; b) concept of image equivalence is a base for recognition through exploiting the partial image models; c) the final solution is obtained by the algorithm fusion methods using algebra of images and algebra of algorithms.
technology for automated morphologic analysis of cytological slides. methods and results. the information technology for automated morphologic analysis of the cytological slides, taken from patients with the lymphatic system tumors, was developed. the main components of the technology are: acquisition of cytological slides, method for segmentation of nuclei in the cytological slides, synthesis of the feature based nuclei description for subsequent classification, nuclei image analysis based on pattern recognition and scale-space techniques. the experiments confirmed efficiency of the developed technology. the discussion of the obtained results is given. the developed technology is implemented in the software system.
method for early diagnostics of lymphatic system tumors on the basis of the analysis of chromatin constitution in cell nucleus images. in this paper, a new criterion for early diagnostics of lymphatic system tumor from images of cell nuclei of lymphatic nodes is considered. a method for image analysis of chromatin structure is developed on the basis of the scale-space approach. a diagnostically important criterion is defined as a total amount of points of spatial intensity extrema in the families of blurred images generated by the given image of a cell nucleus. the procedure for calculating criterion values is presented. testing of the obtained criterion is carried out.
rapid spline-based kernel density estimation for bayesian networks. the likelihood for patterns of continuous attributes for the naive bayesian classifier (nbc) may be approximated by kernel density estimation (kde), letting every pattern influence the shape of the probability density thus leading to accurate estimation. kde suffers from computational cost making it unpractical in many real-world applications. we smooth the density using a spline thus requiring only very few coefficients for the estimation rather than the whole training set, allowing rapid implementation of the nbc without sacrificing classifier accuracy. experiments conducted over several real-world databases reveal acceleration, sometimes in several orders of magnitude, in favor of the spline approximation making the application of kde to the nbc practical.
weighted loss functions to make risk-based language identification fused decisions. making a pattern recognition decision with the maximum-likelihood rule is a particular case of the risk-based bayesian decision rule which is simplified when the loss function is zero-one symmetrical and classes are equally a priori probable. in the case the recognition system is composed of several experts, we can take into account their estimated performance at the class level as a key heuristic-like factor to weight the loss function and drive the recognition process while fusing their decisions. such indices are formally computed by applying the discriminant factor analysis method. the experiments are carried out in the automatic language identification domain with a system composed of several identification experts. fusion of expert decisions is achieved by building statistical classifiers.
structural representation of speech for phonetic classification. this paper explores the issues involved in using symbolic metric algorithms for automatic speech recognition (asr), via a structural representation of speech. this representation is based on a set of phonological distinctive features which is a linguistically well-motivated alternative to the "beads-on-a-string" view of speech that is standard in current asr systems. we report the promising results of phoneme classification experiments conducted on a standard continuous speech task.
adjustable invariant features by partial haar-integration. a very common type of a-priori knowledge in pattern analysis problems is invariance of the input data with respect to transformation groups, e.g. geometric transformations of image data like shifting, scaling etc. for enabling most general analysis techniques, this knowledge should be incorporated in the feature-extraction stage. in the present work a method for this, called haar-integration, is generalized to make it applicable to more general transformation sets, namely subsets of transformation groups. the resulting features are no longer precisely invariant, but their variability can be adjusted and quantified. experimental results demonstrate the increased separability by these features and considerably improved recognition performance on a character recognition task.
camera self-calibration: a new approach for solving the modulus constraint. in this paper, the modulus constraint is used to retrieve the scale factors that are responsible for the nonlinearity of kruppa's equations. in the case of constant intrinsic parameters, each pair of images identifies a pair of 3dpoints at infinity whose coordinates are expressed in terms of the scale factors we are looking for. by enforcing the coplanarity constraint on these points, a set of quintic bivariate equations is obtained for each triplet of images. once the scale factors are calculated, the problems of retrieving the plane at infinity and solving kruppa's equations become straightforward and linear.
unsupervised learning using locally linear embedding: experiments with face pose analysis. this paper considers a recently proposed method for unsupervised learning and dimensionalityreduction, locally linear embedding (lle). lle computes a compact representation of high-dimensional data combining the major advantages of linear methods (computational efficiency, global optimality, and flexible asymptotic convergence guarantees) with the advantages of non-linear approaches (flexibility to learn a broad of class on non-linear manifolds). we assess the performance of the lle algorithm on a real-world data (face imagesin different poses) and compare the results with those obtained with two different approaches (pca and som). extensions to the original lle algorithm are proposed and applied to the problem of pose estimation.
selecting models from videos for appearance-based face recognition. in this paper, we propose an unsupervised approach to select representative face samples (models) from raw videos and build an appearance-based face recognition system. the approach is based on representing the face manifold in a low-dimensional space using the locally linear embedding (lle) algorithm and then performing k-means clustering. we define the face models as the cluster centers. our strategy is motivated by the efficiency of lle to recover meaningful low-dimensional structures hidden in complex and high dimensional data such as face images. two other well-known unsupervised learning algorithms (isomap and som) are also considered. we compare and assess the efficiency of these different schemes on the cmu mobo database which contains 96 face sequences of 24 subjects. the results clearly show significant performance enhancements over traditional methods such as the pca-based one.
a hybrid approach to face detection under unconstrained environments. to detect faces in natural and unconstrained environments, we propose an approach which combines the advantages of both color and gray scale based methods. the idea consists of first preprocessing the images using a state-ofthe- art approach for skin modeling in order to determine the potential skin regions. thus, a scanning of the whole image when searching for faces is avoided. then, in contrast to the existing methods, we consider the fact that the skin detection step still may produce unsatisfactory results or even fail and therefore we apply an exhaustive search in and around the detected skin regions using a new gray scale based approach. the experimental results show that the proposed approach inherits the speed from the color based methods and the efficiency from the gray scale based ones.
target model estimation using particle filters for visual servoing. in this paper, we present a novel method for model estimation for visual servoing. this method employs a particle filter algorithm to estimate the depth of the image features online. a gaussian probabilistic model is employed to model the object points in the current camera frame. a set of 3d samples drawn from the model is projected into the image space in the next frame. the 3d sample that maximizes the likelihood is considered to be the most probable real-world 3d point. the variance value of the depth density function converges to very small value within a few iterations. results show accurate estimate of the depth/model and a high level of stability in the visual servoing process.
human detection in outdoor scene using spatio-temporal motion analysis. we propose an image processing algorithm for detecting human in outdoor scenes containing changeful background. in this work, regions extracted through background subtraction procedure are accurately classified into human and others by motion analysis in the three dimensional feature space constructed by the spatial uniqueness of image motion f¿, the temporal uniqueness of image motion f¿ , and the temporal motion continuity f¿. evaluation test proved that proposed algorithm can reduce the error rates of both false positive and false negative to about 1/3 compared with a conventional method. we also tested by a pc-based real-time system over two weeks in real environments, that resulted in its false negative error rate of less than 1% and false positive error number of less than 3 times per day.
adaptive control of video display for diagnostic assistance by analysis of capsule endoscopic images. in this paper, we present a method for reducing diagnostic time by adaptively controlling the frame rate in a capsule.. endoscopic image sequence. the video sequence, which was capture over 8 hours, requires from 45 minutes to two hours of extreme concentration by examining doctors to make diagnosis. effectiveness of the method is that the sequence can be played at high..speed in stable regions to save time and then decreased at rough changes that can then help ascertain suspicious findings more..conveniently. to realize such a system, the capturing conditions are classified into groups corresponding to the changing states between two frames. the.. delay time of these frames was calculated by the parametric functions. the optimal parameter set was determined from.. evaluations by medical doctors. we concluded that the average diagnostic time could be reduced from 8 hours down to about 30 minutes.
fast restoration of colour movie scratches. this paper presents a new type of scratch removal algorithm based on a causal adaptive multidimensional multitemporal prediction. the predictor use available information from the neighbourhood of a missing multispectral pixels due to spectral, temporal and spatial correlation of video data but not any information from the failed pixels themselves.
btf image space utmost compression and modelling method. the bidirectional texture function (btf) describes texture appearance variations due to varying illumination and viewing conditions. this function is acquired by large number of measurements for all possible combinations of illumination and viewing positions hence some compressed representation of these huge btf texture data spaces is obviously inevitable. in this paper we present a novel efficient probabilistic model-based method for multispectral btf texture compression which simultaneously allows its efficient modelling. this representation model is capable of seamless btf space enlargement and direct implementation inside the graphical card processing unit. the analytical step of the algorithm starts with btf texture surface estimation followed by the spatial factorization of an input multispectral texture image. single band-limited factors are independently modelled by their dedicated 3d causal autoregressive models (car). we estimate an optimal contextual neighbourhood and parameters for each car. finally the synthesized multiresolution multispectral texture pyramid is collapsed into the required size fine resolution synthetic smooth texture. resulting btf is combined in a displacement map filter of the rendering hardware using both multispectral and range information, respectively. the presented model offers immense btf texture compression ratio which cannot be achieved by any other sampling-based btf texture synthesis method.
a gaussian mixture-based colour texture model. a new method of colour texture modelling based on gaussian distribution mixtures is discussed. we estimate the local statistical properties of the monospectral version of the target texture in the form of a gaussian mixture of product components. the synthesized texture is obtained by means of a step-wise prediction of the texture image. in order to achieve a realistic colour texture image and to avoid possible loss of high-frequency details we use optimally chosen pieces of the original colour source texture in the synthesis phase. in this sense the proposed texture modelling method can be viewed as a statistically controlled sampling. by using multispectral or mutually registered btf texture pieces the method can be easily extended also for these textures.
a multiscale colour texture model. a fast recursive model-based algorithm for realistic colour texture synthesis is proposed. the algorithm starts with a colour texture image decomposition into a multiresolution grid. each band pass colour factors are independently modelled by their dedicated 3d causal autoregressive random field models (car). we estimate an optimal contextual neighbourhood and parameters for each of the car submodel. finally the synthesized multiresolution colour texture pyramid is collapsed into the required fine resolution colour texture. the benefit of the multigrid approach is the replacement of a large neighbourhood car model with a set of several simpler car models which are easy to synthesize and wider application area of these multi-grid models capable of reproducing realistic textures for enhancing realism in various texture application areas.
unsupervised texture segmentation using multispectral modelling approach. a new unsupervised multispectral texture segmentation method with unknown number of classes is presented. multispectral texture mosaics are locally represented by four causal multispectral random field models recursively evaluated for each pixel. the segmentation algorithm is based on the underlying gaussian mixture model and starts with an over segmented initial estimation which is adaptively modified until the optimal number of homogeneous texture segments is reached. the performance of the presented method is extensively tested on the prague segmentation benchmark using the commonest segmentation criteria and compares favourably with several alternative texture segmentation methods.
illumination invariant texture retrieval. two fast illumination invariant image retrieval methods for scenes comprising textured objects with variable illumination are introduced. both methods are based on texture gradient modelled by efficient set of random field models. we developed the illumination insensitive measures for textured images representation and compared them favorably with steerable pyramid and gabor features in the illumination invariant btf texture recognition.
multimodal range image segmentation by curve grouping. a fast range image segmentation method for scenes comprising general faced objects is introduced. the range segmentation is based on a recursive adaptive probabilistic detection of step discontinuities which are present at object face borders in mutually registered range and intensity data. detected face outlines guides the subsequent region growing step where the neighbouring face curves are grouped together. region growing based on curve segments instead of pixels like in the classical approaches considerably speed up the algorithm. the exploitation of multimodal data significantly improves the segmentation quality.
ontology and taxonomy collaborated framework for meeting classification. a framework for classification of meeting videos is proposed in this paper. we define our framework consisting of a four level concept hierarchy having movements, events, behavior, and genre; which is based on the meeting ontology and taxonomy. ontology is the formal specification of domain concepts and their relationships. taxonomy is the general categorization based on a class/subclass relationships. this concept hierarchy is mapped to an implementation of finite state machines (fsm) and rule-based system (rbs) to classify the meetings. events are detected by the fsms based on the movements (head and hand tracks). classification of the meetings is performed by the rbs based on the events, and behaviors of the people present in the meetings. our framework is novel and scalable, capable of adding new meeting types with no re-training. we conducted experiments on various meeting sequences and classified meetings into voting, argument, presentation, and object passing. this framework has applications in automated video surveillance, video segmentation and retrieval (multimedia), human computer interaction, and augmented reality.
estimating geospatial trajectory of a moving camera. this paper proposes a novel method for estimating the geospatial trajectory of a moving camera. the proposed method uses a set of reference images with known gps (global positioning system) locations to recover the trajectory of a moving camera using geometric constraints. the proposed method has three main steps. first, scale invariant features transform (sift) are detected and matched between the reference images and the video frames to calculate a weighted adjacency matrix (wam) based on the number of sift matches. second, using the estimated wam, the maximum matching reference image is selected for the current video frame, which is then used to estimate the relative position (rotation and translation) of the video frame using the fundamental matrix constraint. the relative position is recovered upto a scale factor and a triangulation among the video frame and two reference images is performed to resolve the scale ambiguity. third, an outlier rejection and trajectory smoothing (using b-spline) post processing step is employed. this is because the estimated camera locations may be noisy due to bad point correspondence or degenerate estimates of fundamental matrices. results of recovering camera trajectory are reported for real sequences.
a novel approach to very fast and noise robust, isolated word speech recognition. a novel very light weight approach to isolated word speech recognition is introduced. the approach uses a new simplistic feature set and a neural network recognition system. the algorithm's main processing requirements are fft computation and a simple neural network comparison, making the method a suitable solution for low price embedded devices. the proposed method is tested on single speaker and multiple speaker test sets and the results are compared with a widely used speech recognition approach, presenting very fast recognition and quite good recognition rate.
image retrieval by local evaluation of nonlinear kernel functions around salient points. feature histograms based on the evaluation of haar integrals with nonlinear kernel functions were used successfully for the purpose of invariant content based image retrieval. in addition to being invariant to rotation and translation, the features have the advantage of preserving structural information of the image. the work presented here concentrates on the idea of calculating these features by evaluating the kernel functions around a small set of preselected points. these points are called the salient points and represent, together with their neighborhood, the most important visual information in an image. the use of these salient points leads to a better representation of the image. compared to previous work, experiments show that this method gives better retrieval results without introducing extra computational overhead.
a trainable low-level feature detector. we introduce a trainable system that simultaneously filters and classifies low-level features into types specified by the user. the system operates over full colour images, and outputs a vector at each pixel indicating the probability that the pixel belongs to each feature type. we explain how common features such as edge, corner, and ridge can all be detected within a single framework, and how we combine these detectors using simple probability theory. we show its efficacy, using stereo-matching as an example.
a comparative study between decision fusion and data fusion in markovian printed character recognition. a comparison is made between several hidden markov models in the context of printed character recognition. two hmms are first compared, one dealing with columns of a character image, the other dealing with lines. these 2 hmms are then associated in a decision fusion scheme combining the log-likelihoods provided by each hmm classifier. the statistical assumptions underlying the combination formula are described and the combination formula is shown to be an approximation of a real joint log-likelihood. the last experiment consists in building a single hmm, modeling the joint flow of lines and columns. this data fusion scheme is shown to be more accurate as it highlights correlations between line and column features.
affine structure from translational motion with varying and unknown focal length. in this paper a method for obtaining affine structure from an image sequence taken by a translating camera with varying and unknown focal length is presented. a general geometric constraint, expressed using the camera matrices, is derived and this constraint is used in a least squares solution of the problem. the proposed algorithm extends the previous result of affine structure recovery from an image sequence with a translating camera with constant intrinsic parameters to the case with a camera with varying and unknown focal length and otherwise known intrinsic parameters. the noise sensitivity of the method is evaluated in simulated experiments.
color texture signatures for art-paintings vs. scene-photographs based on human visual system. efficient image filters that classify web-images as photograph of a real-scenes or as paintings are very desired in a content-based image retrieval system. the main contribution of this paper is the proposition of two feature vectors, the receptive field profiles (rfps) and the composite visual feature (cvf), that effectively discriminate art-paintings from scene-photographs. the formulation of these signatures were inspired by the model and analysis of human visual system (hvs); the rfps are approximated by a multi-channel color gabor filters which capture color texture properties; the cvf measures color uniqueness, saturation and smoothness and edge discrepancy. experimentations on a database of 20,000 images, collected from the web, with extremely variable visual contents, shown a very promising classification results (93%). we found that rfps features are larger for photographs than for painting. the boundary separation between classes in feature spaces were modeled using gaussian mixture models (gmm) and support vector machines (svm). a comparative analysis is conducted and gmm shown higher performance.
semi-parametric model-based clustering for dna microarray data. various clustering methods have been proposed for the analysis of gene expression data, but conventional clustering algorithms have several critical limitations; how to set parameters such as number of clusters, initial cluster centers, and so on. in this paper, we propose a semi-parametric model-based clustering algorithm in which the underlying model is a mixture of gaussian. each gene expression data builds a gaussian kernel, and the uncertainty of microarray data is naturally integrated in the data representation. our algorithm provides a principled method to automatically determine parameters - number of components in the mixture, mean, covariance, and weight of each gaussian - by mean-shift procedure [2] and curvature fitting. after the initialization, expectation maximization (em) algorithm is employed for clustering to achieve maximum likelihood (ml). the performance of our algorithm is compared with standard em algorithm using real data as well as synthetic data.
from massively parallel image processors to fault-tolerant nanocomputers. parallel processors such as simd computers have been successfully used in various areas of high performance image and data processing. due to their characteristics of highly regular structures and mainly local interconnections, simd or simd-like architectures have been proposed for a large-scale integration of recently developed quantum and nanoelectronic devices. in this paper, we present a fault-tolerant technique suitable for an implementation in nanoelectronics, the triplicated interwoven redundancy (tir). the tir is a general class of triple modular redundancy (tmr), but implemented with random interconnections. a prototype structure for an image processor is proposed for the implementation of the tir technique and a simulation based reliability model is used to investigate its fault-tolerance. the tir is extended to higher orders, namely, the n-tuple interwoven redundancy (nir), to achieve higher system reliabilities. it is shown that the reliability of a general tir circuit is,inmost cases,comparablewiththat of anequivalent tmr circuit, and that the design and implementation of restorative devices (voters) are important for the nir (tir) structure. our study indicates that the nir (tir) is in particular suitable for an implementation by the manufacturing process of stochastically molecular assembly, and that it may be an effective fault-tolerant technique for a massively parallel architecture based on molecular or nanoelectronic devices.
video foreground segmentation based on sequential feature clustering. segmentation of videos into layers of foreground objects and background has many important applications, such as video compression, human computer interaction, and motion analysis. most existing methods work on image pixels or color segmentations which are computation expensive. some methods require extensive manual input, static cameras, and/or rigid scenes. in this paper we propose a fully automatic segmentation method based on sequential clustering of sparse image features. the sparseness makes the method computation efficient. we use both edge and corner features to capture the outline of the foreground objects. sequential linear regression is applied to the movement sequences of image features in order to compute the motion parameters for foreground objects and background layers, and consider the temporal smoothness simultaneously. foreground layer is then extracted by a pyramidal markov random field (mrf) model taking into account the spatial smoothness constraint. experimental results on videos taken by webcams are shown and discussed.
understanding inexplicit utterances using vision for helper robots. speech interfaces should have a capability of dealing with inexplicit utterances including such as ellipsis and deixis since they are common phenomena in our daily conversation. their resolution using context and a priori knowledge has been investigated in the fields of natural language and speech understanding. however, there are utterances that cannot be understood by such symbol processing alone. in this paper, we consider inexplicit utterances caused from the fact that humans have vision. if we are certain that the listeners share some visual information, we often omit or mention ambiguously things about it in our utterances. we propose a method of understanding speech with such ambiguities using computer vision. it tracks the human's gaze direction, detecting objects in the direction. it also recognizes the human's actions. based on these bits of visual information, it understands the human's inexplicit utterances. experimental results show that the method helps to realize human-friendly speech interfaces.
the morphological top-hat operator generalised to multi-channel images. the morphological top-hat operator for greyscale images is part of the basic toolbox of mathematical morphology operators. we discuss two ways of generalising the top-hat operator to multi-channel images, such as colour images. the first method presented is the use of a vectorial order in the relevant vector space. the second is based on the demonstration that the top-hat operator can be rewritten in terms of increments. these increments can be replaced by any vectorial distance function, removing the requirement to first impose an order on the vectors. we present examples of the use of the suggested top-hat operators in feature detection in colour images and defect detection in texture.
memory consistency validation in a cognitive vision system. ensuring the consistency of memory content is a key feature of cognitive vision systems. this paper presents an approach to deal with functional dependencies of hypotheses stored in a visual active memory. by means of bayesian networks a probabilistic approach is used to incorporate uncertainty of observations. furthermore, a measurement to detect inconsistencies in the memory is introduced. the benefit of this validation module as part of an integrated system is shown for the task of visual surveillance in an office scenario.
action recognition in awearable assistance system. enabling artificial systems to recognize human actions is a requisite to develop intelligent assistance systems that are able to instruct and supervise users in accomplishing tasks. in order to enable an assistance system to be wearable, head-mounted cameras allow to perceive a scene visually from a user's perspective. but realizing action recognition without any static sensors causes special challenges. the movement of the camera is directly related to the user's head motion and not controlled by the system. in this paper we present how a trajectory-based action recognition can be combined with object recognition, visual tracking, and a background motion compensation to be applicable in such a wearable assistance system. the suitability of our approach is proved by user studies in an object manipulation scenario.
color image enhancement by fuzzy intensification. a gaussian membership function to model image information in spatial domain has been proposed in this paper. we introduce a new contrast intensification operator, which involves a parameter t for enhancement of color images. by minimizing the fuzzy entropy of the image information, the parameter t is calculated globally. a visible improvement in the image quality for human contrast perception is observed, also demonstrated here by the reduction in 'index of fuzziness' and 'entropy' of the output image.
motion-based handwriting recognition for mobile interaction. this paper presents a new interaction technique for camera-enabled mobile devices. the handheld device can be used for writing just by moving the device. in our method, interframe dominant motion is estimated from images, and the discrete cosine transform is used for computing discriminating features from motion trajectories. the k-nearest neighbor rule is applied for classification. a realtime implementation of the method was developed for a mobile phone. in experiments, recognition rates ranging from 92 % to 98 % were achieved, which testifies to the practicality of our approach.
coupled shape model segmentation in pig carcasses. in this paper we are concerned with multi-object segmentation. for each object we will train a level set function based shape prior from a sample set of outlines. the outlines are aligned in a multi-resolution scheme wrt. an euclidean similarity transformation in order to maximize the overlap of the interior between all pairs of outlines. then the outlines are converted to level set functions. a shape model is constructed from the mean level set and the first few principal variations. we combine the prior model with an observation model based on the chan-vese functional assuming constant intensity levels inside the outline as well as in a narrow band outside the outline. the maximum a posteriori estimate of the outline is found by gradient descent optimization. in order to segment a group of mutually dependent objects we propose 2 procedures, 1) the objects are found sequentially by conditioning the initialization of the next search from already found objects; 2) all objects are found simultaneously and a repelling force is introduced in order to avoid overlap between outlines in the solution. the methods are applied to segmentation of cross sections of muscles in slices of ct scans of pig backs for quality assessment of bacon slices.
cluster analysis and priority sorting in huge point clouds for building reconstruction. terrestrial laser scanners produce point clouds with a huge number of points within a very limited surrounding. in built-up areas, many of the man-made objects are dominated by planar surfaces. we introduce a ransac based preprocessing technique that transforms the irregular point cloud into a set of locally delimited surface patches in order to reduce the amount of data and to achieve a higher level of abstraction. in a second step, the resulting patches are grouped to large planes while ignoring small and irrelevant structures. the approach is tested with a dataset of a builtup area which is described very well needing only a small number of geometric primitives. the grouping emphasizes man-made structures and could be used as a preclassification.
basic concepts for testing the torah code hypothesis. this is the first part of a tutorial discussing the major strategies and methodologies by which a test of the null hypothesis of no torah effect can be done. the basic concepts of equidistant letter sequence, skip specification, resonance specification, and compactness features are discussed here.
testing the torah code hypothesis: the experimental protocol. this is the second part of a tutorial discussing the experimental protocol issues in testing the torah code hypothesis. the principal concept is the test statistic which is used to do the actual hypothesis testing of the null hypothesis against a simple alternative or against a complex of alternatives. we illustrate the methodology using the data sets from the wrr[3] experiment. we use the wrr key word sets of list 1 and 2 combined. the experiment produces a p-value of less than 1/100,000 in the genesis text. we performed another experiment pairing rule based transliterations for the spellings of the names of the american presidents into hebrew with the hebrew word for president. taking into account bonferroni, the resulting p-value of the 100,000 trial experiment was less than 1/66,667.
human model for people detection in dynamic scenes. the problem of multiple people detection in monocular video streams is addressed. the proposed method involves a human model based on skin color and foreground information. robustness to local motion of background and global color changes is achieved by modeling images as fields of color distributions, and robustly estimating temporal background global variations. the estimation of the human model parameters is done via monte carlo simulations to deal with the multimodal nature of the posterior distribution, introduced by the presence of multiple people and cluttered scene. promising results are presented for transportation vehicles sequences.
recognizing hand gesture using fourier descriptors. this paper describes a novel application of fourier descriptor techniques for the recognition of hand gesture trajectories. appearance based coordinates of hand centroids and time steps are normalized to a fixed length by multirate techniques. fourier techniques are applied to the data to produce frequency domain data that is scale and translation invariant. the results of inputting the complex harmonic data to a probabilistic neural network for gesture classification are discussed. an understanding of underlying structure of gesture trajectories can be gained from modeling them as an infinite set of ellipses at given orientations. the rotation of the ellipses are visualized in the time domain as 'elliptic corkscrews'.
video shot interpretation using principles of perceptual prominence and perceptual grouping in spatio-temporal domain. we propose a computational model for generating an interpretation of a video shot based on our proposed principle of perceptual prominence. we also provide a formulation of the perceptual grouping problem in the spatio-temporal domain to identify the perceptual clusters. we illustrate our approach with experimental results.
bayesian ms lesion classification modeling regional and local spatial information. a fully automatic bayesian framework for multiple sclerosis (ms) lesion classification is presented, using posterior probability distributions and entropy values to classify normal and lesion tissue. spatial variability in intensities of multimodal mr images over the brain is explicitly modeled by building region-specific multivariate likelihood distributions. local smoothness is ensured by incorporating neighboring voxel tissue information using markov random fields. a probabilistic measure of confidence for the classification is then presented, which can also be used to assess disease burden. the method was tested on 10 patients with ms by comparing automatically classified lesions, with and without regional information, to manual classifications by five expert raters using volume count and overlap. results improve with the incorporation of spatial information, and are comparable to manual classifications. this method also enables a more accurate classification in the posterior fossa, where no other method reports success.
a hybrid tree approach for efficient image database retrieval with dynamic feedback. the need always exists for indexing mechanisms that can precisely retrieve imagery from a database, as well as maintain certain efficiencies for large-scale image database search. to achieve this, we developed a hybrid search tree called skd-metric tree. this novel approach merges the classification power of the statistical k-dimensional tree and the efficiency of computation of the metric-tree for nearest neighbor (nn) search. another feature of skd-metric tree is its flexibility to formulate a new metric function while the retrieval system utilizes user's feedback to improve accuracy. in addition, unlike traditional relevance feedback approaches that, in most cases, sequentially search the entire database to obtain new retrieval results, skd-metric tree features a fast retrieval refinement procedure that needs to update only a small portion of the database. an extensive study, based on experiments performed for evaluating retrieval precision and computational efficiencies, is presented. we have applied our approach to a large-scale medical image database. the experimental results show that skd-metric tree can achieve a high accuracy rate with dynamic relevance feedback that requires much less computation than existing techniques.
learning video processing by example. we present an algorithm that approximates the output of an arbitrary video processing algorithm based on a pair of input and output exemplars. our algorithm relies on learning the mapping between the input and output exemplars to model the processing that has taken place. we approximate the processing by observing that pixel neighborhoods similar in appearance and motion to those in the exemplar input should result in neighborhoods similar to the exemplar output. since there are not many pixel neighborhoods in the exemplars, we use techniques from texture synthesis to generalize the output of neighborhoods not observed inthe exemplars. the same algorithm is used to learn such processing as motion blur, color correction, and painting.
exploiting the geometry of gene expression patterns for unsupervised learning. typical gene expression clustering algorithms are restricted to a specific underlying pattern model while overlooking the possibility that other information carrying patterns may co-exist in the data. this may potentially lead to a large bias in the results. in this paper we discuss a new method that is able to cluster simultaneously various types of patterns. our method is based on the observation that many of the patterns that are considered significant to infer gene function and regulatory mechanisms all share the geometry of linear manifolds.
a robust method of recognizing multi-font rotated characters. this paper presents a new robust recognition method for rotated character images. we first construct an eigen sub-space for each category using the covariance matrix calculated from a sufficient number of rotated patterns averaged by several fonts. next, we can obtain a locus by projecting their rotated characters onto the eigen sub-space and interpolating between their projected points. an unknown character is also projected onto the eigen sub-space of each category. then, verification is carried out by calculating the distance between the projected point of the unknown character and the locus. in our experiment, we obtained quite good results for three fonts of 26 capital letters of the english alphabet.
electronic endoscope system for shape measurement. in endoscope observation, acquiring shape information of a lesion area is highly demanded for objective and statistical judgment. for in-vivo applications, a high-speed measurement is also considerable. therefore, we proposed an electronic endoscope system that equips an imagefiber and a laser scanner, and achieves the high-speed measurement by using the space-encoding method with laser-scanning. in our experiment, the measurement error was 1~2 % of the distance from the endoscope tip. moreover, the acquired shape information shows that can assist physician for understanding the surface topology of lesion and would be effective in computer aided diagnosis.
electronic endoscope system for shape measurement. in endoscope observation, acquiring shape information of a lesion area is highly demanded for objective and statistical judgment. for in-vivo applications, a high-speed measurement is also considerable. therefore, we proposed an electronic endoscope system that equips an imagefiber and a laser scanner, and achieves the high-speed measurement by using the space-encoding method with laser-scanning. in our experiment, the measurement error was 1~2 % of the distance from the endoscope tip. moreover, the acquired shape information shows that can assist physician for understanding the surface topology of lesion and would be effective in computer aided diagnosis.
a fingerprint verification algorithm using the differential matching rate. we propose a fingerprint verification algorithm with template matching based on the cyclic structure of the fingerprint image. for a correlation value between a template and a sensed image, we use the differential matching rate. the differential matching rate utilize the cyclic structure observed in the local area of a fingerprint pattern, which is calculated by the maximum matching rate minus the minimum matching rate detected near the point where the matching rate is maximum. in order to extract the maximum effectiveness of the cyclic structure, we compare divided windows of a template image against a sensed image. a verification experiment confirmed that the proposed method judges whether a template imageand a sensed image are same finger's fingerprints more accurately than the conventional method using the maximum matching rate as a correlation value. we obtain the equal error rate (eer) of 3.6%, which is better than half that of the conventional method.
ecoc and boosting with multi-layer perceptrons. the combination of boosting and ecoc with multi-layer perceptron base classifiers is experimentally evaluated for a problem in pose classification. while accuracy compared with ecoc is not improved, boosted ecoc ensembles are less sensitive to tuning parameters.
outlier detection using k-nearest neighbour graph. we present an outlier detection using indegree number (odin) algorithm that utilizes k-nearest neighbour graph. improvements to existing knn distance-based method are also proposed. we compare the methods with real and synthetic datasets. the results show that the proposed method achieves resonable results with synthetic data and outperforms compared methods with real data sets with small number of observations.
visible edges thresholding: a hvs based approach. this paper presents a technique, which determines whether an edge is visible for a human eye or not. first, a threshold function is built according to the optical characteristics of the sensor and a contrast sensitivity function (csf). then, the dct coefficients of each 8 × 8 block are computed. for each one, the computed spectrum is compared with the previous threshold function, which enables to conclude about the presence of visible picture elements. finally, this information is applied to edges detection using a binarization technique. results are given on images grabbed onboard a moving vehicle.
evaluating hierarchical graph-based segmentation. using real world images, two hierarchical graph-based segmentation methods are evaluated with respect to segmentations produced by humans. global and local consistency measures do not show big differences between the two representative methods although human visual inspection of the results show advantages for one method. to a certain extent this subjective impression is captured by the new criteria of 'region size variation
age and gender estimation based on wrinkle texture and color of facial images. we are researching about an age and gender estimation based on wrinkle texture and color of facial images. preliminary questionnaire (enquete) examination how effectively the facial images could be used for gender and age estimations was executed by using 300 different faces and 21 examinees. wrinkles appeared in the face and the shape and size of the facial parts are selected to model the age and gender estimation in this research basing on thisenquete. basing on this preliminal consideration, an image processing algorithm for wrinkle modeling was proposed in this paper. in addition, a method for making relationships between facial images and their keywords was proposed by using the latent semantic indexing. an efficient interface for displaying the relationships among keywords and facial images has been introduced with 2d/3d-feature space defined by the indexing.
human identification by spatio-temporal symmetry. we describe spatio-temporal symmetry and its extraction via a generalised symmetry operator. its use in gait recognition is reinforced by the view from psychology that human gait is a symmetrical pattern of motion. we show that by including temporal information in our symmetry calculations we are not recognizing people by their body shape but also by their motion. here, the new technique is applied to a database of 28 subjects, which equals in size the largest contemporaneous gait databases. the results of the new approach agree with earlier results that the symmetrical properties of human gait appear to be unique and can indeed be used for analysis and for recognition. the results achieved so far give promising performance and higher recognition rates than those of an earlier spatial approach. performance analyses suggest that symmetry enjoys practical advantages such as ability to handle noise and occlusion, and especially when resolution is too low for other biometrics to be deployed.
key techniques and methods for imaging iris in focus. automated iris recognition is a promising method for noninvasive verification of identity. how to acquire an iris image in focus is a key issue in iris recognition. based on imaging properties of a simple lens, working principles of fixed focus and auto focus imaging systems are described. key techniques for imaging iris in focus are discussed in this paper, such as illumination, lens design and self-alignment to position the iris in the system's depth of field. according to the techniques, a clear iris acquisition system is developed and experimental results are presented in this paper.
robust partial volume segmentation with bias field correction in brain mri. in mr imaging, image noise, bias field, and partial volume effect are adverse phenomena that increases intertissue overlapping and hampers quantitative analysis. this study provides a powerful fully automated classification method, which combines the bias field correction and pv segmentation together. the method has been validated on simulated and real mr images for which gold standard segmentation available. the experimental results show that the proposed method is more accurate and robust than currently available models.
w-boost and its application to web image classification. when training data is not sufficient, boosting algorithms tend to overfit as more weak learners are combined to form a strong classifier. in this paper, we propose a new variant of realboost, called w-boost, which is based on a novel weight update scheme and uses changeable bin number to estimate marginal distributions in weak learner design. this new boosting procedure results in both fast convergence rate and small generalization error. experimental results on synthetic data and web image classification demonstrate the effectiveness of our approach.
face recognition with relative difference space and svm. in this paper, a new method based on relative difference space (rds) and support vector machine (svm) is proposed for multi-class recognition. first the rds transformation converts the multi-class problem to a binary-class problem, and then svm is used for the binary classification directly. compared with the traditional method of difference space (ds), rds is reversible and it overcomes the illtransformation problem. this method is applied to face recognition in yale face database b, and the recognition result demonstrates its robust performance under different illumination conditions.
iris localization via pulling and pushing. iris localization is a critical module in iris recognition because it defines the inner and outer boundaries of iris region used for feature analysis. state-of-the-art iris localization methods need to implement a bruteforce search of the large parameter space, which is time-consuming and sensitive to noises. this paper proposes a novel iris localization method based on a spring force-driven iteration scheme. first, the coarse localization of pupil is obtained by an adaboost-based iris detection method. then the radial edge points are detected in polar coordinate, which contribute a force on the circle center based on hooke's law. finally the center and radius of pupil and iris are refined according to the composition of forces from all points. after 3-4 iterations, the precise location of iris could be found. experimental results show that our method is faster and more accurate than state-of-the-art iris localization methods.
texture image retrieval using novel non-separable filter banks based on centrally symmetric matrices. though millions of images are stored in a large digital image library today, the user can not access or make full use of these image information unless the digital image library is well organized in order to allow efficient browsing, searching and retrieval. thus, research in image retrieval has been an active discipline since 70's last century. image retrieval is a typical problem of pattern recognition, consisting of two parts: extracting features (ef) and similarity measurement (sm). in this paper, we develop new non-separable filter banks based on the centrally symmetric matrixes, and apply them to extract the features of texture images. compared to tensor product wavelets, our new filter banks can capture more directional texture information, which is helpful for texture image retrieval. experiments show that our novel non-separable filter banks are satisfiable and achieve a better retrieval effectiveness than daubechies wavelets.
dense estimation of layer motions in the atmosphere. in this paper, we address the problem of estimating dense motion fields related to a stratified atmosphere which is observed through satellite imagery. estimating the evolving vertical distribution of horizontal wind fields from satellite image time series is of great importance for the study of atmospheric dynamics. because of the sparse 3-dimensional nature of observations, classical correlation-based techniques are not suited for the dense estimation of layer motion. moreover, such methods are not necessarily temporally consistent. this paper proposes a sound energy-based estimator producing dense wind fields estimates for each partially observed atmospheric layer. the energy function to be minimized is composed of a data term based on the continuity equation which cancels out the influence of undesirable layers and of a specific div curl regularization term. to preserve the temporal consistency of the estimates, the variational method is initialized by propagation of the previous estimated field according to a velocity-vorticity formulation of navier-stokes equations. the relevance of our estimator is demonstrated on meteosat image sequences.
hand gesture recognition: self-organising maps as a graphical user interface for the partitioning of large training data sets. gesture recognition is a difficult task in computer vision due to the numerous degrees of freedom of a human hand. fortunately, human gesture covers only a small part of the theoretical "configuration space" of a hand, so an appearance based representation of human gesture becomes tractable. a major problem, however, is the acquisition of appropriate labelled image data from which an appearance based representation can be built. in this paper we apply self-organising maps for a visualisation of large amounts of segmented hands performing pointing gestures. using a graphical interface, an easy labelling of the data set is facilitated. the labelled set is used to train a neural classification system, which is itself embedded in a larger architecture for the recognition of gestural reference to objects.
multi-scale autoconvolution for affine invariant pattern recognition. this paper describes a novel image transform called multi-scale autoconvolution which is invariant with respect to affine transformations of the spatial image coordinates. the transform can be applied directly to image patches without segmentation. algebraically, the transform is simple requiring only rescaling of the image and computation of two-dimensional convolutions that can be performed efficiently in the frequency domain. similar transforms can also be derived for other linear distortions of the image. the experiments performed show that classification of complex patterns can be carried out reliably with only a small set of transform coefficients.
searching for similarities in nearly periodic signals with application to ecg data compression. this paper proposes a new methodology to identify and correlate patterns on nearly periodic signal, based on signal simplification and clustering approaches. using cubic bezier curves some significant signal samples (control points), enabling to segment adequately the original signal, are extracted in a first step. next, given the correlation among extracted control points, the detection of similarities within the overall signal is then performed through a clustering technique. although the approach is useful for many types of signals, the compression of electrocardiogram signals (ecg) is here investigated. results with standard mitbih databases show promising compression ratios, in particular, high compression ratios are found for long duration signals, when the signal presents strong regularities.
robust multihypothesis discrimination of controlled i.i.d. processes. this paper describes a general framework for the robust discrimination of objects represented as a family of i.i.d. random distributions. testing is based on accumulating evidences on the discrimination between all-pairs of hypotheses by sampling the family of distributions according to an optimal control law. the optimality criterion is built on constraint satisfaction issues. an application on 2d rotation invariant shape recognition with noisy contours illustrates the approach.
affine layer segmentation and adjacency graphs for vortex detection. in this paper we review and present different methods for the detection and characterization of vortices. our algorithm works on the segmentation of the image into affine layers. these layers are computed using a parametric tensor voting and encoded in an adjacency graph. paths are computed from the adjacency graph and are used for characterizing paths' properties such as: critical points and vortices. we illustrate the proposed approach to a satellite image sequence of water vapor in the atmosphere.
detection of presynaptic terminals on dendritic spines in double labeling confocal images. for the analysis of learning processes and the underlying changes of the shape of excitatory synapses (spines), 3-d volume samples of selected dendritic segments are scanned by a confocal laser scanning microscope. the images are unsharp because of the (direction dependent) resolution limit. a deconvolution on image data is not sufficient for the resolution needed. therefore a parametric model is used to reconstruct the dendrite and the spines. the parameter estimation of model is done in a two step approach. first, rough center axes of dendrite and spines are found by a growing model which can be adjusted interactively. in a second step the model parameters are optimized during an iterative process. to estimate the deviation between the microscope image and the model, the model is sampled with the same resolution as the microscope image and convolved by the microscope point spread function (psf). the result is a accurate model of dendrite and spines. the model fitting process is comparable with a deconvolution but with a limited number of model parameters and stable results without strong distortions by psf. the associated presynaptic terminal can be detected in a second image channel inside a region of interest (roi) on spine position. morphological features of spines from geometrical model and from second channel roi are combined for statistical analysis.
differential-algebraic multiview constraints. in this paper we present a novel type of multiview constraints, called dtfferential-algebraic multiview constraints. these constraints are based on both corresponding feature points and the motion of these feature points, thus combining the discrete multiview constraints with the continuous multiview constraints. the main usage of these constraints is as a theoretical basis forjltering approaches to structure and motion recovery, enabling an update of a current rnotion estimate when a new image becomes available. one importantfeature is that the update formula becomes linear in the motion parameters in the calibrated case, which is a major inzprovement compared to the standard discrete approach. another advantage is that fewer points are needed in the update formula then when calculating the motion without using a prior estimate.
scene recognition based on relationship between human actions and objects. in this paper, we propose a novel method for scene recognition using video images through analysis of human activities. we aim at recognizing three kinds of things such as human activities, objects and environment. in the previous method, locations and orientations of objects are estimated using shape models, which are often claimed to be dependent upon individual scene. instead of shape models, we employ conceptual knowledge about function and/or usage of objects as well as that about human actions. in our method, the location and usage of objects can be identified by observing interaction of human with them.
estimation of 3d motion trajectory and velocity from monocular image sequences in the context of human gait recognition. we propose a simple method for human gait recognition from monocular color image sequences which recovers the approximate 3d motion trajectory. we provide concrete evidence that object-to-image height ratios can be used for estimating 3d motion trajectories and motion velocities with sufficient accuracy for making judgments about the states of motion. we also introduce a method for estimating the leg frequency of a walking person.
quantification of shrinkage of lung lobe from chest ct images using the 3d extended voronoi division and its application to the benign/malignant discrimination of tumor shadows. in this paper, we prop ose a method to quantify the convergence of tissue in lung caused by cancer, using the three-dimensional (3d) extended voronoi division from chest x-ray ct images. the convergence is the phenomenon that the pulmonary tumors pull tissues such as blood vessels and interstitium toward the pulmonary tumors. because the malignant tumors (especially adenocarcinoma) often accompanies the convergence, quantification of the convergence is useful for the benign/malignant discrimination.we first calculate the voronoi diagrams using the vessel regions which were classified according to the radius of vessels.then a feature was calculated using the volumes of the v oronoiregions in the whole of lung region and those of the neighborho odof tumor region. the significant correlation between the proposed feature and the existence of the convergence is shown experimentally using actual ct images.
level-set evolution with region competition: automatic 3-d segmentation of brain tumors. we develop a new method for automatic segmentation of anatomical structures from volumetric medical images. driving application is tumor segmentation from 3-d mris, which is known to be a very challenging problem due to the variability of tumor geometry and intensity patterns. level-set snakes offer significant advantages over conventional statistical classification and mathematical morphology, however snakes with constant propagation need careful initialization and can leak through weak or missing boundary parts. our region competition method overcomes these problems by modulating the propagation term with a signed local statistical force, leading to a stable solution.a pre- vs. post-contrast difference image is used to calculate probabilities for background and tumor regions, with a mixture-modelling fit of the histogram. preliminary results on five cases with significant shape and intensity variability demonstrate that the new method might become a powerful and efficient tool for the clinic. validity is demonstrated by comparison with manual expert segmentation.
group-based relevance feedback with support vector machine ensembles. support vector machines (svms) have become one of the most promising techniques for relevance feedback in content-based image retrieval (cbir). typical svm-based relevance feedback techniques simply apply the strict binary classifications: positive (relevant) class and negative (irrelevant) class. however, in a real-world relevance feedback task, it is more reasonable and practical to assume the data come from multiple positive classes and one negative class. in order to formulate an effective relevance feedback algorithm, we propose a novel group-based relevance feedback scheme constructed with the svm ensembles technique. experiments are conducted to evaluate the performance of our proposed scheme and the traditional svm-based relevance feedback technique in cbir. the experimental results show that our proposed scheme is more effective than the regular method.
application of semiparametric density estimation to classification. a density estimation approach to statistical pattern recognition is discussed. the pattern vector is split into two parts factoring a high dimensional class density function into a product of two lower dimensional density functions. the first factor, corresponding to the non-gaussian structure in the data, is modeled nonparametrically. the second factor is modeled as a multivariate gaussian conditionally on the first part of the pattern vector. exploratory data analysis based on two-dimensional scatter plots is used to examine the plausibility of the density model. the proposed method is applied to classification of handwritten digits and satellite image data.
multimodal temporal pattern mining. this paper proposes an approach for mining multimodal temporal patterns from multiple synchronous signal sequences generated by different modalities. the instances of the temporal patterns suffer from noise and non-linear temporal warping. there are non-pattern signal segments separating the instances of the temporal patterns in the whole signal sequences. hidden markov models with thresholds of supports are trained to capture the sub-patterns in each modality. the sub-patterns have overlaps and can be stitched together to form complete temporal patterns. the temporal information of the instances the patterns in different modalities is then utilized to discover the multimodal temporal patterns.
vibratory image feature extraction based on local log-polar symmetry. we propose a feature extraction method for a newly developed vibratory image sensor. the proposed method extracts a local log-polar symmetry as image feature. in this article, it is shown that log-polar symmetric patterns include well-known characteristic points such as edges, corners, peaks, and so on. the principle of our method is as follows: a periodic vibration of an image sensor modulates radial and angular components of local image pattern into separated temporal frequency components of incident light on each pixel. comb type filters after a photo detector decompose the radial component and the angular one, and accumulate their powers in a frame time. these powers are read out for calculating unevenness between them. the unevenness indicates the strength of symmetry of corresponding local image pattern. because our method modulates local image pattern using image sensor's vibration, the extracted features are free from spatial quantization errors.
fusion algorithm for locally arranged linear models. as an extension to a recently proposed local linear approximation method we present an algorithm that generates more compact solutions for supervised-learning problems. given a network of linear models each trained to approximate the target function in a local region of the input space, the algorithm reduces the number of the models significantly without diminishing the accuracy of the approximation. it fuses linear models by combining their local regions of validity to more complex, non-symmetrically shaped ones. a neighborhood graph introducing edges in a purely data-driven manner between adjacent linear models is used to determine which models should be fused. the also extended model for a region of validity allows to detect automatically data which is novel to a trained network and should be regarded as an outlier. the effectiveness of the proposed methods is shown with a benchmark test achieving a five times smaller rmse than the best competitors.
fusion algorithm for locally arranged linear models. as an extension to a recently proposed local linear approximation method we present an algorithm that generates more compact solutions for supervised-learning problems. given a network of linear models each trained to approximate the target function in a local region of the input space, the algorithm reduces the number of the models significantly without diminishing the accuracy of the approximation. it fuses linear models by combining their local regions of validity to more complex, non-symmetrically shaped ones. a neighborhood graph introducing edges in a purely data-driven manner between adjacent linear models is used to determine which models should be fused. the also extended model for a region of validity allows to detect automatically data which is novel to a trained network and should be regarded as an outlier. the effectiveness of the proposed methods is shown with a benchmark test achieving a five times smaller rmse than the best competitors.
the effect of the inhibition-compensation learning scheme on n-tuple based classifier performance. the inhibition-compensation learning scheme (icls) has been proposed as a way of enhancing the performance of the moving window classifier . in this paper, the effect of icls on three n-tuple based classification techniques has been investigated. presegmented handwritten characters from the nist database have been used as the pattern data. results show that approximately 2-6% gain in classification accuracy can be achieved in the ocr task domain with no adverse effect on the classification throughput.
re-evaluating colour constancy algorithms. we present a re-evaluation of previous experimental data for five different colour constancy algorithms, based on experiments on real and synthetic images. our work is motivated by the observation that previous analysis of algorithm performance is flawed because it uses inappropriate statistical measures of performance. we discuss these flaws in detail and suggest more appropriate statistical tests. we show that using these tests conclusions as to the relative performance of algorithms are significantly changed as compared to the original analysis of the data. in particular we conclude that the performance of two algorithms: gamut mapping and color by correlation is statistically equivalent and significantly better than the three other algorithms tested (max-rgb and two versions of grey-world).
a real-time multi face detection technique using positive-negative lines-of-face template. this paper describes a real-time multi face detection technique for color video sequences. a 3d rational skin color model and a positive-negative lines-of-face template are proposed to improve signal to noise ratio (snr) in face detection. steady state genetic algorithm (ssga) is employed for lines-of-face detection from entire image. hardware architecture is optimized for high-speed operation and small hardware resources. an experimental system is developed in field programmable gate array (fpga), with only 40k gates for logic and 240k gates for memory. it detects 6 faces in real-time (30fps:every 33ms) from 320x240pixels (qvga) color video sequences. detection rate of 98% is achieved for 89 images including 205 faces from daily scenes.
comparison of support vector machines with autocorrelation kernels for invariant texture classification. support vector machines (svms) with autocorrelation kernels are applied to texture classification invariant to similarity transformations and noise. the inner product of autocorrelation functions of an arbitrary order is effectively calculated through the 2nd-order crosscorrelation of original data. texture classification experiments show that higher performance of svms is achieved by exploiting the autocorrelation kernels.
estimation of color for gray-level image by probabilistic relaxation. a color estimation method for a gray-level image is proposed by giving a few color pixels. it is known that a density value in the gray-level image will be calculated by linear combination of an rgb vector of the color image. the problem dealt with in this study can be formulated as an ill-posed problem which searches for an rgb vector from a density value as a solution. by assuming a restricted condition to minimize the total of the color difference defined among adjacent pixels, the color will be optimized by the probabilistic relaxation method. theperformance of the proposed method is verified by experiments. the proposed algorithm works very well when the solution is known with confidence in a few percents of the image.
similarity measure of labelled images. a similarity measure is developed for comparing labelled images. the proposed measure is calculated based on binary relations of arbitrary pixels in the labelled images. so, the proposed measure can evaluate the difference between two images speedy by pixel-to-pixel calculation. the measure can be used for not only spatial labelled images by area-based labelling such as region segmentation, but also colour labelled images by pixel-based labelling such as colour clustering. a few actual applications are shown in order to explain the behaviour.
a higher-order active contour model for tree detection. we present a model of a 'gas of circles', the ensemble of regions in the image domain consisting of an unknown number of circles with approximately fixed radius and short range repulsive interactions, and apply it to the extraction of tree crowns from aerial images. the method uses the recently introduced 'higher order active contours' (hoacs), which incorporate long-range interactions between contour points, and thereby include prior geometric information without using a template shape. this makes them ideal when looking for multiple instances of an entity in an image. we study an existing hoac model for networks, and show via a stability calculation that circles stable to perturbations are possible for constrained parameter sets. combining this prior energy with a data term, we show results on aerial imagery that demonstrate the effectiveness of the method and the need for prior geometric knowledge. the model has many other potential applications.
support vector machine with local summation kernel for robust face recognition. this paper presents support vector machine (svm) with local summation kernel for robust face recognition.in recent years, the effectiveness of svm and local features is reported.however, conventional methods apply one kernel to global features.the effectiveness of local features is not used in those methods. in order to use the effectiveness of local features in svm, one kernel is applied to local features.it is necessary to compute one kernel value from local kernels in order to use the local kernels in svm. in this paper, the summation of local kernels is used because it is robust to occlusion.the robustness of the proposed method under partial occlusion is shown by the experiments using the occluded face images. in addition, the proposed method is compared with the global kernel based svm.the recognition rate of the proposed method is over 80% under large occlusion, while the recognition rate of the svm with global gaussian kernel decreases dramatically.
adaptive weighting of local classifiers by particle filter. this paper presents adaptive weighting method for combining local classifiers by particle filter. in recent years, the effectiveness of combination of local classifiers (features) is reported. however, those methods can not cope with partial occlusion or shadows by illumination direction changes, because the stable weight is used for combining local classifiers. to be robust to them, the weight should be changed adaptively. namely, we must select the good weight set given high likelihood from the weight space adaptively. for this purpose, particle filter is used. each particle corresponds to the weight set for combining local classifiers. by selecting the particle (weight set) given high likelihood in current situation, the proposed method can cope with partial occlusion. the proposed method is applied to face tracking problem. performance is evaluated by using the test sequence that the occluded area is changed dynamically. the proposed method decreases the weight for occluded region automatically, and it can track face under partial occlusion. effectiveness of the proposed method is shown by comparison with stable weight set used in conventional methods.
pattern recognition using average patterns of categorical k-nearest neighbors. the typical nonparametric method of pattern recognition "k-nearest neighbor rule (knn)" is carried out by counting the labels of k-nearest training samples to a test sample.this method collects the k-nearest neighbors without taking into account a class, and it outputs the class of the test sample by using only the labels of neighborhoods.this paper presents a classifier that outputs the class of a test sample by measuring the distance between the test sample and the average patterns, which are calculated using the k-nearest neighbors belonging to individual classes.a kernel method can be applied to this classifier for improving recognition rates.the performance of the proposed method is verified by experiments with benchmark data sets.
filter algorithm for 3d pose estimation of maneuvering target. this paper presents a filter algorithm for more accurate 3d pose estimation of a maneuvering target. first, by analyzing the error propagation from the 2d images to the target pose, linear measurement equations are derived. then, two filter schemes are proposed. the first filter uses the maneuver detection technique, in which two detectors fit for fast and slow maneuvers are deduced respectively, and limited memory filtering is adopted for maneuver correction. in the second filter, a robust dynamic model is constructed by the numerical differentiation technique, and an adaptively estimated fading factor is imported to restrain the filter divergence. finally, the two filter modules are combined for more accurate estimation. superior to previous approaches that were limited to the slowly and smoothly moving target, this algorithm is applicable for a maneuvering target that acts in an unknown manner. simulation results show the capacity of this algorithm.
estimation of the fundamental matrix based on ev mode. this thesis presents a nonlinear method to estimate the fundamental matrix, a key problem arising in projective motion estimation and reconstruction, based on a general errors-in-variables (ev) model. in this model, the method considers that all the measurements are corrupted by noises, and minimizes a cost function derived from a nonlinear criterion to estimate both the fundamental matrix and corrupted data, involving the rank-2 constraint with reasonably adjusted data, this method turns out to significantly increase the accuracy and robustness with a simple form of computation. the performance of the proposed approach is justified by theory and assessed by several experiments on real images.
sketched symbol recognition using zernike moments. in this paper, we present an on-line recognition method for hand-sketched symbols. the method is independent of stroke-order, -number, and -direction, as well as invariant to scaling, translation, rotation and reflection of symbols. zernike moment descriptors are used to represent symbols and three different classification techniques are compared: support vector machines (svm), minimum mean distance (mmd), and nearest neighbor (nn). we have obtained a 97% recognition accuracy rate on a dataset consisting of 7,410 sketched symbols using zernike moment features and a svm classifier.
morphology-based license plate detection from complex scenes. this paper presents a morphology-based method for detecting license plates from cluttered images. the proposed system consists of three major components. at the first, a morphology-based method is proposed to extract important contrast features as guides to search the desired license plates. the contrast feature is robust to lighting changes and invariant to several transformations like scaling, translation, and skewing. then, a recovery algorithm is applied for reconstructing a license plate if the plate is fragmented into several parts. the last step is to do license plate verification. the morphology-based method can significantly reduce the number of candidates extracted from the cluttered images and thusspeeds up the subsequent plate recognition. under the experimental database, 128 examples got from 130 images were successfully detected. the average accuracy of license plate detection is 98%. experimental results show that the proposed method improves the state-of-the-art work in terms of effectiveness and robustness of license plate detection.
a shadow elimination method for vehicle analysis. this paper proposes a novel shadow elimination method for solving the shadow occlusion problems of vehicle analysis. different from traditional methods which only consider intensity properties in shadow modeling, this method introduces a new important feature to eliminate all unwanted shadows, i.e., lane line geometries. in this approach, a set of moving vehicles are first segmented from backgrounds by using a background subtraction technique. at this moment, each extracted vehicle may contain shadows which will cause the failure of further vehicle analysis. to remove these unwanted shadows, a histogram-based method is then proposed for detecting different lane dividing lines from video sequence. according to these lines, a line-based shadow modeling process is then applied for shadow elimination. two kinds of lines are used here for shadow elimination, i.e., the ones parallel and vertical to lane directions, respectively. different type of lines has different capabilities to eliminate different kinds of shadows. experiments demonstrate that approximately 92% of shadows can be successfully eliminated from moving vehicles.
improving retrieval performance by global analysis. in this paper, we propose a global analysis approach for query expansion in information retrieval. this approach, which concentrates on extracting associated expansion terms for a given query so as to improve the retrieval performance, can be divided into three stages. the first stage, called association calculation, is to measure associations between term-term pairs. the second stage focuses on how to select suitable terms for expansion. in the last stage, a reweighting scheme is introduced in order to clarify the impact of each expansion term. experimental results on the trec collection demonstrate the effectiveness of our approach.
tracking people through occlusions. in people tracking, one of the most challenging issues is occlusion handling. to cope with it, we introduce a bayesian network which involves human 2d ellipse models and an extra hidden process for occlusion relation. the 2d ellipse model combines color and spatial information simultaneously by creating color histograms for serval sub-regions. the extra hidden process for occlusion indicates the depth information of people through occlusions. the tracking process is performed using a condensation algorithm. experiments show the effectiveness of the proposed method.
robust projective reconstruction with missing information. this paper presents a robust approach based on evolutionary agents for projective reconstruction in the presence of missing data and unknown depths. agents denote possible submatrices for rank constraints, and carry out some evolutionary behavior to exploit a vast solution space. our approach combines the benefits of excellent searching ability of evolutionary agents for getting a good solution, with a proper treatment of missing information with linear fitting. experimental results demonstrate better performance of our approach than other typical methods in terms of accuracy and robustness to noise and missing data.
an interweaved hmm/dtw approach to robust time series clustering. we introduce an approach for model-based sequence clustering that addresses several drawbacks of existing algorithms. the approach uses a combination of hidden markov models (hmms) for sequence estimation and dynamic time warping (dtw) for hierarchical clustering, with interlocking steps of model selection, estimation and sequence grouping. we demonstrate experimentally that the algorithm can effectively handle sequences of widely varying lengths, unbalanced cluster sizes, as well as outliers.
normalization of functional magnetic resonance images by classified cerebrospinal fluid cluster. for functional magnetic resonance imaging (fmri) time series data, traditional intensity normalization techniques may introduce negative correlation with the neurological stimulation in non-activated voxels, and hence may cause incorrect identification of the activated/deactivited region. in this study, we present a modified proportional scaling method for intensity normalization using segmented specific tissue. in particular, the mean intensity across the classified cerebrospinal fluid (csf) cluster, instead of the one across the entire intracerebral voxels, is used for the rescaling of all voxel intensity of a particular image frame. the usefulness of the method is demonstrated on block design fmri data, which shows that the approach can avoid the negative shift in z statistics quite well. in addition, this strategy can also be applicable to the analysis of positron emission tomography (pet), single photon emission computed tomography (spect) and other functional imaging modalities.
moving obstacles extraction with stereo global motion model. extraction of moving obstacles from a moving observer is vital for many its applications like forward vehicle collision mitigation (fvcm) and adaptive cruise control (acc) systems. single camera based global motion model (gmm) like optical flow is commonly used in the past decade. this paper addresses a relatively new problem in the literature: gmm based on binocular stereovision which involves the depth (disparity) information in the model, thus global motion can be analyzed in 3d space rather than the traditional 2d image plane. an efficient algorithm is presented which parameterizes the gmm based on the 3d camera motion analysis within u-v-disparity domain. combining the geometric and motion information, regions that do not match the gmm will be extracted as moving obstacles.
a new kernel based on weighted cross-correlation coefficient for svms and its application on prediction of t-cell epitopes. t-cell epitopes play vital roles in immune response. its recognition by t-cell receptors is a precondition for the activation of t-cell clone. this recognition is antigen-specific. therefore, identifying the pattern of a mhc restricted t-cell epitopes is of great importance for immunotherapy and vaccine design. in this paper, we designed a new kernel based on weighted crosscorrelation coefficients for support vector machine and applied it to the direct prediction of t-cell epitopes. the experiment was carried on an mhc type i restricted t-cell clone lau203-1.5. the results showed that this approach is efficient and promising.
automatic pose recovery for high-quality textures generation. this paper proposes new techniques to generate high quality textures for urban building models by automatic camera calibration and pose recovery. the camera pose is decomposed into an orientation and a translation, an edge error model and knowledge-based filters are used to estimate correct vanishing points with heavy trees occlusion, and the vanishing points are used for the camera calibration and orientation estimation. we propose new techniques to estimate the camera orientation with infinite vanishing points and translation with under-constraints. the final textures are generated using color calibration and blending with the recovered pose. a number of textures for outdoor buildings are automatically generated, which shows the effectiveness of our algorithms.
boosting nested cascade detector for multi-view face detection. in this paper, a novel nested cascade detector for multi-view face detection is presented. this nested cascade is learned by schapire and singer's improved boosting algorithms that use real-valued confidence-rated weak classifiers [improved boosting algorithms using confidence-rated predictions], wherewe use confidence-rated look-up-table (lut) weak classifiers based on haar features. experiments show the system performance is significantly improved compared with previous methods.
a pixel-wise object tracking algorithm with target and background sample. in this paper, we present a clustering-based tracking algorithm for non-rigid object. non-rigid object tracking is a challenging task because the target often appears as a concave shape or an object with apertures. in such cases, many background areas will be mixed into the tracking target, which are difficult to be removed by modifying the shape of the search area. our algorithm realizes robust tracking for such objects by classifying the pixels in the search area into "target" and "background" with k-means clustering algorithm that uses both the "positive" and "negative" samples. the contributions of this research are: 1) using a 5d feature vector to describe both the geometric feature "(x, y)' and color feature "(y,u, v )" of an object (or a pixel) uniformly. this description enables the simultaneous adaptation of both the geometric and color variance during tracking; 2) using a variable ellipse model (a) to describe the search area; (b) to model the surrounding background. this guarantees the stable tracking of objects with various geometric transformations. through extensive experiments in various environments and conditions, the effectiveness and the efficiency of the proposed algorithm is confirmed.
segmentation of medical images with regional inhomogeneities. this paper presents a novel deformable model for accurate delineation of regions of interest in medical images that contain regional inhomogeneities. such images are common in various medical imaging domains including endoscopy and radiology. the proposed model improves the active contour without edges (acwe) model by excluding sparse regional inhomogeneities from both the foreground and the background of the images to be segmented. the proposed model is tolerant to noise and allows for the delineation of multiple objects. experiments were performed on both endoscopic and ultrasonic images from different organs. the results show that the proposed model can be effectively utilized for the delineation of abnormal tissue findings, and in presence of regional inhomogeneities it can be more accurate compared with the acwe model.
contrast context histogram - a discriminating local descriptor for image matching. this paper presents a new invariant local descriptor, contrast context histogram, for image matching. it represents the contrast distributions of a local region, and serves as a local distinctive descriptor of this region. object recognition can be considered as matching salient corners with similar contrast context histograms on two or more images in our work. our experimental results show that the developed descriptor is accurate and efficient for matching.
a wrapper for feature selection based on mutual information. this paper adopts a wrapper method to find a subset of features that are most relevant to the classification task. the approach utilizes an improved estimation of the conditional mutual information which is used as an independent measure for feature ranking in the local search operations. meanwhile, the mutual information between the predictive labels of a trained classifier and the true classes is used as the fitness function in the global search for the best subset of features. thus, the local and global searches consist of a hybrid genetic algorithm for feature selection. experimental results demonstrate both parsimonious feature selection and excellent classification accuracy of the method on a range of benchmark data sets.
road sign interpretation using matching pursuit method. this paper describes an automatic a new road sign interpretation method using matching pursuit (mp) filters. there are two processes. the detection process finds the relative position of road sign in the original distant image and then extract the internal content of road sign from the closer view image. the recognition process consists of two stages: training and testing. in the first stage, it finds a set of best mp filter bases for each road sign. in the second stage, it projects the input unknown road sign to different set of the mp filter bases to find the best match.
model-based human body tracking. visual tracking of human body movement is a key technology in a number of areas. in this paper we present a 2-d model-based method ofhuman body trackingfrom a monocular video sequence. morris & rehg put forward a 2-d scaled prismatic model (spm) for figure registration which has far fewer singularity problems than 3-d models. here we extend it in a 2-d cardboard human body model with additional one dof ofwidth change. we set up a mixture motion model for body movements and then solve body motion parameters using em in a statistical framework, where the model-based kinematic constraints are incorporated in a linear form. tracking results from real video sequences are encouraging.
a region-based method for model-free object tracking. we propose a region-based methodfor model-free object tracking. in our method the object information of temporal motion and spatial luminance are fully utilized. we first compute dominant motion of the tracked object. using this result we warp the object template to generate a prediction template. static segmentation is incorporated to modify this prediction, where the warping error of each watershed segment and its rate of overlapping with warped template are utilized to help classification of some possible watershed segments near the object bordel: applications of facial expression tracking and two-handed gesture tracking demonstrate its performance.
improving mmi with enhanced-fcm for the fusion of brain mr and spect images. recently, maximization mutual information (mmi) of image intensities has been proposed as a new matching criterion for automated multimodality image registration. however, the success of the mmi relies on the similarity of the histogram distribution between the images to be fused. this condition is usually hard to be achieved in practical application. besides, mmi is time consuming because it needs to find an optimal solution about six parameters (three for shifts and three for rotations) during the registration process. to overcome these drawbacks of using traditional mmi, a novel scheme, named improved mmi, which is based on fuzzy c-means (fcm) and mmi, is proposed. the experimental results, using mr and spect images, to confirm the superior performance of the proposed method in comparison with the traditional mmi method are also included.
a vision-based vehicle identification system. this paper presents a vision-based vehicle identification system which consists of object extraction, object tracking, occlusion detection and segmentation, and vehicle classification. since the vehicles on the freeway may occlude each other, their trajectories may merge or split. to separate the occluded objects, we develop three processed: occlusion detection, motion vector calibration, and motion field clustering. finally, the segmented objects are classified into seven different categorized vehicles.
a secret image sharing method using integer-to-integer wavelet transform. we present a new image sharing method based on the integer-to-integer (iti) wavelet transform and shamir's (r, m) threshold scheme that provide highly compact shadows for real time progressive transmission. our approach, working in the wavelet domain, processes the transform coefficients in each subband, divides each of the resulting combination coefficient into m shadows for sharing, and recovers the complete secret image using any r or more shadows(r \leqslant m). we take advantage of the properties of the wavelet multi-resolution representation of an image, such as coefficient magnitude decay and excellent energy compaction, to design combination procedures for transform coefficients and processing sequences in wavelet decomposition subbands such that compact shadows for real time progressive transmission are obtained.
solving the small sample size problem of lda. the small sample size problem is often encountered in pattern recognition. it results in the singularity of the within-class scatter matrix sw in linear discriminant analysis (lda). different methods have been proposed to solve this problem in face recognition literature. some methods reduce the dimension of the original sample space and hence unavoidably remove the null space of sw, which has been demonstrated to contain considerable discriminative information; whereas other methods suffer from the computational problem. in this paper, we propose a new method to make use of the null space of sw effectively and solve the small sample size problem of lda. we compare our method with several well-known methods, and demonstrate the efficiency of our method.
toward a speaker-independent real-time affect detection system. the ability to detect the human affective states is rapidly gaining interests among researchers and industrial developers since it has a broad range of applications. this paper reports the advances of human affect detection from acoustic signals in motorola labs. we focus on two parts of affect detection: emotion detection and conversational engagement detection. the emotion detection part is the major component of our system. the system is based only on acoustic information, that is to say, there is no recognizer and no linguistic or semantic information available. given the truth that speech is a short-time stationary signal, we employ the hidden markov model (hmm) to capture the variation and trend of acoustic signal structures caused by affective states. the affect-sensitive segmental features such as pitch, energy, zero crossing rate and energy slope are extracted to capture the finer structures of acoustic signals. each state of the hmm is modeled by a gaussian mixture model (gmm), which captures the range, mean, median and variability of above affect-sensitive measures. besides testing the algorithm in the ldc databases, we implement a real-time conversation monitor, which can recognize and express the eight basic human emotions and can detect the conversational engagement level.
a hybrid face recognition method using markov random fields. we propose a hybrid face recognition method that combines holistic and feature analysis-based approaches using a markov random field (mrf) model. the face images are divided into small patches, and the mrf model is used to represent the relationship between the image patches and the patch id's. the mrf model is first learned from the training image patches, given a test image. the most probable patch id's are then inferred using the belief propagation (bp) algorithm. finally, the id of the test image is determined by a voting scheme from the estimated patch id's. experimental results on several face datasets indicate the significant potential of our method.
moment-based shape priors for geometric active contours. in this paper a new method that incorporates moment-based shape information into geometric active contours is presented. as any shape may theoretically be characterized by its set of moments, the shape prior is represented based on legendre moments. by combining the shape prior with the powerful geometric active contours proposed by chan and vese, the improved model can retain all the advantage of the chan-vese model and have the additional ability of being able to compactly represent global shape of an object. experiments on synthetic and real image segmentation show the efficiency of our method.
a new iris segmentation method for recognition. as the first stage, iris segmentation is very important for an iris recognition system. if the iris regions were not correctly segmented, there would possibly exist four kinds of noises in segmented iris regions: eyelashes, eyelids, reflections and pupil, which will result in poor recognition performance. this paper proposes a new noise-removing approach based on the fusion of edge and region information. the whole procedure includes three steps: 1) rough localization and normalization, 2) edge information extraction based on phase congruency, and 3) the infusion of edge and region information. experimental results on a set of 2,096 images show that the proposed method has encouraging performance for improving the recognition accuracy.
moving object extraction with a localized pyramid. in this paper, we present a tracking initialization method that combines a rough extraction of moving objects and a refined segmentation of their contours. the extraction of moving objects is obtained with a classical global motion compensation. to obtain accurate contours of the objects, a spatial segmentation is performed with an original localized graph pyramid that focuses the segmentation process either on the object areas or on their borders.
a bayesian approach to video object segmentation via merging 3d watershed volumes. in this paper, we propose a bayesian approach to video object segmentation, which consists of two stages. in the first stage, we partition the video data into a set of 3d watershed volumes, where each watershed volume is a series of corresponding 2d image regions. these 2d image regions are obtained by applying to each image frame the marker-controlled watershed segmentation. in the second stage, we use a markov random field to model the spatio-temporal relationship among the 3d watershed volume. then, the desired video objects can be extracted by merging watershed volumes having similar motion characteristics within a bayeysian framework. our experiments have shown that the proposed method has great potential in extracting moving objects from a video sequence.
real-time camera pose and focal length estimation. this paper presents a novel approach to estimate the changing internal and external parameters of the camera in real time using a few 3d-2d point correspondences. we approach the problem by constructing two filters which can individually track motion and zoom respectively in a robust manner. then, the viterbi algorithm is used to select a filter depending on whether the camera is undergoing motion or zoom. we assume that the camera cannot move and zoom simultaneously, though our method can tolerate some hand held movement during zoom. the application of our approach is demonstrated on synthetic and real data.
bayesian feedback in data clustering. in many clustering applications, the user has some vague notion of the number and membership of the desired clusters. however, it is difficult for the user to provide such knowledge explicitly in the clustering process. we propose a solution to circumvent this difficulty by introducing a feedback mechanism. the notion of bayesian inference for relevance feedback in content-based image retrieval is modified for data clustering. given the number of clusters, the proposed algorithm seeks information about the target partition by asking the user a sequence of queries about whether a pair of objects should be put in the same cluster or not. information-theoretic criteria is adopted to select the queries to be presented to the user. the assumption made here is that cluster labels are "smooth", i.e., similar objects should share the same cluster labels. we show that it is possible to obtain reasonable partitions based on the user feedback alone, without the need of specifying a clustering objective function.
biometrics: a grand challenge. reliable person identification is an important problem in diverse businesses. biometrics, identification based on distinctive personal traits, has the potential to become an irreplaceable part of any identification system. while successful in some niche markets, the biometrics technology has not yet delivered its promise of foolproof automatic identification. with the availability of inexpensive biometric sensors and computing power, it is becoming increasingly clear that widespread usage of biometric person identification is being stymied by our lack of understanding of three fundamental problems: (i) how to accurately and efficiently represent and recognize biometric patterns? (ii) how to guarantee that the sensed measurements arenot fraudulent? and (iii) how to make sure that the application is indeed exclusively using pattern recognition for the expressed purpose (function creep [biometrics: personal identification in networked society])? solving these core problems will not only catapult biometrics into mainstream applications but will also stimulate adoption of other pattern recognition applications for providing effective automation of sensitive tasks without jeopardizing our individual freedoms. for these reasons, we view biometrics as a grand challenge - "a fundamental problem in science and engineering with broad economic and scientific impact".
landscape of clustering algorithms. numerous clustering algorithms, their taxonomies and evaluation studies are available in the literature. despite the diversity of different clustering algorithms, solutions delivered by these algorithms exhibit many commonalities. an analysis of the similarity and properties of clustering objective functions is necessary from the operational/user perspective. we revisit conventional categorization of clustering algorithms and attempt to relate them according to the partitions they produce. we empirically study the similarity of clustering solutions obtained by many traditional as well as relatively recent clustering algorithms on a number of real-world data sets. sammon's mapping and a complete-link clustering of the inter-clustering dissimilarity values are performed to detect a meaningful grouping of the objective functions. we find that only a small number of clustering algorithms are sufficient to represent a large spectrum of clustering criteria. for example, interesting groups of clustering algorithms are centered around the graph partitioning, linkage-based and gaussian mixture model based algorithms.
hiding a face in a fingerprint image. with the wide spread utilization of biometric identification systems, establishing the authenticity of biometric data itself has emerged as an important research issue. we present a fingerprint image watermarking method that can embed facial information into host fingerprint images. this scheme has the advantage that in addition to fingerprint matching, the recovered face during the decoding can be used to establish the authenticity of the fingerprint and the user.by computing the roc curves on a fingerprint database of 160 individuals, we show the advantages of the proposed watermarking scheme. further, our scheme does not introduce any significant degradation in the fingerprint matching performance.
preprocessing and recognition of characters in container codes. this paper describes the recognition of container code characters. the system has to deal with outdoor images which usually have damaged characters and obtain an answer in real time. tophat transformation, equalization and adaptive cropping have been applied so as to reduce the noise and correct the inclusion box. the training corpus is artificially grown by applying controlled deformations of the samples which increase the recognition rate. approximated nearest neighbours are used in order to perform a fast search with a large corpus.
an accurate shape reconstruction from photometric stereo using four approximations of surface normal. we present a new shape reconstruction method from photometric stereo. the method gives more accurate shapes than the existing method that uses three images and an algorithm based on the frankot-chellappa's to convert the surface normal to height. the new method, which is applicable to the case of two or more images available, solves the combination of two or more nonlinear equations representing the consistency between the reflectance maps and the observed images in an iterative way for the shape. and this is repeated for each of the four approximations of the surface normal and the results are averaged, to get a better shape estimate. computer experiments are made to show the usefulness of the method and to present some of the characteristics.
locating destination address block in korean mail images. in this paper, we propose a method of locating destination address blocks in both machine-printed and handwritten korean mail images. the proposed method extracts connected components from a binarized mail image, generates rough text lines by merging them, and then groups the text lines into nine clusters. a destination address block is determined by selecting some clusters. considering the geometric characteristics of information on korean mails, we segment a mail image into nine areas with an equal size. the nine clusters are initialized with the center coordinate of each area. a modified manhattan distance is used to calculate the distance between a text line and a cluster. we modified the distance function on which the aspect ratio of mail image could be reflected. the experiment done with live korean mail images has demonstrated the superiority of the proposed method. the success rate for the 1,988 testing images was about 93.56%.
sensor fusion as optimization: maximizing mutual information between sensory signals. sensor fusion is one of the fundamental issues to develop intelligent systems that recognize the scene around them precisely and robustly. previous approaches of sensor fusion combined different kind of sensors after feature extraction and abstraction ("task-level fusion"). this paper proposes a new approach that combines sensory signals from different kind of sensors before abstraction ("signal-level fusion"). by formalizing sensory fusion as an optimization that maximizes mutual information between sensory signals, a target in a changing scene is detected by heuristic search algorithm. as an example, experimental results of a sound source detection with one video camera one microphone are shown.
integrating independent components and support vector machines for gender classification. computer vision and pattern recognition systems play an important role in our lives by means of automated face detection, face and gesture recognition, and estimation of gender and age. we have developed a gender classifier with performance superior to existing gender classifiers. this paper addresses the problem of gender classification using frontal facial images. the testbed consists of 500 images (250 females and 250 males) randomly withdrawn from the feret facial database. independent component analysis (ica) is used to represent each image as a feature vector in a low dimensional subspace. different classifiers are studied in this lower dimensional subspace. our experimental results show the best accuracy of 96% in gender classification by combining ica and support vector machines (svms).
a peer dataset comparison outlier detection model applied to financial surveillance. outlier detection is a key element for intelligent financial surveillance system.the detection procedures generally fall into two categories: comparing every transaction against its account history and further more, comparing against a peer group to determine if the behavior is unusual. the later approach shows particular merits in efficiently extracting suspicious transaction and reducing false positive rate. peer group analysis concept is largely dependent on a cross-datasets outlier detection model. in this paper, we propose a new cross outlier detection model based on distance definition incorporated with the financial transaction data features. an approximation algorithm accompanied with the model is provided to optimize the computation of the deviation from tested data point to the reference dataset. an experiment based on real bank data blended with synthetic outlier cases shows promising results of our model in reducing false positive rate while enhancing the discriminative rate remarkably
fingerprint image enhancement by pixel-parallel processing. this paper proposes a fingerprint image enhancement algorithm that can be mapped onto the compact pixel-parallel architecture, such as a fingerprint identification chip that senses and identifies fingerprints by itself. the algorithm is composed of two parts. first, ridges are enhanced by extracting their center lines and removing white noises using the center line image. then valleys are enhanced by detecting areas where they are thin and disconnected and dilating them at these areas. both enhancements are done with the structures of the fingerprint maintained. the experimental results show fingerprint identification using the proposed image enhancement algorithm becomes much better, that the error ratio becomes a quarter of that of the conventional method, and the execution time is 0.14 msec when the proposed algorithm is performed on the array of processing elements in the fingerprint identification chip.
a hybrid, recursive algorithm for clustering expressed sequence tags in chlamydomonas reinhardtii. we present an efficient, fully automated algorithm to assemble ests into full-length cdna sequences that represent the complete coding regions of a gene. our est clustering algorithm is neither hierarchical nor incremental, but recursive, processing each est once. the algorithm exploits a variety of syntactic and statistical features of the ests. the resulting assembly shows significant improvement in computational efficiency and information extraction over a previous assembly of c. reinhardtii ests. the algorithm was developed using iterative and participatory design on c. reinhardtii; however, it can be used for any organism with a draft genomic sequence.
integrated region-based image retrieval using region??s spatial relationships. among representative content-based image retrieval schemes, region-based retrieval has shown promise in retrieving similar images that exhibit considerable local variations. however,since humans are accustomed to relying on object-level concepts rather than low-level regions, robust and accurate object segmentation is an essential step. while many interestingimage segmentation techniques have been proposed, their performance in practical applications remains limited. thus, integrating related regions into meaningful objects becomes a promising alternative. in this paper, we propose a new multiple-region level image retrieval algorithm based on region-level image segmentation and its spatial relationship. to capturespatial similarity, we apply hausdorff distance (hd) to our region-based image retrieval system-frip (finding region in the pictures). in contrast to other object or multiple region-based retrieval systems, we update classical hd to retrieve similar regions regardless of their spatial translation, insertion, and deletion. furthermore, we incorporate relevance feedback to reflect the user's high-level query and subjectivity to the system and to compensate for performance degradation due to imperfect image segmentation. the efficacy of our method is validated using a set of 3000 images from corel-photo cd.
video mosaicing for curved documents based on structure from motion. various methods for video mosaicing have been already investigated by many researchers. most of these methods, however, assume that the target object is flat or very far from the camera to avoid the disparity problem. this paper describes a novel video mosaicing method for curved documents based on 3-d reconstruction. with the proposed method, the mosaic image of the geometrically restored target document is generated, even if the document has a curved surface. experiments on curved documents have shown the feasibility of the proposed method.
registration of an uncalibrated image pair to a 3d surface model. the following data fusion problem is considered: given a 3d geometric model of an object and two uncalibrated images of the same object, and assuming that the object surface is textured and lambertian, precisely register the images to the model. solving this problem is necessary for building a geometrically accurate, photorealistic model from laser-scanned 3d data and high quality images. we generalise the photo-consistency approach by clarkson et al. [using photo-consistency to register 2d optical images of the human face to a 3d surface model] to the case of uncalibrated cameras, when both intrinsic and extrinsic parameters are unknown. this gives a user the freedom of taking the pictures by a conventional digital camera, from arbitrary positions and with varying zoom. we discuss a number of possible approaches to the problem and propose a method based on manual pre-registration followed by a genetic optimisation algorithm. the issues of speed and robustness are addressed. results for real data are shown.
representing cultural heritage in digital forms for vr systems through computer vision techniques. this paper overviews our research on digital preservation of cultural assets and digital restoration of their original appearance. geometric models are digitally achieved through a pipeline consisting of scanning, registering and merging multiple range images. we have developed a robust simultaneous registration method and an efficient and robust voxel-based integration method. on the geometric models created, we have to align texture images acquired from a color camera. we have developed a texture mapping method to utilize laser reflectance. in an attempt to restore the original appearance of historical heritage objects, we have synthesized several buildings and statues using scanned data and literature survey with advice from experts.
proposal of a parallel architecture for a motion detection algorithm. this paper proposes a parallel architecture for the estimation of motion of an underwater robot. it is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. in a motion estimation algorithm, correspondences between two images has to be solved at the low level. in the underwater imaging, normalised correlation can be a solution in presence of non-uniform illumination. due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed.
digitalwatermarking in contourlet domain. digital watermarking has been proposed as a method of copyright protection of audio, images, video and text. we propose to use the newly introduced transform for two dimensional signals, namely, the contourlet transform for image watermarking application. we have carried out simulations with two kinds of images- maps consisting of lot of curves and texts and those with textures. the watermarked images were subjected to different attacks like mean filtering, quantization and jpeg compression. it is observed that the contourlet based algorithm outperforms wavelet and dct based methods in this application. it is also apparent from the simulation results that contourlet based techniques give a distinct advantage over conventional techniques in images like maps which consist of lot of curves and texts.
gaussian mixture pdf in one-class classification: computing and utilizing confidence values. in this study a confidence measure for probability density functions (pdfs) is presented. the measure can be used in one-class classification to select a pdf threshold for class inclusion. in addition, confidence information can be used to verify correctness of a decision in a multi-class case where for example the bayesian decision rule reveals which class is the most probable. additionally, using confidence valueswhich represent in which quantile of the probability mass a pdf value resides ([0, 1]) - is often straightforward compared to using arbitrarily scaled pdf values. as the main contributions, use of confidence information in classification is described and a method for confidence estimation is presented.
automatic object-of-interest segmentation from natural images. in this paper, we propose a novel ooi (object-of-interest) segmentation algorithm from natural images that is based on human attention and semantic region merging. to do this, we segment an image into regions and merge them as a semantic object. then, we create an attention window based on saliency map and saliency points from an image. within the aw, a support vector machine is used to select the salient regions, which are then clustered into the ooi using the proposed region merging. unlike other algorithms, the proposed method allows multiple oois to be segmented according to the saliency map. experiments with the algorithm on more than 300 natural images have shown results close to human perception.
appearance-based nude image detection. in this paper, we propose an appearance-based nude image detection system. the proposed system is novel in that shape information is used to classify the nude images, and detect small nude images in a large background image. first, the proposed system finds skin regions using texture characteristics of the human skin, which then generates the skin likelihood image. since the skin likelihood image contains shape information as well as skin color information, we used the skin likelihood image as a high level feature to classify the nude images. the image feature vector (resized skin likelihood image) is used as an input to a nonlinear-svm. experimental results show that the proposed system can achieve an excellent classification performance. additionally, the proposed system can detect small nude images in a large image.
a stochastic optimization approach for parameter tuning of support vector machines. support vector machines (svms) are both mathematically well-funded and efficient in a large number of real-world applications. however, the classification results highly depend on the parameters of the model: the scale of the kernel and the regularization parameter. estimating these parameters is referred to as tuning. tuning requires to estimate the generalization error and to find its minimum over the parameter space. classical methods use a local minimization approach. after empirically showing that the tuning of parameters presents local minima, we investigate in this paper the use of global minimization techniques, namely genetic algorithms and simulated annealing. this latter approach is compared to the standard tuning frameworks and provides a more reliable tuning method.
principal curve analysis for temporal data. in this paper, we develop an algorithm for the learning of the medial axis of temporal random point sets, employing the principal curve analysis. the principal curve analysis is a generalization of principal axis analysis, which is a standard method for data analysis in pattern recognition.
two-hand gesture recognition using coupled switching linear model. we present a method coupling multiple switching linear models. the coupled switching linear model is an interactive process of two switching linear models. coupling is given through causal influence between their hidden discrete states. the parameters of this model are learned via em algorithm. tracking is performed through the coupled-forward algorithm based on kalman filtering and a collapsing method. a model with maximum likelihood is selected out of a few learned models during tracking. we demonstrate the application of the proposedmodel to tracking and recognizing two-hand gestures.
two-hand gesture recognition using coupled switching linear model. we present a method coupling multiple switching linear models. the coupled switching linear model is an interactive process of two switching linear models. coupling is given through causal influence between their hidden discrete states. the parameters of this model are learned via em algorithm. tracking is performed through the coupled-forward algorithm based on kalman filtering and a collapsing method. a model with maximum likelihood is selected out of a few learned models during tracking. we demonstrate the application of the proposedmodel to tracking and recognizing two-hand gestures.
hand gesture recognition for deaf people interfacing. in this paper, an approach for deaf-people interfacing using computer vision is presented. the recognition of alphabetic static signs of the spanish sign language is addressed. the proposed approach combines a number of norms to evaluate the distance of the current sign, to the sign models stored in a database (a dictionary). this solution leads to a largely selective criterion. the method is simple enough to provide real-time recognition, and works suitably for most letters.
historical hand-written string recognition by non-linear discriminant analysis using kernel feature selection. in this paper, we propose a method to compose a classifier by non-linear discriminant analysis using kernel method combined with kernel feature selection for holistic recognition of historical hand-written string. through experiments using historical hand-written string database hcd2, we show that our approach can obtain high recognition accuracy comparable to that of individual character recognition.
recognizing frontal face images using hidden markov models with one training image per person. recently, many important face recognition systems could deal well with frontal view face images. however few of them work well when there is only one training image per person. in this paper, we propose an approach to cope with the problem by using 1d discrete hidden markov model (1d-dhmm). the model training and recognition part were carried out on both vertical and horizontal directions. new way of extracting observations and using observation sequences in recognition is introduced. the haar wavelet transform was applied to the image to lessen the dimension of the observation vectors. our experiment results tested on the frontal view ar face database show that the proposed method outperforms the pca, lda, lfa approaches tested on the same database.
non-iterative two-dimensional linear discriminant analysis. linear discriminant analysis (lda) is a well-known scheme for feature extraction and dimensionality reduction of labeled data in a vector space. recently, lda has been extended to two-dimensional lda (2dlda), which is an iterative algorithm for data in matrix representation. in this paper, we propose non-iterative algorithms for 2dlda. experimental results show that the non-iterative algorithms achieve competitive recognition rates with the iterative 2dlda, while they are computationally more efficient than the iterative 2dlda.
an intelligent real-time vision system for surface defect detection. in recent years, there is an increased need for quality control in the manufacturing sectors. in the steel making, the rolling operation is often the last process that significantly affects the bulk microstructure of the steel. the cost of having defects on rolled steel is high because it takes more than 5000 kw-hr to produce a ton of steel. early detection of defects can reduce product damage and manufacturing cost. this paper describes a real-time visual inspection system that uses support vector machine to automatically learn complicated defect patterns. based on the experimental results generated from over one thousand images, the proposed system is found to be effective in detecting steel surface detects. the speed of the system for feature extraction and defect detection is less than 6 msec per one-megabyte image.
improved stone's complexity pursuit for hyperspectral imagery unmixing. as a blind source separation (bss) process, independent component analysis (ica) has recently been used in hyperspectral imagery (hsi) unmixing. it models a "mixed" pixel as a linear mixture of the constituent (endmember) spectra weighted by the correspondent abundance fractions. however, the unmixing results of ica are not satisfied. in this paper, a complexity based bss algorithm called complexity pursuit is introduced. compared to the other bss techniques, this algorithm has two major advantages. first, it does not ignore signal structure. second, the impact of noise can be largely reduced. in addition, an improved conjecture is proposed which makes complexity pursuit suitable for hsi unmixing. the experimental results show that complexity pursuit provides a promising approach to unmix hsi. keywords: complexity pursuit, independent component analysis, hyperspectral imagery unmixing
three-dimensional enhancement of confocal scanning laser fluorescence microscope images for vascular reconstruction. this paper presents a fast method for enhancing the images of the vascular network of zebrafish embryo from confocal scanning laser microscope (cslm) stained with fluorescent probe. specifically, we split the 3d enhancement process into two separate stages and adoptdifferent methods respectively to deconvolve the lateral and optical directions in the observed images. the resulting algorithm increased both lateral and optical resolution and decreased the out of focus light of the images. the enhanced volumetric image is characterized by an improvement both in contrast and edge definition. the algorithm can be efficiently implemented on a general pc and the computation time is small even for the case of large volume of images. the value of the method for enhancing fluorescence images of biological objects is demonstrated by a comparison of the results of 3d vascular reconstruction.
an advanced segmental semi-markov model based online series pattern detection. the online pattern detection technology is an important part of the time series analysis, and some methods have been proposed, in which subsequence matching based window-sliding is popular applied. for window-sliding, euclidean distance and dynamic time warping (dtw) are always used as subsequence matching, but they have the drawbacks of sensitivity and expensive computational load respectively. recently, the model based method is introduced into the field of online pattern detection, especially, the segmental semi-markov model shows better performance than sliding methods in many aspects. however, it has some limitations, e.g., it is difficult to estimate the parameters of the model, and nowaday methods are too rough, etc. in this paper the advanced segmental semi-markov model is proposed to improve the existed segmental semi-markov model. and it is successfully demonstrated on real data sets, including financial and medical data.
gaussian weighted histogram intersection for license plate classification. the conventional histogram intersection (hi) algorithm computes the intersected section of the corresponding color histograms in order to measure the matching rate between two color images. since this algorithm is strictly based on the matching between bins of identical colors, the final matching rate can be easily affected by color variation caused by various environment changes. in this paper, a gaussian weighted histogram intersection (gwhi) algorithm is proposed to facilitate the histogram matching via taking into account matching of both identical and similar colors. the weight is determined by the distance between two colors. the algorithm is applied to license plate classification. experimental results show that the proposed algorithm produces a much lower intra-class distance and a much higher inter-class distance than previous hi algorithms for tested images which are captured under various illumination conditions.
3d shape-based face recognition using automatically registered facial surfaces. in this paper, we address the use of three dimensional facial shape information for human face identification. we propose a new method to represent faces as 3d registered point clouds. fine registration of facial surfaces is done by first automatically finding important facial landmarks and then, establishing a dense correspondence between points on the facial surface with the help of a 3d face template-aidedthin plate spline algorithm. after the registration of facial surfaces, similarity between two faces is defined as a discrete approximation of the volume difference between facial surfaces. experiments done on the 3d rma dataset show that the proposed algorithm performs as good as the point signature method, and it is statistically superior to the point distribution model-based method and the 2d depth imagery technique. in terms of computational complexity, the proposed algorithm is faster than the point signature method.
a miniature stereo vision machine (msvm-iii) for dense disparity mapping. we have developed a miniature stereovision machine (msvm-iii) with three cameras for generating high-resolution dense disparity maps at the video rate. the msvm-iii only uses one fpga chip to compactly compute trinocular rectification, log filtering, and area-based matching. the machine, running at 60 mhz, could process more than 30 fps dense disparity maps with 640×480 pixels in 64-pixel disparity search range, and 120 fps with 320×240 pixels. moreover, the msvm-iii has an ieee 1394 port to a host at the video rate, an interface port to lcd as a miniature 3d imager, and a user board for controlling small mobile robot or other autonomous systems.
graph database filtering using decision trees. graphs are a powerful representation formalism for structural data. they are, however, very expensive from the computational point of view. in pattern recognition it is often necessary to match an unknown sample against a database of candidate patterns. in this process, however, the size of the database is introduced as an additional factor into the overall complexity of the matching process. to reduce the influence of that factor, an approach based on machine learning techniques is proposed in this paper. graphs are represented using feature vectors. based on these vectors a decision tree is built to index the database. the decision tree allows at runtime to eliminate a number of graphs from the database as possible matching candidates.
a pattern recognition approach to automated coronary calcium scoring. an automated method for coronary calcification detection is presented. first the heart region is extracted, in which objects potentially representing calcifications are obtained by thresholding. besides coronary calcifications, the set of objects includes other heart calcifications, bony structures and noise. for each object, features describing its size, shape, position and appearance are computed. several classifiers and classification strategies are evaluated. best results are obtained with a specifically designed sequence of knn classifiers that employ sequential forward feature selection. first obvious non-calcifications are removed, then calcifications are distinguished from non-calcifications and a final classifier discerns coronary calcifications from other cardiac calcifications. in 14 ct scans containing 61 coronary calcifications, 46 (75%) are detected at the expense of on average 0.9 false positive objects per scan.
substring alignment method for lexicon based handwritten chinese string recognition and its application to address line recognition. this paper presents a lexicon based method for chinese string recognition. in this method, we recognize a chinese string image as a whole by matching it against lexicons in a database. we first over-segment the input line image into a series of radicals and recognize all the possible radical combinations. we then search for candidate lexicons in a given database according to the extracted keywords. each lexicon is compared with the image to find the best match between the radicals and the given string by substring alignment. in this process, the segmentation and recognition results are determined synchronously. our method is tested on 500 handwritten images of chinese address and achieves a correct rate of 87% in address match.
identification of degraded traffic sign symbols by a generative learning method. we present a novel training method for recognizing traffic sign symbols undergoing image degradations. in order to cope with the degradations, it is desirable to use similarly degraded images as training data. our method artificially generates these data from an original image in accordance with the actual degradations. we experimentally confirmed the usefulness of our method for the camera-based traffic sign recognition.
likelihood word image generation model for word recognition. this paper describes a new word image generation model for word recognition. this model can generate a word image with likelihood based on linguistic knowledge, segmentation and character image. in the recognition process, first, the model generates the word image which approximates an input image best for each of a dictionary of possible words. next, the model calculates the distance value between the input image and each generated word image. the efficiency of the proposed method as evaluated in an experiment using type-written museum archive card images. results show that a recognition rate of 99.8% was obtained, compared with only 70.3%f or a recently published comparator algorithm.
convex quadratic programming for object localization. we set out an object localization scheme based on a convex programming matching method. the proposed approach is designed to match general objects, especially objects with very little texture, and in strong background clutter; traditional methods have great difficulty in such situations. we propose a convex quadratic programming (cqp) relaxation method to solve the problem more robustly. the cqp relaxation uses a small number of basis points to represent the target point space and therefore can be used in very large scale matching problems. we further propose a successive convexification scheme to improve the matching accuracy. scale and rotation estimation is integrated as well so that the proposed scheme can be applied to general conditions. experiments show very promising results for the proposed method in object localization applications.
synthesis of stereoscopic 3d videos by limited resources of range images. recently, depth-image-based rendering has been suggested for 3d video creation, in which a monoscopic video stream is recorded along with a depth (range) video stream and a stereoscopic video stream is then generated at the user end. the fundamental assumption of this framework is the full availability of range images at video rate. in this work we alleviate this hard demand and assume that only limited resources of range images are available, i.e. corresponding range images exist for some, but not all, color images of the monoscopic video stream. we propose to synthesize the missing range images between two consecutive range images. our approach eases the recording of 3d material by using less expensive range sensors and enables to enhance existing 2d video material with 3d effect by limited manual overhead. experiments on real videos have demonstrated very encouraging results. especially, one 3d video was generated from a 2d video without any sensory 3d data available at all. in a quality evaluation using an autostereoscopic 3d display the test viewers have attested similar 3d video quality for our synthesis technique and rendering based on depth ground truth.
face and head detection for a real-time surveillance system. this paper describes a face and head detection method for a real-time surveillance system. since there is no guarantee that surveillance cameras can capture frontal face or full-body of human, face and head detection has an advantage for the practical use. proposed method employs four directional features and linear discriminant analysis. it can detect face and head simultaneously, and reduce computation cost. in the experiments, comparison of two classifiers and evaluation of proposed human detection method were performed using still images and video scenes. the results showed that the performances of two classifiers were almost equivalent. thus, the classifier labeled face samples to one class was better in terms of computation cost. in the human detection experiment, the results were 87.2% (48/55) for human detection rate, and 83.6% (832/995) for reliability of detection. the proposed detection method was implemented on a pc and run at approximately over 10fps for vga input with motion detection.
reference point detection for fingerprint recognition. a fingerprint recognition algorithm needs to recover the pose transformation between the input fingerprint and the template. one solution is to determine a unique reference point for fingerprint alignment. this work develops a new algorithm to detect a unique reference point consistently for all types of fingerprints. our detection algorithm works on the orientation field smoothed with an adaptively varying neighborhood. the adaptive window is used to attenuate noise of orientation field effectively while maintaining the detailed orientation information in the high curvature area. a new approach of reference point localization is proposed that is based on hierarchical analysis of the orientation coherence. experiments demonstrate that our developed algorithm consistently locates a unique reference point with high accuracy for all types of fingerprints.
perfect perspective projection using a varifocal mirror and its application to three-dimensional close-up imaging. an imaging system with a focusing mechanism based on perfect perspective projection was devised using a varifocal mirror to achieve high-quality three-dimensional imaging and precise measurement of shapes. it was constructed so that the varifocal mirror was placed at the object focal point of the image-taking lens. the focal point of the lens was fixed when focusing with the varifocal mirror. magnification was exactly equal to the ratio of the focal length and the object point distance from the object focal point of the lens. this held at magnifications larger than unity. the surface shape of a spherical dent (3.5 mm in diameter) could accurately be measured with the shape-from-focus method because the dent could be viewed from the side in the perspective projection system.
supervised evaluation methodology for curvilinear structure detection algorithms. curvilinear structures are useful features in a variety of applications. compared to other commonly used features such as edges, there is relatively few work on curvilinear structure detection and its performance evaluation. in this paper we propose a novel supervised methodology for evaluating the performance of curvilinear structure detection algorithms. we consider the two aspects of performance, namely detection rate and detection accuracy, separately, in contrast to their mixed handling in earlier approaches that typically produces biased impression of detection quality. by doing so, the proposed performance measures giveus a more informative and precise performance characterization. we will demonstrate the advantages of our approach using both synthetic and real examples.
a compact model of human postures extracting common motion from individual samples. model-based markerless human motion capture is ofien affected by instabilities of estimation mainly due to high degrees of freedom and inaccuracies in the body model. the authors propose a compact model of human postures which extracts common motion across different persons from individual samples. our analysis on motion capture data shows that individualities appear as constant offsets that represent individual figures. the proposed model compactly describes the variations of postures in common motion by using a low-dimensional linear model. experimental results show that our model gives moderate constraints to improve the accuracy of posture estimation from a single image of an unknown person whose body size is unknown.
graph based image matching. given two or more images, we can define different but related problems on pattern matching such as image registration, pattern detection and localization, and common pattern discovery. these problems have different levels of purpose and difficulties, as a result, often associate with different solutions. in this paper, we propose a novel approach to solve these problems under a unified framework based on graph matching. we first split the images into small blocks and represent each block as a node in a bipartite graph. a maximum weighted bipartite graph matching algorithm is then employed in an iterative way to find the best transformation set. experimental results show that our approach can handle rotation, scaling and translation, as well as distortion and occlusion. another virtue of our approach is its efficiency.
shape alignment by learning a landmark-pdm coupled model. this paper revisits the model-based approaches for groupwise shape alignment. the key contribution is modeling the landmarks instead of considering them as nodes sliding along the shape contour. the shape group is thus modeled by a landmark-pdm coupled model instead of a constrained point distribution model (pdm). this coupled model is estimated by a stable four-stage estimation algorithm. there are two significant achievements. first, shapes are aligned in a fully unsupervised manner - both the number and location of landmarks are automatically decided. second, extremely noisy and largely deformed shapes can be robustly aligned. these are demonstrated using both synthesized and real data.
fast and accurate facial pose estimation by aligning a 3d appearance model. this paper proposes a method to estimate facial pose, ranging from frontal to profile, from an image captured under various illumination conditions. our proposed method formulates pose estimation by minimization of the errorbetween the target image and an image reproduced by a 3dappearance model. taking a rough initial estimate, the pose is optimized so that the error is decreased by the steepest descent. the performances for static and realtime pose estimation are evaluated with test images captured under drastically varied illumination conditions. the experimental results show that our proposed method estimates facial poses including rotations indepth up to 60 degrees from the frontal with an average error of 2.3 degreeseven when the initial error is 10 degrees. our proposed method is fast enough to realize a realtime face tracking system which runs at 20 frames per second on a pentium 4 3.2 ghz pc.
an enhanced appearance model for ultrasound image segmentation. active appearance model (aam) [active appearance models] had been popular on object segmentation for medical images. however, its performance is not good on ultrasound (us) images. in this paper, we propose an enhanced appearance model which represents the texture by edge structure [on representing edge structure for model matching] and reduces the view-dependent feature of us images by a novel data normalization process. in our experiments on general us data, the proposed model shows considerable improvements compared to the original one [active appearance models].
a method of reducing speckle noise of sar images based on wavelets and wedgelet hmt models. in terms of the statistical characteristic of sar images, combining the multi-scale wavelets and wedgelet approximation with hmt models, a novel method of reducing speckle noise of sar images is presented in this paper. furthermore, analyze the mechanism and computation complexity of this technique. the validity and efficiency are shown by experiments.
detection and recognition of moving objects by using motion invariants. motion invariant features, which are called either absolute or relative invariant linear features, are useful for detection and recognition of moving objects from image streams. we conducted simple experiments using these invariant features. the first experiment tested our method for moving object recognition with a fixed camera using absolute invariant linear features. in the second experiment, another method was used to detect moving objects with a moving camera using both relative and absolute invariant linear features. the results of these experiments confirmed the effectiveness of the proposed methods.
a non-parametric hmm learning method for shape dynamics with application to human motion recognition. the shape dynamics, i.e., the spatial-temporal shape deformation of an object during its movement, provides much important information about the identity of the object, and even motions performed by the object. in this paper, we proposed a system recognizing object motions based on their shape dynamics. in the proposed system, we use kenall's definition of shape to represent the object contour extracted from each frame, and construct a tangent space with the full procrustes mean shape as the pole to approximate a linear space for the dataset, in which the euclidean distance metric can be used to approximate the full procrustes distance between shapes. the spatial-temporal shape deformation in motions is captured by hidden markov models. since in the traditional hmm framework the hidden states are typically coupled with the training data, which will bring many undesired problems to the learning procedure, we introduce a non-parametric hmm approach that uses continuous output hmms with arbitrary states (decoupled from training data) to learn the shape dynamics directly from large amounts of training data where a non-parametric kernel density estimation algorithm is applied to learn the observation probability distribution in order to compensate for the uncertainty introduced by those arbitrary hidden states. this optimizes the hmm training procedure. we then use the proposed system for view-dependent human motion recognition.
recovering structures and motions from mutual projection of cameras. in this paper, we propose a new method for recovering camera motions and structures of the scene accurately and reliably.for recovering motions and structures, it is very important to compute the epipolar geometry accurately. although some linear methods have been proposed for computing theepipolar geometry, they are still less accurate than non-linear methods. the non-linear methods, on the other hand, require a lot of computational power, and sometimes fall into local minima. in this paper, we show that by using the actual projection of cameras, the epipolar geometry can be computed much more reliably from less image correspondences by a linear method. we also show that by using the epipolar geometry derived from the mutual projection of cameras, the structures of the scene can be recovered much more accurately and reliably than the existing methods.
a probabilistic model for camera zoom detection. camera motion detection is essential for automated video analysis. we propose a new probabilistic model for detecting zoom-in/zoom-out operations. the model uses em to estimate the probability of a zoom versus a non-zoom operation from standard mpeg motion vectors.traditional methods usually set an empirical threshold after deriving parameters proportional to zoom, pan, rotate and tilt. in contrast, our probabilistic model has a solid probabilistic foundation and a clear, simple probability threshold. experiments show that this probabilisticmodel significantly out-performs a baseline parametric method for zoom detection in both precision and recall.
spoken document classification with svms using linguistic unit weighting and probabilistic couplers. the task addressed by this paper is spoken document classification (sdc) of german tv news with support vector machines (svms). it shows the benefits of weighting different linguistic units when combined into one feature vector. further experiments show that probabilistic svms (psvms) with recently introduced couplers perform well on a sdc task. new couplers for multi-category classification, both for psvms and non-psvms, will be discussed. they are easy to implement and show good and promising results. it turns out that using the distance instead of the decision value can be favorable. theoretical justification is given for our approaches, and some results are explained theoretically.
a novel adaptive image enhancement algorithm for face detection. image enhancement techniques are discussed in this paper as a necessary preprocessing step for face detection. first, a measure of the distribution of image information, termed the entropy error rate (eer), is presented on the basis of information theory. then, by integrating a histogram ridge analysis technique and an optimal intensity transform method that aims to minimize the eer of an enhanced image, a novel adaptive enhancement algorithm is proposed. in a baseline face detection test using the algorithm presented by viola et al. in [robust real-time object detection], comparison experiments are conducted with the yale b face dataset and our own movie face dataset. the results demonstrate that image enhancement preprocessing can significantly improve face detection accuracy, and that the adaptive enhancement algorithm performs much better than classical histogram-based enhancement techniques such as linear stretching and histogram equalization.
a hybrid resampling framework for facial shape alignment. the modelisation of human faces from single or multiple images can be solved by fitting an active appearance model (aam). however, fitting such models with unknown prior estimation is a challenging task since shape and appearance are closely linked. in this paper, we address the efficiency of the sampling technique in regard to the shape alignment accuracy. the hybrid method we propose is based on a non-uniform barycentric resampling of the face model. the selected subsampled locations are improving the representativity of the generic texture reference.
speech separation from background of music based on single-channel recording. this paper presents a speech separation algorithm, which is capable of extracting speech signals from music background when given only a single-channel recording. the main idea is to employ both the tool of spectrogram and the image processing methods to solve the problem of speech signals processing. edge detection algorithm and hough transform are used to detect the fundamental frequency and the corresponding harmonic components of the music. the experimental results show that the proposed algorithm can effectively remove background music from the input signals and output the speech signals needed.
dense wide-baseline disparities from conventional stereo for immersive videoconferencing. we propose an algorithm creating consistent, dense disparity maps from incomplete disparity data generated by a conventional stereo system used in a wide-baseline configuration. the reference application is ibr-oriented immersive videoconferencing, in which disparities are used by a view synthesis module to create instantaneous views of remote speakers consistent with the local speaker's viewpoint.we perform spline-based disparity interpolation within non-overlapping regions.regions are defined by discontinuity boundaries identified in the incomplete disparity map.we demonstrate very good results on significantly incomplete disparity data computed by a conventional correlation-based stereo algorithm on real wide-baseline stereo pair acquired by an immersive videoconferencing system.
neural network based modeling and color rendering for mixed reality. this paper describes a new approach to color image rendering for mixed reality applications. the approach has two steps. the first uses neural network based photometric stereo to obtain both a 3d shape model and color reflectance factors simultaneously. the second uses neural network based image rendering to generate realistic virtual images for arbitrary viewpoint and direction of light source. the proposed approach achieves high quality 3d modeling of real objects and subsequent virtual image rendering based on empirical measurements obtained in a simple experimental environment. the approach is empirical using only a standard digital camera and light sources. assumptions about surface reflectance are reasonably generic. experiments using real data are demonstrated.
a hybrid classifier for precise and robust eye detection. eye location is an important visual cue for face image processing such as alignment before face recognition, gaze tracking, expression analysis, etc. in this paper a novel eye detection algorithm is presented, which integrates the characteristics of single eye and eye-pair images to develop a hybrid classifier under the learning paradigm. the low dimensional features representing eye patterns yield by subspace projection are selected via a filter and a wrapper method for a simplified maximum likelihood and a svm classifier respectively. eye candidates determined by a cascade of the two classifiers are further verified with eye-pair template matching scores to reject false detections. the performance of this eye detector is assessed on several publicly available face databases and the experimental results demonstrate its robustness to the variations in head pose, facial expressions, partial occlusions and lighting conditions.
a novel vision based finger-writing character recognition system. a new vision based finger writing character recognition system (fwcrs) is proposed in this paper. the fwcrs allows people to write characters virtually just using his finger-tip (we call this "fingerwriting"). the trajectories of the finger-tip are tracked and reconstructed as a kind of inkless character pattern and finally recognized by a classifier. in this paper, a simple but effective background model is built for the fwcrs to segment human finger from cluttered background. a robust fingertip detection algorithm based on feature matching is presented. the fingerwriting character is finally recognized by a dtw classifier. experiments show that the fwcrs can recognize finger-writing uppercase & lowercase english characters with the accuracy of 95.6%, 98.5% respectively.
scanner artifact removal in simultaneous eeg-fmri for epileptic seizure prediction. simultaneous recording of electroencephalographic (eeg) and functional magnetic resonance imaging (fmri) has been a new modality in brain imaging very recently. blood oxygen level-dependent (bold) in fmri provides sufficient information about the hemodynamics of the brain during changes in the brain metabolism such as in the event of seizure. however, the major drawback of these joint recordings is the destructive effect of the fmri scanner artifact. without removal of such artifact the eeg signals cannot be processed. in this paper, an effective method for removal of the scanner artifact has been established by applying blind source extraction (bse) algorithm followed by the averaging-and-subtraction method. the results have shown that the scanner artifacts have been effectively mitigated.
parallel tracking of all soccer players by integrating detected positions in multiple view images. soccer, one of the popular sports around the world, is often broadcasted on tv, and various researches have done on soccer scene images such as strategy analysis, scene recovery, automatic indexing of soccer scenes, and automatic intelligent sports casting. as robust player tracking is fundamental to those researches, there is a demand for an automatic player tracking system using soccer imaging data. in this paper, we propose a method of tracking soccer players using multiple views. tracking is done by integrating the tracking data from all cameras, using the geometrical relationship between cameras called homography. integrating information from all cameras enables stable tracking on the scene, where the tracking by a single camera often fails in the case of occlusion.
learning in hidden annotation-based image retrieval. learning in an image retrieval scheme that uses hidden annotations is investigated. compared with low level visual features that are straightforward functions of the raw pixel values, hidden annotations are higher level hidden semantic attributes. in the proposed scheme, a small set of images is manually labeled with several hidden annotations. for each annotation, a support vector machine (svm) classifier is trained using the images labeled with it as positive examples and others as negative examples. based on the trained svms, the annotations are propagated to the unlabeled images in the database. to perform relevance feedback in the annotation space, a probabilistic re-weighting algorithm is proposed. experimental results on a general-purpose database of 10,000 images demonstrate the potential of hidden annotation-based image retrieval and the superiority of the proposed relevance feedback algorithm over two existing algorithms.
development of a guide dog system for the blind people with character recognition ability. this paper introduces a guide dog system with character recognition ability. the main purpose of this system is to assist blind people. a guide dog helps a visually impaired person to act corresponding to the surrounding environment. however, it cannot do complex tasks such as reading words. we constructed a system that can read characters to support them. usually, character recognition systems segment character from the general background by using some information. this time, our system focuses exclusively on reading a room number. therefore, we used a method of character searching by template matching.
a novel approach for lexical noise analysis and measurement in intelligent information retrieval. latent semantic indexing (lsi) is a technique used in information retrieval (ir) as an alternative to traditional keyword matching search techniques. lsi is a preferred technique as it can cope with problems and inaccuracies that arise due to synonymy and polysemy. in this paper a new philosophy for lsi analysis and evaluation is presented based on the use of image processing tools. the term document matrix (tdm) generated in the lsi process can now be visualized and treated as an image. once in this form, techniques from image processing can be applied. the new approach has been validated and evaluated using different key performance metrics used in image processing and ir.
relationship between identification metrics: expected confusion and area under a roc curve. the mathematical relationship between the expected-confusion metric and the area under a receiver operating characteristic (roc) curve is derived. given a limited database of subjects and an identification technique that generates a feature vector per subject, expected confusion is used to predict how well the feature vector will filter identity in a larger population. related is the area under a roc curve that can be used to determine the probability ofcorrectly discriminating between subjects given the feature vector. these two measures have different connotations, but we show mathematically and verify experimentally that a simple transformation can be applied to the expected confusion to find the probability of incorrectly discriminating between subjects, which is the complement of the area under a roc curve. furthermore, we show that as a function of the number of subjects, this transformed expected-confusion measure converges more quickly than direct calculation of the area under a roc curve.
an event-based execution model for efficient image processing on workstation clusters and the grid. the event model of the functional language cml (concurrent meta language) is used to capture concurrency, which normally remains unexploited within conventional parallel geometric harnesses running on (virtual) arrays of processors. this complexity is hidden from the application programmer, who merely supplies conventional geometric sequential code which is automatically executed in parallel. an example of a low-level image filtering operation is used, to show how execution efficiency can be maintained in spite of the communication delays and indeterminacies encountered in real networks.
informational classifier fusion. classifier combination has proven itself a powerful tool for achieving high recognition rates with otherwise moderately discriminating classifiers. while progress has been made during the last decade in terms of generating powerful classifier ensembles, the actual combination process is not understood yet. in this paper, i present an information-theoretical solution to classifier combination that integrates the information conveyed by each classifier. my proposed method transforms the likelihood values of a classifier in such a way that they equal the information conveyed, without affecting its individual performance. this implicitly postulates that the elementary sum-rule performs at least as good as any other, more complex combination scheme. i evaluated my method by combining on-line and off-line japanese character recognizers, computing a considerable improvement of more than 4.5% compared to the best single recognition rate.
correspondence-free associative learning. we study the problem of learning a non-parametric mapping between two continuous spaces without having access to input-output pairs for training, but rather to groups of input-output pairs, where the correspondence structure within each group is unknown and where outliers may be present. this problem is solved by transforming each space using the channel representation, and finding a linear mapping on the transformed domain. the asymptotical behavior of the method for a large number of training samples is found to be very related to the case of known correspondences. the results are evaluated on simulated data.
dense stereo matching using kernel maximum likelihood estimation. there has been much interest, recently, in the use of bayesian formulations for solving image correspondence problems. for the two-view stereo matching problem, typical bayesian formulations model the disparity prior as a pairwise markov random field (mrf). approximate inference algorithms for mrfs, such as graph cuts or belief propagation, treat the stereo matching problem as a labelling problem yielding discrete valued disparity estimates. in this paper, we propose a novel robust bayesian formulation based on the recently proposed kernel maximum likelihood (kml) estimation framework. the proposed formulation uses probability density kernels to infer the posterior probability distribution of the disparity values. we present an efficient iterative algorithm, which uses a variational approach to form a kml estimate from the inferred distribution. the proposed algorithm yields continuous-valued disparity estimates, and is provably convergent. the proposed approach is validated on standard stereo pairs, with known sub-pixel disparity ground-truth data.
fpga based real-time visual servoing. real-time image processing tasks not only require high computing power but also high data bandwidth. though current processors excel in computing power, memory throughput is still the bottleneck for stream-oriented applications such as low-level image processing tasks. the alternative of special-purpose systems lacks flexibility at a high design effort and long development time. this effort often becomes void by the rapid advance of mainstream computing technology. fpga technology promises flexibility and the necessary computing performance at affordable design costs. in this paper we describe our approach for a prototype image processing system for robot vision applications, based on fpga technology. we use a commercially available pci-board to implement a typical application based on the experimental servicing satellite (ess) scenario.
estimation of the bayesian network architecture for object tracking in video sequences. it was recently proposed the use of bayesian networks for object tracking. bayesian networks allow to model the interaction among detected trajectories, in order to obtain a reliable object identification in the presence of occlusions. however, the architecture of the bayesian network has been defined using simple heuristic rules which fail in many cases. this paper addresses the above problem and presents a new method to estimate the network architecture from the video sequences using supervised learning techniques. experimental results are presented showing that significant performance gains (increase of accuracy and decrease of complexity) are achieved by the proposed methods.
pores and ridges: fingerprint matching using level 3 features. fingerprint friction ridge details are generally described in a hierarchical order at three levels, namely, level 1 (pattern), level 2 (minutiae points) and level 3 (pores and ridge shape). although high resolution sensors (¡«1000dpi) have become commercially available and have made it possible to reliably extract level 3 features, most automated fingerprint identification systems (afis) employ only level 1 and level 2 features. as a result, increasing the scan resolution does not provide any matching performance improvement [1]. we develop a matcher that utilizes level 3 features, including pores and ridge contours, for 1000dpi fingerprint matching. level 3 features are automatically extracted using wavelet transform and gabor filters and are locally matched using the icp algorithm. our experiments on a median-sized database show that level 3 features carry significant discriminatory information. eer values are reduced (relatively ¡«20%) when level 3 features are employed in combination with level 1 and 2 features.
fundamental frequency gabor filters for object recognition. gabor filters are a widely used feature extraction method in image analysis. in this study, a new method is presented that utilises gabor filters for extracting fundamental frequencies of objects. the fundamental frequencies represent the shape of an object and can be used to classify objects with dissimilar spatial dimensions. theoretical results are verified by experiments with real images of electronic components. experiments indicate that the fundamental frequency gabor filters are a robust tool for rotation and translation invariant object recognition.
a hybrid license plate extraction method for complex scenes. this paper presents a hybrid method for extracting license plates from cluttered images. the proposed algorithm consists of three major components. first, a line detection method is proposed to detect straight lines in the edge map. second, a weight assignment scheme is applied to obtain a weight based edge density map. regions with the densest edges are selected as candidates. third, all candidate plates will pass to a refining selection procedure. one candidate that best satisfy the color constraints becomes the output.
photometric stereo under blurred observations. in this paper we address the problem of simultaneous estimation of structure and restoration of images from blurred photometric measurements. given the blurred observations of a static scene captured with a stationary camera, under different illuminant directions, we obtain the structure represented by the surface gradients and the albedo and also perform blind image restoration. the surface gradients and the albedo are modeled as separate markov random fields (mrf) and a suitable regularization scheme is used to estimate the different fields as well as the blur parameter.
a maximum-likelihood approach to symbolic indirect correlation. symbolic indirect correlation (sic) is a nonparametric method that offers significant advantages for recognition of ordered unsegmented signals. a previously introduced formulation of sic based on subgraph-isomorphism requires very large reference sets in the presence of noise. in this paper, we seek to address this issue by formulating sic classification as a maximum likelihood problem. we present experimental evidence that demonstrates that this new approach is more robust for the problem of online handwriting recognition using noisy input.
integration of range images in a multi-view stereo system. a novel method for integrating multiple range images in a multi-view stereo imaging system is presented here. due to self-occlusion an individual range image provides only a partial model of an object surface. therefore multiple range images from differing viewpoints must be captured and merged to extend the surface area that can be captured. in our approach range images are decomposed into subset patches and then evaluated in a "confidence competition". redundant patches are removed whilst winning patches are merged to complete a single plausible mesh that represents the acquired object surface.
bernoulli mixture models for binary images. mixture modelling is a hot area in pattern recognition. although most research in this area has focused on mixtures for continuous data, there are many pattern recognition tasks for which binary or discrete mixtures are better suited. this paper focuses on the use of bernoulli mixtures for binary data and, in particular, for binary images. results are reported on a task of handwritten indian digits.
calibrating freely moving cameras. we present a novel practical method for self-calibrating a camera which may move freely in space while changing it internal parameters by zooming. we show that point correspondences between a pair of images, and the fundamental matrix computed from these point correspondences, are sufficient to recover the internal parameters of a camera. unlike other methods, no calibration object with known 3-d shape is required and no limitation are put on the unknown motion, as long as the camera is projective. the main contribution of this paper is development of a global linear solution which is based on the well-known kruppa equations. we introduce a formulation different from the huang and faugeras constraints. the method has been extensively tested on synthetic and real data and promising results are reported.
configuring mixed reality environment. we present a practical framework for registering a mixed reality(mr) environment of an arbitrary number of agents. each agent consist of a head mounted display (hmd), which consists of a pair of stereo cameras. each agent is assumed to be moving freely in 3d space and multiple hmds need not have a common field of view (fov). we show that the plane at infinity and a common vertical vanishing point can be use to determine the exact orientation of all hmds with respect to each other, and establish a common reference frame. our method generalizes previous work which considers restricted camera motions. using minimal assumptions, we are able to successfully demonstrate promising results on real data.
multi feature path modeling for video surveillance. this paper proposes a novel method for detecting nonconforming trajectories of objects as they pass through a scene. existing methods mostly use spatial features to solve this problem. using only spatial information is not adequate; we need to take into consideration velocity and curvature information of a trajectory along with the spatial information for an elegant solution. our method has the ability to distinguish between objects traversing spatially dissimilar paths, or objects traversing spatially proximal paths but having different spatio-temporal characteristics. the method consists of a path building training phase and a testing phase. during the training phase, we use graph-cuts for clustering the trajectories, where the hausdorff distance metric is used to calculate the edge weights. each cluster represents a path. an envelope boundary and an average trajectory are computed for each path. during the testing phase we use three features for trajectory matching in a hierarchical fashion. the first feature measures the spatial similarity while the second feature compares the velocity characteristics of trajectories. finally, the curvature features capture discontinuities in velocity, acceleration, and position of the trajectory. we use real-world pedestrian sequences to demonstrate the practicality of our method.
frame grouping measure for factorization-based projective reconstruction. the factorization-based method generally suffers less from drift and error accumulation than the merging. however, the factorization method assumes that all correspondences must remain in all frames. in order to overcome the limitation, we present a new factorization-based projective reconstruction from un-calibrated image sequences. the proposed method breaks the full sequence into sub-sequences based on a quantitative measure considering the number of matching points between frames, the homography error, and the distribution of matching points in the image. all of projective reconstructions in sub-sequences are registered into the same coordinate frame for a complete description of the scene. experimental results showed our algorithm can recover more precise 3d structure than the merging method.
radial distortion refinement by inverse mapping-based extrapolation. "caltech calibration toolbox" by jean-yves bouguet is one of the most famous open-source calibration tools [1]. although it works well for general camera lenses, it reveals problems in case of wide-angle lens. this paper analyzes the problem and shows that the insufficient calibration of radial distortion is caused by lease-square based polynomial fitting. to overcome the problem, this paper proposes novel refinement method using inverse mapping-based extrapolation. the proposed method is expected to be an efficient supplement and is opened to the public in the appendix as a short matlab script.
selective sampling based on the variation in label assignments. in this paper, a new selective sampling method for the active learning framework is presented.initially, a small training set t and a large unlabeled set ¿ are given.the goal is to select, one by one, the most informative objects from ¿ such that, after labeling by an expert, they will guarantee the best improvement in the classifier performance. our sampling strategy relies on measuring the variation in label assignments (of the unlabeled set) between the classifier trained on t and the classifiers trained on t with a single unlabeled object added with all possible labels. we compare the performance of our algorithm with two traditional procedures random sampling and uncertainty sampling. we show empirically across a range of datasets that the proposed selective sampling method decreases the number of labeled instances needed to achieve the desired error for the fixed size of t.experimental results on toy problems and the uci datasets are presented.
domain based lda and qda. we propose an alternative to probability density classifiers based on normal distributions lda and qda. instead of estimating covariance matrices using the standard maximum likelihood estimator we estimate class domains by the minimum volume enclosing ellipsoid (í-mvee). the í-mvee is a robust statistic rejecting a specified fraction í of the data. the performance of the domain and density approaches are compared in small sample size problems and in situations where sampling of a training and test sets is not i.i.d..
affine parameter estimation from the trace transform. in this paper, we assume that we are given the images of two segmented objects, one of which may be an affinely distorted version of the other, and wish to recover the values of the parameters of the affine transformation between the two images. the images may also differ by the overall level of illumination. the multiplicative constant of such difference may also be recovered. we present a generic theoretical framework to solve this problem. in terms of this framework, other proposed methods may be interpreted. we show how, in this framework, one can recover the affine parameters in a way that is robust to various effects, such as occlusion and illumination variation. the proposed method is generic enough to be applicable also to matching two images that do not depict the same scene or object.
reverse engineering the human vision system: a possible explanation for the role of microsaccades. we present a method of image reconstruction which is invariant to the chosen group of transformations of the spline grid used to reconstruct the image. integration over a group of transformations may be what the human eye does during microsaccades which may be an explanation of why the images we see are not aliased although the sensors with which we record them are irregularly placed in the retina.
address-block extraction by bayesian rule. a method for extracting a recipient address-block from a mail image has been developed. the method is composed of two steps: nomination of address-block candidates and evaluation of these candidates by using the bayesian rule according to each of address-block type. accordingly, the proposed method can cope with various types of address-blocks. the effectiveness of the method was confirmed in several address extraction experiments. these experiments show that the top-five extraction results include one correct address -block in 94% of total number of printed-mail cases and 89% in of handwritten- mail cases.
spectral image distortion map. in this paper a novel technique of spectral image quality evaluation using spectral image distortion map (sidm) is proposed. the method is based on a recent approach to evaluation of color differences in a spectral space. what is calculated here, in fact, is a pixelwise spectral distortion. as the measure of the dissimilarity a novel kernel based similarity measure is used. the metric produces comparable values of differences for perceptually equally disparate colors. as a result a gray-scale spectral distortion image is obtained, where the intensity of each of the pixels is a difference between the original image and the distorted one. a perceptual image distortion map (pidm) has also been constructed to show the accuracy of sidm. a comparison of pidm and sidm shows that the latter provides an excellent fit to the response of the human visual system.
3d acquisition system using uncalibrated line-laser projec. in this paper, we propose a new 3d scanner, which is easy to operate. till date several 3d scanners, including commercial products, are available; however, most of these are usually large, heavy, and expensive. although inexpensive 3d scanners manufactured using vision-based techniques, such as stereo vision, are available, they cannot be used in actual measurements because the techniques are still being researched. our proposed scanner consists of only a laser projector and a single camera and is based on the self-calibarating technique; thus it does not require both precalibration and expensive mechanical devices. this implies that the system to be low-cost and the occlusions can be effectively reduced by moving the projector while scanning. experiments of our method were performed using both synthesized and real data and the 3d information of the scene was successfully reconstructed.
conformal method for quantitative shape extraction: performance evaluation. we evaluate our recently developed conformal method for quantitative shape extraction from unorganized 3d oriented point clouds. the conformal method has been tested previously on real, noisy, 3d data. here we focus on the empirical evaluation of its performance on synthetic, ground truth data, and comparisons with other methods for quantitative extraction of mean and gauss curvatures presented in the literature.
automated segmentation of archaeological profiles or classification. classification and reconstruction of archaeological fragments is based on the profile, which is the cross-section of the fragment in the direction of the rotational axis of symmetry. in order to segment the profile into primitives like rim, wall, and base, rules based on expert knowledge are created. the input data for the estimation of the profile is a set of points produced by the acquisition system. a function fitting this set is constructed and later on processed to find the characteristic points necessary to classify the original fragment. the one we propose is based on b-splines or bell-shaped splines.
a new color image segmentation algorithm based on watershed transformation. a new color segmentation method is presented in this paper. the method is specified for color images that have both large and small objects, and objects with both step and ramp edges. scanned pages of color magazines and newspapers are the examples of this kind of images. watershed transformation algorithm is the basis of the proposed method. our method incorporates the original multi-scale analysis that allows to segment edges of different slope. this analysis uses fine-to-coarse strategy and prevents the already detected sharp edges from smoothing while moving to coarser scales. in the same time the introduced algorithm allows to detect ramp edges successfully at coarse scales. for fine scales we propose a special gradient operator and a modification of watershed transformation for small objects segmentation.
on 3d mosaicing of rotationally symmetric ceramic fragments. a major obstacle to the wider use of 3d object reconstruction and modeling is the extent of manual intervention needed. such interventions are currently massive and exist throughout every phase of a 3d reconstruction project: collection of images, image management, establishment of sensor position and image orientation, extracting the geometric detail describing an object, merging geometric, texture and semantic data. this work aims to develop a solution for automated documentation of archaeological pottery, which also leads to a more complete 3d model out of multiple fragments. generally the 3d reconstruction of arbitrary objects from their fragments can be regarded as a 3d puzzle. in order to solve it we identified the following main tasks: 3d data acquisition, orientation of the object, classification of the object and reconstruction.we demonstrate the method and give results on synthetic and real data.
modification of watershed transformation for images, containing small objects. we present a new method, which allows successful application of watershed transformation for images containing small objects. the method can be divided into two stages. during the first stage of segmentation a special gradient operator is applied to get the gradient of the image. it gives us a possibility to increase the resolution of the gradient doubly in comparison with the resolution of the original image. we can achieve this by approximation of the first-order derivative not only in image pixels, but also between pixels. during the second stage the author's modification of watershed transformation is applied. this modification enables us make optimal use of the image gradient obtained at the first stage. the method to be introduced was probed on a large amount of images with small details, and showed better results than the traditional watershed algorithm.
piecewise linear skeletonization using principal curves. we propose an algorithm to find piecewise linear skeletons of handwritten characters by using principal curves. the development of the method was inspired by the apparent similarity between the definition of principal curves (smooth curves which pass through the "middle" of a cloud of points) and the medial axis (smooth curves that go equidistantly from the contours of a character image). the central fitting-and-smoothing step of the algorithm is an extension of the polygonal line algorithm which approximates principal curves of data sets by piecewise linear curves. the polygonal line algorithm is extended to find principal graphs and complemented with two steps specific to the task of skeletonization: an initialization method to capture the approximate topology of the character, and a collection of restructuring operations to improve the structural quality of the skeleton produced by the initialization method. an advantage of our approach over existing methods is that we optimize the skeleton graph by minimizing an intuitive and explicit objective function that captures the two competing criteria of smoothing the skeleton and fitting it closely to the pixels of the character image. we tested the algorithm on isolated handwritten digits and images of continuous handwriting. the results indicate that the proposed algorithm finds a smooth medial axis of the great majority of a wide variety of character templates and substantially improves the pixelwise skeleton obtained by traditional thinning methods.
an efficient face recognition system using a new optimized localization method. in this paper a system is developed for face recognition processes. preprocessing and face localization is necessary to obtain a high classification rate in face recognition tasks. in this study after preprocessing of face images, for omitting the redundant information such as background and hair, the oval shape of face is approximated by an ellipse using shape information. then the parameters (orientation and center coordinates) of this ellipse are optimized using genetic algorithm (ga). high order pseudo zernike moment invariant (pzmi) which has useful properties is utilized to produce feature vectors. also radial basis function neural network (rbfnn) with hla learning rule has been used as a classifier. simulation results on orl database indicate that the error rate of proposed system which uses genetic algorithm for optimizing the face localization step is lower than an older system which described in [2].
robust phase correlation. phase-correlation (pc) is a computationally efficient method for two and three dimensional translation estimation. we presents a projection operator which significantly improves the accuracy and robustness of the pc scheme. the operator projects the estimated correlation function into the space of correlation functions resulting from a certain range of translations, while rejecting components which are unrelated to the estimated motion.thus, the registration accuracy is improved by an order of magnitude, especially in the registration of noisy images and volumes. in addition, this approach is shown to be complementary with other subpixel phase correlation based techniques.
recognizing facial expressions by tracking feature shapes. reliable facial expression recognition by machine is still a challenging task. we propose a framework to recognise various expressions by tracking facial features. our method uses localized active shape models to track feature points in the subspace obtained from localized non-negative matrix factorization. the tracked feature points are used to train conditional model for recognising prototypic expressions like anger, disgust, fear, joy, surprise and sadness. we formulate the task as a sequence labelling problem and use conditional random fields(crf) to probabilistically predict expressions. in crf, the distribution is conditioned on the entire sequence rather than a single observation. for the joint probability defined for the entire sequence, crf does global normalization of the exponential model, as opposed to memm, for which the per state exponential distribution is locally normalized. unlike generative models(hmm), no prior dependencies between the features are assumed. we adopt a simplistic approach to classify expressions without explicitly monitoring the change in shapes of the individual facial features. instead, we allow crf to learn the complex dependencies between the features and recognize the expressions directly. experimental results demonstrate that accurately tracked feature shapes provide reliable discriminative cues to robustly recognize facial expressions for an image sequence.
an algebraic approach to symmetry detection. we present an algorithm for detecting cyclic and diherdral symmetries of an object.both symmetry types can be detected by the special patterns they generate in the object's fourier transform.these patterns are effectively detected and analyzed using the "angular difference function" (adf), which measures the difference in the angular content of images.the adf is accurately computed by using the pseudo-polar fourier transform, which rapidly computes the fourier transform of an object on a near-polar grid.the algorithm detects all the axes of centered and non-centered symmetries.the proposed algorithm is algebraically accurate and uses no interpolations.
combining generative and discriminative methods for pixel classification with multi-conditional learning. it is possible to broadly characterize two approaches to probabilistic modeling in terms of generative and discriminative methods. provided with sufficient training data the discriminative approach is expected to yield superior accuracy as compared to the analogous generative model since no modeling power is expended on the marginal distribution of the features. conversely, if the model is accurate the generative approach can perform better with less data. in general it is less vulnerable to overfitting and allows one to more easily specify meaningful priors on the model parameters. we investigate multi-conditional learning a method combining the merits of both approaches. through specifying a joint distribution over classes and features we derive a family of models with analogous parameters. parameter estimates are found by optimizing an objective function consisting of a weighted combination of conditional loglikelihoods. systematic experiments in the context of foreground/ background pixel classification with the microsoft- berkeley segmentation database using mixtures of factor analyzers illustrate tradeoffs between classifier complexity, the amount of training data and generalization accuracy. we show experimentally that this approach can lead to models with better generalization performance than purely generative or discriminative approaches.
3d scene reconstruction from reflection images in a spherical mirror. this paper proposes a method for reconstructing a 3d scene structure by using the images reflected in a spherical mirror. in our method, the mirror is moved freely within the field of view of a camera in order to observe a surrounding scene virtually from multiple viewpoints. the observation scheme, therefore, allows us to obtain the wide-angle multiviewpoint images of a wide area. in addition, the following characteristics of this observation enable multi-view stereo with simple calibration of the geometric configuration between the mirror and the camera; (1) the distance and direction from the camera to the mirror can be estimated directly from the position and size of the mirror in the captured image and (2) the directions of detected points from each position of the moving mirror can be also estimated based on reflection on a spherical surface. some experimental results show the effectiveness of our 3d reconstruction method.
an lvq-based automotive occupant classification system. this paper presents a description of a system designed to classify a passenger in an automobile into one of three classes: a) adult, b) children (6 years and younger) and infants in child seats and c) empty seat. the authors examine the application of neural networks (bp, lvq etc.) for this occupant classification system (ocs).
real-time estimation of light source environment for photorealistic augmented reality. this paper proposes a vision-based augmented reality system with correct representation of attached and cast shadows.to realize a seamless augmented reality system, we need to resolve a number of problems.especially, the geometric and photometric registration problems are important. these problems require to estimate the positions of light sources and user's viewpoint.the proposed system resolves the problems using a 3d marker which combines a 2d square marker and a mirror ball.the 2d marker and the mirror ball are used to estimate the relationship between the real and virtual worlds and the positions of light sources in the real world, respectively.
a fast template matching algorithm with adaptive skipping using inner-subtemplates' distances. this paper proposes a new fast template matching algorithm that skips comparison between a template and search windows neighboring an already compared dissimilar sub-window. comparison skipping is executed when a lower bound of distance between the template and a window exceeds a threshold. the lower bound of distance between the template and the window is determined by the triangular inequality in distances: the distance between a subtemplate and a subwindow and that between inter-subtemplates. experimental results demonstrate that the proposed method is up to five times faster than the conventional fast exhaustive search method (sequential similarity detection algorithm), strictly guaranteeing the same accuracy.
snake-based technique for plasmapause tracking. a new approach to tracking the boundary of the plasma-sphere (i.e., the plasmapause) in a time-series of satellite images of the earth is described. the approach is based on the active contour models (snakes) and exploits prior knowledge of the plasmasphere to automatically initialize and refine the snake's position in each image. it then uses a greedy minimization scheme to drive the snake toward the plasmapause in each image. a voronoi diagram is used to restrict the snake evolution to ensure that the snake does not loop over itself. correspondences between successive images are established using a radial alignment process. the approach aids in quantifying plasmasphere changes, which are key indicators of the impact of solar events on the earth's magnetosphere.
bayesian network structure learning and inference in indoor vs. outdoor image classification. bayesian network model selection techniques may be used to learn and elucidate conditional relationships between features in pattern recognition tasks. the learned bayesian network may then be used to infer unknown node-states, which may correspond to semantic tasks. one such application of this framework is scene categorization. in this paper, we employ low-level classification based on color and texture, semantic features, such as sky and grass detection, along with indoor vs. outdoor ground truth information, to create a feature set for bayesian network structure learning. indoor vs. outdoor inference may then be performed on a set of features derived from a testing set where node states are unknown. experimental results show that this technique provides classification rates of 97% correct, which is a significant improvement over previous work, where a bayesian network was constructed based on expert opinion.
local context in non-linear deformation models for handwritten character recognition. we evaluate different two-dimensional non-linear deformation models for handwritten character recognition. starting from a true two-dimensional model, we derive pseudo-two-dimensional and zero-order deformation models. experiments show that it is most important to include suitable representations of the local image context of each pixel to increase performance. with these methods, we achieve very competitive results across five different tasks, in particular 0.5% error rate on the mnist task.
linear discriminant analysis and discriminative log-linear modeling. we discuss the relationship between the discriminative training of gaussian models and the maximum entropy framework for log-linear models. observing that linear transforms leave the distributions resulting from the log-linear model unchanged, we derive a discriminative linear feature reduction technique from the maximum entropy approach and compare it to the well-known linear discriminant analysis. from experiments on different corpora we observe that the new technique performs better than linear discriminant analysis if the dimensionality of the feature space is large with respect to the number of classes.
on-line signature verification by exploiting inter-feature dependencies. the traditional on-line signature verification process involves use of various dynamic features such as velocity, pressure, acceleration, angles, etc. the idea is to device a composite vector structure combining more than one feature where each feature is treated independently. our proposed research work is an attempt to exploit the interfeature dependencies by employing a higher dimensional vector approach. the strategy adopted here is to obtain pressure strokes with respect to various velocity bands. the strokes thus obtained are found to portray a reasonably accurate basis for discriminating genuine vs forgery class. the simulation results validate our assumptions and show improvements in the discriminating index.
using constraint inequality on estimated correlation for rapid image search. a rapid algorithm of searching for similar images to an object image in a set of registered images is proposed. provided that correlations of all the pairs of registered images in advance, we can derive a constraint inequality for similarity of the object. by use of the upper bounds defined by the inequality, three conditions of neglect can be derived, which enable to quicken computation of searching. efficiency rate of eight times in average could be obtained for searching 204 images in the set of 1,200 registered images.
parallel pattern recognition computations within a wireless sensor network. the computational properties of a wireless sensor network (wsn) have been investigated by implementing a fully distributed pattern recognition algorithm within the network. it is shown that the set up allows a physical object to develop a capability, which to some extent may be considered similar to our sense of touch, with the wsn acting as an artificial nervous system in this regard. the effectiveness of the algorithm is inspected by comparing the outputs from the sensors with the stress patterns generated through a simple finite element model and then stored within the network. it is shown that the test object could successfully differentiate between its internal stress states resulting from the changes to its external loading conditions. suitability of the algorithm is discussed with respect to the data storage requirement per node of the wsn.
combining visual features with semantics for a more effective image retrieval. we present a new framework which tries to improve the effectiveness of cbir by integrating semantic concepts extracted from text. our model is inspired from the vsm model developed in information retrieval. we represent each image in our collection with a vector of probabilities linking it to the different keywords. in addition to the semantic content of images, these probabilities capture the user's preference in each step of relevance feedback. the obtained features are then combined with visual ones in retrieval phase. evaluation carried out on more than 10,000 images shows that this considerably improves retrieval effectiveness.
object reacquisition using invariant appearance model. we present an approach for reacquisition of detected moving objects. we address the tracking problem by modeling the appearance of the moving region using stochastic models. the appearance of the object is described by multiple models representing spatial distributions of objects' colors and edges. this representation is invariant to 2d rigid and scale transformation. it provides a good description of the object being tracked, and produces an efficient blob similarity measure for tracking. three different similarity measures are proposed, and compared to show the performance of each model. the proposed appearance model allows to track a large number of moving people with partial and total occlusions and permits to reacquire objects that have been previously tracked. we demonstrate the performance of the system on several real video surveillance sequences.
non-iterative approach to multiple 2d motion estimation. we present an innovative method estimating multiple 2d motions from uncalibrated images. our approach robustly and non-iteratively estimates multiple 2d parametric motions, affine or homography, from noisy initial matches without pre-specifying the number of motions this approach is based on: (1) a parametric motion model to detect and extract 2d affine or homography motions; (2) the representation of matching points in decoupled joint image spaces; (3) the characterization of the property associated with affine transformation in the defined spaces; (4) a non-iterative process to extract multiple 2d motions simultaneously based on tensor-voting; (5) local affine to global homography estimation. the major contribution of our work is the extension to our existing affine motion estimation method for homography estimation. the robustness of the approach is demonstrated with several results.
product approximation by minimizing the upper bound of bayes error rate for bayesian combination of classifiers. in combining multiple classifiers using a bayesian formalism, a high dimensional probability distribution is composed of a class and decisions of classifiers. in order to do product approximation of the probability distribution, the upper bound of bayes error rate, bounded by the conditional entropy of a class and decisions, should be minimized. a second-order dependency-based product approximation is proposed in this paper by considering the second-order dependency between the class and decisions. the proposed method is evaluated by combining the classifiers recognizing unconstrained handwritten numerals.
predicting the benefit of sample size extension in multiclass k-nn classification. in industrial quality inspection obtaining the training data needed for classification problems is still a very costly task. nevertheless, the classifier quality is crucial for economic success. thus, the question whether the influence of the training data on the classification error has been fully exploited and enough data has been obtained is very important. this paper introduces a method to answer this question for a specific problem. to be able to make a concrete statement and not only general recommendations, we focus on the k-nn classifier, since it is widely used in industrial implementations. the method is tested on four different multiclass problems: original data from an optical media inspection problem, the mnist database, and two artificial problems with known probability densities.
real-time multiple people tracking using competitive condensation. the condensation algorithm has attracted as it has robust tracking performance and potential of real-time implementation. however the condensation tracker has difficulty with real-time implementation for multiple people tracking since it requires complicated shape model and large number of samples for precise tracking performance. this paper presents two improvements for real-time multiple object tracking: the discrete shape model with a small search space and the competition rule which requires a small number of samples to track multiple people. we show that they achieve robust and real-time tracking for image sequences of a crowd of people.
hough transform in log-polar image including foveal and peripheral information. line equation in cartesian space can be mapped conformally to log-polar. but many the applications of log-polar mapping are using only the peripheral region. this paper presents a method of a hough transform for a log-polar mapped edge image that includes both foveal and peripheral visual information. it is shown that this method achieves a good performance for line detection on the log-polar space.
scene text extraction in natural scene images using hierarchical feature combining and verification. we propose a method that extracts text regions in natural scene images using low-level image features and that verifies the extracted regions through a high-level text stroke feature. then the two level features are combined hierarchically. the low-level features are color continuity, gray-level variation and color variance. the color continuity is used since most of the characters in a text region have the same color, and the gray-level variation is used since the text strokes are distinctive to the background in their gray-level values. also, the color variance is used since the text strokes are distinctive in their colors to the background, and this value is more sensitive than the gray-level variations. as a high level feature, text stroke is examined using multi-resolution wavelet transforms on local image areas and the feature vector is input to a svm(support vector machine) for verification. we tested the proposed method with various kinds of the natural scene images and confirmed that extraction rates are high even in complex images.
evaluation on selection criteria of multiple numeral recognizers with the fixed number of recognizers. the combination of multiple recognizers shows various performances according to the selection of recognizers and the combination method of them. the selection of recognizers on how to select them or how many to select them still remains one of important research issues. in this paper, information-theoretic criteria for selecting the multiple numeral recognizers are evaluated together with the simple selection criteria in terms of recognition rates by the handwritten numerals from concordia university and uci, on the supposition that the number of selected recognizers is fixed in advance. the selection criteria are applied to the pool of numeral recognizers and examine the possible recognizer sets from the pool, and then select one of the recognizer sets as a multiple recognizer system candidate.
visual keywords labeling in soccer video. in this paper, we propose a framework to label soccer video shots with pre-defined visual keywords to bridge the semantic gap between low-level features and semantic understanding. based on these visual keywords, further structure analysis and event detection will be facilitated. in our system, a mpeg-1 soccer video stream is partitioned into shots, from which each p-frame is converted into color-based and edge-based binary maps. then, we detect the playing field and segment the regions of interest (rois) inside the playing field. finally two support vector machine classifiers and some decision rules are applied to the properties of the rois such as size, position, texture ratio, etc and the position of the playing field to label the video shot with visual keyword. we have applied the proposed method to 3495 soccer video shots and achieved 94.3% and 97.2% average precision and recall respectively.
ica-based clustering for resolving permutation ambiguity in frequency-domain convolutive source separation. permutation ambiguity is an inherent limitation in independent component analysis, which is a bottleneck in frequency-domain methods of convolutive source separation. in this paper we present a method for resolving this permutation ambiguity, where we group vectors of estimated frequency responses into clusters in such a way that each cluster contains frequency responses associated with the same source. the clustering is carried out, applying independent component analysis to estimated frequency responses. in contrast to existing methods, the proposed method does not require any prior information such as the geometric configuration of microphone arrays or distances between sources and microphones. experimental results confirm the validity of our method.
automatic text location using cluster-based template matching. this paper proposes a method for automatic text location in images including multi-segment characters. accordingly, we use shape information in addition to size and location information.this shape information is represented by cluster-based templates obtained from target characters using k -means clustering algorithm. experimental results show the effectiveness of the proposed method.
a generic camera calibration method for fish-eye lenses. fish-eye lenses are convenient in such computer vision applications where a very wide angle of view is needed. however, their use for measurement purposes is limited by the lack of an accurate, generic, and easy-to-use calibration procedure. we hence propose a generic camera model for cameras equipped with fish-eye lenses and a method for calibration of such cameras. the calibration is possible by using only one view of a planar calibration object but more views should be used for better results. the proposed calibration method was evaluated with real images and the obtained results are promising. the calibration software will become commonly available at the author's web page.
robust feature matching across widely separated color images. we present a novel method for feature matching across widely separated color images. the proposed approach is robust and can support various correspondence based algorithms e.g. the recovery of epipolar geometry. our algorithm extends an existing gray-scale corner detector to color. the feature matching algorithm robustly segments the area around the feature into significant color regions using the mean shift mode estimator. the recovered data structures are matched under all possible rotations and the best rotation and its corresponding matches are selected. the results of the matching algorithm are used for recovery of the epipolar geometry from wide base line stereo image pairs. the algorithm has been tested extensively yielding good results over a wide range of scenes and viewpoints. a small subset of these results are presented in the paper.
post-processing scheme for improving recognition performance of touching handwritten numeral strings. this paper describes post-processing scheme to improve recognition performance of touchinghandwritten numeral strings. verification factors are defined to rectify recognition results of digits that are segmented by the highest reliability values. three kinds of verification factors from structural features and recognition probability are used to determine missegmented digits. additional segment digit set is included in valid digit sets when it satisfies the reconsideration condition. final optimal digit set is selected as the highest ranked segment digit set among all candidate segmented digit sets. introduction of reconsideration condition and additional segment digit set improves the reliability of recognition result as well as recognition performance. experiments are carried out with touching handwritten numeral strings of nist sd19 database and an encouraging recognition result has been obtained.
text extraction from web images based on a split-and-merge segmentation method using colour perception. this paper describes a complete approach to the segmentation and extraction of text from web images for subsequent recognition, to ultimately achieve both effective indexing and presentation by non-visual means (e.g., audio). the method described here (the first in the authorsý systematic approach to exploit human colour perception) enables the extraction of text in complex situations such as in the presence of varying colour (characters and background). more precisely, in addition to using structural features, the segmentation follows a split-and-merge strategy based on the hue-lightness-saturation (hls) representation of colour as a first approximation of an anthropocentric expression of the differences in chromaticity and lightness. character-like components are then extracted as forming textlines in a number of orientations and along curves.
variational multigrid for fast 3d interpretation of image sequences. we propose a variational multigrid method for fast 3d interpretation of image sequences, in which a dense depth map and 3d motion are directly recovered from spatiotemporal change of intensity images without prior matching and estimation. in this paper, we adopt the multigrid methods to efficiently reduce the computational complexity of the variational method, and suggest a new variational formulation to reliably perform the 3d interpretation. we show the efficiency and effectiveness of our method through experimental results with synthetic and real images.
a ground truth correspondence measure for benchmarking. automatic localisation of correspondences for the construction of statistical shape models from examples has been the focus of intense research during the last decade. several algorithms are available and benchmarking is needed to rank the different algorithms. prior work has focused on evaluating the quality of the models produced by the algorithms by measuring compactness, generality and specificity. in this paper problems with these standard measures are discussed. we propose that a ground truth correspondence measure (gcm) is used for benchmarking and in this paper benchmarking is performed on several state of the art algorithms. minimum description length (mdl) with a curvature cost comes out as the winner of the automatic methods. hand marked models turn out to be best but a semi-automatic method is shown to lie in between the best automatic method and the hand built models in performance.
parameterisation invariant statistical shape models. in this paper novel theory to automate shape modelling is described. the main idea is to develop a theory that is intrinsically defined for curves, as opposed to a finite sample of points along the curves. the major problem here is to define shape variation in a way that is invariant to curve parameterisations. instead of representing continuous curves using landmarks, the problem is treated analytically and numerical approximations are introduced at the latest stage. the problem is solved by calculating the covariance matrix of the shapes using a scalar product that is invariant to global reparameterisations. an algorithm for implementing the ideas is proposed and compared to a state of the art algorithmfor automatic shape modelling. the problems with instability in earlier formulations are solved and the resulting models are of higher quality.
automatic segmentation of zona pellucida in hmc images of human embryos. an important prognostic parameter for assessing the success of an in vitro fertilization treatment is the variation in thickness of the zona pellucida. zona pellucida, the envelope of the human embryo, is usually visualized using hoffman modulation contrast microscopy (hmc). the paper addresses the problem of segmenting the zona pellucida in hmc images of embryos. we propose a variational method based on an image model for the zona which takes advantage of the characteristic appearance of hmc images. the simple topology of the embryo allows us to focus on parametric models. our approach is partly inspired by the works of chan and vese, to which it has some similarities.
how human visual systems recognize objects - a novel computational model. this paper presents a novel computational model of 3d object recognition based on human visual system. conventional schemes have feed forward structure based on the bottom-up process of human vision. however, psychological and physiological evidence suggests that top-down process and feature binding by visual attention are also important. so, we propose a method to integrate these facts under statistical framework, markov chain monte carlo. in this scheme, object recognition is regarded as parameter optimization problem. the bottom-up process is used to initialize parameters and top-down process is used to optimize them. on both processes, feature map binding is performed by spatial attention mechanism. experimental results show that the proposed computational model is feasible for 3d object recognition.
efficient region based indexing and retrieval for images with elastic bucket tries. retrieval and indexing in multimedia databases has been an active topic both in the information retrieval and computer vision communities for a long time. in this paper we propose a novel region based indexing and retrieval scheme for images. first we present our virtual textual description using which, images are converted to text documents containing keywords. then we look at how these documents can be indexed and retrieved using modified elastic bucket tries and show that our approach is one order better than standard spatial indexing approaches. we also show various operations required for dealing with complex features like relevance feedback. finally we analyze the method comparatively and and validate our approach.
a quick video search method based on local and global feature clustering. this paper proposes a quick method of similarity-based video searching to detect and locate a specific video clip given as a query in a stored long video stream.the method employs a two-stage process: local and global feature clustering. the local clustering exploits continuity or local similarities between video features, and the global clustering gathers similar video frames that are not necessarily adjacent to each other.these processes prune irrelevant sections on a video stream.the method guarantees the exactly same search result as the exhaustive search. experiments performed on a pc show that the proposed method can correctly detect and lcoate a 7.5-second clip in a 150-hour video recording in 15 ms on average.
a wavelet-based watershed image segmentation for vop generation. this paper presents a wavelet-based watershed image segmentation method for extracting video objects from a video sequence. the method is based on a multiresolution application of a wavelet and watershed transformation, followed by a wavelet coefficient-based region merging procedure. the procedure toward complete segmentation consists of four steps: pyramid representation, region segmentation, region merging, and region projection. first, the pyramid representation creates multiresolution images using a wavelet transform. second, region segmentation is used to segment the lowest-resolution image of the created multiresolution image. third, the region merging is merged to segmented regions using the third-order central moment values of the wavelet coefficients. finally, the region projection is used to recover a full-resolution image by inverse wavelet transform. experimental results of the presented method can be applied to the segmentation of noise or degraded images and reduction of over-segmentation.
human head tracking in three dimensional voxel space. this paper proposes a new approach to track a human head in 3-d voxel space. information of both color and distance is obtained from multiple stereo cameras and integrated in 3-d voxel space. formulating a likelihood function from voxel location and its color information can achieve stable tracking with particle filtering in 3-d voxel space.
ent-boost: boosting using entropy measure for robust object detection. recently, boosting has come to be used widely in object-detection applications because of its impressive performance in both speed and accuracy. however, learning weak classifiers which is one of the most significant tasks in using boosting is left to users. in discrete adaboost, weak classifiers with binary output are too weak to boost when the training data is complex. meanwhile, determining the appropriate number of bins for weak classifiers learned by real adaboost is a challenging task because small ones might not accurately approximate the real distribution while large ones might cause over-fitting, increase computation time and waste storage space. we have developed ent-boost, a novel boosting scheme for efficiently learning weak classifiers using entropy measures. class entropy information is used to automatically estimate the optimal number of bins through discretization process. then kullback-leibler divergence which is the relative entropy between probability distributions of positive and negative samples is used to select the best weak classifier in the weak classifier set. experiments showed that strong classifiers learned by ent-boost can achieve good performance, and achieve compact storage space. the result of building a robust face detector using ent-boost showed the boosting scheme to be effective.
real-time, 3-d-multi object position estimation and tracking. for autonomously acting robots and driver assistance systems powerful optical stereo sensor systems are required. object positions and environmental conditions have to be acquired in real-time. in this paper a hardware-software co-design is applied, acting within the presented stereophotogrammetric system. for calculation of the depth map an optimized algorithm is implemented as a hierarchical parallel hardware solution. by adapting the image resolution to the distance, real-time processing is possible. the object clustering and the tracking is realized in a processor. the density distribution of the disparity in the depth map (disparity histogram) is used for object detection. a kalman filter stabilizes the parameters of the results.
simultaneous classification and visualword selection using entropy-based minimum description length. in this paper, we present a new entropy-based minimum description length (mdl) criterion for simultaneous classification and visual word selection. conventional mdl criteria focus on how to minimize cluster size and maximize the likelihood of data points. we extend the mdl by replacing the likelihood term with the entropy of class posterior. this new criterion can provide optimal visual words with enough classification accuracy. we validate the entropybased mdl to learn optimal visual words for place classification and categorization of the caltech 101 object database.
camera calibration with a transparent calibration tool using color filters: application to stereo camera calibration for a distant object. in this paper, we propose a transparent calibration tool that can calibrate in a straightforward manner without resetting or removing the tool, which consists of two parallel transparent boards with patterns of dots of a color filter material. the tool is installed in front of a color camera, which acquires images through it. images for calibration and the scene image are acquired simultaneously in different color bands. the proposed method is applied to stereo camera calibration for a distant small object.
estimating intrinsic parameters of cameras using two arbitrary rectangles. in this paper, we propose new camera calibration methods assuming a static camera. two corresponding imaged rectangles whose aspect ratios are unknown are sufficient to calibrate a camera. by warping the images properly, we show that the information from the imaged rectangles can be transformed to the form of camera constraints. based on this results, we propose two methods, one for three or more images and the other for only two images. the proposed methods are verified with synthetic and real images, and the results are comparable with less assumptions on cameras and on scenes.
vizwear-active: distributed monte carlo face tracking for wearable active cameras. in this paper, we discuss a distributed monte carlo (dmc) tracking method which achieves real-time and accurate face tracking for wearable active vision systems. the dmc is an extension of sequential monte carlo approaches to a client-server distributed architecture. the client feeds back the results of tracking for use in the control of the wearable active camera with minimal delay, and the server accurately tracks the faces at the same time. in our method, the client is able to complete the tracking processes even when it is unable to communicate with the server. furthermore, more accurate results are obtained when it is able to communicate with the server. we have implemented and demonstrated this method on the vizwear-active system which includes a wearable active camera.
multi-modal sequential monte carlo for on-line hierarchical graph structure estimation in model-based scene interpretation. we present a computationally efficient, on-line graph structure estimation method for model-based scene interpretation. different scenes have different hierarchical graphical models composed of place, objects, and parts. generally, it is very difficult and time-consuming to estimate dynamic graph structures. the key idea is to represent hypothesized graph structures as multi-modal particles instead of joint particle representation. such monte carlo representation makes the one-line hierarchical graph structure estimation feasible. the proposed method is supported by the neurobiological inference model. large-scale experimental results in an indoor (12 places, 112 3d objects) validate the feasibility of the proposed inference method.
face recognition using lda mixture model. linear discriminant analysis (lda) provides the projection that discriminates data well, and shows a good performance for face recognition. however, since lda provides only one transformation matrix over the whole data, it is not sufficient to discriminate complex data consisting of many classes with high variations, such as human faces. to overcome this weakness, we propose a new face recognition method based on the lda mixture model, where the set of all classes are partitioned into several clusters and we obtain a transformation matrix for each cluster. this accurate and detailed representation will improve classification performance. simulation results of face recognition show that lda mixture model outperforms pca, lda, and pca mixture model in terms of classification performance.
multicue mrf image segmentation: combining texture and color features. herein, we propose a new markov random field (mrf) image segmentation model which aims at combining color and texture features. the model has a multi-layer structure: each feature has its own layer, called feature layer, where an mrf model is defined using only the corresponding feature. a special layer is assigned to the combined mrf model. this layer interacts with each feature layer and provides the segmentation based on the combination ofdifferent features. the uniqueness of our algorithm is that it provides both color only and texture only segmentations as well as a segmentation based on combined color and texturefeatures. the number of classes on feature layers is given by the user but it is estimated on the combined layer.
usefulness of boundary sequences in computing shape features for arbitrary shaped regions. a boundary sequence is a good representation of arbitrary shaped regions, but not directly used in computing shape features such as area, centroid, orientation, and so forth. in this paper, we show that the shape features can be easily computed by using cross-sections derived from a boundary sequence. the cross-sections are vertical line segments in the region and can be determined by tracing the boundary sequence once. furthermore, a boundary sequence extraction method is also proposed, which generates a boundary sequence for each region in a binary image by scanning the image only once. the proposed method workswell even if a region has holes.
direct condensing: an efficient voronoi condensing algorithm for nearest neighbor classifiers. voronoi condensing reduces training patterns of nearest neighbor classifiers without changing the classification boundaries. this method plays important roles not only in the nearest neighbor classifiers but also in the other classifiers such as the support vector machines, because the resulting prototype patterns involve support vectors in many cases. however, previous algorithms for voronoi condensing were computationally inefficient in general pattern recognition tasks. this is because they use proximity graphs for entire training patters, which require computational time exponentially for the dimension of pattern space. for solving this problem, we proposed an efficient algorithm for voronoi condensing named direct condensing that does not require the entire proximity graphs of training patterns. we confirmed that direct condensing efficiently calculates voronoi condensed prototypes in high dimension (from 2 to 20 dimensions).
box-like superquadric recovery in range images by fusing region and boundary information. this work contributes to the robotic bin-picking problem, and more specifically to the problem of localizing piled box-like objects. we employ range imagery, and use box-like superquadrics for modeling the target objects. our approach for superquadric segmentation is an extension of the widespread recover-and-select framework, which employs only region information and therefore suffers from the region over- growing problem. our approach equally considers both region and boundary-based information for performing the recovery task. extensive experimentation with a variety of target object configurations demonstrates that it outperforms the recover-and-select framework in terms of both robustness and computational efficiency. moreover, if implemented in a parallel hardware environment, our approach can operate in real time.
new enhancement algorithm for fingerprint images. in this paper, an improved algorithm for enhancement of fingerprint image is proposed on the basis of the image normalization and gabor filter. firstly, the adaptive normalization based on block processing is suggested for improvement of fingerprint images. an input image is partitioned into sub-blocks with the size of k × l at first and the region of interest (roi) of the fingerprint image is acquired. the parameters for the image normalization are adaptively determined according to the statistics of each block. by utilizing these parameters, the block image is normalized for the next process. secondly, a new technique for selection of two important parameters of gabor filter is devised. these parameters are the ridge direction and the ridge frequency. in this study, the ridge direction of a block image is determined by the probabilistic approach unlike other works. with this ridge direction, the ridge frequency is selected by utilizing the directional projection. the proposed algorithms are tested with nist fingerprint images and show significant improvement in the experiments.
edge detection in range images of piled box-like objects. we present a framework for edge detection in range images acquired by a time of flight laser sensor. our edge detection approach is inspired by [edge detection in range images based on scan line approximation], in the context of which edge detection via scan line approximation with geometric parametric models is performed. the main drawback of this edge detector, namely the scan line over-segmentation problem is addressed by the introduction of a simple merging step. in addition, we incorporate a method for detection of the noisy data points created by the effect of laser beam splitting between surfaces of different ranges. finally, a procedure for fine localization of the edge points is introduced. experimental results on a variety of target object configurations demonstrate that our edge detection framework exhibits increased robustness and accuracy with regard to [edge detection in range images based on scan line approximation]. these characteristics in combination with the computational efficiency of our approach, allows for its usage as a component of a real time system for automatic unloading of piled box-like objects.
a robust license-plate extraction method under complex image conditions. a robust approach for extracting car license plate from images with complex background and relatively poor quality is presented in this paper. the approach focuses on dealing with images taken under weak lighting condition. the proposed method is divided into two steps: 1) searching candidate areas from the input image using gradient information, and 2) determining the plate area among the candidates and adjusting the boundary of the area by introducinga plate template. a set of experiments has been performed to prove the robustness and accuracy of the approach. for many images collected from a large underground parkingplace the result shows that 90% of them are correctly segmented.
robustness of linear discriminant analysis in automatic speech recognitio. this paper focuses on the problem of a robust estimation of different transformation matrices based on the well known linear discriminant analysis (lda) as it is used in automatic speech recognition systems. we investigate the effect of class distributions with artificial features and compare the resulting fisher criterion. this paper shows that it is not very helpful to use only the fisher criterion for an assessment of class separability. furthermore we address the problem of dealing with too many additional dimensions in the estimation. special experiments performed on subsets of the wallstreet journal database (wsj) indicate that a minimum of about 2000 feature vectors per class is needed for robust estimations with monophones. finally we make a prediction to future experiments on the lda matrix estimation with more classes.
stroke verification with gray-level image for hangul video text recognition. traditional ocr uses binarization technique, which makes ocr simple. but it makes strokes ambiguous and that causes recognition errors. main reason of those errors is similar grapheme pair confusing error. it can be reduced by verifying ambiguous area of gray level image. after checking whether there is similar grapheme pair by analyzing traditional ocr result candidates, the base stroke of confused grapheme can be found using the fitness function which reflects the base stroke characteristics. the possibility of confused stroke existence can be measured by analyzing the boundary area of the base stroke. the result is merged with traditional ocr using score-probability converting. we achieved 68.1% error reduction for target grapheme pair errors by the proposed method and it means that 23.1 % total error is reduced.
recognition and segmentation of scene content using region-based classification. we present a novel method for joint segmentation and pixelwise classification of images, classifying each pixel in the image into one of a set of broad categories. we propose a 2-step approach for this problem, first estimating image structure through dense region segmentation, which provides initial spatial grouping (superpixels), then performing recognition by classifying each superpixel according to its features. two types of region features are investigated: perceptual grouping features derived from neighborhood relations in the superpixel graph, and a histogram of pixel textons within the superpixel. region classification is performed by boosting for perceptual features and histogram matching for texton features. we also introduce a novel extension of multi-class boosting: map estimation in the space of classifier ensemble outputs. extensive results on aerial imagery are presented using a label vocabulary of trees, roads, vehicles, grass, shadows, and buildings. we evaluate the two methods across the categories, and compare them to the standard approach of classifying image blocks without prior segmentation. in our experiments perceptual features using multi-class boosting provide the best performance.
joint optimization of image registration and comparametric exposure compensation based on the lucas-kanade algorithm. an iterative registration algorithm, the lucas-kanade algorithm, is combined with an exposure compensation algorithm to jointly optimize the spatial registration and the exposure compensation. the coordinate descent method is employed to minimize a mean squared error between image pairs. based on a simple regression model, a nonparametric estimator, the empirical conditional mean and its polynomial fitting are used as histogram transformation functions for the exposure compensation. the proposed algorithm performs a good registration for real perspective and microscopic images, and can easily adopt other exposure compensation approaches and variations of the lucas- kanade algorithms due to its implicit flexibility.
handwriting authentication by envelopes of sound signatures. frictions between a rigid-nib pen and paper result in audible sounds that are correlated with the dynamics of writing. such writing-sounds were previously used as a biometric identity to achieve writer authentication. this paper presents an alternative and supplement algorithm for sound-based handwriting authentication. envelopes of writing-sounds estimated by the hilbert transforms are found useful in differentiating topologically similar characters written by different individuals. a straightforward supervised neural network in conjunction with a purpose-designed pre-processor can be trained on examples to effectively differentiate patterns of writing-sounds and thus achieve writer authentication, providing a straightforward and potential alternative to existing methods.
handwritten character recognition based on structural characteristics. in this paper a handwritten character recognition algorithm based on structural characteristics, histograms and profiles, is presented. the well- known horizontal and vertical histograms are used, in combination with the newly introduced radial histogram, out-in radial and in-out radial profiles for representing 32 x 32 matrices of characters, as 280- dimension vectors.the k-means algorithm is used for the classification of these vectors. detailed experiments performed in nist and gruhd databases gave promising accuracy results that vary from 72.8% to 98.8% depending on the difficulty of the database and the character category.
object class recognition using images of abstract regions. with the advent of many large image databases, both commercial and personal, content-based image retrieval has become an important research area. while most early efforts retrieved images based on appearance, it is now recognized that most users want to retrieve images based on the objects present in them. this paper addresses the challenging task of recognizing common objects in color photographic images. we represent images as sets of feature vectors of multiple types of abstract regions, which come from various segmentation processes. we model each abstract region as a mixture of gaussian distributions over its feature space. we have developed a new semi-supervised version of the em algorithm for learning the distributions of the object classes. we use supervisory information to tell the procedure the set of objects that exist in each training image, but we do not use any such supervisory information about where (ie. in which regions) the objects are located in the images. instead, we rely on our em-like algorithm to break the symmetry in an initial solution that is estimated with error. experiments are conducted on a set of 860 images to show the efficacy of our approach.
sky-ground representation for local scene description. this paper proposes a new representation, called a sky-ground representation, for describing scenes of environment at a local place. a sky-ground representation is a spherical image with full field of view, combined with a vertical reference which is determined by sensing the direction of gravity. the scene of environment at a local place is observed by a spherical image sensor. the acquired spherical image is divided into two parts, sky part and ground part, along the horizon according to their positions, above or below the horizon. the horizon is determined by sensing the gravity from an acceleration sensor.
a comparison of the gender differentiation capability between facial parts. the main purpose of our research is to evaluate which subject's facial parts are most effective at making the difference between men and women. we prepared the four directional feature fields on multiple facial parts images, such as face, jaw, lip, nose, eyes, and r eye. then, we recognized these images by using the linear discriminate analysis. furthermore, we analyzed the feature space by using cluster discriminate analysis. after experimenting on a large number of subjects, we conclude that face and jaw make good feature spaces.
a clustering based color model and fast algorithm for object tracking. the paper presents a clustering based color model and develops a fast algorithm for object tracking. the color model is built upon k-means clustering, by which the color space of the object can be partitioned adaptively and the histogram bins can be determined accordingly. in addition, in each bin the multi-channel gray level is modelled as gaussian distribution. a metric based on chernov distance is defined to measure similarity between the reference model and the candidate model. the integral images are proposed for computation of mean vector and covariance matrix of color images, through which the similarity metric can be evaluated very fast. comparisons with the wellknown mean shift algorithm demonstrate the validity of the model and performance of the proposed algorithm.
integration of pose recognition for a person wearing short or long sleeves. in this paper; we propose a tv control system for aged and bedridden people. we have been constructing the interface, which changes tv channels and operate volume controls using pose recognition. however; users were required to wear the short-sleeved shirt torecognize the poses by using the skin color regions as arms. to allow the long sleeve for users, we improve our system to introduce the relation of the position of the higher local auto correlation features to identify the pose.first, face and hand regions of the user are detected by using the skin color from the input image. since it assumed that a width of a face region should be larger than arms, the face region is decided from the detected skin color regions by the erosion operation. after detecting the face region, a pose recognition area that is decided on the basis of the face position is divided into 9 (3 x 3) regions. the features are extracted from the 6 areas because the arms appear within the 6 areas. using our algorithm, our system can recognize poses even if the user wears a long sleeve or short-sleeved shirt.
real-time spherical stereo. by defining the disparity of a spherical stereo we reformulate the real-time stereo problem. based upon this definition the realtime spherical stereo becomes a general model which can cope with cameras with any wide field of view including conventional ones. by transforming the rectified spherical images to latitudelongitude representation, the correspondence of feature points can be speeded up by the same processing as planar stereo images. the effectiveness of this approach is shown by realizing a real-time spherical stereo using a pair of fisheye cameras.
real-time detection of anomalous objects in dynamic scene. there are many methods to extract moving objects in a scene using background subtraction. however, most methods assume that there are no moving objects except intruders in the observing space. in this paper, we propose the iterative optimal projection method to estimate a varied background in real time from a dynamic scene with intruders. at first, background images are collected for a while, because we assume that the motion of background is well known. then, the background images are compressed using eigenspace method to form a database. while monitoring the scene, new image is taken by a camera, and the image is projected onto the eigenspace to estimate the background. but however, the estimated image is much affected by the intruders, so the intruder region is calculated by using background subtraction with former estimated background to exclude the region from the projection. thus the image whose intruder region is replaced by the former background is projected to eigenspace and we have updated background. we proved that the cycle converges to a correct background image and we confirmed we can calculate the right region of the object through some experiments.
wavelet-based morphological approach for detection of human face region. in this paper, we present a novel method to detect a human skin region from a given head and shoulder image. the presented method consists of two stages: region segmentation and facial region detection. in the region segmentation, the input image is segmented into an appropriate set of arbitrary regions using the wavelet-based watershed algorithm. then, to merge the regions forming an object, we use a spatial similarity between two regions since the regions forming an object share some common wavelet characteristics. in facial region detection, the facial regions are identified from the segmented results using a skin-color model. the results of region segmentation and facial region detection are integrated to provide facial regions with accurate and closed boundaries. in our experiments, the algorithm detected 87-94% of the faces, including frames from videoconference sequences. the average run time range from 0.23-0.34 sec per frame.
non-contrast based edge descriptor for image segmentation. we present an efficient object segmentation strategy based on edge information to assist object-based video coding, motion estimation and motion compensation for the mpeg system. two parameters are introduced and described based on edge information from the analysis of a local histogram. using these features, a non-contrast based edge function is defined to generate an edge information map, which can be thought as a gradient image. then, an improved marker-based region growing and merging techniques are derived to separate image regions. the proposed algorithm is tested on several standard images and demonstrates high reliability for object segmentation.
a support system for visually impaired persons to understand three-dimensional visual information using acoustic interface. visual information processing technology is very important in the implementation for sensory substitution of visually impaired persons as well as applications to factory automation. this paper outlines the design of a visual support system that provides 3d visual information using 3d virtual sounds. three-dimensional information, such as distance map, object recognition, and object tracking required for the visually impaired user, is obtained by analyzing imagescaptured by stereo cameras. using a 3d virtual acoustic display, which relies on head related transfer functions (hrtfs), the user is informed of the locations and movements of objects. the user's external auditory sense is not impeded as the system uses bone conduction headphones which do not block out environment sounds. the proposed system is expected to be useful in the situations where the infrastructure is incomplete and the situation changes in real-time. we plan experiments using this system to guide users while walking and playing sports.
geographic hypermedia using search space transformation. we present a new approach for linking heterogeneous data of the same objective nature, such as 2d maps, 3d virtual environments and videos with gps data. we have identified three key challenges (georeferencing, content creation for geospatial videos and bidirectional linking) that should be addressed to link among geographic hypermedia. we propose an easily implementable data model that serves well as a foundation for point query in 2d and attribute query in a video. we also present a point query processing algorithm for video browsing by using the modified r-tree. the proposed method supports a geographic hypermedia navigation by providing the bidirectional linking. experimental results indicate that the proposed approach is effective in retrieving geospatial video clips and nonspatial data.
object boundary edge selection using normal direction derivatives of a contour in a complex scene. recently, nguyen proposed a method[tracking nonparameterized object contours in video]for tracking a nonparameterized object (subject) contour in a single video stream. nguyenýs approach combined outputs of two steps: creating a predicted contour and removing background edges. in this paper, we propose a method to increase object tracking accuracy by improving the background edge removal process. nguyen's background edge removal method of leaving many irrelevant edges is subject to inaccurate contour tracking. our accurate tracking is based on reducing affects from irrelevant edges by selecting the boundary edge only. we select high-valued edge pixels of average image intensity gradients in the contour normal direction. our experimental results show that our tracking approach is robust enough to handle a complex-textured scene.
tracking 3d human body using particle filter in moving monocular camera. in this paper, we propose a method for human tracking using 3d human body model in a video sequence with a monocular moving camera. tracking a human with unconstrained movement in moving monocular camera image sequence is extremely challenging. our 3d human body model which is formed with articulation model of hierarchical tree structure can express all human's movement by parameters. we can obtain 3d human body model which has the most similar shape with input image through similarity matching. in order to predict the region and movement of human using 3d human body model in the obtained current frame, we use the particle filter which predicts the posterior distribution by the random probability variable based on monte carlo sampling. as a result, it can be possible to track robustly for human's motion and random movement of camera in the environment with moving camera. we can get the result of converging toward minimized error values using boundary distance between a predicted 3d human body model and an input image. in the result of experiment, the proposed method showed correct tracking result for complex background and various human movements.
background robust object labeling by voting of weight-aggregated local features. in this paper, we present a new voting-based object labeling method that is robust to background clutter. the conventional simple voting method shows very poor performance under clutter. to reduce the effect of clutter, first we aggregate the weights between the features and the support features using similarity and proximity. through the recursive weight aggregation process, features belonging to the same objects get stronger weights, and features belonging to clutter get weaker weights. then, we vote the weightaggregated features to get the object labels. we validate the enhancement of the proposed method by using an open database and a real test set.
a new attributed relational graph matching algorithm using the nested structure of earth mover's distance. in general, object features can be represented as the nodes in attributed relational graph (arg) with the connecting edges implying their relations. therefore, the arg matching plays a significant role in object recognition. actually, the arg matching can be implemented as a 2-step procedure, composed of constructing a distance matrix and establishing the correspondence based on the distance matrix, which seems to be similar to the point matching procedure. in this paper, we present a new arg matching algorithm using the nested structure of earth mover's distance (emd). more specifically, the nested structure of the emd consists of inner emd and outer emd: the inner emd reflects the difference of both nodes and edges between a pair of nodes in two arg's in a perceptual manner, and the outer emd establishes the correspondence between nodes in the two arg's in a natural way. in order to demonstrate the robustness of the proposed algorithm against noise, we have conducted synthetic experiments for fully connected and undirected arg's as in [kronecker product graph matching].
new mrf parameter estimation technique for texture image segmentation using hierarchical gmrf model based on random spatial interaction and mean field theory. this paper presents a new markov random field (mrf) parameter estimation technique using hierarchical mrf model based on the random spatial interaction (rsi) and the mean field theory for the textured image segmentation. by considering spatial interaction of the mrf as random fields, the fluctuation of the spatial interaction that occurs in the conventional mrf model can be efficiently alleviated. also, by assuming randomness of the spatial interaction as the mrf model, it allows us to obtain more robust information for segmentation during the feature extraction. the gaussian mrf model is applied to the proposed hierarchical mrf scheme, and the expectation of the rsi is uniquely obtained by simple linear equation without using a window based on the mean field theory. experimental results on synthetic and real world images show that the proposed algorithm provides good feature extraction and segmentation.
acceleration of similarity-based partial image retrieval using multistage vector quantization. we propose a new method for quick and accurate partial image retrieval from a huge number of images based on a prede ned distance measure. the proposed method utilizes vector quantization (vq) on multiple layers, namely color, block, and feature layers. this can greatly reduce the amount of calculation needed for partial image retrieval. experiments indicate that the proposed method can detect partial images that are similar to queries through 1000 images within 4 seconds. this is approximately 30 times faster than the method to which multistage vq is not applied.
parallel volume segmentation with tetrahedral adaptive grid. we propose a general-purposed parallel algorithm for volume segmentation, which does not require any prior knowledge on volume nor region. the algorithm provides binary tree structured split-and-merge mechanism to search and localize boundaries along discontinuities and adapts the partition of volume to those detected discontinuities. this algorithm is independent from order of processing or seed selection. and, even though overlapping only one voxel wide boundary between process blocks, by adopting the smoothness-based local feature as homogeneity criteria, consistencies are maintained without overhead of communication between adjacent process blocks. our efficient hierarchical step-wised mechanism in merging target evaluation makes merge process so simple and efficient that only two brother blocks are considered at each merge step in binary fashion. experimental results on an artificial and a ct scan volume data are shown.
an extension of the generalized hough transform to realize affine-invariant two-dimensional (2d) shape detection. in this paper, we present a new method for two-dimensional (2d) shape detection applicable under affine transformation. the problem of affine-invariant shape detection is an important and fundamental research subject in computer vision. although various methods have been proposed to solve this problem, most of those approaches are not well suited for the following general cases: (1) a shape to be detected is occluded by other overlapping objects, (2) a shape boundary is partially broken because of noise or other factors. we introduce a new method to deal with such cases, which extends the generalized hough transform [1] to be an affine-invariant shape detector. this method, called the affine-ght, utilizes pairwise parallel tangents and basic properties of an affine transformation to carry the direct computation for six parameters of an affine transformation. experimental result demonstrates that the proposed method performs successfully and efficiently.
bin-picking based on harmonic shape contexts and graph-based matching. in this work we address the general bin-picking problem where 3d data is available. we apply harmonic shape contexts (hsc) features since these are invariant to translation, scale, and 3d rotation. each object is divided into a number of sub-models each represented by a number of hsc features. these are compared with hsc features extracted in the current data using a graph-based scheme. results show that the approach is somewhat sensitive to noise, but works in presence of occlusion.
efficient recognition of planar objects based on hashing of keypoints - an approach towards making the physical world clickable. this paper presents a method of planar object recognition for aiming at accessing information about objects by taking pictures of them. for this purpose efficiency of processing is the central issue because current state-of-the-art technologies with tree structures do not necessarily work well with a large amount of data represented as high dimensional vectors. to solve this problem, we employ hashing of keypoints extracted from images of objects. with the help of hash keys obtained as integers converted from the real valued vectors, keypoints are stored with object ids and retrieved with no search process. voting for object ids is employed to determine a recognized object as the one with the largest vote. experimental results show that the proposed method is at least 400 times faster than a brute-force method while 90% of objects were correctly recognized.
change detection using joint intensity histogram. in the present paper, a method for detecting changes between two images of the same scene taken at different times using their joint intensity histogram is proposed. first, the joint histogram, which is a two-dimensional (2d) histogram of combinatorial intensity levels, (i1(x), i2(x)), is calculated. by checking the characteristics of the ridges of clusters on the joint histogram, clusters that are expected to correspond to background are selected. the combinations of (i1, i2) covered by the clusters are determined as insignificant changes. pixels having a different combinatorial intensity (i1(x), i2(x)) from these combinations, are extracted as candidates for significant changes. based on the gradient correlation between the images for each region consisting of these pixels, only regions with significant changes are distinguished. experiments using real scenes show the practical usefulness of the method.
a deformable model driven method for handling clothes. a model-driven method for handling clothes by two manipulators based on observation with stereo cameras is proposed. the task considered in this paper is to hold up a specific part of clothes (e.g. one shoulder of a pullover) by the second manipulator, when the clothes is held in the air by the first manipulator. first, the method calculates possible 3d shapes of the hanging clothes by simulating the clothes deformation. the 3d shape whose appearance gives the best fit with the observed appearance is selected as estimation of the current state. then, based on the estimated shape, the 3d position and normal direction of the part where the second manipulator should hold are calculated. the experiments using actual two manipulators have shown the good potential of the proposed method.
stealth vision for protecting privacy. we propose an anonymous video capturing system, called "stealth vision", that protects the privacy of objects by fading out their appearance. in order to avoid difficulty in detecting the region of human faces (privacy-protected regions) in an image captured with a mobile camera, the fade-out areas are determined in 3d (three-dimensional) space instead of 2d image space. the 3d position of the captured object is estimated with a simple algorithm, which projects the foreground region in the overhead image onto several horizontal 3d planes and extracts the 3d position while merging the projecting results. by projecting the 3d information onto an image plane of mobile camera, the region to use for the anonymizing process is determined. experimental results show that our system successfully protects the privacy of target objects.
fractional component analysis (fca) for mixed signals. this paper proposes the fractional component analysis (fca), whose goal is to decompose the observed signal into component signals and recover their fractions. the uniqueness of our idea in comparison with other similar methods is the concept of the virtual pdf (probability distribution function) that models signal mixing on the sensor. in this paper, we derive the virtual pdf based on positivity constraint, unity constraint, and randomness assumption, and we then build it into the mixture density model. in order to learn parameters of this model from data using em (expectation-maximization) algorithm, the key point is to derive the approximation of the virtual pdf using its cumulants. finally we illustrate experimental results on synthetic data to show the unique decision boundary obtained from our method.
a method for automated extraction of aorta and pulmonary artery in the mediastinum using medial line models from 3d chest x-ray ct images without contrast materials. this paper proposes a new method of automated extraction of aorta and pulmonary artery (pa) areas in the mediastinum from uncontrasted 3d chest x-ray ct images. the proposed method does not extract contours of these blood vessels directly, but extracts the medial line of each vessel and recovers each vessel area. first, the process performs edge detection based on the local standard deviation to get edge areas of vessels. second, the euclidean distance transformation is applied for non-edge areas and the likelihood image of the center of vessels is obtained. medial line models are deformed basing upon the likelihood image so as to be fit to the center of each artery. the aorta and the pa areas are obtained by applying the reverse distance transformation to medial lines extracted above. we appliedthe proposed method to seven cases of uncontrasted 3d chest x-ray ct images. the experimental results showed that the aorta and the pa areas could be extracted satisfactorily.
recognition of lung lobes and its application to the bronchial structure analysis. this paper describes a method for recognizing the lung lobes and its application to analysis of the bronchial structure. analysis of the lung structure is one of important functions in a computer aided diagnosis system for chest ct data. since the lung is composed of five lobes, analysis of the lung requires recognition of each lobe area. thin membranes, called interlobar pleura, exist between lobes. their ct values are higher than those of the lung parenchyma on ct images. therefore, the proposed method extracts interlobar pleura regions and interpolates the regions by fitting quadratic surfaces. then, lung regions are divided into lobes using fitted surfaces. from the obtained lung lobe regions and the bronchial tree data extracted beforehand, each bronchial branch is classified into the lobe to which it belongs. the proposed method was applied to fourteen cases of 3d chest ct images. the experimental results showed that lung regions were satisfactorily divided into lobes and that most bronchi were classified into lobes to which they belong.
the effect of texture representations on aam performance. the active appearance model (aam) algorithm matches statistical models of shape and texture to images rapidly by assuming a linear relationship between the texture residual and changes in the model parameters. when the texture is represented as raw intensity values, this has been shown to be a reasonable approximation in many cases. however, models built on them are sensitive to changes in illumination conditions. this paper examines the effect of using different representations of image texture to improve the accuracy and robustness of the aam search. we show that normalising the gradient images by non-linear techniques can give much improved matching with higher accuracy and a wider effective range of convergence.
segment-based stereo matching using belief propagation and a self-adapting dissimilarity measure. a novel stereo matching algorithm is proposed that utilizes color segmentation on the reference image and a selfadapting matching score that maximizes the number of reliable correspondences. the scene structure is modeled by a set of planar surface patches which are estimated using a new technique that is more robust to outliers. instead of assigning a disparity value to each pixel, a disparity plane is assigned to each segment. the optimal disparity plane labeling is approximated by applying belief propagation. experimental results using the middlebury stereo test bed demonstrate the superior performance of the proposed method.
switche may solve adjacency problems. this paper presents a new and simple method for defining grid-point adjacencies, called the switch approach. it is discussed how it relates to connectedness definition in multi-valued images. the paper illustrates how the method can be used, and provides a few experimental data illustrating the relevance and simplicity of the approach.
svm-based salient region(s) extraction method for image retrieval. in region-based image retrieval, not all the regions are important for retrieving similar images and rather, the user is often interested in performing a query on only salient regions. therefore, we propose a new method for extraction of salient regions using support vector machines (svm) and a method for importance score learning according to the user's interaction. once an image is segmented, our algorithm permits the attention window (aw) according to the variation of an image and selects salient regions by using the pre-defined feature vector and svm within the aw. by using svm, we do not need to determine the heuristic feature parameters and produce more reasonable results. the distance values from svm are used for initial importance scores of salient regions and our proposed updating algorithm using relevance feedback updates them automatically. through performance comparison with parametric salient extraction method, our proposed method shows better performance as well as semantic query interface for object-level image retrieval.
improved n-division output coding for multiclass learning problems. the output coding for multiclass learning problems is a generalization of one-per-class, all-pairs, and error correcting output codes. although, the prevailing concepts of output coding has been error correcting properties, the one-per-class and all-pairs are still considered to be one of the state-of-art methods. however, these two methods are contrary to each other in the aspect of producing complex dichotomies and the problem of nonsense outputs. in additions, they all perform a prior decomposition without regards to the properties of a given training data set. in this paper, we propose a new data-driven output coding method that is the generalized form of one-per-class and all-pairs. we present the properties of the proposed method. from experimental results on both a toy problem and real benchmark datasets, we present that our proposed method achieves a comparable performance with good properties.
a new objective function for ensemble selection in random subspaces. most works based on diversity suggest that there exists only weak correlation between diversity and ensemble accuracy. we show that by combining the diversities with the classification accuracy of each individual classifier, we can achieve a strong correlation between the combined diversities and the ensemble accuracy in random subspaces.
a new image segmentation method for removing background of object movies by learning shape priors. this paper proposes a new object movie (om) segmentation method that incorporates shape priors into the segmentation algorithm. the shape prior introduced into every image of the om is learned from the 3d model reconstructed by the volumetric graph cuts. here, the constraint derived from the discrete medial axis is used to improve the reconstruction algorithm. our segmentation method requires only a small amount of user intervention, which is to select a subset of acceptable segmentations of the om after the initial segmentation process. compared to other techniques, our method provides not only the better segmentation result but also the better 3d reconstruction result.
action and simultaneous multiple-person identification using cubic higher-order local auto-correlation. we propose a new method - cubic higher-order local auto-correlation (chlac) - to address three-way data analysis. this method is a natural extension of higher-order local auto-correlation (hlac) [a new scheme for practical flexible and intelligent vision systems], which deals only with two-way data. both methods use "correlation" to summarize relative positions or motions within a local data region, and these can be calculated simply with a low computational load. moreover, our new method (chlac) offers several preferable properties as well as hlac: shift-invariance to data (rendering the method segmentation-free), additivity for data, and robustness to noise in data. in this study, we applied this method to action and simultaneous multiple-person identification from a motion-image sequence through the property of data additivity. experimental results showed that this method performed well.
determining optimal filters for binarization of degraded characters in color using genetic algorithms. this paper proposes a new binalization technique of characters in color using genetic algorithms (ga) to search for an optimal sequence of filters through a filter bank. the filter bank contains simple image processing filters as applied to one of the rgb color planes and logical/arithmetic operations between two color planes. first, we classify images of degraded characters extracted from the public icdar 2003 robust ocr dataset into several groups according to degradation categories. then, in the learning stage, by selecting training samples from each degradation category we apply ga to the combinatorial optimization problem of determining a filter sequence that maximizes the average fitness value calculated between the filtered training samples and their respective target images ideally binarized by humans. finally, in the testing stage, we apply the optimal filter sequence to binarization of remaining test samples. experimental results show the promising ability of the proposed method against a variety of image degradation causes.
asymmetric kernel method and its application to fisher's discriminant. in this paper, we propose the asymmetric kernel method. furthermore, we apply it to fisher's discriminant and provide an kernel fisher's discriminant with variable kernel parameters. we also provide the experimental result of the existing and the new kernel fisher's discriminants by using several standard datasets and show the advantage of our method.
rotated complex wavelet based texture features for content based image retrieval. in this paper we have proposed a novel approach of extracting texture features for content-based image retrieval. a new set of two-dimensional (2-d) rotated complex wavelet filters (rcwf) is designed with complex wavelet filter coefficients. 2-d rcwf are nonseparable and oriented, which improves characterization of oriented textures. dual-tree rotated complex wavelet filter (dt-rcwf) and dual-tree complex wavelet transform (dt-cwt) are used jointly for texture analysis in twelve different directions. texture features are obtained by computing the energy and standard deviation of each subband. retrieval results obtained using each individual method and in combination are presented. retrieval performance obtained with the combined filterbank is superior relative to the performance obtained using the other existing methods. new method also retains comparable levels of computational complexity.
multiresolution polygonal approximation of digital curves. we propose optimal split algorithm for multiresolution polygonal approximation of digital curves. instead of using a sequence of heuristic split steps as in the previous methods, we apply optimal approximation to obtain the next (higher) resolution levels using the previous (lower) resolution level as starting point. we compare the proposed approach against fast heuristic multiresolution algorithm based on a merge strategy under the l¿ error measure.
enhancements for local feature based image classification. using local features with nearest neighbor search and direct voting obtains excellent results for various image classification tasks. in this work we decompose the method into its basic steps which are investigated in detail. different feature extraction techniques, distance measures, and probability models are proposed and evaluated. we show that improvements are possible for each of the investigated enhancements. this shows that the important aspect of the framework is the decomposition of the training images into sets of local features for each class.
analysis of rotational robustness of hand detection with a viola-jones detector. the research described in this paper analyzes the in-plane rotational robustness of the viola-jones object detection method when used for hand appearance detection. we determine the rotational bounds for training and detection for achieving undiminished performance without an increase in classifier complexity. the result - up to 15° total - differs from the method's performance on faces (30° total). we found that randomly rotating the training data within these bounds allows for detection rates about one order of magnitude better than those trained on strictly aligned data. the implications of the results effect both savings in training costs as well as increased naturalness and comfort of vision-based hand gesture interfaces.
a viewpoint invariant approach for crowd counting. this paper describes a viewpoint invariant learningbased method for counting people in crowds from a single camera. our method takes into account feature normalization to deal with perspective projection and different camera orientation. the training features include edge orientation and blob size histograms resulted from edge detection and background subtraction. a density map that measures the relative size of individuals and a global scale measuring camera orientation are estimated and used for feature normalization. the relationship between the feature histograms and the number of pedestrians in the crowds is learned from labeled training data. experimental results from different sites with different camera orientation demonstrate the performance and the potential of our method.
a conditional random field model for video super-resolution. in this paper, we propose a learning-based method for video super-resolution. there are two main contributions of the proposed method. first, information from cameras with different spatial-temporal resolutions is combined in our framework. this is achieved by constructing training dictionary using the high resolution images captured by still camera and the low resolution video is enhanced via searching in this customized database. second, we enforce the spatio-temporal constraints using the conditional random field (crf) and the problem of video super-resolution is posed as finding the high resolution video that maximizes the conditional probability. we apply the algorithm to video sequences taken from different scenes using cameras with different qualities and promising results are presented.
coplanar light sweep-surface supported uncalibrated photometric stereo. in lambertian uncalibrated photometric stereo (ups), the object surface albedo and normals, the lighting directions and intensities are determined up to an arbitrary invertible matrix. in this paper, a novel method is proposed to reduce such an ambiguity. with the support of a coplanar light sweep-surface (clss), some key normals are determined relative to a fiducial normal which is estimated by the clss. thus the arbitrary transformation is reduced to invertible matrix up to a rotation and a scale. the rotation can be solved by controlling the direction of camera, the resulting ambiguity transformation can be finally determined up to a global scale.
competitive coding scheme for palmprint verification. there is increasing interest in the development of reliable, rapid and non-intrusive security control systems. among the many approaches, biometrics such as palmprints provide highly effective automatic mechanisms for use in personal identification. this paper presents a new method for extracting features from palmprints using the competitive coding scheme and angular matching. the competitive coding scheme uses multiple 2-d gabor filters to extract orientation information from palm lines. this information is then stored in a feature vector called the competitive code. the angular matching with an effective implementation is then defined for comparing the proposed codes, which can make over 9,000 comparisons within 1s. in our testing database of 7,752 palmprint samples from 386 palms, we can achieve a high genuine acceptance rate of 98.4% and a low false acceptance rate of 3 x 10^{-6} %. the execution time for the whole process of verification, including preprocessing, feature extraction and final matching, is 1s.
an anatomy of iriscode for precise phase representation. iriscode, a widely deployed iris recognition algorithm, developed in 1993 and continuously modified by daugman has attracted considerable attentions. iriscode using a coarse phase representation has number of properties such as rapid matching, binomial imposter distribution and predictable false acceptance rate. although many similar coding methods have been developed for irises and palmprints based on iriscode, a theoretical analysis of iriscode has not been provided. in this paper, we aim at studying (1) the nature of iriscode, (2) the property of the phase of gabor function, (3) the extension of bitwise hamming distance and (4) the theoretical foundation of the binomial imposter distribution and extending the coarse phase representation to a precise phase representation. precisely, we demonstrate that iriscode is a clustering algorithm with four prototypes; the locus of a gabor function is a two-dimensional ellipse with respect to the phase parameter and bitwise hamming can be regarded as angular distance. using these properties, we provide a precise phase representation for iriscode with an effective implementation for filtering and matching. practically, the imposter distribution of iriscode follows binomial distribution. however, the theoretical evidence is incomplete according to our analysis.
detection of spiralwaves in video. this paper presents novel video-based algorithms for detection and tracking of spiral waves in a spinning disk reactor. the algorithms are based on spiral wave model and their performance is compared with results predicted by the computational fluid dynamics algorithms for fluid flow. in each frame points on the top of waves are detected and a spiral model fitted to the points. using experimental video data, the developed models and algorithms allow investigators to estimate the characteristics of wave regimes such as wavelength and inclination angles. results computed from video data are compared with number predicted by the theoretical model.
global localization and relative pose estimation based on scale-invariant features. the capability of maintaining the pose of the mobile robot is central for basic navigation and map building tasks. in this paper we describe a vision-based hybrid localization scheme based on scale-invariant keypoints. in the first stage the topological localization is accomplished by matching the keypoints detected in the current view with the database of model views. once the best match has been found, the relative pose between the model view and the current image is recovered. we demonstrate the efficiency of the location recognition approach and present a closed form solution to the relative pose recovery for the case of planar motion and unknown focal length of the camera. the approach is demonstrated on several examples of indoors environments.
ok-quantization theory - a mathematical theory of quantization -. a mathematical basis for the digitization of gray value of an image is proposed. this was called oteru-koshimizu quantization theorem (ok-qt), on the analogy of the shannon sampling theorem (shannon-st) for the digitization of the shape of the image. inspired by the fact that the shannon-st is the reconstruction theorem of the analog image from the discrete image, ok-qt was modeled as the reconstruction theorem of the shape of the probability density function of gray values of an image. this is a novel and unique mathematical basis for the digitization of the gray scale of an image. this paper outlines this theorem and also shows some experimental results to demonstrate its practical applicability. through this, the ok-qt gives a clue to the mathematical paradigm for the complete basis for digitization, together with shannon st.
entropy-based measures for clustering and som topology preservation applied to content-based image indexing and retrieval. content-based image retrieval (cbir) addresses the problem of finding images relevant to the usersý information needs, based principally on low-level visual features for which automatic extraction methods are available. for the development of cbir applications, an important issue is to have efficient and objective performance assessment methods for different features and techniques. in this paper, we study the efficiency of clustering methods for image indexing with entropy-based measures. furthermore, the self-organizing map (som) as an indexing method is discussed further and an analysis method which takes into account also the spatial configuration of the data on the somis presented. the proposed methods enable computationally light measurement of indexing and retrieval performance for individual image features.
adaptive variational sinogram interpolation of sparsely sampled ct data. we present various kinds of variational pde based methods to interpolate missing sinogram data for tomographic image reconstruction. using the observed sinogram data we inpaint the projection data by diffusion. to overcome the problem of contour blurring we consider nonlinear and anisotropic diffusion based regularizers and include optical flow information in order to preserve the sinuodal traces corresponding to object contours in the reconstructed image. we compare our results to a spectral deconvolution based interpolation and show that the method can easily be extended to 3d.
efficient coding of stroke-rendered paintings. there are more and more applications of non-photorealistic rendered images, sketches and drawings. several techniques for generating such imagery are widely known. the stochastic painting-based painterly image (and video) generation presented herein is a multi-purpose image rendering and representation method, suitable for many purposes: painterly rendering, storing, compression or indexing. it incorporates many new features like multiscale edge following, stroke-set optimizations, templates, color morphology, etc. we will demonstrate that the presented technique (called enhanced stochastic paintbrush transformation or espt) is suitable for fast high quality painterly rendering, providing good lossless painted compression ratios and features that make it suitable for many applications. one of these we wish to emphasize is the suitability to code painted images in a way that does not introduce any coding artifacts (blockiness, ringings, etc.) but provides a compact form of representation that still retains the main property of a painting: that it is a painting after all.
towards image retrieval for eight percent of color-blind men. about 8% of men (but not women) are suffering from color blindness. the objective of this work was to investigate the problem of image retrieval based on color co-occurrence features when comparing normal vision and three kinds of color blindness (dichromasia): protanopia, deuteranopia, and tritanopia. original database comprises 12000 images that were also converted into three dichromatic versions using the vischeck simulation tool. results of 48000 queries were used to study influence of color blindness on retrieval results. principal component analysis, multidimensional scaling, hierarchical clustering, support vector machines, and statistical methods were employed for investigating feature space distortions associated with color blindness.
a new method for quantification of age-related brain changes. a new method is proposed for quantification of age-related brain changes. the method includes calculating 3d volumetric texture descriptors, extracting principal components, and assessing the significance of brain changes using multivariate analysis techniques. structural changes were evaluated using high resolution anatomical mri-t1 brain images of a group of 152 healthy subjects aged from 18 to 70 years (76 males and 76 females). the talairach parcellation system was applied to study normal brain aging on four scale levels: the whole cerebrum, the nine coronal sections, the twelve axial sections, and 108 box-shaped sections resulting from both subdivisions. statistical analysis has revealed significant brain deteriorations with age at different scale levels. most of the brain regions are affected with a slight predominance in the frontal lobes. we concluded that 3d texture analysis followed by statistical evaluation procedures is a robust technique for detecting age-related changes in the anatomical mr images of the human brain.
structural brain asymmetry as revealed by 3d texture analysis of anatomical mr images. we used 3d texture analysis approach to examine the structural brain asymmetry. the method is based on extended, multi-sort co-occurrence matrices that employ intensity, gradient and anisotropy image features in a uniform way. the asymmetry in normals and in patients with pathological findings was evaluated on a large sample of 310 mri-t1 images with the focus on the asymmetry differences associated with gender. the analysis revealed higher asymmetry in males comparing females (t=7.23, p
the classification gradient. we propose a method that uses bootstraping to classify the pixles in the two halves of a sliding window, assuming that if there is a real image boundary separating the two halves, the pixels in the two halves will be classified in two separate classes. the accuracy of the classification is used as a local "gradient". high values of this gradient allow us to detect weak statistical borders in 2d and 3d images.
initialization and system modeling in 3-d pose tracking. initialization and choice of adequate motion models are two important but seldom discussed problems in 3d modelbased pose (position and orientation) tracking. in this paper, we propose an automatic initialization approach suitable for textured objects. in addition, we define, study and experimentally evaluate three motion models commonly used in visual servoing and augmented reality.
iris identification using wavelet packets. in this paper, we present a new method for iris identification particularly convenient for visible light images. it relies on the use of packets of wavelets [texture classification by wavelet packet signatures] for the production of an iris code. experiments, conducted on a database of 700 iris images, acquired with visible light illumination, show an improvement of 2% of far and of around 11.5% of frr with the proposed method relatively to the classical wavelet method [high confidence recognition of persons by rapid video analysis of iris texture]. the contribution of colour information is also studied with such method.
robust detection of buildings in digital surface models. there is growing interest in the automatic interpretation of range data acquired by airborne laser scanners. huge volumes of data involved in land use analysis and building reconstruction applications necessitate a preliminary step to focus attention on interesting areas. in this paper, we present a technique to detect and discriminate buildings and vegetation in dense digital surface models (dsm) by combining curvature based features and edge information. our results demonstrate the effectiveness of differential geometric properties in the analysis of range data.
feature selection based on the training set manipulation. a novel filter feature selection technique is introduced. the method exploits the information conveyed by the evolution of the training samples weights similarly to the adaboost algorithm. features are selected on the basis of their individual merit using a simple error function. the weights dynamics and its effect on the error function are utilised to identify and remove redundant and irrelevant features. in experiments we show that the performance of commonly employed learning algorithms using features selected by the proposed method is the same or better than that obtained with features selected by the traditional state-of-theart techniques.
mixture of support vector machines for hmm based speech recognition. speech recognition is usually based on hidden markov models (hmms), which represent the temporal dynamics of speech very efficiently, and gaussian mixture models, which do non-optimally the classification of speech into single speech units (phonemes). in this paper we use parallel mixtures of support vector machines (svms) for classification by integrating this method in a hmm-based speech recognition system. svms are very appealing due to their association with statistical learning theory and have already shown good results in pattern recognition and in continuous speech recognition. they suffer however from the effort for training which scales at least quadratic with respect to the number of training vectors. the svm mixtures need only nearly linear training time making it easier to deal with the large amount of speech data. in our hybrid system we use the svm mixtures as acoustic models in a hmm-based decoder. we train and test the hybrid system on the darpa resource management (rm1) corpus, showing better performance than hmm-based decoder using gaussian mixtures.
singular point detection in fingerprints using quadrant change information. automatic localization of singular points in fingerprints is of critical importance in many algorithms. existing methods of detecting singular points often require tedious ad-hoc parameter tuning, particularly in the presence of degraded quality fingerprints. in this paper we present an approach towards singular point detection in fingerprints that operates on the quadrant change information and is largely insensitive to the degradation of fingerprint quality.
lossless compression methods for hyperspectral images. a novel efficient algorithm for lossless compression of hyperspectral images has been developed. the algorithm uses entropy function as a measure of interband similarity instead of correlation and mutual information functions that have been previously involved. the algorithm owes its performance to a newly invented adaptive prediction model. image band reordering and prediction have been done according to the model steps. edmond's algorithm has been proposed for finding optimal band ordering as an alternative to prim's algorithm. the results obtained are outstanding. moreover, three best lossless compression algorithms have been reviewed, tested using the same satellite data and compared to our method. we show that the proposed algorithm is capable of achieving compression ratios superior to that of the best-known lossless compression algorithms for hyperspectral images.
virtual view generation by linear processing of two differently focused images. in this sketch, we present a novel approach to image-based rendering (ibr) techniques for generating a virtual view image from different positions with arbitrary focus using two differently focused images captured from a fixed position. in the conventional approach [potmesil and chakravarty 1981], focus blur have been produced by applying a realistic camera model to given 3d objects. we propose here a much simpler and more effective method only using space-invariant filters to render both parallax and focusing effects on objects in a scene, according to the virtual camera's position and focus depth respectively. the proposed method does not need any segmentation and 3d modeling.
training of classifiers using virtual samples only. this paper describes the training of classifiers entirely based on virtual images, rendered by a ray-tracing software. two classifers, a support vector machine and a polynomial classifier, are trained solely with virtual samples and used for classification of real samples.the objects to be distinguished are holes vs. garbage (non-holes) out of a set of hole candidates in images of flanges.we analysed the effect of different classifier parameters and manipulation of the virtual samples.error rates of 1.6% on real test samples are achieved.
transitions of the pre-symmetry set. the symmetry set (ss) and its subset the medial axis (ma), can be used to describe a shape.the representation of the ss in parameter space is called the pre-symmetry set.changes in the shape are directly related to so-called transition (topological changes) of the ss.they have also effect on the pre-ss.since the pre-ss can be used to represent the shape efficiently, it is important to study the transitions of the pre-ss and their impact.we present these transitions, as well as the presence of the ma in the pre-ss.
matching 2d shapes using their symmetry sets. we introduce a shape descriptor that is based on the symmetry set. this set represents pairwise symmetric points and consists of several branches. the begin and end points of the branches relate to extrema of the curvature along the shape. consequently, extrema of the curvature are pairwise connected via a symmetry set branch with a certain finite length. the novel shape descriptor is given by a string representing these extrema, together with the pair wise connections and a length measure. next, an algorithm is given to match strings. this algorithm is based on a modified shortest path algorithm, taking into account the allowed changes of the symmetry set. examples show the usability of the presented theory, applied to different types of shapes, including noise and occlusions.
video clip recognition using joint audio-visual processing model. the automatic recognition of video clips is an important capability with applications in broadcast monitoring for content theft and adherence to advertisement campaign. in this paper, we present an approach for video clip recognition based on hmm and gmm for modeling video and audio streams respectively. the approach is used to model tv commercials. the recognition results of using single stream and joint models are compared. the error rate of 0.01% is achieved when the joint audio-visual processing model is employed.
visual servoing in presence of non-rigid motion. most robotic vision algorithms have been proposed by envisaging robots operating in industrial environments, where the world is assumed to be static and rigid. these algorithms cannot be used in environments where the assumption of a rigid world does not hold. in this paper, we study the problem of visual servoing in presence of nonrigid objects and analyze the design of servoing strategies needed to perform optimally even in unconventional environments. we also propose a servoing algorithm that is robust to non-rigidity. the algorithm extracts invariant features of the non-rigid object and uses these features in the servoing process. we validate the technique with experiments and demonstrate the applicability.
combining fingerprint, palmprint and hand-shape for user authentication. this paper investigates a new approach for personal authentication by combining unique biometric features which can be acquired from hand images alone. the proposed method attempts to improve the performance of fingerprint-based verification system by integrating palmprint and hand-shape features. the matching scores for the fingerprint images are computed using the number of matched minutiae on the overlapping areas while those for palmprint and hand-shape images are based on distance of feature vectors. these matching scores are combined using simple fusion rule which does not require any training. our experimental results on the database of 100 users achieve promising results and therefore confirm the usefulness of proposed method.
multiscale fourier descriptor for shape-based image retrieval. the shapes occurring in the images are important in the content-based image retrieval. in this paper we introduce a new fourier-based descriptor for the characterization of the shapes for retrieval purposes. this descriptor combines the benefits of the wavelet transform and fourier transform. this way the fourier descriptors can be presented in multiple scales, which improves the shape retrieval accuracy of the commonly used fourier-descriptors. the multiscale fourier descriptor is formed by applying the complex wavelet transform to the boundary function of an object extracted from an image. after that, the fourier transform is applied to the wavelet coefficients in multiple scales. this way the multiscale shape representation can be expressed in a rotation invariant form. the retrieval efficiency of this multiscale fourier descriptor is compared to an ordinary fourier descriptor and css-shape representation.
embodied proactive human interface "pico-2". we are conducting research on "embodied proactive human interface". the aim of this research is to develop a new human-friendly active interface based on two key technologies, an estimation mechanism of human intention for supporting natural communication named "proactive interface", and a tangible device using robot technology. this paper introduces the humanoid-type two-legged robot named "pico-2", which was developed as a tangible telecommunication device for the proactive human interface. in order to achieve the embodied telecommunication with pico-2, we propose new tracking technique of human gestures using a monocular video camera mounted on pico-2, and natural gesture reproduction by pico-2 which absorbs the difference of body structure between the user and the robot.
a neural network classifier for occluded images. this paper proposes a neural network classifier which can automatically detect the occluded regions in the given image and replace that regions with the estimated values. an auto-associative memory is used to detect outliers such as pixels in the occluded regions. certainties of each pixels are estimated by comparing the input pixels with the outputs of the auto-associative memory. the input values to the associative memory are replaced with the new values which are defined depending on the certainties. by repeating this process, we can get an image in which the pixel values of the occluded regions are replaced with the estimates. the proposed classifier is designed by integrating this associative memory with a simple classifier.
a robust audio searching method for cellular-phone-based music information retrieval. we propose a search method for detecting a query audio signal fragment in long audio recordings. the query signal is assumed to be captured by a portable terminal, such as a cellular phone, in the real world. a major problem in this kind of search is that the features of the query sound may include distortions due to terminal characteristics or environment noise. the method proposed here comprises local time-frequency-region normalization and robust sub-space spanning. the former is used to make features invariant to additive noise and frequency characteristics, and the latter to choose frequency bands that minimize the effect offeature distortions. experiments using cellular phones in the real world show the proposed method is effective.
kanji recognition in scene images without detection of text fields - robust against variation of viewpoint, contrast, and background texture. with the goal of indexing scene images, we propose a novel recognition method for kanji characters captured in scene images. our method scans multi-resolution images and classifies clipped regions with recognition dictionaries generated by learning a large amount of partial patterns of characters with large geometric transformation. the problem of scanning time, which tends to be impractically long, is solved by using multi-compression coarse-to-fine scanning, and by detecting peak points after coarse searching. despite the wrong results generated in the background, our method well supports image retrieval since it uses the regular spacing of characters. experimental results show that this recognition method recognized characters at the rate of 82%. precision was 84% and recall was 64% for image retrieval.
planar shape recognition across multiple views. multiview studies in computer vision have concentrated on the constraints satisfied by individual primitives such as points and lines. not much attention has been paid to the properties of a collection of primitives in multiple views, which could be studied in the spatial domain or in an appropriate transform domain. we derive an algebraic constraint for planar shape recognition across multiple views based on the rank of a matrix of fourier domain descriptor coefficients of the shape in different views. we also show how correspondence between points on the boundary can be computed for matching shapes using the phase of a measure for recognition.
structure relaxation method for self-organizing neural networks. self-organizing neural networks achieve more predictable and accurate results then the classic ones with the static architecture.neurons and connections of such neural networks are dynamically built during the learning process.self-organizing neural networks based on the group method of data handling (gmdh) have proven to be one of the most efficient approaches to solving the problems of pattern recognition with the statistical learning data.in this article we propose a new method for searching deeper interrelations of the inputs and the output of the system under the study of such a neural network.the method allows eliminating links to the inputs that are no longer useful at the later steps of the neural network construction, thus allowing to simplify the neural network structure and increase prediction accuracy.hence the method is called the structure relaxation method.for complex problems the method helps to find deeper system inputs interrelations, increase the prediction accuracy, and, at the same time, decrease the number of the inputs being used.the proposed relaxation method was tested on the real world problems; the results are also presented herein.
hangul tree classifier for type clustering using horizontal and vertical strokes. hangul is clustered into six different types in general. type clustering has an effect of coarse classification in syllable matching and becomes the pre-processing stage for the segmentation in the grapheme matching process. in this paper, we define a set of grapheme region of a preconsonants, vowel and post-consonant, that can absorb the change of the character's shape and the noise. a method for extracting the main stroke of the horizontal vowel and vertical vowel that appear in the region is proposed in this paper.
optimum block size detection for image quality measure. this paper deals with the quality of the image itself as well as the algorithm used for evaluating the quality of the fingerprints to construct an effective algorithm for evaluating the quality of the fingerprints. the quality of the fingerprint is acquired by taking the regional quality of each fingerprint image. the amount of fingerprint varies according to the size of each block which makes the result unsteady. we concentrated on finding the right size for the block used to acquire the fingerprint image. also, the quality distribution included in the fingerprint image was acquired when the optimal block size was adopted.
fingerprint matching method using minutiae clustering and warping. solving non-linear distortion problems in fingerprint matching is important and still remains as a challenging topic. we have developed a new fingerprint matching method to deal with non-linear distortion problems efficiently by clustering locally matched minutiae and warping the fingerprint surface using minutiae clusters. specifically, local invariant structures encoding the neighborhood information of each minutia are utilized in clustering the matched minutiae and then the fingerprint surface is warped to describe the deformation pattern properly. finally, to make an additional increase in performance, the overlapped region of two fingerprints is considered in the score computation stage. experimental results show that the proposed algorithm is performed best compared with other ones.
local variance driven self-organization for unsupervised clustering. we propose a new, novel unsupervised clustering technique based on traditional kohonen self organization, competitive hebbian learning (chl), and the hebbian based maximum eigenfilter (hme). this method fits into the family of dynamic selfgenerating, self-organizing map (som) algorithms. the approach uses a vigilance based, global parsing strategy as a guide for the hierarchical partitioning of an underlying data distribution into a set of dominant prototypes: each consisting of a dual memory element for the online estimation of both position and maximal local variance. a co-operative scheme exploits the interplay between global vigilance and maximal local variance such that an informed choice may be made regarding insertion sites for new nodes into the map. the network is related to self-organizing tree maps (sotm), growing neural gas (gng) and their variants. a framework is presented and performance demonstrated against gng.
scheduling of image processing using anytime algorithm for real-time system. this paper proposes an adaptive scheduling method using anytime algorithm under such a condition that the processing time is restricted or is not enough. by using typical image processing procedure as an example, this paper discusses how to modify conventional image processing algorithms to anytime algorithmic image processing, modeling of timeprecision function and an adaptive scheduling method to realize the maximum performance in the restricted time.
contact lens extraction by using thermo-vision. the surface of the eye is always covered with water, and if he/she opens his/her eyes, the temperature gradually falls because of the evaporation of water. the transition of the temperature differs whether he/she wears contact lenses or not, and furthermore, there exists some differences between soft and hard lenses. basing on these properties, this paper proposes a system to extract and distinguish contact lenses by using a thermo-vision camera. some experimental results show about 72% success and this means the possibility to apply this basic method to the preprocessing of biometrics.
resolution independent deformable model. in this paper we propose a parametric deformable model that automatically adapts its topology and that recovers accurately image components with a complexity independent from the resolution of the input image. the main idea is to equip the image space with a metric that expands interesting features in the image depending on their geometry.
using specularities to recover multiple light sources in the presence of texture. recovering multiple point light sources from a sparse set of photographs in which objects of unknown texture can move is challenging. this is because both diffuse and specular reflections appear to slide across surfaces. what is seldom demonstrated, however, is that it can be taken advantage of to address the light-source recovery problem. in this paper, we therefore show that, if 3d models of the moving objects are available or can be computed from the images, we can solve the problem without any a priori constraints on the number of sources, on their color, or on the surface albedos. our approach involves finding local maxima in individual images, checking them for consistency across images, retaining the apparently specular ones, and having them vote in a hough-like scheme for potential light source directions. the precise directions of the sources and their relative power are then obtained by optimizing a standard lighting model. as a byproduct we also obtain an estimate of various material parameters such as the unlighted texture and specular properties. we show that the resulting algorithm can operate in presence of arbitrary textures and an unknown number of light sources of possibly different unknown colors. we also estimate its accuracy using ground-truth data.
a shape-preserving non-parametric symmetry transform. recently, a non-parametric image measure, symmetry, for local binary patterns has been introduced. in this paper, we propose a generalised symmetry transform for arbitrary neighbourhoods and describe its theoretical properties. the symmetry of the local binary patterns is shown to be a special case of a more general non-parametric concept. applications of the symmetry include searching of interest points and correspondence.
successive-least-squares error algorithm on minimum description length neural networks for time series prediction. a successive least-squares approach is proposed to find an optimal model of a flat neural network in a short period of time. it is based on a minimum description length (mdl) neural network that uses the mdl principle as the stopping criterion. different from conventional algorithms on flat neural networks that apply least-squares technique on weights between hidden layer and output layer only, it extends the least-squares technique to weights between the input layer and the hidden layer. we apply this algorithm to the chaotic mackey-glass time series and chaotic laser time series. the results show that it provides satisfactory prediction within a small amount of time.
using extended em to segment planar structures in 3d. the proposed algorithm segments planar structures out of data gained from 3d laser range scanners, typically used in robotics. the approach first fits planar patches to the dataset, using a new, extended expectation maximization (em) algorithm. this algorithm solves the classical em problems of insufficient initialization by iteratively determining the number and positions of patches in a split and merge framework. determining the fitting quality of the gained patches, the approach then allows for segmentation of planar surfaces out of the 3d environment. the result is a set of 2d objects, which can be used as input for classical computer vision applications, in particular for object recognition. our approach makes it possible to apply classical tools of 2d image processing to solve problems of 3d robot mapping, e.g. landmark recognition.
registration and fusion of retinal images: a comparative study. we present a new method to register high and low resolution color images of the retina as well as high resolution angiographies. the registration method is based on global point mapping with blood vessel bifurcations as control points. we also present results of various image fusion algorithms to determine the most appropriate one. registration and fusion quality assessment is also discussed.
human identification by using the motion and static characteristic of gait. in this paper, we propose a gait recognition algorithm that fuses motion and static spatio-temporal templates of sequences of silhouette images, the motion silhouette contour templates (mscts) and static silhouette templates (ssts). the performance of the proposed algorithm is evaluated experimentally using the soton dataset and the usf dataset. the proposed algorithm has a recognition rate of around 80% in intrinsic difference group (probe a-c) of usf dataset which is 14% higher than the baseline algorithm.
improved clustering algorithm based on calculus of variation. a major problem in data clustering is the degradation in performance due to outliers. we have developed a robust method to solve this problem using the l2m-fcm algorithm. however, this method has to solve a non-linear equation and can converge to a local optimum. in this paper, we introduce a regularized version of the l2m-fcm algorithm. the essential idea is to constrain the descent direction in the optimization procedure. we employ a novel method to correct the direction using the calculus of variations. experimental results show that the proposed method has a better performance than seven other clustering algorithms for both synthetic and real world data sets.
background subtraction using competing models in the block-dct domain. many image analysis applications rely on background subtraction as a pre-processing step. hence it should be efficient and robust. we present a background subtraction algorithm that uses multiple competing hidden-markov-models (hmms) over small neighbourhoods to maintain a locally valid background model in all situations. we use the dct coefficients of jpeg encoded images directly to minimize computation and to use local information in a principled way. region level processing is reduced to the minimum so that the extracted information that goes to higher level processing is unbiased.
atlas-based 3d-shape reconstruction from x-ray images. in many cases x-ray images are the only basis for surgery planning. nevertheless it is desirable to draw conclusions about the 3d-anatomy of the patient from such data. this work presents a method to reconstruct 3d shapes from few digital x-ray images on the basis of 3d-statistical shape models. at the core of this method lies an algorithm which optimizes a similarity measure assessing the difference between projections of the shape model and the x-ray images. based on theoretical and experimental observations we propose to measure the distance between the silhouettes of the object in the projections. the method is tested on 23 synthetically generated x-rays from ct data sets of the the geometrically as well as topologically complex shape of the pelvic bone.
machine learning for video compression: macroblock mode decision. video compression currently is dominated by engineering and fine-tuned heuristic methods. in this paper, we propose to instead apply the well-developed machinery of machine learning in order to support the optimization of existing video encoders and the creation of new ones. exemplarily, we show how by machine learning we can improve one encoding step that is crucial for the performance of all current video standards: macroblock mode decision. by formulating the problem in a bayesian setup, we show that macroblock mode decision can be reduced to a classification problem with a cost function for misclassification that is sample dependent. we demonstrate how to apply different machine learning techniques to obtain suitable classifiers and we show in detailed experiments that all of these perform better than the state-of-the-art heuristic method.
multi-level anchorperson detection using multimodal association. in contemporary tv news programs, multi-level anchorpersons are often used which indicate the inherent hierarchical structure of news program. however, these diverse anchorperson patterns make the conventional anchorperson detection algorithms failed. in this paper, we propose a robust approach to anchorperson detection by integrating visual modality, auditory modality and human appearance modality into multimodal associated clustering. based on the structure of clustered multi-level anchorpersons, the toc (table-of-content) of news video can be effectively generated. the effectiveness and robustness of the proposed approach are demonstrated by the experiments on five hours news programs fromz different tv channels.
precision-recall operating characteristic (p-roc) curves in imprecise environments. traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. in this paper, we consider the case of imprecise environments, where little may be known about these factors and they may well vary significantly when the system is applied. specifically, the use of precision-recall analysis is investigated and compared to the more well known performance measures such as error-rate and the receiver operating characteristic (roc). we argue that while roc analysis is invariant to variations in class priors, this invariance in fact hides an important factor of the evaluation in imprecise environments. therefore, we develop a generalised precision-recall analysis methodology in which variation due to prior class probabilities is incorporated into a multi-way analysis of variance (anova). the increased sensitivity and reliability of this approach is demonstrated in a remote sensing application.
tree-like data structures for effective recognition of 2-d solids. an approach to extracting and recognizing the patterns given by the solids in two-level images is developed.the applied data processing and analyzing procedures are based on using the tree-structured representations of both the whole image and the individual patterns.these representations provide a significant reduction of calculations at the stages of pattern segmentation and recognition.the estimations of the fidelity and computational complexity performances have been obtained for the recognition procedure based on source coding and sequential decoding schemes.
active feature models. in this paper active feature models are proposed. they utilize local texture features and a statistical shape model for the reliable localization of landmarks in images. they are related to active appearance models, but instead of modelling the entire texture of an object they represent image texture by means of local descriptors. the approach has advantages with complex image data like anatomical structures that exhibit high texture variation with limited relevance for the recognition of the object location. experimental results and the comparison to aams on different data sets indicate that active feature models can improve search speed and result accuracy, considerably.
building and registering parameterized 3d models of vessel trees for visualization during intervention. in this paper we address the problem of multimodal registration of coronary vessels by developing a 3d parametrical model of vessel trees from computer tomography data and registering it to angiography images during intervention. thus, the interventionist takes profit from 3d data otherwise only available before the intervention. this facilitates orientation in ambiguous radiographs, interactive visualization of all vessel structures to estimate their mutual position and navigation within the vessel system and ultimately reduces the radiation the patient and the physicians are exposed to. the model is build by exploring the branching vessel tree starting from a single position and successively expanding through the vessels guided by a local deformable surface. the result is a tree of cylindrical segments each adapted to the vessel walls that is registered to angiography images in a fast and robust way. validation on 8 patients confirms the robustness of our method.
gender recognition in non controlled environments. in most of the automatic face classification applications, images should be captured in natural environments, where partial occlusions or high local changes in the illumination are frequent. for this reason, face classification tasks in uncontrolled environment are still nowadays unsolved problems, given that the loss of information caused by these artifacts can easily mislead any classifier. we present in this paper a system to extract robust face features that can be applied to encode information from any zone of the face and that can be used for different face classification problems. to test this method we include the results obtained in different gender classification experiments, considering controlled and uncontrolled environments and extracting face features from internal and external face zones. the obtained rates show, on the one hand, that we can obtain significant information applying the presented feature extraction scheme and, on the other hand, that the external face zone can contribute useful information for classification purposes.
a fast discriminant approach to active object recognition and pose estimation. this paper presents a new criterion for viewpoint selection in the context of active bayesian object recognition and pose estimation. recognition is performed by probabilistically fusing successive observations with the current belief state of the system. based on the current belief state, the next viewpoint is chosen to maximize the expected discriminability of the current competing hypotheses. experiments on a difficult database of aircraft models show that this approach achieves comparable recognition performance to the widely used information theoretic approaches at a much lower computational cost.
velocity adaptation of space-time interest points. the notion of local features in space-time has recently been proposed to capture and describe local events in video. when computing space-time descriptors, however, the result may strongly depend on the relative motion between the object and the camera. to compensate for this variation, we present a method that automatically adapts the features to the local velocity of the image pattern and, hence, results in a video representation that is stable with respect to different amounts of camera motion. experimentally we show that the use of velocity adaptation substantially increases the repeatability of interest points as well as the stability of their associated descriptors. moreover, for an application to human action recognition we demonstrate how velocity-adapted features enable recognition of human actions in situations with unknown camera motion and complex, non-stationary backgrounds.
object tracking with dynamic template update and occlusion detec. the objective of this paper is to track moving objects using dynamic template initializations and updates, and to identify tracking events in videos such as occlusions and merging of motion regions. the proposed tracking method is based on spatiotemporal texture motion regions, image alignment, and minimum cost estimation based template selection. the dynamic template update is based on the detection of events in videos. the proposed method has been experimentally evaluated on color and thermal infrared videos.
stroke extraction and stroke sequence estimation on signatures. this article addresses the problem in strokes extraction and stroke sequence estimation from a static signature. a new algorithm is proposed based on a simple but effective writer model. the results are encouraging.
shape-based contour interpolation and extrapolation using distance mapping. we propose an approach to the problem of reconstruction of 3d surfaces from magnetic resonance (mr) images. we use shape-based contour interpolation and extrapolation algorithms implemented based on the active contour technique; our idea is to use distance mapping of feature points in order to model the active contour dynamics. we establish differential equations describing the active contour dynamics and set up an iterative procedure for numerical solution. the efficiency of approach is demonstrated on contours of liver and liver tumors in mr images.
local behaviours labelling for content based video copy detection. this paper presents an approach for indexing a large set of videos by considering the dynamic behaviour of local visual features along the sequences. the proposed concept is based on the extraction and the local description of interest points and further on the estimation of their trajectories along the video sequence. analysing the low-level description obtained allows to highlight trends of behaviour and then to assign a label. such an indexing approach of the video content has several interesting properties: the lowlevel descriptors provide a rich and compact description, while labels of behaviour provide a generic semantic description of the video content, relevant for video content retrieval. we demonstrate the effectiveness of this approach for content-based copy detection (cbcd) on large collections of videos (several hundred hours of videos).
learning integrated perception-based speed control. advances in the area of autonomous mobile robotics have allowed robots to explore vast and often unknown terrains. this paper presents a particular form of autonomy that allows a robot to autonomously control its speed, based on perception, while traveling on unknown terrain. the robot is equipped with an onboard camera and a 3-axis accelerometer. the method begins by classifying a query image of the terrain immediately before the robot. classification is based on the gabor wavelet features. in learning the speed, a genetic algorithm is used to map the gabor texture features to approximate speed that minimizes changes in accelerations along the three axes from their nominal values. learning is performed continuously. experiments are done in real time.
svm training time reduction using vector quantization. in this paper, we describe a new method for training svm on large data sets. vector quantization is applied to reduce a large data set by replacing examples by prototypes. training time for choosing optimal parameters is greatly reduced. some experimental results yields to demonstrate that this method can reduce training time by a factor of 100, while preserving classification rate. moreover this method allows to find a decision function with a low complexity when the training data set includes noisy or error examples.
3d hand reconstruction from a monocular view. in this paper, we describe an approach for human hand motion detection and its reconstruction using an articulated model with hand kinematics constraints. each finger can be modeled as planar robot arm with 3 joints and 3 links. we assume that first joints connecting palm and each finger configure a rigid form. by this simplification, we have several hand constraints which reduce the complexity of the estimation process and allow to infer the 3d hand motion and pose in ambiguous situations. the main advantage of the proposed approach is its ability to capture general articulated hand motion with self self-occlusion and rotation of the palm. the proposed method is illustrated on a set of examples of a hand motion captured from a monocular image sequence.
a robust fingerprint matching algorithm using local alignment. this paper describes a minutiae-based fingerprint matchig algorithm. geerally, a figerprit image is non-linearly deformed by torsion and traction when a finger is pressed on the sensor. this nonlinear deformation changes both position and orientation of minutiae and decreases thereliability o f minutiae. therefore, in matching algorithm using one referece minutiae pair, the reliability of a minutia decreases as the distance from the minutia to the minutia used for alignment increases. the proposed algorithm over-comes this problem by normalizing the distance between minutiae and using local alignment. experimental results show that the performace of the proposed algorithm is superior to that of using one referece minutiae pair.
extraction and recognition of license plates of motorcycles and vehicles on highways. in this paper, a recognition system is proposed to extract and recognize license plates of motorcycles and vehicles on highways. in the first stage, a block-difference method is used to detect moving objects. according to the variance and the similarity of the mxn blocks defined on two diagonal lines, the blocks are categorized as three kinds: low-contrast, stationary and moving blocks. in the second stage, a screening method based on the projection of edge magnitudes is used to find two peaks in the projection histograms to bound license plates. the scanning lines with low counts can be removed. in the third stage, character images are segmented and recognized. in our experiments, we tested 180 pairs of images. the block-difference method has a 98% success rate and can remove 88% of pixels from an image on average. the screening method has a 94.4% success rate and the character recognition method has a 95.7% precision rate.
nonlinear shape and appearance models for facial expression analysis and synthesis. facial expression passes through nonlinear shape and appearance deformations with variations in different people and expressions. we present nonlinear shape and appearance models for facial expression analysis and synthesis using nonlinear generative models for different facial expressions in different people. to achieve accurate shape normalized appearance models, we utilize nonlinear warping using thin plate spline (tps). a novel nonlinear generative model using conceptual manifold embedding and empirical kernel maps for facial expressions provides facial shape and appearance samples according to the configuration, personal style, and expression parameters. we can recognize facial expressions based on estimated facial expression parameters after iterative estimations of facial expression and style. in addition, the model provides accurate synthesis of facial expression sequences even with high nonlinear deformations of shape and appearance during facial expressions.
simultaneous inference of view and body pose using torus manifolds. inferring 3d body pose as well as viewpoint from a single silhouette image is a challenging problem. we present a new generative model to represent shape deformations according to view and body configuration changes on a two dimensional manifold. we model the two continuous states by a product space (different configurations × different views) embedded on a conceptual two dimensional torus manifold. we learn a nonlinear mapping between torus manifold embedding and visual input (silhouettes) using empirical kernel mapping. since every view and body pose has a corresponding embedding point on the torus manifold, inferring view and body pose from a given image becomes estimating the embedding point from a given input. as the shape varies in different people even in the same view and body pose, we extend our model to be adaptive to different people by decomposing person dependent style factors. experimental results with real data as well as synthetic data show simultaneous estimation of view and body configuration from given silhouettes from unknown people.
an adaptive icp registration for facial point data. an algorithm for finding coupling points plays an important role in the iterative closest point algorithm (icp) which is widely used in medical imaging and 3-d architecture applications. in recent researches of finding coupling points, approximate k-d tree search algorithm (ak-d tree) is an efficient nearest neighbor search algorithm with comparable results. we proposed adaptive dual ak-d tree search algorithm (adak-d tree) for searching and synthesizing coupling points as significant control points to improve the registration accuracy in icp registration applications. adak-d tree utilizes ak-d tree twice in different geometrical projection orders to reserve true nearest neighbor points used in later icp stages. an adaptive threshold in adak-d tree is used to reserve sufficient coupling points for a smaller alignment error. experimental results are shown that the registration accuracy of using adak-d tree is improved than of using ak-d tree and the computation time is acceptable. we also design a system gui based on the proposed algorithm to register the facial point data which are extracted from prestore ct imaging and captured via range scan equipments or a 3-d digitizer.
automated detection of solar loops by the oriented connectivity method. an automated technique to segment solar coronal loops from intensity images of the sun's corona is introduced. it exploits physical characteristics of the solar magnetic field to enable robust extraction from noisy images. the technique is a constructive curve detection approach, constrained by collections of estimates of the magnetic field's orientation. its effectiveness is evaluated through experiments on synthetic and real coronal images.
robust vehicle detection based on shadow classification. the multi-level shadow classification has been shown to provide reliable information on the presence of vehicles in traffic scenes. the method is based on classifying the shadow shapes into six categories at each threshold level. non-overlapping shadow shapes with higher priority are selected at each level. shadow-reshaping capability makes the resulting shadow information robust to the variation of operating conditions. unlike other approaches, vehicle movement information between frames is not utilized; thereby the traffic parameters can be measured quantitatively even when the vehicle movement is not observed. also the detecting performance is not affected by the abrupt change of weather because background information is not utilized.
face reconstruction with low resolution facial images by feature vector projection in kernel space. in spite of increasing interest in person identification based on biometrics, face recognition technology has not been applied into real world. it is caused by appearance changes such as illumination, noise, degradation, and occlusion. among these problems, we focus on the low resolution problem and propose a new face recognition method of extending the svdd(support vector data description). in the proposed method, we first solve the svdd problem for the data belonging to the given prototype facial images, and model the data region for the normal faces as the ball resulting from the svdd problem. next, for each input facial image in low resolution, we project its feature vector onto the decision boundary of the svdd ball so that it can be tailored enough to belong to the normal region. finally, we synthesize facial images which are obtained from the preimage of the projection, and then perform the face recognition. the applicability of the proposed method is illustrated via some experiments using general recognition algorithm.
fusion of chaotic measure into a new hybrid face-gait system for human recognition. in this paper we describe a method to recognize people using face and gait features in a novel yet natural way, using a single camera. we show that frontal-normal motion analysis yields more dynamic information as compared to fronto-parallel motion and allows us to analyse gait in a new way, using nonlinear dynamics of time series normally used in chaos theory. a set of point light sources attached to various points of a walking person allows the walker to be identified. phase-space analysis of trajectories of these moving light displays (mlds) provides sufficient information for identification of people by their gait. using chaotic measures to identify humans by their gait is a significant precedent. to demonstrate the usefulness of this result, we perform face recognition in a nonideal environment and show that by augmenting with gait data, we get better recognition rates, providing a more robust identification scheme..
robust multiclass ensemble classifiers via symmetric functions. we introduce a generalization to the multiclass framework of a previous approach to boosting by constructing symmetric functions. this approach contrasts with the usual adaboost-type boosting algorithms using linear separators. indeed, multiclass induction does not necessitate combination tricks such as those for linear separators, and it achieves some novel agnostic learning properties, as well as significant malicious noise tolerance. experiments on a large testbed against adaboost and c4.5 display the efficiency of the approach proned.
supervised image classification by som activity map comparison. this article presents a method aiming at quantifying the visual similarity between two images. this kind of problem is recurrent in many applications such as object recognition, image classification, etc. in this paper, we propose to use self-organizing feature maps (som) to measure image similarity. to reach this goal, we feed local signatures associated to salient patches into the neural network. at the end of the learning step, each neural unit is tuned to a particular local signature prototype. during the recognition step, each image presented to the network generates a neural map that can be represented by an activity histogram. image similarity is then computed by a quadratic distance between histograms. this scheme offers very promising results for image classification with a percentage of 84.47% of correct classification rates.
a two level classifier process for audio segmentation. we are dealing in this paper with audio segmentation. we propose a two level segmentation process that enables the audio tracks to be sampled in short sequences which are classified into several classes. the segmentation is performed by computing several features for each audio sequence. these features are computed either on a complete audio segment or on a frame (set of samples) which is a subset of the audio segment. the proposed approach formicrosegmentation of audio data consists of a combination of a k-means classifier at the segment level and of a multidimensional hidden markov model system using the frame decomposition of the signal. a fir st classification is obtained using the k-means classifier and segment-based features. then final result comes from the use of multi-dimensional hidden markov models and frame-based features involving temporary results. multidimensional hidden markov models are an extension of classical hidden markov model dedicated to multicomponents data. they are particularly adapted in our case where each audio segmentcan be characterized by several features of different nature.
adaboost tracker embedded in adaptive particle filtering. due to computational simplicity, low-level visual cues (such as color, contour and corner) have been widely integrated into various visual trackers. however, the robustness of these trackers will be challenged by cluttered backgrounds, partial occlusion and varying illuminations. in many applications, the classes of the interested objects to be tracked are usually known in advance. hence, high-level information from trained classifiers can be fused into the visual tracker to overcome the above limitations. in this paper, a novel approach is proposed to integrate all weak and strong classifiers of the trained adaboost cascade into the observation model of sampled particles in particle filtering. furthermore, in order to track objects undergoing non-stationary movement, decisions of the whole boosted cascade on all sampled particles are incorporated to adapt the proposal distribution of sampling for better approximation of the desired posterior distribution. experimental results on tracking different objects over indoor and outdoor video sequences have shown the proposed tracker is able to effectively handle rapid movements, partial occlusion, varying illuminations, and large changes of scale and viewpoint.
an ubm-based reference space for speaker recognition. the universal background model represents the speaker independent distribution of features, so it can be used to construct a reference space for speaker recognition. in the anchor models, one speaker utterance can be located at one point in the anchor space. we construct the reference space using the gaussian distributions in the universal background model instead of the virtual speakers in the anchor models, and one speaker's all utterances mainly locate in a small portion of the whole space. on the other hand, we use the support vector machine to separate this speaker dependent portion from the whole space while the euclidean distance measure is used in the anchor models in general. the experiments on the yoho database show that our method can get better performance comparing with the decision fashion based on the euclidean distance which is widely used in the anchor models.
efficient gaussian mixture for speech recognition. this article presents a clustering algorithm to determine the optimal number of components in a gaussian mixture. the principle is to start from an important number of mixture components then group the multivariate normal distributions into clusters using the divergence, a weighted symmetric, distortion measure based on the kullback-leibler distance. the optimal cut in the tree, i.e. the clustering, satisfies criteria based on either the minimum amount of available training data or dissimilarities between clusters. the performance of this algorithm is compared favorably against a reference system and a likelihood loss based clustering system. the tree cutting criteria are also discussed. about an hour of ester, a french broadcast news database is used for the recognition experiments. performance are significantly improved and the word error rate decreases by about 4.8%, where the confidence interval is 1%.
experiments on eigenfaces robustness. this paper is an experimental study on the robustness of the eigenfaces method for face recognition. to build a face recognition system, especially in an unconstrained surveillance system where a clear, direct, and normalized view of the face cannot be assumed, one needs to implement several image preprocessing steps like segmentation, deskewing, zooming, rotation, warping, etc., before processing the face image per se. our aim is to determine how efficient these preprocessing steps must be in order to apply the eigenfaces method with success. the experiments are conducted on a subset of the ar-face color image database.real images are used and altered synthetically to study the effects of 7 parameters that can be translated into corresponding preprocessing artifacts: horizontal and vertical translations, downsampling, zooming, rotation, morphing and lighting.
recognition of non-negative patterns. principal component analysis (pca) is one of the most important and popular tools used to recognize and compress patterns. the principal components are the basis functions that minimize the mean-squared error and they can be used as matched filters. in many pca applications it has been observed that the eigenvector with the largest eigen-value has only non-negative entries when the vectors of the underlying stochastic process have only non-negative values. this has been used to show that the coordinate vectors in pca are all located in a cone. this in turn can be used to construct invariants, for tracking or compression (see [estimation of illumination characteristics, two stage principal component analysis of color]). in this paper we will show how this empirical observation can be rigourously proved. for the case of patterns described by vectors we use the perron-frobenius theory of non-negative matrices to investigate stochastic processes of finite-dimensional patterns that assume only non-negative function values. we will show that they always have a first eigenfunction that assumes only non-negative values. we will also describe the conditions under which the first eigenfunction has strictly positive values. for stochastic processes of patterns in hilbert (or banach) spaces we will use versions of the krein-rutman theory to prove the non-negativity of the first eigenfunction. in contrast to the finite-dimensional case we will see that this formulation gives a more direct connection to the conical structure of the underlying pattern space. as a concrete example we will sketch how these results can be used in multi-spectral color processing.
lie methods in color signal processing: illumination effects. in this paper we describe illumination changes with the help of elements in the lorentz group su(1,1). we show how lie-theoretical methods can be applied to solve problems related to illumination changes. we derive partial differential equations that describe the changes in the space of color signals. we show how these changes effect the induced variations in the space of rgb vectors. we illustrate the application of these methods with two examples: in the first example we derive a simple linear equation system that links the pointwise pixel changes to the parameters of the illumination change. in the second example we construct operators in the rgb space that either compensate illumination changes or predict the effects of illumination changes.
complex human activity recognition for monitoring wide outdoor environments. the problem of automatic recognition of human activities is among the most important and challenging open areas of research in computer vision. this paper presents a new approach to automatically recognize complex human activities embedded in video sequences acquired with a large scale view in order to monitoring wide area (car parking, archeological site. etc) with a single static camera. the recognition process is performed in two steps: at first the human body posture isestimated frame by frame and then the temporal sequences of the detected postures are statistically modeled. body postures are estimated starting from the binary shapes associatedto humans, selecting as features the horizontal and vertical histograms and supplying them as input to an unsupervised clustering algorithm. the manhattan distance is used for both clusters building and run-time classification. statistical modeling of the detected postures is performed by discrete hiddenmarkov models. the system has been tested on image sequences acquired in an outdoor archaeological site. four kinds of activities have been automatically classified with high percentage of right decisions.
continuous activity recognition with missing data. human activity recognition involves several problems like changes when an activity is performed by different persons. this means the people can perform the same activity faster or slower and also the way that an activity is performed can change, therefore we can have different trajectories representing the same activity. another problem exists when we do not have the whole trajectory because of occlusion or noise. in this work, an approach for human activity recognition based on the fourier transform and bayesian networks is presented. this approach can recognize activities performed at different velocities by different people and can work with missing data. it performs continuous activity recognition without the necessity of manually indicating when the activity starts or finishes.
non-overlapping distributed tracking using particle filter. tracking people or objects across multiple cameras is a challenging research area in visual computing especially when these cameras have non-overlapping field-of-views. the important task is to associate a target of interest with its previous appearances across time and space within the camera network. in this paper, we propose a unified tracking framework using particle filter to efficiently switch between track prediction (to deal with non-overlapping region tracking) and visual tracking. the particle filter tracking system uses a map to provide the possible trajectory information of the target as it moves within the non-overlapping regions. we implemented and tested this tracking approach in an in-house multiple cameras system. promising results were obtained which suggested the feasibility of such an approach.
linear and non-linear geometric object matching with implicit representation. this paper deals with the matching of geometric objects including points, curves, surfaces, and subvolumes using implicit object representations in both linear and non-linear settings. this framework can be applied to feature-based non-linear image warping in biomedical imaging with the deformation constrained to be one-to-one, onto, and diffeomorphic. moreover, a theoretical connection is established between the well known hausdorff metric and the framework proposed in this paper. a general strategy for matching geometric objects in both 2d and 3d is discussed. the corresponding euler-lagrange equations are presented and gradient descent method is employed to solve the time dependent partial differential equations.
learning bayesian networks for cytogenetic image classification. we experimentally learn structures of bayesian networks classifying signals enabling genetic abnormality diagnosis. structures learned based on the naive bayesian classifier, expert knowledge or using the k2 algorithm are compared. inferiority of the k2-based classifier has motivated an investigation of the algorithm initial ordering, search procedure and metric. replacing the k2 search with hill-climbing search improves accuracy as does the inclusion of hidden variables into the structure. however, it is proved experimentally that this inferiority of the k2-based classifier is mainly due to the k2 metric soliciting structures having enhanced representability but limited classification accuracy.
image classification for genetic diagnosis using fuzzy artmap. we investigate the fuzzy artmap (fa) in off and online image classification for diagnosis of genetic abnormalities. we evaluate the classification task (detecting abnormalities separately or simultaneously), classifier paradigm (monolithic or hierarchical), ordering strategy (averaging or voting), training mode (for one epoch, with validation or until completion) and sensitivity to parameters. we find the fa accurate in achieving the tasks requiring only few training epochs. superiority is found for the voting strategy and training until completion mode. compared to other classifiers, the fa does not loose but gain accuracy when overtrained. its accuracy is comparable with those of the multi-layer perceptron and support vector machine and superior to those of the naive bayesian and linear classifiers.
texture and profile features for drawing media recognition in underdrawings. in this study we analyze texture and profile features of painted strokes in order to identify the drawing media used for sketching underdrawings. underdrawings are preliminary drawings on the panel prepared for paintings and are unseen in the finished work. cameras working in the near infrared range allow the visualization of underdrawings. due to the tiny width of the strokes we perform an alignment of the feature extraction windows in order to obtain a major content of the stroke texture. the method is tested on strokes applied on test panels and underdrawing strokes in ir images of medieval paintings.
selecting vantage objects for similarity indexing. to make similarity searching in multimedia databases practical, indexing has become a necessity. vantage indexing is an indexing technique which maps a dissimilarity space onto a vector space such that each object is represented by a vector of dissimilarities to a small set of m reference objects, the vantage objects. querying takes place within this vector space, reducing the number of distance calculations to m. the retrieval performance of a system based on this technique can be improved significantly through a proper choice of vantage objects. we propose a new technique for selecting vantage objects and present experimental results based on data sets of different modality.
an energy minimisation approach to stereo-temporal dense reconstruction. we propose a novel energy minimisation framework for the dense reconstruction of stereo image sequences that incorporates data delity as well as spatial and temporal regularity. an iterated dynamic programming scheme is proposed to minimise the energy function. we also present an efficient implementation of the minimisation scheme by introducing morphological decomposition techniques to solve the dynamic programming subproblem. our proposed method is capable of reconstructing dynamic scenes with complex motion. results are presented demonstrating the strength of our proposed algorithm.
b-spline snakes in two stages. in using snake algorithms, the slow convergence speed is due to the large number of control points to be selected, as well as difficulties in setting the weighting factors that comprise the internal energies of the curve. even in using the b-spline snakes, splines cannot be fitted into the corner of the object completely. in this paper, a novel two-stage method based on b-spline snakes is proposed. it is superior both in accuracy and fast convergence speed over previous b-spline snakes. the first stage reduces the number of control points using potential function v(x,y) minimization. hence, it allows the spline to quickly approach the minimum energy state. the second stage is designed to refine the b-spline snakes based on the node points of the polynomials without knots. in other words, an elasticity spline is controlled by node points where knots are fixed. simulation and validation of results are presented. compared to the traditional b-spline snakes, better performance was achieved using the method proposed in this paper.
normalization of contrast in document images using generalized fuzzy operator with least square method. the visual effect of non-uniform contrast and brightness surrounds in the image is a very common problem in the applications of photocopying, ic manufacture and medicine. in using the digital/ccd camera to capture documents and photos based on non-uniform illumination condition, the poor image will be seen. the poor image can result in achieving the inaccurate reading from the optical character recognition (ocr) system. this paper present a new approach to normalize the local contrast in documentation based on the least square method and also enhance the object of interest using generalized fuzzy operator (gfo). two typical examples are used for evaluating the method.
ica-fx features for classification of singing voice and instrumental sound. this paper describes a new approach in locating the segments of singing voice in pop musical songs. initially, glr distance measure is employed to temporally detect the boundaries of singing voices and instrumental sounds. ica-fx is then adopted to extract the independent components of acoustic features for svm classification. experimental results indicate that ica-fx can improve the classification performance by significantly reducing the independent components that are not related to class label information.
sparse scene structure recovery from atmospheric degradation. scene structure can be recovered from images taken under different visibility conditions. we propose a new method using derivatives of images in order to accomplish this. two images of the same scene are needed, each acquired from the same viewpoint under different conditions of visibility. our approach was tested with images of both virtual and real scenes and results confirm its validity.
component analysis of torah code phrases. in this paper, we develop a new tool, called component analysis (ca), to study the significance of long torah code phrases. ca quantifies the relevance of such a phrase, by comparing its components (sub-phrases) to randomly constructed competitor phrases. in the process, we gain insight into how highly unusual it is to discover focused relevance among these randomly constructed competitors. under the null hypothesis of no torah codes, we would therefore not expect to find focused relevance in the torah code phrases, but our experience suggests otherwise, as reflected in the highly significant example studied here. ca lends itself well to being duplicated and verified by others, even those unfamiliar with hebrew.
serialized unsupervised classifier for adaptative color image segmentation: application to digitized ancient manuscripts. this paper presents an adaptative algorithm for the segmentation of color images suited for document image analysis. the algorithm is based on a serialization of the k-means algorithm that is applied sequentially by using a sliding window over the image. the algorithm reuses information about the clusters computed by the previous classification and automatically adjusts the clusters during the windows displacement in order to better adapt the classifier to any new local modification of the colors. for digitized documents, we propose to define several different clusters in the color feature space for the same logical class. we also reintroduce the user into the initialization step who must define the different samples of colors for each class and the number of classes. this algorithm has been tested successfully on ancient color manuscripts having heavy defects, showing lighting variation and transparency. nevertheless, the proposed algorithm is generic enough to be applied on a large variety of images using other features for different purposes like color image segmentation as well as image binarization.
towards surface regularization via medial axis transitions. the reconstruction of objects from data in practical applications often leads to surfaces with small perturbations and other artifacts which make the detection of their ridges and generalized axes difficult. we propose an approach to smoothing small structures while preserving ridges which is based on the medial axis structure of the surface. the medial axis of the surface is organized as a graph structure and the closeness of the medial axis graph to points of instability (transitions) is used to identify those structures which are most likely due to perturbations. the removal of these structures is our approach to regularizing both the medial axis and the surface. this paper focuses on a subset of medial transitions arising from protrusions and the method is illustrated for a few synthetic and real images.
bayesian marker extraction for color watershed in segmenting microscopic images. in this paper we study the ability of the cooperation of bayesian color pixel classification in extracting seeds for color watershed. using color pixel classification alone does not extract accurately enough color regions so we suggest to use a strategy based on three steps: simplification, bayesian classification and color watershed. color watershed is based on an aggregation function using local and global criteria. the strategy is performed on microscopicimages. quantitative measures are used to evaluate the resulting segmentations according to a set of reference images.
effective and generic structure from motion using angular error. generic camera modeling using raxels and associated methods was recently introduced in computer vision. the main advantage is the applicability for any camera model, which contrasts to the many specific methods designed for a single camera model. this paper introduces a bundle adjustment based on angular error for the generic structure from motion problem. experiments include automatic, robust and optimal estimation of scene structure and camera motion from a long image sequence acquired by a handheld non-central (calibrated) catadioptric camera.
full-view spherical image camera. this paper proposes a method of realizing a full-view spherical image camera, called spherical camera, and gives its calibration method. the spherical camera can acquire a full-view spherical image by one capture of a single camera. the spherical field of view is divided into two hemispherical ones. each hemispherical field of view is imaged by a fisheye lens, respectively. the both of hemispherical views are fused by a mirror so as to acquire them on a single image plane. as for the calibration of this spherical camera, we let the spherical camera observe the inside of a calibration box so that the control points for calibration can cover the whole view of each fisheye lens, and calibrate it based upon a spherical camera model. we developed the prototype of the spherical image camera and an application of monitoring the whole surrounding environment of vehicle by the spherical camera is also given.
texture-constrained shape prediction for mouth contour extraction and its state estimation. in this paper, we present an automatic mouth contour and state estimation system. an efficient mouth contour extraction algorithm is proposed under the framework of active shape model (asm). considering large mouth shape variations, we propose a textureconstrained shape prediction method for initialization. to improve accuracy and robustness of classical asm, we use classifiers trained by real adaboost to characterize the local texture model. this model is proved to have much stronger discriminative power than gaussian model of classical asm. after extracting the mouth contour, the mouth is classified into one of 4 typical states by support vector machine (svm) based on the shape parameter. experiments over a large set show that extracted mouth contours have achieved good accuracy, with an average 89.5% acceptable rate, and the mouth state estimation reaches an average 93% correct rate. this automatic system reaches a speed of about 10 frames per second on a pentium-iv 1.7ghz pc, which may have potential applications in visual speech recognition etc.
object recognition using composed receptive field histograms of higher dimensionality. recent work has shown that effective methods for recognising objects or spatio-temporal events can be constructed based on receptive field responses summarised into histograms or other histogram-like image descriptors. this paper presents a set of composed histogram features of higher dimensionality, which give significantly better recognition performance compared to the histogram descriptors of lower dimensionality that were used in the original papers by swain & ballard (1991) or schiele & crowley (2000). the use of histograms of higher dimensionality is made possible by a sparse representation for efficient computation and handling of higher-dimensional histograms. results of extensive experiments are reported, showing how the performance of histogram-based recognition schemes depend upon different combinations of cues, in terms of gaussian derivatives or differential invariants applied to either intensity information, chromatic information or both. it is shown that there exist composed higher-dimensional histogram descriptors with much better performance for recognising known objects than previously used histogram features. experiments are also reported of classifying unknown objects into visual categories.
classification using the local probabilistic centers of k-nearest neighbors. in high dimensional feature space with finite samples, severe bias can be introduced in the nearest neighbor algorithm. in this paper, we propose a new classification method, which performs classification task based on local probability center of each class. moreover, this prototypebased method classifies the query sample by using two measures, one is the distance between query and local probability centers, the other is the posterior probability of query. although both measures are effect, the experiments show the second one is the better. the investigation results prove that this method improves the classification performance of nearest neighbor algorithm substantially.
a new approach to automated retinal vessel segmentation using multiscale analysis. computer based analysis for automated segmentation of blood vessels in retinal images will help eye care specialists screen larger populations for vessel abnormalities. however, automated retinal segmentation is complicated by the fact that the width of retinal vessels can vary from very large to very small, and that the local contrast of vessels is unstable, especially in unhealthy ocular fundus. we propose a novel method that takes these facts into account. our method includes a multiscale analytical scheme using gabor filters and scale production, and a threshold probing technique utilizing the features of retinal vessel network. our method is good for detecting large and small vessels concurrently. it also offers an efficient way to denoise and enhance the responses of line filters, allowing the detection of vessels with low local contrast.
classification using the local probabilistic centers of k-nearest neighbors. in high dimensional feature space with finite samples, severe bias can be introduced in the nearest neighbor algorithm. in this paper, we propose a new classification method, which performs classification task based on local probability center of each class. moreover, this prototypebased method classifies the query sample by using two measures, one is the distance between query and local probability centers, the other is the posterior probability of query. although both measures are effect, the experiments show the second one is the better. the investigation results prove that this method improves the classification performance of nearest neighbor algorithm substantially.
high-dimensional discriminant analysis and its application to color face images. multilinear algebra plays an important role in signal processing. in this paper, a multilinear generalization of linear discriminant analysis is discussed. similar to hosvd, an iterative algorithm is developed for solving high-dimensional linear discriminant analysis. meanwhile, a non-iterative algorithm is also proposed. in addition, hdlda provides a unified framework for classical lda and 2dlda. experimental results on color face images show the effectiveness and usefulness of the proposed method.
hybrid kernel machine ensemble for imbalanced data sets. a two-class imbalanced data problem (idp) emerges when the data from majority class are compactly clustered and the data from minority class are scattered. though a discriminative binary support vector machine (svm) can be trained by manually balancing the data, its performance is usually poor due to the inadequate representation of the minority class. a recognition-based one-class svm can be trained using the data from the well-represented class only. however, it is not highly discriminative. exploiting the complementary natures of the two types of svms in an ensemble can bring benefits from both worlds in addressing the idp. experimental results on both artificial and real benchmark data sets support the feasibility of our proposed method.
fingerprint matching using minutia polygons. fingerprint distortion changes both the geometric position and orientation of minutiae, and leads to difficulties in establishing a match among multiple impressions acquired from the same finger. in this paper, minutia polygons are used to match distorted fingerprints. a minutia polygon describes not only the minutia type and orientation but also the minutia shape. this allows the minutia polygon to be bigger than the conventional tolerance box without losing matching accuracy. in other words, a minutia polygon has a higher ability to tolerate distortion. furthermore, the proposed matching method employs an improved distortion model using a multi-quadric basis function with parameters. adjustable parameters make this model more suitable for fingerprint distortion. experimental results show the proposed method is two times faster and more accurate (especially, on fingerprints with heavy distortion) than the method in [1].
detecting abnormal regions in colonoscopic images by patch-based classifier ensemble. in this paper, a new method is proposed to detect abnormal regions in colonoscopic images by patch-based classifier ensemble. through supervised learning from image patches of various sizes, a set of basic svm classifiers is trained for each size. a diagnostic model can then be constructed based on the ensemble of basic classifiers which is then used to detect abnormal regions in colonoscopic images. the multiple sizes of patches provide multiple level representation of the image content, which can help improve detection results. several fusion criteria are explored to determine the final output of the ensemble. experimental results show promising performance of our proposed method.
galilean-diagonalized spatio-temporal interest operators. this paper presents a set of image operators for detecting regions in space-time where interesting events occur. to define such regions of interest, we compute a spatio-temporal second-moment matrix from a spatio-temporal scale-space representation, and diagonalize this matrix locally, using a local galilean transformation in space-time, optionally combined with a spatial rotation, so as to make the galilean invariant degrees of freedom explicit. from the galilean-diagonalized descriptor so obtained, we then formulate different types of space-time interest operators, and illustrate their properties on different types of image sequences.
uncalibrated two-view metrology. a method of visual metrology from uncalibrated cameras is proposed in this paper, whereby a camera, which captures two images separated by a (near) pure translation, becomes a height measurement device. a novel projective construction allows accurate affine height measurements to be made relative to a reference plane, given that the reference plane planar homography between the two views can be accurately recovered. to this end a planar homography estimation method is presented, which is highly accurate and robust and based on a novel reciprocal-polar (rp) image rectification. the absolute height of any pixel or feature above the reference plane can be obtained from this affine height once the cameraýs distance to the reference plane, or the height of a second measurement in the image is specified. results from our data show a mean absolute error of 6.9mm and with two outliers removed this falls to 1.5mm.
a multi-label front propagation approach for object segmentation. for effective image segmentation methods, speed, accuracy and smoothness of the result are essential. in this paper, an iterative object segmentation approach is proposed based on minimal path theory. each iterative step includes one morphological dilatation and one multi-label front propagation. a narrow band is obtained by dilating the current contour with the known size. a new contour is again formed by multi-label front propagation, which is based on minimal path theory. its propagation speed is decided by the local image mean values together with the edge function. the final boundary will be obtained automatically through finite iterations. this algorithm is a global optimization method. it is simple and fast with complexity o(n). the initial contour may be chosen freely. the multi-label front propagation guarantees continuity and smooth contours with the capability to handle topology changes. furthermore, it is easy to extend to the 3d case. some experimental results are also presented.
learning high-level independent components of images through a spectral representation. statistical methods, such as independent component analysis, have been successful in learning local low-level features from natural image data. here we extend these methods for learning high-level representations of whole images or scenes. we show empirically that independent component analysis is able to capture some intuitive natural image categories when applied on histograms of outputs of ordinary gabor-like filters. this can be taken as an indication that maximizing the independence or sparseness of features may be a meaningful strategy even on higher levels of image processing, for such advanced functionality as object recognition or image retrieval from databases.
camera-based document image mosaicing. in this paper we present an image mosaicing method for camera-captured documents. our method is unique in not restricting the camera position, thus allowing greater flexibility than scanner-based or fixed-camera-based approaches. to accommodate for the perspective distortions introduced by varying poses, we implement a two-step image registration process that relies on accurately computing the projectivity between any two document images with an overlapping area as small as 10%. in the overlapping area, we apply a sharpness based selection process to obtain seamless blending across the border and within. experiments show that our approach can produce a very sharp, high resolution and accurate full page mosaic from small image patches of a document.
page classification through logical labelling. in this paper, we propose an integrated approach to page classification and logical labelling. layout is represented by a fully connected attributed relational graph that is matched to the graph of an unknown document, achieving classification and labelling simultaneously. byincorporating global constraints in an integrated fashion, ambiguity at the zone level can be reduced, providing robustness to noise and variation. models are automatically trained from sample documents. experimental results show promise for the classification and labelling oftechnical article title pages, and supports the idea of a hierarchical model base.
facial feature selection based on svms by regularized risk minimization. in this paper we present a method based on svms by regularized risk minimization for the facial feature selection aiming at improving performance of the classifier by (1) using wt + kpca as filter approach to choose a set of more meaningful representatives to replace the original data for feature selection; (2) using svm rfe iterative procedure as wrapper approach to obtain the optimum feature subset; (3) using regularized risk minimization as feature selection ranking criterion. experimental results on feret face database subsets indicate that the proposed method has a significant improvement in the classification accuracy and speed.
recognition of human periodic motion - a frequency domain approach. we present a frequency domain analysis technique for modelling and recognizing human periodic movements from moving light displays (mlds). we model periodic motions by motion templates, that consist of a set of feature power vectors extracted from unidentified vertical component trajectories of feature points. motion recognition is carried out in the frequency domain, by comparing an observed motion template with prestored templates. this method contrasts with common spatio-temporal approaches. the proposed method is demonstrated by some examples of human periodic motion recognition in mlds.
a new shape transformation approach to handwritten character recognition. a new simple algorithm, based on dynamic programming is presented, for handwritten character recognition, with improved accuracy. the proposed shape transform (st) approach is based on the calculation of the cost of transforming the image of a given character into that of another, thus taking into account local geometrical similarities and differences. a large experiment is conducted on the nist database. [2], and the effectiveness of the proposed method, is compared to the karhunen loeve transform (klt) method, with which a similar experiment was contacted [1] reporting the best results in the literature. the experiments performed, show that this new approach leads to improved recognition. it is more demanding in computer time, which is becoming ever more plentiful, but it lends itself to very efficient parallel hardware implementation.
face recognition using shading-based curvature attributes. in this paper we apply shape-from-shading to face images to extract elds of surface normals and make estimates of surface curvature attributes. the attributes studied include minimum andmaximum curvature, mean and gaussian curvature, and, curvedness and shape-index. the curvature attributes are encoded as histograms and are used to perform recognition using a number of distance and similarity measures including the euclidean distance, the shannon entropy, the renyi entropy and the tsallis entropy. we compare the results obtained using the differentcurvature attributes and the different entropy measures. using precision-recallcurves, we find that the best performance is delivered when the shannonentropy is applied to histograms of shape index and curvedness.
five-point motion estimation made easy. estimating relative camera motion from two calibrated views is a classical problem in computer vision. the minimal case for such problem is the so-called five-point problem, for which the state-of-the-art solution is nistér's algorithm [1][2]. however, due to the heuristic nature of the procedures it applies, to implement it needs much effort for non-expert user. this paper provides a simpler algorithm based on the hidden variable resultant technique. instead of eliminating the unknown variables one by one (i.e, sequentially) using the gauss-elimination as in [1], our algorithm eliminates many unknowns at once. moreover, in the equation solving stage, instead of back-substituting and solve all the unknowns sequentially, we compute the minimal singular vector of the coefficient matrix, by which all the unknown parameters can be estimated simultaneously. experiments on both simulation and real images have validated the new algorithm.
extraction of 3d microtubules axes from celluar electron tomography images. microtubules are structural and motile elements. they are essential in numerous cell processes. their function will be greatly improved by our understanding of their molecular structure, which requires extracting microtubules from the cellular electron tomography images. manual segmentation and measurement of the microtubules from 3d dataset may require several man-hours of work, and the manual approach suffers from inter-observer and intra-observer variabilities.localizing microtubules axes is an important step for the successful segmentation. in this paper, a graph searching based technique for extracting central axes of microtubules from three dimensional cellular electron tomography images is presented. a tube enhancement filter is introduced in order to define a distance metric for graph searching. the results are promising, indicating that accurate mea-surements can be obtained in a semi-automatic fashion.
a coarse-to-fine strategy for vehicle motion trajectory clustering. high-level semantic understanding of vehicle motion behaviors is often based on vehicle motion trajectory clustering. in this paper, we propose an effective trajectory clustering framework in which a coarse-to-fine strategy is taken. our framework consists of four stages: trajectory smoothing, feature extraction, trajectory coarse clustering and trajectory fine clustering. wavelet decomposition is imposed on raw trajectories to reduce noise in the trajectory smoothing stage. besides the commonly used positional feature, a novel feature called trajectory directional histogram is proposed to describe the statistic directional distribution of a trajectory in the feature extraction stage. both coarse clustering and fine clustering are based on a novel graphtheoretic clustering algorithm called dominant-set clustering, but they deal with different trajectory features. experiments in our pre-labeled trajectory database demonstrate that the proposed trajectory clustering framework possesses a very high accuracy.
feature selection for linear support vector machines. feature selection is attracted much interest from researchers in many fields such as pattern recognition and data mining. in this paper, a novel algorithm for feature selection is developed. the proposed algorithm uses the standard linear svm algorithm and is performed in an iterative way. feature selection is carried out by assigning weights to features. experimental results on uci data set and face images confirm the feasibility and validation of the proposed method.
semantic feature extraction using genetic programming in image retrieval. one of the big hurdles facing current content-based image retrieval (cbir) is the semantic gap between the low-level visual features and the high-level semantic features. we proposed an approach to describe and extract the global texture semantic features. according to tamura texture model, we utilize the linguistic variable to describe the texture semantics, so it becomes possible to depict the image in linguistic expression such as coarse, fine. and we use genetic programming to simulate the human visual perception and extract the semantic features value. our experiments show that the semantic features have good accordance with the human perception, and also have good retrieval performance. in some extent, our approach bridges the semantic gap in cbir.
chinese character recognition via gegenbauer moments. moment features have been applied in pattern recognition systems since the moment method was developed. in this paper, a set of moment features extracted from the newly developed gegenbauer moment method for chinese character recognition is proposed. compared with the results based on other moment methods, the gegenbauer moments can provide a modest improvement in terms of recognition for those chinese characters that are very similar in shapes. we conclude that the proposed new gegenbauer moment method can supplement the existing chinese character recognition techniques based on local structure features.
a machine learning approach for locating boundaries of liver tumors in ct images. in this paper, we propose a novel machine learning approach for locating boundaries of liver tumors in ct (computed tomography) images. given a marker indicating a rough location of a tumor, the proposed solution locates its boundary. our approach consists of training process and locating process. in training process, we train adaboosted histogram classifiers to classify true boundary positions and false ones on the 1-d intensity profiles of tumor regions. in locating process, we locate the boundaries by using the trained adaboosted histogram classifiers. the novelty of our approach is that we use adaboost in the training process to learn diverse intensity distributions of the tumor regions, and utilize the trained results successfully in locating process. experimental results show our approach locates the boundaries successfully, despite the diverse intensity distributions of the tumor regions, marker location variability and tumor region shape variability. our framework is also generic and can be applied for locating boundaries of blob-like targets with diverse intensity distributions in other applications.
classification of audio signals in all-night sleep studies. in this paper, we describe the classification of audio signals recorded in all-night sleep studies. our objective is to separate the episodes into snoring sounds and non-snoring sounds. to begin with, we employ hierarchical classification schemes to classify sounds into human sounds and non-human sounds. we then attempt to organize human sounds into snore and non-snore segments based on their acoustic properties. we perform further analysis of the extracted snoring sounds to check if the testee has apnea. experimental results have validated the efficacy of the proposed method.
behavior modeling and recognition based on space-time image features. a novel method based on space-time image features is proposed for automatic behavior modeling and recognition. the method is composed of the following three steps: (1). video sequences are converted into a space-time image, and the image is divided into equal length segments; (2). from these segments, an unsupervised technique based on dynamic time warping is used to determine the groups of different behaviors; (3). the behavior templates are built according to these groups, and are used for the recognition of behaviors. the method does not need to track the body parts and can model the behaviors without any prior knowledge. experiments also demonstrate the effectiveness of our new method.
cvml - an xml-based computer vision markup language. we propose an xml-based computer vision markup language for use in cognitive vision, to enable separate research groups to collaborate with each other as well as making their research results more available to other areas of science and industry, without having to reveal any proprietary ideas, algorithms or even software. the computer vision markup language can communicate any type and amount of information, making unavailable functionality accessible to anyone. in this paper we introduce the language and describe how we have implemented it in a very large cognitive vision project. we provide a free open source library for working with this language, which can easily be implemented into existing code providing seamless network communication abilities and multi-platform support. last we describe the future of cvml and how it might evolve to include other areas of research.
probabilistic image-based rendering with gaussian mixture model. one major challenge in traditional image-based rendering is 3d scene reconstruction by estimating accurate dense depth map, which suffers from the ambiguities in textureless or periodically textured regions. alternatively, statistical methods may be used to estimate a most likely color for each pixel for photorealistic rendering from multiple views of the same scene. such statistical methods normally require a relatively large number of input images to achieve reasonable quality for the synthesized image, if the estimation is purely nonparametric. in this paper, based on some reasonable assumptions on the configuration of the multiple views, we propose to use a two-component gaussian mixture model for the appearance of a given pixel in all the views so that both the problem of occlusion and the problem of noise can be considered simultaneously. then we use the expectation-maximization algorithm to estimate the model parameters. the virtual pixel is given as a maximum likelihood estimate for one of the mixture components. experiments shows that reasonable performance can be obtained even with only a few input images.
hierarchical identification of palmprint using line-based hough transform. the hough transform (ht) is a powerful technique for line detection. its main advantage is that it is relatively unaffected by noise or gaps in lines. this work proposes a line-based hough transform method, which extracts global features for coarse-level filtering in hierarchical palmprint identification system. the local information extracted from position and orientation of individual line is used for further finelevel identification. line-based hausdorff distance (lhd) algorithm is applied for local line matching. this is a novel approach to the application of the hough transform for feature extraction of palmprint. experiments had been conducted on a palmprint database collected by hong kong polytechnic university. 99% identification rate has been achieved with much reduced running time.
supervised training based hand gesture recognition system. we have developed a hand gesture recognition system, based on the shape analysis of static gestures, for human computer interaction purposes. our appearance-based recognition uses modified fourier descriptors for the classification of hand shapes. as always found in literature, such recognition systems consist of two phases: training and recognition. in our new practicalapproach, following the chosen appearance-based model, training and recognition is done in an interactive supervised way: the adaptation for untrained gestures is also solved by hand signals. our experimental results with three different users are reported. in this paper, besides describing the recognition itself, we demonstrate our interactive training method in a practicalapplication.
multi-resolution curve alignment based on salient features. in this paper, we present a novel approach to the problem of curve alignment, which measures and matches the similarity of two curves. our method extracts curve features with high priorities given to salient and general features, and therefore leads to a satisfied result that meets human being's perceptions. we investigate the bimorphism in the level of subsegment correspondences to ensure symmetric mapping. a solution to closed curve alignment is also given. finally, the coarse-to-fine aligning algorithm is introduced to match curves under different resolutions. the experiments showed satisfying and approving results, that our approach can capture the curve features and align them properly.
dynamic training of hand gesture recognition system. we developed an augmented reality tool for vision-based hand gesture recognition in a camera-projector system. our recognition method uses modified fourier descriptors for the classification of static hand gestures. hand segmentation is based on a background subtraction method, which is improved to handle background changes. most of the recognition methods are trained and tested by the same service-person, and training phase occurs only preceding the interaction. however, there are numerous situations when several untrained users would like to use gestures for the interaction. in our new practical approach the correction of faulty detected gestures is done during the recognition itself. our main result is the quick on-line adaptation to the gestures of a new user to achieve user-independent gesture recognition.
a geometric active contour framework using multi-cue and local feature. there exist two key issues in the traditional geometric active contour (gac): only single cue based driven force and edge leakage. in this paper, we propose two new gacs, i.e., multi-cue based gac (mc-gac) and local-feature based gac (lf-gac), to deal with these two problems respectively. in mc-gac, a multi-cue based force is generated by introducing the customized vector flow into the model. to utilize local feature information, lf-gac is developed, in which local edge information is considered to produce continuous edge. further, we unify these two gacs into a novel general gac framework. extensive experiments showed the advantages of the proposed method.
multi-view-based cooperative tracking of multiple human objects in cluttered scenes. this paper presents a multi-view-based cooperative tracking of multiple human objects. occlusion is one of the difficult problems for human object tracking in cluttered scenes. based on the homographic relation between the two views, we proposed a so-called cooperative tracking which consists of particle filter tracking for the objects in different views. the multiple view tracking is modeled as different sequences of hidden process and observation. in addition, based on the interaction between targets, a hidden variable is added in to reveal the reliability of the tracking result in that specific view. with this hidden variable, the cooperative tracking allocates computational resources for tracking the objects in different views. experimental results show the efficiency of the proposed method.
multibaseline stereo in the presence of specular reflections. we address the problem of accurate depth estimation using multibaseline stereo in the presence of specular reflections. specular reflections can cause the intensity and color of corresponding points to change dramatically according to different viewpoints, thus producing severe matching errors for various stereo algorithms. in this paper, we propose a new method to deal with this problem by treating specular reflections as occlusions. our idea is to first detect specular pixels by computing the uncertainty of depth estimates. then we combine the use of flexible windows and an adaptively selected subset of images to avoid these specular areas in all the multibaseline stereo images. even though specularities may exist in the reference image, accurate depth is nevertheless estimated for all pixels. experiments show that our consideration of specular reflections leads to improved stereo results.
a fast mode decision method for h.264/avc using the spatial-temporal prediction scheme. in the h.264/avc coding standard, the high computation cost of the full searching in the reference software jm-9.3 makes the encoding process inefficient. in this paper, the spatial-temporal correlations between the current frame and reference frame are analyzed to develop a fast mode decision method in which no extra image processes are used. furthermore, the concept of drift compensation is adopted to avoid the error accumulation phenomenon during the mode decision process. the experimental results show that the computation cost may be reduced above 60% and the average psnr is only dropped about 0.04db. keywords: h.264, jm-9.3, mode decision.
new algorithm for geometric transformations of digital images and patterns. nonlinear geometric transformations, such as the splitting-shooting method (ssm), the splitting-integrating method (sim), and their advanced versions s¯s¯m, s¯im, cs¯i¯m have been developed in [4-6]. this paper proposes new versions of such nonlinear transformations, s¯s¯#m, s¯i¯#/m, cs¯#i¯#m, approximated by piecewise linear transformations to circumvent the necessity of finding the nonlinear solutions, and to obtain exact integration computationally. the absolute errors of pixel greyness are proven to be 0(h), h is the length of a pixel region. it is worth pointing out that the new algorithms in this paper do not produce any sequential errors as n = n0. apart from this distinctive feature, the absolute error bound 0(h) can be applied to all kinds of images with discontinuity, including fully isolated pixels.
entropic estimation of noise for medical volume restoration. this paper presents an unsupervised approach for medical volume restoration. to cope with various scanning modalities and strongly corrupted data, an original information tool is introduced: the entropic deviation. to validate the robustness of this estimation, a non-linear restoration filter based on markov random fields is proposed. no parameter tuning is required from the user thanks to the adaptive value of the entropy power. finally, the good quality of the filtered volumes are promising for any clustering application aiming at anatomical structures extraction in medical volume datasets.
selection of statistical features based on mutual information for classification of human coding and non-coding dna sequences. the classification of human gene sequences into exons and introns is an important but difficult problem. we study the discriminative power of various statistical features (22 in total) in term of their mutual information (mi). by performing correlation analysis, we are able to identify a set of features that has high mi value while at the same time is complementary in their information content. using the set of features, which consists of the three sz features, the ami feature, and the first stop codon feature, we are able to achieve classification accuracy as high as 92%.
a hybrid method of unsupervised feature selection based on ranking. feature selection is a key problem to pattern recognition. so far, most methods of feature selection focus on sample data where class information is available. for sample data without class labels, however, the related methods for feature selection are few. this paper proposes a new way of unsupervised feature selection. our method is a hybrid approach based on ranking the features according to their relevance to clustering using a new ranking index which belongs to exponential entropy. firstly a candidate feature subset is selected using a modified fuzzy feature evaluation index (ffei) with a new method to calculate the feature weight, which makes the algorithm to be robust and independent of domain knowledge. then a wrapper method is used to select compact feature subset from the candidate feature set based on the clustering performance. experimental results on benchmark data sets indicate the effectiveness of the proposed method.
rehashing for bayesian geometric hashing. geometric hashing is a model-based recognition technique based on matching of transformation-invariant object representations stored in a hash table. in the last decade a number of enhancements have been suggested to the basic method improving its performance and reliability. one of the important enhancements is rehashing, improving the computational performance by dealing with the problem of non-uniform occupancy of hash bins. however the proposed rehashing schemes aim to redistribute the hash entries uniformly, which is not appropriate for bayesian approach, another enhancement optimizing the recognition rate in presence of noise. in this paper we derive the rehashing for bayesian voting scheme, thus improving the computational performance by minimizing the hash table size and the number of bins accessed, while maintaining optimal recognition rate.
a novel framework for urban change detection using vhr satellite images. we present a novel framework for detecting urban changes from a pair of very high resolution (vhr) satellite images such as those taken by satellite quickbird-ii or ikonos. image differences due to variations of imaging conditions such as view angle and illumination are distinguished from significant urban changes in the scene. first, we adopt a new image registration method, which makes several useful geometrical constraints available. then we find changed line segments over time. after that we match scale invariant feature transform (sift) points and generate corresponding regions in order to exclude changed line segments due to parallax. we perform shadow detection to exclude changed line segments due to shadow change. finally we group the remaining changed line segments into clusters, among which the significant ones form the changed regions as output. our experiments with real quickbird-ii images show that the proposed method can well detect significant urban changes.
ldv remote voice acquisition and enhancement. laser doppler vibrometers (ldvs) have been widely used in industry inspection. one of the superior characteristics of an ldv is that it can detect and measure extremely tiny vibration of a target at a large distance, with sensitivity on the order of 1ìm/s. on the other hand, we have found that most objects nearby audio sources can be vibrated by the audio waves. these two aspects motivate our research in a new application of the ldvs, namely remote voice detection from surrounding vibrated objects. however, the detected speech signals may be corrupted by many noise sources, such as laser photon noises, target movements, and background acoustic noises (wind, engine sound, etc.). therefore, speech enhancement algorithms based on gaussian bandpass and wiener filters are designed to effectively improve the intelligibility of the noisy voice signals detected by the ldv system experimental results show that remote voice detection via an ldv is very promising, when choosing appropriate targets close to human subjects and using the proposed enhancement techniques.
jet based feature classification. in this paper, we investigate to which extent the "raw" mapping of taylor series coefficients into jet-space can be used as a "language" for describing local image structure in terms of geometrical image features. based on empirical data from the van hateren database, we discuss modelling of probability densities for different feature types, calculate feature posterior maps, and finally perform classification or simultaneous feature detection in a bayesian framework. we introduce the brownian image model as a generic background class and extend with empirically estimated densities for edges and blobs. we give examples of simultaneous feature detection across scale.
new method for sparse point-sets matching with underlying non-rigidity. we propose a novel method for matching two sparse point-sets of identical cardinality with distribution similarity. the point-sets are extracted from two subjects with underlying non-rigidity and non-uniform scaling, one being a model set with point identity and the other representing the observed data. there exists neither a global nor local affine transformations between the point-sets. to establish a one-to-one match, we introduce anew similarity k-dimensional tree which is well adapted and robust to such data. weconstruct a similarity k-d tree for the model set. then a corresponding tree of the data set is constructed following the structure information embedded in the model tree. matching sequences of the two point sets are generated by traversing the identically structured trees. experimental results based on synthetic data analysis and real data confirm this method is applicable for robust spatial matching of sparse point-sets under non-rigid distortion.
scene identification using discriminative patterns. with the proliferation of camera phones, new information retrieval applications will emerge. the image of a scene captured by a camera phone can be a query to a remote server to identify the scene and return relevant information. but unconstrained scene identification is an open problem. in this paper, we propose a discriminative measure to rank image patterns sampled from target scene classes. support vector classifiers are then trained using top discriminative patterns for scene identification using voting. we demonstrate our generic approach on two scene databases (zubud and stoic) with promising results.
a segmentation method for touching italic characters. segmentation is an essential part of a recognition system. it is difficult to handle touching characters, especially for italic fonts. we present a method to achieve the accurate segmentation of touching italic characters. it is free of slant correction, so extra noises will not be introduced. we use slant projection and contour analysis to find the segmentation points. then the shortest path approach is adopted for accurately locating the cut path of each candidate segmentation point. based on dynamic programming, we can find the best segmentation result from those cut paths. by this method, we can improve the recognition rate on italic fonts.
multimodal registration using the discrete wavelet frame transform. image registration is a critical step in medical image analysis. in this paper, a novel image registration method based on the discrete wavelet frame transform (dwft) and the sum of absolute distance (sad) method is proposed. first, the multimodal images are decomposed by dwft, which is shift-invariant compared to traditional dyadic wavelet transforms. then the energy maps are computed from the details sub-band images. finally, genetic algorithm (ga) is adopted to obtain the minimum sad between the two energy maps. the proposed method is tested on 50 pairs of two-dimensional t1-weighted and t2- weighted modal images. experimental results demonstrated that the proposed method can achieve high accuracy in the rigid transformation case.
consistent line clusters for building recognition in cbir. this paper introduces a new mid-level feature, the consistent line cluster, for use in content-based image retrieval. the color, orientation, and spatial features of line segments are exploited to group them into line clusters. the interrelationships among different clusters and the intrarelationships within single clusters are used to recognize and roughly locate buildings in photographic images. experiments are performed on a database of color images of outdoor scenes.
high accuracy handwritten chinese character recognition using quadratic classifiers with discriminative feature extraction. we aim to improve the accuracy of handwritten chinese character recognition using two advanced techniques: discriminative feature extraction (dfe) and discriminative learning quadratic discriminant function (dlqdf). both methods are based on the minimum classification error (mce) training method of juang et al. [7], and we propose to accelerate the training process on large category set using hierarchical classification. our experimental results on two large databases show that while the dfe improves the accuracy significantly, the dlqdf improves only slightly. compared to the modified quadratic discriminant function (mqdf) with fisher discriminant analysis, the error rates on two test sets were reduced by factors of 29.9% and 20.7%, respectively.
svm-based classifier design with controlled confidence. a new classification methodology with controlled error rates and a reject option is proposed in this paper. the proposed methodology is implemented using support vector machine's (svm's) posterior probability preserving property. a new nonparametric method is proposed to accurately estimate error rates from the output of a trained svm. the experimental results clearly demonstrate the efficacy of the suggested classifier design methodology.
cascading classifiers for consumer image indexing. in this paper, we propose a cascading framework of binary classifiers to extract and combine intra-image and inter-class semantics for image indexing and retrieval. support vector detectors are first trained on semantic support regions without image segmentation. the reconciled and aggregated detection-based indexes then serve as input for support vector learning of image classifiers to generate class-relative image indexes. during retrieval, similarities based on both indexes are combined to rank images. query-by-example experiments on2400 heterogeneous consumer photos with 16 semantic queries show that the combined matching approach is better than matching with single index. it also outperformed combined matching of color and texture features by 55% in average precision.
image tangent space for image retrieval. image tangent space is actually high-level semantic space learned from low-level feature space by modified local tangent space alignment which was originally proposed for nonlinear manifold learning. under the assumption that a data point in image space can be linearly approximated by some nearest neighbors in its local neighborhood, we develop a lazy learning method to locally approximate the optimal mapping function between image space and image tangent space. that is, the semantics of a new query image in image space can be inferred by the local approximation in its corresponding image tangent space. while euclidean distance induced by the ambient space is often used to represent the difference between images, clearly, their natural distance is possibly different from euclidean distance. here, we compare three distance metrics: chebyshev, manhattan and euclidean distances, and find that chebyshev distance outperforms the other two in measuring the semantic similarity during retrieval. experimental results show that our approach is effective in improving the performance of image retrieval systems.
image retrieval with relevance feedback based on graph-theoretic region correspondence estimation. this paper presents a graph-theoretic approach for region-based image retrieval. when dealing with image matching problem, we propose converting the region correspondence estimation into an attributed graph matching problem and measuring the image similarity in terms of both the region correspondence and the low-level features. in addition, during the relevance feedback, we propose using a maximum likelihood method to re-estimate region features and region importance while retaining its inherent spatial organization. experimental results show that the proposed graph-theoretic matching criterion outperforms other existing methods which include no spatial information in the matching criterion. the experiments also show that the performance can be further improved with our proposed relevance feedback scheme.
discovering operators and features for object detection. in this paper, we learn to discover composite operators and features that are evolved from combinations of primitive image processing operations to extract regions-of-interest (rois) in images. our approach is based on genetic programming (gp). the motivation for using gp is that there are a great many ways of combining these primitive operations and the human expert, limited by experience, knowledge and time, can only try a very small number of conventional ways of combination. genetic programming, on the other hand, attempts many unconventional ways of combination that may never be imagined by human experts. in some cases, these unconventional combinations yield exceptionally good results. our experimental results show that gp can find good composite operators to effectively extract the regions of interest in an image and the learned composite operators can be applied to extract rois in other similar images.
face recognition using patch-based spin images. this paper explores how spin images can be constructed using shape-from-shading information and used for the purposes of face recognition. we commence by extracting needle-maps from gray-scale images of faces, using a mean needle-map to enforce the correct pattern of facial convexity and concavity. spin images [4] are estimated from the needle maps using local spherical geometry to approximate the facial surface. our representation is based on the spin image histograms for an arrangement of image patches. we demonstrate how this representation can be used to perform face recognition across different subjects and illumination conditions. experiments show the method to be reliable and accurate.
vision based fire detection. vision based fire detection is potentially a useful technique. with the increase in the number of surveillance cameras being installed, a vision based fire detection capability can be incorporated in existing surveillance systems at relatively low additional cost. vision based fire detection offers advantages over the traditional methods. it will thus complement the existing devices. in this paper, we present spectral, spatial and temporal models of fire regions in visual image sequences. the spectral model is represented in terms of the color probability density of fire pixels. the spatial model captures the spatial structure within a fire region. the shape of a fire region is represented in terms of the spatial frequency content of the region contour using its fourier coefficients. the temporal changes in these coefficients are used as the temporal signatures of the fire region. specifically, an autoregressive model of the fourier coefficient series is used. experiments with a large number of scenes show that our method is capable of detecting fire reliably.
influence of language models and candidate set size on contextual post-processing for chinese script recognition. in the chinese language, a word consisting of one or more characters is a basic syntax-meaningful unit, however, each character in the word also has a definite meaning in itself. in this paper, we compare the perplexities of four n-gram language models (character-based bigram, character-based trigram, word-based bigram and class-based bigram) and their influence on the performance of contextual post-processing of chinese scripts in an offline handwritten chinese character recognition system. we also demonstrate the influence of the candidate set size on the performance of contextual post-processing in detail, and indicate that the number of candidates should vary with each script.
depth recovery from motion blurred images. this paper presents a novel method to obtain the depth information from motion blurred images. under the assumption of uniform linear motion between the camera and the scene during finite exposure time, both the pinhole model and the camera with a finite aperture are considered. it is shown that the image blur produced by lateral motion of the camera is inversely proportional to the distance of the object. furthermore, if the speed of the relative motion is known, the depth of the object can be acquired by identifying the blur parameters. an image blur model for uniform linear motion is formulated based on geometric optics. the proposed method has been verified experimentally using edge images.
an off-line chinese writer retrieval system based on text-sensitive writer identification. in this paper an off-line chinese writer retrieval system based on text-sensitive writer identification is practised. ocr technique is used to mark the handwritten script content. the used text-sensitive writer identification algorithm extracts directional element features(defs), reduces the dimensions using pca and lda, and adopts the simple euclidean classifier. by introducing negative samples, the similarity measure is more comprehensive. however the writer identification algorithm is text-sensitive, a novel method for retrieving in an amount of writers who has different handwriting script content is proposed in this paper, by combining and sorting the confidence results of writing identification. an experiment, which is carried out in a handwriting script database, demonstrates the effectiveness of the proposed method.
a real-time multiple-vehicle detection and tracking system with prior occlusion detection and resolution, and prior queue detection and resolution. the proposed multiple-vehicle detection and tracking (mvdt) system utilizes a color background to segment moving objects and exploits relations among the moving objects and existed trajectories to track vehicles. initially, the background is extracted by classification. then, it is regularly updated by previous moving objects to guarantee robust segmentation in luminance-change circumstance. for partial wrong converged background due to roadside parking vehicles, it will be corrected later by checking fed back trajectories to avoid false detection after the vehicles moving away. in tracking processing, the relations of distances or distances and angles are applied to determine whether to create, extend, and delete a trajectory. if occlusion detected after trajectory creation, it will be resolved by rule-based tracking reasoning. otherwise, lane information will be used. in addition, to further resolve occlusion occurred in lane, a queue detection and resolution technique will be utilized prior to tracking processing. finally, for easy setup, parameter automation for the system is proposed.
a novel blind watermarking algorithm in contourlet domain. a novel watermarking algorithm based on contourlet transform is proposed in this paper. the watermark composed of pseudo-random sequence is embedded in the selected contourlet transform coefficients by means of multiplicative method. the contourlet coefficients are modeled with generalized gaussian distribution with zero mean, and then watermark detection method is proposed based on maximum likelihood detection. furthermore the decision rule is optimized via neyman-pearson criterion. experimental results show that the fidelity of the watermarked image is good and robust to signal processing and small geometrical attacks.
3d model acquisition based on projections of level curves. a novel method for 3d model acquisition based on projections of level curves is presented. the idea is similar to surface from parallel contours. however, different from ct or laser range scanning for range data acquisition, our approach is implemented on a low-cost passive camera system. the object is placed in a container and the level curves are generated by raising the water level. the 3d surface is recovered by multiple 2d projections of parallel level curves with camera pose estimation. furthermore, the complete 3d model is reconstructed by registration and integration of multi-view 3d shape acquisition. experimental results are presented for real image sequences. the average error is less than 3 mm in the working range of about 1 meter from the camera.
reliable video clock time recognition. we propose a novel approach to read the video clock in real time by recognizing the clock digits using a few techniques relative to the transition patterns of the clock. with these techniques, the clock digits are located without recognizing all the text characters overlaid together with the clock on the video, the sample digit patterns are automatically extracted and labeled in real time. the clock digits are recognized while the video is playing back without any offline training. the recognition result is further verified against the digit transition sequence to improve the performance. experimental results show that this approach is reliable and the result is accurate regardless of the variation of font, size and color of the digit characters in different videos.
normalized sampling for color clustering in medical diagnosis. the classical approach of using minimum cut criterion for clustering is often ineffective due to the existence of outliers in the data. this paper presents a novel normalized graph sampling algorithm for clustering that improves the solution of clustering via the incorporation of a priori constraint in a stochastic graph sampling procedure. the quality of the proposed algorithm is empirically evaluated on two synthetic datasets and a color medical image database.
an embedded watermark technique in video for copyright protection. as the internet and storage equipment become more and more populous, the digital data can easy to distribution. the pirate can easy and limitless to copy digital multimedia. therefore people are more and more attentive the copyright protection for digital multimedia. digital watermarking is an important emerging technique for copyright protection and authentication. this paper presents a novel videowatermarking algorithm based on block matching algorithm to achieve copyright protection of owner. the watermark is mainly embedded in the uncompressed domain and is detected without the use of the original video information. our proposed method is easy to perform and can provide an adjustable threshold to obtain the imperceptibility and robustness performance. the obtained results show the robustness of this approach.
a real-time vehicle detection and tracking system in outdoor traffic scenes. this paper presents a moving vehicle detection and tracking system, mvdt, for real-time operation in outdoor scenes. mvdt consists of three major components: road detection, vehicle detection, and vehicle tracking. the road detection algorithm utilizes a plane-fitting feature, the vehicle detection uses both segmented blob and snakes blob features in a neural network classifier, and a fast vehicle tracking algorithm is designed to locate vehicles in consecutive image frames. we show through experiments that mvdt is effective in detecting moving vehicles in various outdoor scenes and can indeed reach real-time operation requirements.
switching auxiliary chains for speech recognition based on dynamic bayesian networks. this paper investigates the problem of incorporating auxiliary information (e.g. pitch) for speech recognition using dynamic bayesian networks (dbns). previous works usually model acoustic features conditional on the pitch auxiliary variable for both voiced and unvoiced phonetic states, and therefore ignore the fact that pitch (frequency) information is meaningful only for voiced states.. in this paper we propose a switching two auxiliary chain model tailored to voiced/unvoiced states for exploiting pitch information, which is essentially built on the switching parent functionality of bayesian multinets. experiments on the ogi numbers database show that significant performance improvements are achieved from switching auxiliary chain modeling, compared with regular auxiliary chain modeling and the standard hmm.
fingerprint indexing based on symmetrical measurement. due to the small number of classes and uneven distribution, the henry's fingerprint classification approach is not able to provide an efficient way to narrow down the search when identifying a person in a large database. in this paper, three symmetrical filters are used to measure different orientation structures. we proposed a new fingerprint indexing approach based on these three symmetrical measurements. experiments conducted on the nist database 4 show the effectiveness of the proposed approach.
an adaptive data hiding technique for binary images. a simple data hiding technique for binary images is proposed. the proposed method embeds secure data at the edge portion of host binary image. we find the best changeable pixels in a block by changing distance matrix dynamically and compute its changeable score by weighting mechanism. the proposed method uses the pseudo random number generator based on rabin public key cryptography system to embed secret data into a binary image. according to the pseudo random number generator, we can distribute secret data into the binary image to make binary image quality better and get high security.
image segmentation based on inscribed circle. we present an image segmentation algorithm based on inscribed circle (icseg) in this paper. the algorithm includes multi-step. it examines edges at first, and then produces a binary image with edges as foreground. after that, inscribed circles are created to cover the background of the binary image. in the first partition, the image is subdivided into separated regions by combining inscribed circles. finally, the regions are merged by computing their shape and gray level features. this approach integrates the boundarybased and region-based techniques. it is a simple and efficient way for full image segmentation.
off-line handwritten chinese character stroke extraction. stroke extraction is of great significance for an offline character recognition system. in this paper, we present an efficient stroke extraction method based on a combination of a simple feature point detection scheme and a novel stroke segment connecting method. the algorithm can fast and accurately extract the strokes from the thinned chinese character images. experimental results on a large data set with over eighteen thousand character strokes achieve over 99% accuracy.
detecting text lines in handwritten documents. although detecting text lines in machine printed documents is typically considered a solved problem, it is still a challenge to segment handwritten text lines in the general sense given no prior knowledge of script. this paper models text line detection as an image segmentation problem by enhancing text line structures using a gaussian window and adopting the level set method to evolve text line boundaries. experiments show that the method, which is script independent, achieves high accuracy for detecting text lines in heterogeneous handwritten documents.
articulate hand motion capturing based on a monte carlo nelder-mead simplex tracker. this paper presents an algorithm for tracking the articulate hand motion in monocular video sequences. the task is challenging due to the high degrees of freedom involved in the hand motion. the complexity can be reduced by considering the natural motion constraints. to take advantage of the constraints, we propose to use a nonparametric representation of the feasible configuration space and employ a monte carlo nelder-mead simplex search algorithm. the tracker combines the strengths of both sequential monte carlo and direct search algorithms. first, its multiple hypotheses nature increases the chance of the simplex method to identify the global maximum. second, the direct search algorithm produces a set of more representative particles. experiment results show that this hybrid approach is robust for tracking the hand motion.
a new strategy for selecting working sets applied in smo. at present sequential minimal optimization (smo) is one of the most popular and efficient training algorithms for support vector machines (svm), especially for large-scale problems. a novel strategy for selecting working sets applied in smo is presented in the paper. based onthe original feasible direction method, the new strategy also takes the efficiency of kernel cache maintained in smo into consideration. it is shown in the experiments on the well-known data sets that computation of the kernel function and training time is reduced greatly,especially for the problems with many samples and support vectors.
continuous optimization based-on boosting gaussian mixture model. a new estimation of distribution algorithm(eda) based-on gaussian mixture model (gmm) is proposed, in which boosting, an efficient ensemble learning method, is adopted to estimate gmm. by boosting simple gmm with two components, it has the ability of learning the model structure and parameters automatically without any requirement for prior knowledge. moreover, since boosting can be viewed as a gradient search for a good fit of some objective in function space, the new eda is time efficient. a set of experiments is implemented to evaluate the efficiency and performance of the new algorithm. the results show that, with a relatively smaller population and less number of generations, the new algorithm can perform as well as compared edas in optimizing multimodal functions.
bagging based efficient kernel fisher discriminant analysis for face recognition. kernel fisher discriminant analysis (kfda) has achieved great success in pattern recognition recently. however, the training process of kfda is too time consuming (even intractable) for a large training set, because, for a training set with n examples, both its between-class and within-class scatter matrices are of n×nand the time complexity of the kfda training process is ofo(n^3). aiming at this problem, this paper employs bagging technique to decrease the time-space cost of kfda training process. in addition, this paper is more than just a simple application of bagging. we have made an important adaptation which can further guarantee the performance of kfda. our experimental results demonstrate that the proposed method can not only greatly reduce the cost of time of the training process, but also achieve higher recognition accuracy than traditional kfda and the simple application of bagging.
object tracking using incremental fisher discriminant analysis. this paper presents a novel object tracking algorithm using incremental fisher linear discriminant (fld) algorithm. the sample distribution of the target class is modeled by a single gaussian and the non-target background class is modeled by a mixture of gaussians. to a facilitate a multiclass classification problem, we recast the classic fld algorithm in which the number of classes does not need to be pre-determined. the most discriminant projection matrix that best separates the samples in the projected space is computed using fld at each frame. based on the current target location, an efficient sampling algorithm is used to predict the possible locations in the next frame. using the current projection matrix computed by fld, the most likely candidate which is closed to the center of the target class in the projected space is selected. since the fld is repeatedly computed at each frame, we develop an incremental and efficient method to compute the projection matrix based on the previous results. experimental results show that our tracker is able to follow the target with large lighting, pose and expression variation.
fft snake: a robust and efficient method for the segmentation of arbitrarily shaped objects in image sequences. a robust and efficient algorithm for segmenting arbitrarily shaped objects in images, which is called fft snake, is proposed in this paper. a low-pass filter with the fast fourier transform (fft) of the curve as theoretic internal force is first introduced to smooth the contours. in real algorithm, it is composed of the curves trimming and crossing chains cutting. at last the contours are evolved in the direction of normal vectors of the curve to match the feature-map. the algorithm is then applied to the rapid video feedback on the motion for the real-time diving training. the results are highly encouraging to capture the contours of arbitrarily shaped objects for real-time tracking systems. we believe that fft snake has wide uses in video compression, multimedia applications, and so on.
shadow detection by integrating multiple features. cast shadows of moving foreground objects in a scene often result in problems for many applications such as surveillance, object tracking/recognition, video content analysis and intelligent transportation systems. in this paper we presented an algorithm exploiting information of color, shading, texture, neighborhoods and temporal consistency to detect shadows in a scene efficiently and reliably. the experimental results showed that the proposed method can detect umbra as well as penumbra in different kinds of scenarios under various illumination conditions.
latent layout analysis for discovering objects in images. latent layout analysis (lla) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. lla defines a generative model that associates latent aspects to local appearances. the dependency between aspects and position is captured by a spatial sensitive aspect model. this dependency distinguishes lla from probabilistic latent semantic analysis (plsa). the latent aspects together with the latent layout constitute a compact scene representation. we demonstrate that the proposed lla significantly outperforms probabilistic latent semantic analysis in two tasks: object discovery (detection) and object localization.
distance based kernel pca image reconstruction. principal component analysis (pca) is widely used in data compression, de-noising and reconstruction, but it is inadequate to describe real images with complex nonlinear variations, such as illumination, distortion, etc, because it is a linear method in nature. in this paper, kernel pca (kpca) is presented to describe real images, which combines the nonlinear kernel trick with pca. first, the kernel trick is used to map the input data into an implicit feature space f, and then pca is performed in f to produce nonlinear principal components of the input data. however, there exists a problem for kpca reconstruction, as the feature space f is implicit and unknown. in order to deal with this problem, we propose to employ a new kernel called the distance kernel to set up a corresponding relation based on distance between the input space and the implicit feature space f. experimental results illustrate that the proposed method has an encouraging performance.
accurate dense optical flow estimation using adaptive structure tensors and a parametric model. an accurate optical flow estimation algorithm is proposed in this paper. by using a 3d structure tensor and a parametric flow model, the optical flow estimation is converted to generalized eigenvalue problem to avoid solving a linear system explicitly. the optical flow can be accurately estimated from the generalized eigenvectors. the confidence measurement derived from the generalized eigenvalues is used to adaptively adjust the coherent motion region to further improve the accuracy. experiments on both synthetic sequences with ground truth and real sequences are used to test our method. comparison with classical and recently published methods are given to demonstrate that our algorithm is accurate and robust to the aperture problem.
improve handwritten character recognition performance by heteroscedastic linear discriminant analysis. in this paper, we propose a new linear dimensionality reduction method to deal with heteroscedastic feature distribution in handwritten character recognition. marc loog's between-class scatter matrix decomposition and directed distance matrix (ddm) concept is adopted, while the chernoff criterion he used is replaced by a new mahalanobis criterion proposed in this paper, and the pairwiseclass calculation is removed to reduce computational cost. we experiment our heteroscedastic linear discriminant analysis algorithm on different character recognition problems, and demonstrate its superiority over conventional linear discriminant analysis.
a bayesian predictive method for automatic speech segmentation. implicit speech segmentation is basically to find time instances when the spectral distortion is large. spectral variation function is a widely used measure of spectral distortion. however, svf is a data-dependent measure. in order to make the measurement data-independent, a likelihood ratio is constructed to measure the spectral distortion. this ratio can be computed efficiently with a bayesian predictive model. the prior of the bayesian predictive model is estimated from unlabeled data via an unsupervised machine learning technique . gaussian mixture model(gmm). the experimental results show that effectiveness of this novel method. the performance on timit corpus indicate the potential applications in speech recognition, synthesis and coding.
cast shadow removal with gmm for surface reflectance component. cast shadow on the background is generated by an object moving between a light source and the background. the position and illumination of the source always change with time, while the background is stable. therefore, features connected with light source always change with time, such as geometry and color. in this paper, we present a shadow removal method by homomorphic model to extract surface reflectance component, which is only connected with background of the scene and is robust to change of light source. we assume that reflectance component fits gaussian distribution, and then use gmm to model it. experimental results show that, except dealing with shadow, our method is not sensitive to the change of illumination.
robust local scoring function for text-independent speaker verification. traditionally, the universal background model (ubm) is viewed as the background model of the entire acoustic feature space. we propose a novel interpretation of the ubm model, and consider it as a mapping function that transforms the variable length observations (speech utterances) into a fixed dimensional feature vector (sufficient statistics). after this mapping, a similarity measurement is computed on the fixed dimensional features. with this novel interpretation, we proposed a new similarity measurement which produces more than 10% relative improvement over the conventional ubm-map framework in both equal error rate and detection cost function.
fingerprint retrieval by complex filter responses. this paper proposes an approach of fingerprint retrieval based on the continuous classification of two complex filter responses. two complex filters are introduced and applied on the fingerprint orientation field to extract the local singularities, the similarities to the singular points. a numerical feature vector from the aligned fingerprint local singularities is constructed as the global feature for fingerprint retrieval. the continuous classification is employed to retrieve a subset of fingerprints similar to the query fingerprint for the finer matching. experimental results on nist fingerprint database 4 (nist-4) show the effectiveness of the proposed fingerprint retrieval approach.
inverse validation for accurate range image registration with structured data. automatic range image registration is a fundamental yet extremely difficult problem in machine vision. in this paper, we extend a promising registration algorithm (gicp) [6] for structured image data. the extended algorithm is based on a relaxation method combining the motion estimation results from the possible correspondences established by the gicp algorithm and those that are further ev aluated by an in verse validation procedure. a comparative studybased on real images has shown that the extended algorithm is more accurate and robust than the original algorithm.
genus-zero shape classification using spherical normal image. a new method for three dimensional (3d) genus-zero shape classification is proposed. it conformally maps a 3d mesh onto a unit sphere and uses normal vectors to generate a spherical normal image (sni). unlike extended gaussian images which have an ambiguity problem, the sni is unique for each shape. spherical harmonics coefficients of snis are used as feature vectors and a self-organizing map is adopted to explore the structure of a shape model database. since the method compares only the snis of different objects, it is computationally more efficient than the methods which compare multiple 2d views of 3d objects. the experimental results show that the proposed method can discriminate collected 3d shapes very well, and is robust to mesh resolution and pose difference.
free form shape matching using deterministic annealing and softassign. free form shape matching is a fundamental problem in both the machine vision and pattern recognition literatures. however, the automatic approach to free form shape matching still remains open. in this paper, we improve an existing deterministic annealing and softassign method for automatic free form shape matching through incorporating rigid motion constraints. the experiments based on both synthetic data and real images show the effectiveness of the improved algorithm.
object tracking using globally coordinated nonlinear manifolds. we present a dynamic inference algorithm in a globally parameterized nonlinear manifold and demonstrate it on the problem of visual tracking. an appearance manifold is usually nonlinear, embedded in a high dimensional space, and can be approximated by a mixture of locally linear models. existing methods for nonlinear dimensionality reduction, which map an appearance manifold to a single low dimensional coordinate system, preserve only spatial relationships among manifold points and render low dimensional embeddings rather than mapping functions. in this paper, we parameterize the mixture of linear appearance subspaces of an object in a global coordinate system, and apply it to visual tracking using a rao-blackwellized particle filter. experimental results demonstrate that the proposed approach performs well on object tracking problem in scenes with significant clutter and temporary occlusions which pose difficulties for other methods.
handwritten numeral string recognition: character-level vs. string-level classifier training. the performance of handwritten numeral string recognition integrating segmentation and classification relies on the classification accuracy and the resistance to non-characters of the underlying classifier. the classifier can be trained at either character level (with character and non-character samples) or string level (with string samples). we show that both character-level and string-level training yield superior string recognition performance. string-level training improves segmentation but deteriorates classification. by combining the character-level trained classifier and the string-level trained classifier, we have achieved higher string recognition performance. we show the experimental results of three classifier structures on the numeral strings of nist special database 19.
detecting virulent cells of cryptococcus neoformans yeast: clustering experiments. the yeast cryptococcus neoformans can cause dangerous infections such as meningitis. the presence of a thick capsule is shown to be correlated with virulence of a yeast cell. this paper reports on our approach towards developing a classifier for detecting virulent cells in images. we present our methods for creating samples, collecting images, preprocessing the images, identifying cells and creating features for each cell. unsupervised clustering experiments have provided preliminary evidence that our methods results in features that can successfully be used to group and distinguish virulent from normal cells. in our future work we plan to use the same methods and feature set to build supervised classification models.
a spectral representation for appearance-based classification and recognition. we present a spectral representation for appearance-based image classification and object recognition. based on a generative process, the representation is derived by partitioning the frequency domain into small disjoint regions. this gives rise to a set of filters and a representation consisting of marginal distributions of those filter responses. we use a neural network to learn a classifier through training examples. we propose a filter selection algorithm by maximizing the performance over training data. a distinct advantage of our representation is that it can be effectively used for different classification and recognition tasks, which is demonstrated by experiments and comparisons in texture classification, face recognition, and appearance-based 3d object recognition.
reinforcement learning-based feature learning for object tracking. feature learning in object tracking is important because the choice of the features significantly affects system's performance. in this paper, a novel online feature learning approach based on reinforcement learning is proposed. reinforcement learning has been extensively used as a generative model of sequential decision-making that interacts with uncertain environment. we extend this technique to feature selection for object tracking, and further add human-computer interaction to reinforcement learning to reduce the learning complexity and speed the convergence rate. experiments of the object tracking are provided to verify the effectiveness of the proposed approach.
simplest representation yet for gait recognition: averaged silhouette. we present a robust representation for gait recognition that is compact, easy to construct, and affords efficient matching. instead of a time series based representation comprising of a sequence of raw silhouette frames or of features extracted therein, as has been the practice, we simply align and average the silhouettes over one gait cycle. we then base recognition on the euclidean distance between these averaged silhouette representations. we show, using the recently formulated gait challenge problem (www.gaitchallenge.org), that the improvement in execution time is 30 times while possessing recognition power that is comparable to the gait baseline algorithm, which is becoming the comparison standard in gait recognition. experiments with portions of the average silhouette representation show that recognition power is not entirely derived from upper body shape, rather the dynamics of the legs also contribute equally to recognition. however, this study does raise intriguing doubts about the need for accurate shape and dynamics representations for gait recognition.
personalized face verification system using owner-specific cluster-dependent lda-subspace. in this paper, we propose an owner-specific cluster-dependent linear discriminant analysis (oscd-lda) method, and apply it to develop a personalized face verification system. before the owner enrollment, our system first divides all the training face images into a number of clusters, each containing a subset of face images having similar characteristics. once the owner completes the enrollment procedure, the system will assign the owner to the cluster that contains faces most similar to the owner's training faces. then, the system uses the training faces in this most similar cluster to determine the oscd-lda subspace for computing the matching score. this oscd-lda subspace can be considered as a personalized subspace, trained specifically for this owner in order to best discriminate this particular owner from other non-owners. our experimental results have shown that the proposed oscd-lda method outperforms the conventional lda method, and can reduce false acceptance rate and false rejection rate by about 40 percent when using the xm2vts database.
image complexity and feature extraction for steganalysis of lsb matching steganography. in this paper, we present a scheme for steganalysis of lsb matching steganography based on feature extraction and pattern recognition techniques. shape parameter of generalized gaussian distribution (ggd) in the wavelet domain is introduced to measure image complexity. several statistical pattern recognition algorithms are applied to train and classify the feature sets. comparison of our method and others indicates our method is highly competitive. it is highly efficient for color image steganalysis. it is also efficient for grayscale steganalysis in the low image complexity domain.
newspaper headlines extraction from microfilm images. automatic indexing is important for a digital library to provide digitized manuscripts of old document images and their electronic text. as an essential step in creating such a system, this paper discusses the issue of extracting headlines from old newspaper microfilms. most research on document layout analysis has largely assumed relatively clean images. however microfilm images of old newspapers present a challenge. such images are usually insufficiently illuminated and considerably dirty. to overcome the problem we propose a new effective method for separating characters from noisy background since conventional threshold selection techniques are inadequate to deal with these kinds of images. a run length smearing algorithm (rlsa) is applied in the headline extraction. experiment shows that our approach has improved the recall, precision and combined rates.
kernel scatter-difference based discriminant analysis for face recognition. there are two problems with the fisher linear discriminant analysis (flda) for face recognition. one is the singularity problem of the within-class scatter matrix due to small training sample size. the other is that flda cannot efficiently describe complex nonlinear variations of face images with illumination, pose and facial expression variations, due to its linear property. in this paper, a kernel scatter-difference based discriminant analysis is proposed to overcome these two problems. we first use the nonlinear kernel trick to map the input data into an implicit feature space f. then a scatter-difference based discriminant rule is defined to analysis the data in f. the proposed method can not only produce nonlinear discriminant features in accordance with the principle of maximizing between-class scatter and minimizing within-class scatter, but also avoid the singularity problem of the within class scatter matrix. experiments on the feret database show an encouraging recognition performance of the new algorithm.
feature extraction with genetic algorithms based nonlinear principal component analysis for face recognition. principal component analysis (pca) and linear discriminant analysis (lda) are two commonly used feature extraction techniques. in this paper, a nonlinear evolutionary weighted principal component analysis (ewpca) based on genetic algorithms is proposed. similar to lda, the ewpca maximizes the ratio of between-class variations to that of within-class variations, and achieves better classification performance than that of traditional pca. genetic algorithms are chosen as the searching method to select optimal weights for the ewpca. in face recognition, evolutionary facial feature obtained by performing ewpca is used as the representation of original face images. experimental results on orl and combo face databases prove that ewpca outperforms both pca, kernel pca and lda.
facial expression recognition based on fusion of multiple gabor features. in order to accomplish subject-independent facial expression recognition task, a multiple gabor features based facial expression recognition method is presented in this paper. different channels of gabor filters have different contributions on the facial expression recognition and reasonable combination of these features can improve the performance of a facial expression recognition system. nn based data fusion method is designed for facial expression recognition in this paper. experimental results show that the facial expression recognition rate can be improved by using multiple channel features and neural network fusion.
low resolution character recognition by image quality evaluation. the character image database plays an important role for the evaluation of a character recognition system. but there is no measure which tells the level of recognition difficulty of a given database. this paper proposes a novel approach for the low resolution character recognition, which fits the input character for the appropriate character database according to the input image quality. it is composed of two stems: character image quality evaluation, character recognition. firstly, it presents the gray distribution feature to evaluate the character image quality. secondly, according to the evaluation result the appropriate character database and recognition method are selected for the input character image which makes the classification have the higher probability of being the correct decision. experiment results demonstrate the proposed approach highly improved the performance of the degraded character recognition system.
winner update on walsh-hadamard domain for fast motion estimation. motion estimation (me) plays an important role in video compression. block-based me has been adopted in most video compression standards due to its efficiency. in this paper, we propose a novel and fast block-based me algorithm that is based on applying the winner-update search in the walsh-hadamard transform domain. due to the energy packing capability of the walsh-hadamard transform, the modified winner update procedure is performed only on a small number of most representative transform coefficients. in addition, our algorithm can skip the search at some locations based on the predicted sad of the current block. the superior performance of the proposed algorithm is demonstrated through experimental comparison with some representative motion estimation methods.
nearest intra-class space classifier for face recognition. in this paper, we propose a novel classification method, called nearest intra-class space (nics), for face recognition. in our method, the distribution of face patterns of each person is represented by the intra-class space to capture all intra-class variations. then, a regular principal subspace is derived from each intra-class space using principal component analysis. the classification is based on the nearest weighted distance, combining distance-from-subspace and distance-in-subspace,between the query face and each intra-class subspace. experimental results show that the nics classifier outperforms other classifiers in terms of recognition performance.
texture classification through directional empirical mode decomposition. this paper presents a method for texture classification through directional empirical mode decomposition (demd).although there have been many filtering based techniques proposed for texture retrieval, problems of non-adaptivity and redundancy are still hard to solve simultaneously.as a technique being introduced into signal processing recently, empirical mode decomposition (emd) is an adaptive and approximately orthogonal filtering process.to apply emd to texture classification, we propose a new method of extending 1-d emd to 2-d case called demd.the approach adaptively decomposes images into local narrow band ingredients-intrinsic mode functions (imfs) and extracts their features including frequency and envelopes.to improve its classification ability the fractal dimensions of the imfs are also considered. decomposition of several directions is computed for rotation invariance.experiments for textures in brodatz set and usc database indicate the effectiveness of our technique.
iris recognition based on dlda. iris feature extraction is very important for an iris recognition system. this paper focuses on iris feature extraction. in this paper we propose direct linear discriminant analysis (dlda) which combines with wavelet transform to extract iris feature. in our method, firstly, we apply wavelet decomposition to the normalized iris image whose size is 64×256 and just choose the coefficients of the approximation part of the second level wavelet decomposition to represent the iris image because this part contains main feature of the original iris image but the size of this part is only 16×64. and then make use of dlda to extract the iris feature from this approximation part. during classification, the euclidean distance is applied to measure the similarity degree of two iris classes. in the end of this paper, the proposed method was tested on the second version casia iris database. we evaluate the performance by equal error rate (eer) which is the point that the false match rate (fmr) is equal to false non-match rate (fnmr) in valve. the experiment shows that the eer of our method is about 1.44% which is lower than other methods such as principle component analysis (pca) and independent component analysis (ica) etc.
a new hybrid gmm/svm for speaker verification. this paper proposes a new combination approach between gaussian mixture model (gmm) and support vector machine (svm) by feature extraction based on adapted gmm for svm in text-independent speaker verification. because of excellent scalability, adapted gmm was used to extract a small quantity of typical feature vectors from large numbers of speech data for svm speaker verification. using this new combination approach, our speaker verification system performed significantly better than the current state-of-the-art gmm-ubm system on the nist'04 1side-1side database.
nonparametric background generation. a novel background generation method based on nonparametric background model is presented for background subtraction. we introduce a new model, named as effect components description (ecd), to model the variation of the background, by which we can relate the best estimate of the background to the modes (local maxima) of the underlying distribution. based on ecd, an effective background generation method, most reliable background mode (mrbm), is developed. the basic computational module of the method is an old pattern recognition procedure, the mean shift, which can be used recursively to find the nearest stationary point of the underlying density function. the advantages of this method are threefold: first, backgrounds can be generated from image sequence with cluttered moving objects; second, backgrounds are very clear without blur effect; third, it is robust to noise and small vibration. extensive experimental results illustrate its good performance.
occlusion robust face recognition with dynamic similarity features. in this paper, we present a new scheme for face recognition. the main idea is to represent the images with the similarity features against the reference set and to provide the relative match for two images. for any image, we first compute the similarities between it and all the reference images, and then we take these similarities as its feature. based on the similarity features, a linear discriminating classifier is constructed to recognize the querying image. inspired by research in cognitive psychology, the perceptual distance based dynamic similarity function is proposed to compute the similarity features. the proposed method can be regarded as a generalization of kernel discriminant analysis, and it can well deal with the nonlinear variations, especially occlusion. extensive experiments are conducted to show its performance and robustness to occlusion.
a novel volumetric shape from silhouette algorithm based on a centripetal pentahedron model. in this paper we present a novel volumetric shape from silhouette algorithm based on a centripetal pentahedron model. the algorithm first partitions the space with a set of infinite triangular pyramids derived from a geodesic sphere. then the pyramids are cut by silhouettes into a set of pentahedrons, which together constitute the centripetal pentahedron model of the visual hull. this process is accelerated by precomputed polar silhouette graphs (psgs) and reduced psgs. finally a mesh surface model is extracted by marching pentahedrons. our algorithm has the advantages of robustness, speediness and preciseness.
minimum enclosing and maximum excluding machine for pattern description and discrimination. this work addresses the description problem of a target class in the presence of negative samples or outliers. traditional support vector machines (svm) has strong discrimination capability to distinguish the target class but does not reject the uncharacteristic patterns well. the one-class svm, on the other hand, provides good representation for the class of interest but overlooks the discrimination issue between the class and outliers. this paper presents a new one-class classifier named minimum enclosing and maximum excluding machine (memem), which offers capabilities for both pattern description and discrimination. the properties of memem are analyzed and the performance comparisons using synthetic and real data are presented.
fingerprint reference point detection based on local axial symmetry. reference point detection is an important process for fingerprint analysis. in this paper, we propose a novel feature which is named local axial symmetry (las) and present an algorithm to calculate reference point of a fingerprint based on this kind of feature. experimental results demonstrate its feasibility, validity and the ability to detect reference points of all classes of fingerprints including arch-type fingerprints which is difficult to locate a stable reference point with other methods.
word extraction from on-line handwritten text lines. in this paper we investigate the word extraction task in on-line recognition of cursively handwritten text lines. for the segmentation we propose a method which is based on the assumption that the size of gaps between consecutive words may considerably vary, but humans usually leave more whitespace between two consecutive words than between two connected components that belong to the same word. we use several metrics known from off-line word segmentation for measuring the distances between two adjacent components. then we apply different procedures to get the initial threshold for segmentation. using these techniques we could significantly increase the segmentation rate compared to methods which are usually applied in on-line text recognition systems.
euclidean reconstruction of deformable structure using a perspective camera with varying intrinsic parameters. in this paper we present a novel approach for the 3d euclidean reconstruction of deformable objects observed by a perspective camera with variable intrinsic parameters. we formulate the non-rigid shape and motion estimation problem as a non-linear optimization where the objective function to be minimised is the image reprojection error. our approach is based on the observation that often some of the points on the observed object behave rigidly, while others deform from frame to frame. we propose to use the set of rigid points to obtain an initial estimate of the camera's varying internal parameters and the overall rigid motion. the prior information that some of the points in the object are rigid can also be added to the non-linear minimization scheme in order to avoid ambiguous configurations. results on synthetic and real data prove the performance of our algorithm even when using a minimal set of rigid points and when varying the intrinsic camera paremeters.
an illumination insensitive representation for face verification in the frequency domain. we present a comparison of several face representation methods from the point of view of their sensitivity to illumination changes. the sensitivity is measured in terms of the overlap of the distributions of normalized correlations used for inter class and intra class image comparisons. the result suggests, that better illumination invariance could be achieved in feature spaces in the frequency domain derived for a differentiated image rather than using the original input image.
evaluation of three optical flow-based observation models for tracking. in this paper, we study the use of optical flow as a characteristic for tracking. we analyze the behavior of three flow-based observation models for particle filter algorithms, and compare the results with those obtained using a well-known, gradient-based, observation model. although in theory, optical flow could be used directly to displace an object model, in practice, flow estimation techniques lack the necessary precision. in view of the fact that probabilistic tracking algorithms enable imprecise or incomplete information to be handled naturally, these models have been used as a natural way of incorporating flow information into the tracking.
approximation of digital curves using a multi-objective genetic algorithm. in this paper, a digital planar curve approximation method based on a multi-objective genetic algorithm is proposed. in this method, the optimization/exploration algorithm locates breakpoints on the digital curve by minimizing simultaneously the number of breakpoints and the approximation error. using such an approach, the algorithm proposes a set of solutions at its end. the user may choose his own solution according to its objective. the proposed approach is evaluated on curves issued from the literature and compared successfully with many classical approaches.
robust detection of region-duplication forgery in digital image. region duplication forgery, in which a part of a digital image is copied and then pasted to another portion of the same image in order to conceal an important object in the scene, is one of the common image forgery techniques. in this paper, we describe an efficient and robust algorithm for detecting and localizing this type of malicious tampering. we present experimental results which show that our method is robust and can successfully detect this type of tampering for images that have been subjected to various forms of post region duplication image processing, including blurring, noise contamination, severe lossy compression, and a mixture of these processing operations.
refining 3d models using a two-stage neural network-based iterative process. this paper presents a refinement method that supplements the 3d model construction process. the refinement method addresses the issue of using inaccurate 3d positional information to construct the 3d model. in the context of this paper, the inaccuracies in the 3d information come from a low-cost and low-precision range finder system. the core component of the refinement system is a neural network architecture termed ifosart that attempts to associate particular corrections to the 3d model given range and intensity information. results presented show the refinement system successfully reduces the inaccuracies in real-world 3d models.
active learning to recognize multiple types of plankton. this paper presents an active learning method which reduces the labeling effort of domain experts in multi-class classification problems. active learning is applied in conjunction with support vector machines to recognize underwater zooplankton from higher-resolution, new generation sipper ii images. most previous work on active learning with support vector machines only deals with two class problems. in this paper, we propose an active learning approach "breaking ties" for multi-class support vector machines using the one-vs-one approach with a probability approximation. experimental results indicate that our approach often requires significantly less labeled images to reach a given accuracy than the approach of labeling the least certain test example and random sampling. it can also be applied in batch mode resulting in an accuracy comparable to labeling one image at a time and retraining.
architectural design issues for bayesian contextual vision. sensor fusion technology has been so far developed for the fusion of camera and different sensors, e.g. radar, sonar, etc. the same techniques apply to integrating several vision algorithms into a multi-modular system. in this paper, we abstract our attempt on the matter and propose a uniform paradigm to integrate both "vision modules" directly observing targets (e.g. intruders in video surveillance) and "accessory modules" observing scene features that may trigger system adaptation to the current context. to be concrete, we completely develop a real example in re-designing a previous context-dependent video surveillance system.
design and implementation of a card reader based on build-in camera. with the availability of high-resolution cameras and increased computation power, it becomes possible to implement ocr applications such as business card reader in the mobile device. in this paper we introduced the design and implementation of a business card reader based on build-in camera. in order to deal with the challenge of limited resource in mobile device, we proposed a new method based on multi-resolution analysis of document images. this method improves computation speed and reduces memory requirement of the image-processing step by detecting the text areas in the downscaled image and then analyzing each detected area in the original image. for the ocr engine, we used a two-layer classifier to improve speed. our experiment gives satisfactory result.
a hybrid model for invariant and perceptual texture mapping. texture is an important visual feature for computer vision tasks. in applications such as image retrieval and computer image understanding, texture similarity should be measured in a manner that is invariant to texture scale and orientation, as well as consistent with human's perception. however, most existing computational features and similarity measures are not perceptually consistent. a solution is to map textures into an invariant and perceptual space such that similarity measured in the space is perceptually consistent. this paper presents a hybrid method, using convolutional neural network and svm, to perform the invariant and perceptual mapping. test results show that it's overall performance is better than that of an individual neural network and a svm.
conditional linear discriminant analysis. dimensionality reduction by means of linear discriminant analysis (lda) can generally lead to considerable improvements in classification accuracy and computation time. however, in supervised, pixel-based, image segmentation, the limiting factor of lda that it cannot extract more than k - 1 features (k the number of classes) often prevents successfully employing it as k is typically small. based on the observation that the kind of feature to extract should often depend on the kind of image structure that is in the vicinity, we propose to condition lda on auxiliary variables extracted from the manual segmentations (which are only available in the training phase). the conditioned fisher criteria obtained through this are subsequently combined to construct our final global fisher-like dimensionality reduction criterion. this conditional lda is capable of extracting more features than standard lda, which can considerably improve the segmentation accuracy as our experiments show.
static posterior probability fusion for signal detection: applications in the detection of interstitial diseases in chest radiographs. this work presents general signal detection schemes based on the static fusion of posterior probabilities. starting with the assumption that for every pixel in an image there is a posterior probability-indicating the probability of the presence or the absence of the signal to be detected, some well-known probability fusion schemes and generalizations thereof are proposed to come to an overall decision regarding the presence or absence of the signal. in addition to these well-known static fusion schemes-i.e.,voting, averaging, maximum rule, etcetera, a quantile-based combination rule is presented as well. the performance of the several rules is evaluated on two real-world, medical image analysis task. both tasks consider the computer-aided diagnosis (cad) of standard posteroanterior chest radiographs. more specifically, in the first task the general detection of interstitial diseases is studied, while in the second task the focus is on the detection of tuberculosis.
graph spectral approach for learning view structure. in this paper we explore how to represent object view-structure by embedding the neighbourhood graphs of feature points in a pattern-space. we adopt a graph-spectral approach. we use the leading eigenvectors of the graph adjacency matrix to define clusters of nodes. for each cluster, we compute vectors of cluster properties. we embed these vectors in a pattern-space using two contrasting approaches. the first of these involves performing principal components analysis on the covariance matrix for the spectral pattern vectors. the second approach involves performing multidimensional scaling on the l2 norm for pairs of pattern vectors. we demonstrate the both methods result in well-structured view spaces for graph-data extracted from 2d views of 3d objects.
local discriminant analysis. the main objective of the work presented here is to introduce a supervised, nonlinear dimensionality reduction technique which, performs well-known linear discriminant analysis in a local way and which is able to provide a powerful mapping with less computational effort than other nonlinear reduction methods. additionally, because of the close connection of the new approach to fisher's lda, it is more clear that it acts discriminatively, which is not immediately apparent from previous formulations. the method makes use of the optimal scoring framework advocated by hastie et al. and it is coined local discriminant analysis (eda).
unified model for omnidirectional vision using the conformal geometric algebra framework. this work presents the application of the unified model for handling diverse catadioptric mirrors using the conformal geometric algebra framewok. this framefork is well equiped with incidence algebra operations (duality, meet and join) necessary for reflecting and projecting geometric entities of the visual space through the mirror to the camera. in this paper we show that our mathematical reduces the algebraic burden, as a result the development of algorithms for omnidirectrional vision is easier and effective.
omnidirectional vision and invariant theory for robot navigation using conformal geometric algebra. the automatic landmark identification is very important in autonomous robot navigation tasks. in this work we use a monocular omnidirectional vision system to extract images features, and with help of the conformal geometric algebra (cga), we show how these features can be used to calculate projective and permutation p2-invariants. these p2-invariants represent scene sub-landmarks and a set of them characterize a landmark.
pattern matching by sequential subdivision of transformation space. pattern matching is a well-known pattern recognition technique. this paper proposes a novel pattern matching algorithm that searches transformation space by sequential subdivision. the algorithm subdivides the transformation space in depth-first manner by conducting boolean operations on the constraint sets that are defined by pairs of template points and target points. for constrained polynomial transformations that have no more than two parameters on each coordinate, a constraint set can be represented as a 2d polygon or a cartesian product of 2d polygons. then, the boolean operations can be computed through generic polygon clipping algorithms. preliminary experiments on randomly generated point patterns show that the algorithm is effective and efficient under practical conditions.
region of interest watermarking based on fractal dimension. an image watermarking algorithm that aims to protect the region of interest (roi) is proposed based on fractal dimension. the roi in an image is determined by the user, and is mapped to the subband of wavelet decomposition. a visually significative watermark is scaled according to the size of the roi. embedding is completed by enforcing the relationship between the subband coefficients and approximate coefficients. the parameters and strength is determined according to the feature analysis to the image which is based on fractal dimension. extraction is blind that requires neither the host image nor the original watermark. experimental results show that this algorithm can robustly resist cropping, patching, and compression.
efficient monocular 3d reconstruction from segments for visual navigation in structured environments. we present an algorithm for performing real time 3d reconstructions of indoor scenes from a single image. the technique has been successfully used in indoor robot visual navigation applications. to solve the depth ambiguity inherent to the process of image formation, the procedure interprets the scene in terms of a set of vertical planes in arbitrary orientations (e.g. walls and doors) lying on a common horizontal plane (the floor). interpretation is based on a zone classification algorithm that divides the image into a set of disjoint patches, each one belonging to a different plane. in order to make the reconstruction possible in real time, we use a very fast feature extraction algorithm based on robust extraction of the most salient segments of the scene, augmented with local color information. the extracted segments help in both the construction of the zone classification machine and the posterior 3d reconstruction, which is in turn based on a powerful single image projective geometry result.
a physics-motivated approach to detecting sky in photographs. sky is among the subject matters frequently seen in photographs and useful for image understanding, processing, and retrieval. we propose a novel approach to sky detection based on color classification, region extraction, and physics-motivated sky signature validation. first, the color classification is performed to generate a belief map of sky colored pixels. next, connected components are extracted from the sky color belief map to generate candidate sky regions. finally and most importantly, we determine the orientation of a candidate sky region, analyze traces within the region based on a physics-motivated model, and compute the sky belief of the region. for a database of 1800 amateur photos of variable content and quality, the recall ratte is 96% with a precision rate of 98% on a per region basis.
context-sensitive bayesian classifiers and application to mouse pressure pattern classification. in this paper, we propose a new context-sensitive bayesian learning algorithm. by modeling the distributions of data locations by a mixture of gaussians, the new algorithm can utilize different classifier complexities for different contexts/locations and, at the same time, keep the optimality of bayesian solutions. this algorithm is also an online learning algorithm, efficient in training, and easy for incorporating new knowledge from data sets available in the future. we apply this algorithm to detecting computer-user mouse pressure patterns during episodes likely to be frustrating to the user. by modeling user identity as hidden context, this algorithm achieves on average 10.6% user-independent test error rate.
graph manifolds from spectral polynomials. gaph structures have proved computationally cumbersome for pattern analysis. the reason for this is that before graphs can be converted to pattern vectors, correspondences must be established between the nodes of structures which are potentially of different size. to overcome this problem, in this paper we turn to the spectral decomposition of the laplacian matrix. we show how the elements of the spectral matrix for the laplacian can be used to construct symmetric polynomials that are permutation invariants. the co-efficients of these polynomials can be used as graph-features which can be encoded in a vectorial manner. we explore whether the vectors of invariants canbe embedded in a low dimensional space using a number of alternative strategies including principal components analysis (pca), multidimensional scaling (mds) and locality preserving projection (lpp).
an efficient automatic redeye detection and correction algorithm. a fully automatic redeye detection and correction algorithm is presented to address the redeye artifacts in digital photos. the algorithm contains a redeye detection part and a correction part. the detection part is modeled as a feature based object detection problem. adaboost is used to simultaneously select features and train the classifier. a new feature set is designed to address the orientation-dependency problem associated with the haar-like features commonly used for object detection design. for each detected redeye, a correction algorithm is applied to do adaptive desaturation and darkening over the redeye region.
novel adaptive nearest neighbor classifiers based on hit-distance. in this paper, a novel idea of distance, hit-distance, was firstly introduced to generalize the representational capacity of available prototypes. novel adaptive nearest neighbor classifiers based on hit-distance were then proposed. experiments were performed on 8 benchmark datasets from the uci machine learning repository. it was shown that the proposed classifiers performed much better than the classical nearest neighbor classifier (nn) and the nearest feature line method (nfl), the nearest feature plane method (nfp), the nearest neighbor line method (nnl) and the nearest neighbor plane method (nnp).
self-calibration of a camera from video of a walking human. analysis of human activity from a video camera is simplified by the knowledge of the camera's intrinsic and extrinsic parameters. we describe a technique to estimate such parameters from image observations without requiring measurements of scene objects. we first develop a general technique for calibration using vanishing points and vanishing line. we then describe a method for estimating the needed points and line by observing the motion of a human in thescene. experimental results, including error estimates, are presented.
semantic interpretation of object activities in a surveillance system. activity analysis and semantic interpretation of tracked targets in a dynamic image sequence has recently attracted more attentions in computer vision. in this paper, a framework for semantic interpretation of vehicle and pedestrian's behaviors is proposed for practical applications in visual traffic surveillance. the trajectories recorded in the visual tracking process are analyzed using dynamic clustering and classification on which high level semantic interpretation is based. experimental results are presented to illustrate the performance of the proposed algorithm.
face detection based on hierarchical support vector machines. this paper presents a method of detecting faces based on hierarchical support vector machines (svm). the hierarchical svm classifier is composed of a combination of linear svm (clsvm) and a nonlinear svm. in training stage, the nonlinear svm is trained under theconstraint of the clsvm to select more effective non-face samples. in detection stage, the clsvm is used to fast exclude most non-/aces in images and the nonlinear svm is used to verify possible face candidates further. experimental result on several databases demonstrates the feasibility of the method.
adaptive word style classification using a gaussian mixture model. in this paper, we present a new approach to detect bold and italic words in scanned documents. under the assumption that ocr results are available, features used for classification are selected automatically using feature selection. for each scanned page, a gaussian mixture model is constructed for characters with the same character code, and word styles are determined using a weighted majority vote. we applied this method to a variety of documents and compared the results with current commercial ocr software that provides style information. the experimental results show that our method performs better.
image and feature co-clustering. the visual appearance of an image is closely associated with its low-level features. identifying the set of features that best characterizes the image is useful for tasks such as content-based image indexing and retrieval. in this paper, we present a method which simultaneously models and clusters large sets of images and their low-level visual features. a computational energy function suited for co-clustering images and their features is first constructed and a hopfield model based stochastic algorithm is then developed for its optimization. we apply the method to cluster digital color photographs and present results to demonstrate its usefulness and effectiveness.
chaining planar homographies for fast and reliable 3d plane tracking. this paper addresses the problem of tracking a 3d plane over a sequence of images acquired by a free moving camera, a task that is of central importance to a wide variety of vision tasks. a feature-based method is proposed which given a triplet of consecutive images and a plane homography between the first two of them, estimates the homography induced by the same plane between the second and third images, without requiring the plane to be segmented from the rest of the scene. thus, the proposed method operates by "chaining" (i.e. propagating) across frames the imageto- image homographies due to some 3d plane. the chaining operation represents projective space using a "plane + parallax" decomposition, which permits the combination of constraints arising from all available point matches, regardless of whether they actually lie on the tracked 3d plane or not. experimental results are also provided.
sparse bayesian regression for head pose estimation. this paper presents a high performance ........ pose estimation system based on the newly-proposed sparse bayesian regression technique (relevance vector machine, rvm) and sparse representation of facial patterns. in our system, after localizing 20 key facial points, sparse features of these points are extracted to represent facial property, and then..rvm is utilized to learn the relation between the sparse representation and yaw and pitch angle. because rvm requires only a very few kernel functions, it can guarantee better generalization, faster speed and less memory in a practical implementation. to thoroughly evaluate the performance of our system, we compare it with conventional methods such as cca, kernel cca, svr on a large database; in experiments, we also investigate the influence of the facial points localization error on pose estimation by using manually labelled results and automatically localized results separately, and the influence of different features on pose estimation such as geometrical features and texture features. these experimental results demonstrate that our system can estimate face pose more accurately, robustly and fast than those based on conventional methods.
a graph-based approach to corner matching using mutual information as a local similarity measure. corner matching constitutes a fundamental vision problem that serves as a building block of several important applications. the common approach to dealing with this problem starts by ranking potential matches according to their affinity, which is assessed with the aid of window-based intensity similarity measures. then, actual matches are established by optimizing global criteria involving all potential matches. this paper puts forward a novel approach for solving the corner matching problem that uses mutual information as a window similarity measure, combined with graph matching techniques for determining a matching of corners that is globally optimal. experimental results illustrate the effectiveness of the approach.
using b-spline curves for hand recognition. the b-spline curve and surface provide an accurate tool to record object shape. we present a biometric identification system through hand geometry measurements by using b-spline curves. we use 4 b-spline curves to fit with fingers (except thumb) from a single hand image for a single person. then we store these 4 curves as well as other geometry measurements of the hand as the "signature" of that person into the database. by computing the differences between the curves from database hand images and the curves from the query hand image using the point projection method, we are able to verify/identify the person by locating the closest database hand image to the query hand image.
evaluation of tracking reliability metrics based on information theory and normalized correlation. the efficiency of three tracking reliability metrics based on information theory and normalized correlation is examined in this paper. the two information theory tools used for the metrics construction are the mutual information and the kullback-leibler distance. the metrics are applicable to any feature-based tracking scheme. in the context of this work they are applied for comparison purposes on an object tracking scheme using multiple feature point correspondences. experimental results have shown that the information theory based metrics perform better than the normalized correlation one.
pruning the vocabulary for better context recognition. language independent 'bag-of-words' representations are surprisingly effective for text classification. the representation is high dimensional though, containing many non-consistent words for text categorization. these non-consistent words result in reduced generalization performance of sub-sequent classifiers, e.g., from ill-posed principal component transformations. in this communication our aim is to study the effect of reducing the least relevant words from the bag-of-words representation. we consider a new approach, using neural network based sensitivity maps and information gainfor determination of term relevancy, when pruning the vocabularies. with reduced vocabularies documents are classified using a latent semantic indexing representation and a probabilistic neural network classifier. reducing the bag-of-words vocabularies with 90%-98%, we find consistent classification improvement using two mid size data-sets. we also study the applicability of information gain and sensitivity maps for automated keyword generation.
joint distributions based on dfb and gaussian mixtures for evaluation of style similarity among paintings. in this paper, we studies the ability of joint statistical information of directional subbands in evaluating style similarity among chinese ink paintings by employing the gaussian mixture models with different mixture components. the optimal number of mixture components can be automatically learned from the training features by pruning the mixture models. two types of gaussian mixture models are built on two different sets of features: one is based on the high-order statistical moments of directional subbands; the other one is based on the parameters of generalized gaussian density (ggd) of the marginal distributions of directional subbands. the experimental results show that the accuracy of the model based on the parameters of ggd is better than that of the model based on the high-order statistical moments.
fast image retrieval based on equal-average equal-variance k-nearest neighbour search. this paper presents two fast schemes to speed up the retrieval process for conventional content-based image retrieval systems. the traditional features such as color and invariant histograms are extracted offline from each image to compose a feature vector. all these feature vectors construct the feature database. then the system performs the online retrieval based on this database as soon as possible. in the case of a small number of returned images, an equal-average equalvariance k nearest neighbour search (eeknns) method is used to speed up the retrieval process. in the case of a large number of returned images, an iterative eeknns (ieeknns) method is given. experimental results show that the proposed retrieval methods can largely accelerate the retrieval process while guaranteeing the same recall and precision.
shapes modeling of 3-d objects based on a hybrid representation using extended b-spline surface model. this paper presents a method for shapes modeling of 3-d objects using a b-spline surface model based on a projection expression. the surface model is locally defined on each patch that is effectively arranged depending on object shapes. in order to assure the continuity of the resultant surface, a nurbs (non-uniform rational b-splines) surface with embedding functions is employed. consequently, this model can be considered as a hybrid model that is consist of polygon patches and nurbs surfaces. in order to estimate the surface function, a regularization problem is solved by an iterative algorithm. in the algorithm, since the domainswhere the surface has to be estimated are restricted to the only error patches, the computation time can be reduced. howevel; the accuracy of estimation is never inferior sincea subdivision operation ofnurbs is employedfor the other domains.
accurate 3d scanning of swaying human body parts by one projection based on oimp technique. three-dimensional (3d) shape measurement based on spatial pattern projection (coded structured light projection) technique has been used in practical applications. however, multiple pattern projection is required for the measurement, and so application to a swaying human body part is difficult. a new technique for measuring the 3d topography of swaying human body parts or a human face using optimal intensity- modulation projection (oimp) technique is presented. since the proposed technique can correctly detect the stripe order of the projected pattern through a single pattern projection and double image capture, swaying human body parts or a human face can be measured with an accuracy of approximately 0.5 mm.
practical 3-d shape measurement using optimal intensity-modulated projection and intensity-phase analysis techniques. in the field of 3-d image measurement, a technique based on stripe pattern projection and observation image intensity analysis is expected to be able to detect several stripes by a single projection. it is necessary to increase the stripe number of the projection pattern in order to improve the measurement accuracy of depth distance. however, when the stripe number is increased, the difference of the intensity between stripes will be reduced and stripe detection will become difficult. in order to improve the detection accuracy of the stripe order and shorten the 3-d measurement time, we use the optimal intensity-modulation projection (oimp) technique, and in order to improve the depth distance measurement accuracy, we propose an intensity-phase analysis (ipa) technique. in the proposed ipa technique, the observation pattern be segmented by the intensity of the intensity-modulated stripe, and in every segmentation the depth distance of all pixels are obtained by phase analysis. by using a combination of the oimp and ipa techniques, high-speed (single projection and double image captures) and high-accuracy (error less than 0.1%) practical 3-d shape measurement can be realized.
robust head pose estimation using lgbp. in this paper, we introduce a novel discriminative feature which is efficient for pose estimation. the multi-view face representation is based on local gabor binary patterns( lgbp) and encodes the local facial characteristics in to a compact feature histogram. in lgbp, gabor filters can extract the feature of the orientation of head and local binary pattern(lbp) can extract the features of facial local orientation. to keep the spatial information of the multi-view face images, lgbp is operated on many subregions of the images. the combination of them can represent well and truly the multi-view face images. considering the derived feature space, a radial basis function(rbf) kernel svm classifier is trained to estimate pose. extensive experiments demonstrate that the facial representation can be effective for pose estimation. is a face. the experimental results show that the proposed method is promising for the detection of occluded faces.
three-dimensional model based face recognition. the performance of face recognition systems that use two-dimensional (2d) images is dependent on consistent conditions such as lighting, pose and facial expression. we are developing a multi-view face recognition system that utilizes three-dimensional (3d) information about the face to make the system more robust to these variations. this paper describes a procedure for constructing a database of 3d face models and matching this database to 2.5d face scans which are captured from different views, using coordinate system invariant properties of the facial surface. 2.5d is a simplified 3d (x, y, z) surface representation that contains at most one depth value (z direction) for every point in the (x, y) plane. a robust similarity metric is defined for matching, based on an iterative closest point (icp) registration process. results are given for matching a database of 18 3d face models with 113 2.5d face scans.
crack defect detection and localization using genetic-based inverse voting hough transform. in this paper we propose a genetic-based inverse voting hough transform (gbivht) method to detect buried crack defects in engineering structures. the method is applied to b-scan images obtained according to the ultrasonic time of flight diffraction technique. in these image representations of the ultrasound data, crack defects are characterized by multiple arcs of diffraction that can be approximated by a parabolic model. thus, the crack defect detection problem in non-destructive inspection of engineering structures is transformed into a parabola detection and localization on b-scan images. in the proposed gbivht method, the local peak detection problem of conventional ht is converted into a parameter optimization problem that operates directly on the b-scan images. the optimization task is done using the well-knowngenetic algorithms. our main goals are an accurate detection of the parabolas while circumventing the computational complexity and huge storage problem tied to conventional ht.
periodic nonlinear principal component neural networks for humanoid motion segmentation, generalization, and generation. in an experiment with a soccer playing robot, periodic temporally-constrained nonlinear principal component neural networks (nlpcnns) are shown to characterize humanoid motion effectively by exploiting fundamental sensorimotor relationships. each network learns a periodic or transitional trajectory in a phase space of possible actions, and thus abstracts a kind of protosymbol. nlpcnns can play a key role in a system that learns to imitate people, enabling a robot to recognize the behavior of others because it has grounded that behavior in terms of its own bodily movements.
camera calibration from two shadow trajectories. we introduce an efficient method for recovering the camera parameters automatically from the cast shadows of two 3d points observed over time. compared to previous related work, our method has less restrictions in the sense that object-to-shadow correspondences do not have to be available in the image. we demonstrate how the horizon line may be recovered from only shadow points, and how the camera intrinsic and extrinsic parameters are determined using the pole-polar relationship and minimizing the algebraic distance of the principal point. the approach is fully validated on both synthetic and real data, and tested against various sources of error. we finally present an application to metrology from shadows only - i.e. when the object is not visible in the image.
a graph decomposition approach to least squares attributed graph matching. in this paper, a graph decomposition model is combined with recent developments in least squares methods for matching attributed graphs. in particular, we show how this approach improves the robustness of graph matching and also reveals important structural similarities between subgraphs of target and model graphs.
segmentation of range data based on a stochastic clustering method with competitive process. in this paper, a stochastic clustering method with a competitive process is proposed to segment significantly the entire circumferential range data. the segmentation technique is utilized as the preprocessing of 3-d shape modeling so that the modeling can be more easily achieved for the object that has arbitrary topology, in which the data points are divided into the several subsets that represent the 3-d shapes of different quadric surfaces. the clustering method is implemented by evaluating a distance computed between each data point and each quadric surface. furthermore, it consists of creation and competitive processes in order to obtain the desirable clusters. consequently, since the only appropriate clusters are remaining, the segmentation can be achieved by assigning the data points to these clusters.
the bbn byblos japanese ocr system. the bbn byblos ocr system implements a script-independent methodology for ocr using hidden markov models (hmms). we have successfully ported the system to arabic, pashto, english, and chinese. in this paper, we discuss our recent effort in configuring the system to perform recognition of noisy machine printed japanese documents. the data for our experimentation was taken from the university of washington (uw-ii) japanese ocr corpus and the ldc japanese business news supplement corpus. we evaluated the performance of a whole-character configuration in which each character was modeled using a separate hmm. as in the case of our chinese ocr system [multilingual machine printed ocr], we also used a sub-character modeling approach[porting the bbn byblos ocr system to new languages] in which each japanese character was spelled using a shared set of automatically generated sub-characters. we experimentally evaluated the performance of different sub-character clusters as well as different hmm topologies to identify the best overall system configuration. on a fair test using noisy/degraded images from the uw-ii corpus, the best sub-character configuration resulted in a character error rate of 20.13%. on relatively cleaner data, consisting of scanned newspaper images, the system delivered an error rate of 7.85%. using a whole-character configuration the corresponding error rates were 11.94% and 4.55% respectively.
a new structural constraint and its application in wide baseline matching. we introduce a new structural constraint that can be used for matching points in image pairs taken from a wide baseline. no assumption is made about the geometry of the 3d points or of surfaces in the scene, nor about the location or orientation of the cameras. this structural constraint can be used to reduce the search space when matching a number of feature points in two images, eliminating the risk of selecting a matching that is provably wrong because unrealizable.
a generic method for eager interpretation of on-line handwritten structured documents. in this paper, a new approach for on-line handwritten structured document interpretation is presented. it aims at interpreting the strokes progressively. the major component of our approach is a flexible formalism for the recognition of the document elements. its originality is the modelling of the document global structure. the system then drives dedicated recognizers and looks only for the likely symbols depending on the document structural context in which that element is located. moreover, the formalism defines a "canonical on-line signal form" of the recognizer entries to facilitate the interpretation process which is then more robust and more efficient. to highlight its genericity, this approach has been used to design two pen-based prototypes, for musical score editing and for graph editing.
multilinear principal component analysis of tensor objects for recognition. in this paper, a multilinear formulation of the popular principal component analysis (pca) is proposed, named as multilinear pca (mpca), where the input can be not only vectors, but also matrices or higher-order tensors. it is a natural extension of pca and the analogous counterparts in mpca to the eigenvalues and eigenvectors in pca are defined. the proposed mpca has wide range of applications as a higher-order generalization of pca. as an example, mpca is applied to the problem of gait recognition using a novel representation called eigentensorgait. a gait sequence is divided into half gait cycles and each half cycle, represented as a 3rd-order tensor, is considered as one data sample. experiments show that the proposed mpca performs better than the baseline algorithm in human identification on the gait challenge data sets.
lesion detection using morphological watershed segmentation and modelbased inverse filtering. in this paper, we present a method that detects lesions in two-dimensional (2d) cross-sectional brain images. use of the morphological watershed segmentation technique localizes shape variation in the gray level distribution of brain images and, in turn, identifies the regions with abnormal shape and/or texture structure. the detected brain areas are then subjected to a model-based inverse filtering to determine their physiological characteristics whether they are lesions or other types of anomalies. the proposed algorithm was tested on different images of "the whole brain atlas" database [13]. the experimental results have produced 90% classification accuracy in processing 10 arbitrary images, representing different kinds of brain lesion.
separating color and pattern information for color texture discrimination. the analysis of colored surface textures is a challenging research problem in computer vision. current approaches to this task can be roughly divided into two categories: methods that process color and texture information separately and those that utilize multispectral texture descriptions. motivated by recent psychophysical findings, we find the former approach quite auspicious. we propose the use of complementary color and texture measures that are combined on a higher level, and empirically demonstrate the validity of our proposion using a large set of natural color textures.
word spotting in chinese document images without layout analysis. an approach to searching user-specified words/phrases in chinese document images, without the requirements of layout analysis, is proposed in this paper. bounding boxes of chinese character images are fir st determined using connected component analysis. next, a suitable character from the user-specified word/phrase is chosen as the initial character to search for a matching candidate in the document. once a matched candidate is found, its adjacent characters in the horizontal and vertical directions are examined for matching with other corresponding characters in the user-specified word/phrase, subject to the constraints of positional relation and size similarity. the character matching is done in two stages. the coarse matching is carried out based on the stroke density features. a weighted hausdorff distance (whd) is proposed for the second matching phase. experimental results show that the proposed method can effectively search the user-specified chinese word/phrase from horizontal or vertical text lines of document images.
an efficient features - based license plate localization method. this paper presents a feature-based license plate localization algorithm that copes with multi-object problem in different image capturing conditions. the proposed algorithm is robust against illumination, shadow, scale, rotation, and weather condition. it extracts license plate candidates using edge statistics and morphological operations and removes the incorrect candidates according to the determined features of license plates. we have formed a rather complete database of 269 images in different conditions. the proposed algorithm successfully detecteds the accurate location of the license plates in 96.5% cases, which outperforms the other available approaches in the literature.
document flattening through grid modeling and regularization. for document images captured by a digital camera, perspective and geometric distortions make it hard to recognize the document content properly. in this paper, we propose an integrated document restoration technique, which is capable of removing perspective and geometric distortions, and producing a flattened and fronto-parallel text image that is friendly to the generic ocr systems. the proposed document restoration is accomplished through grid modeling, which divides camera images into multiple quadrilateral grids using vertical text directions and the x lines and base lines. the global distortions are then removed through grid regularization that transforms the quadrilateral grids together with the pixel contents to the regular square grids. experimental results show the proposed method is fast and easy for implementation.
the influence of the noise in the restoration of solar radio images using adaptive regularization techniques based on clustering. this article describes the efficiency analysis of the new restoration algorithm applied to solar radio images and the influence that an additive noise has in the roughness classification process of the degraded image pixels. as the deconvolution problems are ill-conditioned, small disturbances, caused by the noise can imply in great variations in the estimate of the solution of the problem. therefore, several simulations were performed to evaluate the efficiency of the proposed algorithm in cases that the noise exerts significant influence in the result of the processing.
camera text recognition based on perspective invariants. as camera resolution increases, high-speed non-contact text capture through a digital camera is opening up a new channel for document capture and understanding. unfortunately, perspective and geometric distortions in camera image of documents make it hard to recognize the document content properly. in this paper, we propose a character recognition technique, which is capable of recognizing camera text lying over a planar or smoothly curved surface in perspective views. in our proposed method, a few perspective invariants including character ascender and descender, centroid intersection numbers, and water reservior are first detected. camera texts are then recognized using a classification and regression tree (cart) structure. experimental results show our method is fast and improves recognition performance greatly.
dense estimation of surface reflectance properties based on inverse global illumination rendering. in augmented virtuality, estimating object surface reflectance properties is important when rendering objects under arbitrary illumination conditions. however, faithfully estimating surface reflectance properties is difficult for objects having interreflections. the present paper describes a new method for densely estimating the non-uniform surface reflectance properties of real objects constructed of convex and concave surfaces having diffuse and specular interreflections. the registered range and surface color texture images were obtained using a laser rangefinder. in the proposed method, the light positions are first determined in order to take color images, which are then used to discriminate diffuse and specular reflection components of surface reflection. surface reflectance parameters are then estimated based on an inverse global illumination rendering. experiments were conducted to reveal the usefulness of the proposed method.
dense estimation of surface reflectance properties of objects with interreflections. in augmented virtuality which virtualizes real objects to construct a mixed reality environment, it is important to estimate object surface reflectance properties to render objects under arbitrary illumination conditions. the authors developed a method to estimate reflectance properties ofobject surfaces densely. however, it was difficult to estimate surface reflectance properties faithfully for objects with interreflections. this paper describes a new method of densely estimating non-uniform surface reflectance properties of real objects constructed of convex and concave surfaces with interreflections. we use registered range and surface color texture images obtained by a laser range finder. the proposed method first determines positions oflight to take color images for discriminating diffuse and specular reflection components of surface reflection. then, surface reflectance parameters are estimated based on radiosity. experiments show the usefulness of the proposed method.
a target detection method in range-doppler domain from sar echo data. the direct evidence of radar target recognition is the backscatter energy and its distribution of objects, which is concluded by imaging process of synthetic aperture radar (sar) in the two-dimension image domain. so the issues about automatic target recognition (atr) of sar are often a "post-process" following sar imaging. a method of target detection in the state of non-imaging based on analyzing the features of all kinds of targets on sar echo data is presented in this paper, where the targets are detected in range-doppler domain (rdd). based on analysis of target features in rdd, an algorithm of target detection in a rdd image is developed. the experimental results indicate the validity of the algorithm for special kinds of target detection. the algorithm is simple, able to recurrent, easy for real-time processing and hardware implementation. it can also apply to getting target alarm with real-time sar data forthe pre-selected targets and do the imaging process selectively at the same time.
a pde-based method for optical flow estimation. in this paper, we proposed a new method for accurate optical flow estimation. the significance of this work is twofold. first in this paper we showed that the optical flow estimation could be viewed as a diffusion-reaction process (pde-based) instead of a variational problem of minimizing some energy functions. the minimization often need the corresponding regularizer be restricted to some forms with convex and differentiable in view of convergence and the euler-lagrange equation. second, we adopted coherence enhancing scheme as the diffusion part of the diffusion-reaction equation to encourage smoothing along motion boundaries and preserving them. qualitative and quantitative results for synthetic and real-world scenes demonstrate that the new method can produce an accurate result.
view-based 3-d object recognition using shock graphs. the shock graph is an emerging shape representation for object recognition, in which a 2-d silhouette is decomposed into a set of qualitative parts, captured in a directed acyclic graph. although a number of approaches have been proposed for shock graph matching, these approaches do not address the equally important indexing problem. we extend our previous work in both shock graph matching and hierarchical structure indexing to propose the first unified framework for view-based 3-d object recognition using shock graphs. the heart of the framework is an improved spectral characterization of shock graph structure that not only drives a powerful indexing mechanism (to retrieve similar candidates from a large database), but also drives a matching algorithm that can accommodate noise and occlusion. we describe the components of our system and evaluate its performance using both unoccluded and occluded queries. the large set of recognition trials (over 25,000) from a large database (over 1400 views) represents one of the most ambitious shock graph-based recognition experiments conducted to date.
a hybrid recognition scheme based on partially labeled som and mlp. we propose a hybrid system for bangla handwritten numeral recognition based on partially labeled two-layer som and mlp classifiers. partially labeled mechanism is introduced to the kohonen's som for reducing recognition error rate, and two-layer structure is applied for improving the performance of the som classifier. the directional and density features are utilized in our system, and the partially labeled som is applied first. in the case that the character cannot be recognized by the partially labeled som, it will be feed to a multi-layer perceptron classifier for further processing. the experiments on the bangla handwritten numeral samples captured from real envelopes have found that the hybrid system achieves 96.7% correct recognition rate.
augmented lagrangian approach for projective reconstruction from multiple views. in this paper, we propose a new factorizationbased algorithm for projective reconstruction by minimizing the 2d reprojection error in multiple images. reformulating the projective reconstruction problem into a constrained minimization one, we estimate the projective depths, the projection matrix and the projective motion together by the solving a sequence of unconstrained minimization problems using the augmented lagrangian method. the proposed algorithm is ready to handle missing data and it is guaranteed to converge more robustly and rapidly than the algorithm of [6].
symbolic graph matching using the em algorithm and singular value decomposition. this paper describes an efficient algorithm for inexact graph matching. the method is purely structural, that is, it uses only the edge or connectivity structure of the graph and does not draw on node or edge attributes. we make two contributions: 1) commencing from a probability distribution for matching errors, we show how the problem of graph matching can be posed as maximum-likelihood estimation using the apparatus of the em algorithm; and 2) we cast the recovery of correspondence matches between the graph nodes in a matrix framework. this allows one to efficiently recover correspondence matches using the singular value decomposition. we experiment with the method on both real-world and synthetic data. here, we demonstrate that the method offers comparable performance to more computationally demanding methods
a novel caption extraction scheme for various sports captions. the study proposes a novel scheme to extract various captions in sports videos. a caption detection process based on an iteratively temporal averaging technique is used to automatically detect and locate a caption region in a series of video frames. moreover, a caption identification approach is used to classify some caption candidates into one of the caption types in order to extract accurately the contents of the caption rather than a projection-based segmentation process. experimental results show that the proposed caption extraction approach is robust for generalizing the learning knowledge to identify various sports captions.
activity recognition from silhouettes using linear systems and model (in)validation techniques. in this work we propose a model (in)validation approach to gait recognition, using a system that tries to discriminate specific activities of people. the recognition process departs from an abstraction obtained from video image sequences for different activities performed by different people, by first using a suitable representation for each frame and for each frame sequence. for each frame two commonly used models for describing silhouettes are employed: fourier descriptors and vectors of widths. then each sequence is modeled as a linear time invariant (lti) system that captures the dynamics of the evolution of the frame description vectors in time. finally a standard classification tool, svm, is used to recognize activities using similarity measures obtained through model (in)validation. the main contribution of this work is the provision of an activity recognition model and the performance evaluation of this model using two different feature spaces.
singer identification based on vocal and instrumental models. in this paper, we propose a novel method to identify the singer of a query song from the audio database. the database contains over 100 popular songs of solo singers. the rhythm structure of the song is analyzed using our proposed rhythm tracking method and the song is segmented into beat space time frames, where within the beat space time length the harmonic structure is quasi stationary. this inter-beat time resolution of the song is used for both feature extraction and training of the classifiers (i.e. support vector machine (svm) for vocal/instrumental boundary detection and gaussian mixture models (gmms) for modeling the singer). combining the instrumental music similarities in the songs of the same singer with the vocal model can improve the identification of the singer with an accuracy of over 87%.
web-based evaluation and deployment of pattern recognizers. this paper describes a framework for the automatic web-based evaluation and deployment of pattern recognizers. several usage modes are identified and the issues and tradeoffs involved in designing web-based evaluation systems are discussed. the system operates by exchanging xml messages between a recognition client and an evaluation server. http post is used for message exchange, which works through most firewalls.to use the system a researcher downloads a simple evaluation client, and then uses this client to invoke their recognizer. the recognizer must implement a simple problem-specificinterface. the system is illustrated with the aid of a sequence recognition example.
sequence recognition with scanning n-tuple ensembles. the scanning n-tuple classifier (snt) is a fast and accurate method for classifying sequences.applications include both on-line and off-line hand-written character recognition.snts have conventionally been trained using maximum likelihood parameter estimation.this paper describes a disciminative training rule that can be applied to ensembles of snts.results demonstrate a significant improvement for the discriminative ensemble method.for comparison purpose we also implemented a support vector machine (svm) operating in the sequence domain.we tested each method on a chain-coded version of the mnist hand-written digit dataset.the snt is not quite as accurate as the svm, but is much faster both in training and recognition.
gabor wavelet correlogram algorithm for image indexing and retrieval. in this paper, a new algorithm called gabor wavelet correlogram (gwc) is proposed for image indexing and retrieval. gwc is an effort to extend our former wavelet correlogram algorithm by introducing rotation invariant features using gabor wavelets. we also present some ideas in order to handle effectively the redundancy problem due to non-orthogonal decomposition of gabor wavelets. additionally, we use an optimized weighted relative distance measure to improve the retrieval performance. the retrieval results obtained by applying gwc to a 1000 image database demonstrated significant improvements in rank, precision, and recall compared to the wavelet correlogram and enhanced wavelet correlogram algorithms.
video modelling and segmentation using gaussian mixture models. this paper describes a new approach to the video modelling and segmentation problem using gaussian mixture model descriptors. these have several advantages over conventional, histogram-based techniques, including: a rigorous statistical basis; the possibility of encoding spatial, colour, texture and motion features in a unified system; and the ability to trade off accuracy of representation against data volume. after a brief introduction to the class of models, results are presented to show their efficacy.
intelligibility of children with cleft lip and palate: evaluation by speech recognition techniques. cleft lip and palate (clp) may cause functional limitations even after adequate surgical and non-surgical treatment, speech disorder being one of them. until now, an objective means to determine and quantify the intelligibility does not exist. an automatic speech recognition system was applied to 31 recordings of clp children who spoke a german standard test for articulation disorders. the speech recognition system was trained with normal adult speakers' and children's speech. a subjective evaluation of the intelligibility was performed by a panel of 3 experts and confronted to the automatic speech evaluation. the automatic speech recognition yielded word accuracies between 1.2% and 75.8% (48.0% ± 19.6%) with sufficient discrimination. it complied with experts' rating of intelligibility. thus we show that automatic speech recognition serves as a good means to objectify and quantify global speech outcome of children with clp.
approximate nearest neighbor search using a single space-filling curve and multiple representations of the data points. in this work, a fast approximate nearest neighbour search algorithm using single space-filling curve (spfc) mapping and a set of synthetic prototype representations is presented. the results are comparable to a multiplespacefilling scheme, but achieving a much faster execution time, since computing multiple transformations and spfc mapping's is avoided, at the expense of having a more densely populated one-dimensional representation of the data-set. the advantages and limitations of the model are discussed, and an experimental evaluation with synthetic data and with a large, real high-dimensional optical character recognition data-set is presented.
fvc2002: second fingerprint verification competition. two years after the first edition, a new fingerprint verification competition (fvc2002) was organized by the authors, with the aim of determining the state-of-the-art in this challenging pattern recognition application. the experience and the feedback received from fvc2000allowed the authors to improve the organization of fvc2002 and to capture the attention of a significantly higher number of academic and commercial organizations ( 33 algorithms were submitted). this paper discusses the fvc2002 database, the test protocol and the main differences between fvc2000 and fvc2002. the algorithm performance evaluation will be presented at the 16th icpr.
an image watermarking scheme using hvs characteristics and spread transform. the paper presents a robust digital image watermarking scheme that uses both the characteristics of the human visual system (hvs) and statistical information measure. spread transform approach is used where data is embedded through transform coefficients of both the cover and the watermark data. the spread transform watermarking technique yields better results in terms of imperceptibility, resiliency, capacity and cost compared to widely used spread spectrum watermarking schemes. hadamard transformation is used not only for simpler implementation but also for its higher data hiding capacity [capacity estimates for data hiding in compressed images]. experimental results show that the visual quality of the extracted watermark is good in spite of several external attacks. the fact is also supported by mutual information values used as objective measure.
parallelizing motion segmentation by perceptual organization of xyt. the front end of many motion analysis algorithms is usually a process that generates bounding boxes around each moving object, roughly segmenting the objects from the background. processing to finely define the moving object boundary can follow, but only within these rough bounding boxes. in this paper, we consider a method that exploits the structure and organization in the spatio-temporal block (xyt) of motion data to create bounding boxes around moving objects. this method has been shown to be robust with respect to illumination changes,noise, and occlusion events. this algorithm, however, begins with a 3d edge detection step across a sequence of images, which is a time consuming process. we have mapped this 3d edge detection to run on any mpi enabled parallel computer, thus achieving significant speedups especially for large image frames. we present results on sequences of various sizes and lengths from the recently formulated human id gait challenge problem dataset. we compare the quality of the automatically created bounding boxes with the semi-autonomously generated boxes that come with the gait challenge dataset.
rotation estimation from spherical images. robotic navigation algorithms increasingly make use of the panoramic field of view provided by omnidirectional images to assist with localization tasks. since the images taken by a particular class of omnidirectional sensors can be mapped to the sphere, the problem of attitude estimation arising from 3d rotations of the camera can be treated as a problem of estimating rotations between spherical images. recently it has been shown that direct signal processing techniques are effective tools in handling rotations of the sphere, but are limited when the signal is altered by larger rotations of omnidirectional cameras. we present an effective solution to the attitude estimation problem under large rotations. our approach utilizes a shift theorem for the spherical fourier transform to produce a solution in the spectral domain.
image flows and one-liner graphical image representation. in this paper we introduce a novel graphical image representation comprising a single curve ¿ the one-liner.the first step involves the detection and linking of image edges. we use a new technique, so-calledf "edge exploration," to simultaneously perform both tasks. this process is based on "image flows." it uses a gradient vector field and a new operator to explore image edges. estimating the derivatives of the image is performed by using local taylor expansions in conjunction with a weighted least-squares estimation method. this process finds all the possible image edges without any pruning, and collects information thatallows us to prioritize the found edges. this enables us to select the most important edges, that form a "skeleton" of the sought representation. the next step connects the selected edges into one continuous curve ¿ the one-liner. it orders the selected edges and finds curves connecting between them. we solve these two problems separately. since the abstract graph setting of the first problem is np-complete, we reduce it to a variant of tsp and compute an approximate solution to it. we solve the second problem by using dijkstra's shortest-path algorithm. we have a full software implementation for the entire one-liner etermination process.
qim watermarking combined to jpeg2000 part i and ii. on the one hand, lossy image compression, especially at very low bit rate, is considered as a strong attack for watermark process, 0n the other hand, with the blossoming demand for efficiently storing and transmitting digital visual information, lossy compression has been increasingly vital. this leads us to combine a watermarking scheme based on qim1 with a jpeg2000 coder. among the coding schemes supported by the standard, we select two coders derived respectively from part i and ii. comparative tests have been made in order to decide which of these coders is more suitable to be combined with our watermark scheme.
adaptation to walking direction changes for gait identification. this paper describes adaptation to gradual changes of walking directions for gait identification. first, we propose a method of body tilt correction due to changes of walking directions when constructing a spatio-temporal gait silhouette volume. next, we propose a view transformation model in the frequency domain to match gait features of different walking directions. finally, experiments of gait identification for a circular path demonstrate the effectiveness of the proposed method.
online learning of color transformation for interactive object recognition under various lighting conditions. this paper describes an online learning method of color transformation for interactive object recognition. in order to recognize objects under various lighting conditions, the system estimates a color transformation from the color of an object model by observing the color of a reference object. the system first initializes a general color transformation. next the system automatically recognizes a target object with the color transformation. when the system fails in recognition, the system recovers the failure with user interaction. then the system improves the color transformation with an observed color pair of the recognized target object. by repeating this process, the system adapts to the new environment. experiments using real-world refrigerator scenes are shown.
object recognition supported by user interaction for service robots. this paper describes an interactive vision system for a robot that finds an object specified by a user and brings it to the user. the system first registers object models automatically. when the user specifies an object, the system tries to recognize the object automatically. when the recognition result is shown to the user, the user may provide additional information via speech such as pointing out mistakes, choosing the correct object from multiple candidates, or giving the relative position of the object. based on the advice, the system tries again to recognize the object. experiments are described using real-world refrigerator scenes.
contour encoding based on extraction of key points using wavelet transform. in many situations it is convenient to represent pictorial data in the form of contours. it may become necessary to compress such contour data for efficient storage and transmission. we present here a technique for achieving very high levels of compression of 2-d contours. the goal here is to represent each contour using a discrete set of representative points known as key points. a novel method of extracting the key points using wavelet transform is presented. the scheme exploits the properties of the high frequency coefficients to identify these points. local peaks in the magnitude plot of high frequency coefficients are designated as key points and are identified using an efficient algorithm. the performance of the scheme is evaluated using multiple actual contours derived from weather radar reflectivity fields.
vector quantization using reflections of triangular subcodevectors. the design of a codebook consisting of codevectors is the goal of vector quantization (vq) schemes. this solution is not unique and many variants of vq have been proposed. vq suffers from computational and memory complexities that increase with the size of codebook and codevector dimensions. the lack of a universal codebook that works across different class of images necessitates the transmission of the codebook along with the codevector indices. this paper proposes a novel method of vector quantization using reflections of triangular subcodevectors. this method jointly reduces the memory and computational resources required for vq. numerical results are presented for the proposed scheme in comparison to a traditional vq method and a method based on reflections.
precise radial un-distortion of images. radial image distortion is a frequently observed defect when using wide angle, low focal length lenses. in this paper a new method for its calibration and removal is presented. an inverse distortion model is derived that is accurate to a sub-pixel level, over a broad range of distortion levels. an iterative technique for estimating the models parameters from a single view is also detailed. results on simulated and real images clearly indicate significantly improved performance compared to existing methods.
motion dependent spatiotemporal smoothing for noise reduction in very dim light image sequences. a new method for noise reduction using spatiotemporal smoothing is presented in this paper. the method is developed especially for reducing the noise that arises when acquiring video sequences with a camera under very dim light conditions. the work is inspired by research on the vision of nocturnal animals and the adaptive spatial and temporal summation that is prevalent in the visual systems of these animals. from analysis using the so-called structure tensor in the three-dimensional spatiotemporal space, motion segmentation and global ego-motion estimation, gaussian shaped smoothing kernels are oriented mainly in the direction of the motion and in spatially homogeneous directions. in static areas, smoothing along the temporal dimension is favoured for maximum preservation of structure. the technique has been applied to various dim light image sequences and results of these experiments are presented here.
three dimensional measurement using color structured patterns and imaging spectrograph. in this paper, we propose a simultaneous measurement system of spectral reflectance and shape of an object with the use of color gray code structured patterns and an imaging spectrograph.color and shape information are very important for us to recognize objects. therefore, we have proposed an earlier system which is able to measure spectral reflectance and shape simultaneously by the imaging spectrograph. this system uses the gray code patterns to measure the shape of target. however, the measurement time for whole target was long, because this system measures only 1 line at a time. therefore, a more effective measuring method is needed.this paper describes a measuring method using color gray code structured patterns. this proposed method uses the spectral characteristics of the projector effectively.
measurement of shape and refractive index of transparent object. when digitalizing characteristics of objects, shapes of objects is very important information. however the measurement methods of transparent objects are few. this paper proposes a new measurement method of a transparent object by changing background patterns. a silhouette of the transparent object is extracted using the change of the background patterns according to refraction, and the shape is measured with the use of the silhouette. furthermore, the refractive index of the transparent object is estimated by changing background patterns and the measured shape.
character segmentation-by-recognition using log-gabor filters. natural scene images coming usually from lowresolution sensors in embedded context suffer from low text recognition results. due to several types of degradations, existing algorithms are not robust enough. in order to improve recognition, we present in this paper a character segmentation using log-gabor filters to take advantage simultaneously of gray-level variation and spatial location. the recognition step is used to determine dynamically some of the parameters needed for the filter. finally, several quantified results are presented to highlight the efficiency of this method against several issues.
a modified fuzzy inference system for pattern classification. the use of fuzzy inferencing systems in pattern classifiers and expert systems is now more popular as the linguistic descriptions of inputs helps to deal with input uncertainty. a problem with these systems, however, is that outputs are monotonic and can only add to an output when extra information is acquired. this paper looks at a possible solution to the problem, which involves the inhibition of some rules' output by other rules making the classification of certain difficult patterns easier. this inhibition is achieved by redefining the consequent not function, such modification enables rules to describe holes in the data. several methods of incorporation are proposed, followed by some areas of suggested usage.
trajectory segmentation using dynamic programming. we consider the segmentation of a trajectory into piece-wise polynomial parts, or possibly other forms. segmentation is typically formulated as an optimization problem which trades off model fitting error versus the cost of introducing new segments. heuristics such as split-and-merge are used to find the best segmentation. we show that for ordered data (eg., single curves or trajectories) the global optimum segmentation can be found by dynamic programming. the approach is easily extended to handle different segment types and top down information about segment boundaries, when available. we show segmentation resultsfor video sequences of a basketball undergoing gravitional and non-gravitaional motion.
factorization-based planar mapping method for generating intermediate views. planar mapping approach for generating intermediate views is presented. whereas most existing mapping procedure employ matching and/or point-patching strategies, the proposed method is based on transformation of moments using a factorization formulation. the extended factorization method makes it possible to obtain shape parameters with planar surfaces. the technique is applied to map the texture of an object with many surfaces as an demonstration of its utility.
on classifier domains of competence. we study the domain of dominant competence of six popular classifiers in a space of data complexity measurements. we observe that the simplest classifiers, nearest neighbor and linear classifier, have extreme behavior of being the best for the easiest and the most difficult problems respectively, while the sophisticated ensemble classifiers tend to be robust for wider types of problems and are largely equivalent in performance. we characterize such behavior in detail using the data complexity metrics, and discuss how such a study can be matured for providing practical guidelines in classifier selection.
hybrid chinese/english text detection in images and video frames. in this paper, we propose a multiscale texture-based method using local energy analysis for hybrid chinese/english text detection in images and video frames. local energy analysis has been shown to work well in text detection, where remarkable local energy variations of pixels correspond to text region or boundary of other objects and lower local energy variations of pixels correspond to background or the interior of non-text objects. local energy variation is calculated in a local region based on the wavelet transform coefficients of images. hybridchinese/english text in images and video frames can be detected whether it is aligned horizontally or vertically. the font size of text to be detected may vary in a wide range of values. the proposed method has been tested on 321 frame images obtained from local tv programs and a tested dataset with low missed rate and false alarm rate.
constructing dense correspondences to analyze 3d facial change. this paper presents an improved method to construct dense correspondences for 3d facial analysis, which are capable of providing a full 3d description of a surface and extending the conventional landmark-based approaches. based on the technique of elastic deformation, the dense correspondences are established by mapping a generic model onto the 3d surface of an individual. the method used here is accurate in driving the conformation of the generic model and efficient in dealing with outliers, which can appear during local deformation. the experiments indicates for open surfaces as face with this method, more than 95 percent of triangles on the deformed generic mesh are within the range of 1mm to the original model and the average landmark errors are only 2mm.
logical entity recognition in multi-style document page images. logical entity recognition in document page images is the essential part of a document image analysis system. a heterogeneous collection of document pages usually has many layout styles. features extracted from same logical entities in different styles may have very different values and vice versa. therefore, logical entity classifiers learned from a training set of multistyle document pages may not be reliable due to possible feature overlap of different logical entities in different styles. in this paper, we propose a novel method in which style information is used in both logical entity classifier training and recognition phases. in the training phase, training data are first classified into distinct styles, and a dedicated support vector machine (svm) is then learned for each style. in the recognition phase, the style of a new document page image is first identified and its logical entities are then recognized using corresponding svm. we show in our experiments that the use of the style information significantly improves the accuracy of logical entity recognition in multi-style document page images.
incorporating conditional independence assumption with support vector machines to enhance handwritten character segmentation performance. learning bayesian belief networks (bbn) from corpora and incorporating the extracted inferring knowledge with a support vector machines (svm) classifier has been applied to character segmentation for unconstrained handwritten text. by taking advantage of the plethora in unlabeled data found in image databases in addition to some available labeled examples, we overcome the expensive task of annotating the whole set of training data and the performance of the character segmentation learner is increased. apart from this approach, which has not previously used for this task, we have experimented with two well-known machine learning methods (learning vector quantization and a simplified version of the transformation-based learning theory). we argue that a classifier generated from bbn and svm is well suited for learning to identify the correct segment boundaries. empirical results will support this claim. performance has been methodically evaluated using both english and modern greek corpora in order to determine the unbiased behavior of the trained models.limited training data are proved to endow with satisfactory results. we have been able to achieve precision exceeding 87.5%.
performance evaluation of object detection algorithms. the continuous development of object detection algorithms is ushering in the need for evaluation tools to quantify algorithm performance. in this paper, a set of seven metrics are proposed for quantifying different aspects of a detection algorithm' s performance. the strengths and weaknesses of these metrics are described. they are implemented in the video performance evaluation resource (viper) system and will be used to evaluate algorithms for detecting text, faces, moving people and vehicles. results for running two previous text-detection algorithms on a common data set are presented.
empirical study of multi-scale filter banks for object categorization. the aim of this work is the evaluation of different multiscale filter banks, mainly based on oriented gaussian derivatives and gabor functions, to be used in the generation of robust features for visual object categorization. in order to combine the responses obtained from several spatial scales, we use the biologically inspired hmax model [13]. we have tested the different sets of features on the challenging caltech-101 database, and we have performed the categorizarion procedure with adaboost, support vector machines and jointboosting classifiers, achieving remarkable results.
methodology for the registration of whole slo sequences. images acquired with the scanning laser ophthalmoscope (slo) device offer a very good tool for the evaluation of retinal diseases and obtaining interesting haemodynamic variables related to retinal blood flow . but because of the unavoidable eye movements, it is necessary a previous registration process to obtain a reliable analysis of the information extracted from these set of frames. this paper explains an algorithm which allows a fully automatic registration of the whole slo sequence by combining two registration techniques: a landmark based registration and a mutual information based one. the accurate registration of the frames will allow the automatic calculation of the so called dye dilution curves, which are computed by means of a robust fitting algorithm based on the optimisation method simulated annealing. with that curves it will be possible to obtain valuable haemodynamic variables, like the arteriovenous passage time described here.
feature selection based on a black hole model of data reorganization. this paper introduces a new model of feature selection based on a pattern recognition model using the concept of black holes. we show that that this method of feature selection is robust and provides an efficient subset of features for classification.
microfossils shape classification using a set of width values. recognition the shape of objects is a particularly relevant problem in pattern recognition. foraminifera are very important microfossil to determine geological age of marine rocks. in this paper we propose an approach to shape recognition that takes as input the measurements of widths of the most common foraminifera shells after a pre-processing step to rotate the object in order to have vertical alignment. a k-nn and a mlp classifiers are compared for classification of chambers arrangement, experimental results show 87.1 and 97.1% of right answers, respectively.
a sofm improves a real time quality assurance machine vision system. we present a high speed machine vision system for the inspection and quality assurance of canned tuna, which is currently working at a rate over 1000 cans per minute. the system inspects the geometry of the can and its contents at a resolution of 4 pixels/mm. it is the evolution of a first prototype through the introduction of a kohonen network, which maps texture features into a two dimensional grid where the user defines quality neighbourhoods. the inspection time, increased from 35 ms to 38 ms per can, allows the introduction of the system in the same production lines without affecting total performance, but with higher accuracy and user satisfaction.
a new sammon algorithm for sparse data visualization. sammon's mapping is an important non-linear projection technique that has been widely applied to the visualization of high dimensional data. however when dealing with sparse data, the object relations induced by the map become often meaningless. in this paper, we present a new sammon algorithm (ssammon) that overcomes this problem by previously transforming the dissimilarity matrix in an appropriate manner. the connection between our algorithm and a kernelized version of sammon's mapping is also studied. the new model has been applied to the high dimensional and sparse problem of word relation visualization. we report that ssammon outperforms two widely used alternatives proposed in the literature.
learning an optimal naive bayes classifier. the naive bayes classifier is an efficient classification model that is easy to learn and has a high accuracy in many domains. however, it has two main drawbacks: (i) its classification accuracy decreases when the attributes are not independent, and (ii) it can not deal with nonparametric continuous attributes. in this work we propose a method that deals with both problems, and learns an optimal naive bayes classifier. the method includes two phases, discretization and structural improvement, which are repeated alternately until the classification accuracy can not be improved. discretization is based on the minimum description length principle. to deal with dependent and irrelevant attributes, we apply a structural improvement method that eliminates and/or joins attributes, based on mutual and conditional information measures. the method has been tested in two different domains with good results.
learning an optimal naive bayes classifier. the naive bayes classifier is an efficient classification model that is easy to learn and has a high accuracy in many domains. however, it has two main drawbacks: (i) its classification accuracy decreases when the attributes are not independent, and (ii) it can not deal with nonparametric continuous attributes. in this work we propose a method that deals with both problems, and learns an optimal naive bayes classifier. the method includes two phases, discretization and structural improvement, which are repeated alternately until the classification accuracy can not be improved. discretization is based on the minimum description length principle. to deal with dependent and irrelevant attributes, we apply a structural improvement method that eliminates and/or joins attributes, based on mutual and conditional information measures. the method has been tested in two different domains with good results.
a fast and precise system for taking high-density human head measurements with surrounding range finders. this paper presents a novel head measurement system with surrounding range finders, which enables highly dense 3-d human head shape measurements to be taken quickly and precisely. since short measurement time is as important as the inherent accuracy of instruments for measuring the human body, the system concurrently controls multiple range finders at video rate. it can capture all images of the human head, including the top and thechin, within a single second. moreover, it enables measurements less than 1mm 2 in density to be taken with average error as low as 0.4mm. no conventional systems have both these advantages. the 3-d data acquired by the system will be utilized to design ergonomic products.
real-time k-means clustering for color images on reconfigurable hardware. k-means clustering is a very popular clustering technique, which is used in numerous applications. however, clustering is a time consuming task, particularly for large dataset, and large number of clusters. in this paper, we show that real-time k-means clustering can be realized for large size color images (24-bit full color rgb) and large number of clusters (up to 256) using an off-the-shelf fpga (field programmable gate arrays) board. in our current implementation with one fpga, the performance for 512 × 512 and 640 × 480 pixel images is more than 30 fps, and 20 - 30 fps for 756 × 512 pixel images in average when dividing to 256 clusters.
robust real time tracking of 3d objects. in this article the problem of tracking rigid 3d objects is addressed. the contribution of the proposed approach is an algorithm which combines: efficiency (i.e. the algorithm is designed before all to be real time using standard architecture), robustness (occlusions are allowed) and accuracy (sub-pixel accuracy is obtained). it is devoted to the tracking of 3d rigid objects, assuming that the 3d geometry as well as the texture of the surface is known. such performances can be obtained through a two levels scheme: the core of the approach consists in an efficient 2d patch tracker whose results are combined robustly to compute the 3d object pose. this article provides experimental results proving the soundness of the proposed approach.
quickstroke: an incremental on-line chinese handwriting recognition system. this paper presents quickstroke: a system for the incremental recognition of handwritten chinese characters. only a few strokes of an ideogram need to be entered in order for a character to be successfully recognized. incremental recognition is a new approach for on-line recognition of ideographic characters. it allows a user to enter characters a factor of 2 times faster than systems that require entry of full characters. incremental recognition is performed by a two-stage system which utilizes 68 neural networks with more than 5 million free parameters. to enable incremental recognition, we use specialized time-delay neural networks (tdnns) that are trained to recognize partial characters. to boost the recognition accuracy of complete characters, we also use standard fully-connected neural networks. quickstroke is 97.3% accurate for the incremental writer-independent recognition of 4400 simplified gb chinese ideograms.
combining global and local classifiers with bayesian network. this paper introduces a classification method based on feature space segmentation. since the classification task is equivalent to a probability distribution estimation, a bayesian network is used as an inference mechanism for dealing with the underling probability distribution function that, presumably, is complex and factored. the article presents a method for splitting the feature space into regions that are associated to local classifiers. after that, a bayesian network is used for combining their outputs. experimental results reveal that this is a suitable approach for speeding up the training phase for large databases as well as to ensure good recognition rates.
combining global and local classifiers with bayesian network. this paper introduces a classification method based on feature space segmentation. since the classification task is equivalent to a probability distribution estimation, a bayesian network is used as an inference mechanism for dealing with the underling probability distribution function that, presumably, is complex and factored. the article presents a method for splitting the feature space into regions that are associated to local classifiers. after that, a bayesian network is used for combining their outputs. experimental results reveal that this is a suitable approach for speeding up the training phase for large databases as well as to ensure good recognition rates.
object localization based on directional information: case of 2d raster data. a directional spatial relationship to a reference object (e.g., "east of the post office") can be represented by a spatial template. the template partitions the space into regions where the relationship holds (to various extents) and regions where it does not hold. the objects for which the relationship holds can then be located. a template can be easily modeled. computationally, however, exact calculation of the model in case of 2d raster data is prohibitively expensive, and a tractable approximation algorithm was proposed. here, we introduce a new concept: the concept of the f-template. it leads to a new approximation algorithm, which is faster, gives better results, and is more flexible.
prototype setting for elastic matching-based image pattern recognition. the purpose of this paper is to emphasize the importance the consistency between the distance measures on prototype setting and discrimination in elastic matching (em)-based recognition. specifically, this paper focuses on the following points: (i) confirmation of performance degradation when euclidean distance is used on prototype setting whereas em-distance is used on discrimination, and (ii) proposal of new prototype setting algorithm where this inconsistency is avoided. through an experiment of handwritten character recognition, the effectiveness of the proposed algorithm was quantified.
reconciling landmarks and level sets. shape warping is a key problem in statistical shape analysis. this paper proposes a framework for geometric shape warping based on both shape distances and landmarks. our method is compatible with implicit representations and a matching between shape surfaces is provided at no additional cost. it is, to our knowledge, the frst time that landmarks and shape distances are reconciled in a pure geometric level set framework. the feasibility of the method is demonstrated with two- and three-dimensional examples. combining shape distance and landmarks, our approach reveals to need only a small number of landmarks to obtain improvements on both warping and matching.
a novel svm geometric algorithm based on reduced convex hulls. geometric methods are very intuitive and provide a theoretically solid viewpoint to many optimization problems. svm is a typical optimization task that has attracted a lot of attention over the recent years in many pattern recognition and machine learning tasks. in this work, we exploit recent results in reduced convex hulls (rch) and apply them to a nearest point algorithm (npa) leading to an elegant and efficient solution to the general (linear and nonlinear, separable and non-separable) svm classification task.
evaluation of correspondence errors for stereo. the computation of a scalar correspondence error is the fundamental step in most stereo algorithms. the quality of the results obtained by the reconstruction algorithm directly depends on the characteristics of such error. we developed a procedure to evaluate different methods proposed for the computation of the correspondence error. the evaluation is based on exploring the shape of the error surface and test it for uniqueness, isolation and compatibility. experiments are reported which assess the behaviour of three different methods for correspondence error calculation. for the scenes used, it is possible to identify the most appropriate method to compute the correspondence error.
attentive visual servoing in the mpeg compressed domain for un-calibrated motion parameter estimation of road traffic. an attentive vision system is proposed that estimates traffic motion parameters from mpeg-2 compressed video recorded using an un-calibrated camera mounted on a pantilt unit. compressed domain information from a stream of mpeg-2 video is used to estimate a traffic motion field and infer the 2d frame location of the traffic lanes. with these visual cues attentive visual servoing automatically adjusts camera pose so as to improve the motion parameter estimation process. an existing technique to acquire motion parameters from an un-calibrated camera is used after obtaining an optimal camera pose. this system provides a computationally inexpensive alternative to existing intelligent transport systems for surveillance.
seeing around occluding objects. this paper presents a novel method for the removal of unwanted image intensity due to occluding objects far from the plane of focus. such occlusions may arise in scenes with large depth discontinuities, and result in image regions where both the occluding and background objects contribute to pixel intensities. the contribution of the occluding object's radiance is modeled by reverse projection, and can be removed from this region by a simple operation on the pixel's intensity. experimental results demonstrate our ability to accurately recover the background's appearance despite significant occlusion. as compared with processing based a linear model of occlusion, the results show lower error and a more accurate contrast.
a bayesian approach to visual size classification of everyday objects. humans are adept at size classification from visual images of objects. a challenging computer vision problem is that of automatic visual size classification. current size classification systems assume controlled environments and use features geared towards a particular object category and pose. however, certain applications may require algorithms that can adapt to a variety of object categories and handle complex environments. in this paper, we propose a bayesian approach to automatic visual size classification, inspired by human visual perception, for a more generalized and robust size classifier. initial results show that the proposed approach can handle multiple object categories and is invariant to scale changes.
learning spatial context from tracking using penalised likelihoods. map estimation of gaussian mixtures through maximisation of penalised likelihoods was used to learn models of spatial context. this enabled prior beliefs about the scale, orientation and elongation of semantic regions to be encoded, encouraging one-to-one correspondences between mixture components and these regions. in conjunction with minimum description length this enabled automatic learning of inactivity zones and entry zones from track data in a supportive home environment.
part-based probabilistic point matching. we present a probabilistic technique for matching partbased shapes. shapes are represented by unlabeled point sets, so discontinuous boundaries and non-boundary points do not pose a problem. occlusions and significant dissimilarities between shapes are explained by a 'background model' and hence, their impact on the overall match is limited. using a part-based model, we can successfully match shapes which differ as a result of independent part transformations a form of variation common amongst real objects of the same class. a greedy algorithm that learns the parts sequentially can be used to estimate the number of parts and the initial parameters for the main algorithm.
automatic color space selection for biological image segmentation. in this paper, we have tested criteria designed by liu and borsotti to automatically evaluate the quality of a color segmentation. as they do not correctly answer our microscopy image problems, we propose two modified criteria adapted to two different biological applications. penalizing inhomogeneity, numerous small regions and misclassified regions, our modified criteria help to select the best color space, for a given segmentation method.
color image segmentation based on markov random field clustering for histological image analysis. in order to characterise the virulence factors of different mycobacterium tuberculosis strains responsible of tuberculosis disease, the quantification, by cell counting, of immune cell recruitment is necessary. however, this task by microscopic observations is very tedious and difficult to reproduce. hence we propose an automatic counting approach, consisting in color image segmentation to discriminate three regions: cell nuclei, immune cells and background,followed by the extraction of each cell entity. for color segmentation, a markov random field clustering approach taking simultaneously into account both color and spatial information is chosen. our technique was sucessfully applied to several color images of different strains, andan evaluation of the results has been performed, showing the robustness of the method against noise, marker color changes, illumination changes and blurring.
generation of a 3-d face model from one camera. the generation of a fully textured 3-d model of a person's face presents difficult technical challenges, buthas many applications in several fields, such as video games, immersive telepresence, and medicine. current commercial systems rely on booth-like set-ups, equippedwith laser-based scanners, or project a pattern on the subject's face.the major drawbacks of such systems are the cost of the hardware they require, and the lack of operational flexibility. we present here a fully automatic system to generate a 3-d model from a sequence of images taken by a single camera. unlike other methods, we do not use a generic 3-d face subject to deformation, but instead proceed in a fully bottom-up fashion.the approach is a two-stage process. first, we estimate for each view the pose of the object with respect to the camera. this is accomplished by robust feature matching and global bundle adjustment. then, we consider sets of adjacent views, which we treat as stereo pairs, and generate partial depth maps, which are then integrated into a single 3-d model. the texture is obtained by merging the images themselves. we describe the algorithm in detail, and show results on a number of real datasets.
affine propagation for surface reconstruction in wide baseline stereo. the problem of dense matching in wide baseline stereo is considered. it is assumed that the scene is formed by piecewise-smooth, lambertian, textured surfaces and that rectified images of the scene are available. we present a novel dense matching algorithm that accounts for local affine distortion and propagates the best matching affine parameters on each surface until a surface discontinuity is reached. disparity maps and projective reconstructions for real-world wide baseline stereo images are shown.
anchor point thinning using a skeleton based on the euclidean distance transformation. thinning is one of the most frequently used methods to know the geometrical feature of objects. it also provides the topological feature and length measurements about an object. for example, the tree structure of the bronchus is determined by using the thinned result of it. this paper presents a three dimensional thinning method which can control the quality of result concerning appearance of spurious short branches by a parameter value.this method is constructed by integrating the anchor point thinning algorithm and the skeletonization algorithm based upon the euclidean metric. we applied the proposed method to artificial figures and a three dimensional bronchus region extracted from a real chest x-ray ct image and confirmed that the proposed method could control the number of spike branches and shrinkage of branches.dr. toyofumi saito, an associate professor who was one of the most active researchers in the field of image processing in japan and a young leader of the author's laboratory, passed away on 26 october 2000. this paper describes one of his last works. we have lost a most reliable and most promising colleague, an experienced supervisor, and a very sincere friend. we would like to dedicate this paper to dr. toyofumi saito and to all those who have shared and cherished the memories of him.
adaptive step size window matching for detection. an often overlooked problem in matching lies in selecting an appropriate step size. the selection of the step size for real-time applications is critical both from the point of view of computational efficiency and detection performance. current systems set the step size in an ad hoc manner. this paper describes an algorithm for selecting the step size based on a theoretical worst case analysis. we have implemented this adaptive step size method in an object detection algorithm. experimental evaluation demonstrates the effectiveness of our proposed algorithm.
image categorization using local probabilistic descriptors. image categorization involves the well known difficulties with different visual appearances of a single object, but introduces also the problem of within-category variation. this within-category variation makes highly distinctive local descriptors less appropriate for categorization. in this paper we propose a family of local image descriptors, called probabilistic patch descriptors (ppds). ppds encode the appearance of image fragments as well as their variability within a category. ppds extend the usual local descriptors by modelling also the variance of the descriptors' elements, e.g. pixels or bins in a histogram. we apply ppds to image categorization by using machine learning where the features are the matching scores between images and ppds. we experiment with two variants of ppds that are based on complementary local descriptors. an interesting observation is that combining the two ppd variants improves categorization accuracy. experiments indicate benefits of modelling the within-category variation and show good robustness with respect to noise.
using signal/residual information of eigenfaces for pca face space dimensionality characteristics. principal component analysis has been used since 1990 [1] in many recognition algorithms to get a face feature representation and to exploit the dimensionality reduction characteristic of the principal component analysis (pca). the way to determine the optimal dimension of the reduced space is still not available. another critical point when working with pca is the influence of the training set, denoted here as pca construction set. in this paper we are working on the behaviour of the signal/residual information of the pcaeigenspectrum in order to determine an optimal threshold that could be used for the dimensionality reduction. we also study the influence of different sets used to construct the pca representation. our experiments are done on the frgcv21 database, using the bee pca baseline software. we also use images from the banca database for the construction of the pca respresentations.
data fusion for 3d gestures tracking using a camera mounted on a robot. this article describes a multiple feature data fusion applied to an auxiliary particle filter for markerless tracking of 3d two-arm gestures by using a single camera mounted on a mobile robot. the human limbs are modelled by a set of linked degenerated quadrics which are truncated by pairs of planes also modelled as degenerated quadrics. the method relies on the projection of both the model's silhouette and local features located on the model surface, to validate the particles (associated configurations) which generate the best model-to-image fittings. our cost metric combines robustly two imaging cues i.e. model contours and colour or texture based patches located on the model surface, subject to 3d joint limits and also non self-intersection constraints. the results show the robustness and versatility of our data fusion based approach.
local visual primitives (lvp) for face modelling and recognition. this paper proposes a novel simple yet effective generative model based on local visual primitives (lvp) for face modeling and classification. the lvps, as the pattern of local face region, are learnt by clustering a great number of local patches. visually, these lvps correspond to intuitive low-level micro visual structures very well, and they are expected to constitute those high-level semantic features, such as eyes, nose and mouth. we show that, though face appearances vary dramatically, these lvps are very effective for face image reconstruction. for face recognition, block-based histograms of the lvps indexes are extracted as the face representation to compare for classification. primary experiments on feret face database have shown that the lvp method can achieve encouraging recognition rate.
ant colony system with extremal dynamics for point matching and pose estimation. for a point-based image registration method, point matching is a hard and a computationally intensive task to handle especially when issues of noisy and outlying data have to be considered. in this paper we cast the problem as a combinatorial optimization task and wedescribe a global optimization method to achieve robust point matching and pose estimation for image registration purpose. the basic idea is to use ant colony system (acs) as a population based search strategy to evolve promising starting solutions i.e affine transformations. an appropriate local search inspired from extremal optimization is developed and embedded within the search strategy to refine the solutions found. experimental results are very promising and show the ability of the method to cope with outliers and to achieverobust pose estimation.
human-robot eye contact through observations and actions. eye contact is an effective means of controlling communication for humans, such as starting communication. it seems that we can make eye contact if we look at each other. in addition, we need to be aware of being watched by each other. in this paper, we propose a method of eye contact between humans and robots considering the above two conditions. then, we present a robot that can recognize hand gestures after making eye contact with the human. experimental results show that the robot can recognize hand gestures without false detection, proving the effectiveness of eye contact as a means of controlling communication.
face authentication test on the banca database. this paper details the results of a face authentication test (fat2004) [http://www.ee.surrey.ac.uk/banca/icpr2004] held in conjunction with the 17th international conference on pattern recognition. the contest was held on the publicly available banca database [http://www.ee.surrey.ac.uk/banca] according to a defined protocol [the banca database and evaluation protocol]. the competition also had a sequestered part in which institutions had to submit their algorithms for independent testing. 13 different verification algorithms from 10 institutions submitted results. also, a standard set of face recognition software packages from the internet [http://www.cs.colostate.edu/evalfacerec] were used to provide a baseline performance measure.
unsupervised decomposition of mixed pixels using the maximum entropy principle. due to the wide existence of mixed pixels, the derivation of constituent components (endmembers) and their proportions (abundances) at subpixel scales has become an important research topic. in this paper, we propose a novel unsupervised decomposition method based on the classical maximum entropy principle, termed umaxent. the algorithm integrates a global least square error-based endmember detection and a per-pixel maximum entropy learning to find the most possible proportions. we apply the proposed method to the subject of spectral unmixing. the experimental results obtained from both simulated and real hyperspectral data demonstrate the effectiveness of the umaxent method.
regression analysis and automorphic orbits in free groups of rank 2. the main goal of this paper is to show that pattern recognition techniques can be successfully used in abstract algebra. we introduce a pattern recognition system to recognize words of minimal length in their automorphic orbits in free groups of rank 2. this system is based on linear regression and does not use any particular results from group theory. the corresponding classifier is very fast and surprisingly accurate.
a hierarchical projection pursuit clustering algorithm. we define a cluster to be characterized by regions of high density separated by regions that are sparse. by observing the downward closure property of density, the search for interesting structure in a high dimensional space can be reduced to a search for structure in lower dimensional subspaces. we present a hierarchical projection pursuit clustering (hppc) algorithm that repeatedly bi-partitions the dataset based on the discovered properties of interesting 1-dimensional projections. we describe a projection search procedure and a projection pursuit index function based on cho, haralick and yi's improvement of the kittler and illingworth optimal threshold technique. the output of the algorithm is a decision tree whose nodes store a projection and threshold and whose leaves represent the clusters (classes). experiments with various real and synthetic datasets show the effectiveness of the approach.
local multiple orientation estimation: isotropic and recursive oriented network. in this paper we propose a new operator for texture orientation estimation. we focus on directional textures which can have more than a single orientation at the same point. our operator consists in a steerable network of parallel lines along which a homogeneity feature is computed in the spatial domain. the analysis of the network response along each direction allows us to set up the presence of single or multiple orientations. in order to reduce the computing cost, we propose a recursive implementation of our operator, thanks to the rotations of the image instead of the rotation of the network. our operator works on a small support, and thus provides a local estimation of the orientations. results obtained both with synthetic textures and natural images are accurate and show the selectivity and the isotropic behaviour of our operator.
image acquisition enhancement for active video surveillance. last years have seen a big effort of research community to solve the security problems by developing video surveillance systems. normally, developed systems have the characteristic to be executed on images acquired by autonomous cameras. in this paper we propose a new way to develop visual surveillance systems which would not be a set of passive modules but systems that actively decide both what to see and how to see it. in particular, our idea is to act on the regulation of the acquisition parameters as consequence of what the system needs to see. the regulation strategy is based on two parameters, focus and iris, and aims to identify an optimal sequence of steps to enhance the acquisition quality of the object of interest. to this end, a hierarchy of neural networks has been employed to select first which parameter must be regulated then to adjust it.
focusing on target's features while tracking. usually tracking objects by means of a moving camera means solving the problem of segmenting its motion from the background and maintain the gaze on it. usually key points, i.e. features like corners, are matched throughout consecutive frame to register frames and detecting objects or to compute a fixation point on the object of interest. none of the methods proposed so far investigates how, more then just matching features between frames, the tuning of their quality would increase the robustness of the methods. hence, the novelty proposed in this paper concerns the automatic tuning of the focus parameter to increase the tracking capabilities and strength the robustness of the entire system.
bayesian rendering with non-parametric multiscale prior model. this paper investigates the use of the bayesian inference for devising an example-based rendering procedure. as prior model of this bayesian inference, we exploit the multiscale non-parametric model recently proposed by wei et al. for texture synthesis. this model appears to be interesting to also capture some characteristics of a rendering style from an artistic illustration example. obtained results, with a prior model capturing the rendering style ofdrawing samples or trained with synthetic and real input textures, are presented. our results indicate that the proposed method allows to simulate automatic synthesis of various illustration style. more generally, the proposed scheme is able to re-render an input image in the style of an other image allowing, in this way, to create a very broad range of artistic and visual effects.
lossless data compression for image decomposition with recursive idp algorithm. specific algorithms for lossless compression of the data, obtained after processing of halftone and color images with the inverse difference pyramid decomposition (idp), are described in this paper. the basic steps of the idp algorithm (coding and decoding) are defined, and the corresponding diagram for modified huffman code generation is shown. the presented lossless run-length and modified huffman algorithms are used together with a lossy image coding method, and are aimed at preserving the image quality after the idp decomposition unchanged. some practical results and comparison with the standard jpeg2000 are given also.
two-stage classification system combining model-based and discriminative approaches. for the tasks of classification, two types of patterns can generate problems: ambiguous patterns and outliers. furthermore, it is possible to separate classification algorithms into two main categories. discriminative approaches try to find the better separation among all classes and minimize the first type of error. but, in general they cannot deal with outliers. besides, model-based approaches make the outlier detection possible but are not sufficiently discriminative. thus, we propose to combine a model-based approach with support vectors classifiers (svc) in a two-stage classification system. another advantage of this combination is to reduce the principal burden of svc: the processing time necessary to make a decision. finally, the experiments on handwriting digit recognition have shown that it is possible to maintain the accuracy of svcs, while decreasing complexity significantly.
exact view-dependent visual hulls. the visual hull is widely used to produce three dimensional models from multiple views, due to the reliability of the resulting surface. this paper presents a novel method for efficiently evaluating the exact view-dependent visual hull without using approximations. methods for selecting intersections and ordering them via the cross ratio are presented. results show the high quality of the surfaces produced using this method.
word completion with latent semantic analysis. current word completion tools rely mostly on statistical or syntactic knowledge. can using semantic knowledge improve the completion task? we propose a languageindependent word completion algorithm which uses latent semantic analysis (lsa) to model the semantic context of the word being typed. we find that a system using this algorithm alone achieves keystroke savings of 56% and a hit rate of 42%. this represents improvements of 6.9% and 17%, respectively, over existing approaches.
activity recognition based on multiple motion trajectories. we propose an method for activity recognition based on multiple motion trajectories. motion trajectotires generated from body parts (hand, feet, and joints) are used as features. we not only recognize each activity but also temporally locate the start and end point of its duration. input sequences are divided into separate temporal segments based on the number of detected trajectories. segments with same number of trajectories are temporally segmented using the hmm model for each movement (activity). the experimental results show that our approach can successfully locate each activity in continuous video sequences.
tensor voting accelerated by graphics processing units (gpu). this paper presents a new gpu-based tensor voting implementation which achieves significant performance improvement over the conventional cpu-based implementation. although the tensor voting framework has been used for many vision problems, it is computationally very intensive when the number of input tokens is very large. however, the fact that each token independently collects votes allows us to take advantage of the parallel structure of gpus. also, the good computing power of modern gpus contributes to the performance improvement as well. our experiments show that the processing time of gpu-based implementation can be, for example, about 30 times faster than the cpu-based implementation at the voting scale factor ó = 15 in 5d.
edge-preserving simultaneous joint motion-disparity estimation. we propose an energy-based joint motion and disparity estimation algorithm with an anisotropic diffusion operator to yield correct and dense displacement vectors. the model estimates the left and right motions simultaneously in order to increase accuracy. we use the euler-lagrange equation with variational methods and solve the equation with the finite difference method (fdm). then, the method computes the initial disparity in the current frame with joint estimation constraint, and regularizes this disparity by using our energy model. experimental results show that the proposed algorithm provides accurate motion-disparity maps, and preserve the discontinuities of the object boundaries well.
multi-layer mosaics in the presence of motion and depth effects. in this paper, we present a new segmentation-based 2d mosaic framework. most of current mosaic algorithms do not explicitly remove moving objects from images before registration, so that they often fail when the size of the moving objects is relatively large. to solve this problem, we first segment moving objects from the input images using the tensor voting framework, and then only the remaining backgrounds are processed for the background mosaic. the second mosaicking step is straightforward because the first motion segmentation step also produces very accurate dense matches. by providing comparative examples, we show that the quality of the background mosaics can be significantly improved by our framework.
model estimation for photometric changes of outdoor planar color surfaces caused by changes in illumination and viewpoint. in this paper we compare different ways of representing the global photometric changes in image intensities caused by changes in illumination and viewpoint, aiming at a balance between goodness-of-fit and low complexity. a series of model selection tests are performed for the case of outdoor imagery consisting of several views of several instances of billboards taken under different viewing angles and different illumination (natural light). possible candidates for a transformation model on (r,g,b) color space are investigated and different approaches for the model selection problem are considered.the results are used within ongoing research into computation of new invariant features for planar color patterns, as the model choice is an important issue to decide on when extracting invariants. these results can be of benefit to other areas of research into color pattern or object recognition, which motivated us to report here in detail about the model selection work.
robust tracking of soccer players based on data fusion. this paper presents a technique for integrating multiple visual features for tracking moving objects. our proposed method consists of observation (pattern-matching) units and prediction units, which form a ladder structure.the major feature of our proposed method is that each of the observation units with different pattern matching algorithms is executed step-by-step to innovate the state vector considering the reliability of the observation. the fusion of multiple observations makes the tracks robust to occlusion and to deformation.in this paper, experiments with soccer sequences are shown to validate the technique's robustness. its applications to broadcasting services are also briefly discussed.
a probabilistic approach to fast and robust template matching and its application to object categorization. this paper presents a new statistic, called probabilistic increment sign correlation (probabilistic isc), for evaluating similarity between images of objects which have intra-class variation such as individual differences of human faces. the new statistic evaluates similarity between an input image and object classes, whereas most conventional methods, such as normalized cross-correlation, calculate correlation between an input image and a template. the new statistic is defined as a log-likelihood based on probabilities of observing the increment signs. probabilistic isc provides two advantages over conventional correlationbased methods: 1) robustness against the intra-class variation because it gives larger weights to stable features which are commonly observed in reference images and 2) robustness against noise and change in illumination. it yields higher performance even if a small number of reference images are given, whereas other methods such as the subspace method and adaboost cannot maintain their accuracy. we show these advantages through several experiments of face detection and face orientation estimation.
artificial images for classifying diffuse lung opacities in thin-section computed tomography images. the classification of diffuse lung opacities in thin-section computed tomography(hrct) images is very fundamental for developing a computer-aided diagnosis(cad) system.however, in designing such a cad system, the number of the available samples is usually small.this leads to the difficulties of designing the cad system.one way to overcome this problem is to generate artificial images from available real images by image rotation and reversal.in this paper, we discuss the use of artificial images for designing the cad system.
environment recognition based on analysis of human actions for mobile robot. in this paper, we propose a novel method for recognizing environment based on relationship between human actions and objects for a mobile robot. most of previous works on environment recognition for robots focused on generating obstacle maps for path-planning. in addition, model-based object recognition techniques are also used for searching particular objects. it is, however, difficult in reality to prepare a lot of models in advance for recognizing various objects in unknown environments. on the other hand, human can often recognize objects not from their appearances but by watching other person taking actions on them. this is because the function and/or the usage of the objects are closely related with human actions. we have introduced conceptual models of human actions and objects for classifying objects by observing human activities in our previous work. in this paper, we apply this key idea to a mobile robot. we also demonstrate that the arrangement of objects can be recognized by analyzing human actions.
combining the gabor and histogram features for classifying diffuse lung opacities in thin-section computed tomography. the classification of diffuse lung opacities in thin-section computed tomography (hrct) images is an important step for developing a computer-aided diagnosis (cad) system. in designing the cad system for classifying diffuse lung opacities in hrct images, a gabor filter-based approach has been shown to be effective. in order to improve further the classification performance of the cad system, we explore the combination of the gabor and histogram features. the ex-perimental results show that combining the gabor and histogram features leads to clear improvement of the classification performance.
connected pattern segmentation and title grouping in newspaper images. this paper presents an algorithm that performs automated segmentation and classification of newspaper images. the algorithm discusses a technique for segmenting components that are connected to other components and presents another technique to correctly group titles and subtitles. the algorithm uses a bottom-up approach to initially segment the image, classify patterns and extract text lines. the classified patterns are then merged into complete regions. the algorithm is tested on a set of complex newspaper images taken from the first international newspaper segmentation contest, and the results are compared with the contest results.
a moe framework for biclustering of microarray data. biclustering or simultaneous clustering of both genes and conditions have generated considerable interest over the past few decades, particularly related to the analysis of high-dimensional gene expression data in information retrieval, knowledge discovery, and data mining. the objective is to find sub-matrices, i.e., maximal subgroups of genes and subgroups of conditions where the genes exhibit highly correlated activities over a range of conditions. since these two objectives are mutually conflicting, they become suitable candidates for multi-objective modeling. in this study, a novel multi-objective evolutionary biclustering framework is introduced by incorporating local search strategies. the experimental results on benchmark datasets demonstrate better performance as compared to existing algorithms available in literature.
feature selection and gene clustering from gene expression data. in this article we describe an algorithm for feature selection and gene clustering from high dimensional gene expression data. the method is based on measuring similarity between features/genes whereby redundancy therein is removed. this does not need any search and therefore is fast. a novel feature similarity measure, called maximum information compression index, is used. the feature selection algorithm also obtains gene clusters in a multiscale fashion. the superiority of the algorithm, in terms of speed and performance, is established on a real life molecular cancer classification dataset.
comparison of microarray-based predictive systems for early recurrence of cancer. in our previous study, we successfully developed a novel predictive system with microarray data in order to predict early intrahepatic recurrence of hepatocellular carcinoma after curative resection. in this paper, we compare our system with other systems in terms of the predictive performance. from experimental results, our system was superior to other systems. this success comes from our gene selection procedure that can cope with the sample variability.
an online handwritten music score recognition system. the objective of this study is to produce a system that would allow music symbols to be written by hand using a pen-based computer that would simulate the feeling of writing on sheets of paper and that would also accurately recognize the music symbols. to accomplish these objectives, the following methods are proposed: (1) two features, time-series data and an image of a handwritten stroke, are used to recognize strokes; and (2) the strokes are combined, as efficiently as possible, and outputted automatically as a music symbol. as a result, recognition rates of 97.60 and 98.80% were obtained in tests with strokes and music symbols, respectively.
automatic extraction of buildings utilizing geometric features of a scanned topographic map. we have been developing the feature oriented and progressive algorithm in order to is to make an object-oriented digital map database (dmd)from printed topographic maps by using raster-vector conversion and extracting various objects such as natural objects, man-made objects, and notations. this paper concentrates to discuss how to extract the buildings.
a learning process to the identification of feature points on chinese characters. the paper describes a new stroke extraction approach to identify the feature points of a character, using line-filtering and learning-based techniques. the line-filtering technique based on the convolution operations with a set of l-d gabor templates is efficient in extracting the stroke segments of the character and robust in noise tolerance. furthermore, unlike convectional feature-point detection techniques where decision rules and thresholds have to be specified, our learning-based technique for feature-point identification implicitly represents the rules and thresholds without further parameter adjustments. experimental results show that the learning-based technique is capable of generalizing the learning knowledge to identify feature points and can get an average identification rate of 95.27% for hand-printed test characters and 96.78% for machine-printed test characters.
a proposal of neural network architecture for non-linear function approximation. in this paper, a neural network architecture for non-linear function approximation is proposed. we point out problems in non-linear function approximation with traditional neural networks, that is, difficulty in analyzing internal representation, no reproducibility in function approximation due to the random scheme for weight initialization, and the insufficient generalization ability in learning without enough samples. based on these considerations, we suggest three main improvements. the first is the design of a sigmoidal function with localized derivative. the second is a deterministic scheme for weight initialization. the third is an updating rule for weight parameters. simulation results show beneficial characteristics of our proposed method; low approximation error at the beginning of iterative calculation, smooth convergence of error and its improvement for difficulty in analyzing internal representation.
constraint-based prototyping for understanding three orthographic views. we propose a prototyping approach to understanding three orthographic views based on constraint satisfaction and discuss practicability of the proposed prototyping system. our approach reconstructs 3d objects by solving the constraint satisfaction problem that is equivalently transformed from the input 2d data. we perform some experiments comparing our prototyping system with the handcoded system developed separately in which a set of restoration knowledge is implemented. after evaluating efficiency for several drawing examples, we point out two factors that cause inefficiency and propose ideas to cope with them.
improvement of the virtual printing scheme for synthesizing ukiyo-e. in this paper, we propose a physically based model for the printing process in the virtual woodblock printing for improvement of printing quality. virtual printing is a simulation of real printing using "woodblocks", "a paper sheet", "a baren (japanese squeegee)", and "inks" in a virtual 3d space. a print is synthesized by an interaction among them, and it is very important to study physical properties and behaviors of the virtual items. we focus on the property and the behavior of ink and study a variety of effects due to the degree of moisture of the ink. this improvement enables the virtual printing to synthesize japanese traditional multicolor prints ukiyo-e.
factorized local appearance models. we propose a novel local appearance modeling method for object detection and recognition in cluttered scenes. the approach is based on the joint distribution of local feature vectors at multiple salient points and factorization with independent component analysis (ica). the resulting non-parametric densities are simple multiplicative histograms. this leads to computationally tractable joint probability densities which can model high-order dependencies. testing and evaluation shows that the factorized density model with spatial encoding improves modeling accuracy and outperforms global appearance models in image/object retrieval. furthermore, experiments in detection of substantially occluded objects in cluttered scenes have demonstrated promising results.
on-line script recognition. automatic identification of handwritten script facilitates many important applications such as automatic transcription of multi-lingual documents and search for documents on the internet containing a particular script. the increase in usage of handheld devices which accept handwritten input is creating a huge volume of handwritten data. we propose a method to classify words and lines in an on-line handwritten document into arabic, cyrillic, devnagari, han, hebrew and roman scripts. the proposed classification system, based on spatial and temporal features of the strokes, attained an overall classification accuracy of 86:5% at the word level on a dataset containing 13; 379 words. the classification accuracy improves to 95% as the number of words in the test sample is increased to five and to 95:1% for complete text lines.
agglomerative clustering for image segmentation. the paper presents an agglomerative clustering technique for image segmentation. to initiate agglomeration, a set of homogeneous segments is found in the image using level set analysis (lsa). a relational matrix is then defined establishing relations between neighbouring segments present in the image. these relations are derived based on the intensity and boundary features of the segments. the agglomeration is performed on this relationship based on asymmetric agglomerative clustering criteria. the performance is demonstrated through results on a number of natural images and through cluster validity criteria.
retrieval of on-line hand-drawn sketches. sketch matching algorithms are commonly used for indexing and retrieval of documents based on printed or hand-drawn sketches.one could use a hand-held computer to do sketch-based queries to a database containing hand-drawn and printed sketches.we present an on-line hand-drawn sketch matching algorithm based on a line-based representation of sketches.a distance measure is defined for comparing two sketches based on this representation. the algorithm is computationally efficient and achieves a recall rate of 88.44% at the same precision, when tested on a database of 150 sketches collected from 5 users.
a non-iterative approach to reconstruct face templates from match scores. regeneration of biometric templates from match scores has security and privacy implications related to any biometric based authentication system. in this paper, we propose a novel non-iterative scheme to reconstruct face templates from match scores. we use an affine transformation of the images to approximate the behavior of the given face recognition system based on an independent set of face templates termed as "break-in” set. selected templates from the "break-in” set are matched only once with the enrolled template of the target account and match scores are recorded. these scores are then embedded in the approximating affine space along with break-in set templates to compute the co-ordinates of the target template. the inverse transformation is used to reconstruct the original target template. we present the reconstruction of templates for three different face recognition algorithms: bayesian intrapersonal/extrapersonal classifier, elastic bunch graph matching (ebgm) algorithm and baseline algorithm used in face recognition grand challenge (2005). we also report the initial result to break an user's account using the reconstructed template for bayesian algorithm. bayesian algorithm was set to operate at 0.1% false acceptance rate and 98% true acceptance rate with 100 enrollments. we observed that with proposed scheme, at most 600 attempts is required to achieve a 0.99 probability of break-in the bayesian face recognition algorithm.
integration of feature distributions for colour texture segmentation. this paper proposes a new framework for colour texture segmentation and determines the contribution of colour and texture. the distributions of colour and texture features provides the discrimination between different colour textured regions in an image. the proposed method was tested using different mosaic and natural images. from the results, it is evident that the incorporation of colour information enhanced the colour texture segmentation and the developed framework is effective.
a general multichannel image restoration method using compound models. in this paper we present a multichannel image restoration method using compound gauss markov random field (cgmrf) models. information regarding the objects present in the scene is shared via the line process in the cgmrf. two new iterative algorithms to estimate the underlying multichannel image are presented, which can be considered as extensions of the classical simulated annealing and icm methods. experimental results demonstrate the effectiveness of the proposed approach.
quality-based score level fusion in multibiometric systems. the quality of biometric samples has a significant impact on the accuracy of a matcher. poor quality biometric samples often lead to incorrect matching results because the features extracted from these samples are not reliable. therefore, dynamically assigning weights to the outputs of individual matchers based on the quality of the samples presented at the input of the matchers can improve the overall recognition performance of a multibiometric system. we propose a likelihood ratio-based fusion scheme that takes into account the quality of the biometric samples while combining the match scores provided by the matchers. instead of estimating the quality of the template and query images individually, we estimate a single quality metric for each template-query pair based on the local image quality measures. experiments on a database of 320 users with iris and fingerprint modalities demonstrate the advantages of utilizing the quality information in multibiometric systems.
a cluster validity approach based on nearest-neighbor resampling. we introduce an approach for validating clustering results based on partition stability under a nearestneighbor resampling. the approach is relatively robust, efficient, and avoids conceptual problems of other common validation strategies. encouraging results compared to those of subsampling-based consensus clustering are presented for simulated data and (tumor) gene expression benchmark data sets. the proposed method is discussed in view of future applications to unsupervised learning from sample data.
a fuzzy min-max neural network classifier with compensatory neuron architecture. this paper proposes a supervised learning neural network classifier with compensatory neuron architecture. the proposed "fuzzy min-max neural network classifier with compensatory neurons" (fmcn) extends the principle of minimal disturbance. the new architecture consists of compensating neurons that are trained to handle the hyperbox overlap and containment. the fmcn is capable of learning data on-line, in a single pass through, with reduced classification and gradation error. one of the good features of fmcn is that its performance is almost independent of the expansion coefficient i.e. maximum hyperbox size. the paper demonstrates the performance of fmcn with several examples.
a reflex fuzzy min max neural network for granular data classification. granular data classification and clustering is an upcoming and important issue in the field of pattern recognition. the paper proposes a granular neural network called as "reflex fuzzy min-max neural network" for classification. reflex mechanism inspired from human brain is exploited here to handle class overlaps. this network can be trained on-line using granular or point data. the proposed neuron activation functions are designed to tackle data of different granularity (size). experimental results on real datasets show that the proposed algorithm can classify granules of different granularity more correctly compared to general fuzzy min max neural network proposed by gabrycz and bargiela.
unifying background models over complex audio using entropy. in this paper we extend an existing audio background modelling technique, leading to a more robust application to complex audio environments. the determination of background audio is used as an initial stage in the analysis of audio for surveillance and monitoring applications. knowledge of the background serves to highlight unusual or infrequent sounds. an existing modelling approach uses an online, adaptive gaussian mixture model technique that uses multiple distributions to model variations in the background. the method used to determine the background distributions of the gmm leads to a failure mode of the existing technique when applied to complex audio. we propose a method incorporating further information, the proximity of distributions determined using entropy, to determine a more complete background model. the method was successful in more robustly modelling the background for complex audio scenes.
model-based brain and tumor segmentation. combining image segmentation based on statistical classification with a geometric prior has been shown to significantly increase robustness and reproducibility. using a probabilistic geometric model and image registration serves both initialization of probability density functions and definition of spatial constraints. a strong spatial prior, however, prevents segmentation of structures that are not part of the model.our driving application is the segmentation of brain tissue and tumors from three-dimensional magnetic resonance imaging (mri). our goal is a high-quality segmentation of both healthy tissue and tumor. we present an extension to an existing expectation maximization (em) segmentation algorithm that modifies a probabilistic brain atlas with an individual subject's information about tumor location obtained from subtraction of post- and pre-contrast mri. the new method handles various types of pathology, space-occupying mass tumors and infiltr ating changes like edema. preliminary results on five cases presenting tumor types with very different characteristics demonstrate the potential of the new technique for clinical routine use for planning and monitoring in neurosurgery, radiation oncology, and radiology.
perceptual grouping for multiple view stereo using tensor voting. we address the problem of multiple view stereo from a perceptual organization perspective. currently, the leading methods in the field are volumetric. they operate at the level of scene voxels and image pixels, without considering the structures depicted in them. on the other hand, many perceptual organization methods for binocular stereo are not extensible to more images. we present an approach where feature matching and structure reconstruction are addressed within the same framework. in order to handle noise, lack of image features, anddiscontinuities, we adopt a tensor representation for the data and tensor voting for information propagation. the key contributions of this paper are twofold. first, we introduce "saliency" instead of correlation as the criterion to determine the correctness of matches; second, ourtensor representation and voting enable us to perform the complex computations associated with multiple view stereo at a reasonable computational cost. we present results on real data.
3d scanning using spatiotemporal orientation. we present a new approach to volumetric scene reconstruction which can produce accurate models from turntable image sequences. instead of an epipolar plane image (epi) volume, we consider a function on the 4d spatiotemporal volume valued with the intensity back projection of the camera (time) to the particular voxel. using an optical flow technique we compute the local orientation of this spatiotemporal image and decide on occupancy based on the relative orientation between the viewing ray of the voxel at the particular time and the local image structure. our method does not require a background compensation like the silhouette-based methods and is comparable in performance with space carving.
estimation and analysis of the deformation of the cardiac wall using doppler tissue imaging. this paper presents different ways to use the doppler tissue imaging (dti) in order to determine deformation of the cardiac wall. as an extra information added to the ultrasound images, the dti gives the velocity in the direction of the probe. we first show a way to track points along the cardiac wall in a m-mode image (1d+t). this is based on energy minimization similar to a deformable grid. we then extend the ideas to finding the deformation field in a sequence of 2d images (2d+t). this is based on energy minimization including spatio-temporal regularization.
a variational approach for color image segmentation. in this paper we use a variational bayesian framework for color image segmentation. each image is represented in the l*u*v color coordinate system before being segmented by the variational algorithm. the model chosen to describe the color images is a gaussian mixture model. the parameter estimation uses variational learning by taking into account the uncertainty in parameter estimation. in the variational bayesian approach we integrate over distributions of parameters. we propose a maximum log-likelihood initialization approach for the variational expectation-maximization (vem) algorithm and we apply it to color image segmentation. the segmentation task in our approach consists of the estimation of the distribution hyperparameters.
pen pressure features for writer-independent on-line handwriting recognition based on substroke hmm. this paper discusses the use of pen pressure as a feature in writer-independent on-line handwriting recognition. we propose two kinds of features related to pen pressure: one is the pressure representing pen ups and downs in a continuous manner; the other is the time-derivative of the pressure representing the temporal pattern of the pen pressure. combining either of them with the existing feature (velocity vector), a 3-dimensional feature is composed for character recognition. some techniques of interpolating the pen pressure during the pen-up interval is also proposed for a pre-processing purpose. through experimental evaluation using 1,016 elementary kanji characters compared with the baseline performance using velocity vector only, the additional use of pen pressure improved the performance from97.5% to 98.1% for careful writings and from 91.1% to 93.1% for cursive writings.
decomposing chinese characters into stroke segments using sogd filters and orientation normalization. the paper presents a novel directional feature extraction approach based on a directional filtering technique for chinese character recognition. the proposed filtering technique uses a set of the second-order gaussian derivative (sogd) filters to decompose a character into a number of stroke segments. moreover, a gaussian function is used to extract the stroke segments along arbitrary orientations. the optimal orientation of each stroke segment can be estimated by finding the maximal power response of the stroke segment from the gaussian function. finally, the effects of decomposition process are analyzed using some simple structural and statistical features extracted from the stroke segments. experimental results indicate that the proposed sogd filtering-based approach is very efficient to decompose noisy and degraded character images into a number of stroke segments along an arbitrary orientation. furthermore, the recognition performance from the application of decomposition process can be improved about 17.31% in test character set.
integration of shape and a multihypotheses fisher color model for figure-ground segmentation in non-stationary environments. in this paper a new technique to perform figure-ground segmentation in image sequences of scenarios with varying illumination conditions is proposed. the set of color points of both the target and background are modelled with mixture of gaussians (mog), which optimum number is automatically initialized. based on the 'linear discriminant analysis' (lda) a new colorspace that maximizes the foreground/background classseparability is presented. moreover, there is no need to assume gradual change of the viewing conditions over time, because the method works with multiple hypotheses about the next state of the color distribution (some considering small changes and other more abrupt variations). the hypothesis that generates the best object segmentation and the shape information in the previous iteration are fused to accurately detect the object boundary, in a stage denominated 'sample concentration', introduced as a final step to the classical condensation algorithm.
a three-frame approach to constraint-consistent motion estimation. we study the motion estimation across three images by simultaneously enforcing the geometric constraint of trilinearity and the constant-brightness constraint. an iterative and hierarchical three-frame scheme is proposed to solve the geometry-consistent and appearance-consistent motion fields. it provides an uncalibrated approach to dense motion estimation, applicable to both 2-d and 3-d rigid scenes under perspective projection with unconstrained camera motion. valid and consistent constraints are explored to alleviate the inherent aperture and over smoothing problems.
a target dependent colorspace for robust tracking. the selection of the appropriate colorspace for tracking applications has not been an issue previously considered in the literature. many color representations have been suggested, based on the invariance to illumination changes. nevertheless, none of them is invariant enough to deal with general and unconstrained environments. in tracking tasks, we might prefer to represent image pixels into a colorspace where the distance between the target and background colorpoints were maximized, simplifying the task of the tracker. based on this criterion, we propose an 'object dependent' colorspace, which is computed as a simple calibration procedure before tracking. furthermore, this colorspace may be easily adapted at each frame. synthetic and real experiments show how this colorspace allows for a better discrimination of the foreground and background, and permits to track in circumstances where the same tracking algorithm relying on other colorspaces would fail.
a practical stereo scheme for obstacle detection in automotive use. we propose a novel stereo scheme for obstacle detection which is aimed at practical automotive use. the basic methodology involves simple region matching between images, observed from a stereo camera rig, where it is assumed the images are related by a pseudo-projective transform. it provides an effective solution for determining boundaries of obstacles in noisy conditions, e.g. caused by weather or poor illumination, which conventional planar projection approaches cannot cope with. the linearity of the camera model also contributes significantly to compensation of road inclination. essentially, precise lane detection and prior knowledge concerning obstacles or ambient conditions are unnecessary and the proposed scheme is therefore applicable to a wide variety of outdoor scenes. we have also developed a multi-vliwprocessor that fulfills the essential specifications for automotive use. our scheme for obstacle detection is largely reflected in the processor design so that real-time on-board processing can be realized with acceptable cost to both automobile users and manufacturers. the implementation of a prototype and experimental results illustrate our method.
a hierarchical palmprint identification method using hand geometry and grayscale distribution features. palmprint identification, as an emerging biometric technique, has been actively researched in recent years. in existing palmprint identification algorithms, roi segmentation is always a must step. this paper presents a novel hierarchical palmprint identification method without roi extraction, which measures hand geometry and angle values in coarse-level feature extraction, and calculates unit information entropy of each subimage to describe grayscale distribution as the fine-level feature. we utilize the grayscale distribution variance caused by particular positions of principle lines, wrinkles and minutiae in primitive hand images as the palm descriptor instead of roi-based features. experiments were developed on a database of 990 images from 99 individuals. accuracy up to 99.24% has been obtained when using 6 samples per class for training. a performance comparison between the proposed method and roi-based pca method was made also.
a new classification rule based on nearest neighbour search. the nearest neighbour (nn) classification rule is usually chosen in a large number of pattern recognition systems due to its simplicity and good properties. as the problem of finding the nearest neighbour of an unknown sample is also of interest in other scientific communities (very large databases, data mining, computational geometry, ...), a vast number of fast nearest neighbour search algorithms have been developed during the last years. in order to improve classification rates, the k-nn rule is often used instead of the nn rule, but it yields higher classification times. in this work we introduce a new classification rule applicable to many of those algorithms in order to obtain classification rates better than those of the nearest neighbour (similar to those of the k-nn rule) without significantly increasing classification time.
3d real-time head tracking fusing color histograms and stereovision. a system that performs the tracking of a human head in 3d in real time is presented. the head shape is modeled by an ellipse with a trained color histogram of skin and hair samples. the color histogram is dynamically updated based on incoming image data in order to accommodate for varying illumination conditions. on the other hand, the size of the searched ellipse projected on the image is scaled depending on the depth information gathered from stereo vision. the strength of our method resides on the use of a predictive filter to fuse color and depth information, iteratively refining the location of the head in 3d and the parametersof the head color histogram.
category-dependent feature extraction for recognition of degraded handwritten characters. conventional methods for recognizing multiple fonts and handwriting are generally robust against deformation but are weak against degradation. this paper proposes a category-dependent feature extraction method that resists both deformation and degradation. our proposed method compares an input pattern with the template of each category and estimates the degree of degradation of the input pattern. approximate stroke run-lengths without degradation are then obtained by compensating the inaccurate runs caused by degradation. recognition experiments using degraded handwritten characters show that the proposed feature is superior to conventional ones in resisting degradation.
gray-scale thinning by using a pseudo-distance map. in this paper, the algorithm for thinning of greyscale images is proposed that is based on a pseudodistance map (pdm). the pdm is a simplified distance map of gray-scale image and uses only that features of image and objects that are necessary to build a skeleton. the algorithm works fast for large gray-scale images and allows constructing a high quality skeleton.
early recognition and prediction of gestures. this paper is concerned with an early recognition and prediction algorithm of gestures. early recognition is the algorithm to provide recognition results before input gestures are completed. motion prediction is the algorithm to predict the subsequent posture of the performer by using early recognition. in addition to them, this paper considers a gesture network for improving the performance of these algorithms. the performance of the proposed algorithm was evaluated by experiments of real-time control of a humanoid by gestures.
multi-resolution template kernels. domains in which shapes of objects change rapidly and significantly are a challenge for existing representation techniques: sport is a good example of this. we present a texture-based approach that copes with these problems in addition to resolution variation. a set of exemplar poses are learned from subsampled example images of the target object, creating a set of multi-resolution template kernels which when convolved with the image respond suitably. this technique may then be used in established tracking algorithms (e.g. condensation [contour tracking by shochastic propagation of conditional density]). we demonstrate the technique in two domains, and suggest a markov approach using it to model behaviour.
a generalized k-means algorithm with semi-supervised weight coefficients. a new classification algorithm corresponding to a generalization of the k-means algorithm is proposed, whose algorithm is named as a weighted k-means algorithm. weight coefficients, which provide weighted distortions between data and cluster centers, are incorporated into the algorithm to realize reliable classification. a method determining the appropriate values of the weight coefficients from class labeled data is introduced. under the situations where statistical distributions of data are changing gradually with time, the weighted k-means algorithm for semi-supervised data composed from initial labeled data and succeeding unlabeled data is investigated.
an oriented-contour point based voting algorithm for vehicle type classification. this communication deals with an oriented-contour point based voting algorithm for multiclass vehicle type identification (make and model). the system obtains similar results for equivalent recognition frameworks with different feature selections [8]. results also show the method to be robust to partial occlusion.
tracking objects using recognition. tracking is frequently considered a frame-to-frame operation. as such, object recognition techniques are generally too slow to be used for tracking. there are domains, however, where the objects of interest do not move most of the time. in these domains, it is possible to watch for activity in the scene and then apply object recognition techniques to find the object''s new location. this makes tracking a discrete process of watching for object disappearances and reappearances. we have developed a memory assistance tool that uses this approach to help people with slight to moderate memory loss keep track of important objects around the house. the system is currently deployed in a prototype smart home.
three dimensional short-term memory image. we proposed the three dimensional short-term memory image related to human memory and human vision. three dimensional short-term memory image composed of the three dimensional features reconstructed from the binocular foveated vision. the next fixation point is determined statistically from the feature points in the image projected from the 3-d short-term memory image. we show the effectiveness by simulating the binocular eye movements for the virtual world generated computer graphics and for the real world using pan-tilt cameras. it is found that the viewing world does not change suddenly though the eye moves quickly by introducing the 3-d short-term memory.
real-time object tracking without feature extraction. in this paper we propose an appearance-based tracking method without any feature extraction from the images. at first, range-finder system or stereo cameras measure the shape of the incoming object to prepare a cg model of the object. then many images are generated from the model and compared with input images captured by the cameras. motion parameter of the object is modified to minimize the difference between generated and captured images, and the parameter tracks the motion of the real object precisely when minimization is converged. at the image generating stage, occlusion is also simulated and we can easily handle the visible region of the object.
combining adaptive pde and wavelet shrinkage in image denoising with edge enhancing property. partial differential equation (pde) and wavelet shrinkage are two kinds of feature preserving regularized image recovery methods. in this paper, the equivalence of the two methods is discussed according to function space theory, and a new hybrid model combining adaptive pde and wavelet shrinkage is proposed. in the new hybrid model, we use adaptive pde with edge enhancing property. the regular coefficient of adaptive model is locally adjusted according to directional derivatives of image. compared with traditional smoothing models, the new hybrid model has no gibbs phenomena, smoothes image without staircasing, and enhances edge to preserve feature and texture of image. both theoretical analysis and experiments have verified the validity o f the new model proposed in this paper.
efficient non-maximum suppression. in this work we scrutinize a low level computer vision task - non-maximum suppression (nms) - which is a crucial preprocessing step in many computer vision applications. especially in real time scenarios, efficient algorithms for such preprocessing algorithms, which operate on the full image resolution, are important. in the case of nms, it seems that merely the straightforward implementation or slight improvements are known. we show that these are far from being optimal, and derive several algorithms ranging from easy-to-implement to highly-efficient.
eigen nodule: view-based recognition of lung nodule in chest x-ray ct images using subspace method. we previously proposed a recognition method of lung nodules based on experimentally selected feature values (such as contrast, circularities, etc.) of pathological candidate regions detected by our quoit filter. in this paper, we propose a new recognition method of lung nodule using each ct value itself in roi (region of interest) area as a feature value. in the clustering stage, first, the pathological candidate regions are classified into some clusters using principal component(pc) theories. a set of ct values in each roi is regarded as a feature vector, and then eigen vectors and eigen values are calculated for each cluster by applying principal component analysis(pca). the eigen vectors (we call them eigen images) corresponding to the 10 largest eigen values, are utilized as base vectors for subspaces of the clusters in the feature space. in the discrimination stage, correlations are measured between the testing feature vector and the subspace which is spanned by the eigen images. if the correlation with the abnormal subspace is large, the pathological candidate region is determined to be abnormal. otherwise, it is determined to be normal. by applying our new method, good results have been acquired.
objects velocity estimation on images sequences by hough transform with projection (htp). we propose to extend the hough transform (ht) to 3d lines in a particular case: for each 3d point, we search for the line passing through this point and fitting the other points. the method uses projection of data on different planes and the combination of these results using least square algorithm. we call this algorithm "hough transform with projection (htp)". the robustness of this method, compared to the classical ht will be displayed. we use later this algorithm to compute the speed of moving regions in images sequences, without any tracking.
direct mapping of visual input to motor torques. most methods for visual control of robots formulate the robot command in joint or cartesian space. to move the robot these commands are remapped to motor torques usually requiring a dynamic model of the robot. in this paper we present a method for parameterizing joint torques and learning to map visual input directly to them. the system is implemented and used to control a crs 465 robot. the results of the implementation demonstrate that the parameterization of the torques allows both the motion and position of the robot's end effectors to be controlled. moreover, it is shown that it is possible to map visual input directly to joint torques.
pattern recognition in interrelated data: the problem, fundamental assumptions, recognition algorithms. as an adjunct to the classical pattern recognition theory dealing with single objects, a new approach to supervised pattern recognition is proposed for a variety of practical problems in which the class-memberships of several inter-related objects making an entire data array are to be estimated jointly. it is assumed, first, that the known structure of the array has the form of an undirected graph of immediate pair-wise adjacency of objects represented by their feature vectors, and, second, that the a priori knowledge on expected combinations of classes is expressed as a hidden markov random field on that graph. the presence of pronounced a priori information on interdependence of class-memberships of immediately adjacent objects allows for drawing much more reliable decisions from relatively unreliable features than in the classical case when the classes of single object are a priori considered as independent.
a probabilistic approach to learning costs for graph edit distance. graph edit distance provides an error-tolerant way to measure distances between attributed graphs. the effectiveness of edit distance based graph classification algorithms relies on the adequate definition of edit operation costs. we propose a cost inference method that is based on a distribution estimation of edit operations. for this purpose we employ an expectation maximization algorithm to learn mixture densities from a labeled sample of graphs and derive edit costs that are subsequently applied in the context of a graph edit distance computation framework. we evaluate the performance of the proposed distance model in comparison to another recently introduced learning model for edit costs.
a convolution edit kernel for error-tolerant graph matching. general graph matching methods often suffer from the lack of mathematical structure in the space of graphs. using kernel functions to evaluate structural graph similarity allows us to formulate the graph matching problem in an implicitly existing vector space and to apply well-known methods for pattern analysis. in this paper we propose a novel convolution graph kernel. our kernel function differs from other graph kernels mainly in that it is closely related to error-tolerant graph edit distance and can therefore be applied to attributed graphs of various kinds. the proposed kernel function is evaluated on two graph datasets. it turns out that our method is generally more accurate than a standard edit distance based nearest-neighbor classifier, an edit distance based kernel variant, and a random walk graph kernel.
elastic transformation of the image pixel grid for similarity based face identification. nonlinear transformation of one image plane relative to another by spatially constrained elastic matching of two pixel grids is proposedas a technique of measuring image similarity for the purpose of featureless face identification. the elastic matching algorithm is devised as a combination of two dynamic programming procedures applied independently to each row and then to each column of the pixel grid. in contrast to the commonly adopted method of measuring face image similarity based on the dynamic link architecture, the proposed method is non-iterative and it avoids image segmentation. most importantly the method provides the linear computational complexity with respect to the number of pixels without application of parallel computers.
automatic segmentation of muscles of mastication from magnetic resonance images using prior knowledge. we propose a knowledge-based, fully automatic methodology for segmenting muscles of mastication from 2-d magnetic resonance (mr) images. to the best of our knowledge, there is currently no methodology which automatically segment muscles of mastication. in our approach, mr images with muscles of interest that have been manually segmented by medical experts are used to train the system to identify a relationship between the region of interest (roi) of the head and roi of the muscle. anisotropic diffusion is used to smooth the roi of the latter. neighboring regions of the muscle are removed by thresholding. a template of the muscle, from the manual tracings, is used to obtain an initial segmentation of the muscle. small unwanted regions in the roi are removed via connected components labeling. a gradient vector flow (gvf) snake, using the initial segmentation as initialization, is used to refine the initial segmentation. we performed 2-d segmentation of the medial and lateral pterygoids on a total of 50 mr images, in the mid-facial region through the mandible with accuracy ranging from 85% to 98%.
adjacent orientation vector based fingerprint minutiae matching system. minutia matching is the most popular approach to fingerprint recognition. in this paper, we analyzed a novel fingerprint feature named adjacent orientation vector, or aov, for fingerprint matching. in the first stage, aov is used to find possible minutiae pairs. then one minutiae set is rotated and translated. this is followed by a preliminary matching to ensure reliability as well as a fine matching to overcome possible distortion. such method has been deployed to a payroll and security access information system and its workability is encouraging. the information system aims to offer a highly secured and automated identification system for payroll tracking as well as authorized access to working areas.
a unified strategy to deal with different natures of reject. the interest of reject for classifier optimization has been shown many times. the diversity of the applications requiring this concept makes us to distinguish two main natures of reject with distinct goals: the confusion reject and the distance reject. after the description of this two kinds of reject, we present a unified formalism to define them using reliability functions and reject thresholds. then we present a generic algorithm dedicated to the automatic learning of these thresholds. finally, we compare various possibilities of reject to achieve application goals.
fingerprint image enhancement using a parallel ridge filter. fingerprint image enhancement is an important process for improving the matching performance of low quality fingerprints. in order to eliminate high contrast noise lines such as deep wrinkles, which are prevalent in the low quality fingerprint images, we focus on the fact that true ridges have multiple paralleling neighbors. in this report, we propose the parallel ridge filtering method which can strongly suppress non-parallel noise lines by utilizing the parallelism of ridges. we also show the efficiency of our method by experimental results.
separating subsurface scattering from photometric image. while subsurface scattering is common in many real objects, almost all separation algorithms focus on extracting specular and diffuse components from real images. in this paper, we present a model-less approach derived from the bi-directional surface scattering reflectance distribution function (bssrdf). in our approach, we show that an illumination image is composed by the lambertian diffuse and subsurface scattering images. by converting the separation problem into one of two-layer separation in the illumination domain, a bayesian framework is used to solve the optimization problem which incorporates spatial and illumination constraints, the latter of which are captured as a set of diffuse priors. we present the detailed mathematical formulation and experimental results.
monocular vision based slam for mobile robots. this paper describes a new vision based method for the simultaneous localization and mapping of mobile robots. the only data used is a video input from a moving calibrated monocular camera. from the detection and matching of interest points in images at video rate, robust estimates of the camera poses are computed in real-time and a 3d map of the environment is reconstructed. the computed 3d structure is constantly refined thanks to the introduction of a fast and local bundle adjustment method that makes this approach particularly accurate and reliable. actually, this method can be seen as a new visual tool that may be used in conjunction with usual systems (gps, inertia sensors, etc) in slam applications.
one dimensional fractal coder for online signature recognition. fractal theory has been used for computer graphics, image compression and different fields of pattern recognition. in this paper we simplified a general purpose two-dimensional fractal coder used for image compression. since in the case of on-line signature recognition, we loose gray levels, contrast and luminosity information, we do not employ these parameters in the fractal coder. instead, we focused on geometrical relationship between the range block and its best domain block. then, some features were extracted directly by the proposed one dimensional fractal coder. we will show their usefulness in the application of persian on-line signature recognition.
feature comparison between fractal codes and wavelet transform in handwritten alphanumeric recognition using svm classifier. in this paper we proposed a new method for isolated handwritten farsi/arabic characters and numerals recognition using fractal codes and haar wavelet transform. fractal codes represent affine transformations which when iteratively applied to the range-domain pairs in an arbitrary initial image, the result is close to the given image. each fractal code consists of six parameters such as corresponding domain coordinates for each range block, brightness offset and an affine transformation. in this system, the support vector machine (svm) whih is based on statistical learning theory, with good generalization ability is used as the classifier. this method is robust to scale and frame size changes. 32 farsi's characters are categorized to 8 different classes in which the characters are very similar to each others. there are ten digits in farsi/arabic language and since two of them are not used in the postal codes in iran, therefore 8 more classes are needed for digits. according to experimental results, classification rates of 92.71% and 92% were obtained for digits and characters respectively on the test sets gathered from various people with different educational background and different ages.
traffic prediction using ying-yang fuzzy cerebellar model articulation controller. traffic prediction is a critical element in traffic control today. with the increase of transportation, an effective traffic prediction allows to prevent traffic problems. this research aims to propose a novel approach to traffic prediction using ying-yang fuzzy cerebellar model articulation controller (yyfcmac). the model is motivated from the famous chinese ancient ying-yang philosophy, which views everything as a product of conflict-harmony process between ying and yang. that principle is applied to find the optimal number of clusters and fuzzy sets in the fuzzification phase of the hybrid fuzzy-neural yyfcmac network. the analyzed experiment on a set of real traffic data flow of the east-bound pan island expressway (pie) in singapore shows the effectiveness of the yy-fcmac in universal approximation and prediction.
hierarchical monitoring of people's behaviors in complex environments using multiple cameras. we present a distributed, surveillance system that works in large and complex indoor environments. to track and recognize behaviors of people, we propose the use of the abstract hidden markov model (ahmm), which can be considered as an extension of the hidden markov model (hmm), where the single markov chain in the hmm is replaced by a hierarchy of markov policies. in this policy hierarchy, each behavior can be represented as a policy at the corresponding level of abstraction. the noisy observations are handled in the same way as an hmm and an efficient rao-blackwellised particle filter method is used to compute the probabilities of the current policy at different levels of the hierarchy. the novelty of the paper lies in the implementation of a scalable framework in the context of both the scale of behaviors and the size of the environment, making it ideal for distributed surveillance. the results of the system demonstrate the ability to answer queries about people's behaviors at different levels of details using multiple cameras in a large and complex indoor environment.
a markovian approach for handwritten document segmentation. we address in this paper the problem of segmenting complex handritten pages such as novelist drafts or authorial manuscripts. we propose to use stochastic and contextual models in order to cope with local spatial variability, and to take into account some prior knowledge about the global structure of the document image. the models we propose to use are markov random field models.
extending the linear interpolating condition to advanced synthetic discriminant function variants. in previous work, we demonstrated that a linearity condition was sufficient for us to estimate distortion from the output of the synthetic discriminant function (sdf). however, many variants of the sdf have been developed. we extend the linear interpolating property to a class of sdf variants and use this result to analyse the properties of two of these variants.
4-d voting for matching, densification and segmentation into motion layers. we present a novel approach for grouping from motion, based on a 4-d tensor voting computational framework. from sparse point tokens in two frames we recover the dense velocity field, motion boundaries and regions, in a non-iterative process that does not involveinitialization or search in a parametric space, and therefore does not suffer from local optima or poor convergence problems. we encode the image position and potential velocity for each token into a 4-d tensor. a voting process then enforces the smoothness of motion while preserving motion discontinuities, selecting the correct velocity for each input point, as the most salient token. by performing an additional dense voting step we infer velocities at every pixel location, which are then used to determine motion boundaries and regions. we demonstrate our contribution with synthetic and real images, by analyzing several difficult cases ¿ opaque and transparent motion, rigid and non-rigid motion.
matching images features in a wide base line with ica descriptors. in this paper we present a method to recognize images features with a wide base line between learning and recognition phases. the method is based in feature descriptors derived from independent component analysis (ica). this technique is inspired by the problems of mobile robot mapping and localization using single camera. in the learning phase the descriptors are created to capture the variations in the appearance of each feature across a small base line tracking and stored in a database. the recognition phase proceeds to match descriptors created from the incoming video (with a wide base line respect to the learning phase) in the database. the implementation shows good computational performance.
a stereo and color-based method for face pose estimation and facial feature extraction. this paper describes a method to perform face pose estimation and high resolution facial feature extraction on the basis of stereoscopic color images. unlike other approaches no light projection is required at running time. in our method face detection is based on color driven clustering of 3d points derived from stereo. a mesh model is registered with the post-processed face cluster using a variant of the iterative closest point algorithm (icp). pose is derived from correspondence. then, pose and model information is used for face normalization and facial feature localization. results show, stereo and color are powerful cues for finding the face and its pose under a wide range of poses, illuminations and expressions (pie). head orientation may vary in out of plane rotations up to ± 45°.
knowledge based image enhancement using neural networks. in this paper we combine the concept of adaptive filters with neural networks in order to be able to include high level knowledge about the contents of the image in the filtering process. adaptive image enhancement algorithms often utilize low level knowledge like gradient information to guide filtering parameters. the advantage is that these filters do not need any specific knowledge and can thus be applied to a broad spectrum of images. however, for many problems this low level information is not sufficient to achieve good results. for example in medical imaging it is often very important that some features are preserved while others are suppressed. usually these features cannot be distinguished by low level information. therefore we propose a method to incorporate high level knowledge in the filtering process in order to adjust the parameters of any given filter thus creating a guided filter. we present a scheme for acquiring this high level knowledge which allows us to apply our method to all kinds of images using pattern recognition and special preprocessing techniques. the design of the guided filter itself is easy as for the high level knowledge only some sample pixels including their neighborhood and the desired parameters for these pixels are necessary.
luminance quasi-preserving color quantization for digital steganography to palette-based images. this paper proposes a method to apply bpcs-steganography that we have already proposed for gray scale images to palette-based images which consists of a palette storing color vector information and an index image whose pixel value is corresponding to a index in the palette. a palette-based images can be represented by combining r g and b color component images. we embed secret information into the g images. a number of color vectors in a palette after embedding by bpcs would be over the maximum number, which is usually 256. in order to reduce the number of colors, the rest two component images are then changed in a way that minimizes the square error. the idea behind the color quantization is that the degrading of images manipulated to reduce color is worse than the degrading which occurs with the embedding.
prominent symmetry points as landmarks in finger print images for alignment. for the alignment of two fing erprints position of certain landmarks are needed. these should be automatically extracted with low misidentification rate. as landmarks we suggest the prominent symmetry points (core-points) in the fing erprint. they are extracted from the complex orientation field estimated from the global structure of the fingerprint, i.e. the overall pattern of the ridges and valleys. complex filter s, applied to the orientation field in multiple resolution scales, are used to detect the symmetry and the type of symmetry. experimental results are reported.
human tracking using floor sensors based on the markov chain monte carlo method. the aim of this paper is to develop a human tracking system that is resistant to environmental changes and covers wide area. simply structured floor sensors are low-cost and can track people in a wide area. however, the sensor reading is discrete and missing; therefore, footsteps do not represent the precise location of a person. a markov chain monte carlo method (mcmc) is a promising tracking algorithm for these kinds of signals. we applied two prediction models to the mcmc: a linear gaussian model and a highly nonlinear bipedal model. the gaussian model was efficient in terms of computational cost while the bipedal model discriminated people more accurate than the gaussian model. the gaussian model can be used to track a number of people, and the bipedal model can be used in situations where more accurate tracking is required.
process mapping and functional correlation in surface metrology: a novel clustering application. surface finish of engineering components is measured and controlled to achieve a desired function. surface finish can also be used to provide feedback to the manufacturing process. an area of active research in surface metrology is in developing tools and techniques for providing greater insight into the relationship between surface texture, a component's function and the manufacturing process. in this context, this paper explores the use of different clustering techniques such as k-means, isodata and neural networks to relate surface metrology data to a component's function and the manufacturing process that produced the part.
model-based segmentation of leukocytes clusters. human leukocytes (white blood cells) can be divided into about twenty subclasses and the estimation of their distribution, called differential counting, is an important diagnostic tool in various clinical settings. automatic differential counters based on digital image analysis require good segmentation algorithms to locate each cell and the accuracy of the subsequent classification depends on the correct segmentation of solitary cells as well as complex cell clusters.early leukocyte segmentation algorithms relied on various thresholding schemes to locate the nucleus and cytoplasm of solitary cells but could not handle clusters. recently we described a complete segmentation procedure that solves the cluster-separation problem using moving interface models and a model-based combinatorial optimization scheme. in this paper, the algorithm is improved and its accuracy is evaluated.
statistical classification of raw textile defects. in this paper, the problem of classification of defects occurring in a textile manufacture is addressed. a new classification scheme is devised in which different features, extracted from the gray level histogram, the shape, and co-occurrence matrices, are employed. these features are classified using a support vector machines (svm) based framework, and an accurate analysis of different multi-class classification schemes and svm parameters has been carried out. the system has been tested using two textile databases showing very promising results.
biometric identification of mice. we present a new application area for biometric recognition: the identification of laboratory animals to replace today's invasive methods. through biometric identification a non invasive identification technique is applied with a code space that is restricted only by the uniqueness of the biometric identifier in use, and with an error rate that is predictable. in this work we present the blood vessel pattern in a mouse-ear as a suitable biometric identifier used for mouse identification. genuine and impostor score distributions are presented using a total of 50 mice. an eer of 2.5% is reported for images captured at the same instance of time which verifies the distinctive property of the biometric identifier.
object-based video coding using pixel state analysis. in archiving video for surveillance, frame-based coding has been used and it makes storage size large because the whole image is stored even if there is no object in the image. on the other hand, object-based coding has the capability to make storage size small, because it distinguishes between the foreground and the background regions of the image, and stores only foreground objects such as people. this paper describes object-based coding by pixel state analysis. in our method, pixel state analysis detects the foreground objects and background regions in video frames. furthermore, it distinguishes foreground object pixels as stationary or transient pixels. for stationary pixels, it is possible to restore the color intensity by refering to the same pixel location in the last frame. therefore, our method makes the storage size smaller. additionally, the transient pixels of foreground objects are compressed using lzh codec. since lzh codec uses lossless compression, the object region can be compressed with lesser loss in image quality. we have evaluated our system over 9 test sequences and obtained an improvement of 15% in compression ratio and better quality for the moving parts of the object region compared to mpeg-4.
correcting show-through effects on document images by multiscale analysis. this paper describes a new approach to restoring color document images where the backside image shows through the paper sheet. a new framework is presented for correcting show-through components using digital image processing techniques. first, the foreground components on the front side are separated from the background and backside components through locally adaptive binarization for each color component and edge magnitude thresholding. background colors are estimated locally through color thresholding to generate a restored image, and then corrected adaptively through multiscale analysis along with comparison of edge distributions between the original and the restored image. the proposedmethod is able to correct unneeded image components through analysis of the front side image alone. experimental results are given to verify effectiveness of the proposed method.
3d reconstruction from uncalibrated cameras and uncalibrated projectors from shadows. recently, projector camera systems have been studied extensively for designing man machine interaction systems. in this paper, we propose a new method for calibrating uncalibrated projector camera systems. in particular, we show that it is possible to calibrate camera projector systems projectively and reconstruct 3d information reliably by using shadows of objects made my projector lights. we also show that by using the projectively calibrated projector camera systems we can achieve virtual music instruments, such as virtual piano.
1d-hmm for face verification: model optimization using improved algorithm and intelligent selection of training images. in this paper, we present an optimized version of 1d-hmm for real-time face verification. dct coefficients of face images are used as observation vectors in hmm states. three modifications have been proposed to improve the overall performance of the approach: (1) replacing baum-welch algorithm with a clustering algorithm, (2) adding a clustering performance measure to the clustering algorithm and (3) selecting an intelligent training set among available images in data set. despite its lower computational complexity, this approach shows better verification performance compared with other 1d-hmm methods. the proposed algorithm has been successfully tested on the well known orl face data set, exhibiting an accuracy of 96%. this is more than 10% higher than the verification results of the classical 1d-hmms and is comparable with the results obtained with 2d-hmms, which is much more complex than 1d-hmm.
laplacian based non-linear diffusion filtering. this paper aims to introduce a diffusion filtering based on the laplacian map. classical non-linear diffusion filtering using the gradient-map-controlled local diffusivity. the laplacian maps has similar geometric properties with the gradient map for the extraction of the region boundaries. laplacian-based diffusion function has the same property with the perona-malik type and the weickert type diffusion functions for the small scale. however, for the large scale, the diffusion operation has similar geometrical properties with the linear diffusion filtering. therefore, the filtering operation in this paper provides a method for the combination of hierarchical expression based on linear and non-linear diffusion filtering operations.
view dependent enhancement of the dynamic range of video. there are many applications for computer vision where a scene observed contains a wide range of brightness. often, the low dynamic range of a camera limits the accuracy of information that can be extracted from the video. frames may contain saturated pixels of bright targets, poor resolution and noisy data for dark regions, or both. in this paper, we propose a method for generating high dynamic range (hdr) videos by combining successive frames. the first phase is to set the exposures for each frame contributing to one hdr frame. the exposures are automatically adapted according to image contents to provide a maximum amount of information about the target. hdr frames are then combined in a maximum likelihood manner, based on the noise model of image acquisition. experiments for texture based classification show that utilizing a proposed methodology, even the hdr videos built in real-time, contribute to many topical vision systems.
adaptive fusion for diurnal moving object detection. fusion of different sensor types (e.g. video, thermal infrared) and sensor selection strategy at signal or pixel level is a non-trivial task that requires a well-defined structure. in this paper, we provide a novel fusion architecture that is flexible and can be adapted to different types of sensors. the new fusion architecture provides an elegant approach to integrating different sensing phenomenology, sensor readings, and contextual information. a cooperative coevolutionary method is introduced for optimally selecting fusion strategies. we provide results in the context of a moving object detection system for a full 24 hours diurnal cycle in an outdoor environment. the results indicate that our architecture is robust to adverse illumination conditions and the evolutionary paradigm can provide an adaptable and flexible method for combining signals of different modality.
stereo correspondence using stripe adjacency graph. this paper presents a new approach to solve the problem of stereo correspondence. in order to extract visible surfaces with similar texture from two different images, our method encodes input images to a series of so-called stripe adjacency graphs (sag). a stripe is a connected region with only one segment on each scan-line and a sag is a group of stripes with neighbourhood relationships. the algorithm retrieves surfaces from binocular images according to the matching degree between two sub-graphs in two images. the extracted surfaces are evaluated by the global matching cost that is defined as the sum of inter-stripe and intra-stripe energy. the experimental results show that our algorithm is a fast as well as an effective algorithm. it can give a dense disparity map.
high-resolution video generation using morphing. in imaging devices such as ccds, there is a trade-off between the image resolution and frame rate because of the limitation of data transfer speed. this creates difficulties in producing a high-quality imaging system using only one sensor. therefore, we use a camera that has two imaging sensors with different spatio-temporal resolutions. the camera captures a high-resolution image sequence at a low frame rate and a low-resolution image sequence at a video rate. we propose using an image-morphing method to generate high-resolution video sequences from these two image sequences.
simultaneous determination of object shape and color by moire analysis using a reflection model. a method for determining the shape and color of an object simultaneously based on moiré analysis using a reflection model is presented. an rgb color system is employed to represent color information, and the color of an object is determined from the reflectance of rgb planes. utilizing color consistency and the specular reflection of reflected light, reflectance ambiguity for each rgb plane is reduced when using even a single light source, significantly improving the reliability of shape and reflectance determination for each rgb plane.
recovering non-overlapping network topology using far-field vehicle tracking data. this paper presents a weighted statistical method to learn the environment's topology using a large amount of far field vehicle tracking data collected by multiple, stationary non-overlapping cameras. first, an appearance model is constructed by the combination of normalized color and overall model size to measure the moving object's appearance similarity across the non-overlapping views. then based on the similarity in appearance, weighted votes are used to learn the temporally correlating information and hence to estimate the mutual information. by exploiting the statistical spatio-temporal information, our method can automatically learn the possible links between disjoint views and recover the topology of the network. the effectiveness of the proposed method is demonstrated by experimental results both on simulated and real video surveillance data.
bayesian approach with nonlinear kernels to feature extraction. presented here is a new algorithm for finding the positions of features in images of samples from particular object classes, such as human faces. existing algorithms that address this problem mostly deal only with image variations resulting from simple translation in the image plane, as well as differences of objects in the classes, by searching for features across the image plane. in our new algorithm, larger classes of image variations, including those resulting from object rotation in 3d space and scaling (i.e. translation in depth) are handled, in addition to image plane translation. in order to do this, we develop a new kernel-based map (maximum a posteriori) estimation technique using gaussian distribution in a potentially higher dimensional space to model the relationship between images and feature positions. experimental results of facial feature extraction in images of human faces taken from varying viewing directions and from varying distances demonstrate the superior performance of the new method relative to that of existing algorithms.
2d cascaded adaboost for eye localization. in this paper, 2d cascaded adaboost, a novel classifier designing framework, is presented and applied to eye localization. by the term "2d”, we mean that in our method there are two cascade classifiers in two directions: the first one is a cascade designed by bootstrapping the positive samples, and the second one, as the component classifiers of the first one, is cascaded by bootstrapping the negative samples (please refer to fig.1). the advantages of the 2d structure include: (1) it greatly facilitates the classifier designing on huge-scale training set; (2) it can easily deal with the significant variations within the positive (or negative) samples; (3) both the training and testing procedures are more efficient. the proposed structure is applied to eye localization and evaluated on four public face databases, extensive experimental results verified the effectiveness, efficiency, and robustness of the proposed method.
biometrics based asymmetric cryptosystem design using modified fuzzy vault scheme. we propose a novel biometrics cryptosystem where one can send and receive secure information using just the fingerprints. this cryptosystem is a judicious blend of the asymmetric cryptosystem like rsa and the symmetric fuzzy vault scheme having the advantages of both the aforementioned cryptosystems. we have proposed a modification of the fuzzy vault scheme to make it more robust against variations in the values of biometric features. finally we propose the use of invariant features as a key to producing a hierarchical security system where the same key (fingerprint) can be used to generate encrypted messages at different levels of security.
statistical borders for incremental mining. data streams - data flows in which the information arrives in a timely manner - have recently become a major subfield of knowledge extraction. one of their most important singularity is that only a part of the information remains available at a time, which makes it necessary to cope with uncertainty. in this paper, we introduce a novel statistical approach which biases the initial support for patterns mining. this approach holds the advantage to maximize one of two parameters (precision or recall) chosen by the user, while guaranteeing a statistical near optimal degradation of the other. this leads us to introduce the statistical borders, the relevant sets of frequent patterns in incremental mining of data streams. experiments performed on sequential patterns demonstrate the potential of this approach.
a coupon classification method based on adaptive image vector matching. this paper describes a coupon classification system based on image vector matching. this method features following two points. (1) extract a feature vector from a gray-scale image using a feature map which is derived from training coupon images. (2) classify a coupon image by adaptive mask distance to cope with the recognition difficulty such as partial cutting of coupon and putting stamp on it. we have implemented this method and experimented with collected samples. it achieved 100% of recognition rates, processing speed 11.76msec/sheet to 969 images for 42 kinds of coupon samples.
improving clustering algorithms through constrained convex optimization. inspired by the recent successes of boosting algorithms, a trend in unsupervised learning has begun to emphasize the need to explore the design of weighted clustering algorithms. in this paper, we handle clustering as a constrained minimization of a bregman divergence. theoretical results show benefits resembling those of boosting algorithms, and bring new modified weighted versions of clustering algorithms such as k-means, expectation-maximization (em) and k-harmonic means. experiments display the quality of the results obtained, and corroborate the advantages that subtle data reweightings may indeed bring to clustering.
grouping with bias for distribution-free mixture model estimation. some authors have recently devised adaptations of spectral grouping algorithms to integrate prior knowledge, as constrained eigenvalues problems. in this paper, we adapt recent statistical grouping algorithms to this task, as a non-parametric mixture model estimation problem. the approach appears to be attractive for its theoretical benefits, and its experimental results, as light bias brings dramatic improvements over unbiased approaches on hard images.
visual pattern recognition in the years ahead. conventional classification algorithms have already reached a plateau at the trade-off imposed by the bias due to the structure of the classifier and the variance due to the limited size of the training set. the latter may be alleviated by exploiting known constraints, including class and style priors, language models, statistical correlations between spatially proximate patterns, statistical dependence due to isogeny (common source) of patterns, and even information-theoretic properties of the representations that have evolved for symbolic patterns intended for communication. another development that may lead to new applications of pattern recognition is more effective human intervention. the interplay of human and machine abilities requires models that are both human and computer accessible.
activity summarisation and fall detection in a supportive home environment. automatic semantic summarisation of human activity and detection of unusual inactivity are useful goals for a vision system operating in a supportive home environment. learned models of spatial context are used in conjunction with a tracker to achieve these goals. the tracker uses a coarse ellipse model and a particle filter to cope with cluttered scenes with multiple sources of illumination. summarisation in terms of semantic regions is demonstrated using acted scenes through automatic recovery of the instructions given to the actor. the use of 'unusual inactivity' detection as a cue for fall detection is also demonstrated.
simple and efficient colorization in ycbcr color space. we have already proposed a colorization method in rgb color space, where the colorization problem is formulated as the maximum a posteriori (map) estimation of a color image given a monochrome image. markov random field (mrf) is used for modeling a color image which is utilized as a prior for the map estimation. in this paper, a colorization method in ycbcr space is presented, which is derived by the same formulation as in rgb color space. the presented method in ycbcr space is much simpler than that in rgb space and requires much less computation time: about one fourth of computation time in rgb space. as for quality of estimated color image, both methods in ycbcr and rgb space produce color images with comparable psnr values.
a formalization of on-line handwritten japanese text recognition free from line direction constraint. this paper presents a formalization of an on-line writing-box free, line-direction free handwritten japanese text recognition and its effect. by normalizing character orientation, even text of arbitrary character orientation can be recognized. the method evaluates the likelihood composed of character segmentation, character recognition, character pattern structure and context. the likelihood of character pattern structure considers the plausible height, width and gaps within a character pattern that appear in chinese characters composed of multiple radicals (subpatterns). we show how the newly modeled factors in the likelihood affect the overall recognition rate.
speaker verification using a novel set of dynamic features. dynamic cepstral features such as delta and deltadelta cepstra have been shown to play an essential role in capturing the transitional characteristics of the speech signal. in this paper, a set of new dynamic features for speaker verification system are introduced. these new features, known as delta cepstral energy (dce) and delta-delta cepstral energy (ddce), can compactly represent the information in the delta and delta-delta cepstra. furthermore, it is shown theoretically that dce carries the same information as the delta cepstrum using an entropy criterion. experimental speaker verification results on the timit database support the theoretical result, showing a significant improvement in terms of equal error rate compared with conventional feature extraction methods using delta and delta-delta cepstra.
morphology analysis of physiological signals using hidden markov models. we describe a clustering algorithm based on continuous hidden markov models (hmm) to automatically classify both electrocardiogram (ecg) and intracranial pressure (icp) beats based on their morphology. the algorithm detects, classifies and labels each beat based on morphology. in order to avoid the numerical problems with classical expectation-maximization (em) algorithm we apply a novel method of simulated annealing (sim) for hmm optimization. we show that better results are achieved using simulated annealing approach.
sharpening of ct images by cubic interpolation using b-spline. computed tomography (ct) is a method by which an original image is reconstructed based on the data of projected images collected from various directions, and is widely used in the fields of medicine and industry. however, the edge of the image reconstructed by ct is unsharp, therefore, microflaws are often overlooked. in this paper, we demonstrated that one of the causes of the decreased sharpness of the reconstructed image is associated with the linear interpolation during the back-projection process, and in our method, the linear interpolation is replaced by cubic interpolation using the b-spline. in addition, by calculating the control points of b-spline by fourier transform, the process required for the calculation of the control points appears to be eliminated. in the experiment, the reduction of unsharpness to 1/2 that of the conventional method and the reduction of processing time to a level equivalent to that of the conventional method have been achieved.
embedding motion in model-based stochastic tracking. particle filtering (pf) is now established as one of the most popular methods for visual tracking. within this framework, two assumptions are generally made. the first is that the data are temporally independent given the sequence of object states, and the second one is the use of the transition prior as proposal distribution. in this paper, we argue that the first assumption does not strictly hold and that the second can be improved. we propose to handle both modeling issues using motion. explicit motion measurements are used to drive the sampling process towards the new interesting regions of the image, while implicit motion measurements are introduced in the likelihood evaluation to model the data correlation term. the proposed model allows to handle abrupt motion changes and to filter out visual distractors when tracking objects with generic models based on shape representations. experimental results compared against the condensation algorithm have demonstrated superior tracking performance.
improving human activity detection by combining multi-dimensional motion descriptors with boosting. a new, combined human activity detection method is proposed. our method is based on efros et al.'s motion descriptors[2] and ke et al.'s event detectors[3]. since both methods use optical flow, it is easy to combine them. however, the computational cost of the training increases considerably because of the increased number of weak classifiers. we reduce this computational cost by extend ke et al.'s weak classifiers to incorporate multi-dimensional features. the proposed method is applied to off-air tennis video data, and its performance is evaluated by comparison with the original two methods. experimental results show that the performance of the proposed method is a good compromise in terms of detection rate and of computation time of testing and training.
robust 3d head tracking using camera pose estimation. in this paper we present a robust method to recover 3d position and orientation (pose) of a moving head using a single stationary camera. head pose is recovered via a camera pose estimation formulation. 3d feature points (artificial or natural occurring) are acquired from the head prior to tracking and used as a model. pose is estimated by solving a robust version of "perspective n point" problem. the proposed algorithm can handle self occlusions, outliers and recover from tracking failures. results were validated by simultaneous tracking using our system and an accurate magnetic field 3d measuring device. our contribution is a system that is not restricted to track only human heads, and is accurate enough to be used as a measuring device. to demonstrate the applicability of our method, three types of heads (human, barn owl, chameleon) were tracked in a series of biological experiments.
pattern recognition and understanding for visual information media. pattern recognition and understanding, pru, is a fundamental technology to realize intelligent visual information media, which can select, summarize, and augment the visual information in the real world according to the need of each individual. a three years research project, "pattern recognition and understanding for visual information media (vis-pru)", sponsored by the mext (ministry of education, culture, sports, science and technology, japan), has finished this march. the purpose of this project is to restructure the pru technology, which has been developed for making automatic machines to replace humans, into a key technology in the multimedia fields where the information media are expected to support the human activity and to augment the human ability. the critical difference between the two cases is that a human consumes the output of pru in multimedia systems, while a machineconsumes it in automated systems for substituting humans. in this talk, the achievements of the research project will be introduced and the pru in real time, human centered systems will be discussed.
faxed form identification using histogram of the hough-space. ordering and charging goods have been increasingly treated with faxed forms. although the faxocr system for specified forms is used practically, the performance to unspecified forms is not enough, because of the effect of noise on the faxed forms during the facsimile transmission. the final target of this study is to construct a practical faxocr system for unspecified forms. as the first stage, an identification method for unspecified faxed forms is proposed in this paper. in our approach, character separation and position adjustment are performed in the hough-space as pre-processing. then the form identification is carried out by using vote histogram in the hough-space. the performance of the proposed technique is verified experimentally by using actual faxed forms.
automatic tracking of local myocardial motion by correlation weighted velocity method. in this paper, we propose a new method for automatically tracking the motion of local region in left ventricular myocardium by means of ultrasonic pulsed doppler signal. this method consists of a velocity detection procedure based on correlation weighted mean instantaneous velocity and a motion tracking procedure employing a myocardial elastic model. most of ultrasonic pulsed doppler signals observed in clinical diagnosis contain considerable amount of speckle noise, which causes detection error of velocity. the detection error is accumulated in the motion tracking procedure and yields obviously incorrect motion trajectory. the procedure of correlation weighted mean velocity is aimed to reduce the velocity detection error, and the myocardial elastic model is used to avoid the accumulation of the error to keep track of the motion of the myocardium in reasonable accuracy. the result of evaluation test shows that this method is able to improve the accuracy of tracking approximately 40 % relative to a conventional cls approach.
outex- new framework for empirical evaluation of texture analysis algorithms. this paper presents the current status of a new initiative aimed at developing a versatile framework and image database for empirical evaluation of texture analysis algorithms. the proposed outex framework contains a large collection of surface textures captured under different conditions, which facilitates construction of a wide range of texture analysis problems. the problems are encapsulated into test suites, for which baseline results obtained with algorithms from literature are provided. the rich functionality of the framework is demonstrated with examples in texture classification, segmentation and retrieval. the framework has a web site for public dissemination of the database and comparative results obtained by research groups world wide.
temporally evaluated optical flow: study on accuracy. in order for visual feedback systems to have quick response, an image sequence captured at a much higher frame rate than the video rate has recently been employed. however, when optical flow, which is often used for vision-based control, is computed by the conventional methods using such an image sequence, the result contains significant error because there is almost no variance between any two successive image frames. to deal with this problem, we propose temporally evaluated optical flow, which we compute by measuring the time required for each pixel to move a fixed distance using temporally consistent shifts of each pixel. experimental results show that the proposed method improves accuracy and is superior to the conventional methods in terms of robustness.
a method for fine registration of multiple view range images considering the measurement error properties. this paper presents a new method for fine registration of two range images from different viewpoints that have been roughly registered. our method deals with the properties of the measurement error of the range image data. the error distribution is different for each point in the image and is usually dependent on both the viewing direction and the distance to the object surface. we find the best transformation of two range images to align each measured point and reconstruct 3d total object shape by taking such properties of the measurement error into account. the position of each measured point is corrected according to the variance and the extent of the distribution of its measurement error. the best transformation is selected by the evaluation of the effectiveness of this correction of every measured point. the experiments showed that our method produced better results than the conventional icp method.
robust estimation of camera translation between two images using a camera with a 3d orientation sensor. it is still a difficult problem to establish correspondences of feature points and to estimate view relations for multiple images of a static scene, if the images have large disparities. in this paper we explore the possibility of applying a cheap and general-purpose 3d orientation sensor to improve the robustness of matching such two images. we attach a 3d orientation sensor to a camera and use the system to acquire the images. the camera orientation is obtained from the sensor. assuming known intrinsic parameters of the camera, we are to estimate only the camera translation between the two views. owing to the small number of parameters needed to be estimated, it becomes possible to apply a voting method. we show that the method by voting is more robust than the methods based on random sampling, especially for difficult pair of images to make corre-spondences. in addition, using the known camera orientation, the images can be rectified so that it is as if they were taken by parallel cameras, before the candidate matches are searched for. this helps finding as many correct matches as possible for pairs of images that include rotation around the camera axis. experimental results for synthetic images as well as real images are shown.
range image registration preserving local structures of object surfaces. we propose a registration method for range images that preserves local structures of object surfaces. the method introduces shape patterns and a skewness of correspondences, both of which are extracted from the local surface nearby a point of interest in each image. the shape patterns are used to eliminate false corresponding pairs of surfaces, while the skewness is used to estimate the transformation that relates the coordinates between different range images. these two features enable us to estimate the transformation that preserves local structures of object surfaces.
robust text detection from binarized document images. many document images are rich in color and have complex background. to detect text from them, a standard approach utilizes both color and binary information. this often leads to time-consuming processing and requires a lot of parameters to be tuned. in contrast, we propose a new method for text detection using a binary image alone. the main virtues of our method include detection of both normal and inverted text and robustness to various font types, styles and sizes and small skew angles, combined with a moderate number of free parameters.
honeybees as an intelligent based approach for 3d reconstruction. this work is about the communication system used by honeybees with the idea of designing a new intelligent approach for 3d reconstruction. a new framework is proposed to allow the communication between 3d points in order to achieve an improved quasi-dense reconstruction. this method could be used reliably in further visual computing tasks because the obtained reconstruction emerges as a by product of an algorithmic intelligent process.
improving rbf-dda performance on optical character recognition through parameter selection. the dynamic decay adjustment (dda) algorithm is a fast constructive algorithm for training rbf neural networks. in previous works it has been shown that for some datasets the generalization performance of rbf-dda depends only weakly on the algorithm parameters ¿+ and ¿-. however, we have observed experimentally that for some problems performance is considerably dependent on the value of ¿-. in this work we propose a method for selecting the value of ¿- for performance optimization. the proposed method has been evaluated on three optical recognition datasets from the uci repository. the results show that the proposed method considerably improves the performance of rbf-dda with default parameters on these tasks. the results are compared to mlp and k-nn results obtained in previous works. it is shown that the method proposed in this paper outperforms mlps and obtains results comparable to k-nn on these tasks.
feature selection using multi-objective genetic algorithms for handwritten digit recognition. this paper discusses the use of genetic algorithm for feature selection for handwriting recognition. its novelty lies in the use of a multi-objective genetic algorithms where sensitivity analysis and neural network are employed to allow the use of a representative database to evaluate fitness and the use of a validation database to identify the subsets of selected features that provide a good generalization. comprehensive experiments on the nist database confirm the effectiveness of the proposed strategy.
a new approach to the classification of mammographic masses and normal breast tissue. a new approach to mammographic mass detection is presented in this paper. although different algorithms have been proposed for such a task, most of them are application dependent. in contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. in this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. two different databases were used to show the robustness of the approach. the first one consisted on a set of 160 regions of interest (rois) extracted from the mias database, being 40 of them with confirmed masses and the rest normal tissue. the second set of rois was extracted from the ddsm database, and contained 196 rois containing masses and 392 with normal, but suspicious regions. initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach.
pose clustering guided by short interpretation trees. it is common in object recognition algorithms based on viewpoint consistency to find object poses that align many of the object features with features extracted from a search image. algorithms usually treat these features as having no information other than location. however, in many applications, the features are much more distinctive than this. this distinctiveness can be used to improve recognition with respect to both the search time and the reliability of the recognition. we modify an efficient clustering method for detecting objects using geometry to incorporate short trees that help prune many of the possible matches between object features and image features prior to the more expensive clustering step. the methodology is applied to a problem of computing a spacecraft position with respect to a celestial body by recognizing the configuration of craters visible on the surface.
optimal estimation of perspective camera pose. in this paper we propose a practical and efficient method for finding the globally optimal solution to the problem of camera pose estimation for calibrated cameras. while traditional methods may get trapped in local minima, due to the non-convexity of the problem, we have developed an approach that guarantees global optimality. the scheme is based on ideas from global optimization theory, in particular, convex under-estimators in combination with branch and bound. we provide a provably optimal algorithm and demonstrate good performance on both synthetic and real data.
affine invariant information embedment for accurate camera-based character recognition. recognizing characters in a scene image taken by a digital camera has been studied for decades. however, it is still a challenging problem to achieve high accuracy. in this paper, we propose a method of embedding information in a character pattern so that the class of the character can be identified. the information should be robust against geometric distortions since an image taken by a digital camera is usually geometrically distorted. in the proposed method, a character pattern is designed in two colors so that the information is embedded as the area ratio of regions of two colors. since the area ratio is affine invariant, it is expected that the area ratio is correctly extracted even if a character image is affine-transformed. we generate character patterns with the embedded information and discuss the effectiveness of the proposed method.
precise estimation of high-dimensional distribution and its application to face recognition. in statistical pattern recognition, it is important to estimate true distribution of patterns precisely to obtain high recognition accuracy. normal mixtures are sometimes used for representing distributions. however, precise estimation of the parameters of normal mixtures requires a great number of sample patterns, especially for high dimensional vectors. for some pattern recognition problems, such as face recognition, very high dimensional feature vectors are necessary and there are always not enough training samples compared with the dimensionality. we present a method to estimate the distributions based on normal mixtures with small number of samples. the proposed algorithm is applied to face recognition problem which requires high dimensional feature vectors. experimental results show the effectiveness of the proposed algorithm.
learning wormholes for sparsely labelled clustering. distance functions are an important component in many learning applications. however, the correct function is context dependent, therefore it is advantageous to learn a distance function using available training data. many existing distance functions is the requirement for data to exist in a space of constant dimensionality and not possible to be directly used on symbolic data. to address these problems, this paper introduces an alternative learnable distance function, based on multi-kernel distance bases or wormholes that connects spaces belonging to similar examples that were originally far away close together. this work only assumes the availability of a set data in the form of relative comparisons, avoiding the need for having labelled or quantitative information. to learn the distance function, two algorithms were proposed: 1) building a set of basic wormhole bases using a boosting-inspired algorithm. 2) merging different distance bases together for better generalisation. the learning algorithms were then shown to successfully extract suitable distance functions in various clustering problems, ranging from synthetic 2d data to symbolic representations of unlabelled images.
scale invariants of three-dimensional legendre moments. three-dimensional digital images are gaining more attention in pattern recognition field. mostly literatures, however, only focus on theoretical framework of twodimensional moment invariants, that are only implemented on two-dimensional images. consequently, it reduces the invariance flexibility to support three-dimensional objects. in this paper, we introduce three-dimensional scale invariants of legendre moments. they are algebraically derived directly from legendre polynomials. simulated experiments using three-dimensional binary images are carried out to verify the validity of proposed invariance.
deciphering layered meaning in gestures. signs produced by gestures (such as in american sign language) can have a basic meaning coupled with additional meanings that are layered over the basic meaning of the sign. these layered meanings are conveyed by temporal and spatial modification of the basic form of thegesture movement. the work reported in this paper seeks to recognize temporal and spatial modifiers of hand movement and integrates them with the recognition of the basic meaning of the sign. to this end, a bayesian network framework is explored with a simulated vocabularyof 4 basic signs which give rise to 14 different combinations of basic meanings and layered meanings. recognition accuracies of upto 88.2% were obtained.
shooting the lecture scene using computer-controlled cameras based on situation understanding and evaluation of video images. in this paper, we propose a computer-controlled camera work that shoots object scenes to model the professional cameramen's work and selects the best image among plural video images as a switcher. we apply this system to a shooting of a lecture scene. in the first, our system estimates a teacher's action based on features of a teacher and a blackboard. in the next, each camera is directed to a shooting area based on the teacher's action, automatically. in the last, this system selects the best image among plural images under the evaluation rule. moreover, we have tried experiments of shooting lecture scene and have confirmed the effectiveness of our approach.
space-time analysis of spherical projection image. in this paper, a novel analysis of space-time volume of spherical projection image is presented. so far, space-time analyses have been extensively conducted for various purposes, i.e. 3-d reconstruction, estimation of camera motion and novel view synthesis and most of them consider only a planer projection and a single camera. in contrast, we conducted analysis on spherical projection for multiple cameras. since spherical projection does not change its appearance in relation to rotation around the origin of the sphere, extrinsic camera parameters and synchronous parameters of multiple video cameras can be simultaneously estimated by registering multiple space-time volumes of spherical projection, which can be easily achieved by block-matching technique. by using the parameters, multiple video images can be successfully integrated into single omni-directional images without distortions.
moving object detection using a cross correlation between a short accumulated histogram and a long accumulated histogram. this paper presents a method for detecting moving objects effectively in the weather whose visibility is bad, such as in a snowfall or in a dense fog. in such weather, the visibility changes rapidly in a short time and the intensity of each pixel changes hard every frame. in order to overcome these problems, the proposed method divides an input image into grid regions and in each region, calculates a cross correlation between two histograms whose accumulated number of frames are different. a short accumulated histogram, generated from accumulating a few number of frames, changes quickly whenever moving objects go into the region. on the other hand, a long accumulated histogram, generated from accumulating the more number of frames, changes slowly. therefore, moving objects are detected by measuring a variation on a cross correlation between a short accumulated histogram and a long accumulated histogram. experimental results obtained with heavy snow images have shown the effectiveness of the proposed method.
large scene reconstruction with local details recovery. we propose a method to recover the global structure with local details around a point. to handle a large scale of motion i.e. 360 degree around the point, we use an optimization-based algorithmto estimate the structure from the panorama around the fixed camera point. the global structure estimated can thus be used to initialize a structure from motion algorithm to recover the local details through simple camera motion such as panning. synthetic as well as real data are used to test the validity of the algorithm. our method can be used in applications such as authoring of virtual environments from real scene.
2d silhouette and 3d skeletal models for human detection and tracking. in this paper we propose a statistical model for detection and tracking of human silhouette and the corresponding 3d skeletal structure in gait sequences. we follow a point distribution model (pdm) approach using a principal component analysis (pca). the problem of non-lineal pca is partially resolved by applying a different pdm depending of pose estimation; frontal, lateral and diagonal, estimated by fisher's linear discriminant. additionally, the fitting is carried out by selecting the closest allowable shape from the training set by means of a nearest neighbor classifier. to improve the performance of the model we develop a human gait analysis to take into account temporal dynamic to track the human body. the incorporation of temporal constraints on the model increase reliability and robustness.
monocular lie algebra approach for 3d motion estimation. this work presents a monocular method to estimate 3d motion of an object in the visual space. our method is based on the theory of system identification, it identifies the optimal estimated value of the parameters that defines a 3d motion. the lie algebra approach assures the estimation of the parameters of the shortest orbit (geodesic) of the involved group action. experiments validate the effectiveness of the method.
omnidirectional vision tracking with particle filter. visual tracking is one of the most important topics of computer vision. challenging situations occurs when the time between frames is long enough to show significant spatial jumps of the target being tracked or when the target has unexpected motions. in this paper we offer an alternative to these situations. we use background subtraction to find the foreground regions (regions that move between frames). using the foreground regions and a modified version of the well-known particle filter we are able to track targets in an omnidirectional sequence with a low frame rate (one or two frames per second). our approach can tackle unexpected discontinuities and changes in the direction of the motion.
gaussian noise elimination in colour images by vector-connected filters. this paper deals with the use of vector-connected filters for eliminating gaussian noise in colour images. this class of morphological filters suppresses noise but preserves the contours of the objects. we impose a total order between pixels for morphological processing. once the hsi space has been adapted, we employ it in the lexicographical order. as such, all of the morphological operations are vectorial. after having defined the vectorial geodesic operators, they are then employed to eliminate gaussian noise.
comparison of colour spaces for optic disc localisation in retinal images. the location of the optic disc is of critical importance in retinal image analysis. in this work we improve on an approach introduced in [3] which localises an optic disc region through greylevel morphology followed by snake fitting. we propose and implement both the automaticinitialisation of the snake and the application of morphology in colour space. we examine various methods of performing the morphology step (to remove the interference of blood vessels) and compare them against each other. we demonstrate that our proposed simple lab colour morphology method is particularly suitable for the characteristics of our optic disc images. results indicate 90.32% average accuracy in localising the optic disc boundary.
human tracking by particle filtering using full 3d model of both target and environment. this work presents a new approach based on particle filtering to directly estimate the 3d positions of humans. our system can predict occlusions due to other movements because we track humans in a 3d space, not on a 2d image plane. in addition, we introduce a 3d environmental model as the background model for tracking. this makes it easier to handle occlusions due to fixed objects in the environment. the 3d environmental model is automatically constructed by our original method from video sequences. experiments show that our system is stable under occlusions due to the movements of both other subjects and fixed objects.
talking faces - technologies and applications. this paper gives an overview of facial animation techniques. while facial animation is currently used in the entertainment and advertisement industry, it will become part of dialog systems in commercial applications. animation techniques based on 3d models and image-based rendering are presented and evaluated by the following characteristics: automatism, realism and flexibility. while animation techniques based on 3d models provide for high flexibility and automatism, they often lack realism. image-based techniques achieve photo realism, but lack in automatism and flexibility.
a particle filter for tracking densely populated objects based on explicit multiview occlusion analysis. a novel particle filter is presented for tracking densely populated objects moving on a two-dimensional plane; it is based on a probabilistic framework of explicit multiview occlusion analysis. the spatial structure of 2-d occlusion process between objects is modeled as a hidden process controlled by a markov probability structure. the tracking problem is then formulated as a recursive bayesian framework for solving the simultaneous estimation problem of two interactive processes; hypothesis generation/testing of the occlusion structure and the computation of posterior probability distribution of object states such as position and pose. for efficient implementation of the formulated framework, we develop a novel particle filter in which each particle can support multiple posterior distributions of object states on different occlusion hypotheses. experiments using synthetic and real data confirm the robustness of the proposed method even in the face of severe occlusion.
multiclass pattern classification using neural networks. multiclass neural learning involves finding appropriate neural network architecture, encoding schemes, learning algorithms, etc. in this paper, we discuss major approaches used in neural networks for classifying multiple classes. the discussion is focused d on these architectures using either a system of multiple neural networks or a single neural network. we will discuss various learning algorithms, one-again-all, one-against-one, and p-against-q. we will also discuss training procedures associated with each approach, implementation and time complexity. these methods are evaluated though their performances on the nist handwritten digit database.
self-supervised writer adaptation using perceptive concepts: application to on-line text recognition. we recently designed a hand-printed text recognizer. the system is based on three set of experts respectively used to segment, classify and validate the text (with a french lexicon : 200k words). we present in this communication writer adaptation methods. the first is supervised by the user. the others are self-supervised strategies which compare classification hypothesis with lexical hypothesis and modify consequently classifier parameters. the last method increases the system accuracy and the classification speed. experiments are presented on a large database of 90 texts (5400 words) written by 54 different writers and good recognition rates (82%) have been obtained.
developing assistant tools for geometric camera calibration: assessing the quality of input images. this paper proposes two indicators for predicting the quality of camera model parameters from a set of input images. the first indicator is based on the acutance. it can quickly indicate static or motion blur during image capture and correlates well with the 3d reconstruction error when using stereo cameras. the second indicator provides the overall distribution of control points in a set of input images. although the importance of covering the entire field of view is verified, the spatial distribution of control points need not be uniform. the analysis is supported by experiments with mono and stereo cameras calibrated using both a low cost planar and a high quality 3d target.
markovian random fields energy minimization algorithms. this paper introduces two frameworks that are modified versions of iterated conditional modes (icm) algorithm. these methods provide an efficient minimization of markovian random fields (mrf) energy function with substantial reduction in computing time. an application to a multi-resolution motion detection scheme is then presented and the results of the two frameworks are discussed and compared to those obtained by icm.
fingerprint matching with rotation-descriptor texture features. a novel texture correlation matching method for fingerprint verification using fourier-mellin descriptor and phase-only correlation function is proposed in this paper. fourier-mellin descriptor correlation is used to align the template and query fingerprint images and a matching score is obtained. matching takes about 1 second in celeron 2.0 ghz processor, and the experimental results show that eer is 3.8%; fusion with minutia matching gets a better result.
exploring human eye behaviour using a model of visual attention. it is natural in a visual search to look at any object that is similar to the target so that it can be recognised and a decision made to end the search. eye tracking technology offers an intimate and immediate way of interpreting users' behaviours to guide a computer search through large image databases. this paper describes experiments carried out to explore the relationship between gaze behaviour and a visual attention model that identifies regions of interest in image data. results show that there is a difference in behaviour on images that do and do not contain a clear region of interest.
tracking hands and objects for an intelligent video production system. we propose a novel method for detecting hands and hand-held objects in desktop manipulation situations. in order to achieve robust tracking under few constraints, we use multiple image sensors, that is, a rgb camera, a stereo camera, and an ir camera. by using these sensors, our system realized robust tracking without the prior knowledge of an object even if there are moving people or objects in the background. we experimentally verified the performance of object tracking by each of the three sensors and evaluated the effectiveness of their integration.
a trainable similarity measure for image classification. in object recognition problems a two-stage system is usually adopted composed of a fast and simple detector and a more complex classifier. this paper studies a design of the second stage classifier based on the recently proposed trainable similarity measure which is specifically designed for supervised classification of images. common global measures such as correlation suffer from uninformative pixels and occlusions. the proposed measure is based on local matches in a set of regions within an image which increases its robustness. the configuration of local regions is derived specifically for each prototype by a training procedure. the paper compares the classifiers built using the trainable similarity to the state-of-the-art adaboost classifiers on a real-world pedestrian recognition problem. the paper illustrates that for a given range of sample sizes the trainable similarity represents a better solution for secondstage classification than the adaboost algorithm which requires significantly larger training sets.
multi-class extensions of the gldb feature extraction algorithm for spectral data. the generalized local discriminant bases (gldb) algorithm proposed by kumar, ghosh and crawford in [best-bases feature extraction algorithm for classification of hyperspectral data], is a effective feature extraction method for spectral data.it identifies groups of adjacent spectral wavelengths and for each group finds a fisher projection maximizing the separability between classes. the authors defined gldb as a two-class feature extractor and proposed a bayesian pairwise classifier (bpc) building all pairwise extractors and classifiers followed by a classifier combining scheme. with a growing number of classes the bpc classifier quickly becomes computationally prohibitive solution. in this paper, we propose two alternative multi-class extensions of gldb algorithm, and study their respective performances and execution complexities on two real-world datasets. we show how to preserve high classification performance while mitigating the computational requirements of the gldb-based spectral classifiers.
a new optimised de bruijn coding strategy for structured light patterns. coded structured light is an optical technique based on active stereovision that obtains the shape of objects. one-shot techniques are based on projecting a unique light pattern with an lcd projector so that grabbing an image with a camera, a large number of correspondences can be obtained. then, a 3d reconstruction of the illuminated object can be recovered by means of triangulation. the most used strategy to encode one-shot patterns is based on de bruijn sequences. in this paper a new way to design patterns using this type of sequences is presented. the new coding strategy minimises the number of required colours and maximises both the resolution and the accuracy.
recognition of english multi-oriented characters. there are some printed artistic documents where text lines may be curved in shape. as a result, characters of a single line may be multi-oriented. to handle such artistic documents, in this paper, we present a scheme towards the recognition of multi-oriented and multi-sized english characters. the features used here are invariant to character orientation and computed based on the angular information of the border points of the characters. we used modified quadratic discriminant function (mqdf) for recognition. we tested our proposed scheme on a dataset of 18232 characters and obtained 98.34% accuracy from the system.
fast object localization using multi-scale image relevance function. an object detection method using a model-based visual attention mechanism is proposed in application to visual inspection problems and medical diagnostic imaging. the proposed method is based on a multi-scale operator called image relevance function - a non-linear multi-scale filter bank that has local maxima at the centers of object locations. model-based design of this operator takes into account intensity, shape and texture features of the objects to be detected. this approach offers several advantages, including fast and accurate object localization, simple extraction of shape features, adaptive segmentation of object regions.
multi-scale model-based skeletonization of object shapes using self-organizing maps. in this paper, a new skeletonization algorithm suitable for the skeletonization of sparse shape is described. it is based on self-organizing maps (som) -a class of neural networks with unsupervised learning. the so-called structured som with local shape attributes such as scale and connectivity of vertices are used to determine the object shape in the form of piecewise linear skeletons. the location of each vertex of piecewise linear generating lines on the image plane corresponds to the position of a particular som unit. this method makes it possible to extract the object skeletons and to reconstruct the planar shape of sparse objects based on the topological constraints of generating lines and estimation of scales.
perceptual knowledge extraction using bayesian networks of salient image objects. a novel approach to perceptual knowledge extraction from images based on the concept of salient image objects is proposed. salient image object - a concise description of a image fragment within a circular region - is a vector of salient image features, which describes the fragment invariantly to geometrical transformations and some intensity changes. bayesian network of salient image objects - a kind of generative image modeling - is used as a model for the knowledge representation, which includes semantic entities (e.g., real-world objects) and provides probabilistic relations between image features and semantic entities. the proposed technique of multi-scale image relevance function permits a fast and ordered extraction of salient image objects.
perceptual knowledge extraction using bayesian networks of salient image objects. a novel approach to perceptual knowledge extraction from images based on the concept of salient image objects is proposed. salient image object - a concise description of a image fragment within a circular region - is a vector of salient image features, which describes the fragment invariantly to geometrical transformations and some intensity changes. bayesian network of salient image objects - a kind of generative image modeling - is used as a model for the knowledge representation, which includes semantic entities (e.g., real-world objects) and provides probabilistic relations between image features and semantic entities. the proposed technique of multi-scale image relevance function permits a fast and ordered extraction of salient image objects.
bottom-up hierarchical image segmentation using region competition and the mumford-shah functional. this paper generalizes the methods in a previous paper [10] in two ways. first, a more comprehensive analysis of the initialization problem of the chan-vese models is given. second, the image segmentation method proposed in [10] is improved by applying bimodal curve evolution with region competition. the improved method maintains the advantages of the previous method. it is efficient, stable in the presence of strong noise and able to handle complicated images. it outperforms the previous method for images with weak edges. experimental results in this paper demonstrate these improvements.
novel seed selection for multiple objects detection and tracking. this paper proposes a unified approach for initializing, detecting and tracking of multiple moving objects. object initialization is achieved through novel seed selection which is adaptively activated, depending on the quality of tracking, to select the best possible frames along the temporal direction for object detection. em algorithm is then employed to robustly segment and detect multiple objects in a selected frame. each detected object is represented by an appearance-based model and mean shift tracking procedure is adopted to rapidly and effectively track the target objects.
finding symmetry plane of 3d face shape. the symmetry plane detection from 3d face shape is much helpful for pose estimation and feature extraction for a wide range of applications, e.g. 3d face recognition. this paper proposes a robust symmetry plane detection method for 3d face models, which is an extension of egi-based approach. the experiments using two data sets, usf humanid 3d face database and 3dfed database covering significant variation in facial expression, demonstrate the effectiveness.
on automated tongue image segmentation in chinese medicine. automated tongue image segmentation in chinese medicine is difficult due to two special factors: (1) there are a lot of pathological details on the surface of tongue, which have a large influence on edge extraction; (2) the shapes of tongue bodies captured from various diseases or persons are quite different, so they are impossible to be properly described by a predefined deformable template. to address these problems, in this paper, we propose an original technique based on the combination of a bi-elliptical deformable template and an active contour model, namely bi-elliptical deformable contour (bedc). applying our approach to clinical tongue images, the experimental results indicate that it is superior over both traditional dt (deformable templates) and acm (active contour model or snakes) with respect to stability and veracity.
structure in errors: a case study in fingerprint verification. measuring the accuracy of biometrics systems is important. accuracy estimates depend very much on the quality of the test data that are used. including poor quality data will degrade the accuracy estimates. what are the good quality data and what are the poor quality data is not revealed by simple accuracy estimates. we propose a novel methodology to analyze how the overall accuracy estimate of a system relates to the specific quality of biometrics samples. using a large collection of fingerprint samples, we present an analysis of system accuracy, which suggests that a signifi cant part of the error is due to few fingers.
mandarin emotional speech recognition based on svm and nn. the exploration of how we as human beings react to the world and interact with it and each other remains one of the greatest scientific challenges. the ability to recognize emotional states of a person perhaps the most important for successful inter-personal social interaction. automatic emotional speech recognition system can be characterized by the used features, the investigated emotional categories, the methods to collect speech utterances, the languages, and the type of classifier used in the experiments. in this paper, we used svm and nn classifiers and feature selection algorithm to classify five emotions from mandarin emotional speech and compared their experimental results. the overall experimental results reveal that the svm classifier (84.2%) outperforms than nn classifier (80.8%) and detects anger perfectly, but confuses happiness with sadness, boredom and neutral. the nn classifier achieves better performance in recognizing sadness and neutral and differentiates happiness and boredom perfectly.
quasi-invariants for human action representation and recognition. although human action ecognition has been the subject of much esearch in the past, the issue of viewpoint invariance has eceived scarce attention. in this paper, we present an approach to detect human action with a high tolerance to viewpoint change. canonical body poses are modeled in a view invariant manner to enable detection from a general viewpoint. while there exist no invariants for 3d to 2d projection, there exists a wealth of techniques in 2d invariance that can be used to advantage in 3d to 2d projection. we employ 2d invariants to recognize canonical poses of the human body leading to an effective way to represent and recognize human action which we evaluate theoretically and experimentally on 2d projections of publicly available human motion capture data.
learning prototypes and distances (lpd). a prototype reduction technique based on nearest neighbor error minimization. a prototype reduction algorithm is proposed which simultaneous train both a reduced set of prototypes and a suitable local metric for these prototypes. starting with an initial selection of a small number of prototypes, it iteratively adjusts both the position (features) of these prototypes and the corresponding local-metric weights. the resulting prototypes/metric combination minimizes a suitable estimation of the classification error probability. good performance of this algorithm is assessed through experiments with a number of benchmark data sets and through a real two-class classification task which consists of detecting human faces in unrestricted-background pictures.
ancient initial letters indexing. discrimination of images is necessary in many tasks, either understanding or indexing for example. here we are concerned by indexing. more precisely we are working about initial letters extracted from early renaissance printed documents as an application. different observation levels can be considered according to the applications, either details can be observed or more globally what could be called the style. here we are concerned with a global view of image. then we are going to present a new method to index ornamental letters in ancient books. we show how the zipf law, originally used in mono-dimensional domains can be adapted to the image domain. we use it as a model to characterize the distribution of patterns occurring in these special images that are initial letters. based on this model some new features are extracted and we show their efficiency for image indexing and retrieval.
event semantics in two-person interactions. this paper presents a method to represent two-person interactions at a semantic level with a natural language description. a human interaction is composed of two single-person actions, which in turn are made up of torso and arm/leg motions. we adopt the 'everb argument structure' in linguistics to represent human action in terms of triplets. various two-person interactions are represented at a detailed level using multiple triplets aligned along a time line according to the spatial/temporal constraints of the interactions. our method provides a user-friendly natural-language description of various human interactions, and properly describes positive, neutral, and negative interactions occurring between two persons.
efficient measurement of eye blinking under various illumination conditions for drowsiness detection systems. in this paper, we propose an efficient way of measuring the level of eye blinking under various illumination conditions (such as day and night) for drowsiness detection systems which use a single camera. determining the level of drowsiness by using eye blinking, it is an important way of detection eye positions and measuring eyelid movements. for robust eye detection under various illumination conditions, we propose a simple illumination compensation algorithm and a novel way of measuring of eyelid movements. in order to estimate the performance of the proposed methods, we collected video data during real driving situations under various illumination conditions, such as during the day and during the night. experimental results demonstrate an average eye detection rate of over 98% and an accurate measurement of eye blinking when using the proposed drowsiness detection system.
vise: visual search engine using multiple networked cameras. we propose a visual search engine (vise) as a semi-automatic component in a surveillance system using networked cameras. the vise aims to assist the monitoring operation of huge amounts of captured video streams, which tracks and finds people in the video based on their primitive features with the interaction of a human operator. we address the issues of object detection and tracking, shadow suppression and color-based recognition for the proposed system. the experimental results on a set of video data with ten subjects showed that vise retrieves correct candidates with 83% recall at 83% precision.
support vector clustering combined with spectral graph partitioning. in this paper, we propose a new support vector clustering (svc) strategy by combining (svc) with spectral graph partitioning (sgp). svc has two main steps: support vector computation and cluster labeling using adjacency matrix. spectral graph partitioning (sgp) method is applied to the adjacency matrix to determine the cluster labels. it is feasible to combine multiple adjacency matrices computed using different parameters. a novel multi-resolution combination method is proposed for cluster labeling using the sgp for the purpose of boosting the clustering performance.
enhancing low-resolution facial images using error back-projection for human identification at a distance. this paper proposes a new method of enhancing the resolution of low-resolution facial images using an error back-projection method based on a top-down learning. a face is represented by a linear combination of prototypes of shape and texture. with the shape and texture information about the pixels in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes. in addition, an error back-projection procedure is applied to improve the accuracy of resolution enhancement.
automatic microarray image segmentation based on watershed transformation. microarrays are miniature arrays of gene fragments attached to glass chips. microarrays allow the detection of subtle differences in genome sequences so that they can be used to detect and classify genetic diseases very accurately. microarray experiments generate large amounts of data, because they allow thousands of genes to be processed in a single experiment. to obtain meaningful information from the massive microarray experimental results, it is needed to develop a fully automatic subgrid and spot segmentation algorithm which can measure the expression levels of each gene and the relative ratios of the genes in different situations without additional information or user intervention. in this paper, we used watershed transformation to get basic features of microarray images. then, a graph model was used for subgrid gridding and spot segmentation based on the watershed transformation results. to verify the efficiency of our algorithm, we compared its performance with that of two previous methods: profile and mknn(modified k nearest neighbor) algorithm. the result demonstrated the accuracy and robustness of the proposed algorithm in subgrid and spot segmentation.
superimposing 3d virtual objects using markerless tracking. this paper presents a novel methods to estimate the coordinates of a 3d object using the four vertices of a quadrangle and to track the markerless feature points. these methods are basic and important problems in augmented reality. however, many tracking solutions are dependent on fiducial markers in video or known coordinate systems which are required to superimpose virtual objects on frames. in this paper, we begin with the fact that the rectangular objects in 3d real world are projected the perspective quadrangle onto image plane through camera. we can estimate 3d object coordinates from 4 vertices of quadrangle through transformations of image coordinates. also, the markerless tracking method of 4 vertices is presented and the camera motion parameters between successive frames are calculated using epipolar geometry.
shape decomposition and skeleton extraction of character patterns. this paper proposes an approach to extract skeletons from the character patterns. it first decomposes the pattern into a set of near-convex parts and then extracts skeletons from the parts. in shape decomposition stage, the convex hull information is used to identify the splitting paths. for the skeleton extraction, an operation that ties the adjacent strokes by a knot is developed. our control procedure processes a variety of different situations of the adjacentstrokes in a systematic way.
a two-stage approach for segmentation and recognition of handwritten digit strings collected from mail pieces. in this paper, we present an approach to interpret handwritten digit strings by employing a two-stage segmentation and recognition scheme. the first stage processing is to deal with possible touching between digits. an input string is represented with an abstractive means, called primitive. candidate segmentation points are sought from the representation. to locate a boundary between digits, a recognition engine, which is rough but fast, is applied to a combined segment. the second stage recognition process, which is more accurate but slow, is applied to the combined segment depending on the recognition confidence of the first stage process. features for the segmentation and recognition are defined and described. to evaluate the effectiveness of the approach, experiments have been performed on a set of digit string images collected from real mail pieces, and promising preliminary results have been observed.
regularized patch motion estimation. this paper presents a new formulation of the problem of motion estimation which attempts to give solutions to classical problems in the field, such as detection of motion discontinuities and insufficiency of the optical flow constraint in areas with low intensity variation. an initial intensity segmentation phase partitions each frame into patches so that areas with low intensity variation are guaranteed to belong to the same patch. a parametric model is assumedto describe the motion of each patch. regularization in the motion parameter space provides the additional constraints for patches where the intensity variation is insufficient to constrain the estimation of the motion parameters and smooths the corresponding motion field. in orderto preserve motion discontinuities we use robust functions as a regularization mean. experimental results show that the proposed method deals successfully with motions large in magnitude, motion discontinuities and produces accurate piecewise smooth motion fields.
pose estimation for central catadioptric systems: an analytical approach. the number of applications for central catadioptric systems, often called central panoramic systems, are increasing. among these are surveillance systems, commercial systems for web navigation and robot localization and navigation. this works includes itself in the last case, and presents an analytical method for pose estimation using any central catadioptric system. any known four points in the world, forming a planar rectangle, may be used for pose computation. the computed pose includes the rotation and the translation from the camera coordinate system to the world coordinate system.
non-linear local harmonic filters for edge-preserving image denoising. we propose a new class of non-linear image recovery operators based on local smoothing applied both in the spatial domain (horizontal smoothing) and in the gray-level domain (vertical smoothing). the commonly used horizontal smoothing gives the way of reducing the noise level (noise filtering), whereas the vertical smoothing yields the edge preservation property. the method is indexed by a real parameter yielding a generalized class of local harmonic filters. in particular the classical min/max filters as well as all linear locally weighted filters can be obtained as special cases.
fast atomic decomposition by the inhibition method. a new algorithm is introduced which is related to matching pursuit but allows updating more than one coding coefficient per iteration: the updated coefficients correspond to mutually orthogonal elements of the dictionary. coding experiments on natural images show that the new method achieves the same trade-off as matching pursuit between number of coding coefficients and reconstruction error, but significantly faster convergence.
novel error concealment method with adaptive prediction to the abrupt and gradual scene changes. in this paper, the impact of the scene change on the conventional error concealment method is addressed and a novel error concealment method is proposed to improve the insufficiency of conventional temporal error concealment algorithm due to the occurrence of scene change. combining with the low complexity scene change detection algorithm using macroblock type information, the corrupt blocks resulting from bit errors are concealed either temporally or spatially depending on whether or not an abrupt scene change is found. in the case of gradual scene change, a novel error concealment method of interpolation and extrapolation is proposed to utilize the linear property of gradual scene change sequence, and effectively reduce the concealment error in comparison with the conventional algorithm. great improvement about 3 to 5 db psnr is obtained with only little overhead memory and computation.
a method for ir point target detection based on spatial-temporal bilateral filter. the problem of detecting and locating point targets in cluttered and noised ir (infrared) images is a difficult and important task in ir applications. in this paper, we proposed a new method for detecting dim moving point target in ir image sequence. the significance of this work is that the ideal of bilateral filtering is adopted, which leads to a simple detection. in order to make use of the temporal information of ir sequence, we extended the conventional 2d bilateral filter to the 3d spatial-temporal bilateral filter, which can remove noise efficiently and enhance the contrast between targets and background. the filter can finish the preprocessing job within three frames, which is important for real-time application for fast moving target detection. the limited qualitative results in the experiments demonstrate that the new method can produce an accurate result.
hiding multiple data in color images by histogram modification. in this paper, we present a new histogram-based data-hiding algorithm that secret data is embedded in the least significant bit of the histogram value. to change the pixel value, it will alter the histogram to accomplish data-hiding work. in the proposed algorithm, it is able to perform data hiding on the one-dimension histogram, two-dimension histogram map and three-dimension histogram cube. besides, the multiple secret data hiding in various combinations of histogram spaces are successfully demonstrated in our experimental results. in addition, the natural and limited color images are tested in our experiments.
prototype selection for finding efficient representations of dissimilarity data. the nearest neighbor (n n) ru le is a simple and intuitive method for solving classification problems. originally, it uses distances to the complete training set. it performs well, however, it is sensitive to noisy objects, due to its operation on local neighborhoods only . a more global approach is possible by mapping the distance data on to a pseudo-euclidean space, such that the distances are preserved as well as possible. then, a classifier built in such a space can out perform the nn rule. however, again all objects from th e training set are used for a projection of new data.this paper addresses the issue of reducing the training set while possibly preserving the original structure of the mapped data. some criteria are introduced and evaluated against two problems, polygon recognition and digit recognition. our experiments show that the representation mismatch criterion is beneficial for the applications considered. moreover, the linear classifier built in the pseudo-euclidean space, determined by 20% -25% of the training objects, outperforms the nn rule based on all of them.
dissimilarity-based classification for vectorial representations. general dissimilarity-based learning approaches have been proposed for dissimilarity data sets [11, 10]. they arise in problems in which direct comparisons of objects are made, e.g. by computing pairwise distances between images, spectra, graphs or strings. in this paper, we study under which circumstances such dissimilarity-based techniques can be used for deriving classifiers in feature vector spaces. we will show that such classifiers perform comparably or better than the nearest neighbor rule based either on the entire or condensed training set. moreover, they can be beneficial for highlyoverlapping classes and for non-normally distributed data sets, with categorical, mixed or otherwise difficult features.
adaptive kernel metric nearest neighbor classification. nearest neighbor classification assumes locally constant class conditional probabilities. this assumption becomes invalid in high dimensions due to the curse-of-dimensionality. severe bias can be introduced under these conditions when using the nearest neighbor rule. we propose an adaptive nearest neighbor classification method to try to minimize bias. we use quasiconformal transformed kernels to compute neighborhoods over which the class probabilities tend to be more homogeneous. as a result, better classification performance can be expected. the efficacy of our method is validated and compared against other competing techniques using a variety of data sets.
a new efficient svm-based image registration method. a frequently felt difficulty with image registration is the lack of guiding rules to choose a model for unknown geometric distortion. previous work has concentrated on the use of certain model of mapping function to deal with arbitrarily structured data. the performance of such technique may deteriorate if the model is not well. we consider a general case where a set of models is trained in advance, instead of using one model to register images directly. this technique can find an optimal model for particular deformation. moreover, central to our approach is that it constitutes a practical implementation of the structural risk minimization principle (srm) that aims at minimizing a bound on the generalization error of a model, rather than minimizing the mean square error over control points.
images similarity detection based on directional gradient angular histogram. in this paper, an images similarity measure based on directional gradient angular histogram (dgah) is proposed. analysis and experimental results reveal that the proposed technique not only acquires a superior detection performance, but also the invariance to illumination changes and the robustness to translation, scale and rotation of the image object. in addition, the proposed technique is easily integrated within a wavelet-based image coder since the angular histogram features can be constructed directly on the wavelet coefficients decomposed using anti-symmetrical bi-orthogonal wavelets (asbw).
a computational model of social signalin. i have proposed that unconscious voice, face, hand, and body gestures form a motion texture that convey social signals, and that these signals are an important determinant of human behavior [1]. in this paper i will describe the theoretical and computational framework that i have developed for measuring social signaling, and survey the results obtained using this computational model for the perception of social displays.
epipolar geometry from two correspondences. a novel algorithm for robust ransac-like estimation of epipolar geometry (of uncalibrated camera pair) from two correspondences of local affine frames (lafs) is presented. each laf is constructed from three points independently detected on a maximally stable extremal region. the algorithm assumes that a sufficiently accurate approximation of the fundamental matrix is obtained from two laf correspondences by the 6-point algorithm of stewe´nius et al. the so-far-the-best hypotheses are further processed by so-called local optimization to estimate the epipolar geometry. special attention is paid to planar sample degeneracy, since the probability of drawing two coplanar laf correspondences is not negligible. combining the 6-point solver, local optimization, and the degeneracy test enables ransac to draw samples of only two lafs to generate hypotheses and thus to reduce the number of samples drawn. we experimentally show that using the 6-point algorithm (approximating the real camera by camera with unit aspect ratio, zero skew, principal point in the center of image, and a common unknown focal length) generates hypotheses that are sufficient for eg estimation in lo-ransac framework.
bayesian object-level change detection in grayscale imagery. we present a change detection algorithm formulated in a bayesian framework that uses the output of an object detector to reason about change at a higher level than comparing pixels. the object detector mitigates pixel-level noise, and presents objects to the change detection framework. this in turn ties the objects across images and determines change. the bayesian framework allows us to easily add domain knowledge into the change detection process to improve detection. we show that our approach can successfully detect changes across grayscale images with significantly greater variance in imaging conditions (such as viewpoint, resolution, and illumination) than those handled by traditional methods.
recognition of airborne fungi spores in digital microscopic images. we propose and evaluate a method for the recognition of airborne fungi spores. we use a model-based object recognition method to identify spores in a digital microscopic image. we do not use the gray values of the model, but use the object edges instead. the similarity measure measures the average angle between the vectors of the template and the object. model generation is done semi-automatically by manually tracing the object, automatic shape alignment, similarity calculation, clustering and prototype calculation.
3d surface inspection using coupled hmms. this paper proposes coupled hidden markov models (chmm) for analysis of steel surfaces containing three-dimensional flaws. due to scale on the surface, the reflection property across the intact surface changes and intensity imaging fails. hence, the light sectioning method is used to acquire the surface range data. the steel block is vibrating on the conveyor during data acquisition which complicates the task. after depth map recovery and feature extraction, segments of the surface are classified by means of chmms. we present classification results of the chmm and compare them to the naïve bayes classifier. the chmm outperforms the naïve bayes approach.
2d and 3d vegetation resource parameters assessment using marked point processes. high resolution aerial and satellite images of forests have a key role to play in natural resource management. as they enable to study forests at the scale of trees, it is now possible to get a more accurate evaluation of the forest resources, from which can be deduced information on biodiversity and ecological sustainability. in that prospect, automatic algorithms are needed to give a further exploitation of the data and to assist human operators. in this paper, we present a stochastic geometry approach to extract 2d and 3d parameters of the trees, by modelling the stands as some realizations of a marked point process of ellipses or ellipsoids, whose points are the positions of the trees and marks their geometric features. this approach gives also the number of stems, their position, and their size. it is an energy minimization problem, where the energy embeds a regularization term (prior density), which introduces some interactions between the objects, and a data term, which links the objects to the features to be extracted. results are shown on aerial images provided by the french national forest inventory (ifn).
visual learning and recognition of a probabilistic spatio-temporal model of cyclic human locomotion. we present a novel representation of cyclic human locomotion based on a set of spatio-temporal curves of tracked points on the surface of a person. we start by extracting a set of continuous, phase aligned spatio-temporal curves from trajectories of random points tracked over several cycles of locomotion in a monocular video sequence. we analyze a pca representation of a set of cyclic curves, pointing out properties of the representation which can be used for spatio-temporal alignment in tracking and recognition tasks. we model the curve distribution density by a mixture of gaussians using expectation-maximization algorithm. for recognition, we use maximum a posteriori estimate combined with linear data adaptation. we tested the algorithms on cmu mobo database with favourable results for the recognition of people "by walking" from monocular video sequences captured from the side view.
p-aflc: a parallel scalable fuzzy clustering algorithm. clustering is the unsupervised classification of data items into homogeneous groups called clusters. clustering algorithms are computationally intensive, particularly when they are used to analyze large amounts of data and this is the case in many pattern recognition, image analysis applications. a possible approach to reduce the processing time is based on the implementation of clustering algorithms on scalable parallel computers. this paper describes the design and implementation of p-aflc, a parallel version of the adaptive fuzzy leader clustering system based upon the competitive learning model for determining optimal classes in large data sets. the system architecture, its implementation, and experimental performance results are reported, together with theoretical performance evaluation.
vehicle type recognition with match refinement. we describe a system for automatic recognition of verhicle type (make and model) from frontal views, aimed at secure access, surveillance and traffic monitoring applications. the system extracts gradient features from reference patches in images of car fronts and performs recognition in two stages.in the first stage gradient based feature vectors are used to produce a ranked list of possible candidate classes.the result is then refined by using a novel match refinement algorithm that maximizes the discrimination between the subset of most likely classes by optimising for objectpose and adaptively normalising feature vectors.we test the system on over 1000 images containing 77 difference vehicle classes, and demonstrate that such a system can provide reliable verification (eer
automatic hip bone segmentation using non-rigid registration. this paper presents a method for automatic segmentation of bone from volumetric computed tomography (ct) data. due to osteoporosis, which degenerates the bone density and hence decreases the intensity of the bone in the ct dataset, it is not possible to use conventional thresholding techniques to handle the segmentation. furthermore we want to use prior knowledge about shapes and relations of the bones in the area of interest to be able to e.g. separate adjoining bones from each other. the method we suggest is the morphon algorithm [4]. this is a non-rigid registration technique where an 2d or 3d image is iteratively deformed to match the corresponding structure in a target image. the method uses difference in local quadrature phase and certainty measures to estimate the deformations.
human action segmentation via controlled use of missing data in hmms. segmentation of individual actions from a stream of human motion is an open problem in computer vision. this paper approaches the problem of segmenting higher-level activities into their component sub-actions using hidden markov models modified to handle missing data in the observation vector. by controlling the use of missing data, action labels can be inferred from the observation vector during inferencing, thus performing segmentation and classification simultaneously. the approach is able to segment both prominent and subtle actions, even when subtle actions are grouped together. the advantage of this method over sliding windows and viterbi state sequence interrogation is that segmentation is performed as a trainable task, and the temporal relationship between actions is encoded in the model and used as evidence for action labelling.
observation-switching linear dynamic systems for tracking humans through unexpected partial occlusions by scene objects. this paper focuses on the problem of tracking people through occlusions by scene objects. rather than relying on models of the scene to predict when occlusions will occur as other researchers have done, this paper proposes a linear dynamic system that switches between two alternatives of the position measurement in order to handle occlusions as they occur. the filter automatically switches between a foot-based measure of position (assuming z=0) to a head-based position measure (given the person's height) when an occlusion of the person's lower body occurs. no knowledge of the scene or its occluding objects is used. unlike similar research [2, 14], the approach does not assume a fixed height for people and so is able to track humans through occlusions even when they change height during the occlusion. the approach is evaluated on three furnished scenes containing tables, chairs, desks and partitions. occlusions range from occlusions of legs, occlusions whilst being seated and near-total occlusions where only the person's head is visible. results show that the approach provides a significant reduction in false-positive tracks in a multi-camera environment, and more than halves the number of lost tracks in single monocular camera views.
fundamental matrix and slightly overlapping views. this paper proposes a method to compute the fundamental matrix from slightly overlapping views. slight overlaps are preferable to substantial overlaps in large multi-camera surveillance applications, because otherwise the number of cameras and thus the overall application costs would gravely increase. instead of using point correspondences alone, we additionally use the infinite homography. the infinite homography can be computed from line segments when we have a manhattan world scene and assume cameras with square pixels and the same alignment of the scene in both views. all assumptions are not too restrictive and occur frequently. the infinite homography and one of the epipoles determine the fundamental matrix. the paper demonstrates a simple solution to compute the epipoles from at least two point correspondences without requiring points uniformly distributed within the images. experiments on synthetic images clearly show the advantages of the proposed method compared to the classical eight point algorithm. images of an office scene show the idea on real world images.
metric tree partitioning and taylor approximation for fast support vector classification. this paper presents a method to speed up support vec- tor classification, especially important when data is high- dimensional. unlike previous approaches which focus on less support vectors, we partition the data space into lo- cal regions, and perform approximation by linear functions. the experimental results on 31 datasets show that the per- formance degrades marginally, while the speedup is signif- icant, up to three orders of magnitude.
the gait identification challenge problem: data sets and baseline algorithm. recognition of people through gait analysis is an important research topic, with potential applications in video surveillance, tracking, and monitoring. recognizing the importance of evaluating and comparing possible competing solutions to this problem, we previously introduced the humanid challenge problem consisting of a set of experiments of increasing difficulty, a baseline algorithm, and a large set of video sequences (about 300 gb of data related to 452 sequences from 74 subjects) acquired to investigate important dimensions of this problem, such as variations due to viewpoint, footwear, and walking surface. in this paper, we present a detailed investigation of the baseline algorithm, quantify the dependence of the various co-variates on gait-based identification, and update the previous baseline performance with optimized ones. we establish that the performance of the baseline algorithm is robust with respect to its various parameters. the overall identification performance is also stable with respect to the quality of the silhouettes. we find that the approximately lower 20% of the silhouette accounts for most of the recognition achieved. viewpoint has barely statistically significant effect on identification rates, whereas footwear and surface-type does have significant effects with the effect due to surface-type being approximately 5 times that ofshoe-type. the data set, the source code for the baseline algorithm, and unix scripts to reproduce the basic results reported here are available to the research community at marathon.csee.usf.edu/gaitbaseline/
adaptive region growing impulse noise estimator for color images. in this paper, a novel region growing impulse noise estimator for color images is proposed. the aim of this estimator is to distinguish noisy pixels from uncorrupted pixels and subsequently measure the noise proportion efficiently. we use a region growing technique to segment the images into clusters of pixels and propose an adaptive decision scheme to measure the noise proportion. performance analyses show the proposed scheme outperforms some of the state-of-theart techniques.
incremental statistical geo-temporal structuring of a personal camera phone image collection. this paper makes a proposal for automatically organizing the personal image collection that would be collected from a mobile phone equipped with a digital camera. doing so, it attempts to address emerging needs from this rapidly developping device family. having sketched user needs, we underline the interest of temporal and spatial meta-data in the chosen context. collection organization is then formulated as an unsupervised classification problem, in both space and time. a criterion and an estimation procedure are proposed, based on the statistical integrated completed likelihood criterion, providing effective solutions to model complexity determination, non-gaussianity of clusters, and incrementality. for further summarization, a technique for fusing the temporal and geolocation-based partitions is finally put forward, to ease browsing of the image collection along a single dimension.
morphological recognition of the spatial patterns of olive trees. a pair of algorithms to segment olive groves and recognize its individual trees in high spatial resolution remotely sensed images is presented. the developed algorithms are applied with success by exploiting the typical spatial patterns presented by this cover and are mainly based on mathematical morphology operators.
learned probabilistic image motion models for event detection in videos. we present new probabilistic motion models of interest for the detection of relevant dynamic contents (or events) in videos. we separately handle the dominant image motion assumed to be due to the camera motion and the residual image motion related to scene motion. these two motion components are then represented by different probabilistic models which are further recombined for the event detection task. the motion models associated to pre-identified classes of meaningful events are learned from a training set of video samples. the event detection scheme proceeds in two steps which exploit different kinds of information and allow us to progressively select the video segments of interest using maximum likelihood (ml) criteria. the efficiency of the proposed approach is demonstrated on sports videos.
feature extraction for improved profile hmm based biological sequence analysis. state-of-the-art systems for biological sequence analysis employ statistical modeling techniques, most notably so-called profile hmms. however, all approaches still rely on a purely symbolic sequence representation, which severely limits their capabilities in describing weak similarities between remotely homologue members of sequence families. therefore, we propose a multi-channel signal-like sequence representation based on a combination of several numerically encoded biochemical properties of the individual residues. from this representation features are extracted capturing relevant local sequence properties by applying wavelet and principal component analysis. evaluation results on a challenging task of sequence family classification prove that profile hmms trained on the feature-based sequence representation significantly outperform discrete models.
automatic detection of song changes in music mixes using stochastic models. the annotation of song changes in music mixes created by djs or radio stations for direct access in digital recordings is, usually, a very tedious work. in order to support this process we developed an automatic song change detection method which can be used for arbitrary music mixes. stochastic models are applied to music data aiming at their segmentation with respect to automatically obtained abstract generic acoustic units. the local analysis of these stochastic music models provides hypotheses for song changes. results of an experimental evaluation processing music mix data demonstrate the effectiveness of our method for supporting the annotation with respect to song changes.
comparison of eigenface-based feature vectors under different impairments. we study the performance of a new eigenface-based method for face recognition. specifically, we perform dct preprocessing followed by the pca-lda combination. we compare the new method to existing ones (pca, pca-lda, dct-pca) under impairments like changes in brightness, direction-of-illumination, hairstyle, clothing, expression, head orientation, and added noise.
optimal cascade construction for detection using 3d models. we describe a method for optimal construction of a detection cascade comprising 3d models of increasing levelof- detail (lod). an lod 3d model hierarchy of the target object is first generated. by analyzing detection performance of each individual model in the lod hierarchy, an optimization framework that allows trade-off between speed and accuracy is formulated. the formulation allows models to be explicitly selected for inclusion in the final detection cascade while achieving optimal running time with respect to a target detection performance.
a new method in locating and segmenting palmprint into region-of-interest. various techniques in analyzing palmprint have been proposed but to the best of our knowledge, none has been studied on the selection and division of the region-of-interest (roi). previous methods were always applied only to a fixed size square region chosen as the central part of the palm, which were then divided into square blocks for extraction of local features. in this paper, we proposed a new method in locating and segmenting the roi for palmprint analysis, where the selected region varies with the size of the palm. instead of square blocks, the region is divided into sectors of elliptical half-rings, which are less affected by misalignment due to rotational error. more importantly, our arrangement of the feature vectors ensures that only features extracted from the same spatial region of two aligned palms will be compared with each other. encouraging results obtained favor the use of this method in the future development of palmprint analysis techniques.
on performance evaluation of face detection and localization algorithms. when comparing different methods for face detection or localization, one realizes that just simply comparing the reported results is misleading as, even if the results are reported on the same dataset, different authors have different views of what a correct detection/localization means. this paper addresses exactly this problem, proposing an objective measure for the goodness of a detection/localization for the case of frontal faces. the usage of the proposed technique insures a fair and unbiased way of reporting the results, making the experiment repeatable, measurable, and comparable by anybody else.
scale-adaptive orientation estimation. this paper focuses on directional textures. it provides a new framework for the design of convolution masks dedicated to orientation estimation and an adaptive algorithm which chooses the best mask size for each pixel.the design of the adaptive algorithm is based on the combination of two complementary operators: a gradient based operator which is adapted to sloped regions and a valleyness detector which fits the crests and valleys. each operator is optimized in terms of bias reduction. the scale adaptive implementation of the operator is carried out in two steps. firstly, characteristic points are detected. their relative positions provide us with an estimation of the scale. secondly, the size of the convolution masks is chosen according to the estimated scale.experiments on synthetic and natural textures are provided and show the efficiency and the relevance of our approach.
tangent vector kernels for invariant image classification with svms. this paper presents an application of the general sample-to-object approach to the problem of invariant image classification. the approach results in defining new svm kernels based on tangent vectors that take into account prior information on known invariances. real data of face images are used for experiments. the presented approach integrates virtual sample and tangent distance methods. we observe a significant increase in performance with respect to standard approaches. the experiments also illustrate (as expected) that prior knowledge becomes more important as the amount of training data decreases.
graph-based transformation manifolds for invariant pattern recognition with kernel methods. we present here an approach for applying the technique of modeling data transformation manifolds for invariant learning with kernel methods. the approach is based on building a kernel function on the graph modeling the invariant manifold. it provides a way for taking into account nearly arbitrary transformations of the input samples. the approach is verified experimentally on the task of optical character recognition, providing state-of-the-art performance on harder problem settings.
graph-based transformation manifolds for invariant pattern recognition with kernel methods. we present here an approach for applying the technique of modeling data transformation manifolds for invariant learning with kernel methods. the approach is based on building a kernel function on the graph modeling the invariant manifold. it provides a way for taking into account nearly arbitrary transformations of the input samples. the approach is verified experimentally on the task of optical character recognition, providing state-of-the-art performance on harder problem settings.
improving shape from focus using defocus information. shape from focus (sff) method determines the degree of focus in a sequence of observations to estimate the shape of a 3-d object. existing sff algorithms use an ad hoc interpolation strategy to account for the error due to the finite step-size by which the translational table is moved while capturing the images. we propose an improved sff method that uses relative defocus blur derived from actual image data to arrive at the final estimates of the shape of the object. a space-variant image restoration scheme is also proposed to obtain a focused image of the 3-d object. the shape estimates as well as the quality of the restored image using the proposed method are superior to that of traditional sff.
consensus-based identification of spectral signatures for classification of high-dimensional biomedical spectra. the identification of spectral signatures is crucial for the classification/profiling of biomedical spectra. because only limited number of biomedical samples of high dimensionality is typically available, dimensionality reduction techniques (identification of discriminatory features) are essential for robust classifier development. we show, on three real-world biomedical datasets, the potential of a consensus-based identification of important feature subsets, using a genetic algorithm and a sparse linear classifier. when training data are in short supply, the proposed methodology leads to more stable subset identification and higher classification accuracy.
class separability in spaces reduced by feature selection. we investigated the geometrical complexity of several high-dimensional, small sample classification problems and its changes due to two popular feature selection procedures, forward feature selection (ffs) and linear programming support vector machine (lpsvm). we found that both procedures are able to transform the problems to spaces of very low dimensionality where class separability is improved over that in the original space. the study shows that geometrical complexities have good potentials for comparing different feature selection methods in aspects relevant to classification accuracy, yet independent of particular classifier choices.
feature subset selection using ica for classifying emphysema in hrct images. feature subset selection, applied as a pre-processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier performance. in recent years, data in some applications has increased in both the number of instances and features. it is in this context that we introduce a novel approach to reduce both instance and feature space through independent component analysis (ica) for the classification of emphysema in high resolution computer tomography (hrct) images. the technique was tested successfully on 60 hrct scans having emphysema using three different classifiers (naïve bayes, c4.5 and seeded k means). the results were also compared against "density mask'', a standard approach used for emphysema detection in medical image analysis. in addition, the results were visually validated by radiologists.
fast dynamic mosaicing and person following. a system for video surveillance purposes in wide areas based on active cameras, also capable to follow a person in the scene by keeping him framed, is presented. the proposed approach is based on the so-called direction histograms to compute the ego-motion and on frame differencing for detecting moving objects. it exploits post-processing and active contours to extract precise shape of moving objects to be fed to a probabilistic algorithm to track moving people in the scene. person following, instead, is based on simple heuristic rules that move the camera as soon as the selected person is close to the border of the field of view. experimental results on a live active camera demonstrate the feasibility of real-time person following.
an adaptive classification algorithm using robust incremental clustering. in this paper we present an adaptive classification method that features a robust, efficient and simple to use incremental clustering algorithm. a new assignment strategy for incorporating new data patterns allows clusters to align more exhaustively with the data structure. this almost eliminates the sensitivity to the order of input data, many incremental clustering algorithms suffer from, reduces the number of clusters needed and thus improves also time efficiency. for updating the clusters' representations we utilize an incremental version of pca which generates its learning rate automatically from the number of patterns. furthermore, the size and number of clusters is controlled by the classification error. so we get a classification method where nothing but the target error needs to be pre-specified. we conducted experiments on artificial and real data to demonstrate the capabilities of the proposed algorithm.
model-free augmented reality by virtual visual servoing. this paper presents a method based on the virtual visual servoing approach [10] to achieve markerless augmented reality applications. this work aims to realize this task using as little prior 3d information as possible. virtual visual servoing techniques that lead to a non-linear minimization approach allow one to estimate the 2d transformation between two images of a video sequence which permits to achieve augmented reality on this sequence. thanks to the work that has already been carried out in this domain, the presented method is efficient and robust wrt. noise and occlusions. it allows very realistic augmented videos with minimum knowledge about the real environment.
parameter tuning using the out-of-bootstrap generalisation error estimate for stochastic discrimination and random forests. stochastic discrimination is a machine learning algorithm with strong theoretical underpinnings and good published results on uci datasets. however, it has not been popular amongst practitioners. we look at some of the issues involved in its use, propose the out-of-bootstrap error estimator as a means of tuning stochastic discrimination's and other classifiers' performance and contrast stochastic discrimination's utility with that of a related classification technique of random forests.
a method for the identification of noisy regions in normalized iris images. in this paper we propose a new method for the identification of noisy regions in normalized iris images. starting from a normalized and dimensionless iris image in the polar coordinate system, our goal consists in the classification of every pixel as "noise" or "not noise". this classification could be helpful in the posterior feature extraction or feature comparison stages regarding the construction of biometric iris signatures more robust to noise. we propose the extraction of 8 well known features for each pixel of the images followed by the classification through a neural network.
toward blind robust watermarking of vector maps. digital watermarking technology is applied on multimedia data such as images, audio and video etc., for copyright protection and temper proofing. vector type images are commonly employed in cartography or geographical information system, and their copyright or ownership must be protected. previous works on digital watermarking of vector maps adopted the informed or non-blind method, which needs the original maps for watermark detection. in this paper, we propose a novel and blind watermarking approach, which firstly subdivides the map into mesh segments, and then embed the watermark in each segment. in the detection step, either map segmentation or watermark detection doesn't need the original map. simulation results show that the proposed approach also resists to cropping and noise attacks.
migration analysis: an alternative approach for analyzing learning performance. estimated generalization error is the main index that indicates learning performance, but it is inadequate for further analysis. bias-variance theory tries to overcome the limitation of analyzing learning performance, but the concept of bias-variance is still controversial when applied to the classification problem. in this paper, we propose a new alternative, simple and practical, analytical method called 'migration analysis' to analyze the learning results. we compare the properties of migration analysis to bias-variance framework, and use it to analyze two so-called ensemble learners: bagging and adaboost. the results not only explain these ensemble learners in different ways, but also shed light to the new promising learning algorithm.
real-time camera tracking using known 3d models and a particle filter. we present an algorithm which can track the 3d pose of a hand held camera in real-time using predefined models of objects in the scene. the technique utilises and extends recently developed techniques for 3d tracking with a particle filter. the novelty is in the use of edge information for 3d tracking which has not been achieved before within a realtime bayesian sampling framework. we develop a robust tracker by carefully designing the particle filter observation model: grouping line segments from a known model into 3d junctions and performing fast inlier/outlier counts on projected junction branches. results demonstrate the ability to track full 3d pose in dense clutter whilst using a minimal number of junctions.
semantic analysis on medical images: a case study. computer aided diagnosis (cad) systems, as secondopinion assistance to radiologists, are being developed. however, the lack of semantic information at the image processing stage is expected to limit the ultimate performance of such cad systems. a solution can be provided by a specific medical domain terminology, which contains several concepts that describe features of abnormalities and the relationships (properties) between these concepts; as such is well readable by both human beings (radiologists) and machine agents (cad systems). here we investigate a specific ontology and provide a clear evaluation based on string and description logic (dl). the results provide a clear understanding of semantic medical image analysis with which cad systems are expected to improve their performance.
a bayesian approach to simultaneous motion estimation of multiple independently moving objects. in this paper, the problem of simultaneous motion estimation of multiple independently moving objects is addressed. a novel bayesian approach is designed for solving this problem using the sequential importance sampling (sis) method. in the proposed algorithm, a balancing step is added into the sis procedure to preserve samples of low weights so that all objects have enough samples to propagate empirical motion distributions. by using the proposed algorithm, the relative motions of all moving objects with respect to camera can be simultaneously estimated . this algorithm has been tested on both synthetic and real image sequences. improved results have been achieved.
affine invariant dynamic time warping and its application to online rotated handwriting recognition. dynamic time warping (dtw) has been widely used to align and compare two sequences. dtw can efficiently deal with local warp or deformation between sequences. however, it can't take account of affine transformation of sequences, such as rotation, shift and scale. this paper introduces a novel affine invariant dynamic time warping (ai-dtw) method, which tries to deal with the affine transformation and sequence alignment in a unified framework. we propose an iterative algorithm to estimate the optimal transformation matrix and warping path by mutually updating them. recognition experiments on the online rotated handwritten data illustrated that the ai-dtw achieves a recognition rate of 95.54%, which is significantly higher than that (65.87%) of the classical dtw method.
recover writing trajectory from multiple stroked image using bidirectional dynamic search. the recovery of writing trajectory from offline handwritten image is generally regarded as a difficult problem [1]. this paper introduced a method to recover the writing trajectory from multiple stroked images by searching the best matching writing paths of template strokes. the searching procedure is guided by a matching cost function which is defined as the summation of positional distortion cost and directional difference cost between the template stroke and its matching path. we develop a bidirectional search algorithm based on dynamic programming to find the best matching path. the algorithm can efficiently reduce the searching space, while hold the start/end vertex constraint. experiments on the handwritten english words and chinese characters demonstrated the effectiveness of our method.
an improved semi-supervised support vector machine based translation algorithm for bci systems. in this study, we propose an improved semi-supervised support vector machine (svm) based translation algorithm for brain-computer interface (bci) systems, aiming at reducing the time-consuming training process and enhancing the adaptability of bci systems. in this algorithm, we apply a semi-supervised svm, which builds a svm classifier based on small amounts of labeled data and large amounts of unlabeled data, to translating the features extracted from the electrical recordings of brain into control signals. for reducing the time to train the semi-supervised svm, we improve it by introducing an batch-mode incremental training method, which also can be used to enhance the adaptability of online bci systems. the off-line data analysis results demonstrated the effectiveness of our algorithm.
efficient feature extraction based on regularized uncorrelated chernoff discriminant analysis. in this paper, two regularized uncorrelated chernoff discriminant analysis (rucda) techniques are introduced. as a heteroscedastic extension of the classwise weighted fisher criterion, the class-wise weighted chernoff criterion employed in rucda better approximates the chernoff upper bound of the bayes classification error in the transformed space, which enable the resulting rucda to extract uncorrelated discriminatory information from both mean and covariance differences. experiments performed on uci benchmark and protein secondary structure datasets demonstrate good performance of the proposed technique.
unsupervised texture classification: automatically discover and classify texture patterns. in this paper, we present a novel approach to classify texture collections. this approach does not require experts to provide annotated training set. given the image collection, we extract a set of invariant descriptors from each image. the descriptors of all images are vector-quantized to form 'keypoints'. then we represent the texture images by 'bagof- keypoints' vectors. by analogy text classification, we use probabilistic latent semantic indexing(plsi) to perform unsupervised classification. the proposed approach is evaluated using the uiuc database which contains significant viewpoint and scale changes. the performances of classifying new images using the parameters learnt from the unannotated image collection are also presented. the experiment results clearly demonstrate that the approach is robust to scale and viewpoint changes, and achieves good classification accuracy even without annotated training set.
kernel neural gas algorithms with application to cluster analysis. we present a kernel neural gas (kng) algorithm, to generalize the original neural gas (ng) algorithm into a higher dimensional feature space. the proposed kng algorithm can successfully tackle nonlinearly structured datasets. compared with several existing kernel clustering algorithms, the kng can be insensitive to initializations due to employing the sequential learning strategy and the neighborhood cooperation scheme. further, a distortion sensitive kng (dskng) algorithm is proposed to tackle the imbalanced clustering problem. experimental results show that our kng algorithm can successfully deal with nonlinearly structured datasets and multi-modal datasets, while the imbalanced clusters are detected by the dskng.
a novel kernel prototype-based learning algorithm. in this paper, we propose a novel kernel prototype-based learning algorithm, called kernel generalized learning vector quantization (kglvq) algorithm, which can significantly improve the classification performance of the original generalized learning vector quantization algorithm in complex pattern classification tasks. in addition, the kglvq can also serve as a good general kernel learning framework for further investigation.
face recognition under varying lighting based on the probabilistic model of gabor phase. this paper present a novel method for robust illumination-tolerant face recognition based on the gabor phase and a probabilistic similarity measure. invited by the work in eigenphases [1] by using the phase spectrum of face images, we use the phase information of the multi-resolution and multi-orientation gabor filters. we show that the gabor phase has more discriminative information and it is tolerate to illumination variations. then we use a probabilistic similarity measure based on a bayesian (map) analysis of the difference between the gabor phases of two face images. we train the model using some images in the illumination subset of cmu-pie database and test on the other images of cmu-pie database and the yale b database and get comparative results.
tone mapping for hdr image using optimization a new closed form solution. this work studies an optimization approach for designing tone reproduction curve (trc) based tone mapping operators for the display of high dynamic range (hdr) images in low dynamic range (ldr) reproduction media. previous work has shown that the tone mapping problem can formulated as that of optimizing a two-term cost function where adjusting the relative weightings of the two terms allows users to interactively control the appearance of the output image. however, only heuristic solutions to the tone mapping objective function have been found in past research. the main contribution of this paper is the re-formulation of the objective function to allow the introduction of a closed-form solution to the two-term tone mapping objective function. the new solution has simplified previous heuristic solutions and made this approach mathematically more elegant, computationally faster and practically easier to implement.
grey scale image skeletonisation from noise-damped vector potential. this paper describes a method for curvature dependant skeletonisation in grey-scale images. we commence from a magnetostatic analogy, where the tangential edge flow (the cross product of the edge gradient and the image plane normal) is intepretted as a current. a vector potential is constructed by integrating the current weighted by inverse distance over the image plane. the skeleton corresponds to the location of valley lines in the vector potential. to damp noise effects we damp the current with an exponential function of the local curvature.
graph matching using commute time spanning trees. this paper exploits the properties of the commute time for the purposes of graph matching. our starting point is the random walk on the graph, which is determined by the heat-kernel of the graph and can be computed from the spectrum of the graph laplacian. we characterise the random walk using the commute time between nodes, and show how this quantity may be computed from the laplacian spectrum using the discrete green's function. we use the commute-time to locate the minimum spanning tree of the graph. the spanning trees located using commute time prove to be stable to structural variations. we match the graphs by applying a tree-matching method to the spanning trees. we experiment with the method on synthetic and real-world image data, where it proves to be effective.
graph matching using commute time spanning tr. this paper exploits the properties of the commute time for the purposes of graph matching. our starting point is the random walk on the graph, which is determined by the heat-kernel of the graph and can be computed from the spectrum of the graph laplacian. we characterise the random walk using the commute time between nodes, and show how this quantity may be computed from the laplacian spectrum using the discrete green's function. we use the commute-time to locate the minimum spanning tree of the graph. the spanning trees located using commute time prove to be stable to structural variations. we match the graphs by applying a tree-matching method to the spanning trees. we experiment with the method on synthetic and real-world image data, where it proves to be effective.
a hybrid watermarking scheme for h.264/avc video. a novel h.264/avc watermarking method is proposed in this paper. by embedding the robust watermark into dct domain and the fragile watermark into motion vectors respectively, the proposed method can jointly achieve both copyright protection and authentication. our scheme outperforms other video watermarking schemes on higher watermarking capacity especially in lower compression bit-rates. furthermore, being well aligned with lagrangian optimization for mode choice featured in h.264/avc, the proposed scheme only introduces small distortions into the video content. experimental results also demonstrate that the proposed solution is very computationally efficient during watermark extraction.
efficient relevance feedback using semi-supervised kernel-specified k-means clustering. in this paper, we present an efficient and convenient relevance feedback (rf) by using a semi-supervised kernel-specified kmeans clustering (skkc) technique. skkc is used to cluster the retrieval results so that rf can be conducted on the cluster level. compared with traditional rf conducted on the point/single-image level, the new rf will facilitate the rf selection and reduce user's efforts on it. furthermore, the proposed approach enables an accumulated learning ability by recording and learning from the history of users' rfs. the new rf is applied in a content-based medical image retrieval (cbmir) system. experimental results on imageclef database of around 9,000 images have shown that the proposed new rf is able to improve effectiveness and efficiency of cbmir.
spectrum analysis based onwindows with variable widths for online signature verification. in this paper, an online signature verification scheme based on spectrum analysis and mahalanobis decision is proposed. we firstly divided signatures to a number of frames with variable widths according to the characteristics of the time sequences, and then employed the fast fourier transformation(fft) to extract the spectrum of signatures. the distance between the fourier coefficient within the corresponding frames is computed, and the mahalanobis decision making is employed. experimentation demonstrates that spectrum analysis based on windows with variable widths is effective for online signature signals.
a robust method for the vietnamese handwritten and speech recognition. in this paper,we propose an approach based on hmm and linguistics for the vietnamese recognition problem, including handwritten and speech recognition.the main contribution is that our method could be used to model all vietnamese isolated words by a small number of hmms. the method is not only used for handwritten recognition but also for speech recognition.furthermore,it could be integrated with language models to improve the accuracy.experimental results show that our approach is robust and considerable.
perceptual criterion based fragile audio watermarking using adaptive wavelet packets. in this paper a novel watermarking scheme for audio authentication is proposed. during quantization process, the watermark is embedded in the wavelet packet domain. the best basis of the wavelet packets adapts to the psychoacoustic model so that the decomposed subband structure is closer to that of critical bands, which makes the embedding algorithm more flexible. unlike previous schemes, the new method embeds several bits of watermark message into one coefficient. by introducing the detecting function, the proposed scheme can authenticate the integrity of the audio signals as well as locate the tamper in time/frequency domain. effectiveness of the new approach is demonstrated by the experimental results.
data hiding in mpeg compressed audio using wet paper codes. in this paper a novel data hiding scheme for mpeg compressed audio is proposed. it exploits wet paper codes as the communication channel and hides data directly in the mpeg audio bit stream by modifying the mpeg audio quantization process. it is applicable to all three layers of mpeg audio. experimental results show that the proposed method is sustainable against transcoding and re-encoding without degrading the audio quality or increasing the file size.
a probabilistic framework for specular shape-from-shading. in this paper we address the problem of separating lambertian and specular reflection components in order to improve the quality of surface normal information recoverable using shape-from-shading (sfs). the framework for our study is provided by the iterated conditional modes algorithm. we develop a maximum a posteriori probability (map) estimation method for estimating the mixing proportions for the two reflectances, and also, for recovering local surface normals. the map estimation scheme has two model ingredients. firstly, there are separate conditional measurement densities which describe the distributions of surface normals for the two reflectance components. the second ingredient is a smoothness prior which models the distribution of surface normals over local image regions. we experiment with the method on real-world data. ground truth data is provided by imagery obtained with crossed polaroid filters. this reveals not only that the method accurately estimates the proportion of specular reflection, but that it also results in good surface normal reconstruction in the proximity of specular highlights.
reflectance from surfaces with layers of variable roughness. a new model for the scattering of light from layered surfaces with boundaries of variable roughness is introduced. the model contains a surface scattering component together with a subsurface scattering component. the former component corresponds to the roughness on the upper surface boundary and is modeled using the modified beckmann model. the latter component accounts for both refraction due to fresnel transmission through the layer and rough scattering at the lower layer boundary. by allowing independent roughness parameters for each surface boundary we can achieve excellent fits of the model to the measured brdf data. we experiment with brdf data from skin surface samples (human volunteers) and show that the new model outperforms alternative variants of the beckmann model and the lafortune et al. reflectance model.
robust appearance-based human action recognition. an automatic human action representation and recognition technique is proposed in this paper. appearance-change problem due to human wearing dresses and body shapes is also investigated in this study for automatic human action recognition. a tuned eigenspace technique is proposed for automatic human posture and/or motion recognition that successfully overcome the preceding problems. we employ image pre-processing by gaussian and sobel edge filter, called the first stage tuning, for reducing a dress effect, and a mean eigenspace produced by taking a mean of the similar postures, called the second stage tuning, for avoiding the preceding problems. an eigenspace called a tuned eigenspace is obtained from the mentioned processes and it is used for further recognition of unfamiliar postures and actions. the proposed method is compared with a related technique and the robustness of this approach is presented.
recognizing human behavior using universal eigenspace. an efficient application of eigenspace technique to recognize human behaviors is described. the present paper investigates two types of recognition, i.e., recognition of an unknown human posture and a particular behavior by identifying human postures among several behaviors. a number of different posture sets from some selected behaviors create universal eigenspace and different sets of unknown postures are recognized from it. in contrast to the classical method, the paper proposes to employ some image processing of input images for better performance of the eigenspace technique instead of using just original images for human postures recognition. a new approach of producing eigenspace is described and the robustness of the method is effectively proved in the experiment.
object classification with multi-scale autoconvolution. this paper assesses the recently proposed affine invariant image transform called multi-scale autoconvolution (msa) in some practical object classification problems. a classification framework based on msa and support vector machines is introduced. as shown by the comparison with another affine invariant technique, it appears that this new technique provides a good basis for problems where the disturbances in classified objects can be approximated with spatial affine transformation. the paper also introduces a new property clarifying the parameter selection in the multi-scale autoconvolution.
convexity recognition using multi-scale autoconvolution. this paper introduces a novel measure for object convexity using the recently introduced multi-scale autoconvolution transform. the proposed measure is computationally efficient and recognizes even small errors in a convex domain. we also consider its implementation and give a complete matlab algorithm for computing this measure for digital images. finally, we give examples to verify its applicability and accuracy. the examples also consider convexity as a measure for complexity.
generalized affine moment invariants for object recogntion. this paper introduces a new way of extracting affine invariant features from image functions. the presented approach is based on combining affine moment invariants (ami) with multiscale invariants, in particular multiscale autoconvolution (msa) and spatial multiscale affine invariants (sma). our approach includes all of these invariants as special cases, but also makes it possible to construct new ones. according to the performed experiments the introduced features provide discriminating information for affine invariant object classification, clearly outperforming standard ami, msa, and sma.
auto-calibration of multi-projector display walls. by treating projectors as pin-hole cameras, we show it is possible to calibrate the projectors of a casually-aligned, multi-projector display wall using the principles of planar auto-calibration. we also use a pose estimation technique for planar scenes to reconstruct the relative pose of a calibration camera, the projectors and the plane they project on. together with assumptions about the pose of the camera, we use the reconstruction to automatically compute the projector-display homographies needed to render properly scaled and oriented imagery on the display wall. the main contribution of this paper is thus to provide a fully automated approach to calibrate a multi-projector display wall without the need for fiducials or interaction.
using boosting to improve oil spill detection in sar images. marine surveillance system which uses synthetic aperture radar (sar) images to oil spill detection must minimize false alarms in order to improve its reliability. this paper presents an application that uses boosting method to minimize misclassification and yields better generalization. different feature sets were applied to neural network classifiers and its performance compared do boosting methods. the experiments reached substantial improvement in the classification accuracy to discriminate oil spots from the look-alike ones.
efficient alignment of fingerprint images. fingerprint matching is a common technique for biometric authentication. solid state sensors allow that fingerprint recognition is used in small sized embedded systems. the size of these sensors makes it necessary to store several impressions of the same fing er. in order to reduce memory requirements and matching time all these images can be fused into one larger image. we present a ransac based method to determine a rigid transformation which aligns two fingerprint images using solely minutiae coordinates and minutiae angles. the reliability of the method is demonstrated with experimental results.
object detection using background context. detection of objects is in general a computationally demanding task. to simplify the problem it is of interest to utilize contextual information and perform a staggered recognition where context is recognized as a precursor to object detection. in this paper an approach to object detection, using context is presented. the presented methodology is evaluated in the context of a tabletop scenario.
finding gait in space and time. we describe an approach to characterize the signatures generated by walking humans in spatio-temporal domain. to describe the computational model for this periodic pattern, we take the mathematical theory of geometry group theory, which is widely used in crystallographic structure research. both empirical and theoretical analysis prove that spatio-temporal helical patterns generated by legs belong to the frieze groups because they can be characterized by a repetitive motif along the direction of walking. the theory is applied to an automatic detection-and-tracking system capable of counting heads and handling occlusion by recognizing such patterns. experimental results for videos acquired from both static and moving ground sensors are presented. our algorithm demonstrates robustness to nonrigid human deformation as well as background clutter.
joint correspondence and background modeling based on tree dynamic programming. foreground segmentation with moving camera is a challenging task due to the presence of parallax effect, registration error, scene variations in out door, and etc. currently, background modeling techniques either assumes correspondence among pixels in concurrent frames or do not model it explicitly. the contribution by this paper is in two folds. first, we achieve a new background model by introducing correspondence into it. second, we pose foreground segmentation and correspondence estimation as a labeling problem. spatial context is enforced in shape of tree structure and global optimal label at each node is computed using dynamic programming. finally, based on the optimal correspondence, background model is updated. resultantly, parallax effect and registration error are reduced significantly. primary experiments proved our algorithm to be robust in performance.
a heterogeneous feature-based image alignment method. in this paper, we propose a robust heterogeneous feature based image alignment method that utilizes points, lines and regions in a unified framework. the image motion is decomposed into progressively complex components, i.e., translation, similarity, affine, and projective motion models, and alignment is obtained with deliberatively selected suitable feature types and associated descriptors. large convergence range is obtained by gradually constraining the search range of features in each stage. notably, point and line features are jointly used and formulated in a ransac (random sample consensus) framework for robust estimation of a homography between low textured images. further improvement is obtained with region based direct method. experiments demonstrate superior alignment results of our approach to both gradient-based direct method and tradition point feature based alignment method.
cancelable biometrics: a case study in fingerprints. biometrics offers usability advantages over traditional token and password based authentication schemes, but raises privacy and security concerns. when compromised, credit cards and passwords can be revoked or replaced while biometrics are permanently associated with a user and cannot be replaced. cancelable biometrics attempt to solve this by constructing revocable biometric templates. we present several constructs for cancelable templates us- ing feature domain transformations and empirically exam- ine their efficacy. we also present a method for accurate registration which is a key step in building cancelable trans- forms. the overall approach has been tested using large databases and our results demonstrate that without losing much accuracy, we can build a large number of cancelable transforms for fingerprints.
temporal color correlograms for video retrieval. this paper presents a novel method to retrieve segmented video shots based on thier color content. the temporal color correlogram captures the spatio-temporal relationship of colors in a video shot using co-occurrence statistics. the temporal color correlogram extends the hsv color correlogram that has been found to be very effective in content-based image retrieval. temporal color correlograms compute the autocorrelation of quantized hsv color values from a set of frame samples taken from a video shot. in this paper, the efficiency of the temporal color correlogram and hsv color correlograms are evaluated against other retrieval systems participating the trec video track evaluation and against color histograms used commonly in content-based retrieval. we used queries and relevance judgments on the 11 hours of segmented mpeg-1 video provided to track participants. tests are executed using our content-based multimedia retrieval systems that was specifically developed for multimedia information retrieval applications.
a simple linear method to obtain height ordering of scene points. we present a novel algorithm to extract height ordering information for points relative to the ground plane. the ordering of scene points is obtained by exploiting the idea of linearly invariant representation of space points, image points, and optical center of the camera, from which we derive a measure that is monotonic with respect to the height of points relative to the ground plane. we present results of the algorithm on data obtained from a mobile robot.
new operators of genetic algorithms for traveling salesman problem. this paper describes an application of genetic algorithm to the traveling salesman problem. new knowledge based multiple inversion operator and a neighborhood swapping operator are proposed. experimental results on different benchmark data sets have been found to provide superior results as compared to some other existing methods.
head pose estimation by nonlinear manifold learning. in this paper we propose an isomap-based nonlinear alternative to the linear subspace method for manifold representation of view-varying faces. being interested in user-independent head pose estimation, we extend the isomap model [a global geometric framework for nonlinear dimensionality reduction] to beable to map (high-dimensional) input data points which are not in the training data set into the dimensionality-reduced space found by the model. from this representation, a pose parameter map relating the input face samples to view angles is learnt. the proposed method is evaluated on a large database of multi-view face images in comparison to two other recently proposed subspace methods.
a new predictive full-search block motion estimation. this paper describes a novel and fast approach to full search block matching (fsbm) employing prediction of search region, based on the sampled statistics of sum-of-absolute difference (sad) distributions. the motion vector is predicted to belong to either of two regions, representing long-motion and short-motion, with limited amount of overlap between the two. the proposed prediction is statistically validated with more than 98% successes for different video sequences. experimental results reveal that the proposed predicted fsbm (pfsbm) algorithm saves up to 89% of computations, as compared to fsbm and the estimation accuracy is very close to that of fsbm. its performance has been compared with three-step search (tss) and fsbm for different standard video sequences.
a feasibility study of on-board data compression for infrared cameras of space observatories. in this paper, the feasibility of on-board data reduction/compression concept described in[on-board data compression: noise and complexity related aspects] is evaluated for infrared images taken from space observatories. the method described in [on-board data compression: noise and complexity related aspects], which was initially designed and developed for the pacs (photodetector array camera and spectrometer) instrument [http://www.mpe.mpg.de/projects.html], makes use of on-board integration to achieve higher compression ratio (cr) for applications with modest telemetry rate. the evaluation of the reduction concept takes into account the visual performance (distortion) and the compression ratio. the distortion is assessed by calculating the reconstruction error using 4 metrics, namely, root mean square error (rmse), signal-to-noise-ratio (snr), peak-signal-to-noise-ratio (psnr) and potential information loss (pil). a quantitative evaluation of the on-board compression concept is performed on data from the infrared camera isocam (infrared space observatory camera). we conclude with a short summary.
invariant features for 3d-data based on group integration using directional information and spherical harmonic expansion. due to the increasing amount of 3d data for various applications there is a growing need for classification and search in such databases. as the representation of 3d objects is not canonical and objects often occur at different spatial position and in different rotational poses, the question arises how to compare and classify the objects. one way is to use invariant features. group integration is a constructive approach to generate invariant features. several variants of group integration features are already proposed. in this paper we present two main extensions, we include local directional information and use the spherical harmonic expansion to compute more descriptive features. we apply our methods to 3d-volume data (pollen grains) and 3d-surface data (princeton shape benchmark)
3d and infrared face reconstruction from rgb data using canonical correlation analysis. in this paper, we apply a multiple regression method based on canonical correlation analysis (cca) to face data modelling. cca is a factor analysis method which exploits the correlation between two high dimensional signals. we first use cca to perform 3d face reconstruction and in a separate application we predict near-infrared (nir) face texture. in both cases, the input data are color (rgb) face images. experiments show, that due to the correlation between input and output signal, only a small number of canonical factors are needed to describe the functional relation of rgb images to the respective output (nir images and 3d depth maps) with reasonable accuracy.
segmentation and classification of meeting events using multiple classifier fusion and dynamic programming. in this paper the segmentation of a meeting into meeting events is investigated as well as the recognition of the detected segments. first the classification of a meeting event is examined. five different classifiers are combined through multiple classifier fusion. then a way for finding the optimal segment boundaries is presented. with a dynamic programming approach quite encouraging results can be obtained. the results show further that by classifier fusion a more stable result can be achieved than using only one single classifier.
a gauss-markov model for hyperspectral texture analysis of urban areas. in this paper we tackle the problem of texture segmentation using a joint spectral and spatial analysis of pixel distribution. hyperspectral images are considered and using a markovian model we develop a vectorial approach for this image type. a classification algorithm using this model has been implemented for extracting and classifying urban areas. results obtained from aviris images are shown.
video sequence matching with spatio-temporal constraints. the main aim of this paper is to introduce a novel spatio-temporal model of video matching. this model uses information on image object spatial relationship in frames as well as transition between frames to generate a vector representing that frame. we discuss how these vectors can be generated and matched for video retrieval.
extraction of consistent subsets of descriptors using choquet integral. this paper presents a novel approach to automatically extract a subset of shape descriptors dedicated to an application under consideration. basic descriptors having low time processing and allowing to keep nice geometric properties were implemented. then a model based on choquet integral and shapley values, is proposed to select suitable descriptors. experimental studies using real databases attest of the robustness of our approach.
color correction for the virtual recomposition of fragmented frescos. the paper describes the solution to the color correction problem used in the digital system we have designed for the reconstruction of the s. matthew fresco, painted by cimabue for the upper church of s. francis in assisi. the characteristics of the problem make difficult to evaluate correspondences between colors and require specific corrections to be applied to different parts of the fresco. the obtained improvement in terms of color similarity and retrieval results is shown.
virtual recomposition of frescos: separating fragments from the background. the paper addresses the segmentation of fragments from the background using a clustering approach in the color space. the problem is involved in the on-going development of a digital system for the virtual aided recomposition of fragmented frescos, an innovative approach currently being proved on the s. matthew's fresco, made by cimabue for the upper church of s. francis in assisi and broken, during the earthquake in 1997, into more than 140.000 pieces. the developed technique has been used to build the fragments' database. the segmentation process is based on the fast global k-means algorithm. experiments show that separation of foreground and background on a so large number of images is much more manageable and effective using prototypes built by the clustering algorithm.
sparse, variable-representation active contour models. active contours are a widely used class of models that locate object boundaries in an image by minimizing an energy function which depends on "internal" terms such as the length and curvature of the contour, and "external" terms which are functions of the image values on and near the contour. if we use the inverse rate of change of the image value as the external term, the energy will be low when the contour coincides with a strong, short, smooth boundary in the image. it is well known that this basic active contour model has difficulties in detecting object boundaries that are initially far from the contour; in locating boundary shape details; and in avoiding local minima due to image noise. the first two difficulties can be overcome by varying the energy function during the minimization process, and we show in this paper that the third difficulty can be overcome by modifying the contour representation during the process.
geometric approach for simultaneous projective reconstruction of points, lines, planes, quadrics, plane conics and degenerate quadrics. in this paper we present an algorithm for the simultaneous projective reconstruction of points, lines, planes, quadrics, plane conics and degenerate quadrics using bundle adjustment. in contrast, most existing work on projective reconstruction focuses mainly on one type of primitive. furthermore, for the reconstruction of quadrics (both full-rank and degenerate) and plane conics, a novel algorithm for the rectification of the outlines projected in n views is presented.finally, we show that reaching the global minimum during bundle adjustment is not always necessary or desirable since this state might break the topology of the quadrics being reconstructed.
an evidence combining approach to shape-from-shading. in this paper we describe a statistical framework for shape-from-shading. first, we commence by making least squares estimates of local hessian matrices using samples of surface normals. these estimated hessians are used to perform parallel transport of the surface normals across the surface. by transporting neighbouring surface normals in this way we are able collect samples of votes for the surface normal direction at each location. we select between these alternatives on the basis of compliance with the image irradiance equation.
art extension for description, indexing and retrieval of 3d objects. this paper presents a new three-dimensional shape descriptor: 3d angular radial transform. it is an extension of the 2d region based shape descriptor proposed by mpeg-7, the angular radial transform (art).we propose to generalize the art to index 3d models.
a new approach for the registration of images with inconsistent differences. in this paper, we focus on the image registration problem. mathematically, this problem consists of minimizing an energy which is composed of a regularization term and a similarity term. the similarity term, which depends on image intensities, has to be chosen according to the nature of image grey-level dependencies. its adequacy always depends on the validity of some assumptions about these dependencies. but, in medical applications, there are many situations where these assumptions are not confirmed. in particular, intensity variations caused by observed pathologies may not be consistent with assumptions. such variations may distort registration constraints and cause registration errors. in order to cope with this problem, we propose a new approach which takes into account possible inconsistencies in the computation of registration constraints. this approach is described from two different points of view. first, we formulate a new minimization problem with an extra unknown which measures the degree of inconsistency on each pixel. then, we show that this problem is equivalent to another one which can be related to usual ones. we also outline several ways to generalize our approach and propose an algorithm to solve numerically problems. finally, we illustrate on synthetic data some characteristics of the algorithmwhen dealing with inconsistent image differences.
local fisher embedding. in recent work, several supervised spectral embedding procedures have been proposed. although experimentally validated, the construction of these algorithms was rather ad hoc. this paper shows how supervised locally linear embedding can be seen as performing a local fisher mapping. a new formulation, combining linear and fisher embedding, is proposed and experimentally validated.
curvature estimation of surfaces in 3d grey-value images. in this paper we present a novel method to estimate curvature of iso grey-level surfaces in grey-value images. our method succeeds where isophote curvature fails. there is neither a segmentation of the surface needed nor a parametric model assumed. our estimator works on the orientation (normal vector) field of the surface. this orientation field and a description of local structure is obtained by the gradient structure tensor. the estimated orientation field has discontinuities mod ¡. it is mapped via the knutsson mapping to a continuous representation. the principal curvatures of the surface, a coordinate invariant property, arecomputed in this mapped representation. an evaluation shows that our curvature estimation is robust even in the presence of noise, independent of the scale of the object and furthermore the relative error stays small.
fundamental matrix estimation via tip - transfer of invariant parameters. the fundamental matrix (fm) represents the perspective transform between two or more uncalibrated images of a stationary scene, and is traditionally estimated based on 2- parameter point-to-point correspondences between image pairs. recent invariant correspondence techniques however, provide robust correspondences in terms of 4 to 6- parameter invariant regions. such correspondences contain important information regarding scene geometry, information which is lost in fm estimation techniques based solely on 2-parameter point translation. in this article, we present a method of incorporating this additional information into point-based fm estimation routines, entitled tip (transfer of invariant parameters). the tip method transforms invariant correspondence parameters into additional point correspondences, which can be used with fm estimation routines. experimentation shows that the tip methods result in more robust fm estimates in the case of sparse correspondence, and allows estimation based on as few as 3 correspondences in the case of affine-invariant features.
feature extraction from micrographs of forged nickel based alloy. various algorithms for the automatic extraction of features from micrographs of forged inconel 718 tm will be presented in this paper. this includes the extraction of an optimized boundary image, the elimination of scratches and parallel lines ("twins") and from subsequent evaluation and the detection of ä phase particles. requested features are grain size, the amount and distribution of ä phase with respect to grain boundaries and anisotropic effects.
multi-objective evolutionary clustering using variable-length real jumping genes genetic algorithm. in this paper, we present a novel multi-objective evolutionary clustering approach using variable-length real jumping genes genetic algorithms (vrjgga). the proposed algorithm that extends jumping genes genetic algorithm (jgga) [1] evolves near-optimal clustering solutions using multiple clustering criteria, without apriori knowledge of the actual number of clusters. experimental results based on several artificial and realworld data show that vrjgga can obtain non-dominated and near-optimal clustering solutions in terms of different cluster quality measures and classification performance.
the twin towers cluster in torah codes. in this paper we describe a torah code experiment which: - focuses on a famous contemporary event. - has a simple and explicit data collection. - has considerably simpler measurements than in previous torah code experiments.the pattern we study here is a cluster of related key words in the form of elss in a single table. the cluster that we discover contains a subset of all key words obtained in the data collection. we account for the choices needed to determine this subset using the bonferroni inequality. our protocol involves some other explicit choices, accounted for in a similar way. the final p-value is less than 5.14×10-5.
action spaces for efficient bayesian tracking of human motion. bayesian tracking implemented as a particle filter is one of the most used techniques for full-body human tracking. however, given the high-dimensionality of the models to be tracked, the number of required particles to properly populate the space of solutions make the problem computationally very expensive. to overcome this, we present an efficient scheme which makes use of an action model that guides the prediction step of the particle filter. in this manner, particles are propagated to locations in the search space with most a posteriori information. hence, we sample from a smooth motion model only those postures which are feasible given a particular action. we show, that this scheme improves the efficiency and accuracy of the overall tracking approach.
non-rigid registration and geometric approach for tracking in neurosurgery. registration of points obtained from preoperative 3d model and points of intraopertive stereo 3d representation, as well as tracking of surgical devices are two important stages in computer aided surgery (cas). this work shows the application and comparison of two different methods (rpm and icp) in the registration process of patient's head markers, as well as the use of geometric methods to track the surgical device in real time.
non-rigid alignment and real-time tracking using the geometric algebra framework. this paper presents two applications of geometric algebras: the main is a variant of the thin-plate - robust point matching algorithm, named by us "robust sphere matching", to register 3d objects modeled as sets of spheres using the representation of such spheres in the conformal geometric algebra. by this way, we take advantage and combine the geometric interpretation of entities of such algebra with the statistical methods used in the algorithm. in the experimental part, examples using synthetic and real data are presented to show how the algorithm works reliably, aligning volumetric models based on spheres. the second applications is the real time tracking of devices.
texture feature extraction and indexing by hermite filters. we present a texture feature extraction for image indexing and retrieval based on gabor-like hermite filters. these ones satisfy a frequency constraint of steered discrete hermite filters, which form a local orthogonal basis and agree with the gaussian derivative model of the human visual system. fast implementation of such filters is performed by a normalized recurrence relation of their discrete representation, the krawtchouk filters. in order to achieve dimensionality reduction for texture image indexing purposes, we apply a compact parametric texture model, which corresponds to the spatial autocorrelation of each subband output. experimental results obtained from a texture image database are also presented.
a real-time system for classification of moving objects. the paper describes a system for moving object classification. being restricted by real-time system constraints we found a small set of features, characterizing object shape and motion dynamics. the system was tested on a large movies database including more than 100 images sequences showing people, animals, vehicles and plants in motion. the svm classifier [1] was used in our system, yielding very good classification results.
part-based multi-frame registration for estimation of the growth of cellular networks in plant roots. motion estimation from confocal scanning laser microscope images of growing plant cell structures presents interesting challenges; motion exhibits multiple local discontinuities and noise is non-isotropic and non-gaussian. a method is presented for estimating motion of cell networks based on a physically motivated, part-based model of cell boundary structure. each part models the shape and appearance of a localised image region and can undergo constrained non-rigid deformation. this enables motion discontinuities between parts to be modelled. parts are coupled in order to improve localisation and increase computational efficiency. results from applying mcmc show accurate localisation of the structure across multiple frames. the form of the model assists biologists in interpreting growth.
online appearance learning or 3d articulated human tracking. a human appearance modelling framework where colour distributions are associated with surface regions on an articulated body model is presented. in general, these distributions are unknown, multi-modal and changing in time. we therefore propose using recursively updated histograms to represent them. for a certain pose, a set of histograms may be collected and a likelihood constructed based on the histograms' similarity with the previously learned histograms. to ease histogram estimation and improve computational efficiency, a merging and splitting algorithm is derived which groups surface regions based upon histogram similarity and prior knowledge of clothing layout. an investigation of the behaviour of this likelihood shows it to be broad, smooth and peaked around the correct location, a good candidate for coarse sampling and gradient-based search methods. we show how conditioning the likelihood to maximise foreground usage reduces secondary maxima. finally, we present results from tracking a challenging sequence.
optimal detection of blurred edges. i develop a variational model for the detection of blurred edges. though yielding a complicated general solution, the model gives insight into edge detection models previously proposed for step edges. in particular it shows that a previous iir solution for step edges is correct even in the fir case, and suggests why operators approximating the first derivative of a gaussian are successful, despite their suboptimality for step edge detection. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
a graph-spectral approach to surface segmentatio. in this paper we describe a graph-spectral method for 3d surface segmentation from 2d imagery. the method locates patches by finding groups of pixels that can be connected using a curvature minimising path. the path is the steady state markov chain on transition probability matrix. we provide two methods for computing this matrix. the fir st uses information provided by the field of surface normals extracted from the 2d intensity image using shape-from-shading. here we compute the elements of the transition matrix using the change in surface normal directions to estimate the normal curvature. the second approachuses the raw image brightness together with a lambertian reflectance model to make estimates of curvature. we compare the surface segmentations delivered by these two methods with those obtained using shape-index maximal patches.
vector field smoothing via heat flow. in this paper, we develop a new method for recovering and smoothing fields of surface normals in shape-from-shading. we show how transform the problem of recovering surface normals that satisfy lmbeert's law into that of solving the steady state heat equation for a scalar potential. according to this picture, the smoothed field of surface normals is found by taking the gradient of the scalar field. the heat equation for the scalar field can be solved using simple finite difference methods, and leads to an iterative procedure for vector estimation. we illustrate the utility of the new method on real world imagery and compare our results with those delivered by an alternative.
pollen classification using brightness-based and shape-based descriptors. pollen grain classification have recently received more attention from computer vision researchers. to distinguish among taxa, palynologist make direct use of keys such as the size, exine structure and sculpture of the pollen grains. we propose a framework in which the pollen grains of each taxa are characterized using brightness and shape descriptors derived from their intensity images. these descriptors are associated to the ornamentation and morphology of the pollen grain. the method is statistically evaluated on preparations containing species of the urticaceae family.
range image segmentation based on split-merge clustering. in this paper, we present a split-merge clustering segmentation algorithm based on gaussian mixture models, which resolves the models by expectation-maximization (em) algorithm and seeks model via bayesian information criterion (bic). it starts iteratively splitting from a single gaussian model, then iteratively merging clusters. after convergence of the last stage, the clustering model is selected via a modified bic and used to gain an initial segmentation, followed by a region merge step to achieve final segmentation. new algorithm was applied to 60 range images acquired by two kinds of range cameras, and got approving results with acceptable computation time.
augmenting fast stereo with silhouette constraints for dynamic 3d capture. we propose and evaluate a method that combines a visual hull with multi-view stereo for the fast acquisition of dynamic 3d data. both use the same set of cameras. the focus lies on high speed, as 3d has to be generated repeatedly, based on the output of multiple video cameras. the underlying principle is to bootstrap the system with quickly computed sparse stereo, constrained by silhouette information. we further show how this integrates with a fast plane sweeping algorithm, as our dense stereo algorithm of choice.
gesture detection in low-quality video. the spotting and recognition of the human gestures is a key task in automating the analysis of the video material and human-robot interaction. specially, applying this technology to low-resolution video has many potential applications. the human area is small with respect to input video frames in broadcast sports video, surveillance video, etc. however, this condition makes the spotting certain gesture in a video sequence a challenging task, especially if there is large camera motion. to overcome the problems, we propose a posture matching method based on curvature scale space templates of the human silhouette. we also propose a new recognition method which is robust to noisy sequences of data.
volume motion template for view-invariant gesture recognition. the representation of gestures changes dynamically, depending on camera viewpoints. this camera viewpoints problem is difficult to solve in environments with a single directional camera, since the shape and motion information for representing gestures is different at different viewpoints. in view-based methods, data for each viewpoint is required, which is ineffective and ambiguous in recognizing gestures. in this paper, we propose a volume motion template (vmt) to overcome the viewpoint problem in a single-directional stereo camera environment. the vmt represents motion information in 3d space using disparity maps. motion orientation is determined with 3d motion information. the projection of vmt at the optimal virtual viewpoint can be obtained by motion orientation. the proposed method is not only independent of variations of viewpoints, but also can represent depth motion. the proposed method has been evaluated in view-invariant representation and recognition using the gesture sequences which include parallel motion in an optical axis. the experimental results demonstrated the effectiveness of the proposed vmt for view-invariant gesture recognition.
automatic adjacency grammar generation from user drawn sketches. in this paper we present an innovative approach to automatically generate adjacency grammars describing graphical symbols. a grammar production is formulated in terms of rulesets of geometrical constraints among symbol primitives. given a set of symbol instances sketched by a user using a digital pen, our approach infers the grammar productions consisting of the ruleset most likely to occur. the performance of our work is evaluated using a comprehensive benchmarking database of on-line symbols.
smoothing with active surfaces: a multiphase level set approach. in this paper, we propose to use an active contour method to attract active surfaces towards non-smoothed segmentation masks. to achieve this task, we introduce a new region-based term for active contour segmentation in the multiphase level set framework. this term attracts evolving curves to reference contours while being constrained by rigidity terms. this technique considerably reduces flickering on the boundaries of the segmentation masks.
description of local singularities for image registration. recently, it has been shown that gradient-based meth- ods are the most powerful approaches for describing the lo- cal content of digital images in the neighborhood of salient points. in practice, salient points are always located on image singularities whatever the detector used. in this pa- per, we show that a more efficient mathematical notion can be used to describe singularities: the h¨older exponent. we propose here to conjointly use the h¨older exponents and the direction of minimal regularity of the bidimensionnal signal singularities to compute a signature describing precisely a region of interest centered on an interest point. h¨older ex- ponents are estimated thanks to the foveal wavelets theory and the resulting descriptor is shown to be more efficient than classical sift and pca-sift descriptors in the case of an image registration application.
adaptative evaluation of image segmentation results. we present in this article a new unsupervised evaluation criterion that enables the quantification of the quality of an image segmentation result according to the type of the original image. we first briefly present a comparative study of existing unsupervised evaluation criteria. then, we present a method for the determination of the type of the original image: uniform, mixed or textured by using a learning method (support vector machine). in the third part, we present the proposed algorithm for segmentation evaluation and the experimental results on synthetic images from a large database. last, we conclude and present some perspectives of this work.
measuring shape: ellipticity, rectangularity, and triangularity. object classification often operates by making decisions based on the values of several shape properties measured from an image of the object. this paper describes several algorithms (both old and new) for calculating ellipticity, rectangularity, and triangularity shape descriptors. the methods are evaluated by testing on both synthetic and real data.
a symmetric convexity measure. a new area-based convexity measure for polygons is described. it has the desirable properties that it is not sensitive to small boundary defects, and it is symmetric with respect to intrusions and protrusions. the measure requires a maximally overlapping convex polygon, and this is efficiently estimated using a genetic algorithm. examples of the measures application to medical image analysis are shown.
a hybrid fingerprint matcher. we describe a hybrid fingerprint matching scheme that uses both minutiae and ridge flow information to represent and match fingerprints. a set of 8 gabor filters, whose spatial frequencies correspond to the average inter-ridge spacing in fingerprints, is used to capture the ridge strength at equally spaced orientations. a square tessellation of the filtered images is then used to construct an eight-dimensional feature map, called the ridge feature map. the ridge feature map along with the minutiae set of a fingerprint image is used for matching purposes. the genuine accept rate of the hybrid matcher is observed to be ~ 10% higher thanthat of a minutiae-based matcher at low false accept rates. fingerprint verification using the hybrid matcher on a pentium iii (800 mhz) processor, takes - 1.4 seconds.
comparison of methods for hyperspherical data averaging and parameter estimation. averaging is an important concept which has found numerous applications in general and in pattern recognition and computer vision in particular. in this paper we consider averaging directional vectors of arbitrary dimensions. given a set of vectors, we intend to compute an average vector which optimally represents the input vectors according to some formal criterion. several optimisation criteria are formulated. in particular, we present a class of robust estimators of up to 50% outlier tolerance. furthermore, we propose a technique to estimate another distribution parameter. experimental results on spherical data are presented to demonstrate the usefulness of the proposed methods.
building detection by dempster-shafer fusion of lidar data and multispectral aerial imagery. a method for the classification of land cover in urban areas by the fusion of first and last pulse lidar data and multi-spectral images is presented. apart from buildings, the classes "tree", "grass land", and "bare soil" are also distinguished by a classification method based on the theory of dempster - shafer for data fusion. examples are given for a test site in germany.
coarse-to-fine multiscale affine invariant shape matching and classification. in this paper, a multiscale algorithm for matching and classifying 2-d shapes is developed. the algorithm uses the 1-d dyadic wavelet transform (dwt) to decompose a shape's boundary into multiscale levels. then the coarse to fine matching and classification are achieved in two stages. in the first stage, the global features are extracted by calculating the curve moment invariants of the approximation coefficients. by calculating the normalized cross correlation of the 1-d triangle area representation of the detail coefficients, the local similarity is achieved by the second stage. the proposed algorithm is invariant to the affine transformation and to the boundary starting point variation. in addition, the results demonstrate that the new algorithm is not sensitive to small boundary deformations.
a new perceptive system for the recognition of cursive handwriting. we present a new system for the recognition of cursive handwriting that is based on a perceptive model and neural networks. at the high level, our system takes into account several psychological effects such as the word superiority effect. at the low level, it utilizes a global feature extraction method which models how some features might be preattentively detected by the human visual system. it presents a very good tolerance to noise and stroke disconnections and captures most of the information contained in the singular part of the cursive word. at the pre-recognition stage, external letters are better recognized than middle letters. thus, because it uses a recognition process that is based on an interactive activation mechanism, recognition is performed from the outside to the inside of the word. we have obtained encouraging results.
semantic understanding of continued and recursive human activities. this paper presents a methodology for semantic understanding of complex and continued human activities. a context-free grammar (cfg) based representation scheme developed earlier is extended to construct a description for continued and recursive human activities. new system recognizes recursively described high-level interactions: fighting and greeting. the system understands activities by detecting the time intervals that satisfy their semantic descriptions.
template adaptation based fingerprint verification. this paper proposes a minutiae-based template adaptation algorithm which can be applied after the fingerprint authentication process. the algorithm updates a template by using a query fingerprint, which is successfully verified by the fingerprint matcher as a high quality genuine input. this algorithm generates an updated minutiae set by using not only the minutiae but also local fingerprint quality information and utilizes a successive bayesian estimation to evaluate the credibility of minutiae and their types. the proposed algorithm updates fingerprint minutiae information in the template as well as appends new minutiae from the query fingerprint. preliminary experiments show an average 32.7% eer reduction and an even higher matching accuracy improvement at low false accept rates.
shape decomposition approach for ultrasound color doppler image segmentation. we present a novel technique for segmenting blood vessels in ultrasound color doppler images based on shape decomposition. ultrasound color doppler images frequently suffer from a vessel linking artifact called 'color bleeding'. the proposed technique decomposes a complex binary object representing either two or more vessels artificially linked together or a main vessel with its branches. the resulting simple parts represent distinct vessels that can be used in further object recognition and quantification applications.
optimally regularised kernel fisher discriminant analysis. mika et al. [fisher discriminant analysis with kernels] introduce a non-linear formulation of fisher's linear discriminant, based the now familiar "kernel trick", demonstrating state-of-the-art performance on a wide range of real-world benchmark datasets.in this paper, we show that the usual regularisation parameter can be adjusted so as to minimise the leave-one-out cross-validation error with a computational complexity of only o(l^2) operations, where l is the number of training patterns, rather than the o(l^4) operations required for a naïeve implementation of the leave-one-out procedure.this procedure is then used to form a component of an efficient heirarchical model selection strategy where the regularisation parameter is optimised within the inner loop while the kernel parameter are optimised in the outer loop.
combining shape from silhouette and shape from structured light for volume estimation of archaeological vessels. an algorithm for the automatic construction of a 3d model of archaeological vessels using two different 3d algorithms is presented. in archeology the determination of the exact volume of arbitrary vessels is of importance since this provides information about the manufacturer and the usag of the vessel. to acquire the 3d shape of objects with handles is complicated, since occlusions of the object's surface are introduced by the handle and can only be resolved by taking multiple views. therefore, the 3d reconstruction is based on a sequence of images of the object taken from different viewpoints with two different algorithms; shape from silhouette and shape from structured light. the out-put of both algorithms are then used to construct a single 3d model. results of the algorithm developed are presented for both synthetic and real input images.
a new clustering method for improving plasticity and stability in handwritten character recognition systems. this paper presents a new online clustering algorithm in order to improve plasticity and stability in handwritten character recognition systems. our clustering algorithm is able to automatically determine the optimal number of clusters in the input data. an incremental learning technique similar to adaptive resonance theory (art) is used to determine the best cluster for new data. our technique also allows the previously learned clusters to be merged whenever the newly arrived data points push their centers close together. we also developed new features and similarity measures in order to describe and compare the shapes of handwritten digits to be used in our clustering algorithm. results of our algorithm on clustering the shapes of the handwritten numerals from the cenparmi isolated digit database are shown. our method can incrementally learn new handwriting styles of digits, without forgetting the previous ones, therefore it can improve plasticity and stability.
joint spatial and temporal structure learning for task based control. we present an example of a joint spatial and temporal task learning algorithm that results in a generative model that has applications for on-line visual control. we review work on learning transformed mixture of gaussians (due to frey and jojic) and variable length markov models (vlmms due to ron, singer and tishby). we show how a temporal model, learned through an extension of vlmms to deal with multinomially distributed input symbol vectors, can be used as an improvement on maximum likelihood (ml) for prior parameter estimation for the expectation maximisation (em) process.
fast feature extraction approach for multi-dimension feature space problems. recently, we proposed a fast feature extraction approach denoted fsom utilizes self organizing map (som). fsom [1] overcomes the slowness of traditional som search algorithm. we investigated the superiority of the new approach using two lip reading data sets which require a limited feature space as the experiments in [1] showed. in this paper, we continue fsom investigation but using an rgb face recognition database across different poses and different lighting conditions. we believe that such data sets require multi-dimensional feature space to extract the information included in the original data in an effective way especially if you have a big number of classes. again, we show here how is fsom reduces the feature extraction time of traditional som drastically while preserving same som's qualities.
a texture based matching approach for automated assembly of puzzles. the puzzle assembly problem has many application areas such as restoration and reconstruction of archeological findings, repairing of broken objects, solving jigsaw type puzzles, molecular docking problem, etc. the puzzle pieces usually include not only geometrical shape information but also visual information such as texture, color, and continuity of lines. this paper presents a new approach to the puzzle assembly problem that is based on using textural features and geometrical constraints. the texture of a band outside the border of pieces is predicted by inpainting and texture synthesis methods. feature values are derived from these original and predicted images of pieces. an affinity measure of corresponding pieces is defined and alignment of the puzzle pieces is carried out using an fft based image registration technique. the optimization of total affinity gives the best assembly of puzzle. experimental results are presented on real and artificial data sets.
cbir using perception based texture and colour measures. we have designed and implemented an experimental cbir system that uses a texture co-occurence matrix. fuzzy index of major colours are also used as colour feature to improve performance. a new measure is suggested to find out the relevance of the retrieved images and to evaluate the cbir system. accordingly, the performance study of the proposed system is carried out and compared with a similar system. the study has established the effectiveness of the features.
coarse-to-fine support vector classifiers for face detection. we describe a new hierarchical face detection algorithm which allows fast background rejection in major parts of images and fine processing in area containing faces. this coarse-to-fine classification strategy is based on learning support vector classifiers (svms) with increasing evaluation complexity (resp. decreasing invariance and false alarm rates) top-down in the hierarchy. the complexity, in terms of the number of support vectors, of each detector inthe hierarchy is reduced by clustering. we introduce the bias variation technique which allows each simplified svm function to satisfy the conservation hypothesis as a criterion to get a consistent classifier in terms of detection rate, false alarms and background rejection efficiency . face detection is performed using a depth-first search and cancel strategy which, for a given "face pattern", finds a root-leaf path with a sequence of positive answers.
a robust semi-supervised em-based clustering algorithm with a reject option. in this paper, we address the problem of semi-supervision in the framework of parametric clustering by using labeled and unlabeled data together. clustering algorithms can take advantage from few labeled instances in order to tune parameters, improve convergence and overcome local extrema due to bad initialization. we extend a robust parametric clustering algorithm able to manage outlier rejection to the semi-supervision approach. this is achievedby modifying the expectation-maximization algorithm. the proposed method shows good performance with respect to data structure discovering, even facing to outliers.
automatic recognition of blooming flowers. this paper describes an automatic method for recognizing a blooming flower based on a photograph taken with a digital camera in natural scene. the problem of identifying an object against the background is known to be difficult. in this paper, we employ a photograph where the object (a blooming flower) is focused but the background is defocused. for extracting a flower region, we propose a new method that extracts a boundary by selecting a route with minimizing a sum of the local cost divided by the route length. experiments were conducted for 600 pictures (20 pictures each for 30 species). a successful boundary extraction rate of 97% and a flower recognition rate of 90% were obtained.
automatic segmentation of liver region through blood vessels on multi-phase ct. recently four phases ct has been widely used for diagnosing liver diseases, especially cancer. this paper describes an automatic method for segmenting the liver region from third phase abdominal ct. first, blood vessels in the liver are extracted with a threshold. then morphological dilation enables us to define an approximate liver region, which is found to be very useful for removing abutting organs. the final liver region is extracted with a threshold. experiments were conducted for eight ct data. the extracted regions agree well with those detected manually.
human and object detection in smoke-filled space using millimeter-wave radar based measurement system. in recent years, crisis management's response to terrorist attacks and natural disasters, as well as accelerating rescue operations have become an important issue. in rescue operations of fire disaster, one of the biggest problems is that the firefighter's view is obstructed by dense smoke. we considered the most important task for firefighters is to understand the inside situation of the dense smoke space. therefore, we aim to develop a system visualizing the situation of the space. first, we scanned target space by using millimeter-wave radar combined with a gyro sensor. then, due to detect humans and objects, we construct a 3d map from signal-reflection datasets using 3d image processing techniques. in this paper, we introduce our system and report the results of the measurement experiment in the real smoke space situation.
genetic translator: how to apply query learning to practical ocr. we propose a novel learning method combining query learning and a "genetic translator" we developed.query learning is a useful technique for high-accuracy, high-speed learning. however, it has not been applied for practical optical character readers (ocrs), since human beings cannot recognize queries in the feature space used in practical ocr devices. we previously proposed a character image reconstruction method using the genetic algorithm. here, this method is applied as a "translator" from feature space for query learning of character recognition. the results of an experiment with hand-printed numeral recognition demonstrate the potential of the proposed method.
a real-life test of face recognition system for dialogue interface robot in ubiquitous environments. this paper discusses a face recognition system for a dialogue interface robot that really works in ubiquitous environments and reports an experimental result of real-life test in a ubiquitous environment. while a central module of the face recognition system is composed of the decomposed eigenface method, the system also includes a special face detection module and the face registration module. since face recognition should work on images captured by a camera equipped on the interface robot, all the methods are tuned for the interface robot. the face detection and recognition modules accomplish robust face detection and recognition when one of the registered users is talking to the robot. some interesting results are reported with careful analysis of a sufficient real-life experiment.
image-recognition technologies towards advanced automated teller machines. several image-recognition techniques that can provide the important functions required by advanced-intelligent automated teller machines (ai-atms) are described. these functions are (1) basic cash handling such as withdrawal and deposit of money, (2) handling remittance forms and cheques, (3) delivering information as an "information kiosk," and (4) security maintenance such as identification of users and surveillance of the atm environment. the image-recognition techniques for realising these ai-atm functions are (1) banknote image processing, (2) form processing and character recognition, (3) intention recognition, and (4) biometric techniques.
incremental mixtures of factor analysers. a mixture of factor analyzer is a semiparametric density estimator that performs clustering and dimensionality reduction in each cluster (component) simultaneously. it performs nonlinear dimensionality reduction by modeling the density as a mixture of local linear models. the approach can be used for classification by modeling each class-conditional density using a mixture model and the complete data is then a mixture of mixtures. we propose an incremental mixture of factor analysis algorithm where the number of components (local models) in the mixture and the number of factors in each component (local dimensionality) are determined adaptively. our results on different pattern classification tasks prove the utility of our approach and indicate that our algorithms find a good trade-off between model complexity and accuracy.
object segmentation and feature estimation using shadows. we introduce an automatic underwater video-based system for estimating features such as length and 3-d velocity of fish from a single-view camera system. artificial light provides a high contrast object shadow, which is exploited both in the segmentation process, and to achieve 3-d inference about the fish. the proposed video segmentation method is demonstrated successfully on video-recordings of greenland halibut.
a new method to detect arcs and segments from curvature profiles. in this paper a new method of arc detection based on arithmetic discrete lines is presented. key points are extracted from such a profile and used for the reconstruction. the used method is fast and easy to implement. experimental studies on several series of test images show the stability and the robustness of the proposed method.
learning classes for video interpretation with a robust parallel clustering method. we propose an original learning approach for image classification problems. recognizing semantic events in video requires to preliminary learn the different classes of events. this first stage is crucial since it conditions the further classification results. in video content analysis, the task is especially difficult due to the high intra-class variability and to noisy measurements. we then represent each class by the centers of several sub-classes (or clusters) thanks to a robust partitional clustering algorithm which can be applied in parallel to a (non-predefined) number of classes. our clustering technique overcome three main limitations of standard k-means methods: sensitivity to initialization, choice of the number of clusters and influence of outliers. moreover, it can process the training data in an incremental way. experimental results on sports videos are reported.
prioritized region of interest coding in jpeg2000. a method is proposed to encode multiple regions of interest in the jpeg2000 image-coding framework. the algorithm is based on the rearrangement of packets in the code-stream to place the regions of interest before the background coefficients. in order to improve the quality of the reconstructed image, partial background information is included with the regions of interest. the proposed technique is fully compatible with the current jpeg2000 standard and allows transmission of different regions of interest with different priorities. experimental results demonstrating the validity of the proposed approach are presented and compared with existing region of interest coding techniques.
a theory of the quasi-static world. we present the theory behind a novel unsupervised method for discovering quasi-static objects, objects that are stationary during some interval of observation, within image sequences acquired by any number of uncalibrated cameras. for each pixel we generate a signature that encodes the pixel's temporal structure. using the set of temporal signatures gathered across views, we hypothesize a global schedule of events and a small set of objects whose arrivals and departures explain the events. the paper specifies observability conditions under which the global schedule can be established and presents the qsl algorithm that generates the maximally-informative mapping of pixels' observations onto the objects they stem from. our framework ignores distracting motion, correctly deals with complicated occlusions, and naturally groups observations across cameras. the sets of 2d masks we recover are suitable for unsupervised training and initialization of object recognition and tracking systems.
on authorship attribution via markov chains and sequence kernels. we investigate the use of recently proposed character and word sequence kernels for the task of authorship attribution and compare their performance with two probabilistic approaches based on markov chains of characters and words. several configurations of the sequence kernels are studied using a relatively large dataset, where each author covered several topics. utilising moffat smoothing, the two probabilistic approaches obtain similar performance, which in turn is comparable to that of character sequence kernels and is better than that of word sequence kernels. the results further suggest that when using a realistic setup that takes into account the case of texts which are not written by any hypothesised authors, about 5000 reference words are required to obtain good discrimination performance.
motion analysis using frame differences with spatial gradient measures. the paper considers making inferences about the underlying true 2-d motion when only evaluations of a local block-based cost function, the mean of absolute or squared differences, for a set of motion candidates are available. considering bounds for these criteria, it is shown that simple local image gradient measures provide useful information for interpreting the criterion values. based on analysis, a thresholding scheme for the criteria is proposed. using a gaussian approximation for the thresholding result, estimates of local motions and related uncertainties can be obtained.
shape similarity image retrieval by hypothesis and test. image retrieval by shape similarity systems usually either focus their attention on images with isolated objects (uniform backgrounds and no occluding objects) or perform time consuming exhaustive initializations to localize the portion of the image possibly containing the searched shape. we propose a content based image retrieval (cbir) method merging classic alignment techniques for an efficient shape localization with an innovative verification strategy able to deal with an inexact matching between the searched and the found shape.
class-specific subspace-based two-dimensional principal component analysis for face recognition. in this paper, we proposed a class-specific subspacebased two-dimensional principal component analysis (2dpca) for face recognition. in 2dpca, 2d face image matrices do not need to be previously transformed into a vector. in this way, the spatial information can be preserved. moreover, 2dpca can achieve higher performance than pca both in face recognition and face representation task. however, both pca and 2dpca are unsupervised techniques, no information of class labels are considered. therefore, the directions that maximize the scatter of the data might not be as adequate to discriminate between classes. in recognition task, a projection is required to emphasize the discrimination between classes. the face-specific subspace (fss) was proposed in concept of class-specific subspace. each subspaces learned from the training images which correspond to only one class, thus the number of these subspaces is equal to the number of classes. since the information of class labels are considered in fss, so the discriminant power can be improved. we apply 2dpca to class-specific concept in our framework which consists of two methods: the first one, we apply fss to 2dpca method and the second one, we use the bilateral-projection-based 2dpca (b2dpca) instead of 2dpca. the b2dpca does not only allows further reducing of the dimension of feature matrix of 2dpca-based but also improving the classi fi cation accuracy. experimental results on yale face database showed an improvement of our proposed techniques over the conventional 2dpca.
texture analysis using level-crossing statistics. we present a novel statistical texture descriptor employing level-crossing statistics. images are first mapped into 1d signals using space-filling curves, such as peano or hilbert curves, and texture features are extracted via signal-dependent sampling. texture parameters are based on the level-crossing statistics of the 1d signal, i.e. crossing rate, crossing slope and sojourn time. despite the simplicity of texture features used, our approach offers state-of-the art performance in the texture classification and texture segmentation tasks, outperforming other tested algorithms.
an unsupervised algorithm for anchor shot detection. in this paper we present a novel algorithm for anchor shot detection (asd). asd is a fundamental step for segmenting news video into stories that is among key issues for achieving efficient treatment of news-based digital libraries. the proposed algorithm firstly uses a clustering method for individuating candidate anchor shots and then employs a two-stage pruning technique for reducing the number of falsely detected anchor shots. both clustering and pruning are carried out in an unsupervised way. the algorithm has been tested on a wide database and compared with other state-of-the-art algorithms, demonstrating its effectiveness with respect to them.
fair: towards a new feature for affinely-invariant recognition. in this paper we propose the first version of fair, a low-dimensional image neighborhood descriptor that shows performance comparable to sift introduced by lowe. the dimension of fair we tested is 30, compared to the dimension of 128 in sift. sensitivity of the fair descriptor to skew, rotation, image blur and noise is similar to sift. fair shows better localization in scale-space than sift. several extensions of fair that could improve its performance are discussed.
iterative error bound minimisation for aam alignment. the active appearance model (aam) is a powerful generative method used for modelling and segmenting deformable visual objects. linear iterative methods have proven to be an efficient alignment method for the aam when initialisation is close to the optimum. however, current methods are plagued with the requirement to adapt these linear update models to the problem at hand when the class of visual object being modelled exhibits large variations in shape and texture. in this paper, we present a new precomputed parameter update scheme which is designed to reduce the error bound over the model parameters at every iteration. compared to traditional update methods, our method boasts significant improvements in both convergence frequency and accuracy for complex visual objects whilst maintaining efficiency.
image classification: classifying distributions of visual features. we classify an image by generating a list of salient visual features present in the luminance channel, and matching the resulting variable-length feature list to categoryspecific generative models for such features. to facilitate quick computation, we use thresholded viola-jones rectangular features, each represented by a five-dimensional descriptor. for each image category, a probability distribution for feature-lists is given by a latent conditional independence (lci) model and classification is maximum likelihood. on the nist tax forms database [3], where intracategory variations include variable scan-lightness, skew, noise, and machine-printed form-filling, our method improves performance over published results, while requiring very little training data, and without relying on an extensive set of handcrafted features.
decoder banks: versatility, automation, and high accuracy without supervised training. a methodology using decoder banks is proposed for high-accuracy, fully automatic recognition of machine printed text across a wide range of challenging image qualities, without requiring manual intervention or supervised training. this approach is made possible by two crucial properties of document image decoding (did) technology: (1) it is trainable for high accuracy across a wide range of explicitly parameterized image degradations; and (2) decoders for arbitrary parameter settings can be generated automatically. we report the results of large-scale experiments on synthetic images which demonstrate that, when many pretrained decoders are applied in parallel to an input image with unknown parameters, the decoder that yields the highest accuracy is often the one that exhibits the highest did posterior 'viterbi score'. when implemented naively, in a brute-force manner, decoder banks are computationally intensive: but we suggest ways that this cost may be reduced with no loss of versatility, automation, or accuracy.
multiple target tracking by appearance-based condensation tracker using structure information. multiple target tracking is a challenging problem, especially when targets are frequently crossing each other. it becomes very difficult and confusing when some targets are often occluded by other targets. this paper proposes a novel tracking method for the problem using an appearance-based condensation tracker. in order to overcome difficulties in the occlusion problem, a target object is regarded as a set of partsthat constrains each other in the target structure. while each part is tracked basically in the condensation method, all the parts cooperate in the drift step of the condensation. experimental results show the effectiveness of the proposed method formultiple person tracking and human face tracking.
3-d modeling of an outdoor scene by multi-baseline stereo using a long sequence of images. three-dimensional (3-d) models of outdoor scenes are widely used for object recognition, navigation, mixed reality, and so on. because such models are often made manually with high costs, automatic 3-d modeling has been investigated. a 3-d model is usually generated by using a stereo method. however, such approaches cannot use several hundreds images together for dense depth estimation because it is dicult to accurately calibrate a large numberof cameras. in this paper, we propose a 3-d modeling method that first estimates extrinsic camera parameters of a monocular image sequence captured by a moving video camera, and then reconstructs a 3-d model of a scene. we can acquire a 3-d model of an outdoor scene accurately by using several hundreds input images.
change detection in streetscapes from gps coordinated omni-directional image sequences. as part of its technology, to achieve quick map updates, we propose a method for automatically detecting changes in streetscapes from images captured by car-mounted omnidirectional cameras. it comprises two stages; accurate alignment of a map and street images taken at various times, and detection of changes in streetscapes from the aligned data. the system will collect data via many free-running cars fitted with low-cost equipment to obtain images at various times and along routes. in the first stage, we process the alignment of the image frames taken at same locations and determine the accurate position information of each frame by a method composed of dimension reduction and dp matching. then in the second stage, we detect changes in streetscapes from images taken at various times. experiments with 44 data items which were collected over about a year, demonstrate the effectiveness of our method.
a color-based tracking by kalman particle filter. in this paper, a method for real-time tracking of moving objects is proposed. we applied kalman particle filter (kpf) to color-based tracking. this kpf is a particle filter including the principle of kalman filter, and it was adopted to the object contour tracking. we modified this kpf for color-based tracking. this modified kpf can approximate the probabilistic density of the position of the tracked object properly and needs fewer particles for tracking than conventional particle filters. we made experiments to confirm effectiveness of this method.
development of omni-directional stereo vision-based intelligent electric wheelchair. this paper describes the development of a support technology to enhance the independent mobility of disabled persons, featuring an electric wheelchair fitted with an innovative camera system "stereo omnidirectional system (sos)". the sos can capture omnidirectional color images and range information in real time, enabling automatic detection and avoidance of dangers in the wheelchair's traveling environment, and has a remote assistance function. this study deals principally with basic platform design, focusing on the basic technology required for application of the sos to electric wheelchairs, such as high-speed, highdefinition integrated processing of omni-directional images, and automatic correction of camera pose.
unsupervised robust clustering for image database categorization. content-based image retrieval can be dramatically improved by providing a good initial database overview to the user. to address this issue, we present in this paper the adaptive robust competition. this algorithm relies on a non-supervised database categorization, coupled with a selection of prototypes in each resulting category. in our approach, each image is represented by a high-dimensional signature in the feature space, and a principal component analysis is performed for every feature to reduce dimensionality. image database overview is computed in challenging conditions since clusters are overlapping with outliers and the number of clusters is unknown.
an lbp-based active contour algorithm for unsupervised texture segmentation. this paper presents a novel algorithm for unsupervised texture segmentation. the proposed algorithm incorporates the local binary pattern operator under a segmentation framework based on the active contour without edges model. the experiments performed, show that it can be used for fast segmentation of two-textured images, outperforming recent texture segmentation algorithms, with a segmentation quality that reaches 99% on average.
"eigenphases vs. eigenfaces". in this paper we present a novel method for performing robust illumination-tolerant and partial face recognition that is based on modeling the phase spectrum of face images. we perform principal component analysis in the frequency domain on the phase spectrum of the face images and we show that this improves the recognition performance in the presence of illumination variations dramatically compared to normal eigenface method and other competing face recognition methods such as the illumination subspace method and fisherfaces. we show that this method is robustl even when presented with partial views of the test faces, without performing any pre-processing and without needing any a-priori knowledge of the type or part of face that is occluded or missing. we show comparative results using the illumination subset of cmu-pie database consisting of 65 people showing the performance gain of our proposed method using a variety of training scenarios using as little as three training images per person. we also present partial face recognition results that obtained by synthetically blocking parts of the face of the test faces (even though training was performed on the full face images) showing gain in recognition accuracy of our proposed method.
road extraction by snake with inertia and differential features. in this paper we propose an extraction technique based on an active contour model (snake) considering inertia and differential features of an object in movie. in many methods for tracking a moving object, a snake is applied to a scene frame by frame, and initial positions of control points in a frame refer to results in the previous frame. we focus on inertia which works between previous and present frames. in this paper inertia is the tendency of a control point to resist changes in its state of motion in an image space. we propose an internal energy for snakes based on inertia of control points. proposed method is applied to extract road geometry from a video camera equipped on the head of a vehicle. internal energy functions based on differential features of road geometry is also introduced. experimental results indicate the availability of the proposed method.
unsupervised learning of dense hierarchical appearance represe. we describe an unsupervised, probabilistic method for learning visual feature hierarchies. starting from local, low-level features computed at random locations, the method combines features hierarchically. at each level of the hierarchy, pairs of features are identified that tend to occur at stable positions relative to each other, by clustering the configurational distributions of observed feature cooccurrences using expectation-maximization. stable pairs of features thus identified are combined into higher-level features. this learning scheme results in a graphical model that constitutes a probabilistic representation of a flexible visual feature hierarchy. for detection, evidence is propagated using nonparametric belief propagation, a recent generalization of particle filtering. in experiments, the proposed approach demonstrates effective learning and robust detection of objects in the presence of clutter and occlusion.
unsupervised texture segmentation by spectral-spatial-independent clustering. a novel color texture unsupervised segmentation algorithm is presented which processes independently the spectral and spatial information. the algorithm is composed of two parts. the former provides an over-segmentation of the image, such that basic components for each of the textures which are present are extracted. the latter is a region growing algorithm which reduces drastically the number of regions, and provides a region-hierarchical texture clustering. the over-segmentation is achieved by means of a color-based clustering (cbc) followed by a spatial-based clustering (sbc). the sbc, as well as the subsequent growing algorithm, make use of a characterization of the regions based on shape and context. experimental results are very promising in case of textures which are quite regular.
wavelet denoising of multicomponent images, using a gaussian scale mixture model. in this paper, denoising on multicomponent images is performed. the presented procedure is a spatial waveletbased denoising techniques, based on bayesian leastsquares optimization procedures, using a prior model for the wavelet coefficients that account for the intercorrelations between the multicomponent bands.the applied prior model for the multicomponent signal is a gaussian scale mixture (gsm) model. the method is compared to single-band wavelet denoising and to multiband denoising using a gaussian prior. experiments on a landsat multispectral remote sensing image are conducted.
multiscale watershed segmentation of multivalued images. in this paper, a new segmentation technique for multi-valued images is elaborated. the technique accesses multiscale edge information of a multivalued image by a concept, called multiscale fundamental form. at different scales, an edge map of the multivalued images is obtained, at which a watershed-based algorithm is applied. the multiscale behavior of the obtained watershed regions is employed to conduct a region merging procedure. in order to remove noise or local texture, prior to segmentation an anisotropic diffusion þlter is applied, also making use of the multiscale fundamental forms. in this way, the entire procedure is applied using multivalued processing.
using adapted levenshtein distance for on-line signature authentication. in this paper a new method for on-line signature authentication will be presented, which is based on a event-string modelling of features derived from pen-position and pressure signals of digitizer tablets. a distance measure well known from textual pattern recognition, the levenshtein distance, is used for comparison of signatures and classification is carried out applying a nearest neighbor classifier. results from a test set of 1376 signatures from 41 persons are presented, which have been conducted for four different feature sets. the results are rather encouraging, with correct identification rates of 96% at zero false classifications.
the epipolar geometry of the log-polar image plane. this paper presents an explicit formulation of the epipolar geometry of two oriented log-polar images.a method is derived for efficient pixel-by-pixel computation of epipolar lines in the log-polar plane, which are complicated non-linear functions.as an example, the method is applied for dense stereo matching: it is shown that it is more efficient to perform one-dimensional disparity estimation in the log-polar plane than to remap the images to cartesian coordinates.
off-line handwriting identification using hmm based recognizers. in this paper, an off-line, text independent system for writer identification using hidden markov model (hmm) based recognizers is described. for each writer we build an individual recognizer and train it on text lines written by that writer. a text line of unknown origin is presented to each of these recognizers. as a result we get, from each recognizer, a transcription including the log-likelihood score for the considered input. we rank all scores, and based on the assumption that the recognizer with the highest log-likelihood is the one that has been trained using text lines of this writer, we assign the text line to the writer whose score ranks first. we tested our system using over 2,200 text lines from 50 writers and have in 94.47% of all cases correctly identified the writer. using a simple confidence measure to define a rejection mechanism, we achieved an error rate of 0% by rejecting 15% of the results.
off-linewriter identification using gaussian mixture models. writer identification is the task of determining the author of a sample handwriting from a set of writers. in this paper, we propose gaussian mixture models (gmms) to address the task of off-line, text independent writer identification of text lines. the resulting system is compared to a system that uses a hidden markov model (hmm) based approach. while the gmm based system is conceptually much simpler and faster to train than the hmm based system, it achieves a significantly higher writer identification rate of 98.46% on a data set of 4,103 text lines coming from 100 writers.
performance evaluation metrics for motion detection and tracking. this paper introduces a methodology for evaluating the operational range of a video surveillance system in terms of robustness and reliability. we propose the generation of semi and full-synthetic video sequences under controlled variation of selected parameters. this data provides the necessary ground truth information for evaluating the motion detection and tracking systems. in addition, we propose several error metrics for quantitative evaluation.
a split & merge approach to metric-topological map-building. we present a novel split and merge based method for dividing a given metric map into distinct regions, thus effectively creating a topological map on top of a metric one. the initial metric map is obtained from range data that are converted to a geometric map consisting of linear approximations of the indoor environment. the splitting is done using an objective function that computes the quality of a region, based on criteria such as the average region width (to distinguish big rooms from corridors) and overall direction (which accounts for sharp bends). a regularization term is used in order to avoid the formation of very small regions, which may originate from missing or unreliable sensor data. experiments based on data acquired by a mobile robot equipped with sonar sensors are presented, which demonstrate the capabilities of the proposed method.
fast exact euclidean distance (feed) transformation. fast exact euclidean distance (feed) transformation is introduced, starting from the inverse of the distance transformation. the prohibitive computational cost of a naive implementation of traditional euclidean distance transformation, is tackled by three operations: restriction of both the number of object pixels and the number of background pixels taken in consideration and pre-computation of the euclidean distance. compared to the shih and liu 4-scan method the feed algorithm is often faster and is less memory consuming.
robust model driven matching method for face analysis with multi image photogrammetry. a vision based method to recover human faces from video sequences is presented. although video sequences acquired from multiple static synchronized ccd cameras have been used as a tool for 3-d reconstruction of the face before, the precision and reliability remain as concerning issues, which are addressed in this paper. moreover, the presented matching algorithm is invariant to scaling, rotation and insufficient calibration. a geometric primitive guides the matching approach through object space and therefore allows to compare gray values in an unique coordinate system.
recognizing human actions: a local svm approach. local space-time features capture local events in video and can be adapted to the size, the frequency and the velocity of moving patterns. in this paper we demonstrate how such features can be used for recognizing complex motion patterns. we construct video representations in terms of local space-time features and integrate such representations with svm classification schemes for recognition. for the purpose of evaluation we introduce a new video database containing 2391 sequences of six human actions performed by 25 people in four different scenarios. the presented results of action recognition justify the proposed method and demonstrate its advantage compared to other relative approaches for action recognition.
metric-based shape retrieval in large databases. this paper examines the problem of database organization and retrieval based on computing metric pairwise distances. a low-dimensional euclidean approximation of a high-dimensional metric space is not efficient, while search in a high-dimensional euclidean space suffers from the "curse of dimensionality". thus, techniques designed for searching metric spaces must be used. we evaluate several such existing exact metric-based indexing techniques, and show that they require extensive computational effort. this motivates the development of an approximate nearest neighbor search technique where the k nearest neighbors are used to approximate the local neighborhood of a point. the resulting k nn graph is searched in a best-first fashion producing excellent indexing efficiency.
emotion recognition based on joint visual and audio cues. recent technological advances have enabled human users to interact with computers in ways previously unimaginable. beyond the confines of the keyboard and mouse, new modalities for human-computer interaction such as voice, gesture, and force-feedback are emerging. however, one necessary ingredient for natural interaction is still missing - emotions. this paper describes the problem of bimodal emotion recognition and advocates the use of probabilistic graphical models when fusing the different modalities. we test our audio-visual emotion recognition approach on 38 subjects with 11 hci-related affect states. the experimental results show that the average person-dependent emotion recognition accuracy is greatly improved when both visual and audio information are used in classification.
skin detection: a bayesian network approach. the automated detection and tracking of humans in computer vision necessitates improved modeling of the human skin appearance. in this paper we propose a bayesian network approach for skin detection. we test several classifiers and propose a methodology for incorporating unlabeled data. we apply the semi-supervised approach to skin detection and we show that learning the structure of bayesian network classifiers enables learning good classifiers with a small labeled set and a large unlabeled set.
emotion recognition using a cauchy naive bayes classifier. recognizing human facial expression and emotion by computer is an interesting and challenging problem. in this paper we propose a method for recognizing emotions through facial expressions displayed in video sequences. we introduce the cauchy naive bayes classifier which uses the cauchy distribution as the model distribution and we provide a framework for choosing the best model distribution assumption. our person-dependent andperson-independent experiments show that the cauchy distribution assumption typically provides better results than the gaussian distribution assumption.
"firefly capturing method": motion capturing by monocular camera with large spherical aberration of lens and hough-transform-based image processing. we demonstrate a new motion capturing method that uses the monocular camera with large spherical aberration of lens to measure 3d positions of point light sources attached on an object in real time without any sequential lighting. point light sources are transformed into circle patterns by the large spherical aberration of lens mounted in the camera. the diameter and center position of circle pattern give the distance and direction to the light source, resulting in measuring its 3d position. circle patterns are extracted by video image processing based on hough transform even if they are overlapped each other. we tracked the circle patterns by predicting their next positions by kalman filter that includes the acceleration of movement. by combining these processing techniques we succeeded in demonstrating the motion capturing of several leds in real time, which is shown in 3d graphics.
proposal of recordable pointer: pointed position measurement by projecting interference concentric circle pattern with a pointing device. we propose a new pointing device that can measure pointed positions by processing the interference concentric circles projected with a pointing device. the pointing device has a donut-shaped lens that is designed so as both to make the laser source be two hypothetical sources for forming optical interference and to project the concentric circle pattern widely. two image sensors set on the projected side capture small parts of the concentric circles, and its center coordinate that is a pointed position of the pointing device is calculated from two normal lines to the arcs of the circles. in practice, we succeeded in measuring the pointed position accurately by real-time processing of the widely projected concentric circle patterns. we demonstrated mouse cursor operation on a large screen with the pointing device and also used it as real-object-based user interface to show the related information of real objects by pointing them.
improving appearance-based object recognition in cluttered backgrounds. appearance-based object recognition systems are currently the most successful approach for dealing with 3d recognition of arbitrary objects in the presence of clutter and occlusion. however, no current system seems directly scalable to human performance levels in this domain. in this report we describe a series of experiments on a previously described object recognition system that try to see which, if any, design axes of such systems hold the greatest potential for improving performance. we look at the potential effect of different design modifications and we conclude that the greatest leverage lies at the level of intermediate feature construction.
image analysis for core geological descriptions : strata and granulometry detection. digital signal processing is commonly used in geophysics. methods combining core sample physical property measurements with image analysis are beginning to emerge. in this paper, we describe a digital processing method applied directly to core sample images. our approach uses a number of time-frequency and scale-frequency transformations as well as morphological operators that reach a resolution equivalent to and even better than the geologist's eye. the resources presented below are free from operator-related subjectivity and provide efficient, reliable and repeatable sequential descriptions of geological borehole samples that include both layer detection and grain analysis. our process's efficiency is demonstrated through analyses carried out on a number of core samples taken from cretaceous to upper eocene volcano-sedimentary series on new caledonia's west coast.
blind audio watermark decoding using independent component analysis. this paper proposes an audio watermark extraction technique which adopts independent component analysis (ica) for blind watermark decoding. unlike the existing work, our method allows to combine data synchronization and watermark decoding into one optimization procedure, thus robust to transmission over different channels. watermark encoder is designed as a nonlinear data embedding machine which is compatible to mpeg layer1 model 1. it is shown that the proposed ica based watermark decoding scheme allows decoding watermark info accurately even though the watermark to signal ratio is less than -20 db. the method is robust to stereo-to-mono conversions and performs very well when the channel noise level is high.
a new affine invariant curve normalization technique using independent component analysis. a new affine invariant curve normalization method using independent component analysis (ica) is presented. first, principal component analysis (pca) is used for translation, scale and shear normalization. ica and the third order moments are then employed for rotation and reflection normalization. it is shown that all affine transformed versions of an object have a unique or canonical representation. experiments are conducted to asses the robustness of our approach. proposed normalization technique can be used as a pre-processing for object modelling and recognition.
efficient tracking in 6-dof based on the image-constancy assumption in 3-d. in this contribution maximum likelihood (ml) based approaches are presented which track an a-priori known surface and texture in monocular video streams. in contrast to established tracking algorithms based on homographies the surface is not modeled as planar or piecewise planar but as a collection of 3-d surface points and surface normals. thus, any free-form surface can be modeled. this paper introduces a novel description of the image jacobian in terms of a reference jacobian based on the image-constancy (ic) assumption in 3-d. tracking with this computationally efficient description is compared to the standard ml approach with respect to the region and speed of convergence.
probabilistic object tracking using multiple features. we present a generic tracker which can handle a variety of different objects. for this purpose, groups of low-level features like interest points, edges, homogeneous and textured regions, are combined on a flexible and opportunistic basis. they sufficiently characterize an object and allow robust tracking as they are complementary sources of information which describe both the shape and the appearance of an object. these low-level features are integrated into a particle filter framework as this has proven very successful for non-linear and non-gaussian estimation problems. in this paper we concentrate on rigid objects under affine transformations. results on real-world scenes demonstrate the performance of the proposed tracker.
differentiation of alphabets in handwritten texts. our aim is to differentiate between parts of handwritten text written using different alphabets. we achieve our goal thanks to a fractal analysis of handwriting style. for each alphabet, a set of characteristics is extracted. advantage is taken from the autosimilarity properties that are present in the handwriting. in order to do that, some invariant patterns characterizing the writing are statistically extracted. during the training step these invariant patterns appear while performing a fractal compression process, then they are organized in a reference base that can be associated with the alphabet. the alphabet identification is performed during a pattern matching process using the different reference bases successively. the results of this analyze are estimated through a correlation coefficient between the initial image of the text and a synthetic reconstruction of the text based on the references.
distance between 2d-scenes based on oriented matroid theory. in this paper a novel method for representing and comparing views of objects is presented. the topological properties of the regions of the views of objects are used to define a structure, called set of cocircuits, based on the oriented matroid theory. it is a formalism for qualitative spatial representation and reasoning and encodes information about relative position of the disjoint regions of the view and give local and global topological information about their spatial distribution. this topological technique is applied to recognising indoor scenes for the localization of a mobile robot.
vision-based robot positioning by an exact distance between hi. most vision-based robot positioning techniques rely on analytical formulations of the relationship between the robot pose and the projected image coordinates of several geometric features of the observed scene. this usually requires that several simple features such as points, lines or circles be visible in the image and be properly extracted. in this paper, we present a method to compare images (scenes that the robot has learned) based on a fast and exact distance between histograms. in contrast to the methods described before, our method is faster and with less storage space do to the images do not need to be segmented and only a lossless description of the histograms are stored in the data base.
orientation-improved minutiae for fingerprint matching. for minutiae-based fingerprint matching, alignment-based point pattern matching algorithm has been proposed to reduce the computational cost with a suitable criterion on ridge similarity. however, a large percentage of spurious pairs have rather similar ridges as well, which slows down the matching process and limits the matching accuracy. in this paper, orientation-based ridge patterns are utilized to improve the minutiae feature, which remove more spuriously matched pairs. in addition, to reduce errors caused by broken bifurcation, we propose a new scheme that compares two minutiae regardless their types. experiments conducted on a large fingerprint database (nist-4) show that the proposed method produces a much improved performance.
minutiae-based fingerprint matching using subset combination. in this paper, we propose an effective fingerprint matching algorithm based on ridge count matching and minutiae subset combination. in the algorithm, the orientation-based ridge patterns are first utilized to remove the spuriously matched minutiae pairs. then the reliable ridge counts between every two minutiae are estimated to improve the minutiae relationship, and finally the matched minutiae subsets corresponding to different alignments are selectively combined to reduce the influence caused by distortions in fingerprints. experimental results on nist-4 show that our method achieves a much better matching performance.
pixel-accurate representation and evaluation of page segmentation in document images. this paper presents a new representation and evaluation procedure of page segmentation algorithms and analyzes six widely-used layout analysis algorithms using the procedure. the method permits a detailed analysis of the behavior of page segmentation algorithms in terms of over- and undersegmentation at different layout levels, as well as determination of the geometric accuracy of the segmentation. the representation of document layouts relies on labeling each pixel according to its function in the overall segmentation, permitting pixel-accurate representation of layout information of arbitrary layouts and allowing background pixels to be classified as "don't care". our representations can be encoded easily in standard color image formats like png, permitting easy interchange of segmentation results and ground truth.
natural image correction by iterative projections to eigenspace constructed in normalized image space. image correction is discussed for realizing both effective object recognition and realistic image-based rendering. three image normalizations are compared in relation with the linear subspaces and eigenspaces, and we conclude that the normalization by l1-norm, which normalizes the total sum of intensities, is the best for our purposes. based on noise analysis in the normalized image space (nis), an image correction algorithm is constructed, which is accomplished by iterative projections along with corrections of an image to an eigenspace in nis. experimental results show that the proposed method works well for natural images which include various kinds of noise shadows, reflections and occlusions. the proposed method provides a feasible solution to the object recognition based on the illumination cone [2]. the technique can also be extended to face detection of unknown person and registration/recognition using eigenfaces.
review the strength of gabor features for face recognition from the angle of its robustness to mis-alignment. gabor feature has been widely recognized as better representation for face recognition in terms of rank-1 recognition rate. in this paper, we review the strength of gabor feature for face recognition from the new angle of its robustness to mis-alignment using a novel quantificational evaluation method combining both the alignment precision and the recognition accuracy. our experiments show that, compared with the gray-level intensity, gabor feature is much more robust to image variation caused by the imprecision of facial feature localization, which further support the feasibility of gabor representation.
face recognition robust to head pose from one sample image. most face recognition systems only work well under quite constrained environments. in particular, the illumination conditions, facial expressions and head pose must be tightly controlled for good recognition performance. in 2004, we proposed a new face recognition algorithm, adaptive principal component analysis (apca) [4], which performs well against both lighting variation and expression change. but like other eigenface-derived face recognition algorithms, apca only performs well with frontal face images. the work presented in this paper is an extension of our previous work to also accommodate variations in head pose. following the approach of cootes et al, we develop a face model and a rotation model which can be used to interpret facial features and synthesize realistic frontal face images when given a single novel face image. we use a viola-jones based face detector to detect the face in real-time and thus solve the initialization problem for our active appearance model search. experiments show that our approach can achieve good recognition rates on face images across a wide range of head poses. indeed recognition rates are improved by up to a factor of 5 compared to standard pca.
a riemannian weighted filter for edge-sensitive image smoothing. this paper describes a new method for image smoothing. we view the image features as residing on a differential manifold, and we work with a representation based on the exponential map for this manifold (i.e. the map from the manifold to a plane that preserves geodesic distances). on the exponential map we characterise the features using a riemannian weighted mean. we show how both gradient descent and newton's method can be used to find the mean. based on this weighted mean, we develop an edge-preserving filter that combines gaussian and median filters of gray-scale images. we demonstrate our algorithm both on direction fields from shape-from-shading and tensor-valued images.
ensemble of piecewise fda based on spatial histograms of local (gabor) binary patterns for face recognition. spatial histogram* of local binary pattern (lbp) and local gabor binary pattern (lgbp) has been successfully applied to face recognition and achieved state-of-the-art performance. both lbp and lgbp utilize traditional histogram matching method such as histogram intersection for face classification. in this paper, we propose a statistical extension for l(g)bp similarity computation by introducing fisher discriminant analysis (fda) of the l(g)bp spatial histogram "features". more than a simple application of fda, we have constructed ensemble of piecewise fda (epfda) classifiers, each of which is designed using one segment of the entire spatial histogram features. we show that this extension not only greatly reduces the feature dimension but also brings very impressive performance improvement. especially, we have made a large step to recognizing all the faces in the standard feret face database.
robust appearance-based tracking of moving object from moving platform. we present a robust algorithm for tracking moving objects from a moving platform. robustness is achieved by incorporating temporal differencing and shape detection in an appearance-based object tracking algorithm. in addition, the incorporation of these two methods also improves accuracy and computational efficiency of detection. some experimental results using airborne-video tracking are given to illustrate the effectiveness of this method.
multinational license plate recognition system: segmentation and classification. image-based car license plate recognition (clpr) systems provide an inexpensive automatic solution for remote vehicle identification. localization stage of the clpr yields a gray-scale plate clip with printed characters. this paper describes the method of plate clip segmentation into isolated characters, feature extraction and classification. the method is independent on character size, thickness, illumination and is capable of handling plates from various countries. the method uses extensively the gray-scale information and is robust to breaks in character connectivity. it is tolerant to character deformations, such as shear and skew. promising results have been obtained on israeli and bulgarian plates.
an iterative algorithm for segmentation of isolated handwritten words in gurmukhi script. segmentation of handwritten text in gurmukhi script is an uphill task primarily because of the structural features of the script and varied writing styles. the presence of a horizontal line connecting characters of a word (i.e. head line), half characters and overlapping of some vowel between middle and lower zone of a word make the task even more difficult. handwritten text is also prone to the problem of overlapped, connected and merged characters with in a word. structural features are helpful in segmentation of machine printed text but these are of little help for segmentation of handwritten words. the proposed technique segments the words in an iterative manner by focusing on presence of headline, aspect ratio of characters and vertical and horizontal projection profiles. the proposed approach of segmentation can be used for handwritten text of indian language scripts like devnagri, bangla etc. having structural feature similar to gurmukhi script.
manifold pursuit: a new approach to appearance based recognition. manifold pursuit (mp) extends principal component analysis to be invariant to a desired group of image-plane transformations of an ensemble of un-aligned images.we derive a simple technique for projecting a misaligned target image onto the linear subspace defined by the superpositions of a collection of model images. we show that it is possible to generate a fixed projection matrix which would separate the projected image into the aligned projected target and a residual image which accounts for the misalignment. an iterative procedure is then introduced for eliminating the residual image and leaving the correctaligned projected target image.taken together, we demonstrate a simple and effective technique for obtaining invariance to image-plane transformations within a linear dimensionality reduction approach.
gabor wavelets and kernel direct discriminant analysis for face recognition. a novel gabor-kernel face recognition method is proposed in this paper. this involves convolving a face image with a series of gabor wavelets at different scales, locations, and orientations and extracting features from resulting gabor filtered images. kernel discriminant analysis (kdda) is then applied to the feature vectors for dimension reduction as well as class separability enhancement. a database of 600 frontal-view face images from the feret face database is used to test the method. experimental results demonstrate the advantage of kdda over other kernel methods such as kernel principal component analysis (kpca) and general discriminant analysis (gda). significant improvements are also observed when features are extracted from gabor filtered images instead of the original images. a 94% accuracy has been observed for the novel gabor + kdda method on the feret database using a simple classifier, which could be further improved by employing a more complex classifier and distance measurer.
finding text in natural scenes by figure-ground segmentation. much past research on finding text in natural scenes uses bottom-up grouping processes to detect candidate text features as a first processing step. while such grouping procedures are a fast and efficient way of extracting the parts of an image that are most likely to contain text, they still suffer from large amounts of false positives that must be pruned out before they can be read by ocr. we argue that a natural framework for pruning out false positive text features is figure-ground segmentation. this process is implemented using a graphical model (i.e. mrf) in which each candidate text feature is represented by a node. since each node has only two possible states (figure and ground), and since the connectivity of the graphical model is sparse, we can perform rapid inference on the graph using belief propagation. we show promising results on a variety of urban and indoor scene images containing signs, demonstrating the feasibility of the approach.
video completion for perspective camera under constrained motion. this paper presents a novel technique to fill in missing background and moving foreground of a video captured by a static or moving camera. different from previous efforts which are typically based on processing in the 3d data volume, we slice the volume along the motion manifold of the moving object, and therefore reduce the search space from 3d to 2d, while still preserve the spatial and temporal coherence. in addition to the computational efficiency, based on geometric video analysis, the proposed approach is also able to handle real videos under perspective distortion, as well as common camera motions, such as panning, tilting, and zooming. the experimental results demonstrate that our algorithm performs comparably to 3d search based methods, and however extends the current state-of-the-art repairing techniques to videos with projective effects, as well as illumination changes.
an undecimated wavelet transform based denoising, ppca based pulse modeling and detection-classification of pd signals. authors address the problem of recognition and retrieval of relatively weak industrial signal such as partial discharges (pd) buried in excessive noise. the major bottleneck being the recognition and suppression of stochastic pulsive interference (pi) which has similar frequency characteristics as pd pulse. also, the occurrence of pi is random like pd pulses. in this paper we provide techniques to de-noise, detect, estimate and classify the pd signal in a statistical perspective. to avoid aliasing due to interference of high frequency noise, pd signals are generally digitized in much higher sampling rates (in terms of tens of mhz), than actually required. a multi-resolution analysis based technique is incorporated to discard the huge amount of redundant data in acquired signal. a scale dependent mmse based estimator is implemented in undecimated wavelet transform (udwt) domain to enhance the noisy signal, due to its inherent advantages offered in the analysis of pd signal. the probability density function of the enhanced signal is derived using probabilistic principal component analysis (ppca) in which pd/pi pulses are modeled as mean of the distribution. the parameters of the pulses are estimated using maximum aposteriroi probability (map) based technique. a statistical test known as generalized log likelihood ratio test (glrt) was incorporated to ensure the existence of the pulse. the decision as to whether a pulse is a noise or a desired signal has been made based on a weighted-nearest neighbor methodology.
improvements of volume computation from non-parallel cross-sections. we describe an algorithm for volume evaluation of a 3d object from area measurements done in non-parallel cross-sections. the algorithm is based on watanabe formula for volume computation and uses an interpolation by cubic splines. the same splines are applied also for computation of object area and centroid in every cross-section. it allowed us to derive an explicit formula for volume computation and to extend the algorithm described in [fast surface and volume estimation from non-parallel cross-sections for freehand 3-d ultrasound].
historical document image enhancement using background light intensity normalization. this paper presents a new background light intensity normalization algorithm suitable for historical document images. the algorithm uses an adaptive linear function to approximate the uneven background due to the uneven surface of the document paper, aged color and light source of the cameras for image lifting. our algorithm adaptively captures the background with a "best fit" linear function and normalized with respect to the approximation. the technique works for both gray scale and color images with significant improvement in readability.
fingerprint image enhancement based on skin profile approximation. the performance of the fingerprint identification and verification systems relies heavily on the quality of the input fingerprint images. in this paper, we propose an effective image enhancement algorithm especially suitable for low quality fingerprint images, which can improve the clarity and continuity of the ridge structures. unclean sensor plates, non-uniform and inconsistent contacts are among the major causes for poor samples and feature extraction artifacts during image processing. the proposed algorithm estimates the finger elasticity by approximating the uneven finger skin due to poor skin condition or imperfect acquisitions. then the fingerprint image is normalized with respect to the approximation. experimental results show that the enhanced image quality by using the proposed normalization algorithm is effective and much better than other existing methods for improving the minutiae detection.
critical vector learning to construct rbf classifiers. sensitivity is initially investigated for the construction of a network prior to its design. sensitivity analysis applied to network pruning seems particularly useful and valuable when network training involves a large amount of redundant data. this paper proposes a novel learning algorithm for the construction of radial basis function (rbf) classifiers using sensitive vectors (senv), to which the output is the most sensitive. in training, the number of hidden neurons and the centers of their radial basis functions are determined by the maximization of the output's sensitivity to the training data. in classification, the minimal number of such hidden neurons with the maximal sensitivity will be the most generalizable to unknown data. our experimental results suggests that our proposed methodology outperforms classical rbf classifiers constructed by clustering.
automatic grading prototype system for kanji dictation test. this paper presents an automatic grading prototype system developed as recognition engine for japanese kanji dictation test which aims to certificate the reading and writing ability of kanji characters. the system is designed to replace the conventional human-grading process. different from general handwritten character recognition systems which allow to read incorrect (misspelled) characters, the grading system is required to discriminate miswritten characters more strictly from correct ones. this paper introduces the core processing stages of the system. focused on the relationship between "error of judgement" and "rejection",several discrimination methods based on the character classification approach and the likelihood approach are comparatively evaluated. a grading accuracy of error rate less than 0.5% with rejection rate less than 50% is achieved in the performance evaluation test.
self-localization of a mobile robot using compressed image data of average and standard deviation. in this paper, an image-based self-localization method is proposed for a mobile robot. images are compressed for each column, and the average and standard deviation of the pixels in each column are used. environmental and observational data, which are the compressed image data at the registration and observational stages, are matched, and the position of the robot is obtained. the entire environment can be represented continuously with a small amount of data. a simple and robust matching method based on a voting process is introduced. the methods are evaluated through several experiments with omnidirectional images.
an error bound of relative image blur analysis. a lower bound of the relative image blur estimation error of a pair of images is derived analytically in this paper. this error analysis result shows that the optimal camera parameters for obtaining the most accurate depth from defocusing (dfd) results are strongly related to the object depth. therefore, dfd methods using only two images usually cannot achieve the most accurate depth estimates. instead of using only two images, a sequence of images focused at different depths should be provided in order to obtain accurate dfd results. with some prior knowledge of the object depth, the derived error bound is used to select optimal image pairs from the input image sequence for computing dfd. real experimental results show that the resulting dfd method outperforms both a dff method and a dfd method using two images.
a bi-directional visual stereo interface for accessing stereo matching results from a human brain. in this paper, a novel interface, termed bvsi, allowing people to input stereo correspondences more efficiently is proposed. the bvsi consists of a stereo display for providing a stereo view of a 3-d scene and a binocular gaze tracker for recording the binocular fixation points of an operator. a calibration method of the bvsi is presented in this paper. the horizontal gaze tracking error of the calibrated bvsi is about ± 10 pixels. real experiments have been conducted and the results showed that the proposed system is very promising.
face detection using discriminating feature analysis and support vector machine in video. this paper presents a novel face detection method in video by using discriminating feature analysis (dfa) and support vector machine (svm). our method first incorporates temporal and skin color information to locate the field of interests. then the face class is modelled using a small training set and the nonface class is defined by choosing nonface images that lie close to the face class. finally, the svm classifier together with bayesian statistical analysis procedure applies the efficient features defined by dfa for face and nonface classification. experiments using both still images and video streams show the feasibility of our new face detection method. in particular, when using 92 images (containing 282 faces) from the mit-cmu test sets, our method achieves 98.2% correct face detection accuracy with 2 false detections. when using video streams, our method detects faces reliably with computational efficiency of more than 20 frames per second.
simultaneous optimization of class configuration and feature space for object recognition. a new algorithm for object classification based on an extension of the fisher's discriminant analysis is presented. object recognition algorithms using the standard fisher's algorithm, such as the fisherface, train the classifier using sample-class pairs, where, for the classes, object categories determined in the application systems are used directly. in contrast, the new algorithm automatically produces sub-classes, within each predetermined category, that are actually used for classification, via unsupervised learning. in order to perform this, we combine the fisher's discriminant analysis with the akaike information criterion, optimizing the class configuration, i.e. sample-subclass correspondences, and the feature extraction function simultaneously, thereby improving the potential of linear separability. by applying this new method to face recognition, we show how it outperforms the traditional fisher-based method.
constituting origami models from sketches. this paper proposes an approach to constituting craese patterns, the unfolded origami models, by using skeletons obtained from 2-d images such as handwriting sketches. firstly, we describe a method for constructing a data structure which represents all the parts of an origami model and their relationships based on an extracted skeleton, and then give an algorithm for constituting a crease pattern using this data structure. to show the validity of proposed method and algorithm, we finally demonstrate how a crease pattern is generated and how a origami model is actually realized using some real illustrations taken from a origami drill book.
analysis of overlapping faces for constructing paper-made objects from sketches. this paper describes an approach to constructing a 3- d paper-made object from hand-written sketches. this approach consists of two phases. one is the phase that constitutes a crease pattern based on a sketch. another is the phase that constructs a virtual origami model from the obtained crease pattern. the crease pattern is a set of line segments in an unfolded sheet of paper and often designed by origami design methods. when an origami model is folded from a crease pattern, faces in the crease pattern may be transformed into the same plane and some inconsistent objects may be represented. in order to construct feasible (fold-able) objects, we need to dispose the faces on the same plane consistently. therefore, in this paper, a method for analyzing overlap order of faces based on simulated annealing is proposed. furthermore, we show some examples of 3-d objects constructed by our method. the proposed method is useful for packaging and architectural modeling.
estimation of ball route under overlapping with players and lines in soccer video image sequence. this paper deals with the analysis of broadcast soccer video. to recognize interesting events such as a goal, estimation of ball movements is necessary. it is, however, sometimes difficult to detect a ball by a simple color and shapebased method when it overlaps with players and lines. we therefore develop a method of estimating a ball route during such overlaps by considering spatio-temporal relationships between players, lines, and the ball. the method can deal with difficult cases such as the one where a ball disappears at a player and re-appears from another player. experimental results show the effectiveness of the method.
super-resolution under image deformation. this paper proposes a new method to obtain precise projective parameters of image deformation simultaneously with non-iterative calculation by extending area-based matching and sub-pixel estimation. the method requires no "a priori" knowledge of images at all. the proposed method is based on a practical similarity model in 8-dparameter space. using similarity measures obtained at discrete positions in the parameter space, our method provides a highly accurate maximum position of similarity in sub-sampling resolution; that position corresponds to image deformation parameters. the estimated parameters can be used for direct multi-image super-resolution, which can directly reconstruct a high-resolution full-color image from a set of low-resolution bayer cfa images. experiments on the super-resolution processing were performed using real image sequences to verify the proposed method.
moving object detection with mobile stereo omni-directional system (sos) based on motion compensatory inter-frame depth subtraction. moving object detection with a mobile image sensor is an important task when considering mobile robots for use in human environments. in this paper, we propose a novel method for effectively solving the problem of detecting moving objects for mobile robots by using the stereo omni-directional system (sos) which has a complete spherical fov. we first predict the depth image for the present time from the self-motion of the sos and the depth image obtained at the previous time, and then detect the moving objects by comparing the predicted depth image with the actual one obtained at the present time. experiments in the real world show the effectiveness of the proposed method.
efficient search and verification for function based classification from real range images. in this work we propose a probabilistic model for generic object classification from raw range images. our approach supports a validation process in which classes are verified using a functional class graph in which functional parts and their realization hypotheses are explored. the validation tree is efficiently searched. some functional requirements are validated in a final procedure for more efficient separation of objects from non-objects. the search employs a knowledge repository mechanism that monotonically adds knowledge during the search and speeds up the classification process. finally, we describe our implementation and present results of experiments on a database that comprises about one-hundred-and-fifty real raw range images of object instances from ten classes.
triangular mesh generation of octrees of non-convex 3d objects. a general surface-generating algorithm, the marching cube, produces triangular meshes from octants where the vertices of octants are clearly classified into either inside or outside the object. however, the algorithm is ambiguous for octrees corresponding to nonconvex objects generated using a shape from silhouette technique. this paper presents a methodology which involves delaunay triangulation to generate surface meshes for such octrees. since the general 3d delaunay triangulation creates 3d convex hull which consists of tetrahedron meshes, we propose a method which applies the delaunay algorithm locally in order to deal with non-convex objects. the proposed method first slices an octree and detects the clusters in each slice. all clusters between adjacent slices are linked based on a 3d probability density cube. the delaunay algorithm is then applied to locally-linked clusters. finally the accumulation of triangular meshes forms a final non-convex surface mesh.
correction of intensity of a color image using a range intensity image. this paper proposes a method of correcting intensity of a color image, which is used for the texture of a 3d model, using a range intensity image. a range intensity image has an effective characteristic that it is obtained under controlled illumination. this enables correction of the intensity of the color image without estimating illumination for the color image. experiments show the effectiveness of the proposed method and a 3d model with proper color information generated by the method.
an efficient text capture method for moving robots using dct feature and text tracking. when a moving robot tries to find text in the surrounding scene by an onboard video camera, the same text strings appear in many image frames. since it is a waste of time to recognize the same text strings repeatedly, it is necessary to decrease text candidate regions for recognition. this paper presents a text capture system that can look around the environment by an active camera, reducing the number of text strings to be recognized. the text candidate regions are extracted from the images by an improved dct feature. the text regions are tracked in a video sequence to reduce the text candidate strings. in experiments, we tested 55 images of corridor with seven text strings. the text candidate regions are reduced by 86.8% by our method.
multi-biometrics fusion for identity verification. in this paper, we accomplish matching score level fusion of multi-biometrics. in order to solve the incomparability among different classifiers' outputs, adaptive confidence transform (act) is introduced to convert the raw outputs of different classifiers to the estimates of posteriori probabilities conforming to different users. these posteriori probabilities are then combined using several fusion methods. experiments conducted on a database (including face, iris, online signature and offline signature traits) of about 100 users indicate that for the same fusion method, act based normalization generally results in better verification performance and is more robust compared to other normalization methods. effects of different normalization and fusion methods on combination of "strong" and "weak" classifiers are also examined.
moving shadow detection with support vector domain description in the color ratios space. moving shadow detection is a fundamental step in video-surveillance applications since it is generally confused with foreground. in this paper, we propose a novel statistical non-parametric method to detect moving shadow in a road traffic image sequences. we consider a diagonal model to describe the shadow distortion in the rgb color space. a support vector domain description (svdd) algorithm is applied in the color ratios space in order to discriminate shaded pixels from foreground.
real-time multi-frame analysis of dominant translation. this paper describes an ultratfast method ,for estimation of translational motion in video sequences. the method is based on the princkle that 2 0 image translation results in translation of imageprojections. to obtain superior robustness and accuracy we developed a multitfranie e-xtension, which robustly integrates motion information over time. our methodgives reliable results even when video images are blurred by significant and rapid motion and in the presence of independent local motions. the estimation process is very fast: on a standard desktop computer without using any hardwareor assembler-based optimization it works at a rate of 1400 fps (vga frame size), exceeding real-time requirements and is typically 500 times faster than some prior-art approaches, including 2 0 phase correlation. our method also provides a ve ry compact description of a video,frame, applicable to motion analysis and other video processing tasks in low-cost dsp systems.
real time limb tracking with adaptive model selection. we describe an efficient and robust method of tracking human forearms as skin colored regions. of special consideration in the design of this system are real-time and robustness issues. we approach this as 2d tracking problem using skin color and edge information. multiple 2d limb models are used to enhance tracking of the underlying 3d structure. this includes models for lateral forearm views (waving) as well as for pointing gestures. experiments on test sequences demonstrate the efficacy of this approach.
detecting human motion with support vector machines. this paper presents a method for detection of humans in video sequences. the intended application of the method is outdoor surveillance. in such an uncontrolled environment, the appearance of humans varies hugely due to clothing, identity, weather and amount and direction of light. the idea is therefore to detect patterns of human motion, which to a large extent is independent of the differences in appearance. to this end, a support vector machine is trained with dense optical flow patterns originating from humans. the subjects are moving in different angles to the camera plane, on different image scales. this trained svm is the core of a human detection algorithm which searches optical flow images for human-like motion patterns.
improvement of histogram-based image retrieval and classification. histogram-based techniques are commonly used in image retrieval ranging from basic color histograms to sophisticated histograms of various local feature vectors. our approach considers multidimensional histograms of locally invariant features. in order to get rid of the discontinuous behavior of traditional histograms we develop a fuzzy histogram which does no sharp assignment of a feature vector to one bin only but performs a weighted assignment to allneighboring bins. this improvement is not restricted to the kind of feature histograms considered here but could generally improve histogram-based retrieval or classification techniques.
a multi-agent based interactive system towards child's emotion performances quantified through affective body gestures. studies in cognitive science have found that interactive robots, interactive games, etc., may help the emotional development of children with mental-health problems (e.g. autistic children). it is very important with these children to show empathic behaviors and to take into account their emotion when relating to them. current technology cannot do this because it cannot recognize the emotion of the children. few studies are directed toward this goal by categorizing affective behavior of the child into a set of discrete categories. but still two problems exist: gesture is not yet a concern as channel of affective communication in interactive technology, and existing systems only model discrete categories, but not affective dimensions, e.g., intensity. in this work, we propose a multi-agent based interactive system that can quantify child's performance (emotion with intensity of emotion) in real time.
optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning. in this article we describe a feature extraction algorithm for pattern classification based on bayesian decision boundaries and pruning techniques. the proposed method is capable of optimizing mlp neural classifiers by retaining those neurons in the hidden layer that reallycontribute to correct classification. also in this article we proposed a method which defines a plausible number of neurons in the hidden layer based on the stem-and-ieaf graphics of training samples. experimentai investigation reveals the efficiency of the proposed method.
locating characters in scene images using frequency features. this paper presents a {language-independent) method of locating rectangular text regions in natural scene images. the method consists in two steps that can be applied in succession or independently: the frequency of edge pixels across vertical and horizontal scan lines, and thefundamental frequency in the fourier domain. the frequency feature of text images is highly intuitive, and thus appealing as much. this is the focus of the research. also addressed is the detection of rectangles using rough transform. since texts that is meaningful to many viewersusually appear in rectangles of colours of high contrast to the background. hence it is natural to assume the detection rectangles may be helpful for locating desired texts correctly in natural outdoor scene images.
robust klt tracking with gaussian and laplacian of gaussian weighting functions. object tracking algorithms extensively found in literature are either constrained with assumptions or are overly sensitive to noise. we propose and successfully test two new weighting functions for a feature-based object tracker to achieve superior tracking performance and noise immunity. also presented is a mechanism for image based optimal weighting function determination.
colour image texture analysis: dependence on colour spaces. in this paper we investigate the role of colour spaces on texture analysis. we extract a range of correlogram and colour moment features for the vistex colour texture benchmark in different colour spaces and find the average probabilistic distance of separation across different objects for different features and suggest the colour spaces that are best suited for the classification process. we also show the results of knn classification for different features and their combined set.
background learning for robust face recognition. in this paper, we propose a robust face recognition technique based on the principle of eigenfaces. the traditional eigenface recognition (efr) method works quite well when the input test patterns are cropped faces. however, when confronted with recognizing faces embedded in arbitrary backgrounds, the efr method fails to discriminate effectively between faces and background patterns, giving rise to many false alarms. in order to improve robustness in the presence of background, we argue in favor of learning the distribution of background patterns. a background space is constructed from the background patterns and this space together with the face space is used for recognizing faces. the proposed method outperforms the traditional efr technique and gives very good results even on complicatedscenes.
spatial texture analysis: a comparative study. in this paper we compare some of the traditional, and some fairly new techniques of texture analysis on the meastex and vistex benchmarks to illustrate their relative abilities. the methods considered include autocorrelation (acf), co-occurrence matrices (cm), edge frequency (ef), law's masks (lm), run length (rl), binary stack method (bsm), texture operators (to ), and texture spectrum (ts). in addition, we illustrate the advantage of using feature selection on a combined set that improves the overall recognition performance.
a comparison of image enhancement techniques for explosive detection. the enhancement of images plays a crucial role in the detection of illicit objects from airport luggage. on the basis of 11 statistical measures of image viewability, we compare both new and old methods of image enhancement for aviation security application. our research shows that some of the newer methods of enhancement consistently outperform most others that are regularly used at airports on measures of viewability, which supports our argument that airport security consoles must be updated with our suggested enhancement techniques.
feature selection for face recognition based on data partitioning. feature selection is an important consideration in several applications where one needs to choose a smaller subset of features from a complete set of raw measurements such that the improved subset generates as good or better classification performance compared to original data. in this paper, we describe a novel feature selection approach that is based on the estimation of classification complexity though data partitioning. this approach allows us to select the n best features from a given set in order of their ability to separate data from different classes. in this paper, we perform our experiments on the orlface database thatconsists of 400 images. the results show that the proposed approach outperforms the probability distance approach and is a viable method for implementing more advanced search methods of feature selection.
synchronization and calibration of camera networks from silhouettes. we propose an automatic approach to synchronize a network of uncalibrated and unsynchronized video cameras, and recover the complete calibration of all these cameras. in this paper, we extend recent work on computing the epipolar geometry from dynamic silhouettes, to deal with unsynchronized sequences and find the temporal offset between them. this is used to compute the fundamental matrices and the temporal offsets between many view-pairs in the network. knowing the time-shifts between enough view-pairs allows us to robustly synchronize the whole network. the calibration of all the cameras is recovered from these fundamental matrices. the dynamic shape of the object can then be recovered using a visual-hull algorithm. our method is especially useful for multi-camera shape-from-silhouette systems, as visual hulls can now be reconstructed without the need for a specific calibration session.
fast color image quantization using squared euclidean distance of adjacent color points along the highest color variance axis. a new color image quantization algorithm that uses the squared euclidean distance of adjacent color points along the highest color variance axis is proposed. this algorithm is a hierarchically divisive colormap design technique. colors are sorted along the axis with the highest variance of color distribution. the squared euclidean distances between any adjacent colors' along the axis are then used to find the cutting plane that divides a color cell into two subcells with approximately equal quantization errors respect to their centroids. the proposed algorithm is effective and yields a short execution time.
recognizing expressions in a new database containing played and natural expressions. we describe a new expression database which contains video sequences of both played and natural expressions and an expression classification system based on warped optical flow fields and texture features. we analyze the system's generalization performance when confronted with subjects that were not present in the training set and its recognition performance when tested on natural expressions. we evaluate several techniques for combining the classifier outputs computed on single images to perform classification of a temporal sequence of expression images.
evaluation of nine similarity measures used in rigid registration. because image registration is carried out by optimising a criterion function or similarity measure, the behaviour of a similarity measure greatly influences the final result of registration. in this paper we describe a protocol to quantitatively evaluate the behaviour of similarity measures. registered mr/ct images of the spine and mr/mr brain images were used to evaluate nine similarity measures. besides, the effects of binning and noise on the similarity measures were studied. the normalised and non-normalised mutual information were the two measures that performed the best.
defuzzification of discrete objects by optimizing area and perimeter similarity. we present a defuzzification method which produces a crisp digital object starting from a fuzzy digital one, while keeping selected properties of them as similar as possible. our main focus is on defuzzification based on the invariance of perimeter and area measures while taking into account with the membership values. we perform a similarity optimization procedure using on a region growing approach to obtain a crisp object with the desired properties.
ranklets: orientation selective non-parametric features applied to face detection. we introduce a family of multiscale, orientation-selective, non-parametric features ("ranklets") modelled on haar wavelets. we clarify their relation to the wilcoxon rank-sum test and the rank transfor and provide an efficient scheme for computation based on the mann-whitney statistics. finally, we show that ranklets outperform other rank features, haar wavelets, snow and linear svms (based on independently published results) in face detection experiments over the 24'045 test images in the mit-cbcl database.
estimating cast shadows using sfs and class-based surface completion. this paper describes a method for cast shadow removal from obliquely illuminated images of faces. the method draws on a statistical model of surface normal directions. the model is fitted to shadowed facial images using robust statistics and constraints provided by shape-from-shading. regions associated with poor fit residuals are associated with shadow regions. we illustrate the method on the yale b database where it gives both good shadow map estimates and fills-in the facial surface in the shadow regions.
face recognition using angular lda and svm ensembles. one successful approach to feature extraction in face recognition problems is that of linear discriminant analysis (lda). we examine an extension of this technique, called angular lda, in which a non-linear transformation is applied after the lda representation has been determined. we present experimental evidence, using the xm2vts face database, that an ensemble of svm classifiers operating in the angular lda space is capable of making more accurate face verification and identification decisions than the same classifiers operating in the standard lda space. we also compare experimentally the relative effectiveness of a number of techniques for ensemble design, ensemble decoding metric and svm calibration algorithm.
measurement function design for visual tracking applications. extracting human postural information from video sequences has proved a difficult research question. the most successful approaches to date have been based on particle filtering, whereby the underlying probability distribution is approximated by a set of particles. the shape of the underlying observational probability distribution plays a significant role in determining the success, both accuracy and efficiency, of any visual tracker. in this paper we compare approaches used by other authors and present a cost path approach which is commonly used in image segmentation problems, however is currently not widely used in tracking applications.
skin reflectance modelling for face recognition. we present a parameter-free method for estimating the brdf of a subject's skin from a single image. we show how the technique can be used for photometric correction as a preprocessing step for face analysis tasks, and show its application to graphics by re-rendering faces with different skin reflectance models.
on the fast modification of the vector median filter. a new filtering approach designed to eliminate impulsive noise in color images, while preserving fine image details is presented in this paper. the comparison shows that the newfilter outperforms the vmf, as well as other standard procedures used in color image processing for the elimination of impulsive noise.
watershed lines suppression by waterfall marker improvement and line-neighbourhood analysis. in this paper we present a new self-sufficient image segmentation method based on watershed-lines neighbourhood. this work-study uses two morphological concepts, watershed and waterfall, for the development of a line-based catalogue concerning neighbourhood analysis. innovation in waterfall hierarchical evolution is achieved with a marker-constraint implementation along the process, improving detail suppression. watershed lines are than separated into multiple semi-lines for a further line suppression by semi-lines neighbourhood analysis. in many cases, unless a feature has a high thinness, different from image background (i.e., a thin road, in which case can be defined by a single watershed line), its representation is a set of watershed-connected lines that makes ambiguous feature-line detection for recognition of image structures. applying watershed to the morphological gradient image, feature contouring is better characterized or waterfall application.
inter-stage feature propagation in cascade building with adaboost. a modification of the cascaded detector with the ada-boost trained stage classifiers is proposed and brought to bear on the face detection problem. the cascaded detector is a sequential classifier with the ability of early rejection of easy samples. each decision in the sequence is made by a separately trained classifier, a stage classifier. in proposed modification the features from one stage of training are propagated to the next stage classifier. the proposed intra-stage feature propagation is shown to be greedily optimal, does not increase computational complexity of the stage classifier and leads to shorter stage classifiers and accordingly to faster detectors. a cascaded face detector is built with the intra-stage feature propagation and is compared with the viola and jones approach. the same detection and false positive rates are achieved with a detector that is 25% faster and consists of only two thirds of the weak classifiers needed for a cascade trained by the viola and jones approach. the latter property facilitates hardware implementation, the former opens scope for the increase in the search space, e.g. the range of scales at which faces are sought.
a comparative analysis of face recognition performance with visible and thermal infrared imagery. we present a comprehensive performance analysis of multiple appearance-based face recognition methodologies, on visible and thermal infrared imagery. we compare algorithms within and between modalities in terms of recognition performance, false alarm rates and requirements to achieve specified performance levels. the effect of illumination conditions on recognition performance is emphasized, as it underlines the relative advantage of radiometrically calibrated thermal imagery for face recognition.
thermal face recognition over time. we present a comparative study of face recognition performance with visible and thermal infrared imagery, emphasizing the influence of time-lapse between enrollment and testing images. most previous research in this area, with few exceptions, focused on results obtained when enrollment and testing images were acquired in the same session. we show that the performance difference between visible and thermal recognition in a time-lapse scenario is smaller than previously believed, and in fact is not statistically significant on existing data sets.
fuzzy direction field method for fringe and tree-like patterns analysis. the problem of geometrical structure detection and measurements for fringe patterns and tree-like objects images is considered. we introduce the notion of a local-structure function that generalizes the concepts of direction and spatial frequency fields and describes local geometrical properties of the images under study. it can be considered as a fuzzy set of directions and spatial frequencies in every point of image. on basis of fuzzy sets operations we develop a number of general-purpose image analyzing algorithms that have parametrical tuning on image type. we have shown experimentally that this approach allows us to analyze efficiently various technical and medical diagnostic images of specified classes, such as interference patterns, objects registered in structural light, blood vessels images, and so on.
geodesic curves for analysis of continuous implicit shapes. a method is proposed for performing shape analysis of m-surfaces, e.g. planar curves and surfaces, with a geometric interpretation. the analysis uses an implicit surface representation and connects the popular level set approach with shape analysis. the representation is continuous and completely landmark-free. shapes are represented as points on an infinite-dimensional manifold and the distance between two surfaces is given by the length of a path on this manifold. the analysis is valid in any dimension and examples of applications such as interpolation and clustering are given.
geodesic curves for analysis of continuous implicit shapes. a method is proposed for performing shape analysis of m-surfaces, e.g. planar curves and surfaces, with a geometric interpretation. the analysis uses an implicit surface representation and connects the popular level set approach with shape analysis. the representation is continuous and completely landmark-free. shapes are represented as points on an infinite-dimensional manifold and the distance between two surfaces is given by the length of a path on this manifold. the analysis is valid in any dimension and examples of applications such as interpolation and clustering are given.
estimating surface shape and extending known structure using specular reflections . in this paper a method for shape estimation and structure extension of a surface using information from specularities is proposed. the structure of the scene is obtained from an image sequence using standard structure and motion techniques. if there are specularities in the scene, there may be parts where the scene geometry can not be determined. the method proposed in this paper extends the known structure over these regions. methods for determining the light source position are introduced and together with the reflections, this gives constraints on the surface normals. these constraints are complemented by a smoothness condition in order to estimate the surface shape unambiguously. the viability of the proposed method is demonstrated in experiments with real data from image sequences.
initialization techniques for segmentation with the chan-vese model. this paper introduces an effective initialization approach for segmentation using the chan-vese model. the initial curve is found by searching among the extremals of the fidelity term, as a form of intelligent thresholding where the regularity of the threshold level is incorporated. the method has a nice connection to the curvature of the optimal initial partition boundary. the method is tested on several examples and gives considerable increase in performance.
dynamic foveation model for video compression. there are some techniques of video compression based on the foveation image coding and processing algorithms. one of the most frequently asked questions is: "how do we know the foveation points?" in this paper a computational model of automatic localization of the foveation point is proposed. till now, except for a few cases, the research related to foveation points determination has mainly concerned with the analysis of static images. the proposed model, on the contrary, simulates the gaze shifting of a human observer when the scene in development is dynamic. through the selective attention the most relevant part of an image is selected, the so called "focus of attention" (foa).
edge color distribution transform: an efficient tool for objectdetection in images. object detection in images is a fundamental task in many image analysis applications. existing methods for low-level object detection always perform the color-similarity analyses in the 2d image space. however, the crowded edges of different objects make the detection complex and error-prone. this paper proposes to detect objects in a new edge color distribution space (ecds) rather than in the image space. in the 3d ecds, the edges of different objects are segregated and the spatial relation of a same object is kept as well, which make the object detection easier and less error-prone. since uniform-color objects and textured objects have different distribution characteristics in ecds, this paper gives a 3d edge-tracking algorithm for the former and a cuboid-growing algorithm for the latter. the detection results are correct and noise-free, so they are suitable for the high-level object detection. the experimental results on a synthetic image and a real-life image are included.
a new approach for line recognition in large-size images using hough transform. the application of hough transform (ht) has been limited to small-size images for a long time. for large-size images, the peak detection and the line verification become much more time-consuming. many ht-based line detection methods are not able to detect line width. thispaper proposes a new approach for detecting line segments using ht, which makes ht applicable to large-size images, especially for those applications whose line width is critical. our approach applies a boundary recorder to eliminate redundant analyses, and employs an image-analysis-based line-verification method to overcome the difficulty of using a threshold to distinguish short lines from noise. it avoids the overlapping lines by removing the pixels of detected line segments, which is more robust than only clearing the n × n neighborhood. this approach could be easily extended to improved ht methods that perform the global accumulation. the experimental result shows that this approach is very time-efficient for large-size images.
graphics recognition from binary images: one step or two steps. recognizing graphic objects from binary images is an important task in many real-life applications. generally, there are two ways to do the graphics recognition: one-step methods and two-step methods. the former recognizes graphic objects from binary images directly,while the latter consists of vectorization and postprocessing. neither of them is perfect enough to handle all difficulties. this paper first reviews popular graphics recognition methods to understand their advantages and disadvantages. next, the performance comparison between two classes of methods is made in two important aspects: the time efficiency and the graphics quality, and the experimental results of time-efficiency comparison of 7 popular methods are also reported. finally, we propose a new hybrid graphics-recognition paradigm to integrate the advantages of both one-step methods and two-step methods and minimize their disadvantages. the proposed paradigm is capable of recognizing straight lines, arcs, circles and curves efficiently, and is helpful for extracting text images in text-graphics touching cases.
simultaneous gesture segmentation and recognition based on forward spotting accumulative hmms. in this paper, we propose a forward spotting scheme that executes gesture segmentation and recognition simultaneously by detecting start point. by using competitive differential observation probability, sliding window and accumulative hmms, we apply the proposed method to recognize the upper-body gestures for controlling the curtains and lights in a smart home environment.
combined face-body tracking in indoor environment. background subtraction is commonly used for tracking objects in outdoor environment. but it doesn't work that well indoors, because of the problems caused by illumination change, shadows, occlusion and targets' changing appearances. in contrast, color tracking is relatively resistant to these problems, but suffers from the need of initialization. to complete the specific human tracking task in indoor environment, this paper utilizes the specific human face-body structure, and tracks face and body simultaneously and cooperatively. the advantage of this approach is that it can keep tracking in some bad situations, when one of the parts is missing, which makes it more robust than single-part tracking. experimental tracking results on a meeting room video data are given.
unsupervised band selection for multispectral images using information theory. in this paper, the implication of the relations of information in the case of multispectral images is analyzed. higher-order mutual information can adopt positive or negative values depending of the correlation among ensembles. therefore, the existence of negative values reflects higher-order correlations in the conditional informations. on the other hand, the extraction of optimal subsets of spectral images is proposed as a maximization of the conditional entropies at same time that the dependent information among images is minimized.
attribute relevance in multiclass data sets using the naive bayes rule. feature selection using the naive bayes rule is presented for the case of multiclass data sets. in this paper, the em algorithm is applied to each class projected over the features in order to obtain an estimation of the class probability density function. a matrix of weights per class and feature is then obtained, where it collects the level of relevance of each feature for the different classes. we show different ways to extract this information and compare the behavior of the ranking of relevance obtained applying the naive bayes and k-nn classifiers.
bayesian networks classifiers applied to documents. this paper discusses the use of the bayesian network model for a classification problem related to the document image understanding field. our application is focused on logical labeling in documents, which consists in assigning logical labels to text blocks. the objective is to map a set of logical tags, composing the document logical structure, to the physical text components. we build a bayesian network model that allows this mapping using supervised learning, and without imposing a priori constraints on the document structure. the learning strategy is based partly on genetic programming tools. a prototype has been implemented, andtested on tables of contents found in periodicals and magazines.
evaluating the range flow motion constraint. the instantaneous three-dimensional velocity field of a moving surface can be computed from a sequence of dense range data sets. here we discuss the computation of the underlying motion constraint equation. this involves the evaluation of derivatives of the depth coordinate with respect to the other world coordinates. as these are not evenly sampled the sampling has to be taken into account explicitly. we quantitatively compare four methods to compute derivatives based on the validity of the resulting constraint equation.
progress in document reconstruction. we combine information from a language model and character image pattern matching to iteratively reduce ambiguity in document images. combining word shape information and lists of similar bitmap patterns in a document at least partially resolves the character content without optical character recognition. we present the output in various ways. suitable for human readers or for differing downstream processes.
clothed people detection in still images. we present a trainable system for locating clothed people in photographic images. people detection is a particularly challenging image understanding problem; as a result of variations in clothing and posture, the appearance of people may vary enormously from image to image.our approach attempts to construct a maximally person-like assembly of image regions, where candidate regions are provided by color-based segmentation followed by non-purposive grouping. a tree structured probability model is employed to allow efficient searches. this structure represents the pairwise configuration of body parts as a function of relative position, relative size, and adjacency. face and skin detection is also used to help the search. the problem of occlusion is addressed through a mixture of trees, where the different mixture components represent the possible subsets of visible parts. different clothing styles are accounted for by separate models. experimental results are shown to demonstrate the promise of and challenges for the current system.
a non-random data sampling method for classification model assessment. data sampling is a critical factor for building and evaluating the quality of classifiers, such as neural networks. traditional techniques, such as k-fold cross validation, exhibit limitations when dealing with small data sets. this paper introduces an alternative method that splits the data into training and testing partitions, which have similar statistical characteristics. this method is compared with a traditional technique, using a relatively small dataset and several neural network classifiers. results suggest that this new technique can reduce variability of predictive accuracies and provide consistent results across different classification models.
competitive mixtures of simple neurons. we propose a competitive finite mixture of neurons (or perceptrons) for solving binary classification problems. our classifier includes a prior for the weights between different neurons such that it prefers mixture models made up from neurons having classification boundaries as orthogonal to each other as possible. we derive an em algorithm for learning the mixing proportions and weights of each neuron, consisting of an exact e step and a partial m step, and show that our model covers the regions of high posterior probability in weight space and tends to reduce overfitting. we demonstrate the way in which our mixture classifier works using a toy 2-dimensional data set, showing the effective use of strategically positioned components in the mixture. we further compare its performance against svms and one-hidden-layer neural networks on four realworld data sets from the uci repository, and show that even a relatively small number of neurons with appopriate competitive priors can achieve superior classification accuracies on held-out test data.
small-world approximations in spectral segmentation. spectral segmentation has been shown to produce perceptually meaningful groupings. the underlying similarity matrices are usually very large. several approximations - deterministic and stochastic - areused in practice. the approximations usually use only local information. it has been shown recently that a few random long-range interactions facilitate emergence of structure in several domains like ising models. in this paper we explore the use of long-range interactions in spectral segmentation.
a dynamic approach to learning vector quantization. learning vector quantization networks are generally considered a powerful pattern recognition tool. their main drawback, however, is the competitive learning algorithm they are based upon, that suffers of the so called under-utilized or dead unit problem. to solve this problem, algorithms substantially based on a modified distance calculation, such as the frequency sensitive competitive learning (fscl), have been proposed, but their attainable performance strongly depends on the selection of an appropriate number of neurons. this choice generally require knowledge about the number of clusters in the feature space. in this paper we propose a new supervised training algorithm for lvq neural networks, which provide the optimal number of neurons for each class by dynamically adding or removing neurons on the basis of a measure of their performance. the experimental results, performed on different databases of synthetic data, confirmed the effectiveness of our approach.
improving dynamic learning vector quantization. we introduce some improvements to the dynamic learning vector quantization algorithm proposed by us for tackling the two major problems of those networks, namely neuron over-splitting and their distribution in the feature space. we suggest to explicitly estimate the potential improvement on the recognition rate achievable by splitting neurons in those regions of the feature space in which two or more classes overlap. we also suggest to compute the neuron splitting frequency, and to combine these information for selecting the most promising neuron to split. experimental results on both synthetic and real data extracted from uci machine learning repository show substantial improvements of the proposed algorithm with respect to the state of the art.
a multiresolution approach to on-line handwriting segmentation and feature extraction. we present an approach to on-line handwriting segmentation into elementary strokes. the segmentation is achieved by exploiting curvature information extracted from the electronic ink at different level of resolution. such information is then combined into a saliency map, through which the segmentation points are eventually found. information from the saliency map is also used to select the optimal resolution to be used for describing the curvature of each stroke. experiments conducted by encoding stroke curvature information into strings have shown that similar strings are associated with similar parts of the original ink, independently of the actual word they belong to.
dense stereo based on the uniqueness constraint. the paper presents the matching core of a stereo algorithm suitable to real-time applications. unlike most area-based algorithms, the proposed approach relies on a single matching phase (i.e. do not include the check for left-right consistency). unreliable disparity measuremnts areprimarly detected on the basis of the violation of the uniqueness constraint. in order to further improve the reliability of the matches we enforce additional contraints based on the behaviour of the error function that can be veryfied at a very small computational cost. experimental results show that the proposed approach provides reliable disparity measurements and that it is significantly fast.
3d object digitization: majority interpolation and marching cube. in a previous paper we showed that a 3d object can be digitized without changing the topology if the object is r-regular and if the reconstruction method fulfills certain requirements. in this paper we give two important examples for such reconstruction methods. first, we introduce majority interpolation, an algorithm to interpolate sampling points at doubled resolution such that topological ambiguities are resolved. second, we show how the well-known marching cubes algorithm has to be modified such that it is topology preserving. this is the first approach of digitizing 3d objects which guarantees topology preservation for voxel-based or polygonal surface-based reconstructions.
3d object digitization: majority interpolation and marching cubes. in a previous paper we showed that a 3d object can be digitized without changing the topology if the object is r-regular and if the reconstruction method fulfills certain requirements. in this paper we give two important examples for such reconstruction methods. first, we introduce majority interpolation, an algorithm to interpolate sampling points at doubled resolution such that topological ambiguities are resolved. second, we show how the well-known marching cubes algorithm has to be modified such that it is topology preserving. this is the first approach of digitizing 3d objects which guarantees topology preservation for voxel-based or polygonal surface-based reconstructions.
3d object digitization: topology preserving reconstruction. in this paper we derive a sampling theorem, which is the first one to guarantee topology preservation during digitization of 3d objects. this new theorem is applicable to several reconstruction methods, e.g. a unionof- balls reconstruction and the trilinear interpolation.
a visual attention estimator applied to image subject enhancement and colour and grey level compression. image segmentation technology has immediate application to compression where image regions can be identified and economically coded for storage or transmission. normally segmentation identifies regions that are uniform and homogeneous with respect to some characteristic such as colour or texture and ideally these regions coincide with image objects and thereby offer the potential of huge compression ratios. this paper proposes a technique for colour variability reduction that only affects background material and leaves perceptually important areas unchanged.
class dependent cluster refinement. unsupervised classification is a very common problem in pattern recognition even when the classes are known. in many areas intra-class variations may be greater than the inter-class variations causing a need for a subdivision of the training set of a class into smaller subunits often referred to as clusters. the subdivision or clustering is often performed independently of the relative properties of the other present classes in the recognition task. this paper presents a novel class-dependent approach to the clustering problem. experiments with online handwriting data show that the novel clustering approach cdcr produces a clustering better suited for the task of pattern recognition. although only validated for two recognition methods in this paper, the same approach could be applied to other methods as well as to other pattern recognition problems.
motion imagery navigation using terrain estimates. all aircraft rely on on-board sensor systems for navigation. the drawback to inertial sensors is that their position error compounds over time. global positioning systems (gps) overcome that problem for location but not orientation; also, gps is sensitive to signal dropout and hostile jamming. in this paper, we present a system capable of estimating the six-degree-of-freedom (6dof) state (geo-location and orientation) of an air vehicle given digital terrain elevation data (dted), an estimate of the vehicle's velocity, and a sequence of images from an onboard video camera. this system first reconstructs individual terrain map sections from pairs of images taken by the onboard video camera as it flies over the terrain. the velocity estimate is used to convert the metric units produced by the reconstruction to euclidean units (such as meters). the individual reconstructed map sections are then stitched together to form a larger terrain map. this reconstructed terrain map is then matched against the dted to produce an estimate of the 6dof state of the vehicle.
identifying vehicles using vibrometry signatures. laser vibrometry is an exciting new sensor technology that promises to improve automatic target recognition (atr) performance. sensors such as micro-laser interferometer doppler (mlid) measure minute vibrations on the surface of an object from a large standoff distance. in this paper, we demonstrate a baseline atr algorithm designed for vibrometry data that can reliably recognize military vehicles when trained and tested on similar operating conditions.
estimating the location of illuminants in realist master paintings computer image analysis addresses a debate in art history of the baroque. we address the problem of estimating the position illuminants in realist master paintings. to this end, we apply an algorithm from computer vision that has been used to detect forgeries and composites in digital photographs. our contributions are three-fold: 1) we introduce the application of a two-dimensional, modelfree occluding contour algorithm to the problem of locating the source of illumination in realist master paintings, 2) we introduce a maximum-likelihood criterion and computational method for integrating estimates from multiple occluding contours, and 3) we apply our methods to a key painting adduced as evidence in a recent controversial theory about painting praxis in the renaissance and baroque.
surface skeletons in grids with non-cubic voxels. an algorithm for computing surface skeletons on the face-centered cubic (fcc) grid and the body-centered cubic (bcc) grid is presented. the fcc grid and the bcc grid are three-dimensional grids where the voxels are rhombic do-decahedra and truncated octahedra, respectively. the dt is used to generate the set of centres of maximal balls (cmbs) which will be "anchor points" when constructing the skeleton. simple points are used in order to make the skeleton topologically correct and cmbs to produce a fully reversible skeleton. using only simple points and the cmbs generates a skeleton with a lot of branches. by using a set of additional conditions for removal and preservation of gridpoints, most of these branches are merged into surfaces. for comparison, the algorithm is also implemented for the cubic grid.
using the hexagonal grid for three-dimensional images: direct fourier method reconstruction and weighted distance transform. an image reconstruction technique for computed tomography (ct) images, the direct fourier method, is shown to apply to non-standard grids. in ct, the 3d image is obtained by reconstructing 2d slices separately. we propose to use the hexagonal grid for the 2d slices, resulting in 3d images on non-standard grids. low-level image processing is also considered for these grids - optimal weights to be used for computing the weighted distance transform are calculated.
scale adaptive complexity measure of 2d shapes. in this paper, we describe a complexity (or irregularity) measure of 2d shapes. three properties are first calculated to separately describe the complexity of the boundary, the global structure, and the symmetry of the shape. then, a model consisting of the above parameters are developed to describe the entire complexity of the shape. this model further incorporates the scale information into the boundary complexity definition and also into the determination of weights associated with different properties. finally, we test our complexity model on a synthetic dataset, and demonstrate its application on screening shapes extracted from noisy shoeprint images.
patch-based gabor fisher classifier for face recognition. face representations based on gabor features have achieved great success in face recognition, such as elastic graph matching, gabor fisher classifier (gfc), and adaboosted gabor fisher classifier (agfc). in gfc and agfc, either down-sampled or selected gabor features are analyzed in holistic mode by a single classifier. in this paper, we propose a novel patch-based gfc (pgfc) method, in which gabor features are spatially partitioned into a number of patches, and on each patch one gfc is constructed as component classifier to form the final ensemble classifier using sum rule. the positions and sizes of the patches are learned from a training data using adaboost. experiments on two large-scale face databases (feret and cas-peal-r1) show that the proposed pgfc with only tens of patches outperforms the gfc and agfc impressively.
a multimodal and multistage face recognition method for simulated portrait. recognition of simulated portrait obtained through face composition technique is a challenging task in public security area. an innovative method for simulated portrait recognition is presented in this paper. this method can be used to perform recognition of simulated portraits from anonymous cadaver, from the description of a witness, and from surveillance video. based on principal component analysis (pca), we have constructed eigenface, eigenbrow+ eye, eigeneye, eigennose, and eigenmouth. altogether 31 recognition modes can be formed through different weighted combinations of these eigen-parts. face recognition of simulated portrait is first performed using this multimodal part based pca (mmp-pca)technique, results of which are then used as inputs for further recognition based on modified line segment hausdorff distance (lhd). experiment results show that this innovative recognition method has achieved good results for the recognition of simulated portraits in a database of 100,000 face images.
detecting a gazing region by visual direction and stereo cameras. we develop a wearable vision system that consists of a user's visual direction sensor and stereo cameras. first, we establish a method for calibrating the system so that it can detect user's blink points even in a real situation such that the depth of blink points changes. next, we propose a method for detecting a gazing region of a user in terms of the planar convex polygon. in our method, the system first identifies the fixation point of a use1; and then appliesa stereo algorithm and robust statistics to detect his gazing region. now the system can detect the gazing region of a user and provide him with its 3d position.
obstacle detection using millimeter-wave radar and its visualization on image sequence. sensor fusion of millimeter-wave radar and a camera is beneficial for advanced driver assistance functions such as obstacle avoidance and stop&go. however, millimeter-wave radar has low directional resolution which engenders low measurement accuracy of object position and difficulty of calibration between radar and camera. in this paper, we first propose a calibration method between millimeter-wave radar and ccd camera using homography. the proposed method does not require estimation of rotation and translation between them, or intrinsic parameters of the camera. then, we propose an obstacle detection method which consists of an occupancy-grid representation, and a segmentation technique which divides data acquired by radar into clusters(obstacles); thereafter we display them as an image sequence using calibration results. we demonstrate the validity of the proposed methods through experiments using sensors that are mounted on a vehicle.
camera calibration and reconstruction from the chain connection of mutual camera projections. the relative position and orientation of multiple cameras are very important for reconstructing 3d objects and for generating arbitrary views of the scene. the relationship of these multiple cameras can be described by the epipolar geometry. recently, it has been shown that the epipolar geometry can be computed accurately and efficiently by using the mutual projection of cameras. in this paper, we propose a method for calibrating a large amount of multiple cameras efficiently by extending the mutual projection method for three views. we also show that the proposed method can be applied for reconstructing 3d objects accurately.
graph method for generating affine moment invariants. a general method of systematic derivation of affine moment invariants of any weights and orders is introduced. each invariant is expressed by its generating graph. techniques for elimination of reducible invariants and dependent invariants are discussed. this approach is illustrated on the set of all affine moment invariants up to the weight ten.
hyper frame vision: a real-time vision system for 6-dof object localization. a new system for robot vision is proposed that integrates a 3-d object recognition task and a 3-d object tracking task, enabling real-time 6-dof localization of a known continuously moving object. a computational time-lag between the two tasks is absorbed by a large amount of frame memory. for 3-d sensing, calibrated trinocular stereo cameras are used to employ stereo-vision-based object recognition and tracking methods that allow objects of any shape to be dealt with and to provide robust performance in an environment with partial occlusions and cluttered backgrounds. the effectiveness of the system is demonstrated by experimentalresults.
multi-linguistic optical font recognition using stroke templates. one of the essential distinctions between different fonts is their stroke shape. a method is presented to automatically extract representative stroke templates from a text image, which contains characters of the same typeface. the collected stroke templates are classified and saved to a font database. to recognize an unknown font for an input text image, a bayes decision rule is used to determine which font entrant in the database provides the best matching to the unknown font. the experiment demonstrates that this approach can distinguish between chinese and english fonts without the prior information of their script. another advantage is that it can learn a new font very quickly. forty fonts (twenty english and twenty chinese) are used in our experiment. an average recognition accuracy of 97 percent can be achieved in the present system.
bayesian image segmentation based on an inhomogeneous hidden markov random field. this paper introduces a bayesian image segmentation algorithm with the consideration of label scale variability in many images. an inhomogeneous hidden markov random field is adopted in this algorithm to model the label scale variability as a prior probability. an em algorithm is developed to estimate parameters for both the prior probability and likelihood probability. the image segmentation is established by a map estimator. different images are tested to verify our algorithm. and comparisons with other segmentation algorithms are made. the segmentation results show our algorithm has better performance than others.
active discriminant functions for handwriting recognition. a novel active discriminant functions (adfs) for handwriting recognition is presented in this paper. first, statistical feature based deformable model in principal subspace is proposed and a minimum distance between an unknown pattern and the deformable model is given. second, to improve the accuracy of recognition, the minor subspace is also considered in adfs. third, as parameters of the adfs, the optimal constraints of a deformable model are searched by applying minimum classification error (mce) criterion. finally, empirical experiments are conducted on handwritten chinese characters used in banking and the results show that our proposed adfs outperform other representative techniques, such as support vector machine, multiplayer perceptron, etc.
3d reconstruction of indoor and outdoor scenes using a mobile range scanner. this paper describes 3d mapping of indoor and outdoor environment using a mobile range scanner. in the raw range data preprocessing stage, we propose to use area decreasing flow for surface mesh smoothing instead of the mean curvature flow. although the proposed area decreasing flow approach is mathematically equivalent to the mean curvature flow, it can avoid the difficulty in curvature estimation and provide an optimal flowing step size. geometric details are preserved by adaptive smoothing on crease edges. in the multi-view 3d reconstruction stage, we combine the space carving with hilton's implicit surface-based method to generate watertight 3d models from limited number of scans. volumetric deformation by mean curvature flow using the level set method is applied in the post-processing stage to remove outliers. we present results of 3d reconstruction of real indoor and outdoor environment from multi-view noisy range data.
the role of featural and configural information in face classification a simulation of the expertise hypothesis. face recognition in adults is the product of a unique mechanism in the brain and it is based on years of experience. the goal of this paper is to analyze the role of configural and featural information for face classification and to compare the performance of bayesian network classifiers with the human performance in three experiments: similarity matching, gender, and race classification. our results show that despite the fact that the machine classification results are worse than the one of the humans, they are consistent with human classification results.
fast linear feature detection using multiple directional non-maximum suppression. linear feature detection is a very important issue in the areas of image analysis, computer vision, and pattern recognition. it has found applications in many diverse areas such as neurite outgrowth detection, compartment assay analysis, retinal vessel extraction, skin hair removal for malonoma detection, plant root analysis, and roads detection. we have developed a new algorithm for linear feature detection using multiple directional non-maximum suppression. the algorithm is very fast compared with methods in the literature. we also show a large number of application examples using our linear feature detection algorithm, and very good results have been obtained.
robust direction estimation of gradient vector field for iris recognition. as a reliable personal identification method, iris recognition has been receiving increasing attention. based on the theory of robust statistics, a novel geometry-driven method for iris recognition is presented in this paper. an iris image is considered as a 3d surface of piecewise smooth patches. the direction of the 2d vector, which is the planar projection of the normal vector of image surface, is illumination insensitive and opposite to the direction of gradient vector. so the directional information of iris imageýs gradient vector field (gvf) is used to represent iris pattern. robust direction estimation, direction diffusion followed by vector directional filtering, is performed on the gvf to extract stable iris feature. extensive experimental results demonstrate that the recognition performance of the proposed algorithm is comparable with the best method in the open literature.
evaluation of 3d facial feature selection for individual facial model identification. face recognition using 3d information has been intensively investigated in recent years. the features selected from 3d facial surfaces are invariant to pose and lighting conditions. however, they are sensitive to expression variations. in this paper, we investigate the issues on selecting good features for 3d facial shape classification, and evaluate its applicability to various types of models. based on our existing work on feature selection using a genetic algorithm, we derived a set of features from the individualized wire-frame models. we evaluate the usefulness of such features not only to the generated models from images, but also to the range data from 3d imaging systems with variable resolutions. we tested the algorithm on two types of data sets: generic model based dataset and range-scan model based dataset. experimental results show that the optimal features derived from both datasets are robust among two databases. the resolution of captured models affects the selection of optimal features; however, the combination of the optimal features improves the recognition rate.
better foreground segmentation for static cameras via new energy form and dynamic graph-cut. in this paper, we propose a new foreground segmentation method for applications using static cameras. it formulates foreground segmentation as an energy minimization problem, and produces much better results than conventional background subtraction methods. due to the integration of better likelihood term, shadow elimination term and contrast term into energy function, it also achieves more accurate segmentation than existing method of the same type. furthermore, real-time performance is made possible by employing dynamic graph-cut algorithm. quantitative and qualitative experiments on real videos demonstrate our improvements.
segmentation and probabilistic registration of articulated body models. there are different approaches to pose estimation and registration of different body parts using voxel data. we propose a general bottom-up approach in order to segment the voxels into different body parts. the voxels are first transformed into a high dimensional space which is the eigenspace of the laplacian of the neighbourhood graph. we exploit the properties of this transformation and fit splines to the voxels belonging to different body segments in eigenspace. the boundary of the splines is determined by examination of the error in spline fitting. we then use a probabilistic approach to register the segmented body segments by utilizing their connectivity and prior knowledge of the general structure of the subjects. we present results on real data, containing both simple and complex poses. while we use human subjects in our experiment, the method is fairly general and can be applied to voxel-based registration of any articulated or non-rigid object composed of primarily 1-d parts.
a real-time facial expression recognition using the staam. this paper proposes a real-time person independent facial expression recognition in two folds. one is using the stereo active appearance model (staam) fitting algorithm that uses a geometric relationship between two tightly coupled views to increases the accuracy and speed of fitting. also, a layered generalized discriminant analysis (gda) classifier combines 3d shape and appearance to improve the recognition performance of person independent facial expressions. experimental results show that the staam have a better fitting stability than the multi-view aam (mvaam), and the combination of the shape and appearance features using a layered gda classifier improves the recognition performance of facial expressions greatly.
iris recognition using collarette boundary localization. there has been a rapid increase in the need of accurate and reliable personal identification infrastructure in recent years, and biometrics has become an important technology for security. the iris recognition system consists of four-process: image acquisition, preprocessing, feature extraction and identification or verification. in this paper, we propose the methods for localizing the iris area between the inner boundary and the collarette boundary, to remove unnecessary areas and to increase the recognition rate. for finding the collarette boundary, histogram equalization and a high pass filter, after using an one-dimensional dft, are applied to the image. the collarette boundary is found using an statistical information from the image which removes low-frequencies, and, finally, the iris is localized between the inner boundary and the collarette boundary. the iris is localized by two kinds of methods, and the recognition rate were compared. the recognition rate was evaluated by using dwt and svm. these show that the iris localization by the proposed methods contains more information than the previous methods and improves the recognition rate.
super-resolution in the presence of space-variant blur. an efficient algorithm using maximum a posteriori- markov random field (map-mrf) based approach for recovering a high-resolution image from multiple sub-pixel shifted low-resolution images is proposed. the algorithm can be used for super-resolution of both space-invariant and space-variant blurred images. we prove an important theorem that the posterior is also markov and derive the exact posterior neighborhood structure in the presence of warping, blurring and down-sampling operations. the posterior being markov enables us to perform all matrix operations as local image domain operations thereby resulting in a considerable speedup. experimental results are given to demonstrate the effectiveness of our method.
automatic local effect of window/level on 3-d scale-space ellipsoidal filtering on run-off-arteries from white blood magnetic resonanc angiography. pre-filtering is a critical step in 3-d segmentation of the blood vessel and its display. this paper presents the local effect of window/level over the 3-d scale-space approach for filtering the white blood angiographic volumes and its implementation issues. the raw mr angiographic volume is first converted to an isotropic volume, and then the window/level is automatically adjusted slice by slice and a composite volume is generated. then, 3-d edges are generated using the separable gaussian derivative convolution with known scales. the edge volume is then run by the directional processor at each voxel where the eigenvalues of the 3-d ellipsoid are computed. the vessel score per voxel is then estimated based on these three eigenvalues which suppress the non-vasculature and background structures, yielding the filtered volume. the filtered volume is ray-cast to generate the maximum intensity projection images for display. the performance of the system is evaluated by computing the mean, variance, snr and cnr images. we compare the filtering results with and without the usage of the local effect of window/level over 3-d scale-space ellipsoidal filtering. we show that the automatic window/level is effective in detecting small vessels which are otherwise difcult to extrapolate them. the system was run over 20 patient studies from different parts of the body such as: brain, abdomen, kidney and knee/ankle. the computer program takes around 150 seconds of processing time per study for study for a data size of 512 × 512 × 194 which includes the complete performance evaluation.
a comparison of state-of-the-art diffusion imaging techniques for smoothing medical/non-medical image data. partial differential equations (pde's) have dominated image processing research recently (see suri et al. [1], [3], [5], [4] and haker [6].the three main reasons for their success are: (1) their ability to transform a segmentation modeling problem into a partial differential equation framework and their ability to embed and integrate different regularizers into these models; (2) their ability to solve pde's in the level set framework using finite difference methods; and (3) their easy extension to a higher dimensional space.this paper is an attempt to summarize p e's and their solutions applied to image diffusion. the paper first presents the fundamental diffusion equation. next, the multi-channel anisotropic diffusion imaging is presented, followed by tensor non-linear anisotropic diffusion. we also present the anisotropic diffusion based on p e and the tukey/huber weight function for image noise removal. the paper also covers the recent growth of image denoising using the curve evolution approach and image denoising using histogram modification based on p e. finally, the paper presents the non-linear image denoising. examples covering both synthetic and real world images are presented.
mutual information based evaluation of 3d building models. this paper presents a metric based on information theory principles that compares 3d object models to images. the metric is based on the formulation of the mutual information between the model and the images. the technique does not require a priori information about the surface properties of the object and is robust with respect to variations of illumination. as result the method is quite general and may be used in a wide variety of applications.experiments are presented that demonstrate the approach by evaluating reconstructed 3d building models in aerial images.
using a fuzzy framework for delineation and decomposition of immunoglobulin g in cryo electron tomographic images. in structural studies of proteins, the first task is to identify the different parts of the protein. we present a robust method using a fuzzy framework for delineating a protein and to identify its parts. the method is used in a study of the immunoglobulin g antibody, individually imaged using cryo electron tomography, with satisfactory results.
order-preserving clustering and its application to gene expression data. clustering of ordered data sets is a common problem faced in many pattern recognition tasks. existing clustering methods either fail to capture the data or use restrictive models such as hmms or ar models to model the data. in this paper, we present a general order-preserving clustering algorithm that allows arbitrary patterns of data evolution by representing each ordered set as a curve. clustering of the data then reduces to grouping curves based on shape similarity. we develop a novel measure of shape similarity between curves using scale-space distance. shape similarity or dis-similarity is judged by composing higher-dimensional curves from constituent curves and noting the additional twists and turns in such curves that can be attributed to shape differences. an algorithm analogous to k-means clustering is then developed that uses prototypical curves for representing clusters. results are demonstrated on ordered gene expression data sets obtained from gene chips.
technical symbols recognition using the two-dimensional radon transform. we introduce a new method to generate feature vectors to be used in symbol recognition. we propose a new exploitation of the radon transform to generate relevant features. the radon transform is essentially a transformation of an image into a transform plane (p, ¿) represented by an accumulator in the discrete case. from the accumulator array we extract a signature (r-signature) which provides a global information of a binary shape whatever its type and its form. the signature allows to keep fundamental geometrical transformation like scale, translation and rotation.
recognition of symbols in grey level line-drawings from an adaptation of the radon transform. an adaptation of the radon transform is proposed to recognize grey level symbols. we directly process on the grey level document in order to improve the recognition step. a tridimensional signature is defined which takes into account the variations of photometry and the shape of a symbol. the proposed signature also allows to keep fundamental geometric transformations (scale, translation and rotation). experimental results on technical documents show the promising aspect of our approach.
retrieving images by content from strong relational graph matching. a new method is proposed to retrieve images by content. the approach is based on the matching of strong graphs defined by relational signatures computed between clusters of a fuzzy partition. such a representation combines color and spatial information between the regions and have nice geometric properties w.r.t scale factor, rotation and translation.
binarization of color images from an adaptation of possibilistic c-means algorithm. a color image binarization is presented in this paper. the iterative possibilistic c-means algorithm is adapted by adding a fuzzy entropy criterion to split the membership function in two clusters (background and object). such an improvement allows to perform a threshold free color binarization. experimental results show the promising aspect of our approach.
fast visual search using simplified pruning rules - streamlined active search. object detection in an image has a lot of applications. it has been reported that color information has advantages in detecting objects. in this paper, a high-speed visual search strategy using color histograms by introducing simplified pruning rules and global pruning is proposed. experimental results show that the proposed method outperforms traditional methods.
feature selection using tabu search for improving the classification rate of prostate needle biopsies. the introduction of multispectral imaging in pathology problems such as the identification of prostatic cancer is recent. unlike conventional rgb color space, it allows the acquisition of large number of spectral bands within the visible spectrum. this results in a feature vector of size greater than 100. for such high dimensionality problems, pattern recognition techniques suffer from the well-known curse-of-dimensionality problem. the two well known techniques to solve this problem are feature extraction and feature selection. in this paper, a feature selection technique using tabu search with an intermediate-term memory is proposed. the cost of a feature subset is measured by leave-one-out correct-classification rate of a nearest-neighbor (1-nn) classifier. experiments have been carried out on textured multispectral images taken at 16 spectral channels and the results have been compared with a reported classical feature extraction technique.
simultaneous image denoising and compression by multiscale 2d tensor voting. in this paper we propose a method that simultaneously performs image denoising and compression by using multiscale tensor voting. given a real color image, the pixels are first converted into a set of tokens to be grouped by tensor voting, where optimal scales are automatically selected among others for perceptual grouping and faithful reconstruction. tensor voting at multiple scales are performed at all input tokens to infer the feature grouping attributes such as region-ness, curve-ness, and junction-ness with their optimal scales. we perform experiments on complex real images to demonstrate the robustness of our method.
planning of multiple camera arrangement for object recognition in parametric eigenspace. when objects are recognized by using multiple cameras, recognition rates strongly depend on the camera arrangement. in this paper, we propose a new method for planning a multiple camera arrangement for accurate recognition. we use a parametric eigenspace method for the recognition framework in which objects are represented as manifolds in an eigenspace. the proposed method evaluates the adequacy of camera arrangement according to the relations between the manifolds in the eigenspace. in the experiments, we defined a function that measures relations by the distances between manifolds. the experimental results show the effectiveness of the proposed method.
high quality isosurface generation from volumetric data and its application to visualization of medical ct data. we propose a method for generating an isosurface from volumetric data sampled with a face-centered cubic lattice. the display quality of the isosurface obtained by our method is greatly enhanced because it generates many good aspect ratio triangle patches. we applied the method to visualization of a colonic wall from medical data. we experimentally compared the resulting surface of our method with those of existing methods, showing the effectiveness of our method.
dvhmm: variable length text recognition error model. this paper proposes a text recognition error model called the dual variable length output hidden markov model (dvhmm) and gives a parameter estimation algorithm based on the em algorithm. although existing probabilistic error models are limited to substitution (1,1), insertion (1,0), and deletion (0,1) errors, the dvhmm can handle error patterns of any pair (i, j) of lengths including substitution, insertion, and deletion.
object contour detection using spatio-temporal self-sim. a novel contour detector that refines a rough boundary between an object and a background to a precise boundary in moving pictures robustly is proposed. to estimate boundaries of objects, the proposed method uses self-similar block matching (ssbm) in spatio-temporal 3-d space. ssbm, which searches a larger similar block for each block placed near a boundary, estimates contours correctly. in this paper, it is shown analytically that the robustness of spatiotemporal ssbm is superior to that of conventional 2-d ssbm. since ssbm does not assume contour smoothness, the proposed algorithm can detect sharp corners more accurately than the methods using smooth constraints such as snake. experimental results show that the proposed method is effective for estimating precise regions of objects even if pictures are noisy.
3d reconstruction and virtual forming in rotationally symmetric space. for reconstructing 3d objects and for generating arbitrary views of the scene, accurate calibration of multiple cameras is very important. in this paper, we introduce rotationally symmetric space, and show that in rotationally symmetric space, cameras can be calibrated and 3d points can be reconstructed just from a single basis line reliably. the proposed method is applied for deforming virtual clay in rotationally symmetric space and for generating augmented reality images of virtual pottery.
a study on character recognition error correction at higher level recognition step for mathematical formulae understanding. in this paper we propose a method for correcting character recognition errors at the higher level recognition step in an understanding system for mathematical formulae. the system consists of two-level recognition steps: the low level recognition including character recognition, and the higher level recognition including layout recognition. we use the layout information recognized in the latter step to correct the character recognition errors by using two sources of information. one is based on some keywords such as mathematical function names, and the other is based on a cost tree and co-occurrence probabilities between symbols. the efficacy of the proposed method is verified by some experimental results, and the character recognition rate increased from 80.2% to 89.2%.
surface reconstruction from stereovision data using a 3-d mrf of discrete object models. in the present paper, we propose a method for reconstructing the surfaces of objects from stereovision data. both the fitness of stereo data to surfaces and interrelation between the surfaces are defined in the framework of a three-dimensional (3-d) markov random field (mrf) model. the surface reconstruction is accomplished by searching for the most likely state of the mrf model. an experimental result is shown for a real scene.
recognition of lung nodules from x-ray ct images using 3d markov random field models. in this paper, we propose a new recognition method of lung nodules from x-ray ct images using 3d markov random field(mrf) models. pathological shadow candidates are detected by a mathematical morphology filter, and volume of interest(voi) areas which include the shadow candidates are extracted. the probabilities of the hypotheses that the voi areas come from nodules(which are candidates of cancers) and blood vessels are calculated using nodule andblood vessel models evaluating the relations between these object models by 3d mrf models. if the probabilities for the nodule models are higher, the shadow candidates are determined to be abnormal. by applying this new recognition method to actual 38 ct images, good results has been acquired.
applying the conjugate gradient method for text document categorization. in this paper, we investigate the effectiveness of two different methods to solve the linear least squares fit (llsf) problem for document categorization.the first method is the singular value decomposition (svd) method that has been previously used to solve the document categorization problem.the second method is the conjugate gradient (cg) method that is one of the most effective algorithms for solving a linear equation problem.however, up to our knowledge, the cg method has never been applied to handle the document classification problem.therefore, we compare the effectiveness of these two llsf methods to categorize text documents.in addition, we examine the effect of using different term weighting schemes on their performance for document classification.lastly, we compare the performance of the llsf classifiers agaisnt the neighborhood-based dt-knn classifier, our best variant of the knn classifier integrated with a dynamic threshold scheme, on the reuters 21578 dataset.besides being the first proposal to use the cg method for document classification, our work opens up many exciting directions for future investigation.
string-like occluding region extraction for background restoration. in this paper, we propose a method for extracting stringlike objects in a still image for background restoration. we assume that the object regions occluding the background are long and narrow, and contrasted in intensity with background. first the method introduces a circle contrast, the intensity difference between a pixel and those on a circle around, to find the occluding string-like regions. then the signs of the circle contrast are decided so that the occluding regions and backgrounds are well separated, and further enhanced by an optimization process. extracted regions are removed with interpolation (inpainting) for background restoration. experimental results on real images show the validity of the proposed method.
smartalbum - towards unification of approaches for image retrieval. in this paper we present a novel application (called smartalbum) for photo indexing and retrieval that unifies two different image indexing approaches. the system uses two modalities to extract information about a digital photograph; i.e. content-based and speech annotation forimage description. the result is a powerful image retrieval tool that has capabilities beyond what current single-mode retrieval systems can offer. we show on a corpus of 1200 images the interest of our approach.
robust image denoising using kernel-induced measures. in this paper, we propose a class of novel nonlinear robust filters for image denoising by incorporating kernel -induced measures into classical linearmean filter. particularly, we place more focus on gaussian kernel based filter (gk) due to its simplicity. the gk filter not only generalizes and makes the original linear mean filter highly resistant to outliers but also outperforms a typical and powerful mean-logcauchy filter recently developed by hamza et al in the mixed noise removal in certain specific conditions in the normalized mean square error (nmse) sense. also the experimental results illustrate that the kernel-based nonlinear filters are promising.
efficient night gait recognition based on template matching. gait is a useful biometric which can be used to recognize people at a distance when other biometrics are incapable. however, most work on gait recognition has been visible spectrum-oriented over the past decade, ignoring recognition at night which is in reality demandimperative. this paper deals with the problem of night gait recognition via thermal infrared imagery. first of all, human detection is accomplished, based on the gaussian mixture modeling of the background. then, human silhouettes are extracted on the basis of preceding detection results. moreover, a new gait representation called hti is proposed to characterize gait signatures for recognition. an infrared night gait database was built to provide a foundation for night gait recognition. experimental results on two gait datasets show the effectiveness of this method.
a theoretical and experimental consideration on interference in resolutions between sampling theorem and ok-quantization theory. ok-quantization theory for the digitization in value ensures the reconstruction of the probabilistic density function of the image. this paper shows some experimental demonstrations to reduce the number of the gray levels, and shows mainly that there is a necessary but very important analytical relationship between sampling and quantization based on the equivalence relationship between two kinds of the integral, riemann and lebesgue integrals for calculating the volume of the image. experimental demonstrations are also shown in this paper.
use of viewpoint information for example selection in cbir. images play important role in telerobotic interface systems. a set of images taken by an image sensor equipped on a mobile robot is helpful for a remote user to recognize the conditions of the robot as well as its operating environments. we view such an image set as a large-scale image database, and apply content-based image retrieval (cbir) to visualize the image database. we will propose a novel cbir method that efficiently searches such relevant objects based not only on their features, but also on their locations with respect to the operating environment.
constructing speech processing systems on universal phonetic codes accompanied with reference acoustic models. this paper proposes a novel speech processing framework, where all of the speech data are once encoded into universal phonetic code (upc) sequences and speech processing systems, such as speech recognition, retrieval, digesting, are constructed on this upc domain. first of all, we introduce an ipa-based sub-phonetic segment (sps) set as the upc to deal withmultilingual speech. in the upc (sps) domain, each upc accompanies a reference acoustic model which is independent of real acoustic models used in the encoding process. processing, such as recognition, in the upc domain is conducted based on the distance between upc sequences estimated by using the reference acoustic models. we confirm the proposed framework by constructing a speech recognition and a vocabulary-free speech retrieval system on the sps domain. we show several experimental results on these systems, using japanese and english speech data sets.
neighbor pixel mixture. pixel mixture is a technique to reduce the read-out time of an image by mixing multiple pixel values on an imager. ordinary pixel mixtures mix the values of equicolor pixels. however, the equicolor pixels are not contiguous on the bayer pattern. mixing non-contiguous pixels degrades the resolution of the mixed image. this paper proposes a novel pixel mixture method which we call a "neighbor pixel mixture". the resolution of the neighbor pixel mixture image is superior to that of exisiting pixel mixtures. the proposed method mixes the values of the neighbor pixels with different colors. in the proposed method, a weighted average is used for the mixing operation, whereas ordinary pixel mixtures apply a simple average. we also discuss a guideline to design weights for averaging.
probabilistic localization for mobile robots using incomplete maps. this paper addresses the problem of global localization for mobile robots in changeable environments, i.e. to estimate self-position using a map that is partially or completely different from the environment. it is difficult to detect changes when both of the self-position and the map have large uncertainties. to solve the problem, in this paper, we extend monte carlo localization (mcl) and sensor resetting localization (srl), so as to generate a number of hypotheses about the change as well as the self-position. as a result of tests in a number of environments as well as changes, we found the proposed method is effective even when "rate of changes (roc)" is high in the environment.
retrieval method for multi-category images. we propose an image retrieval technique based on multiple categories. generally, an image can be associated with many concepts or objects. when concepts or objects are regarded as categories, an image could have multiple labels corresponding to these categories. thus, image retrieval based on multiple categories would be an important technology for an image database system. to realize multi-category image retrieval, we employ the pmm (parametric mixture model) of multi-category text classification. we carried out multi-category image classification experiments using pmm and the color histogram feature. the experimental results show the possibility of multi-category image classification and retrieval using pmm.
probabilistic image processing based on the q-ising model by means of the mean-field method and loopy belief propagation. the framework is presented of bayesian image restoration for multi-valued images by means of the q-ising model. hyperparameters in the probabilistic model are determined so as to maximize the marginal likelihood. practical algorithms are described based the conventional mean-field approximation and loopy belief propagation. we compare the results empirically with those provided by conventional filters and the new methodsarefound to be superior.
active mass estimation with haptic vision. real-world objects exhibit rich physical interaction behaviors on contact. such behaviors depend on how heavy and hard it is when hold, how its surface feels when touched, how it deforms on contact, etc. recently, there are growing needs for haptic exploration to estimate and extract such physical object properties as mass, friction, elasticity, etc.. in this paper, we propose an active mass estimation method based on haptic vision. we first observe an object with active vision to extract its 3d shape and posture. next, we estimate a contact point and contact force and apply it to cause the object to move without rotation by a robot hand. we observe changes in the contact force using a force feedback sensor, and also observe its straight movement using a ccd camera. then we estimate the mass of the object using known static and dynamic friction coefficients. experimental results show that the mass of solids such as wood, iron, and ceramic objects were estimated efficiently within 10% error bound.
recognition of unconstrained legal amounts handwritten on chinese bank checks. this paper presents a novel research investigation on legal amount recognition of unconstrained cursive handwritten chinese character in the environment of a2ia checkreader¿ - a commercial bank check recognition system. the following problems and their solutions are described: character set of chinese legal amounts, preprocessing (slant detection and correction), segmentation, feature extraction, grammar, automatic annotation of chinese characters before and during training, and neural network/hidden markov model training and recognition. the system is trained with 47.8 thousand real bank checks, and validated with 12 thousand real bank checks. the recognition rate at the character level is 93.5%, and the recognition rate at the legal amount level is 60%. this is the first successful commercial product in this domain.
a novel method for harmonic geometric transformation model based on wavelet collocation. geometric distortion may occur in the data acquisition phase in information systems, and it can be characterized by some geometric transformation models. once the distorted image is approximated by a certain geometric transformation model, we can apply its inverse transformation for the geometric restoration to remove the distortion. harmonic model is a very important one, which can cover other linear and nonlinear geometric models. however, its implementation is very complicated, because it can not be described by any fixed functions in mathematics. in fact, it is represented by partial differential equation with a given boundary condition. in this paper, a novel wavelet-based method is presented to handle the harmonic model. our approach has two main advantages, the shape of an image is arbitrary and the program code is independent of the boundary. the performances are evaluated by experiments.
automatic segmentation of the papilla in a fundus image based on the c-v model and a shape restraint. for computer aided glaucoma diagnostics it is essential to robustly and automatically detect and segment the main regions, e.g. the papilla (optic nerve head), in a fundus image. in this paper an effective method for automatic papilla segmentation based on the c-v model and a shape restraint is proposed. the method is a combination between the c-v model using level sets and the elliptic shape restraint for papilla segmentation. the combination of the level set framework with a shape restraint ensures that the evolving curve stays an ellipse. experiments verify that the method shows a good performance in detecting the papilla shapes and computing the shape feature parameters within a broad variety of fundus images. the experiment results also show that the method is robust to noise and object deformity.
fast linear discriminant analysis using binary bases. linear discriminant analysis (lda) is a widely used technique for pattern classification. it seeks the linear projection of the data to a low dimensional subspace where the data features can be modelled with maximal discriminative power. the main computation in lda is the dot product between lda base vector and the data point which involves costly element-wise floating point multiplications. in this paper, we present a fast linear discriminant analysis method called binary lda (b-lda), which possesses the desirable property that the subspace projection operation can be computed very efficiently. we investigate the lda guided non-orthogonal binary subspace method to find the binary lda bases, each of which is a linear combination of a small number of haar-like box functions. we also show that b-lda base vectors are nearly orthogonal to each other. as a result, in the non-orthogonal vector decomposition process, the computationally intensive pseudo-inverse projection operator can be approximated by the direct dot product without causing significant distance distortion. this direct dot product projection can be computed as a linear combination of the dot products with a small number of haar-like box functions which can be efficiently evaluated using the integral image. the proposed approach is applied to face recognition on orl and feret dataset. experiments show that the discriminative power of binary lda is preserved and the projection computation is significantly reduced.
learning a sparse representation from multiple still images for on-line face recognition in an unconstrained environment. in a real-world environment a face detector can be applied to extract multiple face images from multiple video streams without constraints on pose and illumination. the extracted face images will have varying image quality and resolution. moreover, also the detected faces will not be precisely aligned. this paper presents a new approach to on-line face identification from multiple still images obtained under such unconstrained conditions. our method learns a sparse representation of the most discriminative descriptors of the detected face images according to their classification accuracies. on-line face recognition is supported using a single descriptor of a face image as a query. we apply our method to our newly introduced bhg descriptor, the sift descriptor, and the lbp descriptor, which obtain limited robustness against illumination, pose and alignment errors. our experimental results using a video face database of pairs of unconstrained low resolution video clips of ten subjects, show that our method achieves a recognition rate of 94% with a sparse representation containing 10% of all available data, at a false acceptance rate of 4%.
human motion de-noising via greedy kernel principal component analysis filtering. kernel principal component analysis (kpca) has been shown to be a powerful non-linear de-noising technique. a disadvantage of kpca, however, is that the storage of the kernel matrix grows quadratically, and the evaluation cost grows linearly with the number of exemplars. the size of the training set composing of these exemplars is therefore vital in any real system incorporating kpca. given long human motion sequences, we show how the greedy kpca algorithm can be applied to filter exemplar poses to build a reduced training set that optimally describes the entire sequence. we compare motion de-noising between standard kpca using all poses in the original sequence as training exemplars and de-noising using the reduced set filtered by the greedy algorithm. we show how both have superior denoising qualities over pca, whilst greedy kpca results in lower evaluation cost due to the reduced training set.
reconstruction of medical images by perspective shape-from-shading. shape-from-shading (sfs) is a fundamental problem in computer vision; it is based upon the image irradiance equation. recently, the authors proposed to solve the image irradiance equation under the assumption of perspective projection rather than the common orthographic one. the solution was a modification of the fast marching method of kimmel and sethian. this paper presents an application of this novel perspective algorithm to reconstruction of medical images. we focus on gastrointestinal endoscopy and compare the two versions of the fast marching method (orthographic vs. perspective). the examples and comparison show that, unlike orthographic sfs, perspective sfs is robust and can be utilized for real-life applications.
nonparametric discriminant analysis in relevance feedback for content-based image retrieval. relevance feedback (rf) has been wildely used to improve the performance of content-based image retrieval (cbir). how to select a subset of features from a large-scale feature pool and to construct a suitable dissimilarity measure are key steps in rf. biased discriminant analysis (bda) has been proposed to select features during relevance feedback iterations. however, bda assumes all positive feedbacks form a single gaussian distribution which may not be the case for cbir. although kernel bda can overcome the drawback to some extent, the kernel parameter tuning makes the online learning unfeasible. to avoid the parameter tuning problem and the single gaussian distribution assumption in bda, we construct a new nonparametric discriminant analysis (nda). to address the small sample size problem in nda, we introduce the regularization method and the null-space method. because the regularization method may meet the ill-posed problem and the null-space method will lose somediscriminant information, we proposed here a full-space method. the proposedfull-space nda is demonstrated to outperform bda based rf significantly based on a large number of experiments in corel database with 17,800 images.
object predetection based on kernel parametric distribution fitting. multimodal distribution fitting is an important task in pattern recognition. for instance, the predetection which is the preliminary stage that limits image areas to be processed in the detection stage amounts to the modeling of a multimodal distribution. different techniques are available for such modeling. we propose a pros and cons analysis of multimodal distribution fitting techniques convenient for object predetection in images. this analysis leads us to propose efficient and accurate variants over the previously proposed techniques as shown by our experiments. these variants are based on parametric distribution fitting in the rkhs space induced by a positive definite kernel.
uncertainties-driven surface morphing: the case of photo-realistic transitions between facial expressions. reproduction of facial animation play a fundamental role in applications requiring human-computer interactions the objective of this paper is to introduce a geometric mechanism that exploits a fix number of states and is able to execute a subsequent number of transitions between facial expressions. standard stereo-based techniques are used to reproduce the geometry and appearance of the most characteristic facial expressions. a novel free-form-deformation technique based on uncertainty driven local geometric registration in the space of distance transforms is used to produce a one-to-one mapping between the surfaces and the associated textures. standard techniques from image morphing introduce the temporal aspect in the process. experimental results and comparisons with actual observation demonstrate the potentials of such an approach.
robust recursive learning for foreground region detection in videos with quasi-stationary backgrounds. detecting regions of interest in video sequences is the most important task in many high level video processing applications. in this paper a robust technique based on recursive learning of video background and foreground models is presented. our contributions can be described along four directions. first, a recursive learning scheme is developed to build pixel models based on their colors. second, we generate background and foreground models to enforce the temporal consistency of detected foregrounds. third, we exploit dependencies between pixel colors to insure that the model is not restricted to using only independent features. finally, an adaptive pixel-wise criterion is proposed that incorporates different spatial situations in the scene.
linear model combining by optimizing the area under the roc curve. in some classification problems, like the detection of illnesses in patients, classes are very unbalanced and the misclassification costs for different classes vary significantly. then it is better not to minimize the classification error, but to optimize the ordering of the data, or to optimize the area under the roc curve (auc). in this paper we propose to optimize a linear combination of features (or base model outputs) by optimizing auc. the advantages are that a relatively small training set is required for the optimization and that the training set can have a large class imbalance. furthermore, the classifier does not make distributional assumptions, making it very suitable to combine the outputs of base classifiers. in the application of the detection of interstitial lung diseases it is shown to be very advantageous and to outperform standard classification rules.
a consistency-based model selection for one-class classification. model selection in unsupervised learning is a hard problem. in this paper a simple selection criterion for hyper-parameters in one-class classifiers (occs) is proposed. it makes use of the particular structure of the one-class problem. the mean idea is that the complexity of the classifier is increased until the classifier becomes inconsistent on the target class. this defines the most complex classifier which can still reliably be trained on the data. experiments indicated the usefulness of the approach.
optimal inference for hierarchical skeleton abstraction. skeletons are well-known representations that accommodate shape abstraction and qualitative shape matching. however, skeletons are sometimes unstable to compute and sensitive to shape detail, thus making shape abstraction and matching difficult. to address these problems, we propose a principled framework that generates a simplified, abstracted skeleton hierarchy by analyzing the quasi-stable points of a bayesian-inspired energy function. the resulting model is parameterized by both boundary and internal structure variations corresponding to object scale and abstraction dimensions, and trades-off reconstruction accuracy and representation parsimony. our experimental results show that the method can produce useful multi-scale skeleton representations at a variety of abstraction levels.
robust computation of optical flow under non-uniform illumination variations. in this paper, an energy minimization method is proposed to estimate the optical flow of an image sequence in the presence of non-uniform illumination variations. the energy function is formulated by combining a data constraint energy that considers the illumination variations and a smoothness constraint, which minimizes the pixel-to-pixel variation of the velocity and illumination fields. minimization of this energy function is equivalent to solving a linear system, which is accomplished by using an incomplete cholesky preconditioned conjugate gradientalgorithm. a dynamic weighting scheme, which considers the statistical properties of estimated optical flow. is also combined with this algorithm to improve the robustness of our algorithm. this algorithm has been successfully applied to synthetic and real image sequences and someexperimental results demonstrate that this algorithm can estimate the optical flow under non-uniform illumination variations accurately.
color decomposition of overlapped watercolors. in this paper we propose a color decomposition method for multicolor printing of watercolors including areas overlapping each print layer. watercolors have an important feature that the observed colors are different by the printing order. this method is based on a particle density model for expressing the effects of watercolors. the approach of this method is to solve an inverse problem, that is, determining a printed area corresponding to a watercolor from an observed image. our purpose in this study is to estimate woodblocks from a woodblock print. we focus on multicolor woodblock prints such as ukiyo-e: japanese traditional woodblock printing. the results of woodblock estimation will be utilized to preserve techniques and prints of ukiyo-e. an ukiyo-e print is created from several woodblocks with several watercolors, and has a mixing color expression similar to the effects of watercolor painting.
mixed anisotropic diffusion. this paper deals with the filtering and the enhancement of strongly oriented patterns. we propose a new filter combining scalar and tensor based diffusivities. the computation of an orientation confidence allows us to choose the best strategy to locally diffuse the gray levels.we will show that this approach overcomes some drawbacks of the classical methods like corner smoothing or pinhole effect. the proposed method was applied on digital images of engravings. this type of images contain strongly oriented patterns and a large amount of details that have to be preserved during the diffusion.
combination of shape descriptors using an adaptation of boosting. many different kinds of shape descriptors have been defined but usually, each of them is only suitable for some particular kinds of shapes. then, a strategy to improve performance in arbitrary shapes is the use of several descriptors. in this paper, we address the problem of how to combine several shape descriptors into a single representation. we present an adaptation of the boosting algorithm that permits to train a different classifier for each descriptor and combine all these classifiers to obtain a global classifier. the contribution of each descriptor to this final classifier is determined according to its performance along the boosting iterations. thus, the most relevant descriptors have the greatest influence in the final classifier.
robust face detection and hand posture recognition in color images for human-machine interaction. a system for the detection of human faces and for the classification of hand postures in color images is presented. we first propose to apply a combination of a skin chrominance-based image segmentation with a color vector gradient-based edge detection [1 ] [2 ] to efficientlydetect faces and hands. a statistical model for face detection based on invariant moments [3] [4 ] is then used to discriminate between faces and hands in the segmented images. a novel approach to hand posture recognition based on phase-only correlation [5 ] is finally applied toclassify a subset of static hand postures of the japanese sign language, each posture representing a given phoneme, and also to discriminate between hand postures and the image scene background. experiments show that the additional use of the color gradient significantly improves the correct rate of face detection, and that the phase-only correlation filter yields a high rate of discrimination between different static hand postures aswell as between hand postures and the scene background.
druide : a real-time system for robust multiple face detection, tracking and hand posture recognition in color video sequences. "druide", which stands for "detection, recognition, unification, interpretation, decision, evolution", is a novel, real-time system primarily designed for the detection and tracking of multiple human faces as well as for the simultaneous recognition of multiple hand postures in color video sequences and in complex environments. the system relies on the three fundamental cues of color, shape and motion, and integrates three mutually complementary sub-systems, in order to achieve high rates of detection, tracking and recognition. preliminary experiments yield an average correct face detection rate of about 90%, and the additional use of tracking increases significantly the robustness of the proposed system, particularly to illumination conditions and to partial occlusions. although we first focus specifically on human faces and hand postures, the ultimate goal of druide extends beyond human-computer interactions, to encompass the adaptive detection, tracking and recognition of various objects under unconstrained scene conditions.
vehicle lateral position estimation method based on matching of top-view images. in this paper, a method to estimate the lateral position of the vehicle from a sequence of moving camera images is proposed. proposed method relies on the plane projective transform (homography) between the ground and the image plane of the present and the next frame. homographies are obtained according to the information of the calibrated camera and the vehicles' speed. the movement of the camera is obtained by the registration of the 2 consecutive input images. the proposed method does not rely on extraction of features such as lines, flow vectors or lane markers, but based on matching of warped top-view images between two consecutive frames. therefore, vehicle movement can be estimated even from images without such explicit image features or without special sensors or gps. in this paper, experiments are done with both synthesized and real images and enough accuracy is shown even compared to conventional method.
occlusion resistant shape classifier based onwarped optimal path matching. in this paper, we present a novel occlusion resistant shape classification scheme for hidden markov modeled shapes. first, hidden markov model (hmm) is built using multiple example shapes for each shape class. a reference path for each class is built from the corresponding hmm, which is nothing but optimal path followed by the most likely example shape. the reference path stores temporal information about the entire shape, while the hmm only retains relationship between temporal information. finally to classify a shape, occluded or not, its optimal path through hmm is calculated and warped to match the reference path using dynamic time warping (dtw). correct class is identified as the one for which the warping cost is minimum. classification results obtained for two shape data sets are presented for varying degrees of occlusion and are compared with the conventional maximum likelihood (ml) hmm classifier.
hierarchical probabilistic models for video object segmentation and tracking. when tracking and segmenting semantic video objects, different forms of representational model can be used to find the object region on a per-frame basis. we propose a novel hierarchical technique using parametric models to describe the appearance and location of an object and then use non-parametric methods to model the sub-object regions for accurate pixel-wise segmentation. our motivation is to use parametric models to locate the object, improving the sensitivity of the non-parametric sub-object region models to background clutter. the results indicate this is a promising approach to extracting video objects.
classification of team behaviors in sports video games. this paper considers the application of pattern recognition techniques in modern computer games. towards the problem of realizing more life-like behavior for artificial game characters, we record the network traffic of online multiplayer games. dealing with a soccer game, we cluster these data and train hmms in order to achieve fast and robust recognition of behaviors and actions in the virtual game world. experimental results indicate that pattern recognition and machine learning provide an auspicious avenue towards more convincing artificial characters.
a low-complexity deformation invariant descriptor. in this paper, we propose a descriptor which is invariant to general deformations (only intensity locations change but not their value) by using hilbert scanning. in our method, an image is converted to a 1-d sequence through hilbert scanning at first. then, we embed this sequence as a 1- d curve in the 2-d space. because hilbert scanning preserves the coherence in a 2-d image, it is easily to understand that the area under the curve is invariant to intensity location changes, naturally. hence, we use some areas for an interest point as a deformation invariant descriptor. this descriptor can be computed in the 2-d space efficiently than other approaches where an image is embedded in the 3-d space or the dimensions of descriptors are very large. the experimental results show that our descriptor is low-complexity and superior to other approaches on interest point matching in deformation images.
an efficient algorithm for point matching using hilbert scanning distance. a fast and accurate similarity named hilbert scanning distance(hsd) [9] has recently been presented for point matching. in this study, we improved an efficient algorithm of search strategy for hsd in the large search space. this search strategy is associated with two ideas: a relaxation greedy search, and an accelerating process using monte carlo sampling. the experimental results implicate that this improved algorithm is robust and efficient for point matching using hsd. it also makes a tradeoff between accuracy and speed under different requirements.
voting weighted modified hausdorff distance through multiscale space for automatic image-map registration. the purpose of image-map registration is to revise the digital map included in geographic information system (gis) with aerial image. the traditional method for this task requires the manual selection of tie points in both image and map. in this study, we propose a distance measure named voting weighted modified hausdorff distance (vwmhd) for this task. in order to overcome the differences in representations between image and map in urban area, after several times of edge extraction through multiscale space, we give weights to each edge point in the initial scale based on its voting times and then compute the vwmhd for registration. the experimental results implicate that our vwmhd can provide sufficient information for automatic image-map registration and is robust to noises.
a shunting inhibitory convolutional neural network for gender classification. demographic features, such as gender, are very important for human recognition and can be used to enhance social and biometric applications. in this paper, we propose to use a class of convolutional neural networks for gender classification. these networks are built upon the concepts of local receptive field processing and weight sharing, which makes them more tolerant to distortions and variations in two dimensional shapes. tested on two separate data sets, the proposed networks achieve better classification accuracy than the conventional feedforward multilayer perceptron networks. on the feret benchmark dataset, the proposed convolutional neural networks achieve a classification rate of 97.1%.
3d texture classification using the belief net of a segmentation tree. this paper presents a statistical approach to 3d texture classification from a single image obtained under unknown viewpoint and illumination. unlike in prior work, in which texture primitives (textons) are defined in a filter-response space, and texture classes modeled by frequency histograms of these textons, we seek to extract and model geometric and photometric properties of image regions defining the texture. to this end, texture images are first segmented by a multiscale segmentation algorithm, and a universal set of texture primitives is specified over all texture classes in the domain of region geometric and photometric properties. then, for each class, a tree-structured belief network (tsbn) is learned, where nodes represent the corresponding image regions, and edges, their statistical dependecies. a given unknown texture is classified with respect to the maximum posterior distribution of the tsbn. experimental results on the benchmark curet database demonstrate that our approach outperforms the state-of-the-artmethods.
detection of artificial structures in natural-scene images using dynamic trees. we seek a framework that addresses localization, detection and recognition of man-made objects in natural-scene images in a unified manner. we propose to model artificial structures by dynamic tree-structured belief networks (dts-bns). dtsbns provide for a distribution over tree structures that we learn using our structured approximation (sva) inference algorithm. furthermore, we propose multi-scale linear-discriminant analysis (mlda) as a feature extraction method, which appears well suited for our goals, as we assume that man-made objects are characterized primarily by geometric regularities and by patches of uniform color. mlda extracts edges over a finite range of locations, orientations and scales, decomposing an image into dyadic squares. both the color of dyadic squares and the geometric properties of extracted edges represent observable input to our dtsbns. experimental results demonstrate that dts-bns, trained on mlda features, offer a viable solution for detection of artificial structures in natural-scene images.
detection over viewpoint via the object class invariant. in this article, we present a new model of object class appearance over viewpoint, based on learning a relationship between scale-invariant image features (e.g. sift) and a geometric structure that we refer to as an oci (object class invariant). the oci is a perspective invariant defined across instances of an object class, and thereby serves as a common reference frame relating features over viewpoint change and object class. a single probabilistic oci model can be learned to capture the rich multimodal nature of object class appearance in the presence of viewpoint change, providing an efficient alternative to the popular approach of training a battery of detectors at separate viewpoints and/or poses. experimentation demonstrates that an oci model of faces can be learned from a small number of natural, cluttered images, and used to detect faces exhibiting a large degree of appearance variation due to viewpoint change and intra-class variability (i.e. (sun)glasses, ethnicity, expression, etc.).
attention navigation by keeping screen layout for switching multiple views. to show a multi-directional scene situation with switching different views, we have to keep a screen layout of a remarkable object for intelligible image media. in this paper, we propose a method to navigate a viewer to one of objects in the scene by keeping its screen layout for switching multiple views. in order to keep the layout, we developed "virtual swiveling" by using fixed-viewpoint pan-tilt-zoom camera, based on area and center of gravity of extracted objects from captured images. we also show several experimental results to confirm an effectiveness of our method.
pen-coordinate information modeling by scpr-based hmm for on-line japanese handwriting recognition. this paper describes stochastic modeling of pencoordinate information in hmms with structured character pattern representation (scpr) for on-line japanese handwriting recognition. scpr allows hmms for kanji character patterns to share common subpatterns. although scpr-based hmms have been successfully applied to kanji character recognition, the pen-coordinate feature has not been modeled since it is unique feature in each character pattern. in this paper, we employ mapping from a common subpattern to each occurrence in kanji patterns and adaptation of state parameters to each character pattern in generating character hmms by composing scprbased hmms. experimental results show that the pencoordinate feature modeled in the scpr-based hmms effects significantly.
discriminatory power of handwritten words for writer recognition. analysis of allographs (characters) and allograph combinations (words) is the key for the identification/verification of a writer's handwriting.while allographs are usually part of words and the segmentation of a word into allographs is a subjective process, analysis of handwritten words is a natural option, complementary to allograph and document-level analysis. we consider four different types of features obtained using both segmentation-based and segmentation-free approaches: (i) gsc(gradient, structural and concavity) features that are extracted from the cells of a grid superimposed on the word image (ii) wmr (word model recognizer) features, extracted from the cells of superimposed grids on the segmented characters (iii) sc (shape curvature) features that describe characters by the distribution of curvature values on their contours and (iv) scon (shape context) features that measure the similarity between character contour shapes. their individual and accumulated performance is evaluated for the writer identification and verification tasks on over 75000 words images, written by more than 1000 writers. experimental results show that handwritten words are very effective in discriminating handwriting and that both segmentation-free and segmentation-based approaches are valid.
estimation of human motion from multiple cameras for gesture recognition. we have been researching human sensing technologies based on computer vision for the realization of the percept-room as an intelligent environment. this room offers several services such as the control of electrical appliances by use of gestures. a more caring technology is strongly expected for providing more human-friendly interfaces.as a first step, the recognition of human motion in the percept-room is an important task. we propose a method for extracting humans and then hand gestures from multi-channel motion images captured in the percept-room. the human position and the rising handgestures are estimated by integrating the silhouettes from multiple cameras by a background image subtraction and a frame subtraction. we describe the proposed methods and the experimental results obtained by use of a pc system implemented in the percept-room.
estimation of surface properties of art paintings using a multi-band camera. this paper describes a method for precisely estimating the surface properties of art paintings, including surface normal, surface spectral reflectance, and reflection model parameters. we use a multi-band camera system with six spectral channels. the surface of a painting is observed under different illumination directions by the camera. we use the torrance- sparrow model as a reflection model. the surface normal is estimated on the different illumination observations by the photometric stereo. the spectral reflectance is estimated on the multi-band data by the wiener method. the model parameters are estimated on the statistical distribution of the specular component. finally, all estimates are combined for rendering various appearances of the painting under different illumination and viewing conditions.
arbitrary viewpoint rendering from multiple omnidirectional images for interactive walkthroughs. recently, the interactive walkthrough which enables us to look around a virtualized real world has been widely investigated. the walkthrough system can be applied to simulation, telepresence, and so on. this paper describes a method of interactive walkthrough which takes a real scene and enables us to look around in the virtualized scene. our method is based on acquiring omnidirectional images at multiple points in the real world by using anomnidirectional camera. the method generates an omni-directional image at an arbitrary location from captured omnidirectional images, and presents a user a converted view-dependent perspective image. in the experiment, we realized the interactive walkthrough using indoor omnidi-rectional images and confirmed the feasibility of the method.
local motion analysis and its application in video based swimming style recognition. in this paper we study the problem of local motion analysis and apply it to swimming style recognition in broadcast sports video. local motion analysis is challenging for two reasons: 1) local motion is usually buried in clutters involving complex motion from multiple objects; and 2) the process is more sensitive to noises compared to the recovery of global motion. however, an effective approach to local motion analysis is significant for understanding human activity from image sequences. in this work, we firstly extract the object-induced local motion by utilizing robust motion estimation and salient color. the object motion is accordingly characterized by compensated motion vectors and confidence measurement. beyond a single image, we attempt to capture the motion periodicity over the local motion sequence. for each period, we locate a so-called salient frame within which we derive a compact representation to distinctly characterize an image sequence with repeated actions. finally, we employ a hierarchical classifier to distinguish local motion based on periodicity and salient frames. promising results have been achieved on swimming style recognition in broadcast sports video.
multiview facial feature tracking with a multi-modal probabilistic model. dynamically tracking facial features with large variation of face pose has been shown as one of the most challenging issues in facial feature tracking. the traditional statistical models employ a principal component analysis (pca) to characterize the statistics of a set of example shapes, however they are restricted to a narrow view due to the global linearity assumption. in this paper, a novel model-based multi-modal probabilistic approach is proposed to capture the complicated relationships among facial features under different face poses by using a mixture of local linear probabilistic pcas. based on the probabilistic evaluation of the component probabilistic pcas, the proposed method provides an effective way to choose the appropriate local pca automatically and accurately when face poses are undergoing large variations. experiment results demonstrate that the proposed method could track the facial features robustly with high accuracy under large variations of pose over time.
an effective and fast soccer ball detection and tracking method. a ball detection and tracking approach in real soccer game is proposed in this paper. in view of difficulties of direct detection, an indirect strategy based on non-ball elimination is applied. we distinguish the ball with a coarse-to-fine process. game field is firstly extracted and the posterior operations are restricted within it. then, at the coarse step, some distinct non-ball regions are removed via evaluation of color and shape. and at the fine step, the remained regions are further examined and the optimal one is determined as ball. afterwards, condensation algorithm is utilized to track ball. region optimization is appended to adapt to the ball's size and color/texture changes in response to movement along sequential frames through maximizing the normalization sum of intensity gradient around its perimeter. moreover, a confidence measure representing the ball region's reliability is presented to guide possible re-detection for continuous tracking. experiments have demonstrated the method is valid and fast in real soccer sequences.
continuous-discrete filtering for cardiac kinematics estimation under spatio-temporal biomechanical constrains. a continuous-discrete filtering strategy is proposed for cardiac kinematics estimation from periodic medical image sequences. stochastic multi-frame filtering frameworks are constructed to deal with the parameter uncertainty of the biomechanical constraining model and the noisy nature of the imaging data coordinately. for the system with continuous dynamics and discrete measurements, the state estimates are predicted according to the continuous-time state equation between observation time points, and updatedwith the new measurements obtained at discrete time instants, yielding physically more meaningful and more accurate estimation results for the continuously evolving cardiac dynamics. the strategy is validated through synthetic data experiments to illustrate its advantages and on canine mr phase contrast images to show its clinical relevance.
multiresolution mesh reconstruction from noisy 3d point sets. we augment the tensor voting framework with a datadriven multiscale scheme for reconstructing a multiresolution mesh from a noisy 3d point set. the augmentations are effective, automatic but very simple, consisting of surface saliency inference, scale segmentation, and data normalization. these data analysis steps enable tensor voting to operate at a single scale in each normalized data segment, by decoupling scale and smoothness control. they also guide tensor voting to reconstruct at optimal resolutions subject to the sampling theory. the output is a multiresolution mesh that captures large and small scale features faithfully, without using the maximum resolution everywhere in the domain. the augmented methodology is very robust in the presence of noisy and irregular samples, and non-trivial holes that cover large areas involving multiple-scale features.
evolutionary optimization of feature representation for 3d point-based. in this paper, we introduce a new approach for the classification of point-based 3d computer graphics models. we propose a new representation for 3d point cloud models based on a set of principal projection axes. the point set is then projected on to each of these axes, and a suitable summary statistics of the projected point set along each axis is calculated. the complete set of statistics is then adopted as the feature representation of the point set. based on this representation, we need to search for the optimal set of projection axes which can best distinguish the different classes of point cloud models in the database. in general, this optimization problem is difficult due to the size of the search space. as a result, we propose to adopt evolutionary strategy (es)[3] as the optimization technique. this is in view of the capability of es to explore many regions of the search space in parallel. our experiment results indicate that the proposed optimized feature representation based on only the point set can attain a classification accuracy which is comparable to alternative feature representations which require the availability of the original polygonal representation.
facial feature tracking using a multi-state hierarchical shape model under varying face pose and facial expression. this paper presents a multi-state hierarchical approach for facial feature tracking. a hierarchical formulation of statistical shape models is proposed to characterize both global shape constraints of human faces and local structural details of facial components. gabor wavelets and gray level profiles are integrated for effective and efficient representation of feature points. furthermore, multi-state local shape models are presented to deal with shape variations of facial components. meanwhile, face pose estimation helps improve shape constraints for the feature search. both facial component states and feature point positions are dynamically estimated using a multi-modal tracking approach. experimental results demonstrate that the proposed method accurately and robustly tracks facial features under different facial expressions and pose variations.
local identification and removal of scatter artefacts based on the temporal information in dynamic spect images. scatter in spect images may mask decreseased uptake of radiopharmaceuticals in the left ventricle of the heart which can alter the diagnostic outcome of the study. the newly developed dynamic spect (dspect) method, which reconstructs 4d images from a standard acquisition protocol, provides additional temporal information which may be helpful to recognise such artefacts. each voxel carries a time signature, which is different for different organs. in this paper, we investigate whether this signature can be used to detect and remove scatter. time activity curves (tacs) from segmented data are tested for their potential to locally identify scatter according to a simple model. the investigation is carried out on artificial artefacts in real patient data as well as on existing scatter. tests on the artificial artefacts showed that scatter can indeed be detected and removed while tests on real data revealed that the simplified model may suffice to remove the majority of local scatter.
adaptive clustering ensembles. clustering ensembles combine multiple partitions of the given data into a single clustering solution of better quality. inspired by the success of supervised boosting algorithms, we devise an adaptive scheme for integration of multiple non-independent clusterings. individual partitions in the ensemble are sequentially generated by clustering specially selected subsamples of the given data set. the sampling probability for each data point dynamically depends on the consistency of its previous assignments in the ensemble. new subsamples are drawn to increasingly focus on the problematic regions of the input feature space. a measure of a data point's clustering consistency is defined to guide this adaptation. an empirical study compares the performance of adaptive and regular clustering ensembles using different consensus functions on a number of data sets. experimental results demonstrate improved accuracy for some clustering structures.
discriminative features for document classification. document representation using the bag-of-words approach may require bringing the dimensionality of the representation down in order to be able to make effective use of various statistical classification methods. latent semantic indexing (lsi) is one such method that is based on eigendecomposition of the covariance of the document-term matrix. another often used approach is to select a small number of most important features out of the whole set according to some relevant criterion. this paper points out that lsi ignores discrimination while concentrating on representation. furthermore, selection methods fail to produce a feature set that jointly optimizes class discrimination. as a remedy, we suggest supervised linear discriminative transforms, and report good classification results applying these to the reuters-21578 database.
shape-space from tree-union. in this paper we investigate how to construct a shape space for sets of shock trees. to do this we construct a super-tree to span the union of the set of shock trees. this super-tree is constructed so that it both minimizes the total tree edit distance and preserves edge consistency constraints. each node of the super-tree corresponds to a dimension of the pattern space. individual such trees are mapped to vectors in this pattern space.
four metrics for efficiently comparing attributed trees. we address the problem of comparing attributed trees and propose four novel distance metrics centered around the notion of a maximal similarity common subtree, and hence can be computed in polynomial time. we experimentally validate the usefulness of our metrics on shape matching tasks, and compare them with edit-distance.
spontaneous handwriting recognition and classification. finite-state models are used to implement a handwritten text recognition and classification system for a real application entailing casual, spontaneous writing with large vocabulary.handwritten short paragraphs are to be classified into a small number of predefined classes.the paragraphs involve a wide variety of writing styles and contain many non-textual artifacts.hmms and n-grams are used for text recognition and n-grams are also used for text classification. experimental results are reported which, given the extreme difficulty of the task, are encouraging.
detection of moving shadows using mean shift clustering and a significance test. an algorithm that discriminates moving objects from their shadows is presented. starting from the change mask of an image sequence, first of all the changed area is devided into subregions consisting of pixels with similar colour properties. this is done using the mean shift algorithm which is very powerful in non-parametric clustering of data. in a second step a significance test is performed to classify each image pixel inside the change mask into one of the classes foreground or shadow. to do this a straight-forward image model is used where the grey-level of a foreground pixel covered by a shadow is given by the product of the corresponding background pixels' grey-level and a constant value. assuming that fore- and background images are corrupted by gaussian white noise, a significance test is derived which classifies all pixels inside the change mask. in the third step global and local information from the first and second steps are combined. for each region inside the change mask it is examined if the majority of pixels survived the second step. if this is the case, the whole region is kept for the final moving object mask, if not the region is set to zero.
vision-based augmentation of a sentient computing world model. this paper presents work which integrates computer vision information obtained from calibrated cameras with location events from an office-based ultrasonic location system. bayesian networks are used to model dependencies and reliabilities of the multi-modal variables and perform fusion. context is represented using a world model which incorporates aspects of both the static and dynamic environment. information from the sentient computing system is used to guide and constrain the computer vision components, which in turn enhance the accuracy and capabilities of the world model.
image mosaicing from a set of images without configuration information. we proposed a method for creating image mosaics automatically under the condition that arrangement of partial images or camera movement is unknown. in this problem, the process can be divided into two steps. the first step is to search rough arrangements of partial images. the next step is to adjust detailed positioning using rough arrangements. in the first step, it is difficult to check up all combinations of arrangements because the number of them is huge. the proposed method utilizes a genetic algorithm (ga) for the first step. the second one for detailed positioning is performed by local search.
symbol recognition of printed piano scores with touching symbols. to build a music database efficiently, an automatic score recognition system is a critical component. many previous methods are applicable only to some simple music scores. in case of complex music scores it becomes difficult to detect symbols correctly because of noise and connection between symbols included in the scores. in this paper, we propose a score recognition method which is applicable to the complex music scores. symbol candidates are detected by template matching. from these candidates correct symbols are selected by considering their relative positions and mutual connections. under the presence of noise and connected symbols, the proposed method outperformed "score maker” which is an optical music score recognition software.
a study of symbol segmentation method for handwritten mathematical formula recognition using mathematical structure information. symbol segmentation is very important in handwritten mathematical formula recognition, since it is the very first portion of the recognition process. this paper proposes a new symbol segmentation method using mathematical structure information. the base technique of symbol segmentation employed in the existing methods is dynamic programming which optimizes the overall results of individual symbol recognition. the new method we propose here improves symbol recognition performance by using correction values together with evaluation values of symbol recognition. these correction values are calculated from the relations among handwritten stroke positions and mathematical structure. there is no report which takes account of mathematical structure information for symbol segmentation in the handwritten mathematical formula recognition. our experiments have proven that the recognition rate of symbol segmentation by existing methods is between 90.2% and 93.3%, while our proposed method gives correct recognition rate of 97.1%.
a probabilistic model with parsinomious representation for sensor fusion in recognizing activity in pervasive environment. to tackle the problem of increasing numbers of state transition parameters when the number of sensors increases, we present a probabilistic model together with several parsinomious representations for sensor fusion. these include context specific independence (csi), mixtures of smaller multinomials and softmax function representations to compactly represent the state transitions of a large number of sensors. the model is evaluated on real-world data acquired through ubiquitous sensors in recognizing daily morning activities. the results show that the combination of csi and mixtures of smaller multinomials achieves comparable performance with much fewer parameters.
a fast multiscale edge detection algorithm based on a new edge preserving pde resolution scheme. in this communication we present a new explicit numerical scheme to approximate the solution of the linear diffusion filtering. it allows to introduce a new edge preserving scheme which is fast, stable, easy to program and applicable to any dimensions. our diffusion scheme is then put into a simple and original multi-scale edge detection algorithm. some experimental results of the proposed approach for the multi-scale detection of edges in greyscale images are presented, as well as a comparison with other diffusion filtering schemes.
optimizing nearest neighbour in random subspaces using a multi-objective genetic algorithm. in this work, the authors have evaluated almost 20 millions ensembles of classifiers generated by several methods. trying to optimize those ensembles based on the nearest neighbours and the random subspaces paradigms, we found that the use of a diversity metric called "ambiguity" had no better positive impact than plain stochastic search.
novel dct and dwt based watermarking techniques for digital images. two digital image watermarking techniques that have higher level of security compared to most of the existing algorithms have been proposed. the proposed digital watermarking scheme uses the properties of discrete cosine transform (dct) and discrete wavelet transforms (dwt) to achieve almost zero visible distortion in the watermarked images. these techniques use a unique method for spreading, embedding and extracting the watermark. embedding using a linear relation between the transform coefficients of the watermark and a security matrix has been proposed with satisfactory results. it has been shown that instead of adding the watermark to the source image, as is normally done, multiplying the watermark with the transformed source could be a preferred technique, as it would retain the original bit rate to a large extent. the watermarked images were tested subject to image cropping.
using evolution to learn how to perform interest point detection. the performance of high-level computer vision applications is tightly coupled with the low-level vision operations that are commonly required. thus, it is advantageous to have low-level feature extractors that are optimal with respect to a desired performance criteria. this paper presents a novel approach that uses genetic programming as a learning framework that generates a specific type of low-level feature extractor: interest point detector. the learning process is posed as an optimization problem. the optimization criterion is designed to promote the emergence of the detectors' geometric stability under different types of image transformations and global separability between detected points. this concept is represented by the operators repeatability rate [11]. results prove that our approach is effective at automatically generating low-level feature extractors. this paper presents two different evolved operators: ipgp1 and ipgp2. their performance is comparable with the harris [5] operator given their excellent repeatability rate. furthermore, the learning process was able to rediscover the det corner detector proposed by beaudet.
background removal system for object movies. in this paper, we present an interactive system for removing the backgrounds from object movies. our system automatically extracts initial segmentation results based on observed characteristics of object movies. these characteristics are (1) the distribution of background color is gaussian, (2) the color difference between foreground and background is distinct, and (3) the background of the images set with the same tilt angle is static. the user can modify misclassified pixels in only a few frames. the corrected result is propagated to all frames through spatial and temporal coherence. after user manipulation, the alpha estimation process is performed to obtain the alpha values for pixels that are composed of both background and foreground. our automatic process for obtaining initial segmentation results extracts most foreground and background pixels, and thus more accurate results are obtained with little user intervention.
multiple human objects tracking in crowded scenes. this paper introduces a multiple human objects tracking system to detect and track multiple objects in the crowded scene in which occlusions occur. our method assign each pixel to different human object based on its relative distance to that object and the corresponding color model. if no occlusion, we easily track each object independently based on each segmented object region and optical flow. with occlusion, we analyze the color distribution of the occlusion group to differentiate each object in the group. by calculating the distances between objects, we can determine whether an object is separated from the occlusion group and to be tracked individually afterwards.
independent component analysis based filter design for defect detection in low-contrast textured images. in this paper, we propose a convolution filtering scheme for detecting defects in low-contrast textured surface images and, especially, focus on the application for glass substrates in liquid crystal display (lcd) manufacturing. a defect embedded in a low-contrast surface image shows no distinct intensity from its surrounding region, and even worse, the sensed image may present uneven brightness on the surface. all these make the defect detection in lowcontrast surface images extremely difficult. in this study, a constrained ica (independent component analysis) model is proposed to design an optimal filter with the objective that the convolution filter will generate the most representative source intensity of the background surface without noise. the prior constraint incorporated in the ica model confines the source values of all training image patches of a defect-free image within a small interval of control limits. in the inspection process, the same control parameter used in the constraint is also applied to set up the thresholds that make impulse responses of all pixels in faultless regions within the control limits, and those in defective regions outside the control limits. a stochastic evolutionary computation algorithm, particle swarm optimization (pso), is applied to solve for the constrained ica model. experimental results have shown that the proposed method can effectively detect defects in textured lcd glass substrate images.
classification of segmented regions in brightfield microscope images. the subcellular localisation of proteins in living cells is an important step to determine their function. a common method is the evaluation of fluorescence images. the position of marked proteins, visible as bright spots, enables conclusions concerning their function. in order to determine the subcellular localisation, it is crucial to know the exact positions of the considered cells within an image. these are provided by the segmentation of a corresponding brightfield microscope image. as the resulting segments do not exclusively comprise cells, they have to be classified. therefore, we propose an approach for the classification of the resulting segments in 'cells' and 'non-cells', which is an essential step of the automatic recognition of cells and thus of the automatic subcellular localisation of proteins in living cells.
evaluating feature importance for object classification in visual surveillance. feature-based object classification, which distinguish a moving object to human or vehicle, is important in visual surveillance. in order to improve classification performance, in addition to choosing between the classification (such as svm, ann etc), we have to pay attention to which subset of features to employ in the classifier. this paper describes a method to evaluate the relative importance of various features for object type classification. starting with a given set of features, we apply the adaboost method and then we compute a metric which enables us to choose a good subset of the features. we apply our method to the task of distinguishing whether an image blob is a vehicle, a single human, a human group, or a bike, and we determine that shape-based feature, texture-based feature, and motion-based feature are reliable for this classification task. we validate our method by comparing with performance of ann-based classification.
metric measurement on arbitrary planes in 2 images using the conformal point. in 2001, richard hartley et al. [visual navigation in a plane using the conformal pint]described a novel entity known as the conformal point p which enables direct measurement of angles in the image. in spite of its convenience, p is plane-dependent. if the angle lies on another plane, the vanishing line changes and hence, the conformal point moves too. sometimes the angle lies on a virtual plane where the vanishing line is not easy to discover. this paper proposes a novel algorithm to address this problem. after ideal plane stabilization, the angle is marked in both images. through mapping the angle lines from one image to the target image, the location of the vanishing line in the target image can be determined. with the camera calibrated, the conformal point can be directly determined. the angle can then be computed as in [visual navigation in a plane using the conformal pint]. real experimentsshow that an angle in the 3d world can be computed quite accurately using the proposed method.
real-time sound source localization based on audiovisual frequency integration. we propse a pixelwise sound source localization algorithm based on audiovisual frequency integration. the localization is realized by detecting the common vibration dynamics of sound sources in the audio and the brightness signal. in order to detect the common vibration dynamics, temporal correlation values between the two signals are calculated in the algorithm. several experimental results are shown for vibrated objects, and the pixelwise sound source localization images are obtained.
surface models based on face hierarchies and dynamic control of the model lods. we present a new method of constructing hierarchical surface models which are represented by binary trees of faces. the models are useful both for hierarchical approximation of the surfaces and for efficient computation using the face-based hierarchy. our method creates at first a roughly approximated model and then generates the hierarchical models by iterative splitting faces. we also describe the method of dynamic control of levels of detail (lods) of the surface models. and we show the results of control of lods by a gaze point.
levels of detail control based on correlation analysis between surface position and direction. this paper presents a new lod control method using surface smoothness measure based on correlation analysis between surface position and direction. this control method renders smooth surface with less data. we also describe a new method of generating hierarchical data structures of face clusters.
motion tracking of cattle with a constrained deformable model. in this paper, we propose a method for monitoring the motion of cows by tracking the white patterns on them with constrained deformable models. as input for observation, we use image sequences of overhead views of cows taken by a camera installed on the ceiling of a breeding room. first, the 3d coordinates of the boundaries of the white patterns on the head, neck and torso parts respectively are registered. for each body part, the relationship betweenvariations of the patterns in appearance and the parameters specifying the movement are defined in advance from that part's movement characteristics. using deformable models which are constrained to be deformed based on these relations, the boundaries of the patterns are robustly tracked, producing as output the parameters specifying the movement of each part. preliminary experiments using actual image sequences have shown the practical usefulness of the proposed method.
a volumetric approach for the registration and integration of range images: towards interactive modeling systems. this paper presents a new approach for registering and integrating range images where these two processes are merged and performed in a common volumetric representation. the proposed approach allows both simultaneous and incremental registration where matching complexity is linear with respect to the number of images. this improvement leads to incremental modeling from range image acquisition to surface reconstruction. it is shown that the approach is tolerant to initial registration errors as well as to measurement errors while keeping the details of the initial range images. the paper describes the formalism of the approach. experimental results demonstrate performance advantages and tolerance to aforementioned types of errors for free form objects.
myocardial strain imaging with tagged mri. a 4-d b-spline model has been created to accurately capture the dynamic motion of the heart from tagged magnetic resonance imaging (mri) enabling displacement field reconstruction of myocardial deformation. the 4-d model is allowed to deform based on the location of the tag lines for all frames within the constraints of the model's spatio-temporal internal energy. from a displacement field, the corresponding long and short axis lagrangian strain maps are produced. motion fields from simulated data produced by a cardiac motion simulator are used to create corresponding strain images. in addition, strain images produced from porcine data with posterolateral myocardial in-farction are illustrated.
brain symmetry plane computation in mr images using inertia axes and optimization. detection of the best symmetry plane in 3d images can be treated as a registration problem between the original and the reflected images. the registration is performed in 3d space of parameters defining orientation and shift of reflection plane. we use the normalized l2 metric as the similarity measure between original and reflected images and investigate an algorithm for computation of the best symmetry plane. the algorithm computes first an initial position of the plane by analyzing principal inertia axes. we demonstrate on several mr brain images that the initial position is in the neighborhood of the global maximum. therefore the downhill simplex method is further used for the computation of the best symmetry plane. the proposed algorithm was tested on simulated and real mr brain images.
estimating rigid motions via the conformal model of euclidean space. estimating rigid motions from 3-d point correspondances and image projections is an important computer vision problem. we present a novel estimation algorithm using the recent conformal model of euclidean space. we derive an origin independent semi-closed form for the optimal transformation, solving it using an svd-based technique.
a unified information-theoretic approach to the correspondence problem in image registration. we consider the correspondence problem associated with the non-rigid registration of a group of images; in particular, the theoretical basis for the derivation of the objective function that defines the 'best' correspondence across a set of images. for intra-subject registration, there is an actual physical deformation process underlying the observed deformation, but for inter-subject registration, there is no such physical process, and hence no hypothetical process that generates the observed data. this leads to the conclusion that our construction should be based on the data alone. such a construction is possible using criteria derived from information theory. we show how many commonly used pairwise voxel-based similarity measures can be generated using these criteria, and discuss how this approach can be extended to give a unified theoretical basis for the generation of novel objective functions in the groupwise case, where both image discrepancy and image deformation terms should be included in a principled way.
ocr fonts revisited for camera-based character recognition. in order to realize accurate camera-based character recognition, machine-readable class information is embedded into each character image. specifically, each character image is printed with a pattern which comprises five stripes and the cross ratio derived from the pattern represents class information. since the cross ratio is a projective invariant, the class information is extracted correctly regardless of camera angle. the results of simulation experiments showed that recognition rates over 99% were obtained by the extracted cross ratio under heavy projective distortions.
using eigen-deformations in handwritten character recognition. deformations in handwritten characters have class-dependent tendencies. for example,characters of class "a" are often deformed by global slant transformation and never deformed to be similar to "r". in this paper, the extraction and the utilization of such tendencies called eigen-deformations are investigated for better performance of elastic matching basedrecognition systems. the eigen-deformations are extracted by the principal component analysis of actual deformations automatically collected by elastic matching. from experimental results it was shown that the extracted eigen-deformations represent typical deformations of each class. it was also shown that the recognition performance can be improved significantly by using the eigen-deformations in detecting overfitting, which often results in misrecognition.
active modeling of articulated objects with haptic vision. recently, there are growing needs for haptic exploration to estimate and extract physical object properties such as mass, friction, elasticity, function etc. in this paper, we propose a novel approach to active modeling of articulated objects with haptic vision. the method automatically extracts and describes both geometrical and physical properties of an articulated object, through the observation of interactions with active vision and "active touch" by a robot hand, using a ccd camera, range and force-feedback sensors. such models can provide users with reality-based interactions with the objects in virtual environments, to test and extract physical properties such as functions, parts motions and linking structures etc. experimental results on a paper punch and a pair of pliers were shown and these results were successfully used to construct a reality-based virtual environment simulator.
two-dimensional heteroscedastic linear discriminant analysis for age-group classification. this paper presents a novel lda algorithm named 2dhlda (2-dimensional heteroscedastic linear discriminant analysis). the proposed algorithms are applied on age-group classification using facial images under various lighting conditions. 2dhlda significantly overcomes the singularity problem, so-called 'small sample size' problem (s3 problem), and the original feature space is split into useful dimensions and nuisance dimensions to reduce the influence of different lighting conditions. a two-phased dimensional reduction step, namely 2dhlda+lda, is used in our experiment. our experimental results show that the new 2dhlda-based approach improves classification accuracy more than the conventional 1d and 2d-based approaches.
an efficient implementation technique of bidirectional matching for real-time trinocular stereo vision. bidirectional matching(bm) is an effective technique for area-based binocular stereo vision for maintaining one-toone correspondence, detecting half-occlusions and discarding false matches. this paper presents an extension of bm to trinocular stereo vision and proposes its memoryefficient implementation that maintains locality of memory access and thus enables the use of simd instruction sets of cpu for high time-performance. by using this scheme together with several other implementation techniques, 50fps throughput in generating disparity maps of approx. 320 × 240 sizes has been attained with ordinary pc workstations.
real-time cooperative multi-target tracking by communicating active vision agents. this paper presents a real-time cooperative multi-target tracking system. the system consists of a group of active vision agents (avas, in short) representing a logical model of a network-connected computer with an active camera. all avas track their target objects cooperatively by interacting dynamically with each other. as a result, the system as a whole can track multiple moving objects simultaneously under complicated dynamic situations in the real world. to implement real-time cooperation among avas, we designed a three-layered interaction architecture. in each layer, parallel processes mutually exchange a variety of information for effective cooperation. we employed the dynamic memory architecture to achieve real-time information exchange. experimental results demonstrated that avas track their target objects cooperatively in real-time while adaptively changing their roles.
extracting a gaze region with the history of view directions. we propose a method for extracting a gaze region from an observed image by analyzing human's view directions and image information. the view direction of the user, which is represented as a 2d gaze point in the observed image, is obtained by an eye-mark recorder at every image-capturing timing. all gaze points are translated to one of the images for extracting the gaze region based on the history of the view directions. the system divides all gaze points into several groups by comparing color information etc., and then generates several convex hulls as initial regions. each initial region is extended based on its color information and the spatial distribution of the gaze points. all regions are finally integrated and regarded as the gaze region.
probabilistic phase based sparse stereo. in this study, a multi-scale phase based sparse disparity algorithm and a probabilistic model for matching are proposed. the disparity algorithm and the probabilistic approach are verified on various stereo image pairs.
registration of range and color images using gradient constraints and range intensity images. this paper proposes a method for the registration of range and color (or intensity) images, based on the range intensity image that is simultaneously acquired with a range image. the gradient constraint between the range intensity image and the color image is introduced, and a linear equation for the registration parameters is derived, which combines displacement estimations for extrinsic and intrinsic parameters. by using the equation, precise automatic registration without explicit detection of correspondences is achieved. experimental results illustrate the proposed method.
a system to detect houses and residential street networks in multispectral satellite images. maps are vital tools for most government agencies and consumers. however, their manual generation and updating is tedious and time consuming. as a step toward automatic map generation, we introduce a novel system to detect houses and street networks in ikonos multispectral images. our system consists of four main blocks: multispectral analysis to detect cultural activity, segmentation of possible human activity regions, decomposition of segmented images, and graph theoretical algorithms to extract the street network and to detect houses over the decompositions. we tested our system on a large and diverse data set. our results indicate the usefulness of our system in detecting houses and street networks, hence generating automated maps.
a theoretical and experimental investigation of graph theoretical measures for land development in satellite imagery. cities are evolving and districts are changing their characteristics faster than ever before. although the evolution is slow in the central parts of most cities, it is typically fairly fast in outlying regions. they affect the public and private utility networks and maps become less reliable. as a result, emergency plans based on these maps may be ineffective. to assist experts, planners, policy makers, and civil defense organizations, we are developing automated techniques. in previous work, we considered discriminating rural and urban regions [classifying land development in high resolution satellite images using straight line statistics]. to automate the fine classification process, this paper introduces graph theoretical measures over grayscale images. these measures are monotonic with increasing structure (organization) in the image. thus, increased cultural activity and land development are indicated by increases in these measures - without explicit extraction of road networks, buildings, residences etc. we present a theoretical basis for the measures followed by extensive experimental results. we consider commercial ikonos data, which are metric images. our dataset is large and diverse, including sea and coastline, rural, forest, residential, industrial, and urban areas. on this data set we obtained promising results.
whole shape measurement system using a single camera and a cylindrical mirror. this paper proposes a three-dimensional measurement system with a simple structured system. the proposed system consists of a camera with a fish-eye lens and a cylinder whose inside is coated by a silver reflective layer. a target object is placed inside the cylinder and an image is captured by the camera from right above. the captured image includes sets of points that are observed from multiple viewpoints: one is observed directly, and the other is observed via the mirror. therefore, the whole shape of the object can be measured using stereo vision in a single shot. an actual experimental situation was simulated and the accuracy is evaluated. in addition, a prototype system was implemented and the shape of the real object was measured.
connected rotation-invariant size-shape granulometries. in this paper we describe a rotation-invariant multi-scale morphological method for texture analysis. compared with existing methods our method has three advantages. first, it can be implemented efficiently. furthermore, our method can be used for the computation of size and strict shape attributes, which we use for the computation of 2-d size-shape pattern spectra. finally, our method is rotation-invariant. although the latter can also be approximated by morphological methods by using structuring elements at different angles, this tends to be computationally intensive.
video synchronization based on co-occurrence of appearance changes in video sequences. this paper presents a method for synchronizing multiple cameras from only the images captured by the cameras, assuming that they are not connected to an external clock signal source. it is assumed that the cameras are stationary and take the images of the same scene from various viewpoints, in which there are moving objects such as human in motion. the method uses the appearance changes in an image sequence as a temporal feature and matches two or more sequences by evaluating the correlation among their temporal features. we show through several experiments that the method shows good performance of synchronization in spite of its simplicity. we also present a method for synchronization in sub-frame accuracy and also for adaptively selecting regions suitable for deriving the temporal features. the latter resolves the difficulty with the case where some objects appear in some of the cameras and do not in the rest, which could deteriorate accuracy of the synchronization.
a novel energy minimization criterion for color image segmentation. in this article, we present an unsupervised segmentation algorithm through a multiresolution approach which uses both color and edge information with a quadtree structure, through as well as an iterative minimization process of an energy function. the algorithm has been applied to fruit images in order to distinguish the different areas of the fruit surface in fruit quality assessment applications. due to the unsupervised nature of the method, it can adapt itself to the huge variability of colors and shapes of the regions in fruit inspection tasks.
clustering-based multispectral band selection using mutual information. this work presents the application of a novel technique on dimensionality reduction to deal with multispectral images. a distance based on mutual information is used to construct a hierarchical clustering structure. experimental results show that the method provides a very suitable subset of multispectral bands for pixel classification purposes.
view-based detection of 3-d interaction between hands and real objects. we propose a vision-based method to detect interactions between human hand(s) and real objects. since humans perform various kinds of tasks with their hands, detection of hand-object interactions is useful for building intelligent systems that understand and support human activities. we use a statistical color model to detect hand regions in input images. target objects are dynamically modeled based on their appearances by giving consideration to occlusions by the hand. the appearance model tracks the translation and relative rotation of target objects. this system is useful for recording, indexing and instructing object manipulations and/or hand-object interactions. experimental results show the effectiveness of our method.
audio segmentation and speaker localization in meeting videos. segmenting different individuals in a group meeting and their speech is an important first step for various tasks such as meeting transcription, automatic camera panning, multimedia retrieval and monologue detection. in this effort, given a meeting room video, we attempt to segment individual person's speech and localize them in the video, based on data from a single audio and video source. the segmentation method is driven by audio and enhanced by video cues. we used bayesian information criterion (bic) to segment the feature vector streams and graph spectral partitioning to cluster them. we compare our results with audio based segmentation method and our localization technique with the commonly used mutual information.
probabilistic shape-based image indexing and retrieval. in this paper we present a probabilistic framework for shape-based indexing and retrieval of images. in our framework shape-based features are extracted from each image and then a statistical model of the image is constructed using an effective determininstic method for gaussian mixture modeling. in this way, each image is finally represented as a mixture of gaussians and shape-based similarity between images is computed by measuring the distance between the corresponding mixture distributions. several distance measures are presented and experimentally compared. experimental results on the retrieval of logo images indicate that the method is very effective and exhibits robustness to the presence of various types of edge-related noise in the query image.
structural description of textile and tile pattern designs using image processing. cataloguing pattern and tiling designs using their geometrical features is an old research topic, whose main goal is the synthesis of new designs. but little effort have been made to approach the inverse problem, this is the analysis of a design using image processing techniques. in this paper a set of structural descriptors for automatically classifying designs of textile and tile fabric is proposed. graphic descriptors as parallelogram fundamental, design cluster, design symmetry axes etc.. are properly re-defined in a new framework that, using the theory of symmetry groups, tries to describe the structure of a pattern design. we describe the sequence of operations introduced for the analysis and extraction of these structural descriptors and the methodology used in each stage, devoting special attention to the techniques used in the image segmentation, object extraction, and clustering stages. experimental results with textile patrimony images and tile museum images are also included.
scan-to-xml: automatic generation of browsable technical documents. in this paper we experiment and validate an approach for the automatic generation of browsable technical documents. the application demonstrated in this work is restricted to cutaway diagrams with a particular visual representation. the global approach in which it is integrated is of a far more general interest, however. our principal aim is to automatically generate an xml description of a graphical document that will allow for further use of its content by establishing links within the document or with other documents, thus constructing a corpus of interconnected documents sharing zones of similar content or semantics.
a fast detector of line images acquired by an uncalibrated paracatadioptric camera. we propose a new method to simultaneously detect the images of lines acquired by an uncalibrated paracatadioptric camera and estimate its parameters. this method is very efficient thanks to our new linear formulation of the constraint for the paracatadioptric line images and to some proposed algorithmic improvements. the line images that are straight lines and circular arcs are detected similarly, after being projected to a virtual paraboloid. robust estimation methods are then used to find which detected line images are consistent with the best set of camera parameters. we provide experimental results that demonstrate the efficiency and robustness of the proposed method.
a new linear calibration method for paracatadioptric cameras. we propose a new calibration method for the paracatadioptric cameras using one image of at least three observed lines. this method is based on the geyer & daniilidis [2] one but has two main advantages. first, a geometric distance is used to compute the camera parameters instead of an algebraic distance. second, it allows to deal with lines that are projected to straight lines or to circular arcs in an unified manner. we provide a geometric interpretation of the algorithm: the line images are firstly projected to a virtual paraboloid, then planes are fitted on these projections and their intersection finally provides the camera parameters. thanks to this new formulation, the method is also able to deal very efficiently with outliers. we compare results with existing methods from geyer & daniilidis [2] and from barreto & araujo [3].
nonlinear multiscale graph theory based segmentation of color images. in this paper the issue of image segmentation within the framework of nonlinear multiscale watersheds in combination with graph theory based techniques is addressed. first, a graph is created which decomposes the image in scale and space using the concept of multiscale watersheds. in the subsequent step the obtained graph is partitioned using recursive graph cuts in a coarse to fine manner. in this way, we are able to combine scale and feature measures in a flexible way: the feature-set that is used to measure the dissimilarities may change as we progress in scale. we employ the earth mover's distance on a featureset that combines color, scale and contrast features to measure the dissimilarity between the nodes in the graph. experimental results demonstrate the efficiency of the proposed method for natural scene images.
off-line handwritten textline recognition using a mixture of natural and synthetic training data. in this paper the problem of off-line handwritten cursive text recognition is considered. a method for expanding the set of available training textlines by applying random perturbations is presented. the goal is to improve the recognition performance of an off-line handwritten textline recognizer by providing it with additional synthetic training data. three important issues - quality, variability, and capacity - relatedto this method are discussed, and a basic strategy to make use of the possibility of expanding the training set by synthetic textlines is proposed. it is shown that significant improvement of the recognition performance is possible even when the original training set is large and the textlines are provided by many different writers.
tool wear estimation from acoustic emissions: a model incorporating wear-rate. almost all prior work on modeling the dependence of acoustic emissions on tool wear have concentrated on the effect of wear-level on the sound. we give justification for including the wear-rate information contained in the sound to improve estimation of wear. a physically meaningful model is proposed which results in a hidden markov model (hmm) whose states are a combination of the wear-level and rate and observations are the feature vectors extracted from the sound. we also present an efficient method for picking feature vectors that are most useful for the classification problem.
detecting irregularities in regular patterns. this study compares three different methods designed for detecting irregularities from regular dot patterns. frequency domain information is used to split an original regular pattern into two images: the first image contains the perfect repeating pattern and the second one includes all irregularities in the original image. the methods are based on the fourier transform, but they differ in how they separate or utilize the regular and irregular image parts. performances of these methods are compared, and their strengths and weaknesses are discussed.
human motion signatures: analysis, synthesis, recognition. human motion is the composite consequence of multiple elements, including the action performed and a motion signature that captures the distinctive pattern of movement of a particular individual. we develop a new algorithm that is capable of extracting these motion elements and recombining them in novel ways. the algorithm analyzes motion data spanning multiple subjects performing different actions. the analysis yields a generative motion model that can synthesize new motions in the distinctive styles of these individuals. our algorithms can also recognize people and actions from new motions by comparing motion signaturesand action parameters.
classification probability analysis of principal component null space analysis. in a previous paper [a linear classifier for gaussian class conditional distributions with unequal covariance matrices], we have presented a new linear classification algorithm, principal component null space analysis (pc-nsa) which is designed for problems like object recognition where different classes have unequal and non-white noise covariance matrices. pcnsa first obtains a principal components space (pca space) for the entire data and in this pca space, it finds for each class 'i', and m{i} dimensional subspace along which the class's intra-class variance is the smallest.we call this subspace an approximate null space (ans) since the lowest variance is usually "much smaller" than the highest.a query is classified into class 'i' if its distance from the class's mean in the class's ans is a minimum.in this paper, we discuss the pcnsa algorithm more precisely and derive tight upper bounds on its classification error probability.we use these expressions to compare classification performance of pcnsa with that of subspace linear discriminant analysis (slda)[subspace linear discriminant analysis for face recognition].
experiments on gait analysis by exploiting nonstationarity in the distribution of feature relationships. we consider the use of nonstationarity in the distribution of feature relationships over time for walking gait-based recognition. we statistically model the features of a person by computing the distribution of the relations among the features, rather than the features themselves. theserelational distributions of feature relations are represented as points in a space of probability functions (sopf). our database presently consists of twenty subjects walking out-doors along three different paths at 0° (frontal-parallel), 22° and 45° with respect to the image plane and walking in both directions, left to right and right to left. we performed statistical tests to demonstrate that variations between persons are statistically more significant than the variations due to walking angles and walking directions. we also present identification results on people walking at different directions and different angles.
an improved approach to generating realistic kanji character images from on-line characters and its benefit to off-line recognition performance. this paper proposes a method for generating realistic calligraphic kanji character images from on-line data. the proposed method is an improvement of our former method presented in [1]. our new method can cope also with connected on-line strokes, i.e., stroke number variations, which were not correctly painted in our previous method. the new method decomposes strokes into three different parts (end part, bend part, connecting part), and paints each part according to a prototypical shape assigned to it from a calligraphic stroke shape library.our generated calligraphic off-line images serve two purposes: first, they provide additional training samples for off-line recognition. second, they allow application of off-line methods in on-line recognition. this paper also presents some experiments for these purposes.
an evaluation of face and ear biometrics. face recognition based on principal component analysis is a heavily researched topic in computer vision. the ear has been proposed as a biometric, with claimed advantages over the face. we have applied the pca approach to images of the face and ear using the same set of subjects. testing wass done with three different gallery/probe combinations. for faces we have: 1) probes of same day but different expression, 2) probes of a different day but similar expression, and 3) probes of different day and different expression. analogously, for ears, we have: 1) probes of same day but other ear, 2) probes of a different day but same ear,and 3) probes of different day and other ear. results indicate that the face provides a more reliable biometric than the ear.
accelerating the computation of 3d gradient vector flow fields. in 3d segmentation, a deformable model can be efficiently guided by a gradient vector flow (gvf) field. the computation of a gvf field consists mainly of solving a huge discretized system of elliptic partial differential equations. these discrete equations have several properties that can be utilized to accelerate the process of finding an approximate solution. here, stationary iterative methods, preconditioned conjugate gradient methods, and multigrid methods are considered in order to compute the gvf field at computational times acceptable for interactive 3d segmentation.
biometric hash based on statistical features of online signatures. this paper presents a new approach to generate biometric hash values based on statistical features in online signature signals. whilst the output of typical online signature verification systems are threshold-based true-false decisions, based on a comparison between test sample signals and sets of reference signals, our system responds to a signature input with a biometric hash vector, which is calculated based on an individual interval matrix.especially for applications, which require key management strategies (e.g. e-commerce, smart cards), hash values are of great interest, as keys can be derived directly from the hash value, whereas a verification decision can only grant or refuse access to a stored key. further, our new approach does not require storage of templates for reference signatures, thus increases the security of the system.in our prototype implementation, the generated biometric hash values are calculated on a pen-based pda and used for key generation for a future secure data communication between a pda and a server by encryption. first tests show that the system is actually able to generate stable biometric hash values of the users and although the system was exposed to skilled forgeries, no test person was able to reproduce another subject's hash vector. during tests, we were able to tune the system to a far of 0% at a frr level of 7.05%.
an algorithm for cutting 3d surface meshes. the cutting operation of 3d surface meshes plays an important role in surgery simulators. one of the important requirements for surgical simulators is the faithful representation of interaction paths of a surgical tool. we propose a new strategy for cutting on surface meshes: refinement and separate strategy consisting of the refinement followed by the separation of the refined mesh element.the proposed strategy gives the faithful representation of interaction paths.
motion from focus. based on the triangulation method, the 3d motion of an object can be completely recognized by a stereo camera. however, the question whether or not the 3d motion of an object can be completely recognized by a motionless / fixed monocular camera is the yet-unanswered question. in this paper we propose a method using a motionless monocular camera of which the focus is changed in cycle to recognize the absolute 3d motion of an object.
on the influence of fixing the principal point in frame-by-frame multiplanar calibration. calibrating sequences were a camera moves without zooming is often considered as a pure viewpoint estimation problem. here, we demonstrate that considering varying principal point while keeping the focal length constant allows us to obtain a reprojection error similar to the one obtained with full calibration while imposing existing constraints on the camera (no zooming). then, we propose a robust calibration process which can be used for any scene that contains planar structures. robustness is obtained by estimating independently the principal point position and the viewpoint.
an efficient technique for protein sequence clustering and classification. in this paper, a technique to reduce time and space during protein sequence clustering and classification is presented. during training and testing phase, the similarity score value between a pair of sequences is determined by selecting a portion of the sequence instead of the entire sequence.it is like selecting a subset of features for sequence data sets.the experimental results of the proposed method shows that the classification accuracy (ca) using the prototypes generated/used do not degrade much but the training and testing time are reduced significantly. thus the experimental results indicate that the similarity score need not be calculated by considering the entire length of the sequence for achieving a good ca.even space requirement is reduced during execution phase.we have tested this using k-medians, supervised k-medians and nearest neighbour classifier (nnc) techniques.
automatic detection of intestinal juices in wireless capsule video endoscopy. wireless capsule video endoscopy is a novel and challenging clinical technique, whose major reported drawback relates to the high amount of time needed for video visualization. in this paper, we propose a method for the rejection of the parts of the video resulting not valid for analysis by means of automatic detection of intestinal juices. we applied gabor filters for the characterization of the bubble-like shape of intestinal juices in fasting patients. our method achieves a significant reduction in visualization time, with no relevant loss of valid frames. the proposed approach is easily extensible to other image analysis scenarios where the described pattern of bubbles can be found.
data mining applied to acoustic bird species recognition. in this work we explore the application of data mining techniques to the problem of acoustic recognition of bird species. most bird song analysis tools produce a large amount of spectral and temporal attributes from the acoustic signal. the identification of distinctive features has become critical in resource constrained applications such as habitat monitoring by sensor networks. reducing computational requirements makes affordable to run a classifier on devices with power consumption constraints, such as nodes in a sensor network. experimental results demonstrate that considerable dimensionality reduction can be achieved without significant loss in classification efficiency.
computation of rotation local invariant features using the integral image for real time object detection. we present a framework for object detection that is invariant to object translation, scale, rotation, and to some degree, occlusion, achieving high detection rates, at 14 fps in color images and at 30 fps in gray scale images. our approach is based on boosting over a set of simple local features. in contrast to previous approaches, and to effi- ciently cope with orientation changes, we propose the use of non-gaussian steerable filters, together with a new orientation integral image for a speedy computation of local orientation.
image disocclusion using a probabilistic gradient orientation. in this paper we devise a new method to remove occlusions in an image by using its level-lines. we take into account the error in the computation of their orientation by introducing a field of probabilities for the level-lines orientations. we use second order partial differential equations for this field and the image to interpolate in the occluded part.
noisy text categorization. this work presents categorization experiments performed over noisy texts. by noisy, we mean any text obtained through an extraction process (affected by errors) from media other than digital texts (e.g., transcriptions of speech recordings extracted with a recognition system). the performance of a categorization system over the clean and noisy (word error rate between \sim 10 and \sim 50 percent) versions of the same documents is compared. the noisy texts are obtained through handwriting recognition and simulation of optical character recognition. the results show that the performance loss is acceptable for recall values up to 60-70 percent depending on the noise sources. new measures of the extraction process performance, allowing a better explanation of the categorization results, are proposed.
sociometry based multiparty audio recordings summarization. this paper shows how social network analysis, the study of relational data in specific social environments, can be used to summarize multiparty radio news recordings. a social network is extracted from each recording and it is analyzed in order to detect the role of each speaker (e.g. anchorman, guest, etc.). the role is then used as a criterion to select the segments that are more representative of the recording content. the results show that the length of the recordings can be reduced by more than 90 percent while still preserving most of the information about their content.
offline cursive word recognition using continuous density hidden markov models trained with pca or ica features. this work presents an offline cursive word recognition system dealing with single writer samples. the system is based on a continuous density hiddden markov model trained using either the raw data, or data transformed using principal component analysis or independent component analysis. both techniques significantly improved the recognition rate of the system.preprocessing, normalization and feature extraction are described as well as the training technique adopted. several experiments were performed using a publicly available database. the accuracy obtained is the highest presented in the literature over the same data.
multiple rectangle model for vuildings segmentation and 3d scene reconstruction. this paper introduces a method for automatic extraction of buildings in aerial images. we first present a method based on rectangular buildings, which are the most common constructions. after a rough segmentation, we estimate a criterion of similarity of each region with the best matching rectangle. for buildings of complex shapes, we introduce an iterative way to divide a region in order to optimize its approximation by a set of rectangles. we use a parametric deformable model for refining rectangle size and positions. these rectangles are then used to enhance a 3d realistic reconstruction of the scene including building models.
divide-and-conquer algorithm for creating neighborhood graph for clustering. k-nearest neighbor graph has been used for reducing the number of distance calculations in pnn-based clustering. the bottleneck of the approach is the creation of the graph. in this paper, we develop a fast divide-and-conquer method for graph creation based on algorithm previously used in the closest pair problem. the proposed algorithm is then applied to agglomerative clustering, in which it outperforms previous projection-based algorithm for high dimensional spatial data sets.
a fast and efficient ensemble clustering method. ensemble of clustering methods is recently shown to perform better than conventional clustering methods. one of the drawback of the ensemble is, its computational requirements can be very large and hence may not be suitable for large data sets. the paper presents an ensemble of leaders clustering methods where the entire ensemble requires only a single scan of the data set. further, the component leaders complement each other while deriving individual partitions. a heuristic based consensus method to combine the individual partitions is presented and is compared with a well known consensus method called co-association based consensus. experimentally the proposed methods are shown to perform well.
a pattern synthesis technique with an efficient nearest neighbor classifier for binary pattern recognition. important factors affecting the efficiency and performance of the nearest neighbor classifier (nnc) are space, classification time requirements and for high dimensional data, due to the curse of dimensionality, the training set size should be large. in this paper we propose novel techniques to improve the performance of nnc and at the same time to reduce its computational burden. a compact representation of the training set along with an efficient nnc which does implicit pattern synthesis is presented. a comparison of empirical results is made with relevant methods.
l-dbscan : a fast hybrid density based clustering method. density based clustering techniques like dbscan can find arbitrary shaped clusters along with noisy outliers. a severe drawback of the method is its huge time requirement which makes it a unsuitable one for large data sets. one solution is to apply dbscan using only a few selected prototypes. but because of this the clustering result can deviate from that which uses the full data set. a novel method proposed in the paper is to use two types of prototypes, one at a coarser level meant to reduce the time requirement, and the other at a finer level meant to reduce the deviation of the result. prototypes are derived using leaders clustering method. the proposed hybrid clustering method called l-dbscan is analyzed and experimentally compared with dbscan which shows that it could be a suitable one for large data sets.
robust local max-min filters by normalized power-weighted filtering. a normalized, power-weighted averaging filter (npf) is a very good approximation to the well-know local maximum and minimum filters along the object edges and offers noise reduction in foreground and background regions. this favorable combination turns out to be very effective in image smoothing, edges detection and image sharpening. it offers a clear improvement over the existing operators based on true max-min filtering. our filter can be implemented very efficiently by a table lookup (for the power) and two (separable) convolutions.
multi-orientation analysis by decomposing the structure tensor and clustering. the structure tensor yields an excellent characterization of the local dimensionality and the corresponding orientation for simple neighborhoods, i.e. neighborhoods exhibiting a single orientation. we show that we can disentangle crossing structures if the tensor scale is much larger than the gradient scale. mapping the gradient vectors to a continuous orientation representation yields a ½d(d+1)- dimensional feature vector per pixel. clustering of the vectors in this new space allows identification of multiple orientations. each cluster of gradient vectors can be analyzed separately using the structure tensor approach. proper clustering yields an unbiased estimate of the underlying orientations.
a statistical shape model without using landmarks. this paper describes the construction of a statistical shape model based on the iterative closest point algorithm. the method does not require manual nor automatic identification of explicit landmarks on example shapes. corresponding features are found by retrieving the nearest points via interpolation along the surface. the application to analyse carpal bone shape renders evidence that the lunate bone occurs in distinct types.
a comparison of techniques for automatic clustering of handwritten characters. this work reports experiments with four hierarchical clustering algorithms and two clustering indices for on-line handwritten characters. the main motivation of the work is to develop an automatic method for finding a set of prototypical characters which would represent well the different writing styles present in a large international database. one of the major obstacles in achieving this goal is the uneven representation of different writing styles in the database. on the basis of the results of the experiments, we claim that a good set of prototypes can be formed from the combined results of the different clustering algorithms. however, the number of clusters cannot be determined automatically but some human intervention is required.
recognition of screen-rendered text. the recognition of screen-rendered text is to our knowledge a yet unaddressed task. it has to be performed e.g. by translation tools which allow users to click on any text on the screen and give a translation. this often requires to capture a screenshot and to perform optical character recognition which is very challenging due to very small and smoothed fonts. this paper presents a method capable of recognizing smoothed and non-smoothed screen-rendered text of very small size which also works for colored fonts on inhomogeneous backgrounds.
an evolutionary approach for the generation of diversiform characters using a handwriting model. in pattern recognition, a large number of diversiform characters is necessary to train/test a handwritten character recognition system. however, it is not easy to collect a large number of natural samples. the artificial diversification of characters has been suggested as one means of collecting a variety of characters [1]. in this paper, we show that a handwriting model can be applied to the diversification of characters. the characters diversified by the model can be used as a database of character images for training/testing purposes. wada amp; kawato's handwriting model [2] is based on an optimal principle and the feature space of the characters includes sets of via-points extracted from actual handwritten characters. the handwriting model can be used to generate a variety of characters by changing via-point information . in this paper, we propose a method for generating a large variety of characters by changing via-point information based on a genetic algorithm and we show that the accuracy of a handwritten character recognition system that uses the characters generated by the proposedmethod as the training data, is equivalent to that of a system composed by using natural data.
adaptive normalization of handwritten characters using gat correlation and mixture models. this paper proposes an adaptive or category-dependent normalization technique for handwritten characters featuring global affine transformation (gat) correlation and mixture models. key ideas are twofold. first, we estimate a probability density function (pdf) of black pixels for each category using mixture models of gaussian distribution functions and the em algorithm. second, we determine optimal, global affine transformation that maximizes a normalized cross-correlation value between a gat-superimposed input pattern and the above-mentioned pdf by the successive iteration method. experiments using the handwritten numeral database iptp cdrom1b show that the entropy of optimally gat-superimposed test samples decreases substantially by more than 20%. we discuss the enhanced normalization ability and the computational complexity of the proposed method.
face tracking in meeting room scenarios using omnidirectional views. the robust localization and tracking of faces in video streams is a fundamental concern for many subsequent multi-modal recognition approaches. especially in meeting scenarios several independent processing queues often exist that use the position and gaze of faces, such as group action- and face recognizers. the costs for multiple camera recordings of meeting scenarios are obviously higher compared to those of a single omnidirectional camera setup. therefore it would be desirable to use these easier to acquire omnidirectional recordings. the present work presents an implementation of a robust particle filter based face-tracker using omnidirectional views. it is shown how omnidirectional images have to be unwarped before they can be processed by localization and tracking systems being invented for undistorted material. the performance of the system is evaluated on a part of the pets-icvs 2003 smart meeting room dataset.
efficient facial component extraction for detection and recognition. in this paper, we present an efficient algorithm for facial component extractions, which are eyes detection and the mouth width measuring, and pose estimation. the algorithm is based on the novel overcomplete wavelet feature template, the support vector machine (svm) classifier, and the wavelet entropy filtering to robustly detect and segment the t-shape face region. the segmented t-shape face region, which is the smallest area enclosed by the face ellipse including eyes and mouth, is used to select the corresponding viewbased classifier for face recognition. the experimental results show that the proposed method is robust against the complex scenes.
abnormal walking gait analysis using silhouette-masked flow histograms. abnormalities of gait patterns can provide telltale signs of the onset or progression of certain diseases. this paper proposes a simple but effective approach to abnormal gait analysis using computer vision techniques. the proposed method starts with the extraction of human silhouettes from input videos and the computation of frame-to-frame optical flows, then motion metrics based on histogram representations of silhouette-masked flows, and finally gait analysis with eigenspace transformation. different from current gait classification and recognition studies, the proposed method deals with another interesting problem, namely not only determining different styles of the same walking action but detecting whether or not it is deviated from usual walking pattern, which is expected as a feasible means to deduce physical conditions of people. experimental results show its promising performance.
colony delineation on image classification. this paper presents a methodology for high resolution image classification and segmentation. the size and information volume of the images, taken by a high resolution digital camera, will be tens to hundreds times as the ones taken by an ordinary ccd camera. in order to speed up the image segmentation process of the large images, we classify the images first by using a low resolution image, then, segment them by a fast segmentation algorithm. the algorithm is studied mainly based on multi-resolution technique and the fusion of edge detection result and similarity segmentation result. by use this methodology, the whole image segmentation process time is reduced by tens' times than traditional segmentation methods. and the accuracy of the image segmentation is not decreased.
online aggregate particle size measurement on a conveyor belt. in order to quickly and accurately estimate average size of densely packed aggregate particles on a moving conveyor belt, a new image processing method is studied. the method consists of two major algorithms, one is a one-pass boundary detection algorithm that is specially designed for the images of densely packed particles (the word "particle" is used in a wide sense), and the other is average size estimation based on image edge density. the algorithms are cooperative. our method has been tested experimentally for different kinds of closely packed particle images which are difficult to detect by ordinary edge detections. the new method avoids delineating and measuring every particle on an image, therefore, is suitable for realtime imaging. it is particularly applicable for a densely packed and complicated particle image sequence.
from blob metrics to posture classification to activity profiling. the development of unobtrusive monitoring systems is important to obtain informative cues of human postures and behaviours for the next generation pervasive home care environment. to this end, this paper applies a set of computationally efficient vision techniques to classify human postures, and consequently, to analyze human behaviours such as fall detection. the method starts with the extraction of human silhouettes, then blob metrics using multiple appearance representations, and finally activity profiling based on frame-by-frame posture classification. a large number of experimental results have demonstrated its validity regardless of its simplicity.
compact representation of multidimensional data using tensor rank-one decomposition. this paper presents a new approach for representing multidimensional data by a compact number of bases. we consider the multidimensional data as tensors instead of matrices or vectors, and propose a tensor rank-one decomposition (trod) algorithm by decomposing nth-order data into a collection of rank-1 tensors based on multilinear algebra. by applying this algorithm to image sequence compression, we obtain much higher quality images with the same compression ratio as principle component analysis (pca). experiments with gray-level and color video sequences are used to illustrate the validity of this approach.
multi-lingual phoneme recognition and language identification using phonotactic information. previous research indicates that automatic language identification systems based on phonotactic information produce the best results compared with other systems based on acoustic or prosodic information. this paper investigates two different approaches that use phonotactic information: parallel phoneme recognition followed by language modeling (pprlm) and multi-lingual prlm. in the pprlm approach, we have modified the system by using four different language models with different discounting methods, including the linear, absolute, good- turning and witten-bell. our results show that the modified pprlm system with the witten-bell discounting outperforms other systems and achieves 75.5% language identification accuracy for the ogits speech corpus.
automatic estimation of 3d transformations using skeletons for object alignment. an algorithm for automatic estimation of 3d transformations between two objects is presented in this paper. skeletons of the 3d objects are created using a fully parallel thinning technique, feature point pairs (land markers) are automatically extracted from skeletons, and a least squares method is applied to solve an over determined linear system to estimate the 3d transformation matrix. experiments show that this method is quite accurate when the translations and rotation angles are small, even when there is some noise in the data. the estimation process requires about 2 seconds on an intel centrino laptop with 512 mb memory, for a complex model with about 37,000 object points and 500 object points for its skeletons.
captcha challenge tradeoffs: familiarity of strings versus degradation of images. it is a well documented fact that, for human readers, familiar text is more legible than unfamiliar text. current-generation computer vision systems also are able to exploit some kinds of prior knowledge of linguistic context: for example, many ocr systems can use known lexica (word-lists, such as of commonly occurring english words) to disambiguate interpretations. it is interesting that human readers can exploit various degrees of familiarity: for example, strings of characters which, while not found in dictionaries, are similar to spelled words: e.g. "pronounceable" strings, or strings made up of frequently occurring character n-grams. in contrast to this, computer vision technologies for exploiting such poorly characterized constraints (absent an explicit, complete lexicon) are not yet well developed. this gap in ability may allow us to design stronger captchas. we measure the familiarity of challenge strings generated by four methods (described by bentley and mallows) and we use the scattertype captcha to degrade challenge images. we report the results of a human legibility trial which supports the hypothesis that more familiar strings are indeed more legible in captchas. our measurements may enable engineering captchas with a more uniform distribution of difficulty by balancing image degradations against familiarity.
performance prediction for multimodal biometrics. sensor fusion is commonly used to improve the detection and recognition performance of a pattern recognition system. in this paper we propose a prediction model to predict the performance of a sensor fusion system. in particular, we answer two questions associated with the performance prediction in a sensor fusion system: (a) given the characteristics of the individual sensors how can we predict the performance of the fusion system? (b) how good the prediction is? we provide the cramer-rao bounds for the prediction model. we carry out experiments on the publicly available database xm2vts that has speech and face data.
combining hmm-based two-pass classifiers for off-line word recognition. for off-line recognition of cursive handwritten word, the intersection between segmentation and recognition is complicated and makes the recognition problem still a challenging task. hidden markov models (hmms) have the ability to perform segmentation and recognition in a single step. in this paper we present an hmm based unsymmetric two-pass modeling approach for recognizing cursive handwritten word. the two-pass recognition approach exploits the segmentation ability of the viterbi algorithm and creates three different hmm sets and carries out two passes of recognition. a weighted voting approach is used to combine results of the two recognition passes. high recognition rate has been achieved for recognizing cursive handwritten words with a lexicon of 1120 words. experiment on nist sample hand print data of ten different writers has also been carried out. the experimental results demonstrate that the two-pass approach can achieve better recognition performance and reduce the relative error rate significantly .
robust modelling of local image structures and its application to medical imagery. a robust modelling method for detecting and measuring isotropic, linear features and bifurcations is described and applied to analysing 2d eletrophoresis and retinal images. features are modelled as a superposition of gaussian functions with the hermite expansion and estimated by a combination of a multiresolution, windowed fourier approach followed by an em type of spatial regression. a penalised likelihood test, the akakie information criteria (aic) is used to select the best model and scale for feature segments. results are shown by using samples on both gel and retinal images.
detecting video texts using spatial-temporal wavelet transform. in this paper we present a novel approach to detect texts in video frames. the approach proposes a spatio-temporal wavelet transform to integrate information of multiple frames rather than a single one. static and dynamic texts are detected separately due to their characteristics in temporal domain. sub-bands decomposed from the original image sequence are combined to form a salience map, which features are extracted from. the approach is verified by experiments with various types of videos. high average recall and precision rates confirm the effectiveness of the proposed method.
mv-map: multiresolution video visualization and summarization on maps. this paper considers visualizing and summarizing image sequences using manifold learning and multiresolution techniques. the images in a video are found usually lying on a significantly low-dimensional manifold, which provides intrinsic information on the video content and formation. the parametrization of the manifold is discovered using a nonlinear subspace method preserving underlying geometry, especially local topology, in the original space. two modes of video roadmaps have been constructed using vmaps [vmap: video visualization and summarization on embedded manifold articulation primitives]. the first discovers the landmark points signaling dramatic changes in video content in the temporal order. the second reveals the global content coherence, without the temporal ordering. to facilitate the browsing of long sequences with complicated contents and structures, we build multiresolution visualization and summarization tools on vmaps. experimental results validate the proposed method. it may find applications to video monitoring and surveillance for interactive exploitation of video contents, intrusion detection, etc.
vision-based traffic measurement system. in this paper, we present a vision-based traffic measurement system. the system automatically counts the vehicles passing through a designated segment of roadway and measures their speeds. based on the obtained number of vehicles and their speeds, a variety of traffic parameters are readily calculated. a number of experiments with the video sequences taken under different weather, illumination and traffic conditions have been conducted. the results have revealed that the proposed system could perform well under different conditions.
enhancing training set for face detection. we present a novel method to enhance training set for face detection with nonlinearly generated examples from the original data. the motivation is from support vector machines (svm) that, for classification problems, examples lying close to class boundary usually have more influence and thus are more informative than those far from the boundary. we utilize a nonlinear technique - reduced set (rs) method and a new image distance metric to generate new examples, and then add them to the original collected database to enhance it. extensive experiments show that the proposed approach has an encouraging performance.
a verification method for viewpoint invariant sign language recognition. viewpoint variance is one of the inevitable problems in vision based sign language recognition. however, most researchers avoid this problem by assuming a special view, especially the front view. in the paper, we propose a verification method for viewpoint invariant sign language recognition. in general, there are two major variances between two video sequences of the same sign: performance variance and viewpoint variance. for small performance variance, dtw can help us eliminate it. when there is only viewpoint variance between two sequences, we can consider the two sequences as obtained synchronously by a stereo vision system. thus, for the current input, we can judge whether the known template is the matched one by verifying whether the two sequences can be considered as obtained by a stereo vision system. our experiments demonstrate the efficiency of the proposed method. furthermore, such verification method can be easily extended to other recognition tasks.
hierarchical content classification and script determination for automatic document image processing. page segmentation and image content classification plays an important role in automatic document image processing with apllications to mixed-type document image compression, form and check reading, and automatic mail sorting. in this paper, we propose an enhanced backgroung-thinning based page segmentation algorithm to process document images rapidly and eliminate some small regions embedded in other regions. we then present a hierarchical approach, which combines cross correlation measure, kolmogorov complexity measure, and a neural network, to classify sub-images into halftones and texts. the approach also achieves high accuracy in text determination using a three-layer feed-forward network, where text region can be classified into chinese or alphabetic character. experimental results on a number of mixed-type document images show the efficiency and effectiveness of our approach.
a dynamic bayesian network approach to multi-cue based visual tracking. visual tracking has been an active research field of computer vision. however, robust tracking is still far from satisfactory under conditions of various background clutter, poses and occlusion in the real world. to increase reliability, this paper presents a novel dynamic bayesian networks (dbns) approach to multi-cue based visual tracking. the method first extracts multi-cue observations such as skin color, ellipse shape, face detection, and then integrates them with hidden motion states in a compact dbn model. by using particle-based inference with multiple cues, our method works well even in background clutter without the need to resort to simplified linear and gaussian assumptions. the experimental results are compared against the widely used condensation and kf approaches. our better tracking results along with ease of fusing new cues in the dbn framework suggest that this technique is a fruitful basis to build top performing visual tracking systems.
tensor discriminant analysis for view-based object recognition. in this paper, we use a general mth order tensor discriminant analysis approach [11] for view based object recognition. this method is an extension of the 2d image coding technique [10] to general mth order tensors for discriminant analysis, and has good convergence property. we demonstrate the performance advantages of this approach over existing techniques using experiments on the coil-100 and the eth-80 datasets. specifically, our experimental results on eth-80 show the particular strength of this tensor discriminant analysis method when only a small number of training samples with big intra-class variation are available.
an efficient algorithm for fingerprint matching. this paper proposes novel topology-based algorithms for fingerprint matching. three major aspects of fingerprint matching are considered: local matching, tolerance to deformation and global matching. the approach improves both the accuracy and the speed of fingerprint identification. computational geometry methods including delaunay triangulation and spatial interpolation are used. the proposed methods are able to efficiently deal with the distortions of fingerprints. experimental results confirm that the algorithms presented are effective and more efficient compared to other fingerprint matching algorithms.
palmprint identification using boosting local binary pattern. local binary pattern (lbp) is a powerful texture descriptor that is gray-scale and rotation invariant [3]. because texture is one of the most clearly observable features in low-resolution palmprint images, we think local binary pattern based features are very discriminative for palmprint identification. in this paper, we propose a palmprint identification approach using boosted local binary pattern based classifiers. the palmprint area is scanned with a scalable subwindow from which local binary pattern histograms [4] are extracted to represent the local features of a palmprin image. the multi-class problem is transformed into a two-class one of intra- and extraclass by classifying every pair of palmprint images as intra-class or extra-class ones[19]. we use the adaboost[18] algorithm to select those sub-windows that are more discriminative for classification. weak classifiers are constructed based on the chi square distance between two corresponding local binary pattern histograms. experiments on the ust-hk palmprint database show competitive performance.
probabilistic relaxation using the heat equation. in this paper a new formulation of probabilistic relaxation labeling is developed using the theory of diffusion processes on graphs. according to this picture, the label probabilities are given by the state-vector of a continuous time random walk on a support graph. the state-vector is the solution of the heat equation on the support-graph. the nodes of the support graph are the cartesian product of the object-set and label-set of the relaxation process. the compatibility functions are combined in the weight matrix of the support graph. the solution of the heat-equation is found by exponentiating the eigensystem of the laplacian matrix for the weighted support graph with time. we demonstrate the new relaxation process on a feature correspondence matching problem abstracted in terms of relational graphs.
a new attempt to gait-based human identification. vision-based human identification at a distance has attracted more attention recently. this paper makes a simple but efficient attempt to gait recognition. for each image sequence, animproved background subtraction procedure is first used to accurately extract spatial silhouettes of a walker from the background; then, eigenspace transformation to time-varyingsilhouette shapes is performed to realize feature extraction; the nearest neighbor classifier using spatio-temporal correlation or the normalized euclidean distance measure is finally utilized in the lower-dimensional eigenspace for recognition, and some additional personalized physical properties are selected for the validation of final decision. experimental results on a small database show that the proposed algorithm has an encouraging recognition rate with relatively lower computational cost.
a new approach for fractal image compression on a virtual hexagonal structure. in this paper, we propose a fractal image compression method on a virtual hexagonal image structure by adopting fisher's basic method on the traditional square image structure. the modification on the definition of range block and domain block is implemented in order to utilize the enhanced image structure. the results of the proposed approach applied to testing images are analyzed and higher fidelity is obtained. the further research directions are discussed.
multi-view face detection under complex scene based on combined svms. a single face classifier has difficulty in detecting multi-view faces under real and complex scenes due to various poses, cluttering environment and small size of faces.in this paper, we propose a novel combination of svms to detect multi-view faces, using both cascading and bagging methods. in our method, the faces are divided into seven views. each of them models a typical pose under complex scenes. by the modified bootstrap method applied in our method, a cascade of svms are constructed to quickly select face candidates from image with expected accuracy.bagging of different svms can further eliminate the false detections that are difficult to handle by single svm.such combination of svms can effectively detect multi-view faces even with large rotation angles and heavy shadow.the experiment results show better accuracy and generalization performance over single classifier.
segmentation of the left ventricle from cardiac mr images based on degenerated minimal surface diffusion and shape priors. segmentation of cardiac mr images is a hot topic in the community of medical image analysis and remains one of the open problems. in this study, we address the segmentation of 2d cardiac mr images based on gradient vector flow snake and make three contributions: firstly, the degenerated minimal surface gvf is proposed, this new flow outperforms the original one referring to boundary preserving; secondly, the shape of the left ventricle is taken into account and a shape based energy for the snake model is adopted, with this energy, the snake contour can conquer the unexpected local minimum stemming from image inhomogeneity and the final results could depend much less on the initial contour. in order to extract the epicardium, a novel approach is developed to generate the desired external force. this new external forces can overcome the demerits of the gvf force directly derived from the usual edge map and maintains the epicardium boundaries even if the contrast between the myocardium and neighbor organs is very low, taking the endocardium contour as initialization, the snake can capture the epicardium fast and accurately. the proposed strategy is also validated experimentally.
a novel video caption detection approach using multi-frame integration. captions in videos often play an important role in video information indexing and retrieval. in this paper, we present a novel video caption detection approach. we first apply a new multiple frames integration (mfi) method to minimize the variation of the background of the image. a time-based minimum (or maximum)pixel value search is employed and sobel edge map is used to determine the mode of search. then block-based text detection is performed, i.e. a small window is used to scan the image and classified as text or non-text, using sobel edges as features. we use a two-level pyramid to detect various text sizes. finally, we present a new iterative text line decomposition method and accurate text bounding boxes are extracted from candidate text areas. experimental result shows that the proposed approach achieves a high precision and recall.
automatic alignment of high-resolution nmr spectra using a bayesian estimation approach. nuclear magnetic resonance (nmr) spectral analysis has recently become one of the major means for the detection and recognition of metabolic changes of disease state, physiological alteration, and natural biological variation. for the pattern recognition tasks in which two or more nmr spectra need to be compared, it is critical to properly align the spectra for the subsequent pattern recognition analysis. previous spectral alignment methods do not consider any baseline intensity variation between the spectra and disregard the effect of noise. here we formulate the spectra alignment problem in a bayesian statistical framework, which allows us to simultaneously and efficiently estimate the spectral shift and the baseline intensity variation in the existence of independent additive noise. experimental results with real high-resolution nmr spectral data from human plasma demonstrate the effectiveness and robustness of the proposed approach.
bilateral two dimensional linear discriminant analysis for stereo face recognition. a new method called two-dimensional fisher discriminant analysis (2d-fda) is proposed to deal with the small sample size (sss) problem in lda based face recognition. then appearance and depth information are combined to improve face recognition rate. different from the conventional 1d-fda (pca plus lda) approaches, 2d-fda is based on 2d image matrices rather than column vectors so the image matrix does not need to be transformed into a long vector before feature extraction. the advantage arising in this way is that the sss problem does not exist any more because the between-class and withinclass scatter matrices constructed in 2d-fda are both of full-rank. it was verified that 2d-fda outperforms 1d fda.
characteristic line of planar homography matrix and its applications in camera calibration. in this paper, we employ the concept of characteristic line to show some useful properties of planar homography matrix. these properties relate the characteristic line of a planar homography matrix with euler angles of the planar pattern. based on the characteristic line, a new method of linear camera calibration is proposed and a strategy to select poses of planar pattern during taking calibration images is suggested. this strategy can help ensure accuracy of calibration. experiment results including both simulated data and real images validate the method and strategy.
adaptive persistence utilizing motion compensation for ultrasound images. persistence, also called temporal averaging, takes the weighted average between successive image frames to reduce the ultrasound speckle noise. conventional methods apply persistence coefficients as a function of two image pixels at the same location of two successive frames that always make structure blurring during tissue movement. in this paper we apply the motion analysis technique in a way of compensating the internal tissue motions to have accurate image registration such that the persistence works at the right spatial positions without blurring the tissue structure. to meet the real-time requirement of ultrasound imaging, we use the sum-absolute-difference based block matching method for local motion estimation, followed by motion dependent persistence averaging. in vivo tests show that our method can increase signalto- noise ratio of imaging and also present better edge differentiation in structure regions.
pattern recognition and computer vision for mineral froth. this paper presents a windows based system for image analysis and computer vision of mineral froth. to make the system work efficiently both in laboratory and in the plant, the main content of the system consists of image acquisition, image processing, froth (bubble) delineation, froth analysis and modeling, and interface between different computers in use. hundreds of functions for froth analysis and statistics are included in the system, especially in the froth delineation part. a number of newly-developed algorithms can delineate bubbles with high accuracy and high speed.
topological localization based on salient regions in unknown environments. this paper presents a new topological localization system for mobile robot navigation based on salient visual regions. these salient regions are obtained by computing the opponencies of color and texture among multi-scale image spaces. then they are organized to construct the vertex of topological map using hidden markov model. so localization problem can be transformed to the evaluation problem of hmm. in our system, the topological map of environment can be created online and the robot locates itself concurrently. experiments show that higher ratio of vertex recognition, that is localization, is obtained. and our system can guarantee mobile robot navigation safely in unknown environments.
fingerprint minutiae matching based on coordinate system bank and global optimum alignment. minutiae pattern remains a widely used representation of a fingerprint. the research on minutiae matching never stops due to its complexity and intractability. in this paper, an efficient fingerprint minutiae matching algorithm is proposed. to obtain reliable reference minutiae pairs, the bank of coordinate systems is introduced. the coordinate systems bank is derived from the original minutiae features and applied to get more useful information about the minutiae. to improve the accuracy of minutiae matching, a global optimum alignment approach is developed, which is targeted on the alignment of the set of reference minutiae pairs. experimental results show that this algorithm achieves excellent performance with high matching speed and high matching reliability.
video local pattern based image matching for visual mapping. image matching plays an important role in visual mapping, a critical task of vision based mobile robot navigation. based on the observation that the visual content in these video sequences generally changes in a slow and continuous mode, a concept of "video local pattern" is proposed to model each video frame, which is defined as a set of frames that are visuallysimilar and temporally-adjacent to that frame. instead of manually labelling, a tracking based method is developed to automatically detect the local pattern for each frame. a model is then estimated from a local pattern, and the matching of images is performed by comparing these models. experimental results demonstrated its improvement over that comparing individual frames.
tensor voting toward feature space analysis. in this paper, a general technique is proposed for the analysis of multi-dimensional feature space. the basic computational module of the technique is the tensor voting theory, which was formerly used for structure inference from sparse data. we analyze the methodology of tensor voting systematically. its relation to kernel density estimation and mean shift is also established, based on what the utilities for two fundamental analyses of feature space, density estimation and mode detection, are discussed. algorithms for two low-level vision tasks, discontinuity preserving smoothing and motion layer inference, are described as applications of tensor voting. several experimental results illustrate its excellent performance.
automatic lipreading with limited training data. speech recognition solely based on visual information such as the lip shape and its movement is referred to as lipreading. this paper presents an automatic lipreading technique for speaker dependent (sd) and speaker independent (si) speech recognition tasks. since the visual features are derived according to the frame rate of the video sequence, spline representation is then employed to translate the discrete-time sampled visual features into continuous domain. the spline coefficients in the same word class are constrained to have similar expression and can be estimated from the training data by the em algorithm. in addition, an adaptive multi-model approach is proposed to overcome the variation caused by different speaking style in speaker-independent recognition task. the experiments are carried out to recognize the ten english digits and an accuracy of 96% for speaker dependent recognition and 88% for speaker independent recognition have been achieved, which shows the superiority of our approach compared with other classifiers investigated.
real-time multi-view face detection and pose estimation in video stream. technologies for real-time multi-view face detection from video streams are indispensable to video content- based retrieval systems and video surveillance systems.. in this paper, we proposed a solution for real-time multi-view face detection and pose estimation in video stream. integrating both asymmetric and symmetric rectangle features, adaboost learning algorithm and pyramid like architecture is employed. asymmetric rectangle features (arfs) are inherited from symmetric rectangle features (srf) to reasonably interpret asymmetric gray distribution in profile face image. pose estimation for multi-view faces are brought out by view-based weighting algorithm (vbwa). our primary experiments demonstrated that the system achieved high accuracy and high speed to detect both front and profile faces with their pose information from soccer video streams.
a minimum sphere covering approach to pattern classification. in this paper we present a minimum sphere covering approach to pattern classification that seeks to construct a minimum number of spheres to represent the training data and formulate it as an integer programming problem. using soft threshold functions, we further derive a linear programming problem whose solution gives rise to radial basis function (rbf) classifiers and sigmoid function classifiers. in contrast to traditional rbf and sigmoid function networks, in which the number of units is specified a priori, our method provides a new way to construct rbf and sigmoid function networks that explicitly minimizes the number of base units in the resulting classifiers. our approach is advantageous compared to svms with gaussian kernels in that it provides a natural construction of kernel matrices and it directly minimizes the number of basis functions. experiments using real-world datasets demonstrate the competitiveness of our method in terms of classification performance and sparsity of the solution.
a method for document zone content classification. this paper describes an algorithm to classify each given document zone into one of nine classes and provides a protocol for its performance evaluation. the classification scheme uses an optimized binary decision tree and viterbi algorithm for hmm to find the optimal solution. our algorithm was trained and tested on a total of 24,177 zones within the 1600 images from uwcdrom iii database. its accuracy rate is 98.45% with a mean false alarm rateof 0.50%
face recognition using optimal non-orthogonal wavelet basis evaluated by information complexity. detecting and recognizing face images automatically is a difficu lt task due to the variability of illumination, presentation angle, face expression and other common problems of machine vision. in this paper, we represent face images as combinations of 2-d gabor wavelet basis which are non-orthogonal. genetic algorithm (ga) is used to find an optimal basis derived from a combination of frequencies and orientation angles in the 2-d gabor wavelet transform. instead of using the widely used within and between class scatter evaluation as the fitness function in ga, we use entropy to measure the information complexity of the wavelet transform. compared to the well-known "eigenface" algorithm which represents face images based on an orthogonal basis, this gabor wavelet representation with optimal basis can provide a more accurate and effic ient projection scheme and therefore a better classification result.
kernel fisher discriminant analysis for palmprint recognition. in this paper, a method for palmprint recognition, kernel fisher discriminant analysis (kfda), is proposed. the method introduces kfda to represent palmprint features for palmprint recognition. in the paper, a device without fixed peg is developed to capture palmprint images. because the movement, the rotation and the stretching of hands are uncontrollable, the features extracted from these palmprint images have a little nonlinearity. classic linear feature extraction approaches, such as pca and flda, only take the 2-order statistics among palmprint image pixels into account, and are not sensitive to higher order statistics of data. therefore, kfda is used to extract higher order relations among palmprint images for future recognition. the experiment results denote that kfda have a better performance than eigenpalms and fisherpalms, especially in case of using a small quantity of training samples.
seamless video editing. this paper presents a new framework for seamless video editing in the gradient domain. the spatio-temporal gradient fields of target videos are modified or mixed to generate a new gradient field, which is usually not integrable. we propose a 3d video integration algorithm, which finds a potential function, whose gradient field is closest to the resulting gradient field in the sense of least squares. the video is reconstructed by solving a 3d poisson equation. we use a fast and accurate 3d discrete poisson solver using diagonal multigrids. a set of gradient operators are defined for user interaction. the resulting video has temporal coherency and no artifacts. we evaluate our algorithm using a variety of examples.
background subtraction based on a robust consensus method. statistical background modeling is a fundamental and important part of many visual tracking systems and of other computer vision applications. in this paper, we presents an effective and adaptive background modeling method for detecting foreground objects in both static and dynamic scenes. the proposed method computes sample consensus (sacon) of the background samples and estimates a statistical model per pixel. numerous experiments on both indoor and outdoor video sequences show that the proposed method, compared with several state-of-theart methods, can achieve very promising performance.
facial components detection with boosting and geometric constraints. an efficient framework utilizing both local features and geometrical distribution for detecting facial components is presented. first, candidate facial components are efficiently collected by cascaded boosting of haar-like features. the candidates may include false positives and multiple detections. then, geometrical distribution of facial components is imposed on the candidates to select the optimal configuration. for simplicity, we suppose full dependence between the components and model it with multivariate gaussian. the effectiveness of the framework is evaluated with experiments.
informative shape representations for human action recognition. shape and kinematics are two important cues in human movement analysis. due to real difficulties in extracting kinematics from videos accurately, this paper proposes to address the problem of human action recognition by spatiotemporal shape analysis. without explicit feature tracking and complex probabilistic modeling of human movements, we directly convert an associated sequence of human silhouettes derived from videos into two types of computationally efficient representations, i.e., average motion energy and mean motion shape, to characterize actions. supervised pattern classification techniques using various distance measures are used for recognition. the encouraging experimental results are obtained on a recent dataset including 10 different actions from 9 subjects.
efficient visual tracking by probabilistic fusion of multiple cues. it has been shown that integrating multiple cues will increase the reliability and robustness of a vision system in situations that no single cue is reliable. in this paper, we propose a method by fusing multiple cues (i.e., the color cue and the edge cue). in contrast to previous work, we propose a novel shape similarity measure which includes the spatial distribution of, the number of, and the gradient intensity of the edge points. we integrate this shape similarity measure with our recently proposed smog-based color similarity measure in the framework of particle filter (pf). experimental results demonstrate the high robustness and effectiveness of our method in handling appearance changes, cluttered background, moving camera, and occlusions.
age simulation for face recognition. in this paper, an automatic age simulation method used for robust face recognition is proposed. we first use a shape and texture vectors to represent a facial image by projecting it in the eigenspace of shape or texture. then we use age function combined with aging way classification to estimate age. and we use estimated age, typical vector creating function and the feature vector of the original test image to generate the synthesized feature vectors at target age. at last we reconstruct the shape and texture in eigenspaces and combine them to synthesize facial image at target age. experiments show that the proposed method can effectively "change” the age of face images, and help to get face recognition result robust to age variation.
bayesian face recognition based on gaussian mixture models. bayesian analysis is a popular subspace based face recognition method. it casts the face recognition task into a binary classification problem with each of the two classes, intrapersonal variation and extrapersonal variation, modeled as a gaussian distribution. however, with the existence of significant transformations, such as large illumination and pose changes, the intrapersonal facial variation cannot be modeled as a single gaussian distribution, and the global linear subspace often fails to deliver good performance on the complex non-convex data set. in this paper, we extend the bayesian face recognition into gaussian mixture models. the complex intrapersonal variation manifold is learnt by a set of local linear intrapersonal subspaces and thus can be effectively reduced. the effectiveness of the novel method is demonstrated by experiments on the data set from ar face database containing 2340 face images.
improving face recognition by online image alignment. face recognition accuracy is affected by many factors. this paper studies one of the factors, and provides a reliable image alignment for face recognition. for this purpose, a performance metric is extracted from an analysis of face recognition similarity scores. the metric varies with face alignment, and has a relationship with the actual recognition accuracy. our method adjusts face alignment online by selecting an alignment candidate corresponding to the largest performance metric. the experimental results show that the presented method can improve the accuracy and robustness of current face recognition systems.
tracking a variable number of human groups in video using probability hypothesis density. we apply a multi-target recursive bayes filter, the probability hypothesis density (phd) filter, to a visual tracking problem: tracking a variable number of human groups in video. first, we use background subtraction to detect human groups which appear as foreground blobs. the phd filter is implemented using sequential monte carlo methods; and the centroids of the foreground blobs are used as the measurements to update the phd filter. our experimental results show that when human groups appear, merge, split, and disappear in the field of view of a camera, our method can track them correctly.
content-based audio classification using support vector machines and independent component analysis. in this paper, we present a new audio classification system. first, a frame-based multiclass support vector machine (svm) for audio classification is proposed. the accuracy rate has significant improvements over conventional file-based svm audio classifier. in feature selection, this study transforms the log powers of the critical-band filters based on independent component analysis (ica). this new audio feature is combined with mel-frequency cepstral coefficients (mfccs) and five perceptual features to form an audio feature set. the superiority of the proposed system has been demonstrated via a 15-class sound database with a 91.7% accuracy rate.
incorporating prior knowledge into svm for image retrieval. svm based image retrieval suffers from the scarcity of labelled samples. in this paper, this problem is solved by incorporating prior knowledge into svm. firstly, some prior knowledge of image retrieval is discussed and constructed. after that, the knowledge is incorporated into svm optimization as a constraint, and a new knowledge-based target function is formulated. based on this, a framework of image retrieval with knowledge based svm is proposed. experimental results demonstrate that the proposed method can effectively improve the learning and retrieval performance of svm, especially when the number of labelled samples is small.
automatic sports video genre classification using pseudo-2d-hmm. building a generic content-based sports video analysis system remains a challenging problem because of the diversity in sports rules and game features which makes it difficult to discover generic low-level features or high-level modeling algorithms. one possible alternative is to first classify the sports genre and then apply specific sports domain knowledge to perform analysis. in this paper we describe a multi-level framework to automatically recognize the genre of the sports video. the system consists of a pseudo-2d-hmm classifier using low-level visual/audio features to evaluate the video clips. the experimental results are satisfactory and extension of the framework to a generic sports video analysis system is being implemented.
efficient topological localization using orientation adjacency coherence histograms. this paper describes an efficient vision-based global topological localization approach that uses a coarse-tofine strategy. orientation adjacency coherence histogram (oach), a novel image feature, is proposed to improve the coarse localization. the coarse localization results are taken as inputs for the fine localization which is carried out by matching harris-laplace interest points characterized by the sift descriptor. computation of oachs and interest points is efficient due to the fact that these features are computed in an integrated process. we have implemented and tested the localization system in real environments. the experimental results demonstrate that our approach is efficient and reliable in both indoor and outdoor environments.
level set methods, distance function and image segmentation. in the study of level set methods, several significant problems were neglected all along, such as the existence, uniqueness and singularities of level set methods. in this article we give the proof that in a neighborhood of the initial zero level set, for the level set equations with the restriction of distance function, there exists a unique solution, which must be the signed distance function with respect to the evolving surface. we also present the analysis of singular points' effect on level set evolution and give an adaptive narrow banding algorithm. the detailed numerical analysis and a simplified definition for singular points are presented. we give an adaptive narrow banding algorithm, which avoids the singular points and is proved to be robust and efficient in segmentation of ct data and synthesized images.
kernel sample space projection classifier for pattern recognition. we propose a new kernel-based method for pattern recognition. support vector machine (svm), principal component analysis (pca), and fisher discriminant have been extended to kernel based methods and they achieve better performance. in this paper, we propose kernel sample space projection classifier (ksp) for pattern recognition. in ksp, an unknown input pattern is discriminated by comparing the norms onto kernel sample spaces which are spanned by sample vectors mapped to a high dimensional feature space by mercer kernel function. in this paper, we provide a closed form of our method and show its advantages by experimental results of the recognition problem using handwritten digit database "mnist" and some two-class classification problems. finally we compare it with other methods from several points of view.
non-linear wiener filter in reproducing kernel hilbert space. wiener filters are used widely for inverse problems. from an observed signal, a wiener filter provides the best restored signal with respect to the square error averaged over the original signal and the noise among linear operators. we introduce the non-linear wiener filter, which is a kernel-based extension of the wiener filter. when the kernel method is applied to the wiener filter directly, the dimensions of the space where the calculation has to be done is very large since noise samples have to be used. we provide a realistic solution using the first order approximation. moreover, we provide the experimental results to demonstrate the advantages of this method.
planar structure based registration of multiple range images. in this paper, we describe the method for aligning multiple range images given by a range finder. especially we will use range images of inside and outside of buildings which contain many planar structures. in our method for registration of range images, we consider not only 3d positions of range data but normal vectors of planes in the scene in order to refine the icp (iterative closest point) algorithm. first, we extract planes of range images in order to calculate normal vectors of planes in the scene. then, we estimate the motion parameters that are composed of a rotation matrix and a translation vector using our refined icp algorithm. we present results that demonstrate our approach's ability to align range images more accurately and faster than the standard icp algorithm.
motion prediction using vc-generalization bounds. this paper describes a novel application of statistical learning theory (slt) for motion prediction. slt provides analytical vc-generalization bounds for model selection; these bounds relate unknown prediction risk (generalization performance) and known quantities such as the number of training samples, empirical error, and a measure of model complexity called the vc-dimension. we use the vc-generalization bounds for the problem of choosingoptimal motion models from small sets of image measurements (flow ). we present results of experiments on image sequences for motion interpolation and extrapolation; these results demonstrate the strengths of our approach.
unsupervised segmentation using gabor wavelets and statistical features in lidar data analysis. in this paper, we address issues in segmentation of remotely sensed lidar (light detection and ranging) data. the lidar data, which were captured by airborne laser scanner, contain 2.5 dimensional (2.5d) terrain surface height information, e.g. houses, vegetation, flat field, river, basin, etc. our aim in this paper is to segment ground (flat field) from non-ground (houses and high vegetation) in hilly urban areas. by projecting the 2.5d data onto a surface, we obtain a texture map as a grey-level image. based on the image, gabor wavelet filters are applied to generate gabor wavelet features. these features are then grouped into various windows. among these windows, a combination of their first and second order of statistics is used as a measure to determine the surface properties. the test results have shown that ground areas can successfully be segmented from lidar data. most buildings and high vegetation can be detected. in addition, gabor wavelet transform can partially remove hill or slope effects in the original data by tuning gabor parameters.
digital image restoration by exposure-splitting and registration. with the explosion of digital imaging systems, high image noise levels, particularly motion blur and sensor noise, limit applications of mobile cameras. in this paper, a novel restoration approach is developed. by uniformly splitting the exposure time and averaging the multiple under-exposed captures, a single image is obtained, in which both types of noise are mitigated. comprehensive experiments demonstrate successful image restoration under various exposure conditions. exposure-splitting is further optimized to fully recover the image quality under severe motion blur. this technique can be easily implemented into contemporary digital imaging systems.
fingerprint verification based on multistage minutiae matching. this paper proposes a novel and distortion-tolerant fingerprint verification technique based on multistage minutia matching. in the first stage, the local similarities of minutiae between two fingerprints are evaluated by matching their local orientation fields and local minutiae topologic structures. in the second stage, the top 5 minutia pairs obtained in the first matching stage are used as the reference minutiae pairs to align two minutia sets, and a set of matched minutia pairs is obtained by matching the aligned two minutia sets. in the third stage, the set of matched pairs obtained in the second stage are matched again by matching two global topologic structures constructed based on the set of matched pairs. the final matching score is obtained based on the set of matched pairs obtained in the second matching stage and the separate matching scores calculated in three stages. experiments on database of fvc2002 show that this fingerprint matching technique is effective.
specification of image acquisition parameters for stereo panoramas. the specification of image acquisition parameters needs to be in accordance with given constraints defined by application requirements, the architecture of the camera, and specifications of the targeted 3d scenes. this paper proposes a novel approach for specifying acquisition parameters at image acquisition time to ensure high-quality stereo panoramas. our approach satisfies commonly demanded application requirements such as: proper scene composition in resultant images; adequate sampling at a particular scene distance; and desired stereo quality (i.e. depth level resolution) over a diversity of scenes of interest. previous studies have paid great attentions on how proposed stereo panorama imaging models/methods support the epipolar geometry constraint and system realizations. the image acquisition parameter assignment problem has not yet been dealt with in these studies. the lack of guidance in specifying image acquisition parameters affects the validity ofresults for any subsequent processes.
the design of a stereo panorama camera for scenes of dynamic range. existing stereo panorama cameras do not allow controllability of pictorial/scene composition and stereo acuity (depth levels) over dynamic 3d scene ranges. we specify the design of such a camera allowing this type of flexibility. previous approaches to design panorama cameras even lack studies with respect to this important aspect, while other design issues such as epipolar geometry, optics optimization, or realization-oriented approximations have been investigated. without incorporating the controllability into stereo panorama camera design, the poor quality of produced stereo panoramas is foreseeable (e.g. incoherence,cardboard-effect, dipopia etc).the paper proposes a solution to incorporate controllability into previously discussed [3, 8, 7, 5] stereo panorama camera models. by using a stereo panorama camera equipped with the designed camera parameters according to our solution, the desired/expected pictorial composition and stereo acuity in resultant stereo panoramas can be en-sured.
robust face recognition under lighting variations. in this paper, we propose a new face recognition algorithm based on the matching of relative image gradient magnitudes between images. the recognition algorithm first uses a face localization procedure to provide rough face regions under different lighting conditions, followed by an iterative optimization procedure for precise face matching. both our face localization and matching procedures are based on matching relative image gradient to be robust against lighting variations. then a robust face similarity measure based on comparison of relative image gradients is used to determine the face recognition results. the face localization step finds some candidate poses of the face in the image through a fast k-nn search of the best match of the relative gradient features from the database of training feature vectors, which are obtained through image synthesis. after the face images are aligned, the face similarity measure is computed from the normalized correlation between the relative gradients. experimental results are shown to demonstrate its robust recognition performance under different lighting conditions.
a hybrid som-svm method for analyzing zebra fish gene expression. microarray technology can be employed to quantitatively measure the expression of thousands of genes in a single experiment. it has become one of the main tools for global gene expression analysis in molecular biology research in recent years. the large amount of expression data generated by this technology makes the study of certain complex biological problems possible, and machine learning methods are expected to play a crucial role in the analysis process. we present our results from integrating a self-organizing maps (som) and a support vector machine (svm) for the analysis of the various functions of zebra fish genes based on their expression. we discuss how som can be used as a data-filtering tool to improve the classification performance of the svm on this data set.
markov chain monte carlo data association for merge and split detection in tracking protein clusters. tagging and tracking protein molecules with the help of laser scanning confocal microscope (lscm) are a key to better understanding of proteomics in diverse aspects. one challenge of tracking multiple green fluorescent protein (gfp) clusters is how to deal with the interaction between multiple objects, namely splitting and merging. in this paper, we propose a framework to track multiple gfp clusters merge and split by using markov chain monte carlo data association (mcmcda) method combined with asymmetric region matching strategy. the experimental results show that the method is promising.
remote sensing image fusion on gradient field. this paper presents two methods to fuse a low spatial resolution multispectral image and a high spatial resolution panchromatic one to produce a new multispectral image with high spatial resolution. first, the poisson fusion method is developed based on minimizing the gradient difference between the synthesized image and the panchromatic image with boundary conditions sampled from the multispectral image. the fusion result can therefore be achieved by solving the poisson equation with dirichlit boundary conditions. secondly, an optimal fusion technique, which minimizes the gradient difference and the color difference with respect to the panchromatic and multispectral images respectively is given and the result is induced by an iterative optimization algorithm. both of them can be applied to color composites and individual bands. their advantages of the fidelity to spectral property and the spatial resolution improvement over the hsi, brovey, pca and wavelet transform are convincingly demonstrated in the experiments from visual evaluation and statistical analysis.
an information theoretic approach for next best view planning in 3-d reconstruction. we present an algorithm for optimal view point selection for 3-d reconstruction of an object using 2-d image points. since the image points are noisy, a kalman filter is used to obtain the best estimate of the object's geometry. this kalman filter allows us to efficiently predict the effect of any given camera position on the uncertainty, and therefore quality, of the estimate. by choosing a suitable optimization criterion, we are able to determine the camera positions which minimize our reconstruction error. we verify our results using two experiments with real images: one experiment uses a calibration pattern for comparison to a ground-truth state, the other reconstructs a real world object.
fast object and pose recognition through minimum entropy coding. we present a pattern recognizer to classify a variety of objects and their pose on a table from real world images. learning of weights in a linear discriminant is based on estimating the relative information contributed by a set of features to the final decision. evaluation of the discriminant is very fast, allowing for about three decisions per second on datasets without segmentation difficulties like the coil-100 database. experiments on that database yield high recognition rates and good generalisation over pose.
mixing spectral representations of graphs. generative models are well known in the domain of statistical pattern recognition. typically, they describe the probability distribution of patterns in a vector space. the individual patterns are defined by vectors and so the individual features of the pattern are well defined. in contrast, very little has been done with generative models of graphs. graphs are not naturally represented in a vector space since there is no natural labelling of the vertices of the graphs - different labellings lead to different representations of the graph structure. because of this, simple statistical quantities such as mean and variance are difficult to define for a group of graphs. while we can define statistical quantities of individual edges, it is not so straightforward to define how sets of edges in graphs are related. the spectral decomposition of a graph can be used to extract information about the relationship of edges and parts in a graph. in this paper we look at the problem of mixing graphs by using the spectral representation of a graph as an intermediate step. the spectral representation allows us to mix different structural features from each of the graphs to create new combinations. we can also define an averaging process on the spectral representations which generates a graph close to the graph median.
reconstruction of spheres using occluding contours from stereo images. this paper discusses an efficient way of reconstructing spheres from the occluding contours of two views. it takes into consideration, the geometric properties of the system and uses frontier points as additional data. this algorithm is especially useful for applications where the objects to be modelled are known to resemble spheres and where speed is of importance. it is developed for fruit sorting applications where the processing has to be done in real-time.
generalized pattern spectra sensitive to spatial information. morphological pattern spectra computed from granulometries are frequently used to classify the size classes of details in textures and images. an extension of this technique, which retains information on the spatial distribution of the details in each size class is developed. algorithms for computation of these spatial pattern spectra for a large number of granulometries on binary images are presented.
probabilistic automatic red eye detection and correction. in this paper we propose a new probabilistic approach to red eye detection and correction. it is based on stepwise refinement of a pixel-wise red eye probability map. red eye detection starts with a fast non red eye region rejection step. a classification step then adjusts the probabilities attributed to the detected red eye candidates. the correction step finally applies a soft red eye correction based on the resulting probability map. the proposed approach is fast and allows achieving an excellent correction of strong red eyes while producing a still significant correction of weaker red eyes.
alignment of multiple non-overlapping axially symmetric 3d datasets. uknown to us, an axially-symmetric surface is broken into disjoint pieces along a set of break-curves, i.e., the curves along which the surface locally breaks into two pieces. a subset of the pieces are available and for each of them we obtain noisy 3d measurements of its surface and break-curves. using the piece measurements and knowledge of which pieces share a common break-curve, we propose a stochastic method for automatically estimating the unknown axially-symmetric global surface. surface and break-curve estimation is then an alignment problem where we must estimate the unknown axially-symmetric surface and break-curves while simultaneously estimating the euclidean transformation that positions each measured piece with respect to the a-priori unknown surface. parameter estimation is implemented as maximum likelihood estimation where we seek the global pot geometry which best explains the measured fragment data. this new approach is robust, fast, and accurate. experimental results are presented which solves an application of interest, specifically the reconstruction of archaeological pots from subsets of their surface pieces.
surface sculpting with stochastic deformable 3d surfaces. this paper introduces a new stochastic surface model for deformable 3d surfaces and demonstrates its utility for the purpose of 3d sculpting. this is the problem of simple-to-use and intuitively interactive 3d free-form model building. a 3d surface is a sample of a markov random field (mrf) defined on the vertices of a 3d mesh where mrf sites coincide with mesh vertices and the mrf cliques consist of subsets of sites. each site has 3d coordinates (x,y,z) as random variables and is a member of one or more clique potentials which are functions of the vertices in a clique and describe stochastic dependencies among sites. data, which is used to deform the surface can consist of, but is not limited to, an unorganized set of 3d points and is modeled by a conditional probability distribution given the 3d surface. a deformed surface is a map (maximum a posteriori probability) estimate of the joint distribution of the mrf surface model and the data. the generality and simplicity of the mrf model provides the ability to incorporate unlimited local and global deformation properties. included in our development is the introduction of new data models, new anisotropic clique potentials, and cliques which involve sites that are spatially far apart. other applications of these models are possible, e.g., stereo reconstruction.
modelling of 2d gel electrophoresis images for proteomics databases. an image modelling technique, based on the use of hermite functions and a multiresolution image alignment algorithm, is described and applied to the problem of analysing 2d electrophoresis images of biological samples. after a brief description of the principles underlying the model, its use is illustrated on some images of samples. the model forms the core of an image analysis and database system currently being developed for proteomics.
storage capacity of the exponential correlation associative memory. in this paper we analyze the pattern storage capacity of the exponential correlation associative memory (ecam). this architecture was first studied by chiueh and goodman &lsqb;3&rsqb; who concluded that, under certain conditions on the input patterns, the memory has a storage capacity that was exponential in the length of the bit-patterns. a recent analysis by pelillo and hancock &lsqb;9&rsqb;, using the kanerva picture of recall, concluded that the storage capacity was limited by 2n&minus;1/n2 patterns. both of these analyses can be criticised on the basis that they overlook the role of initial bit-errors in the recall process and deal only with the capacity for perfect pattern recall. in other words, they fail to model the effect of presenting corrupted patterns to the memory. this can be expected to lead to a more pessimistic limit. here we model the performance of the ecam when presented with corrupted input patterns. our model leads to an expression for the storage capacity of the ecam both in terms of the length of the bit-patterns and the probability of bit-corruption in the original input patterns. these storage capacities agree closely with simulation. in addition, our results show that slightly superior performance can be obtained by selecting an optimal value of the exponential constant.
levenshtein distance for graph spectral features. graph structures play a critical role in computer vision, but they are inconvenient to use in pattern recognition tasks because of their combinatorial nature and the consequent difficulty in constructing feature vectors. spectral representations have been used for this task which are based on the eigensystem of the graph laplacian matrix.however, graphs of different sizes produce eigensystems of different sizes where not all eigenmodes are present in both graphs. in this paper we use the levenshtein distance to compare spectral representations under graph edit operations which add or delete vertices.the spectral representations are therefore of different sizes.we use the concept of the string-edit distance to allow for the missing eigenmodes and compare the correct modes toeach other.we evaluate the method by first using generated graphs to compare the effect of vertex deletion operations.we then examine the performance of the method on graphs from a shape database.
a person and context specific approach for skin color classification. skin color is an important feature of faces. various applications benefit from robust skin color detection. depending on camera settings, illumination, shadows, people's tans, and ethnic groups skin color looks differently, which is a challenging aspect for detecting it automatically. in this paper, we present an approach that uses a high level vision module to detect an image specific skin color model. this model is then used to adapt parametric skin color classifiers to the processed image. this approach is capable to distinguish skin color from extremely similar colors, such as lip color or eyebrow color. its high speed and high accuracy make it appropriate for real time applications such as face tracking and recognition of facial expressions.
diversity/accuracy and ensemble classifier design. for an ensemble of multi-layer perceptrons (mlp), test error is shown in this paper to be well correlated with a diversity/accuracy measure computed between pairs of patterns. a weighted combination that uses the proposed measure to set the weights is shown to be less sensitive to the number of training epochs compared with majority vote.
probabilistic classification between foreground objects and background. tracking of deformable objects like humans is a basic operation in many surveillance applications. objects are detected as they enter the field of view of the camera and they are then tracked during the time they are visible. a problem with tracking deformable objects is that the shape of the object should be re-estimated for each frame. we propose a probabilistic framework combining object detection, tracking and shape deformation. we make use of the probabilities that a pixel belongs to the background, a new object or any of the known objects. instead of using arbitrary thresholds for deciding to which class the pixel should be assigned we assign the pixel based on the bayes criterion. preliminary experiments show the classification error drops to about half the error of traditional approaches.
the hidden birth dates of personalities of genesis. witztum, rips and rosenberg [4] have shown that when the book of genesis is written as two-dimensional arrays with the topology of a cylinder, equidistant letter sequences spelling words with related meaning appear non randomly in close proximity. here we adopt the quantitative tools developed in [4] to measure another type of pattern found in the same book. in the new patterns, equidistant letter sequences spelling out expressions appear in close proximity, on two-dimensional arrays, with conceptually related expressions appearing in the string of letters of the text. we measure the significance of this new type of pattern, using two samples of name-date word pairs, thus similar to the experiment done in [4]. the p-levels obtained were 0.00051 and 0.000046 respectively.
multi-camera real-time depth estimation with discontinuity handling on pc graphics hardware. this paper describes a system for dense depth estimation from multiple color images in real-time.our algorithm runs almost entirely on standard graphics hardware, leaving the main cpu free for other tasks such as i mage capture and higher level recognition. we follow a plane-sweep approach extended by truncated ssd scores, spatially shiftable windows and best camera selection to handle discontinuities.we do not need specialized hardware and exploit the computational power of freely programmable pc gpu hardware.dense depth maps are computed with up to 20 fps.
3d surface reconstruction by self-consistent fusion of shading and shadow features. in this paper a novel framework for three-dimensional surface reconstruction by self-consistent fusion of shading and shadow features is presented. based on the analysis of at least two pixel-synchronous images of the scene under different illumination conditions, this framework combines a shape from shading approach for estimating surface gradients and altitude variations with a shadow analysis that allows for an accurate determination of altitude differences on the surface. as a first step, the result of shadow analysis is used for selecting a consistent solution of the shape from shading reconstruction algorithm. as a second step, an additional error term derived from the fine-structure of the shadow is incorporated into the reconstruction algorithm. this framework is applied to three-dimensional reconstruction of regions on the lunar surface using ground-based ccd images. beyond the planetary science scenario, it is applicable to classical machine vision tasks such as surface inspection in the context of industrial quality control.
binarization of low quality text using a markov random field model. binarization techniques have been developed in the document analysis community for over 30 years and many algorithms have been used successfully. on the other hand, document analysis tasks are more and more frequently being applied to multimedia documents such as video sequences. due to low resolution and lossy compression, the binarization of text included in the frames is a non trivial task. existing techniques work without a model of the spatial relationships in the image, which makes them less powerful. we introduce a new technique based on a markov random field (mrf) model of the document. the model parameters (clique potentials) are learned from training data and the binary image is estimated in a bayesian framework. the performance is evaluated using commercial ocr software.
segmentation of vector fields by critical point analysis: application to brain deformation. mri examinations may be used to monitor the progress of neurological disease. arising structural changes can then be quantified using non-rigid registration procedures. however, the interpretation of the resulting large scale vector fields is difficult without further processing. we propose using contraction mapping to detect critical points such as attractors and repellors in order to characterize deforming areas. with the application to time series images we show that critical points help to get a better perception of the brain deformation and the underlying pathological process.
a software algorithm prototype for optical recognition of embossed braille. braille is a tactile format of written communication for sight-impaired people worldwide. this paper proposes a software solution prototype to optically recognise single sided embossed braille documents using a simple image processing algorithm and probabilistic neural network. the output is a braille text file formatted to preserve the layout of the original document which can be sent to an electronic embosser for reproduction. preliminary experiments have been performed with an excellent recognition rate, where the transcription accuracy is at 99%.
continuous gesture recognition using a sparse bayesian classifier. an approach to recognise and segment 9 elementary gestures from a video input is proposed and it can be applied to continuous sign recognition. an isolated gesture is recognised by first converting a portion of video into a motion gradient orientation image and then classifying it into one of the 9 gestures by a sparse bayesian classifier. the portion of video used is decided by using a sampling technique based on condensation framework. by doing so, gestures can be segmented from the video in a probabilistic manner. experiments show that the proposed method can achieve accuracy around 90% in both isolated and continuous gesture recognition without using special equipment such as glove devices and the system can run in real-time.
adaptive processing of face emotion tree structures. this paper describes a novel recursive neural network for adaptive processing of face emotion tree structures (feets). we proposed to use tree structures to represent gabor face emotion features. we demonstrated the robustness of our proposed system by testing against other well-known classifiers using the cohn-kanade au-coded facial expression database [1]. the system yields an accuracy of about 93% and 57% for known and unknown subjects respectively.
indexing and retrieval of 3d models by unsupervised clustering with hierarchical som. a hierarchical indexing structure for 3d model retrieval based on the hierarchical self organizing map (hsom) is proposed. the proposed approach organizes the database into a hierarchy so that head models are partitioned by coarse features initially and finer scale features are used in lower levels. the aim is to traverse a small subset of the database during retrieval. this is made possible by exploiting the multi-resolution capability of spherical wavelet features to successively approximate the salient characteristics of the head models, which are encoded in the form of weight vectors associated with the nodes at different levels (from coarse to fine) of the hsom. to avoid premature commitment to a possibly erroneous model class, search is propagated from a subset of nodes at each level, which is selected based on a fuzzy membership measure between the query feature vector and weight vector, instead of taking the winner-take-all approach. experiments show that, in addition to efficiency improvement, model retrieval based on the hsom approach is able to achieve a much higher accuracy compared with the case where no indexing is performed.
handwritten digit recognition using multi-layer feedforward neural networks with periodic and monotonic activation functions. the problem of handwritten digit recognition is tackled by multi-layer feedforward neural networks with different types of neuronal activation functions. three types of activation functions are adopted in the network, namely, the traditional sigmoid function, the sinusoidal function and a periodic function that can be considered as a combination of the first two functions. to speed up the learning, as well as to reduce the network size, the extended kalman filter (ekf) algorithm conjunct with a pruning method is used to train the network. simulation results show that periodic activation functions perform better than monotonic ones in solving multi-cluster classification problems such as handwritten digit recognition.
brush writing style classification from individual chinese characters. chinese calligraphic artwork usually contains a few or even a single character. in order to perform automatic brush writing style classification on these kinds of chinese calligraphic images, existing approaches need to be modified because they assume that many characters of the same style exist in the input image. a novel approach is proposed to address the brush writing style classification problem for single-character chinese calligraphic images by combining the texture analysis and the structural information through a set of parameterised ellipses.
improving text classifier performance based on auc. to evaluate the performance of text classifiers, we usually look at measures related to precision and recall, and most machine learning methods are optimized for these measures. in recent year, the use of receiver operating characteristics (roc) graph and its extension area under the roc curve (auc) in gauging classifier performance has attracted much attention from the machine learning community. this measure is especially useful when a data set is imbalanced or when operating characteristics are unknown. some researchers have started investigating the optimization of existing learning model for this new performance criterion. in this paper, we proposed modifications to the well-known weight updating text classifier sleeping-experts (se) for auc optimization. our experiments show that through our new sampling and updating strategy we can improve the classifier both in terms of auc and the traditional performance measures.
blind phase-amplitude modulation classification with unknown phase offset. this paper first discusses the maximum likelihood (ml) classifier for automatic classification of digital modulations. the classifier is optimum for classification of phase-amplitude modulated signals under ideal environment. however, this is not the case in the presence of phase offset owing to inaccurate estimation. in this paper, we propose a novel non-coherent ml classifier to mitigate the effect phase offset. the non-coherent ml classifier adopts a pre-classification phase correction stage through a closed form estimator based on higher order statistics. experimental results show improvement of classification accuracy at reasonable signal to noise ratio.
robust appearance-based tracking using a sparse bayesian classifier. an appearance-based approach to track an object that may undergo appearance change is proposed. unlike recent methods that store a detailed representation of object's appearance, this method allows an appearance feature with a reduced dimension to be used. through the use of a sparse bayesian classifier, high classification and detection accuracy can be maintained even if a reduced feature vector is used. in addition, the classifier allows online-training which enables online-updating of the original classification model and provides better adaptability. experiments show that the method can be used to track targets undergo appearance change due to the change in view-point, facial expression and lighting direction.
lexicon-based browsers for searching in news video archives. in this paper we present the methods and visualizations used in the mediamill video search engine. the basis for the engine is a semantic indexing process which derives a lexicon of 101 concepts. to support the user in navigating the collection, the system defines a visual similarity space, a semantic similarity space, a semantic thread space, and browsers to explore them. the search system is evaluated within the trecvid benchmark. we obtain a top-3 result for 19 out of 24 search topics. in addition, we obtain the highest mean average precision of all search participants.
enhanced canny edge detection using curvature consistency. edges are often considered as primary image artifacts for extraction by low-level processing techniques, and the starting point for many computer vision techniques. as a result, reliable edge detection has long been a research goal. this paper describes initial nvestigations into recovering reliable edges using curvature models. essentially, we modify canny's edge detector, using a curvature consistency process to adjust the gradient direct on estimates prior to finding the zero crossings in those directions.
integration frameworks for large scale cognitive vision systems - an evaluative study. owing to the ever growing complexity of present day computer vision systems, system architecture has become an emerging topic in vision research. systems that integrate numerous modules and algorithms of different i/o and time scale behavior require sound and reliable concepts for interprocess communication. consequently, topics and methods known from software and systems engineering are becoming increasingly important. especially framework technologies for system integration are required. this contribution results from a cooperation between two multinational projects on cognitive vision. it discusses functional and non-functional requirements in cognitive vision and compares and assesses existing solutions.
an xml based framework for cognitive vision architectures. distributed processing and memory structures are very important aspects of cognitive vision systems. both issues not only require sophisticated conceptual designs but also pose problems of software and systems engineering. in this paper, we describe a general xml based solution to these problems. practical experiences are reported to underline its suitability.
glasses detection by boosting simple wavelet features. in this paper we propose a novel method for glasses detection. the glasses detectors are learned by using a variation of boosting algorithm, called real adaboost [improved boosting algorithms using confidence-rated predictions], to boost simple wavelet feature based look-up-table type weak classifiers. two types of wavelet features, haar and gabor, have been investigated. experiments results are reported to show that our method has very high correctness and extremely fast running speed. based on this method we have developed a glasses detection system which can detect the glasses in facial images automatically.
visual line estimation from a single image of two eyes. this paper describes a conic-based algorithm for estimating visual line from a single monocular image. by assuming that the visual lines of the both eyes are parallel and the iris boundaries are circles, we propose a "two-circle" algorithm that can estimate the normal vector of the supporting plane of the iris boundaries, from which the visual line is calculated. our new method does not use either the eye corners, or some heuristic knowledge about the structure of the eye. another advantage of our algorithm is that a camera with an unknown focal length can be used without assuming the orthographical projection. this is a very useful feature because it allows one to use a zoom lens and to change the zooming factor whenever he or she likes. it also gives one more freedom of the camera setting because keeping the camera far from the eyes is not necessary in our method. the extensive experiments over simulated images and real images demonstrate the robustness and the effectiveness of our method.
face recognition based on discriminative manifold learning. in this paper, a discriminative manifold learning method for face recognition is proposed which achieved the discriminative embedding the high dimensional face data into a low dimensional hidden manifold. unlike the recently proposed lle, isomap and eigenmap algorithms, which are based on reconstruction purpose, our method use the rca algorithm to achieve nonlinear embedding and data discrimination at the same time. also, the lle and isomap algorithms are crucially depends on the appropriateness of the neighborhood construction rule, in this paper, a ck-nearest neighborhood rule is proposed to achieve better neighborhood construction. experimental results indicate the promising performance of the proposed method.
license plate extraction in low resolution video. extensive study has been conducted in the detection of license plate for the applications in intelligent transportation system (its). however, these results are all based on images acquired at a resolution of 680x480. in this paper, a new method is proposed to extract license plate from the surveillance video which is shot at lower resolution ( 320x240) as well as degraded by video compression. morphological operations of bottom-hat and morphology gradient are utilized to detect the lp candidates, and effective schemes are applied to select the correct one. the average rates of correct extraction and false alarms are 96.22% and 1.77%, respectively, based on the experiments using more than four hours of video. the experimental results demonstrate the effectiveness and robustness of the proposed method.
willhunter: interactive image retrieval with multilevel relevance measurement. relevance feedback has become a key component in cbir system. although most current relevance feedback approaches are based on dichotomous relevance measurement, this coarse measurement is a distortion of the reality. we study relevance feedback with multi-level relevance measurement to better identify the user needs and preferences. to validate the use of multi-level relevance measurement and our relevance feedback algorithm, we developed a cbir prototype system - willhunter.there are two novelties in our system, one is our svm-based fast learning algorithm; another is the easy-to-use graphical user interface, especially the relevance-measuring instrument. not only experiments are conducted to assess the algorithm, but also usability study is carried out to evaluate the user interface.
a semi-supervised svm for manifold learning. many classification tasks benefit from integrating manifold learning with semi-supervised learning. by formulating the learning task in a semi-supervised manner, we propose a novel objective function that combines the manifold consistency of whole dataset with the hinge loss of class label prediction. this formulation results in a svm-alike task operating on the kernel derived from the graph laplacian, and is capable of capturing the intrinsic manifold structure of the whole dataset and maximizing the margin separating labelled examples. results on face and handwritten digit recognition tasks show significant performance gain. the performance gain is particularly impressive when only a small training set is available, which is often the true scenario of many real-world problems.
a new method of object segmentation in the basketball videos. object segmentation is one of key issues in object based video analysis and retrieval. in this paper, a basketball segmentation algorithm is proposed. the algorithms involve a hierarchical basketball detection algorithm and a motion tracking algorithm based on adaptive object model. basketball detection algorithm is started firstly, only when a basketball is detected, the tracking algorithm is started in the next frame. moreover, there is a tracking result evaluation module in motion tracking algorithm, if it is true, the tracking algorithm is used in the next frame, otherwise, the detection module is started again. the experimental results from real basketball video confirm the efficiency of the proposed algorithms.
biologically inspired hierarchical model for feature extraction and localization. some of the most important problems of computer vision are feature extraction and subsequent localization of those features in a new image. since it is computationally prohibitive to search for the features over all possible locations and scales, it is necessary to design an algorithm that can selectively focus on and process information from only some regions within the image. in this work we present such an algorithm that is biologically inspired and performs a hierarchical search, from coarse to fine, in order to minimize the computational costs. the algorithm is very robust to non-linear image transformations such as changes in scale, rotation, skew, addition of noise, and changes in brightness and contrast. we demonstrate the computational efficiency as well as the effectiveness of the algorithm on several real world images.
object removal by cross isophotes exemplar-based inpainting. exemplar-based inpainting algorithm is a new model used for large region removal. it combines the advantages of both inpainting and texture synthesis. the crucial part of this model is data term which is used to preserve linear structure. in this paper, basing on anisotropic diffusion, deeper mathematical analysis of along isophotes exemplar- based inpainting (aiei) is given, and it is also proved the data term is the strength of isophotes. a novel cross isophotes exemplar-based inpainting (ciei) model is proposed, which determines the data term cross the isophotes. data term in ciei considers the extent of edge, so ciei has better linear structure preserving property, and it can fill the target region of natural scene more plausibly. both theoretical analysis and experiments have verified the validity of the new ciei model proposed in this paper.
a regression model in tensorpca subspace for face image super-resolution reconstruction. a regression model in the tensorpca subspace is proposed in this paper for face super-resolution reconstruction. an approximate conditional probability model is used for the tensor subspace coefficients and maximum-likelihood estimator gives a linear regression model. the approximation is corrected by adding non-linear component from a rbf-type regressor. experiments on face images from feret database validate the algorithm. although each projection coefficient is estimated by a local estimator, tensorpca subspace analysis is still a global descriptor, which makes the algorithm have certain ability to deal with partially occluded images.
high frequency component compensation based super-resolution algorithm for face video enhancement. this paper proposes a video-based high-frequency component compensation (hfcc) super-resolution algorithm. the lost high-frequency information is estimated by local map criteria, using the registered frames. by compensating the high frequency component iteratively, the high-resolution images are recovered. the algorithm has lower computational cost than the alternatives. experimental evaluation verified the usefulness of the algorithm.
resolution enhancement by adaboost. this paper proposes a learning scheme based still image super-resolution reconstruction algorithm. super-resolution reconstruction is proposed as a binary classification problem and can be solved by conditional class probability estimation. assuming the probability takes the form of additive logistic regression function, adaboost algorithm is used to predict the probability. experiments on face images validate the algorithm.
regularized image restoration based on adaptively selecting parameter and operator. regularization has been widely used in image restoration. however, selection of the regularization parameter and the regularization operator is not solved completely and is still the main difficulty for adaptively regularized image restoration. this paper presents a new approach to select the local regularization parameter and the local regularization operator. the local regularization parameter is selected according to the distribution of local noise value in degraded images, and the local regularization operator is selected according to anisotropic properties. experiment results show that the proposed methods work well in the presence of many types noise.
fuzzy directional element energy feature (fdeef) based palmprint identification. palmprint is a novel biometric method to identify a person. generally, there are two types of features in palmprint, i.e. structural features and statistical features. structural features, such as lines, can characterize a palm exactly, but are difficult to be extracted and represented.contrarily, statistical features can be extracted and represented easily, but are unable to reflect the structural information of a palmprint. the fact that the principal features of both chinese character and palmprint are lines motivates us to try some methods of chinese character recognition to identify palmprint. in this paper, we use the idea of an efficient chinese character recognition method, directional element feature (def), to define a novel palm-print feature, named fuzzy directional element energy feature (fdeef) which is a statistical feature containing some line structural information about palmprints. it can be extracted and represented easily and, at the same time, has a strong ability to distinguish palms. two other low-dimensional features: global fuzzy directional element energy feature (gfdeef) and block edge energy feature (beef) are also derived from fdeef in this paper. the experimental results demonstrate the power of this method.
palmprint recognition using directional line energy feature. palm-lines, including the principal lines and wrinkles, can describe a palmprint clearly. this paper presents a novel approach of line feature extraction for palmprint recognition called the directional line energy feature (dlef). the directional lines in different directions are first extracted using a set of directional line detectors. then each directional line magnitude image is divided into several overlapped small grids and the magnitudes of the line points in these grids are used to compute the dlef. a template-matching method based on euclidean distance is adopted to measure the similarity of two dlefs. best results have been obtained when dlefs with 6 different directions were employed. accuracies of 97.92% and 97.5% are obtained by using the proposed approach in one-against-one matching and one-against-320 matching, respectively.
optimal gabor filters for high speed face identification. this paper describes a fast face identification method with gabor filters. two efforts are made to achieve the acceptable processing speed: 1) we design the optimal gabor filters with the arrangement theory that uses a few directions and layers. 2) the transformation with gabor filters (as called gabor transformation) is only done over the regions around the facial feature points, not the whole input image. the facial feature points extraction is performed by detecting the facial organ regions with color information and edge information, followed by the corner detection in each detected facial organ region with the susan operator.
relevant linear feature extraction using side-information and unlabeled data. "learning with side-information" is attracting more and more attention in machine learning problems. in this paper, we propose a general iterative framework for relevant linear feature extraction. it efficiently utilizes both the side-information and unlabeled data to enhance gradually algorithms' performance and robustness. both good relevant feature extraction and reasonable similarity matrix estima-tion can be realized. specifically, we adopt relevant component analysis (rca) under this framework and get the derived iterative self-enhanced relevant component analysis (iserca) algorithm. the experimental results on several data sets show that iserca outperforms rca.
a neural network approach for hand gesture recognition in virtual reality driving training system of spg. the recognition of hand gestures is a challenging task for the high degrees of freedom of hand motion. we develop a virtual reality based driving training system of self-propelled gun (spg). for this system, a dataglove with 18 sensors is employed to perform some driving tasks such as pressing switches, manipulating steering wheel, changing gears, etc. to accomplish these tasks, some hand gestures must be defined from the dataglove sensors data. a feedforward neural network can represent an arbitrary functional mapping so it is possible to map raw data directly to the required hand gestures. this paper uses bp neural network to recognize the hand patterns which exist in the raw sensor data of the dataglove. a pattern set of 300 hand gestures is used to train and test the neural network. the recognition system achieves good performance. it can be effectively used in our virtual reality training system of spg to perform various manipulating tasks in a more fast, precise, and natural way.
topological segmentation of discrete human body shapes in various postures based on geodesic distance. this paper extends our previous reeb graph approach [a discrete reeb graph approach to the segmentation of human body scans] based on a new morse function, namely geodesic distance, to segment whole body scan data into primarybody parts in various postures. because of the bending invariance of geodesic distance, the resulting reeb graph can remain stable in a large range of postures. consequently, the approach is capable of segmenting data within the posture range. the application of geodesic distance also brings the independence of coordinate frame selection. we present a number of experiments conducted on both real body 3d scan samples and simulated datasets to demonstrate the validity of the approach.
a multi-object tracking system for surveillance video analysis. in this paper we present a novel and robust clustering based multi-object tracking system for surveillance video analysis. it is designed to extract the trajectory data of vehicles in crowded traffic scenes and can be extended to other applications of surveillance and sports video analysis. in our system, a fast accurate fuzzy clustering algorithm is employed, and the feature space is constructed by extracting the position, color and velocity information of foreground pixels. by using growing and predictive adaptation, fixed linkages are expected between meaningful targets and corresponding active cluster centroids. in this way the motion classifier and tracker are combined seamlessly. experimental results suggest the efficiency and robustness of the proposed method with severe occlusions and clutter effect.
speech animation using coupled hidden markov models. we present a novel speech animation approach using coupled hidden markov models (chmms). different from the conventional hmms that use a single state chain to model the audio-visual speech with tight inter-modal synchronization, we use the chmms to model the asynchrony, different discriminative abilities, and temporal coupling between the audio speech and the visual speech, which are important factors for animations looking natural. based on the audio-visual chmms, visual animation parameters are predicted from audio through an em-based audio to visual conversion algorithm. experiments on the jewel av database show that compared with the conventional hmms, the chmms can output visual parameters that are much closer to the actual ones. explicit modelling of audio-visual speech is promising in speech animation.
improved two-stage wiener filter for robust speaker identification. in order to solve the problem of robustness in textindependent speaker identification, two-stage wiener filter presented in the etsi standard is used in this paper. however, the performance of the voice activity detection (vad) block in the standard is not so satisfying under lower snr. thus constrainedclustering vector quantization is presented to improve the block in the wiener filter method. experiments based on the msra's mandarin speech corpora show the good robustness of the improved method to several common additive noises.
bootstrap methods for reject rules of fisher lda. when there are uncertainties in pattern recognition it may be better to introduce a rejection option to reduce the total costs, and two rules have been proposed: chow's rule based on posterior probabilities and tortorella's rule based on roc curves. however, both have shortcomings for the application in practice: first, it is extremely difficult to obtain the exact posterior probability for each example to be recognized; second, for small data size, the associated roc curves may have very little number of convex points, resulting in the ineffectiveness of tortorella's rule. this paper proposes a new bootstrap algorithm for obtaining sampling distributions of test example scores produced by fisher lda. these distributions can not only convert the scores into posterior probabilities but also generate a roc curve with a lot of convex points. thus, this bootstrap method can improve the effectiveness of chow's rule and tortorella's rule in the real applications.
ndft-based audio watermarking scheme with high security. uniform discrete fourier transform (dft) has the drawback of public frequency points. on the other hand, nonuniform discrete fourier transform (ndft) could set up random sampling points in frequency domain as desired rather than fixed frequency points in dft. that is dft is the special condition of ndft. this paper utilizes ndft to instead uniform dft in the algorithm of audio watermarking scheme with the purpose of providing the probability of hidden embedding positions. moreover, to further improve the systematic security, in our method, we use coupledchaotic sequence to randomly select the ndft-domain frequency points used for embedding watermark, which overcomes the flaws brought by single chaotic map which is finite word length effect and vulnerable to repeated group attack. good experimental results have shown the proposed scheme possesses higher systematic security than dft-based watermarking scheme.
a multibit geometrically robust image watermark based on zernike moments. in image watermarking, the watermark robustness to geometric transformations is still an open problem. using invariant image features to carry the watermark is an effective approach to addressing this problem. in this paper, a multibit geometrically robust image watermarking algorithm using zernike moments is proposed. some zernike moments of an image are seleted, and their magnitudes are dither-modulated to embed an array of bits. the watermarked image is obtained via reconstruction from the modified moments and those left intact. in watermark extraction, the embedded bits are estimated from the invariant magnitudes of the zernike moments using a minimum distance decoder. simulation results show that the hidden message can be decoded at low error rates, robust against image rotation, scaling and flipping, and as well, a variety of other distortions such as lossy compression.
statistical landscape features for texture classification. this paper proposes the use of information derived from the graph of a texture image function for texture description. the graph of an image function is a rumpled surface in the three-dimensional space that appears like a landscape. four novel texture feature curves are used to characterize the texture. this method is named statistical landscape features (slf). slf achieves a very high correct classification rate of 94.53% on the entire brodatz set. besides the very good performance, another remarkable advantage of the proposed method is that it has no parameter to tune.
multiscale blob features for gray scale, rotation and spatial scale invariant texture classification. this paper proposes to apply a series of flexible threshold planes to the textured image and then use the topological and geometrical attributes of the blobs in the obtained binary images to describe image texture. the proposed multiscale blob features (mbf) is invariant to linear gray-level scaling and rotation, and is insensitive to uniform spatial scaling. the experiment results show that mbf offers very low error rate on the entire brodatz texture database, and confirm its invariance properties.
delta-mse dissimilarity in suboptimal k-means clustering. k-means clustering is a well-known partition-based technique in unsupervised learning to construct pattern models. the main difficulty, however, is that its performance is highly susceptible to the initialized partition. to attack this problem, a suboptimal k-means algorithm is briefly reviewed by applying dynamic programming over the principal component direction. in particular, a heuristic clustering dissimilarity, the delta-mse function, is incorporated into the suboptimal k-means algorithm. the delta-mse function is derived by calculating the difference of within-class variance before and after moving a given data sample from one cluster to another. experimental results show that the suboptimal k-means algorithm that uses the delta-mse dissimilarity generally outperforms the original l¿ distance based suboptimal algorithm and a specific kd-tree clustering algorithm.
segmentation and recognition of vocalized outlines in pitman shorthand. there is a wish to be able to enter text into mobile computing devices at the speed of speech. only handwritten shorthand schemes can achieve this data recording rate. a novel approach to the recognition of vocalized outlines in pitmanýs shorthand is proposed in this paper. in this approach, the recognition process is divided into two steps. the consonant outline is first recognized by a two-stage (segmentation and classification) approach. afterwards surrounding vowel and diphthong symbols are classified and their positions in relation to an associated consonant stroke are determined. promising results of over 70% recognition accuracy have been obtained.
high accuracy classification of eeg signal. improving classification accuracy is a key issue to advancing brain computer interface (bci) research from laboratory to real world applications. this article presents a high accuracy eeg signal classification method using single trial eeg signal to detect left and right finger movement. we apply an optimal temporal filter to remove irrelevant signal and subsequently extract key features from spatial patterns of eeg signal to perform classification. specifically, the proposed method transforms the original eeg signal into a spatial pattern and applies the rbf feature selection method to generate robust feature. classification is performed by the svm and our experimental result shows that the classification accuracy of the proposed method reaches 90% as compared to the current reported best accuracy of 84%.
active learning based pedestrian detection in real scenes. this work presents an active learning based method for pedestrian detection in complicated real-world scenes. through analyzing the distribution of all positive and negative samples under every possible feature, a highly efficient weak classifier selection method is presented. moreover, a novel boosting architecture is given to get satisfied false positive rate (fpr) and false negative rate (fnr) with few weak classifiers. a unique characteristic of the algorithm is its ability to train special cascade classifier dynamically for each individual scene. the benefit is that the trained classifier will only focus on the differences between the positive samples and the limited negative samples of each individual scene, thus greatly reduce the complexity of classification and achieve robust detection result even with few classifiers. a real-time pedestrian detection system is developed based on the proposed algorithm. the system produces fast and robust detection results as demonstrated by extensive experiments which use video sequences under different environments.
complete two-dimensional pca for face recognition. we propose a novel method, the complete twodimensional principal component analysis (complete 2dpca), for image features extraction. compared to the original 2dpca, complete 2dpca not only gain a higher recognition rate, but also reduce the feature coefficients needed for face recognition. complete 2dpca is based on 2d image matrices. two image covariance matrices are constructed directly using the original image matrix and theirs eigenvectors are derived for image feature extraction. our experiments were performed on orl face database, and experimental results show that the proposed method has an encouraging performance.
comparison of structural variables with spatio-temporal variables concerning the identifiability of okuri class and player in japanese traditional dancing. this paper experimentally examined the characteristics of structural variables and spatio-temporal variables through the identifiability of okuri classes and players( dancers) in traditional japanese dancing. the data for the experiment were acquired using a motion capture system, which monitored dancing motions performed by a master player (dancer) followed by two expert dancers and three beginners. the discrimination of two okuri classes, feminine okuri and descriptive okuri, and that of 5 dancers was experimentally attempted using structural variables and spatio-temporal variables. the experimental result suggested that spatio-temporal variables were more advantageous than structural variables for identification of okuri classes and dancers.
3-d affine moment invariants generated by geometric primitives. 3-d affine moment invariants are derived in a convenient way in this paper. the property of volume of a tetrahedron is studied first under affine transformation. 3-d affine moment invariants are constructed then by the multiple integrals of the combinations of this kind of geometric primitive. numerical experiments of deformed models are conducted to certificate the invariance of the new 3-d affine moment invariants given in this paper.
robust clustering based on winner-population markov chain. in this paper, we propose an unsupervised genetic clustering algorithm, which produces a new chromosome without any conventional genetic operators, and instead according to the gene reproducing probabilities determined by markov chain modeling. selection of cluster centers from the dataset enables construction of a look-up table that saves the distances between all pairs of data points. the experimental results show that the proposed algorithm not only solves the premature problem to provide a more stable clustering performance in terms of number of clusters and clustering results, but also improves the time efficiency.
face recognition by expression-driven sketch graph matching. we present a novel face recognition method using automatically extracted sketch by a multi-layer grammatical face model. first, the observed face is parsed into a 3- layer (face, parts and sketch) graph. in the sketch layer, the nodes not only capture the local features (strength, orientation and profile of the edge), but also remember the global information inherited from the upper layers (i.e. the facial part they belong to and status of the part). next, a sketch graph matching is performed between the parsed graph and a pre-built reference graph database, in which each individual has a parsed sketch graph. similar to the other successful edge-based methods in the literature, the use of sketch increases the robustness of recognition under varying lighting conditions. furthermore, with high-level semantic understanding of the face, we are able to perform an intelligent recognition process driven by the status of the face, i.e. changes in expressions and poses. as shown in the experiment, our method overcomes the significant drop in accuracy under expression changes suffered by other edge-based methods.
3-d surface moment invariants. 3-d surface moments and surface moment invariants under similarity transformation are defined in this paper. this variation of traditional moments and moment invariants can handle the situation where the object is unclosed. 3-d surface moment invariants can be used as shape descriptors for the representation of free-form surfaces. some explicit surface moment invariants are illustrated in the experiment to describe the partial meaningful polygonal patches.
object detection with adaptive background model and margined sign cross correlation. in this paper, we propose a successive method for adaptively estimating background components using kalman filters, and a novel method for detecting objects using margined sign cross correlation (msc). msc is a natural extension of sign cross correlation, in other words, peripheral increment sign correlation. msc has a margin to deal with observation noise. by applying msc to our adaptive background model, our proposed system can robustly and accurately perform object detection. we show experimental results using real images to demonstrate the performance of the proposed system.
entropy optimized contrast stretch to enhance remote sensing imagery. this paper presents a contrast stretch (cs) method based on minimum entropy constraint to enhance images obtained in remote sensing applications such as ground penetrating radar (gpr), synthetic aperture radar, and infra-red imagery. the cs enhances contrast of the low-contrast part of an image. in remote sensing, it is usually the desirable signals that are of low contrast while interference of high contrast. the cs modifies the original image such that pixel values above and below preset boundaries are set to zero and the maximum possible pixel value and the pixel values falling between the boundaries are stretched out to enhancethe contrast of the image. using the cs we can enhance the contrast of desirable signals from, for example, a buried landmine or an object obscured by some interference. on the other hand, the cs inevitably enhances other parts of a remote sensing images, such as clutters and measurement noise. therefore there is a trade-off in using the cs. it is beneficial to find the correct "cut-off" boundaries in the cs in some optimal sense. we propose using minimum entropy as a criterion of looking for the optimal cs parameter. using field data from gpr application, we show that improved image can be obtained which makes further processing such as detection more accurate.
a charged geometric model for active contours. this paper presents a new deformable model based on charged particle dynamics and geometric contour propagation. it detects object boundaries with a charged active contour that propagates under the influence of lorentz forces in an image-based electrostatic field. we make use of level set representation to allow topological changes to be handled naturally. also, we build on the centre of divergence concept towards automatic initialisation.
a robust and accurate method for pupil features extra. precise pupil features detection is an important factor for face recognition. this paper presents a robust and accurate algorithm to precisely estimate pupil features: pupil center and pupil radius. first, a pupil parameters estimation step is taken and a weight ring mask is created. then, a weighted hough transform is used to precisely extract pupil features. because of the estimation step, the influence of eyelid and eyelash is largely eliminated. the experimental results show very good robustness and accuracy.
layered search spaces for accelerating large set character recognition. this paper describes "layered search spaces” (lss) to accelerate recognition of a large category set. the basic concept is to employ pivots into a search space of character pattern prototypes. given an input pattern, it is compared only with the pivots and those close to it are selected. then, it matched with prototypes close to the selected pivots. this paper introduces multiple layers. an input pattern is compared with the top-layer pivots and those close to it are selected. then, it is compared with the 2nd-top-layer pivots close to the selected top-layer pivots. this comparison is repeated until in the base-layer and a small set of candidate prototypes are selected. we applied this method to a handwritten japanese character recognizer with the result that the coarse classification time was reduced to 47.1% and the whole recognition time was reduced to 46.2% while keeping classification and recognition rates as the original.
tree based behavior monitoring for adaptive fraud detection. the general basis for anomaly detection and fraud detection is pattern recognition. an effective online fraud detection system should be able to discover both known and new attacks as early as possible. the detection process should be self-adjustable to allow the system to deal with the constantly changing nature of online attacks. in this paper, we present an anomaly detection technique based on behavior mining and monitoring that work at both the individual and system level. frequent pattern tree is utilized to profile the normal behavior adaptively. a novel tree-based pattern matching algorithm is designed to discover individual level anomalies. an algorithm for computing tree similarity is proposed to solve the system level problems. empirical evaluations of our technique on both synthetic and real-world data show that we can accurately differentiate anomalous behaviors from the profiled normal behavior.
harmonic cut and regularized centroid transform for localization of subcellular structures. two novel computational techniques, harmonic cut and regularized centroid transform, are developed for segmentation of cells and their corresponding substructures observed with an epi-fluorescence microscope. harmonic cut detects small regions that correspond to subcellular structures. these regions also affect the accuracy of the overall segmentation. they are detected, removed, and interpolated to ensure continuity within each region. we show that interpolation within each region (subcellular compartment) is equivalent to solving the laplace equation on a multi-connected domain with irregular boundaries. the second technique, referred to as the regularized centroid transform, aims to separate touching compartments. this is achieved by adopting a quadratic model for the shape of the object and relaxing it for final segmentation.
generating omnifocus images using graph cuts and a new focus measure. in this paper, we discuss how to generate omnifocus images from a sequence of different focal setting images. we first show that the existing focus measures would encounter difficulty when detecting which frame is most focused for pixels in the regions between intensity edges and uniform areas. then we propose a new focus measure that could be used to handle this problem. in addition, after computing focus measures for every pixel in all images, we construct a three dimensional (3d) node-capacitated graph and apply a graph cut based optimization method to estimate a spatio-focus surface that minimizes the summation of the new focus measure values on this surface. an omnifocus image can be directly generated from this minimal spatio-focus surface. experimental results with simulated and real scenes are provided.
stereo computation using radial adaptive windows. while stereo algorithms using global methods produce good depth maps, local methods are still preferred for their efficiency . in this paper, we present a novel algorithm that determines the adaptive support windows by radial computations. motivated by the experiences of human vision, we use the certainties of the initial disparity distributions to determine the support window. certain other cues, such as differences of the initial disparity distributions, and colorsimilarities, are integrated to determine the weights in support window. extensive experiments have been conducted. the algorithm performs well in textureless areas, and preserving sharp disparity discontinuities.
a maximum margin discriminative learning algorithm for temporal signals. we propose a new maximum margin discriminative learning algorithm here for classification of temporal signals. it is superior to conventional hmm in the sense that it does not need prior knowledge of the data distribution. it learns the classifier by using a nonlinear discriminative procedure based on a maximum margin criterion, providing a strong generalization mechanism. this maximum margin discriminative learning method is presented together with a two-step learning algorithm. we evaluate the kernel based hiddenmarkov model by applying it to some simulation and real experiments. the preliminary results have shown significant improvement in classification accuracy.
localization of saliency through iterative voting. saliency is an important perceptual cue that occurs at different scales of resolution. important attributes of saliency are symmetry, continuity, and closure. detection of these attributes is often hindered by noise, variation in scale, and incomplete information. an iterative voting method using oriented kernels is introduced for inferring saliency as it relates to symmetry or continuity. a unique aspect of the technique is in the kernel topography, which is refined and reoriented iteratively. the technique can cluster and group nonconvex perceptual circular symmetries along the radial line or sparse features along the trangential direction. it has an excellent noise immunity, and is shown to be tolerant to perturbation in scale. applications of this approach to blobs with incomplete and noisy boundaries and to scientific images are demonstrated.
depth vs. intensity: which is more important for face recognition? both depth and intensity are important information for face recognition. in this paper, based on 3d face modelling, we extract depth features and intensity features respectively, and further compare their capacity to characterize the individuals in our database, 3dpef. the experimental results show that depth information is more important than intensity information for recognition under the same condition. this work will be a good reference to the future work on face recognition.
human-robot interaction by whole body gesture spotting and recognition. an intelligent robot is required for natural interaction with humans. visual interpretation of gestures can be useful in accomplishing natural human-robot interaction (hri). previous hri research focused on issues such as hand gesture, sign language, and command gesture recognition. automatic recognition of whole body gestures is required in order for hri to operate naturally. this presents a challenging problem, because describing and modeling meaningful gesture patterns from whole body gestures, is a complex task. this paper presents a new method for recognition of whole body key gestures in hri. a human subject is first described by a set of features, encoding the angular relationship between a dozen body parts in 3d. a feature vector is then mapped to a codeword of gesture hmms. in order to spot key gestures accurately, a sophisticated method of designing a garbage gesture model is proposed; model reduction, which merges similar states, based on data-dependent statistics and relative entropy. the proposed method has been tested with 20 persons' samples and 200 synthetic data. the proposed method achieved a reliability rate of 94.8% in spotting task and a recognition rate of 97.4% from an isolated gesture.
automatic iris segmentation based on local areas. in this paper a novel and robust method for automatic iris segmentation based on local areas is described. such method is composed of three main parts. (a) find the local rectangle region which has the minimum intensity mean and extend it to locate pupil. (b) select two small local sector areas including the outer boundaries of iris to locate outer iris. (c) translate the iris from polar coordinates into cartesian coordinates and normalize it to fixed size to compensate the stretching of the iris texture as the pupil changes in size and remove the nonconcentricity of the iris and the pupil. the method was implemented using casia iris image databases. the experimental results show that the proposed method has an encouraging result with an overall accuracy of 98.42%.
a novel pattern classification scheme: classwise non-principal component analysis (cnpca). this paper1 presents a novel pattern classification scheme: class-wise non-principal component analysis (cnpca), which utilizes the distribution characteristics of the samples in each class. the euclidean distance in the subspace spanned by the eigenvectors associated with smallest eigenvalues in each class, named cnpca distance, is adopted as the classification criterion. the number of the smallest eigenvalues is selected in such a way that the classification error in a given database is minimized. it is a constant for the database and can be determined by experiment. the cnpca classification scheme usually outperforms other classification schemes under the situations of high computational complexity (associated with high dimensionality of features and/or calculation of inverse variance matrix) or high classification error rate (e.g., owing to the scattering of between-class being less than that of within-class). the experiments have demonstrated that this method is promising in practical applications.
near-duplicate image recognition and content-based image retrieval using adaptive hierarchical geometric centroids. in this paper, we present a new feature extraction method that simultaneously captures the global and local characteristics of an image by adaptively computing hierarchical geometric centroids of the image. we show that these hierarchical centroids have some very interesting properties such as illumination invariant and insensitive to scaling. we have applied the method for near-duplicate image recognition and for content-based image retrieval. we present experimental results to show that our method works effectively in both applications.
robust feature selection by weighted fisher criterion for multiclass prediction in gene expression profiling. this paper presents a robust feature selection approach for multiclass prediction with application to microarray studies. first, individually discriminatory genes (idgs) are identified by using weighted fisher criterion (wfc). second, jointly discriminatory genes (jdgs) are selected by a sequential search method, according to their joint class separability. to combat the small size effect on feature selection, leave-one-out procedures are incorporated into both idg and jdg selection steps to improve the robustness of the approach. by applying this approach to a microarray study of small round blue cell tumors (srbcts) of childhood, we have demonstrated that our robust feature selection method can be used to successfully identify a subset of genes with superior classification performance for multiclass prediction.
detecting coarticulation in sign language using conditional random fields. coarticulation is one of the important factors that makes automatic sign language recognition a hard problem. unlike in speech recognition, coarticulation effects in sign languages are over longer durations and simultaneously impact different aspects of the sign such as the hand shape, position, and movement. due to this effect, the appearance of a sign, especially at the beginning and at the end, can be significantly different under different sentence contexts, which makes the recognition of signs in sentences hard. we advocate a two-step approach, where in the first step one segments the individual signs in a sentence and in the next step one recognizes the signs. in this work, we show how the first step, i.e. sign segmentation, can be performed effectively by using the conditional random fields (crf) to directly detect the coarticulation points. the crf approach does not make conditional independence assumptions about the observations and can be trained with fewer samples than hidden markov models (hmms). we validate our approach by demonstrating performance with american sign language (asl) sentence level data and show that the crf approach is 85% accurate in segmenting signs compared to 60% for the hmm approach at 0.1 false alarm rate.
feature selection based on the bhattacharyya distance. this paper presents a bhattacharyya distance based feature selection method, which utilizes a recursive algorithm to obtain the optimal dimension reduction matrix in terms of the minimum upper bound of classification error under normal distribution for multi-class classification problem. in our scheme, pca is incorporated as a pre-processing to reduce the intractably heavy computation burden of the recursive algorithm. the superior experimental results on the handwritten-digit recognition with the mnist database and the steganalysis applications have demonstrated the effectiveness of our proposed method.
feature selection based on the bhattacharyya distance. this paper presents a bhattacharyya distance based feature selection method, which utilizes a recursive algorithm to obtain the optimal dimension reduction matrix in terms of the minimum upper bound of classification error under normal distribution for multi-class classification problem. in our scheme, pca is incorporated as a pre-processing to reduce the intractably heavy computation burden of the recursive algorithm. the superior experimental results on the handwritten-digit recognition with the mnist database and the steganalysis applications have demonstrated the effectiveness of our proposed method.
people tracking by integrating multiple features. because a people detection system that considers only a single feature tends to be unstable, many people detection systems that consider multiple features simultaneously have been proposed. these detection systems usually integrate features using a heuristic method based on the designers' observations and induction. whenever the number of features to be considered is changed, the designer must change and adjust the integration mechanism accordingly. to avoid this tedious process, we propose a multi-modal fusion system that can detect and track people in a scalable, accurate, robust and flexible manner. each module considers a single feature and all modules operate independently at the same time. the outputs from the individual modules are integrated together and tracked using a kalman filter.
3d+2d face localization using boosting in multi-modal feature space. facial feature extraction is important in many facerelated applications, such as face alignment for recognition. recently, boosting-based methods have led to the state-of-the-art face detection and localization systems. in this paper, we propose a multi-modal boosting algorithm to integrate 3d (range) and 2d (intensity) information provided from a facial scan to detect the face and feature point (nose tip, eyes center). given a face scan, gauss and mean curvature are calculated. face, nose and eyes detectors are trained in color images and curvature maps features space using adaboost. as a result, a fully automatic multi-modal face location system is developed. the performance evaluation is conducted for the proposed feature extraction algorithm on a publicly available data-base, containing 4007 facial scans of 466 subjects.
adaptive contour construction for face regions. contours contribute much to object analysis in many applications. in this paper, an adaptive method of constructing face contours is proposed. first, a region splitting scheme is adopted to automatically generate grids over face regions. based on the grids, initial face contours are then constructed. finally, the contours are refined according to the minimum energy principle. experimental results show that the proposed method has a good performance in face contour construction.
performance prediction for handwritten word recognizers and its application to classifier combination. this paper introduces a performance prediction model for handwritten word recognizers . this model considers the factors involved in word recognition, i.e . the recognizer, input images and lexicons, and presents a quantitative formula to associate performance with these factors. it produces a direct measure of recognition difficulty by predicted performance whic h can be utilized to improve the combiation of multiple recognizers. we support the accuracy of our model by extensive experiments conducted on five word recognizers and its applications to multiple classifier systems.
iterative image restoration using a non-local regularization function and a local regularization operator. the regularization of the least-squares criterion has been established as an effective approach of solving illposed image restoration problems. unfortunately, a proper global regularization parameter is very difficult to be determined, and edges are usually smoothed by restoration process. in this paper, a new iterative regularization algorithm is presented. before restoration, we divide the pixels of the blurred and noisy image into two types of regions: flat regions and edge regions (edges and the regions near edges). a non-local adaptive regularization function is used instead of a global regularization parameter, and a local regularization operator which is determined by the orientation of pixels is employed in edge regions. experiments show that our algorithm is effective and the edge details are well preserved during the restoration process.
regression nearest neighbor in face recognition. in this paper, we introduce a regression nearest neighbor framework for general classification tasks. to alleviate potential problems caused by nonlinearity, we propose a kernel regression nearest neighbor (krnn) algorithmand its convex counterpart (ckrnn) as two specific extensions of nearest neighbor algorithm and present a fast and useful kernel selection method correspondingly. comprehensive analysis and extensive experiments are used to demonstrate the effectiveness of our methods in real face datasets
unsupervised discriminant projection analysis for feature extraction. this paper develops an unsupervised discriminant projection (udp) technique for feature extraction. udp takes the local and non-local information into account, seeking to find a projection that maximizes the non-local scatter and minimizes the local scatter simultaneously. this characteristic makes udp more intuitive and more powerful than the up-to-date methodlocality preserving projection (lpp, which considers the local information only) for classification tasks. the proposed method is applied to face biometrics and examined using the orl and feret face image databases. our experimental results show that udp consistently outperforms lpp, pca, and lda.
a modified non-negative matrix factorization algorithm for face recognition. in this paper, we propose a new variation of the nonnegative matrix factorization (nmf) for face recognition. the original nmf algorithm is distinguished from the other methods of pattern recognition by its non-negativity constraints which lead to a parts-based representation because they allow only additive combinations. however, it should be considered as an unsupervised method since class information in the training set is not used. to take advantage of more information in the training images and improve the performance for classification problem, we integrate the fisher linear discriminant analysis into the nmf algorithm, which results in a novel modified non-negativematrix factorization algorithm. our new update rule guarantees the non-negativity for all the coefficients and hence preserve the intuitive meaning for the base vectors and weight vectors while facilitating the supervised learning of within-class information. our new technique is tested on a well-known face database: the orl face database. the experimental results are very encouraging and outperformed traditional techniques including the original nmf and the eigenface method.
an efficient image-based rendering method. given a set of images of the same scene, we propose an efficient method for realistically synthesizing a new image seen from a new viewpoint. compared with some existing techniques which explicitly reconstruct the 3d geometry of the scene, we directly reconstruct the colour of each pixel in the new image by utilizing a weighted photoconsistency constraint. global photoconsistency constraint of one pixel is firstly utilized to generate a list of plausible colours for each rendered pixel in the new image. considering the existing of partial occlusion or the deficiencies in the image-formation model, we iteratively update the colour for each rendered pixel based on local texture statistics similar to the input images. experimental results on the generation of a new image from a new viewing position from a set of input images show that our proposed method is promising and satisfactory.
an integrated monte carlo data association framework for multi-object tracking. we propose a sequential monte carlo data association algorithm based on a two-level computational framework for tracking varying number of interacting objects in dynamic scene. firstly, we propose a hybrid measurements generation process to facilitate varying number problems, the process mixes target-oriented measurements provided by target dynamics prior model and data-oriented measurements based on discriminative model . secondly, an improved monte carlo joint data association filter is used to combat the curse of dimension problem. finally, the particle based belief propagation is used to facilitate interactions among objects. this framework integrates discriminative model learning, monte carlo joint data association filtering, and belief propagation algorithm, these methods are realized as different levels of approximation to an 'ideal' generative model of multiple visual targets tracking, and result in a novel sequential monte carlo data association algorithm. the algorithm is illustrated via tracking many pedestrians in a real video sequence.
on-line handwritten chinese word recognition based on lexicon. we proposed a new method for on-line handwritten chinese word recognition based on lexicon. a pre-segment strategy is first applied to the input strokes and merges the strokes into candidate character boxes. segmentation path generation and filtering method is then invoked to generate segmentation paths from the boxes and filter out impossible paths by the recognition results of candidate character and lexicon-based technique. the optimal segmentation path along with the best matching word in the lexicon is finally chosen by a voting strategy using both recognition and geometrical information. superiority of the proposed approach has been proven by testing it with 8550 words collected by tablet pc. the accuracy of segmentation and recognition is about 99%
evaluation of fingerprint orientation field registration algorithms. the majority of modern fingerprint registration algorithms are based on the alignment ofminutiae features. however, shortcomings of this approach are becoming apparentdue to the difficulty of extracting minutiae from noisy or low quality images. this papers explores a novel approach to fingerprint registration based on orientation field alignment. one main advantage of this method is that orientation fields can be computed reliably for poor quality images, providing a robust feature for registration. three orientation field alignment algorithms are presented, and their performance is evaluated using an fvc2002 dataset.
fast robust ga-based ellipse detection. this paper discusses a novel and effective technique for extracting multiple ellipses from an image, using a multi-population genetic algorithm (mpga). mpga evolves a number of subpopulations in parallel, each of which is clustered around an actual or perceived ellipse. it utilizes both evolution and clustering to direct the search for ellipses - full or partial. mpga is explained in detail, and compared with both the widely used randomized hough transform (rht) and the sharing genetic algorithm (sga). in thorough and fair experimental tests, utilizing both synthetic and real-world images, mpga exhibits solid advantages over rht and sga in terms of accuracy of recognition - even in the presence of noise or/and multiple imperfect ellipses, as well as speed of computation.
integrating differential evolution and condensation algorithms for license plate tracking. in this paper, we propose a novel method for position estimation and tracking of license plates in 3d from monocular camera view. given an initial estimate, we try to track the position of the license plate in the successive video frames. in our previous works, we utilized condensation algorithm for estimating the state of the object and filtering the measurements. in this work, we present decondensation algorithm, which is an integration of condensation and differential evolution (de) algorithms. the new algorithm is composed of the probability density propagation of condensation algorithm and a fine scale optimization step according to de algorithm. each sample of the de-condensation algorithm is an estimate for the license plate's position in 3d and projected to the image plane by perspective camera model for evaluation. while tracking the license plate's texture by probability density propagation, de optimization gives a fine tuning according to the license plate boundaries. de-condensation algorithm outperforms the standard condensation algorithm and reduces the number of samples significantly.
analysis and improvement of an iris identification algorithm. iris recognition using complex valued 2d gabor filters received a great success in broad applications. such method encoded the iris phase information which was extracted according to the complex valued 2d filters' response. in this paper, we theoretically analyzed the complex-valued 2d gabor filters. based on analysis, we concluded that the real part of complex-valued 2d gabor filter would reduce the whole system performance because it is not perfectly band passed filter. an improved algorithm then proposed to extract the phase information of iris image. the new method has more advantages such as lower false rate, much less space of codes and shorter time of encoding and matching. in order to reduce the disturbance of eyelashes, eyelids, specular reflections, or other noise, a matching template is designed by dilating the positions of them. experimental results show that the latter method has an encouraging performance.
on the relationship of human walking and running: automatic person identification by gait. the intimate relationship between human walking and running lies within the skeleto-muscular structure. this is expressed as a mapping that can transform computer vision derived gait signatures from running to walking and vice versa, for purposes of deployment in gait as a biometric or for animation in computer graphics. the computer vision technique can extract leg motion by temporal template matching with a model defined by forced coupled oscillators as the basis. the (biometric) signature is derived from fourier analysis of the variation in the motion of the thigh and lower leg. in fact, the mapping between these gait modes clusters better than the original signatures (of which running is the more potent) and can be used for recognition purposes alone, or to buttress both of the signatures. moreover, the two signatures can be made invariant to gait mode by using the new mapping.
iris recognition algorithm using modified log-gabor filters. in this paper, we presented an iris recognition algorithm based on modified log-gabor filters. the algorithm is similar as the method proposed by daugman in general procedure while modified log-gabor filters are adopted to extract the iris phase information instead of complex gabor filters used in daugman's method. the advantage of log- gabor filters over complex gabor filters is the former are strictly bandpass filters and the latter are not. the property of strictly bandpass makes the log-gabor filters more suitable to extract the iris phase features regardless of the background brightness. the comparison experiments between complex gabor filters based methods and the proposed method are also presented in this paper.
real time large vocabulary continuous sign language recognition based on op/viterbi algorithm. up to now, continuous sign language recognition is mainly based on statistical methods, especially hidden markov models (hmm) and viterbi-beam searching. however, the recognition speed often gets unacceptable with an increased vocabulary, which could cause a long time delay that is not fit for the real time recognition system. to speed up the recognition process, we present a method using one-pass (op) pre-searching before viterbi recognition. the experiments are processed in the large vocabulary database. results show that the average recognition speed of op/viterbi approach can get a notable raise comparing with the single frame's without reducing too much recognition accuracy.
hipprint person identification and behavior analys. it has been gathering great deal of attention to provide personalized services in the home or in the small office. as a necessary technology for it, person recognition by pressure sensors on a chair is described. it exploits the hipprints of users. such a method makes it possible to automatically login to a computer when the user sits. the recognition rate reached to 99.6% for 5 people and 98.4% for 10 people. in addition, a change of the hipprints is available to figure out roughly what he/she was doing.
systematic static shadow detection. a systematic static shadow detection algorithm for color images is presented in this paper. the image is modeled by an undirected graph and the shadow detection is achieved through maximizing the graph probability using the em algorithm. further analysis shows the connection between our model and the relaxation labeling (rl) model. experiments clearly indicate that our method is superior to a state-of-the-art shadow detection algorithm.
space-time moment invariants and recognition of non-rigid motions from arbitrary viewpoints. the geometric invariants are very useful for recognizing objects in the scene from arbitrary viewpoints. recently, it has been shown that some geometric invariants can be defined in the space with time domain, and they can be applied for recognizing dynamic motions from arbitrary viewpoints. however, the existing invariants on motions are computed from multiple points in the sequence of images, and thus accurate tracking of image features is required. as a result, if tracking of image features fails, these invariants cannot be computed. in this paper, we propose invariants on motions, which are defined by using image moments. we show that by using the proposed moment invariants on motions, we can recognize non-rigid motions from arbitrary viewpoints without tracking image features. we also show that they can reflect entire changes in object shapes and motions in image sequences.
directly modeling of correlation matrices for gmm in speaker identification. in this paper, we present a new framework to model full covariance matrices of gaussian components. in this framework, directly modeling the full correlation matrix instead of the full covariance matrix is our purpose, as the correlation matrix is the direct description of the correlation of inter-feature elements. in order to model full correlation matrices, we share linear transformations among components' full correlation matrices. thus, the full correlation matrix of each component is represented by a shared linear transformation and a componentspecific diagonal correlation matrix. the transformation is used to help the diagonal correlation matrix to model the correlation of inter feature-vector elements more precisely. we evaluate our new framework on a mandarin speaker identification task. experiments show that above 35% reduction in speaker identification error rate is achieved compared with the best diagonal covariance models. furthermore, our algorithm achieved better performance than stc does.
tracking players and a ball in video image sequence and estimating camera parameters for 3d interpretation of soccer games. to recognize and retrieve soccer game scenes, the movement of the players and the ball must be analyzed. this paper describes a method of tracking the players and the ball and estimating their 3d positions from video images recorded from tv broadcasting. our system detects the players and tracks them by predicting their motions. our system determines the ball from among ball candidates by considering the motion continuity of the ball. the camera parameters (pan, tilt, and zoom) are estimated by detecting line regions on the field in every frame and by matching them to the model. because our method uses not only straight lines but also circular ones for the matching, it can be applied to the whole area of the field. our system also estimates the 3d position of the ball by fitting a 3d physical model to the observed ball trajectory. the effectiveness of the method is shown by experiments with actual image sequences.
detecting femur fractures by texture analysis of trabeculae. 30% of women and 13% of men worldwide suffer from osteoporotic bone fractures worldwide. in large hospitals, doctors need to visually inspect a large number of x-ray images to identify the fracture cases, which typically constitute about 12% of all the x-ray images examined. automated fracture detection can help to screen for obvious cases and flag suspicious cases for closer examinations. this paper describes a method of detecting femur fractures by analyzing trabecular texture patterns. test results show that it is more accurate than an existing method based on neck-shaft angle. moreover, combining the methods further improve of the overall performance of fracture detection.
vehicle ego-motion estimation and moving object detection using a monocular camera. this paper proposes a method for estimating the egomotion of the vehicle and for detecting moving objects on roads by using a vehicle mounted monocular camera. there are two problems in ego-motion estimation. firstly, a typical road scene contains moving objects such as other vehicles. secondly, roads display fewer feature points compared to the number associated with background structures. in our approach, ego-motion is estimated from the correspondences of feature points extracted from various regions other than those in which objects are moving. after estimating the ego-motion, the three dimensional structure of the scene is reconstructed and any moving objects are detected. in our experiments, it has been shown that the proposed method is able to detect moving objects such as vehicles and pedestrians.
audio music genre classification using different classifiers and feature selection methods. we examine performance of different classifiers on different audio feature sets to determine the genre of a given music piece. for each classifier, we also evaluate performances of feature sets obtained by dimensionality reduction methods. finally, we experiment on increasing classification accuracy by combining different classifiers. using a set of different classifiers, we first obtain a test genre classification accuracy of around 79.6 ± 4.2% on 10 genre set of 1000 music pieces. this performance is better than 71.1 ± 7.3% which is the best that has been reported on this data set. we also obtain 80% classification accuracy by using dimensionality reduction or combining different classifiers. we observe that the best feature set depends on the classifier used.
character extraction from natural scene images by hierarchical classifiers. this paper proposes a method to extract character regions in natural scene images by hierarchical classifiers. the hierarchy consists of two types of classifiers : histogram based classifier and svm. on the bottom level, fast and reliable histogram based classifier is used to reject apparent non-character regions. on the next level, a non-linear svm is exploited to make a final decision. one of the drawbacks of non-linear svms is its computational cost. to reduce the computational cost, we use sparse wavelet representation. moreover, to reduce the cost further, we propose a method to approximate a svm with sparse support vectors. we experimentally show this two-step method can perform very well with respect to both the computational cost and recognition rate.
reconstructing 3d human body pose from stereo image sequences using hierarchical human body model learning. this paper presents a novel method for reconstructing a 3d human body pose using depth information based on top-down learning. the human body pose is represented by a linear combination of prototypes of 2d depth images and their corresponding 3d body models in terms of the position of a predetermined set of joints. in a 2d depth image, the optimal coefficients for a linear combination of prototypes of 2d depth images can be estimated using least square minimization. the 3d body model of the input depth image is obtained by applying the estimated coefficients to the corresponding 3d body model of prototypes. in the learning stage, the proposed method is hierarchically constructed by classifying the training data recursively into several clusters with silhouette images and depth images. in applying hierarchical human body model learning to estimate 3d human body pose, the similar pose in a silhouette image can be estimated as a different 3d human body pose. the proposed method has been tested with 20 persons' sequences. the proposed method achieved the average errors 0f 12.3 degree for all human body components.
detection of fence climbing from monocular video. this paper presents a system that detects humans climbing fences. after extracting a binary blob contour, the system models the human with an extended star-skeleton representation consisting of the highest contour point and the blob centroid as the two stars. distances between stars and contour points are computed and smoothed to detect local maximum points. the system then finds certain predicates to form a feature vector for each frame. to analyze the resulting time series, a block based discrete hidden markov model (hmm) is built with predefined action classes {walk, climb up, cross over, drop down} as the state blocks. each block contains a subset of hidden states and is trained independently to improve the model estimation accuracy with a limited number of sequences. the detection is achieved by decoding the state sequence of the block based hmm. the experiments on image sequences of human climbing fences yield excellent results.
an integrated decoding framework for audio watermark extraction. this paper proposes a blind audio watermark extraction technique that allows performing watermark decoding while installing data synchronization. the proposed decoding algorithm employs correlation techniques supported by a wavelet denoising process, thus improves the decoding performance significantly. a data adaptive nonlinear mpeg layer 1 model 1 compatible watermark encoder is designed for watermark embedding. a channel encoder is also included into the system to take the advantage of error correction. the method does not require the original audio for decoding and it is robust to channel noise, filtering as well as stereo-to-mono conversions. it allows working at very low watermark-to-signal ratios thus preserves inaudibility.
arm-pointing gesture interface using surrounded stereo cameras system. we propose an interface achieved using surrounding stereo cameras as a method of independently recognizing the intentional arm-pointing gestures of several users. the stereo cameras provide depth information maps in real time with resulting robustness against the influence of changes in lighting and users' clothing. utilizing this, we developed a method capable of sensing intentional arm-pointing gestures that ignored unconscious arm-pointing gestures. this interface does not depend on the user's position, direction, or posture. we placed four stereo cameras in four corners of the ceiling and used this method in various lighting environments. we evaluated the arm-pointing gestures of seven subjects at multiple points and obtained reliable accuracy. furthermore, we applied this method to the arm-pointing gesture interface of home electronics appliances using bluetooth.
morphological analysis of spatio-temporal patterns for the segmentation of cyclic human activities. this paper describes a new method for the temporal segmentation of human actions based on a 2d inter-frame similarity plot. this similarity matrix contains relevant information for the analysis of cyclic and symmetric human activities, where the motion performed during the first semi-cycle is repeated in the opposite direction during the second semi-cycle. thus, the pattern associated to a periodic activity in the similarity matrix is rectangular and decomposable into elementary units. we propose a morphology-based approach for the detection and analysis of activity patterns. pattern extraction is further used for the detection of the temporal boundaries of the cyclic symmetric activities. result evaluation approach is based on a statistical estimation of the ground truth segmentation and on a confidence ratio for temporal segmentations. research reported in this paper was supported by a discovery grant of the national sciences and engineering research council of canada.
support vector machine with orthogonal chebyshev kernel. an orthogonal chebyshev kernel function for support vector machine (svm) is proposed based on extensive research about the properties of kernel functions. chebyshev polynomials are firstly constructed through chebyshev formulae. then based on these polynomials chebyshev kernels are created satisfying mercer condition. as chebyshev polynomial has the best uniform proximity and its orthogonality promises the minimum data redundancy in feature space, it is possible to represent the data with less support vectors. experimental result shows that compared with other tradition support vector machines, chebyshev kernel support vector machine performs much better and has less support vectors. chebyshev kernel also has the ability of generalization. it is proved to be an excellent, widely suited and practical kernel both theoretically and experimentally.
an experimental study on automatic face gender classification. this paper presents an experimental study on automatic face gender classification by building a system that mainly consists of four parts, face detection, face alignment, texture normalization and gender classification. comparative study on the effects of different texture normalization methods including two kinds of affine mapping and one delaunay triangulation based warping as preprocesses for gender classification by svm, lda and real adaboost respectively is reported through experiments on very large sets of snapshot images.
shape reconstruction and image restoration for non-flat surfaces of documents with a stereo vision system. in this paper, we propose a shape reconstruction and image restoration method for paper documents with curved surfaces or fold lines by using a stereo vision system. characters in images of thick book's pages acquired with an image scanner are difficult to recognize because they are deformed under the influence of curved surface. therefore, 3-d shape reconstruction of the book's surface is executed from the result of the stereoscopic measurement by putting the book upward, and an image of a flat surface is recovered from the curved or folded surface. the validity of the proposed method is shown through experiments.
1d-pca, 2d-pca to nd-pca. in this paper, we first briefly reintroduce the 1d and 2d forms of the classical principal component analysis (pca). then, the pca technique is further developed and extended to an arbitrary n-dimensional space. analogous to 1d- and 2d-pca, the new nd-pca is applied directly to n-order tensors (n . 3) rather than 1-order tensors (1d vectors) and 2-order tensors (2d matrices). in order to avoid the difficulties faced by tensors computations (such as the multiplication, general transpose and hermitian symmetry of tensors), our proposed nd-pca algorithm has to exploit a newly proposed higher-order singular value decomposition (ho-svd). to evaluate the validity and performance of nd-pca, a series of experiments are performed on the frgc 3d scan facial database.
3d human body measurement by multiple range images. a compact and high-speed 3d human body measurement system is proposed. whole human body data which we can take from systems that have been developed with a few viewpoints is not successfully acquired due to occlusion. it is proposed a method that can obtain successful data by allocating multiple rangefinders correctly. four compact rangefinders are installed in a pole. those four pole units with 16 rangefinders are assigned around a human. multiple viewpoint range images allow the 3d shape reconstruction for a human body. the measurement time is 2 seconds and the average error is found to be 1.88 mm. in this paper, system configuration, calibration and experimental results are described.
separating reflections from images using kernel independent component analysis. when we view a scene through transparent glass, the image is a linear superposition of two images, a real image observed through a glass and a virtual image reflected on it. we can separate the reflections by a polarization and independent component analysis (ica). since the image observed through digital camera is non-linearly transformed by gamma correction etc, it may cause error in image processing for image analysis and measurement. the kernel-based methods are effective for such non-linearity. in this paper, we remove the reflections by using kernel independent component analysis (kica) and show that kica is more effective than ica even if the observed image is non-linearly transformed by camera.
stochastic framework for symmetric affine matching between point sets. this paper presents a new approach to obtain symmetry in point matching problem. here, symmetric matching means the essential property that the choices of source and target should not determine the eventual matching results. most earlier approaches to achieve symmetric matching have been in deterministic fashions, where symmetry constraints are added into the matching cost functions to impose source-target symmetric property during the matching process. nevertheless, these modified cost functions cannot generally converge to real ground truth, and further, the perfect source-target symmetry cannot be achieved. given initial forward and backward matching matrices pair, computed from any reasonable matching strategies, our approach yields perfectly symmetric mapping matrices from a stochastic framework that simultaneously considers the errors underneath the initial matching matrices and the imperfectness of the symmetry constraint. an iterative generalized total least square (gtls) strategy has been developed such that perfect source-target symmetry is imposed.
multiple camera calibration with bundled optimization using silhouette geometry constraints. we propose a method of calibrating multiple camera systems that operates by adjusting the camera parameters and the 3d shape of objects onto silhouette observations. our method employs frontier points, which are geometrically meaningful points on object surfaces, to determine the geometrical relations among multiple cameras. in contrast to conventional methods, both camera parameters and the 3d positions of the frontier points are jointly estimated by minimizing the 2d projection errors between the 2d projected positions of the frontier points and observed silhouette contours for all cameras. this method makes it possible to obtain accurate calibration results without using any special instruments. experimental results using real image data demonstrate the effectiveness of our method.
an omnidirectional stereo vision system using a single camera. we describe a new omnidirectional stereo imaging system that uses a concave lens and a convex mirror to produce a stereo pair of images on the sensor of a conventional camera. the light incident from a scene point is split and directed to the camera in two parts. one part reaches camera directly after reflection from the convex mirror and forms a single-viewpoint omnidirectional image. the second part is formed by passing a subbeam of the reflected light from the mirror through a concave lens and forms a displaced single viewpoint image where the disparity depends on the depth of the scene point. a closed-form expression for depth is derived. since the optical components used are simple and commercially available, the resulting system is compact and inexpensive. this, and the simplicity of the required image processing algorithms, make the proposed system attractive for real-time applications, such as autonomous navigation and object manipulation. the experimental prototype we have built is described.
joint image segmentation and interpretation using iterative semantic region growing on sar sea ice imagery. segmentation of images into disjoint regions and interpretation of the regions for semantic meanings are two central tasks in an image analysis system. typically, the segmentation and interpretation are performed separately with the interpretation as a post processing of segmentation. in this paper, we use an iterative method that keeps refining the segmentation and producing semantic class labels at the same time. the segmentation algorithm is based on a region growing technique and the interpretation is a markov random field (mrf) based classification. the two processes are integrated under the bayesian framework, with both aiming at reducing a defined energy. the interactions between the two are bidirectional by letting the interpretation result have some degree of control on the region growing process. various features can hence be efficiently combined, and accurate classifications are obtained for operational synthetic aperture radar (sar) sea ice applications.
a maximum a posteriori probability viterbi data association algorithm for ball tracking in sports video. in this paper, we derive a data association algorithm for object tracking in a maximum a posteriori framework: the output of the algorithm is the sequence of measurement-totarget associations with maximum a posteriori probability. we model the object motion as a markov process, and solve this otherwise combinatorially complex problem efficiently by applying the viterbi algorithm. a method for combining forward and backward tracking results is also developed, to recover from tracking errors caused by abrupt motion changes of the object. the proposed algorithm is applied to broadcast tennis video to track a tennis ball. experiments show that its performance is comparable to that of a computationally more expensive particle-filter-based algorithm.
classifier combination based on active learning. in this paper, we propose classifier combination based on active learning, which deals with the design of classifier combination systems as training a combiner at the aggregation level and introduces svm active learning into the design of this multi-category decision combiner. this algorithm presented greatly reduces the number of labeled data the classifier system needs in order to achieve satisfactory performance. this algorithm consists of two main steps: firstly designing and training first level classifiers which can output posterior probability vectors as the input of the second level combiner, secondly designing second level combiner based on svm active learning and classifying testing samples with this combiner. experiments on standard database show that our algorithm performs better than current classifier combination rules when considering both labeling cost and classification accuracy.
string kernels for matching seriated graphs. graph seriation allows the nodes of a graph to be placed in a string order, and then matched using string alignment algorithms. prior work has used bayesian methods to derive the string edit costs required in matching. the aim in this paper is to demonstrate how the matching of seriated graphs can be kernelised. to do this we make use of string kernels and show how the parameters of the kernels can be linked to edge density. we illustrate that the graph edit distances computed using the string kernel can be used for graph clustering.
dimensionality reduction with adaptive kernels. a kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. in this work, we propose a kind of new kernel, called locality- adaptive-kernel (lake), which adaptively measures the data similarity by considering the geometrical structure of the data set. in theory, we prove that the lake is a special marginalized kernel; and intuitively, when the local kernel in lake is constrained to be linear, it has the explicit semantic of merging multiple local linear analyzers into a single global nonlinear one. we show in a toy problem that the kernel principal component analysis with lake well captures the intrinsic nonlinear principal curve of the data set. moreover, a large set of experiments are presented to verify that the classification performance is sensitive to the kernel variation; and the extensive face recognition experiments on different databases demonstrate that kpca and kda based on lake are both superior to those based on traditional fixed kernels.
estimation of rigid and non-rigid facial motion using anatomical face model. we present a model-based approach to recover the rigid and non-rigid facial motion parameters in video sequences. our face model is based on anatomically motivated muscle actuator controls to model the articulated non-rigid motion of a human face. the model is capable of generating a variety of facial expressions by using a small number of muscle actuator controls. we estimate rigid and non-rigid parameters in two steps. first, we use a multi-resolution scheme to recover the global 3d rotation and translation by linear least squareminimization. then, we estimate the muscle actuator controls using the levenberg-marquardt minimization technique applied to a function, which is constrained by both optical flow and the dynamics of the deformable model. we present the results of our system on both real and synthetic images.
a nonlinear variational model for pet reconstruction. pet image was often influenced by noise. in this paper, we proposed a nonlinear variational model for improving reconstruction of pet images. the use of variational model was due to its effectiveness for reducing noise in 2d images while preserving edges. our results indicated that the proposed method application to computer-simulated and real pet phantom outperformed the conventional method in terms of both visual quality and quantitative accuracy.
combining cepstral and prosodic features in language identification. a novel approach of combining cepstral features and prosodic features in language identification is presented in this paper. this combination approach shows a significant improvement on a gmm-ubm based language identification (lid) system which utilizes modern shifted delta cepstrum (sdc) and feature warping techniques. the proposed system achieves a high accuracy of 87.1% on a 10-language task, and outperforms the baseline system by 12%. the prosodic features are proven to be very effective in both tonal and non-tonal lid, as they deliver new language-discrimination information in addition to those from widely used cepstral features. additionally, the performance of mfcc and plp features with different coefficient numbers in language identification tasks are researched and compared. less number of coefficients is more likely to be sufficient or even better for language identification.
improving retrieval performance by long-term relevance information. relevance feedback (rf) is an iterative process which improves the retrieval performance by utilizing the user's feedback on retrieved results. traditional rf techniques use solely the short-term experience and are short of knowledge of cross-session agreement. in this paper, we propose a novel rf framework which facilitates the combination of short-term and long-term experiences by integrating the traditional methods and a new technique called the virtual feature. the feedback history of all the users is digested by the system and is represented as a virtual feature of the images. as such, the dissimilarity measure can be adapted dynamically depending on the estimate of the relevance probability derived from the virtual features. the results manifest that the proposed framework outperforms the one that adopts a single traditional rf technique.
extended isomap for classification. the isomap method has demonstrated promising results in finding a low dimensionalembedding from samples in the high dimensional input space. the crux of this method is to estimate geodesic distance with multidimensional scaling fo dimensionality eduction. since the isomap method is developed based on the reconstruction principle, it may not be optimal from the classification viewpoint. we present an extended isomap method that utilizes fisher linear discriminant for pattern classification. numerous experiments on image data sets show that our extension is more effective than the original isomap method for pattern classification. furthermore, the extended isomap shows promising results compared with best classification methods in the literature.
a unification framework for tree and block wavelet encoders. wavelet transform coefficient encoders are broadly categorized as depending on correlations: across sub-bands through a zerotree, or within sub-bands through a block quad-tree. this paper proposes a unification framework that allows a suitable algorithm to be crafted according to need. an example block-tree algorithm is described in detail, and results show that the performance closely approaches a state-of-the-art encoder, without needing the complexity of arithmetic coding.
statistical model for the classification of the wavelet transforms of t-ray pulses. this study applies auto regressive (ar) and auto regressive moving average (arma) modeling to wavelet decomposed terahertz pulsed signals to assist biomedical diagnosis and mail/packaging inspection. t-ray classification systems supply a wealth of information about test samples to make possible the discrimination of heterogeneous layers within an object. in this paper, the classification of normal human bone (nhb) osteoblasts against human osteosarcoma (hos) cells and the identification of seven different powder samples are demonstrated. a correlation method and an improved prony's method are investigated in the calculation of the ar and arma model parameters. these parameters are obtained for models from second to eighth orders and are subsequently used as feature vectors for classification. for pre-processing, wavelet de-noising methods including the sure (stein's unbiased estimate of risk) and heuristic sure soft threshold shrinkage algorithms are employed to de-noise the normalised t-ray pulsed signals. a mahalanobis distance classifier is used to perform the final classification. the error prediction covariance of ar/arma modeling and the classification accuracy are calculated and used as metrics for comparison.
sammon's nonlinear mapping using geodesic distances. sammon's nonlinear mapping (nlm) is an iterative procedure to project high dimensional data into low dimensional configurations. this paper discusses nlm using geodesic distances and proposes a mapping method geonlm. we compare its performance through experiments to the performances of nlm and isomap. it is found that both geonlm and isomap can unfold data manifolds better than nlm. geonlm outperforms isomap when the short-circuit problem occurs in computing the neighborhood graph of data points. in turn, isomap outperforms geonlm if the neighborhood graph is correctly constructed. these observations are discussed to reveal the features of geodesic distance estimation by graph distances.
analyzing facial expressions using intensity-variant 3d data for human computer interaction. research on automatic techniques for analyzing human facial behavior has been intensified, driven by the emerging research field of affective computing [10, 9] and its important application in human computer interaction and intelligent systems. the face surface is a three dimensional timevarying 'wave', which is associated with the movement of facial expressions. tracing the behavior of the 3d primitive features could reveal precious information about the nature of the underlying physical process. in this paper, we propose to study the intensity-variant facial expressions in a 3d space. we present a new approach for 3d expression model analysis, tracking and classification. we demonstrate the feasibility and advantage of the proposed method using the 3d range data for prototypic 3d facial expression recognition.
k-edge connected neighborhood graph for geodesic distance estimation and nonlinear data projection. nonlinear data projection based on geodesic distances requires the construction of a neighborhood graph that spans all data points so that the geodesic distance between any pair of data points could be estimated by the graph distance between the pair. this paper proposes an approach for constructing a k-edge connected neighborhood graph. the approach works by repeatedly extracting minimum spanning trees from the complete euclidean graph of all data points. the constructed neighborhood graph has the following properties: (1) it is k-connected; (2) each point connects to its k nearest neighbors; (3) if the graph is cut into two partitions, the cut edges contain k shortest edges between the two partitions. experiments show that the presented approach works well for clustered data and outperforms the nearest neighbor approaches used in isomap for evenly distributed data.
spherical objects based motion estimation for catadioptric cameras. in this paper, spherical objects are employed to estimate motion parameters between two central catadioptric cameras. an occluding contour of a sphere is projected to a conic in the central catadioptric image, and such a conic is called a sphere image. the main contribution of this work is that such a sphere image is shown to be able to be parameterized by only three parameters rather than five ones as a generic conic requires. based on such a finding, an efficient motion estimation algorithm is proposed which consists of the following three main steps: firstly, sphere images are efficiently detected by the hough transform and refined by minimizing the orthogonal distances. secondly, the centers of these spherical objects are estimated from the above obtained sphere images in the two catadioptric camera coordinate systems respectively. thirdly, motion parameters are estimated from the corresponding centers. the proposed algorithm is shown workable by experiments and can be applied to camera network calibration and robot localization.
building connected neighborhood graphs for locally linear embedding. locally linear embedding is a nonlinear method for dimensionality reduction and manifold learning. it requires well-sampled input data in high dimensional space so that neighborhoods of all data points overlap with each other. in this paper, we build connected neighborhood graphs for the purpose of assigning neighbor points. a few methods are examined to build connected neighborhood graphs. they have made lle applicable to a wide range of data including under-sampled data and non-uniformly distributed data. these methods are compared through experiments on both synthetic and real world data sets.
catadioptric line features detection using hough transform. a line in space is projected to a conic in the central catadioptric image, and such a conic is called a line image. this paper proposes a novel approach for efficiently detecting line images using hough transform. detecting line images brings two novel challenges for conic detection: one is that effects of occlusion are very significant where traditional conic detecting methods may fail, the other is that line images can belong to any type of conic, such as, line, circle, ellipse, hyperbola, parabola etc., and it is very difficult to detect a conic when its type is unknown. the main contribution of this work is that we prove a line image can be parameterized by only two parameters on the gaussian sphere rather than five ones as a generic conic requires, and the above two challenges can be substantially solved accordingly. the validity of our proposed approach is illustrated by experiments.
locally multidimensional scaling for nonlinear dimensionality reduction. a data embedding method is introduced to configure global coordinates of data using local distances as input. the method applies classical multidimensional scaling within a neighborhood of each data point. the local models are then aligned to derive global coordinates in order to minimize a residual measure. the residual measure has a quadratic form of resulting global coordinates, which makes the alignment problem solved analytically by using an eigensolver. experiments show that the method produces less deformed embedding results than locally linear embedding. variations of the method and possible extensions are also discussed.
fast leave-one-out evaluation and improvement on inference for ls-svms. in this paper, a fast leave-one-out (loo) evaluation formula is introduced for least squares support vector machine (ls-svm) classifiers. the computation cost can be reduced to approximately 1/n when compared to normal loo procedure (is the number of training samples). inspired by its fast speed, we are able to use it to replace the original level 3 posterior probability approximation formula of the bayesian framework [bayesian framework for least squares support vector machine classifiers, gaussian processes and kernel fisher discriminant analysis] for ls-svm classifiers. the improved inference framework shows higher generalization performance and faster computation speed.
face pose estimation and its application in video shot selection. in this paper, a face pose estimation method and its application in video shot selection for face image preprocessing is introduced. the pose estimator is learned by a boosting regression algorithm called squarelev.r [boosting methods for regression] that learns poses from simple haar-type features. it consists of two tree structured subsystems for the left-right angle and up-down angle respectively. as a specific application in video based face recognition, the best shot selection problem is discussed, which results in a real-time system that can automatically select the most frontal face from a video sequence.
a novel linear approach to camera calibration from sphere images. recently, some linear approaches to camera calibration from sphere images are proposed. in this paper, a novel linear approach is proposed by exploiting the identity constraint on the entries of the matrices for the sphere images, which is much simpler and more intuitive than previous linear ones. this novel algorithm has been tested in extensive experiments with respect to noise sensitivity.
a combination of generative and discriminative approaches to object detection. this paper presents a new simple algorithm which combines generative and discriminative approaches to object detection. the research makes two key contributions. the first contribution is the introduction of a new algorithm called the dt(decomposition-tree) which is capable of clustering on the manifold of object patterns(using gaussian clusters) and determining the thresholds of each cluster by using hard samples which are selected during learning. the second contribution is that the learning time of the dt algorithm has been reduced rapidly. because the dt algorithm shows spatial relationships of training patterns in the form of a tree, it requires relearning rather than new learning. to evaluate the performance of the proposed object detection algorithm, we experimented with face detection. the dt algorithm yields face detection performance comparable to that of the best previous systems[4]
using sphere images for calibrating fisheye cameras under the unified imaging model of the central catadioptric and fisheye cameras. this paper proposes a novel calibration method for fisheye cameras using sphere images which is an extension of the calibration method for central catadioptric cameras. we show that, each sphere image under fisheye cameras is tangent to the modified calibrating conic (mcc) at two double-contact image points. the calibration method is proposed by first finding the double-contact image points, then fitting the mcc, and final obtaining the intrinsic parameters using the ldlt factorization of the mcc.
stereo camera based non-contact non-constraining head gesture interface for electric wheelchairs. for persons with severe disabilities who find it difficult to operate the joystick or the chin stick of an electric wheelchair, we have developed an interface that allows the wheelchair to be operated by gestures such as head movements. by using a camera to perform visual sensing, we aim to implement a non-contact non-constraining interface where no wires or equipment of any kind have to be attached to the user, thereby making the interface much more convenient to use. range information obtained from a stereo camera is used to control the electric wheelchair in any situation regardless of whether it is used indoors or outdoors. we are keeping this study user-oriented by performing clinical trials with the help of actual users to determine where the camera should be situated, how it should be used, and so on.
skin color detection using multiple cues. in this paper, we present a novel space transformation to describe the skin and non-skin attributes, and build a new non-linear skin color classifier combining the spatial and probabilistic distributions of pixels. to weaken the illumination effect on images, we introduce a new gamma correction (gc) method. experimental results show that our approach has good performance in skin color detection.
binarization and recognition of degraded characters using a maximum separability axis in color space and gat correlation. this paper proposes a new technique of binarization and recognition of characters in color with a wide variety of image degradations and complex backgrounds. the key ideas are twofold. one is to automatically select one axis in the rgb color space that maximizes the between-class separability by a suitably chosen threshold for segmentation of character and background or binarization. the other is affine-invariant or distortiontolerant grayscale character recognition using global affine transformation (gat) correlation that yields the maximum correlation value between input and template images. in experiments, we use a total of 698 test images extracted from the public icdar 2003 robust ocr dataset containing a variety of single-character images in natural scenes. in advance, we classify those images into seven groups according to the degree of image degradations and/or background complexity. on the other hand, we only prepare a single-font set of 62 alphanumerics for templates. experimental results show an average recognition rate of 81.4%, ranging from 94.5% for clear images to 39.3% for seriously distorted images.
a novel approach to detecting adult images. this paper presents a novel approach to recognizing adult images. to effectively detect the rois (region of interest) with plentiful skin information, we structurize an image with regions and points. then based on the rois, we obtain some reliable features for image classification. experimental results show that our algorithm performs well in detecting objectionable images.
line-based affine invariant object location using transformation space decomposition. this paper presents a novel line-based affine invariant object location methodology. our algorithm employs a new line-based transformation space decomposition technique to exploit intrinsic structural information provided by line features. furthermore, we propose a new line-based distance transform to integrate with our algorithm to provide efficient transformation cell evaluation and subdivision in a coarse to fine manner. the algorithm is able to rapidly accelerate the searching process while maintaining high discriminative power and minimal storage requirement. the efficiency and discriminative power of this methodology are demonstrated using real-world examples with promising results.
human perception based color image quantization. we present a new algorithm for color image quantization based on human color perception properties. we construct two kinds of map by analyzing the spatial color distributions to take account of the human visual system; homogeneity map (h-map) and distinctiveness map (d-map). then, we assign weight value to all color vectors by combining these maps to consider two factors at the same time. to extract representative colors, we define a new cost function and use the lkma (local k-means algorithm) with weighted color vectors. in this stage, we utilize an incremental splitting scheme with a penalty term to determine optimal number of clusters adaptively. the experimental results show that proposed algorithm reproduces an image preserving significant local features while removing unimportant details of an original image from the viewpoint of human.
multi-snr gmms-based noise-robust speaker verification using 1/fa noises. environmental noises greatly degrade the performance of speaker verification system. this paper designs a novel noise-robust speaker verification system based on multi- snr techniques using 1/f\alpha noises. during training phase, the 1/f\alpha noises are employed to simulate environmental noises. to simplify the computation load, an optimal value of a is selected. to evaluate the performance of the system, speaker verification experiments are conducted on 5 kinds of environmental noises: "airport", "bus", "lobby", "restaurant", and "office" at 0db snr. the experimental results demonstrate that a notable degradation of verification error rates is obtained while using 1/f\alpha noises.
reconstruction of 3d face model from single shading image based on anatomical database. we propose a method to reconstruct 3d face model from a single face-frontal shading image based on a database of the original 3d face shapes which are created according to anatomical basis of the human head. in the proposed method, we reconstruct the 3d shape of the face from the input shading image by estimating small number of eigen- values taken by principal component analysis(pca) of the anatomical database of the head, rather than directly recov- ering the shape from the input shading image. the eigen- values are estimated based on the optimization of the error value computed by comparing shading information of input image to that of model image created from the shape rep- resented by the eigenvalues. for evaluating the effective- ness, we reconstruct various face shapes from single shad- ing images of the objects based on the proposed method. the reconstructed shape for a statue of head with the av- erage shape of the databases provides an error evaluation, which is 2.6mm in average. this is sufficiently accurate for the future applications, such as on-line order-made of face- wearing products.
multiple pedestrian detection and tracking based on weighted temporal texture features. this paper presents a novel method for detecting and tracking pedestrians from video images taken by a fixed camera. a pedestrian may be totally or partially occluded in a scene for some period of time. the proposed approach uses the appearance model for the identification of pedestrians and the weighted temporal texture features. we compared the proposed method with other related methods using color and shape features, and analyzed the features' stability. experimental results with various real video data revealed that real time pedestrian detection and tracking is possible with increased stability over 5-15% even under occasional occlusions in video surveillance applications.
confidence-driven architecture for real-time vision processing and its application to efficient vision-based human motion sensing. in this paper, we discuss a real-time vision architecture which provides a mechanism of controlling trade-off between the accuracy and the latency of vision systems. in vision systems, to acquire accurate information from input-images, the huge amount of computation power is usually required. on the other hand, to realize real-time processing, we must reduce the latency. therefore, under given hardware resources, we must make difficult trade-off between the accuracy and the latency so that the quality of the system's output keeps appropriate. to solve the problem, we propose confidence-driven scheme, which enables us to control the trade-off dynamically and easily without rebuilding vision systems. in the confidence-driven architecture, the trade-off can be controlled by specifying a generalized parameter called confidence, which relatively indicates how accurate the analysis should be. here, we present the concept of confidence-driven architecture, and then, we show a shared memory which uses confidence-driven scheme. using confidence-driven memory, we can use imprecise computation model to reduce the latency without a large decrease of accuracy.
automatic physiognomic analysis by classifying facial component feature. this paper presents a method for generating physiognomic information from facial images, by analyzing features of facial components. the physical personality of the face can be modeled by the combination of facial feature components. the facial region is detected from an input image, in order to analyze the various facial feature components. then, the gender of the subject is subsequently classified, and facial components are extracted. the active appearance model (aam) is used to extract facial feature points. from these facial feature points, 16 measures are computed to distinguish each facial component into defined classes, such as large eye, small mouth, and so on. after classifying facial components with each classification criterion and gender of subject, physiognomic information is generated by combining the classified results of each classification criteria. the proposed method has been tested with 200 persons' samples. the proposed method achieved a classification rate of 85.5% for all facial components feature.
emotional speech analysis on nonlinear manifold. this paper presents a speech emotion recognition system on nonlinear manifold. instead of straight-line distance, geodesic distance was adopted to preserve the intrinsic geometry of speech corpus. based on geodesic distance estimation, we developed an enhanced lipschitz embedding to embed the 64-dimensional acoustic features into a sixdimensional space. in this space, speech data with the same emotional state were located close to one plane, which was beneficial to emotion classification. the compressed testing data were classified into six archetypal emotional states (neutral, anger, fear, happiness, sadness and surprise) by a trained linear support vector machine (svm) system. experimental results demonstrate that compared with traditional methods of feature extraction on linear manifold and feature selection, the proposed system makes 9%-26% relative improvement in speaker-independent emotion recognition and 5%-20% improvement in speaker-dependent.
face representation by using non-tensor product wavelets. this paper presents a new approach to represent face by using a non-tensor product bivariate wavelet filters. a new non-tensor product bivariate wavelet filter banks with linear phase are constructed from the centrally symmetric matrices. our investigations demonstrate that these filter banks have a matrix factorization and they are capable of representing facial features for recognition. the implementations of our algorithm are made of three parts: first, face images are represented by the lowest resolution subbands after 2-level new non-tensor product wavelet decomposition. second, the principal component analysis (pca) feature selection scheme is adopted to reduce the computational complexity of feature representation. finally, support vector machines (svm) is applied for classification.the experimental results show that our method is superior to other methods in terms of recognition accuracy and efficiency.
document image ground truth generation from electronic text. the problem of generating synthetic data for the training and evaluation of document analysis systems has been widely addressed in recent years. with the increased interest in processing multilingual sources, however, there is a tremendous need to be able to rapidly generate data in new languages and scripts, without the need to develop specialized systems. we have developed an approach, which uses language support of the ms windows operating system combined with custom print drivers to render tiff images simultaneously with windows enhanced metafile directives. the metafile information is parsed to generate zone, line, word, and character ground truth including location, font information and content in any language supported by windows. the resulting images can be physically or synthetically degraded, and used for training and evaluating ocr systems. in this paper, we briefly survey related work and describe our system.
comparison of similarity measures for trajectory clustering in outdoor surveillance scenes. this paper compares different similarity measures used for trajectory clustering in outdoor surveillance scenes. six similarity measures are presented and the performance is evaluated by correct clustering rate (ccr) and time cost (tc). the experimental results demonstrate that in outdoor surveillance scenes, the simpler pca+euclidean distance is competent for the clustering task even in case of noise, as more complex similarity measures such as dtw, lcss are not efficient due to their high computational cost .
neighborhood discriminant projection for face recognition. we propose a novel manifold learning approach, called neighborhood discriminant projection (ndp), for robust face recognition. the purpose of ndp is to preserve the within-class neighboring geometry of the image space, while keeping away the projected vectors of the samples of different classes. for representing the intrinsic within-class neighboring geometry and the similarity of the samples of different classes, the within-class affinity weight and the between-class affinity weight are used to model the within-class submanifold and the between-class submanifold of the samples, respectively. comprehensive comparisons and extensive experiments on face recognition are performed to demonstrate the effectiveness and robustness of our proposed method.
learning-based license plate detection using global and local features. this paper proposes a license plate detection algorithm using both global statistical features and local haar-like features. classifiers using global statistical features are constructed firstly through simple learning procedures. using these classifiers, more than 70% of background area can be excluded from further training or detecting. then the adaboost learning algorithm is used to build up the other classifiers based on selected local haar-like features. combining the classifiers using the global features and the local features, we obtain a cascade classifier. the classifiers based on global features decrease the complexity of the system. they are followed by the classifiers based on local haar-like features, which makes the final classifier invariant to the brightness, color, size and position of license plates. the encouraging detection rate is achieved in the experiments.
geodesic closest point constrained inter-subject non-rigid registration. in this paper, we propose an inter-subject brain registration method by combining the intensity and the geodesic closest point based similarity metric. each of the brain hemisphere can be topologically equalized into a sphere. the inter-subject variance can be better reduced by using cortical surface based analysis method[high-resolution intersubject averaging and a coor-dinate system for the cortical surface, surface-based analysis i: segmentation and surface reconstruc-tion]. a one to one mapping of the points on spherical surfaces of two subjects can be achieved by using this technique. we find the geodesic correspondence between subjects by using spherical registration first. then the correspondence on the cortical surface between subjects are used to guide the volumetric inter-subject registration. by adding these anatomical constraints of the cortical surface, the inter-subject registration result will be more anatomically meaningful and accurate. the cortical surface correspondence between subjects can be combined with the general non-rigid registration. in our experiments, the proposed method performs better than the method of hartkens et al [using points and surfaces to improve voxel-based non-rigid registration].
supervised learning for guiding hierarchy construction: application to osteo-articular medical images database. most merging and splitting segmentation methods aim to construct a hierarchical structure from an image by minimizing or maximizing a homogeneity measure. this latter generally includes radiometrical information, but rarely includes geometrical information and ignore the high level information on the image content. moreover, the hierarchies issued from these approaches may suffer from a structural instability and deficiency in the "semantic" of the regions related to the image content and to the energy or the criterion which does not contain any high level prior knowledge. in this paper, we propose to improve the semantic content of the hierarchy by adding a new term called "contextual cost". this term integrates the prior knowledge on the image, derived from a classifier after a supervised learning on the semantic classes composing the image. its purpose is to better drive the merging process in the construction of meaningful regions by penalizing spurious fusions.
elastic face, an anatomy-based biometrics beyond visible cue. this paper describes a face recognition method that is designed based on the consideration of anatomical and biomechanical characteristics of facial tissues. elastic strain pattern inferred from facial expression can reveal an individual's biometric signature associated with the underlying anatomical structure, and thus has the potential for face recognition. a method based on the continuum mechanics in finite element formulation is employed to compute the strain pattern. experiments show very promising results. the proposed method is quite different from other face recognition methods, and both its advantages and limitations, as well as future research for improvement are discussed.
super-resolution restoration of facial images in video. reconstruction-based super-resolution has been widely treated in computer vision. however, super-resolution of facial images has received very little attention. since different parts of a face may have different motions in normal videos, this paper proposes a new method for enhancing the resolution of low-resolution facial image by handling the facial image non-uniformly. we divide low-resolution face image into different regions based on facial features and estimate motions of each of these regions using different motion models. our experimental results show we can achieve better results than applying super-resolution on the whole face image uniformly.
filament preserving segmentation for sar sea ice imagery using a new statistical model. modelling spatial context constraints using markov random field (mrf) has been widely used in the segmentation of noisy images [7][10][17]. its applicability to sar sea ice segmentation has also been demonstrated recently [6]. however, most existing mrf models are not capable of preserving filaments, specifically leads and ridges for sar sea ice, which are valuable for ship navigation applications and helpful for identifying certain ice types. a new statistical context model is proposed that can preserve such narrow elongated features while producing similar smooth segmentation results as those of existing mrf based approaches.
point pattern matching for articulated or multiple objects. an efficient point pattern matching algorithm for articulated and multiple objects is presented in this paper. a local to global strategy is adopted to get three layered matches starting from an initial partition of the point set using clustering method. firstly, initial match with three point correspondences is obtained through local neighborhood and exhaustive search. then, cental match is expanded from initial match by alternating between next point matching and transformation update. finally, ambiguous boundary points are matched and classified into their correspondent parts using the estimated alignment transformations, and missing or extra points are detected and rejected as outliers. experiments on real images present satisfying results.
boosted markov chain monte carlo data association for multiple target detection and tracking. in this paper, we present a probabilistic framework for automatic detection and tracking of objects. we address the data association problem by formulating the visual tracking as finding the best partition of a measurement graph containing all detected moving regions. in order to incorporate model information in tracking procedure, the posterior distribution is augmented with adaboost image likelihood. we adopt a mrf-based interaction to model the inter-track exclusion. to avoid the exponential complexity, we apply markov chain monte carlo (mcmc) method to sample the solution space efficiently. we take data-oriented sampling driven by an informed proposal scheme controlled by a joint probability model combining motion, appearance and interaction among detected regions. proposed data association method is robust and efficient, capable of handling extreme conditions with very noisy detection.
real-time face detection using boosting in hierarchical feature spaces. boosting-based methods have recently led to the state-of-the-art face detection systems. in these systems, weak classifiers to be boosted are based on simple, local, haar-like features. however, it can be empirically observed that in later stages of the boosting process, the non-face examples collected by bootstrapping become very similar to the face examples, and the classification error of haar-like feature-based weak classifiers is thus very close to 50%. as a result, the performance of a face detector cannot be further improved. this paper proposed a solution to this problem, introducing a face detection method based on boosting in hierarchical feature spaces (both local and global). we argue that global features, like those derived from principal component analysis, can be advantageously used in the later stages of boosting, when local features do not provide any further benefit. we show that weak classifiers learned in hierarchical feature spaces are better boosted. our methodology leads to a face detection system that achieves higher performance than a current state-of-the-art system, at a comparable speed.
vignetting distortion correction method for high quality digital imaging. vignetting refers to a position dependent loss of light in the output of an optical system causing gradual fading out of an image near the periphery. in this paper, we propose a method for correcting vignetting distortion by introducing nonlinear model fitting of a proposed vignetting distortion function. the proposed method aims for embedded digital imaging applications as well as conventional image enhancement. we could obtain a light intensity profile distribution without precisely controlled illumination and considerably reduce memory requirement for vignetting correction compared with traditional lookup table (lut) methods. we show the effectiveness of the proposed method by presenting experimental results obtained from commercial digital cameras.
face recognition by combining kernel associative memory and gabor transforms. kernel associative memory (kam) has previously been proposed as an efficient scheme for face recognition. in this paper, a hybrid method of combining kam and gabor wavelet transform is proposed. in this method, face images of each person are first decomposed into their spatial/ frequency domains by gabor transforms, which are then modelled by a kam. while gabor properties of orientation selectivity and spatial frequency selectivity provide discriminating features, kam offers the means to capture the important intra-class variations. experimental results obtained on two standard face databases demonstrated that the proposed method consistently improved the system performance.
shape-based discrimination and classification of cortical surfaces. advances in medical imaging technique make it possible to study shape variations of neuroanatomical structures in vivo, which has been proved useful in the study of neuropathology and neurodevelopment. in this paper, we propose the use of spherical wavelet transformation to extract shape features, as it can characterize the underlying functions in a local fashion in both space and frequency, in contrast to spherical harmonics that have a noncompact basis set. the extracted shape features can be used to statistically detect and visualize group shape differences from a coarse to fine resolution, and facilitate shape-based classification. a procedure is developed to apply this method to cortical surface models, and promising results are acquired on synthetic and real data.
weakly supervised learning on pre-image problem in kernel methods. this paper presents a novel alternative approach, namely weakly supervised learning (wsl), to learn the pre-image of a feature vector in the feature space induced by a kernel. it is known that the exact preimage may typically seldom exist, since the input space and the feature space are not isomorphic in general, and an approximate solution is required in past. the proposed wsl, however, would find an appropriate rather than only a purely approximate solution. wsl is able to involve some weakly supervised prior knowledge into the study of pre-image. the prior knowledge is weak and no class label of the sample is required, providing only information of positive class and negative class which should properly depend on applications. the proposed algorithm is demonstrated on kernel principal component analysis (kpca) with application to illumination normalization and image denoising on faces. evaluations of the performance of the proposed algorithm show notable improvement as comparing with some well-known existing approaches.
spatial-hmm: a new approach for semantic annotation of histological. this paper presents a new spatial-hmm for automatically classifying and annotating histological images. our model is a 2d generalization of hmm. given a matrix of feature vectors for all blocks in an image, the most appropriate semantic labels determined by our models are used for annotation. our experimental results showed that our model is superior to hmm in both recognition and annotation accuracy.
an efficient svm classifier for lopsided corpora. this paper explores application of svm to lopsidedcorpora in text categorization. by means of integrating kernel caching with shrinking policies effectively, an improved svm training algorithm for weightcalculation formula is proposed under the decomposition framework. extensive experiments on lopsided-corpora have been conducted. the conclusion can make it possible to apply the improved svm training algorithm to lopsided corpora in text categorization.
cryptographic key generation from biometric data using lattice mapping. crypto-biometric systems are recently emerging as an effective process of key management to address the security weakness of conventional key release systems using passcodes, tokens or pattern recognition based biometrics. this paper presents a lattice mapping based fuzzy commitment method for cryptographic key generation from biometric data. the proposed method not only outputs high entropy keys, but also conceals the original biometric data such that it is impossible to recover the biometric data even when the stored information in the system is open to an attacker. simulated results have demonstrated that its authentication accuracy is comparable to the well-known k-nearest neighbour classification.
an approximative calculation of relative convex hulls for surface area estimation of 3d digital objects. relative convex hulls have been suggested for multigrid-convergent surface area estimation. besides the existence of a convergence theorem there is no efficient algorithmic solution so far for calculating 3d relative convex hulls. this article discusses an approximative solution based on minimum-length polygon calculations. it is illustrated that this approximative calculation also proves (experimentally) to provide a multigrid convergent measurement.
removing temporal stationary blur in route panoramas. the route panorama is a continuous, compact and complete image representation of scenes along a route. it is generated continuously from reading a preset line in a camera frame that moves along a smooth path. more complicated than the mathematical model of slit scanning, the physical width of a sampling line may yield a temporal blur, named stationary blur, in the route panorama. it is the counterpart of the motion blur and appears at distant scenes. we analyze the sampling of the route panorama, and recover the intrinsic high frequency components from spatiotemporal slit data. the sharpened results enhance the cityscapes archiving and visualization in virtual tour and navigation.
shape recognition using curve segment hausdorff distance. a novel shape recognition approach (cshd) combining the template and syntactic matching schemes is proposed in this paper to generalize the hausdorff distance (hd) from matching two sets of points to matching two sets of lines/curves. the new approach retains the desirable features of hd. these include nonexplicit feature correspondence (natural allowance for portions of one shape to be compared with another) and simplicity in computation. in addition, a fast searching technique is employed to identify a list of likely matches. the proposed system has been applied to logo, palmprint and stationery recognitions with superior results. it has greatly out-performed the hd and is robust to noise, occlusion, skewing and minor broken line effect.
italic font recognition using stroke pattern analysis on wavelet decomposed word images. this paper describes an italic font recognition method using stroke pattern analysis on wavelet decomposed word images. the word images are extracted from scanned text documents containing word objects in various fonts and styles. earlier font recognition methods mainly focus on slanted texture or pattern analysis on single character or large text blocks, which are sensitive to noise and subject to font and style variations such as size, serifness, boldness, etc. our method takes advantage of 2-d wavelet decomposition on each word image and performs statistical analysis on stroke patterns obtained from wavelet decomposed sub-images. experiments are carried out with 22,384 frequently used word images in both normal and italic styles of four different fonts. on average, a recognition accuracy of 95.76% for normal style and 96.49% for italic style is achieved. experiments conducted on word images extracted from scanned documents with scattered italic words also show an encouraging result.
multiresolution block sampling-based method for texture synthesis. we present an efficient multiresolution block sampling-based texture synthesis algorithm that works well for a wide variety of challenging textures. we consider the texture synthesis as a procedure that first estimates and then resamples a probability function. to achieve the effect of good and fast estimation of the probabaility function for a given texture as well as to retain the structural information during synthesis, we propose a concept of block sampling and a corresponding novel scheme of texture synthesis based on multiresolution block sampling (mbs). the computational complexity of the proposed algorithm is much lower than that of existing algorithms. experimental results have shown that this novel texture synthesis algorithm produces superior results for many challenging textures.
recognition of expression variant faces using weighted subspaces. in the past decade or so, subspace methods have been largely used in face recognition - generally with quite success. subspace approaches, however, generally assume the training data represents the full spectrum of image variations. unfortunately, in face recognition applications one usually has an under-represented training set. a known example is that possed by images bearing different expressions; i.e., where the facial expression in the training image and in the testing image diverge. if the goal is to recognize the identity of the person in the picture, facial expressions will be seen as distracters. subspace methods do not address this problem successfully, because the feature-space learned is dependent over the set of training images available - leadingto poor generalization results. in this communication, we show how one can use the deformation of the face (between the training and testing images) to solve the above defined problem. to achieve this, we calculate the facial deformation between the testing and each of the training images, project this result onto the (learned) sub-space, and there weight each of the features (dimensions) inverse-proportionally to the estimated deformation. we show experimental results of our approach on those representations given by the following subspace techniques: principal components analysis (pca), independent components analysis (ica) and linear discriminant analysis (lda). we also present comparison results with a number of known techniques and show the superiority of our weighted lda algorithm over the rest.
accurate 3-d motion tracking with an application to super-resolution. many of the existing image processing applications, in particular the construction of super-resolution videos, require an accurate high-speed motion tracking algorithm. this paper proposes an efficient recursive approach that recovers 3-d motion from a stereo image sequence with high precision based on the trifocal tensor. in the computation process, neither the 3-d structure of the scene nor its reconstruction is necessary. the validity of the proposed algorithm is demonstrated by applying it to upgrade the resolution of real stereo images. empirical comparisons show that our novel approach outperformed traditional work in terms of both the accuracy of motion estimation and the quality of super-resolved images.
a robust algorithm for generalized orthonormal discriminant vectors. in this paper, we propose a robust and efficient algorithm for generalized orthonormal discriminant vectors (godv). the major advantage of the proposed method is the use of the rank-one update technique, rather than the lagrange multipliers method, to iteratively derive the formula of computing the discriminant vectors of godv. by contrast with the previous algorithms of godv, the proposed algorithm has the computational efficiency and the numerical stability because of the avoidance of solving the inverse computation of matrices. moreover, the proposed algorithm can be easily extended to tackle the nonlinear problem via kernel trick. the performance of the proposed algorithm is tested on the yale face database and orl face database, respectively.
effective classification image space which can solve small sample size problem. linear discriminant analysis (lda) is one of the most popular methods in feature extraction and dimension reduction. however, in many real applications, particularly in image recognition applications such as face recognition, conventional lda algorithm will often encounter small sample size problem. in this paper, an effective classification image space is defined and optimal features are extracted from this space. with the proposed method, an effective classification image space of each original image is first obtained. then, optimal features are extracted from this space. the small sample size problem is solved effectively with the proposed method. experimental results on xm2vts face database demonstrate the effectiveness of the proposed method.
adaptive discriminant projection for content-based image retrieval. content-based image retrieval (cbir) is a computer vision application that aims at automatically retrieving images based on their visual content. linear discriminat analysis and its variants have been widely used in cbir applications because of their effectiveness in finding a projection that maps the original highdimensional space to a low-dimensional one and preserves the most discriminant features. those techniques assume images from certain class(es) are all visually similar and try to cluster them in the projected space. in this paper we show that the human high-level concept of semantic similarity between images may not arise only from the low-level visual similarity and consequently that assumption is inappropriate in many cases. we propose an adaptive discrimant projection (adp) framework which could model different data distributions based on the clustering of different classes. to learn the best model fitting the real scenario, boosted adaptive discriminant projection is further proposed. extensive experiments are designed to evaluate our methods and compare them to the state-of-the-art techniques on benchmark data set and real image retrieval applications. the results show the superior performance of our proposed methods.
multiscale feature extraction of finger-vein patterns based on curvelets and local interconnection structure neural network. in this paper, we originally propose a multiscale feature extraction method of finger-vein patterns based on curvelets and local interconnection structure neural networks. the curvelets is used to perform the multiscale self-adaptive enhancement transform on the finger-vein image and a neural network with local interconnection structure is designed to extract the features of the finger-vein pattern. this method has the following features: firstly, the feature of finger-vein is line feature, or anisotropy, which is more suitable to be processed by curvelets than wavelets, especially when dealing with the obscure anisotropic features. secondly, when the multiscale self-adaptive enhancement transform is applied to the finger-vein image, the finger-vein pattern is emphasized and noises are refrained greatly. thirdly, a local interconnection neural network with linear receptive field is designed to deal with finger-vein patterns of different thickness and capture the patterns. fourthly, the method is very fast by using the integral image method. the experimental results show the proposed method is superior to other methods in finger-vein feature extraction and solve the problem of how to extract features from obscure images efficiently. the eer of the proposed method is 0.128%.
a framework for evaluating the effect of view angle, clothing and carrying condition on gait recognition. gait recognition has gained increasing interest from researchers, but there is still no standard evaluation method to compare the performance of different gait recognition algorithms. in this paper, a framework is proposed in an attempt to tackle this problem. the framework consists of a large gait database, a large set of well designed experiments and some evaluation metrics. there are 124 subjects in the database, and the gait data was captured from 11 views. three variations, namely view angle, clothing and carrying condition changes, are separately considered in the database. the database is one of the largest database among the existing databases. three sets of experiments, including a total of 363 experiments, are designed in the framework. some metrics are proposed to evaluate gait recognition algorithms.
a complete and rapid feature extraction method for face recognition. feature extraction is one of the key steps in face recognition. in this paper, common vector is used to extract features from null space of within-class scatter matrix, which is independent of the sample index in the same class and accelerates the speed of feature extraction. furthermore, effective features in regular space are extracted to enhance the performance of face recognition. the proposed method not only solves the small sample size problem, but also extracts more effective features from face images. experimental results on two popular databases demonstrate the effectiveness of the proposed method.
gca: a real-time grid-based clustering algorithm for large data set. few of the current existing methods for unsupervised learning (clustering) algorithms consider clustering the data points in a low-dimensional subspace in real time. in this paper, we present a grid based clustering algorithm (gca) with time complexity (o(n)). unlike previous clustering algorithm, gca pays more attention to the running time of the algorithm. gca achieves low running time by (i) determining the number of the clusters according to the point density of the grid cell and (ii) computing the distances between the centers of the clusters and the grid cells, not the data points. in order to make gca more efficient, principal component analysis(pca) is introduced to transform the data points from high dimension to low dimension. finally, we analyze the performance of gca and show that it outperforms most of the current state-of-the-art methods in terms of efficiency. in particular, it outperforms k-means algorithm by several orders in the running time.
surface tortuosity and its application to analyzing cracks in concrete. previous studies of tortuosity were restricted to a curve in 2d or 3d. we propose several measures of surface tortuosity based on surface normals and principal curvatures, and apply these measures to analyze the tortuosity of three-dimensional crack surfaces of concrete. we show that all crack surfaces are similar in tortuosity despite their different sizes and locations, while distinctive from various geometric surfaces.
genetic-based k-means algorithm for selection of feature variables. this paper proposes a genetic-based k-means(gk) algorithm for selection of the k value and selection of feature variables by minimizing an associated objective function. the algorithm combines the advantage of genetic algorithm(ga) and k-means to search the subspace thoroughly. therefore, our algorithm converges globally. a weighting function is then introduced to initialize the parameters of the algorithm. the experiments on a synthetic dataset and a real dataset shows that (i) gk outperforms kmeans since gk achieves the minimal value of the objective function and (ii) gk with the weighting function performs better than gk.
improved temporal correspondences in stereo-vision by ransac. determining the image correspondences of scene points in two or more views remain elusive especially for large baselines and (or) rotations. assuming a calibrated stereo rig, we propose two novel ransac-based algorithms to establish temporal correspondences of triplet and quadruplet matches in two stereo pairs robustly. we devise an efficient technique for the absolute orientation problem with minimum three matches [closed-form solution of absolute orientation using orthonormal matrices]. this drastically reduces the number of random samplings, for a given probability of selecting no outlier in at least one set, compared to the application of the 7-/8-point algorithms [a robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry, the developement and comparison of robust methods for estimating the fundamental matrix]. within the general ransac paradigm, a low-cost selective random sampling scheme is incorporated to further enhance the robustness of the algorithm that utilizes quadruplet matches.
mining uncertain data in low-dimensional subspace. mining for clusters in a database with uncertain data is a hot topic in many application areas, such as sensor database, location database, face recognition system and so on. since it is commonly assumed that most of the objects which are contained in a high-dimensional dataset are located in a low-dimensional subspace, mining clusters in a subspace in an uncertain database is a new task. in this paper, we adopt and combine fractal correlation dimension with fuzzy distance function to find out the clusters in a low-dimensional subspace in an uncertain database. we also propose the fuzzy kth nn algorithm to retrieve the kth nearest neighbor which can accelerate the process of mining. the experiments show that the new algorithm works well in an uncertain database.
style quantification of scanned multi-source digits. the co-occurring patterns in a group carrying the traits of common origin are statistically dependent via an underlying style context. exploiting style consistency in groups of patterns from multiple sources can increase ocr accuracy. the accuracy gains obtained by a style consistent classifier depend on the amount of style in isogenous (same-source) fields. we present mathematical models to quantify the amount of single-class and multi-class style using entropy, correlation and mutual information. we also demonstrate a method for style homogenization that allows testing our metrics on real data.
a fast recursive 3d model reconstruction algorithm for multimedia applications. a recursive two-step method to recover structure and motion from image sequences based on kalman filtering is described in this paper. the algorithm consists of two major steps. the first step is an extended kalman filter for the estimation of the object's pose. the second step is a set of extended kalman filters, one for each model point, for refining the positions of the model features in the 3d space. the initial guess is a planar model formed under the assumption of orthographic projection on the first image. these two steps alternate from frames to frames. the planar model converges to the final structure as the image sequence is scanned sequentially. the performance of the algorithm is demonstrated with both synthetic data and real world objects. comparisons with different approaches have been performed and show that our method is more efficient.
on estimation of secret message length in jsteg-like steganography. image steganalysis has attracted more attention recently. in this paper, a new method for detecting secret message and estimating the secret message length of bit-streams embedded using j-steg like steganography is proposed. first, based on the model of statistical distribution of quantized dct coefficients, the histogram of cover image is estimated from stego image. then the secret message is detected and the secret message length is estimated with the estimated cover histogram. interestingly, our study on steganalysis of j-steg like embedding offers a proof of zhang et al.'s method [a fast and effective steganalytic technique against jsteg-like algorithms]. the methodology described in this paper is a framework which can also be applied to many other stegaographic methods such as jpeg2000 file format embedding.
svm vs regularized least squares classification. support vector machines (svms) and regularized least squares (rls) are two recent promising techniques for classification. svms implement the structure risk minimization principle and use the kernel trick to extend it to the non-linear case. on the other hand, rls minimizes a regularized functional directly in a reproducing kernel hilbert space defined by a kernel. while both have a sound mathematical foundation, rls is strikingly simple. on the other hand, svms in general have a sparse representation of solutions. in addition, the performance of svms has been well documented but little can be said of rls. this paper applies these two techniques to a collection of data sets and presents results demonstrating virtual identical performance by the two methods.
steganalysis of data hiding in binary images. it is commonly believed that data hiding in binary image can't be detected due to little and noise like changes of data hiding. this paper proposes a steganalytic technique that can detect the existence of hidden message embedded in binary images. the technique is based on statistical analysis of the image statistics such as black-and-white border complexity, block noisiness and block coarseness. the probability of both false positive and false negative rates can also be estimated. the experimental results show that the proposed method can detect hiding fact very effectively.
learning optimal filter representation for texture classification. crucial to texture classification are texture features and classifiers that operate on the features. there are several approaches to computing texture features. of particular interest is multichannel filtering because of its simplicity. multichannel filtering works by decomposing the frequency domain of an image, resulting in a bank of filtered feature images. many techniques have been proposed to optimize multichannel filtering. however, the optimization is with respect to image representation, thus giving no guarantee for texture classification. this paper proposes a novel technique for learning optimal filters for texture classification. we use regularization techniques such as support vector machines (svms) to learn multichannel filters. since filter training in our approach is naturally tied to classifier training, the resulting filters are optimized for classification. experimental results validate the efficacy of our proposed technique.
reconstructing a dynamic surface from video sequences using graph cuts in 4d space-time. this paper is concerned with the problem of dynamically reconstructing the 3d surface of an object undergoing non-rigid motion. the problem is cast as reconstructing a continuous optimal 3d hyper-surface in 4d space-time from a set of calibrated video sequences. the imaging model of video cameras in 4d space-time is derived and a photo-inconsistency cost function is defined for a hyper-surface in the 4d space-time. we use a 4d node-cut algorithm to find a global minimum of the cost function and obtain the corresponding optimal hyper-surface. experimental results show that the proposed algorithm is effective in recovering continuously changing shapes and exhibits good noise resistance.
3-d object representation from multi-view range data applying deformable superquadrics. this paper presents a new framework for recovering superquadrics with global deformations from multi-view real range data. the framework aims at improving confidence and accuracy of recovered models by utilizing multi-view information, and consists of the initial superquadricmodel recovery, view registration, view integration, and final model recovery from integrated data. a quadrant analysis technique is proposed to aid the recovery of bending superquadrics. a modified range data registration method based on recovered superquadrics is also proposed to handle tapered superquadrics. experimental results indicate the proposed framework of multi-view representation significantly improved the accuracy and confidence of recoveredsuperquadrics compared with existing recovery strategies which rely on single-view range images.
subband noise estimation for adaptive wavelet shrinkage. in this article, we present an adaptive image denoising method based on subband noise modeling. for wavelet shrinkage, choosing the threshold depends on correctly estimating the noise variance. by modeling the inter-subband noise variance with a parameterized normalized exponential function, the problem becomes identifying the maximum noise variance. such a maximum exists in the highest decomposition level and can be estimated by locating the extreme of the first derivative of the subband variance function. the experiments demonstrate that our method outperforms peers, especially in the cases of large noise variance.
euclidean quality assessment for binary images. for binary images is proposed. in the algorithm euclidean distance between noise and signal points measures the noise energy and the euler number change of images describes the structural effects caused by noise. furthermore assessment on image quality is calculated in quantity in psnr form. generally image assessments could be classified into two categories: subjective and objective assessment. the latter is judged by the correlation coefficient with subjective quality measurement mean opinion score (mos). the experiments show that the results of the algorithm are highly correlative with subjective mos and the algorithm is more simple and computational saving than traditional objective assessments.
robust frontal face detection in complex environment. we have constructed a simple and fast system to detect frontal human faces in complex environment. there are two main contributions of our work: 1) we use a fast image segmentation method based on connected components labelling to select candidate face areas. 2) we propose a positive-negative attractor template to examine face areas. a valley detector is used to search the valley-like points of eyes and mouths. we test the system on images in complex environment and with confusing objects. the experiment shows a robust detection result with few false detected faces.
recognition of strong and weak connection models in continuous sign language. a new method to recognize continuous sign language based on hidden markov model (hmm) is proposed in this paper. according to the dependence of linguistic context, connections between elementary subwords are classified as strong connection and weak connection. the recognition of strong connection is accomplished with the aid of subword trees, which describe the connection of subwords in each sign language word; in weak connection, the main problem is how to extract the best matched subwords and find their end-points with little help of context information. the proposed method improves the summing process of viterbi decoding algorithm which is constrained in every individual model and compares the end score at each frame to find the ending frame of a subword. experimental results show an accuracy of 70% for continuous sign sentences that comprise no more than 4 subwords.
a new data selection principle for semi-supervised incremental learning. current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. we show that for many applications this data selection strategy is not correct. this is because the confidence score is primarily a metric to measure the classification correctness on a particular example, rather than one to measure the example's contribution to the training of an improved model, especially in the case that the information used in the confidence annotator is correlated with that generated by the classifier. to address this problem, we propose a performance-driven principle for unlabeled data selection in which only the unlabeled examples that help to improve classification accuracy are selected for semisupervised learning. encouraging results are presented for a variety of public benchmark datasets.
simulated static electric field (ssef) snake for deformable models. in this paper, a novel design of external force for snake is proposed. this kind of external force is actually a field, which we call the simulated static electric field (ssef). this field is created by simulated static electric charges, and the forces in this field are computed by the coulomb's law which is used in the analysis of static charge fields. the existing problems, such as the capture range, initialization, noise sensitivity and poor convergence to concavities, which appeared in the other designs of snake can be largely solved by this new scheme. also, cracked boundaries extracted from real images can be located. several comparisons with gradient vector flow (gvf) snake are presented in this paper to show the performance of our snake.
robust visual tracking via pixel classification and integration. we propose a novel framework for tracking non-rigid objects via pixel classification and integration (pci). given a new input frame, the tracker first performs object classification on each pixel and then finds the region that has the highest integral of scores. there are several key advantages of the proposed approach: it is computationally very efficient; it finds a global, instead of local (e.g., mean-shift), optimal solution within a search range; and it is inherently robust to different object scales with minimum extra computation.within this framework, a mixture of long-term and shortterm appearance model is further introduced to perform pci. as a result, the tracker is able to adapt to both slow and rapid appearance changes without drifting. challenging video sequences are presented to illustrate how the proposed tracker handles large motion, dramatic shape changes, scale variations, illumination variations and partial occlusions.
fragile watermarking scheme exploiting non-deterministic block-wise dependency. block-wise dependency is recognized as a key requirement in fragile watermarking schemes to thwart the vector quantization (vq) attack.it has also been observed that deterministic dependency is still susceptible to transplantation attack or even simple cover-up attack. in this work, a new fragile watermarking scheme exploiting non-deterministic dependency is proposed. to watermark the original image, each pixel is adjusted according to the consistency between a key-dependent binary watermark bit, the information from the pixel itself and the non-deterministic secret dependency information calculated froma neighborhood centered at that pixel. localization resolution is enhanced with a post-processing operation on the output difference map.
discovery of the tri-edge inequality with binary vector dissimilarity measures. in certain spaces using some distance measures, the sum of any two distances is always bigger than the third one. such a special property is called the tri-edge inequality (tei). in this paper, the tri-edge inequality characterizing several binary distance measures is mathematically proven and experimentally verified, and the implications of tei are discussed as well.
ear recognition using improved non-negative matrix factorization. an improved non-negative matrix factorization with sparseness constraints (inmfsc) is proposed by imposing an additional constraint on the objective function of nmfsc, which can control the sparseness of both the basis vectors and the coefficient matrix simultaneously. the update rules to solve the objective function with constraints are presented. research of ear recognition and its application is a new subject in the field of biometrics authentication. in practical application, ear is maybe partially occluded by hair etc. so the proposed inmfsc is applied on ear recognition with normal images and partially occluded images. experiment results show that, compared with the traditional nmfsc, the proposed method not only obtains higher recognition rate, but also improves the sparseness and the orthogonality of coefficient matrix.
an approach for constructing sparse kernel classifier. this paper presents a new approach for constructing sparse kernel classifier with large margin. firstly, we propose a kernel function pursuit strategy for selecting a small number of kernel functions which are used for expanding final classifier. and then an added constraint controls the sparseness of the final classifier and an approach is provided to solve the optimization problem with l2 loss function and complexity measure. the experiment results show that sparse kernel classifier can achieved higher efficiency for both training and testing without sacrificing prediction accuracy.
motion segmentation by multibody trifocal tensor using line correspondence. we present a geometric approach to multibody motion segmentation from line correspondences. given three perspective views containing multiple moving objects, we demonstrate that after applying a polynomial embedding to the line correspondences, they became related by the so-called multibody trilinear constrain and its associated multibody trifocal tensor. we show how to obtain the individual trifocal tensor from the second order derivatives of the multibody trilinear constraint. given trifocal tensors, we obtain the clustering of the motions and correspondences. experimental results on synthetic and real dynamic scenes are presented.
convex set-based estimation of image flows. we introduce a set-based approach for estimating image motion based on an optical flow constraint and a finite number of arbitrary differential constraints describing physically plausible vector fields. compared to related variational estimation approaches, our approach strictly satifies each separate constraint and becomes not more involved in the presence of higher-order differential operators. the approach is implemented using established sub-gradient projection schemes onto the set of feasible solutions. our approach is particularly suited if quantitative prior knowledge about structural flow properties is available, and for the regularized estimation of highly non-rigid image motion.
a global geometric approach for image clustering. we propose an appearance-based image clustering approach called ggci (global geometric clustering for image). for face images taken with varying pose, expression, eyes (wearing sunglasses or not) or object images under different viewing conditions, ggci uses easily measured local metric information to learn the underlying global geometry of images space, then apply the extended nearest neighbor approach to cluster images. different from the usual nearest neighbor approach, ggci considers the density around the nearest points within clusters. moreover, our approach clusters based on the geodesic distance measure instead of euclidean distance measure, which better reflects the intrinsic geometric structure of manifold embedded in high dimensional image space. experimental results suggest that the proposed ggci approach achieves lower error rates in image clustering when manifolds are embedded in image space.
fast and robust search method for short video clips from large video collection. in this paper a fast and robust method is proposed to search a large video collection for given short clips. compared with existing video searching methods which use visual features only, our scheme performs a two-phase hierarchical matching technique using visual and audio features successively. considering that video sampling rate (25 or 30 fps) is much lower than that of audio (8 to 48 khz), a coarse search is implemented with sub-sampled video frames first, and then potential matches will be verified and accurately located using fine audio features. both features are extracted directly from mpeg compressed video for computational efficiency. experiments have been conducted on over 10.5 hours of video to search for re-occurrences of 83 tv commercials and one news lead-out clip. all the 220 instances are correctly detected with no false alarm. our experiments also show that the proposed method is robust to variations of video bit rate, frame rate, frame size and color shifting.
a global geometric approach for image clustering. we propose an appearance-based image clustering approach called ggci (global geometric clustering for image). for face images taken with varying pose, expression, eyes (wearing sunglasses or not) or object images under different viewing conditions, ggci uses easily measured local metric information to learn the underlying global geometry of images space, then apply the extended nearest neighbor approach to cluster images. different from the usual nearest neighbor approach, ggci considers the density around the nearest points within clusters. moreover, our approach clusters based on the geodesic distance measure instead of euclidean distance measure, which better reflects the intrinsic geometric structure of manifold embedded in high dimensional image space. experimental results suggest that the proposed ggci approach achieves lower error rates in image clustering when manifolds are embedded in image space.
perspective symmetry invariant and its applications. face is a perceptually symmetric object; however, it often appears not so in captured image due to the rotation in depth within the 3d space. in this paper, we explore the invariant of the symmetry point pair when the pose and symmetry radius are changed. under the general perspective camera model, we present an invariant, called perspective symmetry invariant (psi), which only depends on the focus length and the rotation angle in depth when the angle is relatively small. psi is discriminating for pose estimation; meanwhile, it can be used to synthesize face shape in novel views with different psi values. encouraging experiments on these two contributions of psi are presented.
restoringwarped document images using shape-from-shading and surface interpolation. with current high resolution handheld digital devices such as camera phones and pdas, image capturing of documents like books and posters has become a convenient and efficient way of collecting and disseminating information. nevertheless, a simple snapshot of such documents in an uncontrolled environment often results in distorted images. one particular example is when capturing documents with non-planar geometric shapes, such as thick bound book pages, rolled posters, etc. the resultant images often exhibit both perspective and geometric distortions. this paper proposes a method to remove these warping distortions through a shape recovery process based on shape-from- shading (sfs) followed by restoration using surface interpolation techniques. we evaluated the proposed method using various snapshot images captured by normal handheld digital cameras. the ocr results on the original images and the restored images are compared. the precision is shown to be increased up to 22.3%. the comparison with a 2-d interpolation approach also shows a clear improvement on the restored images near the warping area.
estimation of 3d shape of warped document surface for image restoration. while scanning pages from a thick, bound book, there are two sources of distortion in the document images: 1) shade along the book 'spine', and 2) warping of the book surface in the shade area. in this paper, we propose a fast method to estimate the 3d shape of a book surface. based on this shape, we remove the shade and correct the warping to restore the document images. the experiments show that the photometric and geometric distortions are mostly removed. the ocr tests on the original and restored document images are also presented.
real-time object recognition using relational dependency based on graphical model. this paper proposes a real-time object recognition using the relational dependency among the objects that is represented by the graphical model. when we recognize the objects, it is effective to use the relational dependency in which several different objects co-exist each other. the relational dependency has been modeled by the transition matrix in the graphical model. the transition matrix precisely represents the conditional probability of object's existence at time t, given the existence of others at time t-1. we use a very fast cascaded adaboost detector in order to detect all object candidates in the image. then, the existence probability of the object from a given object candidate is estimated by a logistic regression using the softmax function. the estimated existence probability is updated by the trained transition matrix to reflect the relational dependency of the objects. the object's existence is determined by the threshold level. experiment results validate that the proposed method is a very fast and effective way of recognizing the objects in terms of high recognition rate and low false alarm rate.
a robust and accurate segmentation of iris images using optimal partitioning. an effective and accurate identification of human individuals from their iris features is largely dependent on proper segmentation of the iris and the pupil features from camera images. most modern segmentation schemes exploit the circular geometry of the iris to fit a circle or an ellipse to an edge map of the iris. in this paper, we present a new method for automatically localizing and segmenting iris features by optimal partitioning using the relative distribution of gray-level intensities across an image. first, the eye images are unrolled after detecting the center of the pupil from the image local minima. for each radial sample, segments corresponding to regions that are statistically different are computed using dynamic programming applied to a poisson-based cost function. the results are a set of change points marking the edges of different features including those of the pupil and the iris. the radius of the pupil and the iris are then obtained by searching for the best fit of two lines connecting the detected edge points. the proposed method is superior to other methods in that artifacts such as excessive or weak illumination, blurring and occlusion by eyelids do not interfere with the segmentation process. moreover, our algorithm is also robust and accurate even in the presence of eyewear such as glasses. applying this method to 122 images revealed a 98% segmentation accuracy. the algorithm has been shown to be effective in images with large field of view containing other facial features
online multicamera tracking with a switching state-space model. the paper presents a novel method for online tracking of multiple objects with non-overlapping cameras. the method is based on a generative model defining probabilistic dependencies between observations, the underlying color properties of objects and their dynamics. it allows for a full bayesian inference of trajectories. we developed an on-line algorithm for efficient, approximate inference and we demonstrate it to be accurate in an office environment.
kernel autoassociator with applications to visual classification. autoassociator is an important issue in concept learning, and the learned concept of a particular class can be used to distinguish the class from the others. for nonlinear autoassociation, this paper presents a new model referred to as kernel autoassociator. using kernel feature space as a potential nonlinear manifold, the model formulates the autoassociation as a special reconstruction problem from kernel feature space to input space. two methods are developed to solve the problem. we evaluate the autoassociator with artificial data, and apply it to handwritten digit recognition and multiview face recognition, yielding positive experimental results.
reducing artifacts in bdct-coded images by adaptive pixel-adjustment. generating artifacts is a major problem with compressed images coded by the block discrete cosine transform (bdct). an iterative deblocking method based on projection onto convex sets (pocs) is presented in this paper. the method considers pixel-wise local adaptability. the adjustment of a pixel is determined by local properties of the pixel. a coded image is iteratively projected onto two locally adaptive smoothness constraint sets, a locally adaptive quantization constraint set and an intensity constraint set to obtain an improved image where artifacts are reduced. the proposed method is tested on jpeg encoded images with excellent results.
automatic surveying of cutaneous hemangiomas. this paper presents a method for the fully automatic surveying of cutaneous hemangiomas by means of a hemangioma segmentation and a ruler visible in the images. the algorithm computes the spatial resolution of an image. hemangioma segmentation is accomplished by a single-layer perceptron classification by means of pixel color features. the algorithm was evaluated on a set of 120 images. it achieves satisfactory results on images with clearly visible, saturated hemangiomas.
core-based structure matching algorithm of fingerprint verification. fingerprint matching algorithm is a key issue of the fingerprint recognition, and there already exist many fingerprint matching algorithms, according to the dependence of the core point, fingerprint matching algorithms are divided into two groups, core-based match algorithms and noncore-based match algorithms. most of the noncore-based matching algorithm is time consuming, therefore, they are not suitable for online application; meanwhile, the core-based matching algorithm is efficient than the noncore-based matching algorithm, but it highly depends on the core detection precision. in this paper, we present a new core-based structure matching algorithm which considers both efficient and precision. firstly we used core detection algorithm to get the core position, then we define some local structure of the core area. used these local structure, we can find some correspondent points of the two fingerprint image. secondly, we use the correspondent points in the first stage to match the global feature of the fingerprint. experimental results show that the performance of the proposed algorithm is good.
robust background subtraction and maintenance. background subtraction is one of the main techniques to extract moving objects from background scenes. a mixture of gaussians is a common model for background subtraction that has been used in many applications. however modelling background pixels using this model results into a low-level process at pixel level. some of its main drawbacks are: a subtracted (moving object) region may contain holes; it can not solve partial occlusion problems, and it requires updates in cases of shadows or sudden changes in the scene. we present a multi-layered mixture of gaussians model named pixelmap. we combine the mixture of gaussians model with concepts defined by region level and frame level considerations. our experimental results show that our method improved the accuracy of extracting moving objects from background. a single stationary camera has been used.
an image segmentation framework based on patch segmentation fusion. in this paper we present an image segmentation framework based on patch segmentation fusion. an image is first split into small patches. segmentation is then performed on each patch using the algorithms of standard normalized cut [9], mean shift clustering [3], or k-means clustering. each region in a patch segmentation is assigned a label so as to represent different parts. after that, a connectedness value is calculated between any two overlapping patch segmentations with certain kinds of labeling. a weight called border strength is calculated for a segmentation with a certain labeling. we optimize a global criterion function that quantifies the consistency and quality of patch segmentations by a simulated annealing algorithm [5] in order to find the optimal patch segmentations and labeling. finally, global segmentation is reconstructed by fusing patch segmentations by multiple techniques. experimental results on natural images are reported. precision and recall rates are also calculated to evaluate the performance quantitively.
tracking of point targets in ir image sequence using multiple model based particle filtering and mrf based data association. particle filtering is being investigated extensively due to its important feature of target tracking based on nonlinear and non-gaussian model. it tracks a trajectory with a known model at a given time. it means that particle filter tracks an arbitrary trajectory only if the time instant when trajectory switches from one model to another model is known apriori. because of this reason particle filter is not able to track any arbitrary trajectory where transition from one model to another model is not known. for real world application, trajectory is always random in nature and may follow more than one model. in this paper we propose a novel method, which overcomes the above problem. in the proposed method a multiple model based approach is used along with particle filtering, which automates the model selection process for tracking an arbitrary trajectory. in the proposed approach, there is no need to have apriori information about the exact model that a target may follow. for data association, markov random field (mrf) based method has been utilized. it allows us to exploit the neighborhood concept for data association, i.e. the association of a measurement influences an association of its neighbor measurement.
efficient, simultaneous detection of multiple object classes. at present, the object categorisation literature is still dominated by the use of individual class detectors. detecting multiple classes then implies the subsequent application of multiple such detectors, but such an approach is not scalable towards high numbers of classes. this paper presents an alternative strategy, where multiple classes are detected in a combined way. this includes a decision tree approach, where ternary rather than binary nodes are used, and where nodes share features. this yields an efficient scheme, which scales much better. the paper proposes a strategy where the object samples are first distinguished from the background. then, in a second stage, the actual object class membership of each sample is determined. the focus of the paper lies entirely on the first stage, i.e. the distinction from background. the tree approach for this step is compared against two alternative strategies, one of them being the popular cascade approach. while classification accuracy tends to be better or comparable, the speed of the proposed method is systematically better. this advantage gets more outspoken as the number of object classes increases.
multiple regions of interest image coding using compensation scheme and alternating shift. maxshift method is the efficient region of interest (roi) coding algorithm recommended by jpeg2000. however, it cannot support the multiple roi coding based on different degrees of interest. in the paper, a new multiple roi coding method called bcashift (bitplanes compensation alternating shift) is presented. for multiple rois, the new method can encode the significant bitplanes of rois and background (bg) by alternating shift model, which ensures these rois to be encoded according to different degrees of interest. the least significant bitplanes of bg can be last encoded based on compensation scheme. experimental result shows that the presented method cannot only efficiently encode multiple rois with different degrees of interest in an image, but also flexibly adjust the compression quality between roi and bg by selecting an arbitrary scaling value without any roi shape information.
insulators recognition for 220kv/330kv high-voltage live-line cleaning robot. this paper approaches the problem of recognizing and localizing insulators with curved smooth and weak textured surfaces in a cluttered scene for the 220kv/330kv high-voltage live-line cleaning robot (hlcr). in this work we introduce susan edge-based scale invariant feature (sesif) to describe insulators, which is robust to noise, cluttered scene, changes on viewpoint and illumination. a coarse-to-fine method is applied to recognize and localize insulators using sesif. firstly, a coarse location is estimated with general hough transform and ransac method. secondly, an accurate location of insulator is found with an edge-based tracker. results are demonstrated for a 220kv insulator in a cluttered scene.
preprocessing of handwritten date images on chinese cheque. the preprocess procedure of handwritten date images in our automatic chinese cheque processing system is introduced. it consists of three major components: preprinted characters removal, binarization and extra strokes removal. a pixel-contour distance based method is proposed to remove preprinted characters while preserving the connection of object strokes. in binary, a local feature called morphological double edge is used to enhance the character strokes, and then a global threshold is selected by a new recursive method. extra strokes locate below date characters. we remove them by contour analysis. experiment results on real-life cheque images demonstrate the efficiency of our proposed methods.
semantic object segmentation by a spatio-temporal mrf model. in this paper, a region-based spatio-temporal markov random field (stmrf) model is proposed to segment moving objects semantically. the stmrf model combines segmentation results of four successive frames and integrates the temporal continuity in the uniform energy function. the segmentation procedure is composed of two stages: one is the short-term's classification and the other is temporal integration. at the first stage, moving objects are extracted by a region-based mrf model between two frames in a frame group of four successive frames. at the second stage, the ultimate semantic object is labeled by minimization the energy function of the stmrf model. such phased segmentation process is corresponding to a multi-level simulated anneal strategy. experimental results show that the proposed algorithm can efficiently capture the motion semantic meaning of objects and accurately extract moving objects.
a bayesian framework for automatic concept discovery in image collections. this paper develops a bayesian framework for automatic hidden semantic concept discovery to address effective semantics-intensive content based image retrieval. each image in the database is segmented to regions associated with homogenous color, texture, and shape features. by employing self-organization map learning, a uniform and sparse region-based representation is obtained. with this representation a probabilistic model based on the statistical-hidden-class assumptions of the image database is developed, to which expectation-maximization technique is applied to analyze semantic concepts hidden in the database. an elaborated retrieval algorithm is designed to support the probabilistic model. the semantic similarity is measured through integrating the posterior probabilities of the transformed query image, as well as a constructed negative vector, to the discovered semantic concepts. the proposed approach has a solid statistical foundation and the experimental evaluations on a database of 10,000 general-purposed images demonstrate its promise of the retrieval effectiveness.
type-2 fuzzy hidden markov models to phoneme recognition. this paper presents a novel extension of hidden markov models (hmms): type-2 fuzzy hmms (type-2 fhmms). the advantage of this extension is that it can handle both randomness and fuzziness within the framework of type-2 fuzzy sets (fss) and fuzzy logic systems (flss). membership functions (mfs) of type-2 fuzzy sets are three-dimensional. it is the third dimension that provides the additional degrees of freedom that make it possible to handle both uncertainties. we apply the type-2 fhmm as acoustic models for phoneme recognition on timit speech database. experimental results show that the type-2 fhmm has a comparable performance as that of the hmm but is more robust to noise, while it retains almost the same computational complexity as that of the hmm.
driver fatigue detection based intelligent vehicle control. driver fatigue problem is one of the important factors that cause traffic accidents. therefore the vision-based driver fatigue detection is the most prospective commercial applications of hci. however, it is a challenging issue due to a variety of factors such as head and eyes moving fast, external illuminations interference and realistic lighting conditions, etc. this tends to significantly limit its scope of application. in this paper, we present an intelligent vehicle control based on driver fatigue detection. firstly, the face is located using haar algorithm and eye location is found with projection technique. after finding eye templates, we propose a new real time eye tracking method based on unscented kalman filter. thirdly, driver fatigue can be detected whether the eyes are closed over 5 consecutive frames using vertical projection matching. finally, if driver fatigue is confirmed, the vehicle cruise control is start-up with slow speed, and maintains set slow speed such as 5 km/h. the experimental results show that intelligent vehicle control based on driver fatigue detection will be availability in traffic.
stroke segmentation of chinese characters using markov random fields. this paper presents markov random fields (mrfs) to segment strokes of chinese characters. the distortions caused by the thinning process make the thinning-based stroke segmentation difficult to extract continuous strokes and handle the ambiguous intersection regions. the mrfs reflect the local statistical dependencies at neighboring sites of the stroke skeleton, where the likelihood clique potential describes the statistical variations of directional observations at each site, and the smoothness prior clique potential describes the interactions among observations at neighboring sites. based on the cyclic directional observations by gabor filters, we formulate the stroke segmentation as an optimal labeling problem by the maximum a posteriori (map) criterion. the results of stroke segmentation on the etl-9b character database are encouraging.
a two-level method for unsupervised speaker-based audio segmentation. in this paper, we propose a two-level segmentation method that detects speaker changes in a continuous audio stream effectively. in our approach, we divide the change detection process into two levels: region level that detects the potential change regions containing candidate speaker change points, and boundary level that searches and refines the true change points. at the region level, we employ the modified generalized likelihood ratio (mglr) metric to search for the potential change regions in continuous local windows. at the boundary level, we perform t2 and bayesian information criterion (bic) algorithm to detect segment boundaries within the potential windows. the experimental results on the 1997 broadcast news hub4-ne mandarin corpus show the efficiency of the proposed scheme.
type-2 fuzzy markov random fields to handwritten character recognition. this paper integratesmarkov random fields (mrfs) with type-2 fuzzy sets (t2 fss) referred to as t2 fmrfs, which can handle the fuzziness of the labeling space as well as the randomness of observations within the unified framework. because fuzzy and random uncertainties exist in many computer vision problems, we extend the maximum a posteriori (map) criterion for the best labeling configuration by t2 fss operations. we apply t2 fmrfs as character models to similar handwritten chinese character recognition on etl- 9b and kaist databases. experimental results show that t2 fmrfs have a better classification and generalization ability for similar patterns than classical mrfs.
robust carving for non-lambertian objects. this paper presents a new surface reconstruction method that extends previous carving methods for non-lambertian objects by integrating the smoothness and image information of different aspects. we introduce a robust multi-view photo-consistency function and a single-view visual-consistency function. the former considers a general specularity that may introduce both reflectance models and robust statistics, while the latter is based on pixel homogeneity and continuity in individual images. the new consistent shape, with both multi-view and single-view, extends previous photo hull and visual hull, and is proven to be included in both photo hull and visual hull. this approximate shape is then refined by a graph-cut optimization method. sample reconstructions from real sequences for both global and local optimizations are demonstrated.
super-resolving compressed video with large artifacts. we propose methods to super-resolve compressed video sequences that may consist of frames with missing blocks of pixels in addition to compression artifacts. different from traditional resolution enhancement algorithms, our methods include two key components that are crucial to handle compressed video sequences. the first component is dynamic masking that dynamically computes image masks used to reject outliers. the second component is flow-based image repairing that reconstructs missing blocks or a whole frame by exploring both temporal and spatial information. we demonstrate the proposed methods with real mpeg video sequences.
conversation detection in feature films using finite state machines. in this paper, we address the problem of detecting the conversation scenes from feature films and propose and efficient and robust method for the stated problem. this method utilizes the structural information of the movie scenes with the combination of the low-level and mid-level features. we propose and demonstrate that a finite state machine (fsm) is suitable for detecting movie scenes with conversational settings. tow major characteristics of motion pictures, motion and audio, are used in our approach. the transitions of the fsm are determined by two mid-level features of each shot in the scene: the activity intensity and the face identity. our fsm has been experimented on over 50 clips with both positive and negative examples and produces convincing results.
gait recognition using fractal scale and wavelet moments. video-based gait recognition is a challenging problem in computer vision. in this paper, fractal scale wavelet analysis is applied to describe and automatically recognize gait. fractal scale based on wavelet analysis represents the self-similarity of signals, and improves the flexibility of wavelet moments. optimal wavelets based on generalized multi-resolution analysis are used to improve the recognition rate. descriptors of fractal scale are translation, scale and rotation invariant. moreover, a combination of fractal scale and wavelet moments improves the recognition rate. experiments show that the proposed descriptor is efficient for gait recognition.
a robust split-and-merge text segmentation approach for images. in this paper we describe a robust approach to segment text from color images. the proposed approach mainly includes four steps. firstly, a preprocessing step is utilized to enhance text blocks in images; secondly, these image blocks are split into connected components and most of them are eliminated by a component filtering procedure; thirdly, the left connected components are merged into several text layers, and a set of appropriate constraints are applied to find the real text layer; finally, the text layer is refined through a post-processing step to generate a binary output. our experimental results show that the proposed approach has a good performance in character recognition rate and processing speed. moreover, it is robust to text color, font size, as well as different styles of characters in different languages.
iterative figure-ground discrimination. figure-ground discrimination is an important problem in computer vision. previous work usually assumes that the color distribution of the figure can be described by a low dimensional parametric model such as a mixture of gaussians. however, such approach has difficulty selecting the number of mixture components and is sensitive to the initialization of the model parameters. in this paper, we employ non-parametric kernel estimation for color distributions of both the figure and background. we derive an iterative sampling-expectation (se) algorithm for estimating the color distribution and segmentation. there are several advantages of kernel-density estimation. first, it enables automatic selection of weights of different cues based on the bandwidth calculation from the image itself. second, it does not require model parameter initialization and estimation. the experimental results on images of cluttered scenes demonstrate the effectiveness of the proposed algorithm.
multi-view active shape model with robust parameter estimation. active shape model is an efficient way for localizing objects with variable shapes. when asm is extended to multiview cases, the parameter estimation approaches in previous works are often sensitive to the initial view, as they do not handle the unreliability of local texture search, which can be caused by bad initialization or cluttered background. to overcome this problem, we propose a novel algorithm for parameter estimation, using robust estimators to remove outliers. by weighting dynamically, our method acts as a model selection method, which reveals the hidden shape and view parameters from noisy observations of local texture models. experiments and comparisons on multi-view face alignment are carried out to show the efficiency of our approach.
multiblock-fusion scheme for face recognition. a multiblock-fusion scheme for face recognition is proposed in this paper. three face recognition algorithms, i.e. probabilistic match, linear discriminant analysis (lda) and discrete cosine transform (dct) are compared under the fusion strategy. by combining global and local features, the multiblock-fusion enhances the robustness against variations of illumination, facial expressions and pose. different partitions and combinations show specific performancefor each method. the experimental results demonstrate that the fusion outperforms the single method. some other characteristics of the three methods are also verified by the experiments.
robust eye detection under active infrared illumination. eye detection is very important for automatic face recognition and gaze tracking. in this paper we propose an algorithm for eye detection under active infrared (ir) illumination. a simple hardware enables us to make use of a physiological property of the eyes. a new thresholding method is introduced in order to effectively search the regions of interest (roi). an appearance model is then used to verify the pupil candidates. however, the existence of eyeglasses has a negative effect on selection of candidates. regarding this the generalized symmetry transform (gst) is exploited. by using a simplified distance weight, we reduce the computational cost of the original transform. experimental results demonstrate the effectiveness of the proposed eye detection method.
a wavelet-based edge detection method by scale multiplication. a wavelet-based multiscale edge detection scheme is presented in this paper. by multiplying the wavelet coefficients at two adjacent scales to magnify significant structures and suppress noise, we determined edges as the local maxima directly in the scale product after an efficientthresholding instead of first forming the edge maps at several scales and then synthesizing them together, which was employed in many multiscale techniques. it is shown that the scale multiplication achieves better results than either of the two scales, especially on the localization performance. experiments on natural images are compared with the laplacian of gaussian (log) and canny edge detection algorithms.
automated face pose estimation using elastic energy models. face pose estimation forms an important part in a face recognition system. however, fully automated and accurate pose determination still remains an unsolved problem in the research community. in this paper, we propose a novel elastic energy model to automatically estimate face poses. our method employs statistical energy contributions of a set of feature points, which can avoid over-trusting selected anchor points. it provides a robust solution to the feature localisation inaccuracy problem, which is inevitable in practical applications with cluttered backgrounds. as a general configuration, our model can be easily implemented and extended to other non-rigid objects. its effectiveness and robustness are revealed in our experiments.
comparing different localization approaches of the radon transform for road centerline extraction from classified satellite imagery. using a local radon transform helps improve the performance of the radon transform-based linear feature detection. in this paper, three different approaches to localize the radon transform are implemented and compared in the context of road centerline extraction from classified satellite imagery.
part based human tracking in a multiple cues fusion framework. this paper presents a real time video surveillance system which is capable of tracking multiple humans simultaneously. to better deal with various challenging issues such as occlusions, sharp motion changes and multi-person confusions, we propose an intelligent fusion framework where multiple cues are combined to seek the optimal objects state and more reliable cues have larger influences on the final decision. further, part based human tracking provides a second-level information fusion in that parts with weak observability can be compensated by tracking other more visible ones, which demonstrates its effectiveness for highly articulated objects like humans.
minimum classification error training for handwritten character recognition. in the offline handwritten character recognition, the classifier with modified quadratic discriminant function (mqdf) has achieved good performance. the parameters of the mqdf are commonly estimated using the maximum likelihood estimator, which maximizes the within-class likelihood but not directly minimizes the classification errors. to improve the mqdf performance, the mqdf parameters are revised using the discriminative training of minimum classification error (mce). our algorithm effectiveness is demonstrated by applying it to the nist handwritten numerals and handwritten chinese characters. the experimental results show that one of the highest recognition accuracies ever reported is achieved.
human silhouette extraction based on hmm. this paper presents a system that can extract regions of a person from an image sequence. the system first detects foreground regions based on a background model. after foreground regions are extracted a human model is used to identify human regions. in the human model, we adopt a hidden markov model (hmm) to model human silhouettes. to separate human and non-human regions, we represent non-human silhouettes by another hmm. the human silhouette model can extract incomplete human regions even when parts of the person are covered by background objects. experimental results show the system proposed is very effective.
ball hit detection in table tennis games based on audio analysis. as bearer of high level semantics, audio signal is being more and more used in content-based multimedia retrieval. in this paper, we investigate the ball hit detection for sports games and propose a novel approach to detect ball hits. by employing energy peak detection (epd) and mel frequency cepstral coefficient-based (mfcc-based) refinement (mbr), high precision (91%) and adequate recall (73%) of ball hit detection are achieved with a low computational complexity and an easy training process. the proposed algorithm can be applied in audio content-based highlight detection systems and provide valuable information for semantical understanding of sports games.
hand-eye calibration based on screw motions. when computer vision technique is used in robotics, robotic hand-eye calibration is a very important research task. many algorithms have been proposed for hand-eye calibration. based on these algorithms, we introduce a new hand-eye calibration algorithm in this paper, which employs the screw motion theory to establish a hand-eye matrix equation by using quaternion and gets a simultaneous result for rotation and translation by solving linear equations. the algorithm proposed in this paper has high and stable computational efficiency without non-linear minimization and can be understood easily. both simulations and real experiments show the superiority of our algorithm over the comparative algorithms.
a hierarchical object recognition system based on multi-scale principal curvature regions. this paper proposes a new generic object recognition system based on multi-scale affineinvariant image regions. image segments are obtained by a watershed transform of the principal curvature of a contrast enhanced image. each region is described by an intensity-based statistical descriptor and a pcasift descriptor. the spatial relations between regions are represented by a cluster-index distribution histogram. with these new descriptors, we develop a hierarchical object recognition system which uses an improved boosting feature selection method [9] to construct layer classifiers by automatically selecting the most discriminative features in each layer. all layer classifiers are then combined to give the final classification. this system is tested on various object recognition problems. experimental results show that the new hierarchical system outperforms the comparable solutions on most of the datasets tested.
3d tracking of human locomotion: a tracking as recognition approach. estimating mode (walking/running/standing) and phases of human locomotion is important for video understanding. we present a new "tracking as recognition" approach. a hierarchical finite state machine constructed from 3d motion capture data serves as a prior motion model. motion templates are used as the observation model. robustness is achieved by making inferences in the prior motion model which resolves the short-term ambiguity of the observations that may cause a regular tracking formulation to fail. experiments show very promising results on some difficult sequences.
detection of moving cast shadows using image orthogonal transform. in many image and computer vision applications, shadows interfere with fundamental tasks such as moving objects segmentation and tracking. in this paper, a novel method is proposed to detect the moving cast shadows in the scene. the normalized coefficients of orthogonal transform of image block are proved to be illumination invariant and are used to classify moving shadows and foreground objects. five kinds of orthogonal transform: dct, dft, haar transform, svd and hadamard transform, are utilized in our work to detect moving cast shadows. experimental results show that the proposed method succeeds in detecting moving cast shadows within indoor and outdoor environments.
local binary pattern descriptors for dynamic texture recognition. dynamic texture is an extension of texture to the temporal domain. in this paper, a new method for recognizing dynamic textures is proposed. the textures are modeled with concatenated local binary patterns in three orthonormal planes. the circular neighborhoods are generalized to elliptical sampling to fit to the space-time statistics. this is an extension of the lbp approach widely used in still texture analysis, combining the motion and appearance together. our approach has many advantages compared with the earlier approaches providing a better performance for the dyntex and mit databases.
moving cast shadows detection based on ratio edge. in this paper we propose a novel method for moving cast shadows detection. based on the analysis to the physical model of moving shadows, we prove that the ratio edge is illumination invariant. the distribution of the ratio edge is discussed and a significance test is performed to classify each image pixel into foreground object or moving shadow. experimental results on typical scenes show that the proposed method can detect moving shadows robustly.
fingerprint registration using minutia clusters and centroid structure 1. in this paper a novel distortion-tolerant fingerprint registration method based on clustering is proposed. in this method, minutiae features of the query fingerprint are divided into various clusters. several local structure transformations are estimated by local structure sets. then the global structures (centroid structures) are constructed according to the local structure transformation. the global transformation is determined by the score of local structure transformation together with the similarity level of the global structure. experimental results show that this algorithm is robust for aligning fingerprints with a small number of minutia and heavy distortions. such situations are often encountered in forensic applications.
automatic texture synthesis for face recognition from single views. one possible solution for pose- and illuminationinvariant face recognition is to employ appearancebased approaches, which rely greatly on correct facial textures. however, existing facial texture analysis algorithms are suboptimal, because they usually neglect specular reflections and require numerous training images for virtual view synthesis. this paper presents a novel texture synthesis approach from a single frontal view for face recognition. using a generic 3d face shape, facial textures are analyzed with consideration of all of the ambient, diffuse, and specular reflections. virtual views are synthesized under different poses and illuminations. the proposed approach was evaluated using the cmu-pie face database. encouraging results show that the proposed approach improves face recognition performances across pose and illumination variations.
incremental construction of neighborhood graphs for nonlinear dimensionality reduction. most nonlinear data embedding methods use bottom-up approaches for capturing underlying structures of data distributed as points on nonlinear manifolds in high dimensional spaces. these methods usually start by designating neighbor points to each point. neighbor points have to be designated in such a way that the constructed neighborhood graph is connected so that the data can be projected to a single global coordinate system. in this paper, we present an incremental method for updating neighborhood graphs. the method guarantees k-edge-connectivity of the constructed neighborhood graph. together with incremental approaches for geodesic distance estimation and multidimensional scaling, our method enables incremental embedding of high dimensional data streams. the method works even when the data are under-sampled or non-uniformly distributed. it has important applications in the processing of data streams and multimedia data.
recovering elastic property of soft tissues using 2d image sequences with limited range data. detecting abnormal material properties associated with diseased tissues from images requires accurate displacement data. we examined three affine model-based methods for measuring 3d displacements in regular image sequences. the advantage of these methods is that only one or no range image is needed for the whole sequence. we demonstrate, using images of both synthetic material and real burn patients, that the affine tracking method is suitable for many image based medical analyses.
stabilizing route panoramas. the route panorama (rp) has been proposed as a new digital medium to record and visualize cityscapes along a route. it is a compact, continuous and complete visual representation of scenes collected from a sequence of slit views with a camera moving along a smooth path. in real scene acquisition, a camera may suffer from vehicle shaking and the obtained route panoramas are jagged and waved. to improve the quality of route panoramas, we develop an algorithm to stabilize them. by referring the continuous linear features, we use median filters to smooth the 2d route panorama. by setting the slit properly with respect to the camera, we can reduce the influence from the vehicle shaking in the rp without matching consecutive video frames. we have rectified long distance route panoramas to a moderate level for virtual tours and visual navigation.
machine printed arabic character recognition using s-gcm. arabic characters are widely used in arabic countries. however, there is a little work has been done on recognition of arabic characters. this paper proposed a new method for recognition machine printed arabic characters. the proposed method employs ishii et al's chaotic neural network model, which is called globally coupled map using the symmetric map (s-gcm), for recognizing arabic characters. the proposed method is tested on two fonts, simplified arabic and arabic transparent, and 9 sizes, 8, 9, 10, 11, 12, 14, 16, 18, 20. the recognition rate is greater than 97%.
recognizing rotated faces from two orthogonal views in mugshot databases. tolerance to pose variations is one of the key remaining problems in face recognition. it is of great interest in airport surveillance systems using mugshot databases to screen travellers' faces. this paper presents a novel poseinvariant face recognition approach using two orthogonal face images from mugshot databases. virtual views under different poses are generated in two steps: shape modeling and texture synthesis. in the shape modeling step, a feature-based multilevel quadratic variation minimization approach is applied to generate smooth 3d face shapes. in the texture synthesis step, a non-lambertian reflectance model is explored to synthesize facial textures taking into account both diffuse and specular reflections. a view-based face recognizer is used to examine the feasibility and effectiveness of the proposed pose-invariant face recognition. the experimental results show that the proposed method provides a new solution to the problem of recognizing rotated faces.
regularized locality preserving learning of pre-image problem in kernel principal component analysis. in this paper, we address the pre-image problem in kernel principal component analysis (kpca). the preimage problem finds a pattern as the pre-image of a feature vector defined in the nonlinear principal component space produced by kpca. since the preimage typically seldom exists in general, an approximate solution is appreciated. by posing a novel perspective, we find the pre-image with regularized locality preserving learning. our approach achieves a unique solution, avoiding iteration and numerical instability. significant superiority of the proposed novel algorithm is demonstrated by driving two applications, namely face denoising and occluded face reconstruction, as comparing with some existing wellknown methods on pre-image learning.
a riemannian weighted filter for edge-sensitive image smoothing. this paper describes a new method for image smoothing. we view the image features as residing on a differential manifold, and we work with a representation based on the exponential map for this manifold (i.e. the map from the manifold to a plane that preserves geodesic distances). on the exponential map we characterise the features using a riemannian weighted mean. we show how both gradient descent and newton's method can be used to find the mean. based on this weighted mean, we develop an edge-preserving filter that combines gaussian and median filters of gray-scale images. we demonstrate our algorithm both on direction fields from shape-from-shading and tensor-valued images.
control double inverted pendulum by reinforcement learning with double cmac network. to accelerate the learning of reinforcement learning, many types of function approximation are used to represent state value. however function approximation reduces the accuracy of state value, and brings difficulty in the convergence. to solve the problems of tradeoff between the generalization and accuracy in reinforcement learning, we represent state-action value by two cmac networks with different generalization parameters. the accuracy cmac network can represent values exactly, which achieves precise control in the states around target area. and the generalization cmac network can extend experiences to unknown area, and guide the learning of accuracy cmac network. the algorithm proposed in this paper can effectively avoid the dilemma of achieving tradeoff between generalization and accuracy. simulation results for the control of double inverted pendulum are presented to show effectiveness of the proposed algorithm.
kernel-based method for tracking objects with rotation and translation. this paper addresses the issue of tracking translation and rotation simultaneously. starting with a kernel-based spatial-spectral model for object representation, we define an l¿-norm similarity measure between the target object and the observation, and derive a new formulation to the tracking of translational and rotational object. based on the tracking formulation, an iterative procedure is proposed. we also develop an adaptive kernel model to cope with varying appearance. experimental results are presented for both synthetic data and real-world traffic video.
rejection strategies for offline handwritten sentence recognition. this paper investigates three different rejection strategies for offline handwritten sentence recognition. the rejection strategies are implemented as a postprocessing step of a hidden markov model based text recognition system and are based on confidence measures derived from a list of candidate sentences produced by the recognizer. the better performing confidence measures make use of the fact that the recognizer integrates a word bigram language model. experimental results on extracted sentences from the iam database validate the effectiveness of the proposed rejection strategies.
a unifying map-mrf framework for deriving new point similarity measures for intensity-based 2d-3d registration. similarity measure is one of the main factors that affect the accuracy of intensity-based 2d-3d registration of x-ray fluoroscopy to ct images. this paper presents a unifying map-mfr framework for rationally deriving point similarity measures based on bayes theorem. three new similarity measures derived from this framework are presented and evaluated using a phantom and a human cadaveric specimen. their behaviors are compared to other well-known similarity measures and the comparison results are reported. combining any one of the new similarity measures with a previously introduced spline-based multiresolution 2d-3d registration scheme, we develop a fast and accurate registration algorithm. we report their capture ranges, converging speeds, and registration accuracies.
real-time face recognition using gram-schmidt orthogonalization for lda. a real-time face recognition method using gram-schmidt orthogonalization for linear discriminant analysis (gslda) is presented in this paper. the gslda algorithm avoids the large matrices computation such as computing the inverse or diagonalization of matrices, which may be somewhat problematic in terms of computational demands and numerical accuracy. on the other hand, gslda also achieves better recognition performance than the classical linear discriminant analysis (lda) by overcoming the degenerate eigenvalue problem of lda. experimental results on real face databases have confirmed the better performance of the proposed method.
object detection based on combination of conditional random field and markov random field. many approaches for object detection are based on markov random field (mrf) and conditional random field (crf) respectively. mrf and crf have very different characteristics. this work discusses in detail their strength and weaknesses. from the discussion, a new object detection algorithm using combination of crf and mrf was derived. we utilize the algorithm to detect urban areas, and corresponding to the urban area object, we introduce a generic feature vector for each image site. the proposed algorithm was tested extensively on a large number of remote sensing images, and very promising results can be presented.
feature fusion of face and gait for human recognition at a distance in video. a new video based recognition method is presented to recognize non-cooperating individuals at a distance in video, who expose side views to the camera. information from two biometric sources, side face and gait, is utilized and integrated at feature level. for face, a high-resolution side face image is constructed from multiple video frames. for gait, gait energy image (gei), a spatio-temporal compact representation of gait in video, is used to characterize human walking properties. face features and gait features are obtained separately using principal component analysis (pca) and multiple discriminant analysis (mda) combined method from the high-resolution side face image and gait energy image (gei), respectively. the system is tested on a database of video sequences corresponding to 46 people. the results showed that the integrated face and gait features carry the most discriminating power compared to any individual biometric.
extracting lines in noisy image using directional information. detection of lines in noisy image is not easy. when using hough transform, multiple false peaks may be generated from collinear noisy edge points, which in turn may create false line segments. to overcome this problem, we introduce a method for detecting lines in noise based on directional information. orientations are generated by gabor filters to guide an anisotropic gaussian filtering process, and they are also used in the peak selection in hough transform. the experimental results show the effectiveness of this method.
multiple-exemplar discriminant analysis for face recognition. face recognition is characteristically different from regular pattern recognition and, therefore, requires a different discriminant analysis other than linear discriminant analysis (lda). lda is a single-exemplar method in the sense that each class during classification is represented by a single exemplar, i.e. the sample mean of the class. in this paper, we present a multiple-exemplar discriminant analysis (meda) where each class is represented using several exemplars or even the whole available sample set. the proposed approach produces improved classification results when tested on a subset of feret database where lda is ineffective.
weighted bayesian network for visual tracking. bayesian network has been shown to be very successful for muny computer vision applications, most of which are solved using the generative approaches. we propose a novel weighted bayesian network which relaxes the conditional independent assumption in traditional bayesian network by assigning weights to the estimations of conditional probabilities. in the weighted bayesian network, the hidden variables are estimated generatively as in the traditional graphical models, and the weights of conditional probabilities are adjusted discriminatively from the training samples. the combined generative/discriminative approach in a loop preserves the advantage of generative model to perform unsupervised learning and handle missing data while improve the model flexibility and performance by the discriminative learning of probability estimation weights. our experiments show a number of real-time examples in visual tracking where the performances are signijicantly improved with the weighted bayesian networks.
representing and recognizing complete set of geons using extended superquadrics. in this paper, we take the advantages of extended superquadrics to represent and recognize the entire set of 36 geons. extended superquadrics are novel volumetric shape models that include superquadrics as a special case. an extended superquadric model can be deformed in any direction because it extends the exponents of the superquadric model from constants to functions of the latitude and longitude angles in the spherical coordinate system. thirteen features derived from the extended superquadric parameters are recovered in order to distinguish between all the 36 geon classes. classification error rates are estimated for the nearest neighbor classifier and the back-propagation neural network. both simulated data (at different noise levels) and real geon models are tested in our experiments. the results are very encouraging and has significant benefits for an object recognition system.
estimation of the size and location of multiple area light sources. most illuminant estimation algorithms worked on point light sources or directional light sources. little attempt has been made, however, to estimate area light sources. in this paper, we present a novel scheme that estimates the size and location of multiple area light sources using a set of stereo images of a sphere with a shiny surface. the parameters of the area light source are estimated by a novel algorithm which minimizes the matching error between the corresponding specular patches. experiments on real images show that our method is accurate and robust in estimating the parameters of the area light source.
the pattern classification based on the nearest feature midpoints. in this paper, we propose a novel method, called the nearest feature midpoint (nfm), for pattern classification. any two feature points of the same class are generalized by the feature midpoint (fm) between them. the representational capacity of available prototypes is thus expanded. the classification is based on the nearest distance from the query feature point to each fm. a theoretical proof is provided in this paper to show that for the n-dimensional gaussian distribution, the classification based on the nfm distance metric will achieve the least error probability as compared to those based on any other points on the feature lines. furthermore, a theoretical investigation indicates that under some assumption the nfl is approximately equivalent to the nfm when the dimension of the feature space is high. the empirical evaluation on a simulated data set concurs with all the theoretical investigations.
unusual event detection via multi-camera video mining. this paper describes a framework for detecting unusual events in surveillance videos. most surveillance systems consist of multiple video streams, but traditional event detection systems treat individual video streams independently or combine them in the feature extraction level through geometric reconstruction. our framework combines multiple video streams in the inference level, with a coupled hidden markov model (chmm).we use two-stage training to bootstrap a set of usual events, and train a chmm over the set. by thresholding the likelihood of a test segment being generated by the model, we build a unusual event detector. we evaluate the performance of our detector through qualitative and quantitative experiments on two sets of real world videos.
rectification with intersecting optical axes for stereoscopic visualization. there exist various methods for stereoscopic viewing of images, most requiring some special glasses for controlling what goes to the left and the right eyes of the viewer. recent technology developments have resulted in displays that enable 3d viewing without glasses. however, these displays demand a true stereo pair as the input, which greatly limits their practical use, as true stereoscopic media are scarce. in our recent work [6], we developed a systematic approach to automatic rectification of two images of the same scene captured by cameras at general positions, so that the results can be viewed on a 3d display. however, the approach cannot work well for large camera displacement (i.e., very wide baseline). in this paper, we propose a new rectification scheme to address this wise baseline rectification problem, with the basic idea of using a special stereo setup with intersecting optical axes,. in a sense, the idea mimics human vision when viewing objects close to the eyes. experiments with a 3d display demonstrate the feasibility and effectiveness of the proposed approach.
flag guided integration of multiple registered range images. integration of multiple registered range images finds applications in numerous areas. while most existing integration algorithms detect corresponding points between neighbouring views based on interpoint distances, we define in this paper corresponding area for each point and then carry out geometrical, rigidity, and orientation tests for the same purpose, not only reflecting the scanning nature of sampling resolution, but also the geometry of object surface. to more accurately fuse corresponding points, while most existing algorithms consider the confidence of points, we consider an accumulative fusion scheme of confidences, reflecting the number of times of observation. the fused points are finally triangulated using the improved delaunay triangulation method, guaranteeing a watertight surface. a comparative study based on real images shows that the proposed algorithm is accurate and efficient and is able to compensate both the accumulative registration errors and imaging noise.
symmetric pixel-group based stereo matching for occlusion handling. in this paper, we propose a symmetric pixel-group stereo model for handling occlusion in a segment-based style. firstly, both images are segmented based on color, disparity, and the segments of the other image sequencely. then the uniqueness constraint is embodied in pixel-group level. finally, a symmetric belief propagation (bp) optimization framework is used to find correspondence and occlusions simultaneously. results obtained for benchmark indicate that the proposed method is able to compete with the state-of-the-art algorithms.
face verification using gaborwavelets and adaboost. this paper presents a new face verification algorithm based on gabor wavelets and adaboost. in the algorithm, faces are represented by gabor wavelet features generated by gabor wavelet transform. gabor wavelets with 5 scales and 8 orientations are chosen to form a family of gabor wavelets. by convolving face images with these 40 gabor wavelets, the original images are transformed into magnitude response images of gabor wavelet features. the adaboost algorithm selects a small set of significant features from the pool of the gabor wavelet features. each feature is the basis for a weak classifier which is trained with face images taken from the xm2vts database. the feature with the lowest classification error is selected in each iteration of the adaboost operation. we also address issues regarding computational costs in feature selection with adaboost. a support vector machine (svm) is trained with examples of 20 features, and the results have shown a low false positive rate and a low classification error rate in face verification.
tracking periodic motion using bayesian estimation. this paper presents a bayesian approach to achieve efficient and accurate motion tracking in monocular image sequences. we first extract a deterministic motion model with six degrees of freedom in an on-line learning phase. this is followed by predicting the image points in successive frames, and achieving correspondence in the context of monte carlo estimation. meanwhile, the motion parameters of the camera are simultaneously estimated. the experimental results show that the stable and accurate ego-motion parameters can be obtained.
face recognition by combining several algorithms. there are many algorithms for human face recognition proposed in recent years. here, we will study how to combine these algorithms to perform better. a fusion framework combining the existing recognition algorithms based on support vector machine is developed. the experimental results demonstrate its effectiveness.
compound stochastic models for fingerprint individuality. the question of fingerprint individuality can be posed as follows: given a query fingerprint, what is the probability that the observed number of minutiae matches with a template fingerprint is purely due to chance? an assessment of this probability can be made by estimating the variability inherent in fingerprint minutiae. we develop a compound stochastic model that is able to capture three main sources of minutiae variability in actual fingerprint databases. the compound stochastic models are used to synthesize realizations of minutiae matches from which numerical estimates of fingerprint individuality can be derived. experiments on the fvc2002db1 and ibm hursley databases show that the probability of obtaining a 12 minutiae match purely due to chance is 1.6×10-5 when the number of minutiae in the query and template fingerprints are both 46.
comparing decision boundary curvature. classifier decision boundary is important for classification. by studying properties of decision boundary, we can predict the classifier's performance. an algorithm of comparing classifiers' decision boundary curvature is introduced in this paper. geometrical methods are used to carry out the comparison. this comparison can be used to measure difference between classifiers which is useful for designing multiple classifier systems. the effectiveness of this comparison is confirmed by experiments.
3d face pose tracking from an uncalibrated monocular camera. we propose a new near-real time technique for 3d face pose tracking from a monocular image sequence obtained from an uncalibrated camera. the basic idea behind our approach is that instead of treating 2d face detection and 3d face pose estimation separately, we perform simultaneous 2d face detection and 3d face pose tracking. specifically, 3d face pose at a time instant is constrained by the face dynamicsusing kalman filtering and by the face appearance in the image. the use of kalman filtering limits possible 3d face poses to a small range while the best matching betweenthe actual face image and the projected face image allows to pinpoint the exact 3d face pose.face matching is formulated as an optimization problem so that the exact face location and 3d face pose can be estimated e ciently. another major feature of our approach lies in the use of active ir illumination, which allows to robustly detect eyes. the detected eyes can in turn constrain the face in the imageand regularize the 3d face pose, therefore the tracking drift issue can be avoided and the processing can speedup. finally, the face model is dynamically updated to account for variations in face appearances caused by face pose, face expression, illumination and the combination of them.
robust pose invariant facial feature detection and tracking in real-time. in this paper, a robust technique is proposed to detect and track a set of twenty-eight prominent facial features under various facial expressions and face orientations in real-time. specifically, after the face image is captured from the camera, a trained face mesh is first employed to estimate a rough position for each facial feature based on the located eye positions. subsequently, an accurate position is obtained for each facial feature by searching around its roughly estimated position. once the facial features are located, by using the appearance information of each facial feature together with the geometry information among the facial features, a shape-constrained correction-based tracking mechanism is activated to track them in the subsequent image frames. finally, the performance of the proposed technique is demonstrated through building a real-time facial feature tracking system that can detect and track a set of twenty-eight facial features automatically as soon as a person is sitting in front of the camera.
nonlinear eye gaze mapping function estimation via support vector regression. we propose a novel method for tracking eye gaze that allows natural head movement. most existing remote eye gaze trackers cannot work under natural head movement due to the difficulty of building a gaze mapping function that can incorporate head motion information. therefore, the user is required to hold his/her head unnaturally still, possibly with the use of chin-rest. in addition, before each usage of the tracking system, a cumbersome calibration procedure must be performed to obtain a gaze mapping function. our proposed method significantly improves the conventional pupil center corneal refection (pccr) technique to permit natural head movement and to minimize calibration. support vector regression (svr) is used to construct a highly nonlinear generalized gaze mapping function that accounts for head movement. as the head moves naturally in front of the camera, the associated gaze mapping function with each new head position will be obtained automatically by the learned generalized gaze mapping function. once learned, the generalized gaze mapping function can be used by other users via a simple personal adaptation without retraining. experiments for multiple users show that eye gaze can be estimated accurately under natural head movement via the proposed technique.
key-based melody segmentation for popular songs. in music theory, a key specifies the tonal structure of a music piece. popular songs are mostly composed using particular music keys. it is common that the key changes at some point of the piece for an emotional uplifting effect. the change is usually in pitch of the tonic rather than in key style. automatically segmenting melody based on the key changes can facilitate content-based music retrieval. little work has been done for this problem. in this paper, we present a novel approach for detecting multiple keys and locating the key boundaries in the melody of popular songs in midi format. a tonality analysis of the melody using diatonic scale model first extracts overlapping segments of the melody that each conforms to the tonal structure of a single key. a modality (key style) analysis then determines the center mode of the melody based on the modes of the extracted melody segments. the segments of unrelated modes are then eliminated. and finally the keys and the key boundaries are determined by grouping remaining segments according to the pitch of the tonic. the proposed method is not confined to the two key styles, major and minor, as the previous techniques. thus this method is effective for detecting key changes and insensitive to the presence of accidental notes. experimental results on 50 randomly selected midi songs have demonstrated the performance of the proposed method.
car detection based on multi-cues integration. in this paper we present a novel fast multi-cues based car detection technique in still outdoor images. on the bottom level, two novel area templates based on edge cue and interest points cue are first designed, which can rapidly reject most of the non-car sub-windows at the cost of missing few of the car sub-windows. on the top level, both global structure cue and local texture cue are considered. to character the global structure property the odd gabor moments are introduced and trained by svms. the multi channels even gabor based local texture property extracted from corner area is modeled as a gaussian distribution. the final experiment results show that the integration of global structure property and local texture property is more powerful in discrimination between car and non-car objects and a high detection accurate 93% is obtained.
a landweber algorithm for 3d confocal microscopy restoration. a new landweber algorithm for 3d microscopy deconvolution is introduced in this paper. the algorithm is formulated from the fredholm equation of the first kind. artificial 3d images are used to test this algorithm and the restored results are compared with a nonlinear iterative de-convolution algorithm (ida). the experimental results show that the landweber algorithm can effectively suppress background noise and remove asymmetric point spread function (psf) degradation. finally, a typical real 3d confocal image is restored by the landweber algorithm and the results are compared with ida.
a robust regularised restoration algorithm based on topkis-veinott optimisation method. we present a robust iterative algorithm for restoration of blurred and noisy images. the restoration model is first regularised and then solved iteratively. an optimal regularisation parameter is estimated using the topkis-veinott gradient method. this restoration algorithm is compared with other competitive restoration algorithms in the literature. experimental results are presented to demonstrate the comparative important features of our algorithm, namely, robustness in the presence of noise and high quality restoration results.
scalable representative instance selection and ranking. finding a small set of representative instances for large datasets can bring various benefits to data mining practitioners so they can (1) build a learner superior to the one constructed from the whole massive data; and (2) avoid working on the whole original dataset all the time. we propose in this paper a scalable representative instance selection and ranking (sristar pronounced 3star) mechanism, which carries two unique features: (1) it provides a representative instance ranking list, so that users can always select instances from the top to the bottom, based on the number of examples they prefer; and (2) it investigates the behaviors of the underlying examples for instance selection, and the selection procedure tries to optimize the expected future error. given a dataset, we first cluster instances into small data cells, each of which consists of instances with similar behaviors. then we progressively evaluate data cells and their combinations, and order them into a list such that the learners built from the top cells are more accurate.
gmm-based classification method for continuous prediction in brain-computer interface. brain-computer interface (bci) requires effective classification algorithms for electroencephalogram (eeg) signal processing. to train a classifier for continuous prediction, trials in training dataset are first divided into segments. the difficulty here is how to combine the predictions across time to make the final decision of a whole trial as early and as accurately as possible. in this paper, we propose a novel statistical approach based on gaussian mixture models (gmm) to classify the eeg trials by combining the predictions of segments according to the discriminative powers at individual time intervals during a trial. we evaluate the proposed method on two datasets of bci competition 2003 and 2005. the experimental results have shown that the performance of the proposed method is among the best.
document image binarization based on stroke enhancement. this paper proposes a novel document image binarization approach based on stroke neighborhood enhancement. first, foreground pixels are initially labeled. then, the strokes are enhanced based on their neighborhood information which include gradient information and foreground-background pixel distances of foreground pixels and their neighboring background pixels. at last, the enhanced image is finally binarized. this approach can provide good result for those document images suffering from lighting variance, low resolution and blurring.
action recognition in broadcast tennis video. motion analysis in broadcast sports video is a challenging problem especially for player action recognition due to the low resolution of players in the frames. this paper presents a novel approach to recognize the basic player actions in broadcast tennis video where the player is about 30 pixels tall. two research challenges, motion representation and action recognition, are addressed. a new motion descriptor, which is a group of histograms based on optical flow, is proposed for motion representation. the optical flow here is treated as spatial pattern of noisy measurement instead of precise pixel displacement. to recognize the action performed by the player, support vector machine is employed to train the classifier where the concatenation of histograms is formed as the input features. the experimental results demonstrate that our method is promising.
a new textual/non-textual classifier for document skew correction. a robust approach is proposed for document skew detection. we use fourier analysis and svm to classify textual areas from non-textual areas of documents. we also propose a robust method to determine the skew angle from textual areas. our approach achieves good performance on documents with large area of non-textual contents.
a digital watermarking algorithm and implementation based on improved svd. an improved digital watermarking algorithm based on block-svd is put forward, which has better robustness. it can deal with the rectangle matrices directly and can extract better-quality watermarks. it takes little time to embed and extract the watermark in large images and this method can avoid some disadvantages such as the distortion caused by the computing error when extracting the watermark in the diagonal direction. robustness testing results and time comparing analysis between svd and block-svd are presented in this paper. compared with traditional cox method, this algorithm has better robustness, faster speed and is more practical.
optimizing the integration of a statistical language model in hmm based o.ine handwritten text recognition. although handwritten text recognition has been studied for some years, only few authors have used statistical language models to increase the performance of their recognizers. in those few cases where a language model has been used, its integration has not been systematically optimized. in this paper we investigate the optimization ofthe integration of statistical language models into hmm based recognition systems for offline handwritten text. based on experiments with the iam database we show that the recognition performance of a general offline handwritten text recognizer can be substantially improved.
phoneme segmentation of speech. in most approaches to speech recognition, the speech signals are segmented using constant-time segmentation, for example into 25 ms blocks. constant segmentation risks losing information about the phonemes. different sounds may be merged into single blocks and individual phonemes lost completely. a more satisfactory approach is to attempt to segment the phoneme boundaries from the speech signals and use these boundaries to define blocks. the discrete wavelet transform (dwt) is interesting in the analysis of speech since it is easy to extract parameters which take into account the properties of the human hearing system. the analysis of the power in different frequency bands offers potential for distinguishing the start and end of phonemes. for many boundaries, there is no discernible drop in overall power, and at some frequencies, the power is broadly constant over the lifetime of the phoneme. however, many phonemes exhibit rapid changes in particular subbands which can be used to detect their start and endpoints. in this paper we apply the dwt to speech signals and analyse the resulting power spectrum and its derivatives to locate candidates for the boundaries of phonemes in continuous speech. we compare the results with hand segmentation and constant segmentation over a number of words. the method proves effective for finding most phoneme boundaries.
unsupervised learning of a finite gamma mixture using mml: application to sar image analysis. this paper discusses the unsupervised learning problem for a mixture of gamma distributions. an important part of the unsupervised problem is determining the number of components which best describes some data. we apply the minimum message length (mml) criterion to the unsupervised learning problem in the case of a mixture of gamma distributions. we give a comparison of criteria in the literature for estimating the number of components in a data set. the comparison concerns synthetic and radarsat sar images.
improved adaptive gaussian mixture model for background subtraction. background subtraction is a common computer vision task. we analyze the usual pixel-level approach. we develop an efficient adaptive algorithm using gaussian mixture probability density. recursive equations are used to constantly update the parameters and but also to simultaneously select the appropriate number of components for each pixel.
content-based image retrieval: on theway to object features. content-based systems retrieve images based on lowlevel features (color,texture) while the user usually seeks some objects from real world. as segmentation is never accurate, such systems do not allow the use of powerful feature during retrieval (shape, structure). we propose a new system that relies on a hierarchy of segmentations, in order to handle some artifacts. besides, it allows using some object-related features for indexing (shape, structure). we also present some result on a 600 images database from corel.
virtual audio system customization using visual matching of ear parameters. applications in the creation of virtual auditory spaces (v as) and sonification require individualized head related transfer functions (hrtfs) for perceptual fidelity. hrtfs exhibit significant variation from person to person due to differences between their pinnae, and their body sizes. in this paper we propose and preliminarily implement a simple hrtf customization based on use of a recently published database of hrtfs [i] that also contains geometricalmeasurements of subject pinnae. we measure some of these features via simple image processing, and select the hrtf that has features most closely corresponding to the individual's features. this selection procedure is implemented along with the virtual auditory system described in [2], and listener tests conducted comparing the "customized" hrtf and a fixed hrtf. despite the simplicity of the method, tests reveal average improvement in localization accuracy of about 25 percent, though performance improvement varies with source location and individuals.
human activity classification based on gait energy image and coevolutionary genetic programming. in this paper, we present a novel approach based on gait energy image (gei) and co-evolutionary genetic programming (cgp) for human activity classification. specifically, hu's moment and normalized histogram bins are extracted from the original geis as input features. cgp is employed to reduce the feature dimensionality and learn the classifiers. the strategy of majority voting is applied to the cgp to improve the overall performance in consideration of the diversification of genetic programming. this learningbased approach improves the classification accuracy by approximately 7 percent in comparison to the traditional classifiers.
the generalization performance of learning machine based on phi-mixing sequence. the generalization performance is the important property of learning machines. it has been shown previously by vapnik, cucker and smale that, the empirical risks of learning machine based on i.i.d. sequence must uniformly converge to their expected risks as the number of samples approaches infinity. this paper extends the results to the case where the i.i.d. sequence is replaced by phi-mixing sequence. we establish the rate of uniform convergence of learning machine by using bernstein's inequality for phimixing sequence, and estimate the sample error of learning machine. in the end, we compare these bounds with known results.
evaluation of model-based interactive flower recognition. we introduce the concept of computer assisted visual interactive recognition (caviar). in caviar, a parameterized geometrical model serves as the human-computer communication channel. we implemented a flower recognition system and evaluated it on 30 inexperienced subjects. major conclusions include: 1) the accuracy of the caviar system is much higher than that of the machine alone; 2) its recognition time is much lower than that of the human alone; 3) it can be initialized with as few as one training sample per class and still achieve high accuracy; 4) it demonstrates a self-learning ability, which suggests that instead of initializing the caviar system with many training samples, we can trust the system's self-learning ability.
experimental comparison of combination rules using simulated data. in this paper, we report an experimental comparison between widely used combination rules, i.e. sum, product, maximum, borda count and best rank rules. we focus on the behavior of the considered combination rules for ensembles of classifiers exhibiting different performance of recognition. to this end, a simulation method using as input a specified performance matrix (i.e. recognition rates for each position of the true class and rejection rates) is proposed. this simulator generates ensembles of classifier outputs with specified profiles of performance within their list of solutions. our experimental results tend to show that these profiles of performance are one of the factors that affect the behavior of the combination rules.
simulating classifier ensembles of fixed diversity for studying plurality voting performance. this paper presents a new method for the artificial generation of classifier outputs in order to analyse the performance of plurality voting according both to the accuracies of the combined classifiers and to the agreement among them. this analysis is conducted in parallel with majority voting in order to compare the efficiency of these two methods when combining dependent classifiers. the experimental results show that the plurality voting is more efficient in achieving the trade-off between rejection rate and recognition rate.
constrained structure and motion estimation from optical flow. unbiased and consistent estimates of structure and motion can be obtained by least squares minimization of the differential epipolar constraint. previous work on this subject does not make use of geometrical constraints that often are present in natural and man built scenes. this paper shows how linear constraints among feature points (collinearity and coplanarity) and bilinear relations among such entities (parallelism and incidence) can be incorporated in the minimization process to improve the structure and motion estimates. there are 2 main contributions: (i) the formulation of a constrained minimization problem for structure and motion estimation from optical flow and (ii) the solution of the optimization problem by levenberg-marquardt and direct projection. we show that the proposed approach is stable, fast and efficient.
browsing graphics without prior knowledge. in this paper, we present a system to browse a set of graphical documents without prior knowledge of their content. this system relies on a new structural method locating regions potentially embedding a symbol, using an unsupervised reconstruction of the documents from their representation as chain of points. the method is complemented by a querying mechanism that retrieves from these regions those that are the most similar to a given input symbol. this mechanism uses a specific user feedback scheme to improve the accuracy of the retrieval.
texture based segmentation: automatic selection of co-occurrence matrices. texture is one of the least understood areas in computer vision. one of the major short-comings of texture segmentation approaches has been the ad-hoc selection of the set of feature vectors. we present an approach to qualitatively select a sub-set of a large (in principle infinite) set of co-occurrence matrices. a transportation measure is used to determine the difference between co-occurrence matrices resulting from various textures. this results in an ordered set of matrices, of which the resulting segmentation performance is directly related to the transportation measure. by combining segmentation results from various matrices the overall performance improves only when the matrices enhance different image areas. the most probable candidates for this can be obtained by using the same transportation measure applied to dimensional co-occurrence data. again, this results in an ordered set. texture segmentation results indicate a monotone increase in performance when adding subsequent matrices results from the ordered set.
multi-order standard deviation based distance metrics and its application in handwritten chinese character recognition. distance metric is the most popular metrics in the area of pattern recognition, and it is always used as a measure of similarity between the test pattern and the reference patterns. in this paper, a new distance metric based on manhattan distance is proposed. in the distance metric, not only the standard deviation but also the multi-order standard deviation of the reference patterns' feature vectors is involved. this paper develops this metric and the experiments based on the distance metric are discussed. according to our experiments on hcl2004 handwritten chinese characters database, the proposed distance metric shows its efficiency by improving the recognition accuracy of the system 4.01% compared with the system performance based on the standard deviation weighted distance metric
camera calibration using circle and right angles. in this paper, a new method is proposed for camera calibration using planar pattern which includes a circle and right angles. it is shown that a dual conic constraint on the vanishing line of a plane can be derived from a right angle and a circle on the same plane. given an image of a model plane containing a circle and three right angles, the vanishing line and the images of the circular points can be uniquely determined. as a result, camera calibration can be achieved by taking several images of the model plane from different view angles. there are three advantages of the proposed method. first, no correspondences between images need to be established. secondly, conics and lines forming the right angles in an image can be extracted and fitted very accurately. thirdly, it is practical as circular patterns and right angles are widely available. experiments with real images demonstrate the performance of the presented method.
reconstruction from plane mirror reflection. the 3d reconstruction problem from a single view of an object and its image reflected by a mirror plane is addressed in this paper. it is shown that the object and its mirror counterpart constitute a bilateral symmetric structure, in which correspondences are related by a harmonic homology associated with the mirror plane and the plane normal in 3d space. a novel method utilizing the profile as well as features of the object is proposed to determine the images of the plane normal and point correspondences. once they are recovered, 3d reconstruction can be computed using general stereo vision technique. experiment with real image is given to demonstrate the performance of the proposed method.
lennard-jones force field for geometric active contour. this paper presents a new geometric active contour (gac) model based on lennard-jones (l-j) force field, which is inspired by the theory of intermolecular interaction. different from conventional gradient based gac models, the proposed model does not rely on any pre-computed edge map. we take each pixel of image as a particle, and design an l-j force field for gac model according to interaction between pixels. we introduce a parameter of distance regularization to make the force tunable, and define an energy function for the l-j function to integrate various image features efficiently. a switch parameter c generates two different characteristics for the l-j force field: in the case of c=0, the force vector flows bi-directionally converge to boundaries, while in the case of c
choosing good distance metrics and local planners for probabilistic roadmap methods. this paper presents a comparative evaluation of different distance metrics and local planners within the context of probabilistic roadmap methods for motion planning. both c-space and workspace distance metrics and local planners are considered. the study concentrates on cluttered three-dimensional workspaces typical, e.g., of mechanical designs. our results include recommendations for selecting appropriate combinations of distance metrics and local planners for use in motion planning methods, particularly probabilistic roadmap methods. our study of distance metrics showed that the importance of the translational distance increased relative to the rotational distance as the environment become more crowded. we find that each local planner makes some connections than none of the others do --- indicating that better connected roadmaps will be constructed using multiple local planners. we propose a new local planning method we call {\em rotate-at-s} that outperforms the common straight-line in c-space method in crowded environments.
probabilistic roadmap methods are embarrassingly parallel. in this paper we report on our experience parallelizing probabilistic roadmap motion planning methods (prms). we show that significant, scalable speedups can be obtained with relatively little effort on the part of the developer. our experience is not limited to prms, however. in particular, we outline general techniques for parallelizing types of computations commonly performed in motion planning algorithms, and identify potential difficulties that might be faced in other efforts to parallelize sequential motion planning methods.
descrete events models + temporal logic = supervisory controller: automatic synthesis of locomotion controllers. in this paper, we address the problem of the synthesis of controller programs for a variety of robotics and manufacturing tasks. the problem we choose for test and illustrative purposes is the standard ``walking machine problem,'''' a representative instance of a real "hybrid" problem with both logical/discrete and continuous properties and strong mutual influence without any reasonable separation. we aim to produce a ``compiler technology'''' for this class of problems in a manner analogous to the development of the so-called ``silicon compilers'''' for the vlsi technology. to cope with the difficulties inherent to the problem, we resort to a novel approach that combines many key ideas from a variety of disciplines: namely, ``discrete event supervisory systems'''', petri nets approaches and ``temporal logic''''. notes: will appear in the 1995 ieee international conference on robotics and automation, nagoya, japan
enhancing randomized motion planners: exploring with haptic hints. in this paper, we investigate methods for enabling a human operator and an automatic motion planner to cooperatively solve a motion planning query. our work is motivated by our experience that automatic motion planners sometimes fail due to the difficulty of discovering &lsquo;critical&rsquo; configurations of the robot that are often naturally apparent to a human observer.our goal is to develop techniques by which the automatic planner can utilize (easily generated) user-input, and determine &lsquo;natural&rsquo; ways to inform the user of the progress made by the motion planner. we show that simple randomized techniques inspired by probabilistic roadmap methods are quite useful for transforming approximate, user-generated paths into collision-free paths, and describe an iterative transformation method which enables one to transform a solution for an easier version of the problem into a solution for the original problem. we also illustrate that simple visualization techniques can provide meaningful representations of the planner's progress in a 6-dimensional c-space. we illustrate the utility of our methods on difficult problems involving complex 3d cad models.
sensorless manipulation using massively parallel microfabricated actuator arrays. this paper investigates manipulation tasks with arrays of microelectromechanical structures (mems). we develop a geometric model for the mechanics of microactuators and a theory of sensorless, parallel manipulation, and we describe efficient algorithms for their evaluation. the theory of limit surfaces offers a purely geometric characterization of microscale contacts between actuator and moving object, which can be used to efficiently predict the motion of the object on an actuator array. it is shown how simple actuator control strategies can be used to uniquely align a part up to symmetry without sensor feedback. this theory is applicable to a wide range of microactuator arrays. our actuators are oscillating structures of sigle-crystal silicon fabricated in a ic-compatible process. calculations show that these actuators are strong enough to levitate and move e.g. a piece of paper.
automatic sensor configuration for task-directed planning. we consider the problem of planning the configuration of a sensor within the context of a robotic task. in this paper, we focus on geometrically specified tasks in the plane, and give algorithms for computing the regions from which an idealized point-and-shoot sensor can detect a polygonal robot. our main algorithm allows sensor configurations from which the robot may be partially obstructed, and computes the regions from which the robot can be detected as it translates through the goal at a known orientation. this algorithm runs in time $o(kmn^{3}(n+m))$ for an environment of complexity $n$, a robot of complexity $m$, and a goal of complexity $k$. the regions constructed can be used by an active sensing system to configure sensors that are guaranteed to observe the robot as it enters the goal.
frontal plane algorithms for dynamic bipedal walking. this paper presents two frontal plane algorithms for 3d dynamic bipedal walking. one of which is based on the notion of symmetry and the other uses reinforcement learning algorithm to learn the lateral foot placement. the algorithms are combined with a sagittal plane algorithm and successfully applied to a simulated 3d bipedal robot to achieve level ground walking. the simulation results showed that the choice of the local control law for the stance-ankle roll joint could significantly affect the performance of the frontal plane algorithms.
a unified force control approach to autonomous underwater manipulation. a unified force control scheme for an autonomous underwater robotic system is proposed in this paper. this robotic system is composed of a six degree-of-freedom autonomous underwater vehicle (auv) and a robotic arm that is mounted on the auv. a unified force control approach, which combines impedance control with hybrid position&#x002f;force control by means of fuzzy switching to perform autonomous underwater manipulation, is presented in this paper. this controller requires a dynamic model of the underwater vehicle-manipulator system. however, it does not require any model of the environment and therefore will have the potential to be useful in underwater tasks where the environment is generally unknown. the proposed approach combines the advantages of impedance control with hybrid control so that both smooth contact transition and force trajectory tracking can be achieved. in the absence of any functional autonomous underwater vehicle-manipulator system that can be used to verify the proposed controller, extensive computer simulations are performed and the results are presented in the paper.
approximating a single viewpoint in panoramic imaging devices. recent panoramic cameras present a very wide field of view from a single viewpoint. a single viewpoint is useful in mobile robotics for a number of reasons, including perspective reprojection and stereo analysis. however, the requirement of single viewpoint for panoramic cameras restricts the optical and geometrical design of these devices. in this paper, we present a method for approximating a single viewpoint in panoramic devices that allows much greater freedom in design. we illustrate the method with a compact catadioptric device using a spherical mirror and standard optics, and apply it to perspective reprojection. the resultant panoramic camera has been integrated as a surveillance device on a small mobile robot.
the synthesis of 3-d form-closure grasps. this paper presents a new formulation of computing three-dimensional (3-d) frictional form-closure grasps of n robotic fingers. as 3-d form-closure grasps involve 6-d wrench space, we first propose a recursive reduction technique to transform the complicated problem in the 6-d space into a simpler 3-d one. next, we rewrite the sufficient and necessary condition for form-closure grasps into its equivalent form of two sets of linear inequalities. then, according to the linear inequality theory, the problem is transformed to searching for a set of points which ensure the inconsistency of each of the two linear inequality systems. to search for such points, we proposed two methods: the first one is based on testing whether the convex region formed by each linear inequality system is empty, while the second one relies on the potential field method. we have implemented the algorithm and confirmed their efficiency for the synthesis of 3-d form-closure grasps.
using haptic vector fields for animation motion control. we are exploring techniques for animation authoring and editing using a haptic force-feedback device. in our system, a family of animations is encoded by a bundle of trajectories. this bundle in turn defines a time-varying, higher-order vector field on a configuration space for the animation. a haptic input device provides a low-dimensional parameterization of the resulting dynamical system, and the haptic force feedback permits browsing and editing of the space of animations, by allowing the user to experience the vector field as physical forces.
analyzing teams of cooperating mobile robots. in [don4], we described a manipulation task for cooperating mobile robots that can push large, heavy objects. there, we asked whether explicit local and global communication between the agents can be removed from a family of pushing protocols. in this paper, we answer in the affirmative. we do so by using the general methods of [don4] analyzing information invariants. we discuss several measures for the information complexity of the task of pushing with cooperating mobile robots, and we present a methodology for creating new manipulation strategies out of existing ones. we develop and analyze synchronous and asynchronous manipulation protocols for a small team of cooperating mobile robots that can push large boxes. the protocols we describe have been implemented in several forms on the cornell mobile robots in our laboratory.
designing stable finite state machine behaviors using phase plane analysis and variable structure control. this paper discusses how phase plane analysis can be used to describe the overall behavior of single and multiple autonomous robotic vehicles with finite state machine rules. the importance of this result is that we can begin to design provably stable group behaviors from a set of simple control laws and appropriate switching points with decentralized variable structure control. the ability to prove stable group behavior is especially important for applications such as locating military targets or land mines. in this paper, we demonstrate how phase plane analysis has been used to explain the behavior of a 16 cm3 autonomous line-tracking robot with four finite states. after which, the analysis is extended to include the design of a decentralized variable structure controller that guides multiple vehicles to a goal while avoiding each other.
spanning-tree based coverage of continuous areas by a mobile robot. this paper considers the problem of covering a continuous planar area by a square-shaped tool attached to a mobile robot. using a tool-based approximation of the work-area, we present an algorithm that covers every point of the approximate area for tasks such as floor cleaning, lawn mowing, and field demining. the algorithm, called i>spanning tree covering (stc), subdivides the work-area into disjoint cells corresponding to the square-shaped tool, then follows a spanning tree of the graph induced by the cells, while covering every point precisely once. we present and analyze three versions of the stc algorithm. the first version is off-line, where the robot has perfect apriori knowledge of its environment. the off-line stc algorithm computes an optimal covering path in linear time o(i>n), where i>n is the number of cells comprising the approximate area. the second version of stc is on-line, where the robot uses its sensors to detect obstacles and construct a spanning tree of the environment while covering the work-area. the on-line stc algorithm completes an optimal covering path in time o(i>n), but requires o(i>n) memory for its implementation. the third version of stc is &ldquo;ant&rdquo;-like. in this version, too, the robot has no apriori knowledge of the environment, but it may leave pheromone-like markers during the coverage process. the ant-like stc algorithm runs in time o(i>n), and requires only o(1) memory. finally we present simulation results of the three stc algorithms, demonstrating their effectiveness in cases where the tool size is significantly smaller than the work-area characteristic dimension.
building 3-d models from unregistered range images. in this paper, we describe a new approach for building a three-dimensional model from a set of range images. the approach is able to build models of free-form surfaces obtained form arbitrary viewing directions, with no initial estimate of the relative viewing directions. the approach is based on building discrete meshes representing the surfaces observed in each of the range images, to map each of the meshes to a spherical image, and to compute the transformations between the views by matching the spherical images. these meshes are built using an interative fitting algorithm previously developed; the spherical images are built by mapping the nodes of the surface meshes to the nodes of a reference mesh on the unit sphere and by storing a measure of curvature at every node. we describe the algorithms used for building such models from range images and for matching them. we show results obtained using range images of complex objects.
sensor placement desigu for object pose determination with three light-stripe range finders. the pose of a polyhedral object can be determined with range data obtained from a set of simple light-stripe range sensors. however, localization results are highly dependent on sensor placement. this paper presents a method for designing an optimal sensor placement of three light-stripe sensors with which to determine the pose of an arbitrarily positioned object. we evaluate a sensor placement on the basis of average performance measures over the whole state space of object pose by a monte carlo method. an optimal sensor placement is then selected by another monte carlo method which searches for a maximal score function of the performance measures over the whole state of sensor placements.
an integrated mobile robot path (re)planner and localizer for personal robots. personal robotics applications require autonomous mobile robot navigation methods that are safe, robust, and inexpensive. most of the previous techniques proposed do not meet these competing goals. in this paper, we describe a method for navigation in a known indoor environment, such as a home or office, that requires only inexpensive range sensors. our framework includes a high-level planner which integrates and coordinates path planning and localization modules with the aid of a module for computing regions which are expected, with high probability, to contain the robot at any given time. the localization method is based on simple geometric properties of the environment which are computed during a preprocessing stage. the roadmap-based path planner enables one to select routes, and sub-goals along those routes, that will facilitate localization and other optimization criteria. in addition, our framework enables one to quickly plan new routes, dynamically, based on the current position as computed by intermediate localization operations. we present simulation and hardware experimental results that illustrate the practicality and potential of our approach.
a suite of tools for debugging distributed autonomous systems. this paper describes a set of tools that enables developers to log and analyze the run-time behavior of distributed control systems. a feature of the tools is that they can be applied to distributed systems. the logging tools enable developers to instrument c or c++ programs so that data indicating state changes can be logged automatically in a variety of formats. in particular, run-time data from distributed systems can be synchronized into a single relational database. tools are also provided for visualizing the logged data. analysis to verify correct program behavior is done using a new interval logic that is described in this paper. the logic enables system engineers to express temporal specifications for the autonomous control program that are then checked against the logged data. the data logging, visualization, and interval logic analysis tools are all fully implemented. results are given from a nasa distributed autonomous control system application.
on-line manipulation planning for two robot arms in a dynamic enviroment. in a constantly changing and partially unpredictable environment, robot motion planning must be on-line. the planner receives a continuous flow of information about occurring events and generates new plans, while previously planned motions are being executed. this paper describes an on-line planner for two cooperating arms whose task is to grab parts of various types on a conveyor belt and transfer them to their respective goals while avoiding collision with obstacles. parts arrive on the belt in random order, at any time. both goals and obstacles may be dynamically changed. this scenario is typical of manufacturing cells serving machine-tools, assembling products, or packaging objects. the proposed approach breaks the overall planning problem into subproblems, each involving a low-dimensional configuration or configuration-time space, and orchestrates very fast primitives solving these subproblems. the resulting planner has been implemented and extensively tested in a simulated environment, as well as with a real dual-arm system. its competitiveness has been evaluated against an oracle making (almost) the best decision at any one time; the results show that the planner compares extremely well.
a novel potential-based path planning of 3-d articulated robots with moving bases. this paper proposes a novel path planning algorithm of 3-d articulated robots with moving bases based on a generalized potential field model. the approach computes, similar to that done in electrostatics, repulsive forces and torques between charged objects. a collision-free path can be obtained by locally adjusting the robot configuration to search for minimum potential configurations using these forces and torques. the proposed approach is efficient since these potential gradients are analytically tractable. in order to speedup the computation, a sequential planning strategy is adopted. simulation results show that the proposed algorithm works well, in terms of collision avoidance and computation efficiency.
marker-augmented robot-environment interaction. there has been an increasing interest in developing computational theories of autonomous robots. however, the previous work has focused on intelligent modifications to internal computational structure of a robot, ignoring modifications to external environments. our work is the first to formalize the modification of an environment by an introduction of markers that replace the internal state. replacing internal state by addition of markers increases communication through the world. use of markers has been shown to improve the effectiveness of robots at american association of artificial intelligence robot competitions and robocup competitions. we report on the semantics of markers using their logical description and the internal state they replace. we introduce several properties of markers and marker sets like redundancy, mutual exclusivity and efficiency. we show how the stimuli of behaviours can be modified when markers are introduced to replace internal state. we also report on a semi-automatic algorithm that allows robots to place markers in their world. we show how the algorithm can be extended for obtaining a higher replacement of internal state and for handling an autonomous removal of markers. we provide several guidelines for effectively introducing markers in a robot's world.
the formula one tire changing robot (f-t.c.r.). formula one racing is one of the most fascinating sports ever, it is a perfect combination of high speed, technology, pressure and danger. one problem associated with car racing is the time differential between teams during pits stops, which substantially affects the final results. in addition, a high percentage of the accidents in formula one is due to pit stop problems. changing the tires of a car while almost in motion, after reaching dangerous pressure and temperature values, is a very risky challenge, no matter how well a team is trained. approximately 15&ndash;25 people are constantly exposed to serious dangers. the risks taken are extreme and any idea of reducing it without affecting the quality of the race should be considered. our idea is to build a fully robotized system that takes over the tire changing and refueling process. there will practically be no need for human intervention. the system will demonstrate remarkable time accuracy, precision and low risk implications, uniformity of performance across teams, the competition being relayed solely upon the pilots.
development of self-learning vision-based mobile robots for acquiring soccer robots behaviors. an input generalization problem is one of the most important ones in applying reinforcement learning to real robot tasks. to cope with this problem, we propose a self-partitioning state space algorithm which can make non-uniform quantization of the state space. to show that our algorithm has generalization capability, we apply our method to two tasks in which a soccer robot shoots a ball into a goal and prevents a ball from entering a goal. to show the validity of this method, the experimental results for computer simulation and a real robot are shown
tracking adaptive impedance robot control with visual feedback. in this paper we propose a tracking adaptive impedance controller for robots with visual feedback. it is based on a generalized impedance concept where the sensed distance is introduced as a fictitious force to the control in order to avoid obstacles in restricted motion tasks. the controller is designed to compensate for full non-linear robot dynamics. robot parameters adjustment is introduced to reduce the sensibility of the controller design to dynamic uncertainties of the robot and the manipulated load. it is proved that the vision control errors are ultimately bounded in the image coordinate system. simulations are carried out to evaluate the controller performance.
passive night vision sensor comparison for unmanned ground vehicle stereo vision navigation. one goal of the "demo iii" unmanned ground vehicle program is to enable autonomous nighttime navigation at speeds of up to 10 m.p.h. to perform obstacle detection at night with stereo vision will require night vision cameras that produce adequate image quality for the driving speeds, vehicle dynamics, obstacle sizes, and scene conditions that will be encountered.this paper analyzes the suitability of four classes of night vision cameras (3-5 mm cooled flir, 8-12 mm cooled flir, 8-12 mm uncooled flir, and image intensifiers) for night stereo vision, using criteria based on stereo matching quality, image signal to noise ratio, motion blur, and synchronization capability. we find that only cooled flirs will enable stereo vision performance that meets the goals of the demo iii program for nighttime autonomous mobility.
multi-robot collaboration for robust exploration. this paper presents a new sensing modality for multirobot exploration. the approach is based on using a pair of robots that observe each other, and act in concert to reduce odometry errors. we assume the robots can both directly sense nearby obstacles and see each other. the proposed approach improves the quality of the map by reducing the inaccuracies that occur over time from dead reckoning errors. furthermore, by exploiting the ability of the robots to see each other, we can detect opaque obstacles in the environment independently of their surface reflectance properties. two different algorithms, based on the size of the environment, are introduced, with a complexity analysis, and experimental results in simulation and with real robots.
motion planning in stereotaxic radiosurgery. stereotaxic radiosurgery is a procedure which uses a beam of radiation as an ablative surgical instrument to destroy brain tumors. the beam is produced by a linear accelerator which is moved by a jointed mechanism. radiation is concentrated by crossfiring at the tumor from multiple directions and the amount of energy deposited in normal brain tissues is reduced. because access to the tumor is obstructed along some directions by critical regions (e.g., brainstem, optic nerves) and most tumors are not shaped like spheres, planning the path of the beam is often difficult and time-consuming. this paper describes a computer-based planner developed to assist the surgeon generate a satisfactory path, given the spatial distribution of the brain tissues obtained with medical imaging. experimental results with the implemented planner are presented, including a comparison with manually generated paths. according to these results, automatic planning significantly improves energy deposition. it can also shorten the overall treatment, hence reducing the patient''s pain and allowing the radiosurgery equipment to be used for more patients. stereotaxic radiosurgery is an example of so-called "bloodless surgery". computer-based planning techniques are expected to facilitate further development of this safer, less painful, and more cost effective type of surgery.
planning paths of minimal curvature. we consider the problem of planning curvature constrained paths amidst polygonal obstacles, connecting given start and target configurations. let the critical curvature rc be the minimal curvature for which a constrained path exists. we describe an algorithm, which approximates the critical curvature and finds a corresponding path. further, we give an efficient decision procedure to determine if there exists a path satisfying a given curvature constraint r, with running time polynomial in |r-rc|/r. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
a motion planning approach to folding: from paper craft to protein folding. in this paper, we present a framework for studying folding problems from a motion planning perspective. the version of the motion planning problem we consider is that of determining a sequence of motions to transform some configuration of a foldable object (the start) into another configuration (the goal). modeling foldable objects as tree-like multi-link objects allows us to apply recent techniques developed in the robotics motion planning community for articulated objects with many degrees of freedom (many links) to folding problems. an important feature of this approach is that it not only allows us to study foldability questions, such as, can one object be folded (or unfolded) into another object, but also provides us with another tool for investigating the dynamic folding process itself. the framework proposed here has application to traditional motion planning areas such as automation and animation, and presents a novel approach for studying protein folding pathways. preliminary experimental results with traditional paper crafts (e.g., box folding) and small proteins (approximately 60 residues) are quite encouraging.
customizing prm roadmaps at query time. in this paper, we propose a new approach for building and querying probabilistic roadmaps. in the roadmap construction stage, we build coarse roadmaps by performing only an approximate validation of the roadmap nodes and/or edges. in the query stage, the roadmap is validated and refined only in the area of interest for the query, and moreover, is customized in accordance with any specified query preferences. this approach, which postpones some of the validation checks (e.g., collision checks) to the query phase, yields more efficient solutions to many problems. an important benefit of our approach is that it gives one the ability to customize the same roadmap in accordance with multiple, variable, query preferences. for example, our approach enables one to find a path which maintains a particular clearance, or makes at most some specified number of sharp turns. our preliminary results on problems drawn from diverse application domains show that this new approach dramatically improves performance, and shows remarkable flexibility when adapting to different query requirements.
disassembly sequencing using a motion planning approach. we propose a new approach for generating disassembly sequences. our motion planning based approach treats the parts in the assembly as robots and operates in the composite configuration space of the parts'' individual configuration spaces. randomized techniques inspired by recent methods proposed for motion planning are used to sample configurations in this space. although a purely randomized approach to sampling is successful in systems with a small number of parts, typical assemblies consist of numerous parts and the corresponding composite c-spaces have high dimensionality. in such cases, a completely randomized sampling approach would be ineffective since many important configurations for the disassembly sequence will involve closely packed parts, i.e., the disassembly sequence will pass through narrow passages in the c-space. our solution to this problem is to bias the sampling by computing potential movement directions based on the geometric characteristics of configurations known to be reachable from the assembled configuration (the start). for example, we select potential directions which are perpendicular to part faces. thus, our disassembly algorithm constructs a disassembly tree which is rooted at the starting assembled configuration. our experimental results with several non-trivial puzzle-like assemblies show the potential of this approach.
maprm: a probabilistic roadmap planner with sampling on the medial axis of the free space. probabilistic roadmap planning methods have been shown to perform well in a number of practical situations, but their performance degrades when paths are required to pass through narrow passages in the free space. we propose a new method of sampling the configuration space in which randomly generated configurations, free or not, are retracted onto the medial axis of the free space. we give algorithms that perform this retraction while avoiding explicit computation of the medial axis, and we show that sampling and retracting in this manner increases the number of nodes found in small volume corridors in a way that is independent of the volume of the corridor and depends only on the characteristics of the obstacles bounding it. theoretical and experimental results are given to show that this improves performance on problems requiring traversal of narrow passages.
motion capture from demonstrator's viewpoint and its application to robot teaching. in this paper, we propose a kind of &ldquo;teaching by demonstration&rdquo; method, aiming at its application to humanoid robots at home in the future. the demonstrator's motion is captured by a pair of stereo cameras mounted on his&sol;her head, locating very close to his&sol;her eyes. by tracking the landmarks attached to the demonstrator's hand and the working environment, one can estimate not only the demonstrator's hand motion but also his&sol;her head motion, which can be used for the active vision system. experimental result shows the effectiveness of the proposed framework. &copy; 2005 wiley periodicals, inc.
automatic calibration and visual servoing for a robot navigation system. this paper attacks the problem of automatic location of a mobile robot in an indoor environment. this may be used for calibration to locate the robot accurately before it starts to navigate, or it can be used in visual servoing as feed back to the controller which is maintaining the robot on a course. in this paper, we examine the problem in a special case, where the ground plane is assumed to be horizontal and there are two locally parallel side-lines available. this assumption holds in many indoor environments, such as hallways, where the system''s success has been demonstrated. the algorithm uses geometric features such as vanishing points and line orientations. both theoretical analysis and experimental results show that this algorithm works very robustly and accurately.
revising the robust control design for rigid robot manipulators. robust controllers for robot manipulators ensure stability of the closed-loop system, even if only partial knowledge of the dynamic model of the manipulator is available. existing derivations of robust-control laws, while guaranteeing the stability result, present an undesired dependence of the robust-control term on the gains of the controller for the nominal system. this dependence forces larger robust-control terms when the nominal control gains are large. based on a structured representation of the model uncertainty, this paper proposes a derivation of the robust-control law, where these limitations are removed. experimental results on the comau smart 3s industrial robot in a 3-degree-of-freedom (dof) configuration confirm the advantages of the proposed controller.
multi-robot area patrol under frequency constraints. patrolling involves generating patrol paths for mobile robots such that every point on the paths is repeatedly covered. this paper focuses on patrolling in closed areas, where every point in the area is to be visited repeatedly by one or more robots. previous work has often examined paths that allow for repeated coverage, but ignored the frequency in which points in the area are visited. in contrast, we first present formal frequency-based optimization criteria used for evaluation of patrol algorithms. then, we present a patrol algorithm that guarantees maximal uniform frequency, i.e., each point in the target area is covered at the same optimal frequency. this solution is based on finding a circular path that visits all points in the area, while taking into account terrain directionality and velocity constraints. robots are positioned uniformly along this path in minimal time, using a second algorithm. moreover, the solution is guaranteed to be robust in the sense that uniform frequency of the patrol is achieved as long as at least one robot works properly. we then present a set of algorithms for handling events along the patrol path. the algorithms differ in the way they handle the event, as a function of the time constraints for handling them. however, all the algorithms handle events while maintaining the patrol path, and minimizing the disturbance to the system.
3d reconstruction of a femoral shape using a parametric model and two 2d fluoroscopic images. in medical diagnostic imaging, the x-ray ct scanner and the mri system have been widely used to examine 3d shapes and internal structures of living organisms and bones. however, these apparatuses are generally large and very expensive. since an appointment is also required before examination, these systems are not suitable for urgent fracture diagnosis in emergency treatment. however, x-ray/fluoroscopy has been widely used as traditional medical diagnosis. therefore, the realization of the reconstruction of precise 3d shapes of living organisms or bones from a few conventional 2d fluoroscopic images might be very useful in practice, in terms of cost, labor, and radiation exposure. the present paper proposes a method by which to estimate a patient-specific 3d shape of a femur from only two fluoroscopic images using a parametric femoral model. first, we develop a parametric femoral model by the statistical analysis of 3d femoral shapes created from ct images of 56 patients. then, the position and shape parameters of the parametric model are estimated from two 2d fluoroscopic images using a distance map constructed by the level set method. experiments using synthesized images, fluoroscopic images of a phantom femur, and in vivo images for hip prosthesis patients are successfully carried out, and it is verified that the proposed system has practical applications.
crowds of moving objects: navigation planning and simulation. this paper presents a solution to interactive navigation planning and real-time simulation of a very large number of entities moving in a virtual environment. from the environment geometry analysis, we deduce a structure called navigation graph, which is the base to our method. after the description of this structure, we introduce a set of algorithms dedicated to answer navigation queries with a set of various solution paths and to execute the planned navigation in an efficient manner. we equally demonstrate method performance and robustness over several examples.
safe planning for human-robot interaction. this paper presents a strategy for improving the safety of human-robot interaction by minimizing a danger criterion during the planning stage. this strategy is one part of the overall methodology for safe planning and control in human-robot interaction. the focus application is a hand-off task between an articulated robot and an inexpert human user. two formulations of the danger criterion are proposed: a criterion assuming independent safety-related factors, and a criterion assuming mutually dependent factors. simulations of the proposed planning strategy are presented for both 2d and 3d robots. the results indicate that a criterion based on scaled mutually dependent factors such as the robot inertia and the human robot distance generates safe, feasible paths for interaction. &copy; 2005 wiley periodicals, inc.
temporal range registration for unmanned ground and aerial vehicles. an iterative temporal registration algorithm is presented in this article for registering 3d range images obtained from unmanned ground and aerial vehicles traversing unstructured environments. we are primarily motivated by the development of 3d registration algorithms to overcome both the unavailability and unreliability of global positioning system (gps) within required accuracy bounds for unmanned ground vehicle (ugv) navigation. after suitable modifications to the well-known iterative closest point (icp) algorithm, the modified algorithm is shown to be robust to outliers and false matches during the registration of successive range images obtained from a scanning laser detection and ranging (ladar) rangefinder on the ugv. towards registering ladar images from the ugv with those from an unmanned aerial vehicle (uav) that flies over the terrain being traversed, we then propose a hybrid registration approach. in this approach to air to ground registration to estimate and update the position of the ugv, we register range data from two ladars by combining a feature-based method with the aforementioned modified icp algorithm. registration of range data guarantees an estimate of the vehicle's position even when only one of the vehicles has gps information. temporal range registration enables position information to be continually maintained even when both vehicles can no longer maintain gps contact. we present results of the registration algorithm in rugged terrain and urban environments using real field data acquired from two different ladars on the ugv.
general solution for the dynamic modeling of parallel robots. in this paper, we present a general method to calculate the inverse and direct dynamic models of parallel robots. the models are expressed in a closed form by a single equation in which all the elements needed are expressed. the solution is given in terms of the dynamic models of the legs, the dynamics of the platform and some jacobian matrices. the proposed method is applied in this paper on two parallel robots with different structures.
improving perception in time delayed teleoperation. telerobotics has long struggled to provide realistic force feedback to a user, especially across substantial time delays. wave variable based controllers provide stable force reflection at frequencies up to a few hertz for typical communication delays; however, the bandwidth of human perception extends to a thousand hertz. in this paper we aim to improve the user's perception by constructing a fundamentally asymmetric controller that better matches the sensory capabilities of the human operator. the improvements stem from two extensions to a normal wave variable controller. first, we revisit wave reflections and utilize wave filtering and shaping to separate distracting oscillations from useful reaction information. this avoids excess damping inherent to impedance matching and enhances the low-frequency feel of the system. secondly, we incorporate high-frequency feedback from a force sensor located at the slave end-effector. this augmented system leverages the passivation capabilities of wave filters to compensate for energy generation. it renders the complete spectrum of environment interaction forces to the user, allowing the perception of small environment features across substantial delays. these improvements are tested and validated in three simple experiments on a three-degrees-of-freedom testbed.
minimum wheel-rotation paths for differential-drive mobile robots. the shortest paths for a mobile robot are a fundamental property of the mechanism, and may also be used as a family of primitives for motion planning in the presence of obstacles. this paper characterizes shortest paths for differential-drive mobile robots, with the goal of classifying solutions in the spirit of dubins curves and reeds-shepp curves for car-like robots. to obtain a well-defined notion of shortest, the total amount of wheel-rotation is optimized. using the pontryagin maximum principle and other tools, we derive the set of optimal paths, and we give a representation of the extremals in the form of finite automata. it turns out that minimum time for the reeds-shepp car is equal to minimum wheel-rotation for the differential-drive, and minimum time curves for the convexified reeds-shepp car are exactly the same as minimum wheel-rotation paths for the differential-drive. it is currently unknown whether there is a simpler proof for this fact.
error-driven active learning in growing radial basis function networks for early robot learning. in this paper, we describe a new error-driven active learning approach to self-growing radial basis function networks for early robot learning. there are several mappings that need to be set up for an autonomous robot system for sensorimotor coordination and transformation of sensory information from one modality to another, and these mappings are usually highly nonlinear. traditional passive learning approaches usually cause both large mapping errors and nonuniform mapping error distribution compared to active learning. a hierarchical clustering technique is introduced to group large mapping errors and these error clusters drive the system to actively explore details of these clusters. higher level local growing radial basis function subnetworks are used to approximate the residual errors from previous mapping levels. plastic radial basis function networks construct the substrate of the learning system and a simplified node-decoupled extended kalman filter algorithm is presented to train these radial basis function networks. experimental results are given to compare the performance among active learning with hierarchical adaptive rbf networks, passive learning with adaptive rbf networks and hierarchical mixtures of experts, as well as their robustness under noise conditions.
on the design of traps for feeding 3d parts on vibratory tracks. in the context of automated feeding (orienting) of industrial parts, we study the algorithmic design of traps in the bowl feeder track that filter out all but one orientation of a given polyhedral part. we propose a new class of traps that removes a v-shaped portion of the track. the proposed work advances the state-of-the-art in algorithmic trap design by extending earlier work1,6,17—which focuses solely on 2d parts—to 3d parts, and by incorporating a more realistic part motion model in the design algorithm. we exploit the geometric structure of the design problem and build on concepts and techniques from computational geometry to obtain an efficient algorithm that reports the complete set of valid traps.
stability analysis for prioritized closed-loop inverse kinematic algorithms for redundant robotic systems. stability analysis of priority-based kinematic control algorithms for redundant robotic systems is approached in this paper. starting from the classical applications in position control of manipulators, the kinematic-based approaches have lately been applied to, e.g., visual servoing and quadruped or multirobot coordination control. a common approach consists in the definition of several tasks properly combined in priority. in this paper, by resorting to a lyapunov-based stability discussion for several prioritized inverse kinematics algorithms, sufficient conditions for the control gains and the tasks' design are given for the regulation problem. two case studies show the practical implementation of the results.
robot assisted real-time tumor manipulation for breast biopsy. breast biopsy guided by imaging techniques such as ultrasound is widely used to evaluate suspicious masses within the breast. the current procedure allows the clinician to determine the location and extent of a tumor in the patient breast before inserting the needle. however, there are several problems with this procedure: the complex interaction dynamics between the needle force and the breast tissue will likely displace the tumor from its original position, necessitating multiple insertions, causing clinicians' fatigue, patient's discomfort, and compromising the integrity of the tissue specimen. in this paper, we present a new concept for real-time manipulation of a tumor using a robotic controller that monitors the image of the tumor to generate appropriate external force to position the tumor at a desired location. the idea here is to demonstrate that it is possible to manipulate a tumor in real time by applying controlled external force in an automated way such that the tumor does not deviate from the path of the needle. experiments on breast phantoms are presented to demonstrate the essence of this concept. the success of this approach has the potential to reduce the number of attempts a clinician makes to capture the desired tissue specimen, minimize tissue damage, improve speed of biopsy, reduce patient discomfort, and eliminate false negative results.
insertable surgical imaging device with pan, tilt, zoom, and lighting. in this paper we describe work we have done in developing an insertable surgical imaging device with multiple degrees of freedom for minimally invasive surgery. the device is fully insertable into the abdomen using standard 12 mm trocars. it consists of a modular camera and lens system which has pan and tilt capability provided by two small dc servo motors. it also has its own integrated lighting system that is part of the camera assembly. once the camera is inserted into the abdomen, the insertion port is available for additional tooling, motivating the idea of single-port surgery. a third zoom axis has been designed for the camera as well, allowing close-up and far-away imaging of surgical sites with a single camera unit. in animal tests with the device we have performed surgical procedures including cholecystectomy, appendectomy, running (measuring) the bowel, suturing, and nephrectomy. preliminary tests suggest that the new device may have advantages over a standard laparoscope including the following. • low-cost and simple design. • easier and more intuitive to use than a standard laparoscope. • joystick operation requires no specialized operator training. • pan/tilt functions provide a large imaging volume not restricted by the fulcrum point of standard laparoscope. • time to perform procedures was better than or equivalent to a standard laparoscope. we believe these insertable platforms will be an integral part of future surgical systems. the platforms can be used with tooling as well as imaging devices, allowing many surgical procedures to be performed using such a system.
baseball seasons and dog years. from 1995 through 1997, instant sports used the internet to provide interactive real-time coverage of major league baseball. the changes in instant sports core architecture during that time provide some lessons about architectural evolution in the context of rapidly changing technology, including the need to identify fundamental issues rather than trendy ones, the importance of a good domain model, and the role of domain characteristics in balancing computational and communication resources.
an automatic programming system to support an experimental science. programs are often used in experimental sciences to test new models and theories against real-world data. one of the major bottlenecks in that process is the need to write the program which implements the new model. &oslash;0 is an automatic programming system which supports petroleum scientists in testing quantitative log interpretation models against log data from oil wells. the user (a petroleum scientist) describes a model by interacting with &oslash;0 in the natural terms of the domain. &oslash;0 then automatically writes a program which implements the model. the entire process takes from ten to twenty minutes and achieves results which previously required two to three weeks of effort.
observations on the interaction between coding and efficiency knowledge in the psi program synthesis system. this paper discusses how the synthesis phase of the psi system constructs programs from high level program models by using coding knowledge and efficiency knowledge. in our preliminary implementation, these knowledge bases are separated into distinct modules, the coding expert and the efficiency expert. we describe how the coding expert uses rule-based programming knowledge to produce alternative algorithm and data structure choices, and how the efficiency expert selects the best choice by estimating the costs of the alternatives using analysis of algorithm techniques. communication between the modules centers around descriptions of partially developed programs which are produced by the coding expert and analyzed by the efficiency expert. our system has implemented several small programs. from our experience with these modules, we conclude that there is a strong interaction between coding and efficiency knowledge which necessitates a corresponding complexity in the communication mechanism.
the stream machine: a data flow architecture for real-time applications. the stream machine is a software architecture designed to support the development and evolution, as well as the efficient execution, of software that performs both data acquisition and process control under real-time constraints. a stream machine program consists of a set of concurrently executing modules communicating through streams of data. streams provide essentially a data flow style of communication, thereby supporting deterministic data acquisition and calculation. the basic constructs have been augmented by several time-based operations to support process control software. in addition, explicit declarations of timing constraints layered on stream machine programs are currently being explored for resource allocation and scheduling. our experience to date with two implementations of the stream machine suggests that it facilitates the mixture of software that performs both data acquisition and process control.
the dimensions of healthy maintenance. what characterizes &ldquo;healthy&rdquo; or &ldquo;satisfactory&rdquo; software maintenance? how can we know it when we see it? this paper gives initial answers to these questions. we first argue the need for objectively measurable maintenance performance criteria in judging the &ldquo;adequacy&rdquo; of maintenance and present a set of criteria for judging maintenance performance in a particular software environment. we then subject the criteria to a practical test by applying them in this environment. we show how applying the criteria enables an informed overall maintenance performance appraisal, locates general maintenance problems, stimulates suggestions for improving maintenance on individual projects, allows these projects' maintenance to be compared and the projects ordered for improvement, and assesses the potential effectiveness of the suggestions in new project maintenance. we also sketch how criteria application can be generalized to software development monitoring and design methodology evaluation.
a flexible environment for program development based on a symbolic interpreter. the paper describes an interactive programming system which provides an integrated collection of tools for dealing with the whole process of program development. the pivot tool, the symbolic interpreter, may cover a broad range of applications, from testing to correctness proving. the aspects in which the symbolic interpreter differs from a conventional interpreter, i.e. the possibility of handling nondeterministic branching at choice points and the presence of a system for manipulating symbolic expressions, are described. furthermore, the main features of a programming language, around which the programming system is built, are presented.
facts and myths affecting software reuse. discusses the three most important facts or myths affecting reuse. there is a great deal of misunderstanding about reuse in the software domain and it is difficult to pick out only three: there has been to much emphasis on the reuse of code; software reuse implies some form of modification of the artifact being reused; and software development processes do not explicitly support reuse, in fact they implicitly inhibit reuse
a compliance notation for verifying concurrent systems. the compliance notation provides a practical system where both formal and informal techniques can be employed in software verification. the notation has been successfully applied in verifying some industrial safety-critical systems, but currently it has no support for verifying concurrent systems. this research aims to extend the compliance notation with appropriate support for verifying concurrent systems.
estimation of project success using bayesian classifier. the software projects are considered to be successful if the cost and the duration are within the estimated ones and the quality is satisfactory. to attain project success, the project management, in which the final status of project is estimated, must be incorporated.in this paper, we consider estimation of the final status(that is, successful or unsuccessful) of project by applying bayesian classifier to metrics data collected from project. in order to attain high estimation accuracy rate, we must select only a set of appropriate metrics to be applied. here we consider two selection methods: the first method by the experts and the second method by the statistical test.then we conducted an experiment using 28 project data and 29 metrics data in an organization of a certain company. the result showed that the method by the test gave higher accuracy rates than the method by the experts, and bayesian classifier with the test method is effective to estimate project success.
using version control data to evaluate the impact of software tools. software tools can improve the quality and maintainability of software, but are expensive to acquire, deploy and maintain, especially in large organizations. we explore how to quantify the effects of a software tool once it has been deployed in a development environment. we present a simple methodology for tool evaluation that correlates tool usage statistics with estimates of developer effort, as derived from a project's change history (version control system). our work complements controlled experiments on software tools, which usually take place outside the industrial setting, and tool assessment studies that predict the impact of software tools before deployment. our analysis is inexpensive, non-intrusive and can be applied to an entire software project in its actual setting. a key part of our analysis is how to control confounding variables such as developer work-style and experience in order accurately to quantify the impact of a tool on developer effort. we demonstrate our method in a case study of a software tool called ve, a version-sensitive editor used in belllabs. ve aids software developers in coping with the rampant use of preprocessor directives (such as if/ endif) in c source files. our analysis found that developers were approximately 36% more productive when using ve than when using standard text editors.
an analysis of software project failure. the main aim of this paper is to indicate how various losses may be reduced or avoided when the development of software does not proceed according to its schedule; i.e., if what we call &ldquo;bankruptcy&rdquo; occurs. data were collected from twenty three projects in various types of applications, the projects together containing a million lines of code. the causes of failure in developing software were obtained by interviewing the managers of the projects under observation. having analysed these two aspects, this paper points out under what circumstances managers are likely to fail and proposes a method of detecting failures in the software development.
automating bug report assignment. open-source development projects typically support an open bug repository to which both developers and users can report bugs. a report that appears in this repository must be triaged to determine if the report is one which requires attention and if it is, which developer will be assigned the responsibility of resolving the report. large open-source developments are burdened by the rate at which new bug reports appear in the bug repository. the thesis of this work is that the task of triage can be eased by using a semi-automated approach to assign bug reports to developers. the approach consists of constructing a recommender for bug assignments; examined are both a range of algorithms that can be used and the various kinds of information provided to the algorithms. the proposed work seeks to determine through human experimentation a sufficient level of precision for the recommendations, and to analytically determine the trade-offs of the various algorithmic and information choices.
introducing a software design language. this paper introduces software design language sdl-1, which is designed to serve as a design tool for the software engineer. in order to achieve this objective, some novel language constructs have been conceived. a sdl-1 design specification is a top-down 3-level structure. special keywords (called structure, storage, and control keywords) are employed and placed to clearly indicate the design structure. these keywords are highly suggestive and descriptive to the nature of data structure and control constructs. sdl-1 requires the declaration of all procedure names and the description of their functions at the very beginning of the design specifications. it requires also the declaration of all data storages and all switches, it describes the procedure structure, the data-storage reference structure, and the switch structure. all procedures are defined with single-in-single-out control constructs with one exception. the first procedure is the main procedure. no procedure definition is permitted within a procedure definition. the writing style and design practice are also a necessary part in using the language for a software design. in short, a sdl design specification is a structured design whose data storage is descriptive and direct, whose procedure structure describes the procedure calling and returning relationship, whose switch structure and reference structure indicate the inter-procedure communication, and whose control flow in a procedure is structured and readily observable.
modeling and implementing software architecture with acme and archjava. we demonstrate a tool to incrementally synchronize an acme architectural model described in the acme architectural description language (adl) with an implementation in archjava, an extension of the java programming language that includes explicit architectural modeling constructs.
the design of whole-program analysis tools. building efficient tools for understanding large software systems is difficult. many existing program understanding tools build control flow and data flow representations of the program a priori, and therefore may require prohibitive space and time when analyzing large systems. since much of these representations may be unused during an analysis, we construct representations on demand, not in advance. furthermore, some representations, such as the abstract syntax tree, may be used infrequently during an analysis. we discard these representations and recompute them as needed, reducing the overall space required. finally, we permit the user to selectively trade off time for precision and to customize the termination of these costly analyses in order to provide finer user control. we revised the traditional software architecture for compilers to provide these features without unnecessarily complicating the analyses themselves. these techniques have been successfully applied in the design of a program slicer for the comprehensive health care system (chcs), a million line hospital management system written in the mumps programming language.
software engineering 2004: acm/ieee-cs guidelines for undergraduate programs in software engineering. this paper is an overview of software engineering 2004, the software engineering volume of the computing curricula 2001 project. we briefly describe the contents of the volume, the process used in developing the volume's guidelines, and how we expect the volume to be used in practice.
inferring templates from spreadsheets. we present a study investigating the performance of a system for automatically inferring spreadsheet templates. these templates allow users to safely edit spreadsheets, that is, certain kinds of errors such as range, reference, and type errors can be provably prevented. since the inference of templates is inherently ambiguous, such a study is required to demonstrate the effectiveness of any such automatic system. the study results show that the system considered performs significantly better than subjects with intermediate to expert level programming expertise. these results are important because the translation of the huge body of existing spreadsheets into a system based on safety-guaranteeing templates cannot be performed without automatic support. we also carried out post-hoc analyses of the video recordings of the subjects' interactions with the spreadsheets and found that although expert-level subjects needed less time and developed more accurate templates than less experienced subjects, they did not inspect fewer cells in the spreadsheet. %and found that expert-level subjects spend less time and inspect fewer cells in the spreadsheet and develop more accurate templates than subjects with less experience.
accelerating software development through collaboration. in early 1999, va software launched a project to understand how the internet development community had been able to produce software such as linux, apache and samba that was generally developed faster and with higher quality than comparable commercially available alternatives [1,2,3,20]. our goal was simple: determine how to make more software development projects successful.we discovered that successful internet community projects employed a number of practices that were not well characterized by traditional software engineering methodologies. we now refer to those practices as collaborative software development or csd. late in 1999 we developed the sourceforge platform to make it easy for even small software development projects to employ those practices, and in november of 1999 launched the sourceforge.net web site based on the sourceforge platform.the site was an overwhelming success, and in less than two years, grew to support more than 27,000 software development projects and over a quarter million software developers worldwide. sourceforge.net affords us an unequaled test bed for understanding csd. in response to demand from companies seeking to enable csd within their organizations, we announced a commercial version of the sourceforge platform, sourceforge enterprise edition, in august 2001.this paper describes the principles of csd, the software development pain points those principles address, and our experience enabling csd with the sourceforge platform.
commitment development in software process improvement: critical misconceptions. it has been well established in the software process improvement (spi) literature and practice that without commitment from all organizational levels to spi the initiative will most likely fail or the results are not far reaching. commitment construct is explored and three forms of commitment are introduced: affective, continuance and normative commitment. analysis shows that current models of commitment development lack scientific validity and are based on four misconceptions: (1) the assumption of linearity of the human cognitive processes (i.e., commitment in this case), (2) the controllability of this process, (3) the notion of singular commitment construct, and (4) the sole utility perspective on the commitment phenomenon. implications of these findings for spi research and practice are discussed.
validating the unit correctness of spreadsheet programs. financial companies, engineering firms and even scientistscreate increasingly larger spreadsheets and spreadsheetprograms. the creators of large spreadsheets makeerrors and must track them down. one common class oferrors concerns unit errors, because spreadsheets often employformulas with physical or monetary units.in this paper, we describe xelda, our tool for unit checkingexcel spreadsheets. the tool highlights cells if theirformulas process values with incorrect units and if derivedunits clash with unit annotations. in addition, it draws arrowsto the sources of the formulas for debugging. the toolis sensitive to many of the intricacies of excel spreadsheetsincluding tables, matrices, and even circular references.using xelda, we have detected errors in some publishedscientific spreadsheets.
addressing software dependability with statistical and machine learning techniques. our ability to design and deploy large complex systems is outpacing our ability to understand their behavior. how do we detect and recover from "heisenbugs," which account for up to 40% of failures in complex internet systems, without extensive application-specific coding? which users were affected, and for how long? how do we diagnose and correct problems caused by configuration errors or operator errors? although these problems are posed at a high level of abstraction, all we can usually measure directly are low-level behaviors---analogous to driving a car while looking through a magnifying glass. machine learning can bridge this gap using techniques that learn "baseline" models automatically or semi-automatically, allowing the characterization and monitoring of systems whose structure is not well understood a priori. i'll discuss initial successes and future challenges in using machine learning for failure detection anbd diagnosis, configuration troubleshooting, attribution (which low-level properties appear to be correlated with an observed high-level effect such as decreased performance), and failure forecasting.
new directions on agile methods: a comparative analysis. agile software development methods have caught the attention of software engineers and researchers worldwide. scientific research is yet scarce. this paper reports results from a study, which aims to organize, analyze and make sense out of the dispersed field of agile software development methods. the comparative analysis is performed using the method's life-cycle coverage, project management support, type of practical guidance, fitness-for-use and empirical evidence as the analytical lenses. the results show that agile software development methods, without rationalization, cover certain/different phases of the software development life-cycle and most of the them do not offer adequate support for project management. yet, many methods still attempt to strive for universal solutions (as opposed to situation appropriate) and the empirical evidence is still very limited based on the results, new directions are suggested in principal it is suggested to place emphasis on methodological quality -- not method quantity.
improving software security with a c pointer analysis. this paper presents a context-sensitive, inclusion-based, field-sensitive points-to analysis for c and uses the analysis to detect and prevent security vulnerabilities in programs. in addition to a conservative analysis, we propose an optimistic analysis that assumes a more restricted c semantics that reflects common c usage to increase the precision of the analysis.this paper uses the proposed pointer alias analyses to infer the types of variables in c programs and shows that most c variables are used in a manner consistent with their declared types. we show that pointer analysis can be used to reduce the overhead of a dynamic string-buffer overflow detector by 30% to 100% among applications with significant overheads. finally, using pointer analysis, we statically found six format string vulnerabilities in two of the 12 programs we analyzed.
formal methods in industry: achievements, problems, future. two real projects using the b formal method are quickly presented. they show how some important parts of complex systems can be developed in such a way that the outcome is "correct by construction". a number of factors are then analyzed relating the pros, the cons, and the difficulties in applying this approach in industry.
the graft-host method for design change. the authors report on the graft-host (g-h) method, a practical method for changing designs incrementally by means of graft-and-repair steps. the method is not automated. computational support to designers applying g-h comes in the form of tools to help them reuse design information and manage databases of constraints. the method derives its strength from the reuse of analysis and design information. some key features of g-h are: evaluation of grafts and host systems at the analysis and design level by reusing information from technology books (g. arango et al., 1993); reuse and adaptation of software components driven by analysis and design considerations; evaluation of designs along multiple design dimensions; and composition of change rationales as formal explanations of change propagation and change tradeoff analyses. the g-h method was validated on the redesign of industrial products in the context of technology books
experimental results on the paging behavior of numerical programs. traces of numerical programs are used to examine their behavior in a paged virtual memory system. the working set policy is used for the replacement algorithm. it is found that the behavior of such programs is different from the behavior of other types of programs like compilers and system programs. these differences are most significant in the lifetime curves and the space-time cost curves. all programs examined showed ill-behavior. moreover, the space-time costs of executing these programs are very sensitive to the choice of the control parmater, the window size. our measurements show that approximations based on the common practice of using virtual time instead of real time in generating statistics are often inaccurate. the &ldquo;primary knee criterion&rdquo; of optimizing the space-time cost did not hold for some programs. the parameter-real memory and the real memory-fault rate anomalies show significantly in all but one of the seventeen programs examined.
opsis: a view mechanism for software processes which supports their evolution and reuse. the paper describes opsis, a view mechanism applied to graph based process modelling languages of type petri net. a view is a sub model which can be mechanistically constructed from another model by application of a perspective which: identifies all parts of the original model that are contained in the submodel; identifies and transforms all parts that constitute the interface to other sub models; adds new link relations to describe the behaviour of the sub model in interaction with the other sub models. sub models are more easy to grasp and can be limited in scope to some well defined aspects of a global model, such as the view point ofa single role player. composition of sub models is achieved through a merge operation on interface elements of sub models. the intended use of opsis is: 1) process evolution-changes can be localised to certain views, which largely reduces the complexity of applying change; and 2) process reuse-libraries can contain reusable fragments of type view that can be combined using the composition operators.
optimization of software development. for many companies, including leaders in software development, software is becoming an increasingly critical competitive factor. for example, at siemens, sixty percent of our business is strongly influenced by software and approximately fifty percent of all siemens patents are software related. with more than 30,000 software developers worldwide and an expenditure of more than 3 billion euros, siemens is playing in the 'champions league' of the world's leading software companies. but this fact is not well known because most of the software developed at siemens is embedded. it's embedded in the products and solutions sold to customers, such as medical devices, automation controls, trains, automotive components, and even power plants. yet a major part of the functionality of these products and solutions is defined by software.because of the high cost of developing software, and because of its extraordinarily high business impact, optimizing the software development process has become a top priority at siemens. simplifying, standardizing and stabilizing development processes and measuring progress according to the cmmi of the software engineering institute, making better use of existing synergy potentials, for example by using cross-divisional software platforms and architectures, and reducing costs by making structural changes, such as offshoring software development to low-wage countries and using the skills of different cultures, especially in rapidly-developing asian markets.the three levers will be described in detail and examples will be provided. the presentation will emphasize the early phases of software development, particularly with reference to requirements engineering and the importance of functional and non-functional requirements. a simple metrics system to measure success in software development will be presented. the siemens software initiative, a company-wide program specializing on software engineering and management at siemens will also be described.
analyzing partially-implemented real-time systems. we propose a method for analyzing partially-implemented real-time systems. here we consider real-time concurrent systems for which some components are implemented in ada and some are partially specified using regular expressions and graphical interval logic (gil), a real-time temporal logic. we show how to construct models of the partially-implemented systems that account for such properties as run-time overhead and scheduling of processes, yet support tractable analysis of nontrivial programs. the approach can be fully automated, and we illustrate it by analyzing a small example.
extending the discipline: how software can help or hinder human decision making (and vice-versa). developments in computing offer experts in many fields specialised support for decision making under uncertainty. however, the impact of these technologies remains controversial. in particular, it is not clear how advice of variable quality from a computer may affect human decision makers. here i review research showing strikingly diverse effects of computer support on expert decision-making. decisions support can both systematically improve or damaged the performance of decision makers in subtle ways depending on the decision maker's skills, variation in the difficulty of individual decisions and the reliability of advice from the support tool.in clinical trials decision support technologies are often assessed in terms of their average effects. however this methodology overlooks the possibility of differential effects on decisions of varying difficulty, on decision makers of varying competence, of computer advice of varying accuracy and of possible interactions among these variables. research that has teased apart aggregated clinical trial data to investigate these possibilities has discovered that computer support was less useful for - and sometimes hindered - professional experts who were relatively good at difficult decisions without support; at the same time the same computer support tool helped those experts who were less good at relatively easy decisions without support. moreover, inappropriate advice from the support tool could bias decision makers' decisions and, predictably, depending on the type of case, improve or harm the decisions.
design and verification of communication procedures: a bottom-up approach. the verification of functional specifications is performed by means of a formal model, based upon petri nets. a so-called "reduction" operation is introduced to handle the concept of abstraction. a bottom-up approach is developped in the case of communication between two processors. the definition of software modules is emphasized.
human capacities in the software process: empiric validation. in this paper an empiric validation of a person to role allocation process is presented. in this process the allocation of persons to fulfill roles is made according to the capacities that the persons possess and those required by the roles in the software process. a set of experiments are carried out dealing with the development of the initiation, planning and estimation process, domain study process, requirements analysis process and design process of eight projects. it was proved that the estimated time deviation, as well as the errors found in the technical reviews of requirements specification, were less when the persons fulfilling the roles of planning engineer, domain analyst, requirements specificator and designer were allocated, according to the proposed process, considering the set of critical human capacities.
specification and verification of distributed systems using prolog interpreded petri nets. this paper presents a formal description technique for distributed systems. the basic choices concern petri nets as a modeling tool and prolog as a programming environment. the key elements of the introduced approach are a symbolic interpreter for predicate transition nets, and a technique for interfacing concurrent processes. several illustrative examples are provided.
an interactive tool for program manipulation. an interactive system for understanding programs has been designed. this system provides informations about control structure and data flow. it also performs powerful semantic transformations that are checked for validity. the system relies on previously implemented algorithms that apply to a graph representation of programs.
interactive software development tool: isdt. this paper describes an interactive software development tool(isdt),which supports the detailed system design and the manufacture phase in the business application system development. the isdt is based on standardized technology and engineering for programming support (steps), experience gained is complied, and new program development support techniques are adopted. the isdt user will be able to design programs interactively while sitting at a display terminal. isdt manages specifications stored in a database and automatically generates cobol programs and documents as required. this paper discusses business application program characteristics at first. then it is shown how the development support system should be handled. next, isdt functions are explained with plenty of figures.
towards a distributed software architecture evaluation process: a preliminary assessment. scenario-based methods for evaluating software architecture require a large number of stakeholders to be collocated for evaluation sessions. collocating stakeholders is often an expensive exercise. we have proposed a framework for distributed evaluation process. we present the proposed framework and initial results of a controlled experiment that we ran to assess the effectiveness of the proposed idea.
developing and deploying software engineering courseware in an adaptable curriculum framework. we describe an effort to design an adaptable framework for teaching and learning in software engineering. we are developing a repository of asynchronous, multimedia courseware that facilitates the rapid incorporation of new advances in research and technology, enables courses to be tailored to individual student needs and interests, leverages innovations in educational technology and encourages innovation in teaching and in student learning. our emphasis is on developing composable multi-level &ldquo;knowledge and topic units&rdquo; (ku/tus) that can be employed to tailor course content and depth to fit the needs of a diverse student population. we have developed &ldquo;live&rdquo; and on-line course material for ku/tus in software engineering and taught courses using this material. the framework was deployed in three software engineering courses (previously taught concurrently) and provides quite different learning environments for the students in each course and, to some extent, tailors the courses to individual students within the classes based on their skills, objectives and backgrounds. we describe efforts at formative evaluation. student satisfaction is high and available measures of success, e.g., student performance, have improved markedly. we also describe a project now beginning to build on this prototype that will be accompanied by more extensive formative and summative evaluation.
data-driven implementation of data flow diagrams. current software engineering methods employ a variety of design notations and techniques during the development process. this paper suggests a new, unified approach to developing software, termed program/system design. programs are viewed as being made up of systems of data-coupled, data-activated processing units. using a coherent hierarchy of data flow diagrams, complex systems are specified as compositions of successively simpler systems. the methods are illustrated by a program/system solution to the telegram problem.
design considerations in language processing tools for ada. the ada language system (als) is a complete programming environment for the development of ada programs. this paper discusses the design objectives of those portions of the als which support translation and execution of ada programs, particularly the compiler, linker, and program library. the als capabilities for maintenance of software configuration control are highlighted. tradeoffs in the design of the compiler phase structure and intermediate languages are presented.
verification system for formal requirements description. the requirements description which is proved to be correct is the key to the successful development of a reliable system. since the adaptability of the requirements description language is obtained with a simple and extensible language structure, most part of communication is maintained with proper use of labels. many verification system can provide only restricted capability because of lack of the recognition of meaning of labels. this paper proposes the verification method with assertion description which gives another view of a target system. first, the formal model of the verification is given. next, the verification method based on theorem proving and several views for verification are mentioned. last, the verification system and examples are shown.
introduction to the attribute driven design method. this tutorial will introduce the attribute driven design (add) method. add is a method for designing the software architecture of a system or collection of systems based on an explicit articulation of the quality attribute goals for the system(s). the method is appropriate for any quality attributes but has been particularly elaborated for the attributes of performance, modifiability, security, reliability/availability and usability. the method has been used for designing the software architecture of products ranging from embedded to information systems.
a fast assembly level reverse execution method via dynamic slicing. one of the most time consuming parts of debugging istrying to locate a bug. in this context, there are two powerfuldebugging aids which shorten debug time considerably:reverse execution and dynamic slicing. reverse executioneliminates the need for repetitive program restartsevery time a bug location is missed. dynamic slicing, onthe other hand, isolates code parts that influence an erroneousvariable at a program point. in this paper, we presentan approach which provides assembly level reverse executionalong a dynamic slice. in this way, a programmer notonly can find the instructions relevant to a bug, but also canobtain runtime values of variables in a dynamic slice whiletraversing the slice backwards in execution history.reverse execution along a dynamic slice skips recoveringunnecessary program state; therefore, it is potentiallyfaster than full-scale reverse execution. the experimentalresults with four different benchmarks show a wide range ofspeedups from 1.3x for a small program with few data inputsto six orders of magnitude (1,928,500x) for 400x400matrix multiply. furthermore, our technique is very memoryefficient. our benchmark measurements show between3.4x and 2240x memory overhead reduction as comparedto our implementation of the same features using traditionalapproaches.
lessons from using basic lotos. we describe three case studies in the use of basic lotos for electronic switching systems software. the studies cover design recovery, requirements specification, and design activities. we also report lessons learned from the studies. early lessons suggested changes to the syntax of the language used, and the need for some specific analysis tools. the last case study reports some of the results of these changes
automatic generation of rule-based software configuration management systems. we propose a model-driven methodology and toolset for automatic scm system repository creation and feature composition using code generation and rule engine technologies.
a quality-driven systematic approach for architecting distributed software applications. architecting distributed software applications is a complex design activity. it involves making decisions about a number of inter-dependent design choices that relate to a range of design concerns. each decision requires selecting among a number of alternatives; each of which impacts differently on various quality attributes. additionally, there are usually a number of stakeholders participating in the decision-making process with different, often conflicting, quality goals, and project constraints, such as cost and schedule. to facilitate the architectural design process, we propose a quantitative quality-driven approach that attempts to find the best possible fit between conflicting stakeholders' quality goals, competing architectural concerns, and project constraints. the approach uses optimization techniques to recommend the optimal candidate architecture. applicability of the proposed approach is assessed using a real system.
enhancing program readability and comprehensibility with tools for program visualization. in order to make computer programs more comprehensible, the presentation of program source text, program documentation, and program execution needs to be enhanced over its conventional treatment. the paper describes a number of new techniques and tools developed to achieve these ends. one of these is a novel design for the effective presentation of source text in the c programming language using high quality digital typography, and a processor which implements the design. some experimental evidence is summarized to demonstrate that the resulting source text presentation is significantly more readable and comprehensible than the presentation conventionally used today. brief descriptions are also given of two other techniques, the development of a novel system of structured program documentation incorporating both text and graphics, and the portrayal of program execution with coloured computer animation.
component-based self-adaptability in peer-to-peer architectures. current peer-to-peer architectures are hardly resistantagainst unanticipated exceptions such as the failure ofsingle peers. this can be justified by the absence of sophisticatedmodels for detecting and handling exceptionin peer-to-peer architectures. on the other hand, existingmodels for such self-adaptable architectures are rathergeneric and less practical for end-users. in this work, acomponent-based self-adaptability model for peer-to-peerarchitectures is presented that supports end-users in thehandling of exceptions during use time. support is alsoprovided to handle exceptions during deployment andadaptation of an application. all these approaches areintegral parts of deevolve, a peer-to-peer runtime environmentfor component-based peer services.
the two-step commitment protocol: modeling, specification and proof methodology. a two-step commitment algorithm which assures transaction update atomicity in a distributed data base is modelled using colored petri nets. the modeling helps in determining the numerous crash possibilities and in specifying recovery procedures and associated protocols. the use of unalterable logs is required and modelled accordingly. a methodology for proof correctness based on linear invariants is presented.
archjava: connecting software architecture to implementation. software architecture describes the structure of a system, enabling more effective design, program understanding, and formal analysis. however, existing approaches decouple implementation code from architecture, allowing inconsistencies, causing confusion, violating architectural properties, and inhibiting software evolution. archjava is an extension to java that seamlessly unifies software architecture with implementation, ensuring that the implementation conforms to architectural constraints. a case study applying archjava to a circuit-design application suggests that archjava can express architectural structure effectively within an implementation, and that it can aid in program understanding and software evolution.
using a web-based project process throughout the software engineering curriculum. in order to facilitate the study and use of software process, which is essential to the education of future software professionals, a standard and tailorable project process has been developed over the last five years at texas tech university for use in both undergraduate and graduate curricula, with a total 12 courses involved. the process is entirely web-based, and includes a complete set of html document templates in order to facilitate the creation of project artifacts which are posted to the course web page. this method enhances communication between team members, including distance education students, and between the project team and client. the project process has received positive feedback from all stakeholders involved.this paper discusses the benefits of the web-based project process, its relation to curriculum models, and plans for a more formal assessment of the process. the portability of process to other institutions is also discussed, with an example provided.
visual timed event scenarios. formal description of real-time requirements is a difficult and error prone task. conceptual and tool support for this activity plays a central role in the agenda of technologytransference from the formal verification engineeringcommunity to the real time systems development practice.in this article we present v ts, a visual language to define complex event-based requirements such as freshness, bounded response, event correlation, etc. the underlyingformalism is based on partial orders and supports real-timeconstraints. the problem of checking whether a timed automatonmodel of a system satisfies these sort of scenariosis shown to be decidable. moreover, we have also developeda tool that translates visually specified scenarios into observertimed automata. the resulting automata can be composedwith a model under analysis in order to check satisfactionof the stated scenarios. we show the benefits of applyingthese ideas to some case studies.
a meta-model for software development resource expenditures. one of the basic goals of software engineering is the establishment of useful models and equations to predict the cost of any given programming project. many models have been proposed over the last several years, but, because of differences in the data collected, types of projects and environmental factors among software development sites, these models are not transportable and are only valid within the organization where they were developed. this result seems reasonable when one considers that a model developed at a certain environment will only be able to capture the impact of the factors which have a variable effect within that environment. those factors which are constant at that environment, and therefore do not cause variations in the productivity among projects produced there, may have different or variable effects at another environment. this paper presents a model-generation process which permits the development of a resource estimation model for any particular organization. the model is based on data collected by that organization which captures its particular environmental factors and the differences among its particular projects. the process provides the capability of producing a model tailored to the organization which can be expected to be more effective than any model originally developed for another environment. it is demonstrated here using data collected from the software engineering laboratory at the nasa/goddard space flight center.
the making of orbix and the iportal suite. iona released the first full implementation of the corba standard in august 1992, and our first product, orbix, has become the most successful object request broker, capturing almost 70-percent of this market. it has spawned many follow-on products from iona and from partner companies. this development followed nearly ten years of research in the area of distributed object systems within trinity college dublin, centered on language support for developers of distributed systems.this paper captures some of the lessons we ve learned in the transition from academia to business. we ve had to learn many software engineering skills. we ve had to find the right mix between engineering, marketing and sales expertise. we ve had to learn how to release new products while staying committed to current ones. and most recently, we ve had to learn how to become an internet-company in order to deliver the iportal suite. for ionaians, it has been a fascinating journey.
formalizing architectural connection. as software systems become more complex the overall system structure - or software architecture - becomes a central design problem. an important step towards an engineering discipline of software is a formal basis for describing and analyzing these designs. we present a theory for one aspect of architectural description, the interactions between components. the key idea is to define architectural connectors as explicit semantic entities. these are specified as a collection of protocols that characterize each of the participant roles in an interaction and how these roles interact. we illustrate how this scheme can be used to define a variety of common architectural connectors. we provide a formal semantics and show how this lends to a sound deductive system in which architectural compatibility can be checked in a way analogous to type checking in programming languages
visualizing software systems. there are many graphical techniques for visualizing software. unfortunately, the current techniques do not scale to display large software systems and are largely unused. we present a method for visualizing statistics associated with code that is divided hierarchically into subsystems, directories, and files. using this technique, we can display the relative sizes of the components in the system, which components are stable and which are changing, where the new functionality is being added, and identify error-prone code with many bug fixes. using animation, we can display the historical evolution of the code
an investigation on the use of machine learned models for estimating correction costs. we present the results of an empirical study in which we have investigated machine learning (ml) algorithms with regard to their capabilities to accurately assess the correctability of faulty software components. three different families of algorithms have been analyzed. we have used (1) fault data collected on corrective maintenance activities for the generalized support software reuse asset library located at the flight dynamics division of nasa's gsfc and (2) product measures extracted directly from the faulty components of this library
problems and programmers: an educational software engineering card game. problems and programmers is an educational card game that we have developed to help teach software engineering. it is based on the observation that students, in a typical software engineering course, gain little practical experience in issues regarding the software process. the underlying problem is time: any course faces the practical constraint of only being able to involve students in at most a few small software development projects. problems and programmers overcomes this limitation by providing a simulation of the software process. in playing the game, students become aware of not only general lessons, such as the fact that they must continuously make tradeoffs among multiple potential next steps, but also specific issues such as the fact that inspections improve the quality of code but delay its delivery time. we describe game play of problems and programmers, discuss its underlying design, and report on the results of a small experiment in which twenty-eight students played the game.
edmas: a locally distributed mail system. the eden project is a five-year effort to design, build and test operating system structures for local area networks. a specific goal is to allow users to obtain the advantages of both physical distribution and logical integration. since eden is physically distributed, its users can take advantage of personal workstations. since eden is logically integrated, system resources can be named and accessed in a location independent way. edmas, the eden mail system, was designed to be an early test of eden's usefulness. this paper describes the design and implementation of edmas, and presents several of the lessons we have learned about constructing location independent services and about the design of mail systems.
evaluating the tradeoffs of mobile code design paradigms in network management applications. the question of whether technologies supporting mobile code are bringing significant benefits to the design and implementation of distributed applications is still an open one. even more difficult is to identify precisely under which conditions a design exploiting mobile code is preferable over a traditional one. in this work, we present an in-depth evaluation of several mobile code design paradigms against the traditional client-server architecture, within the application domain of network management. the evaluation is centered around a quantitative model, which is used to determine precisely the conditions for the selection of a design paradigm minimizing the network traffic related to management
an extensible file system for hydra. an extensible file system has been designed and implemented for hydra, an advanced capability-based operating system. this system demonstrates three notable contributions to subsystem design: - it provides a protected and efficient implementation via user-level code of functions ordinarily implemented as part of a conventional system's monolithic privileged section, - it provides practical solutions to two protection problems, the modification problem and the confinement problem, for users of the file system, and - it provides separation of mechanisms for data representation from mechanisms for protection and synchronization, thus allowing an extensible family of subfile systems to evolve. this paper treats the design and implementation of the hydra file system and reflects on its implications for subsystem design and implementation.
ppt: a cots integration case study. t. rowe price investment technologies built the product and project tracking system (ppt) to reduce the human resources needed to track and forecast information technology projects. instead of developing or purchasing a new system, the need was met by integrating commercial-off-the-shelf (cots) products already used and licensed by the company. the conclusion can be made that this approach reduces development costs while providing more flexibility than a single vendor solution. this paper described the process used and issues encountered in building a system from software products generally intended for stand-alone applications. it discusses the rationale behind the system, the choice of products, the software engineering process used, the handling of changes, and modifications made in business practice. a discussion will be made of the initial return on investment and ongoing support requirements.
research towards a technology to support the specification of data processing system performance requirements. this paper summarizes the results of an initial investigation of a language and underlying technology for the design of data processing system performance requirements. the initial research results indicate that a technology based on petri nets, formal logic, and simulation can be used to describe and analyze some important aspects of data processing performance requirements. these initial language and technology concepts were successfully applied to fully describe a benchmark problem. future research will focus on the implementation and evaluation of automated verification and analysis procedures based on the technology.
a principle for resilient sharing of distributed resources. a technique is described which permits distributed resources to be shared (services to be offered) in a resilient manner. the essence of the technique is to a priori declare one of the server hosts primary and the others backups. any of the servers can perform the primary duties. thus the role of primary can migrate around the set of servers. the concept of n-host resiliency is introduced and the error detection and recovery schemes for two-host resiliency are presented. the single primary, multiple backup technique for resource sharing is shown to have minimal delay. in the general case, this is superior to multiple primary techniques.
inference of message sequence charts. software designers draw message sequence charts for early modeling of the individual behaviors they expect from the concurrent system under design. can they be sure that precisely the behaviors they have described are realizable by some implementation of the components of the concurrent system? if so, can we automatically synthesize concurrent state machines realizing the given mscs? if, on the other hand, other unspecified and possibly unwanted scenarios are "implied" by their mscs, can the software designer be automatically warned and provided the implied mscs? in this paper, we provide a framework in which all these questions are answered positively. we first describe the formal framework within which one can derive implied mscs and then provide polynomial-time algorithms for implication, realizability, and synthesis.
towards an effective software engineering course project. software engineering instructors face many challenges. among these challenges is the course project. instructors are required to train their students on the professional skills to be ready for the real world business, which requires the students to work on real projects. however, because of the low quality of the students' work, not all of the professional organizations are cooperating to offer a chance for the software engineering students to work on a real project. therefore, most of the software engineering courses' projects are in-class project, in which the instructors represent the clients. in this paper, i proposed a solution to this problem based on my experience in involving my software engineering students in real world projects.
bridging the requirements/design gap in dynamic systems with use case maps (ucms). two important aspects of future software engineering techniques will be the ability to seamlessly move from analysis models to design models and the ability to model dynamic systems where scenarios and structures may change at run-time. use case maps (ucms) are used as a visual notation for describing causal relationships between responsibilities of one or more use cases. ucms are a scenario-based software engineering technique most useful at the early stages of software development. the notation is applicable to use case capturing and elicitation, use case validation, as well as high-level architectural design and test case generation. ucms provide a behavioural framework for evaluating and making architectural decisions at a high level of design. architectural decisions may be based on performance analysis of ucms. ucms bridge the gap between requirements and design by combining behaviour and structure in one view and by flexibly allocating scenario responsibilities to architectural components. they also provide dynamic (run-time) refinement capability for variations of scenarios and structure and they allow incremental development and integration of complex scenarios. therefore, ucms address the issues mentioned above.
tolerating inconsistency. this is a short paper about a simple technique for making applications robust by marking data that violates specially identified invariants and using those marks as guards around code which is sensitive to that invariant. such a capability is needed when dealing with the exceptions that arise in practical applications and distinguish them from idealized specifications. previous techniques either required the removal of the constraint so that the exception would be allowed, or its modification to exclude the particular exception from the restriction. our technique softens the entire constraint without introducing special cases, and is intended primarily for temporary exceptions. rather than synchronizing all updates required by some constraint, it allows them instead to occur distributed in time in any arbitrary order. thus, it is particularly useful in multiclient applications with shared responsibilities and authority, such as cooperative design (including software development). while the constraint is violated, the offending data is automatically marked by guards to screen it from, or identify it to, code segments sensitive to the violation. when the time distributed update is complete so that the data is no longer inconsistent, the guards are automatically removed so that the data can again be processed normally. the relevance of this work to the process workshop is that it provides a technique for relaxing the synchronization problem among multiple users cooperating on some compound update and allows them instead to operate asynchronously. that is, this technique allows us to write more realistic process programs describing the flexible time-distributed coordinations among agents without loosing the formal constraints on their shared goals. the cost of this flexibility is the conditionalization of the cooperating agents to tolerate these temporary inconsistencies. we have created two implementations of our technique for softening constraints to allow temporary inconsistencies. both are fully automatic and both handle arbitrary constraints expressed in our first-order logic formalism. the first converts the original constraint into a pair of constraints that require the presence of the guards while the original constraint is violated and their absence otherwise. these new constraints have &ldquo;repairs&rdquo; which fix violations by respectively inserting or removing the guards. the second implementation replaces the original constraint by an inference rule which derives the guard if and only if the original constraint predicate was violated. our contribution lies in formally representing constraints whose temporary inconsistency can be tolerated by an application, and in automatically marking the particular offending data while the constraint is being violated. the goal of minimizing the number and duration of such violations is informal and implicit. the task of identifying sensitive code segments and determining how they should respond to the temporary inconsistencies is likewise informal and manual. our work has an interesting relationship with the recent work on transactions by pu, kaiser, and hutchinson @cite(split-transactions) addressing the times and set of users over which a constraint applies. they, too, are interested in multi-party transactions, and have proposed &ldquo;splitting&rdquo; transactions into pieces with differing visibility scopes so that users in some group could see the changes made by the splits within the transaction, while those outside the group wouldn't see any changes until the entire transaction was committed. split-transactions can be viewed as another approach to exception handling. rather than dealing with an exception or an inconsistency after a completed transaction, pu, kaiser, and hutchinson subdivide the transaction so that the multi-party coordinations can occur within it. as in all transactions, constraints are only applied when committed. thus, during the transaction the effect is to remove the constraints. the power of the split-transaction approach is the scoping (potentially multi-level) that it provides to allow groups to cooperatively prepare a compound update for a broader community. however, within the transaction, since the constraints are not in effect, the inconsistency is not explicit, and hence cannot be tracked, managed, or supported except by informal mechanisms outside the system. but there is no reason why split transactions couldn't be combined with our own techniques for tolerating inconsistency to provide the advantages of both. while the inconsistency existed, it would be guarded by pollution markers, but it would only be visible to the group (dynamically formed) needed to resolve that inconsistency. after it was resolved, the pollution markers would be removed, and the new consistent state would be visible outside the group.
cross software development for microprocessors using a translator writing system. this paper illustrates four experiences in cross software development for microprocessors. after a comparison among some programming techniques (high-level languages, macroprocessors, meta-assemblers and special purpose systems) a translator writing system has been used to implement a cross-assembler, a simulator, a microassembler and a cross compiler for a microprocessor, showing its great flexibility at a low cost. each of the four applications is briefly described and compared with similar programs written using other techniques.
application downloading. the purpose of our research is to investigate the feasibility of this methodology for distributed application development by examining possible approaches to carrying out such developments. in particular, our emphasis lies in transformation technology, wherein user-invoked source-to-source transformations are applied to the partitioned system for the purpose of optimizing the transactions required to effect the distributed behavior. in this way, the application downloading system need only produce a correct partitioning of the original program, not an efficient one. the user, with system guidance, optimizes the partitioned program by applying transformations chosen from the system library. thus, application downloading can be viewed as a narrow domain in which to apply the transformation technology we have developed elsewhere in a broader context(1).
supporting industrial hyperwebs: lessons in scalability. open hypermedia is one approach to managing the relationships that exist in software development projects. a key technical issue in this endeavor is support for scalability. our experience supporting scalability in open hypermedia has revealed several key insights including the notion of the transitivity of scalability, the need to consider issues of scale in moving from design to implementation, the need to apply multiple techniques in tandem, and the unexpected nontechnical issues that arise when scaling a system to meet the demands of industrial software engineering. these insights are grounded in observations of a development project that scaled an open hypermedia system, chimera, two orders of magnitude to meet the demands of an industrial user.
on the transformational implementation approach to programming. this paper discusses various approaches to programming, defining and highlighting transformational implementation; it then examines the basic causes of the software problem and their resolution with transformational implementation. finally, an example illustrating the approach is given.
dragonfly: linking conceptual and implementation architectures of multiuser interactive systems. software architecture styles for developing multiuser applications are usually defined at a conceptual level, abstracting such low-level issues of distributed implementation as code replication, caching strategies and concurrency control policies. ultimately, such conceptual architectures must be cast into code. the iterative design inherent in interactive systems implies that significant evolution will take place at the conceptual level. equally, however, evolution occurs at the implementation level in order to tune performance. this paper introduces dragonfly, a software architecture style that maintains a tight, bidirectional link between conceptual and implementation software architectures, allowing evolution to be performed at either level. dragonfly has been implemented in the java-based telecomputing developer (tcd) toolkit.
3rd international workshop on adoption-centric software engineering acse 2003. the key objective of this workshop is to explore innovative approaches to the adoption of software engineering tools and practices---in particular by embedding them in extensions of commercial off-the-shelf (cots) software products and/or middleware technologies. the workshop aims to advance the understanding and evaluation of adoption of software engineering tools and practices by bringing together researchers and practitioners who investigate novel solutions to software engineering adoption issues.
recovery blocks in action: a system supporting high reliability. the need for reliable complex systems motivates the development of techniques by which acceptable service can be maintained, even in the presence of residual errors. recovery blocks allow a software designer to include tests on the acceptability of the various phases of a system's operation, and to specify alternative actions should the acceptance tests fail. this approach relies on certain architectural features, ideally implemented in hardware, by which control and data structures can be retrieved after errors. a brief account is presented of the recovery block scheme, together with a description of a new implementation of the underlying cache mechanism. the salient features of a proposed computer architecture are described, which incorporates this implementation and also provides a high level of detection for errors such as the corruption of code and data. a prototype system has been constructed to test the viability of these techniques by executing programs containing recovery blocks on an emulator for the proposed architecture. experiences in running this system are recounted with respect to the execution of programs based on erroneous algorithms and also with respect to errors introduced by deliberate attempts to corrupt the system.
4th international workshop on adoption-centric software engineering. the acse series of events aims to advance the adoptionof software engineering tools and techniques by bringingtogether researchers and practitioners who investigatenovel approaches to fostering the transition betweenlimited-use research prototypes and broadly applicablepractical solutions. one proven technique to aidadoption is to leverage existing commercial platformsand infrastructure. the key objective of acse 2004 is toexplore innovative approaches to the adoption of proof-of-concept systems by embedding them in extensions of commercial off-the-shelf (cots) products and/or using middleware technologies to integrate the prototypes into existing toolsets.
towards large-scale information integration. software engineers confront many challenges during software development. one challenge is managing the relationships that exist between software artifacts. we refer to this task as information integration, since establishing a relationship between documents typically implies that an engineer must integrate information from each of the documents to perform a development task. in the past, we have applied open hypermedia techniques and technology to address this challenge. we now extend this work with the development of an information integration environment. we present the design of our environment along with details of its first prototype implementation. furthermore, we describe our efforts to evaluate the utility of our approach. our first experiment involves the discovery of keyword relationships between text-based software artifacts. our second experiment examines the code of an open source project and generates a report on how its module relationships have evolved over time. finally, our third experiment develops the capability to link code claiming to implement w3c standards with the xhtml representation of the standards themselves. these experiments combine to demonstrate the promise of our approach. we conclude by asserting that the process of software development can be significantly enhanced if more tools made their relationships available for integration.
hiding distribution in distributed systems. the author focuses on the evolution of transparency in distributed systems, that is, the provision of logically centralized system facilities on distributed system architectures. the author proposes a comparison between the virtues and faults of centralized and distributed architectures, and reviews the evolution of distributed systems. the notion of transparency is described in detail with some examples. the main features of new technologies used to build transparent subsystems on distributed architectures are discussed
an automated program testing methodology and its implementation. this paper describes an automated testing methodology and an experiment performed to determine its effectiveness. the method is to insert in the program to be tested a number of &ldquo;executable assertions,&rdquo; statements about the program that trigger error signals whenever they are evaluated to be false (violated). a test-case is then developed for the program using actual values of the input variables. when the program is run, a plot is generated of the number of assertions violated versus the input variable values used. the resulting function is called the &ldquo;error function&rdquo;. heuristic search algorithms can then be used to maximize this function and thereby automatically locate input values which cause the most errors to occur. the experiment included developing assertions for the program to be tested, choosing and inserting representative errors into the program, and implementing search and data collection algorithms for testing. the results indicate that combining executable assertions with heuristic search algorithms is an effective method for automating the testing of computer programs.
language features for description of cooperating processes. language features are introduced in order to describe communicating processes. these constructs allow a clear separation of the definition of processes from that of their cooperations rules. elements of a language for the description of communications are presented and discussed.
is mutation an appropriate tool for testing experiments? the empirical assessment of test techniques plays an important role in software testing research. one common practice is to instrument faults, either manually or by using mutation operators. the latter allows the systematic, repeatable seeding of large numbers of faults; however, we do not know whether empirical results obtained this way lead to valid, representative conclusions. this paper investigates this important question based on a number of programs with comprehensive pools of test cases and known faults. it is concluded that, based on the data available thus far, the use of mutation operators is yielding trustworthy results (generated mutants are similar to real faults). mutants appear however to be different from hand-seeded faults that seem to be harder to detect than real faults.
computational reflection in software process modeling: the slang approach. slang is a domain-specific language for software process modeling and enactment. the authors present the basic features provided by slang to support the enactment and, in particular, dynamic evolution of a process model. software production processes are subject to changes during their lifetime. therefore, software process formalism must include mechanisms to support the analysis and dynamic modification of process models, even while they are being enacted. it is thus necessary for a process model to have the ability to reason about its own structure. petri net based process languages have been criticized because of the lack of these reflective features and their inability to effectively support process evolution. the reflective features offered by slang are outlined, which is a process formalism based on a high-level petri net notation. in particular, the mechanisms are discussed to create and modify different net fragments while the modeled process is being enacted
theme: an approach for aspect-oriented analysis and design. aspects are behaviours that are tangled and scatteredacross a system. in requirements documentation, aspectsmanifest themselves as descriptions of behaviours that areintertwined, and woven throughout. some aspects may beobvious, as specifications of typical crosscutting behaviour.others may be more subtle, making them hard to identify. ineither case, it is difficult to analyse requirements to locateall points in the system where aspects should be applied.these issues lead to problems achieving traceability of aspectsthroughout the development lifecycle. to identify aspectsearly in the software lifecycle, and establish sufficienttraceability, developers need support for aspect identificationand analysis in requirements documentation. to addressthis, we have devised the theme approach for viewingthe relationships between behaviours in a requirements document,identifying and isolating aspects in the requirements,and modelling those aspects using a design language. thispaper describes the approach, and illustrates it with a casestudy and analysis.
third international workshop on dynamic analysis(woda 2005). dynamic analysis techniques reason over program executions and show promise in aiding the development of robust and reliable large-scale systems. it has become increasingly clear that limitations of static analysis can be overcome by integrating static and dynamic analyses, and that the performance and value of dynamic analysis can be improved by static analysis. hence, a key focus of the workshop will be on hybrid analyses that involve both static and dynamic components.
conceptual module querying for software reengineering. many tools have been built to analyze source. most of these tools do not adequately support reengineering activities because they do not allow a software engineer to simultaneously perform queries about both the existing and the desired source structure. this paper introduces the conceptual module approach that overcomes this limitation. a conceptual module is a set of lines of source that are treated as a logical unit. we show how the approach simplifies the gathering of source information for reengineering tasks, and describe how a tool to support the approach was built as a front-end to existing source analysis tools.
broad-spectrum studies of log file analysis. this paper reports on research into applying the technique of log file analysis for checking test results to a broad range of testing and other tasks. the studies undertaken included applying log file analysis to both unit- and system-level testing and to requirements of both safety-critical and non-critical systems, and the use of log file analysis in combination with other testing methods. the paper also reports on the technique of using log file analyzers to simulate the software under test, both in order to validate the analyzers and to clarify requirements. it also discusses practical issues to do with the completeness of the approach, and includes comparisons to other recently-published approaches to log file analysis.
design pattern rationale graphs: linking design to source. a developer attempting to evolve a system in which design patterns have been applied can benefit from knowing which code implements which design pattern. for instance, the developer may be able to understand the purpose, or to assess the flexibility of the code, more quickly. the degree to which the developer benefits depends upon their understanding of the pattern. achieving an in-depth understanding of even a simple pattern can be difficult as pattern descriptions span several pages of text, and discuss interrelated design concepts and choices. to enable a developer to effectively trace the design goals associated with a pattern to and from source, we have developed the design pattern rationale graph (dprg) approach and associated tool. a dprg makes explicit the relationships between design concepts in a design pattern, provides a graphical representation of the design pattern text, and supports the linking of those concepts to implementing code. in this paper, we introduce the dprg approach and tool, and present case studies to show that a dprg can, at low-cost, help a developer identify design goals in a pattern, and can improve a developer's confidence about how those goals are realized in a code base.
extracting concepts from file names: a new file clustering criterion. decomposing complex software systems into conceptually independent subsystems is a significant software engineering activity which received considerable research attention. most of the research in this domain considers the body of the source code; trying to cluster together files which are conceptually related. we discuss techniques for extracting concepts (abbreviations) from a more informal source of information: file names. the task is difficult because nothing indicates where to split the file names into substrings. in general, finding abbreviations would require domain knowledge to identify the concepts that are referred to in a name and intuition to recognize such concepts in abbreviated forms. we show by experiment that the techniques we propose allow about 90% of the abbreviations to be found automatically
programming at the processor-memory-switch level. users of networks of heterogeneous processors are concerned with allocating specialized resources to tasks of medium to large size. they need to create processes, which are instances of tasks, allocate these processes to processors, and specify the communication patterns between processes. these activities constitute processor-memory-switch (pms) level programming, in contrast with traditional programming activities, which take place at the instruction set processor (isp) level. in this paper we describe the use of pms-level programming in computation-intensive, real-time applications, e.g., vision, robotics, and vehicular control, that require efficient concurrent execution of multiple tasks, e.g., sensor data collection, obstacle recognition, and global path planning, devoted to specific pieces of the application. at cmu we are developing languages and tools for this new style of programming, and in this paper we describe their status.
functional paleontology: system evolution as the user sees it. it has long been accepted that requirements analysis should precede architectural design and implementation, but in software evolution and reverse engineering this concern with black-box analysis of function has necessarily been de-emphasized in favor of code-based analysis and designer-oriented interpretation. in this paper, we redress this balance by describing &ldquo;functional paleontology&rdquo;, an approach to analyzing the evolution of user-visible features or services independent of architecture and design intent. we classify the benefits and burdens of interpersonal communication services into core and peripheral categories and investigate the telephony services available to domestic subscribers over a fifty-year period. we report that services were introduced in discrete bursts, each of which emphasized different benefits and burdens. we discuss the general patterns of functional evolution that this &ldquo;fossil record&rdquo; illustrates and conclude by discussing their implications for forward engineering of software products.
the use of goals to surface requirements for evolving systems. this paper addresses the use of goals to surface requirements for the redesign of existing or legacy systems. goals are widely recognized as important precursors to system requirements, but the process of identifying and abstracting them has not been researched thoroughly. we present a summary of a goal-based method (gbram) for uncovering hidden issues, goals, and requirements and illustrate its application to a commercial system, an intranet-based electronic commerce application, evaluating the method in the process. the core techniques comprising gbram are the systematic application of heuristics and inquiry questions for the analysis of goals, scenarios and obstacles. we conclude by discussing the lessons learned through applying goal refinement in the field and the implications for future research
who should fix this bug? open source development projects typically support an open bug repository to which both developers and users can report bugs. the reports that appear in this repository must be triaged to determine if the report is one which requires attention and if it is, which developer will be assigned the responsibility of resolving the report. large open source developments are burdened by the rate at which new bug reports appear in the bug repository. in this paper, we present a semi-automated approach intended to ease one part of this process, the assignment of reports to a developer. our approach applies a machine learning algorithm to the open bug repository to learn the kinds of reports each developer resolves. when a new report arrives, the classifier produced by the machine learning technique suggests a small number of developers suitable to resolve the report. with this approach, we have reached precision levels of 57% and 64% on the eclipse and firefox development projects respectively. we have also applied our approach to the gcc open source development with less positive results. we describe the conditions under which the approach is applicable and also report on the lessons we learned about applying machine learning to repositories used in open source development.
a case study of the evolution of jun: an object-oriented open-source 3d multimedia library. jun is a large open-source graphics and multimedia library. it is object-oriented and supports 3d geometry, topography and multimedia. this paper reviews the development of the jun library from five perspectives: open-source, software evolution processes, development styles, technological support, and development data. we conclude the paper with lessons learned from the perspective of a for-profit company providing open-source object-oriented software to the community.
tutorial: towards dynamic web services. this tutorial introduces dynamic web services as a solution to cope with the dynamism and flexibility required by many modern software systems. current technologies (wsdl, ws-bpel, etc.) have proven insufficient in addressing these issues; however, they remain a good starting point for the analysis of the current situation and for building for the future.the core part of the tutorial analyzes ---by looking at available technologies and prominent research proposals---the deployment and execution of these applications within three separate phases: a composition phase, to discover available services and implement the desired behavior, a monitoring phase, to understand if a given service is behaving correctly (with respect to both functional and non-functional requirements), and a recovery phase, to react to anomalies by means of suitable replanning or recovery strategies.in conclusion, the tutorial summarizes the main topics, presents a list of still-to-be-solved problems, and highlights possible directions for future research.
agile software process and its experience. this article proposes a new software process model, asp (agile software process) and discusses its experience in large-scale software development. the japanese software factory was a successful model in the development of quality software for large-scale business applications in the 80s. however, the requirements for software development have dramatically changed. development cycle-time has been promoted to one of the top goals of software development in the 90s. unlike conventional software process models based on volume, the asp is a time-based process model which aims at quick delivery of software products by integrating the lightweight processes, modular process structures and incremental and iterative process enaction. the major contributions of aps include: a new process model and its enaction mechanism based on time; a software process model for evolutional delivery; a software process architecture integrating concurrent and asynchronous processes, incremental and iterative process enaction, distributed multi-site processes, and the people-centered processes; a process-centered software engineering environment for asp; and experience and lessons learned from the use of asp in the development of a family of large-scale communication software systems for more than five years
principles of software evolution: 5 international workshop on principles of software evolution (iwpse 2002). we present an overview of the 5th international workshop on principles of software evolution (iwpse 2002).
web services engineering: promises and challenges. web services are emerging technologies to reuse software as services over the internet by wrapping underlying computing models with xml. web services are rapidly evolving and are expected to change the paradigms of both software development and use. this panel will discuss the current status and challenges of web services technologies.
software engineering challenges in bioinformatics. data from biological research is proliferating rapidlyand advanced data storage and analysis methods are requiredto manage it. we introduce the main sources of biologicaldata available and outline some of the domainspecific problems associated with automated analysis. we discuss two major areas in which we are likely experiencesoftware engineering challenges over the next ten years:data integration and presentation.
aspectual mixin layers: aspects and features in concert. feature-oriented programming (fop) decomposes complex software into features. features are main abstractions in design and implementation. they reflect user requirements and incrementally refine one another. although, features crosscut object-oriented architectures they fail to express all kinds of crosscutting concerns. this weakness is exactly the strength of aspects, the main abstraction mechanism of aspect-oriented programming (aop). in this article we contribute a systematic evaluation and comparison of both paradigms, aop and fop, with focus on incremental software development. it reveals that aspects and features are not competing concepts. in fact aop has several strengths to improve fop in order to implement crosscutting featuressymmetrically, the development model of fop can aid aop in implementing incremental designs. consequently, we propose the architectural integration of aspects and features in order to profit from both paradigms. we introduce aspectual mixin layers (amls), an implementation approach that realizes this symbiosis. a subsequent evaluation and a case study reveal that amls improve the crosscutting modularity of features as well as aspects become well integrated into incremental development style.
a framework for evaluating specification methods for reactive systems: experience report. numerous formal specification methods for reactive systems have been proposed in the literature. because the significant differences between the methods are hard to determine, choosing the best method for a particular application can be difficult. we have applied several different methods, including modechart, vfsm, esterel, basic lotos, z, sdl, and c, to an application problem encountered in the design of software for at&t's 5ess¯ telephone switching system. we have developed a set of criteria for evaluating and comparing the different specification methods. we argue that the evaluation of a method must take into account not only academic concerns, but also the maturity of the method, its compatibility with the existing software development process and system execution environment, and its suitability for the chosen application domain.
supporting the deployment of object-oriented frameworks. frameworks [4] are usually large and complex, and typically reusers need to understand them well enough to effectively use them. this research concentrates on verifying applications built on top of oo frameworks. the idea is to get framework builders to specify a set of constraints for the correct usage of the framework and check them using static analysis techniques.
efficient and precise dynamic impact analysis using execute-after sequences. as software evolves, impact analysis estimates the potential effects of changes, before or after they are made, by identifying which parts of the software may be affected by such changes. traditional impact-analysis techniques are based on static analysis and, due to their conservative assumptions, tend to identify most of the software as affected by the changes. more recently, researchers have begun to investigate dynamic impact-analysis techniques, which rely on dynamic, rather than static, information about software behavior. existing dynamic impact-analysis techniques are either very expensive---in terms of execution overhead or amount of dynamic information collected---or imprecise. in this paper, we present a new technique for dynamic impact analysis that is almost as efficient as the most efficient existing technique and is as precise as the most precise existing technique. the technique is based on a novel algorithm that collects (and analyzes) only the essential dynamic information required for the analysis. we discuss our technique, prove its correctness, and present a set of empirical studies in which we compare our new technique with two existing techniques, in terms of performance and precision.
on the uniformity of software evolution patterns. preparations for y2k reminded the software engineering community of the extent to which long-lived software systems are embedded in our daily environments. as systems are maintained and enhanced throughout their lifecycles they appear to follow generalized behaviors described by the laws of software evolution. within this context, however, there is some question of how and why systems may evolve differently. the objective of this work is to answer the question: do systems follow a set of identifiable evolutionary patterns? in this paper we use software volatility to describe the lifecycle evolution of a portfolio of 23 software systems. we show by example that a vector of software volatility levels can represent lifecycle behavior of a software system. we further demonstrate that the portfolio ' s 23 software volatility vectors can be grouped into four distinguishable patterns. thus, we show by example that there are different patterns of system lifecycle behavior, i.e. software evolution.
artificial intelligence and software engineering. software engineering is a knowledge-intensive activity, requiring extensive knowledge of the application domain and of the target software itself. many software engineering costs can be attributed to the ineffectiveness of current techniques for managing this knowledge, and artificial intelligence techniques can help alleviate this situation. more than two decades of research have led to many significant theoretical results, but few demonstrations of practical utility. this is due in part to the amount and diversity of knowledge required by software engineering activities, and in part to the fact that much of the research has been narrowly focused, missing many issues that are of great practical importance. important issues that remain to be addressed include the representation and use of domain knowledge and the representation of the design and implementation history of a software system. if solutions to these issues are found, and experiments in practical situations are successful, the implications for the practice of software engineering will be profound, and radically different software development paradigms will become possible.
a process for consolidating and reusing design knowledge. significant improvements in design quality and productivity are possible when designers operate in a domain-specific information workspace with low-cost access to relevant application, design, and technology information. the authors present a validated process for constructing such workspaces to support product family design and evolution. the process involves three related efforts: techniques to consolidate critical analysis and design information from different projects and different engineering sites called domain analysis; online representation of the information in structured form called technology books; and methods and tools to reuse information. each area is described, with the focus being on technology books. technology books are object-oriented databases whose objects capture typed information about analyses, designs, and code in a variety of notations. relations with well-defined semantics link objects; these can be used to navigate through the technology book, and to reason about the information it contains
process engineering with spearmint/epg. this paper presents the spearmint process modeling tool and the electronic process guide (epg) generator. together they enable process engineers to elicit, model, analyze and document software processes and then to automatically generate web-based guidebooks based on the documented processes.
automatic programming for streams ii: transformational implementation. &phgr;nix is an automatic programming system, now under development, for writing programs which interact with external devices through temporally-ordered streams of values. abstract specifications are stated in terms of constraints on the values of input and output streams. the target language is the stream machine, a language which includes concurrently executing processes communicating and synchronizing through streams. &phgr;nix produces programs by repeatedly transforming abstract specifications through successively more concrete forms until concrete stream machine programs are produced. an example which &phgr;nix has successfully implemented involves three major steps: transforming the specification into an applicative expression, transforming the applicative expression into three imperative processes, and merging the processes into a single process. each major step involves several other transformation steps that reformulate and simplify intermediate expressions.
understanding and predicting the process of software maintenance release. one of the major concerns of any maintenance organization is to understand and estimate the cost of maintenance releases of software systems. planning the next release so as to maximize the increase in functionality and the improvement in quality are vital to successful maintenance management. the objective of the paper is to present the results of a case study in which an incremental approach was used to better understand the effort distribution of releases and build a predictive effort model for software maintenance releases. the study was conducted in the flight dynamics division (fdd) of nasa goddard space flight center (gsfc). the paper presents three main results: (1) a predictive effort model developed for the fdd's software maintenance release process, (2) measurement-based lessons learned about the maintenance process in the fdd, (3) a set of lessons learned about the establishment of a measurement-based software maintenance improvement program. in addition, this study provides insights and guidelines for obtaining similar results in other maintenance organizations.
empirically driven se research: state of the art and required maturity. software engineering researchers are increasingly relying on the empirical approach to advance the state of the art. the level of empirical rigor and evidence required to guide software engineering research, however, can vary drastically depending on many factors. in this session we identify some of these factors through a discussion of the state of the art in performing empirical studies in software engineering, and we show how we can utilize the notion of empirical maturity to set and adjust the empirical expectations for software engineering research efforts.regarding the state of the art in performing empirical studies, we will offer perspectives on two classes of study: those concerned with humans utilizing a technology, e.g., a person applying a methodology, a technique, or a tool, where human skills and the ability to interact with the technology are some of the primes issues, and those concerned with the application of the technology to an artifact, e.g., a technique or tool applied to a design or a program. in the first case, the emphasis is typically on issues like feasibility, usefulness, and then on effectiveness. the technology tends to be less well specified and based more on the experience and skills of the technology applier. in the second case, the emphasis is typically on the efficiency and effectiveness of the technology. the technology tends to be well defined and the assumption is that the individual skill and experience plays a less important role. we will discuss the set of factors that influence the design, implementation, and validity of these studies.regarding empirical maturity and its implications on the se community's expectations, we will provide examples of the large spectrum of studies with different maturity levels that can be performed to successfully support software engineering research. we will then identify and analyze the following aspects that are likely to impact a study's maturity level: technology (well-specified vs. under development), goals of the study (effectiveness vs. feasibility), type of design and analysis (controlled experiment vs. case study, quantitative vs. qualitative), control and specification of threats to validity (internal vs. external threats), dependence on context (in vivo vs. in vitro), relationship to previous empirical work (replicated on-site, replicated off-site, non-replicated, non-replicable), and purposes of the study (exploratory vs. confirmatory). we will lead a discussion on these key aspects that must be considered to assess the empirical maturity of a piece of work in the context of its research area and the empirical maturity of that area.
lessons learned from 25 years of process improvement: the rise and fall of the nasa software engineering laboratory. for 25 years the nasa/gsfc software engineering laboratory (sel) has been a major resource in software process improvement activities. but due to a changing climate at nasa, agency reorganization, and budget cuts, the sel has lost much of its impact. in this paper we describe the history of the sel and give some lessons learned on what we did right, what we did wrong, and what others can learn from our experiences. we briefly describe the research that was conducted by the sel, describe how we evolved our understanding of software process improvement, and provide a set of lessons learned and hypotheses that should enable future groups to learn from and improve on our quarter century of experiences.
tailoring the software process to project goals and environments. this paper presents a methodology for improving the software process by tailoring it to the specific project goals and environment. this improvement process is aimed at the global software process model as well as methods and tools supporting that model. the basic idea is to use defect profiles to help characterize the environment and evaluate the project goals and the effectiveness of methods and tools in a quantitative way. the improvement process is implemented iteratively by setting project improvement goals, characterizing those goals and the environment, in part, via defect profiles in a quantitative way, choosing methods and tools fitting those characteristics, evaluating the actual behavior of the chosen set of methods and tools, and refining the project goals based on the evaluation results. all these activities require analysis of large amounts of data and, therefore, support by an automated tool. such a tool &mdash; tame (tailoring a measurement environment) &mdash; is currently being developed.
analyzing medium-scale software development. the collection and analysis of data from programming projects is necessary for the appropriate evaluation of software engineering methodologies. towards this end, the software engineering laboratory was organized between the university of maryland and nasa goddard space flight center. this paper describes the structure of the laboratory and provides some data on project evaluation from some of the early projects that have been monitored. the analysis relates to resource forecasting using a model of the project life cycle based upon the rayleigh equation and to error rates applying ideas developed by belady and lehman.
evaluation of a software requirements document by analysis of change data. we describe in this paper an effective data collection method for evaluating software development methodologies, from definition of the objectives of the data collection to analysis of the results. we show how the data analysis can answer questions with respect to how successfully the goals of the development methodology are met. the a-7 requirements document is used as an example. we provide the results of data analyses conducted partway through the a-7 flight software development cycle, and discuss the utility of information obtained by such partial analyses. results from the study show that data collection is feasible and useful when performed as part of configuration control, that data distributions based on partial data provide useful feedback to the developers, and that the a-7 requirements document is easily maintained and changed.
beyond templates: a study of clones in the stl and some general implications. templates (or generics) help us write compact, generic code, which aids both reuse and maintenance. the stl is a powerful example of how templates help achieve these goals. still, our study of the stl revealed substantial, and in our opinion, counter-productive repetitions (so-called clones) across groups of similar class or function templates. clones occurred, as variations across these similar program structures were irregular and could not be unified by suitable template parameters in a natural way. we encountered similar problems in other class libraries as well as in application programs, written in a range of programming languages. in the paper, we present quantitative and qualitative results from our study. we argue that the difficulties we encountered affect programs in general. we present a solution that can treat such template-unfriendly cases of redundancies at the meta-level, complementing and extending the power of language features, such as templates, in areas of generic programming.
prestige: a case workbench for the jsd implementor. the authors provide an overview of prestige, a case toolkit which supports the implementation phase of jackson system development (jsd). the authors present an outline of jsd, a brief discussion on operational specifications, and a description of the two-stage model of jsd implementation which forms the basis of the toolkit's functionality. the toolkit's current capabilities are described and illustrated through simple examples. finally, the authors indicate directions for further work
usability-supporting architectural patterns. software architects have techniques to deal with manyquality attributes such as performance, reliability, andmaintainability. usability, however, has traditionallybeen concerned primarily with presentation and notbeen a concern of software architects beyondseparating the user interface from the remainder of theapplication.in this tutorial, we present usability-supportingarchitectural patterns. each pattern describes ausability concern that is not supported by separationalone. for each concern, a usability-supportingarchitectural pattern provides the forces from thecharacteristics of the task and environment, thehuman, and the state of the software to motivate animplementation independent solution cast in terms ofthe responsibilities that must be fulfilled to satisfy theforces. furthermore, each pattern includes a samplesolution implemented in the context of an overridingseparation based pattern such as j2ee model viewcontroller.
experimental evaluation of a fuzzy-set based measure of software correctness using program mutation. experimental evaluation of software reliability models that depend on the source code of the target program is expensive due to the need for a large sample of programs. the authors have used program mutation to generate many versions of one of the more complex components comprising a hypothetical but realistic nuclear reactor safety control program. trivial mutants were filtered by using branch and path testing. these programs were used to assess a fuzzy set based measure of program correctness. the results confirmed that the model is conservative. in addition, the experiments provided new insights into the model, including reassessment of its assumptions and directions for refining it
some classes of naturally provable programs. three different classes of programs are identified for which the proof of correctness is shown to be &ldquo;natural&rdquo;, in that the functional input-output specifications of the programs lead, in a straightforward manner, to the verification conditions that should be proven. furthermore, these verification conditions are shown to be necessary and sufficient so that a proof/refutation follows by proving/disproving the corresponding verification conditions. it is not necessary to follow the exact control flow of the programs to generate these conditions; certain simple checks are enough to show whether a particular program belongs to one of the classes. these apparently different programs have the common feature that they operate &ldquo;uniformly&rdquo; on the data domain; changing the input to the program changes the dynamic behavior of the program in a predictable, easily definable fashion. implications of this feature in program construction are discussed.
product-line architectures, aspects, and reuse (tutorial session). genvoca pla designs have been created for diverse domains: 2-way radios, extensible compilers, communication protocols, command-and-control fire support, avionics, and matrix computation libraries [7]. genvoca designs are used in industry; its central concepts relate a wide variety of contemporary and classical research topics, including: aspect-oriented programming, parameterized programming, oo frameworks, perry's lite semantics [8], generative programming [7], design maintenance [9], and layered software.
a tutorial on feature oriented programming and product-lines. feature oriented programming (fop) is a design methodology and tools for program synthesis. the goal is to specify a target program in terms of the features that it offers, and to synthesize an efficient program that meets these specifications. fop has been used to develop product-lines in disparate domains, including compilers for extensible java dialects [3], fire support simulators for the u.s. army [5], high-performance network protocols [1], and program verification tools [14].
feature-oriented programming and the ahead tool suite. feature oriented programming (fop) is an emerging paradigmfor application synthesis, analysis, and optimization. atarget application is specified declaratively as a set of features,like many consumer products (e.g., personal computers,automobiles). fop technology translates suchdeclarative specifications into efficient programs.
scaling step-wise refinement. step-wise refinement is a powerful paradigm for developing a complex program from a simple program by adding features incrementally. we present the ahead (algebraic hierarchical equations for application design) model that shows how step-wise refinement scales to synthesize multiple programs and multiple non-code representations. ahead shows that software can have an elegant, hierarchical mathematical structure that is expressible as nested sets of equations. we review a tool set that supports ahead. as a demonstration of its viability, we have bootstrapped ahead tools solely from equational specifications, generating java and non-java artifacts automatically, a task that was accomplished only by ad hoc means previously.
improving test suites for efficient fault localization. the need for testing-for-diagnosis strategies has been identified for a long time, but the explicit link from testing to diagnosis (fault localization) is rare. analyzing the type of information needed for efficient fault localization, we identify the attribute (called dynamic basic block) that restricts the accuracy of a diagnosis algorithm. based on this attribute, a test-for-diagnosis criterion is proposed and validated through rigorous case studies: it shows that a test suite can be improved to reach a high level of diagnosis accuracy. so, the dilemma between a reduced testing effort (with as few test cases as possible) and the diagnosis accuracy (that needs as much test cases as possible to get more information) is partly solved by selecting test cases that are dedicated to diagnosis.
programming as an evolutionary process. programming is studied as an evolutionary process (starting with the problem description and ending with some computer program), which is done in a sequence of transformation steps. nature of these steps at several levels is illustrated by typical examples. the aim is to arrive at a computer-surveyed, intuition-controlled programming support system (cips). some aspects of this project, which is under way at the technical university of munich informatics institute, are discussed.
from specifications to machine code: program construction through formal reasoning. due to modern technology, software will to an increasing extent be frozen into hardware. this is just one example for situations where bugs in the software are absolutely intolerable. therefore programming must soon become a safe process of program construction; that is, it has to be organized as a sequence of steps of rational reasoning. starting from an elaborate formal problem specification using elements of predicate logic, set theory and primitives from some algebras, the application of formal rules leads to algorithmic versions and finally to programs oriented towards the instruction repertoire of particular concrete machines. a genuine program construction process needs strict formalization throughout. all versions including the specifications can conveniently be represented by one programming language comprising the complete spectrum of descriptive, applicative and procedural styles. such a language includes the concept of nondeterminism, which makes the development process transparent and extremely flexible, and it is to be interpreted by some model of the underlying abstract data types. the use of formally proved transformation rules guarantees this correctness. in addition, the transformational approach is universal in the sense that the collection of rules can be adapted to the application in question: although initially envisaged and mainly used now for the construction of software for classical sequential stored-program machines, the approach can be extended to other computational models corresponding to the often cited innovative hardware architectures.
test plan generation using formal grammars. a test plan generation algorithm is proposed for systems such as process-control systems or transaction-processing systems. input to the algorithm is a description of the functional requirements for a given system. this is converted to an augmented finite state automaton (fsa) from which a regular grammar is derived. the grammar is used to generate test &ldquo;sentences&rdquo; each of which describes a sequence of stimuli to be applied to the system under test and responses required of the system under test.
using transformation systems for software maintenance and reengineering. software maintenance costs dominate software engineering costs, partly because most such engineering is done manually. program transformation tools leverage an engineer-provided base of &ldquo;transforms&rdquo; (a kind of generative reuse of programming knowledge), to automate analysis, modification, and generation of software, enhancing productivity and quality over conventional methods. this tutorial provides a complete overview of program transformation, from theory to implementation to application. several real transformation systems will be examined, with application examples including automated detection and removal of duplicate code from large systems, and the potential for semi-automated refactoring of large object frameworks. the tutorial progresses from introductory to intermediate, but all the necessary background will be provided, so attendees need only basic software engineering knowledge and motivating experience modifying software.
dms®: program transformations for practical scalable software evolution. while a number of research systems have demonstratedthe potential value of program transformations, very few ofthese systems have made it into practice. the core technologyfor such systems is well understood; what remains isintegration and more importantly, the problem of handlingthe scale of the applications to be processed.this paper describes dms, a practical, commercialprogram analysis and transformation system, and sketchesa variety of tasks to which it has been applied, from redocumentingto large-scale system migration. its successderives partly from a vision of design maintenance and theconstruction of infrastructure that appears necessary tosupport that vision. dms handles program scale by carefulspace management, computational scale via parallelismand knowledge acquisition scale via domains.
quantifying software designs. this paper describes an effort to use metrics to evaluate software designs early in the design process. key facets of the work include a machine processable design notation and the definition of software design metrics. we believe that the future success of building an intelligent software design assistant depends on the ability to quantify attributes of a software design, as well as to have the representation of the design available for automated examination.
program and interface slicing for reverse engineering. reverse engineering involves a great deal of effort in comprehension of the current implementation of a software system and the ways in which it differs from the original design. automated support tools are critical to the success of such efforts. it is shown how program slicing techniques can be employed to assist in the comprehension of large software systems, through traditional slicing techniques at the statement level, and through a new technique, interface slicing, at the module level
traits: tools and methodology. traits are an object-oriented programming language constructthat allow groups of methods to be named and reusedin arbitrary places in an inheritance hierarchy. classes canuse methods from traits as well as defining their own methodsand instance variables. traits thus enable a new styleof programming, in which traits rather than classes are theprimary unit of reuse. however, the additional sub-structureprovided by traits is always optional: a class written usingtraits can also be viewed as a flat collection of methods,with no change in its semantics.this paper describes the tool that supports these two alternateviews of a class, called the traits browser, and theprogramming methodology that we are starting to developaround the use of traits.
symbolic invariant verification for systems with dynamic structural adaptation. the next generation of networked mechatronic systems will be characterized by complex coordination and structural adaptation at run-time. crucial safety properties have to be guaranteed for all potential structural configurations. testing cannot provide safety guarantees, while current model checking and theorem proving techniques do not scale for such systems. we present a verification technique for arbitrarily large multi-agent systems from the mechatronic domain, featuring complex coordination and structural adaptation. we overcome the limitations of existing techniques by exploiting the local character of structural safety properties. the system state is modeled as a graph, system transitions are modeled as rule applications in a graph transformation system, and safety properties of the system are encoded as inductive invariants (permitting the verification of infinite state systems). we developed a symbolic verification procedure that allows us to perform the computation on an efficient bdd-based graph manipulation engine, and we report performance results for several examples.
a robust b-tree implementation. a storage structure for b-trees is presented which is robust in that any pair of changes to structural fields of an instance of the structure can be detected, as well as many sets of larger numbers of changes. included in the paper are a motivation for robustness as a design criterion, cost and performance implications of the b-tree implementation, and a solution to the subproblem of a robust implementation for each node's contiguous list of pointers and keys.
a case study on the automated verification of groupware protocols. we report on a fruitful combination of applying academic experience with formal modelling and verification techniques to an industrial case study. the goal of the case study was to investigate a priori, i.e. before implementation, the effects of adding a lightweight and easy-to-use publish/subscribe (event) notification service to thinkteam--an asynchronous and dispersed groupware system which was developed by think3. researchers from the formal methods and tools (fm&t) group of isti-cnr--with a longstanding experience in research on the development and application of formal methods, notations, and software tools for the specification, design, and verification of complex computer systems--therefore teamed up with think3--a global provider of integrated product development solutions that provides mechanical design and product data management (pdm) software catering the product management needs of design processes in the manufacturing industry. the technical details of this joint research effort have been documented elsewhere, here we report on the lessons learned from this experience.
oil and water? high performance garbage collection in java with mmtk. increasingly popular languages such as java and c# requireefficient garbage collection. this paper presents thedesign, implementation, and evaluation of mmtk, a memorymanagement toolkit for and in java. mmtk is an efficient, composable, extensible, and portable framework for building garbage collectors. mmtk uses design patternsand compiler cooperation to combine modularity and efficiency. the resulting system is more robust, easier to maintain, and has fewer defects than monolithic collectors. experimentalcomparisons with monolithic java and c implementationsreveal mmtk has significant performance advantagesas well. performance critical system software typicallyuses monolithic c at the expense of flexibility. our resultsrefute common wisdom that only this approach attainsefficiency, and suggest that performance critical softwarecan embrace modular design and high-level languages.
do students recognize ambiguity in software design? a multi-national, multi-institutional report. successful software engineering requires experience and acknowledgment of complexity, including that which leads designers to recognize ambiguity within the software design description itself. we report on a study of 21 post-secondary institutions from the usa, uk, sweden, and new zealand. first competency and graduating students as well as educators were asked to perform a software design task. we found that as students go from first competency to graduating seniors they tend to recognize ambiguities in under-specified problems. additionally, participants who recognized ambiguity addressed more requirements of the design.
central flow control software development: a case study of the effectiveness of software engineering techniques. the purpose of this paper is to present cost and error data collected during the development cycle of a large-scale software effort, to analyze this data in comparison with other available data from similar projects, and to evaluate the effectiveness of the techniques utilized on the project. the project being reported on is computer sciences corporation's development of the central flow control software system for the federal aviation administration's air traffic control system command center. analysis of the cost data provides insight not only into the added development costs associated with severely limiting module sizes, but also into the effectiveness of various cost estimation techniques. the error data analysis supports the usefulness of the software engineering techniques which were used on the project in conjunction with definitive module-level test requirements. the paper provides a foundation upon which to establish the development and data collection environment for future software systems.
observing timed systems by means of message sequence chart graphs. tools that feature msc do not have the ability to check model or implementation executions against the specified behavior.in this paper, we present a method for observing the behavior of timed systems specified using message sequence chart graphs (msc-graphs) (a simplified version of itu z.120 notation [5]).we believe that a log-analyzer and a run-time monitor based on msc-graphs are practical and powerful tools to improve the quality of real-time systems. on one hand, the log analyzer can play the role of an oracle while testing non-functional requirements. on the other hand, the run-time monitor can help in the verification of protocol assertions given in terms of message interchange annotated with time constraints.the work is built over a formal definition of the syntax and semantics of msc-graphs, which is similar to [1] (i.e. based on partial orders). those msc-graphs are enriched with timers and delay intervals in a similar way to [2] and [3].the work will mainly feature:&bull; an algorithm to check whether a time stamped log conforms a specification given by means of a msc-graph. the msc-graph does not need to be safe realizable [4] or bounded [1] to be treated by our algorithm. the proof of coorectness is given incrementally following a series of is given incrementally following a series of enhancements, starting from a basic algorithm.&bull; software architecture and an implementation for a log analyzer and a monitoring system.integration with existing tools supporting mscs (i.e.: teleogic tau [6], rational rose real tiem [7], rhapsody [8], distributed middlewares, etc.).coverage reporting over msc-graphs.
specifications: a key to effective software development. specifications provide the fundamental link to make the transition between the concept and definition phases of the system development cycle. straightforward, unambiguous specifications are required to ensure successful results and at the same time minimize cost overruns during the development cycle. many of the problems currently being addressed by software engineers have their origins in the frequently inconsistent and incomplete nature of system specifications. the u.s. army ballistic missile defense advanced technology center (bmdatc) is currently studying several advanced software development technologies. bmdatc's efforts are directed toward identifying and resolving the fundamental problems that plague the software community: excessive costs, unrealistic or inappropriate schedules, and inadequate performance. a primary category of the bmdatc program is data processing system engineering research. this research employs an advanced engineering approach to the generation, verification, and unambiguous communication of a complete and consistent set of system requirements. the key elements of this technology are: (1) a mathematically rigorous decomposition technology that effectively translates system requirements into a traceable graphic representation; (2) a usable system specification language (ssl) that supports simulation and specification generation; (3) a set of software tools that aid in the development, verification, and configuration control of the decomposed requirements; and (4) a management approach that supports the designed-in quality of the developed specification. definitive specifications are of primordial importance to the development process in that they are both the springboard for the design process and the yardstick of the test procedures. this paper describes the importance of verifying systems specifications before commencing any software design and delineates a technique for accomplishing this objective.
three paradigms for developing information systems. this paper examines three paradigms for information system development. development here is defined to include all activities associated with the implementation of an information system from initial requirements analysis through operational maintenance. that is, the full life cycle. two of the paradigms reflect common implementation environments. the third suggests an alternate approach.
software requirements: are they really a problem? do requirements arise naturally from an obvious need, or do they come about only through diligent effort&mdash;and even then contain problems? data on two very different types of software requirements were analyzed to determine what kinds of problems occur and whether these problems are important. the results are dramatic: software requirements are important, and their problems are surprisingly similar across projects. new software engineering techniques are clearly needed to improve both the development and statement of requirements.
on the use of formal methods in software development. we propose a total framework for the software development stages of specification (definition), design and coding. this framework is based on three cornerstones: (a) the concept of software development graphs which specify all the stages and steps of development; (b) the use of formal methods, in our case vdm, the vienna software development method, in all stages and steps of development; and (c) the clearly separate r&ocirc;les of theoretical computer scientists, programmers, software engineers, and development managers in all aspects of software development. thus not only programming is formalised (ie. programs considered formal objects), but also development, its engineering and management (ie. the entire programming itself is also considered a formal object about which to reason).
automatic input of flow chart in document image. the technology of document image processing has the possibility of automatic document input. by utilizing it, the flow chart in document image as the alternate expression of fortran source statements is automatically input into the computer. the paper reports the algorithm and the experimental results of field segmentation and classification in document image, the recognition of flow chart including control lines and blocks, and hand-written alpha-numerical characters in the blocks and the explanatory fields, the conversion of flow chart into program functions and the generation of fortran source statements. it showed the possibility that program functions such as initialization, input/output format and branch address were determined by the analysis of flow chart and explanatory description under the writing rule of it and also the restriction that the flow chart should have the good quality in order to recognize the flow and characters and be subject to the writing rule.
fargo: a system for mobile component-based application development. the design of efficient and reliable distributed applications that need to operate over various machines which are networked by wide area and/or low-bandwidth connections, demands new programming abstractions and mechanisms. in particular, the conventional static design-time determination of local-remote relationships between components implies that dynamic environmental changes are hard if not impossible to address without reengineering the application. the fargo system presents a novel programming model that is centered around the concept of "dynamic application layout", which permits the manipulation of component location at runtime, thereby enabling to map dynamically the logical components onto physical hosts. since the emphasis is on components that are part of a larger application (as opposed to "agents" that are often autonomous applications), component mobility preserves the validity of incoming and outgoing component references, in addition to the internal state of the component. thus, fargo inter-component references can dynamically stretch (i.e., become remote) and shrink (become local), unlike traditional references, which are fixed at design time to be either local or remote.
a view of 20th and 21st century software engineering. george santayana's statement, "those who cannot remember the past are condemned to repeat it," is only half true. the past also includes successful histories. if you haven't been made aware of them, you're often condemned not to repeat their successes.in a rapidly expanding field such as software engineering, this happens a lot. extensive studies of many software projects such as the standish reports offer convincing evidence that many projects fail to repeat past successes.this paper tries to identify at least some of the major past software experiences that were well worth repeating, and some that were not. it also tries to identify underlying phenomena influencing the evolution of software engineering practices that have at least helped the author appreciate how our field has gotten to where it has been and where it is.a counterpart santayana-like statement about the past and future might say, "in an era of rapid change, those who repeat the past are condemned to a bleak future." (think about the dinosaurs, and think carefully about software engineering maturity models that emphasize repeatability.)this paper also tries to identify some of the major sources of change that will affect software engineering practices in the next couple of decades, and identifies some strategies for assessing and adapting to these sources of change. it also makes some first steps towards distinguishing relatively timeless software engineering principles that are risky not to repeat, and conditions of change under which aging practices will become increasingly risky to repeat.
a paradigm for decentralized process modeling and its realization in the oz environment. we present a model for decentralized process centered environments (pces), which support concerted efforts among geographically-dispersed teams - each local team with its own autonomous process - and emphasize flexibility in the tradeoff between collaboration vs. autonomy. we consider both decentralized process modeling and decentralized process enaction. we describe a realization in the oz decentralized pce, which employs a rule-based formalism, and also investigate the application to pces based on petri-nets
multi-platform user interface construction: a challenge for software engineering-in-the-small. the popular view of software engineering focuses on managing teams of people to produce large systems. this paper addresses a different angle of software engineering, that of development for re-use and portability. we consider how an essential part of most software products - the user interface - can be successfully engineered so that it can be portable across multiple platforms and on multiple devices. our research has identified the structure of the problem domain, and we have filled in some of the answers. we investigate promising solutions from the model-driven frameworks of the 1990s, to modern xml-based specification notations (views, xul, ximl, xaml), multi-platform toolkits (qt and gtk), and our new work, mirrors which pioneers reflective libraries. the methodology on which views and mirrors is based enables existing gui libraries to be transported to new operating systems. the paper also identifies cross-cutting challenges related to education, standardization and the impact of mobile and tangible devices on the future design of uis. this paper seeks to position user interface construction as an important challenge in software engineering, worthy of ongoing research.
debugging by asking questions about program output. one reason debugging is the most time-consuming part of software development is because developers struggle to map their questions about a program's behavior onto debugging tools' limited support for analyzing code. interrogative debugging is a new debugging paradigm that allows developers to ask questions directly about their programs' output, helping them to more efficiently and accurately determine what parts of the system to understand. an interrogative debugging prototype called the whyline is described, which has been shown to reduce debugging time by a factor of eight. several extensions and generalizations to it are proposed, including plans for evaluating their effectiveness.
software process management: lessons learned from history. regarding history, george santayana once said, &ldquo;those who cannot remember the past are condemned to repeat it.&rdquo;i have always been dissatisfied with that statement. it is too negative. history has positive experiences too. they are the ones we would like both to remember and to repeat.the three papers in this session are strong examples of positive early experiences in large-scale software engineering. the papers are:h.d. benington, &ldquo;production of large computer programs,&rdquo; proceedings, onr symposium, june 1956.w.a. hosier, &ldquo;pitfalls and safeguards in real-time digital systems with emphasis on programming,&rdquo; ire transactions on engineering management, june, 1961.w.w. royce, &ldquo;managing the development of large software systems: concepts and techniques,&rdquo; proceedings, wescon, august 1970.given the short lifespan of the software field, they can certainly be called &ldquo;historic.&rdquo; indeed, since many people date the software engineering field from the nato garmisch conference in 1968, two of them can even be called &ldquo;prehistoric.&rdquo; they are certainly sufficiently old that most people in the software engineering field have not been aware of them. the intent of this session is to remedy this situation by reprinting them in the conference proceedings, and by having the authors (or, in one case, hosier's colleague j.p. haverty) discuss both the lessons from their papers which are still equally valid today, and the new insights and developments which have happened in the interim.
haemo dialysis software architecture design experiences. in this paper we present the experiences and architecture from a research project conducted in cooperation with two industry partners. the goal of the project was to reengineer an existing system for haemo dialysis machines into a domain specific software architecture. our main experiences are (1) architecture design is an iterative and incremental process, (2) software quality requires a context, (3) quality attribute assessment methods are too detailed for use during architectural design, (4) application domain concepts are not the best abstractions, (5) aesthetics guides the architect in finding potential weaknesses in the architecture, (6) it is extremely hard to decide when an architecture design is ready, and (7) documenting software architectures is an important problem. we also present the architecture and design rational to give a basis for our experiences. we evaluated the resulting architecture by implementing a prototype application.
software architectures: critical success factors and cost drivers. some useful perspectives on the potential and the pitfalls of software architecture investments can be gained via analysis of software architecture critical success factors and their associated cost and benefit drivers. basically, the potential of software architecture investments comes from appropriately identifying and exploiting positive cost-benefit relationships. the pitfalls come from neglecting critical success factors or from making unrealistic assumptions about their associated cost drivers. examples from practice of both potential and pitfalls are given in the context of a table which summarizes a framework of software architecture critical success factors and cost drivers being developed at usc
production of large computer programs. the paper is adapted from a presentation at a symposium on advanced programming methods for digital computers sponsored by the navy mathematical computing advisory panel and the office of naval research in june 1956. the author describes the techniques used to produce the programs for the semi-automatic ground environment (sage) system.
software engineering: as it is. this paper presents a view of software engineering as it is in 1979. it discusses current software engineering practice with respect to lessons learned in the past few years, and concludes that the lessons are currently not heeded roughly half of the time. the paper discusses some of the factors which may account for this lag, including rapid technological change, education shortfalls, technology transfer inhibitions, resistance to disciplined methods, inappropriate role models, and a restricted view of software engineering. the paper also updates a 1976 state of the art survey of software engineering technology, including such topics as requirements and specifications, design, programming, verification and validation, maintenance, software psychology, and software economics. it concludes that the field is making solid progress, but that it is growing more complex at a faster rate than we can put it in order.
polymorphism measures for early risk prediction. polymorphism is an essential feature of the object-oriented paradigm. however, polymorphism induces hidden forms of class dependencies, which may impact software quality. in this paper, we define and empirically investigate the quality impact of polymorphism on oo design. we define measures of two main aspects of polymorphic behaviors provided by the c++ language: polymorphism based on compile time linking decisions (overloading functions for example) and polymorphism based on run-time binding decisions (virtual functions for example). then, we validate our measures by evaluating their impact on class fault-proneness, a software quality attribute. the results show that our measures are capturing different dimensions than loc a size measure, as well as they are significant predictors of fault proneness. in fact, we show that they constitute a good complement to the existing oo design measures.
quantitative evaluation of software quality. the study reported in this paper establishes a conceptual framework and some key initial results in the analysis of the characteristics of software quality. its main results and conclusions are: &bull; explicit attention to characteristics of software quality can lead to significant savings in software life-cycle costs. &bull; the current software state-of-the-art imposes specific limitations on our ability to automatically and quantitatively evaluate the quality of software. &bull; a definitive hierarchy of well-defined, well-differentiated characteristics of software quality is developed. its higher-level structure reflects the actual uses to which software quality evaluation would be put; its lower-level characteristics are closely correlated with actual software metric evaluations which can be performed. &bull; a large number of software quality-evaluation metrics have been defined, classified, and evaluated with respect to their potential benefits, quantifiability, and ease of automation. &bull;particular software life-cycle activities have been identified which have significant leverage on software quality. most importantly, we believe that the study reported in this paper provides for the first time a clear, well-defined framework for assessing the often slippery issues associated with software quality, via the consistent and mutually supportive sets of definitions, distinctions, guidelines, and experiences cited. this framework is certainly not complete, but it has been brought to a point sufficient to serve as a viable basis for future refinements and extensions.
spiral development of software-intensive systems of systems. no abstract available
a laboratory for the development and evaluation of bmd software quality enhancement techniques. this paper describes a software quality laboratory which will be used to develop new software quality analysis tools and evaluate their effectiveness. the laboratory will consist of a centralized data base for storing information about programs and a set of analysis routines which can be invoked interactively. a major effort using the laboratory will be the development of an executable assertion language. the laboratory will also be used to perform research in program verification and testing.
software requirements negotiation: some lessons learned. negotiating requirements is one of the first steps in any software system life cycle, but its results have probably the most significant impact on the system's value. however, the processes of requirements negotiation are not well understood. we have had the opportunity to capture and analyze requirements negotiation behavior for groups of projects developing library multimedia archive systems, using an instrumented version of the usc winwin groupware system for requirements negotiation. some of the more illuminating results were: most stakeholder win conditions were noncontroversial (were not involved in issues); negotiation activity varied by stakeholder role; lco package quality (measured by grading criteria) could be predicted by negotiation attributes; and winwin increased cooperativeness, reduced friction, and helped focus on key issues
the evaluation of large, complex uml analysis and design model. this paper describes techniques for analyzing largeuml models. the first part of the paper describesheuristics and processes for creating semantically correctuml analysis and design models. the second part of thepaper briefly describes the internal designadvisorresearch tool that was used to analyze siemens models.the results are presented and some interestingconclusions are drawn.
the trw software productivity system. this paper presents an overview of the trw software productivity system (sps), an integrated software support environment based on the unix operating system, a wide range of trw software tools, and a wideband local network. section 2 summarizes the quantitative and qualitative requirements analysis upon which the system is based. section 3 describes the key architectural features and system components. finally, section 4 discusses our conclusions and experience to date.
metrics for model driven requirements development. the cmmi defines two process areas associated with requirements elicitation: requirements development (rd) and requirements management (reqm). the measurements and analysis process area (ma) requires measurements and quantitative objectives for rd and reqm, but nowhere does it state what those measurements are. furthermore, in order to extract measurements and evaluate them, a process must enable or otherwise support the taking of measurements. it is especially difficult to do this during requirements development, as it is generally viewed as a writing activity that does not lend itself to quantitative measurements. this paper describes a cmmi compliant formal approach to measurement and analysis during a model-driven requirements development process. it presents a set of metrics that were used successfully on several siemens projects, describing team dynamics, project size and staffing, how the metrics were captured and used, and lessons learned.
software component models. component-based development (cbd) is an important emerging topic in software engineering, promising long sought after benefits like increased reuse and reduced time-to-market (and hence software production cost). however, there are at present many obstacles to overcome before cbd can succeed. for one thing, cbd success is predicated on a standardised market place for software components, which does not yet exist. in fact currently cbd even lacks a universally accepted terminology. existing component models adopt different component definitions and composition operators. therefore much research remains to be done. we believe that the starting point for this endeavour should be a thorough study of current component models, identifying their key characteristics and comparing their strengths and weaknesses. a desirable side-effect would be clarifying and unifying the cbd terminology. in this tutorial, we present a clear and concise exposition of all the current major software component models, including a taxonomy. the purpose is to distill and present knowledge of current software component models, as well as to present an analysis of their properties with respect to commonly accepted criteria for cbd. the taxonomy also provides a starting point for a unified terminology.
an experiment in technology transfer: paisley specification of requirements for an undersea lightwave cable system. from may to october 1985 members of the undersea systems laboratory and the computer technology research laboratory of at&t bell laboratories worked together to apply the executable specification language paisley to requirements for the &ldquo;sl&rdquo; communications system. this paper describes our experiences and answers three questions based on the results of the experiment: can sl requirements be specified formally in paisley? can members of the sl project learn to read and write specifications in paisley? how would the use of paisley affect the productivity of the software-development team and the quality of the resulting software?
prototyping vs. specifying: a multi-project experiment. in this experiment, seven software teams developed versions of the same small-size (2000-4000 source instruction) application software product. four teams used the specifying approach. three teams used the prototyping approach. the main results of the experiment were: prototyping yielded products with roughly equivalent performance, but with about 40% less code and 45% less effort. the prototyped products rated somewhat lower on functionality and robustness, but higher on ease of use and ease of learning. specifying produced more coherent designs and software that was easier to integrate. the paper presents the experimental data supporting these and a number of additional conclusions.
educating software engineering students to manage risk. in 1996, usc switched its core two-semester software engineering course from a hypothetical-project, homework-and-exam course based on the bloom taxonomy of educational objectives (knowledge, comprehension, application, analysis, synthesis, evaluation). the revised course is a real-client team-project course based on the cresst model of learning objectives (content understanding, problem solving, collaboration, communication, and self-regulation). we used the cresst cognitive demands analysis to determine the necessary student skills required for software risk management and the other major project activities, and have been refining the approach over the last four years of experience, including revised versions for one-semester undergraduate and graduate project course at columbia. this paper summarizes our experiences in evolving the risk management aspects of the project course. these have helped us mature more general techniques such as risk-driven specifications, domain specific simplifier and complicator lists, and the schedule as an independent variable (ssiv) process model. the largely positive results in terms of review pass/fail rates, client evaluations, product adoption rates, and hiring manager feedback are summarized as well.
about the development of a point of sale system: an experience report. this report comprises some experiences, which were made during the development of a point of sale (pos) system. specific about the project is the fact that it started as an attempt to develop customizable standard software, and then was restructured to deliver a unique project solution. this report details the situation before and after the restructuring, and discusses the experiences made through the ongoing development. these experiences relate mostly to three areas, which are: software project management, prototyping, and testing.
theory-w software project management: a case study. the search for a single unifying principle to guide software project management has been relatively unrewarding to date. most candidate principles are either insufficiently general to apply in many situations, or so general that they provide no useful specific guidance. this paper presents a candidate unifying principle which appears to do somewhat better. reflecting various alphabetical management theories (x, y, z), it is called the theory w approach to software project management. theory w: make everyone a winner the paper explains the theory w principle and its two subsidiary principles: plan the flight and fly the plan; and, identify and manage your risks. to test the practicability of theory w, a case study is presented and analyzed: the attempt to introduce new information systems to a large industrial corporation in an emerging nation. the case may seem unique, yet it is typical. the analysis shows that theory w and its subsidiary principles do an effective job both in explaining why the project encountered problems, and in prescribing ways in which the problems could have been avoided.
observations and lessons learned from automated testing. this report addresses some of our observations made in a dozen of projects in the area of software testing, and more specifically, in automated testing. it documents, analyzes and consolidates what we consider to be of interest to the community. the major findings can be summarized in a number of lessons learned, covering test strategy, testability, daily integration, and best practices.the report starts with a brief description of five sample projects. then, we discuss our observations and experiences and illustrate them with the sample projects. the report concludes with a synopsis of these experiences and with suggestions for future test automation endeavors.
dimensions of software engineering course design. a vast variety of topics relate to the field of software engineering. some universities implement curricula covering all aspects of software engineering. a number of other courses cover detailed aspects, e.g. programming, usability and security issues, analysis, architecture, design, and quality. other universities offer general curricula considering software engineering in few or single course only. in each case, a course set has to be defined which directly relates to a specific student outcome. this work provides a method for categorizing and analyzing a course set within abstract dimensions for course design. we subsequently show the results of applying the dimensions to the course degree scheme in use. the course design dimensions can also be related to the student outcomes defined in se2004 cc section 3.2 [10].
balancing agility and discipline: evaluating and integrating agile and plan-driven methods. rapid change and increasing software criticality drive successful development and acquisition organizations to balance the agility and discipline of their key processes. the emergence of agile methods in the software community is raising the expectations of customers and management, but the methods have shortfalls and their compatibility with traditional plan-driven methods such as those represented by cmmi, iso-15288, and uk-defstan-00-55 is largely unexplored.this tutorial pragmatically examines the aspects of agile and plan-driven methods and provides an approach to balancing through examples and case studies.
database system support for software engineering. the activity of computer-aided software engineering (case) generates much data. although there are few, if any, database system products with features that attend to the requirements of case environments, there is a flurry of research work in the database field to develop technology to meet these requirements. the purpose of this paper is to raise the level of awareness in the software engineering community about this research on database systems for design applications. it describes technical problems and proposed solutions, and provides an extensive bibliography.
second international workshop on from software requirements to architectures (straw?03). the second international workshop on from software requirements to architectures (straw'03) was held in portland, oregon, usa on 9 may 2003 just after the twenty- fifth international conference on software engineering (icse'03). this brief paper outlines the motivation, goals, and organization of the workshop, summarizes the presen- tations, and, along the way, gathers some lessons learned about running a workshop.
4th international workshop on scenarios and state machines: models, algorithms and tools (scesm'05). no abstract available
a scalable formal method for design and automatic checking of user interfaces. the article addresses the formal specification, design and implementation of the behavioral component of graphical user interfaces. the complex sequences of visual events and actions that constitute dialogs are specified by means of modular, communicating grammars called veg (visual event grammars), which extend traditional bnf grammars to make them more convenient to model dialogs.a veg specification is independent of the actual layout of the gui, but it can easily be integrated with various layout design toolkits. moreover, a veg specification may be verified with the model checker spin, in order to test consistency and correctness, to detect deadlocks and unreachable states, and also to generate test cases for validation purposes.efficient code is automatically generated by the veg toolkit, based on compiler technology. realistic applications have been specified, verified and implemented, like a notepad-style editor, a graph construction library and a large real application to medical software. it is also argued that veg can be used to specify and test voice interfaces and multimodal dialogs. the major contribution of our work is blending together a set of features coming from gui design, compilers, software engineering and formal verification. even though we do not claim novelty in each of the techniques adopted for veg, they have been united into a toolkit supporting all gui design phases, that is, specification, design, verification and validation, linking to applications and coding.
on executable models for rule-based prototyping. this paper proposes a particular style of executable specifications as a method for rapid prototyping. using a general state-transition framework, system behavior is specified by pattern-oriented rules containing pre- and post-conditions for each transition. the specification method is introduced by two small examples in which a finite-state machine and database are modeled. the main example is an executable model of a backtracking prolog interpreter, which is specified using five transition rules adapted from the formal-semantic literature. all models in the paper are executable and written in prolog; minimal familiarity with prolog is assumed.
deriving test plans from architectural descriptions. the paper presents an approach for deriving test plans for the conformance testing of a system implementation with respect to the formal description of its software architecture (sa). the sa describes a system in terms of its components and connections, therefore the derived test plans address the integration testing phase. we base our approach on a labelled transition system (lts) modeling the sa dynamics, and on suitable abstractions of it, the abstract labelled transition systems (altss). altss offer specific views of the sa dynamics by concentrating on relevant features and abstracting away from uninteresting ones. alts is a tool we provide to the software architect that lets him/her focus on relevant behavioral patterns and more easily identify those that are meaningful for validation purposes. intuitively, deriving an adequate set of functional test classes means deriving a set of paths appropriately covering the alts. we describe our approach in the scope of a real world case study and discuss in detail all the steps of our methodology, from alts identification to test plan generation
the software engineering impacts of cultural factors on multi-cultural software development teams. this paper is based on our experiences in trying to apply software engineering practices to development projects staffed by developers from three distinct cultures; japan, india, and the united states. the development of commercial software products has always been difficult. the standard balancing act that occurs between features, schedules, and resources is at the core of the difficulty. we found that cultural differences also had a large impact on our software engineering work.much has been written and said about software engineering methods that can be applied to development projects to reduce and control these core difficulties. methods that were thought to be "best practices" turned out to be ineffective or very difficult to implement. our understanding of the possible root causes for these difficulties greatly increased when we began to study some of the cultural dynamics within the team. this paper describes our observations in terms of how these cultural factors impacted the software engineering techniques used on the projects.
an overview of the icse 2000 workshop program. past icse attendees will recognize&mdash;with pleasure, we hope&mdash;workshops that have been successful in previous years. indeed, we have tried to balance the program between workshops based on novel and promising ideas, with those strongly continuing the work started in previous icses. in two cases, the program also includes workshops that already have some tradition, but are associated with icse for the first time: the isaw workshop (4th edition) and the dsv-is workshop (7th edition).advanced summaries of many of the workshops follow this overview. for those of you unable to attend a workshop, we hope that this provides a flavor of the interesting discussions that occurred. for those of you who were able to attend, we hope it serves as a reminder of those discussions.we would like to thank pascale le gall (university of evry, france) and premkumar (prem) devanbu (university of california at davis, usa) for helping us in reviewing submissions and making the program. their contributions have been invaluable!
a framework for component deployment testing. component-based development is the emerging paradigm in software production, though several challenges still slow down its full taking up. in particular, the "component trust problem" refers to how adequate guarantees and documentation about a component' s behaviour can be transferred from the component developer to its potential users. the capability to test a component when deployed within the target application environment can help establish the compliance of a candidate component to the customer's expectations and certainly contributes to "increase trust". to this purpose, we propose the cdt framework for component deployment testing. cdt provides the customer with both a technique to early specify a deployment test suite and an environment for running and reusing the specified tests on any component implementation. the framework can also be used to deliver the component developer's test suite and to later re-execute it. the central feature of cdt is the complete decoupling between the specification of the tests and the component implementation.
software product lines: organizational alternatives. software product lines enjoy increasingly wide adoption in the software industry. most authors focus on the technical and process aspects and assume an organizational model consisting of a domain engineering unit and several application engineering units. in our cooperation with several software development organizations applying software product line principles, we have identified several other organizational models that are employed as well. in this article, we present a number of organizational alternatives, organized around four main models, i.e. development department, business units, domain engineering unit and hierarchical domain engineering units. for each model, its characteristics, applicability and advantages and disadvantages are discussed, as well as an example. based on an analysis of these models, we present three factors that influence the choice of the organizational model, i.e. product-line assets, the responsibility levels and the type of organizational units.
specifying and measuring quality in use (tutorial session). select a product from among alternative products
relational programming with crocopat. many structural analyses of software systems are naturally formalized as relational queries, for example, the detection of design patterns, patterns of problematic design, code clones, dead code, and differences between the as-built and the as-designed architecture. this paper describes crocopat, an application-independent tool for relational programming. through its efficiency and its expressive language, crocopat enables practically important analyses of real-world software systems that are not possible with other graph analysis tools, in particular analyses that involve transitive closures and the detection of patterns in graphs. the language is easy to use, because it is based on the well-known first-order predicate logic. the tool is easy to integrate into other software systems, because it is a small command-line tool that uses a simple text format for input and output of relations.
software variability management. during recent years, the amount of variability that hasto be supported by a software artefact is growingconsiderably and its management is evolving into amajor challenge during development, usage, andevolution of software artefacts. successful managementof variability in software leads to better customizablesoftware products that are in turn likely to result inhigher market success.the aim of this tutorial is to present softwarevariability management both from a ýproblemsý andfrom a ýsolutionsý perspective by discussingexperiences from industrial practice and from appliedresearch in academia. issues that are addressedinclude, but are not limited to, technological, process,and organizational aspects as well as notation,assessment, design, and evolution aspects.
product-line architectures in industry: a case study. in this paper, a case study investigating the experiences from using product-line architectures is presented involving two swedish companies, axis communications ab and securitas larm ab. key persons in these organizations have been interviewed and information has been collected from documents and other sources. the study identified a collection of problems and issues. the identified problems include the amount of required background knowledge, information distribution, the need for multiple versions of assets, dependencies between assets, use of assets in new contexts, documentation, tool support, management support and effort estimation. issues collected from the case study are the questioned necessity of domain engineering units, business units versus development departments, time-to-market versus asset quality and common features versus feature superset. for each problem, a problem description, an example, underlying causes, available solutions and research issues are identified whereas for each issue the advantages and disadvantages of each side are discussed.
post-process feedback with and without attribute focusing: a comparative evaluation. historically, the identification and correction of inadequacies in the process of software production called process feedback has been a difficult, time-consuming, manual exercise. recently, a methodology for process feedback, called attribute focusing, has been developed. the authors compare post-process feedback with and without attribute focusing to determine how the methodology fares against current practice in post-process correction. five project teams analyzed post-process defect data and made recommendations to improve the quality of a large operating systems product. that data was based on a multiple-choice questionnaire that was completed for every defect in a sample of defects that was chosen by each team. subsequently, the same data was reanalyzed using attribute focusing. the comparison suggests attribute focusing can do at least as well or better than current practice in postprocess analysis, while reducing cost of analysis substantially
designing software architectures for usability. usability is increasingly recognized as a quality attribute that one has to design for. the conventional alternative is to measure usability on a finished system and improve it. the disadvantage of this approach is, obviously, that the cost associated with implementing usability improvements in a fully implemented system are typically very high and prohibit improvements with architectural impact. in this tutorial, we present the insights gained, techniques developed and lessons learned in the eu-ist project status (software architectures that supports usability). these include a forward-engineering perspective on usability, a technique for specifying usability requirements, a method for assessing software architectures for usability and, finally, for improving software architectures for usability. the topics are extensively illustrated by examples and experiences from many industrial cases.
a user's viewpoint on the programmer's workbench. the programmer's workbench boasts a broad set of highly useful features aimed at the application program developer. it claims to be a &ldquo;human-end&rdquo; computer providing tools and services to ease the load on the application system designer, programmer, documenter, tester, and delivery personnel. this paper shows the benefits of using the pwb tools, individually and in combination. through specific examples drawn from the history of a software project, evidence is given that the use of the programmer's workbench can be a major contributing factor in the successful development of a software project.
exception handling: formal specification and systematic program construction. we present an algebraic specification language (pluss) and a program construction method. programs are built systematically from an algebraic specification of the data they deal with. the method was tested on a realistic problem (part of a telephone switching system). in these experiments, it turned out that error handling was the difficult part to specify and to program. this paper shows how to cope with this problem at the specification level and during the program development process.
interactive transformation of java programs in eclipse. implementing large and sweeping changes to software source code can be tedious and error-prone. a conceptually simple change may require a significant code editing effort. integrating scriptable source-to-source program transformations into development environments can assist developers with this task. we present a developer-oriented interactive source code transformation tool for java that addresses this need.
investigating the cost-effectiveness of reinspections in software development. software inspection is one of the most effective methods to detect defects. reinspection repeats the inspection process for software products that are suspected to contain a significant number of undetected defects after an initial inspection. as a reinspection is often believed to be less efficient than an inspection an important question is whether a reinspection justifies its cost. in this paper we propose a cost-benefit model for inspection and reinspection. we discuss the impact of cost and benefit parameters on the net gain of a reinspection with empirical data from an experiment in which 31 student teams inspected and reinspected a requirements document. main findings of the experiment are: a) for reinspection benefits and net gain were significantly lower than for the initial inspection. yet, the reinspection yielded a positive net gain for most teams with conservative cost-benefit assumptions. b) both the estimated benefits and number of major defects are key factors for reinspection net gain, which emphasizes the need for appropriate estimation techniques.
evaluating the accuracy of defect estimation models based on inspection data from two inspection cycles. defect content estimation techniques (dcets), based on defect data from inspection, estimate the total number of defects in a document to evaluate the development process. for inspections that yield few data points dcets reportedly underestimate the number of defects. if there is a second inspection cycle, the additional defect data is expected to increase estimation accuracy. in this paper we consider 3 scenarios to combine data sets from the inspection-reinspection process. we evaluate these approaches with data from an experiment in a university environment where 31 teams inspected and reinspected a software requirements document. main findings of the experiment were that reinspection data improved estimation accuracy. with the best combination approach all examined estimators yielded on average estimates within 20% around the true value, all estimates stayed within 40% around the true value.
lutess: a specification-driven testing environment for synchronous software. several studies have shown that automated testing is a promising approach to save significant amounts of time and money in the industry of reactive software. but automated testing requires a formal framework and adequate means to generate test data. in the context of synchronous reactive software, we have built such a framework and its associated tool-lutess-to integrate various well-founded testing techniques. this tool automatically constructs test harnesses for fully automated test data generation and verdict return. the generation conforms to different formal descriptions: software environment constraints, functional and safety-oriented properties to be satisfied by the software, software operational profiles and software behavior patterns. these descriptions are expressed in an extended executable temporal logic. they correspond to more and more complex test objectives raised by the first pre-industrial applications of lutess. this paper concentrates on the latest development of the tool and its use in the validation of standard feature specifications in telephone systems. the four testing techniques which are coordinated in lutess uniform framework are shown to be well-suited to efficient software testing. the lessons learnt from the use of lutess in the context of industrial partnerships are discussed.
linux as a case study: its extracted software architecture. many software systems do not have a documented system architecture. these are often large, complex systems that are difficult to understand and maintain. one approach to recovering the understanding of a system is to extract architectural documentation from the system implementation. to evaluate the effectiveness of this approach, we extracted architectural documentation from the linux/sup tm/ kernel. the linux kernel is a good candidate for a case study because it is a large (800 kloc) system that is in widespread use and it is representative of many existing systems. our study resulted in documentation that is useful for understanding the linux system structure. also, we learned several useful lessons about extracting a system's architecture.
assessing undergraduate experience of continuous integration and test-driven development. a number of agile practices are included in software engineering curricula, including test-driven development. continuous integration often is not included, despite it becoming increasingly common in industry to code, test, and integrate at the same time. this paper describes a study whereby software engineering undergraduates were given a short intensive experience of test-driven development with continuous integration using an environment that imitated a typical industrial circumstance. assessment was made of students' agile experience rather than of project deliverables, using a novel set of process measures that examined students' participation and performance in agile testing. results showed good participation by student pairs, and clear understanding of agile processes and configuration management. future work will investigate automation of the assessment of continuous integration and configuration management server data.
reuse technologies and their niches. this article characterizes various categories of reuse technologies in terms of their underlying architectures, the kinds of problems that they handle well, and the kinds of problems that they do not handle well. it describes their operational envelopes and niches. the emphasis is on generative reuse technologies.
a series of development methodologies for a variety of systems in korea. to meet the development condition of inside of the country, domestic development methodologies are made with the abbreviation of marmi (magic and robust methodology integrated) in a series of methodologies in south korea. the marmi have the four different methodologies for developing information, object-oriented, component-based, embedded systems. in this paper, the authors describe the feature and structure of each methodology and show our movement for the methodology transfer.
extending the potts and bruns model for recording design rationale. an extension of the model proposed by c. potts and g. bruns (1988) for recording design rationale is presented. the extension consists of enriching the internal structure of justification in the potts and bruns model by making explicit the goals presupposed by arguments, the relations among arguments, and the first-class nature of these relations. the author describes the potts and bruns model briefly. a language whose underlying model extends the potts and bruns model and a system that supports the use of this language are presented. related studies on recording design rationale are briefly discussed. the limitations of the language presented are discussed as further research problems
table: object oriented editing of complex structures. this research adopts the point of view that much of software development is a process of editing complex structures, structures that represent a tightly coupled integration of textual and graphical material. in the context of text and table objects, this research explores a smalltalk-like, object oriented architecture for editors of such complex structures. based on this experience, we propose certain design and operation principles for such editors.
the role of software in successful computer applications. this paper discusses the steps that are required to produce computer programs that satisfactorily implement a computer application. it is a major contention that those steps impacted by structured programming are not the most critical to the development of a successful computer application. successful computer applications depend more heavily on the statement of the problem, the conceptual solution, and software specification. ample precedents for approaches to these more crucial steps can be found in good engineering practice and applied science. heavy emphasis is placed on the purpose and use of software specifications.
platform-independent and tool-neutral test descriptions for automated software testing. current automatic test execution techniques are sensitive to changes in program implementation. moreover, different test descriptions are required by different testing tools. as a result, it is difficult to maintain or port test descriptions. to address this problem, we developed testtalk, a comprehensive testing language. testtalk test descriptions are platform-independent and tool-neutral. the same software test in testtalk can be automatically executed by different testing tools on different platforms. the goal of testtalk is to make software test descriptions, which represent a significant portion of a software project, last as long as the software project.
the concept assignment problem in program understanding. the problem of discovering individual human oriented concepts and assigning them to their implementation-oriented counterparts for a given program is the concept assignment problem. it is argued that the solution to this problem requires methods that have a strong plausible reasoning component. these ideas are illustrated through recovery system called desire. desire is evaluated based on its use on real-world problems over the years
introduction to the wellmade design methodology. an overview of a design methodology called wellmade is presented. wellmade is a synthesis of results obtained from recent research on software engineering and the experience gained at his/phoenix. the principles, procedures, and notation of wellmade are briefly outlined and an example is presented, illustrating the approach for deriving correct programs and the notation for its design specification.
a data structure and drive mechanism for a table-driven simulation system employing multilevel structural representations of digital systems. this paper describes the design and development of a very large fortran simulation program. this discussion includes; the data structure, drive mechanism, and event scheduling for a time-based digital simulation system that could handle functional level models of logical devices. five different types of functional modules are likely to be specified: a) combinational, b) ripple-effect arithmetic, c) register, d) memories, and e) basic logical devices. currently implemented modules include decoders, encoders, universal shift registers, up-down counters, random-access memories, and ripple-carry adders. additional functional modules could be added and basic gates can be intermixed with the functions.
programming cost estimate: is it reasonable? a basic concern when considering a programming cost estimate is its reasonableness. a statistical examination of over thirty completed products was conducted, using least square error methods, to develop an improved method for establishing a central value and an acceptable range of values for programming product cost estimates. eight variables associated with the coding process, such as the number of lines of new and modified basic assembler language and number of new modules, were found to be useful in developing reasonableness equations. using regression equations developed from the variables, we developed reasonableness tests that compare the estimate prepared by the developer to the actual development effort applied to previous products. insight also was gained about programmer productivity, the quality of code estimations, and the optimum number of lines of code per module. estimates are usually based on the experience of the past. but whatever method is used, the main consideration is the error of estimate associated with that method. the basic question about any estimate is: how good is it? the current state of the art of the cost estimating of software projects evolved from the works of walverton1 attempting to correlate the size of effort in person-months with the size of the product expressed in thousand lines of source code (kloc). large dispersion of data forced walston and felix2 to take into account additional variables such as programmer experience and the complexity of the application as well as over twenty variables. putnam3 simplified staffing (life cycle curve) to a small and easily managed set of parameters that could be expressed in the form of nomograms. this paper contributes to the software cost estimation by identifying those variables of the product which were found to be governing: the importance of distinguishing higher level language programming language systems (pls) from low level basic assembler language (bal), the importance of recognizing the major increase of effort if code is modified rather than new code created. the magnitude of these differences is quantified. finally in the analysis of the optional number of modules for a product, a balance is shown between the intramodule complexity and the intermodule complexity. parametric data associated with program product development costs has been actively collected since mid-1976 by the program cost estimating department, now located at ibm's santa teresa laboratory. this data represents the actual person-month resources used to match program development requirements. products that were analyzed are a collection of classic ibm mainframe products: languages (such as cobol, pl/i, apl), utilities (vsam, os utilities, sort, etc.), and data base products (ims, data dictionary, etc.). these are &ldquo;system programs&rdquo; rather than applications. the range and median sizes of the products are shown in table 1. twenty six of the thirty products contain modified modules.
an empirical study of predicate dependence levels and trends. many source code analyses are closely related to and strongly influenced by interdependence among program components. this paper reports results from an empirical study of the interdependences involving program predicates and the formal parameters and global variables which potentially affect them.the findings show that it is possible to eliminate from consideration approximately 30% of the formal parameters, 50% of the 'touched' global variables, and 97% of the 'visible' global variables.another important and encouraging finding is a strong inverse correlation between the number of formal parameters and dependence level. the fact that no such correlation was found for global variables provides evidence to support the conjecture that global variables are harmful.
validation of the coupling dependency metric as a predictor of run-time failures and maintenance measures. the coupling dependency metric (cdm) is a successful design quality metric. here we apply it to four case studies: run-time failure data for a cobol registration system; maintenance data for a c text-processing utility; maintenance data for a c++ patient collaborative care system; and maintenance data for a java electronic file transfer facility. cdm outperformed a wide variety of competing metrics in predicting run-time failures and a number of different maintenance measures. these results imply that coupling metrics may be good predictors of levels of interaction within a software product
bi-criteria models for all-uses test suite reduction. using bi-criteria decision making analysis, a new modelfor test suite minimization has been developed that pursuestwo objectives: minimizing a test suite with regard to a particularlevel of coverage while simultaneously maximizingerror detection rates. this new representation makes it possibleto achieve significant reductions in test suite size withoutexperiencing a decrease in error detection rates. usingthe all-uses interprocedural data flow testing criterion, twobinary integer linear programming models were evaluated,one a single-objective model, the other a weighted-sums bicriteriamodel. the applicability of the bi-criteria model toregression test suite maintenance was also evaluated. thedata show that minimization based solely on definition-useassociation coverage may have a negative impact on the errordetection rate as compared to minimization performedwith a bi-criteria model that also takes into account theability of test cases to reveal error. results obtained withthe bi-criteria model also indicate that test suites minimizedwith respect to a collection of program faults are effectiveat revealing subsequent program faults.
enriching software engineering courses with service-learning projects and the open-source approach. real-world software engineers deal with complex problem. yet many software engineering courses do not involve projects of enough complexity to give students such experience. we sense that service-learning projects, while difficult to manage and sustain, can serve a crucial role in this regard. through trials in a senior-level software engineering course, we discovered that the open-source approach works well to enable students to work on large, multiple-term service-learning projects. we developed grow, a cross-term, cross-team educational software process to meet the challenges of adopting complex, real-world projects in one-term courses, and to sustain service learning.
prototyping a process monitoring experiment. features are often the basic unit of development for a very large software system and represent long-term efforts, spanning up to several years from inception to actual use. developing an experiment to monitor (by means of sampling) such lengthy processes requires a great deal of care in order to minimize casts and to maximize benefits. just as prototyping is often a necessary auxiliary step in a large-scale, long-term development effort, so, too, is prototyping a necessary step in the development of a large-scale, long-term process monitoring experiment. therefore, we have prototyped our experiment using a representative process and reconstructed data from a large and rich feature development. this approach has yielded three interesting sets of results. first, we reconstructed a 30-month time diary for the lead engineer of a feature composed of both hardware and software. these data represent the daily state (where the lead engineer spent the majority of his time) for a complete cycle of the development process. second, we found that we needed to modify our experimental design. our initial set of states did not represent the data as well as we had hoped. this is exemplified by the fact that the "other" category is too large. finally, the data provide evidence for both a waterfall view and an interactive, cyclic view of software development. we conclude that the prototyping effort is a necessary part of developing and installing any large-scale process monitoring experiment.
adding high availability and autonomic behavior to web services. rapid acceptance of the web services architecturepromises to make it the most widely supported andpopular object-oriented architecture to date. oneconsequence is that a wave of mission-critical webservices applications will certainly be deployed incoming years. yet the reliability options available withinweb services are limited in important ways. to use aterm proposed by ibm, web services systems need tobecome far more "autonomic," configuring themselves,diagnosing faults, and managing themselves. highavailability applications need more attention. moreover,the scenarios in which such issues arise often entail verylarge deployments, raising questions of scalability. in thispaper we propose a path by which the architecture couldbe extended in these respects.
journey of enlightenment: the evolution of development at microsoft. like many software companies, microsoft has been doing distributed application development for many years. however, recent changes in the market have altered the rules, both in terms of customer expectations and programming models for ubiquitous interconnected smart devices. these changes have provoked two dramatic shifts in the way we develop software. the first is the creation and use of the .net framework as a simple, secure, and robust platform for device-independent software development, data manipulation, and communications. the second is an agile yet highly disciplined approach to designing, testing, implementing, and verifying our software which presumes all bugs are unacceptable and must be found and fixed early before they impact internal groups, external partners, and eventually our customers. this paper discusses the nature and impact of these two dramatic shifts to the development practices at microsoft.
integrating hundred's of product through one architecture: the industrial it architecture. during the last few years, software product line engineering has gained significant interest as a way for creating software products faster and cheaper. but what architecture is needed to integrate huge amounts of products, from different product lines? this paper describes such an architecture and its support processes and tools. through cases, it is illustrated how the architecture is used to integrate new --- and old --- products in such diverse integration projects as vessel motion control, airport baggage handling systems, pulp&paper and oil&gas, in a very large organization. however, in a large organization it is a challenge to make everyone follow an architecture. steps taken to ensure global architectural consistency are presented. it is concluded that a single architecture can be used to unify development in a huge organization, where the distributed development practices otherwise may prohibit integration of various products.
statestep: a tool for systematic, incremental specification. statestep is an interactive tool for editing and checkingspecifications based on the finite state machine (fsm)model. the tabular notation supported is a novel yet simpleone, first developed to specify the external behaviour of aseries of audio compact disc recorders. the technique helpsto describe system behaviour in a systematic manner, intendedprincipally to ensure that no unusual scenarios, orcorner cases, are overlooked at the specification stage. thenotation is readily understandable and can reduce or eliminatethe need for internal events or other structuring primitives.it supports a naturally incremental approach to specification and seems especially suited to dealing with the kind of complexity that can arise in embedded user interfaces.
improving problem-oriented mailing list archives with mcs. developers often use electronic mailing lists when seeking assistance with a particular software application. the archives of these mailing lists provide a rich repository of problem-solving knowledge. developers seeking a quick answer to a problem find these archives inconvenient, because they lack efficient searching mechanisms, and retain the structure of the original conversational threads which are rarely relevant to the knowledge seeker.we present a system called mcs which improves mailing list archives through a process called condensation. condensation involves several tasks: extracting only messages of longer-term relevance, adding metadata to those messages to improve searching, and potentially editing the content of the messages when appropriate to clarify. the condensation process is performed by a human editor (assisted by a tool), rather than by an artificial intelligence (ai) system.we describe the design and implementation of mcs, and compare it to rlated systems. we also present our experiences condensing a 1428 message mailing list archive to an archive containing only 177 messages (an 88% reduction). the condensation required only 1.5 minutes of editor effort per message. the condensed archive was adopted by the users of the mailing list.
cobra: a hybrid method for software cost estimation, benchmarking, and risk assessment. current cost estimation techniques have a number of drawbacks. for example, developing algorithmic models requires extensive past project data. also, off-the-shelf models have been found to be difficult to calibrate but inaccurate without calibration. informal approaches based on experienced estimators depend on estimators' availability and are not easily repeatable, as well as not being much more accurate than algorithmic techniques. we present a method for cost estimation that combines aspects of algorithmic and experiential approaches (referred to as cobra, cost estimation, benchmarking, and risk assessment). we find through a case study that cost estimates using cobra show an average are of 0.09. although we do not have the room to describe the benchmarking and risk assessment parts, the reader will find detailed information in (briand et al., 1997)
an assessment and comparison of common software cost estimation modeling techniques. this paper investigates two essential questions related to data-driven, software cost modeling: (1) what modeling techniques are likely to yield more accurate results when using typical software development cost data? and (2) what are the benefits and drawbacks of using organization-specific data as compared to multi-organization databases? the former question is important in guiding software cost analysts in their choice of the right type of modeling technique, if at all possible. in order to address this issue, we assess and compare a selection of common cost modeling techniques fulfilling a number of important criteria using a large multi-organizational database in the business application domain. namely, these are: ordinary least squares regression, stepwise anova, cart, and analogy. the latter question is important in order to assess the feasibility of using multi-organization cost databases to build cost models and the benefits gained from local, company-specific data collection and modeling. as a large subset of the data in the multi-company database came from one organization, we were able to investigate this issue by comparing organization-specific models with models based on multi-organization data. results show that the performances of the modeling techniques considered were not significantly different, with the exception of the analogy-based models which appear to be less accurate. surprisingly, when using standard cost factors (e.g., cocomo-like factors, function points), organization specific models did not yield better results than generic, multi-organization models.
explaining the cost of european space and military projects. there has been much controversy in the literature on several issues underlying the construction of parametric software development cost models. for example, it has been argued whether (dis)economies of scale exist in software production, what functional form should be assumed between effort and product size, whether cocomo factors were useful, and whether the cocomo factors are independent. answers to such questions should help software organizations define suitable data collection programs and well-specified cost models. we use a data set collected by the european space agency to perform such an investigation. to ensure a certain degree of consistency in our data, we focus our analysis on a set of space and military projects that represent an important application domain and the largest subset in the database. these projects have been performed, however, by a variety of organizations. first, our results indicate that two functional forms are plausible between effort and product size: linear and log-linear. this also means that different project subpopulations are likely to follow different functional forms. second, besides product size, the strongest factor influencing cost appears to be team size. larger teams result in substantially lower productivity, which is interesting considering this attribute is rarely collected in software engineering cost databases. third, although some cocomo factors appear to be useful and significant covariates, they play a minor role in explaining project effort.
automated, contract-based user testing of commercial-off-the-shelf components. commercial-off-the-shelf (cots) components provide a means to construct software (component-based) systems in reduced time and cost. in a cots component software market there exist component vendors (original developers of the component) and component users (developers of the component-based systems). the former provide the component to the user without source code or design documentation, and as a result it is difficult for the latter to adequately test the component when deployed in their system. in this article we propose a framework that clarifies the roles and responsibilities of both parties so that the user can adequately test the component in a deployment environment and the vendor does not need to release proprietary details. then, based on this framework we combine and adapt two specification-based testing techniques and describe (and implement) a method for the automated generation of adequate test sets. an evaluation of our approach on a case study demonstrates that it is possible to automatically generate cost effective test sequences and that these test sequences are effective at detecting complex errors.
a replicated assessment and comparison of common software cost modeling techniques. delivering a software product on time, within budget, and to an agreed level of quality is a critical concern for many software organizations. underestimating software costs can have detrimental effects on the quality of the delivered software and thus on a company's business reputation and competitiveness. on the other hand, overestimation of software cost can result in missed opportunities to funds in other projects. in response to industry demand, a myriad of estimation techniques has been proposed during the last three decades. in order to assess the suitability of a technique from a diverse selection, its performance and relative merits must be compared.the current study replicates a comprehensive comparison of common estimation techniques within different organizational contexts, using data from the european space agency. our study is motivated by the challenge to assess the feasibility of using multi-organization data to build cost models and the benefits gained from company-specific data collection. using the european space agency data set, we investigated a yet unexplored application domain, including military and space projects. the results showed that traditional techniques, namely, ordinary least-squares regression and analysis of variance outperformed analogy-based estimation and regression trees. consistent with the results of the replicated study no significant difference was found in accuracy between estimates derived from company-specific data and estimates derived from multi-organizational data.
using simulation to empirically investigate test coverage criteria based on statechart. a number of testing strategies have been proposedusing state machines and statecharts as test models inorder to derive test sequences and validate classes orclass clusters. though such criteria have the advantage ofbeing systematic, little is known on how cost effective theyare and how they compare to each other.this article presents a precise simulation and analysisprocedure to analyze the cost-effectiveness of statechart-basedtesting techniques. we then investigate, using thisprocedure, the cost and fault detection effectiveness ofadequate test sets for the most referenced coveragecriteria for statecharts on three different representativecase studies. through the analysis of common results anddifferences across studies, we attempt to draw moregeneral conclusions regarding the costs and benefits ofusing the criteria under investigation.
modeling and managing risk early in software development. the authors present an automated modeling technique which can be used as an alternative to regression techniques to improve the quality of the software development process. the modeling process will allow for the reliable detection of potential problem areas and for the interpretation of the cause of the problem so that the most appropriate remedial action can be taken. it is shown that it can be used to facilitate the identification and aid the interpretation of the significant trends which characterize high risk components in several ada systems. the effectiveness of the technique is evaluated based on a comparison with logistic regression based models
investigating quality factors in object-oriented designs: an industrial case study. this paper aims at empirically exploring the relationships between most of the existing coupling and cohesion measures for object-oriented (oo) systems, and the fault-proneness of oo system classes. the underlying goal of such a study is to better understand the relationship between existing design measurement in oo systems and the quality of the software developed. the study described here is a replication of an analogous study conducted in an university environment with systems developed by students. in order to draw more general conclusions and to (dis)confirm the results obtained there, we now replicated the study using data collected on an industrial system developed by professionals. results show that many of our findings are consistent across systems, despite the very disparate nature of the systems under study. some of the strong dimensions captured by the measures in each data set are visible in both the university and industrial case study. for example, the frequency of method invocations appears to be the main driving factor of fault-proneness in all systems. however, there are also differences across studies which illustrate the fact that quality does not follow universal laws and that quality models must be developed locally, wherever needed.
a procedure for designing abstract interfaces for device interface modules. this paper describes the abstract interface principle and shows how it can be applied in the design of device interface modules. the purpose of this principle is to reduce maintenance costs for embedded real-time software by facilitating the adaptation of the software to altered hardware interfaces. this principle has been applied in the naval research laboratory's redesign of the flight software for the navy's a-7 aircraft. this paper discusses a design approach based on the abstract interface principle and presents solutions to interesting problems encountered in the a-7 re-design. the specification document for the a-7 device interface modules is available on request; it provides a fully worked out example of the design approach discussed in this paper.
using a behavioral theory of program comprehension in software engineering. a theory is presented of how a programmer goes about understanding a program. the theory is based on a representation of knowledge about programs as a succession of knowledge domains which bridge between the problem domain and the executing program. a hypothesis and verify process is used by programmers to reconstruct these domains when they seek to understand a program. the theory is useful in several ways in software engineering: it makes accurate predictions about the effectiveness of documentation; it can be used to systematically evaluate and critique other claims about documentation, and it may even be a useful guideline to a programmer in actually constructing documentation.
an examination of the current state of ipse technology. the concept of an integrated project support environment (ipse) was developed in response to a recognition that communication and coordination between all tools used in software development and maintenance are essential to the efficient production of quality software systems. the author begins by examining some of the reasons for the relative implementation of ipse in the commercial world, and then turns his attention to alternative solutions which have seen greater success. the main areas of ipse research currently being pursued are highlighted. an analysis is given of key issues for the future
a graph theoretic approach to the verification of program structures. for large computer programs, verification of compliance with structured programming rules can present difficult problems for programmers and managers. in order to certify that code is structured, an algorithm and test tool were recently developed to audit source code and verify the use of structured constructs. the paper describes the segmentation of programs as a way of representing their logical control structure; presents the basic algorithm, illustrates algorithm extensions; and briefly reports on experience in using the tool on a large software project.
a critical overview of computer performance evaluation. effective computer performance evaluation requires: theories and models which effectively represent computer systems and computer processes, evaluation techniques which generate accurate assessments of system or program behavior from models and theories, technology for data gathering on executing systems or processes and technology for data analysis. this paper assesses the extent to which these requirements are currently met. a greater emphasis on combining empirical and theoretical work is needed. the significance and value of current applications of performance measurement and analysis are assessed. network and data base systems offer high leverage for application of performance modeling and evaluation.
fast: a second generation program analysis system. fast (fortran analysis system) implements a powerful set of analysis capabilities on fortran source language programs. its implementation was accomplished through the integration of existing software systems and by the use of modern language system development tools. the result is an order of magnitude reduction in effort of implementation coupled with a sizable increase in system capabilities. the use of a general purpose, commercially available data management system as a data handler and data correlator was a dominant factor in both reduction in effort of implementation and generation of additional power and flexibility in the analysis capabilities offered by fast. fast implements a capability for systematically qualified program analyses which is unique among existing program analyzers. this capability should be particularly useful in the program maintenance environment.
reuse library interoperability and the world wide web. the reuse library interoperability group (rig) was formed in 1991 for the purpose of drafting standards enabling the interoperation of software reuse libraries. at that time, prevailing wisdom among many reuse library operators was that each should be a stand-alone operation. many operators saw a need for only a single library, their own, and most strived to provide the most general possible services to appeal to a broad community of users. the asset program, initiated by the advanced research project agency stars program, was the first to make the claim that it should properly be one part of a network of interoperating libraries. shortly thereafter, the rig was formed, initially as a collaboration between the stars program and the air force raasp program, but growing within six months to a self-sustaining cooperation among twelve chartering organizations. the rig has grown to include over twenty members from government, industry, and academic reuse libraries. it has produced a number of technical reports and proposed interoperability standards, some of which are described in this report.
specification and modeling: an academic perspective. the specification and modeling of software systems, of their aspects, and their development processes is at the heart of software engineering. over the years, we have achieved a much deeper and more comprehensive understanding of software and its models as a basis for its specification. however, there is still a way to go to make sure that all we know right now is transferred into practice, and that all we do not understand so far is investigated in depth. the goal is a tractable scientific basis for modeling and specification in programming, software and system engineering and its employment in engineering methods.
automotive software engineering. information technology has become the driving force of innovation in many areas of technology and also in cars. embedded software controls the functions of cars, supports and assists the driver and realizes systems for information and entertainment. software in automobiles is today one of the great challenges for software engineering. on modern cars we find all issues of software systems in a nutshell. it is a challenge for software and systems engineering.
challenges in automotive software engineering. the amount of software in cars grows exponentially. driving forces of this development are cheaper and more powerful hardware and the demand for innovations by new functions. the rapid increase of software and software based functionality brings various challenges (see [21], [23], [25], [26]) for the automotive industries, for their organization, key competencies, processes, methods, tools, models, product structures, division of work, logistics, maintenance, and long term strategies. from a software engineering perspective, the automotive industry is an ideal and fascinating application domain for advanced techniques. although the automotive industry may adopt general results and solutions from the software engineering body of knowledge gained in other domains, the specific constraints and domain specific requirements in the automotive industry ask for individual solutions and bring various challenges for automotive software engineering. in cars we find literally all interesting problems and challenging issues of software and systems engineering.
software engineering: management, personnel and methodology. three key factors often determine the success or failure of a software project: the management of the project, the selection of personnel, and the development methodology that is used. this paper discusses the important considerations that should be addressed in each of these areas and examines the results of a typical project that paid attention to these factors. in particular, it was concluded that a good development methodology can help ensure the reliability, maintainability and timeliness of any software project.
finding latent code errors via machine learning over program executions. this paper proposes a technique for identifying programproperties that indicate errors. the technique generates machinelearning models of program properties known to resultfrom errors, and applies these models to program propertiesof user-written code to classify and rank propertiesthat may lead the user to errors. given a set of propertiesproduced by the program analysis, the technique selectssubset of properties that are most likely to reveal an error.an implementation, the fault invariant classifier,demonstrates the efficacy of the technique. the implementationuses dynamic invariant detection to generate programproperties. it uses support vector machine and decision treelearning tools to classify those properties. in our experimentalevaluation, the technique increases the relevance(the concentration of fault-revealing properties) by a factorof 50 on average for the c programs, and 4.8 for the javaprograms. preliminary experience suggests that most of thefault-revealing properties do lead a programmer to an error.
rapid prototyping of control systems using high level petri nets. this paper presents a rapid prototyping methodology for the carrying out of control systems in which high level petri nets provide the common framework to integrate the main phases of software development: specification, validation, performance evaluation, implementation. petri nets are shown to be translatable into ada program structures concerning processes and their synchronizations.
discovering faults in idiom-based exception handling. in this paper, we analyse the exception handling mechanism of a state-of-the-art industrial embedded software system. like many systems implemented in classic programming languages, our subject system uses the popular return-code idiom for dealing with exceptions. our goal is to evaluate the fault-proneness of this idiom, and we therefore present a characterisation of the idiom, a fault model accompanied by an analysis tool, and empirical data. our findings show that the idiom is indeed fault prone, but that a simple solution can lead to significant improvements.
software engineering for secure systems. no abstract available
a framework of greedy methods for constructing interaction test suites. greedy algorithms for the construction of software interaction test suites are studied. a framework is developed to evaluate a large class of greedy methods that build suites one test at a time. within this framework are many instantiations of greedy methods generalizing those in the literature. greedy algorithms are popular when the time for test suite construction is of paramount concern. we focus on the size of the test suite produced by each instantiation. experiments are analyzed using statistical techniques to determine the importance of the implementation decisions within the framework. this framework provides a platform for optimizing the accuracy and speed of "one-test-at-a-time" greedy methods.
static checking of interrupt-driven software. resource-constrained devices are becoming ubiquitous. examples include cell phones, palm pilots, and digital thermostats. it can be difficult to fit required functionality into such a device without sacrificing the simplicity and clarity of the software. increasingly complex embedded systems require extensive brute-force testing, making development and maintenance costly. this is particularly true for system components that are written in assembly language. static checking has the potential of alleviating these problems, but until now there has been little tool support for programming at the assembly level. in this paper we present the design and implementation of a static checker for interrupt-driven z86-based software with hard real-time requirements. for six commercial microcontrollers, our checker has produced upper bounds on interrupt latencies and stack sizes, as well as verified fundamental safety and liveness properties. our approach is based on a known algorithm for model checking of pushdown systems, and produces a control-flow graph annotated with information about time, space, safety, and liveness. each benchmark is approximately 1000 lines of code, and the checking is done in a few seconds on a standard pc. our tool is one of the first to give an efficient and useful static analysis of assembly code. it enables increased confidence in correctness, significantly reduced testing requirements, and support for maintenance throughout the system life-cycle.
performing systematic literature reviews in software engineering. context: making best use of the growing number of empirical studies in software engineering, for making decisions and formulating research questions, requires the ability to construct an objective summary of available research evidence. adopting a systematic approach to assessing and aggregating the outcomes from a set of empirical studies is also particularly important in software engineering, given that such studies may employ very different experimental forms and be undertaken in very different experimental contexts.objectives: to provide an introduction to the role, form and processes involved in performing systematic literature reviews. after the tutorial, participants should be able to read and use such reviews, and have gained the knowledge needed to conduct systematic reviews of their own.method: we will use a blend of information presentation (including some experiences of the problems that can arise in the software engineering domain), and also of interactive working, using review material prepared in advance.
international workshop on realising evidence-based software engineering. this workshop is concerned with defining the procedures that are needed to establish a sound empirical foundation for the practices of software engineering. our goal is to begin building a community that will review, analyse, codify and promulgate software engineering experiences as well as to identify the processes and infrastructure that are needed to support these activities.
experiments with prolog design descriptions and tools in caede: an iconic design environment for multitasking, embdedded systems. we report on experiments with prolog design descriptions and tools in caede (carleton embedded system design environment), an experimental, iconic design environment for multitasking, embedded systems. the philosophy of caede is to enter structural and temporal design information iconically, via a graphics interface, to serve as the basis for design analysis and skeleton code generation, and then to enter, under control of the iconic interface, program &ldquo;strips&rdquo; to fill in the functional gaps in the skeleton code. the iconic information is converted automatically into a prolog design data base of facts and rules. caede aims to support incremental design and to be incrementally extensible. in the current implementation of caede, which runs on a sun workstation supporting design for ada, the iconic interface is limited to structural design. here we describe the prolog side of our research, covering the nature of the facts produced from the iconic input by the current implementation and their use by experimental prolog tools for structural analysis, temporal analysis and ada code generation. the aim is to show how prolog is contributing to the framework of a powerful, extensible design environment.
action language: a specification language for model checking reactive systems. we present a specification language called action language for model checking software specifications. action language forms an interface between transition system models that a model checker generates and high level specification languages such as statecharts, rsml and scr&mdash;similar to an assembly language between a microprocessor and a programming language. we show that action language translations of statecharts and scr specifications are compact and they preserve the structure of the original specification. action language allows specification of both synchronous and asynchronous systems. it also supports modular specifications to enable compositional model checking.
the fujaba real-time tool suite: model-driven development of safety-critical, real-time systems. no abstract available
end-user software engineering with assertions in the spreadsheet paradigm. there has been little research on end-user program development beyond the activity of programming. devising ways to address additional activities related to end-user program development may be critical, however, because research shows that a large proportion of the programs written by end users contain faults. toward this end, we have been working on ways to provide formal "software engineering" methodologies to end-user programmers. this paper describes an approach we have developed for supporting assertions in end-user software, focusing on the spreadsheet paradigm. we also report the results of a controlled experiment, with 59 end-user subjects, to investigate the usefulness of this approach. our results show that the end users were able to use the assertions to reason about their spreadsheets, and that doing so was tied to both greater correctness and greater efficiency.
process assessments in nasa. a software process assessment procedure, recently refined by the software engineering institute (sei), gives managers a useful tool to identify the strengths and weaknesses of software organizations. the author discusses how process assessment techniques were introduced to nasa and how the procedure was enlarged to evaluate not just software development but also software quality assurance operations. initially, the techniques were extended to cover contract management and especially software quality assurance organizations. a preliminary assessment tool (questionnaire) consisting of 98 items was introduced. after some revision, it demonstrated its usefulness at a series of on-site surveys. the combined surveys demonstrated that a nasa questionnaire can point a team in the right direction
security attribute evaluation method: a cost-benefit approach. conducting cost-benefit analyses of architectural attributes such as security has always been difficult, because the benefits are difficult to assess. specialists usually make security decisions, but program managers are left wondering whether their investment in security is well spent. this paper summarizes the results of using a cost-benefit analysis method called saem to compare alternative security designs in a financial and accounting information system. the case study presented in this paper starts with a multi-attribute risk assessment that results in a prioritized list of risks. security specialists estimate countermeasure benefits and how the organization's risks are reduced. using saem, security design alternatives are compared with the organization's current selection of security technologies to see if a more cost-effective solution is possible. the goal of using saem is to help information-system stakeholders decide whether their security investment is consistent with the expected risks.
no 1a ess laboratory support system - erasable flag facility. a laboratory support system (lss) is provided in all no. 1a electronic switching system (ess) test laboratories to support the ess software development process. the lss tools are utilized by the developers to accomplish ess program database management, lab load administration, lab load generation, and program testing and debugging in the laboratory environment. this document describes one of the lss testing and debugging tools: the no. 1a ess laboratory erasable flag system. this facility is a test coverage analyzer which monitors how well an executed test procedure has exercised, or covered, specified instruction and data words resident in no. 1a ess memory. erasable flag output data makes it possible to enhance test procedures to achieve a more comprehensive level of software checkout during feature development and system integration of ess code.
engineering mobile-agent applications via context-dependent coordination. mobility introduces peculiar coordination problems in agent-based internet applications. first, it suggests the exploitation of an infrastructure based on a multiplicity of local interaction spaces. second, it may require coordination activities to be adapted both to the characteristics of the execution environment where they occur and to the needs of the application to which the coordinating agents belong. this paper introduces the concept of context-dependent coordination based on programmable interaction spaces. on the one hand, interaction spaces associated to different execution environments may be independently programmed so as to lead to differentiated, environment-dependent, behaviors. on the other hand, agents can program the interaction spaces of the visited execution environments to obtain an application-dependent behavior of the interaction spaces themselves. several examples show how an infrastructure for context-dependent coordination can be exploited to simplify the design of internet applications based on mobile agents. in addition, the mars coordination infrastructure is presented as an example of a system in which the concept of context-dependent coordination has found a clean and efficient implementation.
a periodic object model for real-time systems. time-sensitive objects (tso), a data-oriented model for real-time systems, impose timing constraints on object values using validity intervals and object histories. periodic objects, a class of objects within the tso model, are described in detail and compared with more traditional periodic processes. advantages of periodic objects are identified, including greater scheduling independence of processing related through data dependencies, more opportunity for concurrency, and improved structure for timing fault tolerance
path expressions in pascal. this paper describes the enhancement of pascal to specify synchronization between concurrent processes by path expressions. the extended language is being used to gain experience in the design and construction of practical real time systems and operating systems. an encapsulation mechanism is included to synchronize all accesses to encapsulated data. a network message transfer system is presented as an extended example of the use of path expressions.
concurrent software system design, supported by sara at the age of one. this paper presents a multilevel modeling method suitable for the design of concurrent hardware or software systems. the methodology is requirement driven and uses tools incorporated in a programming system called sara (systems architect's apprentice). both top down refinement and bottom up abstraction are supported. the design of an asynchronous sender receiver illustrates the key steps in going smoothly from programming in the large to programming in the small or actual code. the same methodology can be used to design hardware systems by applying different pragmatics than those proposed for software systems. sara consists of a set of interactive tools implemented both at ucla and also on the mit-multics system. although sara continues in long-term development, completed design tools accessible for experimentation by authorized users at either location via the arpanet.
developing and executing java awt applications on limited devices with tcpte. the paper describes tcpte, a framework that supports the development of thin-client applications for mobile devices. by using this framework, java awt applications can be executed on a server and their graphical interfaces can be displayed on a remote client. tcpte combines in a single framework the advantages of thin-client computing with the richness of client-server graphical interfaces and the simplicity of development that characterizes desktop applications.
modeling and controlling the software test process. a novel approach for modeling and control of the software test process is presented. the approach is based on the concept of state variables and uses techniques from the well-established field of automatic control theory. an initial model of the software test phase is described and the results of a case study analysis are presented.
compositional verification of middleware-based software architecture descriptions. in this paper we present a compositional reasoningto verify middleware-based software architecture descriptions.we consider a nowadays typical software system development,namely the development of a software applicationa on a middleware m. our goal is to efficiently integrateverification techniques, like model checking, in thesoftware life cycle in order to improve the overall softwarequality. the approach exploits the structure imposed on thesystem by the software architecture in order to develop anassume-guarantee methodology to reduce properties verification from global to local. we apply the methodology on a non-trivial case study namely the development of a gnutellasystem on top of the siena event-notification middleware.
practical software measurement. this tutorial provides a one-day overview of practical software measurement (psm). the measurement approach focuses on satisfying the information needs of project managers. innovative elements of psm include the measurement process model and the measurement information model. rather than discussing specific numerical techniques in detail, this course emphasizes basic concepts.
statistical techniques for software engineering practice. many factors are combining to promote theuse of quantitative and statistical methods bypracticing software engineers. while thesetechniques are not new to industry in general,they are relatively new to the software industry.consequently, there is significant uncertainty inthe community about their difficulty andapplicability. this tutorial provides anintroduction to basic concepts and shows howthey can be applied to help solve commonsoftware engineering problems.
criteria for software modularization. a central issue in programming practice involves determining the appropriate size and information content of a software module. this study attempted to determine the effectiveness of two widely used criteria for software modularization, strength and size, in reducing fault rate and development cost. data from 453 fortran modules developed by professional programmers were analyzed. the results indicated that module strength is a good criterion with respect to fault rate, whereas arbitrary module size limitations inhibit programmer productivity. this analysis is a first step toward defining empirically based standards for software modularization.
transitions in programming models: 2. the future of programming languages is not what it used to be. from the 50's to the 90's, richer, more flexible, and more robust structures were imposed on raw computation. generally, new models of data and control managed to subsume older ones. but now, as programs and applications expand beyond a single local network and a single administrative domain, the very nature of data and control changes, and many long-lasting conceptual invariants are disrupted. we discuss three of these disruptive changes, which seem to be happening all at the same time, and for related reasons: asynchronous concurrency, semistructured data, and (in much less detail) security abstractions. we outline research project that address issues in those areas, mostly as examples of much larger territories yet to explore.
comparing frameworks and layered refinement. object-oriented frameworks are a popular mechanism for building and evolving large applications and software product lines. this paper describes an alternative approach to software construction, java layers (jl), and evaluates jl and frameworks in terms of flexibility, ease of use, and support for evolution. our experiment compares schmidt's ace framework against a set of ace design patterns that have been implemented in jl. we show how problems of framework evolution and overfeaturing can be avoided using jl's component model, and we demonstrate that jl scales better than frameworks as the number of possible application features increases. finally, we describe how constrained parametric polymorphism and a small number of language features can support jl's model of loosely coupled components and stepwise program refinement.
software research in the department of defense. the department of defense has a comprehensive program of coordinated r & d initiatives to improve software engineering tools and methods. one thrust of the program is to automate significant aspects of the software development and maintenance process. another thrust is to increase the availability of software tools and to institutionalize the exchange of the best tools and techniques throughout dod.
structured programming: from theory to practice. one of the more controversial topics to appear within the field of computer science has been the theory of structured programming and the specific tools and techniques associated with this generic title. with respect to this topic, it is the intent of this paper to provide a documented history of the research, prototyping and deliberate implementation of the structured programming technology within the united states army computer systems command. structured programming as used within the context of this paper involves the concepts of structured code, top down development, walkthrus, program design language, design and documentation tools, program support library and a programming team. the usacsc experience is viewed as not just another case study but rather an organizational change impacting a large number (500 cobol programmers) of personnel, standards, and normal operating procedures. one of the more intriguing topics to appear within the field of computer science has been the theory of structured programming and the specific tools and techniques associated with this generic title. after several years of discussion, pilot projects, technical articles and more discussions, the basic questions remain: what does the technology buy you? what does it cost you? how does one implement the technology on a large scale in a software production shop? with respect to these questions, and many others that the software community shares regarding structured programming, it is the intent of this paper to provide a documented history of the research, prototyping and deliberate implementation of the structured programming technology within the united states army computer systems command (usacsc).
integrating prior knowledge with a software reliability growth model. the authors describe an application of ohba's inflection s reliability growth model to an ibm software product consisting of 1200 kloc. the central theme deals with the management requirement that forecasts be made early in the test cycle when there is little data. a simple brute force monte carlo simulation is implemented which utilizes prior knowledge about the total number of failures in the product prior to test. attention is also given to the decisions made regarding the data to select as input to the model. scaled forecasts and field results are presented which show reasonably good results
third international workshop on distributed event-based systems - debs '04. event-based systems are made of reactive componentsthat cooperate by exchanging information and control in theform of events. the occurrence of an event, as well as thedata characterizing that event, may trigger the execution ofone or more components, which may in turn generate otherevents. in a distributed event-based system, where componentsare physically distributed over a network, eventsmust be signaled to remote components through some formof communication mechanism. this workshop is about (1)the engineering methods that support the design of event-basedapplications, and (2) the design of the communicationmechanisms that support the event-based interactionof components over a network.
comparison of two component frameworks: the fipa-compliant multi-agent system and the web-centric j2ee platform. this work compares and contrasts two component frameworks: (1) the web-centric java 2 enterprise edition (j2ee) framework and (2) the fipa-compliant multi-agent system (mas). fipa, the foundation for intelligent physical agents, provides specifications for agents and agent platforms. both frameworks are component frameworks; servlets and enterprise java beans (ejbs) in the case of j2ee and software agents in the case of mas. both frameworks are specification based. both frameworks mandate platform responsibilities towards their respective component(s).we develop a framework with which to structure the comparison of the component frameworks. we apply this comparison structure in the context of a 'data access' scenario to application development in the respective component frameworks. furthermore, we have prototyped this scenario in each of the two component frameworks. we conclude with a discussion of the benefits, drawbacks, and issues of developing new applications in each of the component frameworks.
experience with a modular typed language: protel. the support for modular software and the ability to perform type checking across module boundaries are becoming the mainstay of recent high level language design. this is well illustrated by languages such as mesa and the us department of defence's new standard language ada. at bell-northern research, protel, one of the first modular typed languages, has been used since 1975 to implement a substantial software system. the experience accumulated in building this system has given us a unique perspective. it has shown that the confidence of language designers in modular typed languages is well founded. it has also revealed some pitfalls which others will undoubtedly encounter. the purpose of this paper is to share our experience by outlining the nature of the problems and our solutions to them.
little-jil/juliette: a process definition language and interpreter. little-jil, a language for programming coordination in processes is an executable, high-level language with a formal (yet graphical) syntax and rigorously defined operational semantics. the central abstraction in little-jil is the &ldquo;step,&rdquo; which is the focal point for coordination, providing a scoping mechanism for control, data, and exception flow and for agent and resource assignment. steps are organized into a static hierarchy, but can have a highly dynamic execution structure including the possibility of recursion and concurrency.little-jil is based on two main hypotheses. the first is that coordination structure is separable from other process language issues. little-jil provides rich control structures while relying on separate systems for resource, artifact, and agenda management. the second hypothesis is that processes are executed by agents that know how to perform their tasks but benefit from coordination support. accordingly, each little-jil step has an execution agent (human or automated) that is responsible for performing the work of the step.this approach has proven effective in supporting the clear and concise expression of agent coordination for a wide variety of software, workflow, and other processes.
from software requirements to architectures. the first international workshop from software requirements to architectures (straw01) was held in toronto, ontario, canada, on may 14, 2001, just before the 23rd international conference on software engineering (icse). this brief paper outlines the motivation, goals and organisation of the workshop.
managing software artifacts on the web with labyrinth. software developers are increasingly exploiting the web as a document management system. however, the web has some limitations, since it is not aware of the structure and semantics associated to pieces of information (e.g., the fact that a document is a requirement specification) and of the semantics of relationships between pieces of information (e.g., the fact that a requirement specification document may be associated to some design specification document). in the labyrinth project we enhance the capabilities of the web as a document management system by means of a semantic model (called schema, in analogy with database schemas), which is associated to web documents. this model is itself a web document and can be accessed and navigated through a simple web browser.
p2p file sharing analysis for a better performance. the so-called second generation p2p file-sharing applications have with no doubt a better performance than the first implementations. the most remarkable difference is due to the file division into smaller pieces, where a receiving peer of any piece automatically becomes a new source to other peers. but a new question arises on how we distribute all the pieces provided by a seed peer to minimize the global and presumably individual download times. in this paper we summarize part of the work we have developed up until now to answer this general question, in particular, we will analyze how close the present second generation p2p file-sharing applications remain from an ideal solution with the theoretical best performance, that is, where all peers are interconnected with each other and all peers have an altruistic behavior always uploading its contents at any chance. successive modifications of the ideal solution will lead us to more realistic scenarios. we will estimate the performance on each case and finally present the current studies we are carrying out to improve the overall capacity.
autonomous adaptation to dynamic availability using a service-oriented component model. this paper describes a project, called gravity, that defines a component model, where components provide and require services (i.e., functionality) and all component interaction occurs via services. this approach introduces service-oriented concepts into a component model and execution environment. the goal is to support the construction and execution of component-based applications that are capable of autonomously adapting at run time due to the dynamic availability of the services provided by constituent components. in this component model the execution environment manages an application that is described as an abstract composition that can adapt and evolve at run time depending on available functionality. the motivation of gravity is to simplify the construction of applications where dynamic availability arises, ranging from modern extensible systems to novel computing approaches, such as contrext-aware applications.
safety verification in murphy using fault tree analysis. murphy is a language-independent, experimental methodology for building safety-critical, real time software, which will include an integrated tool set. using ada as an example, this paper presents a technique for verifying the safety of complex, real-time software using software fault tree analysis. the templates for ada are presented along with an example of applying the technique to an ada program. the tools in the murphy tool set to aid in this type of analysis are described.
modular verification of software components in c. we present a new methodology for automatic verification of c programs against finite state machine specifications. our approach is compositional, naturally enabling us to decompose the verification of large software system into subproblems of manageable complexity. the decomposition reflects the modularity in the software design. we use weak simulation as the notion of conformance between the program and its specification. following the abstract-verify-refine paradigm, our tool magic first extracts a finite model from c source code using predicate abstraction and theorem proving. subsequently, simulation is checked via a reduction to boolean satisfiability. magic is able to interface with several publicly available theorem provers and sat solvers. we report experimental results with procedures from the linux kernel and the openssl toolkit.
decoupling synchronization from local control for efficient symbolic model checking of statecharts. symbolic model checking is a powerful formal verification technique for reactive systems. we address the problem of symbolic model checking for software specifications written as statecharts. we concentrate on how the synchronization of statecharts relates to the efficiency of model checking. we show that statecharts synchronized in an oblivious manner, such that the synchronization and the local control are decoupled, tend to be easier for symbolic analysis. based on this insight, the verification of some non-oblivious systems can be optimized by a simple, transparent modification to the model to separate the synchronization from the local control. the technique enabled the analysis of the statecharts model of a fault tolerant electrical power distribution system developed by the boeing commercial airplane group. the results disclosed subtle modeling and logical flaws not found by simulation.
promises: limited specifications for analysis and manipulation. structural change in a large system is hindered when information is missing about portions of the system, as is often the case in a distributed development process. an annotation mechanism called promises is described for expressing properties that can enable many kinds of structural change in systems. promises act as surrogates for an actual component, and thus are analogous to &ldquo;header&rdquo; files, but with more specific semantic information. unlike formal specifications, however, promises are designed to be easily extracted from systems and managed by programmers using automatic analysis tools. promises are described for effects, unique references, and use properties. by using promises, a component developer can offer additional opportunity for change (flexibility) to clients, but at a potential cost in flexibility for the component itself. this suggests the possibility of using promises as a means to allocate flexibility among the components of a system
drt: a tool for design recovery of interactive graphical applications. nowadays, the majority of productivity applications are interactive and graphical in nature. in this demonstration, we explore the possibility of taking advantage of these two characteristics in a design recovery tool. specifically, the fact that an application is interactive means that we can identify distinct execution bursts corresponding closely to "actions" performed by the user. the fact that the application is graphical means that we can describe those actions visually from a fragment of the application display itself. combining these two ideas, we obtain an explicit mapping from high-level actions performed by a user (similar to use case scenarios/specification fragments) to their low-level implementation. this mapping can be used for design recovery of interactive graphical applications. we demonstrate our approach using lyx, a scientific word processor.
design recovery of interactive graphical applications. nowadays, the majority of productivity applications are interactive and graphical in nature. in this paper, we explore the possibility of taking advantage of these two characteristics in a design recovery tool. specifically, the fact that an application is interactive means that we can identify distinct execution bursts corresponding closely to "actions" performed by the user. the fact that the application is graphical means that we can describe those actions visually from a fragment of the application display itself. combining these two ideas, we obtain an explicit mapping from high-level actions performed by a user (similar to use case scenarios/specification fragments) to their low-level implementation. this mapping can be used for design recovery of interactive graphical applications. we demonstrate our approach using lyx, a scientific word processor.
software model checking in practice: an industrial case study. we present an application of software model checking to the analysis of a large industrial software product: lucent technologies' cdma call-processing library. this software is deployed on thousands of base stations in wireless networks world-wide, where it sets up and manages millions of calls to and from mobile devices everyday. our analysis of this software was carried out using verisoft, a tool developed at bell laboratories that implements model-checking algorithms for systematically testing concurrent reactive software.verisoft has now been used for over a year for analyzing several releases and versions of the cdma call-processing software. although we started this work with a fairly robust version of the software, the application of model checking exposed several problems that had escaped traditional testing. model checking also helped developers maintain a high degree of confidence in the library as it evolved through its many releases and versions.to our knowledge, software model checking has rarely been applied to software systems of this scale. in this paper, we describe our experience in applying this technology in an industrial environment.
bayesian models of design based on intuition. most computer system designers use a great deal of intuition in the design process. intuition is often used to handle uncertainty in design parameters. since uncertainty seems to be intrinsic to most design problems it follows that designers will continue to rely on intuition or &ldquo;sound engineering judgement&rdquo;. this paper attempts to use bayesian decision theory to explore the possibility of setting up a structure and theory for making design decisions in the computer system design environment while explicitly taking the intuitive nature of many design decisions into account. we shall focus attention on a particular problem in distributed data base design in which the designer must use his intuition to estimate the load on the system which he is designing. similar bayesian approaches could be used in other design problems.
symbolic model checking of declarative relational models. this paper explores the idea of augmenting traditional model checkers with the expressiveness of a declarative, relational language. the goal is to enable programmers to write very intuitive and compact specifications, in order to allow the automatic verification of more complicated software systems. the key idea is that many structural operations (common in object-oriented programs) can be easily described using relations and relational operators, while other operations are best described using the primitive data types and their operations (such as simple arithmetic operations on numbers). by allowing a mixture of both, and by allowing parts of the model to be described declaratively rather than imperatively, the programmer has the freedom to model each part of the system differently, using the most intuitive and simple constructs. we built a bdd-based model checker for the language, and successfully verified a straightforward model of the dependency algorithm in apache ant for up to 5 nodes.
fluent-based web animation: exploring goals for requirements validation. we present a tool that provides effective graphical animations as a means of validating both goals and software designs. goals are objectives that a system is expected to meet. they are decomposed until they can be represented as fluents. animations are specified in terms of fluents and driven by behaviour models.
evaluating object-oriented designs with link analysis. the hyperlink induced topic search algorithm,which is a method of link analysis, primarily developedfor retrieving information from the web, is extended inthis paper, in order to evaluate one aspect of quality inan object-oriented model. considering the number ofdiscrete messages exchanged between classes, it ispossible to identify "god" classes in the system, elementswhich imply a poorly designed model. the principaleigenvectors of matrices derived from the adjacencymatrix of a modified class diagram, are used to identifyand quantify heavily loaded portions of an object-orienteddesign that deviate from the principle ofdistributed responsibilities. the non-principaleigenvectors are also employed in order to identifypossible reusable components in the system. themethodology can be easily automated as illustrated by ajava program that has been developed for this purpose.
demonstration of agenda tool set for testing relational database applications. database systems play an important role in nearly every modern organization, yet relatively little research effort has focused on how to test them. agenda, a (test) generator for database applications, is a research prototype tool set for testing db application programs. in testing such applications, the states of the database before and after execution play an important role, along with the user's input and system output. agenda components populate the database, generate inputs, and check aspects of the correctness of output and new db state.
program refinement by transsformation. program maintenance is simplified when the program to be modified can be viewed as an abstract algorithm to which clearly documented implementation decisions have been applied to produce an efficient realization. the harvard program development system (pds) [8] is a programming support environment that encourages users to take this view of programs. a user of the pds creates transformations that incorporate implementation choices, and the system uses these transformations to refine concrete programs from their abstract counterparts. in addition to simplifying maintenance, this method supports the use of notational extensions and the development of program families. we describe the transformation facilities available to the user of the pds, and we discuss aspects of the implementation of these facilities.
a system for program refinement. the program development system (pds) is a programming environment, an integrated collection of interactive tools that support the process of program definition, testing, and maintenance. the pds is intended to aid the development of large programs, especially program families whose members must be maintained in synchrony. the system facilitates implementation by stepwise refinement, and it keeps a refinement history that allows program modifications made at a high level of abstraction to be reflected efficiently and automatically in the corresponding low level code. analysis tools are used both to support program validation and to guide program refinement. we describe the pds and the tools incorporated in it, and we conclude with an example of its use.
extending the implementation scheme of functional programming system fp for supporting the formal software development methodology. an extension to the implementation scheme of functional programming system fp is proposed for handling multiple order operations at function level. the concepts of functional form operator (ffo), nth order applications, and invariant semantics of functional forms are introduced. an ffo can be taken as either an operator at function level, or a variable of other operations for building new ffo's. thus variable-free operators can be defined for mappings from a list of functions to a new function denoted by a functional form, or from a list of ffo's to a new one. together with the notion of multi-order applications, a hierarchy of operations at function level can be handled. this approach is useful for supporting the formal software development methodology characterized by top-down functional specification, bottom-up function mapping construction and stepwise validation.
testtube: a system for selective regression testing. the paper describes a system called testtube that combines static and dynamic analysis to perform selective retesting of software systems written in c. testtube first identifies which functions, types, variables and macros are covered by each test unit in a test suite. each time the system under test is modified, testtube identifies which entities were changed to create the new version. using the coverage and change information, testtube selects only those test units that cover the changed entities for testing the new version. we have applied testtube to selective retesting of two software systems, an i/o library and a source code analyzer. additionally, we are adapting testtube for selective retesting of nondeterministic systems, where the main drawback is the unsuitability of dynamic analysis for identification of covered entities. our experience with testtube has been quite encouraging, with an observed reduction of 50% or more in the number of test cases needed to test typical software changes
use of cluster analysis to evaluate software engineering methodologies. the development of quantitative measures to evaluate software development techniques is necessary if we are going to develop appropriate methodologies for software production. data is collected by the software engineering laboratory at nasa goddard space flight center on developing medium scale projects of up to ten man years effort. in this study, cluster analysis was used on this collected data and several measures are proposed. these measurements are objective, quantifiable, are the results of the methodology, and most important, seem relevant.
software engineering for adaptive and self-managing systems. the objective of this workshop is to consolidate the interest in the software engineering community on autonomic, self-managing, self-healing, self-optimizing, self-configuring, and self-adaptive systems. the workshop will provide a forum for researchers to share new results, raise awareness of new adaptive concerns, and promote collaboration among the community. this workshop will be the first of several to assess progress and identify challenges in this important area.
an integrated method for effective behaviour analysis of distributed systems. behavioural analysis is a valuable aid for the design and maintenance of well-behaved distributed systems. dataflow and reachability analyses are two orthogonal, but complementary, behavioural analysis techniques. individually, each of these techniques may be inadequate for the analysis of large-scale distributed systems. on the one hand, dataflow analysis algorithms, while tractable, may not be sufficiently accurate to provide meaningful detection of errors. on the other hand, reachability analysis, while providing exhaustive analysis, may be computationally too expensive for complex systems. in this paper, we present a method which integrates dataflow and reachability analysis techniques to provide a flexible and effective means for analysing distributed systems at the preliminary and final design stages respectively. we also describe some effective measures taken to improve the adequacy of the individual analysis techniques using the concepts of action dependency and context constraints. a prototype supporting the method has been built, and its performance is described in this paper. a realistic example of a distributed track control system is used as a case study
checking subsystem safety properties in compositional reachability analysis. the software architecture of a distributed program can be represented by an hierarchical composition of subsystems, with interacting processes at the leaves of the hierarchy. compositional reachability analysis has been proposed as a promising automated method to derive the overall behavior of a distributed program in stages, based on its architecture. the method is particularly suitable for the analysis of programs which are subject to evolutionary change. when a program evolves, only behavior of those subsystems affected by the change need be re-evaluated. the method however has a limitation. the properties available for analysis are constrained by the set of actions that remain globally observable. the properties of subsystems, may not be analyzed. we extend the method to check safety properties of subsystems which may contain actions that are not globally observable. these safety properties can still be checked in the framework of compositional reachability analysis. the extension is supported by augmenting finite-state machines with a special undefined state /spl pi/. the state is used to capture possible violation of the safety properties specified by software developers. the concepts are illustrated using a gas station system as a case study.
a model for description of communication protocol. this paper presents a model for the description of communication protocol in view of the total behavior of terminal equipment. in this model, a protocol entity is modeled as a group of processes and monitors, and synchronization between input and output processes is represented by the synchronizing mechanism based on the concept of the monitor. furthermore, it is possible to specify the relation between entities of different layers of the protocol, including the relation between communication and local functions of terminal equipment. as an example of protocol description based on this model, teletex document layer protocol written in concurrent pascal language is illustrated.
verifying safety policies with size properties and alias controls. many software properties can be analysed through a relational size analysis on each function's inputs and outputs. such relational analysis (through a form of dependent typing) has been successfully applied to declarative programs, and to restricted imperative programs; but it has been elusive for object-based programs. the main challenge is that objects may mutate and they may be aliased. in this paper, we show how safety policies of programs can be analysed by tracking size properties of objects and be enforced by objects' invariants and the preconditions of methods. we propose several new ideas to allow both mutability and sharing of objects, whilst aiming for precision in our analysis. we introduce the concept of size-immutability to facilitate sharing, and also a set of alias controls to track unaliased objects whose size properties may change. we formalise our results through a set of advanced type checking rules for an object-based imperative language. we re-affirm the utility of the proposed type system by showing how a variety of software properties can be automatically verified according to size-inspired safety policies.
high-level specification of concurrency control in distributed database systems. concurrency control is one of the major issues in database systems; therefore, many concurrency control algorithms based on different strategies have been proposed. unfortunately there is still lack of a general model for describing these algorithms. hence, algorithms cannot be uniformly presented, which makes it hard to understand them and to prove their correctness. this paper proposes a high level specification, based on an object-oriented model, of concurrency control algorithms. concurrency control algorithms are specified in a high level fashion without losing their formality. basing on the object-oriented model, objects are individually specified. therefore, the specification of a concurrency control algorithm consists of the specifications of objects and their interactions.
diagnostic system for distributed software: a relational database approach. software errors in distributed systems are difficult to detect, locate and correct. the relational database approach in software diagnostics is an integrated approach encompassing most features in static analysis, dynamic testing, symbolic execution and performance evaluation techniques. modified syntax analysis of source program and testing run of the instrumented code generate the basis relations (symbol tables, graph models, program fragments, execution histories) from which diagnostic information is retrieved interactively. the basis relations contain necessary information to diagnose the software since data structures, algorithms and execution behavior of the software are included. implementations of some typical dynamic testing features extended to distributed software are discussed and illustrated.
software engineering for large-scale multi-agent systems - selmas'04. the development of multi-agent systems (mas) is nota trivial task. in addition, with the advances in internettechnologies, mas are undergoing a transition from closedto open architectures composed of a huge number of autonomousagents, which operate and move across differentenvironments. in fact, openness introduces additional complexityto the system modeling, design and implementation.it also impacts on most quality attributes of mas, includingscalability, interoperability, reliability and adaptability.this workshop brings together researchers and practitionersto discuss the current state and future direction of researchin software engineering for open mas. a particularinterest is to understand those issues in the agent technologythat make it difficult and/or improve the production oflarge open systems.
fifth workshop on software engineering for large-scale multi-agent systems (selmas). software is becoming present in every aspect of our lives, pushing us inevitably towards a world of ambient computing systems. multi-agent systems (mas) are a prominent technology which facilitates modeling and development of large-scale distributed systems. in recent years, software engineering research has focused on methodologies and techniques for improving mas design and implementation. however, making large mas dependable is still an open issue. the fifth workshop on software engineering for large-scale multi-agent systems (selmas 2006) aims to bring together academic, industrial and commercial communities interested in agent-oriented software engineering topics to discuss the different technologies being defined and used in the development of dependable mas.
a generalized assertion language. the motivation behind the work in debugging languages is to provide the programmer with primitives so that he may search for events during execution, which are suspected to be anomalous. events that may be specified by most existing debugging languages are very elementary. also, there are no facilities to combine them into more complex events. even though he can selectively monitor the history of execution, the programmer usually has to explore a vast mass of information in order to check the absence or presence of anomalous conditions. the philosophy of the assertion approach is to provide facilities with which the programmer may specify conditions, which the system can check at execution time. only violations are reported. by suppressing irrelevant information, it makes it a lot easier to detect anomalies. the assertion language described in this paper is generalized in the sense that it permits the programmer to refer to not only current events, but also past events. without such generalization, it is not possible to specify many interesting properties of programs. in addition, the language is open-ended by allowing a user to define checking routines of his own. relevant aspects of the language and examples are given.
non-intrusive object introspection in c++: architecture and application. we describe the design and implementation of system architecture to support object introspection in c++. in this system, information is collected by parsing class declarations, and used to build a supporting environment for object introspection. our approach is nonintrusive because it requires no change to the original class declarations and libraries, and it guarantees compatibility between objects before and after the addition of introspective capability. this is critical if one wants to integrate third-party class libraries, which are often supplied as black boxes and allow no modification, into highly dynamic applications. we show two applications: automatic i/o support for c++ objects; and an interactive exercise of dynamically loaded c++ class libraries
workshop description of 4th workshop on software quality (wosq). cost, schedule and quality are highly correlated factors in software development. they basically form three sides of the same triangle. beyond a certain point (the "quality is free" point), it is difficult to increase the quality without increasing either cost or schedule or both for the software under development. as products and applications mature, users expect higher quality products. they want it organizations to be responsible and accountable for the quality claims made by the product marketing teams. in the last couple decades, much software engineering research has focussed on standards, methodologies and techniques for improving software quality, measuring software quality and software quality assurance. most of this research is focused on the internal/development view of quality. more recent studies done in conjunction with the marketing groups have made attempts to understand the customer view of quality. all of these different ongoing activities to understand quality from the various perspectives have made the field even more enriching and exciting. the fourth workshop on software quality aims to bring together academic, industrial and commercial communities interested in software quality topics to discuss the different technologies being defined and used in the software quality area.
models and processes for the evaluation of off-the-shelf components -- mpec'05. this workshop summary presents an overview of the one-day international workshop on models and processes for the evaluation of off-the-shelf components (mpec'05), held in conjunction with the 27th international conference on software engineering (icse'05). details about mpec'05 may be found at http://www.lsi.upc.edu/events/mpec/.
use of state diagrams to engineer communications software. this paper presents our experience with a variation on the use of state diagrams in the development of a communications system. the following techniques are described: - state diagram notation functions as the design language used to describe the functional specification of major program modules. - these modules are coded in a high-level language using the state diagrams as the program structure and specification. - the actual programs are used as input to a simulator which performs a structured walk-through. - automatically produced state diagrams from final software serve as documentation and act as a check on meeting initial system requirements.
the concern manipulation environment. no abstract available
structure charts and program correctness proofs. structured design has been widely used in the software industry with good results. on the other hand, program development hand-in-hand with program-correctness proof techniques has shown promising signs for future software development. this paper attempts to bridge the gap between structured design and program development with proofs. three basic constructs used in structure charts have been modified to incorporate guarded commands. software design can be proved informally using the modified structure charts. with this technique, the benefits of both structured design and program correctness proofs can be applied to the development of large programs.
on the education of future software engineers. the education of software engineers more and more addresses organizational and management issues, like for instance modeling the business structure and environment which will receive a new software system. the teaching to software engineering students of modeling technologies based on standards like uml and the rational unified process, stressing the focus on designing business-oriented management of software services, raises novel questions than need to be addressed.
automated refactoring to introduce design patterns. software systems have to be flexible in order to cope with evolving requirements. however, since it is impossible to predict with certainty what future requirements will emerge, it is also impossible to know exactly what flexibility to build into a system. design patterns are often used to provide this flexibility, so this question frequently reduces to whether or not to apply a given design pattern. we address this problem by developing a methodology for the construction of automated transformations that introduce design patterns. this enables a programmer to safely postpone the application of a design pattern until the flexibility it provides becomes necessary. our approach deals with the issues of reuse of existing transformations, preservation of program behaviour and the application of the transformations to existing program code.
error recovery in systems of communicating processes. this paper deals with some of the relevant problems concerning the backward recovery of autonomous processes. the tools for the description of the past history of a system are formally defined, and an implementation is outlined.
calibrating the cocomo ii post-architecture model. the cocomo ii model was created to meet the need for a cost model that accounted for future software development practices. this paper describes some of the experiences learned in calibrating cocomo ii post-architecture model from eighty-three observations. the results of the multiple regression analysis, their implications, and a future calibration strategy are discussed
a comparison of data flow path selection criteria. a number of path selection testing criteria have been proposed throughout the years. unfortunately, little work has been done on comparing these criteria. to determine what would be an effective path selection criterion for revealing errors in programs, we have undertaken an evaluation of these criteria. this paper reports on the results of our evaluation for those path selection criteria based on data flow relationships. we show how these criteria relate to each other, thereby demonstrating some of their strengths and weaknesses.
composition patterns: an approach to designing reusable aspects. requirements such as distribution or tracing have an impact on multiple classes in a system. they are cross-cutting requirements, or aspects. their support is, by necessity, scattered across those multiple classes. a look at an individual class may also show support for cross-cutting requirements tangled up with the core responsibilities of that class. scattering and tangling make object-oriented software difficult to understand, extend and reuse. though design is an important activity within the software lifecycle with well-documented benefits, those benefits are reduced when cross-cutting requirements are present. this paper presents a means to mitigate these problems by separating the design of cross-cutting requirements into composition patterns. composition patterns require extensions to the uml, and are based on a combination of the subject-oriented model for composing separate, overlapping designs, and uml templates. this paper also demonstrates how composition patterns map to one programming model that provides a solution for separation of cross-cutting requirements in code&mdash;aspect-oriented programming. this mapping serves to illustrate that separation of aspects may be maintained throughout the software lifecycle.
the design of a template structure for a generalized data structure definition facility. a template structure capable of defining the runtime configuration of general data structures, e.g. arrays (homogeneous and non-homogeneous), cells, stacks, queues, trees, and general lists (graphs), for a generalized data structure definition facility that has practical utility in applications where thousands of data structures can be in existence at any given time is described. an important aspect of this template structure organization is that like instances of a data structure allocated at runtime share a common template rather than each allocated instance of a data structure having its own individual template. the motivation for sharing templates is derived from the fact that large numbers of data structures can be active at runtime, and templates can occupy a considerable amount of storage (in some instances a template can occupy as much or more storage than the data structure elements themselves). the importance of template sharing in a paging system, and the capability of the template structure for facilitating the design and implementation of general operations such as insert and delete are discussed.
financially informed requirements prioritization. this tutorial introduces a financially responsible approach to requirements prioritization that enhances the value creating potential of a software development project. the approach, known as the incremental funding method (ifm), is described in the book "software by numbers: low-risk, high-return development" [2,3]. tutorial attendees will learn how to group requirements into "chunks" of revenue-generating functionality known as minimal marketable features (mmfs), and how to carefully sequence those mmfs in order to maximize the overall value of the project, reduce initial funding investments, and manipulate other project metrics such as the time needed for a project to reach break-even status. a gentle introduction to financial analysis will also equip participants to analyze and understand the impact of other requirements prioritization decisions upon the financial returns of a project. this process is applicable within any iterative development approach.
goal-centric traceability for managing non-functional requirements. this paper describes a goal centric approach for effectively maintaining critical system qualities such as security, performance, and usability throughout the lifetime of a software system. in goal centric traceability (gct) non-functional requirements and their interdependencies are modeled as softgoals in a softgoal interdependency graph (sig). a probabilistic network model is then used to dynamically retrieve links between classes affected by a functional change and elements within the sig. these links enable developers to identify potentially impacted goals; to analyze the level of impact on those goals; to make informed decisions concerning the implementation of the proposed change; and finally to develop appropriate risk mitigating strategies. this paper also reports experimental results for the link retrieval and illustrates the gct process through an example of a change applied to a road management system.
early aspects at icse: workshop in aspect-oriented requirements engineering and architecture design. this paper summarizes the workshop in aspect-oriented requirements engineering and architecture design.
formal specification and development of an ada compiler - a vdm case study. the vienna development method (vdm) has been employed by dansk datamatik center (ddc) on a large-scale, industrial ada compiler development project. vdm is a formal specification and development method in that it insists on the initial specifications and all design steps being expressed in a formal (mathematically based) notation. this paper gives an overview of how vdm was used in the various steps of the ddc ada project, and we guide the reader through the steps involved from the initial formal specification of ada down to the actually coded multipass compiler. finally we report on the quantitative and qualitative experiences we have gained, both as regards the technical suitability of vdm for the project and as regards the implications on software management and quality assurance.
locating causes of program failures. which is the defect that causes a software failure? by comparing the program states of a failing and a passing run, we can identify the state differences that cause the failure. however, these state differences can occur all over the program run. therefore, we focus in space on those variables and values that are relevant for the failure, and in time on those moments where cause transitions occur---moments where new relevant variables begin being failure causes: "initially, variable argc was 3; therefore, at shell_sort(), variable [2] was 0, and therefore, the program failed." in our evaluation, cause transitions locate the failure-inducing defect twice as well as the best methods known so far.
the right algorithm at the right time: comparing data flow analysis algorithms for finite state verification. finite state verification is emerging as an important technology for proving properties about software. in our experience, we have found that analysts have different expectations at different times. when an analyst is in an exploratory mode, initially formulating and verifying properties, analyses usually find inconsistencies because of flaws in the properties or in the software artifacts being analyzed. once an inconsistency is found, the analyst begins to operate in a fault finding mode, during which meaningful counter example traces are needed to help determine the cause of the inconsistency. eventually systems become relatively stable, but still require re-verification as evolution occurs. during such periods, the analyst is operating in a maintenance mode and would expect re-verification to usually report consistent results. although it could be that one algorithm suits all three of these modes of use, the hypothesis explored here is that each would be best served by an algorithm optimized for the expectations of the analyst.
computer-aided micro-analysis of programs. an approach is described whereby one may, with the help of a computer, perform micro-analyses of programs by constructing their time-formulas. time-formulas are symbolic formulas which express execution times as functions of variables representing the time needed to perform common, elementary operations (e.g., addition, assignment, subscripting, loop overhead). by binding the variables to numeric values corresponding to a specific machine, one can estimate program execution times without resorting to empirical tests. some programs which have been analyzed using the suggested approach are reviewed in this paper. these include strassen's matrix multiplication algorithm, deterministic parsers and a certain class of straight-line programs. the software tools which are desirable for performing the suggested type of analysis are also discussed. finally, the paper outlines some of the related research problems which are worth investigating.
constructing test suites for interaction testing. software system faults are often caused by unexpected interactions among components. yet the size of a test suite required to test all possible combinations of interactions can be prohibitive in even a moderately sized project. instead, we may use pairwise or t-way testing to provide a guarantee that all pairs or t-way combinations of components are tested together. this concept draws on methods used in statistical testing for manufacturing and has been extended to software system testing. a covering array, ca(n; t, k, v), is an n &times; k array on v symbols such that every n &times; t sub-array contains all ordered subsets from v symbols of size t at least once. the properties of these objects, however, do not necessarily satisfy real software testing needs. instead we examine a less studied object, the mixed level covering array and propose a new object, the variable strength covering array, which provides a more robust environment for software interaction testing. initial results are presented suggesting that heuristic search techniques are more effective than some of the known greedy methods for finding smaller sized test suites. we present a discussion of an integrated approach for finding covering arrays and discuss how application of these techniques can be used to construct variable strength arrays.
must there be so few? including women in cs. women's under-representation in academic computer science is described for the u.s. and internationally. conditions that contribute to this situation are indentified, and motivations for increasing women's participation in computer science are discussed. according to recent research in the u.s., effective interventions at the undergraduate level include: actively recruiting women encouraging women to persist, and mentoring for the purpose of overcoming under-representation. the latter two practices are easily implemented.
from research to reward: challenges in technology transfer. over a five year period the applied science & technology group of ibm's hursley laboratory in england turned itself from a fully-funded research organisation into an entirely self-funded technology transfer group. much practical experience and insight was gained into the questions of: what are the obstacles to overcome in successful technology transfer? how to find a match between technology and customer? how best to manage risk and expectation?to be successful a technology transfer group needs to be correctly positioned within its sponsoring organisation, use management processes that provide flexibility and control, and develop a sophisticated engagement model for working with its customers.
the rmt (recursive multi-threaded) tool: a computer aided software engineering tool for monitoring and predicting software development progress. a number of software life-cycles for object-oriented software development (fountain model, recursive/parallel model, mcgregor and sykes model, and chaos model life cycle) exist today. however, these existing life-cycles have little or no support for estimating and monitoring progress during the development of the software. the ability to measure progress during the development is significant because it allows both the managers and the developers to determine whether a project is on schedule or not. identifying that a project is behind schedule allows managers and developers to notify appropriate individuals of any scheduling and/or budgetary impacts at an early stage during the development and to determine appropriate course of action. this demonstration presents the recursive multi-threaded (rmt) software life-cycle and the implemented computer aided software engineering tool based on rmt. the rmt tool supports the monitoring of progress during development, addresses the specific needs of the developing object-oriented software, and attempts to resolve deficiencies found in many existing software lifecycles. what makes rmt unique from existing software life-cycles is its use of a "thread" for partitioning and organizing software development activities. threads support iteration and recursion, which are critical concepts for the development of the software.
usage-centered software engineering: an agile approach to integrating users, user interfaces, and usability into software engineering practice. usage-centered design is a systematic, model-driven approach to visual and interaction design with an established record of effectiveness in a wide variety of settings and areas of application. the tutorial introduces the models and methods of usage-centered design and explores the integration of usage-centered approaches into software engineering practice. agile approaches to modeling will be emphasized, with the focus on use cases, which are central to usage-centered design and serve as a common thread throughout an integrated usage-centered software engineering process.
measuring memory protection. a protection measure based on a simple model of a protection system is presented. the measure shows how closely a computer system adheres to the principle of minimum privilege. its application to the operating system of the cambridge university cap computer is described and ways of bringing the operating system closer to a state of minimum privilege are discussed. the results of this work have demonstrated that the measure provides a useful tool for the designers of operating systems and other software. a module in a computer system has a repertoire of services it can perform; the services provided by a module are made available to other modules as functions. an original feature of the work described in this paper is the attention paid to functions in the context of protection in computer systems. the protection model and the protection measure are defined in terms of the objects accessible to a process and it is important to note that functions are considered to be objects.
highly reliable upgrading of components. after a system is deployed, fixes, enhancements, and modifications all occur that change the components that make up the system. unfortunately, new versions of components can introduce new errors and break existing, depended-upon behavior. when this happens, the old component version could have provided the correct behavior, but it is no longer part of the system. we propose a framework, hercules, for upgrading system components that, instead of removing the old version of the component, keeps multiple versions of a component running. doing so allows behavior to be utilized from all versions, and maintains system integrity and correctness even in the presence of newly introduced errors. this framework ensures that the move towards dynamic, configurable software systems does not lessen, but rather provides capabilities to enhance the reliability that software will achieve through the next century.
icse workshop on dynamic analysis (woda 2003). dynamic analysis of software systems has long proven to be a practical approach to gain understanding of the operational behavior of the system. this workshop will bring together researchers in the field of dynamic analysis to discuss the breadth off the field, order the field along logical dimensions, expose common issues and approaches, and stimulate synergistic collaborations among the participants.
safe query objects: statically typed objects as remotely executable queries. developers of data-intensive applications are increasingly using persistence frameworks such as ejb, hibernate and jdo to access relational data. these frameworks support both transparent persistence for individual objects and explicit queries to efficiently search large collections of objects. while transparent persistence is statically typed, explicit queries do not support static checking of types or syntax because queries are manipulated as strings and interpreted at runtime. this paper presents safe query objects, a technique for representing queries as statically typed objects while still supporting remote execution by a database server. safe query objects use object-relational mapping and reflective metaprogramming to translate query classes into traditional database queries. the model supports complex queries with joins, parameters, existentials, and dynamic criteria. a prototype implementation for jdo provides a type-safe interface to the full query functionality in the jdo 1.0 standard.
adaptive testing. the primary vehicle for demonstrating the performance of ballistic missile defense (bmd) software is testing in a simulated environment. the complexity of bmd software logic and the large volumes of input data preclude exhaustive testing. the problem is compounded by limitations on testing time, complicated test procedures, and lack of systematic procedures for performance analysis. this paper describes an approach towards providing an effective means for identifying the boundary of performance of bmd software. the approach, called adaptive testing, uses performance data to systematically redefine input data that will produce some specified level of system performance. components of the adaptive testing technology include an interactive scenario generator, a performance evaluator, an adaptive algorithm for test case perturbation, and a system, environment, and threat simulator (sets). problems associated with the approach are discussed as well as the expected payoff.
multiple mass-market applications as components. truly successful models for component-based software development continue to prove elusive. one of the few is the use of operating system, database and similar programs in many systems. we address three related problems in this paper. first, we lack needed models. second, we do not know the conditions under which such models can succeed. in particular, it is unclear whether the notable success with operating systems can be replicated. third, we do not know whether certain specific models can succeed. we are addressing these problems by evaluating a particular model that shares important characteristics with the successful operating system example: using compatible pc packages as components. our approach to evaluating such a model is to engage in a case study that aims to build an industrially successful system representative of an important class of systems. we report on our use of the model to develop a computational tool for reliability engineering. we draw two conclusions. first, this kind of model has the potential to succeed. second, even today, the model can produce significant returns, but it clearly carries considerable risks.
galileo: a tool built from mass-market applications. we present galileo, an innovative engineering modeling and analysis tool built using an approach we call package-oriented programming (pop). galileo represents an ongoing evaluation of the pop approach, where multiple large, architecturally coherent components are tightly integrated in an overall software system. galileo utilizes microsoft word, internet explorer, and visio to provide a low cost, richly functional fault tree modeling superstructure. based on the success of previous prototypes of the tool, we are now building a version for industrial use under an agreement with nasa langley research center.
sound methods and effective tools for engineering modeling and analysis. modeling and analysis is indispensable in engineering. to be safe and effective, a modeling method requires a language with a validated semantics; feature-rich, easy-to-use, dependable tools; and low engineering costs. today we lack adequate means to develop such methods. we present a partial solution combining two techniques: formal methods for language design, and package-oriented programming for function and usability at low cost. we have evaluated the approach in an end-to-end experiment. we deployed an existing reliability method to nasa in a package-oriented tool and surveyed engineers to assess its usability. we formally specified, improved, and validated the language. to assess cost, we built a package-based tool for the new language. our data show that the approach can enable costeffective deployment of sound methods by effective tools.
bandera: extracting finite-state models from java source code. finite-state verification techniques, such as model checking, have shown promise as a cost-effective means for finding defects in hardware designs. to date, the application of these techniques to software has been hindered by several obstacles. chief among these is the problem of constructing a finite-state model that approximates the executable behavior of the software system of interest. current best-practice involves hand-construction of models which is expensive (prohibitive for all but the smallest systems), prone to errors (which can result in misleading verification results), and difficult to optimize (which is necessary to combat the exponential complexity of verification algorithms).in this paper, we describe an integrated collection of program analysis and transformation components, called bandera, that enables the automatic extraction of safe, compact finite-state models from program source code. bandera takes as input java source code and generates a program model in the input language of one of several existing verification tools; bandera also maps verifier outputs back to the original source code. we discuss the major components of bandera and give an overview of how it can be used to model check correctness properties of java programs.
bandera: a source-level interface for model checking java programs. despite emerging tool support for assertion-checking and testing of object-oriented programs, providing convincing evidence of program correctness remains a difficult challenge. this is especially true for multi-threaded programs. techniques for reasoning about finite-state systems have been developing rapidly over the past decade and have the potential to form the basis of powerful software validation theologies.we have developed the bandera toolset [1] to harness the power of existing model checking tools to apply them to reason about correctness requirements of java programs. bandera provides tool support for defining and managing collections of requirements for a program, for extracting compact finite-state models of the program to enable tractable analysis, and for displaying analysis results to the user through a debugger-like interface. this paper describes and illustrates the use of bandera's source-level user interface for model checking java programs.
transformations of software models into performance models. it is widely recognized that in order to make performance validation an integrated activity along the software lifecycle it is crucial to be supported from automated approaches. easiness to annotate software models with performance parameters (e.g. the operational profile) and automated translations of the annotated models into "ready-to-validate" models are the key challenges in this direction. several methodologies have been introduced in the last few years to address these challenges. the tutorial introduces the attendance to the main methodologies for annotating and transforming software models into performance models.
towards aspect weaving applications. software must be adapted to accommodate new features in the context of changing requirements. in this paper, we illustrate how applications with aspect weaving capabilities can be easily and dynamically adapted with unforseen features. aspects were used at three levels: in the context of semantic analysers, within a bpel engine that orchestrates web services, and finally within bpel processes themselves. each level uses its own tailored domain-specific aspect language that is easier to manipulate than a general-purpose one (close to the programming language) and the pointcuts are independent from the implementation.
documentation for safety critical software. the authors review some of the fundamental difficulties presented by the design and the validation of software for safety critical applications. they suggest that software formal documentation techniques ameliorate the problems described. the principles behind a method of documenting both requirements and software design are presented. the methods have been used by the atomic energy control board of canada in its safety assessment of the shutdown software of the darlington generating station (d.l. parnas et al., 1991). the method is illustrated by applying it to a small portion of the safety feature actuation system of a pwr nuclear reactor
1st international workshop on advances and applications of problem frames. software problems originate from real worldproblems. a software solution must address its real worldproblem in a satisfactory way. a software engineer musttherefore understand the real world problem that theirsoftware intends to address. to be able to do this, thesoftware engineer must understand the problem contextand how it is to be affected by the proposed software,expressed as the requirements. without this knowledge theengineer can only hope to chance upon the right solutionfor the right problem. application of the problem framesapproach may well be a way of meeting this need.
tool support for formal methods. the author discusses the state of the art of formal methods tool support. the focus is on a particular tool: the eves verification system. eves is a new formal methods tool that integrates techniques from, among others, language design, language semantics, and logic and automated deduction. eves demonstrates a number of the features that can be found in the state-of-the-art formal methods tool. the author gives brief introductions to various other formal methods tools (e.g., hol, ehdm, the boyer-moore theorem prover) and discusses how these tools are being applied
m-eves: a tool for verifying software. this paper describes the development of a new tool for formally verifying software. the tool is called m-eves and consists of a new language, called m-verdi, for implementing and specifying software; a new logic, which has been proven sound; and a new theorem prover, called m-never, which integrates many state-of-the-art techniques drawn from the theorem proving literature. two simple examples are used to present the fundamental ideas embodied within the system.
a recovery mechanism for modular software. when an exception occurs, the state of a system is damaged : further processing may cause additional exceptions. under some hypotheses concerning the system structure we give an a priori estimate of the damage caused by exceptions. based on this estimate we propose a recovery strategy and a recovery mechanism.
component-based software engineering for embedded systems. although attractive, cbd has not been widely adopted in domains of embedded systems. the main reason is inability of these technologies to cope with the important concerns of embedded systems, such as resource constraints, real-time or dependability requirements. however an increasing understanding of principles of cbd makes it possible to utilize these principles in implementation of different component-based models more appropriate for embedded systems. the aim of this tutorial is to point to the opportunity of applying this approach for development and maintenance of embedded systems. the tutorial gives insights into basic principles of cbd, the main concerns and characteristics of embedded systems and possible directions of adaptation of component-based approach for these systems. different types of embedded systems and approaches for applying cbd are presented and illustrated by examples from research and practices. also, challenges and research directions of cbd for embedded systems are discussed.
a case study: demands on component-based development. building software systems with reusable components brings many advantages. the development becomes more efficient, the realibility of the products is enhanced, and the maintenance requirement is significantly reduced. designing, developing and maintaining components for reuse is, however, a very complex process which places high requirements not only for the component functionality and flexibility, but also for the development organization. in this paper we discuss the different levels of component reuse, and certain aspects of component development, such as component generality and efficiency, compatibility problems, the demands on development environment, maintenance, etc. the evolution of requirements for products generates new requirements for components, if components are not enough general and mature. this dynamism determines the component life cycle where the component first reaches its stability and later degenerates in an asset that is difficult to use, difficult to adapt and maintain. when reaching this stage, the component becomes an obstacle for efficient reuse and should be replaced. questions related to use of standard and de-facto standard components are addressed specifically. as an illustration of reuse issues, we present a successful implementation of a component-based system which is widely used for industrial process control.
4th icse workshop on component-based software engineering: component certification and system prediction. this workshop brings together researchers from the areas of component trust and certification, component technology, and software architecture. the goal of this workshop is to ensure that work in the areas of certification of software components and architectural analysis for prediction of system quality attributes will be mutually aware, if not mutually reinforcing. the output of the workshop will be a defined set of community model problems that reflects this intersection of interests.
5 icse workshop on component-based software engineering: benchmarks for predictable assembly. this workshop brings together researchers and practitioners from the community interested in predictable assembly from certifiable components. the goal of this workshop is to ensure continued collaboration among the members of this community. one output of the workshop will be an understanding of composition theory and how it applies to community model problems that were suggested at the workshop on component-based software engineering held at icse in 2001. a second output will be the identification of research opportunities that lie on the perimeter of predictable assembly.
6th icse workshop on component-based software engineering: automated reasoning and prediction. this report gives an overview of the 6th icse workshop on component-based software engineering held at 25th international conference on software engineering. the workshop brought together researchers and practitioners from three communities: component technology, software architecture, and software certification. the primary goal of the workshop was to continue clarifying the concepts, identifying the main challenges and findings of predictable assembly of certifiable software components. this report gives a comprehensive summary of the position papers, of the workshop, its findings, and its results.
check 'n' crash: combining static checking and testing. we present an automatic error-detection approach that combines static checking and concrete test-case generation. our approach consists of taking the abstract error conditions inferred using theorem proving techniques by a static checker (esc/java), deriving specific error conditions using a constraint solver, and producing concrete test cases (with the jcrasher tool) that are executed to determine whether an error truly exists. the combined technique has advantages over both static checking and automatic testing individually. compared to esc/java, we eliminate spurious warnings and improve the ease-of-comprehension of error reports through the production of java counterexamples. compared to jcrasher, we eliminate the blind search of the input space, thus reducing the testing time and increasing the test quality.
dynamically discovering likely interface invariants. dynamic invariant detection is an approach that has received considerable attention in the recent research literature. a natural question arises in languages that separate the interface of a code module from its implementation: does an inferred invariant describe the interface or the implementation? furthermore, if an implementation is allowed to refine another, as, for instance, in object-oriented method overriding, what is the relation between the inferred invariants of the overriding and the overridden method? the problem is of great practical interest. invariants derived by real tools, like daikon, often suffer from internal inconsistencies when overriding is taken into account, becoming unsuitable for some automated uses. we discuss the interactions between overriding and inferred invariants, and describe the implementation of an invariant inference tool that produces consistent invariants for interfaces and overridden methods.
a comparison of communication technologies to support novice team programming. this paper describes an initial investigation of how different conditions for conducting a team programming exercise impact learning. we conducted a series of in-depth case studies on the use of various communication technologies and compared them with face-to-face case studies of team programming. we explored how these communication technologies can help improve students' learning. we summarize the findings from these studies and give guidance to instructors and to tool designers on how future tools can be improved to support collaborative learning in team programming.
exploiting an event-based infrastructure to develop complex distributed systems. the development of complex distributed systems demands for the creation of suitable architectural styles (or paradigms) and related run-time infrastructures. an emerging style that is receiving increasing attention is based on the notion of event. in an event-based architecture, distributed software components interact by generating and consuming events. the occurrence of an event in a component (called source) is asynchronously notified to any other component (called recipient) that has declared some interest in it. this paradigm holds the promise of supporting a flexible and effective interaction among highly reconfigurable distributed software components. we have developed an object-oriented infrastructure, called jedi (java event-based distributed infrastructure), to support the development and operation of event-based systems. during the past year, jedi has been used to implement a significant example of distributed system, namely, the opss workflow management system. the paper illustrates jedi main features and how we have used it to implement the opss workflow management system. moreover, it provides an initial evaluation of our experiences in using an event-based architectural style
from mcc and cmm: technology transfers bright and dim. this paper describes lessons learned during the author's five lives in technology transfer. the author's first life came in general electric's space division where he performed research on software metrics and structured programming, and transferred technology to the pages of technical journals. his second life came at itt's programming technology center where he was responsible for transferring software measurement practices into common use across itt's worldwide software operations. some measurement initiatives survived, but most were short-lived. his third life came in mcc's human interface laboratory and software technology program. mcc's member companies were only occasionally able to transfer the advanced technology they challenged mcc to produce. his fourth life came in directing the software process program at the software engineering institute where he led the team that produced the capability maturity model. although the cmm's transfer was occasionally too rapid to control, the cmm suggested that you should transfer no technology before its time. the author's fifth and current life involves co-founding teraquest and helping companies to improve their software development capability. the paper includes twenty-five lessons in technology transfer and one model.
fifteen years of psychology in software engineering: individual differences and cognitive science. since the 1950's, psychologists have studied the behavioral aspects of software engineering. however, the results of their research have never been organized into a subfield of either software engineering or psychology. this failure results from the difficulty of integrating theory and data from the mixture of paradigms borrowed from psychology. this paper will review some of the psychological research on software engineering performed since the garmisch conference in 1968. this review will be organized under two of the psychological paradigms used in exploring programming problems: individual differences and cognitive science. the major theoretical and practical contributions of each area to the theory and practice of software engineering will be discussed. the review will end with a call for more research guided by the paradigm of cognitive science, since such results are the easiest to integrate with new developments in artificial intelligence and computer science theory.
on building software process models under the lamppost. most software process models are based on the management tracking and control of a project. the popular alternatives to these models such as rapid prototyping and program transformation are built around specific technologies, many of which are still in their adolescence. neither of these approaches describe the actual processes that occur during the development of a software system. that is, these models focus on the series of artifacts that exist at the end of phases of the process, rather than on the actual processes that are conducted to create the artifacts. we conducted a field study of large system development projects to gather empirical information about the communication and technical decision-making processes that underlie the design of such systems. the findings of this study are reviewed for their implications on modeling the process of designing large software systems. the thesis of the paper is that while there are many foci for process models, the most valuable are those which capture the processes that control the most variance in software productivity and quality.
evaluating pattern catalogs: the computer games experience. patterns and pattern catalogs (pattern languages) have been proposed as a mechanism for re-use. traditionally, patterns have been used to foster design re-use, and generative design patterns have been used to achieve both design and code re-use. in theory, a pattern catalog could be created and used to provide re-usable patterns within a project and across a group of related projects. this idea raises a natural question. how can we measure the effectiveness of a pattern catalog or compare the effectiveness of different pattern catalogs? in this paper, we define four metrics that can be used to measure the effectiveness of pattern catalogs. we illustrate these metrics by applying them to a case study that uses a pattern catalog of generative design patterns to generate scripting code for computer games. the metrics are general enough to assess any pattern catalog, independent of application domain or whether the patterns are generative or descriptive.
non-functional requirements: from elicitation to modelling languages. although non-functional requirements (nfrs) have been present in many software development methods, they have been presented as a second or even third class type of requirement, frequently hidden inside notes and therefore, frequently neglected or forgotten. surprisingly, despite the fact that non-functional requirements are among the most expensive and difficult to deal with there are still few works that focus on nfrs as first class requirements. although these works have brought a contribution on how to represent and deal with nfrs, two aspects remain not sufficiently explored: how to elicit nfrs and how to merge these nfrs with conceptual models. our work aims at filling this gap, proposing a strategy to elicit nfrs and to integrate them into conceptual models we focus our attention on conceptual models expressed using uml, and therefore, we propose extensions to uml such that nfrs can be expressed. more precisely, we will show how to integrate nfrs to the class, sequence and collaboration diagrams. we will also show how use cases and scenarios can be adapted to deal with nfrs. this work was validated by three case studies and their results suggest that by using our proposal we can improve the quality of uml models.
reliable software and communication: software quality, reliability, and safety. examines the software development process and suggests opportunities for improving the process by using a combination of statistical and other process control techniques. each phase of the software process affects the ultimate quality, reliability, and safety of the software. control of the process, supported by appropriate tools to collect and analyze data, is essential to improvement of the software product. since the ability to observe, control, and improve software depends on the ability to measure and analyze data drawn from the software process, data collection is central to the approach. detailed data about each of the subprocesses are needed, along with tools to measure and analyze the data. statistical process control techniques, besides improving system reliability, can produce a substantial economic gain in the software development process. the views are based upon experiences with large telecommunications systems
workshop on advances in model-based software testing. the paper summarizes the themes and goals of the workshop on advances in model-based software testing.
workshop on global software development. the goal of this workshop is to bring together researchers and practitioners in trying to understand the emerging phenomenon of global software development. as we witness an increased globalization of software development, it is important that research addresses the challenges of distributed software engineering and informs the development of techniques and technologies to improve such practice.
instructional design and assessment strategies for teaching global software development: a framework. in the context of increasing pressure to adopt global approaches to software development, the importance of teaching skills for geographically distributed software development (gsd) becomes essential. this paper reports the experience of teaching a course to prepare graduates for software engineering (se) in global customer-developer teams, and which was taught in three-university collaboration (canada, australia and italy). the course emphasized the learning of requirements management activities in frequent synchronous computer-mediated client-developer relationships and created a gsd environment with significant time zone and language differences. we describe our instructional approach and assessment strategies within a gsd instructional design framework which integrates (a) required gsd skills and strategies for aligning classroom projects with contemporary and authentic gsd conditions, (b) strategies for assessment of learning of gsd skills and (c) examples from our gsd course.
the 3rd international workshop on global software development. the goal of this workshop is to provide anopportunity for researchers and industry practitioners toexplore both the state-of-the art and the state-of-the-practicein global software development (gsd).increased globalization of software developmentcreates software engineering challenges due to the impactof temporal, geographical and cultural differences, andrequires development of techniques and technologies toaddress these issues. the workshop will foster interactionbetween practitioners and researchers and help grow acommunity of interest in this area. practitionersexperiencing challenges in gsd will share their concernsand successful solutions and learn from research aboutcurrent investigations. researchers addressing gsd willgain a better understanding of the key issues facingpractitioners and share their work in progress with othersin the field.
the role of asynchronous discussions in increasing the effectiveness of remote synchronous requirements negotiations. important and yet very difficult process in software development, requirements engineering is plagued with additional challenges in the emergent dynamics of geographically distributed software teams. our hypothesis is that a mix of lean and rich communication media are needed towards increasing the effectiveness of meetings in reaching mutual agreement when stakeholders are geographically dispersed.we studied tool-supported remote inspections in six educational global project teams in a multicultural software development environment. in this paper we present the preliminary results from comparing the effectiveness of the requirements negotiations when preceded by the asynchronous discussions to those negotiations with no prior asynchronous discussions.
addressing the challenges of software industry globalization: the workshop on global software development. the goal of this workshop is to provide an opportunity for researchers and industry practitioners to explore both the state-of-the art and the state-of-the-practice in global software development (gsd).increased globalization of software development creates software engineering challenges due to the impact of temporal, geographical and cultural differences, and requires development of techniques and technologies to address these issues. the workshop will foster interaction between practitioners and researchers and help grow a community of interest in this area. practitioners experiencing challenges in gsd will share their concerns and successful solutions and learn from research about current investigations. researchers addressing gsd will gain a better understanding of the key issues facing practitioners and share their work in progress with others in the field.
three approximation techniques for astral symbolic model checking of infinite state real-time systems. astral is a high-level formal specification language for real-time systems. it has structuring mechanisms that allow one to build modularized specifications of complex real-time systems with layering. based upon the astral symbolic model checler reported in [13], three approximation techniques to speed-up the model checking process for use in debugging a specification are presented. the techniques are random walk, partial image and dynamic environment generation. ten mutation tests on a railroad crossing benchmark are used to compare the performance of the techniques applied separately and in combination. the test results are presented and analyzed.
using the astral model checker to analyze mobile ip. astral is a high level formal specification language for real time systems. it is provided with structuring mechanisms that allow one to build modularized specifications of complex real time systems with layering. the astral model checker checks the satisfiability of critical requirements of a specification by enumerating possible runs of transitions within a given time bound. the paper discusses the mechanism of the model checker and how it can be used to analyze encryption protocols. several classic benchmarks have been investigated, including the needham-schroeder public-key authentication protocol (r.m. needham and m.d. schroeder, 1978) and the tmn protocol, and a number of attacks were uncovered. the paper focuses on using astral to specify mobile ip (c. perkins, 1996) and testing the specification using the model checker.
an infrastructure for the rapid development of xml-based architecture description languages. research and experimentation in software architectures over the past decade have yielded a plethora of software architecture description languages (adls). continuing innovation indicates that it is reasonable to expect more new adls, or at least adl features. this research process is impeded by the difficulty and cost associated with developing new notations. an architect in need of a unique set of modeling features must either develop a new architecture description language from scratch or undertake the daunting task of modifying an existing language. in either case, it is unavoidable that a significant effort will be expended in building or adapting tools to support the language. to remedy this situation, we have developed an infrastructure for the rapid development of new architecture description languages. key aspects of the infrastructure are its xml-based modular extension mechanism, its base set of reusable and customizable architectural modeling constructs, and its equally important set of flexible support tools. this paper introduces the infrastructure and demonstrates its value in the context of several real-world applications.
using off-the-shelf middleware to implement connectors in distributed software architectures. software architectures promote development focused on modular building blocks and their interconnections. since architecture-level components often contain complex functionality, it is reasonable to expect that their interactions will also be complex. modeling and implementing software connectors thus becomes a key aspect of architecture-based development. software interconnection and middleware technologies such as rmi, corba, ilu, and activex provide a valuable service in building applications from components. the relation of such services to software connectors in the context of software architectures, however, is not well understood. to understand the tradeoffs among these technologies with respect to architectures, we have evaluated several off-the-shelf middleware technologies and identified key techniques for utilizing them in implementing software connectors. our platform for investigation was c2, a component- and message-based architectural style. by encapsulating middleware functionality within software connectors, we have coupled c2's existing benefits such as component interchangeability, substrate independence and structural guidance with new capabilities of multi-lingual, multi-process and distributed application development in a manner that is transparent to architects.
twenty dirty tricks to train software engineers. many employers find that graduates and sandwich students come to them poorly prepared for the every day problems encountered at the workplace. although many university students undertake team projects at their institutions, an education environment has limitations that prevent the participants experiencing the full range of problems encountered in the real world. to overcome this, action was taken on courses at the plessey telecommunications company and loughborough university to disrupt the students' software development progress. these actions appear mean and vindictive, and are labeled 'dirty tricks' in this paper, but their value has been appreciated by both the students and their employers. the experiences and learning provided by twenty 'dirty tricks' are described and their contribution towards teaching essential workplace skills is identified. the feedback from both students and employers has been mostly informal but the universally favourable comments received give strong indications that the courses achieved their aim of preparing the students for the workplace. the paper identifies some limitations on the number and types of 'dirty tricks' that can be employed at a university and concludes that companies would benefit if such dirty tricks were employed in company graduate induction programmes as well as in university courses.
a systematic approach to derive the scope of software product lines. product line scoping is a critical activity because it elicits the common realms upon which the different products of a product line can be optimally engineered with respect to economies of scope. this, in turn, upper bounds the overall economic benefits that can be accrued from product line based development. inherently, product line scoping is difficult because of the complexity of the factors that must be taken into account. many are not known a priori. traditional scoping approaches (from domain engineering) have focused on the notion of application domains. however, domains proved difficult to optimally scope and engineer from an enterprise standpoint because a domain captures extraneous elements that are of no interest to an enterprise which must focus on particular products, whether existing, under development, or anticipated. hence, the domain view provides a flawed economic basis for making a scoping decision. we introduce pulse-eco, a technique especially developed to address the aforementioned issues. its main characteristics are: a complete product-centric orientation done via product maps, the separation of concerns achieved through the definition and operationalization of strategic business objectives, and last, diverse types of analyses performed upon product maps allowing scoping decisions based on these objectives. we illustrate the technique with a running example.
avoiding packaging mismatch with flexible packaging. to integrate a software component into a system, it must interact properly with the system's other components. unfortunately, the decisions about how a component is to interact with other components are typically committed long before the moment of integration and are difficult to change. this paper introduces the flexible packaging method, which allows a component developer to defer some decisions about component interaction until system integration time. the method divides the component's source into two pieces: the ware, which encapsulates the component's functionality; and the packager, which encapsulates the details of interaction. both the ware and the packager are independently reusable. a ware, as a reusable part, allows a given piece of functionality to be employed in systems in different architectural styles. a packager, as a reusable part, encapsulates conformance to a component standard, like an activex control or an odbc database accessor. because the packager's source code is often formulaic, a tool is provided to generate the packager's source from a high-level description of the intended interaction, a description written in the architectural description language unicon. the method and tools are evaluated with a series of experiments in which three wares and nine types of packaging are combined to form thirteen components.
programmer performance and the effects of the workplace. wide variation in programmer performance has been frequently reported in the literature [1, 2, 3]. in the absence of other explanation, most managers have come to accept that the variation is due to individual characteristics. the presumption that there are order-of-magnitude differences in individual performance makes accurate cost projection seem nearly impossible. in an extensive study, 166 programmers from 35 different organizations, participated in a one-day implementation benchmarking exercise. while there were wide variations across the sample, we found evidence that characteristics of the workplace and of the organization seemed to explain a significant part of the difference.
syncro: a dataflow command shell for the lilith/modula computer. syncro is a two-dimensional command interpreter that allows human interface through a graphic command language. this paper describes the concept of two-dimensional commands for direct implementation of leveled data flow structures, and comments on the syncro scheme for effecting them. syncro is implemented in modula-2 on niklaus wirth's lilith/modula computer.
progress toward automated software testing. mothra is an integrated environment for automated software validation. using mothra, a tester can create and execute test cases, measure test case adequacy, determine input-output correctness, locate and remove faults or bugs, and control and document the test. there are no size constraints built into the design of the environment. a goal of the research has been to exploit computational opportunities in each of the major subtasks of software validation. the author has attempted to reduce test case generation, measurement of the effectiveness of test cases, input-output correctness checking, and debugging to one or more computational metaphors and to design the appropriate algorithms. the result is a system where there is a high degree of control over the apparent cost of testing
role-based exploration of object-oriented programs. we present a new technique for helping developers understand heap properties of object-oriented programs and how the actions of the program affect these properties. our dynamic analysis uses the aliasing properties of objects to synthesize a set of roles; each role represents an abstract object state intended to be of interest to the developer. we allow the developer to customize the analysis to explore the object states and behavior of the program at multiple different and potentially complementary levels of abstraction.the analysis uses roles as the basis for three abstractions: role transition diagrams, which present the observed transitions between roles and the methods responsible for the transitions; role relationship diagrams, which present the observed referencing relationships between objects playing different roles; and enhanced method interfaces, which present the observed roles of method parameters.together, these abstractions provide useful information about important object and data structure properties and how the actions of the program affect these properties. we have used our implemented role analysis to explore the behavior of several java programs. our experience indicates that, when combined with a powerful graphical user interface, roles are a useful abstraction for helping developers explore and understand the behavior of object-oriented programs.
data structure repair using goal-directed reasoning. data structure repair is a promising technique for enabling programs to execute successfully in the presence of otherwise fatal data structure corruption errors. previous research in this field relied on the developer to write a specification to explicitly translate model repairs into concrete data structure repairs, raising the possibility of 1) incorrect translations causing the supposedly repaired concrete data structures to be inconsistent, and 2) repaired models with no corresponding concrete data structure representation.we present a new repair algorithm that uses goal-directed reasoning to automatically translate model repairs into concrete data structure repairs. this new repair algorithm eliminates the possibility of incorrect translations and repaired models with no corresponding representation as concrete data structures.
an empirical evaluation of fault-proneness models. planning and allocating resources for testing is difficult and it is usually done on empirical basis, often leading to unsatisfactory results. the possibility of early estimating the potential faultiness of software could be of great help for planning and executing testing activities. most research concentrates on the study of different techniques for computing multivariate models and evaluating their statistical validity, but we still lack experimental data about the validity of such models across different software applications.this paper reports an empirical study of the validity of multivariate models for predicting software fault-proneness across different applications. it shows that suitably selected multivariate models can predict fault-proneness of modules of different software packages.
the project library : a tool for software development. the project library presented in this article insures the harmonious development of the documentation for a software system in tandem with the development of the system itself. it offers the programmer a well-defined framework for his work, and gives management an articulate means for planning and control. the structure of the project library is defined by three dimensions: (1) systems structure (modularization), (2) standard organization and (3) development status. the project library has been realized as a system of files on the programm-entwicklungs-terminalsystem pet/x1150 (known in the usa as maestro) and supported by an appropriate variety of pet-procedures. our experience with the project library, specifically in the start project, has been very positive and instructive.
resolving component deployment & configuration challenges for enterprise dre systems via frameworks & generative techniques. component-based software engineering (cbse) is increasingly being adopted for large-scale software systems, particularly for enterprise distributed real-time and embedded (dre) systems. one of the most challenging-and often most neglected-problems in cbse for enterprise dre systems is the system (re)deployment and (re)configuration (d&c) process, where the increasing heterogeneity and versatility of application domains requires supports for an unprecedented level of configurability and adaptability. existing d&c technologies suffer from two major problems: (1) insufficient module-level reusability and ability to evolve in the face of functionality evolution and diversification due to the interaction of too many orthogonal concerns imposed by a wide range of application requirements and (2) significant inherent and accidental complexities stemming from inadequate design tools. to address these problems, my research focuses on improving both computing performance and human productivity associated with the d&c of component-based enterprise dre systems. to improve computing performance, my research has systematically identified bottlenecks with conventional d&c approaches and provides an aspect-oriented approach to decouple "extrinsic" orthogonal d&c concerns from "intrinsic" core d&c infrastructure, thereby enabling different crosscutting d&c concerns to be weaved independently to create a light-weight, highly optimized and extensible d&c infrastructure. to improve human performance, my research provides model-driven tools and analysis techniques to alleviate key inherent and accidental complexities in the d&c process.
invariant-based specification, synthesis, and verification of synchronization in concurrent programs. concurrency is used in modern software systems as a means of addressing performance, availability, and reliability requirements. the collaboration of multiple independently executing components is fundamental to meeting such requirements and such collaboration is realized by synchronizing component execution.using current technologies developers are faced with a tension between correct synchronization and performance. developers can be confident when simple forms of synchronization are used, for example, locking all accesses to shared data. unfortunately, such simple approaches can result in significant run-time overhead, and, in fact, there are many cases in which such simple approaches cannot implement required synchronization policies. implementing more sophisticated (and less constraining) synchronization policies may improve run-time performance and satisfy synchronization requirements, but fundamental difficulties in reasoning about concurrency make it difficult to assess their correctness.this paper describes an approach to automatically synthesizing complex synchronization implementations from formal high-level specifications. moreover, the generated coded is designed to be processed easily by software model-checking tools such as bandera. this enables the generated synchronization solutions to be verified for important system correctness properties. we believe this is an effective approach because the tool-support provided makes it simple to use, it has a solid semantic foundation, it is language independent, and we have demonstrated that it is powerful enough to solve numerous challenging synchronization problems.
testing database transactions with agenda. agenda is a tool set for testing relational database applications. an earlier prototype was targeted to applications consisting of a single query and included components for populating a database with data suitable for testing the application, generating inputs to the query, and checking relatively simple aspects of the results of executing the query. this paper describes substantial extensions to agenda, allowing it to test transactions with multiple queries and with complex intended behavior. the paper introduces a technique for checking complex properties of the database state transition performed by the transaction under test, as well as an improved input generation heuristic. results of using agenda to test three applications with seeded faults are presented.
addressing crosscutting deployment and configuration concerns of distributed real-time and embedded systems via aspect-oriented & model-driven software development. model-driven development (mdd) is gaining importance as an approach to resolving lifecycle challenges of large-scale distributed real-time and embedded (dre) systems (e.g., avionics mission computing). dre systems are characterized by their stringent requirements for quality of service (qos), such as predictable end-to-end latencies, timeliness and scalability. delivering the qos needs of dre systems entails the need to configure correctly, fine tune and provision the infrastructure used to host the dre systems, which crosscuts different layers of middleware, operating systems and networks. addressing these tangled deployment and configuration concerns of dre systems requires integrating the principles of aspect-oriented software development (aosd) with mdd. this demo showcases a set of software tools that resolve both the inherently and accidental complexities arising due to the configuration and deployment crosscutting concerns of component middleware-based dre systems.
sacificing the calf of flexibility on the altar of reliability. a pattern of conflict between flexibility and reliability in system designs is examined.
the evolution of programs: program abstraction and instantiation. our goal is to develop techniques for abstracting a given set of concrete programs into a program schema and for instantiating a schema to satisfy concrete specifications. for example, from two programs using the binary-search method, one to compute quotients and another to compute cube-roots, an abstract schema is derived that embodies the method and that can be instantiated to solve similar new problems. we suggest the formulation of analogies as a basic tool in program abstraction. an analogy is first sought between the specifications of the given programs; this yields an abstract specification that may be instantiated to any of the given concrete specifications. the analogy is then used as a basis for transforming the existing programs into an abstract schema that represents the embedded technique. the invariant assertions and correctness proofs of the given programs are used to complete the analogy.
inference rules for program annotation. methods are presented whereby an algol-like program given together with its specifications can be documented automatically. the program is incrementaly annotated with invariant relations that hold between program variables at intermediate points in the program text and explain the actual workings of the program regardless of whether it is correct. thus, this documentation can be used for proving correctness of programs or may serve as an aid in debugging incorrect programs.
identifying objects using cluster and concept analysis. many approaches to support (semi-automatic) identification of objects in legacy code take the data structures as starting point for candidate classes. unfortunately, legacy data structures tend to grow over time, and may contain many unrelated fields at the time of migration. we propose a method for identifying objects by semi-automatically restructuring the legacy data structures. issues involved include the selection of record fields of interest, the identification of procedures actually dealing with such fields, and the construction of coherent groups of fields and procedures into candidate classes. we explore the use of cluster and concept analysis for the purpose of object identification, and we illustrate their effect on a 100,000 loc cobol system. furthermore, we use these results to contrast clustering with concept analysis techniques.
software architecture reconstruction. architecture reconstruction is the reverse engineeringprocess that aims at recovering the past design decisionsthat have been made about the software architecture ofa system. to be a successful activity, we need to identifythe proper architecturally significant information andto extract it from the artefacts. how to identify extract/present/analyse it ? what are the critical issues that have to be considered ? how to manage the reconstructionprocess in a product family ? what tools are available? this tutorial will address these and other questions that are relevant for the development of large and complex softwaresystems. we introduce the key concepts of a softwarearchitecture description and the context of the architecturereconstruction activity. we present our architecture reconstructionmethod with a strong emphasis on its practicalaspects and the tools supporting it. the extraction of architecturallysignificant information and its analysis are thekey goals of our approach that will be demonstrated with aset of examples taken from real cases. we derive our experiencemainly from the telecommunication domain. however,we believe the same general principles can be applied toother domains. the tutorial addresses software engineersand project managers that are involved in the developmentof complex software systems.
chime: customizable hyperlink insertion and maintenance engine for software engineering environments. source code browsing is an important part of program comprehension. browsers expose semantic and syntactic relationships (such as between object references and definitions) in gui-accessible forms. these relationships are derived using tools which perform static analysis on the original software documents. implementing such browsers is tricky. program comprehension strategies vary, and it is necessary to provide the right browsing support. analysis tools to derive the relevant cross-reference relationships are often difficult to build. tools to browse distributed documents require extensive coding for the gui, as well as for data communications. therefore, there are powerful motivations for using existing static analysis tools in conjunction with www technology to implement browsers for distributed software projects. the chime framework provides a flexible, customizable platform for inserting html links into software documents using information generated by existing software analysis tools. using the chime specification language, and a simple, retargetable database interface, it is possible to quickly incorporate a range of different link insertion tools for software documents, into an existing, legacy software development environment. this enables tool builders to offer customized browsing support with a well-known gui. this paper describes the chime architecture, and describes our experience with several re-targeting efforts of this system.
techniques for trusted software engineering. how do we decide if it is safe to run a given piece of software on our machine? software used to arrive in shrink-wrapped packages from known vendors. but increasingly, software of unknown provenance arrives over the internet as applets or agents. running such software risks serious harm to the hosting machine. risks include serious damage to the system and loss of private information. decisions about hosting such software are preferably made with good knowledge of the software product itself, and of the software process used to build it. we use the term trusted software engineering to describe tools and techniques for constructing safe software artifacts in a manner designed to inspire trust in potential hosts. existing approaches have considered issues such as schedule, cost and efficiency; we argue that the traditionally software engineering issues of configuration management and intellectual property protection are also of vital concern. existing approaches (e.g., java) to this problem have used static type checking, run-time environments, formal proofs and/or cryptographic signatures; we propose the use of trusted hardware in combination with a key management infrastructure as an additional, complementary technique for trusted software engineering, which offers some attractive features
analytical and empirical evaluation of software reuse metrics. how much can be saved by using existing software components when developing new software systems? with the increasing adoption of reuse methods and technologies, this question becomes critical. however, directly tracking the actual cost savings due to reuse is difficult. a worthy goal would be to develop a method of measuring the savings indirectly by analyzing the code for reuse of components. the focus of the paper is to evaluate how well several published software reuse metrics measure the "time, money and quality" benefits of software reuse. we conduct this evaluation both analytically and empirically. on the analytic front, we introduce some properties that should arguably hold of any measure of "time, money and quality" benefit due to reuse. we assess several existing software reuse metrics using these properties. empirically, we constructed a toolset (using gen+s) to gather data on all published reuse metrics from cs+ code; then, using some productivity and quality data from "nearly replicated" student projects at the university of maryland, we evaluate the relationship between the known metrics and the process data. our empirical study sheds some light on the applicability of our different analytic properties, and has raised some practical issues to be addressed as we undertake broader study of reuse metrics in industrial projects.
automated construction of testing and analysis tools. many software testing and analyse's tools manipulate graph representations of programs, such as abstract syntax trees or abstract semantics graphs. hand-crafting such tools in conventional programming languages can be difficult, error prone, and time consuming. our approach is to use application generators targeted for the domain of graph-representation-based testing and analysis tools. moreover, we generate the generators themselves, so that the development of tools based on different languages and/or representations can also be supported better. in this paper we report on our experiences in developing a system called aria that generates testing and analysis tools based on an abstract semantics graph representation for c and c++ cabled reprise. aria itself was generated by the genoa system. we demonstrate the utility of aria and, thereby, the pourer of our approach, by showing aria's use in the development of a tool that derives control dependence graphs directly from reprise abstract semantics graphs
forcing behavioral subtyping through specification inheritance. a common change to object-oriented software is to add a new type of data that is a subtype of some existing type in the program. however, due to message passing, unchanged pearls of the program may now call operations of the new type. to avoid reverification of unchanged code, such operations should have specifications that are related to the specifications of the appropriate operations in their supertypes. this paper presents a specification technique that uses inheritance of specifications to force the appropriate behavior on the subtype objects. this technique is simple, requires little effort by the specifier, and avoids reverification of unchanged code. we present two notions of such behavioral subtyping, one of which is new. we show how to use these techniques to specify examples in c++.
backwards-compatible array bounds checking for c with very low overhead. the problem of enforcing correct usage of array and pointer references in c and c++ programs remains unsolved. the approach proposed by jones and kelly (extended by ruwase and lam) is the only one we know of that does not require significant manual changes to programs, but it has extremely high overheads of 5x-6x and 11x-12x in the two versions. in this paper, we describe a collection of techniques that dramatically reduce the overhead of this approach, by exploiting a fine-grain partitioning of memory called automatic pool allocation. together, these techniques bring the average overhead checks down to only 12% for a set of benchmarks (but 69% for one case). we show that the memory partitioning is key to bringing down this overhead. we also show that our technique successfully detects all buffer overrun violations in a test suite modeling reported violations in some important real-world programs.
finding failures by cluster analysis of execution profiles. we experimentally evaluate the effectiveness of using cluster analysis of execution profiles to find failures among the executions induced by a set of potential test cases. we compare several filtering procedures for selecting executions to evaluate for conformance to requirements. each filtering procedure involves a choice of a sampling strategy and a clustering metric. the results suggest that filtering procedures based on clustering are more effective than simple random sampling for identifying failures in populations of operational executions, with adaptive sampling from clusters being the most effective sampling strategy. the results also suggest that clustering metrics that give extra weight to unusual profile features are most effective. scatter plots of execution populations, produced by multidimensional scaling, are used to provide intuition for these results.
software visualization. this half-day tutorial gives an overview of the current state-of-the-art in software visualization. software visualization encompasses the development and evaluation of methods for graphically representing different aspects of software, including its structure, its execution, and its evolution. in contrast to visual programming and diagramming for software design, software visualization is not so much concerned with the construction, but with the analysis of programs and their development process. software visualization combines techniques from areas like software engineering, programming languages, data mining, computer graphics, information visualization and human-computer interaction. topics covered in this tutorial include static program visualization, algorithm animation, visual debugging, as well as the visualization of the evolution of software. in particular we identify common principles illustrated by many examples and give pointers to tools available today.
computer-assisted assume/guarantee reasoning with verisoft. we show how the state space exploration tool verisoft can be used to analyze parallel c/c++ programs compositionally. verisoft is used to check assume/guarantee specifications of parallel processes automatically. the analysis is meant to complement standard assume/guarantee reasoning which is usually carried out solely with "pencil and paper". while a successful analysis does not always imply the general correctness of the specification, it increases the confidence in the verification effort. an unsuccessful analysis always produces a counterexample which can be used to correct the specification or the program. verisoft's optimization and visualization techniques make the analysis relatively efficient and effective.
an empirical study of an informal knowledge repository in a medium-sized software consulting company. numerous studies have been conducted on design and architecture of knowledge repositories. this paper addresses the need for looking at practices where knowledge repositories are actually used in concrete work situations. this insight should be used when developing knowledge repositories in the future.through methods inspired by ethnography this paper investigates how an unstructured knowledge repository is used for different purposes by software developers and managers in a medium-sized software consulting company. the repository is a part of the company's knowledge management tool suite on the intranet. we found five distinct ways of using the tool, from solving specific technical problems to getting an overview of competence in the company. we highlight the importance of informal organization and the social integration of the tool in the daily work practices of the company.
progressive open source. the success of several open source&trade; software systems, e.g., apache, bind, emacs, and linux, has recently sparked interest in studying and emulating the software engineering principles underlying this innovative development and use model. certain aspects of the open source development method, e.g., community building, open discussions for requirements and features, and evolvable and modular designs are having fundamental and far reaching consequences on general software engineering practices.to leverage such open source methods and tools, we have defined an innovative software engineering paradigm for large corporations: progressive open source (pos). pos leverages the power of open source methods and tools for large corporations in a progressive manner: starting from completely within the corporation, to include partner businesses, and eventually complete open source. in this paper we present the design goals and principles for pos. we illustrate pos with two programs in hp: corporate source and the collaborative development program (cdp). we present early results from both these programs suggesting the power and necessity of pos for all modern large corporations.
redesigning legacy applications for the web with uwat+: a case study. this paper reports on a case study of redesigning a legacy application for the web using the ubiquitous web applications design framework with an extended version of its transaction design model (uwat+). web application design methodologies hold the promise of engineering high-quality and long-lived web systems and rich internet applications. however, many such techniques focus solely on green-field development, and do not properly address the situation of leveraging the value locked in legacy systems. the redesign process supported by uwat+ holistically blends design recovery technologies for capturing the know-how embedded in the legacy application with forward design methods particularly well suited for web-based systems. the case study highlights some of the benefits of using uwat+ in this context, as well as identifying possible areas for improvement in the redesign process and opportunities for tool automation to support it.
integrated support for project management. conventional `off-line` project management tools are being overtaken by integrated project support environments which are capable of imposing more direct control over project activities. such environments can lead to a more systematic approach to planning, monitoring and controlling software development. this paper describes the facilities offered by istar for integrated support of project management.
software engineering in avionics applications. flight control for commercial aircraft has to fulfil stringent requirements. this paper describes first the main lines of the system development process in order to situate the software validation problem which is only a part of the whole validation exercise. the appropriate methods and tools used in the different software development stages are then presented. a great deal of our attention was in the software analysis stage (preliminary design) for which a software decomposition approach, a software integration strategy and a managerial procedure was developed. real-time testing also deserved a great deal of effort. a full set of real-time facilities was created around our airborne computer (ump 7800) which is a software oriented machine whose essential features are roughly described in the paper. special emphasis is given to a hardware device (trace) connected to the computer bus which is capable to check and record critical numerical data and program paths. finally some quantitative evaluation of the methodologies we use are given based on some of our avionics projects.
using the balanced scorecard process to compute the value of software applications. this paper describes a method that will provide practical help for it managers and other enterprise executives who want to determine the value of their software projects. a set of measures is described that can help the it manager determine the value of it projects, either at the time a project is initiated or at the time the project is operational. this paper identifies relevant performance measures used in the balanced scorecard process and then maps them to it benefits: which are categorized by strategic, informational, and transactional dimensions. the appropriate measure can be identified and value quantified based upon the expected it benefit.
the leap load and test driver. leap is a facility for testing interactive applications that are implemented on ibm system/360 and system/370 computers; it simulates concurrently the actions of several ibm 3270-type terminals and of their operators. leap allows one to organize, in a systematic and efficient fashion, a large-scale, repeatable testing program for such an interactive application system. leap is one of the tools of the programmer's work-bench. it operates under the unix time sharing system; all test preparation, testing, and test analysis is performed at a unix terminal. leap can be used for both regression (functional) testing and load (stress and performance) testing. several post-test analysis tools are provided.
an introduction to the programmer's workbench. the programmer's workbench (pwb) is a specialized computing facility dedicated to satisfying the needs of developers of computer programs. the pwb might well be called a &ldquo;human-end&rdquo; computer; like &ldquo;front-end&rdquo; and &ldquo;back-end&rdquo; computers, it improves productivity by efficient specialization. it provides a convenient working environment and a uniform set of programming tools to a diverse group of programming projects. these projects produce software for various &ldquo;target&rdquo; computers, including ibm system/370 and univac 1100 systems of much greater size than the pwb machines. the projects range in size from several people up to several hundred. the first pwb machine was installed in october, 1973; usage, acceptance, and interest have grown rapidly since that time. the pwb currently supports about 110 time-sharing terminals, utilizing a network of four dec pdp-11 computers, all running the unix time-sharing system. the pwb adds tools to unix to support large projects. this paper gives an overview of the pwb and its development; further details appear in the five following companion papers [bia76a, dol76b, knu76a, mas76a, mas76b].
imposing a memory management discipline on software deployment. the deployment of software components frequently failsbecause dependencies on other components are not declaredexplicitly or are declared imprecisely. this resultsin an incomplete reproduction of the environment necessaryfor proper operation, or in interference between incompatiblevariants. in this paper we show that these deploymenthazards are similar to pointer hazards in memory models ofprogramming languages and can be countered by imposinga memory management discipline on software deployment.based on this analysis we have developed a generic, platformand language independent, discipline for deploymentthat allows precise dependency verification; exact identification of component variants; computation of complete closures containing all components on which a component depends;maximal sharing of components between such closures;and concurrent installation of revisions and variantsof components. we have implemented the approach in thenix deployment system, and used it for the deployment of alarge number of existing linux packages. we compare its effectivenessto other deployment systems.
a logical framework for design composition. the design of a large component-based software system typically involves the composition of different components. the lack of rigorous reasoning about the correctness of composition is an important barrier towards the promise of &ldquo;plug and play&rdquo;. in this paper, we describe a rigorous logic framework to reason about component compositions. we focus our analysis on design components, such as design patterns, which have been used by a large number of applications. we also propose methods to verify structural and behavioral composition correctness.
state, event, time and diagram in system modeling. the design of complex systems requires powerful mechanisms for modeling state, concurrent events, and real-time behavior; as well as for visualising and structuring systems in order to control complexity. methods integration has become a recent research trend in software specification and design. in the graphical area, many object-oriented methods have merged into one, the unified modeling language (uml) which combines various diagrammatic modeling techniques to model static and dynamic aspects of software systems. although traditional formal methods have not scale-up well, new integrated formal methods show great promise. this tutorial will present the state of the art in formal modeling techniques (state-based object-z and event-based timed csp), their integration (tcoz), and transformation techniques from the integrated formalism to uml diagrams. an xml web environment for projecting integrated formal models to uml diagrams will also be demonstrated.
from semantic web to expressive software specifications: a modeling languages spectrum. many researchers at w3c currently focus on developing the next generation of the web --- the semantic web. the development of the web ontology languages, rdf, owl and swrl, is reminiscent of the early development of system specification languages in software engineering communities. indeed, from the expressiveness point of view, web ontology languages are subsets of alloy, uml/ocl, vdm, z and object-z. one can futher predict that the modeling languages for capturing the behaviours of the semantic web services and agents can be drawn from the rich collections of software dynamic modeling techniques, i.e., state machines, process algebra and integrated design methods. this tutorial will present a concise modeling languages spectrum that includes a few key representative modeling languages ranging from simple static web ontology modeling techniques to expressive dynamic integrated modeling techniques. comparisons and transformations between those languages will be discussed. furthermore, based on transformation approaches, the latest research results on applying software modeling techniques and tools to the semantic web domain will be also demonstrated.
highspec: a tool for building and checking ozta models. highspec is an interactive system for composing and checking ozta specifications. the integrated high level specification language, ozta, is a combination of object-z (oz) and timed automata (ta). building on the strength of object-z's in specifying data structures and timed automata's in modelling dynamic and real-time behaviors, ozta is well suited for presenting complete and coherent requirement models for complex real-time systems. highspec supports editing, type-checking as well as projecting ozta models into ta models and alloy models so that ta model checkers-uppaal and the alloy analyzer can be utilized for verification. most importantly, highspec supports a novel yet effective mechanism advocated by ozta for structural ta design, i.e., using a set of composable timed patterns to capture high level timing requirements and process behaviors and generate the ta part of model in a top-down way. highspec can also generate latex document as an alternative media for the spread and read of established ozta models.
verifying daml+oil and beyond in z/eves. semantic web, the next generation of web, gives datawell-defined and machine-understandable meaning so thatthey can be processed by remote intelligent agents cooperatively.ontology languages are the building blocks of semanticweb as they prescribe how data are defined and related.the existing reasoning and verification tools for semanticweb are improving however still elementary. we believethat semantic web can be a novel application domainfor software modeling languages and tools. z is aformal modeling language for specifying software systemsand z/eves is a proof tool for z. in this paper, we firstlypresent z semantics for ontology language daml+oil.this semantic model is embedded as a z section daml2zinz/eves, which serves as an environment for checking andverifying web ontologies. then we present a tool for automaticallytransforming ontology documents into the specializedz codes understood by z/eves. finally, we usea recent real application, the military plan ontologies, todemonstrate the different reasoning tasks that z/eves canperform. furthermore, undiscovered errors in the originalontologies were found by z/eves and some of these errorsare even beyond semantic web modeling and reasoning capabilities.
practical applications of a syntax directed program manipulation environment. we present applications in various domains of a system built around a syntax directed editor: the mentor system. the main characteristics of the system are the abstract representation of data, programmability of the command language, and language independance. the applications presented belong to the area of program editing and manipulation, extensions of programming languages through the development of preprocessors, processing of multi-formalism documents and program portability.
iteration in the software process: review of the 3rd international software process workshop. the 3rd international process workshop, with the theme 'iteration in the software process' was held in colorado in november 1986. iteration, which was taken to subsume 'backtracking', 'rework', 'repetition' and so on, seems to be central to the software process; selecting it as a main topic allowed intensive consideration of many of the key problems that face software engineering. much of the workshop discussion focused on the concept of executable representations of the process, exemplified by osterweil's process programs. the general conclusion was that exploring the process programming paradigm and its limitations would prove a fruitful area for investigation in the near term.
istar and the contractual approach. istar is a production-quality project support environment that was first released commercially during 1986. istar is language and method independent, supports distributed projects, is portable and includes a rich and open ended tool set; its architecture and tools are described more fully elsewhere (see [dowson87a]). this description concentrates on the underlying approach to software development built in to istar and its relationship to various views of the software process.istar is organized to support a powerful and general approach to software development, the contractual approach. the essence of the contractual approach is that it views every task in a software project as having the nature of a contract; that is, a well defined package of work that can be performed independently by a contractor for a client. contract specifications, of course, can include acceptance tests for contract deliverables, schedules, requirements s to standards which must be adhered to, obligations to make periodic reports and so on. but the key point is that the contractor is free to decide how to fulfill the contract specification. in general, this freedom includes the ability to let subcontracts to perform all or part of the work, and so on recursively.support for this approach is built into the structure of istar which creates independent contract databases for the execution of each contract. in addition, istar provides contractual operations for assigning contracts, amending or cancelling them when necessary, accepting their deliverables and communicating formal reports between them. using istar to support a project, then, results in the creation of a dynamic hierarchy of contracts (and their contract databases) which corresponds to the organization of the project. it is important to note that the hierarchy is organizational, and that its structure is determined by more or less autonomous decsions by contractors (project staff) at various levels. another way of saying this is that the contractual approach does not prescribe a particular software process &mdash; but is capable of providing effective support for a wide variety of processes. for example, the 'root' contract in a project hierarchy (the initial contract for the project as a whole) could let subcontracts for successive phases of the work such as 'specification', 'design', 'code', 'integrate', 'test', following a simple waterfall model of development. alternatively, the first level subcontracts could follow a functional division and each be for the complete development of a part of the system. of course, the contractual approach does constrain the process to be hierarchical, and insists that everyone in a project knows what they are supposed to be doing and for whom. but this reflects the observation that most effective processes have these minimum properties.in either case, the specifications of the initial ontracts might or might not include transitive obligations to organize subhierarchies in the same way, or even prescribe or forbid further subcontracting. thus, the degree of autonomy that can be exercised by project staff is, quite properly, under managerial control, with istar providing flexible mechanisms to support it. in practice, the degree of autonomy allowed is likely to vary throughout the contract hierarchy; the overall project manager will grant his group managers considerable freedom to organize their assigned work, while junior programmers will get clear instructions on how to proceed from their team leaders. as usual, the power of the approach is exposed when examining what happens when things go wrong rather than what happens when they go right. when a contractor cannot complete an assigned task within its schedule, or with the available resources, or at all, some sort of 'iteration' ([downson87b]) is required. at this stage it is worth noting that the contractual operations, and the contractually required reports that they help provide, are not intended to replace the normal informal or semi-formal (eg project meeting) within-project communication mechanisms, but to supplement them with formal communication paths that are guaranteed to correspond to the formal organization of the project. contractors will thus get formal notification of subcontract problems (either via one of the reports required in the subcontract specification or by the absence of a scheduled deliverable), but corrective action may well be triggered by prior information acquired by less formal routes.what does the contractor do? there are two options: deal with the problem. providing that it can be done while remaining within the constraints of the contract specification, the contractor is free to re-organize the contract work as much as necessary. this might be as simple as finding some additional resources to staff one new subcontract (the problematic subcontract will have to have its specification modified, of course), or as extensive as cancelling all the existing subcontracts, effectively deleting the complete sub-hierarchy, re-planning the work and issuing a new set of subcontracts. pass the problem up the hierarchy. the client (that is, the contractor at the next level in the hierarchy) will now have the same two options available to resolve the problem. as usual, the power of the approach is exposed when examining what happens when things go wrong rather than what happens when they go right. when a contractor cannot complete an assigned task within its schedule, or with the available resources, or at all, some sort of 'iteration' ([downson87b]) is required. at this stage it is worth noting that the contractual operations, and the contractually required reports that they help provide, are not intended to replace the normal informal or semi-formal (eg project meeting) within-project communication mechanisms, but to supplement them with formal communication paths that are guaranteed to correspond to the formal organization of the project. contractors will thus get formal notification of subcontract problems (either via one of the reports required in the subcontract specification or by the absence of a scheduled deliverable), but corrective action may well be triggered by prior information acquired by less formal routes.what does the contractor do? there are two options: deal with the problem. providing that it can be done while remaining within the constraints of the contract specification, the contractor is free to re-organize the contract work as much as necessary. this might be as simple as finding some additional resources to staff one new subcontract (the problematic subcontract will have to have its specification modified, of course), or as extensive as cancelling all the existing subcontracts, effectively deleting the complete sub-hierarchy, re-planning the work and issuing a new set of subcontracts. pass the problem up the hierarchy. the client (that is, the contractor at the next level in the hierarchy) will now have the same two options available to resolve the problem. istar goes further than many environments by retaining a permanent record of all contractual operations executed in the course of a project. although these operations are essentially local, the record of them constitutes an implicit description of the process followed. this is a step in the right direction. future environments will need to make these descriptions explicit so that they can be used as a basis for progressively improving the software process.
approach and case study of requirement analysis where end users take an active role. in the traditional approach to software analysis, systems analysts interview end users to capture requirements. the authors propose an approach called automated user requirements acquisition (aura) where end users take an active role in analysis by identifying requirements. this approach takes advantage of end users domain knowledge. aura uses a question-and-answer model to guide end users in describing their problem. additionally, aura provides problem domain knowledge to suggest answers for the questions. the business application domain was selected to explain and demonstrate the approach. while the aura approach can benefit any analysis technique, an object-oriented analysis technique was selected as the underlying method. a prototype tool, aura-biz, was developed to demonstrate aura in the business domain. aura-biz was evaluated through a case study where end users created the analyses of their business problem. the data collected showed that the end users successfully modeled their problem by following the questions and using the suggestions
software engineering for user interfaces. the discipline of software engineering can be extended in a natural way to deal with the issues raised by a systematic approach to the design of human-machine interfaces. two main points are made: that the user should be treated as part of the system being designed, and that projects should be organized to take account of the current (small) state of a priori knowledge about how to design interfaces.
simulation in software engineering training. simulation is frequently used for training in many application areas like aviation and economics, but not in software engineering. we present the sesam project which focuses on software engineering education using simulation. in the sesam project a simulator was developed. using this simulator, a student can take the role of a software project manager. the simulated software project can be finished within a couple of hours because it is simulated in &ldquo;quick-motion&rdquo; mode.in this paper, the background and goals of the sesam project are presented. a new simulation model, the so called qa model, is introduced. the model behavior is demonstrated by investigating and comparing different strategies for software development. the results of experiments based on the qa model are reported. finally, conclusions are drawn from the experiments and future work is outlined.
the preliminary design as a key to successful software development. a successful software development effort is predicated upon the establishment of a complete preliminary design. a well disciplined methodology is required to ensure the satisfaction of the following key principles: 1) clear definition of data processing requirements 2) top-down design definition 3) design traceability 4) design verification a well integrated approach which considers these key elements ensures continuity between data processing subsystems engineering and detail design. it also provides clear visibility to management and reduces the risk in software development. trw has developed a preliminary design methodology which has successfully been applied to large scale software development. the methodology is a disciplined integration of design activities from initial system definition to successful completion of software preliminary design review. this paper will discuss the benefits from complete preliminary design and some of the specific design techniques employed.
gridunit: software testing on the grid. software testing is a fundamental part of system development. as software grows, its test suite becomes larger and its execution time may become a problem to software developers. this is especially the case for agile methodologies, which preach a short develop/test cycle. moreover, due to the increasing complexity of systems, there is the need to test software in a variety of environments. in this paper, we introduce gridunit, an extension of the widely adopted junit testing framework, able to automatically distribute the execution of software tests on a computational grid with minimum user intervention. experiments conducted with this solution have showed a speed-up of almost 70x, reducing the duration of the test phase of a synthetic application from 24 hours to less than 30 minutes. the solution does not require any source-code modification, hides the grid complexity from the user and provides a cost-effectiveness improvement to the software testing experience.
the role of a project-based capstone course. a project-based capstone course aims at using software development skills while performing a project in the course domain. one of our main challenges is to simulate a real world environment so to provide our students with the experience they need. planning this experience we should consider academic constraints as well as the students' schedule and skills. in this paper we describe how we implement an agile software development method in a project-based capstone course in the domain of operating systems. we elaborate on how we simulate a real world environment and present a role scheme that is used by the students to manage the process. we suggest a discussion on how to use the role scheme as an assessment tool to measure the development process in general and students' contribution in particular. we expect to extend and refine the comprehension regarding process measurement in students' teams at the academia.
a framework for modelling and analysis of software systems scalability. scalability is a widely-used term in scientific papers, technical magazines and software descriptions. its use in the most varied contexts contribute to a general confusion about what the term really means. this lack of consensus is a potential source of problems, as assumptions are made in the face of a scalability claim. a clearer and widely-accepted understanding of scalability is required to restore the usefulness of the term. this research investigates commonly found definitions of scalability and attempts to capture its essence in a systematic framework. its expected contribution is in assisting software developers to reason, characterize, communicate and adjust the scalability of software systems.
models and processes for the evaluation of cots components. this workshop summary presents an overview of theone-day international workshop on models and processesfor the evaluation of cots components (mpecý04), heldin conjunction with the 26th international conference onsoftware engineering (icseý04). details about mpecý04may be found at http://www.lsi.upc.es/events/mpec/.
coca: an automated debugger for c. presents coca, an automated debugger for c, where the breakpoint mechanism is based on events related to language constructs. events have semantics, whereas the source lines used by most debuggers do not have any. a trace is a sequence of events. it can be seen as an ordered relation in a database. users can specify precisely which events they want to see by specifying values for event attributes. at each event, visible variables can be queried. the trace query language is prolog with a handful of primitives. the trace query mechanism searches through the execution traces using both control flow and data, whereas debuggers usually search according to either control flow or data. as opposed to fully "relational" debuggers which use plain database querying mechanisms, the coca trace querying mechanism does not require any storage. the analysis is done on-the-fly, synchronously with the traced execution. coca is therefore more powerful than "source-line" debuggers and more efficient than relational debuggers.
a review of automated debugging systems: knowledge, strategies, and techniques. our review is based on descriptions of 18 existing automated systems on program debugging and of a dozen cognitive studies on debugging. we propose a classification of debugging knowledge, and a description of the corresponding knowledge representation in the systems. then we propose a classification of global debugging strategies used in the systems, and a description of the corresponding techniques. we assess the identified strategies from a real world program development point of view. the knowledge types we have identified are 1) knowledge of the intended program, 2) knowledge of the actual program, 3) understanding of the programming language, 4) general programming expertise, 5) knowledge of the application domain, 6) knowledge of bugs, 7) knowledge on debugging methods. the strategies we have identified are 1) filtering, 2) checking computational equivalence of intended program and actual one, 3) checking the well-formedness of actual program and 4) recognizing stereotyped errors.
a demand-driven analyzer for data flow testing at the integration level. data-flow testing relies on static analysis for computing the definition-use pairs that serve as the test case requirements for a program. when testing large programs, the individual procedures are first tested in isolation during unit testing. integration testing is performed to specifically test the procedure interfaces. the procedures in a program are integrated and tested in several steps. since each integration step requires data-flow analysis to determine the new test requirements, the accumulated cost of repeatedly analyzing a program can contribute considerably to the overhead of testing. data-flow analysis is typically computed using an exhaustive approach or by using incremental data-flow updates. this paper presents a new and more efficient approach to data-flow integration testing that is based on demand-driven analysis. we developed and implemented a demand-driven analyzer and experimentally compared its performance during integration testing with the performance of (i) a traditional exhaustive analyzer, and (ii) an incremental analyzer. our experiments show that demand-driven analysis is faster than exhaustive analysis by up to a factor of 25. the demand-driven analyzer also outperforms the incremental analyzer in 80% of the test programs by up to a factor of 5.
software development productivity tools and metrics. the continuing emphasis on improving productivity in the building of software has resulted in clearer definitions of software quality and software engineer productivity, and a greater interest by management and software engineer alike in the tools and measurements that aid in knowing a project is &ldquo;in control&rdquo;. this paper describes the software development process used within one software engineering group at digital equipment corporation, and the methods and tools used within the group to support the development of software products. experience in the application of software metrics to parts of the process as a means of quantifying productivity and quality is described.
using attributed grammars to test designs and implementations. we present a method for generating test cases that can be used throughout the entire life cycle of a program. this method uses attributed translation grammars to generate both inputs and outputs, which can then be used either as is, in order to test the specifications, or in conjunction with automatic test drivers to test an implementation against the specifications. the grammar can generate test cases either randomly or systematically. the attributes are used to guide the generation process, thereby avoiding the generation of many superfluous test cases. the grammar itself not only drives the generation of test cases but also serves as a concise documentation of the test plan. in the paper, we describe the test case generator, show how it works in typical examples, compare it with related techniques, and discuss how it can be used in conjunction with various testing heuristics.
communication system design using ada. this paper describes an experiment in ada design and some of the lessons learned from it. the experiment itself involved redesigning and reimplementing portions of an existing communication system. the paper compares the project team's design, based on traditional top-down structured design methods, with an alternative design based on information hiding. the project was intended to monitor how a typical industrial software team might adapt to using ada on realistic embedded application projects. just as important, however, were the insights gained on how to use ada in system design. although the team used virtually every novel feature of ada, they produced a design remarkably similar to that produced by the original implementors of the system, who used fortran and assembler. thus, the major problem in using ada appears to be one of education. it is not enough merely to teach the ada language itself. instead, one must stress the methodology&mdash;information hiding&mdash;that ada supports.
software reuse in an industrial setting: a case study. a summary of an ongoing case study of software reuse being carried out by the authors in cooperation with sperry marine incorporated is presented. the goals of the study are to analyze the problems that limit reuse and to seek solutions suitable for industrial application. to help determine its suitability for use within sperry marine, an experimental evaluation of object-oriented development was performed that focused on a specific subsystem domain found in several of sperry marine's commercial software products. a reuse library populated with classes written in c++ was prepared, and from this library simple versions of two representative subsystems were built. measurement of the resulting software showed a very high level of reuse
automating the detection of reusable parts in existing software. presents a model based on an expert-system approach for the scavenging of reusable components from existing software systems. the authors also describe a toolset called code miner that implements part of the model. the toolset uses prolog as its inference engine. code miner is designed to assist the programmer in finding reusable components in existing software written in c. to investigate the feasibility of the approach, an empirical study was conducted of the effectiveness of the toolset. in the study, public-domain software was scanned by the toolset for reusable parts and its output was examined by a team of human experts. the results of this experiment are outlined
object-oriented inspection in the face of delocalisation. software inspection is now widely accepted as an effective technique for defect detection. this acceptance is largely based on studies using procedural program code. this paper presents empirical evidence that raises significant questions about the application of inspection to object-oriented code.a detailed analysis of the 'hard to find' defects during an inspection experiment shows that many of them can be characterised as 'delocalised' &mdash; the information needed to recognise the defect is distributed throughout the software. the paper shows that key features of object-oriented technology are likely to exaggerate delocalisation.as a result, it is argued that new methods of inspection for object-oriented code are required. these must address: partitioning code for inspection (&ldquo;what to read&rdquo;), reading strategies (&ldquo;how to read&rdquo;), and support for understanding what isn't read &mdash; &ldquo;localising the delocalisation&rdquo;.
further investigations into the development and evaluation of reading techniques for object-oriented code inspection. this paper describes the development and experimental evaluation of a rigorous approach for effective object-oriented (oo) code inspection. since their development, inspections have been shown to be powerful defect detection strategies but little research has been done to investigate their application to oo systems, which have very different structural and execution models compared to procedural systems. previous investigations have demonstrated that the delocalised nature of oo software - the resolution of frequent non-local references, and the incongruous relationship between its static and dynamic representations, are primary inhibitors to its effective inspection. the experiment investigates a set of three complementary code reading techniques devised specifically to address these problems: one based on a checklist adapted to address the identified problems of oo inspections, one focused on the systematic construction of abstract specifications, and the last centered on the dynamic slice that a use-case takes through a system. the analysis shows that there is a significant difference in the number of defects found between the three reading techniques. the checklist-based technique emerges as the most effective approach but the other techniques also have noticeable strengths and so for the best results in a practical situation a combination of techniques is recommended.
a report on random testing. random testing of programs is usually (but not always) viewed as a worst case of program testing. test case generation that takes into account the program structure is usually preferred. path testing is an often proposed ideal for structural testing. path testing is treated here as an instance of partition testing. (partition testing is any testing scheme which forces execution of at least one test case from each subset of a partition of the input domain.) simulation results are presented which treat path and partition testing in a reasonably favorable way, and yet still suggest that random testing may often be more cost effective. results of actual random testing experiments are presented which tend to confirm the viability of random testing as a useful validation tool.
specification and verification of an object request broker. this paper reports the results of specifying, modeling and verifying a safe object request broker. this method has been applied on several case studies by using the spin verification tool. an object request broker has been implemented using sc++, a concurrent extension of c++ designed by our team. liveness and safety properties have been checked on the model to ensure the system behaviour is correct. this application shows the efficiency of using formal methods in building safe applications. it also shows that sc++ is appropriate for developing protocols and communicating systems and is easily translatable from models such as promela
patterns in property specifications for finite-state verification. model checkers and other finite-state verification tools allow developers to detect certain kinds of errors automatically. nevertheless, the transition of this technology from research to practice has been slow. while there are a number of potential causes for reluctance in adopting such formal methods, we believe that a primary cause is that practitioners are unfamiliar with specification processes, notations, and strategies. in a recent paper, we proposed a pattern-based approach to the presentation, codification and reuse of property specifications for finite-state verification. since then, we have carried out a survey of available specifications, collecting over 500 examples of property specifications. we found that most are instances of our proposed patterns. furthermore, we have updated our pattern system to accommodate new patterns and variations of existing patterns encountered in this survey. this paper reports the results of the survey and the current status of our pattern system.
a flexible architecture for building data flow analyzers. data flow analysis is a versatile technique that can be used to address a variety of analysis problems. typically, data flow analyzers are hand-crafted to solve a particular analysis problem. the cost of constructing analyzers can be high and is a barrier to evaluating alternative analyzer designs. we describe an architecture that facilitates the rapid prototyping of data flow analyzers. with this architecture, a developer chooses from a collection of pre-existing components or, using high-level component generators, constructs new components and combines them to produce a data flow analyzer. in addition to support for traditional data flow analysis problems, this architecture supports the development of analyzers for a class of combined data flow problems that offer increased precision. this architecture allows developers to investigate quickly and easily a wide variety of analyzer design alternatives and to understand the practical design tradeoffs better. we describe our experience using this architecture to construct a variety of different data flow analyzers.
a compact petri net representation for concurrent programs. array(0x8441c50) summary information that is necessary for performing program analysis. we present a flexible framework for checking a variety of properties of concurrent programs using the reachability graph generated from a tpn. we present experimental results that demonstrate the benefit of tpns over alternate petri net representations and discuss the applicability of petri net reduction techniques to tpns.
user perceived quality of interactive systems. user-perceived quality of interactive systems is defined in terms of statistically nonoverlapping categories, so-called dimensions or factors categories are identified by factor analysis and represent a dimensional concept of the quality of interactive systems as perceived by its users. each category describes essential user requirements.
a framework for multi-valued reasoning over inconsistent viewpoints. in requirements elicitation, different stakeholders often hold different views of how a proposed system should behave, resulting in inconsistencies between their descriptions. consensus may not be needed for every detail, but it can be hard to determine whether a particular disagreement affects the critical properties of the system. in this paper, we describe the xbel framework for merging and reasoning about multiple, inconsistent state machine models. xbel permits the analyst to choose how to combine information from the multiple viewpoints, where each viewpoint is described using an underlying multi-valued logic. the different values of our logics typically represent different levels of agreement. our multi-valued model checker, xchek, allows us to check the merged model against properties expressed in a temporal logic. the resulting framework can be used as an exploration tool to support requirements negotiation, by determining what properties are preserved for various combinations of inconsistent viewpoints.
2nd international workshop on living with inconsistency. in software engineering, there has long been a recognition that inconsistency is a fact of life. evolving descriptions of software artefacts are frequently inconsistent, and tolerating this inconsistency is important if flexible collaborative working is to be supported. this workshop will focus on reasoning in the presence of inconsistency, for a wide range of software engineering activities, such as building and exploring requirements models, validating specifications, verifying correctness of implementations, monitoring runtime behaviour, and analyzing development processes. a particular interest is on how existing automated approaches such as model checking, theorem proving, logic programming, and model-based reasoning can still be applied in the presence of inconsistency.
requirements uncertainty: influencing factors and concrete improvements. practically all industry studies on software project results conclude that good requirements engineering plays a pivotal role for successful projects. a key reason for project failures is insufficient management of changing requirements during all stages of the project life cycle. this article investigates one of the root causes for changing requirements, namely requirements uncertainty. in an experimental field study we looked into four underlying drivers for requirements uncertainty. we found several techniques must be used simultaneously to see tangible success. using only one such technique in isolation doesn't make a difference. the field study is supported by extensive data from well over 200 projects stemming from very different business areas of alcatel over a period of two years. results are presented with practical experiences to allow effective transfer.
improving validation activities in a global software development. global software development challenges traditional techniques of software engineering, such as peer reviews or teamwork. effective teamwork and coaching of engineers highly contribute towards successful projects. we will evaluate within this case study experiences with validation activities in a global setting within alcatel's switching and routing business. we will investigate three hypotheses related to effects of collocated inspections, intensive coaching, and feature-oriented development teams on globally distributed projects. as all these activities mean initial investment compared to a standard process with scattered activities, the major validation criteria for the 3 hypotheses is cost reduction due to earlier defect detection and less defects introduced. the data is taken from a sample of over 60 international projects of various sizes from which we collected all type of product and process metrics in the past 4 years.
tricks and traps of initiating a product line concept in existing product. many industries are hampered with introducing the product line concept into already existing products. though appealing, the concept is very difficult to introduce specifically into a legacy environment. all too often the impacts and risks are not considered adequately. this article describes the introduction of a product line approach in alcatel's s12 voice switching system business unit. practical impacts during the introduction are described as well as tricks and traps. the article not only summarizes the key software engineering principles, but also provides empirical evidence and practical techniques on which to build.
architecture, design, implementation. the terms architecture, design, and implementation are typically used informally in partitioning software specifications into three coarse strata of abstraction. yet these strata are not well-defined in either research or practice, causing miscommunication and needless debate.to remedy this problem we formalize the intension and the locality criteria, which imply that the distinction between architecture, design, and implementation is qualitative and not merely quantitative. we demonstrate that architectural styles are intensional and non-local; that design patterns are intensional and local; and that implementations are extensional and local.
can quality graduate software engineering courses really be delivered asynchronously on-line? this article briefly presents a case study in on-line asynchronous course delivery. it sketches the design of a graduate computer science course entitled &ldquo;software design and quality,&rdquo; illustrating an effective approach to distance learning that accommodates learning by doing, team collaboration, and critical thinking. it also shows that there are effective alternatives to &ldquo;canned&rdquo; streaming media presentations that achieve quality on-line education.
recast: reverse engineering from cobol to ssadm specification. the reverse engineering into case technology (recast) method takes the source code for an existing common business-oriented language (cobol) system and derives a no-loss representation of the system documented in a structured systems analysis and design method (ssadm) format. this representation of the system is derived through the use of a series of transformations. the environment within which recast has been developed is described, the stages and steps of the recast method are outlined, and the use of software support tools is discussed. an overview is given of a case study that has been carried out for a live system
a scenario-driven approach to traceability. design traceability has been widely recognized as being an integral aspect of software development. in the past years this fact has been amplified due to the increased use of legacy systems and cots (commercial-off-the-shelf) components mixed with the growing use of elaborate &ldquo;upstream&rdquo; software modeling techniques such as the unified modeling language (uml). the more intensive emphasis on upstream (non-programming) software development issues has, however, widened the gap between software components (e.g., subsystems, modules) and software models (e.g., class diagrams, data flow diagrams), creating the need for a better understanding of the intricacies and interrelationships between the two. this paper demonstrates how observable run-time information of software systems can be used to detect traceability information between software systems and their models. we do this by employing a technique that evaluates the &ldquo;footprints&rdquo; that usage scenarios (e.g., test cases) make during the execution of software systems. those footprints can be compared, resulting in additional traceability information among modeling elements associated with those scenarios. our approach is tool supported.
instant consistency checking for the uml. inconsistencies in design models should be detected immediately to save the engineer from unnecessary rework. yet, tools are not capable of keeping up with the engineers' rate of model changes. this paper presents an approach for quickly, correctly, and automatically deciding what consistency rules to evaluate when a model changes. the approach does not require consistency rules with special annotations. instead, it treats consistency rules as black-box entities and observes their behavior during their evaluation to identify what model elements they access. the uml/analyzer tool, integrated with ibm rational rose™, fully implements this approach. it was used to evaluate 29 models with tens-of-thousands of model elements, evaluated on 24 types of consistency rules over 140,000 times. we found that the approach provided design feedback correctly and required, in average, less than 9ms evaluation time per model change with a worst case of less than 2 seconds at the expense of a linearly increasing memory need. this is a significant improvement over the state-of-the-art.
modeling software failures and reliability growth during system testing. a number of time-domain software reliability models attempt to predict the growth of a system's reliability during the system test phase of the development life cycle. in this paper we examine the results of applying several types of poisson-process models to the development of a large system for which system test was performed in two parallel tracks, using different strategies for test data selection. we show that the reliability growth predicted by non-homogeneous poisson process models was found for only one of these testing strategies. these results imply that the applicability of a reliability growth model to a given software development project will depend on the nature of that project's system test process; they also raise theoretical questions about the assumption of certain statistical properties for failure occurrence during testing.
an evaluation of software test environment architectures. software test environments (stes) provide a means of automating the test process and integrating testing tools to support required testing capabilities across the test process. specifically, stes may support test planning, test management, test measurement, test failure analysis, test development and test execution. the software architecture of an ste describes the allocation of the environment's functions to specific implementation structures. an ste's architecture can facilitate or impede modifications such as changes to processing algorithms, data representation or functionality. performance and reusability are also subject to architecturally imposed constraints. evaluation of an ste's architecture can provide insight into modifiability, extensibility, portability and reusability of the ste. this paper proposes a reference architecture for stes. its analytical value is demonstrated by using saam (software architectural analysis method) to compare three software test environments: protest ii (prolog test environment, version ii), taos (testing with analysis and oracle support), and cite (convex integrated test environment).
static and dynamic structure in design patterns. design patterns are a valuable mechanism for emphasizing structure, capturing design expertise, and facilitating restructuring of software systems. patterns are typically applied in the context of an object-oriented language and are implemented so that the pattern participants correspond to object instances that are created and connected at run-time. this paper describes a complementary realization of design patterns, in which many pattern participants correspond to statically instantiated and connected components.our approach separates the static parts of the software design from the dynamic parts of the system behavior. this separation makes the software design more amenable to analysis, thus enabling more effective and domain-specific detection of system design errors, prediction of run-time behavior, and more effective optimization. this technique is applicable to imperative, functional, and object-oriented languages: we have extended c, scheme, and java with our component model. in this paper, we illustrate our approach in the context of the oskit, a collection of operating system components written in c.
software architecture recovery of a program family. the concept of software architecture has gained a lot of attention and has found its way into the software development process in industry. software architecture recovery focuses on the recovery of architectural information from existing systems. this paper presents a framework for recovering the software architecture of a program family. based on the available system information architectural properties such as safety or system control are recovered using different reverse engineering methods and tools in combination with architectural descriptions. we describe our architecture recovery process and discuss the recovery of system structure as one example of the case study. the framework was developed while working on the recovery of the family architecture of a train control system
experience in teaching a software reengineering course. software engineering curricula emphasize developing new software systems. little attention is given to how to change and modernize existing systems, i.e., the theory and practice of software maintenance and reengineering. this paper presents the author's experience in teaching software reengineering in a masters-level course at university of leicester, uk. it presents the course objectives, outline and the lessons learned. the main lessons are: first, there is a big shortage of educational materials for teaching software reengineering. second, selecting the suitable materials (that balance theory and practice) and the right tool(s) for the level of students and depth of coverage required is a difficult task. third, teaching reengineering using toy exercises and assignments does not convey the practical aspects of the subject. while, teaching with real, even small size, exercises and assignments, is almost infeasible. getting the balance right requires careful consideration and experimentation. finally, students understand and appreciate this topic much more if they have previous industrial experience and when they are presented with real industrial case studies.
improving web application testing with user session data. web applications have become critical components of the global information infrastructure, and it is important that they be validated to ensure their reliability. therefore, many techniques and tools for validating web applications have been created. only a few of these techniques, however, have addressed problems of testing the functionality of web applications, and those that do have not fully considered the unique attributes of web applications. in this paper we explore the notion that user session data gathered as users operate web applications can be successfully employed in the testing of those applications, particularly as those applications evolve and experience different usage profiles. we report results of an experiment comparing new and existing test generation techniques for web applications, assessing both the adequacy of the generated tests and their ability to detect faults on a point-of-sale web application. our results show that user session data can produce test suites as effective overall as those produced by existing white-box techniques, but at less expense. moreover, the classes of faults detected differ somewhat across approaches, suggesting that the techniques may be complimentary.
incorporating varying test costs and fault severities into test case prioritization. test case prioritization techniques schedule test cases for regression testing in an order that increases their ability to meet some performance goal. one performance goal, rate of fault detection, measures how quickly faults are detected within the testing process. in previous work we provided a metric, apfd, for measuring rate of fault detection, and techniques for prioritizing test cases to improve apfd, and reported the results of experiments using those techniques. this metric and these techniques, however, applied only in cases in which test costs and fault severity are uniform. in this paper, we present a new metric for assessing the rate of fault detection of prioritized test cases, that incorporates varying test case and fault costs. we present the results of a case study illustrating the application of the metric. this study raises several practical questions that might arise in applying test case prioritization; we discuss how practitioners could go about answering these questions.
an experiment in software engineering: the architecture research facility as a case study. software developers often complain that researchers in the field of software engineering propose new ideas without testing these ideas in practical applications. the architecture research facility (arf) was developed utilizing several software engineering techniques in order to discover their usefulness in actual software system developments. such techniques as the complete design and documentation of the individual components and interfaces prior to coding, design reviews, code specification in a pseudo-language, code-reading prior to testing, information-hiding modules, run-time error checking mechanisms, strong-typing and the use of support software tools are discussed. we describe the motivation for using the techniques as well as how these techniques were applied to arf's development. staff reactions to using these techniques were favorable although at the time some frustration at the lack of apparent coding progress was felt. our results would prove useful to software developers planning to use new development techniques since we highlight many of these techniques' strengths and weaknesses.
characteristic program complexity measures. twenty program complexity measures are studied with respect to how well they identify the more complex procedures in a software system. the measures have been applied to three large sets of pl/i procedures representing three different types of applications. four of these complexity measures have been found to form a characteristic set. that is, when procedures are kept within reasonable bounds for the four selected measures, they will most likely be within reasonable bounds for all of the other measures. the measures and their interpreted meanings are length&mdash;the quantity of source code, unique operators&mdash;the variety of programming language actions, data difficulty&mdash;the average number of variable appearances, and unique operands&mdash;the variety of constants and variables.
recognizing and responding to "bad smells" in extreme programming. the agile software development process called extreme programming (xp) is a set of best practices which, when used, promises swifter delivery of quality software than one finds with more traditional methodologies. in this paper, we describe a large software development project that used a modified xp approach, identifying several unproductive practices that we detected over its two-year life that threatened the swifter project completion we had grown to expect. we have identified areas of trouble in the entire life cycle, including analysis, design, development, and testing. for each practice we identify, we discuss the solution we implemented to correct it and, more importantly, examine the early symptoms of those poor practices ("bad smells") that project managers, analysts, and developers need to look out for in order to keep an xp project on its swifter track.
a knowledge structure for reusing abstract data types. a knowledge structure for a software library consisting of abstract data types (adts) is defined. both automatically-derived and explicitly-defined relationships are used to impose a knowledge structure on the adts. adts are defined by an adt descriptor and one or more adt implementations. performance characteristics and default implementations are provided to assist users in choosing among alternatives. an explanation is given as to how the knowledge structure helps users find adts of interest, browse through similar adts to investigate alternatives, and build and customize executable software components from adts in the library.
assessing the quality of abstract data types written in ada. as software systems have become more complex, a search for better abstraction mechanisms has led to the use of abstract data types (adts). to more appropriately use adts, however, it is imperative that their properties and characteristics be understood. in this paper we present a method of assessing the quality of adts in terms of cohesion and coupling. we argue that an adt that contains and exports only one domain and exports only operations that pertain to that domain has the best cohesive properties, and we argue that adts that make neither explicit nor implicit assumptions about other adts in the system have the best coupling properties. formal definitions are presented for each of the cohesion and coupling characteristics discussed. their application to ada&reg; packages is also investigated, and we show how a tool can be developed to assess the quality of an ada package that represents an adt. we analyzed nearly one hundred ada adt packages found in ada text books, articles about ada, and student projects and discovered that more than half of them had inferior cohesive characteristics and almost half of them allowed inferior coupling characteristics.
a discriminant metric for module cohersion. the decomposition of a large program into modules can be guided by the use of a property called cohesion, first described by constantine. cohesion is a quality that describes the degree to which the different actions performed by a module contribute to a unified function. however, this technique may be difficult to apply due to the subjective nature of the definitions of levels of cohesion. in this paper a software metric is defined and proposed as a discriminant for classifying modules according to their cohesion. formal properties of the metric are derived which can be used to set the metric value ranges for module classification.
distributed component technologies and their software engineering implications. in this state of the art report, we review advances in distributed component technologies, such as the enterprise java beans specification and the corba component model. we assess the state of industrial practice in the use of distributed components. we show several architectural styles for whose implementation distributed components have been used successfully. we review the use of iterative and incremental development processes and the notion of model driven architecture. we then assess the state of the art in research into novel software engineering methods and tools for the modelling, reasoning and deployment of distributed components. the open problems identified during this review result in the formulation of a research agenda that will contribute to the systematic engineering of distributed systems based on component technologies.
component technologies: java beans, com, corba, rmi, ejb and the corba component model. this one-day tutorial is aimed at software engineering practitioners and researchers, who are familiar with object-oriented analysis, design and programming and want to obtain an overview of the technologies that are enabling component-based development. we introduce the idea of component-based development by defining the concept and providing its economic rationale. we describe how object-oriented programming evolved into local component models, such as java beans and distributed object technologies, such as the common object request broker architecture (corba), java remote method invocation (rmi) and the component object model (com). we then address how these technologies matured into distributed component models, in particular enterprise java beans (ejb) and the corba component model (ccm). we give an assessment of the maturity of each of these technologies and sketch how they are used to build distributed architectures.
implementing incremental code migration with xml. we demonstrate how xml and related technologies can be used for code mobility at any granularity, thus overcoming the restrictions of existing approaches. by not fixing a particular granularity for mobile code, we enable complete programs as well as individual lines of code to be sent across the network. we define the concept of incremental code mobility as the ability to migrate and add, remove, or replace code fragments (i.e., increments) in a remote program. the combination of fine-grained and incremental migration achieves a previously unavailable degree of flexibility. we examine the application of incremental and fine-grained code migration to a variety of domains, including user interface management, application management on mobile thin clients, for example pdas, and management of distributed documents.
software engineering economics: background, current practices, and future directions. the field of software economics seeks to develop technical theories, guidelines, and practices of software development based on sound, established, and emerging models of value and value-creation---adapted to the domain of software development as necessary. the premise of the field is that software development is an ongoing investment activity---in which developers and managers continually make investment decisions requiring the expenditure of valuable resources, such as time, talent, and money. the overriding aim of this activity is to maximize the value added subject to an equitable distribution among the participating stakeholders. the goal of the tutorial is to expose the audience to this line of thinking and introduce the tools pertinent to its pursuit. the tutorial is designed to be self-contained and will cover concepts from introductory to advanced. both practitioners and researchers with an interest in the impact of value considerations in software decision-making will benefit from attending it.this tutorial is offered in conjunction with the fourth international workshop on economics-driven software engineering research (edser-4). the tutorial is meant in part to enable those who would like to participate in the workshop, but who might not possess the requisite background, to come up to speed.
research summary for dynamic detection of program invariants. explicitly stated program invariants can help programmers by identifying program properties that must be preserved when modifying code; invariants also play a number of other valuable roles in program development and evolution. in practice, however, these invariants are usually implicit. an alternative to expecting programmers to fully annotate code with invariants is to automatically infer invariants from the program itself. this research aims to develop and evaluate dynamic techniques for discovering invariants from execution traces. our hypothesis is that such techniques are effective at extracting invariants from programs and that the extracted invariants are useful to programmers. experiments with our prototype implementation provide preliminary support for this hypothesis.
the groupthink specification exercise. teaching students to read and write specifications is difficult. it is even more difficult to motivate specifications---to convince students of the value of specifications and make students eager to use them. this paper describes the groupthink specification exercise. groupthink is a fun group activity, in the style of a game show, that teaches students about specifications (the difficulty of writing them, techniques for getting them right, and criteria for evaluating them), teamwork, and communication. specifications are not used as an end in themselves, but are motivated to students as a means to solving realistic problems that involve understanding system behavior. students enjoy the activity, and it improves their ability to read and write specifications. the two-hour, low-prep activity is self-contained, scales from classes of ten to hundreds of students, and is freely available to other instructors.
quickly detecting relevant program invariants. explicitly stated program invariants can help programmers by characterizing certain aspects of program execution and identifying program properties that must be preserved when modifying code. unfortunately, these invariants are usually absent from code. previous work showed how to dynamically detect invariants from program traces by looking for patterns in and relationships among variable values. a prototype implementation, daikon, accurately recovered invariants from formally-specified programs, and the invariants it detected in other programs assisted programmers in a software evolution task. however, daikon suffered from reporting too many invariants, many of which were not useful, and also failed to report some desired invariants.this paper presents, and gives experimental evidence of the efficacy of, four approaches for increasing the relevance of invariants reported by a dynamic invariant detector. one of them &mdash; exploiting unused polymorphism &mdash; adds desired invariants to the output. the other three &mdash; suppressing implied invariants, limiting which variables are compared to one another, and ignoring unchanged values &mdash; eliminate undesired invariants from the output and also improve runtime by reducing the work done by the invariant detector.
dynamically discovering likely program invariants to support program evolution. explicitly stated program invariants can help programmers by identifying program properties that must be preserved when modifying code. in practice, however, these invariants are usually implicit. an alternative to expecting programmers to fully annotate code with invariants is to automatically infer likely invariants from the program itself. this research focuses on dynamic techniques for discovering invariants from execution traces. this article reports three results. first, it describes techniques for dynamically discovering invariants, along with an implementation, named daikon, that embodies these techniques. second, it reports on the application of daikon to two sets of target programs. in programs from gries's work on program derivation, the system rediscovered predefined invariants. in a c program lacking explicit invariants, the system discovered invariants that assisted a software evolution task. these experiments demonstrate that, at least for small programs, invariant inference is both accurate and useful. third, it analyzes scalability issues, such as invariant detection runtime and accuracy, as functions of test suites and program points instrumented.
automatic generation and maintenance of correct spreadsheets. existing spreadsheet systems allow users to change cells arbitrarily, which is a major source of spreadsheet errors. we propose a system that prevents errors in spreadsheets by restricting spreadsheet updates to only those that are logically and technically correct. the system is based on the concept of templates that describe the principal structure of the initial spreadsheet and all of its future versions. we have developed a program generator that translates a template into an initial spreadsheet together with customized update operations for changing cells and inserting/deleting rows and columns for this particular template.we have designed a type system for templates that ensures the following form of "spreadsheet maintenance safety": update operations that are generated from a type-correct template are proved to transform the spreadsheet only according to the template and to never produce any omission, reference, or type errors.finally, we have developed a prototype as an extension to excel, which has been shown by a preliminary usability study to be well accepted by end users.
verification support for workflow design with uml activity graphs. we describe a tool that supports verification of workflow models specified in uml activity graphs. the tool translates an activity graph into an input format for a model checker according to a semantics we published earlier. with the model checker arbitrary propositional requirements can be checked against the input model. if a requirement fails to hold an error trace is returned by the model checker. the tool automatically translates such an error trace into an activity graph trace by high-lighting a corresponding path in the activity graph. one of the problems that is dealt with is that model checkers require a finite state space whereas workflow models in general have an infinite state space. another problem is that strong fairness is necessary to obtain realistic results. only model checkers that use a special model checking algorithm for strong fairness are suitable for verifying workflow models. we analyse the structure of the state space. we illustrate our approach with some example verifications.
impact of the research community for the field of software configuration management. software configuration management (scm) is an important discipline in professional software development and maintenance. the importance of scm has increased as programs have become larger, more complex, and more mission/life-critical.this paper presents a brief summary of a full report that discusses the evolution of scm technology from the early days of software development to present, and the specific impact university and industrial research has had along the way.
towards safe distributed application development. distributed application development is overly tedious, asthe dynamic composition of distributed components is hardto combine with static safety with respect to types (typesafety) and data (encapsulation). achieving such safetyusually goes through specific compilation to generate theglue between components, or making use of a single programminglanguage for all individual components with ahardwired abstraction for the distributed interaction.in this paper, we investigate general-purpose programminglanguage features for supporting third-party implementationsof programming abstractions for distributed interactionamong components. we report from our experiencesin developing a stock market application based ontype-based publish/subscribe (tps) implemented (1) as alibrary in standard java as well as with (2) a homegrownextension of the java language augmented with specificprimitives for tps, motivated by the lacks of former implementation.we then revisit the library approach, investigatingthe impact of genericity, reflective features, and thetype system, on the implementation of a satisfactory tpslibrary. we then discuss the impact of these features alsoon other distributed programming abstractions, and henceon the engineering of distributed applications in general,pointing out lacks of mainstream programming environmentssuch as java as well as .net.
using raddle to design distributed systems. we describe our linguistic tool, raddle, and its use in designing distributed systems. raddle coordinates concurrent processes with the n-party interaction, a new high-level communication primitive. another important feature of raddle is the team, which encapsulates communicating processes. we discuss our efforts towards developing a complete methodology for using raddle and briefly describe our software toolset.
second international workshop on dynamic analysis (woda 2004). dynamic analysis techniques reason over programexecutions and show promise in aiding the developmentof robust and reliable large-scale systems. it has becomeincreasingly clear that limitations of static analysis can beovercome by integrating static and dynamic analyses, andthat the performance and value of dynamic analysis canbe improved by static analysis. hence, a key focus of theworkshop will be on hybrid analyses that involve bothstatic and dynamic components.
inculcating invariants in introductory courses. one goal of introductory software engineering courses is to motivate and instill good software engineering habits. unfortunately, practical constraints on typical courses often lead to student experiences that are antithetical to that goal: instead of working in large teams and dealing with changing requirements and maintaining programs over many years, courses generally involve students working alone or in small teams with short projects that end the first time the program works correctly on some selected input. small projects tend to reinforce poor software engineering practices. since the programs are small enough to manage cognitively in ad hoc ways, effort spent more precisely documenting assumptions seems wasteful. it is infeasible to carry out full industrial software development within the context of a typical university course. however, it is possible to simulate some aspects of safety critical software engineering in an introductory software engineering course. this paper describes an approach that focuses on thinking about and precisely documenting invariants, and checking invariants using lightweight analysis tools. we describe how assignments were designed to emphasize the importance of invariants and to incorporate program analysis tools with typical software engineering material and report on results from an experiment measuring students understanding of program invariants.
power: a tool for quantitative evaluation of software project effectiveness. in this paper a tool for quantitative method of evaluating software projects is presented. this method constitutes the project observation workbench and evaluation reportor (power). a representative project evaluation with power is presented to demonstrate its application.
how to design a system in which modules can be changed on the fly. in a system made up of many modules, each managing its own peculiar types of data structures, it is often necessary to update one of the modules so as to provide new features or an improvement in the internal organization. if the interface to the module is unchanged or merely augmented the programs which interact with the module need not be changed. if the system can be brought to an orderly halt and if the module does not manage permanent data structures, it will merely be necessary to recompile the modified module, relink the system, stop the old system, and install the new one. if the module does manage permanent data structures which must be modified and the system is one which is expected to continue operation throughout the change, the problem is more difficult, but it can be solved. this paper discusses a solution.
design and test of distributed applications. it is well known that programming and testing distributed systems can be extremely difficult. reasons for this include non-deterministic behavior, non-reproducibility of events, complex timing of events, and complex states. this paper presents a paradigm and system that will support a programmer when designing, programming, and testing a distributed application. our main point is that the structure introduced by the paradigm must be kept and exploited during design, programming, and testing. one is not helped by a programming method which introduces a structure just to break it down again. we have developed a structural model based on common structures in distributed systems. this structural model is used to describe the logical relationships between components in a system. it is also integrated into the programming environment.
why can't they create architecture models like "developer x"? an experience report. a large financial company, struggling with legacy systems that did not interoperate, performed a pilot project to teach software architecture to an enthusiastic application development team. experienced mentors, including the author, worked with the application team for seven months to complete their engineering goal successfully. however, the mentors were unsuccessful in their attempt to train any of the six members of the application team to create architecture models on their own, though they were able to create them collaboratively with the mentors. this surprising result is due to the application team's strong preference for concrete artifacts over abstract ones. even more surprising, an application developer from a different project, "developer x", read the architecture modeling documentation on an internal website and, without mentoring, created architecture models within a few days. in light of this failure to teach software architecture, two short-term strategies are suggested for the use of software architecture in companies.
achieving industrial relevance with academic excellence: lessons from the oregon master of software engineering. many educational institutions are developing graduate programs in software engineering targeted to working professionals. these educators face the dilemma of providing programs with both industrial relevance and academic excellence. this paper describes our experience and lessons learned in developing such a program, the oregon master of software engineering (omse). it describes a structured approach to curriculum design, curriculum design principles and methods that can be applied to develop a quality professional program.
icse 2003 workshop on software engineering for high assurance systems: synergies between process, product, and profiling (sehas 2003). a critical issue in software engineering is how to construct high assurance software systems, i.e., software systems where compelling evidence is required that the system delivers its services in a manner satisfying critical properties, such as safety and security. this two-day icse workshop, the third in a series of workshops on high assurance systems, will provide a forum for researchers and practitioners to exchange ideas and experiences relevant to the development of software for aerospace systems, medical systems, systems controlling nuclear power plants, and other critical systems. participants of the sehas 2003 workshop will explore the opportunities for, and benefits of, synergies between three important themes---product, process, and profiling---each theme reflecting an important aspect of software development for high assurance systems.
an incremental programming environment. this document describes an incremental programming environment (ipe) based on compilation technology, but providing facilities traditionally found only in interpretive systems. ipe provides a comfortable environment for a single programmer working on a single program. in ipe the programmer has a uniform view of the program in terms of the programming language. the program is manipulated through a syntax-directed editor and its execution is controlled by a debugging facility, which is integrated with the editor. other tools of the traditional tools cycle (translator, linker, loader) are applied automatically and are not visible to the programmer. the only interface to the programmer is the user interface of the editor.
adaptive feedback scheduling of incremental and design-to-time tasks. this paper discusses an approach for adaptive feedback scheduling in resource insufficient environments. in particular, we examine the problem of maximizing the utilization of the cpu for a collection of periodic incremental and design-to-time tasks with variations in actual execution times. cpu allocation beyond a minimum is performed according to a quality-of-service (qos) based utility function. schedulability analysis results are utilized to determine guaranteed execution time limits (worst-case schedulability boundary). past history based on actual task execution times is used to identify the actual schedulability boundary and execution time allocations are adjusted accordingly. this feedback control approach to scheduling supports opportunistic resource allocation beyond the analytic limits, while minimizing deadline misses and limiting them to optional execution increments.
transforming and extending the enterprise through it. in this time of economic turmoil, it is emerging as a foundation for transition to the new economy. this presentation provides a high-level perspective on the key business and technology megatrends shaping the future of it, as well as the key management initiatives required to harness and exploit it effectively. key issues include:&bull; what are the key trends and events that will drive new it investments during the next five years?&bull; how will technology advances and changes impact it deployment decisions?&bull; how can organizations harness and exploit it despite ever-increasing complexity and volatility?
validating real-time systems by history-checking trio specifications. we emphasize the importance of formal executable specifications in the development of real-time systems, as a means to assess the adequacy of the requirements before a costly development process takes place. trio is a first-order temporal logic language for executable specification of real-time systems that deals with time in a quantitative way by providing a metric to indicate distance in time between events and length of time intervals. we summarize the language and its model-parametric semantics. then we present an algorithm to perform history checking, i.e., to check that a history of the system satisfies the specification. this algorithm can be used as a basis for an effective specification testing tool. the algorithm is described; an estimation of its complexity is provided; and the main functionalities of the tool are presented, together with sample test cases. finally, we draw conclusions and indicate directions of future research.
new languages from old: the extension of programming languages by embedding, with a case study. embedding is the extension of a programming language without altering the processor for that language, and preferably using only the facilities of that language. while a single subroutine is the simplest form of semantic extension by embedding, embedding can produce powerful application-oriented languages (aol) in a relatively economical fashion. a first approximation to a design discipline for writing embedded aols is presented. snobol4 is discussed as a particularly receptive host language, in that it has flexible subroutine, data-structure, and storage allocation facilities, has a run-time compiler which can be called from a snobol4 program, and is widely available for almost all research computer systems. a description is given of automat, a snobol4-embedded aol for classroom or research experiments with abstract sequential machines. the generalized transition table is introduced as a data structure in which finite-state machines (fsm), turing machines, pushdown automata, and the like can be represented as special cases. data structures for sets, partitions and covers, sparse matrices, and tapes are provided as well. the automat aol currently includes over 100 operators developed according to the proposed method. applications thus far include an extensive fsm utility system, universal simulators for fsm and other models, fsm minimization, and krohn-rhodes decomposition. performance statistics are presented.
1st workshop on open source software engineering. open source software (oss) has recently become the focus of considerable interest, yet there remains a need for rigorous analytical inquiry into the subject. this workshop seeks to articulate oss as an se paradigm and to address the requirements of oss in terms of methodology & process, tools & enabling technologies, and human resources & project management. format: round-table discussion. size: maximum 40 participants. position papers required. the workshop report will be published in a special issue of iee proceedings - software on open source software engineering, and workshop participants will be encouraged to submit full research papers based on their position papers for possible inclusion in the special issue.
the 3rd workshop on open source software engineering. building on the success of "making sense of the bazaar" and "meeting challenges and surviving success" --- the 1st and 2nd workshops on open source software engineering (icse 2001 and icse 2002) --- this workshop ("taking stock of the bazaar') brings together researchers and practitioners for the purpose of discussing the diverse array of techniques --- as well as supporting tools and social/organizational contexts --- which can be observed in the domain of open source software.
collaboration, conflict and control: the 4th workshop on open source software engineering. building on the success of the first three workshops inthe series, which were held at icse 2001 (toronto), icse2002 (orlando) and icse 2003 (portland), the 4thworkshop on open source software engineering,("collaboration, conflict and control") brings togetherresearchers and practitioners for the purpose ofdiscussing the platforms and tools, techniques andprocesses, and the organizational structures that are usedto support and sustain communication, collaboration andconflict resolution within and between open sourcesoftware communities.
open source application spaces: the 5th workshop on open source software engineering. the goal of the 5th workshop on open source software engineering is to bring together researchers and practitioners for the purpose of building a roadmap of the ways in which various computing application spaces have been impacted by open source software and also by open source development methods, tools and organizational structures.
making resource decisions for software projects. software metrics should support managerial decisionmaking in software projects. we explain how traditionalmetrics approaches, such as regression-based models forcost estimation fall short of this goal. instead, wedescribe a causal model (using a bayesian network)which incorporates empirical data, but allows it to beinterpreted and supplemented using expert judgement.we show how this causal model is used in a practicaldecision-support tool, allowing a project manager totrade-off the resources used against the outputs(delivered functionality, quality achieved) in a softwareproject. the model and toolset have evolved in a numberof collaborative projects and hence capture significantcommercial input. extensive validation trials are takingplace among partners on the ec funded projectmodist (this includes philips, israel aircraft industriesand qinetiq) and the feedback so far has been verygood. the estimates are sensible and the causalmodelling approach enables decision-makers to reasonin a way that is not possible with other projectmanagement and resource estimation tools. to ensurewide dissemination and validation a version of thetoolset with the full underlying model is being madeavailable for free to researchers.
an experiment in program restructuring for performance enhancement. an experiment intended to determine the influence of the input data on the performance improvements resulting from program restructuring is described. this influence is found to be non-significant for the particular program, memory policy, restructuring procedure and inputs considered in the experiment. it is speculated that such a conclusion is likely to have much more general validity.
some results from an empirical study of computer software. a study has been carried out to relate the maintenance performance of a collection of pl/i programs to measures that characterize control flow, data usage, and software science attributes of the programs. the programs are from two subsystems of a business data processing application. interesting relationships were found not only between the maintenance data and the measures but also among the measures themselves. this paper discusses some of the stronger of these relationships.
clinical requirements engineering. in this paper, i make a case for integration of requirements engineering (re) with clinical disciplines. to back my case, i look at two examples that employ a clinical re approach, first, that of introducing email into the life of a brain-injured individual, and second, introducing digital darkroom tools into my life. the former uses a brownfield approach by starting with an existing clinical process, cognitive rehabilitation, and then defining an re process that fits. the latter uses a greenfield approach that postulates a new clinical re process that focuses on the problems some of us have using digital darkroom tools.
software architecture in an open source world. in spite of the hype and hysteria surrounding open source software development, there is very little that can be said of open source in general. open source projects range in scope from the miniscule, such as the thousands of non-maintained code dumps left behind at the end of class projects, dissertations, and failed commercial ventures, to the truly international, with thousands of developers collaborating, directly or indirectly, on a common platform. one characteristic that is shared by the largest and most successful open source projects, however, is a software architecture designed to promote anarchic collaboration through extensions while at the same time preserving centralized control over the interfaces.this talk features a survey of the state-of-the-practice in open source development in regards to software architecture, with particular emphasis on the modular extensibility interfaces within several of the most successful projects, including apache httpd, eclipse, mozilla firefox, linux kernel, and the world wide web (which few people recognize as an open source project in itself). these projects fall under the general category of collaborative open source software development, which emphasizes community aspects of software engineering in order to compensate for the often-volunteer nature of core developers and take advantage of the scalability obtainable through internet-based virtual organizations.
principled design of the modern web architecture. the world wide web has succeeded in large part because its software architecture has been designed to meet the needs of an internet-scale distributed hypermedia application. the modern web architecture emphasizes scalability of component interactions, generality of interfaces, independent deployment of components, and intermediary components to reduce interaction latency, enforce security, and encapsulate legacy systems. in this article we introduce the representational state transfer (rest) architectural style, developed as an abstract model of the web architecture and used to guide our redesign and definition of the hypertext transfer protocol and uniform resource identifiers. we describe the software engineering principles guiding rest and the interaction constraints chosen to retain those principles, contrasting them to the constraints of other architectural styles. we then compare the abstract model to the currently deployed web architecture in order to elicit mismatches between the existing protocols and the applications they are intended to support.
process issues in course projects. defined software engineering process help teaching and guiding software engineering courses projects. however, using them raises several issues related to process and course features. architecture issues relate to matching process and course lifecycle models. size issues address project scope and extent. support issues deal with student and instructor materials and tools.
a software process for time-constrained course projects. defined software engineering processes help to perform and guide software engineering course projects. however, several difficult issues are involved in designing a software process for this purpose. this design is even harder when it must suit time-constrained course projects. here, we discuss several issues concerning such processes, focusing on an educational setting.
software engineering education: a place in the sun? virtually every research specialisation in software engineering would be prepared to claim that its particular concern is the most important in the field. the author wishes to claim such a status for software engineering education, a specialisation barely regarded as respectable among the majority of researchers. what are the grounds for this claim? virtually all the technologies which we believe hold promise of improving software development are dependent on professionally skilled and educated staff. software engineering education remains our most powerful means of technology transfer and hence of narrowing the gap between what is known in the research community and what is applied in industry and commerce. despite economic hiccups the skills shortage is still a critical component of the omnipresent software crisis. industry is spending a large proportion of its software development budget on training and on recruitment to offset the costs of fundamental education problems
assessment of system evolution through characterization. owing to the growing diffusion of the object-oriented paradigm and the need to keep the process of software development under control, industries are looking for metrics/indicators capable of evaluating system evolution to control quality, reusability, maintainability, etc. some new metrics are proposed for monitoring system development and maintenance. these metrics are used with a set of histograms to give a clear characterization of the system under development. histograms call be profitably used to detect critical conditions during the system life-cycle. the semantics of these histograms has been validated against several projects: an example is also reported
engineering safety-related requirements for software-intensive systems. many software-intensive systems have significant safety ramifications and need to have their associated safety-related requirements properly engineered. however, there is little effective interaction and collaboration between the requirements and safety teams on most projects. this tutorial is intended to improve such collaboration by providing clear definitions of the different kinds of safety-related requirements, examples of such requirements, and a generic process for producing them.
engineering safety-related requirements for software-intensive systems. many software-intensive systems have significant safety ramifications and need to have their associated safety-related requirements properly engineered. it has been observed by multiple consultants, researchers, and authors that inadequate requirements are a major cause of accidents involving software-intensive systems. yet in practice, there is very little interaction between the requirements and safety disciplines and little collaboration between their respective communities. most requirements engineers know little about safety engineering, and most safety engineers know little about requirements engineering. also, safety engineering typically concentrates on architectures and designs rather than requirements because hazard analysis typically depends on the identification of hardware and software components, the failure of which can cause accidents. this leads to safety-related requirements that are often ambiguous, incomplete, and even missing. the tutorial begins with a single common realistic example of a safety critical system that will be used throughout to provide good examples of safety-related requirements. the tutorial then provides an introduction to requirements engineering for safety engineers and an introduction to safety engineering for requirements engineers. the tutorial then provides clear definitions and descriptions of the different kinds of safety-related requirements and finishes with a practical process for producing them.
software engineering themes for the future. the objective of this tutorial is to provide the participants with opportunities to think differently about future challenges facing software engineering research and practice. collaborative design, social creativity, and meta-design are identified as themes that will be of great importance in the years to come. the concept of design is used very broadly affecting all aspects of the process of creating, using, and evolving software-intensive systems. stakeholders coming from different disciplines and engaging in collaborative design can contribute to social creativity by exploring new approaches, new problems, and new visions. meta-design is a methodology empowering users to act not only as passive consumers but as active contributors and designers, thereby facilitating and supporting social creativity.the themes of the tutorial will be illustrated with specific theoretical frameworks and innovative systems. the relevance of these themes has been demonstrated by their desirability and importance on research, education, and design practices in companies, educational institutions, and research organizations.
cognitive tools for locating and comprehending software objects for reuse. the authors describe a conceptual framework to facilitate software reuse. it is shown that high functionality computer systems by themselves do not provide sufficient support for software reuse. two systems that support this framework, codefinder and explainer, are presented. codefinder addresses issues on information access for software reuse. support for comprehending software objects is demonstrated with explainer. a scenario describing how the two systems are used in a reuse situation is presented. the authors show how these systems fit into the bigger pictures of software development environments, address limitations of the systems, and discuss future directions
from design to redesign. software engineering environments have to support design methodologies whose main activity is not the generation of new independent programs, but the maintenance, integration, modification and explanation of existing ones. especially for software systems in ill-structured problem domains where detailed specifications are not available (like artificial intelligence and human-computer communication), incremental, evolutionary redesign has to be efficiently supported.to achieve this goal we have designed and constructed an object-oriented, knowledge-based user interface construction kit and a large number of associated tools and intelligent support systems to be able to exploit this kit effectively. answers to the &ldquo;user interface design question&rdquo; are given by providing appropriate building blocks that suggest the way user interfaces should be built. the object-oriented system architecture provides great flexibility, enhances the reusability of many building blocks, and supports redesign. because existing objects can be used either directly or with minor modifications, the designer can base a new user interface on standard and well-tested components.
knowledge-based communication processes in software engineering. a large number of problems to be solved with the help of computer systems are ill-structured. their solution requires incremental design processes, because complete and stable specifications are net available. for tasks of this sort, life cycle models are inadequate. our design methodology is based on a rapid prototyping approach which supports the coevolution of specification and implementation. communication between customers, designers and implementors and communication between the humans and the knowledge base in which the emerging product is embedded are of crucial importance. our work is centered around knowledge-based systems which enhance and support the communication needs in connection with software systems. program documentation systems are used as an example to illustrate the relevance of knowledge-based human-computer communication in software engineering.
the interaction between the preliminary designs and the technical requirements for the dod common high order language. the common high order language effort began in january 1975 as part of a dod wide program to reduce the cost and to improve the quality of its software. the effort is an attempt to create a situation in which software for new embedded computer systems are developed and maintained using a minimal number of general-purpose programming languages, and that those languages be suited to the applications, be widely used in dod, and be well supported.
automated test case generation for spreadsheets. spreadsheet languages, which include commercial spreadsheets and various research systems, have had a substantial impact on end-user computing. research shows, however, that spreadsheets often contain faults. thus, in previous work, we presented a methodology that assists spreadsheet users in testing their spreadsheet formulas. our empirical studies have shown that this methodology can help end-users test spreadsheets more adequately and efficiently; however, the process of generating test cases can still represent a significant impediment. to address this problem, we have been investigating how to automate test case generation for spreadsheets in ways that support incremental testing and provide immediate visual feedback. we have utilized two techniques for generating test cases, one involving random selection and one involving a goal-oriented approach. we describe these techniques, and report results of an experiment examining their relative costs and benefits.
verification and change-impact analysis of access-control policies. sensitive data are increasingly available on-line through the web and other distributed protocols. this heightens the need to carefully control access to data. control means not only preventing the leakage of data but also permitting access to necessary information. indeed, the same datum is often treated differently depending on context.system designers create policies to express conditions on the access to data. to reduce source clutter and improve maintenance, developers increasingly use domain-specific, declarative languages to express these policies. in turn, administrators need to analyze policies relative to properties, and to understand the effect of policy changes even in the absence of properties.this paper presents margrave, a software suite for analyzing role-based access-control policies. margrave includes a verifier that analyzes policies written in the xacml language, translating them into a form of decision-diagram to answer queries. it also provides semantic differencing information between versions of policies. we have implemented these techniques and applied them to policies from a working software application.
global talent and innovation. in his groundbreaking 2002 bestseller the rise of the creative class, economist richard florida identified the 3 ts of economic development: technology, talent, and tolerance. now, with the flight of the creative class, florida is back - and he's gone global. how does the movement of talented people across borders affect regional growth? what do tighter immigration, faltering education systems, and strong international competition mean for u.s. growth? who are the up-and-comers in the global creative economy? florida takes on these questions and more as he charts a course for creativity in the 21st century - and explains what the impact will be for countries, cities, and companies the world over.
modeling software tools with icon. this paper describes a new software test automation tool, a powerful new programming language, and the software development process that resulted when these tools were combined. a small development team of software developers and potential customers devised the unconventional process to meet a short deadline. the process produced an operational prototype or model of the entire software system that customers were able to use during the time it was being developed. the first model of the buster&trade; automated testing system was conceived, designed, and implemented ahead of schedule in less than six months, complete with many features and components. the buster system provides a test-information subsystem with facilities for multi-project test sharing, per-project test storage and planning, and test downloading for lab use. a separate test execution facility is also included that features test-result logging, a results database, and per-session i/o recording. the customer, at&t 3b4000 system test, reports that system soak tests that had taken three weeks now can be completed in one week, using buster. the software modeling technique that was used to create the buster test system is a new idea that can be used to produce reliable low-cost software in many applications. unlike more conventional software engineering approaches, including rapid prototyping, the model can be used by customers as it is slowly evolved into a finished product. the model is used to embody and test designs and identify missing requirements before making large investments in production level code and documentation. in addition, software modeling makes it possible to develop comprehensive system test suites long before production level software is available. the process is composed of three major components: brainstorming and team building with customers, high-level language engineering, and automated software testing.
an exact array reference analysis for data flow testing. data-flow testing is a well-known technique, and it has proved to be better than the commercially-used branch testing. the problem with data-flow testing is that, apart from scalar variables, only approximate information is available. this paper presents an algorithm that precisely determines the definition-use pairs for arrays within a large domain. there are numerous methods addressing the array data-flow problem; however, these methods are only used in the optimization or parallelization of programs. data-flow testing, however, requires at least one real solution of the problem for which the necessary program path is executed. contrary to former precise methods, we avoid negation in formulae, which seems to be the biggest problem in all previous methods.
on the time overhead of counters and traversal markers. the problem of minimizing the time overhead of counters and traversal markers is studied. the methodology used to study the problem is based upon markov processes. a fundamental result is presented that characterizes those flowcharts where the problem can be solved uniquely in the case of counters. two methods are described that avoid poor choices of counter placement by choosing counter placements from a dominating set. with respect to the problem of traversal marker placement, the basic result that traversal markers must be placed on the complement of a uni-connected sub-graph is extended to flowcharts with circuits. finally it is shown that complements of uni-connected subgraphs that are minimal in size may not have minimal time overheads.
global data flow analysis by decomposition into primes. the concept of prime program is applied as a decomposition technique to the global data flow analysis problem. this is done both in the abstract and through the use of the live variables problem as an example. it is also shown how the prime program decomposition is equivalent to the arrangement of a certain matrix (associated with the global data flow analysis problem) into block triangular form.
an algebra for data flow anomaly detection. an algebra a is developed that is specialized for the detection of data flow anomalies by interpreting the regular expression for the paths in a program as an a expression. two methods are subsequently presented that use a but do not require the explicit computation of the regular expression for the paths. one method is based on the prime program decomposition. the other is based upon the iterative algorithms of global data flow analysis. in addition the use of the algebra to get better warning messages than just the detection of anomalies is presented.
the detection of anomalous interprocedural data flow. in an earlier paper, the authors have defined type 1 and type 2 data flow anomalies to be, respectively, the reference to an undefined variable and the definition of a variable without subsequent reference. it is not difficult to devise search techniques to detect such anomalies when the anomalous data flow is contained in a single procedure. when the data flow crosses procedure boundaries, however, many difficulties may arise. in this paper, we carefully define the conditions under which interprocedural anomalies occur. we also show how algorithms currently used in global program optimization can easily be adapted to yield highly efficient algorithms for the detection of such interprocedural anomalies.
ltsa-ws: a tool for model-based verification of web service compositions and choreography. in this paper we describe a tool for a model-based approach to verifying compositions of web service implementations. the tool supports verification of properties created from design specifications and implementation models to confirm expected results from the viewpoints of both the designer and implementer. scenarios are modeled in uml, in the form of message sequence charts (mscs), and then compiled into the finite state process (fsp) process algebra to concisely model the required behavior. bpel4ws implementations are mechanically translated to fsp to allow an equivalence trace verification process to be performed. by providing early design verification and validation, the implementation, testing and deployment of web service compositions can be eased through the understanding of the behavior exhibited by the composition. the approach is implemented as a plug-in for the eclipse development environment providing cooperating tools for specification, formal modeling, verification and validation of the composition process.
refactoring. this tutorial is an example driven introduction to refactoring: a disciplined approach to changing the design of an existing code base.
information systems architecture. this tutorial provides an overview of patterns and principles that we've found useful in designing business information systems.
uml for software engineers. this tutorial presents the modeling concepts of the standard object modeling language, the unified modeling language (uml). particular attention is paid to the use of the uml for modeling system/software requirements and designs. a system development process and an example of its application is presented. the materials will be based on the recently released uml 1.4 standard. the tutorial also presents some of the major issues and challenges facing the evolution of the uml.
an interactive debugger for a concurrent language. this work deals with issues of interactive debugging for the concurrent language ecsp. the debugger matches a formal specification of the expected behavior of a program against its actual behaviour. this specification can be given at different levels of abstraction. control is returned to the user when an error is detected. the user can then modify the flow of the computation and/or dynamically change the specification of the expected behavior. the debugger implementation is based on program transformation techniques.
a hybrid architectural style for distributed parallel processing of generic data streams. immersive, interactive applications grouped under theconcept of immersipresence require on-line processing andmixing of multimedia data streams and structures. one criticalissue seldom addressed is the integration of differentsolutions to technical challenges, developed independentlyin separate fields, into working systems, that operateunder hard performance constraints. in order to realizethe immersipresence vision, a consistent, generic approachto system integration is needed, that is adapted tothe constraints of research development. this paper introducessai, a new software architecture model for designing,analyzing and implementing applications performing distributed,asynchronous parallel processing of generic datastreams. sai provides a universal framework for the distributedimplementation of algorithms and their easy integrationinto complex systems that exhibit desirable softwareengineering qualities such as efficiency, scalability, extensibility,reusability and interoperability. the sai architecturalstyle and its properties are described. the use of saiand of its supporting open source middleware (mfsm) is illustratedwith integrated, distributed interactive systems.
hardware/software codesign: a perspective. the authors propose that rather than maintain the traditional distinction between hardware and software engineering, a more fruitful approach to computer system design is to combine the hardware and software perspectives from the earliest stages of the design process and exploit the design flexibility and efficient allocation of function that such an approach offers. since current hardware and software design methodologies have their differences, a unified codesign approach must be developed that will comprise both the hardware and software points of view. increasingly, computer system design of the future will require this codesign approach. custom chip design and asic design are discussed. issues in codesign are considered
an analytical comparison of the fault-detecting ability of data flow testing techniques. compares several data flow based software testing criteria to one another and to branch testing. the fact that criterion c1 subsumes criterion c2, does not guarantee that c1 is better at detecting faults than c2. however, if a certain stronger relation between the criteria holds, then for any program and any specification, c1 is guaranteed to be better at detecting faults than c2 in the following sense: a test suite selected by independent random selection of one test case from each c1 subdomain is at least as likely to detect a fault as a suite similarly selected using c2. it is shown that under those conditions, the expected number of failure-causing inputs in the c1 test suite. these results are used to compare a number of data flow testing criteria to one another and to branch testing
effective identification of source code authors using byte-level information. source code author identification deals with the task of identifying the most likely author of a computer program, given a set of predefined author candidates. this is usually .based on the analysis of other program samples of undisputed authorship by the same programmer. there are several cases where the application of such a method could be of a major benefit, such as authorship disputes, proof of authorship in court, tracing the source of code left in the system after a cyber attack, etc. we present a new approach, called the scap (source code author profiles) approach, based on byte-level n-gram profiles in order to represent a source code author's style. experiments on data sets of different programming-language (java or c++) and varying difficulty (6 to 30 candidate authors) demonstrate the effectiveness of the proposed approach.a comparison with a previous source code authorship identification study based on more complicated information shows that the scap approach is language independent and that n-gram author profiles are better able to capture the idiosyncrasies of the source code authors. moreover, the scap approach is able to deal surprisingly well with cases where only a limited amount of very short programs per programmer is available for training. it is also demonstrated that the effectiveness of the proposed model is not affected by the absence of comments in the source code, a condition usually met in cyber-crime cases.
trustworthy and sustainable operations in marine environments. in order to address challenges and opportunities of engineering information systems for network-centric warfare, we have developed a prototype for trustworthy and sustainable operations in marine environments (twosome). the system developed addressed qualities such as information fusion, target acquisition, and self-organization in open computational systems; comprised of distributed services. as such, the system prototype executes on a service-oriented layered architecture for communicating entities (solace) and, furthermore, different perspectives of the prototype are visualized by means of a distributed interaction system for complex entity relation networks (discern).
a proposed curriculum for software engineering education. we propose a curriculum for a graduate professional degree in software engineering. after presenting the instructional objectives to be met by this curriculum, we present its underlying philosophy and assumptions. a number of suggestions are made for implementing the curriculum. in particular, we emphasize that this is a specific curriculum (for a master's degree) which can serve as a starting point for the development of other software engineering curricula.
essential elements of software engineering education. software engineering involves the application of principles of computer science, management science, and other fields to the design and construction of software systems. education in software engineering is fundamentally different from education in computer science, management science, or other constituent fields, even though it shares a large common area of concern. as we move toward the development of coordinated software engineering curricula, it is mandatory that we identify principles, not just random collections of techniques, on which to build them. our research, teaching, and practical experience leads us to argue for five essential elements of any software engineering curriculum: computer science, management science, communication skills, problem solving, and design methodology. this paper will discuss these areas, illustrate their current application in courses, and indicate their implications for curriculum development.
refactoring-aware version control. today, refactorings are supported in some integrated development environments (ides). the refactoring operations can only work correctly if all source code that needs to be changed is available to the ide. however, this precondition neither holds for application programming interface (api) evolution, nor in team development. the research presented in this paper aims to support refactoring in api evolution and team development by extending ide and version control to allow refactoring-aware merging and migration.
architectural framework modeling in telecommunication domain. architectural frameworks have been shown to increase the design reusability in large-scale object-oriented systems. drawing on experience in complex software systems development in the telecommunication domain, we present concepts and techniques for domain partitioning and an architectural framework modeling and layering. in particular, we discuss how a component-based approach, architectural modeling styles, and the systematic usage of architectural and design patterns provide a common framework for product-line development. two application frameworks based on this model are presented as case studies.
dynalloy: upgrading alloy with actions. we present dynalloy, an extension to the alloy specification language to describe dynamic properties of systems using actions. actions allow us to appropriately specify dynamic properties, particularly, properties regarding execution traces, in the style of dynamic logic specifications.we extend alloy's syntax with a notation for partial correctness assertions, whose semantics relies on an adaptation of dijkstra's weakest liberal precondition. these assertions, defined in terms of actions, allow us to easily express properties regarding executions, favoring the separation of concerns between the static and dynamic aspects of a system specification.we also extend the alloy tool in such a way that dynalloy specifications are also automatically analyzable, as standard alloy specifications. we present the foundations, two case-studies, and empirical results evidencing that the analysis of dynalloy specifications can be performed efficiently.
mgen - a generator for menu driven programs. many interactive computer applications can with advantage be built after the menu principle. mgen is a program that automatically builds a skeleton of a menu driven program. it is a well known problem that users of programs normally cannot state what they really want until they see the finished program running. with mgen, the resulting program can be simulated by the use of examples. to enable efficient utilization by skilled users, a feature called &ldquo;quick selection&rdquo; is implemented.
unifying artifacts and activities in a visual tool for distributed software development teams. in large projects, software developers struggle with two sources of complexity ¿ the complexity of the code itself, and the complexity of of the process of producing it. both of these concerns have been subjected to considerable research investigation, and tools and techniques have been developed to help manage them. however, these solutions have generally been developed independently, making it difficult to deal with problems that inherently span both dimensions.we describe augur, a visualization tool that supports distributed software development processes. augur creates visual representations of both software artifacts and software development activities, and, crucially, allows developers to explore the relationship between them. augur is designed not for managers, but for the developers participating in the software development process.we discuss some of the early results of informal evaluation with open source software developers. our experiences to date suggest that combining views of artifacts and activities is both meaningful and valuable to software developers.
the intertwining between risk and project management. this summary recalls the aims of the tutorial, describes its main topics and lists its contents.
examples of applying software estimate tool. although estimating the cost of a software project and the effort involved is very important, improving accuracy and establishing the software as a technology are both difficult. to solve these problems we have tried to use a software estimating tool. this tool has two characteristics. the first is that the tool uses function point analysis (fpa) instead of source lines of code, and the second is that special factors present in software development (usually estimated only from experience) are considered. this report provides some examples of how software project effort estimates can be improved
prompter: a knowledge based support tool for code understanding. as an experiment for the application of knowledge-based techniques to large-scale software maintenance, a program called prompter which produces annotations for programs written in an assembly language is being developed. prompter adopts object-oriented approach and represents both hardware and programming knowledge as class/instance definitions. object-oriented representation helps decompose the knowledge and organize it in a hierarchical way. it is shown that most of conventions such as data definitions which are the major obstacles to understanding system programs can be well formalized in this framework.
efficiency analysis of model-based review in actual software design. in this paper, we quantitatively analyze the efficiency of the model-based review (mbr) method in an actual software design from the two points of view; cost and reviewability. the mbr method is a modeling procedure for the purpose of reviewing preliminary design specifications of web-based applications. we have collected process data in applying both of the mbr method and an ordinary review to a preliminary design of a developing web-based library system. analyzing the collected process data, we quantitatively compare the efficiency of the mbr method and that of the ordinary review. as a result of this comparative analysis, we show that the mbr method is superior to the ordinary review in terms of not only reviewability but also cost through the experimental design process.
development of computer programs by problem analysis diagram (pad). a new tree-structured diagram for describing computer program logics is presented. the diagraming technique called pad(problem analysis diagram) is used as basis in establishing method of coding, testing, and data type description. it is proposed as a functionally superior substitute for flowcharts. the fact that some 1000 hitachi programmers have converted from flowcharts to pad within the last 15 months is indicative of the broad potential utility of this notation.
parameterized programming in obj2. parameterized programming [9] is a powerful technique for the construction, maintenance, and reuse of software. in this technique, modules may be parameterized over very general interfaces that describe what properties of an environment are required for the module to work correctly. ease of construction, maintenance, and reuse of software are all enhanced by the flexibility of the parameterization mechanism provided.obj2 [8] is designed to support parameterized programming, using algebraic specification techniques [2, 16, 17]; it provides facilities for user-definable abstract data types, parameterized
a hierarchical structuring method for functional software systems. a hierarchical structuring method for functional software systems is described. this method is greatly influenced by the authors experiences in developing the experimental hierarchical software processor (hisp) during the last four years. in this paper, however, the method is described in a general setting. this method appears to be applicable to a broad class of functional software systems. we first describe the words &ldquo;functional&rdquo; and &ldquo;hierarchical&rdquo;. then the hierarchical structuring method is presented. some applications of this method are also discussed. in particular, an example of transformational programming based on this structuring method is presented. the truncated syntax diagrams of the hisp language are also given as an appendix.
the design of a reliable applications system. the design of tactics, a large interactive statistical analysis and modelling system which has proven highly reliable is presented. overall reliability was achieved by first identifying and then focusing on the critical system components. these are enumerated and their design described in detail.
software evolution: analysis and visualization. gaining higher level evolutionary information about large software systems is a key challenge in dealing with increasing complexity and decreasing software quality. software repositories such as modifications, changes, or release information are rich sources for distinctive kinds of analyses: they reflect the reasons and effects of particular changes made to the software system over a certain period of time. if we can analyze these repositories in an effective way, we get a clearer picture of the status of the software. software repositories can be analyzed to provide information about the problems concerning a particular feature or a set of features. hidden dependencies of structurally unrelated but over time logically coupled files exhibit a high potential to illustrate software evolution and possible architectural deterioration. in this tutorial, we describe the investigation of software evolution by taking a step towards reflecting the analysis results against software quality attributes. different kinds of analyses (from architecture to code) and their interpretation will be presented and discussed in relation to quality attributes. this will show our vision of where such evolution investigations can lead and how they can support development. for that, the tutorial will touch issues such as meta-models for evolution data, data analysis and history mining, software quality attributes, as well as visualization of analysis results.
agile, open source, distributed, and on-time: inside the eclipse development process. eclipse is a widely recognized open source project dedicated to providing a platform for developing integrated tools. throughout the history of eclipse the development team was successful in hitting projected delivery dates with precision and quality. this isn't possible without a team strongly committed to ship quality software. how is this really done? how does eclipse achieve quality and just-in-time delivery?this talk sheds light on the key practices of the eclipse development process - from the development mantras "always beta", "milestones first", "api first", and "performance first" to practices such as ensuring quality through multiple feedback loops. erich will reflect on proven practices for managing a large project performed by geographically dispersed teams and open source contributors in a highly competitive market. most of these practices have evolved in the open source project, but they are equally applicable to closed source projects and will help to improve quality, timeliness and reduce development stress in both types of environments.
automatic discovery of api-level exploits. we argue that finding vulnerabilities in software components is different from finding exploits against them. exploits that compromise security often use several low-level details of the component, such as layouts of stack frames. existing software analysis tools, while effective at identifying vulnerabilities, fail to model low-level details, and are hence unsuitable for exploit-finding.we study the issues involved in exploit-finding by considering application programming interface (api) level exploits. a software component is vulnerable to an api-level exploit if its security can be compromised by invoking a sequence of api operations allowed by the component. we present a framework to model low-level details of apis, and develop an automatic technique based on bounded, infinite-state model checking to discover api-level exploits.we present two instantiations of this framework. we show that format-string exploits can be modeled as api-level exploits, and demonstrate our technique by finding exploits against vulnerabilities in widely-used software. we also use the framework to model a cryptographic-key management api (the ibm cca) and demonstrate a tool that identifies a previously known exploit.
a specification matching based approach to reverse engineering. specification matching is a technique that has been used to retrieve reusable components from reuse libraries. the relationship between a query specification and a library specification is typically based on refinement, where a library specification matches a query specification if the library specification is more detailed than the query specification. reverse engineering is a process of analyzing components and component interrelationships in order to construct descriptions of a system at a higher level of abstraction. in this paper, we define the concept of an abstraction match as a basis for reverse engineering and show how the abstraction match can be used to facilitate a process for generalizing specifications. finally, we apply the specification generalization technique to a portion of a nasa jpl ground-based mission control system for unmanned flight systems.
an approach to architectural analysis of product lines. this paper addresses the issue of how to perform architectural analysis on an existing product line architecture. the con tribution of the paper is to identify and demonstrate a repeatable product line architecture analysis process. the approach defines a &ldquo;good&rdquo; product line architecture in terms of those quality attributes required by the particular product line under development. it then analyzes the architecture against these criteria by both manual and tool-supported methods. the phased approach described in this paper provides a structured analysis of an existing product line architecture using (1) formal specification of the high-level architecture, (2) manual analysis of scenarios to exercise the architecture's support for required variabilities, and (3) model checking of critical behaviors at the architectural level that are required for all systems in the product line. results of an application to a software product line of spaceborne telescopes are used to explain and evaluate the approach.
experiences on defining and evaluating an adapted review process. this paper presents our experiences with the introduction of a review process for software requirements documents in a development project of the passenger car development business unit (pcd) of daimlerchrylser ag. as software quality management and quality assurance must be carefully integrated into existing company processes or business cultures, we had to substantially adapt the review process to the specific needs of the above project and its context characteristics. the chief difference to the traditional procedure for conducting reviews as, for example, set out in [1] or [2] is that our review process has a strong workshop character with an emphasis on one of the most crucial success factors for reviews: sufficient time for the individual preparation of the reviewers. we also describe the phase of analyzing the effort and defect data captured with respect to cost benefit aspects and the quality of the reviewed documents in relation to each other.
software engineering for large-scale multi-agent systems - selmas'05. software is becoming present in every aspect of our lives, pushing us inevitably towards a world of distributed, context-aware computing systems. selmas'05, "software everywhere - context-aware agents", was built on the success of precedent selmas workshops, but with a special emphasis on the impact of the agent technology in the development of large context-aware systems. selmas has a track record of bringing together researchers and practitioners with a variety of perspectives in order to engage in lively discussion and debate. a particular interest of this workshop was to understand those issues in the agent technology that make it difficult and/or improve the production of context-aware systems.
the smart approach for software process engineering. describes a methodology for software process engineering and an environment, smart, that supports it. smart supports a process life-cycle that includes the modeling, analysis, and execution of software processes. smart's process monitoring capabilities can be used to provide feedback from the process execution to the process model. smart represents the integration of three separately developed process mechanisms, and it uses two modeling formalisms (object-oriented data representation and imperative-style programming language) to bridge the gap between process modeling, analysis, and execution. smart demonstrates the meta-environment concept, using a process modeling formalism as input specification to a generator that produces process-centered software engineering environments (psees). furthermore, smart supports a team-oriented approach for process modeling, analysis, and execution
software architecture: practice, potential, and pitfalls. whatever the long-term impact of software architecture may turn out to be, an appropriate starting point is a concrete appraisal of the current state of the practice in the use of software architecture. it is the purpose of the article to take a step in this direction. it provides concrete examples of what is now possible when architectural principles are applied to industrial problems in systematic ways, considers the potential impact of software architecture over the next few years, and suggests steps that should be taken to bring this about
architectural mismatch or why it's hard to build systems out of existing parts. many would argue that future breakthroughs in software productivity will depend on our ability to combine existing pieces of software to produce new applications. an important step towards this goal is the development of new techniques to detect and cope with mismatches in the assembled parts. some problems of composition are due to low-level issues of interoperability, such as mismatches in programming languages or database schemas. however, in this paper we highlight a different, and in many ways more pervasive, class of problem: architectural mismatch. specifically, we use our experience in building a family of software design environments from existing parts to illustrate a variety of types of mismatch that center around the assumptions a reusable part makes about the structure of the application in which is to appear. based on this experience we show how an architectural view of the mismatch problem exposes some fundamental, thorny problems for software composition and suggests possible research avenues needed to solve them.
nico habermann's research: a brief retrospective. the last decade and a half of nico habermann's research career focused on software engineering, and in particular on software development environments. his earlier work was oriented more towards operating systems and programming language research. we take this opportunity to look back at his research, putting it in a larger perspective, identifying some general themes that characterize his contributions to software engineering in particular, and to computer science in general
deas 2005: workshop on the design and evolution of autonomic application software. understanding software engineering issues for autonomic computing systems is critical for the software and information technology sectors, which are continually challenged to reduce the complexity of their systems. to be autonomic, a system must know itself as well as its boundaries and its environment, configure and reconfigure itself, continually optimize itself, recover or heal from malfunction, protect itself, and function in a heterogeneous world-while keeping its complexity hidden from the user. the goal of this workshop is to bring together researchers and practitioners, who investigate concepts, methodologies, techniques, technologies, and tools to design and evolve autonomic software.
traffic-aware stress testing of distributed systems based on uml models. a stress test methodology aimed at increasing chances of discovering faults related to network traffic in distributed systems is presented. the technique uses the uml 2.0 model of the distributed system under test, augmented with timing information, and is based on an analysis of the control flow in sequence diagrams. it yields stress test requirements that are made of specific control flow paths along with time values indicating when to trigger them. different variants of our stress testing technique already exist (they stress different aspects of a distributed system) and we focus here on one variant that is designed to identify and to stress test the system at the instant when data traffic on a network is maximal. using a real-world distributed system specification, we design and implement a prototype distributed system and describe, for that particular system, how the stress test cases are derived and executed using our methodology. the stress test results indicate that the technique is significantly more effective at detecting network traffic-related faults when compared to test cases based on an operational profile.
process design engineering: a methodology for real-time software development. this paper describes the process design methodology, a disciplined engineering approach to development of a real-time software process. the approach described is part of an overall software research thrust, sponsored by the bmd advanced technology center, which is directed at resolving fundamental problems of excessive cost, failure to meet schedules, and inadequate performance associated with the specification, design, implementation, and testing of bmd software processes.
reporting about industrial strength software engineering courses for undergraduates. how do you organize an "industrial strength" one semester educational programming project for up to 200 second year students? this paper reports on four years of experience with such projects at the university of paderborn and the university of braunschweig. key properties of our project design are: starting with an existing large application, regular hard deadlines with peer reviews and presentations to a large audience, working in groups, applying project and configuration management tools, a standard system architecture with interchangeable components and competing software agents, quality assurance and standard conformance testing through final overall system integration spanning all groups, and exposure to real-world project threats.
a model of roll-back recovery with multiple checkpoints. a stochastic model of a transaction oriented computer system in the presence of intermittent failures, operating with a checkpoint and roll-back recovery scheme, is proposed in the case of a hierarchy of checkpoints and failures. an analysis provides the stationary probability distribution for the model and the optimum checkpoint intervals for two cases of interest: when a fixed checkpoint is used for each failure and when the allowable checkpoint closest in time is used.
knowledge-based architectural adaptation management for self-adaptive systems. self-adaptive systems continually evaluate and modify their own behavior to meet changing demands. an important element in the construction of architecture-based self-adaptive software is the specification of adaptation policy: this extended abstract presents an overview of work towards basing such specification on architecture-centric knowledge-based policies. this approach leverages techniques from the artificial intelligence field to explicitly represent adaptation policy at the architectural level, providing for strong decoupling between policy specification and architectural compositions, and supports dynamic runtime policy evolution promoting reuse potential and runtime flexibility.
application of axiomatic methods to a specification analyser. the goal of this paper was to model a specification language and its analyser using axiomatic methods derived from those applied previously to abstract data type and state transition specifications. the models attempt to cover many interesting features of psl/psa, a widely used specification language and analyser for information systems. simple properties expected to hold for actual psl/psa were formalized and proved about some models, with assumptions about undefined parts. both model formulation and property proofs were performed within the affirm specification and verification system. the results show (1) the applicability of axiomatic methods for modeling a new kind of software system, (2) insights into the psl/psa class of specification system, (3) a possible route for formal definition of such analysers, and (4) additional lessons on the art of specification, modeling, verification, and validation.
formal methods: an international perspective. the goal of formal methods is to base the software development process upon a workable set of mathematical techniques. the common names associated with various subclasses of formal methods express both the purpose and mode of the technique; formal specification, mathematical verification, proofs of correctness, formal description languages, rigorous development methods, stepwise refinement, etc. north american and european research groups took different technical directions. the author provides the perspective of one us researcher who has been particularly influenced by the international forces shaping the formal methods field as both a technical subject and a social enterprise
observations on industrial practice using formal methods. formal methods refer to the use of mathematically based techniques in software and system engineering. the authors summarize observations on their use in a dozen applications in industrial settings. application goals ranged from reengineering to system certification. the purpose is to extract some of the key observations about practice in software engineering terms with minimal reference to formal methods terminology and glossing over distinctions among methods. the methodology of the study is described. applications include oscilloscopes, nuclear reactors, trains, planes, ships, satellites, smartcards, transaction processing, arithmetic units, networks, medical instruments, and language processors. the observations follow from a systematic survey of these applications using a structured interview process and analysis of results using a set of features covering various aspects of practice: process, methods, tools, and technology transfer
the challenges of software engineering education. we discuss the technical skills that a software engineer should possess. we take the viewpoint of a school of engineering and put the software engineer's education in the wider context of engineering education. we stress both the common aspects that crosscut all engineering fields and the specific issues that pertain to software engineering. we believe that even in a continuously evolving field like software, education should emphasize principles and recognize what are the stable and long-lasting design concepts. even though the more mundane technological solutions cannot be ignored, the students should be equipped with skills that allow them to dominate the evolution of technology.
assume-guarantee verification of source code with design-level assumptions. model checking is an automated technique that can beused to determine whether a system satisfies certain requiredproperties. to address the "state explosion" problemassociated with this technique, we propose to integrateassume-guarantee verification at different phases of systemdevelopment. during design, developers build abstract behavioralmodels of the system components and use them toestablish key properties of the system. to increase the scalabilityof model checking at this level, we have previously developedtechniques that automatically decompose the verification task by generating component assumptions for the properties to hold. the design artifacts are subsequentlyused to guide the implementation of the system, but also toenable more efficient reasoning of the source code. in particular,we propose to use assumptions generated for the designto similarly decompose the verification of the actualsystem implementation. we demonstrate our approach ona significant nasa application, where design models wereused to identify and correct a safety property violation, andthe generated assumptions allowed us to check successfullythat the property was preserved by the implementation.
advanced visual modeling (tutorial session): beyond uml. the tutorial is example driven and illustrates how the new notations are combined with those of uml, including ocl. some of the examples are drawn from industrial contexts, in particular the telecomms sector. highlights include:a crash critique of uml, stressing its weaknesses and strengths.a rich visual constraint language and an insight into subtle issues that arise when defining a visual language.lots of examples, some taken from an industrial context.a demonstration of a graphical editor (available free from the web and on disk at the tutorial) for the constraint-diagrams language.a series of 3d notations for providing rich visualizations of dynamic behavior.a vision for visual modeling tools of the futurefor more information see http://www.cs.ukc.ac.uk/people/staff/sjhk/cds.html
advanced visual modelling: beyond uml. with the adoption of uml by the omg and industry as the linguae-francae of visual systems modelling, one begins to ponder what will come next in this field? this tutorial brings a vision for visual modelling beyond uml. we present and consolidate radical new notations, proposed in a series of research papers and with quickly increasing adoption by industry, for the specification of complex systems in an intuitive visual, yet precise manner. the recurring theme of these notations is the upgrading of familiar diagrams into a powerful visual language. spider diagrams considerably extend venn-diagrams to the specification of oo-systems. most familiar oo-concepts are translated to set theoretical terms: class into set of objects, inheritance corresponding to subset, and even harel's statecharts interpreted as the set of objects in that state. constraint diagrams enhance the arrow notation to describe static system invariants which cannot be described by uml class-object diagram. reasoning rules are developed for the notation and strong completeness results are given. finally, 3d-diagrams show how the third dimension and vrml modelling can be used for a conceptual modelling of dynamic system behaviour. much of the tutorial will be based on a case study developed in industry, illustrating how the new notations are combined with those of uml, including ocl.highlights include:&bull; a crash critical overview in uml, stressing its weaknesses and strengths,&bull; a rich visual constraint language and an insight into subtle issues that arise when defining a visual language, for applying the popular design-by-contract using a visual formalism&bull; a discussion of diagrammatic reasoning with the notation, including completeness results&bull; a case study&bull; a demonstration of a graphical editor for the constraint-diagrams language&bull; a look to the future of visual modelling, including ideas about 3d modelling notations and visual modelling tools.
an integrated system for program testing using weak mutation and data flow analysis. the idea of weak mutation testing is to construct test data which would force program components such as expressions and variable references to produce a wrong 'result' if they were to contain certain types of error, for example, off-by-a-constant or wrong-variable. the idea of data flow driven testing is to construct test data which forces the execution of different interactions between variable definitions and references in a program. this paper describes a tool for fortran 77 programs which has been developed to help a user apply the weak mutation and data flow testing techniques. the tool instruments a given source program and collects a program execution history. it is then able to report on the completeness of the test data with respect to weak mutation and a family of data flow path selection criteria. some preliminary experiments with use of the tool are described.
designing and implementing : design process, architectural style, lessons learned. this paper reports on the design and implementation of a software development framework named coo (which stands for cooperation and coordination in the software process). its design process is first detailed and justified. then, the paper emphasizes its layered and subject-oriented architecture. particularly, it is shown how this architectural style leads to a very flexible and powerful way of defining, integrating and combining services in a software development environment.
interacting process classes. many reactive control systems consist of classes of interacting objects where the objects belonging to a class exhibit similar behaviors. such interacting process classes appear in telecommunication, transportation and avionics domains. in this paper, we propose a modeling and simulation technique for interacting process classes. our modeling style uses standard notations to capture behavior. in particular, the control flow of a process class is captured by a labeled transition system, unit interactions between process objects are described by message sequence charts and the structural relations are captured via class diagrams. the key feature of our approach is that our execution semantics leads to a symbolic simulation technique. our simulation strategy is both time and memory efficient and we demonstrate this on well-studied non-trivial examples of reactive systems.
the value of a usability-supporting architectural pattern in software architecture design: a controlled experiment. design patterns have been claimed to facilitate modification and improve understanding in software design. a controlled experiment was performed to assess the usefulness of portions of a usability-supporting architectural pattern (usap) in modifying the design of software architectures to support a specific usability concern. software engineering and information technology graduate students received different subsets of a usap supporting cancellation functionality. they then studied a software architecture design and made modifications to add the ability to cancel commands. results showed that participants who received a usability scenario, a list of general responsibilities, and a sample solution thought of significantly more key issues than participants who saw only the scenario. implications for software development are that usability concerns can be included at architecture design time, and that usaps can significantly help software architects to consider responsibilities inherent from usability concerns.
designing concurrent, distributed, and real-time applications with uml. object-oriented concepts are crucial in software design because they address fundamental issues of adaptation and evolution. with the proliferation of object-oriented notations and methods, the unified modeling language (uml) has emerged to provide a standardized notation for describing object-oriented models. however, for the uml notation to be effectively applied, it needs to be used with an object-oriented analysis and design method. this tutorial describes the comet method for designing real-time and distributed applications, which integrates object-oriented and concurrency concepts and uses uml.
designing concurrent, distributed, and real-time applications with uml. object-oriented concepts are crucial in software design because they address fundamental issues of adaptation and evolution. with the proliferation of object-oriented notations and methods, the unified modeling language (uml) has emerged to provide a standardized notation for describing object-oriented models. however, for the uml notation to be effectively applied, it needs to be used with an object-oriented analysis and design method. this tutorial describes the comet method for designing real-time and distributed applications, which integrates object-oriented and concurrency concepts and uses uml.
prototyping as a tool in the specification of user requirements. one of the major problems in developing new computer applications is specifying the user's requirements such that the requirements specification is correct, complete and unambiguous. although prototyping is often considered too expensive, correcting ambiguities and misunderstandings at the specification stage is significantly cheaper than correcting a system after it has gone into production. this paper describes how a prototype was used to help specify the requirements of a computer system to manage and control a semiconductor processing facility. the cost of developing and running the prototype was less than 10% of the total software development cost.
an interactive fortran structuring aid. this paper describes a tool at the jet propulsion laboratory which aids a programmer in converting fortran to a structured syntax. the program is a highly interactive system using computer graphics techniques to facilitate the operations necessary for such a conversion. editing and structure recognition capabilities, including the ability to handle arbitrary levels of block structure, have been combined into a system that reduces the effort involved in updating old software.
using weaves for software construction and analysis. the authors discuss the architectural features of weaves, their implementation, and their use in a variety of applications. weaves are networks of concurrently executing tool fragments that communicate by passing objects. weaves are distinguished from other dataflow styles by their emphasis on instrumentation, continuous observability, and dynamic rearrangement: basic low-overhead instrumentation is inserted automatically, executing weaves can be observed at any time by means of sophisticated analysis agents, without degrading the performance of the weave, and weaves can be dynamically snipped and spliced without interrupting the data flow
architecting in the face of uncertainty: an experience report. understanding an applicationýs functional and non-functionalrequirements is normally seen as essential fordeveloping a robust product suited to client needs. thispaper describes our experiences in a project that, bynecessity, commenced well before concrete clientrequirements could be known. after a first version of theapplication was successfully released, emergingrequirements forced an evolution of the applicationarchitecture. the key reasons for this are explained,along with the architectural strategies and softwareengineering practices that were adopted. the resultingapplication architecture is highly flexible, modifiable andscalable, and therefore should provide a solid foundationfor the duration of the applicationýs lifetime.
software component quality assessment in practice: successes and practical impediments. this paper describes the authors' experiences of initiating and sustaining a project at csiro aimed at accelerating the successful adoption of cots middleware technologies in large business and scientific information systems. the projects aims are described, along with example outcomes and an assessment of what is needed for wide-scale software component quality assessments to succeed.
architectures and technologies for enterprise application integration. architects are faced with the problem of buildingenterprise scale information systems, with streamlined,automated internal business processes and web-enabledbusiness functions, all across multiple legacyapplications. the underlying architectures for suchsystems are embodied in a range of diverse productsknown as enterprise application integration (eai)technologies. in this tutorial, we highlight some of themajor problems, approaches and issues in designingeai architectures and selecting appropriatesupporting technology. the tutorial presents a rangeof the common architectural patterns frequently usedfor eai applications. it also explains service orientedarchitectures as the current best practice architecturalframework for eai. it then describes the state-or-the-artin eai technologies that support thesearchitectural styles, and discusses some of the keydesign trade-offs involved when selecting anappropriate integration technology (including buyversus build decisions).
an architects guide to enterprise application integration with j2ee and .net. architects are faced with the problem of building enterprise scale information systems, with streamlined, automated internal business processes and web-enabled business functions, all across multiple legacy applications. the underlying architectures for such systems are embodied in a range of diverse products known as enterprise application integration (eai) technologies. in this tutorial, we highlight some of the major problems, approaches and issues in designing eai architectures and selecting appropriate supporting technology. an architect's perspective on designing large-scale integrated applications is taken, and we discuss requirements elicitation, architecture patterns, eai technology and features, and risk mitigation. j2ee and .net technologies are used to illustrate the capabilities of state-or-the-art integration technologies.
tool support for just-in-time architecture reconstruction and evaluation: an experience report. the need for software architecture evaluation has drawn considerable attention in recent years. in practice, this is a challenging exercise for two main reasons. first, in deployed projects, software architecture documentation is often not readily available, and may not be a correct representation of the as built architecture. second, large software systems have numerous potential views of the various architecturally significant structures in the system. in this paper we assess the capabilities of software reverse engineering and architecture reconstruction tools to support just-in-time architecture reconstruction. if an application's architecture can be reconstructed efficiently, this could promote more effective architecture reviews and evaluations. we describe our experiences in leveraging multiple reconstruction tools and how these guided the choice of design artifacts to construct. we discovered that the tools complemented each other in identifying reconstruction scope, critical architectural elements, potential design irregularities and creating useful architectural views for different evaluation tasks. with the help of these tools, the reconstruction and evaluation effort was significantly streamlined and productive. finally, we also report some potential improvements these tools could make.
ethical considerations in software engineering. the author discusses ethical considerations that arise in the practice of software engineering and uses cases to help focus the discussion on ethical concerns in the practice of software engineering. the author comments on the relationship between software safety and ethics, informed consent and ethical decisions, the customer's responsibility for end-product quality, internal performance standards and customer consent to inferior work, and techniques for addressing ethical issues
on the modelling, analysis and design of protocols - a special class of software structures. in this paper we review briefly some of the formal models and techniques that can be applied on the modelling, analysis and design of communication protocols.
static checking of dynamically generated queries in database applications. many data-intensive applications dynamically constructqueries in response to client requests and execute them.java servlets, e.g., can create string representations ofsql queries and then send the queries, using jdbc, to adatabase server for execution. the servlet programmer enjoysstatic checking via javaýs strong type system. however,the java type system does little to check for possible errorsin the dynamically generated sql query strings. thus,a type error in a generated selection query (e.g., comparinga string attribute with an integer) can result in an sqlruntime exception. currently, such defects must be rootedout through careful testing, or (worse) might be found bycustomers at runtime. in this paper, we present a sound,static, program analysis technique to verify the correctnessof dynamically generated query strings. we describe ouranalysis technique and provide soundness results for ourstatic analysis algorithm. we also describe the details of aprototype tool based on the algorithm and present severalillustrative defects found in senior software-engineeringstudent-team projects, online tutorial examples, and a real-worldpurchase order system written by one of the authors.
dynamic restructuring in an experimental operating system. a well-structured system can easily be understood and modified. moreover, it may lend itself even to dynamic modification: under special conditions, the possibility of changing system parts while the system is running can be provided at little additional cost. our approach to the design of dynamically modifiable systems is based on the principle of data abstraction applied to types and modules. it allows for dynamic replacement or restructuring of a module's implementation if this does not affect its specification (or if it leads to some kdnd of compatible specification). the fundamental principles of such "replugging" are exhibited, and the implementation of a replugging facility for an experimental operating system on a pdp-11/40e is described.
linguistic support for the evolutionary design of software architectures. as a program's functionality evolves over time, its software architecture should evolve as well so that it continues to match the program's design. this paper introduces the architecture language of clock, a language for the development of interactive, multiuser applications. this architecture language possesses three properties supporting the easy restructuring of software architectures: restricted scoping supported by a constraint-based communication system, automatic message routing, and easy hierarchical restructuring of architectures. clock's architecture language has a visual syntax, supported by the clock-works programming environment.
advanced control flows for flexible graphical user interfaces: or, growing guis on trees or, bookmarking guis. web and gui programs represent two extremely common and popular modes of human-computer interaction. many gui programs share the web's notion of browsing through data- and decision-trees. this paper compares the user's browsing power in the two cases and illustrates that many gui programs fall short of the web's power to clone windows and bookmark applications. it identifies a key implementation problem that gui programs must overcome to provide this power. it then describes a theoretically well-founded programming pattern, which we have automated, that endows gui programs with these capabilities. the paper provides concrete examples of the transformation in action.
an empirical study of regression test selection techniques. regression testing is the process of validating modified software to detect whether new errors have been introduced into previously tested code and to provide confidence that modifications are correct. since regression testing is an expensive process, researchers have proposed regression test selection techniques as a way to reduce some of this expense. these techniques attempt to reduce costs by selecting and running only a subset of the test cases in a program's existing test suite. although there have been some analytical and empirical evaluations of individual techniques, to our knowledge only one comparative study, focusing on one aspect of two of these techniques, has been reported in the literature. we conducted an experiment to examine the relative costs and benefits of several regression test selection techniques. the experiment examined five techniques for reusing test cases, focusing on their relative ablilities to reduce regression testing effort and uncover faults in modified programs. our results highlight several differences between the techiques, and expose essential trade-offs that should be considered when choosing a technique for practical application.
using software component generators to contstruct a meta-weaver framework. several new modularity technologies have been proposed that improve separation of concerns in programming languages. the initial efforts to demonstrate these technologies are usually focused on a single programming language. since we live in a polyglot world, this proposal addresses the goal of being able to take these new powerful technologies to other languages. the approach uses software generators that create new &ldquo;weavers&rdquo; from meta-specifications of programming languages.
design of large-scale polylingual systems. building systems from existing applications writtenin two or more languages is common practice. such systemsare polylingual. polylingual systems are relatively easyto build when the number of apis needed to achieve languageinteroperability is small. however, when the numberof distinct apis become large, maintaining and evolvingpolylingual systems becomes a notoriously difficult task.in this paper, we present a simple, practical, and effectiveway to develop, maintain, and evolve large-scale polylingualsystems. our approach relies on recursive type systemswhose instances can be manipulated by reflection. foreignobjects (i.e. objects that are not defined in a host programminglanguage) are abstracted as graphs and path expressionsare used for accessing and manipulating data. pathexpressions are implemented by type reification ¿ turningforeign type instances into first-class objects and enablingaccess to and manipulation of them in a host programminglanguage. doing this results in multiple benefits, includingcoding simplicity and uniformity that we demonstrate in acomplex commercial project.
the design of the psi program synthesis system. this paper presents an overview of the current state of the psi automatic program synthesis system and discusses the design considerations. the psi system allows a user to specify a desired program in a dialogue using natural language and traces. psi then synthesizes a program meeting these specifications. the target programs are simple symbolic computation programs in lisp. psi may be described as a knowledge-based program understanding system. it is organized as a collection of closely interacting modules, or experts in the areas of natural language, discourse, traces, application domain, high-level program modelling, coding, and efficiency. an implementation effort is underway and several modules are now working.
assuring and evolving concurrent programs: annotations and policy. assuring and evolving concurrent programs requires understanding the concurrency-related design decisions used in their implementation. in java-style shared-memory programs, these decisions include which state is shared, how access to it is regulated, the roles of threads, and the policy that distinguishes desired concurrency from race conditions. these decisions rarely have purely local manifestations in code.in this paper, we use case studies from production java code to explore the costs and benefits of a new annotation-based approach for expressing design intent. our intent is both to assist in establishing "thread safety" attributes in code and to support tools that safely restructure code---for example, shifting critical section boundaries or splitting locks. the annotations we use express "mechanical" properties such as lock-state associations, uniqueness of references, and encapsulation of state into named aggregations. our analyses revealed race conditions in our case study samples, drawn from open-source projects and library code.the novel technical features of this approach include (1) flexible encapsulation via aggregations of state that can cross object boundaries, (2) the association of locks with state aggregations, (3) policy descriptions for allowable method interleavings, and (4) the incremental process for inserting, validating, and exploiting annotations.
capturing more world knowledge in the requirements specification. the view is adopted that software requirements involve the representation (modeling) of considerable real-world knowledge, not just functional specifications. a framework (rmf) for requirements models is presented and its main features are illustrated. rmf allows information about three types of conceptual entities (objects, activities, and assertions) to be recorded uniformly using the notion of properties. by grouping all entities into classes or metaclasses, and by organizing classes into generalization (specialization) hierarchies, rmf supports three abstraction principles (classification, aggregation, and generalization) which appear to be of universal importance in the development and organization of complex descriptions. finally, by providing a mathematical model underlying our terminology, we achieve both unambiguity and the potential to verify consistency of the model.
on formal requirements modeling languages: rml revisited. research issues related to requirements modeling are introduced and discussed through a review of the requirements modeling language rml, its peers and its successors from the time it was first proposed at the sixth international conference on software engineering (icse-6) to the present - ten icses later. we note that the central theme of &ldquo;capturing more world knowledge&rdquo; in the original rml proposal is becoming increasingly important in requirements engineering. the paper highlights key ideas and research issues that have driven rml and its peers, evaluates them retrospectively in the context of experience and more recent developments, and points out significant remaining problems and directions for requirements modeling research
cooperating evolving components: a rigorous approach to evolving large software systems. large software systems have a large number of components and are developed over a long time period frequently by a large number of people. we describe a framework approach to evolving such systems based on an integration of product and process modelling. the evolving system is represented as a product tower, a hierarchy of components which provides views of the product at multiple levels of refinement. the evolution process is component based with the cooperation between components being mediated by the product tower. this ensures that the evolution process is scaleable and that it maintains, and evolves, the design model. we illustrate our approach with an example, outlining an evolution both of the product and of the process. the reflexive facilities of the process are shown to be key in ensuring the framework's ability to evolve.
software technology in an automotive company - major challenges. the automotive industry is one of the sectors which has been affected significantly by the industrial software revolution during the last few years. competitive challenges, which are of major relevance for the growing number of software-based automotive innovations, are presented by a dramatic growth in system complexity, rising time and cost pressure, and high quality demands.all these requirements lead to a number of software-related challenges which will be of significant competitive importance for the automotive industry in the future. asides from the question of whether an automotive company decides to develop software in-house or whether this is carried out by suppliers, every automotive key player has to hold or to build up specific software competencies. the most important competence areas are the software development process, software quality management including supplier cooperation, the overall architecture of the in-vehicle software, as well as the ability to specify, to integrate and to test the system.
software needs engineering: a position paper. when the general press refers to 'software' in its headlines, then this is often not to relate a success story, but to expand on yet another 'software-risk-turned-problem-story.'for many people the term 'software' evokes the image of an application package running either on a pc or some similar stand-alone usage. over 70% of all software, however, are not developed in the traditional software houses as part of the creation of such packages. much of this software comes in the form of products and services that end users would not readily associate with software. these can be complex systems with crucial connections made through software, such as telecommunications or banking systems, or the logistics systems of airports. or these can be end-user products with software embedded, ranging from battery management systems in electric shavers, over mobile phones to engine management and safety systems in cars. e-commerce systems fall into this category, too.yes, there is software that works reliably and as expected, and there are professional approaches to create such products &mdash; one can engineer software, in the right environment, with the right people.
software reuse experience at hewlett-packard. at hewlett-packard, we have had visible divisional software reuse efforts since the mid-1980s. in 1990, we initiated a multi-faceted corporate reuse program to gather information about reuse from within hp and from other companies. as we studied the existing reuse programs, we discovered that certain issues were poorly understood, and as a consequence, mistakes were made in starting and running certain programs at hp and elsewhere. our corporate reuse program focused on packaging best-practice information and guidelines to avoid common pitfalls. we also developed technology transfer and educational processes to spread this information and enhance reuse practice within the company. in 1992, we launched a multi-disciplinary research program to investigate and develop better methods for domain-specific, reuse-based software engineering. we have learned that for large-scale reuse to work, the problems to be overcome are mostly non-technical
architecting for large-scale systematic component reuse. organizations building highly complex business and technical systems need to architect families of systems and implement these with large-scale component reuse. without carefully architecting the systems, components, organizations and processes for reuse, object reuse will not succeed. experience with software reuse practice and adoption experience at hp and ericsson led us to a systematic approach to component-based software engineering, based on object-oriented business and system modeling. this article explains how higher-level uml constructs support architected reuse, and describes a systematic process, leading from the business processes of an enterprise, through the system architecture for a family of applications that support these business processes, to the design and use of highly reusable component systems.
a component architecture for an extensible, highly integrated context-aware computing infrastructure. ubiquitous context-aware computing systems present several challenges in their construction. principal among them is the tradeoff between easily providing new context-aware services to users and the tight integration of those services, as demanded by the small form factor of the devices typically found in ubiquitous computing environments. performance issues further complicate the management of this tradeoff.mechanisms have been proposed and toolkits developed for aiding the construction of context-aware systems, but there has been little consideration of how to specialize, organize, and compose these mechanisms to meet the above requirements. we motivate and describe a software architecture that provides the desired integration and extensibility of services in a context-aware application infrastructure. a key result is the fissioning of intuitive class organizations, both across layers and within layers, to achieve the required integration of services and separation of concerns.
introduction to research papers. at the heart of the icse-2005 program are the 44 research papers selected by the program committee (pc) from the 313 submissions to the conference. all submissions were rigorously reviewed by the pc -- each submission received reviews from at least three different pc members. the pc then met on 5-6 november 2004 in newport beach, california, usa, to discuss the submissions and make the final selections for the program. each of the papers selected for publication in the proceedings and presentation at the conference was chosen on its own merits and without comparison to any others.the papers selected cover a wide range of research areas, which are not always amenable to a simple classification. nevertheless, the papers are clustered into sessions that broadly represent the dominant research themes of the work described.the pc comprised 43 members drawn from a wide cross section of the software engineering community. the pc members worked hard to put the program of research papers together. each pc member received an average of 22 papers to review prior to the pc meeting, followed by a substantial e-mail conversation and two full days discussing papers at the pc meeting. it was our pleasure and privilege to work with such a professional group of people to produce the quality of the program before you. our deepest thanks go to the pc.we must also thank the organizers of sigsoft fse 2005, who generously hosted our pc meeting and assisted in numerous local arrangements. in particular, we thank dick taylor, debra brodbeck, and susan knight. their help in producing a trouble-free, enjoyable pc meeting helped keep the pc's spirits high through two long days.we would be remiss if we did not lavish praise and thanks on richard van de stadt and the cyberchair conference management system. cyberchair streamlined many of the pc's activities, and richard added several new features to cyberchair that saved us days of work in staging the pc meeting.finally, we thank our general chair, catalin roman, for bringing us together, making us partners in creating icse 2005, and giving us the guidance and freedom we needed to create the best possible research program. in doing so, he has given us one of the most rewarding experiences of our professional lives.
exploiting the map metaphor in a tool for software evolution. software maintenance and evolution are the dominant activities in the software lifecycle. modularization can allow design decisions to be independently evolved, but eventually modularizations fail to do so, and then complicated global changes are required. tool support can reduce the costs of these unfortunate changes, but current tools are limited in their ability to manage information for large-scale software evolution. in this paper we argue that the map metaphor can serve as an organizing principle for the design of effective tools for performing global software changes. we describe the design of aspect browser, developed around the map metaphor, and discuss a case study of removing a feature from a 500,000 line program written in fortran and c.
workflow management based on process model repositories. workflow management is an area of increasing interest. nonetheless there are only a few workflow systems which are actually used for supporting business processes in an industrial context. most of these systems only deal with processes which create and manipulate unstructured pieces of information, like documents and images. our workflow management approach, called the funsoft net approach, additionally supports the management of structured pieces of information, called objects. in doing so, we use a repository which is used to store information about process models and about individual processes. this repository is particularly useful for processes dealing with highly structured information, such as software processes. we describe the experience in using such a repository. we point out which of these experiences may be useful for developers of other workflow management systems as well
software process modeling and enactment: an experience report related to problem tracking in an industrial project. the paper provides an overview of process research and the application of research results to practice and then describes process models using funsoft nets and a workflow management system leu. the example from which the experience is drawn is that of a problem tracking system and the components of the model are described and illustrated. the experience reported comes in three flavors: the appropriateness of funsoft nets as a modeling mechanisms and the alternative use of state transition diagrams; the benefits of the model and its support of the business process; and finally some implications for process research
workshop on directions in software engineering environments (wodisee). the goal of this workshop was is to bring togetherresearchers and practitioners with an interest indeveloping, extending, deploying and using softwareengineering tools. theis workshop will provides aninteractive forum for the exchange of ideas anddiscussion about future trends in software engineeringenvironment research and development.the outcomes of this workshop will beare a summary ofthe state of the art in software engineering environmentresearch and development, and the identification of keydirections for future research in this area.
identifying "good" architectural design alternatives with multi-objective optimization strategies. architecture trade-off analysis methods are appropriate techniques to evaluate design decisions and design alternatives with respect to conflicting quality requirements. however, the identification of good design alternatives is a time consuming task, which is currently performed manually. to automate this task, this paper proposes to use evolutionary algorithms and multi-objective optimization strategies based on architecture refactorings to identify a sufficient set of design alternatives. this approach will reduce development costs and improve the quality of the final system, because an automated and systematic search will identify more and better design alternatives.
self-healing web service compositions. no abstract available
fourth international workshop on dynamic analysis (woda 2006). dynamic analysis techniques reason over program executions and deal with data produced at program execution time. dynamic analysis and static analysis techniques complement each other. hence, a key focus of the workshop is dynamic analysis of software systems with an emphasis on research that integrates static and dynamic analyses.
a case study of a corporate open source development model. open source practices and tools have proven to be highly effective for overcoming the many problems of geographically distributed software development. we know relatively little, however, about the range of settings in which they work. in particular, can corporations use the open source development model effectively for software projects inside the corporate domain? or are these tools and practices incompatible with development environments, management practices, and market-driven schedule and feature decisions typical of a commercial software house? we present a case study of open source software development methodology adopted by a significant commercial software project in the telecommunications domain. we extract a number of lessons learned from the experience, and identify open research questions.
towards the principled design of software engineering diagrams. diagrammatic specification, modelling and programming languages are increasingly prevalent in software engineering and, it is often claimed, provide natural representations which permit of intuitive reasoning. a desirable goal of software engineering is the rigorous justification of such reasoning, yet many formal accounts of diagrammatic languages confuse or destroy any natural reading of the diagrams. hence they cannot be said to be intuitive. the answer, we feel, is to examine seriously the meaning and accuracy of the terms &ldquo;natural&rdquo; and &ldquo;intuitive&rdquo; in this context. this paper highlights, and illustrates by means of examples taken from industrial practice, an ongoing research theme of the authors. we take a deeper and more cognitively informed consideration of diagrams which leads us to a more natural formal underpinning that permits (i) the formal justification of informal intuitive arguments, without placing the onus of formality upon the engineer constructing the argument; and (ii) a principled approach to the identification of intuitive (and counter-intuitive) features of diagrammatic languages.
the design of data type specifications. this paper is about the design of data types in creating a software system. the major point is to explore a means for specifying a data type which is independent of its eventual implementation. the particular style of specification, called algebraic axioms, is exhibited by axiomatizing many commonly used data types. as such, these examples reveal a great deal about the intricacies of data type specification via algebraic axioms, and, in addition, provide a standard to which alternative forms may be compared. further uses of this specification technique are in proving the correctness of implementations and in interpretively executing a large system design before actual implementation commences.
feature-based decomposition of inductive proofs applied to real-time avionics software: an experience report. the hardware and software in modern aircraft controlsystems are good candidates for verification using formalmethods: they are complex, safety-critical, and challengethe capabilities of test-based verification strategies. wehave previously reported on our use of model checking toverify the time partitioning property of the deos¿ real-timeoperating system for embedded avionics. the size and complexityof this system have limited us to analyzing only oneconfiguration at a time. to overcome this limit and generalizeour analysis to arbitrary configurations we have turnedto theorem proving.this paper describes our use of the pvs theorem proverto analyze the deos scheduler. in addition to our inductiveproof of the time partitioning invariant, we present afeature-based technique for modeling state-transition systemsand formulating inductive invariants. this techniquefacilitates an incremental approach to theorem proving thatscales well to models of increasing complexity, and has thepotential to be applicable to a wide range of problems.
modular checking for buffer overflows in the large. we describe an ongoing project, the deployment of a modular checker to statically find and prevent every buffer overflow in future versions of a microsoft product. lightweight annotations specify requirements for safely using each buffer, and functions are checked individually to ensure they obey these requirements and do not overflow. our focus is on the incremental deployment of this technology: by layering the annotation language, using aggressive inference techniques, and slicing warnings by checker confidence, teams must pay only part of the cost of annotating a program to achieve part of the benefit, which provides incentive for further annotation. to date over 400,000 annotations have been added to specify buffer usage in the source code for this product, of which over 150,000 were automatically inferred, and over 3,000 potential buffer overflows have been found and fixed.
scientific rigour, an answer to a pragmatic question: a linguistic framework for software engineering. discussions of the role of mathematics in software engineering are common and have probably not changed much over the last few decades. there is now much discussion about the &ldquo;intuitive&rdquo; nature of software construction and analogies are drawn (falsely) with graphic design, (conventional) architecture, etc. the conclusion is that mathematics is an unnecessary luxury and that, like these other disciplines, it is not needed in everyday practice. we attempt to refute these arguments by recourse to ideas from the philosophy of science developed over the past century. we demonstrate why these ideas are applicable, why they establish a framework (in the sense of carnap) in which many central ideas in software engineering can be formalised and organised, why they refute the simplistic recourse to &ldquo;intuition&rdquo;, and why they provide a scientific/engineering framework in which contributions to the theory and practice of software engineering can be judged.
requirements analysis for real-time automation projects. it is in general accepted that the development of software consists of a series of activities which in ideal case follows one another sequentially. this general concept is represented through several life-cycle models, among which the most renowned model was proposed by b. boehm in his life-cycle model [l]. prorec (system for process oriented requirements capturing) has been developed on the basis of such a model and in the first phase of this development the analysis of the requirements and their formulations are investigated.
architecture-oriented programming using fred. implementing application-specific code conforming to architectural rules and conventions can be tedious. we will demonstrate a tool prototype for architecture-oriented programming that takes an architectural description as a set of programming patterns and provides an interactive task-based programming environment for the architecture. incorporating adaptive code generation and documentation, the tool provides a convenient way to adopt as well as effectively reuse a framework or architectural standard such as java beans.
preventing sql injection attacks using amnesia. amnesia is a tool that detects and prevents sql injection attacks by combining static analysis and runtime monitoring. empirical evaluation has shown that amnesia is both effective and efficient against sql injection.
tool interfaces in integrated project support environments. it is generally agreed that to meet these objectives and achieve integration an ipse should be built round a kernel or infrastructure of common services.coherence is then achieved if the infrastructure provides services to tools which relieve the toolwriter of the need to code, for example, user interface handling. not only does this aid uniformity, but of course it also offers economic leverage.control of the environment resides in the kernel and it is not possible for tools to ignore the controls and prejudice the integrity of the project data.sharing is achieved because the project data and its structure reside in the database which is under the control of the kernel.early efforts to build such an ipse were based on the stoneman model, where the kernel was the kapse. the crucial interface in this architecture is the kapse interface, which offers services to all tools. we did not sufficiently realise, however, that there is a major economic problem in designing a new interface from scratch. all tools which are to be used in an environment must, by definition, conform to this interface definition. this means that all the tools have to be specially written to use the new interface, and it became apparent that no single organisation could or should expect to provide a complete new tool kit in this way. rather one wants an open market in software tools, in the same way that it is hoped ada will lead to an open market in software components. the more recent history of ipse efforts, therefore, has been an attempt to resolve the conflict between the desire for integration and the need for environments to accept a wide range of tools from various sources. perhaps the most ambitious project taking this approach is aspect, a project within the uk alvey programme, which is currently delivering prototypes for evaluation. aspect aims to provide a highly functional open tool interface covering coherence, control and sharing. it does this by treating the open tool interface as a special case of an adaptable interface which provides user-defined views of the underlying kernel. this approach depends heavily on the notions of views developed in the relational database world.
a cooperative approach to support software deployment using the software dock. software deployment is an evolving collection of interrelated processes such as release, install, adapt, reconfigure, update, activate, deactivate, remove, and retire. the connectivity of large networks, such as the internet, is affecting how software deployment is performed. it is necessary to introduce new software deployment technologies that leverage this connectivity. the software dock framework creates a distributed, agent based deployment framework to support the ongoing cooperation and negotiation among software producers themselves and among software producers and software consumers. this deployment framework is enabled by the use of a standardized deployment schema for describing software systems, called the deployable software description (dsd) format. the software dock also employs agents to traverse between software producers and consumers in order to perform software deployment activities by interpreting the descriptions of software systems. the software dock infrastructure allows software producers to offer their customers high level deployment services that were previously not possible.
2nd international workshop on advances and applications of problem frames. software problems originate from real world problems. a software solution must address its real world problem in a satisfactory way. a software engineer must therefore understand the real world problem that their software intends to address. to be able to do this, the software engineer must understand the problem context and how it is to be affected by the proposed software, expressed as the requirements. without this knowledge the engineer can only hope to chance upon the right solution for the problem. application of the problem frames approach may well be a way of meeting this need.
an operational requirement description model for open systems. requirement engineering has been successfully applied to many superficial problems, but there has been little evidence of transfer to complex system construction. in this paper we present a new conceptual model which is for incomplete requirement descriptions. the model is especially designed for supporting the requirement specification and the analysis of open systems. an analysis of existing models and languages shows the main problem in requirement engineering: the harmony between a well-defined basic model and a convenient language. the new model remos combines the complex requirements of open systems with the basic characteristics of transaction-oriented systems. transaction-oriented systems are fault-tolerant and offer security and privacy mechanisms. such systems provide such excellent properties - why don't we already profit from it during requirement specification? the model remos and the applicative language relos take advantage of transaction properties. the idea remos is based on is the definition of scenarios and communicating subsystems. remos guides the users to making their requirements more clear, and relos offers a medium for requirement definition.
m. h. halstead's software science - a critical examination. karl popper has described the scientific method as &ldquo;the method of bold conjectures and ingenious and severe attempts to refute them&rdquo;. software science has made &ldquo;bold conjectures&rdquo; in postulating specific relationships between various 'metrics' of software code and in ascribing psychological interpretations to some of these metrics. this paper describes tests made on the validity of the relationships and interpretations which form the foundations of software science. the results indicate that the majority of them represent neither natural laws nor useful engineering approximations.
measuring reliability of computer center software. this paper investigates the application of the execution time theory of software reliability [1,2] to operational computation center software. a brief review of software reliability concepts is provided. studies of individual operating system components are discussed, as well as a functional subsystem. this work is based on data taken at a large operating computation center over a period of 15 months.
theory of software reliability based on components. we present a foundational theory of software system reliability based on components. the theory describes how component developers can design and test their components to produce measurements that are later used by system designers to calculate composite system reliability &mdash; without implementation and test of the system being designed. the theory describes how to make component measurements that are independent of operational profiles, and how to incorporate the overall system-level operational profile into the system reliability calculations. in principle, the theory resolves the central problem of assessing a component, which is: a component developer cannot know how the component will be used and so cannot certify it for an arbitrary use; but if the component buyer must certify each component before using it, component-based development loses much of its appeal. this dilemma is resolved if the component developer does the certification and provides the results in such a way that the component buyer can factor in the usage information later, without repeating the certification. our theory addresses the basic technical problems inherent in certifying components to be released for later use in an arbitrary system. most component research has been directed at functional specification of software components; our theory addresses the other, equally important, side of the coin: component quality.
a framework for data base semantic integrity. a structured framework is provided for describing the semantic integrity requirements of a data base. the semantic integrity of a data base is said to be violated when the data base ceases to represent a legitimate configuration of the application domain it is intended to model. in the context of the relational data model, it is possible to identify multiple levels of semantic integrity information. relation constraints comprise one such level; they express the semantic information not contained in the structure of the relations nor in the identity of their underlying domains. the three components of a relation constraint are considered: (1) the assertion (a predicate on the state of the data base or on transitions between data base states), (2) the validity requirement (the occasion(s) at which the assertion must hold), and (3) the violation-action (the action that is to occur if the assertion does not hold at a time when it should). a framework for relation constraints is presented. details of a structured classification scheme are outlined. this scheme is intended to form a basis for a high level, well-directed, and disciplined methodology for the design of relational data bases. emphasis is placed on the assertion component of relation constraints. assertions are viewed as more than expressions of some relationship among different values in a data base; assertions single out the data that is constrained, and state the properties that this data must possess. a classification is provided of the various predicate types used to identify constrained data and to state the properties which they are to possess. approaches to the relation constraint assertion specification process are discussed.
managing exceptions in the medical workflow systems. over the years, medical informatics researchers have studied how to use software technologies to provide decision support for using evidence-based medical procedures. software professionals have investigated how to support hospital administration, therapy and laboratory workflows. for many of these efforts, managing the exceptions in the workflows is a key issue since the medical workflows must cope with a wide variety of patient medical situations as well as those of the healthcare environments. this paper presents an analysis of past research in managing medical workflow exceptions, and proposes future research that would benefit the medical applications. the paper is focused on three topics: representing, handling and analyzing exceptions. based upon our analysis, we believe that techniques for verifying exception management models and for handling dynamic exceptions should be useful and possibly essential for developing large scale, practical medical workflow systems.
a learning curve based simulation model for software development. many of the non conventional software development methodologies (such as object-oriented analysis methodology) and tools (such as visual programming environment) have been applied in real life projects. these projects have been started without sufficient previous training given to the developers. an increment in the productivity has been seen as the projects progress. this paper proposes a simulation model for software development which can deal with variances of developers' productivity during software development. as the proposed model takes into account the developer's learning curve, it can be used to compute a developer's productivity and the quantity of gain to the developer's knowledge in executing an activity. the proposed model has been applied to four typical scenarios in our case study. the results show that it is highly practicable. an outline of a project planning prototype which is based on the proposed model is presented. the prototype can be used to make project plans which take the developer's learning curve into consideration
tracking down software bugs using automatic anomaly detection. this paper introduces diduce, a practical and effective tool that aids programmers in detecting complex program errors and identifying their root causes. by instrumenting a program and observing its behavior as it runs, diduce dynamically formulates hypotheses of invariants obeyed by the program. diduce hypothesizes the strictest invariants at the beginning, and gradually relaxes the hypothesis as violations are detected to allow for new behavior. the violations reported help users to catch software bugs as soon as they occur. they also give programmers new visibility into the behavior of the programs such as identifying rare corner cases in the program logic or even locating hidden errors that corrupt the program's results.we implemented the diduce system for java programs and applied it to four programs of significant size and complexity. diduce succeeded in identifying the root causes of programming errors in each of the programs quickly and automatically. in particular, diduce is effective in isolating a timing-dependent bug in a released jsse (java secure socket extension) library, which would have taken an experienced programmer days to find. our experience suggests that detecting and checking program invariants dynamically is a simple and effective methodology for debugging many different kinds of program errors across a wide variety of application domains.
a systems engineering view of requirements management for software-intensive systems. the importance of requirements management is widely understood and appreciated. nevertheless, the rules used to guide the process, while recognized, but rarely followed in a consistent way. requirements management often exists as a vague, undefined collection of process fragments. this presentation explores the system decomposition function of systems engineering. transition zones are defined that mark the boundaries where, during the decomposition process, the change of technical disciplines is needed. the success of the requirements management process here is defined as the systems engineer's ability to recognize and manage these transitions.
improving test suites via operational abstraction. this paper presents the operational difference technique for generating, augmenting, and minimizing test suites. the technique is analogous to structural code coverage techniques, but it operates in the semantic domain of program properties rather than the syntactic domain of program text.the operational difference technique automatically selects test cases; it assumes only the existence of a source of test cases. the technique dynamically generates operational abstractions (which describe observed behavior and are syntactically identical to formal specifications) from test suite executions. test suites can be generated by adding cases until the operational abstraction stops changing. the resulting test suites are as small, and detect as many faults, as suites with 100% branch coverage, and are better at detecting certain common faults.this paper also presents the area and stacking techniques for comparing test suite generation strategies; these techniques avoid bias due to test suite size.
executable object modeling with statecharts. a behaviorally expressive set of diagrammatic languages for modeling object-oriented systems is presented. it constitutes the constructive subset of uml, and is supported by rhapsody, a tool that enables model execution and full code synthesis.
statemate; a working environment for the development of complex reactive systems. this paper provides a brief overview of the statemate system, constructed over the past three years by i-logix inc., and ad cad ltd. statemate is a graphical working environment, intended for the specification, analysis, design and documentation of large and complex reactive systems, such as real-time embedded systems, control and communication systems, and interactive software. it enables a user to prepare, analyze and debug diagrammatic, yet precise, descriptions of the system under development from three inter-related points of view, capturing, structure, functionality and behavior. these views are represented by three graphical languages, the most intricate of which is the language of statecharts used to depict reactive behavior over time. in addition to the use of state-charts, the main novelty of statemate is in the fact that it `understands` the entire descriptions perfectly, to the point of being able to analyze them for crucial dynamic properties, to carry out rigorous animated executions and simulations of the described system, and to create running code automatically. these features are invaluable when it comes to the quality and reliability of the final outcome.
seminal: software engineering using metaheuristic innovative algorithms. metaheuristic search algorithms have been widely applied to almost all engineering disciplines with the exception of software engineering. it is surprising that these essentially software driven technologies have not yet fully penetrated the software engineering research community and are not widely applied when compared to the more traditional engineering disciplines. this workshop aims to build the embryonic research community interested in the application of metaheuristic algorithms to software engineering problems.
workshop on technology transfer in software engineering. in many industries, the adoption of technology developed at universities and independent research labs is the prevalent paradigm. however, in the software space, this is a relatively rare occurrence. in many cases, academic software engineering tends to lag rather than lead commercial developments. the goal of this workshop is to open a dialouge between researchers and practitioners to address this problem.
reuse-driven interprocedural slicing. to manage the evolution of software systems effectively, software developers must understand software systems, identify and evaluate alternative modification strategies, implement appropriate modifications, and validate the correctness of the modifications. one analysis technique that assists in many of these activities is program slicing. to facilitate the application of slicing to large software systems, we adapted a control flow-based interprocedural slicing algorithm so that it accounts for interprocedural control dependencies not recognized by other slicing algorithms, and reuses slicing information for improved efficiency. our initial studies suggest that additional slice accuracy and slicing efficiency may be achieved with our algorithm
a retrospective on the development of star. star, officially known as the xerox 8010 information system, is a workstation for professionals, providing a comprehensive set of capabilities for the office environment. the star software consists of just over 250,000 lines of code. its development required 93 work years over a 3.5 year period. the development of star depended heavily on the use of powerful personal computers connected to a local-area network and on the use of the mesa language and development environment. an integration service was introduced to speed up the building of star and to relieve the programmers of many complex, but repetitive, tasks.
a scalable, automated process for year 2000 system correction. as the 21st century approaches, many computer programs will begin to fail. applications that rely on dates of any kind may simply stop working or produce incorrect results. the year 2000 problem is a matter of business importance, not just software maintenance. program failures arise from representing calendar dates (year, month, and day) in just 6 digits, a format that allows only 2 digits for the year. the year 2000 problem is pervasive. it occurs in calculations, comparisons and other logic involving date-related processing including date-oriented sorting and date-indexed tables. the problem occurs in databases and files as well as in code. the paper discusses the design of an automated software tool for code and data y2000 correction and shows how to use the tool in a large scale system correction process. the solution is discussed in the context of large, cobol-based commercial systems. nonetheless, our approach is fully generalizable to other languages and classes of applications.
understanding natural programs using proper decomposition. the author presents a practical method for automatic control concept recognition in large, unstructured imperative programs. control concepts are abstract notions about interactions between control flow, data flow, and computation, e.g., read-process loops. they are recognized by comparing a language-independent abstract program representation against standard implementation plans. recognition is efficient and scalable because the program representation is hierarchically decomposed by propers (single entry/exit control flow subgraphs). a recognition experiment using the unprog program understander shows the method's performance, the role of proper decomposition, and the ability to use standard implementations in a sample of programs. how recognized control concepts are used to perform cobol restructuring with quality not possible with existing syntactic methods is described
architecture recovery of web applications. web applications are the legacy software of the future. developed under tight schedules, with high employee turn over, and in a rapidly evolving environment, these systems are often poorly structured and poorly documented. maintaining such systems is problematic.this paper presents an approach to recover the architecture of such systems, in order to make maintenance more manageable. our lightweight approach is flexible and retargetable to the various technologies that are used in developing web applications. the approach extracts the structure of dynamic web applications and shows the interaction between their various components such as databases, distributed objects, and web pages. the recovery process uses a set of specialized extractors to analyze the source code and binaries of web applications. the extracted data is manipulated to reduce the complexity of the architectural diagrams. developers can use the extracted architecture to gain a better understanding of web applications and to assist in their maintenance.
msr 2005 international workshop on mining software repositories. no abstract available
msr 2004: international workshop on mining software repositories. the goal of this one-day workshop is to bring together researchersand practitioners to consider methods that use datastored in software repositories (such as source control systems,defect tracking systems, and archived project communications)to further understanding of software developmentpractices.
the dublo architecture pattern for smooth migration of business information systems: an experience report. while the importance of multi-tier architectures for enterpriseinformation systems is widely accepted and theirbenefits are well published, the systematic migration frommonolithic legacy systems toward multi-tier architectures isknown to a much lesser extent. in this paper we present apattern on how to re-use elements of legacy systems withinmulti-tier architectures, which also allows for a smooth migrationpath. we report on experience we made with migratingexisting municipal information systems towards a multitierarchitecture. the experience is generalized by describingthe underlying pattern such that it can be re-used forsimilar architectural migration tasks. the emerged dublopattern is based on the partial duplication of businesslogic among legacy system and newly deployed applicationserver. while this somehow contradicts the separation-of-concernsprinciple, it offers a high degree of flexibility inthe migration process and allows for a smooth transition.experience with the combination of outdated databasetechnology with modern server-side component and webservices technologies is discussed. in this context, we alsoreport on technology and architecture selection processes.
cadena: an integrated development, analysis, and verification environment for component-based systems. the use of component models such as enterprise java beans and the corba component model (ccm) in application development is expanding rapidly. even in real-time safety/mission-critical domains, component-based development is beginning to take hold as a mechanism for incorporating non-functional aspects such as real-time, quality-of-service, and distribution. to form an effective basis for development of such systems, we believe that support for reasoning about correctness properties of component-based designs is essential.in this paper, we present cadena -- an integrated environment for building and modeling ccm systems. cadena provides facilities for defining component types using ccm idl, specifying dependency information and transition system semantics for these types, assembling systems from ccm components, visualizing various dependence relationships between components, specifying and verifying correctness properties of models of ccm systems derived from ccm idl, component assembly information, and cadena specifications, and producing corba stubs and skeletons implemented in java. we are applying cadena to avionics applications built using boeing 's bold stroke framework.
conspectus of software engineering environments. aspects of software engineering environments are discussed, namely motivations, life cycle models, concepts, methods, description means and tools. some general conclusions about these aspects as well as about the area of software engineering environments are drawn. the paper is based on a study of selected software engineering environments.
detection of conflicting functional requirements in a use case-driven approach: a static analysis technique based on graph transformation. in object-oriented software development, requirements of different stakeholders are often manifested in use case models which complement the static domain model by dynamic and functional requirements. in the course of development, these requirements are analyzed and integrated to produce a consistent overall requirements specification. iterations of the model may be triggered by conflicts between requirements of different parties.however, due to the diversity, incompleteness, and informal nature, in particular of functional and dynamic requirements, such conflicts are difficult to find. formal approaches to requirements engineering, often based on logic, attack these problems, but require highly specialized experts to write and reason about such specifications.in this paper, we propose a formal interpretation of use case models consisting of uml use case, activity, and collaboration diagrams. the formalization, which is based on concepts from the theory of graph transformation, allows to make precise the notions of conflict and dependency between functional requirements expressed by different use cases. then, use case models can be statically analyzed, and conflicts or dependencies detected by the analysis can be communicated to the modeler by annotating the model.an implementation of the static analysis within a graph transformation tool is presented.
software engineering education in the era of outsourcing, distributed development, and open source software: challenges and opportunities. as software development becomes increasingly globally distributed, and more software functions are delegated to common open source software (oss) and commercial off-the-shelf (cots) components, practicing software engineers face significant challenges for which current software engineering curricula may leave them inadequately prepared. a new multi-faceted distributed development model is emerging that effectively commoditizes many development activities once considered integral to software engineering, while simultaneously requiring practitioners to apply engineering principles in new and often unfamiliar contexts. we discuss the challenges that software engineers face as a direct result of outsourcing and other distributed development approaches that are increasingly being utilized by industry, and some of the key ways we need to evolve software engineering curricula to address these challenges.
component design of retargetable program analysis tools that reuse intermediate representations. interactive program analysis tools are often tailored to one particular representation of programs, making adaptation to a new language costly. one way to ease adaptability is to introduce an intermediate abstraction&mdash;an adaptation layer&mdash;between an existing language representation and the program analysis tool. this adaptation layer translates the tool's queries into queries on the particular representation.our experiments with this approach on the startool program analysis tool resulted in low-cost retargets for c, tcl/tk, and ada. required adjustments to the approach, however, led to insights for improving a client's retargetability. first, retargeting was eased by having our tool import a tool-centric (i.e., client-centric) interface rather than a general-purpose, language-neutral representation interface. second, our adaptation layer exports two interfaces, a representation interface supporting queries on the represented program and a language interface that the client queries to configure itself suitably for the given language. straightforward object-oriented extensions enhance reuse and ease the development of multi-language tools.
evaluating individual contribution toward group software engineering projects. it is widely acknowledged that group or team projects are a staple of undergraduate and graduate software engineering courses. such projects provide students with experiences that better prepare them for their careers, so teamwork is often required or strongly encouraged by accreditation agencies. while there are a multitude of educational benefits of group projects, they also pose considerable challenge in fairly and accurately discerning individual contribution for evaluation purposes. issues, approaches, and best practices for evaluating individual contribution are presented from the perspectives of the university of kentucky, university of ottawa, university of southern california, and others.the techniques utilized within a particular course generally are a mix of (1) the group mark is everybody's mark, (2) everybody reports what they personally did, (3) other group members report the relative contributions of other group members, (4) pop quizzes on project details, and (5) cross-validating with the results of individual work.
building enterprise portals: principles to practice. primary objective of this paper is to offer an exclusive view of constructing and deploying enterprise portals by using a component-based development approach. as the dot-com hype dies down, most companies are forced to revisit their enterprise-wide web integration strategies. this paper offers a pragmatic roadmap that these companies may follow in their upcoming enterprise portal deployment initiatives.the academic world plays a significant role in the advances of the portal technology. in this paper, we address the challenges faced in building enterprise portals as a new principle of software engineering. we also explain how the academia will play a significant role in meeting most of these challenges.
teaching framework for software development methods. in this paper we suggest a framework for teaching software development methods (sdms). specifically, based on our accumulative research and in-practice experience of teaching sdms, a set of principles, that guides our teaching of sdms in different settings and teaching experiences, has been formulated. the teaching framework consists of 14 principles that their actual implementation is varied and adjusted in different teaching environments. this paper outlines the principles and addresses their contribution to learners' understanding of the said software development method.
teaching human aspects of software engineering. this paper highlights the teaching of human aspects of software engineering, by presenting a course that deals with this topic. specifically, this paper outlines the course's objective and structure, and, as the cfp asks, suggests two challenges an instructor of software engineering faces today.
introducing software engineering by means of extreme programming. this paper reports on experience from teaching basic software engineering concepts by using extreme programming in a second year undergraduate course taken by 107 students. we describe how this course fits into a wider programme on software engineering and technology and report our experience from running and improving the course. particularly important aspects of our setup includes team coaching (by older students) and "team-in-one-room". our experience so far is very positive and we see that students get a good basic understanding of the important concepts in software engineering, rooted in their own practical experience.
the causes and effects of infeasible paths in computer programs. an analysis is presented of infeasible paths found in the nag library of numerical algorithms. the construction of program paths designed to maximise structural testing measures is shown to be impossible without taking infeasibilities into account. methods for writing programs which do not contain infeasible paths are also discussed.
a new approach to consistency control in software engineering. quality assurance methods as suggested by standards like iso 9000 focus on the principle of review and feedback loops, which may be implemented by computer-based software process management including life cycle models, version control, and change tracking. provided that the software process is modelled independently of concrete design methods, development tools, and software representations, a general representation of quality assurance methods can be obtained. in our paper we introduce such a high-level formalism, heavily exploiting some remarkable analogy between the software development process and distributed computations. our approach is based on labelling each software element and product version during development. by using these labels one can coordinate versions, variant designs, and reconstruct elements of old versions automatically. though our model is independent of particular design methods or programming formalisms, it can be parameterized with tools and compilers in order to be tailored to specific projects. some applications are demonstrated for important problems of software project management that cannot be solved or even detected with nowadays standard methods, but that can easily be dealt with by using our new model.
dynamite: dynamic task nets for software process management. managing the software development and maintenance process has been identified as a great challenge for several years. software processes are highly dynamic and can only rarely be planned completely in advance. dynamic task nets take this into account. they are built and modified incrementally as a software process is executed. dynamic task nets have been designed to solve important problems of process dynamics, deciding product-dependent structure evolution, feedback, and concurrent engineering. in order to describe editing and enactment (and their interaction) in a uniform way, task nets are formally defined by means of a programmed graph rewriting system.
static detection of leaks in polymorphic containers. this paper presents the first practical static analysis tool that can find memory leaks and double deletions of objects held in polymorphic containers. this is especially important since most dynamically allocated objects are stored in containers.the tool is based on the concept of object ownership: every object has one and only one owning pointer. the owning pointer holds the exclusive right and obligation to either delete the object or to transfer the obligation. this paper presents a new type system that allows different instances of a polymorphic container to hold different types of elements, and to independently own or not own their elements.our tool is sound: it will report all potential memory leaks and multiple deletions of pointers in a program. our system automatically identifies the container implementation routines in an application. the user provides a short specification on the container structure and ownership constraints for these routines. the system then solves for the ownership constraints flow- and context-sensitively, and reports inconsistencies in ownership constraints as potential memory leaks and double deletions.we applied our tool to a suite of five large open-source and commercial c and c++ applications totaling one million lines of code. the tool successfully identified memory leaks in these programs and found double deletions of objects that could lead to program failures or security vulnerabilities.
introduction to the experience reports track. it is our great pleasure to welcome you to the experience reports track of the 27th international conference on software engineering (icse). the objective of the experience reports track is to establish a dialogue between software practitioners and software engineering researchers on the benefits, obstacles, and weaknesses of applying software engineering principles, techniques, methods, processes, and tools in an industrial or organizational setting. in the call for papers, we invited four types of submissions: case studies, experience reports, experimental reports and problem statements. the call attracted 72 submissions from all over the world. the program committee of the experience reports track accepted 14 submissions. the selection was based on at least three reviews per submission and the results of intensive consensus discussions prior to and during the experience reports track program committee meeting, held on november 12, 2004 in essen, germany.the accepted papers of the icse 2005 experience reports track cover topics such as agile methods, product lines, requirements engineering, software architecture, testing and verification. they document important lessons learned from applying software engineering principles, techniques, methods, processes, and tools in practice. putting together the experience reports track of icse 2005 was a team effort. we extend our sincerest gratitude to all of the people who helped us shape this event, especially to the members of our program committee and the icse 2005 organizing committee and to richard van de stadt, andreas metzger, and nelufar ulfat-bunyadi. we hope that you find the experience reports track of icse 2005 interesting and thought-provoking.
continous execution: the visiprog environment. to date, program development environments have been static rather than dynamic. even emerging interactive, integrated program development environments, like the cornell program synthesizer, view program editing and execution as essentially independent activities. we envision an even more dynamic environment in which the functionality (input/output relationship) of a network of programs, an individual program, or a program segment can be viewed &ldquo;continuously&rdquo; with editing changes to either the program input or program body. this is the visicalc concept extended to program development environments (visiprog). in this paper, this &ldquo;dynamic&rdquo; approach to program development, testing and debugging is addressed, and considerations for the user interface are discussed. the latter includes a workstation with a flexible windowing system, three-dimensional views of programs, insertion of program control and observation points, and dynamic program slicing for &ldquo;viewing&rdquo; program execution. an existing prototype and current development activities are also discussed.
a tool for writing and debugging algebraic specifications. despite their benefits, programmers rarely use formalspecifications, because they are difficult to write and theyrequire an up front investment in time. to address these issues,we present a tool that helps programmers write anddebug algebraic specifications. given an algebraic specification, our tool instantiates a prototype that can be used just like any regular java class. the tool can also modifyan existing application to use the prototype generatedby the interpreter instead of a hand-coded implementation.the tool improves the usability of algebraic specificationsin the following ways: (i) a programmer can "run" an algebraicspecification to study its behavior. the tool reportsin which way a specification is incomplete for a client application.(ii) the tool can check whether a specification anda hand-coded implementation behave the same for a particularrun of a client application. (iii) a prototype can beused when a hand-coded implementation is not yet available.two case studies demonstrate how to use the tool.
catchup!: capturing and replaying refactorings to support api evolution. library developers who have to evolve a library to accommodate changing requirements often face a dilemma: either they implement a clean, efficient solution but risk breaking client code, or they maintain compatibility with client code, but pay with increased design complexity and thus higher maintenance costs over time.we address this dilemma by presenting a lightweight approach for evolving application programming interfaces (apis), which does not depend on version control or configuration management systems. instead, we capture api refactoring actions as a developer evolves an api. users of the api can then replay the refactorings to bring their client software components up to date.we present catchup!, an implementation of our approach that captures and replays refactoring actions within an integrated development environment semi-automatically. our experiments suggest that our approach could be valuable in practice.
assessing a class of software tools. the roles and capabilities of ldra software testbeds and their appropriate environments have been described in a number of papers [1,2]. the way in which management uses the tools as elements of a controlled software development environment is described in [3]. the principal benefits of such use are that management has the assurance that software development standards are enforced, and has reliable information concerning project status. the explicit standards enforced by the use of these tools are described in detail in [2]. one class of these standards is that of test effectiveness, which is measured primarily through three test effectiveness metrics reinforced by a code auditing capability. this paper attempts to quantify the benefits of using such a software testbed in providing assurance of the absence of program errors. the attempt is made from two viewpoints, the theoretical and the experimental. the theoretical aspect is important because the practical use of a tool may fail to demonstrate that the tool can be a powerful detector of a class of errors simply because no errors of that type were present in the software sample validated. finally the paper attempts to summarise some of the experiences gained through the use of the tools over a twelve year period.
supporting the construction and evolution of component repositories. repositories must be designed to meet the evolving and dynamic needs of software development organizations. current software repository methods rely heavily on classification, which exacerbates acquisition and evolution problems by requiring costly classification and domain analysis efforts before a repository can be used effectively. this paper outlines an approach in which minimal initial structure is used to effectively find relevant software components while methods are employed to incrementally improve repository structures. the approach is demonstrated through peel, a tool to semi-automatically identify reusable components, and codefinder, a retrieval system that compensates for the lack of explicit knowledge structures through spreading activation retrieval and allows component representations to be incrementally improved while users are searching for information. the combination of these techniques yields a flexible software repository that minimizes up-front costs and improves its retrieval effectiveness as developers use it to find reusable software artifacts.
beyond computer science. computer science is necessary but not sufficient to understand and overcome the problems we face in software engineering. we need to understand not only the properties of the software itself, but also the limitations and competences humans bring to the engineering task. rather than rely on commonsense notions, we need a deep and nuanced view of human capabilities in order to determine how to enhance them. i discuss what i regard as promising examples of cognitive and organizational theories and propose research directions to develop new ways of representing run-time behavior and ways of thinking about project coordination. i conclude with observations on creating an interdisciplinary culture.
a systematic survey of cmm experience and results. the capability maturity model (cmm) for software has become very influential as a basis for software process improvement (spi). most of the evidence to date showing the results of these efforts has consisted of case studies. we present a systematic survey of organizations that have undertaken cmm-based spi to get more representative results. we found evidence that process maturity is in fact associated with better organizational performance, and that software process appraisals are viewed, in retrospect, as extremely valuable and accurate guides for the improvement effort. the path was not always smooth, however, and efforts generally took longer and cost more than expected. a number of factors that distinguished highly successful from unsuccessful efforts are identified. most of these factors are under management control, suggesting that a number of specific management decisions are likely to have a major impact on the success of the effort.
conceptual simplicity meets organizational complexity: case study of a corporate metrics program. a corporate-wide metrics program faces enormous and poorly understood challenges as its implementation spreads out from the centralized planning body across many organizational boundaries into the sites where the data collection actually occurs. this paper presents a case study of the implementation of one corporate-wide program, focusing particularly on the unexpected difficulties of collecting a small number of straightforward metrics. several mechanisms causing these difficulties are identified, including attenuated communication across organizational boundaries, inertia created by existing data collection systems, and the perceptions, expectations, and fears about how the data will be used. we describe how these factors influence the interpretation of the definitions of the measurements and influence the degree of conformance that is actually achieved. we conclude with lessons learned about both content and mechanisms to help in navigating the tricky waters of organizational dynamics in implementing a company-wide program
splitting the organization and integrating the code: conway's law revisited. it is widely acknowledged that coordination of large scale software development is an extremely difficult and persistent problem. since the structure of the code mirrors the structure of the organization, one might expect that splitting the organization across time zones, cultures, and (natural) languages would make it difficult to assemble the components. this paper presents a case study of what indeed turned out to be the most difficult part of a geographically distributed software project, i.e., integration. coordination problems were greatly exaggerated across sites, largely because of the breakdown of informal communication channels. the results imply that multi-site development can benefit to some extent from stable plans, processes, and specifications. the inherently unpredictable aspects of projects, however, require communication channels that can be invoked spontaneously, by developers, as needed. these results shed light on the problems and mechanisms underlying the coordination needs of development projects generally, be they co-located or distributed.
an empirical study of global software development: distance and speed. global software development is rapidly becoming the norm for technology companies. previous qualitative research suggests that multi-site development may increase development cycle time. we use both survey data and data from the source code change management system to model the extent of delay in a multi-site software development organization, and explore several possible mechanisms for this delay. we also measure differences in same-site and cross-site communication patterns, and analyze the relationship of these variables to delay. our results show that compared to same-site work, cross-site work takes much longer, and requires more people for work of equal size and complexity. we also report a strong relationship between delay in cross-site work and the degree to which remote colleagues are perceived to help out when workloads are heavy. we discuss implications of our findings for collaboration technology for distributed software development.
global software development at siemens: experience from nine projects. we report on the experiences of siemens corporation in nine globally-distributed software development projects. these projects represent a range of collaboration models, from co-development to outsourcing of components to outsourcing the software for an entire project. we report experience and lessons in issues of project management, division of labor, ongoing coordination of technical work, and communication. we include lessons learned, and conclude the paper with suggestions about important open research issues in this area.
analysis of error remediation expenditures during validation. approximately 200 errors were detected during the formal in-house validation of a real time communications system that provides for ship-to-shore communications via both conventional and satellite links. a cost equation was developed to assess the utilization of expenditures associated with validation. the components of this equation reflected the costs that are typically expended during validation, such as reporting, analysis, remediation, retesting, and general managerial over-head. the results of a parametric analysis of the cost equation with respect to error cause and system impact indicated a significant under utilization of resources expended for validation.
a perspective on software development. this paper retraces an evolution of thought on the key problems in producing software. the author's perspective is traced through an early emphasis on development tools and methodology to an emphasis on specifications and requirements to a broader emphasis on overall manageability. the evolving thought process is projected ahead and illustrated by some current efforts and activities. the paper concludes with a discussion of the approaches to further enhancing the development process and the author's view on which areas should be given the main attention.
towards systematic recycling of systems requirements. many (technical) systems are not developed from scratch but as an evolution of existing systems. consequently, a large portion of the system requirements employed can be recycled when building the next version of the product. usually, this recycling step is performed unsystematically, i.e. simply by copying and modifying complete requirements documents.in this paper, we present in a case study a lightweight requirements recycling approach which evolved from observations and concrete needs of projects at daimler-chrysler passenger car development. the basic idea of the approach is separation of model-dependent from model-independent requirements on the same level of abstraction. this notion is supported by document structures, criteria for identifying reusable requirements and tool support.the paper presents the core elements of the approach and provides observations and valuable experiences we made in the projects.
cost estimation of software intensive projects: a survey of current practices. the authors describe a survey conducted at the jet propulsion laboratory (jpl) to estimate software costs for software intensive projects in jpl's technical divisions. respondents to the survey described what techniques they use in estimating software costs and, in an experiment, each respondent estimated the size and cost of a specific piece of software described in a design document provided by the authors. it was found that the majority of the technical staff estimating software costs use informal analogy and high-level partitioning of requirements, and that no formal procedure exists for incorporating risk and uncertainty. the technical staff is significantly better at estimating effort than size. however, in both cases the variances are so large that there is a 30% probability that any one estimate can be more than 50% off
an approach to large-scale collection of application usage data over the internet. empirical evaluation of software systems in actual usage situations is critical in software engineering. prototyping, beta testing, and usability testing are widely used to refine system requirements, detect anomalous or unexpected system and user behavior, and to evaluate software usefulness and usability. the world wide web enables cheap, rapid, and large-scale distribution of software for evaluation purposes. however, current techniques for collecting usage data have not kept pace with the opportunities presented by web-based deployment. this paper presents an approach and prototype system that makes large-scale collection of usage data over the internet a practical possibility. a general framework for comparing software monitoring systems is presented and used to compare the proposed approach to existing techniques
an open framework for dynamic reconfiguration. dynamic reconfiguration techniques appear promisingfor building systems that have requirements for adaptabilityand/or high availability. current systems that supportdynamic reconfiguration tend to use a single, fixed, reconfiguration algorithm to manage the change process. furthermore, existing change management systems lack supportfor measuring the impact of reconfiguration on a runningsystem. in this paper, we introduce openrec, an openframework for managing dynamic reconfiguration which addressesthese drawbacks. using openrec, developers canobserve the costs, in terms of time and disturbance, associatedwith making a particular run-time change. in addition,openrec employs an extensible set of reconfiguration algorithmswhere one algorithm can be substituted for another.developers can thus make an informed decision as to whichalgorithm to use based on comparative analysis. finally,openrec is itself dynamically reconfigurable.
moving from a plan driven culture to agile development. plan driven cultures are characterized by a strong belief in the plannability and predictability of software development projects. the sei-cmm, software process improvement initiatives, and software metrics programs are some of the hallmarks of this school of thought. the more recent trend towards agile development places the emphasis on constantly adapting to a project's changing goals rather than on detailed upfront planning. the majority of reports from pracitioners of agile development are positive and confirm the advantages of this approach. however, moving from a plan driven culture to agile development is not easy. making the transition requires changes to many established practices and may even touch core values held by stakeholders. areas affected are requirements and change management, user involvement, willingness to take on responsibility, contract management, and the ability to live with many uncertainties. this talk looks at what it takes to make the transition and presents lessons learned from organizations and projects which have successfully completed the switch to agile development.
building systems from commercial components. the question of which design methods are appropriate for component-based development (cbd) is complicated by different understandings of the end objectives of cbd. a further complication is different understandings of what is meant by "component." these differences lead to entirely distinct classes of design problem. the aim of this tutorial is to, first, outline the different classes of design problem that span these differing interpretations of cbd, and, second, to outline the required methodological responses to these design problems.
software engineering: a keynote address. this paper argues that our recent progress in the development of a sound programming methodology should not lead us to ignore the more difficult aspects of engineering; and that in future we should pay more attention to the quality of our designs, and not just the accuracy of their implementation.
using ocl-queries for debugging c++. this demonstration will present a design and preliminary implementation of the ocl query-based debugger, oqbd, which is a tool to debug c++ programs using queries formulated in the object constraint language, ocl. we will illustrate how queries can be formulated to verify constraints such as class invariants and pre and post-conditions for member functions. the queries can be reused after code generation to verify the design contract, as part of the testing process, and to facilitate fault detection.
a system for automatic software evaluation. the production of consistently executable and dependable software demands a thoughtful systematic implementation&mdash;with clear documentation at each production stage. recognizing this, the data systems laboratory, at marshall space flight center, nasa, began a research effort to help discover and institute sound engineering principles into a methodology for the production of software. the design of this methodology is based upon five principal stages of software development: 1. feasibility: can software be written to solve the initial problem? 2. requirements/design: are software requirements and design clear, complete, traceable, and testable? 3. coding: is use being made of reliable high level coding practices? 4. testing: is testing sufficiently thorough to instill initial user confidence? 5. maintenance: has the software and its design been explicitly documented?
scm-10: tenth international workshop on software configuration management. new practices, new challenges, and new boundaries. with its tenth anniversary, the scm workshop series is &ldquo;leaving behind&rdquo; a long and successful past: although the tools, techniques, and processes developed over the last twenty years have proven to be extremely valuable, they are inadequate to address the rapidly changing practices that define the world of tomorrow. exemplified by component-based software development, open source, virtual enterprises, a ubiquitous use of xml, and the increasing dynamic nature of software, these new practices bring new challenges that necessitate dramatic changes to the field of cm.
configurable software architecture in support of configuration management and software deployment. in this research article we introduce the menage project. menage is based on the vision that the notion of software architecture, extended with the concept of versioning, can be used as an organizing abstraction for some of the activities in the software life cycle. in particular, we are investigating how two of those activities, namely configuration management and software deployment, can benefit from the availability of an explicit architectural representation that is enhanced with versioning capabilities.
a generic, peer-to-peer repository for distributed configuration management. distributed configuration management is intended to support the activities of projects that span multiple sites. nucm (network-unified configuration management) is a testbed that we are developing to help us explore the issues of distributed configuration management. nucm separates configuration management repositories (i.e. the stores for versions of artifacts) from configuration management policies (i.e. the procedures by which the versions are manipulated) by providing a generic model of a distributed repository and an associated programmatic interface. this paper describes the model and the interface, presents an initial repository distribution mechanism, and sketches how nucm can be used to implement two rather different configuration management policies, namely check-in/check-out and change sets.
a b.s. degree in informatics: contextualizing software engineering education. software engineering (se) is very different in focus from traditional computer science: it is not just about computers and software, but as much about the context in which they are used. this means we must teach about software and information, development and design, technical and social issues, while creating solutions as well as understanding and analyzing them. in effect, we must teach a discipline broader than se or cs alone for se education to be effective. at uc irvine, we designed and now offer a program doing just this -- a four-year b.s. degree in informatics. the major brings topics in se together with human-computer interaction, computer-supported collaborative work, social analysis, and management, along with other application disciplines. here, we discuss the philosophy behind the major, its structure, and the questions concerning se education that the new major raises.
david l. parnas symposium. david l. parnas is one of the grandmasters of software engineering. his academic research and industrial collaborations have exerted far-reaching influence on software design and development. his groundbreaking writings capture the essence of the innovations, controversies, challenges, and solutions of the software industry. together, they constitute the foundation for modern software theory and practice. this symposium is being held in recognition of parnas's work and in honour of his 60th birthday. it is an opportunity for everyone in the software engineering community to celebrate his contributions, and to think hard about where we are today and where we are going.
dynamic layout of distributed applications in fargo. the design of efficient and reliable distributed applications that operate in large networks, over links with varying capacities and loads, demands new programming abstractions and mechanisms. the conventional static design-time determination of local-remote relationships between components implies that (dynamic) environmental changes are hard if not impossible to address without reengineering. the paper presents a novel programming model that is centered around the concept of "dynamic application layout", which permits the manipulation of component location at runtime. this leads to a clean separation between the programming of the application's logic and the programming of the layout, which can also be performed externally at runtime. the main abstraction vehicle for layout programming is a reflective inter-component reference, which embodies co- and re-location semantics. we describe an extensible set of reference types that drive and constrain the mapping of components to hosts, and show how this model elevates application performance and reliability yet requires minimal changes in programming the application's logic. the model was realized in the fargo system, whose design and implementation in java are presented, along with an event based scripting language and corresponding event monitoring service for managing the layout of fargo applications.
unanticipated reuse of large-scale software features. software reuse has been endorsed as a way to reduce development times and costs while increasing software quality and reliability. techniques designed to encourage software reuse have concentrated on creating reusable software in the form of frameworks, reuse repositories, and component libraries. these approaches do not help a developer who wants to leverage, from an existing system, a complex feature that was not designed to be reusable. we propose an approach that allows developers to investigate the reuse potential of a feature within an existing system, to create a plan for reusing the feature, and to support the transformation of the feature to the developer's project. we believe that by providing explicit support for the reuse of large-scale source code features, the reuse process---and its benefits---can be made accessible to developers.
using structural context to recommend source code examples. when coding to a framework, developers often become stuck, unsure of which class to subclass, which objects to instantiate and which methods to call. example code that demonstrates the use of the framework can help developers make progress on their task. in this paper, we describe an approach for locating relevant code in an example repository that is based on heuristically matching the structure of the code under development to the example code. our tool improves on existing approaches in two ways. first, the structural context needed to query the repository is extracted automatically from the code, freeing the developer from learning a query language or from writing their code in a particular style. second, the repository can be generated easily from existing applications. we demonstrate the utility of this approach by reporting on a case study involving two subjects completing four programming tasks within the eclipse integrated development environment framework.
a practical method for verifying event-driven software. formal verification methods are used only sparingly in software development. the most successful methods to date are based on the use of model checking tools. to use such tools, the user must first define a faithful abstraction of the application (the model), specify how the application interacts with its environment, and then formulate the properties that it should satisfy. each step in this process can become an obstacle. to complete the verification process successfully often requires specialized knowledge of verification techniques and a considerable investment of time. in this paper we describe a verification method that requires little or no specialized knowledge in model construction. it allows us to extract models mechanically from the source of software applications, securing accuracy. interface definitions and property specifications have meaningful defaults that can be adjusted when the checking process becomes more refined. all checks can be executed mechanically, even when the application itself continues to evolve. compared to conventional software testing, the thoroughness of a check of this type is unprecedented.
data flow testing as model checking. this paper presents a model checking-based approach to data flow testing. we characterize data flow oriented coverage criteria in temporal logic such that the problem of test generation is reduced to the problem of finding witnesses for a set of temporal logic formulas. the capability of model checkers to construct witnesses and counterexamples allows test generation to be fully automatic. we discuss complexity issues in minimal cost test generation and describe heurstic test generation algorithms. we illustrate our approach using ctl as temporal logic and smv as model checker.
distributed software prototyping with ads. the difficulties ordinarily experienced in designing and developing large software systems are greatly increased in the case of distributed data processing (ddp) systems. thus there is an urgent need to support the software life cycle activities with effective prototyping tools and techniques. the architecture development system (ads) is being developed for use in prototyping ddp systems within a distributed testbed. ads features an interactive graphical user interface, a distributed runtime environment, and a prototyping framework based on the concept of abstract ddp objects with attributes and relationships. this paper presents the ads prototyping features and the user interface to describe, synthesize, execute and analyze system representations. then a discussion is presented of the applicability of ads support to the distributed software life cycle. the current implementation status of ads is also summarized.
pitfalls and safeguards in real-time digital systems with emphasis on programming. real-time digital systems are largely a technical innovation of the past decade, but they appear destined to become more wide spread in the future. they monitor or control a real physical environment, such as an air-traffic situation, as distinguished from simulating that environment on an arbitrary time scale. the complexity and rapid variation of such an environment necessitates use of a fast and versatile central-control device, a role well suited to digital computers. the usual system will include some combination of sensors, communication, control, display, and effectors. although many parts of such a system pose no novel management problems, their distinguishing feature, the central digital device, frequently presents unusually strict requirements for speed, capacity, reliability and compatibility, together with the need for a carefully designed stored program. these features, particularly the last, have implications that are not always foreseen by management. an attempt is made to point out specific hazards common to most real-time digital systems and to show a few ways of minimizing the risks associated with them.
experimental context classification: incentives and experience of subjects. there is a need to identify factors that affect the result of empirical studies in software engineering research. it is still the case that seemingly identical replications of controlled experiments result in different conclusions due to the fact that all factors describing the experiment context are not clearly defined and hence controlled. in this article, a scheme for describing the participants of controlled experiments is proposed and evaluated. it consists of two main factors, the incentives for participants in the experiment and the experience of the participants. the scheme has been evaluated by classifying a set of previously conducted experiments from literature. it can be concluded that the scheme was easy to use and understand. it is also found that experiments that are classified in the same way to a large extent point at the same results, which indicates that the scheme addresses relevant factors.
establishing experience factories at daimler-benz an experience report. the experience factory concept enables systematic learning and continuous improvement in software development. as with most learning initiatives, it is hard to establish. in our experience, there is a great deal of uncertainty and skepticism about the mission and contents of an experience factory. the starting phase is especially endangered through pitfalls or unexpected delays. as expectations vary and there is pressure to demonstrate success within only a few months, tension arises which may jeopardize the entire enterprise. in the course of a large-scale software improvement program, we have established three experience factories in different environments of the daimler-benz ag within two years. at each site, several application projects are involved. we describe how we approached the task, what actions we took, and the lessons we learned
signaling in monitors. monitors are a convenient and powerful tool for writing schedulers in concurrent programs. there are at least four conventions for handling their wait and signal operations: the signaling process may yield to the waiting one, continue and thus leave the signal pending, or return immediately from the monitor; or signals may be performed automatically. formal proof schemas are presented for each of the signaling conventions. such schemas not only support proof of monitors, they also display the conventions' properties precisely and allow them to be compared. it is shown that all of the conventions are equivalent except for immediate return, which is strictly weaker than the others. a modification of immediate return which corrects its weakness and retains its desirable features is proposed.
theoretical and empirical studies of program testing. two approaches to the study of program testing are described. one approach is theoretical and the other empirical. in the theoretical approach situations are characterized in which it is possible to use testing to formally prove the correctness of programs or the correctness of properties of programs. in the empirical approach statistics are collected which record the frequency with which different testing strategies reveal the errors in a collection of programs. a summary of the results of two research projects which investigated these approaches are presented. the differences between the two approaches are discussed and their relative advantages and disadvantages are compared.
completeness criteria for testing elementary program functions. program testing metrics are based on criteria for measuring the completeness of a set of program tests. branch testing measures the percentage of program branches that are traversed during a set of tests. mutation testing measures the ability of a set of tests to distinguish a program from similar programs. a criterion for test completeness is introduced in this paper which measures the ability of a set of tests to distinguish between functions which are implemented by parts of programs. the criterion is applied to functions which are implemented by different kinds of programming language statements. it is more effective than branch testing and incorporates some of the advantages of mutation testing. its effectiveness can be discussed formally and it can be described as part of an integrated approach to testing. a tool can be used to implement the method.
a method of large-scale software development. large-scale software requires a consistent development philosophy in all phases, from design through coding to maintenance. this paper describes the closed control tree structure concept which we used to achieve this consistency while developing aim/rdb, a large relational data base system.
a software engineering experience in the management, design and implementation of a data secure system. hsdms (highly secure data management system) is a secure, on-line and multi-user experimental database management system developed on the digital equipment corporation's pdp-10 computer system. it is a vehicle for testing new facilities and applications of data management and access control. furthermore the development of hsdms itself has been aimed at the outset as an exercise in software engineering management and control. in the first part of the paper, the software engineering techniques that were used in the management and control of the programming team and efforts are discussed. the discussion centers on the application of some of the known concepts such as the chief programmer team, structured programming and composite design to programming of the database management system. in the second part of the paper, system goals and capabilities are presented. the goals for hsdms were to achieve data independence, efficient storage and access, effective user interface, and secure access control. the ability of hsdms to meet the goals result from the utilization and integration of a number of design concepts and implementation approaches. for each system goal the concepts and approaches that have provided hsdms with the capabilities to achieve the goal are shown. in the final part of the paper, we attempt to relate this single experience with hsdms to its possible impact on software engineering of database management systems in general and to data secure systems in particular.
applying the value/petri process to erp software development in china. commercial organizations increasingly need software processes sensitive to business value, quick to apply, and capable of early analysis for subprocess consistency and compatibility. this paper presents experience in applying a lightweight synthesis of a value-based software quality achievement (vbsqa) process and an object-petri-net-based process model (called vbsqa-opn) to achieve a manager-satisfactory process for software quality achievement in an on-going erp software project in china. the results confirmed that 1) the application of value-based approaches was inherently better than value-neutral approaches adopted by most erp software projects; 2) the vbsqa-opn model provided project managers with a synchronization and stabilization framework for process activities, success-critical stakeholders and their value propositions; 3) process visualization and simulation tools significantly increased management visibility and controllability for the success of software project.
easy language extension with meta-aspectj. domain-specific languages hold the potential of automating the software development process. nevertheless, the adoption of a domain-specific language is hindered by the difficulty of transitioning to different language syntax and employing a separate translator in the software build process. we present a methodology that simplifies the development and deployment of small language extensions, in the context of java. the main language design principle is that of language extension through unobtrusive annotations. the main language implementation idea is to express the language as a generator of customized aspectj aspects, using our meta-aspectj tool. the advantages of the approach are twofold. first, the tool integrates into an existing software application much as a regular api or library, instead of as a language extension. this means that the programmer can remove the language extension at any point and choose to implement the required functionality by hand without needing to rewrite the client code. second, a mature language implementation is easy to achieve with little effort since aspectj takes care of the low-level issues of interfacing with the base java language.
a database model for effective configuration management in the programming environment. the effective management of configurations by programmers requires automatic techniques which are operative in the program development environment. in this paper, an abstract model is developed to cover the significant aspects of a typical programming environment pertinent to configuration management, using a database to capture configuration knowledge. the two aspects of the model deal with configuration identification and configuration control. in considering configuration identification, it is shown that the tools in the programming environment determine which configuration items need to be identified and also determine what the interesting and useful relations are among those items. in considering configuration control, the notion of a workspace, consisting of certain modification rights and certain visibility into the database, is developed to prevent conflict and to promote cooperation among programmers. the entire model can be used to evaluate the effectiveness of configuration management within a particular programming environment or as the basis of a programming environment design.
a multiple case study on the impact of pair programming on product quality. pair programming is a programming technique in which two programmers use one computer to work together on the same task. there is an ongoing debate over the value of pair programming in software development. the current body of knowledge in this area is scattered and unorganized. review shows that most of the results have been obtained from experimental studies in university settings. few, if any, empirical studies exist, where pair programming has been systematically under scrutiny in real software development projects. thus, its proposed benefits remain currently without solid empirical evidence. this paper reports results from four software development projects where the impact of pair programming on software product quality was studied. our empirical findings appear to offer contrasting results regarding some of the claimed benefits of pair programming. they indicate that pair programming may not necessarily provide as extensive quality benefits as suggested in literature, and on the other hand, does not result in consistently superior productivity when compared to solo programming.
an index organization for applications with highly skewed access patterns. the conventional way of organizing indices in large data base systems is to use balanced tree structures such as b-trees or static tree structures, e.g. isam. it is well known in practice that most applications do not have a uniform record reference distribution but rather the 80/20-rule or zipf's law applies. the balanced index implementations mentioned do not exploit these skewed access patterns. this paper, which is an extract from the author's ph.d.-thesis, proposes a data structure - the c-tree - which is designed to exploit the skewness of such access distributions with the intent of obtaining short response times for transactions accessing the index. an analytical model of the proposed structure and a b-tree is used for making a comparative evaluation of the structures. conclusions are drawn and discussed with regard to the circumstances under which the proposed structure outperforms the b-tree.
using the web for document versioning: an implementation report for delta v. the current suite of systems that offer client/server capabilities for document versioning relies on proprietary protocols for communicating between a central versioning repository and a remote client. in order to support better document authoring via the web, the deltav working group of the web-dav (www distributed authoring and versioning) project of the internet engineering task force is working on a standard protocol for versioning over http. the authors present a prototype of deltav based on the 04.5 draft. this system demonstrates that, though important aspects of the protocol need to be revised, versioning via the web can be a practical means of supporting remote access to a central versioning repository.
applying winwin to quality requirements: a case study. this paper describes the application of the winwin paradigm to identify and resolve conflicts in a series of real-client, student-developer digital library projects. the paper is based on a case study of the statistical analysis of 15 projects and an in-depth analysis of one representative project. these analyses focus on the conflict resolution process, stakeholders' roles and their relationships to quality artifacts, and tool effectiveness. we show that stakeholders tend to accept satisfactory rather than optimal resolutions. users and customers are more proactive in stating win conditions, whereas developers are more active in working toward resolutions. further, we suggest that knowledge-based automated aids have potential to significantly enhance process effectiveness and efficiency. finally, we conclude that such processes and tools have theoretical and practical implications in the quest for better software requirements elicitation.
a dynamic pair-program sending architecture for industrial remote operations. remote operations such as maintenance, diagnoses, and command executions are more and more needed in industrial automation domains. remote operation software that flexibly responds to changes in requirements from factory, chemical plants, or remote-side operators is desired. we developed a dynamic program-sending and automatic starting architecture for this purpose. in the architecture, a pair of programs appears in one remote operation context at a time. one program called a "worker" is dynamically sent to a plant side and another called a "workergui" is dynamically sent to a remote operator side. both programs are simultaneously started and communicate each other using java/rmi. the remote-side operator's commands via the "workergui" are sent and executed in the plant side "worker" program and the execution results are sent back to the operator side "workergui". by using this architecture, a remote-side operator is able to select best match programs whenever he or she needs, and dynamically send and start them. thus, the architecture establishes flexible remote operation environments. in this paper, we explain our architecture first, and then, report the evaluation results through experiences of architecture development, three prototype application developments, and using the applications in a real remote plant operation environment.
component rank: relative significance rank for software component search. collections of already developed programs are important resources for efficient development of reliable software systems. in this paper, we propose a novel method of ranking software components, called component rank, based on analyzing actual use relations among the components and propagating the significance through the use relations. we have developed a component-rank computation system, and applied it to various java programs. the result is promising such that non-specific and generic components are ranked high. using the component rank system as a core part, we are currently developing software product archiving, analyzing, and retrieving system named spars.
introduction to education and training track. the attendees of icse comprise some of the top researchers in software engineering and also many educators of software engineering. traditionally, however, these two groups do not talk to each other about educational issues. then there are the practitioners who attend icse who have their own opinions about the relevance, strengths, and shortcomings of current software engineering education offered in universities. the goal of this year's track on software engineering education and training at icse is to bring these three communities together to discuss some urgent questions that have profound effect on how we structure our educational programs. considering the tremendous changes taking place in the software engineering industry, and in the industrial world in general, it seems appropriate to confront the needs of the software engineering educators.consider just the following increasingly common developments:outsourcing of software projectspervasiveness of software in all areas of commerce, industry, and societyincreasingly distributed platformsopen-source developmentglobalization, leading to international (multi-cultural) distributed software teamshow should these developments change the way we teach software engineering? should textbooks be updated? should software engineering play a different role in the computer science curriculum, that is, be more pervasive? how are professors in universities handling these issues?these are some of the questions we address in this track. in particular, we consider current challenges, current solutions, and future challenges. we are pleased to have six distinguished researchers to present their views and fifteen presenters from universities around the world presenting their innovative approaches in their classrooms. we expect lively and active discussion between the speakers and the audience.
formal verification applied to java concurrent software. applying existing finite-state verification tools to software systems is not yet easy for a variety of reasons. this research activity aims to integrate formal verification with programming languages currently used in software development. in particular, it focuses on elaborating a formal method for the specification and validation of temporal logic properties concerning the behavior of java concurrent programs.
domain modeling for software engineering. the authors examine domain modeling approaches from the viewpoint of their operational goals. domain models are representations of an application domain that can be used for a variety of operational goals in support of specific software engineering tasks or processes. some of the operational goals of domain modeling for software engineering are illustrated. a workshop on domain modeling was organized around operational goals and their resultant domain models and modeling methodologies. the workshop verified the importance of generalized meta-models and their use in instantiating domain knowledge into application domain models. representation, domain classification and analysis, model development, instantiation evolution and validation, and knowledge structuring and inference are discussed
a model for estimating program size and its evaluation. estimation of the size and time required for software development is probably the most difficult aspect of any project. up to now, most estimates have been done subjectively by experts. these estimates are often inaccurate. in the midst of development, faulty estimates may contribute to delays and/or excess expenses. in the last several years, several estimation have been proposed, most of which were models to estimate software development cost {manpower). these models used program size as a variable. however at the beginning of development, when estimations are made, program sizes are usually uncertain and costs (manpower) are equally uncertain. the authors developed a program-size estimation model for batch programs in a banking system, and used the model in an actual project. using the adapted model, estimation errors amounted to only 7 percent. this is much better than the accuracy of estimtions made by experts in the field (usually about 10 percent accuracy), and indicates that objective estimation methods can be derived for program-size. in this paper, we introduce our estimation model and discuss the adaptation of that model for a specific project.
a method for asynchronous parallelization. asynchronous parallelization assists the utilization of parallel hardware by sequential software: a sequential program is decomposed into a program network according a given partition. each generated program may run autonomous, dependencies are realized by communication statements. an algorithm is presented decomposing pascal programs and producing a distributed-pascal program network. at last there is a description of an existing tool using the presented method, and an example will illustrate the method.
information systems: modelling, sequencing and transformations. specification and design of an information system conventionally starts from consideration of the system function. this paper argues that consideration may more properly be given first to the system as a model of the reality with which it is concerned, the function being subsequently superimposed on the model. the form of model proposed is a network of sequential processes communicating by serial data streams. such a model permits a clear representation of change or activity over time, and it also prevents over-specification of sequencing by separating problem-oriented from solution-oriented sequencing constraints. the model, however, cannot be efficiently executed on uniprocessor hardware without transformation. some relevant kinds of transformation are mentioned, and the derivation, by means of them, of conventional information system configurations from the proposed model.
aspect: an economical bug-detector. a technique-aspect-for catching code-level bugs is presented. aspect is intended to be economical for everyday software development. it comprises a formal specification language and a code-checking method. programmers write simple assertions about the information required to compute a result; an efficient mechanical checker can then find bugs in the annotated code. careless slips that escape type-checking and standard compiler anomaly tests can be detected, without the cost of formal verification or the uncertainty of testing. the essence of aspect is reasoning about dependencies between the aspects of abstract objects
alcoa: the alloy constraint analyzer. alcoa is a tool for analyzing object models. it has a range of uses. at one end, it can act as a support tool for object model diagrams, checking for consistency of multiplicities and generating sample snapshots. at the other end, it embodies a lightweight formal method in which subtle properties of behaviour can be investigated.alcoa's input language, alloy, is a new notation based on z. its development was motivated by the need for a notation that is more closely tailored to object models (in the style of uml), and more amenable to automatic analysis. like z, alloy supports the description of systems whose state involves complex relational structure. state and behavioural properties are described declaratively, by conjoining constraints. this makes it possible to develop and analyze a model incrementally, with alcoa investigating the consequences of whatever constraints are given.alcoa works by translating constraints to boolean formulas, and then applying state-of-the-art sat solvers. it can analyze billions of states in seconds.
lightweight extraction of object models from bytecode. a program's object model captures the essence of its design. for some programs, no object model was developed during design; for others, an object model exists but may be out-of-sync with the code. this paper describes a tool that automatically extracts an object model from the classfiles of a java program. unlike existing tools, it handles container classes by inferring the types of elements stored in a container and eliding the container itself. this feature is crucial for obtaining models that show the structure of the abstract state and bear some relation to conceptual models. although the tool performs only a simple, heuristic analysis that is almost entirely local, the resulting object model is surprisingly accurate. the paper explains what object models are and why they are useful; describes the analysis, its assumptions, and limitations; evaluates the tool for accuracy, and illustrates its use on a suite of sample programs.
where do you go when you're through the turnstile? ten years ago, our paper described how a very small system might be developed to control a coin-operated turnstile in a zoo [1]. it arose out of our efforts to understand how requirements, domain knowledge and specifications fit together, and how specifications could be derived systematically. a particular goal was to understand requirements and specifications for telecommunication systems well enough to handle the feature interaction problem that plagues telecommunication software.a year later we published a more comprehensive version of our requirements framework [3], and began to develop the distributed feature composition (dfc) architecture for telecommunication services [2]. we continued to work on it together until mid-2002. dfc has proven successful in practice, and is now being used in a commercial voice-over-ip service.since publishing the requirements framework, we have worked on different kinds of system, and have been confronted with important differences in how its principles apply. it has taken all this time to achieve the goal of understanding requirements for telecommunication services and other connection services. in this domain, requirements are heavily influenced by the fact that services are assemblies of components added to a basic network infrastructure. our work in another direction has led to a focus on system interaction with the human and physical world, recognising the varying roles of formalisation and formal reasoning in problems of different kinds, and the need for a stronger grip on the relationship between engineering of software and engineering in the world.the common lesson of these experiences is that the requirements framework of ten years ago is a good generalization, but specific domains and situations require their own specializations of it.
development of object oriented frameworks for spatio-temporal information systems. domain specific information systems (is) have traditionally been developed using conventional structured analysis and design. this investigation looks into the various aspects of designing and developing an environmental information system (eis) using object technology and in the process identifying new, generic and specific design patterns which can be used in developing object oriented frameworks for the environment domain.
parameter value computation by least square method and evaluation of software availability and reliability at service-operation by the hyper-geometric distribution software reliability growth model (hgdm). the authors explain precisely the idea of the capture-recapture process for software faults in the context of a proposed testing environment and introduce the least square method into the model to estimate the parameter values of the hdgm. for real observed data collected during the service-operational phase, the authors show the applicability of the hgdm in estimating the degree of unavailability of a software system in operation (service). furthermore, the estimated probability of discovering zero faults as service-operation proceeds can be taken as a reliability measure
the information technology security evaluation criteria. the author presents the technical approach adopted for the information technology security evaluation criteria (itsec). the itsec are the result of harmonizing the security evaluation criteria of france, germany, the netherlands and the united kingdom. various background information which led to the development of the itsec in their current form with respect to structure, underlying evaluation philosophy, software engineering practice and external influence is presented. a wider field of applicability than previously developed security criteria was one of itsec's goals. by drawing from the best features of existing national criteria and harmonizing where possible and innovating only where necessary, it is expected that this goal has been achieved
3rd international workshop on net-centric computing (ncc 2001): theme: migrating to the web. the theme of the 3rd international workshop on net-centric computing (ncc 2001) is &ldquo;migrating to the web.&rdquo; the workshop will focus on issues related to reengineering legacy systems for use in an ncc environment. in particular, on holistic techniques for web-enabling existing applications that integrates various reengineering aspects (e.g., code, data, and user interface reengineering) into a &ldquo;whole system&rdquo; modernization process.
moving from iso9000 to higher levels of the cmm (tutorial session). practices in a &ldquo;general&rdquo; iso organizationbrief introduction to cmmleveraging iso structures for cmmgaps in an iso organization with respect to different levels of the cmm.target maturity level for an iso organizationmanaging the transitionco-existence of iso and cmm
overcoming the nah syndrome for inspection deployment. despite considerable evidence to show that inspections can help reduce costs and improve quality, inspections are not widely deployed in the software industry. one of the likely reasons for this is the &ldquo;not applicable here (nah)&rdquo; syndrome-developers and managers believe that in their environment, inspections will not provide the benefits seen by other organizations. one of the big challenges for deploying inspections is to overcome this syndrome. we describe two experiments that can be conducted, with little effort, in an organization to obtain data from the organization to build a case for inspections. by conducting one of these experiments, we were able to effectively overcome the nah syndrome in our organization-many developers and managers are now ready to try inspections in their projects. though the purpose of the experiment was to overcome the syndrome, the data from the experiment also shows how code inspections compare with unit testing in terms of defect detection capability, and the effect of inspections on the overall cost of development
enterprise application integration by means of a generic corba ldap gateway. telecommunication applications are inherently distributed and the interface provided to third party applications is often complex and also distributed. usually, these third party components need only a subset of the provided data, therefore a simple and standardized access method would be preferred. such an interface is provided by the lightweight directory access protocol (ldap) and we designed an ldap to corba (common object request broker architecture) gateway acting as a bridge between the involved technologies.
improving the customer configuration update process by explicitly managing software knowledge. the implementation and continuous support of a software product at a customer with evolving requirements is a complex task for a product software vendor. there are many customers for the vendor to serve, all of whom might require their own version or variant of the application. furthermore, the software application itself will consist of many (software) components that depend on each other to function correctly. on top of that, these components will evolve over time to meet the changing needs of customers. to alleviate this problem we propose to alleviate the software release and deployment effort and reduce risks associated with it. this will be achieved by explicitly managing typical knowledge about the software product, such as configuration and dependency information, thereby allowing software vendors to improve the customer configuration updating process. the proposed solution of knowledge management at both the customer and vendor site, is validated through industrial case studies.
research journey towards industrial application of reuse technique. component-based reuse in mission critical command and control system domain was a starting point for a long lasting research collaboration between national university of singapore (nus) and st electronics pte. ltd. (stee). stee industrial projects as well as nus lab studies revealed limitations of conventional architecture-centric, component-based reuse in the area of generic design to unify similarity patterns (e.g., similar classes, components or architectural patterns) commonly found in software. further research showed that meta-level extensions to conventional techniques could strengthen their generic design capabilities, considerably improving effectiveness of reuse solutions, and increasing productivity gains due to reuse. these experiences led to development of "mixed strategy" approach based on synergistic application of meta-level generative programming technique of xvcl, together with conventional programming techniques. in the paper, we describe university-industry collaboration that proved beneficial for both parties: stee advanced reuse practice via application of xvcl in several software product line projects. early inputs from stee helped nus team validate and refine xvcl reuse methods, and expand into new research directions. we describe a sequence of projects that led to successful application of xvcl in industrial projects. we describe experiences from those projects and their significance for both industrial practice and understanding principles of flexible software, i.e., software that can be easily changed and adapted to various reuse contexts.
cost-effective engineering of web applications pragmatic reuse: building web application product lines. web applications (wa) are developed and maintained under tight schedules. much similarity across was creates opportunities for cutting development cost and easing evolution via reuse. this tutorial shows a practical way to exploit similarity patterns - at architecture and code levels - to simplify the design of was, helping to meet the unique challenges of web engineering.
emergent process design. no abstract available
formal specification and automatic programming. an automatic programming system is proposed based on the works of noonan [2] and jazayeri and walter [10]. the system may be used to automatically produce text processing programs or to test the specifications for such programs. this is the first of three reports covering, respectively, the background and overview, architecture, and implementation of the system.
validating the tame resource data model. this paper presents a conceptual model of software development resource data and validates the model by reference to the published literature on necessary resource data for development support environments. the conceptual model presented here was developed using a top-down strategy. a resource data model is a prerequisite to the development of integrated project support environments which aim to assist in the processes of resource estimation, evaluation and control. the model proposed is a four dimensional view of resources which can be used for resource estimation, utilization, and review. the model is validated by reference to three publications on resource databases, and the implications of the model arising out of these comparisons is discussed.
an inter-organizational comparison of programming productivity. the factors which influence program size and program development time have been investigated across three dissimilar organisations. data on a total of 93 cobol programs has been collected and analysed. eighteen variables covering the characteristics of the program, programmer and programming environment were recorded. program size and program development time were found to have a strong program characteristic and organisation dependency. programmer characteristics did not appear to play a role in influencing program size or program development time. the best determinant of program development time was found to be procedure division lines of code, which gave a simple regression r2 in excess of .79 for the two organisations using well formulated programming standards. productivity measures based on lines of code per hour are shown to be misleading in inter-organisational comparisons.
atlas - an automated software testing system. the automated testing and load analysis system (atlas) formalizes a concept of model-referenced testing for large software systems. a directed graph model of the software under test, describing the sequential stimulus-response behavior of the software system, forms the basis of the approach. the objective of atlas is to certify the software under test against the model. this objective is met by components of atlas that automatically identify, generate, apply, and verify the set of tests required to establish that the software has correctly realized the model. the system has been successfully employed in testing over 40,000 instructions of bell laboratories large no. 4 ess software package. usage data and experience from this application and a critique of the approach are given.
reifying configuration management for object-oriented software. using a solid software configuration management (scm) is mandatory to establish and maintain the integrity of the products of a software project throughout the project's software life cycle. even with the help of sophisticated tools, handling the various dimensions of scm can be a daunting (and costly) task for many projects. the contribution of this paper is to propose a method (based on the use creational design patterns) to simplify scm by reifying the variants of an object-oriented software system into language-level objects; and to show that newly available compilation technology makes this proposal attractive with respect to performance (memory footprint and execution time) by inferring which classes are needed for a specific configuration and optimizing the generated code accordingly, we demonstrate this idea on an artificial case study intended to be representative of a properly designed oo software. all the performance figures me get are obtained with freely available software, and, since the source code of our case study is also freely available, they are easily reproducible and checkable
survivability analysis of network systems. survivability is the ability of a system to continue operating despite the presence of abnormal events such as failures and intrusions. ensuring system survivability has increased in importance as critical infrastructures have become heavily dependent on computers. in this paper we present a systematic method for performing survivability analysis of networked systems. an architect injects failure and intrusion events into a system model and then visualizes the effects of the injected events in the form of scenario graphs. our method enables further global analyses, such as reliability, latency, and cost-benefit analyses, where mathematical techniques used in different domains are combined in a systematic manner. we illustrate our ideas on an abstract model of the united states payment system.
portfolio management of software development projects using cocomo ii. software development projects are subject to external and internal risks that cause delays, budget overrun and poor quality. portfolio management can be used to alleviate this problem, as it pools resources together and allows for resource sharing among projects. consequently, projects are more likely to succeed. however, portfolio management using only deadlines and the number of employees to improve probability of success is still confined. this paper proposes integrating portfolio management with cocomo ii that offers more management flexibility. managers can adjust other resources, such as tools, staff capability, communication support, etc. to improve the project's success. the proposed method can also be applied despite limited historical data and expert judgment. in addition, this paper introduces time constraints into portfolio management without assuming unrealistic linearity between effort and time.
osprey: a practical type system for validating dimensional unit correctness of c programs. misuse of measurement units is a common source of errors in scientific applications, but standard type systems do not prevent such errors. dimensional analysis in physics can be used to manually detect such errors in physical equations. it is, however, not feasible to perform such manual analysis for programs computing physical equations because of code complexity. in this paper, we present a type system to automatically detect potential errors involving measurement units. it is constraint-based: we model units as types and flow of units as constraints. however, standard type checking algorithms are not powerful enough to handle units because of their abelian group nature (e.g., being commutative, multiplicative, and associative). our system combines techniques such as type inference and gaussian elimination to overcome this problem. we have implemented osprey, a prototype of the system for c programs, and evaluated it on various test programs, including computational physics and mechanical engineering applications. osprey discovered unknown errors in mature code; it is precise with few false positives; it is also efficient and scales to large programs---we have successfully used it to analyze programs with hundreds of thousands of lines of code.
human and social factors of software engineering. no abstract available
second international workshop on software engineering for high performance computing system applications. no abstract available
deriving specifications from requirements. specification-based software development makes software easier to validate and maintain. yet specifications of large systems are themselves large, making understanding and validation difficult. one cause for this problem is that specifications and requirements are kept distinct. this paper describes an approach to specification development in which the specification arises naturally through the requirements analysis process. the emerging specification is developed into a complete system description using formal transformations called high-level editing commands. automated support for this development process within the knowledge-based specification assistant will be described. this support involves applying high-level editing commands, assisting in the choice of editing commands, and tracking the effects of these commands.
an instrumented approach to improving software quality through formal technical review. formal technical review (ftr) is an essential component of all software quality assessment, assurance and improvement techniques. however, current ftr practice leads to significant expense, clerical overhead, group process obstacles, and research methodology problems. csrs is an instrumented, computer-supported cooperative work environment for formal technical review. csrs addresses problems in the practice of ftr by providing computer support for both the process and products of ftr. csrs also addresses problems in research on ftr through instrumentation supporting fine-grained, high quality data collection and analysis. this paper describes csrs, a computer-mediated review method called ftarm, and selected findings from their use to explore issues in formal technical review
beyond the personal software process: metrics collection and analysis for the differently disciplined. pedagogies such as the personal software process (psp) shift metrics definition, collection, and analysis from the organizational level to the individual level. while case study research indicates that the psp can provide software engineering students with empirical support for improving estimation and quality assurance, there is little evidence that many students continue to use the psp when no longer required to do so. our research suggests that this "psp adoption problem" may be due to two problems: the high overhead of psp-style metrics collection and analysis, and the requirement that psp users "context switch" between product development and process recording. this paper overviews our initial psp experiences, our first attempt to solve the psp adoption problem with the leap system, and our current approach called hackystat. this approach fully automates both data collection and analysis, which eliminates overhead and context switching. however, hackystat changes the kind of metrics data that is collected, and introduces new privacy-related adoption issues of its own.
proust: knowledge-based program understanding. this paper describes a program called proust which does on-line analysis and understanding of pascal written by novice programmers. proust takes as input a program and a nonalgorithmic description of the program requirements, and finds the most likely mapping between the requirements and the code. this mapping is in essence a reconstruction of the design and implementation steps that the programmer went through in writing the program. a knowledge base of programming plans and strategies, together with common bugs associated with them, is used in constructing this mapping. bugs are discovered in the process of relating plans to the code; proust can therefore give deep explanations of program bugs by relating the buggy code to its underlying intentions.
fault localization using visualization of test information. attempts to reduce the number of delivered faults in softwareare estimated to consume 50% to 80% of the developmentand maintenance effort [3]. among the tasks requiredto reduce the number of delivered faults, debugging is oneof the most time-consuming [2, 12], and locating the errorsis the most dif.cult component of this debugging task (e.g.,[13]). clearly, techniques that can reduce the time requiredto locate faults can have a signi.cant impact on the cost andquality of software development and maintenance.
visualization of test information to assist fault localization. one of the most expensive and time-consuming components of the debugging process is locating the errors or faults. to locate faults, developers must identify statements involved in failures and select suspicious statements that might contain faults. this paper presents a new technique that uses visualization to assist with these tasks. the technique uses color to visually map the participation of each program statement in the outcome of the execution of the program with a test suite, consisting of both passed and failed test cases. based on this visual mapping, a user can inspect the statements in the program, identify statements involved in failures, and locate potentially faulty statements. the paper also describes a prototype tool that implements our technique along with a set of empirical studies that use the tool for evaluation of the technique. the empirical studies show that, for the subject we studied, the technique can be effective in helping a user locate faults in a program.
task forces: distributed software for solving problems of substantial size. task is a 'high level' specification language for defining software that executes on distributed computers. software is in the form of task forces&mdash;collections of communicating parallel processes that cooperate to achieve a common goal. using the task language, a programmer specifies the interrelated components of his task force: modules exporting functions which are potentially executed in parallel, multiple data and code objects, and processes. the user may adapt the configuration of the task force to enhance performance, reliability, or the degree of distribution. in particular, data or processes may be replicated, data may be partitioned into multiple memory units, and physical resource allocations may be controlled.
formulabuilder: a tool for graph-based modelling and generation of formulae. in this paper we present the formulabuilder, a flexible tool for graph-based modelling and generation of formulae. the formulabuilder allows easy and intuitive creation of formulae by using basic components called formula building blocks (fbbs) and arranging them as graphs according to the syntactic structure of a formula. such a graph can then be validated and used to generate the corresponding formula on the basis of a specific syntax which is chosen from a list of syntaxes supported by the formulabuilder.an important application of the formulabuilder is the formal specification of properties that describe the requirements of a system. such property specifications are usually needed by verification tools like model checkers, that help software engineers to detect errors in a specified system. the formulabuilder allows users to model property specifications as formula graphs by using commonly-occurring specification patterns.
how to integrate usability into the software development process. usability is increasingly recognized as a quality attribute that one has to explicitly deal with during development. nevertheless, usability techniques, when applied, are decoupled from the software development process. the host of techniques offered by the hci (human-computer interaction) field make the task of selecting the most appropriate ones for a given project and organization a difficult task. project managers and developers aiming to integrate usability practices into their software process have to face important challenges, as the techniques are not described in the frame of a software process as it is understood in se (software engineering). even when hci experts (either in-house or from an external organization) are involved in the integration process, it is also a tough endeavour due to the strong differences in terminology and overall approach to software development between hci and se. in this tutorial we will present, from a se viewpoint, which usability techniques can be most valuable to development teams with little or no previous usability experience, how a particular set of techniques can be selected according to the specific characteristics of the organization and project, and how usability techniques match with the activity groups in the development process.
sound methods and effective tools for model-based security engineering with uml. developing security-critical systems is difficult and there are many well-known examples of security weaknesses exploited in practice. thus a sound methodology supporting secure systems development is urgently needed.we present an extensible verification framework for verifying uml models for security requirements. in particular, it includes various plugins performing different security analyses on models of the security extension umlsec of uml. here, we concentrate on an automated theorem prover binding to verify security properties of umlsec models which make use of cryptography (such as cryptographic protocols). the work aims to contribute towards usage of uml for secure systems development in practice by offering automated analysis routines connected to popular case tools. we present an example of such an application where our approach found and corrected several serious design flaws in an industrial biometric authentication system.
tools for model-based security engineering. we present tool-support for checking uml models and c code against security requirements. a framework supports implementing verification routines, based on xmi output of the diagrams from uml case tools, and on control flow generated from the c code. the tool also supports weaving security aspects into the code generated from the models. advanced users can use this open-source framework to implement verification routines for the constraints of self-defined security requirements. we focus on a verification routine that automatically verifies crypto-based software for security requirements by using automated theorem provers.
a validation of software metrics using many metrics and two resources. in this paper are presented the results of a study in which several production software systems are analyzed using ten software metrics. the ten metrics include both measures of code details, measures of structure, and combinations of these two. historical data recording the number of errors and the coding time of each component are used as objective measures of resource expenditure of each component. the metrics are validated by showing: (1) the metrics singly and in combination are useful indicators of those components which require the most resources, (2) clear patterns between the metrics and the resources expended are visible when both resources are accounted for, (3) measures of structure are as valuable in examining software systems as measures of code details, and (4) the choice of which, or how many, software metrics to employ in practice is suggested by measures of &ldquo;yield&rdquo; and &ldquo;coverage&rdquo;.
how to identify binary relations for domain models. many approaches to requirements engineering include building a model of the domain. those using entity relationship modeling or deriving from it employ the concept of relations between entities, but identifying the relations is still more of an art than science or engineering. we deal with this problem primarily in the context of object oriented analysis (ooa), where relations between object classes are to be identified. our new approach uses natural language definitions of object classes and looks for names of other object classes in these definitions, since such a reference indicates a relation. based on this idea, we identify most binary relations for domain models in a new way. we also provide tool support for this method, which shows that a high degree of automation is possible. both a case study using the well known atm (automated teller machine) example and real world experience with our approach suggest its usefulness.
an architecture for intelligent assistance in software development. we define an architecture for a software engineering environment that behaves as an intelligent assistant. our architecture consists of three key aspects: an objectbase, a model of the software development activities, and controlled automation. our objectbase is adapted from other research, but our model is unique in that is consists primarily of rules that define the preconditions and multiple postconditions of software development activities. our most significant contribution is opportunistic processing, whereby the environment performs software development activities through controlled automation. this is accomplished by a forward and backward chaining interpretation of the rule set. activities are automatically carried out at some time between when their preconditions are satisfied and when their postconditions are required. automation is controlled through strategies that guide the assistant in choosing an appropriate point for carrying out each activity.
a bi-level language for software process modeling. the authors present a multi-user implementation of a bi-level process modeling language (pml). most process modeling formalisms are well-suited to one of two levels of specification, but not both. some concentrate on global control flow and synchronization. these languages make it easy to define the broad outline of a process, but harder to refine the process by expressing constraints and policies on individual tools and data. other process formalisms are inherently local. it is easy to define constraints, but far from straightforward to express control flow. combining global and local formalisms is proposed to produce bi-level formalisms suitable for expressing the enacting large scale processes. the new pml is called the activity structures language. the activity structures language integrates global constrained expressions with local rules. its implementation on top of the marvel rule-based environment is described
a conceptual model of software maintenance. four distinct maintenance systems are studied and synthesised: the sei quality framework and three industrial systems belonging to abb, ellemtel, and ericsson. the goal is to validate the sei framework, and to build a &ldquo;state of the practice&rdquo; conceptual model of the most fundamental software maintenance concepts. this model can help understand the underlying conditions for managing software maintenance. it can provide guidance to organisations in the process of building or improving their maintenance systems. it also constitutes a common basis for communication, for reasoning about software quality, and for building quality and maintenance models
corrective maintenance maturity model (cm): maintainer's education and training. what is the point of improving maintenance processes if the most important asset, people, is not properly utilised? knowledge of the product(s) maintained, maintenance processes and communications skills is very important for achieving quality software and for improving maintenance and development processes. in this paper, we present cm3: maintainer's education and training &mdash; a maturity model for educating and training maintenance engineers. this model is the result of a comparative study of two industrial processes utilised at abb, and of process models such as ieee 1219, iso/iec 12207, cmm, people cmm, and tickit.
maintenance support tools for java programs: ccfinder and jaat. this paper describes a maintenance support tools, ccfinder and jaat, for java programs. ccfinder identifies code clones in java program. jaat executes alias analysis for java program.
parametric analysis of real-time embedded systems with abstract approximation interpretation. my research area is fundamental of formal analysis ofreal-time embedded systems. the main objective of thisresearch is the theoretical and practical development of averification algorithm for the formal analysis of real-timeembedded systems based on the combination of real-timemodel checking and abstract interpretation of real-timemodels. the objective of the proposed combination is animproved behavior both in time and space requirement ofthe resulting algorithm. one of drawbacks of all currentreal-time model-checking tools is the limited size of thesystems that can be analyzed. by combination of state-spaceexploration with abstract interpretation we expectto scale up the size of applications
daily build and feature development in large distributed projects. daily build is a software development paradigm that originated in the pc industry to get control of the development process, while still allowing the focus on end user requirements and code. the pc industry used daily build to avoid chaos in increasingly larger applications in an environment without a strong development process. ericsson radio systems has chosen to implement daily build to increase the focus on end user requirements and code, but from a different starting point with a traditionally strong development process. in this article we discuss our experiences with daily build and feature oriented development in this context. we also relate our experience to the concept of extreme programming, arguing that our ideas can help extend the applicability of extreme programming beyond small co-located projects.
verification of fairness in an implementation of monitors. an implementation in pascal by saxena and bredt of the monitor construct is studied. techniques are given for using a program verifer to analyse the conditions under which the implementation is fair (i.e. once a process is delayed it eventually will be continued). by use of a virtual data structure, fairness is represented in terms of simple properties which can be verified automatically. examples are given illustrating how the verification can force unstated assumptions upon which the implementation depends to be made explicit, and how it can be used to study whether the implementation makes adequate use of resources. the development of techniques for analysis of such implementations is required before the correctness of high-level language operating systems such as brinch hansen's solo can be completely established.
a flexible approach to alliances of complex applications. complex distributed environments contain thousands of workstations that can run hundreds of applications. multiple networks are used to connect the workstations to dozens of behind-the-scenes servers, all of which are necessary for the user to perform even simple tasks. such distributed environments are difficult to design and maintain, and current software engineering practices are not well adapted to deal with this inherent complexity. this paper describes the single glass project in the boeing commercial airplane group. single glass expands the number of both internally developed and commercial-off-the-shelf applications a single user can access from any workstation. the result is in production use by over 6,000 people in both puget sound and wichita. the key to success is a flexible and scaleable architecture that works within a complex, heterogeneous application and delivery system environment. our work has focused on both computing technology (software and delivery systems) and general processes (primary technology, support, and organization). agreements on both technology and process improvements are essential to project success. single glass is a work in progress, and we describe areas that require additional investigation. our experience indicates that most technical problems can be addressed. however, significant improvement is needed in software engineering processes and practices to design and build applications and systems that can be tested, delivered, supported, and diagnosed when made available alongside other, independently developed applications and systems.
hfp: a hierarchical and functional programming based on attribute grammar. a hierarchical and functional programming based on attribute grammar is presented. in this approach, programs are hierarchically decomposed into modules and each module is characterized by its inputs and outputs. a set of equations is associated with each decomposition, which specifies relationship between inputs and outputs of modules that participate in the decomposition. after giving formalisms and examples, an algorithm is described which transforms a program specification in our approach into a procedural type program and optimizations that should be applied to the generated program is discussed.
towards increasing the compatibility of student pair programmers. as pair programming is used widely in software engineering education, instructors may wish to proactively form pairs to increase the likelihood of compatible pairs. a study involving 361 software engineering students was carried out at north carolina state university to understand and predict pair compatibility. we have found that students are compatible with partners whom they perceive of similar skill, although instructors cannot proactively manage this perception. pairing of two minority students is more likely and mixed gender pairs are less likely to be compatible. additionally, pairing of students with similar actual skill level as measured by midterm grades in class, gpa, and sat/gre scores also likely results in compatible pairs. our research addresses the following challenges faced by instructors in software engineering: 1) organizational concern in pairing of students; 2) increasing the retention rates of female and minority students in classes; and 3) proactively forming mutually-compatible pairs.
paris: a system for reusing partially interpreted schemas. this paper describes paris, an implemented system that facilitates the reuse of partially interpreted schemas. a schema is a program and specification with abstract, or uninterpreted, entities. different interpretations of those entities will produce different programs. the paris system maintains a library of such schemas and provides an interactive mechanism to interpret a schema into a useful program by means of partially automated matching and verification procedures.
applying and adjusting a software process improvement model in practice: the use of the ideal model in a small software enterprise. software process improvement is a demanding and complex undertaking. to support the constitution and implementation of software process improvement schemes the software engineering institute (sei) proposes a framework, the so-called ideal model. this model is based on experiences from large organizations. the aim of the research described here was to investigate the suitability of the model for small software enterprises. it has therefore been deployed and adjusted for successful use in a small danish software company. the course of the project and the application of the model are presented and the case is reflected on the background of current knowledge about managing software process improvement as organizational change.
quantifying the costs and benefits of architectural decisions. the benefits of a software system are assessable only relative to the business goals the system has been developed to serve. in turn, these benefits result from interactions between the system's functionality and its quality attributes (such as performance, reliabilty and security). its quality attributes are, in most cases, dictated by its architectural design decisions. therefore, we argue in this paper that the software architecture is the crucial artifact to study in making design tradeoffs and in performing cost-benefit analyses. a substantial part of such an analysis is in determining the level of uncertainty with which we estimate both costs and benefits. in this paper we offer an architecture-centric approach to the economic modeling of software design decision making called cbam (cost benefit analysis method), in which costs and benefits are traded off with system quality attributes. we present the cbam, the early results from applying this method in a large-scale case study, and discuss the application of more sophisticated economic models to software decision making.
bridging the gaps between software engineering and human-computer interaction. the first international workshop on the relationships between software engineering and human-computer interaction was held on may 3--4, 2003 as part of the 2003 international conference on software engineering, in portland, or, u.s.a. this workshop was motivated by a perception among researchers, practitioners, and educators that the fields of human-computer interaction and software engineering were largely ignoring each other and that they needed to work together more closely and to understand each other better. this paper describes the motivation, goals, organization, and outputs of the workshop.
bridging the gaps ii: bridging the gaps between software engineering and human-computer interaction. the second international workshop on the relationshipsbetween software engineering and human-computer interaction was held on may 24-25, 2004 as part of the 2004 international conference on softwareengineering, in edinburgh, scotland. this workshop wasthe second at icse and the fourth in a series held at internationalconferences in the past two years. it was motivatedby a perception among researchers, practitioners,and educators that the fields of human-computer interactionand software engineering were largely ignoringeach other and that they needed to work together moreclosely and to understand each other better. this reportdescribes the motivation, goals, organization, and outputsof the workshop.
experience with performing architecture tradeoff analysis. software architectures, like complex designs in any field, embody tradeoffs made by the designers. however, these tradeoffs are not always made explicitly by the designers and they may not understand the impacts of their decisions. this paper describes the use of a scenario-based and model-based analysis technique for software architectures-called atam-that not only analyzes a software architecture with respect to multiple quality attributes, but explicitly considers the tradeoffs inherent in the design. this is a method aimed at illuminating risks in the architecture through the identification of attribute trends, rather than at precise characterizations of measurable quality attribute values. in this paper, the operationalization of atam is illustrated via a specific example in which we analyzed a u.s. army system for battlefield management.
designing and analyzing software architectures using abass (tutorial session). this tutorial will discuss, exemplify, and involve the students in the use of attribute-based architectural styles (abass)&mdash;architectural styles accompanied by explicit analysis reasoning frameworks&mdash;in both the design and analysis of software and system architectures. the tutorial has several objectives: to introduce the students to a catalog of abass covering performance, availability, testability, modifiability, and usability; to convince students that abass provide a basis for insightful reasoning about a software architecture's ability to meet its quality attribute goals; and to demonstrate the utility of abass by showing examples of how abass are used to design and analyze real-world system architectures. we will present some large excerpts from our growing abas handbook and show that abass help us in designing architectures efficiently and predictably and in quickly finding architectural risks and tradeoffs when doing analysis.
the 8th international workshop on economics-driven software engineering research. this paper presents the 8th international workshop on economics-driven software engineering research (edser-8).
agile process tailoring and problem analysis (aptly). developing software using a well-defined, well-understoodprocess improves the likelihood of deliveringa product with the required quality. enhancing thatprocess to meet recognised process standards, such ascmmi and iso 9000, can further facilitate thedevelopment of complex systems in a repeatable andpredictable way. there are tradeoffs involved, however.in particular, because projects differ in their scale, scope,and technical challenge, the same process will not suit allcircumstances. agile approaches to development, such asextreme programming (xp), scrum and crystalmethodologies, recognise this dilemma and suggest thatprocesses be tailored to each situation. the researchproblem for postgraduate investigation is to determine indetail how this can be achieved successfully. this willinclude a consideration of how best to define, maintainand give access to a knowledge base recording details ofprocess concepts, techniques and experience.
an inheritance-based technique for building simulation proofs incrementally. this paper presents a formal technique for incremental construction of system specifications, algorithm descriptions, and simulation proofs showing that algorithms meet their specifications.the technique for building specifications and algorithms incrementally allows a child specification or algorithm to inherit from its parent by two forms of incremental modification: (a) signature extension, where new actions are added to the parent, and (b) specialization (subtyping), where the child's behavior is a specialization (restriction) of the parent's behavior. the combination of signature extension and specialization provides a powerful and expressive incremental modification mechanism for introducing new types of behavior without overriding behavior of the parent; this mechanism corresponds to the subclassing for extension form of inheritance.in the case when incremental modifications are applied to both a parent specification s and a parent algorithm a, the technique allows a simulation proof showing that the child algorithm a&prime; implements the child specification s&prime; to be constructed incrementally by extending a simulation proof that algorithm a implements specification s. the new proof involves reasoning about the modifications only, without repeating the reasoning done in the original simulation proof.the paper presents the technique mathematically, in terms of automata. the technique has been used to model and verify a complex middleware system; the methodology and results of that experiment are summarized in this paper.
user interface development and software environments: the chiron-1 system. the authors discuss a list of requirements which should be met by the user interface development system (uids) to address the special demands of software environments. chiron-1 uses an annotation-based, concurrent model which makes a clear separation between an application's functional and user interface parts, while still promoting effective communication between those parts. the uids model and language interface and the uids architecture are described. the authors describe how applications are built with chiron-1, and illustrate the process with an example. important chiron-1 concepts are presented, and their significance in the software environment context is explained. the authors detail some design issues and report on the status of current work and the plans for future research
a comprehensive process model for studying software process papers. efficient and effective study of scientific papers is an important part of software engineering education. a comprehensive process model has been developed, enacted, improved and validated. the process model describes literature search, paper selection, reading, and group discussion of papers, as well as recording, validation, and retrieval of the data captured from the selected papers. the focus lies on the group discussion of the model. a model of this sub-process describes the systematic classification, analysis, and evaluation of the papers. it is used to guide the group discussion, and helps to ensure that pertinent information from the discussion is retained in an annotated database
pattern-based reverse-engineering of design components. many reverse-engineering tools have been developed to derive abstract representations from source code. yet, most of these tools completely ignore recovery of the all-important rationale behind the design decisions that have lead to its physical shape. design patterns capture the rationale behind proven design solutions and discuss the trade-offs among their alternatives. we argue that it is these patterns of thought that are at the root of many of the key elements of large-scale software systems, and that, in order to comprehend these systems, we need to recover and understand the patterns on which they were built. in this paper, we present our environment for the reverse engineering of design components based on the structural descriptions of design patterns. we give an overview of the environment, explain three case studies, and discuss how pattern-based reverse-engineering helped gain insight into the design rationale of some of the pieces of three large-scale c++ software systems.
a comparison of four design methods for real-time systems. the purpose of this paper is to compare four design methods which are of current interest in real-time software development. the comparison presents the relative strengths and weakness of each method with additional information on graphic notation and the recommended sequence of steps involved in the use of each method. the methods selected for comparison were:structured design for real-time systemsobject oriented designpamela (process abstraction method for embedded large applications)scr (software cost reduction project - naval research laboratory) readers interested in a framework for comparing methods, an overview of the four selected methodologies, and an aid to narrowing candidates for adoption should find this find this paper helpful.
cybersecurity. as more business activities are being automated and an increasing number of computers are being used to store sensitive information, the need for secure computer systems becomes more apparent. this need is even more apparent as systems and applications are being distributed and accessed via an insecure network, such as the internet. the internet itself has become critical for governments, companies, financial institutions, and millions of everyday users. networks of computers support a multitude of activities whose loss would all but cripple these organizations. as a consequence, cybersecurity issues have become national security issues. protecting the lnternet is a difficult task.cybersecurity can be obtained only through systematic development; it can not be achieved through haphazard seat-of-the-pants methods. applying software engineering techniques to the problem is a step in the right direction. however, software engineers need to be aware of the risks and security issues associated with the design, development, and deployment of network-based software.this paper introduces some known threats to cybersecurity, categorizes the threats, and analyzes protection mechanisms and techniques for countering the threats. approaches to prevent, detect, and respond to cyber attacks are also discussed.
research challenges of autonomic computing. autonomic computing is a grand-challenge vision of the future in which computing systems will manage themselves in accordance with high-level objectives specified by humans. the it industry recognizes that meeting this challenge is imperative; otherwise, it systems will soon become virtually impossible to administer. but meeting this challenge is also extremely difficult, and will require a worldwide collaboration among the best minds of academia and industry. in the hope of motivating researchers in relevant areas to apply their expertise to this vitally important problem, i outline some of the main scientific and engineering challenges that collectively make up the grand challenge of autonomic computing, and provide pointers to initial efforts to address these challenges.
specification and implementation of parallel activities on abstract objects. this paper describes a new method for the specification and implementation of parallel activities on abstract objects. the priority relationship, which is of practical importance, is an important part of this method. the syntax of a suitable specification language is given. restrictions in the lower levels of a hierarchical system can be hidden towards the upper levels (e.g. finite capacity of buffers or memories) by an appropriate use of synchronization. to make the use of a particular level as flexible as possible, the level should be subject to as few restrictions as possible. synchronization conditions on different levels can lead to deadlocks.
a comparison of lifecycle models. preliminary comparison of world views in systems development is given. the purpose of the paper is to present the finnish psc systemeering model to the software engineering (se) community and to compare it with the ideas of d. ross and practical approaches in se.
a synthetic english query language for a relational accociative processor. synthetic english is a very-high-level query language based on natural english. query specification in synthetic english parallels the user's natural thought processes, thereby allowing him to formulate complex queries without regard to implicit or explicit language control structures. synthetic english is designed to be used in conjunction with the functional data model, which is a conceptual graph model whose nodes and arcs represent sets and total functions, respectively. further, the functional model admits a transformation to the relational model representation. queries written in synthetic english are easily parsed, using semantic predication analysis and the underlying graph, into primitive templates which are in one-to-one correspondence with the high-level machine language of the relational associative processor called rap. rap is an associative and cellular back-end processor designed to support relational data bases. rap's proven performance superiority over conventional architectures, its high-level machine language, and its query processing philosophy, make the interface to synthetic english extremely efficient, avoiding intermediate-level code generation.
analysis of a scheduler for a cad framework. the experience report describes a case study in which a key component of a software system was modeled and analyzed to better understand a proposed algorithm prior to implementation. a promela model of a linear scheduler for a cad framework was developed. the spin simulator was used to debug the model and, later, to illustrate how the algorithm works in different scenarios. additionally, the spin verifier was used to check various safety and liveness properties. the study revealed a deficiency with the algorithm, as originally proposed. subsequently, the modeling tools provided by spin were used in devising solutions to the problems. finally, the promela model was modified and verified to be correct. the actual implementation of the scheduler involves a significant amount of message passing, multiple execution threads, and potentially huge data structures. by focusing on the interfaces between threads, restricting the system scope, and abstracting details of data structures and irrelevant computations, a very simple model was obtained, which nevertheless provides an accurate representation of the communication between threads. the paper describes the steps that were abstracted and highlights the restrictions imposed on the model.
extending the representational state transfer (rest) architectural style for decentralized systems. because it takes time and trust to establish agreement,traditional consensus-based architectural styles cannotsafely accommodate resources that change faster than ittakes to transmit notification of that change, nor resourcesthat must be shared across independent agencies.the alternative is decentralization: permitting independentagencies to make their own decisions. ourdefinition contrasts with that of distribution, in whichseveral agents share control of a single decision.ultimately, the physical limits of network latency and thesocial limits of independent agency call for solutions thatcan accommodate multiple values for the same variable.our approach to this challenge is architectural: proposingconstraints on the configuration of componentsand connectors to induce particular desired properties ofthe whole application. specifically, we present, implement,and evaluate variations of the world wide webýsrepresentational state transfer (rest) architecturalstyle that support distributed and decentralized systems.
aspect-oriented programming. no abstract available
aspect-oriented programming and modular reasoning. aspects cut new interfaces through the primary decomposition of a system. this implies that in the presence of aspects, the complete interface of a module can only be determined once the complete configuration of modules in the system is known. while this may seem anti-modular, it is an inherent property of crosscutting concerns, and using aspect-oriented programming enables modular reasoning in the presence of such concerns.
a type-checking program linkage system for pascal. we describe a new software facility useful in the development, debugging, and integration of quasi-independent program modules. it has been implemented in conjunction with a pascal compiler for ibm 360 computers, but the linkage facility is machine-independent up to the point of formattingsystem object modules. with some minor syntactic extensions to permit the designation of external references, pascal becomes a powerful language for modular programming. the new linkage subsystem allows the compile-time verification of type-correctness of pascal programs to be extended uniformly across program module interfaces. this extends not only those diagnostics formerly restricted to compilation, but also the post-mortem diagnostic capability of the progranming system, and without sacrifice of run-time efficiency. the paper also discusses several language issues raised in meeting the requirements of modular programming, as well as implementation considerations.
a software engineering experiment in software component generation. the paper presents results of a software engineering experiment in which a new technology for constructing program generators from domain-specific specification languages has been compared with a reuse technology that employs sets of reusable ada program templates. both technologies were applied to a common problem domain, constructing message translation and validation modules for military command, control, communications and information systems (c/sup 3/i). the experiment employed four subjects to conduct trials of use of the two technologies on a common set of test examples. the experiment was conducted with personnel supplied and supervised by an independent contractor. test cases consisted of message specifications taken from air force c/sup 3/i systems. the main results are that greater productivity was achieved and fewer error were introduced when subjects used the program generator than when they used ada templates to implement software modules from sets of specifications. the differences in the average performance of the subjects are statistically significant at confidence levels exceeding 99 percent.
asadal: a tool system for co-development of software and test environment based on product line engineering. recently, product line software engineering (plse) is gaining popularity. to employ plse methods, many organizations are looking for a tool system that supports plse methods so that core assets and target software can be developed and tested in an effective and systematic way.asadal (a system analysis and design aid tool) supports the entire lifecycle of software development process based on a plse method called form (feature-oriented reuse method) [6]. it supports domain analysis, architecture and component design, code generation, and simulation-based verification and validation (v&v). using the tool, users may co-develop target software and its test environment and verify software in a continuous and incremental way.
uml-based service robot software development: a case study. the research field of intelligent service robots, which has become more and more popular over the last years, covers a wide range of applications from climbing machines for cleaning large storefronts to robotic assistance for disabled or elderly people. when developing service robot software, it is a challenging problem to design the robot architecture by carefully considering user needs and requirements, implement robot application components based on the architecture, and integrate these components in a systematic and comprehensive way for maintainability and reusability. furthermore, it becomes more difficult to communicate among development teams and with others when many engineers from different teams participate in developing the service robot. to solve these problems, we applied the comet design method, which uses the industry-standard uml notation, to developing the software of an intelligent service robot for the elderly, called t-rot, under development at center for intelligent robotics (cir). in this paper, we discuss our experiences with the project in which we successfully addressed these problems and developed the autonomous navigation system of the robot with the comet/uml method.
re-engineering software architecture of home service robots: a case study. with the advances of robotics, computer science, and other related areas, home service robots attract much attention from both academia and industry. home service robots present interesting technical challenges to the community in that they have a wide range of potential applications, such as home security, patient caring, cleaning, etc., and that the services provided by the robots in each application area are being defined as markets are formed and, therefore, they change constantly.without architectural considerations to address these challenges, robot manufacturers often focus on developing technical components (e.g., vision recognizer, speech processor, and actuator) and then attempt to develop service robots by integrating these components. when prototypes are developed for a new application, or when services are added, modified, or removed from existing robots, unexpected, undesirable, and often dangerous side-effects, which are known as feature interaction problem, happen frequently. reengineering of such robots can make a serious impact in delivery time and development cost.in this paper, we present our experience of re-engineering a prototype of a home service robot developed by samsung advanced institute of technology. first, we designed a modular and hierarchical software architecture that makes interaction among the components visible. with the visibility of interactions, we could assign functional responsibilities to each component clearly. then, we re-engineered existing codes to conform to the new architecture using a reactive language esterel. as a result, we could detect and solve feature interaction problems and alleviate the dificulty of adding or updating components.
a history-based test prioritization technique for regression testing in resource constrained environments. regression testing is an expensive and frequently executed maintenance process used to revalidate modified software. to improve it, regression test selection (rts) techniques strive to lower costs without overly reducing effectiveness by carefully selecting a subset of the test suite. under certain conditions, some can even guarantee that the selected test cases perform no worse than the original test suite.but this ignores certain software development realities such as resource and time constraints that may prevent using rts techniques as intended (e.g., regression testing must be done overnight, but rts selection returns two days worth of tests). in practice, testers work around this by prioritizing the test cases and running only those that fit within existing constraints. unfortunately this generally violates key rts assumptions, voiding rts technique guarantees and making regression testing performance unpredictable.despite this, existing prioritization techniques are memoryless, implicitly assuming that local choices can ensure adequate long run performance. instead, we proposed a new technique that bases prioritization on historical execution data. we conducted an experiment to assess its effects on the long run performance of resource constrained regression testing. our results expose essential tradeoffs that should be considered when using these techniques over a series of software releases.
an empirical study of regression test application frequency. regression testing is an expensive maintenance process used to revalidate modified software. regression test selection (rts) techniques try to lower the cost of regression testing by selecting and running a subset of the existing test cases. many such techniques have been proposed and initial studies show that they can produce savings. we believe, however, that issues such as the frequency with which testing is done have a strong effect on the behavior of these techniques. therefore, we conducted an experiment to assess the effects of test application frequency on the costs and benefits of regression test selection techniques. our results expose essential tradeoffs that should be considered when using these techniques over a series of software releases.
restructuring oodesigner: a case tool for omt. this report describes our experience acquired when we restructured oodesigner, a computer aided software engineering (case) tool for object modeling techniques (omt). we had developed the version 1.x of oodesigner during 3 years since 1994. although we had developed this version using omt and c++, we recognized the potential maintenance problem that originated from the ill-designed class architecture. thus we totally restructured the old version of oodesigner during 12 months, and obtained a new version that is much easier to maintain than the old one
web engineering device independent web services. today's web services not only have to be flexible, but also have to be device independent to support mobile devices such as wap and pdas. supporting multiple web formats (e.g., wml, html, etc.) is still an open challenge. most sites have to provide a separate application for every format and reuse is not common. we are working on a methodology and a tool to support the web developer in building flexible, device independent web services.
a flexible software process model. the development of software products is a complex activitywith a large number of factors involved in definingsuccess. as real-world experimentation is difficult andcostly, researchers have used various techniques in an attemptto model the development process. this field of softwareprocess simulation has received substantial attentionover the last twenty years. the aims have been to betterunderstand the software development process and to mitigatethe problems that continue to occur in the industry byproviding support for management decision making.
intellectual property protection for software in the united states and europe (tutorial session): the changing roles of patents and copyrights. this tutorial addresses how both the object management group (omg) specifications and the implementation choices made by middleware providers and application developers affect common object request broker architecture (corba) application scalability. we will cover a range of scalability issues, starting with object request broker (orb) internals and working outward to full-scale applications, addressing issues such as connection management, portable object adapter (poa) scalability features, multithreading, object lifecycle issues, object location, system configuration, maintenance, and management, and common application architectures. this tutorial is not language-centric and is useful to developers using java, c++, or any other language to develop corba-based applications.
sda: a novel approach to software environment design and construction. a software designer's associate (sda) is a workstation-based collection of tools which support: 1) the description, evaluation and comparison of software system architectural designs, and 2) cooperation among, and management of, a team of software designers [ridd87]. each software designer's associate is a specific instance of a generic facility which supports a team member's design activities, cooperation among team members, and overall team management. it provides a framework for the integration of tools supporting the use of various notations within the context of a particular set of technical and managerial methods. these tools, notations and methods may be adapted to support the needs of a particular project or the habits of an individual developer by selecting the particular tools to be added to the generic facility. the software designer's associate project is a joint effort involving a consortium of researchers from academic and industrial organizations in both japan and the united states. this paper describes the concept of software designer's associates and the cooperative, international project which is intended to lead to the realization of that concept.
evidence-based software engineering. objective: our objective is to describe how softwareengineering might benefit from an evidence-basedapproach and to identify the potential difficultiesassociated with the approach.method: we compared the organisation and technicalinfrastructure supporting evidence-based medicine (ebm)with the situation in software engineering. we consideredthe impact that factors peculiar to software engineering(i.e. the skill factor and the lifecycle factor) would haveon our ability to practice evidence-based softwareengineering (ebse).results: ebse promises a number of benefits byencouraging integration of research results with a view tosupporting the needs of many different stakeholdergroups. however, we do not currently have theinfrastructure needed for widespread adoption of ebse.the skill factor means software engineering experimentsare vulnerable to subject and experimenter bias. thelifecycle factor means it is difficult to determine howtechnologies will behave once deployed.conclusions: software engineering would benefit fromadopting what it can of the evidence approach providedthat it deals with the specific problems that arise from thenature of software engineering.
inter-item correlations among function points. the paper reports on an empirical investigation of albrecht function points.the study suggests that function points are not well-formed metrics because there is a correlation between their constituent elements. it also suggests that (for the dataset under investigation) two of the constituent elements were as good at predicting effort as the raw function point count and that the unweighted counts can be reasonable predictors of effort
lessons learnt from the analysis of large-scale corporate databases. this paper presents the lessons learnt during the analysis of the corporate databases developed by ibm global services (australia). ibm is rated as cmm level 5. following cmm level 4 and above practices, ibm designed several software metrics databases with associated data collection and reporting systems to manage its corporate goals. however, ibm quality staff believed the data were not as useful as they had expected. nicta staff undertook a review of ibm's statistical process control procedures and found problems with the databases mainly due to a lack of links between the different data tables. such problems might be avoided by using m3p variant of the gqm paradigm to define a hierarchy of goals, with project goals at the lowest level, then process goals and corporate goals at the highest level. we propose using e-r models to identify problems with existing databases and to design databases once goals have been defined.
industrial-strength software product-line engineering. software product-line engineering is one of the few approaches to software engineering that shows promise of improving software productivity by factors of 5 to 10. there are still few examples of its successful application on a large scale, partly because of the complexity of initiating a product-line engineering project and the many factors that must be addressed for such a project to be successful.this tutorial draws on experiences in introducing and sustaining product-line engineering in lucent technologies and in avaya. the objective is to convey to participants the obstacles involved in transitioning to product line engineering and how to overcome such obstacles, particularly in large software development organizations. participants will learn both technical and organizational aspects of the problem. participants will leave the tutorial with many ideas on how to introduce product line engineering into an organization in a systematic way.
a high level language for specifying graph based languages and their programming environments. the authors describe a high level language for specifying programming environments for programming languages that are based on directed attributed graphs. the high level language allows the specifier to describe views of portions of a program written in such a graph-based language, the editing operations used to create the program, animations of the execution of the program, and sufficient detail of the execution semantics to support the animations. the use of the specification language is demonstrated with a simple example of a graph-based language. the automatic generation of the programming environment is described for such graph based languages from descriptions made in the specification language. the specification language is based on using a grammar to describe the components of the graph based language and using a first-order logic based language to describe state changes in editing, execution, and animation
icse workshop on software variability management. during recent years, the amount of variability that has to be supported by a software artifact is growing considerably and its management is developing as a main challenge during development, usage, and evolution of software artifacts. successful management of variability in software artifacts leads to better customizable software products that are in turn likely to result in higher market success.the aim of this workshop is to study software variability management both from a 'problems' and from a 'solutions' perspective by bringing together people from industrial practice and from applied research in academia to present and discuss their respective experience.issues to be addressed include, but are not limited to, technological, process, and organizational aspects as well as notation, assessment, design, and evolution aspects.
safety critical systems: challenges and directions. safety-critical systems are those systems whose failure could result in loss of life, significant property damage, or damage to the environment. there are many well known examples in application areas such as medical devices, aircraft flight control, weapons, and nuclear systems. many modern information systems are becoming safety-critical in a general sense because financial loss and even loss of life can result from their failure. future safety-critical systems will be more common and more powerful. from a software perspective, developing safety critical systems in the numbers required and with adequate dependability is going to require significant advances in areas such as specification, architecture, verification, and process. the very visible problems that have arisen in the area of information-system security suggests that security is a major challenge also.
an experimental evaluation of simple methods for seeding program errors. this paper describes an experiment in which simple syntactic alterations were introduced into program text in order to evaluate the testing strategy known as error seeding. the experiment's goal was to determine if randomly placed syntactic manipulations can produce failure characteristics similar to those of indigenous errors found within unseeded programs. as a result of a separate experiment, several programs were available, all of which were written to the same specifications and thus were intended to be functionally equivalent. the use of functionally equivalent programs allowed the influence of individual programmer styles to be removed as a variable from the error seeding experiment. each of six different syntactic manipulations were introduced into each program and the mean times to failure for the seeded errors were observed. the seeded errors were found to have a broad spectrum of mean times to failure independent of the syntactic alteration used. we conclude that it is possible to seed errors using only simple syntactic techniques that are arbitrarily difficulty to locate. in addition, several unexpected results indicate that some issues involved in error seeding have not been addressed previously.
a modification request control system. the modification request control system (mrcs) tracks and reports project change requests and resulting activity through interactive input and extraction of change request data from computer files. mrcs is one of the tools available as part of the programmer's workbench (pwb). it was developed to aid in the timely control and coordination of software changes. it provides the capability to: (1) interactively create, update, and print mrs; (2) track and record the flow of the mr through the system development cycle; and (3) provide management with timely mr status information via reports and on-line inquiries. mrcs supports many projects, each project with its own mr data base and commands. it provides, via common control logic, standard operations such as the creation, updating, and printing of mrs, and the extraction of data from them. each project then defines the fields, validity checks, defaults, prompting sequences, and report formats which satisfy its particular requirements, and these are used to produce an mrcs for that project.
eliciting design requirements for maintenance-oriented ides: a detailed study of corrective and perfective maintenance tasks. recently, several innovative tools have found their way into mainstream use in modern development environments. however, most of these tools have focused on creating and modifying code, despite evidence that most of programmers' time is spent understanding code as part of maintenance tasks. if new tools were designed to directly support these maintenance tasks, what types would be most helpful? to find out, a study of expert java programmers using eclipse was performed. the study suggests that maintenance work consists of three activities: (1) forming a working set of task-relevant code fragments; (2) navigating the dependencies within this working set; and (3) repairing or creating the necessary code. the study identified several trends in these activities, as well as many opportunities for new tools that could save programmers up to 35% of the time they currently spend on maintenance tasks.
analysis of the interaction between practices for introducing xp effectively. in this paper, we discuss interactions between xp (extreme programming) practices. we discuss 2 case studies of introducing xp practices selectively from the 13 practices which are defined in xp, and we analyze how to select practices. our analysis is based on interviews with developers. while it is difficult to introduce all the xp practices at once, our knowledge makes it easier to determine more effective combinations of practices.
integrating uml diagrams for production control systems. this paper proposes to use sdl block diagrams, uml class diagrams, and uml behavior diagrams like collaboration diagrams, activity diagrams, and statecharts as a visual programming language. we describe a modeling approach for flexible, autonomous production agents, which are used for the decentralization of production control systems. in order to generate a (java) implementation of a production control system from its specification, we define a precise semantics for the diagrams and we define how different (kinds of) diagrams are combined to a complete executable specification.generally, generating code from uml behavior diagrams is not well understood. frequently, the semantics of a uml behavior diagram depends on the topic and the aspect that is modeled and on the designer that created it. in addition, uml behavior diagrams usually model only example scenarios and do not describe all possible cases and possible exceptions.we overcome these problems by restricting the uml notation to a subset of the language that has a precise semantics. in addition, we define which kind of diagram should be used for which purpose and how the different kinds of diagrams are integrated to a consistent overall view.
modeling aspect mechanisms: a top-down approach. a plethora of aspect mechanisms exist today. all of these diverse mechanisms integrate concerns into artifacts that exhibit crosscutting structure. what we lack and need is a characterization of the design space that these aspect mechanisms inhabit and a model description of their weaving processes. a good design space representation provides a common framework for understanding and evaluating existing mechanisms. a well-understood model of the weaving process can guide the implementor of new aspect mechanisms. it can guide the designer when mechanisms implementing new kinds of weaving are needed. it can also help teach aspect-oriented programming (aop). in this paper we present and evaluate such a model of the design space for aspect mechanisms and their weaving processes. we model weaving, at an abstract level, as a concern integration process. we derive a weaving process model (wpm) top-down, differentiating a reactive from a nonreactive process. the model provides an in-depth explanation of the key subprocesses used by existing aspect mechanisms.
an innovative approach to system requirements analysis by using structural modeling method. as an innovative approach to the system requirements analysis, this paper proposes a computer aided method to develop objectives trees. this method consists of a procedure, algorithms and, a man-machine interactive graphic system. and two typical kinds of applications of the objectives tree in computer applications system planning are described. by this method, working man-hours to develop an objectives tree can be decreased, and quality of communication among system venders, end-users of a computer system, edp managers and top executives, can be highly improved.
experiences of applying spc techniques to software development processes. experiences of applying spc techniques to software development processes are described. several real examples to apply spc in hitachi software are given. measures, control charts, and analysis judgment are given. characteristics of software development processes, their influence on spc, and lessons learned when applying spc to software processes are described. in particular, the importance of self-directed and proactive improvement is discussed.
assurance patterns for distributed real-time embedded systems. no abstract available
real-time specification patterns. embedded systems are pervasive and frequently used for critical systems with time-dependent functionality. dwyer et al have developed qualitative specification patterns to facilitate the specification of critical properties, such as those that must be satisfied by embedded systems. thus far, no analogous repository has been compiled for real-time specification patterns. this paper makes two main contributions: first, based on an analysis of timing-based requirements of several industrial embedded system applications, we created real-time specification patterns in terms of three commonly used real-time temporal logics. second, as a means to further facilitate the understanding of the meaning of a specification, we offer a structured english grammar that includes support for real-time properties. we illustrate the use of the real-time specification patterns in the context of property specifications of a real-world automotive embedded system.
a case study in applying a systematic method for cots selection. this paper describes a case study that used and evaluated key aspects of a method developed for systematic reusable off-the-shelf software selection. the paper presents a summary of the common problems in reusable off-the-shelf software selection, describes the method used and provides details about the case study carried out. the case study indicated that the evaluated aspects of the method are feasible, improve the quality and efficiency of reusable software selection and the decision makers have more confidence in the evaluation results, compared to traditional approaches. furthermore, the case study also showed that the choice of evaluation data analysis method can influence the evaluation results.
fifth international workshop on economics-driven software engineering research (edser-5) "the search for value in engineering decisions". the series of edser workshops are a unique forum to discuss and advance the state-of-the-art research and practice in economics driven software engineering. the edser-5 will bring together leading researchers and practitioners to provide further understanding how economic and business considerations affect -- and should affect -- software engineering decisions.
managing commitments and risks: challenges in distributed agile development. software development is always a challengingundertaking and it requires high commitments fromindividuals who participate in it. software developmentoften involves new technology, challenging or unknownrequirements, and tight schedules ¿ making itparticularly prone to several types of risk. thesechallenges are even more paramount in agiledevelopment and in distributed development, where theneed for efficient information sharing is important, yetthe distributed development makes it very difficult.this tutorial uses innovative and new learning methodsto explore and to learn about these challenges and howto deal with them. the tutorial is partially based onpresentations given by authors, but a major element inthe tutorial is the case study that is introduced and inwhich will involve all the participants. the learning inthe tutorial is strongly facilitated by participantsýdiscussions and the insights generated in concreteproblem solving situations.
process design system: an integrated set of software development tools. the process design engineering program, under the direction of the ballistic missile defense advanced technology center, has as its objective the development of a unified software engineering discipline addressing all software development problems from receipt of software requirements to delivery of the operational software system. during the first two years of this program, initial process design engineering and management procedures were developed which led to the systematic top-down development of real-time software processes. a prototype set of software tools to support these procedures was designed and implemented as process design system 1 (pds 1 ), and an experimental bmd baseline software process was then designed and implemented using these techniques and tools. the baseline experiment demonstrated that although the basic concepts employed were effective for the tactical software (1), there were several deficiencies in the process design tools. the most important deficiency stemmed from the fact that the system was designed to support the development of only the tactical software. this resulted in the operating system software (the most difficult component) being implemented without the aid of pds and in assembly language at cost of thirty percent of the budget for nine percent of the code. additional problem areas were the lack of positive control over data accessing, inadequate data structuring capability, and the interruption and synchronization of operations.
assertion-oriented automated test data generation. assertions are recognized as a powerful tool for automatic run time detection of software errors. however, existing testing methods do not use assertions to generate test cases. we present a novel approach of automated test data generation in which assertions are used to generate test cases. in this approach the goal is to identify test cases on which an assertion is violated. if such a test is found then this test uncovers an error in the program. the problem of finding program input on which an assertion is violated may be reduced to the problem of finding program input on which a selected statement is executed. as a result, the existing methods of automated test data generation for white box testing may be used to generate tests to violate assertions. the experiments have shown that this approach may significantly improve the chances of finding software errors as compared to the existing methods of test generation.
from uml to java, building a 3-tier architecture: case study. the successful use of object technology requires far more than simply the adoption of a modern software technology or notation such as uml, java, corba or com. what is crucial, is knowing how to use these technologies to build commercially robust software systems. in this session the speaker draws on his experience at nasa, at&t, ibm, nova gass, and other leading companies to illustrate the pitfalls and best practices of component based software development.
scene: using scenario diagrams and active text for illustrating object-oriented programs. scenario diagrams are a well-known notation for visualizing the message flow in object-oriented systems. traditionally, they are used in the analysis and design phases of software development to prototype the expected behavior of a system. we show how they can be used in reverse for understanding and browsing existing software. we have implemented a tool called scene (scenario environment) that automatically produces scenario diagrams for existing object-oriented systems. the tool makes extensive use of an active text framework providing the basis for various hypertext-like facilities. it allows the user to browse not only scenarios but also various kinds of associated documents, such as source code (method definitions and calls), class interfaces, class diagrams and call matrices.
model processing tools in uml. unified modeling language (uml) provides several diagram types viewing a system from different perspectives. in this research, we exploit logical relationships between different uml models. we propose operations to compare, merge, slice and synthesize uml diagrams based on these relationships. in the formal demonstration we show how statechart diagrams can be synthesized semi-automatically from a set of sequence diagrams using an interactive algorithm called mas. we also demonstrate how a class diagram, annotated with pseudocode presentations of key operations, can be synthesized from sequence diagrams, and how class diagrams and sequence diagrams can be sliced against each other.
the internet as a medium for software engineering experiments. empirical software engineering often faces the challenge of large variability of results among individual subjects. variability can be reduced by using a larger group of subjects, but such group quickly becomes too expensive. another challenge is finding a group of subjects that is representative of some relevant population of software engineers. this paper explores the potential of using the internet as the medium for software engineering experiments to address the problems of sample size and representativeness.
segras - a formal and semigraphical language combining petri nets and abstract data types for the specification of distributed systems. segras is formal language for writing and analyzing specifications of distributed software systems. it unifies algebraic specifications of abstract data types with high-level petri net specifications of nonsequential systems in a common syntactic and semantic framework. the data structure of a system, the information content of its local states, and static constraints to state changes are specified algebraically using positive conditional equations. dynamic behavior is specified by high level petri nets. each net defines a (distributed) initial state and a partial ordering in which state changing operations may happen. segras addresses advanced programming methodologies by offering facilities for modularization and parameterization, and a type system which supports polymorphism with dependent types, higher-order types, subtypes, and overloading. some examples are given to illustrate these language concepts.
distributed software engineering. the term &ldquo;distributed software engineering&rdquo; is ambiguous. it includes both the engineering of distributed software and the process of distributed development of software, such as cooperative work. this paper concentrates on the former, giving an indication of the special needs and rewards in distributed computing. in essence, we argue that the structure of these systems as interacting components is a blessing which forces software engineers towards compositional techniques which offer the best hope for constructing scalable and evolvable systems in an incremental manner. we offer some guidance and recommendations as to the approaches which seem most appropriate, particularly in languages for distributed programming, specification and analysis techniques for modelling and distributed paradigms for guiding design
exoskeletal software. the author advocates the use of a separate and explicit structural language to describe software architectures. the structural nature makes it amenable to both textual and graphical description. since it is a language, it can be used to support general descriptions and to provide the framework for checking interconnections. in addition, it can be used to generate and manage the system itself. this approach, initially under the guise of simple &ldquo;module interconnection languages&rdquo; (mil) and subsequently as &ldquo;configuration languages&rdquo;, provides generalised support for a wide variety of component and interaction types. generic (skeleton) architectures provide the means for reusing structures with different constituent components. dynamic constructs support explicit extension while constraining the potential structures of the system to those expressed as valid. further, change can be supported at the architectural level, either offline on the design or code, or dynamically on the system itself. system structure (architecture), separately and explicitly described, should be recognised as the unifying framework upon which to hang specification, design, construction and evolution of systems
the role of abstraction in software engineering. this workshop explores the concept of abstraction in software engineering at the individual, team and organization level. the aim is to explore the role of abstraction in dealing with complexity in the software engineering process, to discuss how the use of different levels of abstraction may facilitate performance of different activities, and to examine whether or not abstraction skills can be taught.
the specification and testing of quantified progress properties in distributed systems. there are two basic parts to the behavioral specification of distributed systems: safety and progress. in earlier work, we developed a tool to monitor progress properties of corba components specified using the temporal operator transient. in this paper, we address the specification and testing of transient properties that are quantified (over both bounded and unbounded domains). we categorize typical quantifications that arise in practical systems and discuss possible implementation strategies. we define functional transience, a subclass of quantified transient properties that can be monitored in constant space and time. we outline the design and implementation of a tool for testing these properties in corba components.
on the inference of configuration structures from source code. we apply mathematical concept analysis to the problem of inferring configuration structures from existing source code. concept analysis has been developed by german mathematicians over the last years; it can be seen as a discrete analogon to fourier analysis. based on this theory, our tool will accept source code, where configuration-specific statements are controlled by the preprocessor. the algorithm will compute a so-called concept lattice, which - when visually displayed - allows remarkable insight into the structure and properties of possible configurations. the lattice not only displays fine-grained dependencies between configuration threads, but also visualizes the overall quality of configuration structures according to software engineering principles. the paper presents a short introduction to concept analysis, as well as experimental results on various programs
global software development for the practitioner. this international workshop on global software development for the practitioner (gsd2006) was held in conjunction with the 28th international conference on software engineering (icse 2006) on may 23rd, 2006 in shanghai, china. the workshop was motivated by the industry trend towards developing software in globally distributed settings: geographically distributed teams, or outsourcing parts of the software development to other organizations in other parts of the world. topics presented and discussed in the workshop focused on grounded, practical strategies and techniques that address the geographic, temporal, organizational, and cultural boundaries inherent in global software projects.
tutorial: describing software architecture with uml. the presence of a solid architectural vision is a key discriminator in the success or failure of a software project. this tutorial examines what software architecture is and what it is not. it discusses and illustrates how to describe architecture through a set of design viewpoints and views and how to express these views in the uml, in the spirit of the new ieee standard 1471:2000:recommended practice for architectural description. the tutorial shows of how architectures drive the development process and how to capture architectural design patterns using the uml. it is illustrated by several widely applicable architectural patterns in different domain.
efficient exploration of service-oriented architectures using aspects. an important step in the development of large-scale distributed, reactive systems is the design of architectures that effectively support the systems' purposes. early prototypes help to decide upon the most effective architecture for a given situation. questions to answer include the boundaries of components, communication topologies and of replication. it is desirable to evaluate and compare architectures for functionality and quality attributes before implementing or changing the whole system. often, the effort required is prohibitive. in this paper we present an approach to efficiently create prototypes for service-oriented architectures using aspect-oriented programming techniques. we explain a procedure for transforming interaction based software specifications into aspectj programs. we show how to map the same set of interaction scenarios to different candidate architectures. this significantly reduces the effort required to explore architectural alternatives. we explain and evaluate our approach using the center tracon automation system as a running example.
understanding metamodeling. metamodeling not only directly underpins the specification of modeling languages such as the uml, but is also the foundation for making the omg's mda vision come true. this tutorial starts by motivating metamodeling as an advanced way of creating software and then goes on to explore its fundamental principles. in particular, important new metamodeling concepts such as the distinction between ontological and linguistic instance-of relationships, the unification of class and object facets and deep instantiation are introduced. a metamodeling framework suitable for mda is constructed step-by-step and then used to explain and critique the omg's various metamodeling technologies. this information furnishes modelers with the heuristics they need to more effectively utilize omg metamodeling technology and to know when metamodeling concepts are suitable and when they are not. the tutorial ends with some methodological advice on how to model in the presence of more than two modeling levels (objects & classes).
improved updating in relational dat base systems by deuter-shere algorithms. the need to ease the user's handling of data banks concerning natural insertions and deletions, requires more data independencies. a fundamental trend to 'normalize' relations in first and second normal forms has been indicated by codd and kent. when it comes to the third normal form, obscurities are spreading. this touches the very moment, when adequate content relations of programming morphologies to content realities are missing. as chamberlin, gray and traiger pointed out, a so called 'rectangle of a base relation' aids to clarify natural function dependencies. these indications have been further developed and advanced to a level, where each tuple and entity is subdivided into six deuter-criteria: 1. identity, 2. age, 3. association, 4. frequency, 5. significance and 6. truth. the validity of each criterion is related to all potential components within a relational data base. the metric data of each deuter criterion can be derived by analytical methods within three- and four dimensional realities in the model of a deuter-sphere. this leads to fundamental insertion- and deletion rules and an improved updating.
a form-based approach to human engineering methodologies. experience in the development and maintenance of software leads to the design of methodologies for different phases of the software engineering process. such methodologies attempt to usefully support the programmer's thought process for re-creating only good, standard patterns of programming without limiting creativity. however methodologies, as they are generally used, are limited in their impact on software quality. in this paper we present an approach for human engineering methodologies based on forms. the advantages of using a form-based interface for a software engineering environment are discussed by focusing on the design of forms, on the impact of forms on the software engineering process, and on the improved tool support facilitated by the standardization achieved by forms.
function point measurement from java programs. function point analysis (fpa) was proposed to help measure the functionality of software systems. it is used to estimate the effort required for the software development. however, it has been reported that since function point measurement involves judgment on the part of the measurer, differences for the same product may occur even in the same organization. also, if an organization tries to introduce fpa, fp will have to be measured from the past software developed there, and this measurement is cost-consuming. in this paper, we intend to examine the possibility to measure fp from source code automatically. at first, we propose measurement rules to count data and transactional functions for object-oriented program based on ifpug method and develop the function point measurement tool. then, we have applied the tool to practical java programs in a computer company and examined the difference between the fp values obtained by the tool and those of an fp measurement specialist. as the results, the number of data and transactional functions extracted by the tool is similar to ones by the specialist though for the classification of each function there is some difference between them.
requirements engineering for product families. in search for improved software quality and high productivity, software reuse has become a key research area. one of the most promising reuse approaches is product families. however, current practices in requirements engineering do not support product families. this paper describes a definition hierarchy method for requirements capturing, structuring, analysis and documentation. this method helps to identify architectural drivers of the product family and shows how different products in the family vary.
efficient authoring of software documentation using rapid7. this paper presents a method, developed in nokia, for efficient document authoring in software development projects. the method is called rapid7 (rapid production of documentation, 7 steps). the method improves traditional approach for document authoring in which work is typically started by informal initiative, and the actual writing of a document is a task performed by a single individual. traditional document authoring usually relies on inspections to verify the quality of the documentation. rapid7 addresses the document authoring problem by getting people involved in the documentation work earlier as a team in order to guarantee quality, calendar time efficiency, commitment and improved communication. this paper also compares rapid7 with some other similar approaches and presents results from a large-scale experiment with rapid7.
maintaining mental models: a study of developer work habits. to understand developers' typical tools, activities, and practices and their satisfaction with each, we conducted two surveys and eleven interviews. we found that many problems arose because developers were forced to invest great effort recovering implicit knowledge by exploring code and interrupting teammates and this knowledge was only saved in their memory. contrary to expectations that email and im prevent expensive task switches caused by face-to-face interruptions, we found that face-to-face communication enjoys many advantages. contrary to expectations that documentation makes understanding design rationale easy, we found that current design documents are inadequate. contrary to expectations that code duplication involves the copy and paste of code snippets, developers reported several types of duplication. we use data to characterize these and other problems and draw implications for the design of tools for their solution.
testing levels for object-oriented software. one of the characteristics of object-oriented software is the complex dependency that may exist between classes due to inheritance, association and aggregation relationships. hence, where to start testing and how to define an integration strategy are issues that require further investigation. this paper presents an approach to define a test order by exploiting a model produced during design stages (e.g., using omt, uml), namely the class diagram. our goal is to minimize the number of stubs to be constructed in order to decrease the cost of testing. this is done by testing a class after the classes it depends on. the novelty of the test order lies in the fact that it takes account of: (i) dynamic (polymorphism) dependencies; (ii) abstract classes that cannot be instantiated, making some testing levels infeasible. the test order is represented by a graph showing which testing levels must be done in sequence and which ones may be done independently. it also provides information about the classes involved in each level and how they are involved (e.g., instantiation or not). the approach is implemented in a tool called toons (testing level generator for object-oriented software). it is applied to an industrial case study from the avionics domain.
specification of time dependencies and synthesis of concurrent processes. there is a need to incorporate reasoning about time dependencies into program synthesis systems. such dependencies have often been phrased in terms of temporal logic systems. we present an alternative method of specifying time dependencies, in a calculus of binary relations between time intervals [lad86.1, lad86.2]. we show how the interval calculus may be used to give very-high-level specifications of concurrent process protocols, and how these specifications may be automatically refined using interval calculus into a target specification language. we indicate how the target language may be executed, under certain sequencing assumptions.
explicit assumptions enrich architectural models. design for change is a well-known adagium in software engineering. we separate concerns, employ well-designed interfaces, and the like to ease evolution of the systems we build. we model and build in changeability through parameterization and variability points (as in product lines). these all concern places where we explicitly consider variability in our systems. we conjecture that it is helpful to also think of and explicitly model invariability, things in our systems and their environment that we assume will not change. we give examples from the literature and our own experience to illustrate how evolution can be seriously hampered because of tacit assumptions made. in particular, we show how we can explicitly model assumptions in an existing product family. from this, we derive a metamodel to document assumptions. finally, we show how this type of modeling adds to our understanding of the architecture and the decisions that led to it.
generalizing perspective-based inspection to handle object-oriented development artifacts. the value of software inspection for uncovering defects early in the development lifecycle has been well documented. of the various types of inspection methods published to date, experiments have shown perspective-based inspection to be one of the most effective, because of its enhanced coverage of the defect space. however, inspections in general, and perspective-based inspections in particular, have so far been applied predominantly in the context of conventional structured development methods, and then almost always to textual artifacts, such as requirements documents or code modules. object-oriented models, particularly of the graphical form, have so far not been adequately addressed by inspection methods. this paper tackles this problem by first discussing the difficulties involved in tailoring the perspective-based inspection approach to object-oriented development methods and, second, by presenting a generalization of the approach which overcomes these limitations. the new version of the approach is illustrated in the context of uml-based object-oriented development.
rule-based approach to computing module cohesion. stevens, myers, and constantine introduced the notion of cohesion, an ordinal scale of seven levels that describes the degree to which the actions performed by a module contribute to a unified function (1974). they provided rules, termed as associative principles to examine the relationships between processing elements of a module and designate a cohesion level to it. stevens et al., however, did not give a precise definition for the term processing element. the author interprets the output variables of a module as its processing elements. stevens et al.'s associative principles are transformed to relate the output variables based on their data and control dependence relationships. what results is a rule-based approach to computing cohesion. experimental results show that, but for temporal cohesion, the cohesion associated to a module under this reinterpretation and that due to the original definitions are identical for all examples
requirements engineering in the year 00: a research perspective. requirements engineering (re) is concerned with the identification of the goals to be achieved by the envisioned system, the operationalization of such goals into services and constraints, and the assignment of responsibilities for the resulting requirements to agents such as humans, devices, and software. the processes involved in re include domain analysis, elicitation, specification, assessment, negotiation, documentation, and evolution. getting high-quality requirements is difficult and critical. recent surveys have confirmed the growing recognition of re as an area of utmost importance in software engineering research and practice.the paper presents a brief history of the main concepts and techniques developed to date to support the re task, with a special focus on modeling as a common denominator to all re processes. the initial description of a complex safety-critical system is used to illustrate a number of current research trends in re-specific areas such as goal-oriented requirements elaboration, conflict management, and the handling of abnormal agent behaviors. opportunities for goal-based architecture derivation are also discussed together with research directions to let the field move towards more disciplined habits.
goal-oriented requirements engineering: from system objectives to uml models to precise software specifications. this tutorial presents a comprehensive overview of state-of-the-art techniques for eliciting, modeling, specifying, analyzing and documenting high-quality system requirements.
elaborating security requirements by construction of intentional anti-models. caring for security at requirements engineering time is amessage that has finally received some attention recently.however, it is not yet very clear how to achieve thissystematically through the various stages of therequirements engineering process.the paper presents a constructive approach to themodeling, specification and analysis of application-specificsecurity requirements. the method is based on agoal-oriented framework for generating and resolvingobstacles to goal satisfaction. the extended frameworkaddresses malicious obstacles (called anti-goals) set up byattackers to threaten security goals. threat trees are builtsystematically through anti-goal refinement until leafnodes are derived that are either software vulnerabilitiesobservable by the attacker or anti-requirementsimplementable by this attacker. new security requirementsare then obtained as countermeasures by application ofthreat resolution operators to the specification of the anti-requirementsand vulnerabilities revealed by the analysis.the paper also introduces formal epistemic specificationconstructs and patterns that may be used to support aformal derivation and analysis process. the method isillustrated on a web-based banking system for whichsubtle attacks have been reported recently.
improving the quality of uml models in practice. the importance of uml models in software engineering is increasing. inherent to the uml is its lack of a formal semantics, its risk for inconsistency and completeness defects and the absence of modeling norms. these properties are sources for poor model quality and defects. to find out to which extent defects occur and what types of defects occur in practice we empirically investigate the state-of-the-practice of quality in uml models using a practitioners survey and a series of industrial case studies. additionally we analyze the effects of defects in uml models experimentally. based on this experiment we present an objective classification of uml defects which allows for prioritizing defects and thus allocate resources for defect removal. we aim at building a rule-set, metrics and visualization techniques to improve the quality of uml models during development. we propose a quality model that is specific for uml models. finally, we propose modeling conventions, similar to coding conventions, to prevent for defects and to assure uniformity of modeling within an organization. we aim at empirically validating our techniques to provide pragmatic technology that can be transferred to industrial practice.
effects of defects in uml models: an experimental investigation. the unified modeling language (uml) is the de facto standard for designing and architecting software systems. uml offers a large number of diagram types that can be used with varying degree of rigour. as a result uml models may contain consistency defects. previous research has shown that industrial uml models that are used as basis for implementation and maintenance contain large numbers of defects. this study investigates to what extent implementers detect defects and to what extent defects cause different interpretations by different readers. we performed two controlled experiments with a large group of students (111) and a group of industrial practitioners (48). the experiment's results show that defects often remain undetected and cause misinterpretations. we present a classification of defect types based on a ranking of detection rate and risk for misinterpretation. additionally we observed effects of using domain knowledge to compensate defects. the results are generalizable to industrial uml users and can be used for improving quality assurance techniques for uml-based development.
codecrawler: an information visualization tool for program comprehension. codecrawler (in the remainder of the text cc) is a language independent, interactive, information visualization tool. it is mainly targeted at visualizing object-oriented software, and has been successfully validated in several industrial case studies over the past few years. cc adheres to lightweight principles: it implements and visualizes polymetric views, visualizations of software enriched with information such as software metrics and other source code semantics. cc is built on top of moose, an extensible language independent reengineering environment that implements the famix metamodel. in its last implementation, cc has become a general-purpose information visualization tool.
tutorial: mastering design patterns. this tutorial is an introduction to design patterns used in the design of object-oriented software applications.
slicing object-oriented software. describes the construction of system dependence graphs for object-oriented software on which efficient slicing algorithms can be applied. we construct these system dependence graphs for individual classes, groups of interacting classes and complete object-oriented programs. for an incomplete system consisting of a single class or a number of interacting classes, we construct a procedure dependence graph that simulates all possible calls to public methods in the class. for a complete system, we construct a procedure dependence graph from the main program in the system. using these system dependence graphs, we show how to compute slices for individual classes, groups of interacting classes and complete programs. one advantage of our approach is that the system dependence graphs can be constructed incrementally because representations of classes can be reused. another advantage of our approach is that slices can be computed for incomplete object-oriented programs such as classes or class libraries. we present our results for c++, but our techniques can be applied to other statically typed object-oriented languages such as ada-95.
module structure in an evolving family of real time systems. the problems of maintaining a large number of customized software systems are discussed. module structuring techniques developed at bell-northern research and used in the development of the northern telecom dms 100 family of telephone switching equipment are described. application of these techniques simplifies the evolution of the system to handle new features.
dynamic mutation testing in integrated regression analysis. a new method of integrated regression analysis is proposed. its core is the clustering, a method for automatic identification of program modifications. clustering is used to formulate a hypothesis about the existence of a fault in the modified program, and to guide the process of testing this hypothesis. it is postulated that static and dynamic program analysis be used for that purpose. specifically, the authors introduce dynamic mutation testing (dmt), an experimental technique for testing the fault hypothesis. dmt estimates the sensitivity of the test-induced program state to reveal the postulated fault in the modified program. if all tests pass and are found to have a high sensitivity, the fault hypothesis can be rejected at a high level of confidence
the impact of mesa on system design. the mesa programming language supports program modularity in ways that permit subsystems to be developed separately but to be bound together with complete type safety. separate and explicit interface definitions provide an effective means of communication, both between programs and between programmers. a configuration language describes the organization of a system and controls the scopes of interfaces. these facilities have had a profound impact on the way we design systems and organize development projects. this paper reports our recent experience with mesa, particularly its use in the development of an operating system. it illustrates techniques for designing interfaces, for using the interface language as a specification language, and for organizing a system to achieve the practical benefits of program modularity without sacrificing strict type-checking.
automated support for process-aware definition and execution of measurement plans. some of the problems with process measurement are generally due to the fact that the definition of measurement plans does not rely on a reference model of the development process that can drive and explain the measuring activities. one of the most popular methodologies addressing the definition of process measurement plans is the gqm (goal/question/metrics). this paper discusses how to support the creation of gqm plans by means of an explicit model of the process being measured. such a model guides the gqm process, and makes it possible to define precisely -if not formally- the metrics involved. a tool supporting the proposed method is also illustrated.
a constructive approach to reliable synchronization code. this paper describes a new approach to developing reliable software for communication between parallel processes. the basis of this approach is the shared use of abstract data objects, and the separation of synchronization-related software from the software performing the actual data access. the paper presents a language in which synchronization behavior for abstract data objects can be specified independently of other kinds of behavior. specifications written in this language can be used as a basis for constructing the required synchronization software automatically. also discussed is the use of such specifications in verifying properties of programs which make use of the abstract objects for interprocess communication.
whole program path-based dynamic impact analysis. impact analysis, determining when a change in one part of a program affects other parts of the program, is time-consuming and problematic. impact analysis is rarely used to predict the effects of a change, leaving maintainers to deal with consequences rather than working to a plan. previous approaches to impact analysis involving analysis of call graphs, and static and dynamic slicing, exhibit several tradeoffs involving computational expense, precision, and safety, require access to source code, and require a relatively large amount of effort to re-apply as software evolves. this paper presents a new technique for impact analysis based on whole path profiling, that provides a different set of cost-benefits tradeoffs -- a set which can potentially be beneficial for an important class of predictive impact analysis tasks. the paper presents the results of experiments that show that the technique can predict impact sets that are more accurate than those computed by call graph analysis, and more precise (relative to the behavior expressed in a program's profile) than those computed by static slicing.
an examination of evolution dynamics. data on the history of seven systems was analysed to statistically test the 5 laws of software evolution proposed first by belady and lehman in 1976. while there was some evidence supporting laws 1 and 2, laws 3-5 were not supported by the data. in the light of the result a new discontinuous model of software evolution is proposed to replace the smoothly changing continuous model proposed by lehman.
using kids as a tool support for vdm. kids/vdm is an experimental environment that supports the synthesis of executable prototypes from vdm specifications. the development proceeds as a series of correctness preserving transformations under the strict control of the tool. a by-product of this development is the proof of consistency properties of the original specification. experiments with the tool have shown its ability to handle independently written specifications. it also revealed useful to detect errors in specifications. the environment is based on, technologies of the kestrel institute development system, including the refine and regroup languages, the design and optimization tactics, and the theorem prover.
application of clustering to estimate missing data and improve data integrity. two problems in the use of computerized data base systems are: (1) how can we estimate the values for missing data? (2) how can we improve data integrity, that is, reduce the number of errors in the data? the tool that we introduce to attack these problems is clustering analysis. experimental results indicate that our method is feasible. our algorithm detected an error in the book &ldquo;weyer's warships of the world 1969.&rdquo; each of the approximately 2000 warships listed in the book has 18 variables associated with it. it would be difficult for a person to find errors in the book. our methods do not require any a priori knowledge about the data, for example, about warships.
process models, process programs, programming support. one way of responding to a keynote speaker is to put the expressed views into context, pointing to highlights in the address, suggesting areas where alternative viewpoints might have been presented, exposing any chinks in the armour of the otherwise solid structure erected by the speaker.logistics have made it impossible for this respondent to see the paper to be presented to icse9 by professor l osterweil before generating his own written response,. the above approach cannot, therefore, be taken. instead, i raise a fundamental issue that follows from a comparison of the respective approaches to process modelling taken by osterweil and myself. what is expressed here reflects my current understanding of his views on process programs and process programming, my reaction to what i believe he will present. i can only hope that this will not do too much violence to views to be expressed in his proceedings paper or in the keynote lecture itself.to set the scene and to provide a basis and framework for discussion, let me first summarize my view of studies of the software development process in terms of my own involvement in them.f to the best of my knowledge, the first such study was a 1956 paper by benington [ben56]. in this, a process model with basic characteristics of that subsequently termed the 'waterfall model', was first presented. current interest in the software development process makes it most appropriate that this historic paper is to re-presented at this conference. in 1968/9, totally unaware of the earlier paper, i engaged in a study whose conclusions were presented in a confidential report entitled 'the programming process' [leh69]. this has now become available in the open literature [leh85, chapter 3] and is, i believe, as relevant today as at the time it was written. it was this study and the continuing research it triggered that subsequently led my colleagues and me to the concepts of process models, evolution dynamics, program evolution and support environments.our earliest process models reflected the dynamics of the process [leh85, chs. 5-9, 14, 16, 19]. by the mid 70's, at about the time that barry boehm [boe76] popularized the waterfall model first proposed by royce [roy70], my studies had led to a search for better understanding of the total process of software development. this total process was seen as extending from initial verbalization of the problem to be solved or computer application to be implemented, through delivery of the product and over its subsequent evolution. the search was expressed through the development and refinement of a sequence of process models [leh85 chs. 3, 7, 14, 20, 21, 2]. it was directed towards first formulating a model of an ideal process ('ideal' though unachievable in the sense of the 'ideal' cycle of thermodynamics). such a model would constitute a general paradigm. a practical process would be obtained by instantiation in terms of relevant concepts, available technologies, specific implementation environments, process constraints and so on. this development of process models culminated in the lst model [leh84] and its subsequent analysis and application as presented at the first two process workshops [spw84, 86]. the importance of that model is not only in the process it depicts. it is a canonical model of software development and of development steps.what has all this to do with process programs? process programs, as described by osterweil, are also process models. they are models constructed from linguistic elements expressed and structured in programmatic form. they are intended to define a procedure for achieving some desired end from an initial starting point and are expressed in terms of expressions in a natural or formal language. the procedure is implemented by executing the primitive actions named in the program. a process program to describe a process that, if followed, will permit execution of some specific task in its environment, can be systematically developed, top-down, in a manner equivalent to top-down development of a procedural program. the osterweil approach is essentially equivalent, in the context of process modelling, to the use of procedural programming (in contrast to styles such as functional, imperative and so on). its power is defined by the properties of the language used in relation to available execution mechanisms. in fact, a process program is precisely that - a procedural program whose value depends on the constructability of a mechanism that can execute it mechanically, human intervention being restricted primarily to the provision of information. this is a view that osterweil will not dispute; in the papers that i have seen the algorithmic nature of process programs is repeatedly stressed.and therein lies the rub. the approach is fine, almost certainly useful, when comprehensive models of the phenomenon, the domain and the system that are the subject of the program are known and understood, when strategies and algorithms for achieving the desired ends are known a priori, when computational, managerial and administrative practices are fully defined. it is useless, indeed meaningless, if such phenomenological and algorithmic models do not exist [tur86], if progress in definition (and execution) of the process is a function of the process itself.
software architectures for dependable systems: a software engineering perspective. although there is a large body of research in dependability, architectural level reasoning about dependability is only just emerging as an important theme in software development. this is due to the fact that dependability concerns are often left until too late in the process of development. in addition, the complexity of emerging applications and the trend of building trustworthy systems from existing untrustworthy components are urging dependability concerns to be considered at the architectural level. this tutorial will present the current challenges and promising solutions for structuring dependable systems at the architectural level. in addition of providing basic concepts related to dependability and software architectures, the rest of the tutorial is presented in the context of the dependability technologies. throughout the tutorial, case studies will be used to exemplify the key concepts.
icse 2002 workshop on architecting dependable systems. this summary gives a brief overview of a one-day workshop on architecting dependable systems (wads) held in conjunction with icse 2004. it was organised as a twin workshop with a workshop held in conjunction with the international conference on dependable systems and network (dsn 2004).
program evolution and its impact on software engineering. large scale, widely used programs such as operating systems are never complete. they undergo a continuing evolutionary cycle of maintenance, augmentation and restructuring to keep pace with evolving usage and implementation technologies. the paper provides quantitative evidence, from widely different environments, of the existence and nature of this evolutionary process. interpretations and possible significance of some of the observed phenomena are discussed. some implications for software engineering and for project planners and managers are noted.
icse 2003 workshop on software architectures for dependable systems. this workshop summary gives a brief overview of a one-day workshop on "software architectures for dependable systems" held in conjunction with icse 2003.
twin workshops on architecting dependable systems (wads 2004). this workshop summary gives a brief overview onthe workshop on "architecting dependable systems"held in conjunction with icse 2004. it is organisedas a twin workshop to another to be held inconjunction with the international conference ondependable systems and network (dsn 2004). thisis an ambitious project that aims to promote cross-fertilizationbetween the communities of softwarearchitectures and dependability. both communitieswill benefit from the clarification of approaches thathave been previously tried and succeeded, as well asthose that have been tried but have not yet shown tobe successful.
workshop on architecting dependable systems (wads 2005). this workshop summary gives a brief overview of the workshop on "architecting dependable systems" held in conjunction with the icse 2005. the main aim of this workshop is to promote cross-fertilization between the software architecture and dependability communities. we believe that both of them will benefit from clarifying approaches that have been previously tested and have succeeded as well as those that have been tried but have not yet been shown to be successful.
tutorial on fundamental concepts for practical software architecture. architecture of software is a collection of design decisions that are expensive to change. how to identify which design decisions are expensive to change? what are architecture views and which views are needed to adequately describe the architecture of a specific system? how to create and manage software architecture for a product family? this tutorial offers answers to these and other questions that arise in the context of complex software development. we introduce a system of concepts useful in order to understand, design, and evaluate architecture of software intensive systems and system families. our approach utilizes different software structures in order to control important system qualities related to its development, performance, and evolution. we draw our experience primarily from software embedded in voice and data communication systems. however the same principles can be applied to software architecture in other domains. this tutorial should be useful to engineers and technical managers involved in construction or evaluation of complex software.
the icse2000 doctoral workshop. doctoral research in software engineering is a major source of new ideas and of key importance in training scientists for the information technology community. the rapid evolution of information technology is challenging the relevance of doctoral programs in software engineering. these are facing the risk of losing their leading role in training scientists and engineers. many universities are threaten by a decreasing number of applications and an increasing number of drop outs. a major goal of the icse doctoral workshop, at the turn of the millennium, is to promote doctoral study and provide help and encouragement to those engaged in it. consequently, the icse2000 doctoral workshop not only provides a forum for graduate students to present and discuss their dissertation research, it also provides (together with a panel session in the main conference) an opportunity to discuss the role of doctoral research in the new information society. an opening talk by lee osterweil is intended to give participants a clear view of both the goal of doctoral research and the methodology with which it is carried out. the presentation of doctoral plans and the open discussion between the committee and the invited students is a unique opportunity to compare phd programs in different institutions and in different countries. the summary panel scheduled as part of the conference program is designed to open the discussion between the academic and the industrial communities on the role that doctoral research plays in the development and evolution of software engineering.
an empirical evaluation of test case filtering techniques based on exercising complex information flows. some software defects trigger failures only when certain complex information flows occur within the software. profiling and analyzing such flows therefore provides a potentially important basis for filtering test cases. we report the results of an empirical evaluation of several test case filtering techniques that are based on exercising complex information flows. both coverage-based and profile-distribution-based filtering techniques are considered. they are compared to filtering techniques based on exercising basic blocks, branches, function calls, and def-use pairs, with respect to their effectiveness for revealing defects.
graphical animation of behavior models. graphical animation is a way of visualizing the behavior of design models. this visualization is of use in validating a design model against informally specified requirements and in interpreting the meaning and significance of analysis results in relation to the problem domain. in this paper we describe how behavior models specified by labeled transition systems (lts) can drive graphical animations. the semantic framework for the approach is based on timed automata. animations are described by an xml document that is used to generate a set of javabeans. the elaborated javabeans perform the animation actions as directed by the lts model.
multivariate visualization in observation-based testing. we explore the use of multivariate visualization techniques to support a new approach to test data selection, called observation-based testing. applications of multivariate visualization are described, including: evaluating and improving synthetic tests; filtering regression test suites; filtering captured operational executions; comparing test suites; and assessing bug reports. these applications are illustrated by the use of correspondence analysis to analyze test inputs for the gnu gcc compiler.
blending object-z and timed csp: an introduction to tcoz. object-z is an extension to the z language designed to facilitate specification in an object-oriented style. it is an excellent tool for modeling data and algorithms, but its object semantics are single threaded and operations are atomic. therefore, it is difficult to use object-z to capture the behaviour of concurrent real-time reactive systems. on the other hand, timed csp is good at modeling real-time concurrent behaviour, but has little support for modeling the state of a complex system. this paper introduces a blending of object-z and timed csp, known as tcoz. the blended notation is particularly suited for specifying complex systems whose components have their own thread of control
automated generation of test programs from closed specifications of classes and test cases. most research on automated specification-based softwaretesting has focused on the automated generation oftest cases. before a software system can be tested, it must beset up according to the input requirements of the test cases.this setup process is usually performed manually, especiallywhen testing complex data structures and databases.after the system is properly set up, a test execution tool runsthe system according to the test cases and pre-recorded testscripts to obtain the outputs, which are evaluated by a testevaluation tool.this paper complements the current research on automatedspecification-based testing by proposing a schemethat combines the setup process, test execution, and test validationinto a single test program for testing the behavior ofobject-oriented classes. the test program can be generatedautomatically given the the desired test cases and closedspecifications of the classes. with closed specifications, everyclass method is defined in terms of other methods whichare, in turn, defined in their own class specifications. thecore of the test program generator is a partial-order plannerwhich plans the sequence of instructions required in thetest program. the planner is, in turn, implemented as a tree-searchalgorithm. it makes function calls to the omega calculatorlibrary, which solves the constraints given in thetest cases. a first-cut implementation of the planner hasbeen completed, which is able to handle simple arithmeticsand existential quantifications in the class specifications. asoundness and completeness proof sketch of the planner isalso provided in this paper.
on what exactly is going on when software is developed step-by-step. in this paper we present a (necessarily) informal and brief description of formal concepts which lend mathematical support to a paradigm of software development. some important obligations which must be met by the software developers are pointed out. correspondences between widely adhered to practices and their mathematical counterparts are identified and explained.
a case study in root cause defect analysis. there are three interdependent factors that drive our software development processes: interval, quality and cost. as market pressures continue to demand new features ever more rapidly, the challenge is to meet those demands while increasing, or at least not sacrificing, quality. one advantage of defect prevention as an upstream quality improvement practice is the beneficial effect it can have on interval: higher quality early in the process results in fewer defects to be found and repaired in the later parts of the process, thus causing an indirect interval reduction.we report a retrospective root cause defect analysis study of the defect modification requests (mrs) discovered while building, testing, and deploying a release of a transmission network element product. we subsequently introduced this analysis methodology into new development projects as an in-process measurement collection requirement for each major defect mr.we present the experimental design of our case study discussing the novel approach we have taken to defect and root cause classification and the mechanisms we have used for randomly selecting the mrs to analyze and collecting the analyses via a web interface. we then present the results of our analyses of the mrs and describe the defects and root causes that we found, and delineate the countermeasures created to either prevent those defects and their root causes or detect them at the earliest possible point in the development process.we conclude with lessons learned from the case study and resulting ongoing improvement activities.
developing use cases and scenarios in the requirements process. scenarios are often used for discovering requirements using established techniques, but how such scenarios are initially developed is not so well understood. this experience paper reports the application of one scenario-based approach - rescue - to discover requirements for dman, an air traffic management system for the uk's national air traffic services. a retrospective analysis of the dman use cases, scenarios and requirements artifacts revealed the importance of diverse information sources in the specification of use cases that enabled systematic requirements discovery. results were used to explore 3 research questions that arose in previous studies. the paper reports lessons from this experience and offers guidelines that practitioners can apply in their requirements processes and academics can use to inform their research.
monitoring and control in scenario-based requirements analysis. scenarios are an effective means for eliciting, validating and documenting requirements. at the requirements level, scenarios describe sequences of interactions between the software-to-be and agents in the environment. interactions correspond to the occurrence of an event that is controlled by one agent and monitored by another.this paper presents a technique to analyse requirements-level scenarios for unforeseen, potentially harmful, consequences. our aim is to perform analysis early in system development, where it is highly cost-effective. the approach recognises the importance of monitoring and control issues and extends existing work on implied scenarios accordingly. these so-called input-output implied scenarios expose problematic behaviours in scenario descriptions that cannot be detected using standard implied scenarios. validation of these implied scenarios supports requirements elaboration. we demonstrate the relevance of input-output implied scenarios using a number of examples.
creative requirements: invention and its role in requirements engineering. requirements is too often seen as a "stenographer's task", one where the requirements engineer passively listens and records while the stakeholders state their needs. however, this approach relies on stakeholders knowing what they need, and what they want. experience tells us that except for rare visionaries, people do not know what they want until they see it. many of the useful products that we take for granted today, did not come about from the stakeholders' imagination, but from an invention. in this tutorial we explain and illustrate how to use creative techniques to invent requirements that result in more useful, usable and competitive products. we provide a guide for invention, and show participants how to use this guide to invent innovative requirements for a familiar system.
agent-based tactics for goal-oriented requirements elaboration. goal orientation is an increasingly recognized paradigm for eliciting, structuring, analyzing and documenting system requirements. goals are statements of intent ranging from high-level, strategic concerns to low-level, technical requirements on the software-to-be and assumptions on its environment. achieving goals require the cooperation of agents such as software components, input/output devices and human agents. the assignment of responsibilities for goals to agents is a critical decision in the requirements engineering process as alternative agent assignments define alternative system proposals.the paper describes a systematic technique to support the process of refining goals, identifying agents, and exploring alternative responsibility assignments. the underlying principles are to refine goals until they are assignable to single agents, and to assign a goal to an agent only if the agent can realize the goal.there are various reasons why a goal may not be realizable by an agent, e.g., the goal may refer to variables that are not monitorable or controllable by the agent. the notion of goal realizability is first defined on formal grounds; it provides a basis for identifying a complete taxonomy of realizability problems. from this taxonomy we systematically derive a catalog of tactics for refining goals and identifying agents so as to resolve realizability problems. each tactics corresponds to the application of a formal refinement pattern that relieves the specifier from verifying the correctness of refinements in temporal logic.our techniques have been used in two case studies of significant size; excerpts are shown to illustrate the main ideas.
precise modeling of design patterns in uml. prior research attempts to formalize the structure ofobject-oriented design patterns for a more precisespecification of design patterns. it also allows automationsupport to be developed for user-defined design patternsin the future case tools. targeting to a particular type ofautomation (e.g. verification of pattern instances),previous specification approaches over-specify patternstructures to a certain extend. over-specification makespattern specification ambiguous and disallows thespecification language to be used for specifyingcompound patterns. in this paper, we present thestructural properties of design patterns which reveal thetrue abstract nature of pattern structures. to supportthese properties so as to solve the over-specificationproblem, we propose an extension to uml 1.5 (basicallyuml 1.4 with action semantics). the specialization andrefining mechanism of uml provides also a smoothsupport for the instantiation, refinement and integrationof pattern structures specified in uml. our work makesno significant extension to the uml 1.5 meta-model butmore in a uml profile approach to ease the migration ofour work to uml 2.0, which has not yet officiallyreleased by omg during this work.
high-pressure steam engines and computer software. the introduction of computers into the control of potentially dangerous devices has led to a growing awareness of the possible contribution of software to serious accidents. the number of computer-related accidents so far has been small due to the restraint shown in introducing computers into safety-critical control loops. however, as the economic and technological benefits of using computers become more widely accepted, their use is increasing dramatically. we need to ensure that computers are introduced into safety-critical systems in the most responsible way possible and at a speed that does not expose people to undue risk. risk induced by technological innovation existed long before computers; this is not the first time that humans have come up with an extremely useful new technology that is potentially dangerous. studying parallels in the early development of high-pressure steam engines and of software engineering can help.
decision table programming and reliability. the language in which programs are written influence their structure, style, reliability and verifiability. in this paper, we discuss the use of decision tables as a programming language, and related reliability questions. while both good and bad programs can be written in any language, it is suggested here that decision table programming is worth more serious consideration for general purpose computing.
mohca-java: a tool for c++ to java conversion support. as java increases in popularity and maturity, many people find it desirable to convert legacy c++ or c programs to java. our hypothesis is that a tool which performs rigorous analysis on a c++ program, providing detailed output on the changes necessary, will make conversion a much more efficient and reliable process. mohca-java is such a tool. it performs detailed analysis on a c++ abstract syntax tree; the parameters of the analysis can be specified and extended very quickly and easily using a rule-based language. we have found that mohca-java is very useful for identifying and implementing source code changes, and that its extensibility is a very important factor, specially to adapt the tool to assist in the conversion of c++ code that makes extensive use of libraries to java code that uses similar libraries.
beyond albe/p: language neutral form. albe/p is a language-based crt editor for pascal programs. the crt screen serves as a window through which a programmer can view and modify a &ldquo;pretty-printed&rdquo; picture of any part of a pascal program. the albe/p system differs from conventional screen-oriented text editors in that the program is stored as a pascal parse tree and the editing operations are designed specifically for the pascal language. moreover, because albe/p is language-based, it will not accept programs with local syntax errors (e.g., ill-formed expressions) or global errors (e.g., undeclared variables). the system is also an effective tool for developing and maintaining application systems and subroutine packages in multiple language environments. programs can be entered in language-neutral form (lnf), a pascal subset with language features common to c, pl/i, and algol. then, albe will generate a pascal program to be run and debugged under the host operating system. when program development is complete, albe/lnf will generate equivalent programs for the desired target languages and operating system environments. currently, albe/lnf supports pascal, c, and fortran under vax/vms.
an empirical study on decision making in off-the-shelf component-based development. component-based software development (cbsd) is becoming more and more important since it promotes reuse to higher levels of abstraction. as a consequence, many components are available being either open-source software (oss) or commercial-off-the-shelf (cots). however, it is still unclear how the decision for acquiring oss or cots components is made in practice. this paper describes an empirical study on why project decision-makers selected cots instead of oss components, or vice versa. the study was performed as an international survey in norway, italy and germany. it focused on decision making on using off-the-shelf (ots) components. we have gathered answers from 83 projects using only cots components and 44 projects using only oss components. results of this study show significant differences and commonalities of integrating oss or cots components. moreover, the study illustrates several research questions that warrant future research.
supporting program comprehension using semantic and structural information. the paper focuses on investigating the combined use of semantic and structural information of programs to support the comprehension tasks involved in the maintenance and reengineering of software systems. here, semantic refers to the domain specific issues (both problem and development domains) of a software system. the other dimension, structural, refers to issues such as the actual syntactic structure of the program along with the control and data flow that it represents. an advanced information retrieval method, latent semantic indexing, is used to define a semantic similarity measure between software components. components within a software system are then clustered together using this similarity measure. simple structural information (i.e., file organization) of the software system is then used to assess the semantic cohesion of the clusters and files, with respect to each other. the measures are formally defined for general application. a set of experiments is presented which demonstrates how these measures can assist in the understanding of a nontrivial software system, namely a version of ncsa mosaic.
a risk-driven method for extreme programming release planning. xp (extreme programming) has become popular for iid (iteration and increment development). it is suitable for small teams, lightweight projects and vague/volatile requirements. however, some challenges are left to developers when they desire to practise xp. a critical one of them is constructing the release plan and negotiating it with customers. in this paper, we propose a risk-driven method for xp release planning. it has been applied in a case study and the results show the method is feasible and effective. xp practicers can follow it to decide a suitable release plan and control the development process.
source viewer 3d (sv3d) - a framework for software visualization. source viewer 3d is a software visualization framework that uses a 3d metaphor to represent software system and analysis data. the 3d representation is based on the seesoft pixel metaphor. it extends the original metaphor by rendering the visualization in a 3d space. new, object-based manipulation methods and simultaneous alternative mappings are available to the user.
experiences and results from initiating field defect prediction and product test prioritization efforts at abb inc. quantitatively-based risk management can reduce the risks associated with field defects for both software producers and software consumers. in this paper, we report experiences and results from initiating risk-management activities at a large systems development organization. the initiated activities aim to improve product testing (system/integration testing), to improve maintenance resource allocation, and to plan for future process improvements. the experiences we report address practical issues not commonly addressed in research studies: how to select an appropriate modeling method for product testing prioritization and process improvement planning, how to evaluate accuracy of predictions across multiple releases in time, and how to conduct analysis with incomplete information. in addition, we report initial empirical results for two systems with 13 and 15 releases. we present prioritization of configurations to guide product testing, field defect predictions within the first year of deployment to aid maintenance resource allocation, and important predictors across both systems to guide process improvement planning. our results and experiences are steps towards quantitatively-based risk management.
a bayesian approach to diagram matching with application to architectural models. it system architectures, as well as other systems, are often described by formal models or informal diagrams. in practice, there are often a number of versions of a model, e.g. for different views of a system, divergent variants, or a series of revisions. understanding how versions of a model correspond or differ is crucial, yet little work has been done on automated assistance for matching models and diagrams.we have designed a framework based on bayesian methods for finding these correspondences automatically. we represent models and diagrams as graphs whose nodes have attributes such as name, type, connections, and containment relations, and we have developed probabilistic models for rating the quality of candidate correspondences based on various features of the nodes in the graphs. given the probabilistic models, we can find high quality correspondences using search algorithms. preliminary experiments focusing on architectural models suggest that the technique is promising.
light-weight context recovery for efficient and accurate program analyses. to compute accurate information efficiently for programs that use pointer variables, a program analysis must account for the fact that a procedure may access different sets of memory locations when the procedure is invoked under different callsites. this paper presents light-weight context recovery, a technique that can efficiently determine whether a memory location is accessed by a procedure under a specific callsite. the paper also presents a technique that uses this information to improve the precision and efficiency of program analyses. our empirical studies show that (1) light-weight context recovery can be quite precise in identifying the memory locations accessed by a procedure under a specific call-site and (2) distinguishing memory locations accessed by a procedure under different callsites can significantly improve the precision and the efficiency of program analyses on programs that use pointer variables.
breaking the ice for agile development of embedded software: an industry experience report. a software engineering department in a daimler-chrysler business unit was highly professional at developing embedded software for busses and coaches.however, customer specific add-ons were a regularsource of hassle. simple as they are, those individualrequirements have to be implemented in hours or daysrather than weeks or months. poor quality or late uploadinto the bus hardware would cause serious cost andoverhead. established software engineering methodswere considered inadequate and needed to be cut short.agile methods offer guidance when quality, flexibilityand high speed need to be reconciled. however, we didnot adopt any full agile method, but added single agilepractices to our "process improvement toolbox". wesuggested a number of classical process improvementactivities (such as more systematic documentation andmeasurement) and combined them with agile elements(e.g. test first process). this combination seemed tofoster acceptance of agile ideas and may help us to breakthe ice for a cautious extension of agile processimprovement.
software engineering provisioning process. the main theme of the 8th international conference on software engineering is the &ldquo;establishment of a better understanding of the software process and its improvement through the provision of better models, methods and tools.&rdquo; this paper addresses the second half of this theme by defining the issues involved with making strategic improvements to environments and suggesting a process for &ldquo;provisioning&rdquo; (or providing) better computer-aided software engineering methods and tools. the paper focuses primarily on the process for transforming existing, large to very large scale software development and support environments into conceptual &ldquo;software factories.&rdquo; to achieve this goal, arguments are made for strategically planning and developing well architected, modifiable software engineering environments. this is considered a prerequisite to effective &ldquo;provisioning&rdquo; of new and improved methods and tools. taken as a whole, the paper should be useful to software developers, tool providers and major software buyers alike. through typical environment evolution scenarios and concrete examples, many useful suggestions are provided to each of these players on how they can assist in the software engineering improvement process.
prototyping in industrial software projects - bridging the gap between theory and practice. prototyping, a method and technique frequently used in many engineering disciplines, has been adopted as a technique in software engineering to improve the calculation of new projects involving risks. however, there has so far been a lack of documented experience with the use of prototyping in industrial software production. the paper tries to close this gap. first, we introduce central prototyping concepts and terminology. we also present five industrial software projects in which explicit use was made of prototyping. based on our analysis of these projects we present the resulting conclusions: prototyping means more than rapidly developing user interfaces; prototyping is a central part of a development strategy; prototyping means end user involvement; finding the right mixture of prototypes improves the development process.
is 'sometime' sometimes better than 'always'? intermittent assertions in proving program correctness. this paper explores a technique for proving the correctness and termination of programs simultaneously. this approach, which we call the intermittent-assertion method, involves documenting the program with assertions that must be true at some time when control passes through the corresponding point, but that need not be true every time. the method, introduced by burstall, promises to provide a valuable complement to the more conventional methods. we first introduce the intermittent-assertion method with a number of examples of correctness and termination proofs. some of these proofs are markedly simpler than their conventional counterparts. on the other hand, we show that a proof of correctness or termination by any of the conventional techniques can be rephrased directly as a proof using intermittent assertions. finally, we show how the intermittent assertion method can be applied to prove the validity of program transformations and the correctness of continuously operating programs. this is a revised and simplified version of a previous paper with the same title (aim-281, june 1976).
controlling the complexity of software design. our research has focused on identifying techniquesto develop software that is amenable to refactoring andchange. the law of demeter (lod) was one contributionin this effort. but it led to other problems. with thecurrent state of the art focused on aspect-oriented softwaredevelopment (aosd), it is useful to revisit thegeneral objectives of the lod and adapt it to the newideas. hence we introduce the law of demeter for concernsand discuss the important intersection of these approacheswith traversals. we explore the ramifications ofthe laws of demeter (lod and lodc) to achieve betterseparation of concerns through improved software processes.they are supported by language mechanisms thatare implemented using novel applications of automata theory.a revised version of this paper and the slides are availablefrom the demeter website:http://www.ccs.neu.edu/research/demeterin the directory papers/icse-04-keynote/
the prism model of changes. the author addresses the problem of managing changes to items of various types in a multitype software environment. prism, a model of changes, has been designed with the following features: (1) a separation of concern between changes to the described items and changes to the environmental facilities housing these items; (2) a facility, called the dependency structure, for describing various items and their interdependencies, and for identifying the items affected by a given change; (3) a facility, called the change structure, for classifying, recording and analyzing change related data, and for making qualitative judgments of the consequences of a change; (4) identification of the many distinct properties of a change; and (5) a built-in mechanism for providing feedback. the rationale for the design of the model of changes as well as that of the dependency structure and the change structure is given
building modular object-oriented systems with reusable collaborations (tutorial session). new approaches propose to deal with the tangling of logical units by extending the object-oriented language to support module (de)composition along more than one dimension of concern. the tutorial will briefly survey aspect-oriented programming (@@@@ectj tool), adaptive programming (the demeter tool), and hyper-dimensional separation of concerns (the hyper/j tool). the primary focus of the tutorial, however, will be on a daptive plug-and-play components (ap&pc) [2, 1].the ap&pc model enables the programmer to define reusable collaborations, in the sense of the unified modeling language (uml), in separate modules. in the ap&pc approach, an application is built out of a set of base classes that lay down the static structure of the application and several modules of reusable collaborations that are non-intrusively adapted to the needs of the base classes by means of explicit connectors, or adapter constructs. each module itself may be a composition of simpler collabortion modules. the adaptation includes the embedding of uml class diagrams into more elaborate uml class diagrams. we will show how such embeddings may be conveniently expressed using the traversal language of adaptive programming (which is also used in the xml traversal language called xpath.) we will discuss how the model supports the building of better modular object-oriented systems. in addition, the advantages and disadvantages of static versus dynamic adaptation of the reusable collaborations will be considered.in summary, the tutorial presents ap&pc and adapters as useful constructs to encapsulate logical units of design that cut across several classes. we compare ap&pc with other approaches to the tangling problem in software design and implementation.
the synthesis of structure changing programs. deductive techniques are presented for deriving programs systematically from given specifications. the specifications express the purpose of the desired program without giving any hint of the algorithm to be employed. the desired program is intended to achieve this purpose by means of such low-level primitives as assignment statements, the conditional statements, and recursion. the basic approach is to transform the specifications repeatedly according to certain rules, until a satisfactory program is produced. the rules are guided by a number of strategic controls. many of the transformation rules represent knowledge about the program's subject domain (e.g., numbers, lists, sets); some represent the meaning of the constructs of the specification language and the target programming language; and a few rules represent basic programming principles. the weakest-precondition operator and the concept of protection are employed to construct programs that must achieve more than one condition simultaneously. our previous work has centered on the synthesis of structure-maintaining programs, which produce an output without altering the value of any variable or changing the configuration of any data structure. here, we extend our previous techniques to permit the construction of structure-changing programs, which can reset the values of variables, change the contents of an array, and alter the structure of a list or other data object.
demeter: a case study of software growth through parameterized classes. demeter&trade; is a system designed for the development of large software projects using a new software design methodology which focuses on growing rather than building software. we describe the software development process as one of growth and evolution as opposed to building and rebuilding because most complex objects in the real world are grown and not built. since software design is obviously a complex process this new paradigm may be helpful in unraveling some of the problems associated with current software design practices. demeter begins by providing an ideal environment for the sprouting and nurturing of a seed (data dictionary) into a plant (large scale software project). in addition, through the combined use of object-oriented programming technology, and parameterized classes, demeter provides a facility for the reuse of software which was developed in previous software projects.
modeling of data-processing software for generating and reusing their programs. we propose a new modeling scheme named s-model (which is the abbreviation of &ldquo;semantic model&rdquo;) based on a uniform object-relationship formalism. s-model is the mixture of notations in logic, set theory, and abstract syntax and covers wide range of information of file-processing and data-structure manipulating software. by procedural algorithms and problem-solving capability of s-model system, we can generate and reuse programs in various fields.
configuration management with logical structures. when designing software, programmers usually think in terms of modules that are represented as functions and classes, but using existing configuration management systems, programmers have to deal with versions and configurations that are organized by files and directories. this is inconvenient and error-prone, since there is a gap between handling source code and managing configurations. we present a framework for programming environments that handles versions and configurations directly in terms of the functions and classes in source code. we show that with this framework, configuration management issues in software reuse and cooperative programming become easier. we also present a prototype environment that has been developed to verify our ideas.
early experiences with a multi-display programming environment. we summarize the features of mdps, an advanced programming environment with multiple crt displays, and describe our early experiences with mdps.
integrating static analysis and general-purpose theorem proving for termination analysis. we present emerging results from our work on termination analysis of software systems. we have designed a static analysis algorithm which attains increased precision and flexibility by issuing queries to a theorem prover. we have implemented our algorithm and initial results show that we obtain a significant improvement over the current state-of-the-art in termination analyses. we also outline how our approach, by integrating theorem proving queries into static analyses, can significantly impact the design of general-purpose static analyses.
control structure aptness: a cast study using top-down parsing. the range of control structures available in a higher-level programming language directly governs the set of algorithms conveniently programmable therein. this fact has been well-demonstrated by the salutary effect the ideas of structured programming have had on traditional control structures (sequential, iterative, and procedural). this paper seeks to demonstrate this same fact for more advanced control structures through the use of top-down parsing as a case study. a series of increasingly more satisfactory top-down parsers are presented, using (i) iterative, (ii) recursive, (iii) coroutine, and (iv) nondeterministic control forms. a fifth solution, using a new control form termed &ldquo;non-forgetful backtracking&rdquo;, is sketched. this study indicates that the development of new control forms, as well as more thorough understanding and application of existing ones, are worthy pursuits for software engineering. a few directions for continuing work in this spirit are offered in the concluding section.
developing new approaches for software design quality improvement based on subjective evaluations. this research abstract presents two approaches forutilizing the developersý subjective design qualityevaluations during the software lifecycle. in process-basedapproach developers study and improve theirsystemýs structure at fixed intervals. tool-based approachuses subjective evaluations as input to tool analysis.these approaches or their combination are expected toimprove software design and promote organizationallearning about software design.
designing data entry programs using state diagram as a common model. a minicomputer based data entry system recently developed at bell laboratories supports 73 transaction types and approximately 1000 fields. the user communicates with the system from a crt terminal in field-by-field mode via a uniform interface. this paper presents a common design for the family of data entry programs that process the various types of transactions. the design is represented by a compact, orderly, and verifiable model to demonstrate the consistent program behavior. the model is formalized and proved correct to validate the design. the common model reduces design effort, provides design generality, enables code generation, and enhances ease of maintenance. the correctness proof eliminates high level design errors and their consequences. in the general area of business application, a common design lends itself to quickly mass produce components of a software product, and makes it easy to maintain them later.
tools for understanding the behavior of telecommunication systems. many methods and tools for the reengineering of software systems have been developed so far. however, the domain-specific requirements of telecommunication systems have not been addressed sufficiently. these system are designed in a process- rather than in a data-centered way. furthermore, analyzing and visualizing dynamic behavior is a key to system understanding. in this paper, we report on tools for the reengineering of telecommunication systems which we have developed in close cooperation with an industrial partner. these tools are based on a variety of techniques for understanding behavior such as visualization of link chains, recovery of state diagrams from the source code, and visualization of traces by different kinds of diagrams. tool support has been developed step by step in response to the requirements and questions stated by telecommunication experts at ericsson eurolab germany.
a software methodology for buidling interactive tools. the methodology proposed is intended to aid in the development of cooperative interactive tools (i.e., those which are natural, helpful, and consistent). cooperative tools must incorporate knowledge of their own capabilities, limitations, and requirements. this required knowledge of tool functionality is provided by programming the tool in the process script formalism. the process script formalism is a specialized procedural/declarative language for writing tools. the key aspect of the process script specification of a tool is that, besides being executable, process scripts can be analyzed and understood for the purpose of cooperative interaction with the end user. this paper describes the process script formalism and explains its role in the development of a cooperative interactive system.
augmenting sadt to develop computer support for cooperative work. using the language-action perspective proposed by t. winograd and f. flores (1986), the author creates a general framework for both systems analysis and its practice. structured analysis and design technique (sadt), a systems analysis methodology, is augmented using this framework. this work took place on the contract (commitment negotiation and tracking tool) project. the author includes the experiences of both users and systems analysts during the project, and emphasizes how to develop sadt descriptions with users to represent the richness and complexity of social interactions at work. the resulting software specification is also presented, including how it aided the work of the people who actually helped develop it
an experimental, pluggable infrastructure for modular configuration management policy composition. building a configuration management (cm) system isa difficult endeavor that regularly requires tens of thousandsof lines of code to be written. to reduce this effort,several experimental infrastructures have been developedthat provide reusable repositories upon which to build acm system. in this paper, we push the idea of reusabilityeven further. whereas existing infrastructures only reusea generic cm model (i.e., the data structures used to capturethe evolution of artifacts), we have developed a novelexperimental infrastructure, called mccm, that additionallyallows reuse of cm policies (i.e., the rules bywhich a user evolves artifacts stored in a cm system).the key contribution underlying mccm is that a cmpolicy is not a monolithic entity; instead, it can be composedfrom small modules that each address a uniquedimension of concern. using the pluggable architectureand base set of modules of mccm, then, the core of adesired new cm system can be rapidly composed bychoosing appropriate existing modules and implementingany remaining modules only as needed. we demonstrateour approach by showing how the use of mccm significantlyreduces the effort involved in creating several representativecm systems.
static and dynamic data modeling for information system design. this paper illustrates an approach to designing software information systems. we have found this strategy to be sufficiently systematic and practically useful enough to merit exposition for a wider audience. the most novel aspect of our approach is how we analyze the problem in successive steps to produce a logical design. briefly, the steps are: (1) identify the (classes of) things in the problem's context and the invariant relationships between them. (2) for each (class of) thing that is of central importance to the problem describe the main stages and transitions in the thing's &ldquo;life&rdquo; with respect to the problem, (3) synthesize the logical data base structure with attributes determined for all record types using results from the previous two steps. these three steps are the way we model static and dynamic aspects of data as a prerequisite to designing information systems.
a software engineering approach and tool set for developing internet applications. if a business built a plant to produce products without first designing a process to manufacture them, the risk would be lack of capacity without significant plant redesign. similarly, lacking a software engineering approach and tools for designing e-business connections before creating them, can risk: 1) designing the business partnership incorrectly, 2) not implementing the connection quickly enough, or 3) having operations that cannot adapt to changes in business direction. this paper presents a software engineering tool for developing process-oriented internet applications that implement e-business connections. it gives an approach for using this tool in conjunction with standard commercial idefo tools to create adaptable connections. it is organized to match a formal demonstration that shows the step-by-step usage of these tools, and cites software engineering principles that, when applied, ensure adaptability.
cleanroom software engineering for zero-defect software. cleanroom software engineering is a theory-based, team-oriented process for developing very high quality software under statistical control. cleanroom combines formal methods of object-based box structure specification and design, function-theoretic correctness verification, and statistical usage testing for quality certification to produce software that has zero defects with high probability. the process of cleanroom development and certification is carried out incrementally. interface and design errors are rare because at each stage the harmonious operation of future increments at the next level of refinement is predefined by increments already in execution. the cleanroom process is being successfully applied in ibm and other applications. quality results from several cleanroom projects are summarized
recovering documentation-to-source-code traceability links using latent semantic indexing. an information retrieval technique, latent semantic indexing, is used to automatically identify traceability links from system documentation to program source code. the results of two experiments to identify links in existing software systems (i.e., the leda library, and albergate) are presented. these results are compared with other similar type experimental results of traceability link identification using different types of information retrieval techniques. the method presented proves to give good results by comparison and additionally it is a low cost, highly flexible method to apply with regards to preprocessing and/or parsing of the source code and documentation.
a study on exception detecton and handling using aspect-oriented programming. aspect-oriented programming (aop) is intended to ease situations that involve many kinds of code tangling. this paper reports on a study to investigate aop's ability to ease tangling related to exception detection and handling. we took an existing framework written in java&trade;, the jwam framework, and partially reengineered its exception detection and handling aspects using aspectj&trade;, an aspect-oriented programming extension to java.we found that aspectj supported implementations that drastically reduced the portion of the code related to exception detection and handling. in one scenario, we were able to reduce that code by a factor of 4. we also found that, with respect to the original implementation in plain java, aspectj provided better support for different configurations of exceptional behaviors, more tolerance for changes in the specifications of exceptional behaviors, better support for incremental development, better reuse, automatic enforcement of contracts in applications that use the framework, and cleaner program texts. we also found some weaknesses of aspectj that should be addressed in the future.
toward new techniques to assess the software implementation process. the author presents the concept of software boundaries and their automated detection. he describes an objective, high-level assessment technology to support process control of software development. the technique is largely independent of underlying design and development methods. an example illustrates an automated system partitioning application. the technique analyzes the end product and the delivered software code. by suitable adjustment of the analysis goals, measures, and criteria, the technique can help evaluate the effectiveness of many software implementation methods. the author discusses the technique's potential for increasing confidence in the fault-tolerating properties of a system
reducing and estimating the cost of test coverage criteria. test coverage criteria define a set of entities of a program flowgraph and require that every entity is covered by some test. we first identify e/sub c/, the set of entities to be covered according to a criterion c, for a family of widely used test coverage criteria. we then present a method to derive a minimum set of entities, called a spanning set, such that a set of test paths covering the entities in this set covers every entity in e/sub c/. we provide a generalised algorithm, which is parametrized by the coverage criterion. we suggest several useful applications of spanning sets of entities to testing. in particular they help to reduce and to estimate the number of tests needed to satisfy test coverage criteria.
dependability assessment of software-based systems: state of the art. my talk will present a personal and rather selective view of the state of the art of some aspects of dependability assessment for software-based systems. this short note gives a brief outline of the issues i shall address.
an architecture for heterogeneous groupware applications. the proliferation of wireless networks and small portable computing devices raises the need for applications that are adaptable to heterogeneous computing and communication environments and the contexts in which they are used. however, most current groupware systems as well as other software applications are not well prepared to handle the heterogeneity. the manifold framework presented here provides a software architecture for synchronous groupware applications to deal with heterogeneity. the framework's main characteristic is data centricity. the users collaborate on and exchange data, and the data is dynamically transformed to adapt to the particular computing/network platform. the design is based on multi-tier architecture and uses extensible markup language (xml) as a generic means for information exchange. the resulting design is simple yet very powerful and scalable. manifold is implemented and tested by developing several complex groupware applications.
how to measure software reliability, and how not to. this paper examines critically, with a view to stimulating a discussion, some concepts which have been used in early work on software reliability measurement, and suggests improvements and areas of potentially fruitful future research. it is proposed that hardware-motivated measures such as mttf, mtbf should not be used for software without justification, and it is shown that such justification may be lacking under quite unexceptionable circumstances. alternative methods of measuring software reliability are proposed. emphasis is placed upon differentiating between two concepts of software reliability which are often blurred in the work of previous authors. these are, on the one hand, the reliability of the program-as-it-is (the number of bugs it contains), on the other, the reliability of the program-as-it-performs (failure rate, distribution of time to next failure, etc.). it is argued that the latter, here called operational reliability, is the one we should use. measures of operational reliability which avoid use of mttf, etc., are proposed. a case is made for software engineers adopting a bayesian stand-point:both in the interpretation of probability statements and in inference procedures. it is suggested that reliability modelling solely in terms of failures (or number of bugs) is unnecessarily naive. interest really centres upon the consequences of failures as much as on their frequency. it is proposed that more effort be devoted to the development of models which incorporate a cost (or utility) structure. finally, brief consideration is given to the question of program structure. the enormous success of hardware reliability theory, in combining component reliabilities with knowledge of system sturcture, must be emulated for software. unfortunately, software structure does not easily lend itself to such an exercise. some existing models are considered.
interactive system for structured program production. the automation of program development procedures is one of the important subjects to be solved for improving productivity. the documentation of program specification and coding process involve many mechanical operations. presently, however, they are done mostly by human efforts. this greatly hinders the improvement of both productivity and program quality. for the purpose of solving all the problems, we developed an experimental system sdl/pad. upon receipt of the specifications described in a structured form which has been defined in accordance with structured design, the sdl/pad. system automatically generates programs written with a computer language such as pl/m or the like and specification documents. this system eliminates the troublesome inconsistency between documents and source programs.
a program complexity metric based on data flow information in control graphs. this paper presents a new approach to measuring program complexity with the use of data flow information in programs. a complexity metric, called du, is defined for the control graph of a structured program. this new metric is different from other control-graph based metrics in that it is based on &ldquo;representative&rdquo; data flow information in a control graph. an algorithm for computing the value of du(g) for a control graph g is given. the lower and upper bounds of du(g) are provided. the du metric is shown to have several advantages over other control-graph based complexity metrics.
fault tolerance via diversity against design faults (tutorial session): design principles and reliability assessment. research results indicate that (as usual in software engineering) these question can only be answered with reference to each specific application context and that diversity is no &ldquo;silver bullet&rdquo;. but diversity is an attractive option, made more interesting by current trends like the preference for cots items, and it is important for practitioners to go beyond the summary opinions and misunderstanding that surround it.this tutorial is designed for people involved in system design, acceptance or certification, especially in companies with high dependability requirements or plans to improve on current levels to move into more demanding markets. it is also appropriate for researchers in software engineering wishing to obtain an up-to-date view of knowledge in this area.this tutorial describes:the motivations behind the use of software fault tolerance, and thus the circumstances in which it should be considered as a possible choice;what design schemes one may adopt, and which issues a designer needs to be aware of, for effective application. we present both examples of industrial use and explanations of the important design choices and trade-offs. in this part, we cover the widely published solutions of n-version programming and recovery blocks, but also describe the various options available to a designer, and interesting specific solutions adopted in the railway and aviation industry, and scheme for applications to safety systems. we discuss the factors that may decide the scheme to be adopted and the design of adjudication between conflicting results; &ldquo;what one should really believe&rdquo; about the effectiveness of software fault tolerance in improving reliability, beyond the controversy and the misunderstandings surrounding it. we give a picture, assembled from more than 10 years of research, of what evidence has really been produced for and against software diversity. we explain the weaknesses of the extreme opinions voiced for and against software fault tolerance, and discuss the criteria that should affect practical decisions about using it, about how to improve its effectiveness by appropriate decisions in developing alternate versions of software components, and about its value for system acceptance.
experience from applying rim to educational erp development. developing a complex system requires partitioning the target system into several subsystems. it is generally difficult to define each subsystem's scope and functional requirements as well as data dependencies among subsystems. requirements integration model (rim), which consists of a workflow model and a work procedure, can provide specific guidelines and techniques to increase quality of requirements obtained under a time constraint. we have applied the technique to the implementation of the educational system for the department of computer engineering at chulalongkorn university, thailand. experiences from this case study have shown that the model can assist developers to clearly specify functional requirements for each subsystem and to identify data dependencies among subsystems.
understanding software application interfaces via string analysis. in software systems, different software applications often interact with each other through specific interfaces by exchanging data in string format. for example, web services interact with each other through xml strings. database applications interact with a database through strings of sql statements. sometimes these interfaces between different software applications are complex and distributed. for example, a table in a database can be accessed by multiple methods in a database application and a single method can access multiple tables. in this paper, we propose an approach to understanding software application interfaces through string analysis. the approach first performs a static analysis of source code to identify interaction points (in the form of interface-method-call sites). we then leverage existing string analysis tools to collect all possible string data that can be sent through these different interaction points. then we manipulate collected string data by grouping similar data together. for example, we group together all collected sql statements that access the same table. then we associate various parts of aggregated data with interaction points in order to show the connections between entities from interacting applications. our preliminary results show that the approach can help us understand the characteristics of interactions between database applications and databases. we also identify some challenges in this approach for our future work.
visual languages for event integration specification. we are exploring existing approaches and developing new techniques for visual event-based system integration. we are using domain-specific visual languages with different high-level visual metaphors (including tool abstraction, event-query-filter-action and spreadsheet) to specify event-handling support and provide backend processing tool support for event integration specification and visualisation of event propagation. we aim to generalise from three exemplar visual event-driven system metaphors and develop a new, generic visual event handling metaphor. from this we will build a visual environment for specifying event-based system integration. the visual metaphor we are developing should adapt the event-based communication model to a wide range of application domains, and also should support complex and intelligent system design and implementation.
feature oriented refactoring of legacy applications. feature oriented refactoring (for) is the process of decomposinga program into features, where a feature is an increment in programfunctionality. we develop a theory of for that relates code refac-toring to algebraic factoring. our theory explains relationshipsbetween features and their implementing modules, and why fea-tures in different programs of a product-line can have differentimplementations. we describe a tool and refactoring methodologybased on our theory, and present a validating case study.
automatic method refactoring using weighted dependence graphs. while refactoring makes frameworks more reusable, it is complex to do by hand. this paper presents a mechanism that automatically refactors methods in object-oriented frameworks by using weighted dependence graphs, whose edges are weighted based on the modification histories of the methods. to find the appropriate boundary between frozen spots and hot spots in the methods, the value of the weight varies based on whether the dependence in the original methods has been repeatedly preserved or destroyed in the methods of applications created by programmers. the mechanism constructs both template methods that contain the invariant dependence and hook methods that are separated by eliminating the variant dependence. the new template methods and hook methods tailored to each programmer save him/her from writing superfluous code when reusing a framework. experimental results show a reduction rate of up to 22% in the number of statements a programmer has to write when creating several applications; this percentage is double that achievable by a conventional refactoring technique.
xml conceptual modeling with xuml. as xml has become the standard format for representing structured and semi-structured data on the web, the methods for designing xml schemas is becoming more and more important. xml schemas represent the logical models of the documents. in order to design or integrate xml schemas, it is necessary to first design the conceptual structures with a proper conceptual model. we thus specify a xml conceptual model, xuml, which has following characteristics comparing with the existing xml conceptual models: 1) expressing the containment semantics more explicitly; 2) supporting the concept of business components; 3) specifying the data dependencies in multiple contexts. xuml is defined based on the uml2 standard, so it will be more friendly and practical for those who have had knowledge and experience on uml. based on xuml, we further present a framework of the methodology which is dedicated to the design of xml documents and xml databases. in this paper, the focus is put on xuml.
modeling and analysis of a virtual reality system with time petri nets. the design, implementation, and testing of virtual environments is complicated by the concurrency and real-time features of these systems. therefore, the development of formal methods for modeling and analysis of virtual environments is highly desirable. in the past, petri net models have led to good empirical results in the automatic verification of concurrent and real-time systems. we applied a timed extension of petri nets to modeling and analysis of the cavetm virtual environment at the university of illinois at chicago. we report on our time petri net model and on empirical studies that we conducted with the cabernet toolset from politecnico di milano. our experiments uncovered a flaw in the way a shared buffer is used by cave processes. due to an erroneous synchronization on the buffer, different cave walls can simultaneously display images based on different input information. we conclude from our empirical studies that petri net-based tools can effectively support the development of reliable virtual environments
specification, analysis, and prototyping of mobile systems. mobile code offers new strategies for the development of systems. i adopt a formal approach to study advantages, limitations, classification, and future trends of mobile code technologies.
an analytic framework for specifying and analyzing imprecise requirements. there are at least three challenges with requirements analysis. first, it needs to bridge informal requirements, which are often vague and imprecise, to formal specification methods. second, requirements often conflict with each other. third, existing formal requirement specification methodologies are limited in supporting trade-off analysis between conflicting requirements and identifying the impact of a requirement change to the rest of the system. in this paper, an analytic framework is developed for the specification and analysis of imprecise requirements. in this framework, the elasticity of imprecise requirements is captured using fuzzy logic and the relationships between requirements are formally classified into four categories: conflicting, cooperative, mutually exclusive and irrelevant. this formal foundation facilitates the inference of relationships between requirements for detecting implicit conflicts, to assess the relative priorities of requirements for resolving conflicts, and to assess the effect of a requirement change.
ltrules: an automated software library usage rule extraction tool. the need to manually specify temporal properties of software systems is a major barrier to wider adoption of software model checking, because the specification of software temporal properties is a difficult, time-consuming, and error-prone process. to address this problem, we propose to automatically extract software library usage rules, which are one type of temporal specifications. our approach uses a model checker to check a set of software library usage rule candidates against known good programs using that library, and identifies valid rules based on model checking results. these valid rules can help programmers learn about common software library usage. they can also be used to check new programs using the same library. we have implemented our approach in an eclipse plug-in named ltrules, which can extract software library usage rules from c programs using blast as the underlying model checker.
using a command language as a high-level programming language. the command language for the programmer's workbench (pwb) utilizes an extended version of the standard unix shell program, plus commands designed mainly for use within shell procedures (command files). modifications have been aimed at improving the use of the shell by large programming groups, and making it even more convenient to use as a high-level programming language. in line with the philosophy of much existing unix software, an attempt has been made to add new features only when they are shown necessary by actual user experience in order to avoid contaminating a compact, elegant system through &ldquo;creeping featurism.&rdquo; by utilizing the shell as a programming language, pwb users have been able to eliminate a great deal of the programming drudgery that often accompanies a large project. many manual procedures have been quickly, cheaply, and conveniently automated. because it is so easy to create and use shell procedures, each separate project has tended to customize the general pwb environment into one tailored to its own requirements, organizational structure, and terminology. a summary is given of the usage patterns revealed by a survey of 1,725 existing shell procedures.
xas: a system for accessing componentized, virtual xml documents. xml is emerging as an important format for describing the schema of documents and data to facilitate integration of applications in a variety of industry domains. an important issue that naturally arises is the requirement to generate, store and access xml documents. it is important to reuse existing data management systems and repositories for this purpose. in this paper, we describe the xml access server (xas), a general purpose xml based storage and retrieval system which provides the appearance of a large set of xml documents while retaining the data in underlying federated data sources that could be relational, object-oriented, or semi-structured. xas automatically maps the underlying data into virtual xml components when mappings between dtds and underlying schemas are established. the components can be presented as xml documents or assembled into larger components. xas manages the relationship between xml components and the mapping in the form of document composition logic. the versatility in its ways to generate xml documents enables xas to serve a large number of xml components and documents efficiently and expediently.
documentation tools and techniques. in a software development project of any appreciable size, the production of usable, accurate documentation may well consume more effort than the production of the software itself. several years of experience on many programmer's workbench projects have shown that document preparation should not be separated from software development and that the combination of a flexible operating system, a powerful command language, and good text processing facilities permits quick and convenient production of many kinds of documentation which might be otherwise unobtainable, impractical, or very expensive. our basic approach has been to develop techniques for effective combination of existing unix facilities. a number of case histories are given to illustrate the flexibility, convenience, and general usefulness of these techniques.
empirical studies on requirement management measures. the goal of this research is to demonstrate that a subsetof a set of 38 requirements management measures are goodpredictors of stability and volatility of requirements andchange requests. at the time of writing we have theoreticallyvalidated ten of these 38 measures. we are currentlyplanning and performing an industrial case study where wewant to reach the goal described above.
modeling mutation on a vector processor. mutation analysis is a software testing methodology designed to substantiate the correctness of a program &phgr;. the mutation approach is to induce syntactically correct changes in &phgr;, thereby creating a set of mutant programs. the goal of a tester is to construct a set of test data t that distinguishes the output of &phgr;(t) from that of all mutant programs. test data sensitive enough to distinguish al1 mutant programs is deemed adequate to infer the probable correctness of &phgr;. we propose an algorithm designed to exploit the architecture of a vector processor like the cyber 205 or cray x/mp. the algorithm manages the simultaneous execution of multiple mutant fortran 77 programs. this is accomplished by viewing the execution of these mutants as a sequence of vector instructions. the algorithm promises potential to greatly increase the performance of a mutation based testing system, as well as points towards a general method of simultaneous program execution against multiple data sets.
implementing a software management discipline. the paper did not arrive prior to press time.
comparison of software product line architecture design methods: copa, fast, form, kobra and qada. product line architectures (plas) have been undercontinuous attention in the software research communityduring the past few years. although several methods havebeen established to create plas there are not availablestudies comparing pla methods. five methods are knownto answer the needs of software product lines: copa,fast, form, kobra and qada. in this paper, anevaluation framework is introduced for comparing pladesign methods. the framework considers the methodsfrom the points of view of method context, user, structureand validation. comparison revealed distinguishableideologies between the methods. therefore, methods donot overlap even though they all are pla design methods.all the methods have been validated on various domains.the most common domains are telecommunicationinfrastructure and information domains. some of themethods apply software standards; at least omgýs mdafor method structures, uml for language and ieee std-1471-2000 for viewpoint definitions.
task interaction graphs for concurrency analysis. a representation for concurrent programs, called `task interaction graphs'', is presented. task interaction graphs divide a program into maximal sequential regions connected by edges representing task inter- actions. this representation is illustrated and it is shown how it can be used to create concurrency graph representations that are much smaller than those created from control flow graph representations. both task interaction graphs and their corresponding concurrency graphs facilitate analysis of concurrent programs. some analyses and optimizations on these representations are also described.
improving design and source code modularity using aspectj (tutorial session). using only traditional techniques the implementation of concerns like exception handling, multi-object protocols, synchronization constraints, and security policies tends to be spread out in the code. the lack of modularity for these concerns makes them more difficult to develop and maintain. this tutorial shows how to use aspect-oriented programming (aop) [2, 3] to implement concerns like these in a concise modular way. we discuss the effect aspects have on software design and on code modularity. the concrete examples in the tutorial use aspectj [1], a freely available aspect-oriented extension to the java&trade; programming language.
a software architecture-based framework for highly distributed and data intensive scientific applications. modern scientific research is increasingly conducted by virtual communities of scientists distributed around the world. the data volumes created by these communities are extremely large, and growing rapidly. the management of the resulting highly distributed, virtual data systems is a complex task, characterized by a number of formidable technical challenges, many of which are of a software engineering nature. in this paper we describe our experience over the past seven years in constructing and deploying oodt, a software framework that supports large, distributed, virtual scientific communities. we outline the key software engineering challenges that we faced, and addressed, along the way. we argue that a major contributor to the success of oodt was its explicit focus on software architecture. we describe several large-scale, real-world deployments of oodt, and the manner in which oodt helped us to address the domain-specific challenges induced by each deployment.
designing components versus objects: a transformational approach. a good object-oriented design does not necessarily make a good component-based design, and vice versa. what design principles do components introduce? this paper examines component-based programming and how it expands the design space in the context of an event-based component architecture. we present a conceptual model for addressing new design issues these components afford, and we identify fundamental design decisions in this model that are not a concern in conventional object-oriented design. we use javabeans-based examples to illustrate concretely how expertise in component-based design, as embodied in a component taxonomy and implementation space, impacts both design and the process of design. the results are not exclusive to javabeans&mdash;they can apply to any comparable component architecture.
pluggable reflection: decoupling meta-interface and implementation. reflection remains a second-class citizen in current programming models, where it's assumed to be imperative and tightly bound to its implementation. in contrast, most object-oriented apis allow interfaces to vary independently of their implementations. components take this separation a step further by describing unforeseeable attributes---the key to pluggable third-party components. this paper describes how reflection can benefit from a similar evolutionary path.
knowledge-based software design using design schemas. design schemas provide a means for abstracting software designs into broadly reusable components that can be assembled and refined into new software designs. this paper describes a knowledge-based software development paradigm that is based on the design schema representation. it combines design schemas, domain knowledge, and various types of rules to assist in the quick generation of software designs from user specifications. a prototypical environment, idea (intelligent design aid), is described that supports the knowledge-based paradigm. the schema-based techniques used in idea are presented along with some examples of their use.
what you always wanted to know about agile methods but did not dare to ask. a fleet of emerging agile methods is both gaining popularity and generating lots of controversy. real-world examples argue for (e.g. [4]) and against (e.g. [6]) agile methods. several leading software engineering experts suggest that synthesizing the two (agile with traditional) may provide developers with a comprehensive spectrum of methods (e.g. [1], [2], [5]). this high-level overview tutorial provides background to understand how agile teams are trying to solve modern software development issues.
agile methods: moving towards the mainstream of the software industry. a fleet of emerging agile methods of software development (with extreme programming and scrum being the most broadly used) is both gaining popularity and generating lots of controversy. this high-level tutorial gives an overview of agile methods and provides background to understand how agile teams are trying to address modern software development challenges. analysis of initial empirical evidence is used to discuss strengths and limitations of agile methods in various contexts. the participants are introduced to the innovation diffusion models and environments, and discuss what is needed for agile methods to cross the chasm and move into the mainstream of software development.
developing initial ooa models. the authors developed an initial object-oriented requirements model for an existing missile planning system. they adopted two approaches: a bottom-up approach in which object-oriented model fragments were constructed that corresponded to segments of the requirements documents, and a top-down approach that was driven by the construction and analysis of scenarios. the strengths and limitations of each approach were discussed in the context of the example. a bottom-up, fragment-driven approach is appropriate in cases where there is a large, rich body of documentation. a top-down, scenario-driven approach should dominate where there is no requirements specification, but some high-level, unintegrated information about how the system should operate
representation of factual information by equations and their evaluation. this paper describes a methodology for application software development, the objective being the reduction of volume of code and ease of maintenance. it is shown that constants as well as rules and regulations typically found in business applications should be factored out and stored separately from the application programs in a data base. definitional equations are proposed as a method for specifying such rules and regulations. the equations can be used as parameters to various types of interpreters to be used by application programs. as an illustration of the methodology, one such interpreter has been implemented. this paper shows its application to a screen handling program; other uses are discussed. the interpreter and its implementation are outlined.
assessing test-driven development at ibm. in a software development group of ibm retail store solutions, we built a non-trivial software system based on a stable standard specification using a disciplined, rigorous unit testing and build approach based on the test- driven development (tdd) practice. using this practice, we reduced our defect rate by about 50 percent compared to a similar system that was built using an ad-hoc unit testing approach. the project completed on time with minimal development productivity impact. additionally, the suite of automated unit test cases created via tdd is a reusable and extendable asset that will continue to improve quality over the lifetime of the software system. the test suite will be the basis for quality checks and will serve as a quality contract between all members of the team.
software engineering for large-scale multi-agent systems: selmas'2002. objects and agents are abstractions that exhibit points of similarity, but the development of agent-based software poses other challenges to software engineering since software agents are inherently more complex entities. in addition, a large-scale multi-agent system needs to satisfy multiple stringent requirements such as reliability, security, interoperability, scalability, reusability, and maintainability. this workshop brought together researchers and practitioners to discuss the current state and future direction of research in software engineering for large-scale multi-agent systems. a particular interest was to understand those issues in the agent technology that difficult and/or improve the production of large-scale distributed systems.
multilanguage interoperability in distributed systems. the q system provides interoperability support for multilingual, heterogeneous component-based software systems. initial development of q began in 1988, and was driven by the very pragmatic need for a communication mechanism between a client program written in ada and a server written in c. the initial design was driven by language features present in c, but not in ada, or vice-versa. in time our needs and aspirations grew and q evolved to support other languages, such as c++, lisp, prolog, java, and tcl. as a result of pervasive usage by the arcadia sde research project, usage levels and modes of the q system grew and so more emphasis was placed upon portability, reliability, and performance. in that context we identified specific ways in which programming language support systems can directly impede effective interoperability. this necessitated extensive changes to both our conceptual model and our implementation of the q system. we also discovered the need to support modes of interoperability far more complex than the usual client-server. the continued evolution of q has allowed the architecture of arcadia software to become highly distributed and component-based, exploiting components written in a variety of languages. in addition to becoming an arcadia project mainstay, and has also been made available to over 100 other sites, and it is currently in use in a variety of other projects. this paper summarizes key points that have been learned from this considerable base of experience.
the data transform programming metho: an example for file processing problems. this paper presents a new programming method, called the data transform programming method. in particular, we present a specialization of data transform programming to deal with file processing applications. direct comparison is made with jackson's approach1 by the presentation of uniform solutions to problems that cannot be solved through his basic method. the new method consists of the application of data transformations to the abstract problem statement, following the formal notions of problem reduction and problem decomposition. data transformations are expressed in programming terms through a basic set of data type constructors.
predicate-based test generation for computer programs. the author first describes a number of existing testing strategies for simple predicates and then explains why intuitive extensions of such strategies are ineffective or impractical for testing compound predicates, which are predicates with one or more and/or operators. two fault-based testing strategies for compound predicates are defined, bor (boolean operator) testing and bro (boolean and relational operator) testing. it is shown that for a predicate with n, n>0, and/or operators, at most n+2 (2*n+3) tests are needed to satisfy bor (bro) testing. preliminary experimental results indicate that bor and bro testing are effective for the detection of various types of faults in a predicate and provide more specific guidance than branch testing for test generation
behavioral analysis of software architectures using ltsa. the ltsa (labeled transition system analyzer) is a tool for modeling and analyzing the behavior of concurrent systems. the demonstration will focus on the use of architectural descriptions in developing behavioral models and on the analysis that can be performed on these models. three concurrent architecture examples; filter pipeline, supervisor-worker and announcer-listener which each use a different type of connector are used to illustrate the capabilities of the tool.
developing cost-effective model-based techniques for gui testing. most of today's software users interact with the software through a graphical user interface (gui). while guis have become ubiquitous, testing of guis has remained until recently, a neglected research area. existing gui testing techniques are extremely resource intensive primarily because guis have very large input spaces. this research proposes to advance the state-of-the-art in gui testing by empirically studying gui faults, interactions between gui events, why certain event interactions lead to faults, and use the results of these studies to develop cost-effective model-based gui testing techniques. the novel feature of this research will be a reduced model of the gui's event-interaction space. the model will be derived automatically from the gui; it will be used to automatically generate specialized gui test cases that are effective at detecting gui faults. the model will be extended to develop new test oracles, new coverage criteria for guis, and new regression testing techniques. moreover, this research will empirically evaluate the developed techniques.
system acquisition based on software product assessment. the procurement of complex software product involves many risks. to properly assess and manage those risks, bell canada has developed methods and tools that combine process capability assessment with a static analysis based software product assessment. this paper describes the software product assessment process that is part of our risk management approach. the process and the tools used to conduct a product assessment are described. the assessment is in part based on static source code metrics and inspections. a summary of the lessons learned since the initial implementation in 1993 is provided. over 20 products totalling more than 100 million lines of code have gone through this process.
comprehension processes during large scale maintenance. we present results of observing professional maintenance engineers working with industrial code at actual maintenance tasks. protocol analysis is used to explore how code understanding might differ for small versus large scale code. the experiment confirms that cognition processes work at all levels of abstraction simultaneously as programmers build a mental model of the code. cognition processes emerged at three levels of aggregation representing lower and higher level strategies of understanding. they show differences in what triggers them and how they achieve their goals. results are useful for defining core competencies which maintenance engineers need for their work and for documentation and development standards
requirements discovery during the testing of safety-critical software. this paper describes the role of requirements discovery during the testing of a safety-critical software system. analysis of problem reports generated by the integration and system testing of an embedded, safety-critical software system identified four common mechanisms for requirements discovery and resolution during testing: (1) incomplete requirements, resolved by changes to the software, (2) unexpected requirements interactions, resolved by changes to the operational procedures, (3) requirements confusion by the testers, resolved by changes to the documentation, and (4) requirements confusion by the testers, resolved by a determination that no change was needed. the experience reported here confirms that requirements discovery during testing is frequently due to communication difficulties and subtle interface issues. the results also suggest that "false positive" problem reports from testing (in which the software behaves correctly but unexpectedly) provide a rich source of requirements information that can be used to reduce operational anomalies in critical systems.
evaluation of mutation testing for object-oriented programs. the effectiveness of mutation testing depends heavily on the types of faults that the mutation operators are designed to represent. thus, the quality of the mutation operators is key to mutation testing. although, mutation operators for object-oriented languages have previously been presented, little research has been done to show the usefulness of the class mutation operators. to assess the usefulness of class mutation operators, we conducted two empirical studies. in the first study, we examine the number and kinds of mutants that are generated for object-oriented programs. in the second study, we investigate the way in which class mutation operators model faults that are not detected by traditional mutation testing. we conducted our studies using a well-known object-oriented system, bcel.
an adaptable generation approach to agenda management. as software engineering efforts move to more complex, distributed environments, coordinating the activities of people and tools becomes very important. while groupware systems address user level communication needs and distributed computing technologies address tool level communication needs, few attempts have been made to synthesize the common needs of both. this paper describes our attempt to do exactly that. we describe a framework for generating an agenda management system (ams) from a specification of the system's requirements. the framework can meet a variety of requirements and produces a customized ams appropriate for use by both humans and software tools. the framework and generated system support evolution in several ways, allowing existing systems to be extended as requirements change. we also describe our experiences using this approach to create an ams to support a process programming environment
mujava: a mutation system for java. mutation testing is a valuable experimental research technique that has been used in many studies. it has been experimentally compared with other test criteria, and also used to support experimental comparisons of other test criteria, by using mutants as a method to create faults. in effect, mutation is often used as a ``gold standard'' for experimental evaluations of test methods. although mutation testing is powerful, it is a complicated and computationally expensive testing method. therefore, automated tool support is indispensable for conducting mutation testing. this demo presents a publicly available mutation system for java that supports both method-level mutants and class-level mutants. mujava can be freely downloaded and installed with relative ease under both unix and windows. mujava is offered as a free service to the community and we hope that it will promote the use of mutation analysis for experimental research in software testing.
agile software reuse recommender. no abstract available
a model for program complexity analysis. a frequently stated objective of structured programming is to control program complexity. however, since the notion of complexity is not well under-stood and the existing techniques for measuring complexity are crude, it is difficult to determine if indeed structured programming can achieve this objective. the purpose of this paper is two-fold: to discuss the probable sources of complexity in a well-structured program to present a methodology for measuring and controlling complexity in a well-structured program.
experiences in assessing product family software architecture for evolution. software architecture assessments are a means to detect architectural problems before the bulk of development work is done. they facilitate planning of improvement activities early in the lifecycle and allow limiting the changes on any existing software. this is particularly beneficial when the architecture has been planned to (or already does) support a whole product family, or a set of products that share common requirements, architecture, components or code. as the family requirements evolve and new products are added, the need to assess the evolvability of the existing architecture is vital. i illustrate two assessment case studies i have recently worked on in the mobile telephone software domain: the symbian operating system platform and the network resource access control software system. the former assessment has been carried out as a task within the european project esaps, while the latter has been performed solely by nokia. by means of simple experimental data, i show evidence of the usefulness of architectural assessment as rated by the participating stakeholders. both assessments have led to the identification of previously unknown architectural defects, and to the consequent planning of improvement initiatives. in both cases, stakeholders noted that a number of side benefits, including improvement of communication and architectural documentation, were also of considerable importance. i illustrate the lessons we have learned, and outline suggestions for future research and experimentation.
sql dom: compile time checking of dynamic sql statements. most object oriented applications that involve persistent data interact with a relational database. the most common interaction mechanism is a call level interface (cli) such as odbc or jdbc. while there are many advantages to using a cli -- expressive power and performance being two of the most key -- there are also drawbacks. applications communicate through a cli by constructing strings that contain sql statements. these sql statements are only checked for correctness at runtime, tend to be fragile and are vulnerable to sql injection attacks. to solve these and other problems, we present the sql dom: a set of classes that are strongly-typed to a database schema. instead of string manipulation, these classes are used to generate sql statements. we show how to extract the sql dom automatically from an existing database schema, demonstrate its applicability to solve the mentioned problems, and evaluate its performance.
system dynamics modeling of an inspection-based process. a dynamic simulation model of an inspection-based software lifecycle process has been developed to support quantitative process evaluation. the model serves to examine the effects of inspection practices on cost, scheduling and quality throughout the lifecycle. it uses system dynamics to model the interrelated flows of tasks, errors and personnel throughout different development phases and is calibrated to industrial data. if extends previous software project dynamics research by examining an inspection-based process with an original model, integrating it with a knowledge-based method for risk assessment and cost estimation, and using an alternative modeling platform. while specific enough to investigate inspection practices, it is sufficiently general to incorporate changes for other phenomena. it demonstrates the effects of performing inspections or not, the effectiveness of varied inspection policies, and the effects of other managerial policies such as manpower allocation. the results of testing indicate a valid model that can be used for process evaluation and project planning, and can serve as a framework for incorporating other dynamic process factors.
the impact of pair programming on student performance, perception and persistence. this study examined the effectiveness of pair programming in four lecture sections of a large introductory programming course. we were particularly interested in assessing how the use of pair programming affects student performance and decisions to pursue computer science related majors. we found that students who used pair programming produced better programs, were more confident in their solutions, and enjoyed completing the assignments more than students who programmed alone. moreover, pairing students were significantly more likely than non-pairing students to complete the course, and consequently to pass it. among those who completed the course, pairers performed as well on the final exam as non-pairers, were significantly more likely to be registered as computer science related majors one year later, and to have taken subsequent programming courses. our findings suggest that not only does pairing not compromise students' learning, but that it may enhance the quality of their programs and encourage them to pursue computer science degrees.
operations for programming in the all. a primary goal of software engineering is to improve the process of software development. it is being recognised that recent integrated programming environments have made significant progress towards this aim. this paper describes new operations, suitable for such environments, which are applicable in a much wider scope of programming, termed here as programming in the all. development of software in this new scope is carried out incrementally in program fragments of various types, called fragtypes. fragtypes range from a simple expression type to a complete subsystem type, and therefore are suited to the development of non-trivial software. the proposed operations on fragtypes have been incorporated in the design of the programming environment mupe-2 for modula-2, which is currently under development at mcgill university.
model based process assessments. the authors present an approach that combines process modeling with process assessments. they use the structured analysis and design technique (sadt) modeling notation (d.a. marca and c.l. mcgowan, 1988). the dod cim initiative has standardized on a subset of sadt, called idef0, to model business processes. a sadt (idef0) model was created of a large software maintenance process and the model led to process improvements that might have been missed otherwise. this model based process assessment approach is described as a process in its own right
impact of commercial off-the-shelf (cots) software on the interface between systems and software engineering. this presentation examines the changes in the interface between systems engineering and software engineering which are required to make effective use of commercial off-the-shelf software products, especially in large or complex systems.
the translation and compatibility of sequel and query by example. the problem of the translation and compatibility of high level data base query languages is addressed via a case study of the languages sequel and query by example. in particular, an algorithm for translating queries on a relational data base stated in query by example into queries expressed in sequel is introduced. this algorithm is used as a vehicle to describe a consistent interpretation of the semantics of sequel and query by example. the compatibility of query by example and sequel is briefly discussed. examples of the operation of the algorithm are presented.
a general framework for formalizing uml with formal languages. informal and graphical modeling techniques enable developers to construct abstract representations of systems. object-oriented modeling techniques further facilitate the development process. the unified modeling language (uml), an object-oriented modeling approach, could be broad enough in scope to represent a variety of domains and gain widespread use. currently, uml comprises several different notations with no formal semantics attached to the individual diagrams. therefore, it is not possible to apply rigorous automated analysis or to execute a uml model in order to test its behavior, short of writing code and performing exhaustive testing. we introduce a general framework for formalizing a subset of uml diagrams in terms of different formal languages based on a homomorphic mapping between metamodels describing uml and the formal language. this framework enables the construction of a consistent set of rules for transforming uml models into specifications in the formal language. the resulting specifications derived from uml diagrams enable either execution through simulation or analysis through model checking, using existing tools. this paper describes the use of this framework for formalizing uml to model and analyze embedded systems. a prototype system for generating the formal specifications and results from an industrial case study are also described.
a language and environment for architecture-based software development and evolution. software architectures have the potential to substantially improve the development and evolution of large, complex, multi-lingual, multi-platform, long-running systems. however, in order to achieve this potential, specific techniques for architecture-based modeling, analysis, and evolution must be provided. furthermore, one cannot fully benefit from such techniques unless support for mapping an architecture to an implementation also exists. this paper motivates and presents one such approach, which is an outgrowth of our experience with systems developed and evolved according to the c2 architectural style. we describe an architecture description language (adl) specifically designed to support architecture-based evolution and discuss the kinds of evolution the language supports. we then describe a component-based environment that enables modeling, analysis, and evolution of architectures expressed in the adl, as well as mapping of architectural models to an implementation infrastructure. the architecture of the environment itself can be evolved easily to support multiple adls, kinds of analyses, architectural styles, and implementation platforms. our approach is fully reflexive: the environment can be used to describe, analyze, evolve, and (partially) implement itself, using the very adl it supports. an existing architecture is used throughout the paper to provide illustrations and examples.
second international workshop on interdisciplinary software engineering research (wiser). wiser is a series of international workshops that focus on identifying and transferring techniques from other disciplines that might usefully be applied to software engineering research and practice.the workshops address this topic through presentations and discussions of both actual case studies and of ways in which potentially useful approaches can be identified, adapted and adopted within software engineering.
evolving legacy systems using feature engineering and cbse. this dissertation explores the relationships between feature engineering, cbse, and software evolution. software endusers and developers have different perspectives of a software system, resulting in a complexity gap between user expectations and the software functionality [2]. this gap together with aging code has resulted in lost assets for many organizations. by combining feature engineering and cbse, legacy code can be modernized so that many organizations can benefit from this technique. in our approach, we identify the legacy system's features through test cases and test suites. we then apply our code carving techniques to identify the code associated with those features and extract the code to create components. we validate our results in two ways. first, by inserting the component(s) back into the legacy system to continue functioning. second, by measuring the cost of adding a new feature after applying the methodology.
evolving legacy system features into fine-grained components. there is a constant need for practical, efficient, and cost-effective software evolution techniques. we propose a novel evolution methodology that integrates the concepts of features, regression tests, and component-based software engineering (cbse). regression test cases are untapped resources, full of information about system features. by exercising each feature with its associated test cases using code profilers and similar tools, code can be located and refactored to create components. these components are then inserted back into the legacy system, ensuring a working system structure. this methodology is divided into three parts. part one identifies the source code associated with features that need evolution. part two deals with creating components and part three measures results. by applying this methodology, afs has successfully restructured its enterprise legacy system and reduced the costs of future maintenance. additionally, the components that were refactored from the legacy system are currently being used within a web-enabled application.
towards a taxonomy of software connectors. software systems of today are frequently composed from prefabricated, heterogeneous components that provide complex functionality and engage in complex interactions. existing research on component-based development has mostly focused on component structure, interfaces, and functionality. recently, software architecture has emerged as an area that also places significant importance on component interactions, embodied in the notion of software connectors. however, the current level of understanding and support for connectors has been insufficient. this has resulted in their inconsistent treatment and a notable lack of understanding of what the fundamental building blocks of software interaction are and how they can be composed into more complex interactions. this paper attempts to address this problem. it presents a comprehensive classification framework and taxonomy of software connectors. the taxonomy is obtained through an extensive analysis of existing component interactions. the taxonomy is used both to understand existing software connectors and to suggest new, unprecedented connectors. we demonstrate the use of the taxonomy on the architecture of a large, existing system.
a cross-program investigation of students' perceptions of agile methods. research was conducted on using agile methods in software engineering education. this paper explores the perceptions of students from five different academic levels of agile practices. information has been gathered through the collection of quantitative and qualitative data over three academic years, and analysis reveals student experiences, mainly positive but also some negative. student opinions indicate the preference to continue to use agile practices at the workplace if allowed. a way these findings may potentially be extrapolated to the industrial settings is discussed. finally, this report should encourage other academics considering adoption of agile methods in their computer science or software engineering curricula.
using a goal-driven approach to generate test cases for guis. the widespread use of guis for interacting with software is leading to the construction of more and more complex guis. with the growing complexity comes challenges in testing the correctness of a gui and the underlying software. we present a new technique to automatically generate test cases for guis that exploits planning, a well developed and used technique in artificial intelligence. given a set of operators, an initial state and a goal state, a planner produces a sequence of the operators that will change the initial state to the goal state. our test case generation technique first analyzes a gui and derives hierarchical planning operators from the actions in the gui. the test designer determines the preconditions and effects of the hierarchical operators, which are then input into a planning system. with the knowledge of the gui and the way in which the user will interact with the gui, the test designer creates sets of initial and goal states. given these initial and final states of the gui, a hierarchical planner produces plans, or a set of test cases, that enable the goal state to be reached. our technique has the additional benefit of putting verification commands into the test cases automatically. we implemented our technique by developing the gui analyzer and extending a planner. we generated test cases for microsoft's word-pad to demonstrate the viability and practicality of the approach.
skoll: distributed continuous quality assurance. quality assurance (qa) tasks, such as testing, profiling,and performance evaluation, have historically been donein-house on developer-generated workloads and regressionsuites. since this approach is inadequate for many systems,tools and processes are being developed to improve softwarequality by increasing user participation in the qa process.a limitation of these approaches is that they focus onisolated mechanisms, not on the coordination and controlpolicies and tools needed to make the global qa process efficient, effective, and scalable. to address these issues, we have initiated the skoll project, which is developing and validatingnovel software qa processes and tools that leveragethe extensive computing resources of worldwide user communitiesin a distributed, continuous manner to significantlyand rapidly improve software quality. this paper providesseveral contributions to the study of distributed continuousqa. first, it illustrates the structure and functionality ofa generic around-the-world, around-the-clock qa processand describes several sophisticated tools that support thisprocess. second, it describes several qa scenarios builtusing these tools and process. finally, it presents a feasibilitystudy applying these scenarios to a 1mloc+ softwarepackage called ace+tao. while much work remains to bedone, the study suggests that the skoll process and toolseffectively manage and control distributed, continuous qaprocesses. using skoll we rapidly identified problems thathad taken the ace+tao developers substantially longer tofind and several of which had previously not been found.moreover, automatic analysis of qa task results often provideddevelopers information that quickly led them to theroot cause of the problems.
validation methods for calibrating software effort models. coconut calibrates effort estimation models using an ex-haustive search over the space of calibration parameters in a cocomo i model. this technique is much simpler than other effort estimation method yet yields pred levels com-parable to those other methods. also, it does so with less project data and fewer attributes (no scale factors). how-ever, a comparison between coconut and other methods is complicated by differences in the experimental methods used for effort estimation. a review of those experimental methods concludes that software effort estimation models should be calibrated to local data using incremental hold-out (not jack knife) studies, combined with randomization and hypothesis testing, repeated a statistically significant number of times.
the grand challenge of trusted components. reusable components equipped with strict guarantees of quality can help reestablish software development on a stronger footing, by taking advantage of the scaling effect of reuse to justify the extra effort of ensuring impeccable quality. this discussion examines work intended to help the concept of trusted component brings its full potential to the software industry, along two complementary directions: a "low road" leading to qualification of existing components, and a "high road" aimed at the production of components with fully proved correctness properties.
the software knowledge base. we describe a system for maintaining useful information about a software project. the &ldquo;software knowledge base&rdquo; keeps track of software components and their properties; these properties are described through binary relations and the constraints that these relations must satisfy. the relations and constraints are entirely user-definable, although a set of predefined libraries of relations with associated constraints is provided for some of the most important aspects of software development (specification, design, implementation, testing, project management). the use of the binary relational model for describing the properties of software is backed by a theoretical study of the relations and constraints which play an important role in software development.
data mining library reuse patterns using generalized association rules. in this paper, we show how data mining can be used to discover library reuse patterns in existing applications. specifically, we consider the problem of discovering library classes and member functions that are typically reused in combination by application classes. this paper improves upon our earlier research using &ldquo;association rules&rdquo; [8] by taking into account the inheritance hierarchy using &ldquo;generalized association rules&rdquo;. this turns out to be a non-trivial but worthwhile endeavor.by browsing generalized association rules, a developer can discover patterns in library usage in a way that takes into account inheritance relationships. for example, such a rule might tell us that application classes that inherit from a particular library class often instantiate another class or one of its descendents. we illustrate the approach using our tool, codeweb, by demonstrating characteristic ways in which applications reuse classes in the kde application framework.
assessing software libraries by browsing similar classes, functions and relationships. comparing and contrasting a set of software libraries is useful for reuse related activities such as selecting a library from among several candidates or porting an application from one library to another. the current state of the art in assessing libraries relies on qualitative methods. to reduce costs and/or assess a large collection of libraries, automation is necessary. although there are tools that help a developer examine an individual library in terms of architecture, style, etc., we know of no tools that help the developer directly compare several libraries. with existing tools, the user must manually integrate the knowledge learned about each library. automation to help developers directly compare and contrast libraries requires matching of similar components (such as classes and functions) across libraries. this is different than the traditional component retrieval problem in which components are returned that best match a user's query. rather, we need to find those components that are similar across the libraries under consideration. in this paper, we show how this kind of matching can be done.
helping users avoid bugs in gui applications. in this paper, we propose a method to help users avoid bugs in gui applications. in particular, users would use the application normally and report bugs that they encounter to prevent anyone -- including themselves -- from encountering those bugs again. when a user attempts an action that has led to problems in the past, he/she will receive a warning and will be given the opportunity to abort the action -- thus avoiding the bug altogether and keeping the application stable. of course, bugs should be fixed eventually by the application developers, but our approach allows application users to collaboratively help each other avoid bugs -- thus making the application more usable in the meantime. we demonstrate this approach using our "stabilizer" prototype. we also include a preliminary evaluation of the stabilizer's bug prediction.
formalizing design patterns. design patterns facilitate reuse of good design practices. they are typically given by using conventional notations that lack well-defined semantics and, therefore reasoning about their behaviors requires formalization. even when formalized, conventional communication abstractions may lead to too laborious formalizations when addressing the temporal behavior of a pattern as a whole instead of behaviors local to its components. we show that rigorous reasoning can be eased by formalizing temporal behaviors of patterns in terms of high-level abstractions of communication, and that by using property-preserving refinements, specifications can be naturally composed by using patterns as building blocks
"how do i know what i have to do?": the role of the inquiry culture in requirements communication for distributed software development projects. as software specifications for complex systems are practically never 100% complete and consistent, the recipient of the specification needs domain knowledge in order to decide which parts of the system are specified clearly and which parts are specified ambiguously and thus need inquiry to achieve a more detailed specification. in this paper we classify 16 different situations (states) of requirements communication and analyze, based on a state diagram, how a mature inquiry culture can help to initiate transitions from undesirable states into more desirable states. in a case study the inquiry practices of a very large software development organization are shown. knowledge networks within the organization play an important role in building up a mature inquiry culture.
a closer look at iteration: the self stabilizing capability of loops. let p be an iterative program on domain d, with state s. a close look at the structure of the loop invariant of p reveals that p has a desirable self stabilizing property: if during the computation, an error causes the state to take a contaminated value s', then, under some conditions, it is possible to recover from this contamination without knowing any previous correct state. this feature contrasts with the classical error recovery mechanisms which equate error recovery with the retrieval of a previously saved correct state, and the backtracking of the computation.
an integrated cost model for software reuse. several cost models have been proposed in the past for estimating, predicting, and analyzing the costs of software reuse. in this paper we analyze existing models, explain their variance, and propose a tool-supported comprehensive model that encompasses most of the existing models.
a system for classifying program verification methods: assigning meanings to program verification methods. many program verification methods are known nowadays: inductive assertion method, invariant assertion method, intermittent assertion method, symbolic execution method, subgoal induction method, computational induction method, structural induction method, fixpoint theory of programs. this paper presents a simple classification of them.
completely monotone regression estimates of software failure rates. a new method for estimating the present failure rate of a program is presented. a crude nonparametric estimate of the failure rate function is obtained from past failure times. this estimate is then smoothed by fitting a completely monotonic function, which is the solution of a quadratic programming problem. the value of the smoothed function at present time is used as the estimate of present failure rate. a monte carlo study gives an indication of how well this method works.
independent on-line monitoring of evolving systems. we argue that the trustworthiness of evolving software systems can be significantly enhanced by a rigorous process of independent on-line monitoring. such monitoring can prevent fraud, encourage careful maintenance, and serve as an early detector of irregularities in the state and behavior of a system. unfortunately, there is a conflict between the concepts of on-line and independent monitoring. this conflict is due to the fact that on-line monitoring requires the embedding of some kinds of sensors in the base-system. but the introduction of such sensors requires a degree of cooperation with the developers of the base system, and may interfere with the operations of that system, contrary to the requirements of independent monitoring. we describe a way to resolve this conflict by applying the concept of law-governed architecture.
ensuring integrity by adding obligations to privileges. conventional authorization mechanisms provide actors with permissions to act, without the actor ever incurring any obligations as a result of executing the permitted action. there exist, however, many situations where system integrity requires that certain actions always be followed by others, within some reasonable time frame. we propose an extension to conventional authorization which allows the explicit association of obligations with permissions, and enforces them. we demonstrate that the extended mechanism can be used to support and enforce several general types of control policies and integrity constraints which are otherwise difficult or impossible to support.
an evaluation of the paired comparisons method for software sizing. this paper evaluates the accuracy, precision and robustness of the paired comparisons method for software sizing and concludes that the results produced by it are superior to the so called &ldquo;expert&rdquo; approaches.
hdd: hierarchical delta debugging. inputs causing a program to fail are usually large and often contain information irrelevant to the failure. it thus helps debugging to simplify program inputs. the delta debugging algorithm is a general technique applicable to minimizing all failure-inducing inputs for more effective debugging. in this paper, we present hdd, a simple but effective algorithm that significantly speeds up delta debugging and increases its output quality on tree structured inputs such as xml. instead of treating the inputs as one flat atomic list, we apply delta debugging to the very structure of the data. in particular, we apply the original delta debugging algorithm to each level of a program's input, working from the coarsest to the finest levels. we are thus able to prune the large irrelevant portions of the input early. all the generated input configurations are syntactically valid, reducing the number of inconclusive configurations that need to be tested and accordingly the amount of time spent simplifying. we have implemented hdd and evaluated it on a number of real failure-inducing inputs from the gcc and mozilla bugzilla databases. our hierarchical delta debugging algorithm produces simpler outputs and takes orders of magnitude fewer test cases than the original delta debugging algorithm. it is able to scale to inputs of considerable size that the original delta debugging algorithm cannot process in practice. we argue that hdd is an effective tool for automatic debugging of programs expecting structured inputs.
demand-driven structural testing with dynamic instrumentation. producing reliable and robust software has become one of the most important software development concerns in recent years. testing is a process by which software quality can be assured through the collection of information. while testing can improve software reliability, current tools typically are inflexible and have high over-heads, making it challenging to test large software projects. in this paper, we describe a new scalable and flexible framework for testing programs with a novel demand-driven approach based on execution paths to implement test coverage. this technique uses dynamic instrumentation on the binary code that can be inserted and removed on-the-fly to keep performance and memory overheads low. we describe and evaluate implementations of the framework for branch, node and defuse testing of java programs. experimental results for branch testing show that our approach has, on average, a 1.6 speed up over static instrumentation and also uses less memory.
effects of software industry structure on a research framework for empirical software engineering. the authors describe a new research framework for applying empirical software engineering methods in industrial practice and accomplishments in using it. the selected target for applying the framework is a governmentally funded software development project involving multiple vendors. this project involved in-process project data measurement in real time, data sharing with industry and academia, data analysis, and feedback to the project members. today the project is in the system integration process. this paper shows the value of this research framework and describes issues of empirical data sharing between industry and academia which have emerged while using it. this experiment raised two major issues. one is the necessity of a new research framework for project measurement called the "macro measurement tool". the other is effects of the software industry structure on this framework.
a reliability model combining representative and directed testing. directed testing methods, such as functional or structural testing, have been criticized for a lack of quantifiable results. representative testing permits reliability modeling, which provides the desired quantification. over time, however, representative testing becomes inherently less effective as a means of improving the actual quality of the software under test. a model is presented which permits representative and directed testing to be used in conjunction. representative testing can be used early, when the rate of fault revelation is high. later results from directed testing can be used to update the reliability estimates conventionally associated with representative methods. the key to this combination is shifting the observed random variable from interfailure time to a post-mortem analysis of the debugged faults, using order statistics to combine the observed failure rates of faults no matter how those faults were detected.
some considerations in database application programming. this paper describes the experimental approach to achieve the higher productivity, reliability, maintainability and the performance in the database application programming or of the programs. we have practiced the structured programming on the database processings in order to write the reliable database application programs. then we introduce the simulated forms of the basic control structures in cobol which is the host language, the structured representations of the dml (data manipulation language) statements to be precompiled to the cobol statements, and the programming standards firstly, and the program structuring guidelines to the highly efficient database processings nextly, based on the fact that the database processing performance is affected by the data reference behavior which is called as a data locality of the database application program. the way to structure the database application program which has a good data locality and the tool which is useful to examine the program structure are described. finally, we describe the results got through the experiments.
toward an effective software reliability evaluation. effective software reliability evaluation requires theories of software reliability which define and deal with software reliability quantitatively, technologies for reliability data measurement and data analysis, techniques to estimate or predict software reliability, and practical reliability evaluation methodologies which effectively reflect the characteristics of software. this paper assesses the extents to which these requirements are currently met, and introduces improved approaches for an effective software reliability evaluation. introduced are the methodologies for software reliability evaluation and the software reliability evaluation-aid tools.
cocomo evaluation and tailoring. this paper gives the results of our efforts to evaluate and tailor a software cost estimation model called cocomo.1 the precise data for the analysis was collected from the records of 33 completed projects. we evaluate the original cocomo model, which overestimates the efforts required to develop software in our environment. then we tailor the model according to the cocomo tailoring methodology. to increase the precision and stability of the tailored model, we delete some unnecessary cost drivers in a heuristic manner with the aid of nonparametric statistical method. as a result, we can greatly improve the model. finally we suggest a method to tailor the cocomo effort multipliers. we believe we maintain the same direction as the originator's philosophy, and that our efforts can contribute to the progress of the cocomo tailoring methodology.
software metrics using deviation value. the deviation-value (d-value) is a new measure for software data involved during software development. the d-value provides an alternative to software metrics based upon &ldquo;per number of lines of code&rdquo; such as error rate (number of errors per thousand lines of code) and documentation rate (number of pages of module design documentation per thousand lines of code). using d-value, the data of software modules are much more fairly evaluated than these conventional metrics.this paper presents the derivation of the d-value using the theoretical background of a control chart called u chart and weighted regression analysis. the advantage of using the d-value rather than metrics based upon &ldquo;per number of lines of code&rdquo; is demonstrated through an analysis of the data of four projects. the d-value is used to find the data items which actually relate to software quality, and we find that the quality of each module measured by d-value becomes better as the documentation rate d-value increases. finally, using the theory behind the d-value, a new software acceptance guideline is discussed.
the portable communication protocol program compas for data terminal systems. the communication protocol program compas (dcna communication processing packages), which is portable to various data terminal systems, has been developed according to the data communication network architecture dcna. the method used in compas and its practicability are described in this paper.
analyzing effects of cost estimation accuracy on quality and productivity. this paper discusses the effects of estimation accuracy for software development cost on both the quality of the delivered code and the productivity of the development team. the estimation accuracy is measured by metric re (relative error). the quality and productivity are measured by metrics fq (field quality) and tp (team productivity). using actual project data on thirty-one projects at a certain company, the following are verified by correlation analysis and testing of statistical hypotheses. there is a high correlation between the faithfulness of the development plan to standards and the value of re (a coefficient of correlation between them is -0.60). both fq and tp are significantly different between projects with -10%<re<+10% and projects with re&ges;+10% (the level of significance is chosen as 0.05)
characterization of risky projects based on project managers' evaluation. during the process of software development, senior managers often find indications that projects are risky and take appropriate actions to recover them from this dangerous status. if senior managers fail to detect such risks, it is possible that such projects may collapse completely.in this paper, we propose a new scheme for the characterization of risky projects based on an evaluation by the project manager. in order to acquire the relevant data to make such an assessment, we first designed a questionnaire from five viewpoints within the projects: requirements, estimations, team organization, planning capability and project management activities. each of these viewpoints consisted of a number of concrete questions. we then analyzed the responses to the questionnaires as provided by project managers by applying a logistic regression analysis. that is, we determined the coefficients of the logistic model from a set of the questionnaire responses. the experimental results using actual project data in company a showed that 27 projects out of 32 were predicted correctly. thus we would expect that the proposed characterizing scheme is the first step toward predicting which projects are risky at an early phase of the development.
comparison of concurrent software reliability models. a comparsion of three concurrent software reliability models (littlewood/verrall, musa, and goel/okumoto) has been performed. a set of criteria for evaluating a software reliability model is devoloped and a method for model assessment is presented. then this assessment method is applied to the three selected models.
a case study of open source software development: the apache server. according to its proponents, open source style software development has the capacity to compete successfully, and perhaps in many cases displace, traditional commercial development methods. in order to begin investigating such claims, we examine the development process of a major open source application, the apache web server. by using email archives of source code change history and problem reports we quantify aspects of developer participation, core team size, code ownership, productivity, defect density, and problem resolution interval for this oss project. this analysis reveals a unique process, which performs well on important measures. we conclude that hybrid forms of development that borrow the most effective techniques from both the oss and commercial worlds may lead to high performance software processes.
expertise browser: a quantitative approach to identifying expertise. finding relevant expertise is a critical need in collaborative software engineering, particularly in geographically distributed developments. we introduce a tool that uses data from change management systems to locate people with desired expertise. it uses a quantification of experience, and presents evidence to validate this quantification as a measure of expertise. the tool enables developers, for example, easily to distinguish someone who has worked only briefly in a particular area of the code from someone who has more extensive experience, and to locate people with broad expertise throughout large parts of the product, such as module or even subsystems. in addition, it allows a user to discover expertise profiles for individuals or organizations. data from a deployment of the tool in a large software development organization shows that newer, remote sites tend to use the tool for expertise location more frequently. larger, more established sites used the tool to find expertise profiles for people or organizations. we conclude by describing extensions that provide continuous awareness of ongoing work and an interactive, quantitative resume.
understanding and predicting effort in software projects. we set out to answer a question we were asked by software project management: how much effort remains to be spent on a specific software project and how will that effort be distributed over time? to answer this question we propose a model based on the concept that each modification to software may cause repairs at some later time and investigate its theoretical properties and application to several projects in avaya to predict and plan development resource allocation. our model presents a novel unified framework to investigate and predict effort, schedule, and defects of a software project. the results of applying the model confirm a fundamental relationship between the new feature and defect repair changes and demonstrate its predictive properties.
predictors of customer perceived software quality. predicting software quality as perceived by a customer may allow an organization to adjust deployment to meet the quality expectations of its customers, to allocate the appropriate amount of maintenance resources, and to direct quality improvement efforts to maximize the return on investment. however, customer perceived quality may be affected not simply by the software content and the development process, but also by a number of other factors including deployment issues, amount of usage, software platform, and hardware configurations. we predict customer perceived quality as measured by various service interactions, including software defect reports, requests for assistance, and field technician dispatches using the afore mentioned and other factors for a large telecommunications software system. we employ the non-intrusive data gathering technique of using existing data captured in automated project monitoring and tracking systems as well as customer support and tracking systems. we find that the effects of deployment schedule, hardware configurations, and software platform can increase the probability of observing a software failure by more than 20 times. furthermore, we find that the factors affect all quality measures in a similar fashion. our approach can be applied at other organizations, and we suggest methods to independently validate and replicate our results.
academic software engineering: what is and what could be? results of the first annual survey for international se programs. according to data received from an international survey, almost 6800 students are enrolled in software engineering degree programs in 11 countries, as of january, 2001. a total of 94 academic programs in software engineering are in place at 60 univcrsities with 350 full-time faculty and nearly 200 part-time faculty teaching hundreds of undergraduate and graduate courses in the discipline. over 5500 people have obtained degrees in software engineering since 1979. the authors are conducting the first of an ongoing annual survey of international academic software engineering programs, as a joint acm/ieee-cs project. this status report covers: history, audience, initial survey, initial partial results available on the www, request for evaluation of www-site, request for additional questions for next version of survey, time-line for next version of the survey, &ldquo;lessons learned,&rdquo; and some future directions. the annual report and survey results will be posted on a wide variety of web pages. a more current report, based on the sabbatical of the first author, will be presented at the conference. the sabbatical involves the initial development of an &ldquo;international software engineering university consortium - iseuc.&rdquo; a sample scenario for an employee in industry who becomes a student in iseuc is given.
effort estimation of use cases for incremental large-scale software development. this paper describes an industrial study of an effort estimation method based on use cases, the use case points method. the original method was adapted to incremental development and evaluated on a large industrial system with modification of software from the previous release. we modified the following elements of the original method: a) complexity assessment of actors and use cases, and b) the handling of non-functional requirements and team factors that may affect effort. for incremental development, we added two elements to the method: c) counting both all and the modified actors and transactions of use cases, and d) effort estimation for secondary changes of software not reflected in use cases. we finally extended the method to: e) cover all development effort in a very large project. the method was calibrated using data from one release and it produced an estimate for the successive release that was only 17% lower than the actual effort. the study identified factors affecting effort on large projects with incremental development. it also showed how these factors can be calibrated for a specific context and produce relatively accurate estimates.
an empirical study of software reuse vs. defect-density and stability. the paper describes results of an empirical study,where some hypotheses about the impact of reuse ondefect-density and stability, and about the impact ofcomponent size on defects and defect-density in thecontext of reuse are assessed, using historical data ("datamining") on defects, modification rate, and software sizeof a large-scale telecom system developed by ericsson.the analysis showed that reused components have lowerdefect-density than non-reused ones. reused componentshave more defects with highest severity than the totaldistribution, but less defects after delivery, which showsthat that these are given higher priority to fix. there arean increasing number of defects with component size fornon-reused components, but not for reused components.reused components were less modified (more stable) thannon-reused ones between successive releases, even ifreused components must incorporate evolvingrequirements from several application products. thestudy furthermore revealed inconsistencies andweaknesses in the existing defect reporting system, byanalyzing data that was hardly treated systematicallybefore.
methods for improving controlled experimentation in software engineering. within the past decade computer science researchers have begun to use controlled experimentation to address questions of human factors in the programming process. however, some of this work has been criticized for lack of experimental controls, insufficient sample sizes, and questionable generality. in a study of 160 student and professional programmers, several key biographical factors have been identified which account for a large proportion of performance variation on typical experimental tasks. the study has implications for subject selection and interpretation of results in software experimentation. our findings should lead to improved experimental design and analysis techniques with increased confidence in the results of software psychology studies.
pdas: an assistant for detailed design and implementation of programs. the development of reliable documents is an important challenge facing the software industry today. this paper presents the programming and design assist system (pdas), which supports detailed design and implementation of system programs. pdas uses a design language as the kernel of the system. japanese/english documents and programs are generated from specifications written in the design language. the design language is a forms-oriented language based on pdl. to standardize the level of abstraction of document description, the language introduces a data model called a &ldquo;set&rdquo;. the model is an abstraction of linked lists, arrays, queues, and stacks. in operating systems, there are many such data structures, and the ability to simplify their manipulation is very helpful.
evaluating the quality of information models: empirical testing of a conceptual model quality framework. this paper conducts an empirical analysis of a semiotics-based quality framework for quality assuring information models. 192 participants were trained in the concepts of the quality framework, and used it to evaluate models represented in an extended entity relationship (er) language. a randomised, double-blind design was used, in which each participant independently reviewed multiple models and each model was evaluated by multiple reviewers. a combination of quantitative and qualitative analysis techniques were used to evaluate the results, including reliability analysis, validity analysis, interaction analysis, influence analysis, defect pattern analysis and task accuracy analysis. an analysis was also conducted of the framework's likelihood of adoption in practice. the study provides strong support for the validity of the framework and suggests that it is likely to be adopted in practice, but raises questions about its reliability and the ability of participants to use it to accurately identify defects. the research findings provide clear directions for improvement of the framework. the research methodology used provides a general approach to empirical validation of quality frameworks.
project leap: personal process improvement for the differently disciplined. software developers and managers have faced the problem of producing quality software since the beginning of the computer age. many people have studied the software quality problem and have proposed many solutions. we can categorize these different solutions into two groups: (1) "topdown" solutions, that focus on software development as a group effort and (2) "bottom-up" solutions, that focus on the individual software developer. some of the many top-down solutions include: the capability maturity model, clean room development, software quality assurance groups, and formal. technical review. these top down methods help improve the quality of the software, however they may not be enough.
quantifying the value of architecture design decisions: lessons from the field. this paper outlines experiences with using economic criteria to make architecture design decisions. it briefly describes the cbam (cost benefit analysis method) framework applied to estimate the value of architectural strategies in a nasa project, the ecs. this paper describes the practical difficulties and experiences in applying the method to a large real-world system. it concludes with some lessons learned from the experience.
a tool for analyzing and detecting malicious mobile code. we present a tool for analysis and detection of malicious mobile code such as computer viruses and internet worms based on the combined use of code simulation, static code analysis, and os execution emulation. unlike traditional anti-virus methods, the tool directly inspects the code and identifies commonly found malicious behaviors such as mass mailing, self duplication, and registry overwrite without relying on ``pattern files'' that contain ``signatures'' of previously captured samples. the prohibited behaviors are defined separately as security policies at the level of api library function calls in a state-transition like language. the tool also features data flow analysis based on static single assignment forms, which are useful in tracing various values stored in registers and memory locations. the current tool targets at win32 binary programs on intel ia32 architectures and can detect most email virusesslash worms that had spread in the wild in recent years.
investigating and improving a cots-based software development. the work described in this paper is an investigation of cots-based software development within a particular nasa environment, with an emphasis on the processes used. fifteen projects using a cots-based approach were studied and their actual process was documented. this process is evaluated to identify essential differences in comparison to traditional software development. the main differences, and the activities for which projects require more guidance, are requirements definition and cots selection, high level design, integration and testing. starting from these empirical observations, a new process and guidelines for cots-based development are developed and briefly presented. the new process is currently under experimentation.
is software education narrow-minded? a position paper. the content of computer science and software engineering courses needs to be examined so that students are better prepared to cope with the challenges of a rapidly changing software industry.
an incremental project plan: introducing cleanroom method and object-oriented development method. introducing new technologies into a software development process or project often produces both good and bad effects. if it is well planned it will improve both productivity and quality. we present an incremental development process planning approach (idpa) which uses the idea of technical dependency-based assessment of the project planning for a small and stable development team shifting slowly but steadily to a new software paradigm that fits the traditional development process. the project plan was a well-connected set of incremental fragments of improvements with the introduction of new technologies or methods to the previous plans. idpa is a method of assessing each technology or method to be decomposed and scheduled according to the technical dependency at the time of introduction. we also present a case study applying this idea to a real development project, in which object-oriented technology and the cleanroom method were introduced, and present the results of its evaluation
software engineering for distributed applications: the design project. the design project combines a set of new approaches to software engineering for distributed applications. distributed applications may thereby consist of a large, varying number of interacting processes. specific problems encountered with the development of such distributed applications are not suitably reflected by known programming languages and software engineering environments. the design system in its current version integrates consistent approaches specifically suited for distributed application development. these approaches pertain to the areas `language support`, `performance prediction/rapid prototyping`, and `project support environment`. most parts of the design system have been implemented and successfully applied to first sample distributed applications.
applying algorithm animation techniques for program tracing, debugging, and understanding. algorithm animation presents a dynamic visualization of an algorithm or program. this work seeks to bridge the two domains of data structure display and algorithm animation. the application-specific nature of algorithm animation views could be a valuable debugging aid for software developers. a system called lens was developed that allows programmers to rapidly develop animations of their programs. lens supports application-specific semantic program views as seen in many algorithm animation systems, but does not require graphics programming. lens is integrated with a system debugger to support iterative testing and refinement. the authors describe the conceptual model on which lens is based, illustrate how program animations are built with lens, and outline some of the implementation challenges the system presents
rigi - a system for programming-in-the-large. this paper describes rigi, a model and a tool for programming-in-the-large. rigi uses a graph model and abstraction mechanisms to structure and represent the information accumulated during the development process. the objects and relationships of the graph model represent system components and their dependencies. the objects can be arranged in aggregation and generalization hierarchies. the rigi editor assists the designers, programmers, integrators, and maintainers in defining, manipulating, exploring, and understanding, the structure of large, integrated, evolving software systems. rigi was designed to address three of the most difficult problems in the area of programming-in-the-large: the mastery of the structural complexity of large software systems, the effective presentation of development information, and the definition of procedures for checking and maintaining the completeness, consistency, and traceability of system descriptions. thus, the major objective of rigi is to effectively represent and manipulate the building blocks of a software system and their myriad dependencies, thereby aiding the development phases of the project.
case study: extreme programming in a university environment. extreme programming (xp) is a new and controversial software process for small teams. a practical training course at the university of karlsruhe led to the following observations about the key practices of xp. first, it is unclear how to reap the potential benefits of pair programming, although pair programming produces high quality code. second, designing in small increments appears problematic but ensures rapid feedback about the code. third, while automated testing is helpful, writing test cases before coding is a challenge. and last, it is difficult to implement xp without coaching. this paper also provides some guidelines for those starting out with xp.
requirement specification description system in japanese language - jisdos. the syntax of a requirement specification description language should be similar to the language in which the users think. we have developed a system called jisdos in which a user can describe his requirements using a formalized japanese language. the description language, called jpsl, is basically a translation of psl with the syntactic characteristics of the japanese language. pre- and post-processors are added to psa for transformations of jpsl descriptions into psl and conversely to psl reports into jpsl, so that no modification was performed on psl/psa. a user inputs jpsl statements either in katakana (square phonetic characters) or romaji (english alphabetic representation of japanese characters), and he can receive various kinds of reports in hiragana (curved phonetic characters) and kanji (chinese characters). it is concluded that jpsl has a high degree of readability and descriptive power in writing requirement specifications.
algorithm development in the mobile environment. mobility is emerging as a new research field with its own characteristic problems, models, and algorithms. fixed networks are commonplace but the challenges of mobility such as the transient nature of connections, reduced bandwidth, and limited processing power have made incorporating mobility into this existing environment challenging. our contribution to the rapid integration of mobility is the design and development of algorithms in the mobile environment which will serve as a foundation for mobile applications. in this paper, we describe two models for mobility, outline the challenges of each environment, and provide approaches to algorithm development within each model.
separating features in source code: an exploratory study. most software systems are inflexible. reconfiguring a system's modules to add or to delete a feature requires substantial effort. this inflexibility increases the costs of building variants of a system, amongst other problems. new languages and tools that are being developed to provide additional support for separating concerns show promise to help address this problem. however, applying these mechanisms requires determining how to enable a feature to be separated from the codebase. in this paper, we investigate this problem through an exploratory study conducted in the context of two existing systems: gnu.regexp and jftpd. the study consisted of applying three different separation of concern mechanisms&mdash;hyper/j,tm aspectj,tm and a lightweight, lexically-based approach&mdash;to separate features in the two packages. in this paper, we report on the study, providing contributions in two areas. first, we characterize the effect different mechanisms had on the structure of the codebase. second, we characterize the restructuring process required to perform the separations. these characterizations can help researchers to elucidate how the mechanisms may be best used, tool developers to design support to aid the separation process, and early adopters to apply the techniques.
an empirical study of static call graph extractors. informally, a call graph represents calls between entities in a given program. the call graphs that compilers compute to determine the applicability of an optimization must typically be conservative: a call may be omitted only if it can never occur an any execution of the program. numerous software engineering tools also extract call graphs, with the expectation that they will help software engineers increase their understanding of a program. the requirements placed on software engineering tools when computing call graphs are typically more related than for compilers. for example, some false negatives-calls that can in fact take place in some execution of the program, but which are omitted from the call graph-may be acceptable, depending on the understanding task at hand. in this paper we empirically show a consequence of this spectrum of requirements by comparing the c call graphs extracted from three software systems (mapmaker, mosaic, and gee) by five extraction tools (cflow, cia, field, mk-functmap, and rigiparse). a quantitative analysis of the call graphs extracted for each system shows considerable variation, a result that is counterintuitive to many experienced software engineers. a qualitative analysis of these results reveals a number of reasons for this variation: differing treatments of macros, function pointers, input formats, etc. we describe and discuss the study, sketch the design space, and discuss the impact of our study on practitioners, tool developers, and researchers.
meeting the challenges of web application development: the web engineering approach. the web has very rapidly become central to many applications in diverse areas. as our reliance on web-based applications continues to increase and the web systems supporting these applications become more complex, there is growing concern about the manner in which the web-based systems/applications are created and their quality, integrity and maintainability. the development of web-based systems has generally been ad hoc, resulting in poor quality and maintainability. in the recent times, there have been many failures of web applications due to a variety of problems and causes. the way the developers address these problems is critical to deploying successful large-scale web applications.this tutorial addresses these issues and offers a holistic approach to managing the complexity of development of web-based systems and web applications. it highlights the various real-world issues, challenges and considerations in development of large web applications, compared to traditional software development, and recommends the web engineering approach that web/software developers could follow.web engineering deals with systematic, disciplined and quantifiable approaches to development, operation, and maintenance of web-based systems and applications [1-9]. it embodies engineering principles and practices to web application and web site development and draws on software engineering and a number of contributing disciplines.specifically, the tutorial aims to:&bull; highlight the problems, complexity and challenges of web application development relative to software development&bull; offer a holistic approach to development of web applications&bull; present web development methodologies and processes&bull; address the issues of scalability, maintainability, usability, configuration management and other non-technical aspects&bull; recommend suitable web testing and quality assurance approaches&bull; discuss project management issues specific to web developmentthis tutorial is specifically targeted to address the needs of a growing community of software practitioners, web application developers, project managers it and business professionals, ecommerce system implementers, academics, researchers and students.
a logarithmic poisson execution time model for software reliability measurement. a new software reliability model is developed that predicts expected failures (and hence related reliability quantities) as well or better than existing software reliability models, and is simpler than any of the models that approach it in predictive validity. the model incorporates both execution time and calendar time components, each of which is derived. the model is evaluated, using actual data, and compared with other models.
designing an economic-driven evaluation framework for process-oriented software technologies. during the last decade there has been a dramatic increase in the number of paradigms, standards and tools that can be used to realize process-oriented information systems. a major problem neglected in software engineering research so far has been the systematic determination of costs, benefits, and risks that are related to the use of these process-oriented software engineering methods and technologies. this task is quite difficult as the added value is influenced by many drivers. this paper sketches an economic-driven evaluation methodology to analyze costs, benefits, and risks of process-oriented software technologies and corresponding projects. we introduce an evaluation meta model and sketch a formalism to describe economic-driven evaluation scenarios.
exploiting adls to specify architectural styles induced by middleware infrastructures. architecture definition languages (adls) enable the formalization of the architecture of software systems and the execution of preliminary analyses on them. these analyses aim at supporting the identification and solution of design problems in the early stages of software development. we have used adls to describe middleware-induced architectural styles. these styles describe the assumptions and constraints that middleware infrastructures impose on the architecture of systems. our work originates from the belief that the explicit representation of these styles at the architectural level can guide designers in the definition of an architecture compliant with a pre-selected middleware infrastructure, or, conversely can support designers in the identification of the most suitable middleware infrastructure for a specific architecture. in this paper we provide an evaluation of adls as to their suitability for defining middleware-induced architectural styles. we identify new requirements for adls, and we highlight the importance of existing capabilities. although our experimentation starts from an attempt to solve a specific problem, the results we have obtained provide general lessons about adls, learned from defining the architecture of existing, complex, distributed, running systems.
use of software engineering tools in japan. this paper describes the current status of software engineering tool usage by the japanese software industry based upon statistics obtained from several surveys conducted by the japan information services industry association and related organizations. it also analyzes various social and technical factors behind these statistics. practical application of various software engineering tools in japan currently seems to remain at a very low level. some concluding comments will be made suggesting directions for possible future improvements.
toward a software testing and reliability early warning metric suite. the field reliability is measured too late for affordablyguiding corrective action to improve the quality of thesoftware. software developers can benefit from an earlywarning of their reliability while they can still affordablyreact. this early warning can be built from a collection ofinternal metrics. an internal metric, such as the numberof lines of code, is a measure derived from the productitself [15]. an external measure is a measure of a productderived from assessment of the behavior of the system[15]. for example, the number of defects found in test isan external measure. the iso/iec standard [15] statesthat "[i]nternal metrics are of little value unless there isevidence that they are related to external quality."internal metrics can be collected in-process and moreeasily than external metrics. additionally, internalmetrics have been shown to be useful as early indicatorsof externally-visible product quality [1]. for these earlyindicators to be meaningful, they must be related (in astatistically significant and stable way) to the fieldquality/reliability of the product. the validation of suchmetrics requires the convincing demonstration that (1) themetric measures what it purports to measure and (2) themetric is associated with an important external metric,such as field reliability, maintainability, or fault-proneness[12].software metrics have been used as indicators ofsoftware quality [1, 19-21, 23] and fault proneness [8-10,24]. there is a growing body of empirical results thatsupports the theoretical validity of the use of higher-orderearly metrics, such as oo metrics [1] defined bychidamber-kemerer (ck) [6] and the mood [5] oometric suites as predictors of field quality. however,general validity of these metrics (which are oftenunrelated to the actual operational profile of the product)is still open to criticism [7].
use of relative code churn measures to predict system defect density. software systems evolve over time due to changes in requirements, optimization of code, fixes for security and reliability bugs etc. code churn, which measures the changes made to a component over a period of time, quantifies the extent of this change. we present a technique for early prediction of system defect density using a set of relative code churn measures that relate the amount of churn to other variables such as component size and the temporal extent of churn.using statistical regression models, we show that while absolute measures of code churn are poor predictors of defect density, our set of relative measures of code churn is highly predictive of defect density. a case study performed on windows server 2003 indicates the validity of the relative code churn measures as early indicators of system defect density. furthermore, our code churn metric suite is able to discriminate between fault and not fault-prone binaries with an accuracy of 89.0 percent.
effective software architecture design: from global analysis to uml descriptions. it is now generally accepted that separating software architecture into multiple views can help in reducing complexity and in making sound decisions about design trade-offs. our four views are based on current practice; they are loosely coupled, and address different engineering concerns [1]. this tutorial will teach you how global analysis can improve your design, and how to use uml to describe these views. you will learn: (1) the purpose of having separate software architecture views, (2) the difference between using uml for software architecture and the use of uml for designing oo implementations, (3) how to apply global analysis to analyze factors that influence the architecture and to develop strategies that guide the design, (4) the importance of designing for anticipated change to produce more maintainable architectures, and (5) how to incorporate software architecture design in your software process. this tutorial is aimed at experienced software engineers, architects, and technical managers. it is assumed that participants know the basic uml diagrams. experience in developing models and software design is helpful.
static analysis tools as early indicators of pre-release defect density. during software development it is helpful to obtain early estimates of the defect density of software components. such estimates identify fault-prone areas of code requiring further testing. we present an empirical approach for the early prediction of pre-release defect density based on the defects found using static analysis tools. the defects identified by two different static analysis tools are used to fit and predict the actual pre-release defect density for windows server 2003. we show that there exists a strong positive correlation between the static analysis defect density and the pre-release defect density determined by testing. further, the predicted pre-release defect density and the actual pre-release defect density are strongly correlated at a high degree of statistical significance. discriminant analysis shows that the results of static analysis tools can be used to separate high and low quality components with an overall classification rate of 82.91%.
mining metrics to predict component failures. what is it that makes software fail? in an empirical study of the post-release defect history of five microsoft software systems, we found that failure-prone software entities are statistically correlated with code complexity measures. however, there is no single set of complexity metrics that could act as a universally best defect predictor. using principal component analysis on the code metrics, we built regression models that accurately predict the likelihood of post-release defects for new entities. the approach can easily be generalized to arbitrary projects; in particular, predictors obtained from one project can also be significant for new, similar projects.
reuse that pays. a company builds a software system capable of running a diesel engine in a week, and in one case over a weekend, as opposed to the full year that it used to take. another company builds one of its typical systems with 13 software engineers instead of the more than 100 it once required, and at the same time decreases the systems defect rate ten-fold. still another increases its software-intensive product offerings from four per year to 50 per year. imagine being able to use one person to integrate and test 1.5 million source lines of ada for a real-time command-and-control system onboard a ship, with safety-critical requirements? or increasing software productivity four-fold over three years, as another company has done? these organizations all achieved their results through strategic software reuse. we software people have been promising the benefits of reuse for decades. are we finally achieving a reuse strategy that lives up to its hype?
panel: perspectives on software engineering. this panel gives a non-standard view of the future of software engineering. two of the speakers are recent ph.d. graduates in computer science, with expertise in software engineering, who have taken academic positions; as people who will educate the next generation of software engineering practitioners and researchers, they provide a key vision of the future. the other two speakers are senior, having moved from the research community into a world in which they face the problems of engineering software on a daily basis. collectively, along with interactions from the audience, these two often underrepresented perspectives provide a sense of the key directions in which software engineering&mdash; practice, research, and education&mdash;should and must go.
extension and software development. enhancement is the most costly phase of the software development life-cycle. by developing an extension mechanism that allows users to augment a software system without modifying the underlying source code, we address enhancement directly. we describe the design and implementation of the extension mechanism. we also demonstrate how the availability of this flexible mechanism alters not only the enhancement phase of the life-cycle, but the design and implementation phases as well.
an evaluation of required element testing strategies. in this paper we discuss required element testing strategies and present some experimental evaluations of their effectiveness. these strategies use data flow analysis as a basis for developing test cases. the basic strategy (required pairs) is compared with random and branch testing using mutation analysis as a measure of test set effectiveness. extensions of the basic strategy are also studied.
analysis of multi-agent systems based on kaos modeling. the purpose of this study is to reduce the gap between the requirement analysis and analysis phases of developing multi-agent systems. we utilize kaos, one of the goal-oriented analysis methodologies, as a requirement analysis method, and propose a model translation into an analysis model for simple and effective development of multi-agent systems.
supporting reuse by delivering task-relevant and personalized information. technical, cognitive, and social factors inhibit the widespread success of systematic software reuse. our research is primarily concerned with the cognitive and social challenges faced by software developers: how to motivate them to reuse and how to reduce the difficulty of locating components from a large reuse repository. our research has explored a new interaction style between software developers and reuse repository systems enabled by information delivery mechanisms. instead of passively waiting for software developers to explore the reuse repository with explicit queries, information delivery autonomously locates and presents components by using the developers' partially written programs as implicit queries.we have designed, implemented, and evaluated a system called codebroker, which illustrates different techniques to address the essential challenges in information delivery: to make the delivered information relevant to the task-at-hand and personalized to the background knowledge of an individual developer. empirical evaluations of codebroker show that information delivery is effective in promoting reuse.
detecting low usability web pages using quantitative data of users' behavior. the purpose of this research is to detect low usability web pages from the behavior of users, such as browsing time, mouse movement and eye movement. we experimented to investigate the relation between the quantitative data viewing behavior of users and web usability evaluation by subjects. we analyzed the data to detect low usability web pages using discriminant analysis. low usability web pages, 94.4% (17pages / 18pages = detectable pages / low usability pages) were detectable from the moving speed of gazing points and the amount of wheel rolling of a mouse. moreover, this detection reduced the number of web pages which should be evaluated by half (46% = 89 pages / 192 pages = detected pages / all pages).
call-mark slicing: an efficient and economical way of reducing slice. when one debugs and maintain large software, it is very important to localize the scope of concern to small program portions. program slicing is a promising technique for identifying portions of interest. there are many research results on the program slicing method. x static slice, which is a collection of program statements possibly affecting a particular variable's value, limits the scope, but the resulting collections are often still large. a dynamic slice, which is a collection of executed program statements affecting a particular variable's value, generally reduces the scope considerably, but its computation is expensive since the execution trace of the program must be recorded. in this paper, we propose a new slicing technique named call-mark slicing that combines static analysis of a program's structure with lightweight dynamic analysis. the data dependences and control dependences among the program statements are statically analyzed beforehand, and procedure/function invocations (calls) are recorded (marked) during execution. from this information, the dynamic dependences of the variables are explored. this call-mark slicing mechanism has been implemented, and the effectiveness of the method has been investigated.
an editor for documentation in pi-system to support software development and maintenance. a lot of information necessary to maintain a software tends to be lost in conventional documentation. one of the leading causes is considered that the ideas of developers which maintainers will want to know later are not fixed in any documents while the ideas are fresh. to remove the cause, we propose a new description form, called a frame, and construct a system called &pgr;, to support a software through its lifetime. this system gathers all the information with the frames, stores it in a database and provides the various services with respect to programming and documentation. this paper describes the frames and a subsystem, called &pgr;-editor, which provides a user friendly interface to make it easy to gather essential information. by using frames, (1) the associated information around one programming concept can be gathered at one time and (2) lack of necessary information hardly arises. the editor has the distinguished features such as (1) a structure-oriented display editor, (2) facilities to display selective information, provide helpful user guides, and check input errors immediately.
technology transfer macro-process: a practical guide for the effective introduction of technology. in our efforts to increase software development productivity, we have worked to introduce numerous software development techniques and technologies into various target organizations. through these efforts, we have come to understand the difficulties involved in technical transfer. some of the major hurdles that these organizations face during technical transfers are tight schedules and budgets. we have made efforts to lighten this load by using various customization techniques and have defined an overall process called the technology transfer macro-process that we can use to introduce a wide variety of software development techniques and technologies into a target organization.this paper introduces this simple and practical process along with important methods and concepts such as the process plug-in method and the process warehouse, for the introduction of new tools, technologies, and processes within an organization. the issue of initial productivity loss will also be discussed and a suggestion on how to avoid this will be made. these methods have been successfully used to introduce object-oriented technology (oot) into actual development projects and have helped to increase overall productivity within the target development organizations.
static analysis-based program evolution support in the common lisp framework. the common lisp framework(clf) is an object-oriented environment to support the development and maintenance of programs written in the language common lisp. a static analysis tool, which is part of clf, supports program evolution in clf. since the effectiveness of our approach stems from the basic design and architecture of clf, we provide an overview of the relevant features of clf. the static analysis tool asserts the static properties of program objects definitions into the clf objectbase. clf's general mechanism to add rules to the objectbase provides the conceptual basis to respond to changes in the static properties of program objects in several interesting ways &mdash; from programming routine responses to program changes to viewing program alterations idiomatically.
viewpoints: meaningful relationships are difficult! the development of complex systems invariably involves many stakeholders who have different perspectives on the problem they are addressing, the system being developed, and the process by which it is being developed. the viewpoints framework was devised to provide an organisational framework in which these different. perspectives, and their relationships, could be explicitly represented and analysed. the framework acknowledges the inevitability of multiple inconsistent views, promotes separation of concerns, and encourages decentralised specification while providing support for integration through relationships and composition. in this paper, we reflect on the viewpoints framework, current work, and future research directions.
data flow analysis for checking properties of concurrent java programs. in this paper we show how the flavers data flow analysis technique, originally formulated for programs with the rendezvous model of concurrency, can be applied to concurrent java programs. the general approach of flavers is based on modeling a concurrent program as a flow graph and using a data flow analysis algorithm over this graph to check statically if a property holds on all executions of the program. the accuracy of this analysis can be improved by supplying additional information, represented as finite state automata, to the data flow analysis algorithm. in this paper we present a straightforward approach for modeling java programs that uses the accuracy improving mechanism to represent the possible communications among threads in java programs, instead of representing them directly in the flow graph model. we also discuss a number of error-prone thread communication patterns that can arise in java and describe how flavers can be used to check for the presence of these.
the echo approach to formal verification. in this research abstract, we propose echo: a general formal verification approach that combines theorem proving, model checking, and code-level tools to show an implementation's compliance with its formal specification. we believe that this approach is novel since the major proof step is carried out between two abstract specification models, thus avoiding or mitigating the difficulty of the direct compliance proof of a concrete implementation against an abstract formal specification in traditional floyd-hoare verification. we present our prototype design and implementation of the major components of the approach and we instantiate the approach to verify spark ada implementations against pvs specifications. we conducted an initial experiment to determine the feasibility of the approach using a hypothetical avionics system.
expressing the relationships between multiple views in requirements specification. the authors generalize and formalize the definition of a viewpoint to facilitate its manipulation for composite system development. a viewpoint is defined to be a loosely-coupled, locally managed object encapsulating representation knowledge, development process knowledge and partial specification knowledge about a system and its domain. in attempting to integrate multiple requirements specification viewpoints, overlaps must be identified and expressed, complementary participants made to interact and cooperate, and contradictions resolved. the notion of inter-viewpoint communication is addressed as a vehicle for viewpoint integration. the communication model presented straddles both the method construction stage during which inter-viewpoint relationships are expressed, and the method application stage during which these relationships are enacted
living assistance systems: an ambient intelligence approach. in this paper, we present an integrated system concept for the living assistance domain based on ambient intelligence technology and discuss the resulting challenges for the software engineering discipline. automated living assistance systems represent a promising approach for the prolongation of an independent and self-conducted life of handicapped and elderly people thereby, enhancing their quality of life and minimizing the need for manual social/medical care. it is demonstrated that living assistance systems must realize flexibility and adaptability at the algorithmic, architectural and human interface level to an extent unknown in present systems. the construction of robust, trustworthy living assistance systems is an extremely challenging task and requires novel approaches for dependable self-adapting software architectures, resource efficiency, and self-adapting multi-modal human-computer interfaces. the resulting consequences and challenges for the discipline of software engineering are outlined in this paper.
consistency management with repair actions. comprehensive consistency management requires a strong mechanism for repair once inconsistencies have been detected. in this paper we present a repair framework for inconsistent distributed documents. the core piece of the framework is a new method for generating interactive repairs from full first order logic formulae that constrain these documents. we present a full implementation of the components in our repair framework, as well as their application to the uml and related heterogeneous documents such as ejb deployment descriptors. we describe how our approach can be used as an infrastructure for building higher-level, domain specific frameworks and provide an overview of related work in the database and software development environment community.
software development and proofs of multi-level security. this paper summarizes current research at ri aimed at developing secure operating systems and verifying certain critical properties of these systems. it is seen that proofs of design properties can be relatively straightforward when the design is specified in suitable formal specification language. these proofs demonstrate the correspondence between the desired properties and a specification of the system design. various on-line tools aid considerably in this process. in addition, correctness proofs for implementations of such systems are now feasible, because of both various theoretical advances and the use of supporting tools.
introduction to agile processes and extreme programming. extreme programming is one of the most discussed subjects in the software development community. but what makes xp extreme? and how does it fit into the new world of agile methodologies? this tutorial will establish the underpinnings of agile methodology and explain why you might want to try one. then we will see how xp uses a set of practices to build an effective software development team that produces quality software in a predictable and repeatable manner.
european experiences with software process improvement. assessment models used include spice (iso/iec tr 15504) [1] and software engineering institute's cmm1 [2] (one organisation also achieved iso9001 certification).
critical factors in establishing and maintaining trust in software outsourcing relationships. trust is considered one of the most important factors for successfully managing software outsourcing relationships. however, there is lack of research into understanding the factors that are considered important in establishing and maintaining trust between clients and vendors. the goal of this research is to gain an understanding of software outsourcing vendors' perceptions of the importance of factors that are critical to the establishment and maintenance of trust in software outsourcing projects in vietnam. we used a multiple case study design to guide our research and in-depth interviews to collect qualitative data from 12 vietnamese software development practitioners drawn from 8 companies that have been developing software for far eastern, european, and american clients. vendor companies identified that cultural understanding, creditability, capabilities, and personal visits are important factors in gaining the initial trust of a client, while cultural understanding, communication strategies, contract conformance, and timely delivery are vital factors in maintaining that trust.
a weakly constrained approach to software change coordination. the development of a software system ¿ of any reasonablesize ¿ from initial conception through ongoing maintenanceand evolution accrues significant coordination overheads.often the mechanisms used to manage change andcoordination detract from the time developers have to pursuethe principal goal of constructing the desired system.this is one of the motivators behind the emerging ýagileýmethodologies. by permitting people to work as independentlyas possible and yet be aware of each otherýs dependenciesand constraints, it is believed that these secondarycosts can be minimised. the position taken in theresearch summarised here is that better support can beprovided for this type of weakly constrained coordinationby enhancing the awareness, automated traceability, andconstraint checking capabilities of software configurationmanagement systems. current progress in the research andplans for future work are described.
an infrastructure for development of object-oriented, multi-level configuration management services. in an integrated development environment, the ability to manage the evolution of a software system in terms of logical abstractions, compositions, and their interrelations is crucial to successful software development. this paper presents a novel framework and infrastructure, molhado, upon which to build object-oriented software configuration management (scm) services in a scm-centered integrated development environment. key contributions of this paper include a product versioning model, an extensible, logical, and object-oriented system model, and a reusable product versioning scm infrastructure, that allow new types of objects to be implemented as extensions of the system model's basic entities. versions and configurations of objects are managed at different levels of abstraction and granularity. a new scm-centered editing environment or development environment for a specific development paradigm can be rapidly realized by re-using molhado's infrastructure and implementing new object types and their associated tools. this paper also demonstrates our approach in creating prototypes of scm-centered development environments for different paradigms.
practical approach to development of spi activities in a large organization: toshiba's spi history since 2000. for the effective promotion of software process improvement (spi) activities in a large-scale organization, it is necessary to establish an organizational structure and a deployment method for promotion and to develop training courses, support tools, and other materials. even if an organizational promotion system is established, the spi activities of each development department cannot be promoted effectively without spi community. to promote spi activities throughout the toshiba group, we organized a corporate software engineering process group in april 2000. we also have been focused to establish spi community, while promoting spi activities in each development department. the fundamental our operating policy of spi is "bottom-up". this paper discusses the problems encountered in the promotion of spi activities and presents solutions to the problems. the actual results obtained show that the framework and solutions developed by us can be used to effectively promote spi activities.
the vienna component framework enabling composition across component models. the vienna component framework (vcf) supports the interoperability and composability of components across different component models, a facility that is lacking in existing component models. the vcf presents a unified component model---implemented by a fa&ccedil;ade component---to the application programmer. the programmer may write new components by composing components from different component models, accessed through the vcf. the model supports common component features, namely, methods, properties, and events. to support a component model within the vcf, a plugin component is needed that provides access to the component model. the paper presents the vcf's design, implementation issues, and evaluation. performance measurements of vcf implementations of com, enterprise javabeans, corba distributed objects, and javabeans show that the overhead of accessing components through the vcf is negligible for distributed components.
the fujaba environment. however, a single collaboration diagram is usually not expressive enough to model complex operations performing several modifications at different parts of the overall object structure. such series of modifications need several collaboration diagrams to be modeled. in addition, there may be different situations where certain collaboration diagrams should be executed and others not. thus, we need additional control structures to control the execution of collaboration diagrams. in our approach we combine collaboration diagrams with statecharts and activity diagrams for this purpose. this means, instead of just pseudo code, any state or activity may contain a collaboration diagram modeling the do-action of this step.figure 1 illustrates the main concepts of fujaba. fujaba uses a combination of statecharts and collaboration diagrams to model the behavior of active classes. a combination of activity diagrams and collaboration diagrams models the bodies of complex methods. this integration of class diagrams and uml behavior diagrams enables fujaba to perform a lot of static analysis work facilitating the creation of a consistent overall specification. in addition, it turns these uml diagrams into a powerful visual programming language and allows to cover the generation of complete application code. during testing and maintenance the code of an application may be changed on the fly, e.g. to fix small problems. some application parts like the graphical user interface or complex mathematical computations may be developed with other tools. in cooperative (distributed) software development projects some developers may want to use fujaba, others may not. code of different developers may be merged by a version management tool. there might already exist a large application and one wants to use fujaba only for new parts. one may want to do a global search-and-replace to change some text phrases. one may temporarily violate syntactic code structures while she or he restructures some code. for all these reasons, fujaba aims to provide not just code generation but also the recovery of uml diagrams from java code. one may analyse (parts of) the application code, recover the corresponding uml diagram (parts), modify these diagram (parts), and generate new code (into the remaining application code). so far, this works reasonable for class diagrams and to some extend for the combination of activity and collaboration diagrams. for statecharts this is under development.the next chapters outline the (forward engineering) capabilities of fujaba with the help of an example session.
an experimental evaluation of selective mutation. mutation testing is a technique for unit-testing software that, although powerful, is computationally expensive. the principal expense of mutation is that many variants of the test program, called mutants, must be repeatedly executed. selective mutation is a way to approximate mutation testing that saves execution by reducing the number of mutants that must be executed. the authors report experimental results that compare selective mutation testing to standard, or nonselective, mutation testing. the results support the hypothesis that selective mutation is almost as strong as nonselective mutation. in experimental trials, selective mutations provide almost the same coverage as nonselective mutation, with significant reductions in cost
fuzzy logic based interactive recovery of software design. this abstract presents an approach to semi-automatically detect pattern instances and their implementations in a software system. design patterns are currently best practice in software development and provide solutions for nearly all granularity of software design and makes them suitable for representing design knowledge. the proposed approach overcomes a number of scalability problems as they exist in other approaches by using fuzzy logic, user interaction and a learning component.
experiences of software quality management using metrics through the life-cycle. many software quality metrics to objectively grasp software products and process have been proposed in the past decades. in actual projects, quality metrics has been widely applied to manage software quality. however, there are still several problems with providing effective feedback to intermediate software products and the software development process. we have proposed a software quality management using quality metrics which are easily and automatically measured. the purpose of this proposal is to establish a method for building in software quality by regularly measuring and reviewing. the paper outlines a model for building in software quality using quality metrics, and describes examples of its application to actual projects and its results. as the results, it was found that quality metrics can be used to detect and remove problems with process and products in each phase. regular technical reviews using quality metrics and information on the change of the regularly measured results was also found to have a positive influence on the structure and module size of programs. further, in the test phase, it was found that with the proposed model, the progress of corrective action could be quickly and accurately grasped.
towards pattern-based design recovery. a method and a corresponding tool is described which assist design recovery and program understanding by recognising instances of design patterns semi-automatically. the approach taken is specifically designed to overcome the existing scalability problems caused by many design and implementation variants of design pattern instances. our approach is based on a new recognition algorithm which works incrementally rather than trying to analyse a possibly large software system in one pass without any human intervention. the new algorithm exploits domain and context knowledge given by a reverse engineer and by a special underlying data structure, namely a special form of an annotated abstract syntax graph. a comparative and quantitative evaluation of applying the approach to the java awt and jgl libraries is also given.
object-oriented reengineering patterns. the rapid growth of object-oriented development overthe past twenty years has given rise to many object-orientedsystems that are large, complex and hard to maintain. thesesystems exhibit a range of problems, effectively preventingthem from satisfying the evolving requirements imposedby their customers. in our tutorial, we addressproblem of understanding and reengineering such object-orientedlegacy systems. the material is presented as aof "reengineering patterns" ¿ recurring solutions that expertsapply while reengineering and maintaining object-orientedsystems. the patterns distill successful techniquesin planning a reengineering project, reverse-engineering,problem detection, migration strategies and software redesign.the principles and techniques described have beenobserved and validated in a number of industrial projects,and reflect best practice in object-oriented reengineering.
deriving executable process descriptions from uml. in the recent past, a relevant effort has been devoted to the definition of process modeling languages (pmls). the resulting languages and environments -although technically successful-did not receive much attention from industry. on the contrary, researchers and practitioners have recently started experimenting with the usage of uml as a pml. being so popular and widely used, uml has an important competitive advantage compared to any specialized pml. however, it has also a main limitation. while most pmls are executable by some process engine, uml was conceived as a non-executable, semi-formal language. the work described here aims at assessing the possibility of employing a subset of uml as an executable pml. the article proposes a formalization of the semantics of the uml subset and presents the translation of uml process models into code, which can be enacted in the opss process-centered environment. the paper also presents a case study to validate the approach. we expect that process modeling by means of uml is easier and available to a larger community of software process managers. moreover, process enactment makes the process more efficient, reliable, predictable and controllable, as widely shown by previous research.
conducting empirical software engineering research in nigeria: the posing problems. empirical software engineering research has advanced in many parts of the world especially the western nations, but little has been contributed in this research domain by the developing nations such as nigeria, the well-acclaimed 'giant of africa'. the fast growing software industry in the country suggests that we need to incorporate solid software engineering studies into the various software process activities of the stakeholders in the industry, if at all quality software products must be turned out into the ever-competing global market. recent survey of the nigeria software industry shows that the industry is just coming into limelight, and that the industry is beset with 'software process compromise'. this short article takes a cursory look into the state of software engineering research in nigeria with particular reference to the nature of the nation's software industry and the student/academic environment as well as their posing problems. the article concludes with some cogent recommendations.
workshop on software quality. in the recent years, software products have increased in size and complexity, becoming a critical and strategic asset in the organizations' business. in this scenario it is a challenge to obtain software products of quality under the time and resources constraints established in projects. standards, methodologies and techniques to promote software quality assurance have been continually proposed by the researchers and used by software engineers in the industry. the workshop on software quality (wosq) aims at bringing together academic, industrial and commercial communities interested in software quality topics to discuss the different technologies being defined and used in the software quality area.
the community workbench. community is a formal approach to software architecture with a strict separation of the computation, coordination, and distribution aspects. the approach is based on a parallel design language with state, which facilitates the specification of computations compared to the process calculi used by other formal approaches, and on category theory, which provides an intuitive yet precise graph-based semantics for the configuration of components and connectors. the community workbench is being developed as a proof of concept of the community framework, providing a graphical integrated development environment to write components, draw configurations, and execute the resulting system.
building product populations with sofware components. two trends have made reuse of embedded software for consumer electronics an urgent issue: the software of individual products becomes more and more complex, and the market demands a larger variety of products at an increasing rate. for that reason, various business groups within philips organize their products as product families. a third trend is the integration of functions that until now were only found in separate products (e.g. a tv with dolby digital sound and a built-in dvd player). this requires software reuse between product families, which - when organized systematically - leads to a product population approach.we have set up such a product population approach, and applied it in various business groups within our organization. we use a component technology that stimulates context independence, and allows the composition of new products out of existing parts. we use an architectural description language to explicitly describe the architecture, and also to generate efficient bindings. we have aligned our development process and organization with the new 'compositional' way of working. this paper outlines our approach and reports on our experiences with it.
a flexible approach to decentralized software evolution. reducing the costs and risks associated with changing complex software systems has been a principal concern of software engineering research and development. one facet of this effort concerns decentralized software evolution (dse), which, simply stated, enables third-parties to evolve a software application independent of the organization that originally developed it. popular approaches to dse include application programming interfaces or apis, software plug-ins, and scripting languages. application vendors employ dse as a means of attracting additional users to their applications-and, consequentially, increasing their market share-since it opens up the possibility that a third-party modified version of the application would satisfy the needs of end-users unsatisfied with the original version. this benefits everyone involved: the original application vendor sells more product since customization constitutes use; third-party developers deliver a product in less time and with lower cost by reusing software as opposed to building it from scratch; and customers receive a higher quality product, customized to suit their needs, in less time and with lower cost. by increasing the opportunity for buying and customizing software instead of building it from scratch, dse attacks brook's "essential" difficulties of software development.
architecture-based runtime software evolution. continuous availability is a critical requirement for an important class of software systems. for these systems, runtime system evolution can mitigate the costs and risks associated with shutting down and restarting the system for an update. we present an architecture-based approach to runtime software evolution and highlight the role of software connectors in supporting runtime change. an initial implementation of a tool suite for supporting the runtime modification of software architectures, called archstudio, is presented
tools for real-time system design. this paper describes the development of a toolset that supports the specification and design of large real time systems. the starting point is the evolution of a method suitable for use in practical environments; for example in the specification of telecommunication systems. the characteristics that are required of a good specification method for real time systems are discussed and a method based upon the ccitt sdl notation is described which aims to satisfy these characteristics. the component parts in the toolset to support this method are described.
an empirical comparison of dynamic impact analysis algorithms. impact analysis ¿ determining the potential effects ofchanges on a software system ¿ plays an important rolein software engineering tasks such as maintenance, regressiontesting, and debugging. in previous work, two new dynamicimpact analysis techniques, coverageimpact andpathimpact, were presented. these techniques performimpact analysis based on data gathered about program behaviorrelative to specific inputs, such as inputs gatheredfrom field data, operational profile data, or test-suite executions.due to various characteristics of the algorithms theyemploy, coverageimpactand pathimpactare expectedto differ in terms of cost and precision; however, there havebeen no studies to date examining the extent to which suchdifferences may emerge in practice. since cost-precisiontradeoffs may play an important role in technique selectionand further research, we wished to examine these tradeoffs.we therefore designed and performed an empirical study,comparing the execution and space costs of the techniques,as well as the precisions of the impact analysis results thatthey report. this paper presents the results of this study.
icse workshop on remote analysis and measurement of software systems (ramss). the goal of this one-day workshop was to bring together researchers and practitioners interested in exploring how the characteristics of today's area of computing (e.g., high connectivity, substantial computing power for the average user, higher demand for and expectation of frequent software updates) can be leveraged to improve software quality and performance.
second icse workshop on remote analysis and measurement of software systems (ramss). the goal of this workshop is to bring together researchersand practitioners interested in exploring how the characteristicsof todayýs area of computing (e.g., high connectivity,substantial computing power for the average user, higher demandfor and expectation of frequent software updates) canbe leveraged to improve software quality and performance.
software development engineer in microsoft: a subjective view of soft skills required. this paper is a position statement. there are important requirements on software development engineers that go beyond the normal academic qualifications and technical skills, and which quite often receive a lower priority in education and training.
hyper/j: multi-dimensional separation of concerns for java. hyper/j supports a new approach to constructing, integrating and evolving software, called multi-dimensional separation of concerns. developers can decompose and organize code and other artifacts according to multiple, arbitrary criteria (concerns) simultaneously&mdash;even after the software has been implemented&mdash;and synthesize or integrate the pieces into larger-scale components and systems. hyper/j facilitates several common development and evolution activities non-invasively, including: adaptation and customization, mix-and-match of features, reconciliation and integration of multiple domain models, reuse, product line management, extraction or replacement of existing parts of software, and on-demand remodularization. hyper/j works with standard java software, not requiring special compilers or environments. this demonstration will show it in action in a number of software engineering scenarios at different stages of the software lifecycle.
toolpack - an experimental software development environment research project. this paper discusses the goals and methods of the toolpack project and in this context discusses the architecture and design of the software system being produced as the focus of the project. toolpack is presented as an experimental activity in which a large software tool environment is being created for the purpose of general distribution and then careful study and analysis. the paper begins by explaining the motivation for building integrated tool sets. it then proceeds to explain the basic requirements that an integrated system of tools must satisfy in order to be successful and to remain useful both in practice and as an experimental object. the paper then summarizes the tool capabilities that will be incorporated into the environment. it then goes on to present a careful description of the actual architecture of the toolpack integrated tool system. finally the toolpack project experimental plan is presented, and future plans and directions are summarized.
lessons of current environments. this panel will examine and evaluate some notable current and recent software environment efforts from the perspective of this conference&mdash;namely that environments should be viewed as vehicles for fostering the automation of software processes.at this conference we are exploring the premise that software is a product whose creation and evolution can and should be carried out according to the dictates of systematic and orderly processes. investigations such as software lifecycle modeling efforts have attempted to help us understand the nature of these processes by identifying major subactivities, subproducts and information flows. work on software environments has, in the past, emphasized the integration of tools, but has all too often not addressed the issue of how these integrated tools support software processes. fortunately there is an increasing realization that such process support is the goal of software environments, and more recent environments are addressing that goal more sharpl. in this panel we shall attempt to review some notable and influential tool integration and environment development efforts from this more contemporary perspective in an attempt to perceive current trends and directions more clearly and to more sharply identify the key contributions which this work has made. as an aid to setting this tone and perspective for the panel, we shall begin with a presentation by nelson weiderman, for the software engineering institute, carnegie-mellon university, pittsburgh, pa, usa. dr. weiderman will summarize a paper which he coauthored with a. n. habermann, m.w. borger and m.h. klein in which they suggest that environments should be evaluated in precisely this way. their paper details a flow of methodological steps for evaluation of toolsets and environments which stresses that such systems should be measured against a clear enunciation of the software activities which the tools and environments are purported to support. the paper goes on to describe how dynamic testing of subject toolsets should be organized to gain quantitative insights into the effectiveness of the subject systems in supporting the identified processes.the significance of this evaluative approach is at least twofold. first it forces environment developers to recognize that the key result of their work is support of processes, and second it forces all of us as a community to realize that we must increasingly work to understand the set of activities which comprise software processes and software objects which comprise our products. these realizations will help lead us to the more effective environments of the coming decade. after dr. weiderman's opening presentation there will be six subsequent presentations of current and recent work. these presentations have been carefully selected to represent a variety of approaches to providing support for a variety of client communities in a variety of locations. each presenter has been asked to consider the way in which his system supports a particular process or subactivities of a process; any architectural features which distinguish or characterize his system; how effective he believes his system has been in conveying support for the portion of the process which has been identified; and whether the architectural approach taken has or has not been particularly useful in helping to achieve the process support goals for the system.
lightweight vs. heavyweight processes: is this even the right question? interest in the use of processes to provide assistance in software development activities remains at a high level. but the focus of attention has shifted in recent years. early work emphasizing the study of languages for defining processes was rapidly eclipsed by process evaluation and improvement work, most notably the capability maturity model (cmm). as process improvement has matured as a strategy and philosophy it has also given rise to a strong reaction to the perception that it is unduly ponderous and constraining. movements such as extreme programming (xp) have cast themselves as lightweight alternatives, emphasizing the primacy of freedom and flexibility. both philosophies and communities continue to grow in size, development, and depth of understanding.the goal of this panel will be to explore the differences between these major approaches to the use of process in software development by bringing together leading articulate exponents of the approaches. each panelist will be charged with presenting a very concise characterization of the approach being represented. but the focus of the panel will be on understanding the nature of the differences in approach, and the reasons for these differences. similarities will be sought as well.an underlying hypothesis of the panel is that the differences in approach arise in large measure from differences in objective and differences in assumptions about the software development context. thus, for example, one approach may be intended to support very long range organizational objectives, while the other may be more tactically oriented. one approach may assume that evolvability is an overriding objective, while another may be more focused on speed to market. one may make stronger assumptions about the skills and training of project personnel. the panel will attempt to delve into these issues to see if it may be possible to suggest criteria for suggesting which approach (and possible adaptation) should be selected for a given development situation.in a larger sense, the goal of this panel is to suggest the possibility of a discipline of software process engineering. insofar as the panel is able to suggest that development situations can be used to guide the selection of process approaches to the provision of assistance, might this then be an indication that process formalisms could play a role in subsequent specification of detailed processes, and evaluation of their effectiveness?the panel will react to this and related questions. while lively interchanges among the panelists will be stimulated and expected, similar interchanges with the audience will also be cultivated.
lime: linda meets mobility. lime is a system designed to assist in the rapid development of dependable mobile applications over both wired and ad hoc networks. mobile agents reside on mobile hosts and all communication takes place via transiently shared tuple spaces distributed across the mobile hosts. the decoupled style of computing characterizing the linda model is extended to the mobile environment. at the application level, both agents and hosts perceive movement as a sudden change of context. the set of tuples accessible by a particular agent residing on a given host is altered transparently in response to changes in the connectivity pattern among the mobile hosts. in this paper we present the key design concepts behind the lime system.
new software engineering faculty symposium. new software engineering faculty face many challenges and tremendous pressures today. the icse community is committed to helping these young faculty members survive in academia. this symposium will bring together faculty who have survived their early years with potential, new, and junior faculty. the attendees can work together on strategies for success and shop from the best ideas and experiences of their colleagues.
developing mobile computing applications with lime. mobile computing defines a very dynamic and challenging scenario for which software engineering practices are still largely in their initial developments. lime is a middleware designed to enable the rapid development of dependable applications in the mobile environment. the model underlying lime allows for coordination of physical and logical mobile units by exploiting a reactive, transiently shared tuple space whose contents changes according to connectivity. in this demonstration, we report about initial experiences in developing applications for physical mobility using lime.
conceptual modeling through linguistic analysis using lida. despite the advantages that object technology can provide to the software development community and its customers, the fundamental problems associated with identifying objects, their attributes, and methods remain: it is a largely manual process driven by heuristics that analysts acquire through experience. while a number of methods exist for requirements development and specification, very few tools exist to assist analysts in making the transition from textual descriptions to other notations for object-oriented analysis and other conceptual models. in this paper we describe a methodology and a prototype tool, linguistic assistant for domain analysis (lida), which provide linguistic assistance in the model development process. we first present our methodology to conceptual modeling through linguistic analysis. we give an overview of lida's functionality and present its technical design and the functionality of its components. we also provide a comparison of lida's functionality with that of other research prototypes. finally, we present an example of how lida is used in a conceptual modeling task.
a software reliability assessment based on a structural and behavioral analysis of programs. this paper deals with the problem of assessing the reliability of programs written using structured programming techniques and having undergone a certain amount of testing. a program is said to be verified if, for a given set of tests it can be shown that every case of interest has been tested. as this end is, however, unattainable, we will consider, in the following, that a program is verified if one can prove that all the logic paths in the program flow graph have been traversed. therefore, we will consider that a certain degree of verification is attained with a given set of tests, according to the number of paths actually traversed. this degree of verification, which is a non-decreasing function of the number of tests can be considered as an assessment of program reliability. the degree of verification attained through experiments can then be deduced from the images of experiments in the program flow graph. this paper defines a practical procedure to perform such an evaluation.
software visualisation for object-oriented program comprehension. software visualisation is the process of modellingsoftware systems for comprehension [6]. thecomprehension of software systems both during and afterdevelopment is a crucial component of the softwareprocess [8]. the complex interactions inherent in theobject-oriented paradigm make visualisation a particularlyappropriate comprehension technique, and the largevolume of information typically generated duringvisualisation necessitates tool support.
empirical interval estimates for the defect content after an inspection. we present a novel method for estimating the number of defects contained in a document using the results of an inspection of the document. the method is empirical, being based on observations made during past inspections of comparable documents. the method yields an interval estimate, that is, a whole range of values which is likely to contain the true value of the number of defects in the document. we also derive point estimates from the interval estimate. the method is validated using a known empirical inspection dataset and clearly outperforms existing approaches for estimating the defect content after inspections.
extending requirement specifications using analogy. creating the specifications for a new system is a labour intensive task. analogical reasoning provides a flexible mechanism to retrieve and adapt past specifications. previous work in applying analogical reasoning to requirement specifications has departed from the psychological foundations of analogical reasoning, introducing specific ontologies and abstract templates to constrain the reasoning process. we argue that similar results can be obtained without introducing domain specific constraints and that using analogical reasoning engines based on well-established psychological theories, such as the structure-mapping engine, will lead to better results and scale up more effectively.
pragmatic techniques for program analysis and verification. the program development system (pds) is a collection of programming tools created as an extension of the ecl programming system23. it contains components that assist the programmer in the definition and modular structuring of large programs at different levels of algorithmic abstraction. these components are supplemented by a program analysis package that produces an information pool to be used for such tasks as source-to-source optimization, semi-automated program documentation, fault detection and program verification. this paper describes the core of the analyzing package, the symbolic evaluator. in its implementation we have incorporated pragmatic methods for handling data sharing patterns, and for characterizing and reasoning about the behaviour of loops and procedures. the impact of these methods upon program verification techniques is briefly discussed.
lisfs: a logical information system as a file system. we present logical information systems (lis). a lis can be viewed as a schema-less database whose objects are described by logical formulas. objects are automatically organized according to their logical description, and logical formulas can be used for representing both queries and navigation links. the key feature of a lis is that it answers a query with a set of navigation links expressed in the same logic as the query. as navigation links are dynamically computed from any query, and can be used as query increments, it follows that querying and navigation steps can be combined in any order.we then present lisfs, a file-system implementation of a lis, where objects are files or parts of files. this has the benefit to make lis features available right now to existing applications. this implementation can easily be extended and specialized through a plug-in mechanism.finally, we present some applications in the field of personal databases (e.g., music, images, emails) and in the field of software engineering.
coverage measurement experience during function test. the authors discuss the issues of test coverage measurement in industry and justify the benefits of the measurement using a framework developed by them. some results of experiences using test coverage measurement are outlined. the function test of large-scale system software is defined and analyzed. based on the discussions of function test, a framework for analyzing the function test error removal process is developed. an experience-based error removal model and a cost model are proven to be useful tools for justifying test coverage measurement during function test. data obtained from a real project are analyzed using the framework for validation
beyond structured programming. structured programming principles are not strong enough to control complexity and guarantee high reliability of software at the module level. stronger organizing principles and stronger properties of components are needed to make significant gains in the quality of software. practical proposals, based on the definition of normal forms which have a mathematical/logical foundation, are suggested as a vehicle for constructing software that is both simpler and of higher quality with regard to clearly defined and justifiable criteria.
automated support for classifying software failure reports. this paper proposes automated support for classifying reported software failures in order to facilitate prioritizing them and diagnosing their causes. a classification strategy is presented that involves the use of supervised and unsupervised pattern classification and multivariate visualization. these techniques are applied to profiles of failed executions in order to group together failures with the same or similar causes. the resulting classification is then used to assess the frequency and severity of failures caused by particular defects and to help diagnose those defects. the results of applying the proposed classification strategy to failures of three large subject programs are reported. these results indicate that the strategy can be effective.
information systems development at the virtual global university: an experience report. in this paper, we present our experiences gained from the course "information systems development" which is entirely taught online at the virtual global university (vgu). we identify technical, economic, and pedagogical problems and challenges which are of general interest to anyone teaching software engineering online.
test procedures: a new approach to software verification. a test procedure is a formal specification of test cases to be applied to one or more target program modules. test procedures are executable. a process called the verifier applies a test procedure to its target modules and produces an exception report indicating which test cases, if any, failed. test procedures facilitate thorough software testing by allowing individual modules or arbitrary groups of modules to be thoroughly tested outside the environment in which they will eventually reside. test procedures are complete, self-contained, self-validating and execute automatically. test procedures are a deliverable product of the software development process and are used for both initial checkout and subsequent regression testing of target program modifications. test procedures are coded in a new language called tpl (test procedure language). the paper analyzes current testing practices, describes the structure and design of test procedures and introduces the fortran test procedure language.
automatic revision of formal test procedures. an automatic software test driver is a new type of software tool which controls and monitors the execution of software tests. an automatic test driver is controlled by a formal test procedure coded in a special software test language. the test procedure replaces the test data and test setup instructions of conventional testing. the specific goals of automatic test drivers are to eliminate the need for writing drivers and stubs for module and subsystem testing, to provide a standard format and language for specifying software tests, to provide a standard execution setup for software tests, and to automate the verification of test execution results. a test procedure contains input data to be supplied to the program under test and model outputs against which actual outputs of the target program are verified. typically, ninety percent or more of the text of a test procedure consists of model outputs which must be revised each time the target program is modified. the tpl/2.0 automatic software test driver described in this paper automates both the initial generation and subsequent revision of test procedure model outputs.
dynamic configuration of resource-aware services. an important emerging requirement for computing systemsis the ability to adapt at run time, taking advantage oflocal computing devices, and coping with dynamicallychanging resources. three specific technical challenges insatisfying this requirement are to (1) select an appropriateset of applications or services to carry out a userýs task, (2)allocate (possibly scarce) resources among those applications,and (3) reconfigure the applications or resource assignmentsif the situation changes. in this paper we showhow to provide a shared infrastructure that automates configurationdecisions given a specification of the userýs task.the heart of the approach is an analytical model and anefficient algorithm that can be used at run time to makenear-optimal (re)configuration decisions. we validate thisapproach both analytically and by applying it to a representativescenario.
requirements for a layered software architecture supporting cooperative multi-user interaction. layered interactive systems lend themselves to be adapted for cooperation if inter-layer communication is charged to separated connectors. point-to-point connectors can be replaced with cooperative connectors multiplexing and demultiplexing i/o between a particular layer and multiple instances of the next lower one. for this technique to be most effective, some general guidelines should be followed that support the design of good quality software where discrimination between heterogeneous functionality at the architectural level allows multiple interacting users to exploit different system features based on their role in the cooperation. this provides a sound basis for augmenting collaboration-transparent layered systems with powerful collaboration support (e.g. complex coordination policies) yet preserving separation of concerns between applicative and cooperative functionality. the paper discusses these issues both in general and with reference to their application within the csdl framework for cooperative systems design.
multibook's test environment. well engineered web based courseware and exercises provide flexibility and added value to the students, which goes beyond the traditional text book or cd-rom based courses. the multibook project explores the boundaries of customized learning materials by composing learning trails dynamically as learners have set their profile to access a course. in this paper we first give an overview of the core project ideas and illustrate them along our software engineering course. then we present a novel extension to the project's exercise environment with a graph editing component that particularly fits the needs of structure-related assignments.
contribution to simplifying the mobile agent programming. this paper introduces an experimental framework for mobile agents. it utilizes expressiveness and formal foundation of concurrent constraint programming to solve the problem of system support for dynamic rebinding of not transferable resources and inter-agent collaboration based on logic variables. proposed solutions help to make the agent-based programming easier and more straightforward and at the same time offer a basis for more sophisticated multi-agent systems.
variability management in software product line engineering. by explicitly modeling and managing variability, software product line engineering provides a systematic approach for creating a diversity of similar products at low cost, in short time, and with high quality. this tutorial focuses on the two principle differences of software product line engineering when compared to single systems development: the differentiation of two key development processes (domain engineering and application engineering) and the explicit representation and management of variability. we characterize the two processes and their main activities and introduce the orthogonal variability modeling approach (ovm). we further illustrate the ovm approach in the product line requirements engineering and product line testing activities.
designing software for ease of extension and contraction. designing software to be extensible and easily contracted is discussed as a special case of design for change. a number of ways that extension and contraction problems manifest themselves in current software are explained. four steps in the design of software that is more flexible are then discussed. the most critical step is the design of a software structure called the " uses" relation. some criteria for design decisions are given and illustrated using a small example. it is shown that the identification of minimal subsets and minimal extensions can lead to software that can be tailored to the needs of a broad variety of users.
software engineering in the development of the trident fire control system. this paper presents a short description of some of the methods and tools used in the trident fire control software development. use of a program design language (pdl), use of a high order language (hol) for programming, and the use of a schema approach to software debug are some of the highlights. this paper will discuss the trident fire control system software development effort, stressing software engineering concepts being used. specific points that will be mentioned are: 1. parallel computer - operating system development 2. use of prototypes/planned updates 3. structured design method 4. use of a higher order language 5. software test concepts 6. configuration control/v & v effort
software aging. programs, like people, get old. we can't prevent aging, but we can understand its causes, take steps to limits its effects, temporarily reverse some of the damage it has caused, and prepare for the day when the software is no longer viable. a sign that the software engineering profession has matured will be that we lose our preoccupation with the first release and focus on the long-term health of our products. researchers and practitioners must change their perception of the problems of software development. only then will software engineering deserve to be called &ldquo;engineering&rdquo;
the modular structure of complex systems. this paper discusses the organization of software that is inherently complex because of very many arbitrary details that must be precisely right for the software to be correct. we show how the software design technique known as information hiding, or abstraction, can be supplemented by a hierarchically structured document, which we call a module guide. the guide is intended to allow both designers and maintainers to identify easily the parts of the software that they must understand, without reading irrelevant details about other parts of the software. the paper includes an extract from a software module guide to illustrate our proposals.
procurement of enterprise resource planning systems: experiences with some hong kong companies. many cases of adoption of enterprise resource planning (erp) systems have been reported in the literature. some of the adopted erp systems fail to satisfy the customer's requirements, despite the high spending and substantial efforts that have been put into the adoption exercise. this is undoubtedly unsatisfactory. a way to avoid this problem is to adopt a well planned, managed, and controlled erp procurement process. this paper describes our studies of three chinese companies in hong kong which have adopted erp systems. we report the experience of these companies, and discuss how the chinese culture might have shaped the procurement practices in their erp adoption exercises.
response to undesired events in software systems. this paper discusses an approach to handling run-time errors in software systems. it is often assumed that in programs which can be proven correct, errors will not be a problem. this paper is predicted on the assumption that, even with correct programs, undesired events at run-time will continue to be a problem. routines to respond to these undesired events (ues) must be provided in reliable systems. this paper describes a program organization which aims at satisfying the following criteria: (1) ue response routines are written by each programmer in terms of the abstract machine which he uses for his normal case code. ues are reported in those terms. he is never forced to use information about the implementation of other modules in the system. (2) programs can be written so that the code for ue detection, ue correction, and normal case, are lexically separate and can be modified independently. (3) the system can evolve from an initial version that does little recovery to one which uses sophisticated recovery techniques without a change in the structure of the system. (4) even with unsophisticated recovery procedures, the task of locating the module containing a bug discovered at run-time does not require internal knowledge of many modules. (5) costs incurred because of the recovery techniques are low as no ue occurs.
experiences with an environment generation system. the authors report on research experience using the gandalf environment generation system as a prototyping vehicle for the inscape environment. a gandalf-based environment consists of four parts: a structure editor kernel, which is simply linked into each executable, a set of grammar tables describing the language to the kernel in terms of its abstract syntax, one or more concrete syntax views, and a collection of action routines written in the extension language, arl. positive aspects of the research included experimentation, incremental evolution, multiple views, the coupling of semantic and editing actions, and the use of domain-specific facilities. negative aspects consisted primarily of problems with presentation and object management
active design reviews: principles and practices. although many new software design techniques have emerged in the past 15 years, there have been few changes to the procedures for reviewing the designs produced using these techniques. this paper describes an improved technique, based on the following ideas, for reviewing designs. the efforts of each reviewer should be focussed on those aspects of the design that suit his experience and expertise. the characteristics of the reviewers needed should be explicitly specified before reviewers are selected. reviewers should be asked to make positive assertions about the design rather than simply allowed to point out defects. the designers pose questions to the reviewers, rather than vice versa. these questions are posed on a set of questionnaires that requires careful study of some aspect of the design. interaction between designers and reviewers occurs in small meetings involving 2 - 4 people rather than meetings of large groups. illustrations of these ideas drawn from the application of active design reviews to the naval research laboratory's software cost reduction project are included.
experience with application of modern software management controls. this paper presents the experience of the software development laboratory of raytheon company, submarine signal division, in applying modern software management control techniques to the development of software for real-time embedded computer systems. the paper initially describes the characteristics of the software projects during the period 1969-1979, and the ultimate use of the systems. the software is developed for embedded computers of many types and for systems requiring from one to eleven racks of electronics, and it is programmed in many languages. the systems are installed in submarines, surface ships, aircraft, shore-based facilities and weapons. the paper then summarizes development methodologies and follows with a detailed description of the software management and control techniques, which include: manpower forecasting; tailored status reports for financial, module, and cost-milestone-schedule; cost estimating; support librarian and configuration management; policies and procedures; training; and staffing and organization.
so you want brooks in your classroom? fred brooks' seminal book, "the mythical man-month" (mmm) is a firmly established classic in software engineering. many of us feel compelled to use this work to help our students appreciate and put into practice the fundamental software engineering concepts contained between its covers. this often amounts to using "passive" lesson plans such as required readings followed by lectures and exams; these rarely fully satisfy our learning objectives. rather, students often have mixed reactions to mmm with the result that it has little impact on their attitudes and practices, both in and out of the classroom. this paper outlines a more active approach to incorporating mmm into the classroom, one that we have refined over 6 years, at multiple universities and in both graduate and undergraduate courses. it includes learning objectives, a lesson plan, sample materials, an implementation discussion, and an evaluation of the approach's impact.
an experiment to assess different defect detection methods for software requirements inspections. software requirements specifications (srs) are usually validated by inspections, in which several reviewers read all or part of the specification and search for defects. we hypothesize that different methods for conducting these searches may have significantly different rates of success. using a controlled experiment, we show that a scenario-based detection method, in which each reviewer executes a specific procedure to discover a particular class of defects has a higher defect detection rate than either ad hoc or checklist methods. we describe the design, execution and analysis of the experiment so others may reproduce it and test our results for different kinds of software developments and different populations of software engineers
experiments with computer software complexity and reliability. experiments with quantitative assessment and prediction of software reliability are presented. the experiments are based on the analysis of the error and the complexity characteristics of a large set of programs. the first part of the study concerns the data collection process and the analysis of the error data and complexity measures. the relationships between the complexity profile and the error data of the procedures of the programs are then investigated with the help of discriminant statistical analysis technique. the results of these analyses show that an estimation can be derived from the analysis of its complexity profile.
design and verification of real-time systems. this paper presents a methodology for the design and verification of a class of real-time systems frequently encountered in applications of digital control. these methodologies are described in the form of a design and informal verification of a system used for navigation control of airborne vehicles. the high reliability standards required for such tasks suggest the use of fault-tolerant hardware and software. a design is presented for both an abstract version of the system running in an ideal environment and for a version running in a non-ideal fault-prone one. a specification language for real-time systems is developed as an extension of the programming language pascal, that provides for concise and clear system descriptions while preserving the degree of efficiency and portability needed to qualify as a practical high-level system implementation language. an informal verification of both designs is given.
regression test selection for aspectj software. as aspect-oriented software development gains popularity, there is growing interest in using aspects to implement cross-cutting concerns in object-oriented systems. when aspect-oriented features are added to an object-oriented program, or when an existing aspect-oriented program is modified, the new program needs to be regression tested to validate these changes. to reduce the cost of regression testing, a regression-test-selection technique can be used to select only a necessary subset of test cases to rerun. unfortunately, existing approaches for regression test selection for object-oriented software are not effective in the presence of aspectual information woven into the original code. this paper proposes a new regression-test-selection technique for aspectj programs. at the core of our approach is a new control-flow representation for aspectj software which captures precisely the semantic intricacies of aspect-related interactions. based on this representation, we develop a novel graph comparison algorithm for test selection. our experimental evaluation shows that, compared to existing approaches, the proposed technique is capable of achieving significantly more precise test selection.
residual test coverage monitoring. structural coverage criteria are often used as an indicator of the thoroughness of testing, but complete satisfaction of a criterion is seldom achieved. when a software product is released with less than 100% coverage, testers are explicitly or implicitly assuming that executions satisfying the remaining test obligations (the residue) are either infeasible or occur so rarely that they have negligible impact on quality. violation of this assumption indicates shortcomings in the testing process. monitoring in the deployed environment, even in the beta test phase, is typically limited to error and sanity checks. monitoring the residue of test coverage in actual use can provide additional useful information, but it is unlikely to be accepted by users unless its performance impact is very small. experience with a prototype tool for residual test coverage monitoring of java programs suggests that, at least for statement coverage, the simple strategy of removing all probes except those corresponding to the residue of coverage testing reduces execution overhead to acceptably low levels.
recording the reasons for design decisions. we outline a generic model for representing design deliberation and the relation between deliberation and the generation of method-specific artifacts. a design history is regarded as a network consisting of artifacts and deliberation nodes. artifacts represent specifications or design documents. deliberation nodes represent issues, alternatives or justifications. existing artifacts give rise to issues about the evolving design, an alternative is one of several positions that respond to the issue (perhaps calling for the creation or modification of an artifact), and a justification is a statement giving the reasons for and against the related alternative. the model is applied to the development of a text formatter. the example necessitates some tailoring of the generic model to the method adopted in the development, liskov and guttag's design method. we discuss the experiment and the method-specific extensions. the example development has been represented in hypertext and as a prolog database, the two representations being shown to complement each other. we conclude with a discussion of the relation between this model and other work, and the implications for tool support and methods.
kongsberg's road to an industrial software methodology. kongsberg våpenfabrikk, norway, has been engaged in establishing an up-to-date software engineering facility since late 1976.
discrete event simulation as a means of validating jsd design specifications. it is difficult to visualize the behaviour of an embedded system in its operational environment from a specification of the system alone. however, it is unacceptable to wait for system completion before validating its behaviour. discrete event simulation is an effective technique for making quantitative predictions about system behaviour, provided that the model is derived carefully from the system specification. we summarize the steps involved in deriving an ada** simulation program from a jsd function step specification, using a lift system as an illustration. having used this technique, we conclude that while it is time-consuming and not amenable to automation in the near future, it is cost-effective because it helps to elucidate counter-intuitive interactions between system functions and environmental parameters.
rules of thumb for secure software engineering. no abstract available
a formal approach for designing corba based applications. the design of distributed applications in a corba based environment can be carried out by means of an incremental approach, which starts from the specification and leads to the high level architectural design. this is done by introducing in the specification all typical elements of corba and by providing a methodological support to the designers. the paper discusses a methodology to transform a formal specification written in trio into a high level design document written using an extension of trio named tc. the tc language is suited to formally describe the high level architecture of a corba based application. the methodology and the associated language are presented by means of an example involving a real supervision and control system.
an algorithm to support code-skeleton generation for concurrent systems. computers are increasingly being used in engineering systems which could utilize a multiplicity of processors. computer aided design methods are needed to support the design of inherently complex concurrent software. ucla's sara (system architects apprentice) is a design environment which provides computer aid to both hardware and software design of concurrent systems. this paper focusses on an improved capability to aid software design. this capability is provided by defining a module interface description (mid), which allows designers to deal with the structure of code, and effecting a mapping between sara models and mid-models. it then becomes clear how to create a tool to accept these descriptions and perform various checks on the consistency and completeness of the modeling and implementation descriptions. the addition of this capability reduces the gap between the modeling and realization of systems by providing for automatic generation of code skeletons.
verification of time partitioning in the deos scheduler kernel. this paper describes an experiment to use the spin model checking system to support automated verification of time partitioning in the honeywell deos real-time scheduling kernel. the goal of the experiment was to investigate whether model checking could be used to find a subtle implementation error that was originally discovered and fixed during the standard formal review process. to conduct the experiment, a core slice of the deos scheduling kernel was first translated without abstraction from c++ into promela (the input language for spin). we constructed an abstract &ldquo;test-driver&rdquo; environment and carefully introduced several abstractions into the system to support verification. several experiments were run to attempt to verify that the system implementation adhered to the critical time partitioning requirements. during these experiments, the known error was rediscovered in the time partitioning implementation. we believe this case study provides several insights into how to develop cost-effective methods and tools to support the software design and implementation review process.
model-based testing. "broadcasting" is an information dissemination process in which a member of a system generates a message communicated to all other members. we model this process by ordered rooted trees and investigate a special class of rooted trees allowing broadcasting from the root to all other vertices of the tree in the minimum time (over all rooted trees with n vertices). we characterize trees from this class ("mbt") and give an algorithm deciding membership in the class. we also present an algorithm to construct all mbt's with a given number of vertices and give a recursive formula to count these trees.
holistic framework for establishing interoperability of heterogeneous software development tools and models. this research is an initial investigation into the development of a holistic framework for software engineering (hfse) that establishes mechanisms by which existing software development tools and models will interoperate. the hfse captures and uses dependency relationships among heterogeneous software development artifacts, the results of which can be used by software engineers to improve software processes and product integrity.
one evaluation of model-based testing and its automation. model-based testing relies on behavior models for the generation of model traces: input and expected output---test cases---for an implementation. we use the case study of an automotive network controller to assess different test suites in terms of error detection, model coverage, and implementation coverage. some of these suites were generated automatically with and without models, purely at random, and with dedicated functional test selection criteria. other suites were derived manually, with and without the model at hand. both automatically and manually derived model-based test suites detected significantly more requirements errors than hand-crafted test suites that were directly derived from the requirements. the number of detected programming errors did not depend on the use of models. automatically generated model-based test suites detected as many errors as hand-crafted model-based suites with the same number of tests. a sixfold increase in the number of model-based tests led to an 11% increase in detected errors.
software interconnection models. we present a formulation of interconnection models and present the unit and syntactic models &mdash; the primary models used for managing the evolution of large software systems. we discuss various tools that use these models and evaluate how well these models support the management of system evolution. we then introduce the semantic interconnection model. the semantic interconnection model incorporates the advantages of the unit and syntactic interconnection models and provides extremely useful extensions to them. by refining the grain of interconnections to level of semantics (that is, to the predicates that define aspects of behavior) we provide tools that are better suited to manage the details of evolution in software systems and that provide a better understanding of the implications of changes. we do this by using the semantic interconnection model to formalize the semantics of program construction, the semantics of changes, and the semantics of version equivalence and compatibility. thus, with this formalization, we provide tools that are knowledgeable about the process of system construction and evolution and that work in symbiosis with the system builders to construct and evolve large software systems.
version control in the inscape environment. we present the important issues to be considered in version control mechanisms and characterize and compare the kinds of version control systems extant in current programming environments. we then characterize inscape's version control mechanism. invariant, and show that it makes several significant advances in the state of the art. using instress (inscape's module interface specification language) specifications, invariant provides a better understanding of the notion of parallel versions, a more comprehensive notion of version consistency, and a more flexible method of system composition than current mechanisms. in particular, invariant provides a formalization of the notions of version equivalence and compatibility that correspond closely with our intuitive (and practical) notions of version equivalence and compatibility. these various forms of version compatibility provide the system builder with the concept of plug-compatibility &mdash; an extremely useful facility in composing systems from component parts.
a methodology for prototyping-in-the-large. the authors define prototyping as an experimental activity intended to reduce risk of failure in a software product. in this context, they explore the effect of scale in prototyping and then describe a methodology for prototyping a large application. the authors describe a system being developed to evaluate this methodology, featuring a pair of languages (promo and moblog) to serve both large-scale and component-level prototyping needs. the authors conclude with a presentation of how the proposed methodology would be applied to a sample problem, a fault-prediction subsystem within the space station freedom project
polyphony in architecture. based on interviews with a number of architects andmanagers from a wide range of organizations, we characterizehow architecture is perceived in practice. we identifythree groups of organizations that differ with respect to theirlevel of architectural thinking and the alignment of businessand it on architectural issues. analysis of the interviewsfurther indicates that these three groups differ in thearchitecture aspects and critical success factors they emphasize.our results provide a starting point for assessingarchitecture maturity and alignment within organizations,and can be used to help harmonize different architecturaltunes played within organizations.
the deployer's problem: configuring application servers for performance and reliability. frameworks such as j2ee are designed to simplify the process of developing enterprise applications by handling much of the complexity of concurrency, transaction, and persistence management. an application server that supports such a framework implements these concerns, freeing the application developer to focus on the task of implementing the business logic aspect of the application, in such frameworks, the deployer, the individual(s) who configures the application server to manage concurrency, transaction and persistence correctly and efficiently, plays a central role. a deployer has few tools to assist with performing this complicated task. incorrect configuration can lead to application failure or severe underperformance. we outline the problems facing the deployer of applications, present a methodology that can assist the programmer with the task of configuring application servers, and present two case studies that validate the usefulness of our methodology.
models of software development environments. we present a general model of software development environments that consists of three components: policies, mechanisms and structures. the advantage of this formalization is that it distinguishes precisely those aspects of an environment that are useful in comparing and contrasting software development environments. we introduce four classes of models by means of a sociological metaphor that emphasizes scale: the individual, the family, the city and the state models. the utility of this taxonomy is that it delineates the important classes of interaction among software developers and exposes the ways in which current software development environments inadequately support the development of large systems. environments reflecting the individual and family models are the current state of the art. unfortunately, these two models are ill-suited for the development of large systems that require more than, say, 20 programmers. we argue that there is a qualitative difference between the interactions among a small, &ldquo;family&rdquo; project and a large, &ldquo;city&rdquo; project and that this qualitative difference requires a fundamentally different model of software development environments. we illustrate the city model with inscape/infuse and istar, the only two environments we know of that instantiate this model, and show that there is a pressing need for further research on this kind of environment. finally, we postulate a state model, which is in need of further clarification, understanding and, ultimately, implementation.
one more step in the direction of modularized integration concerns. component integration creates value by automatingthe costly and error-prone task of imposing desiredbehavioral relationships on components manually.requirements for component integration, however,complicate software design and evolution in severalways: first, they lead to coupling among components;second, the code that implements various integrationconcerns in a system is often scattered over and tangledwith the code implementing the component behaviors.straightforward software design techniques mapintegration requirements to scattered and tangled code,compromising modularity in ways that dramaticallyincrease development and maintenance costs.
classpects: unifying aspect- and object-oriented language design. the contribution of this work is the design, implementation, and early evaluation of a programming language that unifies classes and aspects. we call our new module construct the classpect. we make three basic claims. first, we can realize a unified design without significantly compromising the expressiveness of current aspect languages. second, such a design improves the conceptual integrity of the programming model. third, it significantly improves the compositionality of aspect modules, expanding the program design space from the two-layered model of aspectj-like languages to include hierarchical structures. to support these claims, we present the design and implementation of eos-u, an aspectj-like language based on c# that supports classpects as the basic unit of modularity. we show that eos-u supports layered designs in which classpects separate integration concerns flexibly at multiple levels of composition. the underpinnings of our design include support for aspect instantiation under program control, instance-level advising, advising as a general alternative to object-oriented method invocation and overriding, and the provision of a separate join-point-method binding construct.
case studies for software engineers. the topic of this full-day tutorial was the correct useand interpretation of case studies as an empiricalresearch method. using an equal blend of lecture anddiscussion, it gave attendees a foundation for conducting,reviewing, and reading case studies. there were lessonsfor software engineers as researchers who conduct andreport case studies, reviewers who evaluate papers, andpractitioners who are attempting to apply results frompapers. the main resource for the course was the bookcase study research: design and methods by robert k.yin. this text was supplemented with positive andnegative examples from the literature.
case studies for software engineers. the topic of this full-day tutorial was the correct use and interpretation of case studies as an empirical research method. using an equal blend of lecture and discussion, it gave attendees a foundation for conducting, reviewing, and reading case studies. there were lessons for software engineers as researchers who conduct and report case studies, reviewers who evaluate papers, and practitioners who are attempting to apply results from papers. the main resource for the course was the book case study research: design and methods by robert k. yin. this text was supplemented with positive and negative examples from the literature.
parallel changes in large scale software development: an observational case study. an essential characteristic of large-scale software development is parallel development by teams of developers. how this parallel development is structured and supported has a profound effect on both the quality and timeliness of the product. we conduct an observational case study in which we collect and analyze the change and configuration management history of a legacy system to delineate the boundaries of, and to understand the nature of, the problems encountered in parallel development. the results of our studies are (1) that the degree of parallelism is very highhigher than considered by tool builders; (2) there are multiple levels of parallelism, and the data for some important aspects are uniform and consistent for all levels; (3) the tails of the distributions are long, indicating the tail, rather than the mean, must receive serious attention in providing solutions for these problems; and (4) there is a significant correlation between the degree of parallel work on a given component and the number of quality problems it has. thus, the results of this study are important both for tool builders and for process and project engineers.
symbolic interpretation and tracing of pascal-programs. in this paper we describe a system for symbolic interpretation and tracing of programs written in pascal. we show how the symbolic execution method of king can be extended to handle special pascal-features and complex data structures. the system is designed for practical use. it should support the programmer in the modular program development process without bothering him with additional specifications.
semantics-based reverse engineering of object-oriented data models. we present an algorithm for reverse engineering object-oriented (oo) data models from programs written in weakly-typed languages like cobol. these models, similar to uml class diagrams, can facilitate a variety of program maintenance and migration activities. our algorithm is based on a semantic analysis of the program's code, and we provide a bisimulation-based formalization of what it means for an oo data model to be correct for a program.
test case generation using prolog. for the validation of the kernel system calls of a family of unix 1) systems a knowledge based test environment was conceived. a prototype version is currently implemented in prolog. the knowledge base consists essentially of three parts: test case specifications of the various system calls, a test suite generator with predicates including information about unix system properties and sound test practices, and a test protocol archive including utilities to extract and prepare reports about the test results. all information in the knowledge base is stored as horn clauses, i.e. facts and rules immediately to be consulted and executed by a prolog interpreter.
a model of software engineering. the field of software engineering is currently in its formative stages. consequently, it does not exhibit the structure and discipline present in other, more established engineering disciplines. the technique of morphological analysis is applied to the field of software engineering to identify the form and structure present. applications in the areas of software engineering research and software engineering curricula are discussed.
dual: an interactive tool for developing documented programs by step-wise refinements. programs are integrated hierarchical structures of formal texts - instructions - and informal texts - documentation. only if there is a mechanical connection between program design and program development there can be higher chances that the program documentation, originated at design time, will not, sooner or later, become obsolete with respect to the current state of the system. dual is an interactive, incremental, intelligent editor of program and documentation texts to be used for software implementations whose anticipated life cycle is significantly long to deserve much attention. the screen interface plays a unique role in dual since it allows a visitor ( designer or maintenance engineer) &ldquo;to replay&rdquo; as many times as desired the evolution of the system from design to implementation. the access to the hierarchically organized design information is made easy and natural by the dual video oriented user interface.
building awareness of system testing issues. managers of large software projects with system test groups face a problem that they may not be aware of. vague notions among project members about the role of system testing tend to cloud the relationship between developers and testers with misunderstanding and disappointment. the main source of the problem is unrealistic expectations about what can be accomplished during the system test phase of the project. this has the effect of de-emphasizing the developers' responsibility for software quality and imposing a definition of success on system testers that is not possible to achieve. this paper describes a series of role awareness seminars at which a discussion technique was used to clarify expectations between developers and testers. transcending the discussion of roles was a fundamental message: the quality of software is determined during the development phase and cannot be radically improved during the system test phase.
modeling behavioral design patterns of concurrent objects. object-oriented software development practices are being rapidly adopted within increasingly complex systems, including reactive, real-time and concurrent system applications. while data modeling is performed very well under current object-oriented development practices, behavioral modeling necessary to capture critical information in real-time, reactive, and concurrent systems is often lacking. addressing this deficiency, we offer an approach for modeling and analyzing concurrent object-oriented software designs through the use of behavioral design patterns, allowing us to map stereotyped uml objects to colored petri net (cpn) representations in the form of reusable templates. the resulting cpns are then used to model and analyze behavioral properties of the software architecture, applying the results of the analysis to the original software design.
resource controller tasks in ada: their structure and semantics. the focus of this paper is on the processes that control access to shared resources in concurrent systems. processes that access a shared resource send access requests to the controller of the shared resource which in turn services requests based on such criteria as the conditions enabling the requests, the fairness specified, etc. in this paper we examine the structure of resource controllers, in particular, we show how resource controllers manifest themselves in ada. our prime motivation for this work is to develop schemes by which controllers with complex resource control policies can be implemented using the tasking constructs of ada. to enable the verification of ada resource controllers, we provide a temporal semantics for the tasking constructs as well as for the resource controller components.
specifying and proving properties of sentinel processes. this paper presents a technique for specifying and verifying properties of &ldquo;sentinels&rdquo;&mdash;a high-level language construct for synchronizing access to shared resources. statements in the specification language possess formal temporal semantics. as a prelude to proving the correctness of sentinels, the semantics of constructs used in sentinels is given. the proof technique involves showing that the temporal behavior of a sentinel conforms to that defined by the specification. the methodology is illustrated by applying it to a typical synchronization problem.
algorithmic cost estimation for software evolution. this study addresses the problem of cost estimation in the context of software evolution by building a set of quantitative models and assessing their predictive power. the models aim at capturing the relationship between effort, productivity and a suite of metrics of software evolution extracted from empirical data sets.
understanding code mobility (tutorial session). the tutorial provides a conceptual framework for code mobility by illustrating a taxonomy of related technologies, architectural paradigms, and applications. as a final case study, the concepts developed in the taxonomy are then applied to a quantitative assessment of the benefits of mobile code technologies and architectures in the network management application domain.
exception-chain analysis: revealing exception handling architecture in java server applications. although it is common in large java programs to rethrow exceptions, existing exception-flow analyses find only single exception-flow links, thus are unable to identify multiple-link exception propagation paths. this paper presents a new static analysis that, when combined with previous exception-flow analyses, computes chains of semantically-related exception-flow links, and thus reports entire exception propagation paths, instead of just discrete segments of them. these chains can be used 1) to show the error handling architecture of a system, 2) to assess the vulnerability of a single component and the whole system, 3) to support better testing of error recovery code, and 4) to facilitate the tracing of the root cause of a logged problem. empirical findings and a case history for tomcat show that a significant portion of the chains found in our benchmarks span multiple components, and thus are hard to find manually.
analyzing the test process using structural coverage. a large, commercially developed fortran program was modified to produce structural coverage metrics. the modified program was executed on a set of functionally generated acceptance tests and a large sample of operational usage cases. the resulting structural coverage metrics are combined with fault and error data to evaluate structural coverage in the sel environment. we can show that in this environment the functionally generated tests seem to be a good approximation of operational use. the relative proportions of the exercised statement sub-classes (executable, assignment, call, do, if, read, write) changes as the structural coverage of the program increases. we also propose a method for evaluating if two sets of input data exercise a program in a similar manner. we also provide evidence that implies that in this environment, faults revealed in a procedure are independent of the number of times the procedure is executed and that it may be reasonable to use procedure coverage in software models that use statement coverage. finally, the evidence suggests that it may be possible to use structural coverage to aid in the management of the acceptance test process.
3rd international workshop on software engineering for automotive systems - seas 2006. this workshop summary presents an overview of the one-day international workshop on software engineering for automotive systems (seas 2006), held in conjunction with the 28 th international conference on software engineering (icse'06). details about seas 2006 may be found at: http://www.inf.ethz.ch/personal/pretscha/events/seas06/.
data flow analysis techniques for test data selection. this paper examines a family of program test data selection criteria derived from data flow analysis techniques similar to those used in compiler optimization. it is argued that currently used path selection criteria which examine only the control flow of a program are inadequate. our procedure associates with each point in a program at which a variable is defined, those points at which the value is used. several related path criteria, which differ in the number of these associations needed to adequately test the program, are defined and compared.
aspect-oriented software development beyond programming. this tutorial focuses on applying aspect-oriented software development (aosd) concepts beyond the programming stage of the software development life cycle. using concrete methods, tools, techniques and notations we discuss how to use aosd techniques to systematically treat crosscutting concerns during requirements engineering (re), architecture design and detailed design as well as the mapping between aspects at these stages. with a clear focus on composition, modelling, trade-off analysis and assessment methods, the tutorial imparts an engineering ethos for translation into day-to-day processes and practices.
human-computer communication meets software engineering. a contemporary software engineering problem is to adapt an existing piece of software to a new interface technology.we describe the process of integrating a software engineering tool with a window-based direct manipulation interface. four stages of this process are described - from a simple integration to a fully integrated system in which it becomes hard to separate properties of the tool from those of the interface.we take advantage of wlisp, an object-oriented, knowledge-based user interface construction kit that contains a large number of tools and intelligent support systems. the object-oriented architecture of wlisp is well suited for making use of existing interface components and tailoring them to the specific needs of the application. this is illustrated by describing the implementation of two of the four integration stages in some detail. thereby we show benefits and problems of separating the interface from the application system.
software evolution in componentware using requirements/assurances contracts. in practice, pure top-down and refinement-based development processes are not sufficient. usually, an iterative and incremental approach is applied instead. existing methodologies, however, do not support such evolutionary development processes very well. in this paper, we present the basic concepts of an overall methodology based on component ware and software evolution. the foundation of our methodology is a novel, well-founded model for component-based systems. this model is sufficiently powerful to handle the fundamental structural and behavioral aspects of component ware and object-orientation. based on the model, we are able to provide a clear definition of a software evolution step.during development, each evolution step implies changes of an appropriate set of development documents. in order to model and track the dependencies between these documents, we introduce the concept of requirements/assurances contracts. these contracts can be rechecked whenever the specification of a component evolves, enabling us to determine the impacts of the respective evolution step. based on the proposed approach, developers are able to track and manage the software evolution process and to recognize and avoid failures due to software evolution. a short example shows the usefulness of the presented concepts and introduces a practical description technique for requirements/assurances contracts.
the structure and characteristics of distributed systems. phrases such as 'distributed processing' and 'distributed operating systems' are currently very much in vogue and are being applied to many systems that seem to be entirely different in nature. what used to be a system with a separate input-output channel or a multiprocessor system or a network without load balancing is now a distributed system. the common feature seems to be a multiplicity; i. e., more than one, of clearly distinguishable modules, as determined by the beholder, operating simultaneously. this paper is an attempt to categorize distributed systems so that one can examine the generic characteristics and problems associated with each category. the first step is to realize that distribution involves the apportioning of a set of tasks among a set of entities that can perform the tasks.
architectural interaction diagrams: aids for system modeling. this paper develops a modeling paradigm called architectural interaction diagrams, or aids, for the high-level design of systems containing concurrent, interacting components. the novelty of aids is that they introduce interaction mechanisms, or buses, as first-class entities into the modeling vocabulary. users then have the capability, in their modeling, of using buses whose behavior captures interaction at a higher level of abstraction than that afforded by modeling notations such as message sequence charts or process algebra, which typically provide only one fixed interaction mechanism. this paper defines aids formally by giving them an operational semantics that describes how buses combine subsystem transitions into system-level transitions. this semantics enables aids to be simulated; to incorporate subsystems given in different modeling notations into a single system model; and to use testing, debugging and model checking early in the system design cycle in order to catch design errors before they are implemented.
on the syllogistic structure of object-oriented programming. recent works by sowa and by rayside & campbell demonstrate that there is a strong connection between object-oriented programming and the logical formalism of the syllogism, first set down by aristotle in the prior analytics. in this paper, we develop an understanding of polymorphic method invocations in terms of the syllogism, and apply this understanding to the design of a novel editor for object-oriented programs. this editor is able to display a polymorphic call graph, which is a substantially more difficult problem than displaying a non-polymorphic call graph. we also explore the design space of program analyses related to the syllogism, and find that this space includes unique name, class hierarchy analysis, class hierarchy slicing, class hierarchy specialization, and rapid type analysis.
semantic anomaly detection in online data sources. much of the software we use for everyday purposes incorporates elements developed and maintained by someone other than the developer. these elements include not only code and databases but also dynamic data feeds from online data sources. although everyday software is not mission critical, it must be dependable enough for practical use. this is limited by the dependability of the incorporated elements.it is particularly difficult to evaluate the dependability of dynamic data feeds, because they may be changed by their proprietors as they are used. further, the specifications of these data feeds are often even sketchier than the specifications of software components.we demonstrate a method of inferring invariants about the normal behavior of dynamic data feeds. we use these invariants as proxies for specifications to perform on-going detection of anomalies in the data feed. we show the feasibility of our approach and demonstrate its usefulness for semantic anomaly detection: identifying occasions when a dynamic data feed is delivering unreasonable values, even though its behavior may be superficially acceptable (i.e., it is delivering parsable results in a timely fashion).
supporting reflective practitioners. the theme and title for this panel is inspired bydonald schönýs writings about the reflective practitionerin which he describes professional practice as being aprocess of reflection in action. ill-defined problemsincluding design decisions lead to breakdowns, whichbecome opportunities for reflection and modification ofpractice. this panel seeks to provide icse attendees witha broad cross section of the history, state of the art, andopen issues with some of the methods and tools directedat supporting reflective software practitioners.
reuse of verificatino efforts and incomplete specifications in a formalized, iterative and incremental software process. the possibility of verifying systems during any phase of the software development process is one of the most significant advantages of using formal methods. model checking is considered to be the broadest used formal verification technique, even though a great quantity of computing resources are needed to verify medium-large and large systems. as verification is prevent over the whole software process, these amount of resources is more critic in incremental and iterative life cycles. our proposal focuses on reusing incomplete models and their verification results &mdash;which are obtained from a model checking algorithm&mdash; in order to improve these kind of life cycles. making good use of these previous verification results can reduce the formal verification costs by minimizing the set of requirements and the set of system states where the properties must be verified. the unspecification inherent to incomplete systems is used to provide an approximate and content-oriented retrieval which is supplemented by suggestions to match the desired specifications.
software technology maturation. we have reviewed the growth and propagation of a variety of software technologies in an attempt to discover natural characteristics of the process as well as principles and techniques useful in transitioning modern software technology into widespread use. what we have looked at is the technology maturation process, the process by which a piece of technology is first conceived, then shaped into something usable, and finally &ldquo;marketed&rdquo; to the point that it is found in the repertoire of a majority of professionals. a major interest is the time required for technology maturation &mdash; and our conclusion is that technology maturation generally takes much longer than popularly thought, especially for major technology areas. but our prime interest is in determining what actions, if any, can accelerate the maturation of technology, in particular that part of maturation that has to do with transitioning the technology into widespread use. our observations concerning maturation facilitators and inhibitors are the major subject of this paper.
prototyping real-time vision systems: an experiment in dsl design. describes the enhancement of xvision, a large library of c++ code for real-time vision processing, into fvision (pronounced "fission"), a fully-featured domain-specific language (dsl) embedded in haskell. the resulting prototype system substantiates the claims of increased modularity, effective code reuse and rapid prototyping that characterize the dsl approach to systems design. it also illustrates the need for judicious interface design: relegating computationally expensive tasks to xvision (pre-existing c++ components) and leaving modular compositional tasks to fvision (haskell). at the same time, our experience demonstrates how haskell's advanced language features (specifically, parametric polymorphism, lazy evaluation, higher-order functions and automatic storage reclamation) permit a rapid dsl design that is itself highly modular and easily modified. overall, the resulting hybrid system exceeded our expectations: visual tracking programs continue to spend most of their time executing low-level image processing code, while haskell's advanced features allow us to quickly develop and test small prototype systems within a matter of a few days, and to develop realistic applications within a few weeks.
jive: visualizing java in action demonstration description. dynamic software visualization should provide a programmer with insights as to what the program is doing. most current dynamic visualizations either use program traces to show information about prior runs, slow the program down substantially, show only minimal information, or force the programmer to indicate when to turn visualizations on or off. we have developed a dynamic java visualizer that provides a view of a program in action with low enough overhead that it can be used almost all the time by programmers to understand what their program is doing while it is doing it.
pecan: program development systems that support multiple views. this paper describes the pecan family of program development systems. pecan supports multiple views of the user's program. the views can be representations of the program or of the corresponding semantics. the primary program view is a syntax-directed editor. the current semantic views include expression trees, data type diagrams, flow graphs, and the symbol table. pecan is designed to make effective use of powerful personal machines with high-resolution graphics displays and is currently implemented on apollo workstations.
a conceptual programming environment. conceptual programming means having programmers work directly with their models of how their system is put together. it means providing them with the means for designing, coding and maintaining systems on a computer using the pictures and text they normally use on paper. an environment for conceptual programming requires flexibility to support a wide range of languages and graphics to support languages based on pictures. the garden system is a prototype conceptual programming environment that uses an object-oriented framework to meet these requirements.
simplifying data integration: the design of the desert software development environment. this paper describes the design and motivations behind the desert environment. the desert environment has been created to demonstrate that the facilities typically associated with expensive data integration can be provided inexpensively in an open framework. it uses three integration mechanisms: control integration, simple data integration based on fragments, and a common editor. it offers a variety of capabilities including hyperlinks and the ability to create virtual files containing only the portions of the software that are relevant to the task on hand. it does this in an open environment that is compatible with existing tools and programs. the environment currently consists of a set of support facilities including a context database, a fragment database, scanners, and a tooltalk interface, as well as a preliminary set of programming tools including a context manager and extensions to framemaker to support program editing and insets for non-textual software artifacts.
clime: an environment for constrained evolution demonstration description. we are building a software development environment that uses constraints to ensure the consistency of the different artifacts associated with software. this approach to software development makes the environment responsible for detecting most inconsistencies between software design, specifications, documentation, source code, and test cases. the environment provides facilities to ensure that these various dimensions remain consistent as the software is written and evolves. the environment works with the wide variety of artifacts typically associated with a large software system. it handles both the static and dynamic aspects of software. moreover, it works incrementally so that consistency information is readily available to the developer as the system changes. the demonstration will show this environment and its capabilities.
encoding program executions. dynamic analysis is based on collecting data as the program runs. however, raw traces tend to be too voluminous and too unstructured to be used directly for visualization and understanding. we address this problem in two phases: the first phase selects subsets of the data and then compacts it, while the second phase encodes the data in an attempt to infer its structure. our major compaction/selection techniques include gprof-style n-depth call sequences, selection based on class, compaction based on time intervals, and encoding the whole execution as a directed acyclic graph. our structure inference techniques include run-length encoding, context-free grammar encoding, and the building of finite state automata.
demonstration of jive and jove: java as it happens. dynamic software visualization is designed to provide programmers with insights as to what the program is doing. most current visualizations either use program traces to show information about prior runs, slow the program down substantially, show only minimal information, or force the programmer to indicate when to turn visualizations on or off. we have developed a dynamic java visualizer that provides a statement-level view of a java program in action with low enough overhead so that it can be used almost all the time by programmers to understand what their program is doing while it is doing it.
a user interface for online assistance. this paper describes a software user interface that enables programmers to provide and maintain online aids in an interactive system. through the interface, users are given a set of consistent and unobtrusive aids that display summary information, command descriptions, explanations of error messages, and other online documentation. the interface is presented here from the views of both the end-user and the programmer.
prediction and management of program quality. techniques such as design reviews, code inspections, and system testing are commonly being used to remove defects from programs as early as possible in the development process. the objective of this paper is to demonstrate that predictors can be devised which tell us how well defects are being removed during the defect removal process. the approach is to develop a straightforward model of the defect removal process, and then use that model to develop formulas that show how measurable parameters&mdash;such as the ratio of major problems (mps) removed by reviews and inspections to the number of problems (ptms) removed by testing and the length (l) of an average problem fix&mdash;can be used to estimate: - effectiveness of the overall defect removal process - number of defects that remain at the time the product is first shipped to customers. on the bases of statistics for current products, numerical values for effectiveness measures can then be calculated.
chianti: a change impact analysis tool for java programs. chianti is a change impact analysis tool for java that is implemented in the context of the eclipse environment. chianti analyzes two versions of a java program, decomposes their difference into a set of atomic changes, and a partial order inter-dependences of these changes is calculated. change impact is then reported in terms of affected (regression or unit) tests whose execution behavior may have been modified by the applied changes. for each affected test, chianti also determines a set of affecting changes that were responsible for the test's modified behavior. this latter step of isolating failure inducing changes for one specific test from irrelevant changes can be used as a debugging technique in situations where a test fails unexpectedly after a long editing session.
systems engineering: an essential engineering discipline for the 21st century. the engineering of systems in the 21st century demands robust use of the systems approach given the nature of our times, as well as the systems being created. the global marketplace, changing competition dynamics, shorter life cycles, and increasing complexity characterize our environment. we are building systems that are much larger than ever before. and, we are building systems that are infinitely smaller than ever before. maturity of technical, management, and infrastructure processes are competitive discriminators. systems engineering, both as a profession and as practiced by multi-discipline practitioners, is key to addressing these challenges.over the past decade, there have been frequent debates on whether systems engineering is an approach or a formal field of engineering. given the technical, management, and environmental challenges of this century, i believe that systems engineering must be an essential engineering discipline for the 21st century. this talk will discuss the state of the art and practice of systems engineering, and several initiatives focused on its evolution as a formal engineering discipline.while systems engineering approaches date back to ancient times, the recent few decades have largely featured practices and methods that extend from efforts of the 1950's, thus drawing heavily from hardware engineering. as software engineering has grown as a discipline, it has had significant influence on the field of systems engineering. further, as systems engineering becomes a more integral part of commercial product development, the character of the systems engineering discipline expands and the associated research agenda takes new shape. systems engineering and software engineering must each evolve as unique engineering disciplines to address the engineering problems of the 21st century. we must ensure their evolution results in shared knowledge, and highly collaborative approaches and methods drawing on the unique strengths of each discipline.
analysis and testing of web applications. the economic relevance of web applications increases the importance of controlling and improving their quality. moreover, the new available technologies for their development allow the insertion of sophisticated functions, but often leave the developers responsible for their organization and evolution. as a consequence, a high demand is emerging for methodologies and tools for quality assurance of web based systems. in this paper, a uml model of web applications is proposed for their high level representation. such a model is the starting point for several analyses, which can help in the assessment of the static site structure. moreover, it drives web application testing, in that it can be exploited to define white box testing criteria and to semi-automatically generate the associated test cases. the proposed techniques were applied to several real world web applications. results suggest that an automatic support to the verification and validation activities can be extremely beneficial. in fact, it guarantees that all paths in the site which satisfy a selected criterion are properly exercised before delivery. the high level of automation that is achieved in test case generation and execution increases the number of tests that are conducted and simplifies the regression checks.
the inspection metho applied to small projects. the inspection method is a quality-control for written material. it is used on large projects and takes 3 to 8 persons for correct use. this excludes small projects with less than three persons from proper inspection. this paper shows how the personnel restriction may be circumvented in small projects. an example of inspection in a small project (writing a report) is given.
a partition analysis method to increase program reliability. a major drawback of most program testing methods is that they ignore program specifications, and instead base their analysis solely on the information provided in the implementation. this paper describes the partition analysis method, which assists in program testing and verification by evaluating information from both a specification and an implementation. this method employs symbolic evaluation techniques to partition the set of input data into procedure subdomains so that the elements of each subdomain are treated uniformly by the specification and processed uniformly by the implementation. the partition divides the procedure domain into more manageable units. information related to each subdomain is used to guide in the selection of test data and to verify consistency between the specification and the implementation. moreover, the test data selection process, called partition analysis testing, and the verification process, called partition analysis verification, are used to enhance each other, and thus increase program reliability.
on reliable topologies for computer networks. a computer communiation network is topologically described as a linear graph. network topologies are characterized by their associated reliability (invulnerability), overall link capacity (bandwidth) and maximal average message terminal delay. the corresponding graph theoretical parameters are the connectivity, number of lines and diameter of the underlying graph. for store-and-forward computer networks, k-connected topologies yielding the minimal delay-capacity product values are presented. such structures are noted to have a node of very high degree (i.e., connected to many other nodes). subsequently, we consider k-connected networks with regular nodes (of low degree) containing also a set of &ldquo;advanced&rdquo; (&ldquo;central&rdquo;) nodes (of higher, though appropriately bounded) degree. corresponding extremal k-connected topologies which guarantee every regular node to be within a prescribed distance from the center (being the set of central nodes), and to include a minimal center size, are derived. the optimal radius values for such network structures, to yield a minimal delay-capacity product value, are also noted.
a context-oriented framework for software testing in pervasive environment. in this article, we present our test framework for assuring pervasive software applications that overcomes the identified challenges faced by conventional testing techniques. the framework will serve as a basis for automating the test process, as well as to assist testers in generating adequacy test sets or finding test oracles.
distributed development: an education perspective on the global studio project. the global studio project integrated the work of software engineering students spread across four countries into a single project and represented, for most of the students, their first major "real-world" development experience. interviews indicated that the major areas of learning were informal skills that included learning to establish and work effectively within a team, learning how to react quickly to frequent changes in requirements, architecture and organization, and learning to manage and optimize communications. since all these skills require rapid reaction to unpredictable factors, we view them as improvisation and discuss the role of experiential education in facilitating improvisation.
embedded architect: a tool for early performance evaluation of embedded software. embedded architect is a design automation tool that embodies a static performance evaluation technique to support early, architecture-level design space exploration for component-based embedded systems. a static control flow characterization, called an evaluation scenario, is specified based on an incremental refinement of software source code, from which a pseudo-trace of operations is generated. in combination with architecture mapping and several component parameters, a software performance metric is estimated.the novel contribution is the implementation of a tool that automates specification of an evaluation scenario, which sets the context for a rapid performance evaluation of distinct candidate architectures.
improving the software process. needs and possibilities for software processes are constantly changing, and improvement is therefore a continual process. part of the task of software process improvement is the comparative evaluation of alternatives with the intent of deciding whether to shift to a new process or keep/adjust an existing one. an equally important task is to constantly increase the flexibility to adapt a software process to meet new project-related or organizational needs or utilize new technology.the intent of this panel is to expose, compare and contrast a variety of strategies and tactics for improving the software process. the assumption is that no single strategy or set of tactics will ever be best in all situations. to set the stage, the strategy and tactics discussed in the paper &ldquo;tailoring the software process to project goals and environments,&rdquo; by basili and rombach, will be presented. the panelists, each of whom has a direct responsibility for software technology improvement, will then briefly present the approaches they are using to guide software process improvement. the ensuing discussion is intended to uncover critical differences and similarities and lead to an understanding of the contexts in which the various approaches can succeed.
designing software for use by humans, not machines. the authors describe an architecture that supports a more user-centered way to design software applications architectures, and by using a specific example, they also describe benefits gained by the software applications that result. the architecture aims to resolve some management and maintenance problems which have arisen in the telecommunications support systems network specifically, but which the authors also envision arising in any large-scale, multivendor, database environment. this examination includes consideration of technological advances in user-centered design, recent discoveries about the ability to separate processing functionalityfrom user interface functionality, and the rapidly expanding wealth of available user interface software tools
experimental program analysis: a new paradigm for program analysis. program analysis techniques are used by software engineers to deduce and infer targeted characteristics of software systems for tasks such as testing, debugging, maintenance, and program comprehension. recently, some program analysis techniques have been designed to leverage characteristics of traditional experimentation in order to analyze software systems. we believe that the use of experimentation for program analysis constitutes a new program analysis paradigm: experimental program analysis. this research seeks to accomplish four goals: to precisely define experimental program analysis, to provide a means for classifying experimental program analysis techniques, to identify existing experimental program analysis techniques in the research literature, and to enhance the use of experimental program analysis by improving existing, and by creating new, experimental program analysis techniques.
behavior modelling during software design. a modeling scheme is presented which provides a medium for the rigorous, formal, and abstract specification of large-scale software system components. the scheme allows the description of component behavior without revealing or requiring the description of a component's internal operation. both collections of sequential processes and the data objects which they share may be described. the scheme is of particular value during the early stages of software system design, when the system's modules are being delineated and their interactions designed, and when rigorous, well-defined specification of undesigned components allows formal and informal arguments concerning the design's correctness to be formulated.
an empirical study of fault localization for end-user programmers. end users develop more software than any other group of programmers, using software authoring devices such as e-mail filtering editors, by-demonstration macro builders, and spreadsheet environments. despite this, there has been little research on finding ways to help these programmers with the dependability of their software. we have been addressing this problem in several ways, one of which includes supporting end-user debugging activities through fault localization techniques. this paper presents the results of an empirical study conducted in an end-user programming environment to examine the impact of two separate factors in fault localization techniques that affect technique effectiveness. our results shed new insights into fault localization techniques for end-user programmers and the factors that affect them, with significant implications for the evaluation of those techniques.
when the project absolutely must get done: marrying the organization chart with the precedence diagram. very little is new in project planning, but this is! we present a technique to marry the organization chart with a project's task precedence diagram. this permits us to simulate the project at a micro, project-specific level never before achieved. we can perform &ldquo;what-if&rdquo; scenarios related to organization structures, the deployment of specific individuals and skills, and the structure of information flow and exception-handling in a project. the tool used, viteproject, was developed over the last ten years in a stanford university laboratory, where substantial results have been achieved when applied to design activities other than software. we present our real-world experience with several software projects, where it has improved project visibility and allowed us to rationally optimize projects in a way hitherto impossible.
visualizing software release histories with 3dsoftvis. this paper briefly introduces a 3-d visualization tool (3dsoftvis) that has been developed for the analysis of the evolution of an industrial software system.
using event-based translation to support dynamic protocol evolution. all systems built from distributed components involve theuse of one or more protocols for inter-component communication.whether these protocols are based on a broadlyused "standard" or are specially designed for a particularapplication, they are likely to evolve. the goal of the workdescribed here is to contribute techniques that can supportprotocol evolution. we are concerned not with how or whya protocol might evolve, or even whether that evolution isin some sense correct. rather, our concern is with making itpossible for applications to accommodate protocol changesdynamically. our approach is based on a method for isolatingthe syntactic details of a protocol from the semanticconcepts manipulated within components. protocol syntaxis formally specified in terms of tokens, message structures,and message sequences. event-based translation techniquesare used in a novel way to present to the application the semanticconcepts embodied by these syntactic elements. weillustrate our approach by showing how it would support anhttp 1.1 client interacting with an http 1.0 server.
software engineering and the internet. to successfully compete in the drive towards e-business, businesses are faced with challenges that strain their resources across all fronts. in their bid to win new market share, businesses must balance the necessity of new innovative products, released on ever shortening cycles, with the maintenance of their core business" a core that provides the capital leverage needed to fuel this new growth. businesses must succeed in these changes with a skills base that is, relative to the market requirements, diminishing. achieving equilibrium between demands that historically have been treated as dichotomous will require nothing less than a change in the very culture of the software engineering community. this change is evident, but how will we, as a the software community, be successful in effecting this change? successful modification of this culture begins with an understanding, at all levels, of the change in the skills pool and the exponential rise in the need for reliable, scalable systems that can accommodate millions of customers on ever more complex internet based e-business applications. while an increasing number of businesses deploy mission critical applications and begin to build e-market places on the internet, we need to be able to adapt our software engineering philosophy to create software in a more flexible enviromnent that focuses on delivering capability in a more time-critical fashion than we have been challenged to do in the past. the paradigm of designing to perfection must be scaled back to a model that facilitates progressive discovery for the growing population of programmers who are relatively new to the business. only when we can deliver flexible software to support the deployment of these new e-business applications will we succeed in supporting the drive to e-business.
concern graphs: finding and describing concerns using structural program dependencies. many maintenance tasks address concerns, or features, that are not well modularized in the source code comprising a system. existing approaches available to help software developers locate and manage scattered concerns use a representation based on lines of source code, complicating the analysis of the concerns. in this paper, we introduce the concern graph representation that abstracts the implementation details of a concern and makes explicit the relationships between different parts of the concern. the abstraction used in a concern graph has been designed to allow an obvious and inexpensive mapping back to the corresponding source code. to investigate the practical tradeoffs related to this approach, we have built the feature exploration and analysis tool (feat) that allows a developer to manipulate a concern representation extracted from a java system, and to analyze the relationships of that concern to the code base. we have used this tool to find and describe concerns related to software change tasks. we have performed case studies to evaluate the feasibility, usability, and scalability of the approach. our results indicate that concern graphs can be used to document a concern for change, that developers unfamiliar with concern graphs can use them effectively, and that the underlying technology scales to industrial-sized programs.
test factoring: focusing test suites for the task at hand. no abstract available
continuous testing in eclipse. continuous testing uses excess cycles on a developer's workstation to continuously run regression tests in the background, providing rapid feedback about test failures as code is edited. it reduces the time and energy required to keep code well-tested, and it prevents regression errors from persisting uncaught for long periods of time.
first international workshop on the modeling and analysis of concerns in software (macs 2005). many software engineering activities are organized around the idea of concerns. separation of concerns is a basic tenet of software engineering intended to facilitate the development and evolution of software systems. unfortunately, separation of concerns is not always possible in practice, and concerns often end up scattered and tangled. the goal of the macs workshop is to bring together researchers and practitioners with interest and experience in techniques for modeling and analyzing the realization of concerns in software systems.
specifying multithreaded java semantics for program verification. the java programming language supports multithreading where the threads interact among themselves via read/write of shared data. most current work on multithreaded java program verification assumes a model of execution that is based on interleaving of the operations of the individual threads. however, the java language specification (which any implementations of java multithreading must follow) supports a weaker model of execution, called the java memory model (jmm). the jmm allows certain reordering of operations within a thread and thus permits more behaviors than the interleaving based execution model. therefore, programs verified by assuming interleaved thread execution may not behave correctly for certain java multithreading implementations.the main difficulty with the jmm is that it is informally described in an abstract rule-based declarative style, which is unsuitable for formal verification. in this paper, we develop an equivalent formal executable specification of the jmm. our specification is operational and uses guarded commands. we then use this executable model to verify popular software construction idioms (commonly used program fragments/patterns) for multithreaded java. our prototype verifier tool detects a bug in the widely used "double-checked locking" idiom, which verifiers based on interleaving execution model cannot possibly detect.
measuring cognitive activities in software engineering. this paper presents an approach to the study of cognitive activities in collaborative software development. this approach has been developed by a multidisciplinary team made up of software engineers and cognitive psychologists. the basis of this approach is to improve our understanding of software development by observing professionals at work. the goal is to derive lines of conduct or good practices based on observations and analyses of the processes that are naturally used by software engineers. the strategy involved is derived from a standard approach in cognitive science. it is based on the videotaping of the activities of software engineers, transcription of the videos, coding of the transcription, defining categories from the coded episodes and defining cognitive behaviors or dialogs from the categories. this project presents two original contributions that make this approach generic in software engineering. the first contribution is the introduction of a formal hierarchical coding scheme, which will enable comparison of various types of observations. the second is the merging of psychological and statistical analysis approaches to build a cognitive model. the details of this new approach are illustrated with the initial data obtained from the analysis of technical review meetings
specification of abstract data types with partially defined operations. we investigate equational inference rules for partial algebras and propose conditionally complete equational inference rules for partial algebras. based on the results obtained from the investigation we propose a new algebraic specification technique for partial abstract data types. it requires no superfluous equations concerning undefinedness.
efficient path conditions in dependence graphs. program slicing combined with constraint solving is a powerful tool for software analysis. path conditions are generated for a slice or chop, which --- when solved for the input variables --- deliver compact "witnesses" for dependences or illegal influences between program points.in this contribution we show how to make path conditions work for large programs. aggressive engineering, based on interval analysis and bdds, is shown to overcome the potential combinatoric explosion. case studies and empirical data will demonstrate the usefulness of path conditions for practical program analysis.
toward computational support for software process improvement activities. software organizations and projects need guidance on how to improve software process, not just guidelines on what to improve. several surveys demonstrate that the capability maturity model (cmm) and iso-9000 only provide the latter. we report our in-depth analysis on a seventeen-month effort in software process improvement (spi) at omron corporation. the goal of the analysis was to identify issues and challenges of spi and to design a step-wise practical method to avoid such problems. major problems we have found include the lack of shared goal among stakeholders, insufficient understanding of the current progress of spi efforts, and underutilization of a large amount of complex information generated during spi. we present the method for software organizations and projects for dealing with the problems, and argue for a knowledge-based spi support system based on the method
the software engineer and the development, management and use of intellectual property. this full day tutorial will offer instruction on patent, copyright, trade secret and other intellectual property issues faced by developers and users of software in protecting their innovations, including information on avoiding infringing the intellectual property rights of others in the software development process. the course is directed to conference attendees who are involved in any aspect of the development, management or use of intellectual property, including those in the private sector, universities and government. the course will be presented at a basic and understandable, level tailored for the software engineer audience. the course will comprise an oral presentation of nine (9) 30-35 minute segments, with 10 minute breaks for refreshments and specific attendee questions. the instructors will remain available for questions from attendees during breaks. answers to questions will also be provided during each session. power point slides will be used, and actual anecdotal experiences will be presented to illustrate important points.
challenges in the age of ubiquitous computing: a case study of t-engine, an open development platform for embedded systems. ubiquitous computing poses new challenges for the software engineering community. the t-engine platform consisting of standard real-time kernel, t-kernel, running on the standard hardware with networking facility creates broad application opportunities based on the collaboration of cutting edge microelectronics, software and embedded system technologies. however, to realize the true potential of such a system in a ubiquitous computing environment, we need to overcome software engineering issues among many hurdles we encounter. we describe such issues and the future challenges inherent in the ubiquitous computing based on our experience of using ubiquitous communicator terminal that is based on t-engine.
a model driven approach for software systems reliability. the main contribution of this research is to provideplatform-independent means to support reliability designfollowing the principles of a model driven approach. thecontribution aims to systematically address dependabilityconcerns from the early to the late stages of software development.mda appears to be a suitable framework toassess these concerns and, therefore, semantically integrateanalysis and design models into one environment.
a methodology for decomposing system requirements into data processing requirements. top level system design is considered, with attention focused on the decomposition of system requirements into subsystem requirements. primary interest is in the data processing subsystem. implementation details involving operating systems, selection and configuration of computers, and choice of specific algorithms are excluded from this study. a methodology is presented for transforming system requirements into functional structure and system operating rules. this methodology is viewed as the first step of a comprehensive software development methodology comprising: top level design, algorithm development, computer selection, and the translation of the functional algorithmic design into operational software. the top level design is carried to such detail that algorithms, to be developed subsequently and to be realized ultimately with hardware or software, can be considered bounded by the interfaces of the data processing subsystem (dps). that is, the interfaces are defined sufficiently well that the algorithm designer needs to consider neither the destination of data leaving the dps nor the source of data entering the dps. a system can be decomposed into four structural elements: functions, control, functional flows, and data. each of these elements is a subject of the decomposition methodology. the inter-relationships of system functions are structured to define a partial ordering of system functions that is amendable to representation as a directed graph. the system control mechanism is defined to be a finite state machine, whose only cycles are loops, having start and end states. for real time operation end states fold onto start states. functional flows represent each output of the control machine as a serial/parallel execution of the functions, consistent with their partial ordering. data is used to relate the several functions within a functional flow, to drive the control mechanism, and to link control to the functional flows.
a new program structure to improve accuracy and readability of pascal software. based on an analysis of errors in a piece of pascal software a new language feature is introduced to increase the degree of compile time checking of program logic and thus improve the confidence of the programmer in the correctness of a program. specifically this involves a form of abstract data type, augmented by restrictions on the use of operations provided with the type, and a means of allowing the programmer to bring logically related segments of program together textually.
2nd international workshop on software engineering for automotive systems. no abstract available
software test program: a software residency experience. the software test program (stp) is a cooperation between motorola and the center for informatics of the federal university of pernambuco. it has been conceived with inspiration on the medical residency, adjusted to the software development practice. a software residency includes the formal teaching of the relevant concepts and deep practice, with specialization on some specific subject; here the focus is on software testing. the stp has been of great benefit to all parties involved.
specifying software/hardware interactions in distributed systems. this paper describes a system level specification approach that enables the designer to formulate and answer questions regarding the system's logical correctness and performance characteristics when the interaction between the hardware and the software is important, i.e., when the impact of faults, failures, communication delay, hardware selection, scheduling policies, etc., must be considered. in the simplest terms, our concern extends beyond the traditional software correctness questions by addressing the issue of employing logical verification techniques to determine software correctness and performance characteristics when running on a particular distributed hardware architecture and using a particular operating system. a language called csps (an extension of hoare's csp) is used in the illustration of the approach. employing csp as a base allows modelled systems to be verified using techniques already developed for verifying csp programs.
software architecture based on communicating residential environments. this paper describes an alternative approach to software architecture, where the classical division of responsibilities between operating systems, programming languages and compilers, and so forth is revised. our alternative is organized as a set of self-contained environments which are able to communicate pieces of software between them, and whose internal structure is predominantly descriptive and declarative. the base structure within each environment (its diversified shell) is designed so that it can accomodate such arriving software modules. the presentation of that software architecture is done in the context of an operational implementation, the screen system (system of communicating residential environments).
language and visualization support for large-scale concurrency. sdl (shared dataspace language) is a language for writing and visualizing programs consisting of thousands of processes executing on a highly-parallel multiprocessor. sdl is based on a model in which processes use powerful transactions to manipulate abstract views of a virtual, content-addressable data structure called the dataspace. the process society is dynamic and supports varying degrees of process anonymity. the transactions are executed over abstract views of the dataspace. this facilitates elegant conceptualization of dataspace transformations and compact program representation. processes and transactions enable sdl to combine elements of both large and fine grained concurrency. the view is a novel abstraction mechanism whose significance is derived from the fact that it allows processes to interrogate the dataspace at a level of abstraction convenient for the task they are pursuing. the view also plays a role in the definition of continuously updated, programmer-defined visual abstractions which enable exploration of the program's functionality and performance.
on the influence of scale in a distributed system. scale should be recognized as a primary factor influencing the architecture and implementation of distributed systems. this paper uses andrew, a distributed environment at carnegie mellon university, to validate this proposition. the design of andrew is dominated by considerations of performance, operability and security. caching of information and placing trust in as few machines as possible emerge as two general principles that enhance scalability. the separation of concerns made possible by specialized mechanisms is also valuable. heterogeneity is a natural consequence of growth and anticipating it in the initial stages of system design is important. a location transparent shared file system considerably enhances the usability of a distributed environment.
multifaceted distributed systems specification using processes and event synchronization. a new approach to modelling distributed systems is presented. it uses sequential processes and event synchronization as the major building blocks and is able to capture the functionality, architecture, scheduling policies, and performance attributes of a distributed system. the approach is meant to provide the foundation for a uniform incremental strategy for verifying both logical and performance properties of distributed systems. in addition, this approach draws together work on performance evaluation, resource allocation, and verification of concurrent processes by reducing some problems from the first two areas to equivalent problems in the third. a language called csps (an extension of hoare's csp) is used in the illustration of the approach. employing csp as a base allows modelled systems to be verified using techniques already developed for verifying csp programs
verification of a monitor specification. a specification of the monitor primitives that have been proposed for mutual exclusion and interprocess communication in operating systems is verified to be correct. the specification is given in the pascal programming language and the proofs of correctness use the axiomatic definition of this language. two aspects of correctness are considered: the correctness of the program implementation of the primitives and the correctness as viewed by the processes that execute the monitor primitives.
predictor models in software engineering (promise). no abstract available
consistent group membership in ad hoc networks. the design of ad hoc mobile applications often requires the availability of a consistent view of the application state among the participating hosts. such views are important because they simplify both the programming and verification tasks. essential to constructing a consistent view is the ability to know what hosts are within proximity of each other, i.e., form a group in support of the particular application. in this paper we propose an algorithm that allows hosts within communication range to maintain a consistent view of the group membership despite movement and frequent disconnections. the novel features of this algorithm are its reliance on location information and a conservative notion of logical connectivity that creates the illusion of announced disconnection. movement patterns and delays are factored in the policy that determines which physical connections are susceptible to disconnection.
network abstractions for context-aware mobile computing. context-aware computing is characterized by the ability of a software system to continuously adapt its behavior to a changing environment over which it has little or no control. previous work along these lines presumed a rather narrow definition of context, one that was centered on resources immediately available to the component in question, e.g., communication bandwidth, physical location, etc. this paper explores context-aware computing in the setting of ad hoc networks consisting of numerous mobile hosts that interact with each other opportunistically via transient wireless interconnections. we extend the context to encompass awareness of an entire neighborhood within the ad hoc network. a formal abstract characterization of this new perspective is proposed. the result is a specification method and associated context maintenance protocol. the former enables an application to define an individualized context, one that extends across multiple mobile hosts in the ad hoc network. the latter makes it possible to delegate the continuous reevaluation of the context and the performance of operations on it to some middleware operating below the application level. this relieves application development of the obligation of explicitly managing mobility and its implications on the component's behavior.
assertional reasoning about pairwise transient interactions in mobile computing. mobile computing represents a major point of departure from the traditional distributed computing paradigm. the potentially very large number of independent computing units, a decoupled computing style, frequent disconnections, continuous position changes, and the location-dependent nature of the behavior and communication patterns of the individual components present designers with unprecedented challenges in the areas of modularity and dependability. the paper describes two ideas regarding a modular approach to specifying and reasoning about mobile computing. the novelty of our approach rests with the notion of allowing transient interactions among programs which move in space. we restrict our concern to pairwise interactions involving variable sharing and action synchronization. the motivation behind the transient nature of the interactions comes from the fact that components can communicate with each other only when they are within a certain range. the notation we propose is meant to simplify the writing of mobile applications and is a direct extension of that used in unity. reasoning about mobile computations relies on the unity proof logic.
an architecture-centric approach to the development of a distributed model-checker for timed automata. research in model-checking is focused on increasing the size of the problems tools can deal with. the ultimate wave has been the use of distributed-computing, where a cluster of computers work together to solve the problem [8, 3, 9].in our work we present a distributed model-checker that evolves from the tool kronos [5] and can handle backwards computation of tctl-reachability formulae [1] over timed-automata [2]. our proposal, including the arguments of its correctness, is based on software architectures, using a notation adapted from [6]. we find such an approach a natural and general way to address the development of complex tools that need to incorporate new features and optimizations as they evolve.we introduce some interesting features such as a priori graph partitioning (using metis [7], a standard library for graph partitioning), a sophisticated machinery to reach optimum performance (communication piggybacking and delayed messaging) and dead-time utilization, where every processor uses time intervals of inactivity to perform auxiliary, time-consuming tasks that will later speed up the rest of the computation.the correctness proof strategy combines an architecture evolution with the theoretical results about fix point calculation developed by patrick cousot in 1978 [4].
workshop on software engineering and mobility. mobility is redefining the hardware and software fabric of distributed systems. wireless communication allows network hosts to participate in a distributed computation while on the move. novel middleware technologies allow software components to migrate across hosts for enhanced flexibility or performance. workshop participants were invited to analyze the software engineering implications of this wave of technological changes, by discussing fundamental models, emerging themes, research opportunities, technological trends, and market forces.
design using software engineering principles: overview of an educational program. in 1981 ibm initiated a corporate-wide training program to introduce a standard, software engineering-based, programming technology, based on a similar program established in the federal systems division during the late seventies. the software engineering workshop has a strong mathematical orientation. the central focus is on mathematical models for program functions and data abstractions. the models allow mathematical statements of specifications, stepwise refinement, and function-based mental verification of each refinement step. the technology and a textual design language encourage orderly problem decomposition, encapsulation, and separation of concerns. this paper introduces the material taught in the workshop and summarizes the workshop's history and results. use of the technology is producing higher quality programs and providing greater professional satisfaction among its users.
software process maturity: measuring its impact on productivity and quality. with the current worldwide focus on improvement in software process, there is clearly a need for an understanding of its impact on software engineering productivity and quality. the paper documents an attempt to provide an empirical metrics `view' of such initiatives based on data collected in a worldwide benchmarking effort conducted between march, 1991 and december, 1991. surprisingly, of the more than 300 organizations that participated, fewer than 1 in 5 had any quantifiable performance data available prior to the start of this study. however, those that had embarked on significant process improvement efforts and were actively using metrics were able to demonstrate substantial grains in productivity and quality. in addition, insights derived from this large scale data analysis provide a framework for determining which metrics should be included in a standard software engineering measurement `dashboard'
software engineering management. the author discusses the links between management and software engineering. the author tries to show why, in europe and the usa, management has failed so often in this field. this seems to be due to a combination of narrow-minded attitudes from all the players: academia, work-force and management. the two main issues are software engineering does not produce competent managers, and software development is still an individual affair
an architectural style for multiple real-time data feeds. we present an architectural style for the integration of multiple real-time data feeds on windows nt platforms. we motivate the development of this style by highlighting different application areas in which the style has been deployed. we present the requirements that will be met by the architectural style and discuss the design of customizable components that implement the style based on microsoft's component object model.
acmestudio: supporting style-centered architecture development. software architectural modeling is crucial to the developmentof high-quality software. tool support is requiredfor this activity, so that models can be developed,viewed, analyzed, and refined to implementations. thissupport needs to be provided in a flexible and extensiblemanner so that the tools can fit into a companyýs processand can use particular, perhaps company-defined, domain-specific architectural styles. in this research demonstration, we describe acmestudio, a style-neutral architecturedevelopment environment that can be easilyspecialized for architectural design in different domains.
a comprehensive product line scoping approach and its validation. product line engineering is a recent approach to software development that specifically aims at exploiting commonalities and systematic variabilities among functionally overlapping systems in terms of large scale reuse. taking full advantage of this potential requires adequate planning and management of the reuse approach as otherwise huge economic benefits will be missed due to an inappropriate alignment of the reuse infrastructure.key in product line planning is the scoping activity, which aims at focussing the reuse investment where it pays. scoping actually happens on several levels in the process: during the domain analysis step (analysis of product line requirements) a focusing needs to happen just like during the decision of what to implement for reuse. the latter decision has also important ramifications for the development of an appropriate reference architecture as it provides the reusability requirements for this step.in this paper, we describe an integrated approach that has been developed, improved, and validated over the last few years. the approach fully covers the scoping activities of domain scoping and reuse infrastructure scoping and was validated in several industrial case studies.
introducng a software modeling concept in a medium-sized company. in this paper, we describe, using the quality improvement paradigm (qip), how an improvement project aimed at improving the modeling and documentation approach of a medium-sized company (msud) was conducted. we discuss the new modeling approach which may serve for other companies as a template for deriving their own adapted approach. further, we illustrate our insights from this project that can help in future technology transfer projects. a major characteristic of this project was that it was embedded in a long-term consulting relationship.
introducing the pulse approach to an embedded system population at testo ag. over the last few years, product line engineering has become a major theme in software engineering research, and is increasingly becoming a central topic of software engineering practice in the embedded domain.migrating towards a product line approach is not an easy feat. it is even less so, if it is done under tight technology constraints in an embedded environment. it becomes even more difficult if the transition directly aims at integrating two product families into a single product population. in this paper, we discuss our experiences with a project where we successfully dealt with these difficulties and achieved a successful product line transition. in our paper we strongly emphasize the role of technology transfer, as many facets of product line know-how had to be transferred to guarantee a complete transition to product line engineering. from the experiences of this project many lessons learned can be deduced, which can be transferred to different environments.
patterns, frameworks, and middleware: their synergistic relationships. the knowledge required to develop complex software has historically existed in programming folklore, the heads of experienced developers, or buried deep in the code. these locations are not ideal since the effort required to capture and evolve this knowledge is expensive, time-consuming, and error-prone. many popular software modeling methods and tools address certain aspects of these problems by documenting how a system is designed. however, they only support limited portions of software development and do not articulate why a system is designed in a particular way, which complicates subsequent software reuse and evolution.patterns, frameworks, and middleware are increasingly popular techniques for addressing key aspects of the challenges outlined above. patterns codify reusable design expertise that provides time-proven solutions to commonly occurring software problems that arise in particular contexts and domains. frameworks provide both a reusable product-line architecture [1] guided by patterns -- for a family of related applications and an integrated set of collaborating components that implement concrete realizations of the architecture. middleware is reusable software that leverages patterns and frameworks to bridge the gap between the functional requirements of applications and the underlying operating systems, network protocol stacks, and databases. this paper presents an overview of patterns, frameworks, and middleware, describes how these technologies complement each other to enhance reuse and productivity, and then illustrates how they have been applied successfully in practice to improve the reusability and quality of complex software systems.
calculating architectural reliability via modeling and analysis. we present a software architecture-based approach tocompositional estimation of systemýs reliability. ourapproach is applicable to early stages of developmentwhen the implementation artifacts are not yet available,and exact execution profile is unknown. the uncertainty ofthe execution profile is modeled using stochastic processeswith unknown parameters. the compositional approachcalculates overall reliability of the system as a function ofthe reliability of its constituent components and their(complex) interactions. sensitivity analysis to identify criticalcomponents and interactions will be provided.
consistency checking within embedded design languages. it is difficult to ensure consistency between a program's design and its implementation. an embedded design language (one superimposed on an implementation language) can help. this paper describes a particular embedded design language that was successfully used to design and implement a very large compiling system. this design language has a rich set of constructs for expressing the high-level and detailed designs of a program. it also supports various levels of design and implementation consistency checking, and the generation of a variety of documents for use by programmers and reviewers.
estimating software component reliability by leveraging architectural models. software reliability techniques are aimed at reducing or eliminat-ing failures in software systems. reliability in software systems istypically measured during or after system implementation. how-ever, software engineering methodology lays stress on doing the"correct things" early on in the software development lifecycle inorder to curb development and maintenance costs. in this paper, wepropose a framework for reliability estimation of software compo-nents at the level of software architecture.
prototypes as assets, not toys: why and how to extract knowledge from prototypes. software prototypes are becoming more and more important, as computer applications invade new domains and as personal prototyping environments become more powerful. although numerous approaches recommend their use, prototypes are sometimes treated like their developers' personal toys, and little effort is made to extract and share the experiences and knowledge that emerged as a by-product of building the prototype. in this paper, a strategy is proposed to extract crucial pieces of knowledge from a prototype and from its developer. the strategy is based on monitoring explanations that developers give, analyzing their structure, and feeding results back to support and to focus explanations. during this process, the prototype turns into the centerpiece of a hyperstructured information base, which can be used to convey concepts, implementation tricks and experiences. if organizations begin to view-and treat-prototypes as executable representations of knowledge, they can fully capitalize on the assets prototypes really are.
effective experience repositories for software engineering. software development and acquisition require knowledge and experience in many areas of software engineering. experience helps people to make decisions under uncertainty, and to find better compromises. experience-based process improvement considers experience as a prerequisite for competent behavior in software development. there is usually a repository to store experiences and to make it available for reuse. at daimlerchrysler, we have been building those repositories for more than five years. we learned to concentrate on certain properties that seem to be key success factors for experience repositories. during our experience-based work in business units, five key quality aspects have been identified that determine the chances for success of an experience repository. the quality criteria can be used to analyze a given repository; or they can be applied to guide the construction of more effective experience repositories.
teaching contract programming concepts to future software engineers. current research in software engineering at karlstad university is concentrated on non-formal software design methods with a focus on semantics. one goal is to produce methods, which may be applied in both industry and academia. in concrete terms, ideas from contract programming, including pre- and post-conditions have been introduced into the first year curriculum. this paper presents results taken from three surveys of the same group of first-year students during their second semester, in an attempt to ascertain how well the students have internalised these and other programming concepts. the results show that the majority of the students are aware of the concepts but are still at various stages of understanding. a good understanding of terminology emerges as one key area of focus for future courses. the results are a reasonable reflection of reality, given the limited time in which the students are expected to absorb these ideas, and provide feedback for further integration and development of the related programming courses.
extreme programming at universities - an educational perspective. to address the problems of traditional software devel- opment, recent years have shown the introduction of more light-weight or "agile" development processes (extreme programming being the most prominent one). these processes are intended to support early and quick production of working code by structuring the development into small release cycles and focus on continual interaction between developers and customers. as such software development processes become more popular, there is a growing demand from industry to introduce agile development practices in tertiary education.this is not a straightforward task as the corresponding practices may run counter to educational goals or may not be adjusted easily to a learning environment. in this paper, we discuss some of these issues and reflect on the problems of teaching agile processes in tertiary education.
integrated program measurement and documentation tools. this paper describes an attempt to integrate the collection and the efficient utilisation of measurements in the development and the use of programs. the work presented consists in three parts: - the design of both static and dynamic measurement tools, - examples of data processing on measurements collected on a sample of pascal programs, - the design of a quantitative documentation of a program, which is automatically built as measurements are collected. the first and third steps have been developed inside an existing programming environment, mentor, and we shall discuss the advantages we found in integrating the tools in such an environment.
understanding and aiding code evolution by inferring change patterns. evolution continues to play an ever-increasing role in software engineering. although changing a program is the core of software evolution, program change patterns have not been considered as a first class entity in most classic studies of software evolution. past empirical studies of software evolution primarily relied on quantitative and statistical analyses of a programover time [1], but did not focus on semantic and qualitative change patterns of a program. we hypothesize that by treating change patterns as first class entities we can better understand software evolution and also aid programmers in changing software.
wysiwyt testing in the spreadsheet paradigm: an empirical evaluation. is it possible to achieve some of the benefits of formal testing within the informal programming conventions of the spreadsheet paradigm? we have been working on an approach that attempts to do so via the development of a testing methodology for this paradigm. our &ldquo;what you see is what you test&rdquo; (wysiwyt) methodology supplements the convention by which spreadsheets provide automatic immediate visual feedback about values by providing automatic immediate visual feedback about &ldquo;testedness&rdquo;. in previous work we described this methodology; in this paper, we present empirical data about the methodology's effectiveness. our results show that the use of the methodology was associated with significant improvement in testing effectiveness and efficiency even with no training on the theory of testing or test adequacy that the model implements. these results may be due at least in part to the fact that use of the methodology was associated with a significant reduction in overconfidence.
the first workshop on end-user software engineering. weuse is a workshop dedicated to the problems faced by end-user programmers, and research that can address those problems.
cost estimation for web applications. in this paper, we investigate the application of the cobra&trade; method (cost estimation, benchmarking, and risk assessment) in a new application domain, the area of web development. cobra combines expert knowledge with data on a small number of projects to develop cost estimation models, which can also be used for risk analysis and benchmarking purposes. we modified and applied the method to the web applications of a small australian company, specializing in web development. in this paper we present the modifications made to the cobra method and results of applying the method. in our study, using data on twelve web applications, the estimates derived from our web-cobra model showed a mean magnitude of relative error (mmre) of 0.17. this result significantly outperformed expert estimates from allette systems (mmre 0.37). a result comparable to web-cobra was obtained when applying ordinary least squares regression with size in terms of web objects as an independent variable (mmre 0.23).
scl: static enforcement and exploration of developer intent in source code. software developers spend a large fraction of their time dealing with intent, seeking to answer questions like does this code really do what it is expected to do?is this module used appropriately?is this code easy to modify or extend?can this code be used in a different context? as a result, developers make many mutually-dependent design decisions to express intentions about software and try to convert them into code precisely.
the impact of test suite granularity on the cost-effectiveness of regression testing. regression testing is an expensive testing process used to validate software following modifications. the cost-effectiveness of regression testing techniques varies with characteristics of test suites. one such characteristic, test suite granularity, involves the way in which test inputs are grouped into test cases within a test suite. various cost-benefits tradeoffs have been attributed to choices of test suite granularity, but almost no research has formally examined these tradeoffs. to address this lack, we conducted several controlled experiments, examining the effects of test suite granularity on the costs and benefits of several regression testing methodologies across six releases of two non-trivial software systems. our results expose essential tradeoffs to consider when designing test suites for use in regression testing evolving systems.
a system for parallel programming. the programming of efficient parallel software typically requires extensive experimentation with program prototypes. a programming system that supports rapid prototyping of parallel programs should provide high-level primitives with which programs can be explicitly, statically or dynamically tuned with respect to performance and reliability. when using such primitives, programmers should not need to interact explicitly or even be aware of the software tools involved in program construction and tuning, such as compilers, linkers, and loaders. in addition, programmers should be provided with the information about the executing program and the parallel hardware required for tuning. such information may include monitoring data about the current or previous program or even hints regarding appropriate tuning decisions.a programming system that includes primitives and tools for program tuning is presented in this paper. the system has been implemented, and has been tested with a variety of parallel applications on a network of unix workstations.
a framework for evaluating regression test selection techniques. regression testing is a necessary but expensive activity aimed at showing that code has not been adversely affected by changes. a selective approach to regression testing attempts to reuse tests from an existing test suite to test a modified program. this paper outlines issues relevant to selective retest approaches, and presents a framework within which such approaches can be evaluated. this framework is then used to evaluate and compare existing selective retest algorithms. the evaluation reveals strengths and weaknesses of existing methods, and highlights problems that future work in this area should address
using return on investment to compare agile and plan-driven practices in undergraduate group projects. in this paper we describe our experiences of introducing agile practices into undergraduate group work by comparing the results to more traditional plan-driven groups. when considering whether to adopt an agile or plan-driven project management strategy in a commercial context, return on investment (roi) is an important factor. we have adapted the roi model to our analysis to assess what affect a chosen development approach has on the outcome of the groups' projects. in our investigation we observed seven software teams as they implemented a business information system. two groups adopted agile practices, including fortnightly iterative delivery; the other groups were controls. we found that being labelled agile did not necessarily imply that a group's practices were more agile. also, it was unclear whether the so-called agile groups delivered a better roi than their plan-driven counterparts.
handling safety-related feature interaction in safety-critical product lines. the variation management of software product lines is currently handled without adequately taking safety or other system-level properties into account. this is largely due to (1) the fact that the available product-line variation-management techniques lack sufficient support for representing the combined effect of different features, and (2) the existing feature interaction techniques do not suffice for handling one-to- many feature interactions typical of many safety-critical product lines. the challenge is that we need to track the safety-related feature interactions while still promoting reuse. the expected contribution of this work is to demonstrate how safety-related feature interactions can be better investigated and managed by the safety-analysis guided, model-based approach described in this paper.
what you see is what you test: a methodology for testing form-based visual programs. form-based visual programming languages, which include commercial spreadsheets and various research systems, have had a substantial impact on end-user computing. research shows, however, that form-based visual programs often contain faults. we would like to provide at least some of the benefits of formal testing methodologies to the creators of these programs. this paper presents a testing methodology for form-based visual programs. to accommodate the evaluation model used with these programs, and the interactive process by which they are created, our methodology is validation driven and incremental. to accommodate the users of these languages, we provide an interface to the methodology that does not require an understanding of testing theory. we discuss our implementation of this methodology and empirical results achieved in its use
an intelligent tool for re-engineering software modularity. the author describes a software tool that provides heuristic modularization advice for improving existing code. a heuristic design similarity measure is defined, based on the parna information hiding principle. the measure supports two services: clustering, which identifies groups of related procedures, and maverick analysis, which identifies individual procedures that appear to be in the wrong module. the tool has already provided useful advice in several real programming projects. the tool will soon incorporate an automatic tuning method, which allows the tool to learn from its mistakes, adapting its advice to the architect's preferences. a preliminary experiment demonstrates that the automatically tuned similarity function can assign procedures to modules very accurately
object naming analysis for reverse-engineered sequence diagrams. uml sequence diagrams are commonly used to represent object interactions in software systems. this work considers the problem of extracting uml sequence diagrams from existing code for the purposes of software understanding and testing. a static analysis for such reverse engineering needs to map the interacting objects from the code to sequence diagram objects. we propose an interprocedural dataflow analysis algorithm that determines precisely which objects are the receivers of certain messages, and assigns the appropriate diagram objects to represent them. our experiments indicate that the majority of message receivers can be determined exactly, resulting in highly-precise object naming for reverse-engineered sequence diagrams.
fragment class analysis for testing of polymorphism in java software. adequate testing of polymorphism in object-oriented software requires coverage of all possible bindings of receiver classes and target methods at call sites. tools that measure this coverage need to use class analysis to compute the coverage requirements. however, traditional whole-program class analysis cannot be used when testing partial programs. to solve this problem, we present a general approach for adapting whole-program class analyses to operate on program fragments. furthermore, since analysis precision is critical for coverage tools, we provide precision measurements for several analyses by determining which of the computed coverage requirements are actually feasible. our work enables the use of whole-program class analyses for testing of polymorphism in partial programs, and identifies analyses that compute precise coverage requirements and therefore are good candidates for use in coverage tools.
software evolution management: an integrated discipline for managing software. many models have been devised to represent the processes involved in developing software with hopes of providing foundations for increasingly useful environment support tools. they have met with varied success in their abilities to relate to &ldquo;reality&rdquo;. this paper presents a model called the software evolution management (sem) model. the sem model focuses on the problems and situations that commonly arise in commercial software development organizations, although it is probably relevant to other situations as well. this paradigm establishes a structure within which a tracking system can be implemented that smoothly integrates many different types of management and development activities.
the finalization operation for abstract types. in this paper we argue the importance of a finalization capability in a programming language abstract type facility. finalization, the dual of initialization, is crucial for applications involving the allocation of, and access to, abstract resources. a semantic model for finalization is given, defining both statically and dynamically allocated abstract objects, in the presence of exception handling. for illustration, we incorporate finalization in an abstract data type facility designed as an extension of ada.
an engineering methodology for presenting software functional architecture. a method of presenting software architecture has been developed which is useful for reviewing and documenting software designs. diagrams showing all software levels as well as inputs and outputs are systematically developed to provide an understanding of the construction and operation of software systems and programs. the manner in which the software architecture is displayed provides an effective way for managers to understand and review software designs.
a new technique for improving the quality of computer programs. a new rule is proposed for computer systems: every item of data stored by a computer program should subsequently be read; if not, a program must state explicitly whenever it wishes to overwrite or destroy an unused value. this rule is unknown in previous computer systems, yet violations usually indicate a confusing, incorrect or inefficient program. many programming errors also manifest themselves as violations of this rule. the idea has been tested on practical programs by modifying a compiler used at npl. the results are encouraging: when programs are being developed sources of inefficiency are often indicated and many errors show themselves more rapidly. the new rule is no hindrance when writing clear well-structured programs, but confused or obscure programs are more difficult to get (almost!) working. the technique can be implemented in suitably designed hardware very cheaply and easily.
empowering software engineers in human-centered design. usability is about to become the quality measure of today's interactive software including web sites, and mobile appliances. user-centered design approach emerges from this need for developing more usable products. however, interactive systems are still designed and tested by software and computer engineers unfamiliar with ucd and the related usability engineering techniques. while most software developers may have been exposed with basic concepts such as gui design guidelines, few developers are able to understand the human/user-centered design (ucd) toolbox at a level that allows them to incorporate it into the software development lifecycle. this paper describes an approach skilling developers and students enrolled in an engineering program in critical user-centered design techniques and tools. the proposed approach starts from the analysis of the usability and software engineer's work context, identifies critical ucd skills and then associates relevant learning resources with each of the identified skills. our approach suggests a list of patterns for facilitating the integration the ucd skills into the software engineering lifecycle.
monitoring compliance of a software system with its high-level design models. as a complex software system evolves, its implementation tends to diverge from the intended or documented design models. such undesirable deviation makes the system hard to understand, modify and maintain. this paper presents a hybrid computer-assisted approach for confirming that the implementation of a system maintains its expected design models and rules. our approach closely integrates logic-based static analysis and dynamic visualization, providing multiple code views and perspectives. we show that the hybrid technique helps determine design-implementation congruence at various levels of abstraction: concrete rules like coding guidelines, architectural models like design patterns or connectors, and subjective design principles like low coupling and high cohesion. the utility of our approach has been demonstrated in the development of /spl mu/choices, a new multimedia operating system which inherits many design decisions and guidelines learned from experience in the construction and maintenance of its predecessor, choices.
metric-driven analysis and feedback systems for enabling empirically guided software development. the authors summarize the goals of metric-driven analysis and feedback systems and describe a prototype system, amadeus, which defines abstract interfaces and embodies architectural principles for these types of systems. metric-driven analysis and feedback systems enable developers to define empirically guided processes for software development and maintenance. the authors provide an overview of the amadeus system operation, including an example of the empirically guided process, a description of the system characteristics, an explanation of the system conceptual operation, and a summary of the users' view of the system. the centerpiece of the system is a pro-active server, which interprets scripts and coordinates event monitoring and agent activation. amadeus provides an extensible framework for adding new empirically based analysis techniques
tutorial h2: an overview of uml 2.0. this half-day tutorial covers the salient aspects of the first major revision of the unified modeling language, uml 2.0. it includes background information on what drove the requirements and the design rationale---from the point of view of one of its primary designers. the overall structure of uml 2.0 is described followed by a more detailed description of the most prominent new modeling features illustrated with many examples. the ability of uml 2.0 to deal with the needs of model-driven development methods is also covered.
tutorial: an overview of uml 2.0. this half-day tutorial covers the salient aspects of thefirst major revision of the unified modeling language ¿uml 2.0. in this brief summary, we briefly review someof the main points covered in the tutorial.
tutorial: an overview of uml 2. this half-day tutorial covers the salient features of the first major revision of the unified modeling language - uml 2. this short note summarizes the major topics covered by the tutorial.
describing software architecture with uml. the presence of a solid architectural vision is a key discriminator in the success or failure of a software project. this tutorial examines what software architecture is and what it is not. it discusses and illustrates how to describe architecture through a set of design viewpoints and views and how to express these views in the uml [1], in the spirit of the new ieee standard: recommended practice for architectural description [2]. the tutorial shows of how architectures drive the development process and how to capture architectural design patterns using the uml. it is illustrated by several widely applicable architectural patterns in different domain.
efficient decentralized monitoring of safety in distributed systems. we describe an efficient decentralized monitoring algorithm that monitors a distributed program's execution to check for violations of safety properties. the monitoring is based om formulae written in pt-dtl, a variant of past time linear temporal logic that we define. pt-dtl is suitable for expressing temporal properties of distributed systems. specifically, the formulae of pt-dtl are relative to a particular process and are interpreted over a projection of the trace of global states that represents what that process is aware of. a formula relative to one process may refer to other processes' local states through remote expressions and remote formulae. in order to correctly evaluate remote expressions, we introduce the notion of knowledge vector and provide an algorithm which keeps a process aware of other processes' local states that can affect the validity of a monitored pt-dtl formula. both the logic and the monitoring algorithm are illustrated through a number of examples. finally, we describe our implementation of the algorithm in a tool called diana.
a research agenda for distributed software development. in recent years, a number of business reasons have caused software development to become increasingly distributed. remote development of software offers several advantages, but it is also fraught with challenges. in this paper, we report on our study of distributed software development that helped shape a research agenda for this field. our study has identified four areas where important research questions need to be addressed to make distributed development more effective. these areas are: collaborative software tools, knowledge acquisition and management, testing in a distributed set-up and process and metrics issues. we present a brief summary of related research in each of these areas, and also outline open research issues.
interform: a cad system for program development. based on a theoretical approach, we tried to implement a system for assistance to a programmer during the most difficult phase of the programming activity: software design. as we carried out the system project, it become apparent that the system could encompass more than just program design. in the paper, the main ideas of the theoretical approach are outlined. briefly described is the state-oriented architecture of the system. the system structure is also presented.
an effective layout adaptation technique for a graphical modeling tool. editing graphic models always entails layout problems. inserting and deleting items requires tedious manual work for shifting existing items and rearranging the diagram layout. hence, techniques that automatically expand a diagram when space is required for insertion and contract it when free space becomes avaliable are highly desirable.existing layout generation algorithms are no good solution for that problem: they may completely rearrange a diagram after an editing operation, while users want to preserve the overall visual appearance of a diagram.we have developed a technique which automatically expands or contracts a diagram layout when items are inserted or removed while preserving its overall shape, i.e. the positions of the items relative to each other. our technique has been implemented in a prototype tool. we are using it not just for simplifying editing, but primarily for implementing an aspect-oriented visualization concept.
dat flow, abstraction levels and specifications for communications switching systems. the purpose of this effort was the specification and design of a family of communications switching systems, such that each design and implementation of the specification leads to a family member. each set of design and implementation decisions chosen would lead to some appropriate desired member of the family. basically, our methodology consists of the following six steps, system modelling, data flow modelling, features selection, modules selection, hierarchicalization, and abstract machines specification.
modeling of component based systems. component based software development (cbsd) becomes a popular paradigm for internet based systems. compared to other popular paradigms, cbsd supports the development from reusable components other than the development from the scratch. consequently, modeling becomes more important than programming and the modeling techniques in traditional paradigms have to be changed more or less. particularly, improper selection and misuse of modeling techniques would prevent the target system from benefiting from cbsd and even make the project fail. for helping researchers and practitioners to equip with cbsd, this tutorial will provide basic knowledge and skill of modeling component based systems systematically. firstly, we will introduce the technical and non-technical motivations of cbsd with emphasis on software reuse which puts a significant impact on modeling. secondly, we will present a systematic approach to modeling component based systems with a set of existing well-proved modeling techniques, including feature modeling for requirements specification, architecture modeling for abstract design, and object oriented modeling for detailed design. these modeling techniques and a real-life project will be discussed in details in the rest of the tutorial.
a knowledge base for supporting and intelligent program editor. this paper presents work in progress towards a program development and maintenance aid called the intelligent program editor (ipe), which applies artificial intelligence techniques to the task of manipulating and analyzing programs. the ipe is a knowledge based tool: it gains its power by explicitly representing textual, syntactic, and many of the semantic (meaning related) and pragmatic (application oriented) structures in programs. to demonstrate this approach, we implement a subset of this knowledge base, and a search mechanism called the program reference language (prl), which is able to locate portions of programs based on a description provided by a user. this research was supported by the air force office of scientific research under contract f49620-81-c-0067, the office of naval research under contract n00014-82-c-0119, and rome air development center under contract f30602-80-c-0176.
an interactive multimedia software house simulation for postgraduate software engineers. the open university's m880 software engineering is a postgraduate distance education course aimed at software professionals. the case study element of the course (approximately 100 hours of study) is presented through an innovative interactive multimedia simulation of a software house open software solutions (oss). the student 'joins' oss as an employee and performs various tasks as a member of the company's project teams. the course is now in its sixth presentation and has been studied by over 1500 students. in this paper, we present the background to the development, and a description of the environment and student tasks.
the coming-of-age of software architecture research. over the past decade, software architecture research has emerged as the principled study of the overall structure of software systems, especially the relations among subsystems and components. from its roots in qualitative descriptions of useful system organizations, software architecture has matured to encompass broad explorations of notations, tools, and analysis techniques. whereas initially the research area interpreted software practice, it now offers concrete guidance for complex software design and development. we can understand the evolution and prospects of software architecture research by examining the research paradigms used to establish its results. these are, for the most part, the paradigms of software engineering. we advance our fundamental understanding by posing research questions of several kinds and applying appropriate research techniques, which differ from one type of problem to another, yield correspondingly different kinds of results, and require different methods of validation. unfortunately, these paradigms are not recognized explicitly and are often not carried out correctly; indeed not all are consistently accepted as valid. this retrospective on a decade-plus of software architecture research examines the maturation of the software architecture research area by tracing the types of research questions and techniques used at various stages. we will see how early qualitative results set the stage for later precision, formality, and automation and how results build up over time. this generates advice to the field and projections about future impact.
procedure calls are the assembly language of software interconnection: connectors deserve first-class status. software designers compose systems from components written in some programming language. they regularly describe systems using abstract patterns and sophisticated relations among components. however, the configuration tools at their disposal restrict them to composition mechanisms directly supported by the programming language. to remedy this lack of expressiveness, we must elevate the relations among components to first-class entities of the system, entitled to their own specifications and abstractions.
deciding what to design: closing a gap in software engineering education. software has jumped "out of the box" - it controls critical systems; it pervades business and commerce; it is embedded in myriad mechanisms; it infuses entertainment, communication, and other activities of everyday life. designs for these applications are constrained not only by traditional considerations of capability and performance but also by economic, business, market, and policy issues and the context of intended use. the diversity of applications requires adaptability in responding to client needs, and the diversity of clients and contexts requires the ability to discriminate among criteria for success.as a result, software designers must also get out of their boxes: in addition to mastering traditional software development skills, they must understand the contextual issues that discriminate good solutions from merely competent ones. current software engineering education, however, remains largely "in the box": it neglects the rich fabric of issues that lie between the client's problem and actual software development. at carnegie mellon we have addressed this major shortcoming with a course that teaches students to understand both the capabilities required by the client and the constraints imposed by the client's context.this paper presents our view of the engineering character of software engineering, describes the content and organization of our new course, reports on our experience from the first three offerings of our course, and suggests ways to adapt our course for other educational settings.
an efficient set of software degree programs for one domain. there is increasing urgency to put software engineering (se) programs in place at universities in north america. for years, the computer science and professional engineering communities neglected the area, but both are now paying serious attention. there is creative tension as efforts accelerate to define the field faster than is possible. this paper discusses a set of four software degree programs that have evolved over 14 years at a small university with close ties to one software community. the context is computer engineering in a department of electrical and computer engineering, so the natural domain is software that is close to the hardware. this means an emphasis on real-time, embedded, and, to a lesser extent, safety critical issues. the newest of the four programs is a ph.d. program. it demonstrates that ph.d. programs can be created with limited resources, given the right circumstances. if similar circumstances exist in other small universities, the rate of ph.d. production in software engineering may be able to be increased, while maintaining quality. this paper describes the four degree programs, how they are related to each other, and how the programs have evolved. it makes limited comparisons to programs at other universities.
how to do inspections when there is no time. the concepts of inspection are presented, organized around the three ms of inspection (management, mechanics and metrics). fundamentally, inspection provides a way of observing and quantifying software processes while improving software quality. it can be used as a statistical quality control technique for software production. the tutorial addresses variations in inspection processes and techniques, and presents recent research results that investigate which variations are more effective than others. this is done with recognition of the need to adapt inspection approaches to fit local circumstances.
the effects of symbology and spatial arrangement on the comprehension of software specifications. seventy-two participants were presented with specifications for each of three modular-sized computer programs. nine different specification formats were prepared for each program. these formats varied along two dimensions: type of symbology and spatial arrangement. the type of symbology included natural language, constrained language (pdl), and ideograms (flowchart symbols). the spatial arrangement included sequential, branching, and hierarchical versions. the participants answered a series of comprehension questions on each program using only the program specifications. three types of questions were presented: forward-tracing, backward-tracing, and input-output. both forward- and backward-tracing questions were answered more quickly from specifications presented in pdl or ideograms than in natural language. forward-tracing questions were answered most quickly from a branching arrangement, and backward-tracing questions were answered more quickly from branching and hierarchical arrangements. response times to the input-output questions did not vary significantly as a function of the type of symbology or the spatial arrangement.
effort estimation using analogy. the staff resources or effort required for a software project are notoriously difficult to estimate in advance. to date most work has focused upon algorithmic cost models such as cocomo and function points. these can suffer from the disadvantage of the need to calibrate the model to each individual measurement environment coupled with very variable accuracy levels even after calibration. an alternative approach is to use analogy for estimation. we demonstrate that this method has considerable promise in that we show it to out perform traditional algorithmic methods for six different datasets. a disadvantage of estimation by analogy is that it requires a considerable amount of computation. the paper describes an automated environment known as angel that supports the collection, storage and identification of the most analogous projects in order to estimate the effort for a new project. angel is based upon the minimisation of euclidean distance in n-dimensional space. the software is flexible and can deal with differing datasets both in terms of the number of observations (projects) and in the variables collected. our analogy approach is evaluated with six distinct datasets drawn from a range of different environments and is found to outperform other methods. it is widely accepted that effective software effort estimation demands more than one technique. we have shown that estimating by analogy is a candidate technique and that with the aid of an automated environment is an eminently practical technique.
will earlier projects plus a disciplined process enforce se principles throughout the cs curriculum? this paper discusses two related challenges faced by software engineering instructors. first, assuming that projects are necessary to produce successful computer science majors, what should be the role of projects and how best do we integrate theory and application? second, what life cycle models and associated processes should students have the opportunity to experience, and where in the curriculum should a disciplined process first appear? we review several curriculum plans that have been employed to address these problems. we also offer recommendations based on our experiences both with undergraduate computer science majors and with high school students in project tri-p-lets, where beginning programming students are taught to develop games and software simulations following a process.
configuration control for evolutional software products. this paper describes the concept of and a system for configuration control for evolutional software products, in which a wide spectrum of varied software products are being continuously evolved, along with rapid advancements in hardware technologies. the system contains a database for dealing with the overall configuration structure, including hierarchical product structure with change status, master file directories, difficulty occurrences and user information. the data representing the configuration can be in more abstract or macroscopic level than the traditional software configuration control, since the configuration manager should control the overall outlines for all software products. the concept and system described in the paper have been used for intelligent terminal software product management in nec's data terminals division.
a systematic approach to domain-oriented software development. we describe our experience with domain-oriented software development in the domain of automatic teller machine applications. we systematically proceeded with development in four phases: domain analysis, domain formalization, domain facility building, and product development. in this development, we built domain facilities consisting of a domain framework and domain case (computer aided software engineering) tools, then employed them for application development. the framework shared about 4% of the application, and the remaining 96% was generated by the case tools automatically. our approach was found to realize effective reuse of design and implementation and to enable domain-oriented development in large domains
automatic tuning of multi-task programs for real-time embedded systems. this paper describes a programming tool for real-time embedded systems. real-time embedded systems are usually implemented by multiple tasks. it is important to allocate tasks to the system appropriately. our tool, called true, performs the allocation of tasks by transformation of the program the user has written. true reads the program and the requirements about its response time. true transforms the program applying rules based on the requirements. then the program is translated into a code for operating system i-tron. i-tron is our original real-time operating system for 32-bit microprocessors. this paper also describes the implementation of true and an example of its use.
a new design language for communication protocols and a systematic design method of communication systems. a systematic design method of a communication system is given, by which the design, validation, implementation and maintenance of the system can be developed under the consistent philosophy. next, the dai-expression method for describing communication protocols is proposed to support the above design method. here, the dai-expression consists of three types of expressions, namely, the d-expression, a-expression and i-expression depending upon the purposes such as design, validation and implementation. and the new design language copdel is given as the d-expression which is a logical design-oriented expression. finally, the validation algorithm expa is given, which is a generalization of the perturbation analysis given by c.h.west. furthermore, the expa can validate communication protocols described by the copdel.
structural models for software reliability prediction. many previous software reliability prediction models by this author and others have concentrated on the bulk (macro) aspects of the program. this paper describes a newly developed micro model which is based on program structure. it is assumed that the program has been written in structured or modular form so that decomposition in to its constituent parts is simple. further, we assume that via analysis of the program the decomposition can be related to several paths or other functional structures within the program. the model is constructed based upon the frequencies with which each of the j paths are run, (fj), the running time of each path, (tj), and the probability of error along each path, (qj). several methods of calculating or measuring the fj, tj, and qj parameters are suggested. in fact it is possible to use one technique (historical data) to produce crude estimates at the start of the design, and refine the estimates with more accurate values as the design progresses. the paper concludes with the application of the model to a particular example: calculation of the roots of a quadratic equation, and a discussion of proposed experiments for validating the model.
improving software inspections by using reading techniques. reading techniques are step-by-step procedures that guide individual inspectors while they uncover defects in a software artifact. reading techniques provide a systematic and well-defined way of inspecting a document, allowing feedback and improvement. this tutorial introduces perspective-based reading (pbr), a specific reading technique used to review software requirements. pbr verifies the quality of requirements specifications by requiring each reviewer to take the perspective of a specific stakeholder of the document (such as designer, tester, and user). this tutorial aims at industry practitioners, managers and developers alike, who want to learn more about ways to improve their software inspections with systematic reading techniques. attending this tutorial will enable the participants to be more effective and more focused in looking for potential defects in software documents. since the focus of the tutorial is on systematic reading techniques for defect detection, it is beneficial for participants to have some basic understanding about software inspections.
why use the model driven architecture to design and build distributed applications? omg's model driven architecture® (mda®)[1] unifies and simplifies modeling, design, implementation, and integration of applications -- including large and complex ones -- by defining software fundamentally at the model level, expressed in omg's standard unified modeling language® (uml®)[2]. an mda-based development goes through three steps -- two producing models, one producing code -- and typically iterates through these several times.an mda application's base model specifies every detail of its business functionality and behavior in a technology-neutral way; in mda terminology this is the application's platform-independent model (pim). use of well-known patterns, imported into the model from a library and parameterized to suit the application, speeds development and reduces error while still producing a complete and detailed pim. technology independence allows domain experts to concentrate on getting the business process correct, and preserves the model's usefulness beyond the technology churn cycle.working from the pim, mda tools follow an omg-standard mapping to generate an intermediate model tailored to the target middleware implementation platform. (omg is standardizing mappings to all popular middleware platforms; several have already been adopted.) termed a platform-specific model (psm), this intermediate product adds non-business, computing-related details (typically affecting performance and resource usage), possibly following "markup" inserted on the pim by your architects, and the version produced by the mda tool will probably require some hand-tuning before it can be used for the next step. (the amount of hand-tuning required will vary depending on the sophistication of the tool, the complexity of the application, and the maturity of the mda in your application domain.in the final development step, working from the psm, mda tools generate interface definitions, application code, makefiles, and configuration files for the psm's middleware platform. because the industry has been working on this transformation for years already, and the model is tailored specifically for this transformation, the automated conversion in this step is typically 100% or nearly so. performing a "build" on these artifacts yields a deployable application.because the pim is middleware-neutral and conversion to the psm and then to the implementation is mostly automatic, it is practical to produce equivalent implementations of mda-based applications on multiple target platforms. in addition, tools can generate cross-platform invocations, allowing easy interworking among suites of mda-based applications wherever they reside. another benefit of the mda: because industry standards defined as an mda pim are platform-independent, they can be implemented on multiple targets and then used by every enterprise even in industries that haven't converged on a single middleware platform.based on uml, automation, and sound architectural principles, the mda supports applications over their full lifecycle starting with design and moving on to coding, testing, and deployment, through maintenance, and eventually to evolution to a new platform when an application's existing platform becomes obsolete. the mda became the base architecture for omg standards in september 2001.
requirements, domain and specifications: a viewpoint-based approach to requirements engineering. viewpoint-based requirements engineering (vbre) is based on the fact that there is a multiplicity of stakeholders that take part in any requirements process. this will inevitably lead to conflicts and inconsistencies that, if adequately managed, can be used to improve the process, as they are sources of requirements. there comes a time in every vbre process when different viewpoints need to be compared to fin discrepancies (conflicts, inconsistencies). but in requirements engineering (re) we also deal with other categories of statements, apart from "requirements", like domain descriptions and interface specifications. we could use this categorization to (i) internally classify the contents of each viewpoint by categories; (ii) compare the contents of one viewpoint against another, taking into account that this comparison should only be made between elements of the same category; (iii) classify the discrepancies by the affected categories and (iv) generate resolutions for the discrepancies according to this classification. in this paper, we present a vbre method based on this approach, which is not constrained to a particular representation formalism. the proposed framework includes discrepancy detection and classification and solution generation.
using benchmarking to advance research: a challenge to software engineering. benchmarks have been used in computer science to compare the performance of computer systems, information retrieval algorithms, databases, and many other technologies. the creation and widespread use of a benchmark within a research area is frequently accompanied by rapid technical progress and community building. these observations have led us to formulate a theory of benchmarking within scientific disciplines. based on this theory, we challenge software engineering research to become more scientific and cohesive by working as a community to define benchmarks. in support of this challenge, we present a case study of the reverse engineering community, where we have successfully used benchmarks to advance the state of research.
the ramp-up problem in software projects: a case study of how software immigrants naturalize. joining a software development team is like moving to a new country to start employment; the immigrant has a lot to learn about the job, the local customs, and sometimes a new language. in an exploratory case study, we interviewed four software immigrants, in order to characterize their naturalization process. seven patterns in four major categories were found. in this paper, these patterns are substantiated, and their implications discussed. the lessons learned from this study can be applied equally to improving the naturalization process, and to the formulation of further research questions
on the supervision and assessment of part-time postgraduate software engineering projects. this paper describes existing practices in the supervision and assessment of projects undertaken by part-time, post-graduate students in software engineering. it considers this aspect of the learning experience, and the educational issues raised, in the context of existing literature---much of which is focussed upon the experience of full-time, undergraduate students. the importance of these issues will increase with the popularity of part-time study at a postgraduate level; the paper presents a set of guidelines for project supervision and assessment.
using an information retrieval system to retrieve source code samples. software developers often face steep learning curves in using a new framework, library, or new versions of frameworks for developing their piece of software. in large organizations, developers learn and explore use of frameworks, rarely realizing, several peers may have already explored the same. a tool that helps locate samples of code, demonstrating use of frameworks or libraries would provide benefits of reuse, improved code quality and faster development. this paper describes an approach for locating common samples of source code from a repository by providing extensions to an information retrieval system. the approach improves the existing approaches in two ways. first, it provides the scalability of an information retrieval system, supporting search over thousands of source code files of an organization. second, it provides more specific search on source code by preprocessing source code files and understanding elements of the code as opposed to considering code as plain text.
positive experiences with an open project assignment in an introductory programming course. the course sif8005 object-oriented programming at the ntnu is in many respects taught in a quite traditional manner, with a well-known textbook, lectures in huge auditoria, and compulsory exercises that the students have to deliver to be allowed to sit a final written exam. the exercise part of the course is a mixture of individual exercises on a weekly basis, and a somewhat larger project to be done by groups of 4 students.this paper particularly discusses the project, which has become a huge success after some notable changes were made for the 2001 offering of the course. then the assignment profile was changed from one of fixed requirements set by staff to an open assignment, where each group made a computer game according to their own preferences. this change eliminated many of the problems present in earlier offerings and increased student inspiration.
beg, borrow, or steal (workshop session): using multidisciplinary approaches in empirical software engineering research. the goal of this workshop is to provide an interactive forum for software engineers and empirical researchers to investigate the feasibility of applying proven methods from other research disciplines to software engineering research. participants submitted position papers describing problems that might benefit from a multidisciplinary approach. expert guest speakers from software engineering and other disciplines will address the issues highlighted in the papers with the goal of encouraging more multidisciplinary research.
system-dependence-graph-based slicing of programs with arbitrary interprocedural control flow. many algorithms for automating software engineering tasks require program slices. to be applicable to large software systems, these slices must be computed interprocedurally. slicing techniques based on the system dependence graph (sdg) provide one approach for computing interprocedural slices, but these techniques are defined only for programs in which called procedures necessarily return to call sites. when applied to programs that contain arbitrary interprocedural control flow, existing sdg-based slicing techniques can compute incorrect slices; this limits their applicability. this paper presents an approach to constructing sdgs, and computing slices on sdgs, that accommodates programs with arbitrary interprocedural control flow. the main benefit of our approach is that it allows the use of the sdg-based slicing technique on a wide class of practical programs to which it did not previously apply.
automated support for development, maintenance, and testing in the presence of implicit control flow. although object-oriented languages can improve programmingpractices, their characteristics may introducenew problems for software engineers. one important problemis the presence of implicit control flow caused byexception handling and polymorphism. implicit controlflow causes complex interactions, and can thus complicatesoftware-engineering tasks. to address this problem, wepresent a systematic and structured approach, for supportingthese tasks, based on the static and dynamic analyses ofconstructs that cause implicit control flow. our approachprovides software engineers with information for supportingand guiding development and maintenance tasks. wealso present empirical results to illustrate the potential usefulnessof our approach. our studies show that, for thesubjects considered, complex implicit control flow is alwayspresent and is generally not adequately exercised.
software components in a data structure precompiler. predator is a data structure precompiler that generates efficient code for maintaining and querying complex data structures. it embodies a novel component reuse technology that transcends traditional generic data types. in this paper, we explain the concepts of our work and our prototype system. we show how complex data structures can be specified as compositions of software building blocks and present performance results that compare predator output to hand-optimized programs.
a formal approach to component-based software engineering: education and evaluation. this paper summarizes an approach for introducing component-based software engineering (cbse) early in the undergraduate cs curriculum, and an evaluation of the impact of the approach at two institutions. principles taught include a modular style of software development, an emphasis on human understanding of component behavior even while using formal specifications, and the importance of maintainability, as well as classical issues such as efficiency analysis and reasoning. qualitative and quantitative evaluations of student outcomes and end-to-end changes in student attitudes show mostly positive results that are statistically significant, confirming that (1) it is possible to teach cbse principles without displacing "classical principles usually taught in introductory courses, (2) students can understand and reuse formally-specified components without knowing their implementations, and (3) student attitudes towards software engineering can be altered in directions heretofore often assumed to be difficult to achieve.
precise service level agreements. slang is an xml language for defining service levelagreements, the part of a contract between the client andprovider of an internet service that describes the quality attributesthat the service is required to possess. we definethe semantics of slang precisely by modelling the syntax ofthe language in uml, then relating the language model toa model that describes the structure and behaviour of services.the presence of slang elements imposes behaviouralconstraints on service elements, and the precise definitionof these constraints using ocl constitutes the semantic descriptionof the language. we use the semantics to define anotion of sla compatibility, and an extension to uml thatenables the modelling of service situations as a precursorto analysis, implementation and provisioning activities.
fault-tolerance in a distributed management system: a case study. our case study provides the most important conceptual lessons learned from the implementation of a distributed telecommunication management system (dtms), which controls a networked voice communication system. major requirements for the dtms are fault-tolerance against site or network failures, transactional safety, and reliable persistence. in order to provide distribution and persistence both transparently and fault-tolerant we introduce a two-layer architecture facilitating an asynchronous replication algorithm. among the lessons learned are: component based software engineering poses a significant initial overhead but is worth it in the long term; a fault-tolerant naming service is a key requirement for fail-safe distribution; the reasonable granularity for persistence and concurrency control is one whole object; asynchronous replication on the database layer is superior to synchronous replication on the instance level in terms of robustness and consistency; semi-structured persistence with xml has drawbacks regarding consistency, performance and convenience; in contrast to an arbitrarily meshed object model, a accentuated hierarchical structure is more robust and feasible; a query engine has to provide a means for navigation through the object model; finally the propagation of deletion operation becomes more complex in an object-oriented model. by incorporating these lessons learned we are well underway to provide a highly available, distributed platform for persistent object systems.
on the effectiveness of set associative page mapping and its application to main memory management. set associative page mapping algorithms have become widespread for the operation of cache memories for reasons of cost and efficiency. in this paper we show how to calculate analytically the effectiveness of set associative paging relative to full associative (unconstrained mapping) paging. for two miss ratio models, saltzer's linear model and a mixed geometric model, we are able to obtain simple, closed form expressions for the relative lru fault rates. trace driven simulations are used to verify the accuracy of our results. we suggest that as electronically accessed third level memories, such as electron beam memories, magnetic bubbles or charge coupled devices become available, algorithms currently used only for cache paging will be applied to main memory, for the same reasons of efficiency, implementation ease and cost.
propel: an approach supporting property elucidation. property specifications concisely describe what a software system is supposed to do. it is surprisingly difficult to write these properties correctly. there are rigorous mathematical formalisms for representing properties, but these are often difficult to use. no matter what notation is used, however, there are often subtle, but important, details that need to be considered. propel aims to make the job of writing and understanding properties easier by providing templates that explicitly capture these details as options for commonly-occurring property patterns. these templates are represented using both "disciplined" natural language and finite-state automata, allowing the specifier to easily move between these two representations.
mining components for a software architecture and a product line: the options analysis for reengineering (oar) method. this tutorial discusses the problem of identifying candidate software components from legacy systems and determining their reuse potential for insertion in a new architecture, particularly in a software product line architecture. the tutorial outlines options analysis for reengineering (oar), which is a systematic method for evaluating the feasibility and benefits of mining existing components for a product line. oar operates like a funnel in which a set of potential assets is screened out so that the effort can focus on those components that will most effectively meet the technical and programmatic needs of the target architecture. the method incorporates a set of scalable techniques and exercises to collaboratively analyze existing components, determine viable mining options, and evaluate the most promising options. it provides a structured approach to determine the cost, effort, and risk of mining a set of software components from legacy systems.
design and evaluation of the mobile agent architecture for distributed consistency management. the proposed mobile agent architecture for carrying out incremental consistency checks between sets of distributed software engineering documents is described and evaluated. functionality of architectural components and collaboration between them throughout the consistency check are described. architecture simulation, based on concurrent &ldquo;execution&rdquo; of state chart models of components, is used for evaluation of scalability in a number of system configurations. this work represents the first part of a thesis, which aims to establish applicability of mobile agent technology to the domain of distributed consistency management.
experiences with place lab: an open source toolkit for location-aware computing. location-based computing (lbc) is becoming increasing important in both industry and academia. a key challenge is the pervasive deployment of lbc technologies; to be effective they must run on a wide variety of client platforms, including laptops, pdas, and mobile phones, so that location data can be acquired anywhere and accessed by any application. moreover, as a nascent area, lbc is experiencing rapid innovation in sensing technologies, the positioning algorithms themselves, and the applications they support. lastly, as a newcomer, lbc must integrate with existing communications and application technologies, including web browsers and location data interchange standard.this paper describes our experience in developing the place lab architecture, a widely used first-generation open source toolkit for client-side location sensing. using a layered, pattern-based architecture, it supports modular development in any dimension of lbc, enabling the field to move forward more rapidly as these innovations are shared with the community as pluggable components. our experience shows the benefits of domain-specific abstractions, and how we overcame high-level language constraints to support a wide array of platforms in this emerging space. we also describe our experience in re-engineering parts of the architecture based on the needs of the user community, including insights on software licensing issues.
understanding requirements for computer-aided healthcare workflows: experiences and challenges. medical informatics and software engineering researchers have studied how to use software technologies to define, analyze, automate, and provide decision support for healthcare workflows. we, as the requirement engineering and prototyping group of the siemens r&d center, have been involved in the research and development of healthcare workflows. during interactions with the workflow users and developers, we found significant confusion about the terminologies and the purposes of supporting different healthcare workflows. thus, we are motivated to classify computer-aided healthcare workflows, including their approaches, goals, and major characteristics. this paper also discusses workflow application issues and software challenges based upon our experiences and research.
responsibilities and rewards: specifying design patterns. design patterns provide guidance to system designers onhow to structure individual classes or groups of classes, aswell as constraints on the interactions among these classes,to enable them to implement flexible and reliable systems.patterns are usually described informally. while such informaldescriptions are useful and even essential, if we wantto be sure that designers precisely and unambiguously understandthe requirements that must be met when applyinga given pattern, and be able to reliably predict the behaviorsthe resulting system will exhibit, we also need formalcharacterizations of the patterns.in this paper, we develop an approach to formalizing designpatterns. the requirements that a designer must meetwith respect to the structures of the classes, as well as withrespect to the behaviors exhibited by the relevant methods,are captured in the responsibilities component of the patternýsspecification; the benefits that will result by applyingthe pattern, in terms of specific behaviors that the resultingsystem will be guaranteed to exhibit, are captured in therewards component. one important aspect of many designpatterns is their flexibility; our approach is designed to ensurethat this flexibility is retained in the formalization ofthe pattern. we illustrate the approach by applying it to astandard design pattern.
a spiral approach to software engineering project management education. this paper describes the experiences of an instructor, experienced in management, teaching a software engineering project management course at a school that specializes in software education. a "spiral approach" was used to provide for the parallel acquisition of management knowledge and experience, while building on recently acquired skills in software technology and developing confidence through the successful development of a software product. this paper describes the reason for selecting the approach, the course content, the observation of the students and the instructor, the advantages and disadvantages of the approach as applied, and conclusions. course objectives were met and course evaluations by students indicated a much higher level of acceptance than previous traditional approaches. the observations indicated that the approach may extend beyond the classroom to the industrial setting where on the job training, career path planning, and management development are of concern.
a compositional formalization of connector wrappers. increasingly systems are composed of parts: software components, and the interaction mechanisms (connectors) that enable them to communicate. when assembling systems from independently developed and potentially mismatched parts, wrappers may be used to overcome mismatch as well as to remedy extra-functional defciencies.unfortunately the current practice of wrapper creation and use is ad hoc, resulting in artifacts that are often hard to reuse or compose, and whose impact is diffcult to analyze. what is needed is a more principled basis for creating, understanding, and applying wrappers. focusing on the class of connector wrappers (wrappers that address issues related to communication and compatibility), we present a means of characterizing connector wrappers as protocol transformations, modularizing them, and reasoning about their properties. examples are drawn from commonly practiced dependability enhancing techniques.
mixin up components. recently we proposed a language called acoel (a component-oriented extension language) for abstracting and composing software components. components in acoel are black-box components, and each component consists of (1) an internal implementation containing classes, methods, and fields that is hidden to the external world, and (2) an external contract consisting of a set of typed input and output ports. components in acoel interact with each other only via these ports. in this paper we extend acoel in two directions: (1) use mixins to customize the services provided by a component without exposing its internal implementation, (2) add support for virtual types and sub-type relation among components. we will show how mixins and virtual types together allows us to build adaptable applications based on black-box component principles.
object oriented reuse: experience in developing a framework for speech recognition applications. the development of highly interactive software systems with complex user interfaces has become increasingly common, where prototypes are often used as a vehicle for demonstrating visions of innovative systems. given this trend, it is important for new technology to be based on flexible architectures that do not mandate the understanding of all complexities inherent in a system. in this context, we share our experience with developing an object oriented framework for a specific new technology, i.e. speech recognition. we describe the benefits of the object oriented paradigm rich with design patterns, which provide a natural way to model complex concepts and capture system relationships effectively, along with achieving a high level of software reuse
software engineering for undergraduates. software engineering has evolved, over a short period of time, into a dominant and omnipresent industry. in education we have recognized the importance of both managerial and technical aspects, but often failed to organize them in a coherent course with a relevant, if not realistic laboratory project. the problem is far-reaching, and should be dealt with accordingly. this paper presents our before and after findings, and elaborates on cpe 207, the new software engineering course that, in our opinion, helps in bridging the gap between university and industry.
a collection of software tools for analyzing design of concurrent software systems. we present results from a research project to investigate the feasibility of software tools for analyzing designs of software systems. such analysis would help the software developer to assess the acceptability of designs before the development of the software moves from the design phase into the implementation phase. if this could be done, futile implementation efforts based on faulty designs could be avoided. we have constructed a language for expressing designs of sequential and concurrent software systems, and software tools to analyze these designs. our analysis tools derive behavior information, in terms of reachable states or possible sequences of significant events, from system descriptions in a variety of ways. by means of controlled human-factors experiments, we have determined that our analysis tools and techniques are indeed useful, to varying extents, in helping people to understand designs and find flaws in them.
database theory for supporting specification-based database systems development. we report on the development of a formal theory of databases designed to support specification-based development of database systems. this theory formalizes database systems which include non-first normal form relations, complex integrity constraints, transactions, and embedded data types such as integers, character strings, and user-defined types. our theory is based on two axiomatized algebras (abstract data types) and is being used to mechanically prove the properties of relational algebra and functional dependencies, as well as the relationships between integrity constraints and the primitive operations on databases, e. g., inserts and deletes of tuples. we are also using the theory to prove whether or not specific transactions obey complex integrity constraints which can include universal and existential quantifiers. the latter proofs (as well as failed attempts at proofs) can be used during the design of specific systems and in the optimization of system implementations.
on the role of an environment. it is suggested that the role of an environment is to support effective use of an effective process. such a process is complex, varied, organisation-specific, and evolving. consideration of these process characteristics raises a number of issues concerning the scope of an environment, its overall architecture, and its data structures.
requirements expression and verification aid. samm is a top-down dominated activity modeling technique which has a representation scheme which has been automated. the automation, called samdf, validates the input, verifies the model, and produces a document illustrating the functional relationships of the system being modeled. sammdf significantly enhances the perception of system requirements, and it is this perception that benefits the design produced from the requirements.
an analysis of the resources used in the safeguard system software development. the safeguard system represents the development of one of the largest, most complex software systems ever undertaken. various types of software were developed, including real time applications, support, and hardware installation and maintenance. two million instructions were developed at a cost of approximately five thousand staff years of effort. the objective of this paper is to document the staff resources utilized in this development. the actual development rates for the different types of software and the various factors affecting those rates are analyzed. software productivity is shown to be a function of the type of software - logical, algorithmic, man machine, etc. emphasis is placed upon total project productivity. the allocation of staff resources for the systems engineering, design, code and unit test, and integration activities, which had an approximate percentage distribution of 20, 20, 17, 43, is analyzed and characterized.
the software engineering of agent-based intelligent adaptive systems. future software systems will be intelligent and adaptive. they will have the ability to seamlessly integrate with smart applications that have not been explicitly designed to work together. traditional software engineering approaches offer limited support for the development of intelligent systems. to handle the tremendous complexity and the new engineering challenges presented by intelligence, adaptiveness and seamless integration, developers need higher-level development constructs. agent concepts are natural to describe intelligent adaptive systems. agent-based technologies have been incorporating software engineering practices, and have matured to offer useful insights and concrete practices to mainstream software engineers.this tutorial presents the state of the art in agent development from a software engineering perspective, focusing on practices that are applicable today. we will walk the audience through analysis, design and verification of a portion of a real-world problem: a smart home network. we show how agent concepts more naturally match the engineering challenges of such systems like trust between adaptive components. the audience will have hands-on experience with analyzing and designing parts of the smart home network and learn how to incorporate agent technologies into their current projects.
some experience in building portable software. several authors have discussed methodology for making software portable, but less has been written about the specific components of programs which are likely to be system-dependent. this paper is based on several years of successful experience in making a major software product (mark iv) transportable among many operating systems and machines. the product is implemented in assembly language and developed on a single support system for all of the "target" systems. the specific strategies and conclusions presented here are based on more general principles, and should be more or less applicable to systems developed in higher-level languages. the system dependencies are isolated in as few modules as possible. various techniques are used to include system-dependent code at assembly time, at installation tape creation time and at customer installation time. the system-dependent functions addressed by this paper are: program start and termination, input/output, primary storage management, interrupt control, checkpointing, module loading, overlay structures and object module format and other installation considerations.
test templates: a specification-based testing framework. test templates and a test template framework are introduced as useful concepts in specification-based testing. the framework can be defined using any model-based specification notation and used to derive tests from model-based specifications. it is demonstrated using the z notation. the framework formally defines test data sets and their relation to the operations in a specification and other test data sets, providing structure to the testing process. flexibility is also preserved, so that many testing strategies can be used. important application areas of the framework are discussed, including refinement of test data, regression testing, and test oracles
a comparison of the use of links and secondary indices in a relational data base system. the possibility of supporting relational data sublanguages on top of a data base system with an underlying network data structure has been widely suggested. in this paper we present a formal model of a mix of interactions in one non procedural relational language. under a collection of assumptions concerning the data base and the performance criteria, we compare the following performance oriented data structures: (1) secondary indices (2) a network structure similar to a pointer array implementation of dbtg sets (3) structures 1) and 2) together it is shown that option 2) is never preferred to both @@@@ and 3) over the range of model parameters, hence, the sole use of sets or &ldquo;links&rdquo; as a performance oriented access path is questionable.
traceability for system families. system families are an idea of software reuse in a specific problem domain. existing methods have little requirements engineering support for system family development. this short paper proposes a requirements metamodel for system family development. traceability throughout model elements is a necessary precondition for preserving the consistency of the complete family model during development and is a main issue in this paper as well as for software development in general. family development based on the metamodel guarantees traceability by the inclusion of all development artifacts in a single and consistent model.
testing concurrent java components. testing concurrent software is notoriously difficult due to problems with non-determinism and synchronisation. while tools and techniques for the testing of sequential components are well-understood and widely used, similar tools and techniques for concurrent components are not commonly available. this tutorial will look at the problems associated with testing concurrent components and propose techniques for dealing with these problems. the conan (concurrency analyser) testing tool supports these techniques for the testing of concurrent java components and will be discussed and demonstrated in the tutorial. the limitations of the techniques and conan, as well as additional v&v tools and techniques to address these limitations will be presented.
how software is really engineered? the term software engineering currently ranks high on the list of today's popular buzz words. yet we still don't agree on its definition and often overlook many pragmatics associated with its use. a software engineering community is emerging which is devoting a great deal of attention to various &ldquo;systematic&rdquo; programming methodologies and automated programming tools. much of this problem stems from the difficulty of combining theoretically rich technology with an aesthetically unpleasant engineering philosophy. this engineering philosophy espouses doing what appears to be necessary to complete a large project. it is this last point which i would like to explore in the balance of this short paper. this paper will explore various pragmatic aspects of real world projects relating to &ldquo;software engineering.&rdquo; the subsequent panel discussion will serve as a forum for relating specific observations from typical project environments. extrapolation of these observations to future projects will also be discussed.
abstract models of dialogue concepts. we introduce formal, abstract models for specifying modern dialogue concepts offered by dialogue interfaces. the dialogue concepts considered in this paper are menus, forms, and windows. using these abstract models a totally formal definition of man-machine interactions and screen layouts is achieved. thus the semantics of user actions can be formalized. the specification method we are using is the vienna development method. examples are taken from the application development and support system ads which offers dialogue functions for generating and using application systems.
supporting dynamic composition of components. the internet creates new opportunities for component distribution. infrastructure for dynamic, web-based composition of software components appears to be a very impelling need. this demonstration focuses on a web-based system that supports dynamic component composition.
holmes: an intelligent system to support software product line development. holmes is a software product line tool that supports all core activities of software product line analysis and development. holmes integrates its tools using a blackboard architecture based on a linda tuple space. a novel feature is the use of a critiquing system to provide semantic support. this is demonstrated with an example.
7th international workshop on economics-driven software engineering research. the 7th international workshop on economics-driven software engineering research (edser-7) continues to be the leading forum for the discussion of emerging research ideas in software economics. the focus of the workshop is on the use of economic models for reasoning about technical issues and decisions in the definition, design, development, deployment, and evolution of software and software-intensive systems.
experience assessing an architectural approach to large-scale systematic reuse. systematic reuse of large-scale software components promises rapid, low cost development of high-quality software through the straightforward integration of existing software assets. to date this promise remains largely unrealized, owing to technical, managerial, cultural, and legal barriers, one important technical barrier is architectural mismatch. recently, several component integration architectures have been developed that purport to promote large-scale reuse. microsoft's ole technology and associated applications are representative of this trend. to understand the potential of these architectures to enable large-scale reuse, we evaluated ole by using it to develop a novel fault-tree analysis tool. although difficulties remain, the approach appears to overcome architectural impediments that have hindered some previous large-scale reuse attempts, to be practical for use in many domains, and to represent significant progress towards realizing the promise of barge-scale systematic reuse.
information survivability control systems. we address the dependence of critical infrastructures-including electric power, telecommunications, finance and transportation-on vulnerable information systems. our approach is based on the notion of control systems. we envision hierarchical, adaptive, multiple model, discrete state distributed control systems to monitor infrastructure information systems and respond to disruptions (e.g., security attacks) by changing operating modes and design configurations to minimize loss of utility. to explore and evaluate our approach, we have developed a toolkit for building distributed dynamic models of infrastructure information systems. we used this toolkit to build a model of a simple subset of the united states payment system and a control system for this model information system.
science of design. in this plenary panel session, three distinguished scholars of design will provide a range of perspectives on a science of design for software and software-intensive systems. the session will include brief presentations by the panelists as well as dialog among the panelists and with members of the audience.
a web-oriented architectural aspect for the emerging computational tapestry. an emerging tapestry of computations will soon integrate systems around the globe. it will evolve without central control. its complexity will be vast. we need new ideas, tools and methods to help map, understand and manage this tapestry. we contribute a light-weight architectural aspect that designers can use without compromising their own architectural preferences. widespread use could help. the idea is for objects to provide web-based interfaces to object-specific meta-data, state, and monitoring and control services. we discuss applications, implementation, scalability, performance, tradeoffs, and related work.
software quality assessment technology. necessities for software quality measurement and assurance technology have been increased. b. boehm and mccall proposed software evaluation criteria. based on these studies, g. murine developed software quality metrics (sqm). sqm was applied to several projects in nec experimentally. an outline of the experiment will be presented and the results discussed. software quality measurement and assurance technology (sqmat) was developed in nec as a total technology for applying to various types and size of software projects, throughout the software life cycle.
program complexity measure for software development management. the program complexity measure currently seems to be the most capable measure for both quantitative and objective control of the software project. five program complexity measures (step count, mccabe's v(g), halstead's e, weighted statement count and process v(g)) were assessed from such a viewpoint. this empirical study was done with the data collected through a practical software project. all of these measures have highly significant correlations with the management data. application of complexity measures to software development management is discussed and a method for the detection of anomalous modules in a program is proposed.
architectural support for trust models in decentralized applications. decentralized applications are composed of distributed entities that directly interact with each other and make local autonomous decisions in the absence of a centralized coordinating authority. such decentralized applications, where entities can join and leave the system at any time, are particularly susceptible to the attacks of malicious entities. each entity therefore requires protective measures to safeguard itself against these entities. trust management solutions serve to provide effective protective measures against such malicious attacks. trust relationships help an entity model and evaluate its confidence in other entities towards securing itself. trust management is, thus, both an essential and intrinsic ingredient of decentralized applications. however, research in trust management has not focused on how trust models can be composed into a decentralized architecture. the pace architectural style, described previously [21], provides structured and detailed guidance on the assimilation of trust models into a decentralized entity's architecture. in this paper, we describe our experiments with incorporating four different reputation-based trust models into a decentralized application using the pace architectural style. our observations lead us to conclude that pace not only provides an effective and easy way to integrate trust management into decentralized applications, but also facilitates reuse while supporting different types of trust models. additionally, pace serves as a suitable platform to aid the evaluation and comparison of trust models in a fixed setting towards providing a way to choose an appropriate model for the setting.
the dimensions of maintenance. the area of software maintenance has been described by one author as an &ldquo;iceberg.&rdquo; (edp analyzer, 1972) much goes on here that does not currently meet the eye. in part, this is the consequence of measurement difficulties. practitioners and researchers can benefit from an understanding of the &ldquo;dimensionality&rdquo; of the maintenance problem. some measures are suggested for coming to grips with this dimensionality, and problems of utilization associated with these measures are explored.
component technology - what, where, and how?. software components, if used properly, offer many software engineering benefits. yet, they also pose many original challenges starting from quality assurance and ranging to architectural embedding and composability. in addition, the recent movement towards services, as well as the established world of objects, causes many to wonder what purpose components might have.this extended abstract summarizes the main points of my frontiers of software practice (fosp) talk at icse 2003. the topics covered aim to offer an end-to-end overview of what role components should play, where they should be used, and how this can be achieved some key open problems are also pointed out.
the making of a software engineer challenges for the educator. software engineering is foremost an engineering discipline. engineering in general and software engineering specifically has to balance many factors to achieve viable tradeoffs - an understanding of the factors as well as the viability criteria is at the heart of the educational challenge. all engineering has one ultimate goal: the delivery of artifacts (products, commercial or not) that meet the needs of those using such artifacts. all engineering lives in the intersection of people, technology, domain, and opportunity aspects. software engineering, however, is laden with its own specific difficulties. software as an engineering medium fills a space between the fluidity of digital content, with which software shares the representation, and the nature of machines, with which software shares the flexible and repeatable application.
agent system development method based on agent patterns. this paper proposes a method of agent system development based on agent patterns that represent typical and recurring structures and behaviors of agents. the agent patterns are classified according to their appropriate architectural levels and the degree of their dependence on specific agent platforms. our method enables developers to design agent systems efficiently since they can construct complicated system architectures and behaviors by dividing the design process into two architectural levels and applying the appropriate agent patterns. in addition, the higher level designs are independent of specific agent platforms and can be therefore easily reused.
a programmer performance measure based on programmer state transitions in testing and debugging process. to organize and manage software development teams, it as important to evaluate the capability of each programmer based on reliable and easily collected data. we present a system which automatically monitors programmer activities, and propose a programmer debugging performance measure based on data monitored by the system. the system automatically categorizes programmer activity in real time into three types (compilation, program execution, and program modification) by monitoring and analyzing key strokes of a programmer. the resulting outputs are the time sequences of monitored activities. the measure we propose is the average length of debugging time per fault, d, estimated from the data sequences monitored by the system. to estimate the debugging time per fault, we introduce a testing and debugging process model. the process model has parameters associated with the average length of a program modification, d, and the probability of a fault being fixed completely by a program modification, r. by taking account of r as well as d, the debugging time per fault can be estimated with high accuracy. the model parameters, such as d and r, are computed from the monitored data sequences by using a maximum likelihood estimation method
visual aid for fortran program debugging. this paper presents a new type of debugging tool for fortran programs. we call this the &ldquo;dock&rdquo; system, referring to the dock where ships stay during repairs. dock provides new debugging functions such as slow display of program execution. major functions and a brief indication of the methods of implementation are given in this paper. four &ldquo;execution modes&rdquo; control execution speed. execution is displayed on the screen in full screen mode. the source program listing is displayed with the executing statement shown in a different color or brightness. at certain places, the program stops temporarily in a status called &ldquo;stationary mode&rdquo;. in the stationary mode, several debugging functions are available.
an empirical study of a model for program error prediction. a model is presented for estimating the number of errors remaining in a program at the beginning of the testing phase of development. the relationships between the errors occurring in a program and the various factors that affect software development, such as programmer skill, are statistically analyzed. the model is then derived using the factors significantly identified in the analysis. on the basis of data collected during the development of large-scale software systems, it is shown that factors such as frequency of program specification change, programmer skill, and volume of program design documentation are significant and that the model based on these factors is more reliable than conventional error prediction methods based on program size alone.
how to teach software modeling. to enhance motivation of students to study software engineering, some way of finding balance between the scientific aspect and the practical aspect of software engineering is required. in this paper, we claim that teaching multiple software modeling techniques from a unified viewpoint is a good way of obtaining the balance and attracting the students' interest as well.
requirements and design change in large-scale software development: analysis from the viewpoint of process backtracking. change of requirements and design specifications is one of the fatal causes of large scale software development project problems. the authors study this problem from the viewpoint of software process backtracking. they conducted case studies of real business application system development projects. it was found that there were several cases of process backtracking in large scale projects and the process model should be flexible to allow reversibility. the users learning processes are considered. among many probable factors that cause the volatility of user requirements and thus result in process backtracking, specific attention is given to the fact that as users learn to use a system and accumulate experience of the system usage, they change their system requirements level. the importance of considering this evolution process and finding a way of predicting changes in user requirements are discussed
an adaptive object model with dynamic role binding. to achieve the goal of realizing object adaptation to environments, a new role-based model epsilon and a language epsilonj is proposed. in epsilon, an environment is defined as a field of collaboration between roles and an object adapts to the environment assuming one of the roles. objects can freely enter or leave environments and belong to multiple environments at a time so that dynamic adaptation or evolution of objects is realized. environments and roles are the first class constructs at runtime as well as at model description time so that separation of concerns is not only materialized as a static structure but also observed as behaviors. environments encapsulating collaboration are independent reuse components to be deployed separately from objects. in this paper, the epsilon model and the language are explained with some examples. the effectiveness of the model is illustrated by a case study on the problem of integrated systems. implementation of the language is also reported.
heuristic-based model refinement for flavers. flavers is a finite-state verification approach that allowsan analyst to incrementally add constraints to improvethe precision of the model of the system being analyzed. exceptfor trivial systems, however, it is impractical to computewhich constraints should be selected to produce preciseresults for the least cost. thus, constraint selection hasbeen a manual task, guided by the intuition of the analyst.in this paper, we investigate several heuristics for selectingtask automaton constraints, a kind of constraint that tendsto reduce infeasible task interactions. we describe an experimentshowing that one of these heuristics is extremelyeffective at improving the precision of the analysis resultswithout significantly degrading performance.
managing space for finite-state verification. finite-state verification (fsv) techniques attempt to prove properties about a model of a system by examining all possible behaviors of that model. this approach suffers from the state-explosion problem, where the size of the model or the analysis costs may be exponentially large with respect to the size of the system. using symbolic data structures to represent subsets of the state space has been shown to usually be an effective optimization approach for hardware verification. the value for software verification, however, is still unclear. in this paper, we investigate applying two symbolic data structures, binary decision diagrams (bdds) and zero-suppressed binary decision diagrams (zdds), in two fsv tools, ltsa and flavers. we describe an experiment showing that these two symbolic approaches can improve the performance of both fsv tools and are more efficient than two other algorithms that store the state space explicitly. moreover, the zdd-based approach often runs faster and can handle larger systems than the bdd-based approach.
estimating loc for information systems from their conceptual data models. effort and cost estimation is crucial in software management. estimation of software size plays a key role in the estimation. line of code (loc) is still a commonly used software size measure. despite the fact that software sizing is well recognized as an important problem for more than two decades, there is still much problem in existing methods. conceptual data model is widely used in the requirements analysis for information systems. it is also not difficult to construct conceptual data models in the early stage of developing information systems. much characteristic of an information system is actually reflected from its conceptual data model. we explore into the use of conceptual data model for estimating loc. this paper proposes a novel method for estimating loc for an information system from its conceptual data model through the use of multiple linear regression model. we have validated the method through collecting samples from both the industry and open-source systems.
consistency management for complex applications. consistency management is important in many complex applications, but current languages and database systems inadequately support it. to address this limitation, we defined a consistency management model and incorporated it into the pleiades object management system. this paper illustrates some typical consistency management requirements and discusses the requirements in terms of both functionality and cross-cutting concerns that affect how this functionality is provided. it then describes the model and some design and implementation issues that arose in instantiating it. finally, we discuss user feedback and future research plans
workshop on multi-dimensional separation of concerns in software engineering. separation of concerns has been central to software engineering for decades, yet its many advantages are still not fully realized. a key reason is that traditional modularization mechanisms do not allow simultaneous decomposition according to multiple kinds of (overlapping and interacting) concerns. this workshop was intended to bring together researchers working on more advanced modularization mechanisms, and practitioners who have experienced the need for them, as a step towards a common understanding of the issues, problems and research challenges.
hyper/j: multi-dimensional separation of concerns for java. hyper/j supports a new approach to constructing, integrating and evolving software, called multi-dimensional separation of concerns. it addresses a number of common problems in the development, evolution, and integration of large-scale, complex software systems, helping to achieve many goals of software engineering. these include: improved comprehension and reduced complexity of software; non-invasive adaptation and customization, promoting off-the-shelf reuse; the ability to synthesize, compose, and integrate separate pieces of software into new pieces of software; the ability to extract new concerns from existing software, non-invasively; non-invasive, low-impact evolution; and improved ability to allow multiple, decentralized teams to work on different, but overlapping, parts of software simultaneously, thus reducing development bottlenecks and promoting more rapid software development.
workshop on advanced separation of concerns in software engineering. separation of concerns can provide a host of well-known and crucial benefits, but only if the concerns that are separated and modularized match the concerns one needs to deal with&mdash;which can be of dramatically different kinds in different development contexts. traditional modularization approaches have proven inadequate. work in the growing area of advanced separation of concerns seeks to provide more powerful and flexible modularization, capable of encapsulating multiple kinds of overlapping, interacting and crosscutting concerns. this workshop is intended to bring together researchers and practitioners in this and related areas, to explore some of the many open issues..
a programming environment supporting reuse of object-oriented software. we have developed a programming environment for object-oriented programming. this environment supports reuse of classes, especially retrieval of them with an expert system. the user can find classes and methods by describing the features of objects and operations according to an object model proposed by us. the target programming language is momo, which is developed by us to implement the object model. this paper mainly focuses on the retrieval part of the environment.
a technique for prototyping directly from a specification. a technique is described for prototyping a system directly from a specification. the technique uses the logic programming language prolog and involves translating the specification into a prolog form. this is used in conjunction with a set of functions, also written in prolog, which provide an operational interpretation of the semantics of the specification language, and a user interface which allows the user to exercise the specification and examine its behaviour.
workshop on software engineering and computer-human interaction: joint research issues. software engineering and computer-human interaction have much to do with each other, but their respective research communities typically have little interaction. the purpose of the article is to explore the intersections of these areas, determining what each community has to offer the other as well as to identify and address open problems of mutual interest. topics of discussion were drawn from the following: cost drivers, current products, prototyping, requirements, formal methods and specifications, testing and evaluation, design and development, architectures, user interfaces and software environments, chi and cscw concerns and toolkits
steps to an advanced ada programming environment. conceptual simplicity, tight coupling of tools, and effective support of host-target software development will characterize advanced ada programming support environments. several important principles have been demonstrated in the arcturus system, including template-assisted ada editing, command completion using ada as a command language, and combining the advantages of interpretation and compilation. other principles, relating to analysis, testing, and debugging of concurrent ada programs, have appeared in other contexts. this paper discusses several of these topics, considers how they can be integrated, and argues for their inclusion in an environment appropriate for software development in the late 1980's.
a tour through cedar. this lively walk through a sophisticated programming environment is taken from a videotaped demonstration of the system. there is no need to adjust your set.
an early report on encompass. encompass is an environment to support the incremental construction of ada&reg; programs using executable specifications and formal techniques similar to the vienna development method. encompass supports the rigorous development of software: parts of a project may use completely formal methods, while other, less critical parts use less expensive techniques. encompass provides automated support for all aspects of the development process including specification, prototyping, testing, formal verification, documentation, configuration control and project management. in encompass, software can be specified using please, an ada-based executable specification language which can be automatically translated into prolog. a prototype implementation of encompass has been constructed. in this paper, we give an overview of encompass, describe the decisions made in the design of the prototype, and discuss the lessons learned in the process.
evolution in the design of abstract machines for software portability. the abstract machine model is the best one for solving the difficult problem of program transferring, but an evolution in the design of these machines is necessary. after a brief survey of the well-known abstract machines, this paper proposes the design of a more general one to implement portable operating systems. the complex problem of relating this abstract machine to existing computers is discussed and the paper explains how the top-down methodology is an inestimable means to reduce the machine dependence.
team-based fault content estimation in the software inspection process. the main objective of software inspection is to detectfaults within a software artifact. this helps to reduce thenumber of faults and to increase the quality of a softwareproduct. however, although inspections have been performedwith great success, and although the quality of theproduct is increased, it is difficult to estimate the quality.during the inspection process, attempts with objective estimationsas well as with subjective estimations have beenmade. these methods estimate the fault content after an inspectionand give a hint of the quality of the product. thispaper describes an experiment conducted throughout theinspection process, where the purpose is to compare the estimationmethods at different points. the experiment evaluatesteam estimates from subjective and objective faultcontent estimation methods integrated with the software inspectionprocess. the experiment was conducted at two differentuniversities with 82 reviewers. the result shows thatobjective estimates outperform subjective when point andconfidence intervals are used. this contradicts the previousstudies in the area.
third international summit on software engineering education (ssee iii): bridging the university/industry gap. innovative university/industry interactions are examined in this open event with the aim of providing inputs to an international project that is being funded through the united kingdom's teaching fellowship scheme. these inputs will support the first stage of the project which is concerned with gaining knowledge of industrial software engineering practices and the development of a framework that can be used in the classification and evaluation of such practices.
design, implementation, and evaluation of a revision control system. the revision control system (rcs) is a software tool that helps in managing multiple revisions of text. rcs automates the storing, retrieval, logging, identification, and merging of revisions, and provides access control. it is useful for text that is revised frequently, for example programs and documentation. this paper presents the design and implementation of rcs. both design and implementation are evaluated by contrasting rcs with sccs, a similar system. sccs is implemented with forward, merged deltas, while rcs uses reverse, separate deltas. (deltas are the differences between successive revisions.) it is shown that the latter technique improves run-time efficiency, while requiring almost no extra space.
binary refactoring: improving code behind the scenes. we present binary refactoring: a software engineering technique for improving the implementation of programs without modifying their source code. while related to regular refactoring in preserving a program's functionality, binary refactoring aims to capture modifications that are often applied to source code, although they only improve the performance of the software application and not the code structure. we motivate binary refactoring, present a binary refactoring catalogue, describe the design and implementation of barber---our binary refactoring browser for java, and demonstrate the usefulness of binary refactoring through a series of benchmarks.
evaluating the reverse engineering capabilities of web tools for understanding site content and structure: a case study. this paper describes an evaluation of the reverse engineering capabilities of three web tools for understanding site content and structure. the evaluation is based on partitioning web sites into three classes (static, interactive, and dynamic), and is structured using an existing reverse engineering environment framework (reef). this case study also represents an initial evaluation of the applicability of the reef in the related but qualitatively different domain of web sites. the case study highlights several shortcomings of current web tools in the context of aiding understanding to support evolution. for example, most web tools are geared towards new page design and development, not to understanding detailed page content or overall site structure. the evaluation also identified some aspects of the reef that might benefit from refinement to better reflect web tool capabilities that support common evolution tasks. for example, web server log file analysis as a specialized form of data gathering and subsequent information presentation.
improvement of a configuration management system. the company cad-ul ag develops software tools for embedded systems. single tools as compilers, linkers and debuggers are offered as well as complete development tool chains for the software development process. in contrast to application software for personal computers, embedded systems require very specialized software of highly optimized and exhaustively tested code.since the previously existing configuration management was not efficient in comparison to the state-of-the-art in software engineering, an improvement was implemented by the introduction of a modern configuration management (cm) system [1].in this presented paper, cad-ul intends to show the results and the experiences of the european systems & software initiative process improvement experiment (essi-pie) icms with the new configuration management system.
formal concept analysis in software engineering. given a binary relationship between objects and attributes,concept analysis is a powerful technique to organizepairs of related sets of objects and attributes into a conceptlattice, where higher level concepts represent generalfeatures shared by many objects, while lower level conceptsrepresent the object-specific features. concept analysis wasrecently applied to several software engineering problems,such as: restructuring the code into more cohesive components,identifying class candidates, locating features in thecode by means of dynamic analysis, reengineering class hierarchies.this tutorial provides the background knowledgerequired by such applications. moreover, the methodologicalissues involved in the different applications of this techniqueare considered by giving a detailed presentation ofthree of them: module restructuring, design pattern inferenceand impact analysis based on decomposition slicing.the tutorial is concluded by an overview on other kinds ofapplications.
reverse engineering of object oriented code. during software evolution, programmers devote most of their effort to the understanding of the structure and behavior of the system. for object-oriented code, this might be particularly hard, when multiple, scattered objects contribute to the same function. design views offer an invaluable help, but they are often not aligned with the code, when they are not missing at all.this tutorial describes some of the most advanced techniques that can be employed to reverse engineer several design views from the source code. the recovered diagrams, represented in uml (unified modeling language), include class, object, interaction (collaboration and sequence), state and package diagrams. a unifying static code analysis framework used by most of the involved algorithms is presented at the beginning of the tutorial. a single running example is referred all over the presentation. trade-offs (e.g., static vs. dynamic analysis), limitations and expected benefits are also discussed.
the second international workshop on automated program analysis, testing and verification. program analysis, testing and verification are key techniques for building confidence in and increasing the quality of software systems. such activities typically cost upwards of 50% of total development costs. automation aims to allow both reduced costs and more thorough analysis, testing and verification and is vital to keep pace with increasing software complexity. this workshop follows on from the successful workshop held as part of icse 2000 in ireland to further discuss these issues and the current start-of-the-art.
software reuse myths revisited. in acm software engineering notices, vol. 13, no. 1, pp. 17-21 (1988), the author published the paper &ldquo;software reuse myths&rdquo;. this paper comments on these &ldquo;myths&rdquo; in the light of recent technology advances: (1) software reuse is a technical problem; (2) special tools are needed for software reuse; (3) reusing code results in huge increases in productivity; (4) artificial intelligence will solve the reuse problem; (5) the japanese have solved the reuse problem; (6) ada has solved the reuse problem; (7) designing software from reusable parts is like designing hardware using integrated circuits; (8) reused software is the same as reusable software; and (9) software reuse will just happen
development of a hybrid cost estimation model in an iterative manner. cost estimation is a very crucial field for software developing companies. the acceptance of an estimation technique is highly dependent on estimation accuracy. often, this accuracy is only determined after an initial application. possible further steps for improving the underlying estimation model typically do not influence the decision on whether to discard the technique or deploy it. in addition, most estimation techniques do not explicitly support the evolution of the underlying estimation model in an iterative manner. this increases the risk of overlooking some important cost drivers or data inconsistencies. this paper presents an enhanced process for developing a cobra® cost estimation model by systematically including iterative analysis and feedback cycles, and its evaluation in a software development unit of oki electric industry co., ltd., japan. during the model improvement cycles, estimation accuracy was improved from an initial 120% down to 14%. in addition, lessons learned with the iterative development approach are described.
a management approach to the development of computer-based systems. many organizations have experienced serious difficulties in developing complex computer-based systems, especially their software components. the problems include large cost overruns, schedule slippages, inadequate performance, and inability to use the system as originally envisioned. one major reason for such lack of success has been the inability of the management of the organization or the development effort to understand the need for a total-system management approach. in particular, acquisition of software and hardware separately with the hope of integrating them later does not work in complex systems. this paper outlines a management approach to acquiring computer systems which encompasses the whole system, with emphasis on the software, from the initial concept formulation to the support of the operational system. expected improvements in the development process and organizational implications of this management approach are discussed.
using web service technologies to create an information broker: an experience report. this paper reports on our experiences with using theemerging web service technologies and tools to create ademonstration information broker system as part of ourresearch into information management in a distributedenvironment. to provide a realistic context we chose tostudy the use of information in the healthcare domain,and this context sets some challenging parameters andconstraints for our research and for the demonstrationsystem. in this paper we both report on the extent towhich existing web service technologies have proved tobe mature enough to meet these requirements, and alsoassess their current limitations.
the software factory: combining undergraduate computer science and software engineering education. industry often complains that current university curricula fail to address the practical issues of real software development. this paper outlines a proposal for an innovative core curriculum for a bachelor of science in computer science. the proposed core curriculum contains elements of traditional computer science programs combined with software engineering via a team-oriented, hands-on approach to large-scale software development. in addition to traditional lecture/project/exam courses, students are required to take an eight-semester sequence of &ldquo;software factory&rdquo; courses. software factory courses put the students' newly acquired skills to work in a real software organization staffed and managed by all students in the program. students from all courses in the software factory sequence meet simultaneously to fulfill their roles in the software organization. we expect the students will be better-prepared software engineering practitioners after completing a curriculum that combines traditional courses with practical software factory experience.
ensemble of missing data techniques to improve software prediction accuracy. software engineers are commonly faced with the problem of incomplete data. incomplete data can reduce system performance in terms of predictive accuracy. unfortunately, rare research has been conducted to systematically explore the impact of missing values, especially from the missing data handling point of view. this has made various missing data techniques (mdts) less significant. this paper describes a systematic comparison of seven mdts using eight industrial datasets. our findings from an empirical evaluation suggest listwise deletion as the least effective technique for handling incomplete data while multiple imputation achieves the highest accuracy rates. we further propose and show how a combination of mdts by randomizing a decision tree building algorithm leads to a significant improvement in prediction performance for missing values up to 50%.
silver bullet or fool's gold: supporting usability in open source software development. at first glance it can look like open source software development violates many, if not all, of the precepts of decades of careful research and teaching in software engineering. one could take a classic se textbook and compare the activities elaborated and advocated in the various chapters with what is actually done in plain sight in the public logs of an oss project in say sourceforge. for a professor of software engineering this might make for rather depressing reading. are the principles of se being rendered obsolete? has oss really discovered brooks' silver bullet? or is it just a flash in the pan or fool's gold.in this talk i will mainly look at one aspect of open source development, the 'problem' of creating usable interfaces, particularly for non-technical end-users. any approach involves the challenge of how to coordinate distributed collaborative interface analysis and design, given that in conventional software development this is usually done in small teams and almost always face to face. indeed all the methods in any hci text just assume same-time same-place work and don't map to distributed work, let alone the looser mechanisms of oss development. instead what is needed is a form of participatory usability involving the coordination of end users and developers in a constantly evolving redesign process.
a workbench for synthesising behaviour models from scenarios. scenario-based specifications such as message sequence charts (mscs) are becoming increasingly popular as part of a requirements specification. our objective is to facilitate the development of behaviour models in conjunction with scenarios. in this paper, we first present an msc language with semantics in terms of labelled transition systems and parallel composition. the language integrates existing languages based on the use of high-level mscs (hmscs) and on identifying component states. this integration allows stakeholders to break up scenario specifications into manageable parts using hmcss and to explicitly introduce additional information and domain-specific or other assumptions using state labels. secondly, we present an algorithm, implemented in java, which translates scenarios into a specification in the form of finite sequential processes. this can then be fed to the labelled transition system analyser for model checking and animation. finally we show how many of the assumptions embedded in existing synthesis approaches can be translated into our approach. thus we provide the basis of a common workbench for supporting msc specifications, behaviour synthesis and analysis.
a cooperative approach to software development by application engineers and software engineers. we have tried a new project management approach for the development of engineering application software systems. the key factor of this new approach is the introduction of the role of &ldquo;interpreter&rdquo; who sits in between application engineers and programmers and handles all of the communication problems among them. our major objectives were: (1) to release application engineers from unfamiliar programming tasks as much as possible. (2) and to increase the productivity of a small group of technical staffs. experiments upon real projects resulted in much greater improvement of productivity and quality than we had expected. and also the morale of team members was improved. this paper describes the results of these experiments and the characteristics of this new development approach in comparison with the traditional one.
modeling software for accurate data flow representation. a particular model used for data flow oriented structural testing is the def-use graph which captures intraprocedural data flow dependencies within the control flow exhibited by a program written in a procedural language. since procedures in a program are closely interrelated, data flow oriented structural testing must also be performed at the program level utilizing the interprocedural data flow dependencies. the authors point out that the accuracy of the representation of data flow dependencies by the def-use graph is no longer acceptable at the program level where the accurate representation of interprocedural data flow dependencies is needed. this point is illustrated by an error that cannot be revealed by existing data flow oriented test path selection criteria when the procedures of a program are considered individually, but can be revealed by at least two of the criteria which require accurate representation of interprocedural data flow dependencies. a new model, called the extended def-use graph is proposed to represent both intraprocedural and interprocedural data flow dependencies in the control flow exhibited by a program. this model facilitates the application of the existing data flow oriented test path selection criteria at the program level
software development with executable functional specifications. the descartes specification language and support software provides a tool for developing and executing functional specifications. a variety of specifications have been developed to support the language design and evaluation. in addition, the language has been applied to the development of a large specification. current research efforts include: specification development, support software enhancements, and software life cycle impact. an overview of the specification language is included in this paper. the language processor for descartes is described in relation to providing the capability for executing specifications. program development and testing with respect to utilizing descartes is outlined.
using process technology to control and coordinate software adaptation. we have developed an infrastructure for end-to-end run-time monitoring, behavior/performance analysis, and dynamic adaptation of distributed software. this infrastructure is primarily targeted to pre-existing systems and thus operates <u>outside</u> the target application, without making assumptions about the target's implementation, internal communication/computation mechanisms, source code availability, etc. this paper assumes the existence of the monitoring and analysis components, presented elsewhere, and focuses on the mechanisms used to control and coordinate possibly complex repairs/reconfigurations to the target system. these mechanisms require lower-level effectors somehow attached to the target system, so we briefly sketch one such facility (elaborated elsewhere). our main contribution is the model, architecture, and implementation of workflakes, the decentralized process engine we use to tailor, control, coordinate, etc. a cohort of such effectors. we have validated the workflakes approach with case studies in several application domains. due to space restrictions we concentrate primarily on one case study, briefly discuss a second, and only sketch others.
experience with the development of hard real-time embedded ada software. though already intrinsically demanding, the development of real-time embedded on-board software is often made harsher by the constraining nature of the execution environment and the general lack of suitable support. one of the key needs in the design of these systems is to get guidance towards the definition of a system that is truly analysable against timing requirements; specialised methods and tools are needed to accommodate this particular demand. this paper reports on the use of a novel design method especially tailored towards the construction of hard real-time systems
engineering the software requirements of nonprofits: a service-learning approach. this paper is a cross-study of service-learning projects executed by student groups in a 10-week course on software engineering. the principal benefits of service-learning are demonstrated by the groups in this setting. the course is structured to support the project activities; timely brainstorming and negotiation roleplay exercises help the teams arrive at pragmatic baselines with their clients. the study highlights overlaps in the software requirements of nonprofits. the paper apprises the reader of some common mistakes committed by the various stakeholders, some of which can eventually undermine the project's mission.
jungl: a scripting language for refactoring. refactorings are behaviour-preserving program transformations, typically for improving the structure of existing code. a few of these transformations have been mechanised in interactive development environments. many more refactorings have been proposed, and it would be desirable for programmers to script their own refactorings. implementing such source-to-source transformations, however, is quite complex: even the most sophisticated development environments contain significant bugs in their refactoring tools.we present a domain-specific language for refactoring, named jungl. it manipulates a graph representation of the program: all information about the program, including asts for its compilation units, variable binding, control flow and so on is represented in a uniform graph format. the language is a hybrid of a functional language (in the style of ml) and a logic query language (akin to datalog). jungl furthermore has a notion of demand-driven evaluation for constructing computed information in the graph, such as control flow edges. borrowing from earlier work on the specification of compiler optimisations, jungl uses so-called `path queries' to express dataflow properties.we motivate the design of jungl via a number of non-trivial refactorings, and describe its implementation on the.net platform.
five years of product line engineering in a small company. in 1999, a new team at market maker software ag began to develop a software product line for managing and displaying stock market data and financial market news. the basic idea was to use web technology in all applications for delivering services to customers. it soon turned out that the company had to change both the processes and the organization. this report summarizes the changes made and the lessons learned over the past five years, when the product line idea was introduced into a small company which faced the pressure to quickly market the first product line instances.
a methodology and tool for performance analysis of distributed server systems. we present a methodology and tool for performance analysis of distributed server systems, which allows high-level specification of the system, and generates and solves the underlying queueing network model. our approach is different from the existing ones in that the specification captures the natural manner in which application servers are deployed on machines and machines are deployed on networks. the model does not impose any strict tiers on the server system. multiple use case scenarios can be specified, and the tool computes measures such as end-to-end response times for each scenario while taking into account queueing delays at the hardware device, software threads and at the network. the development of the tool is ongoing, and will include detailed network protocol models as well as more flexible distributed system behavior, in the future.
analyzing software architectures with argus-i. this formal research demonstration attempts to present an approach to develop and assess architecture and component-based systems based on specifying software architecture augmented by statecharts representing component behavioral specifications [1]. the approach is applied for the c2 style [2] and associated adl and is supported within a quality-focussed environment, called argus-i, which assists specification-based analysis and testing at both the component and architecture levels.
introduction to corba (tutorial session). this tutorial provides the basics that developers need to begin understanding the common object request broker architecture (corba) and using it to write industrial-strength distributed systems. you will learn about the basics of the object management group's (omg) object management architecture (oma), with a focus on its corba component. by the end of the tutorial, you will understand how to write object interface specifications using the omg interface definition language (idl), how to write simple distributed applications in c++, how to use the portable object adapter (poa), the dynamic invocation interface (dii) and the dynamic skeleton interface (dsi), and the interface repository (ifr). you will also know the basics of several corba services such as naming, trading, and events.
scalability issues in corba-based systems (tutorial session). this tutorial addresses how both the object management group (omg) specifications and the implementation choices made by middleware providers and application developers affect common object request broker architecture (corba) application scalability. we will cover a range of scalability issues, starting with object request broker (orb) internals and working outward to full-scale applications, addressing issues such as connection management, portable object adapter (poa) scalability features, multithreading, object lifecycle issues, object location, system configuration, maintenance, and management, and common application architectures. this tutorial is not language-centric and is useful to developers using java, c++, or any other language to develop corba-based applications.
empirical validation of pair programming. this paper discusses an empirical assessment of pair programming.
the multics system programming process. features of the multics system programming process lead to high programmer productivity with a small programming staff and a finished system with high software reliability. other workers' predictions of increasing difficulty of system maintenance with time have not been observed; reasons for this are suggested.
some myths of software engineering education. based on many years of teaching software engineering, i present a number of lessons i have learned over the years. i do so in the form of a series of myths, the reverse of which can be considered challenges to educators. the overall message i wish to convey is that there's more to software engineering than engineering. the engineering metaphor gives us a lot of useful guidance in shaping our profession. but there's also a downside, in that this goes at the expense of the human, social dimension that is an essential element of our profession.
aspects of design, test and validation of the software for a computerized reactor protection system. in safety-oriented applications, the software has to fulfil certain stringent reliability requirements. in order to determine the reliability of the software, a variety of different methods can be used. the methods used for the reliability proof of a computerized reactor protection system are discussed in this paper. in addition to the constructive approach with structured programming, defensive programming and other guidelines also concerning the operating system, the analytical approach is taken. this includes the use of an automatic test system for statical and dynamical analysis of the software and automatic test data generation. finally, a systemtest is conducted, where test data are produced according to the process and the results are compared with the results of a simulation model.
software engineering challenges: a cio's perspective. to be competitive in today's market, businesses face many challenges in the development and maintenance of information systems. these systems are usually widely distributed. they incorporate highly critical corporate knowledge, which has to be easily accessible and maintainable. engineering these large systems efficiently requires making decisions about a number of issues. decisions about whether to build or buy software affect qualities of the software such as customization and reusability, and decisions about mobility of services affect qualities of the software such as maintainability. moreover, for improved reliability, techniques that can provide seamless but secure and reliable information flow and transaction processing, although expensive, must be integrated into the development process. finally, systems must be adaptable to new technologies such as wireless computing. old existing legacy software has to be integrated with new web-based applications such as portals or the whole world of &ldquo;e&rdquo;.
software templates. software components often cannot be reused since the algorithms they realize are encoded in terms of particular implementations. this paper presents an approach to reusability where algorithms and implementations are specified separately. an algorithm is specified by a sequence of recursion equations called a software template. templates are defined over values of abstract data types whose implementations are specified separately and catalogued. when a template's data types are bound to catalogued implementations, the template is automatically translated into a component tailored to the chosen implementations, a process called template instantiation. different implementations of an algorithm can be achieved by merely binding the data types of its template, specification to different implementations.
productivity factors and programming environments. fourteen factors that influence the efficiency of programming projects were identified in a corporate-wide study of 44 itt programming projects in nine countries. productivity factors were classified according to project management's ability to control them. product-related factors are not generally under the control of project management. they describe intrinsic properties of the programming product and tend to place limitations on achievable productivity. project-related factors, on the other hand, are controllable by project management to varying degrees. these factors provide real opportunities for productivity improvement. the analysis indicates that productivity variation is almost equally attributable to product-related and project-related factors.
an initial assessment of aspect-oriented programming. the principle of separation of concerns has long been used by software engineers to manage the complexity of software system development. programming languages help software engineers explicitly maintain the separation of some concerns in code. as another step towards increasing the scope of concerns that can be captured cleanly within the code, kiczales and colleagues have introduced aspect-oriented programming. in aspect-oriented programming, explicit language support is provided to help modularize design decisions that cross-cut a functionally-decomposed program. aspect-oriented programming is intended to make it easier to reason about, develop, and maintain certain kinds of application code. to investigate these claims, we conducted two exploratory experiments that considered the impact of aspect-oriented programming, as found in aspectj version 0.1, on two common programming activities: debugging and change. our experimental results provide insights into the usefulness and usability of aspect-oriented programming. our results also raise questions about the characteristics of the interface between aspects and functionally-decomposed core code that are necessary to accrue programming benefits. most notably, the separation provided by aspect-oriented programming seems most helpful when the interface is narrow (i.e., the separation is more complete); partial separation does not necessarily provide partial benefit.
methods of component-based software engineering: essential concepts and classroom experience. the crucial role of software components in the construction of enterprise information management systems is now manifest. notwithstanding this, the implication of software components on software engineering methods is not well understood by many practitioners. this tutorial explores the implications of two classes of component-based development efforts. first, those efforts where components are custom-developed and deployed onto a pre-fabricated component infrastructure such as enterprise javabeanstm, and second, efforts where commercial off-the-shelf components are integrated into an enterprise infrastructure upon which business logic can be deployed.
architectural level risk assessment tool based on uml specifications. recent evidences indicate that most faults in software systems are found in only a few of a system's components [1]. the early identification of these components allows an organization to focus on defect detection activities on high risk components, for example by optimally allocating testing resources [2], or redesigning components that are likely to cause field failures. this paper presents a prototype tool called architecture-level risk assessment tool (arat) based on the risk assessment methodology presented in [3]. the arat provides risk assessment based on measures obtained from unified modeling language (uml) artifacts [4]. this tool can be used in the design phase of the software development process. it estimates dynamic metrics [5] and automatically analyzes the quality of the architecture to produce architectural-level software risk assessment [3].
bsr: a statistic-based approach for establishing and refining software process performance baseline. high-level process management is quantitative management. the process performance baseline (ppb) of process or subprocess under statistical management is the most important concept. it is the basis of process control and improvement. the existing methods for establishing process baseline are too coarse-grained or have some limitation, which lead to inaccurate or ineffective quantitative management. in this paper, we propose an approach called bsr (baseline-statistic-refinement) for establishing and refining software process performance baseline, and present the experience result to validate its effectiveness for quantitative process management.
a worldwide survey of base process activities towards software engineering process excellence. a survey has been designed to seek the practical foundation of base process activities (bpas) in the software industry and to support research in modelling the software engineering processes. a superset of bpas compatible with the current software process models, such as spice (iso 15504), cmm, iso 9000 and bootstrap, were identified for the construction of the questionnaires. this paper reports the survey findings on bpas in software engineering processes. a summary of the current software engineering process techniques and practices modelled by 83 bpas in 10 processes and three categories is given. each bpa is benchmarked on attributes of mean importance and ratios of significance, practice and effectiveness. based on the benchmarks, and by comparing with the current practice of the reader's organization, recommendations can be given on which specific areas need to have processes established first, and which areas should be highest priority for process improvement
simulating the behaviour of software modules by trace rewriting. the trace assertion method is a module interface specification method based on the finite state machine model. to support this method, we plan to develop a specification simulation tool, a trace simulator, that symbolically interprets trace assertions of trace specifications and simulates the externally observable behavior of the modules specified. we first present the trace assertion method. then we formally define trace rewriting systems and show how trace rewriting, a technique similar to term rewriting, can be applied to implement trace simulation.
using compressed bytecode traces for slicing java programs. dynamic slicing is a well-known program debuggingtechnique. given a program p and input i, it finds all programstatements which directly/indirectly affect the valuesof some variablesý occurrences when p is executed with i.dynamic slicing algorithms often proceed by traversing theexecution trace of p produced by input i (or a dependencegraph which captures control/data flow in the executiontrace). consequently, it is important to develop space efficient representations of the execution trace.in this paper, we use results from data compression tocompactly represent bytecode traces of sequential java programs.the major space savings come from the optimizedrepresentation of data (instruction) addresses used by memoryreference (branch) bytecodes as operands. we give detailedexperimental results on the space efficiency and timeoverheads for our compact trace representation. we thenshow how dynamic slicing algorithms can directly traverseour compact traces without resorting to costly decompression.we also develop an extension of dynamic slicing whichallows us to explain omission errors (i.e. why some eventsdid not happen during program execution).
reengineering standalone c++ legacy systems into the j2ee partition distributed environment. many enterprise systems are developed in c++ language and most of them are standalone. because the standalone software can not follow the new market environment, reengineering the standalone legacy systems into distributed environment becomes a critical problem. some methods have been proposed on related topics such as design recovery, the identification of the component, modeling the interfaces of components and components allocation. up to now, there does not exist a reengineering process for partition distributed environment, which will offer distinct advantages on horizontal scalability and performance over normal distributed solutions. this paper presents a new process to reengineer c++ legacy systems into the j2ee partition distributed environment. the process consists of four steps: translation from c++ to java code; extraction of components using the cluster technology; modeling component interfaces and partition of the components in j2ee distribute environment. it has been applied to a large equity-trading legacy system which has proved to be successful.
system challenges for ubiquitous & pervasive computing. the terms ubiquitous and pervasive computing were first coined at the beginning of the 90's, by xerox parc and ibm respectively, and capture the realization that the computing focus was going to change from the pc to a more distributed, mobile and embedded form of computing. furthermore, it was predicted by some researchers that the true value of embedded computing would come from the orchestration of the various computational components into a much richer and adaptable system than had previously been possible. now some fifteen years later, we have made progress towards these aims. the hardware platforms used to implement these systems encapsulate significant computation capability in a small form-factor, consume little power and have a small cost. however, the system software capabilities have not advanced at a pace that can take full advantage of this infrastructure. this paper will describe where software and hardware have combined to enable ubiquitous computing, where these systems have limitations and where the biggest challenges still remain.
map: a tool for understanding software. maintenance of software is a major problem that the data processing industry faces today. this paper describes map, a tool, that addresses the problems of software maintenance by helping programmers to understand their programs.
experience with a module package in developing production quality pascal programs. a module package (amp) is a preprocessor to a pascal compiler to support data encapsulation and modular system development. experience with amp in developing a software product at amdahl corporation has demonstrated its utility and robustness.
experiments on quality evaluation of embedded software in japan robot software design contest. as a practical opportunity for educating japanese young developers in the field of embedded software development, a software design contest involving the design of software to automatically control a line-trace robot, and conduct running performance tests was held. in this paper,we give the results of the contest from the viewpoint of software quality evaluation. we create a framework for evaluating the software quality which integrated design model quality and the final system performance, and conduct analysis using the framework. as a result of analysis,it is found that the quantitative measurement of the structural complexity of the design models bears a strong relationship to qualitative evaluation of the design conducted by judges. it is also found that there is no strong correlation between design model quality evaluated by the judges and the final system performance. for embedded software development, it is particularly important to estimate and verify reliability and performance in the early stages,using the model. based on the analysis result,we consider possible remedies with respect to the models submitted,the evaluation methods used and the contest specifications. in order to adequately measure several non-functional quality characteristics including performance on the model,it is necessary to improve the way of developing robot software (such as applying model driven development)and reexamine the evaluation methods.
reuse facts and myths. this paper on software reuse is the view of a practitioner rather than of a scientist. myth 1: oo technology eats up reuse. fact 1: oo does not automatically yield high reuse rates-both oo and reuse can complement each other. myth 2: incentives are key to reuse success. fact 2: incentives create awareness, are cheap but don't change much. myth 3: reuse is for free. fact 3: reuse is a mid-term investment impacting the entire software development process. it must be based on a product strategy which spans several releases or a family of products
user software engineering and the design of interactive systems. the successful construction of interactive systems requires the utilization of principles of user-centered design, combined with techniques for software engineering, in order to produce systems that are reliable, easy to use, and well adapted to user needs. this paper presents some of these principles and shows how they are achieved in the user software engineering (use) project, which is intended to provide the applications developer with a development environment that supports the systematic specification and implementation of interactive systems.
implications of hardware advances for software development. during the past few years, advances in hardware technology have significantly changed the nature of software development. in the 1970's, the model of software development environments changed from batch processing to time sharing, with all software developers connected to the time-sharing system via terminals. this model of computing has changed in the 1980's from time sharing to distributed processing. software developers now have their own personal computers, which is connected to other computers over a local area network. leading software engineering organizations have developed computing environments based around engineering workstations, such as those manufactured by sun microsystems, apollo computer, digital equipment corporation, hewlett-packard, and others, the current estimate is that approximately 50,000 such workstations are being used for software development, and this number is growing rapidly. these software development environments are based upon a distributed network of workstations, connected by a local area network, such as an ethernet or decnet. individual workstations may be &ldquo;diskfull&rdquo; or diskless, with one or more workstations acting as file servers, where a distributed file system, such as nfs or rfs, provides all users will access to files. once the system is configured, the combination of the local area network and the distributed file system supports file location transparency. these workstations support windowing systems as well, allowing users to have several active windows concurrently performing tasks. new window systems, such as mit's x windows and sun's news, support host/client processing, so that windows on the client machine can be used to execute window-based applications on the host. the combination of the local area network with the distributed window system supports &ldquo;execution transparency,&rdquo; so that the user need not be aware of the processor on which a task is executed, as long as all of the resources needed for execution of the task are available. of course, the distributed file system is an essential part of the necessary support for execution transparency. as this model evolves, the computing environment will grow in terms of the number of users on the network, the volume of traffic on the local area network, and the volume of data to be stored. advances in hardware technology are needed to support the evolution of this model of computing. this panel session addresses some of these requirements for future distributed software development environments. among the topics to be discussed are: what are the price/performance characteristics of future workstations? where will today's personal computers, such as the ibm pc and the macintosh, fit into this computing environment? what are the expected uses of increased workstation computing power? what are the limitations of current local area network technology? what are the characteristics of emerging high performance local area networks? how can optical disk technology be used in computing environments? what are the implications of distributed window systems and distributed file systems for future distributed computing environments? what are the expected costs and benefits for software development organizations? anthony west of sun microsystems, inc., will discuss aspects of future workstations, including sun's high performance processor work and their sparc architecture. such processors already provide 7 mips of desktop computing power, figure that will increase sharply in the next few years. w.r. franta of network systems, inc., will discuss the ethernet and its successors, including emerging technology that offers a bandwidth that is 100 times greater than that available with the ethernet. koichi ogawa of fujitsu laboratories will discuss optical disk systems and their use for mass storage. the panel will then discuss the ways in which such mass storage can be used in a distributed software development environment.
a specification-based adaptive test case generation strategy for open operating system standards. the paper presents a specification based adaptive test case generation (sbatcg) method for integration testing in an open operating system standards environment. in the sbatcg method, templates describing abstract state transitions are derived from a model based specification, and the templates are refined to the internal structure of each implementation. we adopt the z notation, one of the most widely used formal specification languages. we conducted mutation analysis to study the fault exposure abilities of the sbatcg method and that of a strategy based only on a specification. in our experiment, we used a z version of the itron2 real time multi task operating system specification and two commercially available itron2 implementations. the results of this equipment show that the sbatcg method can achieve a higher fault detecting ability than can the strategy using only a specification.
brazilian software quality in 2002. brazil aims to achieve international standards on quality and productivity in the software sector. from 1993 onwards there are strategies and projects to reach the brazilian objective on software quality. since 1995 there have been nationwide surveys on software quality every 2 years. this paper highlights the main trends on software quality in brazil based both on the results of four surveys (1995, 1997, 1999, and 2001) and on other pieces of evidence. the paper concludes that the software quality in brazil is continuously improving.
research pradigms in computer science. this paper explores the ramifications of four influential definitions of computer science: 1. computer science is the study of phenomena related to computers, newell, perlis and simon, 1967 2. computer science is the study of algorithms, knuth, 1968 3. computer science is the study of information structures, wegner, 1968, curriculum 68 4. computer science is the study and management of complexity, dijkstra, 1969. the first definition reflects an empirical tradition since it asserts that computer science is concerned with the study of a class of phenomena. the second and third definitions reflect a mathematical tradition since algorithms and information structures are two abstractions from the phenomena of computer science. the fourth definition reflects the great complexity of engineering problems encountered in managing the construction of complex software-hardware systems. it is argued in section 1 that computer science was dominated by empirical research paradigms in the 1950s, by mathematical research paradigms in the 1960s and by engineering oriented paradigms in the 1970s. section 2 illustrates how these three phases of development are reflected in the field of programming languages. the remaining sections consider in greater detail how empirical, mathematical and engineering research paradigms have affected the development of computer science. section 3 indicates that although the phenomena of computer science are created by man they can be studied using the empirical techniques of the natural sciences. section 4 distinguishes between &ldquo;micro computer science&rdquo; concerned with the study of individual algorithms and &ldquo;macro computer science&rdquo; concerned with the study of mechanisms and notations for specifying all algorithms; and between intensional &ldquo;how&rdquo; specifications and extensional &ldquo;what&rdquo; specifications for programs and computing systems. section 5 distinguishes between the uses of the term &ldquo;complexity&rdquo; in software engineering and the analysis of algorithms and suggests that different terms be used to denote these two kinds of complexity. in a final section it is argued that the diversity of research paradigms in computer science may be responsible both for our difficulties in deciding how computer scientists should be trained and for divergences of opinion concerning the nature of computer science research.
research directions in software technology. this paper reports on the results of a study, sponsored by afosr, aro and onr, of current and future research directions in technological areas of computer science. this study is similar in spirit to the nsf-sponsored cosers (computer science and engineering research study) project, but is narrower in scope, emphasizing concepts and research issues relevant to software technology rather than the whole spectrum of research directions in computer science. it was started in the summer of 1975 and has resulted in a book to be published by the mit press in the summer of 1978. section 1 of this paper discusses the objectives and organization of the book and introduces a framework for structuring the subject matter of software technology which parallels the structure of the book. sections 2 and 3 respectively discuss the impact on research of the changing technological environment and the unusual nature of software products. sections 4-7 present a detailed summary of the contributions of individual chapters. section 8 enumerates research directions for each of the areas considered. section 9 briefly considers time horizons and funding philosophies.
evaluating software development environments. the purpose of defining a methodology for evaluating software development environments is to add a degree of rigor and standardization to the process in much the same way as benchmark test suites do for evaluating certain hardware and software. the methodology developed at the software engineering institute is user-oriented, comprehensive, repeatable, extensible, and partly environment independent. it has been used to evaluate several ada environments so that they may be compared objectively according to the same criteria.the methodology is based on the underlying activities of software engineering since it focuses on the support of key software lifecycle activities rather than on adherence to a pre-existing tool taxonomy. the following paragraphs briefly describe the steps of each of the six phases of the methodology. the first three phases are independent of any particular environment and the last three are repeated for each environment evaluated.
overstructured management of software engineering. poor management can increase software costs more rapidly than any other factor, yet few studies have been made of poor management. one model suggests that poor management may arise from overly structured thinking on the part of software engineers who become managers after achieving technical success.
quality of service engineering with uml, .net, and corba. the concern for non-functional properties of software components and distributed applications has increased significantly in recent years. non-functional properties are often subsumed under the term quality of service (qos). it refers to quality aspects of a software component or service such as real-time response guarantees, availability, and fault-tolerance, the degree of data consistency, the precision of some computation, or the level of security. consequently, the specification and implementation of qos mechanisms has become an important concern in the engineering of distributed applications. in this tutorial the attendees will learn how non-functional requirements can be engineered in a systematic way into applications on top of distribution platforms such as corba and .net. the tutorial focuses on two major subjects areas: (1) specification of qos properties and (2) implementation of qos mechanisms in middleware. we present a comprehensive, model-driven approach. it starts with a platform-independent model (pim) in uml that captures the application qos requirements. this model is mapped by a tool to a platform-specific model (psm) tailored for a specific middleware, which is extended with the corresponding qos mechanisms. finally, the psm is translated to code. participants in this tutorial will get a thorough understanding of general qos requirements, qos modeling alternatives and qos mechanism integration in respect to popular distributed object middleware. furthermore, we will discuss the pros and cons of corba and .net for qos engineering. a tool will be demonstrated that eases substantially the modeling stages and the code generation.
program slicing. program slicing is a method used by experienced computer programmers for abstracting from programs. starting from a subset of a program's behavior, slicing reduces that program to a minimal form which still produces that behavior. the reduced program, called a &ldquo;slice&rdquo;, is an independent program guaranteed to faithfully represent the original program within the domain of the specified subset of behavior. finding a slice is in general unsolvable. a dataflow algorithm is presented for approximating slices when the behavior subset is specified as the values of a set of variables at a statement. experimental evidence is presented that these slices are used by programmers during debugging. experience with two automatic slicing tools is summarized. new measures of program complexity are suggested based on the organization of a program's slices.
goal-oriented software assessment. companies that engage in multi-site, multi-project software development continually face the problem of how to understand and improve their software development capabilities. we have defined and applied a goal-oriented process that enables such a company to assess the strengths and weaknesses of those capabilities. our goals are to help a) to decrease the time and cost to develop software, b)to decrease the time needed to make changes to existing software, c) to improve software quality, d) to attract and retain a talented engineering staff, and e) to facilitate more predictable management of software projects. in response to the variety of product requirements, market needs, and development environments, we selected a goal-oriented process, rather than a criteria-oriented process, to advance our strategy and ensure relevance of the results. we describe the design of the process, discuss results achieved, and present vulnerabilities of the methodology. the process includes both interviews with projects' personnel and analysis of change data. several common issues have emerged from the assessments across multiple projects, enabling strategic investments in software technology. teams report satisfaction with the outcome in that they act on the recommendations, ask for additional future assessments, and recommend the process to sibling organizations.
the design, analysis, and verification of the sift fault-tolerant system. the sift (software implemented fault tolerance) computer is a fault-tolerant computer in which fault tolerance is achieved primarily by software mechanisms. tasks are executed redundantly on multiple, independent processors that are loosely synchronized. each processor is multiprogrammed over a set of distinct tasks. a system of independently accessible busses interconnects the processors. when task a needs data from task b, each version of a votes, using software, on the data computed by the different versions of b. (a processor cannot write into another processor; all communication is accomplished by reading.) thus, errors due to a malfunctioning processor or bus can be confined to the faulty unit and can be masked, and the faulty unit can be identified. an executive routine effects the fault location and reconfigures the system by assigning the tasks, previously assigned to the faulty unit, to an operative unit. since fault-tolerant computers are used in environments where reliability is at a premium, it is essential that the software of sift be correct. the software is realized as a hierarchy of modules in a way that significantly enhances proof of correctness. the behavior of each module is characterized by a formal specification, and the implementation of the module is verified with respect to its specification and those of modules at lower level of the hierarchy. an abstract, markov-like model is used to describe the reliability behavior of sift. this model is formally related to the specifications of the top-most modules of the hierarchy; thus the model can be shown to describe accurately the behavior of the system. at the time of writing, the verification of the system is not complete. the paper describes the design of sift, the reliability model, and the approach to mapping from the system to the model.
a system to improve incorrect programs. this paper presents a system (phenarete) which understands and improves incompletely defined lisp programs, such as those written by students beginning to program in lisp. this system takes, as input, the program without any additional information. in order to understand the program, the system meta-evaluates it, using a library of pragmatic rules, describing the construction and correction of general program constructs, and a set of specialists, describing the syntax and semantics of the standard lisp functions. the system can use its understanding of the program to detect errors in it, to eliminate them and, eventually, to justify its proposed modifications. this paper gives a brief survey of the working of the system, emphasizing some commented examples.
the design of an integrated, interactive and incremental programming environment. we are currently implementing a system to help experienced programmers during the development, implementation and debugging of their programs. this system, built on top of a screen oriented structural editor, offers possibilities of attaching descriptors to every portion of the program and to maintain - simultaneously - different versions of the program being written, including tentative hypothetical versions. it comprises a mecanism to maintain minimal consistency between modified parts of code, the non-modified parts of code and the attached descriptors, as well as an evaluation module functioning in different modes : normal evaluation, symbolic evaluation and checking evaluation. the standard programming aids, such as indexors, pretty printers, trace packages, undo- and history-facilities are generalized to handle the descriptors and unfinished programs as well.
maxims for malfeasant designers, or how to design languages to make programming as difficult as possible. communication with the computer is by artificial languages: programming languages and command languages, as well as ad hoc languages of messages. while many such languages are sufficiently rich to permit proper expression of what must be said, some are so limited or inconsistent that a user must go to needless effort in learning the language and using it to communicate successfully with the computer. as part of the final exam of a course on the design of computer languages for human use, students were asked to suggest what &ldquo;... the language designer can do to make the programming process as difficult as possible.&rdquo; this paper contains some of the more popular responses, annotated with examples from current programming languages and systems.1
high-integrity code generation for state-based formalisms. we are attempting to create a translator for a formal state-based specification language (rsml-&egr;) that is suitable for use in safety-critical systems. for such a translator, there are two main concerns: the generated code must be shown to be semantically equivalent to the specification, and it must be fast enough to be used in the intended target environment. we address the first concern by providing a formal proof of the translation, and by keeping the implementation of the tool as simple as possible. the second concern is addressed through a variety of methods: (1) decomposing a specification into parallel subtasks, (2) providing provably-correct optimizations, and (3) making worst-case performance guarantees on the generated code.
a defense view of software engineering. the department of defense is engaged in a number of management initiatives to improve the cost and quality of defense software systems. a new dod directive 5000.29 provides guidelines for management and technology to promote software engineering in the dod. a major defense-wide initiative is a thrust toward common programming languages. an hol working group has set unified requirements for dod languages and in evaluating existing languages against these requirements. interim common languages are being set. the eventual goal is a minimal number of common high order programming languages for defense systems. these will be provided with rigorous control and extensive support facilities.
an introduction to java 2 micro edition (j2me); java in small things. by now, most people are familiar with the java 2 platform and how sun has grouped java technologies into three editions (standard, micro and enterprise editions). sun introduced the java 2, micro edition (j2me) in june 1999 to address the needs of the consumer electronics and embedded devices community. specifically, the j2me was built for devices with limited power, network connectivity (often wireless), and graphical user interface capabilities. today, the j2me provides a java platform to an incredibly diverse set of devices. generally speaking, this space covers devices with less computing capabilities than a personal computer, yet more capabilities than a smart card.
enterprise javabean architecture and design issues. enterprise javabeans (ejb) technology has become a staple in distributed object and component architectures. however, like most technologies, ejb provides technology tradeoffs that must be weighted by the architect contemplating its use. furthermore, like most technologies, ejb cannot save a poor system design. design issues surrounding an enterprise system, in particular design issues of an ejb system, can be addressed at two levels. ejb design at the &ldquo;macro&rdquo; level is concerned with system architectural issues such as determining whether ejb technology is right for a project, how to model ejbs, and how to select an appropriate ejb server. ejb design from a &ldquo;micro&rdquo; level perspective concentrates on the use and organization of the various ejb types in an application. these &ldquo;micro&rdquo; issues include: when and where to use entity versus session beans, the granularity (fine or coarse) of ejbs, and the impact of the underlying database on bean design.
towards and engineering approach to software design. the software design process is discussed from an engineering point of view. initially, a distinction is made between software design and program design. software design is then described in terms of evolving a system architecture independently of implementation considerations. computation structures are introduced as a means of modeling the dynamic behavior of a software architecture. functional completeness, quality, machine independence, and performance completeness of a design are then used as criteria for engineering design decisions. finally, the basic elements of a system to support the software design process are described.
experiments determining best paths for testing computer program predicates. zeil has developed a vector space measure which indicates those paths which best detect errors in a selected program predicate. this measure has to be applied to a set of paths post hoc, and so the problem is to heuristically characterize those paths which will provide maximal test information about the selected predicate; the problem of selecting the optimal set of paths is np-hard. experiments have been conducted which utilize the vector space criterion to indicate those characteristics of paths which can best be used to test a given predicate. these characteristics will then provide a selection mechanism for an appropriate set of paths. other questions involve the selection of those paths which sufficiently test all the program predicates, and to experimentally identify those program properties which lead to an irreducible error space for a predicate.
workshop description of 5th intl. workshop on scenarios and state machines: models-algorithms-and tools (scesm). scesm '06 is the 5th international workshop on scenarios and state machines: models, algorithms and tools. it is a one day icse '06 workshop. details about scesm '06 may be found at http://ise.gmu.edu/scesm06/.
generating statechart designs from scenarios. this paper presents an algorithm for automatically generating uml statecharts from a collection of uml sequence diagrams. computer support for this transition between requirements and design is important for a successful application of uml's highly iterative, distributed software development process. there are three main issues which must be addressed when generating statecharts from sequence diagrams. firstly, conflicts arising from the merging of independently developed sequence diagrams must be detected and resolved. secondly, different sequence diagrams often contain identical or similar behaviors. for a true interleaving of the sequence diagrams, these behaviors must be recognized and merged. finally, generated statecharts usually are only an approximation of the system and thus must be hand-modified and refined by designers. as such, the generated artifact should be highly structured and readable. in terms of statecharts, this corresponds to the introduction of hierarchy. our algorithm successfully tackles all three of these aspects and will be illustrated in this paper with a well-known atm example.
from scenarios to code: an air traffic control case study. two high profile workshops at oopsla and icse, an ieee computer article by david harel and a growing number of research papers have all suggested algorithms that translate scenarios of a system's behavior into state machines. one of the uses of such algorithms is in the transition from requirements scenarios to component design. to date, however, most efforts have concentrated on the algorithmic details of the proposed translations. less work has been done on evaluating these algorithms on a realistic case study. in this paper, we do exactly that for the algorithm presented in [10]. our study is a component of an air traffic advisory system developed at nasa ames research center.
producing more reliable software: mature software engineering process vs. state-of-the-art technology? a customer of high assurance software recently sponsored a software engineering experiment in which a real-time software system was developed concurrently by two popular software development methodologies. one company specialized in the state-of-the-practice waterfall method rated at a capability maturity model level 4. a second developer employed his mathematically based formal method with automatic code generation. as specified in separate contracts, c++ code plus development documentation and process and product metrics (errors) were to be delivered. both companies were given identical functional specs and agreed to a generous and equal cost, schedule, and explicit functional reliability objectives. at conclusion of the experiment an independent third party determined through extensive statistical testing that neither methodology was able to meet the user's reliability objectives within cost and schedule constraints. the metrics collected revealed the strengths and weaknesses of each methodology and why they were not able to reach customer reliability objectives. this paper will explore the specification for the system under development, the two competing development processes, the products and metrics captured during development, the analysis tools and testing techniques by the third party, and the results of a reliability and process analysis.
supporting diversity with component frameworks as architectural elements. in this paper, we describe our experience with component frameworks within a family architecture for a medical imaging product family. the component frameworks are handled as an integral part of the architectural approach and are an important means to support diversity in the functionality provided by the individual family members.this paper focuses on a particular kind of component framework that has been applied throughout the medical imaging product family. this kind of framework is useful when the various family members are based on the same concepts and the diversity is formed by the differences in the specific instances of these concepts that are present in the family members. these component frameworks have a number of similarities, allowing a standardised approach to their development. they support the division of the system into a generic architectural skeleton, which can be extended with plug-ins to realise specific family members, each with their own set of features.
specification level interoperability. there is an increasing need and desire to develop systems by combining components that are written in different languages and/or that are run on different kinds of machines. success at this depends in large part on the `interoperability'' of the components---that is, the ability of the compon- ents to communicate and work together despite their differing backgrounds. while most previous approaches to interoperability have provided support at the representation level, we are pursuing an approach that will provide support at the specification level. we have developed a model of such sup- port that consists of four components: 1) a `unified type model'', which is a notation for describing the entities to be shared by interoperating pro- grams; 2) `language bindings'', which connect the type models of the lan- guages to the unified type model; 3) `underlying implementations'', which realize the types used by the different interoperating programs; and 4) `automated assistance'', which eases the task of combining components into an interoperability, describe our current prototype realization of the of the specification level approach and our experience with its use, and outline our plans for extending both the approach and its realization.
design evaluation of the compiler generating system mugi. mug1 has been designed and implemented at the technical university of munich. its purpose is the generation of efficient one-pass compilers. the main goals of the design were to offer a readable and easily modifiable compiler description language, and to build an efficiently usable system. moreover the system was to detect certain classes of errors in the description, to allow for an exchange of alternative system modules such as parser generators, and to be portable. the paper discusses the most important design decisions in terms of their implications for attaining the design goals, and compares the resultant system with other compiler generating systems.
software process modeling: a behavioral approach. recently, the software engineering community has focused its attention on the process of software creation and evolution as well as the products of that process. much of this attention has concentrated on modeling the software process. software process models are seen as important vehicles for understanding and reasoning about software creation and evolution activities. software process models may also provide a basis for structuring automated software environments. despite this attention and the advantages to be gained through the use of software process models, however, no wholly satisfactory model of the software process has yet emerged. this paper presents an approach to software process modeling which is based on behavioral descriptions of software development activities. the use of behavioral descriptions makes it possible to describe the software process at any desired level of abstraction and, therefore, assists in accommodating aspects of the process which are poorly understood. this approach also provides the ability to reason about the software process and is sufficiently rigorous to provide a basis for structuring automated software environments. an overview of the model is presented, followed by a formal definition. examples are given to illustrate the application of the model to existing software processes and software methods. finally, the implications of the model for automated software environments are discussed.
das: an automated system to support design analysis. the das is an automated system that supports design verification with the goal of improved software quality and reduced life cycle costs. the integral use of a system engineering language for requirements and design specification, automatic simulation model generation, and user-oriented features are key to the comprehensive approach. this paper briefly describes das' components and its intended application.
computer aided design of software systems. this paper presents results of studies conducted at hughes aircraft company into automated aids for designing large software systems. in particular, we describe two automated tools that have been developed to establish the feasibility of aiding the construction, modification, and goodness testing of large structure charts of software modules. further, we present conclusions of studies which establish software system design engineering principles that are necessary for disciplined software development. we conclude by proposing a system which incorporates these engineering principles and the experience gained from using current automated tools into a forward thinking computer aided software design system.
an intensional approach to the specification of test cases for database applications. when testing database applications, in addition to creating in-memory fixtures it is also necessary to create an initial database state that is appropriate for each test case. current approaches either require exact database states to be specified in advance, or else generate a single initial state (under guidance from the user) that is intended to be suitable for execution of all test cases. the first method allows large test suites to be executed in batch, but requires considerable programmer effort to create the test cases (and to maintain them). the second method requires less programmer effort, but increases the likelihood that test cases will fail in non-fault situations, due to unexpected changes to the content of the database. in this paper, we propose a new approach in which the database states required for testing are specified intensionally, as constrained queries, that can be used to prepare the database for testing automatically. this technique overcomes the limitations of the other approaches, and does not appear to impose significant performance overheads.
a requirements and design aid for relational data bases. a tool is described for defining data processing system requirements and for automatically generating data base designs from the requirements. the generated designs are specific to system r but the mapping rules are valid for the relational model in general and can be adapted to other data models as well. the requirements and design are stored in a system r data base, are cross-referenced with each other, and can be accessed and used for other purposes. the requirements are defined in terms of an organized common-sense semantic model and serve the function of the conceptual schema in the ansi/sparc three schema framework. the tool generates (synthesizes) relational designs that have no redundancy, no update anomalies, and are in 5th normal form. the requirements analysis and design generation procedures are illustrated with a case study.
version control in families of large programs. programs products are quite often families of large and modular programs. modern programming languages support the formulation of such program families only partially. at the time being it is usually not possible to describe different revisions, variants, and versions of single program building blocks and whole programs. this paper presents a proposal for the formulation of such version information as part of the program text. in a newly introduced config part of a program building block the programmer can express: (1) to which versions the building block belongs, and (2) which versions of other building blocks it uses. in this new construct a version is defined as a pair (revision, variant), and a variant as a vector of attribute values. with these language constructs the &ldquo;knowledge&rdquo; about the program versions can be expressed by facts and rules. the representation of this knowledge is adapted to the structure of the program, and the generation of specific program versions can be done automatically. the configuration algorithm has been implemented in prolog, and this prototype implementation has been used for some examples.
defect content estimations from review data. reviews are essential for defect detection and they provide an opportunity to control the software development process. this paper focuses upon methods for estimating the defect content after a review and hence to provide support for process control. two new estimation methods are introduced as the assumptions of the existing statistical methods are not fulfilled. the new methods are compared with a maximum-likelihood approach. data from several reviews are used to evaluate the different methods. it is concluded that the new estimation methods provide new opportunities to estimate the defect content
generating wrappers for command line programs: the cal-aggie wrap-o-matic project. software developers writing new software have strong incentives to make their products compliant to standards such as corba, com, and java beans. standards-compliance facilitates inter-operability, component-based software assembly, and software reuse, thus leading to improved quality and productivity. legacy software, on the other hand, is usually monolithic, and hard to maintain and adapt. many organizations, saddled with entrenched legacy software, are confronted with the need to integrate legacy assets into more modern, distributed, componentized systems that provide critical business services. thus wrapping legacy systems for inter-operability has been an area of considerable interest. wrappers are usually constructed by hand which can be costly and error-prone. in this paper, we specifically target command-line oriented legacy systems and describe a tool framework that automates away some of the drudgery of constructing wrappers for these systems. we describe the cal-aggie wrap-o-matic system (cawom), and illustrate its use to create corba wrappers for a) the jdb debugger, thus supporting distributed debugging using other corba components, and b) the apache web-server, thus allowing remote web-server administration, potentially mediated by corba-compliant security services. while corba has some limitations, in several relatively common settings it can produce better wrappers at lower cost.
dado: enhancing middleware to support crosscutting features in distributed, heterogeneous systems. some "non-" or "extra-functional" features, such as reliability, security, and tracing, defy modularization mechanisms in programming languages. this makes such features hard to design, implement, and maintain. implementing such features within a single platform, using a single language, is hard enough. with distributed, heterogeneous (dh) systems, these features induce complex implementations which cross-cut different languages, oss, and hardware platforms, while still needing to share data and events. worse still, the precise requirements for such features are often locality-dependent and discovered late (e.g., security policies). the dado1 approach helps program cross-cutting features by improving dh middleware. a dado service comprises pairs of adaplets which are explicitly modeled in idl. adaplets may be implemented in any language compatible with the target application, and attached to stubs and skeletons of application objects in a variety of ways. dado supports flexible and type-checked interactions (using generated stubs and skeletons) between adaplets and between objects and adaplets. adaplets can be attached at run-time to an application object. we describe the approach and illustrate its use for several cross-cutting features, including performance monitoring, caching, and security. we also discuss software engineering process, as well as run-time performance implications.
design and implementation of distributed crosscutting features with dado. some "non-" or "extra-functional" features, such as reliability, security, and tracing, defy modularization mechanisms in programming languages. with distributed, heterogeneous (dh) systems, these features induce complex implementations which crosscut different languages, oss, and hardware platforms, while still needing to share data and events. the dado approach helps program crosscuting features by improving dh middleware. a dado service comprises pairs of adaplets which are explicitly modeled in idl. dado supports flexible and type-checked interactions (using generated stubs and skeletons) between adaplets and between objects and adaptlets. adaptlets can be attached at run-time to an application object.
glueqos: middleware to sweeten quality-of-service policy interactions. a holy grail of component-based software engineeringis "write-once, reuse everywhere". however, inmodern distributed, component-based systems supportingemerging application areas such as service-orientede-business (where web services are viewed as components)and peer-to-peer computing, this is difficult. non-functional requirements (related to quality-of-service (qos) issues such as security, reliability,and performance) vary with deployment context, andsometimes even at run-time, complicating the task ofre-using components. in this paper, we present amiddleware-based approach to managing dynamicallychanging qos requirements of components. policiesare used to advertise non-functional capabilities andvary at run-time with operating conditions. we alsoprovide middleware enhancements to match, interpret,and mediate qos requirements of clients and servers atdeployment time and/or runtime.
software improvements in an international company. the schlumberger laboratory for computer science (slcs) was formed in 1989 as a corporate-wide resource to enhance the quality and creativity of software products within schlumberger and to improve the productivity of software development. because of a wide range of needs, it was necessary to decide which techniques slcs's small software improvement team could use most effectively. the authors describe the choices made and the effectiveness of those choices in work with schlumberger's engineering organizations. through the motivation efforts of a small group, productive changes have occurred across the company. improvements were made in many development areas, including project planning and requirements management. the catalysts behind these advances included capability assessments, training, and collaboration
requirements interaction management in an extreme programming environment: a case study. this work reports experience applying the process of requirements interaction management (rim) within the context of developing a commercial, internet-based software application in an industrial venue, employing the extreme programming (xp) methodology. we describe our means of managing the interactions -- by extending the standard xp requirements process while maintaining consistency with the principles of xp itself. we outline our rationale for modifying the xp requirements process, and provide a temporal comparison showing that, for this project, modified process is essential to successful application of rim.
interface control and incremental development in the pic environment. the pic environment is designed to provide support for interface control that facilitates incremental development of a software system. interface control, the description and analysis of relationships among system components, is important from the earliest stages of the software development process right through to the implementation and maintenance stages. incremental development, wherein a software system is produced through a sequence of relatively small steps and progress may be rigorously and thoroughly assessed after each step, must be accommodated by any realistic model of the software development process. this paper focuses on the analysis component of the pic environment and demonstrates how it contributes to precise interface control capabilities while supporting an incremental software development process.
use of software inspection inputs in practice. the effects in the empirical study of different kinds of inputs on the software inspection process can be classified into explicit inputs and implicit inputs. explicit inputs are the software artifacts to be inspected, the documentation and inspection aids used by the inspectors. implicit inputs include inspectors' expertise, norms, beliefs and values.
second workshop on software quality. software products are a critical and strategic asset in anorganizations' business. they are becoming larger, moresophisticated and more complex. the challenge is to developmore complicated software products within the constraints oftime and resources without the sacrifice of quality. qualitystandards, methodologies and techniques have been continuallyproposed by researchers and used by software engineers in theindustry. the second workshop on software quality aims tobring together academic, industrial and commercial communitiesinterested in software quality topics to discuss the differenttechnologies being defined and used in the software quality area.
third workshop on software quality. to develop software on time and within budget is not good enough if the software produced is full of defects. as the software market matures, users want to be assured of quality. they no longer accept claims made by the it department at face value, but expect concrete demonstrations of quality. software stakeholders are also demanding higher quality software than ever before. in recent years, much software engineering research has focussed on standards, methodologies and techniques for improving software quality, measuring software quality and software quality assurance. most of this research is focused on an internal view of quality whereas few measures of the customer view of quality exist. the third workshop on software quality aims to bring together academic, industrial and commercial communities interested in software quality topics to discuss the different technologies being defined and used in the software quality area.
the effect of modularization and comments on program comprehension. an experiment was conducted to investigate how different types of modularization and comments are related to programmers' ability to understand programs. forty-eight experienced programmers were given eight different versions of the same program and asked to answer a twenty question quiz used to measure comprehension. these eight different versions were the result of the program being constructed with four types of modularization (monolithic, functional, super, and abstract data type), each with and without comments. those subjects whose programs contained comments were able to answer more questions than those without comments. also, those subjects who were given the abstract data type version of the program were able to do significantly better than those with any other type of modularization.
ou learningworks: a customized programming environment for smalltalk modules. we have exploited and adapted goldberg's learningworks framework to produce an environment with new programming tools, visualization tools, and system simulations. the environment is designed to be used via plug-in modules, called learningbooks, sets of classes and persistent objects, for which we have developed a pedagogic standard that includes, for example, an html browser and various of the aforementioned tools and systems. the context for this development has been a distance learning degree-level course in object technology which is enrolling over 5000 mature students per year, mostly in the uk, western europe and singapore. the course, m206, computing: an object-oriented approach from the open university (ou), will soon be introduced into the usa. while adhering to the original conception of learningworks that it promote a software engineering approach of systems building, we have successfully added support for the needs of the distance learning neophyte. by showing various microworlds and programming tools these notes outline the environment we have implemented and deployed.
exploiting smalltalk modules in a customizable programming environment. this paper describes how we extended a module structure of the smalltalk learningworks framework to provide a programming environment designed for very large scale technology transfer. the 'module' is what we have termed the learningbook, a set of classes and persistent objects, including an html browser, programming and visualization tools, and microworlds. the context for this development is a distance learning university course in object technology which is enrolling over 5000 mature students per year-making it the largest such course in the world. while promoting a systems building approach, we have successfully added support for programming in the small and the needs of the isolated novice. two guiding principles have been: (i) the environment and its modules fit into a consistent structure for personal management of learning and (ii) details of complex facilities, such as the class library, are progressively disclosed as knowledge and sophistication grow. the paper shows how these principles have guided the exploitation of learningbook modules. to provide context, relevant academic background is given. early informal feedback is reported and a project currently underway to observe in detail how thousands of learners use the programming environment is sketched.
the program understanding problem: analysis and a heuristic approach. program understanding is the process of making sense of a complex source code. this process has been considered as computationally difficult and conceptually complex. so far no formal complexity results have been presented, and conceptual models differ from one researcher to the next. we formally prove that program understanding is np hard. furthermore, we show that even a much simpler subproblem remains np hard. however we do not despair by this result, but rather offer an attractive problem solving model for the program understanding problem. our model is built on a framework for solving constraint satisfaction problems, or csps, which are known to have interesting heuristic solutions. specifically, we can represent and heuristically address previous and new heuristic approaches to the program understanding problem with both existing and specially designed constraint propagation and search algorithms.
performance-related completions for software specifications. to evaluate a software specification for its performance potential, it is necessary to supply additional information, not required for functional specification. examples range from the execution cost of operations and details of deployment, up to missing subsystems and layers. the term "completions" is used here to include all such additions, including annotations, component insertions, environment infrastructure, deployment, communication patterns, design refinements and scenario or design transformations which correspond to a given deployment style. completions are related to the purpose of evaluation, so they are tailored to describing the performance at a suitable level of detail. completions for evaluating other attributes such as reliability or security are also possible. the paper describes how completions are added to a specification regardless of the language used (provided that it describes the system behaviour as well as its structure), and experience with completions in use case maps.
an architectural style for high-performance asymmetrical parallel computations. researchers with deep knowledge of scientific domains are becoming more interested in developing highly-adaptive and irregular (asymmetrical) parallel computations, leading to development challenges for both delivery of data for computation and mapping of processes to physical resources. using software engineering principles, we have developed a new communications protocol and architectural style for asymmetrical parallel computations called adapt.utilizing the support of architecturally-aware middleware, we show that adapt provides a more efficient solution in terms of message passing and load balancing than asymmetrical parallel computations using collective calls in the message-passing interface (mpi) or more advanced frameworks implementing explicit load-balancing policies. additionally, developers using adapt gain significant windfall from good practices in software engineering, including implementation-level support of architectural artifacts and separation of computational loci from communication protocols.
early experiences with euclid. the programming language euclid was designed to be used for the construction of reliable and efficient systems software. this paper discusses the authors' experience in the design and implementation of the first large (about 60,000 source lines) piece of software written in euclid. the emphasis in this paper is on how the various language features in euclid affected the implementation of the software.
overseas development for a major u.s. ecommerce website. in this paper, we describe our experience in establishing a software development center in china with the purpose of supporting a major u.s. ecommerce website. we have established a set of development processes that fit our business needs to develop a large number of relatively small projects and release them in very short intervals. our processes allow us to accurately monitor the project status, schedule resources, predict the delivery and assess the productivity. we believe only with such systems in place that businesses can ensure successful overseas software operations.
automatic extraction of abstract-object-state machines from unit-test executions. an automatic test-generation tool can produce a large number of test inputs to exercise the class under test. however, without specifications, developers cannot inspect the execution of each automatically generated test input practically. to address the problem, we have developed an automatic test abstraction tool, called abstra, to extract high level object-state-transition information from unit-test executions, without requiring a priori specifications. given a class and a set of its generated test inputs, our tool extracts object state machines (osm): a state in an osm represents an object state of the class and a transition in an osm represents method calls of the class. when an object state in an osm is concrete (being represented by the values of all fields reachable from the object), the size of the osm could be too large to be useful for inspection. to address this issue, we have developed techniques in the tool to abstract object states based on returns of observer methods, branch coverage of methods, and individual object fields, respectively. the tool provides useful object-state-transition information for programmers to inspect unit-test executions effectively. in particular, the tool helps facilitate correctness inspection, program understanding, fault isolation, and test characterization.
3d visualization for concept location in source code. the paper presents a set of tools that work in conjunction to support concept location in software. one of the tools, iriss (information retrieval based software search), is a search engine, designed and implemented to allow searching the source code of a software system. the other tool, sv3d (source viewer 3d), is a visualization front end, designed to represent software data with 3d renderings.the two tools are integrated with ms visual studio, with iriss providing the infrastructure for indexing the source code and querying, while sv3d helps the user in visually navigating the results of the queries and keeps track of the navigation path.
design mentoring based on design evolution analysis. no abstract available
incremental consistency checking for pervasive context. applications in pervasive computing are typically required to interact seamlessly with their changing environments. to provide users with smart computational services, these applications must be aware of incessant context changes in their environments and adjust their behaviors accordingly. as these environments are highly dynamic and noisy, context changes thus acquired could be obsolete, corrupted or inaccurate. this gives rise to the problem of context inconsistency, which must be timely detected in order to prevent applications from behaving anomalously. in this paper, we propose a formal model of incremental consistency checking for pervasive contexts. based on this model, we further propose an efficient checking algorithm to detect inconsistent contexts. the performance of the algorithm and its advantages over conventional checking techniques are evaluated experimentally using cabot middleware.
software architecture classification for estimating the cost of cots integration. the use of commercial-off-the-shelf (cots) products creates a software integration problem, whether a single cots software component is being integrated into a software system, or the whole system is being built primarily from cots products. this integration may require considerable effort and affect system quality. a good estimate of integration cost can help in the decision of whether or not to use a cots solution, the selection of the best cots products, and determine the amount and type of glueware that needs to be built, in this paper, we introduce a set of variables that have the potential to estimate the integration cost. we present a classification scheme of software architectures with respect to the integration of cots products. the scheme is based on inter-component interactions within software architectures. the classification scheme allows the comparison of integration costs of different cots products relative to different software architectures.
the problem of knowledge decoupling in software development projects. in our ethnographic investigation of software integration projects a recurrent pattern emerges. the detailed understanding leaders have of the design and development decreases over time as they become busier and busier attending meetings, creating documents, and resolving issues and thus cannot spend much time on design or development work. as a result, their leadership becomes increasingly decoupled from the work of the project. we discuss various dimensions of this problem.
discotect: a system for discovering architectures from running systems. one of the challenging problems for software developersis guaranteeing that a system as built is consistentwith its architectural design. in this paper we describe atechnique that uses run time observations about an executingsystem to construct an architectural view of thesystem. with this technique we develop mappings thatexploit regularities in system implementation and architecturalstyle. these mappings describe how low-levelsystem events can be interpreted as more abstract architecturaloperations. we describe the current implementationof a tool that uses these mappings, and show that itcan highlight inconsistencies between implementationand architecture.
assessing cots integration risk using cost estimation inputs. most risk analysis tools and techniques require the user to enter a good deal of information before they can provide useful diagnoses. in this paper, we describe an approach to enable the user to obtain a cots glue code integration risk analysis with no inputs other than the set of glue code cost drivers the user submits to get a glue code integration effort estimate with the constructive cots integration cost estimation (cocots) tool. the risk assessment approach is built on a knowledge base with 24 risk identification rules and a 3-level risk probability weighting scheme obtained from an expert delphi analysis. each risk rule is defined as one critical combination of two cocots cost drivers that may cause certain undesired outcome if they are both rated at their worst case ratings. the 3-level nonlinear risk weighting scheme represents the relative probability of risk occurring with respect to the individual cost driver ratings from the input. further, to determine the relative risk impact, we use the productivity range of each cost driver in the risky combination to reflect the cost consequence of risk occurring. we also develop a prototype called cocots risk analyzer to automate our risk assessment method. the evaluation of our approach shows that it has done an effective job of estimating the relative risk levels of both small usc e-services and large industry cots-based applications.
perracotta: mining temporal api rules from imperfect traces. dynamic inference techniques have been demonstrated to provide useful support for various software engineering tasks including bug finding, test suite evaluation and improvement, and specification generation. to date, however, dynamic inference has only been used effectively on small programs under controlled conditions. in this paper, we identify reasons why scaling dynamic inference techniques has proven difficult, and introduce solutions that enable a dynamic inference technique to scale to large programs and work effectively with the imperfect traces typically available in industrial scenarios. we describe our approximate inference algorithm, present and evaluate heuristics for winnowing the large number of inferred properties to a manageable set of interesting properties, and report on experiments using inferred properties. we evaluate our techniques on jboss and the windows kernel. our tool is able to infer many of the properties checked by the static driver verifier and leads us to discover a previously unknown bug in windows.
development of software engineering: co-operative efforts from academia, government and industry. in the past 40 years, software engineering has emerged as an important sub-field of computer science. the quality and productivity of software have been improved and the cost and risk of software development been decreased due to the contributions made in this sub-field. the software engineering community needs to invest much more efforts to cope with the drastically increasing demands on the information technology as well as the extremely open and dynamic nature of the internet. the history of software engineering is reviewed with emphasis on the driving forces of software and the milestones of software engineering development. the history of software engineering in china is reviewed with emphasis on the relationship between software engineering and the software industry. based on the above reviews, we argue that software engineering should become an independent discipline along with computer science and co-operative efforts from academia, governments and industries should be needed for the harmonious development of software engineering. some results are presented based on china's experience of developing software engineering under this model.
software process description using lotos and its enaction. software processes can be treated as cooperative works among several engineers. in order to enact a software process in a distributed environment, the engineers must communicate with each other for exchanging data values and synchronization messages. such communications should be described in a process description for enacting the process automatically and clarifying the engineers' work. since these communications are numerous, it is troublesome for the process designers to describe them minutely in the process description. they also make the description unreadable. we propose a formal software process model where we describe only a whole description of a process in which we describe only the contents and temporal orders of primitive activities, and do not specify the communications. from the whole description, we derive each engineer's individual description, automatically where the contents and orders of his activities and communications to others are described. a whole process is enacted by executing all individual descriptions in parallel. both whole and individual descriptions are described in lotos/spd, an extension of the formal specification language lotos. we have also developed a support system for deriving the individual descriptions and executing them on unix machines
an approach to error-resistant software design. this paper presents a flexible framework, using a system monitor, to design error-resistant software. the system monitor contains the code and data for error detection, error containment and recovery at the module level, program level, and system level. it contains five types of components: the internal process supervisor, the external process supervisor, the interaction supervisor, the system monitor kernel, and the maintenance program. the functions of each component is discussed, followed by a discussion of the strategies to handle errors in the module, program, and system levels.
publishing and composition of atomicity-equivalent services for b2b collaboration. exception handling resolves inconsistency by backward or forward error recovery methods or both in business-to-business (b2b) process collaboration. to avoid committing irrevocable tasks followed by exceptions, b2b processes, which guarantee the atomicity sphere property, are attractive. while atomicity sphere ensures its outcomes to be either all or nothing, conflicting local recoveries may lead to global b2b inconsistencies. existing (global) analysis techniques however mandate every process unveiling all individual tasks. such an analysis is infeasible when some business parties refuse to disclose their process details for privacy or business reasons. to address this problem, we propose a process algebraic technique to prove, construct, and check atomicity-equivalent public views from b2b processes. by checking atomicity spheres in the composition of these public views, business parties can identify suitable services that respect their individual and overall atomicity requirements. an example based on a real-life multilateral supply chain process is included.
toward precise measurements using software normalization. there has been a lot of interest in defining appropriate ways of measuring the attributes of software. we think these measures should accurately represent those attributes which they quantify. however, these software measures are usually not precise enough because they measure elements that need not be included. reducing redundant structures of the program before they are measured is a simple yet important concept. we propose a strategy of software normalization for enhancing software measurement. most importantly, this program normalization allows those metrics to measure what is meant to be measured and avoid imprecise results.
two-way translators based on attribute grammar inversion. an attribute grammar is a non-procedural specification of a translation from one language to another. in this paper we consider restrictions on attribute grammars to make them invertible. given an attribute grammar defining a translation t: l1 &rarr; l2 obeying these restrictions, we show how to automatically synthesize the attribute grammar t-1: l2 &rarr; l1 describing the inverse translation; i.e., t &ogr; t-1 &ogr; t = t. this allows for the generation of bi-directional translators from a single description. we provide motivation and demonstrate the practical utility of these concepts by describing the inversion of an attribute grammar used as part of an interface for database users.
main effects screening: a distributed continuous quality assurance process for monitoring performance degradation in evolving software systems. developers of highly configurable performance-intensive software systems often use a type of in-house performance-oriented "regression testing" to ensure that their modifications have not adversely affected their software's performance across its large configuration space. unfortunately, time and resource constraints often limit developers to in-house testing of a small number of configurations and unreliable extrapolation from these results to the entire configuration space, which allows many performance bottlenecks and sources of qos degradation to escape detection until systems are fielded. to improve performance assessment of evolving systems across large configuration spaces, we have developed a distributed continuous quality assurance (dcqa) process called main effects screening that uses in-the-field resources to execute formally designed experiments to help reduce the configuration space, thereby allowing developers to perform more targeted in-house qa. we have evaluated this process via several feasibility studies on several large, widely-used performance-intensive software systems. our results indicate that main effects screening can detect key sources of performance degradation in large-scale systems with significantly less effort than conventional techniques.
java program analysis projects in osaka university: aspect-based slicing system adas and ranked-component search system spars-j. in our research demonstration, we show two development support systems for java programs. one is an aspect-oriented dynamic analysis and slice calculation system named adas, and another is a software product archiving, analyzing, and retrieving system for java named spars-j.
functional specification of synchronized processes based on modal logic. we present in this paper a pseudo functional language and a specification language both of which are designed to describe systems of synchronized processes with shared resources. the semantics of the pseudo functional language is defined by translating its statements to the set of formulas of intensional logic. the specification language contains formulas of the logic, hence its semantics can be treated by the model theory as usual. a proof method for the program written in the language is proposed. time dependent aspects of processes are described in terms of intensional logic. specification of parallel systems can be described in a well structured manner in our specification language, more precisely, they are described hierarchically according to the function decomposition of the system, and at each level of the hierarchy the configuration of processes and resources and time dependent properties are separately described. resources are defined as an abstract data type with synchronization specification. we give an example of specification and a proof of a program written in the parallel pseudo functional programming language.
open: a flexible oo/cbd process for software-intensive systems development, a uml exposition. object technology is an approach that is increasingly being adopted for the development of quality software and software-intensive systems. recent experience has demonstrated that it provides a sophisticated environment to support high quality software engineering practice. however, the use of object technology should not be restricted to languages but should encompass analysis, design, v&v and many such aspects belonging to the methodological dimension of the development life-cycle. furthermore, it should also cover other issues belonging to the technological and contextual aspects.
design principles behind chiron: a uims for software environments. user interface facilities are a crucial part of the infrastructure of a software environment. we discuss the particular demands and constraints on a user interface management system (uims) for a software environment, and the relation between the architecture of the environment and the uims. a model for designing user interface management systems for large, extensible environments is presented. this model synthesizes several recent advances in user interfaces and specializes them to the domain of software environments. the model can be applied to a wide variety of environment contexts. a prototype implementation is described.
an incremental flow- and context-sensitive pointer aliasing analysis. pointer aliasing analysis is used to determine if two object names containing dereferences and/or field selectors (e.g., *p,9->t) may refer to the same location during execution. such information is necessary for applications such as data-flow-based testers, program understanding tools, and debuggers, but is expensive to calculate with acceptable precision. incremental algorithms update data flow information after a program change rather than recomputing it from scratch, under the assumption that the change impact will be limited. two versions of a practical incremental pointer aliasing algorithm have been developed, based on landi-ryder flow- and context-sensitive alias analysis. empirical results attest to the time savings over exhaustive analysis (a six-fold speedup on average), and the precision of the approximate solution obtained (on average same solution as exhaustive algorithm for 75% of the tests.).
an analysis of the fault correction process in a large-scale sdl production model. improvements in the software development process depend on our ability to collect and analyze data drawn from various phases of the development life cycle. our design metrics research team was presented with a large-scale sdl production model plus the accompanying problem reports that began in the requirements phase of development. the goal of this research was to identify and measure the occurrences of faults and the efficiency of their removal by development phase in order to target software development process improvement strategies. the number and severity of problem reports were tracked by development phase and fault class. the efficiency of the fault removal process using a variety of detection methods was measured. through our analysis of the system data, the study confirms that catching faults in the phase of origin is an important goal. the faults that migrated to future phases are on average eight times more costly to repair. the study also confirms that upstream faults are the most critical faults and more importantly it identifies detailed design as the major contributor of faults, including critical faults.
on the success of empirical studies in the international conference on software engineering. critiques of the quantity and quality of empirical evaluations in software engineering have existed for quite some time. however such critiques are typically not empirically evaluated. this paper fills this gap by empirically analyzing papers published by icse, the prime research conference on software engineering. we present quantitative and qualitative results of a quasi-random experiment of empirical evaluations over the lifetime of the conference. our quantitative results show the quantity of empirical evaluation has increased over 29 icse proceedings but we still have room to improve the soundness of empirical evaluations in icse proceedings. our qualitative results point to specific areas of improvement in empirical evaluations.
executable requirements for embedded systems. an approach to requirements specification for embedded systems, based on constructing an executable model of the proposed system interacting with its environment, is proposed. the approach is explained, motivated, and related to data-oriented specification techniques. portions of a specification language embodying it are introduced, and illustrated with an extended example in which the requirements for a process-control system are developed incrementally.
using peer reviews in teaching framework development. framework development is one of the most challenging software development tasks. teaching framework development is even more challenging. in this paper, we propose a creative process to teach framework development. we propose using peer review in the process. we present the process and some examples and findings out of our experience.
perturbation testing for computation errors. the use of algebraic techniques in defining a neighborhood of functions is particularly suited to testing for computation errors. two possible approaches are howden's algebraic testing method and perturbation testing, which in this paper is generalized to permit analysis of individual test points rather than entire paths. these approaches are shown to be mathematically equivalent when applied to a program's black-box output. perturbation testing, however, offers more flexibility in the choice of potential errors to be investigated. a significant alternative offered by perturbation testing is the ability to work in the static domain, choosing test data to eliminate possible error terms in specific assignment and output statements.
interpretation in a tool-fragment environment. the philosophy of composition of new software tools from previously created tool fragments is a useful approach to facilitating the development of software systems. this paper examines the extension of this philosophy to the design of program interpreters, demonstrating how the separation of interpretation into a core algorithm, value kind definitions, and computation model allows the capture of conventional execution models, symbolic execution models, dynamic data flow tracking, and other useful forms of program interpretation. an interpretation system based upon this separation, called aries, is currently under development.
sufficient tset sets for path analysis testing strategies. many testing methods require the selection of a set of paths over which testing is to be conducted. this paper presents an analysis of the effectiveness of individual paths for testing predicates in linearly domained programs. a measure is derived for the marginal advantage of testing another path after several paths have already been tested. this measure is used to show that any predicate in such programs may be sufficiently tested using at most m+n+1 paths, where m is the number of input values and n is the number of program variables.
automatic program analysis and evaluation. there is currently considerable interest in the computing community in the evaluation of computer programming. however, in order to objectively evaluate such concepts, it is necessary to undertake a thorough evaluation of the programming process itself. most previous studies of this type have analyzed, by hand usually, a few instances of programs. this has led to some general conjectures; however, the amount of information that must be processed precludes any large scale analysis. in order to avoid this problem, an automatic data collection facility has been implemented as part of a pl/1 compiler at the university of maryland. this system automatically collects information on each program that has been compiled - at almost no additional cost to the user of the compiler. this paper will describe the system and will evaluate some of the characteristics of some of the 25,000 programs that have been run since july, 1975.
use of an environment classification model. various reference models have been proposed for the classification of features present in an integrated software engineering environment. two such models are studied and a target system is mapped to the set of services present in these models. this system consisted of approximately 23000 lines of pascal source code in 31 modules and provided tools for developing pascal programs using either a syntax-directed editor or a line-oriented editor. in addition to describing the system, this mapping exercise provided additional feedback on the effectiveness of the two reference models used. the results of this mapping and comments on the effectiveness of the models are given
understanding iv & v in a safety critical and complex evolutionary environment: the nasa space shuttle program. the national aeronautics and space administration is an internationally recognized leader in space science and exploration. nasa recognizes the inherent risk associated with space exploration; however, nasa makes every reasonable effort to minimize that risk. to that end for the space shuttle program nasa instituted a software independent verification and validation (iv&v) process in 1988 to ensure that the shuttle and its crew are not exposed to any unnecessary risks. using data provided by both the shuttle software developer and the iv&v contractor, in this paper we describe the overall iv&v process as used on the space shuttle program and provide an analysis of the use of metrics to document and control this process. our findings reaffirm the value of iv&v and show the impact iv&v has on multiple releases of a large complex software system.
model-based development of dynamically adaptive software. increasingly, software should dynamically adapt its behavior at run-time in response to changing conditions in the supporting computing and communication infrastructure, and in the surrounding physical environment. in order for an adaptive program to be trusted, it is important to have mechanisms to ensure that the program functions correctly during and after adaptations. adaptive programs are generally more difficult to specify, verify, and validate due to their high complexity. particularly, when involving multi-threaded adaptations, the program behavior is the result of the collaborative behavior of multiple threads and software components. this paper introduces an approach to create formal models for the behavior of adaptive programs. our approach separates the adaptation behavior and non-adaptive behavior specifications of adaptive programs, making the models easier to specify and more amenable to automated analysis and visual inspection. we introduce a process to construct adaptation models, automatically generate adaptive programs from the models, and verify and validate the models. we illustrate our approach through the development of an adaptive gsm-oriented audio streaming protocol for a mobile computing application.
locating faults through automated predicate switching. typically debugging begins when during a program execution a point is reached at which an obviously incorrect value is observed. a general and powerful approach to automated debugging can be based upon identifying modifications to the program state that will bring the execution to a successful conclusion. however, searching for arbitrary changes to the program state is difficult due to the extremely large search space. in this paper we demonstrate that by forcibly switching a predicate's outcome at runtime and altering the control flow, the program state can not only be inexpensively modified, but in addition it is often possible to bring the program execution to a successful completion (i.e., program produces the desired output). by examining the switched predicate, also called the critical predicate, the cause of the bug can then be identified. since the outcome of a branch can only be either true or false, the number of modified states resulting by predicate switching is far less than those possible through arbitrary state changes. thus, it is possible to automatically search through modified states to find one that leads to the correct output. we have developed an implementation based upon dynamic instrumentation to perform this search through program re-execution -- the program is executed from the beginning and a predicate's outcome is switched to produce the desired change in control flow. to evaluate our approach, we tried our technique on several reported bugs for a number of unix utility programs. our technique was found to be practical (i.e., acceptable in time taken) and effective (i.e., we were able to automatically identify critical predicates). moreover we show that bidirectional dynamic slices of critical predicates capture the faulty code.
precise dynamic slicing algorithms. dynamic slicing algorithms can greatly reduce the de bugging effort by focusing the attention of the user on a relevant subset of program statements. in this paper we present the design and evaluation of three precise dynamic slicing algorithms called the full preprocessing (fp), no preprocessing (np) and limited preprocessing (lp) algorithms. the algorithms differ in the relative timing of constructing the dynamic data dependence graph and its traversal for computing requested dynamic slices. our experiments show that the lp algorithm is a fast and practical precise slicing algorithm. in fact we show that while precise slices can be orders of magnitude smaller than imprecise dynamic slices, for small number of slicing requests, the lp algorithm is faster than an imprecise dynamic slicing algorithm proposed by agrawal and horgan.
efficient forward computation of dynamic slices using reduced ordered binary decision diagrams. dynamic slicing algorithms can greatly reduce the debuggingeffort by focusing the attention of the user on a relevantsubset of program statements. recently algorithms forforward computation of dynamic slices have beenproposed which maintain dynamic slices of all variables asthe program executes. an advantage of this approach is thatwhen a request for a slice is made, it is already available.the main disadvantage of using such an algorithm for slicingrealistic programs is that the space and time requiredto maintain a large set of dynamic slices corresponding toall program variables can be very high. in this paper weanalyze the characteristics of dynamic slices and identifyproperties that enable space efficient representation of a setof dynamic slices. we show that by using reduced orderedbinary decision diagrams (robdds) to represent a set ofdynamic slices, the space and time requirements of maintainingdynamic slices are greatly reduced. in fact not onlycan the latest dynamic slices of all variables be easilymaintained, but rather all dynamic slices of all variablesthroughout a programýs execution can be maintained. ourexperiments show that our robdd based algorithm for forwardcomputation of dynamic slices can maintain 107-217million dynamic slices arising during long program runs usingonly 28-392 megabytes of storage. in addition, the performanceof the robdd based forward computation methodcompares favorably with the performance of the lp backwardcomputation algorithm.
babel: representing business rules in xml for application integration. in this paper, we discuss babel, a prototype tool for integrating multiple heterogeneous applications, by wrapping them and by specifying the logic of their interoperation in xml.
a new approach for software testability analysis. software testability analysis has been an important research direction since 1990s and becomes more pervasive when entering 21st century. in this paper, we summarize problems in existing research work. we propose to use beta distribution to indicate software testability. when incorporating testing effectiveness information, we theoretically prove that the distribution can express testing effort and test value at the same time. we conduct experiment and validate our results on siemens programs. future work concentrate on deducing a prior estimation of the distribution for given software and testing criterion pair from program slicing and semantic analysis.
sniafl: towards a static non-interactive approach to feature location. to facilitate software maintenance and evolution, a helpfulstep is to locate features concerned in a particular maintenancetask. in the literature, both dynamic and interactive approacheshave been proposed for feature location. in this paper, wepresent a static and non-interactive method for achieving thisobjective. the main idea of our approach is to use theinformation retrieval (ir) technology to reveal the basicconnections between features and computational units in sourcecode. due to the characteristics of the retrieved connections, weuse a static representation of the source code named brcg tofurther recover both the relevant and the specific computationalunits for each feature. furthermore, we recover therelationships among the relevant units for each feature. apremise of our approach is that programmers should usemeaningful names as identifiers. we perform an experimentalstudy based on a gnu system to evaluate our approach. in theexperimental study, we present the detailed quantitativeexperimental data and give the qualitative analytical results.
applying regression test selection for cots-based applications. abb incorporates a variety of commercial-off-the-shelf (cots) components in its products. when new releases of these components are made available for integration and testing, source code is often not provided. various regression test selection processes have been developed and have been shown to be cost effectiveness. however, the majority of these test selection techniques rely on access to source code for change identification. in this paper we present the application of the lightweight integrated - black-box approach for component change identification (i-bacci) version 3 process that select regression tests for applications that use cots components. two case studies, examining a total of nine new component releases, were conducted at abb on products written in c/c++ to determine the effectiveness of i-bacci. the results of the case studies indicate this process can reduce the required number of regression tests at least 70% without sacrificing the regression fault exposure.
an experimental comparison of four test suite reduction techniques. as a test suite usually contains redundancy, a subset of the test suite (representative set) may still satisfy all the test objectives. as the redundancy increases the cost of executing the test suite, many test suite reduction techniques have been brought out in spite of the np-completeness of the general problem of finding the optimal representative set of the test suite. in the literature, some experimental studies of test suite reduction techniques have already been reported, but there are still shortcomings of the studies of these techniques. this paper presents an experimental comparison of the four typical test suite reduction techniques: heuristic h, heuristic gre, genetic algorithm-based approach and ilp-based approach. the aim of the study is to provide a guideline for choosing the appropriate test suite reduction techniques.
revisiting statechart synthesis with an algebraic approach. the idea of synthesizing statecharts out of a collection of scenarios has received a lot of attention in recent years. however due to the poor expressive power offirst generation scenario languages, including uml1.xsequence diagrams, the proposed solutions often use adhoc tricks and suffer from many shortcomings. the recent adoption in uml2.0 of a richer scenario language, including interesting composition operators, now makesit possible to revisit the problem of statechart synthesis with a radically new approach. inspired by the way uml2.0 sequence diagrams can be algebraically composed, we first define an algebraic framework for composing state charts. then we show how to leverage thealgebraic structure of uml2.0 sequence diagrams toget a direct algorithm for synthesizing a compositionof state charts out of them. the synthesized statechartsexhibit interesting properties that make them particularly useful as a basis for the detailed design process. beyond offering a systematic and semanticallywell founded method, another interest of our approachlies in its flexibility: the modification or replacement ofa given scenario has a limited impact on the synthesisprocess, thus fostering a better traceability between therequirements and the detailed design.
investigating the readability of state-based formal requirements specification languages. the readability of formal requirements specification languages is hypothesized as a limiting factor in the acceptance of formal methods by the industrial community. an empirical study was conducted to determine how various factors of state-based requirements specification language design affect readability using aerospace applications. six factors were tested in all, including the representation of the overall state machine structure, the expression of triggering conditions, the use of macros, the use of internal broadcast events, the use of hierarchies, and transition perspective (going-to or coming-from). subjects included computer scientists as well as aerospace engineers in an effort to determine whether background affects notational preferences. because so little previous experimentation on this topic exists on which to build hypotheses, the study was designed as a preliminary exploration of what factors are most important with respect to readability. it can serve as a starting point for more thorough and carefully controlled experimentation in specification language readability.
taking lessons from history. mining of software repositories has become an active research area. however, most past research considered any change to software as beneficial. this thesis will show how we can benefit from a classification into good and bad changes. the knowledge of bad changes will improve defect prediction and localization. furthermore, we will describe how to learn project-specific error patterns that will help reducing future errors.
mining version histories to guide software changes. we apply data mining to version histories in order toguide programmers along related changes: "programmerswho changed these functions also changed. . . ". given aset of existing changes, such rules (a) suggest and predictlikely further changes, (b) show up item coupling that is indetectableby program analysis, and (c) prevent errors dueto incomplete changes. after an initial change, our roseprototype can correctly predict 26% of further files to bechanged ¿ and 15% of the precise functions or variables.the topmost three suggestions contain a correct locationwith a likelihood of 64%.
an insider's survey on software development. this paper presents an overview of the results from &ldquo;an insider's survey on software development&rdquo;. the purpose of the survey was: to provide a vehicle for the communication of information on the usefulness and effectiveness of methodologies, tools, control mechanisms, metrics, and data collection used by bell telephone laboratories software developers; to evaluate the severity of certain obstacles to project development; and to ascertain feelings on the value of specific software quality issues. the results of the survey emphasize the need for work in the requirements area; the lack of attention given to the importance of maintenance within the software life cycle; and the need for more tools and methodologies, automated data collection, and effective software metrics.
a framework for automatic generation of evolvable e-commerce workplaces using business processes. business processes encapsulate the knowledge of operations and services provided by organizations. due to the changing nature of business processes, the design and implementation of e-commerce applications, such as workplace applications, could not be evolved consistently to support changing business requirements. e-commerce workplaces suffer from design and usability problems and may not conform to updated and constantly changing business processes. in this research demonstration, we present a framework that automatically generates business workplaces using workflow specifications. the generated workplaces can easily adapt to the changing business needs and reflect better the interaction within complex business processes in organizations.
research abstract: semantic concepts for the specification of non-functional properties of component-based software. in my research i try to de.ne a framework which can beused to provide semantics for non-functional specificationsof component-based systems. some of the key questionsdriving my work are:what is the fundamental difference between functionaland non-functional specifications? what formal apparatusis required to provide for this difference?what effects need to be taken into consideration whencomposing components with non-functional properties?what is the dependency between functional and nonfunctionalspecifications?what evaluation or analysis algorithms will be appliedto a non-functional specification? what informationmust be extractable from the semantics of a nonfunctionalspecification?
from use cases to code - rigorous software development with uml. the rational unified process lacks technical guidance for the development of object oriented applications. this tutorial fills this gap. we first use uml scenario diagrams to analyze use-cases. next, we show a method to analyze scenarios and to derive uml class diagrams and uml behavior modeling for active classes and methods. we show how to choose and embed design patterns in a design and how to employ different architectural styles. from such a precise design, smart case tools generate fully functional implementations. we explain state-of-the-art code generation concepts for uml and assess current case tools for their code generation capabilities and for their support through all software development phases more generally.
story driven modeling: a practical guide to model driven software development. the rational unified process lacks practical guidance for the development of object oriented applications. model driven software development (mdd) proposes to do most of these development steps at the model level of abstraction. this tutorial takes the mdd idea and examplifies such a development process. the tutorial guides the user from textual requirements descriptions through uml scenario modeling to the derivation of test case specifications, class diagrams and uml behavior models and finally to the implementation of the desired system. the tutorial employs a running example that allows to illustrate the modeling activities for each development phase and the guidelines for each modeling step. we discuss how existing case tools may be used in such an approach and how the fujaba environment supports our development process.
helping the automated validation process of user interfaces systems. this paper describes the prototype of a software environment that was devised for helping the formal validation of user interfaces systems. the paper suggests an approach to include such formal operations in the design process. an abstract and formal representation of the user interface system is produced to perform formal verifications on it. the paper explains why the user interface system can be modelled properly by a dataflow system and how this model can be expressed by using equations of flows in the language lustre. it describes then some main tools of the environment
crisp--a fault localization tool for java programs. crisp is an eclipse plug-in tool for constructing intermediate versions of a java program that is being edited. after a long editing session, a programmer will run regression tests to make sure she has not invalidated previously tested functionality. if a test fails unexpectedly, crisp allows the programmer to select parts of the edit that affected the failing test and to add them to the original program, creating an intermediate version guaranteed to compile. then the programmer can re-execute the test in order to locate the exact reasons for the failure by concentrating on those affecting changes that were applied. using crisp, a programmer can iteratively select, apply, and undo individual (or sets of) affecting changes and, thus effectively find a small set of failure-inducing changes. crisp is an extension to our change impact analysis tool, chianti, [6].
a sound assertion semantics for the dependable systems evolution verifying compiler. the verifying compiler (vc) project is a core component of the dependable systems evolution grand challenge. the vc offers the promise of automatically proving that a program or component is correct, where correctness is defined by program assertions. while several vc prototypes exist, all adopt a semantics for assertions that is unsound. this paper presents a consolidation of vc requirements analysis activities that, in particular, brought us to ask targeted vc customers what kind of semantics they wanted. taking into account both practitioners' needs and current technological factors, we offer recovery of soundness through an adjusted definition of assertion validity that matches user expectations and can be implemented practically using current prover technology. we describe how support for the new semantics has been added to esc/java2. preliminary results demonstrate the effectiveness of the new semantics at uncovering previously indiscernible specification errors.
spotlight: a prototype tool for software plans. software evolution is made difficult by the need to integrate new features with all previously implemented features in the system. we present spotlight, a prototype editor for software plans that seeks to address this problem by providing the programmer a principled way to separately develop and incrementally integrate independent features.
parallel randomized state-space search. model checkers search the space of possible program behaviors to detect errors and to demonstrate their absence. despite major advances in reduction and optimization techniques, state-space search can still become cost-prohibitive as program size and complexity increase. in this paper, we present a technique for dramatically improving the cost-effectiveness of state-space search techniques for error detection using parallelism. our approach can be composed with all of the reduction and optimization techniques we are aware of to amplify their benefits. it was developed based on insights gained from performing a large empirical study of the cost-effectiveness of randomization techniques in state-space analysis. we explain those insights and our technique, and then show through a focused empirical study that our technique speeds up analysis by factors ranging from 2 to over 1000 as compared to traditional modes of state-space search, and does so with relatively small numbers of parallel processors.
compatibility and regression testing of cots-component-based software. software engineers frequently update cots components integrated in component-based systems, and can often chose among many candidates produced by different vendors. this paper tackles both the problem of quickly identifying components that are syntactically compatible with the interface specifications, but badly integrate in target systems, and the problem of automatically generating regression test suites. the technique proposed in this paper to automatically generate compatibility and prioritized test suites is based on behavioral models that represent component interactions, and are automatically generated while executing the original test suites on previous versions of target systems.
bug hunt: making early software testing lessons engaging and affordable. software testing efforts account for a large part of software development costs. however, as educators, we struggle to properly prepare students to perform software testing activities. this struggle is caused by multiple factors: 1) it is challenging to effectively incorporate software testing into an already over-packed curriculum, 2) ad-hoc efforts to teach testing generally happen too late in the students' career, after bad habits have already been developed, and 3) these efforts lack the necessary institutional consistency and support to be effective. to address these challenges we created bug hunt, a web-based tutorial to engage students in learning software testing strategies. in this paper we describe the most interesting aspects of the tutorial including the lessons and feedback mechanisms, and the facilities for instructors to configure the tutorial and obtain automatic student assessment. we also present the lessons learned after two years of deployment.
refactoring for parameterizing java classes. type safety and expressiveness of many existing java libraries and their client applications would improve, if the libraries were upgraded to define generic classes. ef- ficient and accurate tools exist to assist client applications to use generic libraries, but so far the libraries themselves must be parameterized manually, which is a tedious, time-consuming, and error-prone task. we present a type-constraint- based algorithm for converting non-generic libraries to add type parameters. the algorithm handles the full java language and preserves backward compatibility, thus making it safe for existing clients. among other features, it is capable of inferring wildcard types and introducing type parameters for mutually-dependent classes. we have implemented the algorithm as a fully automatic refactoring in eclipse. we evaluated our work in two ways. first, our tool parameterized code that was lacking type parameters. we contacted the developers of several of these applications, and in all cases they confirmed that the resulting parameterizations were correct and useful. second, to better quantify its effectiveness, our tool parameterized classes from already-generic libraries, and we compared the results to those that were created by the libraries' authors. our tool performed the refactoring accurately.in 87% of cases the results were as good as those created manually by a human expert, in 9% of cases the tool results were better, and in 4% of cases the tool results were worse.
korat: a tool for generating structurally complex test inputs. this paper describes the korat tool for constraint-based generation of structurally complex test inputs for java programs. korat takes (1) an imperative predicate that speci fies the desired structural integrity constraints and (2) a finitization that bounds the desired test input size. korat generates all inputs (within the bounds) for which the predicate returns true. to do so, korat performs a systematic search of the predicate's input space. the inputs that korat generates enable bounded-exhaustive testing for programs ranging from library classes to stand-alone applications.
randomized differential testing as a prelude to formal verification. most flight software testing at the jet propulsion laboratory relies on the use of hand-produced test scenarios and is executed on systems as similar as possible to actual mission hardware. we report on a flight software development effort incorporating large-scale (biased) randomized testing on commodity desktop hardware. the results show that use of a reference implementation, hardware simulation with fault injection, a testable design, and test minimization enabled a high degree of automation in fault detection and correction. our experience will be of particular interest to developers working in domains where on-time delivery of software is critical (a strong argument for randomized automated testing) but not at the expense of correctness and reliability (a strong argument for model checking, theorem proving, and other heavyweight techniques). the effort spent in randomized testing can prepare the way for generating more complete confidence using heavyweight techniques.
adaptive online program analysis. analyzing a program run can provide important insights about its correctness. dynamic analysis of complex correctness properties, however, usually results in significant run-time overhead and, consequently, it is rarely used in practice. in this paper, we present an approach for exploiting properties of stateful program specifications to reduce the cost of their dynamic analysis. with our approach, analysis results are guaranteed to be identical to those of a traditional expensive dynamic analyses, while analysis cost is very low -- between 23% and 33% more than the un-instrumented program for the analyses we studied. we describe the principles behind our adaptive online program analysis technique, extensions to our java run-time analysis framework that support such analyses, and report on the performance and capabilities of two different families of adaptive online program analyses.
feedback-directed random test generation. we present a technique that improves random test generation by incorporating feedback obtained from executing test inputs as they are created. our technique builds inputs incrementally by randomly selecting a method call to apply and finding arguments from among previously-constructed inputs. as soon as an input is built, it is executed and checked against a set of contracts and filters. the result of the execution determines whether the input is redundant, illegal, contract-violating, or useful for generating more inputs. the technique outputs a test suite consisting of unit tests for the classes under test. passing tests can be used to ensure that code contracts are preserved across program changes; failing tests (that violate one or more contract) point to potential errors that should be corrected. our experimental results indicate that feedback-directed random test generation can outperform systematic and undirected random test generation, in terms of coverage and error detection. on four small but nontrivial data structures (used previously in the literature), our technique achieves higher or equal block and predicate coverage than model checking (with and without abstraction) and undirected random generation. on 14 large, widely-used libraries (comprising 780kloc), feedback-directed random test generation finds many previously-unknown errors, not found by either model checking or undirected random generation.
automatic inference of structural changes for matching across program versions. mapping code elements in one version of a program to corresponding code elements in another version is a fundamental building block for many software engineering tools. existing tools that match code elements or identify structural changes--refactorings and api changes--between two versions of a program have two limitations that we overcome. first, existing tools cannot easily disambiguate among many potential matches or refactoring candidates. second, it is difficult to use these tools' results for various software engineering tasks due to an unstructured representation of results. to overcome these limitations, our approach represents structural changes as a set of high-level change rules, automatically infers likely change rules and determines method-level matches based on the rules. by applying our tool to several open source projects, we show that our tool identifies matches that are difficult to find using other approaches and produces more concise results than other approaches. our representation can serve as a better basis for other software engineering tools.
presentations by programmers for programmers. common form of live technical presentation is that given by programmers for a programming audience during conferences, demonstrations, code reviews, and tutorials. such presentations require manual switching between general presentation software and the integrated development environment (ide), as well as reconfiguration of the ide's ui to be readable by an audience. in this paper, we present a novel system that allows programmers to easily combine traditional slideware with seamless transitions to user-specified regions of the ide along with special effects for live demonstration.
path-sensitive inference of function precedence protocols. function precedence protocols define ordering relations among function calls in a program. in some instances, precedence protocols are well-understood (e.g., a call to pthread mutex init must always be present on all program paths before a call to pthread mutex lock ). oftentimes, however, these protocols are neither well-documented, nor easily derived. as a result, protocol violations can lead to subtle errors that are difficult to identify and correct. in this paper, we present chronicler, a tool that applies scalable inter-procedural path-sensitive static analysis to automatically infer accurate function precedence protocols. chronicler computes precedence relations based on a program's control-flow structure, integrates these relations into a repository, and analyzes them using sequence mining techniques to generate a collection of feasible precedence protocols. deviations from these protocols found in the program are tagged as violations, and represent potential sources of bugs. we demonstrate chronicler's effectiveness by deriving protocols for a collection of benchmarks ranging in size from 66k to 2m lines of code. our results not only confirm the existence of bugs in these programs due to precedence protocol violations, but also highlight the importance of path sensitivity on accuracy and scalability.
reflections on software engineering education. in recent years, the software engineering community has focused on organizing its existing knowledge and finding opportunities to transform that knowledge into a university curriculum. swebok (the guide to the software engineering body of knowledge) and software engineering 2004 are two initiatives to that end. while these projects have increased se education's visibility, they've also focused largely on se's engineering aspects, at the expense of its human and social dimensions. this article describes how a pure engineering approach contributes to traps that se educators can fall into that in turn can mislead students as to se's true nature.
predicting faults from cached history. we analyze the version history of 7 software systems to predict the most fault prone entities and files. the basic assumption is that faults do not occur in isolation, but rather in bursts of several related faults. therefore, we cache locations that are likely to have faults: starting from the location of a known (fixed) fault, we cache the location itself, any locations changed together with the fault, recently added locations, and recently changed locations. by consulting the cache at the moment a fault is fixed, a developer can detect likely fault-prone locations. this is useful for prioritizing verification and validation resources on the most fault prone files or entities. in our evaluation of seven open source projects with more than 200,000 revisions, the cache selects 10% of the source code files; these files account for 73%-95% of faults--a significant advance beyond the state of the art
uml/analyzer: a tool for the instant consistency checking of uml models. large design models contain thousands of model elements. designers easily get overwhelmed maintaining the consistency of such design models over time. not only is it hard to detect new inconsistencies while the model changes but it also hard to keep track of known inconsistencies. the uml/analyzer tool identifies inconsistencies instantly with design changes and it keeps track of all inconsistencies over time. it does not require consistency rules with special annotations. instead, it treats consistency rules as black-box entities and observes their behavior during their evaluation. the uml/analyzer tool is integrated with the uml modeling tool ibm rational rose^tm for broad applicability and usability. it is highly scalable and was evaluated on dozens of design models.
mining security-sensitive operations in legacy code using concept analysis. his paper presents an approach to statically retrofit legacy servers with mechanisms for authorization policy enforcement. the approach is based upon the obser- vation that security-sensitive operations performed by a server are characterized by idiomatic resource manipula- tions, called fingerprints. candidate fingerprints are auto- matically mined by clustering resource manipulations using concept analysis. these fingerprints are then used to iden- tify security-sensitive operations performed by the server. case studies with three real-world servers show that the approach can be used to identify security-sensitive opera- tions with a few hours of manual effort and modest domain knowledge.
applying template meta-programming techniques for a domain-specific visual language--an industrial experience report. template meta-programming techniques can be used to increase efficiency in software development. these techniques have traditionally been used with textual programming languages, such as c++. in this paper, we discuss how corresponding techniques can be used with visual languages. the visual language under study in this paper is function block language (fbl). fbl is used in metso automation for writing automation control programs that are executed in real-time distributed environments. efficient development of high quality programs and easy customizability of existing programs are key requirements in practical customer projects. these requirements have been one of the main motivations to develop template meta-programming support in fbl discussed. in this paper, we focus both on the technical aspects and on the lessons learnt from programmers' experiences and ways to work with templates. fbl and the programming techniques proposed have been used in hundreds of real-world projects at metso automation.
goaldebug: a spreadsheet debugger for end users. we present a spreadsheet debugger targeted at end users. whenever the computed output of a cell is incorrect, the user can supply an expected value for a cell, which is employed by the system to generate a list of change suggestions for formulas that, when applied, would result in the user-specified output. the change suggestions are ranked using a set of heuristics. in previous work, we had presented the system as a proof of concept. in this paper, we describe a systematic evaluation of the effectiveness of inferred change suggestions and the employed ranking heuristics. based on the results of the evaluation we have extended both, the change inference process and the ranking of suggestions. an evaluation of the improved system shows that change inference process and the ranking heuristics have both been substantially improved and that the system performs effectively.
softguess: visualization and exploration of code clones in context. we introduce softguess, a code clone exploration system. softguess is built on the more general guess system which provides users with a mechanism to interactively explore graph structures both through direct manipulation as well as a domain-specific language. we demonstrate softguess through a number of mini-applications to analyze evolutionary code-clone behavior in software systems. the mini-applications of softguess represent a novel way of looking at code-clones in the context of many system features. it is our hope that softguess will form the basis for other analysis tools in the software-engineering domain.
automated inference of pointcuts in aspect-oriented refactoring. software refactoring is the process of reorganizing the internal structure of code while preserving the external behavior. aspect-oriented programming (aop) provides new modularization of software systems by encapsulating crosscutting concerns. based on these two techniques, aspect-oriented (ao) refactoring restructures crosscutting elements in code. ao refactoring includes two steps: aspect mining (identification of aspect candidates in code) and as- pect refactoring (semantic-preserving transformation to mi- grate the aspect-candidate code to ao code). aspect refac- toring clusters similar join points together for the aspect candidates and encapsulates each cluster with an effective pointcut definition. with the increase in size of the code and crosscutting concerns, it is tedious to manually identify aspects and their corresponding join points, cluster the join points, and infer pointcut expressions. therefore, there is a need to auto- mate the process of ao refactoring. this paper proposes an automated approach that identifies aspect candidates in code and infers pointcut expressions for these aspects. our approach mines for aspect candidates, identifies the join points for the aspect candidates, clusters the join points, and infers an effective pointcut expression for each clus- ter of join points. the approach also provides an addi- tional testing mechanismto ensure that the inferred pointcut expressions are of correct strength. the empirical results show that our approach helps achieve a significant reduc- tion in the total number of pointcut expressions to be used in the refactored code.
synthesis: a tool for automatically assembling correct and distributed component-based systems. synthesis is a tool for automatically assembling correct and distributed component-based systems. in our context, a system is correct when it is deadlock-free and performs only specified component interactions. in order to automatically synthesize the correct composition code, synthesis takes as input an high-level behavioural description for each component that must form the system to be built and a specification of the component interactions that must be enforced in the system. the automatically derived composition code is implemented as a set of distributed component wrappers that cooperatively interact with each other and with their wrapped components in order to prevent possible deadlocks and make the composed system exhibit only the specified interactions. the current version of synthesis supports two possible development platforms: microsoft com/dcom, and ejb (enterprise java beans).
the challenges of software engineering education. we discuss the technical skills that a software engineer should possess. we take the viewpoint of a school of engineering and put the software engineer's education in the wider context of engineering education. we stress both the common aspects that crosscut all engineering fields and the specific issues that pertain to software engineering. we believe that even in a continuously evolving field like software, education should emphasize principles and recognize what are the stable and long-lasting design concepts. even though the more mundane technological solutions cannot be ignored, the students should be equipped with skills that allow them to dominate the evolution of technology.
on accurate automatic verification of publish-subscribe architectures. the paper presents a novel approach based on bogor for the accurate verification of applications based on publish- subscribe infrastructures. previous efforts adopted standard model checking techniques to verify the application behavior, but they introduce strong simplifications on the underlying infrastructure to cope with the state space explosion problem and make automatic verification feasible. instead of building on top of existing model checkers, our proposal embeds the asynchronous communication mechanisms of publish-subscribe infrastructures within bogor. this way, publish-subscribe primitives become part of the specification language as additional, domain-specific, constructs. accurate models become feasible without incurring in state space explosion problems, thus enabling the automated verification of applications on top of realistic communication infrastructures.
enhancing software testing by judicious use of code coverage information. recently, tools for the analysis and visualization of code coverage have become widely available. at first glance, their value in assessing and improving the quality of automated test suites seems to be obvious. yet, experimental studies as well as experience from projects in industry indicate that their use is not without pitfalls. we found these tools in a number of recent projects quite beneficial. therefore, we set out to gather code coverage information from one of these projects. in this experience report, first the system under scrutiny as well as our methodology is described. then, four major questions concerning the impact and benefits of using these tools are discussed. furthermore, a list of ten lessons learned is derived. the list may help developers judiciously use code coverage tools, in order to reap a maximum of benefits.
model-based security engineering of distributed information systems using umlsec. given the explosive growth of digitally stored information in modern enterprises, distributed information systems together with search engines are increasingly used in companies. by enabling the user to search all relevant information sources with one single query, however, crucial risks concerning information security arise. in order to make these applications secure, it is not sufficient to penetrate-and- patch past system development, but security analysis has to be an integral part of the system design process for such distributed information systems. this work presents the experiences and results of the security analysis of a search engine in the intranet of a german car manufacturer, by making use of an approach to model-based security engineering that is based on the uml extension umlsec. the focus lies on the application's single-sign-on-mechanism, which was analyzed using the umlsec method and tools. main results of the paper include a field report on the employment of the umlsec method in an industrial context as well as indications on its benefits and limitations.
software engineering education in the era of outsourcing, distributed development, and open source software: challenges and opportunities. as software development becomes increasingly globally distributed, and more software functions are delegated to common open source software (oss) and commercial off-the-shelf (cots) components, practicing software engineers face significant challenges for which current software engineering curricula may leave them inadequately prepared. a new multi-faceted distributed development model is emerging that effectively commoditizes many development activities once considered integral to software engineering, while simultaneously requiring practitioners to apply engineering principles in new and often unfamiliar contexts. we discuss the challenges that software engineers face as a direct result of outsourcing and other distributed development approaches that are increasingly being utilized by industry, and some of the key ways we need to evolve software engineering curricula to address these challenges.
tool support for developing advanced mechatronic systems: integrating the fujaba real-time tool suite with camel-view. the next generation of advanced mechatronic systems is expected to use its software to exploit local and global networking capabilities to enhance their functionality and to adapt their local behavior when beneficial. such systems will therefore include complex hard real-time coordination at the network level. this coordination is further reflected locally by complex reconfiguration in form of mode management and control algorithms. we present in this paper the integration of two tools which allow the integrated specification of real-time coordination and traditional control engineering specifically targeting the required complex reconfiguration of the local behavior.
using experiments in software engineering as an auxiliary tool for teaching--a qualitative evaluation from the perspective of students' learning process. in this paper we discuss issues of using students as subjects from the perspective of their benefits in terms of learning. we conduct interviews with students who participated in the experiments and present their perceptions of the experiments in order to validate the claims posed in the existing literature. finally we show quantitative data on the rate of obtaining the distinctive pass grades for courses with and without experiments. the results show that integrating experiments with courses could lead to improvements of the performance of students on courses.
an empirical study of the evolution of an agile-developed software system. we have analyzed evolution patterns over two and a half years for a system developed using extreme programming. we find that the system shows a smooth pattern of growth overall, that (mccabe) code complexity is low, and that the relative amount of complexity control work (e.g. refactoring) is higher than in other systems we have studied. to interpret these results, we have drawn on qualitative data including the results of an observational study, records of progress and productivity, and comments on our findings from team members.
using gui run-time state as feedback to generate test cases. this paper presents a new automated model-driven technique to generate test cases by using feedback from the execution of a .seed test suite. on an application under test (aut). the test cases in the seed suite are designed to be generated automatically and executed very quickly. during their execution, feedback obtained from the aut's run-time state is used to generate new, .improved. test cases. the new test cases subsequently become part of the seed suite. this .anytime technique. continues iteratively, generating and executing additional test cases until resources are exhausted or testing goals have been met. the feedback-based technique is demonstrated for automated testing of graphical user interfaces (guis). an existing abstract model of the gui is used to automatically generate the seed test suite. it is executed; during its execution, state changes in the gui pinpoint important relationships between gui events, which evolve the model and help to generate new test cases. together with a reverse-engineering algorithm used to obtain the initial model and seed suite, the feedback-based technique yields a fully automatic, end-to-end gui testing process. a feasibility study on four large fielded open-source software (oss) applications demonstrates that this process is able to significantly improve existing techniques and help identify/report serious problems in the oss. in response, these problems have been fixed by the developers of the oss in subsequent versions.
the role of experience and ability in comprehension tasks supported by uml stereotypes. proponents of design notations tailored for specific application domains or reference architectures, often available in the form of uml stereotypes, motivate them by improved understandability and modifiability. however, empirical studies that tested such claims report contradictory results, where the most intuitive notations are not always the best performing ones. this indicates the possible existence of relevant influencing factors, other than the design notation itself. in this work we report the results of a family of three experiments performed at different locations and with different subjects, in which we assessed the effectiveness of uml stereotypes for web design in support to comprehension tasks. replications with different subjects allowed us to investigate whether subjects' ability and experience play any role in the comprehension of stereotyped diagrams. we observed different behaviors of users with different degrees of ability and experience, which suggests alternative comprehension strategies of (and tool support for) different categories of users.
usability implications of requiring parameters in objects' constructors. the usability of apis is increasingly important to programmer productivity. based on experience with usability studies of specific apis, techniques were explored for studying the usability of design choices common to many apis. a comparative study was performed to assess how professional programmers use apis with required parameters in objects' constructors as opposed to parameterless "default" constructors. it was hypothesized that required parameters would create more usable and self-documenting apis by guiding programmers toward the correct use of objects and preventing errors. however, in the study, it was found that, contrary to expectations, programmers strongly preferred and were more effective with apis that did not require constructor parameters. participants' behavior was analyzed using the cognitive dimensions framework, and revealing that required constructor parameters interfere with common learning strategies, causing undesirable premature commitment.
software development environments for scientific and engineering software: a series of case studies. the need for high performance computing applications for computational science and engineering projects is growing rapidly, yet there have been few detailed studies of the software engineering process used for these applications. the darpa high productivity computing systems program has sponsored a series of case studies of representative computational science and engineering projects to identify the steps involved in developing such applications (i.e. the life cycle, the workflows, technical challenges, and organizational challenges). secondary goals were to characterize tool usage and identify enhancements that would increase the programmers' productivity. finally, these studies were designed to develop a set of lessons learned that can be transferred to the general computational science and engineering community to improve the software engineering process used for their applications. nine lessons learned from five representative projects are presented, along with their software engineering implications, to provide insight into the software development environments in this domain.
good practices for educational software engineering projects. recent publications indicate the importance of software engineering in the computer science curriculum. in this paper, we present the final part of software engineering education at university of groningen in the netherlands and växjö university in sweden, where student teams perform an industrial software development project. it furthermore presents the main educational problems encountered in such real-life projects and explains how this international course addresses these problems. the main contribution of this paper is a set of seven good practices for project based software engineering education.
fixing inconsistencies in uml design models. changes are inevitable during software development and so are their unintentional side effects. the focus of this paper is on uml design models, where unintentional side effects lead to inconsistencies. we demonstrate that a tool can assist the designer in discovering unintentional side effects, locating choices for fixing inconsistencies, and then in changing the design model. our techniques are "on-line," applied as the designer works, and non-intrusive, without overwhelming the designer. this is a significant improvement over the state-of-the-art. our tool is fully integrated with the design tool ibm rational rose^tm. it was empirically evaluated on 48 case studies.
suade: topology-based searches for software investigation. the investigation of a software system prior to a modification task often constitutes an important fraction of the overall effort associated with the task. we present suade, an eclipse plug-in to automatically generate suggestions for software investigation. the goal of suade is to increase the efficiency with which developers explore the source code by recommending locations that are likely to be relevant to the task. based on a context of software elements (fields and methods) explicitly specified by a developer, suade automatically generates other elements that are likely to be relevant given the context, by analyzing the topology of structural dependencies in a software system.
a leveled examination of test-driven development acceptance. test-driven development (tdd) has garnered considerable attention in professional settings and has made some inroads into software engineering and computer science education. a series of leveled experiments were conducted with students in beginning undergraduate programming courses through upper-level undergraduate, graduate, and professional training courses. this paper reports that mature programmers who try tdd are more likely to choose tdd over a similar test-last approach. additionally this research reveals differences in programmer acceptance of tdd between beginning programmers who were reluctant to adopt tdd and more mature programmers who were more willing to adopt tdd. attention is given to confounding factors, and future studies aimed at resolving these factors are identified. finally proposals are made to improve early programmer acceptance of tdd.
can requirements be creative? experiences with an enhanced air space management system. requirements engineering is a creative process in which stakeholders work together to create ideas for new software systems that are eventually expressed as requirements. this paper reports a workshop that integrated creativity techniques with different types of use case and system context modeling to discover stakeholder requirements for easm, a future air space management software system to enable the more effective, longer-term planning of uk and european airspace use. the workshop was successful in that it provided a range of outputs that were later assessed for their novelty and usefulness in the final specification of the easm software. the paper describes the workshop structure, gives examples of outputs from it, and uses these results to answer 2 research questions about the utility of creativity techniques and workshops that had not been answered in previous research.
reconceptualizing a family of heterogeneous embedded systems via explicit architectural support. it has been widely advocated that software architecture provides an effective set of abstractions for engineering (families of) complex software systems. however, architectural concepts are seldom supported directly at the level of system implementation. in embedded environments in particular, developers are often forced to rely on low-level programming languages. while this is conducive to fine-grain control over the system, it does not lend itself to addressing larger issues such as ensuring architectural integrity or managing an application family. in this paper we describe our experience with fundamentally altering the manner in which a family of embedded applications is designed, analyzed, implemented, deployed, and evolved using explicit architectural constructs. we discuss our strategy, the challenges we faced in the course of our project, the lessons learned in the process, and several open issues that remain unresolved.
the social dynamics of pair programming. this paper presents data from a four month ethnographic study of professional pair programmers from two software development teams. contrary to the current conception of pair programmers, the pairs in this study did not hew to the separate roles of "driver" and "navigator". instead, the observed programmers moved together through different phases of the task, considering and discussing issues at the same strategic "range" or level of abstraction and in largely the same role. this form of interaction was reinforced by frequent switches in keyboard control during pairing and the use of dual keyboards. the distribution of expertise among the members of a pair had a strong influence on the tenor of pair programming interaction. keyboard control had a consistent secondary effect on decision-making within the pair. these findings have implications for software development managers and practitioners as well as for the design of software development tools.
a formal framework for automated round-trip software engineering in static aspect weaving and transformations. we present a formal framework for a recently introduced approach to automated round-trip software engineering (are) in source-level aspect weaving systems. along with the formalization we improve the original method and suggest a new concept of weaving transactions in aspect-oriented programming (aop). as the major contribution we formally show how, given a tree-shaped intermediate representation of a program and an ancillary transposition tree, manual edits in statically woven code can consistently be mapped back to their proper source of origin, which is either in the application core or in an element in the aspect space. the presented formalism is constructive. it frames aop by generalizing static aspect weaving to classical tree transformations.
a technique for enabling and supporting debugging of field failures. it is difficult to fully assess the quality of software inhouse, outside the actual time and context in which it will execute after deployment. as a result, it is common for software to manifest field failures, failures that occur on user machines due to untested behavior. field failures are typically difficult to recreate and investigate on developer platforms, and existing techniques based on crash reporting provide only limited support for this task. in this paper, we present a technique for recording, reproducing, and minimizing failing executions that enables and supports inhouse debugging of field failures. we also present a tool that implements our technique and an empirical study that evaluates the technique on a widely used e-mail client.
kato: a program slicing tool for declarative specifications. this paper presents kato, a tool that implements a novel class of optimizations that are inspired by program slicing for imperative languages but are applicable to analyzable declarative languages, such as alloy. kato implements a novel algorithm for slicing declarative models written in alloy and leverages its relational engine kodkod for analysis. given an alloy model, kato identifies a slice representing the model's core: a satisfying instance for the core can systematically be extended into a satisfying instance for the entire model, while unsatisfiability of the core implies unsatisfiability of the entire model. the experimental results show that for a variety of subject models kato's slicing algorithm enables an order of magnitude speed-up over alloy's default translation to sat.
mining object usage models. programs usually follow many implicit programming rules or patterns, violations of which frequently lead to failures. this thesis proposes a novel approach to statically mine object usage models representing such patterns for objects used in a program. additionally, we will describe how object usage models can be used to automatically detect defects, increase program understanding and support programmers by providing code templates. in preliminary experiments the proposed method detected two previously unknown bugs in open source software.
applying iso 9001: 2000, mps.br and cmmi to achieve software process maturity: bl informatica's pathway. customer satisfaction, quality improvement and rework reduction are known to be the most important benefits obtained through deployment of software process maturity models and standards within an organization. since 2003 bl informática has been motivated and has established and maintained its software processes based on international standards (like iso 9001:2000) and maturity models (like mps.br and cmmi). in spite of the lack of financial and human resources, the organization achieved satisfactory results. this paper describes bl infomática's software processes improvement plan, lessons learned, difficulties and benefits that where collected during the execution of the improvement plan. it also presents quantitative results that demonstrate the return on investment during these years.
agility and experimentation: practical techniques for resolving architectural tradeoffs. this paper outlines our experiences with making architectural tradeoffs between performance, availability, security, and usability, in light of stringent cost and time-to-market constraints, in an industrial web-conferencing system. we highlight the difficulties in anticipating future architectural requirements and tradeoffs and the value of using agility and experiments as a tool for mitigating architectural risks in situations when up front pen-and- paper analysis is simply impossible.
role migration and advancement processes in ossd projects: a comparative case study. socio-technical processes have come to the forefront of recent analysis of the open source software development (ossd) world. interest in making these processes explicit is mounting, from industry and the software process community, as well as among those who may become contributors to ossd organization. this paper serves to close this gap by providing an empirical analysis of the role migration and project career advancement process, and role-sets within, that we have observed through comparative case studies within three large ossd project organizations: mozilla.org, apache.org, and netbeans.org.
on the impact of a collaborative pedagogy on african american millennial students in software engineering. millennial students (those born after 1982), particularly african americans and women, have demonstrated a propensity toward collaborative activities. we conducted a collective case study at north carolina state university and north carolina a&t to ascertain the role of collaboration and social interaction in attracting and retaining students in information technology. responses from semi-structured interviews with 11 representative african american students in these classes were coded and analyzed. the responses from these minority students were used to evolve a social interaction model. the conjectures generated from the model suggest that pair programming and agile software methodologies effectively create a collaborative environment that is desirable to millennial students, male and female, and, with the new evidence, minority and majority. additionally, the african american millennial students enjoy learning from their peers and believe that a collaborative environment better prepares them for the "real world."
feature oriented model driven development: a case study for portlets. model driven development (mdd) is an emerging paradigm for software construction that uses models to specify programs, and model transformations to synthesize executables. feature oriented programming (fop) is a paradigm for software product lines where programs are synthesized by composing features. feature oriented model driven development (fomdd) is a blend of fop and mdd that shows how products in a software product line can be synthesized in an mdd way by composing features to create models, and then transforming these models into executables. we present a case study of fomdd on a product line of portlets, which are components of web portals. we reveal mathematical properties of portlet synthesis that helped us to validate the correctness of our abstractions, tools, and specifications, as well as optimize portlet synthesis.
supporting generic sketching-based input of diagrams in a domain-specific visual language meta-tool. software engineers often use hand-drawn diagrams as preliminary design artefacts and as annotations during reviews. we describe the addition of sketching support to a domain-specific visual language meta-tool enabling a wide range of diagram-based design tools to leverage this human-centric interaction support. our approach allows visual design tools generated from high-level specifications to incorporate a range of sketching-based functionality including both eager and lazy recognition, moving from sketch to formalized content and back, and using sketches for secondary annotation and collaborative design review. we illustrate the use of our sketching extension for an example domain-specific visual design tool and describe the architecture and implementation of the extension as a plug-in for our eclipse-based meta-tool.
company-wide implementation of metrics for early software fault detection. to shorten time-to-market and improve customer satisfaction, software development companies commonly want to use metrics for assessing and improving the performance of their development projects. this paper describes a measurement concept for assessing how good an organization is at finding faults when most cost-effective, i.e. in most cases early. the paper provides results and lessons learned from applying the measurement concept widely at a large software development company. a major finding was that on average, 64 percent of all faults found would have been more cost effective to find during unit tests. an in-depth study of a few projects at a development unit also demonstrated how to use the measurement concept for identifying which parts in the fault detection process that needs to be improved to become more efficient (e.g. reduce the amount of time spent on rework).
modeling product line architectures through change sets and relationships. the essence of any modeling approach for product line architectures lies in its ability to express variability. existing approaches do so by explicitly specifying variation points inside the architectural specification of the entire product line, usually with optional and alternative elements of some form. this, however, leads to a sizable mismatch between conceptual variability (i.e., the features through which architects logically view and interpret differences in product architectures) and actual variability (i.e., the modeling constructs through which the logical differences must be expressed). we contribute a new product line architecture modeling approach that unites the two. our approach uses change sets to group related architectural differences and relationships to govern which change set combinations are valid when composed into a particular product architecture. the result lifts modeling of variability out of modeling architectural structure, consolidates related variation points, and explicitly and separately manages their compatibilities.
bringing the systems analysis and design course into 21^st century: a case study in implementing modern software engineering principles. while today's it students may have a theoretical knowledge of all the phases in the systems development lifecycle, they often have little exposure to software development core practices. few are able to build a new system from scratch. this paper examines a pedagogical approach to modern software engineering based on "doing" systems development from day one. course materials were produced by agile methodology expert, alistair cockburn. early results from an implementation of the experimental approach to the systems analysis and design course are examined.
using soloman-felder learning style index to evaluate pedagogical resources for introductory programming classes. soloman-felder learning style index has been applied extensively in engineering education to ascertain the learning styles of students. this paper presents an approach showing how learning styles of students can be used to evaluate pedagogical resources. in specific, learning style can be used to help determine an appropriate textbook and an appropriate mixture of additional pedagogical devices such as virtual labs or "clickers'. an example from a first undergraduate programming course is used to illustrate the approach.
overview of the impact project. this session is intended to introduce the icse audience to the impact project, whose goals are to 1) study the impact that software engineering research has had upon software engineering practice, and 2) promulgate project findings to the community, and then broadly to industry, academe, and government. the project is being sponsored by acm sigsoft, and funded by a variety of international funding sources. the project has been in operation for over six years, and preliminary reports on the project were presented at icse 2001 and icse 2002. formal reports have begun to appear as articles in acm tosem. here at icse 2007 we will report on the project again in the form of a 3-session mini-track. this first session will (re)introduce the project, and outline the studies that have been completed, are underway, and are anticipated. it will also summarize some of the larger findings and understandings about research impact that have been gleaned so far from observation of the various studies. this session and the mini-track are aimed at informing the community, and also at engaging it in both the studies themselves, and the discussions of the findings. thus, this session will conclude with ample time for discussion.
sequential circuits for relational analysis. the alloy tool-set has been gaining popularity as an alternative to traditional manual testing and checking for design correctness. alloy uses a first-order relational logic for modeling designs. the alloy analyzer translates alloy formulas for a given scope, i.e., a bound on the universe of discourse, to boolean formulas in conjunctive normal form (cnf), which are subsequently checked using propositional satisfiability solvers. we present sera, a novel algorithm that compiles a relational logic formula for a given scope to a sequential circuit. there are two key advantages of sequential circuits: they form a more succinct representation than cnf formulas, sometimes by several orders ofmagnitude. also sequential circuits are amenable to a range of powerful automatic analysis techniques that have no counterparts for cnf formulas. our experiments show that sera, used in conjunction with a sequential circuit analyzer, can check formulas for scopes that are an order of magnitude higher than those feasible with the alloy analyzer.
using server pages to unify clones in web applications: a trade-off analysis. server page technique is commonly used for implementing web application user interfaces. server pages can represent many similar web pages in a generic form. yet our previous study revealed high rates of repetitions in web applications, particularly in the user interfaces. code duplication, commonly known as "cloning', signals untapped opportunities to achieve simpler, smaller, more generic, and more maintainable web applications. using php server page technique, we conducted a case study to explore how far server page technique can be pushed to achieve clone-free web applications. our study suggests that clone unification using server pages affects system qualities (e.g., runtime performance) to an extent that may not be acceptable in many project situations. our paper discusses the trade-offs we observed when applying server pages to unify clones in web applications. we expect our findings to help in developing and validating complementary techniques that can unify clones without incurring such trade-offs.
'good' organisational reasons for 'bad' software testing: an ethnographic study of testing in a small software company. in this paper we report on an ethnographic study of a small software house to discuss the practical work of software testing. through use of two rich descriptions, we discuss that "rigour' in systems integration testing necessarily has to be organisationally defined. getting requirements "right', defining "good' test scenarios and ensuring "proper' test coverage are activities that need to be pragmatically achieved taking account of organisational realities and constraints such as: the dynamics of customer relationships; using limited effort in an effective way; timing software releases; and creating a market. we discuss how these organisational realities shape (1) requirements testing; (2) test coverage; (3) test automation; and (4) test scenario design.
supporting heterogeneous architecture descriptions in an extensible toolset. many architecture description languages (adls) have been proposed to model, analyze, configure, and deploy complex software systems. to face this diversity, extensible adls (or adl interchange formats) have been proposed. these adls provide linguistic support for integrating various architectural aspects within the same description. nevertheless, they do not support extensibility at the tool level, i.e. they do not provide an extensible toolset for processing adl descriptions. in this paper, we present an extensible toolset for easing the development of architecture-based software systems. this toolset is not bound to a specific adl, but rather uses a grammar description mechanism to accept various input languages, e.g. adls, interface definition languages (idls), domain specific languages (dsls). moreover, it can easily be extended to implement many different features, such as behavioral analysis, code generation, deployment, etc. its extensibility is obtained by designing its core functionalities using fine-grained components that implement flexible design patterns. experiments are presented to illustrate both the functionalities implemented by the toolset and the way it can be extended.
matching and merging of statecharts specifications. model management addresses the problem of managing an evolving collection of models, by capturing the relationships between models and providing well-defined operators to manipulate them. in this paper, we describe two such operators for manipulating hierarchical statecharts: match, for finding correspondences between models, and merge, for combining models with respect to known correspondences between them. our match operator is heuristic, making use of both static and behavioural properties of the models to improve the accuracy of matching. our merge operator preserves the hierarchical structure of the input models, and handles differences in behaviour through parameterization. in this way, we automatically construct merges that preserve the semantics of statecharts models. we illustrate and evaluate our work by applying our operators to at&t telecommunication features.
revel8or: model driven capacity planning tool suite. designing complex multi-tier applications that must meet strict performance requirements is a challenging software engineering problem. ideally, the application architect could derive accurate performance predictions early in the project life-cycle, leveraging initial application design-level models and a description of the target software and hardware platforms. to this end, we have developed a capacity planning tool suite for component-based applications, called revel8tor. the tool adheres to the model driven development paradigm and supports benchmarking and performance prediction for j2ee, .net and web services platforms. the suite is composed of three different tools: mdaperf, mdabench and dslbench. mdaperf allows annotation of design diagrams and derives performance analysis models. mdabench allows a customized benchmark application to be modeled in the uml 2.0 testing profile and automatically generates a deployable application, with measurement automatically conducted. dslbench allows the same benchmark modeling and generation to be conducted using a simple performance engineering domain specific language (dsl) in microsoft visual studio. dslbench integrates with visual studio and reuses its load testing infrastructure. together, the tool suite can assist capacity planning across platforms in an automated fashion.
refactoring-aware configuration management for object-oriented programs. current text based software configuration management (scm) systems have trouble with refactorings. refactorings result in global changes and lead to merge conflicts. a refactoring-aware scm system reduces merge conflicts, preserves program history better and makes it easier to understand program evolution. this paper describes molhadoref, a refactoring-aware scm system and the merge algorithm at its core. molhadoref records change operations (refactorings and edits) used to produce one version, and replays them when merging versions. since refactorings are change operations with well defined semantics, molhadoref treats them intelligently. a case-study shows that molhadoref solves automatically more merge conflicts than cvs while resulting in fewer merge errors.
when role models have flaws: static validation of enterprise security policies. modern multiuser software systems have adopted role- based access control (rbac) for authorization management. this paper presents a formal model for rbac policy validation and a static-analysis model for rbac systems that can be used to (i) identify the roles required by users to execute an enterprise application, (ii) detect potential inconsistencies caused by principal-delegation policies, which are used to override a user's role assignment, (iii) report if the roles assigned to a user by a given policy are redundant or insufficient, and (iv) report vulnerabilities that can result from unchecked intra-component accesses. the algorithms described in this paper have been implemented as part of ibm's enterprise security policy evaluator (espe) tool. experimental results show that the tool found numerous policy flaws, including ten previously unknown flaws from two production-level applications, with no false-positive reports.
tracking code clones in evolving software. code clones are generally considered harmful in software development, and the predominant approach is to try to eliminate them through refactoring. however, recent research has provided evidence that it may not always be practical, feasible, or cost-effective to eliminate certain clone groups. we propose a technique for tracking clones in evolving software. our technique relies on the concept of abstract clone region descriptors (crd), which describe clone regions within methods in a robust way that is independent from the exact text of the clone region or its location in a file. we present our definition of crds, and describe a complete clone tracking system capable of producing crds from the output of a clone detection tool, notify developers of modifications to clone regions, and support the simultaneous editing of clone regions. we report on two experiments and a case study conducted to assess the performance and usefulness of our approach
introducing accessibility requirements through external stakeholder utilization in an undergraduate requirements engineering course. undergraduate software engineering courses aim to prepare students to deliver software in a variety of domains. the manner in which these courses are conducted varies, though team projects with real or imaginary stakeholders are common. while the key course concepts vary from the entire lifecycle to specific aspects of design, concepts like accessibility are rare. this paper will present a study of team projects in a requirements engineering course. one group of students conducted projects with accessibility requirements while another group of students delivered projects without accessibility requirements. the course content was the same, including discussion of accessibility. to support the understanding of accessibility, stakeholders with disabilities were included in the requirements engineering process. both teams benefited from the experience as indirect knowledge acquisition occurred. students from a previous offering of the course, with no external stakeholder interaction, demonstrated lower levels of accessibility understanding.
top se: educating superarchitects who can apply software engineering tools to practical development in japan. this paper discusses the top se program established to bridge the industry-academia gap. the program features extensive use of software engineering tools, not only to introduce students to the tools, but also as a conduit for learning the techniques and guidelines needed to apply the tools to practical software development situations. the curriculum is organized around practical problems mainly from the area of digital home appliances and focuses on upper stream software development processes. the top se program is developed and operated by a close collaboration between industry and academia. we illustrate our discussion with examples from one of the courses, verification of design models, which takes up model checking technologies, including three specific tools: spin, smv, and ltsa.
soquet: query-based documentation of crosscutting concerns. understanding crosscutting concerns is difficult because their underlying relations remain hidden in a class-based decomposition of a system. based on an extensive investigation of crosscutting concerns in existing systems and literature, we identified a number of typical implementation idioms and relations that allow us to group such concerns around socalled .sorts.. in this paper, we present soquet, a tool that uses sorts to support the consistent description and documentation of crosscutting relations using pre-defined, sort-specific query templates.
information hiding and visibility in interface specifications. information hiding controls which parts of a class are visible to non-privileged and privileged clients (e.g., subclasses). this affects detailed design specifications in two ways. first, specifications should not expose hidden class members. as noted in previous work, this is important because such hidden members are not meaningful to all clients. but it also allows changes to hidden implementation details without invalidating correctness proofs for client code, which is important for maintaining verified programs. second, to enable sound modular reasoning, certain specifications must be visible to clients. we present rules for information hiding in specifications for java-like languages, and demonstrate their application to the specification language jml. these rules restrict proof obligations to only mention visible class members, but retain soundness. this allows maintenance of implementations and their specifications without affecting client reasoning.
precise memory leak detection for java software using container profiling. a memory leak in a java program occurs when object references that are no longer needed are unnecessarily maintained. such leaks are difficult to understand because static analyses typically cannot precisely identify these redundant references, and existing dynamic analyses for leak detection track and report fine-grained information about individual objects, producing results that are usually hard to interpret and lack precision. we introduce a novel container-based heap-tracking technique, based on the observation that many memory leaks in java programs occur due to containers that keep references to unused data entries. the novelty of the described work is two-fold: (1) instead of tracking arbitrary objects and finding leaks by analyzing references to unused objects, the technique tracks only containers and directly identifies the source of the leak, and (2) the approach computes a confidence value for each container based on a combination of its memory consumption and its elements' staleness (time since last retrieval), while previous approaches do not consider such combined metrics. our experimental results show that the reports generated by the proposed technique can be very precise: for two bugs reported by sun and for a known bug in specjbb, the top containers in the reports include the containers that leak memory.
behaviour model synthesis from properties and scenarios. synthesis of behaviour models from software development artifacts such as scenario-based descriptions or requirements specifications not only helps significantly reduce the effort of model construction, but also provides a bridge between approaches geared toward requirements analysis and those geared towards reasoning about system design at the architectural level. however, the models favoured by existing synthesis approaches are not sufficiently expressive to describe both universal constraints provided by requirements and existential statements provided by scenarios. in this paper, we propose a novel synthesis technique that constructs behaviour models in the form of modal transition systems (mts) from a combination of safety properties and scenarios. mtss distinguish required, possible and proscribed behaviour, and their elaboration not only guarantees the preservation of the properties and scenarios used for synthesis but also supports further elicitation of new requirements.
a constructivist approach to teaching software processes. recreating the context in which software processes are developed is difficult in the undergraduate classroom environment. as a result, traditional lecture-based teaching approaches do not necessarily translate into long-term understanding of software processes. to give students a deeper appreciation for the strengths and weaknesses of software process models, we designed the software process simulation game using constructivism as the underlying foundation. in this paper, we discuss the challenges associated with teaching software processes models, provide an overview of the game, detail its mechanics, and discuss the lessons learned from playing the game. since the game does not involve actual programming or design activities, it can be used effectively for teaching both novice and experienced software engineers.
overview and evaluation of constraint validation approaches in java. integrity is a dependability attribute partially ensured through runtime validation of integrity constraints. a wide range of different constraint validation approaches exists--ranging from simple if conditions over explicit constraint validation methods and contract specifications to constraints as first class runtime entities of an application. however, increased support for explicitness and flexibility often comes at the price of increased performance costs. to address this issue, we contribute with an overview and evaluation of different constraint validation approaches for the java programming language with respect to implementation, maintainability and performance. our results show that the benefits of some of the more advanced approaches are certainly worth their costs by introducing a runtime overhead of only two to ten times the runtime of the fastest approach while other approaches introduce runtime overheads of more than 100, which might be simply too slow in certain applications.
ajaxifying classic web applications. recently, a new web development technique for creating interactive web applications, dubbed ajax, has emerged in response to the limited degree of interactivity in large-grain stateless web interactions. in this new model, the web interface is composed of individual components which can be updated/replaced independently, and the client/server communication is based on a delta-communication style of interaction. with the rise of ajax web applications classical multi-page web applications are becoming legacy systems. this research seeks to explore how software engineering techniques can assist in comprehending, analyzing, and restructuring classic web applications towards ajax.
ownership and immutability inference for uml-based object access control. we propose a mechanism for object access control which is based on the uml. specifically, we propose use of ownership and immutability constraints on uml associations and verification of these constraints through reverse engineering. these constraints inherently support software design principles, and impose requirements on the implementation that may help prevent serious program flaws. we propose implementation-level models for ownership and immutability that capture well the meaning of these concepts in design, and we develop novel static ownership and immutability inference analyses. we perform an empirical investigation on several small-to-large java programs. the results indicate that the inference analyses are precise and practical. therefore, the analyses can be integrated in reverse engineering tools and can help support effective reasoning about software quality and security.
the factory pattern in api design: a usability evaluation. the usability of software apis is an important and infrequently researched topic. a user study comparing the usability of the factory pattern and constructors in api designs found highly significant results indicating that factories are detrimental to api usability in several varied situations. the results showed that users require significantly more time (p = 0.005) to construct an object with a factory than with a constructor while performing both context-sensitive and context-free tasks. these results suggest that the use of factories can and should be avoided in many cases where other techniques, such as constructors or class clusters, can be used instead.
performance evaluation and prediction for legacy information systems. database-centric information systems are critical to the operations of large organisations. in particular, they often process a large amount of data with stringent performance requirements. currently, however, there is a lack of systematic approaches to evaluating and predicting their performance when they are subject to an exorbitant growth of workload. in this paper, we introduce such a systematic approach that combines benchmarking, production system monitoring, and performance modelling (bmm) to address this issue. the approach helps the performance analyst to understand the system's operating environment and quantify its performance characteristics under varying load conditions via monitoring and benchmarking. based on such realistic measurements, modelling techniques are used to predict the system performance. our experience of applying bmm to a real-world system demonstrates the capability of bmm in predicting the performance of existing and enhanced software architectures in planning for its capacity growth.
the impact of research on middleware technology. various commercial trends have led to an increasing demand for distributed systems. distributed systems can integrate legacy components, thus preserving investment, they can decrease the time to market, they can be scalable and tolerant against failures. the caveat, however, is that the construction of a truly distributed systems is considerably more difficult than building a centralized or client/server system. this is because there are multiple points of failure in a distributed system, system components need to communicate with each other through a network, which complicates communication and opens the door for security attacks. middleware has been devised in order to conceal these difficulties from application engineers as much as possible; middleware is commonly defined as a software layer between applications and operating systems that provides application programmers with higher level of abstractions, such as remote procedure invocation, reliable message exchange or transactions. these abstractions considerably simplify distributed system construction and as a result middleware products are rapidly being adopted in industry and middleware is generally perceived as a success technology.
maturity status within front-end support organisations. it may not be enough to develop mature processes at the back-end support level. other strongly collaborating front-end support processes may substantially undermine them. for this reason, we have created cm3: front-end problem management - a detailed problem management process model to be utilised at the front-end support level. in this paper, we present the cm3 maturity levels at the front-end support and match them against the industrial state of practice within 15 software organisations. our goal is to establish the current status of support maturity using cm3: front-end problem management. our results show that the industrial processes studied suffice to provide basic problem management support at the front-end support level. however, only two out of 15 organisations studied have almost achieved the highest maturity level.
creating a computer security curriculum in a software engineering program. this paper discusses our experiences developing and delivering a computer security curriculum in a graduate software engineering program. it describes our program and student backgrounds, our approach to teaching computer security aimed towards a software engineering audience with disparate backgrounds, other challenges and solutions, course contents with emphasis on our core course, and additional venues and future plans.
automated generation of context-aware tests. the incorporation of context-awareness capabilities into pervasive applications allows them to leverage contextual information to provide additional services while maintaining an acceptable quality of service. these added capabilities, however, introduce a distinct input space that can affect the behavior of these applications at any point during their execution, making their validation quite challenging. in this paper, we introduce an approach to improve the test suite of a context-aware application by identifying context-aware program points where context changes may affect the application's behavior, and by systematically manipulating the context data fed into the application to increase its exposure to potentially valuable context variations. preliminary results indicate that the approach is more powerful than existing testing approaches used on this type of application.
opium: optimal package install/uninstall manager. linux distributions often include package management tools such as apt-get in debian or yum in redhat. using information about package dependencies and conflicts, such tools can determine how to install a new package (and its dependencies) on a system of already installed packages. using off-the-shelf sat solvers, pseudo-boolean solvers, and integer linear programming solvers, we have developed a new package-management tool, called opium, that improves on current tools in two ways: (1) opium is complete, in that if there is a solution, opium is guaranteed to find it, and (2) opium can optimize a user-provided objective function, which could for example state that smaller packages should be preferred over larger ones. we performed a comparative study of our tool against debian's apt-get on 600 traces of real-world package installations. we show that opium runs fast enough to be usable, and that its completeness and optimality guarantees provide concrete benefits to end users.
dynamic round-trip gui maintenance. one difficulty in software maintenance is that the relationship between observed program behavior and source code is not always clear. this is true for the maintenance of graphical user interfaces (guis), because user interface code can be scattered across the decomposition of applications. a popular approach to develop and maintain guis is to use "what you see is what you get" editors. they allow developers to work directly with a graphical design view instead of scattered source elements. unfortunately gui editors are limited by their ability to statically reconstruct dynamic collaborations between objects. in our research we investigate the combination of a hybrid dynamic and static approach to allow for round-trip maintenance of guis. dynamic analysis reconstructs object relationships, providing a concrete context in which maintenance can be performed. static checking guides the reconciliation between the gui editors' design view and source. we implemented a prototype ide plugin and evaluate our approach by applying it to five open source projects.
polus: a powerful live updating system. this paper presents polus, a software maintenance tool capable of iteratively evolving running software into newer versions. polus's primary goal is to increase the dependability of contemporary server software, which is frequently disrupted either by external attacks or by scheduled upgrades. to render polus both practical and powerful, we design and implement polus aiming to retain backward binary compatibility, support for multithreaded software and recover already tainted state of running software, yet with good usability and very low runtime overhead. to demonstrate the applicability of polus, we report our experience in using polus to dynamically update three prevalent server applications: vsftpd, sshd and apache http server. performance measurements show that polus incurs negligible runtime overhead: a less than 1% performance degradation (but 5% for one case). the time to apply an update is also minimal.
deckard: scalable and accurate tree-based detection of code clones. detecting code clones has many software engineering applications. existing approaches either do not scale to large code bases or are not robust against minor code modifications. in this paper, we present an efficient algorithm for identifying similar subtrees and apply it to tree representations of source code. our algorithm is based on a novel characterization of subtrees with numerical vectors in the euclidean space \mathbb{r}^n and an efficient algorithm to cluster these vectors w.r.t. the euclidean distance metric. subtrees with vectors in one cluster are considered similar. we have implemented our tree similarity algorithm as a clone detection tool called deckard and evaluated it on large code bases written in c and java including the linux kernel and jdk. our experiments show that deckard is both scalable and accurate. it is also language independent, applicable to any language with a formally specified grammar.
information needs in collocated software development teams. previous research has documented the fragmented nature of software development work. to explain this in more detail, we analyzed software developers' day-to-day information needs. we observed seventeen developers at a large software company and transcribed their activities in 90-minute sessions. we analyzed these logs for the information that developers sought, the sources that they used, and the situations that prevented information from being acquired. we identified twenty-one information types and cataloged the outcome and source when each type of information was sought. the most frequently sought information included awareness about artifacts and coworkers. the most often deferred searches included knowledge about design and program behavior, such as why code was written a particular way, what a program was supposed to do, and the cause of a program state. developers often had to defer tasks because the only source of knowledge was unavailable coworkers.
identifying feature interactions in multi-language aspect-oriented frameworks. the simultaneous use of multiple aspect languages has the potential of becoming a significant one, as new aspect-oriented frameworks are developed and existing ones expand to incorporate features of others. a key challenge in combining multiple aspect-oriented languages is identifying and resolving adverse feature interactions. these interactions occur due to the incompatible and inconsistent treatment of aspects, join points, and advice across different languages. in this paper, we analyze the root cause of this feature interaction problem. we classify common features of aspect languages, describe how these features may interact when using different aspect languages in tandem, and concretely illustrate how these interactions may be resolved. our work allows aop users and tool developers to reason about the occurrence of such adverse and unexpected feature interactions, and to apply several patterns for resolving these problems.
hybrid concolic testing. we present hybrid concolic testing, an algorithm that interleaves random testing with concolic execution to obtain both a deep and a wide exploration of program state space. our algorithm generates test inputs automatically by interleaving random testing until saturation with bounded exhaustive symbolic exploration of program points. it thus combines the ability of random search to reach deep program states quickly together with the ability of concolic testing to explore states in a neighborhood exhaustively. we have implemented our algorithm on top of cute and applied it to obtain better branch coverage for an editor implementation (vim 5.7, 150k lines of code) as well as a data structure implementation in c. our experiments suggest that hybrid concolic testing can handle large programs and provide, for the same testing budget, almost 4× the branch coverage than random testing and almost 2× that of concolic testing.
engineering safety and security related requirements for software intensive systems. many software-intensive systems have significant safety and security ramifications and need to have their associated safety- and security-related requirements properly engineered. it has been observed by several consultants, researchers, and authors that inadequate requirements are a major cause of accidents involving software-intensives systems, and poor security requirements prevent the early incorporation of security concerns into the architecture. yet in practice, there is very little interaction between the requirements, safety, and security disciplines and little collaboration between their respective communities. most requirements engineers, safety engineers, and security engineers know little about their respective disciplines. also, safety and security engineering typically concentrates on architectures and designs rather than requirements because hazard and threat analysis typically depends on the identification of hardware and software components, the failure of which can cause accidents and vulnerabilities which can enable successful attacks. this leads to safety- and security-related requirements that are often ambiguous, incomplete, unverifiable, and even missing. this tutorial begins with a single common realistic example of a safety- and security-critical system that will be used throughout to provide good examples of safety- and security-related requirements. the tutorial provides a consistent ontology of safety, security, and requirements concepts and terminology, provides clear definitions and descriptions of the different kinds of safety- and security-related requirements, and finishes with a practical consistent combined process for engineering them.
supporting the investigation and planning of pragmatic reuse tasks. software reuse has long been promoted as a means to increase developer productivity; however, reusing source code is difficult in practice and tends to be performed in an ad hoc manner. this is problematic because poor decisions can be made either to attempt an unwise, overly complex reuse task, or to avoid a reuse task that would have saved time and effort. this paper describes a lightweight tool that supports the investigation and planning of pragmatic reuse tasks. the tool helps developers to identify the dependencies from the source code they wish to reuse, and to decide how to deal with those dependencies. questions about pragmatic reuse are evaluated through a survey of industrial developers. the tool is evaluated through the planning and execution of reuse tasks by industrial developers.
do maintainers utilize deployed design patterns effectively?. one claimed benefit of deploying design patterns is facilitating maintainers to perform anticipated changes. however, it is not at all obvious that the relevant design patterns deployed in software will invariably be utilized for the changes. moreover, we observe that many well-known design patterns consist of three types of programming elements (called participants), and that performing an anticipated change typically entails multiple tasks related to different types of participants. this paper studies empirically whether maintainers utilize deployed design patterns, and when they do, which tasks they more commonly perform. our experiments show that almost all subjects perform the task of adding new concrete participants, fewer perform the tasks involving clients, whereas even fewer perform the tasks involving abstract participants. furthermore, utilizing deployed design patterns (by performing whichever of the corresponding tasks) is found to be statistically associated with the delivery of less faulty codes.
detection of duplicate defect reports using natural language processing. defect reports are generated from various testing and development activities in software engineering. sometimes two reports are submitted that describe the same problem, leading to duplicate reports. these reports are mostly written in structured natural language, and as such, it is hard to compare two reports for similarity with formal methods. in order to identify duplicates, we investigate using natural language processing (nlp) techniques to support the identification. a prototype tool is developed and evaluated in a case study analyzing defect reports at sony ericsson mobile communications. the evaluation shows that about 2/3 of the duplicates can possibly be found using the nlp techniques. different variants of the techniques provide only minor result differences, indicating a robust technology. user testing shows that the overall attitude towards the technique is positive and that it has a growth potential.
very-large scale code clone analysis and visualization of open source programs using distributed ccfinder: d-ccfinder. the increasing performance-price ratio of computer hardware makes possible to explore a distributed approach at code clone analysis. this paper presents d-ccfinder, a distributed approach at large-scale code clone analysis. d-ccfinder has been implemented with 80 pc workstations in our student laboratory, and a vast collection of open source software with about 400 million lines in total has been analyzed with it in about 2 days. the result has been visualized as a scatter plot, which showed the presence of frequently used code as easy recognizable patterns. also, d-ccfinder has been used to analyze a single software system against the whole collection in order to explore the presence of code imported from open source software.
aspect-oriented design in java/aspectj and ruby. this tutorial teaches professional developers design principles for "production-quality", aspect-oriented software, written in java/aspectj and ruby. the discussion starts with a review of the rationale for aspect-oriented software development (aosd), how it solves some key problems in enterprise applications, followed by a discussion of tool options and techniques for both languages. after reviewing some of the problems developers encountered during early attempts at aspect-oriented design (aod), recent strategies for addressing those problems are discussed. the majority of the tutorial then covers extensions to standard object-oriented principles and patterns that support designing and implementing aspect software that is agile, robust, maintainable, testable, and reusable. guidelines for when to use aspects vs. other techniques are covered. the tutorial concludes with a look forward to ways that aspects could improve architectures and frameworks.
managing impacts of security protocol changes in service-oriented applications. we present a software tool and a framework for security protocol change management. while we focus on trust negotiation protocols in this paper, many of the ideas are generally applicable to other types of protocols. trust negotiation is a flexible approach to access control that is well suited to dynamic environments typical of service-oriented applications. however, managing the evolution of trust negotiation protocols is a difficult problem that has not been sufficiently addressed, especially in situations where there are ongoing negotiations. by using our framework, the consequences of changing the protocol that applies to ongoing trust negotiations can be automatically determined. we have also implemented a database-backed gui tool to manage the change process as an extension of an existing system, and we have performed experiments to test the efficiency of our management software. our experimental results show that the techniques proposed can scale to applications with tens of thousands of simultaneous users even on commodity pcs.
design and evaluation of a diagrammatic notation to aid in the understanding of concurrency concepts. is generally accepted that concurrency can be difficult for students to reason about. while some studies provide insight into the nature of these difficulties [6], work remains to be done in understanding the aspects of learning about concurrency that are most difficult, and in developing approaches to dealing with this problem. we have conducted instructor interviews and an observational study of students, identified several key difficulties that students encounter, and developed a diagram that we believe will be an aid to understanding and problem-solving. we present the diagram and results of an initial user evaluation.
cost-benefit analysis of software development techniques and practices. investigations of software development practices, processes, and techniques frequently report separately on the costs and benefits of a phenomenon under study, but rarely adequately address the combined bottomline implications. in particular, tensions between the quality and productivity effects are hard to reconcile, making objective, high-level insights elusive. for example, is a practice that is believed to improve product quality significantly, but incurs a mild developer productivity penalty economically feasible? in other words, do the benefits outweigh the costs? and if they do, under which conditions? such questions can be tackled through synthesizing effects and analyzing the resulting behaviors. in this light, the tutorial presented an approach that leverages well-known and simple economic concepts and models. it is used to wrap empirical findings, and is also applicable to the assessment of software projects. the tutorial was geared towards researchers and practitioners interested in software processes, process improvement, project management, process/project measurement, and empirical software engineering.
a template for real world team projects for highly populated software engineering classes. assigning projects of group work in the context of software engineering courses has become a commonly used practice in several educational institutions. previously reported results examined different aspects of this approach. the problem is that most studies are based on relatively small group sizes. in this article a large scale project template for a class-wide project that is currently in use in the department of computer engineering, boðaziçi university, will be presented.
first workshop on the economics of software and computation. software and the computational behaviors it defines are increasingly important sources of both economic costs and benefits for companies, governments and individuals. nevertheless, our ability to reason about the economics of software and computation to improve decision-making remains primitive. the workshop on the economics of software and computation (esc) provides a forum for research discussions in this area.
variability management in software product line engineering. software product line engineering (sple [2], [6]) has proven to be the paradigm for developing a diversity of similar software applications and software-intensive systems at low costs, in short time, and with high quality. numerous reports document the significant achievements of introducing software product lines in industry [6].
towards reusable components with aspects: an empirical study on modularity and obliviousness. the potential of aspect-oriented programming to represent cross-cutting concerns as reusable components has yet to be fully realized. indeed, authors have detailed significant challenges in creating reusable aspect component libraries. proposed solutions include restricting the power of aspects upfront, inferring concern interaction, and shaping base code to conform to abstract design rules. another proposed strategy is to reduce obliviousness in return for increased modularity by extending aspectj with explicit join points (ejps). this paper presents the results of an empirical case study that aides in the understanding of the tradeoffs between obliviousness and modularity. we present a refactoring of the exception handling concern for three real-life java applications to use ejps instead of oblivious aspects. the empirical differences between this version and an equivalent oblivious version are analyzed. finally, we present guiding principles on how to strike a favorable balance between obliviousness and modularity.
clonetracker: tool support for code clone management. code clones are generally considered to be an obstacle to software maintenance. research has provided evidence that it may not always be practical, feasible, or cost-effective to eliminate certain clone groups through refactoring. this paper describes clonetracker, an eclipse plug-in that provides support for tracking code clones in evolving software. with clonetracker, developers can specify clone groups they wish to track, and the tool will automatically generate a clone model that is robust to changes to the source code, and can be shared with other collaborators of the project. when future modifications intersect with tracked clones, clonetracker will notify the developer, provide support to consistently apply changes to a corresponding clone region, and provide support for updating the clone model. clonetracker complements existing techniques by providing support for reusing knowledge about the location of clones in source code, and support for keeping track of clones when refactoring is not desirable.
6th international workshop on scenarios and state machines: models, algorithms, and tools (scesm07). scenarios and state machines are two of the fundamental modeling perspectives for developing behavioral abstractions of complex, reactive software. scenarios represent a partial view on the interactions between multiple system components; state machines typically model the complete behavior of individual components. both perspectives have advantages .. scenarios are easily understood by stakeholders at all levels, lead naturally to tests and focus on inter-component communication; state machines, on the other hand, provide precise descriptions of component behavior and can be used for generating implementations (either manually or automatically). in particular, uml supports both notations and in uml2.0, scenarios can be modeled in a much more expressive way than with previous versions of uml. this workshop aims to investigate the connection between scenarios and state machines, assess how this connection can be exploited to improve software development, support the evaluation of techniques that exploit the connection and support the showcasing of developer tools based on both views.
fifth international workshop on dynamic analysis (woda 2007). dynamic analysis techniques reason over program executions and deal with data produced at program execution time. at the woda 2007 workshop, we bring together researchers and practitioners working in all areas of dynamic analysis to discuss new issues, share results and ongoing works, and foster collaborations.
reliability analysis of concurrent systems using ltsa. the analysis for software dependability is considered an important task within the software engineering life cycle. however, it is often impossible to carry out this task due to the complexity of available tools, lack of expert personnel and time-to-market pressures. as a result, released software versions may present unverified dependability properties subjecting customers to blind software reliability assessment. in particular, concurrent systems present certain behaviour that require a more complex system analysis not easily grasped at system design and architecture level.
dynamic detection of atomic-set-serializability violations. previously we presented atomic sets, memory locations that share some consistency property, and units of work, code fragments that preserve consistency of atomic sets on which they are declared. we also proposed atomic-set serializability as a correctness criterion for concurrent programs, stating that units of work must be serializable for each atomic set. we showed that a set of problematic data access patterns characterize executions that are not atomic-set serializable. our criterion subsumes data races (single-location atomic sets) and serializability (all locations in one set). in this paper, we present a dynamic analysis for detecting violations of atomic-set serializability. the analysis can be implemented efficiently, and does not depend on any specific synchronization mechanism. we implemented the analysis and evaluated it on a suite of real programs and benchmarks. we found a number of known errors as well as several problems not previously reported.
workshop on software technologies for ultra-large scale systems. given the inevitable trends towards increasing complexity of software-intensive systems, many future software-intensive systems will be ultra-large scale (uls). radical scale-up of systems will be manifested in many dimensions: implementation complexity, distribution, decentralization, networking, storage, and quality-of-service, dependability/security, size and structure of development organizations and methods, complexity of organizations surrounding deployed systems, and so forth. radical increases in scale and complexity will demand new approaches to all aspects of system conception, definition, development, deployment, use, maintenance, evolution, and regulation. this workshop, the first icse workshop on uls systems, has several goals: to raise awareness of uls systems in the icse community; to further our understanding of the characteristics of such systems; to explore the unique research problems of uls systems; to help foster a community who study and build uls systems; and to understand the role and the shortcomings of traditional software engineering concepts, methods, and tools relative to uls systems.
1st workshop on assessment of contemporary modularization techniques (acom.07). a number of new modularization techniques are emerging to cope with the challenges of contemporary software engineering, such as aspect-oriented software development (aosd), feature-oriented programming (fop), and the like. the effective assessment of such emerging modularization technologies plays a pivotal role on: (i) a better understanding of their real benefits and drawbacks when compared to conventional development techniques, and (ii) their effective transfer to mainstream software development. the acom workshop is the first initiative to put together researchers and practitioners with different backgrounds in order to discuss the multi-faceted issues that emerge in the assessment and/or comparison of new modularization techniques. the workshop is strongly focused on discussions around short presentations and theme-specific groups.
third international workshop on software engineering for high performance computing (hpc) applications. high performance computing systems are used to develop software in a wide variety of domains including nuclear physics, crash simulation, satellite data processing, fluid dynamics, climate modeling, bioinformatics, and financial modeling. the top500 website (http://www.top500.org) lists the top 500 high performance computing systems. the diversity of government, scientific, and commercial organizations present on this list illustrates the growing prevalence and impact of hpc applications on modern society.
languages for safety-critical software: issues and assessment. safety-critical systems (whose anomalous behavior could have catastrophic consequences such as loss of human life) are becoming increasingly prevalent; standards such as do-178b, originally developed for the certification of commercial avionics, are attracting attention in other communities. the requirement to comply with such standards imposes constraints (on quality assurance, traceability, etc.) much beyond what is typical for commercial-off-the-shelf software. one of the major decisions that affects the development of safety-critical software is the choice of programming language(s). specific language features, either by their presence of absence, may make certification easier or harder. indeed, full genera-lpurpose languages are almost always too complex, and restricted subsets are required. this tutorial compares several languages currently in use or under consideration for safety-critical systems --c (and also c++), ada, and java -- and assesses them with respect to their suitability to be constrained for use for such purposes. it specifically examines the misra c subset, spark, and the in-progress effort to develop a safety-critical profile of the real-time specification for java. the tutorial also identifies the challenges that object oriented programming imposes on safety certification and indicates possible future directions.
the effect of program and model structure on mc/dc test adequacy coverage. in avionics and other critical systems domains, adequacy of test suites is currently measured using the mc/dc metric on source code (or on a model in model-based development). we believe that the rigor of the mc/dc metric is highly sensitive to the structure of the implementation and can therefore be misleading as a test adequacy criterion. we investigate this hypothesis by empirically studying the effect of program structure on mc/dc coverage. to perform this investigation, we use six realistic systems from the civil avionics domain and two toy examples. for each of these systems, we use two versions of their implementation-with and without expression folding (i.e., inlining). to assess the sensitivity of mc/dc to program structure, we first generate test suites that satisfy mc/dc over a non-inlined implementation. we then run the generated test suites over the inlined implementation and measure mc/dc achieved. for our realistic examples, the test suites yield an average reduction of 29.5% in mc/dc achieved over the inlined implementations at 5% statistical significance level.
debugging reinvented: asking and answering why and why not questions about program behavior. when software developers want to understand the reason for a program's behavior, they must translate their questions about the behavior into a series of questions about code, speculating about the causes in the process. the whyline is a new kind of debugging tool that avoids such speculation by instead enabling developers to select a question about program output from a set of why did and why didn't questions derived from the program's code and execution. the tool then finds one or more possible explanations for the output in question, using a combination of static and dynamic slicing, precise call graphs, and new algorithms for determining potential sources of values and explanations for why a line of code was not reached. evaluations of the tool on one task showed that novice programmers with the whyline were twice as fast as expert programmers without it. the tool has the potential to simplify debugging in many software development contexts.
sdsoa 2007: international workshop on systems development in soa environments. the service-oriented architecture (soa) paradigm is having a substantial impact on the way software systems are developed. although significant progress is being made in several fronts, there are not a set of clear, central themes to focus research activity. as a result, there is a danger that important research needs will be overlooked, while other efforts will focus on issues of peripheral long-term significance in practice. the objective of this workshop is to begin developing a long-term community-wide research agenda for the successful development of soa-based systems. a tentative taxonomy of research issues will be presented, as well as papers that focus on specific parts of the taxonomy. through an interactive workshop format, researchers will collaboratively identify open research issues and develop a draft research agenda for the community.
mining software engineering data. software engineering data (such as code bases, exe- cution traces, historical code changes, mailing lists, and bug databases) contains a wealth of information about a project's status, progress, and evolution. using well- established data mining techniques, practitioners and re- searchers can explore the potential of this valuable data in order to better manage their projects and to produce higher-quality software systems that are delivered on time and within budget. this tutorial presents the latest research in mining soft- ware engineering (se) data, discusses challenges associ- ated with mining se data, highlights se data mining suc- cess stories, and outlines future research directions. partic- ipants will acquire knowledge and skills needed to perform research or conduct practice in the field and to integrate data mining techniques in their own research or practice.
migration of legacy assets to service-oriented architecture environments. this tutorial addresses the problem of the migration of legacy assets to service-oriented architecture (soa) environments. it addresses how to develop a realistic strategy for performing such a migration, taking into account both the business needs of the organization and the technical content of the organization's existing systems portfolio. the tutorial outlines an approach for performing an overall analysis and making decisions on the legacy assets that are candidates for migration. it highlights the challenges of building an soa-based system and presents development issues from three perspectives: the application developer, the infrastructure developer, and the service provider. the needs and concerns of each of these participants are considered in order to develop successful soa-based systems.
design and implementation of the software architecture for a 3-d reconstruction system in medical imaging. the design and implementation of the reconstruction system in medical x-ray imaging is a challenging issue due to its immense computational demands. in order to ensure an efficient clinical workflow it is inevitable to meet high performance requirements. hence, the usage of hardware acceleration is mandatory. the software architecture of the reconstruction system is required to be modular in a sense that different accelerator hardware platforms are supported and it must be possible to implement different parts of the algorithm using different acceleration architectures and techniques. this paper introduces and discusses the design of a software architecture for an image reconstruction system that meets the aforementioned requirements. we implemented a multi-threaded software framework that combines two software design patterns: the pipeline and the master/worker pattern. this enables us to take advantage of the parallelism in off-the-shelf accelerator hardware such as multi-core systems, the cell processor, and graphics accelerators in a very flexible and reusable way.
e-bus: a toolkit for extracting business services from java software systems. e-bus (extracting business services) is an integrated environment to extract and model critical business services embedded in java systems by utilizing graphic representations and transformations of system models. the extracted business services can be realized as self-contained components. our evaluation has shown that e-bus is effective and scalable in identifying and extracting business services from large java legacy systems.
workshop summary - icse workshop on software engineering for pervasive computing applications, systems, and environments (sepcase). this workshop aims to provide a forum for researchers to discuss the state of the art of software engineering practices and research challenges in designing and building pervasive computing systems and applications. such systems are intended to support seamless mobility of users across different physical spaces by providing context-aware adaptation of their applications in regard to functionality, transparent resource discovery and access, and proactive actions. context-based dynamic integration of distributed services and components in applications involving mobile users is an intrinsic characteristic of such environments. building pervasive computing applications requires knowledge of many areas, such as programming models and software architectures, component based application integration, service-oriented architectures, middleware systems, security and privacy, sensor data aggregation for context management, database systems, policy-based system designs, fault-tolerant computing, application of formal methods, to name a few.
automation of software test - report on the second interional workshop ast 2007. software testing is indispensable for all software development. as all mature engineering disciplines need to have systematic testing methodologies, software testing is a very important subject of software engineering. in software development practice, testing accounts for as much as 50% of total development efforts. it is imperative to reduce the cost and improve the effectiveness of software testing by automating the testing process, which contains many testing related activities using various techniques and methods.
agile methods: crossing the chasm. an armada of emerging agile methods of software development (with extreme programming and scrum being the most broadly used) is both gaining popularity and generating lots of controversy. this high-level tutorial gives an overview of agile methods and provides background to understand how agile teams are addressing modern software engineering challenges. analysis of empirical evidence is used to discuss strengths and limitations of agile methods in various contexts. the participants are introduced to the innovation diffusion models and environments, and discuss what is needed for agile methods to cross the chasm and move into the mainstream of software development.
developing an architecture of a knowledge-based electronic patient record. medicine as knowledge-intensive domain has been the subject of various approaches of computer-based knowledge management. most of them concentrated on the design and implementation of expert systems for clinical decision support. today, medical knowledge bases are implemented for various purposes, including encyclopedic sources of information for clinicians. we present a prototypical development of architecture for an electronic patient record which structurally depends on such an encyclopedic representation and is therefore knowledge-based. using the kads approach for knowledge engineering, three modeling steps and architectural parts could be identified, definition of basic concepts, the structural knowledge base model, and the interactive process of knowledge instantiation which constitutes clinical documentation. furthermore, we present an analysis of possible benefits of a knowledge-based electronic patient record in health care as well as in adjacent fields.
moda - multiple objective decision analysis: balancing quality attributes in software architectures. a high-quality software architecture facilitates in developing a high quality software-intensive system. to design such architecture, the architect must consider multiple stakeholders' inconsistent, contradictory, and partially understood objectives, and balance the myriad tradeoffs among them. our approach proposes to balance quality attributes in software architectures by identify the important-yet-to-be-addressed quality attributes during the design process and provide architecture analysis methods to help compare the resulting architecture candidates with respect to required quality attributes.
fifth workshop on software quality. cost, schedule and quality are highly correlated factors in software development. they basically form three sides of the same triangle. beyond a certain point (the "quality is free" point), it is difficult to increase the quality without increasing either cost or schedule or both for the software under development. as products and applications mature, users expect higher quality products. they want it organizations to be responsible and accountable for the quality claims made by the product marketing teams. in the last couple decades, much software engineering research has focussed on standards, methodologies and techniques for improving software quality, measuring software quality and software quality assurance. most of this research is focused on the internal/development view of quality. more recent studies done in conjunction with the marketing groups have made attempts to understand the customer view of quality. all of these different ongoing activities to understand quality from the various perspectives have made the field even more enriching and exciting. the fifth workshop on software quality aims to bring together academic, industrial and commercial communities interested in software quality topics to discuss the different technologies being defined and used in the software quality area.
2nd international workshop on realising evidence-based software engineering (rebse-2). the rebse international workshops are concerned with exploring the adaptation and use of the evidence-based paradigm in software engineering research and practice. the workshops address this goal through a mix of presentations and discussion, drawing upon ideas and experiences from other disciplines where appropriate.
empirical methods in software engineering research. over the past decade, empirical methods have gained acceptance for validating tools and methods in software research. this tutorial aims at acquainting participants with the main methods used in empirical work in software research, enabling them to evaluate empirical results for validity as well as providing the basis for carrying out empirical studies. a wide range of empirical approaches are covered, including case studies, experiments, field studies, and surveys. these approaches are introduced by prominent examples from the software engineering literature. common pitfalls are pointed out. participants also critique empirical papers in small discussion groups, based on worksheets with prepared questions.
lean software development. lean software development is the application of the principles of the toyota product development system to software development. toyota has been extremely successful developing complex new vehicles, which include a vast amount of embedded software, in a very short time and always on time. this tutorial examines the underlying engineering principles toyota uses to develop vehicles and shows how they can be applied to software development. when correctly applied, lean software development results in high quality software that is developed quickly and at the lowest possible cost. moreover, the success of many of the practices of agile software development can be explained by understanding the principles of lean software development.
developing secure embedded systems: pitfalls and how to avoid them. we give an overview over the challenges in developing secure embedded systems and show how to use the approach of model-based security engineering (mbse) to address them. in mbse [jür04, jür05a, jür05b, jür06, bjn07], recurring security requirements (such as secrecy, integrity, authenticity and others) and security assumptions on the system environment, can be specified either within a uml specification, or within the source code (java or c) as annotations. the associated tools [uml04] (fig. 1b) generate logical formulas formalizing the execution semantics and the annotated security requirements.
evolving software product lines with aspects: an empirical study on design stability. software product lines (spls) enable modular, large-scale reuse through a software architecture addressing multiple core and varying features. to reap the benefits of spls, their designs need to be stable. design stability encompasses the sustenance of the product line's modularity properties in the presence of changes to both the core and varying features. it is usually assumed that aspect-oriented programming promotes better modularity and changeability of product lines than conventional variability mechanisms, such as conditional compilation. however, there is no empirical evidence on its efficacy to prolong design stability of spls through realistic development scenarios. this paper reports a quantitative study that evolves two spls to assess various design stability facets of their aspect-oriented implementations. our investigation focused upon a multi-perspective analysis of the evolving product lines in terms of modularity, change propagation, and feature dependency. we have identified a number of scenarios which positively or negatively affect the architecture stability of aspectual spls.
towards practical software traceability. the importance of software traceability to software development is recognized by researchers and practitioners; yet, current approaches fall short of providing effective traceability in practice. an analysis of reported difficulties with traceability reveals that interacting factors from the economic, technical, and social perspectives hinder traceability. motivated by the multi-faceted traceability problem, we combine architecture-centric stakeholder-driven traceability with open hypermedia, and we use insights from e-science to guide our approach. we highlight expected contributions and discuss evaluation plans. finally, we distinguish our approach from related research and technologies.
seams 2007: software engineering for adaptive and self-managing systems. the objective of the seams (software engineering for adaptive and self-managing systems) workshops is to consolidate the interest in the software engineering community on autonomic, self-managing, self-healing, self-optimizing, self-configuring, and self-adaptive systems. seams provides a forum for researchers to share new results, raise awareness, and promote collaboration within the community. the seams 2007 workshop builds on the great success of seams 2006 at icse in shanghai to assess progress and identify challenges in this area.
4th international icse workshop on software engineering for automotive systems. the amount of software in cars grows exponentially. driving forces of this development are the availability of cheaper and more powerful hardware as well as the demand for innovation through new functionality. the rapidly growing significance of software and software-based functionality is at the root of various challenges in the automotive industries, concerning their organization, definition of key competencies, processes, methods, tools, models, product structures, division of labor, logistics, maintenance, and long term strategies [1,2].
requirements engineering so things don't get ugly. regardless of which report you read, the battle cry is loud and clear "projects are failing more often than they are successful. something must be done!" but what? that's the million dollar question. a great start for fixing this long-standing software development crisis is with requirements; we must fully understand what we are developing before we can develop the right product for our customers. readers will probably shake their head and say "of course we do" but statistics show that even though this seems to be a "no brainer" we still aren't doing it.
testing concurrent java components. testing concurrent software is notoriously difficult due to problems with non-determinism and synchronisation. while tools and techniques for the testing of sequential components are well-understood and widely used, similar tools and techniques for concurrent components are not commonly available. this tutorial will look at the problems associated with testing concurrent components and propose techniques for dealing with these problems. the conan (concurrency analyser) testing tool supports these techniques for the testing of concurrent java components and will be discussed and demonstrated in the tutorial. the limitations of the techniques and conan, as well as additional v&v tools and techniques to address these limitations will be presented.
existential live sequence charts revisited. scenario-based specifications are a popular means for describing intended system behaviour. we aim to facilitate early analysis of system behaviour and the development of behaviour models in conjunction with scenarios. in this paper we define a novel scenario-based specification language with an existential semantics and that supports conditional specification of behaviour in the form of prechart and main chart. the language semantics is consistent with existing informal scenario-based and use-case based approaches to requirements engineering. the language provides a good fit with universal live sequence charts as standard existential live sequence charts do not adequately support conditional scenarios. in addition, we define a novel synthesis algorithm that, rather than building arbitrarily one of the many behaviour models that satisfy a scenario, constructs a modal transition system (mts) which characterizes all behaviour models that conform to the scenario.
topes: reusable abstractions for validating data. programmers often omit input validation when inputs can appear in many different formats or when validation criteria cannot be precisely specified. to enable validation in these situations, we present a new technique that puts valid inputs into a consistent format and that identifies "questionable" inputs which might be valid or invalid, so that these values can be double-checked by a person or a program. our technique relies on the concept of a "tope", which is an application-independent abstraction describing how to recognize and transform values in a category of data. we present our definition of topes and describe a development environment that supports the implementation and use of topes. experiments with web application and spreadsheet data indicate that using our technique improves the accuracy and reusability of validation code and also improves the effectiveness of subsequent data cleaning such as duplicate identification.
modeling the effect of size on defect proneness for open-source software. software engineering is a decision intensive discipline. do we really understand all the factors that can influence those decisions? can we build models that reveal hidden patterns in software resource management, in development processes, or in software artifacts themselves? how well do these models predict? can they be used without requiring domain expert intervention? do the models lead to better decisions? how are we to validate these models? is the model creation process repeatable? are there better, faster, cheaper ways to build models? how effective are these models for identifying causal relations? the promise workshop seeks to address these questions and others, and to deliver to the software engineering community useful, usable, verifiable models, and public datasets for building and evaluating new models. at present, the promise repository contains more than 30 datasets.
first international workshop on emerging trends in floss research and development. the "emerging trends in floss research and development" workshop series will be based on the growing interest of researchers and practitioners in free/libre open source software (floss). the first workshop will be specifically focused on discussing the phenomenon of global floss development and how to improve cllaboration and the communication of results between researchers, practitioners and floss communities. for this purpose, the overarching theme of this year's workshop is "feeding back the communities". its goal is to bring together academic researchers, industry members and floss developers and to discuss crossfertilization of results on floss research and practice.
engineering medical information systems: architecture, data and usability & security. there has been increasing pressure on the health care sector to adopt information technologies to rationalize service delivery and increase service quality. medical information systems need to be highly interoperable and effectively manage complex information of great sensitivity. moreover, they have to be optimized for usability in a highly complex knowledge base and agile work environment. this tutorial introduces key concepts, methods and techniques essential for engineering clinical information systems, in particular electronic medical records. it targets participants with basic software engineering knowledge who are or will be involved in development, maintenance, evolution or research of medical software.
get your experience factory ready for the next decade - ten years after "how to build and run one". this one-day tutorial aims at industry practitioners, managers and developers alike, who want to learn more about how to successfully design, implement and run an experience factory, to systematically build up and manage the experience of an organization. state-of- the art methods and techniques on how to initially set-up or to further develop and improve an organization's experience factory are discussed. participants should come from organizations (not only from the software domain) that are interested in implementing an experience factory to help effectively support improvement activities (such as tqm, iso 9000, cmmi, spice, or tsp) to gain competitive advantages.
architecture knowledge management: challenges, approaches, and tools. capturing the technical knowledge, contextual information, and rationale surrounding the design decisions underpinning system architectures can greatly improve the software development process. if not managed, this critical knowledge is implicitly embedded in the architecture, becoming tacit knowledge which erodes as personnel on the project change. moreover, the unavailability of architecture knowledge precludes organizations from growing their architectural capabilities. in this tutorial, we highlight the benefits and challenges in managing software architecture knowledge. we discuss various approaches to characterize architecture knowledge based on the requirements of a particular domain. we describe various concepts and approaches to manage the architecture knowledge from both management and technical perspectives. we also demonstrate the utility of captured knowledge to support software architecture activities with a case study covering the use of architecture knowledge management techniques and tools in an industrial project.
experiences with mirth: an open source health care integration engine. integration engines are a crucial piece of the health care information technology puzzle. health care organizations like hospitals and clinics are faced with vast amounts of data and a slew of interchange standards and protocols when addressing the issue of exchanging data between information systems. this paper describes our experience in developing mirth, a popular open source health care messaging integration engine. based on a unique client-server and enterprise service bus hybrid architecture, mirth supports the development of interfaces for moving data between two or more systems. we describe the mirth architecture in detail and discuss our experiences through several case studies that demonstrate its use. we also provide our insights gained in designing the mirth architecture through several lessons learned.
early prediction of software component reliability. the ability to predict the reliability of a software system early in its development, e.g., during architectural design, can help to improve the system's quality in a cost-effective manner. existing architecture-level reliability prediction approaches focus on system-level reliability and assume that the reliabilities of individual components are known. in general, this assumption is unreasonable, making component reliability prediction an important missing ingredient in the current literature. early prediction of component reliability is a challenging problem because of many uncertainties associated with components under development. in this paper we address these challenges in developing a software component reliability prediction framework. we do this by exploiting architectural models and associated analysis techniques, stochastic modeling approaches, and information sources available early in the development lifecycle. we extensively evaluate our framework to illustrate its utility as an early reliability prediction approach.
the architecture of the apex platform, salesforce.com's platform for building on-demand applications. on-demand computing has transformed enterprise software, lowering risk and cost while increasing user adoption and customer success. to be successful, an application must be designed for on-demand from the ground-up, including core architectural elements such as multitenancy, availability, performance, security, metadata-driven customization, integration via web services, etc. as with any new paradigm, initial applications must design and implement all these core attributes, but ultimately platforms emerge that encapsulate core computing services, allowing application developers to focus on innovation and value, and not on reinventing the wheel. with the apex platform, salesforce.com has delivered the first on-demand platform, allowing developers to easily develop and deliver the next generation of on-demand applications. in this talk, steve fisher discusses the technical architecture of the apex platform.
static detection of cross-site scripting vulnerabilities. web applications support many of our daily activities, but they often have security problems, and their accessibility makes them easy to exploit. in cross-site scripting (xss), an attacker exploits the trust a web client (browser) has for a trusted server and executes injected script on the browser with the server's privileges. in 2006, xss constituted the largest class of newly reported vulnerabilities making it the most prevalent class of attacks today. web applications have xss vulnerabilities because the validation they perform on untrusted input does not suffice to prevent that input from invoking a browser's javascript interpreter, and this validation is particularly difficult to get right if it must admit some html mark-up. most existing approaches to finding xss vulnerabilities are taint-based and assume input validation functions to be adequate, so they either miss real vulnerabilities or report many false positives. this paper presents a static analysis for finding xss vulnerabilities that directly addresses weak or absent input validation. our approach combines work on tainted information flow with string analysis. proper input validation is difficult largely because of the many ways to invoke the javascript interpreter; we face the same obstacle checking for vulnerabilities statically, and we address it by formalizing a policy based on the w3c recommendation, the firefox source code, and online tutorials about closed-source browsers. we provide effective checking algorithms based on our policy. we implement our approach and provide an extensive evaluation that finds both known and unknown vulnerabilities in real-world web applications.
computer professional ethics in theory and in practice. the starting place for professional ethics is with the idea that certain occupational groups have special expertise that leads to special responsibilities. the organization of the group into a profession with an organization that controls admission and promulgates a code of ethics is a mechanism for ensuring that the special expertise of members is deployed in ways that benefit the public (consumers, users, non-experts) or, at least, does not harm the public.
limits to dependability assurance - a controversy revisited. more than twenty years ago, as computers were introduced into safety-critical roles in civil aircraft, there was much debate about what claims could be made for their dependability. much of the debate focused, naturally enough, on what could be claimed for the reliability of software. a famous example was the apparent need to claim a probability of failure of less than 10**-9 per hour for some flight-critical avionics. several authors (i was one) demonstrated that such claims were several orders of magnitude beyond what could be supported with scientific rigour. in this talk i shall revisit this debate, showing some advances that have been made in "dependability cases," particularly involving formal notions of "confidence" in dependability claims. however, i shall also show that the bottom line has not changed significantly: although some systems have been shown to have extremely high dependability/ after the fact/ (i.e. in extensive operational use), it still remains impossible to show/ before using it/ that a system will be extremely dependable in operation. the reason is an unforgiving law about the extensiveness of evidence needed to make very strong dependability claims. these limits to assurance should be of interest beyond the technical community: for example, they pose difficult questions for society in estimating the risks associated with the deployment of certain novel systems.
archstudio 4: an architecture-based meta-modeling environment. we will demonstrate archstudio, an environment for software architecture modeling and meta-modeling. we will also showcase a set of innovative architecture-centric applications that use archstudio technologies as their basis.
is code still moving around? looking back at a decade of code mobility. in the mid-nineties, mobile code was on the rise and, in particular, there was a growing interest in autonomously moving code components, called mobile agents. in 1997, we published a paper that introduced the concept of mobile code paradigms, which are design patterns that involve code mobility. the paradigms highlighted the locations of code, resources, and execution as first-class abstractions. this characterization proved useful to frame mobile code designs and technologies, and also as a basis for a quantitative analysis of applications built with them. ten years later, things have changed considerably. in this paper we present our view of how mobile code evolved and discuss which paradigms succeeded or failed in supporting effectively distributed applications.
on the difficulty of replicating human subjects studies in software engineering. replications play an important role in verifying empirical results. in this paper, we discuss our experiences performing a literal replication of a human subjects experiment that examined the relationship between a simple test for consistent use of mental models, and success in an introductory programming course. we encountered many difficulties in achieving comparability with the original experiment, due to a series of apparently minor differences in context. based on this experience, we discuss the relative merits of replication, and suggest that, for some human subjects studies, literal replication may not be the the most effective strategy for validating the results of previous studies.
retrospectives on peopleware. since its publication twenty years ago, "peopleware productive projects and teams" (dorset house, 1987), by tom demarco and tim lister, has enlightened software professionals and non-professionals alike. peopleware introduced among other topics - "team gel", design patterns, the "furniture police" - to the software engineering community and suggested that "sociology matters more than technology or even money." this unique session with the pioneers of our profession is an opportunity to learn, reflect, and share experiences -- looking forward to the future. this compendium consists of brief bios and first person retrospectives on "peopleware".
executable misuse cases for modeling security concerns. misuse cases are a way of modeling negative requirements, that is, behaviors that should not occur in a system. in particular, they can be used to model attacks on a system as well as the security mechanisms needed to avoid them. however, like use cases, misuse cases describe requirements in a high-level and informal manner. this means that, whilst they are easy to understand, they do not lend themselves to testing or analysis. in this paper, we present an executable misuse case modeling language which allows modelers to specify misuse case scenarios in a formal yet intuitive way and to execute the misuse case model in tandem with a corresponding use case model. misuse scenarios are given in executable form and mitigations are captured using aspect-oriented modeling. the technique is useful for brainstorming potential attacks and their mitigations. furthermore, the use of aspects allows mitigations to be maintained separately from the core system model. the paper, supported by a uml-based modeling tool, describes an application to two case studies, providing evidence that the technique can support red-teaming of security requirements forn realistic systems.
agile contracts. in the mid 1980's toyota came to the us and showed detroit how to work with suppliers on a win-win basis. in just five years, toyota was the most trusted automaker among all automotive suppliers, had the lowest procurement costs, and the highest contribution of innovation from supplier companies. what does toyota know about working with contracts that we can learn? for starters, they know that trust lies in specific actions, not interpersonal relationships. they understand the "game' of contracting, and know how to structure relationships so both sides are motivated to contribute to the common good. there's much we can learn from toyota about how to change the contracting game in software development for the benefit of both parties.
a study of student strategies for the corrective maintenance of concurrent software. graduates of computer science degree programs are increasingly being asked to maintain large, multi-threaded software systems; however, the maintenance of such systems is typically not well-covered by software engineering texts or curricula. we conducted a think-aloud study with 15 students in a graduate-level computer science class to discover the strategies that students apply, and to what effect, in performing corrective maintenance on concurrent software. we collected think-aloud and action protocols, and annotated the protocols for a number of behavioral attributes and maintenance strategies. we divided the protocols into groups based on the success of the participant in both diagnosing and correcting the failure. we evaluated these groups for statistically significant differences in these attributes and strategies. in this paper, we report a number of interesting observations that came from this study. all participants performed diagnostic executions of the program to aid program comprehension; however, the participants that used this as their predominant strategy for diagnosing the fault were all unsuccessful. among the participants that successfully diagnosed the fault and displayed high confidence in their diagnosis, we found two commonalities. they all recognized that the fault involved the violation of a concurrent-programming idiom. and, they all constructed detailed behavioral models (similar to uml sequence diagrams) of execution scenarios. we present detailed analyses to explain the attributes that correlated with success or lack of success. based on these analyses, we make recommendations for improving software engineering curriculums by better training students how to apply these strategies effectively.
modeling for maintainability. software maintenance is the cinderella of software engineering. the cost of creating a longlived application is dwarfed by the cost of maintaining, updating and porting it over a lifetime sometimes measured in decades, yet few software engineers plan for maintainability. the only alternative to maintenance is to routinely re-implement working systems to a revised specification, but this is an even more expensive proposition. in fact, as the deployed software base continues to grow, we may already have reached the point where it's economically impossible to replace working applications, and there's no alternative to maintaining them. fortunately, recent studies show that model-driven development methods (such as omg's model driven architecture) not only help develop quality applications quickly and cheaply in the first place, but also yield dramatic savings in the time and effort needed to maintain them. use of model-driven techniques may literally be the only way businesses can afford to keep their software infrastructure running over the next few decades.
deryaft: a tool for generating representation invariants of structurally complex data. deryaft is a tool for generating likely representation invariants of structurally complex data. given a small set of concrete structures, deryaft analyzes their key characteristics to formulate local and global properties that the structures exhibit. for effective formulation of structural invariants, deryaft focuses on graph properties, including reachability, and views the program heap as an edge-labeled graph. deryaft outputs a java predicate that represents the invariants; the predicate takes an input structure and returns true if and only if it satisfies the invariants.
portraits in practice. portraits in practice invites companies with technically advanced software-engineering practices and intriguing research challenges to discuss them with the icse 2007 participants. the sessions in this track let researchers hear industrial practitioners describe their projects and concerns in some detail, and they let other practitioners hear what technologies these companies recommend. the track provides an open discussion and blunt assessment of future needs with experts from these leading industries. the goal is to encourage and foment improved communication between leading companies and academic researchers.
adams re-trace: traceability link recovery via latent semantic indexing. in this demonstration we present the traceability recovery tool developed in adams, a fine-grained artefact management system. the tool is based on an information retrieval technique, namely latent semantic indexing, and aims at supporting the software engineer in the identification of traceability links between artefacts of different types. the tool has also been integrated in the eclipse-based client of adams.
software engineering: the legacy of barry w. boehm. we are convening a symposium to honor barry w. boehm's lifetime contributions to the software engineering community and co-locating this event with the 29th international conference on software engineering.
defining and continuous checking of structural program dependencies. dependencies between program elements need to be modeled from different perspectives reflecting architectural, design, and implementation level decisions. to avoid erosion of the intended structure of the code, it is necessary to explicitly codify these different perspectives on the permitted dependencies and to detect violations continuously and incrementally as software evolves. we propose an approach that uses declarative queries to group source elements - across programming language module boundaries - into overlapping ensembles. the dependencies between these ensembles are also specified as logic queries. the approach has been integrated into the incremental build process of eclipse to ensure continuous checking, using an engine for tabled and incremental evaluation of logic queries. our evaluation shows that our approach is fast enough for day-to-day use along the incremental build process of modern ides.
strada: a tool for scenario-based feature-to-code trace detection and analysis. software engineers frequently struggle with understanding the relationships between the source code of a system and its requirements or high-level features. these relationships are commonly referred to as trace links. the creation and maintenance of trace links is a largely manual, time-consuming, and error-prone process. this paper presents strada (scenario-based trace detection and analysis) -- a tool that helps software engineers explore traces links to source code through testing. while testing is predominantly done to ensure the correctness of a software system, strada demonstrates a vital secondary benefit: by executing source code during testing it can be linked to requirements and features, thus establishing traceability automatically.
incremental state-space exploration for programs with dynamically allocated data. we present a novel technique that speeds up state-space exploration (sse) for evolving programs with dynamically allocated data. sse is the essence of explicit-state model checking and an increasingly popular method for automating test generation. traditional, non-incremental sse takes one version of a program and systematically explores the states reachable during the program's executions to find property violations. incremental sse considers several versions that arise during program evolution: reusing the results of sse for one version can speed up sse for the next version, since state spaces of consecutive program versions can have significant similarities. we have implemented our technique in two model checkers: java pathfinder and the j-sim state-space explorer. the experimental results on 24 program evolutions and exploration changes show that for non-initial runs our technique speeds up sse in 22 cases from 6.43% to 68.62% (with median of 42.29%) and slows down sse in only two cases for -4.71% and -4.81%.
ucsim: a tool for simulating use case scenarios. this paper describes the use case simulator (ucsim), an eclipse plug-in for visualization and simulation of use cases. simulation of use cases allows stakeholders to play with what-if scenarios as a way to test completeness and correctness. textual use cases, however, are not semantically precise enough to be simulated. ucsim, therefore, uses minimal extensions to uml models to describe use cases, transforms the use cases automatically into an executable form (hierarchical uml state machines), and provides a configurable simulator for executing the state machine representation of the use cases.
mining library specifications using inductive logic programming. software libraries organize useful functionalities in order to promote modularity and code reuse. a typical library is used by client programs through an application programming interface (api) that hides its internals from the client. typically, the rules governing the correct usage of the api are documented informally. in many cases, libraries may have complex api usage rules and unclear documentation. as a result, the behaviour of the library under some corner cases may not be well understood by the programmer. formal specifications provide a precise understanding of the api behaviour. we propose a methodology for learning interface specifications using inductive logic programming (ilp). our technique runs several unit tests on the library in order to generate relations describing the operation of the library. the data collected from these tests are used by an inductive learner to obtain rich datalog/prolog specifications. such specifications capture essential properties of interest to the user. they may be used for applications such as reverse engineering the library internals or constructing checks on the application code to enforce proper api usage along with other properties of interest.
building scalable libraries with cj. creating highly reusable software libraries is one of the primary software engineering goals. the ability of a library to be reused, however, depends crucially on the ease of customizing the reusable components. if customization is hard, the well-known library scalability problem [1] ensues: a domain contains n features, but these can produce an exponential (or super-exponential if order matters or features can be replicated) number of combinations. hard-coding all combinations results in an unmaintainably large library. offering features as components that are composed without any customization results in undesirable "bad-fit" solutions, either for reasons of performance or correctness.
mismar: a new approach to developer documentation. successful open source projects foster collaboration and innovation while benefiting from a faster pace of development, but are often plagued by poor developer's documentation. in this paper, we present the rationale and the architecture of mismar, a toolset tightly integrated in the eclipse environment and implementing a concern-oriented approach to documentation. as opposed to traditional documentation artifacts, guides produced by mismar are almost wordless and automatically maintain implementation examples. moreover, since mismar was built from the ground up to be extensible, it is easy to support artifacts written in multiple languages or modeling approaches.
marama: an eclipse meta-toolset for generating multi-view environments. we describe the marama suite of meta-tools. this eclipse-based toolset permits rapid specification of notational elements, meta-models, view editors and view-model mappings. it has a novel set of behavioural specification tools for both visual and model level behaviours. an integrated mapping tool provides model transformation and code generation support. the toolset has been applied to several significant application development tasks and has undergone a variety of evaluations.
a business process explorer: recovering and visualizing e-commerce business processes. a business process is composed of a set of interrelated tasks which are joined together by control flow elements. e-commerce systems implement business processes to automate the daily operations of an organization. organizations must continuously modify their e-commerce systems to accommodate changes to business processes. however, modifying e-commerce systems is a time consuming and error prone task. to correctly perform this task, developers require an in-depth understanding of multi-tiered e-commerce systems and the business processes that they implement. in this paper, we present a business process explorer tool which automatically recovers business processes from three tier e-commerce systems. developers can explore the recovered business processes and browse the corresponding source code. we integrate our tool with ibm websphere business modeler (wbm), a leading commercial tool for business process management and modeling. business analysts could then visualize and analyze the recovered processes using wbm. the business process explorer eases the co-evolution of business processes and their e-commerce system implementation.
decimal and plfaultcat: from product-line requirements to product-line member software fault trees. plfaultcat is a tool for software fault tree analysis (sfta) during product-line engineering. when linked with decimal, a product-line requirements verification tool, the enhanced version of plfaultcat provides traceability between productline requirements and sfta hazards as well as semi-automated derivation of the sfta for each new product-line system previously verified by decimal. the combined tool reduces the effort needed to safely reuse requirements and customize the product-line sfta as each new system is constructed.
a tale of four kernels. the freebsd, gnu/linux, solaris, and windows operating systems have kernels that provide comparable facilities. interestingly, their code bases share almost no common parts, while their development processes vary dramatically. we analyze the source code of the four systems by collecting metrics in the areas of file organization, code structure, code style, the use of the c preprocessor, and data organization. the aggregate results indicate that across various areas and many different metrics, four systems developed using wildly different processes score comparably. this allows us to posit that the structure and internal quality attributes of a working, non-trivial software artifact will represent first and foremost the engineering requirements of its construction, with the influence of process being marginal, if any.
sofya: supporting rapid development of dynamic program analyses for java. dynamic analysis is an increasingly important means of supporting software validation and maintenance. to date, developers of dynamic analyses have used low-level instrumentation and debug interfaces to realize their analyses. many dynamic analyses, however, share multiple common high-level requirements, e.g., capture of program data state as well as events, and efficient and accurate event capture in the presence of threading. we present sofya -- an infra-structure designed to provide high-level, efficient, concurrency-aware support for building analyses that reason about rich observations of program data and events. it provides a layered, modular architecture, which has been successfully used to rapidly develop and evaluate a variety of demanding dynamic program analyses. in this paper, we describe the sofya framework, the challenges it addresses, and survey several such analyses.
todo or to bug: exploring how task annotations play a role in the work practices of software developers. software development is a highly collaborative activity that requires teams of developers to continually manage and coordinate their programming tasks. in this paper, we describe an empirical study that explored how task annotations embedded within the source code play a role in how software developers manage personal and team tasks. we present findings gathered by combining results from a survey of professional software developers, an analysis of code from open source projects, and interviews with software developers. our findings help us describe how task annotations can be used to support a variety of activities fundamental to articulation work within software development. we describe how task management is negotiated between the more formal issue tracking systems and the informal annotations that programmers write within their source code. we report that annotations have different meanings and are dependent on individual, team and community use. we also present a number of issues related to managing annotations, which may have negative implications for maintenance. we conclude with insights into how these findings could be used to improve tool support and software process.
taxi - a tool for xml-based testing. we present the tool taxi which implements the xml-based partition testing approach for the automated generation of xml instances conforming to a given xml schema. in addition it provides a set of weighted test strategies to guide the systematic derivation of instances. taxi can be used for black-box testing of applications accepting in input xml instances and for benchmarking of database management systems.
supporting requirements engineering for medical products: early consideration of user-perceived quality. the usability and, more generally, the overall user-perceived quality of medical devices is an important aspect, which is often insufficiently addressed in the corresponding system development activities. fortunately, the development of new standards like iec/din en 60601-1-6 is strengthening the focus on usability / user acceptance issues. this paper argues for the need to consider usability and user acceptance issues in early system development phases like the requirements engineering phase. in this paper, an empirically validated new quality model for user satisfaction is described first. the importance of the quality aspects included in this quality model for the medical domain is outlined. then, the new quality model is used to develop a systematic methodology called appraisal and measurement of user satisfaction (amuse), which allows gathering user acceptance information early in system development. the key activities of the amuse methodology and typical application scenarios are shown. further on, the application of amuse, which was developed in close cooperation with siemens corporate technology, is demonstrated in a real-world scenario at siemens audiologische technik, a line of business of siemens medical solutions. at the end, the first lessons learned from the application of the amuse methodology in this medical domain are discussed.
shiws: a self-healing integrator for web services. the integration of third-party web services is challenged by the difficulty of keeping consistency between software systems that are maintained by different organizations and may evolve dynamically and independently, because of both changes in service implementation and dynamic discovery of new services.
scalable detection of semantic clones. several techniques have been developed for identifying similar code fragments in programs. these similar fragments, referred to as code clones, can be used to identify redundant code, locate bugs, or gain insight into program design. existing scalable approaches to clone detection are limited to finding program fragments that are similar only in their contiguous syntax. other, semantics-based approaches are more resilient to differences in syntax, such as reordered statements, related statements interleaved with other unrelated statements, or the use of semantically equivalent control structures. however, none of these techniques have scaled to real world code bases. these approaches capture semantic information from program dependence graphs (pdgs), program representations that encode data and control dependencies between statements and predicates. our definition of a code clone is also based on this representation: we consider program fragments with isomorphic pdgs to be clones. in this paper, we present the first scalable clone detection algorithm based on this definition of semantic clones. our insight is the reduction of the difficult graph similarity problem to a simpler tree similarity problem by mapping carefully selected pdg subgraphs to their related structured syntax. we efficiently solve the tree similarity problem to create a scalable analysis. we have implemented this algorithm in a practical tool and performed evaluations on several million-line open source projects, including the linux kernel. compared with previous approaches, our tool locates significantly more clones, which are often more semantically interesting than simple copied and pasted code fragments.
acl2s: "the acl2 sedan". acl2 is the latest inception of the boyer-moore theorem prover, the 2005 recipient of the acm software system award. in the hands of experts it feels like a finely tuned race car, and it has been used to prove some of the most complex theorems ever proved about commercially designed systems. unfortunately, acl2 has a steep learning curve. thus, novices tend have a very different experience: they crash and burn. as part of a project to make acl2 and formal reasoning safe for the masses, we have developed acl2s, the acl2 sedan. acl2s includes many features for streamlining the learning process that are not found in acl2. in general, the goal is to develop a tool that is ''self-teaching,''i.e., it should be possible for an undergraduate to sit down and play with it and learn how to program in acl2 and how to reason about the programs she writes.
a comparative analysis of the efficiency of change metrics and static code attributes for defect prediction. in this paper we present a comparative analysis of the predictive power of two different sets of metrics for defect prediction. we choose one set of product related and one set of process related software metrics and use them for classifying java files of the eclipse project as defective respective defect-free. classification models are built using three common machine learners: logistic regression, naïve bayes, and decision trees. to allow different costs for prediction errors we perform cost-sensitive classification, which proves to be very successful: >75% percentage of correctly classified files, a recall of >80%, and a false positive rate
trio2promela: a model checker for temporal metric specifications. we present trio2promela, a tool for model checking metric temporal logic specifications written in the trio language. our approach is based on the translation of formulae into promela programs for the model checker spin, guided by equivalence between temporal logic and alternating büchi automata. trio2promela may be used also to check satisfiability of temporal logic specifications (a distinguishing difference with other model checking tools).
improving the handsets network test process via dmaic concepts. the wireless network evolution has allowed that the handset technology provides a broad and new set of resources and facilities to their users. however, this evolution is also increasing the number and complexity of testing prior to handsets deployment, so that there is a need to apply methodologies to ensure the quality of the test process while it evolves. this paper relates how the dmaic framework could be used as an option to ensure and improve the quality of handsets network test processes. dmaic is a six sigma framework based on measures and statistical analysis, which has commonly been applied during several stages of software development. our focus, in this paper, is on the definition of the dmaic phases and how this framework could be useful to stress problems and lead the effort of tests corrections and improvements.
using jule to generate a compliance test suite for the uml standard. the java-uml lightweight enumerator (jule) tool implements a vitally important aspect of the framework for software tool certification - test suite generation. the framework uses uml models as the test inputs for the bounded exhaustive-testing approach. within a size bound for the metamodel types, jule enumerates only the set of non-isomorphic models in the form of relational structures. these models are classified into two sets - demonstration and counterexample - using binary decision diagrams (bdds). the power of jule lies in its model enumeration and its use of a high-performance grid infrastructure. hence, jule efficiently generates a very small test suite while increasing the bound on the input size to the extent that is practical for certification purpose.
websob: a tool for robustness testing of web services. web services are a popular way of implementing a service-oriented architecture. testing can be used to help assure both the correctness and robustness of a web service. because manual testing is tedious, tools are needed to automate test generation and execution for web services. this paper presents websob, a tool for automatically generating and executing web-service requests given a service provider's web service description language (wsdl) specification. we have applied websob to freely available web services and our experiences show that websob can be used to quickly generate and execute web-service requests that may reveal robustness problems with no knowledge of the underlying web service implementation.
developing a security protocol for a distributed decision support system in a healthcare environment. in this paper, we describe the unique security issues involved in healthcare domains. these have been addressed to the needs of the healthagents project. in the proposed approach, several levels of security have been provided in accordance with software engineering principles, ethical regulations for healthcare data, as well as the security requirements usually raised from the distributed clinical settings. the result is the production of a secure and maintainable multi-agent system that enables secure communication, uniform home site authentication, and customised resource access authorisation. a security policy rule scheme has been designed for agent interaction modelling. this separates the functional and non-functional (security) requirements but let security policy constraints integrate into the running of the agents via a unified role notion. each user/agent can play a function role only when its assigned social rights roles permit the access to resources of various types and geographical locations, as specified in the function role behaviour. the approach is illustrated using a comprehensive secure access case.
dynamo and self-healing bpel compositions. dynamo augments current bpel technology with self-healing capabilities. dedicated supervision rules allow the designer to set the amount of checks that must be performed at runtime and how the bpel process must react whether anomalies arise. the technological underpinnings come from assertion languages and rule-based systems. the implementation exploits aspects and a rule engine to extend activebpel with self-healing capabilities.
temporal dependency based checkpoint selection for dynamic verification of fixed-time constraints in grid workflow systems. in grid workflow systems, temporal correctness is critical to assure the timely completion of grid workflow execution. to monitor and control the temporal correctness, fixed-time constraints are often assigned to a grid workflow and then verified. a checkpoint selection strategy is used to select checkpoints along grid workflow execution for verifying fixed-time constraints. the problem of existing representative strategies is that they do not differentiate fixed-time constraints as once a checkpoint is selected, they verify all fixed-time constraints. however, these checkpoints do not need to be taken for those constraints whose consistency can be deduced from others. the corresponding verification of such constraints is consequently unnecessary and can severely impact the efficiency of overall temporal verification. to address the problem, in this paper, we develop a new temporal dependency based checkpoint selection strategy which can select checkpoints according to different fixed-time constraints. with our strategy, the corresponding unnecessary verification can be avoided. the comparison and experimental simulation further demonstrate that our new strategy can improve the efficiency of overall temporal verification significantly over the existing representative strategies.
on sufficiency of mutants. mutation is the practice of automatically generating possibly faulty variants of a program, for the purpose of assessing the adequacy of a test suite or comparing testing techniques. the cost of mutation often makes its application infeasible. the cost of mutation is usually assessed in terms of the number of mutants, and consequently the number of "mutation operators" that produce them. we address this problem by finding a smaller subset of mutation operators, called "sufficient", that can model the behaviour of the full set. to do this, we provide an experimental procedure and adapt statistical techniques proposed for variable reduction, model selection and nonlinear regression. our preliminary results reveal interesting information about mutation operators.
analyzing medical processes. this paper shows how software engineering technologies used to define and analyze complex software systems can also be effective in detecting defects in human-intensive processes used to administer healthcare. the work described here builds upon earlier work demonstrating that healthcare processes can be defined precisely. this paper describes how finite-state verification can be used to help find defects in such processes as well as find errors in the process definitions and property specifications. the paper includes a detailed example, based upon a real-world process for transfusing blood, where the process defects that were found led to improvements in the process.
testing and analysis of access control policies. policy testing and analysis are important techniques for high assurance of correct specification of access control policies. we propose a set of testing and analysis techniques for access control policies and tools for empirically investigating and evaluating the proposed techniques. we propose a fault model for access control policies and investigate various fault types and their frequencies of occurrence in policy development; we develop a mutation testing framework that implements the fault model; we propose and investigate various coverage criteria for testing access control policies; we develop various test generation techniques and evaluate them using the coverage criteria and mutation testing framework; we develop a policy model to facilitate refactoring, performance optimizations, dependency identification, and other types of static analysis. to make our discussion concrete, we choose to present our techniques in the context of xacml. note that since xacml is an application-independent, generic access control policy language, our techniques can be equally applied to test policies written in other languages.
the effect of the number of inspectors on the defect estimates produced by capture-recapture models. inspections can be made more cost-effective by using capture-recapture methods to estimate post-inspection defects. previous capture-recapture studies of inspections used relatively small data sets compared with those used in biology and wildlife research (the origin of the models). a common belief is that capture-recapture models underestimate the number of defects but their performance can be improved with data from more inspectors. this increase has not been evaluated in detail. this paper evaluates new estimators from biology not been previously applied to inspections. using a data from seventy-three inspectors, we analyze the effect of the number of inspectors on the quality of estimates. contrary to previous findings indicating that jackknife is the best estimator, our results show that the sc estimators are better suited to software inspections. our results also provide a detailed analysis of the number of inspectors necessary to obtain estimates within 5% to 20% of the actual.
a data model to support end user software engineering. many end user programming tools such as spreadsheets and databases offer poor support for representing data at a level of abstraction that is intuitive to users. for example, users must work with "strings" rather than person names, phone numbers, or street addresses. as a result, validating and manipulating data is difficult. this thesis develops a new user-extensible model for semi-structured data items. each "tope" within this model defines how to recognize a kind of data item based on format and context, and how to transform that kind of item among valid formats. to show the usefulness of this model, we provide an environment to help end-user programmers to create, share, and apply topes, enabling these users to quickly implement data validation and reformatting functionality.
state extensions for java pathfinder. java pathfinder (jpf) is an explicit-state model checker for java programs. jpf implements a backtrackable java virtual machine (jvm) that provides non-deterministic choices and control over thread scheduling. jpf is itself implemented in java and runs on top of a host jvm. jpf represents the jvm state of the program being checked and performs three main operations on this state representation: bytecode execution, state backtracking, and state comparison. this paper summarizes four extensions that we have developed to the jpf state representation and operations. one extension provides a new functionality to jpf, and three extensions improve performance of jpf in various scenarios. some of our code has already been included in publicly available jpf.
a discreet, fault-tolerant, and scalable software architectural style for internet-sized networks. large networks, such as the internet, pose an ideal medium for solving computationally intensive problems, such as np-complete problems, yet no well-scaling architecture for internet-sized systems exists. i propose a software architectural style for large networks, based on a formal mathematical study of crystal growth that will exhibit properties of (1) discreetness (nodes on the network cannot learn the algorithm or input of the computation), (2) fault-tolerance (malicious, faulty, and unstable nodes cannot break the computation), and (3) scalability (communication among the nodes does not increase with network or problem size). i plan to evaluate the style both theoretically and empirically for these three properties.
breaking the barriers to successful refactoring: observations and tools for extract method. refactoring is the process of changing the structure of code without changing its behavior. refactoring can be semi-automated with tools, which should make it easier for programmers to refactor quickly and correctly. however, we have observed that many tools do a poor job of communicating errors triggered by the refactoring process and that programmers using them sometimes refactor slowly, conservatively, and incorrectly. in this paper we characterize problems with current refactoring tools, demonstrate three new tools to assist in refactoring, and report on a user study that compares these new tools against existing tools. the results of the study show that speed, accuracy, and user satisfaction can be significantly increased. from the new tools we induce a set of usability recommendations that we hope will help inspire a new generation of programmer-friendly refactoring tools.
adaptation hiding modularity for self-adaptive systems. growth in the complexity of computing systems, in the dynamism of the environments they operate in, and the need for timely adaptations as conditions change, now pose significant challenges for manual systems management and reconfiguration. there is thus increasing interest in systems that sense relevant conditions and adapt automatically as they change. a problem i have observed in designing such systems is that we lack principles and methods to guide their design. my thesis is that the modern notion of information hiding as a guide to modularization of software artifacts and design processes can be re-interpreted to provide a guide for organizing runtime structures and adaptation dynamics in self-adaptive systems. i argue that such an approach is important to achieving a number of key system properties, including scalability, analyzability, and efficiency. i plan to develop and evaluate my approach through a combination of case studies in a collaboration on self-adapting wireless sensor networks, by application to small, representative examples, and by arguments from first principles.
jpredictor: a predictive runtime analysis tool for java. jpredictor is a tool for detecting concurrency errors in java programs. the java program is instrumented to emit property-relevant events at runtime and then executed. the resulting execution trace is collected and analyzed by predictor, which extracts a causality relation sliced using static analysis and refined with lock-atomicity information. the resulting abstract model, a hybrid of a partial order and atomic blocks, is then exhaustively analyzed against the property and errors with counter-examples are reported to the user. thus, jpredictor can "predict" errors that did not happen in the observed execution, but which could have happened under a different thread scheduling. the analysis technique employed in jpredictor is fully automatic, generic (works for any trace property), sound (produces no false alarms) but it is incomplete may miss errors). two common types of errors are investigated in this paper: dataraces and atomicity violations. experiments show that jpredictor is precise (in its predictions), effective and efficient. after the code producing them was executed only once, jpredictor found all the errors reported by other tools. it also found errors missed by other tools, including static race detectors, as well as unknown errors in popular systems like tomcat and the apache ftp server.
adaptive probabilistic model for ranking code-based static analysis alerts. software engineers tend to repeat mistakes when developing software. automated static analysis tools can detect some of these mistakes early in the software process. however, these tools tend to generate a significant number of false positive alerts. due to the need for manual inspection of alerts, the high number of false positives may make an automated static analysis tool too costly to use. in this research, we propose to rank alerts generated from automated static analysis tools via an adaptive model that predicts the probability an alert is a true fault in a system. the model adapts based upon a history of the actions the software engineer has taken to either filter false positive alerts or fix true faults. we hypothesize that by providing this adaptive ranking, software engineers will be more likely to act upon highly ranked alerts until the probability that remaining alerts are true positives falls below a subjective threshold.
asam odx: syntax as semantics. in this paper, we outline a possible formalization of the semantics of the xml-based odx language. odx is a substantial part of the emerging automotive asam mcd standard, which describes a middleware layer between offboard diagnosis applications and onboard diagnosis services of electronic control units (ecus) of cars. the contribution of our work is threefold: firstly, a consequent application of our results can contribute to a well-structured development process in the automotive diagnosis domain. we are currently showing this in practice as part of our ongoing cooperation with the diagnosis department of audi ag. secondly, our proposition is the first step towards guaranteed standard-conformity of implementations of the mcd run-time system, also specified by the standard and strongly depending on odx and its semantics. last but not least, the paper can serve as an encouraging example of the application of formal methods in practice.
stakeholder value driven threat modeling for off the shelf based systems. as the trend of the usage of third party commercial-off-the-shelf (cots) and open source software continuously increases [2], cots security has become a major concern for many organizations whose daily business extensively relies upon a healthy it infrastructure. but, according to the 2006 csi/fbi computer criminal survey, 47% of the surveyed organizations only spent no more than 2% of the it budget in security. often, competing with limited it resources and the fast changing internet threats, the ability to prioritize security vulnerabilities and address them efficiently has become a critical success factor for every security manager.
predicting defects using network analysis on dependency graphs. in software development, resources for quality assurance are limited by time and by cost. in order to allocate resources effectively, managers need to rely on their experience backed by code complexity metrics. but often dependencies exist between various pieces of code over which managers may have little knowledge. these dependencies can be construed as a low level graph of the entire system. in this paper, we propose to use network analysis on these dependency graphs. this allows managers to identify central program units that are more likely to face defects. in our evaluation on windows server 2003, we found that the recall for models built from network measures is by 10% points higher than for models built from complexity metrics. in addition, network measures could identify 60% of the binaries that the windows developers considered as critical-twice as many as identified by complexity metrics.
modular-like transformations and style checking for crosscutting programming concepts. programmers resort to design patterns, micro-architectures, and other idioms when their design ideas can't be expressed directly in the programming language. the crosscutting code that appears as a result makes it harder to ensure a correct implementation of the idiom, and complicates software evolution when the idiom's implementation cannot be modularly substituted or extended like a method or class. we propose concepts, an ide-based mechanism for declaring, checking, and evolving crosscutting design idioms. programmers code their design idioms as before, but also declare their fundamental properties in supplemental files. a concept's behavior and implementation are described separately. this separation permits describing a new implementation for a concept and then having the concept tool mechanically transform the concept's current implementation into the new one. as a result we aim to get many of the same benefits for concepts that we get for classes: checking of key behaviors and substitutability.
a case study evaluation of maintainability and performance of persistency techniques. efforts for software evolution supersede any other part of the software life cycle. technological decisions have a major impact on the maintainability, but are not well reflected by existing code or architecture based metrics. the way the persistency of object structures with relational databases is solved affects the maintainability of the overall system. besides maintainability other quality attributes of the software are of interest, in particular performance metrics. however, a systematic evaluation of the benefits and drawback of different persistency frameworks is lacking. in this paper we systematically evaluate the maintainability and performance of different technological approaches for this mapping. the paper presents a testbed and an evaluation process with specifically designed metrics to evaluate persistency techniques regarding their maintainability and performance. in the second part we present and discuss the results of the case study.
assessing changeability by investigating the propagation of change types. we propose an approach to build a changeability assessment model for source code entities. based on this model, we will assess the changeability of evolving software systems. the changeability assessment is based on a taxonomy of more than 30 change types and a classifation of these in terms of change significance levels for consecutive versions of software entities. we consider change type propagation on different levels of granularity ranging from method changes to interface and class changes. we claim that this kind of assessment is effective in pointing to potential causes of maintainability problems in evolving software systems.
: factoring-aware inary daptation of evolving libraries. although in theory the apis of software libraries and frameworks should be stable, they change in practice. this forces clients of the library api to change as well, making software maintenance expensive. changing a client might not even be an option if its source code is missing or certain policies forbid its change. by giving a library both the old and the new api, clients can be shielded from api changes and can run with the new version of the library. this paper presents our solution and a tool, reba, that automatically generates compatibility layers between new library apis and old clients. in the first stage, reba generates another version of the library, called adapted-library, that supports both the old and the new apis. in the second stage, reba shrinks the adapted-library into a minimal, client-specific compatibility layer containing only classes truly required by the client. evaluations on controlled experiments and case studies using eclipse core libraries shows that our approach effectively adapts clients to new library versions, and is efficient.
using software model checking for software component certification. recently, the notion of a third-party certifier has emerged. the certifier ensures that the published properties of a component have indeed been verified. while software certification can benefit component buyers and developers, we believe that the lack of techniques and standards has hampered the spread of its use. this research seeks to accomplish two goals: to develop state-space search strategies that enable us to use software model checkers to certify programs and to decrease the amount of intellectual property that the developer is required to share for certification.
dysy: dynamic symbolic execution for invariant inference. dynamically discovering likely program invariants from concrete test executions has emerged as a highly promising software engineering technique. dynamic invariant inference has the advantage of succinctly summarizing both "expected" program inputs and the subset of program behaviors that is normal under those inputs. in this paper, we introduce a technique that can drastically increase the relevance of inferred invariants, or reduce the size of the test suite required to obtain good invariants. instead of falsifying invariants produced by pre-set patterns, we determine likely program invariants by combining the concrete execution of actual test cases with a simultaneous symbolic execution of the same tests. the symbolic execution produces abstract conditions over program variables that the concrete tests satisfy during their execution. in this way, we obtain the benefits of dynamic inference tools like daikon: the inferred invariants correspond to the observed program behaviors. at the same time, however, our inferred invariants are much more suited to the program at hand than daikon's hard-coded invariant patterns. the symbolic invariants are literally derived from the program text itself, with appropriate value substitutions as dictated by symbolic execution. we implemented our technique in the dysy tool, which utilizes a powerful symbolic execution and simplification engine. the results confirm the benefits of our approach. in daikon's prime example benchmark, we infer the majority of the interesting daikon invariants, while eliminating invariants that a human user is likely to consider irrelevant.
a quality-driven approach to enable decision-making in self-adaptive software. self-adaptive software is a closed-loop system aims at altering itself in response to changes at runtime. such a system, normally, requires monitoring, detecting (analyzing), deciding (planning), and acting (effecting) processes to fulfill adaptation requirements. this research mainly focuses on developing a quality-driven framework to facilitate realizing the deciding process. the framework is required to capture goals of adaptation, utility information, and domain characteristics in a knowledge-base.
an empirical study of software developers' management of dependencies and changes. different approaches and tools have been proposed to support change impact analysis, i.e., the identification of the potential consequences of a change, or the estimation of what needs to be modified to accomplish a change. however, just a few empirical studies of software developers' actual change impact analysis approaches have been reported in the literature. to minimize this gap, this paper describes an empirical study of two software development teams. it describes, through the presentation of ethnographic data, the strategies used by software developers to handle the effect of software dependencies and changes in their work. the concept of impact management is proposed as an analytical framework to present these practices and is used to suggest avenues for future research in change impact analysis techniques.
4th international workshop on mining software repositories (msr 2007). software repositories such as source control systems, defect tracking systems, and archived communications between project personnel are used to help manage the progress of software projects. software practitioners and researchers more and more recognize the potential benefit of mining this information to support the maintenance of software systems, improve software design/reuse, and empirically validate novel ideas and techniques. research is now proceeding to uncover the ways in which mining these repositories can help to understand software development, to support predictions about software development, and to plan various evolutionary aspects of software projects.
interval quality: relating customer-perceived quality to process quality. we investigate relationships among software quality measures commonly used to assess the value of a technology, and several aspects of customer perceived quality measured by interval quality (iq): a novel measure of the probability that a customer will observe a failure within a certain interval after software release. we integrate information from development and customer support systems to compare defect density measures and iq for six releases of a major telecommunications system. we find a surprising negative relationship between the traditional defect density and iq. the four years of use in several large telecommunication products demonstrates how a software organization can control customer perceived quality not just during development and verification, but also during deployment by changing the release rate strategy and by increasing the resources to correct field problems rapidly. such adaptive behavior can compensate for the variations in defect density between major and minor releases.
sharig and reusing architectural knowledge - architecture, rationale, and design intent. the shift of the software architecture community towards architectural knowledge has brought along some promising research directions. in this workshop we discuss the issues that lead to the application of architectural knowledge in research and industrial practice as well as presenting ongoing research and new ideas to advance the field. we expect to examine the state of the art and practice and gauge future challenges and trends. this year's workshop has a strong emphasis on documenting, sharing, and reusing architectural rationale and design intent.
automatic modularity conformance checking. according to parnas's information hiding principle and baldwin and clark's design rule theory, the key step to decomposing a system into modules is to determine the design rules (or in parnas's terms, interfaces) that decouple otherwise coupled design decisions and to hide decisions that are likely to change in independent modules. given a modular design, it is often difficult to determine whether and how its implementation realizes the designed modularity. manually comparing code with abstract design is tedious and error-prone. we present an automated approach to check the conformance of implemented modularity to designed modularity, using design structure matrices as a uniform representation for both. our experiments suggest that our approach has the potential to manifest the decoupling effects of design rules in code, and to detect modularity deviation caused by implementation faults. we also show that design and implementation models together provide a comprehensive view of modular structure that makes certain implicit dependencies within code explicit.
the 3rd international workshop on software engineering for secure systems sess07 - dependable and secure. the theme of this year of the international conference on software engineering is about "developing dependable software", acknowledging the fact that our lives depend directly on several complex software-based systems. the internet connects and enables a growing list of critical activities from which people expect services and revenues. they should be able to trust these systems to provide data and elaborations with a degree of confidentiality, integrity, and availability compatible with their needs. the pervasiveness of software products in the creation of critical infrastructures has raised the value of trustworthiness and new efforts should be dedicated to achieve it. yet, nowadays almost every application has some kind of security requirement even if its use is not to be considered critical.
modeling in software engineering. the software modeling community is primarily concerned with reducing the gap between problem and software implementation through the use of models that describe complex systems at multiple levels of abstraction and from a variety of perspectives. a model is an abstraction of some aspect of an existing or planned system. models are created to serve particular purposes, for example, to present a human-understandable description of some aspect of a system or to present information in a form that can be mechanically analyzed.
time will tell: fault localization using time spectra. we present an automatic fault localization technique which leverages time spectra as abstractions for program executions. time spectra have been traditionally used for performance debugging. by contrast, we use them for functional correctness debugging by identifying pieces of program code that take a "suspicious" amount of time to execute. the approach can be summarized as follows: time spectra are collected from passing and failing runs, observed behavior models are created using the time spectra collected from passing runs, and deviations from these models in failing runs are identified and scored as potential causes of failures. our empirical evaluations conducted on three real-life projects suggest that the proposed approach can effectively reduce the space of potential root causes for failures, which can in turn improve the turn around time for fixes.
3-step knowledge transition: a case study on architecture evaluation. software engineering is developing very fast. to keep up with the changes, software companies need effective methods of knowledge transfer. in the paper a 3-step approach to knowledge transfer, called technical drama, is presented. the paper is focused on transferring knowledge concerning architecture evaluation, but the approach could also be applied to transferring knowledge concerning inspections, testing etc. it is claimed in the paper that the technical drama can be useful in the industrial context (two case studies are described) as well as at university (then a kind of software studio is required).
early aspects at icse 2007: workshop on aspect-oriented requirements engineering and architecture design. the "early aspects @ icse'07" is the 11th workshop in the series of early aspects workshops [1] which focuses on aspect identification during the requirements engineering and architecture derivation activities. the specific aim of the present workshop is twofold: (a) to initiate creation of an early aspects application demonstration and comparisons benchmark; and (b) to solicit submission of new research.
evaluating dependability attributes of component-based specifications. component-based development (cbd) is established in many application domains. there is a strong trend in applying the same approach in different domains of dependable systems. however, a precondition of a successful use of cbd in these domains is the utilization of theories, methods and technologies to predict and evaluate dependability attributes. this tutorial gives an analysis of current methodologies of attribute-specific evaluation methods for dependable component-based systems. we identify limitations of the current technologies, discusses existing and possible new solutions to overcome these limitations both from a research-oriented and practical perspective.
juzi: a tool for repairing complex data structures. this paper describes juzi, a tool for automatic repair of complex data structures. juzi takes a java class representing the data structure as well as a predicate method that specifies the structural integrity constraints as inputs. juzi instruments its inputs and generates a new java class which behaves similarly to the original class, yet automatically repairs itself when the structural integrity constraints are violated. juzi implements a novel repair algorithm. given a structure that violates its integrity constraints, juzi performs a systematic search based on symbolic execution to repair the structure, i.e., mutate it such that the resulting structure satisfies the given constraints. experiments on structures ranging from library classes to standalone applications, show that juzi repairs complex structures while enabling programs to recover from erroneous executions caused by data structure corruptions.
metamodel-based tool integration with moflon. nowadays, a typical software development process involves many developers which participate in the development process by using a wide variety of development tools. as a consequence, the data representing the project as a whole is distributed over different development tools. for the purpose of consistency, maintainability, and traceability it is an essential task to be aware of the relationships between semantic equivalent data in different tool repositories. the real-time systems lab at the technische universität darmstadt performs research in the area of tool and metamodel integration to provide solutions to overcome this gap. in this demonstration we present the metamodeling framework moflon that addresses these issues by bringing together the latest omg standards with graph transformations and triple graph grammars. using moflon, developers can generate code for specific tools needed to perform analysis and transformation on one development tool or to incrementally integrate data of different modeling tools.
tracking source locations. many programming tools require information to be associated with source locations. current tools do this in different ways with different degrees of effectiveness. this paper is an investigation into the various approaches to maintaining source locations. it is based on an experiment that attempts to track a variety of locations over the evolution of a source file. the results demonstrate that relatively simple techniques can be very effective.
testing pervasive software in the presence of context inconsistency resolution services. pervasive computing software adapts its behavior according to the changing contexts. nevertheless, contexts are often noisy. context inconsistency resolution provides a cleaner pervasive computing environment to context-aware applications. a faulty context-aware application may, however, mistakenly mix up inconsistent contexts and resolved ones, causing incorrect results. this paper studies how such faulty context-aware applications may be affected by these services. we model how programs should handle contexts that are continually checked and resolved by context inconsistency resolution, develop novel sets of data flow equations to analyze the potential impacts, and thus formulate a new family of test adequacy criteria for testing these applications. experimentation shows that our approach is promising.
a language for advanced protocol analysis in automotive networks. the increased use and interconnection of electronic components in automobiles has made communication behavior in automotive networks drastically more complex. both communication designs at application level and complex communication scenarios are often under-specified or out of scope of existing analysis techniques. we extend traditional protocol analyzers in order to capture communication at the level of abstraction that reflects application design and show that the same technique can be used to specify, monitor and test complex scenarios. we present cfr (channel filter rule) models, a novel approach for the specification of analyzers and a domain-specific language that implements this approach. from cfr models, we can fully generate powerful analyzers that extract design intentions, abstract protocol layers and even complex scenarios from low level communication data. we show that three basic concepts (channels, filters and rules) are sufficient to build such powerful analyzers and identify possible areas of application.
calysto: scalable and precise extended static checking. automatically detecting bugs in programs has been a long-held goal in software engineering. many techniques exist, trading-off varying levels of automation, thoroughness of coverage of program behavior, precision of analysis, and scalability to large code bases. this paper presents the calysto static checker, which achieves an unprecedented combination of precision and scalability in a completely automatic extended static checker. calysto is interprocedurally path-sensitive, fully context-sensitive, and bit-accurate in modeling data operations --- comparable coverage and precision to very expensive formal analyses --- yet scales comparably to the leading, less precise, static-analysis-based tool for similar properties. using calysto, we have discovered dozens of bugs, completely automatically, in hundreds of thousands of lines of production, open-source applications, with a very low rate of false error reports. this paper presents the design decisions, algorithms, and optimizations behind calysto's performance.
analyzing model evolution. model-driven development leads to development processes in which a large number of different versions of models are produced. we present fame, a tool environment which enables fine-grained analysis of the version history of a model. the tool is generic in the sense that it can work with various model types including uml and domain-specific languages.
ahaa --agile, hybrid assessment method for automotive, safety critical smes. the need for software is increasingly growing in the automotive industry. software development projects are, however, often troubled by time and budget overruns, resulting in systems that do not fulfill customer requirements. both research and industry lack strategies to combine reducing the long software development lifecycles (as required by time-to-market demands) with increasing the quality of the software developed. software process improvement (spi) provides the first step in the move towards software quality, and assessments are a vital part of this process. unfortunately, software process assessments are often expensive and time consuming. additionally, they often provide companies with a long list of issues without providing realistic suggestions. the goal of this paper is to describe a new low-overhead assessment method that has been designed specifically for small-to-medium-sized (smes) organisations wishing to be automotive software suppliers. this assessment method integrates the structured-ness of the plan-driven spi models of capability maturity model integration (cmmi) and automotive spice with the flexibleness of agile practices.
rubacon: automated support for model-based compliance engineering. compliance frameworks, laws and regulations such as sarbanes oxley, basel ii, solvency ii, hipaa etc. demand from companies in a more and more rigorous way to demonstrate that their organisation, processes and supporting it landscape implement and follow a set of guidelines at differing levels of abstraction. the work presented in this paper aims to contribute to a software engineering process which is driven by security, risk and compliance management considerations. we concentrate on a part of this approach that focusses on the question how one can use software engineering methods and tools to enforce that the configuration of a system enforces the security policies that arise from business compliance regulations. we present tool support for model-based compliance engineering, i.e. for the model-based development and analysis of software configurations that ensures compliance with security policies. it allows one to check uml models of business applications and their configuration data for adherence to security policies and compliance requirements. the tool is based on standardized data formats, such as uml and xml, which makes its integration into existing business architectures as efficient as possible.
models for model's sake: why explicit system models are also an end to themselves. in automotive software and system design, explicit system and especially software models have only recently found their way into the development process. this paper will try to give an overview for what such models have so-far been used and which advantages they brought to vehicle manufacturers and suppliers. another focus of this paper is the comparison to functional models which are already used in the automotive industry to define control algorithms and function implementation. in many cases too strong analogies have been seen between the existing functional control algorithm models and the new system models - leading to suboptimal development processes and tools. this paper will therefore try to outline differences between these model types. finally, a synthesis between functional, system, and software models will be sketched.
an approach to detecting duplicate bug reports using natural language and execution information. an open source project typically maintains an open bug repository so that bug reports from all over the world can be gathered. when a new bug report is submitted to the repository, a person, called a triager, examines whether it is a duplicate of an existing bug report. if it is, the triager marks it as duplicate and the bug report is removed from consideration for further work. in the literature, there are approaches exploiting only natural language information to detect duplicate bug reports. in this paper we present a new approach that further involves execution information. in our approach, when a new bug report arrives, its natural language information and execution information are compared with those of the existing bug reports. then, a small number of existing bug reports are suggested to the triager as the most similar bug reports to the new bug report. finally, the triager examines the suggested bug reports to determine whether the new bug report duplicates an existing bug report. we calibrated our approach on a subset of the eclipse bug repository and evaluated our approach on a subset of the firefox bug repository. the experimental results show that our approach can detect 67%-93% of duplicate bug reports in the firefox bug repository, compared to 43%-72% using natural language information alone.
the influence of organizational structure on software quality: an empirical case study. often software systems are developed by organizations consisting of many teams of individuals working together. brooks states in the mythical man month book that product quality is strongly affected by organization structure. unfortunately there has been little empirical evidence to date to substantiate this assertion. in this paper we present a metric scheme to quantify organizational complexity, in relation to the product development process to identify if the metrics impact failure-proneness. in our case study, the organizational metrics when applied to data from windows vista were statistically significant predictors of failure-proneness. the precision and recall measures for identifying failure-prone binaries, using the organizational metrics, was significantly higher than using traditional metrics like churn, complexity, coverage, dependencies, and pre-release bug measures that have been used to date to predict failure-proneness. our results provide empirical evidence that the organizational metrics are related to, and are effective predictors of failure-proneness.
automatic generation of software behavioral models. dynamic analysis of software systems produces behavioral models that are useful for analysis, verification and testing. the main techniques for extracting models of functional behavior generate either models of constraints on data, usually in the form of boolean expressions, or models of interactions between components, usually in the form of finite state machines. both data and interaction models are useful for analyzing and verifying different aspects of software behavior, but none of them captures the complex interplay between data values and components interactions. thus related analysis and testing techniques can miss important information. in this paper, we focus on the generation of models of relations between data values and component interactions, and we present gk-tail, a technique to automatically generate extended finite state machines (efsms) from interaction traces. efsms model the interplay between data values and component interactions by annotating fsm edges with conditions on data values. we show that efsms include details that are not captured by either boolean expressions or (classic) fsm alone, and allow for more accurate analysis and verification than separate models, even if considered jointly.
a teamwork-based approach to programming fundamentals with scheme, smalltalk & java. in october 2004 the university of lugano in southern switzerland established a new faculty of informatics. its founding principles are innovation in teaching and faculty participation in the research community. with respect to teaching, students spend mornings attending lectures and afternoons in an atelier designed to support interaction both among students and with the instructors. in teaching the first year "programming fundamentals" courses, we took advantage of the clean slate nature of the faculty to introduce innovative teaching elements. the novel aspects include our use of scheme, smalltalk, and java, our combination of individual, pair and group projects and the integration of expert lectures to introduce useful, but slightly orthogonal elements at key points in the semester. our very positive experience is reported along with a discussion of aspects to improve in the future.
four enhancements to automateddistributed system experimentation methods. experimentation is an essential tool employed by the developers of software systems, especially distributed systems. in prior work we developed a model-driven framework for automating various experimentation tasks, such as workload generation, and demonstrated that it gives the engineer a cost-effective means to conduct large-scale experiments on distributed testbeds. we have enhanced the methods underlying the framework in four significant ways: (1) increasing the expressiveness of workloads by allowing for conditional and reactive behaviors; (2) supporting the repeatability of experiments through the creation of environment workloads that can control the operational context; (3) enabling the composability of application and environment workloads to obtain a broader class of experiments; and (4) extending the scope of experiment management to include control over multiple runs. we use the enhancements to conduct a series of interesting new experiments. specifically, the enhancements allow us to manipulate a fixed-wired testbed so that it simulates a mobile-wireless environment, and to selectively and maliciously inject faults into a system.
granularity in software product lines. building software product lines (spls) with features is a challenging task. many spl implementations support features with coarse granularity - e.g., the ability to add and wrap entire methods. however, fine-grained extensions, like adding a statement in the middle of a method, either require intricate workarounds or obfuscate the base code with annotations. though many spls can and have been implemented with the coarse granularity of existing approaches, fine-grained extensions are essential when extracting features from legacy applications. furthermore, also some existing spls could benefit from fine-grained extensions to reduce code replication or improve readability. in this paper, we analyze the effects of feature granularity in spls and present a tool, called colored ide (cide), that allows features to implement coarse-grained and fine-grained extensions in a concise way. in two case studies, we show how cide simplifies spl development compared to traditional approaches.
tool support for the navigation in graphical models. graphical models are omnipresent in the software engineering field, but most current graphical modeling languages do not scale with the increasing size and complexity of today's systems. the navigation in the diagrams becomes a major problem especially if different aspects of the system are scattered over multiple, only loosely coupled diagrams. in this paper we present the hierarchical navigation capabilities of the adora modeling tool. the user of this tool can freely control the level of detail in different parts of the model to reduce the size and complexity of the diagrams being displayed. our fisheye visualization technique makes it possible to integrate all modeling aspects (structure, data, behavior, etc.) in one coherent model while keeping the size and complexity of the diagrams within reasonable limits.
design patterns: between programming and software design. in computer science curricula the two areas programming and software engineering are usually separated. in programming students learn an object oriented language and then deepen their knowledge in other languages, algorithms and data structures. on the other hand software engineering starts with discussing processes and then addresses topics like requirements engineering, software design and software architectures. design patterns are on the border of these two areas and can be covered from both sides: either as an advanced programming course or as an application of software design and micro architectures. in this paper we present courses on design patterns and on software design which try to bridge this gap.
artoo: adaptive random testing for object-oriented software. intuition is often not a good guide to know which testing strategies will work best. there is no substitute for experimental analysis based on objective criteria: how many faults a strategy finds, and how fast. "random" testing is an example of an idea that intuitively seems simplistic or even dumb, but when assessed through such criteria can yield better results than seemingly smarter strategies. the efficiency of random testing is improved if the generated inputs are evenly spread across the input domain. this is the idea of adaptive random testing (art). art was initially proposed for numerical inputs, on which a notion of distance is immediately available. to extend the ideas to the testing of object-oriented software, we have developed a notion of distance between objects and a new testing strategy called artoo, which selects as inputs objects that have the highest average distance to those already used as test inputs. artoo has been implemented as part of a tool for automated testing of object-oriented software. we present the artoo concepts, their implementation, and a set of experimental results of its application. analysis of the results shows in particular that, compared to a directed random strategy, artoo reduces the number of tests generated until the first fault is found, in some cases by as much as two orders of magnitude. artoo also uncovers faults that the random strategy does not find in the time allotted, and its performance is more predictable.
predicting accurate and actionable static analysis warnings: an experimental approach. static analysis tools report software defects that may or may not be detected by other verification methods. two challenges complicating the adoption of these tools are spurious false positive warnings and legitimate warnings that are not acted on. this paper reports automated support to help address these challenges using logistic regression models that predict the foregoing types of warnings from signals in the warnings and implicated code. because examining many potential signaling factors in large software development settings can be expensive, we use a screening methodology to quickly discard factors with low predictive power and cost-effectively build predictive models. our empirical evaluation indicates that these models can achieve high accuracy in predicting accurate and actionable static analysis warnings, and suggests that the models are competitive with alternative models built without screening.
using the inverted classroom to teach software engineering. an inverted classroom is a teaching environment that mixes the use of technology with hands-on activities. in an inverted classroom, typical in-class lecture time is replaced with laboratory and in-class activities. outside class time, lectures are delivered over some other medium such as video on-demand. in a three credit hour course for instance, contact hours are spent having students actively engaged in learning activities. outside of class, students are focused on viewing 3-6 hours of lectures per week. additional time outside of class is spent completing learning activities. in this paper we present the inverted classroom model in the context of a software engineering curriculum. the paper motivates the use of the inverted classroom and suggests how different courses from the software engineering 2004 model curriculum volume can incorporate the use of the inverted classroom. in addition, we present the results of a pilot course that utilized the inverted classroom model at miami university and describe courses that are currently in process of piloting its use.
an empirical study of the effects of test-suite reduction on fault localization. fault-localization techniques that utilize information about all test cases in a test suite have been presented. these techniques use various approaches to identify the likely faulty part(s) of a program, based on information about the execution of the program with the test suite. researchers have begun to investigate the impact that the composition of the test suite has on the effectiveness of these fault-localization techniques. in this paper, we present the first experiment on one aspect of test-suite composition--test-suite reduction. our experiment studies the impact of the test-suite reduction on the effectiveness of fault-localization techniques. in our experiment, we apply 10 test-suite reduction strategies to test suites for eight subject programs. we then measure the differences between the effectiveness of four existing fault-localization techniques on the unreduced and reduced test suites. we also measure the reduction in test-suite size of the 10 test-suite reduction strategies. our experiment shows that fault-localization effectiveness varies depending on the test-suite reduction strategy used, and it demonstrates the trade-offs between test-suite reduction and fault-localization effectiveness.
formal verification of an automotive scenario in service-oriented computing. we report on the successful application of academic experience with formal modelling and verification techniques to an automotive scenario from the service-oriented computing domain. the aim of this industrial case study is to verify a priori, thus before implementation, certain design issues. the specific scenario is a simplified version of one of possible new services for car drivers to be provided by the in-vehicle computers.
genie: supporting the model driven development of reflective, component-based adaptive systems. engineering adaptive software is an increasingly complex task. here, we demonstrate genie, a tool that supports the modelling, generation, and operation of highly reconfigurable, component-based systems. we showcase how genie is used in two case-studies: i) the development and operation of an adaptive flood warning system, and ii) a service discovery application. in this context, adaptation is enabled by the gridkit reflective middleware platform.
ws-amuse - web service architecture for multimedia services. recently, a move from traditional, network specific multimedia services to ip-based solutions could be observed. although many of these applications have similar requirements and address the same issues, individual solutions based on specialized protocols are commonly used. this specialization prohibits the extraction and reuse of common services and hinders the interoperability between services and the integration with external components. a promising approach to overcome these disadvantages is the adoption of the service-oriented paradigm in communication protocols and a modularization into cooperating services. in this paper, we present a generic framework for multimedia applications consisting of a set of reusable web service components, a modeling language based on finite state automata and a compiler. the results of a bpel based prototypical implementation of a voice-over-ip application show that the service oriented approach and the automaton based modeling language can satisfy the above mentioned criteria and ease application development through a higher level of abstraction. on the other hand our benchmarks indicate that current web service technologies can lead to an insufficient performance, depending on the application scenario. possible solutions to circumvent these deficiencies are presented at the end of the paper.
from programming to modeling: our experience with a distributed software engineering course. distributed software engineering (dse) concepts in computer science (or engineering) degrees are commonly introduced using a hands-on approach mainly consisting of teaching a particular distributed and component-based technology platform (such as java enterprise edition or microsoft .net) and proposing the students to develop a small distributed software application with it. though this approach provides the students with some relevant practical knowledge, we believe that it is not the most appropriate way of teaching all the concepts and particularities of dse. thus, in this paper we report on our experience of redesigning an initial dse course following a model-based approach. by raising the level of abstraction we gained modularity, separation of concerns and technology independence, while making the course evolve according to the latest trends in software development methods.
mining framework usage changes from instantiation code. framework evolution may break existing users, which need to be migrated to the new framework version. this is a tedious and error-prone process that benefits from automation. existing approaches compare two versions of the framework code in order to find changes caused by refactorings. however, other kinds of changes exist, which are relevant for the migration. in this paper, we propose to mine framework usage change rules from already ported instantiations, the latter being applications build on top of the framework, or test cases maintained by the framework developers. our evaluation shows that our approach finds usage changes not only caused by refactorings, but also by conceptual changes within the framework. further, it copes well with some issues that plague tools focusing on finding refactorings such as deprecated program elements or multiple changes applied to a single program element.
symbolic mining of temporal specifications. program specifications are important in many phases of the software development process, but they are often omitted or incomplete. an important class of specifications takes the form of temporal properties that prescribe proper usage of components of a software system. recent work has focused on the automated inference of temporal specifications from the static or runtime behavior of programs. many techniques match a specification pattern (represented by a finite state automaton) to all possible combinations of program components and enumerate the possible matches. such approaches suffer from high space complexity and have not scaled beyond simple, two-letter alternating patterns (e.g. (ab)*). in this paper, we precisely define this form of specification mining and show that its general form is np-complete. we observe a great deal of regularity in the representation and tracking of all possible combinations of system components. this motivates us to introduce a symbolic algorithm, based on binary decision diagrams (bdds), that exploits this regularity. our results show that this symbolic approach expands the tractability of this problem by orders of magnitude in both time and space. it enables us to mine more complex specifications, such as the common three-letter resource acquisition, usage, and release pattern ((ab+c)*). we have implemented our algorithm in a practical tool and used it to find significant specifications in real systems, including apache ant and hibernate. we then used these specifications to find previously unknown bugs.
data flow testing of service-oriented workflow applications. ws-bpel applications are a kind of service-oriented application. they use xpath extensively to integrate loosely-coupled workflow steps. however, xpath may extract wrong data from the xml messages received, resulting in erroneous results in the integrated process. surprisingly, although xpath plays a key role in workflow integration, inadequate researches have been conducted to address the important issues in software testing. this paper tackles the problem. it also demonstrates a novel transformation strategy to construct artifacts. we use the mathematical definitions of xpath constructs as rewriting rules, and propose a data structure called xpath rewriting graph (xrg), which not only models how an xpath is conceptually rewritten but also tracks individual rewritings progressively. we treat the mathematical variables in the applied rewriting rules as if they were program variables, and use them to analyze how information may be rewritten in an xpath conceptually. we thus develop an algorithm to construct xrgs and a novel family of data flow testing criteria to test ws-bpel applications. experiment results show that our testing approach is promising.
time-bounded adaptation for automotive system software. software is increasingly deployed in vehicles as demand for new functionality increases and cheaper and more powerful hardware becomes available. likewise, emerging wireless communication protocols allow the integration of new software into vehicles, thereby enabling time-bounded adaptive response to changes that occur in mobile environments. examples of time-bounded adaptation include adaptive cruise control and the dynamic integration of location-aware services within fixed time bounds. this paper provides three contributions to the study of time-bounded adaptation for automotive system software. first, we categorise automotive systems with respect to requirements for dynamic software adaptation. second, we define a taxonomy that captures various dimensions of dynamic adaptation in emerging automotive system software. third, we use this taxonomy to analyse existing research projects in the automotive domain. our analysis shows that although time-bounded synchronisation of applications and data is a key requirement for next-generation automotive systems, it is not adequately covered by existing work.
seurat: integrated rationale management. a completed software product is the end result of many decisions that must be made throughout the development lifecycle. unfortunately, the rationale for these decisions is usually not captured and is therefore lost. the software using rationale (seurat) system integrates with the eclipse interactive development environment to support rationale capture and use. in addition to presenting the rationale to the developer/maintainer as needed, seurat also supports requirements traceability and impact assessment.
answering conceptual queries with ferret. programmers seek to answer questions as they investigate the functioning of a software system, such as "which execution path is being taken in this case?" programmers attempt to answer these questions, which we call conceptual queries, using a variety of tools. each type of tool typically highlights one kind of information about the system, such as static structural information or control-flow information. unfortunately for the programmer, the tools seldom directly answer the programmer's conceptual queries. instead, the programmer must piece together results from different tools to determine an answer to the initial query. at best, this process is time consuming and at worst, this process can lead to data overload and disorientation. in this paper, we present a model that supports the integration of different sources of information about a program. this model enables the results of concrete queries in separate tools to be brought together to directly answer many of a programmer's conceptual queries. in addition to presenting this model, we present a tool that implements the model, demonstrate the range of conceptual queries supported by this tool, and present the results of use of the conceptual queries in a small field study.
power through brokering: open source community participation in software engineering student projects. many software engineering projects use open source software tools or components. the project team's active participation in the open source community may be necessary for the team to use the technology. based on an in-depth field study of industry software engineering project students interacting with an open source community, we find that participation in the community may affect the team's work and learning by strengthening the power of the broker between the team and the community. we outline pitfalls and benefits of having student teams acquire development-related knowledge from open source communities. the findings are relevant to the organization and supervision of software engineering student projects interacting with open source communities.
applying model-based testing to healthcare products: preliminary experiences. healthcare software systems are becoming more and more complex since they will be highly integrated to support a wide variety of healthcare workflows (e.g., financial, administration, diagnosis, and treatment). in addition, healthcare software systems will be more safety-critical as they will provide medical decision support for doctors. all of those require systematic and thorough testing of the systems before they are put into use or upgraded. model-based testing (mbt) is an approach to apply formal, explicit system use-models to generate the test cases for testing the system behaviors under different input data sets. this paper describes our experiences in applying this approach to testing some siemens healthcare software systems. we will report the benefits and challenges in using mbt for testing healthcare software systems.
are fit tables really talking?: a series of experiments to understand whether fit tables are useful during evolution tasks. test-driven software development tackles the problem of operationally defining the features to be implemented by means of test cases. this approach was recently ported to the early development phase, when requirements are gathered and clarified. among the existing proposals, fit (framework for integrated testing) supports the precise specification of requirements by means of so called fit tables, which express relevant usage scenarios in a tabular format, easily understood also by the customer. fit tables can be turned into executable test cases through the creation of pieces of glue code, called fixtures. in this paper, we test the claimed benefits of fit through a series of three controlled experiments in which fit tables and related fixtures are used to clarify a set of change requirements, in a software evolution scenario. results indicate improved correctness achieved with no significant impact on time, however benefits of fit vary in a substantial way depending on the developers' experience. preliminary results on the usage of fit in combination with pair programming revealed another relevant source of variation.
using components for architecture-based management: the self-repair case. components are widely used for managing distributed applications because they not only capture the software architecture of managed applications as an assembly of components but also permit to dynamically adapt these applications to changing environments. following this approach, our practical experience in the jade environment about developing an autonomic repair management service with a self-healing behavior shows novel requirements on reflective component models for architecture-based management systems. first, we have identified five essential runtime abstractions that a component model must include in order to efficiently support an autonomic repair service. second, our experience suggests that traditional reflective component models should be extended to allow specializing meta-operations. third, our experience also shows that a meta-data checkpointing capability is best-suited for meta-data recovery after failures. we demonstrate the soundness of these findings in several ways. we applied the difficult problem of autonomic repair to both j2ee and jms middleware. we further stressed our algorithms and mechanisms by applying them recursively towards gaining a self-healing property for the repair service itself. although our experience was done in the jade context, using the fractal component model, we believe our findings to be general to architecture-based management systems using reflective component
open source software peer review practices: a case study of the apache server. peer review is seen as an important quality assurance mechanism in both industrial development and the open source software (oss) community. the techniques for performing inspections have been well studied in industry; in oss development, peer reviews are less well understood. we examine the two peer review techniques used by the successful, mature apache server project: review-then-commit and commit-then-review. using archival records of email discussion and version control repositories, we construct a series of metrics that produces measures similar to those used in traditional inspection experiments. specifically, we measure the frequency of review, the level of participation in reviews, the size of the artifact under review, the calendar time to perform a review, and the number of reviews that find defects. we provide a comparison of the two apache review techniques as well as a comparison of apache review to inspection in an industrial project. we conclude that apache reviews can be described as (1) early, frequent reviews (2) of small, independent, complete contributions (3) conducted asynchronously by a potentially large, but actually small, group of self-selected experts (4) leading to an efficient and effective peer review technique.
global consistency checking of distributed models with tremer+. we present tremer+, a tool for consistency checking of distributed models (i.e., models developed by distributed teams). tremer+ works by first constructing a merged model before checking consistency. this enables a flexible way of verifying global consistency properties that is not possible with other existing tools.
rational quality requirements for medical software. in this paper we discuss the challenges of software quality for medical software and present some ideas for improving medical software quality requirements through software engineering methods. we apply the quality requirements engineering method moqare to elicit specific quality requirements for an imaginary drug advisory system and report our lessons learned.
impact analysis of database schema changes. we propose static program analysis techniques for identifying the impact of relational database schema changes upon object-oriented applications. we use dataflow analysis to extract all possible database interactions that an application may make. we then use this information to predict the effects of schema change. we evaluate our approach with a case-study of a commercially available content management system, where we investigated 62 versions of between 70k-127k loc and a schema size of up to 101 tables and 568 stored procedures. we demonstrate that the program analysis must be more precise, in terms of context-sensitivity than related work. however, increasing the precision of this analysis increases the computational cost. we use program slicing to reduce the size of the program that needs to be analyzed. using this approach, we are able to analyse the case study in under 2 minutes on a standard desktop machine, with no false negatives and a low level of false positives.
detecting model inconsistency through operation-based model construction. nowadays, large-scale industrial software systems may involve hundreds of developers working on hundreds of different but related models representing parts of the same system specification. detecting and resolving structural inconsistencies between these models is then critical. in this article we propose to represent models by sequences of elementary construction operations, rather than by the set of model elements they contain. structural and methodological consistency rules can then be expressed uniformly as logical constraints on such sequences. our approach is meta-model independent, allowing us to deal with consistency between different models whatever their kind. we have validated our approach by building a prolog engine that detects violations of structural and methodological constraints specified on uml 2.1 models and requirement models. this engine has been integrated into two contemporary uml-based modelling environments, eclipse emf and rational software architect (rsa).
recommending adaptive changes for framework evolution. in the course of a framework's evolution, changes ranging from a simple refactoring to a complete rearchitecture can break client programs. finding suitable replacements for framework elements that were accessed by a client program and deleted as part of the framework's evolution can be a challenging task. we present a recommendation system, semdiff, that suggests adaptations to client programs by analyzing how a framework adapts to its own changes. in a study of the evolution of the eclipse jdt framework and three client programs, our approach recommended relevant adaptive changes with a high level of precision, and detected non-trivial changes typically undiscovered by current refactoring detection techniques.
tool support for data validation by end-user programmers. end-user programming tools for creating spreadsheets and webforms offer no data types except "string" for storing many kinds of data, such as person names and street addresses. consequently, these tools cannot automatically validate these data. to address this problem, we have developed a new userextensible model for string-like data. each "tope" in this model is a user-defined abstraction that guides the interpretation of strings as a particular kind of data, such as a mailing address. specifically, each tope implementation contains software functions for recognizing and reformatting that tope's kind of data. with our tools, end-user programmers define new topes and associate them with fields in spreadsheets, webforms, and other programs. this makes it possible at runtime to distinguish between invalid data, valid data, and questionable data that could be valid or invalid. once identified, questionable and/or invalid data can be double-checked and possibly corrected, thereby increasing the overall reliability of the data.
mulit-level system integration based on autosar. the design of distributed embedded real-time system is a challenging task. besides solving the control-engineering issues, one has to consider real-time scheduling, reliability and production requirements w.r.t. production cost of the electronic control unit (ecu). this has a considerable impact on the employed software design techniques. these design techniques are well known in the automotive software industry, but are applied with different flavors at each vehicle manufacturer and their suppliers. this situation has changed considerably with the results of the autosar development partnership, which unifies the flavors of automotive software design. automotive software design is embedded in the so-called v-cycle of embedded automotive system development[1]. it starts with the requirements analysis which results later on in a model of the control algorithm. the control algorithm is tested against a vehicle model and establishes the topmost level in system integration. the second system integration level is the adaptation of the control algorithm to be run on a rapid-prototyping system. the rapid-prototyping system is integrated into an existing e/earchitecture. the e/e-architecture consists of the ecus connected by networks like can or flexray and gateways. sensors- and actuators being used by several control algorithms are coupled to an ecu, which might propagate signals to other ecus via a vehicle network. from the software point of view, the controlalgorithm has now to respect real-time scheduling and the quantization of the sensor- and actuator signals, no matter whether these signals are generated on the rapid-prototyping system or exchanged via the bus with other ecus. further development steps in the v-cycle are the software implementation, the ecu- and the network integration. the integrated ecus and networks are tested against vehicle models running on hardware-in-the-loop (hil) systems. if this works fine, the ecus are integrated in the real vehicle for calibration. the software implementation and the ecu integration are deeply influenced by autosar. autosar is a development partnership of all stakeholders in the automotive software development (e.g. vehicle manufacturers and their suppliers) which unifies several software implementation techniques[2]. it describes a common ecu software architecture[3] consisting of configurable basic software modules (bsw), a runtime environment (rte) and a software component description[4]. the software component description describes the interfaces for dataexchange as well as the access points for the rte. the basic idea of consisting of interconnected software components which are later mapped to an e/e-architecture. currently, the vfb structure of autosar software architectures is mainly driven by the next generation e/e-architectures. the vfb structure forms the third system integration level. the next integration step into an autosar environment is the integration of the rapid-prototyping tested control algorithm to autosar software components. since most vfb descriptions use fixed-point interfaces, the control algorithm has to be transformed to fixed-point arithmetic. if the control algorithm is modelled in tools like ascet, this conversion can be achieved by code-generation. the same holds true for control algorithms already being used in e/e-architectures without an autosar software architecture. the vfb-description with the control-algorithms forms the fourth system integration level, which can be simulated with plant-models on a pc by tools like intecrio-vp. the fifth system integration level is given by the mapping process as defined in the autosar methodology[5] and requires the configuration of the rte and the bsw modules for a single ecu. at this integration level, one can perform hil testing and calibration in the same way as for non-autosar systems. several evaluation projects, e.g. [6] and [7], have shown that the multi-level integration approach is feasible to guide the configuration capabilities of autosar software architectures.
best practices in extreme programming course design. teaching (and therefore learning) extreme programming (xp) in a university setting is difficult because of course time limitations and the soft nature of xp that requires first-hand experience in order to see and really learn the methods. for example, iterations are either shorter or fewer than appropriate. in this paper we present the properties to tune when designing an extreme programming course. these are the properties we gathered by conducting three xp labs as part of our software engineering teaching. within this paper we describe our set-up as well as the important properties. lecturers and teachers can use this property system and combine it with their own constraints in order to derive a better xp lab for their curriculum.
clone detection in automotive model-based development. model-based development is becoming an increasingly common development methodology. in important domains like embedded systems already major parts of the code are generated from models specified with domain-specific modelling languages. hence, such models are nowadays an integral part of the software development and maintenance process and therefore have a major economic and strategic value for the software-developing organisations. nevertheless almost no work has been done on a quality defect that is known to seriously hamper maintenance productivity in classic code-based development: cloning. this paper presents an approach for the automatic detection of clones in large models as they are used in model-based development of control systems. the approach is based on graph theory and hence can be applied to most graphical data-flow languages. an industrial case study demonstrates the applicability of our approach for the detection of clones in matlab/simulink models that are widely used in model-based development of embedded systems in the automotive domain.
specification patterns for probabilistic quality properties. probabilistic verification techniques are a powerful means to ensure that a software-intensive system fulfills its quality requirements. to apply these techniques an accurate specification of the required properties in a probabilistic temporal logic is necessary. to help practitioners formulate these properties correctly, this paper presents a specification pattern system of common probabilistic properties called proprost. this pattern system has been a developed based on a survey of 152 properties from academic examples and 48 properties of real-word quality requirements from avionic, defence and automotive systems. furthermore, a structured english grammar that can guide in the specification of probabilistic properties is given. similar to previous specification patterns for traditional and real-time properties, the presented specification pattern system and the structured english grammar captures expert knowledge and helps practitioners to correctly apply formal verification techniques.
sufficient mutation operators for measuring test effectiveness. mutants are automatically-generated, possibly faulty variants of programs. the mutation adequacy ratio of a test suite is the ratio of non-equivalent mutants it is able to identify to the total number of non-equivalent mutants. this ratio can be used as a measure of test effectiveness. however, it can be expensive to calculate, due to the large number of different mutation operators that have been proposed for generating the mutants. in this paper, we address the problem of finding a small set of mutation operators which is still sufficient for measuring test effectiveness. we do this by defining a statistical analysis procedure that allows us to identify such a set, together with an associated linear model that predicts mutation adequacy with high accuracy. we confirm the validity of our procedure through cross-validation and the application of other, alternative statistical analyses.
experience applying the spin model checker to an industrial telecommunications system. model checking has for years been advertised as a way of ensuring the correctness of complex software systems. however, there exist surprisingly few critical studies of the application of model checking to industrial-scale software systems by people other than the model checker's own authors. in this paper we report our experience in applying the spin model checker to the validation of the failover protocols of a commercial telecommunications system. while we conclude that model checking is not yet ready for such applications, we find that current research in the model checking community is working to address the difficulties we encountered.
model-based security analysis for mobile communications. mobile communication systems are increasingly used in companies. in order to make these applications secure, the security analysis has to be an integral part of the system design and it management process for such mobile communication systems. this work presents the experiences and results from the security analysis of a mobile system architecture at a large german telecommunications company, by making use of an approach to model-based security engineering that is based on the uml extension umlsec. the focus lies on the security mechanisms and security policies of the mobile applications which were analyzed using the umlsec method and tools. main results of the paper include a field report on the employment of the umlsec method in an industrial telecommunications context as well as indications of its benefits and limitations.
spyware: a change-aware development toolset. our research is driven by the motivation that change must be put in the center, if one wants to understand the complex processes of software evolution. we built a toolset named spyware which, using a monitoring plug-in for integrated development environments (ides), tracks the changes that a developer performs on a program as they happen. spyware stores these first-class changes in a change repository and offers a plethora of productivity-enhancing ide extensions to exploit the recorded information.
systematically refactoring inheritance to delegation in java. because of the strong coupling of classes and the proliferation of unneeded class members induced by inheritance, the suggestion to use composition and delegation instead has become commonplace. the presentation of a corresponding refactoring in the literature may lead one to believe that such a transformation is a straightforward undertaking. however, closer analysis reveals that this refactoring is neither always possible, nor does it necessarily achieve its desired effect. we have therefore identified the necessary preconditions and realizable postconditions of the refactoring, and built a tool that can perform it completely automatically. by applying this tool to all subclasses of several open-source projects, we have collected evidence of the applicability of the refactoring and of its capability to deliver on its promises. the refactoring builds on constraint graphs originally developed for type inference to check the preconditions and to compute the necessary delegation as well as the subtype relationships that must be maintained.
plural: checking protocol compliance under aliasing. enforcing compliance to api usage protocols is notoriously hard due to possible aliasing of objects through multiple references. in previous work we proposed a sound, modular approach to checking protocol compliance based on typestates that offers a great deal of flexibility in aliasing. in our approach, api protocols are defined based on typestates. every reference is associated with a permission, and reasoning about permissions is appropriately conservative for the "degree" of possible aliasing admitted by a permission. this paper describes plural, a tool to automatically enforce typestate-based protocols using permissions in java. api developers can specify protocols with simple annotations on methods and method parameters. a static flow analysis tracks permissions in code that uses specified apis and issues warnings for possible protocol violations.
third international workshop on sharing and reusing architectural knowledge (shark 2008). the shift of the software architecture community towards architectural knowledge has brought along some promising research directions. in this workshop we discuss the issues that lead to the application of architectural knowledge in research and industrial practice; ongoing research and new ideas to advance the field. in its previous editions we examined the state of the art and practice, future challenges and trends. this third edition will discuss, among others, architectural knowledge as perceived by different research communities, including requirements engineering, service-oriented computing and international standardization.
the design navigator: charting java programs. the design navigator is a semi-automated design mining tool which reverse engineers lepus3 design charts from java™ 1.4 programs at any level of abstraction in reasonable time. we demonstrate the design navigator's step-wise charting process of java foundation classes, generating decreasingly abstract charts of java.awt and discovering building-blocks in its design.
celadon: a change impact analysis tool for aspect-oriented programs. to reduce the manual effort of assessing potential affected program parts during software evolution, we develop a tool, called celadon, which automates the change impact analysis for aspectj programs. celadon is implemented in the context of the eclipse environment and designed as a plugin. it analyzes the source code of two aspectj software versions, and decomposes their differences into a set of atomic changes together with their dependence relationships. the analysis result is reported in terms of impacted program parts and affected tests. for each affected test, celadon also identifies a subset of affecting changes that are responsible for the test's behavior change. in particular, as one of its applications, celadon helps facilitate fault localization by isolating failure-inducing changes for one specific affected test from other irrelevant changes.
the international workshop on software architectures and mobility (sam 2008). e-businesses are increasingly facing the need of porting the provision of their e-services to mobile customers. evolving requirements, such as reliability, security, scalability, performance and privacy, from fixed to mobile settings, has revealed new and important challenges. this is due to the behavioral constraints that mobility poses, and that were not faced in traditional distributed settings. examples include: dynamic network topology, changes in location, constrained resource availability, communication protocols heterogeneity, unstable connectivity, and so forth. industrial practice is demonstrating that such transition is not straightforward and tends to be costly. in particular, the evolution may "break" the software system architecture, thus calling for substantial and expensive changes. even when the system is (re)built from scratch, it is unclear if and how the state-of-the-art in software architectures relate to the requirements and concerns brought forward by mobile software systems. likewise, there is still a lack of systematic software engineering methods and techniques which can assist in developing and evolving mobile software systems. the goal of this workshop is to address these gaps by strengthening the cross fertilization of advances from requirements and domain engineering, software architectures, and middleware to systematically develop and evolve architectures supporting mobility.
: a tool for generating binary adapters for evolving java libraries. although in theory the apis of software libraries and frameworks should be stable, they change in practice. this forces clients of the library api to change as well, making software maintenance expensive. changing a client might not even be an option if its source code is missing or certain policies forbid its change. by giving a library both the old and the new api, clients can be shielded from api changes and can run with the new version of the library. this demo presents our tool, reba, that automatically generates compatibility layers between new library apis and old clients. in the first stage, reba generates another version of the library, called adapted-library, that supports both the old and the new apis. in the second stage, reba shrinks the adapted-library into a minimal, client-specific compatibility layer containing only classes truly required by the client. evaluation on controlled experiments and case studies using eclipse core libraries shows that our approach effectively adapts clients to new library versions, and is efficient.
third international workshop on graph and model transformations. model transformation is an emerging paradigm used in model-driven software development. graph transformations deal with rewriting operations on graphs, and as such can serve as a foundation for constructing model transformation language, tools, and systems. this workshop, the 3rd in a series, investigates the connection between graph and model transformations and intends to bring together interested researchers and practitioners from the two fields.
jigsaw: a tool for the small-scale reuse of source code. developers perform small-scale reuse tasks to save time and to increase the quality of their code. due to the small scale of such tasks, the overhead in reusing source code can quickly outweigh the benefits. existing approaches focus on locating source code for reuse but do not support the integration of the located code within the developer's system, thereby leaving the developer with the burden of performing these steps manually. this paper presents a tool, called jigsaw, that uses the developer's context to help integrate the reused source code into the developer's own source code.
business impact of process improvements. the topic of the workshop "business impact of process improvements" is achieving tangible and sustainable business impact from process improvements. focus is on approaches that are both practical and quantifiable. the kinds of process improvements addressed include, but are not limited to, the introduction of iterative, agile or "lean" approaches, improved requirements engineering, risk management, usage of process improvement reference frameworks, and improved quality control and assurance. busi-ness impact should be illustrated through either increasing the value of what is delivered to the customer or reducing the cost (for example by reduction of rework effort). the audience will share experiences how to reliably set-up, measure and achieve business-oriented process improvements in order to increase return on investment in software engineering.
composing knowledge fragments: a next generation ide. when building a software system, software developers each contribute a flow of information that together forms the system. as they work, programmers continuously consult various facts (knowledge) about this information to answer their questions about the system. the knowledge most easily accessed today in a programming environment involves facts about the structure of the program. however, the knowledge required by a programmer is broader than just structure; it also includes knowledge about design, requirements, and the development process, to name just a few other sources. to enable developers to access this knowledge more efficiently, our goal is to develop a model for programming environments that allows various fragments of different kinds of knowledge to be configured flexibly. this model would enable new presentations to show these knowledge fragments in ways that more directly answer programmers' questions.
formal concept analysis applied to fault localization. one time-consuming task in the development of software is debugging. recent work in fault localization crosschecks traces of correct and failing execution traces, it implicitly searches for association rules which indicate that executing a line will most probably cause the whole execution to fail. this technique has some limitations: it assumes that an error has a single faulty statement origin, and that lines are independent. our research hypothesis is that using association rules with more expressive premises, some limitations can be alleviated. the solution that we propose combines association rules and formal concept analysis. our technique is already usable when the size of the execution traces is not too large. we conjecture that the technique can be used to analyze large executions, thanks to the information contained in the abstract syntax tree.
abctool: a tool for architecture centric engineering of component based systems. in this paper, we present the abctool, a visual tool for modeling software architecture in the whole lifecycle of the target system so that the development, deployment, online maintenance and evolution of a component-based system can be done as a series of refinements and transformations of architectural models in a systematic and automated manner.
sdsoa 2008: second international workshop on systems development in soa environments. the key objective of this workshop is to provide researchers and practitioners an opportunity to discuss open soa research challenges. an soa research agenda that has been developed by sei and a group of collaborators over the past year will be presented as a framework for obtaining feedback and new ideas from researchers and practitioners who do work and research in this area.
summary for leadership and management in software architecture (lmsa 2008). software architecture, in education and practice, is primarily concerned with technical issues associated with the quality of software architecture and design. however, as project size increases, leadership, management skills, and the organizational context of the architect become more important, to the point where the non-technical duties of the project architect can "make or break" a project. this workshop is focused on understanding these non-technical duties.
comeback!: a refactoring-based tool for binary-compatible framework upgrade. maintenance of a software framework often requires restructuring its api (refactoring). upon framework upgrade structural api changes may invalidate existing plugins - modules that used one of its previous versions. to preserve plugins, we use refactoring trace to automatically create an adaptation layer that translates between plugins and the framework. for each encountered refactoring we formally define a comeback - a refactoring to construct adapters. given an ordered set of refactorings occured between two framework versions our tool comeback! executes the corresponding comebacks and yields the adaptation layer.
answering common questions about code. difficulties understanding update paths while un-derstanding code cause developers to waste time and insert bugs. a detailed investigation of these difficulties suggests that a wide variety of problems could be addressed by more easily answering questions about update paths that existing tools do not answer. we are designing a feasible update path static analysis to compute these paths and a visualization for asking questions and displaying results. in addition to grounding the questions we answer and tailoring the program analysis in data, we will also evaluate the usefulness of our tool using lab and field studies.
featuremapper: mapping features to models. variability modelling with feature models is one key technique for specifying the problem space of software product lines (spls). to allow for the automatic derivation of a concrete product based on a given variant configuration, a mapping between features in the problem space and their realisations in the solution space is required. it is crucial to support the developer in the complex task of defining such mappings. these mappings can also be used to provide visualisations of the variant space that allow to reason over variability in spls. in this paper we present featuremapper, a tool that allows for defining mappings of features to model elements specifying feature realisations. these feature realisations can be defined in arbitrary ecore-based languages. furthermore, the tool supports different visualisation techniques that can help developers understand the complex designs of spls.
se-cse 2008: the first international workshop on software engineering for computational science and engineering. computational science and engineering (cs&e) software supports a wide variety of domains including nuclear physics, crash simulation, satellite data processing, fluid dynamics, climate modeling, bioinformatics, and financial modeling. the recent increase in the importance of this type of software motivates the need to better understand how it is developed. this movement creates an opportunity for the software engineering community to apply our techniques and knowledge to a new and important application domain. furthermore, the design, implementation, and maintenance used in cs&e software systems can be significantly different from that used in systems more typically studied by the software engineering community. this workshop brings together researchers from the software engineering community with researchers and practitioners from the cs&e community. the workshop allows participants to share perspectives and present findings from research and practice that are relevant to the cs&e application development. a significant portion of the workshop is devoted to discussion of the position papers with the goal of generating a research agenda to improve tools, techniques, and experimental methods for cs&e software engineering in the future.
developing natural language-based program analyses and tools to expedite software maintenance. with as much as 60-90% of software life cycle resources spent on program maintenance, there is a critical need for automated software tools to help explore and understand today's large and complex software. one important source of information software maintenance tools can draw from is lexical information in comments and identifiers. identifier names often communicate a programmer's intent when writing code, and help developers map real-world concepts to code during comprehension. my dissertation will develop specialized information retrieval techniques and natural language analyses for software so that software maintenance tools can take full advantage of the wealth of information in program identifiers, and integrate these techniques into software tools to expedite the maintenance activities of program exploration, concern location, and fault localization.
runtime software adaptation: framework, approaches, and styles. our icse 1998 paper showed how an application can be adapted at runtime by manipulating its architectural model. in particular, our paper demonstrated the beneficial role of (1) software connectors in aiding runtime change, (2) an explicit architectural model fielded with the system and used as the basis for runtime change, and (3) architectural style in providing both structural and behavioral constraints over runtime change. this paper examines runtime evolution in the decade hence. a broad framework for studying and describing evolution is introduced that serves to unify the wide range of work now found in the field of dynamic software adaptation. this paper also looks to the future, identifying what we believe to be highly promising directions.
software development governance (sdg). governance in a specific organization is an iterative process that starts with the assignment of roles and decision rights as per goals that are set, continues with the establishment of a set of mechanisms to be activated on a specific scope within the organization, and ends with the assessment that leads to the refinement of the goals accordingly. this one-day workshop focuses on software development governance and deals with the issues that are special to software organizations.
summary for scrutinizing agile practices or shoot-out at process corral! agile methods and practices are gaining momentum in industry, and are also slowly making their way in academia bringing fresh air and funny new jargon. some practitioners consider them as the ultimate advance in software engineering. but what do we know about this? where is the evidence? do they scale? do they solve real issues or just substitute new issues to old ones? are the benefits tangible, or just acts of faith? aren't we all agile? are they no agile failures? isn't the "waterfall process" - that piñata of agilistas--the real holy grail of software engineering, and agile processes only a band-aid to compensate for our deficiencies? this workshop aims at challenging the ready-made ideas, the fluff, the hype, putting things into context, and examining these with fresh and open eyes.
monticore: a framework for the development of textual domain specific languages. in this paper we demonstrate a framework for the efficient development of textual domain specific languages and supporting tools. we use a redundance-free and compact definition of a readable concrete syntax and a comprehensible abstract syntax as both representations significantly overlap in their structure. to further improve the usability of the abstract syntax, this definition format integrates additional concepts like associations and inheritance into the well-understood grammar-based approach. modularity concepts like language inheritance and embedding are used to simplify the development of languages based on already existing ones. in addition, the generation of editors and a template approach for code generation is explained.
amida: a sequence diagram extraction toolkit supporting automatic phase detection. amida is a toolkit to record an execution trace of a java program and visualize the trace as a sequence diagram. amida supports our novel approach to efficiently detecting phases; the algorithm precisely divides a long execution trace into a series of smaller diagrams corresponding to features (or tasks to achieve a feature) without deep knowledge on a target system.
a model transformation tool for performance simulation of complex uml models. we present a tool that automatically translates uml2 models of service-oriented systems to models for performance evaluation by a commercial simulator. the strength of our tool lies in its support for complex behaviors, which is made possible by a rich intermediate metamodel with clear operational semantics.
international workshop on multicore software engineering (iwmse 2008). we have reached a major turning point: microprocessor performance can no longer be improved by increasing clock frequencies; instead, higher performance will have to come from parallelism. as multi/manycore processors with multiple cpus on a chip become standard and affordable for everyone, software engineers face the challenge of parallelizing applications of all sorts. however, compared to sequential applications, our repertoire of tools and methods for cost-effectively developing reliable, parallel applications is spotty. the mission of this workshop is to bring together researchers and practitioners with diverse backgrounds in order to advance the state of the art in software engineering for multi/manycore parallel applications. this is the first workshop specifically focusing on software engineering challenges of multi/manycore.
constructing difference tools for models using the sidiff framework. model-driven development requires a full set of development tools. while technologies for constructing graphical editors, compilers etc. are readily available, there is a lack of approaches for constructing version management tools which compare models and show their difference. the general problem is aggravated by the fact that such tools must consider the semantics of each particular model (or diagram) type, i.e. a whole family of tools needs to be constructed. this research demonstration shows how such families of difference tools can be constructed using the sidiff framework.
pacc starter kit: developing software with predictable behavior. the pacc starter kit is an eclipse-based development environment that combines a model-driven development approach with reasoning frameworks that apply performance, safety, and security analyses. these analyses predict runtime behavior based on specifications of component behavior and are accompanied by some measure of confidence.
modelscope: inspecting executable models during run-time. this paper presents a software tool called modelscope which is a co-debugging platform that, during run-time, allows insight into a model running on various different target systems with different views and diagrams for different aspects of the run-time state.
challenges in automotive software engineering. developing and integrating automotive embedded software is a complex undertaking. the software is large. it is developed by many contributors. it is distributed over many control units connected by a variety of in-vehicle buses. often much of the equipment or functions in a car are optional and regulatory requirements also vary between markets, leading to large combinatorial variations of software features. targets running the software have to be cheap. errors can be extremely expensive. new software and system features are demanded by the market and also by governmental regulations. model-based design (mbd) of functional behaviour has been a big help in the recent past on the one hand, and on the other hand has by itself created new complexity by allowing relatively quick development of ever more features, especially when combined with autocoding. all this creates new challenges that did not exist a few years ago when feature development was slow. major new challenges now are to tame all the complexity, get a system view on top of the individual functions, and to leverage executable system models to put more comprehensive testing into early phases of a development. tools are required which really help those engineers and software developers. their needs may not ask for a lot of computer science glamour. they can be quite basic and sophisticated concepts from computer science may find it difficult to find acceptance outside some niches. this presentation will outline the achievements, the current challenges and will point to upcoming tools and approaches that help meeting those challenges.
cooperative and human aspects of software engineering (chase 2008). the chase 2008 workshop is concerned with exploring the cooperative and human aspects of software engineering, and providing a forum for discussing high-quality resarch. accepted papers reflect the diversity of the field of software engineering--ranging from requirements to testing, and from ethnographic research to experiments. moreover, the background of attendees reflects the diversity of researchers in this domain, ranging from sociology to psychology, from informatics to software engineering. chase 2008 met its goals in presenting high-quality research and building community through a mixture of presentations, discussions, posters, and social activities.
on the automation of fixing software bugs. software testing can take up to half of the resources of the development of new software. although there has been a lot of work on automating the testing phase, fixing a bug after its presence has been discovered is still a duty of the programmers. techniques to help the software developers for locating bugs exist though, and they take name of automated debugging. however, to our best knowledge, there has been only little attempt in the past to completely automate the actual changing of the software for fixing the bugs. therefore, in this paper we propose an evolutionary approach to automate the task of fixing bugs. the basic idea is to evolve the programs (e.g., by using genetic programming) with a fitness function that is based on how many unit tests they are able to pass. if a formal specification of the buggy software is given, more sophisticated fitness functions can be designed. moreover, by using the formal specification as an oracle, we can generate as many unit tests as we want. hence, a co-evolution between programs and unit tests might take place to give even better results. it is important to know that, to fix the bugs in a program with this novel approach, a user needs only to provide either a formal specification or a set of unit tests. no other information is required.
a state coverage tool for junit. we present a junit test runner that informs users of missing behavior checks in their tests. the tool tracks variable updates and definitions over the course of a test execution and determines which variables influence which assertions via dynamic taint analysis. the program statements that set outputs which do not influence the outcome of any test assertions are reported as state coverage inadequacies. with traditional code coverage tools, users can ensure that tests execute all program statements; with this tool, they can additionally ensure that program output is checked, in one way or another, by a test.
using software engineering technology to improve the quality of medical processes. in this paper, we describe some of the key observations resulting from our work on using software engineering technologies to help detect errors in medical processes. in many ways, medical processes are similar to distributed systems in their complexity and proneness to contain errors. we have been investigating the application of a continuous process improvement approach to medical processes in which detailed and semantically rich models of the medical processes are created and then subjected to rigorous analyses. the technologies we applied helped improve understanding about the processes and led to the detection of errors and subsequent improvements to those processes. this work is still preliminary, but is suggesting new research directions for medical process improvement, software engineering technologies, and the applicability of these technologies to other domains involving human-intensive processes.
sixth workshop on software quality. software quality has been a major challenge throughout information technology projects. whether it is in software development, in software integration or whether it is in the implementation or customization of shrink-wrapped software, quality is regarded as a major issue. in the last couple of decades, much software engineering research has focussed on standards, methodologies and techniques for improving software quality, measuring software quality and software quality assurance. most of this research is focused on the internal/development view of quality. more recent studies have made attempts to understand the stakeholder view of quality. with globalisation, many new challenges affect software quality. not only do we need to understand the many stakeholder views of quality, we now need to consider the cultural issues, and the outsourcing issues. the sixth workshop on software quality aims to bring together academic, industrial and commercial communities interested in software quality topics to discuss the different technologies being defined and used in the software quality area.
techniques and tools for the automatic generation of optimal test data at code, model and interface level. this article presents two different tools automating the generation of optimized test data for unit, model-based and integration testing by maximizing the coverage and minimizing the number of test cases required. to cope with these conflicting goals, hybrid self-adaptive and multi-objective evolutionary algorithms were applied. the efficiency was demonstrated by evaluating fault detection capability by mutation testing. thanks to the effort reduction offered, the approach is particularly suitable for the verification of complex, safety-relevant software systems.
analyzing dynamic call graphs enhanced with program state information for feature location and understanding. in this paper we present a prototype tool for locating and understanding features in unfamiliar source code of complex c/c++ software systems. the key concepts of the analysis tool are (1) combining dynamic function call graphs with information on the functions' containment within hierarchically structured modules and (2) providing means of gathering program state information on user-defined locations within the call graph. starting from a typically huge dynamic call graph logged during feature execution, developers narrow their search for functions implementing the feature's core functionality by successively pruning the graph from feature-irrelevant functions. the assessment whether a function contributes to a feature is performed on various levels of abstraction, namely on (1) module containment, (2) on the function's call relations, and (3) on the way it modifies data. having sorted out feature-irrelevant functions this way, users are able to analyze the remaining, probably highly feature-relevant functions with other heavy-weight analysis techniques, such as debugging techniques, to get a deep understanding of the feature implementation.
a code provenance management tool for ip-aware software development. in this paper we introduce a code provenance management tool which can track the provenance of source code and generate provenance reports to facilitate best practices for managing intellectual property (ip) throughout the software development lifecycle. we present the ip-aware process supported by the tool and explain how it reduces both the cost and the risk of code ip management. results from three pilots are analyzed to illustrate the effectiveness of cost and risk reduction.
role-based trust management security policy analysis and correction environment (rt-space). this paper presents rt-space, a tool suite for authoring, verifying, and correcting rt access control policies. rt is a role-based trust management framework well suited for use in systems that must protect the interests of multiple stakeholders in a decentralized environment.
advancing test automation technology to meet the challenges of model-driven software development: report on the 3rd workshop on automation of software test. the third workshop on automation of software test (ast 2008) at the 30th interna¬tional conference on software engineering (icse 2008) sets a special theme on model-based software testing. nine full research papers and six short papers will be presented in four sessions at the workshop. this report summarizes the organization of the workshop as well as the sessions and papers to be presented at the workshop.
seams 2008: software engineering for adaptive and self-managing systems. the software engineering for adaptive and self-managing systems (seams) workshop aims at consolidating the interest in the software engineering community on self-adaptive and self-managing systems. seams provides a forum for researchers and practitioners to share new results, discuss challenging issues, raise awareness, and promote collaboration within the community. the seams 2008 workshop builds on the success of seams 2006 at icse in shanghai and seams 2007 at icse in minneapolis.
workshop on comparison and versioning ofsoftware models (cvsm08). comparison and versioning of software models is an urgent theoretical and practical problem area in the context of model-driven software development. a range of detailed issues are addressed by the contributions to cvsm08. this workshop summary introduces important research areas and categorizes the contributions of the workshop.
early aspects at icse 2008: workshop on aspect-oriented requirements engineering and architecture design. the "early aspects @ icse'08" is the 13th edition of the workshop on early aspects [1]. early aspects focuses on the identification, modularization, representation and composition of crosscutting concerns during the requirements engineering and architecture derivation activities. the specific aim of the present workshop is twofold: (a) to stimulate integration of the work on early development activities for product lines with the work for early aspects, and (b) to initiate creation of a product lines application demonstration with early aspects.
designing a prosthetic memory to support software developers. about their activities and the resulting artifacts which helps them remain oriented, avoid omissions, and correctly use artifacts. when stored only in the developer's organic memory, this knowledge may degrade and cannot directly be shared with others. its consistent externalization, however, is currently limited by production costs, indirect returns, and its limited saliency in contexts where it could be useful. in this work we propose a memory aid which strives to overcome these barriers, and reduce the resulting problems. developers will provide short and raw subjective notes which will be associated with the code context but stored separately from it, allowing us to increase saliency via two novel presentations. the first, designed after human episodic memory, chronologically interleaves these subjective notes with an automatically-gathered record of the developer's objective activities. it virtually extends shorter-term memory, aiding with orientation and increasing the saliency of recent knowledge and reminders. the second, a contextual view, uses static dependencies and historical records to present notes which may be relevant to the developer's current context.
3rd international workshop on advances and applications of problem frames. michael jackson's problem frames are a highly promising approach to early life-cycle software engineering. their focus moves the engineer back to the problem to be solved rather than forward to the software and solving a poorly defined problem. by applying the problem frames approach, the software engineer can understand the problem context and how it is to be affected by the proposed software, and ultimately work towards the right solution for the problem. the influence of the problem frames approach and related work is spreading in the fields of domain modelling, business process modelling, requirements engineering, software architecture as well as software engineering in general.
model-driven configuration of os-level mandatory access control: research abstract. trust and assurance of mobile platforms is a prime objective when considering their use in security-critical scenarios like in healthcare or e-government. currently, several complementary approaches can be found in literature, ranging from purely hardware based to operating system level and application level solutions. together, they build a "trusted and secured" technology stack. however, the complex policy configuration mechanisms at every single layer also represent the biggest stumbling block for a rapid adoption. we propose a practicable and efficient solution for leveraging operating system level and application level security mechanisms to realize security-critical applications and services.
mining early aspects from requirements with ea-miner. aspect-oriented requirements engineering (aore) aims at bringing the benefits achieved by separation of concerns (e.g., improved modularity, reusability and maintainability) to requirements engineering. in order to cope with costly tasks performed during aore such as identifying concerns and structuring requirements in different models, tool support is vital to effectively reduce the burden of performing these various tasks. this demonstration describes how the ea-miner tool provides automated support, based on natural language processing techniques, for mining various types of concerns from a variety of early stage requirements documents. the tool is implemented as an eclipse plug-in and enables several features such as visualizing and editing the models and generating specification documents.
4th international workshop on predictor models in se (promise 2008). the promise workshop seeks to deliver to the software engineering community useful, usable, verifiable, and repeatable models. to provide a sound and realistic basis for creating predictive models, and to allow researchers to conduct repeatable software engineering experiments, we maintain the promise repository, a growing collection that now contains 57 empirically-based data sets.
pkm: knowledge management tool for environments centered on the concept of the experience factory. this paper presents pkm - a web-based tool for knowledge management in an environment centered on the concept of the experience factory. the tool focuses on managing explicit knowledge, most of which is collected in an automated way using non-invasive plug-ins and probes. it provides customizable metric views, metric interpretation and abstraction capabilities, helps in extraction and evaluation of metric progress models.
codecity: 3d visualization of large-scale software. codecity is a language-independent interactive 3d visualization tool for the analysis of large software systems. based on a city metaphor, it depicts classes as buildings and packages as districts of a "software city". by offering consistent locality and solid orientation points we keep the viewer oriented during the exploration of a city. we applied our tool on several large-scale industrial systems.
an aspect-oriented approach for improving architecture design efficiency. major issues in software engineering today are the ever increasing size and complexity of systems with, at the same time, high demands for quality. software architectures are a means for coping with size and complexity of systems and also for assuring required qualities. the processes of creating architectures, however, remain affected by these issues. since, in practice, architectures have to be constructed iteratively, the number of established architectural strategies and the number of inter-related models heavily increase over time. hence, the impact analysis of newly introduced quality strategies during later stages becomes highly effort-intensive and error-prone. with our approach we aim at the mitigation of effort needed for such quality impact analyses by enabling efficient separation of concerns. for achieving efficiency, we introduce an aspect-oriented approach that enables the automatic weaving of quality strategies into architectural artifacts. by doing so, we are able to conduct selective quality impact evaluations with significantly reduced effort.
the future of end user programming? one of the holy grails of computer science for many decades has been to make the power of computer programming accessible to more and more people. the earliest "high level" languages, fortran and cobol, were intentionally designed to be written and understood by specific communities of users with problems to solve, namely the scientific/engineering and business communities. as computing became more accessible to more people, the number of dedicated full time programmers mushroomed and formed a community unto itself, who largely created languages and tools by and for themselves to use. the end users, the people with the non-computing problems to solve, became isolated from the computer itself and were forced have their business problems encoded in the increasingly esoteric script of a powerful new programmer priesthood. but even throughout these "dark ages", a small number of valiant dissenters survived and flourished in distant monasteries and hermitages, dedicating their lives and technical prowess to liberate computing from its raised floor temples. resistance was stiff, but not futile, as every decade or so breakthroughs like spreadsheets, hypercard, 4gls and html empowered more and more "non-programmers" to create their own computing solutions. now, well into the second era of the web, consumer-oriented websites like flickr and youtube routinely offer end users "snippets" of javascript code to reuse in their own software creations, their facebook and myspace pages. projects like ibm's coscripter have achieved programming by demonstration for end users. mashup tools abound, and the web is filled with billions of customized applications, most created by end users themselves. have we finally achieved the goals of those happy few who dreamed of a world where programming was as common as dialing a telephone? have we finally arrived at the long tail of programming? and if we have built it, did they come? this talk will assess the current state of end user programming and present a heretical perspective about the future of this endeavor from a confessed true believer.
runtime failure detection. we propose a model-driven methodology to generate and automatically deploy runtime failure detectors that enable self-healing software to deal with functional failures. the methodology rests on addressing key research challenges: (1) identifying classes of properties specified in end-user requirements, which can be associated with typical integration failures. (2) designing runtime efficient detectors for these failures. (3) defining mappings of entities between the domain of end-user requirements and the design model.
continuous software quality supervision using sourceinventory and columbus. several tools and methods for source code quality assurance based on static analysis finally reached a state when they are applicable in practice and recognized by the industry. however, most of these tools are used in an isolated manner and very rarely as organic parts of the quality assurance process. furthermore, little or no help is provided in interpreting the outputs of these tools. this paper presents sourceinventory, a system for source code-based software quality assessment and monitoring, which is able to collect, store and present measurement data including metrics, coding problems and other kinds of data like bug numbers and test coverage information. it helps software developers, architects and managers to take control over their software's quality by performing continuous code scans, fault detection, coding style verification, architecture violation detection, and automatic report generation considering metric baselines.
test case generator for guitar. as guis become more popular, the need for gui testing tools becomes greater. many current gui test generation techniques require proprietary tools and can be hard to use to their fullest potential. this paper outlines a new test case generation strategy, which enables testers to automatically produce cases in a widely used format. we hope that this strategy will encourage more complete gui testing.
the role of abstraction in software engineering. this workshop focuses on the concept of abstraction in software engineering. the aim is to explore the role of abstraction in dealing with complexity in the software engineering process, to discuss how the use of different levels of abstraction may facilitate performance of different activities, and to examine whether abstraction skills can be taught.
a runtime architecture-based approach for the dynamic evolution of distributed component-based systems. dynamic evolution of distributed component-based systems (dcs) is an important task in software engineering. several challenges are posed in this process. for example, how to preserve consistency during evolution and how to reflect the abstract evolution specification in the concrete reconfiguration implementation. having observed the generality of software architecture, researchers have proposed various architectural description languages (adls), enabling evolution techniques, etc. to investigate the problem. these approaches typically employ the formal semantics of dynamic adls at the incremental levels of refinement in the design phase or the explicit maintenance of software architecture at runtime. however, different adls usually address different concerns and the lack of runtime support for the causal relation between adls and the running system easily leads to the mismatch between them, thus inevitably sacrifices their usability. we propose an approach based on a runtime architecture which is visually generated from an attributed type graph meta-model, exists through the lifecycle of dcs, establishes the causal relation between architectural topology and system configuration, and directs the dynamic evolution.
ccvisu: automatic visual software decomposition. understanding the structure of large existing (and evolving) software systems is a major challenge for software engineers. in reverse engineering, we aim to compute, for a given software system, a decomposition of the system into its subsystems. ccvisu is a lightweight tool that takes as input a software graph model and computes a visual representation of the system's structure, i.e., it structures the system into separated groups of artifacts that are strongly related, and places them in a 2- or 3-dimensional space. besides the decomposition into subsystems, it reveals the relatedness between the subsystems via interpretable distances. the tool reads a software graph from a simple text file in rsf format, e.g., call, inheritance, containment, or co-change graphs. the resulting system structure is currently either directly presented on the screen, or written to an output file in svg, vrml, or plain text format. the tool is designed as a reusable software component, easy to use, and easy to integrate into other tools; it is based on efficient algorithms and supports several formats for data interchange.
viedame - flexible and robust bpel processes through monitoring and adaptation. viedame is a tool for monitoring and dynamic service adaptation of bpel processes. the tool monitors partner service interaction to compute quality of service (qos) data and performs dynamic service adaptation based on various available service selection strategies, such as availability or response time. the service adaptation happens transparently at runtime by dynamically selecting an alternative service for an existing service used in the process, without any changes to the deployed bpel process. to gain even more flexibility, the tool provides transformation components to compensate service interface mismatches, which are likely to occur when using alternative services offered by different providers.
performance modeling for service oriented architectures. we present a tool for performance modeling of service oriented architectures (soas). as mission-critical use of whole-of-government soas become pervasive, the capability to model and predict the run-time performance of interdependent composite applications is critical. the tool can be used by architects early in the software engineering lifecycle to predict performance and scalability, to evaluate architectural alternatives, to provide guidance for capacity planning and the negotiation of service level agreements (slas). it directly models and produces metrics for soa applications in terms that are familiar to architects (services, workflows, and compositions of services). the tool enables the performance model to be generated from available architectural artifacts and performance data, making it easy to use. it is highly dynamic to facilitate interactive evaluation of alternative architectural choices. the tool can model complex deployment scenarios such as server virtualisation. development and evaluation of the tool was carried out in the context of architectural modeling for large-scale soa-based australian e-government systems. the tool radically simplified the construction and execution of soa performance models, and contributed critical insights for the architecting of these systems.
second international workshop on ultra-large-scale software-intensive systems (ulssis 2008). software-intensive systems now being envisioned and in some cases developed will surpass complexity thresholds beyond which established software engineering concepts, methods and tools no longer work well. ulssis provides a forum in which researchers from industry, academia and governments come together to understand these issues and to discuss research and development activities to address them.
safety of component-based systems: analysis and improvement using fujaba4eclipse. todays embedded and safety-critical systems incorporate increasing amounts of software. consequently, the software architecture and its connection to hardware elements have a big impact on the safety of those systems. we present in this paper an approach and its implementation in the fujaba4eclipse environment for the analysis and improvement of component-based systems w.r.t. their safety which specifically exploits the software and system structure.
modeling in software engineering. the modeling in software engineering (mise) workshops are a collaboration between the icse and models research communities, with a focus on using models to facilitate software development.
an integrated aspect-oriented model-driven software product line tool suite. software product line engineering is mostly about the systematic management of commonality and variability between product line members. the effectiveness of this approach thus very much depends on how well variability within the family of similar products is implemented and managed. variability often has widespread impact, crosscutting not only multiple parts of individual artifacts but also multiple artifacts in multiple stages of the product line lifecycle. this demonstration presents an approach that facilitates variability implementation, management, and tracing by integrating aspect-oriented and model-driven software development. we demonstrate means for effectively dealing with variability on model, model transformation, and code generation level. the concepts are illustrated with a case study of a home automation system.
an analyzer for extended compositional process algebras. system simulation and verification become more demanding as complexity grows. pat is developed as an interactive system to support composing, simulating and reasoning of process algebra with various extensions like fairness events, global variables and parameterized processes. pat provides user friendly interfaces to support system modeling and simulation. furthermore, it embeds two complementing model checking techniques catering for different systems and properties, namely, an explicit on-the-fly model checker which is designed to verify event-based fairness constraints efficiently and a bounded model checker based on state-of-the-art sat solvers. the model checkers are capable of proving reachability, deadlock-freeness and the full set of linear temporal logic (ltl) properties. compared to other model checkers, pat has two key advantages. firstly, it supports an intuitive annotation of fairness constraints so that it handles large number of fairness constraints efficiently. secondly, the compositional encoding of system models as sat problems allows us to handle compositional process algebra effectively. the experimental results show that pat is capable of verifying systems with large number of states and outperforms the state-of-the-art model checkers in some cases.
a verification system for timed interval calculus. timed interval calculus (tic) is a highly expressive set-based notation for specifying and reasoning about embedded real-time systems. however, it lacks mechanical proving support, as its verification usually involves infinite time intervals and continuous dynamics. in this paper, we develop a system based on a generic theorem prover, prototype verification system (pvs), to assist formal verification of tic at a high grade of automation. tic semantics has been constructed by the pvs typed higher-order logic. based on the encoding, we have checked all tic reasoning rules and discovered subtle flaws. a translator has been implemented in java to automatically transform tic models into pvs specifications. a collection of supplementary rules and pvs strategies has been defined to facilitate the rigorous reasoning of tic models with functional and non-functional (for example, real-time) requirements at the interval level. our approach is generic and can be applied further to support other real-time notations.
prototypes for medical case-based applications. already in the early stages of case-based reasoning prototypes were considered as an interesting technique to structure the case base and to fill the knowledge gap between single cases and general knowledge. unfortunately, later on prototypes never became a hot topic within the cbr community. however, for medical applications they have been used rather regularly, because they correspond to the reasoning of doctors in a natural way. in this paper, we illustrate the role of prototypes by application programs, which cover all typical medical tasks: diagnosis, therapy, and course analysis.
an infrastructure for mining medical multimedia data. biomedical research processes related to disease diagnosis, prognosis and monitoring would great benefit from advanced tools able not exclusively to store and manage multimodal data but also to process and extract significant relations and then novel knowledge from them. indeed, making a prediction on a disease outcome usually requires considering heterogeneous pieces of information obtained from several sources which should be compared and related. mining medical multimedia objects is aimed at discovering and making available the hidden useful knowledge embedded in collections of data and is, then, of key importance for supporting clinical decision-making. in this paper, we report current results of a medical warehouse we are developing in an integrated environment for mining clinical data acquired by different media. in particular, focus is herein given to the infrastructure of the warehouse and its current functionalities not limited to storage and management but including intelligent representation and annotation of multimedia objects.
efficient string mining under constraints via the deferred frequency index. we propose a general approach for frequency based string mining, which has many applications, e.g. in contrast data mining. our contribution is a novel algorithm based on a deferred data structure. despite its simplicity, our approach is up to 4 times faster and uses about half the memory compared to the best-known algorithm of fischer et al. applications in various string domains, e.g. natural language, dna or protein sequences, demonstrate the improvement of our algorithm.
maximum margin active learning for sequence labeling with different length. sequence labeling problem is commonly encountered in many natural language and query processing tasks. svm struct is a supervised learning algorithm that provides a flexible and effective way to solve this problem. however, a large amount of training examples is often required to train svm struct , which can be costly for many applications that generate long and complex sequence data. this paper proposes an active learning technique to select the most informative subset of unlabeled sequences for annotation by choosing sequences that have largest uncertainty in their prediction. a unique aspect of active learning for sequence labeling is that it should take into consideration the effort spent on labeling sequences, which depends on the sequence length. a new active learning technique is proposed to use dynamic programming to identify the best subset of sequences to be annotated, taking into account both the uncertainty and labeling effort. experiment results show that our svm struct active learning technique can significantly reduce the number of sequences to be labeled while outperforming other existing techniques.
using data mining to build integrated discrete event simulations. building a system from disparate software requires analysis to establish commonality of code. the ability of a data mining tool to extract repeating functional structures is the first step to reduce exploration, save development time, and re-use software components. this case study looks specifically at the application of graph-based data mining algorithms to code re-factoring. after writing a module to obtain a graph representation of a discrete event model, we built a tool around the university of washington's subdue package to find recurring patterns of logic. this resulted in cleaner code and increased awareness of code re-use.
local modelling in classification. in classification tasks it may sometimes not be meaningful to build single rules on the whole data. this may especially be the case if the classes are composed of several subclasses. several common as well as recent issues are presented to solve this problem. as it can e.g. be seen in weihs et al. (2006) there may result strong benefit from such local modelling. all presented methods are evaluated and compared on four real-world classification problems in order to obtain some overall ranking of their performance following an idea of hornik and meyer (2007).
relative linkage disequilibrium: a new measure for association rules. association rules are one of the most popular unsupervised data mining methods. once obtained, the list of association rules extractable from a given dataset is compared in order to evaluate their importance level. the measures commonly used to assess the strength of an association rule are the indexes of support, confidence, and the lift.relative linkage disequilibrium (rld) was originally proposed as an approach to analyse both quantitatively and graphically general two way contingency tables. rld can be considered an adaptation of the lift measure with the advantage that it presents more effectively the deviation of the support of the whole rule from the support expected under independence given the supports of the lhs (a) and the rhs (b). rld can be interpreted graphically using a simplex representation leading to powerful graphical display of association relationships. moreover the statistical properties of rld are known so that confirmatory statistical tests of significance or basic confidence intervals can be applied.this paper will present the properties of rld in the context of association rules and provide several application examples to demonstrate it's practical advantages.
improving imbalanced multidimensional dataset learner performance with artificial data generation: density-based class-boost algorithm. improving the learner performance over imbalanced and multidimensional datasets raises a challenging task for machine learning community. although a salient characteristic in data modeling is the amount of data provided for the learner, the proportional distribution of that data in each class has also direct relationship with the classifier performance. in imbalanced datasets when data is distributed into different classes, various in size, understanding of data structure and characteristics plays an important role in improving the learner accuracy. in this paper we introduce a new approach that combines the information gained from traditional classification algorithms, confusion matrix parameters and density-based clustering to generate artificial data in order to increase the learner performance. first a classification algorithm is run on training data. then the confusion matrix is studied and the true positive (tp) rate of each class is measured. the class with the lowest tp rate is selected. using density-based clustering we identify the centroid of the class and measure the samples distribution in multidimensional space in the next step. with the values gained from probability density function estimations for clusters, extra samples are generated and added to the original dataset to rebalance the class proportion and the weight of different classes in the whole training set. our method has been evaluated in terms of tp, f-measure and also overall accuracy against a number of demetra (toxicology) and uci datasets. our method provides an insight view of the data structure and characteristics in order to identify how much and where the data need to be added for increasing the classification accuracy of the learner.
an efficient similarity searching algorithm based on clustering for time series. indexing large time series databases is crucial for efficient searching of time series queries. in the paper, we propose a novel indexing scheme rqi (range query based on index) which includes three filtering methods: first-k filtering, indexing lower bounding and upper bounding as well as triangle inequality pruning. the basic idea is calculating wavelet coefficient whose first k coefficients are used to form a mbr (minimal bounding rectangle) based on haar wavelet transform for each time series and then using point filtering method; at the same time, lower bounding and upper bounding feature of each time series is calculated, in advance, and stored into index structure. at last, triangle inequality pruning method is used by calculating the distance between time series beforehand. then we introduce a novel lower bounding distance function slbs (symmetrical lower bounding based on segment) and a novel clustering algorithm csa (clustering based on segment approximation) in order to further improve the search efficiency of point filtering method by keeping a good clustering trait of index structure. extensive experiments over both synthetic and real datasets show that our technologies provide perfect pruning power and could obtain an order of magnitude performance improvement for time series queries over traditional naive evaluation techniques.
webangels filter: a violent web filtering engine using textual and structural content-based analysis. the development of the web has been paralleled by the proliferation of harmful web pages content. using violent web page as a case study, we review some existing solutions, then we propose a violent web content detection and filtering system called "webangels filter" which uses textual and structural analysis. "webangels filter" has the advantage of combining several data mining algorithms for web site classification. we present a comparative study of different data mining techniques to block violent contentweb pages. also, we discuss how the combination learning based methods can improve filtering performances. our results show that it can detect and filter violent content effectively.
generalized graph matching for data mining and information retrieval. graph based data representation offers a convenient possibility to represent entities, their attributes, and their relationships to other entities. consequently, the use of graph based representation for data mining has become a promising approach to extracting novel and useful knowledge from relational data. in order to check whether a certain graph occurs, as a substructure, within a larger database graph, the widely studied concept of subgraph isomorphism can be used. however, this conventional approach is rather limited. in the present paper the concept of subgraph isomorphism is substantially extended such that it can cope with don't care symbols, variables, and constraints. our novel approach leads to a powerful graph matching methodology which can be used for advanced graph based data mining.
data mining with neural networks for wheat yield prediction. precision agriculture (pa) and information technology (it) are closely interwoven. the former usually refers to the application of nowadays' technology to agriculture. due to the use of sensors and gps technology, in today's agriculture many data are collected. making use of those data via it often leads to dramatic improvements in efficiency. for this purpose, the challenge is to change these raw data into useful information. in this paper we deal with neural networks and their usage in mining these data. our particular focus is whether neural networks can be used for predicting wheat yield from cheaply-available in-season data. once this prediction is possible, the industrial application is quite straightforward: use data mining with neural networks for, e.g., optimizing fertilizer usage, in economic or environmental terms.
weighted association rule mining from binary and fuzzy data. a novel approach is presented for mining weighted association rules (ars) from binary and fuzzy data. we address the issue of invalidation of downward closure property (dcp) in weighted association rule mining where each item is assigned a weight according to its significance w.r.t some user defined criteria. most works on weighted association rule mining so far struggle with invalid downward closure property and some assumptions are made to validate the property. we generalize the weighted association rule mining problem for databases with binary and quantitative attributes with weighted settings. our methodology follows an apriori approach [9] and avoids pre and post processing as opposed to most weighted association rule mining algorithms, thus eliminating the extra steps during rules generation. the paper concludes with experimental results and discussion on evaluating the proposed approach.
an exploration into the power of formal concept analysis for domestic violence analysis. the types of police inquiries performed are very diverse in nature and the current data processing architecture is not sufficiently tailored to cope with this diversity. many information concerning cases is still stored in databases as unstructured text. formal concept analysis is showcased as an exploratory data analysis technique for discovering new knowledge from police reports. it turns out that it provides a powerful framework for exploring the dataset, resulting in essential knowledge for improving current practices. it is shown that the domestic violence definition employed by the police organisation of the netherlands is not always as clear as it should be, making it hard to use it effectively for classification purposes. in addition, newly discovered knowledge for automatically classifying certain cases as either domestic or non-domestic violence is presented. moreover, essential techniques for detecting incorrect classifications, performed by police officers, are provided. finally, some problems encountered because of the sometimes unstructured way of working of police officers are discussed. both using formal concept analysis for exploratory data analysis and its application on this area are novel enough to make this paper into a valuable contribution to the literature.
contrast-set mining of aircraft accidents and incidents. identifying patterns of factors associated with aircraft accidents is of high interest to the aviation safety community. however, accident data is not large enough to allow a significant discovery of repeating patterns of the factors. we applied the stucco algorithm to analyze aircraft accident data in contrast to the aircraft incident data in major aviation safety databases and identified factors that are significantly associated with the accidents. the data pertains to accidents and incidents involving commercial flights within the united states. the ntsb accident database was analyzed against four incident databases and the results were compared. we ranked the findings by the factor support ratio, a measure introduced in this work.
an application for electroencephalogram mining for epileptic seizure prediction. a computational framework to support seizure predictions in epileptic patients is presented. it is based on mining and knowledge discovery in electroencephalogram (eeg) signal. a set of features is extracted and classification techniques are then used to eventually derive an alarm signal predicting a coming seizure. the epileptic patient may then take steps in order to prevent accidents and social exposure.
hopfield networks in relevance and redundancy feature selection applied to classification of biomedical high-resolution micro-ct images. we study filter---based feature selection methods for classification of biomedical images. for feature selection, we use two filters -- a relevance filter which measures usefulness of individual features for target prediction, and a redundancy filter, which measures similarity between features. as selection method that combines relevance and redundancy we try out a hopfield network. we experimentally compare selection methods, running unitary redundancy and relevance filters, against a greedy algorithm with redundancy thresholds [9], the min-redundancy max-relevance integration [8,23,36], and our hopfield network selection. we conclude that on the whole, hopfield selection was one of the most successful methods, outperforming min-redundancy max-relevance when more features are selected.
gep-induced expression trees as weak classifiers. the paper proposes applying gene expression programming (gep) to induce expression trees used subsequently as weak classifiers. two techniques of constructing ensemble classifiers from weak classifiers are investigated in the paper. the working hypothesis of the paper can be stated as follows: given a set of classifiers generated through applying gene expression programming method and using some variants of boosting technique, one can construct the ensemble producing effectively high quality classification results. a detailed description of the proposed gep implementation generating classifiers in the form of expression trees is followed by the report on adaboost and boosting algorithms used to construct an ensemble classifier. to validate the approach computational experiment involving several benchmark datasets has been carried out. experiment results show that using gep-induced expression trees as weak classifiers allows for construction of a high quality ensemble classifier outperforming, in terms of classification accuracy, many other recently published solutions.
browsing assistance service for intranet information systems. improved usability and efficiency of organizational information systems brings economical benefits to the organization and time benefits to the users. we present a browsing assistance service suitable for the organizational intranet environments. it helps users to shorten their browsing interactions and achieve their goals faster. these benefits are accomplished by providing relevant suggestions on the potential navigation targets of interest to the users. the system design employs the analytics of user browsing behavior and its appropriate segmentation. it efficiently utilizes the initial and the terminal navigation points for providing recommendations. the performance of the system has been evaluated on the real world data of a large scale intranet portal.
designing specific weighted similarity measures to improve collaborative filtering systems. the aim of collaborative filtering is to help users to find items that they should appreciate from huge catalogues. in that field, we can distinguish user-based from item-based approaches. the former is based on the notion of user neighbourhoods while the latter uses item neighbourhoods.the definition of similarity between users and items is a key problem in both approaches. while traditional similarity measures can be used, we will see in this paper that bespoke ones, that are tailored to type of data that is typically available (i.e. very sparse), tend to lead to better results.extensive experiments are conducted on two publicly available datasets, called movielens and netflix. many similarity measures are compared. and we will show that using weighted similarity measures significantly improves the results of both user- and item-based approaches.
mining unexpected web usage behaviors. recently, the applications of web usage mining are more and more concentrated on finding valuable user behaviors from web navigation record data, where the sequential pattern model has been well adapted. however with the growth of the explored user behaviors, the decision makers will be more and more interested in unexpected behaviors, but not only in those already confirmed. in this paper, we present our approach user, that finds unexpected sequences and implication rules from sequential data with user defined beliefs, for mining unexpected behaviors from web access logs. our experiments with the belief bases constructed from explored user behaviors show that our approach is useful to extract unexpected behaviors for improving the web site structures and user experiences.
control charts of workflows. this paper focuses on the control of the performance characteristics of workflows modeled with stochastic petri nets (spn's). this goal is achieved by focusing on a new model for artificial social systems (ass's) behaviors, and by introducing equivalent transfer functions for spn's. ass's exist in practically every multi-agent system, and play a major role in the performance and effectiveness of the agents. this is the reason why we introduce a more suggestive model for ass's. to model these systems, a class of petri nets is adopted, and briefly introduced in the paper. this class allows representing the flow of physical resources and control information data of the ass's components. in the analysis of spn we use simulations in respect to timing parameters in a generalized semi-markov process (gsmp). by using existing results on perturbation (e.g., delays in supply with raw materials, derangements of equipments, etc.) analysis and by extending them to new physical interpretations we address unbiased sensitivity estimators correlated with practical solutions in order to attenuate the perturbations.
autonomous forex trading agents. in this paper we describe an infrastructure for implementing hybrid intelligent agents with the ability to trade in the forex market without requiring human supervision. this infrastructure is composed of three modules. the "intuition module", implemented using an ensemble model, is responsible for performing pattern recognition and predicting the direction of the exchange rate. the "a posteriori knowledge module", implemented using a case-based reasoning system, enables the agents to learn from empirical experience and is responsible for suggesting how much to invest in each trade. the "a priori knowledge module", implemented using a rule-based expert system, enables the agents to incorporate non-experiential knowledge in their trading decisions. this infrastructure was used to develop an agent capable of trading the usd/jpy currency pair with a 6 hours timeframe. the agent's simulated and live trading results lead us to believe our infrastructure can be of practical interest to the traditional trading community.
modelling medical time series using grammar-guided genetic programming. the analysis of time series is extremely important in the field of medicine, because this is the format of many medical data types. most of the approaches that address this problem are based on numerical algorithms that calculate distances, clusters, reference models, etc. however, a symbolic rather than numerical analysis is sometimes needed to search for the characteristics of time series. symbolic information helps users to efficiently analyse and compare time series in the same or in a similar way as a domain expert would. this paper describes the definition of the symbolic domain, the process of converting numerical into symbolic time series and a distance for comparing symbolic temporal sequences. then, the paper focuses on a method to create the symbolic reference model for a certain population using grammar-guided genetic programming. the work is applied to the isokinetics domain within an application called i4.
noisy image segmentation by a robust clustering algorithm based on dc programming and dca. we present a fast and robust algorithm for image segmentation problems via fuzzy c-means (fcm) clustering model. our approach is based on dc (difference of convex functions) programming and dca (dc algorithms) that have been successfully applied in a lot of various fields of applied sciences, including machine learning. in an elegant way, the fcm model is reformulated as a dc program for which a very simple dca scheme is investigated. for accelerating the dca, an alternative fcm-dca procedure is developed. moreover, in the case of noisy images, we propose a new model that incorporates spatial information into the membership function for clustering. experimental results on noisy images have illustrated the effectiveness of the proposed algorithm and its superiority with respect to the standard fcm algorithm in both running-time and quality of solutions.
realizing modularized knowledge models for heterogeneous application domains. this paper addresses the realization of modularized knowledge models within a heterogeneous application domain using an existing knowledge management tool. the application domain we deal with is travel medicine, which combines medical aspects with geography, climate, holiday activities and associated traveling conditions. in this paper we present the application's requirements and show how knowledge models can be developed using an industrial strength application. furthermore we present the challenges of a knowledge model based on multi-case bases whereas each case base represents its own area of expertise. hence, we introduce our knowledge model for the travel medicine application and exemplify the implementation of typical data types and similarity measures.
leatherbacks matching by automated image recognition. we describe a method that performs automated recognition of individual laetherback turtles within a large nesting population. with only minimal preprocessing required of the user, we prove able to produce unsupervised matching results. the matching is based on the scale-invariant feature transform by lowe. a strict condition posed by biologists reads that matches should not be missed (no false negatives). a robust criterion is defined to meet this requirement. results are reported for a considerable sample of leatherbacks.
projection with double nonlinear integrals for classification. in this study, a new classification model based on projection with double nonlinear integrals is proposed. there exist interactions among predictive attributes towards the decisive attribute. the contribution rate of each combination of predictive attributes, including each singleton, towards the decisive attribute can be re presented by a fuzzy measure. we use double nonlinear integrals with respect to the signed fuzzy measure to project data to 2-dimension space. then classify the virtual value in the 2-d space projected by nonlinear integrals. in our experiments, we compare our classifier based on projection with double nonlinear integrals with the classical method- naïve bayes. the results show that our classification model is better than naïve bayes.
experiences using clustering and generalizations for knowledge discovery in melanomas domain. one of the main goals in prevention of cutaneous melanoma is early diagnosis and surgical excision. dermatologists work in order to define the different skin lesion types based on dermatoscopic features to improve early detection. we propose a method called somex with the aim of helping experts to improve the characterization of dermatoscopic melanoma types. somex combines clustering and generalization to perform knowledge discovery. first, somex uses self-organizing maps to identify groups of similar melanoma. second, somex builds general descriptions of clusters applying the anti-unification concept. these descriptions can be interpreted as explanations of groups of melanomas. experiments prove that explanations are very useful for experts to reconsider the characterization of melanoma classes.
the impact of noise in spam filtering: a case study. unsolicited commercial e-mail (uce), more commonly known as spam is a growing problem on the internet. every day people receive lots of unwanted advertising e-mails that flood their mailboxes. fortunately, there are several approaches for spam filtering able to detect and automatically delete this kind of messages. however, spammers have adopted some techniques to reduce the effectiveness of these filters by introducing noise in their messages. this work presents a new pre-processing technique for noise identification and reduction, showing preliminary results when it is applied with a flexible bayes classifier. the experimental analysis confirms the advantages of using the proposed technique in order to improve spam filters accuracy.
cell loss performance of the gauss atm switch. the authors present a performance study of the gauss asynchronous transfer mode (atm) switch with respect to cell loss. the gauss switch is a recently proposed, high-performance, output buffered atm switch that can easily be implemented. in general, if an atm switch suffers from cell loss, the exact behavior of this cell loss as a function of parameters such as load, traffic business, internal speed, etc., has to be known. the study focuses on cell loss in the gauss switch due to its reduced internal speed. analytical results for the cell loss probability are provided and compared to corresponding quantities for the well-known knockout switch. the comparison shows that the gauss switch yields significantly smaller cell loss probabilities than the knockout switch
long term resource allocation in video delivery systems. in typical video delivery systems offering programs on-demand, service should be be nearly immediate and continuous. a video server can provide this type of service by reserving sufficient network and server resources for the duration of playout. scalability and reduced cost can be achieved using a single channel to serve multiple customers waiting for the same program (referred to as batching). batching is especially useful during high load periods typically occuring during evening prime time hours. typical channel allocation algorithms use a greedy, allocate-as-needed policy. variations in system load can cause these algorithms to suffer poor and unpredictable short-term performance, and non-optimal long term performance. in this paper, we develop a set of realistic workloads, identify the limitations of greedy allocation algorithms, and propose a set of rate-based allocation schemes to solve these limitations. the performance of various video delivery systems are simulated and compared. the rate-based policies are shown to be robust for the workloads examined, and are easy to implement.
performance analysis of hot-potato routing for multiclass traffic in multihop lightwave networks. the authors present an analytical approach to the performance analysis of multihop lightwave networks with hot-potato routing and multiclass traffic. explicit closed-form expressions are derived for the hop distribution and the probability of `don't care'. the computational complexity is thus reduced as compared to previous approaches, and priorities are readily handled. results for two different classes of traffic are given. the probability of a packet belonging to a particular class of traffic existing on a preferred path is calculated by finding the fixed point of a scale function. the throughput and network delay as well as queuing delay of a particular class are then calculated using the expressions derived for them
state-dependent m/g/1 type queueing analysis for congestion control in data networks. we study a linear-increase multiplicative-decrease flow control mechanism. we consider congestion signals that arrive in batches according to a poisson process. we focus on the case when the transmission rate cannot exceed a certain maximum value. the distribution of the transmission rate in steady state as well as its moments are determined. our model is particularly useful to study the behavior of tcp (transmission control protocol) the congestion control mechanism in the internet. burstiness of packet losses is captured by allowing congestion signals to arrive in batches. by a simple transformation, the problem can be reformulated in terms of an equivalent m/g/1 queue, where the transmission rate in the original model corresponds to the workload in the 'dual' queue. the service times in the queueing model are not i.i.d., and they depend on the workload in the system.
on resource management and qos guarantees for long range dependent traffic. the effect of long-memory processes on queue length statistics of a single queue system is studied through a controlled fractionally differenced arima (1,d,0) input process. this process has two parameters /spl phi//sub 1/ and d representing an auto-regressive component and a long-range dependent component, respectively. results show that the queue length statistics studied (mean, variance and the 0.999 quantile) are proportional to e(c/sup c/spl phi/1/) e(c/sub 2/d), where (c/sub 1/, c/sub 2/) are positive constants, and c/sub 2/
analysis of aimd protocols over paths with variable delay. the throughput of aimd protocols in general and of tcp in particular, has been computed in many existing works by modeling the round-trip time as a constant and thus replacing it by its expectation. there are however many scenarios in which the delays of packets vary, causing a variation of the round-trip time. many typical scenarios occur in wireless and mobile networks. we propose in this paper an analytical model that accounts for the variability of delay, while computing the throughput of an aimd protocol. we derive a closed-form expression for the throughput, that illustrates the impact of delay variability. we show by analysis and simulation, that an increase in the variability of delay improves the performance of an aimd protocol. thus, an analytical model that only considers the average delay could underestimate the performance of an aimd protocol in scenarios where delay is variable.
the distribution of delays of dispersed messages in an m/m/1 queue. we analyze the distribution of the delay of messages in an infinite capacity m/m/1 queue. a message is composed of n packets, and the arrival of the packets to the queue is poisson. our calculations are based on recursive schemes. we obtain explicit expressions for the laplace-stieltjes transform (lst) of the delays, which enables to obtain exact expressions for the moments of the delay in a complexity smaller than the one obtained by using recursive schemes. we repeat the above calculations for the case that messages are dispersed, i.e. packets from several sources arrive to an m/m/1 queue and are served according to the fifo discipline. hence, several packets of other messages may arrive between consecutive packets of a given message.
fractal traffic: measurements, modelling and performance evaluation. observations of both ethernet traffic and variable bit rate (vbr) video traffic have demonstrated that these traffics exhibit "self-similarity" and/or infinite asymptotic index of dispersion for counts (idc). we report here on measurements of traffic in a commercial public broadband network where similar characteristics have been observed. for the purpose of analysis and dimensioning of the central links of an atm network we analyse in this paper the performance of a single server queue fed by gaussian traffic with infinite idc. the analysis lends to an approximation for the performance of a queue in which the arriving traffic is "fractal" gaussian and consequently where there does not exist a dominant negative-exponential tail. the term "fractal" is used here in the sense that the autocovariance of the traffic exhibits self-similarity, that is to say, where the autocovariance of an aggregate of the traffic is the same, or asymptotically the same for large time lags, as the original traffic. we are not concerned with proving or exploiting this self-similarity property as such, but only with performance analysis techniques which are effective for such processes. in order to be able to test the performance analysis formulae, we show that traffic with the same autocovariance as measured in a real network over a wide range of lags (sufficiently wide a range for the traffic to be equivalent from the point of view of queueing performance) can be generated as a mixture of two gaussian ar(1) processes. in this way we demonstrate that the analytic performance formulae are accurate.
bandwidth allocation for guaranteed versus best effort service categories. modern communication networks evolve towards integration of guaranteed-performance and best-effort service types. the coexistence of these two service types offers substantial benefits, such as resource sharing between service classes, and the ability of the user to select an appropriate service class according to its individual requirements and preferences. notwithstanding, such interaction gives rise to more complicated system behavior and related performance issues, which need to be explored and understood in order to allow efficient network operation. in this paper we examine potential congestion phenomena, which arise due to the combined effect of bandwidth sharing and user migration between service classes. we propose a simplified fluid model for session flow, consisting of two coupled queues with state-dependent flows, which captures the essential ingredients of service-class interaction. our analysis shows that the system might exhibit bistable behavior, in the sense that transient congestion may stir the system from a stable and efficient operating point to an inefficient and congested one. we identify conditions which give rise to bistability, and propose a call admission control scheme which prevents the system from getting trapped in a congested-type equilibrium, while not interfering with normal system operation.
cooperative distributed scheduling for ats-based broadband networks. a proactive distributed cooperative control algorithm for resource scheduling of broadband networks based on asynchronous time sharing is presented. the problem setting for distributed, cooperative proactive scheduling is described. an overview of the distributed cooperative algorithm is presented. the general control principles underlying the effectiveness of the cooperative algorithm are discussed. the formal details of the distributed cooperative algorithm and its underlying single noise scheduling algorithm are considered. simulation results comparing the distributed cooperative algorithm with other networkwide scheduling algorithms are reported
design and evaluation of an adaptive flow control scheme. the authors model a virtual circuit in a computer network as a sequence of servers in tandem. they explicitly take into account cross traffic at the servers from other virtual circuits. the analysis of the model leads them to propose a novel flow control scheme, which they term send-time control. a measure to evaluate the performance of flow control schemes, called the packet performance index, is proposed. they compare the send-time control scheme with the window-based flow control scheme of transmission control protocol (tcp) using simulation. the results obtained show that send-time control is superior to the window-based scheme
improving the throughput of point-to-multipoint arq protocols through destination set splitting. an approach to improving the performance of point-to-multipoint automatic repeat request (arq) protocols is considered. the approach involves splitting the destination set into disjoint groups and having the source carry out independent time multiplexed conversations with each group. the performance of memoryless and limited-memory versions of stop-and-wait and go-back-n protocols was investigated and the question of how to pick an optimal grouping of nodes was addressed. the results indicate that destination set splitting can improve the throughput of point-to-multipoint arq protocols, particularly if the receivers' capabilities are not identical
restricted dynamic steiner trees for scalable multicast in datagram networks. the paper addresses the issue of minimizing the number of nodes involved in the routing over a multicast tree and in the maintenance of such a tree in a datagram network. it presents a scheme where the tree routing and maintenance burden is laid only upon the source node and the destination nodes associated with the multicast tree. the main concepts behind this scheme is to view each multicast tree as a collection of unicast paths, and to locate only the multicast source and destination nodes on the junctions of their multicast tree. the paper shows that despite of this restriction, the cost of the created multicast trees is not necessarily higher than the cost of the trees created by other algorithms that do not impose the restriction and therefore require all the nodes along the data path of a tree to participate in the routing over the tree and in the maintenance of the tree.
performance evaluations of a metaring mac protocol integrating video and data traffics in an interconnected environment. the metaring is a medium access control (mac) protocol for lans and mans operating at a speed of 1 gbit/sec and above. the metaring mac protocol offers its users synchronous and asynchronous types of services and can operate under two basic access control modes: buffer insertion for variable size packets, and slotted for fixed length cells. the latter mode of operation is considered in this paper. in the first part of the paper an analysis of the asynchronous type of service is performed. the analysis has been carried out on a network configuration (hereafter called scenario) which, other than being realistic, is particularly critical with respect to slot reuse. it consists of a group of equally spaced nodes sending asynchronous traffic to a gateway interconnecting the metaring with other communication subnetworks. results obtained show that the metaring is unfair and that the unfairness depends, in particular, upon the offered load, besides the k and l protocol parameter values. in the second part of the paper we focus on the study of the traffic integration capability provided by the metaring mac protocol. the results provide a strong indication that the metaring mac protocol is suitable for vbr video and data traffic integrations.
an application of superpositions of two-state markovian sources to the modelling of self-similar behaviour. we present a modelling framework and a fitting method for modelling second order self-similar behaviour with the markovian arrival process (map). the fitting method is based on fitting to the auto-correlation function of counts for a second order self-similar process. it is shown that with this fitting algorithm it is possible closely to match the auto-correlation function of counts for a second order self-similar process over 3-5 time-scales with 8-16 state maps with a very simple structure i.e. a superposition of 3 respectively 4 interrupted poisson processes (ipp) and a poisson process. the fitting method seems to work well over the entire range of the hurst parameter.
optimal routing in communication networks with delay variations. the authors address the problem of optimal routing in packet switched networks. optimality is discussed in terms of end-to-end delay. the variance of delay as well as its mean value are taken into account. achieving optimal routing is necessary for multimedia networks to fully support real-time services. a network is modeled as a weighted graph with its link weights representing link delays. it is assumed that the delay statistics conform to a normal distribution. in the course of analysis, it is shown that this type of routing optimization problem can be formulated as a process of searching for a specific point in a coordinate system defined by the mean and variance of the end-to-end delay. an efficient algorithm is presented for finding the optimal point in this coordinate system
competitive queue policies for differentiated services. we consider the setting of a network providing differentiated services. as is often the case in differentiated services, we assume that the packets are tagged as either being a high priority packet or a low priority packet. outgoing links in the network are serviced by a single fifo queue.our model gives a benefit of α ≥ 1 to each high priority packet and a benefit of 1 to each low priority packet. a queue policy controls which of the arriving packets are dropped and which enter the queue. once a packet enters the queue it is eventually sent. the aim of a queue policy is to maximize the sum of the benefits of all the packets it sends.we analyze and compare different queue policies for this problem using the competitive analysis approach, where the benefit of the online policy is compared to the benefit of an optimal offline policy. we derive both upper and lower bounds for the policies we consider. we believe that competitive analysis gives important insight to the performance of these queuing policies.
finite and infinite qbd chains: a simple and unifying algorithmic approach. in this paper, we present a novel algorithmic approach, the hybrid matrix geometric/invariant subspace method, for finding the stationary probability distribution of the finite qbd process which arises in performance analysis of computer and communication systems. assuming that the qbd state space is defined in two dimensions with m phases and k+1 levels, the solution vector for level k, \pi_k, 0 \leq k \leq k is shown to be in a modified matrix geometric form \pi_k = v_1 r_1^k + v_2 r_2^{k-k} where r_1 and r_2 are certain solutions to two nonlinear matrix equations and v_1 and v_2 are vectors to be determined using the boundary conditions. we show that the matrix geometric factors r_1 and r_2 can simultaneously be obtained independently of k via finding the sign function of a real matrix by an iterative algorithm with quadratic convergence rates. the time complexity of obtaining the coefficient vectors v_1 and v_2 is shown to be o(m^3 \log_2 k) which indicates that the contribution of the number of levels on the overall algorithm is minimal. besides the numerical efficiency, the proposed method is numerically stable and in the limiting case of k \rightarrow \infty, it is shown to yield the well-known matrix geometric solution \pi_k = \pi_0 r_1^k for the infinite qbd chain.
achieving stability in networks of input-queued switches. recent research has generated many interesting results on scheduling input-queued switches. however, most of this work focuses on a single switch in isolation. in this paper, we study the problem of scheduling a network of input-queued switches. we consider the longest-queue-first and longest-port-first scheduling policies that are stable for a single switch, and show that they can be unstable even for a fixed traffic pattern in a simple network of eight input-queued switches. moreover, this result holds regardless of how the traffic sharing the same port-pair is scheduled at each switch. on the positive side, we present a policy, longest-in-network, that is stable in networks of input-queued switches. this result holds even if the traffic pattern is allowed to change over time.
a new hierarchical routing protocol for dynamic multihop wireless networks. the routing techniques used in conventional packet radio networks are not suitable for dynamic multihop wireless networks because of their unique architecture. in this paper, a new hierarchical multihop routing algorithm is introduced which balances the cost of location-update and path-finding operations by partitioning the terminals and mobile base stations to produce a virtual topology. based on the virtual topology, each network entity stores a fraction of the network topology information and maintains the routing efficiency. finally, the performance of the hierarchical multihop routing algorithm is investigated through simulations.
minimizing end-to-end delay in high-speed networks with a simple coordinated schedule. we study the problem of providing end-to-end delay guarantees in connection-oriented networks. in this environment, multiple-hop sessions coexist and interfere with one another.parekh and gallager showed that the weighted fair queueing (wfq) scheduling discipline provides a worst-case delay guarantee comparable to (1/ρi) × ki for a session with rate ρi and ki hops. such delays can occur since a session-i packet can wait for time 1/ρi at every hop.we describe a randomized work-conserving scheme that guarantees, with high probability, an additive delay bound of approximately 1/ρi + ki. this bound is smaller than the multiplicative bound (1/ρi) × ki of wfq, especially when the hop count ki is large. we call our scheme coordinated-earliest-deadline-first (cedf) since it uses an earliest-deadline-first approach in which simple coordination is applied to the deadlines for consecutive hops of a session. the key to the bound is that once a packet has passed through its first server, it can pass through all its subsequent servers quickly.we conduct simulations to compare the delays actually produced by the two scheduling disciplines. in many cases, these actual delays are comparable to their analytical worst-case bounds, implying that cedf outperforms wfq.
on simple algorithms for dynamic load balancing. the paper focuses on the dynamic resource allocation problem. in communication networks such as wireless or circuit switching networks, resources correspond to base stations or links, and the load corresponds to the calls in the network. the principle of load balancing is examined for dynamic resource allocation. the question of interest is the performance of simple allocation strategies which can be implemented online. either finite capacity constraints on resources or mobility of users can be incorporated into the setup. the load balancing problem is formulated as an optimal control problem, and variants of a simple "least loaded routing" policy are shown to be asymptotically optimal for large call arrival rates.
design of a survivable wdm photonic network. i we consider schemes for protecting a network using a wavelength division multiplexing (wdm) infrastructure against component or link failures. first, we explain how protection can be achieved by hardware redundancy. then, we consider that with wdm networks, the failure of a single link or component may cause the simultaneous failure of several optical channels, potentially making impossible the restoration by rerouting in higher layers (sdh, atm, ip). to address this, we introduce the concept of design protection, which aims at making such failure propagations impossible. we present the disjoint alternate path (dap) algorithm which places optical channels in order to maximise design protection. we show the result on the example of the arpa-2 network.
the fat banyan atm switch. a strategy for fully utilizing switch resources, namely the buffers and links in a banyan network is proposed. a new switch model called the fat-banyan switch is introduced with the objective of achieving high performance at minimal cost. the fat-banyan switch model is a unifying model for the design and analysis of dilated banyan switches. the dilated banyan network forms a special case of the fat-banyan model. by keeping the number of input and output links of a switching element to be variable, the fat-banyan switch achieves a lower order of complexity than the dilated banyan. further the fat-banyan switch is superior to the buffered-banyan switch in terms of reduced delay and higher throughput. the performance of the fat-banyan under independent uniform traffic pattern is analyzed.
efficient broadcast using selective flooding. broadcast protocols are closely linked with point-to-point shortest routing in computer networks, and for broadcasting certain identified information, such as topological changes across the network. multi-address messages entail high overheads. reliable and efficient broadcasts are required to properly utilize the network bandwidth and ensure that users update the identified important information. it is assumed that local topological information in terms of connectivity is available at the nodes. this relative relationship is used predictively to reduce redundant transmissions in the broadcast of messages across the network; a simulation study shows the reduction to be significant. furthermore, for regular topologies, the redundancy in transmission can be shown to be zero. in conjunction with appropriate selectivity of information to the broadcast, an efficient and reliable broadcast is obtained. this work is relevant to networks with frequently changing topology in packet radio, cellular telephone, and strategic networks
optimal scheduling of soft handoffs in ds/cdma communication systems. considers the problem of optimal scheduling of soft handoffs as applicable to ds/cdma based cellular networks. the authors have formulated the phenomenon of soft handoffs as a reward/cost stochastic optimization problem wherein the reward is a function of some measurable characteristics of the received signal, and cost can be associated with different factors such as multiple simultaneous active connections, connection set-up and termination overheads. using dynamic programming, a maximum net reward policy that specifies the optimal base stations the mobile should be associated with during each time slot, is determined. the authors also extend their results to the case when there are more than two base stations. furthermore, the decisions are taken in a decentralized online manner. simulation results show that the proposed algorithms offer considerable improvement over the policy proposed in the is-95 standard.
performance improvement of fast packet switching by ldoll queueing. low delay or low loss (ldoll) queuing policies for asynchronous transfer model (atm) fast packet switching allow either retrieval priority or storage priority to be given to the atm cells of traffic streams with different performance requirements. the improvements in performance that can be achieved by using one bit in the atm cell header to make the binary ldoll distinction are analyzed. in the analysis, simulation of the level, where the cell transmission rate of a source may vary between zero and the peak rate and computation at the level, where queuing of individual cells is considered, are combined. it is shown that ldoll queuing, compared with fifo queuing in atm switches, can reduce cell loss probability by many orders of magnitude for low loss traffic. low delay traffic incurs a slightly higher cell loss which is compensated with a reduced cell delay mean and variance
routing strategies for fast networks. modern fast packet switching networks are being forced to rethink the routing schemes that are used in more traditional networks. the reexamination is necessitated because in these fast networks switches on the message's route can afford to make only minimal and simple operations. for example, examining a table of a size proportional to the network size is out of the question. in this paper we examine routing strategies for such networks based on flooding and predefined routes. our concern is to get both efficient routing and an even (balanced) use of network resources. we present efficient algorithms for assigning weights to edges in a controlled flooding scheme but show that the flooding scheme is not likely to yield a balanced use of the resources. we then present efficient algorithms for choosing routes along: 1) bfs trees and 2) shortest paths. we show that in both cases a balanced use of network resources can be guaranteed.
the effects of tuning time in bandwidth-limited optical broadcast networks. we consider the effects of tuning delay in optical broadcast networks. we show that for off-line scheduling these effects are small even if the tuning time is as large as the packet duration. in particular, we consider scheduling of random traffic with tunable transmitters and fixed-tuned receivers. we provide a lower bound to the completion time of any off-line schedule with an arbitrary number of wavelengths. we then describe a near-optimal schedule which is based on the principle of having idle transmitters tune to wavelengths just-in-time to start their transmissions. stability and capacity issues in the transmission of real-time traffic are considered. we show that the scheduling problem admits a single stable equilibrium point, and point out how the traffic capacity of a broadcast network can be reached. we also consider the implications in connection-oriented networks.
interaction of tcp flows as billiards. the aim of this paper is to analyze the performance of a large number of long-lived tcp controlled flows sharing many routers (or links), from the knowledge of the network parameters (capacity, buffer size, topology) and of the characteristics of each tcp flow (rtt, route etc.) when taking synchronization into account. it is shown that in the small buffer case, the dynamics of such a network can be described in terms of iterate of random piecewise affine maps, or geometrically as a billiards in the euclidean space with as many dimensions as the number of flow classes and as many reflection facets as there are routers. this class of billiards exhibits both periodic and nonperiodic asymptotic oscillations, the characteristics of which are extremely sensitive to the parameters of the network. it is also shown that for large populations and in the presence of synchronization, aggregated throughputs exhibit fluctuations that are due to the network as a whole, that follow some complex fractal patterns, and that come on top of other and more classical flow or packet level fluctuations. the consequences on tcp's fairness are exemplified on a few typical cases of small dimension.
adaptive real-time group multicast. this paper shows how to provide an adaptive real-time group multicast (many-to-many) communication service. such a service can be used by applications, like audio/video tele-conferencing, that require low loss, and bounded delay and jitter. in order to meet deterministic quality of service (qos) requirements of a real-time group multicast, some communication resources are reserved. in this work we show (i) how bandwidth is reserved for each group, and (ii) how an active user in a multicast group can dynamically share, in an efficient and fair manner, the bandwidth allocated to its group.quality of service support for a real-time multicast group is based on time driven priority. in this scheme the time is divided into time frames of fixed duration and all the time frames are aligned by using a global time reference which can be obtained from gps (global positioning system). bandwidth is allocated to a multicast group as a whole, rather than individually to each user. the allocation is done by reserving time intervals within time frames in some periodic fashion.this sort of allocation raises two problems that are studied in this paper: (1) scheduling: how time intervals are reserved to each multicast group, and (2) adaptive sharing: how the participants dynamically share the time intervals that have been reserved for their multicast group. the proposed approach is based on embedding multiple virtual rings, one for each multicast group. by using the virtual rings it is simple to route messages to all the participants, while minimizing the bound on the buffer sizes and queuing delays.
radio link admission algorithms for wireless networks with power control and active link quality protection. presents a distributed power control scheme, which maintains the signal/interference ratios (sirs) of operational (active) links above their required thresholds at all times (link quality protection), while new users are being admitted; furthermore, when new users cannot be successfully admitted, existing ones do not suffer fluctuations of their sirs below their required thresholds values. the authors also present two admission/rejection control algorithms, which exercise voluntary drop-out of links inadmissible to the network so as to reduce interference and possibly facilitate the admission of other links.
heuristic algorithms for constructing near-optimal structures of linear multihop lightwave networks. the goal of the study described is to exploit the capabilities of emerging lightwave technology and the fact that the ieee 802.6 man is a linear network, to construct near optimal linear multihop lightwave networks. heuristic algorithms are proposed for constructing photonic implementations of near optimal distributed queue dual bus (dqdb) structures. two sets of heuristic optimization algorithms are formulated. the first set is concerned with minimizing the maximum flow in any link in the network, while the second set of heuristics is aimed at minimizing the network-wide mean packet delay. important properties of these algorithms are analyzed and their performance is demonstrated with several representative numerical examples
a procedure to evaluate the mean transport time in multibuffer deflection-routing networks with nonuniform traffic. the use of independence assumptions has made it possible to derive an approximate model of deflection-routing networks that have multibuffer stations and two-connected topologies. a procedure is presented for estimating the mean transport time (and throughput) of these networks, even when the offered traffic is nonuniform. the proposed procedure is efficient and yields very accurate results, as comparisons with simulations have confirmed. the model is quite general and can be applied to deflection-routing networks that deflect packets according to destination-based priorities. the authors have modeled only a few of the several options for designing a deflection-routing network. in particular, they have modeled a network with no user input buffers, a specific admission-routed policy, and destination-based priorities
quad tree: a cost-effective fault-tolerant multistage interconnection network. a new class of irregular fault-tolerant multistage interconnection networks named quad tree (qt) networks is proposed and analyzed. the network can achieve significant tolerance to faults and good performance with relatively low costs and a simple control scheme. the construction procedure of the qt network is described. algorithms for allocation of path length and routing along with the routing procedure are proposed. the fault-tolerance aspect is described, and the cost-effectiveness of the qt network is discussed
mobile users: to uptdate or not to update? tracking strategies for mobile users in wireless networks are studied. in order to save the cost of using the wireless links mobile users should not update their location whenever they cross boundaries of adjacent cells. this paper focuses on three natural strategies in which the mobile users make the decisions when and where to update: the time-based strategy, the number of movements-based strategy, and the distance-based strategy. we consider both memoryless movement patterns and movements with markovian memory along a topology of cells arranged as a ring. we analyze the performance of each one of the three strategies under such movements, and show the performance differences between the strategies.
broadcast disks with polynomial cost functions. in broadcast disks systems, information is broadcasted in a shared medium. when a client needs an item from the disk, it waits until that item is broadcasted. broadcast disks systems are particularly attractive in settings where the potential customers have a highly-asymmetric communication capabilities, i.e., receiving is significantly cheaper than transmitting. this is the case with satellite networks, mobile hosts in wireless networks, and teletext system.the fundamental algorithmic problem for such systems is to determine the broadcast schedule based on the demand probability of items, and the cost incurred to the system by clients waiting. the goal is to minimize the mean access cost of a random client. typically, it was assumed that the access cost is proportional to the waiting time. in this paper, we ask what are the best broadcast schedules for access costs which are arbitrary polynomials in the waiting time. these may serve as reasonable representations of reality in many cases, where the "patience" of a client is not necessarily proportional to its waiting time.we present an asymptotically optimal algorithm for a fractional model, where the bandwidth may be divided to allow for fractional concurrent broadcasting. this algorithm, besides being justified in its own right, also serves as a lower bound against which we test known discrete algorithms. we show that the greedy algorithm has the best performance in most cases. then we show that the performance of other algorithms deteriorate exponentially with the degree of the cost polynomial and approaches the fractional solution for sub-linear cost. finally, we study the quality of approximating the greedy schedule by a finite schedule.
models of blocking probability in all-optical networks with and without wavelength changers. we introduce a traffic model for circuit switched all-optical networks (aons) which we then use to calculate the blocking probability along a path for networks with and without wavelength changers. we investigate the effects of path length, switch size, and interference length (the expected number of hops shared by two sessions which share at least one hop) on blocking probability and the ability of wavelength changers to improve performance. our model correctly predicts unobvious qualitative behavior demonstrated in simulations by other authors.
performance analysis of the atm shuffleout switching architecture under non-uniform traffic patterns. the authors describe a model for the performance evaluation of the shuffleout asynchronous transfer mode (atm) switch under arbitrary nonuniform traffic patterns. shuffleout is a blocking multistage structure using shortest path routing with deflection, in which output queues are connected to all the stages. the analytical model developed computes the load on each interstage link by tracing all the paths that a packet can follow to reach the addressed switch outlet, that is, by taking into account all the deflections from its shortest path it can receive. such a model allows the computation not only of the average load per stage but also its distribution over the different links belonging to the interstage pattern. thus fairness in packet switching by shuffleout is provided by the model
fast incremental updates for pipelined forwarding engines. pipelined asic architectures are increasingly being used in forwarding engines for high-speed ip routers. we explore optimization issues in the design of memory-efficient data structures that support fast incremental updates in such forwarding engines. our solution aims to balance the memory utilization across the multiple pipeline stages. we also propose a series of optimizations that minimize the disruption to the forwarding process caused by route updates. these optimizations reduce the update overheads by over a factor of two for a variety of different core routing tables and update traces.
degree-constrained multicasting in point-to-point networks. establishing a multicast tree in a point-to-point network of switch nodes, such as a wide-area atm network, is often modeled as the np-complete steiner problem in networks. in this paper, we study algorithms for finding efficient multicast trees in the presence of constraints on the copying ability of the individual switch nodes in the network. we refer to this problem as the degree-constrained multicast tree problem and model it as the degree-constrained steiner problem in networks. steiner heuristics for the degree-constrained case are proposed and their simulation results for sparse, point-to-point networks are presented. the results are compared with respect to their quality of solution, cost (running time), and the number of test cases for which no solution could be found. the results of our research indicate that efficient multicast trees can be found in large, sparse networks with small multicast groups even with limited multicast capability in the individual switches. some of the steiner heuristics tested yielded degree-constrained multicast trees within 5% of the best heuristic solution found in most of the cases. even when the fanout of each switch node was restricted to 2, the heuristics we used were able to generate efficient multicast trees in almost all our test networks. surprisingly few test networks were unsolvable. in those cases where no solution was found by a heuristic, backtracking solved many of the remaining cases. among the heuristics we used, degree-constrained versions of simple path-distance heuristics such as sph and sph-r provided the best tradeoffs between quality of solution and cost.
aries: a rearrangeable inexpensive edge-based on-line steiner algorithm. in this paper, we propose and evaluate aries, a heuristic for updating multicast trees dynamically in large point-to-point networks. the algorithm is based on monitoring the accumulated damage to the multicast tree within local regions of the tree as nodes are added and deleted, and triggering a rearrangement when the number of changes within a connected subtree crosses a set threshold. we derive an analytical upper-bound on the competitiveness of the algorithm. we also present simulation results to compare the average-case performance of the algorithm with two other known algorithms for the dynamic multicast problem, greedy and eba (edge-bounded algorithm). our results show that aries provides the best balance among competitiveness, computational effort, and changes in the multicast tree after each update.
an anchor chain scheme for ip mobility management. this work presents a simple mobility scheme for ip-based networks, termed the "anchor chain" scheme. the scheme combines pointer forwarding and caching methods. every mobile host (mh) is associated with a chain of anchors that connects it to its home agent. each anchor defines the location of the mh at a certain degree of accuracy. the accuracy is increased along the chain until the attachment point of the mh is reached. we develop distributed procedures for updating the anchor chain (binding operation) with mh movements and for delivering messages to a mh (delivery operation). in terms of worst case performance, the total cost of the binding operations is o(move log move), where move is the total geographic distance that the mh has traveled since its activation. the total length of the mh's pointer path is linear with the distance between the mh and its home network, and the delivery cost is near optimal. in addition, the anchor chain of a mh is determined dynamically with no need for preliminary definitions of static anchors or regions. our simulation results show that the anchor chain scheme also yields lower average overheads for both the binding and the delivery operations than other methods that are described in the literature, including the current home approach. we believe that the proposed scheme is scalable, fairly easy to implement and there fore attractive for supporting mhs.
efficient handoff rerouting algorithms: a competitive on-line algorithmic approach. this paper considers the design of handoff rerouting algorithms for reducing the overall session cost in personal communication systems (pcs). most modern communication systems that are used as an infrastructure for pcs networks are based on connection-based technologies. in these systems, the session cost is composed of two components. the setup cost represents the cost associated with the handoff operations, and the hold cost determines the expense related to the use of network resources held by the connection. this work introduces for the first time, rerouting algorithms for general graphs which are cost effective in terms of their worst-case analysis. the algorithms are analyzed using a competitive analysis approach, and it is proved that the competitive ratio of the proposed algorithms is a small constant of which the precise value depends on the ratio between the setup costs and the hold costs of the links. we also prove a lower bound of 2 on the competitive ratio of any online algorithm, which means that the proposed algorithms are close in terms of worst case behavior to the best possible rerouting algorithm. in addition, experimental results also show that the proposed algorithms indeed balance between the session setup cost and the hold cost, yielding overall lower cost when compared to other algorithms described in the literature.
robust monitoring of link delays and faults in ip networks. in this paper, we develop failure-resilient techniques for monitoring link delays and faults in a service provider or enterprise ip network. our two-phased approach attempts to minimize both the monitoring infrastructure costs as well as the additional traffic due to probe messages. in the first phase, we compute the locations of a minimal set of monitoring stations such that all network links are covered, even in the presence of several link failures. subsequently, in the second phase, we compute a minimal set of probe messages that are transmitted by the stations to measure link delays and isolate network faults. we show that both the station selection problem as well as the probe assignment problem are np-hard. we then propose greedy approximation algorithms that achieve a logarithmic approximation factor for the station selection problem and a constant factor for the probe assignment problem. these approximation ratios are provably very close to the best possible bounds for any algorithm.
delay jitter bounds and packet scale rate guarantee for expedited forwarding. we consider the definition of the expedited forwarding per-hop behavior (ef phb) as given in rfc 2598 and its impact on worst case end-to-end delay jitter. on the one hand, the definition in rfc 2598 can be used to predict extremely low end-to-end delay jitter, independent of the network scale. on the other hand, we find that the worst case delay jitter can be made arbitrarily large, while each flow traverses at most a specified number of hops, if we allow networks to become arbitrarily large; this is in contradiction with the previous statement. we analyze where the contradiction originates and find the explanation. it resides in the fact that the definition in rfc 2598 is not easily implementable in schedulers we know of, mainly because it is not formal enough, and also because it does not contain an error term. we propose a new definition for the ef phb, called "packet scale rate guarantee" (psrg) that preserves the spirit of rfc 2598 while allowing a number of reasonable implementations and has very useful properties for per-node and end-to-end network engineering. we show that this definition implies a rate-latency service curve property. we also show that it is equivalent, in some sense, to the stronger concept of "adaptive service guarantee." then we propose some proven bounds on delay jitter for networks implementing this new definition, both in cases without loss and with loss.
code assignment for hidden terminal interference avoidance in multihop packet radio networks. hidden terminal interference is caused by the simultaneous transmission of two stations that cannot hear each other, but are both received by the same destination station. the authors investigate the problem of assigning orthogonal codes to stations to eliminate the hidden terminal interference and minimize the number of codes used. it is shown that this problem is computationally intractable, even for very restricted but very realistic network topologies. optimal algorithms for code assignment in special networks, as well as both centralized and distributed suboptimal heuristic algorithms for general topologies, are presented. the results of extensive simulations to derive the average performance of the proposed heuristics on realistic network topologies are presented
inference and labeling of metric-induced network topologies. the development and deployment of distributed network-aware applications and services require the ability to compile and maintain a model of the underlying network resources with respect to one or more characteristic properties of interest. to be manageable, such models must be compact; and to be general-purpose, should enable a representation of properties along temporal, spatial, and measurement resolution dimensions. in this paper, we propose mint¿a general framework for the construction of such metric-induced models using end-to-end measurements. we present the basic theoretical underpinnings of mint for a broad class of performance metrics, and describe periscope, a linux embodiment of mint constructions. we instantiate mint and periscope for a specific metric of interest¿namely, packet loss rates¿and present results of simulations and internet measurements that confirm the effectiveness and robustness of our constructions over a wide range of network conditions.
tcp boston: a fragmentation-tolerant tcp protocol for atm networks. the popularity of tcp/ip coupled with the premise of high speed communication using asynchronous transfer mode (atm) technology have prompted the network research community to propose a number of techniques to adapt tcp/ip to atm network environments. atm offers available bit rate (abr) and unspecified bit rate (ubr) services for best-effort traffic, such as conventional file transfer. however, recent studies have shown that tcp/ip, when implemented using abr or ubr, leads to serious performance degradations, especially when the utilization of network resources (such as switch buffers) is high. proposed techniques---switch-level enhancements, for example---that attempt to patch up tcp/ip over atms have had limited success in alleviating this problem. the major reason for tcp/ip's poor performance over atms has been consistently attributed to packet fragmentation, which is the result of atm's 53-byte cell-oriented switching architecture.in this paper, we present a new transport protocol, tcp boston, that turns atm's 53-byte cell-oriented switching architecture into an advantage for tcp/ip. at the core of tcp boston is the adaptive information dispersal algorithm (aida), an efficient encoding technique that allows for dynamic redundancy control. aida makes tcp/ip's performance less sensitive to cell losses, thus ensuring a graceful degradation of tcp/ip's performance when faced with congested resources. in this paper, we introduce aida and overview the main features of tcp boston. we present detailed simulation results that show the superiority of our protocol when compared to other adaptations of tcp/ip over atms. in particular, we show that tcp boston improves tcp/ip's performance over atms for both network-centric metrics (e.g., effective throughput) and application-centric metrics (e.g., response time).
application-layer anycasting. server replication is a key approach for maintaining user-perceived quality of service within a geographically wide-spread network. the anycasting communication paradigm is designed to support server replication by allowing applications to easily select and communicate with the ``best" server, according to some performance or policy criteria, in a group of content-equivalent servers. we examine the definition and support of the anycasting paradigm at the application layer, providing a service that maps anycast domain names into one or more ip addresses using anycast resolvers. in addition to being independent from network-layer support, our definition includes the notion of filters, functions that are applied to groups of addresses to affect the selection process. we consider both metric-based filters (e.g., server response time) and policy-based filters; we further allow filtering both at the anycast resolver and local to the anycast client. a key input to the filtering process is metric information describing the relative performance of replicated servers. we examine the use of various techniques for maintaining this information at anycast resolvers.
distributed channel allocation for pcn with bursty traffic. considers the design of efficient channel allocation algorithms in personal communication networks where the cells have varying traffic loads. a common communication channel is to be dynamically shared between the cells. the authors propose a distributed inter-cell channel allocation policy that is easy to implement through the use of simple signalling between neighboring cells. for cells arranged in a line they show that the proposed policy achieves maximum throughput. the same is true when the cells are arranged in a circle and the channel can be reused in every other cell. for larger reuse distances and planar hexagonal arrays, the policy may not always achieve maximal throughput. for these cases the authors provide regions of achievable cell throughputs under the proposed policy and show that they are tight in certain cases.
efficient rate-controlled bulk data transfer using multiple multicast groups. controlling the rate of bulk data multicast to a large number of receivers is difficult, due to the heterogeneity among the end systems' capabilities and their available network bandwidth. if the data transfer rate is too high, some receivers will lose data, and retransmissions will be required. if the data transfer rate is too slow, an inordinate amount of time will be required to transfer the data. in this paper, we examine an approach toward rate-controlled multicast of bulk data in which the sender uses multiple multicast groups to transmit data at different rates to different subgroups of receivers. we present simple algorithms for determining the transmission rate associated with each multicast channel, based on static resource constraints, e.g., network bandwidth bottlenecks. transmission rates are chosen so as to minimize the average time needed to transfer data to all receivers. analysis and simulation are used to show that our policies for rate selection perform well for large and diverse receiver groups and make efficient use of network bandwidth. moreover, we find that only a small number of multicast groups are needed to reap most of the possible performance benefits.
non stationary request distribution in video on demand networks. several works have recently appeared in the literature on the design, performance and dimensioning of networks supporting video on demand and multimedia services. it has been shown that performance is strongly dependent on the model adopted to describe the user's behaviour in terms of requests for programs. in this paper we provide a detailed investigation of a non stationary model for the user's request distribution. numerical results are provided for a network scenario proposed in the literature to investigate the error achieved when the non stationary distribution is approximated with a stationary exponential one.
fiber-optic bus-oriented single-hop interconnections among multi-transceiver stations. the single-path selective-broadcast interconnection (sbi) is a static, passive interconnection among a set of stations, each equipped with multiple c transmitters and receivers. it uses c 2 buses, each interconnecting a subset of the stations, and provides a single common bus to any two stations. the author explores those merits of this sbi which are related directly to its implementation in fiber optics. when compared with c buses, each interconnecting all stations, the sbi is shown to offer substantial advantages in power budget and the maximum number of stations that can be interconnected without repeaters or amplifiers. it is also attractive in terms of the required passive fiber optic components such as fiber segments and star couplers. for a fixed power budget and direct detection, the capacity of this sbi is shown to be highest among bus-oriented single-hop interconnections for both a uniform traffic pattern and the worst-case unknown skew
computing approximate blocking probabilities for a class of all-optical networks. studies a class of all-optical networks using wavelength division multiplexing and wavelength routing in which a connection between a pair of nodes in the network is assigned a path and a wavelength on that path. moreover, on the links of that path no other connection can share the assigned wavelength. using a generalized reduced load approximation scheme the authors calculate the blocking probabilities for the optical network model for two routing schemes: fixed routing and least loaded routing.
routing and wavelength assignment methods in single-hop all-optical networks with blocking. we consider single-hop all-optical networks in which wavelength-routed connections (lightpaths) between source-destination pairs are dynamically established and torn down in response to a random pattern of arriving connection requests and connection holding times. a connection request may be blocked if no wavelength is available on a suitable path from source to destination. for these networks we consider several methods for routing and wavelength assignment which combine in various ways three main principles: wavelength reservation, protecting threshold and alternate routes. the methods are evaluated and compared in two case studies. in this type of network the traffic over lightpaths consisting of multiple links is susceptible to high blocking probabilities, which can interfere with the quality of service requirements. it is shown that some of the routing and wavelength assignment methods studied have the potential to overcome this difficulty.
call admissibility for multirate traffic in wireless atm networks. for multirate wireless atm traffic, the first part of the call admission process is to determine whether to admit calls as long as bandwidth is available or to deny admission to a call of a particular class even if there is enough bandwidth available, in the hope of admitting calls of some other class later. a second part of the process is to determine if the quality of service requested by the call can be met. a scenario in which the first part is particularly important is when the blocking probability requirements for different classes is different. in this paper, we consider four policies to determine the circumstances under which calls of different types are {\it admissible}. for each of these policies, we show how to compute the blocking probabilities. for three of these policies, the blocking probabilities can be found by using results from product form networks. for the fourth, we provide an approximation which works extremely well in practice. we also formulate a non-linear programming problem which attempts to determine the parameters of the admissibility policies in such a way to maximize the call arrival rates while keeping the blocking probabilities under specified bounds. we provide an algorithm for solving the non-linear programming problem and use this as a basis for comparing the policies. we show that under some circumstances, it is possible to improve the system throughput by as much as 35\% by a suitable use of the admissibility policies. this improvement in throughput is particularly important in wireless atm networks, supporting high rate multimedia traffic because of the inherent limitations in bandwidth availability.
performance analysis of statistical multiplexing of vbr sources. the authors propose a versatile point process as a model for a large class of variable bit rate sources and their superpositions. the process belongs to the class of discrete-time batch markovian arrival processes. its use leads to computationally tractable and accurate solutions for the following performance measures of the related statistical multiplexer: buffer occupancy distribution, cell loss probability, and conditional cell loss probability. it is shown that the output process of the multiplexer belongs to the same class of processes
object-oriented network protocols. a wide-range of various network communication services and protocols is required to efficiently support the diverse networks and their applications. it is usual to design a protocol for each new service which is required. an attractive alternative is to use a modular and object-oriented architecture for the design and implementation of network protocols. with it, protocols for individual service provision can be created by simply combining generic protocol functions blocks. the first part of this paper presents a new reference model which gives a foundation for the object-oriented design and implementation of modular network protocols. the second part discusses a case study of an existing object-oriented network communication system.
adaptive bandwidth allocation by hierarchical control of multiple atm traffic classes. the authors introduce a control strategy for bandwidth management in asynchronous transfer mode (atm) networks. a two-level hierarchy is defined, where one level performs fixed class-selective call admission control strategies that are periodically dynamically coordinated by a higher-level bandwidth allocation controller. each admission controller decides to accept or refuse an incoming call on the basis of a class-selective rule designed to maintain a certain quality of service. a decision is taken according to the virtual capacity share that is assigned to the various service classes by the allocation controller. bandwidth shares are periodically recomputed online by means of the constrained minimization of a cost function that takes cell loss probability and refused traffic into account. the control structure, the strategies, and the optimization algorithm used are described as well as the assumptions underlying the choices made. initial simulation results are reported
analysis of a fluid approximation to flow control dynamics. the authors consider a flow control mechanism that dynamically regulates the rate of data flow into a network based on feedback information about the network state. such mechanisms have been introduced in a variety of networks, and have been advocated for future high-speed networks. the authors first model the flow control mechanism by a discrete-space stochastic process and define appropriate performance measures for transient and steady-state regimes. however, the model does not appear to be analytically tractable, and the authors study it through simulation. they then simplify it to a continuous-space deterministic (or fluid) model for which closed-form solutions can be derived easily. it is found that the analytical results for the fluid model agree well with the simulation results obtained using the discrete-space model. both models explicitly consider delay of the feedback information, thus making them relevant for high-speed networks
busy period analysis for an atm switching element output line. the authors consider an n&times;n asynchronous transfer mode (atm) switching element with output queuing, under a uniformity assumption for the traffic arriving on the various input lines and for the output line address of the incoming cells. the traffic on each input line is modeled as a two-state markov chain. the distribution of the busy and idle periods for each output line is analytically derived. it is concluded that it is not easy to identify a simple two-state markov chain model that provides an adequate description for the output traffic. the implications of two different output line address assignment mechanisms for the incoming cells are quantitatively described. an alternative method is outlined for the computation of the steady-state distribution of the number of cells in the system. an analysis of the numerical results is presented
efficient scheduling of nonuniform packet traffic in a wdm/tdm local lightwave network with arbitrary transceiver tuning latencies. a passive-star-based, broadcast-and-select, local lightwave network which can support a limited number of wdm channels (on the order of ten), but serve a much larger number of nodes (a few tens or hundreds), is considered. each node is equipped with one tunable transmitter and one fixed receiver, and each wdm channel is operated in a tdm fashion for carrying packet traffic. bandwidth is allocated to the node pairs when traffic flow between them is non-uniform, while also accommodating transceiver tuning latency. our approach exploits well-known results from scheduling theory to create efficient transmission schedules.
user-level performance of channel-aware scheduling algorithms in wireless data networks. channel-aware scheduling strategies, such as the proportional fair algorithm for the cdma 1xev-do system, provide an effective mechanism for improving throughput performance in wireless data networks by exploiting channel fluctuations. the performance of channel-aware scheduling algorithms has mostly been explored at the packet level for a static user population, often assuming infinite backlogs. in the present paper, we focus on the performance at the flow level in a dynamic setting with random finite-size service demands. we show that in certain cases the user-level performance may be evaluated by means of a multiclass processor-sharing model where the total service rate varies with the total number of users. the latter model provides explicit formulas for the distribution of the number of active users of the various classes, the mean response times, the blocking probabilities, and the throughput. in addition we show that, in the presence of channel variations, greedy, myopic strategies which maximize throughput in a static scenario, may result in sub-optimal throughput performance for a dynamic user configuration and cause potential instability effects.
asymptotic behavior of generalized processor sharing with long-tailed traffic sources. we analyze the asymptotic behavior of long-tailed traffic sources under the generalized processor sharing (gps) discipline. gps-based scheduling algorithms, such as weighted fair queueing, have emerged as an important mechanism for achieving differentiated quality-of-service in integrated-services networks. under certain conditions, we prove that in an asymptotic sense an individual source with long-tailed traffic characteristics is effectively served at a {\em constant} rate, which may be interpreted as the maximum feasible average rate for that source to be stable. thus, asymptotically, the source is only affected by the traffic characteristics of the other sources through their average rate. in particular, the source is essentially immune from excessive activity of sources with `heavier''-tailed traffic characteristics. this suggests that gps-based scheduling algorithms provide an effective mechanism for extracting high multiplexing gains, while protecting individual connections.
packet scale rate guarantee for non-fifo nodes. packet scale rate guarantee (psrg) is a generic node model which underlies the definition of expedited forwarding (ef) proposed in the context of internet differentiated services. for the case of first-in-first-out (fifo) nodes, psrg is equivalent to the well-understood concept of adaptive service curve. however, in practice, many devices do not necessarily preserve the fifo property, and therefore, known fifo results do not hold. this paper analyzes the properties of psrg in the absence of fifo assumption. our analysis is based on a novel characterization of psrg which avoids the use of virtual finish times and is obtained by min-max algebra. we use it to show that delay bounds previously obtained for the fifo case are still valid; in contrast, we find that this is not true for the characterization of the concatenation of two nodes.
the fairness of dqdb networks with slot reuse. the paper analyzes the fairness characteristics of two previously proposed slot reuse protocols for dqdb networks. in particular, the slot reuse protocol proposed for the ieee 802.6e standard [hassanein et al., 1994] results in unfair steady state bandwidth allocations for some overloaded dqdb networks and can cause unbounded access delays under some stable workloads. in contrast, a previously proposed simple counter protocol results in bandwidth allocations in overload that are shown to be at least weakly fair for all workloads and optimally fair for many important workloads. this simple protocol also guarantees bounded access delays for any stable workload. a new modified counter protocol is proposed that has superior fairness characteristics to either of the previous protocols.
copy emulation in checksummed, multiple-packet communication. data copying can be a bottleneck in end-to-end communication over high-speed networks. emulated copy is an alternative i/o data passing scheme that preserves the api and integrity guarantees of copying but avoids the latter using vm manipulations -- transient output copy-on-write (tcow), input alignment, and page swapping. we characterize and evaluate the support necessary in network adapters for emulated copy in checksummed, multiple-packet communication. our experiments on an atm network show that: (1) emulated copy gives performance better than that of copying even without hardware checksumming support; (2) tcow improves multiple-packet output performance without any hardware support or changes in applications; (3) page swapping provides additional similar improvements on multiple-packet input if there is input alignment, which requires either hardware support (early-demultiplexed/system-aligned buffering) or changes in applications (pooled/application-aligned buffering); and (4) the performance of application-aligned buffering is largely unaffected by header/data splitting, a common optimization.we propose a new optimization, buffer snap-off, that extends system-aligned buffering to the general case of arbitrary, unmatched data transfer and application input buffer lengths.
connectivity, performance, and resiliency of ip-based cdma radio access networks. ip-based radio access networks (ran) are expected to be the next generation access networks in umts and cdma networks. the question of connectivity, i.e., how best to connect base stations to the radio network controllers (rnc) in an ip-based ran, has not been addressed by researchers. furthermore, given a connection configuration, an rnc selection algorithm that assigns an incoming call to an rnc is also necessary. this paper examines ran connectivity and its impact on the performance and resiliency of the wireless network using different rnc selection algorithms. for homogeneous networks, we show that the proposed min-load-1 algorithm, which allows at most one hard handoff in order to accommodate each incoming call request, delivers performance close to the optimal algorithm. we also show that allowing a few base stations to connect to two rncs (a 10 percent increase in the number of links in our network) results in resiliency to rnc failures that is comparable to the resiliency of rans with full-mesh connectivity. finally, for heterogeneous networks, we show that the min-load-k algorithm (with at most k hard handoffs per call) is effective in handling load imbalances. these results provide strong motivation for deploying ip-based ran, as they suggest that enhancing current point-to-point ran with few additional links and allowing a few hard handoffs to accommodate incoming calls can result in significant gains in performance and resiliency.
a generic flow control protocol for b-isdn. a generic flow control (gfc) protocol is proposed to regulate multiple terminals within the broadband-isdn customer premises network. the gfc protocol is based on multipriority distributed queuing preceded by a traffic shaping function, and meets the requirements for flexible allocation of service parameters, control of jitter and guarantee of bandwidth. this gfc protocol provides the necessary flexibility to match the constant bit rate (cbr) jitter performance and variable bit rate (vbr) service requirements to the particular service type. it integrates well with usage parameter control without imposing excessive burstiness on each virtual connection cell stream delivered to the network. by allowing connectionless users to access at the lowest priority, only when no higher priority users are queued, there is no reduction in guaranteed capacity available for other vbr and cbr users
mv routing and capacity building in disruption tolerant networks. disruption-tolerant networks (dtns) differ from other types of networks in that capacity is created by the movements of network participants. this implies that understanding and influencing the participants' motions can have a significant impact on network performance. in this paper, we introduce the routing protocol mora, which learns structure in the movement patterns of network participants and uses it to enable informed message passing. we also propose the introduction of autonomous agents as additional participants in dtns. these agents adapt their movements in response to variations in network capacity and demand. we use multi-objective control methods from robotics to generate motions capable of optimizing multiple network performance metrics simultaneously. we present experimental evidence that these strategies, individually and in conjunction, result in significant performance improvements in dtns.
fine-grained layered multicast. abstract traditional approaches to receiver-driven layered multicast have advocated the benefits of cumulative layering, which can enable coarse-grained congestion control that complies with tcp-friendliness equations over large time scales. in this paper, we quantify the costs and benefits of using non-cumulative layering and present a new, scalable multicast congestion control scheme which provides a fine-grained approximation to the behavior of tcp additive increase / multiplicative decrease (aimd). in contrast to the conventional wisdom, we demonstrate that fine-grained rate adjustment can be achieved with only modest increases in the number of layers and aggregate bandwidth consumption, while using only a small constant number of control messages to perform either additive increase or multiplicative decrease.
optimal routing and flow control in networks with real-time traffic. we address the problem of flow control and routing of `real-time traffic'' in a network, where messages must arrive at their destination within given deadlines; otherwise they are considered lost. performance in thisd case is measured in terms of the probability of losing a message. for the case of `n'' parallel links, the problem is formulated as one of optimal flow allocation and solved under gernal conditions. it is shown that for a `fcfs'' service discipline an admission policy rejecting messages before link assignment is optimal when the load exceeds a critical value. thus, we take advantage of the fact that if some messages will exceed their deadlines anyway, it is beneficial not to admit them in the first place. an efficient algorithm for explicitly solving the problem is presented and specific examples are analyzed. we also discuss the applicability of on- line algorithms for this problem when modelling assumptions cannot be made.
server selection using dynamic path characterization in wide-area networks. using tools to measure available bandwidth and round trip latency (rtt), we demonstrate dynamic server selection and compare it to previous static approaches. we show that because of the variability of paths in the internet, dynamic server selection consistently outperforms static policies, reducing response times by as much as 50%.however, we also must adopt a systems perspective and consider the impact of the measurement method on the network. therefore, we look at alternative low-cost approximations and find that the careful measurements provided by our tools can be closely approximated by much lighter-weight measurements. we propose a protocol using this method which is limited to at most a 1% increase in network traffic but which often costs much less in practice.
a new class of qos routing strategies based on network graph reduction. this paper discusses a new approach to qos routing, introducing the notion of algorithm resilience (i.e., its capability to adapt to network and load modifications) as performance index of the algorithm itself.the new approach can be summarized as network graph reduction, i.e., a modification of the graph describing the network before the routing path is computed, in order to exclude from the path selection over-congested portions of the network. this solution leads to a class of two-step routing algorithms, where both steps are simple, hence allowing efficient implementation.simulation experiments, run on randomly-generated topologies and traffic patterns, show that these routing algorithms perform consistently better than both the standard minimum hop algorithm and those qos-based algorithms based on the same metrics but not using the notion of network graph reduction.
fast algorithms for measurement-based traffic modeling. this paper develops fast algorithms for construction of circulant modulated rate process to match with two primary traffic statistical functions: distribution $f(x)$ and autocorrelation $r(\tau)$ of the rate process. using existing modeling techniques, $f(x)$ has to be limited to certain forms such as gaussian or binomial; $r(\tau)$ can only consist of one or two exponential terms which are often real exponentials rather than complex. in reality, these two functions are collective from real traffic traces and generally expressed in much complicated form. our emphasis here is placed on the algorithmic design for matching complicated $r(\tau)$ in traffic modeling. the typical cpu time for the traffic modeling with $r(\tau)$ consisting of five or six complex exponential terms is found in the range of a few minutes by the proposed algorithms. our study further shows an excellent agreement between original traffic traces and sequences generated by the matched analytical model.
design of virtual channel queue in an atm broadband terminal adaptor. it is desirable to interconnect different computer hosts and local area networks (lans) through the asynchronous transfer mode (atm) network via broadband terminal adaptors (btas). the bta must have a sufficiently large buffer, called a virtual channel queue (vcq), to temporarily store multiple, partially received packets from different virtual channels. the buffer requirement of a shared-memory vcq is studied for different packet loss probabilities and virtual channel numbers. two different architectures for implementing the shared-memory vcq are compared. the second architecture with multiple linked queues in the shared-memory requires less memory and has better scalability to accommodate a large number of virtual channels and is adopted in the analysis. several possible error conditions, such as shared-memory overflow, the received packet exceeding its maximum length, and the corruption of the pointer in the logical queue, are discussed. corresponding solutions are proposed in the vcq designs
ascent: adaptive self-configuring sensor networks topologies.. advances in microsensor and radio technology will enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. the low per-node cost will allow these wireless networks of sensors and actuators to be densely distributed. the nodes in these dense networks will coordinate to perform the distributed sensing and actuation tasks. moreover, as described in this paper, the nodes can also coordinate to exploit the redundancy provided by high density so as to extend overall system lifetime. the large number of nodes deployed in these systems will preclude manual configuration, and the environmental dynamics will preclude design-time preconfiguration. therefore, nodes will have to self-configure to establish a topology that provides communication under stringent energy constraints. ascent builds on the notion that, as density increases, only a subset of the nodes are necessary to establish a routing forwarding backbone. in ascent, each node assesses its connectivity and adapts its participation in the multihop network topology based on the measured operating region. this paper motivates and describes the ascent algorithm and presents analysis, simulation, and experimental measurements. we show that the system achieves linear increase in energy savings as a function of the density and the convergence time required in case of node failures while still providing adequate connectivity.
resource optimization in qos multicast routing of real-time multimedia. we consider a network design problem, where applications require various levels of quality-of-service (qos) while connections have limited performance. suppose that a source needs to send a message to a heterogeneous set of receivers. the objective is to design a low-cost multicast tree from the source that would provide the qos levels (e.g., bandwidth) requested by the receivers. we assume that the qos level required on a link is the maximum among the qos levels of the receivers that are connected to the source through the link. in accordance, we define the cost of a link to be a function of the qos level that it provides. this definition of cost makes this optimization problem more general than the classical steiner tree problem. we consider several variants of this problem all of which are proved to be np-hard. for the variant where qos levels of a link can vary arbitrarily and the cost function is linear in its qos level, we give a heuristic that achieves a multicast tree with cost at most a constant times the cost of an optimal multicast tree. the constant depends on the best constant approximation ratio of the classical steiner tree problem. for the more general variant, where each link has a given qos level and cost we present a heuristic that generates a multicast tree with cost o(min {log r, k}) times the cost of an optimal tree, where r denotes the number of receivers, and k denotes the number of different levels of qos required. we generalize this result to hold for the case of many multicast groups.
optical switch configuration and lightpath assignment in wavelength routing multihop lightwave networks. a wide-area transparent optical network can be constructed by using wavelength routers and switches, each dealing with only a small number of wavelengths. in this work we consider the problem of configuring the wavelength routers based on the observed traffic. various policies for wavelength routing, and the corresponding assignment of wavelengths along the routes have been studied before, which are based on minimizing congestion, average hop-distance, and call blocking probability or on maximizing carried traffic, and the number of clear channels. however these approaches often lead to scenarios where a significant number of available wavelengths at the input/output ports of the routers cannot be used due to potential wavelength conflict. the wavelength routing and assignment algorithms presented in this paper focus on maximizing the wavelength-utilization at the switching devices which also improve the overall network performance.
design of a fast restoration mechanism for virtual path-based atm networks. in this paper, we propose a fast restoration mechanism for virtual path-based atm networks. given an atm network topology, the capacity of each physical link, and the primary virtual path (vp) layout at system initialization, the proposed mechanism pre-assigns to each primary vp one backup vp such that (p1) the failure of a single node/link does not lead to the failure of both the primary and backup vps, (p2) the alternate backup vp is routed on a path with the shortest hop count among all possible paths with sufficient bandwidth between the two vp terminators, and (p3) the maximum link load is minimized.during system operation, if a physical node/link fails, the proposed mechanism restores the vps that traverse the failed node/link simply by redirecting cells on the failed vps to their corresponding backup vps. moreover, the proposed mechanism also locates (i) new vps for injured backup vps that traverse the failed node/link, and (ii) second-generation backup vps for newly-activated backup vps that replace their corresponding failed primary vps, both in a decentralized manner.we elaborate on all the component algorithms, and discuss how to configure the functionalities as software daemons that reside at each network node. the proposed mechanism is shown via event-driven simulation to be practically feasible in fast restoring failed vps in a cost effective manner.
multiconnection over multichannels. studies a multiconnection problem, in multichannel networks and proposes an effective multiconnection protocol for establishing and releasing connections with dynamic bandwidth requirement. each originating station in the network is allowed to set up connections to several terminating stations, and send packets to these terminating stations in different slots in a tdm fashion. similarly, each terminating station is allowed to keep connections with several originating stations, and receive packets from these originating stations in different slots in a tdm fashion. effective slot allocation schemes for multiple connections at the same station, as well as conditions for strict-sense acceptance and rearrangeable acceptance are given.
performance of multicasting closed interconnection networks. this paper examines the application of a simple yet general packet replication scheme to achieve multicasting in closed interconnection networks. the performance of these networks is studied and a general throughput equation is obtained to express the overall network throughput in terms of the average routing delay of the corresponding point-to-point network. the multicast performance results are thus built on top of the previously-established, and often simpler, point-to-point results. making use of this formula, we investigate the multicast closed shuffle-exchange network in detail. analytical results are compared with simulation results to obtain further insights into the network operation and ways to improve the network performance.
improving tcp/ip performance over third generation wireless networks. as third generation (3g) wireless networks with high data rate get widely deployed, optimizing tcp performance over these networks would have a broad and significant impact on data application performance. one of the biggest challenges in optimizing tcp performance over the 3g wireless networks is adapting to the significant delay and rate variations over the wireless channel. in this paper, we make two main contributions. first, we present a window regulator algorithm that uses the receiver window field in the acknowledgment packets to convey the instantaneous wireless channel conditions to the tcp source and an ack buffer to absorb the channel variations, thereby maximizing long-lived tcp performance. it improves the performance of tcp sack by up to 100\\% over a simple drop-tail policy with small buffer sizes at the congested router. second, we present a wireless channel and tcp-aware scheduling and buffer sharing algorithm that reduces the latency of short tcp flows while still exploiting user diversity for a wide range of user channel conditions.
experimental evaluation of atm congestion control mechanisms. a critical issue in the design of fast packet-switch-based networks is the avoidance of data loss due to congestion. in the context of atm networks, many link-level congestion control mechanisms for abr traffic have been proposed and simulated, and a few have been implemented. this paper presents, for the first time, an experimental comparison of several such mechanisms. to drive this comparison, we have developed a set of benchmarks that provide a quantitative characterization of congestion control performance. we also describe a simple but novel technique, the ``virtual port card'', for implementing both non-native switch behavior and long link delays in atm networks. this technique allows us to compare a wide range of mechanisms on a single flexible hardware platform. our measurements show that while several of the atm flow control mechanisms can eliminate cell loss, there are still several unresolved problems. first, for some traffic scenarios we see very poor application-level performance, especially in the presence of bursty traffic. second, performance is very sensitive to the flow control parameters and identifying an appropriate set of parameters is difficult since it depends heavily on the traffic conditions.
reliability analysis of sparse topologies for packet radio networks. four connectivity measures are used to compare the reliability of various sparse topologies for packet radio networks. different scenarios, including link failures, node failures, and both types of failures, were simulated for fixed-radius, nearest-neighbor, angle-constrained, degree-constrained, and delaunay triangulation-based topologies. the simulation results demonstrated that the commonly used fixed-radius topologies were the worst among all topologies tested. also, the results showed that triangulation-based and angle-constrained topologies maintained high reliability even under component failures
a filtering theory for deterministic traffic regulation. in this paper, we develop a filtering theory for deterministic traffic regulators that generate f-constrained outputs. we show that such regulators can be implemented by a linear time invariant filter with the impulse response f under the (min,+)-algebra if the function f is increasing and subadditive. the filtering approach not only yields easier proofs for more general results than those in the literature, but also allows us to design traffic regulators via systematic methods such as concatenation, filter bank summation, linear system realization, and fir-iir realization. the theory has many applications, including leaky buckets, traffic regulation for periodic constraint functions, and service curves. in particular, we find a new linear system realization and a new fir-iir realization for a concatenation of leaky buckets. moreover, we find a fir-iir realization for traffic regulators with periodic constraint functions. we also show that such regulators, in conjunction with maximum delay guarantee, guarantee shifted-subadditive service curves. based on this, we provide a couple of rules for service curve allocation among a concatenation of servers. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
on algorithms searching for quasi-optimal subfamilies of gmw sequences suitable for cdma applications. this paper studies several algorithms for constructing quasi-optimal gmw subfamilies in terms of minimized bit error rate under co-channel interference. the results show that performance of resultant sub-families is very sensitive to the algorithms applied and sub-family sizes. a new criterion based on combinational (even plus odd) maximum cross-correlation is introduced for code selection and the resultant highest-peak-deleting and most-peak-deleting algorithms are effective to construct the gmw quasi-optimal sub-families.
computable exponential bounds for intree networks with routing. in this paper, we refine the calculus proposed previously by chang et al. (1994). the new calculus, including network operations for multiplexing, input-output relation, and routing, allows us to compute tighter exponential bounds for the tail distributions of queue lengths in intree networks with routing. in particular, if external arrival processes and routing processes are either markov arrival processes or autoregressive processes, the stationary queue length at a local node is stochastically bounded above by the sum of a constant and an erlang random variable. the decay rate of the erlang random variable is not greater than (in some cases equal to) the decay rate of the tail distribution of the stationary queue length. the number of stages of the erlang random variable is the number of external arrival processes and routing processes contributing to its queue length. for the single queue case, both the lower and upper-bounds are derived.
a bandwidth sharing theory for a large number of http-like connections. there has been tremendous progress in understanding how bandwidth is shared by tcp-like connections. by associating each tcp-like connection with a utility function, the bandwidth sharing problem of tcp-like connections can be modeled as a distributed optimization problem for utility functions. however, little is known on how bandwidth is shared by http-like connections through their utility functions at the tcp level. one of the main objectives of this paper is to provide a theory for bandwidth sharing of a large number of http-like connections. based on certain technical assumptions, we show that there is a utility function at the http level for an http-like connection and such a utility function can be derived from the utility function at the tcp level. the bandwidth is then shared by http-like connections through utility functions at the http level. we also address two possible extensions of the theory: the case with impatient tcp connections and the case with multiple types of requests. with appropriate modification of the utility functions at the http level, we show that the bandwidth is still shared by optimizing their utility functions at the http level for the case with impatient tcp connections. for the case with multiple types of requests, the bandwidth shared at the http level can still be found by solving a unique fixed point limit.
a buffer management scheme for the scoq switch under nonuniform traffic loading. the scoq switch is a batcher-banyan-based high-performance fast packet switch with shared concentration and output queuing, with a maximum of l(<n, the switch size) packets delivered to each output buffer in a slot. the authors consider the performance of the scoq switch under nonuniform traffic loading. based on the analysis of nonuniform traffic patterns, a buffer management congestion control scheme is proposed with the k=n/l output parts of each of the l switching modules sharing their buffering capacity. numerical results show that the buffer management scheme is effective
psd-based neural-net connection admission control. atm (asynchronous transfer mode) systems can support services with bursty traffic. an atm system needs a sophisticated and real-time connection admission controller not only to guarantee the required quality-of-service (qos) for existing calls but also to raise the system efficiency. input process has a power-spectral-density (psd) which explicitly contains the correlation behavior of input traffic and has a great impact on the system performance. also, a neural network has been widely applied to deal with traffic control related problems in atm systems because of its self-learning capability. in this paper, we propose a psd-based neural-net connection admission control (pncac) method for an atm system. under the qos constraint, we construct a decision hyperplane of the connection admission control according to parameters of the power spectrum. we further adopt the learning/adapting capabilities of the neural network to adjust the optimum location of the boundary between these two decision spaces. simulation results show that the pncac method provides a superior system utilization over the conventional cac schemes by an amount of 18%, while keeping the qos contract.
providing guaranteed rate services in the load balanced birkhoff-von neumann switches. in this paper, we propose two schemes for the load balanced birkhoff-von neumann switches to provide guaranteed rate services. the first scheme is based on an earliest eligible time first (eetf) policy. in such a scheme, we assign every packet of a guaranteed rate flow a targeted departure time that is the departure time from the corresponding work conserving link with capacity equal to the guaranteed rate. by implementing the eetf policy with jitter control mechanisms and first come first serve (fcfs) queues, we show that the end-to-end delay for every packet of a guaranteed rate flow is bounded by the sum of its targeted departure time and a constant that only depends on the number of flows and the size of the switch.our second scheme is a frame based scheme as in keslassy and mckeown, 2002. there, time slots are grouped into fixed size frames. packets are placed in appropriate bins (buffers) according to their arrival times and their flows. we show that if the incoming traffic satisfies certain rate assumptions, then the end-to-end delay for every packet and the size of the central buffers are both bounded by constants that only depend on the size of the switches and the frame size. the second scheme is much simpler than the first one in many aspects: 1) the on-line complexity is o(1) as there is no need for complicated scheduling; 2) central buffers are finite and thus can be built into a single chip; 3) connection patterns of the two switch fabrics are changed less frequently; 4) there is no need for resequencing-and-output buffer after the second stage; and 5) variable length packets may be handled without segmentation and reassembly.
nfs dynamics over flow-controlled wide area networks. the network file system protocol (nfs) has been the leading distributed file system for workstations since it was first introduced by sun microsystems in 1986. the geographical scale of nfs has been limited to the local area due to its relatively low performance on the wide area internet. however, with the advent of high bandwidth wide area networks such as atm, nfs over wans may become more promising. in this paper, the performance of nfs over various sizes of wan is studied. the effects of atm flow- control and queuing strategies on nfs are discussed, as are the performance of tcp and udp as nfs transport proto cols. the primary conclusion is that standard nfs over udp works well over atm wans as long as atm-level flow control keeps the cell loss rate under one percent. in some cases, nfs over tcp works badly with small packets due to unfortunate interactions with tcp's congestion window.
delay analyses of token-passing protocols with limited token holding times. the authors consider the ieee 802.4 token-bus, ieee 802.5 token-ring, and fiber distributed data interface (fddi) network standards. they perform the delay analyses for these token-passing network standards when all the network traffic is of the highest priority class. they model them in an unified manner as a cyclic-service system with exhaustive time-limited service policies. they have specifically considered two variants of the time-limited service policies-nonpreemptive and look-ahead. the former models the token-bus and the latter models the token-ring and fddi. the major result is an algorithm to approximate the mean delays for the nonpreemptive policy. numerical results show that the algorithm is reasonably accurate for deterministic and exponential frame sizes. the algorithm is applied to the performance analysis of a token-bus. a similar approach for the look-ahead policy is outlined
buffer sharing in conflict-free wdma networks. a wavelength division multiaccess network with buffer sharing among stations is studied. all stations in the network are connected to a passive optical star coupler and each station has a different fixed wavelength laser for transmitting packets. each station in the network reports its packet backlog to a scheduler which computes and then broadcasts a transmission schedule to all the stations through a control channel in each time slot. a transmission schedule includes two types of assignments: (1) to assign a maximum number of stations for conflict-free transmissions, and (2) to assign to relocation of packets from congested stations to uncongested relaying stations through idling transceivers for distributed buffer sharing. the major benefit is the reduction of packet loss due to buffer overflow. results show that as much as 75% of the buffers can be saved with buffer sharing
effective bandwidths of departure processes from queues with time varying capacities. in this paper, we consider a queue with a time varying capacity and identify the effective bandwidth of the stationary departure process from such a queue. two important observations are made: (i) the effective bandwidths for the transient departure process and the stationary departure process from such a queue are in general different, and (ii) sometimes it is necessary to build up the queue first in order to have a large excursion of the stationary departure process. the new result on the effective bandwidth of the stationary departure process is applied to intree networks with time varying capacities and priority tandem queues. algorithms for approximating the tail distributions of queue lengths in such networks are derived.
a simple architecture for atm switching systems. proposes a new self-routing atm switch. the switch is constructed based on a banyan network in which each inter-stage link is dilated by the stage number power of 2, each dilated link is concentrated from 2/sup d+1/ to 2/sup d/ multiple paths after stage d, and a new proposed shared-link design is used to reduce the cell blocking probabilities yielded by the concentration. by the scheme of interleaving the dilation, concentration, and sharing idle links after stage d, the new network has the advantages: (1) the delay-throughput performance is approximately the same as that of a knockout network with 2/sup d/ output links per output concentrator under the uniform traffic; (2) the hardware cost of network is of o(d2/sup d/nlogn)/spl ap/o(nlogn) as d is small; (3) the self-routing mechanism is very simple and identical to that of a banyan network; and (4) it is very feasible in vlsi design that only three simple and regular cmos chips are enough to construct any size of atm switch.
controlled request dqdb: achieving fairness and maximum throughput in the dqdb network. the author presents a new technique, called controlled request, to combat the unfairness problem in the distributed queue dual bus (dqdb) protocol that achieves 100% throughput. transmission of requests in the controlled request dqdb method is controlled by a mechanism that is similar to the one used in dqdb to transmit segments. fairness is achieved by using the bandwidth balancing technique to prevent an overloaded node form continuously transmitting requests. simulation studies showed that the controlled request dqdb scheme achieves better performance than the dqdb protocol with bandwidth balancing
matching output queueing with a combined input output queued switch. the internet is facing two problems simultaneously: we need a faster switching/routing infrastructure, and we need to introduce guaranteed qualities of service (qos). as a community, we have solutions to each: we can make the routers faster by using input-queued crossbard, instead of shared memory systems; and we can introduce qos using wfq-based packet scheduling. but we don''t know how to do both at the same time. until now, the two solutions have been mutually exclusive - all of the work on wfq- based scheduling algorithms has required that switches/routers use output- queueing, or centralized shared memory. we demonstrate that a combined input output queueing (cioq) switch running twice as fast as an input-queued switch can provide precise emulation of a broad class of packet scheduling algorithms, including wfq and strict priorities. more precisely, we show that a "speedup" of 2 - 1/n is both necessary and sufficient for this precise emulation. we introduce a variety of algorithms that configure the crossbar so that emulation is achieved with a speedup of two, and consider their running time and implementation complexity. we believe that, in the future, these results will make possible the support of qos in very high bandwidth routers.
alternative bandwidth allocation algorithms for packet video in atm networks. a two-node asynchronous transfer mode (atm) network is considered. several video sources are assumed multiplexed at the source node. five alternative algorithms for bandwidth allocation to video sources are considered using: static-slot assignment, buffer-population-based dynamic slot assignment, first-come-first-serve slot assignment and rate-based dynamic slot assignment. the average cell delay and the coefficient of variation of the delay for the five algorithms are determined by computer simulation and compared. it is concluded that the adaptive slot assignment algorithm and the buffer-population-based dynamic slot assignment algorithm are suitable for packet video in atm networks
layered required bandwidth for heterogeneous traffic. bandwidth is engineered for heterogeneous service via a layered notion of required bandwidth. the required bandwidth is requested to satisfy grade of service up to the layer of concern. the most important use of this layer required bandwidth is for bandwidth allocation at the path layer. the mathematical properties of the optimal policy are explored. based on these properties, a fast and accurate algorithm is derived for computing required bandwidth. numerical examples are given
a quantitative assured forwarding service. the assured forwarding (af) service of the ietf diffserv architecture provides a qualitative service differentiation between classes of traffic, in the sense that a low-priority class experiences higher loss rates and higher delays than a high-priority class. however, the af service does not quantify the difference in the service given to classes. in an effort to strengthen the service guarantees of the af service, we propose a quantitative assured forwarding service with absolute and proportional differentiation of loss, service rates, and packet delays. we present a feedback-based algorithm which enforces the desired class-level differentiation on a per-hop basis, without the need for admission control or signaling. measurement results from a testbed of freebsd pc-routers on a 100 mbps ethernet network show the effectiveness of the proposed service, and indicate that our implementation is suitable for networks with high data rates.
high speed communication protocols for optical star coupler using wdm. a network with n stations connected via a passive star coupler using wavelength division multiplexing (wdm) is considered. each station is equipped with a transmitter, transmitting at a fixed frequency, and a tunable receiver, capable of receiving frequencies over the entire transmitting spectrum. two reservation-based protocols are proposed for a local area network (lan) environment: the dynamic allocation scheme (das), which dynamically assigns slots on a packet-by-packet basis, and the hybrid tdm scheme (htdm) which is a combination of tdm and the das, allowing both preassigned slot and dynamic slot assignment. analytical results are derived for the delay performance of the two schemes and these results are compared with that of the tdm. it is shown that the performance of das is close to optimal when the propagation delay is zero. however, it requires a large signaling bandwidth. on the other hand, htdm has lower signaling needs, provides lower delays when compared to tdm (particularly under nonuniform traffic conditions), and is capable of handling bursty data traffic. thus, htdm offers a more practical solution for implementation for lans
an investigation of application level performance in atm networks. the goal of the paper is to investigate the relation that exists between the performance guarantees provided by a network, and what users of the network ultimately get. the focus is on the relation that exists between packet losses in a network, and message loses experienced by the application. this investigation is carried out in the context of an atm network where network packets are of fixed size (cells), and the authors concentrate mostly on the impact of the application peak transmission rate. varying this parameter for a given source while keeping network cell losses constant can translate into significant variation in the loss probability of application messages. in the paper, the authors develop and solve an analytical model to evaluate this behavior, and a set of guidelines that applications can use to determine which performance guarantees to require from the network to erasure an appropriate level of service.
a congestion control algorithm for tree-based reliable multicast protocols. this paper contains a detailed description of the congestion control algorithm of tram, a tree-based reliable multicast protocol. this algorithm takes advantage of regular acknowledgements from the receivers that propagate back to the sender via the repair tree. this scalable feedback mechanism is used to collect receiver credits. complementing the windowing mechanism, packet transmission is smoothed by using a data rate commensurate with the window size. additional details, such as how to prune slow receivers, and how to implement the rate scheduler on non-real-time systems are also discussed. the performance of the congestion control algorithm is then evaluated in extended lans, and wide area networks. the fairness of bandwidth-sharing with other (tcp) traffic is also evaluated.
openet: an open and efficient control platform for atm networks. atm networks are currently moving from the experimental stage of test-beds to a commercial state where production networks are deployed and operated. the atm forum pnni (private network to network interface) standard introduces an architecture suited for an internetwork which, in principle, can also be used as an intra-network nodal interface. however, the current pnni falls short in providing an acceptable solution due to severe performance limitations in intra-network operation, limited functionality and the lack of open interfaces for functional extensions and services. openet is a common, open and high-performance network control platform based on performance and functional enhancements to the pnni platform. it is designed to address the issues of interoperability (being vendor independent), scalability (in terms of network size and volume of calls), high performance (in terms of call processing latency and throughput) and functionality. openet is mainly an intra-networking extension to current pnni. it is compatible with pnni in the internetwork environment where large networks must be partitioned according to natural topological or organizational boundaries. the major novelty of the openet architecture (compared to the current pnni) is its focus on network control performance. a particular emphasis is given to the increase of the overall rate of connection handling, to the reduction of the call establishment latency and to the efficient utilization of the network resources. these performance enhancements are achieved by the use of a native atm distribution tree for the dissemination of utilization update, light-weight call setup, take down and modification signaling, the use of fast setup and takedown with the future option to implement them in hardware, and extensive use of caching and pre-calculation for route computation. openet also extends pnni in terms of functionality. it utilizes a new signaling paradigm that better supports fast reservation and multicast services, a rich control communication infrastructure which enables the development of augmented services leveraging the existing functions, messaging system and information of the network control platform.
optimal allocation of electronic content. the delivery of large files to individual users, such as video on demand or application programs to the envisioned network computers is expected by many to be one of the main tasks of broadband communication networks. this requires high bandwidth capacity as well as fast and dense storage servers. this motivates multimedia service providers to optimize the delivery network, as well as the electronic content allocation.a hierarchical architecture for the distribution of multimedia content was introduced by nussbaumer, patel, schaffa, and sterbenz (infocom 94). they addressed the trade-off between bandwidth and storage requirements that results from the placement of the content servers in the hierarchy tree. they presented a centralized algorithm to compute the best level of the hierarchy for the server location to minimize the combined cost of communication and storage.in this work we solve a general case where servers can be placed at different levels of the hierarchy. we develop a distributed optimal location algorithm that requires small nodal memory capacity and computational power. previous results for related problems for caching system design are of higher complexity. previous results for related classic operations research problems are limited to centralized algorithms, based on linear programming, that are not easy to convert into distributed algorithms. instead, to obtain our results, we observed that the use of dynamic programming naturally lends itself to a distributed implementation.for the specific problem at hand, we also managed to find a natural function (a generalization of the problem) that simplifies the combination operation used in the design of a dynamic program.
on packet loss processes in high-speed networks. an efficient recursive computation methodology is introduced to obtain the exact distribution of the number of lost packets in a block of packet arrivals of a given size for different arrival models and a different number of sessions. the exact distribution is compared with the distribution obtained from an independence assumption on the loss probability of packets. numerical examples are provided to show that the exact distribution may be worse than the distribution obtained under the independence assumption for applications such as forward error correction or better for applications such as straight message retransmission
virtual queueing techniques for abr service: improving abr/vbr interaction. several algorithms have been proposed for the switch behavior for congestion control of available bit rate (abr) services. schemes such as the enhanced proportional rate control algorithm (eprca) and the dynamic max rate control algorithm (dmrca), which use the queue length as congestion indicator to make a simple approximation of the fair share converge to the actual fair share, have become popular, because they offer good performance and are simple to implement. in particular, with no vbr traffic in the network, dmrca has been shown to achieve fairness in all situations, good buffer control, and robust performance. in this paper, first we show that the performance of these schemes may degrade when abr traffic interacts with highly-bursty vbr traffic. if vbr traffic induces congestion in the network, the length of the abr queue cannot serve as a reliable indicator of congestion caused by abr traffic, and the schemes perform poorly, introducing considerable unfairness. then, we propose a simple technique to solve these problems. the switch constructs the length of a virtual queue which is not affected by the instantaneous behavior of vbr traffic, and does not depend on how the two types of traffic are served in order to share the common link capacity; thus, it can serve as a reliable indicator of congestion. we use this technique in dmrca with virtual queueing (dmrca_vq), and show that the new scheme achieves fair rate allocation to the abr connections also in presence of highly-bursty vbr traffic. dmrca_vq maintains the low hardware complexity of dmrca. the virtual queueing technique is a solution for the more general problem of separating rate allocation based on the queue length from scheduling of multiple queues for sharing a common resource.
performance of reservation based (quadro) wdm star networks. the authors introduce a common modeling framework making it possible to develop tractable analytic models of optical star networks with reservation-based control. reservation-based wavelength division multiplexing (wdm) optical star systems, and in particular the quadro-based receiver design, have the performance advantages of high capacity, low response time, and adaptability to changing traffic flows. using the modeling framework introduced, tractable approximate models of reservation-controlled wdm stars were derived. it was shown that the framework allows the representation of different control strategies, while resulting in only a very small error
a fast bypass algorithm for high-speed networks. suggests an algorithm that increases the reservation success probability for bursty traffic in high speed networks by adding flexibility to the construction of the routes. the algorithm is simple enough to be implemented by cheap hardware. it causes no additional delay to packets that use the original route, and a very small delay to the packets that are rerouted. in addition, the presented algorithm has a minimal communication overhead due to the local nature of its work. two high-speed network models are considered: source routing and atm.
analysis of one-way reservation algorithms. modern high speed networks (and atm networks in particular) use resource reservation as a basic means of establishing communications. one-way on-the-fly reservation is a method for allocating resources for short bursts of data when regular reservation is too costly. the first such algorithms were recently suggested by turner. we investigate two examples that are characteristic to the way traffic streams interact in virtual circuit networks: a three node subnetwork that also acts as a 4/spl times/2 switch and a ring. for both systems we compute system throughput under homogeneous load, and compare it with the throughput when fast reservation protocols are used. for the three node subnetwork we also give an explicit expression for an upper bound.
multi-path routing combined with resource reservation. in high-speed networks it is desirable to interleave routing and resource (such as bandwidth) reservation. the pnni standard for private atm networks is a recent example for an algorithm that does this using a sequential crank-back mechanism. in this work, we suggest to do resource reservation along several routes in parallel. we present an analytical model that demonstrates that when there are several routes to the destination it pays to attempt reservation along more than a single route. following this analytic observation, we present a family of algorithms that route and reserve resources along parallel subroutes. the algorithms of the family represent different trade-offs between the speed and the quality of the established route. the presented algorithms are simulated against several legacy algorithm, including pnni crank-back, and exhibit higher network utilization and faster connection set-up time.
the programmable network prototyping system. the programmable network prototyping system (pnps) uses a collection of reusable hardware modules that implement generic communications functions such as transmission, reception, signal propagation, and pattern matching. these modules are interconnected and configured to emulate a variety of communication networks whose behavior can be monitored under different load conditions. the user specifies a network as a set of interacting components using available software tools. these tools are accessible within a prototyping environment that includes a control system for configuring the hardware modules and interconnecting them according to the component specifications. previously designed components are stored in a library and can be used to specify new networks. although pnps is designed to provide a prototyping environment for communication networks, some of the basic ideas can be useful in other contexts.
a new method to determine the queue length distribution at an atm multiplexer. in this paper, we develop a simple analytical technique to determine p({q>q}), the tail of the queue length distribution, at an atm multiplexer. the atm multiplexer is modeled as a fluid queue serving a large number of independent sources. our method is based on the central limit theorem and the maximum variance approximation, and enables us to avoid the state explosion problem. the approach is quite general and not limited by a markovian framework. we apply our analytical method to study the buffer behavior for various traffic sources such as multiplexed homogeneous and heterogeneous markov modulated sources, sources that are correlated at multiple time scales, sources whose autocorrelation function exhibits heavy (sub-exponential) tail behavior, and sources generated from real mpeg-encoded video sequences.
on the all-to-all broadcast problem in optical networks. this paper considers the transmission of uniform deterministic traffic in an optical broadcast-star network using wavelength division multiplexing. lower bounds are established on the minimum time to exchange information between every node pair in such a network with tunable transmitters and fixed-tuned receivers. three different scheduling algorithms are developed that are strictly optimal in three regimes of system parameters. the results are applicable to arbitrary tuning delays and arbitrary numbers of wavelength channels, and indicate the existence of a well-defined transition regime from tuning-limited operation to bandwidth-limited operation.
analysis of point-to-point packet delay in an operational network. in this paper, we perform a detailed analysis of point-to-point packet delay in an operational tier-1 network. the point-to-point delay is the time experienced by a packet from an ingress to an egress point in an isp, and it provides the most basic information regarding the delay performance of the isp's network. using packet traces captured in the operational network, we obtain precise point-to-point packet delay measurements and analyze the various factors affecting them. through a simple, step-by-step, systematic methodology and careful data analysis, we identify the major network factors that contribute to point-to-point packet delay and characterize their effect on the network delay performance. our findings are: (1) delay distributions vary greatly in shape, depending on the path and link utilization; (2) after constant factors dependent only on the path and packet size are removed, the 99th percentile variable delay remains under 1ms over several hops and under link utilization below 90% on a bottleneck; (3) a very small number of packets experience very large delay in short bursts.
a cellular wireless local area network with qos guarantees for heterogeneous traffic. a wireless local area network (wlan) or a cell with quality-of-service (qos) guarantees for various types of traffic is considered. a centralized (i.e., star) network topology is adopted as the topology of a cell which consists of a base station and a number of mobile clients. dynamic time division duplexed (tdd) transmission is used, and hence, the same frequency channel is time-shared for downlink and uplink transmissions under the dynamic control of the base station. we divide traffic into two classes: class i (real-time) and ii (non-real-time). whenever there is no eligible class-i traffic, class-ii traffic is transmitted, while uplink transmissions are controlled with a reservation scheme. class-i traffic is handled with the framing strategy combined with the admission test for adding new class-i connections. finally, we present the performance (average delay and throughput) evaluation of the reservation scheme for class-ii traffic using both analytical calculations and simulations.
associative search in peer to peer networks: harnessing latent semantics. the success of a p2p file-sharing network highly depends on the scalability and versatility of its search mechanism. two particularly desirable search features are scope (ability to find infrequent items) and support for partial-match queries (queries that contain typos or include a subset of keywords). while centralized-index architectures (such as napster) can support both these features, existing decentralized architectures seem to support at most one: prevailing unstructured p2p protocols (such as gnutella and fasttrack) deploy a ''blind'' search mechanism where the set of peers probed is unrelated to the query; thus they support partial-match queries but have limited scope. on the other extreme, the recently-proposed distributed hash tables (dhts) such as can and chord, couple index location with the item's hash value, and thus have good scope but can not effectively support partial-match queries. another hurdle to dhts deployment is their tight control of the overlay structure and the information (part of the index) each peer maintains, which makes them more sensitive to failures and frequent joins and disconnects. we develop a new class of decentralized p2p architectures. our design is based on unstructured architectures such as gnutella and fasttrack, and retains many of their appealing properties including support for partial match queries, and relative resilience to peer failures. yet, we obtain orders of magnitude improvement in the efficiency of locating rare items. our approach exploits associations inherent in human selections to steer the search process to peers that are more likely to have an answer to the query. we demonstrate the potential of associative search using models, analysis, and simulations.
mobile multi-layered ipsec. to achieve high throughput in wireless networks, smart forwarding and processing of packets in access routers is critical for overcoming the effects of the wireless links. however, these services cannot be provided if data sessions are protected using end-to-end encryption as with ipsec, because the information needed by these algorithms resides inside the portion of the packet that is encrypted, and can therefore not be used by the access routers. a previously proposed protocol, called multi-layered ipsec (ml-ipsec) modifies ipsec in a way so that certain portions of the datagram may be exposed to intermediate network elements, enabling these elements to provide performance enhancements. in this paper we extend ml-ipsec to deal with mobility and make it suitable for wireless networks. we define and implement an efficient key distribution protocol to enable fast ml-ipsec session initialization, and two mobility protocols that are compatible with mobile ip and maintain ml-ipsec sessions. our measurements show that, depending on the mobility protocol chosen, integrated mobile ip/ml-ipsec handoffs result in a pause of 53-100 milliseconds, of which only 28-75 milliseconds may be attributed to ml-ipsec. further, we provide detailed discussion and performance measurements of our mml-ipsec implementation. we find the resulting protocol, when coupled with snoop, greatly increases throughput over scenarios using standard tcp over ipsec (165% on average). by profiling the mml-ipsec implementation, we determine the bottleneck to be sending packets over the wireless link. in addition, we propose and implement an extension to mml-ipsec, called dynamic mml-ipsec, in which a flow may switch between plaintext, ipsec and mml-ipsec. using dynamic mml-ipsec, we can balance the tradeoff between performance and security.
configuring sessions in programmable networks. the provision of advanced computational services within networks is rapidly becoming both feasible and economical. we present a general approach to the problem of configuring application sessions that require intermediate processing by showing how the session configuration problem can be transformed to a conventional shortest path problem for unicast sessions or to a conventional steiner tree problem for multicast sessions. we study both a capacity-constrained version of the problem and an unconstrained version and show, through a series of examples, that the method can be applied to a wide variety of different situations. particularly, we show how to extend dijkstra's shortest path algorithm for use on the constrained version, and show that this approach can make significantly better use of network resources.
refreshment policies for web content caches. web content caches are often placed between end users and origin servers as a mean to reduce server load, network usage, and ultimately, user-perceived latency. cached objects typically have associated expiration times, after which they are considered stale and must be validated with a remote server (origin or another cache) before they can be sent to a client. a considerable fraction of cache "hits" involve stale copies that turned out to be current. these validations of current objects have small message size, but nonetheless, often induce latency comparable to full-fledged cache misses. thus, the functionality of caches as a latency-reducing mechanism highly depends not only on content availability but also on its freshness. we propose policies for caches to proactively validate selected objects as they become stale, and thus allow for more client requests to be processed locally. our policies operate within the existing protocols and exploit natural properties of request patterns such as frequency and recency. we evaluated and compared different policies using trace-based simulations.
efficient computation of end-to-end performance measures for multi-link atm networks with multi-media traffic. in this paper, we provide: (a) an efficient method for simplifying mmpp source models, which can be used to solve multi-media queueing problems with complicated aggregate input traffic. the effectiveness of the method is verified through numerical examples. (b) an approximation algorithm for analyzing multi-link queueing networks with mmpp traffic sources and arbitrary configurations. in this algorithm, a queueing network is analyzed by decomposing it into individual queues, each with an arrival rate appropriately reduced by the packet dropping occurred in other queues. each queue is then solved individually by using the simplified source models of (a) while the interdependencies with the other queues are accounted for through this reduced-load approximation. any desirable end-to-end performance measure characterizing the quality of service (qos) of the multi-media traffic can be calculated in this manner. the results obtained by the algorithm have been compared with simulation results, and the observed relative error is satisfactory.
on the computational complexity and effectiveness of n-hub shortest-path routing. in this paper, we study the computational complexity and effectiveness of a concept we term "n-hub shortest-path routing" in ip networks. n-hub shortest-path routing allows the ingress node of a routing domain to determine up to n intermediate nodes ("hubs") through which a packet will pass before reaching its final destination. this facilitates better utilization of the network resources, while allowing the network routers to continue to employ the simple and well-known shortest-path routing paradigm. although this concept has been proposed in the past, this paper is the first to investigate it in depth. we apply n-hub shortest-path routing to the problem of minimizing the maximum load in the network. we show that the resulting routing problem is np-complete and hard to approximate. however, we propose efficient algorithms for solving it both in the online and the offline contexts. our results show that n-hub shortest-path routing can increase network utilization significantly even for n = 1. hence, this routing paradigm should be considered as a powerful mechanism for future datagram routing in the internet.
slot allocation strategies for tdma protocols in multihop packet radio networks. the authors derive an upper bound of the minimum time division multiple access (tdma) frame length of any collision-free node assignment protocol in a packet radio network in which a node has multiple reception capacity. they also derive the optimum tdma frame length for any fully connected network with large reception capacity. when the total number of nodes in the network is unknown, a heuristics to generate a tdma protocol with frame length within some upper bound is presented for any network with large reception capacity
ip addressing and routing in a local wireless network. ip is the basic protocol in the internet. the authors explore a variety of possibilities to adapt the wireless environment to that of ip. they describe the requirements and show how these can be accommodated by using the existing ip. at the heart of the problem is the lack of a capability in the current ip routing services to track topological changes. several alternatives are described, each making use of a different combination of the addressing and routing features offered by ip. the alternatives are compared. the tradeoffs among these alternatives are explored
handover in a micro-cell packet switched mobile network. this paper proposes a distributed handover protocol for a micro-cell packet switched mobile network. in such a network, users move from one cell to another very often, and each change of location may result in misrouted and lost packets. the purpose of the new protocol is to minimize these consequences of location changes: as long as a mobile moves from one cell to another but stays in the same region, the protocol avoids loss of packets and preserves order of transmission. thus it increases the performance of the transport layer protocol by minimizing the need to retransmit packets.
an inversion algorithm for loss networks with state-dependent rates. we extend our recently developed algorithm for computing (exact) steady-state blocking probabilities for each class in product-form loss networks to cover general state-dependent arrival and service rates. this generalization allows us to consider, for the first time, a wide variety of buffered and unbuffered resource-sharing models with non-poisson traffic as may arise with overflows in the context of alternative routing. as before, we consider non-complete-sharing policies involving upper-limit and guaranteed-minimum bounds for the different classes, but here we consider both bounds simultaneously. major features of the algorithm are: dimension reduction by conditional decomposition based on special structure, an effective scaling algorithm to control errors in the inversion, the efficient treatments of multiple classes with identical parameters and the truncation of large sums.
performance of multistage atm switch architectures under nonuniform bursty traffic. a technique for the efficient analysis of multistage atm switch architectures is presented. it is flexible in that it permits arbitrary switching element sizes, a full range of hardware speedup and backpressure between stages. the arriving traffic is assumed to be bursty and the authors do not assume homogeneity of all traffic sources. the flow of cells through the network is approximated as a fluid process, yielding computational complexity that depends only on the representation of the arrival and departure processes of a queue, independent of the number of buffers. simulation results verify the accuracy of this approach. finally, the analysis is used to examine the effect of nonhomogeneous traffic, as well as to present a comparison of the various modes of operation and implementation parameters of the multistage switch, providing insights on design trade-offs.
a decomposition method for the exact analysis of circuit-switched networks. a general-purpose decomposition method is formulated for the exact analysis of blocking probabilities in multirate circuit-switched networks. the procedure is based on a decomposition and aggregation technique that exploits the sparsity that can be found in the routing matrix of a network. use is also made of a recursive algorithm developed by the authors (see ann. oper. res. vol.35, no.1-4, p.31-41, 1992). no special assumptions are made with regard to the structure of the network. by reducing the analysis to that of a set of interrelated subsystems and a reduced system, the overall dimensionality of the problem is diminished, and the computational costs are reduced significantly. this enables the efficient exact analysis of larger network models. an example is provided to illustrate the computational savings that can be realized
optimal cost/performance design of atm switches. the authors propose a methodology for performing an evaluation and optimization of the cost of an asynchronous transfer mode (atm) switching architecture under performance constraints given in terms of virtual connection blocking probability. an analysis of blocking networks is developed and combined with known results concerning nonblocking networks that provide a theoretical model which relates traffic characteristics, network topology, and blocking probability in a multirate/multiservice broadband environment. an analysis of the characteristics determining the cost of a generic atm switch implementation follows. the model is oriented to optimize both the topological parameters and the speed advantage, with respect to the main cost factors of vlsi-based switching networks
what's new: finding significant differences in network data streams. monitoring and analyzing network traffic usage patterns is vital for managing ip networks. an important problem is to provide network managers with information about changes in traffic, informing them about "what's new." specifically, we focus on the challenge of finding significantly large differences in traffic: over time, between interfaces and between routers. we introduce the idea of a deltoid: an item that has a large difference, whether the difference is absolute, relative or variational.we present novel algorithms for finding the most significant deltoids in high-speed traffic data, and prove that they use small space, very small time per update, and are guaranteed to find significant deltoids with pre-specified accuracy. in experimental evaluation with real network traffic, our algorithms perform well and recover almost all deltoids. this is the first work to provide solutions capable of working over the data with one pass, at network traffic speeds.
a reservation-based multicast (rbm) routing protocol for mobile networks: overview of initial route construction. we propose a combined multicast routing and resource reservation protocol, termed reservation-based multicast (rbm), that performs routing in a fashion similar to protocol independent multicast (pim), but which is intended for mobile operation and routes hierarchically-encoded data streams based on user-specified fidelity requirements, real-time delivery thresholds and prevailing network bandwidth constraints. the protocol retains the fully distributed operation, scalability and receiver-initiated orientation of pim; but, unlike pim, the protocol is tightly coupled to an underlying, distributed, unicast routing protocol thereby facilitating operation in a dynamic topology. this paper focuses on the initial route construction phase, assumed to occur during a static "snapshot" of the dynamic topology, and therefore outlines an approach to reservation-based multicast routing for fixed networks as well, e.g. the internet.
modeling superposition of on-off correlated traffic sources in multimedia applications. in this paper a multimedia source is modeled as an arrival process defined as the superposition of heterogeneous correlated arrival processes, each of which models one monomedia source. to this purpose each monomedia source is modeled as an on-off process where the transition rates are functions of the states of the other monomedia sources. auto- and cross-correlation functions are derived for each monomedia source. the analytical model is used to develop results for single media performance in a multimedia multiplexer structure.
the network effects of prefetching. abstract prefetching has been shown to be an effective technique for reducing user perceived latency in distributed systems. in this paper we show that even when prefetching adds no extra traffic to the network, it can have serious negative performance effects. straightforward approaches to prefetching increase the burstiness of individual sources, leading to increased average queue sizes in network switches. however, we also show that applications can avoid the undesirable queueing effects of prefetching. in fact, we show that applications employing prefetching can significantly improve network performance, to a level much better than that obtained without any prefetching at all. this is because prefetching offers increased opportunities for traffic shaping that are not available in the absence of prefetching. using a simple transport rate control mechanism, a prefetching application can modify its behavior from a distinctly on/off entity to one whose data transfer rate changes less abruptly, while still delivering all data in advance of the user''s actual requests.
a queueing system with two arrival streams and reserved servers with application to cellular telephone. the authors consider a service system in which n servers render service to two classes of prioritized traffic, which arrive to the system according to independent poisson processes. newly arriving call requests are granted server access on a first-come-first-served (fcfs) basis as long as there are fewer than g servers occupied. if fewer than g servers are free at the arrival time of a lower priority customer, the higher priority call requests are granted immediate service unless all servers are busy, in which case the call is dropped. this model has been used to study the handoff problem in a cellular telephone system, but the analytic approach taken was very complicated. the authors present a simple, novel, alternative approach to solving for the equilibrium probabilities for the number of lower priority calls in the queue and other quantities of interest. they describe two additional alternative approaches based on neuts' matrix analytic approach for checking results, and point out that while the results of all these approaches agree with each other, they differ from previously published results. because these three approaches are essentially independent, it is conjectured that there are problems with the earlier numerical results. further work has revealed that this is the case
design of real-time admission control algorithms with priority support. a multimedia atm network is shared by media channels with different performance requirements and traffic characteristics. to make efficient use of network resources, the quality of service provided to the users should be as close as possible to their requirements. a scheme with two levels of cell loss priority within each channel is proposed. priorities are assigned and enforced by the network locally at each switch along the path of a connection. the assignment, which can be different for the same connection at two different switches, is also dynamic; it is updated every time a connection is set up or one is terminated. algorithms used by the network to decide the fraction of cells of each stream assigned to each cell loss priority level, along with a simple mechanism to enforce the desired priority assignment and a real-time admission control algorithm, with decision time of very few milliseconds even for thousands of heterogeneous sources are presented.
multicast feedback suppression using representatives. for a reliable, feedback dependent multicast transport protocol to scale, it must avoid the feedback implosion problem, particularly if the protocol targets arbitrarily large multicast groups communicating over lossy networks. most existing suppression based feedback control mechanisms address the implosion problem using timers based on round-trip time (rtt) estimates between each receiver and the source. the algorithm presented has three major benefits: it does not need to compute the rtt from all receivers to the source, does not require knowledge of group membership, and provides prompt feedback. a small set of representative receivers and probabilistic suppression are used to limit feedback. we believe that this approach will perform well in real networks. simulations show that for various multicast group sizes, a few representatives can keep the amount of feedback low while not degrading feedback timeliness.
performance analysis of deflection routing multichannel-metropolitan area networks. the authors evaluate the performance of two different network architectures, implementing multichannel metropolitan area networks (m-mans). deflection routing, no internal storage, and a high connectivity degree are the main characteristics of regular networks built by interconnecting small-size multichannel nodes. analytical models have been developed for network architectures with a connectivity degree equal to four: the bidirectional manhattan street network (bmsn) and the shuffle net (sn). the authors evaluate the performance under uniform traffic distribution and also under the realistic assumption that the user's attachments to network nodes are equipped with input and output buffers. the performances under investigation are throughput, average delay, and packet loss. the availability of an analytical model makes it possible to investigate the performance of networks with a large number of nodes. the strong and weak points of the two m-man architectures are pointed out in the discussion of the results
design of the apic: a high performance atm host-network interface chip. we present the design of a high performance atm host-network interface for multimedia workstations and servers. at washington university, as part of an arpa-sponsored gigabit local atm testbed, we are building a prototype of this interface that can support a sustained aggregate bidirectional data rate of 2.4 gbps. the centerpiece of our interface design is a custom chip called the apic (atm port interconnect controller). multiple such chips can be interconnected to yield a desk-area network (dan) which would serve as a high speed i/o interconnect for the host computer. this paper details the internal design of the apic chip, and outlines some of its key features. noteworthy among these are: connection caching, transmit pacing, cell batching, remote control, and support for aal-0, aal-5, multipoint, and loopback connections. we have chosen to defer to a later paper the details pertaining to several other features which provide support for zero-copy, improved interrupt handling, direct control of the chip from user-space, and efficient buffering and demultiplexing.
the apic approach to high performance network interface design: protected dma and other techniques. we are building a high performance 1.2 gb/s atm network interface chip called the apic (atm port interconnect controller). in addition to borrowing useful ideas from a number of research and commercial prototypes, the apic design embraces several innovative features, and integrates all of these pieces into a coherent whole. some of the novel ideas incorporated in the apic design include: protected dma and protected i/o, which allow applications to queue data for transmission or reception directly from user-space, effectively bypassing the kernel. this argues for moving the entire protocol stack including the interface device driver into user-space, thereby yielding better latency and throughput performance than kernel-resident implementations. pool dma when used with packet splitting, is a technique that can be used to build true zero-copy kernel-resident protocol stack implementations, using a page-remapping technique. finally, orchestrated interrupts and interrupt demultiplexing are mechanisms used to reduce the frequency of interrupts issued by the apic. although many of these ideas have been developed in the context of an atm network interface, we believe they are also applicable in other contexts. in particular, protected dma and i/o are promising techniques for improving the performance of several different types of i/o devices.
on multicast trees: structure and size estimation. this work presents a thorough investigation of the structure of multicast trees cut from the internet and power-law topologies. based on both generated topologies and real internet data, we characterize the structure of such trees and show that they obey the rank-degree power law; that most high degree tree nodes are concentrated in a low diameter neighborhood; and that the sub-tree size also obeys a power law.our most surprising empirical finding suggests that there is a linear ratio between the number of high degree network nodes, namely nodes whose tree degree is higher than some constant, and the number of leaf nodes in the multicast tree (clients). we also derive this ratio analytically. based on this finding, we develop the fast algorithm, that estimates the number of clients, and show that it converges faster than one round trip delay from the root to a randomly selected client.
modified tree structure for location management in mobile environments. suggests a new data structure for location management in mobile networks. the data structure is based on the tree location database structure. the authors suggest replacing the root and some of the higher levels of the tree with another structure that balances the average load of search requests. for this modification they use a set-ary butterfly network, which is a generalization of the well-known k-ary butterfly. they also suggest modifying the lowest level of the tree in order to reflect neighboring geographical regions more accurately and to support simple location data management. the modification of the lowest level also supports simple handoffs. the update of the proposed location database ensures correct location data following any number of transient faults that corrupt the location database information and thus is self-stabilizing.
an efficient priority-based dynamic channel allocation strategy for mobile cellular networks. priority-based dynamic carrier allocation strategies can be classified into three categories: static-priority, dynamic-priority, and hybrid-priority strategies. strategies based on static priorities do not consider the local carrier reuse conditions, while dynamic-priority strategies do take these conditions into consideration. intuitively, one would expect dynamic-priority strategies to perform better than static- and hybrid-priority strategies, but in the literature it is the other way around --- existing dynamic-priority strategies are outperformed by some static- and hybrid-priority strategies.in this paper, we propose a dynamic-priority strategy that significantly improves over all existing strategies. under various traffic conditions, our simulation results indicated that the proposed strategy could reduce call blocking/failure rate by a margin ranging from 15% to 95%.
multiobjective flow control in telecommunication networks. pareto optimality is studied in the context of multiclass telecommunications networks with constraints on the maximum allowable user delays. the performance objective of each individual class is the maximization of throughput under a delay constraint. users share the network on a processor sharing basis. the multiobjective problem that arises is solved via a transformation that leads to a multicriterion linear program. the solution method is outlined by a thorough study of a simple example. pareto optimal solutions are compared on the basis of fairness given to different configurations and traffic characteristics
impact of interferences on connectivity in ad hoc networks. we study the impact of interferences on the connectivity of large-scale ad hoc networks, using percolation theory. we assume that a bi-directional connection can be set up between two nodes if the signal to noise ratio at the receiver is larger than some threshold. the noise is the sum of the contribution of interferences from all other nodes, weighted by a coefficient γ and of a background noise.we find that there is a critical value of γ above which the network is made of disconnected clusters of nodes. we also prove that if γ is nonzero but small enough, there exist node spatial densities for which the network contains a large (theoretically infinite) cluster of nodes, enabling distant nodes to communicate in multiple hops. since small values of γ cannot be achieved without efficient cdma codes, we investigate the use of a very simple tdma scheme, where nodes can emit only every nth time slot. we show that it achieves connectivity similar to the previous system with a parameter γ/n.
error control aspects of high speed networks. error control problems arising in the broadband isdn environment are analyzed. the first problem relates to end-to-end integrity. the second problem is related to synchronization. the third problem is the performance of the cell-based cyclic redundancy check (crc) in the presence of a self-synchronous scrambler to avoid attacks by malicious users. however, the scrambler creates error multiplication whereby a single error on the physical link is translated into two errors in the cell exactly 43 bits apart. in this context, it is proved that the cell-based crc is capable of correcting correlated double errors produced by the self-asynchronous scrambler. the last problem studied is parallel implementation of crc coders and decoders
trajectory sampling with unreliable reporting. we define and evaluate methods to perform robust network monitoring using trajectory sampling in the presence of report loss. the first challenge is to reconstruct an unambiguous set of packet trajectories from the reports on sampled packets received at a collector. in this paper we extend the reporting paradigm of trajectory sampling to enable the elimination of ambiguous groups of reports, but without introducing bias into any characterization of traffic based on the surviving reports. even after the elimination, a proportion of trajectories are incomplete due to report loss. a second challenge is to adapt measurement based applications (including network engineering, path tracing, and passive performance measurement) to incomplete trajectories. to achieve this, we propose a method to join multiple incomplete trajectories for inference, and analyze its performance. we also show how applications can distinguish between packet and report loss at the statistical level.
adaptive leases: a strong consistency mechanism for the world wide web. in this paper, we argue that weak cache consistency mechanisms supported by existing web proxy caches must be augmented by strong consistency mechanisms to support the growing diversity in application requirements. existing strong consistency mechanisms are not appealing for web environments due to their large state space or control message overhead. we focus on the lease approach that balances these trade-offs and present analytical models and policies for determining the optimal lease duration. we present extensions to the http protocol to incorporate leases and, then, implement our techniques in the squid proxy cache and the apache web server. our experimental evaluation of the leases approach shows that 1) our techniques impose modest overheads even for long leases (a lease duration of 1 hour requires state to be maintained for 1,030 leases and imposes an per-object overhead of a control message every 33 minutes), 2) leases yields a 138-425 percent improvement over existing strong consistency mechanisms, and 3) the implementation overhead of leases is comparable to existing weak consistency mechanisms.
an analysis of near optimal call admission and routing model for multi-service loss networks. a state-dependent call admission and routing policy for a multiservice circuit-switched network is analyzed. the policy is based on decomposition of the markov decision problem into a set of separable link problems. to provide an exact link analysis model a value iteration algorithm was offered. this allows examination of the accuracy of several approximations used to reduce the complexity of the problem. the numeral study showed that the convergence of the analyzed strategy is achieved in at most two iterations. the study also showed the good traffic efficiency of the approach and confirmed the predicted ability to control the distribution of call classes grade of service. the approach, together with its sensitivity analysis with respect to the arrival rates, provides a very general framework for studying, constructing, and optimizing other call admission and routing strategies. the results of sensitivity analysis are used to compare the proposed decomposition approach with the decomposition approach developed by f.p. kelly (1988) for optimization of a load sharing policy. also, the relationship to other routing strategies based on markov decision theory is investigated
estimation of aggregate effective bandwidth for traffic admission in atm networks. a framework for adaptive bandwidth management in atm based networks is presented. the central concept of this approach is an adaptive estimation of the aggregate effective bandwidth required by connections carried on each link of the network. to achieve reliable results the estimation process takes into account both the traffic source declarations and the connection superposition process measurements on the network links. this is done in an optimization framework provided by estimation theory. in the paper the authors concentrate on evaluation of a bandwidth reserved for possible estimation error. for this purpose they use the error covariance matrix from a linear two state kalman filter applied for the system state estimation. the bandwidth reserved for the estimation error provides that the source parameter declarations can be more relaxed and that the source policing can be less stringent.
address management and connection control for multicast communication applications. an architecture and associated protocols are presented for managing multicast addresses and performing connection control for multicast communication applications. a scheme to partition the multicast address space on the basis of the network number is proposed (an underlying ip-based internetworking environment is assumed), and its performance and scaling characteristics are discussed. a protocol is then developed to provide for dynamic allocation and release of multicast addresses, as well as maintaining state information for a connection. the protocol is independent of the address partitioning scheme; it is also shown to be robust and efficient. finally, we describe two different mechanisms that enable the use of a common port number by all session participants.
topological design of local area networks using genetic algorithms. continually growing number of users have to exchange increasing amounts of information. local area networks (lans) are commonly used as the communication infrastructure that meets the demands of the users in the local environment. these networks typically consist of several lan segments connected together via bridges. the authors describe an algorithm for designing lans with the objective of minimizing the average network delay. the topology design includes issues such as determination of the number of segments in the network, allocating the users to the different segments and determining the interconnections and routing among the segments. the determination of the optimal lan topology is a complicated combinatorial optimisation problem. therefore, a heuristic algorithm which is based on genetic ideas is used. numerical examples are provided and the quality of the designs obtained by using the algorithm is compared with lower bounds on the average network delay that are developed.
performance evaluation of atm shortcut connections in overlaid ip/atm networks. -------- in this paper we present methods to evaluate the benefit of using direct atm connections (shortcuts) between ip nodes in ip over atm networks, and we evaluate the benefit of atm shortcuts for several networks. we model an ip/atm network with and without atm shortcuts as two loss networks. we propose a metric, the network load ratio, for network performance comparison, that gives the ratio of the number of flows accepted by two networks at the same network blocking probability. we derive an estimator of this metric, the asymptotic load ratio, that has low computational complexity. we use this estimator as a basis for a methodology for network performance comparison, and use it to evaluate the benefit of atm shortcuts in several concrete scenarios.
mate: mpls adaptive traffic engineering. destination-based forwarding in traditional ip routers has not been able to take full advantage of multiple paths that frequently exist in internet service provider networks. as a result, the networks may not operate efficiently, especially when the traffic patterns are dynamic. this paper describes a multipath adaptive traffic engineering scheme, called mate, which is targeted for switched networks such as multiprotocol label switching networks. the main goal of mate is to avoid network congestion by adaptively balancing the load among multiple paths based on measurement and analysis of path congestion. mate adopts a minimalist approach in that intermediate nodes are not required to perform traffic engineering or measurements besides forwarding packets. moreover, mate does not impose any particular scheduling, buffer management, or a priori traffic characterization on the nodes. this paper presents an analytical model, derives a class of mate algorithms, and proves their convergence. several practical design techniques to implement mate are described. simulation results are provided to illustrate the efficacy of mate under various network scenarios.
fluid models for the analysis and design of statistical multiplexing with loss priorities on multiple classes of bursty traffic. the authors give the complete solution for a stochastic fluid model of statistical multiplexing with loss priorities in asynchronous transfer mode (atm)-based broadband isdn. in this model each markov modulated fluid source generates priority and marked cell streams which are bursty, mutually correlated, and periodic during bursts. the output of many such sources is buffered and multiplexed for transmission. the loss priority is implemented by selectively discarding marked cells when the buffer content exceeds a threshold level. the equilibrium state distribution exhibits jumps, a feature not existent in prior fluid models. the computational complexity for two-state sources is dominated by a single system of linear equations of dimension equal to twice the number of sources, in particular, the complexity is independent of buffer size. the complete delay distribution for each traffic class is obtained. numerical results are given. the analysis is generalized to several priority classes of traffic
analysis, approximations and admission control of a multi-service multiplexing system with priorities. we consider an atm system with an architecture which is designed to accommodate users with very different quality of service requirements. sources which belong to a high priority class share a fcfs buffer, which has priority access to the trunk. a low priority class of sources have a separate fcfs buffer, which receives the residual bandwidth, if any. by administering admission control the service guarantees for both classes may be satisfied. the sources are bursty and stochastic fluid models are used to handle burst-scale congestion effects. we develop simple, fast and robust analytic approximations for the queue distributions in the two buffers. we calculate the admissible set by using our analytic approximations and find that it is reasonably accurate and a conservative approximation to the correct set. the key element in our analysis is a characterization of the output of the high priority buffer as another markov-modulated fluid source. a refinement to the now well known effective bandwidth approximation is used to calculate buffer content distributions.
a distributed global queue transmission strategy for a wdm optical fiber network. a new distributed global queueing strategy and medium access protocol that users employ to schedule their transmissions to avoid receiver collisions is introduced for an optical fiber network. the network uses wavelength division multiplexing (wdm) for the data channels. the medium access control utilizes tdma on the control channel to allow users to implement a global reservation scheme to send data packets. the data channels operate under a distributed demand assignment scheme that allows receiver collision-free operation and efficient scheduling. an analytical solution is obtained via equilibrium point analysis (epa). it was shown that the maximum throughput obtained is approximately 42% which exceeds the maximum throughput of aloha based medium access protocols. the delay is shown to be relatively constant for a wide range of operation.
traffic shaping at a network node: theory, optimum design, admission control. this paper develops a framework of traffic shaping which has the goal of increasing the nodal connection-carrying capacity. the shaping filters are designed to interwork with statistical multiplexers which use fifo buffers. differences in delay tolerances between traffic classes are exploited to shape and smooth the less delay sensitive traffic. the source model used in the analysis is asynchronous, worst-case subject to dual leaky bucket regulation, where the asynchrony is due to the assumption of independent sources. this, together with the allowance of small loss probabilities, makes statistical multiplexing feasible.we require the shapers to be lossless so that losses, if any, occur only at the multiplexer. we obtain the optimal design of the shaper such that a given delay tolerance for the connection is satisfied. for purposes of admission control we obtain the admissible region of combinations of sources of various types such that the qos requirements in loss and delay are satisfied. by examining the regions obtained with and without shaping we quantify the capacity gain from shaping. our numerical results show that the gain can be substantial.
xunet 2: a nationwide testbed in high-speed networking. xunet 2 is an experimental wide-area network that serves as a testbed for research on data communications techniques. the authors provide an overview of the architecture of the xunet 2 testbed. xunet 2 has three principal components: routers, switches and network management systems. long-haul transmission between them will initially use ds3 facilities. performance objectives for the backbone have been set to cover a wide range of transmission speeds. each router attaches a local area network to the backbone network. the backbone network provides virtual circuit connectivity between the routers. circuit setup and teardown is done by a control computer associated with each switch, and the network as a whole will be managed by a network management station in the network operations center
optimal energy allocation and admission control for communications satellites. we address the issue of optimal energy allocation and admission control for communications satellites in earth orbit. such satellites receive requests for transmission as they orbit the earth, but may not be able to serve them all, due to energy limitations. the objective is to choose which requests to serve so that the expected total reward is maximized. the special case of a single energy-constrained satellite is considered. rewards and demands from users for transmission (energy) are random and known only at request time. using a dynamic programming approach, an optimal policy is derived and is characterized in terms of thresholds. furthermore, in the special case where demand for energy is unlimited, an optimal policy is obtained in closed form. although motivated by satellite communications, our approach is general and can be used to solve a variety of resource allocation problems in wireless communications.
topological design of interconnected lan-man networks. the authors describe a methodology for designing interconnected local area network/metropolitan area network (lan-man) networks with the objective of minimizing the average network delay. they consider ieee 802.3-5 lans interconnected by transparent bridges. these bridges are required to form a spanning tree topology. the optimization algorithm for finding a minimum delay spanning tree topology is based on simulated annealing. in order to measure the quality of the solutions, a lower bound for the average network delay is found. the comparison of results with this lower bound and several other goodness measures shows that the solutions are not very far from the global minimum. the authors extend the present algorithm for finding minimum delay lan-man topologies consisting of fiber distributed data interface (fddi) mans or switched multi-megabit data service (smds) interconnecting several clusters of bridged lans
fair resource allocation in wireless networks using queue-length-based scheduling and congestion control. we consider the problem of allocating resources (time slots, frequency, power, etc.) at a base station to many competing flows, where each flow is intended for a different receiver. the channel conditions may be time-varying and different for different receivers. it is well-known that appropriately chosen queue-length based policies are throughput-optimal while other policies based on the estimation of channel statistics can be used to allocate resources fairly (such as proportional fairness) among competing users. in this paper, we show that a combination of queue-length-based scheduling at the base station and congestion control implemented either at the base station or at the end users can lead to fair resource allocation and queue-length stability.
an assessment of state and lookup overhead in routers. the current internet is based on a stateless (datagram) architecture. however, many recent proposals rely on the maintenance of state information within network routers, leading to the authors' interest in the implications of a stateful network layer. they collected internetwork traffic traces at the border routers of stub and transit networks, and used these data to evaluate, or predict, the effects of design alternatives for stateful architectures. they present an estimate of the number of active conversations at a router, and from this derive the storage requirements for the associated conversation state table. the analysis shows that, at the network periphery, fine-grain control over the traffic may be possible. however, deeper within the network, it may be more efficient to manage the conversations at a coarser level. the network traffic traces are used to perform trace driven simulations of an lru cache, for different conversation granularities. results show that locality exists for each of the conversation types investigated
delay jitter correlation analysis for traffic transmission on high speed networks. studies the time-dynamic behavior of delay jitter as captured by the autocorrelation function; the second-order statistics provide information relating to consecutive cell loss in real-time services. the authors derive an expression for delay jitter correlation of a stationary traffic stream in an mmpp/m/1/k system with fifo service discipline; use of a type of deterministic rate server yields the same correlation function but with reduced variance. the jitter second-order statistics are shown to depend strongly on those of the queue, and the queue second-order statistics depend strongly on those of the input traffic. the authors show that the shape of the jitter correlation is determined by the weighted difference in queue correlations, and they derive a method for obtaining the weights for an mmpp traffic stream. in the numerical study emphasis is placed on a periodic traffic stream (such as cbr video) multiplexed on a major communication node; the authors investigate the impact of input traffic correlations and queueing system parameters on the queue length and delay jitter second-order statistics. they also briefly consider the delay jitter correlation from a binary markov source (voice model).
an abr feedback control scheme with tracking. we propose an explicit-rate abr feedback control scheme, ut (uniform tracking). the distinct feature of ut is that it achieves max-min fairness by tracking an effective number of sources; specific constraint information is not required. as a result, its implementation is much simpler than that of other fair control schemes; indeed, its complexity is similar to that of *unfair* explicit-rate controls. in the thorough simulation study, ut demonstrates its ability to scale with speed, distance, number of users (both persistent and bursty), and number of switches while remaining robust, efficient, and fair under stressing conditions with mpeg background traffic and multiple propagation delay loops.
a time-wavelength assignment algorithm for a wdm star network. the first time-wavelength assignment algorithm for wavelength division multiplexing (wdm) star-based local and metropolitan area networks is presented. the algorithm incorporates the unique aspects of wdm communication such as a number of tunable transmitters and receivers at each concentrator, the tuning time, and a limited number of wavelengths. the transmission duration is composed of two elements: the packet transmission time, and the overhead incurred due to the tunability of the system's transmitters and receivers. for a given traffic matrix, the algorithm obtains a tdm/wdm schedule with minimal packet transmission duration, while minimizing the tuning time
an optimal establishment of virtual path connections for atm networks. a number of optimization models for the establishment of virtual path connections (vpcs) with reserved capacity have been proposed in the literature. all of them, however, failed to reflect the trade-off between increased capacity costs and reduced control costs explicitly in their formulations. the present authors develop a mathematical formulation for an optimal strategy for the reservation of capacity on vpcs, considering the trade-off between increased capacity costs and reduced control costs. in this formulation, they also consider the reservation of buffers on vpcs. algorithms and numerical results are presented.
fitting mixtures of exponentials to long-tail distributions to analyze network performance models. traffic measurements from communication networks have shown that many quantities characterizing network performance have long-tail probability distributions, i.e., with tails that decays more slowly than exponentially. long-tail distributions can have a dramatic effect upon performance, but it is often difficult to describe this effect in detail, because performance models with component long-tail distributions tend to be difficult to analyze. we address this problem by developing an algorithm for approximating a long-tail distribution by a finite mixture of exponentials. the fitting algorithm is recursive over time scales. at each stage, an exponential component is fit in the largest remaining time scale and then the fitted exponential component is subtracted from the distribution. even though a mixture of exponentials has an exponential tail, it can match a long-tail distribution in the regions of primary interest when there are enough exponential components.
efficient admission control for edf schedulers. in this paper we present algorithms for flow admission control at an edf link scheduler when the flows are characterized by peak rate, average rate and burst size. we show that the algorithms have very low computational complexity and are easily applicable in practice. the complexity can be further decreased by introducing the notion of flex classes. we evaluate the penalty in efficiency that the classes incur to the edf scheduler. we find that this efficiency degradation can be made arbitrarily small and is acceptable even for a small number of classes.
crankback prediction in hierarchical atm networks. when an atm node discovers that it cannot continue the setup of a virtual channel under the requested quality of service (qos), it initiates a backtracking procedure called &ldquo;crankback.&rdquo; we propose a novel scheme, referred to as crankback prediction, that decreases the crankback overhead. under the proposed scheme, nodes check during the connection admission control procedure whether the establishment of a virtual channel has a good chance to be admitted over the entire designated route. if this is not the case, crankback is initiated even before a particular qos parameter is violated. the main idea behind the proposed scheme is to allocate a &ldquo;quota&rdquo; to the peer groups (pgs) along the message path, and then to suballocate this quota to the child pgs of these pgs. this process continues recursively until reaching the 1-level pg, which contains only physical nodes. the main advantage of the proposed scheme is that it lowers the setup delay and the processing and communication load imposed by signaling messages that establish unused portions of virtual channels (vcs)
collision avoidance and resolution multiple access with transmission groups. the carma-ntg protocol is presented and analyzed. carma-ntg dynamically divides the channel into cycles of variable length; each cycle consists of a contention period and a group-transmission period. during the contention period, a station with one or more packets to send competes for the right to be added to the group of stations allowed to transmit data without collisions; this is done using a collision resolution splitting algorithm based on a request-to-send/clear-to-send (rts/cts) message exchange with non-persistent carrier sensing. carma-ntg ensures that one station is added to the group transmission period if one or more stations send requests to be added in the previous contention period. the group-transmission period is a variable-length train of packets, which are transmitted by stations that have been added to the group by successfully completing an rts/cts message exchange in previous contention periods. as long as a station maintains its position in the group, it is able to transmit data packets without collision. an upper bound is derived for the average costs of obtaining the first success in the splitting algorithm. this bound is then applied to the computation of the average channel utilization in a fully connected network with a large number of stations. these results indicate that collision resolution is a powerful mechanism in combination with floor acquisition and group allocation multiple access.
distributed routing with labeled distances. the author presents, verifies, and analyzes a new routing algorithm called the labeled distance-vector routing algorithm (ldr), that is loop-free at every instant, eliminates the counting-to-infinity problem of the distributed bellman-ford (dbf) algorithm, operates with arbitrary link and node delays, and provides shortest paths a finite time after the occurrence of an arbitrary sequence of topological changes. in contrast to previous successful approaches to loop-free routing, ldr maintains dbf's row-independence property and does not require internodal coordination spanning multiple loops. the new algorithm is shown to be loop-free and to converge in a finite time after an arbitrary sequence of topological changes. its performance is compared with the performance of other distributed routing algorithms
a loop-free path-finding algorithm: specification, verification and complexity. the loop-free path-finding algorithm (lpa) is presented. lpa specifies the second-to-last hop and distance to each destination to ensure termination; in addition, it uses an inter-neighbor synchronization mechanism to eliminate temporary loops. a detailed proof of lpa's correctness is presented and its complexity is evaluated. lpa's average performance is compared by simulation with the performance of algorithms representative of the state of the art in distributed routing, namely an ideal link-state (ils) algorithm and a loop free algorithm that is based on internodal coordination spanning multiple hops (dual). the simulation results show that lpa is a more scalable alternative than dual and ils in terms of the average number of steps, messages, and operations needed for each algorithm to converge after a topology change. lpa is shown to achieve loop freedom at every instant without much additional overhead over that incurred by prior algorithms based on second-to-last hop and distance information.
a comparison of bandwidth smoothing techniques for the transmission of prerecorded compressed video. the transfer of prerecorded, compressed video requires multimedia services to support large fluctuations in band width requirements on multiple time scales. bandwidth smoothing techniques can reduce the burstiness of a variable-bit-rate stream by prefetching data at a series of fixed rates, simplifying the allocation of resources in video servers and the communication network. given a fixed client-side prefetch buffer, several bandwidth smoothing algorithms have been introduced that are provably optimal under certain constraints. this paper presents a collection of metrics for comparing these smoothing algorithms and evaluating their cost-performance trade-offs. due to the scarcity of available trace data, we have constructed a video capture testbed and generated a collection of twenty full-length, motion-jpeg encoded video clips. using these video traces and a range of client buffer sizes, we investi gate the interplay between the performance metrics through simulation experiments. the results highlight the unique strengths and weaknesses of each algorithm.
an overload cycle analysis of generalized bandwidth balancing for dqdb. a novel state-space approach is used to characterize the overload cycle behavior of a generalized bandwidth balancing (bwb) scheme for the distributed queue dual bus (dqdb) multiple access procedure. the author exploits the fact that each node and the bus can be modeled by a finite state machine and will have cycles in the state diagram. the cycles of interest are referred to as overload cycles and result when one or more nodes are simultaneously trying to access the bus as quickly as possible. the author determines the overload cycle invariants imposed by bwb and generalizes bwb to be any integral relationship between used and skipped empty segments. it is shown that the ordinary access-based priorities cannot work, without some additional cycle invariants, in a system employing bandwidth balancing since it is impossible to preclude service to an upstream low priority mode and generalized bwb is suggested as an alternative method for obtaining rate-based priority grades of service
v-net: a framework for a versatile network architecture to support real-time communication performance guarantees. the paper proposes a new network architecture, called the versatile network architecture (v-net), which provides a framework for flexible support of communication requirements in real-time networks. applications communicate over the v-net by using simplex end-to-end network connections which support specific real-time and reliability characteristics tailored to meet the application's specified requirements. v-net differs from other proposed architectures in that it does not assume one specific packet scheduling algorithm or a specific traffic policing mechanism. instead, the v-net has been designed to support a variety of packet scheduling algorithms and traffic policing mechanisms. this flexibility is an important design consideration as a real-time network architecture must accommodate existing and future multimedia applications.
usage of vsat for tcp/ip based lan interconnection. an analysis of the possibilities of usage of vsat networks for the interconnection of tcp/ip based lans is performed. in the first part of the paper, a general feasibility overview of tcp/ip through satellite is presented, stressing on the inconveniences and technical problems of arrangement. in the second part, a comparative study between low rate (up to 19.2 kbps) vsat networks and other low capacity data networks (such as x.25) is carried out. the study is based upon measurements performed by telefonica i+d on the hughes isbn vsat system operated by telefonica de espana.
rate-function scheduling. rate-function scheduling (rfs) is a new deadline-based packet-scheduling service discipline that supports quality-of-service guarantees for applications with real-time communication requirements. rfs is distinguished from other service disciplines in that it achieves all of the following goals: analytically-derived performance bounds, performance isolation among sessions, flexible and efficient allocation of bandwidth, implementation simplicity, work-conserving operation, and bandwidth-fair operation (defined in the paper). through the specification of rate functions, sessions can control their bandwidth usage and their upper bounds on delay. for a class of rate functions, which we show is sufficient for providing sessions with delay bounds, rfs is as simple to implement and to calculate service bounds such as zhang's virtualclock service discipline. we also show that the non-preemptive earliest deadline first policy is a simple degeneration of rfs.
on-line routing for permanent virtural circuits. the paper considers the problem of routing a set of permanent virtual circuit requests over a backbone network. several factors make this routing problem complicated. routing decisions must be made on-line without any knowledge of future request sets. furthermore, frequent rerouting to correct inefficiencies that can result from the on-line routing decisions is not possible since rerouting creates a service disruption for the customer. finally, the forward and reverse bandwidth of a virtual circuit must be routed over the same single path. using an extensive set of simulations, the paper evaluates several different strategies for on-line permanent virtual circuit routing. the authors find that a strategy based on results in competitive analysis and ideas from combinatorial optimization consistently provides the best performance. the problem of admission control is closely related to the problem of routing. the paper also provides a theoretical lower bound that suggests that non-greedy admission control is a fundamental component of an efficient on-line permanent virtual circuit routing algorithm.
virtual-topology adaptation for wdm mesh networks under dynamic traffic. we present a new approach to the virtual-topology reconfiguration problem for a wavelength-division-multiplexing-based optical wide-area mesh network under dynamic traffic demand. by utilizing the measured internet backbone traffic characteristics, we propose an adaptation mechanism to follow the changes in traffic without a priori knowledge of the future traffic pattern. our work differs from most previous studies on this subject which redesign the virtual topology according to an expected (or known) traffic pattern, and then modify the connectivity to reach the target topology. the key idea of our approach is to adapt the underlying optical connectivity by measuring the actual traffic load on lightpaths continuously (periodically based on a measurement period) and reacting promptly to the load imbalances caused by fluctuations on the traffic, by either adding or deleting one or more lightpath at a time. when a load imbalance is encountered, it is corrected either by tearing down a lightpath that is lightly loaded or by setting up a new lightpath when congestion occurs. we introduce high and low watermark parameters on lightpath loads to detect any over- or underutilized lightpath, and to trigger an adaptation step. we formulate an optimization problem which determines whether or not to add or delete lightpaths at the end of a measurement period, one lightpath at a time, as well as which lightpath to add or delete. this optimization problem turns out to be a mixed-integer linear program. simulation experiments employing the adaptation algorithm on realistic network scenarios reveal interesting effects of the various system parameters (high and low watermarks, length of the measurement period, etc.). specifically, we find that this method adapts very well to the changes in the offered traffic.
lexicographically optimal balanced networks. we consider the problem of allocating bandwidth between two endpoints of a backbone network so that no parts of the network are unnecessarily loaded. we formulate the problem as lexicographic optimization and develop algorithms for its solution. the solution consists of: 1) identifying a cut in the network where the optimal load can be determined on all the links of the cut and 2) considering the same problem for each of the subnetworks to which the cut is dividing the original network.
exact and efficient analysis of schedulability in fixed-packet networks: a generic approach. a general model for trafic flows on packet-switched, virtual-circuit based, fixed-packet networks is intro- duced, and an exact schedulability test is obtained for systems of such flows. rules are derived that make the evaluation of this schedulability test feasible and eficient under certain circumstances. the practical relevance of this approach is demonstrated by applying it to a number of standard trafic models.
network algorithms and protocol for multimedia servers. in this paper, we present a network service specifically designed for multimedia servers. by coupling a histogram-based traffic characterization with an admission control algorithm, it enables the network to provide heterogeneous statistical qos guarantees to clients. to meet these guarantees, we propose an overload control algorithm and protocol that exploits the regularity and predictability in traffic to provide heterogeneous qos while completely eliminating packet losses in the network. specifically, it: (1) detects congestion in the network prior to its occurrence, (2) allocates bandwidth to competing sources based on their qos guarantees, and (3) transmits feedback packets to the sources indicating the rate allocations. by ensuring that the feedback is received by the sources sufficiently prior to overload occurrence, the protocol enables the sources to employ application specific procedures to adjust their transmission rates so as to conform to the rate allocations, thereby eliminating any packet losses in the network. the key contribution of our protocol lies in combining open-loop and feedback-based control to: (1) provide heterogeneous qos to clients in networking environments consisting of switches that may not have any scheduling support; and (2) migrate the functionality of discarding packets, in the event of congestion, to the sources which understand the semantics of the data. the protocol is efficient, makes very few assumptions about the underlying network, is realizable on current switching hardware (supporting fcfs scheduling), and is completely integrated with the architecture of a multimedia server.
a reliable, adaptive network protocol for video transport. in this paper, we present an adaptive network layer protocol that: (1) minimizes buffer requirement in the network while guaranteeing that packets of vbr encoded video flows will not be lost, and (2) minimizes end-to-end delay and jitter of frames. to achieve the former objective, we utilize receiver-oriented adaptive credit-based flow control algorithm, and derive necessary and sufficient number of buffers that should be reserved for ensuring its reliability. to minimize the end-to-end delay and jitter for vbr encoded video streams, we: (1) present bandwidth estimation techniques which exploit the structure of the video traffic, and (2) define a new fairness criteria for buffer allocation (which is motivated by the delay requirements of video applications) and then present a fair buffer allocation algorithm. to mask the effects of delay jitter on playback continuity, we present a simple technique for adapting the playback point at client sites. we experimentally evaluate this protocol for a wide range of parameters and many network configuration and demonstrate its adaptability. we also compare the performance of the protocol with numerous other schemes and demonstrate its suitability for video transport.
fault tolerant pon topologies. the authors propose a redundant, tree structured passive optical network (pon) configuration which can withstand all single and most double link failures. the redundant configuration results from the superposition of two physically separate, diverse-routed trees. this redundancy is transparent to the user. it does not require switching elements or special controls inside the network. it permits easy identification of the fault by the network control center. the fault tolerance properties of the proposed solution are evaluated. power budget, fiber installation cost, and metropolitan coverage issues are investigated
vbr video over atm: reducing network resource requirements through endsystem traffic shaping. transmission of variable-bitrate (vbr) video over atm is a challenge because it combines the requirement for on-time data delivery with a bursty traffic characteristic. we focus on the role of atm endsystems in the transmission of vbr video and examine how traffic shaping in the sender reduces the burstiness of the video stream and therefore the network resource requirements, both for video encoded in real-time and stored video. shapers based on multiple leaky buckets are popular because they are particularly simple to implement. we present basic results on their buffer requirements and provide new, tighter bounds for their output traffic, enabling efficient resource allocation as well as a significant reduction in the number of leaky buckets required. we extend the basic shaping mechanism to provide efficient shaping for stored video. finally we compare empirically the performance of multiple leaky bucket shaping with an optimal algorithm for mpeg-1 encoded video and find under realistic conditions near-optimal performance with very few leaky buckets.
protocols for an optical star interconnect for high speed mesh networks. optical networks can provide higher throughputs while high speed electronic networks possess the intelligence for network control and management. we present a two level high speed network architecture that combines the throughput advantage of optical networks and the intelligence of electronic processing. one level is a high speed mesh lan which uses wormhole routing, source routing and hop-by-hop flow control mechanisms with mesh routers (asynchronous pipelined crossbar switches) to provide a high speed electronic network. the second level is an optical star network interconnecting high speed mesh networks distributed across metropolitan area distances. we obtain analytical expressions for the average message (worm) delays for the gtdm (group time division multiplexing) multi-access protocol (which includes as special cases tdm and das) for single-hop packet switching in the optical network of such an architecture. we use a two state discrete time markov chain to model the arrival of messages to the optical network. results for both uniform traffic and non-uniform traffic are presented. finally, a modified dynamic allocation scheme is presented for single-hop packet switching which handles the message as a unit rather than sending a message as several fixed sized packets.
lan/man interconnection to atm: a simulation study. the authors compare three strategies, namely, reservation, on-the-fly, and hybrid, for the support of connectionless internet traffic on asynchronous transfer mode (atm). the comparison is based on a simulation experiment in which a mix of virtual paths (some carrying connectionless traffic, some carrying connection-oriented traffic) are multiplexed on a 150 mb/s trunk, called the bottleneck trunk. results based on a variety of measures (cell and burst loss rates, cell delay, and burst delay) show that the on-the-fly approach, which aggressively exploits unused bandwidth, is superior to the reservation scheme, which is handicapped by the renegotiation overhead and the conservative usage of bandwidth. the hybrid scheme exhibits a performance behavior between the other two. this is a bit disappointing, considering the fact that the hybrid scheme is expected to be consistently better than both schemes. still the hybrid scheme offers some interesting features (e.g. lower delays for the background traffic) which should be further explored by a more extensive examination of the working parameters
analysis of alternating-priority queueing models with (cross) correlated switchover times. this paper analyzes a single server queueing system in which service is alternated between two queues and the server requires a (finite) switchover time to switch from one queue to the other. the distinction from classical results is that the sequence of switchover times from each of the queues need not be i.i.d. nor independent from each other; each sequence is merely required to form a stationary ergodic sequence. with the help of stochastic recursive equations explicit expressions are derived for a number of performance measures, most notably for the average delay of a customer and the average queue lengths under different service disciplines. with these expressions a comparison is made between the service disciplines and the influence of correlation is studied. finally, through a number of examples it is shown that the correlation can significantly increase the mean delay and the average queue lengths indicating that the correlation between switchover times should not be ignored. this has important implications for communication systems in which a common communication channel is shared amongst various users and where the time between consecutive data transfers is correlated (for example in ad-hoc networks). in addition to this a number of notational mistakes in well-known existing literature are pointed out.
dynamic maintenance of the virtual path layout. discusses methods for adjusting the layout of virtual paths in an atm network, to the dynamics of changes in the usage of the network by its end-users. the authors first present a centralized algorithm for finding a better layout for the current traffic pattern, and for applying the change in the network, and discuss its drawbacks. they then present a distributed algorithm that emulates the centralized algorithm with a much lower overhead, and enhanced durability to faults. they prove that both algorithms produce identical layouts, thus showing the superiority of the latter algorithm. both algorithms base the changes in the network on a new rerouting protocol, which does not cause any losses in data, nor changes in the fifo order of cells.
seam: scalable and efficient atm multicast. this paper proposes a multipoint-to-multipoint multicast architecture for atm networks. the necessity for such an architecture stems from the scalability requirements, both in terms of state to be maintained in the network and in terms of the group population dynamics, of a wide range of networking applications. we argue that approaches of using multicast servers or meshes of point-to-multipoint virtual circuits (vcs) may be inadequate solutions to this problem. we propose a true multipoint-to-multipoint architecture called seam, which uses a single vc for a multicast group consisting of multiple senders and receivers. we achieve this without changes to atm's aal5. seam relies on an additional switching feature we call cut-through forwarding, which enables the mapping of several incoming vcs into outgoing vcs. we believe that seam is both an important and necessary step in the evolution of atm. it will enable applications relying on group multicast to benefit directly from atm's quality of service support and scalable bandwidth and the resulting performance advantages. also, it considerably simplifies the problem of supporting ip multicast over large atm networks.
queueing analysis of a distributed explicit rate allocation algorithm for abr services. approximate queueing analysis of a distributed explicit rate allocation algorithm for the flow control of available bit rate (abr) service, which captures the effect of bandwidth-delay, is described. attention is focused on bounding the worst case transient queueing behaviour in a strictly-abr environment with persistent start-up sources. at each switch, rm cells are enqueued using a buffer separate from the data cells, and are served with a higher priority than data cells. both single and multiple node network cases are treated for connections with differing delays. the approximate analysis shows relatively good agreement with simulation results for single node networks, but gives looser estimates for the multiple node case.
mobility increases the capacity of ad-hoc wireless networks. the capacity of ad hoc wireless networks is constrained by the mutual interference of concurrent transmissions between nodes. we study a model of an ad hoc network where n nodes communicate in random source-destination pairs. these nodes are assumed to be mobile. we examine the per-session throughput for applications with loose delay constraints, such that the topology changes over the time-scale of packet delivery. under this assumption, the per-user throughput can increase dramatically when nodes are mobile rather than fixed. this improvement can be achieved by exploiting a form of multiuser diversity via packet relaying.
a time-scale decomposition approach to measurement-based admission control. we propose a time-scale decomposition approach to measurement-based admission control (mbac). we identify a critical time scale th such that: 1) aggregate traffic fluctuation slower than th can be tracked by the admission controller and compensated for by flow admissions and departures; and 2) fluctuations faster than th have to be absorbed by reserving spare bandwidth on the link. the critical time scale is shown to scale as th/√n, where th is the average flow duration and n is the size of the link in terms of number of flows it can carry. an mbac design is presented which filters aggregate measurements into low- and high-frequency components separated at the cutoff frequency 1/th, using the low-frequency component to track slow time-scale traffic fluctuations and the high-frequency component to estimate the spare bandwidth needed. our analysis shows that the scheme achieves high utilization and is robust to traffic heterogeneity, multiple time-scale fluctuations and measurement errors. the scheme uses only measurements of aggregate bandwidth and does not need to keep track of per-flow information.
measurement of atm traffic on the cell, burst and activity level by traffic sampling. the authors address the problem of measuring asynchronous transfer mode (atm) traffic on the cell, burst and activity level. with the aid of a traffic sampling mechanism it is shown that efficient data can be collected. these data are then used to estimate the spectral density on each level. it is shown that a forward-backward least square spectral estimator with prefiltering gives an accurate estimation even at low frequencies and that the power spectral density at frequency zero and the load are the most dominant parameters for the queue length and hence also for loss
project acorn and distributed approaches to atm networks. centralized and distributed approaches to the design and implementation of a multi-gigabit per second asynchronous transfer mode (atm) switch are discussed. the implementation constraints associated with a centralized switch are demonstrated and an alternative distributed optical network architecture is described. the distributed approach exploits unique opportunities presented through the use of a passive optical medium. a network based on these principles (teranet), has been implemented that offers user access rates of 1 gbit/s. the distributed atm switch fabric resides in small, geographically dispersed access stations interconnected by a shared, all-optical medium carrying many wavelength-multiplexed channels. although the underlying multihop architecture for the atm network produces a lower per-port throughput than that afforded by a large centralized atm switch, significant implementation advantages exist. possible techniques to yield a higher per-port throughput approaching that of a large centralized switch are also discussed
qos-based routing in networks with inaccurate information: theory and algorithms. we investigate the problem of routing connections with qos requirements across one or more networks, when the information available for making routing decisions is inaccurate and expressed in some probabilistic manner. this uncertainty about the actual state of a node or network arises naturally in a number of different environments, that are reviewed in the paper. the main focus is to determine the impact of such inaccuracies on the path selection process, whose goal is then to identify the path that is most likely to satisfy the qos requirements.
vbr over vbr: the homogeneous, loss-free case. we consider the multiplexing of several variable bit rate (vbr) connections over one variable bit rate connection where the multiplexing uses a multiplexing buffer of size b. the vbr trunk is itself a connection and has a multidimensional connection descriptor, reflecting peak and sustainable rates. given a cost function for the vbr trunk and a connection admission control (cac) method for the input connections, we focus on the problem of finding the vbr trunk connection descriptor that minimizes the cost function and is able to accept a given set of vbr input connections. first, we show that, under reasonable assumptions on the cost function, the optimization problem can be reduced to a simpler one. then we consider the homogeneous, loss-free case, for which we give an explicit cac method. in that case, we find that, for all reasonable cost functions, the optimal vbr trunk is either of the cbr type, or is truly vbr, with a burst duration equal to the burst duration of the input connections. we motivate this study by showing that the optimal peak cell rate is fixed for a given b (thus for a cbr trunk), and a vbr choice can only be an improvement. lastly, we take as example of cost function the equivalent capacity of the vbr trunk. those results are expected to form the basis for a general method for a connection manager at a multiplexing node in an integrated services packet network.
an analysis of internet inter-domain topology and route stability. the internet routing fabric is partitioned into several domains. each domain represents a region of the fabric administered by a single commercial entity. over the past two years, the routing fabric has experienced significant growth. from more than a year's worth of inter-domain routing traces, we analyze the internet inter-domain topology, its route stability behavior, and the effect of growth on these characteristics. our analysis reveals several interesting results. despite growth, the degree distribution and the diameter of the inter-domain topology have remained relatively unchanged. furthermore, there exists a four-level hierarchy of internet domains classified by degree. however, connectivity between domains is significantly non-hierarchical. despite increased connectivity at higher levels in the topology, the distribution of paths to prefixes from the backbone remained relatively unchanged. there is evidence that both route availability and the mean reachability duration have degraded with internet growth.
peak rate enforcement in atm networks. the authors address peak rate enforcement in asynchronous transfer mode (atm) networks by pick-up policing mechanisms. since the network cannot rely on user's compliance when declaring his traffic parameters, the policing function has been introduced to monitor the traffic characteristics of any connection. policing mechanisms proposed in the literature are actually pick-up mechanisms since cells can pass transparently through unless a policing action was performed according to some counting process. the authors analyze the impact of the cell multiplexing jitter on policing mechanism dimensioning. recognizing that dimensioning is a critical point for such mechanisms. it is shown that network buffer overflow cannot be avoided in certain conditions. therefore, a new policing scheme, called cell spacing, is introduced, and two spacing algorithms are presented
on characterizing an atm source via the sustainable cell rate traffic descriptor. the sustainable cell rate (scr) was introduced by the atm forum as a means of characterizing the statistical activity of atm vbr connections. the scr traffic descriptor (scr-td), composed of the sustainable cell rate 1/t/sub scr/ and the intrinsic burst tolerance /spl tau//sub ibt/, is defined with respect to an algorithmic characterization, the generic cell rate algorithm (gcra). this method makes source parameter enforcement straightforward. unfortunately, the current specification of the scr-td is incomplete, leaving the source with an infinite number of (t/sub scr/, /spl tau//sub ibt/) couples to choose from, this ambiguity could bear a negative impact on network efficiency. the authors investigate the issues involved in selecting suitable scr-td values for a given source, both from a user's perspective and from a networking point of view.
resource and connection admission control in real-time transport protocols with deterministic qos guarantees. real-time multimedia applications will require guaranteed quality of service (qos) such as a bound on the maximum message delay and/or on the maximum message loss rate. this poses an exciting challenge to the highspeed transport protocol design and implementations. in this paper, we study the resource and connection admission control algorithms, and give the necessary and sufficient conditions for the schedulability, of n real-time transport connections at a destination host under preemptive and non-preemptive deadline scheduling policy for deterministic qos guarantees. these necessary and sufficient conditions form the mathematical basis for the deterministic qos guarantees in real-time transport communication services. on the basis of these necessary and sufficient conditions, we give the connection admission control algorithms for deterministic qos guarantees. we also calculate the buffer space needed for each real-time transport connection. the results show that real-time transport connections with deterministic qos guarantees can reserve the buffer space at the establishment phase, and no flow control mechanism is required during the data transport phase. our results could be applied to other fields as well, such as real-time operating systems.
performance of a crosspoint buffered atm switch fabric. the authors present a queuing analysis and a simulation study of banyan switch fabrics based on 2&times;2 switching elements with crosspoint buffering. in particular, the results apply to the phoenix switching element based banyan fabrics. the results indicate that crosspoint buffering provides throughput approaching the offered load under uniform traffic conditions. the effect of bursty traffic on the performance of the switch is studied. it is shown that a speedup factor of three or more is required to achieve acceptable delay and packet loss probability. it is also shown that the amount of buffer space required per port increases linearly with the burst size for a desired packet loss performance. for a given burst size the packet loss rate decreases exponentially as the buffer size is increased. the impact of crosspoint buffering and shared buffering in the switching elements on the performance of the banyan fabric is analyzed
priority performance of atm packet switches. an asynchronous transfer mode (atm) packet switch should be capable of handling delay sensitive as well as loss sensitive traffic. the authors consider delinking handling of these two types of priorities in a switching system, and present an analysis of two classes of delay sensitive traffic in an n&times;n nonblocking switch with input queues. in such a switch, two variations of nonpreemptive priority are studied. a packet switch with input buffers has inadequate throughput. to enhance the performance and to provide low delay to high priority traffic, a dual plane switch architecture is examined, where each plane is a nonblocking switch with input buffers. the two planes are connected in parallel to form a load sharing arrangement. the analysis of a single plane nonblocking switch is extended to this architecture. in both cases, the performance is compared with the simulation results of a 64&times;64 switch
resource sharing for multi-party real-time communication. approaches to supporting real-time communication allocate network resources either to individual connections, or to aggregates of connections. resource sharing is a new approach that exploits known relationships between related connections to allow network resources to be shared between them without sacrificing well-defined guarantees. the authors present a fully distributed technique for using resource sharing to provide guaranteed performance communication in a heterogeneous internetwork. results show that resource sharing leads to a large gain in the connection acceptance rate, and a significant reduction in the computational overhead associated with admission control. thus, resource sharing is an important tool for providing real-time performance guarantees for large conferences.
design and performance analysis of a dynamic protocol achieving user fairness in high-speed dual-bus networks. the ieee 802-6 dqdb protocol solves the existing problems in prior round-robin high-speed mac protocols. however, it introduces a new performance unfairness problem when the network size or channel bandwidth increases. the pi-persistent protocol, on the other hand, does not pass any control information over the channels, and was shown capable of achieving various fairness criteria, when each station knows the loads of all other stations. the authors propose a dynamic pi-persistent protocol that is capable of adjusting the network to fair operation in an environment where the station loads change over time. the protocol requires passing of some control information through the network. the information passed is not as detailed as the request information in dqdb. the authors analyze the performance of the protocol in a batch arriving model for load increase. the results show that the protocol is both fast and accurate in responding to network load changes
network transparency: the planet approach. asynchronous transfer mode (atm) is being suggested as the basis for future high speed, universal networks. a key requirement for future atm networks will be transparency, i.e. for the network to alter or manipulate the user information as little as possible. a transparent transport mechanism, planet, based on extensions of the current atm standard and ibm's earlier paris technology, is proposed. it is shown how planet can satisfy the universal transport requirement of atm, while avoiding some demonstrated deficiencies. in fact, planet could be viewed as an enhanced version of atm that may be more suitable for the late 1990s than the current standard
performance of fddi under overload. the performance of the fiber distributed data interface (fddi) under overload is studied. it is well known that, under overload, fddi can settle into one of many recurrent sets of states. the idea of desirable and undesirable states is introduced. a desirable state is one where users share the capacity more or less equally in each token rotation. it is shown that the response times of interactive users are adversely affected if the system operates in an undesirable set of states. the waiting time of heavy users can be reduced by forcing the system to settle into the desirable states. simple control mechanisms are proposed to ensure that the system settle into the desirable states
fast simulation of a voice-data multiplexer. this paper considers the problem of estimating, via simulation, extremely low packet loss rates in a voice-data multiplexer. the multiplexer gives priority to voice packets, unless the data queue length exceeds a threshold. to efficiently simulate such low loss rates requires the proper use of importance sampling. in this paper we describe an importance sampling technique that is guaranteed to provide an exponential decrease in variance over standard simulation. this importance sampling technique has two phases, with a different importance sampling strategy in each phase. experimental results are presented that demonstrate the effectiveness of this approach.
gossip-based ad hoc routing. many ad hoc routing protocols are based on some variant of flooding. despite various optimizations of flooding, many routing messages are propagated unnecessarily. we propose a gossiping-based approach, where each node forwards a message with some probability, to reduce the overhead of the routing protocols. gossiping exhibits bimodal behavior in sufficienty large networks: in some executions, the gossip dies out quickly and hardly any node gets the message; in the remaining executions, a substantial fraction of the nodes gets the message. the fraction of executions in which most nodes get the message depends on the gossiping probability and the topology of the network. in the networks we have considered, using gossiping probability between 0.6 and 0.8 suffices to ensure that almost every node gets the message in almost every execution. for large networks, this simple gossiping protocol uses up to 35% fewer messages than flooding, with improved performance. gossiping can also be combined with various optimizations of flooding to yield further benefits. simulations show that adding gossiping to aodv results in significant performance improvement, even in networks as small as 150 nodes. our results suggest that the improvement should be even more significant in larger networks.
on slot allocation for time-constrained messages in dqdb networks. the paper addresses the issue of guaranteeing the timely delivery of isochronous messages with hard deadlines in a distributed queue dual bus (dqdb) network. the authors propose a slot allocation scheme which can allocate bandwidth for a set of isochronous message streams and provide deterministic deadline guarantees. the allocation scheme is guaranteed to find a feasible slot allocation (in the sense that all messages can be transmitted in a timely manner) as long as the total message density is less than or equal to a certain threshold, where the total message density is defined as the summation (over all message streams) of the ratio of maximum message size to message deadline. the implementation of this scheme is simple and does not require any change of the current dqdb standard.
a polynominal-time optimal synchronous bandwidth allocation scheme for the timed-token mac protocol. numerous methods have been proposed to integrate real-time and non-real-time services of the timed-token medium access control (mac) protocol. one of the key issues in tailoring the timed-token mac protocol for real-time applications is the synchronous bandwidth allocation (sea) problem whose objective is to meet both the protocol and deadline constraints. several non-optimal local sea schemes and an optimal global scheme have been proposed previously. local sea schemes use only information available locally to each node, and are thus preferred to global schemes because of their lower network-management overhead. unfortunately it has been formally proved in han et al. (1995) that there does not exist any optimal local sea scheme. chen et al. [1992] proposed the only-known optimal global sea scheme which is based on an iterative approach. however, their algorithm may not terminate theoretically. the present authors give an optimal global sea scheme of polynomial-time worst-case complexity.
toward formal ttcn-based test execution. formal test execution method is an important research field in formal protocol conformance testing. in this paper, we propose a formal test execution aapproach that is based on test notation ttcn's operational semantics, and describe its executing process by using input-output transition system(iots). we also give out a pratical design of this formal approach. this formal ttcn-based test execution method is very suitable for the construction of general protocol test system, and also an effective means of automatic test suite verification.
performance of alternative routing methods in all-optical switching networks. we study routing methods in all--optical switching networks. in all--optical switching networks, the connection with more hops encounters more call blocking, and it is especially true in optical networks with no wavelength conversions. we therefore consider an alternate routing method with limited trunk reservation in which connections with more hops are prepared more alternate routes. through developing an approximate analytic approach, we show that our method keeps good performance when compared with the existing alternate routing methods, and also that the fairness among connections can be improved. further performance improvement is investigated by introducing a wavelength assignment policy and a dynamic routing method. an effectiveness of the proposed method is investigated through simulation.
measuring bottleneck bandwidth of targeted path segments. abstract accurate measurement of network bandwidth is crucial for flexible internet applications and protocols which actively manage and dynamically adapt to changing utilization of network resources. these applications must do so to perform tasks such as distributing and delivering high-bandwidth media, scheduling service requests and performing admission control. extensive work has focused on two approaches to measuring bandwidth: measuring it hop-by-hop, and measuring it end-to-end along a path. unfortunately, best-practice techniques for the former are inefficient and techniques for the latter are only able to observe bottlenecks visible at end-to-end scope. in this paper, we develop and simulate end-to-end probing methods which can measure bottleneck bandwidth along arbitrary, targeted subpaths of a path in the network, including subpaths shared by a set of flows. as another important contribution, we describe a number of practical applications which we foresee as standing to benefit from solutions to this problem, especially in emerging, flexible network architectures such as overlay networks, ad-hoc networks, peer-to-peer architectures and massively accessed content servers.
comparisons of packet scheduling algorithms for fair service among connections on the internet. we investigate the performance of tcp under three representatives of packet scheduling algorithms at the router. our main focus is to investigate how fair service can be provided for elastic applications sharing the link. packet scheduling algorithms that we consider are fifo (first in first out), red (random early detection), and drr (deficit round robin). through simulation and analysis results, we discuss the degree of achieved fairness in those scheduling algorithms. furthermore, we propose a new algorithm which combines red and drr algorithms in order to prevent the unfairness property of the original drr algorithm, which appears in some circumstances where we want to resolve the scalability problem of the drr algorithm. in addition to tcp reno version, we consider tcp vegas to investigate its capability of providing the fairness. the results show that the principle of tcp vegas conforms to drr, but it cannot help improving the fairness among connections in fifo and red cases, which seems to be a substantial obstacle for the deployment of tcp vegas.
a general purpose cell sequencer/scheduler for atm switches. groups of cells, such as cells belonging to different priority levels, that are all placed in one queue, can be identified by using labels or tags to distinguish them from each other. in this paper we describe a buffering device called sequencer, which can distinguish logical queues within the same physical queue, and at the same time can successfully schedule the service among these logical queues. scheduling the service among cells, vc's, or groups of cells in atm switches is necessary to provide guaranteed qos for each connection which is a major goal of atm networks. the proposed sequencer is quite flexible and can realize different scheduling algorithms in different levels, including per vc scheduling.the sequencer can operate in real time and at very high speeds. it has a simple and modular architecture and can be implemented in a single chip. the size of the buffer can be increased simply by cascading several sequencers.the sequencer can be used as traffic shaper, input buffer, output buffer, or queue controller of ram-based switches.
the single queue switch. in this paper we introduce a new approach to atm switching. we propose an atm switch architecture which: uses only a single shift-register-type buffering element to store and queue the cells; and within the same physical queue switches the cells by organizing them in logical queues destined to different output lines. the buffer is also a sequencer which allows flexible ordering the cells in each logical queue to achieve any appropriate scheduling algorithm.this switch is proposed for use as the building block of large-scale multi-stage atm switches and as the scheduler/controller for the ram-based switches. the single queue switch implements output queueing and performs full buffer sharing. the hardware complexity is low. the number of input and output lines can vary independently without affecting the switch core. the size of the buffering space can be increased by simply cascading the buffering elements to each other.
local optical distribution. the authors explore a metropolitan area network (man) configuration which assumes capabilities of optical fiber and optical components which are anticipated to be available within a ten-year time frame. there are two possible physical configurations: a basic topology, such as the star and the tree, and a compound configuration, such as the tree-star-tree. as a logical overlay which serves to route information packets between stations, a form of perfect shuffle, the shufflenet, is used. performance is calculated in terms of average packet delay as a function of traffic load. of particular interest is the effect of physical limitations on performance. in particular, the effect of a limitation on the bandwidth of optical amplifiers is delineated. this limitation increases the length of the path between originating and terminating stations
reliability and performance of multi-level loop computer networks. an improved network architecture which incorporates high reliability, high performance, and optimal accommodation to environmental topologies is presented. the network investigated is tree-shaped, where the leaves represent host computers or loop subnetworks and the vertices are ring adapters attaching hosts or bridges interconnecting subnetworks. for ease of modeling only balanced and homogeneous structures are considered where loop subnetworks have the same topology. multilevel hierarchical loop networks have minimal diameter when the number of nodes in the subnetworks is proportional to the root of the number of all attached stations. in this case, the diameter grows only with the logarithm of the number of stations. this implies that network reliability and performance are significantly improved using the proposed multilevel hierarchical architecture. the performance analysis assumes the protocol of buffer insertion
switch-aided flooding operations in atm networks. in this paper, we propose a flooding method, called switch-aided flooding (saf), for use in atm networks. saf-based protocols take advantage of hardware-supported cell relay and cell duplication, characteristic of such networks, in order to reduce the time needed to disseminate changes in network topology and resource availability. saf protocols use a spanning multipoint connection (smc), which is a hardware-switched network spanning tree, but revert to conventional link-by-link flooding when the spanning mc is unavailable or under construction. the results of a simulation study reveal that the proposed flooding protocols deliver network updates several times faster than conventional approaches, while using significantly less bandwidth.
dtcap - a distributed tunable-channel access protocol for multi-channel photonic dual bus networks. in a multi-channel photonic dual bus network, each unidirectional bus contains a number of channels (wavelengths) and the bus headend periodically generates fixed length slots on each of the channels. generally, one channel called the control channel is used to carry signals and the others are data channels. each station is equipped with one-fixed-transmitter and one fixed-receiver which are permanently tuned to the dedicated control channel, and n tunable-transmitters and m tunable-receivers are tunable over the entire wavelength range. for non-overlapping traffic in the network, the maximum network throughput will be achieved by applying the wavelength reusing concept. given a set of serving traffic, a set of new traffic requests, and c data channels (wavelengths), the wavelength/receiver assignment problem ((n, m, c)-wrap) is to assign a transmission wavelength and a receiver for each request such that the network throughput is maximized and the number of assigned wavelengths is minimized. in this paper, we prove that the (n, m, c)-wrap is np-hard. an efficient distributed tunable-channel access protocol (dtcap) is proposed for the (1, m, c)-wrap. based on the dtcap, three different schemes are proposed for assigning the wavelength/receiver. the performance of the three proposed schemes on the dtcap are evaluated and compared by simulation. simulation results demonstrate that for a limited number of wavelengths and receivers, the proposed schemes substantially improve the network throughput and access delay under general traffic demands.
virtual lan internetworking over atm networks for mobile stations. one of the most attractive features of the virtual lan (vlan) is the capability to group users into broadcast domains, which are independent of their locations on the physical network. this paper deals with the vlan services using atm lan emulation technology which operates on a client/server model. the focuses are on the issues of supporting transparent vlan services and internetworking among vlans for mobile stations. a mobile vlan (mvlan) architecture is proposed, perhaps for the first time, to efficiently maintain multiple vlan broadcast domains over a single atm network even when the vlans contain mobile stations. the proposed solution (1) ensures that layer 2 frames between a mobile station and any station, either static or mobile, that belongs to the original registered vlan can be exchanged transparently, (2) provides transparent communications between vlans using the layer 2 bridging approach, and (3) handles excessive server-to-server traffic efficiently, including the broadcast/multicast frames. the proposed mvlan architecture moves one step closer towards facilitating the mobility management in an atm network while conforming to the emerging lan emulation standard.
checkpoint and rollback in asynchronous distributed systems. this paper proposes a novel algorithm for taking checkpoints and rolling back the processes for recovery in asynchronous distributed systems. the algorithm has the following properties: (1) multiple processes can simultaneously initiate the checkpointing; (2) no additional message is transmitted for taking checkpoints; (3) a set of local checkpoints taken by multiple processes denotes a consistent global state; (4) multiple processes can initiate simultaneously the rollback recovery; (5) the minimum number of processes are rolled back; and (6) each process is rolled back asynchronously. the number of messages for rolling back the processes is o(l) where l is the number of channels. therefore, the system is kept highly available by the algorithm presented.
analyzing a two-stage entry monitor for high-speed networks. several researchers have suggested employing two-stage entry monitorsfor high-speed networks - the first stage enforcing a long term rate, the second stage enforcing a peak rate over a shorter time scale. in spite of this interest, little work on analyzing such systems has appeared. not only is the analysis hard because of the the correlation between the stages, but for the most popular policing scheme, the leaky bucket, prior work isnot easily generalized to two stages.this paper presents a performance analysis of a two-stage entry monitor,by analyzing the combined queue length of a two-stage system. our analysis is for a two-stage buffered moving window. analyzing such a conservative scheme enables us to bound the penalty of more optimistic schemes, in particular a two stage leaky bucket based system. we obtain a closed form analytical result, and show how to evaluate it for a wide range of parameters of interest. our results show that the performance penalty of having the second stage is minimal under reasonable rateassumptions.
earthworm: a network memory management technique for large-scale distributed multimedia applications. the two main operating constraints of today's multimedia servers are the i/o bandwidth and communication bandwidth limitations. both of these problems are addressed in this paper using a novel technique called "earthworm". in this scheme, the network memory is used as a huge cache for buffering multimedia data. dramatic reduction in the demand on the i/o bandwidth, therefore, can be achieved. this scheme also chains display stations to allow them to forward video streams. this strategy eliminates the congestion at the communication port of the server. removing this bottleneck allows our technique to operate on the vast aggregate bandwidth of the wan, rather than being constrained by the very limited local bandwidth available to the server. a unique feature of the earthworm approach is that every display station using the server attempts to make some contribution to the caching space and communication bandwidth. the arrival of a new request, therefore, can be seen as a contributor, rather than just a burden to the server. this characteristic ensures the scalability of our design to support very large multimedia applications.
a new had algorithm for optimal routing of hierarchically structured data networks. in this paper, a new algorithm based on hierarchical aggregation/disaggregation and decomposition/composition (had) scheme is proposed to solve the optimal routing problems (orp) for hierarchically structured networks of multi-layer backbones. our algorithm has two major differences with the existing had algorithms for hierarchically clustered networks [1], [2]: 1) our algorithm works with more general networks than the networks with the clustered structure; 2) our algorithm parallelizes the computations for different commodities (message flows defined by a pair of origin node and destination node) so that it speeds up with a parallel time complexity of o(mlog2(n)), which is much less than o(mlog2(n)) needed for the existing had algorithms. here, n is the number of nodes in the network; m is the number of commodities and m is a positive number usually much smaller than m and is a function of the patterns of all the commodities including the locations of all origin nodes and destination nodes, and the flow demand of each commodity. furthermore, our algorithm can make a trade-off between the run time and the optimality, i.e., by allowing the solution to be sub-optimal, our algorithm can save great amount of computation time. the implementation of the algorithm for a 200-node network is simulated using opnet simulation package (opnet or optimized network engineering tools is developed by mil3, inc.), and the test results are consistent with our analysis.
cooperating leaky bucket for average rate enforcement of vbr video traffic in atm networks. because of the burstiness of video traffic, a very large sampling interval is needed to obtain acceptable cell loss probability. previous studies reported very high cell loss probabilities for well-behaved sources when using the leaky bucket mechanism (lb) to police vbr video sources. in this paper, a mean rate policing mechanism called cooperating leaky bucket (clb) is introduced. this mechanism can attain better cell loss probability by sharing the leaky buckets among all sources. in addition, it guarantees that the cell loss probability will never be higher than that obtained by lb. depending on the number of traffic sources available, the cell loss probability can be significantly reduced when compared to lb. at the same time, the combined traffic entering the network is enforced to below the total negotiated traffic rate. moreover, the additional overhead due to the implementation of clb is minimal.
adaptive multicast routing in single rate loss networks. propose a new approach, based on the maximum free circuit routing (mfcr) concept, toward multicast routing in single rate loss networks. two versions of the multicast routing problems are studied: static and dynamic. in the static version of the multicast routing problem, the identities of all destination nodes are available to the multicast routing algorithm at once. conversely, in the dynamic version of the multicast problem, the identities of the destination nodes are revealed to the routing algorithm one by one. the authors studied three mfcr-based multicast routing algorithms: one for the static multicast problem and two for the dynamic multicast problem. they also propose a new performance metric, referred to as fractional reward loss, for evaluating these three multicast routing algorithms. the performance of there three multicast routing algorithms are evaluated through simulations.
on designing improved controllers for aqm routers supporting tcp flows. tr#: 00-42 tr title: on designing improved controllers for aqm routers supporting tcp flows authors : c.v hollot, v. misra, d. towsley, w. gong address computer science department 140 governor''s drive university of massachusetts amherst, ma 01003-4601 date: 7/10/00 on designing improved controllers for aqm routers supporting tcp flows in this report we study a previously developed linearized model of tcp and aqm. we use classical control system techniques to develop controllers well suited for the application. the controllers are shown to have better theoretical properties than the well known red controller. we present guidelines for designing stable controllers subject to network parameters like load level, propogation delay etc. we also present simple implementation techniques which require a minimal change to red implementations. the performance of the controllers are verified and compared with red using \texttt{ns} simulations. the second of our designs, the proportional integral (pi) controller is shown to outperform red significantly.
llr routing in homogeneous vp-based atm networks. in atm networks, a virtual path (vp) concept has been proposed to simplify traffic control and resource management. as a consequence, cell routing becomes more flexible and significant call setup processing can be reduced when resources are reserved on vp's. in this paper, we study the routing problem in homogeneous vp-based atm networks in which vp's are used for traffic segregation such that all vc's in a vp have the same traffic characteristics and qos requirement. four adaptive routing algorithms based on the least loaded routing (llr) concept are designed and evaluated. our simulation results show that network blocking probability can be significantly reduced by llr routing.
the effect of processing delay and qos requirements in high speed networks. the authors examine the effects of call processing delay, propagation delay, the admission control function due to quality of service (qos) requirements, and routing algorithms on the call setup time in future b-isdn networks. three routing schemes from circuit-switched networks and two parallel versions of these routing schemes are investigated under various network parameters and different forms of admission control. analytic models for different routing algorithms are developed and were validated by simulation results. the results of the study indicate that call processing delay associated with the admission control function affects the network performance significantly while propagation delay does not affect the performance significantly
on the convergence of traffic measurement and queueing analysis: a statistical-match queueing (smaq) tool. the analytical tool developed in this paper provides a general solution technique for the integration of traffic measurement and queueing analysis. the frequency-domain approach is used to combine the advanced techniques in two areas: signal processing and queueing analysis. essentially, signal processing techniques are used to obtain the steady-state and second-order statistics of a traffic stream. the focus here is on the construction of a special class of markov chains that can statistically match with each given traffic stream (or superposition of different traffic streams). the analytical queueing solutions can therefore be obtained by the folding-algorithm based on the markov chain input modeling. comprehensive numerical examples show the great potential of the smaq tool to solve measurement-based traffic management issues.
usage-based pricing of packet data generated by a heterogeneous user population. usage-based pricing of offered traffic to a data network can be an effective technique for congestion control. to gain insight into the benefits usage-based pricing offers, the authors propose and study a simple model in which many users wish to transmit packets to a single-server queue. based on the announced price per packet and the available quality of service (qos) (e.g., mean delay), each user independently decides whether or not to transmit. given statistical assumptions about the incoming traffic streams and the qos as a function of offered load, the equilibrium relationship between price and qos is determined by a fixed-point equation. the relationships among price, qos, revenue, and server capacity are illustrated numerically, assuming a particular type of random user population. these examples indicate that adjusting the price to maximize revenue results in an efficient use of service capacity with an associated small mean delay.
proactive network fault detection. the increasing role of communication networks in today's society results in a demand for higher levels of network availability and reliability. at the same time, fault management is becoming more difficult due to the dynamic nature and heterogeneity of networks. we propose an intelligent monitoring system using adaptive statistical techniques. the system continually learns the normal behavior of the network and detects deviations from the norm. within the monitoring system, the measurements are segmented, and features extracted from the segments are used to describe the behavior of the measurement variables. this information is combined in the structure of a bayesian network. the proposed system is thereby able to detect unknown or unseen faults. experimental results on real network data demonstrate that the proposed system can detect abnormal behavior before a fault actually occurs.
adaptive data structures for ip lookups. the problem of efficient data structures for ip lookups has been well studied in the literature. techniques such as lc tries and extensible hashing are commonly used. in this paper, we address the problem of generalizing lc tries, based on traces of past lookups, to provide performance guarantees for memory suboptimal structures. as a specific example, if a memory-optimal (lc) trie takes 6 mb and the total memory at the router is 8 mb, how should the trie be modified to make best use of the 2 mb of excess memory? we present a greedy algorithm for this problem and prove that, if for the optimal data structure there are b fewer memory accesses on average for each lookup compared with the original trie, the solution produced by the greedy algorithm will have at least 9 &times; b/11 fewer memory accesses on average (compared to the original trie). an efficient implementation of this algorithm presents significant additional challenges. we describe an implementation with a time complexity of o(&xi;(d)nlog n) and a space complexity of o(n), where n is the number of nodes of the trie and d its depth. the depth of a trie is fixed for a given version of the internet protocol and is typically o(log n). in this case, &xi;(d) &equals; o(log2 n). we also demonstrate experimentally the performance and scalability of the algorithm on actual routing data.
a synchronization mechanism for continuous media in multimedia communications. this paper proposes a media synchronization mechanism which adjusts the output timing among stored continuous media streams in multimedia communications. the proposed method consists of intra-stream and inter-stream synchronization mechanisms. the inter-stream synchronization control is performed after the intra-stream synchronization control. then, whether the intra-stream synchronization is still maintained or not is checked. the mechanism con be used in networks which have unknown delay bounds, and it does not suppose periodical generation of media units such as video frames. it also deals with two types of media streams depending on how strictly to synchronize media streams: tightly-coupled media streams and loosely-coupled media streams. furthermore, we enhance the mechanism to support real-time-inputted media streams as in tv conferencing.
a group synchronization mechanism for stored media in multicast communications. this paper proposes a group synchronization mechanism, which synchronizes slave destinations with the master destination, for stored media in multicast communications. at the master and slave destinations, intra-stream and inter-stream synchronization mechanisms which were proposed by the authors are employed to output the master media stream and slave media streams synchronously. we achieve group synchronization by adjusting the output timing of the master media stream at each slave destination to that at the master destination.we also deal with traffic control by media scaling and control of joining an in-progress multicast group. furthermore, the paper presents experimental results using an atm network. it shows the validity of the mechanism and illustrates the influence of parameters on the system performance.
bounds for the tail distribution in a queue with the superposition of general periodic markov sources. in this paper, we derive the bounds formulas for the asymptotic tail distribution in a queue whose arrival process is a superposition of general periodic markov sources. note that we make no assumption for the structure of the general periodic markov sources except that the underlying markov chains are irreducible. the periodic source model in this paper is thus rather general. taking initial state conditions of the periodic sources into account, we construct a superposed arrival process. contrary to the previous works, this implies that the periodic sources are not independent. we also provide examples to investigate the efficiency and the accuracy of our bound formulas.
performance of a mass storage system for video-on-demand. advancements in storage technology along with the fast deployment of high-speed networks has allowed the storage, transmission and manipulation of multimedia information such as text, graphics, still images, video and audio to be feasible. our study focused on, the performance of the mass storage system for a large-scale video-on-demand server. different video file striping schemes, such as application level striping and device driver level striping, were examined in order to study scalability and performance issues. to study the impact of different concurrent access patterns on the performance of a server, experimental results were obtained on group access on a single video file and multiple group accesses on multiple video files.
modelling prioritized mpeg video using tes and a frame spreading strategy for transmission in atm networks. this paper presents an efficient transmission mechanism, using frame spreading, for variable bitrate (vbr) mpeg compressed video, through an atm multiplexer, such as a cable head-end. a priority scheme is implemented in a software mpeg encoder which produces a proportionate traffic in both (i.e., high and low) priority partitions for all three frame types (intraframe, predicted and interpolated) used in mpeg. an atm multiplexer with a pushout buffer scheme is implemented for the study, in order to provide priority scheduling at the multiplexer for the two priority partitions. the multiplexer is fed with vbr mpeg traffic and performance statistics such as the cell loss ratios are studied for various frame spreading scenarios. two statistical models are developed using tes (transform expand sample) for vbr mpeg video having two levels of priority. the first model is matched with the empirical histogram and autocorrelation function of each frame type (i, p and b). the second model is created with the assumption of a gamma distribution for the number of bits in each frame type. experiments are conducted using both models and the results are compared.
bihop: a bidirectional highly optimized pipelining technique for large-scale multimedia servers. we present a technique, called bidirectional highly optimized pipelining (bihop), for managing disks as a buffer for the tertiary storage of a multimedia server. we implement a simulator to compare its performance to that of a recently proposed scheme called sep. the results show that bihop performs significantly better. its superior performance is attributed to a novel caching approach, which caches every other data fragment of the multimedia file, rather than caches consecutive fragments as in traditional practice. this new approach allows us to use tiny staging buffers for pipelining, which can be implemented in the memory to conserve disk bandwidth. furthermore, the whole disk space can be dedicated for caching purposes to improve hit ratio. another important advantage of bihop is its ability to pipeline in either forward or reverse direction with the same efficiency. this unique feature, not possible with existing schemes, makes it natural for implementing vcr functions.
a very simple algorithm for flow control on high speed networks via la palice queueings. flow control algorithms specially designed for high speed networks are introduced. they are based on a new queuing model called the la palice queue. an algorithm that is simply an extrapolation of the classic flow control algorithm with a request to the destination and an answer to the source is presented. it is shown that the overflow occurrence is lowered to a certain probability by the application of the algorithm. an intermediate algorithm is presented that cancels overflow occurrence, but allows repetition of requests with a certain probability per multipacket message
a forwarding strategy to reduce network impacts of pcs. we propose a per-user forwarding strategy for locating users who move from place to place while using personal communications services (pcs). the forwarding strategy augments the basic location strategy proposed in existing standards such as gsm and is-41, with the objective of reducing network signalling and database loads in exchange for increased cpu processing and memory costs. with the forwarding strategy, calls to a given user will first query the user's home location register (hlr) to determine the first visitor location register (vlr) which the user was registered at, and then follow a chain of forwarding pointers to the user's current vlr. this strategy is useful for those users who receive calls infrequently relative to the rate at which they change registration areas. we use a reference pcs architecture and the notion of a user's call-to-mobility ratio (cmr) to quantify the costs and benefits of using forwarding and classes of users for whom it would be beneficial. we show that sender a variety of assumptions forwarding is likely to yield significant net benefits for certain classes of users, in exchange (possibly) for a small increase in mean call setup time. for instance, under certain cost assumptions, for users with cmr>1 forwarding can result in 20-60% savings over the basic strategy, with no increase in mean call setup time.
an assigned-buffer atm switching architecture. there has been a great technological advancement in microelectronics and communications, which forces, among others, investigations on atm switching architectures. researchers keep on searching an efficient architecture, able to perform at a wide range of traffic loads and patterns, ensuring both minimum probability of cell loss as well as minimum cell delay. the authors propose one more architecture. the main goal is to create an architecture capable of operating at very high data rates. as the result, the switch uses the fastest method of buffer management, and is characterized by sufficiently low probability of blocking and short delay time. appropriate simulation results are presented and some implementation issues are discussed.
scalability and flexibility in authentication services: the kryptoknight approach. this paper studies the issues of flexibility and scalability in the context of network security. in particular, it concentrates on authentication and key distribution services suited for a variety of communication paradigms, network environments, and end-devices. we present the design criteria, specification, and step-by-step construction of authentication and key distribution services based on experience in the kryptoknight project. the central goal of the kryptoknight project was the construction of basic network security functions in a minimal, flexible (thus, versatile) and scalable manner. protocol minimality (in terms of resource usage) and flexibility are not merely theoretical goals; they have clear advantages in environments where computational resources are limited and connectivity is restricted. kryptoknight was aimed at such environments: small and anemic wireless devices, simple network and data-link entities, embedded micro-devices and other special-purpose communication equipment and configurations. furthermore, scalability of protocols makes their deployment possible in the presence of rapid network growth and inter-domain communication.
regular multicast multihop lightwave networks. a class of multicast multihop lightwave networks (mlns) is presented. these networks have a two-layered architecture, with the upper "logical layer" implemented electronically, and supported by an underlying "physical layer" implemented as a purely optical network. the unique feature studied is that the logical topology has a regular multicast structure, which is created through the use of optical multicast in the physical layer. it is shown that this type of logical topology yields networks which have significantly superior performance features, when compared with either purely optical networks, or with multihop networks based on point-to-point connections. special regular logical topologies based on kautz hypergraphs are used in designing the networks.
message delay analysis of the dqdb (ieee 802.6) network. the analytical evaluation of the message delay in a distributed queue dual bus (dqdb) network is investigated. the authors extend the results obtained by c. bisdikian et al. (1990), which assumes that each network station can queue at most one packet, to the case of station queues each holding an entire message containing l packets. an expression is obtained for the number of requests queued ahead of an arriving message. given this expression, the average message delay can be calculated. one conclusion drawn from the analysis is that the average steady-state message delay is linear in sufficiently large l . it is also concluded that the message delay increases considerably with the network load. the analytical results predict the position-dependent characteristics of stations in a heavily loaded network and explain some observations and results of earlier simulation studies
dynamic node activation in networks of rechargeable sensors. we consider a network of rechargeable sensors, deployed redundantly in a random sensing environment, and address the problem of how sensor nodes should be activated dynamically so as to maximize a generalized system performance objective. the optimal sensor activation problem is a very difficult decision question, and under markovian assumptions on the sensor discharge/recharge periods, it represents a complex semi-markov decision problem. with the goal of developing a practical, distributed but efficient solution to this complex, global optimization problem, we first consider the activation question for a set of sensor nodes whose coverage areas overlap completely. for this scenario, we show analytically that there exists a simple threshold activation policy that achieves a performance of at least 3/4 of the optimum over all possible policies. we extend this threshold policy to a general network setting where the coverage areas of different sensors could have partial or no overlap with each other, and show by simulations that the performance of our policy is very close to that of the globally optimal policy. our policy is fully distributed, and requires the sensor nodes to only keep track of the node activation states in its immediate neighborhood. we also consider the effects of spatial correlation on the performance of the threshold activation policy, and the choice of the optimal threshold.
routing restorable bandwidth guaranteed connections using maximum 2-route flows. routing with service restorability is of much importance in multi-protocol label switched (mpls) networks, and is a necessity in optical networks. for restoration, each connection has an active path and a link-disjoint backup path. the backup path enables service restoration upon active path failure. for bandwidth efficiency, backups may be shared. this requires that at least the aggregate backup bandwidth used on each link be distributed to nodes performing route computations. if this information is not available, sharing is not possible. also, one scheme in use for restorability in optical networks is for the sender to transmit simultaneously on the two disjoint paths and for the receiver to choose data from the path with stronger signal. this has the advantage of fast receiver-initiated recovery upon failure but it does not allow backup sharing.in this paper, we consider the problem of efficient dynamic routing of restorable connections when backup sharing is not allowed. our objective is to be able to route as many connections as possible for one-at-a-time arrivals and no knowledge of future arrivals. since sharing cannot be used for achieving efficiency, the goal is to achieve efficiency by improved path selection. we show that by using the minimum-interference ideas used for nonrestorable routing, we can develop efficient algorithms that outperform previously proposed algorithms for restorable routing such as routing with the min-hop like objective of finding two disjoint paths with minimum total hop-count. we present two new and efficient algorithms for restorable routing without sharing, and one of them requires only shortest path computations. we demonstrate that both algorithms perform very well in comparison to previously proposed algorithms.
atmtrap: an asynchronous transfer mode traffic and performance measurement tool. the analysis and development of atm network traffic control algorithms is often performed using theoretical traffic models. algorithms for traffic shaping, policing, flow control, and switch architectures have been proposed based on these models. while the models help to obtain preliminary solutions, the success and validity of the proposed algorithm will be a function of how close the assumed models resemble real traffic patterns. the paper presents atmtrap, an experimental prototype asynchronous transfer mode traffic and performance measurement tool which could be used in the characterization of sources and elements that form the atm network. atmtrap has been used in the nectar gigabit testbed to collect preliminary traffic statistics from sources, such as, a cray c-90 supercomputer, sun workstations, and an iwarp systolic array.
improving the performance of input-queued atm packet switches. the authors propose a single way to dramatically improve the performance of input-queued atm packet switches beyond the 82% saturation point obtained in previous work. the method is an extension of the independent output-port schedulers technique and is based on the notion of recycled time slots, i.e. reusing time slots normally wasted due to scheduling conflicts. in contrast to previous results, the technique yields a throughput improvement from 65% to 92% without speedup, trunking, or complicated hardware. if input grouping with a group size of four is also employed, then the method can yield up to 95% throughput
prevention of deadlocks and livelocks in lossless, backpressured packet networks. no packets will be dropped inside a packet network, even when congestion builds up, if congested nodes send backpressure feedback to neighboring nodes, informing them of unavailability of buffering capacity-stopping them from forwarding more packets until enough buffer becomes available. while there are potential advantages in backpressured networks that do not allow packet dropping, such networks are susceptible to a condition known as deadlock in which throughput of the network or part of the network goes to zero (i.e., no packets are transmitted). in this paper, we describe a simple, lossless method of preventing deadlocks and livelocks in backpressured packet networks. in contrast with prior approaches, our proposed technique does not introduce any packet losses, does not corrupt packet sequence, and does not require any changes to packet headers. it represents a new networking paradigm in which internal network losses are avoided (thereby simplifying the design of other network protocols) and internal network delays are bounded.
an energy efficient mac protocol for wireless lans. this paper presents an optimization of the power saving mechanism in the distributed coordination function (dcf) in ieee 802.11 standard. in the 802.11 power saving mode specified for dcf, time is divided into so-called {\em beacon intervals}. at the start of each beacon interval, each node in the power saving mode periodically wakes up for a duration called the {\em atim window}. the nodes are required to be synchronized to ensure that all nodes wake up at the same time. during the atim window, the nodes exchange control packets to determine whether they need to stay awake for the rest of the beacon interval. the size of the atim window has a significant impact on energy saving and throughput achieved by the nodes. this paper proposes an adaptive mechanism to dynamically choose a suitable atim window size. we also allow the nodes to stay awake for only a fraction of the beacon interval following the atim window. on the other hand, 802.11 dcf mode requires the nodes to stay awake either for the entire beacon interval following the atim window or none at all. simulation results show that the proposed approach outperforms the ieee 802.11 power saving mechanism in terms of throughput and the amount of energy consumed.
performance analysis of the rotating slot generator scheme. a thorough investigation of the performance of the rotating slot generator (rsg) scheme, based on simulation, is presented. rsg is a medium access control protocol appropriate for high-capacity long-distance metropolitan area networks (mans). it uses the looped bus architecture of the distributed queue dual bus (dqdb) in which the slot generators for both busses are colocated inside the same station. however in rsg, all the stations, one after the other in a cyclic order, undertake the task of generating and destroying the slots on both busses. in this way the location of the station relative to the slot generator changes dynamically, and its effect on the performance is drastically reduced. the authors investigate the fairness and performance of rsg under symmetric and asymmetric loading, underload and overload conditions, and under the presence of a single or multiple priority classes of traffic. they also compare its performance with different variations of dqdb
fdq: the fair distributed queue man. a new protocol, fair distributed queue (fdq), suitable for very high speed metropolitan area networks (mans), is presented. fdq is a slotted system implemented on a unidirectional fiber bus. it has similarities to the distributed queue dual bus (dqdb) protocol. fdq achieves full throughput efficiency independent of the bus length, the transmission speed, and the number of nodes. fdq allocates equal bandwidth under heavy load to all active users in a time period less than or equal to the round-trip propagation delay without wasting bandwidth. its delay characteristics were studied via simulation and compared to dqdb. fdq has lower average delays under a poisson load than the dqdb protocol with or without the bandwidth balancing mechanism. the implementation of priority levels and detailed timing structure of the protocol are also described. it was shown that fdq's delay and throughput characteristics were only slightly affected by increasing distances or the number of nodes
exact and approximate analysis of dqdb under heavy load. the distributed queue dual bus (dqdb) standard is studied under heavy load conditions. the dqdb protocol for asynchronous traffic is reviewed. the network model and analysis are presented when there are two active nodes. analytic expressions are derived for the steady-state nodal throughputs and the average value of the request counters of inactive nodes. the three-station case is considered by providing an accurate approximation for the situation when the third node is in between the two initially active nodes. simulation results are given for comparison. the effect of the position of a node was studied via simulation in the three-station case. the case when one of the active nodes becomes inactive in a network with three initially active nodes is analyzed. the state the network assumes is studied in terms of nodal throughputs after one of the nodes turns off, and the impact on the request counters of the inactive nodes are investigated
a comparison of server-based and receiver-based local recovery approaches for scalable reliable multicast. local recovery approaches for reliable multicast have the potential to provide significant performance gains in terms of reduced bandwidth and delay, and higher system throughput. in this report we examine one server--based and two receiver--based approaches, and compare their performance. the server--based approach makes use of specially designated hosts, called repair servers, co--located with routers inside the network. in the receiver-based approach, only the end hosts (sender and receivers) are involved in error recovery. using analytical models, we first show that the three local recovery approaches yield significantly higher protocol throughput and lower bandwidth usage than an approach that does not use local recovery. next, we demonstrate that server--based local recovery yields higher protocol throughput and lower bandwidth usage than receiver--based local recovery when the repair servers have processing power slightly higher than that of a receiver and a few hundred kilobytes of buffer per multicast session.
congestion control policies for ip-based cdma radio access networks. as cdma-based cellular networks mature, the current point-to-point links used in connecting base stations to network controllers will evolve to an ip-based radio access network (ran) for reasons of lower cost due to statistical multiplexing gains, better scalability and reliability, and the projected growth in data applications. in this paper, we study the impact of congestion in a best-effort ip ran on cdma cellular voice networks. we propose and evaluate three congestion control mechanisms, admission control, diversity control, and router control, to maximize network capacity while maintaining good voice quality. we first propose two new enhancements to cdma call admission control that consider a unified view of both ip ran and air interface resources. next, we introduce a novel technique called diversity control that exploits the soft-handoff feature of cdma networks and drops selected frames belonging to multiple soft-handoff legs to gracefully degrade voice quality during congestion. finally, we study the impact of router control where an active queue management technique is used to reduce delay and minimize correlated losses. using simulations of a large mobile network, we show that the three different control mechanisms can help gracefully manage 10-40 percent congestion overload in the ip ran.
comparison of dynamic multicast routing algorithms for wide-area packet switched (asynchronous transfer mode) networks. this paper compares three dynamic multipoint routing algorithms for wide-area packet switched networks like asynchronous transfer mode (atm) networks. the three algorithms compared are the greedy algorithm, the source rooted shortest path (sp) algorithm and the geographic spread dynamic multicast (gsdm) routing algorithm. we present simulation results over random graphs that demonstrate the performance of these algorithms. the algorithms are evaluated via a series of multiple simulations in terms of the number of packet copies per node and their (in)efficiency. a near optimal steiner tree heuristic algorithm called the kmb algorithm is used as a measure of the (in)efficiency of the algorithms.
stwnet: a high bandwidth space-time-wavelength multiplexed optical switching network. we propose stwnet, a self-routing high bandwidth optical network architecture for interconnecting users, grouped together as g groups with w users per group. stwnet uses the three dimensions of space, time, and wavelength by combining the advantages of space and temporal switching with the benefits of wavelength parallel data transmissions. technologically difficult switching of individual wavelengths is avoided by prearranging transmissions in a way that they can be switched in a wavelength insensitive manner. wavelengths are reused within the network thus allowing for a larger switching fabric.the proposed architecture can be internally expanded either in the spatial or temporal dimension to allow for multiple packets to be delivered to the same destination group. the expansion factor is determined based on the group knockout principle and given typical traffic patterns is a small number. stwnet allows easy group to group multicasting and broadcasting while system-wide multicasts and broadcasts can be achieved through repetitive group-to-group transmissions. the network uses readily available components such as opto-electronic directional couplers, fixed wavelength transmitters, and diffraction based parallel receivers while avoiding the use of relatively slow and expensive tunable components.
spanning tree method for link state aggregation in large communication networks. we consider a communication network in which dynamic routing is used for establishing connections that support information transfer between end-users. link state information is exchanged and maintained up-to-date among network nodes for path computation and network resource allocation. when the population of users is large, the amount of link state information can be overwhelming. a common solution is to use a hierarchical structure. in this paper, we present a method for aggregating link state information in a hierarchical network. we assume that each link state parameter associated with a link is symmetrical in both directions of the link. the key idea for the method is to first reduce the original subnetwork topology to a full-mesh representation that consists of a logical link for each pair of border nodes in the subnetwork, and then encode the link state information associated with the full-mesh representation with an appropriate spanning tree.
blocking in a completely shared resource environment with state dependent resource and residency requirements. the generalized erlang blocking model has been used to analyze multiplexing, message storage, and communication network performance. the author modifies this model to permit blocked requests to retry, with reduced resource requirements and arbitrary mean residency requirements. because the modification of the generalized erlang model destroys the product-form structure and greatly increases the size of the state space, and exact solution is out of the question. the present approach modifies a well-known one-dimensional recursion developed for the generalized erlang model in an intuitively satisfying manner, and results in an approximation scheme that is both efficient and quite accurate. this study arose in the context of high-speed networks in which high bandwidth but non-real-time messages may, upon being blocked, request service with smaller bandwidth and larger residency time, as long as the bandwidth-residency time product is the same as originally requested
dynamic global packet routing in wireless networks. we consider schemes for reuse-efficient packet access in wireless data networks. we show that computing the maximum ergodic packet arrival rate is np-hard. we give an upper bound on the maximum ergodic throughput in terms of the eigenvalues of matrices related to the path-gain matrix. we present simple, practical heuristic algorithms which exhibit good throughput and packet delay and report on results of preliminary simulations. more sophisticated algorithms that yield optimal throughput are also presented. a recent result of mckeown, anantharam and walrand on scheduling of input-queued switches is obtained as a byproduct.
generalized longest queue first: an adaptive scheduling discipline for atm networks. in this paper, we propose a generalized longest queue first (glqf) service discipline for atm networks. we classify sources so that sources in one class have the same cell loss probability requirement. assume that there are n classes of traffic. under this discipline, buffer i is assigned a positive number wi for the weight of buffer i. the scheduler transmits a cell from the buffer that has the maximal weighted queue length. the advantage of this discipline is that it can adapt to temporary overload quickly. we approximate the queue length distribution by decomposing the system into n single server queues with probabilistic service discipline. our method is an iterative one, which we prove to be convergent by using stochastic dominance arguments and the coupling technique. for high utilization, we present a heavy traffic limit theorem.
two-way tcp traffic over atm: effects and analysis. we examine the performance of bidirectional tcp/ip connections over asynchronous transfer mode (atm) networks using the available bit rate (abr) service. the problem of ``ack-compression'' re-appears, although the queues are primarily at the end-systems. we further the understanding of the problem by quantitatively analyzing the periodic bursty behavior of the source ip queue. we are able to predict the peak values for the queue and arrive at a simple robust predictor for the degraded throughput, applicable for relatively general situations.the degradation in throughput due to bidirectional traffic can be significant. for example, even in the simple case of symmetrical connections with adequate window sizes, the throughput of each connection is only 66.67% of that under one-way traffic. we validate our analysis using simulation, where the atm network uses the explicit rate option. we show that the analysis predicts the behavior of the queue and the throughput degradation. we observe the need to separate the flow of acknowledgments and data for the bidirectional tcp connection and for inter-leaving their processing at the end-systems to overcome the problem of ack compression.
explicit window adaptation: a method to enhance tcp performance. we study the performance of tcp in an internetwork consisting of both rate-controlled and non-rate-controlled segments. a common example of such an environment occurs when the end systems are part of ip datagram networks interconnected by a rate-controlled segment, such as an atm network using the abr service. in the absence of congestive losses in either segment, tcp keeps increasing its window to its maximum size. mismatch between the tcp window and the bandwidth-delay product of the network will result in accumulation of large queues and possibly buffer overflows in the devices at the edges of the rate-controlled segment, causing degraded throughput and unfairness. we develop an explicit feedback scheme, called explicit window adaptation based on modifying the receiver''s advertised window in tcp acknowledgments returning to the source. the window size indicated to tcp is a function of the free buffer in the edge device. results from simulations with a wide range of traffic scenarios show that this explicit window adaptation scheme can control the buffer occupancy efficiently at the edge device, and results in significant improvements in packet loss rate, fairness, and throughput over a packet discard policy such as drop-from-front or random early detection.
analysis of delay performance of atm signaling link. the paper presents an analytic model to explore the delay performance of sscop (service specific connection oriented protocol), which is a signaling protocol for establishing and removing b-isdn connections in a switched virtual circuit (svc) atm network. a comparison with simulation shows that the analytic model works very well in spite of many complexities of the protocol. such a model is invaluable for choosing appropriate protocol parameters, setting delay requirements, and for studying error monitoring algorithms for atm signaling links.
channel sharing scheme for packet-switched cellular networks. in this paper, we study an approach for sharing channels to improve network utilization in packet-switched cellular networks. our scheme exploits unused resources in neighboring cells without the need for global coordination. we formulate a minimax approach to optimizing the allocation of channels in this sharing scheme. we develop a measurement-based distributed algorithm to achieve this objective and study its convergence. we illustrate, via simulation results, that the distributed channel sharing scheme performs significantly better than the fixed channel scheme over a wide variety of traffic conditions.
a performance study of selective cell discarding using the end-of-packet indicator in aal type 5. the atm adaptation layer type 5 (aal5) is a new adaptation layer protocol for the atm layer of broadband integrated services digital networks. among several features, it is unique in the sense that it includes an end-of-packet (eop) indicator in the header of the atm cell (the atm-layer-user-to-atm-layer-user (auu) parameter in the payload type (pt) field). it was previously suggested that the use of this indicator may be used to provide a means by which buffer occupancy can be reduced by dropping cells from already incomplete packets (armitage, 1993). the objective of this paper is to study the performance of this layer and the effectiveness of the eop indicator. the performance measures of interest are the probability of packet loss and the mean packet delay. an approximate analytical model is constructed in which the blocking of a tagged source is kept track of in an exact manner. the rest of the sources are modeled approximately. the accuracy of the model is enhanced through an iterative approach. a simulation model is also constructed to assess the accuracy of the approximate model.
implementation of self-healing function in atm networks based on virtual path concept. this paper proposes an implementation scheme for the self-healing function in atm networks and assesses its performance. first, our proposed atm self-healing scheme is described. this scheme realizes more rapid restoration of failed virtual paths than other self-healing algorithms, supports the node failure case, and minimizes the spare resources required. next, an implementation scheme is proposed. we propose that the self-healing function be implemented as a software process, and that oam cells are utilized for fast message transmission. next, results of a prototype system that we implemented on an atm cross-connect system are discussed. the fundamental characteristics of restoration performance are measured using an experimental network. based on these results, an ne processing system analysis and computer simulation for estimating the characteristics as applied to a real-scale network are discussed. finally, a management scheme for self-healing is proposed based on the tmn concept.
queueing analysis of atm tandem queues with correlated arrivals. considers tandem queues with correlated arrivals and joining interference, which model a portion of a virtual circuit at the access node in an atm network. the authors focus the main analysis on a two-node tandem network, which they model as a discrete-time queueing system. they derive a functional equation relating the joint generating function of this system between two consecutive slots. the functional equation is then transformed into a suitable form, which enables the derivation of the steady-state joint generating function of the contents of the queues. from this, any moment of the queue length at each node can be extracted. they also give explicit expressions for the average time delay at each node as well as for the total average delay in the network. they illustrate the solution technique by some numerical examples.
adaptive load sharing for network processors. a novel scheme for processing packets in a router is presented that provides load sharing among multiple network processors distributed within the router. it is complemented by a feedback control mechanism designed to prevent processor overload. incoming traffic is scheduled to multiple processors based on a deterministic mapping. the mapping formula is derived from the robust hash routing (also known as the highest random weight--hrw) scheme, introduced in k. w. ross, ieee network, 11(6), 1997, and d. g. thaler et al., ieee trans. networking, 6(1), 1998. no state information on individual flow mapping has to be stored, but for each packet, a mapping function is computed over an identifier vector, a predefined set of fields in the packet. an adaptive extension to the hrw scheme is provided to cope with biased traffic patterns. we prove that our adaptation possesses the minimal disruption property with respect to the mapping and exploit that property to minimize the probability of flow reordering. simulation results indicate that the scheme achieves significant improvements in processor utilization. a higher number of router interfaces can thus be supported with the same amount of processing power.
smart retransmission: performance with overload and random losses. feedback flow control, in conjunction with limited buffering in the network, inevitably leads to packet loss. effective congestion control requires not only effective flow control but also a good retransmission strategy. we present a new retransmission strategy called smart that combines the best features of the traditional go-back-n and selective-retransmit strategies.we show, first, that go-back-n retransmission with static window flow control leads to congestion collapse when the nominal load exceeds the link capacity. second, we can avert congestion collapse by replacing go-back-n with smart retransmission, even with static window flow control. third, smart retransmission, when combined with packet-pair rate-based flow control, performs extremely well, both when losses are due to buffer overflows and when losses are random.
distributing layered encoded video through caches. the efficient distribution of stored information has become a major concern in the internet which has increasingly become a vehicle for the transport of stored video. because of the highly heterogeneous access to the internet, researchers and engineers have argued for layered encoded video. in this paper, we investigate delivering layered encoded video using caches. based on the stochastic knapsack theory, we develop a model for the layered video caching problem. we propose heuristics to determine which videos and which layers in the videos should be cached in order to maximize the revenue from the streaming service. we evaluate the performance of our heuristics through extensive numerical experiments. we find that, for typical scenarios, the revenue increases nearly logarithmically with the cache size and linearly with the link bandwidth that connects the cache to the origin servers. we also consider service models with request queuing and negotiations about the delivered stream quality and find that both extensions provide only small revenue increases.
on guaranteed smooth scheduling for input-queued switches. input-queued switches are used extensively in the design of high-speed routers. as switch speeds and sizes increase, the design of the switch scheduler becomes a primary challenge, because the time interval for the matching computations needed for determining switch configurations becomes very small. possible alternatives in scheduler design include increasing the scheduling interval by using envelopes [19], and using a frame-based scheduler that guarantees fixed rates between input-output pairs. however, both these alternatives have significant jitter drawbacks: the jitter increases with the envelope size in the first alternative, and previously-known methods do not guarantee tight jitter bounds in the second.in this paper, we propose a hybrid approach to switch scheduling. traffic with tight jitter constraints is first scheduled using a frame-based scheduler that achieves low jitter bounds. jitter-insensitive traffic is later scheduled using an envelope-based scheduler. the main contribution of this paper is a scheduler design for generating low-jitter schedules. the scheduler uses a rate matrix decomposition designed for low jitter and different from the minimum-bandwidth birkhoff-von neumann (bv) decomposition. in addition to generating low-jitter schedules, this decomposition in the worst case yields fewer switch configuration matrices (o(n)) than the bv decomposition (o(n2)), and so requires far less high-speed switch memory. we develop an efficient algorithm for decomposing the rate matrix and for scheduling the permutation matrices. we prove that our low-jitter algorithm has an o(logn) factor bound on its bandwidth consumption in comparison to the minimum-bandwidth bv decomposition. experimentally, we find that the bandwidth increase in practice is much lower than the theoretical bound. we also prove several related performance bounds for our scheduler. finally, we propose a practical algorithm for bandwidth-guaranteed algorithm, and show how our findings could even be extended to systems with large tuning time.
harmonic buffer management policy for shared memory switches. in this paper we consider shared-memory switches. we introduce a novel general nonpreemptive buffer management scheme, which considers the queues ordered by their size. we propose a new scheduling policy, based on our general scheme, which we call the harmonic policy. we analyze the performance of the harmonic policy by means of competitive analysis and demonstrate that its throughput competitive ratio is at most ln(n) + 2, where n is the number of output ports. we also present a lower bound of ω(log n/log log n) on the performance of any online deterministic policy. our simulations also show that the harmonic policy achieves high throughput and easily adapts to changing load conditions.
performance evaluation of packet data services over cellular voice networks. in this paper we develop a markov chain modeling framework for throughput/delay analysis of data services over cellular voice networks, using dynamic channel stealing method. some effective approximation techniques are also proposed and verified for simplification of modeling analysis. our study identifies the average voice call holding time as the dominant factor to affect data delay performance. especially in heavy load conditions, namely when the number of free voice channels becomes momentarily less, the data users will experience large network access delay in the range of several minutes or longer on average. we also examine the data performance improvement by using priority data access scheme and speech silence detection technique.
traffic characterization and switch utilization using a deterministic bounding interval dependent traffic model. compressed digital video is one of the most important types of traffic in future integrated services networks. it is difficult to support this class of traffic since, on one hand, compressed video is bursty, while on the other hand, it requires performance guarantees from the network. the common belief is that we are unlikely to achieve a high network utilization while providing performance guarantees to such bursty sources. the authors introduce a new deterministic bounding interval-dependent (d-bind) traffic model, together with tight analysis techniques, to explore the possibility of providing deterministic performance guarantees to vbr traffic while still achieving a reasonable network utilization. the d-bind model consists of a family of rate-interval pairs where the rate is a bounding rate over the interval length. the model captures the intuitive property that over longer interval lengths, a source may be bounded by a rate lower than its peak rate and closer to its long-term overage rate. while the d-bind model is a general deterministic model that can be used to characterize a wide variety of sources, the authors focus on mpeg-compressed video. using two 10 minute traces, they demonstrate the effectiveness of the new model and show that, contrary to common belief, reasonable network utilization can be achieved for compressed video, even when deterministic guarantees are provided.
a control theoretic approach to the design of closed loop rate based flow control for high speed atm networks. in this paper we present a control theoretic approach to the design of closed loop rate based flow control in high speed networks. the proposed control uses a dual proportional derivative controller, where the control parameters can be designed to ensure the stability of the control loop in a control theoretic sense, over a wide range of traffic patterns and propagation delays. we show how the control mechanism can be used to design a controller to support abr service based on feedback of explicit rates. we demonstrate the excellent transient and steady state performance of the controller through a number of examples.
multicasting for multimedia applications. the authors investigate multicast routing for high-bandwidth delay-sensitive applications in a point-to-point network as an optimization problem. they associate an edge cost and an edge delay with each edge in the network. the problem is to construct a tree spanning the destination nodes, such that it has the least cost, and so that the delay on the path from the source to each destination is bounded. since the problem is computationally intractable, the authors present an efficient approximation algorithm. experimental results through simulations show that the performance of the heuristic is near optimal
efficient analysis of polling systems. a large variety of computer communications systems, in particular the token ring network, are modeled and analyzed as polling systems. the authors present the descendant set approach as a general efficient algorithm for deriving all moments of packet delay (in particular, mean delay) in these systems. the method can apply to a very large variety of model variations including: the exhaustive, gated, and fractional service policies; the cyclic visit order; arbitrary periodic visit orders, (polling tables); random polling orders; and customer routing. for most variations the method significantly outperforms the algorithms commonly used
the designer's perspective to noncooperative networks. a noncooperative network is considered, in which each user routes its flow in a way that optimizes its individual performance objective. nash equilibria characterize the operating points of the network. the network designer aims to allocate link capacities, so that the resulting nash equilibria are efficient, according to some system-wide performance criterion. in a noncooperative setting, the solution of such design problems is, in general, complex and at times counterintuitive, since adding link capacity might lead to degradation of user performance. for systems of parallel links, it is shown that such paradoxes do not occur and that the capacity allocation problem has a simple and intuitive optimal solution, that coincides with the solution in the single-user case. extensions to general network topologies are also derived.
on wavelength translation in all-optical networks. in this paper we study the benefits of wavelength translation in all-optical networks providing clear channel circuit-switching among users. we first establish approximate analytical models for a static-routing circuit-switched network with an arbitrary topology, both with and without wavelength translation. we then study performance of the non-blocking centralized switch, the mesh-torus network and the ring network, using the analytical models and simulation results. it is shown that the analytical models match the simulation results very well in the case of the centralized switch and the mesh network. the results of our study also show that the benefits of wavelength translation are marginal for the centralized switch and the ring network. on the other hand, the results show that wavelength translation can significantly improve performance of a large mesh network.
approximate analysis of the end-to-end delay in atm networks. a very general approach for an approximate analysis of end-to-end delay jitter in asynchronous transfer mode (atm) networks for bursty input traffic is presented. since the cell loss requirements within atm networks are very restrictive, interest is in the tail of the complementary probability distribution function of the end-to-end delay to estimate the cell loss probability at the reassembly buffer. an analytical approach for an isolated network node as well as for a whole reference connection is presented. the approximation results are in good agreement with simulation results and indicate that the end-to-end delay jitter is in the range of the maximum transfer delay of one queuing node, if the bursty input traffic is controlled by adequate traffic control mechanisms
statistical characteristics and multiplexing of mpeg streams. this paper presents a study of the statistical characteristics and multiplexing of variable-bit-rate (vbr) mpeg-coded video streams. our results are based on 23 minutes of video obtained from the entertainment movie, the wizard of oz. the experimental setup which was used to capture, digitize, and compress the video stream is described. although the study is conducted at the frame level (as opposed to the slice level), it is observed that the inter-frame correlation structure for the frame-size sequence involves complicated forms of pseudo-periodicity that are mainly affected by the compression pattern of the sequence. a simple model for an mpeg traffic source is developed in which frames are generated according to the compression pattern of the original captured video stream. the number of cells per frame is fitted by a lognormal distribution. simulations are used to study the performance of an atm multiplexer for mpeg streams.
exploiting the temporal structure of mpeg video for the reduction of bandwidth requirements. we present a novel bandwidth allocation scheme for transporting variable-bit-rate mpeg traffic from a video server. using time-varying envelopes to characterize the traffic, this scheme achieves significant bandwidth gain, via statistical multiplexing, while supporting stringent, deterministic qos guarantees. the gain can be maximized by allowing the server to appropriately schedule the starting times of video sources, at the expense of some negligible startup delay. for homogeneous streams, we give the optimal schedule that results in the minimum allocated bandwidth. a suboptimal schedule is given in the heterogeneous case, which is shown to be asymptotically optimal. efficient online procedures for bandwidth computation are provided. numerical examples based on traces of mpeg-coded movies are used to demonstrate the benefits of our allocation strategy.
performance analysis of rate based feedback control for atm networks. closed-loop input rate regulation schemes have come to play an important role in the transport of the available bit rate (abr) traffic service category for atm. in this paper, we present a numerical approach to the performance study of a delayed feedback system with one congested node and multiple connections. this approach consists in modeling the feedback system as a finite quasi-birth-death (qbd) process. due to the peculiar block tri-diagonol nature of its generator, efficient techniques exist for its steady-state and transient solutions. using these techniques, we examine a simple parsimonious feedback system for issues such as throughput/loss performance, fairness and stability.our approach has the flexibility to study the effect of several additional factors such as asynchronous feedback, two-level control and explicit rate notification in the presence of underlying high-priority traffic. this study brings to light the trade-offs between system performance and the complexity of the feedback scheme. our study shows that the time scales of correlation of the feedback system have a dominant effect on its performance. these time scales are associated with the feedback delay, the durations of active/idle periods of traffic sources and the time scales of the underlying high-priority traffic. we also examine the effect of the time scales on the convergence time for the transient queueing system.
new insights from a fixed point analysis of single cell ieee 802.11 wlans. we study a fixed-point formalization of the well-known analysis of bianchi. we provide a significant simplification and generalization of the analysis. in this more general framework, the fixed-point solution and performance measures resulting from it are studied. uniqueness of the fixed point is established. simple and general throughput formulas are provided. it is shown that the throughput of any flow will be bounded by the one with the smallest transmission rate. the aggregate throughput is bounded by the reciprocal of the harmonic mean of the transmission rates. in an asymptotic regime with a large number of nodes, explicit formulas for the collision probability, the aggregate attempt rate, and the aggregate throughput are provided. the results from the analysis are compared with ns2 simulations and also with an exact markov model of the backoff process. it is shown how the saturated network analysis can be used to obtain tcp transfer throughputs in some cases.
an access protection solution for heavy load unfairness in dqdb. the authors discuss the unfairness issue arising in a 802.6 distributed queue dual bus (dqdb) network at heavy loads. based on the 802.6 protocol, the end-nodes along a bus experience longer delays than the other nodes. the origin and remedy for this heavy load unfairness problem are discussed. an access control scheme is proposed as a solution. a comparison of the proposed scheme with the 802.6 protocol is presented. the simulation results and performance characteristics are discussed under several types of loads. with symmetric load conditions under the proposed scheme, all active nodes along a bus experience almost the same access delay and packet loss characteristics. the performance under several other load conditions was also found to be satisfactory
fairness by demand and service pattern match: the alpha tuning mechanism for dqdb mans. this paper proposes a dynamic bandwidth control scheme for the distributed queue dual bus (dqdb) networks. the heavy load unfairness is effectively addressed. the match of demand and service patterns is achieved at fairly uniform delays and success rates of transmission at every node. using a tunable parameter (/spl alpha/), the proposed scheme perceives the presence of several fictitious nodes at the end of the bus and applies access protection. analysis and simulation studies for three standard load patterns, viz., symmetric, asymmetric and equal probability loads, show that it outperforms the bandwidth balancing mechanism.
performance and fluid simulations of a novel shared buffer management system. we consider a switching system that has multiple ports that share a common buffer, in which there is a fifo logical queue for each port. each port may support a large number of flows or connections, which are approximately homogeneous in their statistical characteristics, with common qos requirements in cell loss and maximum delay. heterogeneity may exist across ports. our first contribution is a buffer management scheme based on buffer admission control, which is integrated with connection admission control at the switch. at the same time, this scheme is fair, efficient, and robust in sharing the buffer resources across ports. our scheme is based on the resource-sharing technique of virtual partitioning. our second major contribution is to advance the practice of discrete-event fluid simulations. such simulations are approximations to cell-level simulations and offer orders of magnitude speed-up. a third contribution of the paper is the formulation and solution of a problem of optimal allocation of bandwidth and buffers to each port having specific delay bounds, in a lossless multiplexing framework. finally, we report on extensive simulation results. the scheme is found to be effective, efficient, and robust.
uplink scheduling in cdma packet-data systems. uplink scheduling in wireless systems is gaining importance due to arising uplink intensive data services (ftp, image uploads etc.), which could be hampered by the currently in-built asymmetry in favor of the downlink. in this work, we propose and study algorithms for efficient uplink packet-data scheduling in a cdma cell. the algorithms attempt to maximize system throughput under transmit power limitations on the mobiles assuming instantaneous knowledge of user queues and channels. however no channel statistics or traffic characterization is necessary. apart from increasing throughput, the algorithms also improve fairness of service among users, hence reducing chances of buffer overflows for poorly located users.the major observation arising from our analysis is that it is advantageous on the uplink to schedule "strong" users one-at-a-time, and "weak" users in larger groups. this contrasts with the downlink where one-at-a-time transmission for all users has shown to be the preferred mode in much previous work. based on the optimal schedules, we propose less complex and more practical approximate methods, both of which offer significant performance improvement compared to one-at-a-time transmission, and the widely acclaimed proportional fair (pf) algorithm, in simulations. when queue content cannot be fed back, we propose a simple modification of pf, uplink pf (upf), that offers similar improvement.
receiver-oriented adaptive buffer allocation in credit-based flow control for atm networks. in credit-based flow control for atm networks, a buffer is first allocated to each vc (virtual circuit) and then credit control is applied to the vc for avoiding possible buffer overflow. receiver-oriented, adaptive buffer allocation allows a receiver to allocate its buffer dynamically, to vcs from multiple upstream nodes based on their bandwidth usage. the paper describes, in detail, such an adaptive algorithm capable of supporting a wide range of link speeds and propagation delays, and also packing multiple allocation and credit records in a single message. analysis and simulation results show that even under highly bursty traffic, the adaptive scheme guarantees no cell loss due to congestion, and achieves excellent performance in utilization, fairness, ramp-up and packing, while requiring only relatively small node memory and bandwidth overhead. the required memory need only be 4*rtt+2*n, where rtt is the link round-trip time in cell cycles and n is the number of vcs.
client-server performance on flow-controlled atm networks: a web database of simulation results. extensive simulation has demonstrated the effectiveness of credit-based atm flow control in supporting client-server applications. in particular, request/response protocols used in these applications allow efficient sharing of switch buffer, for the case when all the vcs sharing the same buffer are subject to the same degree of downstream congestion. the required buffer size can be as small as the minimum of bandwidth*rtt for the link and #clients*reply_size. request/response protocols generally tolerate congestion better than greedy loads. being able to avoid synchronization, fifo scheduling is sometimes more efficient than vc round-robin scheduling. these findings are derived from an online web database of simulation results covering more than 10,000 network and load configurations. the web database approach has proven to be effective in managing and navigating a large set of simulation results.
end-to-end congestion control schemes: utility functions, random losses and ecn marks. we present a framework for designing end-to-end congestion control schemes in a network where each user may have a different utility function and may experience noncongestion-related losses. we first show that there exists an additive-increase-multiplicative-decrease scheme using only end-to-end measurable losses such that a socially optimal solution can be reached. we incorporate round-trip delay in this model, and show that one can generalize observations regarding tcp-type congestion avoidance to more general window flow control schemes. we then consider explicit congestion notification (ecn) as an alternate mechanism (instead of losses) for signaling congestion and show that ecn marking levels can be designed to nearly eliminate losses in the network by choosing the marking level independently for each node in the network. while the ecn marking level at each node may depend on the number of flows through the node, the appropriate marking level can be estimated using only aggregate flow measurements, i.e., per-flow measurements are not required.
reliable multicast in multi-access wireless lans. multicast is an efficient paradigm for transmitting data from a sender to a group of receivers. in this paper, we focus on multicast in single channel multi-access wireless local area networks (lans) comprising several small cells. in such a system, a receiver cannot correctly receive a packet if two or more packets are sent to it at the same time, because the ackets "collide". therefore, one has to ensure that only one node sends at a time. we look at two important issues.first, we consider the problem of the sender acquiring the multi-access channel for multicast transmission. second, for reliable multicast in each cell of the wireless lan, we examine arq-based approaches. the second issue is important because the wireless link error rates can be very high. we present a new approach to overcome the problem of feedback collision in single channel multi-access wireless lans, both for the purpose of acquiring the channel and for reliability. our approach involves the election of one of the multicast group members (receivers) as a "leader" or representative for the purpose of sending feedback to the sender. for reliable multicast, on erroneous reception of a packet, the leader does not send an acknowledgment, prompting a retransmission. on erroneous reception of the packet at receivers other than the leader, our protocol allows negative acknowledgments from these receivers to collide with the acknowledgment from the leader,thus destroying the acknowledgment and prompting the sender to retransmit the packet. using analytical models, we demonstrate that the leader-based protocol exhibits higher throughput in comparison to two other protocols which use traditional delayed feedback-based probabilistic methods. last, we present a simple scheme for leader election.
bounds and approximations for the periodic on/off queue with applications to atm traffic control. the authors consider statistical multiplexing of on/off sources in an asynchronous transfer mode (atm) network and its implications on traffic control. the periodic on/off source is used as a worst case output from the traffic enforcement algorithm, and the queue receiving information from a number of independent periodic on/off sources is studied with simulation results and analytical methods. the decomposition of the queuing process into a cell scale and a burst scale component is illustrated. a comparison with the exponentially distributed on/off queue is carried out, and a simple and versatile approximation is provided on which an admission control scheme based on peak, mean and burst duration can be based. some implications on buffer dimensioning and traffic control are discussed
an adaptable and reliable authentication protocol for communication networks. in this paper, we propose a new authentication and key distribution protocol which is adaptable and reliable for communication networks. the secrets for authentication, which are chosen from a relatively small space by common users, are easy to guess. our protocol gives a solution to protect the weak secrets from guessing attacks.compared with other related work, our protocol is more reliable because it is resistant to various kinds of attacks including guessing attacks, and more adaptable because it reduces several overheads which make the existing protocols more expensive. we show how to apply our protocol to the q.931 calling sequences and to the world wide web model.
performance impact of partial reconfigurability in lightwave networks. rearrangeable multihop lightwave networks can be dynamically reconfigured to adapt the connectivity among network stations to prevailing traffic conditions. most of the literature has analyzed the performance of such networks assuming no limitations on the range of tunability of the transmitters and/or receivers allocated to each network station. therefore, all connection diagrams could be realized among network stations, within the constraints of the number of transmitters and receivers at each station. since the number of wavelengths in use may be very large, a practical implementation would restrict the tunability range of each transmitter and receiver to some limited set of contiguous wavelengths, or waveband. however, there is a penalty associated with such restrictions in that all connection diagrams might not be achievable and the network performances could degrade. the author derives lower bounds on the performance degradation experienced by the network when there are tunability limitations. he then proposes and analyzes a waveband assignment and grouping scheme, illustrating that one can design networks with good performance even though there are tunability constraints on the transceivers. he also describes other architectures (multi-fiber physical topology, subcarrier division multiplexing) for which the model and analysis readily apply.
reconfiguration algorithms for rearrangeable lightwave networks. the authors propose a minimally disruptive approach that transitions the network through a sequence of branch exchange operations, so that only two links are disrupted at any given time. it is shown that the problem of finding the shortest sequence, so as to minimize the duration of the reconfiguration phase, is equivalent to the problem of finding a decomposition of an auxiliary graph into the largest number of vertex-disjoint cycles. the authors then propose and compare three different polynomial-time greedy algorithms, on the basis of performance and time complexity. noticing that the length of a sequence increases at most linearly with the size of the network, the authors derived the average rate of growth from simulation results
a generalization of some policing mechanisms. the authors highlight the fact that most of the policing schemes proposed in the literature neglect important information on the past cell blocking behavior of the policing mechanism. they propose a modification of these schemes in which the discarded cell information is used, with almost no overhead compared to the usual strategies. the behavior of the modified policing mechanisms is discussed. this new behavior is illustrated by using the generalized leaky bucket to police the mean rate of a source. analysis using an on/off input process shows that the modified versions detect smaller-magnitude abuses, police the sources closer to their declared resources utilization, and have a faster response time. results are presented showing that the generalized sliding window exhibits the same kind of behavior
a framework for statistical multiplexing onto a variable-bit rate output channel. this paper investigates soft multiplexing, an issue that arises in vp-based atm networks. the main distinguishing feature of this form of multiplexing (as opposed to traditional statistical multiplexing) is that the output channel is a variable-bit rate vp. the concepts of work conservation and greediness were introduced to study soft multiplexing systematically. we assume that the overall multiplexed output traffic is regulated and policed by a leaky bucket. before being allowed to access the output channel, each input traffic stream is also controlled by a leaky bucket. it is shown that although strict performance guarantee can be provided to each input traffic stream by independent leaky bucket operation, output-channel utilization can be rather low, and it can be improved significantly if we allow some interactions among the leaky buckets of the input streams. in particular, we show that two simple soft-multiplexing schemes, excess token passing and token borrowing, can achieve higher output-channel utilization, better delay and loss performance without sacrificing guarantee to each session.
transporting compressed video over atm networks with explicit rate feedback control. we propose a scheme for transmission of variable-bit-rate compressed video over atm networks using the explicit-rate congestion control mechanisms proposed for the available bit rate (abr) service. compressed video is inherently bursty with rate fluctuations over both short and long time scales. we feel that this source behavior can naturally take advantage of the abr service, since the abr explicit-rate schemes allow sources to request varying amounts of bandwidth over time, while reserving a minimum for the entire duration of the connection. moreover when the bandwidth demand cannot be met, the network provides feedback indicating the bandwidth currently available to a connection. this information can be used to match the video source rate to the available bandwidth by modifying the quantization level used during compression. we use trace driven simulations to examine how effective the enhanced explicit rate scheme is in "rate matching" between the network and the source and the effect on end-end delay. we also look at the sensitivity of the proposed scheme to the estimates of the network round-trip times and to inaccuracies in the rate requests made by sources.
burst scheduling: architecture and algorithm for switching packet video. the authors observed that variable bit rate (vbr) video, which is a sequence of encoded pictures, has very large rate fluctuations from picture to picture. in designing a new traffic model, the authors retain the basic notion of a flow but allow the flow rate to fluctuate. in particular, they introduce the concept of a burst which, in a video flow, is a sequence of packets that carry the bits of an encoded picture. they present the architecture of a class of packet switching networks, called burst scheduling networks, for carrying video, audio, and data traffic. the class is characterized by (i) use of virtual clock value as priority in scheduling, (ii) end-to-end delay and delay jitter guarantees provided to flows conforming to the new traffic model, and (iii) traffic flows (in particular, video flows) scheduled efficiently in bursts. some experimental results are presented from a discrete-event simulation in which traces from several mpeg video sequences were used as video sources.
traffic shaping of a tagged stream in an atm network: approximate end-to-end analysis. traffic streams-originally shaped to comply with desired traffic descriptors-may suffer substantial distortion within an atm network due to statistical multiplexing. as a consequence, traffic re-shaping within the network may be necessary. in this work the modification of a tagged traffic stream due to a series of multiplexing operations is studied. the standard fcfs service policy, as well as a peak-rate enforcing multiplexing discipline, are considered. tagged cell delay, jitter and inter-departure processes are considered for the characterization of the tagged traffic stream.
analysis of packet discarding policies in high-speed networks. in this work, selective discarding policies, as a means for congestion avoidance, are studied and compared to non-discarding policies. the partial message discard policy discards packets of tails of corrupted messages. an improvement to this policy is the early message discard that drops entire messages and not just message-tails.a common performance measure of network elements is the effective throughput which measures the utilization of the network links but which neglects the application altogether. we adopt a new performance measure, goodput, which reflects the utilization of the network from the application's point of view and thus better describes network behavior.we develop and analyze a model for systems which employ discarding policies. the analysis shows a remarkable performance improvement when any message-based discarding policy is applied, and that the early message discard policy performs better, especially under high loads. we compute the optimal parameter setting for maximum goodput at different input loads and investigate the performance sensitivity to these parameters.
multicast and self-routing in atm radix trees and banyan networks. considers methods that perform all point-to-multipoint permutations in atm radix tree and banyan networks. the authors investigate the relationship between the structure of the routing tab and the ease of performing multicasting. they first consider a simple explicit addressing scheme that requires (n-1)(log/sub 2/n+1) routing bits. they then present an addressing filtering scheme that requires n routing bits. next they propose a new method, the vertex isolation addressing (via) scheme, which requires r(n-1)/(r-1) bits for radix-r tree networks. thus for binary trees the routing tab i 2(n-1) bits long and as r approaches n the routing tab approaches n bits. the authors demonstrate that the "excess" bits in the via routing tab provide certain error detection capabilities. encoding and decoding algorithms and hardware implementations for the via method are presented. modified via schemes are then investigated for large tree networks. finally the authors show that the via scheme and its modifications are applicable to banyan networks.
virtual path bandwidth allocation in multi-user networks. considers a multi-user network that is shared by noncooperative users. each user sets up virtual paths that optimize its own, selfish, performance measure. this measure accounts for both the guaranteed call level quality of service, as well as for the cost incurred for reserving the resource. the interaction between the user strategies is formalized as a game. the authors show that this game has a unique nash equilibrium, and that it possesses a certain fairness property. they investigate the dynamics of this game, and prove convergence to the nash equilibrium of both a gauss-seidel scheme and a jacobi scheme. they extend their study to various general network topologies.
bandwidth quantization in the broadband isdn. the authors indicate that the number of rates supportable in an asynchronous transfer mode (atm) broadband network has to be limited unless a network is acceptable without knowing its grade of service. the quantization of the channel bandwidth, given the traffic arrival rate as a function of requested bandwidth, is considered. capacity sharing models in atm networks are presented. the calculation procedure for blocking probability which will be affected by the quantization problem is described. a class of control methods that can render a product-form solution is introduced. the results indicate that there is little performance difference between a quantized channel and a continuous-rate channel as the level of quantization exceeds ten
a generalized non-preemptive priority queue. in this paper, we analyze a generalized non-preemptive queue with two priority classes. when the server serves the low priority queue, up to l customers are served before the server returns to the high priority queue. we study the embedded markov chain at departure epochs and obtain the transforms of the queue-length and sojourn-time distributions. from these transforms, it is easy to find the moments.
fault tolerance of banyan using multiple-pass. in order to utilize multiple-pass routing schemes, a faulty banyan network must possess the dynamic full access (dfa) property. the authors determine a necessary and sufficient condition for a banyan network to possess the dfa property and design a general testing procedure based on the condition. they also enumerate the probability that a banyan network loses the dfa property, given the number of faulty switch elements. it is found that, as long as faults do not occur in switch elements located in the first and last stages, this probability is very small even when there are quite a few faulty switch elements. therefore, multiple-pass routing schemes can be very useful if the switch elements in the first and last stages are well protected
a fair high-speed copy network for multicast packet switch. a fair high-speed copy network for multicast packet switching is described. the authors modify the architecture of the copy network proposed by t.t. lee (1988) to make it fair to all the inlets, and reduce the clock rate requirement of the switching fabric. fairness is achieved by adding a banyan network to perform cyclic shifts in front of the copy network. a pipelined architecture is proposed to avoid a huge internal speed-up. the clock rate requirement of the proposed copy network is evaluated and compared with that of the original design. it is found that the clock rate requirement can be reduced significantly if the number of inlets is larger than 64
optimization of a wdm optical packet switch with wavelength converters. this paper investigates a wavelength-division-multiplexed optical packet switch with wavelength converters which can shift optical packets to any wavelength of their destined outbound links. wavelength conversion can reduce packet dropping probability due to wavelength contentions. however, not all the packets need conversion, and hence conversion should be optimized to reduce the number of converters and improve the quality of signals by reducing unnecessary conversion. we derive the maximum number of conversions in a packet switch with l inbound/outbound links and w wavelengths per link and develop a switch control algorithm to minimize the number of wavelength conversions while maintaining the same minimum number of dropped packets. simulation results show that the packet dropping probability decreases significantly with wavelength conversion and that fewer converters than the maximum number of conversions are needed.
characterization of statistical multiplexing of heterogeneous atm sources. two asymptotic analyses of the queue length distribution at a statistical multiplexer supporting heterogeneous exponential on-off sources are considered. the first analysis is performed by approximating the cell generation rate as a multidimensional ornstein-uhlenbeck process and then applying the benes queueing formula. in the second analysis, we start with a system of linear equations derived from the exact expressions of the dominant eigenvalue of the matrix governing the queue length distribution. assuming that there are a large number of sources, we obtain asymptotic approximations to the dominant eigenvalue. based on the analyses, we define a traffic descriptor to include the mean and the variance of the cell generation rate and a burstiness measure. a simple expression for the quality of service (qos) in cell loss rate is derived in terms of the traffic descriptor parameters and the multiplexer parameters (output link capacity and buffer size). this result is then used to quantify the factors determining the required capacity of a call taking the statistical multiplexing gain into consideration.
performance and correctness of the atm abr rate control scheme. we study both the correctness and performance of the source/destination protocol of the available bit rate (abr) service in asynchronous transfer mode (atm) networks. although the basic source/destination protocol for congestion management is relatively simple, the protocol specification has to cope with several "real-world" cases such as failures and delayed/lost feedback which may introduce complexity. rigorous proofs of the correct functioning of the protocol based on a formal specification is necessary. we use a formal extended finite state machine (efsm) model to show that the abr source/destination protocol is free of live-locks, so that under all conditions both resource management (rm) and data cells will be transmitted. we also show that the network options of explicit forward congestion indication (efci) and explicit rate (er) interoperate correctly. we use the understanding of the informal english description of the source/destination behavior and of our efsm model to derive conditions that ensure that the source transmission rate is stable in the presence of delayed or lost feedback rm cells, especially under the operation of a source rule that requires the reduction of the source rate under these conditions. we arrive at bounds on the number of consecutive rm cell losses tolerated while the rate remains stable. we also provide a worst-case analysis of the delay in turning around rm cells at the destination station and the worst-case inter-departure time of forward rm cells from the source.
matching output queueing with a multiple input/output-queued switch. we have previously proposed an efficient switch architecture called multiple input/output-queued (mioq) switch and showed that the mioq switch can match the performance of an output-queued switch statistically. in this paper, we prove theoretically that the mioq switch can match the output queueing exactly, not statistically, with no speedup of any component. more specifically, we show that the mioq switch with two parallel switches (which we call a parallel mioq (pmioq) switch in this paper) can provide exact emulation of an output-queued switch with a broad class of service scheduling algorithms including fifo, weighted fair queueing (wfq) and strict priority queueing regardless of incoming traffic pattern and switch size.to do that, we first propose the stable strategic alliance (ssa) algorithm that can produce a stable many-to-many assignment, and prove its finite, stable and deterministic properties. next, we apply the ssa algorithm to the scheduling of a pmioq switch with two parallel switches, and show that the stability condition of the ssa algorithm guarantees for the pmioq switch to emulate an output-queued switch exactly. to avoid possible conflicts in a parallel switch, each input-output pair matched by the ssa algorithm must be mapped to one of two crossbar switches. for this mapping, we also propose a simple algorithm that requires at most 2n steps for all matched input-output pairs. in addition, to relieve the implementation burden of n input buffers being accessed simultaneously, we propose a buffering scheme called redundant buffering which requires two memory devices instead of n physically-separate memories. in conclusion, we demonstrate that the mioq switch requires two crossbar switches in parallel and two physical memories at each input and output to emulate an output-queued switch with no speedup of any component.
an asymptotic analysis of a threshold load balancing policy. this paper describes and analyzes a specific threshold load balancing policy in a distributed computer system that executes a priority scheduling on jobs according to the location of job origination. an approximate analysis is carried out to obtain the response time performance of the system under the load balancing policy. in the analysis we assume that the arrival of jobs at a node transferred from other nodes are governed by a p0isson process. this allows us to decompose the behavior of the system into separate models of each of the nodes. we then map the behavior of each node into the framework of queueing systems subject to breakdown to obtain a closed-form expression for the mean response time of a job. we prove that the poisson assumption on the job transfers is asymptotically exact and hence the performance predictions of the model is asymptotically exact as the number of nodes in the system increases. simulation studies reveal that the poisson job transfer assumption is good even for small systems when we are interested in obtaining the response time performance of the system.
bandwidth allocation policies for unicast and multicast flows. using multicast delivery to multiple receivers reduces the aggregate bandwidth required from the network compared to using unicast delivery to each receiver. however, multicast is not yet widely deployed in the internet. one reason is the lack of incentive to use multicast delivery. to encourage the use of multicast delivery, we define a new bandwidth-allocation policy, called logrd, taking into account the number of downstream receivers. this policy gives more bandwidth to a multicast flow as compared to a unicast flow that shares the same bottleneck, without starving the unicast flows, however. the logrd policy also provides an answer to the question on how to treat a multicast flow compared to a unicast flow sharing the same bottleneck. we investigate three bandwidth-allocation policies for multicast flows and evaluate their impact on both receiver satisfaction and fairness using a simple analytical study and a comprehensive set of simulations. the policy that allocates the available bandwidth as a logarithmic function of the number of receivers downstream of the bottleneck achieves the best tradeoff between receiver satisfaction and fairness.
an on-demand qos routing protocol for mobile ad hoc networks. we propose an on-demand bandwidth routing protocol for qos (quality of service) support in mobile ad hoc networks. the qos routing feature is important for a mobile network to interconnect wired networks with qos support (e.g., atm, internet, etc.). the qos routing protocol can also work in a stand-alone mobile ad hoc network for real-time applications. under such a routing protocol, the source (or the atm gateway) is informed of the bandwidth and qos available to any destination in the mobile network. this knowledge enables the establishment of qos connections within the mobile network and the efficient support of real time applications. in addition, it enables more efficient call admission control. in case of atm interconnection, the bandwidth information can be used to carry out intelligent handoff between atm gateways and/or to extend the atm virtual circuit service to the mobile network with possible renegotiation of qos parameters at the gateway. simulation results suggest distinct performance advantages of our protocol calculating the bandwidth information. it is particularly useful in call admission control. furthermore, ''on-demand'' routing enhances the performance in the mobile environment because the source can keep more connectivity to a receiver in the path-finding duration. simulation experiments show this improvement.
queue response to input correlation functions: discrete spectral analysis. a new concept of spectral characterization of the wideband input process in high-speed networks is examined. the eigenstructure technique, through the modeling of input markov chains, helps localize wideband sources in a subspace, especially in a low frequency band. simple periodic chains are used for the construction of the input rate process. the input power spectral distribution is defined in a discrete frequency domain. each input traffic stream is characterized by an independent markov modulated poisson process (mmpp). the underlying markov chain is used to reflect the time autocorrelation properties of the input process at a macro level. expressions are derived for correlation and power spectral functions of the mmpp input. a queuing analysis with multiple periodic input functions is described. the queue response to input correlation functions is examined. the advantages of using the spectral domain to analyze and design network control and resource management are discussed
constant-time dynamic atm bandwidth scheduling for guaranteed and best effort services with overbooking. in this paper, we present an analysis of an existing rate-based abr scheduling algorithm described in [1], and propose an enhanced rate-based round robin (rbr) scheduling algorithm for atm switches and end systems. one of the novel aspects of rbr is that the scheduler supports available bit rate (abr) traffic as well as guaranteed bandwidth reservations. in addition, bandwidth overbooking is allowed by the scheduler for abr services to improve link efficiency as recommended by most flow control schemes. under competition, the scheduler distributes the bandwidth in a max-min fair way. any unused reservations for guaranteed services are reallocated to abr services. finally, the operations performed during each scheduling cycle are constant, independent of the number of connections. simulation results are also presented and analyzed.
effects of erlang call holding times on pcs call completion. previous performance studies of pcs channel allocation assumed that call holding times have an exponential distribution. the exponential call holding time assumption is justified for existing cellular systems, where wireless calls are charged based on the length of the call holding time. future pcs systems may exercise flat rate billing, and consequently a more general distribution is desirable to model the call holding times. this paper models the call holding times by the erlang distribution (a generalization of the exponential distribution) to investigate the effect of the variance of the call holding times on the call completion probability. our analysis indicates that the call completion probability decreases as the variance of the call holding times decreases. this effect becomes more pronounced as the variance of the cell residence times decreases.
the split and merge (sam) protocol for interactive video-on-demand systems. a true video-on-demand (vod) system provides the ultimate flexibility in video services by allowing users to select any video programs, at any time, and to perform any vcr-like user interactions. to allow true vod, one approach is to have a dedicated video stream for each customer. this is expensive, especially when multiple identical video streams are sent to multiple customers accessing the same video. to be commercially viable, vod service must be priced competitively with existing video rental services. batching may be used to reduce this cost. it allows multiple users accessing the same video to share the same video stream. the batching approach, however, complicates the provision of user interactions. existing batching schemes only allow near vod services. this paper describes a new protocol, called split and merge (sam), which offers true vod services while allowing multiple users to share the same video stream. this sharing is transparent to the users and it appears as if each has a dedicated video stream. our approach is to split an interactive user from the batch and to serve him with a dedicated video stream. we develop an innovative way to merge these individuals back to the batching streams when they resume normal play mode. the sam protocol therefore significantly improves the system resource utilization and the number of simultaneous users, and more importantly, allows true vod services.
multiple priority csma-type mulitchannel local area network. in this paper, we will introduce a new network access protocol for csma-type multichannel local area network (mlan). this new protocol has the capability of providing different network access priority among the various applications. from the earlier research, it has been shown that the csma-type mlan is superior to a single channel on the equal network bandwidth. on the basis of the developed mlan architecture, we construct a new network access protocol to provide multiple transmission priorities for various applications, e.q., text, voice, video, image, etc. this protocol is called multiple-priority multichannel local area network (mp-mlan). the data transmission of mp-mlan is collision-free, and we can find the throughput characteristics of mp-mlan are higher and more stable than the conventional csma/cd or multichannel csma/cd network from the analysis results. a queueing analysis model for representing the mp-mlan protocol is established, and simulation results are also provided to evaluate the performance of this network.
optimal sliding-window strategies in networks with long round-trip delays. a method commonly used for packet flow control over connections with long round-trip delays is "sliding windows". in general, for a given loss rate, a larger window size achieves a higher average throughput, but also a higher rate of spurious packet transmissions, rejected by the receiver merely for arriving out-of-order. this paper analyzes the problem of optimal flow control quantitatively, for a connection that has a cost per unit time and a cost for every transmitted packet. the optimal strategy is defined as one that minimizes the expected cost/throughput ratio, and is allowed to transmit several copies of a packet within a window. we present an algorithm for computing the optimal strategy and study its properties; in particular, we derive bounds on the optimal strategy cost/throughput performance, and show that it increases merely logarithmically with the time price, whereas the cost/throughput of the 'traditional' classic window scheme is linear in the time price.
maximizing throughput for optical burst switching networks. in optical burst switching (obs) networks, a key problem is to schedule as many bursts as possible on wavelength channels so that the throughput is maximized and the burst loss is minimized. most of the current research on obs has been concentrated on reducing burst loss in an "average-case" sense, and little effort has been devoted to understanding the worst case performance. since obs itself is an open-loop control system, it may exhibit a worst case behavior when adversely synchronized. on the other hand, most commercial systems require an acceptable worst case performance. in this paper, we use competitive analysis to analyze the worst case performance of a large set of scheduling algorithms, called best-effort online scheduling algorithms, for obs networks and establish a number of interesting upper and lower bounds on the performance of such algorithms. our analysis shows that the performance of any best-effort online algorithm is closely related to a few factors, such as the range of offset time, maximum-to-minimum burst-length ratio, and the number of data channels. a surprising discovery is that the worst case performance of any best-effort online scheduling algorithm is primarily determined by the maximum-to-minimum burst-length ratio, followed by the range of offset time. furthermore, if all bursts have the same burst length and offset time, all best-effort online scheduling algorithms generate the same optimal solution, regardless of how different they may look. our analysis can also be extended to some non-best-effort online scheduling algorithms, such as the well-known horizon algorithm, and establish similar bounds. based on the analytic results, we give guidelines for several widely discussed obs problems, including burst assembly, offset time setting, and scheduling algorithm design, and propose a new channel reservation protocol called virtual fixed offset-time (vfo) to improve the worst case performance. our simulation shows that vfo can also reduce the average burst loss rate.
global clock synchronization in sensor networks. global synchronization is important for many sensor network applications that require precise mapping of collected sensor data with the time of the events, for example, in tracking and surveillance. it also plays an important role in energy conservation in mac layer protocols. this paper describes four methods to achieve global synchronization in a sensor network: a node-based approach, a hierarchical cluster-based method, a diffusion-based method, and a fault-tolerant diffusion-based method. the diffusion-based protocol is fully localized. we present two implementations of the diffusion-based protocol for synchronous and asynchronous systems and prove its convergence. finally, we show that, by imposing some constraints on the sensor network, global clock synchronization can be achieved in the presence of malicious nodes that exhibit byzantine failures.
atomic resource sharing in noncooperative networks. in noncooperative networks, resources are shared among selfish users, which optimize their individual performance measure. we consider the generic and practically important case of atomic resource sharing, in which traffic bifurcation is not implemented, hence each user allocates its whole traffic to one of the network resources. we analyze topologies of parallel resources within a game-theoretic framework and establish several fundamental properties. we prove the existence of and convergence to a nash equilibrium. for a broad class of residual capacity performance functions, an upper bound on the number of iterations till convergence is derived. an algorithm is presented for testing the uniqueness of the equilibrium. sufficient conditions for achieving a feasible equilibrium are obtained. we consider extensions to general network topologies. in particular, we show that, for a class of throughput-oriented cost functions, existence of and convergence to a nash equilibrium is guaranteed in all topologies. with these structural results at hand, we establish the foundations of a design and management methodology, that enables to operate such networks efficiently, in spite of the lack of cooperation among users and the restrictions imposed by atomic resource sharing.
stability in atm networks. in this paper, we address the issues of stability in atm networks. a network is stable if and only if all the packets have a bounded delay. we first consider atm networks with fcfs scheduling policy. we then study networks with priority driven scheduling policy. for each network, we develop criteria for testing the stability of an atm network and methods of deriving delay bounds in a stable network. in previous work, the cruz-gallager-parekh ring has been a ``benchmark" architecture to study the stability problem. for example, gallager and parekh claimed that the ring with size no more than four switches is stable when the total utilization of the links is less than 100%. we validated this result. furthermore, we find that a ring with large number of switches is stable if the total utilization of the links is less than or equal to 73\%.
asynchronous multimedia multihop wireless networks. personal communications and mobile computing will require a wireless network infrastructure which is fast deployable, possibly multihop, and capable of multimedia service support. the first infracture of this type was the packet radio network (prnet), developed in the 70's to address the battlefield and disaster recovery communication requirements. prnet was totally asynchronous and was based on a completely distributed architecture. it handled datagram traffic reasonably well, but did not offer efficient multimedia support. recently, under the wamis and glomo arpa programs several mobile, multimedia, multihop (m/sup 3/) wireless network architectures have been developed, which assume some form of synchronous, time division infrastructure. the synchronous time frame leads to efficient multimedia support implementations. however, it introduces more complexity and is less robust in the face of mobility and channel fading. in this paper; we examine the impact of synchronization on wireless m/sup 3/ network performance. first, we introduce maca/pr, an asynchronous network based on the collision avoidance mac scheme employed in the ieee 802.11 standard. there, we evaluate and compare several wireless packet networks ranging from the total asynchronous prnet to the synchronized cluster tdma network. we examine the tradeoffs between time synchronization and performance in various traffic and mobility environments.
channel carrying: a novel handoff scheme for mobile cellular networks. we present a new scheme that addresses the call handoff problem in mobile cellular networks. efficiently solving the handoff problem is important for guaranteeing quality of service (qos) to already admitted calls in the network. our scheme is based on a new concept called channel carrying: when a mobile user moves from one cell to another, under certain mobility conditions, the user is allowed to carry its current channel. we propose a new channel assignment scheme to ensure that this movement of channels will not lead to any extra co-channel interference or channel locking. in our scheme, the mobility of the channels relies entirely on localized information, and no global coordination is required. therefore, the scheme is simple and easy to implement. we further develop a hybrid channel carrying scheme that allows us to maximize the performance under various constraints. we provide numerical results comparing our scheme with the traditional channel reservation techniques. we find that our scheme outperforms the reservation scheme over a broad range of traffic parameters.
a service with bounded degradation in quality-of-service networks. many network applications that require quality-of-service (qos) support, such as transmission of digital voice and video, tolerate a certain level of service degradation. in this study, a novel network service, referred to as service with bounded degradation (bd service), is presented that can take advantage of the delay tolerance of applications. different from previous proposals for similar services, the bd service can guarantee hard lower bounds of the service degradation. this is achieved by strictly limiting the amount of traffic that is subject to service degradation. to implement a bd service, network traffic is partitioned into components with different delay requirements. policing of the traffic components is achieved by multi-level leaky buckets. a novel scheduler, referred to as edd-bd (earliest deadline due-bounded degradation) scheduler, performs switching of packets. properties of the edd-bd scheduler are presented and analyzed.
statistical per-flow service bounds in a network with aggregate provisioning. scalability concerns of qos implementations have stipulated service architectures where qos is not provisioned separately to each flow, but instead to aggregates of flows. this paper determines stochastic bounds for the service experienced by a single flow when resources are managed for aggregates of flows and when the scheduling algorithms used in the network are not known. using a recently developed statistical network calculus, per-flow bounds can be calculated for backlog, delay, and the burstiness of output traffic.
a general packet replication scheme for mutlicasting in interconnection networks. multicasting in broadband packet switches and metropolitan networks can be achieved by first replicating the packets and then routing them to their destinations. this paper studies a very simple but general replication scheme that can be applied to arbitrary interconnection-network topologies. the replication process of a packet adapts itself according to the network topology and the traffic condition. hot spots of replication activities are diffused by this scheme which automatically moves part of the replication efforts to less active network regions. the scheme can potentially be used in networks (e.g., the manhattan-street network) in which multicasting were thought to be inherently difficult. fundamental issues and critical problem areas are laid out, and solutions addressing them are proposed. the performance of the replication algorithm and its implementation (logic diagram level) in the shuffle-exchange copy network are investigated in detail. it is found that the performance of the algorithm improves with the increase of network dimensions.
analysis of an atm buffer with self-similar ("fractal") input traffic. as atm high-speed, cell-relay networks will most likely first make their impact as backbones interconnecting enterprise networks consisting of ethernet and other lans, their proper design and control is crucial. recent studies of high quality, high resolution traffic measurements in bellcore ethernets have revealed that this aggregate ethernet traffic is self-similar ("fractal") in nature, quite different in "burstiness" features from traffic considered and studied up to now. this paper presents an analytical study of an atm buffer driven with self-similar traffic. the probability of buffer occupancy is obtained. it is shown that this probability decreases with the buffer size not exponentially, as in traditionally markovian traffic models, but algebraically.
performance and complexity of multicast cross-path atm switches. a newly proposed large-scale atm switch called cross-path switch has been shown to be capable of handling unicast and multirate traffic efficiently. in this paper, we will study two replication approaches to enhance the switch to support multicast switching. the first approach replicates multicast cells at both input and output stages, while the second one replicates cells at the input stage only. a feasible configuration for each scheme is considered and the effect of multicast traffic on the switch performance in terms of throughput and cell loss probability is studied. we observed that, to achieve the same throughput and loss requirement, the second architecture may require fewer switching elements than the first one.
key to the success of asynchronous transfer mode: an application programming interface. asynchronous transfer mode (atm) networks are scalable via a wide variety of physical link speeds and can be run in both local and wide area. bandwidth reservation and quality of service guarantees make atm attractive to deliver multimedia information in real-time. existing protocol suites can be extended. however, they do not give access to those characteristics. therefore, applications demand an atm application programming interface (api) to take advantage of those features. this paper covers a special syntax mapping of the atm api services on top of x/open transport interface (xti) which is able to give applications access directly to the special quality and trafic services of an atm network. a particular realization of the api on xti environment is proposed and implemented on the macos networking platform. it provides a flexible and modular design of the atm networking. finally, the paper concludes with one atm-aware application (video on demand) which requires real-time streaming data.
an optimization based approach for qos routing in high-bandwidth networks. in this paper, we propose an optimization-based approach for quality of service (qos) routing in high-bandwidth networks. we view a network that employs qos routing as an entity that distributively optimizes some global utility function. by solving the optimization problem, the network is driven to an efficient operating point. in earlier work, it has been shown that when the capacity of the network is large, this optimization takes on a simple form, and once the solution to this optimization problem is found, simple proportional qos routing schemes will suffice. however, this optimization problem requires global information. we develop a distributed and adaptive algorithm that can efficiently solve the optimization online. compared with existing qos routing schemes, the proposed optimization-based approach has the following advantages: 1) the computation and communication overhead can be greatly reduced without sacrificing performance; 2) the operating characteristics of the network can be analytically studied; and 3) the desired operating point can be tuned by choosing appropriate utility functions.
pcup: pipelined cyclic upstream protocol over hybrid fiber coax. in order to span nii (national information infrastructure) into the homes, the community cable tv networks have to be re-engineered to support two-way interactive services. in this work, we propose pcup (pipelined cyclic upstream protocol) as the upstream mac (medium access control) protocol for hfc (hybrid fiber coax) community access network. pcup is designed with the intention of pipelining the upstream channel. this is achieved by proper station positioning, which measures the station propagation offset from the headend, and transmission scheduling, which assigns each station the transmission starting time and duration in a cycle. by taking into account the propagation offsets and the transmission times, transmitted cells can appear back-to-back, i.e. pipelined, at the headend. since only the active stations are scheduled to transmit in a cycle, a membership control mechanism, which runs a contention-based tree walk algorithm, is executed periodically to allow the stations to join or leave.
flexible storage placement of digital video media. in addition to the large data size requirement and real-time constraint in continuous media, future video applications such as video editing demands the flexible storage placement and the random access capability on the video-frame level. to offer efficient buffering schemes and flexible storage placement for supporting random access, we present two buffering schemes: the two-buffer scheme and the k-buffer compensation scheme. the two-buffer scheme requires only all the frames in a block to be stored consecutively while providing random access between blocks. however, this intuitive buffering scheme potentially requires a large block size and buffer space. the k-buffer compensation scheme is proposed to resolve this large buffer space requirement by using more than two buffers and requiring a minimal number of blocks randomly placed in each cylinder. experimental measurement results reveal the significant improvements on the buffer-size reduction and placement flexibility by using the k-buffer compensation scheme.
a study of networks simulation efficiency: fluid simulation vs. packet-level simulation. network performance evaluation through traditional packet-level simulation is becoming increasingly difficult as today''s networks grow in scale along many dimensions. as a consequence, fluid simulation has been proposed to cope with the size and complexity of such systems. this study focuses on analyzing and comparing the relative efficiencies of fluid simulation and packet-level simulation for several network scenarios. we use the ``simulation event'''' rate to measure the computational effort of the simulators and show that this measure is both adequate and accurate. for some scenarios, we derive analytical results for the simulation event rate and identify the major factors that contribute to the simulation event rate. among these factors, the ``ripple effect'''' is very important since it can significantly increase the fluid simulation event rate. for a tandem queueing system, we identify the boundary condition to establish regions where one simulation paradigm is more efficient than the other. flow aggregation is considered as a technique to reduce the impact of the ``ripple effect'''' in fluid simulation. we also show that wfq scheduling discipline can limit the ``ripple effect'''', making fluid simulation particularly well suited for wfq models. our results show that tradeoffs between parameters of a network model determines the most efficient simulation approach.
approximating optimal spare capacity allocation by successive survivable routing. the design of survivable mesh based communication networks has received considerable attention in recent years. one task is to route backup paths and allocate spare capacity in the network to guarantee seamless communications services survivable to a set of failure scenarios. this is a complex multi-constraint optimization problem, called the spare capacity allocation (sca) problem. this paper unravels the sca problem structure using a matrix-based model, and develops a fast and efficient approximation algorithm, termed successive survivable routing (ssr). first, per-flow spare capacity sharing is captured by a spare provision matrix (spm) method. the spm matrix has a dimension the number of failure scenarios by the number of links. it is used by each demand to route the backup path and share spare capacity with other backup paths. next, based on a special link metric calculated from spm, ssr iteratively routes/updates backup paths in order to minimize the cost of total spare capacity. a backup path can be further updated as long as it is not carrying any traffic. furthermore, the spm method and ssr algorithm are generalized from protecting all single link failures to any arbitrary link failures such as those generated by shared risk link groups or all single node failures. numerical results comparing several sca algorithms show that ssr has the best trade-off between solution optimality and computation speed.
optimal partition of qos requirements on unicast paths and multicast trees. we investigate the problem of optimal resource allocation for end-to-end qos requirements on unicast paths and multicast trees. specifically, we consider a framework in which resource allocation is based on local qos requirements at each network link, and associated with each link is a cost function that increases with the severity of the qos requirement. accordingly, the problem that we address is how to partition an end-to-end qos requirement into local requirements, such that the overall cost is minimized. we establish efficient (polynomial) solutions for both unicast and multicast connections. these results provide the required foundations for the corresponding qos routing schemes, which identify either paths or trees that lead to minimal overall cost. in addition, we show that our framework provides better tools for coping with other fundamental multicast problems, such as dynamic tree maintenance.
an algorithm to compute collusion paths. in earlier work we have formulated a collusion problem that determines whether it is possible for a set of colluders to collectively discover a target set of information, starting from their initial knowledge, and have presented a complete solution for a special case of the problem. in this paper we present an algorithm that solves the general case. given a collusion problem the algorithm determines whether it has a solution, and if it does, computes one. a solution to the collusion problem is a method with which the colluders can uncover the hidden information. communications protocols that employ cryptographic techniques are increasingly used to protect privacy as well as to communicate. a cryptographic protocol defines a process by which information is transferred among some users while hidden from others. the algorithm presented here can be used to determine whether a subset of protocol users can discover, during or after the protocol's execution, the information that is designed to be hidden from them.
document marking and identification using both line and word shifting. continues a study of document marking to deter illicit dissemination. an experiment performed reveals that the distortion on the photocopy of a document is very different in the vertical and horizontal directions. this leads to the strategy that marks a text line both vertically using line shifting and horizontally using word shifting. a line that is marked is always accompanied by two unmarked control lines one above and one below. they are used to measure distortions in the vertical and horizontal directions in order to decide whether line or word shift should be detected. line shifts are detected using a centroid method that bases its decision on the relative distance of line centroids. word shifts are detected using a correlation method that treats a profile as a waveform and decides whether it originated from a waveform whose middle block has been shifted left or right. the maximum likelihood detectors for both methods are given.
smds measurements and modeling to predict performance. the authors describe a performance study of a trial switched multimegabit data service (smds) link (intended for inter-lan connection) from the perspective of customers evaluating the feasibility of the link for some target applications. the goals were to take all measurements on the customer premises and to develop a methodology general enough to be used by customers to evaluate the link. the authors measured a lightly loaded system and developed a model of the smds connection suitable for evaluating applications via analysis or simulation. they document their methodology and present the smds connection delay values as well as a likely breakdown of the constituents of that delay. they used these data to create a simulation model and to simulate a simple application. in the trial configuration, where geographical distances were small, smds network delay was one of the notable components of end-to-end delay in the smds connection. however, for most packets, throughput is limited by the t1 capacity for transmitting smds cells, not by the smds network capacity
unified power control, error correction coding and scheduling for a cdma downlink system. transmitting multimedia data over a cdma channel presents a new set of challenges. sometimes, data demands will exceed the system capacity, in which case the system must make the most efficient use of its limited resources. the resources we consider are: fixed bandwidth available for each user and the transmit power budget for each cell. in this paper, we present our approach for unifying power control, variable forward error correction (vfec), and scheduling for a downlink system by allocating the system resources. our objective is to maximize the overall system satisfaction, which we call &ldquo;system utility&rdquo;. this objective is achieved by applying a distributed algorithm which divides the overall optimization problem into a hierarchy of three levels (system, cell and user). at each level, the system performs independent and parallel optimizations; the critical information is then passed to the higher level for further optimization. finally, an iterative and distributed algorithm is applied at the system level to achieve the overall system optimization.
adaptive hodling policies for ip over atm networks. next generation wide area networks will be connection-oriented, with data-link layer connectivity being provided by asynchronous transfer mode (atm). for the huge existing investment in current ip networks such as the internet to remain useful, one must devise mechanisms to carry ip traffic over atm networks. a fundamental issue is to devise holding policies for virtual circuits carrying datagrams. the authors consider two pricing schemes, the first is a likely pricing scheme of future atm networks, while the second is based on characteristics of current networks. for each pricing scheme, the authors devise a simple holding policy that adapts to the characteristics of the ip traffic. the authors simulate their policies on actual network traffic and find that they perform significantly better than previous policies.
an empirical model of http network traffic. the workload of the global internet is dominated by the hypertext transfer protocol (http), an application protocol used by world wide web clients and servers. simulation studies of ip networks will require a model of the traffic patterns of the world wide web, in order to investigate the effects of this increasingly popular application. we have developed an empirical model of network traffic produced by http. instead of relying on server or client logs, our approach is based on packet traces of http conversations. through traffic analysis, we have determined statistics and distributions for higher-level quantities such as the size of http files, the number of files per "web page", and user browsing behavior. these quantities form a model can then be used by simulations to mimic world wide web network applications.
peakedness measures for traffic characterization in high-speed networks. in high-speed networks based on asynchronous transfer mode (atm), variable bit rate (vbr) sources generate bursty cell streams which share link bandwidth wherever multiplexing occurs. in theory, the bandwidth requirement per stream to support a given quality-of-service at a multiplexer should generally decrease as the number of streams increases. in practice, high statistical multiplexing gain is difficult to achieve because good traffic characterizations are usually not available. this paper proposes the use of peakedness-based measures to capture the statistical information from traffic streams needed to determine bandwidth allocations. the standard definition of peakedness applies only to point process models of traffic. yet fluid models of traffic have certain advantages in terms of tractability. hence, we introduce a new measure called {\it modified peakedness}, which encompasses point process and fluid models under a common framework. we develop some of its properties and specialize it to several common traffic models. finally, we study the effectiveness of the peakedness/modified peakedness as burstiness measures for real-time traffic.
implementation and analysis of ip multicast over atm. today it is evident that atm technology will have its role in the future of internetworking. two major internet backbone service providers, sprint and mci, have marketed their investments in atm as a way to push more bandwidth into their internet infrastructures. regardless of whether atm technology will thrive in the wan or lan, it is also evident that the internet protocol (ip), which has been the glue of the internet allowing it to endure exponential growth, must be well supported over atm. ip multicast (protocol extensions to ip that allow ip packets from one source to be distributed to multiple destinations) is an essential part of ip which has allowed multimedia applications, for example, to more efficiently use internet resources. in this paper we describe an implementation of one model of supporting ip multicast over atm, the multicast over atm model developed by the ietf. we discuss empirical measurements gathered in a testbed with both a wan and a lan component that give insights into the behavior of this model. we detail some of the shortcomings of this model and discuss potential modifications to improve it. ideas for other approaches to ip multicast over atm are also described.
robust box bounds: throughput guarantees for closed multiclass queueing networks with minimal stochastic assumptions. to use queuing theory to analyze real systems such as computer communications networks, one makes assumptions that are, strictly speaking, untrue. the authors provide an exact analysis for cases with greatly relaxed assumptions. service times can have general increasing failure rate distributions, different by class even at fifo nodes. routing can be arbitrary, including dependencies along the route, provided the number of visits to each node is a random variable. only the mean service time and mean visit rates at nodes need be specified. a lower throughput bound is found which gives a minimum guaranteed throughput for each class; together with the familiar multiclass asymptotic upper bounds they give a convex feasible region in a multidimensional throughput space. a detailed analysis is given for systems with fifo and infinite-server nodes, and the extension to processor-sharing nodes is described. the results can be reinterpreted as a set of bounds on the separate throughputs. this is equivalent to a circumscribed rectangular region called the robust box bounds
sr: a bandwidth-reservation mac protocol for multimedia applications over all-optical wdm multi-rings. the paper describes sr3 (synchronous round robin with reservations), a collision-free medium access control protocol for all-optical slotted packet networks based on wdm multi-channel ring topologies where nodes are equipped with one fixed-wavelength receiver and one wavelength-tunable transmitter. sr3 is derived from the srr and mmr protocols previously proposed by the same authors for the same class of all-optical networks. srr and mmr already achieve an efficient exploitation of the available bandwidth, while guaranteeing a throughput-fair access to each node. sr3, in addition, allows nodes to reserve slots, thereby achieving a stronger control on access delays; it is thus well suited to meet tight delay requirements, as it is the case for multimedia applications. simulation results show that sr3 provides very good performance to guaranteed quality traffic, but also brings significant performance improvements for best-effort traffic.
pricing strategies under heterogeneous service requirements. this paper analyzes a communication network, used by customers with heterogeneous service requirements. we investigate priority queueing as a way to establish service differentiation. it is assumed that there is an infinite population of customers, who join the network as long as their utility (which is a function of the queueing delay) is larger than the price of the service. we focus on the specific situation with two types of users: one type is delay-sensitive ('voice'), whereas the other is delay-tolerant ('data'); these preferences are reflected in their utility curves. two models are considered: in the first the network determines the priority class of the users, whereas the second model leaves this choice to the users. for both models we determine the prices that maximize the provider's profit. importantly, these situations do not coincide. our analysis uses elements from queueing theory, but also from microeconomics and game theory (e.g., the concept of a nash equilibrium). we conclude the paper by considering a model in which throughput (rather than delay) is the main performance measure. again the pricing strategy exploits the heterogeneity in service requirements and willingness-to-pay.
metaring fairness control schemes in all-optical wdm rings. wdm rings are receiving significant attention in the field of all-optical networks because their implementation appears to be feasible with state-of-the-art components. several mac protocols were recently proposed in order to resolve contentions among nodes sharing the available wavelengths in wdm rings. these mac protocols achieve high efficiency but unsatisfactory fairness, due to the asymmetric position of sources with respect to destinations. thus, in order to improve fairness, it is necessary to adopt a fairness control scheme. in this paper we discuss the adaptation of the metaring fairness control scheme to the context of wdm multi-channel rings. several alternatives are considered and compared via simulation.
using partial differential equations to model tcp mice and elephants in large ip networks. in this paper we propose a new fluid model approach in which a different description of the dynamics of traffic sources is adopted, exploiting partial differential equations. this new description of the source dynamics allows the natural representation of short-lived as well as long-lived tcp connections, with no sacrifice in the scalability of the model. in addition, the use of partial differential equations permits the description of distributions, instead of averages, thus providing better accuracy in the results.the comparison between the performance estimates obtained with fluid models and with ns-2 simulations proves the accuracy of the proposed modeling approach.
cycles and waiting times in symmetric exhaustive and gated multiserver multiqueue systems. the authors consider symmetric multiserver multiqueue systems in the cases of exhaustive and gated service disciplines, and present exact analytical results for the average server cycle and vacation times, as well as approximate closed-form expressions for the average customer waiting time, thus complementing the results obtained by the same authors (1990) for the one-limited service discipline. arrival processes at each queue are assumed to be poisson, with the same rate for all queues; service times and walk times are modeled with independent, identically distributed random variables with arbitrary distributions. the two cases in which at most one server or any number of servers can simultaneously attend a queue are considered
priority service and max-min fairness. we study a priority service where users are free to choose the priority of their traffic, but are charged accordingly by the network. we assume that each user chooses priorities to maximize its own net benefit, and model the resulting interaction among users as a noncooperative game. we show that there exists an unique equilibrium for this game and that in equilibrium the bandwidth allocation is weighted max-min fair.
towards optimal policing in atm networks. this paper proposes a framework for optimal policing in atm networks. a general approach to modeling controllers which implement the policing function is described using finite-state automata. the theory of finite-state accepting automata and regular expressions enables the symbolic computation of the worst-case source and therefore provides a basis for the formulation and derivation of optimal bandwidth enforcement schemes. exhaustive searches are performed for small cases to find optimal finite-state automata. these optimal results are extended to obtain near-optimal solutions for higher-state automata. the optimal and near-optimal finite-state automata are compared to existing schemes, such as leaky buckets, and improvement in terms of cell loss rate of the declared source is achieved.
bandwidth sharing: objectives and algorithms. this paper concerns the design of distributed algorithms for sharing network bandwidth resources among contending flows. the classical fairness notion is the so-called max-min fairness. the alternative proportional fairness criterion has recently been introduced by kelly; we introduce a third criterion, which is naturally interpreted in terms of the delays experienced by ongoing transfers. we prove that fixed-size window control can achieve fair bandwidth sharing according to any of these criteria, provided scheduling at each link is performed in an appropriate manner. we then consider a distributed random scheme where each traffic source varies its sending rate randomly, based on binary feedback information from the network. we show how to select the source behavior so as to achieve an equilibrium distribution concentrated around the considered fair rate allocations. this stochastic analysis is then used to assess the asymptotic behavior of deterministic rate adaption procedures.
the use of communications networks to increase personal privacy. communications networks can separate as well as join information. this ability can be used to increase personal privacy in an environment where advances in technology makes it possible to collect and correlate increasing amounts of information about individuals. the tools and principles necessary to increase personal privacy are demonstrated by creating an anonymous credit card, in which a person's identity and purchases are separated, and a national health insurance plan, in which treatment, payment and an individual's identity are separated. an analysis technique is developed to determine how well the information is separated.
local fairness in general-topology networks with convergence routing. convergence routing is a unique variant of deflection routing which ensures that packets (or cells) will converge to their destinations along a global sense of direction. in this work we show how a global sense of direction can be used in an arbitrary network for the design of a control algorithm which (a) ensures fair access in switch-based local area networks, (b) is efficient with respect to performance measures we have developed, and (c) is easily interfaced to the convergence routing mechanism. we present performance measures which assess the new access- and flow-control algorithm: (i) locality- only the sub-network containing conflicting traffic streams gets involved in the fairness regulation; (ii) scalability-the data-structure sizes used in the algorithm are a function of the switching node degree, and use constant space control signals of only a-bit (the atm standard, for example, dedicates four bits in the header of each cell to generic flow-control); (iii) linear access-time measured by the "the maximal clique in the conflict-graph to which a node belongs", and a frequency which is inverse linear in this parameter (when the traffic pattern stabilizes).
time scale analysis of an atm queueing system with long-range dependent traffic. several types of network traffic have been shown to exhibit long-range dependence (lrd). in this work, we show that the busy period of an atm system driven by a long-range dependent process can be very large. we introduce a new traffic model based on a fractional brownian motion envelope process. we show that this characterization can be used to predict queueing dynamics. furthermore, we derive a new framework for computing delay bounds in atm networks based on this traffic model. we show that it agrees with results given by large deviation theory with less computational complexity.
error control for messaging applications in a wireless environment. the paper investigates error control mechanisms for mobile messaging applications, such as e-mail, fax, and credit card verification. although existing protocols provide efficient error control over conventional networks, wireless networks present significant new challenges. the radio link introduces noise and multipath interference causing long periods of increased error rate, while host motion requires changing communication paths that can cause packet delay, misordering, duplication, and loss. furthermore, scarce radio resources make bandwidth efficiency desirable. using measurements from a field-deployed pcs system in boulder colorado, the authors identify two types of reception area. they highlight the benefits of powerful error control mechanisms in the fringe reception areas, especially selective acknowledgments and combining data from multiple transmissions.
multi-hour, multi-traffic class network design for vp-based wide-area dynamically reconfigurable atm networks. the virtual path (vp) concept has been gaining attention in terms of effective deployment of atm (asynchronous transfer mode) networks in recent years. in this paper, we discuss a multi-hour, multi-traffic class network (capacity) design model for providing specified quality-of-service in dynamically reconfigurable atm networks. our approach is based on statistical multiplexing of traffic within a traffic class by using a virtual path for the class and deterministic multiplexing of different virtual paths, and on providing dynamic bandwidth and reconfigurability through the virtual path concept depending on traffic load during the course of the day. we show that, for test problems based on realistic network data, our approach does between 6% to 20% better than a local shortest path heuristic in terms of network cost. we also show that considering network dynamism through variation of traffic during the course of a day by doing dynamic bandwidth and virtual path reconfiguration can save between 10% to 14% in network design costs compared to a static network based on maximum busy hour traffic.
modeling and analysis of a single server queue with autocorrelated traffic. in performance analysis of computer and communication systems, the designer is often faced with two challenges: modelling an input process accurately and then solving a resulting queueing problem. the authors present a modelling methodology called qtes (quantized transform-expand-sample) which can be used to model the interarrival distribution (histogram) accurately and to capture the effect of autocorrelations approximately. they then show that a difficult queueing problem (using a qtes input with autocorrelations) can be solved. the method is analytically tractable and numerically robust as shown by various examples.
multiplexing spacer outputs on cell emissions. in atm networks, one effective way to provide service guarantees is to shape individual traffic streams at various points in the network. in the paper, the authors present a method for multiplexing a large number of single-stream spacer outputs on cell emissions rather than on cell arrivals. the method not only approximates first come first served (fcfs) multiplexing of such outputs but also better suits bursty arrivals. a number of performance related issues of the proposed method are identified and examined.
multi-channel copy networks: architecture, performance model, fairness, and cell sequencing. this paper develops a copy network architecture that can maintain the cell sequence integration multichannel atm switching. the architecture is internally nonblocking. assuming that cells appear with fanout request values that are distributed independently from cell to cell, we also formulate a method of analyzing the performance of the copy network. we conduct a numerical study for the proposed architecture using this method, and the effects of key network and traffic variables are quantified under arbitrary types of fanout distribution.
charging schemes for atm networks based on virtual effective bandwidths. in this paper, we propose charging schemes for atm networks based on the concept of virtual effective bandwidths (veb). vebs were initially developed by the authors to support real-time connection admission control (cac) in a framework where traffic sources with different quality of service (qos) requirements are multiplexed into the same finite length queue. vebs allow different qos requirements to be related which is important for charging purposes. we propose three charging schemes which can be included in real-time cac: the first one depends solely on the resource requirements of the call; the second is dependent on resource as well as qos requirements of the call; the third is dependent on the current traffic intensity of the other connections also.
performance analysis of multistage interconnection networks with shared-buffered switching elements for atm switching. the performance evaluation of multistage self-routing interconnection networks for asynchronous transfer mode (atm) switching is carried out by means of an analytical approach. the switching elements in the interconnection network are provided with a buffer shared among all the inlets and outlets of the element and no backpressure signals are exchanged between adjacent stages. two analytical models are considered: the scalar model and the vectorial model. in the former case the addresses of the packets in the same buffer are assumed to be mutually independent, whereas in the latter case the model keeps memory of the addresses of the packets stored in the buffer across consecutive time slots. the vectorial model provides performance measures much more accurate than the scalar model
estimation and removal of clock skew from network delay measurements. packet delay and loss traces are frequently used by network engineers, as well as network applications, to analyze network performance. the clocks on the end-systems used to measure the delays, however, are not always synchronized, and this lack of synchronization reduces the accuracy of these measurements. therefore, estimating and removing relative skews and offsets from delay measurements between sender and receiver clocks are critical to the accurate assessment and analysis of network performance. in this paper we introduce a linear programming based algorithm to estimate the clock skew in network delay measurements and compare it with three other algorithms. we show that our algorithm has the time complexity of $o(n)$, leaves the delay after the skew removal positive, and is robust in the sense that the error margin of the skew estimate is independent of the magnitude of the skew. we use traces of real internet delay measurements to assess the algorithm, and compare its performance to that of three other algorithms. furthermore, we show through simulation that our algorithm is unbiased, and that the sample variance of the skew estimates is better(smaller) than existing algorithms.
a method for analysing the performance aspects of the fault-tolerance mechanisms in fddi. the ability of error recovery mechanisms to make the fiber distributed data interface (fddi) satisfy real-time performance constraints in the presence of errors is analyzed. a complicating factor in these analyses is the rarity of the error occurrences, which makes direct simulation unattractive. therefore, a fast simulation technique, called injection simulation, which makes it possible to analyze the performance of fddi, including its fault tolerance behavior, was developed. the implementation of injection simulation for polling models of fddi is discussed, along with simulation results
bulk multicast transport protocol. bmtp offers rate controlled multicast with reliability, high throughput, and support for large numbers of receivers. a multicast sender needs feedback from receivers to recover from errors and to choose an appropriate send rate, but must avoid being overwhelmed as the number of receivers grows. bmtp does this by keeping the rate at which each receiver sends feedback inversely proportional to a running estimate of the number of receivers. bmtp bases its send rate on the minimum of the receive rates observed by the receivers, causing the sender to slow down in the face of packet loss or competing traffic, and to speed up when there is spare network capacity. bmtp's nak-based retransmission rarely sends any data more than twice, a substantial improvement over iterated unicast. rabin's information dispersal algorithm can reduce this re-send rate as close as desired to the underlying loss rate of the network. simulations with 1000 receivers substantiate these claims. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
performance modelling of a multi-buffered banyan switch under bursty traffic. the authors present an analytical model of a buffered banyan asynchronous transfer mode (atm) switch which allows complex switching elements, bursty traffic, and nonuniform destination distributions and permits the analysis of large-scale switches. the atm switch is analyzed by decomposing it into individual switching elements. each switching element is then analyzed numerically in isolation assuming that its arrival and service processes are known. the parameters of the arrival and service processes of the switching elements are obtained using an iterative scheme. the results obtained are approximate and validation tests have shown that they have good accuracy. using this model, the cell loss, throughput, and the mean time to traverse the switch were obtained for different traffic parameters and buffer sizes within a switching element
group allocation multiple access with collision detection. the group allocation multiple access with collision detection (gama/cd) protocol for scheduling variable-length packet transmissions in a local area network is specified and analyzed. gama/cd provides the advantages of both tdma and csma/cd by maintaining a dynamically-sized cycle that varies in length depending on the network load; each cycle is composed of a contention period and a group-transmission period. during the contention period, a station with one or more packets to send competes for membership in the transmission group. once a member of the transmission group, a station is able to send data without collision during each cycle; as long as a station has data to send, it maintains its position in the group. this can be viewed as either allowing stations to ``share the floor'' in an organized manner, or as establishing frames that are not synchronized on a slot-basis and vary their length dynamically based on demand. both the throughput and the delay of gama/cd are presented and analyzed. to validate our analysis, the results of both models are compared to the throughput and delay produced by a simulation of gama/cd.
dynamic time windows and generalized virtual clock: combined closed-loop/open-loop congestion control. the authors present mechanisms for congestion control of data traffic in high-speed wide area networks. the network model assumes reservation of resources based on average requirements. the key ideas involve separation of different sources of network congestion, short-term bursts and medium-term load, and using separate mechanisms to address them. thus, dynamic time window (dtw) admission control is proposed as a mechanism to limit traffic burstiness from sources as a function of the medium-term load on the system, while a new fairness criterion for short-term congestion (pulse) is proposed as a mechanism for dealing with fair scheduling by switches of short-term bursts. the model of the network is presented. the dtw and pulse mechanisms are discussed. a detailed analytical and simulation study is presented for static time-windows and various scheduling algorithms. preliminary results on dtw are discussed
an adaptive connection admission control policy for vbr+ service class. a new service class, called vbr+ (reininger, ramamurthy and raychaudhuri, in&colon; atm forum contribution 94-0353, 1994), has been proposed for multimedia applications on atm networks. vbr+ extends the functionality of the traditional vbr service with the added capability of dynamic resource renegotiation. it makes the specification and modification of the usage parameter controls flexible, and potentially can increase the network resource utilization through statistical multiplexing. these advantages come at the expense of a more complex connection admission controller which should be designed to handle bandwidth renegotiation efficiently. in this paper a connection admission controller for vbr+ service class is proposed. we identify the desirable features of a vbr+ connection admission controller, and present a novel one that can achieve them through (1) dynamic resource partitioning, and (2) dynamic resource redistribution among active connections. simulation results showing the performance of the controller using a number of actual video traces are presented. the results show that the controller is robust in admitting a variety of video sources with widely different traffic burstiness. by partitioning the resource pool dynamically, and distributing resources among contending connections fairly, it can maintain very good quality, and can achieve high utilization. comparison with traditional vbr service reveals that the cac is able to provide comparable quality with higher network utilization. the work was performed when this author was visiting c&c research laboratory, nec usa during summer 1996 while he was with department of computer science and engineering, university of nebraska, lincoln, ne 68588, usa.
comparative study on restoration schemes of survivable atm networks. in self-healing networks, end-to-end restoration schemes have been considered more advantageous than line restoration schemes because of a possible cost reduction of the total capacity to construct a fully restorable network. this paper clarifies the benefit of end-to-end restoration schemes quantitatively through a comparative analysis of the minimum link capacity installation cost. a jointly optimal capacity and flow assignment algorithm is developed for the self-healing atm networks based on end-to-end and line restoration. several networks with diverse topological characteristics as well as multiple projected traffic demand patterns are employed in the experiments to see the effect of various network parameters. the results indicate that the network topology has a significant impact on the required resource installation cost for each restoration scheme. contrary to a wide belief in the economic advantage of the end-to-end restoration scheme, this study reveals that the attainable gain could be marginal for a well-connected and/or unbalanced network.
analysis of flow enforcement algorithm for bursty traffic in atm networks. the authors analyze the flow enforcement algorithm suitable for regulating the flow of the bursty traffic in asynchronous transfer mode (atm) networks (for broadband packet switching). the flow enforcement algorithm has two objectives: to force the input traffic to conform to the traffic parameters which are specified by the source itself at its connection time; and to obtain greater performance gain at the cell multiplexer by regulating the flow to some extent. the authors reveal the tradeoff relationship between the regulation level of the cell flow and the improvement of the link performance. the authors first analyze the flow enforcement mechanism to derive the delay distribution and the interdeparture time distribution for cells at the flow enforcer. for the input traffic, they allow the general independent arrivals of cells to represent the traffic burstiness larger than a poisson distribution. the obtained interdeparture time distributions from the flow enforcer are then used to approximately analyze the performance of the cell multiplexer. for this purpose, a markov-modulated poisson process (mmpp) approximation method is extended to investigate the performance of individual traffic stream in the superposed arriving traffic streams
loop-free internet routing using hierarchical routing trees. we present a new hierarchical routing algorithm that combines the loop-free path-finding algorithm (lpa) with the area-based hierarchical routing scheme first proposed by mcquillan for distance-vector algorithms. the new algorithm, which we call the hierarchical information path-based routing (hipr) algorithm, accommodates an arbitrary number of aggregation levels and can be viewed as a distributed version of dijkstra's algorithm running over a hierarchical graph. hipr is verified to be loop-free and correct. simulations are used to show that hipr is much more efficient than ospf in terms of speed, communication and processing overhead required to converge to correct routing tables. hipr constitutes the basis for future internet routing protocols that are as simple as ripv2, but with no looping and better performance than protocols based on link-states.
approximation techniques for computing packet loss in finite-buffered voice multiplexers. in this paper we examine three different approximation techniques for modeling packet loss in finite-buffer voice multiplexers. the performance models studied differ primarily in the manner in which the superposition of the voice sources (i.e., the arrival process) is modeled. the first approach models the superimposed voice sources as a renewal process and performance calculations are based only on the first two moments of the renewal process. the second approach is based on modeling the superimposed voice sources as a markov modulated poisson process (mmpp). our choice of parameters for the mmpp attempts to capture aspects of the arrival process in an alternate, more intuitive, manner than previously proposed approaches for determining the mmpp parameters and is shown to compute loss more accurately. finally, we also evaluate a fluid flow approximation for computing packet loss. for all three approaches, we consider as a unifying example, the case of multiplexing voice sources over a t1-rate link. the main conclusion of this paper is that both the new mmpp model examined here and the fluid flow approximation can provide accurate loss predictions for parameter ranges of practical interest; these predictions are also shown to be many orders of magnitude better than modeling the superimposed voice sources simply as a poisson process. we also discuss the problem of modeling buffer overflow for general arrival processes and also consider modeling approaches for analyzing finite-buffer multiplexers with general arrival and service processes in a network environment.
qos provisioning in micro-cellular networks supporting multimedia traffic. we introduce an adaptive call admission control mechanism for wireless/mobile networks supporting multimedia traffic, and discuss a number of resource sharing schemes which can be used to allocate wireless bandwidth to different classes of traffic. the adaptive call admission control reacts to changing new call arrival rates, and the resource sharing mechanism reacts to rapidly changing traffic conditions in every radio cell due to mobility of mobile users. in addition, we have provided an analytical methodology which shows that the combination of the call admission control and the resource sharing schemes guarantees a predefined quality-of-service to each class of traffic. one major advantage of our approach is that it can be performed in a distributed fashion removing any bottlenecks that might arise due to frequent invocation of network call control functions.
analyzing non-determinism in telecommunication services using p-invariant of petri-net model. telecommunication service specifications are often modeled by the state transition machine in which a state moves to a next state by the execution of the user's event. if multiple transitions exist for a certain pair of state and user's event, then a non-deterministic behavior occurs at the state.as the result, the non-deterministic behavior causes an illegal state transition against the user's intention, and thus should be eliminated from the state transition machine. the conventional analysis method for non-determinism is based on reachability analysis. since the method must exhaustively enumerate all reachable states of the state transition machine, it cannot be applied to the complex communication services which include many users.this paper proposes a new analysis method based on a petri-net model. the method constructs a logically equivalent petri-net for a given service specification, and obtains a set of states which cause the non-deterministic behaviors using rules in the service specification. then, the method identifies states in the set which are not reachable from the initial state using p-invariant of the petri-net, and deletes them from the set. as p-invariant is sufficient condition, we must finally apply reachability analysis to states in the resultant set. since the number of states in the resultant set may be reduced to relatively small, the new method enables us to analyze the more complex services.
performance analysis of a multichannel local lightwave network with grouping property. the authors propose a multichannel lightwave network with a grouping property which exhibits better channel efficiency as the traffic is more likely within groups. the network also avoids both wavelength agility and pretransmission coordination problems. two network topologies are considered. one is a multichannel lightwave network with full connection within groups. while it requires many receivers in each network interface unit (niu) it exhibits low queuing delay and high network capacity. the other is a multichannel lightwave network with minimal connection within groups. while it gives relatively poor delay-throughput characteristics, a network can be constructed with each niu having only two fixed-wavelength receivers. the network capacities and the mean queuing delays for the two network topologies are presented
scheduled hot-potato routing. this paper is concerned with fast, hot-potato routing, performed according to a predetermined schedule. at each time period each node selects an outgoing link, through which an incoming packet is sent. no buffers are used. we investigate first the problem of how to route a network-wide demand of packets, given the predetermined schedule. we show that certain versions of the problem have efficient solutions, while other versions are intractable. we then consider the problem of finding an optimal schedule given a network-wide demand of packets. we indicate that the problem is tractable for either a single source or single destination. however for the multi-source multi-destination case we show that it is an np-complete problem. the problem remains intractable even for a simple topology of nodes arranged on a bidirectional line. we present an efficient heuristic for directed tree-networks, and adapt it to general topologies through a recursive scheme, for which an efficient performance bound is shown.
on defining, computing and guaranteeing quality-of-service in high-speed networks. future high-speed networks are expected to support a wide variety of services such as voice and video, and to provide a guaranteed quality-of-service (qos). the authors examine the issues of computing and guaranteeing qos. traditionally, the computation of user-oriented performance criteria such as the average delay has been carried out via steady-state analysis of queuing theoretic models of communication networks. it is shown that the steady-state computations are often not sufficient for qos purposes in future high-speed networks. the authors provide mechanisms for computing and guaranteeing qos criteria and consider the issue of approximate qos criteria. it is argued that, for certain envisaged applications, traditional qos criteria are not appropriate. a qos criterion for such applications is proposed
new dynamic spt algorithm based on a ball-and-string model. a key functionality in today's widely used interior gateway routing protocols such as ospf and is-is involves the computation of a shortest path tree (spt). in many existing commercial routers, the computation of an spt is done from scratch following changes in the link states of the network. as there may coexist multiple spts in a network with a set of given link states, such recomputation of an entire spt not only is inefficient but also causes frequent unnecessary changes in the topology of an existing spt and creates routing instability.this paper presents a new dynamic spt algorithm that makes use of the structure of the previously computed spt. our algorithm is derived by recasting the spt problem into an optimization problem in a dual linear programming framework, which can also be interpreted using a ball-and-string model. in this model, the increase (or decrease) of an edge weight in the tree corresponds to the lengthening (or shortening) of a string. by stretching the strings until each node is attached to a tight string, the resulting topology of the model defines an (or multiple) spt(s). by emulating the dynamics of the ball-and-string model, we can derive an efficient algorithm that propagates changes in distances to all affected nodes in a natural order and in a most economical way. compared with existing results, our algorithm has the best-known performance in terms of computational complexity as well as minimum changes made to the topology of an spt. rigorous proofs for correctness of our algorithm and simulation results illustrating its complexity are also presented.
fairness and optimal stochastic control for heterogeneous networks. we consider optimal control for general networks with both wireless and wireline components and time varying channels. a dynamic strategy is developed to support all traffic whenever possible, and to make optimally fair decisions about which data to serve when inputs exceed network capacity. the strategy is decoupled into separate algorithms for flow control, routing, and resource allocation, and allows each user to make decisions independent of the actions of others. the combined strategy is shown to yield data rates that are arbitrarily close to the optimal operating point achieved when all network controllers are coordinated and have perfect knowledge of future events. the cost of approaching this fair operating point is an end-to-end delay increase for data that is served by the network.
performance analysis of generalized multihop shuffle networks. this paper describes the performance analysis of a class of two-connected multihop shufflenets, known as generalized shuffle networks. the topology of such networks is described mathematically by the equation n=kn, where n is the total number of nodes in the network, k the number of stages in the network and n the number of nodes in each stage. compared to classical shufflenets, the definition of generalized shuffle networks allows a larger number of feasible network structures that are realizable for a given network size n. in attempting to find an optimum network structure, network characteristics are discussed and system performance is evaluated. important relationships and interdependencies among the various network parameters are developed to facilitate cross-structural comparison.
optical switching networks with minimum number of limited range wavelength converters. we study the problem of determining the minimum number of limited-range wavelength converters needed to construct strictly, wide-sense, and rearrangeably nonblocking optical cross-connects for both unicast and multicast traffic patterns. we give the exact formula to compute this number for rearrangeably and wide-sense nonblocking cross-connects under both the unicast and multicast cases. we also give optimal cross-connect constructions with respect to the number of limited-range wavelength converters.
on multihop optical network topology using kautz diagraphs. proposes a new topology for multihop, optical networks using kautz digraphs. the properties of such a network as a logical topology are evaluated and compared with other topologies proposed in the literature. for a given degree of each node and a given diameter of the network, a kautz digraph supports more nodes than other topologies like shufflenet or that using a debruijn digraph and hence seems to be an attractive design for the physical topology too.
network architecture and functional requirements for upt. the author identifies major functional requirements to support universal personal telecommunications (upt) within a broad upt reference model. these functional requirements are mapped on the current view of the intelligent network (in) architectural model so that the key functional elements and interfaces in the in architecture can be identified and the necessary network capabilities to support upt specified. network operations requirements for access security and personal privacy protection are presented and the relationship between the access security requirements and upt performance aspects discussed
addressing network survivability issues by finding the k-best paths through a trellis graph. due to the increasing reliance of our society on the timely and reliable transfer of large quantities of information (such as voice, data, and video) across high speed communication networks, it is becoming important for a network to offer survivability, or at least graceful degradation, in the event of network failure. in this paper we aim to offer a solution in the selection of the k-best disjoint paths through a network by using graph theoretic techniques. the basic approach is to map an arbitrary network graph into a trellis graph which allows the application of computationally efficient methods to find disjoint paths. use of the knowledge of the k-best disjoint paths for improving the survivability of atm networks at the virtual path and virtual circuit level is discussed.
optical routing control using coherent pattern-matching circuit for photonic self-routing switch. optical routing control using a coherent optical pattern-matching circuit is described. this circuit can detect any specified pattern in an ultrafast optical signal sequence by using tapped delay-lines to optically correlate the input pattern with a set pattern. a whole 4-bit pattern-matching circuit was monolithically integrated on a silicon substrate by the silica-based planar lightwave circuit technology. the fabricated circuit operated at a bit rate of 4.65 gb/s. pattern-matching circuits can apply to optical routing control for photonic self-routing switches. address-header formats for ring and banyan networks are also discussed from the point of view of the power penalty versus the number of addresses. the header for ring networks is composed of a binary code or a gold code. the header for banyan networks is composed of code-division-multiplexed gold codes. optically routing-controlled photonic packet switching using headers composed of binary codes was experimentally demonstrated at a bit rate of 10 gb/s
performance modelling of reliable multicast transmission. our aim is to investigate reliable transmission for multicast communication and explore its relationship to multicast routing. we derive two characterizations that enable the comparison of routing algorithms and error recovery mechanisms with respect to the multicast tree topology, namely the probability mass function of successful receptions and the expected number of retransmissions needed to deliver a packet from the source to all receivers. we also give a tight approximation of the computationally expensive expected number of retransmissions. these expressions allow to explore the relationship between routing and error recovery for multicast communication. we finally evaluate the impact of routing algorithms on the performance of reliable multicast transmission and give a realistic generic model for a multicast tree.
a look at the mpeg video coding standard for variable bit rate video transmission. the mpeg video coding standard for the transmission of variable-bit-rate video on asynchronous transfer mode (atm)-based broadband isdn is examined. the focus is on its use for real-time transmission of broadcast-quality video. the impact of two key parameters, the intraframe to interframe picture ratio and the quantization index that are defined in the standard, on the bit rates per frame was studied. these parameters can be used to control video sources depending on the state of the network. also, as opposed to previous work which looks only at bit rates per frame, the bits generated per macroblock are studied. this is the basic mpeg coding unit. by packetizing these bits, insight was obtained into the cell arrival process to a network for a mpeg video source
improving the performance of interactive tcp applications using service differentiation. interactive tcp applications, such as telnet and the web, are particularly sensitive to network congestion. indeed, congestion-induced queueing and packet loss can be a significant cause of large delays and variability, thereby decreasing user-perceived quality. we consider addressing these effects using service differentiation, by giving priority to interactive applications' traffic in the network. we study different packet marking schemes and handling mechanisms (packet dropping and scheduling) in the network. for marking packets, two approaches are considered. first, we look into application-based marking, and show how the protection of telnet traffic against loss can eliminate large echo delays caused by retransmit timeouts, and how, by limiting packet loss for web page downloads, their delays can be significantly reduced, resulting in enhanced interactivity. second, we consider differentiation based on tcp state, where we present a marking algorithm that prioritizes packets at the source, based on each connection's window size. in addition, we describe the shaping mechanisms required for conformance to agreements with the network. we show how this marking results in good response times for short transfers, which are characteristic of interactive applications, without significantly affecting longer ones.
broadcast scheduling for information distribution. broadcast data delivery is encountered in many applications where there is a need to disseminate information to a large user community in a wireless asymmetric communication environment. in this paper, we consider the problem of scheduling the data broadcast such that the access latency experienced by the users is low. in a push-based system, where the users cannot place requests directly to the server and the broadcast schedule should be determined based solely on the access probabilities, we formulate a deterministic dynamic optimization problem, the solution of which provides the optimal broadcast schedule. properties of the optimal solution are obtained and then we propose a suboptimal dynamic policy which achieves mean access latency close to the lower bound. the policy has low complexity, it is adaptive to changing access statistics, and is easily generalizable to multiple broadcast channels. in a pull-based system where the users may place requests about information items directly to the server, the scheduling can be based on the number of pending requests for each item. suboptimal policies with good performance are obtained in this case as well. finally, it is demonstrated by a numerical study that as the request generation rate increases, the achievable performance of the pull- and push-based systems becomes almost identical.
minimum-expected-delay alternate routing. the authors consider the problem of finding a routing strategy that minimizes the expected delay from every source to a single destination in a network in which each link fails and recovers according to a markov chain. it is assumed that each node knows the current state of its own outgoing links and the state-transition probabilities for every link of the network. it is shown that the general problem is #p-complete, and two special cases are considered: case 1 assumes the network is a directed acyclic graph oriented toward the destination, and case 2 assumes that the link states are independent from slot to slot. for each case, it is proved that the optimal routing strategy has a simple state-independent representation. an efficient algorithm is presented for finding the optimal strategy.
a highly adaptive distributed routing algorithm for mobile wireless networks. we present a new distributed routing protocol for mobile, multihop, wireless networks. the protocol is one of a family of protocols which we term "link reversal" algorithms. the protocol's reaction is structured as a temporally-ordered sequence of diffusing computations; each computation consisting of a sequence of directed link reversals. the protocol is highly adaptive, efficient and scalable; being best-suited for use in large, dense, mobile networks. in these networks, the protocol's reaction to link failures typically involves only a localized "single pass" of the distributed algorithm. this capability is unique among protocols which are stable in the face of network partitions, and results in the protocol's high degree of adaptivity . this desirable behavior is achieved through the novel use of a "physical or logical clock" to establish the "temporal order" of topological change events which is used to structure (or order) the algorithm's reaction to topological changes. we refer to the protocol as the temporally-ordered routing algorithm (tora).
performance analysis of a multicast switch based on multistage interconnection networks. in this paper, we study multicasting in the self-routing multistage interconnection networks (mins) for asynchronous transfer mode (atm) switch architectures. many b-isdn applications require multicast connections in addition to conventional point-to-point connections. this paper presents a novel approach to support multicast connection, on the basis of a restricted address encoding scheme which constructs a short fixed-size multicast header and a recursive scheme that recycles a multicast packet one or more times through the network to send it to the desired destinations. the proposed two-phase multicast algorithm provides deadlock-free multiple multicast connections in min-based atm switches. the emphasis is on analyzing the performance of an unbuffered min-based switch using the multicast algorithm in terms of network throughput. the proposed algorithm can be easily applied to buffered min-based atm switches.
a virtual topology for wdm multihop lightwave networks. wdm multihop networks require that their virtual topology and routing algorithm be simple and efficient while providing extremely high performance. to comply with this, the interconnections of the bidirectional manhattan street network (bmsn) is hierarchically rearranged. the resulting virtual topology constitutes a four-connected msn-based network called the hierarchical msn (hmsn). having the same node degree as bmsn, the proposed hmsn increases no h/w complexity. routing in hmsn is not also a serious burden to the overall processing overhead since it is a simple two-level extension of the deflection routing used in the two-connected msns. nevertheless, hmsn performs better than the competing bmsn. this improvement in network delay and throughput is verified through numerical implementations.
performance analysis of two-level forward error correction for lost cell recovery in atm networks. the major source of errors in b-isdn/atm systems is expected to be buffer overflow during congested conditions, resulting in atm cell losses which degrade the quality of service. it has been shown by many authors that the performance of the end-to-end system can be made much less sensitive to cell loss by means of forward error correction. this paper discusses the use of a two-level forward error correction scheme for virtual channel and virtual path connections in atm networks. the scheme exploits simple block coding and code interleaving simultaneously. the simple block, interleaved, and joint coding schemes are studied and analyzed by using a novel and accurate discrete-time analytical method which enables the burstiness of cell losses be captured precisely. detailed performance calculations, which indicate that it is possible to reduce the cell loss rate by several orders of magnitude over a wide range of network load for various traffic conditions, are discussed, and compared with simulation results. the comparisons show that the method is very accurate for bursty traffic. the advantages of the three coding techniques are quantified for different traffic characteristics and scenarios.
qlwfq: a queue lenght based weighted fair queueing algorithm in atm networks. a work conserving o(1) per-vc queueing algorithm named qlwfq (queue length based weighted fair queueing) for high-speed atm networks is proposed. the basic process in qlwfq is the comparison of the current queue length with the weight when a cell arrival or departure occurs. qlwfq has upward compatibility with fair queueing and fifo, and can be considered to be a simplified version of weighted round robin. a delay bound and a fairness index are derived analytically for the qlwfq algorithm. the simulation results for heavily and lightly loaded conditions are also presented. the analytical and simulation results show that qlwfq achieves a better balance between traffic isolation and traffic sharing than timestamp based algorithms.
m/g/infinity input processes: a versatile class of models for network traffic. we suggest the m|g|\infty input process as a viable model for network traffic due to its versatility and tractability. we characterize the process as short or long--range dependent by means of a simple test. to gauge its performance, we study the large buffer asymptotics of a multiplexer driven by an m|g|\infty input process. the decay rate of the tail probabilities for the buffer content (in steady--state) is investigated using large deviations techniques suggested by duffield and o'connell. we show that the selection of the appropriate large deviations scaling is related to the forward recurrence time of the service time distribution, and a closed--form expression is derived for the corresponding generalized limiting log--moment generating function associated with the input process. we apply our results to cases where the service time distribution in the m|g|\infty input model is (i) rayleigh (ii) gamma (iii) geometric (iv) weibull (v) log--normal and (vi) pareto -- cases (v) and (vi) have recently been found adequate for modeling packet traffic streams in certain networking applications. finally, we comment on the insufficiency of the short-- vs. long--range dependence characterization of an input process as a means to accurately describe the corresponding buffer dynamics.
on the performance behavior of atm end-stations. shaping of traffic at its source is a prominent congestion control solution in atm networks. the "leaky bucket" with a "cell spacer" is a very popular traffic shaping approach. by sizing the leaky bucket and spacer parameters, an end-station shapes its traffic to conform to a "good behavior" contract with the network. the leaky bucket delays the transmission of selected number of cells, while the spacer forces a minimum time-distance between transmitted cells. when a contracted transmission rate is close to the traffic generation rate by the end-station, this traffic stream will utilize most of the bandwidth available on its virtual connection. the high utilization of such a connection leads to large queues of frames and cells at the end-station, with high adverse consequences to the end-to-end delay and jitter. in this paper, based on the negotiated traffic parameters and source traffic characteristics, we study, through simulations, the contribution of the leaky bucket plus cell spacer subsystem to the delay and jitter in an end-station. we also study the distribution of the size of the burst of cells leaving the end-station and entering the network. finally, we derive the theoretical upper bound for the size of bursts of cells.
an asymmetric protocol for digital cellular communications. describes the design, validation, implementation and performance of an asymmetric link-layer protocol for a wireless link. the motivation for designing a new link-layer protocol is to obtain better performance in terms of end-to-end throughput and latency by correcting errors in an unreliable wireless link in addition to end-to-end correction rather than by correcting errors only by end-to-end retransmissions. the protocol described concentrates on asymmetry, although the concept of adaptive forward error correction is briefly introduced. the protocol also supports mobility. the asymmetry is needed in the design because the wireless terminals have limited power and smaller processing capability than the base stations. the key ideas in the design consist of placing the bulk of the intelligence in the base station as opposed to placing it symmetrically, in requiring the wireless terminal to combine several acknowledgments into a single acknowledgment to conserve power, and in designing the base stations to send periodic status messages, while making the acknowledgment from the wireless terminal event driven. the asymmetry in the protocol design results in a one-third reduction of the compiled code and a two-thirds reduction of processing overhead in the wireless terminal. some performance results are also presented.
locating faults in a systematic manner in a large heterogeneous network. presents several techniques for locating faults in a network which is modeled as an undirected graph. the novelty of these techniques lies in combining the process of collecting status information (from each network element) with the process of locating a fault, which is completely different from the existing techniques in which fault location begins after all the status information has been collected. the techniques presented in the paper have different characteristics and hence they are applicable in different networking environments. however, an intelligent combination of the techniques can be used in a large scale heterogeneous network in an efficient manner for locating faults.
a scalable approach to the partition of qos requirements in unicast and multicast. supporting quality of service (qos) in large-scale broadband networks poses major challenges, due to the intrinsic complexity of the corresponding resource allocation problems. an important problem in this context is how to partition qos requirements along a selected topology (path for unicast and tree for multicast). as networks grow in size, the scalability of the solution becomes increasingly important. this calls for efficient algorithms, whose computational complexity is less dependent on the network size. in addition, recently proposed precomputation-based methods can be employed to facilitate scalability by significantly reducing the time needed for handling incoming requests.we present a novel solution technique to the qos partition problem(s), based on a "divide-and-conquer" scheme. as opposed to previous solutions, our technique considerably reduces the computational complexity in terms of dependence on network size; moreover, it enables the development of precomputation schemes. hence, our technique provides a scalable approach to the qos partition problem, for both unicast and multicast. in addition, our algorithms readily generalize to support qos routing in typical settings of large-scale networks.
incentive pricing in multi-class communication networks. we consider a communication network that offers multi-class services to multiple types of traffic. users choose service classes so as to optimize their own performance. the network associates with each traffic type a nominal service class. optimal prices should provide incentives for the users to assign each traffic type to its nominal service class. we establish necessary and sufficient conditions for the existence of optimal prices and provide an algorithm for their computation. we indicate that optimal prices can tolerate fluctuations in the various parameters. we then devise a distributed algorithm, with which the network can compute optimal prices even when it does not have sufficient knowledge on the traffic characteristics. next, we consider an extended model which explicitly includes congestion effects. a key factor which emerges here is the amount of traffic at the disposal of each user. we consider the typical cases of individual, social and type optimization, for which we generalize our results.
analytical and numerical results for feedback based flow control of b-isdn/atm networks with significant propagation delays. we consider a system comprising of a single bottleneck node fed by multiple markov modulated fluid sources each of which is policed by a corresponding access regulator that marks all excess traffic as well as drops some of the excess traffic. the amount of excess traffic released is varied dynamically based on delayed feedback from the bottleneck. we present analytical and numerical results for this model that allow us to study the role of delayed feedback vis-a-vis certain time constants and traffic parameters associated with the system. in particular we show that even for a large propagation delay such as that required for the length of the continental usa the feedback policy is more effective, though the relative improvement of the feedback policy decreases as the delay increases. we also find that the feedback policy is most effective when the sources are moderately bursty.
dynamic behavior of feedback congestion control schemes. the paper examines the asymptotic behavior of solutions of a simple network model using feedback control under the presence of delays. it shows numerically the existence of complex asymptotic behavior dependent on both parameter values and initial conditions. the presence of multiple asymptotic periodic orbits of different characteristics at the same parameter values indicates that the interaction of asymptotic behavior with parameter ranges and initial histories is an extremely delicate matter.
a scheme for smoothing delay-sensitive traffic offered to atm networks. the authors present a scheme for smoothing delay-sensitive traffic offered to an asynchronous transfer mode (atm) network. they outline such a smoothing scheme, which, when applied to variable bit rate (vbr) coded video traffic, is both optimal and avoids violation of delay constraints. the scheme is based on the assumption that recent behavior of the traffic stream can be used to predict the behavior of the input stream in the near future. the effectiveness of the scheme was evaluated by simulation. the conclusion is that even with a rudimentary forecasting rule, smoothing can lower cell losses and increase the effectiveness of vbr schemes for video transmission
scalable, low-overhead network delay estimation. estimating the network delays between each pair of nodes in a multicast session is the key parameter in reliable multicast; it is used, among other things, in suppressing the implosion of request and repair packets, and in detecting congestion. existing implementations use $o(n)$ multicasts with $o(n)$ message size each (total of $o(n^2)$ bits); here, $n$ is the session size. we present a new protocol that requires $o(n)$ multicasts only with $o(1)$ message size each. we also present another protocol that estimates delays from each receiver to the sender without causing feedback implosion. because of reduced message complexity and feedback implosion, these protocols enhance the scalability of reliable multicast. furthermore, they do not require synchronized clocks, or any knowledge of network topology or the session size.
leaky bucket access control for vbr mpeg video. the leaky bucket (lb) access control scheme has been widely proposed as the usage parameter control (upc) mechanism at the user-network interface (uni) for b-isdn. an important goal for any upc scheme is that it be able to accommodate a wide range of services. in this paper, we investigate the performance of the lb as an access control mechanism for transmission of variable bit rate (vbr) mpeg video. in particular, we focus on the following issues: 1) the requirements for lossless video transmission, 2) the trade-offs between token pool size and token regeneration rate, 3) the effect of traffic smoothing and 4) the performance of different encoded video sequences. finally, we present a new technique for vbr video transmission using multiple lb's and we discuss the advantages of this techniques when cell losses occur.
analysis of multipath impulse response of diffuse and quasi-diffuse optical links for irr-wlan. this paper studies the variation on the power budget, in an infrared optical link for indoor channels with multipath propagation. the multipath propagation produces heavy distortion over the received signal and reduces the maximum baud rate for a given bit error rate. focusing on ir wireless local area network (irwlan), we study some emitter and receiver configurations. in order to allow computer portability these links can be diffuse or quasi-diffuse. these channels do not rely upon the line-of-the-sight path. this works deals not only with the total received power, but with its time and spatial distribution. this paper considers the channel as characterized by its channel transfer function in a deterministic way. this is a good approximation if the variations in the environmental conditions are slow enough compared with the baud rate of the communication system. the source is an ir emitter diode (ired) with different values of directivity, pointing to a reflecting surface, while the receiver is a photodiode characterized through its field of view (f.o.v.) value. the results show that an optical q-diffuse link improves the performances of a diffuse one. we use for the comparative analysis the rms spread delay of the impulse response, the spatial distribution of received power and its standard deviation from the mean. we present extensive simulation results, an emitter configuration and the first measured results obtained using an apd as receiver.
analysis of a queueing network model with class dependent window flow control. the authors consider a multiclass open queueing network with class-dependent window flow control; that is, the total number of jobs of each class that may be present in the network cannot exceed a given value. a job that arrives at the network during the time that the current number of jobs of the same class is equal to the population constraint, is forced to wait in an external queue. a method is presented for obtaining an approximate solution of such a queueing network. the method is based on the use of an equivalent closed queuing network model, which is analyzed using an approximate product-form solution technique. the performance parameters of the original open queueing network are easily derived from the equivalent closed queueing network. numerical results show that this method is fairly accurate
connection preemption: issues, algorithms, and a simulation study. connection preemption can be a means to provide available and reliable services to high-priority connections when a network is heavily loaded and connection request arrival patterns are unknown, or when the network experiences link or node failures. we present a simulation study of preemption in a general connection-oriented network setting. based on the observations made in this study, we have developed two optimal connection preemption selection algorithms that operate in a decentralized/distributed network where individual link managers run the algorithm for connection preemption selection on their outgoing links. the first algorithm optimizes the criteria of (i) the number of connections to be preempted, (ii) the bandwidth to be preempted, and (iii) the priority of connections to be preempted, in that order, and has polynomial complexity. the second algorithm optimizes the criteria of (i) the bandwidth to be preempted, (ii) the priority of connections to be preempted, and (iii) the number of connections to be preempted, in that order, and has exponential complexity. we conclude that the polynomial algorithm is almost as good as the exponential algorithm in terms of overall network performance.
performance of packet video with combined error recovery and concealment. in this paper we analyze the performance of a video transport across an atm network that uses both retransmission and concealment to recover from errors due to cell loss resulting from congestion. we limit the number of retransmission attempts to one. if a frame is still in error after one retransmission attempt, the remaining errors are concealed. we obtain analytic expressions for the peak signal to noise ratio (psnr) with combined retransmission and concealment. the analysis shows that significant improvement in the signal to noise ratio of the reconstructed picture can be achieved if retransmission and concealment are used together.
multi-class connection admission control policy for high speed atm switches. broadband networks based on atm have to support multiple classes of services with widely different traffic characteristics and quality of services. in this paper, we propose and develop a multi-class connection admission control (cac) policy that supports cell loss and delay requirements. in this model-based cac, the source traffic is described in terms of the usage parameter control (upc) parameters. through careful analysis and approximations, we derive simple closed-form formulas to calculate the bandwidth required to meet guarantees on quality of service (qos). while being robust, the cac achieves a high level of resource utilization and can be easily implemented for real-time admission control.
dynamic bandwidth allocation in broadband isdn using a multilevel optimal control approach. this paper presents a novel scheme for the dynamic allocation of bandwidth at the virtual path level in b-isdns. a fluid flow model is developed to describe the time varying mean behaviour of a virtual path and serves as a state variable model. a multilevel optimal control theoretic approach is used in conjunction with the state model to derive a coordinated decentralised algorithm for virtual path bandwidth allocation. the performance of the proposed scheme is evaluated using simulation.
the rate mismatch problem in heterogeneous abr flow control. because the atm forum does not standardize the abr flow control algorithm that an atm switch should run, some atm networks are likely to contain switches that run different abr flow control algorithms. even if all the switches within a ``cloud'' of switches use the same algorithm, individual clouds (each with its own algorithm) will be interconnected by virtual circuits. virtual circuits which traverse multiple clouds will therefore be controlled by two different flow control algorithms concurrently. in this paper we explore some of the ramifications of mixing different flow control algorithms in the same atm network. we identify the rate mismatch problem, which arises when a nonbottleneck switch (that uses one algorithm) interferes with the control of the bottleneck switch (that uses another algorithm). we formulate a hypothesis that states the conditions that lead to the rate mismatch problem. these conditions identify a specific class of problematic topologies. we validate the hypothesis formally and prove that rate mismatch causes unfairness. using four different algorithms, in combinations of two at a time, we illustrate the interoperability of abr flow control algorithms.
multiwavelength optical networks with limited wavelength conversion. this paper proposes optical wavelength division multiplexed (wdm) networks with limited wavelength conversion that can efficiently support lightpaths (connections) between nodes. each lightpath follows a route in the network and must be assigned a channel along each link in its route. the load lambdamax of a set of lightpath requests is the maximum over all links of the number of lightpaths that use the link. at least lambdamax wavelengths will be needed to assign channels to the lightpaths. if the network has full wavelength conversion capabilities then lambdamax wavelengths are sufficient to perform the channel assignment.we propose ring networks with fixed wavelength conversion capability within the nodes that can support all lightpath request sets with load lambdamax at most w-1, where w is the number of wavelengths in each link. we also propose ring networks with selective pairwise wavelength conversion capability within the nodes that can support all lightpath request sets with load lambdamax at most w. we also propose a star network with fixed wavelength conversion capability at its hub node that can support all lightpath request sets with load lambdamax at most w. we extend this result to tree networks and networks with arbitrary topologies. these results show that significant improvements in traffic-carrying capacity can be obtained in wdm networks by providing very limited wavelength conversion capability within the network.
on optimal call admission control in cellular networks. two important quality-of-service (qos) measures for current cellular networks are the fraction of new and handoff ``calls'''' that are blocked due to unavailability of ``channels'''' (radio and/or computing resources). based on these qos measures, we consider optimal admission control policies for three problems: minimizing a linear objective function of the new and handoff call blocking probabilities (minobj), minimizing the new call blocking probability with a hard constraint on the handoff call blocking probability (minblock) and minimizing the number of channels with hard constraints on both the blocking probabilities (minc). we show that the well-known {\it guard channel policy is optimal for the minobj problem}, while a new {\it fractional guard channel policy is optimal for the minblock and minc problems}. the guard channel policy reserves a set of channels for handoff calls while the fractional guard channel policy effectively reserves a non-integral number of guard channels for handoff calls by rejecting new calls with some probability that depends on the current channel occupancy. it is also shown that the fractional policy results in significant savings (20-50\%) in the new call blocking probability for the minblock problem and provides some, though small, gains over the integral guard channel policy for the minc problem. we see that the fractional guard channel policy offers more flexibility than the guard channel policy in the sense of a richer set of parameters but the algorithms developed in the paper for determining the optimal parameter settings for the fractional policy are computationally inexpensive. finally, we briefly explore the possibility of exploiting the combination of these features of the fractional guard channel policy and its concomitant algorithms for real-time control of cellular networks.
average waiting time profiles of uniform dqdb model. the distributed queue dual bus (dqdb) system consists of a linear arrangement of n nodes that communicate with each other using two contra-flowing buses; the nodes use an extremely simple protocol to send messages on these buses. this simple, but elegant, system has been found to be very challenging to analyze. we consider a simple and uniform abstraction of this model to highlight the fairness issues in terms of average waiting time. we introduce a new approximation method to analyze the performance of dqdb system in terms of the average waiting time of a node expressed as a function of its position. our approach abstracts the intimate relationship between the load of the system and its fairness characteristics, and explains all basic behavior profiles of dqdb observed in previous simulation. for the uniform dqdb with equal distance between adjacent nodes, we show that the system operates under three basic behavior profiles and a finite number of their combinations that depend on the load of the network. consequently, the system is not fair at any load in terms of the average waiting times. in the vicinity of a critical load of 1 - 4/n, the uniform network runs into a state akin to chaos, where its behavior fluctuates from one extreme to the other with a load variation of 2/n. our analysis is supported by simulation results. we also show that the main theme of the analysis carries over to the general (non-uniform) dqdb; by suitably choosing the inter-node distances, the dqdb can be made fair around some loads, but such system will become unfair as the load changes.
optimal configuration of ospf aggregates. open shortest path first (ospf) is a popular protocol for routing within an autonomous system (as) domain. in order to scale for large networks containing hundreds and thousands of subnets, ospf supports a two-level hierarchical routing scheme through the use of ospf areas. subnet addresses within an area are aggregated, and this aggregation is a crucial requirement for scaling ospf to large as domains, as it results in significant reductions in routing table sizes, smaller link-state databases, and less network traffic to synchronize the router link-state databases. on the other hand, address aggregation also implies loss of information about the length of the shortest path to each subnet, which in turn, can lead to suboptimal routing.in this paper, we address the important practical problem of configuring ospf aggregates to minimize the error in ospf shortest-path computations due to subnet aggregation. we first develop an optimal dynamic programming algorithm that, given an upper bound k on the number of aggregates to be advertised and a weight assignment function for the aggregates, computes the k aggregates that result in the minimum cumulative error in the shortest-path computations for all source-destination subnet pairs. subsequently, we tackle the problem of assigning weights to ospf aggregates such that the cumulative error in the computed shortest paths is minimized. we demonstrate that, while for certain special cases (e.g., unweighted cumulative error) efficient optimal algorithms for the weight assignment problem can be devised, the general problem itself is np-hard. consequently, we have to rely on search heuristics to solve the weight assignment problem. to the best of our knowledge, our work is the first to address the algorithmic issues underlying the configuration of ospf aggregates and to propose efficient configuration algorithms that are provably optimal for many practical scenarios.
source time scale and optimal buffer/bandwidth trade-off for regulated traffic in an atm node. in this paper, we study the problem of resource allocation and control for an atm node with regulated traffic. both guaranteed lossless service and statistical service with small loss probability are considered. we investigate the relationship between source characteristics and the buffer/bandwidth trade-off under both services.our contributions are the following. for guaranteed lossless service, we find that the optimal resource allocation scheme suggests a time scale separation of sources sharing an atm node with finite bandwidth and buffer space, with the optimal buffer/bandwidth trade-off is determined by the sources' time scale. for statistical service with a small loss probability, we present a new approach for estimating the loss probability in a shared buffer multiplexor with the so called ``extremal'' on-off, periodic sources. under this approach, the optimal resource allocation for statistical service is achieved by maximizing both the benefits of buffering sharing and bandwidth sharing. the optimal buffer/bandwidth trade-off is again determined by time scale separation.besides their obvious application to resource allocation and call admission control, our results have many other implications in network design and control such as network dimensioning and traffic shaping.
the linearity of low frequency traffic flow: an intrinsic i/o property in queueing systems. consider a class of queueing systems which can be modeled by a finite quasi-birth-death (qbd) process. in this paper we develop a powerful computational technique for spectral analyses (i.e. second-order statistics) of output, queue and loss. emphasis is placed on output power spectrum and input-output coherence function in response to various input power spectral properties and system parameters. the coherence function is defined to measure linear relationship between input and output processes. a key technical contribution of this paper is the exploration of linearity of low frequency traffic flow. through the evaluation of the coherence function, one can identify a so-called nonlinear break frequency, /spl omega//sub b/, under which the low frequency traffic stay intact via a queueing system. such a low frequency i/o linearity plays an important role in characterizing the output process, which may form a partial input to other "downstream" queues of the network. after all, it is the "upstream" output low frequency characteristics that will have most impact on the "downstream" queueing performance. our study further indicates that the link capacity required by an input process is essentially characterized by its maximum input rate filtered at /spl omega//sub b/.
on optimal placement of erasure nodes on a dual bus network. erasure node placement on the distributed and queue dual bus (dqdb) network is a well investigated problem. for general traffic conditions, achieving maximum throughput by placing a minimum number of erasure nodes optimally is known as the optimal placement of erasure nodes. to date, all the solutions proposed are either of exponential time complexity of generate suboptimal placement or work under impractical assumptions. the authors present a polynomial time algorithm that obtains optimal placement of erasure nodes for general traffic conditions. they derive a closed form expression for maximum achievable throughput and show that several bounds proposed in the literature can be obtained as special cases from the method.
implementation of a secure bridge in an ethernet environment. the implementation of a security system that caters to the needs of an operating network, the upc net, is presented. the security services that this system offers are confidentiality and authentication (origin authentication and data integrity) of data transmitted on the main segment of an extended ethernet network. the system has been designed to specifically function in the extended ethernet network of the polytechnic university of catalonia. the security system has the following characteristics: it provides cryptographic security services, it does not interfere with the operation of unprotected systems, and it supports transparent operations for protected systems
integrated network management: technologies and implementation experience. an analysis of the requirements and key enabling technologies for the development of intelligent and integrated enterprise network management systems is presented. in particular, the analysis demonstrates the advantages of exploiting the synergy of object-oriented and knowledge-based technologies, together with the emerging network management standard protocols between conformant management entities. the experience with applying these concepts to the evolution of the management system for large multivendor data communication networks is outlined
bandwidth allocation for broadband multichannel systems. the authors examine an optimal bandwidth allocation scheme for multichannel switching systems to switch trunk groups. this multichannel switching system features a simple architecture, high throughput, high channel utilization, and other properties such as preserving packet sequence, being robust to unbalanced input traffic loads, providing fair access to network transmission resources, and fast packet processing via a pipeline structure. numerical results show that the multichannel system can achieve a throughput of 91% per channel for a trunk group of 32 channels while also providing very low average cell delay performance in the presence of correlated inputs
design and analysis of a credit-based controller for congestion control in b-isdn/atm networks. a credit-based controller (cbc), which has a provision for cell tagging, is proposed for usage parameter control (upc). similar in concept to the leaky bucket, the cbc has a credit counter and a data buffer. credits are accumulated at a rate initiated from the network (equivalent to the sustainable cell rate), and depleted at a rate pertaining to the network traffic load. a source has the prerogative whether or not to send its cells as tagged cells when the credit level is nonpositive. the queueing behavior of the cbc fed by a marcov modulated source, is analyzed using a stochastic fluid flow model. it is shown that the performance of the cbc can be altered by tuning the weighting parameter within the cbc. also, adjustments can be made to balance the ratio of tagged and untagged cells sent into the network.
information exchange protocol: a new approch for future network management. the paper proposes a new approach to classify the network management information formally and the authors intend to support the description of the network states and events. the classification concept described is slightly different from the approaches of cmip (common management information protocol). the authors apply the situation classification capability extended from those found in description logic, in order to organize the state and event for network management in hierarchical structure. this approach is an extension of current cmip approach with combined classification facility of relationship, concept and objects.
a comparison of application-level and router-assisted hierarchical schemes for reliable multicast. one approach to achieving scalability in reliable multicast is to use a hierarchy. a hierarchy can be established at the application level, or by using router-assist. with router-assist we have more fine-grain control over the placement of error-recovery functionality, therefore, a hierarchy produced by assistance from the routers is expected to have better performance. in this paper, we test this hypothesis by comparing two schemes, one that uses an application-level hierarchy (alh) and another that uses router-assisted hierarchy (rah). contrary to our expectations, we find that the qualitative performance of alh is comparable to rah. we do not model the overhead of creating the hierarchy nor the cost of adding router-assist to the network. therefore, our conclusions inform rather than close the debate of which approach is better.
a scalable architecture for fair leaky-bucket shaping. this paper presents a shaper architecture that scales to a large number of connections with diverse burstiness and bandwidth parameters. the architecture arbitrates fairly between connections with conforming cells by carefully integrating leaky-bucket traffic shaping with rate-based scheduling algorithms. through a careful combination of per-connection queueing and approximate sorting, the shaper performs a small, bounded number of operations in response to each arrival and departure, independent of the number of connections and cells. to handle a wider range of rate parameters, a hierarchical arbitration scheme can reduce the implementation overheads and the interference between competing connections. simulation experiments demonstrate that the architecture limits shaping delay and traffic distortions, even under heavy congestion.
admission control for hard real-time connections in atm lans. the cac algorithm must efficiently determine if a new connection can be admitted by verifying that its qos requirements can be met without violating those of pr eviously admitted connections. in hard real-time systems, the qos requirements are specified in terms of end-to-end deadlines and no cell loss due to buffer ov erflow. a cac algorithm must account for interdependencies among connections ca used by statistical multiplexing of cells in atm networks. furthermore, arbitra ry topology of the network may lead to cyclic dependencies among various connect ions. we present an efficient cac algorithm that addresses the above issues. t he algorithm uses a traffic descriptor called the maximum traffic rate function to effectively compute bounds on end-to-end delays of connections and buffer req uirements within the network. our work differs from most previous work in that it does not require traffic restoration inside the network.
a unified framework and algorithm for (t/f/c)dma channel assignment in wireless networks. channel assignment problems in the time, frequency and code domains have thus far been studied separately. exploiting the similarity of ``constraints'' that characterize assignments within and across these domains, we introduce the first unified framework for the study of assignment problems. our framework identifies eleven atomic constraints underlying most current and potential assignment problems, and characterizes a problem as a combination of these constraints. based on this framework, we present a unified algorithm for efficient (t/f/c)dma channel assignments to nodes or to inter-nodal links in a (multihop) wireless network. the algorithm is parametrized to allow for tradeoff-selectable use as three different variants called rand, mnf, and pmnf. using theoretical analysis, we show that the worst-case performance guarantee of pmnf is an order of magnitude better than that of the traditional rand and mnf for most networks. we also experimentally study the relative performance for one node and one link assignment problem. we observe that pmnf performs the best, and that a larger fraction of unidirectional links degrades the performance in general.
mtcp: scalable tcp-like congestion control for reliable multicast. we present mtcp, a congestion control scheme for large-scale reliable multicast. congestion control for reliable multicast is important, because of its wide applications in multimedia and collaborative computing, yet non-trivial, because of the potentially large number of receivers involved. many schemes have been proposed to handle the recovery of lost packets in a scalable manner, but there is little work on the design and implementation of congestion control schemes for reliable multicast. we propose new techniques that can effectively handle instances of congestion occurring simultaneously at various parts of a multicast tree.our protocol incorporates several novel features: (1) hierarchical congestion status reports that distribute the load of processing feedback from all receivers across the multicast group, (2) the relative time delay concept which overcomes the difficulty of estimating round-trip times in tree-based multicast environments, (3) window-based control that prevents the sender from transmitting faster than packets leave the bottleneck link on the multicast path through which the sender's traffic flows, (4) a retransmission window that regulates the flow of repair packets to prevent local recovery from causing congestion, and (5) a selective acknowledgment scheme that prevents independent (i.e., non-congestion-related) packet loss from reducing the sender's transmission rate. we have implemented mtcp both on udp in sunos 5.6 and on the simulator ns, and we have conducted extensive internet experiments and simulation to test the scalability and inter-fairness properties of the protocol. the encouraging results we have obtained support our confidence that tcp-like congestion control for large-scale reliable multicast is within our grasp.
layered multicast recovery. we study the problem of localizing repair packets when packets are lost. when repair packets are multicasted, a highly lossy receiver may swamp the entire multicast ``group'''' with duplicate repair packets thereby wasting bandwidth; thus, the protocols need repair locality. we present a multicast layering scheme where the sender proactively distributes fec repair packets among multiple multicast groups. receivers can selectively tune in to a subset of these multicast groups to obtain number of packets close to the number they require. we develop an efficient algorithm that dynamically determines the optimal distribution of fec repair packets to a given (small constant) number of multicast groups. the running time of this algorithm is independent of the number of receivers in the multicast session, and is hence highly scalable. however, the optimal algorithm requires the knowledge of the fec repair requirements of all the receivers in the multicast group, and hence is subject to the implosion problem. to handle the implosion problem, we develop a heuristic algorithm that achieves repair locality very similar to that of the optimal algorithm, but does not require as much global knowledge. our multicast layering scheme can be integrated into many known reliable multicast protocols to enhance their scalability. for concreteness, we focus on singly scoped and hierarchically scoped srm as well as tree-based protocols and present combined protocols incorporating our solutions into each of them. our simulation experiments suggest that our solutions can substantially enhance the scalability of these reliable multicast protocols.
design of logical topologies for wavelength-routed all-optical networks. this paper considers the problem of designing a logical topology over a wavelength-routed all-optical network physical topology. the physical topology consists of the nodes and fiber links in the network. on an all-optical network physical topology, we can set up lightpaths between pairs of nodes, where a lightpath represents a direct optical connection without any intermediate electronics. the set of lightpaths along with the nodes constitutes the logical topology. for a given network physical topology and traffic pattern (relative traffic distribution among the source-destination pairs), our objective is to design the logical topology and the routing algorithm on that topology so as to maximize the network throughput while constraining the average delay seen by a source-destination pair and the amount of processing required at the nodes (degree of the logical topology). we will see that ignoring the delay constraints can result in fairly convoluted logical topologies with very long delays. on the other hand, in all our examples, imposing it results in a minimal reduction in throughput. while the number of wavelengths required to imbed the resulting logical topology on the physical all-optical topology is also a constraint in general, we find that in many cases of interest this number can be quite small. we formulate the combined logical topology design and routing problem described above (ignoring the constraint on the number of available wavelengths) as a mixed integer programming problem which we then solve for a number of cases of a 6-node network. since this programming problem is computationally intractable for larger networks, we split it into two subproblems: logical topology design, which is computationally hard and will probably require heuristic algorithms, and routing, which can be solved by a linear program. we then compare the performance of two heuristic topology design algorithms (that do take wavelength assignment constraints into account) against that of randomly generated topologies.
minimizing the number of optical amplifiers needed to support a multi-wavelength optical lan/man. optical networks based on passive star couplers and employing wavelength-division multiplexing (wdm) have been proposed for deployment in local and metropolitan areas. amplifiers are required in such networks to compensate for the power losses due to splitting and attenuation. however, an optical amplifier has constraints on the maximum gain and the maximum output power it can supply; thus optical amplifier placement becomes a challenging problem. the general problem of minimizing the total amplifier count, subject to the device constraints, is a mixed-integer non-linear problem. previous studies have attacked the amplifier-placement problem by adding the ``artificial'' constraint that all wavelengths, which are present at a particular point in a fiber, be at the same power level. in this paper, we present a method to solve the minimum-amplifier-placement problem while avoiding the equally-powered-wavelength constraint. we demonstrate that, by allowing signals to operate at different power levels, our method can reduce the number of amplifiers required in several small to medium-sized networks.
improving reliable multicast using active parity encoding services (apes). traditional reliable multicast protocols for the internet require large amounts of bandwidth to support reliable delivery of data to numerous receivers. in this paper, we propose and evaluate novel protocols that combine active repair service (a.k.a. local recovery) and parity encoding (a.k.a. forward error correction or fec) techniques. we show that compared to other repair service protocols, our protocols require less buffer inside the network, and maintain the low bandwidth requirements of previously proposed repair service / fec combination protocols. our protocols also reduce the amount of fec processing at repair servers, moving more of this processing to the end-hosts. last, we examine repair service / fec combination protocols in an environment where loss rates are different across domains within the network. we find that in such environments, repair services are more effective than fec at reducing bandwidth utilization. furthermore, adding fec to a repair services protocol not only reduces buffer requirements at repair servers, but also reduces bandwidth utilization in domains with high loss, or in domains with large populations of receivers.
the effect of bottleneck service rate variations on the performance of the abr flow control. one of the main features of abr services is the employment of a rate-based flow control mechanism. feedback from the network switches to the end systems gives users the information necessary to adjust their transmission rates appropriately according to the current network load. this type of control has been investigated to some extent, assuming a constant transmission capacity on a bottleneck link.in this paper we develop a discrete-time analysis to study the effect of bottleneck service rate variations on the performance of the abr flow control mechanism. looking at real systems, such variations occur on the one hand due to the establishment and release of atm connections and on the other hand due to the varying bandwidth demand of vbr connections. to model the rate variations, the bottleneck service rate is assumed to follow a general probability density function.
the converging flows problem: an analytical study. when multiple systems are interconnected through a high-speed backbone network and communicate without resource reservation, under certain conditions a severe overload can appear at the destination system. this problem, called the converging flows problem, can be alleviated by use of a feedback control mechanism that coordinates the emission of the sources. the authors present a dynamic resource management mechanism that both controls the losses at the congested node and attempts to optimize resource utilization. in fact it steers the entire system into a desirable operating regime. they study analytically the behavior of the system under such a control and show that it can be reduced with a few approximations to a well-known physical system. this allows to infer optimal values for the parameters of the command algorithm, and the authors show that these values have a natural physical meaning to the system.
performance of congestion control mechanisms in wormhole routing networks. in order to minimize latency in high-speed interconnection networks, the wormhole routing technique can be employed. with this technique, a switch transmits an incoming message as soon as it receives it, without waiting for the entire message. the problem then is that a message stretches over several links and locks network resources, thus making a contention situation possible. two principal congestion control mechanisms can be considered, backpressure flow control and deflection routing. the performance of these mechanisms depends both on the traffic characteristics and on the network topology. in order to compare them, we study analytically the behavior of a wormhole routing network model with random input traffic under both policies. we estimate the probability of collision between messages and express the average message transit delay as a function of the offered load. simulation provides a good confirmation for the analytical results. this study gives us an understanding of the behavior of the system under different resource management policies.
a linear control approach to explicit rate feedback in atm networks. rate-based feedback congestion control has been proposed as a form of traffic management for available bit rate traffic in atm networks. this paper discusses applying linear control theory to these algorithms. a congestion control scheme for simple networks is designed and analyzed using the tools of classical control theory. this allows insight into the trade-offs in such schemes and suggests approaches to larger networks.
paging cost minimization under delay constraints. efficient paging procedures help minimize the amount of bandwidth expended in locating a mobile unit. given a probability distribution on user location, the optimal paging strategy which minimized the expected number of locations polled e[l] is to query each location sequentially in order of decreasing probability. however, since sequential search over many locations may impose unacceptable polling delay, d, optimal paging subject to delay constraints is considered. substantial reductions in e[l] can be had even after moderate constraints are imposed on acceptable d (i.e., d/spl les/3) since all methods of mobility management eventually reduce to considering a time-varying probability distribution on user location, this work should be applicable to a wide range of problems in the area. most notably those with additive cost structures.
multicast routing with end-to-end delay and delay variation constraints. we study the problem of constructing multicast tree to meet the quality of service requirements of real-time, interactive applications operating in high-speed packet-switched environments. in particular, we assume that multicast communication depends on (a) bounded delay along the paths from the source to each destination, and (b) bounded variation among the delays along these paths. we first establish that the problem of determining such a constrained tree is np-complete. we then derive heuristics that demonstrate good average case behavior in terms of the maximum inter-destination delay variation of the final tree. in addition, our heuristics achieve their best performance under conditions typical of multicast scenarios in high-speed networks. we also show that it is possible to dynamically reorganize the initial tree in response to changes in the destination set, in a way that is minimally disruptive to the multicast session.
topology identification for traffic and configuration management in dynamic networks. the authors address the problem of identifying the topology of a network from data collected at a designated node (possibly one of the network nodes). the data considered are descriptions of the local neighborhood about each node, which specify the identities of the node and of its neighbors. these data are neither required to be correct nor complete. the authors propose a model that describes and relates the network topology and the data. they define costs associated with this model, and reduce the identification problem to a combinational optimization problem with and an objective function based on these costs. a pseudo-polynomial-time algorithm is derived, which yields a local minimum of the objective function. the local minimum appears to be a reasonable solution, as shown by a range of examples
automatic alarm correlation for fault identification. in communication networks, a large number of alarms exist to signal any abnormal behavior of the network. as network faults typically result in a number of alarms, correlating these different alarms and identifying their source is a major problem in fault management. the alarm correlation problem is of major practical significance. alarms that have not been correlated may not only lead to significant misdirected efforts, based on insufficient information, but may cause multiple corrective actions (possibly contradictory) as each alert is handled independently. the paper proposes a general framework to solve the alarm correlation problem. the authors introduce a new model for faults and alarms based on probabilistic finite state machines. they propose two algorithms. the first one acquires the fault models starting from possibly incomplete and incorrect date. the second one correlates alarms in the presence of multiple faults and noisy information. both algorithms have polynomial time complexity, use an extension of the viterbi algorithm to deal with the corrupted data, and can be implemented in hardware. as an example, they are applied to analyse faults using data generated by the ans (advanced network and services, inc.)/nsf t3 network.
delay analysis for forward signaling channels in wireless cellular network. we consider connection-oriented wireless cellular networks. such second generation systems are circuit-switched digital networks which employ dedicated radio channels for the transmission of signaling information. a forward signaling channel is a common signaling channel assigned to carry the multiplexed stream of paging and channel-allocation packets from a base station to the mobile stations. similarly, for atm wireless networks, paging and virtual-circuit-allocation packets are multiplexed across the forward signaling channels as part of the virtual-circuit set-up phase. the delay levels experienced by paging and channel-allocation packets are critical factors in determining the efficient utilization of the limited radio channel capacity. a multiplexing scheme operating in a &ldquo;slotted mode&rdquo; can lead to reduced power consumption at the handsets, but may in turn induce an increase in packet delays. in this paper, focusing on forward signaling channels, we present schemes for multiplexing paging and channel-allocation packets across these channels, based on channelization plans, access priority assignments and paging group arrangements. for such multiplexing schemes, we develop analytical methods for the calculation of the delay characteristics exhibited by paging and channel-allocation packets. the resulting models and formulas provide for the design and analysis of forward signaling channels for wireless network systems.
an all-optical wavelength-division meshed-ring packet-switching network. introduces an all-optical wavelength-division packet-switching meshed-ring local/metropolitan area communication network. this architecture, known as smartnet (scalable multi-channel adaptable ring terabit network), allows the proposed network to offer a significant increase in the throughput capacity realized by any local/metropolitan area shared-medium network. the smartnet architecture is atm capable and fits naturally with, and takes best advantage of, the kinds of high speed optoelectronic and optical components that can actually be constructed. for certain meshed-ring regular physical topologies, an upper bound on the network's throughput efficiency is derived. specific network configurations are demonstrated which achieve a throughput efficiency level which is close to 90% of this bound. such network structures exhibit a throughput capacity level which is 80% higher than that realized by traditional (non-meshed) ring networks.
resource reservation in advance in heterogeneous networks with partial atm infrastructures. resource reservation in advance (rera) enables scheduling and allocation of resources at an early stage in time. this way, the availability of resources can actually be guaranteed for the point in time when the resources are needed. as opposed to that, current reservation protocols such as rsvp perform an "immediate" reservation without advance scheduling. they can therefore suffer shortage of resources with subsequent rejection of applications.this paper describes our new approach for providing resource reservation in advance in atm networks. as a foundation, we first present experiences of ipng and rsvp over atm. based on this work, we then discuss major design issues of an appropriate rera solution. important aspects are the signaling model for rera, the admission control strategy, the duration of connections, and various other time-related parameters. we also discuss our ongoing implementation of rera as an extension of rsvp and outline directions for future research in this area.
measuring the performance of parallel message-based process architectures. message-based process architectures are widely regarded as an effective method for structuring parallel protocol processing on shared memory multi-processor platforms. a message-based process architecture binds one or more processing elements with data messages and control messages received from applications and network interfaces. in this architecture, parallelism is achieved by simultaneously escorting multiple messages on separate processing elements through a stack of protocol tasks. the paper reports performance results from empirical comparisons of a connection-oriented tcp/ip protocol stack implemented using two different parallel message-based process architectures. these performance experiments measure the throughput, context switching, and synchronization exhibited by the two process architectures on a shared memory multi-processor platform. the experimental results demonstrate the extent to which the selection of a parallel process architecture affects protocol stack performance.
a performance evaluation of connectionless overlay networks for atm. introducing the asynchronous transfer mode (atm) causes a backwards compatibility problem, because atm is connection-oriented whereas most of today's lans are connectionless. interconnection can be achieved by the use of connectionless servers (cls). these servers together with a number of preestablished virtual circuits form a connectionless overlay network on top of atm. in this paper we evaluate overlay networks that differ in number, location and interconnection of clss by computation of mean cell delay and link load.
a study on the inaccessibility characteristics of iso 8802/4 token-bus lans. continuity of service and bounded and known message delivery latency are requirements of a number of applications, which are imperfectly fulfilled by standard lans. most previous studies have addressed this issue by computing worst-case access/transmission delays only for normal lan operation. however, lans are subject to failures, namely partitions. since most applications can live with temporary glitches in lan operation, an alternative approach is to quantify all these glitches or temporary partitions, called inaccessibilities, and to derive a worst-case figure, to be added to the worst-case transmission delay in the absence of faults. in these conditions, reliable real-time operation is possible on nonreplicated lans. an exhaustive study of the inaccessibility characteristics of the iso 8802/4 token-bus lan is described
power control and time division: the cdma versus tdma question. for wireless networks, time division multiple access (tdma) offers certain well-known advantages over methods such as spread spectrum code division (cdma). foremost among them is the guarantee that other users will not interfere during a node's dedicated time slots. for this desirable isolation, the cost is synchronization. viewing arbitrary time intervals as potential tdma time slots, we ask whether it is possible to obtain some of the benefit of time division without incurring the synchronization cost. in particular, we address the question of whether a tdma-like state can be induced on asynchronous channels in such a way as to reduce interference and energy consumption. through analysis and simulation we find conditions under which it is desirable to use time division. we then show how autonomous power management may be used as a mechanism to induce a form of time division. in this context a backlog-sensitive power management system is presented.
reliable multi-user tree setup with local identifiers. a protocol for setting up a tree connection for the purpose of multicast communication over a high-speed packet switched network is presented. the tree connection is based on the use of local identifiers, which are swapped at every intermediate node of the tree. local identifiers are simple to manage, provide fast access to the routing tables, and are very efficient in terms of the size of the resulting routing space. the authors consider a high-speed network in which the local label swapping on data messages is performed in hardware by the switching subsystem, while the connection set-up is done in software by the switch control subsystem. a reliable protocol for setting up the tree connection is presented, and its correctness is formally proved. the protocol ensures the integrity of the tree and when failures occur, it is gracefully degraded into a smaller tree
efficient qos routing. we consider the problem of routing in a network where quality of service constraints are placed on network traffic. we provide two optimal algorithms that are based on determining the discontinuities of functions related to the optimization at hand. the proposed algorithms have pseudopolynomial worst case running time and for a wide variety of tested networks they have fairly satisfactory running times. they perform significantly better than the algorithm based on the direct application of the dynamic programming equations and can also be used in conjunction with known polynomial-time approximation algorithms to provide good average case behavior, in addition to guaranteeing polymonial worst-case running time.
on-line routing and wavelength assignment for dynamic traffic in wdm ring and torus networks. we develop on-line routing and wavelength assignment (rwa) algorithms for wdm bidirectional ring and torus networks with n nodes. the algorithms dynamically support all k-allowable traffic matrices, where k denotes an arbitrary integer vector [k1, k2,..., kn], and node i, 1 ≤ i ≤ n, can transmit at most ki wavelengths and receive at most ki wavelengths. both algorithms support the changing traffic in a rearrangeably nonblocking fashion. our first algorithm, for a bidirectional ring, uses ⌈(σi=1n ki)/3⌉ wavelengths in each fiber and requires at most three lightpath rearrangements per new session request regardless of the number of nodes n and the amount of traffic k. when all the ki's are equal to k, the algorithm uses ⌈kn/3⌉ wavelengths, which is known to be the minimum for any off-line rearrangeably nonblocking algorithm. our second algorithm, for a torus topology, is an extension of a known off-line algorithm for the special case with all the ki's equal to k. for an r × c torus network with r ≥ c nodes, our on-line algorithm uses ⌈kr/2⌉ wavelengths in each fiber, which is the same as in the off-line algorithm, and is at most two times a lower bound obtained by assuming full wavelength conversion at all nodes. in addition, the on-line algorithm requires at most c - 1 lightpath rearrangements per new session request regardless of the amount of traffic k. finally, each rwa update requires solving a bipartite matching problem whose time complexity is only o(r), which is much smaller than the time complexity o(kcr2) of the bipartite matching problem for an off-line algorithm.
a new model for scheduling packet radio networks. packet radio networks are modeled as arbitrary graphs by most researchers. in this paper we show that an arbitrary graph is an inaccurate model of the radio networks. this is true because there exists a large class of graphs which will not model the radio networks. radio networks can be modeled accurately by a restricted class of graphs called the planar point graphs. since the radio networks can accurately be modeled only by a restricted class of graphs, the np-completeness results for scheduling using an arbitrary graph as the model, do not correctly reflect the complexity of the problem. in this paper we study the broadcast scheduling problem using the restricted class as the model. we show that the problem remains np-complete even in this restricted domain. we give an o(n log n) algorithm when all the transceivers are located on a line.
optimal multicast smoothing of streaming video over an internetwork. a number of applications such as internet video broadcasts, corporate telecasts, distance learning etc. require transmission of streaming video to multiple simultaneous users across an internetwork. the high bandwidth requirements coupled with the multi-timescale burstiness of compressed video make it a challenging problem to provision network resources for transmitting streaming multimedia. for such applications to become affordable and ubiquitous, it is necessary to develop scalable techniques which can efficiently deliver streaming video to multiple heterogeneous clients across a heterogeneous internetwork. in this paper, we propose using multicasting of smoothed video and differential caching of the video at intermediate nodes in the distribution tree, as techniques for reducing the network bandwidth requirements of such dissemination. we formulate the multicast smoothing problem, and develop an algorithm for computing the set of optimally smoothed transmission schedules for the tree (such that the transmission schedule along each link in the tree has the lowest peak rate and rate variability for any feasible transmission schedule for that link) given a buffer allocation to the different nodes in the tree. we also develop an algorithm to compute the minimum total buffer allocation to the entire tree and the corresponding allocation to each node, such that feasible transmission is possible to all the clients, when the tree has heterogeneous rate constraints. mpeg-2 trace-driven performance evaluations indicate that there are substantial benefits from multicast smoothing and differential caching. for example, our optimal multicast smoothing can reduce the total transmission bandwidth requirements in the distribution tree by more than a factor of 3 as compared to multicasting the unsmoothed stream.
an approach to pricing, optimal allocation and quality of service provisioning in high-speed packet networks. proposes a new methodology based on economic models to provide quality of service (qos) guarantees to competing traffic classes (classes of sessions) in packet networks. the authors consider an economic model of a packet network where resources are priced. traffic classes compete for network resources and they purchase them to satisfy their qos needs. the authors provide a new definition for qos provisioning based on economic models (pareto efficiency). they obtain the set of optimal resource allocations (pareto optimal) which provide qos guarantees to competing traffic classes. they show the impact on equilibrium prices and optimal allocations due to traffic load and variability, and qos requirements. they propose packet scheduling and admission policies to provide qos guarantees to traffic classes based on available qos and prices in the network.
a shared buffer architecture for interactive vod servers. video-on-demand (vod) servers need to be efficiently designed in order to support a large number of users viewing the same or different videos at different rates. while considering a disk-array based vod server, use of a shared buffer at the server end may be more economical than the sole use of dedicated buffers at each user's end. in this paper, we propose a simple buffer sharing architecture that may be used when disk-array based video servers are used. our aim is to support the maximum number of users for a given number of video server disks while employing a simple scheme requiring less buffer space. the number of video segment retrievals that can occur within a certain time (the service round) is maximum when the scan disk scheduling algorithm is used. consequently, we shall assume use of the scan algorithm for disk retrieval. the vod server has a buffer manager that directs retrieved segments to appropriate buffer locations depending on their release and deadlines. the release and deadlines of segments are such that buffer requirement at the user's set-top box is minimized to two video segments while avoiding video starvation and buffer overflow at the user's end. we propose a novel scheme for the operation of the shared buffer that aims at increasing buffer utilization and decreasing cell loss due to buffer overflow. an atm based broadband network is assumed and all segments are stored in buffers as fixed length atm cells.
a model for virtual tree bandwidth allocation in atm networks. the technique of virtual paths is used in atm networks to perform bandwidth allocation for virtual circuits and to simplify setting up of virtual circuits in response to connection requests. the author describe a new technique called virtual trees that can be used for bandwidth allocation in atm networks. a virtual tree corresponds to pre-allocated bandwidth along a set of links in the network that form a tree rooted at a source node and leading to various destinations. the use of virtual trees provides more flexibility to a source node in setting up a virtual circuit and results in smaller rejection probabilities for connection requests. virtual trees retain all the advantages of virtual paths but have a better performance potential. the authors present an optimization model for bandwidth allocation for virtual tree configurations and present the results of a simulation study comparing the performance of virtual trees with that of virtual paths.
multipoint communication by hierarchically encoded data. a novel multipoint communication paradigm, in which each destination receives a subset of the source's signal that corresponds to that destination's terminal and access bandwidth constraints, is presented. the approach to realizing this paradigm is based on integration of layered coding of the source's signal, routing based on bandwidth demand, optimization of signal parameters, and layered error control. the author gives an overview of several hierarchical signal coding techniques; presents methods for finding maximum bandwidth available to destination, establishing maximum-bandwidth routes; and optimally assigns bandwidth to the signal layers to maximize overall reception quality. error control procedures whereby the network, source, and destinations cooperate to maintain layered-based data integrity, using erasure recovery coding and prioritized packet detection are also presented
a distributed algorithm for delay-constrained unicast routing. in this paper, we study the np-hard delay-constrained least-cost path problem, and propose a simple, distributed heuristic solution: the delay-constrained unicast routing (dcur) algorithm. dcur requires limited network state information to be kept at each node: a cost vector and a delay vector. we prove dcur's correctness by showing that it is always capable of constructing a loop-free delay-constrained path within finite time, if such a path exists. the worst case message complexity of dcur is o(|v|^3) messages, where |v| is the number of nodes. however, simulation results show that, on the average, dcur requires much fewer messages. therefore, dcur scales well to large networks. we also use simulation to compare dcur to the optimal algorithm, and to the least-delay path algorithm. our results show that dcur's path costs are within 10% from those of the optimal solution.
preemption-based admission control in multimedia multiparty communications. in multimedia, multiparty communications a typical participant receives and often generates multiple real-time streams. network resources are dedicated to each stream and are dynamically allocated and released in response to changing users demands throughout the session. admission control procedures, which prioritize users' requests for stream delivery, and decide which resources to allocate, are considered. existing admission control schemes base their decisions on resources that are unused at the time of the request, and reject a request (or queue it) if there are insufficient unused resources. the paper presents a novel approach in which admission is based not only on the unused resources but also on the resources occupied by the streams that are currently received by the requestor. if sufficient unused resources to deliver a requested stream are not available, other streams that are delivered to the requestor are preempted and the resources they occupy are reallocated to satisfy the new request. the manner by which candidate streams for preemption are identified and resources are reallocated depends on the relative importance of the streams to the recipient and the topology of the paths leading to it. the effect of the routing used by the network on the topology of the paths leading to a multi-stream receiver is discussed and protocols for preemption-based reallocation are presented.
performance issues in crma networks for integrated broadband communications. the capabilities of the cyclic reservation multiple access (crma) protocol for supporting mixed video and data traffic was evaluated by computer simulation. the results show that in order to obtain good performance and fairness between all the mixed stations, they should have similar requirements in terms of the number of slots that are requested at each reservation cycle. it is therefore important to reduce the variability by aggregating more slots for stations with short packets, and by transmitting long frames in successive cycles for long packets. the optimal selection of the low and high bound on the number of slots can significantly improve the performance of the crma network under mixed traffic conditions
on bandwidth and storage tradeoffs in multimedia distribution networks. multimedia distribution on demand will impose extremely severe bandwidth requirements on the distribution network and will require the use of very high capacity video servers. in the context of archival programs playout (typical video-on-demand applications), the information source can potentially be stored at any level in the distribution network. part of the information may even be duplicated. of course, there is a tradeoff between the bandwidth required to transport the programs to the users and the storage server capabilities of the overall deployment. the paper presents an analytical study of this tradeoff considering different mechanisms aimed at reducing the overall bandwidth and/or storage server costs. a model of the distribution network is established. a cost function is proposed to capture the different parameters and allow comparison of the possible strategies. results provide good insight into the problem, and are used to discuss the proper placement of storage in a distribution network.
economics of network pricing with multiple isps. in this paper, we examine how transit and customer prices and quality of service are set in a network consisting of multiple isps. some isps may face an identical set of circumstances in terms of potential customer pool and running costs. we examine the existence of equilibrium strategies in this situation and show how positive profit can be achieved using threat strategies with multiple qualities of service. it is shown that if the number of isps competing for the same customers is large then it can lead to price wars. isps that are not co-located may not directly compete for users, but are nevertheless involved in a non-cooperative game of setting access and transit prices for each other. they are linked economically through a sequence of providers forming a hierarchy, and we study their interaction by considering a multi-stage game. we also consider the economics of private exchange points and show that their viability depends on fundamental limits on the demand and cost.
unreliable sensor grids: coverage, connectivity and diameter. we consider an unreliable wireless sensor grid network with n nodes placed in a square of unit area. we are interested in the coverage of the region and the connectivity of the network. we first show that the necessary and sufficient conditions for the random grid network to cover the unit square region as well as ensure that the active nodes are connected are of the form p(n)r^2(n)~log(n)/n, where r(n) is the transmission radius of each node and p(n) is the probability that a node is ''active'' (not failed). this result indicates that, when n is large, even if each node is highly unreliable and the transmission power is small, we can still maintain connectivity with coverage. we also show that the diameter of the random grid (i.e., the maximum number of hops required to travel from any active node to another) is of the order n/log(n). finally, we derive a sufficient condition for connectivity of the active nodes (without necessarily having coverage). if the node success probability p(n) is small enough, we show that connectivity does not imply coverage.
scalabel timers for soft state protocols. soft state protocols use periodic refresh messages to keep network state alive while adapting to changing network conditions; this has raised concerns regarding the scalability of protocols that use the soft-state approach. in existing soft state protocols, the values of the timers that control the sending of these messages, and the timers for aging out state, are chosen by matching empirical observations with desired recovery and response times. these fixed timer-values fail because they use time as a metric for bandwidth; they adapt neither to (1) the wide range of link speeds that exist in most wide-area internets, nor to (2) fluctuations in the amount of network state over time.we propose and evaluate a new approach in which timer-values adapt dynamically to the volume of control traffic and available bandwidth on the link. the essential mechanisms required to realize this scalable timers approach are: (1) dynamic adjustment of the senders' refresh rate so that the bandwidth allocated for control traffic is not exceeded, and (2) estimation of the senders' refresh rate at the receiver in order to determine when state can be timed-out and deleted. the refresh messages are sent in a round robin manner not exceeding the bandwidth allocated to control traffic, and taking into account message priorities.we evaluate two receiver estimation methods for dynamically adjusting network state timeout values: (1) counting of the rounds and (2) exponential weighted moving average.
a proof for lack of starvation in dqdb with and without slot reuse. dqdb is the ieee 802.6 mac standard protocol for metropolitan area networks. it is designed for the slotted, dual bus configuration. a simple way to improve the performance of dqdb is to perform slot reuse and many methods have been suggested in the past to efficiently incorporate slot reuse with dqdb. however, some of them can lead to starvation. the authors improve one of these previous suggestions and the main contribution of the paper is that for the first time they also provide a proof that the improved scheme ensures lack of starvation. they also specify this proof for the important case of dqdb without slot reuse.
scheduling data transfers in preemptive hierarchical switching systems with applications to packet radio networks. a communication switching system is considered where nodes communicate through transmitters and receivers that have the same bandwidth. communication constraints are imposed so that the number of active transmitters or receivers on designated subsets of nodes is bounded by prespecified values. the constraints are assumed to have a hierarchical structure. an algorithm is given that produces minimal length schedules of data transfers through the system if transmission preemption is allowed. a variation of the switching system when nodes communicate through transceivers is also considered, and accompanying scheduling algorithms are presented. applications to transmission scheduling in packet radio networks are discussed
big-bang simulation for embedding network distances in euclidean space. embedding of a graph metric in euclidean space efficiently and accurately is an important problem in general with applications in topology aggregation, closest mirror selection, and application level routing. we propose a new graph embedding scheme called big-bang simulation (bbs), which simulates an explosion of particles under a force field derived from embedding error. bbs is shown to be significantly more accurate compared to all other embedding methods, including gnp. we report an extensive simulation study of bbs compared with several known embedding schemes and show its advantage for distance estimation (as in the idmaps project), mirror selection, and topology aggregation.
the ordered core based tree protocol. this paper presents a new protocol, the ordered core based tree (ocbt) protocol, which remedies several shortcomings of the core based tree (cbt) multicast protocol. we show that the cbt protocol can form loops during periods of routing instability, and that it can consistently fail to build a connected multicast tree, even when the underlying routing is stable. the ocbt protocol provably eliminates these deficiencies and reduces the latency of tree repair following a link or core failure. ocbt also improves scalability by allowing flexible placement of the cores that serve as points of connection to a multicast tree. simulation results show that the amount of control traffic in ocbt is comparable to that in cbt.
real-time cell loss ratio estimation and its applications to atm traffic controls. the asymptotics of cell-loss ratio (clr) in the regime of large buffers are characterized by two parameters, the asymptotic constant and asymptotic decay rate. both parameters can be expanded in powers of one minus the link utilization (heavy traffic expansion), thus, once the coefficients in this expansion are obtained, the clr can be very easily estimated from the measured link utilization by using clr asymptotics. this paper proposes an algorithm for estimating these coefficients in, real time. for this purpose, the notion of state-space representation for a single-server queue is introduced: the elements of the state vector are the coeficients in the expansion of the asymptotic constant and asymptotic decay rate. bayesian regression analysis is applied to estimate the state vector based on the buffer measurement. our approach does not require any models describing the statistics of the traffic other than the asymptotic behavior of the clr in the regime of large buffers. in addition, it allows us to estimate the effective bandwidth of the aggregated process easily, so it is applicable to a wide range of atm traffic control methods, such as connection admission control and vp bandwidth control. we describe how this method of clr estimation will be ap- plied to connection admission control and vp bandwidth control by using results from simulation experiments.
performance analysis of mean internodal distance of connective semi-random networks. one of important properties of a multihop network is the mean internodal distance for evaluating transmission delay. the connective semi-random network achieves a smaller mean internodal distance than other networks. however, the results have only been obtained by computer simulation and no theoretical analysis has been performed. in this paper, we theoretically analyze the mean internodal distance of a connective semi-random network. moreover, we also theoretically analyze a restricted connective semi-random network whose network connective probability is larger than that of a conventional connective semi-random network. it is shown that the theoretical analyzed results agree well with the simulated results in a conventional model and our model with small restriction. the influence of restriction on the mean internodal distance becomes small as the number of outgoing links per node becomes large.
sensing the state of voice sources to improve multiplexer performance. the control of source-coded traffic at a multiplexer has been a topic of extensive research. traditional approaches typically use feedback information on the buffer level in designing the control policy. while important, buffer levels capture only part of the information about the overall system state. by setting up this problem as a markov decision process, the authors show that using information on the state (activity) of the sources, in addition to the buffer level, can result in significant improvements over traditional approaches. they demonstrate this for a multiplexer fed by /spl mu/-law encoded voice sources. some of the scenarios studied exhibit a reduction in distortion exceeding 35%. in general, the improvement is heavily dependent on the correlation statistics of the sources. emulations validate the analysis. the form and characteristics of the optimal control policies are also discussed.
a considerate priority queueing system with guaranteed policy fairness. a discrete-time queuing system supporting two classes of customers (packets of information) with different priorities is analyzed. unlike the head-of-the-line priority policy, the priority policy considered provides for limited service to the low-priority class, even in the presence of high-priority customers (considerate system). at the same time, it guarantees that no low-priority customer will be served before a previously arrived high-priority one (guaranteed policy fairness). the proposed policy can be seen as a compromise between the head-of-the-line priority policy and the classical gated/limited service priority policy. a general methodology is developed for the analysis of this policy
analysis of integrated services tdm with correlated traffic. the problem of multiplexing time-critical (tc) and time-non-critical (tnc) packetized information in an integrated services digital network (isdn) is considered. an appropriate time division multiplexing (tdm) scheme is adopted to accommodate the strict delay requirements for the tc traffic. the resulting system is different from those previously considered in at least two aspects. first, the tnc traffic is assumed to exhibit correlation between consecutive slots. second, the tc traffic is not necessarily accommodated in a contiguous subframe, but it may be spread over the whole frame according to any pattern. the nongated service policy is adopted for the service of the tnc traffic, unlike most of the past work. a very flexible approach is developed for the exact analysis of the proposed tdm scheme. numerical results are derived for the case of tc traffic generated by voice sources
new call block versus handoff blocking in cellular networks. in cellular networks, blocking occurs when a base station has no free channel to allocate to a mobile user. one distinguishes between two kinds of blocking, the first is called new call blocking and refers to blocking of new calls, the second is called handoff blocking and refers to blocking of ongoing calls due to the mobility of the users. in this paper, we first provide explicit analytic expressions for the two kinds of blocking probabilities in two asymptotic regimes, i.e., for very slow mobile users and for very fast mobile users, and show the fundamental differences between these blocking probabilities. next, an approximation is introduced in order to capture the system behavior for moderate mobility. the approximation is based on the idea of isolating a set of cells and having a simplifying assumption regarding the handoff traffic into this set of cells, while keeping the exact behavior of the traffic between cells in the set. it is shown that a group of 3 cells is enough to capture the difference between the blocking probabilities of handoff call attempts and new call attempts.
multiservice call blocking approximations for virtual path based atm networks with cbr and vbr traffic. the exact calculation of call blocking probabilities for multiservice atm networks with alternate or adaptive routing for virtual channels (vc) is hardly possible. therefore the paper presents and investigates the equivalent single path model as an approximation to omit the vc routing algorithm in the calculation. the model can be applied to atm networks with several direct virtual path connections between each node pair. further different methods to calculate the multiservice call blocking probabilities are reviewed and compared. a new approximate method is presented for networks, where the trunk reservation fairness mechanism is applied. this method is accurate, fast and may also be used for noninteger capacities and bandwidth requirements, which is important for statistical multiplexing of variable bitrate traffic.
hardware based error and flow control in the axon gigabit host-network interface. the primary goal of the axon architecture is to support a high-performance data path delivering high network bandwidth directly to applications. the axon network interface is described from the perspective of its simulation, and in particular and implementation of error and flow control in hardware. background is provided on the simulation package that has been used to explore these mechanisms, and a brief overview is given of the axon architecture is implemented by the simulator. the error control mechanism, the hardware design, and the functional and performance simulation results are outlined. the rate control scheme is described, along with its implementation and simulation
providing bandwidth guarantees in an input-buffered crossbar switch. introduces and analyzes a method for providing bandwidth reservations in an input-buffered non-blocking crossbar switch. the scheme, which the authors call weighted probabilistic iterative matching (wpim), is an improvement over probabilistic iterative matching and allows flexible allocation of bandwidth among the switch inputs sharing a common output link in a simple manner. weighted probabilistic iterative matching allocates the output bandwidth among the inputs based on reservations made during the connection setup phase, and can guarantee that traffic from each input receives its promised share of the bandwidth of the output link. in addition, the algorithm provides isolation between two flows arriving on distinct input links and directed at a common output link; misbehaving flows at one of the inputs do not affect the bandwidth guarantees or delays of traffic from other inputs. results from simulations show that the scheme is able to maintain probabilistic bandwidth and delay guarantees in the presence of misbehaving traffic. the authors also derive an analytical upper bound for the average delay under the scheme and validate it by simulation.
latency-rate servers: a general model for analysis of traffic scheduling algorithms. in this paper, we develop a general model, called latency-rate servers ($\cal lr$-servers), for the analysis of traffic scheduling algorithms in broadband packet networks. the behavior of an $\cal lr$ scheduler is determined by two parameters --- the latency and the allocated rate. we show that several well-known scheduling algorithms, such as weighted fair queueing, virtualclock, self-clocked fair queueing, weighted round robin, and deficit round robin, belong to the class of $\cal lr$-servers. we derive tight upper bounds on the end-to-end delay, internal burstiness, and buffer requirements of individual sessions in an arbitrary network of ${\cal lr}$-servers in terms of the latencies of the individual schedulers in the network, when the session traffic is shaped by a leaky bucket. thus, the theory of $\cal lr$-servers enables computation of tight upper-bounds on end-to-end delay and buffer requirements in a network of servers in which the servers on a path may not all use the same scheduling algorithm. we also define a self-contained approach to evaluate the fairness of $\cal lr$-servers and use it to compare the fairness of many well-known scheduling algorithms.
a performance model for wavelength conversion with non-poisson traffic. this paper makes the first known attempt to study wavelength-routing networks and the effects of wavelength conversion under dynamic non-poisson traffic. an approximation that characterizes any non-poisson traffic by its first two moments is utilized. the arrival occupancy distribution of busy wavelengths for this approximate process is derived and is used to analyze the effects of wavelength conversion. the model predicts that traffic peakedness plays an important role in determining the blocking performance, and also that wavelength conversion gain is insensitive to traffic peakedness over a large range.
buffer sizing at a host in an atm network. the authors develop a queuing model of a buffer that collects cells for reassembly into packets for a protocol layer above the asynchronous transfer mode (atm) layer. whenever the buffer fills with all packets incomplete, a packet must be sacrificed to make room for others. the queuing model estimates the equilibrium fraction of packets sacrificed. applications to sizing the buffer for a prescribed loss probability are given
characterizing the internet hierarchy from multiple vantage points. the delivery of ip traffic through the internet depends on the complex interactions between thousands of autonomous systems (ases) that exchange routing information using the border gateway protocol (bgp). this paper investigates the topological structure of the internet in terms of customer-provider and peer-peer relationships between ases, as manifested in bgp routing policies. we describe a technique for inferring as relationships by exploiting partial views of the as graph available from different vantage points. next we apply the technique to a collection of ten bgp routing tables to infer the relationships between neighboring ases. based on these results, we analyze the hierarchical structure of the internet and propose a five-level classification of ases. our analysis differs from previous characterization studies by focusing on the commercial relationships between ases rather than simply the connectivity between the nodes.
a lower bound for multicast key distribution. with the rapidly growing importance of multicast in the internet, several schemes for scalable key distribution have been proposed. these schemes require the broadcast of @q(logn) encrypted messages to update the group key when the nth user joins or leaves the group. in this paper, we establish a matching lower bound (independently, and concurrently, richard yang and simon lam discovered a similar bound with slightly different properties and proofs. an earlier version of our paper appeared in infocom 2001 while their result appears in [r. yang, s. lam, a secure group key management communication lower bound, technical report tr-00-24, department of computer sciences, ut austin, july 2000, revised september 2000].), thus showing that @q(logn) encrypted messages are necessary for a general class of key distribution schemes and under different assumptions on user capabilities. while key distribution schemes can exercise some tradeoff between the costs of adding or deleting a user, our main result shows that for any scheme there is a sequence of 2n insertion and deletions whose total cost is @w(nlogn). thus, any key distribution scheme has a worst-case cost of @w(logn) either for adding or for deleting a user.
algebra and algorithms for qos path computation and hop-by-hop routing in the internet. prompted by the advent of quality-of-service routing in the internet, we investigate the properties that path weight functions must have so that hop-by-hop routing is possible and optimal paths can be computed with a generalized dijkstra's algorithm. for this purpose, we define an algebra of weights which contains a binary operation, for the composition of link weights into path weights, and an order relation. isotonicity is the key property of the algebra. it states that the order relation between the weights of any two paths is preserved if both of them are either prefixed or appended by a common, third, path.we show that isotonicity is both necessary and sufficient for a generalized dijkstra's algorithm to yield optimal paths. likewise, isotonicity is also both necessary and sufficient for hop-by-hop routing. however, without strict isotonicity, hop-by-hop routing based on optimal paths may produce routing loops. they are prevented if every node computes what we call lexicographic-optimal paths. these paths can be computed with an enhanced dijkstra's algorithm that has the same complexity as the standard one. our findings are extended to multipath routing as well.as special cases of the general approach, we conclude that shortest-widest paths can neither be computed with a generalized dijkstra's algorithm nor can packets be routed hop-by-hop over those paths. in addition, loop-free hop-by-hop routing over widest and widest-shortest paths requires each node to compute lexicographic-optimal paths, in general.
gateway based approach for conducting multiparty multimedia sessions over heterogeneous signaling domains. emerging networking technologies are being introduced with their own management protocols for routing, resource reservation and signaling. this diversity restricts the interoperability among qos-aware multimedia applications written for different networks. we present an approach for managing multiparty, multimedia sessions in a heterogeneous internetwork spanning multiple signaling domains. participants utilize the native signaling on their respective domains and interact with participants on other domains through signaling gateways that bridge the domains and provide translation of signaling procedures and qos semantics. data streams are transmitted using a hierarchical representation, which allows participants to independently adjust the reception quality of each stream according to their resources and interests. we present a particular design and implementation details for connecting atm and ip signaling domains and conclude with its extension to an arbitrary number of interconnected domains.
locating network monitors: complexity, heuristics, and coverage. there is an increasing interest in passive monitoring of ip flows at multiple locations within an ip network. the objective of such a distributed monitoring system is to sample packets belonging to a large fraction of ip flows in a cost-effective manner by carefully placing monitors and controlling their sampling rates. in this paper, we consider the problem of where to place monitors within the network and how to control their sampling. to address the tradeoff between monitoring cost and monitoring coverage, we propose and study minimum cost and maximum coverage problems under various budget constraints and in the presence of routing changes caused by link failures. we show that all of the problem formulations are np-hard. we propose greedy heuristics, and show that the heuristics provide solutions quite close to the optimal solutions through experiments using synthetic and real network topologies. in addition, our experiments show that a small number of monitors often suffices to monitor most of the traffic in an entire ip network.
secret sharing in graph-based prohibited structures. a secret sharing scheme for the prohibited structure is a method of sharing a master key among a finite set of participants in such a way that only certain pre-specified subsets of participants cannot recover the master key. a secret sharing scheme is called perfect if any subset of participants who cannot recover the master key obtains no information regarding the master key. in this paper, we propose an efficient construction of perfect secret sharing schemes for graph-based prohibited structures where a vertex denotes a participant and an edge does a pair of participants who cannot recover the master key. the information rate of our scheme is 2/n, where n is the number of participants.
spectral decomposition approach for transient analysis of multi-server discrete-time queues. previous work by the authors (see proceedings conf. on information sciences and systems, baltimore, usa, 1990) where the spectral decomposition method was used for the transient analysis of a single-server queue is generalized. for the arrival process a general discrete-time markovian batch arrival process is assumed, where the batch size distribution of the arrivals in successive slots is governed by a n-state discrete-time markov chain. it is shown that once the n eigenvalues of the probability generating matrix of the arrival process are obtained, the complete solution in the transform domain may be given. using the complex analysis technique and cauchy's integral formula, an efficient numerical method is presented for the calculation of a few performance measures. the numerical method is generalized to the situations where the superpositions of a number of independent arrival sources are fed to the queue. it is shown that the numerical complexity are fed to the queue. it is shown that the numerical complexity of obtaining the transient solution in this case can be substantially reduced by using an approach based on the kronecker product
all-optical lan interconnection with a wavelength selective router. this paper formulates the wavelength assignment issues an interconnecting optical broadcast-star local area networks (lans) through a wavelength routing bridge. static and dynamic approaches to partitioning of wavelengths for local and global traffic are compared using analysis and simulations. it is found that static wavelength assignment, the easiest algorithm to implement, is significantly outperformed by dynamic algorithms. several dynamic assignment algorithms are developed, and architectural issues in interconnecting optical networks are discussed. the dependence of the call blocking performance on system parameters, such as the traffic rate, the local and global traffic statistics, and the number of available wavelengths is examined in detail. a simple, yet accurate approximation is also developed to predict the blocking performance with an arbitrary number of lans.
leap forward virtual clock: a new fair queueing scheme with guaranteed delays and throughput fairness. we describe an efficient fair queuing scheme, leap forward virtual clock, that provides end-to-end delay bounds similar to wfq, along with throughput fairness. our scheme can be implemented with a worst-case time o(log log n) per packet (inclusive of sorting costs), which improves upon all previously known schemes that guarantee delay and throughput fairness similar to wfq. interestingly, both the classical virtual clock and the self-clocked fair queuing schemes can be thought of as special cases of our scheme, by setting the leap forward parameter appropriately.
congestion avoidance in atm networks. the authors propose a new policy to prevent congestion phenomena in asynchronous transfer mode (atm) networks. in particular, using a synthesis approach, they define and calculate the bandwidth which is assigned to every acceptable source from the atm network. this bandwidth, which varies between the peak and the average bandwidth demands of the particular source, is called effective or virtual, and is mainly characterized from the burstiness of the source. in constant bit rate sources the effective bandwidth is equal to the peak rate. based on the concept of effective bandwidth, a connection acceptance algorithm that leads to a very high utilization of network resources is formulated
token ring reliability models. a study of the reliability of token rings designed according to the ieee 802.5 standard is described. the reliability model is based on information in the standards, plus implementation details, and is more realistic than previous models. although the analysis is approximate, it includes all factors thought to be important in determining reliability, since an approximate analysis which included all such factors was felt to be more useful than an exact analysis which ignored important factors. the precise reliability measure analyzed is availability of a connection from a specified source to a specified destination. although the use of an active communications medium instead of a passive bus may decrease reliability of the token ring, the architecture gives great flexibility in bypassing or otherwise recovering from faults. for large networks this adds considerably to the reliability. if many devices are inactive, however, this advantage can be eliminated by even a small probability that inactive devices are not successfully bypassed
achieving near-optimal traffic engineering solutions for current ospf/is-is networks. traffic engineering aims to distribute traffic so as to "optimize" some performance criterion. this optimal distribution of traffic depends on both the routing protocol and the forwarding mechanisms in use in the network. in ip networks running the ospf or is-is protocols, routing is over shortest paths, and forwarding mechanisms distribute traffic "uniformly" over equal cost shortest paths. these constraints often make achieving an optimal distribution of traffic impossible. in this paper, we propose and evaluate an approach that can realize near optimal traffic distribution without changes to routing protocols and forwarding mechanisms. in addition, we explore the tradeoff that exists between performance and the configuration overhead that our solution requires. the paper's contributions are in formulating and evaluating an approach to traffic engineering in ip networks that achieves near-optimal performance while preserving the existing infrastructure.
qos provisioning and tracking fluid policies in input queueing switches. the concept of tracking fluid policies by packetized policies is extended to input queueing switches. it is considered that the speedup of the switch is one. one of the interesting applications of the tracking policy in tdma satellite switches is elaborated. for the special case of 2 &times; 2 switches, it is shown that a tracking nonanticipative policy always exists. it is found that, in general, nonanticipative policies do not exist for switches with more than two input and output ports. for the general case of n &times; n switches, a heuristic tracking policy is provided. the heuristic algorithm is based on two notions: port tracking and critical links. these notions can be employed in the derivation of other heuristic tracking policies as well. simulation results show the usefulness of the heuristic algorithm and the two basic concepts it relies on.
blocking in all-optical networks. we present an analytical technique of very low complexity, using the inclusion-exclusion principle of combinatorics, for the performance evaluation of all-optical, wavelength-division multiplexed networks with no wavelength conversion. the technique is a generalized reduced-load approximation scheme which is applicable to arbitrary topologies and traffic patterns. one of the main issues in computing blocking probabilities in all-optical networks is the significant link load correlation introduced by the wavelength continuity constraint. one of the models we propose takes this into account and gives good results even under conditions with high link load correlation. through numerous experiments we show that our models can be used to obtain fast and accurate estimates of blocking probabilities in all-optical networks and scale well with the path length and capacity of the network. we also extend one of our models to take into account alternate routing, ina the form of fixed alternate routing and least loaded routing.
application of network calculus to general topologies using turn-prohibition. network calculus is known to apply in general only to feedforward routing networks, i.e., networks where routes do not create cycles of interdependent packet flows. in this paper, we address the problem of using network calculus in networks of arbitrary topology. for this purpose, we introduce a novel graph-theoretic algorithm, called turn-prohibition (tp), that breaks all the cycles in a network and, thus, prevents any interdependence between flows. we prove that the tp-algorithm prohibits the use of at most 1/3 of the total number turns in a network, for any network topology. using analysis and simulation, we show that the tp-algorithm significantly outperforms other approaches for breaking cycles, such as the spanning tree and up/down routing algorithms, in terms of network utilization and delay bounds. our simulation results also show that the network utilization achieved with the tp-algorithm is within a factor of two of the maximum theoretical network utilization, for networks of up to 50 nodes of degree four. thus, in many practical cases, the restriction of network calculus to feedforward routing networks may not represent a too significant limitation.
mulilevel network management by means of system identification. the paper proposes a new approach to the management of large-scale communication networks. to manage large-scale communication networks effectively, it is essential to get a bird's-eye view of them when they are in their normal conditions. when an indication of faulty state is detected, the focus of the management is narrowed down to the faulty network elements. this management scheme is called multilevel network management. the paper proposes that system identification be used in multilevel network management. the system identification is used to measure transmission delays between two arbitrarily selected nodes in the networks, and multilevel network management is achieved by selecting those two nodes appropriately in accordance with the levels to be managed.
on accommodating mobile hosts in an integrated services packet network. this paper considers the support of real-time applications to mobile hosts in an integrated services packet network. we have proposed a service model for mobile hosts that can support adaptive applications which can withstand wide range of available bandwidth, as well as applications which require mobility independent service guarantees. we describe an admission control scheme and a reservation protocol for implementing this service model. our admission control scheme achieves high utilization of network resources.
a novel upgrade path for transparent optical networks based on wavelength reuse. passive optical networks (pons) provide an economical method of delivering a wide variety of services to a small number of customers. using optical fibre amplifiers, pons can be aggregated to form transparent optical networks (tons) serving a very large customer base. however, the effective bandwidth per user is limited, particularly in the upstream direction. in the future, customers will demand increasingly high bandwidth services requiring tons to be regularly upgraded. a wdm ton upgrade is proposed based on a novel wavelength reuse scheme in which information is routed passively using optical filters without the need for electronic switching, buffering, wavelength conversion or network synchronisation. wavelengths are dynamically allocated to customers, enabling bandwidth to be offered on demand.
complexity of gradient projection method for optimal routing in data networks. derives a time complexity bound for the gradient projection method for optimal routing in data networks. this result shows that the gradient projection algorithm of the goldstein-levitin-poljak type formulated by bertsekas (1982) converges to within /spl epsiv/ in relative accuracy in o(/spl epsiv//sup 2/h/sub min/n/sub max//sup l/) iterations, where n/sub max//sup l/ is the number of paths sharing the maximally shared link, and h/sub min/ is the diameter of the network. based on this complexity result, the authors also show that the one-source-at-a-time update policy has a complexity bound which is o(n) times smaller than that of the all-at-a-time update policy [bertsekas, 1982], where n is the number of nodes in the network. the result of the paper argues for constructing networks with low diameter for the purpose of reducing the complexity of the network control algorithms. the result also implies that parallelizing the optimal rotating algorithm over the network nodes is beneficial.
closed-loop architecture and protocols for rapid dynamic spreading gain adaptation in cdma networks. we present a closed-loop architecture and protocols for rapid dynamic spreading gain adaptation and fast feedback between a transmitter and a receiver communicating with each other in cdma networks. these protocols and architecture do not require the transfer of an explicit control message indicating the change of cdma spreading gain from transmitter to receiver. also, with these protocols, the transmitter can change the spreading gain symbol-by-symbol as opposed to frame-by-frame, and feedback information (e.g., the fast-varying channel condition) can be exchanged almost as frequently as the symbol rate. thus, adaptation to the time-varying channel conditions of wireless networks and/or to the rate variation of traffic can be much faster than is possible with the existing frame-by-frame approach.
measurement-based call admission control: analysis and simulation. we consider the problem of admission control for variable-rate traffic sources sharing a bufferless link, in order to provide a quality-of-service in terms of overload probability. through analysis and simulations, we study the performance of a scheme which has no prior knowledge of the traffic statistics and makes admission decision based on the current network state only. we analyze the dynamics of the system under this control, and show that in the regime of large link capacity and separation of call and burst time-scales, this scheme performs as well as the optimal scheme which has full knowledge of the statistics. we evaluate the performance of the scheme on real traffic sources.
classbench: a packet classification benchmark. packet classification is an enabling technology for next generation network services and often a performance bottleneck in high-performance routers. the performance and capacity of many classification algorithms and devices, including tcams, depend upon properties of filter sets and query patterns. despite the pressing need, no standard performance evaluation tools or filter sets are publicly available. in response to this problem, we present classbench, a suite of tools for benchmarking packet classification algorithms and devices. classbench includes a filter set generator that produces synthetic filter sets that accurately model the characteristics of real filter sets. along with varying the size of the filter sets, we provide high-level control over the composition of the filters in the resulting filter set. the tool suite also includes a trace generator that produces a sequence of packet headers to exercise packet classification algorithms with respect to a given filter set. along with specifying the relative size of the trace, we provide a simple mechanism for controlling locality of reference. while we have already found classbench to be very useful in our own research, we seek to eliminate the significant access barriers to realistic test vectors for researchers and initiate a broader discussion to guide the refinement of the tools and codification of a formal benchmarking methodology. (the classbench tools are publicly available at the following site: http://www.arl.wustl.edu/~det3/classbench/.)
power-saving protocols for ieee 802.11-based multi-hop ad hoc networks. power-saving is a critical issue for almost all kinds of portable devices. in this paper, we consider the design of powersaving protocols for mobile ad hoc networks (manets) that allow mobile hosts to switch to a low-power sleep mode. the manets being considered in this paper are characterized by unpredictable mobility, multi-hop communication, and no clock synchronization mechanism. in particular, the last characteristic would complicate the problem since a host has to predict when another host will wake up to receive packets. we propose three power management protocols, namely dominating-awake-interval, periodically-fully-awake-interval, and quorum-based protocols, which are directly applicable to ieee 802.11-based manets. as far as we know, the power management problem for multihop manets has not been seriously addressed in the literature. existing standards, such as ieee 802.11, hiperlan, and bluetooth, all assume that the network is fully connected or there is a clock synchronization mechanism. extensive simulation results are presented to verify the effectiveness of the proposed protocols.
message authentication with one-way hash functions. fast message integrity and authentication services are much desired in today's high-speed network protocols. current message authentication techniques are mostly encryption-based which is undesirable for several reasons. in this brief paper, we introduce encryption-free message authentication based entirely on fast one-way hash functions. two methods are presented and their strength is analyzed. the security of the proposed methods is based on the strength of the underlying one-way hash function.
large-scale and high-speed interconnection of multiple fddis using atm-based backbone lan. the authors discuss problems related to the bridging method between the asynchronous transfer mode (atm)-based high-speed multimedia backbone local area network (mblan) and a fiber distributed data interface (fddi), especially the filtering database (fdb) construction method for filtering of frames. the problems are achieving high performance, correspondence to a large-scale system, and prevention of broadcast. the fdb construction method was evaluated based on these problems. through the evaluation, it was noted that the fdb learning failure rate must be below 10-3 and a frame filtering process when relaying frames from the mblan to an fddi is not necessary. an fdb access method is proposed. by using a multiple hashing algorithm for the fdb access, the proposed method makes it possible to deal with all terminal addresses, even in a large-scale network system that includes tens of thousands of terminals or more, and also enables high-speed filtering/forwarding of frames between terminals. both the entry search speed and an effective number of entries in the entry table can be adapted to the requirements of an application by changing the maximum number of hashing times
approximation formulae for blocking probabilities in a large erlang loss system: a probabilistic approach. in this paper, we use a probabilistic approach to present a unified view of classical blocking probabilities approximation formulae for a multi-rate erlang loss system, both in the finite and infinite population cases. combining our results with the uniform approximation due to bleistein, we recover the results mitra and morrison which were obtained by saddlepoint techniques. we also show that we can avoid using the uniform approximation to get "specialized" formulae for the heavy, critical, generalized critical and light traffic cases. numerical results for typical loss levels in the atm case are presented where we compare the uniform approximation (ua) with the specialized approximations (sa).
queueing analysis for shared buffer switching networks for non-uniform traffic. uniform traffic does not represent a realistic view of traffic patterns in real systems. non-uniform traffic models better reflect the traffic patterns that need to be accommodated. such traffic may cause the network performance to deteriorate to much lower levels than the ones predicted by uniform traffic analysis. the authors extend the queueing analysis for buffered networks by providing methods for analyzing the queueing behavior of switching networks under non-uniform traffic patterns. they focus on shared buffer switch elements because they have better performance than input or output buffered elements. the analytical method for performance evaluation is compared with simulation on the basis of accuracy, where the performance is measured in terms of maximum throughput and probability of cell loss.
the token grid: multidimensional media access for local and metropolitan networks. a token grid network in which media access is performed over a two-dimensional mesh is introduced. in the resulting system, each station is two-connected and has the same transmission hardware and small station latency as in a dual token ring. in the token grid, however, the total system throughput may be many factors larger than that which is possible in a dual token ring. this advantage increases with the normalized end-to-end propagation delay. in the results presented, the uniform load capacity of the token grid grows with the size of the network. in addition, the token grid can take advantage of communities-of-interest amongst the stations. it is possible to implement the system in such a way as to achieve robust operation in the presence of station and link failures
optical local area networks (lans) using wavelength-selective couplers. in wavelength-division-multiplexed ring and bus networks, stations normally connect to the fiber using fused biconical taper (fbt) attachments. in this paper, we investigate protocols for multichannel photonic bus/ring lans which use active wavelength-selective taps rather than passive ones. since stations actively tap the channel that they are accessing, synchronization and other functions are identical to existing single-channel lans. however, in order to avoid "re-tuning collisions", the media access protocols in these designs must ensure that stations do not re-tune their couplers at inappropriate times. this constraint places restrictions on the physical parameters over which system performance is efficient. in particular, we find that these designs may be efficient in the local area but lack the scalability required for metropolitan coverage. in this paper, capacity and delay models are also derived, and comparisons are made with conventional passive networks.
a transmission scheduling algorithm for mixed traffic: high and low priority. the authors are concerned with the effective accommodation of mixed traffic (high and low priority) by the cellular isdn system. they consider two mutually independent traffic streams sharing a single common channel for transmission. the two streams have different arrival and required transmission time characteristics, as well as different delay constraints. the authors present and analyze an algorithm for accommodating both traffics on the common transmission medium, so that the expected throughput of the system is high and the expected per message delays for both traffics are low. numerical results are presented
multicast routing algorithm for nodal load balancing. the authors propose two multicast routing algorithms which distribute copy operation of packets over all nodes along the multicast path: a link-added type algorithm and a loop-constructed type algorithm. both algorithms, at first, derive an approximate solution for minimum cast path, and then improve the solution to prevent concentration of packet copy operation at one switching node at a little sacrifice of total cost along the path. computer simulation results show that too much copy operation per node can be avoided by these algorithms. compared to the minimum cost solution of the tree-shaped multicast path, the solution of the proposed algorithms makes the average distance connecting a source-destination pair longer, but the sacrifice of total cost is verb small. these algorithms can be applied not only to packet networks but also asynchronous transfer mode (atm) networks
performance simulation of end-to-end windowing in atm networks. the authors focus on the application of adaptive end-to-end windowing as a reactive congestion control mechanism for data communications over asynchronous transfer mode (atm) networks. in particular, an adaptive window mechanism including go-back (n) retransmission is proposed. the performance achievable by its application was evaluated by simulation under a particular network model assumption. the gain possible in terms of improvement of cell acceptance is estimated with different source traffic descriptors and network parameter values. some comments on the interaction between the window mechanism and other congestion control mechanisms for atm networks are given
dqdb man as a transit network for atm cpns. the authors examine the internetworking of the distributed queue dual bus (dqdb) metropolitan area network (man) with asynchronous transfer mode (atm) of broadband integrated services digital network (b-isdn). several scenarios are discussed. it is suggested that the best solution is through the use of a connection-oriented (co) dqdb service. some of the provisions of the co dqdb service necessary for an efficient and simple interworking are provided
guaranteed scheduling for switches with configuration overhead. in this paper, we present three algorithms that provide performance guarantees for scheduling switches, such as optical switches, with configuration overhead. each algorithm emulates an unconstrained (zero overhead) switch by accumulating a batch of configuration requests and generating a corresponding schedule for a constrained switch. speedup is required both to cover the configuration overhead of the switch and to compensate for empty slots left by the scheduling algorithm. scheduling algorithms are characterized by the number of configurations ns they require to cover a batch of requests and the speedup required to compensate for empty slots smin. initially, all switch reconfiguration is assumed to occur simultaneously. we show that a well-known exact matching algorithm, exact, leaves no empty slots (i.e., smin = 1), but requires ns ≈ n2 configurations for an n-port switch leading to high configuration overhead or large batches and, hence, high delay. we present two new algorithms that reduce the number of configurations required substantially. min covers a batch of requests in the minimum possible number of configurations, ns = n, but at the expense of many empty slots, smin ≈ 4log2 n. double strikes a balance, requiring twice as many configurations,ns = 2n, while reducing the number of empty slots so that smin = 2. loosening the restriction on reconfiguration times, the scheduling problem is cast as an open shop. the best known practical scheduling algorithm for open shops, list scheduling (list), gives the same emulation requirements as double. therefore, we conclude that our architecture gains no advantages from allowing arbitrary switch reconfiguration. finally, we show that double and list offer the lowest required speedup to emulate an unconstrained switch across a wide range of port count and delay.
on the multiple shared memory module approach to atm switching. the authors propose a new approach to building large asynchronous transfer mode (atm) switches based on shared memory modules. shared memory modules are proposed to be placed in parallel, with every input and output port having access to every one of the switch models. this approach permits global sharing of the total buffer space. some basic issues in such an arrangement are studied, such as the necessary and sufficient conditions for optimal performance and the minimum number of modules required for the switch to have optimal performance while permitting sharing of the entire buffer space among all the input and output ports and while preserving packet sequencing for any virtual channel. a centralized control algorithm which yields optimal performance is also proposed
classification of access network types: ethernet wireless lan, adsl, cable modem or dialup? ethernet, wireless lan, adsl, cable modem, and dialup are common access networks that have dramatically different characteristics. fast and accurate classification of access networks can benefit a wide range of applications. in this paper, we propose a simple and efficient end-to-end scheme to classify access networks into three categories: ethernet, wireless lan and low-bandwidth connection. our scheme is based on the intrinsic characteristics of the various access networks, and utilizes the median and entropy of packet-pair inter-arrival times. extensive experiments show that our scheme obtains accurate classification results in a very short time (95% accuracy in 2s, with 10 packet pairs).
a nonpreemptive priority delay model with modified-vacation intervals for homogeneous fddi networks. a closed-form analytical expression is derived for the individual priority classes of fddi based on a nonpreemptive priority delay model. to faithfully model the fddi network using the nonpreemptive priority delay model, we use a concept of modified-vacations. the expressions for the mean waiting time of individual priority classes are functions of first and second moments of the modified-vacation intervals of that class. it can be shown that the expression derived for the first and second moments of the modified-vacation intervals of the respective classes are functions of mean and variance of the number of messages transmitted by each priority class per token rotation. these variables are evaluated using an iterative procedure that utilizes the prior knowledge of the throughput characteristics of the fddi network. simulation results show that the nonpreemptive priority delay model provides accurate estimates for the mean waiting time of individual priority classes of a homogeneous fddi network.
performance analysis of traffic control methods in multimedia atm lan. the authors treat traffic control methods suitable to atm lan, in which two service classes are considered; one is for high speed data transfer based on a fast reservation protocol (frp service class) and the other is for continuous bit rate (cbr) traffic such as motion video (cbr service class). the authors first evaluate the performance of the frp service class. when the terminal requests the data transfer, its usable bandwidth is negotiated with the traffic descriptor (c/sub max/, c/sub min/) the former is a desirable data transfer rate, and the latter is a sustainable rate when the network is congested. by carrying out a mathematical analysis, the authors show an appropriate set of the traffic descriptor. the coexistence of frp and cbr service classes are then treated. by using an analytic method, the performance of the cbr service class traffic is shown to be heavily affected by the frp service class traffic. therefore, the authors introduce a reserved bandwidth to the cbr service class to guarantee some appropriate level of performance to the cbr service class.
the helical switch: a multipath atm switch which preserves cell sequence. a novel cell switching architecture for asynchronous transfer mode (atm)-based networks is presented. the proposed helical switch is a multistage interconnection network which implements the self-routing technique with efficient buffer sharing. although the switch may route cells along multiple paths, the connection-oriented mode required by the atm-based network is supported. cell sequence integrity is guaranteed by introducing a virtual helix which forces cells routed along different paths to proceed in order and fill the internal buffers uniformly. under a uniform traffic pattern, it is shown that the minimum achievable throughput is 5/6 per output line
distributed construction of connected dominating set in wireless ad hoc networks. connected dominating set (cds) has been proposed as virtual backbone or spine of wireless ad hoc networks. three distributed approximation algorithms have been proposed in the literature for minimum cds. in this paper, we first reinvestigate their performances. none of these algorithms have constant approximation factors. thus these algorithms cannot guarantee to generate a cds of small size. their message complexities can be as high as o(n2), and their time complexities may also be as large as o(n2) and o(n3). we then present our own distributed algorithm that outperforms the existing algorithms. this algorithm has an approximation factor of at most 8, o(n) time complexity and o(n log n) message complexity. by establishing the ω(n log n) lower bound on the message complexity of any distributed algorithm for nontrivial cds, our algorithm is thus message-optimal.
a mini-product-form-based solution to data-delay evaluation in wireless integrated voice/data networks. although the product-form solution provides an accurate characterization of equilibrium voice-traffic behavior in wireless integrated voice/data networks, it does not directly provide a method to evaluate data-packet delay. however, examination of each link separately in a manner that incorporates interaction with the rest of the network permits one to take advantage of the wireless nature of the network and obtain a three-flow characterization of each link, which also satisfies a product-form solution and is hence termed a "mini-product-form" solution. by matching the values of these flows, which are natural to the wireless network, to the average values obtained from the product-form solution of the entire network, the authors obtain a three-dimensional markov chain characterization of the voice occupancy state on the link, which permits a simpler evaluation of data-packet delay. a further reduction is possible by converting the three-dimensional chain to a single-dimensional one.
design and performance analysis of a growable multicast atm switch. in this paper, we design and analyze a growable multicast atm switch. it can grow to a large size since both cell routing and contention resolution are designed to distribute over switch elements, and the switch structure is modular. the output ports are partitioned into groups to permit sharing of routing paths. the concept of group routing helps reduce an order of magnitude of switch elements. a two-stage switch architecture is described to illustrate our design principle. the switch can be easily expanded to a larger size by using more stages. the performance analysis of the switch in terms of cell loss rate, delay, mean queue length, mean waiting time, and throughput is conducted using the m/geom/1 model. experimental results show that the proposed atm switch not only meets the atm performance requirements either for unicasting or multicasting but also uses fewer switch elements and has less delay than other comparable switches.
movement-assisted sensor deployment. adequate coverage is very important for sensor networks to fulfill the issued sensing tasks. in many working environments, it is necessary to make use of mobile sensors, which can move to the correct places to provide the required coverage. in this paper, we study the problem of placing mobile sensors to get high coverage. based on voronoi diagrams, we design two sets of distributed protocols for controlling the movement of sensors, one favoring communication and one favoring movement. in each set of protocols, we use voronoi diagrams to detect coverage holes and use one of three algorithms to calculate the target locations of sensors if holes exist. simulation results show the effectiveness of our protocols and give insight on choosing protocols and calculation algorithms under different application requirements and working conditions.
re-routing in circuit switched networks. dynamic routing has been adopted in many circuit switched networks in many parts of the world. a number of dynamic routing schemes have been designed and studied with the aim of maximizing the network throughput. the least loaded routing (llr) is simple and efficient, while other more elaborate routing schemes can only provide marginal throughput gain over that of llr. re-routing is the practice of routing calls on alternate paths to direct paths or other less congested alternate paths. it allows the continuous re-distribution of network loads so that the congestion on direct paths can be relieved. in this paper, we study a re-routing scheme based on llr. an original analysis of re-routing is performed and numerical examples confirm the significant throughput gain over llr routing.
on dynamically establishing and terminating isochronous message streams in wdma-based local area lightwave networks. complement to our prior work in [11], we address in the paper the problem of dynamically establishing/terminating real-time message streams in response to call setup/clear requests in single-hop star-coupled wdma-based optical networks. we consider a star-coupled broadcast-and-select network architecture in which n stations are connected to a star coupler with w different wavelength channels (w
designing a distributed authorization service. we present the design of a distributed authorization service which parallels existing distributed authentication services. such a service would operate on top of an authentication substrate. there are two central ideas underlying our design: (1) the use of a language, called generalized access control list (gacl), as a common representation for authorization requirements. (2) the use of authenticated delegation to effect authorization offloading from an end server to an authorization server. we present the syntax and semantics of gacl, and illustrate how it can be used to specify authorization requirements that cannot be easily specified by ordinary acl. we also describe the protocols in our design.
a near-optimal packet scheduler for qos networks. a packet scheduler in a quality-of-service (qos) network should be sophisticated enough to support stringent qos constraints at high loads, but it must also have a simple implementation so that packets can be processed at the speed of the transmission link. the earliest-deadline-first (edf) scheduler is the optimal scheduler for bounded-delay services in the sense that it provides the tightest delay guarantees of any scheduler, but an implementation of edf requires the sorting of packets, a complex operation that is not practical for high-speed networks. in this study we present the design, implementation, and analysis of the novel rotating-priority-queues+ (rpq+) scheduler that is near-optimal in the sense that it can approximate edf with arbitrary precision. the rpq+ scheduler uses a set of prioritized fifo queues whose priorities are rearranged (rotated) periodically to increase the priority of waiting packets. we show that rpq+ has the following desirable properties: its implementation requires operations independent of the number of queued packets, it can provide worst-case delay guarantees, and it is always superior to a static-priority (sp) scheduler. for shared-memory architectures, we show that rpq+ can be implemented with little computational overhead. we derive expressions for the worst-case delays in an rpq+ scheduler and demonstrate that the achievable network utilization increases with the frequency of queue rotations, approaching that of edf in the limit. we use numerical examples, including examples based on mpeg video, to show that in realistic scenarios rpq+ can closely approximate edf even for infrequent queue rotations.
characterizing traffic behavior and providing end-to-end service guarantees within atm networks. we propose a rate-controlled service discipline for supporting b-isdn services. according to our approach, traffic streams from different connections can be well regulated at the output of each node based on their rate requirements. moreover, the traffic envelope of a connection inside the network can be effectively characterized. by assuming a leaky-bucket constrained input source, we further prove that the proposed scheme can provide end-to-end delay and jitter bounds for each connection passing through a multi-hop network. finally, we make a comparison of related works and show the effectiveness of our algorithm.
architecture for two-way data services over residential area catv networks. an architectural design for high speed residential data access using the traditional ieee 802.3 medium access protocol over the existing catv network is proposed. the described architecture is attractive in using the existing infrastructure combined with the exisiting access scheme in the residential area and thus it is cost effective and well-suited for home internet access. however, the traditional csma/cd protocol is not suitable for the cable tv network due to its long propagation delay. thus, we propose to combine the existing ieee 802.3 csma/cd mac with the segmented cable subnetworks so that a home user can get access to the internet as if he is using the ethernet at 10 mbps, or fast-ethernet at 100 mbps. only three subcarriers in the passband cable is used and therefore it will not interfere with the traditional broadcasting channels and the future digital video channels. the segmented cable are interconnected by the defined cable bridge (cb) and a simple flow control mechanism is proposed among the cbs. functional components and operations of each cb will also be described. for a fair performance among the subnetworks, a prioritized queueing scheme is also proposed on each cb.
uplink and downlink capacity analysis for two-tier cdma cellular systems. the combination of macrocell and microcell in a two-tier cellular system is attractive because it provides a balance between maximizing the number of users per unit area and minimizing the network control associated with handoff. in this paper, we study system capacity of a two-tier cellular architecture employing 3 tdma/cdma strategies. both the uplink and downlink are evaluated via mathematical analysis. it shows that system performance degrades for larger macrocell or microcell and the capacities are poor for users near the macrocells' boundary. it also shows that huge discrepancy between the results obtained for the center cell versus those obtained for the boundary cell.
fault detection with multiple observers. the authors propose to use a set of independent observers to detect faults in communication systems that are modeled by finite-state machines. an algorithm for constructing these observers and a fast real-time fault detection mechanism used by each observer are given. since these observers run in parallel and independently, one immediate benefit is that of graceful degradation; one failed observer will not cause collapse of the fault management system. in addition, each observer has a simpler structure than the original system and can be operated at higher speed
analysis on packet resequencing for reliable network protocols. packets are sometimes disordered in the network. reliable protocols such as tcp require packets to be accepted, i.e., delivered to the receiving application, in the order they are transmitted at the sender. in order to do so, the receiver's transport layer must resequence the packets with the help of a resequencing buffer. even if the application can consume the packets infinitely fast, the packets may still be delayed for resequencing. in this paper, we model packet disordering by adding an independently and identically distributed (iid) random propagation delay to each packet and analyze the required buffer size for packet resequencing and the resequencing delay for an average packet. we demonstrate that these two quantities can be significant and show how they scale with the network bandwidth.
a randomized error recovery algorithm for reliable multicast. an efficient error recovery algorithm is essential for reliable multicast in large groups. tree-based protocols (rmtp, tmtp, lbrrm) group receivers into local regions and select a repair server for performing error recovery in each region. hence a single server bears the entire responsibility of error recovery for a region. in addition, the deployment of repair servers requires topological information of the underlying multicast tree, which is generally not available at the transport layer. this paper presents rrmp, a randomized reliable multicast protocol which improves the robustness of tree-based protocols by diffusing the responsibility of error recovery among all members in a group. the protocol works well within the existing ip multicast framework and does not require additional support from routers. both analysis and simulation results show that the performance penalty due to randomization is low and can be tuned according to application requirements.
providing absolute differentiated services for real-time application in static-priority scheduling networks. in this paper, we propose and analyze a methodology for providing absolute differentiated services for real-time applications. we develop a method that can be used to derive delay bounds without specific information on flow population. with this new method, we are able to successfully employ a utilization-based admission control approach for flow admission. this approach does not require explicit delay computation at admission time and, hence, is scalable to large systems. we assume the underlying network to use static-priority schedulers. we design and analyze several priority assignment algorithms and investigate their ability to achieve higher utilization bounds. traditionally, schedulers in differentiated services networks assign priorities on a class-by-class basis, with the same priority for each class on each router. in this paper, we show that relaxing this requirement, that is, allowing different routers to assign different priorities to classes, achieves significantly higher utilization bounds.
real-time block transfer under a link sharing hierarchy. most application-level data units are too large to be carried in a single packet (or cell) and must be segmented for network delivery. to an application, the end-to-end delays and loss rate of its data units are much more relevant performance measures than ones specified for individual packets (or cells). the concept of a burst (or block) was introduced to represent a sequence of packets (or cells) that carry an application data unit. in this paper, we describe how a real-time vbr service, with qos parameters for block transfer delay and block loss rate, can be provided by integrating concepts and delay guarantee results from our previous work on burst scheduling, together with ideas from atm block transfer. two new contributions are presented herein. first, we design an admission control algorithm to provide the following classes of service: bounded-delay block transfer with no loss, and bounded-delay block transfer at a specified block loss rate. second, we show how to extend existing end-to-end delay bounds to networks with hierarchical link sharing.
rate-based headend-controlled bandwidth allocation in unidirectional bus metropolitan area networks. the authors introduce and analyze a protocol for unidirectional bus networks in which bandwidth allocation and access fairness are adaptively controlled by the head end of the bus on the basis of traffic measurements. the proposed protocol can control the admitted traffic of a particular type to a desired fraction of the bus capacity and at the same time enforce access fairness faster than other existing protocols, such as the one used in the recently approved ieee 802.6 metropolitan area network (man) standard
performance of statistical multiplexers with finite number of inputs and train arrivals. a slotted statistical multiplexer with a finite number of input links is considered. messages arriving on each input link contain a fixed number of fixed-length packets and are carried to the multiplexer in the form of a packet train at the rate of one packet per slot. several messages may arrive contiguously on an input link; idle periods are geometrically distributed. the multiplexer buffer is modeled as a discrete-time single-server queuing system with train arrivals. by means of a generating function approach, a technique to derive the moments of the buffer occupancy is developed, and an explicit expression for the mean buffer occupancy is given. furthermore, an approximate method is presented to obtain a tight upper bound for the tail distribution of the buffer occupancy, especially for large traffic load
individual qos versus aggregate qos: a loss performance study. this paper explores the differences that can exist between individual and aggregate loss guarantees in an environment where guarantees are only provided at the aggregate level. the focus is on understanding which traffic parameters are responsible for inducing possible deviations and to what extent. in addition, we seek to evaluate the level of additional resources, e.g., bandwidth or buffer, required to ensure that all individual loss measures remain below their desired target. this paper's contributions are in developing analytical models that enable the evaluation of individual loss probabilities in settings where only aggregate losses are controlled, and in identifying traffic parameters that have a major influence on the differences between individual and aggregate losses. the latter allows us to further construct practical tools and guidelines for rapidly assessing if specific traffic sources can be safely multiplexed into a common service class.
restoration strategies and spare capacity requirements in self-healing atm networks. this paper studies the capacity and flow assignment problem arising in the design of self-healing atm networks using the virtual path (vp) concept. the problem is formulated here as a linear programming problem which is solved using standard methods. the objective is to minimize the spare capacity cost for the given restoration requirement. the spare cost depends on restoration strategies used in the network. in the paper we will compare several restoration strategies, notably, global versus failure-oriented reconfiguration, path versus link based restoration and state-dependent versus state-independent restoration, quantitatively in terms of spare cost. the advantages and disadvantages of various restoration strategies are also highlighted. such comparisons provide useful guidance for real network design. further, a new heuristic algorithm is developed in this paper for the design of large self-healing atm networks using path based restoration. numerical results illustrate that the heuristic algorithm is efficient and can give near-optimal solutions for the spare capacity allocation and flow assignment.
multicast atm switches using buffered min structure: a performance study. a (large) multicast atm switch with an external structure of output queueing and an internal structure of buffered mins (multistage interconnection networks) is considered, where the buffered mins (also called a switching network) are composed of switching elements with shared buffer output queueing. a cell replication while routing scheme is used in the switch to implement the multicast function. in this paper, we study the performance of the switch with multicast traffic, mainly via computer simulations. the multicast traffic can be random and bursty. from our study we found that for multicast traffic with a truncated geometric distribution of cell fanouts it has only a slightly worse impact on the performance of the switching elements in isolation or in the last stage of the switching network. the multicast traffic has no worse effect on the switch output buffer behaviour and cell delay in the switching network. moreover, traffic splitting can substantially improve the switching network performance for highly bursty traffic. some analytical approximations are given which could be useful in the dimensioning of switching networks.
mobility-based predictive call admission control and bandwidth reservation in wireless cellular networks. this paper presents call admission control and bandwidth reservation schemes in wireless cellular networks that have been developed based on assumptions more realistic than existing proposals. in order to guarantee the handoff dropping probability, we propose to statistically predict user mobility based on the mobility history of users. our mobility prediction scheme is motivated by computational learning theory, which has shown that prediction is synonymous with data compression. we derive our mobility prediction scheme from data compression techniques that are both theoretically optimal and good in practice. in order to utilize resource more efficiently, we predict not only the cell to which the mobile will handoff but also when the handoff will occur. based on the mobility prediction, bandwidth is reserved to guarantee some target handoff dropping probability. we also adaptively control the admission threshold to achieve a better balance between guaranteeing handoff dropping probability and maximizing resource utilization. simulation results show that the proposed schemes meet our design goals and outperform the static-reservation and cell-reservation schemes.
ip multicasting for point-to-point local distribution. while support for ip multicasting continues to spread enabling new applications, an increasing number of hosts connects to the worldwide internet via low bandwidth point-to-point links, such as wireline or wireless telephone lines. in this paper we discuss existing proposals for local and wide area ip multicasting and their implications for point-to-point links, identify problems with their integration in this environment, and propose alternative special purpose mechanisms to solve these problems. the main problems are overhead due to igmp leave latency and unnecessary continuous probing of potentially power constrained hosts. our solution is an alternative to igmp mechanisms based on join/leave messages for tracking group membership over ptp networks. after presenting the implementation requirements of our proposed and the existing mechanisms, we compare them with respect to performance, interoperability, robustness and implementation complexity, demonstrating that our join/leave protocol is uniformly superior.
a new protocol test sequence generation method based on uios. the authors propose a novel method for test sequence generation based on uios which only needs a minimal verification part. they also prove that the uiov method (or revised unique input/output method) has the same applicability as the characteristic set method. the uiov method can find a test sequence for any minimal finite-state machine. the proposed method has the same applicability as the uiov method. in addition, the method uses a simple test on a given protocol specification to decide whether a verification part is needed for detecting transfer faults, the method can generate a minimal number of input/output sequences for a verification part. a more efficient algorithm for generating uioss and signature sets is presented. it is proven that the upper bound on the length of a uios is (n-1)&times;n rather than nn, where n is the number of states in a finite-state machine
performance characteristics of the d channel access control scheme. in the basic user/network interface of n-isdn (itu-t recommendation i.430), the d-channel is shared by up to 8 terminals for signal and data packets. an analytical model is proposed to reveal the performance characteristics of the access control scheme for the d-channel. numerical and simulation results are shown to demonstrate the performance differentiation of the terminals with different priorities. it is observed that the mean signal delay at low load may become large because of long service time for packets, and that the priority mechanism may not work properly when the loads at terminals are very asymmetric. keywords: n-isdn user-network interface, d channel access control scheme, queueing model, priority mechanism, performance evaluation, simulation
sensitivity analysis of the loss probability in a stationary gradual queue for high-speed networks. in atm networks, each node has its own buffer to store some cells. the buffer size represents a trade-off between cell loss and transmission delay, and therefore, it is a significant concern to evaluate the performance with respect to the buffer size. in this paper, we investigate the sensitivity of the loss probability with respect to the buffer size by considering a gradual input queue with a finite buffer. gradual inputs are considered as those representing a bursty traffic of cells. applying the perturbation analysis technique to this model, we derive the strongly consistent sensitivity estimates, and combining with the likelihood ratio method, we confirm that our estimates lead to the reasonable simulation results.
multi-channel deflection crossbar (mcdc): a vlsi optimized architecture for multi-channel atm switching. we propose the multi-channel deflection crossbar (mcdc) as a promising architecture for broadband atm switching under the realistic constraints imposed by vlsi technology. mcdc is an internally nonblocking, buffer efficient, crossbar based architecture. mcdc is also capable of multi-channel switching with cell sequence integrity preserved. through a comparative study against a well-known atm switch architecture, we show that the proposed mcdc architecture is able to incorporate a greater number of input channels and buffers for a given ic die size and requires a lower clocking rate.
a reliable and parallel double-ring fddi metropolitan area network. the authors present a reliable double-ring metropolitan area network architecture, called dorfman, based on an enhanced fiber distributed data interface (fddi) protocol. dorfman is composed of two local ring networks interconnected via two monitors. the two monitors are used to perform simple routing and error recovery logic as well as mode transitions of dorfman. there are three modes defined in dorfman: local, global, and transition modes. during the local mode, dorfman allows double rings to operate in parallel. during the global mode, dorfman behaves as an fddi network. modes are dynamically switched between local and global modes on a demand basis. the bandwidth waste resulting from the transition of modes has been reduced to a minimum. performance analysis and simulation results show that with a reasonable degree of locality assumed, twice the throughput of an fddi network can be achieved in dorfman. an error recovery scheme for dorfman is addressed
an end-to-end qos framework with on-demand bandwidth reconfiguration. this paper proposes a new qos framework, called the on-demand qos path framework (odp). it provides end-to-end qos guarantees to individual flows with minimal overhead, while keeping the scalability characteristic of diffserv. odp exercises per-flow admission control and end-to-end bandwidth reservation at the edge of the network and only differentiates service types in the core of the network. in addition, to adapt to dynamically changing traffic load, odp monitors the bandwidth utilization of the network and performs dynamic bandwidth reconfiguration in the network core based on the monitored bandwidth utilization. through extensive simulations, the performance of odp is investigated and compared with that of intserv and diffserv frameworks. the simulation results clearly showed that odp provides end-to-end qos guarantees to individual flows, which diffserv can not provide, with much less overhead than intserv.
a tdm-based multibus packet switch. a novel packet switch architecture using two sets of time division multiplexed (tdm) buses is proposed. the horizontal buses collect packets from the input ports while the vertical buses distribute the packets to the output ports. the two sets of buses are connected by a set of switching elements which coordinate the connections between the horizontal buses and the vertical buses so that each vertical bus is connected to only one horizontal bus at a time. the switch has the advantages of: (1) it adds input and output ports without increasing the bus and i/o adaptor speed; (2) it is internally unbuffered; (3) it has a very simple control circuit; and (4) it has 100% potential throughput under uniform traffic. a combined analytical-simulation method is used to obtain the packet delay and packet loss probability. numerical results show that for satisfactory performance the buses need to run about 30% faster than the input line rate. with this speedup, even at a utilization factor of 0.9, the input queue can give a packet loss of 10 -6 with only 31 buffers per input adaptor. the output queue behaves essentially as an m/d/1 queue
transient behaviors of tcp-friendly congestion control protocols. we investigate the fairness, smoothness, responsiveness, and aggressiveness of tcp and three representative tcp-friendly congestion control protocols: gaimd, tfrc, and tear. the properties are evaluated both analytically and experimentally by studying protocol responses to three network environment changes. the first environment change is the inherent fluctuations in a stationary network environment. we consider three types of sending rate variations: smoothness, short-term fairness, and long-term fairness. for a stationary environment, we observe that smoothness and fairness are positively correlated. we derive an analytical expression for the sending rate coefficient of variation for each of the four protocols. these analytical results match well with experimental results. the other two environment changes we study are a step increase of network congestion and a step increase of available bandwidth. protocol responses to these changes reflect their responsiveness and aggressiveness, respectively.
alternate path routing for multicast. current network-layer multicast routing protocols build multicast trees based only on hop count and policy. if a tree cannot meet application requirements, the receivers have no alternative. in this paper, we propose a general and modular architecture that integrates alternate path routing with the network's multicast services. this enables individual multicast receivers to reroute a multicast tree according to their needs, subject to policy restrictions. our design focuses on the two primary components of this architecture--a loop-free path installation protocol and a scalable, distributed path computation algorithm. based on a simulation study, we demonstrate that using alternate path routing enables receivers to find acceptable paths nearly as well as a link-state protocol, with much lower overhead. we also show that our approach scales to large networks and that performance improves as a multicast group grows in size.
statistical synchronization among participants in real-time multimedia conference. in this paper, an algorithm to determine the set of packets generated continuously and periodically from different participants that are arriving at a node either for mixing at the master of a conference, or for simply playing back at a regular participant of a conference, is proposed. the essence of the algorithm is to estimate the average packet arrival time (or reference time) for each participant. with the reference time at hand, the maximum jitter and the optimum waiting time for a mixer to wait packets from all participants can be determined. the error of the proposed algorithm is enumerated by the chernoff bound and is shown to be acceptable in practical application.
finite buffer discrete-time queues with multiple markovian arrivals and services in atm networks. an efficient computational procedure to calculate the queue size distribution in a finite buffer queuing system with a number of independent sources is presented. each source is characterized by a finite state discrete-time markov chain. an explicit expression for the queue size distribution is obtained directly. the method is based on computing the modified spectral expansion of the state distribution of the system. this representation requires evaluating the roots of the entire system characteristic function and solving a set of linear system equations. exact results show that the cell loss probability depends only on the ratio of the buffer capacity to burst length. an approximation expression for the cell loss probability based on asymptotic analysis is also presented. numerical results show that the approximation is accurate, especially when the system load is heavy. the effect of burst length on the cell loss probability is investigated
logarithmically scalable routing algorithms in large optical networks. in this paper, we present three logarithmically scalable routing algorithms for very large optical networks. the algorithms are based on a hierarchical approach. each algorithm requires a different amount of information to be stored at each node, and results in a different efficiency. the network capacity provided by each algorithm is compared with that provided by the global shortest path algorithm (which is not scalable). it is found that the network capacities of the three algorithms are almost the same as that of the global shortest path algorithm. for fixed routing algorithms, we use an approximate analysis from which the blocking probability at a fixed network load can iterately be obtained (we use call blocking probability as our quality objective and compare network capacity by observing the difference in the offered load which produces the same blocking probability). the approximate analysis is validated through simulation and is found to be very accurate. scalable, quasi-dynamic routing algorithms are also studied. numerical results show that, when the node-capacity is equal to the capacity of a single wavelength and the bandwidth required per call is large ( greater than 24% of the link capacity), the capacity provided by the quasi-dynamic routing algorithm is very close to that of an infinite capacity centralized switch (lowest possible call blocking caused exclusively by congestion on the finite capacity user input/output links, never by the switch fabric itself). in all the examples considered, the improvement of the quasi-dynamic routing algorithm over the fixed routing algorithm is significant.
using the small-world model to improve freenet performance. efficient data retrieval in an unstructured peer-to-peer system like freenet is a challenging problem. in this paper, we study the impact of workload on the performance of freenet. we find that there is a steep reduction in the hit ratio of document requests with increasing load in freenet. we show that a slight modification of freenet's routing table cache replacement scheme (from lru to a replacement scheme that enforces clustering in the key space) can significantly improve performance. our modification is based on intuition from the small-world models and theoretical results by kleinberg; our replacement scheme forces the routing tables to resemble neighbor relationships in a small-world acquaintance graph--clustering with light randomness. our simulations show that this new scheme improves the request hit ratio dramatically while keeping the small average hops per successful request comparable to lru. a simple, highly idealized model of freenet under clustering with light randomness proves that the expected message delivery time in freenet is o(log n) if the routing tables satisfy the small-world model and have the size θ(log2n).
maximal average loss rates for a single gps server system with finite buffers. considers a single server system with finite buffers that services.
a convergence proof for an iterative method for atm networks. a flow model for evaluating the performance of a network of asynchronous transfer mode (atm) switches is presented. the performance measures used include the link (nodal) and end-to-end cell loss probabilities as well as the link (nodal) and end-to-end cell delays. in the model, the routing assignments are assumed to be given. the assumed form of routing assignments may be used to represent either virtual circuit or datagram service. due to the nonlinear relationship between cell losses and offered flows, the flow model is a system of nonlinear equations. the authors develop a sufficient condition for the existence of a unique solution to the nonlinear system of equations. they present an iterative model and prove that it converges to a unique fixed point provided the sufficient condition is satisfied. the unique fixed point corresponds to the unique solution to the flow model
modeling of motion classified vbr video codecs. the authors use a motion adaptive variable-bit-rate (vbr) video codec and propose a motion classified model to represent the characteristics of various classes of motion activities. the codec switches between interframe, motion compensated, and intraframe coding corresponding to low, medium, and high motions and scene changes, respectively. the model captures the motion of various video scenes and the codec structure by providing the statistics of vbr-coded video' traffic through a first-order composite autoregressive process with three motion classes. the parameters of this model are derived from a vbr-coded sample video sequence such that the bit rate distribution and the autocorrelation in bit rates of two successive frames are matched. the validity and accuracy of the model are verified. using this model, the characteristics of aggregated traffic sources are discussed
topological design of loss-free switch-based lans. the paper presents a new design methodology and tools to construct a switch-based lan with (i) scalable throughput, (ii) no loss due to congestion, and (iii) two routing modes: fifo or non-fifo. more specifically, given a bounded degree (number of switch ports) at each node, the design is based on the construction of multiple virtual rings under the following constraints: (i) the virtual rings are pairwise edge-disjoint, and (ii) there is at least one virtual ring between any pair of nodes. the target topology is obtained from the edge union of the multiple virtual rings. the objectives of the above two constraints are (i) to ensure no loss due to congestion inside the network of bursty traffic sources, and (ii) to ensure convergence of packets/cells to their destinations. the virtual rings are constructed by a new methodology that employs combinatorial block designs together with a new algorithm for realizing any size networks. it is shown that the bound on the maximum route length, under the two constraints, is o(/spl radic/n) for an n-node network.
hop-by-hop congestion control over a wireless multi-hop network. this paper focuses on congestion control over multi-hop, wireless networks. in a wireless network, an important constraint that arises is that due to the mac (media access control) layer. many wireless macs use a time-division strategy for channel access, where, at any point in space, the physical channel can be accessed by a single user at each instant of time. in this paper, we develop a fair hop-by-hop congestion control algorithm with the mac constraint being imposed in the form of a channel access time constraint, using an optimization-based framework. in the absence of delay, we show that this algorithm are globally stable using a lyapunov-function-based approach. next, in the presence of delay, we show that the hop-by-hop control algorithm has the property of spatial spreading. in other words, focused loads at a particular spatial location in the network get "smoothed" over space. we derive bounds on the "peak load" at a node, both with hop-by-hop control, as well as with end-to-end control, show that significant gains are to be had with the hop-by-hop scheme, and validate the analytical results with simulation.
efficient selective frame discard algorithms for stored video delivery across resource constrained networks. video delivery from a server to a client across a network is an important component of many multimedia applications. while delivering a video stream across a resource constrained network, loss of frames may be unavoidable. under such circumstances, it is desirable to find a server transmission schedule that can efficiently utilize the network resources while maximizing the perceived quality-of-service (qos) at the client. to address this issue, in this paper we introduce the notion of selective frame discard at the server and formulate the optimal selective frame discard problem using a qos-based cost function. given network bandwidth and client buffer constraints, we develop an o (n log n) algorithm to find the minimum number of frames that must be discarded in order to meet these constraints. the correctness of the algorithm is also formally established. we present a dynamic programming based algorithm for solving the problem of optimal selective frame discard. since the computational complexity of the optimal algorithm is prohibitively high in general, we also develop several efficient heuristic algorithms for selective frame discard. these algorithms are evaluated using jpeg and mpeg video traces.
supporting cooperative caching in ad hoc networks. most researches in ad hoc networks focus on routing and not much work has been done on data access. a common technique used to improve the performance of data access is caching. cooperative caching, which allows the sharing and coordination of cached data among multiple nodes, can further explore the potential of the caching techniques. due to mobility and resource constraints of ad hoc networks, cooperative caching techniques designed for wired networks may not be applicable to ad hoc networks. in this paper, we design and evaluate cooperative caching techniques to efficiently support data access in ad hoc networks. we first propose two schemes: cachedata, which caches the data, and cachepath, which caches the data path. after analyzing the performance of those two schemes, we propose a hybrid approach (hybridcache), which can further improve the performance by taking advantage of cachedata and cachepath while avoiding their weaknesses. cache replacement policies are also studied to further improve the performance. simulation results show that the proposed schemes can significantly reduce the query delay and message complexity when compared to other caching schemes.
dirsmin: a fault-tolerant switch for b-isdn applications using dilated reduced-stage min. develops and analyzes a dilated high performance fault tolerant fast packet multistage interconnection network (min). in this new design, the links at the input and the output stages of a dilated banyan-based min are rearranged to create multiple routes for each source-destination pair in the network after removing one stage in the network. these multiple paths are link- and node-disjoint. fault tolerance at low latency is achieved by sending multiple copies of each input packet simultaneously using different routes and different priorities. this guarantees that high throughput is maintained even in the presence of fault. throughput is analyzed using simulation and analysis and the authors show that the new design has considerably higher performance in the presence of a faulty switching element (se) or link in comparison to dilated networks.
integrated rate and credit feedback control for abr service in atm networks. we propose a flow-control scheme that combines the merits of credit- and rate-based flow-control schemes by applying direct control over both bandwidth and buffer resources. the goal of the proposed scheme is to design an optimal rate-control policy for a given finite buffer capacity that maximizes average throughput and bounds end-to-end delay. by applying higher-order rate control, the proposed scheme not only makes the rate process converge to the neighborhood of link bandwidth, but also confines the queue-length fluctuation to a regime bounded by buffer capacity (thus guaranteeing lossless transmission). using the fluid approximation method, we model the proposed flow-control scheme and study the system dynamic behavior for abr (available bit rate) service under the most stressful traffic condition. we derive the expressions for queue build-ups and average throughput in both transient and equilibrium states. the analytical results have shown the proposed scheme to be stable and efficient in that the source rate and bottleneck queue length rapidly converge to the designated operating region. also, presented are examples showing that the proposed scheme outperforms the other existing schemes.
on-line optimal wavelength assignment in wdm networks with shared wavelength converter pool. in this paper, we study on-line wavelength assignment in wavelength-routed wdm networks under both unicast and multicast traffic where nodes in the networks have wavelength conversion ability. since wavelength converters are still expensive and difficult to implement, we consider the case where nodes in networks have only a limited number of converters that are shared by all input channels. we study the problem of setting up connections in such networks using minimum number of wavelength converters. for unicast traffic, we first study the problem of setting up a lightpath on a given link-path with minimum number of conversions. we give a simple algorithm that solves it in o(tk) time where t is the number of links on the path and k is the number of wavelengths per fiber, as compared to the best known existing method that needs to construct an auxiliary graph and apply the dijkstra's algorithm. we also consider the problem of setting up a lightpath while using wavelength converters at nodes with fewer available converters only when necessary, and give an o(tk) time algorithm. we then generalize this technique to wdm networks with arbitrary topologies and give an algorithm that sets up an optimal lightpath network-wide in o(nk+lk) time, where n and l are the number of nodes and links in the network, respectively. we also consider multicast traffic in this paper. finding an optimal multicast light-tree is known to be np-hard and is usually solved by first finding a link-tree then finding a light-tree on the link-tree. finding an optimal link-tree is also np-hard and has been extensively studied. thus, we focus on the second problem which is to set up a light-tree on a given link-tree with minimum number of conversions. we propose a new multicast conversion model with which the output of the wavelength converter is split-table to save the usage of converters. we show that under this model the problem of setting up an optimal light-tree is np-hard and then give efficient heuristics to solve it approximately.
design of robust congestion controllers for atm networks. we propose an approach to design a rate-based proportional traffic controller in order to flow-regulate the best-effort service (e.g., abr traffic) and guaranteed service traffic through an atm switch. the controller is distributed and it has a very simple structure. its local controller at each source node is open-loop stable and only requires the knowledge of the buffer occupancy at the bottleneck switch. we show that this controller is fair and is not sensitive to the change of vcs over time. it does not have oscillation and can achieve a high utilization.
network bandwidth requirements for scalable on-demand streaming. previously proposed streaming protocols using broadcast or multicast are able to deliver multimedia files on-demand with required server bandwidth that grows much slower than linearly with request rate, or with the inverse of client start-up delay. the same efficiencies can be achieved for network bandwidth if delivery is over a true broadcast channel. this paper considers the required network bandwidth for on-demand streaming over multicast delivery trees. we consider both simple canonical delivery trees, and more complex cases in which delivery trees are constructed using both existing and new algorithms for randomly generated network topologies and client site locations. results in this paper quantify the potential savings from use of multicast trees that are configured to minimize network bandwidth rather than the latency to the content server. further, we determine the network bandwidth usage of particular immediate service and periodic broadcast on-demand streaming protocols. the periodic broadcast protocol is able to simultaneously achieve close to the minimum possible network and server bandwidth usage.
performance analysis of finite output-buffered multistage atm switching fabrics. a new and accurate markov chain model for evaluating the performance of multistage atm switching fabrics with 2/spl times/2 finite output-buffered switching elements is proposed. by comparing the results obtained from the proposed model, existing models, and simulations, it has been shown that the proposed model is much more accurate than existing models in the presence of a non-uniform traffic in the switch. the results from existing models are unsatisfactory in the presence of an increased blocking in the switch arising due to a non-uniform traffic in the switch. on the contrary, the proposed model is very robust even under severe blocking inside the switch.
rdcf: a relay-enabled medium access control protocol for wireless ad hoc networks. it is well known that ieee 802.11 provides a physical layer multirate capability and, hence, mac layer mechanisms are needed to exploit this capability. several solutions have been proposed to achieve this goal. however, these solutions only consider how to exploit good channel quality for the direct link between the sender and the receiver. since ieee 802.11 supports multiple transmission rates in response to different channel conditions, data packets may be delivered faster through a relay node than through the direct link if the direct link has low quality and low rate. in this paper, we propose a novel mac layer relay-enabled distributed coordination function (dcf) protocol, called rdcf, to further exploit the physical layer multirate capability. we design a protocol to assist the sender, the relay node, and the receiver to reach an agreement on which data rate to use and whether to transmit the data through a relay node. considering various issues, such as, bandwidth utilization, channel errors, and security, we propose techniques to further improve the performance of rdcf. simulation results show that rdcf can significantly reduce the packet delay, improve the system throughput, and alleviate the impact of channel errors on fairness.
a five-phase reervation protocol (fprp) for mobile ad hoc networks. a new single channel, time division multiple access (tdma)-based broadcast scheduling protocol, termed the five-phase reservation protocol (fprp), is presented for mobile ad hoc networks. the protocol jointly and simultaneously performs the tasks of channel access and node broadcast scheduling. the protocol allows nodes to make reservations within tdma broadcast schedules. it employs a contention-based mechanism with which nodes compete with each other to acquire tdma slots. the fprp is free of the "hidden terminal" problem, and is designed such that reservations can be made quickly and efficiently with negligible probability of conflict. it is fully-distributed and parallel (a reservation is made through a localized conversation between nodes in a 2-hop neighborhood), and is thus scalable. a "multihop aloha" policy is developed to support the fprp. this policy uses a multihop, pseudo-bayesian algorithm to calculate contention probabilities and enable faster convergence of the reservation procedure. the performance of the protocol, measured in terms of scheduling quality, scheduling overhead and robustness in the presence of nodal mobility, has been studied via simulations. the results showed that the protocol works very well in all three aspects. some future work and applications are also discussed.
using statistical bandwidth in token ring networks. a new network access protocol, called restricted destination access protocol, for transmitting data packets in token ring networks, is proposed and analyzed. this protocol is based on the existing token passing access protocol and makes use of the extra statistical bandwidth that exists in token ring networks. a transmission capacity of greater than unity can be supported. simulation results using the protocol in a modified fiber distributed data interface (fddi) network are included
a source-based algorithm for delay-constrained minimum-cost multicasting. a new heuristic algorithm is presented for constructing minimum-cost multicast trees with delay constraints. the new algorithm can set variable delay bounds on destinations and handles two variants of the network cost optimization goal: one minimizing the total cost (total bandwidth utilization) of the tree, and another minimizing the maximal link cost (the most congested link). instead of the single-pass tree construction approach used in most previous heuristics, the new algorithm is based on a feasible search optimization method which starts with the minimum-delay tree and monotonically decreases the cost by iterative improvement of the delay-bounded tree. the optimality of the costs of the delay-bounded trees obtained with the new algorithm is analyzed by simulation. depending on how tight the delay bounds are, the costs of the multicast trees obtained with the new algorithm are shown to be very close to the costs of the trees obtained by the kou, markowsky and berman's algorithm (1981).
customized service creation: a new order for telecommunication services. the evolution from the intelligent network to the advanced intelligent network (ain) is described. the concept behind ain and its architecture are introduced. a bellcore product for the ain, the space system, is illustrated. the authors discuss the user-friendly programming language, service creation platform, multiple-services application, and reliable node platform of the space system
mobile radio slotted aloha with capture and diversity. in this paper, the slotted aloha protocol in a mobile radio environment, in the presence of ricean fading, two-fold antenna diversity and multiple reception capability, is considered. the capture probabilities and the average throughput are computed, and the issue of stability is addressed. it is shown that diversity can improve the system performance, although only to a certain extent. some extensions are also considered: in particular, the use of a higher degree of diversity is investigated.
fairness in broadband isdn. the authors propose a fairness criterion for sharing spare (unallocated) capacity among different nonguaranteed bursty data sources with different relative usage values. based on this criterion, the throughput of some sources may be controlled in the case where the total average offered traffic within a certain small time interval is greater than the total available spare capacity. it is proposed that all controlled sources will enjoy a share of capacity which is proportional to their relative usage values, and that no uncontrolled source will enjoy higher relative throughput than a controlled source. this criterion uniquely defines a set of throughputs for all sources. a method to compute these throughput values which has been demonstrated by several examples has been presented
a traffic engineering approach for placement and selection of network services. network services are provided by means of dedicated service gateways, through which traffic flows are directed. existing work on service gateway placement has been primarily focused on minimizing the length of the routes through these gateways. only limited attention has been paid to the effect these routes have on overall network performance. we propose a novel approach for the service placement problem, which takes into account traffic engineering considerations. rather than trying to minimize the length of the traffic flow routes, we take advantage of these routes in order to enhance the overall network performance. we divide the problem into two subproblems: finding the best location for each service gateway, and selecting the best service gateway for each flow. we propose efficient algorithms for both problems and study their performance. our main contribution is showing that placement and selection of network services can be used as effective tools for traffic engineering.
cr switch: a load-balanced switch with contention and reservation. load-balanced switches have received a great deal of attention recently as they are much more scalable than other existing switch architectures in the literature. however, as there exist multiple paths for flows of packets to traverse through load-balanced switches, packets in such switches may be delivered out of order. in this paper, we propose a new switch architecture, called the contention and reservation (cr) switch, that not only delivers packets in order but also guarantees 100% throughput. the key idea, as in a multiple-access channel, is to operate the cr switch in two modes: 1) the contention mode in light traffic and 2) the reservation mode in heavy traffic. to do this, we invent a new buffer management scheme, called virtual output queue with insertion (i-voq).with the i-voq scheme, we give rigorous mathematical proofs for 100% throughput and in-order packet delivery of the cr switch. by computer simulations, we also demonstrate that the average packet delay of the cr switch is considerably lower than other schemes in the literature, including the uniform frame spreading scheme [10], the padded frame scheme [8], and the mailbox switch [5].
optimal rate-reliability-delay tradeoff in networks with composite links. networks need to accommodate diverse applications with different quality-of-service (qos) requirements. new ideas at the physical layer are being developed for this purpose, such as diversity embedded coding, which is a technique that combines high rates with high reliability. we address the problem of how to fully utilize different rate-reliability characteristics at the physical layer to support different types of traffic over a network and to jointly maximize their utilities. we set up a new framework based on utility maximization for networks with composite links, meaning that each link consists of sub-links that can attain different rate-reliability characteristics simultaneously. we incorporate delay, in addition to rate and reliability, into the utility functions. to accommodate different types of traffic, we propose distributed algorithms converging to the optimal rate-reliability-delay tradeoff based on capacity division and priority queueing. numerical results show that compared with traditional codes, the new codes can provide higher network utilities for all traffic types simultaneously. the results also show that priority queueing achieves higher network utility than capacity division.
performance of random access scheduling schemes in multi-hop wireless networks. the scheduling problem in multi-hop wireless networks has been extensively investigated. although throughput optimal scheduling solutions have been developed in the literature, they are unsuitable for multi-hop wireless systems because they are usually centralized and have very high complexity. in this paper, we develop a random-access based scheduling scheme that utilizes local information. the important features of this scheme include constant-time complexity, distributed operations, and a provable performance guarantee. analytical results show that it guarantees a larger fraction of the optimal throughput performance than the state-of-the-art. through simulations with both single-hop and multi-hop traffics, we observe that the scheme provides high throughput, close to that of a well-known highly efficient centralized greedy solution called the greedy maximal scheduler.
load balancing in large-scale rfid systems. a radio frequency identifier (rfid) system consists of inexpensive, uniquely-identifiable tags that are mounted on physical objects, and readers that track these tags (and hence these physical objects) through rf communication. for many performance measures in large-scale rfid systems, the set of tags to be monitored needs to be properly balanced among all readers. in this paper we, therefore, address this load balancing problem for readers - how should a given set of tags be assigned to readers such that the cost for monitoring tags across the different readers is balanced, while guaranteeing that each tag is monitored by at least one reader. we first present centralized solutions to two different variants of this load balancing problem: (i) min-max cost assignment (mca), and (ii) min-max tag count assignment (mta). we show that mca, the generalized variant of the load balancing problem, is np-hard and hence present a 2-approximation algorithm for it. we next present an optimal centralized solution for mta, an important specialized variant of the problem. subsequently, we present a localized distributed algorithm that is probabilistic in nature and closely matches the performance of the centralized algorithms. finally we present detailed simulation results that illustrate the performance of the localized distributed approach, how it compares with the centralized optimal and near-optimal solutions, and how it adapts the solution with changes in tag distribution and reader topology. our results demonstrate that our schemes achieve very good performance even in highly dynamic large-scale rfid systems.
multicast scheduling in cellular data networks. multicast is an efficient means of transmitting the same content to multiple receivers while minimizing network resource usage. applications that can benefit from multicast such as multimedia streaming and download, are now being deployed over 3g wireless data networks. existing multicast schemes transmit data at a fixed rate that can accommodate the farthest located users in a cell. however, users belonging to the same multicast group can have widely different channel conditions. thus existing schemes are too conservative by limiting the throughput of users close to the base station. we propose two proportional fair multicast scheduling algorithms that can adapt to dynamic channel states in cellular data networks that use time division multiplexing: inter-group proportional fairness (ipf) and multicast proportional fairness (mpf). these scheduling algorithms take into account (1) reported data rate requests from users which dynamically change to match their link states to the base station, and (2) the average received throughput of each user inside its cell. this information is used by the base station to select an appropriate data rate for each group. we prove that ipf and mpf achieve proportional fairness among groups and among all users inside a cell respectively. through extensive packet-level simulations, we demonstrate that these algorithms achieve good balance between throughput and fairness among users and groups.
designing multihop wireless backhaul networks with delay guarantees. as wireless access technologies improve in data rates, the problem focus is shifting towards providing adequate backhaul from the wireless access points to the internet. existing wired backhaul technologies such as copper wires running at dsl, t1, or t3 speeds can be expensive to install or lease, and are becoming a performance bottleneck as wireless access speeds increase. longhaul, non-line-of-sight wireless technologies such as wimax (802.16) hold the promise of enabling a high speed wireless backhaul as a cost-effective alternative. however, the biggest challenge in building a wireless backhaul is achieving guaranteed performance (throughput and delay) that is typically provided by a wired backhaul. this paper explores the problem of efficiently designing a multihop wireless backhaul to connect multiple wireless access points to a wired gateway. in particular, we provide a generalized link activation framework for scheduling packets over this wireless backhaul, such that any existing wireline scheduling policy can be implemented locally at each node of the wireless backhaul. we also present techniques for determining good interference-free routes within our scheduling framework, given the link rates and cross-link interference information. when a multihop wireline scheduler with worst case delay bounds (such as wfq or coordinated edf) is implemented over the wireless backhaul, we show that our scheduling and routing framework guarantees approximately twice the delay of the corresponding wireline topology. finally, we present simulation results to demonstrate the low delays achieved using our framework.
jetmax: scalable max-min congestion control for high-speed heterogeneous networks. recent surge of interest towards congestion control that relies on single-link feedback (e.g., xcp, rcp, maxnet, emkc, vcp), suggests that such systems may offer certain benefits over traditional models of additive packet loss. besides topology-independent stability and faster convergence to efficiency/fairness, it was recently shown that any stable single-link system with a symmetric jacobian tolerates arbitrary fixed, as well as time-varying, feedback delays. although delay-independence is an appealing characteristic, the emkc system developed in exhibits undesirable equilibrium properties and slow convergence behavior. to overcome these drawbacks, we propose a new method called jetmax and show that it admits a low-overhead implementation inside routers (three additions per packet), overshoot-free transient and steady state, tunable link utilization, and delay-insensitive flow dynamics. the proposed framework also provides capacity-independent convergence time, where fairness and utilization are reached in the same number of rtt steps for a link of any bandwidth. given a 1mb/s, 10gb/s, or googol (10^1^0^0) bps link, the method converges to within 1% of the stationary state in six rtts. we finish the paper by comparing jetmax's performance to that of existing methods in ns2 simulations and discussing its linux implementation.
modeling per-flow throughput and capturing starvation in csma multi-hop wireless networks. multi-hop wireless networks employing random access protocols have been shown to incur large discrepancies in the throughputs achieved by the flows sharing the network. indeed, flow throughputs can span orders of magnitude from near starvation to many times greater than the mean. in this paper, we address the foundations of this disparity. we show that the fundamental cause is not merely differences in the number of contending neighbors, but a generic coordination problem of csma-based random access in a multi-hop environment. we develop a new analytical model that incorporates this lack of coordination, identifies dominating and starving flows and accurately predicts per-flow throughput in a large-scale network.we then propose metrics that quantify throughput imbalances due to the mac protocol operation. our model and metrics provide a deeper understanding of the behavior of csma protocols in arbitrary topologies and can aid the design of effective protocol solutions to the starvation problem.
low-complexity distributed scheduling algorithms for wireless networks. we consider the problem of designing distributed scheduling algorithms for wireless networks. we present two algorithms, both of which achieve throughput arbitrarily close to that of maximal schedules, but whose complexity is low due to the fact that they do not necessarily attempt to find maximal schedules. the first algorithm requires each link to collect local queue-length information in its neighborhood, and its complexity is otherwise independent of the size and topology of the network. the second algorithm, presented for the node-exclusive interference model, does not require nodes to collect queue-length information even in their local neighborhoods, and its complexity depends only on the maximum node degree in the network.
fault-tolerant relay node placement in heterogeneous wireless sensor networks. existing work on placing additional relay nodes in wireless sensor networks to improve network connectivity typically assumes homogeneous wireless sensor nodes with an identical transmission radius. in contrast, this paper addresses the problem of deploying relay nodes to provide fault tolerance with higher network connectivity in heterogeneous wireless sensor networks, where sensor nodes possess different transmission radii. depending on the level of desired fault tolerance, such problems can be categorized as: 1) full fault-tolerant relay node placement, which aims to deploy a minimum number of relay nodes to establish k (k \ge 1) vertex-disjoint paths between every pair of sensor and/or relay nodes and 2) partial fault-tolerant relay node placement, which aims to deploy a minimum number of relay nodes to establish k (k \ge 1) vertex-disjoint paths only between every pair of sensor nodes. due to the different transmission radii of sensor nodes, these problems are further complicated by the existence of two different kinds of communication paths in heterogeneous wireless sensor networks, namely, two-way paths, along which wireless communications exist in both directions; and one-way paths, along which wireless communications exist in only one direction. assuming that sensor nodes have different transmission radii, while relay nodes use the same transmission radius, this paper comprehensively analyzes the range of problems introduced by the different levels of fault tolerance (full or partial) coupled with the different types of path (one-way or two-way). since each of these problems is np-hard, we develop o(\sigma k^2)-approximation algorithms for both one-way and two-way partial fault-tolerant relay node placement, as well as o(\sigma k^3)-approximation algorithms for both one-way and two-way full fault-tolerant relay node placement (\sigma is the best performance ratio of existing approximation algorithms for finding a minimum k-vertex connected spanning graph). to facilitate the applications in higher dimensions, we also extend these algorithms and derive their performance ratios in d-dimensional heterogeneous wireless sensor networks (d \ge 3). finally, heuristic implementations of these algorithms are evaluated via qualnet simulations.
prime: peer-to-peer receiver-driven mesh-based streaming. the success of file swarming mechanisms such as bittorrent has motivated a new approach for scalable streaming of live content that we call mesh-based peer-to-peer (p2p) streaming. in this approach, participating end-systems (or peers) form a randomly connected mesh and incorporate swarming content delivery to stream live content. despite the growing popularity of this approach, neither the fundamental design tradeoffs nor the basic performance bottlenecks in mesh-based p2p streaming are well understood. in this paper, we follow a performance-driven approach to design prime, a scalable mesh-based p2p streaming mechanism for live content. the main design goal of prime is to minimize two performance bottlenecks, namely bandwidth bottleneck and content bottleneck. we show that the global pattern of delivery for each segment of live content should consist of a diffusion phase which is followed by a swarming phase. this leads to effective utilization of available resources to accommodate scalability and also minimizes content bottleneck. using packet level simulations, we carefully examine the impact of overlay connectivity, packet scheduling scheme at individual peers and source behavior on the overall performance of the system. our results reveal fundamental design tradeoffs of mesh-based p2p streaming for live content.
optimal pricing in a free market wireless network. we consider an ad-hoc wireless network operating within a free market economic model. users send data over a choice of paths, and scheduling and routing decisions are updated dynamically based on time varying channel conditions, user mobility, and current network prices charged by intermediate nodes. each node sets its own price for relaying services, with the goal of earning revenue that exceeds its time average reception and transmission expenses. we first develop a greedy pricing strategy that maximizes social welfare while ensuring all participants make non-negative profit. we then construct a (non-greedy) policy that balances profits more evenly by optimizing a profit fairness metric. both algorithms operate in a distributed manner and do not require knowledge of traffic rates or channel statistics. this work demonstrates that individuals can benefit from carrying wireless devices even if they are not interested in their own personal communication.
gradually reconfiguring virtual network topologies based on estimated traffic matrices. traffic matrix is essential to traffic engineering (te) methods. because it is difficult to monitor traffic matrices directly, several methods for estimating them from link loads have been proposed. however, estimated traffic matrix includes estimation errors which degrade the performance of te significantly. in this paper, we propose a method that reduces estimation errors while reconfiguring the virtual network topology (vnt) by cooperating with the vnt reconfiguration. in our method, the vnt reconfiguration is divided into multiple stages instead of reconfiguring the suitable vnt at once. by dividing the vnt reconfiguration into multiple stages, our traffic matrix estimation method calibrates and reduces the estimation errors in each stage by using information monitored in prior stages. we also investigate the effectiveness of our proposal using simulations. the results show that our method can improve the accuracy of the traffic matrix estimation and achieve an adequate vnt as is the case with the reconfiguration using the actual traffic matrices.
cell breathing techniques for load balancing in wireless lans. maximizing network throughput while providing fairness is one of the key challenges in wireless lans (wlans). this goal is typically achieved when the load of access points (aps) is balanced. recent studies on operational wlans, however, have shown that ap load is often substantially uneven. to alleviate such imbalance of load, several load balancing schemes have been proposed. these schemes commonly require proprietary software or hardware at the user side for controlling the user-ap association. in this paper we present a new load balancing technique by controlling the size of wlan cells (i.e., ap's coverage range), which is conceptually similar to cell breathing in cellular networks. the proposed scheme does not require any modification to the users neither the ieee 802.11 standard. it only requires the ability of dynamically changing the transmission power of the ap beacon messages. we develop a set of polynomial time algorithms that find the optimal beacon power settings which minimize the load of the most congested ap. we also consider the problem of network-wide min-max load balancing. simulation results show that the performance of the proposed method is comparable with or superior to the best existing association-based methods.
taking the skeletons out of the closets: a simple and efficient topology discovery scheme for large ethernet lans. we propose a simple and efficient algorithmic solution for discovering the physical topology of large, heterogeneous ethernet lans that may include multiple subnets as well as uncooperative network elements, like hubs. our scheme utilizes only generic mib information and does not require any hardware or software modification of the underlying network elements. by rigorous analysis, we prove that our method correctly infers the network topology and has low communication and computational overheads. our simulation results show that the scheme successfully infers the complete topology in the vast majority of the cases, including many instances that cannot be inferred by other methods. finally, our proof-of-concept implementation demonstrates the practicality of the proposed scheme for network management.
complexity of wavelength assignment in optical network optimization. we study the complexity of a set of design problems for optical networks. under wavelength division multiplexing (wdm) technology, demands sharing a common fiber are transported on distinct wavelengths. multiple fibers may be deployed on a physical link. our basic goal is to design networks of minimum cost, minimum congestion and maximum throughput. this translates to three variants in the design objectives: 1) min-sumfiber: minimizing the total cost of fibers deployed to carry all demands; 2) min-maxfiber: minimizing the maximum number of fibers per link to carry all demands; and 3) max-throughput: maximizing the carried demands using a given set of fibers. we also have two variants in the design constraints: 1) chooseroute: here we need to specify both a routing path and a wavelength for each demand; 2) fixedroute: here we are given demand routes and we need to specify wavelengths only. the fixedroute variant allows us to study wavelength assignment in isolation. combining these variants, we have six design problems. previously we have shown that general instances of the problems min-sumfiber-chooseroute and min-maxfiber-fixedroute have no constant-approximation algorithms. in this paper, we prove that a similar statement holds for all four other problems. our main result shows that min-sumfiber-fixedroute cannot be approximated within any constant factor unless np-hard problems have efficient algorithms. this, together with the previous hardness result of min-maxfiber-fixedroute, shows that the problem of wavelength assignment is inherently hard by itself. we also study the complexity of problems that arise when multiple demands can be time-multiplexed onto a single wavelength (as in time-domain wavelength interleaved networking (twin) networks) and when wavelength converters can be placed along the path of a demand.
broadcasting in sensor networks: the role of local information. flooding based querying and broadcasting schemes have low hop-delays of θ (1/r(n) to reach any node that is a unit distance away, where r(n) is the transmission range of any sensor node. however, in sensor networks with large radio ranges, flooding based broadcasting schemes cause many redundant transmissions leading to a broadcast storm problem. in this paper, we study the role of geographic information and state information (i.e., memory of previous messages or transmissions) in reducing the redundant transmissions in the network. we consider three broadcasting schemes with varying levels of local information where nodes have: (i) no geographic or state information, (ii) coarse geographic information about the origin of the broadcast, and (iii) no geographic information, but remember previously received messages. for each of these network models, we demonstrate localized forwarding algorithms for broadcast (based on geography or state information) that achieve significant reductions in the transmission overheads while maintaining hop-delays comparable to flooding based schemes. we also consider the related problem of broadcasting to a set of "spatially uniform" points in the network (lattice points) in the regime where all nodes have only a local sense of direction and demonstrate an efficient "sparse broadcast" scheme based on a branching random walk that has a low number of packet transmissions. thus, our results show that even with very little local information, it is possible to make broadcast schemes significantly more efficient.
performance analysis of contention based medium access control protocols. this paper studies the performance of contention based medium access control (mac) protocols. in particular, a simple and accurate technique for estimating the throughput of the ieee 802.11 dcf protocol is developed. the technique is based on a rigorous analysis of the markov chain that corresponds to the time evolution of the back-off processes at the contending nodes. an extension of the technique is presented to handle the case where service differentiation is provided with the use of heterogeneous protocol parameters, as, for example, in ieee 802.11e edca protocol. our results provide new insights into the operation of such protocols. the techniques developed in the paper are applicable to a wide variety of contention based mac protocols.
ddc: a dynamic and distributed clustering algorithm for networked virtual environments based on p2p networks. this paper presents a dynamic and distributed algorithm for the clustering of peers in a networked virtual environment (nve) based on a fully distributed peer-to-peer (p2p) network.the main idea is to classify connections in short intra-cluster connections and long inter-cluster connections. the insertion of new peers or the deletion of existing peers can result in the merging of two clusters or the split of one cluster in two parts.
leds: providing location-aware end-to-end data security in wireless sensor networks. providing desirable data security, i.e., confidentiality, authenticity and availability, in wireless sensor networks (wsns) is challenging, as wsns usually consist of a large number of resource constraint sensor nodes, deployed in unattended/hostile environments, and hence are exposed to many types of severe insider attacks due to node compromise. existing security designs mostly provide a hop-by-hop security paradigm and thus are vulnerable to such attacks. furthermore, existing security designs are also vulnerable to various dos attacks, such as report disruption attacks and selective forwarding attacks and thus put data availability at stake. in this paper, we seek to overcome these vulnerabilities for large-scale static wsns. we come up with a location-aware end-to-end security framework in which secret keys are bound to geographic locations. this location-aware property effectively limits the impact of compromised nodes only to their vicinity without affecting end-to-end data security. the proposed multi-functional key management framework assures both node-to-sink and node-to-node authentication along the report forwarding routes. moreover, the proposed data delivery approach guarantees efficient en-route bogus data filtering, and is highly robust against dos attacks. the evaluation demonstrates that the proposed design is highly resilient against an increasing number of compromised nodes and effective in energy savings.
media streaming via tfrc: an analytical study of the impact of tfrc on user-perceived media quality. tcp-friendly rate control (tfrc) is being adopted in internet standards for congestion control of streaming media applications. in this paper, we consider the transmission of prerecorded media from a server to a client by using tfrc, and analytically study the impact of tfrc on user-perceived media quality, which is roughly measured by calculating the rebuffering probability. a rebuffering probability is defined to be the probability that the total duration of all rebuffering events experienced by a user is longer than a certain threshold. several approaches are presented to help an application determine an appropriate initial buffering delay and media playback rate in order to achieve a certain rebuffering probability under a given network condition. first, we derive a closed-form expression to approximate the average tfrc sending rate, which could be used as the maximum allowed playback rate of a media stream. second, we develop a queueing model for a tfrc client buffer with the traffic described by a markov-renewal-modulated deterministic process (mrmdp), which captures the fundamental behavior of tfrc that predicts the immediate future tcp sending rate based on the history of past loss intervals. we present a closed-form solution and a more accurate iterative method to solve the queueing model and calculate the rebuffering probability.
dual-resource tcp/aqm for processing-constrained networks. this paper examines congestion control issues for tcp flows that require in-network processing on the fly in network elements such as gateways, proxies, firewalls and even routers. applications of these flows are increasingly abundant in the future as the internet evolves. since these flows require use of cpus in network elements, both bandwidth and cpu resources can be a bottleneck and thus congestion control must deal with "congestion" on both of these resources. in this paper, we show that conventional tcp/aqm schemes can significantly lose throughput and suffer harmful unfairness in this environment, particularly when cpu cycles become more scarce (which is likely the trend given the recent explosive growth rate of bandwidth). as a solution to this problem, we establish a notion of dual-resource proportional fairness and propose an aqm scheme, called dual-resource queue (drq), that can closely approximate proportional fairness for tcp reno sources with in-network processing requirements. drq is scalable because it does not maintain per-flow states while minimizing communication among different resource queues, and is also incrementally deployable because of no required change in tcp stacks. the simulation study shows that drq approximates proportional fairness without much implementation cost and even an incremental deployment of drq at the edge of the internet improves the fairness and throughput of these tcp flows. our work is at its early stage and might lead to an interesting development in congestion control research.
delay and capacity trade-offs in mobile ad hoc networks: a global perspective. since the original work of grossglauser and tse, which showed that mobility can increase the capacity of an ad hoc network, there has been a lot of interest in characterizing the delay-capacity relationship in ad hoc networks. various mobility models have been studied in the literature, and the delay-capacity relationships under those models have been characterized. the results indicate that there are trade-offs between the delay and capacity, and that the nature of these trade-offs is strongly influenced by the choice of the mobility model. some questions that arise are: (i) how representative are these mobility models studied in the literature? (ii) can the delay-capacity relationship be significantly different under some other "reasonable" mobility model? (iii) what sort of delay-capacity trade-off are we likely to see in a real world scenario? in this paper, we take the first step toward answering some of these questions. in particular, we analyze, among others, the mobility models studied in recent related works, under a unified framework. we relate the nature of delay-capacity trade-off to the nature of node motion, thereby providing a better understanding of the delay-capacity relationship in ad hoc networks in comparison to earlier works.
achieving 100% throughput in reconfigurable optical networks. we study the maximum throughput properties of dynamically reconfigurable optical network architectures having wavelength and port constraints. using stability as the throughput performance metric, we outline the single-hop and multi-hop stability regions of the network. our analysis of the stability regions is a generalization of the bvn decomposition technique that has been so effective at expressing any stabilizable rate matrix for input-queued switches as a convex combination of service configurations. we consider generalized decompositions for physical topologies with wavelength and port constraints. for the case of a single wavelength per optical fiber, we link the decomposition problem to a corresponding routing and wavelength assignment (rwa) problem. we characterize the stability region of the reconfigurable network, employing both single-hop and multi-hop routing, in terms of the rwa problem applied to the same physical topology. we derive expressions for two geometric properties of the stability region: maximum stabilizable uniform arrival rate and maximum scaled doubly substochastic region. these geometric properties provide a measure of the performance gap between a network having a single wavelength per optical fiber and its wavelength-unconstrained version. they also provide a measure of the performance gap between algorithms employing single-hop versus multi-hop electronic routing in coordination with wdm reconfiguration.
packet pacing in short buffer optical packet switched networks. in the absence of a cost-effective technology for storing optical signals, emerging optical packet switched (ops) networks are expected to have severely limited buffering capability. to mitigate the performance degradation resulting from small buffers, this paper proposes that optical edge nodes "pace" the injection of traffic into the ops core. our contributions relating to pacing in ops networks are three-fold: first, we develop real-time pacing algorithms of poly-logarithmic complexity that are feasible for practical implementation in emerging high-speed ops networks. second, we provide an analytical quantification of the benefits of pacing in reducing traffic burstiness and traffic loss at a link with very small buffers. third, we show via simulations of realistic network topologies that pacing can significantly reduce network losses at the expense of a small and bounded increase in end-to-end delay for real-time traffic flows. we argue that the loss-delay tradeoff mechanism provided by pacing can be instrumental in overcoming the performance hurdle arising from the scarcity of buffers in ops networks.
wireless operators in a shared spectrum. cellular networks are notoriously difficult to design and operate; in particular, defining the optimal location of the base stations and fine tuning their configuration parameters is very challenging. for this reason, government agencies (such as the fcc for the us) usually sell or rent, for example by auction, each operator a frequency band for its exclusive usage in a given country or region. only a small part of the whole spectrum is allocated as a shared spectrum, in which networks function in the same (unlicensed) frequency band.
gre encapsulated multicast probing: a scalable technique for measuring one-way loss. we develop techniques for estimating one-way loss from a measurement host to network routers which exploit commonly implemented features on commercial routers and do not require any new router capabilities. the work addressesthe problem of scalably performing one-way loss measurements across specific network paths.
overhead and performance study of the general internet signaling transport (gist) protocol. the general internet signaling transport (gist) protocol is currently being developed as the base protocol compo-nent in the ietf next steps in signaling (nsis) protocol stack to support a variety of signaling applications. we present our study on the protocol overhead and performance aspects of gist. we quantify network-layer protocol overhead and observe the effects of enhanced modularity and security in gist. we developed a first open source gist implementation at the university of göttingen, and study its performance in a linux testbed. a gist node serving 45 000 signaling sessions is found to consume average only 1.1 ms for processing a signaling message and 2.4 kb of memory for managing a session. individual routines in the gist code are instrumented to obtain a detailed profile of their contributions to the overall system processing. important factors in determining performance, such as the number of sessions, state management, refresh frequency, timer management and signaling message size are further discussed. we investigate several mechanisms to improve gist performance so that it is comparable to an rsvp implementation.
connectivity-based localization of large scale sensor networks with complex shape. we study the problem of localizing a large sensor network having a complex shape, possibly with holes. a major challenge with respect to such networks is to figure out the correct network layout, that is, avoid global flips where a part of the network folds on top of another. our algorithm first selects landmarks on network boundaries with sufficient density, then constructs the landmark voronoi diagram and its dual combinatorial delaunay complex on these landmarks. the key insight is that the combinatorial delaunay complex is provably globally rigid and has a unique realization in the plane. thus an embedding of the landmarks by simply gluing the delaunay triangles properly recovers the faithful network layout. with the landmarks nicely localized, the rest of the nodes can easily localize themselves by trilateration to nearby landmark nodes. this leads to a practical and accurate localization algorithm for large networks using only network connectivity. simulations on various network topologies show surprisingly good results. in comparison, previous connectivity-based localization algorithms such as multidimensional scaling and rubberband representation generate globally flipped or distorted localization results.
maximizing restorable throughput in mpls networks. mpls recovery mechanisms are increasing in popularity because they can guarantee fast restoration and high qos assurance. their main advantage is that their backup paths are established in advance, before a failure event takes place. most research on the establishment of primary and backup paths has focused on minimizing the added capacity required by the backup paths in the network. however, this so-called spare capacity allocation (sca) metric is less practical for network operators who have a fixed capacitated network and want to maximize their revenues. in this paper, we present a comprehensive study on restorable throughput maximization in mpls networks.we present the first polynomial-time algorithms for the splittable version of the problem. for the unsplittable version, we provide a lower bound for the approximation ratio and propose an approximation algorithm with an almost identical bound. we present an efficient heuristic which is shown to have excellent performance. one of our most important conclusions is that when one seeks to maximize revenue, local recovery should be the recovery scheme of choice.
cross-layer rate control in wireless networks with lossy links: leaky-pipe flow, effective network utility maximization and hop-by-hop algorithms. we take a cross-layer design approach to study rate control in multihop wireless networks. due to the lossy nature of wireless links, the data rate of a given flow becomes smaller and smaller along its routing path. as a result, the data rate received successfully at the destination node (the effective rate) is typically lower than the transmission rate at the source node (the injection rate). in light of this observation, we treat each flow as a "leaky-pipe" flow and introduce the notion of "effective utility" associated with the effective rate (not the injection rate) of each flow. we then explore rate control through effective network utility maximization (enum) in this study. two network models are studied in this paper: 1) enum with link outage constraints with a maximum error rate at each link; 2) enum with path outage constraints where there exists an end-to-end outage requirement for each flow. for both models, we explicitly take into account the "thinning" feature of data flows and devise distributed hop-by-hop rate control algorithms accordingly. our numerical examples corroborate that higher effective network utility and better fairness can be achieved by the enum algorithms than the standard num.
mac for networks with multipacket reception capability and spatially distributed nodes. the physical layer of future wireless networks will be based on novel radio technologies such as uwb and mimo. one of the important capabilities of such technologies is the ability to capture a few packets simultaneously. this capability has the potential to improve the performance of the mac layer. however, we show that in networks with spatially distributed nodes, reusing backoff mechanisms originally designed for narrow-band systems (e.g., csma/ca) is inefficient. it is well known that when networks with spatially distributed nodes operate with such mac protocols, the channel may be captured by nodes that are near the destination, leading to unfairness. we show that when the physical layer enables multipacket reception, the negative implications of reusing the legacy protocols include not only such unfairness, but also a significant throughput reduction. we present alternative backoff mechanisms and evaluate their performance via markovian analysis, approximations, and simulation. we show that our alternative backoff mechanisms can improve both overall throughput and fairness.
opportunistic scheduling with reliability guarantees in cognitive radio networks. we develop opportunistic scheduling policies for cognitive radio networks that maximize the throughput utility of the secondary (unlicensed) users subject to maximum collision constraints with the primary (licensed) users. we consider a cognitive network with static primary users and potentially mobile secondary users. we use the technique of lyapunov optimization to design an online flow control, scheduling, and resource allocation algorithm that meets the desired objectives and provides explicit performance guarantees.
embracing interference in ad hoc networks using joint routing and scheduling with multiple packet reception. we present an approach that takes advantage of multi-packet reception (mpr) to reduce the negative effects of multiple access interference and therefore increase the capacity of an ad hoc network. we analyze the performance upper bound of joint routing and scheduling for ad hoc networks that embrace interference by using mpr. we formulate the optimization problem under a deterministic model and seek to maximize the aggregate network throughput subject to minimum rate requirements. we then propose a polynomial-time heuristic algorithm aimed at approximating the optimal solution to the joint routing and channel access problem under mpr. we show the effectiveness of our heuristic algorithm by comparing its performance with the upper bound.
relational markov models and their application to adaptive web navigation. relational markov models (rmms) are a generalization of markov models where states can be of different types, with each type described by a different set of variables. the domain of each variable can be hierarchically structured, and shrinkage is carried out over the cross product of these hierarchies. rmms make effective learning possible in domains with very large and heterogeneous state spaces, given only sparse data. we apply them to modeling the behavior of web site users, improving prediction in our proteus architecture for personalizing web sites. we present experiments on an e-commerce and an academic web site showing that rmms are substantially more accurate than alternative methods, and make good predictions even when applied to previously-unvisited parts of the site.
fast nonlinear regression via eigenimages applied to galactic morphology. astronomy increasingly faces the issue of massive, unwieldly data sets. the sloan digital sky survey (sdss) [11] has so far generated tens of millions of images of distant galaxies, of which only a tiny fraction have been morphologically classified. morphological classification in this context is achieved by fitting a parametric model of galaxy shape to a galaxy image. this is a nonlinear regression problem, whose challenges are threefold, 1) blurring of the image caused by atmosphere and mirror imperfections, 2) large numbers of local minima, and 3) massive data sets.our strategy is to use the eigenimages of the parametric model to form a new feature space, and then to map both target image and the model parameters into this feature space. in this low-dimensional space we search for the best image-to-parameter match. to search the space, we sample it by creating a database of many random parameter vectors (prototypes) and mapping them into the feature space. the search problem then becomes one of finding the best prototype match, so the fitting process a nearest-neighbor search.in addition to the savings realized by decomposing the original space into an eigenspace, we can use the fact that the model is a linear sum of functions to reduce the prototypes further: the only prototypes stored are the components of the model function. a modified form of nearest neighbor is used to search among them.additional complications arise in the form of missing data and heteroscedasticity, both of which are addressed with weighted linear regression. compared to existing techniques, speed-ups ach-ieved are between 2 and 3 orders of magnitude. this should enable the analysis of the entire sdss dataset.
cccs: a top-down associative classifier for imbalanced class distribution. in this paper we propose cccs, a new algorithm for classification based on association rule mining. the key innovation in cccs is the use of a new measure, the "complement class support (ccs)" whose application results in rules which are guaranteed to be positively correlated. furthermore, the anti-monotonic property that ccs possesses has very different semantics vis-a-vis the traditional support measure. in particular, "good" rules have a low ccs value. this makes ccs an ideal measure to use in conjunction with a top-down algorithm. finally, the nature of ccs allows the pruning of rules without the setting of any threshold parameter! to the best of our knowledge this is the first threshold-free algorithm in association rule mining for classification.
a statistical theory for quantitative association rules. association rules are a key data-mining tool and as such have been well researched. so far, this research has focused predominantly on databases containing categorical data only. however, many real-world databases contain quantitative attributes and current solutions for this case are so far inadequate. in this paper we introduce a new definition of quantitative association rules based on statistical inference theory. our definition reflects the intuition that the goal of association rules is to find extraordinary and therefore interesting phenomena in databases. we also introduce the concept of sub-rules which can be applied to any type of association rule. rigorous experimental evaluation on real-world datasets is presented, demonstrating the usefulness and characteristics of rules mined according to our definition.
sequential pattern mining using a bitmap representation. we introduce a new algorithm for mining sequential patterns. our algorithm is especially efficient when the sequential patterns in the database are very long. we introduce a novel depth-first search strategy that integrates a depth-first traversal of the search space with effective pruning mechanisms.our implementation of the search strategy combines a vertical bitmap representation of the database with efficient support counting. a salient feature of our algorithm is that it incrementally outputs new frequent itemsets in an online fashion.in a thorough experimental evaluation of our algorithm on standard benchmark data from the literature, our algorithm outperforms previous work up to an order of magnitude.
adaptive duplicate detection using learnable string similarity measures. the problem of identifying approximately duplicate records in databases is an essential step for data cleaning and data integration processes. most existing approaches have relied on generic or manually tuned distance metrics for estimating the similarity of potential duplicates. in this paper, we present a framework for improving duplicate detection using trainable measures of textual similarity. we propose to employ learnable text distance functions for each database field, and show that such measures are capable of adapting to the specific notion of similarity that is appropriate for the field's domain. we present two learnable text similarity measures suitable for this task: an extended variant of learnable string edit distance, and a novel vector-space based measure that employs a support vector machine (svm) for training. experimental results on a range of datasets show that our framework can improve duplicate detection accuracy over traditional techniques.
random projection in dimensionality reduction: applications to image and text data. random projections have recently emerged as a powerful method for dimensionality reduction. theoretical results indicate that the method preserves distances quite nicely; however, empirical results are sparse. we present experimental results on using random projection as a dimensionality reduction tool in a number of cases, where the high dimensionality of the data would otherwise lead to burden-some computations. our application areas are the processing of both noisy and noiseless images, and information retrieval in text documents. we show that projecting the data onto a random lower-dimensional subspace yields results comparable to conventional dimensionality reduction methods such as principal component analysis: the similarity of data vectors is preserved well under random projection. however, using random projections is computationally significantly less expensive than using, e.g., principal component analysis. we also show experimentally that using a sparse random matrix gives additional computational savings in random projection.
group formation in large social networks: membership, growth, and evolution. the processes by which communities come together, attract new members, and develop over time is a central research issue in the social sciences - political movements, professional organizations, and religious denominations all provide fundamental examples of such communities. in the digital domain, on-line groups are becoming increasingly prominent due to the growth of community and social networking sites such as myspace and livejournal. however, the challenge of collecting and analyzing large-scale time-resolved data on social groups and communities has left most basic questions about the evolution of such groups largely unresolved: what are the structural features that influence whether individuals will join communities, which communities will grow rapidly, and how do the overlaps among pairs of communities change over time.here we address these questions using two large sources of data: friendship links and community membership on livejournal, and co-authorship and conference publications in dblp. both of these datasets provide explicit user-defined communities, where conferences serve as proxies for communities in dblp. we study how the evolution of these communities relates to properties such as the structure of the underlying social networks. we find that the propensity of individuals to join communities, and of communities to grow rapidly, depends in subtle ways on the underlying network structure. for example, the tendency of an individual to join a community is influenced not just by the number of friends he or she has within the community, but also crucially by how those friends are connected to one another. we use decision-tree techniques to identify the most significant structural determinants of these properties. we also develop a novel methodology for measuring movement of individuals between communities, and show how such movements are closely aligned with changes in the topics of interest within the communities.
topics in 0--1 data. large 0--1 datasets arise in various applications, such as market basket analysis and information retrieval. we concentrate on the study of topic models, aiming at results which indicate why certain methods succeed or fail. we describe simple algorithms for finding topic models from 0--1 data. we give theoretical results showing that the algorithms can discover the epsilon-separable topic models of papadimitriou et al. we present empirical results showing that the algorithms find natural topics in real-world data sets. we also briefly discuss the connections to matrix approaches, including nonnegative matrix factorization and independent component analysis.
robust information-theoretic clustering. how do we find a natural clustering of a real world point set, which contains an unknown number of clusters with different shapes, and which may be contaminated by noise? most clustering algorithms were designed with certain assumptions (gaussianity), they often require the user to give input parameters, and they are sensitive to noise. in this paper, we propose a robust framework for determining a natural clustering of a given data set, based on the minimum description length (mdl) principle. the proposed framework, robust information-theoretic clustering (ric), is orthogonal to any known clustering algorithm: given a preliminary clustering, ric purifies these clusters from noise, and adjusts the clusterings such that it simultaneously determines the most natural amount and shape (subspace) of the clusters. our ric method can be combined with any clustering technique ranging from k-means and k-medoids to advanced methods such as spectral clustering. in fact, ric is even able to purify and improve an initial coarse clustering, even if we start with very simple methods such as grid-based space partitioning. moreover, ric scales well with the data set size. extensive experiments on synthetic and real world data sets validate the proposed ric framework.
an iterative hypothesis-testing strategy for pattern discovery. pattern discovery has emerged as a direct result of increased data storage and analytic capabilities available to the data analyst. without a massive amount of data, we do not have the evidence to support the discovery of the local deterministic structures that we call patterns. as such, pattern discovery is one of the few areas of data mining that cannot be considered simply as a 'scaling-up' of current statistical methodology to analyze large data sets. however, the philosophies of hypothesis testing and modeling in traditional statistics do lend themselves to forming a framework for pattern discovery, and we can also draw from ideas relating to outlier discovery and residual analysis to discover patterns. we illustrate an iterative strategy in a statistical framework by way of its application to one simulated and two real data sets.
clustering time series from arma models with clipped data. clustering time series is a problem that has applications in a wide variety of fields, and has recently attracted a large amount of research. in this paper we focus on clustering data derived from autoregressive moving average (arma) models using k-means and k-medoids algorithms with the euclidean distance between estimated model parameters. we justify our choice of clustering technique and distance metric by reproducing results obtained in related research. our research aim is to assess the affects of discretising data into binary sequences of above and below the median, a process known as clipping, on the clustering of time series. it is known that the fitted ar parameters of clipped data tend asymptotically to the parameters for unclipped data. we exploit this result to demonstrate that for long series the clustering accuracy when using clipped data from the class of arma models is not significantly different to that achieved with unclipped data. next we show that if the data contains outliers then using clipped data produces significantly better clusterings. we then demonstrate that using clipped series requires much less memory and operations such as distance calculations can be much faster. finally, we demonstrate these advantages on three real world data sets.
ann quality diagnostic models for packaging manufacturing: an industrial data mining case study. world steel trade becomes more competitive every day and new high international quality standards and productivity levels can only be achieved by applying the latest computational technologies. data driven analysis of complex processes is necessary in many industrial applications where analytical modeling is not possible. this paper presents the deployment of kdd technology in one real industrial problem: the development of new tinplate quality diagnostic models.the electrodeposition of tin on steel strips is the most critical stage of a complex process that involves a great amount of variables and operating conditions. its optimization is not only a great commercial and economic challenge but also a compulsion due to the social impact of the tinplate product-more than 90% of the production is used for food packaging. the necessary certification with standards, like iso 9000, requires the use of diagnostic models to minimize the costs and the environmental impact. this aim has been achieved following the multi-stage dm methodology crisp-dm and a novel application of pro-active maintenance methods, as fmea, for the identification of the specific process anomalies. three dm tools have been used for the development of the models. the final results include two ann tinplate quality diagnostic models, that provide the estimated quality of the final product just seconds after its production and only based on the process data. the results have much better performance than the classical faraday's models widely used for the estimation.
the architecture of complexity: the structure and the dynamics of networks, from the web to the cell. networks with complex topology describe systems as diverse as the cell, the world wide web or the society. the emergence of most networks is driven by self-organizing processes that are governed by simple but generic laws. the analysis of the cellular network of various organisms shows that cells and complex man-made networks, such as the internet or the world wide web, and many social and collaboration networks share the same large-scale topology. i will show that the scale-free topology of these complex webs have important consequences on their robustness against failures and attacks, with implications on drug design, the internet's ability to survive attacks and failures, and the ability of ideas and innovations to spread on the network.
cross channel optimized marketing by reinforcement learning. the issues of cross channel integration and customer life time value modeling are two of the most important topics surrounding customer relationship management (crm) today. in the present paper, we describe and evaluate a novel solution that treats these two important issues in a unified framework of markov decision processes (mdp). in particular, we report on the results of a joint project between ibm research and saks fifth avenue to investigate the applicability of this technology to real world problems. the business problem we use as a testbed for our evaluation is that of optimizing direct mail campaign mailings for maximization of profits in the store channel. we identify a problem common to cross-channel crm, which we call the cross-channel challenge, due to the lack of explicit linking between the marketing actions taken in one channel and the customer responses obtained in another. we provide a solution for this problem based on old and new techniques in reinforcement learning. our in-laboratory experimental evaluation using actual customer interaction data show that as much as 7 to 8 per cent increase in the store profits can be expected, by employing a mailing policy automatically generated by our methodology. these results confirm that our approach is valid in dealing with the cross channel crm scenarios in the real world.
a generalized maximum entropy approach to bregman co-clustering and matrix approximation. co-clustering, or simultaneous clustering of rows and columns of a two-dimensional data matrix, is rapidly becoming a powerful data analysis technique. co-clustering has enjoyed wide success in varied application domains such as text clustering, gene-microarray analysis, natural language processing and image, speech and video analysis. in this paper, we introduce a partitional co-clustering formulation that is driven by the search for a good matrix approximation---every co-clustering is associated with an approximation of the original data matrix and the quality of co-clustering is determined by the approximation error. we allow the approximation error to be measured using a large class of loss functions called bregman divergences that include squared euclidean distance and kl-divergence as special cases. in addition, we permit multiple structurally different co-clustering schemes that preserve various linear statistics of the original data matrix. to accomplish the above tasks, we introduce a new minimum bregman information (mbi) principle that simultaneously generalizes the maximum entropy and standard least squares principles, and leads to a matrix approximation that is optimal among all generalized additive models in a certain natural parameter space. analysis based on this principle yields an elegant meta algorithm, special cases of which include most previously known alternate minimization based clustering algorithms such as kmeans and co-clustering algorithms such as information theoretic (dhillon et al., 2003b) and minimum sum-squared residue co-clustering (cho et al., 2004). to demonstrate the generality and flexibility of our co-clustering framework, we provide examples and empirical evidence on a variety of problem domains and also describe novel co-clustering applications such as missing value prediction and compression of categorical data matrices.
an iterative method for multi-class cost-sensitive learning. cost-sensitive learning addresses the issue of classification in the presence of varying costs associated with different types of misclassification. in this paper, we present a method for solving multi-class cost-sensitive learning problems using any binary classification algorithm. this algorithm is derived using hree key ideas: 1) iterative weighting; 2) expanding data space; and 3) gradient boosting with stochastic ensembles. we establish some theoretical guarantees concerning the performance of this method. in particular, we show that a certain variant possesses the boosting property, given a form of weak learning assumption on the component binary classifier. we also empirically evaluate the performance of the proposed method using benchmark data sets and verify that our method generally achieves better results than representative methods for cost-sensitive learning, in terms of predictive performance (cost minimization) and, in many cases, computational efficiency.
generative model-based clustering of directional data. high dimensional directional data is becoming increasingly important in contemporary applications such as analysis of text and gene-expression data. a natural model for multi-variate directional data is provided by the von mises-fisher (vmf) distribution on the unit hypersphere that is analogous to the multi-variate gaussian distribution in rd. in this paper, we propose modeling complex directional data as a mixture of vmf distributions. we derive and analyze two variants of the expectation maximization (em) framework for estimating the parameters of this mixture. we also propose two clustering algorithms corresponding to these variants. an interesting aspect of our methodology is that the spherical kmeans algorithm (kmeans with cosine similarity) can be shown to be a special case of both our algorithms. thus, modeling text data by vmf distributions lends theoretical validity to the use of cosine similarity which has been widely used by the information retrieval community. as part of experimental validation, we present results on modeling high-dimensional text and gene-expression data as a mixture of vmf distributions. the results indicate that our approach yields superior clusterings especially for difficult clustering tasks in high-dimensional spaces.
outlier detection by active learning. most existing approaches to outlier detection are based on density estimation methods. there are two notable issues with these methods: one is the lack of explanation for outlier flagging decisions, and the other is the relatively high computational requirement. in this paper, we present a novel approach to outlier detection based on classification, in an attempt to address both of these issues. our approach isbased on two key ideas. first, we present a simple reduction of outlier detection to classification, via a procedure that involves applying classification to a labeled data set containing artificially generated examples that play the role of potential outliers. once the task has been reduced to classification, we then invoke a selective sampling mechanism based on active learning to the reduced classification problem. we empirically evaluate the proposed approach using a number of data sets, and find that our method is superior to other methods based on the same reduction to classification, but using standard classification methods. we also show that it is competitive to the state-of-the-art outlier detection methods in the literature based on density estimation, while significantly improving the computational complexity and explanatory power.
model-based overlapping clustering. while the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. several approaches to finding overlapping clusters have come from work on analysis of biological datasets. in this paper, we interpret an overlapping clustering model proposed by segal et al. [23] as a generalization of gaussian mixture models, and we extend it to an overlapping clustering model based on mixtures of any regular exponential family distribution and the corresponding bregman divergence. we provide the necessary algorithm modifications for this extension, and present results on synthetic data as well as subsets of 20-newsgroups and eachmovie datasets.
outlier detection by sampling with accuracy guarantees. an effective approach to detecting anomalous points in a data set is distance-based outlier detection. this paper describes a simple sampling algorithm to effciently detect distance-based outliers in domains where each and every distance computation is very expensive. unlike any existing algorithms, the sampling algorithm requires a xed number of distance computations and can return good results with accuracy guarantees. the most computationally expensive aspect of estimating the accuracy of the result is sorting all of the distances computed by the sampling algorithm. the experimental study on two expensive domains as well as ten additional real-life datasets demonstrates both the effciency and effectiveness of the sampling algorithm in comparison with the state-of-the-art algorithm and there liability of the accuracy guarantees.
an objective evaluation criterion for clustering. we propose and test an objective criterion for evaluation of clustering performance: how well does a clustering algorithm run on unlabeled data aid a classification algorithm? the accuracy is quantified using the pac-mdl bound [3] in a semisupervised setting. clustering algorithms which naturally separate the data according to (hidden) labels with a small number of clusters perform well. a simple extension of the argument leads to an objective model selection method. experimental results on text analysis datasets demonstrate that this approach empirically results in very competitive bounds on test set performance on natural datasets.
deriving quantitative models for correlation clusters. correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a common arbitrarily oriented hyperplane of arbitrary dimensionality. several algorithms for this task have been proposed recently. however, all algorithms only compute the partitioning of the data into clusters. this is only a first step in the pipeline of advanced data analysis and system modelling. the second (post-clustering) step of deriving a quantitative model for each correlation cluster has not been addressed so far. in this paper, we describe an original approach to handle this second step. we introduce a general method that can extract quantitative information on the linear dependencies within a correlation clustering. our concepts are independent of the clustering model and can thus be applied as a post-processing step to any correlation clustering algorithm. furthermore, we show how these quantitative models can be used to predict the probability distribution that an object is created by these models. our broad experimental evaluation demonstrates the beneficial impact of our method on several applications of significant practical importance.
data mining case study: modeling the behavior of offenders who commit serious sexual assaults. this paper looks at the use of a self organizing map (som), to link of records of crimes of serious sexual attacks. once linked a profile can be derived of the offender(s) responsible.the data was drawn from the major crimes database at the national crime faculty of the national police staff college bramshill uk. the data was encoded from text by a small team of specialists working to a well-defined protocol. the encoded data was analyzed using soms. two exercises were conducted. these resulted in the linking of several offences in to clusters each of which were sufficiently similar to have possibly been committed by the same offender(s). a number of clusters were used to form profiles of offenders. some of these profiles were confirmed by independent analysts as either belonging to known offenders or appeared sufficiently interesting to warrant further investigation.the prototype was developed over 10 weeks. this contrasts with an in-house study using a conventional approach, which took 2 years to reach similar results. as a consequence of this study the ncf intends to pursue an in-depth follow up study.
extracting decision trees from trained neural networks. neural networks are successful in acquiring hidden knowledge in datasets. their biggest weakness is that the knowledge they acquire is represented in a form not understandable to humans. researchers tried to address this problem by extracting rules from trained neural networks. most of the proposed rule extraction methods required specialized type of neural networks; some required binary inputs and some were computationally expensive. craven proposed extracting mofn type decision trees from neural networks. we believe mofn type decision trees are only good for mofn type problems and trees created for regular high dimensional real world problems may be very complex. in this paper, we introduced a new method for extracting regular c4.5 like decision trees from trained neural networks. we showed that the new method (dectext) is effective in extracting high fidelity trees from trained networks. we also introduced a new discretization technique to make dectext be able to handle continuous features and a new pruning technique for finding simplest tree with the highest fidelity.
global distance-based segmentation of trajectories. this work introduces distance-based criteria for segmentation of object trajectories. segmentation leads to simplification of the original objects into smaller, less complex primitives that are better suited for storage and retrieval purposes. previous work on trajectory segmentation attacked the problem locally, segmenting separately each trajectory of the database. therefore, they did not directly optimize the inter-object separability, which is necessary for mining operations such as searching, clustering, and classification on large databases. in this paper we analyze the trajectory segmentation problem from a global perspective, utilizing data aware distance-based optimization techniques, which optimize pairwise distance estimates hence leading to more efficient object pruning. we first derive exact solutions of the distance-based formulation. due to the intractable complexity of the exact solution, we present anapproximate, greedy solution that exploits forward searching of locally optimal solutions. since the greedy solution also imposes a prohibitive computational cost, we also put forward more light weight variance-based segmentation techniques, which intelligently "relax" the pairwise distance only in the areas that affect the least the mining operation.
detecting outliers using transduction and statistical testing. outlier detection can uncover malicious behavior in fields like intrusion detection and fraud analysis. although there has been a significant amount of work in outlier detection, most of the algorithms proposed in the literature are based on a particular definition of outliers (e.g., density-based), and use ad-hoc thresholds to detect them. in this paper we present a novel technique to detect outliers with respect to an existing clustering model. however, the test can also be successfully utilized to recognize outliers when the clustering information is not available. our method is based on transductive confidence machines, which have been previously proposed as a mechanism to provide individual confidence measures on classification decisions. the test uses hypothesis testing to prove or disprove whether a point is fit to be in each of the clusters of the model. we experimentally demonstrate that the test is highly robust, and produces very few misdiagnosed points, even when no clustering information is available. furthermore, our experiments demonstrate the robustness of our method under the circumstances of data contaminated by outliers. we finally show that our technique can be successfully applied to identify outliers in a noisy data set for which no information is available (e.g., ground truth, clustering structure, etc.). as such our proposed methodology is capable of bootstrapping from a noisy data set a clean one that can be used to identify future outliers.
approximating a collection of frequent sets. one of the most well-studied problems in data mining is computing the collection of frequent item sets in large transactional databases. one obstacle for the applicability of frequent-set mining is that the size of the output collection can be far too large to be carefully examined and understood by the users. even restricting the output to the border of the frequent item-set collection does not help much in alleviating the problem.in this paper we address the issue of overwhelmingly large output size by introducing and studying the following problem: what are the k sets that best approximate a collection of frequent item sets? our measure of approximating a collection of sets by k sets is defined to be the size of the collection covered by the the k sets, i.e., the part of the collection that is included in one of the k sets. we also specify a bound on the number of extra sets that are allowed to be covered. we examine different problem variants for which we demonstrate the hardness of the corresponding problems and we provide simple polynomial-time approximation algorithms. we give empirical evidence showing that the approximation methods work well in practice.
shrinkage estimator generalizations of proximal support vector machines. we give a statistical interpretation of proximal support vector machines (psvm) proposed at kdd2001 as linear approximaters to (nonlinear) support vector machines (svm). we prove that psvm using a linear kernel is identical to ridge regression, a biased-regression method known in the statistical community for more than thirty years. techniques from the statistical literature to estimate the tuning constant that appears in the svm and psvm framework are discussed. better shrinkage strategies that incorporate more than one tuning constant are suggested. for nonlinear kernels, the minimization problem posed in the psvm framework is equivalent to finding the posterior mode of a bayesian model defined through a gaussian process on the predictor space. apart from providing new insights, these interpretations help us attach an estimate of uncertainty to our predictions and enable us to build richer classes of models. in particular, we propose a new algorithm called psvmmix which is a combination of ridge regression and a gaussian process model. extension to the case of continuous response is straightforward and illustrated with example datasets.
architecting a knowledge discovery engine for military commanders utilizing massive runs of simulations. the marine corps' project albert seeks to model complex phenomenon by observing the behavior of relatively simple simulations over thousands of runs. a rich data base is developed by running the simulations thousands of times, varying the agent and scenario input parameters as well as the random seeds. exploring this result space may provide significant insight into nonlinear, surprising, and emergent behaviors. capturing these results can provide a path for making the results usable for decision support to a military commander. this paper presents two data mining approaches, rule discovery and bayesian networks, for analyzing the albert simulation data. the first approach generates rules from the data and then uses them to create descriptive model. the second generates bayesian networks which provide a quantitative belief model for decision support. both of these approaches as well as the project albert simulations are framed in the context of a system architecture for decision support.
a probabilistic framework for semi-supervised clustering. unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clusters. in recent years, a number of algorithms have been proposed for enhancing clustering quality by employing such supervision. such methods use the constraints to either modify the objective function, or to learn the distance measure. we propose a probabilistic model for semi-supervised clustering based on hidden markov random fields (hmrfs) that provides a principled framework for incorporating supervision into prototype-based clustering. the model generalizes a previous approach that combines constraints and euclidean distance learning, and allows the use of a broad range of clustering distortion measures, including bregman divergences (e.g., euclidean distance and i-divergence) and directional similarity measures (e.g., cosine similarity). we present an algorithm that performs partitional semi-supervised clustering of data by minimizing an objective function derived from the posterior energy of the hmrf model. experimental results on several text data sets demonstrate the advantages of the proposed framework.
learning to rank networked entities. several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. however, these algorithms do not model network connections or relations between entities. meanwhile, pagerank and variants find the stationary distribution of a reasonable but arbitrary markov walk over a network, but do not learn from relevance feedback. we present a framework for ranking networked entities based on markov walks with parameterized conductance values associated with the network edges. we propose two flavors of conductance learning problems in our framework. in the first setting, relevance feedback comparing node-pairs hints that the user has one or more hidden preferred communities with large edge conductance, and the algorithm must discover these communities. we present a constrained maximum entropy network flow formulation whose dual can be solved efficiently using a cutting-plane approach and a quasi-newton optimizer. in the second setting, edges have types, and relevance feedback hints that each edge type has a potentially different conductance, but this is fixed across the whole network. our algorithm learns the conductances using an approximate newton method.
evaluating the novelty of text-mined rules using lexical knowledge. in this paper, we present a new method of estimating the novelty of rules discovered by data-mining methods using wordnet, a lexical knowledge-base of english words. we assess the novelty of a rule by the average semantic distance in a knowledge hierarchy between the words in the antecedent and the consequent of the rule - the more the average distance, more is the novelty of the rule. the novelty of rules extracted by the discotex text-mining system on amazon.com book descriptions were evaluated by both human subjects and by our algorithm. by computing correlation coefficients between pairs of human ratings and between human and automatic ratings, we found that the automatic scoring of rules based on our novelty measure correlates with human judgments about as well as human judgments correlate with one another. @text mining
spatial scan statistics: approximations and performance study. spatial scan statistics are used to determine hotspots in spatial data, and are widely used in epidemiology and biosurveillance. in recent years, there has been much effort invested in designing efficient algorithms for finding such "high discrepancy" regions, with methods ranging from fast heuristics for special cases, to general grid-based methods, and to efficient approximation algorithms with provable guarantees on performance and quality.in this paper, we make a number of contributions to the computational study of spatial scan statistics. first, we describe a simple exact algorithm for finding the largest discrepancy region in a domain. second, we propose a new approximation algorithm for a large class of discrepancy functions (including the kulldorff scan statistic) that improves the approximation versus run time trade-off of prior methods. third, we extend our simple exact and our approximation algorithms to data sets which lie naturally on a grid or are accumulated onto a grid. fourth, we conduct a detailed experimental comparison of these methods with a number of known methods, demonstrating that our approximation algorithm has far superior performance in practice to prior methods, and exhibits a good performance-accuracy trade-off.all extant methods (including those in this paper) are suitable for data sets that are modestly sized; if data sets are of the order of millions of data points, none of these methods scale well. for such massive data settings, it is natural to examine whether small-space streaming algorithms might yield accurate answers. here, we provide some negative results, showing that any streaming algorithms that even provide approximately optimal answers to the discrepancy maximization problem must use space linear in the input.
a human-computer cooperative system for effective high dimensional clustering. high dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. therefore, techniques have recently been proposed to find clusters in hidden subspaces of the data. however, since the behavior of the data may vary considerably in different subspaces, it is often difficult to define the notion of a cluster with the use of simple mathematical formalizations. in fact, the meaningfulness and definition of a cluster is best characterized with the use of human intuition. in this paper, we propose a system which performs high dimensional clustering by effective cooperation between the human and the computer. the complex task of cluster creation is accomplished by a combination of human intuition and the computational support provided by the computer. the result is a system which leverages the best abilities of both the human and the computer in order to create very meaningful sets of clusters in high dimensionality.
on effective classification of strings with wavelets. in recent years, the technological advances in mapping genes have made it increasingly easy to store and use a wide variety of biological data. such data are usually in the form of very long strings for which it is difficult to determine the most relevant features for a classification task. for example, a typical dna string may be millions of characters long, and there may be thousands of such strings in a database. in many cases, the classification behavior of the data may be hidden in the compositional behavior of certain segments of the string which cannot be easily determined apriori. another problem which complicates the classification task is that in some cases the classification behavior is reflected in global behavior of the string, whereas in others it is reflected in local patterns. given the enormous variation in the behavior of the strings over different data sets, it is useful to develop an approach which is sensitive to both the global and local behavior of the strings for the purpose of classification. for this purpose, we will exploit the multi-resolution property of wavelet decomposition in order to create a scheme which can mine classification characteristics at different levels of granularity. the resulting scheme turns out to be very effective in practice on a wide range of problems.
using randomized response techniques for privacy-preserving data mining. privacy is an important issue in data mining and knowledge discovery. in this paper, we propose to use the randomized response techniques to conduct the data mining computation. specially, we present a method to build decision tree classifiers from the disguised data. we conduct experiments to compare the accuracy of our decision tree with the one built from the original undisguised data. our results show that although the data are disguised, our method can still achieve fairly high accuracy. we also show how the parameter used in the randomized response techniques affects the accuracy of the results.
collaborative crawling: mining user experiences for topical resource discovery. the rapid growth of the world wide web had made the problem of topic specific resource discovery an important one in recent years. in this problem, it is desired to find web pages which satisfy a predicate specified by the user. such a predicate could be a keyword query, a topical query, or some arbitrary contraint. several techniques such as focussed crawling and intelligent crawling have recently been proposed for topic specific resource discovery. all these crawlers are linkage based, since they use the hyperlink behavior in order to perform resource discovery. recent studies have shown that the topical correlations in hyperlinks are quite noisy and may not always show the consistency necessary for a reliable resource discovery process. in this paper, we will approach the problem of resource discovery from an entirely different perspective; we will mine the significant browsing patterns of world wide web users in order to model the likelihood of web pages belonging to a specified predicate. this user behavior can be mined from the freely available traces of large public domain proxies on the world wide web. we refer to this technique as collaborative crawling because it mines the collective user experiences in order to find topical resources. such a strategy is extremely effective because the topical consistency in world wide web browsing patterns turns out to very reliable. in addition, the user-centered crawling system can be combined with linkage based systems to create an overall system which works more effectively than a system based purely on either user behavior or hyperlinks.
mining distance-based outliers in near linear time with randomization and a simple pruning rule. defining outliers by their distance to neighboring examples is a popular approach to finding unusual examples in a data set. recently, much work has been conducted with the goal of finding fast algorithms for this task. we show that a simple nested loop algorithm that in the worst case is quadratic can give near linear time performance when the data is in random order and a simple pruning rule is used. we test our algorithm on real high-dimensional data sets with millions of examples and show that the near linear scaling holds over several orders of magnitude. our average case analysis suggests that much of the efficiency is because the time to process non-outliers, which are the majority of examples, does not depend on the size of the data set.
towards systematic design of distance functions for data mining applications. distance function computation is a key subtask in many data mining algorithms and applications. the most effective form of the distance function can only be expressed in the context of a particular data domain. it is also often a challenging and non-trivial task to find the most effective form of the distance function. for example, in the text domain, distance function design has been considered such an important and complex issue that it has been the focus of intensive research over three decades. the final design of distance functions in this domain has been reached only by detailed empirical testing and consensus over the quality of results provided by the different variations. with the increasing ability to collect data in an automated way, the number of new kinds of data continues to increase rapidly. this makes it increasingly difficult to undertake such efforts for each and every new data type. the most important aspect of distance function design is that since a human is the end-user for any application, the design must satisfy the user requirements with regard to effectiveness. this creates the need for a systematic framework to design distance functions which are sensitive to the particular characteristics of the data domain. in this paper, we discuss such a framework. the goal is to create distance functions in an automated waywhile minimizing the work required from the user. we will show that this framework creates distance functions which are significantly more effective than popularly used functions such as the euclidean metric.
towards exploratory test instance specific algorithms for high dimensional classification. in an interactive classification application, a user may find it more valuable to develop a diagnostic decision support method which can reveal significant classification behavior of exemplar records. such an approach has the additional advantage of being able to optimize the decision process for the individual record in order to design more effective classification methods. in this paper, we propose the subspace decision path method which provides the user with the ability to interactively explore a small number of nodes of a hierarchical decision process so that the most significant classification characteristics for a given test instance are revealed. in addition, the sd-path method can provide enormous interpretability by constructing views of the data in which the different classes are clearly separated out. even in cases where the classification behavior of the test instance is ambiguous, the sd-path method provides a diagnostic understanding of the characteristics which result in this ambiguity. therefore, this method combines the abilities of the human and the computer in creating an effective diagnostic tool for instance-centered high dimensional classification.
on demand classification of data streams. current models of the classification problem do not effectively handle bursts of particular classes coming in at different times. in fact, the current model of the classification problem simply concentrates on methods for one-pass classification modeling of very large data sets. our model for data stream classification views the data stream classification problem from the point of view of a dynamic approach in which simultaneous training and testing streams are used for dynamic classification of data sets. this model reflects real life situations effectively, since it is desirable to classify test streams in real time over an evolving training and test stream. the aim here is to create a classification system in which the training model can adapt quickly to the changes of the underlying data stream. in order to achieve this goal, we propose an on-demand classification process which can dynamically select the appropriate window of past training data to build the classifier. the empirical results indicate that the system maintains a high classification accuracy in an evolving data stream, while providing an efficient solution to the classification task.
mining massively incomplete data sets by conceptual reconstruction. incomplete data sets have become almost ubiquitous in a wide variety of application domains. common examples can be found in climate and image data sets, sensor data sets and medical data sets. the incompleteness in these data sets may arise from a number of factors: in some cases it may simply be a reflection of certain measurements not being available at the time; in others the information may be lost due to partial system failure; or it may simply be a result of users being unwilling to specify attributes due to privacy concerns. when a significant fraction of the entries are missing in all of the attributes, it becomes very difficult to perform any kind of reasonable extrapolation on the original data. for such cases, we introduce the novel idea of conceptual reconstruction, in which we create effective conceptual representations on which the data mining algorithms can be directly applied. the attraction behind the idea of conceptual reconstruction is to use the correlation structure of the data in order to express it in terms of concepts rather the original dimensions. as a result, the reconstruction procedure estimates only those conceptual aspects of the data which can be mined from the incomplete data set, rather than force errors created by extrapolation. we demonstrate the effectiveness of the approach on a variety of real data sets.
frequent term-based text clustering. text clustering methods can be used to structure large sets of text or hypertext documents. the well-known methods of text clustering, however, do not really address the special problems of text clustering: very high dimensionality of the data, very large size of the databases and understandability of the cluster description. in this paper, we introduce a novel approach which uses frequent item (term) sets for text clustering. such frequent sets can be efficiently discovered using algorithms for association rule mining. to cluster based on frequent term sets, we measure the mutual overlap of frequent sets with respect to the sets of supporting documents. we present two algorithms for frequent term-based text clustering, ftc which creates flat clusterings and hftc for hierarchical clustering. an experimental evaluation on classical text documents as well as on web documents demonstrates that the proposed algorithms obtain clusterings of comparable quality significantly more efficiently than state-of-the- art text clustering algorithms. furthermore, our methods provide an understandable description of the discovered clusters by their frequent term sets.
on privacy preservation against adversarial data mining. privacy preserving data processing has become an important topic recently because of advances in hardware technology which have lead to widespread proliferation of demographic and sensitive data. a rudimentary way to preserve privacy is to simply hide the information in some of the sensitive fields picked by a user. however, such a method is far from satisfactory in its ability to prevent adversarial data mining. real data records are not randomly distributed. as a result, some fields in the records may be correlated with one another. if the correlation is sufficiently high, it may be possible for an adversary to predict some of the sensitive fields using other fields.in this paper, we study the problem of privacy preservation against adversarial data mining, which is to hide a minimal set of entries so that the privacy of the sensitive fields are satisfactorily preserved. in other words, even by data mining, an adversary still cannot accurately recover the hidden data entries. we model the problem concisely and develop an efficient heuristic algorithm which can find good solutions in practice. an extensive performance study is conducted on both synthetic and real data sets to examine the effectiveness of our approach.
a theoretical framework for learning from a pool of disparate data sources. many enterprises incorporate information gathered from a variety of data sources into an integrated input for some learning task. for example, aiming towards the design of an automated diagnostic tool for some disease, one may wish to integrate data gathered in many different hospitals. a major obstacle to such endeavors is that different data sources may vary considerably in the way they choose to represent related data. in practice, the problem is usually solved by a manual construction of semantic mappings and translations between the different sources. recently there have been attempts to introduce automated algorithms based on machine learning tools for the construction of such translations.in this work we propose a theoretical framework for making classification predictions from a collection of different data sources, without creating explicit translations between them. our framework allows a precise mathematical analysis of the complexity of such tasks, and it provides a tool for the development and comparison of different learning algorithms. our main objective, at this stage, is to demonstrate the usefulness of computational learning theory to this practically important area and to stimulate further theoretical and experimental research of questions related to this framework.
mining reference tables for automatic text segmentation. automatically segmenting unstructured text strings into structured records is necessary for importing the information contained in legacy sources and text collections into a data warehouse for subsequent querying, analysis, mining and integration. in this paper, we mine tables present in data warehouses and relational databases to develop an automatic segmentation system. thus, we overcome limitations of existing supervised text segmentation approaches, which require comprehensive manually labeled training data. our segmentation system is robust, accurate, and efficient, and requires no additional manual effort. thorough evaluation on real datasets demonstrates the robustness and accuracy of our system, with segmentation accuracy exceeding state of the art supervised approaches.
exploiting unlabeled data in ensemble methods. an adaptive semi-supervised ensemble method, assemble, is proposed that constructs classification ensembles based on both labeled and unlabeled data. assemble alternates between assigning "pseudo-classes" to the unlabeled data using the existing ensemble and constructing the next base classifier using both the labeled and pseudolabeled data. mathematically, this intuitive algorithm corresponds to maximizing the classification margin in hypothesis space as measured on both the labeled and unlabeled of data. unlike alternative approaches, assemble does not require a semi-supervised learning method for the base classifier. assemble can be used in conjunction with any cost-sensitive classification algorithm for both two-class and multi-class problems. assemble using decision trees won the nips 2001 unlabeled data competition. in addition, strong results on several benchmark datasets using both decision trees and neural networks support the proposed method.
identifying "best bet" web search results by mining past user behavior. the top web search result is crucial for user satisfaction with the web search experience. we argue that the importance of the relevance at the top position necessitates special handling of the top web search result for some queries. we propose an effective approach of leveraging millions of past user interactions with a web search engine to automatically detect "best bet" top results preferred by majority of users. interestingly, this problem can be more effectively addressed with classification than using state-of-the-art general ranking methods. furthermore, we show that our general machine learning approach achieves precision comparable to a heavily tuned, domain-specific algorithm, with significantly higher coverage. our experiments over millions of user interactions for thousands of queries demonstrate the effectiveness and robustness of our techniques.
applications of generalized support vector machines to predictive modeling. the work of the russian mathematician vladimir vapnik (at&t labs) enables us to go back to the roots of theoretical statistics, leaving behind fisher's parameters in favor of the general approaches started in the 1930s by glivenko-cantelli-kolmogorov. nowadays, it has become possible to model millions of events described by thousands of variables, within a reasonable time for a specific application. the srm approach works with a family of models and calibrates the family of models to a point which is the best compromise between accuracy and robustness. it also measures the complexity of the model using vc dimension which is not plagued by number of parameters. hence models for large events described by several parameters can be generalized. this opens up great prospects in numerous fields like customer relationship management, network optimization, risk management, manufacturing yield management, and a number of other data-rich problems.
mark: a boosting algorithm for heterogeneous kernel models. support vector machines and other kernel methods have proven to be very effective for nonlinear inference. practical issues are how to select the type of kernel including any parameters and how to deal with the computational issues caused by the fact that the kernel matrix grows quadratically with the data. inspired by ensemble and boosting methods like mart, we propose the multiple additive regression kernels (mark) algorithm to address these issues. mark considers a large (potentially infinite) library of kernel matrices formed by different kernel functions and parameters. using gradient boosting/column generation, mark constructs columns of the heterogeneous kernel matrix (the base hypotheses) on the fly and then adds them into the kernel ensemble. regularization methods such as used in svm, kernel ridge regression, and mart, are used to prevent overfitting. we investigate how mark is applied to heterogeneous kernel ridge regression. the resulting algorithm is simple to implement and efficient. kernel parameter selection is handled within mark. sampling and "weak" kernels are used to further enhance the computational efficiency of the resulting additive algorithm. the user can incorporate and potentially extract domain knowledge by restricting the kernel library to interpretable kernels. mark compares very favorably with svm and kernel ridge regression on several benchmark datasets.
next frontier. this talk is about the next frontier in knowledge discovery and data mining.
recovering latent time-series from their observed sums: network tomography with particle filters. hidden variables, evolving over time, appear in multiple settings, where it is valuable to recover them, typically from observed sums. our driving application is 'network tomography', where we need to estimate the origin-destination (od) traffic flows to determine, e.g., who is communicating with whom in a local area network. this information allows network engineers and managers to solve problems in design, routing, configuration debugging, monitoring and pricing. unfortunately the direct measurement of the od traffic is usually difficult, or even impossible; instead, we can easily measure the loads on every link, that is, sums of desirable od flows.in this paper we propose i-filter, a method to solve this problem, which improves the state-of-the-art by (a) introducing explicit time dependence, and by (b) using realistic, non-gaussian marginals in the statistical models for the traffic flows, as never attempted before. we give experiments on real data, where i-filter scales linearly with new observations and out-performs the best existing solutions, in a wide variety of settings. specifically, on real network traffic measured at cmu, and at at&t, i-filter reduced the estimation errors between 15% and 46% in all cases.
a framework for analysis of dynamic social networks. finding patterns of social interaction within a population has wide-ranging applications including: disease modeling, cultural and information transmission, and behavioral ecology. social interactions are often modeled with networks. a key characteristic of social interactions is their continual change. however, most past analyses of social networks are essentially static in that all information about the time that social interactions take place is discarded. in this paper, we propose a new mathematical and computational framework that enables analysis of dynamic social networks and that explicitly makes use of information about when social interactions occur.
interactive training of advanced classifiers for mining remote sensing image archives. advances in satellite technology and availability of downloaded images constantly increase the sizes of remote sensing image archives. automatic content extraction, classification and content-based retrieval have become highly desired goals for the development of intelligent remote sensing databases. the common approach for mining these databases uses rules created by analysts. however, incorporating gis information and human expert knowledge with digital image processing improves remote sensing image analysis. we developed a system that uses decision tree classifiers for interactive learning of land cover models and mining of image archives. decision trees provide a promising solution for this problem because they can operate on both numerical (continuous) and categorical (discrete) data sources, and they do not require any assumptions about neither the distributions nor the independence of attribute values. this is especially important for the fusion of measurements from different sources like spectral data, dem data and other ancillary gis data. furthermore, using surrogate splits provides the capability of dealing with missing data during both training and classification, and enables handling instrument malfunctions or the cases where one or more measurements do not exist for some locations. quantitative and qualitative performance evaluation showed that decision trees provide powerful tools for modeling both pixel and region contents of images and mining of remote sensing image archives.
golden path analyzer: using divide-and-conquer to cluster web clickstreams. this paper describes a novel algorithm and deployed system golden path analyzer (gpa) that analyzes clickstreams of people trying to complete the same task on a website. it finds the shortest, successful paths taken by users - 'golden paths' - and uses these as seeds for clickstream clusters. other users are assigned to a cluster if their clickstream is a supersequence of the golden path. the advantages of this approach are that the resulting clusters are easily comprehended, they are few in number, correspond to semantically different strategies used by the users, and jointly partition all the clickstreams. gpa's key contribution over prior work in process funnels is that by not excluding users that make diversions from the golden path, gpa is able to assign more users to fewer clusters. another key contribution is to use actual full clickstreams as cluster seeds to which supersequences of other users are added. golden paths correspond to complete clickstreams that are based on actual user page transitions. gpa is particularly useful for site designers to improve processes such as shopping, returns and registration. its analyses identify which web pages cause many users to deviate from a golden path, which links distract users and the percentage of users taking each golden path. gpa has demonstrated value on more than twenty client projects in diverse industries.
interactive path analysis of web site traffic. the goal of path analysis is to understand visitors' navigation of a web site. the fundamental analysis component is a path. a path is a finite sequence of elements, typically representing urls or groups of urls. a full path is an abstraction of a visit or a session, which can contain attributes described below. subpaths represent interesting subsequences of the full paths.path analysis provides user-configurable extraction, filtering, preprocessing, noise reduction, descriptive statistics and detailed analysis of three basic specific objects: elements, (sub)paths, and couples of elements. in each case, lists of frequent objects --- subject to particular filtering and sorting --- are available. we call the corresponding interactive tools element, path, and couple analyzers.we also allow in-depth exploration of individual elements, paths, and couples: element explorer investigates composition and convergence of traffic through an element and allows conditioning based on the number of preceding/succeeding steps. path explorer visualizes in and out flows of a path and attrition rate along the path. couple explorer presents distinct paths connecting couple elements, along with measures of their association and some additional statistics.
tivo: making show recommendations using a distributed collaborative filtering architecture. we describe the tivo television show collaborative recommendation system which has been fielded in over one million tivo clients for four years. over this install base, tivo currently has approximately 100 million ratings by users over approximately 30,000 distinct tv shows and movies. tivo uses an item-item (show to show) form of collaborative filtering which obviates the need to keep any persistent memory of each user's viewing preferences at the tivo server. taking advantage of tivo's client-server architecture has produced a novel collaborative filtering system in which the server does a minimum of work and most work is delegated to the numerous clients. nevertheless, the server-side processing is also highly scalable and parallelizable. although we have not performed formal empirical evaluations of its accuracy, internal studies have shown its recommendations to be useful even for multiple user households. tivo's architecture also allows for throttling of the server so if more server-side resources become available, more correlations can be computed on the server allowing tivo to make recommendations for niche audiences.
integration of profile hidden markov model output into association rule mining. scientific models typically depend on parameters. preserving the parameter dependence of models in the pattern mining context opens up several applications. within association rule mining (arm), the choice of parameters can be studied with more flexibly then in traditional model building. studying support, confidence, and other rule metrics as a function of model parameters allows conclusions on assumptions underlying the models. we present efficient techniques to handle multiple model output data sets at little more than the cost of one. we integrate output from hidden markov models into the association rule mining framework, demonstrating the potential for frequent pattern mining in the field of scientific modeling and experimentation.
an adaptive nearest neighbor search for a parts acquisition eportal. one of the major hurdles in maintaining long-lived electronic systems is that electronic parts become obsolete, no longer available from the original suppliers. when this occurs, an engineer is tasked with resolving the problem by finding a replacement that is "as similar as possible" to the original part. the current approach involves a laborious manual search through several electronic portals and data books. the search is difficult because potential replacements may differ from the original and from each other by one or more parameters. worse still, the cumbersome nature of this process may cause the engineers to miss appropriate solutions amid the many thousands of parts listed in industry catalogs.in this paper, we address this problem by introducing the notion of a parametric "distance" between electronic components. we use this distance to search a large parts data set and recommend likely replacements. recommendations are based on an adaptive nearest-neighbor search through the parametric data set. for each user, we learn how to scale the axes of the feature space in which the nearest neighbors are sought. this allows the system to learn each user's judgment of the phrase "as similar as possible."
fast ordering of large categorical datasets for better visualization. an important issue in visualizing categorical data is how to order categorical values. the focus of this paper is on constructing such orderings efficiently without compromising their visual quality.
scalable robust covariance and correlation estimates for data mining. covariance and correlation estimates have important applications in data mining. in the presence of outliers, classical estimates of covariance and correlation matrices are not reliable. a small fraction of outliers, in some cases even a single outlier, can distort the classical covariance and correlation estimates making them virtually useless. that is, correlations for the vast majority of the data can be very erroneously reported; principal components transformations can be misleading; and multidimensional outlier detection via mahalanobis distances can fail to detect outliers. there is plenty of statistical literature on robust covariance and correlation matrix estimates with an emphasis on affine-equivariant estimators that possess high breakdown points and small worst case biases. all such estimators have unacceptable exponential complexity in the number of variables and quadratic complexity in the number of observations. in this paper we focus on several variants of robust covariance and correlation matrix estimates with quadratic complexity in the number of variables and linear complexity in the number of observations. these estimators are based on several forms of pairwise robust covariance and correlation estimates. the estimators studied include two fast estimators based on coordinate-wise robust transformations embedded in an overall procedure recently proposed by [14]. we show that the estimators have attractive robustness properties, and give an example that uses one of the estimators in the new insightful miner data mining product.
mining high dimensional data for classifier knowledge. we present in this paper the problem of discovering sets of attribute-value pairs in high dimensional data sets that are of interest not because of co-occurrence alone, but due to their value in serving as cores for potential classifiers of clusters. we present our algorithm in the context of a gene-expression dataset. gene expression data, in most situations, is insufficient for clustering algorithms and any statistical inference because for 6000+ genes, typically only 10s and at most 100s of data points become available. it is difficult to use statistical techniques to design a classifier for such immensely under-specified data. the observed data, though statistically, insufficient contains some information about the domain. our goal is to discover as much information about all potential classifiers as possible from the data and then summarize this knowledge. this summarization provides insights into the composition of potential classifiers. we present here algorithms and methods for mining a high dimensional data set, exemplified by a gene expression data set, for mining such information.
challenges for knowledge discovery in biology. bioinformatics is the study of information flow in biology. interest in the field has exploded in the last 10 years with the emergence of techniques for large scale experimental data collection-including genome sequencing, gene expression analysis, protein interaction detection, high-throughput structure determination and others. these techniques, in the context of a large online published literature, have created relatively large data sets (at least by biological standards) that are not possible to analyze manually. there is therefore a critical need for methods to analyze these data and reduce them to new knowledge. the principle challenges to the field include the great diversity of data types and questions that are asked of the data, and the communication difficulties that can exist between experts in biology and experts in machine learning. in this talk, i will provide an introduction to the major biological questions that are being addressed, why they are important, and how the field is trying to address them with technical approaches.
on the potential of domain literature for clustering and bayesian network learning. thanks to its increasing availability, electronic literature can now be a major source of information when developing complex statistical models where data is scarce or contains much noise. this raises the question of how to integrate information from domain literature with statistical data. because quantifying similarities or dependencies between variables is a basic building block in knowledge discovery, we consider here the following question. which vector representations of text and which statistical scores of similarity or dependency support best the use of literature in statistical models? for the text source, we assume to have annotations for the domain variables as short free-text descriptions and optionally to have a large literature repository from which we can further expand the annotations. for evaluation, we contrast the variables similarities or dependencies obtained from text using different annotation sources and vector representations with those obtained from measurement data or expert assessments. specifically, we consider two learning problems: clustering and bayesian network learning. firstly, we report performance (against an expert reference) for clustering yeast genes from textual annotations. secondly, we assess the agreement between text-based and data-based scores of variable dependencies when learning bayesian network substructures for the task of modeling the joint distribution of clinical measurements of ovarian tumors.
query-time entity resolution. the goal of entity resolution is to reconcile database references corresponding to the same real-world entities. given the abundance of publicly available databases where entities are not resolved, we motivate the problem of quickly processing queries that require resolved entities from such 'unclean' databases. we propose a two-stage collective resolution strategy for processing queries. we then show how it can be performed on-the-fly by adaptively extracting and resolving those database references that are the most helpful for resolving the query. we validate our approach on two large real-world publication databases where we show the usefulness of collective resolution and at the same time demonstrate the need for adaptive strategies for query processing. we then show how the same queries can be answered in real time using our adaptive approach while preserving the gains of collective resolution.
segmentation-based modeling for advanced targeted marketing. fingerhut business intelligence (bi) has a long and successful history of building statistical models to predict consumer behavior. the models constructed are typically segmentation-based models in which the target audience is split into subpopulations (i.e., customer segments) and individually tailored statistical models are then developed for each segment. such models are commonly employed in the direct-mail industry; however, segmentation is often performed on an ad-hoc basis without directly considering how segmentation affects the accuracy of the resulting segment models. fingerhut bi approached ibm research with the problem of how to build segmentation-based models more effectively so as to maximize predictive accuracy. the ibm advanced targeted marketing-single eventstm (ibm atm-setm) solution is the result of ibm research and fingerhut bi directing their efforts jointly towards solving this problem. this paper presents an evaluation of atm-se's modeling capabilities using data from fingerhut's catalog mailings.
computer aided detection via asymmetric cascade of sparse hyperplane classifiers. this paper describes a novel classification method for computer aided detection (cad) that identifies structures of interest from medical images. cad problems are challenging largely due to the following three characteristics. typical cad training data sets are large and extremely unbalanced between positive and negative classes. when searching for descriptive features, researchers often deploy a large set of experimental features, which consequently introduces irrelevant and redundant features. finally, a cad system has to satisfy stringent real-time requirements.this work is distinguished by three key contributions. the first is a cascade classification approach which is able to tackle all the above difficulties in a unified framework by employing an asymmetric cascade of sparse classifiers each trained to achieve high detection sensitivity and satisfactory false positive rates. the second is the incorporation of feature computational costs in a linear program formulation that allows the feature selection process to take into account different evaluation costs of various features. the third is a boosting algorithm derived from column generation optimization to effectively solve the proposed cascade linear programs.we apply the proposed approach to the problem of detecting lung nodules from helical multi-slice ct images. our approach demonstrates superior performance in comparison against support vector machines, linear discriminant analysis and cascade adaboost. especially, the resulting detection system is significantly sped up with our approach.
the "dgx" distribution for mining massive, skewed data. skewed distributions appear very often in practice. unfortunately, the traditional zipf distribution often fails to model them well. in this paper, we propose a new probability distribution, the discrete gaussian exponential (dgx), to achieve excellent fits in a wide variety of settings; our new distribution includes the zipf distribution as a special case. we present a statistically sound method for estimating the dgx parameters based on maximum likelihood estimation (mle). we applied dgx to a wide variety of real world data sets, such as sales data from a large retailer chain, us-age data from at&t, and internet clickstream data; in all cases, dgx fits these distributions very well, with almost a 99% correlation coefficient in quantile-quantile plots. our algorithm also scales very well because it requires only a single pass over the data. finally, we illustrate the power of dgx as a new tool for data mining tasks, such as outlier detection.
style mining of electronic messages for multiple authorship discrimination: first results. this paper considers the use of computational stylistics for performing authorship attribution of electronic messages, addressing categorization problems with as many as 20 different classes (authors). effective stylistic characterization of text is potentially useful for a variety of tasks, as language style contains cues regarding the authorship, purpose, and mood of the text, all of which would be useful adjuncts to information retrieval or knowledge-management tasks. we focus here on the problem of determining the author of an anonymous message, based only on the message text. several multiclass variants of the winnow algorithm were applied to a vector representation of the message texts to learn models for discriminating different authors. we present results comparing the classification accuracy of the different approaches. the results show that stylistic models can be accurately learned to determine an author's identity.
column-generation boosting methods for mixture of kernels. we devise a boosting approach to classification and regression based on column generation using a mixture of kernels. traditional kernel methods construct models based on a single positive semi-definite kernel with the type of kernel predefined and kernel parameters chosen according to cross-validation performance. our approach creates models that are mixtures of a library of kernel models, and our algorithm automatically determines kernels to be used in the final model. the 1-norm and 2-norm regularization methods are employed to restrict the ensemble of kernel models. the proposed method produces sparser solutions, and thus significantly reduces the testing time. by extending the column generation (cg) optimization which existed for linear programs with 1-norm regularization to quadratic programs with 2-norm regularization, we are able to solve many learning formulations by leveraging various algorithms for constructing single kernel models. by giving different priorities to columns to be generated, we are able to scale cg boosting to large datasets. experimental results on benchmark data are included to demonstrate its effectiveness.
systematic data selection to mine concept-drifting data streams. one major problem of existing methods to mine data streams is that it makes ad hoc choices to combine most recent data with some amount of old data to search the new hypothesis. the assumption is that the additional old data always helps produce a more accurate hypothesis than using the most recent data only. we first criticize this notion and point out that using old data blindly is not better than "gambling"; in other words, it helps increase the accuracy only if we are "lucky." we discuss and analyze the situations where old data will help and what kind of old data will help. the practical problem on choosing the right example from old data is due to the formidable cost to compare different possibilities and models. this problem will go away if we have an algorithm that is extremely efficient to compare all sensible choices with little extra cost. based on this observation, we propose a simple, efficient and accurate cross-validation decision tree ensemble method.
exploring the community structure of newsgroups. we propose to use the community structure of usenet for organizing and retrieving the information stored in newsgroups. in particular, we study the network formed by cross-posts, messages that are posted to two or more newsgroups simultaneously. we present what is, to our knowledge, by far the most detailed data that has been collected on usenet cross-postings. we analyze this network to show that it is a small-world network with significant clustering. we also present a spectral algorithm which clusters newsgroups based on the cross-post matrix. the result of our clustering provides a topical classification of newsgroups. our clustering gives many examples of significant relationships that would be missed by semantic clustering methods.
efficient anonymity-preserving data collection. the output of a data mining algorithm is only as good as its inputs, and individuals are often unwilling to provide accurate data about sensitive topics such as medical history and personal finance. individuals maybe willing to share their data, but only if they are assured that it will be used in an aggregate study and that it cannot be linked back to them. protocols for anonymity-preserving data collection provide this assurance, in the absence of trusted parties, by allowing a set of mutually distrustful respondents to anonymously contribute data to an untrusted data miner.to effectively provide anonymity, a data collection protocol must be collusion resistant, which means that even if all dishonest respondents collude with a dishonest data miner in an attempt to learn the associations between honest respondents and their responses, they will be unable to do so. to achieve collusion resistance, previously proposed protocols for anonymity-preserving data collection have quadratically many communication rounds in the number of respondents, and employ (sometimes incorrectly) complicated cryptographic techniques such as zero-knowledge proofs.we describe a new protocol for anonymity-preserving, collusion resistant data collection. our protocol has linearly many communication rounds, and achieves collusion resistance without relying on zero-knowledge proofs. this makes it especially suitable for data mining scenarios with a large number of respondents.
learning to match and cluster large high-dimensional data sets for data integration. part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. in integrating databases found on the web or obtained by using information extraction methods, it is often possible to solve this problem by exploiting similarities in the textual names used for objects in different databases. in this paper we describe techniques for clustering and matching identifier names that are both scalable and adaptive, in the sense that they can be trained to obtain better performance in a particular domain. an experimental evaluation on a number of sample datasets shows that the adaptive method sometimes performs much better than either of two non-adaptive baseline systems, and is nearly always competitive with the best baseline system.
exploiting dictionaries in named entity extraction: combining semi-markov extraction processes and data integration methods. we consider the problem of improving named entity recognition (ner) systems by using external dictionaries---more specifically, the problem of extending state-of-the-art ner systems by incorporating information about the similarity of extracted entities to entities in an external dictionary. this is difficult because most high-performance named entity recognition systems operate by sequentially classifying words as to whether or not they participate in an entity name; however, the most useful similarity measures score entire candidate names. to correct this mismatch we formalize a semi-markov extraction process, which is based on sequentially classifying segments of several adjacent words, rather than single words. in addition to allowing a natural way of coupling high-performance ner methods and high-performance similarity functions, this formalism also allows the direct use of other useful entity-level features, and provides a more natural formulation of the ner problem than sequential word classification. experiments in multiple domains show that the new model can substantially improve extraction performance over previous methods for using external dictionaries in ner.
understanding captions in biomedical publications. from the standpoint of the automated extraction of scientific knowledge, an important but little-studied part of scientific publications are the figures and accompanying captions. captions are dense in information, but also contain many extra-grammatical constructs, making them awkward to process with standard information extraction methods. we propose a scheme for "understanding" captions in biomedical publications by extracting and classifying "image pointers" (references to the accompanying image). we evaluate a number of automated methods for this task, including hand-coded methods, methods based on existing learning techniques, and methods based on novel learning techniques. the best of these methods leads to a usefully accurate tool for caption-understanding, with both recall and precision in excess of 94% on the most important single class in a combined extraction/classification task.
mining optimized gain rules for numeric attributes. association rules are useful for determining correlations between attributes of a relation and have applications in the marketing, financial, and retail sectors. furthermore, optimized association rules are an effective way to focus on the most interesting characteristics involving certain attributes. optimized association rules are permitted to contain uninstantiated attributes and the problem is to determine instantiations such that either the support, confidence, or gain of the rule is maximized. in this paper, we generalize the optimized gain association rule problem by permitting rules to contain disjunctions over uninstantiated numeric attributes. our generalized association rules enable us to extract more useful information about seasonal and local patterns involving the uninstantiated attribute. for rules containing a single numeric attribute, we present an algorithm with linear complexity for computing optimized gain rules. furthermore, we propose a bucketing technique that can result in a significant reduction in input size by coalescing contiguous values without sacrificing optimality. we also present an approximation algorithm based on dynamic programming for two numeric attributes. using recent results on binary space partitioning trees, we show that the approximations are within a constant factor of the optimal optimized gain rules. our experimental results with synthetic data sets for a single numeric attribute demonstrate that our algorithm scales up linearly with the attribute's domain size as well as the number of disjunctions. in addition, we show that applying our optimized rule framework to a population survey real-life data set enables us to discover interesting underlying correlations among the attributes.
fast window correlations over uncooperative time series. data arriving in time order (a data stream) arises in fields including physics, finance, medicine, and music, to name a few. often the data comes from sensors (in physics and medicine for example) whose data rates continue to improve dramatically as sensor technology improves. further, the number of sensors is increasing, so correlating data between sensors becomes ever more critical in order to distill knowlege from the data. in many applications such as finance, recent correlations are of far more interest than long-term correlation, so correlation over sliding windows (windowed correlation) is the desired operation. fast response is desirable in many applications (e.g., to aim a telescope at an activity of interest or to perform a stock trade). these three factors -- data size, windowed correlation, and fast response -- motivate this work.previous work [10, 14] showed how to compute pearson correlation using fast fourier transforms and wavelet transforms, but such techniques don't work for time series in which the energy is spread over many frequency components, thus resembling white noise. for such "uncooperative" time series, this paper shows how to combine several simple techniques -- sketches (random projections), convolution, structured random vectors, grid structures, and combinatorial design -- to achieve high performance windowed pearson correlation over a variety of data sets.
a robust and scalable clustering algorithm for mixed type attributes in large database environment. clustering is a widely used technique in data mining applications to discover patterns in the underlying data. most traditional clustering algorithms are limited to handling datasets that contain either continuous or categorical attributes. however, datasets with mixed types of attributes are common in real life data mining problems. in this paper, we propose a distance measure that enables clustering data with both continuous and categorical attributes. this distance measure is derived from a probabilistic model that the distance between two clusters is equivalent to the decrease in log-likelihood function as a result of merging. calculation of this measure is memory efficient as it depends only on the merging cluster pair and not on all the other clusters. zhang et al [8] proposed a clustering method named birch that is especially suitable for very large datasets. we develop a clustering algorithm using our distance measure based on the framework of birch. similar to birch, our algorithm first performs a pre-clustering step by scanning the entire dataset and storing the dense regions of data records in terms of summary statistics. a hierarchical clustering algorithm is then applied to cluster the dense regions. apart from the ability of handling mixed type of attributes, our algorithm differs from birch in that we add a procedure that enables the algorithm to automatically determine the appropriate number of clusters and a new strategy of assigning cluster membership to noisy data. for data with mixed type of attributes, our experimental results confirm that the algorithm not only generates better quality clusters than the traditional k-means algorithms, but also exhibits good scalability properties and is able to identify the underlying number of clusters in the data correctly. the algorithm is implemented in the commercial data mining tool clementine 6.0 which supports the pmml standard of data mining model deployment.
efficient data reduction with ease. a variety of mining and analysis problems --- ranging from association-rule discovery to contingency table analysis to materialization of certain approximate datacubes --- involve the extraction of knowledge from a set of categorical count data. such data can be viewed as a collection of "transactions," where a transaction is a fixed-length vector of counts. classical algorithms for solving count-data problems require one or more computationally intensive passes over the entire database and can be prohibitively slow. one effective method for dealing with this ever-worsening scalability problem is to run the algorithms on a small sample of the data. we present a new data-reduction algorithm, called ease, for producing such a sample. like the fast algorithm introduced by chen et al., ease is especially designed for count data applications. both ease and fast take a relatively large initial random sample and then deterministically produce a subsample whose "distance" --- appropriately defined --- from the complete database is minimal. unlike fast, which obtains the final subsample by quasi-greedy descent, ease uses epsilon-approximation methods to obtain the final subsample by a process of repeated halving. experiments both in the context of association rule mining and classical &chi;2 contingency-table analysis show that ease outperforms both fast and simple random sampling, sometimes dramatically.
parallel mining of closed sequential patterns. discovery of sequential patterns is an essential data mining task with broad applications. among several variations of sequential patterns, closed sequential pattern is the most useful one since it retains all the information of the complete pattern set but is often much more compact than it. unfortunately, there is no parallel closed sequential pattern mining method proposed yet. in this paper we develop an algorithm, called par-csp (parallel closed sequential pattern mining), to conduct parallel mining of closed sequential patterns on a distributed memory system. par-csp partitions the work among the processors by exploiting the divide-and-conquer property so that the overhead of interprocessor communication is minimized. par-csp applies dynamic scheduling to avoid processor idling. moreover, it employs a technique, called selective sampling to address the load imbalance problem. we implement par-csp using mpi on a 64-node linux cluster. our experimental results show that par-csp attains good parallelization efficiencies on various input datasets.
model compression. often the best performing supervised learning models are ensembles of hundreds or thousands of base-level classifiers. unfortunately, the space required to store this many classifiers, and the time required to execute them at run-time, prohibits their use in applications where test sets are large (e.g. google), where storage space is at a premium (e.g. pdas), and where computational power is limited (e.g. hea-ring aids). we present a method for "compressing" large, complex ensembles into smaller, faster models, usually without significant loss in performance.
dualminer: a dual-pruning algorithm for itemsets with constraints. constraint-based mining of itemsets for questions such as "find all frequent itemsets where the total price is at least $50" has received much attention recently. two classes of constraints, monotone and antimonotone, have been identified as very useful. there are algorithms that efficiently take advantage of either one of these two classes, but no previous algorithms can efficiently handle both types of constraints simultaneously. in this paper, we present the first algorithm (called dualminer) that uses both monotone and antimonotone constraints to prune its search space. we complement a theoretical analysis and proof of correctness of dualminer with an experimental study that shows the efficacy of dualminer compared to previous work.
out-of-core frequent pattern mining on a commodity pc. in this work we focus on the problem of frequent itemset mining on large, out-of-core data sets. after presenting a characterization of existing out-of-core frequent itemset mining algorithms and their drawbacks, we introduce our efficient, highly scalable solution. presented in the context of the fpgrowth algorithm, our technique involves several novel i/o-conscious optimizations, such as approximate hash-based sorting and blocking, and leverages recent architectural advancements in commodity computers, such as 64-bit processing. we evaluate the proposed optimizations on truly large data sets,up to 75gb, and show they yield greater than a 400-fold execution time improvement. finally, we discuss the impact of this research in the context of other pattern mining challenges, such as sequence mining and graph mining.
data mining criteria for tree-based regression and classification. this paper is concerned with the construction of regression and classification trees that are more adapted to data mining applications than conventional trees. to this end, we propose new splitting criteria for growing trees. conventional splitting criteria attempt to perform well on both sides of a split by attempting a compromise in the quality of fit between the left and the right side. by contrast, we adopt a data mining point of view by proposing criteria that search for interesting subsets of the data, as opposed to modeling all of the data equally well. the new criteria do not split based on a compromise between the left and the right bucket; they effectively pick the more interesting bucket and ignore the other.as expected, the result is often a simpler characterization of interesting subsets of the data. less expected is that the new criteria often yield whole trees that provide more interpretable data descriptions. surprisingly, it is a "flaw" that works to their advantage: the new criteria have an increased tendency to accept splits near the boundaries of the predictor ranges. this so-called "end-cut problem" leads to the repeated peeling of small layers of data and results in very unbalanced but highly expressive and interpretable trees.
predicting customer shopping lists from point-of-sale purchase data. this paper describes a prototype that predicts the shopping lists for customers in a retail store. the shopping list prediction is one aspect of a larger system we have developed for retailers to provide individual and personalized interactions with customers as they navigate through the retail store. instead of using traditional personalization approaches, such as clustering or segmentation, we learn separate classifiers for each customer from historical transactional data. this allows us to make very fine-grained and accurate predictions about what items a particular individual customer will buy on a given shopping trip.we formally frame the shopping list prediction as a classification problem, describe the algorithms and methodology behind our system, its impact on the business case in which we frame it, and explore some of the properties of the data source that make it an interesting testbed for kdd algorithms. our results show that we can predict a shopper's shopping list with high levels of accuracy, precision, and recall. we believe that this work impacts both the data mining and the retail business community. the formulation of shopping list prediction as a machine learning problem results in algorithms that should be useful beyond retail shopping list prediction. for retailers, the result is not only a practical system that increases revenues by up to 11%, but also enhances customer experience and loyalty by giving them the tools to individually interact with customers and anticipate their needs.
classification features for attack detection in collaborative recommender systems. collaborative recommender systems are highly vulnerable to attack. attackers can use automated means to inject a large number of biased profiles into such a system, resulting in recommendations that favor or disfavor given items. since collaborative recommender systems must be open to user input, it is difficult to design a system that cannot be so attacked. researchers studying robust recommendation have therefore begun to identify types of attacks and study mechanisms for recognizing and defeating them. in this paper, we propose and study different attributes derived from user profiles for their utility in attack detection. we show that a machine learning classification approach that includes attributes derived from attack models is more successful than more generalized detection algorithms previously studied.
discovery net: towards a grid of knowledge discovery. this paper provides a blueprint for constructing collaborative and distributed knowledge discovery systems within grid-based computing environments. the need for such systems is driven by the quest for sharing knowledge, information and computing resources within the boundaries of single large distributed organisations or within complex virtual organisations (vo) created to tackle specific projects. the proposed architecture is built on top of a resource federation management layer and is composed of a set of different resources. we show how this architecture will behave during a typical kdd process design and deployment, how it enables the execution of complex and distributed data mining tasks with high performance and how it provides a community of e-scientists with means to collaborate, retrieve and reuse both kdd algorithms, discovery processes and knowledge in a visual analytical environment.
adversarial classification. essentially all data mining algorithms assume that the data-generating process is independent of the data miner's activities. however, in many domains, including spam detection, intrusion detection, fraud detection, surveillance and counter-terrorism, this is far from the case: the data is actively manipulated by an adversary seeking to make the classifier produce false negatives. in these domains, the performance of a classifier can degrade rapidly after it is deployed, as the adversary learns to defeat it. currently the only solution to this is repeated, manual, ad hoc reconstruction of the classifier. in this paper we develop a formal framework and algorithms for this problem. we view classification as a game between the classifier and the adversary, and produce a classifier that is optimal given the adversary's optimal strategy. experiments in a spam detection domain show that this approach can greatly outperform a classifier learned in the standard way, and (within the parameters of the problem) automatically adapt the classifier to the adversary's evolving manipulations.
probabilistic modeling of transaction data with applications to profiling, visualization, and prediction. transaction data is ubiquitous in data mining applications. examples include market basket data in retail commerce, telephone call records in telecommunications, and web logs of individual page-requests at web sites. profiling consists of using historical transaction data on individuals to construct a model of each individual's behavior. simple profiling techniques such as histograms do not generalize well from sparse transaction data. in this paper we investigate the application of probabilistic mixture models to automatically generate profiles from large volumes of transaction data. in effect, the mixture model represents each individual's behavior as a linear combination of "basis transactions." we evaluate several variations of the model on a large retail transaction data set and show that the proposed model provides improved predictive power over simpler histogram-based techniques, as well as being relatively scalable, interpretable, and flexible. in addition we point to applications in outlier detection, customer ranking, interactive visualization, and so forth. the paper concludes by comparing and relating the proposed framework to other transaction-data modeling techniques such as association rules.
mining rank-correlated sets of numerical attributes. we study the mining of interesting patterns in the presence of numerical attributes. instead of the usual discretization methods, we propose the use of rank based measures to score the similarity of sets of numerical attributes. new support measures for numerical data are introduced, based on extensions of kendall's tau, and spearman's footrule and rho. we show how these support measures are related. furthermore, we introduce a novel type of pattern combining numerical and categorical attributes. we give efficient algorithms to find all frequent patterns for the proposed support measures, and evaluate their performance on real-life datasets.
feature selection in scientific applications. numerous applications of data mining to scientific data involve the induction of a classification model. in many cases, the collection of data is not performed with this task in mind, and therefore, the data might contain irrelevant or redundant features that affect negatively the accuracy of the induction algorithms. the size and dimensionality of typical scientific data make it difficult to use any available domain information to identify features that discriminate between the classes of interest. similarly, exploratory data analysis techniques have limitations on the amount and dimensionality of the data they can process effectively. in this paper, we describe applications of efficient feature selection methods to data sets from astronomy, plasma physics, and remote sensing. we use variations of recently proposed filter methods as well as traditional wrapper approaches, where practical. we discuss the general challenges of feature selection in scientific datasets, the strategies for success that were common among our diverse applications, and the lessons learned in solving these problems.
probabilistic discovery of time series motifs. several important time series data mining problems reduce to the core task of finding approximately repeated subsequences in a longer time series. in an earlier work, we formalized the idea of approximately repeated subsequences by introducing the notion of time series motifs. two limitations of this work were the poor scalability of the motif discovery algorithm, and the inability to discover motifs in the presence of noise.here we address these limitations by introducing a novel algorithm inspired by recent advances in the problem of pattern discovery in biosequences. our algorithm is probabilistic in nature, but as we show empirically and theoretically, it can find time series motifs with very high probability even in the presence of noise or "don't care" symbols. not only is the algorithm fast, but it is an anytime algorithm, producing likely candidate motifs almost immediately, and gradually improving the quality of results over time.
gaining insights into support vector machine pattern classifiers using projection-based tour methods. this paper discusses visual methods that can be used to understand and interpret the results of classification using support vector machines (svm) on data with continuous real-valued variables. svm induction algorithms build pattern classifiers by identifying a maximal margin separating hyperplane from training examples in high dimensional pattern spaces or spaces induced by suitable nonlinear kernel transformations over pattern spaces. svm have been demonstrated to be quite effective in a number of practical pattern classification tasks. since the separating hyperplane is defined in terms of more than two variables it is necessary to use visual techniques that can navigate the viewer through high-dimensional spaces. we demonstrate the use of projection-based tour methods to gain useful insights into svm classifiers with linear kernels on 8-dimensional data.
belief state approaches to signaling alarms in surveillance systems. surveillance systems have long been used to monitor industrial processes and are becoming increasingly popular in public health and anti-terrorism applications. most early detection systems produce a time series of p-values or some other statistic as their output. typically, the decision to signal an alarm is based on a threshold or other simple algorithm such as cusum that accumulates detection information temporally.we formulate a pomdp model of underlying events and observations from a detector. we solve the model and show how it is used for single-output detectors. when dealing with spatio-temporal data, scan statistics are a popular method of building detectors. we describe the use of scan statistics in surveillance and how our pomdp model can be used to perform alarm signaling with them. we compare the results obtained by our method with simple thresholding and cusum on synthetic and semi-synthetic health data.
scalable discovery of hidden emails from large folders. the popularity of email has triggered researchers to look for ways to help users better organize the enormous amount of information stored in their email folders. one challenge that has not been studied extensively in text mining is the identification and reconstruction of hidden emails. a hidden email is an original email that has been quoted in at least one email in a folder, but does not present itself in the same folder. it may have been (un)intentionally deleted or may never have been received. the discovery and reconstruction of hidden emails is critical for many applications including email classification, summarization and forensics. this paper proposes a framework for reconstructing hidden emails using the embedded quotations found in messages further down the thread hierarchy. we evaluate the robustness and scalability of our framework by using the enron public email corpus. our experiments show that hidden emails exist widely in that corpus and also that our optimization techniques are effective in processing large email folders.
variable latent semantic indexing. latent semantic indexing is a classical method to produce optimal low-rank approximations of a term-document matrix. however, in the context of a particular query distribution, the approximation thus produced need not be optimal. we propose vlsi, a new query-dependent (or "variable") low-rank approximation that minimizes approximation error for any specified query distribution. with this tool, it is possible to tailor the lsi technique to particular settings, often resulting in vastly improved approximations at much lower dimensionality. we validate this method via a series of experiments on classical corpora, showing that vlsi typically performs similarly to lsi with an order of magnitude fewer dimensions.
making holistic schema matching robust: an ensemble approach. the web has been rapidly "deepened" by myriad searchable databases online, where data are hidden behind query interfaces. as an essential task toward integrating these massive "deep web" sources, large scale schema matching (i.e., discovering semantic correspondences of attributes across many query interfaces) has been actively studied recently. in particular, many works have emerged to address this problem by "holistically" matching many schemas at the same time and thus pursuing "mining" approaches in nature. however, while holistic schema matching has built its promise upon the large quantity of input schemas, it also suffers the robustness problem caused by noisy data quality. such noises often inevitably arise in the automatic extraction of schema data, which is mandatory in large scale integration. for holistic matching to be viable, it is thus essential to make it robust against noisy schemas. to tackle this challenge, we propose a data-ensemble framework with sampling and voting techniques, which is inspired by bagging predictors. specifically, our approach creates an ensemble of matchers, by randomizing input schema data into many independently downsampled trials, executing the same matcher on each trial and then aggregating their ranked results by taking majority voting. as a principled basis, we provide analytic justification of the effectiveness of this data-ensemble framework. further, empirically, our experiments on real web data show that the "ensemblization" indeed significantly boosts the matching accuracy under noisy schema input, and thus maintains the desired robustness of a holistic matcher.
mining citizen science data to predict orevalence of wild bird species. the cornell laboratory of ornithology's mission is to interpret and conserve the earth's biological diversity through research, education, and citizen science focused on birds. over the years, the lab has accumulated one of the largest and longest-running collections of environmental data sets in existence. the data sets are not only large, but also have many attributes, contain many missing values, and potentially are very noisy. the ecologists are interested in identifying which features have the strongest effect on the distribution and abundance of bird species as well as describing the forms of these relationships. we show how data mining can be successfully applied, enabling the ecologists to discover unanticipated relationships. we compare a variety of methods for measuring attribute importance with respect to the probability of a bird being observed at a feeder and present initial results for the impact of important attributes on bird prevalence.
data quality through knowledge engineering. traditionally, data quality programs have acted as a preprocessing stage to make data suitable for a data mining or analysis operation. recently, data quality concepts have been applied to databases that support business operations such as provisioning and billing. incorporating business rules that drive operations and their associated data processes is critically important to the success of such projects. however, there are many practical complications. for example, documentation on business rules is often meager. rules change frequently. domain knowledge is often fragmented across experts, and those experts do not always agree. typically, rules have to be gathered from subject matter experts iteratively, and are discovered out of logical or procedural sequence, like a jigsaw puzzle. our approach is to impement business rules as constraints on data in a classical expert system formalism sometimes called production rules. our system works by allowing good data to pass through a system of constraints unchecked. bad data violate constraints and are flagged, and then fed back after correction. constraints are added incrementally as better understanding of the business rules is gained. we include a real-life case study.
data mining in metric space: an empirical analysis of supervised learning performance criteria. many criteria can be used to evaluate the performance of supervised learning. different criteria are appropriate in different settings, and it is not always clear which criteria to use. a further complication is that learning methods that perform well on one criterion may not perform well on other criteria. for example, svms and boosting are designed to optimize accuracy, whereas neural nets typically optimize squared error or cross entropy. we conducted an empirical study using a variety of learning methods (svms, neural nets, k-nearest neighbor, bagged and boosted trees, and boosted stumps) to compare nine boolean classification performance metrics: accuracy, lift, f-score, area under the roc curve, average precision, precision/recall break-even point, squared error, cross entropy, and probability calibration. multidimensional scaling (mds) shows that these metrics span a low dimensional manifold. the three metrics that are appropriate when predictions are interpreted as probabilities: squared error, cross entropy, and calibration, lay in one part of metric space far away from metrics that depend on the relative order of the predicted values: roc area, average precision, break-even point, and lift. in between them fall two metrics that depend on comparing predictions to a threshold: accuracy and f-score. as expected, maximum margin methods such as svms and boosted trees have excellent performance on metrics like accuracy, but perform poorly on probability metrics such as squared error. what was not expected was that the margin methods have excellent performance on ordering metrics such as roc area and average precision. we introduce a new metric, sar, that combines squared error, accuracy, and roc area into one metric. mds and correlation analysis shows that sar is centrally located and correlates well with other metrics, suggesting that it is a good general purpose metric to use when more specific criteria are not known.
single-pass online learning: performance, voting schemes and online feature selection. to learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. online learning methods such as perceptron or winnow are naturally suited to stream processing; however, in practice multiple passes over the same training data are required to achieve accuracy comparable to state-of-the-art batch learners. in the current work we address the problem of training an on-line learner with a single passover the data. we evaluate several existing methods, and also propose a new modification of margin balanced winnow, which has performance comparable to linear svm. we also explore the effect of averaging, a.k.a. voting, on online learning. finally, we describe how the new modified margin balanced winnow algorithm can be naturally adapted to perform feature selection. this scheme performs comparably to widely-used batch feature selection methods like information gain or chi-square, with the advantage of being able to select features on-the-fly. taken together, these techniques allow single-pass online learning to be competitive with batch techniques, and still maintain the advantages of on-line learning.
extracting semantics from data cubes using cube transversals and closures. in this paper we propose a lattice-based approach intended for extracting semantics from datacubes: borders of version spaces for supervised classification, closed cube lattice to summarize the semantics of datacubes w.r.t. count, sum, and covering graph of the quotient cube as a visualization tool of minimal multidimensional associations. with this intention, we introduce two novel concepts: the cube transversals and the cube closures over the cube lattice of a categorical database relation. we propose a levelwise merging algorithm for mining minimal cube transversals with a single database scan. we introduce the cube connection, show that it is a galois connection and derive a closure operator over the cube lattice. using cube transversals and closures, we define a new characterization of boundary sets which provide a condensed representation of version spaces used to enhance supervised classification. the algorithm designed for computing such borders improves the complexity of previous proposals. we also introduce the concept of closed cube lattice and show that it is isomorph to on one hand the galois lattice and on the other hand the quotient cube w.r.t. count, sum. proposed in [16], the quotient cube is a succinct summary of a datacube preserving the rollup/drilldown semantics. we show that the quotient cube w.r.t. count, sum and the closed cube lattice have a similar expression power but the latter has the smallest possible size. finally we focus on the multidimensional association issue and introduce the covering graph of the quotient cube which provides the user with a visualization tool of minimal multidimensional associations.
onboard classifiers for science event detection on a remote sensing spacecraft. typically, data collected by a spacecraft is downlinked to earth and preprocessed before any analysis is performed. we have developed classifiers that can be used onboard a spacecraft to identify high priority data for downlink to earth, providing a method for maximizing the use of a potentially bandwidth limited downlink channel. onboard analysis can also enable rapid reaction to dynamic events, such as flooding, volcanic eruptions or sea ice break-up.four classifiers were developed to identify cryosphere events using hyperspectral images. these classifiers include a manually constructed classifier, a support vector machine (svm), a decision tree and a classifier derived by searching over combinations of thresholded band ratios. each of the classifiers was designed to run in the computationally constrained operating environment of the spacecraft. a set of scenes was hand-labeled to provide training and testing data. performance results on the test data indicate that the svm and manual classifiers outperformed the decision tree and band-ratio classifiers with the svm yielding slightly better classifications than the manual classifier.the manual and svm classifiers have been uploaded to the eo-1 spacecraft and have been running onboard the spacecraft for over a year. results of the onboard analysis are used by the autonomous sciencecraft experiment (ase) of nasa's new millennium program onboard eo-1 to automatically target the spacecraft to collect follow-on imagery. the software demonstrates the potential for future deep space missions to use onboard decision making to capture short-lived science events.
estimating business targets. determining and setting maximal revenue expectations or other business performance targets---whether it is for regional company divisions or individual customers---can have profound financial implications. operational techniques are changed, staffing levels are altered and management attention is re-focused---all in the name of expectations. in practice these expectations are often derived in an ad hoc manner. to address this unsupervised task, we combine nearest neighbor methods and classical statistical methods and derive a new solution to the classical econometric task of frontier analysis. we apply our methodology to two real world business problems in verizon, a major telecommunications provider in the united states, more specifically in the print yellow page division verizon information services: (1) identifying under marketed customers for targeted upselling campaigns and focused sales attention, and (2) benchmarking regional directory divisions to incent performance improvements. our analysis uncovers some commercially useful aspects of these domains and by conservative estimates can increase revenue by several million dollars in each domain.
a general approach to incorporate data quality matrices into data mining algorithms. data quality is a central issue for many information-oriented organizations. recent advances in the data quality field reflect the view that a database is the product of a manufacturing process. while routine errors, such as non-existent zip codes, can be detected and corrected using traditional data cleansing tools, many errors systemic to the manufacturing process cannot be addressed. therefore, the product of the data manufacturing process is an imprecise recording of information about the entities of interest (i.e. customers, transactions or assets). in this way, the database is only one (flawed) version of the entities it is supposed to represent. quality assurance systems such as motorola's six-sigma and other continuous improvement methods document the data manufacturing process's shortcomings. a widespread method of documentation is quality matrices. in this paper, we explore the use of the readily available data quality matrices for the data mining classification task. we first illustrate that if we do not factor in these quality matrices, then our results for prediction are sub-optimal. we then suggest a general-purpose ensemble approach that perturbs the data according to these quality matrices to improve the predictive accuracy and show the improvement is due to a reduction in variance.
data mining challenges in the automotive domain. automotive companies, such as ford motor company, have no shortage of large databases with abundant opportunities for cost reduction and revenue enhancement. the data mining group at ford has worked in the areas of quality, customer satisfaction and warranty analytics for close to ten years. in this time, we have developed a number of methods for building systems to help the business. one area of particular success has been in warranty analysis. while traditional hazard analysis has been applied at ford for a number of years, we have used techniques from other industries (e.g. retail), as well as text mining to view warranty analytics in a new way. however, our success has been tempered by serious challenges particularly in the areas of data understanding, computing meaningful aggregations and implementation. case studies from the automobile industry (warranty, quality, forecasting, etc.) as well as from other industries will be used.
locating secret messages in images. steganography involves hiding messages in innocuous media such as images, while steganalysis is the field of detecting these secret messages. the ultimate goal of steganalysis is two-fold: making a binary classification of a file as stego-bearing or innocent, and secondly, locating the hidden message with an aim to extracting, sterilizing or manipulating it. almost all steganalysis approaches (known as attacks) focus on the first of these two issues. in this paper, we explore the difficult related problem: given that we know an image file contains steganography, locate which pixels contain the message. we treat the hidden message location problem as outlier detection using probability/energy measures of images motivated by the image restoration community. pixels contributing the most to the energy calculations of an image are deemed outliers. typically, of the top third of one percent of most energized pixels (outliers), we find that 87% are stego-bearing in color images and 61% in grayscale images. in all image types only 1% of all pixels are stego-bearing indicating our techniques provides a substantial lift over random guessing.
translation-invariant mixture models for curve clustering. in this paper we present a family of algorithms that can simultaneously align and cluster sets of multidimensional curves defined on a discrete time grid. our approach uses the expectation-maximization (em) algorithm to recover both the mean curve shapes for each cluster, and the most likely shifts, offsets, and cluster memberships for each curve. we demonstrate how bayesian estimation methods can improve the results for small sample sizes by enforcing smoothness in the cluster mean curves. we evaluate the methodology on two real-world data sets, time-course gene expression data and storm trajectory data. experimental results show that models that incorporate curve alignment systematically provide improvements in predictive power and within-cluster variance on test data sets. the proposed approach provides a non-parametric, computationally efficient, and robust methodology for clustering broad classes of curve data.
evolutionary clustering. we consider the problem of clustering data over time. an evolutionary clustering should simultaneously optimize two potentially conflicting criteria: first, the clustering at any point in time should remain faithful to the current data as much as possible; and second, the clustering should not shift dramatically from one timestep to the next. we present a generic framework for this problem, and discuss evolutionary versions of two widely-used clustering algorithms within this framework: k-means and agglomerative hierarchical clustering. we extensively evaluate these algorithms on real data sets and show that our algorithms can simultaneously attain both high accuracy in capturing today's data, and high fidelity in reflecting yesterday's clustering.
pattern discovery in sequences under a markov assumption. in this paper we investigate the general problem of discovering recurrent patterns that are embedded in categorical sequences. an important real-world problem of this nature is motif discovery in dna sequences. we investigate the fundamental aspects of this data mining problem that can make discovery "easy" or "hard." we present a general framework for characterizing learning in this context by deriving the bayes error rate for this problem under a markov assumption. the bayes error framework demonstrates why certain patterns are much harder to discover than others. it also explains the role of different parameters such as pattern length and pattern frequency in sequential discovery. we demonstrate how the bayes error can be used to calibrate existing discovery algorithms, providing a lower bound on achievable performance. we discuss a number of fundamental issues that characterize sequential pattern discovery in this context, present a variety of empirical results to complement and verify the theoretical analysis, and apply our methodology to real-world motif-discovery problems in computational biology.
mining and summarizing customer reviews. merchants selling products on the web often ask their customers to review the products that they have purchased and the associated services. as e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. for a popular product, the number of reviews can be in hundreds or even thousands. this makes it difficult for a potential customer to read them to make an informed decision on whether to purchase the product. it also makes it difficult for the manufacturer of the product to keep track and to manage customer opinions. for the manufacturer, there are additional difficulties because many merchant sites may sell the same product and the manufacturer normally produces many kinds of products. in this research, we aim to mine and to summarize all the customer reviews of a product. this summarization task is different from traditional text summarization because we only mine the features of the product on which the customers have expressed their opinions and whether the opinions are positive or negative. we do not summarize the reviews by selecting a subset or rewrite some of the original sentences from the reviews to capture the main points as in the classic text summarization. our task is performed in three steps: (1) mining product features that have been commented on by customers; (2) identifying opinion sentences in each review and deciding whether each opinion sentence is positive or negative; (3) summarizing the results. this paper proposes several novel techniques to perform these tasks. our experimental results using reviews of a number of products sold online demonstrate the effectiveness of the techniques.
fully automatic cross-associations. large, sparse binary matrices arise in numerous data mining applications, such as the analysis of market baskets, web graphs, social networks, co-citations, as well as information retrieval, collaborative filtering, sparse matrix reordering, etc. virtually all popular methods for the analysis of such matrices---e.g., k-means clustering, metis graph partitioning, svd/pca and frequent itemset mining---require the user to specify various parameters, such as the number of clusters, number of principal components, number of partitions, and "support." choosing suitable values for such parameters is a challenging problem.cross-association is a joint decomposition of a binary matrix into disjoint row and column groups such that the rectangular intersections of groups are homogeneous. starting from first principles, we furnish a clear, information-theoretic criterion to choose a good cross-association as well as its parameters, namely, the number of row and column groups. we provide scalable algorithms to approach the optimal. our algorithm is parameter-free, and requires no user intervention. in practice it scales linearly with the problem size, and is thus applicable to very large matrices. finally, we present experiments on multiple synthetic and real-life datasets, where our method gives high-quality, intuitive results.
estimating the global pagerank of web communities. localized search engines are small-scale systems that index a particular community on the web. they offer several benefits over their large-scale counterparts in that they are relatively inexpensive to build, and can provide more precise and complete search capability over their relevant domains. one disadvantage such systems have over large-scale search engines is the lack of global pagerank values. such information is needed to assess the value of pages in the localized search domain within the context of the web as a whole. in this paper, we present well-motivated algorithms to estimate the global pagerank values of a local domain. the algorithms are all highly scalable in that, given a local domain of size n, they use o(n) resources that include computation time, bandwidth, and storage. we test our methods across a variety of localized domains, including site-specific domains and topic-specific domains. we demonstrate that by crawling as few as n or 2n additional pages, our methods can give excellent global pagerank estimates.
a rank sum test method for informative gene discovery. finding informative genes from microarray data is an important research problem in bioinformatics research and applications. most of the existing methods rank features according to their discriminative capability and then find a subset of discriminative genes (usually top k genes). in particular, t-statistic criterion and its variants have been adopted extensively. this kind of methods rely on the statistics principle of t-test, which requires that the data follows a normal distribution. however, according to our investigation, the normality condition often cannot be met in real data sets.to avoid the assumption of the normality condition, in this paper, we propose a rank sum test method for informative gene discovery. the method uses a rank-sum statistic as the ranking criterion. moreover, we propose using the significance level threshold, instead of the number of informative genes, as the parameter. the significance level threshold as a parameter carries the quality specification in statistics. we follow the pitman efficiency theory to show that the rank sum method is more accurate and more robust than the t-statistic method in theory.to verify the effectiveness of the rank sum method, we use support vector machine (svm) to construct classifiers based on the identified informative genes on two well known data sets, namely colon data and leukemia data. the prediction accuracy reaches 96.2% on the colon data and 100% on the leukemia data. the results are clearly better than those from the previous feature ranking methods. by experiments, we also verify that using significance level threshold is more effective than directly specifying an arbitrary k.
finding recent frequent itemsets adaptively over online data streams. a data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. consequently, the knowledge embedded in a data stream is more likely to be changed as time goes by. identifying the recent change of a data stream, specially for an online data stream, can provide valuable information for the analysis of the data stream. in addition, monitoring the continuous variation of a data stream enables to find the gradual change of embedded knowledge. however, most of mining algorithms over a data stream do not differentiate the information of recently generated transactions from the obsolete information of old transactions which may be no longer useful or possibly invalid at present. this paper proposes a data mining method for finding recent frequent itemsets adaptively over an online data stream. the effect of old transactions on the mining result of the data steam is diminished by decaying the old occurrences of each itemset as time goes by. furthermore, several optimization techniques are devised to minimize processing time as well as main memory usage. finally, the proposed method is analyzed by a series of experiments.
parallel computation of high dimensional robust correlation and covariance matrices. the computation of covariance and correlation matrices are critical to many data mining applications and processes. unfortunately the classical covariance and correlation matrices are very sensitive to outliers. robust methods, such as qc and the maronna method, have been proposed. however, existing algorithms for qc only give acceptable performance when the dimensionality of the matrix is in the hundreds; and the maronna method is rarely used in practice because of its high computational cost.in this paper, we develop parallel algorithms for both qc and the maronna method. we evaluate these parallel algorithms using a real data set of the gene expression of over 6,000 genes, giving rise to a matrix of over 18 million entries. in our experimental evaluation, we explore scalability in dimensionality and in the number of processors. we also compare the parallel behaviours of the two methods. after thorough experimentation, we conclude that for many data mining applications, both qc and maronna are viable options. less robust, but faster, qc is the recommended choice for small parallel platforms. on the other hand, the maronna method is the recommended choice when a high degree of robustness is required, or when the parallel platform features a high number of processors.
cvs: a correlation-verification based smoothing technique on information retrieval and term clustering. as information volume in enterprise systems and in the web grows rapidly, how to accurately retrieve information is an important research area. several corpus based smoothing techniques have been proposed to address the data sparsity and synonym problems faced by information retrieval systems. such smoothing techniques are often unable to discover and utilize the correlations among terms.we propose cvs, a correlation-verification based smoothing method, that considers co-occurrence information in smoothing. strongly correlated terms in a document are identified by their co-occurrence frequencies in the document. to avoid missing correlated terms with low co-occurrence frequencies but specific to the theme of the document, the joint distributions of terms in the document are compared with those in the corpus for statistical significance.a common approach to apply corpus based smoothing techniques to information retrieval is by refining the vector representations of documents. this paper investigates the effects of corpus based smoothing on information retrieval by query expansion using term clusters generated from a term clustering process. the results can also be viewed in light of the effects of smoothing on clustering.empirical studies show that our approach outperforms previous corpus based smoothing techniques. it improves retrieval effectiveness by 14.6%. the results demonstrate that corpus based smoothing can be used for query expansion by term clustering.
a general model for clustering binary data. clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. this paper studies the problem of clustering binary data. this is the case for market basket datasets where the transactions contain items and for document datasets where the documents contain "bag of words". the contribution of the paper is three-fold. first a general binary data clustering model is presented. the model treats the data and features equally, based on their symmetric association relations, and explicitly describes the data assignments as well as feature assignments. we characterize several variations with different optimization procedures for the general model. second, we also establish the connections between our clustering model with other existing clustering methods. third, we also discuss the problem for determining the number of clusters for binary clustering. experimental results show the effectiveness of the proposed clustering model.
liped: hmm-based life profiles for adaptive event detection. in this paper, the proposed liped (life profile based event detection) employs the concept of life profiles to predict the activeness of event for effective event detection. a group of events with similar activeness patterns shares a life profile, modeled by a hidden markov model. considering the burst-and-diverse property of events, liped identifies the activeness status of event. as a result, liped balances the clustering precision and recall to achieve better f1 scores than other well known approaches evaluated on the official tdt1 corpus.
co-clustering documents and words using bipartite spectral graph partitioning. both document clustering and word clustering are well studied problems. most existing algorithms cluster documents and words separately but not simultaneously. in this paper we present the novel idea of modeling the document collection as a bipartite graph between documents and words, using which the simultaneous clustering problem can be posed as a bipartite graph partitioning problem. to solve the partitioning problem, we use a new spectral co-clustering algorithm that uses the second left and right singular vectors of an appropriately scaled word-document matrix to yield good bipartitionings. the spectral algorithm enjoys some optimality properties; it can be shown that the singular vectors solve a real relaxation to the np-complete graph bipartitioning problem. we present experimental results to verify that the resulting co-clustering algorithm works well in practice.
pva: a self-adaptive personal view agent system. in this paper, we present pva, an adaptive personal view information agent system to track, learn and manage, user's interests in internet documents. when user's interests change, pva, in not only the contents, but also in the structure of user profile, is modified to adapt to the changes. experimental results show that modulating the structure of user profile does increase the accuracy of personalization systems.
kernel k-means: spectral clustering and normalized cuts. kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. despite significant research, these methods have remained only loosely related. in this paper, we give an explicit theoretical connection between them. we show the generality of the weighted kernel k-means objective function, and derive the spectral clustering objective of normalized cut as a special case. given a positive definite similarity matrix, our results lead to a novel weighted kernel k-means algorithm that monotonically decreases the normalized cut. this has important implications: a) eigenvector-based algorithms, which can be computationally prohibitive, are not essential for minimizing normalized cuts, b) various techniques, such as local search and acceleration schemes, may be used to improve the quality as well as speed of kernel k-means. finally, we present results on several interesting data sets, including diametrical clustering of large gene-expression matrices and a handwriting recognition data set.
a fast kernel-based multilevel algorithm for graph clustering. graph clustering (also called graph partitioning) --- clustering the nodes of a graph --- is an important problem in diverse data mining applications. traditional approaches involve optimization of graph clustering objectives such as normalized cut or ratio association; spectral methods are widely used for these objectives, but they require eigenvector computation which can be slow. recently, graph clustering with a general cut objective has been shown to be mathematically equivalent to an appropriate weighted kernel k-means objective function. in this paper, we exploit this equivalence to develop a very fast multilevel algorithm for graph clustering. multilevel approaches involve coarsening, initial partitioning and refinement phases, all of which may be specialized to different graph clustering objectives. unlike existing multilevel clustering approaches, such as metis, our algorithm does not constrain the cluster sizes to be nearly equal. our approach gives a theoretical guarantee that the refinement step decreases the graph cut objective under consideration. experiments show that we achieve better final objective function values as compared to a state-of-the-art spectral clustering algorithm: on a series of benchmark test graphs with up to thirty thousand nodes and one million edges, our algorithm achieves lower normalized cut values in 67% of our experiments and higher ratio association values in 100% of our experiments. furthermore, on large graphs, our algorithm is significantly faster than spectral methods. finally, our algorithm requires far less memory than spectral methods; we cluster a 1.2 million node movie network into 5000 clusters, which due to memory requirements cannot be done directly with spectral methods.
a bayesian network classifier with inverse tree structure for voxelwise magnetic resonance image analysis. we propose a bayesian-network classifier with inverse-tree structure (bncit) for joint classification and variable selection. the problem domain of voxelwise magnetic-resonance image analysis often involves millions of variables but only dozens of samples. judicious variable selection may render classification tractable, avoid over-fitting, and improve classifier performance. bncit embeds the variable-selection process within the classifier-training process, which makes this algorithm scalable. bncit is based on a bayesian-network model with inverse-tree structure, i.e., the class variable c is a leaf node, and predictive variables are parents of c; thus, the classifier-training process returns a parent set for c, which is a subset of the markov blanket of c. bncit uses voxels in the parent set, and voxels that are probabilistically equivalent to them, as variables for classification of new image data. since the data set has a limited number of samples, we use the jackknife method to determine whether the classifier generated by bncit is a statistical artifact. in order to enhance stability and improve classification accuracy, we model the state of the probabilistically equivalent voxels with a latent variable. we employ an efficient method for determining states of hidden variables, thus reducing dramatically the computational cost of model generation. experimental results confirm the accuracy and efficiency of bncit.
nemofinder: dissecting genome-wide protein-protein interactions with meso-scale network motifs. recent works in network analysis have revealed the existence of network motifs in biological networks such as the protein-protein interaction (ppi) networks. however, existing motif mining algorithms are not sufficiently scalable to find meso-scale network motifs. also, there has been little or no work to systematically exploit the extracted network motifs for dissecting the vast interactomes.we describe an efficient network motif discovery algorithm, nemofinder, that can mine meso-scale network motifs that are repeated and unique in large ppi networks. using nemofinder, we successfully discovered, for the first time, up to size-12 network motifs in a large whole-genome s. cerevisiae (yeast) ppi network. we also show that such network motifs can be systematically exploited for indexing the reliability of ppi data that were generated via highly erroneous high-throughput experimental methods.
enhanced word clustering for hierarchical text classification. in this paper we propose a new information-theoretic divisive algorithm for word clustering applied to text classification. in previous work, such "distributional clustering" of features has been found to achieve improvements over feature selection in terms of classification accuracy, especially at lower number of features [2, 28]. however the existing clustering techniques are agglomerative in nature and result in (i) sub-optimal word clusters and (ii) high computational cost. in order to explicitly capture the optimality of word clusters in an information theoretic framework, we first derive a global criterion for feature clustering. we then present a fast, divisive algorithm that monotonically decreases this objective function value, thus converging to a local minimum. we show that our algorithm minimizes the "within-cluster jensen-shannon divergence" while simultaneously maximizing the "between-cluster jensen-shannon divergence". in comparison to the previously proposed agglomerative strategies our divisive algorithm achieves higher classification accuracy especially at lower number of features. we further show that feature clustering is an effective technique for building smaller class models in hierarchical classification. we present detailed experimental results using naive bayes and support vector machines on the 20 newsgroups data set and a 3-level hierarchy of html documents collected from dmoz open directory.
a new two-phase sampling based algorithm for discovering association rules. this paper introduces fast, a novel two-phase sampling-based algorithm for discovering association rules in large databases. in phase i a large initial sample of transactions is collected and used to quickly and accurately estimate the support of each individual item in the database. in phase ii these estimated supports are used to either trim "outlier" transactions or select "representative" transactions from the initial sample, thereby forming a small final sample that more accurately reflects the statistical characteristics (i.e., itemset supports) of the entire database. the expensive operation of discovering association rules is then performed on the final sample. in an empirical study, fast was able to achieve 90--95% accuracy using a final sample having a size of only 15--33% of that of a comparable random sample. this efficiency gain resulted in a speedup by roughly a factor of 10 over previous algorithms that require expensive processing of the entire database --- even efficient algorithms that exploit sampling. our new sampling technique can be used in conjunction with almost any standard association-rule algorithm, and can potentially render scalable other algorithms that mine "count" data.
information-theoretic co-clustering. two-dimensional contingency or co-occurrence tables arise frequently in important applications such as text, web-log and market-basket data analysis. a basic problem in contingency table analysis is co-clustering: simultaneous clustering of the rows and columns. a novel theoretical formulation views the contingency table as an empirical joint probability distribution of two discrete random variables and poses the co-clustering problem as an optimization problem in information theory---the optimal co-clustering maximizes the mutual information between the clustered random variables subject to constraints on the number of row and column clusters. we present an innovative co-clustering algorithm that monotonically increases the preserved mutual information by intertwining both the row and column clusterings at all stages. using the practical example of simultaneous word-document clustering, we demonstrate that our algorithm works well in practice, especially in the presence of sparsity and high-dimensionality.
failure detection and localization in component based systems by online tracking. the increasing complexity of today's systems makes fast and accurate failure detection essential for their use in mission-critical applications. various monitoring methods provide a large amount of data about system's behavior. analyzing this data with advanced statistical methods holds the promise of not only detecting the errors faster, but also detecting errors which are difficult to catch with current monitoring tools. two challenges to building such detection tools are: the high dimensionality of observation data, which makes the models expensive to apply, and frequent system changes, which make the models expensive to update. in this paper, we present algorithms to reduce the dimensionality of data in a way that makes it easy to adapt to system changes. we decompose the observation data into signal and noise subspaces. two statistics, the hotelling t2 score and squared prediction error (spe) are calculated to represent the data characteristics in signal and noise subspaces respectively. instead of tracking the original data, we use a sequentially discounting expectation maximization (sdem) algorithm to learn the distribution of the two extracted statistics. a failure event can then be detected based on the abnormal change of the distribution. applying our technique to component interaction data in a simple e-commerce application shows better accuracy than building independent profiles for each component. additionally, experiments on synthetic data show that the detection accuracy is high even for changing systems.
a spectral method to separate disconnected and nearly-disconnected web graph components. separation of connected components from a graph with disconnected graph components mostly use breadth-first search (bfs) or depth-first search (dfs) graph algorithms. here we propose a new algebraic method to separate disconnected and nearly-disconnected components. this method is based on spectral graph partitioning, following a key observation that disconnected components will show up, after properly sorted, as step-function like curve in the lowest eigenvectors of the laplacian matrix of the graph. following an perturbative analysis framework, we systematically analyzed the graph structures, first on the disconnected subgraph case, and second on the effects of adding edges sparsely connecting different subgraphs as a perturbation. several new results are derived, providing insights to spectral methods and related clustering objective function. examples are given illustrating the concepts and results our methods. comparing to the standard graph algorithms, this method has the same o(&verbar;e &verbar; + &verbar;v&verbar;log(&verbar;v&verbar;)) complexity, but is easier to implement (using readily available eigensolvers). further more the method can easily identify articulation points and bridges on nearly-disconnected graphs. segmentation of a real example of web graph for query amazon is given. we found that each disconnected or nearly-disconnected components forms a cluster on a clear topic.
orthogonal nonnegative matrix t-factorizations for clustering. currently, most research on nonnegative matrix factorization (nmf)focus on 2-factor $x=fg^t$ factorization. we provide a systematicanalysis of 3-factor $x=fsg^t$ nmf. while it unconstrained 3-factor nmf is equivalent to it unconstrained 2-factor nmf, itconstrained 3-factor nmf brings new features to it constrained 2-factor nmf. we study the orthogonality constraint because it leadsto rigorous clustering interpretation. we provide new rules for updating $f,s, g$ and prove the convergenceof these algorithms. experiments on 5 datasets and a real world casestudy are performed to show the capability of bi-orthogonal 3-factornmf on simultaneously clustering rows and columns of the input datamatrix. we provide a new approach of evaluating the quality ofclustering on words using class aggregate distribution andmulti-peak distribution. we also provide an overview of various nmf extensions andexamine their relationships.
gess: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces. the similarity join is an important operation for mining high-dimensional feature spaces. given two data sets, the similarity join computes all tuples (x, y) that are within a distance &egr;.one of the most efficient algorithms for processing similarity-joins is the multidimensional-spatial join (msj) by koudas and sevcik. in our previous work --- pursued for the two-dimensional case --- we found however that msj has several performance shortcomings in terms of cpu and i/o cost as well as memory-requirements. therefore, msj is not generally applicable to high-dimensional data.in this paper, we propose a new algorithm named generic external space sweep (gess). gess introduces a modest rate of data replication to reduce the number of expensive distance computations. we present a new cost-model for replication, an i/o model, and an inexpensive method for duplicate removal. the principal component of our algorithm is a highly flexible replication engine.our analytical model predicts a tremendous reduction of the number of expensive distance computations by several orders of magnitude in comparison to msj (factor 107). in addition, the memory requirements of gess are shown to be lower by several orders of magnitude. furthermore, the i/o cost of our algorithm is by factor 2 better (independent from the fact whether replication occurs or not). our analytical results are confirmed by a large series of simulations and experiments with synthetic and real high-dimensional data sets.
web mining from competitors' websites. this paper presents a framework for user-oriented text mining. it is then illustrated with an example of discovering knowledge from competitors' websites. the knowledge to be discovered is in the form of association rules. a user's background knowledge is represented as a concept hierarchy developed from documents on his/her own website. the concept hierarchy captures the semantic usage of words and relationships among words in background documents. association rules are identified among the noun phrases extracted from documents on competitors' websites. the interestingness measure, i.e. novelty, which measures the semantic distance between the antecedent and the consequent of a rule in the background knowledge, is computed from the co-occurrence frequency of words and the connection lengths among words in the concept hierarchy. a user evaluation of the novelty of discovered rules demonstrates that the correlation between the algorithm and the human judges is comparable to that between human judges.
incspan: incremental mining of sequential patterns in large database. many real life sequence databases grow incrementally. it is undesirable to mine sequential patterns from scratch each time when a small set of sequences grow, or when some new sequences are added into the database. incremental algorithm should be developed for sequential pattern mining so that mining can be adapted to incremental database updates. however, it is nontrivial to mine sequential patterns incrementally, especially when the existing sequences grow incrementally because such growth may lead to the generation of many new patterns due to the interactions of the growing subsequences with the original ones. in this study, we develop an efficient algorithm, incspan, for incremental mining of sequential patterns, by exploring some interesting properties. our performance study shows that incspan outperforms some previously proposed incremental algorithms as well as a non-incremental one with a wide margin.
secret: a scalable linear regression tree algorithm. developing regression models for large datasets that are both accurate and easy to interpret is a very important data mining problem. regression trees with linear models in the leaves satisfy both these requirements, but thus far, no truly scalable regression tree algorithm is known. this paper proposes a novel regression tree construction algorithm (secret) that produces trees of high quality and scales to very large datasets. at every node, secret uses the em algorithm for gaussian mixtures to find two clusters in the data and to locally transform the regression problem into a classification problem based on closeness to these clusters. goodness of split measures, like the gini gain, can then be used to determine the split variable and the split point much like in classification tree construction. scalability of the algorithm can be achieved by employing scalable versions of the em and classification tree construction algorithms. an experimental evaluation on real and artificial data shows that secret has accuracy comparable to other linear regression tree algorithms but takes orders of magnitude less computation time for large datasets.
instability of decision tree classification algorithms. the instability problem of decision tree classification algorithms is that small changes in input training samples may cause dramatically large changes in output classification rules. different rules generated from almost the same training samples are against human intuition and complicate the process of decision making. in this paper, we present fundamental theorems for the instability problem of decision tree classifiers. the first theorem gives the relationship between a data change and the resulting tree structure change (i.e. split change). the second theorem, instability theorem, provides the cause of the instability problem. based on the two theorems, algorithmic improvements can be made to lessen the instability problem. empirical results illustrate the theorem statements. the trees constructed by the proposed algorithm are more stable, noise-tolerant, informative, expressive, and concise. our proposed sensitivity measure can be used as a metric to evaluate the stability of splitting predicates. the tree sensitivity is an indicator of the confidence level in rules and the effective lifetime of rules.
mining the network value of customers. one of the major applications of data mining is in helping companies determine which potential customers to market to. if the expected profit from a customer is greater than the cost of marketing to her, the marketing action for that customer is executed. so far, work in this area has considered only the intrinsic value of the customer (i.e, the expected profit from sales to her). we propose to model also the customer's network value: the expected profit from sales to other customers she may influence to buy, the customers those may influence, and so on recursively. instead of viewing a market as a set of independent entities, we view it as a social network and model it as a markov random field. we show the advantages of this approach using a social network mined from a collaborative filtering database. marketing that exploits the network value of customers---also known as viral marketing---can be extremely effective, but is still a black art. our work can be viewed as a step towards providing a more solid foundation for it, taking advantage of the availability of large relevant databases.
an approach to spacecraft anomaly detection problem using kernel feature space. development of advanced anomaly detection and failure diagnosis technologies for spacecraft is a quite significant issue in the space industry, because the space environment is harsh, distant and uncertain. while several modern approaches based on qualitative reasoning, expert systems, and probabilistic reasoning have been developed recently for this purpose, any of them has a common difficulty in obtaining accurate and complete a priori knowledge on the space systems from human experts. a reasonable alternative to this conventional anomaly detection method is to reuse a vast amount of telemetry data which is multi-dimensional time-series continuously produced from a number of system components in the spacecraft.this paper proposes a novel "knowledge-free" anomaly detection method for spacecraft based on kernel feature space and directional distribution, which constructs a system behavior model from the past normal telemetry data from a set of telemetry data in normal operation and monitors the current system status by checking incoming data with the model.in this method, we regard anomaly phenomena as unexpected changes of causal associations in the spacecraft system, and hypothesize that the significant causal associations inside the system will appear in the form of principal component directions in a high-dimensional non-linear feature space which is constructed by a kernel function and a set of data.we have confirmed the effectiveness of the proposed anomaly detection method by applying it to the telemetry data obtained from a simulator of an orbital transfer vehicle designed to make a rendezvous maneuver with the international space station.
mining the internet: the eighth wonder of the world. the internet takes behavioral consumer research to a new level by providing the ability to passively and continuously monitor the complete online behavior of millions of consumers in an opt-in, privacy protected manner. imagine the analytical possibilities if every site visited, every page viewed, content seen, transaction conducted ..... all of this granularity in behavior --- was continuously captured with explicit consumer permission for millions of consumers and privacy was protected. what unique insights could one gain into consumers' behavior, their interests, passions and lifestyles? what behavior could be predicted? what commercial applications would be possible. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
early detection of insider trading in option markets. "inside information" comes in many forms: knowledge of a corporate takeover, a terrorist attack, unexpectedly poor earnings, the fda's acceptance of a new drug, etc. anyone who knows some piece of soon-to-break news possesses inside information. historically, insider trading has been detected after the news is public, but this is often too late: fraud has been perpetrated, innocent investors have been disadvantaged, or terrorist acts have been carried out. this paper explores early detection of insider trading - detection before the news breaks. data mining holds great promise for this emerging application, but the problem also poses significant challenges. we present the specific problem of insider trading in option markets, compare decision tree, logistic regression, and neural net results to results from an expert model, and discuss insights that knowledge discovery techniques shed upon this problem.
proximal support vector machine classifiers. instead of a standard support vector machine (svm) that classifies points by assigning them to one of two disjoint half-spaces, points are classified by assigning them to the closest of two parallel planes (in input or feature space) that are pushed apart as far as possible. this formulation, which can also be interpreted as regularized least squares and considered in the much more general context of regularized networks [8, 9], leads to an extremely fast and simple algorithm for generating a linear or nonlinear classifier that merely requires the solution of a single system of linear equations. in contrast, standard svms solve a quadratic or a linear program that require considerably longer computational time. computational results on publicly available datasets indicate that the proposed proximal svm classifier has comparable test set correctness to that of standard svm classifiers, but with considerably faster computational time that can be an order of magnitude faster. the linear proximal svm can easily handle large datasets as indicated by the classification of a 2 million point 10-attribute set in 20.8 seconds. all computational results are based on 6 lines of matlab code.
rule extraction from linear support vector machines. we describe an algorithm for converting linear support vector machines and any other arbitrary hyperplane-based linear classifiers into a set of non-overlapping rules that, unlike the original classifier, can be easily interpreted by humans. each iteration of the rule extraction algorithm is formulated as a constrained optimization problem that is computationally inexpensive to solve. we discuss various properties of the algorithm and provide proof of convergence for two different optimization criteria we demonstrate the performance and the speed of the algorithm on linear classifiers learned from real-world datasets, including a medical dataset on detection of lung cancer from medical images. the ability to convert svm's and other "black-box" classifiers into a set of human-understandable rules, is critical not only for physician acceptance, but also to reducing the regulatory barrier for medical-decision support systems based on such classifiers.
applications of sampling and fractional factorial designs to model-free data squashing. the concept of "data squashing" was introduced by dumouchel et al [4] as a method of summarizing massive data sets that preserves statistical relationships among variables. the idea is to create a smaller data set that allows statistical modeling to take place using in-memory algorithms, and to preserve the modeling results more accurately than would a same-size random sample from the massive data set. this research attempts to avoid several limitations of previous approaches to data squashing. our method avoids the curse of dimensionality by a double use of principal components transformations that makes computing time linear in the number of cases and quadratic in the number of variables. categorical and continuous variables are smoothly integrated. because the binning is based on principal components, which are uncorrelated, we can use fractional factorial designs that sample less than one point per bin. we also investigate various weighting schemes for the squashed sample to see whether matching moments or matching subregion data counts is more effective. finally, previous work required the specification of a statistical model, either to perform the squashing algorithm or to compare the worth of different squashing methods. our approach to evaluation is model free and does not even require the specification of variables as responses or predictors. instead, we develop a chi-squared like measure of accuracy to compare the closeness of various discrete densities (the squashed data sets) to the discrete massive data set.
empirical bayes screening for multi-item associations. this paper considers the framework of the so-called "market basket problem", in which a database of transactions is mined for the occurrence of unusually frequent item sets. in our case, "unusually frequent" involves estimates of the frequency of each item set divided by a baseline frequency computed as if items occurred independently. the focus is on obtaining reliable estimates of this measure of interestingness for all item sets, even item sets with relatively low frequencies. for example, in a medical database of patient histories, unusual item sets including the item "patient death" (or other serious adverse event) might hopefully be flagged with as few as 5 or 10 occurrences of the item set, it being unacceptable to require that item sets occur in as many as 0.1% of millions of patient reports before the data mining algorithm detects a signal. similar considerations apply in fraud detection applications. thus we abandon the requirement that interesting item sets must contain a relatively large fixed minimal support, and adopt a criterion based on the results of fitting an empirical bayes model to the item set counts. the model allows us to define a 95% bayesian lower confidence limit for the "interestingness" measure of every item set, whereupon the item sets can be ranked according to their empirical bayes confidence limits. for item sets of size j > 2, we also distinguish between multi-item associations that can be explained by the observed j(j-1)/2 pairwise associations, and item sets that are significantly more frequent than their pairwise associations would suggest. such item sets can uncover complex or synergistic mechanisms generating multi-item associations. this methodology has been applied within the u.s. food and drug administration (fda) to databases of adverse drug reaction reports and within at&t to customer international calling histories. we also present graphical techniques for exploring and understanding the modeling results.
efficient closed pattern mining in the presence of tough block constraints. various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemset-based constraints that better capture the underlying application requirements and characteristics. in this paper we introduce a new class of block constraints that determine the significance of an itemset pattern by considering the dense block that is formed by the pattern's items and its associated set of transactions. block constraints provide a natural framework by which a number of important problems can be specified and make it possible to solve numerous problems on binary and real-valued datasets. however, developing computationally efficient algorithms to find these block constraints poses a number of challenges as unlike the different itemset-based constraints studied earlier, these block constraints are tough as they are neither anti-monotone, monotone, nor convertible. to overcome this problem, we introduce a new class of pruning methods that significantly reduce the overall search space and present a computationally efficient and scalable algorithm called cbminer to find the closed itemsets that satisfy the block constraints.
symp: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets. we propose a new clustering algorithm, called symp, which is based on synchronization of pulse-coupled oscillators. symp represents each data point by an integrate-and-fire oscillator and uses the relative similarity between the points to model the interaction between the oscillators. symp is robust to noise and outliers, determines the number of clusters in an unsupervised manner, identifies clusters of arbitrary shapes, and can handle very large data sets. the robustness of symp is an intrinsic property of the synchronization mechanism. to determine the optimum number of clusters, symp uses a dynamic resolution parameter. to identify clusters of various shapes, symp models each cluster by multiple gaussian components. the number of components is automatically determined using a dynamic intra-cluster resolution parameter. clusters with simple shapes would be modeled by few components while clusters with more complex shapes would require a larger number of components. the scalable version of symp uses an efficient incremental approach that requires a simple pass through the data set. the proposed clustering approach is empirically evaluated with several synthetic and real data sets, and its performance is compared with cure.
data mining: are we there yet? data mining started its move out of the statistics and machine learning ghettos and into the mainstream almost 10 years ago. with great fanfare and a large influx of venture capital, data mining was going to change the very nature of business. yet data mining products have had relatively modest success in the marketplace. the reasons include limitations and misplaced emphasis in the products' features and functions, unrealistic expectations set by messages from the data mining community, and a lack of readiness by many prospective users. this session will look at where vendors have succeeded and failed with their products, what expectations users should have, and suggestions for achieving the potential of this exciting and valuable technology.
sewep: using site semantics and a taxonomy to enhance the web personalization process. web personalization is the process of customizing a web site to the needs of each specific user or set of users, taking advantage of the knowledge acquired through the analysis of the user's navigational behavior. integrating usage data with content, structure or user profile data enhances the results of the personalization process. in this paper, we present sewep, a system that makes use of both the usage logs and the semantics of a web site's content in order to personalize it. web content is semantically annotated using a conceptual hierarchy (taxonomy). we introduce c-logs, an extended form of web usage logs that encapsulates knowledge derived from the link semantics. c-logs are used as input to the web usage mining process, resulting in a broader yet semantically focused set of recommendations.
inverted matrix: efficient discovery of frequent items in large datasets in the context of interactive mining. existing association rule mining algorithms suffer from many problems when mining massive transactional datasets. one major problem is the high memory dependency: either the gigantic data structure built is assumed to fit in main memory, or the recursive mining process is too voracious in memory resources. another major impediment is the repetitive and interactive nature of any knowledge discovery process. to tune parameters, many runs of the same algorithms are necessary leading to the building of these huge data structures time and again. this paper proposes a new disk-based association rule mining algorithm called inverted matrix, which achieves its efficiency by applying three new ideas. first, transactional data is converted into a new database layout called inverted matrix that prevents multiple scanning of the database during the mining phase, in which finding frequent patterns could be achieved in less than a full scan with random access. second, for each frequent item, a relatively small independent tree is built summarizing co-occurrences. finally, a simple and non-recursive mining process reduces the memory requirements as minimum candidacy generation and counting is needed. experimental studies reveal that our inverted matrix approach outperform fp-tree especially in mining very large transactional databases with a very large number of unique items. our random access disk-based approach is particularly advantageous in a repetitive and interactive setting.
from run-time behavior to usage scenarios: an interaction-pattern mining approach. a key challenge facing it organizations today is their evolution towards adopting e-business practices that gives rise to the need for reengineering their underlying software systems. any reengineering effort has to be aware of the functional requirements of the subject system, in order not to violate the integrity of its intended uses. however, as software systems get regularly maintained throughout their lifecycle, the documentation of their requirements often become obsolete or get lost. to address this problem of "software requirements loss", we have developed an interaction-pattern mining method for the recovery of functional requirements as usage scenarios. our method analyzes traces of the run-time system-user interaction to discover frequently recurring patterns; these patterns correspond to the functionality currently exercised by the system users, represented as usage scenarios. the discovered scenarios provide the basis for reengineering the software system into web-accessible components, each one supporting one of the discovered scenarios. in this paper, we describe ipm2, our interaction-pattern discovery algorithm, we illustrate it with a case study from a real application and we give an overview of the reengineering process in the context of which it is employed.
accurate decision trees for mining high-speed data streams. in this paper we study the problem of constructing accurate decision tree models from data streams. data streams are incremental tasks that require incremental, online, and any-time learning algorithms. one of the most successful algorithms for mining data streams is vfdt. in this paper we extend the vfdt system in two directions: the ability to deal with continuous data and the use of more powerful classification techniques at tree leaves. the proposed system, vfdtc, can incorporate and classify new information online, with a single scan of the data, in time constant per example. the most relevant property of our system is the ability to obtain a performance similar to a standard decision tree algorithm even for medium size datasets. this is relevant due to the any-time property. we study the behaviour of vfdtc in different problems and demonstrate its utility in large and medium data sets. under a bias-variance analysis we observe that vfdtc in comparison to c4.5 is able to reduce the variance component.
magical thinking in data mining: lessons from coil challenge 2000. coil challenge 2000 was a supervised learning contest that attracted 43 entries. the authors of 29 entries later wrote explanations of their work. this paper discusses these reports and reaches three main conclusions. first, naive bayesian classifiers remain competitive in practice: they were used by both the winning entry and the next best entry. second, identifying feature interactions correctly is important for maximizing predictive accuracy: this was the difference between the winning classifier and all others. third and most important, too many researchers and practitioners in data mining do not appreciate properly the issue of statistical significance and the danger of overfitting. given a dataset such as the one for the coil contest, it is pointless to apply a very complicated learning algorithm, or to perform a very time-consuming model search. in either ease, one is likely to overfit the training data and to fool oneself in estimating predictive accuracy and in discovering useful correlations.
discovering significant opsm subspace clusters in massive gene expression data. order-preserving submatrixes (opsms) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of conditions. in an opsm, the expression levels of all genes induce the same linear ordering of the conditions. opsm mining is reducible to a special case of the sequential pattern mining problem, in which a pattern and its supporting sequences uniquely specify an opsm cluster. those small twig clusters, specified by long patterns with naturally low support, incur explosive computational costs and would be completely pruned off by most existing methods for massive datasets containing thousands of conditions and hundreds of thousands of genes, which are common in today's gene expression analysis. however, it is in particular interest of biologists to reveal such small groups of genes that are tightly coregulated under many conditions, and some pathways or processes might require only two genes to act in concert. in this paper, we introduce the kiwi mining framework for massive datasets, that exploits two parameters k and w to provide a biased testing on a bounded number of candidates, substantially reducing the search space and problem scale, targeting on highly promising seeds that lead to significant clusters and twig clusters. extensive biological and computational evaluations on real datasets demonstrate that kiwi can effectively mine biologically meaningful opsm subspace clusters with good efficiency and scalability.
consistent bipartite graph co-partitioning for star-structured high-order heterogeneous data co-clustering. heterogeneous data co-clustering has attracted more and more attention in recent years due to its high impact on various applications. while the co-clustering algorithms for two types of heterogeneous data (denoted by pair-wise co-clustering), such as documents and terms, have been well studied in the literature, the work on more types of heterogeneous data (denoted by high-order co-clustering) is still very limited. as an attempt in this direction, in this paper, we worked on a specific case of high-order co-clustering in which there is a central type of objects that connects the other types so as to form a star structure of the inter-relationships. actually, this case could be a very good abstract for many real-world applications, such as the co-clustering of categories, documents and terms in text mining. in our philosophy, we treated such kind of problems as the fusion of multiple pair-wise co-clustering sub-problems with the constraint of the star structure. accordingly, we proposed the concept of consistent bipartite graph co-partitioning, and developed an algorithm based on semi-definite programming (sdp) for efficient computation of the clustering results. experiments on toy problems and real data both verified the effectiveness of our proposed method.
data mining with sparse grids using simplicial basis functions. recently we presented a new approach [18] to the classification problem arising in data mining. it is based on the regularization network approach but, in contrast to other methods which employ ansatz functions associated to data points, we use a grid in the usually high-dimensional feature space for the minimization process. to cope with the curse of dimensionality, we employ sparse grids [49]. thus, only o(hn-1nd-1) instead of o(hn-d) grid points and unknowns are involved. here d denotes the dimension of the feature space and hn = 2-n gives the mesh size. we use the sparse grid combination technique [28] where the classification problem is discretized and solved on a sequence of conventional grids with uniform mesh sizes in each dimension. the sparse grid solution is then obtained by linear combination. in contrast to our former work, where d-linear functions were used, we now apply linear basis functions based on a simplicial discretization. this allows to handle more dimensions and the algorithm needs less operations per data point.we describe the sparse grid combination technique for the classification problem, give implementational details and discuss the complexity of the algorithm. it turns out that the method scales linearly with the number of given data points. finally we report on the quality of the classifier built by our new method on data sets with up to 10 dimensions. it turns out that our new method achieves correctness rates which are competitive to that of the best existing methods.
a microeconomic data mining problem: customer-oriented catalog segmentation. the microeconomic framework for data mining [7] assumes that an enterprise chooses a decision maximizing the overall utility over all customers where the contribution of a customer is a function of the data available on that customer. in catalog segmentation, the enterprise wants to design k product catalogs of size r that maximize the overall number of catalog products purchased. however, there are many applications where a customer, once attracted to an enterprise, would purchase more products beyond the ones contained in the catalog. therefore, in this paper, we investigate an alternative problem formulation, that we call customer-oriented catalog segmentation, where the overall utility is measured by the number of customers that have at least a specified minimum interest t in the catalogs. we formally introduce the customer-oriented catalog segmentation problem and discuss its complexity. then we investigate two different paradigms to design efficient, approximate algorithms for the customer-oriented catalog segmentation problem, greedy (deterministic) and randomized algorithms. since greedy algorithms may be trapped in a local optimum and randomized algorithms crucially depend on a reasonable initial solution, we explore a combination of these two paradigms. our experimental evaluation on synthetic and real data demonstrates that the new algorithms yield catalogs of significantly higher utility compared to classical catalog segmentation algorithms.
web site mining: a new way to spot competitors, customers and suppliers in the world wide web. when automatically extracting information from the world wide web, most established methods focus on spotting single html-documents. however, the problem of spotting complete web sites is not handled adequately yet, in spite of its importance for various applications. therefore, this paper discusses the classification of complete web sites. first, we point out the main differences to page classification by discussing a very intuitive approach and its weaknesses. this approach treats a web site as one large html-document and applies the well-known methods for page classification. next, we show how accuracy can be improved by employing a preprocessing step which assigns an occurring web page to its most likely topic. the determined topics now represent the information the web site contains and can be used to classify it more accurately. we accomplish this by following two directions. first, we apply well established classification algorithms to a feature space of occurring topics. the second direction treats a site as a tree of occurring topics and uses a markov tree model for further classification. to improve the efficiency of this approach, we additionally introduce a powerful pruning method reducing the number of considered web pages. our experiments show the superiority of the markov tree approach regarding classification accuracy. in particular, we demonstrate that the use of our pruning method not only reduces the processing time, but also improves the classification accuracy.
a component-based framework for knowledge discovery in bioinformatics. motivation: in the field of bioinformatics there is an emerging need to integrate all knowledge discovery steps into a standardized modular framework. indeed, component-based development can significantly enhance reusability and productivity for short timeline projects with a small team. we present interactive knowledge discovery and data mining (ikdd), an application framework written in java that was specifically designed for these purposes.results: ikdd consists of a component-based architecture and a web-based tool for pre-clinical research and prototype development. the platform provides an intuitive and consistent interface to create and maintain components, e.g., data structures, algorithms and utilities to load, save and visualize data and pipelines. the rich-featured tool supplies database connectivity, workflow processing and rapid prototype building. the architecture was carefully designed using an object-oriented approach that respects crucial goals: usability, openness, robustness and functionality, especially in the abstraction and description of the components, which distinguishes it from other packages. ikdd is well-suited to serve as a public repository of components, to run scientific experiments with a high-level of reproducibility, and also to rapidly build prototypes. this paper describes the general architecture, and demonstrates through examples the ease by which a complex scenario implementation can be facilitated with ikdd.
price prediction and insurance for online auctions. online auctions are generating a new class of fine-grained data about online transactions. this data lends itself to a variety of applications and services that can be provided to both buyers and sellers in online marketplaces. we collect data from online auctions and use several classification algorithms to predict the probable-end prices of online auction items. this paper describes the feature extraction and selection process, and several machine learning formulations of the price prediction problem. as a prototype application, we developed auction price insurance that uses the predicted end-price to offer price insurance to sellers in online auctions. we define price insurance as a service that offers insurance to auction sellers that guarantees a price for their goods, for an appropriate premium. if the item sells for less than the insured price, the seller is reimbursed for the difference. we show that our price prediction techniques are accurate enough to offer price insurance as a profitable business. while this paper deals specifically with online auctions, we believe that this is an interesting case study that applies to dynamic markets where the price of the goods is variable and is affected by both internal and external factors that change over time.
to buy or not to buy: mining airfare data to minimize ticket purchase price. as product prices become increasingly available on the world wide web, consumers attempt to understand how corporations vary these prices over time. however, corporations change prices based on proprietary algorithms and hidden variables (e.g., the number of unsold seats on a flight). is it possible to develop data mining techniques that will enable consumers to predict price changes under these conditions?this paper reports on a pilot study in the domain of airline ticket prices where we recorded over 12,000 price observations over a 41 day period. when trained on this data, hamlet --- our multi-strategy data mining algorithm --- generated a predictive model that saved 341 simulated passengers $198,074 by advising them when to buy and when to postpone ticket purchases. remarkably, a clairvoyant algorithm with complete knowledge of future prices could save at most $320,572 in our simulation, thus hamlet's savings were 61.8% of optimal. the algorithm's savings of $198,074 represents an average savings of 23.8% for the 341 passengers for whom savings are possible. overall, hamlet saved 4.4% of the ticket price averaged over the entire set of 4,488 simulated passengers. our pilot study suggests that mining of price data available over the web has the potential to save consumers substantial sums of money per annum.
funnel report mining for the msn network. data mining research has long concentrated on the five main areas: clustering, association discovery, classification, forecasting and sequential patterns. web data mining projects are concerned mainly with text mining, user segmentation, forecasting web usage and analyzing users' clickstream patterns. we present a new type of web usage mining called funnel analysis or funnel report mining. a funnel report is a study of the retention behavior among a series of pages or sites. for example, of all hits on the home page of www.msn.com, what percentages of those are followed by hits to moneycentral.msn.com? what percentage of www.msn.com hits are followed by moneycentral.msn.com, and then www.msnbc.com? what are the most interesting funnels starting with www.msn.com? where does the greatest drop off rate occur after a user has hit msnbc? funnel reports are extremely useful in e-business because they give product planners an idea of how usable and well-structured their site is. from our experience performing web usage mining for the msn network of sites, funnel reports are requested even more than user segmentation analyses, site affiliation studies and classification exercises. in this paper, we define a framework for funnel analysis and provide a tree-based solution we have been using successfully to extract all relevant funnels using only one scan of the data file.
online novelty detection on temporal sequences. in this paper, we present a new framework for online novelty detection on temporal sequences. this framework include a mechanism for associating each detection result with a confidence value. based on this framework, we develop a concrete online detection algorithm, by modeling the temporal sequence using an online support vector regression algorithm. experiments on both synthetic and real world data are performed to demonstrate the promising performance of our proposed detection algorithm.
privacy preserving mining of association rules. we present a framework for mining association rules from transactions consisting of categorical items where the data has been randomized to preserve privacy of individual transactions. while it is feasible to recover association rules and preserve privacy using a straightforward "uniform" randomization, the discovered rules can unfortunately be exploited to find privacy breaches. we analyze the nature of privacy breaches and propose a class of randomization operators that are much more effective than uniform randomization in limiting the breaches. we derive formulae for an unbiased support estimator and its variance, which allow us to recover itemset supports from randomized datasets, and show how to incorporate these formulae into mining algorithms. finally, we present experimental results that validate the algorithm by applying it on real datasets.
k-ttp: a new privacy model for large-scale distributed environments. secure multiparty computation allows parties to jointly compute a function of their private inputs without revealing anything but the output. theoretical results [2] provide a general construction of such protocols for any function. protocols obtained in this way are, however, inefficient, and thus, practically speaking, useless when a large number of participants are involved.the contribution of this paper is to define a new privacy model -- k-privacy -- by means of an innovative, yet natural generalization of the accepted trusted third party model. this allows implementing cryptographically secure efficient primitives for real-world large-scale distributed systems.as an example for the usefulness of the proposed model, we employ k-privacy to introduce a technique for obtaining knowledge -- by way of an association-rule mining algorithm -- from large-scale data grids, while ensuring that the privacy is cryptographically secure.
regularized multi--task learning. past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks independently. in this paper we present an approach to multi--task learning based on the minimization of regularization functionals similar to existing ones, such as the one for support vector machines (svms), that have been successfully used in the past for single--task learning. our approach allows to model the relation between tasks in terms of a novel kernel function that uses a task--coupling parameter. we implement an instance of the proposed approach similar to svms and test it empirically using simulated as well as real data. the experimental results show that the proposed method performs better than existing multi--task learning methods and largely outperforms single--task learning using svms.
dimension induced clustering. it is commonly assumed that high-dimensional datasets contain points most of which are located in low-dimensional manifolds. detection of low-dimensional clusters is an extremely useful task for performing operations such as clustering and classification, however, it is a challenging computational problem. in this paper we study the problem of finding subsets of points with low intrinsic dimensionality. our main contribution is to extend the definition of fractal correlation dimension, which measures average volume growth rate, in order to estimate the intrinsic dimensionality of the data in local neighborhoods. we provide a careful analysis of several key examples in order to demonstrate the properties of our measure. based on our proposed measure, we introduce a novel approach to discover clusters with low dimensionality. the resulting algorithms extend previous density based measures, which have been successfully used for clustering. we demonstrate the effectiveness of our algorithms for discovering low-dimensional m-flats embedded in high dimensional spaces, and for detecting low-rank sub-matrices.
fragments of order. high-dimensional collections of 0--1 data occur in many applications. the attributes in such data sets are typically considered to be unordered. however, in many cases there is a natural total or partial order &pr; underlying the variables of the data set. examples of variables for which such orders exist include terms in documents, courses in enrollment data, and paleontological sites in fossil data collections. the observations in such applications are flat, unordered sets; however, the data sets respect the underlying ordering of the variables. by this we mean that if a &pr; b &pr; c are three variables respecting the underlying ordering &pr;, and both of variables a and c appear in an observation, then, up to noise levels, variable b also appears in this observation. similarly, if a1 &pr; a2 &pr; &hellip; &pr; al-1 &pr; ai is a longer sequence of variables, we do not expect to see many observations for which there are indices i < j < k such that ai and ak occur in the observation but aj does not.in this paper we study the problem of discovering fragments of orders of variables implicit in collections of unordered observations. we define measures that capture how well a given order agrees with the observed data. we describe a simple and efficient algorithm for finding all the fragments that satisfy certain conditions. we also discuss the sometimes necessary postprocessing for selecting only the best fragments of order. also, we relate our method with a sequencing approach that uses a spectral algorithm, and with the consecutive ones problem. we present experimental results on some real data sets (author lists of database papers, exam results data, and paleontological data).
assessing data mining results via swap randomization. the problem of assessing the significance of data mining results on high-dimensional 0--1 datasets has been studied extensively in the literature. for problems such as mining frequent sets and finding correlations, significance testing can be done by standard statistical tests such as chi-square, or other methods. however, the results of such tests depend only on the specific attributes and not on the dataset as a whole. moreover, the tests are difficult to apply to sets of patterns or other complex results of data mining algorithms. in this article, we consider a simple randomization technique that deals with this shortcoming. the approach consists of producing random datasets that have the same row and column margins as the given dataset, computing the results of interest on the randomized instances and comparing them to the results on the actual data. this randomization technique can be used to assess the results of many different types of data mining algorithms, such as frequent sets, clustering, and spectral analysis. to generate random datasets with given margins, we use variations of a markov chain approach which is based on a simple swap operation. we give theoretical results on the efficiency of different randomization methods, and apply the swap randomization method to several well-known datasets. our results indicate that for some datasets the structure discovered by the data mining algorithms is expected, given the row and column margins of the datasets, while for other datasets the discovered structure conveys information that is not captured by the margin counts.
fast discovery of connection subgraphs. we define a connection subgraph as a small subgraph of a large graph that best captures the relationship between two nodes. the primary motivation for this work is to provide a paradigm for exploration and knowledge discovery in large social networks graphs. we present a formal definition of this problem, and an ideal solution based on electricity analogues. we then show how to accelerate the computations, to produce approximate, but high-quality connection subgraphs in real time on very large (disk resident) graphs.we describe our operational prototype, and we demonstrate results on a social network graph derived from the world wide web. our graph contains 15 million nodes and 96 million edges, and our system still produces quality responses within seconds.
algorithms for discovering bucket orders from data. ordering and ranking items of different types are important tasks in various applications, such as query processing and scientific data mining. a total order for the items can be misleading, since there are groups of items that have practically equal ranks.we consider bucket orders, i.e., total orders with ties. they can be used to capture the essential order information without overfitting the data: they form a useful concept class between total orders and arbitrary partial orders. we address the question of finding a bucket order for a set of items, given pairwise precedence information between the items. we also discuss methods for computing the pairwise precedence data.we describe simple and efficient algorithms for finding good bucket orders. several of the algorithms have a provable approximation guarantee, and they scale well to large datasets. we provide experimental results on artificial and a real data that show the usefulness of bucket orders and demonstrate the accuracy and efficiency of the algorithms.
reverse testing: an efficient framework to select amongst classifiers under sample selection bias. one of the most important assumptions made by many classification algorithms is that the training and test sets are drawn from the same distribution, i.e., the so-called "stationary distribution assumption" that the future and the past data sets are identical from a probabilistic standpoint. in many domains of real-world applications, such as marketing solicitation, fraud detection, drug testing, loan approval, sub-population surveys, school enrollment among others, this is rarely the case. this is because the only labeled sample available for training is biased in different ways due to a variety of practical reasons and limitations. in these circumstances, traditional methods to evaluate the expected generalization error of classification algorithms, such as structural risk minimization, ten-fold cross-validation, and leave-one-out validation, usually return poor estimates of which classification algorithm, when trained on biased dataset, will be the most accurate for future unbiased dataset, among a number of competing candidates. sometimes, the estimated order of the learning algorithms' accuracy could be so poor that it is not even better than random guessing. therefore,a method to determine the most accurate learner is needed for data mining under sample selection bias for many real-world applications. we present such an approach that can determine which learner will perform the best on an unbiased test set, given a possibly biased training set, in a fraction of the computational cost to use cross-validation based approaches.
deriving marketing intelligence from online discussion. weblogs and message boards provide online forums for discussion that record the voice of the public. woven into this mass of discussion is a wide range of opinion and commentary about consumer products. this presents an opportunity for companies to understand and respond to the consumer by analyzing this unsolicited feedback. given the volume, format and content of the data, the appropriate approach to understand this data is to use large-scale web and text data mining technologies.this paper argues that applications for mining large volumes of textual data for marketing intelligence should provide two key elements: a suite of powerful mining and visualization technologies and an interactive analysis environment which allows for rapid generation and testing of hypotheses. this paper presents such a system that gathers and annotates online discussion relating to consumer products using a wide variety of state-of-the-art techniques, including crawling, wrapping, search, text classification and computational linguistics. marketing intelligence is derived through an interactive analysis framework uniquely configured to leverage the connectivity and content of annotated online discussion.
mining images on semantics via statistical learning. in this paper, we have proposed a novel framework to enable hierarchical image classification via statistical learning. by integrating the concept hierarchy for semantic image concept organization, a hierarchical mixture model is proposed to enable multi-level modeling of semantic image concepts and hierarchical classifier combination. thus, learning the classifiers for the semantic image concepts at the high level of the concept hierarchy can be effectively achieved by detecting the presences of the relevant base-level atomic image concepts. to effectively learn the base-level classifiers for the atomic image concepts at the first level of the concept hierarchy, we have proposed a novel adaptive em algorithm to achieve more effective model selection and parameter estimation. in addition, a novel penalty term is proposed to effectively eliminate the misleading effects of the outlying unlabeled images on semi-supervised classifier training. our experimental results in a specific image domain of outdoor photos are very attractive.
a general framework for accurate and fast regression by data summarization in random decision trees. predicting the values of continuous variable as a function of several independent variables is one of the most important problems for data mining. a very large number of regression methods, both parametric and nonparametric, have been proposed in the past. however, since the list is quite extensive and many of these models make rather explicit, strong yet different assumptions about the type of applicable problems and involve a lot of parameters and options, choosing the appropriate regression methodology and then specifying the parameter values is a none-trivial, sometimes frustrating, task for data mining practitioners. choosing the inappropriate methodology can have rather disappointing results. this issue is against the general utility of data mining software. for example,linear regression methods are straightforward and well-understood. however, since the linear assumption is very strong, its performance is compromised for complicated non-linear problems. kernel-based methods perform quite well if the kernel functions are selected correctly. in this paper, we propose a straightforward approach based on summarizing the training data using an ensemble of random decisions trees. it requires very little knowledge from the user, yet is applicable to every type of regression problem that we are currently aware of. we have experimented on a wide range of problems including those that parametric methods performwell, a large selection of benchmark datasets for nonparametric regression, as well as highly non-linear stochastic problems. our results are either significantly better than or identical to many approaches that are known to perform well on these problems.
scaling multi-class support vector machines using inter-class confusion. support vector machines (svms) excel at two-class discriminative learning problems. they often outperform generative classifiers, especially those that use inaccurate generative models, such as the na&iuml;ve bayes (nb) classifier. on the other hand, generative classifiers have no trouble in handling an arbitrary number of classes efficiently, and nb classifiers train much faster than svms owing to their extreme simplicity. in contrast, svms handle multi-class problems by learning redundant yes/no (one-vs-others) classifiers for each class, further worsening the performance gap. we propose a new technique for multi-way classification which exploits the accuracy of svms and the speed of nb classifiers. we first use a nb classifier to quickly compute a confusion matrix, which is used to reduce the number and complexity of the two-class svms that are built in the second stage. during testing, we first get the prediction of a nb classifier and use that to selectively apply only a subset of the two-class svms. on standard benchmarks, our algorithm is 3 to 6 times faster than svms and yet matches or even exceeds their accuracy.
mining tree queries in a graph. we present an algorithm for mining tree-shaped patterns in a large graph. novel about our class of patterns is that they can contain constants, and can contain existential nodes which are not counted when determining the number of occurrences of the pattern in the graph. our algorithm has a number of provable optimality properties, which are based on the theory of conjunctive database queries. we propose a database-oriented implementation in sql, and report upon some initial experimental results obtained with our implementation on graph data about food webs, about protein interactions, and about citation analysis.
tumor cell identification using features rules. advances in imaging techniques have led to large repositories of images. there is an increasing demand for automated systems that can analyze complex medical images and extract meaningful information for mining patterns. here, we describe a real-life image mining application to the problem of tumour cell counting. the quantitative analysis of tumour cells is fundamental to characterizing the activity of tumour cells. existing approaches are mostly manual, time-consuming and subjective. efforts to automate the process of cell counting have largely focused on using image processing techniques only. our studies indicate that image processing alone is unable to give accurate results. in this paper, we examine the use of extracted features rules to aid in the process of tumor cell counting. we propose a robust local adaptive thresholding and dynamic water immersion algorithms to segment regions of interesting from background. meaningful features are then extracted from the segmented regions. a number of base classifiers are built to generate features rules to help identify the tumor cell. two voting strategies are implemented to combine the base classifiers into a meta-classifier. experiment results indicate that this process of using extracted features rules to help identify tumor cell leads to better accuracy than pure image processing techniques alone.
creating social networks to improve peer-to-peer networking. we use knowledge discovery techniques to guide the creation of efficient overlay networks for peer-to-peer file sharing. an overlay network specifies the logical connections among peers in a network and is distinct from the physical connections of the network. it determines the order in which peers will be queried when a user is searching for a specific file. to better understand the role of the network overlay structure in the performance of peer-to-peer file sharing protocols, we compare several methods for creating overlay networks. we analyze the networks using data from a campus network for peer-to-peer file sharing that recorded anonymized data on 6,528 users sharing 291,925 music files over an 81-day period. we propose a novel protocol for overlay creation based on a model of user preference identified by latent-variable clustering with hierarchical dirichlet processes (hdps). our simulations and empirical studies show that the clusters of songs created by hdps effectively model user behavior and can be used to create desirable network overlays that outperform alternative approaches.
non-redundant clustering with conditional ensembles. data may often contain multiple plausible clusterings. in order to discover a clustering which is useful to the user, constrained clustering techniques have been proposed to guide the search. typically, these techniques assume background knowledge in the form of explicit information about the desired clustering. in contrast, we consider the setting in which the background knowledge is instead about an undesired clustering. such knowledge may be obtained from an existing classification or precedent algorithm. the problem is then to find a novel, "orthogonal" clustering in the data. we present a general algorithmic framework which makes use of cluster ensemble methods to solve this problem. one key advantage of this approach is that it takes a base clustering method which is used as a black box, allowing the practitioner to select the most appropriate clustering method for the domain. we present experimental results on synthetic and text data which establish the competitiveness of this framework.
the predictive power of online chatter. an increasing fraction of the global discourse is migrating online in the form of blogs, bulletin boards, web pages, wikis, editorials, and a dizzying array of new collaborative technologies. the migration has now proceeded to the point that topics reflecting certain individual products are sufficiently popular to allow targeted online tracking of the ebb and flow of chatter around these topics. based on an analysis of around half a million sales rank values for 2,340 books over a period of four months, and correlating postings in blogs, media, and web pages, we are able to draw several interesting conclusions.first, carefully hand-crafted queries produce matching postings whose volume predicts sales ranks. second, these queries can be automatically generated in many cases. and third, even though sales rank motion might be difficult to predict in general, algorithmic predictors can use online postings to successfully predict spikes in sales rank.
correlating synchronous and asynchronous data streams. in a variety of modern mining applications, data are commonly viewed as infinite time ordered data streams rather as finite data sets stored on disk. this view challenges fundamental assumptions commonly made in the context of several data mining algorithms.in this paper, we study the problem of identifying correlations between multiple data streams. in particular, we propose algorithms capable of capturing correlations between multiple continuous data streams in a highly efficient and accurate manner. our algorithms and techniques are applicable in the case of both synchronous and asynchronous data streaming environments. we capture correlations between multiple streams using the well known technique of singular value decomposition (svd). correlations between data items, and the svd technique in particular, have been repeatedly utilized in an off-line (non stream) data mining problems, for example forecasting, approximate query answering, and data reduction.we propose a methodology based on a combination of dimensionality reduction and sampling to make the svd technique suitable for a data stream context. our techniques are approximate, trading accuracy with performance, and we analytically quantify this tradeoff. we present a through experimental evaluation, using both real and synthetic data sets, from a prototype implementation of our technique, investigating the impact of various parameters in the accuracy of the overall computation. our results indicate, that correlations between multiple data streams can be identified very efficiently and accurately. the algorithms proposed herein, are presented as generic tools, with a multitude of applications on data stream mining problems.
wavelet synopsis for data streams: minimizing non-euclidean error. we consider the wavelet synopsis construction problem for data streams where given n numbers we wish to estimate the data by constructing a synopsis, whose size, say b is much smaller than n. the b numbers are chosen to minimize a suitable error between the original data and the estimate derived from the synopsis.several good one-pass wavelet construction streaming algorithms minimizing the l2 error exist. for other error measures, the problem is less understood. we provide the first one-pass small space streaming algorithms with provable error guarantees (additive approximation) for minimizing a variety of non-euclidean error measures including all weighted lp (including l∞) and relative error lp metrics.in several previous works solutions (for weighted l2, l∞ and maximum relative error) where the b synopsis coefficients are restricted to be wavelet coefficients of the data were proposed. this restriction yields suboptimal solutions on even fairly simple examples. other lines of research, such as probabilistic synopsis, imposed restrictions on how the synopsis was arrived at. to the best of our knowledge this paper is the first paper to address the general problem, without any restriction on how the synopsis is arrived at, as well as provide the first streaming algorithms with guaranteed performance for these classes of error measures.
unweaving a web of documents. we develop an algorithmic framework to decompose a collection of time-stamped text documents into semantically coherent threads. our formulation leads to a graph decomposition problem on directed acyclic graphs, for which we obtain three algorithms --- an exact algorithm that is based on minimum cost flow and two more efficient algorithms based on maximum matching and dynamic programming that solve specific versions of the graph decomposition problem. applications of our algorithms include superior summarization of news search results, improved browsing paradigms for large collections of text-intensive corpora, and integration of time-stamped documents from a variety of sources. experimental results based on over 250,000 news articles from a major newspaper over a period of four years demonstrate that our algorithms efficiently identify robust threads of varying lengths and time-spans.
mining relational data through correlation-based multiple view validation. commercial relational databases currently store vast amounts of real-world data. the data within these relational repositories are represented by multiple relations, which are inter-connected by means of foreign key joins. the mining of such interrelated data poses a major challenge to the data mining community. unfortunately, traditional data mining algorithms usually only explore one relation, the so-called target relation, thus excluding crucial knowledge embedded in the related so-called background relations. in this paper, we propose a novel approach for classifying relational such domains. this strategy employs multiple views to capture crucial information not only from the target relation, but also from related relations. this information is integrated into the relational mining process. the framework presented here, firstly, explore the relational domain to partition its features space into multiple subsets. subsequently, these subsets are used to construct multiple uncorrelated views, based on a novel correlation-based view validation method, against the target concept. finally, the knowledge possessed by multiple views are incorporated into a meta-learning mechanism to augment one another. based on this framework, a wide range of conventional data mining methods can be applied to mine relational databases. our experiments on benchmark real-world data sets show that the proposed method achieves promising results both in terms of overall accuracy obtained and run time, when compared with two other relational data mining approaches.
quantifying trends accurately despite classifier error and class imbalance. this paper promotes a new task for supervised machine learning research: quantification - the pursuit of learning methods for accurately estimating the class distribution of a test set, with no concern for predictions on individual cases. a variant for cost quantification addresses the need to total up costs according to categories predicted by imperfect classifiers. these tasks cover a large and important family of applications that measure trends over time.the paper establishes a research methodology, and uses it to evaluate several proposed methods that involve selecting the classification threshold in a way that would spoil the accuracy of individual classifications. in empirical tests, median sweep methods show outstanding ability to estimate the class distribution, despite wide disparity in testing and training conditions. the paper addresses shifting class priors and costs, but not concept drift in general.
finding similar files in large document repositories. hewlett-packard has many millions of technical support documents in a variety of collections. as part of content management, such collections are periodically merged and groomed. in the process, it becomes important to identify and weed out support documents that are largely duplicates of newer versions. doing so improves the quality of the collection, eliminates chaff from search results, and improves customer satisfaction.the technical challenge is that through workflow and human processes, the knowledge of which documents are related is often lost. we required a method that could identify similar documents based on their content alone, without relying on metadata, which may be corrupt or missing.we present an approach for finding similar files that scales up to large document repositories. it is based on chunking the byte stream to find unique signatures that may be shared in multiple files. an analysis of the file-chunk graph yields clusters of related files. an optional bipartite graph partitioning algorithm can be applied to greatly increase scalability.
pragmatic text mining: minimizing human effort to quantify many issues in call logs. we discuss our experiences in analyzing customer-support issues from the unstructured free-text fields of technical-support call logs. the identification of frequent issues and their accurate quantification is essential in order to track aggregate costs broken down by issue type, to appropriately target engineering resources, and to provide the best diagnosis, support and documentation for most common issues. we present a new set of techniques for doing this efficiently on an industrial scale, without requiring manual coding of calls in the call center. our approach involves (1) a new text clustering method to identify common and emerging issues; (2) a method to rapidly train large numbers of categorizers in a practical, interactive manner; and (3) a method to accurately quantify categories, even in the face of inaccurate classifications and training sets that necessarily cannot match the class distribution of each new month's data. we present our methodology and a tool we developed and deployed that uses these methods for tracking ongoing support issues and discovering emerging issues at hp.
farming the web for systematic business intelligence (invited talk, abstract only). the technologies of data warehousing, data mining, hypertext analysis, information visualization, and web information resources are rapidly converging. the challenge is to architect these technologies into a system for systematic business intelligence for a corporation. we need to move from an information refining process that is often haphazard and narrow to one that is reliable and continuous. web farming is a new area that suggests a methodology and architecture for accomplishing this.
experiments with random projections for machine learning. dimensionality reduction via random projections has attracted considerable attention in recent years. the approach has interesting theoretical underpinnings and offers computational advantages. in this paper we report a number of experiments to evaluate random projections in the context of inductive supervised learning. in particular, we compare random projections and pca on a number of different datasets and using different machine learning methods. while we find that the random projection approach predictively underperforms pca, its computational advantages may make it attractive for certain applications.
integrating feature and instance selection for text classification. instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. feature selection aims at the reduction of redundant features in a dataset whereas instance selection aims at the reduction of the number of instances. so far, these two methods have mostly been considered in isolation. in this paper, we present a new algorithm, which we call fis (feature and instance selection) that targets both problems simultaneously in the context of text classificationour experiments on the reuters and 20-newsgroups datasets show that fis considerably reduces both the number of features and the number of instances. the accuracy of a range of classifiers including na&iuml;ve bayes, tan and lb considerably improves when using the fis preprocessed datasets, matching and exceeding that of support vector machines, which is currently considered to be one of the best text classification methods. in all cases the results are much better compared to mutual information based feature selection. the training and classification speed of all classifiers is also greatly improved.
empirical bayesian data mining for discovering patterns in post-marketing drug safety. because of practical limits in characterizing the safety profiles of therapeutic products prior to marketing, manufacturers and regulatory agencies perform post-marketing surveillance based on the collection of adverse reaction reports ("pharmacovigilance").the resulting databases, while rich in real-world information, are notoriously difficult to analyze using traditional techniques. each report may involve multiple medicines, symptoms, and demographic factors, and there is no easily linked information on drug exposure in the reporting population. kdd techniques, such as association finding, are well-matched to the problem, but are difficult for medical staff to apply and interpret.to deploy kdd effectively for pharmacovigilance, lincoln technologies and glaxosmithkline collaborated to create a webbased safety data mining web environment. the analytical core is a high-performance implementation of the mgps (multi-item gamma poisson shrinker) algorithm described previously by dumouchel and pregibon, with several significant extensions and enhancements. the environment offers an interface for specifying data mining runs, a batch execution facility, tabular and graphical methods for exploring associations, and drilldown to case details. substantial work was involved in preparing the raw adverse event data for mining, including harmonization of drug names and removal of duplicate reports.the environment can be used to explore both drug-event and multi-way associations (interactions, syndromes). it has been used to study age/gender effects, to predict the safety profiles of proposed combination drugs, and to separate contributions of individual drugs to safety problems in polytherapy situations.
mining from open answers in questionnaire data. surveys are an important part of marketing and customer relationship management, and open answers (i.e., answers to open questions) in particular may contain valuable information and provide an important basis for making business decisions. we have developed a text mining system that provides a new way for analyzing open answers in questionnaire data. the product is able to perform the following two functions: (a) accurate extraction of characteristics for individual analysis targets, (b) accurate extraction of the relationships among characteristics of analysis targets. in this paper, we describe the working of our text mining system. it employs two statistical learning techniques: rule analysis and correspondence analysis for performing the two functions. our text mining system has already been put into use by a number of large corporations in japan in the performance of text mining on various types of survey data, including open answers about brand images, open answers about company images, complaints about products, comments written on home pages, business reports, and help desk records. in this it has been found to be useful in forming a basis for effective business decisions.
clustering spatial data using random walks. discovering significant patterns that exist implicitly in huge spatial databases is an important computational task. a common approach to this problem is to use cluster analysis. we propose a novel approach to clustering, based on the deterministic analysis of random walks on a weighted graph generated from the data. our approach can decompose the data into arbitrarily shaped clusters of different sizes and densities, overcoming noise and outliers that may blur the natural decomposition of the data. the method requires only o(n log n) time, and one of its variants needs only constant space.
user-centered design for kdd. during initial development, kdd solutions often focus heavily on algorithms, architectures, software, hardware, and systems engineering challenges, without first thoroughly exploring how end-users will employ the new kdd technology. as a result of such "system-centered" design, many useless features are implemented that prolong development and significantly add to life cycle cost, while making the system hard to operate and use. this presentation will describe an alternate "user-centered" approach -- borrowed from the consumer products industry -- that can produce kdd solutions with shorter development cycles, lower costs, and much better usability.
a new efficient probabilistic model for mining labeled ordered trees. mining frequent patterns is a general and important issue in data mining. complex and unstructured (or semi-structured) datasets have appeared in major data mining applications, including text mining, web mining and bioinformatics. mining patterns from these datasets is the focus of many of the current data mining approaches. we focus on labeled ordered trees, typical datasets of semi-structured data in data mining, and propose a new probabilistic model and its efficient learning scheme for mining labeled ordered trees. the proposed approach significantly improves the time and space complexity of an existing probabilistic modeling for labeled ordered trees, while maintaining its expressive power. we evaluated the performance of the proposed model, comparing it with that of the existing model, using synthetic as well as real datasets from the field of glycobiology. experimental results showed that the proposed model drastically reduced the computation time of the competing model, keeping the predictive power and avoiding overfitting to the training data. finally, we assessed our results using the proposed model on real data from a variety of biological viewpoints, verifying known facts in glycobiology.
discriminant adaptive nearest neighbor classification. nearest neighbor classification expects the class conditional probabilities to be locally constant, and suffers from bias in high dimensions. we propose a locally adaptive form of nearest neighbor classification to try to ameliorate this curse of dimensionality. we use a local linear discriminant analysis to estimate an effective metric for computing neighborhoods. we determine the local decision boundaries from centroid information, and then shrink neighborhoods in directions orthogonal to these local decision boundaries, and elongate them parallel to the boundaries. thereafter, any neighborhood-based classifier can be employed, using the modified neighborhoods. the posterior probabilities tend to be more homogeneous in the modified neighborhoods. we also propose a method for global dimension reduction, that combines local dimension information. in a number of examples, the methods demonstrate the potential for substantial improvements over nearest neighbor classification.
discovering complex matchings across web query interfaces: a correlation mining approach. to enable information integration, schema matching is a critical step for discovering semantic correspondences of attributes across heterogeneous sources. while complex matchings are common, because of their far more complex search space, most existing techniques focus on simple 1:1 matchings. to tackle this challenge, this paper takes a conceptually novel approach by viewing schema matching as correlation mining, for our task of matching web query interfaces to integrate the myriad databases on the internet. on this "deep web," query interfaces generally form complex matchings between attribute groups (e.g., [author] corresponds to [first name, last name] in the books domain). we observe that the co-occurrences patterns across query interfaces often reveal such complex semantic relationships: grouping attributes (e.g., [first name, last name]) tend to be co-present in query interfaces and thus positively correlated. in contrast, synonym attributes are negatively correlated because they rarely co-occur. this insight enables us to discover complex matchings by a correlation mining approach. in particular, we develop the dcm framework, which consists of data preparation, dual mining of positive and negative correlations, and finally matching selection. unlike previous correlation mining algorithms, which mainly focus on finding strong positive correlations, our algorithm cares both positive and negative correlations, especially the subtlety of negative correlations, due to its special importance in schema matching. this leads to the introduction of a new correlation measure, $h$-measure, distinct from those proposed in previous work. we evaluate our approach extensively and the results show good accuracy for discovering complex matchings.
graphical models for data mining. i will discuss the use of graphical models for data mining. i will review key research areas including structure learning, variational methods, a relational modeling, and describe applications ranging from web traffic analysis to aids vaccine design.
maximal boasting. we introduce the boasting problem, wherein useful trends in historical ordinal data (rankings) are discovered. claims of the form "our object was ranked r or better in x of the last t time units," are formalized, and maximal claims (boasts) of this form are defined under two natural partial orders. for the first partial order, we give an efficient and optimal algorithm for finding all such maximal claims. for the second, we apply a classical result from computational geometry to achieve an algorithm whose running time is significantly more efficient than that of a naïve one. finally, we connect this boasting problem to a novel variation of the problem of finding optimized confidence association rules as originally posed by fukuda, et al. [2], and give an efficient algorithm for solving a simplification of the new problem.
ga-based rule enhancement in concept learning. we describe an application of dogma, a ga-based theory revision system, to mdl-based rule enhancement in supervised concept learning. the system takes as input classification data and a rule-based classification theory, produced by some rule-based learner, and builds a second, hopefully more accurate, model of the data. unlike most theory revision systems dogma doesn''t revise the initial rules, but builds instead a completely new theory, using stochastic sampling and adaptation of the initial rules. the search for the new model is guided by a mdl-based complexity measure. the proposed methodology offers a partial solution both to the local mimima trap of fast greedy rule-based concept learners, and to the time complexity problem of ga-based concept learners. as an example we show how the system improves rules produced by c4.5rules.
combining email models for false positive reduction. machine learning and data mining can be effectively used to model, classify and discover interesting information for a wide variety of data including email. the email mining toolkit, emt, has been designed to provide a wide range of analyses for arbitrary email sources. depending upon the task, one can usually achieve very high accuracy, but with some amount of false positive tradeoff. generally false positives are prohibitively expensive in the real world. in the case of spam detection, for example, even if one email is misclassified, this may be unacceptable if it is a very important email. much work has been done to improve specific algorithms for the task of detecting unwanted messages, but less work has been report on leveraging multiple algorithms and correlating models in this particular domain of email analysis.emt has been updated with new correlation functions allowing the analyst to integrate a number of emt's user behavior models available in the core technology. we present results of combining classifier outputs for improving both accuracy and reducing false positives for the problem of spam detection. we apply these methods to a very large email data set and show results of different combination methods on these corpora. we introduce a new method to compare multiple and combined classifiers, and show how it differs from past work. the method analyzes the relative gain and maximum possible accuracy that can be achieved for certain combinations of classifiers to automatically choose the best combination.
mining for proposal reviewers: lessons learned at the national science foundation. in this paper, we discuss a prototype application deployed at the u.s. national science foundation for assisting program directors in identifying reviewers for proposals. the application helps program directors sort proposals into panels and find reviewers for proposals. to accomplish these tasks, it extracts information from the full text of proposals both to learn about the topics of proposals and the expertise of reviewers. we discuss a variety of alternatives that were explored, the solution that was implemented, and the experience in using the solution within the workflow of nsf.
mining hepatitis data with temporal abstraction. the hepatitis temporal database collected at chiba university hospital between 1982--2001 was recently given to challenge the kdd research. the database is large where each patient corresponds to 983 tests represented as sequences of irregular timestamp points with different lengths. this paper presents a temporal abstraction approach to mining knowledge from this hepatitis database. exploiting hepatitis background knowledge and data analysis, we introduce new notions and methods for abstracting short-term changed and long-term changed tests. the abstracted data allow us to apply different machine learning methods for finding knowledge part of which is considered as new and interesting by medical doctors.
visualization support for a user-centered kdd process. viewing knowledge discovery as a user-centered process that requires an effective collaboration between the user and the discovery system, our work aims to support an active role of the user in that process by developing synergistic visualization tools integrated in our discovery system d2ms. these tools provide an ability of visualizing the entire process of knowledge discovery in order to help the user with data preprocessing, selecting mining algorithms and parameters, evaluating and comparing discovered models, and taking control of the whole discover process. our case-studies with two medical datasets on meningitis and stomach cancer show that, with visualization tools in d2ms, the user gains better insight in each step of the knowledge discovery process as well the relationship between data and discovered knowledge.
learning the unified kernel machines for classification. kernel machines have been shown as the state-of-the-art learning techniques for classification. in this paper, we propose a novel general framework of learning the unified kernel machines (ukm) from both labeled and unlabeled data. our proposed framework integrates supervised learning, semi-supervised kernel learning, and active learning in a unified solution. in the suggested framework, we particularly focus our attention on designing a new semi-supervised kernel learning method, i.e., spectral kernel learning (skl), which is built on the principles of kernel target alignment and unsupervised kernel design. our algorithm is related to an equivalent quadratic programming problem that can be efficiently solved. empirical results have shown that our method is more effective and robust to learn the semi-supervised kernels than traditional approaches. based on the framework, we present a specific paradigm of unified kernel machines with respect to kernel logistic regresions (klr), i.e., unified kernel logistic regression (uklr). we evaluate our proposed uklr classification scheme in comparison with traditional solutions. the promising results show that our proposed uklr paradigm is more effective than the traditional classification approaches.
a perspective on databases and data mining. we discuss the use of database methods for data mining. recently impressive results have been achieved for some data mining problems using highly specialized and clever data structures. we study how well one can manage by using general purpose database management systems. we illustrate our ideas by investigating the use of a dbms for a well-researched area: the discovery of association rules. we present a simple algorithm, consisting of only union and intersection operations, and show that it achieves quite good performance on an efficient dbms. our method can incorporate inheritance hierarchies to the association rule algorithm easily. we also present a technique that effectively reduces the number of database operations when searching large search spaces that contain only few interesting items. our work shows that database techniques are promising for data mining: general architectures can achieve reasonable results.
diagnosing extrapolation: tree-based density estimation. there has historically been very little concern with extrapolation in machine learning, yet extrapolation can be critical to diagnose. predictor functions are almost always learned on a set of highly correlated data comprising a very small segment of predictor space. moreover, flexible predictors, by their very nature, are not controlled at points of extrapolation. this becomes a problem for diagnostic tools that require evaluation on a product distribution. it is also an issue when we are trying to optimize a response over some variable in the input space. finally, it can be a problem in non-static systems in which the underlying predictor distribution gradually drifts with time or when typographical errors misrecord the values of some predictors.we present a diagnosis for extrapolation as a statistical test for a point originating from the data distribution as opposed to a null hypothesis uniform distribution. this allows us to employ general classification methods for estimating such a test statistic. further, we observe that cart can be modified to accept an exact distribution as an argument, providing a better classification tool which becomes our extrapolation-detection procedure. we explore some of the advantages of this approach and present examples of its practical application.
discovering additive structure in black box functions. many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that drive it. a common approach to interpretation is to plot the dependence of a learned function on one or two predictors. we present a method that seeks not to display the behavior of a function, but to evaluate the importance of non-additive interactions within any set of variables. should the function be close to a sum of low dimensional components, these components can be viewed and even modeled parametrically. alternatively, the work here provides an indication of where intrinsically high-dimensional behavior takes place.the calculations used in this paper correspond closely with the functional anova decomposition; a well-developed construction in statistics. in particular, the proposed score of interaction importance measures the loss associated with the projection of the prediction function onto a space of additive models. the algorithm runs in linear time and we present displays of the output as a graphical model of the function for interpretation purposes.
natural communities in large linked networks. we are interested in finding natural communities in large-scale linked networks. our ultimate goal is to track changes over time in such communities. for such temporal tracking, we require a clustering algorithm that is relatively stable under small perturbations of the input data. we have developed an efficient, scalable agglomerative strategy and applied it to the citation graph of the nec citeseer database (250,000 papers; 4.5 million citations). agglomerative clustering techniques are known to be unstable on data in which the community structure is not strong. we find that some communities are essentially random and thus unstable while others are natural and will appear in most clusterings. these natural communities will enable us to track the evolution of communities over time.
cyclic pattern kernels for predictive graph mining. with applications in biology, the world-wide web, and several other areas, mining of graph-structured objects has received significant interest recently. one of the major research directions in this field is concerned with predictive data mining in graph databases where each instance is represented by a graph. some of the proposed approaches for this task rely on the excellent classification performance of support vector machines. to control the computational cost of these approaches, the underlying kernel functions are based on frequent patterns. in contrast to these approaches, we propose a kernel function based on a natural set of cyclic and tree patterns independent of their frequency, and discuss its computational aspects. to practically demonstrate the effectiveness of our approach, we use the popular nci-hiv molecule dataset. our experimental results show that cyclic pattern kernels can be computed quickly and offer predictive performance superior to recent graph kernels based on frequent patterns.
frequent subgraph mining in outerplanar graphs. in recent years there has been an increased interest in algorithms that can perform frequent pattern discovery in large databases of graph structured objects. while the frequent connected subgraph mining problem for tree datasets can be solved in incremental polynomial time, it becomes intractable for arbitrary graph databases. existing approaches have therefore resorted to various heuristic strategies and restrictions of the search space, but have not identified a practically relevant tractable graph class beyond trees. in this paper, we define the class of so called tenuous outerplanar graphs, a strict generalization of trees, develop a frequent subgraph mining algorithm for tenuous outerplanar graphs that works in incremental polynomial time, and evaluate the algorithm empirically on the nci molecular graph dataset.
revi-miner, a kdd-environment for deviation detection and analysis of warranty and goodwill cost statements in automotive industry. revi-miner is a kdd-environment which supports the detection and analysis of deviations in warranty and goodwill cost statements. the system was developed within the framework of a cooperation between daimlerchrysler research & technology and global service and parts (gsp) and is based upon the crisp-dm methodology as a widely accepted process model for the solution of data mining problems. also, we have implemented different approaches based on machine learning and statistics which can be utilized for data cleaning in the preprocessing phase. the data mining models applied have been developed by using a statistical deviation detection approach. the tool supports controllers in their task of auditing the authorized repair shops. in this paper we describe the development phases which have led to revi-miner.
navigating massive data sets via local clustering. this paper introduces a scalable method for feature extraction and navigation of large data sets by means of local clustering, where clusters are modeled as overlapping neighborhoods. under the model, intra-cluster association and external differentiation are both assessed in terms of a natural confidence measure. minor clusters can be identified even when they appear in the intersection of larger clusters. scalability of local clustering derives from recent generic techniques for efficient approximate similarity search. the cluster overlap structure gives rise to a hierarchy that can be navigated and queried by users. experimental results are provided for two large text databases.
mining viewpoint patterns in image databases. the increasing number of image repositories has made image mining an important task because of its potential in discovering useful image patterns from a large set of images. in this paper, we introduce the notion of viewpoint patterns for image databases. viewpoint patterns refer to patterns that capture the invariant relationships of one object from the point of view of another object. these patterns are unique and significant in images because the absolute positional information of objects for most images is not important, but rather, it is the relative distance and orientation of the objects from each other that is meaningful. we design a scalable and efficient algorithm to discover such viewpoint patterns. experiments results on various image sets demonstrate that viewpoint patterns are meaningful and interesting to human users.
spin: mining maximal frequent subgraphs from graph databases. one fundamental challenge for mining recurring subgraphs from semi-structured data sets is the overwhelming abundance of such patterns. in large graph databases, the total number of frequent subgraphs can become too large to allow a full enumeration using reasonable computational resources. in this paper, we propose a new algorithm that mines only maximal frequent subgraphs, i.e. subgraphs that are not a part of any other frequent subgraphs. this may exponentially decrease the size of the output set in the best case; in our experiments on practical data sets, mining maximal frequent subgraphs reduces the total number of mined patterns by two to three orders of magnitude.our method first mines all frequent trees from a general graph database and then reconstructs all maximal subgraphs from the mined trees. using two chemical structure benchmarks and a set of synthetic graph data sets, we demonstrate that, in addition to decreasing the output size, our algorithm can achieve a five-fold speed up over the current state-of-the-art subgraph mining algorithms.
data mining techniques to improve forecast accuracy in airline business. predictive models developed by applying data mining techniques are used to improve forecasting accuracy in the airline business. in order to maximize the revenue on a flight, the number of seats available for sale is typically higher than the physical seat capacity (overbooking). to optimize the overbooking rate, an accurate estimation of the number of no-show passengers (passengers who hold a valid booking but do not appear at the gate to board for the flight) is essential. currently, no-shows on future flights are estimated from the number of no-shows on historical flights averaged on booking class level. in this work, classification trees and logistic regression models are applied to estimate the probability that an individual passenger turns out to be a no-show. passenger information stored in the reservation system of the airline is either directly used as explanatory variable or used to create attributes that have an impact on the probability of a passenger to be a no-show. the total number of no-shows in each booking class or on the total flight is then obtained by accumulating the individual no-show probabilities over the entity of interest. we show that this forecasting approach is more accurate than the currently used method. in addition, the selected models lead to a deepened insight into passenger behavior.
mining complex models from arbitrarily large databases in constant time. in this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. the result of applying the method to an algorithm is that its running time becomes independent of the size of the database, while the decisions made are essentially identical to those that would be made given infinite data. the method works within pre-specified memory limits and, as long as the data is iid, only requires accessing it sequentially. it gives anytime results, and can be used to produce batch, stream, time-changing and active-learning versions of an algorithm. we apply the method to learning bayesian networks, developing an algorithm that is faster than previous ones by orders of magnitude, while achieving essentially the same predictive performance. we observe these gains on a series of large databases "generated from benchmark networks, on the kdd cup 2000 e-commerce data, and on a web log containing 100 million requests.
mining time-changing data streams. most statistical and machine-learning algorithms assume that the data is a random sample drawn from a stationary distribution. unfortunately, most of the large databases available for mining today violate this assumption. they were gathered over months or years, and the underlying processes generating them changed during this time, sometimes radically. although a number of algorithms have been proposed for learning time-changing concepts, they generally do not scale well to very large databases. in this paper we propose an efficient algorithm for mining decision trees from continuously-changing data streams, based on the ultra-fast vfdt decision tree learner. this algorithm, called cvfdt, stays current while making the most of old data by growing an alternative subtree whenever an old one becomes questionable, and replacing the old with the new when the new becomes more accurate. cvfdt learns a model which is similar in accuracy to the one that would be learned by reapplying vfdt to a moving window of examples every time a new example arrives, but with o(1) complexity per example, as opposed to o(w), where w is the size of the window. experiments on a set of large time-changing data streams demonstrate the utility of this approach.
eigenspace-based anomaly detection in computer systems. we report on an automated runtime anomaly detection method at the application layer of multi-node computer systems. although several network management systems are available in the market, none of them have sufficient capabilities to detect faults in multi-tier web-based systems with redundancy. we model a web-based system as a weighted graph, where each node represents a "service" and each edge represents a dependency between services. since the edge weights vary greatly over time, the problem we address is that of anomaly detection from a time sequence of graphs.in our method, we first extract a feature vector from the adjacency matrix that represents the activities of all of the services. the heart of our method is to use the principal eigenvector of the eigenclusters of the graph. then we derive a probability distribution for an anomaly measure defined for a time-series of directional data derived from the graph sequence. given a critical probability, the threshold value is adaptively updated using a novel online algorithm.we demonstrate that a fault in a web application can be automatically detected and the faulty services are identified without using detailed knowledge of the behavior of the system.
adaptive event detection with time-varying poisson processes. time-series of count data are generated in many different contexts, such as web access logging, freeway traffic monitoring, and security logs associated with buildings. since this data measures the aggregated behavior of individual human beings, it typically exhibits a periodicity in time on a number of scales (daily, weekly,etc.) that reflects the rhythms of the underlying human activity and makes the data appear non-homogeneous. at the same time, the data is often corrupted by a number of bursty periods of unusual behavior such as building events, traffic accidents, and so forth. the data mining problem of finding and extracting these anomalous events is made difficult by both of these elements. in this paper we describe a framework for unsupervised learning in this context, based on a time-varying poisson process model that can also account for anomalous events. we show how the parameters of this model can be learned from count time series using statistical estimation techniques. we demonstrate the utility of this model on two datasets for which we have partial ground truth in the form of known events, one from freeway traffic data and another from building access data, and show that the model performs significantly better than a non-probabilistic, threshold-based technique. we also describe how the model can be used to investigate different degrees of periodicity in the data, including systematic day-of-week and time-of-day effects, and make inferences about the detected events (e.g., popularity or level of attendance). our experimental results indicate that the proposed time-varying poisson model provides a robust and accurate framework for adaptively and autonomously learning how to separate unusual bursty events from traces of normal human activity.
solving regression problems with rule-based ensemble classifiers. we describe a lightweight learning method that induces an ensemble of decision-rule solutions for regression problems. instead of direct prediction of a continuous output variable, the method discretizes the variable by k-means clustering and solves the resultant classification problem. predictions on new examples are made by averaging the mean values of classes with votes that are close in number to the most likely class. we provide experimental evidence that this indirect approach can often yield strong results for many applications, generally outperforming direct approaches such as regression trees and rivaling bagged regression trees.
application of kernels to link analysis. the application of kernel methods to link analysis is explored. in particular, kandola et al.'s neumann kernels are shown to subsume not only the co-citation and bibliographic coupling relatedness but also kleinberg's hits importance. these popular measures of relatedness and importance correspond to the neumann kernels at the extremes of their parameter range, and hence these kernels can be interpreted as defining a spectrum of link analysis measures intermediate between co-citation/bibliographic coupling and hits. we also show that the kernels based on the graph laplacian, including the regularized laplacian and diffusion kernels, provide relatedness measures that overcome some limitations of co-citation relatedness. the property of these kernel-based link analysis measures is examined with a network of bibliographic citations. practical issues in applying these methods to real data are discussed, and possible solutions are proposed.
recommendation method for extending subscription periods. online stores providing subscription services need to extend user subscription periods as long as possible to increase their profits. conventional recommendation methods recommend items that best coincide with user's interests to maximize the purchase probability, which does not necessarily contribute to extend subscription periods. we present a novel recommendation method for subscription services that maximizes the probability of the subscription period being extended. our method finds frequent purchase patterns in the long subscription period users, and recommends items for a new user to simulate the found patterns. using survival analysis techniques, we efficiently extract information from the log data for finding the patterns. furthermore, we infer user's interests from purchase histories based on maximum entropy models, and use the interests to improve the recommendations. since a longer subscription period is the result of greater user satisfaction, our method benefits users as well as online stores. we evaluate our method using the real log data of an online cartoon distribution service for cell-phone in japan.
transforming data to satisfy privacy constraints. data on individuals and entities are being collected widely. these data can contain information that explicitly identifies the individual (e.g., social security number). data can also contain other kinds of personal information (e.g., date of birth, zip code, gender) that are potentially identifying when linked with other available data sets. data are often shared for business or legal reasons. this paper addresses the important issue of preserving the anonymity of the individuals or entities during the data dissemination process. we explore preserving the anonymity by the use of generalizations and suppressions on the potentially identifying portions of the data. we extend earlier works in this area along various dimensions. first, satisfying privacy constraints is considered in conjunction with the usage for the data being disseminated. this allows us to optimize the process of preserving privacy for the specified usage. in particular, we investigate the privacy transformation in the context of data mining applications like building classification and regression models. second, our work improves on previous approaches by allowing more flexible generalizations for the data. lastly, this is combined with a more thorough exploration of the solution space using the genetic algorithm framework. these extensions allow us to transform the data so that they are more useful for their intended purpose while satisfying the privacy constraints.
on detecting space-time clusters. detection of space-time clusters is an important function in various domains (e.g., epidemiology and public health). the pioneering work on the spatial scan statistic is often used as the basis to detect and evaluate such clusters. state-of-the-art systems based on this approach detect clusters with restrictive shapes that cannot model growth and shifts in location over time. we extend these methods significantly by using the flexible square pyramid shape to model such effects. a heuristic search method is developed to detect the most likely clusters using a randomized algorithm in combination with geometric shapes processing. the use of monte carlo methods in the original scan statistic formulation is continued in our work to address the multiple hypothesis testing issues. our method is applied to a real data set on brain cancer occurrences over a 19 year period. the cluster detected by our method shows both growth and movement which could not have been modeled with the simpler cylindrical shapes used earlier. our general framework can be extended quite easily to handle other flexible shapes for the space-time clusters.
a model for discovering customer value for e-content. there exists a huge demand for multimedia goods and services in the internet. currently available bandwidth speeds can support sale of downloadable content like cds, e-books, etc. as well as services like video-on-demand. in the future, such services will be prevalent in the internet. since costs are typically fixed, maximizing revenue can maximize profits. a primary determinant of revenue in such e-content markets is how much value the customers associate with the content. though marketing surveys are useful, they cannot adapt to the dynamic nature of the internet market. in this work, we examine how to learn customer valuations in close to real-time. our contributions in this paper are threefold: (1) we develop a probabilistic model to describe customer behavior, (2) we develop a framework for pricing e-content based on basic economic principles, and (3) we propose a price discovering algorithm that learns customer behavior parameters and suggests prices to an e-content provider. we validate our algorithm using simulations. our simulations indicate that our algorithm generates revenue close to the maximum expectation. further, they also indicate that the algorithm is robust to transient customer behavior.
privacy-preserving distributed k-means clustering over arbitrarily partitioned data. advances in computer networking and database technologies have enabled the collection and storage of vast quantities of data. data mining can extract valuable knowledge from this data, and organizations have realized that they can often obtain better results by pooling their data together. however, the collected data may contain sensitive or private information about the organizations or their customers, and privacy concerns are exacerbated if data is shared between multiple organizations.distributed data mining is concerned with the computation of models from data that is distributed among multiple participants. privacy-preserving distributed data mining seeks to allow for the cooperative computation of such models without the cooperating parties revealing any of their individual data items. our paper makes two contributions in privacy-preserving data mining. first, we introduce the concept of arbitrarily partitioned data, which is a generalization of both horizontally and vertically partitioned data. second, we provide an efficient privacy-preserving protocol for k-means clustering in the setting of arbitrarily partitioned data.
nomograms for visualizing support vector machines. we propose a simple yet potentially very effective way of visualizing trained support vector machines. nomograms are an established model visualization technique that can graphically encode the complete model on a single page. the dimensionality of the visualization does not depend on the number of attributes, but merely on the properties of the kernel. to represent the effect of each predictive feature on the log odds ratio scale as required for the nomograms, we employ logistic regression to convert the distance from the separating hyperplane into a probability. case studies on selected data sets show that for a technique thought to be a black-box, nomograms can clearly expose its internal structure. by providing an easy-to-interpret visualization the analysts can gain insight and study the effects of predictive factors.
dynamic, real-time forecasting of online auctions via functional models. we propose a dynamic model for forecasting price in online auctions. one of the key features of our model is that it operates during the live-auction, which makes it different from previous approaches that only consider static models. our model is also different with respect to how information about price is incorporated. while one part of the model is based on the more traditional notion of an auction's price-level, another part incorporates its dynamics in the form of a price's velocity and acceleration. in that sense, it incorporates key features of a dynamic environment such as an online auction. the use of novel functional data methodology allows us to measure, and subsequently include, dynamic price characteristics. we illustrate our model on a diverse set of ebay auctions across many different book categories. we find significantly higher prediction accuracy compared to standard approaches.
polynomial association rules with applications to logistic regression. a new class of associations (polynomial itemsets and polynomial association rules) is presented which allows for discovering nonlinear relationships between numeric attributes without discretization. for binary attributes, proposed associations reduce to classic itemsets and association rules. many standard association rule mining algorithms can be adapted to finding polynomial itemsets and association rules. we applied polynomial associations to add non-linear terms to logistic regression models. significant performance improvement was achieved over stepwise methods, traditionally used in statistics, with comparable accuracy.
interestingness of frequent itemsets using bayesian networks as background knowledge. the paper presents a method for pruning frequent itemsets based on background knowledge represented by a bayesian network. the interestingness of an itemset is defined as the absolute difference between its support estimated from data and from the bayesian network. efficient algorithms are presented for finding interestingness of a collection of frequent itemsets, and for finding all attribute sets with a given minimum interestingness. practical usefulness of the algorithms and their efficiency have been verified experimentally.
fast discovery of unexpected patterns in data, relative to a bayesian network. we consider a model in which background knowledge on a given domain of interest is available in terms of a bayesian network, in addition to a large database. the mining problem is to discover unexpected patterns: our goal is to find the strongest discrepancies between network and database. this problem is intrinsically difficult because it requires inference in a bayesian network and processing the entire, potentially very large, database. a sampling-based method that we introduce is efficient and yet provably finds the approximately most interesting unexpected patterns. we give a rigorous proof of the method's correctness. experiments shed light on its efficiency and practicality for large-scale bayesian networks and databases.
simrank: a measure of structural-context similarity. the problem of measuring "similarity" of objects arises in many applications, and many domain-specific measures have been developed, e.g., matching text across documents or computing overlap among item-sets. we propose a complementary approach, applicable in any domain with object-to-object relationships, that measures similarity of the structural context in which objects occur, based on their relationships with other objects. effectively, we compute a measure that says "two objects are similar if they are related to similar objects:" this general similarity measure, called simrank, is based on a simple and intuitive graph-theoretic model. for a given domain, simrank can be combined with other domain-specific similarity measures. we suggest techniques for efficient computation of simrank scores, and provide experimental results on two application domains showing the computational feasibility and effectiveness of our approach.
mining the space of graph properties. existing data mining algorithms on graphs look for nodes satisfying specific properties, such as specific notions of structural similarity or specific measures of link-based importance. while such analyses for predetermined properties can be effective in well-understood domains, sometimes identifying an appropriate property for analysis can be a challenge, and focusing on a single property may neglect other important aspects of the data. in this paper, we develop a foundation for mining the properties themselves. we present a theoretical framework defining the space of graph properties, a variety of mining queries enabled by the framework, techniques to handle the enormous size of the query space, and an experimental system called f-miner that demonstrates the utility and feasibility of property mining.
why collective inference improves relational classification. procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. for example, collective inference could be used to simultaneously classify a set of hyperlinked documents or infer the legitimacy of a set of related financial transactions. several recent studies indicate that collective inference can significantly reduce classification error when compared with traditional inference techniques. we investigate the underlying mechanisms for this error reduction by reviewing past work on collective inference and characterizing different types of statistical models used for making inference in relational data. we show important differences among these models, and we characterize the necessary and sufficient conditions for reduced classification error based on experiments with real and simulated data.
information awareness: a prospective technical assessment. recent proposals to apply data mining systems to problems in law enforcement, national security, and fraud detection have attracted both media attention and technical critiques of their expected accuracy and impact on privacy. unfortunately, the majority of technical critiques have been based on simplistic assumptions about data, classifiers, inference procedures, and the overall architecture of such systems. we consider these critiques in detail, and we construct a simulation model that more closely matches realistic systems. we show how both the accuracy and privacy impact of a hypothetical system could be substantially improved, and we discuss the necessary and sufficient conditions for this improvement to be achieved. this analysis is neither a defense nor a critique of any particular system concept. rather, our model suggests alternative technical designs that could mitigate some concerns, but also raises more specific conditions that must be met for such systems to be both accurate and socially desirable.
playing hide-and-seek with correlations. we present a method for very high-dimensional correlation analysis. the method relies equally on rigorous search strategies and on human interaction. at each step, the method conservatively "shaves off" a fraction of the database tuples and attributes, so that most of the correlations present in the data are not affected by the decomposition. instead, the correlations become more obvious to the user, because they are hidden in a much smaller portion of the database. this process can be repeated iteratively and interactively, until only the most important correlations remain.the main technical difficulty of the approach is figuring out how to "shave off" part of the database so as to preserve most correlations. we develop an algorithm for this problem that has a polynomial running time and guarantees result quality.
generation of synthetic data sets for evaluating the accuracy of knowledge discovery systems. information discovery and analysis systems (idas) are designed to correlate multiple sources of data and use data mining techniques to identify potential significant events. application domains for idas are numerous and include the emerging area of homeland security.developing test cases for an idas requires background data sets into which hypothetical future scenarios can be overlaid. the idas can then be measured in terms of false positive and false negative error rates. obtaining the test data sets can be an obstacle due to both privacy issues and also the time and cost associated with collecting a diverse set of data sources.in this paper, we give an overview of the design and architecture of an idas data set generator (idsg) that enables a fast and comprehensive test of an idas. the idsg generates data using statistical and rule-based algorithms and also semantic graphs that represent interdependencies between attributes. a credit card transaction application is used to illustrate the approach.
cfi-stream: mining closed frequent itemsets in data streams. mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. extensive studies have been done on mining frequent closed itemsets, but they are mainly intended for traditional transaction databases and thus do not take data stream characteristics into consideration. in this paper, we propose a novel approach for mining closed frequent itemsets over data streams. it computes and maintains closed itemsets online and incrementally, and can output the current closed frequent itemsets in real time based on users' specified thresholds. experimental results show that our proposed method is both time and space efficient, has good scalability as the number of transactions processed increases and adapts very rapidly to the change in data streams.
mining coherent gene clusters from gene-sample-time microarray data. extensive studies have shown that mining microarray data sets is important in bioinformatics research and biomedical applications. in this paper, we explore a novel type of gene-sample-time microarray data sets, which records the expression levels of various genes under a set of samples during a series of time points. in particular, we propose the mining of coherent gene clusters from such data sets. each cluster contains a subset of genes and a subset of samples such that the genes are coherent on the samples along the time series. the coherent gene clusters may identify the samples corresponding to some phenotypes (e.g., diseases), and suggest the candidate genes correlated to the phenotypes. we present two efficient algorithms, namely the sample-gene search and the gene-sample search, to mine the complete set of coherent gene clusters. we empirically evaluate the performance of our approaches on both a real microarray data set and synthetic data sets. the test results have shown that our approaches are both efficient and effective to find meaningful coherent gene clusters.
interactive exploration of coherent patterns in time-series gene expression data. discovering coherent gene expression patterns in time-series gene expression data is an important task in bioinformatics research and biomedical applications. in this paper, we propose an interactive exploration framework for mining coherent expression patterns in time-series gene expression data. we develop a novel tool, coherent pattern index graph, to give users highly confident indications of the existences of coherent patterns. to derive a coherent pattern index graph, we devise an attraction tree structure to record the genes in the data set and summarize the information needed for the interactive exploration. we present fast and scalable algorithms to construct attraction trees and coherent pattern index graphs from gene expression data sets. we conduct an extensive performance study on some real data sets to verify our design. the experimental results strongly show that our approach is more effective than the state-of-the-art methods in mining real gene expression data, and is scalable in mining large data sets.
efficient decision tree construction on streaming data. decision tree construction is a well studied problem in data mining. recently, there has been much interest in mining streaming data. domingos and hulten have presented a one-pass algorithm for decision tree construction. their work uses hoeffding inequality to achieve a probabilistic bound on the accuracy of the tree constructed.in this paper, we revisit this problem. we make the following two contributions: 1) we present a numerical interval pruning (nip) approach for efficiently processing numerical attributes. our results show an average of 39% reduction in execution times. 2) we exploit the properties of the gain function entropy (and gini) to reduce the sample size required for obtaining a given bound on the accuracy. our experimental results show a 37% reduction in the number of data instances required.
similarity measure based on partial information of time series. similarity measure of time series is an important subroutine in many kdd applications. previous similarity models mainly focus on the prominent series behaviors by considering the whole information of time series. in this paper, we address the problem: which portion of information is more suitable for similarity measure for the data collected from a certain field. we propose a model for the retrieval and representation of the partial information in time series data, and a methodology for evaluating the similarity measurements based on partial information. the methodology is to retrieve various portions of information from the raw data and represent it in a concise form, then cluster the time series using the partial information and evaluate the similarity measurements through comparing the results with a standard classification. experiments on data set from stock market give some interesting observations and justify the usefulness of our approach.
simultaneous optimization of complex mining tasks with a knowledgeable cache. with an increasing use of data mining tools and techniques, we envision that a knowledge discovery and data mining system (kddms) will have to support and optimize for the following scenarios: 1) sequence of queries: a user may analyze one or more datasets by issuing a sequence of related complex mining queries, and 2) multiple simultaneous queries: several users may be analyzing a set of datasets concurrently, and may issue related complex queries.this paper presents a systematic mechanism to optimize for the above cases, targeting the class of mining queries involving frequent pattern mining on one or multiple datasets. we present a system architecture and propose new algorithms to simultaneously optimize multiple such queries and use a knowledgeable cache to store and utilize the past query results. we have implemented and evaluated our system with both real and synthetic datasets. our experimental results show that our techniques can achieve a speedup of up to a factor of 9, compared with the systems which do not support caching or optimize for multiple queries.
mining top-n local outliers in large databases. outlier detection is an important task in data mining with numerous applications, including credit card fraud detection, video surveillance, etc. a recent work on outlier detection has introduced a novel notion of local outlier in which the degree to which an object is outlying is dependent on the density of its local neighborhood, and each object can be assigned a local outlier factor (lof) which represents the likelihood of that object being an outlier. although the concept of local outliers is a useful one, the computation of lof values for every data objects requires a large number of &kgr;-nearest neighbors searches and can be computationally expensive. since most objects are usually not outliers, it is useful to provide users with the option of finding only n most outstanding local outliers, i.e., the top-n data objects which are most likely to be local outliers according to their lofs. however, if the pruning is not done carefully, finding top-n outliers could result in the same amount of computation as finding lof for all objects. in this paper, we propose a novel method to efficiently find the top-n local outliers in large databases. the concept of "micro-cluster" is introduced to compress the data. an efficient micro-cluster-based local outlier mining algorithm is designed based on this concept. as our algorithm can be adversely affected by the overlapping in the micro-clusters, we proposed a meaningful cut-plane solution for overlapping data. the formal analysis and experiments show that this method can achieve good performance in finding the most outstanding local outliers.
discovering frequent topological structures from graph datasets. the problem of finding frequent patterns from graph-based datasets is an important one that finds applications in drug discovery, protein structure analysis, xml querying, and social network analysis among others. in this paper we propose a framework to mine frequent large-scale structures, formally defined as frequent topological structures, from graph datasets. key elements of our framework include, fast algorithms for discovering frequent topological patterns based on the well known notion of a topological minor, algorithms for specifying and pushing constraints deep into the mining process for discovering constrained topological patterns, and mechanisms for specifying approximate matches when discovering frequent topological patterns in noisy datasets. we demonstrate the viability and scalability of the proposed algorithms on real and synthetic datasets and also discuss the use of the framework to discover meaningful topological structures from protein structure data.
web usage mining based on probabilistic latent semantic analysis. the primary goal of web usage mining is the discovery of patterns in the navigational behavior of web users. standard approaches, such as clustering of user sessions and discovering association rules or frequent navigational paths, do not generally provide the ability to automatically characterize or quantify the unobservable factors that lead to common navigational patterns. it is, therefore, necessary to develop techniques that can automatically discover hidden semantic relationships among users as well as between users and web objects. probabilistic latent semantic analysis (plsa) is particularly useful in this context, since it can uncover latent semantic associations among users and pages based on the co-occurrence patterns of these pages in user sessions. in this paper, we develop a unified framework for the discovery and analysis of web navigational patterns based on plsa. we show the flexibility of this framework in characterizing various relationships among users and web objects. since these relationships are measured in terms of probabilities, we are able to use probabilistic inference to perform a variety of analysis tasks such as user segmentation, page classification, as well as predictive tasks such as collaborative recommendations. we demonstrate the effectiveness of our approach through experiments performed on real-world data sets.
a maximum entropy web recommendation system: combining collaborative and content features. web users display their preferences implicitly by navigating through a sequence of pages or by providing numeric ratings to some items. web usage mining techniques are used to extract useful knowledge about user interests from such data. the discovered user models are then used for a variety of applications such as personalized recommendations. web site content or semantic features of objects provide another source of knowledge for deciphering users' needs or interests. we propose a novel web recommendation system in which collaborative features such as navigation or rating data as well as the content features accessed by the users are seamlessly integrated under the maximum entropy principle. both the discovered user patterns and the semantic relationships among web objects are represented as sets of constraints that are integrated to fit the model. in the case of content features, we use a new approach based on latent dirichlet allocation (lda) to discover the hidden semantic relationships among items and derive constraints used in the model. experiments on real web site usage data sets show that this approach can achieve better recommendation accuracy, when compared to systems using only usage information. the integration of semantic information also allows for better interpretation of the generated recommendations.
optimizing search engines using clickthrough data. this paper presents an approach to automatically optimizing the retrieval quality of search engines using clickthrough data. intuitively, a good information retrieval system should present relevant documents high in the ranking, with less relevant documents following below. while previous approaches to learning retrieval functions from examples exist, they typically require training data generated from relevance judgments by experts. this makes them difficult and expensive to apply. the goal of this paper is to develop a method that utilizes clickthrough data for training, namely the query-log of the search engine in connection with the log of links the users clicked on in the presented ranking. such clickthrough data is available in abundance and can be recorded at very low cost. taking a support vector machine (svm) approach, this paper presents a method for learning retrieval functions. from a theoretical perspective, this method is shown to be well-founded in a risk minimization framework. furthermore, it is shown to be feasible even for large sets of queries and features. the theoretical results are verified in a controlled experiment. it shows that the method can effectively adapt the retrieval function of a meta-search engine to a particular group of users, outperforming google in terms of retrieval quality after only a couple of hundred training examples.
training linear svms in linear time. linear support vector machines (svms) have become one of the most prominent machine learning techniques for high-dimensional sparse data commonly encountered in applications like text classification, word-sense disambiguation, and drug design. these applications involve a large number of examples n as well as a large number of features n, while each example has only s << n non-zero features. this paper presents a cutting plane algorithm for training linear svms that provably has training time 0(s,n) for classification problems and o(sn log (n))for ordinal regression problems. the algorithm is based on an alternative, but equivalent formulation of the svm optimization problem. empirically, the cutting-plane algorithm is several orders of magnitude faster than decomposition methods like svm light for large datasets.
introducing perpetual analytics. common strategies to liberate an organization's information assets for situational awareness frequently rely on infrastructure components such as data integration, enterprise search, federation, data warehousing, and so on. and while these traditional platforms enable analysts to get better and faster answers to their queries, the next big advance will change this paradigm. users cannot be expected to formulate and ask every smart question every day. and to escape this impractical and un-scalable model, the new paradigm will involve technologies where "the data finds the data" and "relevance finds the user." perpetual analytics describes a class of application whereby enterprise context is assembled, in real-time, on data streams as fast as operational systems record observations. context construction is a "data finds the data" activity which enables events of interest to be streamed to subscribers. in this talk, i will talk at some depth about the dynamics of such systems including scalability and sustainability.
predicting rare classes: can boosting make any weak learner strong? boosting is a strong ensemble-based learning algorithm with the promise of iteratively improving the classification accuracy using any base learner, as long as it satisfies the condition of yielding weighted accuracy > 0.5. in this paper, we analyze boosting with respect to this basic condition on the base learner, to see if boosting ensures prediction of rarely occurring events with high recall and precision. first we show that a base learner can satisfy the required condition even for poor recall or precision levels, especially for very rare classes. furthermore, we show that the intelligent weight updating mechanism in boosting, even in its strong cost-sensitive form, does not prevent cases where the base learner always achieves high precision but poor recall or high recall but poor precision, when mapped to the original distribution. in either of these cases, we show that the voting mechanism of boosting falls to achieve good overall recall and precision for the ensemble. in effect, our analysis indicates that one cannot be blind to the base learner performance, and just rely on the boosting mechanism to take care of its weakness. we validate our arguments empirically on variety of real and synthetic rare class problems. in particular, using adacost as the boosting algorithm, and variations of pnrule and ripper as the base learners, we show that if algorithm a achieves better recall-precision balance than algorithm b, then using a as the base learner in adacost yields significantly better performance than using b as the base learner.
a bag of paths model for measuring structural similarity in web documents. structural information (such as layout and look-and-feel) has been extensively used in the literatuce for extraction of interesting or relevant data, efficient storage, and query optimization. traditionally, tree models (such as dom trees) have been used to represent structural information, especially in the case of html and xml documents. however, computation of structural similarity between documents based on the tree model is computationally expensive. in this paper, we propose an alternative scheme for representing the structural information of documents based on the paths contained in the corresponding tree model. since the model includes partial information about parents, children and siblings, it allows us to define a new family of meaningful (and at the same time computationally simple) structural similarity measures. our experimental results based on the sigmod xml data set as well as html document collections from ibm.com, dell.com, and amazon.com show that the representation is powerful enough to produce good clusters of structurally similar pages.
mining intrusion detection alarms for actionable knowledge. in response to attacks against enterprise networks, administrators increasingly deploy intrusion detection systems. these systems monitor hosts, networks, and other resources for signs of security violations. the use of intrusion detection has given rise to another difficult problem, namely the handling of a generally large number of alarms. in this paper, we mine historical alarms to learn how future alarms can be handled more efficiently. first, we investigate episode rules with respect to their suitability in this approach. we report the difficulties encountered and the unexpected insights gained. in addition, we introduce a new conceptual clustering technique, and use it in extensive experiments with real-world data to show that intrusion detection alarms can be handled efficiently by using previously mined knowledge.
capital one's statistical problems: our top ten list. capital one is a highly quantitatively driven diversified financial services firm. as such, we make broad and deep use of the entire repertory of highly quantitative techniques. this talk will present our top ten statistical problems. indeed, one of them has, as a sub point, the data mining dimension, but it will likely be useful for data miners to see how their research needs to complement, and fit into, the entire range of hard statistical issues.
a system for automated mapping of bill-of-materials part numbers. part numbers are widely used within an enterprise throughout the manufacturing process. the point of entry of such part numbers into this process is normally via a bill of materials, or bom, sent by a contact manufacturer or supplier. each line of the bom provides information about one part such as the supplier part number, the bom receiver's corresponding internal part number, an unstructured textual part description, the supplier name, etc. however, in a substantial number of cases, the bom receiver's internal part number is absent. hence, before this part can be incorporated into the receiver's manufacturing process, it has to be mapped to an internal part (of the bom receiver) based on the information of the part in the bom. historically, this mapping process has been done manually which is a highly time-consuming, labor intensive and error-prone process. this paper describes a system for automating the mapping of bom part numbers. the system uses a two step modeling and mapping approach. first, the system uses historical bom data, receiver's part specifications data and receiver's part taxonomic data along with domain knowledge to automatically learn classification models for mapping a given bom part description to successively lower levels of the receiver's part taxonomy to reduce the set of potential internal parts to which the bom part could map to. then, information about various part parameters is extracted from the bom part description and compared to the specifications data of the potential internal parts to choose the final mapped internal part. mappings done by the system are very accurate, and the system is currently being deployed within ibm for mapping boms received by the corporate procurement/manufacturing divisions.
data mining in the chemical industry. in this paper we describe the experience of introducing data mining to a large chemical manufacturing company. the multi-national nature of doing business with multiple business units, presents a unique opportunity for the deployment of data mining. while each business unit has its own objectives and challenges, which may be at odds with those of other units, they also share many common interests and resources. in this environment, data mining can be used to identify potential value-creating opportunities, through large site integration of multiple assets and synergies from the use of common assets, such as site-wide manufacturing facilities, and world-wide supply-chain, purchasing and other shared services. however, issues arise, on one hand from overly complex systems, and on the other hand, from the danger of reaching sub-optimal solutions, if a big enough picture is not considered when executing projects. the company-wide initiative and use of six sigma at all levels of the company provided a fertile ground for making the case for data mining and facilitating its acceptance. the six sigma mindset of measuring the performance of processes and analyzing data promotes data-based decision making, therefore making data mining a natural extension of this methodology. we will describe the approach for launching a data mining capability within this framework, the strategy for securing upper management support, drawing from internal modeling, statistical, and other communities, and from external consultants and universities. lessons learned from industrial case studies, enterprise-wide tool evaluation and peer benchmarking will be discussed.
generalized clustering, supervised learning, and data assignment. clustering algorithms have become increasingly important in handling and analyzing data. considerable work has been done in devising effective but increasingly specific clustering algorithms. in contrast, we have developed a generalized framework that accommodates diverse clustering algorithms in a systematic way. this framework views clustering as a general process of iterative optimization that includes modules for supervised learning and instance assignment. the framework has also suggested several novel clustering methods. in this paper, we investigate experimentally the efficacy of these algorithms and test some hypotheses about the relation between such unsupervised techniques and the supervised methods embedded in them.
nantonac collaborative filtering: recommendation based on order responses. a recommender system suggests the items expected to be preferred by the users. recommender systems use collaborative filtering to recommend items by summarizing the preferences of people who have tendencies similar to the user preference. traditionally, the degree of preference is represented by a scale, for example, one that ranges from one to five. this type of measuring technique is called the semantic differential (sd) method. web adopted the ranking method, however, rather than the sd method, since the sd method is intrinsically not suited for representing individual preferences. in the ranking method, the preferences are represented by orders, which are sorted item sequences according to the users' preferences. we here propose some methods to recommed items based on these order responses, and carry out the comparison experiments of these methods.
visualizing multi-dimensional clusters, trends, and outliers using star coordinates. interactive visualizations are effective tools in mining scientific, engineering, and business data to support decision-making activities. star coordinates is proposed as a new multi-dimensional visualization technique, which supports various interactions to stimulate visual thinking in early stages of knowledge discovery process. in star coordinates, coordinate axes are arranged on a two-dimensional surface, where each axis shares the same origin point. each multi-dimensional data element is represented by a point, where each attribute of the data contributes to its location through uniform encoding. interaction features of star coordinates provide users the ability to apply various transformations dynamically, integrate and separate dimensions, analyze correlations of multiple dimensions, view clusters, trends, and outliers in the distribution of data, and query points based on data ranges. our experience with star coordinates shows that it is particularly useful for the discovery of hierarchical clusters, and analysis of multiple factors providing insight in various real datasets including telecommunications churn.
when do data mining results violate privacy? privacy-preserving data mining has concentrated on obtaining valid results when the input data is private. an extreme example is secure multiparty computation-based methods, where only the results are revealed. however, this still leaves a potential privacy breach: do the results themselves violate privacy? this paper explores this issue, developing a framework under which this question can be addressed. metrics are proposed, along with analysis that those metrics are consistent in the face of apparent problems.
information retrieval based on collaborative filtering with latent interest semantic map. in this paper, we propose an information retrieval model called latent interest semantic map (lism), which features retrieval composed of both collaborative filtering(cf) and probabilistic latent semantic analysis (plsa). the motivation behind this study is that the relation between users and documents can be explained by the two different latent classes, where users belong probabilistically in one or more classes with the same interest groups, while documents also belong probabilistically in one or more class with the same topic groups. the novel aspect of lism is that it simultaneously provides a user model and latent semantic analysis in one map. this benefit of lism is to enable collaborative filtering in terms of user interest and document topic and thus solve the cold start problem.
mining quantitative correlated patterns using an information-theoretic approach. existing research on mining quantitative databases mainly focuses on mining associations. however, mining associations is too expensive to be practical in many cases. in this paper, we study mining correlations from quantitative databases and show that it is a more effective approach than mining associations. we propose a new notion of quantitative correlated patterns (qcps), which is founded on two formal concepts, mutual information and all-confidence. we first devise a normalization on mutual information and apply it to qcp mining to capture the dependency between the attributes. we further adopt all-confidence as a quality measure to control, at a finer granularity, the dependency between the attributes with specific quantitative intervals. we also propose a supervised method to combine the consecutive intervals of the quantitative attributes based on mutual information, such that the interval combining is guided by the dependency between the attributes. we develop an algorithm, qcomine, to efficiently mine qcps by utilizing normalized mutual information and all-confidence to perform a two-level pruning. our experiments verify the efficiency of qcomine and the quality of the qcps.
maximizing the spread of influence through a social network. models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects of "word of mouth" in the promotion of new products. recently, motivated by the design of viral marketing strategies, domingos and richardson posed a fundamental algorithmic problem for such social network processes: if we can try to convince a subset of individuals to adopt a new product or innovation, and the goal is to trigger a large cascade of further adoptions, which set of individuals should we target?we consider this problem in several of the most widely studied models in social network analysis. the optimization problem of selecting the most influential nodes is np-hard here, and we provide the first provable approximation guarantees for efficient algorithms. using an analysis framework based on submodular functions, we show that a natural greedy strategy obtains a solution that is provably within 63% of optimal for several classes of models; our framework suggests a general approach for reasoning about the performance guarantees of algorithms for these types of influence problems in social networks.we also provide computational experiments on large collaboration networks, showing that in addition to their provable guarantees, our approximation algorithms significantly out-perform node-selection heuristics based on the well-studied notions of degree centrality and distance centrality from the field of social networks.
ensemble-index: a new approach to indexing large databases. the problem of similarity search (query-by-content) has attracted much research interest. it is a difficult problem because of the inherently high dimensionality of the data. the most promising solutions involve performing dimensionality reduction on the data, then indexing the reduced data with a multidimensional index structure. many dimensionality reduction techniques have been proposed, including singular value decomposition (svd), the discrete fourier transform (dft), the discrete wavelet transform (dwt) and piecewise polynomial approximation. in this work, we introduce a novel framework for using ensembles of two or more representations for more efficient indexing. the basic idea is that instead of committing to a single representation for an entire dataset, different representations are chosen for indexing different parts of the database. the representations are chosen based upon a local view of the database. for example, sections of the data that can achieve a high fidelity representation with wavelets are indexed as wavelets, but highly spectral sections of the data are indexed using the fourier transform. at query time, it is necessary to search several small heterogeneous indices, rather than one large homogeneous index. as we will theoretically and empirically demonstrate this results in much faster query response times.
on the need for time series data mining benchmarks: a survey and empirical demonstration. in the last decade there has been an explosion of interest in mining time series data. literally hundreds of papers have introduced new algorithms to index, classify, cluster and segment time series. in this work we make the following claim. much of this work has very little utility because the contribution made (speed in the case of indexing, accuracy in the case of classification and clustering, model accuracy in the case of segmentation) offer an amount of &ldquo;improvement&rdquo; that would have been completely dwarfed by the variance that would have been observed by testing on many real world datasets, or the variance that would have been observed by changing minor (unstated) implementation details.to illustrate our point, we have undertaken the most exhaustive set of time series experiments ever attempted, re-implementing the contribution of more than two dozen papers, and testing them on 50 real world, highly diverse datasets. our empirical results strongly support our assertion, and suggest the need for a set of time series benchmarks and more careful empirical evaluation in the data mining community.
finding surprising patterns in a time series database in linear time and space. the problem of finding a specified pattern in a time series database (i.e. query by content) has received much attention and is now a relatively mature field. in contrast, the important problem of enumerating all surprising or interesting patterns has received far less attention. this problem requires a meaningful definition of "surprise", and an efficient search technique. all previous attempts at finding surprising patterns in time series use a very limited notion of surprise, and/or do not scale to massive datasets. to overcome these limitations we introduce a novel technique that defines a pattern surprising if the frequency of its occurrence differs substantially from that expected by chance, given some previously seen data.
towards parameter-free data mining. most data mining algorithms require the setting of many input parameters. two main dangers of working with parameter-laden algorithms are the following. first, incorrect settings may cause an algorithm to fail in finding the true patterns. second, a perhaps more insidious problem is that the algorithm may report spurious patterns that do not really exist, or greatly overestimate the significance of the reported patterns. this is especially likely when the user fails to understand the role of parameters in the data mining process.data mining algorithms should have as few parameters as possible, ideally none. a parameter-free algorithm would limit our ability to impose our prejudices, expectations, and presumptions on the problem at hand, and would let the data itself speak to us. in this work, we show that recent results in bioinformatics and computational theory hold great promise for a parameter-free data-mining paradigm. the results are motivated by observations in kolmogorov complexity theory. however, as a practical matter, they can be implemented using any off-the-shelf compression algorithm with the addition of just a dozen or so lines of code. we will show that this approach is competitive or superior to the state-of-the-art approaches in anomaly/interestingness detection, classification, and clustering with empirical tests on time series/dna/text/video datasets.
bursty and hierarchical structure in streams. a fundamental problem in text data mining is to extract meaningful structure from document streams that arrive continuously over time. e-mail and news articles are two natural examples of such streams, each characterized by topics that appear, grow in intensity for a period of time, and then fade away. the published literature in a particular research field can be seen to exhibit similar phenomena over a much longer time scale. underlying much of the text mining work in this area is the following intuitive premise&mdash;that the appearance of a topic in a document stream is signaled by a &ldquo;burst of activity,&rdquo; with certain features rising sharply in frequency as the topic emerges.the goal of the present work is to develop a formal approach for modeling such &ldquo;bursts,&rdquo; in such a way that they can be robustly and efficiently identified, and can provide an organizational framework for analyzing the underlying content. the approach is based on modeling the stream using an infinite-state automaton, in which bursts appear naturally as state transitions&semi; it can be viewed as drawing an analogy with models from queueing theory for bursty network traffic. the resulting algorithms are highly efficient, and yield a nested representation of the set of bursts that imposes a hierarchical structure on the overall stream. experiments with e-mail and research paper archives suggest that the resulting structures have a natural meaning in terms of the content that gave rise to them.
maximally informative k-itemsets and their efficient discovery. in this paper we present a new approach to mining binary data. we treat each binary feature (item) as a means of distinguishing two sets of examples. our interest is in selecting from the total set of items an itemset of specified size, such that the database is partitioned with as uniform a distribution over the parts as possible. to achieve this goal, we propose the use of joint entropy as a quality measure for itemsets, and refer to optimal itemsets of cardinality k as maximally informative k-itemsets. we claim that this approach maximises distinctive power, as well as minimises redundancy within the feature set. a number of algorithms is presented for computing optimal itemsets efficiently.
robust space transformations for distance-based operations. for many kdd operations, such as nearest neighbor search, distance-based clustering, and outlier detection, there is an underlying &kgr;-d data space in which each tuple/object is represented as a point in the space. in the presence of differing scales, variability, correlation, and/or outliers, we may get unintuitive results if an inappropriate space is used.the fundamental question that this paper addresses is: "what then is an appropriate space?" we propose using a robust space transformation called the donoho-stahel estimator. in the first half of the paper, we show the key properties of the estimator. of particular importance to kdd applications involving databases is the stability property, which says that in spite of frequent updates, the estimator does not: (a) change much, (b) lose its usefulness, or (c) require re-computation. in the second half, we focus on the computation of the estimator for high-dimensional databases. we develop randomized algorithms and evaluate how well they perform empirically. the novel algorithm we develop called the hybrid-random algorithm is, in most cases, at least an order of magnitude faster than the fixed-angle and subsampling algorithms.
mining e-commerce data: the good, the bad, and the ugly. organizations conducting electronic commerce (e-commerce) can greatly benefit from the insight that data mining of transactional and clickstream data provides. such insight helps not only to improve the electronic channel (e.g., a web site), but it is also a learning vehicle for the bigger organization conducting business at brick-and-mortar stores. the e-commerce site serves as an early alert system for emerging patterns and a laboratory for experimentation. for successful data mining, several ingredients are needed and e-commerce provides all the right ones (the good). web server logs, which are commonly used as the source of data for mining e-commerce data, were designed to debug web servers, and the data they provide is insufficient, requiring the use of heuristics to reconstruct events. moreover, many events are never logged in web server logs, limiting the source of data for mining (the bad). many of the problems of dealing with web server log data can be resolved by properly architecting the e-commerce sites to generate data needed for mining. even with a good architecture, however, there are challenging problems that remain hard to solve (the ugly). lessons and metrics based on mining real e-commerce data are presented.
local sparsity control for naive bayes with extreme misclassification costs. in applications of data mining characterized by highly skewed misclassification costs certain types of errors become virtually unacceptable. this limits the utility of a classifier to a range in which such constraints can be met. naive bayes, which has proven to be very useful in text mining applications due to high scalability, can be particularly affected. although its 0/1 loss tends to be small, its misclassifications are often made with apparently high confidence. aside from efforts to better calibrate naive bayes scores, it has been shown that its accuracy depends on document sparsity and feature selection can lead to marked improvement in classification performance. traditionally, sparsity is controlled globally, and the result for any particular document may vary. in this work we examine the merits of local sparsity control for naive bayes in the context of highly asymmetric misclassification costs. in experiments with three benchmark document collections we demonstrate clear advantages of document-level feature selection. in the extreme cost setting, multinomial naive bayes with local sparsity control is able to outperform even some of the recently proposed effective improvements to the naive bayes classifier. there are also indications that local feature selection may be preferable in different cost settings.
improved robustness of signature-based near-replica detection via lexicon randomization. detection of near duplicate documents is an important problem in many data mining and information filtering applications. when faced with massive quantities of data, traditional duplicate detection techniques relying on direct inter-document similarity computation (e.g., using the cosine measure) are often not feasible given the time and memory performance constraints. on the other hand, fingerprint-based methods, such as i-match, are very attractive computationally but may be brittle with respect to small changes to document content. we focus on approaches to near-replica detection that are based upon large-collection statistics and present a general technique of increasing their robustness via multiple lexicon randomization. in experiments with large web-page and spam-email datasets the proposed method is shown to consistently outperform traditional i-match, with the relative improvement in duplicate-document recall reaching as high as 40-60%. the large gains in detection accuracy are offset by only small increases in computational requirements.
efficient handling of high-dimensional feature spaces by randomized classifier ensembles. handling massive datasets is a difficult problem not only due to prohibitively large numbers of entries but in some cases also due to the very high dimensionality of the data. often, severe feature selection is performed to limit the number of attributes to a manageable size, which unfortunately can lead to a loss of useful information. feature space reduction may well be necessary for many stand-alone classifiers, but recent advances in the area of ensemble classifier techniques indicate that overall accurate classifier aggregates can be learned even if each individual classifier operates on incomplete "feature view" training data, i.e., such where certain input attributes are excluded. in fact, by using only small random subsets of features to build individual component classifiers, surprisingly accurate and robust models can be created. in this work we demonstrate how these types of architectures effectively reduce the feature space for submodels and groups of sub-models, which lends itself to efficient sequential and/or parallel implementations. experiments with a randomized version of adaboost are used to support our arguments, using the text classification task as an example.
learning to detect malicious executables in the wild. in this paper, we describe the development of a fielded application for detecting malicious executables in the wild. we gathered 1971 benign and 1651 malicious executables and encoded each as a training example using n-grams of byte codes as features. such processing resulted in more than 255 million distinct n-grams. after selecting the most relevant n-grams for prediction, we evaluated a variety of inductive methods, including naive bayes, decision trees, support vector machines, and boosting. ultimately, boosted decision trees outperformed other methods with an area under the roc curve of 0.996. results also suggest that our methodology will scale to larger collections of executables. to the best of our knowledge, ours is the only fielded application for this task developed using techniques from machine learning and data mining.
reducing the human overhead in text categorization. many applications in text processing require significant human effort for either labeling large document collections (when learning statistical models) or extrapolating rules from them (when using knowledge engineering). in this work, we describe away to reduce this effort, while retaining the methods' accuracy, by constructing a hybrid classifier that utilizes human reasoning over automatically discovered text patterns to complement machine learning. using a standard sentiment-classification dataset and real customer feedback data, we demonstrate that the resulting technique results in significant reduction of the human effort required to obtain a given classification accuracy. moreover, the hybrid text classifier also results in a significant boost in accuracy over machine-learning based classifiers when a comparable amount of labeled data is used.
determining an author's native language by mining a text for errors. in this paper, we show that stylistic text features can be exploited to determine an anonymous author's native language with high accuracy. specifically, we first use automatic tools to ascertain frequencies of various stylistic idiosyncrasies in a text. these frequencies then serve as features for support vector machines that learn to classify texts according to author native language.
a two-way visualization method for clustered data. we describe a novel approach to the visualization of hierarchical clustering that superimposes the classical dendrogram over a fully synchronized low-dimensional embedding, thereby gaining the benefits of both approaches. in a single image one can view all the clusters, examine the relations between them and study many of their properties. the method is based on an algorithm for low-dimensional embedding of clustered data, with the property that separation between all clusters is guaranteed, regardless of their nature. in particular, the algorithm was designed to produce embeddings that strictly adhere to a given hierarchical clustering of the data, so that every two disjoint clusters in the hierarchy are drawn separately.
measuring and extracting proximity in networks. measuring distance or some other form of proximity between objects is a standard data mining tool. connection subgraphs were recently proposed as a way to demonstrate proximity between nodes in networks. we propose a new way of measuring and extracting proximity in networks called "cycle free effective conductance"(cfec). our proximity measure can handle more than two endpoints, directed edges, is statistically well-behaved, and produces an effectiveness score for the computed subgraphs. we provide an efficien talgorithm. also, we report experimental results and show examples for three large network data sets: a telecommunications calling graph, the imdb actors graph, and an academic co-authorship network.
proximus: a framework for analyzing very high dimensional discrete-attributed datasets. this paper presents an efficient framework for error-bounded compression of high-dimensional discrete attributed datasets. such datasets, which frequently arise in a wide variety of applications, pose some of the most significant challenges in data analysis. subsampling and compression are two key technologies for analyzing these datasets. proximus provides a technique for reducing large datasets into a much smaller set of representative patterns, on which traditional (expensive) analysis algorithms can be applied with minimal loss of accuracy. we show desirable properties of proximus in terms of runtime, scalability to large datasets, and performance in terms of capability to represent data in a compact form. we also demonstrate applications of proximus in association rule mining. in doing so, we establish proximus as a tool for preprocessing data before applying computationally expensive algorithms or as a tool for directly extracting correlated patterns. our experimental results show that use of the compressed data for association rule mining provides excellent precision and recall values (near 100%) across a range of support thresholds while reducing the time required for association rule mining drastically.
molecular feature mining in hiv data. we present the application of feature mining techniques to the developmental therapeutics program's aids antiviral screen database. the database consists of 43576 compounds, which were measured for their capability to protect human cells from hiv-1 infection. according to these measurements, the compounds were classified as either active, moderately active or inactive. the distribution of classes is extremely skewed: only 1.3 % of the molecules is known to be active, and 2.7 % is known to be moderately active.given this database, we were interested in molecular substructures (i.e., features) that are frequent in the active molecules, and infrequent in the inactives. in data mining terms, we focused on features with a minimum support in active compounds and a maximum support in inactive compounds. we analyzed the database using the levelwise version space algorithm that forms the basis of the inductive query and database system molfea (molecular feature miner). within this framework, it is possible to declaratively specify the features of interest, such as the frequency of features on (possibly different) datasets as well as on the generality and syntax of them. assuming that the detected substructures are causally related to biochemical mechanisms, it should be possible to facilitate the development of new pharmaceuticals with improved activities.
density-based clustering of uncertain data. in many different application areas, e.g. sensor databases, location based services or face recognition systems, distances between odjects have to be computed based on vague and uncertain data. commonly, the distances between these uncertain object descriptions are expressed by one numerical distance value. based on such single-valued distance functions standard data mining algorithms can work without any changes. in this paper, we propose to express the similarity between two fuzzy objects by distance probability functions. these fuzzy distance functions assign a probability value to each possible distance value. by integrating these fuzzy distance functions directly into data mining algorithms, the full information provided by these functions is exploited. in order to demonstrate the benefits of this general approach, we enhance the density-based clustering algorithm dbscan so that it can work directly on these fuzzy distance functions. in a detailed experimental evaluation based on artificial and real-world data sets, we show the characteristics and benefits of our new approach.
a parallel learning algorithm for text classification. text classification is the process of classifying documents into predefined categories based on their content. existing supervised learning algorithms to automatically classify text need sufficient labeled documents to learn accurately. applying the expectation-maximization (em) algorithm to this problem is an alternative approach that utilizes a large pool of unlabeled documents to augment the available labeled documents. unfortunately, the time needed to learn with these large unlabeled documents is too high. this paper introduces a novel parallel learning algorithm for text classification task. the parallel algorithm is based on the combination of the em algorithm and the naive bayes classifier. our goal is to improve the computational time in learning and classifying process. we studied the performance of our parallel algorithm on a large linux pc cluster called pirun cluster. we report both timing and accuracy results. these results indicate that the proposed parallel algorithm is capable of handling large document collections.
a multiple tree algorithm for the efficient association of asteroid observations. in this paper we examine the problem of efficiently finding sets of observations that conform to a given underlying motion model. while this problem is often phrased as a tracking problem, where it is called track initiation, it is useful in a variety of tasks where we want to find correspondences or patterns in spatial-temporal data. unfortunately, this problem often suffers from a combinatorial explosion in the number of potential sets that must be evaluated. we consider the problem with respect to large-scale asteroid observation data, where the goal is to find associations among the observations that correspond to the same underlying asteroid. in this domain, it is vital that we can efficiently extract the underlying associations.we introduce a new methodology for track initiation that exhaustively considers all possible linkages. we then introduce an exact tree-based algorithm for tractably finding all compatible sets of points. further, we extend this approach to use multiple trees, exploiting structure from several time steps at once. we compare this approach to a standard sequential approach and show how the use of multiple trees can provide a significant benefit.
a graph-theoretic approach to extract storylines from search results. we present a graph-theoretic approach to discover storylines from search results. storylines are windows that offer glimpses into interesting themes latent among the top search results for a query; they are different from, and complementary to, clusters obtained through traditional approaches. our framework is axiomatically developed and combinatorial in nature, based on generalizations of the maximum induced matching problem on bipartite graphs. the core algorithmic task involved is to mine for signature structures in a robust graph representation of the search results. we present a very fast algorithm for this task based on local search. experiments show that the collection of storylines extracted through our algorithm offers a concise organization of the wealth of information hidden beyond the first page of search results.
structure and evolution of online social networks. in this paper, we consider the evolution of structure within large online social networks. we present a series of measurements of two such networks, together comprising in excess of five million people and ten million friendship links, annotated with metadata capturing the time of every event in the life of the network. our measurements expose a surprising segmentation of these networks into three regions: singletons who do not participate in the network; isolated communities which overwhelmingly display star structure; and a giant component anchored by a well-connected core region which persists even in the absence of stars.we present a simple model of network growth which captures these aspects of component structure. the model follows our experimental results, characterizing users as either passive members of the network; inviters who encourage offline friends and acquaintances to migrate online; and linkers who fully participate in the social evolution of the network.
hierarchical topic segmentation of websites. in this paper, we consider the problem of identifying and segmenting topically cohesive regions in the url tree of a large website. each page of the website is assumed to have a topic label or a distribution on topic labels generated using a standard classifier. we develop a set of cost measures characterizing the benefit accrued by introducing a segmentation of the site based on the topic labels. we propose a general framework to use these measures for describing the quality of a segmentation; we also provide an efficient algorithm to find the best segmentation in this framework. extensive experiments on human-labeled data confirm the soundness of our framework and suggest that a judicious choice of cost measures allows the algorithm to perform surprisingly accurate topical segmentations.
clustering seasonality patterns in the presence of errors. clustering is a very well studied problem that attempts to group similar data points. most traditional clustering algorithms assume that the data is provided without measurement error. often, however, real world data sets have such errors and one can obtain estimates of these errors. we present a clustering method that incorporates information contained in these error estimates. we present a new distance function that is based on the distribution of errors in data. using a gaussian model for errors, the distance function follows a chi-square distribution and is easy to compute. this distance function is used in hierarchical clustering to discover meaningful clusters. the distance function is scale-invariant so that clustering results are independent of units of measuring data. in the special case when the error distribution is the same for each attribute of data points, the rank order of pair-wise distances is the same for our distance function and the euclidean distance function. the clustering method is applied to the seasonality estimation problem and experimental results are presented for the retail industry data as well as for simulated data, where it outperforms classical clustering methods.
algorithms for storytelling. we formulate a new data mining problem called storytelling as a generalization of redescription mining. in traditional redescription mining, we are given a set of objects and a collection of subsets defined over these objects. the goal is to view the set system as a vocabulary and identify two expressions in this vocabulary that induce the same set of objects. storytelling, on the other hand, aims to explicitly relate object sets that are disjoint (and hence, maximally dissimilar) by finding a chain of (approximate) redescriptions between the sets. this problem finds applications in bioinformatics, for instance, where the biologist is trying to relate a set of genes expressed in one experiment to another set, implicated in a different pathway. we outline an efficient storytelling implementation that embeds the cartwheels redescription mining algorithm in an a* search procedure, using the former to supply next move operators on search branches to the latter. this approach is practical and effective for mining large datasets and, at the same time, exploits the structure of partitions imposed by the given vocabulary. three application case studies are presented: a study of word overlaps in large english dictionaries, exploring connections between genesets in a bioinformatics dataset, and relating publications in the pubmed index of abstracts.
learning spatially variant dissimilarity (svad) measures. clustering algorithms typically operate on a feature vector representation of the data and find clusters that are compact with respect to an assumed (dis)similarity measure between the data points in feature space. this makes the type of clusters identified highly dependent on the assumed similarity measure. building on recent work in this area, we formally define a class of spatially varying dissimilarity measures and propose algorithms to learn the dissimilarity measure automatically from the data. the idea is to identify clusters that are compact with respect to the unknown spatially varying dissimilarity measure. our experiments show that the proposed algorithms are more stable and achieve better accuracy on various textual data sets when compared with similar algorithms proposed in the literature.
mining a stream of transactions for customer patterns. transaction data can arrive at a ferocious rate in the order that transactions are completed. the data contain an enormous amount of information about customers, not just transactions, but extracting up-to-date customer information from an ever changing stream of data and mining it in real-time is a challenge. this paper describes a statistically principled approach to designing short, accurate summaries or signatures of high dimensional customer behavior that can be kept current with a stream of transactions. a signature database can then be used for data mining and to provide approximate answers to many kinds of queries about current customers quickly and accurately, as an empirical study of the calling patterns of 96,000 wireless customers who made about 18 million wireless calls over a three month period shows.
combining partitions by probabilistic label aggregation. data clustering represents an important tool in exploratory data analysis. the lack of objective criteria render model selection as well as the identification of robust solutions particularly difficult. the use of a stability assessment and the combination of multiple clustering solutions represents an important ingredient to achieve the goal of finding useful partitions. in this work, we propose a novel way of combining multiple clustering solutions for both, hard and soft partitions: the approach is based on modeling the probability that two objects are grouped together. an efficient em optimization strategy is employed in order to estimate the model parameters. our proposal can also be extended in order to emphasize the signal more strongly by weighting individual base clustering solutions according to their consistency with the prediction for previously unseen objects. in addition to that, the probabilistic model supports an out-of-sample extension that (i) makes it possible to assign previously unseen objects to classes of the combined solution and (ii) renders the efficient aggregation of solutions possible. in this work, we also shed some light on the usefulness of such combination approaches. in the experimental result section, we demonstrate the competitive performance of our proposal in comparison with other recently proposed methods for combining multiple classifications of a finite data set.
the data mining approach to automated software testing. in today's industry, the design of software tests is mostly based on the testers' expertise, while test automation tools are limited to execution of pre-planned tests only. evaluation of test outputs is also associated with a considerable effort by human testers who often have imperfect knowledge of the requirements specification. not surprisingly, this manual approach to software testing results in heavy losses to the world's economy. the costs of the so-called "catastrophic" software failures (such as mars polar lander shutdown in 1999) are even hard to measure. in this paper, we demonstrate the potential use of data mining algorithms for automated induction of functional requirements from execution data. the induced data mining models of tested software can be utilized for recovering missing and incomplete specifications, designing a minimal set of regression tests, and evaluating the correctness of software outputs when testing new, potentially flawed releases of the system. to study the feasibility of the proposed approach, we have applied a novel data mining algorithm called info-fuzzy network (ifn) to execution data of a general-purpose code for solving partial differential equations. after being trained on a relatively small number of randomly generated input-output examples, the model constructed by the ifn algorithm has shown a clear capability to discriminate between correct and faulty versions of the program.
new em derived from kullback-leibler divergence. we introduce a new em framework in which it is possible not only to optimize the model parameters but also the number of model components. a key feature of our approach is that we use nonparametric density estimation to improve parametric density estimation in the em framework. while the classical em algorithm estimates model parameters empirically using the data points themselves, we estimate them using nonparametric density estimates.there exist many possible applications that require optimal adjustment of model components. we present experimental results in two domains. one is polygonal approximation of laser range data, which is an active research topic in robot navigation. the other is grouping of edge pixels to contour boundaries, which still belongs to unsolved problems in computer vision.
similarity analysis on government regulations. government regulations are semi-structured text documents that are often voluminous, heavily cross-referenced between provisions and even ambiguous. multiple sources of regulations lead to difficulties in both understanding and complying with all applicable codes. in this work, we propose a framework for regulation management and similarity analysis. an online repository for legal documents is created with the help of text mining tool, and users can access regulatory documents either through the natural hierarchy of provisions or from a taxonomy generated by knowledge engineers based on concepts. our similarity analysis core identifies relevant provisions and brings them to the user's attention, and this is performed by utilizing both the hierarchical and referential structures of regulations to provide a better comparison between provisions. preliminary results show that our system reveals hidden similarities that are not apparent between provisions based on node content comparisons.
cryptographically private support vector machines. we propose private protocols implementing the kernel adatron and kernel perceptron learning algorithms, give private classification protocols and private polynomial kernel computation protocols. the new protocols return their outputs - either the kernel value, the classifier or the classifications - in encrypted form so that they can be decrypted only by a common agreement by the protocol participants. we show how to use the encrypted classifications to privately estimate many properties of the data and the classifier. the new svm classifiers are the first to be proven private according to the standard cryptographic definitions.
bias and controversy: beyond the statistical deviation. in this paper, we investigate how deviation in evaluation activities may reveal bias on the part of reviewers and controversy on the part of evaluated objects. we focus on a 'data-centric approach' where the evaluation data is assumed to represent the 'ground truth'. the standard statistical approaches take evaluation and deviation at face value. we argue that attention should be paid to the subjectivity of evaluation, judging the evaluation score not just on 'what is being said' (deviation), but also on 'who says it' (reviewer) as well as on 'whom it is said about' (object). furthermore, we observe that bias and controversy are mutually dependent, as there is more bias if there is higher deviation on a less controversial object. to address this mutual dependency, we propose a reinforcement model to identify bias and controversy. we test our model on real-life data to verify its applicability.
passenger-based predictive modeling of airline no-show rates. airlines routinely overbook flights based on the expectation that some fraction of booked passengers will not show for each flight. accurate forecasts of the expected number of no-shows for each flight can increase airline revenue by reducing the number of spoiled seats (empty seats that might otherwise have been sold) and the number of involuntary denied boardings at the departure gate. conventional no-show forecasting methods typically average the no-show rates of historically similar flights, without the use of passenger-specific information.we develop two classes of models to predict cabin-level no-show rates using specific information on the individual passengers booked on each flight. the first of these models computes the no-show probability for each passenger, using both the cabin-level historical forecast and the extracted passenger features as explanatory variables. this passenger-level model is implemented using three different predictive methods: a c4.5 decision-tree, a segmented naive bayes algorithm, and a new aggregation method for an ensemble of probabilistic models. the second cabin-level model is formulated using the desired cabin-level no-show rate as the response variable. inputs to this model include the predicted cabin-level no-show rates derived from the various passenger-level models, as well as simple statistics of the features of the cabin passenger population. the cabin-level model is implemented using either linear regression, or as a direct probability model with explicit incorporation of the cabin-level no-show rates derived from the passenger-level model outputs.the new passenger-based models are compared to a conventional historical model, using train and evaluation data sets taken from over 1 million passenger name records. standard metrics such as lift curves and mean-square cabin-level errors establish the improved accuracy of the passenger-based models over the historical model. all models are also evaluated using a simple revenue model, and it is shown that the cabin-level passenger-based model can produce between 0.4% and 3.2% revenue gain over the conventional model, depending on the revenue-model parameters.
feature bagging for outlier detection. outlier detection has recently become an important problem in many industrial and financial applications. in this paper, a novel feature bagging approach for detecting outliers in very large, high dimensional and noisy databases is proposed. it combines results from multiple outlier detection algorithms that are applied using different set of features. every outlier detection algorithm uses a small subset of features that are randomly selected from the original feature set. as a result, each outlier detector identifies different outliers, and thus assigns to all data records outlier scores that correspond to their probability of being outliers. the outlier scores computed by the individual outlier detection algorithms are then combined in order to find the better quality outliers. experiments performed on several synthetic and real life data sets show that the proposed methods for combining outputs from multiple outlier detection algorithms provide non-trivial improvements over the base algorithm.
effective localized regression for damage detection in large complex mechanical structures. in this paper, we propose a novel data mining technique for the efficient damage detection within the large-scale complex mechanical structures. every mechanical structure is defined by the set of finite elements that are called structure elements. large-scale complex structures may have extremely large number of structure elements, and predicting the failure in every single element using the original set of natural frequencies as features is exceptionally time-consuming task. traditional data mining techniques simply predict failure in each structure element individually using global prediction models that are built considering all data records. in order to reduce the time complexity of these models, we propose a localized clustering-regression based approach that consists of two phases: (1) building a local cluster around a data record of interest and (2) predicting an intensity of damage only in those structure elements that correspond to data records from the built cluster. for each test data record, we first build a cluster of data records from training data around it. then, for each data record that belongs to discovered cluster, we identify corresponding structure elements and we build a localized regression model for each of these structure elements. these regression models for specific structure elements are constructed using only a specific set of relevant natural frequencies and merely those data records that correspond to the failure of that structure element. experiments performed on the problem of damage prediction in a large electric transmission tower frame indicate that the proposed localized clustering-regression based approach is significantly more accurate and more computationally efficient than our previous hierarchical clustering approach, as well as global prediction models.
the distributed boosting algorithm. in this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneous databases that cannot be merged at a single location. our distributed boosting algorithm can also be used as a parallel classification technique, where a massive database that cannot fit into main computer memory is partitioned into disjoint subsets for a more efficient analysis. in the proposed method, at each boosting round the classifiers are first learned from disjoint datasets and then exchanged amongst the sites. finally the classifiers are combined into a weighted voting ensemble on each disjoint data set. the ensemble that is applied to an unseen test set represents an ensemble of ensembles built on all distributed sites. in experiments performed on four large data sets the proposed distributed boosting method achieved classification accuracy comparable or even slightly better than the standard boosting algorithm while requiring less memory and less computational time. in addition, the communication overhead of the distributed boosting algorithm is very small making it a viable alternative to the standard boosting for large-scale databases.
workload-aware anonymization. protecting data privacy is an important problem in microdata distribution. anonymization algorithms typically aim to protect individual privacy, with minimal impact on the quality of the resulting data. while the bulk of previous work has measured quality through one-size-fits-all measures, we argue that quality is best judged with respect to the workload for which the data will ultimately be used.this paper provides a suite of anonymization algorithms that produce an anonymous view based on a target class of workloads, consisting of one or more data mining tasks, as well as selection predicates. an extensive experimental evaluation indicates that this approach is often more effective than previous anonymization techniques.
simple and effective visual models for gene expression cancer diagnostics. in the paper we show that diagnostic classes in cancer gene expression data sets, which most often include thousands of features (genes), may be effectively separated with simple two-dimensional plots such as scatterplot and radviz graph. the principal innovation proposed in the paper is a method called vizrank, which is able to score and identify the best among possibly millions of candidate projections for visualizations. compared to recently much applied techniques in the field of cancer genomics that include neural networks, support vector machines and various ensemble-based approaches, vizrank is fast and finds visualization models that can be easily examined and interpreted by domain experts. our experiments on a number of gene expression data sets show that vizrank was always able to find data visualizations with a small number of (two to seven) genes and excellent class separation. in addition to providing grounds for gene expression cancer diagnosis, vizrank and its visualizations also identify small sets of relevant genes, uncover interesting gene interactions and point to outliers and potential misclassifications in cancer data sets.
sampling from large graphs. given a huge real graph, how can we derive a representative sample? there are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.), but several of them become impractical for large graphs. thus graph sampling is essential.the natural questions to ask are (a) which sampling method to use, (b) how small can the sample size be, and (c) how to scale up the measurements of the sample (e.g., the diameter), to get estimates for the large graph. the deeper, underlying question is subtle: how do we measure success?.we answer the above questions, and test our answers by thorough experiments on several, diverse datasets, spanning thousands nodes and edges. we consider several sampling methods, propose novel methods to check the goodness of sampling, and develop a set of scaling laws that describe relations between the properties of the original and the sample.in addition to the theoretical contributions, the practical conclusions from our work are: sampling strategies based on edge selection do not perform well; simple uniform random node selection performs surprisingly well. overall, best performing methods are the ones based on random-walks and "forest fire"; they match very accurately both static as well as evolutionary graph patterns, with sample sizes down to about 15% of the original graph.
graphs over time: densification laws, shrinking diameters and possible explanations. how do real graphs evolve over time? what are "normal" growth patterns in social, technological, and information networks? many studies have discovered patterns in static graphs, identifying properties in a single snapshot of a large network, or in a very small number of snapshots; these include heavy tails for in- and out-degree distributions, communities, small-world phenomena, and others. however, given the lack of information about network evolution over long periods, it has been hard to convert these findings into statements about trends over time.here we study a wide range of real graphs, and we observe some surprising phenomena. first, most of these graphs densify over time, with the number of edges growing super-linearly in the number of nodes. second, the average distance between nodes often shrinks over time, in contrast to the conventional wisdom that such distance parameters should increase slowly as a function of the number of nodes (like o(log n) or o(log(log n)).existing graph generation models do not exhibit these types of behavior, even at a qualitative level. we provide a new graph generator, based on a "forest fire" spreading process, that has a simple, intuitive justification, requires very few parameters (like the "flammability" of nodes), and produces graphs exhibiting the full range of properties observed both in prior work and in the present study.
incremental maintenance of quotient cube for median. data cube pre-computation is an important concept for supporting olap(online analytical processing) and has been studied extensively. it is often not feasible to compute a complete data cube due to the huge storage requirement. recently proposed quotient cube addressed this issue through a partitioning method that groups cube cells into equivalence partitions. such an approach is not only useful for distributive aggregate functions such as sum but can also be applied to the holistic aggregate functions like median.maintaining a data cube for holistic aggregation is a hard problem since its difficulty lies in the fact that history tuple values must be kept in order to compute the new aggregate when tuples are inserted or deleted. the quotient cube makes the problem harder since we also need to maintain the equivalence classes. in this paper, we introduce two techniques called addset data structure and sliding window to deal with this problem. we develop efficient algorithms for maintaining a quotient cube with holistic aggregation functions that takes up reasonably small storage space. performance study shows that our algorithms are effective, efficient and scalable over large databases.
mining risk patterns in medical data. in this paper, we discuss a problem of finding risk patterns in medical data. we define risk patterns by a statistical metric, relative risk, which has been widely used in epidemiological research. we characterise the problem of mining risk patterns as an optimal rule discovery problem. we study an anti-monotone property for mining optimal risk pattern sets and present an algorithm to make use of the property in risk pattern discovery. the method has been applied to a real world data set to find patterns associated with an allergic event for ace inhibitors. the algorithm has generated some useful results for medical researchers.
very sparse random projections. there has been considerable interest in random projections, an approximate algorithm for estimating distances between pairs of points in a high-dimensional vector space. let a in rn x d be our n points in d dimensions. the method multiplies a by a random matrix r in rd x k, reducing the d dimensions down to just k for speeding up the computation. r typically consists of entries of standard normal n(0,1). it is well known that random projections preserve pairwise distances (in the expectation). achlioptas proposed sparse random projections by replacing the n(0,1) entries in r with entries in -1,0,1 with probabilities 1/6, 2/3, 1/6, achieving a threefold speedup in processing time.we recommend using r of entries in -1,0,1 with probabilities 1/2√d, 1-1√d, 1/2√d for achieving a significant √d-fold speedup, with little loss in accuracy.
clustering moving objects. due to the advances in positioning technologies, the real time information of moving objects becomes increasingly available, which has posed new challenges to the database research. as a long-standing technique to identify overall distribution patterns in data, clustering has achieved brilliant successes in analyzing static datasets. in this paper, we study the problem of clustering moving objects, which could catch interesting pattern changes during the motion process and provide better insight into the essence of the mobile data points. in order to catch the spatial-temporal regularities of moving objects and handle large amounts of data, micro-clustering [20] is employed. efficient techniques are proposed to keep the moving micro-clusters geographically small. important events such as the collisions among moving micro-clusters are also identified. in this way, high quality moving micro-clusters are dynamically maintained, which leads to fast and competitive clustering result at any given time instance. we validate our approaches with a through experimental evaluation, where orders of magnitude improvement on running time is observed over normal k-means clustering method [14].
an integrated framework on mining logs files for computing system management. traditional approaches to system management have been largely based on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. this has been well known and experienced as a cumbersome, labor intensive, and error prone process. in addition, this process is difficult to keep up with the rapidly changing environments. in this paper, we will describe our research efforts on establishing an integrated framework for mining system log files for automatic management. in particular, we apply text mining techniques to categorize messages in log files into common situations, improve categorization accuracy by considering the temporal characteristics of log messages, develop temporal mining techniques to discover the relationships between different events, and utilize visualization tools to evaluate and validate the interesting temporal patterns for system management.
automated detection of frontal systems from numerical model-generated data. fronts are significant meteorological phenomena of interest. the extraction of frontal systems from observations and model data can greatly benefit many kinds of research and applications in atmospheric sciences. due to the huge amount of observational and model data available nowadays, automated extraction of front systems is necessary. this paper presents an automated method to detect frontal systems from numerical model-generated data. in this method, a frontal system is characterized by a vector of features, comprised of parameters derived from the model wind field. k-means clustering is applied to the generated sample set of the feature vectors to partition the feature space and to identify clusters representing the fronts. the probability that a model grid belongs to a front is estimated based on its feature vector. the probability image is generated corresponding to the model grids. a hierarchical thresholding technique is applied to the probability image to identify the frontal systems and a gaussian bayes classifier is trained to determine the proper threshold value. this is followed by post processing to filter out false signatures. experiment results from this method are in good agreement with the ones identified by the domain experts.
construct robust rule sets for classification. we study the problem of computing classification rule sets from relational databases so that accurate predictions can be made on test data with missing attribute values. traditional classifiers perform badly when test data are not as complete as the training data because they tailor a training database too much. we introduce the concept of one rule set being more robust than another, that is, able to make more accurate predictions on test data with missing attribute values. we show that the optimal class association rule set is as robust as the complete class association rule set. we then introduce the k-optimal rule set, which provides predictions exactly the same as the optimal class association rule set on test data with up to k missing attribute values. this leads to a hierarchy of k-optimal rule sets in which decreasing size corresponds to decreasing robustness, and they all more robust than a traditional classification rule set. we introduce two methods to find k-optimal rule sets, i.e. an optimal association rule mining approach and a heuristic approximate approach. we show experimentally that a k-optimal rule set generated by the optimal association rule mining approach performs better than that by the heuristic approximate approach and both rule sets perform significantly better than a typical classification rule set (c4.5rules) on incomplete test data.
mining heterogeneous gene expression data with time lagged recurrent neural networks. heterogeneous types of gene expressions may provide a better insight into the biological role of gene interaction with the environment, disease development and drug effect at the molecular level. in this paper for both exploring and prediction purposes a time lagged recurrent neural network with trajectory learning is proposed for identifying and classifying the gene functional patterns from the heterogeneous nonlinear time series microarray experiments. the proposed procedures identify gene functional patterns from the dynamics of a state-trajectory learned in the heterogeneous time series and the gradient information over time. also, the trajectory learning with back-propagation through time algorithm can recognize gene expression patterns vary over time. this may reveal much more information about the regulatory network underlying gene expressions. the analyzed data were extracted from spotted dna microarrays in the budding yeast expression measurements, produced by eisen et al. the gene matrix contained 79 experiments over a variety of heterogeneous experiment conditions. the number of recognized gene patterns in our study ranged from two to ten and were divided into three cases. optimal network architectures with different memory structures were selected based on akaike and bayesian information statistical criteria using two-way factorial design. the optimal model performance was compared to other popular gene classification algorithms such as nearest neighbor, support vector machine, and self-organized map. the reliability of the performance was verified with multiple iterated runs.
a robust and efficient clustering algorithm based on cohesion self-merging. data clustering has attracted a lot of research attention in the field of computational statistics and data mining. in most related studies, the dissimilarity between two clusters is defined as the distance between their centroids, or the distance between two closest (or farthest) data points. however, all of these measurements are vulnerable to outliers, and removing the outliers precisely is yet another difficult task. in view of this, we propose a new similarity measurement referred to as cohesion, to measure the inter-cluster distances. by using this new measurement of cohesion, we design a two-phase clustering algorithm, called cohesion-based self-merging (abbreviated as csm), which runs in linear time to the size of input data set. combining the features of partitional and hierarchical clustering methods, algorithm csm partitions the input data set into several small subclusters in the first phase, and then continuously merges the subclusters based on cohesion in a hierarchical manner in the second phase. as shown by our performance studies, the cohesion-based clustering is very robust and possesses the excellent tolerance to outliers in various workloads. more importantly, algorithm csm is shown to be able to cluster the data sets of arbitrary shapes very efficiently, and provide better clustering results than those by prior methods.index terms: data mining, data clustering, hierarchical clustering, partitional clustering
discovering informative content blocks from web documents. in this paper, we propose a new approach to discover informative contents from a set of tabular documents (or web pages) of a web site. our system, infodiscoverer, first partitions a page into several content blocks according to html tag <table> in a web page. based on the occurrence of the features (terms) in the set of pages, it calculates entropy value of each feature. according to the entropy value of each feature in a content block, the entropy value of the block is defined. by analyzing the information measure, we propose a method to dynamically select the entropy-threshold that partitions blocks into either informative or redundant. informative content blocks are distinguished parts of the page, whereas redundant content blocks are common parts. based on the answer set generated from 13 manually tagged news web sites with a total of 26,518 web pages, experiments show that both recall and precision rates are greater than 0.956. that is, using the approach, informative blocks (news articles) of these sites can be automatically separated from semantically redundant contents such as advertisements, banners, navigation panels, news categories, etc. by adopting infodiscoverer as the preprocessor of information retrieval and extraction applications, the retrieval and extracting precision will be increased, and the indexing size and extracting complexity will also be reduced.
visually mining and monitoring massive time series. moments before the launch of every space vehicle, engineering discipline specialists must make a critical go/no-go decision. the cost of a false positive, allowing a launch in spite of a fault, or a false negative, stopping a potentially successful launch, can be measured in the tens of millions of dollars, not including the cost in morale and other more intangible detriments. the aerospace corporation is responsible for providing engineering assessments critical to the go/no-go decision for every department of defense space vehicle. these assessments are made by constantly monitoring streaming telemetry data in the hours before launch. we will introduce viztree, a novel time-series visualization tool to aid the aerospace analysts who must make these engineering assessments. viztree was developed at the university of california, riverside and is unique in that the same tool is used for mining archival data and monitoring incoming live telemetry. the use of a single tool for both aspects of the task allows a natural and intuitive transfer of mined knowledge to the monitoring task. our visualization approach works by transforming the time series into a symbolic representation, and encoding the data in a modified suffix tree in which the frequency and other properties of patterns are mapped onto colors and other visual properties. we demonstrate the utility of our system by comparing it with state-of-the-art batch algorithms on several real and synthetic datasets.
distributed data mining in a chain store database of short transactions. in this paper, we broaden the horizon of traditional rule mining by introducing a new framework of causality rule mining in a distributed chain store database. specifically, the causality rule explored in this paper consists of a sequence of triggering events and a set of consequential events, and is designed with the capability of mining non-sequential, inter-transaction information. hence, the causality rule mining provides a very general framework for rule derivation. note, however, that the procedure of causality rule mining is very costly particularly in the presence of a huge number of candidate sets and a distributed database, and in our opinion, cannot be dealt with by direct extensions from existing rule mining methods. consequently, we devise in this paper a series of level matching algorithms, including level matching (abbreviatedly as lm), level matching with selective scan (abbreviatedly as lms), and distributed level matching (abbreviatedly as distibuted lm), to minimize the computing cost needed for the distributed data mining of causality rules. in addition, the phenomena of time window constraints are also taken into consideration for the development of our algorithms. as a result of properly employing the technologies of level matching and selective scan, the proposed algorithms present good efficiency and scalability in the mining of local and global causality rules. scale-up experiments show that the proposed algorithms scale well with the number of sites and the number of customer transactions.index terms: knowledge discovery, distributed data mining causality rules, triggering events, consequential events
induction of semantic classes from natural language text. many applications dealing with textual information require classification of words into semantic classes (or concepts). however, manually constructing semantic classes is a tedious task. in this paper, we present an algorithm, unicon, for unsupervised induction of concepts. some advantages of unicon over previous approaches include the ability to classify words with low frequency counts, the ability to cluster a large number of elements in a high-dimensional space, and the ability to classify previously unknown words into existing clusters. furthermore, since the algorithm is unsupervised, a set of concepts may be constructed for any corpus.
dirt @sbt@discovery of inference rules from text. in this paper, we propose an unsupervised method for discovering inference rules from text, such as "x is author of y &ap; x wrote y", "x solved y &ap; x found a solution to y", and "x caused y &ap; y is triggered by x". inference rules are extremely important in many fields such as natural language processing, information retrieval, and artificial intelligence in general. our algorithm is based on an extended version of harris' distributional hypothesis, which states that words that occurred in the same contexts tend to be similar. instead of using this hypothesis on words, we apply it to paths in the dependency trees of a parsed corpus.
maximum profit mining and its application in software development. while most software defects (i.e., bugs) are corrected and tested as part of the lengthy software development cycle, enterprise software vendors often have to release software products before all reported defects are corrected, due to deadlines and limited resources. a small number of these defects will be escalated by customers and they must be resolved immediately by the software vendors at a very high cost. in this paper, we develop an escalation prediction (ep) system that mines historic defect report data and predict the escalation risk of the defects for maximum net profit. more specifically, we first describe a simple and general framework to convert the maximum net profit problem to cost-sensitive learning. we then apply and compare several well-known cost-sensitive learning approaches for ep. our experiments suggest that the cost-sensitive decision tree is the best method for producing the highest positive net profit and comprehensible results. the ep system has been deployed successfully in the product group of an enterprise software vendor.
collusion in the u.s. crop insurance program: applied data mining. this paper quantitatively analyzes indicators of agent (policy seller), adjuster (indemnity claim adjuster), producer (policy purchaser/holder) indemnity behavior suggestive of collusion in the united states department of agriculture (usda) risk management agency (rma) national crop insurance program. according to guidance from the federal law and using six indicator variables of indemnity behavior, those entities equal to or exceeding 150% of the county mean (computed using a simple jackknife procedure) on all entity-relevant indicators were flagged as "anomalous." log linear analysis was used to test (i) hierarchical node-node arrangements and (2) a non-recursive model of node information sharing. chi-square distributed deviance statistic identified the optimal log linear model. the results of the applied data mining technique used here suggest that the non-recursive triplet and agent-producer doublet collusion probabilistically accounts for the greatest proportion of waste, fraud, and abuse in the federal crop insurance program. triplet and agent-producer doublets need detailed investigation for possible collusion. hence, this data mining technique provided a high level of confidence when 24 million records were quantitatively analyzed for possible fraud, waste, or other abuse of the crop insurance program administered by the usda rma, and suspect entities reported to usda. this data mining technique can be applied where vast amounts of data are available to detect patterns of collusion or conspiracy as may be of interest to the criminal justice or intelligence agencies.
gplag: detection of software plagiarism by program dependence graph analysis. along with the blossom of open source projects comes the convenience for software plagiarism. a company, if less self-disciplined, may be tempted to plagiarize some open source projects for its own products. although current plagiarism detection tools appear sufficient for academic use, they are nevertheless short for fighting against serious plagiarists. for example, disguises like statement reordering and code insertion can effectively confuse these tools. in this paper, we develop a new plagiarism detection tool, called gplag, which detects plagiarism by mining program dependence graphs (pdgs). a pdg is a graphic representation of the data and control dependencies within a procedure. because pdgs are nearly invariant during plagiarism, gplag is more effective than state-of-the-art tools for plagiarism detection. in order to make gplag scalable to large programs, a statistical lossy filter is proposed to prune the plagiarism search space. experiment study shows that gplag is both effective and efficient: it detects plagiarism that easily slips over existing tools, and it usually takes a few seconds to find (simulated) plagiarism in programs having thousands of lines of code.
mining data records in web pages. a large amount of information on the web is contained in regularly structured objects, which we call data records. such data records are important because they often present the essential information of their host pages, e.g., lists of products or services. it is useful to mine such data records in order to extract information from them to provide value-added services. existing automatic techniques are not satisfactory because of their poor accuracies. in this paper, we propose a more effective technique to perform the task. the technique is based on two observations about data records on the web and a string matching algorithm. the proposed technique is able to mine both contiguous and non-contiguous data records. our experimental results show that the proposed technique outperforms existing techniques substantially.
identifying non-actionable association rules. building predictive models and finding useful rules are two important tasks of data mining. while building predictive models has been well studied, finding useful rules for action still presents a major problem. a main obstacle is that many data mining algorithms often produce too many rules. existing research has shown that most of the discovered rules are actually redundant or insignificant. pruning techniques have been developed to remove those spurious and/or insignificant rules. in this paper, we argue that being a significant rule (or a non-redundant rule), however, does not mean that it is a potentially useful rule for action. many significant rules (unpruned rules) are in fact not actionable. this paper studies this issue and presents an efficient algorithm to identify these non-actionable rules. experiment results on many real-life datasets show that the number of non-actionable rules is typically quite large. the proposed technique thus enables the user to focus on fewer rules and to be assured that the remaining rules are non-redundant and potentially useful for action.
discovering the set of fundamental rule changes. the world around us changes constantly. knowing what has changed is an important part of our lives. for businesses, recognizing changes is also crucial. it allows businesses to adapt themselves to the changing market needs. in this paper, we study changes of association rules from one time period to another. one approach is to compare the supports and/or confidences of each rule in the two time periods and report the differences. this technique, however, is too simplistic as it tends to report a huge number of rule changes, and many of them are, in fact, simply the snowball effect of a small subset of fundamental changes. here, we present a technique to highlight the small subset of fundamental changes. a change is fundamental if it cannot be explained by some other changes. the proposed technique has been applied to a number of real-life datasets. experiments results show that the number of rules whose changes are unexplainable is quite small (about 20% of the total number of changes discovered), and many of these unexplainable changes reflect some fundamental shifts in the application domain.
incremental context mining for adaptive document classification. automatic document classification (dc) is essential for the management of information and knowledge. this paper explores two practical issues in dc: (1) each document has its context of discussion, and (2) both the content and vocabulary of the document database is intrinsically evolving. the issues call for adaptive document classification (adc) that adapts a dc system to the evolving contextual requirement of each document category, so that input documents may be classified based on their contexts of discussion. we present an incremental context mining technique to tackle the challenges of adc. theoretical analyses and empirical results show that, given a text hierarchy, the mining technique is efficient in incrementally maintaining the evolving contextual requirement of each category. based on the contextual requirements mined by the system, higher-precision dc may be achieved with better efficiency.
on computing, storing and querying frequent patterns. extensive efforts have been devoted to developing efficient algorithms for mining frequent patterns. however, frequent pattern mining remains a time-consuming process, especially for very large datasets. it is therefore desirable to adopt a "mining once and using many times" strategy. unfortunately, there has been little work reported on managing and organizing a large set of patterns for future use. in this paper, we propose a disk-based data structure, cfp-tree (condensed frequent pattern tree), for organizing frequent patterns discovered from transactional databases. in addition to an efficient algorithm for cfp-tree construction, we also developed algorithms to efficiently support two important types of queries, namely queries with minimum support constraints and queries with item constraints, against the stored patterns, as these two types of queries are basic building blocks for complex frequent pattern related mining tasks. comprehensive experimental study has been conducted to demonstrate the effectiveness of cfp-tree and efficiency of related algorithms.
discovering unexpected information from your competitors' web sites. ever since the beginning of the web, finding useful information from the web has been an important problem. existing approaches include keyword-based search, wrapper-based information extraction, web query and user preferences. these approaches essentially find information that matches the user's explicit specifications. this paper argues that this is insufficient. there is another type of information that is also of great interest, i.e., unexpected information, which is unanticipated by the user. finding unexpected information is useful in many applications. for example, it is useful for a company to find unexpected information bout its competitors, e.g., unexpected services and products that its competitors offer. with this information, the company can learn from its competitors and/or design counter measures to improve its competitiveness. since the number of pages of a typical commercial site is very large and there are also many relevant sites (competitors), it is very difficult for a human user to view each page to discover the unexpected information. automated assistance is needed. in this paper, we propose a number of methods to help the user find various types of unexpected information from his/her competitors' web sites. experiment results show that these techniques are very useful in practice and also efficient.
mining frequent item sets by opportunistic projection. in this paper, we present a novel algorithm opportune project for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. our algorithm is fundamentally different from those proposed in the past in that it opportunistically chooses between two different structures, array-based or tree-based, to represent projected transaction subsets, and heuristically decides to build unfiltered pseudo projection or to make a filtered copy according to features of the subsets. more importantly, we propose novel methods to build tree-based pseudo projections and array-based unfiltered projections for projected transaction subsets, which makes our algorithm both cpu time efficient and memory saving. basically, the algorithm grows the frequent item set tree by depth first search, whereas breadth first search is used to build the upper portion of the tree if necessary. we test our algorithm versus several other algorithms on real world datasets, such as bms-pos, and on ibm artificial datasets. the empirical results show that our algorithm is not only the most efficient on both sparse and dense databases at all levels of support threshold, but also highly scalable to very large databases.
a framework for ontology-driven subspace clustering. traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. while domain knowledge is always the best way to justify clustering, few clustering algorithms have ever take domain knowledge into consideration. in this paper, the domain knowledge is represented by hierarchical ontology. we develop a framework by directly incorporating domain knowledge into clustering process, yielding a set of clusters with strong ontology implication. during the clustering process, ontology information is utilized to efficiently prune the exponential search space of the subspace clustering algorithms. meanwhile, the algorithm generates automatical interpretation of the clustering result by mapping the natural hierarchical organized subspace clusters with significant categorical enrichment onto the ontology hierarchy. our experiments on a set of gene expression data using gene ontology demonstrate that our pruning technique driven by ontology significantly improve the clustering performance with minimal degradation of the cluster quality. meanwhile, many hierarchical organizations of gene clusters corresponding to a sub-hierarchies in gene ontology were also successfully captured.
the ioc algorithm: efficient many-class non-parametric classification for high-dimensional data. this paper is about a variant of k nearest neighbor classification on large many-class high dimensional datasets.k nearest neighbor remains a popular classification technique, especially in areas such as computer vision, drug activity prediction and astrophysics. furthermore, many more modern classifiers, such as kernel-based bayes classifiers or the prediction phase of svms, require computational regimes similar to k-nn. we believe that tractable k-nn algorithms therefore continue to be important.this paper relies on the insight that even with many classes, the task of finding the majority class among the k nearest neighbors of a query need not require us to explicitly find those k nearest neighbors. this insight was previously used in (liu et al., 2003) in two algorithms called kns2 and kns3 which dealt with fast classification in the case of two classes. in this paper we show how a different approach, ioc (standing for the international olympic committee) can apply to the case of n classes where n > 2.ioc assumes a slightly different processing of the datapoints in the neighborhood of the query. this allows it to search a set of metric trees, one for each class. during the searches it is possible to quickly prune away classes that cannot possibly be the majority.we give experimental results on datasets of up to 5.8 x 105 records and 1.5 x 103 attributes, frequently showing an order of magnitude acceleration compared with each of (i) conventional linear scan, (ii) a well-known independent sr-tree implementation of conventional k-nn and (iii) a highly optimized conventional k-nn metric tree search.
rule interestingness analysis using olap operations. the problem of interestingness of discovered rules has been investigated by many researchers. the issue is that data mining algorithms often generate too many rules, which make it very hard for the user to find the interesting ones. over the years many techniques have been proposed. however, few have made it to real-life applications. since august 2004, we have been working on a major application for motorola. the objective is to find causes of cellular phone call failures from a large amount of usage log data. class association rules have been shown to be suitable for this type of diagnostic data mining application. we were also able to put several existing interestingness methods to the test, which revealed some major shortcomings. one of the main problems is that most existing methods treat rules individually. however, we discovered that users seldom regard a single rule to be interesting by itself. a rule is only interesting in the context of some other rules. furthermore, in many cases, each individual rule may not be interesting, but a group of them together can represent an important piece of knowledge. this led us to discover a deficiency of the current rule mining paradigm. using non-zero minimum support and non-zero minimum confidence eliminates a large amount of context information, which makes rule analysis difficult. this paper proposes a novel approach to deal with all of these issues, which casts rule analysis as olap operations and general impression mining. this approach enables the user to explore the knowledge space to find useful knowledge easily and systematically. it also provides a natural framework for visualization. as an evidence of its effectiveness, our system, called opportunity map, based on these ideas has been deployed, and it is in daily use in motorola for finding actionable knowledge from its engineering and other types of data sets.
clustering pair-wise dissimilarity data into partially ordered sets. ontologies represent data relationships as hierarchies of possibly overlapping classes. ontologies are closely related to clustering hierarchies, and in this article we explore this relationship in depth. in particular, we examine the space of ontologies that can be generated by pairwise dissimilarity matrices. we demonstrate that classical clustering algorithms, which take dissimilarity matrices as inputs, do not incorporate all available information. in fact, only special types of dissimilarity matrices can be exactly preserved by previous clustering methods. we model ontologies as a partially ordered set (poset) over the subset relation. in this paper, we propose a new clustering algorithm, that generates a partially ordered set of clusters from a dissimilarity matrix.
fast mining of high dimensional expressive contrast patterns using zero-suppressed binary decision diagrams. patterns of contrast are a very important way of comparing multi-dimensional datasets. such patterns are able to capture regions of high difference between two classes of data, and are useful for human experts and the construction of classifiers. however, mining such patterns is particularly challenging when the number of dimensions is large. this paper describes a new technique for mining several varieties of contrast pattern, based on the use of zero-suppressed binary decision diagrams (zbdds), a powerful data structure for manipulating sparse data. we study the mining of both simple contrast patterns, such as emerging patterns, and more novel and complex contrasts, which we call disjunctive emerging patterns. a performance study demonstrates our zbdd technique is highly scalable, substantially improves on state of the art mining for emerging patterns and can be effective for discovering complex contrasts from datasets with thousands of attributes.
unsupervised learning on k-partite graphs. various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. however, the research on mining the hidden structures from a k-partite graph is still limited and preliminary. in this paper, we propose a general model, the relation summary network, to find the hidden structures (the local cluster structures and the global community structures) from a k-partite graph. the model provides a principal framework for unsupervised learning on k-partite graphs of various structures. under this model, we derive a novel algorithm to identify the hidden structures of a k-partite graph by constructing a relation summary network to approximate the original k-partite graph under a broad range of distortion measures. experiments on both synthetic and real datasets demonstrate the promise and effectiveness of the proposed model and algorithm. we also establish the connections between existing clustering approaches and the proposed model to provide a unified view to the clustering approaches.
co-clustering by block value decomposition. dyadic data matrices, such as co-occurrence matrix, rating matrix, and proximity matrix, arise frequently in various important applications. a fundamental problem in dyadic data analysis is to find the hidden block structure of the data matrix. in this paper, we present a new co-clustering framework, block value decomposition(bvd), for dyadic data, which factorizes the dyadic data matrix into three components, the row-coefficient matrix r, the block value matrix b, and the column-coefficient matrix c. under this framework, we focus on a special yet very popular case -- non-negative dyadic data, and propose a specific novel co-clustering algorithm that iteratively computes the three decomposition matrices based on the multiplicative updating rules. extensive experimental evaluations also demonstrate the effectiveness and potential of this framework as well as the specific algorithms for co-clustering, and in particular, for discovering the hidden block structure in the dyadic data.
adversarial learning. many classification tasks, such as spam filtering, intrusion detection, and terrorism detection, are complicated by an adversary who wishes to avoid detection. previous work on adversarial classification has made the unrealistic assumption that the attacker has perfect knowledge of the classifier [2]. in this paper, we introduce the adversarial classifier reverse engineering (acre) learning problem, the task of learning sufficient information about a classifier to construct adversarial attacks. we present efficient algorithms for reverse engineering linear classifiers with either continuous or boolean features and demonstrate their effectiveness using real data from the domain of spam filtering.
learning nonstationary models of normal network traffic for detecting novel attacks. traditional intrusion detection systems (ids) detect attacks by comparing current behavior to signatures of known attacks. one main drawback is the inability of detecting new attacks which do not have known signatures. in this paper we propose a learning algorithm that constructs models of normal behavior from attack-free network traffic. behavior that deviates from the learned normal model signals possible novel attacks. our ids is unique in two respects. first, it is nonstationary, modeling probabilities based on the time since the last event rather than on average rate. this prevents alarm floods. second, the ids learns protocol vocabularies (at the data link through application layers) in order to detect unknown attacks that attempt to exploit implementation errors in poorly tested features of the target software. on the 1999 darpa ids evaluation data set [9], we detect 70 of 180 attacks (with 100 false alarms), about evenly divided between user behavioral anomalies (ip addresses and ports, as modeled by most other systems) and protocol anomalies. because our methods are unconventional there is a significant non-overlap of our ids with the original darpa participants, which implies that they could be combined to increase coverage.
tensor-cur decompositions for tensor-based data. motivated by numerous applications in which the data may be modeled by a variable subscripted by three or more indices, we develop a tensor-based extension of the matrix cur decomposition. the tensor-cur decomposition is most relevant as a data analysis tool when the data consist of one mode that is qualitatively different than the others. in this case, the tensor-cur decomposition approximately expresses the original data tensor in terms of a basis consisting of underlying subtensors that are actual data elements and thus that have natural interpretation in terms ofthe processes generating the data. in order to demonstrate the general applicability of this tensor decomposition, we apply it to problems in two diverse domains of data analysis: hyperspectral medical image analysis and consumer recommendation system analysis. in the hyperspectral data application, the tensor-cur decomposition is used to compress the data, and we show that classification quality is not substantially reduced even after substantial data compression. in the recommendation system application, the tensor-cur decomposition is used to reconstruct missing entries in a user-product-product preference tensor, and we show that high quality recommendations can be made on the basis of a small number of basis users and a small number of product-product comparisons from a new user.
mining, indexing, and querying historical spatiotemporal data. in many applications that track and analyze spatiotemporal data, movements obey periodic patterns; the objects follow the same routes (approximately) over regular time intervals. for example, people wake up at the same time and follow more or less the same route to their work everyday. the discovery of hidden periodic patterns in spatiotemporal data, apart from unveiling important information to the data analyst, can facilitate data management substantially. based on this observation, we propose a framework that analyzes, manages, and queries object movements that follow such patterns. we define the spatiotemporal periodic pattern mining problem and propose an effective and fast mining algorithm for retrieving maximal periodic patterns. we also devise a novel, specialized index structure that can benefit from the discovered patterns to support more efficient execution of spatiotemporal queries. we evaluate our methods experimentally using datasets with object trajectories that exhibit periodicity.
estimating missed actual positives using independent classifiers. data mining is increasingly being applied in environments having very high rate of data generation like network intrusion detection [7], where routers generate about 300,000 -- 500,000 connections every minute. in such rare class data domains, the cost of missing a rare-class instance is much higher than that of other classes. however, the high cost for manual labeling of instances, the high rate at which data is collected as well as real-time response constraints do not always allow one to determine the actual classes for the collected unlabeled datasets. in our previous work [9], this problem of missed false negatives was explained in context of two different domains -- "network intrusion detection" and "business opportunity classification". in such cases, an estimate for the number of such missed high-cost, rare instances will aid in the evaluation of the performance of the modeling technique (e.g. classification) used. a capture-recapture method was used for estimating false negatives, using two or more learning methods (i.e. classifiers). this paper focuses on the dependence between the class labels assigned by such learners. we define the conditional independence for classifiers given a class label and show its relation to the conditional independence of the features sets (used by the classifiers) given a class label. the later is a computationally expensive problem and hence, a heuristic algorithm is proposed for obtaining conditionally independent (or less dependent) feature sets for the classifiers. initial results of this algorithm on synthetic datasets are promising and further research is being pursued.
visual data mining using principled projection algorithms and information visualization techniques. we introduce a flexible visual data mining framework which combines advanced projection algorithms from the machine learning domain and visual techniques developed in the information visualization domain. the advantage of such an interface is that the user is directly involved in the data mining process. we integrate principled projection algorithms, such as generative topographic mapping (gtm) and hierarchical gtm (hgtm), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates and billboarding, to provide a visual data mining framework. results on a real-life chemoinformatics dataset using gtm are promising and have been analytically compared with the results from the traditional projection methods. it is also shown that the hgtm algorithm provides additional value for large datasets. the computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework.
generating semantic annotations for frequent patterns with context analysis. as a fundamental data mining task, frequent pattern mining has widespread applications in many different domains. research in frequent pattern mining has so far mostly focused on developing efficient algorithms to discover various kinds of frequent patterns, but little attention has been paid to the important nextstep - interpreting the discovered frequent patterns. although some recent work has studied the compression and summarization of frequent patterns, the proposed techniques can only annotate a frequent pattern with non-semantical information (e.g. support), which provides only limited help for a user to understand the patterns.in this paper, we propose the novel problem of generating semantic annotations for frequent patterns. the goal is to annotate a frequent pattern with in-depth, concise, and structured information that can better indicate the hidden meanings of the pattern. we propose a general approach to generate such anannotation for a frequent pattern by constructing its context model, selecting informative context indicators, and extracting representative transactions and semantically similar patterns. this general approach has potentially many applications such as generating a dictionary-like description for a pattern, finding synonym patterns, discovering semantic relations, and summarizing semantic classes of a set of frequent patterns. experiments on different datasets show that our approach is effective in generating semantic pattern annotations.
discovering evolutionary theme patterns from text: an exploration of temporal text mining. temporal text mining (ttm) is concerned with discovering temporal patterns in text information collected over time. since most text information bears some time stamps, ttm has many applications in multiple domains, such as summarizing events in news articles and revealing research trends in scientific literature. in this paper, we study a particular ttm task -- discovering and summarizing the evolutionary patterns of themes in a text stream. we define this new text mining problem and present general probabilistic methods for solving this problem through (1) discovering latent themes from text; (2) constructing an evolution graph of themes; and (3) analyzing life cycles of themes. evaluation of the proposed methods on two different domains (i.e., news articles and literature) shows that the proposed methods can discover interesting evolutionary theme patterns effectively.
a mixture model for contextual text mining. contextual text mining is concerned with extracting topical themes from a text collection with context information (e.g., time and location) and comparing/analyzing the variations of themes over different contexts. since the topics covered in a document are usually related to the context of the document, analyzing topical themes within context can potentially reveal many interesting theme patterns. in this paper, we generalize some of these models proposed in the previous work and we propose a new general probabilistic model for contextual text mining that can cover several existing models as special cases. specifically, we extend the probabilistic latent semantic analysis (plsa) model by introducing context variables to model the context of a document. the proposed mixture model, called contextual probabilistic latent semantic analysis (cplsa) model, can be applied to many interesting mining tasks, such as temporal text mining, spatiotemporal text mining, author-topic analysis, and cross-collection comparative analysis. empirical experiments show that the proposed mixture model can discover themes and their contextual variations effectively.
finding simple intensity descriptions from event sequence data. sequences of events are an important type of data arising in various applications, including telecommunications, bio-statistics, web access analysis, etc. a basic approach to modeling such sequences is to find the underlying intensity functions describing the expected number of events per time unit. typically, the intensity functions are assumed to be piecewise constant. we therefore consider different ways of fitting intensity models to event sequence data. we start by considering a bayesian approach using markov chain monte carlo (mcmc) methods with varying number of pieces. these methods can be used to produce posterior distributions on the intensity functions and they can also accomodate covariates. the drawback is that they are computationally intensive and thus are not very suitable for data mining applications in which large numbers of intensity functions have to be estimated. we consider dynamic programming approaches to finding the change points in the intensity functions. these methods can find the maximum likelihood intensity function in o(n2k) time for a sequence of n events and k different pieces of intensity. we show that simple heuristics can be used to prune the number of potential change points, yielding speedups of several orders of magnitude. the results of the improved dynamic programming method correspond very closely with the posterior averages produced by the mcmc methods.
sleeved coclustering. a cocluster of a m x n matrix x is a submatrix determined by a subset of the rows and a subset of the columns. the problem of finding coclusters with specific properties is of interest, in particular, in the analysis of microarray experiments. in that case the entries of the matrix x are the expression levels of $m$ genes in each of $n$ tissue samples. one goal of the analysis is to extract a subset of the samples and a subset of the genes, such that the expression levels of the chosen genes behave similarly across the subset of the samples, presumably reflecting an underlying regulatory mechanism governing the expression level of the genes.we propose to base the similarity of the genes in a cocluster on a simple biological model, in which the strength of the regulatory mechanism in sample j is hj, and the response strength of gene i to the regulatory mechanism is gi. in other words, every two genes participating in a good cocluster should have expression values in each of the participating samples, whose ratio is a constant depending only on the two genes. noise in the expression levels of genes is taken into account by allowing a deviation from the model, measured by a relative error criterion. the sleeve-width of the cocluster reflects the extent to which entry i,j in the cocluster is allowed to deviate, relatively, from being expressed as the product gihj.we present a polynomial-time monte-carlo algorithm which outputs a list of coclusters whose sleeve-widths do not exceed a prespecified value. moreover, we prove that the list includes, with fixed probability, a cocluster which is near-optimal in its dimensions. extensive experimentation with synthetic data shows that the algorithm performs well.
a distributed learning framework for heterogeneous data sources. we present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites have diverse, possibly overlapping subsets of features. our framework decouples data privacy issues from knowledge integration issues by requiring the individual sites to share only privacy-safe probabilistic models of the local data, which are then integrated to obtain a global probabilistic model based on the union of the features available at all the sites. we provide a mathematical formulation of the model integration problem using the maximum likelihood and maximum entropy principles and describe iterative algorithms that are guaranteed to converge to the optimal solution. for certain commonly occurring special cases involving hierarchically ordered feature sets or conditional independence, we obtain closed form solutions and use these to propose an efficient alternative scheme by recursive decomposition of the model integration problem. to address interpretability concerns, we also present a modified formulation where the global model is assumed to belong to a specified parametric family. finally, to highlight the generality of our framework, we provide empirical results for various learning tasks such as clustering and classification on different kinds of datasets consisting of continuous vector, categorical and directional attributes. the results show that high quality global models can be obtained without much loss of privacy.
a new multi-view regression approach with an application to customer wallet estimation. motivated by the problem of customer wallet estimation, we propose a new setting for multi-view regression, where we learn a completely unobserved target (in our case, customer wallet) by modeling it as a "central link" in a directed graphical model, connecting multiple sets of observed variables. the resulting conditional independence allows us to reduce the maximum discriminative likelihood estimation problem to a convex optimization problem for exponential linear models. we show that under certain modeling assumptions, in particular, when there exist two conditionally independent views and the noise is gaussian, this problem can be reduced to a single least squares regression. thus, for this specific, but widely applicable setting, the "unsupervised" multi-view problem can be solved via a simple supervised learning approach. this reduction also allows us to test the statistical independence assumptions underlying the graphical model and perform variable selection. we demonstrate the effectiveness of our approach on our motivating problem of customer wallet estimation and on simulation data.
efficient multidimensional data representations based on multiple correspondence analysis. in the on line analytical processing (olap) context, exploration of huge and sparse data cubes is a tedious task which does not always lead to efficient results. in this paper, we couple olap with the multiple correspondence analysis (mca) in order to enhance visual representations of data cubes and thus, facilitate their interpretations and analysis. we also provide a quality criterion to measure the relevance of obtained representations. the criterion is based on a geometric neighborhood concept and a similarity metric between cells of a data cube. experimental results on real data proved the interest and the efficiency of our approach.
aggregating time partitions. partitions of sequential data exist either per se or as a result of sequence segmentation algorithms. it is often the case that the same timeline is partitioned in many different ways. for example, different segmentation algorithms produce different partitions of the same underlying data points. in such cases, we are interested in producing an aggregate partition, i.e., a segmentation that agrees as much as possible with the input segmentations. each partition is defined as a set of continuous non-overlapping segments of the timeline. we show that this problem can be solved optimally in polynomial time using dynamic programming. we also propose faster greedy heuristics that work well in practice. we experiment with our algorithms and we demonstrate their utility in clustering the behavior of mobile-phone users and combining the results of different segmentation algorithms on genomic sequences.
yale: rapid prototyping for complex data mining tasks. kdd is a complex and demanding task. while a large number of methods has been established for numerous problems, many challenges remain to be solved. new tasks emerge requiring the development of new methods or processing schemes. like in software development, the development of such solutions demands for careful analysis, specification, implementation, and testing. rapid prototyping is an approach which allows crucial design decisions as early as possible. a rapid prototyping system should support maximal re-use and innovative combinations of existing methods, as well as simple and quick integration of new ones.this paper describes yale, a free open-source environment forkdd and machine learning. yale provides a rich variety of methods whichallows rapid prototyping for new applications and makes costlyre-implementations unnecessary. additionally, yale offers extensive functionality for process evaluation and optimization which is a crucial property for any kdd rapid prototyping tool. following the paradigm of visual programming eases the design of processing schemes. while the graphical user interface supports interactive design, the underlying xml representation enables automated applications after the prototyping phase.after a discussion of the key concepts of yale, we illustrate the advantages of rapid prototyping for kdd on case studies ranging from data pre-processing to result visualization. these case studies cover tasks like feature engineering, text mining, data stream mining and tracking drifting concepts, ensemble methods and distributed data mining. this variety of applications is also reflected in a broad user base, we counted more than 40,000 downloads during the last twelve months.
extracting targeted data from the web. tom m. mitchell is author of the textbook "machine learning" (mcgraw hill, 1997), president of the american association for artificial intelligence and a member of the national research council's computer science and telecommunications board. he is vice president and chief scientist at whizbang labs and is currently on a two-year leave of absence from carnegie mellon university where he is the fredkin professor of learning and ai in the school of computer science and founding director of cmu's center for automated learning and discovery. mitchell's research interests span many areas of machine learning theory and practice. his current work at whizbang labs involves developing machine learning methods for extracting information from text. for example, whizbang has developed the world's largest database of job openings by training its software to automatically locate and extract detailed information from job postings on corporate web sites (see www.flipdog.com).
efficient computations via scalable sparse kernel partial least squares and boosted latent features. kernel partial least squares (kpls) has been known as a generic kernel regression method and proven to be competitive with other kernel regression methods such as support vector machines for regression (svm) and kernel ridge regression. kernel boosted latent features (kblf) is a variant of kpls for any differentiable convex loss functions. it provides a more flexible framework for various predictive modeling tasks such as classification with logistic loss and robust regression with l1 norm loss, etc. however, kpls and kblf solutions are dense and thus not suitable for large-scale computations. sparsification of kpls solutions has been studied for dual and primal forms. for dual sparsity, it requires solving a nonlinear optimization problem at every iteration step and its computational burden limits its applicability to general regression tasks.in this paper, we propose simple heuristics to approximate sparse solutions for kpls and the framework is also applied for sparsifying kblf solutions. the algorithm provides an interesting "path" from a maximum residual criterion based algorithm with orthogonality conditions to the dense kpls/kblf. with the orthogonality, it differentiates itself from many existing forward selection-type algorithms. the computational advantage is illustrated by benchmark datasets and comparison to svm is done.
experimental design for solicitation campaigns. data mining techniques are routinely used by fundraisers to select those prospects from a large pool of candidates who are most likely to make a financial contribution. these techniques often rely on statistical models based on trial performance data. this trial performance data is typically obtained by soliciting a smaller sample of the possible prospect pool. collecting this trial data involves a cost; therefore the fundraiser is interested in keeping the trial size small while still collecting enough data to build a reliable statistical model that will be used to evaluate the remainder of the prospects.we describe an experimental design approach to optimally choose the trial prospects from an existing large pool of prospects. prospects are clustered to render the problem practically tractable. we modify the standard d-optimality algorithm to prevent repeated selection of the same prospect cluster, since each prospect can only be solicited at most once.we assess the benefits of this approach on the kdd-98 data set by comparing the performance of the model based on the optimal trial data set with that of a model based on a randomly selected trial data set of equal size.
information extraction, data mining and joint inference. although information extraction and data mining appear together in many applications, their interface in most current systems would better be described as serial juxtaposition than as tight integration. information extraction populates slots in a database by identifying relevant subsequences of text, but is usually not aware of the emerging patterns and regularities in the database. data mining methods begin from a populated database, and are often unaware of where the data came from, or its inherent uncertainties. the result is that the accuracy of both suffers, and accurate mining of complex text sources has been beyond reach.in this talk i will describe work in probabilistic models that perform joint inference across multiple components of an information processing pipeline in order to avoid the brittle accumulation of errors. after briefly introducing conditional random fields, i will describe recent work in information extraction leveraging factorial state representations, entity resolution, and transfer learning, as well as scalable methods of inference and learning. i'll close with some recent work on probabilistic models for social network analysis, and a demonstration of rexa.info, a new research paper search engine.
data filtering for automatic classification of rocks from reflectance spectra. the ability to identify the mineral composition of rocks and soils is an important tool for the exploration of geological sites. for instance, nasa intends to design robots that are sufficiently autonomous to perform this task on planetary missions. spectrometer readings provide one important source of data for identifying sites with minerals of interest. reflectance spectrometers measure intensities of light reflected from surfaces over a range of wavelengths. spectral intensity patterns may in some cases be sufficiently distinctive for proper identification of minerals or classes of minerals. for some mineral classes, carbonates for example, specific short spectral intervals are known to carry a distinctive signature. finding similar distinctive spectral ranges for other mineral classes is not an easy problem. we propose and evaluate data-driven techniques that automatically search for spectral ranges optimized for specific minerals. in one set of studies, we partition the whole interval of wavelengths available in our data into sub-intervals, or bins, and use a genetic algorithm to evaluate a candidate selection of subintervals. as alternatives to this computationally expensive search technique, we present an entropy-based heuristic that gives higher scores for wavelengths more likely to distinguish between classes, as well as other greedy search procedures. results are presented for four different classes, showing reasonable improvements in identifying some, but not all, of the mineral classes tested.
new cached-sufficient statistics algorithms for quickly answering statistical questions. this talk is about recent work on new ways to exploit preprocessed views of data tables for tractably solving big statistical queries. we'll describe deployments of these new algorithms in the realms of detecting killer asteroids and unnatural disease outbreaks.in recent years, several groups have looked at methods for pre-storing general sufficient statistics of the data in spatial data structures such as kd-trees and ball-trees so that both frequentist and bayesian statistical operations become fast for large datasets. in this talk we will look at two other classes of optimization required in important statistical queries.the first involves iterating over all spatial regions (big and small). the second involves detection of tracks from noisy intermittent observations separated far apart in time and space. we will also discuss the implications that have arisen from making these operations tractable. we will focus particularly ondetecting all asteroids in the solar system larger than pittsburgh's cathedral of learning (data to be collected over 2006-2010). early detection of emerging diseases based on national monitoring of health-related transactions..
algorithms for time series knowledge mining. temporal patterns composed of symbolic intervals are commonly formulated with allen's interval relations originating in temporal reasoning. this representation has severe disadvantages for knowledge discovery. the time series knowledge representation (tskr) is a new hierarchical language for interval patterns expressing the temporal concepts of coincidence and partial order. we present effective and efficient mining algorithms for such patterns based on itemset techniques. a novel form of search space pruning effectively reduces the size of the mining result to ease interpretation and speed up the algorithms. on a real data set a concise set of tskr patterns can explain the underlying temporal phenomena, whereas the patterns found with allen's relations are far more numerous yet only explain fragments of the data.
understandable models of music collections based on exhaustive feature generation with temporal statistics. data mining in large collections of polyphonic music has recently received increasing interest by companies along with the advent of commercial online distribution of music. important applications include the categorization of songs into genres and the recommendation of songs according to musical similarity and the customer's musical preferences. modeling genre or timbre of polyphonic music is at the core of these tasks and has been recognized as a difficult problem. many audio features have been proposed, but they do not provide easily understandable descriptions of music. they do not explain why a genre was chosen or in which way one song is similar to another. we present an approach that combines large scale feature generation with meta learning techniques to obtain meaningful features for musical similarity. we perform exhaustive feature generation based on temporal statistics and train regression models to summarize a subset of these features into a single descriptor of a particular notion of music. using several such models we produce a concise semantic description of each song. genre classification models based on these semantic features are shown to be better understandable and almost as accurate as traditional methods.
optimizing time series discretization for knowledge discovery. knowledge discovery in time series usually requires symbolic time series. many discretization methods that convert numeric time series to symbolic time series ignore the temporal order of values. this often leads to symbols that do not correspond to states of the process generating the time series and cannot be interpreted meaningfully. we propose a new method for meaningful unsupervised discretization of numeric time series called persist. the algorithm is based on the kullback-leibler divergence between the marginal and the self-transition probability distributions of the discretization symbols. its performance is evaluated on both artificial and real life data in comparison to the most common discretization methods. persist achieves significantly higher accuracy than existing static methods and is robust against noise. it also outperforms hidden markov models for all but very simple cases.
mining frequent neighboring class sets in spatial databases. we consider the problem of finding neighboring class sets. objects of each instance of a neighboring class set are grouped using their euclidean distances from each other. recently, location-based services are growing along with mobile computing infrastructure such as cellular phones and pdas. therefore, we expect to see the development of spatial databases that contains very large number of access records including location information. the most typical type would be a database of point objects. records of the objects may consist of "requested service name," "number of packet transmitted" in addition to x and y coordinate values indicating where the request came from. the algorithm presented here efficiently finds sets of "service names" that were frequently close to each other in the spatial database. for example, it may find a frequent neighboring class set, where "ticket" and "timetable" are frequently requested close to each other. by recognizing this, location-based service providers can promote a "ticket" service for customers who access the "timetable."
key semantics extraction by dependency tree mining. we propose a new text mining system which extracts characteristic contents from given documents. we define key semantics as characteristic sub-structures of syntactic dependencies in the given documents, and consider the following three tasks in this paper: 1)key semantics extraction: extracting characteristic syntactic dependency structures not only as ordered trees but also as unordered trees and free trees, 2)redundancy reduction: from the result of extraction, deleting redundant dependency structures such as sub-structures or equivalent structures of the others, and 3)phrase/sentence reconstruction: generating a phrase or sentence in a natural language corresponding to the extracted structure.our system is a combination of natural language processing techniques and tree mining techniques. the system consists of the following five units: 1) syntactic dependency analysis unit, 2) input filters, 3) characteristic ordered subtree extraction unit, 4) output filters, and 5) phrase/sentence reconstruction unit. although ordered trees are extracted in the third unit, the overall behavior of the system can be switched into the extraction of ordered trees, unordered trees, or free trees depending on which of the input filters is/are applied in the second step. the output filters delete redundant trees from the extraction result for efficient knowledge discovery. finally, phrases or sentences corresponding to the extracted subtrees are reconstructed by utilizing the input documents.we demonstrate the validity of our system by showing experimental results using real data collected at a help desk and tdt pilot corpus.
tracking dynamics of topic trends using a finite mixture model. in a wide range of business areas dealing with text data streams, including crm, knowledge management, and web monitoring services, it is an important issue to discover topic trends and analyze their dynamics in real-time. specifically we consider the following three tasks in topic trend analysis: 1)topic structure identification; identifying what kinds of main topics exist and how important they are, 2)topic emergence detection; detecting the emergence of a new topic and recognizing how it grows, 3)topic characterization; identifying the characteristics for each of main topics. for real topic analysis systems, we may require that these three tasks be performed in an on-line fashion rather than in a retrospective way, and be dealt with in a single framework. this paper proposes a new topic analysis framework which satisfies this requirement from a unifying viewpoint that a topic structure is modeled using a finite mixture model and that any change of a topic trend is tracked by learning the finite mixture model dynamically. in this framework we propose the usage of a time-stamp based discounting learning algorithm in order to realize real-time topic structure identification. this enables tracking the topic structure adaptively by forgetting out-of-date statistics. further we apply the theory of dynamic model selection to detecting changes of main components in the finite mixture model in order to realize topic emergence detection. we demonstrate the effectiveness of our framework using real data collected at a help desk to show that we are able to track dynamics of topic trends in a timely fashion.
distributed cooperative mining for information consortia. we consider the situation where a number of agents are distributed and each of them collects a data sequence generated according to an unknown probability distribution. here each of the distributions is specified by common parameters and individual parameters e.g., a normal distribution with an identical mean and a different variance. here we introduce a notion of an information consortium, which is a framework where the agents cannot show raw data to one another, but they like to enjoy significant information gain for estimating the respective distributions. such an information consortium has recently received much interest in a broad range of areas including financial risk management, ubiquitous network mining, etc. in this paper we are concerned with the following three issues: 1) how to design a collaborative strategy for agents to estimate the respective distributions in the information consortium, 2) characterizing when each agent has a benefit in terms of information gain for estimating its distribution or information loss for predicting future data, and 3) charracterizing how much benefit each agent obtains. in this paper we yield a statistical formulation of information consortia and solve all of the above three problems for a general form of probability distributions. specifically we propose a basic strategy for cooperative estimation and derive a necessary and sufficient condition for each agent to have a significant benefit.
mining product reputations on the web. knowing the reputations of your own and/or competitors' products is important for marketing and customer relationship management. it is, however, very costly to collect and analyze survey data manually. this paper presents a new framework for mining product reputations on the internet. it automatically collects people's opinions about target products from web pages, and it uses text mining techniques to obtain the reputations of those products.on the basis of human-test samples, we generate in advance syntactic and linguistic rules to determine whether any given statement is an opinion or not, as well as whether such any opinion is positive or negative in nature. we first collect statements regarding target products using a general search engine, and then, using the rules, extract opinions from among them and attach three labels to each opinion, labels indicating the positive/negative determination, the product name itself, and an numerical value expressing the degree of system confidence that the statement is, in fact, an opinion. the labeled opinions are then input into an opinion database.the mining of reputations, i.e., the finding of statistically meaningful information included in the database, is then conducted. we specify target categories using label values (such as positive opinions of product a) and perform four types of text mining: extraction of 1) characteristic words, 2) co-occurrence words, 3) typical sentences, for individual target categories, and 4) correspondence analysis among multiple target categories.actual marketing data is used to demonstrate the validity and effectiveness of the framework, which offers a drastic reduction in the overall cost of reputation analysis over that of conventional survey approaches and supports the discovery of knowledge from the pool of opinions on the web.
machine learning for online query relaxation. in this paper we provide a fast, data-driven solution to the failing query problem: given a query that returns an empty answer, how can one relax the query's constraints so that it returns a non-empty set of tuples? we introduce a novel algorithm, loqr, which is designed to relax queries that are in the disjunctive normal form and contain a mixture of discrete and continuous attributes. loqr discovers the implicit relationships that exist among the various domain attributes and then uses this knowledge to relax the constraints from the failing query.in a first step, loqr uses a small, randomly-chosen subset of the target database to learn a set of decision rules that predict whether an attribute's value satisfies the constraints in the failing query; this query-driven operation is performed online for each failing query. in the second step, loqr uses nearest-neighbor techniques to find the learned rule that is the most similar to the failing query; then it uses the attributes' values from this rule to relax the failing query's constraints. our experiments on six application domains show that loqr is both robust and fast: it successfully relaxes more than 95% of the failing queries, and it takes under a second for processing queries that consist of up to 20 attributes (larger queries of up to 93 attributes are processed in several seconds).
mining traffic data from probe-car system for travel time prediction. we are developing a technique to predict travel time of a vehicle for an objective road section, based on real time traffic data collected through a probe-car system. in the area of intelligent transport system (its), travel time prediction is an important subject. probe-car system is an upcoming data collection method, in which a number of vehicles are used as moving sensors to detect actual traffic situation. it can collect data concerning much larger area, compared with traditional fixed detectors. our prediction technique is based on statistical analysis using ar model with seasonal adjustment and mdl (minimum description length) criterion. seasonal adjustment is used to handle periodicities of 24 hours in traffic data. alternatively, we employ state space model, which can handle time series with periodicities. it is important to select really effective data for prediction, among the data from widespread area, which are collected via probe-car system. we do this using mdl criterion. that is, we find the explanatory variables that really have influence on the future travel time. in this paper, we experimentally show effectiveness of our method using probe-car data collected in nagoya metropolitan area in 2002.
using retrieval measures to assess similarity in mining dynamic web clickstreams. while scalable data mining methods are expected to cope with massive web data, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary stoppages and reconfigurations is still an open challenge. this dynamic and single pass setting can be cast within the framework of mining evolving data streams. in this paper, we explore the task of mining mass user profiles by discovering evolving web session clusters in a single pass with a recently proposed scalable immune based clustering approach (tecno-streams), and study the effect of the choice of different similarity measures on the mining process and on the interpretation of the mined patterns. we propose a simple similarity measure that has the advantage of explicitly coupling the precision and coverage criteria to the early learning stages, and furthermore requiring that the affinity of the data to the learned profiles or summaries be defined by the minimum of their coverage or precision, hence requiring that the learned profiles are simultaneously precise and complete, with no compromises.in our experiments, we study the task of mining evolving user profiles from web clickstream data (web usage mining) in a single pass, and under different trend sequencing scenarios, showing that compared oto the cosine similarity measure, the proposed similarity measure explicitly based on precision and coverage allows the discovery of more correct profiles at the same precision or recall quality levels.
clustering based large margin classification: a scalable approach using socp formulation. this paper presents a novel second order cone programming (socp) formulation for large scale binary classification tasks. assuming that the class conditional densities are mixture distributions, where each component of the mixture has a spherical covariance, the second order statistics of the components can be estimated efficiently using clustering algorithms like birch. for each cluster, the second order moments are used to derive a second order cone constraint via a chebyshev-cantelli inequality. this constraint ensures that any data point in the cluster is classified correctly with a high probability. this leads to a large margin socp formulation whose size depends on the number of clusters rather than the number of training data points. hence, the proposed formulation scales well for large datasets when compared to the state-of-the-art classifiers, support vector machines (svms). experiments on real world and synthetic datasets show that the proposed algorithm outperforms svm solvers in terms of training time and achieves similar accuracies.
semantic representation: search and mining of multimedia content. semantic understanding of multimedia content is critical in enabling effective access to all forms of digital media data. by making large media repositories searchable, semantic content descriptions greatly enhance the value of such data. automatic semantic understanding is a very challenging problem and most media databases resort to describing content in terms of low-level features or using manually ascribed annotations. recent techniques focus on detecting semantic concepts in video, such as indoor, outdoor, face, people, nature, etc. this approach works for a fixed lexicon for which annotated training examples exist. in this paper we consider the problem of using such semantic concept detection to map the video clips into semantic spaces. this is done by constructing a model vector that acts as a compact semantic representation of the underlying content. we then present experiments in the semantic spaces leveraging such information for enhanced semantic retrieval, classification, visualization, and data mining purposes. we evaluate these ideas using a large video corpus and demonstrate significant performance gains in retrieval effectiveness.
rapid detection of significant spatial clusters. given an n x n grid of squares, where each square has a count cij and an underlying population pij, our goal is to find the rectangular region with the highest density, and to calculate its significance by randomization. an arbitrary density function d, dependent on a region's total count c and total population p, can be used. for example, if each count represents the number of disease cases occurring in that square, we can use kulldorff's spatial scan statistic dk to find the most significant spatial disease cluster. a naive approach to finding the maximum density region requires o(n4) time, and is generally computationally infeasible. we present a multiresolution algorithm which partitions the grid into overlapping regions using a novel overlap-kd tree data structure, bounds the maximum score of subregions contained in each region, and prunes regions which cannot contain the maximum density region. for sufficiently dense regions, this method finds the maximum density region in o((n log n)2) time, in practice resulting in significant (20-2000x) speedups on both real and simulated datasets.
detection of emerging space-time clusters. we propose a new class of spatio-temporal cluster detection methods designed for the rapid detection of emerging space-time clusters. we focus on the motivating application of prospective disease surveillance: detecting space-time clusters of disease cases resulting from an emerging disease outbreak. automatic, real-time detection of outbreaks can enable rapid epidemiological response, potentially reducing rates of morbidity and mortality. building on the prior work on spatial and space-time scan statistics, our methods combine time series analysis (to determine how many cases we expect to observe for a given spatial region in a given time interval) with new "emerging cluster" space-time scan statistics (to decide whether an observed increase in cases in a region is significant), enabling fast and accurate detection of emerging outbreaks. we evaluate these methods on two types of simulated outbreaks: aerosol release of inhalational anthrax (e.g. from a bioterrorist attack) and floo ("fictional linear onset outbreak"), injected into actual baseline data (emergency department records and over-the-counter drug sales data from allegheny county). we demonstrate that our methods are successful in rapidly detecting both outbreak types while keeping the number of false positives low, and show that our new "emerging cluster" scan statistics consistently outperform the standard "persistent cluster" scan statistics approach.
learning relational probability trees. classification trees are widely used in the machine learning and data mining communities for modeling propositional data. recent work has extended this basic paradigm to probability estimation trees. traditional tree learning algorithms assume that instances in the training data are homogenous and independently distributed. relational probability trees (rpts) extend standard probability estimation trees to a relational setting in which data instances are heterogeneous and interdependent. our algorithm for learning the structure and parameters of an rpt searches over a space of relational features that use aggregation functions (e.g. average, mode, count) to dynamically propositionalize relational data and create binary splits within the rpt. previous work has identified a number of statistical biases due to characteristics of relational data such as autocorrelation and degree disparity. the rpt algorithm uses a novel form of randomization test to adjust for these biases. on a variety of relational learning tasks, rpts built using randomization tests are significantly smaller than other models and achieve equivalent, or better, performance.
using relational knowledge discovery to prevent securities fraud. we describe an application of relational knowledge discovery to a key regulatory mission of the national association of securities dealers (nasd). nasd is the world's largest private-sector securities regulator, with responsibility for preventing and discovering misconduct among securities brokers. our goal was to help focus nasd's limited regulatory resources on the brokers who are most likely to engage in securities violations. using statistical relational learning algorithms, we developed models that rank brokers with respect to the probability that they would commit a serious violation of securities regulations in the near future. our models incorporate organizational relationships among brokers (e.g., past coworker), which domain experts consider important but have not been easily used before now. the learned models were subjected to an extensive evaluation using more than 18 months of data unseen by the model developers and comprising over two person weeks of effort by nasd staff. model predictions were found to correlate highly with the subjective evaluations of experienced nasd examiners. furthermore, in all performance measures, our models performed as well as or better than the handcrafted rules that are currently in use at nasd.
statistical entity-topic models. the primary purpose of news articles is to convey information about who, what, when and where. but learning and summarizing these relationships for collections of thousands to millions of articles is difficult. while statistical topic models have been highly successful at topically summarizing huge collections of text documents, they do not explicitly address the textual interactions between who/where, i.e. named entities (persons, organizations, locations) and what, i.e. the topics. we present new graphical models that directly learn the relationship between topics discussed in news articles and entities mentioned in each article. we show how these entity-topic models, through a better understanding of the entity-topic relationships, are better at making predictions about entities.
a quickstart in frequent structure mining can make a difference. given a database, structure mining algorithms search for substructures that satisfy constraints such as minimum frequency, minimum confidence, minimum interest and maximum frequency. examples of substructures include graphs, trees and paths. for these substructures many mining algorithms have been proposed. in order to make graph mining more efficient, we investigate the use of the "quickstart principle", which is based on the fact that these classes of structures are contained in each other, thus allowing for the development of structure mining algorithms that split the search into steps of increasing complexity. we introduce the graph/sequence/tree extraction (gaston) algorithm that implements this idea by searching first for frequent paths, then frequent free trees and finally cyclic graphs. we investigate two alternatives for computing the frequency of structures and present experimental results to relate these alternatives.
graph-based anomaly detection. anomaly detection is an area that has received much attention in recent years. it has a wide variety of applications, including fraud detection and network intrusion detection. a good deal of research has been performed in this area, often using strings or attribute-value data as the medium from which anomalies are to be extracted. little work, however, has focused on anomaly detection in graph-based data. in this paper, we introduce two techniques for graph-based anomaly detection. in addition, we introduce a new method for calculating the regularity of a graph, with applications to anomaly detection. we hypothesize that these methods will prove useful both for finding anomalies, and for determining the likelihood of successful anomaly detection within graph-based data. we provide experimental results using both real-world network intrusion data and artificially-created data.
a hit-miss model for duplicate detection in the who drug safety database. the who collaborating centre for international drug monitoring in uppsala, sweden, maintains and analyses the world's largest database of reports on suspected adverse drug reaction incidents that occur after drugs are introduced on the market. as in other post-marketing drug safety data sets, the presence of duplicate records is an important data quality problem and the detection of duplicates in the who drug safety database remains a formidable challenge, especially since the reports are anonymised before submitted to the database. however, to our knowledge no work has been published on methods for duplicate detection in post-marketing drug safety data. in this paper, we propose a method for probabilistic duplicate detection based on the hit-miss model for statistical record linkage described by copas & hilton. we present two new generalisations of the standard hit-miss model: a hit-miss mixture model for errors in numerical record fields and a new method to handle correlated record fields. we demonstrate the effectiveness of the hit-miss model for duplicate detection in the who drug safety database both at identifying the most likely duplicate for a given record (94.7% accuracy) and at discriminating duplicates from random matches (63% recall with 71% precision). the proposed method allows for more efficient data cleaning in post-marketing drug safety data sets, and perhaps other applications throughout the kdd community.
evaluating classifiers' performance in a constrained environment. in this paper, we focus on methodology of finding a classifier with a minimal cost in presence of additional performance constraints. rocch analysis, where accuracy and cost are intertwined in the solution space, was a revolutionary tool for two-class problems. we propose an alternative formulation, as an optimization problem, commonly used in operations research. this approach extends the rocch analysis to allow for locating optimal solutions while outside constraints are present. similarly to the rocch analysis, we combine cost and class distribution while defining the objective function. rather than focusing on slopes of the edges in the convex hull of the solution space, however, we treat cost as an objective function to be minimized over the solution space, by selecting the best performing classifier(s) (one or more vertex in the solution space). the linear programming framework provides a theoretical and computational methodology for finding the vertex (classifier) which minimizes the objective function.
programming the k-means clustering algorithm in sql. using sql has not been considered an efficient and feasible way to implement data mining algorithms. although this is true for many data mining, machine learning and statistical algorithms, this work shows it is feasible to get an efficient sql implementation of the well-known k-means clustering algorithm that can work on top of a relational dbms. the article emphasizes both correctness and performance. from a correctness point of view the article explains how to compute euclidean distance, nearest-cluster queries and updating clustering results in sql. from a performance point of view it is explained how to cluster large data sets defining and indexing tables to store and retrieve intermediate and final results, optimizing and avoiding joins, optimizing and simplifying clustering aggregations, and taking advantage of sufficient statistics. experiments evaluate scalability with synthetic data sets varying size and dimensionality. the proposed k-means implementation can cluster large data sets and exhibits linear scalability.
towards nic-based intrusion detection. we present and evaluate a nic-based network intrusion detection system. intrusion detection at the nic makes the system potentially tamper-proof and is naturally extensible to work in a distributed setting. simple anomaly detection and signature detection based models have been implemented on the nic firmware, which has its own processor and memory. we empirically evaluate such systems from the perspective of quality and performance (bandwidth of acceptable messages) under varying conditions of host load. the preliminary results we obtain are very encouraging and lead us to believe that such nic-based security schemes could very well be a crucial part of next generation network security systems.
experimental comparisons of online and batch versions of bagging and boosting. bagging and boosting are well-known ensemble learning methods. they combine multiple learned base models with the aim of improving generalization performance. to date, they have been used primarily in batch mode, i.e., they require multiple passes through the training data. in previous work, we presented online bagging and boosting algorithms that only require one pass through the training data and presented experimental results on some relatively small datasets. through additional experiments on a variety of larger synthetic and real datasets, this paper demonstrates that our online versions perform comparably to their batch counterparts in terms of classification accuracy. we also demonstrate the substantial reduction in running time we obtain with our online algorithms because they require fewer passes through the training data.
personalization from incomplete data: what you don't know can hurt. clickstream data collected at any web site (site-centric data) is inherently incomplete, since it does not capture users' browsing behavior across sites (user-centric data). hence, models learned from such data may be subject to limitations, the nature of which has not been well studied. understanding the limitations is particularly important since most current personalization techniques are based on site-centric data only. in this paper, we empirically examine the implications of learning from incomplete data in the context of two specific problems: (a) predicting if the remainder of any given session will result in a purchase and (b) predicting if a given user will make a purchase at any future session. for each of these problems we present new algorithms for fast and accurate data preprocessing of clickstream data. based on a comprehensive experiment on user-level clickstream data gathered from 20,000 users' browsing behavior, we demonstrate that models built on user-centric data outperform models built on site-centric data for both prediction tasks.
mining for misconfigured machines in grid systems. grid systems are proving increasingly useful for managing the batch computing jobs of organizations. one well-known example is intel, whose internally developed netbatch system manages tens of thousands of machines. the size, heterogeneity, and complexity of grid systems make them very difficult, however, to configure. this often results in misconfigured machines, which may adversely affect the entire system.we investigate a distributed data mining approach for detection of misconfigured machines. our grid monitoring system (gms) non-intrusively collects data from all sources (log files, system services, etc.) available throughout the grid system. it converts raw data to semantically meaningful data and stores this data on the machine it was obtained from, limiting incurred overhead and allowing scalability. afterwards, when analysis is requested, a distributed outliers detection algorithm is employed to identify misconfigured machines. the algorithm itself is implemented as a recursive workflow of grid jobs. it is especially suited to grid systems, in which the machines might be unavailable most of the time and often fail altogether.
anf: a fast and scalable tool for data mining in massive graphs. graphs are an increasingly important data source, with such important graphs as the internet and the web. other familiar graphs include cad circuits, phone records, gene sequences, city streets, social networks and academic citations. any kind of relationship, such as actors appearing in movies, can be represented as a graph. this work presents a data mining tool, called anf, that can quickly answer a number of interesting questions on graph-represented data, such as the following. how robust is the internet to failures? what are the most influential database papers? are there gender differences in movie appearance patterns? at its core, anf is based on a fast and memory-efficient approach for approximating the complete "neighbourhood function" for a graph. for the internet graph (268k nodes), anf's highly-accurate approximation is more than 700 times faster than the exact computation. this reduces the running time from nearly a day to a matter of a minute or two, allowing users to perform ad hoc drill-down tasks and to repeatedly answer questions about changing data sources. to enable this drill-down, anf employs new techniques for approximating neighbourhood-type functions for graphs with distinguished nodes and/or edges. when compared to the best existing approximation, anf's approach is both faster and more accurate, given the same resources. additionally, unlike previous approaches, anf scales gracefully to handle disk resident graphs. finally, we present some of our results from mining large graphs using anf.
visualizing changes in the structure of data for exploratory feature selection. using visualization techniques to explore and understand high-dimensional data is an efficient way to combine human intelligence with the immense brute force computation power available nowadays. several visualization techniques have been developed to study the cluster structure of data, i.e., the existence of distinctive groups in the data and how these clusters are related to each other. however, only few of these techniques lend themselves to studying how this structure changes if the features describing the data are changed. understanding this relationship between the features and the cluster structure means understanding the features themselves and is thus a useful tool in the feature extraction phase.in this paper we present a novel approach to visualizing how modification of the features with respect to weighting or normalization changes the cluster structure. we demonstrate the application of our approach in two music related data mining projects.
carpenter: finding closed patterns in long biological datasets. the growth of bioinformatics has resulted in datasets with new characteristics. these datasets typically contain a large number of columns and a small number of rows. for example, many gene expression datasets may contain 10,000-100,000 columns but only 100-1000 rows.such datasets pose a great challenge for existing (closed) frequent pattern discovery algorithms, since they have an exponential dependence on the average row length. in this paper, we describe a new algorithm called carpenter that is specially designed to handle datasets having a large number of attributes and relatively small number of rows. several experiments on real bioinformatics datasets show that carpenter is orders of magnitude better than previous closed pattern mining algorithms like closet and charm.
automatic mining of fruit fly embryo images. we present femine, an automatic system for image-based gene expression analysis. we perform experiments on the largest publicly available collection of drosophila ish (in situ hybridization) images, showing that our femine system achieves excellent performance in classification, clustering, and content-based image retrieval. the major innovation of femine is the use of automatically discovered latent spatial "themes" of gene expressions, lges, in the whole-embryo context, as opposed to patterns in nearly disjoint portions of an embryo proposed in previous methods.
automatic multimedia cross-modal correlation discovery. given an image (or video clip, or audio song), how do we automatically assign keywords to it? the general problem is to find correlations across the media in a collection of multimedia objects like video clips, with colors, and/or motion, and/or audio, and/or text scripts. we propose a novel, graph-based approach, "mmg", to discover such cross-modal correlations.our "mmg" method requires no tuning, no clustering, no user-determined constants; it can be applied to any multimedia collection, as long as we have a similarity function for each medium; and it scales linearly with the database size. we report auto-captioning experiments on the "standard" corel image database of 680 mb, where it outperforms domain specific, fine-tuned methods by up to 10 percentage points in captioning accuracy (50% relative improvement).
discovering word senses from text. inventories of manually compiled dictionaries usually serve as a source for word senses. however, they often include many rare senses while missing corpus/domain-specific senses. we present a clustering algorithm called cbc (clustering by committee) that automatically discovers word senses from text. it initially discovers a set of tight clusters called committees that are well scattered in the similarity space. the centroid of the members of a committee is used as the feature vector of the cluster. we proceed by assigning words to their most similar clusters. after assigning an element to a cluster, we remove their overlapping features from the element. this allows cbc to discover the less frequent senses of a word and to avoid discovering duplicate senses. each cluster that a word belongs to represents one of its senses. we also present an evaluation methodology for automatically measuring the precision and recall of discovered senses.
document preprocessing for naive bayes classification and clustering with mixture of multinomials. naive bayes classifier has long been used for text categorization tasks. its sibling from the unsupervised world, the probabilistic mixture of multinomial models, has likewise been successfully applied to text clustering problems. despite the strong independence assumptions that these models make, their attractiveness come from low computational cost, relatively low memory consumption, ability to handle heterogeneous features and multiple classes, and often competitiveness with the top of the line models. recently, there has been several attempts to alleviate the problems of naive bayes by performing heuristic feature transformations, such as idf, normalization by the length of the documents and taking the logarithms of the counts. we justify the use of these techniques and apply them to two problems: classification of products in yahoo! shopping and clustering the vectors of collocated terms in user queries to yahoo! search. the experimental evaluation allows us to draw conclusions about the promise that these transformations carry with regard to alleviating the strong assumptions of the multinomial model.
probabilistic query models for transaction data. we investigate the application of bayesian networks, markov random fields, and mixture models to the problem of query answering for transaction data sets. we formulate two versions of the querying problem: the query selectivity estimation (i.e., finding exact counts for tuples in a data set) and the query generalization problem (i.e., computing the probability that a tuple will occur in new data). we show that frequent itemsets are useful for reducing the original data to a compressed representation and introduce a method to store them using an adtree data structure. in an extension of our earlier work on this topic we propose several new schemes for query answering based on the compressed representation that avoid direct scans of the data at query time. experimental results on real-world transaction data sets provide insights into various tradeoffs involving the offline time for model-building, the online time for query-answering, the memory footprint of the compressed data, and the accuracy of the estimate provided to the query.
disease progression modeling from historical clinical databases. this paper considers the problem of modeling disease progression from historical clinical databases, with the ultimate objective of stratifying patients into groups with clearly distinguishable prognoses or suitability for different treatment strategies. to meet this objective, we describe a procedure that first fits clinical variables measured over time to a disease progression model. the resulting parameter estimates are then used as the basis for a stepwise clustering procedure to stratify patients into groups with distinct survival characteristics. as a practical illustration, we apply this procedure to survival prediction, using a liver transplant database from the national institute of diabetes and digestive and kidney diseases (niddk).
sequential cost-sensitive decision making with reinforcement learning. recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. a number of approaches have been developed that are effective at optimizing cost-sensitive decisions when each decision is considered in isolation. however, the issue of sequential decision making, with the goal of maximizing total benefits accrued over a period of time instead of immediate benefits, has rarely been addressed. in the present paper, we propose a novel approach to sequential decision making based on the reinforcement learning framework. our approach attempts to learn decision rules that optimize a sequence of cost-sensitive decisions so as to maximize the total benefits accrued over time. we use the domain of targeted' marketing as a testbed for empirical evaluation of the proposed method. we conducted experiments using approximately two years of monthly promotion data derived from the well-known kdd cup 1998 donation data set. the experimental results show that the proposed method for optimizing total accrued benefits out performs the usual targeted-marketing methodology of optimizing each promotion in isolation. we also analyze the behavior of the targeting rules that were obtained and discuss their appropriateness to the application domain.
on mining cross-graph quasi-cliques. joint mining of multiple data sets can often discover interesting, novel, and reliable patterns which cannot be obtained solely from any single source. for example, in cross-market customer segmentation, a group of customers who behave similarly in multiple markets should be considered as a more coherent and more reliable cluster than clusters found in a single market. as another example, in bioinformatics, by joint mining of gene expression data and protein interaction data, we can find clusters of genes which show coherent expression patterns and also produce interacting proteins. such clusters may be potential pathways.in this paper, we investigate a novel data mining problem, mining cross-graph quasi-cliques, which is generalized from several interesting applications such as cross-market customer segmentation and joint mining of gene expression data and protein interaction data. we build a general model for mining cross-graph quasi-cliques, show why the complete set of cross-graph quasi-cliques cannot be found by previous data mining methods, and study the complexity of the problem. while the problem is difficult, we develop an efficient algorithm, crochet, which exploits several interesting and effective techniques and heuristics to efficaciously mine cross-graph quasi-cliques. a systematic performance study is reported on both synthetic and real data sets. we demonstrate some interesting and meaningful cross-graph quasi-cliques in bioinformatics. the experimental results also show that algorithm crochet is efficient and scalable.
extracting collective probabilistic forecasts from web games. game sites on the world wide web draw people from around the world with specialized interests, skills, and knowledge. data from the games often reflects the players' expertise and will to win. we extract probabilistic forecasts from data obtained from three online games: the hollywood stock exchange (hsx), the foresight exchange (fx), and the formula one pick six (f1p6) competition. we find that all three yield accurate forecasts of uncertain future events. in particular, prices of so-called "movie stocks" on hsx are good indicators of actual box office returns. prices of hsx securities in oscar, emmy, and grammy awards correlate well with observed frequencies of winning. fx prices are reliable indicators of future developments in science and technology. collective predictions from players in the f1 competition serve as good forecasts of true race outcomes. in some cases, forecasts induced from game data are more reliable than expert opinions. we argue that web games naturally attract well-informed and well-motivated players, and thus offer a valuable and oft-overlooked source of high-quality data with significant predictive value.
aggregation-based feature invention and relational concept classes. model induction from relational data requires aggregation of the values of attributes of related entities. this paper makes three contributions to the study of relational learning. (1) it presents a hierarchy of relational concepts of increasing complexity, using relational schema characteristics such as cardinality, and derives classes of aggregation operators that are needed to learn these concepts. (2) expanding one level of the hierarchy, it introduces new aggregation operators that model the distributions of the values to be aggregated and (for classification problems) the differences in these distributions by class. (3) it demonstrates empirically on a noisy business domain that more-complex aggregation methods can increase generalization performance. constructing features using target-dependent aggregations can transform relational prediction tasks so that well-understood feature-vector-based modeling algorithms can be applied successfully.
data-driven validation, completion and construction of event relationship networks. event management is a focal point in building and maintaining high quality information infrastructures. we have witnessed the shift of the paradigm of event management in practice from root cause analysis (rca) to action-oriented analysis (aoa). ibm has developed a pioneer event management methodology (emd) based on the aoa paradigm and applied it to more than two hundred production sites with success. foreseeably, more and more event management professionals will apply aoa in different incarnations in building proactive management facilities. by that, building correct and effective event relationship networks (erns) becomes the dominating activity in aoa service design process. currently, the quality of erns and the cost of building them largely depend on the knowledge of domain experts. we believe that we can utilize historical event logs in shortening the erns design process and perfecting the quality of erns. in this paper, we describe in detail how to apply this data-driven approach in ern validation, completion and construction.
new unsupervised clustering algorithm for large datasets. a fast and accurate unsupervised clustering algorithm has been developed for clustering very large datasets. though designed for very large volumes of geospatial data, the algorithm is general enough to be used in a wide variety of domain applications. the number of computations the algorithm requires is ~ o(n), and thus faster than hierarchical algorithms. unlike the popular k-means heuristic, this algorithm does not require a series of iterations to converge to a solution. in addition, this method does not depend on initialization of a given number of cluster representatives, and so is insensitive to initial conditions. being unsupervised, the algorithm can also "rank" each cluster based on density. the method relies on weighting a dataset to grid points on a mesh, and using a small number of rule-based agents to find the high density clusters. this method effectively reduces large datasets to the size of the grid, which is usually many orders of magnitude smaller. numerical experiments are shown that demonstrate the advantages of this algorithm over other techniques.
mining rare and frequent events in multi-camera surveillance video using self-organizing maps. this paper describes a method for unsupervised classification of events in multi-camera indoors surveillance video. this research is a part of the multiple sensor indoor surveillance (msis) project which uses 32 axis-2100 webcams that observe an office environment. the research was inspired by the following practical problem: how automatically classify and visualize a 24 hour long video captured by 32 cameras? raw data are sequences of jpeg images captured by webcams at the rate 2-6 hz. the following features are extracted from the image data: foreground pixels' spatial distribution and color histogram. the data are integrated by event by averaging motion and color features and creating a "summary" frame which accumulates all foreground pixels of frames of the event into one image. the self-organizing map (som) approach is applied to event data for clustering and visualization. one-level and two-level som clustering are used. a tool for browsing results allows exploring units of the som maps at different levels of hierarchy, clusters of units and distances between units in 3d space. a special technique has been developed to visualize rare events. the results are presented and discussed.
improving discriminative sequential learning with rare--but--important associations. discriminative sequential learning models like conditional random fields (crfs) have achieved significant success in several areas such as natural language processing or information extraction. their key advantage is the ability to capture various non--independent and overlapping features of inputs. however, several unexpected pitfalls have a negative influence on the model's performance; these mainly come from an imbalance among classes/labels, irregular phenomena, and potential ambiguity in the training data. this paper presents a data--driven approach that can deal with such hard--to--predict data instances by discovering and emphasizing rare--but--important associations of statistics hidden in the training data. mined associations are then incorporated into these models to deal with difficult examples. experimental results of english phrase chunking and named entity recognition using crfs show a significant improvement in accuracy. in addition to the technical perspective, our approach also highlights a potential connection between association mining and statistical learning by offering an alternative strategy to enhance learning performance with interesting and useful patterns discovered from large dataset.
b-em: a classifier incorporating bootstrap with em approach for data mining. this paper investigates the problem of augmenting labeled data with unlabeled data to improve classification accuracy. this is significant for many applications such as image classification where obtaining classification labels is expensive, while large unlabeled examples are easily available. we investigate an expectation maximization (em) algorithm for learning from labeled and unlabeled data. the reason why unlabeled data boosts learning accuracy is because it provides the information about the joint probability distribution. a theoretical argument shows that the more unlabeled examples are combined in learning, the more accurate the result. we then introduce b-em algorithm, based on the combination of em with bootstrap method, to exploit the large unlabeled data while avoiding prohibitive i/o cost. experimental results over both synthetic and real data sets that the proposed approach has a satisfactory performance.
making every bit count: fast nonlinear axis scaling. existing axis scaling and dimensionality methods focus on preserving structure, usually determined via the euclidean distance. in other words, they inherently assume that the euclidean distance is already correct. we instead propose a novel nonlinear approach driven by an information-theoretic viewpoint, which we show is also strongly linked to intrinsic dimensionality, or degrees of freedom; and uniformity. nonlinear transformations based on common probability distributions, combined with information-driven selection, simultaneously reduce the number of dimensions required and increase the value of those we retain. experiments on real data confirm that this approach reveals correlations, finds novel attributes, and scales well.
is there a grand challenge or x-prize for data mining? this panel will discuss possible exciting and motivating grand challenge problems for data mining, focusing on bioinformatics, multimedia mining, link mining, text mining, and web mining.
capturing best practice for microarray gene expression data analysis. analyzing gene expression data from microarray devices has many important application in medicine and biology, but presents significant challenges to data mining. microarray data typically has many attributes (genes) and few examples (samples), making the process of correctly analyzing such data difficult to formulate and prone to common mistakes. for this reason it is unusually important to capture and record good practices for this form of data mining. this paper presents a process for analyzing microarray data, including pre-processing, gene selection, randomization testing, classification and clustering; this process is captured with "clementine application templates". the paper describes the process in detail and includes three case studies, showing how the process is applied to 2-class classification, multi-class classification and clustering analyses for publicly available microarray datasets.
bayesian analysis of massive datasets via particle filters. markov chain monte carlo (mcmc) techniques revolutionized statistical practice in the 1990s by providing an essential toolkit for making the rigor and flexibility of bayesian analysis computationally practical. at the same time the increasing prevalence of massive datasets and the expansion of the field of data mining has created the need to produce statistically sound methods that scale to these large problems. except for the most trivial examples, current mcmc methods require a complete scan of the dataset for each iteration eliminating their candidacy as feasible data mining techniques.in this article we present a method for making bayesian analysis of massive datasets computationally feasible. the algorithm simulates from a posterior distribution that conditions on a smaller, more manageable portion of the dataset. the remainder of the dataset may be incorporated by reweighting the initial draws using importance sampling. computation of the importance weights requires a single scan of the remaining observations. while importance sampling increases efficiency in data access, it comes at the expense of estimation efficiency. a simple modification, based on the "rejuvenation" step used in particle filters for dynamic systems models, sidesteps the loss of efficiency with only a slight increase in the number of data accesses.to show proof-of-concept, we demonstrate the method on a mixture of transition models that has been used to model web traffic and robotics. for this example we show that estimation efficiency is not affected while offering a 95% reduction in data accesses.
incorporating prior knowledge with weighted margin support vector machines. like many purely data-driven machine learning methods, support vector machine (svm) classifiers are learned exclusively from the evidence presented in the training dataset; thus a larger training dataset is required for better performance. in some applications, there might be human knowledge available that, in principle, could compensate for the lack of data. in this paper, we propose a simple generalization of svm: weighted margin svm (wmsvms) that permits the incorporation of prior knowledge. we show that sequential minimal optimization can be used in training wmsvm. we discuss the issues of incorporating prior knowledge using this rather general formulation. the experimental results show that the proposed methods of incorporating prior knowledge is effective.
learning sparse metrics via linear programming. calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. this calculation is crucial for efficiency since distances are usually evaluated a large number of times, the classical example being query-by-example (find objects that are similar to a given query object). moreover, the performance of these algorithms depends critically on choosing a good distance function. however, it is often the case that (1) the correct distance is unknown or chosen by hand, and (2) its calculation is computationally expensive (e.g., such as for large dimensional objects). in this paper, we propose a method for constructing relative-distance preserving low-dimensional mapping (sparse mappings). this method allows learning unknown distance functions (or approximating known functions) with the additional property of reducing distance computation time. we present an algorithm that given examples of proximity comparisons among triples of objects (object i is more like object j than object k), learns a distance function, in as few dimensions as possible, that preserves these distance relationships. the formulation is based on solving a linear programming optimization problem that finds an optimal mapping for the given dataset and distance relationships. unlike other popular embedding algorithms, this method can easily generalize to new points, does not have local minima, and explicitly models computational efficiency by finding a mapping that is sparse, i.e. one that depends on a small subset of features or dimensions. experimental evaluation shows that the proposed formulation compares favorably with a state-of-the art method in several publicly available datasets.
robust boosting and its relation to bagging. several authors have suggested viewing boosting as a gradient descent search for a good fit in function space. at each iteration observations are re-weighted using the gradient of the underlying loss function. we present an approach of weight decay for observation weights which is equivalent to "robustifying" the underlying loss function. at the extreme end of decay this approach converges to bagging, which can be viewed as boosting with a linear underlying loss function. we illustrate the practical usefulness of weight decay for improving prediction performance and present an equivalence between one form of weight decay and "huberizing" --- a statistical method for making loss functions more robust.
estimating the size of the telephone universe: a bayesian mark-recapture approach. mark-recapture models have for many years been used to estimate the unknown sizes of animal and bird populations. in this article we adapt a finite mixture mark-recapture model in order to estimate the number of active telephone lines in the usa. the idea is to use the calling patterns of lines that are observed on the long distance network to estimate the number of lines that do not appear on the network. we present a bayesian approach and use markov chain monte carlo methods to obtain inference from the posterior distributions of the model parameters. at the state level, our results are in fairly good agreement with recent published reports on line counts. for lines that are easily classified as business or residence, the estimates have low variance. when the classification is unknown, the variability increases considerably. results are insensitive to changes in the prior distributions. we discuss the significant computational and data mining challenges caused by the scale of the data, approximately 350 million call-detail records per day observed over a number of weeks.
cluster-based concept invention for statistical relational learning. we use clustering to derive new relations which augment database schema used in automatic generation of predictive features in statistical relational learning. entities derived from clusters increase the expressivity of feature spaces by creating new first-class concepts which contribute to the creation of new features. for example, in citeseer, papers can be clustered based on words or citations giving "topics", and authors can be clustered based on documents they co-author giving "communities". such cluster-derived concepts become part of more complex feature expressions. out of the large number of generated features, those which improve predictive accuracy are kept in the model, as decided by statistical feature selection criteria. we present results demonstrating improved accuracy on two tasks, venue prediction and link prediction, using citeseer data.
evaluation of prediction models for marketing campaigns. we consider prediction-model evaluation in the context of marketing-campaign planning. in order to evaluate and compare models with specific campaign objectives in mind, we need to concentrate our attention on the appropriate evaluation-criteria. these should portray the model's ability to score accurately and to identify the relevant target population. in this paper we discuss some applicable model-evaluation and selection criteria, their relevance for campaign planning, their robustness under changing population distributions, and their employment when constructing confidence intervals. we illustrate our results with a case study based on our experience from several projects.
short term performance forecasting in enterprise systems. we use data mining and machine learning techniques to predict upcoming periods of high utilization or poor performance in enterprise systems. the abundant data available and complexity of these systems defies human characterization or static models and makes the task suitable for data mining techniques. we formulate the problem as one of classification: given current and past information about the system's behavior, can we forecast whether the system will meet its performance targets over the next hour? using real data gathered from several enterprise systems in hewlett-packard, we compare several approaches ranging from time series to bayesian networks. besides establishing the predictive power of these approaches our study analyzes three dimensions that are important for their application as a stand alone tool. first, it quantifies the gain in accuracy of multivariate prediction methods over simple statistical univariate methods. second, it quantifies the variations in accuracy when using different classes of system and workload features. third, it establishes that models induced using combined data from various systems generalize well and are applicable to new systems, enabling accurate predictions on systems with insufficient historical data. together this analysis offers a promising outlook on the development of tools to automate assignment of resources to stabilize performance, (e.g., adding servers to a cluster) and allow opportunistic job scheduling (e.g., backups or virus scans).
customer lifetime value modeling and its use for customer retention planning. we present and discuss the important business problem of estimating the effect of retention efforts on the lifetime value of a customer in the telecommunications industry. we discuss the components of this problem, in particular customer value and length of service (or tenure) modeling, and present a novel segment-based approach, motivated by the segment-level view marketing analysts usually employ. we then describe how we build on this approach to estimate the effects of retention on lifetime value. our solution has been successfully implemented in amdocs' business insight (bi) platform, and we illustrate its usefulness in real-world scenarios.
visualizing concept drift. we describe a visualization technique that uses brushed, parallel histograms to aid in understanding concept drift in multidimensional problem spaces. this technique illustrates the relationship between changes in distributions of multiple antecedent feature values and the outcome distribution. we can also observe effects on the relative utilization of predictive rules. our parallel histogram technique solves the over-plotting difficulty of parallel coordinate graphs and the difficulty of comparing distributions of brushed and original data. we demonstrate our technique's usefulness in understanding concept drifts in power demand and stock investment returns.
identifying early buyers from purchase data. market research has shown that consumers exhibit a variety of different purchasing behaviors; specifically, some tend to purchase products earlier than other consumers. identifying such early buyers can help personalize marketing strategies, potentially improving their effectiveness. in this paper, we present a non-parametric approach to the problem of identifying early buyers from purchase data. our formulation takes as inputs the detailed purchase information of each consumer, with which we construct a weighted directed graph whose nodes correspond to consumers and whose edges correspond to purchases consumers have in common; the edge weights indicate how frequently consumers purchase products earlier than other consumers.identifying early buyers corresponds to the problem of finding a subset of nodes in the graph with maximum difference between the weights of the outgoing and incoming edges. this problem is a variation of the maximum cut problem in a directed graph. we provide an approximation algorithm based on semidefinite programming (sdp) relaxations pioneered by goemans and williamson, and analyze its performance. we apply the algorithm to real purchase data from amazon.com, providing new insights into consumer behaviors.
critical event prediction for proactive management in large-scale computer clusters. as the complexity of distributed computing systems increases, systems management tasks require significantly higher levels of automation; examples include diagnosis and prediction based on real-time streams of computer events, setting alarms, and performing continuous monitoring. the core of autonomic computing, a recently proposed initiative towards next-generation it-systems capable of 'self-healing', is the ability to analyze data in real-time and to predict potential problems. the goal is to avoid catastrophic failures through prompt execution of remedial actions.this paper describes an attempt to build a proactive prediction and control system for large clusters. we collected event logs containing various system reliability, availability and serviceability (ras) events, and system activity reports (sars) from a 350-node cluster system for a period of one year. the 'raw' system health measurements contain a great deal of redundant event data, which is either repetitive in nature or misaligned with respect to time. we applied a filtering technique and modeled the data into a set of primary and derived variables. these variables used probabilistic networks for establishing event correlations through prediction algorithms. we also evaluated the role of time-series methods, rule-based classification algorithms and bayesian network models in event prediction.based on historical data, our results suggest that it is feasible to predict system performance parameters (sars) with a high degree of accuracy using time-series models. rule-based classification techniques can be used to extract machine-event signatures to predict critical events with up to 70% accuracy.
query chains: learning to rank from implicit feedback. this paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. we observe that users searching the web often perform a sequence, or chain, of queries with a similar information need. using query chains, we generate new types of preference judgments from search engine logs, thus taking advantage of user intelligence in reformulating queries. to validate our method we perform a controlled user study comparing generated preference judgments to explicit relevance judgments. we also implemented a real-world search engine to test our approach, using a modified ranking svm to learn an improved ranking function from preference data. our results demonstrate significant improvements in the ranking given by the search engine. the learned rankings outperform both a static ranking function, as well as one trained without considering query chains.
incentive networks. we propose a notion of incentive networks, modeling online settings in which multiple participants in a network help each other find information. within this general setting, we study query incentive networks, a natural abstraction of question-answering systems with rewards for finding answers. we analyze strategic behavior in such networks and under a simple model of networks, show that the nash equilibrium for participants' strategies exhibits an unexpected threshold phenomenon.
on the use of linear programming for unsupervised text classification. we propose a new algorithm for dimensionality reduction and unsupervised text classification. we use mixture models as underlying process of generating corpus and utilize a novel, l1-norm based approach introduced by kleinberg and sandler [19]. we show that our algorithm performs extremely well on large datasets, with peak accuracy approaching that of supervised learning based on support vector machines (svms) with large training sets. the method is based on the same idea that underlies latent semantic indexing (lsi). we find a good low-dimensional subspace of a feature space and project all documents into it. however our projection minimizes different error, and unlike lsi we build a basis, that in many cases corresponds to the actual topics. we present results of testing of our algorithm on the abstracts of arxiv - an electronic repository of scientific papers, and the 20 newsgroup dataset - a small snapshot of 20 specific newsgroups.
recommender systems in commerce and community. recommender systems have been revolutionizing the way shoppers and information seekers find what they want. we will study some of the tremendous successes and spectacular failures of recommenders in e-commerce to understand the causes of the success or failure. we will leverage that understanding into a set of principles for successfully applying recommenders to business problems. finally, we will study the economic and social forces that are shaping the evolution of recommenders, and peer into the crystal ball to glimpse the directions the technology will be going in the future.
mass collaboration and data mining. mass collaboration is a new "p2p"-style approach to large-scale knowledge sharing, with applications in customer support, focused community development, and capturing knowledge distributed within large organizations. effectively supporting this paradigm raises many technical challenges, and offers intriguing opportunities for mining massive amounts of data captured continually from user interactions. data mining offers the promise of increased business intelligence, and also improved user experiences, leading to increased participation and greater quality in the knowledge that is captured, both of which are central objectives in mass collaboration. in this talk, i will introduce mass collaboration and discuss some important data mining related issues.
regularized discriminant analysis for high dimensional, low sample size data. linear and quadratic discriminant analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. friedman proposed a compromise between linear and quadratic discriminant analysis, called regularized discriminant analysis (rda), which has been shown to be more flexible in dealing with various class distributions. rda applies the regularization techniques by employing two regularization parameters, which are chosen to jointly maximize the classification performance. the optimal pair of parameters is commonly estimated via cross-validation from a set of candidate pairs. it is computationally prohibitive for high dimensional data, especially when the candidate set is large, which limits the applications of rda to low dimensional data.in this paper, a novel algorithm for rda is presented for high dimensional data. it can estimate the optimal regularization parameters from a large set of parameter candidates efficiently. experiments on a variety of datasets confirm the claimed theoretical estimate of the efficiency, and also show that, for a properly chosen pair of regularization parameters, rda performs favorably in classification, in comparison with other existing classification methods.
turning cartwheels: an alternating algorithm for mining redescriptions. we present an unusual algorithm involving classification trees---cartwheels---where two trees are grown in opposite directions so that they are joined at their leaves. this approach finds application in a new data mining task we formulate, called redescription mining. a redescription is a shift-of-vocabulary, or a different way of communicating information about a given subset of data; the goal of redescription mining is to find subsets of data that afford multiple descriptions. we highlight the importance of this problem in domains such as bioinformatics, which exhibit an underlying richness and diversity of data descriptors (e.g., genes can be studied in a variety of ways). cartwheels exploits the duality between class partitions and path partitions in an induced classification tree to model and mine redescriptions. it helps integrate multiple forms of characterizing datasets, situates the knowledge gained from one dataset in the context of others, and harnesses high-level abstractions for uncovering cryptic and subtle features of data. algorithm design decisions, implementation details, and experimental results are presented.
a multinomial clustering model for fast simulation of computer architecture designs. computer architects utilize simulation tools to evaluate the merits of a new design feature. the time needed to adequately evaluate the tradeoffs associated with adding any new feature has become a critical issue. recent work has found that by identifying execution phases present in common workloads used in simulation studies, we can apply clustering algorithms to significantly reduce the amount of time needed to complete the simulation. our goal in this paper is to demonstrate the value of this approach when applied to the set of industry-standard benchmarks most commonly used in computer architecture studies. we also look to improve upon prior work by applying more appropriate clustering algorithms to identify phases, and to further reduce simulation time.we find that the phase clustering in computer architecture simulation has many similarities to text clustering. in prior work on clustering techniques to reduce simulation time, k-means clustering was used to identify representative program phases. in this paper we apply a mixture of multinomials to the clustering problem and show its advantages over using k-means on simulation data. we have implemented these two clustering algorithms and evaluate how well they can characterize program behavior. by adopting a mixture of multinomials model, we find that we can maintain simulation result fidelity, while greatly reducing overall simulation time. we report results for a range of applications taken from the spec2000 benchmark suite.
privacy preserving regression modelling via distributed computation. reluctance of data owners to share their possibly confidential or proprietary data with others who own related databases is a serious impediment to conducting a mutually beneficial data mining analysis. we address the case of vertically partitioned data -- multiple data owners/agencies each possess a few attributes of every data record. we focus on the case of the agencies wanting to conduct a linear regression analysis with complete records without disclosing values of their own attributes. this paper describes an algorithm that enables such agencies to compute the exact regression coefficients of the global regression equation and also perform some basic goodness-of-fit diagnostics while protecting the confidentiality of their data. in more general settings beyond the privacy scenario, this algorithm can also be viewed as method for the distributed computation for regression analyses.
clinical and financial outcomes analysis with existing hospital patient records. existing patient records are a valuable resource for automated outcomes analysis and knowledge discovery. however, key clinical data in these records is typically recorded in unstructured form as free text and images, and most structured clinical information is poorly organized. time-consuming interpretation and analysis is required to convert these records into structured clinical data. thus, only a tiny fraction of this resource is utilized. we present remind, a bayesian framework for reliable extraction and meaningful inference from nonstructured data. remind integrates and blends the structured and unstructured clinical data in patient records to automatically created high-quality structured clinical data. this structuring allows existing patient records to be mined for quality assurance, regulatory compliance, and to relate financial and clinical factors. we demonstrate remind on two medical applications: (a) extract "recurrence", the key outcome for measuring treatment effectiveness, for colon cancer patients (ii) extract key diagnoses and complications for acute myocardial infarction (heart attack) patients, and demonstrate the impact of these clinical factors on financial outcomes.
interactive deduplication using active learning. deduplication is a key operation in integrating data from multiple sources. the main challenge in this task is designing a function that can resolve when a pair of records refer to the same entity in spite of various data inconsistencies. most existing systems use hand-coded functions. one way to overcome the tedium of hand-coding is to train a classifier to distinguish between duplicates and non-duplicates. the success of this method critically hinges on being able to provide a covering and challenging set of training pairs that bring out the subtlety of deduplication function. this is non-trivial because it requires manually searching for various data inconsistencies between any two records spread apart in large lists.we present our design of a learning-based deduplication system that uses a novel method of interactively discovering challenging training pairs using active learning. our experiments on real-life datasets show that active learning significantly reduces the number of instances needed to achieve high accuracy. we investigate various design issues that arise in building a system to provide interactive response, fast convergence, and interpretable output.
combining clustering and co-training to enhance text classification using unlabelled data. in this paper, we present a new co-training strategy that makes use of unlabelled data. it trains two predictors in parallel, with each predictor labelling the unlabelled data for training the other predictor in the next round. both predictors are support vector machines, one trained using data from the original feature space, the other trained with new features that are derived by clustering both the labelled and unlabelled data. hence, unlike standard co-training methods, our method does not require a priori the existence of two redundant views either of which can be used for classification, nor is it dependent on the availability of two different supervised learning algorithms that complement each other.we evaluated our method with two classifiers and three text benchmarks: webkb, reuters newswire articles and 20 newsgroups. our evaluation shows that our co-training technique improves text classification accuracy especially when the number of labelled examples are very few.
cross-training: learning probabilistic mappings between topics. classification is a well-established operation in text mining. given a set of labels a and a set da of training documents tagged with these labels, a classifier learns to assign labels to unlabeled test documents. suppose we also had available a different set of labels b, together with a set of documents db marked with labels from b. if a and b have some semantic overlap, can the availability of db help us build a better classifier for a, and vice versa? we answer this question in the affirmative by proposing cross-training: a new approach to semi-supervised learning in presence of multiple label sets. we give distributional and discriminative algorithms for cross-training and show, through extensive experiments, that cross-training can discover and exploit probabilistic relations between two taxonomies for more accurate classification.
predicting the product purchase patterns of corporate customers. this paper describes tippps (time interleaved product purchase prediction system), which analyses billing data of corporate customers in a large telecommunications company in order to predict high value upsell opportunities. the challenges presented by this prediction problem are significant. firstly, the diversity of products used by corporate telecommunications customers is huge. this, coupled with low product take-up rates, makes this a problem of learning from a very high dimensional feature space with very few minority examples. further, it is important to give priority specifically to the identification of those new customers who are of high value. these challenges are overcome by introducing a number of modifications to standard data pre-processing and machine learning algorithms, the most important of which are time-interleaving of data and value weighting. time interleaving is the concatenation of examples from multiple time periods, thus increasing the number of training examples, and hence the number of minority examples. value weighting assigns importance to minority examples in proportion to the dollar value of take-up, thus biasing the system to identify high value customers. these modifications create a novel algorithm that makes the prediction system practical and usable.comparison with other techniques designed for similar problems shows that the expected average improvement in ranking accuracy achieved using these modifications is 3.7%. tippps has been in operation for several months and has been successful in identifying many upsell opportunities that were not identified by using the previous manual system.
using structure indices for efficient approximation of network properties. statistics on networks have become vital to the study of relational data drawn from areas such as bibliometrics, fraud detection, bioinformatics, and the internet. calculating many of the most important measures - such as betweenness centrality, closeness centrality, and graph diameter-requires identifying short paths in these networks. however, finding these short paths can be intractable for even moderate-size networks. we introduce the concept of a network structure index (nsi), a composition of (1) a set of annotations on every node in the network and (2) a function that uses the annotations to estimate graph distance between pairs of nodes. we present several varieties of nsis, examine their time and space complexity, and analyze their performance on synthetic and real data sets. we show that creating an nsi for a given network enables extremely efficient and accurate estimation of a wide variety of network statistics on that network.
sampling-based sequential subgroup mining. subgroup discovery is a learning task that aims at finding interesting rules from classified examples. the search is guided by a utility function, trading off the coverage of rules against their statistical unusualness. one shortcoming of existing approaches is that they do not incorporate prior knowledge. to this end a novel generic sampling strategy is proposed. it allows to turn pattern mining into an iterative process. in each iteration the focus of subgroup discovery lies on those patterns that are unexpected with respect to prior knowledge and previously discovered patterns. the result of this technique is a small diverse set of understandable rules that characterise a specified property of interest. as another contribution this article derives a simple connection between subgroup discovery and classifier induction. for a popular utility function this connection allows to apply any standard rule induction algorithm to the task of subgroup discovery after a step of stratified resampling. the proposed techniques are empirically compared to state of the art subgroup discovery algorithms.
mining knowledge-sharing sites for viral marketing. viral marketing takes advantage of networks of influence among customers to inexpensively achieve large changes in behavior. our research seeks to put it on a firmer footing by mining these networks from data, building probabilistic models of them, and using these models to choose the best viral marketing plan. knowledge-sharing sites, where customers review products and advise each other, are a fertile source for this type of data mining. in this paper we extend our previous techniques, achieving a large reduction in computational cost, and apply them to data from a knowledge-sharing site. we optimize the amount of marketing funds spent on each customer, rather than just making a binary decision on whether to market to him. we take into account the fact that knowledge of the network is partial, and that gathering that knowledge can itself have a cost. our results show the robustness and utility of our approach.
dense itemsets. frequent itemset mining has been the subject of a lot of work in data mining research ever since association rules were introduced. in this paper we address a problem with frequent itemsets: that they only count rows where all their attributes are present, and do not allow for any noise. we show that generalizing the concept of frequency while preserving the performance of mining algorithms is nontrivial, and introduce a generalization of frequent itemsets, dense itemsets. dense itemsets do not require all attributes to be present at the same time; instead, the itemset needs to define a sufficiently large submatrix that exceeds a given density threshold of attributes present.we consider the problem of computing all dense itemsets in a database. we give a levelwise algorithm for this problem, and also study the top-$k$ variations, i.e., finding the k densest sets with a given support, or the k best-supported sets with a given density. these algorithms select the other parameter automatically, which simplifies mining dense itemsets in an explorative way. we show that the concept captures natural facets of data sets, and give extensive empirical results on the performance of the algorithms. combining the concept of dense itemsets with set cover ideas, we also show that dense itemsets can be used to obtain succinct descriptions of large datasets. we also discuss some variations of dense itemsets.
admit: anomaly-based data mining for intrusions. security of computer systems is essential to their acceptance and utility. computer security analysts use intrusion detection systems to assist them in maintaining computer system security. this paper deals with the problem of differentiating between masqueraders and the true user of a computer terminal. prior efficient solutions are less suited to real time application, often requiring all training data to be labeled, and do not inherently provide an intuitive idea of what the data model means. our system, called admit, relaxes these constraints, by creating user profiles using semi-incremental techniques. it is a real-time intrusion detection system with host-based data collection and processing. our method also suggests ideas for dealing with concept drift and affords a detection rate as high as 80.3% and a false positive rate as low as 15.3%.
improving spatial locality of programs via data mining. in most computer systems, page fault rate is currently minimized by generic page replacement algorithms which try to model the temporal locality inherent in programs. in this paper, we propose two algorithms, one greedy and the other stochastic, designed for program specific code restructuring as a means of increasing spatial locality within a program. both algorithms effectively decrease average working set size and hence the page fault rate. our methods are more effective than traditional approaches due to use of domain information. we illustrate the efficacy of our algorithms on actual data mining algorithms.
treedt: gene mapping by tree disequilibrium test. we introduce and evaluate treedt, a novel gene mapping method which is based on discovering and assessing tree-like patterns in genetic marker data. gene mapping aims at discovering a statistical connection from a particular disease or trait to a narrow region in the genome. in a typical case-control setting, data consists of genetic markers typed for a set of disease-associated chromosomes and a set of control chromosomes. a computer scientist would view this data as a set of strings.treedt extracts, essentially in the form of substrings and prefix trees, information about the historical recombinations in the population. this information is used to locate fragments potentially inherited from a common diseased founder, and to map the disease gene into the most likely such fragment. the method measures for each chromosomal location the disequilibrium of the prefix tree of marker strings starting from the location, to assess the distribution of disease-associated chromosomes.we evaluate experimentally the performance of treedt on realistic, simulated data sets, and comparisons to state of the art methods (tdt, hpm) show that treedt is very competitive.
selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage. we present and empirically analyze a machine-learning approach for detecting intrusions on individual computers. our winnow-based algorithm continually monitors user and system behavior, recording such properties as the number of bytes transferred over the last 10 seconds, the programs that currently are running, and the load on the cpu. in all, hundreds of measurements are made and analyzed each second. using this data, our algorithm creates a model that represents each particular computer's range of normal behavior. parameters that determine when an alarm should be raised, due to abnormal activity, are set on a per-computer basis, based on an analysis of training data. a major issue in intrusion-detection systems is the need for very low false-alarm rates. our empirical results suggest that it is possible to obtain high intrusion-detection rates (95%) and low false-alarm rates (less than one per day per computer), without "stealing" too many cpu cycles (less than 1%). we also report which system measurements are the most valuable in terms of detecting intrusions. a surprisingly large number of different measurements prove significantly useful.
frequent-subsequence-based prediction of outer membrane proteins. a number of medically important disease-causing bacteria (collectively called gram-negative bacteria) are noted for the extra "outer" membrane that surrounds their cell. proteins resident in this membrane (outer membrane proteins, or omps) are of primary research interest for antibiotic and vaccine drug design as they are on the surface of the bacteria and so are the most accessible targets to develop new drugs against. with the development of genome sequencing technology and bioinformatics, biologists can now deduce all the proteins that are likely produced in a given bacteria and have attempted to classify where proteins are located in a bacterial cell. however such protein localization programs are currently least accurate when predicting omps, and so there is a current need for the development of a better omp classifier. data mining research suggests that the use of frequent patterns has good performance in aiding the development of accurate and efficient classification algorithms. in this paper, we present two methods to identify omps based on frequent subsequences and test them on all gram-negative bacterial proteins whose localizations have been determined by biological experiments. one classifier follows an association rule approach, while the other is based on support vector machines (svms). we compare the proposed methods with the state-of-the-art methods in the biological domain. the results demonstrate that our methods are better both in terms of accurately identifying omps and providing biological insights that increase our understanding of the structures and functions of these important proteins.
detecting graph-based spatial outliers: algorithms and applications (a summary of results). identification of outliers can lead to the discovery of unexpected, interesting, and useful knowledge. existing methods are designed for detecting spatial outliers in multidimensional geometric data sets, where a distance metric is available. in this paper, we focus on detecting spatial outliers in graph structured data sets. we define statistical tests, analyze the statistical foundation underlying our approach, design several fast algorithms to detect spatial outliers, and provide a cost model for outlier detection procedures. in addition, we provide experimental results from the application of our algorithms on a minneapolis-st.paul(twin cities) traffic dataset to show their effectiveness and usefulness.
experimental study of discovering essential information from customer inquiry. this paper reports the result of our experimental study on a new method of applying an association rule miner to discover useful information from customer inquiry database in a call center of a company. it has been claimed that association rule mining is not suited for text mining. to overcome this problem, we propose (1) to generate sequential data set of words with dependency structure from the japanese text database, and (2) to employ a new method for extracting meaningful association rules by applying a new rule selection criterion. each inquiry in the sequential data was represented as a list of word pairs, each of which consists of a verb and its dependent noun. the association rules were induced regarding each pair of words as an item. the rule selection criterion comes from our principle that we put heavier weights to co-occurrence of multiple items more than single item occurrence. we regarded a rule important if the existence of the items in the rule body significantly affects the occurrence of the item in the rule head. the selected rules were then categorized to form meaningful information classes. with this method, we succeeded in extracting useful information classes from the text database, which were not acquired by only simple keyword retrieval. also, inquiries with multiple aspects were properly classified into corresponding multiple categories.
probabilistic workflow mining. in several organizations, it has become increasingly popular to document and log the steps that makeup a typical business process. in some situations, a normative workflow model of such processes is developed, and it becomes important to know if such a model is actually being followed by analyzing the available activity logs. in other scenarios, no model is available and, with the purpose of evaluating cases or creating new production policies, one is interested in learning a workflow representation of such activities. in either case, machine learning tools that can mine workflow models are of great interest and still relatively unexplored. we present here a probabilistic workflow model and a corresponding learning algorithm that runs in polynomial time. we illustrate the algorithm on example data derived from a real world workflow.
a bayesian network framework for reject inference. most learning methods assume that the training set is drawn randomly from the population to which the learned model is to be applied. however in many applications this assumption is invalid. for example, lending institutions create models of who is likely to repay a loan from training sets consisting of people in their records to whom loans were given in the past; however, the institution approved loan applications previously based on who was thought unlikely to default. learning from only approved loans yields an incorrect model because the training set is a biased sample of the general population of applicants. the issue of including rejected samples in the learning process, or alternatively using rejected samples to adjust a model learned from accepted samples only, is called reject inference.the main contribution of this paper is a systematic analysis of different cases that arise in reject inference, with explanations of which cases arise in various real-world situations. we use bayesian networks to formalize each case as a set of conditional independence relationships and identify eight cases, including the familiar missing completely at random (mcar), missing at random (mar), and missing not at random (mnar) cases. for each case we present an overview of available learning algorithms. these algorithms have been published in separate fields of research, including epidemiology, econometrics, clinical trial evaluation, sociology, and credit scoring; our second major contribution is to describe these algorithms in a common framework.
modeling and predicting personal information dissemination behavior. in this paper, we propose a new way to automatically model and predict human behavior of receiving and disseminating information by analyzing the contact and content of personal communications. a personal profile, called communitynet, is established for each individual based on a novel algorithm incorporating contact, content, and time information simultaneously. it can be used for personal social capital management. clusters of communitynets provide a view of informal networks for organization management. our new algorithm is developed based on the combination of dynamic algorithms in the social network field and the semantic content classification methods in the natural language processing and machine learning literatures. we tested communitynets on the enron email corpus and report experimental results including filtering, prediction, and recommendation capabilities. we show that the personal behavior and intention are somewhat predictable based on these models. for instance, "to whom a person is going to send a specific email" can be predicted by one's personal social network and content analysis. experimental results show the prediction accuracy of the proposed adaptive algorithm is 58% better than the social network-based predictions, and is 75% better than an aggregated model based on latent dirichlet allocation with social network enhancement. two online demo systems we developed that allow interactive exploration of communitynet are also discussed.
evaluating similarity measures: a large-scale study in the orkut social network. online information services have grown too large for users to navigate without the help of automated tools such as collaborative filtering, which makes recommendations to users based on their collective past behavior. while many similarity measures have been proposed and individually evaluated, they have not been evaluated relative to each other in a large real-world environment. we present an extensive empirical comparison of six distinct measures of similarity for recommending online communities to members of the orkut social network. we determine the usefulness of the different recommendations by actually measuring users' propensity to visit and join recommended communities. we also examine how the ordering of recommendations influenced user selection, as well as interesting social issues that arise in recommending communities within a real social network.
monic: modeling and monitoring cluster transitions. there is much recent work on detecting and tracking change in clusters, often based on the study of the spatiotemporal properties of a cluster. for the many applications where cluster change is relevant, among them customer relationship management, fraud detection and marketing, it is also necessary to provide insights about the nature of cluster change: is a cluster corresponding to a group of customers simply disappearing or are its members migrating to other clusters? is a new emerging cluster reflecting a new target group of customers or does it rather consist of existing customers whose preferences shift? to answer such questions, we propose the framework monic for modeling and tracking of cluster transitions. our cluster transition model encompasses changes that involve more than one cluster, thus allowing for insights on cluster change in the whole clustering. our transition tracking mechanism is not based on the topological properties of clusters, which are only available for some types of clustering, but on the contents of the underlying data stream. we present our first results on monitoring cluster transitions over the acm digital library.
generating english summaries of time series data using the gricean maxims. we are developing technology for generating english textual summaries of time-series data, in three domains: weather forecasts, gas-turbine sensor readings, and hospital intensive care data. our weather-forecast generator is currently operational and being used daily by a meteorological company. we generate summaries in three steps: (a) selecting the most important trends and patterns to communicate; (b) mapping these patterns onto words and phrases; and (c) generating actual texts based on these words and phrases. in this paper we focus on the first step, (a), selecting the information to communicate, and describe how we perform this using modified versions of standard data analysis algorithms such as segmentation. the modifications arose out of empirical work with users and domain experts, and in fact can all be regarded as applications of the gricean maxims of quality, quantity, relevance, and manner, which describe how a cooperative speaker should behave in order to help a hearer correctly interpret a text. the gricean maxims are perhaps a key element of adapting data analysis algorithms for effective communication of information to human users, and should be considered by other researchers interested in communicating data to human users.
self-organizing wireless sensor networks in action. wireless sensor networks (wsn) composed of large numbers of small devices that self-organize are being investigated for a wide variety of applications. two key advantages of these networks over more traditional sensor networks are that they can be dynamically and quickly deployed, and that they can provide fine-grained sensing. applications, such as emergency response to natural or manmade disasters, detection and tracking, and fine grained sensing of the environment are key examples of applications that can benefit from these types of wsn. current research for these systems is widespread. however, many of the proposed solutions are developed with simplifying assumptions about wireless communication and the environment, even though the realities of wireless communication and environmental sensing are well known. many of the solutions are evaluated only by simulation. in this talk i describe a fully implemented system consisting of a suite of more than 30 synthesized protocols. the system supports a power aware surveillance, tracking and classification application running on 203 xsm motes and evaluated in a realistic, large-area environment. technical details and evaluations are presented. i end with a discussion of opportunities and problems for data mining related to wsn.
support envelopes: a technique for exploring the structure of association patterns. this paper introduces support envelopes---a new tool for analyzing association patterns---and illustrates some of their properties, applications, and possible extensions. specifically, the support envelope for a transaction data set and a specified pair of positive integers (m,n) consists of the items and transactions that need to be searched to find any association pattern involving m or more transactions and n or more items. for any transaction data set with m transactions and n items, there is a unique lattice of at most m*n support envelopes that captures the structure of the association patterns in that data set. because support envelopes are not encumbered by a support threshold, this support lattice provides a complete view of the association structure of the data set, including association patterns that have low support. furthermore, the boundary of the support lattice---the support boundary---has at most min(m,n) envelopes and is especially interesting since it bounds the maximum sizes of potential association patterns---not only for frequent, closed, and maximal itemsets, but also for patterns, such as error-tolerant itemsets, that are more general. the association structure can be represented graphically as a two-dimensional scatter plot of the (m,n) values associated with the support envelopes of the data set, a feature that is useful in the exploratory analysis of association patterns. finally, the algorithm to compute support envelopes is simple and computationally efficient, and it is straightforward to parallelize the process of finding all the support envelopes.
discovery of climate indices using clustering. to analyze the effect of the oceans and atmosphere on land climate, earth scientists have developed climate indices, which are time series that summarize the behavior of selected regions of the earth's oceans and atmosphere. in the past, earth scientists have used observation and, more recently, eigenvalue analysis techniques, such as principal components analysis (pca) and singular value decomposition (svd), to discover climate indices. however, eigenvalue techniques are only useful for finding a few of the strongest signals. furthermore, they impose a condition that all discovered signals must be orthogonal to each other, making it difficult to attach a physical interpretation to them. this paper presents an alternative clustering-based methodology for the discovery of climate indices that overcomes these limitiations and is based on clusters that represent regions with relatively homogeneous behavior. the centroids of these clusters are time series that summarize the behavior of the ocean or atmosphere in those regions. some of these centroids correspond to known climate indices and provide a validation of our methodology; other centroids are variants of known indices that may provide better predictive power for some land areas; and still other indices may represent potentially new earth science phenomena. finally, we show that cluster based indices generally outperform svd derived indices, both in terms of area weighted correlation and direct correlation with the known indices.
generalizing the notion of support. the goal of this paper is to show that generalizing the notion of support can be useful in extending association analysis to non-traditional types of patterns and non-binary data. to that end, we describe a framework for generalizing support that is based on the simple, but useful observation that support can be viewed as the composition of two functions: a function that evaluates the strength or presence of a pattern in each object (transaction) and a function that summarizes these evaluations with a single number. a key goal of any framework is to allow people to more easily express, explore, and communicate ideas, and hence, we illustrate how our support framework can be used to describe support for a variety of commonly used association patterns, such as frequent itemsets, general boolean patterns, and error-tolerant itemsets. we also present two examples of the practical usefulness of generalized support. one example shows the usefulness of support functions for continuous data. another example shows how the hyperclique pattern---an association pattern originally defined for binary data---can be extended to continuous data by generalizing a support function.
probabilistic author-topic models for information discovery. we propose a new unsupervised learning technique for extracting information from large text collections. we model documents as if they were generated by a two-stage stochastic process. each author is represented by a probability distribution over topics, and each topic is represented as a probability distribution over words for that topic. the words in a multi-author paper are assumed to be the result of a mixture of each authors' topic mixture. the topic-word and author-topic distributions are learned from data in an unsupervised manner using a markov chain monte carlo algorithm. we apply the methodology to a large corpus of 160,000 abstracts and 85,000 authors from the well-known citeseer digital library, and learn a model with 300 topics. we discuss in detail the interpretation of the results discovered by the system including specific topic and author models, ranking of authors by topic and topics by author, significant trends in the computer science literature between 1990 and 2002, parsing of abstracts by topics and authors and detection of unusual papers by specific authors. an online query interface to the model is also discussed that allows interactive exploration of author-topic models for corpora such as citeseer.
query, analysis, and visualization of hierarchically structured data using polaris. in the last several years, large olap databases have become common in a variety of applications such as corporate data warehouses and scientific computing. to support interactive analysis, many of these databases are augmented with hierarchical structures that provide meaningful levels of abstraction that can be leveraged by both the computer and analyst. this hierarchical structure generates many challenges and opportunities in the design of systems for the query, analysis, and visualization of these databases.in this paper, we present an interactive visual exploration tool that facilitates exploratory analysis of data warehouses with rich hierarchical structure, such as might be stored in data cubes. we base this tool on polaris, a system for rapidly constructing table-based graphical displays of multidimensional databases. polaris builds visualizations using an algebraic formalism derived from the interface and interpreted as a set of queries to a database. we extend the user interface, algebraic formalism, and generation of data queries in polaris to expose and take advantage of hierarchical structure. in the resulting system, analysts can navigate through the hierarchical projections of a database, rapidly and incrementally generating visualizations for each projection.
exploiting response models: optimizing cross-sell and up-sell opportunities in banking. the banking industry regularly mounts campaigns to improve customer value by offering new products to existing customers. in recent years this approach has gained significant momentum because of the increasing availability of customer data and the improved analysis capabilities in data mining. typically, response models based on historical data are used to estimate the probability of a customer purchasing an additional product and the expected return from that additional purchase. even with these computational improvements and accurate models of customer behavior, the problem of efficiently using marketing resources to maximize the return on marketing investment is a challenge. this problem is compounded because of the capability to launch multiple campaigns through several distribution channels over multiple time periods. the combination of alternatives creates a complicated array of possible actions. this paper presents a solution that answers the question of what products, if any, to offer to each customer in a way that maximizes the marketing return on investment. the solution is an improvement over the usual approach of picking the customers that have the largest expected value for a particular product because it is a global maximization from the viewpoint of the bank and allows for the effective implementation of business constraints across customers and business units. the approach accounts for limited resources, multiple sequential campaigns, and other business constraints. furthermore, the solution provides insight into the cost of these constraints, in terms of decreased profits, and thus is an effective tool for both tactical campaign execution and strategic planning.
a streaming ensemble algorithm (sea) for large-scale classification. ensemble methods have recently garnered a great deal of attention in the machine learning community. techniques such as boosting and bagging have proven to be highly effective but require repeated resampling of the training data, making them inappropriate in a data mining context. the methods presented in this paper take advantage of plentiful data, building separate classifiers on sequential chunks of training points. these classifiers are combined into a fixed-size ensemble using a heuristic replacement strategy. the result is a fast algorithm for large-scale or streaming data that classifies as well as a single decision tree built on all the data, requires approximately constant memory, and adjusts quickly to concept drift.
combining linguistic and statistical analysis to extract relations from web documents. the world wide web provides a nearly endless source of knowledge, which is mostly given in natural language. a first step towards exploiting this data automatically could be to extract pairs of a given semantic relation from text documents - for example all pairs of a person and her birthdate. one strategy for this task is to find text patterns that express the semantic relation, to generalize these patterns, and to apply them to a corpus to find new pairs. in this paper, we show that this approach profits significantly when deep linguistic structures are used instead of surface text patterns. we demonstrate how linguistic structures can be represented for machine learning, and we provide a theoretical analysis of the pattern matching approach. we show the benefits of our approach by extensive experiments with our prototype system leila.
beyond streams and graphs: dynamic tensor analysis. how do we find patterns in author-keyword associations, evolving over time? or in data cubes, with product-branch-customer sales information? matrix decompositions, like principal component analysis (pca) and variants, are invaluable tools for mining, dimensionality reduction, feature selection, rule identification in numerous settings like streaming data, text, graphs, social networks and many more. however, they have only two orders, like author and keyword, in the above example.we propose to envision such higher order data as tensors,and tap the vast literature on the topic. however, these methods do not necessarily scale up, let alone operate on semi-infinite streams. thus, we introduce the dynamic tensor analysis (dta) method, and its variants. dta provides a compact summary for high-order and high-dimensional data, and it also reveals the hidden correlations. algorithmically, we designed dta very carefully so that it is (a) scalable, (b) space efficient (it does not need to store the past) and (c) fully automatic with no need for user defined parameters. moreover, we propose sta, a streaming tensor analysis method, which provides a fast, streaming approximation to dta.we implemented all our methods, and applied them in two real settings, namely, anomaly detection and multi-way latent semantic indexing. we used two real, large datasets, one on network flow data (100gb over 1 month) and one from dblp (200mb over 25 years). our experiments show that our methods are fast, accurate and that they find interesting patterns and outliers on the real datasets.
a hybrid unsupervised approach for document clustering. we propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with expectation maximization. we developed several heuristics to automatically select a subset of the clusters generated by the first algorithm as the initial points of the second one. furthermore, our initialization algorithm generates not only an initial model for the iterative refinement algorithm but also an estimate of the model dimension, thus eliminating another important element of human supervision. we have evaluated the proposed system on five real-world document collections. the results show that our approach generates clustering solutions of higher quality than both its individual components.
ordering patterns by combining opinions from multiple sources. pattern ordering is an important task in data mining because the number of patterns extracted by standard data mining algorithms often exceeds our capacity to manually analyze them. in this paper, we present an effective approach to address the pattern ordering problem by combining the rank information gathered from disparate sources. although rank aggregation techniques have been developed for applications such as meta-search engines, they are not directly applicable to pattern ordering for two reasons. first, the techniques are mostly supervised, i.e., they require a sufficient amount of labeled data. second, the objects to be ranked are assumed to be independent and identically distributed (i.i.d), an assumption that seldom holds in pattern ordering. the method proposed in this paper is an adaptation of the original hedge algorithm, modified to work in an unsupervised learning setting. techniques for addressing the i.i.d. violation in pattern ordering are also presented. experimental results demonstrate that our unsupervised hedge algorithm outperforms many alternative techniques such as those based on weighted average ranking and singular value decomposition.
selecting the right interestingness measure for association patterns. many techniques for association rule mining and feature selection require a suitable metric to capture the dependencies among variables in a data set. for example, metrics such as support, confidence, lift, correlation, and collective strength are often used to determine the interestingness of association patterns. however, many such measures provide conflicting information about the interestingness of a pattern, and the best metric to use for a given application domain is rarely known. in this paper, we present an overview of various measures proposed in the statistics, machine learning and data mining literature. we describe several key properties one should examine in order to select the right measure for a given application domain. a comparative study of these properties is made using twenty one of the existing measures. we show that each measure has different properties which make them useful for some application domains, but not for others. we also present two scenarios in which most of the existing measures agree with each other, namely, support-based pruning and table standardization. finally, we present an algorithm to select a small set of tables such that an expert can select a desirable measure by looking at just this small set of tables.
mining long-term search history to improve search accuracy. long-term search history contains rich information about a user's search preferences, which can be used as search context to improve retrieval performance. in this paper, we study statistical language modeling based methods to mine contextual information from long-term search history and exploit it for a more accurate estimate of the query language model. experiments on real web search data show that the algorithms are effective in improving search accuracy for both fresh and recurring queries. the best performance is achieved when using clickthrough data of past searches that are related to the current query.
email data cleaning. addressed in this paper is the issue of 'email data cleaning' for text mining. many text mining applications need take emails as input. email data is usually noisy and thus it is necessary to clean it before mining. several products offer email cleaning features, however, the types of noises that can be eliminated are restricted. despite the importance of the problem, email cleaning has received little attention in the research community. a thorough and systematic investigation on the issue is thus needed. in this paper, email cleaning is formalized as a problem of non-text filtering and text normalization. in this way, email cleaning becomes independent from any specific text mining processing. a cascaded approach is proposed, which cleans up an email in four passes including non-text filtering, paragraph normalization, sentence normalization, and word normalization. as far as we know, non-text filtering and paragraph normalization have not been investigated previously. methods for performing the tasks on the basis of support vector machines (svm) have also been proposed in this paper. features in the models have been defined. experimental results indicate that the proposed svm based methods can significantly outperform the baseline methods for email cleaning. the proposed method has been applied to term extraction, a typical text mining processing. experimental results show that the accuracy of term extraction can be significantly improved by using the data cleaning method.
mining phenotypes and informative genes from gene expression data. mining microarray gene expression data is an important research topic in bioinformatics with broad applications. while most of the previous studies focus on clustering either genes or samples, it is interesting to ask whether we can partition the complete set of samples into exclusive groups (called phenotypes) and find a set of informative genes that can manifest the phenotype structure. in this paper, we propose a new problem of simultaneously mining phenotypes and informative genes from gene expression data. some statistics-based metrics are proposed to measure the quality of the mining results. two interesting algorithms are developed: the heuristic search and the mutual reinforcing adjustment method. we present an extensive performance study on both real-world data sets and synthetic data sets. the mining results from the two proposed methods are clearly better than those from the previous methods. they are ready for the real-world applications. between the two methods, the mutual reinforcing adjustment method is in general more scalable, more effective and with better quality of the mining results.
hierarchical model-based clustering of large datasets through fractionation and refractionation. the goal of clustering is to identify distinct groups in a dataset. compared to non-parametric clustering methods like complete linkage, hierarchical model-based clustering has the advantage of offering a way to estimate the number of groups present in the data. however, its computational cost is quadratic in the number of items to be clustered, and it is therefore not applicable to large problems. we review an idea called fractionation, originally conceived by cutting, karger, pedersen and tukey for non-parametric hierarchical clustering of large datasets, and describe an adaptation of fractionation to model-based clustering. a further extension, called refractionation, leads to a procedure that can be successful even in the difficult situation where there are large numbers of small groups.
assessment and pruning of hierarchical model based clustering. the goal of clustering is to identify distinct groups in a dataset. the basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mixture of gaussians, and to estimate the parameters of the component densities, the mixing fractions, and the number of components from the data. the number of distinct groups in the data is then taken to be the number of mixture components, and the observations are partitioned into clusters (estimates of the groups) using bayes' rule. if the groups are well separated and look gaussian, then the resulting clusters will indeed tend to be "distinct" in the most common sense of the word - contiguous, densely populated areas of feature space, separated by contiguous, relatively empty regions. if the groups are not gaussian, however, this correspondence may break down; an isolated group with a non-elliptical distribution, for example, may be modeled by not one, but several mixture components, and the corresponding clusters will no longer be well separated. we present methods for assessing the degree of separation between the components of a mixture model and between the corresponding clusters. we also propose a new clustering method that can be regarded as a hybrid between model-based and nonparametric clustering. the hybrid clustering algorithm prunes the cluster tree generated by hierarchical model-based clustering. starting with the tree corresponding to the mixture model chosen by the bayesian information criterion, it progressively merges clusters that do not appear to correspond to different modes of the data density.
weighted association rule mining using weighted support and significance framework. we address the issues of discovering significant binary relationships in transaction datasets in a weighted setting. traditional model of association rule mining is adapted to handle weighted association rule mining problems where each item is allowed to have a weight. the goal is to steer the mining focus to those significant relationships involving items with significant weights rather than being flooded in the combinatornal explosion of insignificant relationships. we identify the challenge of using weights in the iterative process of generating large itemsets. the problem of invalidation of the "downward closure property" in the weighted setting is solved by using an improved model of weighted support measurements and exploiting a "weighted downward closure property". a new algorithm called warm (weighted association rule mining) is developed based on the improved model. the algorithm is both scalable and efficient in discovering significant relationships in weighted settings as illustrated by experiments performed on simulated datasets.
mining distance-based outliers from large databases in any metric space. let r be a set of objects. an object o ∈ r is an outlier, if there exist less than k objects in r whose distances to o are at most r. the values of k, r, and the distance metric are provided by a user at the run time. the objective is to return all outliers with the smallest i/o cost.this paper considers a generic version of the problem, where no information is available for outlier computation, except for objects' mutual distances. we prove an upper bound for the memory consumption which permits the discovery of all outliers by scanning the dataset 3 times. the upper bound turns out to be extremely low in practice, e.g., less than 1% of r. since the actual memory capacity of a realistic dbms is typically larger, we develop a novel algorithm, which integrates our theoretical findings with carefully-designed heuristics that leverage the additional memory to improve i/o efficiency. our technique reports all outliers by scanning the dataset at most twice (in some cases, even once), and significantly outperforms the existing solutions by a factor up to an order of magnitude.
mining comparable bilingual text corpora for cross-language information integration. integrating information in multiple natural languages is a challenging task that often requires manually created linguistic resources such as a bilingual dictionary or examples of direct translations of text. in this paper, we propose a general cross-lingual text mining method that does not rely on any of these resources, but can exploit comparable bilingual text corpora to discover mappings between words and documents in different languages. comparable text corpora are collections of text documents in different languages that are about similar topics; such text corpora are often naturally available (e.g., news articles in different languages published in the same time period). the main idea of our method is to exploit frequency correlations of words in different languages in the comparable corpora and discover mappings between words in different languages. such mappings can then be used to further discover mappings between documents in different languages, achieving cross-lingual information integration. evaluation of the proposed method on a 120mb chinese-english comparable news collection shows that the proposed method is effective for mapping words and documents in english and chinese. since our method only relies on naturally available comparable corpora, it is generally applicable to any language pairs as long as we have comparable corpora.
learning domain-independent string transformation weights for high accuracy object identification. the task of object identification occurs when integrating information from multiple websites. the same data objects can exist in inconsistent text formats across sites, making it difficult to identify matching objects using exact text match. previous methods of object identification have required manual construction of domain-specific string transformations or manual setting of general transformation parameter weights for recognizing format inconsistencies. this manual process can be time consuming and error-prone. we have developed an object identification system called active atlas [18], which applies a set of domain-independent string transformations to compare the objects' shared attributes in order to identify matching objects. in this paper, we discuss extensions to the active atlas system, which allow it to learn to tailor the weights of a set of general transformations to a specific application domain through limited user input. the experimental results demonstrate that this approach achieves higher accuracy and requires less user involvement than previous methods across various application domains.
paintingclass: interactive construction, visualization and exploration of decision trees. decision trees are commonly used for classification. we propose to use decision trees not just for classification but also for the wider purpose of knowledge discovery, because visualizing the decision tree can reveal much valuable information in the data. we introduce paintingclass, a system for interactive construction, visualization and exploration of decision trees. paintingclass provides an intuitive layout and convenient navigation of the decision tree. paintingclass also provides the user the means to interactively construct the decision tree. each node in the decision tree is displayed as a visual projection of the data. through actual examples and comparison with other classification methods, we show that the user can effectively use paintingclass to construct a decision tree and explore the decision tree to gain additional knowledge.
a generative probabilistic approach to visualizing sets of symbolic sequences. there is a notable interest in extending probabilistic generative modeling principles to accommodate for more complex structured data types. in this paper we develop a generative probabilistic model for visualizing sets of discrete symbolic sequences. the model, a constrained mixture of discrete hidden markov models, is a generalization of density-based visualization methods previously developed for static data sets. we illustrate our approach on sequences representing web-log data and chorals by j.s. bach.
center-piece subgraphs: problem definition and fast solutions. given q nodes in a social network (say, authorship network), how can we find the node/author that is the center-piece, and has direct or indirect connections to all, or most of them? for example, this node could be the common advisor, or someone who started the research area that the q nodes belong to. isomorphic scenarios appear in law enforcement (find the master-mind criminal, connected to all current suspects), gene regulatory networks (find the protein that participates in pathways with all or most of the given q proteins), viral marketing and many more.connection subgraphs is an important first step, handling the case of q=2 query nodes. then, the connection subgraph algorithm finds the b intermediate nodes, that provide a good connection between the two original query nodes.here we generalize the challenge in multiple dimensions: first, we allow more than two query nodes. second, we allow a whole family of queries, ranging from 'or' to 'and', with 'softand' in-between. finally, we design and compare a fast approximation, and study the quality/speed trade-off.we also present experiments on the dblp dataset. the experiments confirm that our proposed method naturally deals with multi-source queries and that the resulting subgraphs agree with our intuition. wall-clock timing results on the dblp dataset show that our proposed approximation achieve good accuracy for about 6:1 speedup.
regression error characteristic surfaces. this paper presents a generalization of regression error characteristic (rec) curves. rec curves describe the cumulative distribution function of the prediction error of models and can be seen as a generalization of roc curves to regression problems. rec curves provide useful information for analyzing the performance of models, particularly when compared to error statistics like for instance the mean squared error. in this paper we present regression error characteristic (rec) surfaces that introduce a further degree of detail by plotting the cumulative distribution function of the errors across the distribution of the target variable, i.e. the joint cumulative distribution function of the errors and the target variable. this provides a more detailed analysis of the performance of models when compared to rec curves. this extra detail is particularly relevant in applications with non-uniform error costs, where it is important to study the performance of models for specific ranges of the target variable. in this paper we present the notion of rec surfaces, describe how to use them to compare the performance of models, and illustrate their use with an important practical class of applications: the prediction of rare extreme values.
tri-plots: scalable tools for multidimensional data mining. we focus on the problem of finding patterns across two large, multidimensional datasets. for example, given feature vectors of healthy and of non-healthy patients, we want to answer the following questions: are the two clouds of points separable? what is the smallest/largest pair-wise distance across the two datasets? which of the two clouds does a new point (feature vector) come from?we propose a new tool, the tri-plot, and its generalization, the pq-plot, which help us answer the above questions. we provide a set of rules on how to interpret a tri-plot, and we apply these rules on synthetic and real datasets. we also show how to use our tool for classification, when traditional methods (nearest neighbor, classification trees) may fail.
learning a complex metabolomic dataset using random forests and support vector machines. metabolomics is the "omics" science of biochemistry. the associated data include the quantitative measurements of all small molecule metabolites in a biological sample. these datasets provide a window into dynamic biochemical networks and conjointly with other "omic" data, genes and proteins, have great potential to unravel complex human diseases. the dataset used in this study has 63 individuals, normal and diseased, and the diseased are drug treated or not, so there are three classes. the goal is to classify these individuals using the observed metabolite levels for 317 measured metabolites. there are a number of statistical challenges: non-normal data, the number of samples is less than the number of metabolites; there are missing data and the fact that data are missing is informative (assay values below detection limits can point to a specific class); also, there are high correlations among the metabolites. we investigate support vector machines (svm), and random forest (rf), for outlier detection, variable selection and classification. we use the variables selected with rf in svm and visa versa. the benefit of this study is insight into interplay of variable selection and classification methods. we link our selected predictors to the biochemistry of the disease.
time and sample efficient discovery of markov blankets and direct causal relations. data mining with bayesian network learning has two important characteristics: under conditions learned edges between variables correspond to casual influences, and second, for every variable t in the network a special subset (markov blanket) identifiable by the network is the minimal variable set required to predict t. however, all known algorithms learning a complete bn do not scale up beyond a few hundred variables. on the other hand, all known sound algorithms learning a local region of the network require an exponential number of training instances to the size of the learned region.the contribution of this paper is two-fold. we introduce a novel local algorithm that returns all variables with direct edges to and from a target variable t as well as a local algorithm that returns the markov blanket of t. both algorithms (i) are sound, (ii) can be run efficiently in datasets with thousands of variables, and (iii) significantly outperform in terms of approximating the true neighborhood previous state-of-the-art algorithms using only a fraction of the training size required by the existing methods. a fundamental difference between our approach and existing ones is that the required sample depends on the generating graph connectivity and not the size of the local region; this yields up to exponential savings in sample relative to previously known algorithms. the results presented here are promising not only for discovery of local causal structure, and variable selection for classification, but also for the induction of complete bns.
efficient kernel feature extraction for massive data sets. maximum margin discriminant analysis (mmda) was proposed that uses the margin idea for feature extraction. it often outperforms traditional methods like kernel principal component analysis (kpca) and kernel fisher discriminant analysis (kfd). however, as in other kernel methods, its time complexity is cubic in the number of training points m, and is thus computationally inefficient on massive data sets. in this paper, we propose an (1+ε)2-approximation algorithm for obtaining the mmda features by extending the core vector machines. the resultant time complexity is only linear in m, while its space complexity is independent of m. extensive comparisons with the original mmda, kpca, and kfd on a number of large data sets show that the proposed feature extractor can improve classification accuracy, and is also faster than these kernel-based methods by more than an order of magnitude.
handling very large numbers of association rules in the analysis of microarray data. the problem of analyzing microarray data became one of important topics in bioinformatics over the past several years, and different data mining techniques have been proposed for the analysis of such data. in this paper, we propose to use association rule discovery methods for determining associations among expression levels of different genes. one of the main problems related to the discovery of these associations is the scalability issue. microarrays usually contain very large numbers of genes that are sometimes measured in 10,000s. therefore, analysis of such data can generate a very large number of associations that can often be measured in millions. the paper addresses this problem by presenting a method that enables biologists to evaluate these very large numbers of discovered association rules during the post-analysis stage of the data mining process. this is achieved by providing several rule evaluation operators, including rule grouping, filtering, browsing, and data inspection operators, that allow biologists to validate multiple individual gane regulation patterns at a time. by iteratively applying these operators, biologists can explore a significant part of all the initially generated rules in an acceptable period of time and thus answer biological questions that are of a particular interest to him or her. to validate our method, we tested our system on the microarray data pertaining to the studies of environmental hazards and their influence of gane expression processes. as a result, we managed to answer several questions that were of interest to the biologists that had collected this data.
querying multiple sets of discovered rules. rule mining is an important data mining task that has been applied to numerous real-world applications. often a rule mining system generates a large number of rules and only a small subset of them is really useful in applications. although there exist some systems allowing the user to query the discovered rules, they are less suitable for complex ad hoc querying of multiple data mining rulebases to retrieve interesting rules. in this paper, we propose a new powerful rule query language rule-ql for querying multiple rulebases that is modeled after sql and has rigorous theoretical foundations of a rule-based calculus. in particular, we first propose a rule-based calculus rc based on the first-order logic, and then present the language rule-ql that is at least as expressive as the safe fragment of rc. we also propose a number of efficient query evaluation techniques for rule-ql and test them experimentally on some representative queries to demonstrate the feasibility of rule-ql.
single-shot detection of multiple categories of text using parametric mixture models. in this paper, we address the problem of detecting multiple topics or categories of text where each text is not assumed to belong to one of a number of mutually exclusive categories. conventionally, the binary classification approach has been employed, in which whether or not text belongs to a category is judged by the binary classifier for every category. in this paper, we propose a more sophisticated approach to simultaneously detect multiple categories of text using parametric mixture models (pmms), newly presented in this paper. pmms are probabilistic generative models for text that has multiple categories. our pmms are essentially different from the conventional mixture of multinomial distributions in the sense that in the former several basis multinomial parameters are mixed in the parameter space, while in the latter several multinomial components are mixed. we derive efficient learning algorithms for pmms within the framework of the maximum a posteriori estimate. we also empirically show that our method can outperform the conventional binary approach when applied to multitopic detection of world wide web pages, focusing on those from the "yahoo.com" domain.
what's the code?: automatic classification of source code archives. there are various source code archives on the world wide web. these archives are usually organized by application categories and programming languages. however, manually organizing source code repositories is not a trivial task since they grow rapidly and are very large (on the order of terabytes). we demonstrate machine learning methods for automatic classification of archived source code into eleven application topics and ten programming languages. for topical classification, we concentrate on c and c++ programs from the ibiblio and the sourceforge archives. support vector machine (svm) classifiers are trained on examples of a given programming language or programs in a specified category. we show that source code can be accurately and automatically classified into topical categories and can be identified to be in a specific programming language class.
finding partial orders from unordered 0-1 data. in applications such as paleontology and medical genetics the 0-1 data has an underlying unknown order (the ages of the fossil sites, the locations of markers in the genome). the order might be total or partial: for example, two sites in different parts of the globe might be ecologically incomparable, or the ordering of certain markers might be different in different subgroups of the data. we consider the following problem. given a table over a set of 0-1 variables, find a partial order for the rows minimizing a score function and being as specific as possible. the score function can be, e.g., the number of changes from 1 to 0 in a column (for paleontology) or the likelihood of the marker sequence (for genomic data). our solution for this task first constructs small totally ordered fragments of the partial order, then finds good orientations for the fragments, and finally uses a simple and efficient heuristic method for finding a partial order that corresponds well with the collection of fragments. we describe the method, discuss its properties, and give empirical results on paleontological data demonstrating the usefulness of the method. in the application the use of the method highlighted some previously unknown properties of the data and pointed out probable errors in the data.
privacy preserving association rule mining in vertically partitioned data. privacy considerations often constrain data mining projects. this paper addresses the problem of association rule mining where transactions are distributed across sources. each site holds some attributes of each transaction, and the sites wish to collaborate to identify globally valid association rules. however, the sites must not reveal individual transaction data. we present a two-party algorithm for efficiently discovering frequent itemsets with minimum support levels, without either site revealing individual transaction values.
privacy-preserving -means clustering over vertically partitioned data. privacy and security concerns can prevent sharing of data, derailing data mining projects. distributed knowledge discovery, if done correctly, can alleviate this problem. the key is to obtain valid results, while providing guarantees on the (non)disclosure of data. we present a method for k-means clustering when different sites contain different attributes for a common set of entities. each site learns the cluster of each entity, but learns nothing about the attributes at other sites.
camouflaged fraud detection in domains with complex relationships. we describe a data mining system to detect frauds that are camouflaged to look like normal activities in domains with high number of known relationships. examples include accounting fraud detection for rating and investment, insider attacks on corporate networks, and health care insurance fraud. our goal is to help analysts who are overwhelmed with information about companies or on-line system access logs or insurance claims to focus their attentions on features that cause damage in the future. we focused on accounting fraud where the task is to detect the subset of companies that were potentially committing accounting fraud within the total population of public companies that file quarterly and annual filings with the securities and exchange commission (sec). using (a) representation of changes, (b) a mix of decision tree learning, locally weighted logistic regression, k-means clustering, and constant regression in a two phase pipe line, we developed models that rank companies based on the probability of forecasting future damaging performance. the learned models were tested extensively over four years with public data available from sec filings and private data available from rating companies and investment firms. cross validation experiments and analyst based validation of private experiments were found to show that the approach performed as well as or better than domain experts and discovered new relationships that domain experts did not use on a regular basis. finally, the detections preceded public knowledge of such problems by six to eighteen months.
non-linear dimensionality reduction techniques for classification and visualization. in this paper we address the issue of using local embeddings for data visualization in two and three dimensions, and for classification. we advocate their use on the basis that they provide an efficient mapping procedure from the original dimension of the data, to a lower intrinsic dimension. we depict how they can accurately capture the user's perception of similarity in high-dimensional data for visualization purposes. moreover, we exploit the low-dimensional mapping provided by these embeddings, to develop new classification techniques, and we show experimentally that the classification accuracy is comparable (albeit using fewer dimensions) to a number of other classification procedures.
rotation invariant distance measures for trajectories. for the discovery of similar patterns in 1d time-series, it is very typical to perform a normalization of the data (for example a transformation so that the data follow a zero mean and unit standard deviation). such transformations can reveal latent patterns and are very commonly used in datamining applications. however, when dealing with multidimensional time-series, which appear naturally in applications such as video-tracking, motion-capture etc, similar motion patterns can also be expressed at different orientations. it is therefore imperative to provide support for additional transformations, such as rotation. in this work, we transform the positional information of moving data, into a space that is translation, scale and rotation invariant. our distance measure in the new space is able to detect elastic matches and can be efficiently lower bounded, thus being computationally tractable. the proposed methods are easy to implement, fast to compute and can have many applications for real world problems, in areas such as handwriting recognition and posture estimation in motion-capture data. finally, we empirically demonstrate the accuracy and the efficiency of the technique, using real and synthetic handwriting data.
indexing multi-dimensional time-series with support for multiple distance measures. although most time-series data mining research has concentrated on providing solutions for a single distance function, in this work we motivate the need for a single index structure that can support multiple distance measures. our specific area of interest is the efficient retrieval and analysis of trajectory similarities. trajectory datasets are very common in environmental applications, mobility experiments, video surveillance and are especially important for the discovery of certain biological patterns. our primary similarity measure is based on the longest common subsequence (lcss) model, that offers enhanced robustness, particularly for noisy data, which are encountered very often in real world applications. however, our index is able to accommodate other distance measures as well, including the ubiquitous euclidean distance, and the increasingly popular dynamic time warping (dtw). while other researchers have advocated one or other of these similarity measures, a major contribution of our work is the ability to support all these measures without the need to restructure the index. our framework guarantees no false dismissals and can also be tailored to provide much faster response time at the expense of slightly reduced precision/recall. the experimental results demonstrate that our index can help speed-up the computation of expensive similarity measures such as the lcss and the dtw.
1-dimensional splines as building blocks for improving accuracy of risk outcomes models. transformation of both the response variable and the predictors is commonly used in fitting regression models. however, these transformation methods do not always provide the maximum linear correlation between the response variable and the predictors, especially when there are non-linear relationships between predictors and the response such as the medical data set used in this study. a spline based transformation method is proposed that is second order smooth, continuous, and minimizes the mean squared error between the response and each predictor. since the computation time for generating this spline is o(n), the processing time is reasonable with massive data sets. in contrast to cubic smoothing splines, the resulting transformation equations also display a high level of efficiency for scoring. data used for predicting health outcomes contains an abundance of non-linear relationships between predictors and the outcomes requiring an algorithm for modeling them accurately. thus, a transformation that fits an adaptive cubic spline to each of a set of variables is proposed. these curves are used as a set of transformation functions on the predictors. a case study of how the transformed variables can be fed into a simple linear regression model to predict risk outcomes is presented. the results show significant improvement over the performance of the original variables in both linear and non-linear models.
on interactive visualization of high-dimensional data using the hyperbolic plane. we propose a novel projection based visualization method for high-dimensional datasets by combining concepts from mds and the geometry of the hyperbolic spaces. our approach hyperbolic multi-dimensional scaling (h-mds) extends earlier work [7] using hyperbolic spaces for visualization of tree structures data ( "hyperbolic tree browser" ).by borrowing concepts from multi-dimensional scaling we map proximity data directly into the 2-dimensional hyperbolic space (h2). this removes the restriction to "quasihierarchical", graph-based data -- limiting previous work. since a suitable distance function can convert all kinds of data to proximity (or distance-based) data this type of data can be considered the most general.we used the circular poincar&eacute; model of the h2 which allows effective human-computer interaction: by moving the "focus" via mouse the user can navigate in the data without loosing the "context". in h2 the "fish-eye" behavior originates not simply by a non-linear view transformation but rather by extraordinary, non-euclidean properties of the h2. especially, the exponential growth of length and area of the underlying space makes the h2 a prime target for mapping hierarchical and (now also) high-dimensional data.we present several high-dimensional mapping examples including synthetic and real world data and a successful application for unstructured text. by analyzing and integrating multiple film critiques from news:rec.art.movies.reviews and the internet movie database, each movie becomes placed within the h2. here the idea is, that related films share more words in their reviews than unrelated. their semantic proximity leads to a closer arrangement. the result is a kind of high-level content structured display allowing the user to explore the "space of movies".
anonymizing sequential releases. an organization makes a new release as new information become available, releases a tailored view for each data request, releases sensitive information and identifying information separately. the availability of related releases sharpens the identification of individuals by a global quasi-identifier consisting of attributes from related releases. since it is not an option to anonymize previously released data, the current release must be anonymized to ensure that a global quasi-identifier is not effective for identification. in this paper, we study the sequential anonymization problem under this assumption. a key question is how to anonymize the current release so that it cannot be linked to previous releases yet remains useful for its own release purpose. we introduce the lossy join, a negative property in relational database design, as a way to hide the join relationship among releases, and propose a scalable and practical solution.
mining concept-drifting data streams using ensemble classifiers. recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud protection, target marketing, network intrusion detection, etc. conventional knowledge discovery tools are facing two challenges, the overwhelming volume of the streaming data, and the concept drifts. in this paper, we propose a general framework for mining concept-drifting data streams using weighted ensemble classifiers. we train an ensemble of classification models, such as c4.5, ripper, naive beyesian, etc., from sequential chunks of the data stream. the classifiers in the ensemble are judiciously weighted based on their expected classification accuracy on the test data under the time-evolving environment. thus, the ensemble approach improves both the efficiency in learning the model and the accuracy in performing classification. our empirical study shows that the proposed methods have substantial advantage over single-classifier approaches in prediction accuracy, and the ensemble framework is effective for a variety of classification models.
closet+: searching for the best strategies for mining frequent closed itemsets. mining frequent closed itemsets provides complete and non-redundant results for frequent pattern analysis. extensive studies have proposed various strategies for efficient frequent closed itemset mining, such as depth-first search vs. breadthfirst search, vertical formats vs. horizontal formats, tree-structure vs. other data structures, top-down vs. bottom-up traversal, pseudo projection vs. physical projection of conditional database, etc. it is the right time to ask "what are the pros and cons of the strategies?" and "what and how can we pick and integrate the best strategies to achieve higher performance in general cases?"in this study, we answer the above questions by a systematic study of the search strategies and develop a winning algorithm closet+. closet+ integrates the advantages of the previously proposed effective strategies as well as some ones newly developed here. a thorough performance study on synthetic and real data sets has shown the advantages of the strategies and the improvement of closet+ over existing mining algorithms, including closet, charm and op, in terms of runtime, memory usage and scalability.
mining unexpected rules by pushing user dynamics. unexpected rules are interesting because they are either previously unknown or deviate from what prior user knowledge would suggest. in this paper, we study three important issues that have been previously ignored in mining unexpected rules. first, the unexpectedness of a rule depends on how the user prefers to apply the prior knowledge to a given scenario, in addition to the knowledge itself. second, the prior knowledge should be considered right from the start to focus the search on unexpected rules. third, the unexpectedness of a rule depends on what other rules the user has seen so far. thus, only rules that remain unexpected given what the user has seen should be considered interesting. we develop an approach that addresses all three problems above and evaluate it by means of experiments focusing on finding interesting rules.
web object indexing using domain knowledge. a web object is defined to represent any meaningful object embedded in web pages (e.g. images, music) or pointed to by hyperlinks (e.g. downloadable files). in many cases, users would like to search for information of a certain 'object', rather than a web page containing the query terms. to facilitate web object searching and organizing, in this paper, we propose a novel approach to web object indexing, by discovering its inherent structure information with existed domain knowledge. in our approach, first, layered lsi spaces are built for a better representation of the hierarchically structured domain knowledge, in order to emphasize the specific semantics and term space in each layer of the domain knowledge. meanwhile, the web object representation is constructed by hyperlink analysis, and further pruned to remove the noises. then an optimal matching between the web object and the domain knowledge is performed, in order to pick out the structure attributes of the web object from the knowledge. finally, the obtained structure attributes are used to re-organize and index the web objects. our approach also indicates a new promising way to use trust-worthy deep web knowledge to help organize dispersive information of surface web.
topics over time: a non-markov continuous-time model of topical trends. this paper presents an lda-style topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. unlike other recent work that relies on markov assumptions or discretization of time, here each topic is associated with a continuous distribution over timestamps, and for each generated document, the mixture distribution over topics is influenced by both word co-occurrences and the document's timestamp. thus, the meaning of a particular topic can be relied upon as constant, but the topics' occurrence and correlations change significantly over time. we present results on nine months of personal email, 17 years of nips research papers and over 200 years of presidential state-of-the-union addresses, showing improved topics, better timestamp prediction, and interpretable trends.
summarizing itemset patterns using probabilistic models. in this paper, we propose a novel probabilistic approach to summarize frequent itemset patterns. such techniques are useful for summarization, post-processing, and end-user interpretation, particularly for problems where the resulting set of patterns are huge. in our approach items in the dataset are modeled as random variables. we then construct a markov random fields (mrf) on these variables based on frequent itemsets and their occurrence statistics. the summarization proceeds in a level-wise iterative fashion. occurrence statistics of itemsets at the lowest level are used to construct an initial mrf. statistics of itemsets at the next level can then be inferred from the model. we use those patterns whose occurrence can not be accurately inferred from the model to augment the model in an iterative manner, repeating the procedure until all frequent itemsets can be modeled. the resulting mrf model affords a concise and useful representation of the original collection of itemsets. extensive empirical study on real datasets show that the new approach can effectively summarize a large number of itemsets and typically significantly outperforms extant approaches.
pattern-based similarity search for microarray data. one fundamental task in near-neighbor search as well as other similarity matching efforts is to find a distance function that can efficiently quantify the similarity between two objects in a meaningful way. in dna microarray analysis, the expression levels of two closely related genes may rise and fall synchronously in response to a set of experimental stimuli. although the magnitude of their expression levels may not be close, the patterns they exhibit can be very similar. unfortunately, none of the conventional distance metrics such as the lp norm can model this similarity effectively. in this paper, we study the near-neighbor search problem based on this new type of similarity. we propose to measure the distance between two genes by subspace pattern similarity, i.e., whether they exhibit a synchronous pattern of rise and fall on a subset of dimensions. we then present an efficient algorithm for subspace near-neighbor search based on pattern similarity distance, and we perform tests on various data sets to show its effectiveness.
item selection by "hub-authority" profit ranking. a fundamental problem in business and other applications is ranking items with respect to some notion of profit based on historical transactions. the difficulty is that the profit of one item not only comes from its own sales, but also from its influence on the sales of other items, i.e., the "cross-selling effect". in this paper, we draw an analogy between this influence and the mutual reinforcement of hub/authority web pages. based on this analogy, we present a novel approach to the item ranking problem.we apply this ranking approach to solve two selection problems. in size-constrained selection, the maximum number of items that can be selected is fixed. in cost-constrained selection, there is no maximum number of items to be selected, but there is some cost associated with the selection of each item. in both cases, the question is what items should be selected to maximize the profit. empirically, we show that this method finds profitable items in the presence of cross-selling effect.
scalable mining of large disk-based graph databases. mining frequent structural patterns from graph databases is an interesting problem with broad applications. most of the previous studies focus on pruning unfruitful search subspaces effectively, but few of them address the mining on large, disk-based databases. as many graph databases in applications cannot be held into main memory, scalable mining of large, disk-based graph databases remains a challenging problem. in this paper, we develop an effective index structure, adi (for <u>ad</u>jacency <u>i</u>ndex), to support mining various graph patterns over large databases that cannot be held into main memory. the index is simple and efficient to build. moreover, the new index structure can be easily adopted in various existing graph pattern mining algorithms. as an example, we adapt the well-known gspan algorithm by using the adi structure. the experimental results show that the new index structure enables the scalable graph pattern mining over large databases. in one set of the experiments, the new disk-based method can mine graph databases with one million graphs, while the original gspan algorithm can only handle databases of up to 300 thousand graphs. moreover, our new method is faster than gspan when both can run in main memory.
suppressing model overfitting in mining concept-drifting data streams. mining data streams of changing class distributions is important for real-time business decision support. the stream classifier must evolve to reflect the current class distribution. this poses a serious challenge. on the one hand, relying on historical data may increase the chances of learning obsolete models. on the other hand, learning only from the latest data may lead to biased classifiers, as the latest data is often an unrepresentative sample of the current class distribution. the problem is particularly acute in classifying rare events, when, for example, instances of the rare class do not even show up in the most recent training data. in this paper, we use a stochastic model to describe the concept shifting patterns and formulate this problem as an optimization one: from the historical and the current training data that we have observed, find the most-likely current distribution, and learn a classifier based on the most-likely distribution. we derive an analytic solution and approximate this solution with an efficient algorithm, which calibrates the influence of historical data carefully to create an accurate classifier. we evaluate our algorithm with both synthetic and real-world datasets. our results show that our algorithm produces accurate and efficient classification.
mining user session data to facilitate user interaction with a customer service knowledge base in rightnow web. rightnow web is an integrated software package for web-based customer service that has, at its core, a database of answers to frequently asked questions (faqs). one major design goal is to facilitate end-user interaction with this dynamic document collection, i.e. make it as easy and efficient as possible for users to browse the collection and locate desired information. to this end, we perform several types of analysis on the session tracking database that records user navigation histories. first, using both explicit and implicit measures of user satisfaction, we infer a "solved count" representing the average utility of an faq. second, using the user navigation patterns we construct a link matrix representing connections between faqs. the technique of building up the link matrix and using it to advise users on related information amounts to a form of the "swarm intelligence" method of finding optimal paths. both solved count and the link matrix are continuously updated as users interact with the site; furthermore, they are periodically "aged" to emphasize recent activity. the synergistic combination of these techniques allows users to learn from the database in a more effective manner, as evidenced by usage statistics.
discovering associations with numeric variables. this paper further develops aumann and lindell's [3] proposal for a variant of association rules for which the consequent is a numeric variable. it is argued that these rules can discover useful interactions with numeric data that cannot be discovered directly using traditional association rules with discretization. alternative measures for identifying interesting rules are proposed. efficient algorithms are presented that enable these rules to be discovered for dense data sets for which application of auman and lindell's algorithm is infeasible.
discovering significant rules. in many applications, association rules will only be interesting if they represent non-trivial correlations between all constituent items. numerous techniques have been developed that seek to avoid false discoveries. however, while all provide useful solutions to aspects of this problem, none provides a generic solution that is both flexible enough to accommodate varying definitions of true and false discoveries and powerful enough to provide strict control over the risk of false discoveries. this paper presents generic techniques that allow definitions of true and false discoveries to be specified in terms of arbitrary statistical hypothesis tests and which provide strict control over the experiment wise risk of false discoveries.
on detecting differences between groups. understanding the differences between contrasting groups is a fundamental task in data analysis. this realization has led to the development of a new special purpose data mining technique, contrast-set mining. we undertook a study with a retail collaborator to compare contrast-set mining with existing rule-discovery techniques. to our surprise we observed that straightforward application of an existing commercial rule-discovery system, magnum opus, could successfully perform the contrast-set-mining task. this led to the realization that contrast-set mining is a special case of the more general rule-discovery task. we present the results of our study together with a proof of this conclusion.
a large-scale analysis of query logs for assessing personalization opportunities. query logs, the patterns of activity left by millions of users, contain a wealth of information that can be mined to aid personalization. we perform a large-scale study of yahoo! search engine logs, tracking 1.35 million browser-cookies over a period of 6 months. we define metrics to address questions such as 1) how much history is available?, 2) how do users' topical interests vary, as reflected by their queries?, and 3) what can we learn from user clicks? we find that there is significantly more expected history for the user of a randomly picked query than for a randomly picked user. we show that users exhibit consistent topical interests that vary between users. we also see that user clicks indicate a variety of special interests. our findings shed light on user activity and can inform future personalization efforts.
semi-supervised time series classification. the problem of time series classification has attracted great interest in the last decade. however current research assumes the existence of large amounts of labeled training data. in reality, such data may be very difficult or expensive to obtain. for example, it may require the time and expertise of cardiologists, space launch technicians, or other domain specialists. as in many other domains, there are often copious amounts of unlabeled data available. for example, the physiobank archive contains gigabytes of ecg data. in this work we propose a semi-supervised technique for building time series classifiers. while such algorithms are well known in text domains, we will show that special considerations must be made to make them both efficient and effective for the time series domain. we evaluate our work with a comprehensive set of experiments on diverse data sources including electrocardiograms, handwritten documents, and video datasets. the experimental results demonstrate that our approach requires only a handful of labeled examples to construct accurate classifiers.
knowledge-based data mining. we describe techniques for combining two types of knowledge systems: expert and machine learning. both the expert system and the learning system represent information by logical decision rules or trees. unlike the classical views of knowledge-base evaluation or refinement, our view accepts the contents of the knowledge base as completely correct. the knowledge base and the results of its stored cases will provide direction for the discovery of new relationships in the form of newly induced decision rules. an expert system called seas was built to discover sales leads for computer products and solutions. the system interviews executives by asking questions, and based on the responses, recommends products that may improve a business' operations. leveraging this expert system, we record the results of the interviews and the program's recommendations. the very same data stored by the expert system is used to find new predictive rules. among the potential advantages of this approach are (a) the capability to spot new sales trends and (b) the substitution of less expensive probabilistic rules that use database data instead of interviews.
a system for real-time competitive market intelligence. a method is described for real-time market intelligence and competitive analysis. news stories are collected online for a designated group of companies. the goal is to detect critical differences in the text written about a company versus the text for its competitors. a solution is found by mapping the task into a non-stationary text categorization model. the overall design consists of the following components: (a) a real-time crawler that monitors newswires for stories about the competitors (b) a conditional document retriever that selects only those documents that meet the indicated conditions (c) text analysis techniques that convert the documents to a numerical format (d) rule induction methods for finding patterns in data (e) presentation techniques for displaying results. the method is extended to combine text with numerical measures, such as those based on stock prices and market capitalizations, that allow for more objective evaluations and projections.
algorithms for estimating relative importance in networks. large and complex graphs representing relationships among sets of entities are an increasingly common focus of interest in data analysis---examples include social networks, web graphs, telecommunication networks, and biological networks. in interactive analysis of such data a natural query is "which entities are most important in the network relative to a particular individual or set of individuals?" we investigate the problem of answering such queries in this paper, focusing in particular on defining and computing the importance of nodes in a graph relative to one or more root nodes. we define a general framework and a number of different algorithms, building on ideas from social networks, graph theory, markov models, and web graph analysis. we experimentally evaluate the different properties of these algorithms on toy graphs and demonstrate how our approach can be used to study relative importance in real-world networks including a network of interactions among september 11th terrorists, a network of collaborative research in biotechnology among companies and universities, and a network of co-authorship relationships among computer science researchers.
privacy-preserving bayesian network structure computation on distributed heterogeneous data. as more and more activities are carried out using computers and computer networks, the amount of potentially sensitive data stored by business, governments, and other parties increases. different parties may wish to benefit from cooperative use of their data, but privacy regulations and other privacy concerns may prevent the parties from sharing their data. privacy-preserving data mining provides a solution by creating distributed data mining algorithms in which the underlying data is not revealed.in this paper, we present a privacy-preserving protocol for a particular data mining task: learning the bayesian network structure for distributed heterogeneous data. in this setting, two parties owning confidential databases wish to learn the structure of bayesian network on the combination of their databases without revealing anything about their data to each other. we give an efficient and privacy-preserving version of the k2 algorithm to construct the structure of a bayesian network for the parties' joint data.
screening and interpreting multi-item associations based on log-linear modeling. association rules have received a lot of attention in the data mining community since their introduction. the classical approach to find rules whose items enjoy high support (appear in a lot of the transactions in the data set) is, however, filled with shortcomings. it has been shown that support can be misleading as an indicator of how interesting the rule is. alternative measures, such as lift, have been proposed. more recently, a paper by dumouchel et al. proposed the use of all-two-factor loglinear models to discover sets of items that cannot be explained by pairwise associations between the items involved. this approach, however, has its limitations, since it stops short of considering higher order interactions (other than pairwise) among the items. in this paper, we propose a method that examines the parameters of the fitted loglinear models to find all the significant association patterns among the items. since fitting loglinear models for large data sets can be computationally prohibitive, we apply graph-theoretical results to divide the original set of items into components (sets of items) that are statistically independent from each other. we then apply loglinear modeling to each of the components and find the interesting associations among items in them. the technique is experimentally evaluated with a real data set (insurance data) and a series of synthetic data sets. the results show that the technique is effective in finding interesting associations among the items involved.
incremental approximate matrix factorization for speeding up support vector machines. traditional decomposition-based solutions to support vector machines (svms) suffer from the widely-known scalability problem. for example, given a one-million training set, it takes about six days for svmlight to run on a pentium-4 sever with 8g-byte memory. in this paper, we propose an incremental algorithm, which performs approximate matrix-factorization operations, to speed up svms. two approximate factorization schemes, kronecker and incomplete cholesky, are utilized in the primal-dual interior-point method (ipm) to directly solve the quadratic optimization problem in svms. we found out that a coarse approximate algorithm enjoys good speedup performance but may suffer from poor training accuracy. conversely, a fine-grained approximate algorithm enjoys good training quality but may suffer from long training time. we subsequently propose an incremental training algorithm, which uses the approximate ipm solution of a coarse factorization to initialize the ipm of a fine-grained factorization. extensive empirical studies show that our proposed incremental algorithm with approximate factorizations substantially speeds up svm training while maintaining high training accuracy. in addition, we show that our proposed algorithm is highly parallelizable on an intel dual-coreprocessor.
formulating distance functions via the kernel trick. tasks of data mining and information retrieval depend on a good distance function for measuring similarity between data instances. the most effective distance function must be formulated in a context-dependent (also application-, data-, and user-dependent) way. in this paper, we propose to learn a distance function by capturing the nonlinear relationships among contextual information provided by the application, data, or user. we show that through a process called the "kernel trick," such nonlinear relationships can be learned efficiently in a projected space. theoretically, we substantiate that our method is both sound and optimal. empirically, using several datasets and applications, we demonstrate that our method is effective and useful.
mining scale-free networks using geodesic clustering. many real-world graphs have been shown to be scale-free---vertex degrees follow power law distributions, vertices tend to cluster, and the average length of all shortest paths is small. we present a new model for understanding scale-free networks based on multilevel geodesic approximation, using a new data structure called a multilevel mesh.using this multilevel framework, we propose a new kind of graph clustering for data reduction of very large graph systems such as social, biological, or electronic networks. finally, we apply our algorithms to real-world social networks and protein interaction graphs to show that they can reveal knowledge embedded in underlying graph structures. we also demonstrate how our data structures can be used to quickly answer approximate distance and shortest path queries on scale-free networks.
the anatomy of a multimodal information filter. the proliferation of objectionable information on the internet has reached a level of serious concern. to empower end-users with the choice of blocking undesirable and offensive websites, we propose a multimodal information filter, named morf. in this paper, we present morf's core components: its confidence-based classifier, a cross-bagging ensemble scheme, and multimodal classification algorithm. empirical studies and initial statistics collected from the morf filters deployed at sites in the u.s. and asia show that morf is both efficient and effective, due to our classification methods.
a refinement approach to handling model misfit in text categorization. text categorization or classification is the automated assigning of text documents to pre-defined classes based on their contents. this problem has been studied in information retrieval, machine learning and data mining. so far, many effective techniques have been proposed. however, most techniques are based on some underlying models and/or assumptions. when the data fits the model well, the classification accuracy will be high. however, when the data does not fit the model well, the classification accuracy can be very low. in this paper, we propose a refinement approach to dealing with this problem of model misfit. we show that we do not need to change the classification technique itself (or its underlying model) to make it more flexible. instead, we propose to use successive refinements of classification on the training data to correct the model misfit. we apply the proposed technique to improve the classification performance of two simple and efficient text classifiers, the rocchio classifier and the na&iuml;ve bayesian classifier. these techniques are suitable for very large text collections because they allow the data to reside on disk and need only one scan of the data to build a text classifier. extensive experiments on two benchmark document corpora show that the proposed technique is able to improve text categorization accuracy of the two techniques dramatically. in particular, our refined model is able to improve the na&iuml;ve bayesian or rocchio classifier's prediction performance by 45% on average.
coherent closed quasi-clique discovery from large dense graph databases. frequent coherent subgraphs can provide valuable knowledge about the underlying internal structure of a graph database, and mining frequently occurring coherent subgraphs from large dense graph databases has been witnessed several applications and received considerable attention in the graph mining community recently. in this paper, we study how to efficiently mine the complete set of coherent closed quasi-cliques from large dense graph databases, which is an especially challenging task due to the downward-closure property no longer holds. by fully exploring some properties of quasi-cliques, we propose several novel optimization techniques, which can prune the unpromising and redundant sub-search spaces effectively. meanwhile, we devise an efficient closure checking scheme to facilitate the discovery of only closed quasi-cliques. we also develop a coherent closed quasi-clique mining algorithm, <b>cocain</b>1 thorough performance study shows that cocain is very efficient and scalable for large dense graph databases.
clicks: an effective algorithm for mining subspace clusters in categorical datasets. we present a novel algorithm called clicks, that finds clusters in categorical datasets based on a search for k-partite maximal cliques. unlike previous methods, clicks mines subspace clusters. it uses a selective vertical method to guarantee complete search. clicks outperforms previous approaches by over an order of magnitude and scales better than any of the existing method for high-dimensional datasets. these results are demonstrated in a comprehensive performance study on real and synthetic datasets.
experimental comparison of scalable online ad serving. online ad servers attempt to find best ads to serve for a given triggering user event. the performance of ads may be measured in several ways. we suggest a formulation in which the ad network tries to maximize revenue subject to relevance constraints. we describe several algorithms for ad selection and review their complexity. we tested these algorithms using microsoft ad network from october 1 2006 to february 8 2007. over 3 billion impressions, 8 million combinations of triggers with ads, and a number of algorithms were tested over this period. we discover curious differences between ad-servers aimed at revenue versus clickthrough rate.
a cross-collection mixture model for comparative text mining. in this paper, we define and study a novel text mining problem, which we refer to as comparative text mining (ctm). given a set of comparable text collections, the task of comparative text mining is to discover any latent common themes across all collections as well as summarize the similarity and differences of these collections along each common theme. this general problem subsumes many interesting applications, including business intelligence and opinion summarization. we propose a generative probabilistic mixture model for comparative text mining. the model simultaneously performs cross-collection clustering and within-collection clustering, and can be applied to an arbitrary set of comparable text collections. the model can be estimated efficiently using the expectation-maximization (em) algorithm. we evaluate the model on two different text data sets (i.e., a news article data set and a laptop review data set), and compare it with a baseline clustering method also based on a mixture model. experiment results show that the model is quite effective in discovering the latent common themes across collections and performs significantly better than our baseline mixture model.
extracting redundancy-aware top-k patterns. observed in many applications, there is a potential need of extracting a small set of frequent patterns having not only high significance but also low redundancy. the significance is usually defined by the context of applications. previous studies have been concentrating on how to compute top-k significant patterns or how to remove redundancy among patterns separately. there is limited work on finding those top-k patterns which demonstrate high-significance and low-redundancy simultaneously.in this paper, we study the problem of extracting redundancy-aware top-k patterns from a large collection of frequent patterns. we first examine the evaluation functions for measuring the combined significance of a pattern set and propose the mms (maximal marginal significance) as the problem formulation. the problem is known as np-hard. we further present a greedy algorithm which approximates the optimal solution with performance bound o(log k) (with conditions on redundancy), where k is the number of reported patterns. the direct usage of redundancy-aware top-k patterns is illustrated through two real applications: disk block prefetch and document theme extraction. our method can also be applied to processing redundancy-aware top-k queries in traditional database.
attack detection in time series for recommender systems. recent research has identified significant vulnerabilities in recommender systems. shilling attacks, in which attackers introduce biased ratings in order to influence future recommendations, have been shown to be effective against collaborative filtering algorithms. we postulate that the distribution of item ratings in time can reveal the presence of a wide range of shilling attacks given reasonable assumptions about their duration. to construct a time series of ratings for an item, we use a window size of k to group consecutive ratings for the item into disjoint windows and compute the sample average and sample entropy in each window. we derive a theoretically optimal window size to best detect an attack event if the number of attack profiles is known. for practical applications where this number is unknown, we propose a heuristic algorithm that adaptively changes the window size. our experimental results demonstrate that monitoring rating distributions in time series is an effective approach for detecting shilling attacks.
discovering interesting patterns through user's interactive feedback. in this paper, we study the problem of discovering interesting patterns through user's interactive feedback. we assume a set of candidate patterns (ie, frequent patterns) has already been mined. our goal is to help a particular user effectively discover interesting patterns according to his specific interest. without requiring a user to explicitly construct a prior knowledge to measure the interestingness of patterns, we learn the user's prior knowledge from his interactive feedback. we propose two models to represent a user's prior: the log linear model and biased belief model. the former is designed for item-set patterns, whereas the latter is also applicable to sequential and structural patterns. to learn these models, we present a two-stage approach, progressive shrinking and clustering, to select sample patterns for feedback. the experimental results on real and synthetic data sets demonstrate the effectiveness of our approach.
identifying bridging rules between conceptual clusters. a bridging rule in this paper has its antecedent and action from different conceptual clusters. we first design two algorithms for mining bridging rules between clusters in a database, and then propose two non-linear metrics for measuring the interestingness of bridging rules. bridging rules can be distinct from association rules (or frequent itemsets). this is because (1) bridging rules can be generated by infrequent itemsets that are pruned in association rule mining; and (2) bridging rules are measured by the importance that includes the distance between two conceptual clusters, whereas frequent itemsets are measured by only the support.
exploiting a support-based upper bound of pearson's correlation coefficient for efficiently identifying strongly correlated pairs. given a user-specified minimum correlation threshold θ and a market basket database with n items and t transactions, an all-strong-pairs correlation query finds all item pairs with correlations above the threshold θ. however, when the number of items and transactions are large, the computation cost of this query can be very high. in this paper, we identify an upper bound of pearson's correlation coefficient for binary variables. this upper bound is not only much cheaper to compute than pearson's correlation coefficient but also exhibits a special monotone property which allows pruning of many item pairs even without computing their upper bounds. a two-step all-strong-pairs correlation que ry (taper) algorithm is proposed to exploit these properties in a filter-and-refine manner. furthermore, we provide an algebraic cost model which shows that the computation savings from pruning is independent or improves when the number of items is increased in data sets with common zipf or linear rank-support distributions. experimental results from synthetic and real data sets exhibit similar trends and show that the taper algorithm can be an order of magnitude faster than brute-force alternatives.
k-means clustering versus validation measures: a data distribution perspective. k-means is a well-known and widely used partitional clustering method. while there are considerable research efforts to characterize the key features of the k-means clustering algorithm, further investigation is needed to understand how data distributions can have impact on the performance of k-means clustering. to that end, in this paper, we provide a formal and organized study of the effect of skewed data distributions on k-means clustering. along this line, we first formally illustrate that k-means tends to produce clusters of relatively uniform size, even if input data have varied "true" cluster sizes. in addition, we show that some clustering validation measures, such as the entropy measure, may not capture this uniform effect and provide misleading information on the clustering performance. viewed in this light, we provide the coefficient of variation (cv) as a necessary criterion to validate the clustering results. our findings reveal that k-means tends to produce clusters in which the variations of cluster sizes, as measured by cv, are in a range of about 0.3-1.0. specifically, for data sets with large variation in "true" cluster sizes (e.g., cv > 1.0), k-means reduces variation in resultant cluster sizes to less than 1.0. in contrast, for data sets with small variation in "true" cluster sizes (e.g., cv < 0.3), k-means increases variation in resultant cluster sizes to greater than 0.3. in other words, for the earlier two cases, k-means produces the clustering results which are away from the "true" cluster distributions.
utility-based anonymization using local recoding. privacy becomes a more and more serious concern in applications involving microdata. recently, efficient anonymization has attracted much research work. most of the previous methods use global recoding, which maps the domains of the quasi-identifier attributes to generalized or changed values. however, global recoding may not always achieve effective anonymization in terms of discernability and query answering accuracy using the anonymized data. moreover, anonymized data is often for analysis. as well accepted in many analytical applications, different attributes in a data set may have different utility in the analysis. the utility of attributes has not been considered in the previous methods.in this paper, we study the problem of utility-based anonymization. first, we propose a simple framework to specify utility of attributes. the framework covers both numeric and categorical data. second, we develop two simple yet efficient heuristic local recoding methods for utility-based anonymization. our extensive performance study using both real data sets and synthetic data sets shows that our methods outperform the state-of-the-art multidimensional global recoding methods in both discernability and query answering accuracy. furthermore, our utility-based method can boost the quality of analysis using the anonymized data.
mining progressive confident rules. many real world objects have states that change over time. by tracking the state sequences of these objects, we can study their behavior and take preventive measures before they reach some undesirable states. in this paper, we propose a new kind of pattern called progressive confident rules to describe sequences of states with an increasing confidence that lead to a particular end state. we give a formal definition of progressive confident rules and their concise set. we devise pruning strategies to reduce the enormous search space. experiment result shows that the proposed algorithm is efficient and scalable. we also demonstrate the application of progressive confident rules in classification.
dynamic syslog mining for network failure monitoring. syslog monitoring technologies have recently received vast attentions in the areas of network management and network monitoring. they are used to address a wide range of important issues including network failure symptom detection and event correlation discovery. syslogs are intrinsically dynamic in the sense that they form a time series and that their behavior may change over time. this paper proposes a new methodology of dynamic syslog mining in order to detect failure symptoms with higher confidence and to discover sequential alarm patterns among computer devices. the key ideas of dynamic syslog mining are 1) to represent syslog behavior using a mixture of hidden markov models, 2) to adaptively learn the model using an on-line discounting learning algorithm in combination with dynamic selection of the optimal number of mixture components, and 3) to give anomaly scores using universal test statistics with a dynamically optimized threshold. using real syslog data we demonstrate the validity of our methodology in the scenarios of failure symptom detection, emerging pattern identification, and correlation discovery.
extracting key-substring-group features for text classification. in many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. previous research studies in this area mostly focused on different variants of generative markov chain models. although discriminative machine learning methods like support vector machine (svm) have been quite successful in text classification with word features, it is neither effective nor efficient to apply them straightforwardly taking all substrings in the corpus as features. in this paper, we propose to partition all substrings into statistical equivalence groups, and then pick those groups which are important (in the statistical sense) as features (named key-substring-group features) for text classification. in particular, we propose a suffix tree based algorithm that can extract such features in linear time (with respect to the total number of characters in the corpus). our experiments on english, chinese and greek datasets show that svm with key-substring-group features can achieve outstanding performance for various text classification tasks.
discovering outlier filtering rules from unlabeled data: combining a supervised learner with an unsupervised learner. this paper is concerned with the problem of detecting outliers from unlabeled data. in prior work we have developed smartsifter, which is an on-line outlier detection algorithm based on unsupervised learning from data. on the basis of smartsifter this paper yields a new framework for outlier filtering using both supervised and unsupervised learning techniques iteratively in order to make the detection process more effective and more understandable. the outline of the framework is as follows: in the first round, for an initial dataset, we run smartsifter to give each data a score, with a high score indicating a high possibility of being an outlier. next, giving positive labels to a number of higher scored data and negative labels to a number of lower scored data, we create labeled examples. then we construct an outlier filtering rule by supervised learning from them. here the rule is generated based on the principle of minimizing extended stochastic complexity. in the second round, for a new dataset, we filter the data using the constructed rule, then among the filtered data, we run smartsifter again to evaluate the data in order to update the filtering rule. applying of our framework to the network intrusion detection, we demonstrate that 1) it can significantly improve the accuracy of smartsifter, and 2) outlier filtering rules can help the user to discover a general pattern of an outlier group.
a unifying framework for detecting outliers and change points from non-stationary time series data. we are concerned with the issues of outlier detection and change point detection from a data stream. in the area of data mining, there have been increased interest in these issues since the former is related to fraud detection, rare event discovery, etc., while the latter is related to event/trend by change detection, activity monitoring, etc. specifically, it is important to consider the situation where the data source is non-stationary, since the nature of data source may change over time in real applications. although in most previous work outlier detection and change point detection have not been related explicitly, this paper presents a unifying framework for dealing with both of them on the basis of the theory of on-line learning of non-stationary time series. in this framework a probabilistic model of the data source is incrementally learned using an on-line discounting learning algorithm, which can track the changing data source adaptively by forgetting the effect of past data gradually. then the score for any given data is calculated to measure its deviation from the learned model, with a higher score indicating a high possibility of being an outlier. further change points in a data stream are detected by applying this scoring method into a time series of moving averaged losses for prediction using the learned model. specifically we develop an efficient algorithms for on-line discounting learning of auto-regression models from time series data, and demonstrate the validity of our framework through simulation and experimental applications to stock market data analysis.
on-line unsupervised outlier detection using finite mixtures with discounting learning algorithms. outlier detection is a fundamental issue in data mining, specifically in fraud detection, network intrusion detection, network monitoring, etc. smartsifter is an outlier detection engine addressing this problem from the viewpoint of statistical learning theory. this paper provides a theoretical basis for smartsifter and empirically demonstrates its effectiveness. smartsifter detects outliers in an on-line process through the on-line unsupervised learning of a probabilistic model (using a finite mixture model) of the information source. each time a datum is input smartsifter employs an on-line discounting learning algorithm to learn the probabilistic model. a score is given to the datum based on the learned model with a high score indicating a high possibility of being a statistical outlier. the novel features of smartsifter are: (1) it is adaptive to non-stationary sources of data&semi; (2) a score has a clear statistical/information-theoretic meaning&semi; (3) it is computationally inexpensive&semi; and (4) it can handle both categorical and continuous variables. an experimental application to network intrusion detection shows that smartsifter was able to identify data with high scores that corresponded to attacks, with low computational costs. further experimental application has identified a number of meaningful rare cases in actual health insurance pathology data from australia's health insurance commission.
fast mining of spatial collocations. spatial collocation patterns associate the co-existence of non-spatial features in a spatial neighborhood. an example of such a pattern can associate contaminated water reservoirs with certain deceases in their spatial neighborhood. previous work on discovering collocation patterns converts neighborhoods of feature instances to itemsets and applies mining techniques for transactional data to discover the patterns. we propose a method that combines the discovery of spatial neighborhoods with the mining process. our technique is an extension of a spatial join algorithm that operates on multiple inputs and counts long pattern instances. as demonstrated by experimentation, it yields significant performance improvements compared to previous approaches.
beyond classification and ranking: constrained optimization of the roi. classification has been commonly used in many data mining projects in the financial service industry. for instance, to predict collectability of accounts receivable, a binary class label is created based on whether a payment is received within a certain period. however, optimization of the classifier does not necessarily lead to maximization of return on investment (roi), since maximization of the true positive rate is often different from maximization of the collectable amount which determines the roi under a fixed budget constraint. the typical cost sensitive learning does not solve this problem either since it involves an unknown opportunity cost due to the budget constraint. learning the ranks of collectable amount would ultimately solve the problem, but it tries to tackle an unnecessarily difficult problem and often results in poorer results for our specific target. we propose a new algorithm that uses gradient descent to directly optimize the related monetary measure under the budget constraint and thus maximizes the roi. by comparison with several classification, regression, and ranking algorithms, we demonstrate the new algorithm's substantial improvement of the financial impact on our clients in the financial service industry.
linear prediction models with graph regularization for web-page categorization. we present a risk minimization formulation for learning from both text and graph structures which is motivated by the problem of collective inference for hypertext document categorization. the method is based on graph regularization formulated as a well-formed convex optimization problem. we present numerical algorithms for our formulation, and show that such combination of local text features and link information can lead to improved predictive accuracy.
summarizing itemset patterns: a profile-based approach. frequent-pattern mining has been studied extensively on scalable methods for mining various kinds of patterns including itemsets, sequences, and graphs. however, the bottleneck of frequent-pattern mining is not at the efficiency but at the interpretability, due to the huge number of patterns generated by the mining process.in this paper, we examine how to summarize a collection of itemset patterns using only k representatives, a small number of patterns that a user can handle easily. the k representatives should not only cover most of the frequent patterns but also approximate their supports. a generative model is built to extract and profile these representatives, under which the supports of the patterns can be easily recovered without consulting the original dataset. based on the restoration error, we propose a quality measure function to determine the optimal value of parameter k. polynomial time algorithms are developed together with several optimization heuristics for efficiency improvement. empirical studies indicate that we can obtain compact summarization in real datasets.
on the discovery of significant statistical quantitative rules. in this paper we study market share rules, rules that have a certain market share statistic associated with them. such rules are particularly relevant for decision making from a business perspective. motivated by market share rules, in this paper we consider statistical quantitative rules (sq rules) that are quantitative rules in which the rhs can be any statistic that is computed for the segment satisfying the lhs of the rule. building on prior work, we present a statistical approach for learning all significant sq rules, i.e., sq rules for which a desired statistic lies outside a confidence interval computed for this rule. in particular we show how resampling techniques can be effectively used to learn significant rules. since our method considers the significance of a large number of rules in parallel, it is susceptible to learning a certain number of "false" rules. to address this, we present a technique that can determine the number of significant sq rules that can be expected by chance alone, and suggest that this number can be used to determine a "false discovery rate" for the learning procedure. we apply our methods to online consumer purchase data and report the results.
enhancing the lift under budget constraints: an application in the mutual fund industry. a lift curve, with the true positive rate on the y-axis and the customer pull (or contact) rate on the x-axis, is often used to depict the model performance in many data mining applications, especially in the area of customer relationship management (crm). typically, these applications concern only the model accuracy at a relatively small pull or contact/intervention rate of the whole customer base, which is predetermined by a budget constraint for the project, e.g., how many customers can be contacted every month. in this paper, we address the important problem of enhancing the lift (true positive rate) at a specified pull rate. we propose two distinct algorithms, which are applicable to different scenarios. in particular, when the binary class label of the training set is extracted from a continuous variable, we can optimize a training objective which takes into account the specified pull rate rather than the class prior, based on the often ignored continuous variable. in those cases where only the binary class label is available during training, we propose a constrained optimization algorithm to maximize the true positive rate related to a specific decision threshold at which the specified pull rate is achieved. we applied both algorithms to our projects of predicting defection (decline in account value) of mutual fund accounts for two major u.s. mutual fund companies and achieved substantial enhancement of the lift at the specified pull rate.
closegraph: mining closed frequent graph patterns. recent research on pattern discovery has progressed form mining frequent itemsets and sequences to mining structured patterns including trees, lattices, and graphs. as a general data structure, graph can model complicated relations among data with wide applications in bioinformatics, web exploration, and etc. however, mining large graph patterns in challenging due to the presence of an exponential number of frequent subgraphs. instead of mining all the subgraphs, we propose to mine closed frequent graph patterns. a graph g is closed in a database if there exists no proper supergraph of g that has the same support as g. a closed graph pattern mining algorithm, closegraph, is developed by exploring several interesting pruning methods. our performance study shows that closegraph not only dramatically reduces unnecessary subgraphs to be generated but also substantially increases the efficiency of mining, especially in the presence of large graph patterns.
applying data mining in investigating money laundering crimes. in this paper, we study the problem of applying data mining to facilitate the investigation of money laundering crimes (mlcs). we have identified a new paradigm of problems --- that of automatic community generation based on uni-party data, the data in which there is no direct or explicit link information available. consequently, we have proposed a new methodology for link discovery based on correlation analysis (ldca). we have used mlc group model generation as an exemplary application of this problem paradigm, and have focused on this application to develop a specific method of automatic mlc group model generation based on timeline analysis using the ldca methodology, called coral. a prototype of coral method has been implemented, and preliminary testing and evaluations based on a real mlc case data are reported. the contributions of this work are: (1) identification of the uni-party data community generation problem paradigm, (2) proposal of a new methodology ldca to solve for problems in this paradigm, (3) formulation of the mlc group model generation problem as an example of this paradigm, (4) application of the ldca methodology in developing a specific solution (coral) to the mlc group model generation problem, and (5) development, evaluation, and testing of the coral prototype in a real mlc case data.
predicting prostate cancer recurrence via maximizing the concordance index. in order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. the concordance index (ci) is a typical metric for quantifying the predictive ability of a survival model. we propose a new algorithm that directly uses the ci as the objective function to train a model, which predicts whether an event will eventually occur or not. directly optimizing the ci allows the model to make complete use of the information from both censored and non-censored observations. in particular, we approximate the ci via a differentiable function so that gradient-based methods can be used to train the model. we applied the new algorithm to predict the eventual recurrence of prostate cancer following radical prostatectomy. compared with the traditional cox proportional hazards model and several other algorithms based on neural networks and support vector machines, our algorithm achieves a significant improvement in being able to identify high-risk and low-risk groups of patients.
a new scheme on privacy-preserving data classification. we address privacy-preserving classification problem in a distributed system. randomization has been the approach proposed to preserve privacy in such scenario. however, this approach is now proven to be insecure as it has been discovered that some privacy intrusion techniques can be used to reconstruct private information from the randomized data tuples. we introduce an algebraic-technique-based scheme. compared to the randomization approach, our new scheme can build classifiers more accurately but disclose less private information. furthermore, our new scheme can be readily integrated as a middleware with existing systems.
immc: incremental maximum margin criterion. subspace learning approaches have attracted much attention in academia recently. however, the classical batch algorithms no longer satisfy the applications on streaming data or large-scale data. to meet this desirability, incremental principal component analysis (ipca) algorithm has been well established, but it is an unsupervised subspace learning approach and is not optimal for general classification tasks, such as face recognition and web document categorization. in this paper, we propose an incremental supervised subspace learning algorithm, called incremental maximum margin criterion (immc), to infer an adaptive subspace by optimizing the maximum margin criterion. we also present the proof for convergence of the proposed algorithm. experimental results on both synthetic dataset and real world datasets show that immc converges to the similar subspace as that of batch approach.
a data mining approach to modeling relationships among categories in image collection. this paper proposes a data mining approach to modeling relationships among categories in image collection. in our approach, with image feature grouping, a visual dictionary is created for color, texture, and shape feature attributes respectively. labeling each training image with the keywords in the visual dictionary, a classification tree is built. based on the statistical properties of the feature space we define a structure, called α-semantics graph, to discover the hidden semantic relationships among the semantic categories embodied in the image collection. with the α-semantics graph, each semantic category is modeled as a unique fuzzy set to explicitly address the semantic uncertainty and semantic overlap among the categories in the feature space. the model is utilized in the semantics-intensive image retrieval application. an algorithm using the classification accuracy measures is developed to combine the built classification tree with the fuzzy set modeling method to deliver semantically relevant image retrieval for a given query image. the experimental evaluations have demonstrated that the proposed approach models the semantic relationships effectively and the image retrieval prototype system utilizing the derived model is promising both in effectiveness and efficiency.
the complexity of mining maximal frequent itemsets and maximal frequent patterns. mining maximal frequent itemsets is one of the most fundamental problems in data mining. in this paper we study the complexity-theoretic aspects of maximal frequent itemset mining, from the perspective of counting the number of solutions. we present the first formal proof that the problem of counting the number of distinct maximal frequent itemsets in a database of transactions, given an arbitrary support threshold, is #p-complete, thereby providing strong theoretical evidence that the problem of mining maximal frequent itemsets is np-hard. this result is of particular interest since the associated decision problem of checking the existence of a maximal frequent itemset is in p.we also extend our complexity analysis to other similar data mining problems dealing with complex data structures, such as sequences, trees, and graphs, which have attracted intensive research interests in recent years. normally, in these problems a partial order among frequent patterns can be defined in such a way as to preserve the downward closure property, with maximal frequent patterns being those without any successor with respect to this partial order. we investigate several variants of these mining problems in which the patterns of interest are subsequences, subtrees, or subgraphs, and show that the associated problems of counting the number of maximal frequent patterns are all either #p-complete or #p-hard.
building connected neighborhood graphs for isometric data embedding. neighborhood graph construction is usually the first step in algorithms for isometric data embedding and manifold learning that cope with the problem of projecting high dimensional data to a low space. this paper begins by explaining the algorithmic fundamentals of techniques for isometric data embedding and derives a general classification of these techniques. we will see that the nearest neighbor approaches commonly used to construct neighborhood graphs do not guarantee connectedness of the constructed neighborhood graphs and, consequently, may cause an algorithm fail to project data to a single low dimensional coordinate system. in this paper, we review three existing methods to construct k-edge-connected neighborhood graphs and propose a new method to construct k-connected neighborhood graphs. these methods are applicable to a wide range of data including data distributed among clusters. their features are discussed and compared through experiments.
event detection from evolution of click-through data. previous efforts on event detection from the web have focused primarily on web content and structure data ignoring the rich collection of web log data. in this paper, we propose the first approach to detect events from the click-through data, which is the log data of web search engines. the intuition behind event detection from click-through data is that such data is often event-driven and each event can be represented as a set ofquery-page pairs that are not only semantically similar but also have similar evolution pattern over time. given the click-through data, in our proposed approach, we first segment it into a sequence of bipartite graphs based on theuser-defined time granularity. next, the sequence of bipartite graphs is represented as a vector-based graph, which records the semantic and evolutionary relationships between queries and pages. after that, the vector-based graph is transformed into its dual graph, where each node is a query-page pair that will be used to represent real world events. then, the problem of event detection is equivalent to the problem of clustering the dual graph of the vector-based graph. the clustering process is based on a two-phase graph cut algorithm. in the first phase, query-page pairs are clustered based on thesemantic-based similarity such that each cluster in the result corresponds to a specific topic. in the second phase, query-page pairs related to the same topic are further clustered based on the evolution pattern-based similarity such that each cluster is expected to represent a specific event under the specific topic. experiments with real click-through data collected from a commercial web search engine show that the proposed approach produces high quality results.
efficient discovery of error-tolerant frequent itemsets in high dimensions. we present a generalization of frequent itemsets allowing for the notion of errors in the itemset definition. we motivate the problem and present an efficient algorithm that identifies error-tolerant frequent clusters of items in transactional data (customer-purchase data, web browsing data, text, etc.). the algorithm exploits sparseness of the underlying data to find large groups of items that are correlated over database records (rows). the notion of transaction coverage allows us to extend the algorithm and view it as a fast clustering algorithm for discovering segments of similar transactions in binary sparse data. we evaluate the new algorithm on three real-world applications: clustering high-dimensional data, query selectivity estimation and collaborative filtering. results show that the algorithm consistently uncovers structure in large sparse databases that other traditional clustering algorithms fail to find.
opportunity map: identifying causes of failure - a deployed data mining system. in this paper, we report a deployed data mining application system for motorola. originally, its intended use was for identifying causes of cellular phone failures, but it has been found to be useful for many other engineering data sets as well. for this report, the case study is a dataset containing cellular phone call records. this data set is like any dataset used in classification applications, i.e., with a set of attributes which can be continuous or discrete, and a discrete class attribute. in our application, the classes are normally ended calls, calls which failed to setup, and calls which failed while in progress. however, the task is not to predict any failure, but to identify possible causes that resulted in failures. then, engineering efforts may focus on improvements that can be made to the phones. in the course of the project, various classification techniques, e.g., decision trees, naïve bayesian classification and svm were tried. however, the results were unsatisfactory. after several demonstrations and interaction with domain experts, we finally designed and implemented an effective approach to perform the task. the final system is based on class association rules, general impressions and visualization. the system has been deployed and is in regular use at motorola. in this paper, we first describe our experiences with some existing classification systems and discuss why they are not suitable for the task. we then present our techniques. as an illustration, we show several visualization screens in the case study, which reveal some important knowledge. due to confidentiality, we will not give specifics but only present a general discussion about the results.
clope: a fast and effective clustering algorithm for transactional data. this paper studies the problem of categorical data clustering, especially for transactional data characterized by high dimensionality and large volume. starting from a heuristic method of increasing the height-to-width ratio of the cluster histogram, we develop a novel algorithm -- clope, which is very fast and scalable, while being quite effective. we demonstrate the performance of our algorithm on two real world datasets, and compare clope with the state-of-art algorithms.
v-miner: using enhanced parallel coordinates to mine product design and test data. analyzing data to find trends, correlations, and stable patterns is an important task in many industrial applications. this paper proposes a new technique based on parallel coordinate visualization. previous work on parallel coordinate methods has shown that they are effective only when variables that are correlated and/or show similar patterns are displayed adjacently. although current parallel coordinate tools allow the user to manually rearrange the order of variables, this process is very time-consuming when the number of variables is large. automated assistance is required. this paper introduces an edit-distance based technique to rearrange variables so that interesting change patterns can be easily detected visually. the visual miner (v-miner) software includes both automated methods for visualizing common patterns and a query tool that enables the user to describe specific target patterns to be mined or displayed by the system. in addition, the system can filter data according to rules sets imported from other data mining tools. this feature was found very helpful in practice, because it enables decision makers to visually identify interesting rules and data segments for further analysis or data mining. this paper begins with an introduction to the proposed techniques and the v-miner system. next, a case study illustrates how v-miner has been used at motorola to guide product design and test decisions.
learning to predict train wheel failures. this paper describes a successful but challenging application of data mining in the railway industry. the objective is to optimize maintenance and operation of trains through prognostics of wheel failures. in addition to reducing maintenance costs, the proposed technology will help improve railway safety and augment throughput. building on established techniques from data mining and machine learning, we present a methodology to learn models to predict train wheel failures from readily available operational and maintenance data. this methodology addresses various data mining tasks such as automatic labeling, feature extraction, model building, model fusion, and evaluation. after a detailed description of the methodology, we report results from large-scale experiments. these results clearly show the great potential of this innovative application of data mining in the railway industry.
blosom: a framework for mining arbitrary boolean expressions. we introduce a novel framework, called blosom, for mining (frequent) boolean expressions over binary-valued datasets. we organize the space of boolean expressions into four categories: pure conjunctions, pure disjunctions, conjunction of disjunctions, and disjunction of conjunctions. we focus on mining the simplest expressions the minimal generators for each class. we also propose a closure operator for each class that yields closed boolean expressions. blosom efficiently mines frequent boolean expressions by utilizing a number of methodical pruning techniques. experiments showcase the behavior of blosom, and an application study on a real dataset is also given.
2pxminer: an efficient two pass mining of frequent xml query patterns. caching the results of frequent query patterns can improve the performance of query evaluation. this paper describes a 2-pass mining algorithm called 2pxminer to discover frequent xml query patterns. we design 3 data structures to expedite the mining process. experiments results indicate that 2pxminer is both efficient and scalable.
real world performance of association rule algorithms. this study compares five well-known association rule algorithms using three real-world datasets and an artificial dataset. the experimental results confirm the performance improvements previously claimed by the authors on the artificial data, but some of these gains do not carry over to the real datasets, indicating overfitting of the algorithms to the ibm artificial dataset. more importantly, we found that the choice of algorithm only matters at support levels that generate more rules than would be useful in practice. for support levels that generate less than 1,000,000 rules, which is much more than humans can handle and is sufficient for prediction purposes where data is loaded into ram, apriori finishes processing in less than 10 minutes. on our datasets, we observed super-exponential growth in the number of rules. on one of our datasets, a 0.02% change in the support increased the number of rules from less than a million to over a billion, implying that outside a very narrow range of support values, the choice of algorithm is irrelevant.
a dea approach for model combination. this paper proposes a novel data envelopment analysis (dea) based approach for model combination. we first prove that for the 2-class classification problems dea models identify the same convex hull as the popular roc analysis used for model combination. for general k-class classifiers, we then develop a dea-based method to combine multiple classifiers. experiments show that the method outperforms other benchmark methods and suggest that dea can be a promising tool for model combination.
a generalized framework for mining spatio-temporal patterns in scientific data. in this paper, we present a general framework to discover spatial associations and spatio-temporal episodes for scientific datasets. in contrast to previous work in this area, features are modeled as geometric objects rather than points. we define multiple distance metrics that take into account objects' extent and thus are more robust in capturing the influence of an object on other objects in spatial neighborhood. we have developed algorithms to discover four different types of spatial object interaction (association) patterns. we also extend our approach to accommodate temporal information and propose a simple algorithm to derive spatio-temporal episodes. we show that such episodes can be used to reason about critical events. we evaluate our framework on real datasets to demonstrate its efficacy. the datasets originate from two different areas: computational molecular dynamics and computational fluid flow. we present results highlighting the importance of the identified patterns and episodes by using knowledge from the underlying domains. we also show that the proposed algorithms scale linearly with respect to the dataset size.
mining asynchronous periodic patterns in time series data. periodicy detection in time series data is a challenging problem of great importance in many applications. most previous work focused on mining synchronous periodic patterns and did not recognize the misaligned presence of a pattern due to the intervention of random noise. in this paper, we propose a more flexible model of asynchronous periodic pattern that may be present only within a subsequence and whose occurrences may be shifted due to disturbance. two parameters min_rep and max_dis are employed to specify the minimum number of repetitions that is required within each segment of nondisrupted pattern occurrences and the maximum allowed disturbance between any two successive valid segments. upon satisfying these two requirements, the longest valid subsequence of a pattern is returned. a two-phase algorithm is devised to first generate potential periods by distance-based pruning followed by an iterative procedure to derive and validate candidate patterns and locate the longest valid subsequence. we also show that this algorithm cannot only provide linear time complexity with respect to the length of the sequence but also achieve space efficiency.
infominer: mining surprising periodic patterns. in this paper, we focus on mining surprising periodic patterns in a sequence of events. in many applications, e.g., computational biology, an infrequent pattern is still considered very significant if its actual occurrence frequency exceeds the prior expectation by a large margin. the traditional metric, such as support, is not necessarily the ideal model to measure this kind of surprising patterns because it treats all patterns equally in the sense that every occurrence carries the same weight towards the assessment of the significance of a pattern regardless of the probability of occurrence. a more suitable measurement, information, is introduced to naturally value the degree of surprise of each occurrence of a pattern as a continuous and monotonically decreasing function of its probability of occurrence. this would allow patterns with vastly different occurrence probabilities to be handled seamlessly. as the accumulated degree of surprise of all repetitions of a pattern, the concept of information gain is proposed to measure the overall degree of surprise of the pattern within a data sequence. the bounded information gain property is identified to tackle the predicament caused by the violation of the downward closure property by the information gain measure and in turn provides an efficient solution to this problem. empirical tests demonstrate the efficiency and the usefulness of the proposed model.
streaming feature selection using alpha-investing. in streaming feature selection (sfs), new features are sequentially considered for addition to a predictive model. when the space of potential features is large, sfs offers many advantages over traditional feature selection methods, which assume that all features are known in advance. features can be generated dynamically, focusing the search for new features on promising subspaces, and overfitting can be controlled by dynamically adjusting the threshold for adding features to the model. we describe α-investing, an adaptive complexity penalty method for sfs which dynamically adjusts the threshold on the error reduction required for adding a new feature. α-investing gives false discovery rate-style guarantees against overfitting. it differs from standard penalty methods such as aic, bic or ric, which always drastically over- or under-fit in the limit of infinite numbers of non-predictive features. empirical results show that sfs is competitive with much more compute-intensive feature selection methods such as stepwise regression, and allows feature selection on problems with over a million potential features.
combining proactive and reactive predictions for data streams. mining data streams is important in both science and commerce. two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (2) the underlying concept of the data may change over time. different from common practice that keeps recent raw data, this paper uses a measure of conceptual equivalence to organize the data history into a history of concepts. along the journey of concept change, it identifies new concepts as well as re-appearing ones, and learns transition patterns among concepts to help prediction. different from conventional methodology that passively waits until the concept changes, this paper incorporates proactive and reactive predictions. in a proactive mode, it anticipates what the new concept will be if a future concept change takes place, and prepares prediction strategies in advance. if the anticipation turns out to be correct, a proper prediction model can be launched instantly upon the concept change. if not, it promptly resorts to a reactive mode: adapting a prediction model to the new data. a system repro is proposed to implement these new ideas. experiments compare the system with representative existing prediction methods on various benchmark data sets that represent diversified scenarios of concept change. empirical evidence demonstrates that the proposed methodology is an effective and efficient solution to prediction for data streams.
topic-conditioned novelty detection. automated detection of the first document reporting each new event in temporally-sequenced streams of documents is an open challenge. in this paper we propose a new approach which addresses this problem in two stages: 1) using a supervised learning algorithm to classify the on-line document stream into pre-defined broad topic categories, and 2) performing topic-conditioned novelty detection for documents in each topic. we also focus on exploiting named-entities for event-level novelty detection and using feature-based heuristics derived from the topic histories. evaluating these methods using a set of broadcast news stories, our results show substantial performance gains over the traditional one-level approach to the novelty detection problem.
simultaneous record detection and attribute labeling in web data extraction. recent work has shown the feasibility and promise of template-independent web data extraction. however, existing approaches use decoupled strategies - attempting to do data record detection and attribute labeling in two separate phases. in this paper, we show that separately extracting data records and attributes is highly ineffective and propose a probabilistic model to perform these two tasks simultaneously. in our approach, record detection can benefit from the availability of semantics required in attribute labeling and, at the same time, the accuracy of attribute labeling can be improved when data records are labeled in a collective manner. the proposed model is called hierarchical conditional random fields. it can efficiently integrate all useful features by learning their importance, and it can also incorporate hierarchical interactions which are very important for web data extraction. we empirically compare the proposed model with existing decoupled approaches for product information extraction, and the results show significant improvements in both record detection and attribute labeling.
mining web logs for prediction models in www caching and prefetching. web caching and prefetching are well known strategies for improving the performance of internet systems. when combined with web log mining, these strategies can decide to cache and prefetch web documents with higher accuracy. in this paper, we present an application of web log mining to obtain web-document access patterns and use these patterns to extend the well-known gdsf caching policies and prefetching policies. using real web logs, we show that this application of data mining can achieve dramatic improvement to web-access performance.
efficient elastic burst detection in data streams. burst detection is the activity of finding abnormal aggregates in data streams. such aggregates are based on sliding windows over data streams. in some applications, we want to monitor many sliding window sizes simultaneously and to report those windows with aggregates significantly different from other periods. we will present a general data structure for detecting interesting aggregates over such elastic windows in near linear time. we present applications of the algorithm for detecting gamma ray bursts in large-scale astrophysical data. detection of periods with high volumes of trading activities and high stock price volatility is also demonstrated using real time trade and quote (taq) data from the new york stock exchange (nyse). our algorithm beats the direct computation approach by several orders of magnitude.
anonymity-preserving data collection. protection of privacy has become an important problem in data mining. in particular, individuals have become increasingly unwilling to share their data, frequently resulting in individuals either refusing to share their data or providing incorrect data. in turn, such problems in data collection can affect the success of data mining, which relies on sufficient amounts of accurate data in order to produce meaningful results. random perturbation and randomized response techniques can provide some level of privacy in data collection, but they have an associated cost in accuracy. cryptographic privacy-preserving data mining methods provide good privacy and accuracy properties. however, in order to be efficient, those solutions must be tailored to specific mining tasks, thereby losing generality.in this paper, we propose efficient cryptographic techniques for online data collection in which data from a large number of respondents is collected anonymously, without the help of a trusted third party. that is, our solution allows the miner to collect the original data from each respondent, but in such a way that the miner cannot link a respondent's data to the respondent. an advantage of such a solution is that, because it does not change the actual data, its success does not depend on the underlying data mining problem. we provide proofs of the correctness and privacy of our solution, as well as experimental data that demonstrates its efficiency. we also extend our solution to tolerate certain kinds of malicious behavior of the participants.
gpca: an efficient dimension reduction scheme for image compression and retrieval. recent years have witnessed a dramatic increase in the quantity of image data collected, due to advances in fields such as medical imaging, reconnaissance, surveillance, astronomy, multimedia etc. with this increase has come the need to be able to store, transmit, and query large volumes of image data efficiently. a common operation on image databases is the retrieval of all images that are similar to a query image. for this, the images in the database are often represented as vectors in a high-dimensional space and a query is answered by retrieving all image vectors that are proximal to the query image in this space, under a suitable similarity metric. to overcome problems associated with high dimensionality, such as high storage and retrieval times, a dimension reduction step is usually applied to the vectors to concentrate relevant information in a small number of dimensions. principal component analysis (pca) is a well-known dimension reduction scheme. however, since it works with vectorized representations of images, pca does not take into account the spatial locality of pixels in images. in this paper, a new dimension reduction scheme, called generalized principal component analysis (gpca), is presented. this scheme works directly with images in their native state, as two-dimensional matrices, by projecting the images to a vector space that is the tensor product of two lower-dimensional vector spaces. experiments on databases of face images show that, for the same amount of storage, gpca is superior to pca in terms of quality of the compressed images, query precision, and computational cost.
idr/qr: an incremental dimension reduction algorithm via qr decomposition. dimension reduction is a critical data preprocessing step for many database and data mining applications, such as efficient storage and retrieval of high-dimensional data. in the literature, a well-known dimension reduction algorithm is linear discriminant analysis (lda). the common aspect of previously proposed lda-based algorithms is the use of singular value decomposition (svd). due to the difficulty of designing an incremental solution for the eigenvalue problem on the product of scatter matrices in lda, there has been little work on designing incremental lda algorithms that can efficiently incorporate new data items as they become available. in this paper, we propose an lda-based incremental dimension reduction algorithm, called idr/qr, which applies qr decomposition rather than svd. unlike other lda-based algorithms, this algorithm does not require the whole data matrix in main memory. this is desirable for large data sets. more importantly, with the insertion of new data items, the idr/qr algorithm can constrain the computational cost by applying efficient qr-updating techniques. finally, we evaluate the effectiveness of the idr/qr algorithm in terms of classification error rate on the reduced dimensional space. our experiments on several real-world data sets reveal that the classification error rate achieved by the idr/qr algorithm is very close to the best possible one achieved by other lda-based algorithms. however, the idr/qr algorithm has much less computational cost, especially when new data items are inserted dynamically.
analytical view of business data. this paper describes a logical extension to microsoft business framework (mbf) called analytical view (av). av consists of three components: model service for design time, business intelligence entity (bie) for programming model, and intelldrill for runtime navigation between oltp and olap data sources. av feature-set fulfills enterprise application requirements for analysis and decision support, complementing the transactional feature-set currently provided by mbf. model service automatically transforms an "object oriented model (transactional view)" to a "multi-dimensional model (analytical view)" without the traditional extraction/transformation/loading (etl) overhead and complexity. it infers dimensionality from the object layer where richer metadata is stored, eliminating the "guesswork" that a traditional data warehousing process requires when going through physical database schema. bi entities are classes code-generated by model service. as an intrinsic part of the framework, bi entities enable a consistent object oriented way of programming model with strong types and rich semantics for olap, similar to what mbf object persistence technology does for oltp data. more importantly, data contained in bi entities have a higher degree of "application awareness," such as the integrated application level security and customizability. intellidrill links together all the information islands in mbf using metadata. because of the automatic transformation from transactional view to analytical view enabled by model service, we have the ability to understand natively what kind of drill-ability an object would have, thus making information navigation in mbf fully discover-able with built-in ontology.
eliminating noisy information in web pages for data mining. a commercial web page typically contains many information blocks. apart from the main content blocks, it usually has such blocks as navigation panels, copyright and privacy notices, and advertisements (for business purposes and for easy user access). we call these blocks that are not the main content blocks of the page the noisy blocks. we show that the information contained in these noisy blocks can seriously harm web data mining. eliminating these noises is thus of great importance. in this paper, we propose a noise elimination technique based on the following observation: in a given web site, noisy blocks usually share some common contents and presentation styles, while the main content blocks of the pages are often diverse in their actual contents and/or presentation styles. based on this observation, we propose a tree structure, called style tree, to capture the common presentation styles and the actual contents of the pages in a given web site. by sampling the pages of the site, a style tree can be built for the site, which we call the site style tree (sst). we then introduce an information based measure to determine which parts of the sst represent noises and which parts represent the main contents of the site. the sst is employed to detect and eliminate noises in any web page of the site by mapping this page to the sst. the proposed technique is evaluated with two data mining tasks, web page clustering and classification. experimental results show that our noise elimination technique is able to improve the mining results significantly.
show me the money!: deriving the pricing power of product features by mining consumer reviews. the increasing pervasiveness of the internet has dramatically changed the way that consumers shop for goods. consumer-generated product reviews have become a valuable source of information for customers, who read the reviews and decide whether to buy the product based on the information provided. in this paper, we use techniques that decompose the reviews into segments that evaluate the individual characteristics of a product (e.g., image quality and battery life for a digital camera). then, as a major contribution of this paper, we adapt methods from the econometrics literature, specifically the hedonic regression concept, to estimate: (a) the weight that customers place on each individual product feature, (b) the implicit evaluation score that customers assign to each feature, and (c) how these evaluations affect the revenue for a given product. towards this goal, we develop a novel hybrid technique combining text mining and econometrics that models consumer product reviews as elements in a tensor product of feature and evaluation spaces. we then impute the quantitative impact of consumer reviews on product demand as a linear functional from this tensor product space. we demonstrate how to use a low-dimension approximation of this functional to significantly reduce the number of model parameters, while still providing good experimental results. we evaluate our technique using a data set from amazon.com consisting of sales data and the related consumer reviews posted over a 15-month period for 242 products. our experimental evaluation shows that we can extract actionable business intelligence from the data and better understand the customer preferences and actions. we also show that the textual portion of the reviews can improve product sales prediction compared to a baseline technique that simply relies on numeric data.
cross-relational clustering with user's guidance. clustering is an essential data mining task with numerous applications. however, data in most real-life applications are high-dimensional in nature, and the related information often spreads across multiple relations. to ensure effective and efficient high-dimensional, cross-relational clustering, we propose a new approach, called crossclus, which performs cross-relational clustering with user's guidance. we believe that user's guidance, even likely in very simple forms, could be essential for effective high-dimensional clustering since a user knows well the application requirements and data semantics. crossclus is carried out as follows: a user specifies a clustering task and selects one or a small set of features pertinent to the task. crossclus extracts the set of highly relevant features in multiple relations connected via linkages defined in the database schema, evaluates their effectiveness based on user's guidance, and identifies interesting clusters that fit user's needs. this method takes care of both quality in feature extraction and efficiency in clustering. our comprehensive experiments demonstrate the effectiveness and scalability of this approach.
integration of semantic-based bipartite graph representation and mutual refinement strategy for biomedical literature clustering. we introduce a novel document clustering approach that overcomes those problems by combining a semantic-based bipartite graph representation and a mutual refinement strategy. the primary contributions of this paper are the following. first, we introduce a new representation of documents using a bipartite graph between documents and co-occurrence concepts in the documents. second, we show how to enhance clustering quality by applying the mutual refinement strategy to the initial clustering results. third, through the experiments on medline documents, we show that our integrated method significantly enhances cluster quality and clustering reliability compared to existing clustering methods. our approach improves on the average 29.5 cluster quality and 26.3 clustering reliability, in terms of misclassification index, over bisecting k-means with the best parameters.
new algorithms for fast discovery of association rules. association rule discovery has emerged as an important problem in knowledge discovery and data mining. the association mining task consists of identifying the frequent itemsets, and then forming conditional implication rules among them. in this paper we present efficient algorithms for the discovery of frequent itemsets, which forms the compute intensive phase of the task. the algorithms utilize the structural properties of frequent itemsets to facilitate fast discovery. the related database items are grouped together into clusters representing the potential maximal frequent itemsets in the database. each cluster induces a sub-lattice of the itemset lattice. efficient lattice traversal techniques are presented, which quickly identify all the true maximal frequent itemsets, and all their subsets if desired. we also present the effect of using different database layout schemes combined with the proposed clustering and traversal techniques. the proposed algorithms scan a (pre-processed) database only once, addressing the open question in association mining, whether all the rules can be efficiently extracted in a single database pass. we experimentally compare the new algorithms against the previous approaches, obtaining improvements of more than an order of magnitude for our test databases.
automated cyclone discovery and tracking using knowledge sharing in multiple heterogeneous satellite data. current techniques for cyclone detection and tracking employ ncep (national centers for environmental prediction) models from in-situ measurements. this solution does not provide true global coverage, unlike remote satellite observations. however it is impractical to use a single earth orbiting satellite to detect and track events such as cyclones in a continuous manner due to limited spatial and temporal coverage. one solution to alleviate such persistent problems is to utilize heterogeneous sensor data from multiple orbiting satellites. however, this solution requires overcoming other new challenges such as varying spatial and temporal resolution between satellite sensor data, the need to establish correspondence between features from different satellite sensors, and the lack of definitive indicators for cyclone events in some sensor data. we describe an automated cyclone discovery and tracking approach using heterogeneous near real-time sensor data from multiple satellites. this approach addresses the unique challenges associated with knowledge discovery and mining from heterogeneous satellite data streams. we consider two remote sensor measurements in our current implementation, namely: quikscat wind satellite measurements, and merged precipitation data from trmm and other satellites. more satellites will be incorporated in the near future and our solution is sufficiently powerful that it generalizes to multiple sensor measurement modalities. our approach consists of three main components: (i) feature extraction from each sensor measurement, (ii) an ensemble classifier for cyclone discovery, and (iii) knowledge sharing between the different remote sensor measurements based on a linear kalman filter for predictive cyclone tracking. experimental results on historical hurricane datasets demonstrate the superior performance of our approach compared to previous work.
density-based spam detector. the volume of mass unsolicited electronic mail, often known as spam, has recently increased enormously and has become a serious threat to not only the internet but also to society. this paper proposes a new spam detection method which uses document space density information. although it requires extensive e-mail traffic to acquire the necessary information, an unsupervised learning engine with a short white list can achieve a 98% recall rate and 100% precision. a direct-mapped cache method contributes handling of over 13,000 e-mails per second. experimental results, which were conducted using over 50 million actual e-mails of traffic, are also reported in this paper.
on-board analysis of uncalibrated data for a spacecraft at mars. analyzing data on-board a spacecraft as it is collected enables several advanced spacecraft capabilities, such as prioritizing observations to make the best use of limited bandwidth and reacting to dynamic events as they happen. in this paper, we describe how we addressed the unique challenges associated with on-board mining of data as it is collected: uncalibrated data, noisy observations, and severe limitations on computational and memory resources. the goal of this effort, which falls into the emerging application area of spacecraft-based data mining, was to study three specific science phenomena on mars. following previous work that used a linear support vector machine (svm) on-board the earth observing 1 (eo-1)spacecraft, we developed three data mining techniques for use on-board the mars odyssey spacecraft. these methods range from simple thresholding to state-of-the-art reduced-set svm technology. we tested these algorithms on archived data in a flight software testbed. we also describe a significant, serendipitous science discovery of this data mining effort: the confirmation of a water ice annulus around the north polar cap of mars. we conclude with a discussion on lessons learned in developing algorithms for use on-board a spacecraft.
svm selective sampling for ranking with application to data retrieval. learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. svms (support vector machines) - a classification and regression methodology - have also shown excellent performance in learning ranking functions. they effectively learn ranking functions of high generalization based on the "large-margin" principle and also systematically support nonlinear ranking by the "kernel trick". in this paper, we propose an svm selective sampling technique for learning ranking functions. svm selective sampling (or active learning with svm) has been studied in the context of classification. such techniques reduce the labeling effort in learning classification functions by selecting only the most informative samples to be labeled. however, they are not extendable to learning ranking functions, as the labeled data in ranking is relative ordering, or partial orders of data. our proposed sampling technique effectively learns an accurate svm ranking function with fewer partial orders. we apply our sampling technique to the data retrieval application, which enables fuzzy search on relational databases by interacting with users for learning their preferences. experimental results show a significant reduction of the labeling effort in inducing accurate ranking functions.
lungcad: a clinically approved, machine learning system for lung cancer detection. we present lungcad, a computer aided diagnosis (cad) system that employs a classification algorithm for detecting solid pulmonary nodules from ct thorax studies. we briefly describe some of the machine learning techniques developed to overcome the real world challenges in this medical domain. the most significant hurdle in transitioning from a machine learning research prototype that performs well on an in-house dataset into a clinically deployable system, is the requirement that the cad system be tested in a clinical trial. we describe the clinical trial in which lungcad was tested: a large scale multi-reader, multi-case (mrmc) retrospective observational study to evaluate the effect of cad in clinical practice for detecting solid pulmonary nodules from ct thorax studies. the clinical trial demonstrates that every radiologist that participated in the trial had a significantly greater accuracy with lungcad, both for detecting nodules and identifying potentially actionable nodules; this, along with other findings from the trial, has resulted in fda approval for lungcad in late 2006.
distributed multivariate regression based on influential observations. large-scale data sets are sometimes logically and physically distributed in separate databases. the issues of mining these data sets are not just their sizes, but also the distributed nature. the complication is that communicating all the data to a central database would be too slow. to reduce communication costs, one could compress the data during transmission. another method is random sampling. we propose an approach for distributed multivariate regression based on sampling and discuss its relationship with the compression method. the central idea is motivated by the observation that, although communication is limited, each individual site can still scan and process all the data it holds. thus it is possible for the site to communicate only influential samples without seeing data in other sites. we exploit this observation and derive a method that provides tradeoff between communication cost and accuracy. experimental results show that it is better than the compression method and random sampling.
pebl: positive example based learning for web page classification using svm. web page classification is one of the essential techniques for web mining. specifically, classifying web pages of a user-interesting class is the first step of mining interesting information from the web. however, constructing a classifier for an interesting class requires laborious pre-processing such as collecting positive and negative training examples. for instance, in order to construct a "homepage" classifier, one needs to collect a sample of homepages (positive examples) and a sample of non-homepages (negative examples). in particular, collecting negative training examples requires arduous work and special caution to avoid biasing them. we introduce in this paper the positive example based learning (pebl) framework for web page classification which eliminates the need for manually collecting negative training examples in pre-processing. we present an algorithm called mapping-convergence (m-c) that achieves classification accuracy (with positive and unlabeled data) as high as that of traditional svm (with positive and negative data). our experiments show that when the m-c algorithm uses the same amount of positive examples as that of traditional svm, the m-c algorithm performs as well as traditional svm.
automatic labeling of multinomial topic models. multinomial distributions over words are frequently used to model topics in text collections. a common, major challenge in applying all such topic models to any text mining problem is to label a multinomial topic model accurately so that a user can interpret the discovered topic. so far, such labels have been generated manually in a subjective way. in this paper, we propose probabilistic approaches to automatically labeling multinomial topic models in an objective way. we cast this labeling problem as an optimization problem involving minimizing kullback-leibler divergence between word distributions and maximizing mutual information between a label and a topic model. experiments with user study have been done on two text data sets with different genres.the results show that the proposed labeling methods are quite effective to generate labels that are meaningful and useful for interpreting the discovered topic models. our methods are general and can be applied to labeling topics learned through all kinds of topic models such as plsa, lda, and their variations.
efficiently handling feature redundancy in high-dimensional data. high-dimensional data poses a severe challenge for data mining. feature selection is a frequently used technique in pre-processing high-dimensional data for successful data mining. traditionally, feature selection is focused on removing irrelevant features. however, for high-dimensional data, removing redundant features is equally critical. in this paper, we provide a study of feature redundancy in high-dimensional data and propose a novel correlation-based approach to feature selection within the filter model. the extensive empirical study using real-world data shows that the proposed approach is efficient and effective in removing redundant and irrelevant features.
characterising the difference. characterising the differences between two databases is an often occurring problem in data mining. detection of change over time is a prime example, comparing databases from two branches is another one. the key problem is to discover the patterns that describe the difference. emerging patterns provide only a partial answer to this question. in previous work, we showed that the data distribution can be captured in a pattern-based model using compression [12]. here, we extend this approach to define a generic dissimilarity measure on databases. moreover, we show that this approach can identify those patterns that characterise the differences between two distributions. experimental results show that our method provides a well-founded way to independently measure database dissimilarity that allows for thorough inspection of the actual differences. this illustrates the use of our approach in real world data mining.
redundancy based feature selection for microarray data. in gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseases or phenotypes. the problem becomes particularly challenging due to the large number of features (genes) and small sample size. traditional gene selection methods often select the top-ranked genes according to their individual discriminative power without handling the high degree of redundancy among the genes. latest research shows that removing redundant genes among selected ones can achieve a better representation of the characteristics of the targeted phenotypes and lead to improved classification accuracy. hence, we study in this paper the relationship between feature relevance and redundancy and propose an efficient method that can effectively remove redundant genes. the efficiency and effectiveness of our method in comparison with representative methods has been demonstrated through an empirical study using public microarray data sets.
classifying large data sets using svms with hierarchical clusters. support vector machines (svms) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convery several salient properties that other methods hardly provide. however, despite the prominent properties of svms, they are not as favored for large-scale data mining as for pattern recognition or machine learning because the training complexity of svms is highly dependent on the size of a data set. many real-world data mining applications involve millions or billions of data records where even multiple scans of the entire data are too expensive to perform. this paper presents a new method, clustering-based svm (cb-svm), which is specifically designed for handling very large data sets. cb-svm applies a hierarchical micro-clustering algorithm that scans the entire data set only once to provide an svm with high quality samples that carry the statistical summaries of the data such that the summaries maximize the benefit of learning the svm. cb-svm tries to generate the best svm boundary for very large data sets given limited amount of resources. our experiments on synthetic and real data sets show that cb-svm is highly scalable for very large data sets while also generating high classification accuracy.
supervised probabilistic principal component analysis. principal component analysis (pca) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. when labels of data are available, e.g., in a classification or regression task, pca is however not able to use this information. the problem is more interesting if only part of the input data are labeled, i.e., in a semi-supervised setting. in this paper we propose a supervised pca model called sppca and a semi-supervised pca model called s2ppca, both of which are extensions of a probabilistic pca model. the proposed models are able to incorporate the label information into the projection phase, and can naturally handle multiple outputs (i.e., in multi-task learning problems). we derive an efficient em learning algorithm for both models, and also provide theoretical justifications of the model behaviors. sppca and s2ppca are compared with other supervised projection methods on various learning tasks, and show not only promising performance but also good scalability.
learning and making decisions when costs and probabilities are both unknown. in many machine learning domains, misclassification costs are different for different examples, in the same way that class membership probabilities are example-dependent. in these domains, both costs and probabilities are unknown for test examples, so both cost estimators and probability estimators must be learned. this paper first discusses how to make optimal decisions given cost and probability estimates, and then presents decision tree learning methods for obtaining well-calibrated probability estimates. the paper then explains how to obtain unbiased estimators for example- dependent costs, taking into account the difficulty that in general, probabilities and costs are not independent random variables, and the training examples for which costs are known are not representative of all examples. the latter problem is called sample selection bias in econometrics. our solution to it is based on nobel prize-winning work due to the economist james heckman. we show that the methods we propose are successful in a comprehensive comparison with metacost that uses the well-known and difficult dataset from the kdd''98 data mining contest.
joint cluster analysis of attribute and relationship data withouta-priori specification of the number of clusters. in many applications, attribute and relationship data areavailable, carrying complementary information about real world entities. in such cases, a joint analysis of both types of data can yield more accurate results than classical clustering algorithms that either use only attribute data or only relationship (graph) data. the connected k-center (ckc) has been proposed as the first joint cluster analysis model to discover k clusters which are cohesive on both attribute and relationship data. however, it is well-known that prior knowledge on the number of clusters is often unavailable in applications such as community dentification and hotspot analysis. in this paper, we introduce and formalize the problem of discovering an a-priori unspecified number of clusters in the context of joint cluster analysis of attribute and relationship data, called connected x clusters (cxc) problem. true clusters are assumed to be compact and distinctive from their neighboring clusters in terms of attribute data and internally connected in terms of relationship data. different from classical attribute-based clustering methods, the neighborhood of clusters is not defined in terms of attribute data but in terms of relationship data. to efficiently solve the cxc problem, we present jointclust, an algorithm which adopts a dynamic two-phase approach. in the first phase, we find so called cluster atoms. we provide a probability analysis for thisphase, which gives us a probabilistic guarantee, that each true cluster is represented by at least one of the initial cluster atoms. in the second phase, these cluster atoms are merged in a bottom-up manner resulting in a dendrogram. the final clustering is determined by our objective function. our experimental evaluation on several real datasets demonstrates that jointclust indeed discovers meaningful and accurate clusterings without requiring the user to specify the number of clusters.
transforming classifier scores into accurate multiclass probability estimates. class membership probability estimates are important for many applications of data mining in which classification outputs are combined with other sources of information for decision-making, such as example-dependent misclassification costs, the outputs of other classifiers, or domain knowledge. previous calibration methods apply only to two-class problems. here, we show how to obtain accurate probability estimates for multiclass problems by combining calibrated binary probability estimates. we also propose a new method for obtaining calibrated two-class probability estimates that can be applied to any classifier that produces a ranking of examples. using naive bayes and support vector machine classifiers, we give experimental results from a variety of two-class and multiclass domains, including direct marketing, text categorization and digit recognition.
training structural svms with kernels using sampled cuts. discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer vision. focusing on large-margin methods, the most general (in terms of loss function and model structure) training algorithms known to date are based on cutting-plane approaches. while these algorithms are very efficient for linear models, their training complexity becomes quadratic in the number of examples when kernels are used. to overcome this bottleneck, we propose new training algorithms that use approximate cutting planes and random sampling to enable efficient training with kernels. we prove that these algorithms have improved time complexity while providing approximation guarantees. in empirical evaluations, our algorithms produced solutions with training and test error rates close to those of exact solvers. even on binary classification problems where highly optimized conventional training methods exist (e.g. svm-light), our methods are about an order of magnitude faster than conventional training methods on large datasets, while remaining competitive in speed on datasets of medium size.
pattern lattice traversal by selective jumps. regardless of the frequent patterns to discover, either the full frequent patterns or the condensed ones, either closed or maximal, the strategy always includes the traversal of the lattice of candidate patterns. we study the existing depth versus breadth traversal approaches for generating candidate patterns and propose in this paper a new traversal approach that jumps in the search space among only promising nodes. our leaping approach avoids nodes that would not participate in the answer set and reduce drastically the number of candidate patterns. we use this approach to efficiently pinpoint maximal patterns at the border of the frequent patterns in the lattice and collect enough information in the process to generate all subsequent patterns.
real-time ranking with concept drift using expert advice. in many practical applications, one is interested in generating a ranked list of items using information mined from continuous streams of data. for example, in the context of computer networks, one might want to generate lists of nodes ranked according to their susceptibility to attack. in addition, real-world data streams often exhibit concept drift, making the learning task even more challenging. we present an online learning approach to ranking with concept drift, using weighted majority techniques. by continuously modeling different snapshots of the data and tuning our measure of belief in these models over time, we capture changes in the underlying concept and adapt our predictions accordingly. we measure the performance of our algorithm on real electricity data as well as asynthetic data stream, and demonstrate that our approach to ranking from stream data outperforms previously known batch-learning methods and other online methods that do not account for concept drift.
estimating rates of rare events at multiple resolutions. we consider the problem of estimating occurrence rates of rare eventsfor extremely sparse data, using pre-existing hierarchies to perform inference at multiple resolutions. in particular, we focus on the problem of estimating click rates for (webpage, advertisement) pairs (called impressions) where both the pages and the ads are classified into hierarchies that capture broad contextual information at different levels of granularity. typically the click rates are low and the coverage of the hierarchies is sparse. to overcome these difficulties we devise a sampling method whereby we analyze aspecially chosen sample of pages in the training set, and then estimate click rates using a two-stage model. the first stage imputes the number of (webpage, ad) pairs at all resolutions of the hierarchy to adjust for the sampling bias. the second stage estimates clickrates at all resolutions after incorporating correlations among sibling nodes through a tree-structured markov model. both models are scalable and suited to large scale data mining applications. on a real-world dataset consisting of 1/2 billion impressions, we demonstrate that even with 95% negative (non-clicked) events in the training set, our method can effectively discriminate extremely rare events in terms of their click propensity.
distributed classification in peer-to-peer networks. this work studies the problem of distributed classification in peer-to-peer(p2p) networks. while there has been a significant amount of work in distributed classification, most of existing algorithms are not designed for p2p networks. indeed, as server-less and router-less systems, p2p networks impose several challenges for distributed classification: (1) it is not practical to have global synchronization in large-scale p2p networks; (2)there are frequent topology changes caused by frequent failure and recovery of peers; and (3) there are frequent on-the-fly data updates on each peer. in this paper, we propose an ensemble paradigm for distributed classification in p2p networks. under this paradigm, each peer builds its local classifiers on the local data and the results from all local classifiers are then combined by plurality voting. to build local classifiers, we adopt the learning algorithm of pasting bites to generate multiple local classifierson each peer based on the local data. to combine local results, we propose a general form of distributed plurality voting (dpv) protocol in dynamic p2p networks. this protocol keeps the single-site validity for dynamic networks, and supports the computing modes of both one-shot query and continuous monitoring. we theoretically prove that the condition (bob check this 'c')ω0 for sending messages used in dpv0 is locally communication-optimal to achieve the above properties. finally, experimental results on real-world p2p networks show that: (1) the proposed ensemble paradigm is effective even if there are thousands of local classifiers; (2) in most cases, the dpv0 algorithm is local in the sense that voting is processed using information gathered from a very small vicinity, whose size is independent of the network size; (3) dpv0 is significantly more communication-efficient than existing algorithms for distributed plurality voting.
efficiently mining frequent trees in a forest. mining frequent trees is very useful in domains like bioinformatics, web mining, mining semistructured data, and so on. we formulate the problem of mining (embedded) subtrees in a forest of rooted, labeled, and ordered trees. we present treeminer, a novel algorithm to discover all frequent subtrees in a forest, using a new data structure called scope-list. we contrast treeminer with a pattern matching tree mining algorithm (patternmatcher). we conduct detailed experiments to test the performance and scalability of these methods. we find that treeminer outperforms the pattern matching approach by a factor of 4 to 20, and has good scaleup properties. we also present an application of tree mining to analyze real web logs for usage patterns.
mining correlated bursty topic patterns from coordinated text streams. previous work on text mining has almost exclusively focused on a single stream. however, we often have available multiple text streams indexed by the same set of time points (called coordinated text streams), which offer new opportunities for text mining. for example, when a major event happens, all the news articles published by different agencies in different languages tend to cover the same event for a certain period, exhibiting a correlated bursty topic pattern in all the news article streams. in general, mining correlated bursty topic patterns from coordinated text streams can reveal interesting latent associations or events behind these streams. in this paper, we define and study this novel text mining problem. we propose a general probabilistic algorithm which can effectively discover correlated bursty patterns and their bursty periods across text streams even if the streams have completely different vocabularies (e.g., english vs chinese). evaluation of the proposed method on a news data set and a literature data set shows that it can effectively discover quite meaningful topic patterns from both data sets: the patterns discovered from the news data set accurately reveal the major common events covered in the two streams of news articles (in english and chinese, respectively), while the patterns discovered from two database publication streams match well with the major research paradigm shifts in database research. since the proposed method is general and does not require the streams to share vocabulary, it can be applied to any coordinated text streams to discover correlated topic patterns that burst in multiple streams in the same period.
from mining the web to inventing the new sciences underlying the internet. this is an abstract of the invited keynote presentation to be presented at kdd-07. as the internet continues to change the way we live, find information, communicate, and do business, it has also been taking on a dramatically increasing role in marketing and advertising. unlike any prior mass medium, the internet is a unique medium when it comes to interactivity and offers an ability to target and program messaging at the individual level. coupled with its uniqueness in the richness of the data that is available for measurability, in the variety of ways to utilize the data, and in the great dependence of effective marketing on applications that are heavily data-driven, makes data mining and statistical data analysis, modeling, and reporting an essential mission-critical part of running the on-line business. however, because of its novelty and the scale of data sets involved, few companies have figured out how to properly make use of this data. in this talk, i will review some of the challenges and opportunities in the utilization of data to drive this new generation of marketing systems. i will provide several examples of how data is utilized in critical ways to drive some of these capabilities. the discussion will be framed with the more general framework of grand challenges for data mining: pragmatic and technical. i will conclude this presentation witha consideration of the larger issues surrounding the internet as a technology that is ubiquitous in our lives, yet one where very little is understood, at the scientific level, in defining and understanding many of the basics the internet enables: community, personalization, and the new microeconomics of the web. this leads to an overview of the new yahoo! research organization and its aims: inventing the new sciences underlying what we do on the internet, focusing on areas that have received little attention in the traditional academic circles. some illustrative examples will be reviewed to make the ultimate goals more concrete.
a scalable modular convex solver for regularized risk minimization. a wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different regularizers. examples include linear support vector machines (svms), logistic regression, conditional random fields (crfs), and lasso amongst others. this paper describes the theory and implementation of a highly scalable and modular convex solver which solves all these estimation problems. it can be parallelized on a cluster of workstations, allows for data-locality, and can deal with regularizers such as l1 and l2 penalties. at present, our solver implements 20 different estimation problems, can be easily extended, scales to millions of observations, and is up to 10 times faster than specialized solvers for many applications. the open source code is freely available as part of the elefant toolbox.
xrules: an effective structural classifier for xml data. xml documents have recently become ubiquitous because of their varied applicability in a number of applications. classification is an important problem in the data mining domain, but current classification methods for xml documents use ir-based methods in which each document is treated as a bag of words. such techniques ignore a significant amount of information hidden inside the documents. in this paper we discuss the problem of rule based classification of xml data by using frequent discriminatory substructures within xml documents. such a technique is more capable of finding the classification characteristics of documents. in addition, the technique can also be extended to cost sensitive classification. we show the effectiveness of the method with respect to other classifiers. we note that the methodology discussed in this paper is applicable to any kind of semi-structured data.
graphscope: parameter-free mining of large time-evolving graphs. how can we find communities in dynamic networks of socialinteractions, such as who calls whom, who emails whom, or who sells to whom? how can we spot discontinuity time-points in such streams of graphs, in an on-line, any-time fashion? we propose graphscope, that addresses both problems, using information theoretic principles. contrary to the majority of earlier methods, it needs no user-defined parameters. moreover, it is designed to operate on large graphs, in a streaming fashion. we demonstrate the efficiency and effectiveness of our graphscope on real datasets from several diverse domains. in all cases it produces meaningful time-evolving patterns that agree with human intuition.
fast vertical mining using diffsets. a number of vertical mining algorithms have been proposed recently for association mining, which have shown to be very effective and usually outperform horizontal approaches. the main advantage of the vertical format is support for fast frequency counting via intersection operations on transaction ids (tids) and automatic pruning of irrelevant data. the main problem with these approaches is when intermediate results of vertical tid lists become too large for memory, thus affecting the algorithm scalability.in this paper we present a novel vertical data representation called diffset, that only keeps track of differences in the tids of a candidate pattern from its generating frequent patterns. we show that diffsets drastically cut down the size of memory required to store intermediate results. we show how diffsets, when incorporated into previous vertical mining methods, increase the performance significantly.
reasoning about sets using redescription mining. redescription mining is a newly introduced data mining problem that seeks to find subsets of data that afford multiple definitions. it can be viewed as a generalization of association rule mining, from finding implications to equivalences; as a form of conceptual clustering, where the goal is to identify clusters that afford dual characterizations; and as a form of constructive induction, to build features based on given descriptors that mutually reinforce each other. in this paper, we present the use of redescription mining as an important tool to reason about a collection of sets, especially their overlaps, similarities, and differences. we outline algorithms to mine all minimal (non-redundant) redescriptions underlying a dataset using notions of minimal generators of closed itemsets. we also show the use of these algorithms in an interactive context, supporting constraint-based exploration and querying. specifically, we showcase a bioinformatics application that empowers the biologist to define a vocabulary of sets underlying a domain of genes and to reason about these sets, yielding significant biological insight.
influence and correlation in social networks. in many online social systems, social ties between users play an important role in dictating their behavior. one of the ways this can happen is through social influence, the phenomenon that the actions of a user can induce his/her friends to behave in a similar way. in systems where social influence exists, ideas, modes of behavior, or new technologies can diffuse through the network like an epidemic. therefore, identifying and understanding social influence is of tremendous interest from both analysis and design points of view. this is a difficult task in general, since there are factors such as homophily or unobserved confounding variables that can induce statistical correlation between the actions of friends in a social network. distinguishing influence from these is essentially the problem of distinguishing correlation from causality, a notoriously hard statistical problem. in this paper we study this problem systematically. we define fairly general models that replicate the aforementioned sources of social correlation. we then propose two simple tests that can identify influence as a source of social correlation when the time series of user actions is available. we give a theoretical justification of one of the tests by proving that with high probability it succeeds in ruling out influence in a rather general model of social correlation. we also simulate our tests on a number of examples designed by randomly generating actions of nodes on a real social network (from flickr) according to one of several models. simulation results confirm that our test performs well on these data. finally, we apply them to real tagging data on flickr, exhibiting that while there is significant social correlation in tagging behavior on this system, this correlation cannot be attributed to social influence.
event summarization for system management. in system management applications, an overwhelming amount of data are generated and collected in the form of temporal events. while mining temporal event data to discover interesting and frequent patterns has obtained rapidly increasing research efforts, users of the applications are overwhelmed by the mining results. the extracted patterns are generally of large volume and hard to interpret, they may be of no emphasis, intricate and meaningless to non-experts, even to domain experts. while traditional research efforts focus on finding interesting patterns, in this paper, we take a novel approach called event summarization towards the understanding of the seemingly chaotic temporal data. event summarization aims at providing a concise interpretation of the seemingly chaotic data, so that domain experts may take actions upon the summarized models. event summarization decomposes the temporal information into many independent subsets and finds well fitted models to describe each subset.
active exploration for learning rankings from clickthrough data. we address the task of learning rankings of documents from search enginelogs of user behavior. previous work on this problem has relied onpassively collected clickthrough data. in contrast, we show that anactive exploration strategy can provide data that leads to much fasterlearning. specifically, we develop a bayesian approach for selectingrankings to present users so that interactions result in more informativetraining data. our results using the trec-10 web corpus, as well assynthetic data, demonstrate that a directed exploration strategy quicklyleads to users being presented improved rankings in an online learningsetting. we find that active exploration substantially outperformspassive observation and random exploration.
making generative classifiers robust to selection bias. this paper presents approaches to semi-supervised learning when the labeled training data and test data are differently distributed. specifically, the samples selected for labeling are a biased subset of some general distribution and the test set consists of samples drawn from either that general distribution or the distribution of the unlabeled samples. an example of the former appears in loan application approval, where samples with repay/default labels exist only for approved applicants and the goal is to model the repay/default behavior of all applicants. an example of the latter appears in spam filtering, in which the labeled samples can be out-dated due to the cost of labeling email by hand, but an unlabeled set of up-to-date emails exists and the goal is to build a filter to sort new incoming email.most approaches to overcoming such bias in the literature rely on the assumption that samples are selected for labeling depending only on the features, not the labels, a case in which provably correct methods exist. the missing labels are said to be "missing at random" (mar). in real applications, however, the selection bias can be more severe. when the mar conditional independence assumption is not satisfied and missing labels are said to be "missing not at random" (mnar), and no learning method is provably always correct.we present a generative classifier, the shifted mixture model (smm), with separate representations of the distributions of the labeled samples and the unlabeled samples. the smm makes no conditional independence assumptions and can model distributions of semi-labeled data sets with arbitrary bias in the labeling. we present a learning method based on the expectation maximization (em) algorithm that, while not always able to overcome arbitrary labeling bias, learns smms with higher test-set accuracy in real-world data sets (with mnar bias) than existing learning methods that are proven to overcome mar bias.
detecting anomalous records in categorical datasets. we consider the problem of detecting anomalies in high aritycategorical datasets. in most applications, anomalies are defined as datapoints that are "abnormal". quite often we have access to data which consists mostly of normal records, a long with a small percentage of unlabelled anomalous records. we are interested in the problem of unsupervised anomaly detection, where we use the unlabelled data for training, and detect records that do not follow the definition of normality. a standard approach is to create a model of normal data, and compare test records against it. a probabilistic approach builds a likelihood model from the training data. records are tested for anomalies based on the complete record likelihood given the probability model. for categorical attributes, bayes nets give a standard representation of the likelihood. while this approach is good at finding outliers in the dataset, it often tends to detect records with attribute values that are rare. sometimes, just detecting rare values of an attribute is not desired and such outliers are not considered as anomalies in that context. we present an alternative definition of anomalies, and propose an approach of comparing against marginal distribution of attribute subsets. we show that this is a more meaningful way of detecting anomalies, and has a better performance over semi-synthetic as well as real world datasets.
permu-pattern: discovery of mutable permutation patterns with proximity constraint. pattern discovery in sequences is an important problem in many applications, especially in computational biology and text mining. however, due to the noisy nature of data, the traditional sequential pattern model may fail to reflect the underlying characteristics of sequence data in these applications. there are two challenges: first, the mutation noise exists in the data, and therefore symbols may be misrepresented by other symbols; secondly, the order of symbols in sequences could be permutated. to address the above problems, in this paper we propose a new sequential pattern model called mutable permutation patterns. since the apriori property does not hold for our permutation pattern model, a novel permu-pattern algorithm is devised to mine frequent mutable permutation patterns from sequence databases. a reachability property is identified to prune the candidate set. last but not least, we apply the permutation pattern model to a real genome dataset to discover gene clusters, which shows the effectiveness of the model. a large amount of synthetic data is also utilized to demonstrate the efficiency of the permu-pattern algorithm.
privacy-preservation for gradient descent methods. gradient descent is a widely used paradigm for solving many optimization problems. stochastic gradient descent performs a series of iterations to minimize a target function in order to reach a local minimum. in machine learning or data mining, this function corresponds to a decision model that is to be discovered. the gradient descent paradigm underlies many commonly used techniques in data mining and machine learning, such as neural networks, bayesian networks, genetic algorithms, and simulated annealing. to the best of our knowledge, there has not been any work that extends the notion of privacy preservation or secure multi-party computation to gradient-descent-based techniques. in this paper, we propose a preliminary approach to enable privacy preservation in gradient descent methods in general and demonstrate its feasibility in specific gradient descent methods.
imds: intelligent malware detection system. the proliferation of malware has presented a serious threat to the security of computer systems. traditional signature-based anti-virus systems fail to detect polymorphic and new, previously unseen malicious executables. in this paper, resting on the analysis of windows api execution sequences called by pe files, we develop the intelligent malware detection system (imds) using objective-oriented association (ooa) mining based classification. imds is an integrated system consisting of three major modules: pe parser, ooa rule generator, and rule based classifier. an ooa_fast_fp-growth algorithm is adapted to efficiently generate ooa rules for classification. a comprehensive experimental study on a large collection of pe files obtained from the anti-virus laboratory of king-soft corporation is performed to compare various malware detection approaches. promising experimental results demonstrate that the accuracy and efficiency of our imds system out perform popular anti-virus software such as norton antivirus and mcafee virusscan, as well as previous data mining based detection systems which employed naive bayes, support vector machine (svm) and decision tree techniques.
mining complex power networks for blackout prevention. following the recent devastating blackouts in north america, uk and italy, blackout prevention has attracted significant attention, though it is known as a notoriously difficult task. to prevent the blackout, it is essential to accurately predict the instable status of power network components. in the large-scale power network however, existing analysis tools fail to perform accurate and in-time prediction of component instability, because of the sophisticated structure of real-world power networks and the huge amount of system variables to be analyzed. to prevent the blackout, we need an accurate and efficient method that (a) can discover interesting features and patterns relevant to the blackout, from the highly complex structure and ten thousands of system variables of a power network, and (b) can give accurate and fast prediction of system instability whenever required, so that the network operator can take necessary actions in time. in this paper, we report our tool developed for power network instability prediction. the proposed method consists of two major stages. in the first stage,a novel type of patterns namely local correlation network pattern (lcnp) is mined from the structure and system variables of the power network. correlation rules, which are useful for the network operator to locate potentially instable components, can be further generated from the lcnp. in the second stage, a kernel based network classification method is developed to predict the system instability. by testing on a real world power network (the new england system), we demonstrate that the proposed tool is effective in predicting system instability and thus highly useful for blackout prevention.
learning subspace kernels for classification. kernel methods have been applied successfully in many data mining tasks. subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kernel feature space for improved classification. in this paper, we propose to construct a subspace kernel using the hilbert-schmidt independence criterion (hsic). we show that the optimal subspace kernel can be obtained efficiently by solving an eigenvalue problem. one limitation of the existing subspace kernel learning formulations is that the kernel learning and classification are independent and the subspace kernel may not be optimally adapted for classification. to overcome this limitation, we propose a joint optimization framework, in which we learn the subspace kernel and subsequent classifiers simultaneously. in addition, we propose a novel learning formulation that extracts an uncorrelated subspace kernel to reduce the redundant information in a subspace kernel. following the idea from multiple kernel learning, we extend the proposed formulations to the case when multiple kernels are available and need to be combined. we show that the integration of subspace kernels can be formulated as a semidefinite program (sdp) which is computationally expensive. to improve the efficiency of the sdp formulation, we propose an equivalent semi-infinite linear program (silp) formulation which can be solved efficiently by the column generation technique. experimental results on a collection of benchmark data sets demonstrate the effectiveness of the proposed algorithms.
fast best-effort pattern matching in large attributed graphs. we focus on large graphs where nodes have attributes, such as a social network where the nodes are labelled with each person's job title. in such a setting, we want to find subgraphs that match a user query pattern. for example, a "star" query would be, "find a ceo who has strong interactions with a manager, a lawyer,and an accountant, or another structure as close to that as possible". similarly, a "loop" query could help spot a money laundering ring. traditional sql-based methods, as well as more recent graph indexing methods, will return no answer when an exact match does not exist. this is the first main feature of our method. it can find exact-, as well as near-matches, and it will present them to the user in our proposed "goodness" order. for example, our method tolerates indirect paths between, say, the "ceo" and the "accountant" of the above sample query, when direct paths don't exist. its second feature is scalability. in general, if the query has nq nodes and the data graph has n nodes, the problem needs polynomial time complexity o(n n q), which is prohibitive. our g-ray ("graph x-ray") method finds high-quality subgraphs in time linear on the size of the data graph. experimental results on the dlbp author-publication graph (with 356k nodes and 1.9m edges) illustrate both the effectiveness and scalability of our approach. the results agree with our intuition, and the speed is excellent. it takes 4 seconds on average fora 4-node query on the dblp graph.
model-shared subspace boosting for multi-label classification. typical approaches to the multi-label classification problem require learning an independent classifier for every label from all the examples and features. this can become a computational bottleneck for sizeable datasets with a large label space. in this paper, we propose an efficient and effective multi-label learning algorithm called model-shared subspace boosting (mssboost) as an attempt to reduce the information redundancy in the learning process. this algorithm automatically finds, shares and combines a number of base models across multiple labels, where each model is learned from random feature subspace and boots trap data samples. the decision functions for each label are jointly estimated and thus a small number of shared subspace models can support the entire label space. our experimental results on both synthetic data and real multimedia collections have demonstrated that the proposed algorithm can achieve better classification performance than the non-ensemble baselineclassifiers with a significant speedup in the learning and prediction processes. it can also use a smaller number of base models to achieve the same classification performance as its non-model-shared counterpart.
detecting time series motifs under uniform scaling. time series motifs are approximately repeated patterns foundwithin the data. such motifs have utility for many data mining algorithms, including rule-discovery,novelty-detection, summarization and clustering. since the formalization of the problem and the introduction of efficient linear time algorithms, motif discovery has been successfully applied tomany domains, including medicine, motion capture, robotics and meteorology. in this work we show that most previous applications of time series motifs have been severely limited by the definition's brittleness to even slight changes of uniform scaling, the speed at which the patterns develop. we introduce a new algorithm that allows discovery of time series motifs with invariance to uniform scaling, and show that it produces objectively superior results in several important domains. apart from being more general than all other motifdiscovery algorithms, a further contribution of our work isthat it is simpler than previous approaches, in particular we have drastically reduced the number of parameters that need to be specified.
learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming. the kernel function plays a central role in kernel methods. in this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kernel matrices in regularized kernel discriminant analysis (rkda), which performs lineardiscriminant analysis in the feature space via the kernel trick. previous studies have shown that this kernel learning problem can be formulated as a semidefinite program (sdp), which is however computationally expensive, even with the recent advances in interior point methods. based on the equivalence relationship between rkda and least square problems in the binary-class case, we propose a quadratically constrained quadratic programming (qcqp) formulation for the kernel learning problem, which can be solved more efficiently than sdp. while most existing work on kernel learning deal with binary-class problems only, we show that our qcqp formulation can be extended naturally to the multi-class case. experimental results on both binary-class and multi-class benchmarkdata sets show the efficacy of the proposed qcqp formulations.
webpage understanding: an integrated approach. recent work has shown the effectiveness of leveraging layout and tag-tree structure for segmenting webpages and labeling html elements. however, how to effectively segment and label the text contents inside html elements is still an open problem. since many text contents on a webpage are often text fragments and not strictly grammatical, traditional natural language processing techniques, that typically expect grammatical sentences, are no longer directly applicable. in this paper, we examine how to use layout and tag-tree structure in a principled way to help understand text contents on webpages. we propose to segment and label the page structure and the text content of a webpage in a joint discriminative probabilistic model. in this model, semantic labels of page structure can be leveraged to help text content understanding, and semantic labels ofthe text phrases can be used in page structure understanding tasks such as data record detection. thus, integration of both page structure and text content understanding leads to an integrated solution of webpage understanding. experimental results on research homepage extraction show the feasibility and promise of our approach.
building semantic kernels for text classification using wikipedia. document classification presents difficult challenges due to the sparsity and the high dimensionality of text data, and to the complex semantics of the natural language. the traditional document representation is a word-based vector (bag of words, or bow), where each dimension is associated with a term of the dictionary containing all the words that appear in the corpus. although simple and commonly used, this representation has several limitations. it is essential to embed semantic information and conceptual patterns in order to enhance the prediction capabilities of classification algorithms. in this paper, we overcome the shortages of the bow approach by embedding background knowledge derived from wikipedia into a semantic kernel, which is then used to enrich the representation of documents. our empirical evaluation with real data sets demonstrates that our approach successfully achieves improved classification accuracy with respect to the bow technique, and to other recently developed methods.
local decomposition for rare class analysis. given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. however, the rare-class problem remains a critical challenge, because there is no natural way developed for handling imbalanced class distributions. this paper thus fills this crucial void by developing a method for classification using local clustering (cog). specifically, for a data set with an imbalanced class distribution, we perform clustering within each large class and produce sub-classes with relatively balanced sizes. then, we apply traditional supervised learning algorithms, such as support vector machines (svms), for classification. indeed, our experimental results on various real-world data sets show that our method produces significantly higher prediction accuracies on rare classes than state-of-the-art methods. furthermore, we show that cog can also improve the performance of traditional supervised learning algorithms on data sets with balanced class distributions.
the structure of information pathways in a social communication network. social networks are of interest to researchers in part because they are thought to mediate the flow of information in communities and organizations. here we study the temporal dynamics of communication using on-line data, including e-mail communication among the faculty and staff of a large university over a two-year period. we formulate a temporal notion of "distance" in the underlying social network by measuring the minimum time required for information to spread from one node to another - a concept that draws on the notion of vector-clocks from the study of distributed computing systems. we find that such temporal measures provide structural insights that are not apparent from analyses of the pure social network topology. in particular, we define the network backbone to be the subgraph consisting of edges on which information has the potential to flow the quickest. we find that the backbone is a sparse graph with a concentration of both highly embedded edges and long-range bridges - a finding that sheds new light on the relationship between tie strength and connectivity in social networks.
enhanced max margin learning on multimodal data mining in a multimedia database. the problem of multimodal data mining in a multimedia database can be addressed as a structured prediction problem where we learn the mapping from an input to the structured and interdependent output variables. in this paper, built upon the existing literature on the max margin based learning, we develop a new max margin learning approach called enhanced max margin learning (emml) framework. in addition, we apply emml framework to developing an effective and efficient solution to the multimodal data mining problem in a multimedia database. the main contributions include: (1) we have developed a new max margin learning approach - the enhanced max margin learning framework that is much more efficient in learning with a much faster convergence rate, which is verified in empirical evaluations; (2) we have applied this emml approach to developing an effective and efficient solution to the multimodal data mining problem that is highly scalable in the sense that the query response time is independent of the database scale, allowing facilitating a multimodal data mining querying to a very large scale multimedia database,and excelling many existing multimodal data mining methods in the literature that do not scale up at all; this advantage is also supported through the complexity analysis as well as empirical evaluations against a state-of-the-art multimodal data mining method from the literature. while emml is a general framework, for the evaluation purpose, we apply it to the berkeley drosophila embryo image database, and report the performance comparison with a state-of-the-art multimodal data mining method.
active learning with direct query construction. active learning may hold the key for solving the data scarcity problem in supervised learning, i.e., the lack of labeled data. indeed, labeling data is a costly process, yet an active learner may request labels of only selected instances, thus reducing labeling work dramatically. most previous works of active learning are, however, pool-based; that is, a pool of unlabeled examples is given and the learner can only select examples from the pool to query for their labels. this type of active learning has several weaknesses. in this paper we propose novel active learning algorithms that construct examples directly to query for labels. we study both a specific active learner based on the decision tree algorithm, and a general active learner that can work with any base learning algorithm. as there is no restriction on what examples to be queried, our methods are shown to often query fewer examples to reduce the predictive error quickly. this casts doubt on the usefulness of the pool in pool-based active learning. nevertheless, our methods can be easily adapted to work with a given pool of unlabeled examples.
association analysis-based transformations for protein interaction networks: a function prediction case study. protein interaction networks are one of the most promising types of biological data for the discovery of functional modules and the prediction of individual protein functions. however, it is known that these networks are both incomplete and inaccurate, i.e., they have spurious edges and lackbiologically valid edges. one way to handle this problem is by transforming the original interaction graph into new graphs that remove spurious edges, add biologically valid ones, and assign reliability scores to the edges constituting the final network. we investigate currently existing methods, as well as propose a robust association analysis-based method for this task. this method is based on the concept of h-confidence, which is a measure that can be used to extract groups of objects having high similarity with each other. experimental evaluation on several protein interaction data sets show that hyperclique-based transformations enhance the performance of standard function prediction algorithms significantly, and thus have merit.
data mining at the crossroads: successes, failures and learning from them. since the 1989 workshop on knowledge discovery in databases, the field has seen sustained growth and interest and has attained significant maturity. the main objectives of this panel will be to reflect on the successes and failures in the field of data mining over the last eighteen years and to examine what insights we can take with us as we move forward.
knowledge discovery of multiple-topic document using parametric mixture model with dirichlet prior. documents, such as those seen on wikipedia and folksonomy, have tended to be assigned with multiple topics as a meta-data.therefore, it is more and more important to analyze a relationship between a document and topics assigned to the document. in this paper, we proposed a novel probabilistic generative model of documents with multiple topics as a meta-data. by focusing on modeling the generation process of a document with multiple topics, we can extract specific properties of documents with multiple topics.proposed model is an expansion of an existing probabilistic generative model: parametric mixture model (pmm). pmm models documents with multiple topics by mixing model parameters of each single topic. since, however, pmm assigns the same mixture ratio to each single topic, pmm cannot take into account the bias of each topic within a document. to deal with this problem, we propose a model that considers dirichlet distribution as a prior distribution of the mixture ratio.we adopt variational bayes method to infer the bias of each topic within a document. we evaluate the proposed model and pmm using medline corpus.the results of f-measure, precision and recall show that the proposed model is more effective than pmm on multiple-topic classification. moreover, we indicate the potential of the proposed model that extracts topics and document-specific keywords using information about the assigned topics.
using hierarchical clustering for learning theontologies used in recommendation systems. ontologies are being successfully used to overcome semanticheterogeneity, and are becoming fundamental elements of the semanticweb. recently, it has also been shown that ontologies can be used tobuild more accurate and more personalized recommendation systems byinferencing missing user's preferences. however, these systemsassume the existence of ontologies, without considering theirconstruction. with product catalogs changing continuously, newtechniques are required in order to build these ontologies in realtime, and autonomously from any expert intervention.this paper focuses on this problem and show that it is possible tolearn ontologies autonomously by using clustering algorithms. results on the movielens and jester data sets show that recommendersystem with learnt ontologies significantly outperform the classical recommendation approach.
practical learning from one-sided feedback. in many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. such applications includespam filtering in the case where users never checkemails marked "spam", document retrieval where users cannotgive relevance feedback on unretrieved documents,and online advertising where user behavior cannot beobserved for unshown advertisements. one-sided feedback can cripple the performance of classical mistake-driven online learners such as perceptron. previous work under the apple tasting framework showed how to transform standard online learners into successful learners from one sided feedback. however, we find in practice that this transformation may request more labels than necessary to achieve strong performance. in this paper,we employ two active learning methods which reduce the number of labels requested in practice. one method is the use of label efficient active learning. the other method,somewhat surprisingly, is the use of margin-based learners without modification, which we show combines implicit active learning and a greedy strategy to managing the exploration exploitation tradeoff. experimental results show that these methods can be significantly more effective in practice than those using the apple tasting transformation, even on minority class problems.
statistical change detection for multi-dimensional data. this paper deals with detecting change of distribution in multi-dimensional data sets. for a given baseline data set and a set of newly observed data points, we define a statistical test called the density test for deciding if the observed data points are sampled from the underlying distribution that produced the baseline data set. we define a test statistic that is strictly distribution-free under the null hypothesis. our experimental results show that the density test has substantially more power than the two existing methods for multi-dimensional change detection.
spiral: efficient and exact model identification for hidden markov models. hidden markov models (hmms) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use hmm have emerged. the goal of this work is to identify efficiently and correctly the model in a given dataset that yields the state sequence with the highest likelihood with respect to the query sequence. we propose spiral, a fast search method for hmm datasets. to reduce the search cost, spiral efficiently prunes a significant number of search candidates by applying successive approximations when estimating likelihood. we perform several experiments to verify the effectiveness of spiral. the results show that spiral is more than 500 times faster than the naive method.
information genealogy: uncovering the flow of ideas in non-hyperlinked document databases. we now have incrementally-grown databases of text documents ranging back for over a decade in areas ranging from personal email, to news-articles and conference proceedings. while accessing individual documents is easy, methods for overviewing and understanding these collections as a whole are lacking in number and in scope. in this paper, we address one such global analysis task, namely the problem of automatically uncovering how ideas spread through the collection over time. we refer to this problem as information genealogy. in contrast to bibliometric methods that are limited to collections with explicit citation structure, we investigate content-based methods requiring only the text and timestamps of the documents. in particular, we propose a language-modeling approach and a likelihood ratio test to detect influence between documents in a statistically well-founded way. furthermore, we show how this method can be used to infer citation graphs and to identify the most influential documents in the collection. experiments on the nips conference proceedings and the physics arxiv show that our method is more effective than methods based on document similarity.
information distance from a question to an answer. we provide three key missing pieces of a general theory of information distance [3, 23, 24]. we take bold steps in formulating a revised theory to avoid some pitfalls in practical applications. the new theory is then used to construct a question answering system. extensive experiments are conducted to justify the new theory.
community evolution in dynamic multi-mode networks. a multi-mode network typically consists of multiple heterogeneous social actors among which various types of interactions could occur. identifying communities in a multi-mode network can help understand the structural properties of the network, address the data shortage and unbalanced problems, and assist tasks like targeted marketing and finding influential actors within or between groups. in general, a network and the membership of groups often evolve gradually. in a dynamic multi-mode network, both actor membership and interactions can evolve, which poses a challenging problem of identifying community evolution. in this work, we try to address this issue by employing the temporal information to analyze a multi-mode network. a spectral framework and its scalability issue are carefully studied. experiments on both synthetic data and real-world large scale networks demonstrate the efficacy of our algorithm and suggest its generality in solving problems with complex relationships.
high-quantile modeling for customer wallet estimation and other applications. in this paper we discuss the important practical problem of customer wallet estimation, i.e., estimation of potential spending by customers(rather than their expected spending). for this purpose we utilize quantile modeling, whose goal is to estimate a quantile of the discriminative conditional distribution of the response, rather than the mean, which is the implicit goal of most standard regression approaches. we argue that a notion of wallet can be captured through high quantile modeling (e.g, estimating the 90th percentile), and describe a wallet estimation implementation within ibm's market alignment program (map). we also discuss the wide range of domains where high-quantile modeling can be practically important: estimating opportunities in sales and marketing domains, defining 'surprising' patterns for outlier and fraud detection and more. we survey some existing approaches for quantile modeling, and propose adaptations of nearest-neighbor and regression-tree approaches to quantile modeling. we demonstrate the various models' performance in high quantile estimation in several domains, including our motivating problem of estimating the 'realistic' it wallets of ibm customers.
tracking multiple topics for finding interesting articles. we introduce multiple topic tracking (mtt) for iscore to better recommend news articles for users with multiple interests and to address changes in user interests over time. as an extension of the basic rocchio algorithm, traditional topic detection and tracking, and single-pass clustering, mtt maintains multiple interest profiles to identify interesting articles for a specific user given user-feedback. focusing on only interesting topics enables iscore to discard useless profiles to address changes in user interests and to achieve a balance between resource consumption and classification accuracy. also by relating a topic's interestingness to an article.s interestingness, iscore is able to achieve higher quality results than traditional methods such as the rocchio algorithm. we identify several operating parameters that work well for mtt. using the same parameters, we show that mtt alone yields high quality results for recommending interesting articles from several corpora. the inclusion of mtt improves iscore's performance by 9% in recommending news articles from the yahoo! news rss feeds and the trec11 adaptive filter article collection. and through a small user study, we show that iscore can still perform well when only provided with little user feedback.
a concept-based model for enhancing text categorization. most of text categorization techniques are based on word and/or phrase analysis of the text. statistical analysis of a term frequency captures the importance of the term within a document only. however, two terms can have the same frequency in their documents, but one term contributes moreto the meaning of its sentences than the other term. thus, the underlying model should indicate terms that capture these mantics of text. in this case, the model can capture terms that present the concepts of the sentence, which leads todiscover the topic of the document. a new concept-based model that analyzes terms on the sentence and document levels rather than the traditional analysis of document only is introduced. the concept-based model can effectively discriminate between non-important terms with respect to sentence semantics and terms which hold the concepts that represent the sentence meaning. the proposed model consists of concept-based statistical analyzer, conceptual ontological graph representation,and concept extractor. the term which contributes to the sentence semantics is assigned two different weights by the concept-based statistical analyzer and the conceptual ontological graph representation. these two weights are combined into a new weight. the concepts that have maximum combined weights are selected by the concept extractor. a set of experiments using the proposed concept-basedmodel on different datasets in text categorization is conducted. the experiments demonstrate the comparison between traditional weighting and the concept-based weighting obtained by the combined approach of the concept-based statistical analyzer and the conceptual ontological graph. the evaluation of results is relied on two quality measures, the macro-averaged f1 and the error rate. these quality measures are improved when the newly developedconcept-based model is used to enhance the quality of thetext categorization.
use of ranked cross document evidence trails for hypothesis generation. this paper focuses on detecting how concepts are linked across multiple textdocuments by generating an evidence trail explaining the connection. a traditional search involving, for example, two or more person names willattempt to find documents mentioning both of these individuals. this researchfocuses on a different interpretation of such a query: what is the best evidencetrail across documents that explains a connection between these individuals? for example, allmay be good golfers. a generalization ofthis task involves query terms representing general concepts (e.g. indictment,foreign policy). such queries reflect a special case oftext mining. previous attempts to solve this problem have focused on graphapproaches involving hyperlinked documents, and link analysis tools exploiting named entities. a new robust framework is presented, based on (i) generating concept chain graphs, a hybrid content representation, (ii) performing graph matching to select candidate subgraphs, and (iii) subsequently using graphical models to validate hypotheses using ranked evidence trails. we adapt the duc data set for cross-document summarization to evaluate evidence trails generated by this approach.
weighting versus pruning in rule validation for detecting network and host anomalies. for intrusion detection, the lerad algorithm learns a succinct set of comprehensible rules for detecting anomalies, which could be novel attacks. lerad validates the learned rules on a separate held-out validation set and removes rules that cause false alarms. however, removing rules with possible high coverage can lead to missed detections. we propose to retain these rules and associate weights to them. we present three weighting schemes and our empirical results indicate that, for lerad, rule weighting can detect more attacks than pruning with minimal computational overhead.
enhancing semi-supervised clustering: a feature projection perspective. semi-supervised clustering employs limited supervision in the form of labeled instances or pairwise instance constraints to aid unsupervised clustering and often significantly improves the clustering performance. despite the vast amount of expert knowledge spent on this problem, most existing work is not designed for handling high-dimensional sparse data. this paper thus fills this crucial void by developing a semi-supervised clustering method based on spherical k-means via feature projection (screen). specifically, we formulate the problem of constraint-guided feature projection, which can be nicely integrated with semi-supervised clustering algorithms and has the ability to effectively reduce data dimension. indeed, our experimental results on several real-world data sets show that the screen method can effectively deal with high-dimensional data and provides an appealing clustering performance.
efficient ticket routing by resolution sequence mining. it problem management calls for quick identification of resolvers to reported problems. the efficiency of this process highly depends on ticket routing---transferring problem ticket among various expert groups in search of the right resolver to the ticket. to achieve efficient ticket routing, wise decision needs to be made at each step of ticket transfer to determine which expert group is likely to be, or to lead to the resolver. in this paper, we address the possibility of improving ticket routing efficiency by mining ticket resolution sequences alone, without accessing ticket content. to demonstrate this possibility, a markov model is developed to statistically capture the right decisions that have been made toward problem resolution, where the order of the markov model is carefully chosen according to the conditional entropy obtained from ticket data. we also design a search algorithm, called variable-order multiple active state search(vms), that generates ticket transfer recommendations based on our model. the proposed framework is evaluated on a large set of real-world problem tickets. the results demonstrate that vms significantly improves human decisions: problem resolvers can often be identified with fewer ticket transfers.
the minimum consistent subset cover problem and its applications in data mining. in this paper, we introduce and study the minimum consistent subset cover (mcsc) problem. given a finite ground set x and a constraint t, find the minimum number of consistent subsets that cover x, where a subset of x is consistent if it satisfies t. the mcsc problem generalizes the traditional set covering problem and has minimum clique partition, a dual problem of graph coloring, as an instance. many practical data mining problems in the areas of rule learning, clustering, and frequent pattern mining can be formulated as mcsc instances. in particular, we discuss the minimum rule set problem that minimizes model complexity of decision rules as well as some converse k-clustering problems that minimize the number of clusters satisfying certain distance constraints. we also show how the mcsc problem can find applications in frequent pattern summarization. for any of these mcsc formulations, our proposed novel graph-based generic algorithm cag can be directly applicable. cag starts by constructing a maximal optimal partial solution, then performs an example-driven specific-to-general search on a dynamically maintained bipartite assignment graph to simultaneously learn a set of consistent subsets with small cardinality covering the ground set. our experiments on benchmark datasets show that cag achieves good results compared to existing popular heuristics.
scaling up text classification for large file systems. we combine the speed and scalability of information retrieval with the generally superior classification accuracy offered by machine learning, yielding a two-phase text classifier that can scale to very large document corpora. we investigate the effect of different methods of formulating the query from the training set, as well as varying the query size. in empirical tests on the reuters rcv1 corpus of 806,000 documents, we find runtime was easily reduced by a factor of 27x, with a somewhat surprising gain in f-measure compared with traditional text classification.
exploiting duality in summarization with deterministic guarantees. summarization is an important task in data mining. a major challenge over the past years has been the efficient construction of fixed-space synopses that provide a deterministic quality guarantee, often expressed in terms of a maximum-error metric. histograms and several hierarchical techniques have been proposed for this problem. however, their time and/or space complexities remain impractically high and depend not only on the data set size n, but also on the space budget b. these handicaps stem from a requirement to tabulate all allocations of synopsis space to different regions of the data. in this paper we develop an alternative methodology that dispels these deficiencies, thanks to a fruitful application of the solution to the dual problem: given a maximum allowed error, determine the minimum-space synopsis that achieves it. compared to the state-of-the-art, our histogram construction algorithm reduces time complexity by (at least) a blog2n over logε* factor and our hierarchical synopsis algorithm reduces the complexity by (at least) a factor of log2b over logε* + logn in time and b(1-log b over log n) in space, where ε* is the optimal error. these complexity advantages offer both a space-efficiency and a scalability that previous approaches lacked. we verify the benefits of our approach in practice by experimentation.
scan: a structural clustering algorithm for networks. network clustering (or graph partitioning) is an important task for the discovery of underlying structures in networks. many algorithms find clusters by maximizing the number of intra-cluster edges. while such algorithms find useful and interesting structures, they tend to fail to identify and isolate two kinds of vertices that play special roles - vertices that bridge clusters (hubs) and vertices that are marginally connected to clusters (outliers). identifying hubs is useful for applications such as viral marketing and epidemiology since hubs are responsible for spreading ideas or disease. in contrast, outliers have little or no influence, and may be isolated as noise in the data. in this paper, we proposed a novel algorithm called scan (structural clustering algorithm for networks), which detects clusters, hubs and outliers in networks. it clusters vertices based on a structural similarity measure. the algorithm is fast and efficient, visiting each vertex only once. an empirical evaluation of the method using both synthetic and real datasets demonstrates superior performance over other methods such as the modularity-based algorithms.
from frequent itemsets to semantically meaningful visual patterns. data mining techniques that are successful in transaction and text data may not be simply applied to image data that contain high-dimensional features and have spatial structures. it is not a trivial task to discover meaningful visual patterns in image databases, because the content variations and spatial dependency in the visual data greatly challenge most existing methods. this paper presents a novel approach to coping with these difficulties for mining meaningful visual patterns. specifically, the novelty of this work lies in the following new contributions: (1) a principled solution to the discovery of meaningful itemsets based on frequent itemset mining; (2) a self-supervised clustering scheme of the high-dimensional visual features by feeding back discovered patterns to tune the similarity measure through metric learning; and (3) a pattern summarization method that deals with the measurement noises brought by the image data. the experimental results in the real images show that our method can discover semantically meaningful patterns efficiently and effectively.
partial example acquisition in cost-sensitive learning. it is often expensive to acquire data in real-world data mining applications. most previous data mining and machine learning research, however, assumes that a fixed set of training examples is given. in this paper, we propose an online cost-sensitive framework that allows a learner to dynamically acquire examples as it learns, and to decide the ideal number of examples needed to minimize the total cost. we also propose a new strategy for partial example acquisition (pas), in which the learner can acquire examples with a subset of attribute values to reduce the data acquisition cost. experiments on uci datasets show that the new pas strategy is an effective method in reducing the total cost for data acquisition.
a framework for community identification in dynamic social networks. we propose frameworks and algorithms for identifying communities in social networks that change over time. communities are intuitively characterized as "unusually densely knit" subsets of a social network. this notion becomes more problematic if the social interactions change over time. aggregating social networks over time can radically misrepresent the existing and changing community structure. instead, we propose an optimization-based approach for modeling dynamic community structure. we prove that finding the most explanatory community structure is np-hard and apx-hard, and propose algorithms based on dynamic programming, exhaustive search, maximum matching, and greedy heuristics. we demonstrate empirically that the heuristics trace developments of community structure accurately for several synthetic and real-world examples.
fast direction-aware proximity for graph mining. in this paper we study asymmetric proximity measures on directed graphs, which quantify the relationships between two nodes or two groups of nodes. the measures are useful in several graph mining tasks, including clustering, link prediction and connection subgraph discovery. our proximity measure is based on the conceptof escape probability. this way, we strive to summarize the multiple facets of nodes-proximity, while avoiding some of the pitfalls to which alternative proximity measures are susceptible. a unique feature of the measures is accounting for the underlying directional information. we put a special emphasis on computational efficiency, and develop fast solutions that are applicable in several settings. our experimental study shows the usefulness of our proposed direction-aware proximity method for several applications, and that our algorithms achieve a significant speedup (up to 50,000x) over straight forward implementations.
scalable look-ahead linear regression trees. most decision tree algorithms base their splitting decisions on a piecewise constant model. often these splitting algorithms are extrapolated to trees with non-constant models at the leaf nodes. the motivation behind look-ahead linear regression trees (llrt) is that out of all the methods proposed to date, there has been no scalable approach to exhaustively evaluate all possible models in the leaf nodes in order to obtain an optimal split. using several optimizations, llrt is able to generate and evaluate thousands of linear regression models per second. this allows for a near-exhaustive evaluation of all possible splits in a node, based on the quality of fit of linear regression models in the resulting branches. we decompose the calculation of the residual sum of squares in such a way that a large part of it is pre-computed. the resulting method is highly scalable. we observe it to obtain high predictive accuracy for problems with strong mutual dependencies between attributes. we report on experiments with two simulated and seven real data sets.
machine learning for stock selection. in this paper, we propose a new method called prototype ranking (pr) designed for the stock selection problem. pr takes into account the huge size of real-world stock data and applies a modified competitive learning technique to predict the ranks of stocks. the primary target of pr is to select the top performing stocks among many ordinary stocks. pr is designed to perform the learning and testing in a noisy stocks sample set where the top performing stocks are usually the minority. the performance of pr is evaluated by a trading simulation of the real stock data. each week the stocks with the highest predicted ranks are chosen to construct a portfolio. in the period of 1978-2004, pr's portfolio earns a much higher average return as well as a higher risk-adjusted return than cooper's method, which shows that the pr method leads to a clear profit improvement.
corroborate and learn facts from the web. the web contains lots of interesting factual information about entities, such as celebrities, movies or products. this paper describes a robust bootstrapping approach to corroborate facts and learn more facts simultaneously. this approach starts with retrieving relevant pages from a crawl repository for each entity in the seed set. in each learning cycle, known facts of an entity are corroborated first in a relevant page to find fact mentions. when fact mentions are found, they are taken as examples for learning new facts from the page via html pattern discovery. extracted new facts are added to the known fact set for the next learning cycle. the bootstrapping process continues until no new facts can be learned. this approach is language-independent. it demonstrated good performance in experiment on country facts. results of a large scale experiment will also be shown with initial facts imported from wikipedia.
pictor: an interactive system for importing data from a website. we present a demonstration of an interactive wrapper induction system, called pictor, which is able to minimize labeling cost, yet extract data with high accuracy from a website. our demonstration will introduce two proposed technologies: record-level wrappers and a wrapper-assisted labeling strategy. these approaches allow pictor to exploit previously generated wrappers, in order to predict similar labels in a partially labeled webpage or a completely new webpage. our experiment results show the effectiveness of the pictor system.
generalized component analysis for text with heterogeneous attributes. we present a class of richly structured, undirected hidden variable models suitable for simultaneously modeling text along with other attributes encoded in different modalities. our model generalizes techniques such as principal component analysis to heterogeneous data types. in contrast to other approaches, this framework allows modalities such as words, authors and timestamps to be captured in their natural, probabilistic encodings. a latent space representation for a previously unseen document can be obtained through a fast matrix multiplication using our method. we demonstrate the effectiveness of our framework on the task of author prediction from 13 years of the nips conference proceedings and for a recipient prediction task using a 10-month academic email archive of a researcher. our approach should be more broadly applicable to many real-world applications where one wishes to efficiently make predictions for a large number of potential outputs using dimensionality reduction in a well defined probabilistic framework.
interpretable nonnegative matrix decompositions. a matrix decomposition expresses a matrix as a product of at least two factor matrices. equivalently, it expresses each column of the input matrix as a linear combination of the columns in the first factor matrix. the interpretability of the decompositions is a key issue in many data-analysis tasks. we propose two new matrix-decomposition problems: the nonnegative cx and nonnegative cur problems, that give naturally interpretable factors. they extend the recently-proposed column and column-row based decompositions, and are aimed to be used with nonnegative matrices. our decompositions represent the input matrix as a nonnegative linear combination of a subset of its columns (or columns and rows). we present two algorithms to solve these problems and provide an extensive experimental evaluation where we assess the quality of our algorithms' results as well as the intuitiveness of nonnegative cx and cur decompositions. we show that our algorithms return intuitive answers with smaller reconstruction errors than the previously-proposed methods for column and column-row decompositions.
truth discovery with multiple conflicting information providers on the web. the world-wide web has become the most important information source for most of us. unfortunately, there is no guarantee for the correctness of information on the web. moreover, different web sites often provide conflicting information on a subject, such as different specifications for the same product. in this paper we propose a new problem called veracity, i.e., conformity to truth, which studies how to find true facts from a large amount of conflicting information on many subjects that is provided by various web sites. we design a general framework for the veracity problem, and invent an algorithm called truthfinder, which utilizes the relationships between web sites and their information, i.e., a web site is trustworthy if it provides many pieces of true information, and a piece of information is likely to be true if it is provided by many trustworthy web sites. an iterative method is used to infer the trustworthiness of web sites and the correctness of information from each other. our experiments show that truthfinder successfully finds true facts among conflicting information, and identifies trustworthy web sites better than the popular search engines.
mining templates from search result records of search engines. metasearch engine, comparison-shopping and deep web crawling applications need to extract search result records enwrapped in result pages returned from search engines in response to user queries. the search result records from a given search engine are usually formatted based on a template. precisely identifying this template can greatly help extract and annotate the data units within each record correctly. in this paper, we propose a graph model to represent record template and develop a domain independent statistical method to automatically mine the record template for any search engine using sample search result records. our approach can identify both template tags (html tags) and template texts (non-tag texts), and it also explicitly addresses the mismatches between the tag structures and the data structures of search result records. our experimental results indicate that this approach is very effective.
joint optimization of wrapper generation and template detection. many websites have large collections of pages generated dynamically from an underlying structured source like a database. the data of a category are typically encoded into similar pages by a common script or template. in recent years, some value-added services, such as comparison shopping and vertical search in a specific domain, have motivated the research of extraction technologies with high accuracy. almost all previous works assume that input pages of a wrapper induction system conform to a common template and they can be easily identified in terms of a common schema of url. however, we observed that it is hard to distinguish different templates using dynamic urls today. moreover, since extraction accuracy heavily depends on how consistent input pages are, we argue that it is risky to determine whether pages share a common template solely based on urls. instead, we propose a new approach that utilizes similarity between pages to detect templates. our approach separates pages with notable inner differences and then generates wrappers, respectively. experimental results show that our proposed approach is feasible and effective for improving extraction accuracy.
extracting relevant named entities for automated expense reimbursement. expense reimbursement is a time-consuming and labor-intensive process across organizations. in this paper, we present a prototype expense reimbursement system that dramatically reduces the elapsed time and costs involved, by eliminating paper from the process life cycle. our complete solution involves (1) an electronic submission infrastructure that provides multi- channel image capture, secure transport and centralized storage of paper documents; (2) an unconstrained data mining approach to extracting relevant named entities from un-structured document images; (3) automation of auditing procedures that enables automatic expense validation with minimum human interaction. extracting relevant named entities robustly from document images with unconstrained layouts and diverse formatting is a fundamental technical challenge to image-based data mining, question answering, and other information retrieval tasks. in many applications that require such capability, applying traditional language modeling techniques to the stream of ocr text does not give satisfactory result due to the absence of linguistic context. we present an approach for extracting relevant named entities from document images by combining rich page layout features in the image space with language content in the ocr text using a discriminative conditional random field (crf) framework. we integrate this named entity extraction engine into our expense reimbursement solution and evaluate the system performance on large collections of real-world receipt images provided by ibm world wide reimbursement center.
dimac: a disguised missing data cleaning tool. in some applications such as filling in a customer information form on the web, some missing values may not be explicitly represented as such, but instead appear as potentially valid data values. such missing values are known as disguised missing data, which may impair the quality of data analysis severely. the very limited previous studies on cleaning disguised missing data highly rely on domain background knowledge in specific applications and may not work well for the cases where the disguise values are inliers. recently, we have studied the problem of cleaning disguised missing data systematically, and proposed an effective heuristic approach [2]. in this paper, we present a demonstration of dimac, a disguised missing data cleaning tool which can find the frequently used disguise values in data sets without any domain background knowledge. in this demo, we will show (1) the critical techniques of finding suspicious disguise values; (2) the architecture and user interface of dimac system; (3) an empirical case study on both real and synthetic data sets, which verifies the effectiveness and the efficiency of the techniques; and (4) some challenges arising from real applications and several direction for future work.
mining favorable facets. the importance of dominance and skyline analysis has been well recognized in multi-criteria decision making applications. most previous studies assume a fixed order on the attributes. in practice, different customers may have different preferences on nominal attributes. in this paper, we identify an interesting data mining problem, finding favorable facets, which has not been studied before. given a set of points in a multidimensional space, for a specific target point p we want to discover with respect to which combinations of orders (e.g., customer preferences) on the nominal attributes p is not dominated by any other points. such combinations are called the favorable facets of p. we consider both the effectiveness and the efficiency of the mining. a given point may have many favorable facets. we propose the notion of minimal disqualifying condition (mdc) which is effective in summarizing favorable facets. we develop efficient algorithms for favorable facet mining for different application scenarios. the first method computes favorable facets on the fly. the second method pre-computes all minimal disqualifying conditions so that the favorable facets can be looked up in constant time. an extensive performance study using both synthetic and real data sets is reported to verify their effectiveness and efficiency.
a bayesian mixture model with linear regression mixing proportions. classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. this presents problems for applications where the goal is to learn how complex data distributions evolve. we develop models and bayesian learning algorithms for inferring the temporal trends of the components in a mixture model as a function of time. we show the utility of our models by applying them to the real-life problem of tracking changes in the rates of antibiotic resistance in escherichia coli and staphylococcus aureus. the results show that our methods can derive meaningful temporal antibiotic resistance patterns.
a spectral clustering approach to optimally combining numericalvectors with a modular network. we address the issue of clustering numerical vectors with a network. the problem setting is basically equivalent to constrained clustering by wagstaff and cardie and semi-supervised clustering by basu et al., but our focus is more on the optimal combination of two heterogeneous data sources. an application of this setting is web pages which can be numerically vectorized by their contents, e.g. term frequencies, and which are hyperlinked to each other, showing a network. another typical application is genes whose behavior can be numerically measured and a gene network can be given from another data source.we first define a new graph clustering measure which we call normalized network modularity, by balancing the cluster size of the original modularity. we then propose a new clustering method which integrates the cost of clustering numerical vectors with the cost of maximizing the normalized network modularity into a spectral relaxation problem. our learning algorithm is based on spectral clustering which makes our issue an eigenvalue problem and uses k-means for final cluster assignments. a significant advantage of our method is that we can optimize the weight parameter for balancing the two costs from the given data by choosing the minimum total cost. we evaluated the performance of our proposed method using a variety of datasets including synthetic data as well as real-world data from molecular biology. experimental results showed that our method is effective enough to have good results for clustering by numerical vectors and a network.
xproj: a framework for projected structural clustering of xml documents. xml has become a popular method of data representation both on the web and in databases in recent years. one of the reasons for the popularity of xml has been its ability to encode structural information about data records. however, this structural characteristic of data sets also makes it a challenging problem for a variety of data mining problems. one such problem is that of clustering, in which the structural aspects of the data result in a high implicit dimensionality of the data representation. as a result, it becomes more difficult to cluster the data in a meaningful way. in this paper, we propose an effective clustering algorithm for xml data which uses substructures of the documents in order to gain insights about the important underlying structures. we propose new ways of using multiple sub-structuralinformation in xml documents to evaluate the quality of intermediate cluster solutions, and guide the algorithms to a final solution which reflects the true structural behavior in individual partitions. we test the algorithm on a variety of real and synthetic data sets.
unsupervised feature selection for principal components analysis. principal components analysis (pca) is the predominant linear dimensionality reduction technique, and has been widely applied on datasets in all scientific domains. we consider, both theoretically and empirically, the topic of unsupervised feature selection for pca, by leveraging algorithms for the so-called column subset selection problem (cssp). in words, the cssp seeks the "best" subset of exactly k columns from an m x n data matrix a, and has been extensively studied in the numerical linear algebra community. we present a novel two-stage algorithm for the cssp. from a theoretical perspective, for small to moderate values of k, this algorithm significantly improves upon the best previously-existing results [24, 12] for the cssp. from an empirical perspective, we evaluate this algorithm as an unsupervised feature selection strategy in three application domains of modern statistical data analysis: finance, document-term data, and genetics. we pay particular attention to how this algorithm may be used to select representative or landmark features from an object-feature matrix in an unsupervised manner. in all three application domains, we are able to identify k landmark features, i.e., columns of the data matrix, that capture nearly the same amount of information as does the subspace that is spanned by the top k "eigenfeatures."
hierarchical mixture models: a probabilistic analysis. mixture models form one of the most widely used classes of generative models for describing structured and clustered data. in this paper we develop a new approach for the analysis of hierarchical mixture models. more specifically, using a text clustering problem as a motivation, we describe a natural generative process that creates a hierarchical mixture model for the data. in this process, an adversary starts with an arbitrary base distribution and then builds a topic hierarchy via some evolutionary process, where he controls the parameters of the process. we prove that under our assumptions, given a subset of topics that represent generalizations of one another (such as baseball → sports → base), for any document which was produced via some topic in this hierarchy, we can efficiently determine the most specialized topic in this subset, it still belongs to. the quality of the classification is independent of the total number of topics in the hierarchy and our algorithm does not need to know the total number of topics in advance. our approach also yields an algorithm for clustering and unsupervised topical tree reconstruction. we validate our model by showing that properties predicted by our theoretical results carry over to real data. we then apply our clustering algorithm to two different datasets: (i) "20 newsgroups"[19] and (ii) a snapshot of abstracts of arxiv {2} (15 categories, ~240,000 abstracts). in both cases our algorithm performs extremely well.
factorization meets the neighborhood: a multifaceted collaborative filtering model. recommender systems provide users with personalized suggestions for products or services. these systems often rely on collaborating filtering (cf), where past transactions are analyzed in order to establish connections between users and products. the two more successful approaches to cf are latent factor models, which directly profile both users and products, and neighborhood models, which analyze similarities between products or users. in this work we introduce some innovations to both approaches. the factor and neighborhood models can now be smoothly merged, thereby building a more accurate combined model. further accuracy improvements are achieved by extending the models to exploit both explicit and implicit feedback by the users. the methods are tested on the netflix data. results are better than those previously published on that dataset. in addition, we suggest a new evaluation metric, which highlights the differences among methods, based on their performance at a top-k recommendation task.
efficient and effective explanation of change in hierarchical summaries. dimension attributes in data warehouses are typically hierarchical (e.g., geographic locations in sales data, urls in web traffic logs). olap tools are used to summarize the measure attributes (e.g., total sales) along a dimension hierarchy, and to characterize changes (e.g., trends and anomalies) in a hierarchical summary over time. when thenumber of changes identified is large (e.g., total sales in many stores differed from their expected values), a parsimonious explanation of the most significant changes is desirable. in this paper, we propose a natural model of parsimonious explanation, as a composition of node weights along the root-to-leaf paths in a dimension hierarchy, which permits changes to be aggregated with maximal generalization along the dimension hierarchy. we formalize this model of explaining changes in hierarchical summaries and investigate the problem of identifying optimally parsimonious explanations on arbitrary rooted one dimensional tree hierarchies. we show that such explanations can be computed efficiently in time essentially proportional to the number of leaves and the depth of the hierarchy. further, our method can produce parsimonious explanations from the output of any statistical model that provides predictions and confidence intervals, making it widely applicable. our experiments use real data sets to demonstrate the utility and robustness of our proposed model for explaining significant changes, as well as its superior parsimony compared to alternatives.
predictive discrete latent factor models for large scale dyadic data. we propose a novel statistical method to predict large scale dyadic response variables in the presence of covariate information. our approach simultaneously incorporates the effect of covariates and estimates local structure that is induced by interactions among the dyads through a discrete latent factor model. the discovered latent factors provide a redictive model that is both accurate and interpretable. we illustrate our method by working in a framework of generalized linear models, which include commonly used regression techniques like linear regression, logistic regression and poisson regression as special cases. we also provide scalable generalized em-based algorithms for model fitting using both "hard" and "soft" cluster assignments. we demonstrate the generality and efficacy of our approach through large scale simulation studies and analysis of datasets obtained from certain real-world movie recommendation and internet advertising applications.
a framework for classification and segmentation of massive audio data streams. in recent years, the proliferation of voip data has created a number of applications in which it is desirable to perform quick online classification and recognition of massive voice streams. typically such applications are encountered in real time intelligence and surveillance. in many cases, the data streams can be in compressed format, and the rate of data processing can often run at the rate of gigabits per second. all known techniques for speaker voice analysis require the use of an offline training phase in which the system is trained with known segments of speech. the state-of-the-art method for text-independent speaker recognition is known as gaussian mixture modeling (gmm), and it requires an iterative expectation maximization procedure for training, which cannot be implemented in real time. in this paper, we discuss the details of such an online voice recognition system. for this purpose, we use our micro-clustering algorithms to design concise signatures of the target speakers. one of the surprising and insightful observations from our experiences with such a system is that while it was originally designed only for efficiency, we later discovered that it was also more accurate than the widely used gaussian mixture model (gmm). this was because of the conciseness of the micro-cluster model, which made it less prone to over training. this is evidence of the fact that it is often possible to get the best of both worlds and do better than complex models both from an efficiency and accuracy perspective.
topical query decomposition. we introduce the problem of query decomposition, where we are given a query and a document retrieval system, and we want to produce a small set of queries whose union of resulting documents corresponds approximately to that of the original query. ideally, these queries should represent coherent, conceptually well-separated topics. we provide an abstract formulation of the query decomposition problem, and we tackle it from two different perspectives. we first show how the problem can be instantiated as a specific variant of a set cover problem, for which we provide an efficient greedy algorithm. next, we show how the same problem can be seen as a constrained clustering problem, with a very particular kind of constraint, i.e., clustering with predefined clusters. we develop a two-phase algorithm based on hierarchical agglomerative clustering followed by dynamic programming. our experiments, conducted on a set of actual queries in a web scale search engine, confirm the effectiveness of the proposed solutions.
on string classification in data streams. string data has recently become important because of its use in a number of applications such as computational and molecular biology, protein analysis, and market basket data. in many cases, these strings contain a wide variety of substructures which may have physical significance for that application. for example, such substructures could represent important fragments of a dna string or an interesting portion of a fraudulent transaction. in such a case, it is desirable to determine the identity, location, and extent of that substructure in the data. this is a much more difficult generalization of the classification problem, since the latter problem labels entire strings rather than deal with the more complex task of determining string fragments with a particular kind of behavior. the problem becomes even more complicated when different kinds of substrings show complicated nesting patterns. therefore, we define a somewhat different problem which we refer to as the generalized classification problem. we propose a scalable approach based on hidden markov models for this problem. we show how to implement the generalized string classification procedure for very large data bases and data streams. we present experimental results over a number of large data sets and data streams.
calculating latent demand in the long tail. an analytical framework for using powerlaw theory to estimate market size for niche products and consumer groups.
temporal causal modeling with graphical granger methods. the need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. many of these applications naturally involve temporal data, which raises the challenge of how best to leverage the temporal information for causal modeling. recently graphical modeling with the concept of "granger causality", based on the intuition that a cause helps predict its effects in the future, has gained attention in many domains involving time series data analysis. with the surge of interest in model selection methodologies for regression, such as the lasso, as practical alternatives to solving structural learning of graphical models, the question arises whether and how to combine these two notions into a practically viable approach for temporal causal modeling. in this paper, we examine a host of related algorithms that, loosely speaking, fall under the category of graphical granger methods, and characterize their relative performance from multiple viewpoints. our experiments show, for instance, that the lasso algorithm exhibits consistent gain over the canonical pairwise graphical granger method. we also characterize conditions under which these variants of graphical granger methods perform well in comparison to other benchmark methods. finally, we apply these methods to a real world data set involving key performance indicators of corporations, and present some concrete results.
an event-based framework for characterizing the evolutionary behavior of interaction graphs. interaction graphs are ubiquitous in many fields such as bioinformatics, sociology and physical sciences. there have been many studies in the literature targeted at studying and mining these graphs. however, almost all of them have studied these graphs from a static point of view. the study of the evolution of these graphs over time can provide tremendous insight on the behavior of entities, communities and the flow of information among them. in this work, we present an event-based characterization of critical behavioral patterns for temporally varying interaction graphs. we use nonoverlapping snapshots of interaction graphs and develop a framework for capturing and identifying interesting events from them. we use these events to characterize complex behavioral patterns of individuals and communities over time. we show how semantic information can be incorporated to reason about community-behavior events. we also demonstrate the application of behavioral patterns for the purposes of modeling evolution, link prediction and influence maximization. finally, we present a diffusion model for evolving networks, based on our framework.
extracting semantic relations from query logs. in this paper we study a large query log of more than twenty million queries with the goal of extracting the semantic relations that are implicitly captured in the actions of users submitting queries and clicking answers. previous query log analyses were mostly done with just the queries and not the actions that followed after them. we first propose a novel way to represent queries in a vector space based on a graph derived from the query-click bipartite graph. we then analyze the graph produced by our query log, showing that it is less sparse than previous results suggested, and that almost all the measures of these graphs follow power laws, shedding some light on the searching user behavior as well as on the distribution of topics that people want in the web. the representation we introduce allows to infer interesting semantic relationships between queries. second, we provide an experimental analysis on the quality of these relations, showing that most of them are relevant. finally we sketch an application that detects multitopical urls.
modeling relationships at multiple scales to improve accuracy of large recommender systems. the collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past user-item relationships. in this work, we propose novel algorithms for predicting user ratings of items by integrating complementary models that focus on patterns at different scales. at a local scale, we use a neighborhood-based technique that infers ratings from observed ratings by similar users or of similar items. unlike previous local approaches, our method is based on a formal model that accounts for interactions within the neighborhood, leading to improved estimation quality. at a higher, regional, scale, we use svd-like matrix factorization for recovering the major structural patterns in the user-item rating matrix. unlike previous approaches that require imputations in order to fill in the unknown matrix entries, our new iterative algorithm avoids imputation. because the models involve estimation of millions, or even billions, of parameters, shrinkage of estimated values to account for sampling variability proves crucial to prevent overfitting. both the local and the regional approaches, and in particular their combination through a unifying model, compare favorably with other approaches and deliver substantially better results than the commercial netflix cinematch recommender system on a large publicly available data set.
content-based document routing and index partitioning for scalable similarity-based searches in a large corpus. we present a document routing and index partitioning scheme for scalable similarity-based search of documents in a large corpus. we consider the case when similarity-based search is performed by finding documents that have features in common with the query document. while it is possible to store all the features of all the documents in one index, this suffers from obvious scalability problems. our approach is to partition the feature index into multiple smaller partitions that can be hosted on separate servers, enabling scalable and parallel search execution. when a document is ingested into the repository, a small number of partitions are chosen to store the features of the document. to perform similarity-based search, also, only a small number of partitions are queried. our approach is stateless and incremental. the decision as to which partitions the features of the document should be routed to (for storing at ingestion time, and for similarity based search at query time) is solely based on the features of the document. our approach scales very well. we show that executing similarity-based searches over such a partitioned search space has minimal impact on the precision and recall of search results, even though every search consults less than 3% of the total number of partitions.
support feature machine for classification of abnormal brain activity. in this study, a novel multidimensional time series classification technique, namely support feature machine (sfm), is proposed. sfm is inspired by the optimization model of support vector machine and the nearest neighbor rule to incorporate both spatial and temporal of the multi-dimensional time series data. this paper also describes an application of sfm for detecting abnormal brain activity. epilepsy is a case in point in this study. in epilepsy studies, electroencephalograms (eegs), acquired in multidimensional time series format, have been traditionally used as a gold-standard tool for capturing the electrical changes in the brain. from multi-dimensional eeg time series data, sfm was used to identify seizure pre-cursors and detect seizure susceptibility (pre-seizure) periods. the empirical results showed that sfm achieved over 80% correct classification of per-seizure eeg on average in 10 patients using 5-fold cross validation. the proposed optimization model of sfm is very compact and scalable, and can be implemented as an online algorithm. the outcome of this study suggests that it is possible to construct a computerized algorithm used to detect seizure pre-cursors and warn of impending seizures through eeg classification.
density-based clustering for real-time stream data. existing data-stream clustering algorithms such as clustream arebased on k-means. these clustering algorithms are incompetent tofind clusters of arbitrary shapes and cannot handle outliers. further, they require the knowledge of k and user-specified time window. to address these issues, this paper proposes d-stream, a framework for clustering stream data using adensity-based approach. the algorithm uses an online component which maps each input data record into a grid and an offline component which computes the grid density and clusters the grids based on the density. the algorithm adopts a density decaying technique to capture the dynamic changes of a data stream. exploiting the intricate relationships between the decay factor, data density and cluster structure, our algorithm can efficiently and effectively generate and adjust the clusters in real time. further, a theoretically sound technique is developed to detect and remove sporadic grids mapped to by outliers in order to dramatically improve the space and time efficiency of the system. the technique makes high-speed data stream clustering feasible without degrading the clustering quality. the experimental results show that our algorithm has superior quality and efficiency, can find clusters of arbitrary shapes, and can accurately recognize the evolving behaviors of real-time data streams.
nonlinear adaptive distance metric learning for clustering. a good distance metric is crucial for many data mining tasks. to learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a low-dimensional manifold, where geometric relationships such as pairwise distances are preserved. it can be extended to the nonlinear case by applying the kernel trick, which embeds the data into a feature space by specifying the kernel function that computes the dot products between data points in the feature space. in this paper, we propose a novel unsupervised nonlinear adaptive metric learning algorithm, called naml, which performs clustering and distance metric learning simultaneously. naml firstmaps the data to a high-dimensional space through a kernel function; then applies a linear projection to find a low-dimensional manifold where the separability of the data is maximized; and finally performs clustering in the low-dimensional space. the performance of naml depends on the selection of the kernel function and the projection. we show that the joint kernel learning, dimensionality reduction, and clustering can be formulated as a trace maximization problem, which can be solved via an iterative procedure in the em framework. experimental results demonstrated the efficacy of the proposed algorithm.
cross-language information retrieval using parafac2. a standard approach to cross-language information retrieval (clir) uses latent semantic analysis (lsa) in conjunction with a multilingual parallel aligned corpus. this approach has been shown to be successful in identifying similar documents across languages - or more precisely, retrieving the most similar document in one language to a query in another language. however, the approach has severe drawbacks when applied to a related task, that of clustering documents "language-independently", so that documents about similar topics end up closest to one another in the semantic space regardless of their language. the problem is that documents are generally more similar to other documents in the same language than they are to documents in a different language, but on the same topic. as a result, when using multilingual lsa, documents will in practice cluster by language, not by topic. we propose a novel application of parafac2 (which is a variant of parafac, a multi-way generalization of the singular value decomposition [svd]) to overcome this problem. instead of forming a single multilingual term-by-document matrix which, under lsa, is subjected to svd, we form an irregular three-way array, each slice of which is a separate term-by-document matrix for a single language in the parallel corpus. the goal is to compute an svd for each language such that v (the matrix of right singular vectors) is the same across all languages. effectively, parafac2 imposes the constraint, not present in standard lsa, that the "concepts" in all documents in the parallel corpus are the same regardless of language. intuitively, this constraint makes sense, since the whole purpose of using a parallel corpus is that exactly the same concepts are expressed in the translations. we tested this approach by comparing the performance of parafac2 with standard lsa in solving a particular clir problem. from our results, we conclude that parafac2 offers a very promising alternative to lsa not only for multilingual document clustering, but also for solving other problems in cross-language information retrieval.
evolutionary spectral clustering by incorporating temporal smoothness. evolutionary clustering is an emerging research area essential to important applications such as clustering dynamic web and blog contents and clustering data streams. in evolutionary clustering, a good clustering result should fit the current data well, while simultaneously not deviate too dramatically from the recent history. to fulfill this dual purpose, a measure of temporal smoothness is integrated in the overall measure of clustering quality. in this paper, we propose two frameworks that incorporate temporal smoothness in evolutionary spectral clustering. for both frameworks, we start with intuitions gained from the well-known k-means clustering problem, and then propose and solve corresponding cost functions for the evolutionary spectral clustering problems. our solutions to the evolutionary spectral clustering problems provide more stable and consistent clustering results that are less sensitive to short-term noises while at the same time are adaptive to long-term cluster drifts. furthermore, we demonstrate that our methods provide the optimal solutions to the relaxed versions of the corresponding evolutionary k-means clustering problems. performance experiments over a number of real and synthetic data sets illustrate our evolutionary spectral clustering methods provide more robust clustering results that are not sensitive to noise and can adapt to data drifts.
structural and temporal analysis of the blogosphere through community factorization. the blogosphere has unique structural and temporal properties since blogs are typically used as communication media among human individuals. in this paper, we propose a novel technique that captures the structure and temporal dynamics of blog communities. in our framework, a community is a set of blogs that communicate with each other triggered by some events (such as a news article). the community is represented by its structure and temporal dynamics: a community graph indicates how often one blog communicates with another, and a community intensity indicates the activity level of the community that varies over time. our method, community factorization, extracts such communities from the blogosphere, where the communication among blogs is observed as a set of subgraphs (i.e., threads of discussion). this community extraction is formulated as a factorization problem in the framework of constrained optimization, in which the objective is to best explain the observed interactions in the blogosphere over time. we further provide a scalable algorithm for computing solutions to the constrained optimization problems. extensive experimental studies on both synthetic and real blog data demonstrate that our technique is able to discover meaningful communities that are not detectable by traditional methods.
discovering the hidden structure of house prices with a non-parametric latent manifold model. in many regression problems, the variable to be predicted depends not only on a sample-specific feature vector, but also on an unknown (latent) manifold that must satisfy known constraints. an example is house prices, which depend on the characteristics of the house, and on the desirability of the neighborhood, which is not directly measurable. the proposed method comprises two trainable components. the first one is a parametric model that predicts the "intrinsic" price of the house from its description. the second one is a smooth, non-parametric model of the latent "desirability" manifold. the predicted price of a house is the product of its intrinsic price and desirability. the two components are trained simultaneously using a deterministic form of the em algorithm. the model was trained on a large dataset of houses from los angeles county. it produces better predictions than pure parametric and non-parametric models. it also produces useful estimates of the desirability surface at each location.
stochastic processes and temporal data mining. this article tries to give an answer to a fundamental question intemporal data mining: "under what conditions a temporal rule extracted from up-to-date temporal data keeps its confidence/support for future data". a possible solution is given by using, on the one hand, a temporal logic formalism which allows the definition of the main notions (event, temporal rule, support, confidence) in a formal way and, on the other hand, the stochastic limit theory. under this probabilistic temporal framework, the equivalence between the existence of the support of a temporal rule and the law of large numbers is systematically analyzed.
exploiting underrepresented query aspects for automatic query expansion. users attempt to express their search goals through web search queries. when a search goal has multiple components or aspects, documents that represent all the aspects are likely to be more relevant than those that only represent some aspects. current web search engines often produce result sets whose top ranking documents represent only a subset of the query aspects. by expanding the query using the right keywords, the search engine can find documents that represent more query aspects and performance improves. this paper describes abraq, an approach for automatically finding the right keywords to expand the query. abraq identifies the aspects in the query, identifies which aspects are underrepresented in the result set of the original query, and finally, for any particularly underrepresented aspect, identifies keywords that would enhance that aspect's representation and automatically expands the query using the best one. the paper presents experiments that show abraq significantly increases the precision of hard queries, whereas traditional automatic query expansion techniques have not improved precision. abraq also compared favourably against a range of interactive query expansion techniques that require user involvement including clustering, web-log analysis, relevance feedback, and pseudo relevance feedback.
canonicalization of database records using adaptive similarity measures. it is becoming increasingly common to construct databases from information automatically culled from many heterogeneous sources. for example, a research publication database can be constructed by automatically extracting titles, authors, and conference information from online papers. a common difficulty in consolidating data from multiple sources is that records are referenced in a variety of ways (e.g. abbreviations, aliases, and misspellings). therefore, it can be difficult to construct a single, standard representation to present to the user. we refer to the task of constructing this representation as canonicalization. despite its importance, there is little existing work on canonicalization. in this paper, we explore the use of edit distance measures to construct a canonical representation that is "central" in the sense that it is most similar to each of the disparate records. this approach reduces the impact of noisy records on the canonical representation. furthermore, because the user may prefer different styles of canonicalization, we show how different edit distance costs can result in different forms of canonicalization. for example, reducing the cost of character deletions can result in representations that favor abbreviated forms over expanded forms (e.g. kdd versus conference on knowledge discovery and data mining). we describe how to learn these costs from a small amount of manually annotated data using stochastic hill-climbing. additionally, we investigate feature-based methods to learn ranking preferences over canonicalizations. these approaches can incorporate arbitrary textual evidence to select a canonical record. we evaluate our approach on a real-world publications database and show that our learning method results in a canonicalization solution that is robust to errors and easily customizable to user preferences.
detecting changes in large data sets of payment card data: a case study. an important problem in data mining is detecting changes in large datasets. although there are a variety of change detection algorithms that have been developed, in practice it can be a problem to scale these algorithms to large data sets due to the heterogeneity of the data. in this paper, we describe a case study involving payment card data in which we built and monitored a separate change detection model for each cell in a multi-dimensional data cube. we describe a system that has been in operation for the past two years that builds and monitors over 15,000 separate baseline models and the process that isused for generating and investigating alerts using these baselines.
co-clustering based classification for out-of-domain documents. in many real world applications, labeled data are in short supply. it often happens that obtaining labeled data in a new domain is expensive and time consuming, while there may be plenty of labeled data from a related but different domain. traditional machine learning is not able to cope well with learning across different domains. in this paper, we address this problem for a text-mining task, where the labeled data are under one distribution in one domain known as in-domain data, while the unlabeled data are under a related but different domain known as out-of-domain data. our general goal is to learn from the in-domain and apply the learned knowledge to out-of-domain. we propose a co-clustering based classification (cocc) algorithm to tackle this problem. co-clustering is used as a bridge to propagate the class structure and knowledge from the in-domain to the out-of-domain. we present theoretical and empirical analysis to show that our algorithm is able to produce high quality classification results, even when the distributions between the two data are different. the experimental results show that our algorithm greatly improves the classification performance over the traditional learning algorithms.
text classification, business intelligence, and interactivity: automating c-sat analysis for services industry. text classification has matured as a research discipline over the last decade. independently, business intelligence over structured databases has long been a source of insights for enterprises. in this work, we bring the two together for customer satisfaction(c-sat) analysis in the services industry. we present itacs, a solution combining text classification and business intelligence integrated with a novel interactive text labeling interface. itacs has been deployed in multiple client accounts in contact centers. it can be extended to any services industry setting to analyze unstructured text data and derive operational and business insights. we highlight importance of interactivity in real-life text classification settings. we bring out some unique research challenges about label-sets, measuring accuracy, and interpretability that need serious attention in both academic and industrial research. we recount invaluable experiences and lessons learned as data mining researchers working toward seeing research technology deployed in the services industry.
feature selection methods for text classification. we consider feature selection for text classification both theoretically and empirically. our main result is an unsupervised feature selection strategy for which we give worst-case theoretical guarantees on the generalization power of the resultant classification function f with respect to the classification function f obtained when keeping all the features. to the best of our knowledge, this is the first feature selection method with such guarantees. in addition, the analysis leads to insights as to when and why this feature selection strategy will perform well in practice. we then use the techtc-100, 20-newsgroups, and reuters-rcv2 data sets to evaluate empirically the performance of this and two simpler but related feature selection strategies against two commonly-used strategies. our empirical evaluation shows that the strategy with provable performance guarantees performs well in comparison with other commonly-used feature selection strategies. in addition, it performs better on certain datasets under very aggressive feature selection.
efficient incremental constrained clustering. clustering with constraints is an emerging area of data mining research. however, most work assumes that the constraints are given as one large batch. in this paper we explore the situation where the constraints are incrementally given. in this way the user after seeing a clustering can provide positive and negative feedback via constraints to critique a clustering solution. we consider the problem of efficiently updating a clustering to satisfy the new and old constraints rather than reclustering the entire data set. we show that the problem of incremental clustering under constraints is np-hard in general, but identify several sufficient conditions which lead to efficiently solvable versions. these translate into a set of rules on the types of constraints thatcan be added and constraint set properties that must be maintained. we demonstrate that this approach is more efficient than re-clustering the entire data set and has several other advantages.
a framework for simultaneous co-clustering and learning from complex data. for difficult classification or regression problems, practitioners often segment the data into relatively homogenous groups and then build a model for each group. this two-step procedure usually results in simpler, more interpretable and actionable models without any lossin accuracy. we consider problems such as predicting customer behavior across products, where the independent variables can be naturally partitioned into two groups. a pivoting operation can now result in the dependent variable showing up as entries in a "customer by product" data matrix. we present a model-based co-clustering (meta)-algorithm that interleaves clustering and construction of prediction models to iteratively improve both cluster assignment and fit of the models. this algorithm provably converges to a local minimum of a suitable cost function. the framework not only generalizes co-clustering and collaborative filtering to model-basedco-clustering, but can also be viewed as simultaneous co-segmentation and classification or regression, which is better than independently clustering the data first and then building models. moreover, it applies to a wide range of bi-modal or multimodal data, and can be easily specialized to address classification and regression problems. we demonstrate the effectiveness of our approach on both these problems through experimentation on real and synthetic data.
using predictive analysis to improve invoice-to-cash collection. it is commonly agreed that accounts receivable (ar) can be a source of financial difficulty for firms when they are not efficiently managed and are underperforming. experience across multiple industries shows that effective management of ar and overall financial performance of firms are positively correlated. in this paper we address the problem of reducing outstanding receivables through improvements in the collections strategy. specifically, we demonstrate how supervised learning can be used to build models for predicting the payment outcomes of newly-created invoices, thus enabling customized collection actions tailored for each invoice or customer. our models can predict with high accuracy if an invoice will be paid on time or not and can provide estimates of the magnitude of the delay. we illustrate our techniques in the context of real-world transaction data from multiple firms. finally, simulation results show that our approach can reduce collection time up to a factor of four compared to a baseline that is not model-driven.
development of neuroelectromagnetic ontologies(nemo): a framework for mining brainwave ontologies. event-related potentials (erp) are brain electrophysiological patterns created by averaging electroencephalographic (eeg) data, time-locking to events of interest (e.g., stimulus or response onset). in this paper, we propose a generic framework for mining anddeveloping domain ontologies and apply it to mine brainwave (erp) ontologies. the concepts and relationships in erp ontologies can be mined according to the following steps: pattern decomposition, extraction of summary metrics for concept candidates, hierarchical clustering of patterns for classes and class taxonomies, and clustering-based classification and association rules mining for relationships (axioms) of concepts. we have applied this process to several dense-array (128-channel) erp datasets. results suggest good correspondence between mined concepts and rules, on the one hand, and patterns and rules that were independently formulated by domain experts, on the other. data mining results also suggest ways in which expert-defined rules might be refined to improve ontologyrepresentation and classification results. the next goal of our erp ontology mining framework is to address some long-standing challenges in conducting large-scale comparison and integration of results across erp paradigms and laboratories. in a more general context, this work illustrates the promise of an interdisciplinary research program, which combines data mining, neuroinformatics andontology engineering to address real-world problems.
semi-supervised classification with hybrid generative/discriminative methods. we compare two recently proposed frameworks for combining generative and discriminative probabilistic classifiers and apply them to semi-supervised classification. in both cases we explore the tradeoff between maximizing a discriminative likelihood of labeled data and a generative likelihood of labeled and unlabeled data. while prominent semi-supervised learning methods assume low density regions between classes or are subject to generative modeling assumptions, we conjecture that hybrid generative/discriminative methods allow semi-supervised learning in the presence of strongly overlapping classes and reduce the risk of modeling structure in the unlabeled data that is irrelevant for the specific classification task of interest. we apply both hybrid approaches within naively structured markov random field models and provide a thorough empirical comparison with two well-known semi-supervised learning methods on six text classification tasks. a semi-supervised hybrid generative/discriminative method provides the best accuracy in 75% of the experiments, and the multi-conditional learning hybrid approach achieves the highest overall mean accuracy across all tasks.
relational data pre-processing techniques for improved securities fraud detection. commercial datasets are often large, relational, and dynamic. they contain many records of people, places, things, events and their interactions over time. such datasets are rarely structured appropriately for knowledge discovery, and they often contain variables whose meanings change across different subsets of the data. we describe how these challenges were addressed in a collaborative analysis project undertaken by the university of massachusetts amherst and the national association of securities dealers(nasd). we describe several methods for data pre-processing that we applied to transform a large, dynamic, and relational dataset describing nearly the entirety of the u.s. securities industry, and we show how these methods made the dataset suitable for learning statistical relational models. to better utilize social structure, we first applied known consolidation and link formation techniques to associate individuals with branch office locations. in addition, we developed an innovative technique to infer professional associations by exploiting dynamic employment histories. finally, we applied normalization techniques to create a suitable class label that adjusts for spatial, temporal, and other heterogeneity within the data. we show how these pre-processing techniques combine to provide the necessary foundation for learning high-performing statistical models of fraudulent activity.
finding tribes: identifying close-knit individuals from employment patterns. we present a family of algorithms to uncover tribes-groups of individuals who share unusual sequences of affiliations. while much work inferring community structure describes large-scale trends, we instead search for small groups of tightly linked individuals who behave anomalously with respect to those trends. we apply the algorithms to a large temporal and relational data set consisting of millions of employment records from the national association of securities dealers. the resulting tribes contain individuals at higher risk for fraud, are homogenous with respect to risk scores, and are geographically mobile, all at significant levels compared to random or to other sets of individuals who share affiliations.
time-dependent event hierarchy construction. in this paper, an algorithm called time driven documents-partition (tdd) is proposed to construct an event hierarchy in a text corpus based on a given query. specifically, assume that a query contains only one feature - election. election is directly related to the events such as 2006 us midterm elections campaign, 2004 us presidential election campaign and 2004 taiwan presidential election campaign, where these events may further be divided into several smaller events (e.g. the 2006 us midterm elections campaign can be broken down into events such as campaign for vote, election results and the resignation of donald h. rumsfeld). as such, an event hierarchy is resulted. our proposed algorithm, tdd, tackles the problem by three major steps: (1)identify the features that are related to the query according to both the timestamps and the contents of the documents. the features identified are regarded as bursty features; (2) extract the documents that are highly related to the bursty features based on time; (3) partition the extracted documents to form events and organize them in a hierarchicalstructure. to the best of our knowledge, there is little works targeting for constructing a feature-based event hierarchy for a text corpus. practically, event hierarchies can assist us to efficiently locate our target information in a text corpus easily. again, assume that election is used for a query. without an event hierarchy, it is very difficult to identify what are the major events related to it, when do these events happened, as well as the features and the news articles that are related to each of these events. we have archived two-year news articles to evaluate the feasibility of tdd. the encouraging results indicated that tdd is practically sound and highly effective.
fast logistic regression for text categorization with variable-length n-grams. a common representation used in text categorization is the bag of words model (aka. unigram model). learning with this particular representation involves typically some preprocessing, e.g. stopwords-removal, stemming. this results in one explicit tokenization of the corpus. in this work, we introduce a logistic regression approach where learning involves automatic tokenization. this allows us to weaken the a-priori required knowledge about the corpus and results in a tokenization with variable-length (word or character) n-grams as basic tokens. we accomplish this by solving logistic regression using gradient ascent in the space of all ngrams. we show that this can be done very efficiently using a branch and bound approach which chooses the maximum gradient ascent direction projected onto a single dimension (i.e., candidate feature). although the space is very large, our method allows us to investigate variable-length n-gram learning. we demonstrate the efficiency of our approach compared to state-of-the-art classifiers used for text categorization such as cyclic coordinate descent logistic regression and support vector machines.
constraint-driven clustering. clustering methods can be either data-driven or need-driven. data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at organizing the true structure to meet certain application requirements. thus, need-driven (e.g. constrained) clustering is able to find more useful and actionable clusters in applications such as energy aware sensor networks, privacy preservation, and market segmentation. however, the existing methods of constrained clustering require users to provide the number of clusters, which is often unknown in advance, but has a crucial impact on the clustering result. in this paper, we argue that a more natural way to generate actionable clusters is to let the application-specific constraints decide the number of clusters. for this purpose, we introduce a novel cluster model, constraint-driven clustering (cdc), which finds an a priori unspecified number of compact clusters that satisfy all user-provided constraints. two general types of constraints are considered, i.e. minimum significance constraints and minimum variance constraints, as well as combinations of these two types. we prove the np-hardness of the cdc problem with different constraints. we propose a novel dynamic data structure, the cd-tree, which organizes data points in leaf nodes such that each leaf node approximately satisfies the cdc constraints and minimizes the objective function. based on cd-trees, we develop an efficient algorithm to solve the new clustering problem. our experimental evaluation on synthetic and real datasets demonstrates the quality of the generated clusters and the scalability of the algorithm.
trajectory pattern mining. the increasing pervasiveness of location-acquisition technologies (gps, gsm networks, etc.) is leading to the collection of large spatio-temporal datasets and to the opportunity of discovering usable knowledge about movement behaviour, which fosters novel applications and services. in this paper, we move towards this direction and develop an extension of the sequential pattern mining paradigm that analyzes the trajectories of moving objects. we introduce trajectory patterns as concise descriptions of frequent behaviours, in terms of both space (i.e., the regions of space visited during movements) and time (i.e., the duration of movements). in this setting, we provide a general formal statement of the novel mining problem and then study several different instantiations of different complexity. the various approaches are then empirically evaluated over real data and synthetic benchmarks, comparing their strengths and weaknesses.
the future of image search. there are billions of images on the internet. today, searching for a desired image is largely based on textual data such as filename or associated text on the web page; not much use is made of the image content. there are good reasons for this. the field of content-based image retrieval, which emerged during the 1990s, focused primarily on color and texture cues. these were easier to model than shape, but they turned out to be much less useful than originally hoped. i shall review some of the recent developments in the field of visual object recognition in the computer vision community that offer greater promise. much better image features for characterizing shape, advances in machine learning techniques, and the availability of large amounts of training data lie at the heart of these approaches.
cleaning disguised missing data: a heuristic approach. in some applications such as filling in a customer information form on the web, some missing values may not be explicitly represented as such, but instead appear as potentially valid data values. such missing values are known as disguised missing data, which may impair the quality of data analysis severely, such as causing significant biases and misleading results in hypothesis tests, correlation analysis and regressions. the very limited previous studies on cleaning disguised missing data use outlier mining and distribution anomaly detection. they highly rely on domain background knowledge in specific applications and may not work well for the cases where the disguise values are inliers. to tackle the problem of cleaning disguised missing data, in this paper, we first model the distribution of disguised missing data, and propose the embedded unbiased sample heuristic. then, we develop an effective and efficient method to identify the frequently used disguise values which capture the major body of the disguised missing data. our method does not require any domain background knowledge to find the suspicious disguise values. we report an empirical evaluation using real data sets, which shows that our method is effective - the frequently used disguise values found by our method match the values identified by the domain experts nicely. our method is also efficient and scalable for processing large data sets.
dynamic hybrid clustering of bioinformatics by incorporating text mining and citation analysis. to unravel the concept structure and dynamics of the bioinformatics field, we analyze a set of 7401 publications from the web of science and medline databases, publication years 1981-2004. for delineating this complex, interdisciplinary field, a novel bibliometric retrieval strategy is used. given that the performance of unsupervised clustering and classification of scientific publications is significantly improved by deeply merging textual contents with the structure of the citation graph, we proceed with a hybrid clustering method based on fisher's inverse chi-square. the optimal number of clusters is determined by a compound semiautomatic strategy comprising a combination of distance-based and stability-based methods. we also investigate the relationship between number of latent semantic indexing factors, number of clusters, and clustering performance. the hits and pagerank algorithms are used to determine representative publications in each cluster. next, we develop a methodology for dynamic hybrid clustering of evolving bibliographic data sets. the same clustering methodology is applied to consecutive periods defined by time windows on the set, and in a subsequent phase chains are formed by matching and tracking clusters through time. term networks for the eleven resulting cluster chains present the cognitive structure of the field. finally, we provide a view on how much attention the bioinformatics community has devoted to the different subfields through time.
detecting research topics via the correlation between graphs and texts. in this paper we address the problem of detecting topics in large-scale linked document collections. recently, topic detection has become a very active area of research due to its utility for information navigation, trend analysis, and high-level description of data. we present a unique approach that uses the correlation between the distribution of a term that represents a topic and the link distribution in the citation graph where the nodes are limited to the documents containing the term. this tight coupling between term and graph analysis is distinguished from other approaches such as those that focus on language models. we develop a topic score measure for each term, using the likelihood ratio of binary hypotheses based on a probabilistic description of graph connectivity. our approach is based on the intuition that if a term is relevant to a topic, the documents containing the term have denser connectivity than a random selection of documents. we extend our algorithm to detect a topic represented by a set of terms, using the intuition that if the co-occurrence of terms represents a new topic, the citation pattern should exhibit the synergistic effect. we test our algorithm on two electronic research literature collections,arxiv and citeseer.our evaluation shows that the approach is effective and reveals some novel aspects of topic detection.
extracting shared subspace for multi-label classification. multi-label problems arise in various domains such as multi-topic document categorization and protein function prediction. one natural way to deal with such problems is to construct a binary classifier for each label, resulting in a set of independent binary classification problems. since the multiple labels share the same input space, and the semantics conveyed by different labels are usually correlated, it is essential to exploit the correlation information contained in different labels. in this paper, we consider a general framework for extracting shared structures in multi-label classification. in this framework, a common subspace is assumed to be shared among multiple labels. we show that the optimal solution to the proposed formulation can be obtained by solving a generalized eigenvalue problem, though the problem is non-convex. for high-dimensional problems, direct computation of the solution is expensive, and we develop an efficient algorithm for this case. one appealing feature of the proposed framework is that it includes several well-known algorithms as special cases, thus elucidating their intrinsic relationships. we have conducted extensive experiments on eleven multi-topic web page categorization tasks, and results demonstrate the effectiveness of the proposed formulation in comparison with several representative algorithms.
correlation search in graph databases. correlation mining has gained great success in many application domains for its ability to capture the underlying dependency between objects. however, the research of correlation mining from graph databases is still lacking despite the fact that graph data, especially in various scientific domains, proliferate in recent years. in this paper, we propose a new problem of correlation mining from graph databases, called correlated graph search (cgs). cgs adopts pearson's correlation coefficient as a correlation measure to take into consideration the occurrence distributions of graphs. however, the problem poses significant challenges, since every subgraph of a graph in the database is a candidate but the number of subgraphs is exponential. we derive two necessary conditions which set bounds on the occurrence probability of a candidate in the database. with this result, we design an efficient algorithm that operates on a much smaller projected database and thus we are able to obtain a significantly smaller set of candidates. to further improve the efficiency, we develop three heuristic rules and apply them on the candidate set to further reduce the search space. our extensive experiments demonstrate the effectiveness of our method on candidate reduction. the results also justify the efficiency of our algorithm in mining correlations from large real and synthetic datasets.
challenges in mining social network data: processes, privacy, and paradoxes. the profileration of rich social media, on-line communities, and collectively produced knowledge resources has accelerated the convergence of technological and social networks, producing environments that reflect both the architecture of the underlying information systems and the social structure on their members. in studying the consequences of these developments, we are faced with the opportunity to analyze social network data at unprecedented levels of scale and temporal resolution; this has led to a growing body of research at the intersection of the computing and social sciences. we discuss some of the current challenges in the analysis of large-scale social network data, focusing on two themes in particular: the inference of social processes from data, and the problem of maintaining individual privacy in studies of social networks. while early research on this type of data focused on structural questions, recent work has extended this to consider the social processes that unfold within the networks. particular lines of investigation have focused on processes in on-line social systems related to communication [1, 22], community formation [2, 8, 16, 23], information-seeking and collective problem-solving [20, 21, 18], marketing [12, 19, 24, 28], the spread of news [3, 17], and the dynamics of popularity [29]. there are a number of fundamental issues, however, for which we have relatively little understanding, including the extent to which the outcomes of these types of social processes are predictable from their early stages (see e.g. [29]), the differences between properties of individuals and properties of aggregate populations in these types of data, and the extent to which similar social phenomena in different domains have uniform underlying explanations. the second theme we pursue is concerned with the problem of privacy. while much of the research on large-scale social systems has been carried out on data that is public, some of the richest emerging sources of social interaction data come from settings such as e-mail, instant messaging, or phone communication in which users have strong expectations of privacy. how can such data be made available to researchers while protecting the privacy of the individuals represented in the data? many of the standard approaches here are variations on the principle of anonymization - the names of individuals are replaced with meaningless unique identifiers, so that the network structure is maintained while private information has been suppressed. in recent joint work with lars backstrom and cynthia dwork, we have identified some fundamental limitations on the power of network anonymization to ensure privacy [7]. in particular, we describe a family of attacks such that even from a single anonymized copy of a social network, it is possible for an adversary to learn whether edges exist or not between specific targeted pairs of nodes. the attacks are based on the uniqueness of small random subgraphs embedded in an arbitrary network, using ideas related to those found in arguments from ramsey theory [6, 14]. combined with other recent examples of privacy breaches in data containing rich textual or time-series information [9, 26, 27, 30], these results suggest that anonymization contains pitfalls even in very simple settings. in this way, our approach can be seen as a step toward understanding how techniques of privacy-preserving data mining (see e.g. [4, 5, 10, 11, 13, 15, 25] and the references therein) can inform how we think about the protection of eventhe most skeletal social network data.
practical guide to controlled experiments on the web: listen to your customers not to the hippo. the web provides an unprecedented opportunity to evaluate ideas quickly using controlled experiments, also called randomized experiments (single factor or factorial designs), a/b tests (and their generalizations), split tests, control/treatment tests, and parallel flights. controlled experiments embody the best scientific design for establishing a causal relationship between changes and their influence on user-observable behavior. we provide a practical guide to conducting online experiments, where end-users can help guide the development of features. our experience indicates that significant learning and return-on-investment (roi) are seen when development teams listen to their customers, not to the highest paid person's opinion (hippo). we provide several examples of controlled experiments with surprising results. we review the important ingredients of running controlled experiments, and discuss their limitations (both technical and organizational). we focus on several areas that are critical to experimentation, including statistical power, sample size, and techniques for variance reduction. we describe common architectures for experimentation systems and analyze their advantages and disadvantages. we evaluate randomization and hashing techniques, which we show are not as simple in practice as is often assumed. controlled experiments typically generate large amounts of data, which can be analyzed using data mining techniques to gain deeper understanding of the factors influencing the outcome of interest, leading to new hypotheses and creating a virtuous cycle of improvements. organizations that embrace controlled experiments with clear evaluation criteria can evolve their systems with automated optimizations and real-time analyses. based on our extensive practical experience with multiple systems and organizations, we share key lessons that will help practitioners in running trustworthy controlled experiments.
raising the baseline for high-precision text classifiers. many important application areas of text classifiers demand high precision andit is common to compare prospective solutions to the performance of naive bayes. this baseline is usually easy to improve upon, but in this work we demonstrate that appropriate document representation can make out performing this classifier much more challenging. most importantly, we provide a link between naive bayes and the logarithmic opinion pooling of the mixture-of-experts framework, which dictates a particular type of document length normalization. motivated by document-specific feature selection we propose monotonic constraints on document term weighting, which is shown as an effective method of fine-tuning document representation. the discussion is supported by experiments using three large email corpora corresponding to the problem of spam detection, where high precision is of particular importance.
a fast algorithm for finding frequent episodes in event streams. frequent episode discovery is a popular framework for mining data available as a long sequence of events. an episode is essentially a short ordered sequence of event types and the frequency of an episode is some suitable measure of how often the episode occurs in the data sequence. recently,we proposed a new frequency measure for episodes based on the notion of non-overlapped occurrences of episodes in the event sequence, and showed that, such a definition, in addition to yielding computationally efficient algorithms, has some important theoretical properties in connecting frequent episode discovery with hmm learning. this paper presents some new algorithms for frequent episode discovery under this non-overlapped occurrences-based frequency definition. the algorithms presented here are better (by a factor of n, where n denotes the size of episodes being discovered) in terms of both time and space complexities when compared to existing methods for frequent episode discovery. we show through some simulation experiments, that our algorithms are very efficient. the new algorithms presented here have arguably the least possible orders of spaceand time complexities for the task of frequent episode discovery.
cost-effective outbreak detection in networks. given a water distribution network, where should we place sensors toquickly detect contaminants? or, which blogs should we read to avoid missing important stories?. these seemingly different problems share common structure: outbreak detection can be modeled as selecting nodes (sensor locations, blogs) in a network, in order to detect the spreading of a virus or information asquickly as possible. we present a general methodology for near optimal sensor placement in these and related problems. we demonstrate that many realistic outbreak detection objectives (e.g., detection likelihood, population affected) exhibit the property of "submodularity". we exploit submodularity to develop an efficient algorithm that scales to large problems, achieving near optimal placements, while being 700 times faster than a simple greedy algorithm. we also derive online bounds on the quality of the placements obtained by any algorithm. our algorithms and bounds also handle cases where nodes (sensor locations, blogs) have different costs. we evaluate our approach on several large real-world problems,including a model of a water distribution network from the epa, andreal blog data. the obtained sensor placements are provably near optimal, providing a constant fraction of the optimal solution. we show that the approach scales, achieving speedups and savings in storage of several orders of magnitude. we also show how the approach leads to deeper insights in both applications, answering multicriteria trade-off, cost-sensitivity and generalization questions.
mining statistically important equivalence classes and delta-discriminative emerging patterns. the support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. this computational convenience brings both quality and statistical flaws to the results as observed by many previous studies. in this paper, we introduce a novel algorithm that produces itemsets with ranked statistical merits under sophisticated test statistics such as chi-square, risk ratio, odds ratio, etc. our algorithm is based on the concept of equivalence classes. an equivalence class is a set of frequent itemsets that always occur together in the same set of transactions. therefore, itemsets within an equivalence class all share the same level of statistical significance regardless of the variety of test statistics. as an equivalence class can be uniquely determined and concisely represented by a closed pattern and a set of generators, we just mine closed patterns and generators, taking a simultaneous depth-first search scheme. this parallel approach has not been exploited by any prior work. we evaluate our algorithm on two aspects. in general, we compare to lcm and fpclose which are the best algorithms tailored for mining only closed patterns. in particular, we compare to epminer which is the most recent algorithm for mining a type of relative risk patterns, known as minimal emerging patterns. experimental results show that our algorithm is faster than all of them, sometimes even multiple orders of magnitude faster. these statistically ranked patterns and the efficiency have a high potential for real-life applications, especially in biomedical and financial fields where classical test statistics are of dominant interest.
boostcluster: boosting clustering by pairwise constraints. data clustering is an important task in many disciplines. a large number of studies have attempted to improve clustering by using the side information that is often encoded as pairwise constraints. however, these studies focus on designing special clustering algorithms that can effectively exploit the pairwise constraints. we present a boosting framework for data clustering,termed as boostcluster, that is able to iteratively improve the accuracy of any given clustering algorithm by exploiting the pairwise constraints. the key challenge in designing a boosting framework for data clustering is how to influence an arbitrary clustering algorithm with the side information since clustering algorithms by definition are unsupervised. the proposed framework addresses this problem by dynamically generating new data representations at each iteration that are, on the one hand, adapted to the clustering results at previous iterations by the given algorithm, and on the other hand consistent with the given side information. our empirical study shows that the proposed boosting framework is effective in improving the performance of a number of popular clustering algorithms (k-means, partitional singlelink, spectral clustering), and its performance is comparable to the state-of-the-art algorithms for data clustering with side information.
efficient mining of iterative patterns for software specification discovery. studies have shown that program comprehension takes up to 45% of software development costs. such high costs are caused by the lack-of documented specification and further aggravated by the phenomenon of software evolution. there is a need for automated tools to extract specifications to aid program comprehension. in this paper, a novel technique to efficiently mine common software temporal patterns from traces is proposed. these patterns shed light on program behaviors, and are termed iterative patterns. they capture unique characteristic of software traces, typically not found in arbitrary sequences. specifically, due to loops, interesting iterative patterns can occur multiple times within a trace. furthermore, an occurrence of an iterative pattern in a trace can extend across a sequence of indefinite length. since a program behavior can be manifested in numerous ways, analyzing a single trace will not be sufficient. iterative pattern mining extends sequential pattern and episode minings to discover frequent iterative patterns which occur repetitively both within a program trace and across multiple traces. in this paper, we present cliper (closed iterative pattern miner) to efficiently mine a closed set of iterative patterns. a performance study on several simulated and real datasets shows the efficiency of our mining algorithm and effectiveness of our pruning strategy. our case study on jboss application server confirms the usefulness of mined patterns in discovering interesting software behavioral specification.
a probabilistic framework for relational clustering. relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such as web mining, search marketing, bioinformatics, citation analysis, and epidemiology. in this paper, we propose a probabilistic model for relational clustering, which also provides a principal framework to unify various important clustering tasks including traditional attributes-based clustering, semi-supervised clustering, co-clustering and graph clustering. the proposed model seeks to identify cluster structures for each type of data objects and interaction patterns between different types of objects. under this model, we propose parametric hard and soft relational clustering algorithms under a large number of exponential family distributions. the algorithms are applicable to relational data of various structures and at the same time unifies a number of stat-of-the-art clustering algorithms: co-clustering algorithms, the k-partite graph clustering, bregman k-means, and semi-supervised clustering based on hidden markov random fields.
nestedness and segmented nestedness. consider each row of a 0-1 dataset as the subset of the columns for which the row has an 1. then a dataset is nested, if for all pairs of rows one row is either a superset or subset of the other. the concept of nestedness has its origins in ecology, where approximate versions of it has been used to model the species distribution in different locations. we argue that nestedness and its extensions are interesting properties of datasets, and that they can be applied also to domains other than ecology. we first define natural measures of nestedness and study their properties. we then define the concept of k-nestedness: a dataset is (almost) k-nested if the set of columns can be partitioned to k parts so that each part is (almost) nested. we consider the algorithmic problems of computing how far a dataset is from being k-nested, and for finding a good partition of the columns into k parts. the algorithms are based on spectral partitioning, and scale to moderately large datasets. we apply the methods to real data from ecology and from other applications, and demonstrate the usefulness of the concept.
expertise modeling for matching papers with reviewers. an essential part of an expert-finding task, such as matching reviewers to submitted papers, is the ability to model the expertise of a person based on documents. we evaluate several measures of the association between an author in an existing collection of research papers and a previously unseen document. we compare two language model based approaches with a novel topic model, author-persona-topic (apt). in this model, each author can write under one or more "personas," which are represented as independent distributions over hidden topics. examples of previous papers written by prospective reviewers are gathered from the rexa database, which extracts and disambiguates author mentions from documents gathered from the web. we evaluate the models using a reviewer matching task based on human relevance judgments determining how well the expertise of proposed reviewers matches a submission. we find that the apt topic model outperforms the other models.
multiscale topic tomography. modeling the evolution of topics with time is of great value in automatic summarization and analysis of large document collections. in this work, we propose a new probabilistic graphical model to address this issue. the new model, which we call the multiscale topic tomography model (mttm), employs non-homogeneous poisson processes to model generation of word-counts. the evolution of topics is modeled through a multi-scale analysis using haar wavelets. one of the new features of the model is its modeling the evolution of topics at various time-scales of resolution, allowing the user to zoom in and out of the time-scales. our experiments on science data using the new model uncovers some interesting patterns in topics. the new model is also comparable to lda in predicting unseen data as demonstrated by our perplexity experiments.
mining optimal decision trees from itemset lattices. we present dl8, an exact algorithm for finding a decision tree that optimizes a ranking function under size, depth, accuracy and leaf constraints. because the discovery of optimal trees has high theoretical complexity, until now few efforts have been made to compute such trees for real-world datasets. an exact algorithm is of both scientific and practical interest. from a scientific point of view, it can be used as a gold standard to evaluate the performance of heuristic constraint-based decision tree learners and to gain new insight in traditional decision tree learners. from the application point of view, it can be used to discover trees that cannot be found by heuristic decision tree learners. the key idea behind our algorithm is that there is a relation between constraints on decision trees and constraints on itemsets. we show that optimal decision trees can be extracted from lattices of itemsets in linear time. we give several strategies to efficiently build these lattices. experiments show that under the same constraints, dl8 obtains better results than c4.5, which confirms that exhaustive search does not always imply overfitting. the results also show that dl8 is a useful and interesting tool to learn decision trees under constraints.
domain-constrained semi-supervised mining of tracking models in sensor networks. accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. specifically, the localization problem is to determine the location of a client device accurately given the radio signal strength values received at the client device from multiple beacon sensors or access points. conventional data mining and machine learning methods can be applied to solve this problem. however, all of them require large amounts of labeled training data, which can be quite expensive. in this paper, we propose a probabilistic semi supervised learning approach to reduce the calibration effort and increase the tracking accuracy. our method is based on semi-supervised conditional random fields which can enhance the learned model from a small set of training data with abundant unlabeled data effectively. to make our method more efficient, we exploit a generalized em algorithm coupled with domain constraints. we validate our method through extensive experiments in a real sensor network using crossbow mica2 sensors. the results demonstrate the advantages of methods compared to other state-of-the-art object-tracking algorithms.
applying collaborative filtering techniques to movie search for better ranking and browsing. we propose a new ranking method, which combines recommender systems with information search tools for better search and browsing. our method uses a collaborative filtering algorithm to generate personal item authorities for each user and combines them with item proximities for better ranking. to demonstrate our approach, we build a prototype movie search and browsing engine called mad6 (movies, actors and directors; 6 degrees of separation). we conduct offline and online tests of our ranking algorithm. for offline testing, we use yahoo! search queries that resulted in a click on a yahoo! movies or internet movie database (imdb) movie url. our online test involved 44 yahoo! employees providing subjective assessments of results quality. in both tests, our ranking methods show significantly better recall and quality than imdb search and yahoo! movies current search.
febrl -: an open source data cleaning, deduplication and record linkage system with a graphical user interface. matching records that refer to the same entity across data-bases is becoming an increasingly important part of many data mining projects, as often data from multiple sources needs to be matched in order to enrich data or improve its quality. significant advances in record linkage techniques have been made in recent years. however, many new techniques are either implemented in research proof-of-concept systems only, or they are hidden within expensive 'black box' commercial software. this makes it difficult for both researchers and practitioners to experiment with new record linkage techniques, and to compare existing techniques with new ones. the febrl (freely extensible biomedical record linkage) system aims to fill this gap. it contains many recently developed techniques for data cleaning, deduplication and record linkage, and encapsulates them into a graphical user interface (gui). febrl thus allows even inexperienced users to learn and experiment with both traditional and new record linkage techniques. because febrl is written in python and its source code is available, it is fairly easy to integrate new record linkage techniques into it. therefore, febrl can be seen as a tool that allows researchers to compare various existing record linkage techniques with their own ones, enabling the record linkage research community to conduct their work more efficiently. additionally, febrl is suitable as a training tool for new record linkage users, and it can also be used for practical linkage projects with data sets that contain up to several hundred thousand records.
structured entity identification and document categorization: two tasks with one joint model. traditionally, research in identifying structured entities in documents has proceeded independently of document categorization research. in this paper, we observe that these two tasks have much to gain from each other. apart from direct references to entities in a database, such as names of person entities, documents often also contain words that are correlated with discriminative entity attributes, such age-group and income-level of persons. this happens naturally in many enterprise domains such as crm, banking, etc. then, entity identification, which is typically vulnerable against noise and incompleteness in direct references to entities in documents, can benefit from document categorization with respect to such attributes. in return, entity identification enables documents to be categorized according to different label-sets arising from entity attributes without requiring any supervision. in this paper, we propose a probabilistic generative model for joint entity identification and document categorization. we show how the parameters of the model can be estimated using an em algorithm in an unsupervised fashion. using extensive experiments over real and semi-synthetic data, we demonstrate that the two tasks can benefit immensely from each other when performed jointly using the proposed model.
locality sensitive hash functions based on concomitant rank order statistics. locality sensitive hash functions are invaluable tools for approximate near neighbor problems in high dimensional spaces. in this work, we are focused on lsh schemes where the similarity metric is the cosine measure. the contribution of this work is a new class of locality sensitive hash functions for the cosine similarity measure based on the theory of concomitants, which arises in order statistics. consider n i.i.d sample pairs, {(x1; y1); (x2; y2); : : : ;(xn; yn)} obtained from a bivariate distribution f(x, y). concomitant theory captures the relation between the order statistics of x and y in the form of a rank distribution given by prob(rank(yi)=j-rank(xi)=k). we exploit properties of the rank distribution towards developing a locality sensitive hash family that has excellent collision rate properties for the cosine measure. the computational cost of the basic algorithm is high for high hash lengths. we introduce several approximations based on the properties of concomitant order statistics and discrete transforms that perform almost as well, with significantly reduced computational cost. we demonstrate the practical applicability of our algorithms by using it for finding similar images in an image repository.
an inductive database prototype based on virtual mining views. we present a prototype of an inductive database. our system enables the user to query not only the data stored in the database but also generalizations (e.g. rules or trees) over these data through the use of virtual mining views. the mining views are relational tables that virtually contain the complete output of data mining algorithms executed over a given dataset. the prototype implemented into postgresql currently integrates frequent itemset, association rule and decision tree mining. we illustrate the interactive and iterative capabilities of our system with a description of a complete data mining scenario.
context-aware query suggestion by mining click-through and session data. query suggestion plays an important role in improving the usability of search engines. although some recently proposed methods can make meaningful query suggestions by mining query patterns from search logs, none of them are context-aware - they do not take into account the immediately preceding queries as context in query suggestion. in this paper, we propose a novel context-aware query suggestion approach which is in two steps. in the offine model-learning step, to address data sparseness, queries are summarized into concepts by clustering a click-through bipartite. then, from session data a concept sequence suffix tree is constructed as the query suggestion model. in the online query suggestion step, a user's search context is captured by mapping the query sequence submitted by the user to a sequence of concepts. by looking up the context in the concept sequence sufix tree, our approach suggests queries to the user in a context-aware manner. we test our approach on a large-scale search log of a commercial search engine containing 1:8 billion search queries, 2:6 billion clicks, and 840 million query sessions. the experimental results clearly show that our approach outperforms two baseline methods in both coverage and quality of suggestions.
arnetminer: extraction and mining of academic social networks. this paper addresses several key issues in the arnetminer system, which aims at extracting and mining academic social networks. specifically, the system focuses on: 1) extracting researcher profiles automatically from the web; 2) integrating the publication data into the network from existing digital libraries; 3) modeling the entire academic network; and 4) providing search services for the academic network. so far, 448,470 researcher profiles have been extracted using a unified tagging approach. we integrate publications from online web databases and propose a probabilistic framework to deal with the name ambiguity problem. furthermore, we propose a unified modeling approach to simultaneously model topical aspects of papers, authors, and publication venues. search services such as expertise search and people association search have been provided based on the modeling results. in this paper, we describe the architecture and main features of the system. we also present the empirical evaluation of the proposed methods.
get another label? improving data quality and data mining using multiple, noisy labelers. this paper addresses the repeated acquisition of labels for data items when the labeling is imperfect. we examine the improvement (or lack thereof) in data quality via repeated labeling, and focus especially on the improvement of training labels for supervised induction. with the outsourcing of small tasks becoming easier, for example via rent-a-coder or amazon's mechanical turk, it often is possible to obtain less-than-expert labeling at low cost. with low-cost labeling, preparing the unlabeled part of the data can become considerably more expensive than labeling. we present repeated-labeling strategies of increasing complexity, and show several main results. (i) repeated-labeling can improve label quality and model quality, but not always. (ii) when labels are noisy, repeated labeling can be preferable to single labeling even in the traditional setting where labels are not particularly cheap. (iii) as soon as the cost of processing the unlabeled data is not free, even the simple strategy of labeling everything multiple times can give considerable advantage. (iv) repeatedly labeling a carefully chosen set of points is generally preferable, and we present a robust technique that combines different notions of uncertainty to select data points for which quality should be improved. the bottom line: the results show clearly that when labeling is not perfect, selective acquisition of multiple labels is a strategy that data miners should have in their repertoire; for certain label-quality/cost regimes, the benefit is substantial.
bridging centrality: graph mining from element level to group level. despite the pervasiveness of networks as models for real world systems ranging from the internet, the world wide web to gene regulation and scientific collaborations, only a limited number of metrics capable of characterizing these systems are available. the existing metrics for characterizing networks have broad specificity and lack the selectivity for many applications. the purpose of this paper is to identify and critically evaluate a metric, termed bridging centrality, which is highly selective for identifying bridges in networks. the properties of bridges are unique compared to the other network metrics. for a diverse range of data sets, we found that networks are highly susceptible to disruption but robust to loss structural integrity upon targeted deletion of bridging nodes. a novel graph clustering approach, termed `bridge cut', utilizing bridging edges as module boundary is also proposed. the modules identified by the bridge cut algorithm are more effective than the other graph clustering methods. thus, bridging centrality is a network metric with unique properties that may aid in network analysis from element to group level in various areas including systems biology and national security applications.
anticipating annotations and emerging trends in biomedical literature. the biojournalmonitor is a decision support system for the analysis of trends and topics in the biomedical literature. its main goal is to identify potential diagnostic and therapeutic biomarkers for specific diseases. several data sources are continuously integrated to provide the user with up-to-date information on current research in this field. state-of-the-art text mining technologies are deployed to provide added value on top of the original content, including named entity detection, relation extraction, classification, clustering, ranking, summarization, and visualization. we present two novel technologies that are related to the analysis of temporal dynamics of text archives and associated ontologies. currently, the mesh ontology is used to annotate the scientific articles entering the pubmed database with medical terms. both the maintenance of the ontology as well as the annotation of new articles is performed largely manually. we describe how probabilistic topic models can be used to annotate recent articles with the most likely mesh terms. this provides our users with a competitive advantage because, when searching for mesh terms, articles are found long before they are manually annotated. we further present a study on how to predict the inclusion of new terms in the mesh ontology. the results suggest that early prediction of emerging trends is possible. the trend ranking functions are deployed in our system to enable interactive searches for the hottest new trends relating to a disease.
partial least squares regression for graph mining. attributed graphs are increasingly more common in many application domains such as chemistry, biology and text processing. a central issue in graph mining is how to collect informative subgraph patterns for a given learning task. we propose an iterative mining method based on partial least squares regression (pls). to apply pls to graph data, a sparse version of pls is developed first and then it is combined with a weighted pattern mining algorithm. the mining algorithm is iteratively called with different weight vectors, creating one latent component per one mining call. our method, graph pls, is efficient and easy to implement, because the weight vector is updated with elementary matrix calculations. in experiments, our graph pls algorithm showed competitive prediction accuracies in many chemical datasets and its efficiency was significantly superior to graph boosting (gboost) and the naive method based on frequent graph mining.
a sequential dual method for large scale multi-class linear svms. efficient training of direct multi-class formulations of linear support vector machines is very useful in applications such as text classification with a huge number examples as well as features. this paper presents a fast dual method for this training. the main idea is to sequentially traverse through the training set and optimize the dual variables associated with one example at a time. the speed of training is enhanced further by shrinking and cooling heuristics. experiments indicate that our method is much faster than state of the art solvers such as bundle, cutting plane and exponentiated gradient methods.
semi-supervised approach to rapid and reliable labeling of large data sets. in this paper, we propose a method, where the labeling of the data set is carried out in a semi-supervised manner with user-specified guarantees about the quality of the labeling. in our scheme, we assume that for each class, we have some heuristics available, each of which can identify instances of one particular class. the heuristics are assumed to have reasonable performance but they do not need to cover all instances of the class nor do they need to be perfectly reliable. we further assume that we have an infallible expert, who is willing to manually label a few instances. the aim of the algorithm is to exploit the cluster structure of the problem, the predictions by the imperfect heuristics and the limited perfect labels provided by the expert to classify (label) the instances of the data set with guaranteed precision (specificed by the user) with regards to each class. the specified precision is not always attainable, so the algorithm is allowed to classify some instances as dontknow. the algorithm is evaluated by the number of instances labeled by the expert, the number of dontknow instances (global coverage) and the achieved quality of the labeling. on the kdd cup network intrusion data set containing 500,000 instances, we managed to label 96.6% of the instances while guaranteeing a nominal precision of 90% (with 95% confidence) by having the expert label 630 instances; and by having the expert label 1200 instances, we managed to guarantee 95% nominal precision while labeling 96.4% of the data. we also provide a case study of applying our scheme to label the network traffic collected at a large campus network.
social networks: looking ahead. by now, online social networks have become an indispensable part of both online and offline lives of human beings. a large fraction of time spent online by a user is directly influence by the social networks to which he/she belongs. this calls for a deeper examination of social networks as large-scale dynamic objects that foster efficient person-person interaction. the goal of our panel is to discuss social networks from various research angles. in particular, we plan to focus on the following broad research-related topics: large scale data mining, algorithmic questions, sociological aspects, privacy, web search, etc. we will also discuss the business and societal impacts of social networks. each of these topics has generated a lot of research in recent years and while taking stock of what has been done, we will also be discussing the directions in which these topics are headed, from both science and society points of view. our panel will consist of eminent researchers, who have worked/been working on an eclectic and diverse mix of problems in social networks
identifying domain expertise of developers from source code. we are interested in identifying the domain expertise of developers of a software system. a developer gains expertise on the code base as well as the domain of the software system he/she develops. this information forms a useful input in allocating software implementation tasks to developers. domain concepts represented by the system are discovered by taking into account the linguistic information available in the source code. the vocabulary contained in source code as identifiers such as class, method, variable names and comments are extracted. concepts present in the code base are identified and grouped based on a well known text processing hypothesis - words are similar to the extent to which they share similar words. the developer's association with the source code and the concepts it represents is arrived at using the version repository information. in this line, the analysis first derives documents from source code by discarding all the programming language constructs. kmeans clustering is further used to cluster documents and extract closely related concepts. the key concepts present in the documents authored by the developer determine his/her domain expertise. to validate our approach we apply it on large software systems, two of which are presented in detail in this paper.
identifying authoritative actors in question-answering forums: the case of yahoo! answers. we consider the problem of identifying authoritative users in yahoo! answers. a common approach is to use link analysis techniques in order to provide a ranked list of users based on their degree of authority. a major problem for such an approach is determining how many users should be chosen as authoritative from a ranked list. to address this problem, we propose a method for automatic identification of authoritative actors. in our approach, we propose to model the authority scores of users as a mixture of gamma distributions. the number of components in the mixture is estimated by the bayesian information criterion (bic) while the parameters of each component are estimated using the expectation-maximization (em) algorithm. this method allows us to automatically discriminate between authoritative and non-authoritative users. the suitability of our proposal is demonstrated in an empirical study using datasets from yahoo! answers.
de-duping urls via rewrite rules. a large fraction of the urls on the web contain duplicate (or near-duplicate) content. de-duping urls is an extremely important problem for search engines, since all the principal functions of a search engine, including crawling, indexing, ranking, and presentation, are adversely impacted by the presence of duplicate urls. traditionally, the de-duping problem has been addressed by fetching and examining the content of the url; our approach here is different. given a set of urls partitioned into equivalence classes based on the content (urls in the same equivalence class have similar content), we address the problem of mining this set and learning url rewrite rules that transform all urls of an equivalence class to the same canonical form. these rewrite rules can then be applied to eliminate duplicates among urls that are encountered for the first time during crawling, even without fetching their content. in order to express such transformation rules, we propose a simple framework that is general enough to capture the most common url rewrite patterns occurring on the web; in particular, it encapsulates the dust (different urls with similar text) framework [5]. we provide an efficient algorithm for mining and learning url rewrite rules and show that under mild assumptions, it is complete, i.e., our algorithm learns every url rewrite rule that is correct, for an appropriate notion of correctness. we demonstrate the expressiveness of our framework and the effectiveness of our algorithm by performing a variety of extensive large-scale experiments.
angle-based outlier detection in high-dimensional data. detecting outliers in a large set of data objects is a major data mining task aiming at finding different mechanisms responsible for different groups of objects in a data set. all existing approaches, however, are based on an assessment of distances (sometimes indirectly by assuming certain distributions) in the full-dimensional euclidean data space. in high-dimensional data, these approaches are bound to deteriorate due to the notorious "curse of dimensionality". in this paper, we propose a novel approach named abod (angle-based outlier detection) and some variants assessing the variance in the angles between the difference vectors of a point to the other points. this way, the effects of the "curse of dimensionality" are alleviated compared to purely distance-based approaches. a main advantage of our new approach is that our method does not rely on any parameter selection influencing the quality of the achieved ranking. in a thorough experimental evaluation, we compare abod to the well-established distance-based method lof for various artificial and a real world data set and show abod to perform especially well on high-dimensional data.
constraint programming for itemset mining. the relationship between constraint-based mining and constraint programming is explored by showing how the typical constraints used in pattern mining can be formulated for use in constraint programming environments. the resulting framework is surprisingly flexible and allows us to combine a wide range of mining constraints in different ways. we implement this approach in off-the-shelf constraint programming systems and evaluate it empirically. the results show that the approach is not only very expressive, but also works well on complex benchmark problems.
can complex network metrics predict the behavior of nba teams? the united states national basketball association (nba) is one of the most popular sports league in the world and is well known for moving a millionary betting market that uses the countless statistical data generated after each game to feed the wagers. this leads to the existence of a rich historical database that motivates us to discover implicit knowledge in it. in this paper, we use complex network statistics to analyze the nba database in order to create models to represent the behavior of teams in the nba. results of complex network-based models are compared with box score statistics, such as points, rebounds and assists per game. we show the box score statistics play a significant role for only a small fraction of the players in the league. we then propose new models for predicting a team success based on complex network metrics, such as clustering coefficient and node degree. complex network-based models present good results when compared to box score statistics, which underscore the importance of capturing network relationships in a community such as the nba.
identifying biologically relevant genes via multiple heterogeneous data sources. selection of genes that are differentially expressed and critical to a particular biological process has been a major challenge in post-array analysis. recent development in bioinformatics has made various data sources available such as mrna and mirna expression profiles, biological pathway and gene annotation, etc. efficient and effective integration of multiple data sources helps enrich our knowledge about the involved samples and genes for selecting genes bearing significant biological relevance. in this work, we studied a novel problem of multi-source gene selection: given multiple heterogeneous data sources (or data sets), select genes from expression profiles by integrating information from various data sources. we investigated how to effectively employ information contained in multiple data sources to extract an intrinsic global geometric pattern and use it in covariance analysis for gene selection. we designed and conducted experiments to systematically compare the proposed approach with representative methods in terms of statistical and biological significance, and showed the efficacy and potential of the proposed approach with promising findings.
knowledge discovery of semantic relationships between words using nonparametric bayesian graph model. we developed a model based on nonparametric bayesian modeling for automatic discovery of semantic relationships between words taken from a corpus. it is aimed at discovering semantic knowledge about words in particular domains, which has become increasingly important with the growing use of text mining, information retrieval, and speech recognition. the subject-predicate structure is taken as a syntactic structure with the noun as the subject and the verb as the predicate. this structure is regarded as a graph structure. the generation of this graph can be modeled using the hierarchical dirichlet process and the pitman-yor process. the probabilistic generative model we developed for this graph structure consists of subject-predicate structures extracted from a corpus. evaluation of this model by measuring the performance of graph clustering based on wordnet similarities demonstrated that it outperforms other baseline models.
entity categorization over large document collections. extracting entities (such as people, movies) from documents and identifying the categories (such as painter, writer) they belong to enable structured querying and data analysis over unstructured document collections. in this paper, we focus on the problem of categorizing extracted entities. most prior approaches developed for this task only analyzed the local document context within which entities occur. in this paper, we significantly improve the accuracy of entity categorization by (i) considering an entity's context across multiple documents containing it, and (ii) exploiting existing large lists of related entities (e.g., lists of actors, directors, books). these approaches introduce computational challenges because (a) the context of entities has to be aggregated across several documents and (b) the lists of related entities may be very large. we develop techniques to address these challenges. we present a thorough experimental study on real data sets that demonstrates the increase in accuracy and the scalability of our approaches.
efficient computation of personal aggregate queries on blogs. there is an exploding amount of user-generated content on theweb due to the emergence of "web 2.0" services, such as blogger,myspace, flickr, and del.icio.us. the participation of a large number of users in sharing their opinion on the web has inspired researchers to build an effective "information filter" by aggregating these independent opinions. however, given the diverse groups of users on the web nowadays, the global aggregation of the information may not be of much interest to different groups of users. in this paper, we explore the possibility of computing personalized aggregation over the opinions expressed on the web based on a user's indication of trust over the information sources. the hope is that by employing such "personalized" aggregation, we can make the recommendation more likely to be interesting to the users. we address the challenging scalability issues by proposing an efficient method, that utilizes two core techniques: non-negative matrix factorization and threshold algorithm, to compute personalized aggregations when there are potentially millions of users and millions of sources within a system. we show that, through experiments on real-life dataset, our personalized aggregation approach indeed makes a significant difference in the items that are recommended and it reduces the query computational cost significantly, often more than 75%, while the result of personalized aggregation is kept accurate enough.
the persuasive phase of visualization. research in visualization often revolves around visualizing information. however, visualization is a process that extends over time from initial exploration to hypothesis confirmation, and even to result presentation. it is rare that the final phases of visualization are solely about information. in this paper we present a more biased kind of visualization, in which there is a message or set of assumptions behind the presentation that is of interest to both the presenter and the viewer, and emphasizes points that the presenter wants to convey to the viewer. this kind of persuasive visualization -- presenting data in a way that emphasizes a point or message -- is not only common in visualization, but also often expected by the viewer. persuasive visualization is implicit in the deliberate emphasis on interestingness and also in the deliberate use of graphical elements that are processed preattentively by the human visual system, which automatically groups these elements and guiding attention so that they "stand out". we discuss how these ideas have been implemented in the morpherspective system for automated generation of information graphics.
bypass rates: reducing query abandonment using negative inferences. we introduce a new approach to analyzing click logs by examining both the documents that are clicked and those that are bypassed-documents returned higher in the ordering of the search results but skipped by the user. this approach complements the popular click-through rate analysis, and helps to draw negative inferences in the click logs. we formulate a natural objective that finds sets of results that are unlikely to be collectively bypassed by a typical user. this is closely related to the problem of reducing query abandonment. we analyze a greedy approach to optimizing this objective, and establish theoretical guarantees of its performance. we evaluate our approach on a large set of queries, and demonstrate that it compares favorably to the maximal marginal relevance approach on a number of metrics including mean average precision and mean reciprocal rank.
land cover change detection: a case study. the study of land cover change is an important problem in the earth science domain because of its impacts on local climate, radiation balance, biogeochemistry, hydrology, and the diversity and abundance of terrestrial species. most well-known change detection techniques from statistics, signal processing and control theory are not well-suited for the massive high-dimensional spatio-temporal data sets from earth science due to limitations such as high computational complexity and the inability to take advantage of seasonality and spatio-temporal autocorrelation inherent in earth science data. in our work, we seek to address these challenges with new change detection techniques that are based on data mining approaches. specifically, in this paper we have performed a case study for a new change detection technique for the land cover change detection problem. we study land cover change in the state of california, focusing on the san francisco bay area and perform an extended study on the entire state. we also perform a comparative evaluation on forests in the entire state. these results demonstrate the utility of data mining techniques for the land cover change detection problem.
the cost of privacy: destruction of data-mining utility in anonymized data publishing. re-identification is a major privacy threat to public datasets containing individual records. many privacy protection algorithms rely on generalization and suppression of "quasi-identifier" attributes such as zip code and birthdate. their objective is usually syntactic sanitization: for example, k-anonymity requires that each "quasi-identifier" tuple appear in at least k records, while l-diversity requires that the distribution of sensitive attributes for each quasi-identifier have high entropy. the utility of sanitized data is also measured syntactically, by the number of generalization steps applied or the number of records with the same quasi-identifier. in this paper, we ask whether generalization and suppression of quasi-identifiers offer any benefits over trivial sanitization which simply separates quasi-identifiers from sensitive attributes. previous work showed that k-anonymous databases can be useful for data mining, but k-anonymization does not guarantee any privacy. by contrast, we measure the tradeoff between privacy (how much can the adversary learn from the sanitized records?) and utility, measured as accuracy of data-mining algorithms executed on the same sanitized records. for our experimental evaluation, we use the same datasets from the uci machine learning repository as were used in previous research on generalization and suppression. our results demonstrate that even modest privacy gains require almost complete destruction of the data-mining utility. in most cases, trivial sanitization provides equivalent utility and better privacy than k-anonymity, l-diversity, and similar methods based on generalization and suppression.
structured learning for non-smooth ranking losses. learning to rank from relevance judgment is an active research area. itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major techniques in use. listwise structured learning has been applied recently to optimize important non-decomposable ranking criteria like auc (area under roc curve) and map (mean average precision). we propose new, almost-linear-time algorithms to optimize for two other criteria widely used to evaluate search systems: mrr (mean reciprocal rank) and ndcg (normalized discounted cumulative gain) in the max-margin structured learning framework. we also demonstrate that, for different ranking criteria, one may need to use different feature maps. search applications should not be optimized in favor of a single criterion, because they need to cater to a variety of queries. e.g., mrr is best for navigational queries, while ndcg is best for informational queries. a key contribution of this paper is to fold multiple ranking loss functions into a multi-criteria max-margin optimization. the result is a single, robust ranking model that is close to the best accuracy of learners trained on individual criteria. in fact, experiments over the popular letor and trec data sets show that, contrary to conventional wisdom, a test criterion is often not best served by training with the same individual criterion.
morpheus: interactive exploration of subspace clustering. data mining techniques extract interesting patterns out of large data resources. meaningful visualization and interactive exploration of patterns are crucial for knowledge discovery. visualization techniques exist for traditional clustering in low dimensional spaces. in high dimensional data, clusters typically only exist in subspace projections. this subspace clustering, however, lacks interactive visualization tools. challenges arise from typically large result sets in different subspace projections that hinder comparability, visualization and understandability. in this work, we describe morpheus, a tool that supports the knowledge discovery process through visualization and interactive exploration of subspace clusterings. users may browse an overview of the entire subspace clustering, analyze subspace cluster characteristics in-depth and zoom into object groupings. bracketing of different parameter settings enables users to immediately see the effects of parameters and to provide feedback to further improve the subspace clustering. furthermore, morpheus may serve as a teaching and exploration tool for the data mining community to visually assess different subspace clustering paradigms.
sax: indexing and mining terabyte sized time series. current research in indexing and mining time series data has produced many interesting algorithms and representations. however, the algorithms and the size of data considered have generally not been representative of the increasingly massive datasets encountered in science, engineering, and business domains. in this work, we show how a novel multi-resolution symbolic representation can be used to index datasets which are several orders of magnitude larger than anything else considered in the literature. our approach allows both fast exact search and ultra fast approximate search. we show how to exploit the combination of both types of search as sub-routines in data mining algorithms, allowing for the exact mining of truly massive real world datasets, containing millions of time series.
regularization paths and coordinate descent. in a statistical world faced with an explosion of data, regularization has become an important ingredient. in a wide variety of problems we have many more input features than observations, and the lasso penalty and its hybrids have become increasingly useful for both feature selection and regularization. this talk presents some effective algorithms based on coordinate descent for fitting large scale regularization paths for a variety of problems.
learning from multi-topic web documents for contextual advertisement. contextual advertising on web pages has become very popular recently and it poses its own set of unique text mining challenges. often advertisers wish to either target (or avoid) some specific content on web pages which may appear only in a small part of the page. learning for these targeting tasks is difficult since most training pages are multi-topic and need expensive human labeling at the sub-document level for accurate training. in this paper we investigate ways to learn for sub-document classification when only page level labels are available - these labels only indicate if the relevant content exists in the given page or not. we propose the application of multiple-instance learning to this task to improve the effectiveness of traditional methods. we apply sub-document classification to two different problems in contextual advertising. one is "sensitive content detection" where the advertiser wants to avoid content relating to war, violence, pornography, etc. even if they occur only in a small part of a page. the second problem involves opinion mining from review sites - the advertiser wants to detect and avoid negative opinion about their product when positive, negative and neutral sentiments co-exist on a page. in both these scenarios we present experimental results to show that our proposed system is able to get good block level labeling for free and improve the performance of traditional learning methods.
learning classifiers from only positive and unlabeled data. the input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and the other set consists of negative examples. however, it is often the case that the available training data are an incomplete set of positive examples, and a set of unlabeled examples, some of which are positive and some of which are negative. the problem solved in this paper is how to learn a standard binary classifier given a nontraditional training set of this nature. under the assumption that the labeled examples are selected randomly from the positive examples, we show that a classifier trained on positive and unlabeled examples predicts probabilities that differ by only a constant factor from the true conditional probabilities of being positive. we show how to use this result in two different ways to learn a classifier from a nontraditional training set. we then apply these two new methods to solve a real-world problem: identifying protein records that should be included in an incomplete specialized molecular biology database. our experiments in this domain show that models trained using the new methods perform better than the current state-of-the-art biased svm method for learning from positive and unlabeled examples.
colibri: fast mining of large static and dynamic graphs. low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. additionally, it is desirable to track the low-rank structure as the graph evolves over time, efficiently and within limited storage. real graphs typically have thousands or millions of nodes, but are usually very sparse. however, standard decompositions such as svd do not preserve sparsity. this has led to the development of methods such as cur and cmd, which seek a non-orthogonal basis by sampling the columns and/or rows of the sparse matrix. however, these approaches will typically produce overcomplete bases, which wastes both space and time. in this paper we propose the family of colibri methods to deal with these challenges. our version for static graphs, colibri-s, iteratively finds a non-redundant basis and we prove that it has no loss of accuracy compared to the best competitors (cur and cmd), while achieving significant savings in space and time: on real data, colibri-s requires much less space and is orders of magnitude faster (in proportion to the square of the number of non-redundant columns). additionally, we propose an efficient update algorithm for dynamic, time-evolving graphs, colibri-d. our evaluation on a large, real network traffic dataset shows that colibri-d is over 100 times faster than the best published competitor (cmd).
discrimination-aware data mining. in the context of civil rights law, discrimination refers to unfair or unequal treatment of people based on membership to a category or a minority, without regard to individual merit. rules extracted from databases by data mining techniques, such as classification or association rules, when used for decision tasks such as benefit or credit approval, can be discriminatory in the above sense. in this paper, the notion of discriminatory classification rules is introduced and studied. providing a guarantee of non-discrimination is shown to be a non trivial task. a naive approach, like taking away all discriminatory attributes, is shown to be not enough when other background knowledge is available. our approach leads to a precise formulation of the redlining problem along with a formal result relating discriminatory rules with apparently safe ones by means of background knowledge. an empirical assessment of the results on the german credit dataset is also provided.
knowledge transfer via multiple model local structure mapping. the effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from which test examples are to be drawn. the task can be especially difficult when the training examples are from one or several domains different from the test domain. in this paper, we propose a locally weighted ensemble framework to combine multiple models for transfer learning, where the weights are dynamically assigned according to a model's predictive power on each test example. it can integrate the advantages of various learning algorithms and the labeled information from multiple training domains into one unified classification model, which can then be applied on a different domain. importantly, different from many previously proposed methods, none of the base learning method is required to be specifically designed for transfer learning. we show the optimality of a locally weighted ensemble framework as a general approach to combine multiple models for domain transfer. we then propose an implementation of the local weight assignments by mapping the structures of a model onto the structures of the test domain, and then weighting each model locally according to its consistency with the neighborhood structure around the test example. experimental results on text classification, spam filtering and intrusion detection data sets demonstrate significant improvements in classification accuracy gained by the framework. on a transfer learning task of newsgroup message categorization, the proposed locally weighted ensemble framework achieves 97% accuracy when the best single model predicts correctly only on 73% of the test examples. in summary, the improvement in accuracy is over 10% and up to 30% across different problems.
effective label acquisition for collective classification. information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes. a variety of techniques have been introduced and methods that combine attribute information and neighboring label information have been shown to be effective for collective labeling of the nodes in a network. however, in part because of the correlation between node labels that the techniques exploit, it is easy to find cases in which, once a misclassification is made, incorrect information propagates throughout the network. this problem can be mitigated if the system is allowed to judiciously acquire the labels for a small number of nodes. unfortunately, under relatively general assumptions, determining the optimal set of labels to acquire is intractable. here we propose an acquisition method that learns the cases when a given collective classification algorithm makes mistakes, and suggests acquisitions to correct those mistakes. we empirically show on both real and synthetic datasets that this method significantly outperforms a greedy approximate inference approach, a viral marketing approach, and approaches based on network structural measures such as node degree and network clustering. in addition to significantly improving accuracy with just a small amount of labeled data, our method is tractable on large networks.
effective and efficient itemset pattern summarization: regression-based approaches. in this paper, we propose a set of novel regression-based approaches to effectively and efficiently summarize frequent itemset patterns. specifically, we show that the problem of minimizing the restoration error for a set of itemsets based on a probabilistic model corresponds to a non-linear regression problem. we show that under certain conditions, we can transform the nonlinear regression problem to a linear regression problem. we propose two new methods, k-regression and tree-regression, to partition the entire collection of frequent itemsets in order to minimize the restoration error. the k-regression approach, employing a k-means type clustering method, guarantees that the total restoration error achieves a local minimum. the tree-regression approach employs a decision-tree type of top-down partition process. in addition, we discuss alternatives to estimate the frequency for the collection of itemsets being covered by the k representative itemsets. the experimental evaluation on both real and synthetic datasets demonstrates that our approaches significantly improve the summarization performance in terms of both accuracy (restoration error), and computational cost.
learning methods for lung tumor markerless gating in image-guided radiotherapy. in an idealized gated radiotherapy treatment, radiation is delivered only when the tumor is at the right position. for gated lung cancer radiotherapy, it is difficult to generate accurate gating signals due to the large uncertainties when using external surrogates and the risk of pneumothorax when using implanted fiducial markers. in this paper, we investigate machine learning algorithms for markerless gated radiotherapy with fluoroscopic images. previous approach utilizes template matching to localize the tumor position. here, we investigate two ways to improve the precision of tumor target localization by applying: (1) an ensemble of templates where the representative templates are selected by gaussian mixture clustering, and (2) a support vector machine (svm) classifier with radial basis kernels. template matching only considers images inside the gating window, but images outside the gating window might provide additional information. we take advantage of both states and re-cast the gating problem into a classification problem. thus, we are able to use the svm classifier for gated radiotherapy. to verify the effectiveness of the two proposed techniques, we apply them on five sequences of fluoroscopic images from five lung cancer patients against the gating signal of manually contoured tumors as ground truth. our five-patient case study shows that both ensemble template matching and svm are reasonable tools for image-guided markerless gated radiotherapy with an average of approximately 95% precision in terms of delivered target dose at approximately 35% duty cycle.
a visual-analytic toolkit for dynamic interaction graphs. in this article we describe a visual-analytic tool for the interrogation of evolving interaction network data such as those found in social, bibliometric, www and biological applications. the tool we have developed incorporates common visualization paradigms such as zooming, coarsening and filtering while naturally integrating information extracted by a previously described event-driven framework for characterizing the evolution of such networks. the visual front-end provides features that are specifically useful in the analysis of interaction networks, capturing the dynamic nature of both individual entities as well as interactions among them. the tool provides the user with the option of selecting multiple views, designed to capture different aspects of the evolving graph from the perspective of a node, a community or a subset of nodes of interest. standard visual templates and cues are used to highlight critical changes that have occurred during the evolution of the network. a key challenge we address in this work is that of scalability - handling large graphs both in terms of the efficiency of the back-end, and in terms of the efficiency of the visual layout and rendering. two case studies based on bibliometric and wikipedia data are presented to demonstrate the utility of the toolkit for visual knowledge discovery.
using ghost edges for classification in sparsely labeled networks. we address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. techniques for statistical relational learning have been shown to perform well on network classification tasks by exploiting dependencies between class labels of neighboring nodes. however, relational classifiers can fail when unlabeled nodes have too few labeled neighbors to support learning (during training phase) and/or inference (during testing phase). this situation arises in real-world problems when observed labels are sparse. in this paper, we propose a novel approach to within-network classification that combines aspects of statistical relational learning and semi-supervised learning to improve classification performance in sparse networks. our approach works by adding "ghost edges" to a network, which enable the flow of information from labeled to unlabeled nodes. through experiments on real-world data sets, we demonstrate that our approach performs well across a range of conditions where existing approaches, such as collective classification and semi-supervised learning, fail. on all tasks, our approach improves area under the roc curve (auc) by up to 15 points over existing approaches. furthermore, we demonstrate that our approach runs in time proportional to l • e, where l is the number of labeled nodes and e is the number of edges.
reconstructing chemical reaction networks: data mining meets system identification. we present an approach to reconstructing chemical reaction networks from time series measurements of the concentrations of the molecules involved. our solution strategy combines techniques from numerical sensitivity analysis and probabilistic graphical models. by modeling a chemical reaction system as a markov network (undirected graphical model), we show how systematically probing for sensitivities between molecular species can identify the topology of the network. given the topology, our approach next uses detailed sensitivity profiles to characterize properties of reactions such as reversibility, enzyme-catalysis, and the precise stoichiometries of the reactants and products. we demonstrate applications to reconstructing key biological systems including the yeast cell cycle. in addition to network reconstruction, our algorithm finds applications in model reduction and model comprehension. we argue that our reconstruction algorithm can serve as an important primitive for data mining in systems biology applications.
classification with partial labels. in this paper, we address the problem of learning when some cases are fully labeled while other cases are only partially labeled, in the form of partial labels. partial labels are represented as a set of possible labels for each training example, one of which is the correct label. we introduce a discriminative learning approach that incorporates partial label information into the conventional margin-based learning framework. the partial label learning problem is formulated as a convex quadratic optimization minimizing the l2-norm regularized empirical risk using hinge loss. we also present an efficient algorithm for classification in the presence of partial labels. experiments with different data sets show that partial label information improves the performance of classification when there is traditional fully-labeled data, and also yields reasonable performance in the absence of any fully labeled data.
internet advertising and optimal auction design. this talk describes the optimal (revenue maximizing) auction for sponsored search advertising. we show that a search engine's optimal reserve price is independent of the number of bidders. using simulations, we consider the changes that result from a search engine's choice of reserve price and from changes in the number of participating advertisers.
automatic identification of quasi-experimental designs for discovering causal knowledge. researchers in the social and behavioral sciences routinely rely on quasi-experimental designs to discover knowledge from large data-bases. quasi-experimental designs (qeds) exploit fortuitous circumstances in non-experimental data to identify situations (sometimes called "natural experiments") that provide the equivalent of experimental control and randomization. qeds allow researchers in domains as diverse as sociology, medicine, and marketing to draw reliable inferences about causal dependencies from non-experimental data. unfortunately, identifying and exploiting qeds has remained a painstaking manual activity, requiring researchers to scour available databases and apply substantial knowledge of statistics. however, recent advances in the expressiveness of databases, and increases in their size and complexity, provide the necessary conditions to automatically identify qeds. in this paper, we describe the first system to discover knowledge by applying quasi-experimental designs that were identified automatically. we demonstrate that qeds can be identified in a traditional database schema and that such identification requires only a small number of extensions to that schema, knowledge about quasi-experimental design encoded in first-order logic, and a theorem-proving engine. we describe several key innovations necessary to enable this system, including methods for automatically constructing appropriate experimental units and for creating aggregate variables on those units. we show that applying the resulting designs can identify important causal dependencies in real domains, and we provide examples from academic publishing, movie making and marketing, and peer-production systems. finally, we discuss the integration of qeds with other approaches to causal discovery, including joint modeling and directed experimentation.
genesis of postal address reading, current state and future prospects: thirty years of pattern recognition on duty of postal services. abstract intro: an overview is given of the largest industrial ocr application world wide: postal address reading, how it came into being, how it evolved rapidly to its current state-of-the-art and what are its future prospects. some prominent historical-, system-, methodological-, cultural- and social aspects are illuminated.
succinct summarization of transactional databases: an overlapped hyperrectangle scheme. transactional data are ubiquitous. several methods, including frequent itemsets mining and co-clustering, have been proposed to analyze transactional databases. in this work, we propose a new research problem to succinctly summarize transactional databases. solving this problem requires linking the high level structure of the database to a potentially huge number of frequent itemsets. we formulate this problem as a set covering problem using overlapped hyperrectangles; we then prove that this problem and its several variations are np-hard. we develop an approximation algorithm hyper which can achieve a ln(k) + 1 approximation ratio in polynomial time. we propose a pruning strategy that can significantly speed up the processing of our algorithm. additionally, we propose an efficient algorithm to further summarize the set of hyperrectangles by allowing false positive conditions. a detailed study using both real and synthetic datasets shows the effectiveness and efficiency of our approaches in summarizing transactional databases.
microscopic evolution of social networks. we present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. for the first time at such a large scale, we study individual node arrival and edge creation processes that collectively lead to macroscopic properties of networks. using a methodology based on the maximum-likelihood principle, we investigate a wide variety of network formation strategies, and show that edge locality plays a critical role in evolution of networks. our findings supplement earlier network models based on the inherently non-local preferential attachment. based on our observations, we develop a complete model of network evolution, where nodes arrive at a prespecified rate and select their lifetimes. each node then independently initiates edges according to a "gap" process, selecting a destination for each edge according to a simple triangle-closing model free of any parameters. we show analytically that the combination of the gap distribution with the node lifetime leads to a power law out-degree distribution that accurately reflects the true network in all four cases. finally, we give model parameter settings that allow automatic evolution and generation of realistic synthetic networks of arbitrary scale.
finding non-redundant, statistically significant regions in high dimensional data: a novel approach to projected and subspace clustering. projected and subspace clustering algorithms search for clusters of points in subsets of attributes. projected clustering computes several disjoint clusters, plus outliers, so that each cluster exists in its own subset of attributes. subspace clustering enumerates clusters of points in all subsets of attributes, typically producing many overlapping clusters. one problem of existing approaches is that their objectives are stated in a way that is not independent of the particular algorithm proposed to detect such clusters. a second problem is the definition of cluster density based on user-defined parameters, which makes it hard to assess whether the reported clusters are an artifact of the algorithm or whether they actually stand out in the data in a statistical sense. we propose a novel problem formulation that aims at extracting axis-parallel regions that stand out in the data in a statistical sense. the set of axis-parallel, statistically significant regions that exist in a given data set is typically highly redundant. therefore, we formulate the problem of representing this set through a reduced, non-redundant set of axis-parallel, statistically significant regions as an optimization problem. exhaustive search is not a viable solution due to computational infeasibility, and we propose the approximation algorithm statpc. our comprehensive experimental evaluation shows that statpc significantly outperforms existing projected and subspace clustering algorithms in terms of accuracy.
sail: summation-based incremental learning for information-theoretic clustering. information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. a common practice on this topic is so-called info-k-means, which performs k-means clustering with the kl-divergence as the proximity function. while expert efforts on info-k-means have shown promising results, a remaining challenge is to deal with high-dimensional sparse data. indeed, it is possible that the centroids contain many zero-value features for high-dimensional sparse data. this leads to infinite kl-divergence values, which create a dilemma in assigning objects to the centroids during the iteration process of k-means. to meet this dilemma, in this paper, we propose a summation-based incremental learning (sail) method for info-k-means clustering. specifically, by using an equivalent objective function, sail replaces the computation of the kl-divergence by the computation of the shannon entropy. this can avoid the zero-value dilemma caused by the use of the kl-divergence. our experimental results on various real-world document data sets have shown that, with sail as a booster, the clustering performance of k-means can be significantly improved. also, sail leads to quick convergence and a robust clustering performance on high-dimensional sparse data.
local peculiarity factor and its application in outlier detection. peculiarity oriented mining (pom), aiming to discover peculiarity rules hidden in a dataset, is a new data mining method. in the past few years, many results and applications on pom have been reported. however, there is still a lack of theoretical analysis. in this paper, we prove that the peculiarity factor (pf), one of the most important concepts in pom, can accurately characterize the peculiarity of data with respect to the probability density function of a normal distribution, but is unsuitable for more general distributions. thus, we propose the concept of local peculiarity factor (lpf). it is proved that the lpf has the same ability as the pf for a normal distribution and is the so-called µ-sensitive peculiarity description for general distributions. to demonstrate the effectiveness of the lpf, we apply it to outlier detection problems and give a new outlier detection algorithm called lpf-outlier. experimental results show that lpf-outlier is an effective outlier detection algorithm.
stream prediction using a generative model based on frequent episodes in event sequences. this paper presents a new algorithm for sequence prediction over long categorical event streams. the input to the algorithm is a set of target event types whose occurrences we wish to predict. the algorithm examines windows of events that precede occurrences of the target event types in historical data. the set of significant frequent episodes associated with each target event type is obtained based on formal connections between frequent episodes and hidden markov models (hmms). each significant episode is associated with a specialized hmm, and a mixture of such hmms is estimated for every target event type. the likelihoods of the current window of events, under these mixture models, are used to predict future occurrences of target events in the data. the only user-defined model parameter in the algorithm is the length of the windows of events used during model estimation. we first evaluate the algorithm on synthetic data that was generated by embedding (in varying levels of noise) patterns which are preselected to characterize occurrences of target events. we then present an application of the algorithm for predicting targeted user-behaviors from large volumes of anonymous search session interaction logs from a commercially-deployed web browser tool-bar.
fastanova: an efficient algorithm for genome-wide association study. studying the association between quantitative phenotype (such as height or weight) and single nucleotide polymorphisms (snps) is an important problem in biology. to understand underlying mechanisms of complex phenotypes, it is often necessary to consider joint genetic effects across multiple snps. anova (analysis of variance) test is routinely used in association study. important findings from studying gene-gene (snp-pair) interactions are appearing in the literature. however, the number of snps can be up to millions. evaluating joint effects of snps is a challenging task even for snp-pairs. moreover, with large number of snps correlated, permutation procedure is preferred over simple bonferroni correction for properly controlling family-wise error rate and retaining mapping power, which dramatically increases the computational cost of association study. in this paper, we study the problem of finding snp-pairs that have significant associations with a given quantitative phenotype. we propose an efficient algorithm, fastanova, for performing anova tests on snp-pairs in a batch mode, which also supports large permutation test. we derive an upper bound of snp-pair anova test, which can be expressed as the sum of two terms. the first term is based on single-snp anova test. the second term is based on the snps and independent of any phenotype permutation. furthermore, snp-pairs can be organized into groups, each of which shares a common upper bound. this allows for maximum reuse of intermediate computation, efficient upper bound estimation, and effective snp-pair pruning. consequently, fastanova only needs to perform the anova test on a small number of candidate snp-pairs without the risk of missing any significant ones. extensive experiments demonstrate that fastanova is orders of magnitude faster than the brute-force implementation of anova tests on all snp pairs.
categorizing and mining concept drifting data streams. mining concept drifting data streams is a defining challenge for data mining research. recent years have seen a large body of work on detecting changes and building prediction models from stream data, with a vague understanding on the types of the concept drifting and the impact of different types of concept drifting on the mining algorithms. in this paper, we first categorize concept drifting into two scenarios: loose concept drifting (lcd) and rigorous concept drifting (rcd), and then propose solutions to handle each of them separately. for lcd data streams, because concepts in adjacent data chunks are sufficiently close to each other, we apply kernel mean matching (kmm) method to minimize the discrepancy of the data chunks in the kernel space. such a minimization process will produce weighted instances to build classifier ensemble and handle concept drifting data streams. for rcd data streams, because genuine concepts in adjacent data chunks may randomly and rapidly change, we propose a new optimal weights adjustment (owa) method to determine the optimum weight values for classifiers trained from the most recent (up-to-date) data chunk, such that those classifiers can form an accurate classifier ensemble to predict instances in the yet-to-come data chunk. experiments on synthetic and real-world datasets will show that weighted instance approach is preferable when the concept drifting is mainly caused by the changing of the class prior probability; whereas the weighted classifier approach is preferable when the concept drifting is mainly triggered by the changing of the conditional probability.
asymmetric support vector machines: low false-positive learning under the user tolerance. many practical applications of classification require the classifier to produce a very low false-positive rate. although the support vector machine (svm) has been widely applied to these applications due to its superiority in handling high dimensional data, there are relatively little effort other than setting a threshold or changing the costs of slacks to ensure the low false-positive rate. in this paper, we propose the notion of asymmetric support vectormachine (asvm) that takes into account the false-positives and the user tolerance in its objective. such a new objective formulation allows us to raise the confidence in predicting the positives, and therefore obtain a lower chance of false-positives. we study the effects of the parameters in asvm objective and address some implementation issues related to the sequential minimal optimization (smo) to cope with large-scale data. an extensive simulation is conducted and shows that asvm is able to yield either noticeable improvement in performance or reduction in training time as compared to the previous arts.
quantitative evaluation of approximate frequent pattern mining algorithms. traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. in real-life datasets, this limits the recovery of frequent itemset patterns as they are fragmented due to random noise and other errors in the data. hence, a number of methods have been proposed recently to discover approximate frequent itemsets in the presence of noise. these algorithms use a relaxed definition of support and additional parameters, such as row and column error thresholds to allow some degree of "error" in the discovered patterns. though these algorithms have been shown to be successful in finding the approximate frequent itemsets, a systematic and quantitative approach to evaluate them has been lacking. in this paper, we propose a comprehensive evaluation framework to compare different approximate frequent pattern mining algorithms. the key idea is to select the optimal parameters for each algorithm on a given dataset and use the itemsets generated with these optimal parameters in order to compare different algorithms. we also propose simple variations of some of the existing algorithms by introducing an additional post-processing step. subsequently, we have applied our proposed evaluation framework to a wide variety of synthetic datasets with varying amounts of noise and a real dataset to compare existing and our proposed variations of the approximate pattern mining algorithms. source code and the datasets used in this study are made publicly available.
semi-supervised learning with data calibration for long-term time series forecasting. many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one prediction step to the next step. yet, there is a broad range of applications such as climate impact assessments and urban growth planning that require long term forecasting capabilities for strategic decision making. training an accurate model that produces reliable long term predictions would require an extensive amount of historical data, which are either unavailable or expensive to acquire. for some of these domains, there are alternative ways to generate potential scenarios for the future using computer-driven simulation models, such as global climate and traffic demand models. however, the data generated by these models are currently utilized in a supervised learning setting, where a predictive model trained on past observations is used to estimate the future values. in this paper, we present a semi-supervised learning framework for long-term time series forecasting based on hidden markov model regression. a covariance alignment method is also developed to deal with the issue of inconsistencies between historical and model simulation data. we evaluated our approach on data sets from a variety of domains, including climate modeling. our experimental results demonstrate the efficacy of the approach compared to other supervised learning methods for long-term time series forecasting.
tagmark: reliable estimations of rfid tags for business processes. radio frequency identification (rfid) promises optimization of commodity flows in all industry segments. but due to physical constraints, rfid technology cannot detect all rfid tags from an assembly of items. this poses problems when integrating rfid data with enterprise-backend systems for tasks like inventory management or shelf replenishment. in this paper we propose the tagmark method to accomplish this integration. tagmark targets at a retailer scenario, where it estimates the number of tagged items from samples like the sales history or the tags read by smart shelves. the problem is challenging because most existing estimation methods depend on assumptions that do not hold in typical rfid applications, e.g., static item sets, simple random samples, or the availability of samples with user-defined sizes. tagmark adapts mark-recapture-methods in order to provide guarantees for the accuracy of the estimation and bounds for the sample sizes. it can be implemented as a database extension, allowing seamless integration into existing enterprise backend systems. a study with rfid-equipped goods acknowledges that our approach is effective in realistic scenarios, and database experiments with up to 1,000,000 items confirm that it can be efficiently implemented. finally, we explore a broad range of extreme conditions that might stress tagmark, including a thief who knows the location of unread items.
partitioned logistic regression for spam filtering. naive bayes and logistic regression perform well in different regimes. while the former is a very simple generative model which is efficient to train and performs well empirically in many applications,the latter is a discriminative model which often achieves better accuracy and can be shown to outperform naive bayes asymptotically. in this paper, we propose a novel hybrid model, partitioned logistic regression, which has several advantages over both naive bayes and logistic regression. this model separates the original feature space into several disjoint feature groups. individual models on these groups of features are learned using logistic regression and their predictions are combined using the naive bayes principle to produce a robust final estimation. we show that our model is better both theoretically and empirically. in addition, when applying it in a practical application, email spam filtering, it improves the normalized auc score at 10% false-positive rate by 28.8% and 23.6% compared to naive bayes and logistic regression, when using the exact same training examples.
automatic record linkage using seeded nearest neighbour and support vector machine classification. the task of linking databases is an important step in an increasing number of data mining projects, because linked data can contain information that is not available otherwise, or that would require time-consuming and expensive collection of specific data. the aim of linking is to match and aggregate all records that refer to the same entity. one of the major challenges when linking large databases is the efficient and accurate classification of record pairs into matches and non-matches. while traditionally classification was based on manually-set thresholds or on statistical procedures, many of the more recently developed classification methods are based on supervised learning techniques. they therefore require training data, which is often not available in real world situations or has to be prepared manually, an expensive, cumbersome and time-consuming process. the author has previously presented a novel two-step approach to automatic record pair classification [6, 7]. in the first step of this approach, training examples of high quality are automatically selected from the compared record pairs, and used in the second step to train a support vector machine (svm) classifier. initial experiments showed the feasibility of the approach, achieving results that outperformed k-means clustering. in this paper, two variations of this approach are presented. the first is based on a nearest-neighbour classifier, while the second improves a svm classifier by iteratively adding more examples into the training sets. experimental results show that this two-step approach can achieve better classification results than other unsupervised approaches.
an integrated system for automatic customer satisfaction analysis in the services industry. text classification has matured well as a research discipline over the years. at the same time, business intelligence over databases has long been a source of insights for enterprises. with the growing importance of the services industry, customer relationship management and contact center operations have become very important. specifically, the voice of the customer and customer satisfaction (c-sat) have emerged as invaluable sources of insights about how an enterprise's products and services are percieved by customers. in this demonstration, we present the ibm technology to automate customer satisfaction analysis (itacs) system that combines text classification technology, and a business intelligence solution along with an interactive document labeling interface for automating c-sat analysis. this system has been successfully deployed in client accounts in large contact centers and can be extended to any services industry setting for analyzing unstructured text data. this demonstration will highlight the importance of intervention and interactivity in real-world text classification settings. we will point out unique research challenges in this domain regarding label-sets, measuring accuracy, and interpretability of results and we will discuss solutions and open questions.
multi-class cost-sensitive boosting with p-norm loss functions. we propose a family of novel cost-sensitive boosting methods for multi-class classification by applying the theory of gradient boosting to p-norm based cost functionals. we establish theoretical guarantees including proof of convergence and convergence rates for the proposed methods. our theoretical treatment provides interpretations for some of the existing algorithms in terms of the proposed family, including a generalization of the costing algorithm, dse and gbse-t, and the average cost method. we also experimentally evaluate the performance of our new algorithms against existing methods of cost sensitive boosting, including adacost, csb2, and adaboost.m2 with cost-sensitive weight initialization. we show that our proposed scheme generally achieves superior results in terms of cost minimization and, with the use of higher order p-norm loss in certain cases, consistently outperforms the comparison methods, thus establishing its empirical advantage.
scalable and near real-time burst detection from ecommerce queries. in large scale online systems like search, ecommerce, or social network applications, user queries represent an important dimension of activities that can be used to study the impact on the system, and even the business. in this paper, we describe how to detect, characterize and classify bursts in user queries in a large scale ecommerce system. we build upon the approaches discussed in kdd 2002 "bursty and hierarchical structure in streams" [3] and apply them to a high volume industrial context. we describe how to identify bursts on a near real-time basis, classify them, and apply them to build interesting merchandizing applications.
mining preferences from superior and inferior examples. mining user preferences plays a critical role in many important applications such as customer relationship management (crm), product and service recommendation, and marketing campaigns. in this paper, we identify an interesting and practical problem of mining user preferences: in a multidimensional space where the user preferences on some categorical attributes are unknown, from some superior and inferior examples provided by a user, can we learn about the user's preferences on those categorical attributes? we model the problem systematically and show that mining user preferences from superior and inferior examples is challenging. although the problem has great potential in practice, to the best of our knowledge, it has not been explored systematically before. as the first attempt to tackle the problem, we propose a greedy method and show that our method is practical using real data sets and synthetic data sets.
structured metric learning for high dimensional problems. the success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific notions of similarity for the problem at hand. the distance metric learning problem seeks to optimize a distance function subject to constraints that arise from fully-supervised or semisupervised information. several recent algorithms have been proposed to learn such distance functions in low dimensional settings. one major shortcoming of these methods is their failure to scale to high dimensional problems that are becoming increasingly ubiquitous in modern data mining applications. in this paper, we present metric learning algorithms that scale linearly with dimensionality, permitting efficient optimization, storage, and evaluation of the learned metric. this is achieved through our main technical contribution which provides a framework based on the log-determinant matrix divergence which enables efficient optimization of structured, low-parameter mahalanobis distances. experimentally, we evaluate our methods across a variety of high dimensional domains, including text, statistical software analysis, and collaborative filtering, showing that our methods scale to data sets with tens of thousands or more features. we show that our learned metric can achieve excellent quality with respect to various criteria. for example, in the context of metric learning for nearest neighbor classification, we show that our methods achieve 24% higher accuracy over the baseline distance. additionally, our methods yield very good precision while providing recall measures up to 20% higher than other baseline methods such as latent semantic analysis.
cuts3vm: a fast semi-supervised svm algorithm. semi-supervised support vector machine (s3vm) attempts to learn a decision boundary that traverses through low data density regions by maximizing the margin over labeled and unlabeled examples. traditionally, s3vm is formulated as a non-convex integer programming problem and is thus difficult to solve. in this paper, we propose the cutting plane semi-supervised support vector machine (cuts3vm) algorithm, to solve the s3vm problem. specifically, we construct a nested sequence of successively tighter relaxations of the original s3vm problem, and each optimization problem in this sequence could be efficiently solved using the constrained concave-convex procedure (cccp). moreover, we prove theoretically that the cuts3vm algorithm takes time o(sn) to converge with guaranteed accuracy, where n is the total number of samples in the dataset and s is the average number of non-zero features, i.e. the sparsity. experimental evaluations on several real world datasets show that cuts3vm performs better than existing s3vm methods, both in efficiency and accuracy.
model-based document clustering with a collapsed gibbs sampler. model-based algorithms are emerging as a preferred method for document clustering. as computing resources improve, methods such as gibbs sampling have become more common for parameter estimation in these models. gibbs sampling is well understood for many applications, but has not been extensively studied for use in document clustering. we explore the convergence rate, the possibility of label switching, and chain summarization methodologies for document clustering on a particular model, namely a mixture of multinomials model, and show that fairly simple methods can be employed, while still producing clusterings of superior quality compared to those produced with the em algorithm.
weighted graphs and disconnected components: patterns and a generator. the vast majority of earlier work has focused on graphs which are both connected (typically by ignoring all but the giant connected component), and unweighted. here we study numerous, real, weighted graphs, and report surprising discoveries on the way in which new nodes join and form links in a social network. the motivating questions were the following: how do connected components in a graph form and change over time? what happens after new nodes join a network -- how common are repeated edges? we study numerous diverse, real graphs (citation networks, networks in social media, internet traffic, and others); and make the following contributions: (a) we observe that the non-giant connected components seem to stabilize in size, (b) we observe the weights on the edges follow several power laws with surprising exponents, and (c) we propose an intuitive, generative model for graph growth that obeys observed patterns.
mobile call graphs: beyond power-law and lognormal distributions. we analyze a massive social network, gathered from the records of a large mobile phone operator, with more than a million users and tens of millions of calls. we examine the distributions of the number of phone calls per customer; the total talk minutes per customer; and the distinct number of calling partners per customer. we find that these distributions are skewed, and that they significantly deviate from what would be expected by power-law and lognormal distributions. to analyze our observed distributions (of number of calls, distinct call partners, and total talk time), we propose powertrack , a method which fits a lesser known but more suitable distribution, namely the double pareto lognormal (dpln) distribution, to our data and track its parameters over time. using powertrack , we find that our graph changes over time in a way consistent with a generative process that naturally results in the dpln distributions we observe. furthermore, we show that this generative process lends itself to a natural and appealing social wealth interpretation in the context of social networks such as ours. we discuss the application of those results to our model and to forecasting.
banded structure in binary matrices. a 0--1 matrix has a banded structure if both rows and columns can be permuted so that the non-zero entries exhibit a staircase pattern of overlapping rows. the concept of banded matrices has its origins in numerical analysis, where entries can be viewed as descriptions between the problem variables; the bandedness corresponds to variables that are coupled over short distances. banded data occurs also in other applications, for example in the physical mapping problem of the human genome, in paleontological data, in network data and in the discovery of overlapping communities without cycles. we study in this paper the banded structure of binary matrices, give a formal definition of the concept and discuss its theoretical properties. we consider the algorithmic problems of computing how far a matrix is from being banded, and of finding a good submatrix of the original data that exhibits approximate bandedness. finally, we show by experiments on real data from ecology and other applications the usefulness of the concept. our results reveal that bands exist in real datasets and that the final obtained ordering of rows and columns have natural interpretations.
a software system for buzz-based recommendations. in this paper, we present an outline of a software system for buzz-based recommendations. this system is based on a large source of queries in an ecommerce application. the buzz events are detected based on query bursts linked to external entities like news and inventory information. a semantic neighborhood of the chosen buzz query is selected and appropriate recommendations are made on products that relate to this neighborhood. the system follows the paradigm of limited quantity merchandizing, in the sense that on a per-day basis the system shows recommendations around a single buzz query with the intent of increasing user curiosity and promoting user activity and stickiness. the system demonstrates the deployment of an interesting application based on kdd principles applied to a high volume industrial context.
spotting out emerging artists using geo-aware analysis of p2p query strings. record label companies would like to identify potential artists as early as possible in their careers, before other companies approach the artists with competing contracts. the vast number of candidates makes the process of identifying the ones with high success potential time consuming and laborious. this paper demonstrates how datamining of p2p query strings can be used in order to mechanize most of this detection process. using a unique intercepting system over the gnutella network, we were able to capture an unprecedented amount of geographically identified (geo-aware) queries, allowing us to investigate the diffusion of music related queries in time and space. our solution is based on the observation that emerging artists, especially rappers, have a discernible stronghold of fans in their hometown area, where they are able to perform and market their music. in a file sharing network, this is reflected as a delta function spatial distribution of content queries. using this observation, we devised a detection algorithm for emerging artists, that looks for performers with sharp increase in popularity in a small geographic region though still unnoticable nation wide. the algorithm can suggest a short list of artists with breakthrough potential, from which we showed that about 30% translate the potential to national success.
cut-and-stitch: efficient parallel learning of linear dynamical systems on smps. multi-core processors with ever increasing number of cores per chip are becoming prevalent in modern parallel computing. our goal is to make use of the multi-core as well as multi-processor architectures to speed up data mining algorithms. specifically, we present a parallel algorithm for approximate learning of linear dynamical systems (lds), also known as kalman filters (kf). ldss are widely used in time series analysis such as motion capture modeling, visual tracking etc. we propose cut-and-stitch (cas), a novel method to handle the data dependencies from the chain structure of hidden variables in lds, so as to parallelize the em-based parameter learning algorithm. we implement the algorithm using openmp on both a supercomputer and a quad-core commercial desktop. the experimental results show that parallel algorithms using cut-and-stitch achieve comparable accuracy and almost linear speedups over the serial version. in addition, cut-and-stitch can be generalized to other models with similar linear structures such as hidden markov models (hmm) and switching kalman filters (skf).
relational learning via collective matrix factorization. relational learning is concerned with predicting unknown values of a relation, given a database of entities and observed relations among entities. an example of relational learning is movie rating prediction, where entities could include users, movies, genres, and actors. relations encode users' ratings of movies, movies' genres, and actors' roles in movies. a common prediction technique given one pairwise relation, for example a #users x #movies ratings matrix, is low-rank matrix factorization. in domains with multiple relations, represented as multiple matrices, we may improve predictive accuracy by exploiting information from one relation while predicting another. to this end, we propose a collective matrix factorization model: we simultaneously factor several matrices, sharing parameters among factors when an entity participates in multiple relations. each relation can have a different value type and error distribution; so, we allow nonlinear relationships between the parameters and outputs, using bregman divergences to measure error. we extend standard alternating projection algorithms to our model, and derive an efficient newton update for the projection. furthermore, we propose stochastic optimization methods to deal with large, sparse matrices. our model generalizes several existing matrix factorization methods, and therefore yields new large-scale optimization algorithms for these problems. our model can handle any pairwise relational schema and a wide variety of error models. we demonstrate its efficiency, as well as the benefit of sharing parameters among relations.
detecting privacy leaks using corpus-based association rules. detecting inferences in documents is critical for ensuring privacy when sharing information. in this paper, we propose a refined and practical model of inference detection using a reference corpus. our model is inspired by association rule mining: inferences are based on word co-occurrences. using the model and taking the web as the reference corpus, we can find inferences and measure their strength through web-mining algorithms that leverage search engines such as google or yahoo!. our model also includes the important case of private corpora, to model inference detection in enterprise settings in which there is a large private document repository. we find inferences in private corpora by using analogues of our web-mining algorithms, relying on an index for the corpus rather than a web search engine. we present results from two experiments. the first experiment demonstrates the performance of our techniques in identifying all the keywords that allow for inference of a particular topic (e.g. "hiv") with confidence above a certain threshold. the second experiment uses the public enron e-mail dataset. we postulate a sensitive topic and use the enron corpus and the web together to find inferences for the topic. these experiments demonstrate that our techniques are practical, and that our model of inference based on word co-occurrence is well-suited to efficient inference detection.
volatile correlation computation: a checkpoint view. recent years have witnessed increased interest in computing strongly correlated pairs in very large databases. most previous studies have been focused on static data sets. however, in real-world applications, input data are often dynamic and must continually be updated. with such large and growing data sets, new research efforts are expected to develop an incremental solution for correlation computing. along this line, in this paper, we propose a check-point algorithm that can efficiently incorporate new transactions for correlation computing as they become available. specifically, we set a checkpoint to establish a computation buffer, which can help us determine an upper bound for the correlation. this checkpoint bound can be exploited to identify a list of candidate pairs, which will be maintained and computed for correlations as new transactions are added into the database. however, if the total number of new transactions is beyond the buffer size, a new upper bound is computed by the new checkpoint and a new list of candidate pairs is identified. experimental results on real-world data sets show that check-point can significantly reduce the correlation computing cost in dynamic data sets and has the advantage of compacting the use of memory space.
: a system for online review structurization. in this paper, we present a system called cro (chinese review observer) for online product review structurization. by structurization, we mean identifying, extracting and summarizing information from unstructured review text to a structured table. the core tasks include review collection, product feature and user opinion extraction, and polarity analysis of opinions. existing research in this area is mainly english text oriented. to deal with chinese effectively, we propose several novel approaches for fulfilling the core tasks. then we integrated these approaches and implement the whole procedure of review structurization in the system cro. running results for reviews of real products show its performance is satisfactory.
hypergraph spectral learning for multi-label classification. a hypergraph is a generalization of the traditional graph in which the edges are arbitrary non-empty subsets of the vertex set. it has been applied successfully to capture high-order relations in various domains. in this paper, we propose a hypergraph spectral learning formulation for multi-label classification, where a hypergraph is constructed to exploit the correlation information among different labels. we show that the proposed formulation leads to an eigenvalue problem, which may be computationally expensive especially for large-scale problems. to reduce the computational cost, we propose an approximate formulation, which is shown to be equivalent to a least squares problem under a mild condition. based on the approximate formulation, efficient algorithms for solving least squares problems can be applied to scale the formulation to very large data sets. in addition, existing regularization techniques for least squares can be incorporated into the model for improved generalization performance. we have conducted experiments using large-scale benchmark data sets, and experimental results show that the proposed hypergraph spectral learning formulation is effective in capturing the high-order relations in multi-label problems. results also indicate that the approximate formulation is much more efficient than the original one, while keeping competitive classification performance.
composition attacks and auxiliary information in data privacy. privacy is an increasingly important aspect of data publishing. reasoning about privacy, however, is fraught with pitfalls. one of the most significant is the auxiliary information (also called external knowledge, background knowledge, or side information) that an adversary gleans from other channels such as the web, public records, or domain knowledge. this paper explores how one can reason about privacy in the face of rich, realistic sources of auxiliary information. specifically, we investigate the effectiveness of current anonymization schemes in preserving privacy when multiple organizations independently release anonymized data about overlapping populations. 1. we investigate composition attacks, in which an adversary uses independent anonymized releases to breach privacy. we explain why recently proposed models of limited auxiliary information fail to capture composition attacks. our experiments demonstrate that even a simple instance of a composition attack can breach privacy in practice, for a large class of currently proposed techniques. the class includes k-anonymity and several recent variants. 2. on a more positive note, certain randomization-based notions of privacy (such as differential privacy) provably resist composition attacks and, in fact, the use of arbitrary side information.this resistance enables "stand-alone" design of anonymization schemes, without the need for explicitly keeping track of other releases. we provide a precise formulation of this property, and prove that an important class of relaxations of differential privacy also satisfy the property. this significantly enlarges the class of protocols known to enable modular design.
fast collapsed gibbs sampling for latent dirichlet allocation. in this paper we introduce a novel collapsed gibbs sampling method for the widely used latent dirichlet allocation (lda) model. our new method results in significant speedups on real world text corpora. conventional gibbs sampling schemes for lda require o(k) operations per sample where k is the number of topics in the model. our proposed method draws equivalent samples but requires on average significantly less then k operations per sample. on real-word corpora fastlda can be as much as 8 times faster than the standard collapsed gibbs sampler for lda. no approximations are necessary, and we show that our fast sampling scheme produces exactly the same results as the standard (but slower) sampling scheme. experiments on four real world data sets demonstrate speedups for a wide range of collection sizes. for the pubmed collection of over 8 million documents with a required computation time of 6 cpu months for lda, our speedup of 5.7 can save 5 cpu months of computation.
anonymizing transaction databases for publication. this paper considers the problem of publishing "transaction data" for research purposes. each transaction is an arbitrary set of items chosen from a large universe. detailed transaction data provides an electronic image of one's life. this has two implications. one, transaction data are excellent candidates for data mining research. two, use of transaction data would raise serious concerns over individual privacy. therefore, before transaction data is released for data mining, it must be made anonymous so that data subjects cannot be re-identified. the challenge is that transaction data has no structure and can be extremely high dimensional. traditional anonymization methods lose too much information on such data. to date, there has been no satisfactory privacy notion and solution proposed for anonymizing transaction data. this paper proposes one way to address this issue.
using for condensing navigable tag hierarchies from tag clouds. we present the tagflake system, which supports semantically informed navigation within a tag cloud. tagflake relies on tmine for organizing tags extracted from textual content in hierarchical organizations, suitable for navigation, visualization, classification, and tracking. tmine extracts the most significant tag/terms from text documents and maps them onto a hierarchy in such a way that descendant terms are contextually dependent on their ancestors within the given corpus of documents. this provides tagflake with a mechanism for enabling navigation within the tag space and for classification of the text documents based on the contextual structure captured by the created hierarchy. tagflake is language neutral, since it does not rely on any natural language processing technique and is unsupervised.
customer targeting models using actively-selected web content. we consider the problem of predicting the likelihood that a company will purchase a new product from a seller. the statistical models we have developed at ibm for this purpose rely on historical transaction data coupled with structured firmographic information like the company revenue, number of employees and so on. in this paper, we extend this methodology to include additional text-based features based on analysis of the content on each company's website. empirical results demonstrate that incorporating such web content can significantly improve customer targeting. furthermore, we present methods to actively select only the web content that is likely to improve our models, while reducing the costs of acquisition and processing.
a family of dissimilarity measures between nodes generalizing both the shortest-path and the commute-time distances. this work introduces a new family of link-based dissimilarity measures between nodes of a weighted directed graph. this measure, called the randomized shortest-path (rsp) dissimilarity, depends on a parameter θ and has the interesting property of reducing, on one end, to the standard shortest-path distance when θ is large and, on the other end, to the commute-time (or resistance) distance when θ is small (near zero). intuitively, it corresponds to the expected cost incurred by a random walker in order to reach a destination node from a starting node while maintaining a constant entropy (related to θ) spread in the graph. the parameter θ is therefore biasing gradually the simple random walk on the graph towards the shortest-path policy. by adopting a statistical physics approach and computing a sum over all the possible paths (discrete path integral), it is shown that the rsp dissimilarity from every node to a particular node of interest can be computed efficiently by solving two linear systems of n equations, where n is the number of nodes. on the other hand, the dissimilarity between every couple of nodes is obtained by inverting an n x n matrix. the proposed measure can be used for various graph mining tasks such as computing betweenness centrality, finding dense communities, etc, as shown in the experimental section.
a unified approach for schema matching, coreference and canonicalization. the automatic consolidation of database records from many heterogeneous sources into a single repository requires solving several information integration tasks. although tasks such as coreference, schema matching, and canonicalization are closely related, they are most commonly studied in isolation. systems that do tackle multiple integration problems traditionally solve each independently, allowing errors to propagate from one task to another. in this paper, we describe a discriminatively-trained model that reasons about schema matching, coreference, and canonicalization jointly. we evaluate our model on a real-world data set of people and demonstrate that simultaneously solving these tasks reduces errors over a cascaded or isolated approach. our experiments show that a joint model is able to improve substantially over systems that either solve each task in isolation or with the conventional cascade. we demonstrate nearly a 50% error reduction for coreference and a 40% error reduction for schema matching.
privacy-preserving cox regression for survival analysis. privacy-preserving data mining (ppdm) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. in this paper we propose a privacy-preserving (pp) cox model for survival analysis, and consider a real clinical setting where the data is horizontally distributed among different institutions. the proposed model is based on linearly projecting the data to a lower dimensional space through an optimal mapping obtained by solving a linear programming problem. our approach differs from the commonly used random projection approach since it instead finds a projection that is optimal at preserving the properties of the data that are important for the specific problem at hand. since our proposed approach produces an sparse mapping, it also generates a pp mapping that not only projects the data to a lower dimensional space but it also depends on a smaller subset of the original features (it provides explicit feature selection). real data from several european healthcare institutions are used to test our model for survival prediction of non-small-cell lung cancer patients. these results are also confirmed using publicly available benchmark datasets. our experimental results show that we are able to achieve a near-optimal performance without directly sharing the data across different data sources. this model makes it possible to conduct large-scale multi-centric survival analysis without violating privacy-preserving requirements.
mining multi-faceted overviews of arbitrary topics in a text collection. a common task in many text mining applications is to generate a multi-faceted overview of a topic in a text collection. such an overview not only directly serves as an informative summary of the topic, but also provides a detailed view of navigation to different facets of the topic. existing work has cast this problem as a categorization problem and requires training examples for each facet. this has three limitations: (1) all facets are predefined, which may not fit the need of a particular user. (2) training examples for each facet are often unavailable. (3) such an approach only works for a predefined type of topics. in this paper, we break these limitations and study a more realistic new setup of the problem, in which we would allow a user to flexibly describe each facet with keywords for an arbitrary topic and attempt to mine a multi-faceted overview in an unsupervised way. we attempt a probabilistic approach to solve this problem. empirical experiments on different genres of text data show that our approach can effectively generate a multi-faceted overview for arbitrary topics; the generated overviews are comparable with those generated by supervised methods with training examples. they are also more informative than unstructured flat summaries. the method is quite general, thus can be applied to multiple text mining tasks in different application domains.
mining adaptively frequent closed unlabeled rooted trees in data streams. closed patterns are powerful representatives of frequent patterns, since they eliminate redundant information. we propose a new approach for mining closed unlabeled rooted trees adaptively from data streams that change over time. our approach is based on an efficient representation of trees and a low complexity notion of relaxed closed trees, and leads to an on-line strategy and an adaptive sliding window technique for dealing with changes over time. more precisely, we first present a general methodology to identify closed patterns in a data stream, using galois lattice theory. using this methodology, we then develop three closed tree mining algorithms: an incremental one inctreenat, a sliding-window based one, wintreenat, and finally one that mines closed trees adaptively from data streams, adatreenat. to the best of our knowledge this is the first work on mining frequent closed trees in streaming data varying with time. we give a first experimental evaluation of the proposed algorithms.
pattern-miner: integrated management and mining over data mining models. this demo presents pattern-miner, an integrated environment for pattern management and mining that deals with the whole lifecycle of patterns, from their generation (using data mining techniques) to their storage and querying, putting also emphasis on the comparison between patterns and meta-mining operations over the extracted patterns. pattern comparison (comparing results of the data mining process) and meta-mining are high level pattern operations that can be applied in a variety of applications, from database change management to image comparison and retrieval.
efficient semi-streaming algorithms for local triangle counting in massive graphs. in this paper we study the problem of local triangle counting in large graphs. namely, given a large graph g = (v;e) we want to estimate as accurately as possible the number of triangles incident to every node υ ∈ v in the graph. the problem of computing the global number of triangles in a graph has been considered before, but to our knowledge this is the first paper that addresses the problem of local triangle counting with a focus on the efficiency issues arising in massive graphs. the distribution of the local number of triangles and the related local clustering coefficient can be used in many interesting applications. for example, we show that the measures we compute can help to detect the presence of spamming activity in large-scale web graphs, as well as to provide useful features to assess content quality in social networks. for computing the local number of triangles we propose two approximation algorithms, which are based on the idea of min-wise independent permutations (broder et al. 1998). our algorithms operate in a semi-streaming fashion, using o(jv j) space in main memory and performing o(log jv j) sequential scans over the edges of the graph. the first algorithm we describe in this paper also uses o(jej) space in external memory during computation, while the second algorithm uses only main memory. we present the theoretical analysis as well as experimental results in massive graphs demonstrating the practical efficiency of our approach.
heterogeneous data fusion for alzheimer's disease study. effective diagnosis of alzheimer's disease (ad) is of primary importance in biomedical research. recent studies have demonstrated that neuroimaging parameters are sensitive and consistent measures of ad. in addition, genetic and demographic information have also been successfully used for detecting the onset and progression of ad. the research so far has mainly focused on studying one type of data source only. it is expected that the integration of heterogeneous data (neuroimages, demographic, and genetic measures) will improve the prediction accuracy and enhance knowledge discovery from the data, such as the detection of biomarkers. in this paper, we propose to integrate heterogeneous data for ad prediction based on a kernel method. we further extend the kernel framework for selecting features (biomarkers) from heterogeneous data sources. the proposed method is applied to a collection of mri data from 59 normal healthy controls and 59 ad patients. the mri data are pre-processed using tensor factorization. in this study, we treat the complementary voxel-based data and region of interest (roi) data from mri as two data sources, and attempt to integrate the complementary information by the proposed method. experimental results show that the integration of multiple data sources leads to a considerable improvement in the prediction accuracy. results also show that the proposed algorithm identifies biomarkers that play more significant roles than others in ad diagnosis.
probabilistic latent semantic visualization: topic model for visualizing documents. we propose a visualization method based on a topic model for discrete data such as documents. unlike conventional visualization methods based on pairwise distances such as multi-dimensional scaling, we consider a mapping from the visualization space into the space of documents as a generative process of documents. in the model, both documents and topics are assumed to have latent coordinates in a two- or three-dimensional euclidean space, or visualization space. the topic proportions of a document are determined by the distances between the document and the topics in the visualization space, and each word is drawn from one of the topics according to its topic proportions. a visualization, i.e. latent coordinates of documents, can be obtained by fitting the model to a given set of documents using the em algorithm, resulting in documents with similar topics being embedded close together. we demonstrate the effectiveness of the proposed model by visualizing document and movie data sets, and quantitatively compare it with conventional visualization methods.
temporal pattern discovery for trends and transient effects: its application to patient records. we introduce a novel pattern discovery methodology for event history data focusing explicitly on the detailed temporal relationship between pairs of events. at the core is a graphical statistical approach to summarising and visualising event history data, which contrasts the observed to the expected incidence of the event of interest before and after an index event. thus, pattern discovery is not restricted to a specific time window of interest, but encompasses extended parts of the underlying event histories. in order to effectively screen large collections of event history data for interesting temporal relationships, we introduce a new measure of temporal association. the proposed measure contrasts the observed-to-expected ratio in a time period of interest to that in a pre-defined control period. an important feature of both the observed-to-expected graph itself and the measure of association, is a statistical shrinkage towards the null hypothesis of no association. this provides protection against spurious associations and is an extension of the statistical shrinkage successfully applied to large-scale screening for associations between events in cross-sectional data, such as large collections of adverse drug reaction reports. we demonstrate the usefulness of the proposed pattern discovery methodology by a set of examples from a collection of over two million patient records in the united kingdom. the identified patterns include temporal relationships between drug prescription and medical events suggestive of persistent or transient risks of adverse events, as well as temporal relationships between prescriptions of different drugs.
fast: a roc-based feature selection metric for small samples and imbalanced data classification problems. the class imbalance problem is encountered in a large number of practical applications of machine learning and data mining, for example, information retrieval and filtering, and the detection of credit card fraud. it has been widely realized that this imbalance raises issues that are either nonexistent or less severe compared to balanced class cases and often results in a classifier's suboptimal performance. this is even more true when the imbalanced data are also high dimensional. in such cases, feature selection methods are critical to achieve optimal performance. in this paper, we propose a new feature selection method, feature assessment by sliding thresholds (fast), which is based on the area under a roc curve generated by moving the decision boundary of a single feature classifier with thresholds placed using an even-bin distribution. fast is compared to two commonly-used feature selection methods, correlation coefficient and relevance in estimating features (relief), for imbalanced data classification. the experimental results obtained on text mining, mass spectrometry, and microarray data sets showed that the proposed method outperformed both relief and correlation methods on skewed data sets and was comparable on balanced data sets; when small number of features is preferred, the classification performance of the proposed method was significantly improved compared to correlation and relief-based methods.
on updates that constrain the features' connections during learning. in many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. we investigate two online update techniques especially suited to such problems. these updates share a sparsity preservation capacity: they allow for constraining the number of prediction connections that each feature can make. we show that one method, exponential moving average, is solving a "discrete" regression problem for each feature, changing the weights in the direction of minimizing the quadratic loss. we design the other method to improve a hinge loss subject to constraints, for better accuracy. we empirically explore the methods, and compare performance to previous indexing techniques, developed with the same goals, as well as other online algorithms based on prototype learning. we observe that while the classification accuracies are very promising, improving over previous indexing techniques, the scalability benefits are preserved.
generating succinct titles for web urls. how can a search engine automatically provide the best and most appropriate title for a result url (link-title) so that users will be persuaded to click on the url? we consider the problem of automatically generating link-titles for urls and propose a general statistical framework for solving this problem. the framework is based on using information from a diverse collection of sources, each of which can be thought of as contributing one or more candidate link-titles for the url. it can also incorporate the context in which the link-title will be used, along with constraints on its length. our framework is applicable to several scenarios: obtaining succinct titles for displaying quicklinks, obtaining titles for urls that lack a good title, constructing succinct sitemaps, etc. extensive experiments show that our method is very effective, producing results that are at least 20% better than non-trivial baselines.
joint latent topic models for text and citations. in this work, we address the problem of joint modeling of text and citations in the topic modeling framework. we present two different models called the pairwise-link-lda and the link-plsa-lda models. the pairwise-link-lda model combines the ideas of lda [4] and mixed membership block stochastic models [1] and allows modeling arbitrary link structure. however, the model is computationally expensive, since it involves modeling the presence or absence of a citation (link) between every pair of documents. the second model solves this problem by assuming that the link structure is a bipartite graph. as the name indicates, link-plsa-lda model combines the lda and plsa models into a single graphical model. our experiments on a subset of citeseer data show that both these models are able to predict unseen data better than the baseline model of erosheva and lafferty [8], by capturing the notion of topical similarity between the contents of the cited and citing documents. our experiments on two different data sets on the link prediction task show that the link-plsa-lda model performs the best on the citation prediction task, while also remaining highly scalable. in addition, we also present some interesting visualizations generated by each of the models.
constructing comprehensive summaries of large event sequences. event sequences capture system and user activity over time. prior research on sequence mining has mostly focused on discovering local patterns appearing in a sequence. while interesting, these patterns do not give a comprehensive summary of the entire event sequence. moreover, the number of patterns discovered can be large. in this article, we take an alternative approach and build short summaries that describe an entire sequence, and discover local dependencies between event types. we formally define the summarization problem as an optimization problem that balances shortness of the summary with accuracy of the data description. we show that this problem can be solved optimally in polynomial time by using a combination of two dynamic-programming algorithms. we also explore more efficient greedy alternatives and demonstrate that they work well on large datasets. experiments on both synthetic and real datasets illustrate that our algorithms are efficient and produce high-quality results, and reveal interesting local structures in the data.
spectral domain-transfer learning. traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. in many real world applications, however, we wish to make use of the labeled data from one domain (called in-domain) to classify the unlabeled data in a different domain (out-of-domain). this problem often happens when obtaining labeled data in one domain is difficult while there are plenty of labeled data from a related but different domain. in general, this is a transfer learning problem where we wish to classify the unlabeled data through the labeled data even though these data are not from the same domain. in this paper, we formulate this domain-transfer learning problem under a novel spectral classification framework, where the objective function is introduced to seek consistency between the in-domain supervision and the out-of-domain intrinsic structure. through optimization of the cost function, the label information from the in-domain data is effectively transferred to help classify the unlabeled data from the out-of-domain. we conduct extensive experiments to evaluate our method and show that our algorithm achieves significant improvements on classification performance over many state-of-the-art algorithms.
information extraction from wikipedia: moving down the long tail. not only is wikipedia a comprehensive source of quality information, it has several kinds of internal structure (e.g., relational summaries known as infoboxes), which enable self-supervised information extraction. while previous efforts at extraction from wikipedia achieve high precision and recall on well-populated classes of articles, they fail in a larger number of cases, largely because incomplete articles and infrequent use of infoboxes lead to insufficient training data. this paper presents three novel techniques for increasing recall from wikipedia's long tail of sparse classes: (1) shrinkage over an automatically-learned subsumption taxonomy, (2) a retraining technique for improving the training data, and (3) supplementing results by extracting from the broader web. our experiments compare design variations and show that, used in concert, these techniques increase recall by a factor of 1.76 to 8.71 while maintaining or increasing precision.
direct mining of discriminative and essential frequent patterns via model-based search tree. frequent patterns provide solutions to datasets that do not have well-structured feature vectors. however, frequent pattern mining is non-trivial since the number of unique patterns is exponential but many are non-discriminative and correlated. currently, frequent pattern mining is performed in two sequential steps: enumerating a set of frequent patterns, followed by feature selection. although many methods have been proposed in the past few years on how to perform each separate step efficiently, there is still limited success in eventually finding highly compact and discriminative patterns. the culprit is due to the inherent nature of this widely adopted two-step approach. this paper discusses these problems and proposes a new and different method. it builds a decision tree that partitions the data onto different nodes. then at each node, it directly discovers a discriminative pattern to further divide its examples into purer subsets. since the number of examples towards leaf level is relatively small, the new approach is able to examine patterns with extremely low global support that could not be enumerated on the whole dataset by the two-step method. the discovered feature vectors are more accurate on some of the most difficult graph as well as frequent itemset problems than most recently proposed algorithms but the total size is typically 50% or more smaller. importantly, the minimum support of some discriminative patterns can be extremely low (e.g. 0.03%). in order to enumerate these low support patterns, state-of-the-art frequent pattern algorithm either cannot finish due to huge memory consumption or have to enumerate 101 to 103 times more patterns before they can even be found. software and datasets are available by contacting the author.
feedback effects between similarity and social influence in online communities. a fundamental open question in the analysis of social networks is to understand the interplay between similarity and social ties. people are similar to their neighbors in a social network for two distinct reasons: first, they grow to resemble their current friends due to social influence; and second, they tend to form new links to others who are already like them, a process often termed selection by sociologists. while both factors are present in everyday social processes, they are in tension: social influence can push systems toward uniformity of behavior, while selection can lead to fragmentation. as such, it is important to understand the relative effects of these forces, and this has been a challenge due to the difficulty of isolating and quantifying them in real settings. we develop techniques for identifying and modeling the interactions between social influence and selection, using data from online communities where both social interaction and changes in behavior over time can be measured. we find clear feedback effects between the two factors, with rising similarity between two individuals serving, in aggregate, as an indicator of future interaction -- but with similarity then continuing to increase steadily, although at a slower rate, for long periods after initial interactions. we also consider the relative value of similarity and social influence in modeling future behavior. for instance, to predict the activities that an individual is likely to do next, is it more useful to know the current activities of their friends, or of the people most similar to them?
data mining using high performance data clouds: experimental studies using sector and sphere. we describe the design and implementation of a high performance cloud that we have used to archive, analyze and mine large distributed data sets. by a cloud, we mean an infrastructure that provides resources and/or services over the internet. a storage cloud provides storage services, while a compute cloud provides compute services. we describe the design of the sector storage cloud and how it provides the storage services required by the sphere compute cloud. we also describe the programming paradigm supported by the sphere compute cloud. sector and sphere are designed for analyzing large data sets using computer clusters connected with wide area high performance networks (for example, 10+ gb/s). we describe a distributed data mining application that we have developed using sector and sphere. finally, we describe some experimental studies comparing sector/sphere to hadoop.
combinational collaborative filtering for personalized community recommendation. rapid growth in the amount of data available on social networking sites has made information retrieval increasingly challenging for users. in this paper, we propose a collaborative filtering method, combinational collaborative filtering (ccf), to perform personalized community recommendations by considering multiple types of co-occurrences in social data at the same time. this filtering method fuses semantic and user information, then applies a hybrid training strategy that combines gibbs sampling and expectation-maximization algorithm. to handle the large-scale dataset, parallel computing is used to speed up the model training. through an empirical study on the orkut dataset, we show ccf to be both effective and scalable.
unsupervised deduplication using cross-field dependencies. recent work in deduplication has shown that collective deduplication of different attribute types can improve performance. but although these techniques cluster the attributes collectively, they do not model them collectively. for example, in citations in the research literature, canonical venue strings and title strings are dependent -- because venues tend to focus on a few research areas -- but this dependence is not modeled by current unsupervised techniques. we call this dependence between fields in a record a cross-field dependence. in this paper, we present an unsupervised generative model for the deduplication problem that explicitly models cross-field dependence. our model uses a single set of latent variables to control two disparate clustering models: a dirichlet-multinomial model over titles, and a non-exchangeable string-edit model over venues. we show that modeling cross-field dependence yields a substantial improvement in performance -- a 58% reduction in error over a standard dirichlet process mixture.
anomaly pattern detection in categorical datasets. we propose a new method for detecting patterns of anomalies in categorical datasets. we assume that anomalies are generated by some underlying process which affects only a particular subset of the data. our method consists of two steps: we first use a "local anomaly detector" to identify individual records with anomalous attribute values, and then detect patterns where the number of anomalous records is higher than expected. given the set of anomalies flagged by the local anomaly detector, we search over all subsets of the data defined by any set of fixed values of a subset of the attributes, in order to detect self-similar patterns of anomalies. we wish to detect any such subset of the test data which displays a significant increase in anomalous activity as compared to the normal behavior of the system (as indicated by the training data). we perform significance testing to determine if the number of anomalies in any subset of the test data is significantly higher than expected, and propose an efficient algorithm to perform this test over all such subsets of the data. we show that this algorithm is able to accurately detect anomalous patterns in real-world hospital, container shipping and network intrusion data.
simultaneous tensor subspace selection and clustering: the equivalence of high order svd and k-means clustering. singular value decomposition (svd)/principal component analysis (pca) have played a vital role in finding patterns from many datasets. recently tensor factorization has been used for data mining and pattern recognition in high index/order data. high order svd (hosvd) is a commonly used tensor factorization method and has recently been used in numerous applications like graphs, videos, social networks, etc. in this paper we prove that hosvd does simultaneous subspace selection (data compression) and k-means clustering widely used for unsupervised learning tasks. we show how to utilize this new feature of hosvd for clustering. we demonstrate these new results using three real and large datasets, two on face images datasets and one on hand-written digits dataset. using this new hosvd clustering feature we provide a dataset quality assessment on many frequently used experimental datasets with expected noise levels.
stable feature selection via dense feature groups. many feature selection algorithms have been proposed in the past focusing on improving classification accuracy. in this work, we point out the importance of stable feature selection for knowledge discovery from high-dimensional data, and identify two causes of instability of feature selection algorithms: selection of a minimum subset without redundant features and small sample size. we propose a general framework for stable feature selection which emphasizes both good generalization and stability of feature selection results. the framework identifies dense feature groups based on kernel density estimation and treats features in each dense group as a coherent entity for feature selection. an efficient algorithm drags (dense relevant attribute group selector) is developed under this framework. we also introduce a general measure for assessing the stability of feature selection algorithms. our empirical study based on microarray data verifies that dense feature groups remain stable under random sample hold out, and the drags algorithm is effective in identifying a set of feature groups which exhibit both high classification accuracy and stability.
real memory mach. mach was designed with the assumption that the underlying hardware includes a page-based memory management unit, enabling the use of a large, sparse virtual address space. therefore the mach micro-kernel in its current state cannot be used on segmented machines such as cray vector supercomputers or real memory machines such as transputers. this paper describes the results of initial work to adapt the mach microkernel to such architectures, including the architectural changes and results obtained from a prototype system.
mike: a distributed object-oriented programming platform on top of the mach micro-kernel. this paper describes the architecture and implementation of mike - a version of the ik distributed persistent object-oriented programming platform built on top of the mach microkernel. mike's primary goal is to offer a single object-oriented programming paradigm for writing distributed applications. in mike an application programmer can use c++ almost as he would in a non-distributed system. the platform supports fine grained objects which can be invoked in a location transparent way and whose references can be exchanged freely as invocation parameters. these objects are potentially persistent. mike supports the abstraction of one-level store, persistent objects are transparently loaded on demand when first invoked and saved to disk when the application terminates. class objects are special persistent objects which are dynamically linked when needed. the platform also offers distributed garbage collection of non-persistent objects. this paper discusses how mike makes use of mach's features to offer the functionality described above and the techniques used to achieve good performance. mike is compared with the unix versions of ik to evaluate the benefits of using mach abstractions.
kernel support for recoverable-persistent virtual memory. the buffering facilities typically provided by operating systems are not powerful enough to support the performance and consistency requirements of database systems. as a result, most database systems are structured as buffer pool database (bpdb) systems, providing their own buffering facilities, with their own paging policies and recovery schemes. the emergence of operating systems with very large address spaces and flexible memory management makes virtual memory database (vmdb) systems feasible. in such systems, the database is mapped into virtual memory and the buffering facilities of the underlying virtual memory system are used. vmdb systems do not experience many of the problems faced by bpdb systems. to support the consistency and recoverability requirements of vmdb systems, we have proposed that the virtual memory system be extended to support the recoverable-persistent updates (rpu) model. this model is powerful and general enough to support a wide variety of policies for ensuring database recoverability. in this paper we discuss our approach to and progress in extending the mach 3.0 kernel to provide direct support for this rpu model.
using continuations to build a user-level threads library. we have designed and built a user-level threads library that uses continuations for transfers of control. the use of continuations reduces the amount of state that needs to be saved and restored at context switch time thereby reducing the instruction count in the critical sections. our multiprocessor contention benchmarks indicate that this reduction and the use of busy spinning, busy waiting and spin polling increases throughput by as much as 75% on a multiprocessor. in addition, flattening the locking hierarchy reduces context switch latency by 5% to 49% on both uniprocessors and multiprocessors. this paper describes the library's design and compares its overall performance characteristics to the existing implementation.
using the mach communication primitives in x11. we have modified the x11 windowing system to use the native communication facilities of the ach 3.0 microkernel. our new implementation can rely on ach's low-overhead ipc facility as a direct replacement for sockets, or it can use shared memory as a transport between x11 clients and the server. on conventional bsd unix systems. x11 communication is done through sockets. because a user-level process implements unix functionality on top of ach 3.0, a socket-based version of x11 performs substantially worse than when running on a monolithic unix kernel. using ach ipc as the transport between x11 clients and the server. x11 performance is slightly better than that of a monolithic system in which sockets are implemented inside the kernel as opposed to within a user level process. using ach's shared memory facilities as the transport, we have measured performance improvements of over 40%.
sprite on mach. sprite is a distributed operating system that supports a fast, single-image network file system and transparent process migration. over a period of 19 months we ported sprite to run as a server on top of the mach 3.0 microkernel. although the resulting server does not implement some sprite features, it can run in an existing sprite cluster, and it supports standard unix programs like vi, gcc, and make. porting sprite to mach was generally straightforward, though there were some difficulties. many of the problems were related to asynchronous interactions between the sprite server, mach, and sprite user processes. others resulted from trying to maintain native sprite's internal interfaces in the sprite server. the sprite server is 22% smaller than an equivalent sprite kernel, and it contains almost no machine-dependent code. these improvements should significantly simplify porting sprite to new hardware platforms. unfortunately, the sprite server runs the andrew benchmark at only 38% of the speed of native sprite. none of the performance problems appears insurmountable, but they could require a long time to track down and fix.
unix file access and caching in a multicomputer environment. this paper describes the unix file access and caching mechanisms in a version of the osf/1 unix operating system designed to run in a multicomputer environment. the multicomputer hard-ware platforms targeted can consist of hundreds or even thousands of individual nodes, where each node consists of one or more processors. the multicomputer version of osf/1 (called osf/1 ad) uses mach memory objects to cache data from unix files, and relies on an in-kernel distributed shared memory implementation to maintain coherency for data cached across multiple nodes. the focus of this paper is on the modifications made to standard osf/1 functionality to support distributed, efficient access to memory objects. of particular interest are the introduction of a mapped files module for synchronizing clients and maintaining file meta data, the elimination of the traditional unix buffer cache from the file data access path, and the implementation of a disk block reservation scheme to correctly support unix write() semantics. an evaluation of the technology is presented, providing insight into how it can be improved in the future, including several possible enhancements to mach. as will be seen, most of this insight would equally apply to a single-node operating system based on mach.
automatic 3d registration of lung surfaces in computed tomography scans. abstract we developed an automated system that registers chest ct scans temporally. our registration method matches corresponding anatomical landmarks to obtain initial registration parameters. the initial point-to-point registration is then generalized to an iterative surface-to-surface registration method. our ``goodness-of-fit'''' measure is evaluated at each step in the iterative scheme until the registration performance is sufficient. we applied our method to register the 3d lung surfaces of 11 pairs of chest ct scans and report promising registration performance.
towards whole brain segmentation by a hybrid model. segmenting cortical and sub-cortical structures from 3d brain images is of significant practical importance. however, various anatomical structures have similar intensity patterns in mri, and the automatic segmentation of them is a challenging task. in this paper, we present a new brain segmentation algorithm using a hybrid model. (1) a multi-class classifier, pbt.m2, is proposed for learning/computing multi-class discriminative models. the pbt.m2 handles multi-class patterns more easily than the original probabilistic boosting tree (pbt) [11], and it facilitates the process, eventually, toward whole brain segmentation. (2) we use an edge field, by learning, to constraint the region boundaries. we show the improvements due to the two new aspects both numerically and visually, and also compare the results with those by freesurfer [2]. our algorithm is general and easy to use, and the results obtained are encouraging.
nonlinear analysis of bold signal: biophysical modeling, physiological states, and functional activation. there is an increasing interest in exploiting the biophysical plausible models to investigate the physiological mechanisms that underlie observed bold response. however, most existing studies do not produce reliable model parameter estimates, are not robust due to the linearization of the nonlinear model, and do not perform statistics test to detect functional activation. to overcome these limitations, we developed a general framework for the analysis of fmri data based on nonlinear physiological models. it performs system dynamics analysis to gain meaningful insight, followed by global sensitivity analysis for model reduction which leads to better system identifiability. subsequently, a nonlinear filter is used to simultaneously estimate the state and parameter of the dynamic system, and statistics test is performed to derive activation maps based on such model. furthermore, we investigate the change of the activation maps of these hidden physiological variables with experimental paradigm through time as well.
markov dependence tree-based segmentation of deep brain structures. we propose a new framework for multi-object segmentation of deep brain structures, which have significant shape variations and relatively small sizes in medical brain images. in the images, the structure boundaries may be blurry or even missing, and the surrounding background is a clutter and full of irrelevant edges. we suggest a template-based framework, which fuses the information of edge features, region statistics and inter-structure constraints to detect and locate all the targeted brain structures such that manual initialization is unnecessary. the multi-object template is organized in the form of a hierarchical markov dependence tree. it makes the matching of multiple objects efficient. our approach needs only one example as training data and alleviates the demand of a large training set. the obtained segmentation results on real data are encouraging and the proposed method enjoys several important advantages over existing methods.
toward optimal matching for 3d reconstruction of brachytherapy seeds. x-ray c-arm fluoroscopy is a natural choice for intraoperative seed localization in prostate brachy therapy. resolving the correspondence of seeds in the projection images can be modeled as an assignment problem that is np-hard. our approach rests on the practical observation that the optimal solution has almost zero cost if the pose of the c-arm is known accurately. this allowed us to to derive an equivalent problem of reduced dimensionality that, with linear programming, can be solved efficiently in polynomial time. additionally, our method demonstrates significantly increased robustness to c-arm pose errors when compared to the prior art. because under actual clinical circumstances it is exceedingly difficult to track the c-arm, easing on this constraint has additional practical utility.
segmentation of q-ball images using statistical surface evolution. in this article, we develop a new method to segment q-ball imaging (qbi) data. we first estimate the orientation distribution function (odf) using a fast and robust spherical harmonic (sh) method. then, we use a region-based statistical surface evolution on this image of odfs to efficiently find coherent white matter fiber bundles. we show that our method is appropriate to propagate through regions of fiber crossings and we show that our results outperform state-of-the-art diffusion tensor (dt) imaging segmentation methods, inherently limited by the dt model. results obtained on synthetic data, on a biological phantom, on real datasets and on all 13 subjects of a public qbi database show that our method is reproducible, automatic and brings a strong added value to diffusion mri segmentation.
bias image correction via stationarity maximization. automated acquisitions in microscopy may come along with strong illumination artifacts due to poor physical imaging conditions. such artifacts obviously have direct consequences on the efficiency of an image analysis algorithm and on the quantitative measures. in this paper, we propose a method to correct illumination artifacts on biological images. this correction is based on orthogonal polynomial modeling, combined with stationary maximization criteria. to validate the proposed method we show that we improve particle detection algorithm.
primal/dual linear programming and statistical atlases for cartilage segmentation. in this paper we propose a novel approach for automatic segmentation of cartilage using a statistical atlas and efficient primal/dual linear programming. to this end, a novel statistical atlas construction is considered from registered training examples. segmentation is then solved through registration which aims at deforming the atlas such that the conditional posterior of the learned (atlas) density is maximized with respect to the image. such a task is reformulated using a discrete set of deformations and segmentation becomes equivalent to finding the set of local deformations which optimally match the model to the image. we evaluate our method on 56 mri data sets (28 used for the model and 28 used for evaluation) and obtain a fully automatic segmentation of patella cartilage volume with an overlap ratio of 0.84 with a sensitivity and specificity of 94.06% and 99.92%, respectively.
segmentation-driven 2d-3d registration for abdominal catheter interventions. 2d-3d registration of abdominal angiographic data is a difficult problem due to hard time constraints during the intervention, different vessel contrast in volume and image, and motion blur caused by breathing. we propose a novel method for aligning 2d digitally subtracted angiograms (dsa) to computed tomography angiography (cta) volumes, which requires no user interaction intrainterventionally. in an iterative process, we link 2d segmentation and 2d-3d registration using a probability map, which creates a common feature space where outliers in 2d and 3d are discarded consequently. unlike other approaches, we keep user interaction low while high capture range and robustness against vessel variability and deformation are maintained. tests on five patient data sets and a comparison to two recently proposed methods show the good performance of our method.
towards subject-specific models of the dynamic heart for image-guided mitral valve surgery. surgeons need a robust interventional system capable of providing reliable, real-time information regarding the position and orientation of the surgical targets and tools to compensate for the lack of direct vision and to enhance manipulation of intracardiac targets during minimally-invasive, off-pump cardiac interventions. in this paper, we describe a novel method for creating dynamic, pre-operative, subject-specific cardiac models containing the surgical targets and surrounding anatomy, and how they are used to augment the intra-operative virtual environment for guidance of valvular interventions. the accuracy of these pre-operative models was established by comparing the target registration error between the mitral valve annulus characterized in the pre-operative images and their equivalent structures manually extracted from 3d us data. on average, the mitral valve annulus was extracted with a 3.1 mm error across all cardiac phases. in addition, we also propose a method for registering the pre-operative models into the intraoperative virtual environment.
lv motion tracking from 3d echocardiography using textural and structural information. automated motion reconstruction of the left ventricle (lv) from 3d echocardiography provides insight into myocardium architecture and function. low image quality and artifacts make 3d ultrasound image processing a challenging problem. we introduce a lv tracking method, which combines textural and structural information to overcome the image quality limitations. our method automatically reconstructs the motion of the lv contour (endocardium and epicardium) from a sequence of 3d ultrasound images.
real-time tissue tracking with b-mode ultrasound using speckle and visual servoing. we present a method for real-time tracking of moving soft tissue with b-mode ultrasound (us). the method makes use of the speckle information contained in the us images to estimate the in-plane and out-of-plane motion of a fixed target relative to the ultrasound scan plane. the motion information is then used as closed-loop feedback to a robot which corrects for the target motion. the concept is demonstrated for translation motions in an experimental setup consisting of an ultrasound speckle phantom, a robot for simulating tissue motion, and a robot that performs motion stabilization from us images. this concept shows promise for us-guided procedures that require real-time motion tracking and compensation.
proof of concept of a simple computer-assisted technique for correcting bone deformities. we propose a computer-assisted technique for correcting bone deformities using the ilizarov method. our technique is an improvement over prior art in that it does not require a tracking system, navigation hardware and software, or intraoperative registration. instead, we rely on a postoperative ct scan to obtain all of the information necessary to plan the correction and compute a correction schedule for the patient. our laboratory experiments using plastic phantoms produced deformity corrections accurate to within 3.0° of rotation and 1 mm of lengthening.
interactive contacts resolution using smooth surface representation. accurately describing interactions between medical devices and anatomical structures, or between anatomical structures themselves, is an essential step towards the adoption of computer-based medical simulation as an alternative to traditional training methods. however, while substantial work has been done in the area of real-time soft tissue modeling, little has been done to study the problem of contacts occurring during tissue manipulation. in this paper we introduce a new method for correctly handling complex contacts between various combination of rigid and deformable objects. our approach verifies signorini's law by combining lagrange multipliers and the status method to solve unilateral constraints. our method handles both concave and convex surfaces by using a displacement subdivision strategy, and the proposed algorithm allows interactive computation times even in very constrained situations. we demonstrate the efficiency of our approach in the context of interventional radiology, with the navigation of catheters and guidewires in tortuous vessels and with the deployment of coils to treat aneurysms.
autism diagnostics by 3d texture analysis of cerebral white matter gyrifications. the importance of accurate early diagnostics of autism that severely affects personal behavior and communication skills cannot be overstated. neuropathological studies have revealed an abnormal anatomy of the cerebral white matter (cwm) in autistic brains. we explore a possibility of distinguishing between autistic and normal brains by a quantitative shape analysis of cwm gyrifications on 3d proton density mri (pd-mri) images. our approach consists of (i) segmentation of the cwm on a 3d brain image using a deformable 3d boundary; (ii) extraction of gyrifications from the segmented cwm, and (iii) shape analysis to quantify thickness of the extracted gyrifications and classify autistic and normal subjects. the boundary evolution is controlled by two probabilistic models of visual appearance of 3d cwm: the learned prior and the current appearance model. initial experimental results suggest that the proposed 3d texture analysis is a promising supplement to the current techniques for diagnosing autism.
thoracoscopic surgical navigation system for cancer localization in collapsed lung based on estimation of lung deformation. we have developed a thoracoscopic surgical navigation system for lung cancer localization. in our system, the thoracic cage and mediastinum are localized using rigid registration between the intraoperatively digitized surface points and the preoperative ct surface model, and then the lung deformation field is estimated using nonrigid registration between the registered and digitized point datasets on the collapsed lung surface and the preoperative ct lung surface model to predict cancer locations. in this paper, improved methods on key components of the system are investigated to realize clinically acceptable usability and accuracy. firstly, we implement a non-contact surface digitizer under thoracoscopic control using an optically tracked laser pointer. secondly, we establish a rigid registration protocol which minimizes the influence of the deformation in different patient's positions by analyzing mr images of volunteers. these techniques were evaluated by in vitro and clinical experiments.
physically motivated enhancement of color images for fiber endoscopy. fiber optics are widely used in flexible endoscopes which are indispensable for many applications in diagnosis and therapy. computer-aided use of fiberscopes requires a digital sensor mounted at the proximal end. most commercially available cameras for endoscopy provide the images by means of a regular grid of color filters what is known as the bayer pattern. hence, the images suffer from false colored spatial moiré, which is further stressed by the downgrading fiber optic transmission yielding a honey comb pattern. to solve this problem we propose a new approach that extends the interpolation between known intensities of registered fibers to multi channel color applications. the inventive idea takes into account both the gaussian intensity distribution of each fiber and the physical color distribution of the bayer pattern. individual color factors for interpolation of each fiber area make it possible to simultaneously remove both the comb structure from the fiber bundle as well as the bayer pattern mosaicking from the sensor while preserving depicted structures and textures in the scene.
dynamic mri scan plane control for passive tracking of instruments and devices. this paper describes a novel image-based method for tracking robotic mechanisms and interventional devices during magnetic resonance image (mri)-guided procedures. it takes advantage of the multi-planar imaging capabilities of mri to optimally image a set of localizing fiducials for passive motion tracking in the image coordinate frame. the imaging system is servoed to adaptively position the scan plane based on automatic detection and localization of fiducial artifacts directly from the acquired image stream. this closed-loop control system has been implemented using an open-source software framework and currently operates with ge mri scanners. accuracy and performance were evaluated in experiments, the results of which are presented here.
a coupled finite element model of tumor growth and vascularization. we present a model of solid tumor growth which can account for several stages of tumorigenesis, from the early avascular phase to the angiogenesis driven proliferation. the model combines several previously identified components in a consistent framework, including neoplastic tissue growth, blood and oxygen transport, and angiogenic sprouting. first experiments with the framework and comparisons with observations made on solid tumors in vivo illustrate the plausibility of the approach. explanations of several experimental observations are naturally provided by the model. to the best of our knowledge this is the first report of a model coupling tumor growth and angiogenesis.
non-rigid registration of pre-procedural mr images with intra-procedural unenhanced ct images for improved targeting of tumors during liver radiofrequency ablations. in the united states, unenhanced ct is currently the most common imaging modality used to guide percutaneous biopsy and tumor ablation. the majority of liver tumors such as hepatocellular carcinomas are visible on contrast-enhanced ct or mri obtained prior to the procedure. yet, these tumors may not be visible or may have poor margin conspicuity on unenhanced ct images acquired during the procedure. non-rigid registration has been used to align images accurately, even in the presence of organ motion. however, to date, it has not been used clinically for radiofrequency ablation (rfa), since it requires significant computational infrastructure and often these methods are not sufficient robust. we have already introduced a novel finite element based method (fem) that is demonstrated to achieve good accuracy and robustness for the problem of brain shift in neurosurgery. in this current study, we adapt it to fuse pre-procedural mri with intra-procedural ct of liver. we also compare its performance with conventional rigid registration and two non-rigid registration methods: b-spline and demons on 13 retrospective datasets from patients that underwent rfa at our institution. fem non-rigid registration technique was significantly better than rigid (p<10-5), non-rigid b-spline (p<10- 4) and demons (p<10-4) registration techniques. the results of our study indicate that this novel technology may be used to optimize placement of rf applicator during ct-guided ablations.
new motion correction models for automatic identification of renal transplant rejection. acute rejection is the most common reason of graft failure after kidney transplantation and early detection is crucial to survive the transplanted kidney function. in this paper, we introduce a new approach for the automatic classification of normal and acute rejection transplants from dynamic contrast enhanced magnetic resonance imaging (dce-mri). the proposed algorithm consists of three main steps; the first step isolates the kidney from the surrounding anatomical structures. in the second step, new motion correction models are employed to account for both the global and local motion of the kidney due to patient moving and breathing. finally, the perfusion curves that show the transportation of the contrast agent into the tissue are obtained from the kidney and used in the classification of normal and acute rejection transplants. in this paper, we will focus on the second and third steps and the first step is shown in detail in [1].
fast and robust analysis of dynamic contrast enhanced mri datasets. a fully automated method for quantitative analysis of dynamic contrast-enhanced mri data acquired with low and high field scanners, using spin echo and gradient echo sequences, depicting various joints is presented. the method incorporates efficient pre-processing techniques and a robust algorithm for quantitative assessment of dynamic signal intensity vs. time curves. it provides differentiated information to the reader regarding areas with the most active perfusion and permits depiction of different disease activity in separate compartments of a joint. additionally, it provides information on the speed of contrast agent uptake by various tissues. the method delivers objective and easily reproducible results, which have been favourably viewed by a number of medical experts.
prediction of respiratory motion with wavelet-based multiscale autoregression. in robotic radiosurgery, a photon beam source, moved by a robot arm, is used to ablate tumors. the accuracy of the treatment can be improved by predicting respiratory motion to compensate for system delay. we consider a wavelet-based multiscale autoregressive prediction method. the algorithm is extended by introducing a new exponential averaging parameter and the use of the moore-penrose pseudo inverse to cope with long-term signal dependencies and system matrix irregularity, respectively. in test cases, this new algorithm outperforms normalized lms predictors by as much as 50%. with real patient data, we achieve an improvement of around 5 to 10%.
regional homogeneity and anatomical parcellation for fmri image classification: application to schizophrenia and normal controls. this paper presents a discriminative model of multivariate pattern classification, based on functional magnetic resonance imaging (fmri) and anatomical template. as a measure of brain function, regional homogeneity (reho) is calculated voxel by voxel, and then a widely used anatomical template is applied on reho map to parcelate it into 116 brain regions. the mean and standard deviation of reho values in each region are extracted as features. pseudo-fisher linear discriminant analysis (pflda) is performed for training samples to generate discriminative model. classification experiments have been carried out in 48 schizophrenia patients and 35 normal controls. under a full leave-one-out (loo) cross-validation, correct prediction rate of 80% is achieved. anatomical parcellation process is proved useful to improve classification rate by a control experiment. the discriminative model shows its ability to reveal abnormal brain functional activities and identify people with schizophrenia.
mcmc curve sampling for image segmentation. we present an algorithm to generate samples from probability distributions on the space of curves. we view a traditional curve evolution energy functional as a negative log probability distribution and sample from it using a markov chain monte carlo (mcmc) algorithm. we define a proposal distribution by generating smooth perturbations to the normal of the curve and show how to compute the transition probabilities to ensure that the samples come from the posterior distribution. we demonstrate some advantages of sampling methods such as robustness to local minima, better characterization of multi-modal distributions, access to some measures of estimation error, and ability to easily incorporate constraints on the curve.
-space based non-photorealistic rendering for augmented reality. the increasing use of robotic assisted minimally invasive surgery (mis) provides an ideal environment for using augmented reality (ar) for performing image guided surgery. seamless synthesis of ar depends on a number of factors relating to the way in which virtual objects appear and visually interact with a real environment. traditional overlaid ar approaches generally suffer from a loss of depth perception. this paper presents a new ar method for robotic assisted mis, which uses a novel pq-space based non-photorealistic rendering technique for providing see-through vision of the embedded virtual object whilst maintaining salient anatomical details of the exposed anatomical surface. experimental results with both phantom and in vivo lung lobectomy data demonstrate the visual realism achieved for the proposed method and its accuracy in providing high fidelity ar depth perception.
bronchoscope tracking without fiducial markers using ultra-tiny electromagnetic tracking system and its evaluation in different environments. this paper presents a method for bronchoscope tracking without any fiducial markers using an ultra-tiny electromagnetic tracker (uemt) for a bronchoscopy guidance system. the proposed method calculates the transformation matrix, which shows the relationship between the coordinates systems of the pre-operative ct images and the uemt, by registering bronchial branches segmented from ct images and points measured by the uemt attached at the tip of a bronchoscope. we dynamically compute the transformation matrix for every pre-defined number of measurements. we applied the proposed method to a bronchial phantom in several experimental environments. the experimental results showed the proposed method can track a bronchoscope camera with about 3.3mm of target registration error (tre) for wood table environment and 4.0mm of tre for examination table environment.
segmentation and classification of breast tumor using dynamic contrast-enhanced mr images. accuracy of automatic cancer diagnosis is largely determined by two factors, namely, the precision of tumor segmentation, and the suitability of extracted features for discrimination between malignancy and benignancy. in this paper, we propose a new framework for accurate characterization of tumors in contrast enhanced mr images. first, a new graph cut based segmentation algorithm is developed for refining coarse manual segmentation, which allows precise identification of tumor regions. second, by considering serial contrast-enhanced images as a single spatio-temporal image, a spatio-temporal model of segmented tumor is constructed to extract spatio-temporal enhancement patterns (steps). steps are designed to capture not only dynamic enhancement and architectural features, but also spatial variations of pixel-wise temporal enhancement of the tumor. while temporal enhancement features are extracted through fourier transform, the resulting step framework captures spatial patterns of temporal enhancement features via moment invariants and rotation invariant gabor textures. high accuracy of the proposed framework is a direct consequence of this two pronged approach, which is validated through experiments yielding, for instance, an area of 0.97 under the roc curve.
fully automated and adaptive detection of amyloid plaques in stained brain sections of alzheimer transgenic mice. automated detection of amyloid plaques (ap) in post mortem brain sections of patients with alzheimer disease (ad) or in mouse models of the disease is a major issue to improve quantitative, standardized and accurate assessment of neuropathological lesions as well as of their modulation by treatment. we propose a new segmentation method to automatically detect amyloid plaques in congo red stained sections based on adaptive thresholds and a dedicated amyloid plaque/tissue modelling. a set of histological sections focusing on anatomical structures was used to validate the method in comparison to expert segmentation. original information concerning global amyloid load have been derived from 6 mouse brains which opens new perspectives for the extensive analysis of such a data in 3-d and the possibility to integrate in vivo-post mortem information for diagnosis purposes.
online estimation of the target registration error for -ocular optical tracking systems. for current surgical navigation systems optical tracking is state of the art. the accuracy of these tracking systems is currently determined statically for the case of full visibility of all tracking targets. we propose a dynamic determination of the accuracy based on the visibility and geometry of the tracking setup. this real time estimation of accuracy has a multitude of applications. for multiple camera systems it allows reducing line of sight problems and guaranteeing a certain accuracy. the visualization of these accuracies allows surgeons to perform the procedures taking to the tracking accuracy into account. it also allows engineers to design tracking setups interactively guaranteeing a certain accuracy. our model is an extension to the state of the art models of fitzpatrick et al. [1] and hoff et al. [2]. we model the error in the camera sensor plane. the error is propagated using the internal camera parameter, camera poses, tracking target poses, target geometry and marker visibility, in order to estimate the final accuracy of the tracked instrument.
a family of principal component analyses for dealing with outliers. principal component analysis (pca) has been widely used for dimensionality reduction in shape and appearance modeling. there have been several attempts of making pca robust against outliers. however, there are cases in which a small subset of samples may appear as outliers and still correspond to plausible data. the example of shapes corresponding to fractures when building a vertebra shape model is addressed in this study. in this case, the modeling of "outliers" is important, and it might be desirable not only not to disregard them, but even to enhance their importance. a variation on pca that deals naturally with the importance of outliers is presented in this paper. the technique is utilized for building a shape model of a vertebra, aiming at segmenting the spine out of lateral x-ray images. the results show that the algorithm can implement both an outlier-enhancing and a robust pca. the former improves the segmentation performance in fractured vertebrae, while the latter does so in the unfractured ones.
a comprehensive system for intraoperative 3d brain deformation recovery. during neurosurgery, brain deformation renders preoperative images unreliable for localizing pathologic structures. in order to visualize the current brain anatomy, it is necessary to nonrigidly warp these preoperative images to reflect the intraoperative brain. this can be accomplished using a biomechanical model driven by sparse intraoperative information. in this paper, a linear elastic model of the brain is developed which can infer volumetric brain deformation given the cortical surface displacement. this model was tested on both a realistic brain phantom and in vivo, proving its ability to account for large brain deformations. also, an efficient semiautomatic strategy for preoperative cortical feature detection is outlined, since accurate segmentation of cortical features can aid intraoperative cortical surface tracking.
global registration of multiple point sets: feasibility and applications in multi-fragment fracture fixation. an algorithm to globally register multiple 3d data sets (point sets) within a general reference frame is proposed. the algorithm uses the unscented kalman filter algorithm to simultaneously compute the registration transformations that map the data sets together, and to calculate the variances of the registration parameters. the data sets are either randomly generated, or collected from a set of fractured bone phantoms using computed tomography (ct) images. the algorithm robustly converges for isotropic gaussian noise that could have perturbed the point coordinates in the data sets. it is also computationally efficient, and enables real-time global registration of multiple data sets, with applications in computer-assisted orthopaedic trauma surgery.
intra-operative 3d guidance in prostate brachytherapy using a non-isocentric c-arm. intra-operative guidance in transrectal ultrasound (trus) guided prostate brachytherapy requires localization of inserted radioactive seeds relative to the prostate. seeds were reconstructed using a typical c-arm, and exported to a commercial brachytherapy system for dosimetry analysis. technical obstacles for 3d reconstruction on a non-isocentric c-arm included pose-dependent c-arm calibration; distortion correction; pose estimation of c-arm images; seed reconstruction; and c-arm to trus registration. in precision-machined hard phantoms with 40-100 seeds, we correctly reconstructed 99.8% seeds with a mean 3d accuracy of 0.68 mm. in soft tissue phantoms with 45-87 seeds and clinically realistic 15° c-arm motion, we correctly reconstructed 100% seeds with an accuracy of 1.3 mm. the reconstructed 3d seed positions were then registered to the prostate segmented from trus. in a phase-1 clinical trial, so far on 4 patients with 66-84 seeds, we achieved intraoperative monitoring of seed distribution and dosimetry. we optimized the 100% prescribed iso-dose contour by inserting an average of 3.75 additional seeds, making intra-operative dosimetry possible on a typical c-arm, at negligible additional cost to the existing clinical installation.
a clinically motivated 2-fold framework for quantifying and classifying immunohistochemically stained specimens. motivated by the current limitations of automated quantitative image analysis in discriminating among intracellular immunohistochemical (ihc) staining patterns, this paper presents a two-fold approach for ihc characterization that utilizes both the protein stain information and the surrounding tissue architecture. through the use of a color unmixing algorithm, stained tissue sections are automatically decomposed into the ihc stain, which visualizes the target protein, and the counterstain which provides an objective indication of the underlying histologic architecture. feature measures are subsequently extracted from both staining planes. in order to characterize the ihc expression pattern, this approach exploits the use of a non-traditional feature based on textons. novel biologically motivated filter banks are introduced in order to derive texture signatures for different ihc staining patterns. systematic experiments using this approach were used to classify breast cancer tissue microarrays which had been previously prepared using immuno-targeted nuclear, cytoplasmic, and membrane stains.
stabilization of image motion for robotic assisted beating heart surgery. the performance of robotic assisted minimally invasive beating heart surgery is a challenging task due to the rhythmic motion of the heart, which hampers delicate tasks such as small vessel anastomosis. in this paper, a virtual motion compensation scheme is proposed for stabilizing images from the surgical site. the method uses vision based 3d tracking to accurately infer cardiac surface deformation and augmented reality for rendering a motion stabilized view for improved surgical performance. the method forgoes the need of fiducial markers and can be integrated with the existing master-slave robotic consoles. the proposed technique is validated with both simulated surgical scenes with known ground truth and in vivo data acquired from a tecab procedure. the experimental results demonstrate the potential of the proposed technique in performing microscale tasks in a moving frame of reference with improved precision and repeatability.
automatic fetal measurements in ultrasound using constrained probabilistic boosting tree. automatic delineation and robust measurement of fetal anat-omical structures in 2d ultrasound images is a challenging task due to the complexity of the object appearance, noise, shadows, and quantity of information to be processed. previous solutions rely on explicit encoding of prior knowledge and formulate the problem as a perceptual grouping task solved through clustering or variational approaches. these methods are known to be limited by the validity of the underlying assumptions and cannot capture complex structure appearances. we propose a novel system for fast automatic obstetric measurements by directly exploiting a large database of expert annotated fetal anatomical structures in ultrasound images. our method learns to distinguish between the appearance of the object of interest and background by training a discriminative constrained probabilistic boosting tree classifier. this system is able to handle previously unsolved problems in this domain, such as the effective segmentation of fetal abdomens. we show results on fully automatic measurement of head circumference, biparietal diameter, abdominal circumference and femur length. unparalleled extensive experiments show that our system is, on average, close to the accuracy of experts in terms of segmentation and obstetric measurements. finally, this system runs under half second on a standard dual-core pc computer.
simultaneous segmentation, kinetic parameter estimation, and uncertainty visualization of dynamic pet images. we develop a segmentation technique for dynamic pet incorporating the physiological parameters for different regions via kinetic modeling. we demonstrate the usefulness of our technique on fifteen [11c] raclopride simulated pet images. we show qualitatively and quantitatively that the physiologically based algorithm outperforms two classical segmentation techniques. further, we derive a formula to compute and visualize the uncertainty encountered during the segmentation.
instrumentation for epidural anesthesia. a low-cost, sterilizable and unobtrusive instrumentation device was developed to quantify and study the loss-of-resistance technique in epidural anesthesia. in the porcine study, the rapid fall of the applied force, plunger displacement and fluid pressure, and the oral indication of the anesthesiologists were shown to be consistent with the loss-of-resistance. a model based on fluid leakage was developed to estimate the pressure from the force and displacement measurements, so that the pressure sensor could be omitted in human studies. in both human (in vivo) and porcine (in vitro) subjects, we observed that the ligamentum flavum is less amenable to saline injection than the interspinous ligament.
eye-gaze driven surgical workflow segmentation. in today's climate of clinical governance there is growing pressure on surgeons to demonstrate their competence, improve standards and reduce surgical errors. this paper presents a study on developing a novel eye-gaze driven technique for surgical assessment and workflow recovery. the proposed technique investigates the use of a parallel layer perceptor (plp) to automate the recognition of a key surgical step in a porcine laparoscopic cholecystectomy model. the classifier is eye-gaze contingent but combined with image based visual feature detection for improved system performance. experimental results show that by fusing image instrument likelihood measures, an overall classification accuracy of 75% is achieved.
quantifying heterogeneity in dynamic contrast-enhanced mri parameter maps. simple summary statistics of dynamic contrast-enhanced mri (dce-mri) parameter maps (e.g. the median) neglect the spatial arrangement of parameters, which appears to carry important diagnostic and prognostic information. this paper describes novel statistics that are sensitive to both parameter values and their spatial arrangement. binary objects are created from 3-d dce-mri parameter maps by "extruding" each voxel into a fourth dimension; the extrusion distance is proportional to the voxel's value. the following statistics are then computed on these 4-d binary objects: surface area, volume, surface area to volume ratio, and box counting (fractal) dimension. an experiment using 4 low and 5 high grade gliomas showed significant differences between the two grades for box counting dimension computed for extruded ve maps, surface area of extruded ktrans and ve maps and the volume of extruded ve maps (all p < 0.05). an experiment using 18 liver metastases imaged before and after treatment with a vascular endothelial growth factor (vegf) inhibitor showed significant differences for surface area to volume ratio computed for extruded ktrans and ve maps (p = 0.0013 and p = 0.045 respectively).
a novel 3d multi-scale lineness filter for vessel detection. the branching pattern and geometry of coronary microvessels are of high interest to understand and model the blood flow distribution and the processes of contrast invasion, ischemic changes and repair in the heart in detail. analysis is performed on high resolution, 3d volumes of the arterial microvasculature of entire goat hearts, which are acquired with an imaging cryomicrotome. multi-scale vessel detection is an important step required for a detailed quantitative analysis of the coronary microvasculature. based on visual inspection, the derived lineness filter shows promising results on real data and digital phantoms, on the way towards accurate computerized reconstructions of entire coronary trees. the novel lineness filter exploits the local first and second order multi-scale derivatives in order to give an intensity-independent response to line centers and to suppress unwanted responses to steep edges.
smt: split and merge tractography for dt-mri. diffusion tensor magnetic resonance imaging (dt-mri) based fiber tractography aims at reconstruction of the fiber network of brain. most commonly employed techniques for fiber tractography are based on the numerical integration of the principal diffusion directions. although these approaches generate intuitive and easy to interpret results, they are prone to cumulative errors and mostly discard the stochastic nature of dt-mri data. the proposed split & merge tractography (smt) technique aims at overcoming the drawbacks of fiber tractography by incorporating it with markov chain monte carlo techniques. smt is based on clustering diversely distributed short fiber tracts based on their inter-connectivity. smt also provides real-time interaction to adjust a user defined confidence level for clustering.
real-time spect and 2d ultrasound image registration. in this paper we present a technique for fully automatic, real-time 3d spect (single photon emitting computed tomography) and 2d ultrasound image registration. we use this technique in the context of kidney lesion diagnosis. our registration algorithm allows a physician to perform an ultrasound exam after a spect image has been acquired and see in real time the registration of both modalities. an automatic segmentation algorithm has been implemented in order to display in 3d the positions of the acquired us images with respect to the organs.
shape registration by simultaneously optimizing representation and transformation. this paper proposes a novel approach that achieves shape registration by optimizing shape representation and transformation simultaneously, which are modeled by a constrained gaussian mixture model (gmm) and a regularized thin plate spline respectively. the problem is formulated within a bayesian framework and solved by an expectation-maximum (em) algorithm. compared with the popular methods based on landmarks-sliding, its advantages include: (1) it can naturally deal with shapes of complex topologies and 3d dimension; (2) it is more robust against data noise; (3) the registration performance is better in terms of the generalization error of the resultant statistical shape model. these are demonstrated on both synthetic and biomedical shapes.
assessment of perceptual quality for gaze-contingent motion stabilization in robotic assisted minimally invasive surgery. with the increasing sophistication of surgical robots, the use of motion stabilisation for enhancing the performance of micro-surgical tasks is an actively pursued research topic. the use of mechanical stabilisation devices has certain advantages, in terms of both simplicity and consistency. the technique, however, can complicate the existing surgical workflow and interfere with an already crowded mis operated cavity. with the advent of reliable vision-based real-time and in situ in vivo techniques on 3d-deformation recovery, current effort is being directed towards the use of optical based techniques for achieving adaptive motion stabilisation. the purpose of this paper is to assess the effect of virtual stabilization on foveal/parafoveal vision during robotic assisted mis. detailed psychovisual experiments have been performed. results show that stabilisation of the whole visual field is not necessary and it is sufficient to perform accurate motion tracking and deformation compensation within a relatively small area that is directly under foveal vision. the results have also confirmed that under the current motion stabilisation regime, the deformation of the periphery does not affect the visual acuity and there is no indication of the deformation velocity of the periphery affecting foveal sensitivity. these findings are expected to have a direct implication on the future design of visual stabilisation methods for robotic assisted mis.
3-d analysis of cortical morphometry in differential diagnosis of parkinson's plus syndromes: mapping frontal lobe cortical atrophy in progressive supranuclear palsy patients. with the ability to study brain anatomy in vivo using magnetic resonance imaging, studies on regional brain atrophy suggest possible improvements for differential diagnosis of movement disorders with parkinsonian symptoms. in this study, we investigate effects of different parkinsonian syndromes on the cortical gray matter thickness and the geometric shape of the cerebral cortex. the study consists of a total of 24 patients with a diagnosis of probable progressive supranuclear palsy (psp), multiple systems atrophy (msa) or idiopathic parkinson's disease (ipd). we examine dense estimates of cortical gray matter thickness, sulcal depth, and measures of the curvature in a surface-based cortical morphometry analysis framework. group difference results indicate higher cortical atrophy rate in the frontal lobe in psp patients when compared to either msa or ipd. these findings are indicative of the potential use of routine mri and cortical morphometry in performing differential diagnosis in psp, msa and ipd.
longitudinal cortical registration for developing neonates. understanding the rapid evolution of cerebral cortical surfaces in developing neonates is essential in order to understand normal human brain development and to study anatomical abnormalities in preterm infants. several methods to model and align cortical surfaces for cross-sectional studies have been developed. however, the registration of cortical surfaces extracted from neonates across different gestational ages for longitudinal studies remains difficult because of significant cerebral growth. in this paper, we present an automatic cortex registration algorithm, based on surface relaxation followed by non-rigid surface registration. this technique aims to establish the longitudinal spatial correspondence of cerebral cortices for the developing brain in neonates. the algorithm has been tested on 5 neonates. each infant has been scanned at three different time points. quantitative results are obtained by propagating sulci across multiple gestational ages and computing the overlap ratios with manually established ground-truth.
rotational roadmapping: a new image-based navigation technique for the interventional room. for decades, conventional 2d-roadmaping has been the method of choice for image-based guidewire navigation during endovascular procedures. only recently have 3d-roadmapping techniques become available that are based on the acquisition and reconstruction of a 3d image of the vascular tree. in this paper, we present a new image-based navigation technique called roro (rotational roadmapping) that eliminates the guess-work inherent to the conventional 2d method, but does not require a 3d image. our preliminary clinical results show that there are situations in which roro is preferred over the existing two methods, thus demonstrating potential for filling a clinical niche and complementing the spectrum of available navigation tools.
error analysis of calibration materials on dual-energy mammography. dual-energy mammography can suppress the contrast between adipose and glandular tissues and improve the detectability of microcalcifications (mcs). in clinical dual-energy mammography, imaging object is human breast, while in calibration measurements, only phantoms of breast-tissue-equivalent material can be used. the composition and density differences between calibration materials and human breast bring the differences of linear attenuation coefficient which lead to the calculation errors in dual-energy imaging. in this paper, the magnitude of mc thickness error from calibration materials has been analyzed using a first-order propagation of error analysis. this analysis shows that the thickness error from calibration materials ranges from dozens to thousands of microns which can not be ignored when carrying out dual-energy calculations. the evaluation of several popular phantoms shows that it is of great importance to adopt the phantom materials approaching human breast most.
is a single energy functional sufficient? adaptive energy functionals and automatic initialization. energy functional minimization is an increasingly popular technique for image segmentation. however, it is far too commonly applied with hand-tuned parameters and initializations that have only been validated for a few images. fixing these parameters over a set of images assumes the same parameters are ideal for each image. we highlight the effects of varying the parameters and initialization on segmentation accuracy and propose a framework for attaining improved results using image adaptive parameters and initializations. we provide an analytical definition of optimal weights for functional terms through an examination of segmentation in the context of image manifolds, where nearby images on the manifold require similar parameters and similar initializations. our results validate that fixed parameters are insufficient in addressing the variability in real clinical data, that similar images require similar parameters, and demonstrate how these parameters correlate with the image manifold. we present significantly improved segmentations for synthetic images and a set of 470 clinical examples.
quantifying calcification in the lumbar aorta on x-ray images. in this paper we propose to use inpainting to estimate the severity of atherosclerotic plaques from x-ray projections. inpainting allows to "remove" the plaque and estimate what the background image for an uncalcified aorta would have looked like. a measure of plaque severity can then be derived by subtracting the inpainting from the original image. in contrast to the current standard of categorical calcification scoring from x-rays, our method estimates both the size and the density of calcified areas and provides a continuous severity score, thus allowing for measurement of more subtle differences. we discuss a class of smooth inpainting methods, compare their ability to reconstruct the original images, and compare the inpainting based calcification score to the conventional categorical score in a longitudinal study on 49 patients addressing correlations of the calcification scores with hypertension, a known cardiovascular risk factor.
functional near infrared spectroscopy in novice and expert surgeons - a manifold embedding approach. monitoring expertise development in surgery is likely to benefit from evaluations of cortical brain function. brain behaviour is dynamic and nonlinear. the aim of this paper is to evaluate the application of a nonlinear dimensionality reduction technique to enhance visualisation of multidimensional functional near infrared spectroscopy (fnirs) data. manifold embedding is applied to prefrontal haemodynamic signals obtained during a surgical knot tying task from a group of 62 healthy subjects with varying surgical expertise. the proposed method makes no assumption about the functionality of the data set and is shown to be capable of recovering the intrinsic low dimensional structure of in vivo brain data. after manifold embedding, earth mover's distance (emd) is used to quantify different patterns of cortical behaviour associated with surgical expertise and analyse the degree of inter-hemispheric channel pair symmetry.
a probabilistic model for haustral curvatures with applications to colon cad. among the many features used for classification in computer-aided detection (cad) systems targeting colonic polyps, those based on differences between the shapes of polyps and folds are most common. we introduce here an explicit parametric model for the haustra or colon wall. the proposed model captures the overall shape of the haustra and we use it to derive the probability distribution of features relevant to polyp detection. the usefulness of the model is demonstrated through its application to a colon cad algorithm.
predictive k-plsr myocardial contractility modeling with phase contrast mr velocity mapping. with the increasing versatility of cmr, further understanding of intrinsic contractility of the myocardium can be achieved by performing subject-specific modeling by integrating structural and functional information available. the recent introduction of the virtual tagging framework allows for visualization of the localized deformation of the myocardium based on phase contrast myocardial velocity mapping. the purpose of this study is to examine the use of a non-linear, kernel-partial least squares regression (k-plsr) predictive motion modeling scheme for the virtual tagging framework. the method allows for the derivation of a compact non-linear deformation model such that the entire deformation field can be predicted by a limited number of control points. when applied to virtual tagging, the technique can be used to predictively guide the mesh refinement based on the motion of the coarse grid, thus greatly reducing the search space and increasing the convergence speed of the algorithm. the effectiveness and numerical accuracy of the proposed technique are assessed with both numerically simulated data sets and in vivo phase contrast cmr velocity mapping from a group of 7 subjects. the technique presented has a distinct advantage over the conventional mesh refinement scheme and brings cmr myocardial contractility analysis closer to routine clinical practice.
on fiducial target registration error in the presence of anisotropic noise. we study the effect of anisotropic noise on target registration error (tre) by using a tracked and calibrated stylus tip as the fiducial registration application. we present a simple, efficient unscented kalman filter algorithm that is suitable for fiducial registration even with a small number of fiducials. we also derive an equation that predicts tre under anisotropic noise. the predicted tre values are shown to closely match the simulated tre values achieved using our ukf-based algorithm.
a probabilistic framework for tracking deformable soft tissue in minimally invasive surgery. the use of vision based algorithms in minimally invasive surgery has attracted significant attention in recent years due to its potential in providing in situ 3d tissue deformation recovery for intra-operative surgical guidance and robotic navigation. thus far, a large number of feature descriptors have been proposed in computer vision but direct application of these techniques to minimally invasive surgery has shown significant problems due to free-form tissue deformation and varying visual appearances of surgical scenes. this paper evaluates the current state-of-the-art feature descriptors in computer vision and outlines their respective performance issues when used for deformation tracking. a novel probabilistic framework for selecting the most discriminative descriptors is presented and a bayesian fusion method is used to boost the accuracy and temporal persistency of soft-tissue deformation tracking. the performance of the proposed method is evaluated with both simulated data with known ground truth, as well as in vivo video sequences recorded from robotic assisted mis procedures.
unbiased white matter atlas construction using diffusion tensor images. this paper describes an algorithm for unbiased construction of white matter (wm) atlases using full information available to diffusion tensor (dt) images. the key component of the proposed algorithm is a novel dt image registration method that leverages metrics comparing tensors as a whole and optimizes tensor orientation explicitly. the problem of unbiased atlas construction is formulated using the approach proposed by joshi et al., i.e., the unbiased wm atlas is determined by finding the mappings that best match the atlas to the images in the population and have the least amount of deformation. we show how the proposed registration algorithm can be adapted to approximately find the optimal atlas. the utility of the proposed approach is demonstrated by constructing a wm atlas of 13 subjects. the presented dt registration method is also compared to the approach of matching dt images by aligning their fractional anisotropy images using large-deformation image registration methods. our results suggest that using full tensor information can better align the orientations of wm fiber bundles.
a multiphysics simulation of a healthy and a diseased abdominal aorta. abdominal aortic aneurysm is a potentially life-threatening disease if not treated adequately. its pathogenesis is complex and multifactorial and is still not fully understood. many biochemical and biomechanical mechanisms have been identified as playing a role in the formation of aneurysms but it is as yet unclear what triggers the process. we investigated the role of the relevant biomechanical factors, in particular the wall shear stress and the intramural wall stress by simulating fluid structure interaction between the blood flow and the deforming arterial wall in a healthy abdominal aortic bifurcation, the preferred location of the disease. we then extended this study by introducing a hypothetical weakening of the aortic wall. intramural wall stress was considerably higher and wall shear stress considerably lower in this configuration, supporting the hypothesis that biomechanical aneurysmal growth factors are self-sustaining.
a point-wise quantification of asymmetry using deformation fields: application to the study of the crouzon mouse model. this paper introduces a novel approach to quantify asymmetry in each point of a surface. the measure is based on analysing displacement vectors resulting from nonrigid image registration. a symmetric atlas, generated from control subjects is registered to a given subject image. a comparison of the resulting displacement vectors on the left and right side of the symmetry plane, gives a point-wise measure of asymmetry. the asymmetry measure was applied to the study of crouzon syndrome using micro ct scans of genetically modified mice. crouzon syndrome is characterised by the premature fusion of cranial sutures, which gives rise to a highly asymmetric growth. quantification and localisation of this asymmetry is of high value with respect to surgery planning and treatment evaluation. using the proposed method, asymmetry was calculated in each point of the surface of crouzon mice and wild-type mice (controls). asymmetry appeared in similar regions for the two groups but the crouzon mice were found significantly more asymmetric. the localisation ability of the method was in good agreement with ratings from a clinical expert. validating the quantification ability is a less trivial task due to the lack of a gold standard. nevertheless, a comparison with a different, but less accurate measure of asymmetry revealed good correlation.
automatic centerline extraction of irregular tubular structures using probability volumes from multiphoton imaging. in this paper, we present a general framework for extracting 3d centerlines from volumetric datasets. unlike the majority of previous approaches, we do not require a prior segmentation of the volume nor we do assume any particular tubular shape. centerline extraction is performed using a morphology-guided level set model. our approach consists of: i) learning the structural patterns of a tubular-like object, and ii) estimating the centerline of a tubular object as the path with minimal cost with respect to outward flux in gray level images. such shortest path is found by solving the eikonal equation. we compare the performance of our method with existing approaches in synthetic, ct, and multiphoton 3d images, obtaining substantial improvements, especially in the case of irregular tubular objects.
a hierarchical unsupervised spectral clustering scheme for detection of prostate cancer from magnetic resonance spectroscopy (mrs). magnetic resonance spectroscopy (mrs) along with mri has emerged as a promising tool in diagnosis and potentially screening for prostate cancer. surprisingly little work, however, has been done in the area of automated quantitative analysis of mrs data for identifying likely cancerous areas in the prostate. in this paper we present a novel approach that integrates a manifold learning scheme (spectral clustering) with an unsupervised hierarchical clustering algorithm to identify spectra corresponding to cancer on prostate mrs. ground truth location for cancer on prostate was determined from the sextant location and maximum size of cancer available from the acrin database, from where a total of 14 mrs studies were obtained. the high dimensional information in the mr spectra is non linearly transformed to a low dimensional embedding space and via repeated clustering of the voxels in this space, non informative spectra are eliminated and only informative spectra retained. our scheme successfully identified mrs cancer voxels with sensitivity of 77.8%, false positive rate of 28.92%, and false negative rate of 20.88% on a total of 14 prostate mrs studies. qualitative results seem to suggest that our method has higher specificity compared to a popular scheme, z-score, routinely used for analysis of mrs data.
a bayesian 3d volume reconstruction for confocal micro-rotation cell imaging. recently, micro-rotation confocal microscopy has enabled the acquisition of a sequence of slices for a non-adherent living cells where the slices' positions are roughly controlled by a dielectric-field biological cage. the high resolution volume reconstruction requires then the integration of precise alignment of slice positions. we propose in the bayesian context, a new method combining both slice positioning and 3d volume reconstruction simultaneously, which leads naturally to an energy minimization procedure of a variational problem. an automatic calibration paradigm via maximum likelihood estimation (mle) principle is used for the relative hyper-parameter determination. we provide finally experimental comparison results on both conventional z-stack confocal images and 3d volume reconstruction from micro-rotation slices of the same non-adherent living cell to show its potential biomedical application.
non-parametric diffeomorphic image registration with the demons algorithm. we propose a non-parametric diffeomorphic image registration algorithm based on thirion's demons algorithm. the demons algorithm can be seen as an optimization procedure on the entire space of displacement fields. the main idea of our algorithm is to adapt this procedure to a space of diffeomorphic transformations. in contrast to many diffeomorphic registration algorithms, our solution is computationally efficient since in practice it only replaces an addition of free form deformations by a few compositions. our experiments show that in addition to being diffeomorphic, our algorithm provides results that are similar to the ones from the demons algorithm but with transformations that are much smoother and closer to the true ones in terms of jacobians.
clinical evaluation of a respiratory gated guidance system for liver punctures. we have previously proposed a computer guidance system for liver punctures designed for intubated (free breathing) patients. the lack of accuracy reported (1 cm) was mostly due to the breathing motion that was not taken into account. in this paper we modify our system to synchronise the guidance information on the expiratory phases of the patient and present an evaluation on 6 patients of our respiratory gated system. firstly, we show how a specific choice of patient allows us to rigorously and passively evaluate the system accuracy. secondly, we demonstrate that our system can provide a guidance information with an error below 5 mm during expiratory phases.
precision targeting of liver lesions with a needle-based soft tissue navigation system. in this study, we assessed the targeting precision of a previously reported needle-based soft tissue navigation system. for this purpose, we implanted 10 2-ml agar nodules into three pig livers as tumor models, and two of the authors used the navigation system to target the center of gravity of each nodule. in order to obtain a realistic setting, we mounted the livers onto a respiratory liver motion simulator that models the human body. for each targeting procedure, we simulated the liver biopsy workflow, consisting of four steps: preparation, trajectory planning, registration, and navigation. the lesions were successfully hit in all 20 trials. the final distance between the applicator tip and the center of gravity of the lesion was determined from control computed tomography (ct) scans and was 3.5 ± 1.1 mm on average. robust targeting precision of this order of magnitude would significantly improve the clinical treatment standard for various ct-guided minimally invasive interventions in the liver.
combinatorial optimization for electrode labeling of eeg caps. an important issue in electroencephalographiy (eeg) experiments is to measure accurately the three dimensional (3d) positions of the electrodes. we propose a system where these positions are automatically estimated from several images using computer vision techniques. yet, only a set of undifferentiated points are recovered this way and remains the problem of labeling them, i.e. of finding which electrode corresponds to each point. this paper proposes a fast and robust solution to this latter problem based on combinatorial optimization. we design a specific energy that we minimize with a modified version of the loopy belief propagation algorithm. experiments on real data show that, with our method, a manual labeling of two or three electrodes only is sufficient to get the complete labeling of a 64 electrodes cap in less than 10 seconds.
mean template for tensor-based morphometry using deformation tensors. tensor-based morphometry (tbm) studies anatomical differences between brain images statistically, to identify regions that differ between groups, over time, or correlate with cognitive or clinical measures. using a nonlinear registration algorithm, all images are mapped to a common space, and statistics are most commonly performed on the jacobian determinant (local expansion factor) of the deformation fields. in [14], it was shown that the detection sensitivity of the standard tbm approach could be increased by using the full deformation tensors in a multivariate statistical analysis. here we set out to improve the common space itself, by choosing the shape that minimizes a natural metric on the deformation tensors from that space to the population of control subjects. this method avoids statistical bias and should ease nonlinear registration of new subjects data to a template that is 'closest' to all subjects' anatomies. as deformation tensors are symmetric positive-definite matrices and do not form a vector space, all computations are performed in the log-euclidean framework [1]. the control brain b that is already the closest to 'average' is found. a gradient descent algorithm is then used to perform the minimization that iteratively deforms this template and obtains the mean shape. we apply our method to map the profile of anatomical differences in a dataset of 26 hiv/aids patients and 14 controls, via a log-euclidean hotelling's t2 test on the deformation tensors. these results are compared to the ones found using the 'best' control, b. statistics on both shapes are evaluated using cumulative distribution functions of the p- values in maps of inter-group differences.
rapid voxel classification methodology for interactive 3d medical image visualization. in many medical imaging scenarios, real-time high-quality anatomical data visualization and interaction is important to the physician for meaningful diagnosis 3d medical data and get timely feedback. unfortunately, it is still difficult to achieve an optimized balance between real-time artifact-free medical image volume rendering and interactive data classification. in this paper, we present a new segment-based post color-attenuated classification algorithm to address this problem. in addition, we apply an efficient numerical integration computation technique and take advantage of the symmetric storage format of the color lookup table generation matrix. when implemented within our gpu-based volume raycasting system, the new classification technique is about 100 times faster than the unaccelerated pre-integrated classification approach, while achieving the similar or even superior quality volume rendered image. in addition, we propose an objective measure of artifacts in rendered medical image based on high-frequency spatial image content.
bayesian tracking of tubular structures and its application to carotid arteries in cta. this paper presents a bayesian framework for tracking of tubular structures such as vessels. compared to conventional tracking schemes, its main advantage is its non-deterministic character, which strongly increases the robustness of the method. a key element of our approach is a dedicated observation model for tubular structures in regions with varying intensities. furthermore, we show how the tracking method can be used to obtain a probabilistic segmentation of the tracked tubular structure. the method has been applied to track the internal carotid artery from ct angiography data of 14 patients (28 carotids) through the skull base. this is a challenging problem, owing to the close proximity of bone, overlap in intensity values of lumen voxels and (partial volume) bone voxels, and the tortuous path of the vessels. the tracking was successful in 25 cases, and the extracted path were found to be close (< 1.0mm) to manually traced paths by two observers.
similarity metrics for groupwise non-rigid registration. the use of groupwise registration techniques for average atlas construction has been a growing area of research in recent years. one particularly challenging component of groupwise registration is finding scalable and effective groupwise similarity metrics; these do not always extend easily from pairwise metrics. this paper investigates possible choices of similarity metrics and additionally proposes a novel metric based on normalised mutual information. the described groupwise metrics are quantitatively evaluated on simulated and 3d mr datasets, and their performance compared to equivalent pairwise registration.
2d motion analysis of long axis cardiac tagged mri. the tracking and reconstruction of myocardial motion is critical to the diagnosis and treatment of heart disease. currently, little has been done for the analysis of motion in long axis (la) cardiac images. we propose a new fully automated motion reconstruction method for grid- tagged mri that combines gabor filters and deformable models. first, we use a gabor filter bank to generate the corresponding phase map in the myocardium and estimate the location of grid tag intersections. second, we use a non-rigid registration module driven by thin plate splines (tps) to generate a transformation function between tag intersections in two consecutive images. third, deformable spline models are initialized using fourier domain analysis and tracked during the cardiac cycle using the tps generated transformation function. the splines will then locally deform under the influence of gradient flow and image phase information. the final motion is decomposed into tangential and normal components corresponding to the local orientation of the heart wall. the new method has been tested on la phantoms and in vivo heart data, and its performance has been quantitatively validated. the results show that our method can reconstruct the motion field in la cardiac tagged mr images accurately and efficiently.
shape-based myocardial contractility analysis using multivariate outlier detection. this paper presents a new approach to regional myocardial contractility analysis based on inter-landmark motion (ilm) vectors and multivariate outlier detection. the proposed spatio-temporal representation is used to describe the coupled changes occurring at pairs of regions of the left ventricle, thus enabling the detection of geometrical and dynamic inconsistencies. multivariate tolerance regions are derived from training samples to describe the variability within the normal population using the ilm vectors. for new left ventricular datasets, outlier detection enables the localization of extreme ilm observations and the corresponding myocardial abnormalities. the framework is validated on a relatively large sample of 50 subjects and the results show promise in localization and visualization of regional left ventricular dysfunctions.
evaluation of shape-based normalization in the corpus callosum for white matter connectivity analysis. recently, concerns have been raised that the correspondences computed by volumetric registration within homogeneous structures are primarily driven by regularization priors that differ among algorithms. this paper explores the correspondence based on geometric models for one of those structures, mid-sagittal section of the corpus callosum (mscc), and compared the result with registration paradigms. we use geometric model called continuous medial representation (cm-rep) to normalize anatomical structures on the basis of medial geometry, and use features derived from diffusion tensor tractography for validation. we show that shape-based normalization aligns subregions of the mscc, defined by connectivity, more accurately than normalization based on volumetric registration. furthermore, shape-based normalization helps increase the statistical power of group analysis in an experiment where features derived from diffusion tensor tractography are compared between two cohorts. these results suggest that cm-rep is an appropriate tool for normalizing the mscc in white matter studies.
three-dimensional ultrasound mosaicing. the creation of 2d ultrasound mosaics is becoming a common clinical practice with a high clinical value. the next step coming along with the increasing availability of 2d array transducers is the creation of 3d mosaics. in the literature of ultrasound registration, the alignment of multiple images has not yet been addressed. therefore, we propose registration strategies, which are able to cope with problems arising by multiple image alignment. among others, we use simultaneous registration which urges the usage of multivariate similarity measures. in this paper, we propose alternative multivariate extensions based on a maximum likelihood framework. experimental results show the good performance of the proposed registration strategies and similarity measures.
variational guidewire tracking using phase congruency. we present a novel method to track a guidewire in cardiac x-ray video. using variational calculus, we derive differential equations that deform a spline, subject to intrinsic and extrinsic forces, so that it matches the image data, remains smooth, and preserves an a priori length. we analytically derive these equations from first principles, and show how they include tangential terms, which we include in our model. to address the poor contrast often observed in x-ray video, we propose using phase congruency as an image-based feature. experimental results demonstrate the success of the method in tracking guidewires in low contrast x-ray video.
efficient selection of the most similar image in a database for critical structures segmentation. radiotherapy planning needs accurate delineations of the critical structures. atlas-based segmentation has been shown to be very efficient to delineate brain structures [1]. however, the construction of an atlas from a dataset of images [2], particularly for the head and neck region, is very difficult due to the high variability of the images and can generate over-segmented structures in the atlas. to overcome this drawback, we present in this paper an alternative method to select as a template the image in a database that is the most similar to the patient to be segmented. this similarity is based on a distance between transformations. a major contribution is that we do not compute every patient-to-sample registration to find the most similar template, but only the registration of the patient towards an average image. this method has therefore the advantage of being computationally very efficient. we present a qualitative and quantitative comparison between the proposed method and a classical atlas-based segmentation method. this evaluation is performed on a subset of 45 patients using a leave-one-out method and shows a great improvement of the specificity of the results.
detecting mechanical abnormalities in prostate tissue using fe-based image registration. an image registration-based elastography algorithm is presented for assessing the stiffness of tissue regions inside the prostate for the purpose of detecting tumors. a 3d finite-element model of the prostate is built from ultrasound images and used to simulate the deformation of the prostate induced by a trus probe. to reconstruct the stiffness of tissues, their young's moduli are varied using powell's method so that the mutual information between a simulated and deformed image volume is maximized. the algorithm was validated using a gelatin prostate phantom embedded with a cylindrical inclusion that simulated a tumor. results from the phantom study showed that the technique could detect the increased stiffness of the simulated tumor with a reasonable accuracy.
automated extraction of lymph nodes from 3-d abdominal ct images using 3-d minimum directional difference filter. this paper presents a method for extracting lymph node regions from 3-d abdominal ct images using 3-d minimum directional difference filter. in the case of surgery of colonic cancer, resection of metastasis lesions is performed with resection of a primary lesion. lymph nodes are main route of metastasis and are quite important for deciding resection area. diagnosis of enlarged lymph nodes is quite important process for surgical planning. however, manual detection of enlarged lymph nodes on ct images is quite burden task. thus, development of lymph node detection process is very helpful for assisting such surgical planning task. although there are several report that present lymph node detection, these methods detect lymph nodes primary from pet images or detect in 2-d image processing way. there is no method that detects lymph nodes directly from 3-d images. the purpose of this paper is to show an automated method for detecting lymph nodes from 3-d abdominal ct images. this method employs a 3-d minimum directional difference filter for enhancing blob structures with suppressing line structures. after that, false positive regions caused by residua and vein are eliminated using several kinds of information such as size, blood vessels, air in the colon. we applied the proposed method to three cases of 3-d abdominal ct images. the experimental results showed that the proposed method could detect 57.0 % of enlarged lymph nodes with 58 fps per case.
quality-based registration and reconstruction of optical tomography volumes. ultramicroscopy, a novel optical tomographic imaging modality related to fluorescence microscopy, allows to acquire cross-sectional slices of small specially prepared biological samples with astounding quality and resolution. however, scattering of the fluorescence light causes the quality to decrease proportional to the depth of the currently imaged plane. scattering and beam thickness of the excitation laser light cause additional image degradation. we perform a physical simulation of the light scattering in order to define a quantitative function of image quality with respect to depth. this allows us to establish 3d-volumes of quality information in addition to the image data. volumes are acquired at different orientations of the sample, hence providing complementary regions of high quality. we propose an algorithm for rigid 3d-3d registration of these volumes incorporating voxel quality information, based onmaximizing an adapted linear correlation term. the quality ratio of the images is then used, along with the registration result, to create improved volumes of the imaged object. the methods are applied on acquisitions of a mouse brain and mouse embryo to create outstanding three-dimensional reconstructions.
real-time fusion of ultrasound and gamma probe for navigated localization of liver metastases. liver metastases are an advanced stage of several types of cancer, usually treated with surgery. intra-operative localization of these lesions is currently facilitated by intra-operative ultrasound (ious) and palpation, yielding a high rate of false positives due to benign abnormal regions. in this paper we present the integration of functional nuclear information from a gamma probe with ious, to provide a synchronized, real-time visualization that facilitates the detection of active metastases intra-operatively. we evaluate the system in an ex-vivo setup employing a group of physicians and medical technicians and show that the addition of functional imaging improves the accuracy of localizing and identifying malignant and benign lesions significantly. furthermore we are able to demonstrate that the inclusion of an advanced, augmented visualization provides more reliability and confidence on classifying these lesions in the presented evaluation setup.
endoscopic navigation for minimally invasive suturing. manipulating small objects such as needles, screws or plates inside the human body during minimally invasive surgery can be very difficult for less experienced surgeons, due to the loss of 3d depth perception. this paper presents an approach for tracking a suturing needle using a standard endoscope. the resulting pose information of the needle is then used to generate artificial 3d cues on the 2d screen to optimally support surgeons during tissue suturing. additionally, if an external tracking device is provided to report the endoscope's position, the suturing needle can be tracked in a hybrid fashion with submillimeter accuracy. finally, a visual navigation aid can be incorporated, if a 3d surface is intraoperatively reconstructed from video or registered from preoperative imaging.
improving temporal fidelity in blast mri reconstruction. studies of myocardial motion using magnetic resonance imaging usually require multiple breath holds and several methods have been proposed in order to reduce the scan time. rapid imaging using k-t blast has gained much attention with its high reduction factors and image quality. temporal smoothing, however, may reduce the accuracy when assessing cardiac function. in the present work, a modified reconstruction filter is proposed, that preserves more of the high temporal frequencies. artificial decimation of a fully sampled data set was used to evaluate the reconstruction filter. compared to the conventional k-t blast reconstruction, the modified filter produced images with sharper temporal delineation of the myocardial walls. quantitative analysis by means of regional velocity estimation showed that the modified reconstruction filter produced more accurate velocity estimations.
deformable 2d-3d registration of the pelvis with a limited field of view, using shape statistics. our paper summarizes experiments for measuring the accuracy of deformable 2d-3d registration between sets of simulated x-ray images (drr's) and a statistical shape model of the pelvis bones, which includes x-ray attenuation information ("density"). in many surgical scenarios, the images contain a truncated view of the pelvis anatomy. our work specifically addresses this problem by examining different selections of truncated views as target images. our atlas is derived by applying principal component analysis to a population of up to 110 instance shapes. the experiments measure the registration error with a large and truncated fov. a typical accuracy of about 2 mm is achieved in the 2d- 3d registration, compared with about 1.4 mm of an "optimal" 3d-3d registration.
landmark correspondence optimization for coupled surfaces. volumetric layers are often encountered in medical images. unlike solid structures, volumetric layers are characterized by double and nested bounding surfaces. it is expected that better statistical models can be built by utilizing the surface coupleness rather than simply applying the landmarking method on each of them separately. we propose an approach to optimizing the landmark correspondence on the coupled surfaces by minimizing the description length that incorporates local thickness gradient. the evaluations are performed on a set of 2-d synthetic close coupled contours and a set of real-world open surfaces, the skull vaults. compared with performing landmarking separately on the coupled surfaces, the proposed method constructs models that have better generalization ability and specificity.
design and preliminary accuracy studies of an mri-guided transrectal prostate intervention system. this paper reports a novel system for magnetic resonance imaging (mri) guided transrectal prostate interventions, such as needle biopsy, fiducial marker placement, and therapy delivery. the system utilizes a hybrid tracking method, comprised of passive fiducial tracking for initial registration and subsequent incremental motion measurement along the degrees of freedom using fiber-optical encoders and mechanical scales. targeting accuracy of the system is evaluated in prostate phantom experiments. achieved targeting accuracy and procedure times were found to compare favorably with existing systems using passive and active tracking methods. moreover, the portable design of the system using only standard mri image sequences and minimal custom scanner interfacing allows the system to be easily used on different mri scanners.
a mr compatible mechatronic system to facilitate magic angle experiments . when imaging tendons and cartilage in a mri scanner, an increase in signal intensity is observed when they are oriented at 55 degrees with respect to bo (the "magic angle"). there is a clear clinical importance for considering this effect as part of the diagnosis of orthopaedic and other injury. experimental studies of this phenomenon have been made harder by practical difficulties of tissue positioning and orientation in the confined environment of cylindrical scanners. an mri compatible mechatronic system has been developed to position a variety of limbs inside the field of view of the scanner, to be used as a diagnostic and research tool. it is actuated with a novel pneumatic motor comprised of a heavily geared down air turbine, and is controlled in a closed loop using standard optical encoders. mr compatibility is demonstrated as well as the results of preliminary trials used to image the achilles tendon of human volunteers at different orientations. a 4 to 13 fold increase in signal at the tendon is observed at the magic angle.
automatic whole heart segmentation in static magnetic resonance image volumes. we present a fully automatic segmentation algorithm for the whole heart (four chambers, left ventricular myocardium and trunks of the aorta, the pulmonary artery and the pulmonary veins) in cardiac mr image volumes with nearly isotropic voxel resolution, based on shape-constrained deformable models. after automatic model initialization and reorientation to the cardiac axes, we apply a multi-stage adaptation scheme with progressively increasing degrees of freedom. particular attention is paid to the calibration of the mr image intensities. detailed evaluation results for the various anatomical heart regions are presented on a database of 42 patients. on calibrated images, we obtain an average segmentation error of 0.76mm.
tract-based morphometry. multisubject statistical analyses of diffusion tensor images in regions of specific white matter tracts have commonly measured only the mean value of a scalar invariant such as the fractional anisotropy (fa), ignoring the spatial variation of fa along the length of fiber tracts. we propose to instead perform tract-based morphometry (tbm), or the statistical analysis of diffusion mri data in an anatomical tract-based coordinate system. we present a method for automatic generation of white matter tract arc length parameterizations, based on learning a fiber bundle model from tractography from multiple subjects. our tract-based coordinate system enables tbm for the detection of white matter differences in groups of subjects. we present example tbm results from a study of interhemispheric differences in fa.
fiducial-free registration procedure for navigated bronchoscopy. navigated bronchoscopy has been developed by various groups within the last decades. systems based on ct data and electromagnetic tracking enable the visualization of the position and orientation of the bronchoscope, forceps, and biopsy tools within ct data. therefore registration between the tracking space and the ct volume is required. standard procedures are based on point-based registration methods that require selecting corresponding natural landmarks in both coordinate systems by the examiner. we developed a novel algorithm for a fully automatic registration procedure in navigated bronchoscopy based on the trajectory recorded during routine examination of the airways at the beginning of an intervention. the proposed system provides advantages in terms of an unchanged medical workflow and high accuracy. we compared the novel method with point-based and icp-based registration. experiments demonstrate that the novel method transforms up to 97% of tracking points inside the segmented airways, which was the best performance compared to the other methods.
analysis of deformation of the human ear and canal caused by mandibular movement. many hearing aid users experience physical discomfort when wearing their device. the main contributor to this problem is believed to be deformation of the ear and ear canal caused by movement of the mandible. physical discomfort results from added pressure on soft tissue areas in the ear. identifying features that can predict potential deformation is therefore important for identifying problematic cases in advance. a study on the physical deformation of the human ear and canal due to movement of the mandible is presented. the study is based on laser scannings of 30 pairs of ear impressions from 9 female and 21 male subjects. two impressions have been taken from each subject, one with open mouth, and one with the mouth closed. all impressions are registered using non-rigid surface registration and a shape model is built. from each pair of impressions a deformation field is generated and propagated to the shape model, enabling the building of a deformation model in the reference frame of the shape model. a relationship between the two models is established, showing that the shape variation can explain approximately 50% of the variation in the deformation model. an hypothesis test for significance of the deformations for each deformation field reveals that all subjects have significant deformation at tragus and in the canal. furthermore, a relation between the magnitude of the deformation and the gender of the subject is demonstrated. the results are successfully validated by comparing the outcome to the anatomy by using a single set of high resolution histological sectionings of the region of interest.
cell population tracking and lineage construction with spatiotemporal context. automated visual-tracking of cell populations in vitro using phase contrast time-lapse microscopy is vital for quantitative, systematic and high-throughput measurements of cell behaviors. these measurements include the spatiotemporal quantification of migration, mitosis, apoptosis, and cell lineage. this paper presents an automated cell tracking system that can simultaneously track and analyze thousands of cells. the system performs tracking by cycling through frame-by-frame track compilation and spatiotemporal track linking, combining the power of two tracking paradigms. we applied the system to a range of cell populations including adult stem cells. the system achieved tracking accuracies in the range of 83.8%-92.5%, outperforming previous work by up to 8%.
revisiting the evaluation of segmentation results: introducing confidence maps. we introduce a novel framework, called confidence maps estimating true segmentations (comets), to store segmentation references for medical images, combine multiple references, and measure the discrepancy between a segmented object and a reference. the core feature is the use of efficiently encoded confidence maps, which reflect the local variations of blur and the presence of nearby objects. local confidence values are defined from expert user input, and used to define a new discrepancy error measure, aimed to be directly interpreted quantitatively and qualitatively. we illustrate the use of this framework to compare different segmentation methods and tune a method's parameters.
non-local means variants for denoising of diffusion-weighted and diffusion tensor mri. diffusion tensor imaging (dt-mri) is very sensitive to corrupting noise due to the non linear relationship between the diffusion-weighted image intensities (dw-mri) and the resulting diffusion tensor. denoising is a crucial step to increase the quality of the estimated tensor field. this enhanced quality allows for a better quantification and a better image interpretation. the methods proposed in this paper are based on the non-local (nl) means algorithm. this approach uses the natural redundancy of information in images to remove the noise. we introduce three variations of the nl-means algorithms adapted to dw-mri and to dt-mri. experiments were carried out on a set of 12 diffusion-weighted images (dw-mri) of the same subject. the results show that the intensity based nl-means approaches give better results in the context of dt-mri than other classical denoising methods, such as gaussian smoothing, anisotropic diffusion and total variation.
simulation and fully automatic multimodal registration of medical ultrasound. the fusion of 3d freehand ultrasound with ct and cta has benefits for a variety of clinical applications, however a lot of manual work is usually required for correct registration. we developed new methods that allow one to simulate medical ultrasound from ct in real-time, reproducing the majority of ultrasonic imaging effects. the second novelty is a robust similarity measure that assesses the correlation of a combination of multiple signals extracted from ct with ultrasound, without knowing the influence of each signal. this serves as the foundation of a fully automatic registration, which aligns a freehand ultrasound sweep with the corresponding 3d modality using a rigid or an affine transformation model, without any manual interaction. we also present the used initialization, global and local parameter optimization schemes, and validation on abdominal cta and ultrasound imaging of 10 patients.
sources of variability in meg. this paper investigates and characterizes sources of variability in meg signals in multi-site, multi-subject studies. understanding these sources will help to develop efficient strategies for comparing and pooling data across repetitions of an experiment, across subjects, and across sites. in this work, we investigated somatosensory meg data collected at three different sites and applied variance component analysis and nonparametric kl divergence analysis in order to characterize the sources of variability. our analysis showed that inter-subject differences are the biggest factor in the signal variability. we demonstrated that the timing of the deflections is very consistent in the early somatosensory response, which justifies a direct comparison of deflection peak times acquired from different visits, subjects, and systems. compared with deflection peak times, deflection magnitudes have larger variation across sites; modeling of this variability is necessary for data pooling.
prostate implant reconstruction with discrete tomography. we developed a discrete tomography method for prostate implant reconstructions using only a limited number of x-ray projection images. a 3d voxel volume is reconstructed by back-projection and using distance maps generated from the projection images. the true seed locations are extracted from the voxel volume while false positive seeds are eliminated using a novel optimal geometry coverage model. the attractive feature of our method is that it does not require exact seed segmentation of the x-ray images and it yields near 100% correct reconstruction from only six images with an average reconstruction accuracy of 0.86 mm (std=0.46mm).
automatic segmentation of articular cartilage in magnetic resonance images of the knee. to perform cartilage quantitative analysis requires the accurate segmentation of each individual cartilage. in this paper we present a model based scheme that can automatically and accurately segment each individual cartilage in healthy knees from a clinical mr sequence (fat suppressed spoiled gradient recall). this scheme consists of three stages; the automatic segmentation of the bones, the extraction of the bone-cartilage interfaces (bci) and segmentation of the cartilages. the bone segmentation is performed using three-dimensional active shape models. the bci is extracted using image information and prior knowledge about the likelihood of each point belonging to the interface. a cartilage thickness model then provides constraints and regularizes the cartilage segmentation performed from the bci. the accuracy and robustness of the approach was experimentally validated, with (patellar, tibial and femoral) cartilage segmentations having a median dsc of (0.870, 0.855, 0.870), performing significantly better than non-rigid registration (0.787, 0.814, 0.795). the total cartilage segmentation had an average dsc of (0.891), close to the (0.896) obtained using a semi-automatic watershed algorithm. the error in quantitative volume and thickness measures was (8.29, 4.94, 5.56)% and (0.19, 0.33, 0.10) mm respectively.
quantifying effect-specific mammographic density. a methodology is introduced for the automated assessment of structural changes of breast tissue in mammograms. it employs a generic machine learning framework and provides objective breast density measures quantifying the specific biological effects of interest. in several illustrative experiments on data from a clinical trial, it is shown that the proposed method can quantify effects caused by hormone replacement therapy (hrt) at least as good as standard methods. most interestingly, the separation of subpopulations using our approach is considerably better than the best alternative, which is interactive. moreover, the automated method is capable of detecting age effects where standard methodologies completely fail.
vessel and intracranial aneurysm segmentation using multi-range filters and local variances. segmentation of vessels and brain aneurysms on non-invasive and flow-sensitive phase contrast magnetic resonance angiographic (pcmra) images is essential in the detection of vascular diseases, in particular, intracranial aneurysms. in this paper, we devise a novel method based on multi-range filters and local variances to perform segmentation of vessels and intracranial aneurysms on pcmra images. the proposed method is validated and compared using a synthetic and numerical image volume and four clinical cases. it is experimentally shown that the proposed method is capable of segmenting vessels and aneurysms with various sizes on pcmra images.
pca-based magnetic field modeling : application for on-line mr temperature monitoring. magnetic resonance (mr) temperature mapping can be used to monitor temperature changes during minimally invasive thermal therapies. however, mr-thermometry contains artefacts caused by phase errors induced by organ motion in inhomogeneous magnetic fields. this paper proposes a novel correction strategy based on a principal component analysis (pca) to estimate magnetic field perturbation assuming a linear magnetic field variation with organ displacement. the correction method described in this paper consists of two steps: a magnetic field perturbation model is computed in a learning step; subsequently, during the intervention, this model is used to reconstruct the magnetic field perturbation corresponding to the actual organ position which in turns allow computation of motion corrected thermal maps.
classifier selection strategies for label fusion using large atlas databases. structural segmentations of brain mri can be generated by propagating manually labelled atlas images from a repository to a query subject and combining them. this method has been shown to be robust, consistent and increasingly accurate with increasing numbers of classifiers. it outperforms standard atlas-based segmentation but suffers, however, from problems of scale when the number of atlases is large. for a large repository and a particular query subject, using a selection strategy to identify good classifiers is one way to address problems of scale. this work presents and compares different classifier selection strategies which are applied to a group of 275 subjects with manually labelled brain mr images. we approximate an upper limit for the accuracy or overlap that can be achieved for a particular structure in a given subject and compare this with the accuracy obtained using classifier selection. the accuracy of different classifier selection strategies are also rated against the distribution of overlaps generated by random groups of classifiers.
tissue characterization using fractal dimension of high frequency ultrasound rf time series. this paper is the first report on the analysis of ultrasound rf echo time series acquired using high frequency ultrasound. we show that variations in the intensity of one sample of rf echo over time is correlated with tissue microstructure. to form the rf time series, a high frequency probe and a tissue sample were fixed in position and rf signals backscattered from the tissue were continuously recorded. the fractal dimension of rf time series was used as a feature for tissue classification. feature values acquired from different areas of one tissue type were statistically similar. for animal tissues with different cellular microstructure, we successfully used the fractal dimension of rf time series to distinguish segments as small as 20 microns with accuracies as high as 98%. the results of this study demonstrate that the analysis of rf time series is a promising approach for distinguishing tissue types with different cellular microstructure.
orthopedics surgery trainer with ppu-accelerated blood and tissue simulation. this paper presents a novel orthopedics surgery training system with both the components for modeling as well as simulating the deformation and visualization in an efficient way. by employing techniques such as optimization, segmentation and center line extraction, the modeling of deformable model can be completed with minimal manual involvement. the novel trainer can simulate rigid body, soft tissue and blood with state-of-the-art techniques, so that convincing deformation and realistic bleeding can be achieved. more important, newly released physics processing unit (ppu) is adopted to tackle the high requirement for physics related computations. experiment shows that the acceleration gain from ppu is significant for maintaining interactive frame rate under a complex surgical environments of orthopedics surgery.
improved statistical tre model when using a reference frame. target registration error (tre) refers to the uncertainty in localizing a point of interest after a point-based registration is performed. common in medical image registration, the metric is typically represented as a root-mean-square statistic. in the late 1990s, a statistical model was developed based on the rigid body definition of the fiducial markers and the localization error associated in measuring the fiducials. the statistical model assumed that the fiducial localizer error was isotropic, but recently the model was reworked to handle anisotropic fiducial localizer error (fle). in image guided surgery, the statistical model is used to predict the surgical tool tip tracking accuracy associated with optical spatial measurement systems for which anisotropic fle models are required. however, optical tracking systems often track the surgical tools relative to a patient based reference tool. here the formulation for modeling the tre of a surgical probe relative to a reference frame is developed mathematically and evaluated using a monte carlo simulation. the effectiveness of the statistical model is directly related to the fle model, the fiducial marker design and the distance from centroid to target.
automated model-based rib cage segmentation and labeling in ct images. we present a new model-based approach for an automated labeling and segmentation of the rib cage in chest ct scans. a mean rib cage model including a complete vertebral column is created out of 29 data sets. we developed a ray search based procedure for rib cage detection and initial model pose. after positioning the model, it was adapted to 18 unseen ct data. in 16 out of 18 data sets, detection, labeling, and segmentation succeeded with a mean segmentation error of less than 1.3 mm between true and detected object surface. in one case the rib cage detection failed, in another case the automated labeling.
population based analysis of directional information in serial deformation tensor morphometry. deformation morphometry provides a sensitive approach to detecting and mapping subtle volume changes in the brain. population based analyses of this data have been used successfully to detect characteristic changes in different neurodegenerative conditions. however, most studies have been limited to statistical mapping of the scalar volume change at each point in the brain, by evaluating the determinant of the jacobian of the deformation field. in this paper we describe an approach to spatial normalisation and analysis of the full deformation tensor. the approach employs a spatial relocation and reorientation of tensors of each subject. using the assumption of small changes, we use a linear modeling of effects of clinical variables on each deformation tensor component across a population. we illustrate the use of this approach by examining the pattern of significance and orientation of the volume change effects in recovery from alcohol abuse. results show new local structure which was not apparent in the analysis of scalar volume changes.
precise estimation of postoperative cup alignment from single standard x-ray radiograph with gonadal shielding. this paper addresses the problem of estimating postoperative cup alignment from single standard x-ray radiograph with gonadal shielding. the widely used procedure of evaluation of cup orientation following total hip arthroplasty using single standard anteroposterior radiograph is known inaccurate, largely due to the wide variability in individual pelvic position relative to x-ray plate. 2d-3d image registration methods have been introduced to estimate the rigid transformation between a preoperative ct volume and postoperative radiograph(s) for an accurate estimation of the postoperative cup alignment relative to an anatomical reference extracted from the ct data. however, these methods require either multiple radiographs or a radiograph-specific calibration, both of which are not avaiable for most retrospective studies. furthermore, these methods were only evaluated on x-ray radiograph(s) without gonadal shielding. in this paper, we propose to use a hybrid 2d-3d registration scheme combining an iterative landmark-to-ray registration with a 2d-3d intensity-based registration to estimate the rigid transfromation for a precise estimation of cup alignment. quantitative and qualitative results evaluated on clinical and cadaveric datasets are given which indicate the validity of our approach.
deformable density matching for 3d non-rigid registration of shapes. there exists a large body of literature on shape matching and registration in medical image analysis. however, most of the previous work is focused on matching particular sets of features--point-sets, lines, curves and surfaces. in this work, we forsake specific geometric shape representations and instead seek probabilistic representations-- specifically gaussian mixture models--of shapes. we evaluate a closed-form distance between two probabilistic shape representations for the general case where the mixture models differ in variance and the number of components. we then cast non-rigid registration as a deformable density matching problem. in our approach, we take one mixture density onto another by deforming the component centroids via a thin-plate spline (tps) and also minimizing the distance with respect to the variance parameters. we validate our approach on synthetic and 3d arterial tree data and evaluate it on 3d hippocampal shapes.
live-vessel: extending livewire for simultaneous extraction of optimal medial and boundary paths in vascular images. this paper incorporates multiscale vesselness filtering into the livewire framework to simultaneously compute optimal medial axes and boundaries in vascular images. to this end, we extend the existing 2d graph search to 3d space to optimize not only for spatial variables (x, y), but also for radius values r at each node. in addition, we minimize change for both scale and the smallest principle curvature and incorporate vessel boundary evidence in our optimization. when compared to two sets of drive expert manual tracings, our proposed technique reduced the overall segmentation task time by 68.2%, had a similarity ratio of 0.772 (0.775 between manual), and was 98.2% reproducible.
towards intra-operative 3d nuclear imaging: reconstruction of 3d radioactive distributions using tracked gamma probes. nuclear medicine imaging modalities assist commonly in surgical guidance given their functional nature. however, when used in the operating room they present limitations. pre-operative tomographic 3d imaging can only serve as a vague guidance intra-operatively, due to movement, deformation and changes in anatomy since the time of imaging, while standard intra-operative nuclear measurements are limited to 1d or (in some cases) 2d images with no depth information. to resolve this problem we propose the synchronized acquisition of position, orientation and readings of gamma probes intra-operatively to reconstruct a 3d activity volume. in contrast to conventional emission tomography, here, in a first proof-of-concept, the reconstruction succeeds without requiring symmetry in the positions and angles of acquisition, which allows greater flexibility. we present our results in phantom experiments for sentinel node lymph node localization. the results indicate that 3d intra-operative nuclear images can be generated in such a setup up to an accuracy equivalent to conventional spect systems. this technology has the potential to advance standard procedures towards intra-operative 3d nuclear imaging and offers a novel approach for robust and precise localization of functional information to facilitate less invasive, image-guided surgery.
a new method for spherical object detection and its application to computer aided detection of pulmonary nodules in ct images. a novel method called local shape controlled voting has been developed for spherical object detection in 3d voxel images. by introducing local shape properties into the voting procedure of normal overlap, the proposed method improves the capability of differentiating spherical objects from other structures, as the normal overlap technique only measures the 'density' of normal overlapping, while how the normals are distributed in 3d is not discovered. the proposed method was applied to computer aided detection of pulmonary nodules based on helical ct images. experiments showed that this method attained a better performance compared to the original normal overlap technique.
using statistical shape analysis for the determination of uterine deformation states during hydrometra. a fundamental prerequisite of hysteroscopy is the proper distension of the uterine cavity with a fluid, also known as hydrometra. for a virtual reality based simulation of hysteroscopy, the uterus deformation process due to different pressure settings has to be modeled. in previous work we have introduced a hybrid method, which relies on precomputed deformation states to derive the hydrometra changes during runtime. however, new offline computations were necessary for every newly introduced organ mesh. this is not viable if a new surgical scene is to be generated for every training session. therefore, we include the deformation states during hydrometra into our previously developed statistical shape model for undeformed organ instances. this allows deriving the hydrometra steps together with new undeformed uterus meshes. these can then be used during the interactive simulation for predicting uterus deformation without time-intensive precomputation steps.
real-time synthesis of image slices in deformed tissue from nominal volume images. this paper presents a fast image synthesis procedure for elastic volumes under deformation. given the node displacements of a mesh and the 3d image voxel data of an undeformed volume, the method maps the image plane pixels to be synthesized from the deformed configuration back to the nominal pre-deformed configuration, where the pixel intensities are obtained easily through interpolation in the regular-grid structure of the voxel volume. for smooth interpolation, this mapping requires the identification of the mesh element enclosing each image pixel. to accelerate this point location procedure, a fast method of marking the image pixels is employed by finding the intersection of the mesh and the image, and marking this intersection on the image pixels using bresenham's line drawing algorithm. a deformable tissue phantom was constructed, it was modeled using the finite element method, and its 3d ultrasound volume was acquired in its undeformed state. actual b-mode images of the phantom under deformation by the ultrasound probe were then compared with the corresponding synthesized images simulated for the same deformations. results show that realistic images can be synthesized in real-time using the proposed technique.
object localization based on markov random fields and symmetry interest points. we present an approach to detect anatomical structures by configurations of interest points, from a single example image. the representation of the configuration is based on markov random fields, and the detection is performed in a single iteration by the max-sum algorithm. instead of sequentially matching pairs of interest points, the method takes the entire set of points, their local descriptors and the spatial configuration into account to find an optimal mapping of modeled object to target image. the image information is captured by symmetry-based interest points and local descriptors derived from gradient vector flow. experimental results are reported for two data-sets showing the applicability to complex medical data.
small animal radiation research platform: imaging, mechanics, control and calibration. in cancer research, well characterized small animal models of human cancer, such as transgenic mice, have greatly accelerated the pace of development of cancer treatments. the goal of the small animal radiation research platform (sarrp) is to make those same models available for the development and evaluation of novel radiation therapies. in combination with advanced imaging methods, small animal research allows detailed study of biological processes, disease progression, and response to therapy, with the potential to provide a natural bridge to the clinical environment. the sarrp will realistically model human radiation treatment methods in standard animal models. in this paper, we describe the mechanical and control structure of the system. this system requires accurate calibration of the x-ray beam for both imaging and radiation treatment, which is presented in detail in the paper.
alignment of large image series using cubic b-splines tessellation: application to transmission electron microscopy data. 3d reconstruction from serial 2d microscopy images depends on non-linear alignment of serial sections. for some structures, such as the neuronal circuitry of the brain, very large images at very high resolution are necessary to permit reconstruction. these very large images prevent the direct use of classical registration methods. we propose in this work a method to deal with the non-linear alignment of arbitrarily large 2d images using the finite support properties of cubic b-splines. after initial affine alignment, each large image is split into a grid of smaller overlapping sub-images, which are individually registered using cubic b-splines transformations. inside the overlapping regions between neighboring sub-images, the coefficients of the knots controlling the b-splines deformations are blended, to create a virtual large grid of knots for the whole image. the sub-images are resampled individually, using the new coefficients, and assembled together into a final large aligned image. we evaluated the method on a series of large transmission electron microscopy images and our results indicate significant improvements compared to both manual and affine alignment.
probabilistic fiber tracking using particle filtering. this paper presents a novel and fast probabilistic method for white matter fiber tracking from diffusion weighted mri (dwi). we formulate fiber tracking on a nonlinear state space model which is able to capture both smoothness regularity of fibers and uncertainties of the local fiber orientations due to noise and partial volume effects. the global tracking model is implemented using particle filtering, which allows us to recursively compute the posterior distribution of the potential fibers. the fiber orientation distribution is theoretically formulated for prolate and oblate tensors separately. fast and efficient sampling is realised using the von mises-fisher distribution on unit spheres. given a seed point, the method is able to rapidly locate the global optimal fiber and also provide a connectivity map. the proposed method is demonstrated on a brain dataset.
signal lmmse estimation from multiple samples in mri and dt-mri. a method to estimate the magnitude mr data from several noisy samples is presented. it is based on the linear minimum mean squared error (lmmse) estimator for the rician noise model when several scanning repetitions are available. this method gives a closed-form analytical solution that takes into account the probability distribution of the data as well as the existing level of noise, showing a better performance than methods such as the average or the median.
prior knowledge driven multiscale segmentation of brain mri. we present a novel automatic multiscale algorithm applied to segmentation of anatomical structures in brain mri. the algorithm which is derived from algebraic multigrid, uses a graph representation of the image and performs a coarsening process that produces a full hierarchy of segments. our main contribution is the incorporation of prior knowledge information into the multiscale framework through a bayesian formulation. the probabilistic information is based on an atlas prior and on a likelihood function estimated from a manually labeled training set. the significance of our new approach is that the constructed pyramid, reflects the prior knowledge formulated. this leads to an accurate and efficient methodology for detection of various anatomical structures simultaneously. quantitative validation results on gold standard mri show the benefit of our approach.
a study of hippocampal shape difference between genders by efficient hypothesis test and discriminative deformation. hypothesis testing is an important way to detect the statistical difference between two populations. in this paper, we use the fisher permutation and bootstrap tests to differentiate hippocampal shape between genders. these methods are preferred to traditional hypothesis tests which impose assumptions on the distribution of the samples. an efficient algorithm is adopted to rapidly perform the exact tests. we extend this algorithm to multivariate data by projecting the original data onto an "informative direction" to generate a scalar test statistic. this "informative direction" is found to preserve the original discriminative information. this direction is further used in this paper to isolate the discriminative shape difference between classes from the individual variability, achieving a visualization of shape discrepancy.
spatiotemporal normalization for longitudinal analysis of gray matter atrophy in frontotemporal dementia. we present a unified method, based on symmetric diffeomorphisms, for studying longitudinal neurodegeneration. our method first uses symmetric diffeomorphic normalization to find a spatiotemporal parameterization of an individual's image time series. the second step involves mapping a representative image or set of images from the time series into an optimal template space. the template mapping is then combined with the intrasubject spatiotemporal map to enable pairwise statistical tests to be performed on a population of normalized time series images. here, we apply this longitudinal analysis protocol to study the gray matter atrophy patterns induced by frontotemporal dementia (ftd). we sample our normalized spatiotemporal maps at baseline (time zero) and time one year to generate an annualized atrophy map (aam) that estimates the annual effect of ftd. this spatiotemporal normalization enables us to locate neuroanatomical regions that consistently undergo significant annual gray matter atrophy across the population. we found the majority of annual atrophy to occur in the frontal and temporal lobes in our population of 20 subjects. we also found significant effects in the hippocampus, insula and cingulate gyrus. our novel results, significant at p < 0.05 after false discovery rate correction, are represented in local template space but also assigned talairach coordinates and brodmann and anatomical automatic labeling (aal) labels. this paper shows the statistical power of symmetric diffeomorphic normalization for performing deformation-based studies of longitudinal atrophy.
multi-criteria trajectory planning for hepatic radiofrequency ablation. in this paper, we propose a method based on multiple criteria to assist physicians in planning percutaneous rfa on liver. we explain how we extracted information from literature and interviews with radiologists, and formalized them into geometric constraints. we expose then our method to compute the most suitable needle insertion in two steps: computation of authorized insertion zones and multi-criteria optimization of the trajectory within this zones. we focus on the combination of the criteria to optimize and on the optimization step.
effectiveness of the finite impulse response model in content-based fmri image retrieval. the thresholded t-map produced by the general linear model (glm) gives an effective summary of activation patterns in functional brain images and is widely used for feature selection in fmri related classification tasks. as part of a project to build content-based retrieval systems for fmri images, we have investigated ways to make glm more adaptive and more robust in dealing with fmri data from widely differing experiments. in this paper we report on exploration of the finite impulse response model, combined with multiple linear regression, to identify the "locally best hemodynamic response function (hrf) for each voxel" and to simultaneously estimate activation levels corresponding to several stimulus conditions. the goal is to develop a procedure for processing datasets of varying natures. our experiments show that finite impulse response (fir) models with a smoothing factor produce better retrieval performance than does the canonical double gamma hrf in terms of retrieval accuracy.
customised cytoarchitectonic probability maps using deformable registration: primary auditory cortex. a novel method is presented for creating a probability map from histologically defined cytoarchitectonic data, customised for the anatomy of individual fmri volunteers. postmortem structural and cytoarchitectonic information from a published dataset is combined with high resolution structural mr images using deformable registration of a region of interest. in this paper, we have targeted the three subareas of the primary auditory cortex (located on heschl's gyrus); however, the method could be applied to any other cytoarchitectonic region. the resulting probability maps show a significantly higher overlap than previously generated maps using the same cytoarchitectonic data, and more accurately span the macroanatomical structure of the auditory cortex. this improvement indicates a high potential for spatially accurate fmri analysis, allowing more reliable correlation between anatomical structure and function. we validate the approach using fmri data from nine individuals, taken from a published dataset. we compare activation for stimuli evoking a pitch percept to activation for acoustically matched noise, and demonstrate that the primary auditory cortex (te1.0) and the lateral region te1.2 are sensitive to pitch, whereas te1.1 is not.
towards 3d ultrasound image based soft tissue tracking: a transrectal ultrasound prostate image alignment system. the emergence of real-time 3d ultrasound (us) makes it possible to consider image-based tracking of subcutaneous soft tissue targets for computer guided diagnosis and therapy. we propose a 3d transrectal us based tracking system for precise prostate biopsy sample localisation. the aim is to improve sample distribution, to enable targeting of unsampled regions for repeated biopsies, and to make post-interventional quality controls possible. since the patient is not immobilized, since the prostate is mobile and due to the fact that probe movements are only constrained by the rectum during biopsy acquisition, the tracking system must be able to estimate rigid transformations that are beyond the capture range of common image similarity measures. we propose a fast and robust multiresolution attribute-vector registration approach that combines global and local optimization methods to solve this problem. global optimization is performed on a probe movement model that reduces the dimensionality of the search space and thus renders optimization efficient. the method was tested on 237 prostate volumes acquired from 14 different patients for 3d to 3d and 3d to orthogonal 2d slices registration. the 3d-3d version of the algorithm converged correctly in 96.7% of all cases in 6.5s with an accuracy of 1.41mm (r.m.s.) and 3.84mm (max). the 3d to slices method yielded a success rate of 88.9% in 2.3s with an accuracy of 1.37mm (r.m.s.) and 4.3mm (max).
accuracy assessment of global and local atrophy measurement techniques with realistic simulated longitudinal data. the main goal of this work was to assess the accuracy of several well-known methods which provide global (bsi and siena) or local (jacobian integration) estimates of longitudinal atrophy in brain structures using magnetic resonance images. for that purpose, we have generated realistic simulated images which mimic the patterns of change obtained from a cohort of 19 real controls and 27 probable alzheimer's disease patients. siena and bsi results correlate very well with gold standard data (bsi mean absolute error < 0.29%; siena < 0.44%). jacobian integration was guided by both fluid and ffd-based registration techniques and resulting deformation fields and associated jacobians were compared, region by region, with gold standard ones. the ffd registration technique provided more satisfactory results than the fluid one. mean absolute error differences between volume changes given by the ffd-based technique and the gold standard were: sulcal csf < 2.49%; lateral ventricles < 2.25%; brain < 0.36%; hippocampi < 1.42%.
shape analysis with overcomplete spherical wavelets. in this paper, we explore the use of over-complete spherical wavelets in shape analysis of closed 2d surfaces. previous work has demonstrated, theoretically and practically, the advantages of over-complete over bi-orthogonal spherical wavelets. here we present a detailed formulation of over-complete wavelets, as well as shape analysis experiments of cortical folding development using them. our experiments verify in a quantitative fashion existing qualitative theories of neuro-anatomical development. furthermore, the experiments reveal novel insights into neuro-anatomical development not previously documented.
inter-subject modelling of liver deformation during radiation therapy. this paper presents a statistical model of the liver deformation that occurs in addition to the quasi-periodic respiratory motion. having an elastic but still compact model of this variability is an important step towards reliable targeting in radiation therapy. to build this model, the deformation of the liver at exhalation was determined for 12 volunteers over roughly one hour using 4dmri and subsequent non-rigid registration. the correspondence between subjects was established based on mechanically relevant landmarks on the liver surface. leave-one-out experiments were performed to evaluate the accuracy in predicting the liver deformation from partial information, such as a point tracked by ultrasound imaging. already predictions from a single point strongly reduced the localisation errors, whilst the method is robust with respect to the exact choice of the measured predictor.
mr-less high dimensional spatial normalization of 11c pib pet images on a population of elderly, mild cognitive impaired and alzheimer disease patients. β¿ amyloid (aβ) plaques are one of the neuropathological hallmarks of alzheimer's disease (ad) and can be quantified using the marker $^{11}\textnormal{c}$ pib. as $^{11}\textnormal{c}$ pib pet images have limited anatomical information, an magnetic resonance image (mri) is usually acquired to perform the spatial normalization needed for population analysis. we designed and evaluated a high dimensional spatial normalization approach that only uses the $^{11}\textnormal{c}$ pib pet image. the non-rigid registration (nrr) is based on free form deformation (ffd) modelled using b-splines. to compensate for the limited anatomical information, the ffd is constrained to an allowable transform space using a model trained from mr registrations. aβ deposition is dependent on disease staging, so a spatially normalized $^{11}\textnormal{c}$ pib pet appearance model selects and refines the atlas. the approach was compared with mr nrr using data from healthy elderly, mild cognitive impaired and alzheimer disease participants. using segmentation propagation, an average dice similarity coefficient of 0.64 and 0.73 was obtained for white and gray matter. the r-squared correlation between the uptake obtained in the frontal, parietal, occipital and temporal was 0.789, 0.843, 0.871 and 0.964. these are very promising results, considering the low resolution of $^{11}\textnormal{c}$ pib pet images.
fully automatic segmentation of the hippocampus and the amygdala from mri using hybrid prior knowledge. the segmentation of macroscopically ill-defined and highly variable structures, such as the hippocampus hc and the amygdala am, from mri requires specific constraints. here, we describe and evaluate a hybrid segmentation method that uses knowledge derived from a probabilistic atlas and from anatomical landmarks based on stable anatomical characteristics of the structures. combined in a previously published semi-automatic segmentation method, they lead to a fast, robust and accurate fully automatic segmentation of hc and am. the probabilistic atlas was built from 16 young controls and registered with the "unified segmentation" of spm5. the algorithm was quantitatively evaluated with respect to manual segmentation on two mri datasets: the 16 young controls, with a leave-one-out strategy, and a mixed cohort of 8 controls and 15 subjects with epilepsy with variable hippocampal sclerosis. the segmentation driven by hybrid knowledge leads to greatly improved results compared to that obtained by registration of the thresholded atlas alone: mean overlap for hc on the 16 young controls increased from 78% to 87% (p < 0.001) and on the mixed cohort from 73% to 82% (p < 0.001) while the error on volumes decreased from 10% to 7% (p < 0.005) and from 18% to 8% (p < 0.001), respectively. automatic results were better than the semi-automatic results: for the 16 young controls, average overlap increased from 84% to 87% (p < 0.001) for hc and from 81% to 84% (p < 0.002) for am, with equivalent improvements in volume error.
clinical neonatal brain mri segmentation using adaptive nonparametric data models and intensity-based markov priors. this paper presents a bayesian framework for neonatal brain-tissue segmentation in clinical magnetic resonance (mr) images. this is a challenging task because of the low contrast-to-noise ratio and large variance in both tissue intensities and brain structures, as well as imaging artifacts and partial-volume effects in clinical neonatal scanning. we propose to incorporate a spatially adaptive likelihood model using a data-driven nonparametric statistical technique. the method initially learns an intensity-based prior, relying on the empirical markov statistics from training data, using fuzzy nonlinear support vector machines (svm). in an iterative scheme, the models adapt to spatial variations of image intensities via nonparametric density estimation. the method is effective even in the absence of anatomical atlas priors. the implementation, however, can naturally incorporate probabilistic atlas priors and markov-smoothness priors to impose additional regularity on segmentation. the maximum-a-posteriori (map) segmentation is obtained within a graph-cut framework. cross validation on clinical neonatal brain-mr images demonstrates the efficacy of the proposed method, both qualitatively and quantitatively.
exploratory identification of image-based biomarkers for solid mass pulmonary tumors. if imaging is to serve as a valid biomarker in the assessment of the response of cancer to therapies, a reproducible and predictive radiologic metric is required. a biomarker is an indicator of a biological property that can be used to measure the progress of disease. while current size-based, quantitative techniques provide numerical representations of tumors, they are not necessarily indicative of disease progression for advanced cancers. in this paper, we present an end-to-end process to explore the use of other image-based features especially statistical textural features for cancer change detection. we exploit the earth mover's distance metric for measuring the change in the tumor burden over a period, between the time the baseline scans were taken, and the time the therapy response scans were taken. the time-to-progression (ttp) of the disease is our known patient outcome. we analyze the correlations between ttp and our change measurements and discover that the local texture energy feature is most predictive of disease progression, more so than the tumor burden size on which current quantitative measures are made.
modeling glioma growth and mass effect in 3d mr images of the brain. in this article, we propose a framework for modeling glioma growth and the subsequent mechanical impact on the surrounding brain tissue (mass-effect) in a medical imaging context. glioma growth is modeled via nonlinear reaction-advection-diffusion, with a two-way coupling with the underlying tissue elastic deformation. tumor bulk and infiltration and subsequent mass-effects are not regarded separately, but captured by the model itself in the course of its evolution. our formulation is fully eulerian and naturally allows for updating the tumor diffusion coefficient following structural displacements caused by tumor growth/infiltration. we show that model parameters can be estimated via optimization based on imaging data, using efficient solution algorithms on regular grids. we test the model and the automatic optimization framework on real brain tumor data sets, achieving significant improvement in landmark prediction compared to a simplified purely mechanical approach.
active-contour-based image segmentation using machine learning techniques. we introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. we model a category of shapes as a finite dimensional manifold which we approximate using diffusion maps. our method computes a delaunay triangulation of the reduced space, considered as euclidean, and uses the resulting space partition to identify the closest neighbors of any given shape based on its nyström extension. we derive a non-linear shape prior term designed to attract a shape towards the shape prior manifold at given constant embedding. results on shapes of ventricle nuclei demonstrate the potential of our method for segmentation tasks.
automatic recovery of the left ventricular blood pool in cardiac cine mr images. we present a method for automatic localization and rough segmentation of the left ventricle blood pool in cardiac cine magnetic resonance images. the method first detects the whole heart using time-based fourier analysis. it then segments the left ventricle blood pool by grouping connected components across slices using isoperimetric clustering. the system was tested on 253 datasets and failed in only 2 cases.
towards tracking breast cancer across medical images using subject-specific biomechanical models. breast cancer detection, diagnosis and treatment increasingly involves images of the breast taken with different degrees of breast deformation. we introduce a new biomechanical modelling framework for predicting breast deformation and thus aiding the combination of information derived from the various images. in this paper, we focus on mr images of the breast under different loading conditions, and consider methods to map information between the images. we generate subject-specific finite element models of the breast by semi-automatically fitting geometrical models to segmented data from breast mr images, and characterizing the subject-specific mechanical properties of the breast tissues. we identified the unloaded reference configuration of the breast by acquiring mr images of the breast under neutral buoyancy (immersed in water). such imaging is clearly not practical in the clinical setting, however this previously unavailable data provides us with important data with which to validate models of breast biomechanics, and provides a common configuration with which to refer and interpret all breast images. we demonstrate our modelling framework using a pilot study that was conducted to assess the mechanical performance of a subject-specific homogeneous biomechanical model in predicting deformations of the breast of a volunteer in a prone gravity-loaded configuration. the model captured the gross characteristics of the breast deformation with an rms error of 4.2 mm in predicting the skin surface of the gravity-loaded shape, which included tissue displacements of over 20 mm. internal tissue features identified from the mr images were tracked from the reference state to the prone gravity-loaded configuration with a mean error of 3.7 mm. we consider the modelling assumptions and discuss how the framework could be refined in order to further improve the tissue tracking accuracy.
de-enhancing the dynamic contrast-enhanced breast mri for robust registration. dynamic enhancement causes serious problems for registration of contrast enhanced breast mri, due to variable uptakes of agent on different tissues or even same tissues in the breast. we present an iterative optimization algorithm to de-enhance the dynamic contrast-enhanced breast mri and then register them for avoiding the effects of enhancement on image registration. in particular, the spatially varying enhancements are modeled by a markov random field, and estimated by a locally smooth function with boundaries using a graph cut algorithm. the de-enhanced images are then registered by conventional b-spline based registration algorithm. these two steps benefit from each other and are repeated until the results converge. experimental results show that our two-step registration algorithm performs much better than conventional mutual information based registration algorithm. also, the effects of tumor shrinking in the conventional registration algorithms can be effectively avoided by our registration algorithm.
brain fiber architecture, genetics, and intelligence: a high angular resolution diffusion imaging (hardi) study. we developed an analysis pipeline enabling population studies of hardi data, and applied it to map genetic influences on fiber architecture in 90 twin subjects. we applied tensor-driven 3d fluid registration to hardi, resampling the spherical fiber orientation distribution functions (odfs) in appropriate riemannian manifolds, after odf regularization and sharpening. fitting structural equation models (sem) from quantitative genetics, we evaluated genetic influences on the jensen-shannon divergence (jsd), a novel measure of fiber spatial coherence, and on the generalized fiber anisotropy (gfa; [1]) a measure of fiber integrity. with random-effects regression, we mapped regions where diffusion profiles were highly correlated with subjects' intelligence quotient (iq). fiber complexity was predominantly under genetic control, and higher in more highly anisotropic regions; the proportion of genetic versus environmental control varied spatially. our methods show promise for discovering genes affecting fiber connectivity in the brain.
simulation of ground-truth validation data via physically- and statistically-based warps. the problem of scarcity of ground-truth expert delineations of medical image data is a serious one that impedes the training and validation of medical image analysis techniques. we develop an algorithm for the automatic generation of large databases of annotated images from a single reference dataset. we provide a web-based interface through which the users can upload a reference data set (an image and its corresponding segmentation and landmark points), provide custom setting of parameters, and, following server-side computations, generate and download an arbitrary number of novel ground-truth data, including segmentations, displacement vector fields, intensity non-uniformity maps, and point correspondences. to produce realistic simulated data, we use variational (statistically-based) and vibrational (physically-based) spatial deformations, nonlinear radiometric warps mimicking imaging non-homogeneity, and additive random noise with different underlying distributions. we outline the algorithmic details, present sample results, and provide the web address to readers for immediate evaluation and usage.
effects of registration regularization and atlas sharpness on segmentation accuracy. in this paper, we propose a unified framework for computing atlases from manually labeled data at various degrees of "sharpness" and the joint registration-segmentation of a new brain with these atlases. in non-rigid registration, the tradeoff between warp regularization and image fidelity is typically set empirically. in segmentation, this leads to a probabilistic atlas of arbitrary "sharpness": weak regularization results in well-aligned training images and a "sharp" atlas; strong regularization yields a "blurry" atlas. we study the effects of this tradeoff in the context of cortical surface parcellation by comparing three special cases of our framework, namely: progressive registration-segmentation of a new brain to increasingly "sharp" atlases with increasingly flexible warps; secondly, progressive registration to a single atlas with increasingly flexible warps; and thirdly, registration to a single atlas with fixed constrained warps. the optimal parcellation in all three cases corresponds to a unique balance of atlas "sharpness" and warp regularization that yield statistically significant improvements over the previously demonstrated parcellation results.
conformal slit mapping and its applications to brain surface parameterization. we propose a method that computes a conformal mapping from a multiply connected mesh to the so-called slit domain, which consists of a canonical rectangle or disk in which 3d curved landmarks on the original surfaces are mapped to concentric or parallel lines in the slit domain. in this paper, we studied its application to brain surface parameterization. after cutting along some landmark curve features on surface models of the cerebral cortex, we obtain multiple connected domains. by computing exact harmonic one-forms, closed harmonic one-forms, and holomorphic one-forms, we are able to build a circular slit mapping that conformally maps the surface to an annulus with some concentric arcs and a rectangle with some slits. the whole algorithm is based on solving linear systems so it is very stable. in the slit domain parameterization results, the feature curves are either mapped to straight lines or concentric arcs. this representation is convenient for anatomical visualization, and may assist statistical comparisons of anatomy, surface-based registration and signal processing. preliminary experimental results parameterizing various brain anatomical surfaces are presented.
attenuation resilient aif estimation based on hierarchical bayesian modelling for first pass myocardial perfusion mri. non-linear attenuation of the arterial input function (aif) is a major problemin first-pass mr perfusion imaging due to the high concentration of the contrast agent in the blood pool. this paper presents a technique to reconstruct the true aif using signal intensities in the myocardium and the attenuated aif based on a hierarchical bayesian model (hbm). with the proposed method, both the aif and the response function are modeled as smoothed functions by using bayesian penalty splines (p-splines). the derived aif is then used to estimate the impulse response of the myocardium based on deconvolution analysis. the proposed technique is validated both with simulated data using the mmid4 model and ten in vivo data sets for estimating myocardial perfusion reserve rates. the results demonstrate the ability of the proposed technique in accurately reconstructing the desired aif for myocardial perfusion quantification. the method does not involve any mri pulse sequence modification, and thus is expected to have wider clinical impact.
automatic target and trajectory identification for deep brain stimulation (dbs) procedures. this paper presents an automatic surgical target and trajectory identification technique for planning deep brain stimulation (dbs) procedures. the probabilistic functional maps, constructed from population-based actual stimulating field information and intra-operative electrophysiological activities, were integrated into a neurosurgical visualization and navigation system to facilitate the surgical planning and guidance. in our preliminary studies, we compared the actual surgical target locations and trajectories established by an experienced stereotactic neurosurgeon with those automatically planned using our probabilistic functional maps on 10 subthalamic nucleus (stn) dbs procedures. the average displacement between the surgical target locations in both groups was 1.82mm with a standard deviation of 0.77mm. the difference between the surgical trajectories was 3.1° and 2.3° in the lateral-to-medial and anterior-to-posterior orientations respectively.
modeling of needle-tissue interaction using ultrasound-based motion estimation. a needle-tissue interaction model is an essential part of every needle insertion simulator. in this paper, a new experimental method for the modeling of needle-tissue interaction is presented. the method consists of measuring needle and tissue displacements with ultrasound, measuring needle base forces, and using a deformation simulation model to identify the parameters of a needle-tissue interaction model. the feasibility of this non-invasive approach was demonstrated in an experiment in which a brachytherapy needle was inserted into a prostate phantom. ultrasound radio-frequency data and the time-domain cross-correlation method, often used in ultrasound elastography, were used to generate the tissue displacement field during needle insertion. a three-parameter force density model was assumed for the needle-tissue interaction. with the needle displacement, tissue displacement and needle base forces as input data, finite element simulations were carried out to adjust the model parameters to achieve a good fit between simulated and measured data.
methods for inverting dense displacement fields: evaluation in brain image registration. in medical image analysis there is frequently a need to invert dense displacement fields which map one image space to another. in this paper we describe inversion techniques and determine their accuracy in the context of 18 inter-subject brain image registrations. scattered data interpolation (sdi) is used to initialise locally and globally consistent iterative techniques. the inverse-consistency error, eic is computed over the whole image and over 10 specific brain regions. sdi produced good results with mean (max) eic ∼ 0.02mm (2.0mm). both iterative method produced mean errors of ∼ 0.005mm but the globally consistent method resulted in a smaller maximum error (1.9mm compared with 1.4mm). the largest errors were in the cerebral cortex with large outlier errors in the ventricles. simple iterative techniques are, on this evidence, able to produce reasonable estimates of inverse displacement fields provided there is good initialisation.
hierarchical shape statistical model for segmentation of lung fields in chest radiographs. the standard active shape model (asm) generally uses a whole population to train a single pca-based shape model for segmentation of all testing samples. since some testing samples can be similar to only sub-population of training samples, it will be more effective if particular shape statistics extracted from the respective sub-population can be used for guiding image segmentation. accordingly, we design a set of hierarchical shape statistical models, including a whole-population shape model and a series of sub-population models. the whole-population shape model is used to guide the initial segmentation of the testing sample, and the initial segmentation result is then used to select a suitable sub-population shape model according to the shape similarity between the testing sample and each sub-population. by using the selected sub-population shape model, the segmentation result can be further refined. to achieve this segmentation process, several particular steps are designed next. first, all linearly aligned samples in the whole population are used to generate a whole-population shape model. second, an affinity propagation method is used to cluster all linearly aligned samples into several clusters, to determine the samples belonging to the same sub-populations. third, the original samples of each sub-population are linearly aligned to their own mean shape, and the respective sub-population shape model is built using the newly aligned samples in this sub-population. by using all these three steps, we can generate hierarchical shape statistical models to guide image segmentation. experimental results show that the proposed method can significantly improve the segmentation performance, compared to conventional asm.
real-time modeling of vascular flow for angiography simulation. interventional neuroradiology is a growing field of minimally invasive therapies that includes embolization of aneurysms and arteriovenous malformations, carotid angioplasty and carotid stenting, and acute stroke therapy. treatment is performed using image-guided instrument navigation through the patient's vasculature and requires intricate combination of visual and tactile coordination. in this paper we present a series of techniques for real-time high-fidelity simulation of angiographic studies. we focus in particular on the computation and visualization of blood flow and blood pressure distribution patterns, mixing of blood and contrast agent, and high-fidelity simulation of fluoroscopic images.
quantification of blood flow from rotational angiography. for assessment of cerebrovascular diseases, it is beneficial to obtain three-dimensional (3d) information on vessel morphology and hemodynamics. rotational angiography is routinely used to determine the 3d geometry and we propose a method to exploit the same acquisition to determine the blood flow waveform and the mean volumetric flow rate. the method uses a model of contrast agent dispersion to determine the flow parameters from the spatial and temporal development of the contrast agent concentration, represented by a flow map. furthermore, it also overcomes artifacts due to the rotation of the c-arm using a newly introduced reliability map. the method was validated on images from a computer simulation and from a phantom experiment. with a mean error of 11.0% for the mean volumetric flow rate and 15.3% for the blood flow waveform from the phantom experiments, we conclude that the method has the potential to give quantitative estimates of blood flow parameters during cerebrovascular interventions.
on simulating subjective evaluation using combined objective metrics for validation of 3d tumor segmentation. in this paper, we present a new segmentation evaluation method that can simulate radiologist's subjective assessment of 3d tumor segmentation in ct images. the method uses a new metric defined as a linear combination of a set of commonly used objective metrics. the weighing parameters of the linear combination are determined by maximizing the rank correlation between radiologist's subjective rating and objective measurements. experimental results on 93 lesions demonstrate that the new composite metric shows better performance in segmentation evaluation than each individual objective metric. also, segmentation rating using the composite metric compares well with radiologist's subjective evaluation. our method has the potential to facilitate the development of new tumor segmentation algorithms and assist large scale segmentation evaluation studies.
fuzzy nonparametric dti segmentation for robust cingulum-tract extraction. this paper presents a novel segmentation-based approach for fiber-tract extraction in diffusion-tensor (dt) images. typical tractography methods, incorporating thresholds on fractional anisotropy and fiber curvature to terminate tracking, can face serious problems arising from partial voluming and noise. for these reasons, tractography often fails to extract thin tracts with sharp changes in orientation, e.g. the cingulum. unlike tractography--which disregards the information in the tensors that were previously tracked--the proposed method extracts the cingulum by exploiting the statistical coherence of tensors in the entire structure. moreover, the proposed segmentation-based method allows fuzzy class memberships to optimally extract information within partial-volumed voxels. unlike typical fuzzy-segmentation schemes employing gaussian models that are biased towards ellipsoidal clusters, the proposed method models the manifolds underlying the classes by incorporating nonparametric data-driven statistical models. furthermore, it exploits the nonparametric model to capture the spatial continuity and structure of the fiber bundle. the results on real dt images demonstrate that the proposed method extracts the cingulum bundle significantly more accurately as compared to tractography.
classification of suspected liver metastases using fmri images: a machine learning approach. this paper presents a machine-learning approach to the interactive classification of suspected liver metastases in fmri images. the method uses fmri-based statistical modeling to characterize colorectal hepatic metastases and follow their early hemodynamical changes. changes in hepatic hemodynamics are evaluated from $t_2^*$-w fmri images acquired during the breathing of air, air-co 2, and carbogen. a classification model is build to differentiate between tumors and healthy liver tissues. to validate our method, a model was built from 29 mice datasets, and used to classify suspicious regions in 16 new datasets of healthy subjects or subjects with metastases in earlier growth phases. our experimental results on mice yielded an accuracy of 78% with high precision (88%). this suggests that the method can provide a useful aid for early detection of liver metastases.
registration of cardiac spect/ct data through weighted intensity co-occurrence priors. the introduction of hybrid scanners has greatly increased the popularity of molecular imaging techniques. many clinical applications benefit from combining complementary information based on the precise alignment of the two modalities. in case the alignment is inaccurate, then this crucial assumption often made for subsequent processing steps will be violated. however, this violation may not be apparent to the physician. in ct-based attenuation correction (ac) for cardiac spect/ct data, critical misalignments between spect and ct can lead to spurious perfusion defects. in this work, we focus on increasing the accuracy of rigid volume registration of cardiac spect/ct data by using prior knowledge. a new weighting scheme for an intensity co-occurrence prior is introduced to assure accurate and robust alignment in the local heart region. experimental results demonstrate that the proposed method out-performs mutual information registration and shows robustness across a selection of learned distributions acquired from 15 different patients.
detection and segmentation of pathological structures by the extended graph-shifts algorithm. we propose an extended graph-shifts algorithm for image segmentation and labeling. this algorithm performs energy minimization by manipulating a dynamic hierarchical representation of the image. it consists of a set of moves occurring at different levels of the hierarchy where the types of move, and the level of the hierarchy, are chosen automatically so as to maximally decrease the energy. extended graph-shifts can be applied to a broad range of problems in medical imaging. in this paper, we apply extended graph-shifts to the detection of pathological brain structures: (i) segmentation of brain tumors, and (ii) detection of multiple sclerosis lesions. the energy terms in these tasks are learned from training data by statistical learning algorithms.we demonstrate accurate results, precision and recall in the order of 93%, and also show that the algorithm is computationally efficient, segmenting a full 3d volume in about one minute.
real-time mr diffusion tensor and q-ball imaging using kalman filtering. magnetic resonance diffusion imaging (dmri) has become an established research tool for the investigation of tissue structure and orientation. in this paper, we present a method for real time processing of diffusion tensor and q-ball imaging. the basic idea is to use kalman filtering framework to fit either the linear tensor or q-ball model. because the kalman filter is designed to be an incremental algorithm, it naturally enables updating the model estimate after the acquisition of any new diffusion-weighted volume. processing diffusion models and maps during ongoing scans provides a new useful tool for clinicians, especially when it is not possible to predict how long a subject may remain still in the magnet.
left ventricle tracking using overlap priors. this study investigates overlap priors for tracking the left ventricle (lv) endo- and epicardium boundaries in cardiac magnetic resonance (mr) sequences. it consists of evolving two curves following the euler-lagrange minimization of two functionals each containing an original overlap prior constraint. the latter measures the conformity of the overlap between the nonparametric (kernel-based) intensity distributions within the three target regions---lv cavity, myocardium and background---to a prior learned from a given segmentation of the first frame. the bhattacharyya coefficient is used as an overlap measure. different from existing intensity-driven constraints, the overlap priors do not assume implicitly that the overlap between the distributions within different regions has to be minimal. although neither shape priors nor curve coupling were used, quantitative evaluation showed that the results correlate well with independent manual segmentations and the method compares favorably with other recent methods. the overlap priors lead to a lv tracking which is more versatile than existing methods because the solution is not bounded to the shape/intensity characteristics of a training set. we also demonstrate experimentally that the used overlap measures are approximately constant over a cardiac sequence.
real-time nonlinear finite element analysis for surgical simulation using graphics processing units. clinical employment of biomechanical modelling techniques in areas of medical image analysis and surgical simulation is often hindered by conflicting requirements for high fidelity in the modelling approach and high solution speeds. we report the development of techniques for high-speed nonlinear finite element (fe) analysis for surgical simulation. we employ a previously developed nonlinear total lagrangian explicit fe formulation which offers significant computational advantages for soft tissue simulation. however, the key contribution of the work is the presentation of a fast graphics processing unit (gpu) solution scheme for the fe equations. to the best of our knowledge this represents the first gpu implementation of a nonlinear fe solver. we show that the present explicit fe scheme is well-suited to solution via highly parallel graphics hardware, and that even a midrange gpu allows significant solution speed gains (up to 16.4×) compared with equivalent cpu implementations. for the models tested the scheme allows real-time solution of models with up to 16000 tetrahedral elements. the use of gpus for such purposes offers a cost-effective high-performance alternative to expensive multi-cpu machines, and may have important applications in medical image analysis and surgical simulation.
modelling intravasation of liquid distension media in surgical simulators. we simulate the intravasation of liquid distention media into the systemic circulation as it occurs during hysteroscopy and transurethral resection of the prostate. a linear network flow model is extended with a correction for non-newtonian blood behaviour in small vessels and an appropriate handling of vessel compliance. we then integrate a fast lookup scheme in order to allow for real-time simulation. cutting of tissue is accounted for by adjusting pressure boundary conditions for all cut vessels. we investigate the influence of changing distention fluid pressure settings and of the position of tissue cuts. our simulation predicts significant intravasation only on the venous side, and just in cases when larger veins are cut. the implemented methods allow the realistic control of bleeding for short-term and the total resulting intravasation volume for long-term complication scenarios. while the simulation is fast enough to support real-time training, it is also adequate for explaining intravasation effects which were previously observed on a phenomenological level only.
nonrigid registration of dynamic renal mr images using a saliency based mrf model. nonrigid registration of contrast-enhanced mr images is a difficult problem due to the change in pixel intensity caused by the wash-in and wash-out of the contrast agent. in this paper we propose a novel saliency based markov random field approach for effective nonrigid registration of contrast enhanced images. saliency information obtained from the neurobiology-based saliency model alongwith intensity information is used to quantify the degree of similarity between images in the pre- and post-contrast stages. information from these two features is combined by using an exponential function of the saliency difference such that it assigns low values to small differences in saliency and at the same time ensures that saliency information does not bias the energy term. rotationally-invariant edge information from edge-orientation histograms was used to complement the saliency information resulting in better registration results. tests on real patient datasets show that our algorithm results in accurate registration. we also simulated elastic motion on images, and the deformation field recovered by our algorithm was nearly the inverse of the simulated field.
3d cerebral cortical morphometry in autism: increased folding in children and adolescents in frontal, parietal, and temporal lobes. this paper presents a systematic evaluation of cortical folding, or complexity, in autism. it introduces two novel measures to analyze folding in a specific region of interest, which, unlike traditional measures, produce an intuitive easily-interpretable description of folding and inform the nature of folding change by incorporating local surface-patch orientation. this study reports new findings of increased cortical folding in autistics in the frontal, parietal, and temporal lobes, as compared to controls. these differences are stronger in children than adolescents. the paper validates part of the findings using the new measures based on comparisons with traditional measures. unlike studies in the literature, this paper reports new findings, via a fully 3d folding analysis on all brain lobes, based on the consensus of virtually all 6 folding measures used (2 new, 4 traditional) via rigorous statistical permutation testing. in these ways, this paper not only strengthens some previous clinical findings, but also extends the state of the art in autism research.
measuring brain variability via sulcal lines registration: a diffeomorphic approach. in this paper we present a new way of measuring brain variability based on the registration of sulcal lines sets in the large deformation framework. lines are modelled geometrically as currents, avoiding then matchings based on point correspondences. at the end we retrieve a globally consistent deformation of the underlying brain space that best matches the lines. thanks to this framework the measured variability is defined everywhere whereas a previous method introduced by p. fillard requires tensors extrapolation. evaluating both methods on the same database, we show that our new approach enables to describe different details of the variability and to highlight the major trends of deformation in the database thanks to a tangent-pca analysis.
robust autonomous model learning from 2d and 3d data sets. in this paper we propose a weakly supervised learning algorithm for appearance models based on the minimum description length (mdl) principle. from a set of training images or volumes depicting examples of an anatomical structure, correspondences for a set of landmarks are established by group-wise registration. the approach does not require any annotation. in contrast to existing methods no assumptions about the topology of the data are made, and the topology can change throughout the data set. instead of a continuous representation of the volumes or images, only sparse finite sets of interest points are used to represent the examples during optimization. this enables the algorithm to efficiently use distinctive points, and to handle texture variations robustly. in contrast to standard elasticity based deformation constraints the mdl criterion accounts for systematic deformations typical for training sets stemming from medical image data. experimental results are reported for five different 2d and 3d data sets.
robust vessel tree modeling. in this paper, we present a novel method for extracting center axis representations (centerlines) of blood vessels in contrast enhanced (ce)-cta/mra, robustly and accurately. this graph-based optimization algorithm which employs multi-scale medialness filters extracts vessel centerlines by computing the minimum-cost paths. specifically, first, new medialness filters are designed from the assumption of circular/elliptic vessel cross-sections. these filters produce contrast and scale independent responses even the presence of nearby structures. second, they are incorporated to the minimum-cost path detection algorithm in a novel way for the computational efficiency and accuracy. third, the full vessel centerline tree is constructed from this optimization technique by assigning a saliency measure for each centerline from their length and radius information. the proposed method is computationally efficient and produces results that are comparable in quality to the ones created by experts. it has been tested on more than 100 coronary artery data set where the full coronary artery trees are extracted in 21 seconds in average on a 3.2ghz pc.
active scheduling of organ detection and segmentation in whole-body medical images. with the advance of whole-body medical imaging technologies, computer aided detection/diagnosis (cad) is being scaled up to deal with multiple organs or anatomical structures simultaneously. multiple tasks (organ detection/segmentation) in a cad system are often highly dependent due to the anatomical context within a human body. in this paper, we propose a method to schedule multi-organ detection/segmentation based on information theory. the central idea is to schedule tasks in an order that each operation achieves maximum expected information gain. the scheduling rule is formulated to embed two intuitive principles: (1) a task with higher confidence tends to be scheduled earlier; (2) a task with higher predictive power for other tasks tends to be scheduled earlier. more specifically, task dependency is modeled by conditional probability; the outcome of each task is assumed to be probabilistic as well; and the scheduling criterion is based on the reduction of the summed conditional entropy over all tasks. the validation is carried out on two challenging cad problems, multi-organ detection in whole-body ct and liver segmentation in pet-ct. compared to unscheduled and ad hoc scheduled organ detection/segmentation, our scheduled execution achieves higher accuracy with faster speed.
characterizing task-related temporal dynamics of spatial activation distributions in fmri bold signals. we present a new functional magnetic resonance imaging (fmri) analysis method that incorporates both spatial and temporal dynamics of blood-oxygen-level dependent (bold) signals within a region of interest (roi). 3d moment descriptors are used to characterize the spatial changes in bold signals over time. the method is tested on fmri data collected from eight healthy subjects performing a bulb-squeezing motor task with their right-hand at various frequencies. multiple brain regions including the left cerebellum, both primary motor cortices (m1), both supplementary motor areas (sma), left prefrontal cortex (pfc), and left anterior cingulate cortex (acc) demonstrate significant task-related changes. furthermore, our method is able to discriminate differences in activation patterns at the various task frequencies, whereas using a traditional intensity based method, no significant activation difference is detected. this suggests that temporal dynamics of the spatial distribution of bold signal provide additional information regarding task-related activation thus complementing conventional intensity-based approaches.
contraction detection in small bowel from an image sequence of wireless capsule endoscopy. this paper describes a method for automatic detection of contractions in the small bowel through analyzing wireless capsule endoscopic images. based on the characteristics of contraction images, a coherent procedure that includes analyzes of the temporal and spatial features is proposed. for temporal features, the image sequence is examined to detect candidate contractions through the changing number of edges and an evaluation of similarities between the frames of each possible contraction to eliminate cases of low probability. for spatial features, descriptions of the directions at the edge pixels are used to determine contractions utilizing a classification method. the experimental results show the effectiveness of our method that can detect a total of 83% of cases. thus, this is a feasible method for developing tools to assist in diagnostic procedures in the small bowel.
boundary-specific cost functions for quantitative airway analysis. computed tomography (ct) images of the lungs provide high resolution views of the airways. quantitative measurements such as lumen diameter and wall thickness help diagnose and localize airway diseases, assist in surgical planning, and determine progress of treatment. automated quantitative analysis of such images is needed due to the number of airways per patient. we present an approach involving dynamic programming coupled with boundary-specific cost functions that is capable of differentiating inner and outer borders. the method allows for precise delineation of the inner lumen and outer wall. the results are demonstrated on synthetic data, evaluated on human datasets compared to human operators, and verified on phantom ct scans to sub-voxel accuracy.
how do registration parameters affect quantitation of lung kinematics? assessing the quality of motion estimation in the lung remains challenging. we approach the problem by imaging isolated porcine lungs within an artificial thorax with four-dimensional computed tomography (4dct). respiratory kinematics are estimated via pairwise non-rigid registration using different metrics and image resolutions. landmarks are manually identified on the images and used to assess accuracy by comparing known displacements to the registration-derived displacements. we find that motion quantitation becomes less precise as the inflation interval between images increases. in addition, its sensitivity to image resolution varies anatomically. mutual information and cross-correlation perform similarly, while mean squares is significantly poorer. however, none of the metrics compensate for the difficulty of registering over a large inflation interval. we intend to use the results of these experiments to more effectively and efficiently quantify pulmonary kinematics in future, and to explore additional parameter combinations.
atlas-based segmentation of the germinal matrix from in utero clinical mri of the fetal brain. recently developed techniques for reconstruction of high-resolution 3d images from fetal mr scans allows us to study the morphometry of developing brain tissues in utero. however, existing adult brain analysis methods cannot be directly applied as the anatomy of the fetal brain is significantly different in terms of geometry and tissue morphology. we describe an approach to atlas-based segmentation of the fetal brain with particular focus on the delineation of the germinal matrix, a transient structure related to brain growth. we segment 3d images reconstructed from in utero clinical mr scans and measure volumes of different brain tissue classes for a group of fetal subjects at gestational age 20.5---22.5 weeks. we also include a partial validation of the approach using manual tracing of the germinal matrix at different gestational ages.
nonlinear registration of diffusion mr images based on fiber bundles. in this paper, we explore the use of fiber bundles extracted from diffusion mr images for a nonlinear registration algorithm. we employ a white matter atlas to automatically label major fiber bundles and to establish correspondence between subjects. we propose a polyaffine framework to calculate a smooth and invertible nonlinear warp field based on these correspondences, and derive an analytical solution for the reorientation of the tensor fields under the polyaffine transformation. we demonstrate our algorithm on a group of subjects and show that it performs comparable to a higher dimensional nonrigid registration algorithm.
a distributed spatio-temporal eeg/meg inverse solver. we propose a novel ¿1¿2-norm inverse solver for estimating the sources of eeg/meg signals. based on the standard ¿1-norm inverse solver, the proposed sparse distributed inverse solver integrates the ¿1-norm spatial model with a temporal model of the source signals in order to avoid unstable activation patterns and "spiky" reconstructed signals often produced by the original solvers. the joint spatio-temporal model leads to a cost function with an ¿1¿2-norm regularizer whose minimization can be reduced to a convex second-order cone programming problem and efficiently solved using the interior-point method. validation with simulated and real meg data shows that the proposed solver yields source time course estimates qualitatively similar to those obtained through dipole fitting, but without the need to specify the number of dipole sources in advance. furthermore, the ¿1¿2-norm solver achieves fewer false positives and a better representation of the source locations than the conventional ¿2 minimum-norm estimates.
robotic assistant for transperineal prostate interventions in 3t closed mri. numerous studies have demonstrated the efficacy of image-guided needle-based therapy and biopsy in the management of prostate cancer. the accuracy of traditional prostate interventions performed using transrectal ultrasound (trus) is limited by image fidelity, needle template guides, needle deflection and tissue deformation. magnetic resonance imaging (mri) is an ideal modality for guiding and monitoring such interventions due to its excellent visualization of the prostate, its sub-structure and surrounding tissues. we have designed a comprehensive robotic assistant system that allows prostate biopsy and brachytherapy procedures to be performed entirely inside a 3t closed mri scanner. we present a detailed design of the robotic manipulator and an evaluation of its usability and mr compatibility.
anisotropic wave propagation and apparent conductivity estimation in a fast electrophysiological model: application to xmr interventional imaging. cardiac arrhythmias are increasingly being treated using ablation procedures. development of fast electrophysiological models and estimation of parameters related to conduction pathologies can aid in the investigation of better treatment strategies during radio-frequency ablations. we present a fast electrophysiological model incorporating anisotropy of the cardiac tissue. a global-local estimation procedure is also outlined to estimate a hidden parameter (apparent electrical conductivity) present in the model. the proposed model is tested on synthetic and real data derived using xmr imaging. we demonstrate a qualitative match between the estimated conductivity parameter and possible pathology locations. this approach opens up possibilities to directly integrate modelling in the intervention room.
non-rigid image registration using graph-cuts. non-rigid image registration is an ill-posed yet challenging problem due to its supernormal high degree of freedoms and inherent requirement of smoothness. graph-cuts method is a powerful combinatorial optimization tool which has been successfully applied into image segmentation and stereo matching. under some specific constraints, graph-cuts method yields either a global minimum or a local minimum in a strong sense. thus, it is interesting to see the effects of using graph-cuts in non-rigid image registration. in this paper, we formulate non-rigid image registration as a discrete labeling problem. each pixel in the source image is assigned a displacement label (which is a vector) indicating which position in the floating image it is spatially corresponding to. a smoothness constraint based on first derivative is used to penalize sharp changes in displacement labels across pixels. the whole system can be optimized by using the graph-cuts method via alpha-expansions. we compare 2d and 3d registration results of our method with two state-of-the-art approaches. it is found that our method is more robust to different challenging non-rigid registration cases with higher registration accuracy.
probabilistic speckle decorrelation for 3d ultrasound. recent developments in freehand 3d ultrasound (us) have shown how image registration and speckle decorrelation methods can be used for 3d reconstruction instead of relying on a tracking device. estimating elevational separation between untracked us images using speckle decorrelation is error prone due to the uncertainty that plagues the correlation measurements. in this paper, using maximum entropy estimation methods, the uncertainty is directly modeled from the calibration data normally used to estimate an average decorrelation curve. multiple correlation measurements can then be fused within a maximum likelihood estimation framework in order to reduce the drift in elevational pose estimation over large image sequences. the approach is shown to be effective through empirical results on simulated and phantom us data.
shape analysis using a point-based statistical shape model built on correspondence probabilities. a fundamental problem when computing statistical shape models is the determination of correspondences between the instances of the associated data set. often, homologies between points that represent the surfaces are assumed which might lead to imprecise mean shape and variability results. we propose an approach where exact correspondences are replaced by evolving correspondence probabilities. these are the basis for a novel algorithm that computes a generative statistical shape model. we developed an unified map framework to compute the model parameters ('mean shape' and 'modes of variation') and the nuisance parameters which leads to an optimal adaption of the model to the set of observations. the registration of the model on the instances is solved using the expectation maximization - iterative closest point algorithm which is based on probabilistic correspondences and proved to be robust and fast. the alternated optimization of the map explanation with respect to the observation and the generative model parameters leads to very efficient and closed-form solutions for (almost) all parameters. experimental results on brain structure data sets demonstrate the efficiency and well-posedness of the approach. the algorithm is then extended to an automatic classification method using the k-means clustering and applied to synthetic data as well as brain structure classification problems.
automatic inference of sulcus patterns using 3d moment invariants. the goal of this work is the automatic inference of frequent patterns of the cortical sulci, namely patterns that can be observed only for a subset of the population. the sulci are detected and identified using brainvisa open software. then, each sulcus is represented by a set of shape descriptors called the 3d moment invariants. unsupervised agglomerative clustering is performed to define the patterns. a ratio between compactness and contrast among clusters is used to select the best patterns. a pattern is considered significant when this ratio is statistically better than the ratios obtained for clouds of points following a gaussian distribution. the patterns inferred for the left cingulate sulcus are consistent with the patterns described in the atlas of ono.
eeg to mri registration based on global and local similarities of mri intensity distributions. in this paper, a novel method for eeg to mri registration is proposed. initial registration is achieved by extracting and matching symmetry planes of mri and eeg data, followed by iterative registration based on minimizing a cost function. comparison of the intensity distributions of the whole mr image and mri voxels around a head surface point yields global similarities, while the comparison of intensity distributions of mri voxels around corresponding eeg points, which reflects the head's sagittal symmetry, yields local similarities. therefore, when the eeg points are registered to the mr image, maximal global and local similarities should be obtained. the cost function, incorporating global and local similarities, was the sum of kullback-leibler divergences between corresponding intensity distributions. the proposed method was evaluated on clinical mri data with simulated eeg data, yielding mean registration error of 0.48 ±0.33 mm, while with real eeg data an average root-mean-square point-to-surface error of 2.27 ±0.02 mm was obtained.
non-rigid surface registration using spherical thin-plate splines. accurate registration of cortical structures plays a fundamental role in statistical analysis of brain images across population. this paper presents a novel framework for the non-rigid intersubject brain surface registration, using conformal structure and spherical thin-plate splines. by resorting to the conformal structure, complete characteristics regarding the intrinsic cortical geometry can be retained as a mean curvature function and a conformal factor function defined on a canonical, spherical domain. in this transformed space, spherical thin-plate splines are firstly used to explicitly match a few prominent homologous landmarks, and in the meanwhile, interpolate a global deformation field. a post-optimization procedure is then employed to further refine the alignment of minor cortical features based on the geometric parameters preserved on the domain. our experiments demonstrate that the proposed framework is highly competitive with others for brain surface registration and population-based statistical analysis. we have applied our method in the identification of cortical abnormalities in pet imaging of patients with neurological disorders and accurate results are obtained.
virtually extended surgical drilling device: virtual mirror for navigated spine surgery. this paper introduces a new method for navigated spine surgery using a stereoscopic video see-through head-mounted display (hmd) and an optical tracking system. vertebrae are segmented from volumetric ct data and visualized in-situ. a surgical drilling device is virtually extended with a mirror for intuitive planning of the drill canal, control of drill direction and insertion depth. the first designated application for the virtually extended drilling device is the preparation of canals for pedicle screw implantation in spine surgery. the objective of surgery is to install an internal fixateur for stabilization of injured vertebrae. we invited five surgeons of our partner clinic to test the system with realistic replica of lumbar vertebrae and compared the new approach with the classical, monitor-based navigation system providing three orthogonal slice views on the operation site. we measured time of procedure and scanned the drilled vertebrae with ct to verify accuracy of drilling.
automatic dry eye detection. dry eye syndrome is a common disease in the western world, with effects from uncomfortable itchiness to permanent damage to the ocular surface. nevertheless, there is still no objective test that provides reliable results. we have developed a new method for the automated detection of dry areas in videos taken after instilling fluorescein in the tear film. the method consists of a multi-step algorithm to first locate the iris in each image, then align the images and finally analyze the aligned sequence in order to find the regions of interest. since the fluorescein spreads on the ocular surface of the eye the edges of the iris are fuzzy making the detection of the iris challenging. we use ransac to first detect the upper and lower eyelids and then the iris. then we align the images by finding differences in intensities at different scales and using a least squares optimization method (levenberg-marquardt), to overcome the movement of the iris and the camera. the method has been tested on videos taken from different patients. it is demonstrated to find the dry areas accurately and to provide a measure of the extent of the disease.
application of open source image guided therapy software in mr-guided therapies. we present software engineering methods to provide free open-source software for mr-guided therapy. we report that graphical representation of the surgical tools, interconnectively with the tracking device, patient-to-image registration, and mri-based thermal mapping are crucial components of mr-guided therapy in sharing such software. software process includes a network-based distribution mechanism by multi-platform compiling tool cmake, cvs, quality assurance software dart. we developed six procedures in four separate clinical sites using proposed software engineering and process, and found the proposed method is feasible to facilitate multicenter clinical trial of mr-guided therapies. our future studies include use of the software in non-mr-guided therapies.
analysis of surfaces using constrained regression models. we present a study of the relationship between the changes in the shape of the human ear due to jaw movement and acoustical feedback (af) in hearing aids. in particular, we analyze the deformation field of the outer ear associated with the movement of the mandible (jaw bone) to understand its effect on af and identify local regions that play a significant role. our data contains ear impressions of 42 hearing aid users, in two different positions: open and closed mouth, and survey data including information about experienced discomfort due to af. we use weighted support vector machines (wsvm) to investigate the separation between the presence and lack of af and achieve classification accuracy of 80% based on the deformation field. to robustly localize the regions of the deformation field that significantly contribute to af we employ logistic regression penalized with elastic net (en). by visualizing the selected variables on the mean surface, we provide clinical interpretations of the results.
mr brain tissue classification using an edge-preserving spatially variant bayesian mixture model. in this paper, a spatially constrained mixture model for the segmentation of mr brain images is presented. the novelty of this work is an edge-preserving smoothness prior which is imposed on the probabilities of the voxel labels. this prior incorporates a line process, which is modeled as a bernoulli random variable, in order to preserve edges between tissues. the main difference with other, state of the art methods imposing priors, is that the constraint is imposed on the probabilities of the voxel labels and not onto the labels themselves. inference of the proposed bayesian model is obtained using variational methodology and the model parameters are computed in closed form. numerical experiments are presented where the proposed model is favorably compared to state of the art brain segmentation methods as well as to a spatially varying gaussian mixture model.
real-time tracking of the left ventricle in 3d echocardiography using a state estimation approach. in this paper we present a framework for real-time tracking of deformable contours in volumetric datasets. the framework supports composite deformation models, controlled by parameters for contour shape in addition to global pose. tracking is performed in a sequential state estimation fashion, using an extended kalman filter, with measurement processing in information space to effectively predict and update contour deformations in real-time. a deformable b-spline surface coupled with a global pose transform is used to model shape changes of the left ventricle of the heart. successful tracking of global motion and local shape changes without user intervention is demonstrated on a dataset consisting of 21 3d echocardiography recordings. real-time tracking using the proposed approach requires a modest cpu load of 13% on a modern computer. the segmented volumes compare to a semi-automatic segmentation tool with 95% limits of agreement in the interval 4.1 ± 24.6 ml (r = 0.92).
riemannian framework for estimating symmetric positive definite 4th order diffusion tensors. dti is an important tool to investigate the brain in vivo and non-invasively in spite of its shortcomings in regions of fiber-crossings. hardi models such as qbi and higher order tensors (hot) were invented to overcome this shortcoming. hots, however, have not been explored extensively even though sophisticated estimation schemes were developed for dti that guarantee positive diffusivity, such as the riemannian framework. positive diffusivity is an important constraint in diffusion mri since it represents the physical phenomenon of molecular diffusion. it seems apt, to leverage the work done on dti, to apply the positivity constraint to the hot model. we, therefore, propose to extend the riemannian framework from dti to the space of 4th order diffusion tensors. we also review the existing methods for estimating 4th order diffusion tensors and compare all methods on synthetic, phantom and real datasets extensively to test for robustness and speed. our contributions for extending the riemannian framework from dti to estimating 4th order diffusion tensors guarantees positive diffusivity, is robust, is fast, and can be used to discern multiple fiber directions.
topology preserving warping of binary images: application to atlas-based skull segmentation. lots of works have been recently carried out in the field of non-rigid registration to ensure the estimation of one-to-one mappings. however, warping a binary image with such transformations may alter its discrete topological properties if common resampling strategies are considered. this paper proposes an original method for warping a binary image according to some continuous and bijective mapping, while preserving its discrete topological properties. results obtained in the context of atlas-based segmentation highlight the interest of the approach. indeed, the method has been successfully applied to the segmentation of skull structures from a database of 15 ct-scans, providing both geometrically and topologically satisfactory results.
global medical shape analysis using the laplace-beltrami spectrum. this paper proposes to use the laplace-beltrami spectrum (lbs) as a global shape descriptor for medical shape analysis, allowing for shape comparisons using minimal shape preprocessing: no registration, mapping, or remeshing is necessary. the discriminatory power of the method is tested on a population of female caudate shapes of normal control subjects and of subjects with schizotypal personality disorder.
construction of hierarchical multi-organ statistical atlases and their application to multi-organ segmentation from ct images. hierarchical multi-organ statistical atlases are constructed with the aim of achieving fully automated segmentation of the liver and related organs from computed tomography images. constraints on inter-relations among organs are embedded in hierarchical organization of probabilistic atlases (pas) and statistical shape models (ssms). hierarchical pas are constructed based on the hierarchical nature of inter-organ relationships. multi-organ ssms (mo-ssms) are combined with previously proposed single-organ multi-level ssms (ml-ssms). a hierarchical segmentation procedure is then formulated using the constructed hierarchical atlases. the basic approach consists of hierarchical recursive processes of initial region extraction using pas and subsequent refinement using ml/mo-ssms. the experimental results show that segmentation accuracy of the liver was improved by incorporating constraints on inter-organ relationships.
a new benchmark for shape correspondence evaluation. this paper introduces a new benchmark study of evaluating landmark-based shape correspondence used for statistical shape analysis. different from previous shape-correspondence evaluation methods, the proposed benchmark first generates a large set of synthetic shape instances by randomly sampling a specified ground-truth statistical shape model. we then run the test shape-correspondence algorithms on these synthetic shape instances to construct a new statistical shape model. we finally introduce a new measure to describe the difference between this newly constructed statistical shape model and the ground truth. this new measure is then used to evaluate the performance of the test shape-correspondence algorithm. by introducing the ground-truth statistical shape model, we believe the proposed benchmark allows for a more objective evaluation of the shape correspondence than those that do not specify any ground truth.
modelling anisotropic viscoelasticity for real-time soft tissue simulation. previously almost all biomechanically-based time-critical surgical simulation has ignored the well established features of tissue mechanical response of anisotropy and time-dependence. we address this issue by presenting an efficient solution procedure for anisotropic visco-hyperelastic constitutive models which allows use of these in nonlinear explicit dynamic finite element algorithms. we show that the procedure allows incorporation of both anisotropy and viscoelasticity for as little as 5.1% additional cost compared with the usual isotropic elastic models. when combined with high performance gpu execution the complete framework is suitable for time-critical simulation applications such as interactive surgical simulation and intraoperative image registration.
automatic mitral valve inflow measurements from doppler echocardiography. doppler echocardiography is widely used for functional assessment of heart valves such as mitral valve. in current clinical work flow, to extract doppler measurements, the envelopes of acquired doppler spectra are manually traced. we propose a robust algorithm for automatically tracing the envelopes of mitral valve inflow doppler spectra, which exhibit a large amount of variations in envelope shape and image appearance due to various disease conditions, patient/sonographer/instrument differences, etc. the algorithm is learning-based and capable of fully automatic detection and segmentation of the mitral inflow structures. experiments show that the algorithm, running within one second, yields comparable performance to experts.
a training system for ultrasound-guided needle insertion procedures. needle placement into a patient body under guidance of ultrasound is a frequently performed procedure in clinical practice. safe and successful performance of such procedure requires a high level of spatial reasoning and hand-eye co-ordination skills, which must be developed through intensive practice. in this paper we present a training system designed to improve the skills of interventional radiology trainees in ultrasound-guided needle placement procedures. key issues involved in the system include surface and volumetric registration, solid texture modelling, spatial calibration, and real-time synthesis and rendering of ultrasound images. moreover, soft tissue deformation caused by the needle movement and needle cutting is realised using a mass-spring-model approach. these have led to a realistic ultrasound simulation system, which has been shown to be a useful tool for the training of needle insertion procedures. preliminary results of a construct evaluation study indicate the effectiveness and usefulness of the developed training system.
surface-based texture and morphological analysis detects subtle cortical dysplasia. focal cortical dysplasia (fcd), a malformation of cortical development, is an important cause of pharmacoresistant epilepsy. small fcd lesions are difficult to distinguish from normal cortex and remain often overlooked on radiological mri inspection. this paper presents a method to detect small fcd lesions on t1-mri relying on surface-based features that model their textural and morphometric characteristics. the automatic detection was performed by a two step classification. first, a vertex-wise classifier based on a neural-network bagging trained on manual labels. then, a cluster-wise classification designed to remove false positive clusters. the method was tested on 19 patients with small fcd. at the first classification step, 18/19 (95%) lesions were detected. the second classification step kept 13/19 (68%) lesions and decreased efficiently the amount of false positive. this new approach may assist the presurgical evaluation of patients with intractable epilepsy, especially those with unremarkable mri findings.
subject-specific biomechanical simulation of brain indentation using a meshless method. we develop a meshless method for simulating soft organ deformation. the method is motivated by simple, automatic model creation for real-time simulation. our method is meshless in the sense that deformation is calculated at nodes that are not part of an element mesh. node placement is almost arbitrary. fully geometrically nonlinear total lagrangian formulation is used. geometric integration is performed over a regular background grid that does not conform to the simulation geometry. explicit time integration is used via the central difference method. to validate the method we simulate indentation of a swine brain and compare the results to experimental data.
towards an identification of tumor growth parameters from time series of images. in cancer treatment, understanding the aggressiveness of the tumor is essential in therapy planning and patient follow-up. in this article, we present a novel method for quantifying the speed of invasion of gliomas in white and grey matter from time series of magnetic resonance (mr) images. the proposed approach is based on mathematical tumor growth models using the reaction-diffusion formalism. the quantification process is formulated by an inverse problem and solved using anisotropic fast marching method yielding an efficient algorithm. it is tested on a few images to get a first proof of concept with promising new results.
registration of lung tissue between fluoroscope and ct images: determination of beam gating parameters in radiotherapy. significant research has been conducted in radiation beam gating technology to manage target and organ motions in radiotherapy treatment of cancer patients. as more and more on-board imagers are installed onto linear accelerators, fluoroscopic imaging becomes readily available at the radiation treatment stage. thus, beam gating parameters, such as beam-on timing and beam-on window can be potentially determined by employing image registration between treatment planning ct images and fluoroscopic images. we propose a new registration method on deformable soft tissue between fluoroscopic images and drr (digitally reconstructed radiograph) images from planning ct images using active shape models. we present very promising results of our method applied to 30 clinical datasets. these preliminary results show that the method is very robust for the registration of deformable soft tissue. the proposed method can be used to determine beam-on timing and treatment window for radiation beam gating technology, and can potentially greatly improve radiation treatment quality.
a hybrid system for the semantic annotation of sulco-gyral anatomy in mri images. this paper presents an interactive system for the annotation of brain anatomical structures in magnetic resonance images. the system is based on hybrid knowledge and techniques. first, it exploits both numerical knowledge from atlases and symbolic knowledge from a rule-extended ontology represented in owl, the web ontology language, and combines them with graphical data about cortical sulci, automatically extracted from the images. second, the annotations of the parts of gyri and of sulci located in a region of interest are obtained with different reasoning techniques: constraint satisfaction solving and description logics techniques. preliminary experiments have been achieved on normal and also pathological data. the results obtained so far are very promising.
a new and general method for blind shift-variant deconvolution of biomedical images. we present a new method for blind deconvolution of multiple noisy images blurred by a shift-variant point-spread-function (psf). we focus on a setting in which several images of the same object are available, and a transformation between these images is known. this setting occurs frequently in biomedical imaging, for example in microscopy or in medical ultrasound imaging. by using the information from multiple observations, we are able to improve the quality of images blurred by a shift-variant filter, without prior knowledge of this filter. also, in contrast to other work on blind and shift-variant deconvolution, in our approach no parametrization of the psf is required. we evaluate the proposed method quantitatively on synthetically degraded data as well as qualitatively on 3d ultrasound images of liver. the algorithm yields good restoration results and proves to be robust even in presence of high noise levels in the images.
null point imaging: a joint acquisition/analysis paradigm for mr classification. automatic classification of neurological tissues is a first step to many structural analysis pipelines. most computational approaches are designed to extract the best possible classification results out of mr data acquired with standard clinical protocols. we observe that the characteristics of the latter owe more to the historical circumstances under which they were developed and the visual appreciation of the radiographer who acquires the images than to the optimality with which they can be classified with an automatic algorithm. we submit that better performances could be obtained by considering the acquisition and analysis processes conjointly rather than optimising them independently. here, we propose such a joint approach to mr tissue classification in the form of a fast mr sequence, which nulls the magnitude and changes the sign of the phase at the boundary between tissue types. a simple phase-based thresholding algorithm then suffices to segment the tissues. preliminary results show promises to simplify and shorten the overall classification process.
robust computation of mutual information using spatially adaptive meshes. we present a new method for the fast and robust computation of information theoretic similarity measures for alignment of multi-modality medical images. the proposed method defines a non-uniform, adaptive sampling scheme for estimating the entropies of the images, which is less vulnerable to local maxima as compared to uniform and random sampling. the sampling is defined using an octree partition of the template image, and is preferable over other proposed methods of non-uniform sampling since it respects the underlying data distribution. it also extends naturally to a multi-resolution registration approach, which is commonly employed in the alignment of medical images. the effectiveness of the proposed method is demonstrated using both simulated mr images obtained from the brainweb database and clinical ct and spect images.
cutting tool system to minimize soft tissue damage for robot-assisted minimally invasive orthopedic surgery. minimally invasive surgery in orthopedic field is considered to be a challenging problem with a milling robot. one objective of this study is to minimize collision of the cutting tool with soft tissue. the authors have developed a robot with redundant axis to avoid the collision so far. some important components are modeled based on physical requirements, and a geometric optimization approach based on the model has been also proposed to improve performance. in this paper, a protective mechanism to cover the non-working part of the cutting edge is proposed to avoid soft tissue damage. hardware and software have been developed for this application and the effectiveness of this technique was evaluated with urethane bone.
extracting tractosemas from a displacement probability field for tractography in dw-mri. in this paper we present a novel method for estimating a field of asymmetric spherical functions, dubbed tractosemas, given the intra-voxel displacement probability information. the peaks of tractosemas correspond to directions of distinct fibers, which can have either symmetric or asymmetric local fiber structure. this is in contrast to the existing methods that estimate fiber orientation distributions which are naturally symmetric and therefore cannot model asymmetries such as splaying fibers. we propose a method for extracting tractosemas from a given field of displacement probability iso-surfaces via a diffusion process. the diffusion is performed by minimizing a kernel convolution integral, which leads to an update formula expressed in the convenient form of a discrete kernel convolution. the kernel expresses the probability of diffusion between two neighboring spherical functions and we model it by the product of gaussian and von mises distributions. the model is validated via experiments on synthetic and real diffusion-weighted magnetic resonance (dw-mri) datasets from a rat hippocampus and spinal cord.
automatic trajectory planning for deep brain stimulation: a feasibility study. dbs for parkinson's disease involves an extensive planning to find a suitable electrode implantation path to the selected target. we have investigated the feasibility of improving the conventional planning with an automatic calculation of possible paths in 3d. this requires the segmentation of anatomical structures. subsequently, the paths are calculated and visualized. after selection of a suitable path, the settings for the stereotactic frame are determined. a qualitative evaluation has shown that automatic avoidance of critical structures is feasible. the participating neurosurgeons estimate the time gain to be around 30 minutes.
geometric deformable model driven by cocrfs: application to optical coherence tomography. we present a geometric deformable model driven by dynamically updated probability fields. the shape is defined with the signed distance function, and the internal (smoothness) energy consists of a c 1 continuity constraint, a shape prior, and a term that forces the zero-level of the shape distance function towards a connected form. the image probability fields are estimated by our collaborative conditional random field (cocrf), which is updated during the evolution in an active learning manner: it infers class posteriors in pixels or regions with feature ambiguities by assessing the joint appearance of neighboring sites and using the classification confidence. we apply our method to optical coherence tomography fundus images for the segmentation of geographic atrophies in dry age-related macular degeneration of the human eye.
contributions to 3d diffeomorphic atlas estimation: application to brain images. this paper focuses on the estimation of statistical atlases of 3d images by means of diffeomorphic transformations. within a log-euclidean framework, the exponential and logarithm maps of diffeomorphisms need to be computed. in this framework, the inverse scaling and squaring (iss) method has been recently extended for the computation of the logarithm map, which is one of the most time demanding stages. in this work we propose to apply the baker-campbell-hausdorff (bch) formula instead. in a 3d simulation study, bch formula and iss method obtained similar accuracy but bch formula was more than 100 times faster. this approach allowed us to estimate a 3d statistical brain atlas in a reasonable time, including the average and the modes of variation. details for the computation of the modes of variation in the sobolev tangent space of diffeomorphisms are also provided.
ultrasound myocardial elastography and registered 3d tagged mri: quantitative strain comparison. ultrasound myocardial elastography (ume) and tagged magnetic resonance imaging (tmri) are two imaging modalities that were developed in the recent years to quantitatively estimate the myocardial deformations. tagged mri is currently considered as the gold standard for myocardial strain mapping in vivo. however, despite the low snr nature of ultrasound signals, echocardiography enjoys the widespread availability in the clinic, as well as its low cost and high temporal resolution. comparing the strain estimation performances of the two techniques has been of great interests to the community. in order to assess the cardiac deformation across different imaging modalities, in this paper, we developed a semi-automatic intensity and gradient based registration framework that rigidly registers the 3d tagged mris with the 2d ultrasound images. based on the two registered modalities, we conducted spatially and temporally more detailed quantitative strain comparison of the rf-based ume technique and tagged mri. from the experimental results, we conclude that qualitatively the two modalities share similar overall trends. but error and variations in ume accumulate over time. quantitatively tmri is more robust and accurate than ume.
diffuse parenchymal lung diseases: 3d automated detection in mdct. characterization and quantification of diffuse parenchymal lung disease (dpld) severity using mdct, mainly in interstitial lung diseases and emphysema, is an important issue in clinical research for the evaluation of new therapies. this paper develops a 3d automated approach for detection and diagnosis of dplds (emphysema, fibrosis, honeycombing, ground glass).the proposed methodology combines multiresolution image decomposition based on 3d morphological filtering, and graph-based classification for a full characterization of the parenchymal tissue. the very promising results obtained on a small patient database are good premises for a near implementation and validation of the proposed approach in clinical routine.
unsupervised reconstruction of a patient-specific surface model of a proximal femur from calibrated fluoroscopic images. in this paper, we present an unsupervised 2d/3d reconstruction scheme combining a parameterized multiple-component geometrical model and a point distribution model, and show its application to automatically reconstruct a surface model of a proximal femur from a limited number of calibrated fluoroscopic images with no user intervention at all. the parameterized multiple-component geometrical model is regarded as a simplified description capturing the geometrical features of a proximal femur. its parameters are optimally and automatically estimated from the input images using a particle filter based inference method. the estimated geometrical parameters are then used to initialize a point distribution model based 2d/3d reconstruction scheme for an accurate reconstruction of a surface model of the proximal femur. we designed and conducted in vitro and in vivo experiments to compare the present unsupervised reconstruction scheme to a supervised one. an average mean error of 1.2 mm was found when the supervised reconstruction scheme was used. it increased to 1.3 mm when the unsupervised one was used. however, the unsupervised reconstruction scheme has the advantage of elimination of user intervention, which holds the potential to facilitate the application of the 2d/3d reconstruction in surgical navigation.
sample sufficiency and number of modes to retain in statistical shape modelling. statistical shape modelling is a popular technique in medical imaging, but the issue of sample size sufficiency is not generally considered. also the number of principal modes retained is often chosen simply to cover a percentage of the total variance. we show that these simple rules are unreliable. we propose a new method that uses bootstrap replication and a t-test comparison with noise to decide whether each mode direction has stabilised. we establish mode correspondence by minimising the distance between the space spanned by the replicates and their mean. by retaining only stable modes, our method distinguishes real anatomical variation from modes dominated by random noise. this provides a lower stopping rule when the sample is small and converges as the sample size increases. we use this convergence to determine sample sufficiency. for validation we use synthetic datasets of the left ventricle generated with a known number of structural modes and added noise. our stopping rule detected the correct number of modes to retain where other methods failed. the methods were also tested on real 2d (22 points) and 3d (500 points) face data, retaining 24 and 70 modes with sample sufficiency being reached at approximately 50 and 150 samples respectively. for a 3d database of the left ventricle (527 points), 319 samples are not sufficient, but at this level we can retain around 55 stable modes. our method provides a principled foundation for appropriate selection of the number of modes to retain and determination of sample size sufficiency for statistical shape modelling.
cardiac-motion compensated mr imaging and strain analysis of ventricular trabeculae. in conventional cmr, bulk cardiac motion causes target structures to move in and out of the static acquisition plane. due to the partial volume effect, accurate localisation of subtle features through the cardiac cycle, such as the trabeculae and papillary muscles, is difficult. this problem is exacerbated by the short acquisition window necessary to avoid motion blur and ghosting, especially during early systole. this paper presents an adaptive imaging approach with comb multi-tag tracking that follows true 3d motion of the myocardium so that the same tissue slice is imaged throughout the cine acquisition. the technique is demonstrated with motion-compensated multi-slice imaging of ventricles, which allows for tracked visualisation and analysis of the trabeculae and papillary muscles for the first time. this enables novel in-vivo measurement of circumferential and radial strain for trabeculation and papillary muscle contractility. these statistics will facilitate the evaluation of diseases such as mitral valve insufficiency and ischemic heart disease. the adaptive imaging technique will also have significant implications for cmr in general, including motion-compensated quantification of myocardial perfusion and blood flow, and motion-correction of sequences with long acquisition windows.
high throughput analysis of breast cancer specimens on the grid. breast cancer accounts for about 30% of all cancers and 15% of all cancer deaths in women in the united states. advances in computer assisted diagnosis (cad) holds promise for early detecting and staging disease progression. in this paper we introduce a grid-enabled cad to perform automatic analysis of imaged histopathology breast tissue specimens. more than 100,000 digitized samples (1200 × 1200 pixels) have already been processed on the grid. we have analyzed results for 3744 breast tissue samples, which were originated from four different institutions using diaminobenzidine (dab) and hematoxylin staining. both linear and nonlinear dimension reduction techniques are compared, and the best one (isomap) was applied to reduce the dimensionality of the features. the experimental results show that the gentle boosting using an eight node cart decision tree as the weak learner provides the best result for classification. the algorithm has an accuracy of 86.02% using only 20% of the specimens as the training set.
spine segmentation using articulated shape models. including prior shape in the form of anatomical models is a well-known approach for improving segmentation results in medical images. currently, most approaches are focused on the modeling and segmentation of individual objects. in case of object constellations, a simultaneous segmentation of the ensemble that uses not only prior knowledge of individual shapes but also additional information about spatial relations between the objects is often beneficial. in this paper, we present a two-scale framework for the modeling and segmentation of the spine as an example for object constellations. the global spine shape is expressed as a consecution of local vertebra coordinate systems while individual vertebrae are modeled as triangulated surface meshes. adaptation is performed by attracting the model to image features but restricting the attraction to a former learned shape. with the developed approach, we obtained a segmentation accuracy of 1.0 mm in average for ten thoracic ct images improving former results.
on classifying disease-induced patterns in the brain using diffusion tensor images. diffusion tensor imaging (dti) provides rich information about brain tissue structure especially in the white matter, which is known to be affected in several diseases like schizophrenia. identifying patterns of brain changes induced by pathology is therefore crucial to clinical studies. however, the high dimensionality and complex structure of dti make it difficult to apply conventional linear statistical and pattern classification methods to identify such patterns. in this paper, we present a novel framework that uses a combination of dti-based anisotropy and geometry features to effectively identify brain regions with pathology-induced abnormality, and to classify brains into the diseased and healthy groups. our method first directly estimates the underlying overlap between the patient and control groups, based on a semi-parametric bayes error estimation method. by ranking voxels based on these estimation results, the method identifies abnormal brain regions from which features are extracted through kernel principal component analysis (kpca) for subsequent classification. application of the method to a dataset of controls and patients with schizophrenia, demonstrates promising accuracy of this framework in identifying brain patterns to separate two groups, and hence aiding in prognosis and treatment.
3d/2d image registration: the impact of x-ray views and their number. an important part of image-guided radiation therapy or surgery is registration of a three-dimensional (3d) preoperative image to two-dimensional (2d) images of the patient. it is expected that the accuracy and robustness of a 3d/2d image registration method do not depend solely on the registration method itself but also on the number and projections (views) of intraoperative images. in this study, we systematically investigate these factors by using registered image data, comprising of ct and x-ray images of a cadaveric lumbar spine phantom and the recently proposed 3d/2d registration method [1], [2]. the results indicate that the proportion of successful registrations (robustness) significantly increases when more x-ray images are used for registration.
automatic segmentation of blood vessels from dynamic mri datasets. in this paper we present an approach for blood vessel segmentation from dynamic contrast-enhanced mri datasets of the hand joints acquired from patients with active rheumatoid arthritis. exclusion of the blood vessels is needed for accurate visualisation of the activation events and objective evaluation of the degree of inflammation. the segmentation technique is based on statistical modelling motivated by the physiological properties of the individual tissues, such as speed of uptake and concentration of the contrast agent; it incorporates markov random field probabilistic framework and principal component analysis. the algorithm was tested on 60 temporal slices and has shown promising results.
generalized surface flows for deformable registration and cortical matching. despite being routinely required in medical applications, deformable surface registration is notoriously difficult due to large intersubject variability and complex geometry of most medical datasets.we present a general and flexible deformable matching framework based on generalized surface flows that efficiently tackles these issues through tailored deformation priors and multiresolution computations. the value of our approach over existing methods is demonstrated for automatic and user-guided cortical registration.
lv motion and strain computation from tmri based on meshless deformable models. we propose a novel meshless deformable model for in vivo left ventricle (lv) 3d motion estimation and analysis based on tagged mri (tmri). the meshless deformable model can capture global deformations such as contraction and torsion with a few parameters, while track local deformations with laplacian representation. in particular, the model performs well even when the control points (tag intersections) are relatively sparse. we test the performance of the meshless model on a numeric phantom, as well as in vivo heart data of healthy subjects and patients. the experimental results show that the meshless deformable model can fully recover the myocardial motion and strain in 3d.
statistical atlases of bone anatomy: construction, iterative improvement and validation. we present an iterative bootstrapping framework to create and analyze statistical atlases of bony anatomy such as the human pelvis from a large collection of ct data sets. we create an initial tetrahedral mesh representation of the target anatomy and use deformable intensity-based registration to create an initial atlas. this atlas is used as prior information to assist in deformable registration/segmentation of our subject image data sets, and the process is iterated several times to remove any bias from the initial choice of template subject and to improve the stability and consistency of mean shape and variational modes. we also present a framework to validate the statistical models. using this method, we have created a statistical atlas of full pelvis anatomy with 110 healthy patient ct scans. our analysis shows that any given pelvis shape can be approximated up to an average accuracy of 1.5036 mm using the first 15 principal modes of variation. although a particular intensity-based deformable registration algorithm was used to produce these results, we believe that the basic method may be adapted readily for use with any registration method with broadly similar characteristics.
thoracic ct-pet registration using a 3d breathing model. in the context of thoracic ct-pet volume registration, we present a novel method to incorporate a breathing model in a non-linear registration procedure, guaranteeing physiologically plausible deformations. the approach also accounts for the rigid motions of lung tumors during breathing. we performed a set of registration experiments on one healthy and four pathological data sets. initial results demonstrate the interest of this method to significantly improve the accuracy of multimodal volume registration for diagnosis and radiotherapy applications.
comparison and evaluation of segmentation techniques for subcortical structures in brain mri. the automation of segmentation of medical images is an active research area. however, there has been criticism of the standard of evaluation of methods. we have comprehensively evaluated four novel methods of automatically segmenting subcortical structures using volumetric, spatial overlap and distance-based measures. two of the methods are atlas-based --- classifier fusion and labelling (cfl) and expectation-maximisation segmentation using a dynamic brain atlas (ems), and two model-based --- profile active appearance models (pam) and bayesian appearance models (bam). each method was applied to the segmentation of 18 subcortical structures in 270 subjects from a diverse pool varying in age, disease, sex and image acquisition parameters. our results showed that all four methods perform on par with recently published methods. cfl performed significantly better than the other three methods according to all three classes of metrics.
magneto-optic tracking of a flexible laparoscopic ultrasound transducer for laparoscope augmentation. in abdominal surgery, a laparoscopic ultrasound transducer is commonly used to detect lesions such as metastases. the determination and visualization of position and orientation of its flexible tip in relation to the patient or other surgical instruments can be of much help to (novice) surgeons utilizing the transducer intraoperatively. this difficult subject has recently been paid attention to by the scientific community [1, 2, 3, 4, 5, 6]. electromagnetic tracking systems can be applied to track the flexible tip. however, the magnetic field can be distorted by ferromagnetic material. this paper presents a new method based on optical tracking of the laparoscope and magneto-optic tracking of the transducer, which is able to automatically detect field distortions. this is used for a smooth augmentation of the b-scan images of the transducer directly on the camera images in real time.
groupwise combined segmentation and registration for atlas construction. the creation of average anatomical atlases has been a growing area of research in recent years. it is of increased value to construct representations of, not only intensity atlases, but also their segmentation into required tissues or structures. this paper presents novel groupwise combined segmentation and registration approaches, which aim to simultaneously improve both the alignment of intensity images to their average shape, as well as the segmentations of structures in the average space. an iterative em framework is used to build average 3d mr atlases of populations for which prior atlases do not currently exist: preterm infants at one- and two-years old. these have been used to quantify the growth of tissues occurring between these ages.
multivariate normalization with symmetric diffeomorphisms for multivariate studies. current clinical and research neuroimaging protocols acquire images using multiple modalities, for instance, t1, t2, diffusion tensor and cerebral blood flow magnetic resonance images (mri). these multivariate datasets provide unique and often complementary anatomical and physiological information about the subject of interest. we present a method that uses fused multiple modality (scalar and tensor) datasets to perform intersubject spatial normalization. our multivariate approach has the potential to eliminate inconsistencies that occur when normalization is performed on each modality separately. furthermore, the multivariate approach uses a much richer anatomical and physiological image signature to infer image correspondences and perform multivariate statistical tests. in this initial study, we develop the theory for multivariate symmetric normalization (mvsyn), establish its feasibility and discuss preliminary results on a multivariate statistical study of 22q deletion syndrome.
cell spreading analysis with directed edge profile-guided level set active contours. cell adhesion and spreading within the extracellular matrix (ecm) plays an important role in cell motility, cell growth and tissue organization. measuring cell spreading dynamics enables the investigation of cell mechanosensitivity to external mechanical stimuli, such as substrate rigidity. a common approach to measure cell spreading dynamics is to take time lapse images and quantify cell size and perimeter as a function of time. in our experiments, differences in cell characteristics between different treatments are subtle and require accurate measurements of cell parameters across a large population of cells to ensure an adequate sample size for statistical hypothesis testing. this paper presents a new approach to estimate accurate cell boundaries with complex shapes by applying a modified geodesic active contour level set method that directly utilizes the halo effect typically seen in phase contrast microscopy. contour evolution is guided by edge profiles in a perpendicular direction to ensure convergence to the correct cell boundary. the proposed approach is tested on bovine aortic endothelial cell images under different treatments, and demonstrates accurate segmentation for a wide range of cell sizes and shapes compared to manual ground truth.
robust kernel methods for sparse mr image reconstruction. a major challenge in contemporary magnetic resonance imaging (mri) lies in providing the highest resolution exam possible in the shortest acquisition period. recently, several authors have proposed the use of l1-norm minimization for the reconstruction of sparse mr images fromhighly-undersampled k-space data. despite promising results demonstrating the ability to accurately reconstruct images sampled at rates significantly below the nyquist criterion, the extensive computational complexity associated with the existing framework limits its clinical practicality. in this work, we propose an alternative recovery framework based on homotopic approximation of the l0-norm and extend the reconstruction problemto a multiscale formulation. in addition to several interesting theoretical properties, practical implementation of this technique effectively resorts to a simple iterative alternation between bilteral filtering and projection of themeasured k-space sample set that can be computed in a matter of seconds on a standard pc.
a slicing-based coherence measure for clusters of dti integral curves. we present a slicing-based coherence measure for clusters of dti integral curves. for a given cluster, we probe samples from the cluster by slicing it with a plane at regularly spaced locations parametrized by curve arc lengths. then we compute a stability measure based on the spatial relations between the projections of the curve points in individual slices and their change across the slices. we demonstrate its use in refining agglomerative hierarchical clustering results of dti curves that correspond to neural pathways. expert evaluation shows that refinement based on our measure can lead to improvement of clustering that is not possible directly by using standard methods.
automatic determination of arterial input function for dynamic contrast enhanced mri in tumor assessment. dynamic contrast enhanced mri (dce-mri) is today one of the most popular methods for tumor assessment. several pharmacokinetic models have been proposed to analyze dce-mri. most of them depend on an accurate arterial input function (aif). we propose an automatic and versatile method to determine the aif. the method has two stages, detection and segmentation, incorporating knowledge about artery structure, fluid kinetics, and the dynamic temporal property of dce-mri. we have applied our method in dce-mris of four different body parts: breast, brain, liver and prostate. the results show that we achieve average 89.5% success rate for 40 cases. the pharmacokinetic parameters computed from the automatic aif are highly agreeable with those from a manually derived aif (r2=0.89, p(t<=t)=0.19) and a semiautomatic aif (r2=0.98, p(t<=t)=0.01).
geodesic-loxodromes for diffusion tensor interpolation and difference measurement. in algorithms for processing diffusion tensor images, two common ingredients are interpolating tensors, and measuring the distance between them. we propose a new class of interpolation paths for tensors, termed geodesic-loxodromes, which explicitly preserve clinically important tensor attributes, such as mean diffusivity or fractional anisotropy, while using basic differential geometry to interpolate tensor orientation. this contrasts with previous riemannian and log-euclidean methods that preserve the determinant. path integrals of tangents of geodesic-loxodromes generate novel measures of over-all difference between two tensors, and of difference in shape and in orientation.
quantification of measurement error in dti: theoretical predictions and validation. the presence of rician noise in magnetic resonance imaging (mri) introduces systematic errors in diffusion tensor imaging (dti) measurements. this paper evaluates gradient direction schemes and tensor estimation routines to determine how to achieve the maximum accuracy and precision of tensor derived measures for a fixed amount of scan time. we present monte carlo simulations that quantify the effect of noise on diffusion measurements and validate these simulation results against appropriate in-vivo images. the predicted values of the systematic and random error caused by imaging noise are essential both for interpreting the results of statistical analysis and for selecting optimal imaging protocols given scan time limitations.
in-utero three dimension high resolution fetal brain diffusion tensor imaging. we present a methodology to achieve 3d high resolution in-utero fetal brain dti that shows excellent adc as well as promising fa maps. after continuous dti scanning to acquire a repeated series of parallel slices with 15 diffusion directions, image registration is used to realign the images to correct for fetal motion. once aligned, the diffusion images are treated as irregularly sampled data where each voxel is associated with an appropriately rotated diffusion direction, and used to estimate the diffusion tensor on a regular grid. the method has been tested successful on eight fetuses and has been validated on adults imaged at 1.5t.
prostate cancer probability maps based on ultrasound rf time series and svm classifiers. we describe a very efficient method based on ultrasound rf time series analysis and support vector machine classification for generating probabilistic prostate cancer colormaps to augment the biopsy process. to form the rf time series, we continuously record ultrasound rf echoes backscattered from tissue while the imaging probe and the tissue are stationary in position. in an in-vitro study involving 30 prostate specimens, we show that the features extracted from rf time series are significantly more accurate and sensitive compared to two other established categories of ultrasound-based tissue typing methods. the method results in an area under roc curve of 0.95 in 10-fold cross-validation.
finsler tractography for white matter connectivity analysis of the cingulum bundle. in this paper, we present a novel approach for the segmentation of white matter tracts based on finsler active contours. this technique provides an optimal measure of connectivity, explicitly segments the connecting fiber bundle, and is equipped with a metric which is able to utilize the directional information of high angular resolution data. we demonstrate the effectiveness of the algorithm for segmenting the cingulum bundle.
segmentation of myocardial volumes from real-time 3d echocardiography using an incompressibility constraint. real-time three-dimensional (rt3d) echocardiography is a new imaging modality that presents the unique opportunity to visualize the complex three-dimensional (3-d) shape and the motion of left ventricle (lv) in vivo. to take advantage of this opportunity, automatic segmentation of lv myocardium is essential. while there are a variety of efforts on the segmentation of lv endocardial (endo) boundaries, the segmentation of epicardial (epi) boundaries is still problematic. in this paper, we present a new approach of coupled-surfaces propagation to address this problem. our method is motivated by the idea that the volume of the myocardium is close to being constant during a cardiac cycle and takes this tight coupling as an important constraint. we employ two surfaces, each driven by the image-derived information that takes into account the ultrasound physics by modeling speckle using shifted rayleigh distribution while maintaining the coupling. by evolving two surfaces simultaneously, the final representation of myocardium is thus achieved. results from 328 sets of rt3d echocardiographic data are evaluated against the outlines of three observers. we show that the results from automatic segmentation are comparable to those from manual segmentation.
localized shape variations for classifying wall motion in echocardiograms. to quantitatively predict coronary artery diseases, automated analysis may be preferred to current visual assessment of left ventricular (lv) wall motion. in this paper, a novel automated classification method is presented which uses shape models with localized variations. these sparse shape models were built from four-chamber and two-chamber echocardiographic sequences using principal component analysis and orthomax rotations. the resulting shape parameters were then used to classify local wall-motion abnormalities of lv segments. various orthomax criteria were investigated. in all cases, higher classification correctness was achieved using significantly less shape parameters than before rotation. since pathologies are typically spatially localized, many medical applications involving local classification should benefit from orthomax parameterizations.
image guidance of intracardiac ultrasound with fusion of pre-operative images. this paper presents a method for registering 3d intracardiac echo (ice) to pre-operative images. a magnetic tracking sensor is integrated on the ice catheter tip to provide the 3d location and orientation. the user guides the catheter into the patient heart to acquire a series of ultrasound images covering the anatomy of the heart chambers. an automatic intensity-based registration algorithm is applied to align these ultrasound images with pre-operative images. one of the important applications is to help electrophysiology doctors to treat complicated atrial fibrillation cases. after registration, the doctor can see the position and orientation of the ice catheter and other tracked catheters inside the heart anatomy in real time. the image guidance provided by this technique may increase the ablation accuracy and reduce the amount of time for the electrophysiology procedures. we show successful image registration results from animal experiments.
3d reconstruction of internal organ surfaces for minimal invasive surgery. while minimally invasive surgery (mis) offers great benefits to patients compared with open surgery surgeons suffer from a restricted field-of-view and obstruction from instruments. we present a novel method for 3d reconstruction of soft tissue, which can provide a wider field-of-view with 3d information for surgeons, including restoration of missing data. the paper focuses on the use of structure from motion (sfm) techniques to solve the missing data problem and application of competitive evolutionary agents to improve the robustness to missing data and outliers. the method has been evaluated with synthetic data, images from a phantom heart model, and in vivo mis image sequences using the da vinci telerobotic surgical system.
automated segmentation of the liver from 3d ct images using probabilistic atlas and multi-level statistical shape model. an atlas-based automated liver segmentation method from 3d ct images is described. the method utilizes two types of atlases, that is, the probabilistic atlas (pa) and statistical shape model (ssm). voxel-based segmentation with pa is firstly performed to obtain a liver region, and then the obtained region is used as the initial region for subsequent ssm fitting to 3d ct images. to improve reconstruction accuracy especially for largely deformed livers, we utilize a multi-level ssm (ml-ssm). in ml-ssm, the whole shape is divided into patches, and principal component analysis is applied to each patches. to avoid the inconsistency among patches, we introduce a new constraint called the adhesiveness constraint for overlap regions among patches. in experiments, we demonstrate that segmentation accuracy improved by using the initial region obtained with pa and the introduced constraint for ml-ssm.
statistical and topological atlas based brain image segmentation. this paper presents a new atlas-based segmentation framework for the delineation of major regions in magnetic resonance brain images employing an atlas of the global topological structure as well as a statistical atlas of the regions of interest. a segmentation technique using fast marching methods and tissue classification is proposed that guarantees strict topological equivalence between the segmented image and the atlas. experimental validation on simulated and real brain images shows that the method is accurate and robust.
a boosted segmentation method for surgical workflow analysis. as demands on hospital efficiency increase, there is a stronger need for automatic analysis, recovery, and modification of surgical workflows. even though most of the previous work has dealt with higher level and hospital-wide workflow including issues like document management, workflow is also an important issue within the surgery room. its study has a high potential, e.g., for building context-sensitive operating rooms, evaluating and training surgical staff, optimizing surgeries and generating automatic reports. in this paper we propose an approach to segment the surgical workflow into phases based on temporal synchronization of multidimensional state vectors. our method is evaluated on the example of laparoscopic cholecystectomy with state vectors representing tool usage during the surgeries. the discriminative power of each instrument in regard to each phase is estimated using adaboost. a boosted version of the dynamic time warping (dtw) algorithm is used to create a surgical reference model and to segment a newly observed surgery. full cross-validation on ten surgeries is performed and the method is compared to standard dtw and to hidden markov models.
detection of spatial activation patterns as unsupervised segmentation of fmri data. in functional connectivity analysis, networks of interest are defined based on correlation with the mean time course of a user-selected 'seed' region. in this work we propose to simultaneously estimate the optimal representative time courses that summarize the fmri data well and the partition of the volume into a set of disjoint regions that are best explained by these representative time courses. our approach offers two advantages. first, is removes the sensitivity of the analysis to the details of the seed selection. second, it substantially simplifies group analysis by eliminating the need for a subject-specific threshold at which correlation values are deemed significant. this unsupervised technique generalizes connectivity analysis to situations where candidate seeds are difficult to identify reliably or are unknown. our experimental results indicate that the functional segmentation provides a robust, anatomically meaningful and consistent model for functional connectivity in fmri.
robotic assistance for ultrasound guided prostate brachytherapy. we present a robotically assisted prostate brachytherapy system and test results in training phantoms. the system consists of a transrectal ultrasound (trus) and a spatially co-registered robot integrated with an fda-approved commercial treatment planning system. the salient feature of the system is a small parallel robot affixed to the mounting posts of the template. the robot replaces the template interchangeably and uses the same coordinate system. established clinical hardware, workflow and calibration are left intact. in these experiments, we recorded the first insertion attempt without adjustment. all clinically relevant locations were reached. non-parallel needle trajectories were achieved. the pre-insertion transverse and rotational errors (measured with polaris optical tracker relative to the template's coordinate frame) were 0.25mm (std=0.17mm) and 0.75° (std=0.37°). the needle tip placement errors measured in trus were 1.04mm (std=0.50mm). the system is in phase-i clinical feasibility and safety trials, under institutional review board approval.
closed-loop control in fused mr-trus image-guided prostate biopsy. multi-modality fusion imaging for targeted prostate biopsy is difficult because of prostate motion during the biopsy procedure. a closed-loop control mechanism is proposed to improve the efficacy and safety of the biopsy procedure, which uses real-time ultrasound and spatial tracking as feedback to adjust the registration between a preoperative 3d image (e.g. mri) and real-time ultrasound images. the spatial tracking data is used to initialize the image-based registration between intraoperative ultrasound images and a preoperative ultrasound volume. the preoperative ultrasound volume is obtained using a 2d sweep and manually registered to the mri dataset before the biopsy procedure. the accuracy of the system is 2.3±0.9 mm in phantom studies. the results of twelve patient studies show that prostate motion can be effectively compensated using closed-loop control.
medical and technical protocol for automatic navigation of a wireless device in the carotid artery of a living swine using a standard clinical mri system. a 1.5 mm magnetic sphere was navigated automatically inside the carotid artery of a living swine. the propulsion force, tracking and real-time capabilities of a magnetic resonance imaging (mri) system were integrated into a closed loop control platform. the sphere was released using an endovascular catheter approach. specially developed software is responsible for the tracking, propulsion, event timing and closed loop position control in order to follow a 10 roundtrips preplanned trajectory on a distance of 5 cm inside the right carotid artery of the animal. experimental protocol linking the technical aspects of this in vivo assay is presented. in the context of this demonstration, many challenges which provide insights about concrete issues of future nanomedical interventions and interventional platforms have been identified and addressed.
improving the contrast of breast cancer masses in ultrasound using an autoregressive model based filter. the assessment and diagnosis of breast cancer with ultrasound is a challenging problem due to the low contrast between cancer masses and benign tissue. due to this low contrast it has proven to be difficult to achieve reliable segmentation results on breast cancer masses. an autoregressive model has been employed to filter out of the backscattered rf-signal from a tissue harmonic image which is not degraded by harmonic leakage. measurements on the filtered image have shown a significant (up to 45 %) increase in contrast between cancer masses and benign tissue.
outlier rejection for diffusion weighted imaging. this paper introduces an outlier rejection and signal reconstruction method for high angular resolution diffusion weighted imaging. the approach is based on the thresholding of laplacian measurements over the sphere of the apparent diffusion coefficient profiles defined for a given set of gradient directions. exemplary results are presented.
generating fiber crossing phantoms out of experimental dwis. in diffusion tensor imaging (dti), differently oriented fiber bundles inside one voxel are incorrectly modeled by a single tensor. high angular resolution diffusion imaging (hardi) aims at using more complex models, such as a two-tensor model, for estimating two fiber bundles. we propose a new method for creating experimental phantom data of fiber crossings, by mixing the dwi-signals from high fa-regions with different orientation. the properties of these experimental phantoms approach the conditions of real data. these phantoms can thus serve as a 'ground truth' in validating crossing reconstruction algorithms. the angular resolution of a dual tensor model is determined using series of crossings, generated under different angles. an angular resolution of 0.6π was found in data scanned with a diffusion weighting parameter b=1000 s/mm2. this resolution did not change significantly in experiments with b=3000 and 5000 s/mm2, keeping the scanning time constant.
motion and positional error correction for cone beam 3d-reconstruction with mobile c-arms. ct-images acquired by mobile c-arm devices can contain artefacts caused by positioning errors. we propose a data driven method based on iterative 3d-reconstruction and 2d/3d-registration to correct projection data inconsistencies. with a 2d/3d-registration algorithm, transformations are computed to align the acquired projection images to a previously reconstructed volume. in an iterative procedure, the reconstruction algorithm uses the results of the registration step. this algorithm also reduces small motion artefacts within 3d-reconstructions. experiments with simulated projections from real patient data show the feasibility of the proposed method. in addition, experiments with real projection data acquired with an experimental robotised c-arm device have been performed with promising results.
cortical hemisphere registration via large deformation diffeomorphic metric curve mapping. we present large deformation diffeomorphic metric curve mapping (lddmm-curve) for registering cortical hemispheres. we showed global cortical hemisphere matching and evaluated the mapping accuracy in five subregions of the cortex in fourteen mri scans.
tagged volume rendering of the heart. we present a novel system for 3-d visualisation of the heart and coronary arteries. binary tags (generated offline) are combined with value-gradient transfer functions (specified online) allowing for interactive visualisation, while relaxing the offline segmentation criteria. the arteries are roughly segmented using a hessian-based line filter and the pericardial cavity using a fast marching active contour. a comparison of different contour initialisations reveals that simple geometric shapes (such as spheres or extruded polygons) produce suitable results.
one-class acoustic characterization applied to blood detection in ivus. intravascular ultrasound (ivus) is an invasive imaging modality capable of providing cross-sectional images of the interior of a blood vessel in real time and at normal video framerates (10-30 frames/s). low contrast between the features of interest in the ivus imagery remains a confounding factor in ivus analysis; it would be beneficial therefore to have a method capable of detecting certain physical features imaged under ivus in an automated manner. we present such a method and apply it to the detection of blood. while blood detection algorithms are not new in this field, we deviate from traditional approaches to ivus signal characterization in our use of 1-class learning. this eliminates certain problems surrounding the need to provide "foreground" and "background" (or, more generally, n-class) samples to a learner. applied to the blood-detection problem on 40 mhz recordings made in vivo in swine, we are able to achieve ∼95% sensitivity with ∼90% specificity at a radial resolution of ∼600 µm.
phase sensitive reconstruction for water/fat separation in mr imaging using inverse gradient. this paper presents a novel method for phase unwrapping for phase sensitive reconstruction in mr imaging. the unwrapped phase is obtained by integrating the phase gradient by solving a poisson equation. an efficient solver, which has been made publicly available, is used to solve the equation. the proposed method is demonstrated on a fat quantification mri task that is a part of a prospective study of fat accumulation. the method is compared to a phase unwrapping method based on region growing. results indicate that the proposed method provides more robust unwrapping. unlike region growing methods, the proposed method is also straight-forward to implement in 3d.
locus: local cooperative unified segmentation of mri brain scans. we propose to carry out cooperatively both tissue and structure segmentations by distributing a set of local and cooperative models in a unified mrf framework. tissue segmentation is performed by partitionning the volume into subvolumes where local mrfs are estimated in cooperation with their neighbors to ensure consistency. local estimation fits precisely to the local intensity distribution and thus handles nonuniformity of intensity without any bias field modelization. structure segmentation is performed via local mrfs that integrate localization constraints provided by a priori general fuzzy description of brain anatomy. structure segmentation is not reduced to a postprocessing step but cooperates with tissue segmentation to gradually and conjointly improve models accuracy. the evaluation was performed using phantoms and real 3t brain scans. it shows good results and in particular robustness to nonuniformity and noise with a low computational cost.
spline based inhomogeneity correction for c-pib pet segmentation using expectation maximization. with the advent of biomarkers such as 11c-pib and the increase in use of pet, automated methods are required for processing and analyzing datasets from research studies and in clinical settings. a common preprocessing step is the calculation of standardized uptake value ratio (suvr) for inter-subject normalization. this requires segmented grey matter (gm) for voi refinement. however 11c-pib uptake is proportional to amyloid build up leading to inhomogeneities in intensities, especially within gm. inhomogeneities present a challenge for clustering and pattern classification based approaches to pet segmentation as proposed in current literature. in this paper we modify a mr image segmentation technique based on expectation maximization for 11c-pib pet segmentation. a priori probability maps of the tissue types are used to initialize and enforce anatomical constraints. we developed a bézier spline based inhomogeneity correction techniques that is embedded in the segmentation algorithm and minimizes inhomogeneity resulting in better segmentations of 11c-pib pet images. we compare our inhomogeneity with a global polynomial correction technique and validate our approach using co-registered mri segmentations.
hyperspherical von mises-fisher mixture (hvmf) modelling of high angular resolution diffusion mri. a mapping of unit vectors onto a 5d hypersphere is used to model and partition odfs from hardi data. this mapping has a number of useful and interesting properties and we make a link to interpretation of the second order spherical harmonic decompositions of hardi data. the paper presents the working theory and experiments of using a von mises-fisher mixture model for directional samples. the mle of the second moment of the hvmf pdf can also be related to fractional anisotropy. we perform error analysis of the estimation scheme in single and multi-fibre regions and then show how a penalised-likelihood model selection method can be employed to differentiate single and multiple fibre regions.
use of varying constraints in optimal 3-d graph search for segmentation of macular optical coherence tomography images. an optimal 3-d graph search approach designed for simultaneous multiple surface detection is extended to allow for varying smoothness and surface interaction constraints instead of the traditionally used constant constraints. we apply the method to the intraretinal layer segmentation of 24 3-d optical coherence tomography (oct) images, learning the constraints from examples in a leave-one-subject-out fashion. introducing the varying constraints decreased the mean unsigned border positioning errors (mean error of 7.3 ± 3.7 µm using varying constraints compared to 8.3 ± 4.9 µm using constant constraints and 8.2 ± 3.5 µm for the inter-observer variability).
automatic segmentation of bladder and prostate using coupled 3d deformable models. in this paper, we propose a fully automatic method for the coupled 3d localization and segmentation of lower abdomen structures. we apply it to the joint segmentation of the prostate and bladder in a database of ct scans of the lower abdomen of male patients. a flexible approach on the bladder allows the process to easily adapt to high shape variation and to intensity inhomogeneities that would be hard to characterize (due, for example, to the level of contrast agent that is present). on the other hand, a statistical shape prior is enforced on the prostate. we also propose an adaptive non-overlapping constraint that arbitrates the evolution of both structures based on the availability of strong image data at their common boundary. the method has been tested on a database of 16 volumetric images, and the validation process includes an assessment of inter-expert variability in prostate delineation, with promising results.
characterizing spatio-temporal patterns for disease discrimination in cardiac echo videos. disease-specific understanding of echocardiographic sequences requires accurate characterization of spatio-temporal motion patterns. in this paper we present a method of automatic extraction and matching of spatio-temporal patterns from cardiac echo videos. specifically, we extract cardiac regions (chambers and walls) using a variation of multiscale normalized cuts that combines motion estimates from deformable models with image intensity. we then derive spatio-temporal trajectories of region measurements such as wall motion, volume and thickness. the region trajectories are then matched to infer the similarities in disease labels of patients. validation results on patient data sets collected from many hospitals are presented.
integrating functional and structural images for simultaneous cardiac segmentation and deformation recovery. because of their physiological meaningfulness, cardiac physiome models have been used as constraints to recover patient information from medical images. although the results are promising, the parameters of the physiome models are not patient-specific, and thus affect the clinical relevance of the recovered information especially in pathological cases. in view of this problem, we incorporate patient information from body surface potential maps in the physiome model to provide a more patient-specific while physiological plausible guidance, which is further coupled with patient measurements derived from structural images to recover the cardiac geometry and deformation simultaneously. experiments have been conducted on synthetic data to show the benefits of the framework, and on real human data to show its practical potential.
statistical shape modeling using mdl incorporating shape, appearance, and expert knowledge. we propose a highly automated approach to the point correspondence problem for anatomical shapes in medical images. manual landmarking is performed on a small subset of the shapes in the study, and a machine learning approach is used to elucidate the characteristic shape and appearance features at each landmark. a classifier trained using these features defines a cost function that drives key landmarks to anatomically meaningful locations after mdl-based correspondence establishment. results are shown for artificial examples as well as real data.
false positive reduction in mammographic mass detection using local binary patterns. in this paper we propose a new approach for false positive reduction in the field of mammographic mass detection. the goal is to distinguish between the true recognized masses and the ones which actually are normal parenchyma. our proposal is based on local binary patterns (lbp) for representing salient micro-patterns and preserving at the same time the spatial structure of the masses. once the descriptors are extracted, support vector machines (svm) are used for classifying the detected masses. we test our proposal using a set of 1792 suspicious regions of interest extracted from the ddsm database. exhaustive experiments illustrate that lbp features are effective and efficient for false positive reduction even at different mass sizes, a critical aspect in mass detection systems. moreover, we compare our proposal with current methods showing that lbp obtains better performance.
automatic labeling of anatomical structures in mr fastview images using a statistical atlas. we present a method for fast and automatic labeling of anatomical structures in mr fastview localizer images, which can be useful for automatic mr examination planning. fastview is a modern mr protocol, that provides larger planning fields of view than previously available with isotropic 3d resolution by scanning during continuous movement of the patient table. hence, full 3d information is obtained within short acquisition time. anatomical labeling is done by registering the images to a statistical atlas created from training image data beforehand. the statistical atlas consists of a statistical model of deformation and a statistical model of grey value appearance. it is generated by non-rigid registration and principal component analysis of the resulting deformation fields and registered images. labeling of an unseen fastview image is done by non-rigid registration of the image to the statistical atlas and propagating the labels from the atlas to the image. in our implementation, the statistical models of deformation and appearance are both implemented on the gpu (graphics processing unit), which permits computing the atlas based labeling using gpu hardware acceleration. the running times of about 10 to 30 seconds are of the same magnitude as the image acquisition itself, which allows for practical usage in clinical mr routine.
adaptive metamorphs model for 3d medical image segmentation. in this paper, we introduce an adaptive model-based segmentation framework, in which edge and region information are integrated and used adaptively while a solid model deforms toward the object boundary. our 3d segmentation method stems from metamorphs deformable models [1]. the main novelty of our work is in that, instead of performing segmentation in an entire 3d volume, we propose model-based segmentation in an adaptively changing subvolume of interest. the subvolume is determined based on appearance statistics of the evolving object model, and within the subvolume, more accurate and object-specific edge and region information can be obtained. this local and adaptive scheme for computing edges and object region information makes our segmentation solution more efficient and more robust to image noise, artifacts and intensity inhomogeneity. external forces for model deformation are derived in a variational framework that consists of both edge-based and region-based energy terms, taking into account the adaptively changing environment. we demonstrate the performance of our method through extensive experiments using cardiac mr and liver ct images.
mixtures of gaussians on tensor fields for dt-mri segmentation. in this paper, an original approach for the segmentation of tensor fields is proposed. based on the modeling of the data by means of gaussian mixtures directly in the tensor domain, this technique presents a wide range of applications in medical image processing, particularly for diffusion tensor magnetic resonance imaging (dt-mri). the performance of the segmentation method proposed is shown through the segmentation of the corpus callosum from a dataset of 32 dt-mri volumes. comparison with a recent and related segmentation approach is favorable to our method, showing its capability for the automatic extraction of anatomical structures in the white matter.
soft level set coupling for lv segmentation in gated perfusion spect. we present a new segmentation approach for the myocardium in gated and non-gated perfusion spect images. to this end, we represent the epi- and endocardiumby separate signed distance functions and couple them by a soft constraint to give explicit control over the wall thickness. by an explicit modeling of the basal plane, the volume of the blood pool as well as the myocardium are determinable. furthermore, prior shape information is incorporated by applying a kernel density estimation on a number of expert segmentations in a low-dimensional pca subspace. thereby, information along the time axis is fully taken into account by employing 4-dimensional embedding functions.
nonrigid image registration with subdivision lattices: application to cardiac mr image analysis. in this paper we present a new methodology for cardiac motion tracking in tagged mri using nonrigid image registration based on subdivision surfaces and subdivision lattices. we use two sets of registrations to do the motion tracking. first, a set of surface registrations is used to create and initially align the subdivision model of the left ventricle with short-axis and long-axis mr images. second, a series of volumetric registrations are used to perform the motion tracking and to reconstruct the 4d cardiac motion field from the tagged mr images. the motion of a point in the myocardium over time is calculated by registering the images taken during systole to the set of reference images taken at end-diastole. registration is achieved by optimizing the positions of the vertices in the base lattice so that the mutual information of the images being registered is maximized. the presented method is validated using a cardiac motion simulator and we also present strain measurements obtained from a group of normal volunteers.
spatio-temporal registration of real time 3d ultrasound to cardiovascular mr sequences. we extend our static multimodal nonrigid registration [1] to a spatio-temporal (2d+t) co-registration of a real-time 3d ultrasound and a cardiovascular mr sequence. the motivation for our research is to assist a clinician to automatically fuse the information from multiple imaging modalities for the early diagnosis and therapy of cardiac disease. the deformation field between both sequences is decoupled into spatial and temporal components. temporal alignment is firstly performed to re-slice both sequences using a differential registration method. spatial alignment is then carried out between the frames corresponding to the same temporal position. the spatial deformation is modeled by the polyaffine transformation whose anchor points (or control points) are automatically detected and refined by calculating a local mis-match measure based on phase mutual information. the spatial alignment is built in an adaptive multi-scale framework to maximize the phase-based similarity measure by optimizing the parameters of the polyaffine transformation. results demonstrate that this novel method can yield an accurate registration to particular cardiac regions.
graph cuts framework for kidney segmentation with prior shape constraints. we propose a novel kidney segmentation approach based on the graph cuts technique. the proposed approach depends on both image appearance and shape information. shape information is gathered from a set of training shapes. then we estimate the shape variations using a new distance probabilistic model which approximates the marginal densities of the kidney and its background in the variability region using a poisson distribution refined by positive and negative gaussian components. to segment a kidney slice, we align it with the training slices so we can use the distance probabilistic model. then its gray level is approximated with a lcg with sign-alternate components. the spatial interaction between the neighboring pixels is identified using a new analytical approach. finally, we formulate a new energy function using both image appearance models and shape constraints. this function is globally minimized using s/t graph cuts to get the optimal segmentation. experimental results show that the proposed technique gives promising results compared to others without shape constraints.
evaluation of a novel calibration technique for optically tracked oblique laparoscopes. this paper proposes an evaluation of a novel calibration method for an optically tracked oblique laparoscope. we present the necessary tools to track an oblique scope and a camera model which includes changes to the intrinsic camera parameters thereby extending previously proposed methods. because oblique scopes offer a wide 'virtual' view on the surgical field, the method is of great interest for augmented reality guidance of laparoscopic interventions using an oblique scope. the model and an approximated version are evaluated in an extensive validation study. using 5 sets of 40 calibration images, we compare both camera models (i.e. model and approximation) and 2 interpolation schemes. the selected model and interpolation scheme reaches an average accuracy of 2.60 pixel and an equivalent 3d error of 0.60 mm. finally, we present initial experience of the presented approach with an oblique scope and optical tracking in a clinical setup. during a laparoscopic rectum resection surgery the setup was used to augment the scene with a model of the pelvis. the method worked properly and the attached probes did not interfere with normal procedure.
automated planning of scan geometries in spine mri scans. consistency of mr scan planning is very important for diagnosis, especially in multi-site trials and follow-up studies, where disease progress or response to treatment is evaluated. accurate manual scan planning is tedious and requires skillful operators. on the other hand, automated scan planning is difficult due to relatively low quality of survey images ("scouts") and strict processing time constraints. this paper presents a novel method for automated planning of mri scans of the spine. lumbar and cervical examinations are considered, although the proposed method is extendible to other types of spine examinations, such as thoracic or total spine imaging. the automated scan planning (asp) system consists of an anatomy recognition part, which is able to automatically detect and label the spine anatomy in the scout scan, and a planning part, which performs scan geometry planning based on recognized anatomical landmarks. a validation study demonstrates the robustness of the proposed method and its feasibility for clinical use.
a bayesian approach for liver analysis: algorithm and validation study. we present a new method for the simultaneous, nearly automatic segmentation of liver contours, vessels, and metastatic lesions from abdominal cta scans. the method repeatedly applies multi-resolution, multi-class smoothed bayesian classification followed by morphological adjustment and active contours refinement. it uses multi-class and voxel neighborhood information to compute an accurate intensity distribution function for each class. the method requires only one or two user-defined voxel seeds, with no manual adjustment of internal parameters. a retrospective study on two validated clinical datasets totaling 56 ctas was performed. we obtained correlations of 0.98 and 0.99 with a manual ground truth liver volume estimation for the first and second databases, and a total score of 67.87 for the second database. these results suggest that our method is accurate, efficient, and robust to seed selection compared to manually generated ground truth segmentation and to other semi-automatic segmentation methods.
a comparison of methods for recovering intra-voxel white matter fiber architecture from clinical diffusion imaging scans. diffusion tensor magnetic resonance imaging is widely used to study the structure of the fiber pathways of brain white matter. however, the diffusion tensor cannot capture complex intra-voxel fiber architecture such as fiber crossings. consequently, a number of methods have been proposed to recover intra-voxel fiber bundle orientations from high angular-resolution diffusion imaging scans, which are optimized to resolve fiber crossings. in this work we study how multi-tensor, spherical deconvolution, analytical qball and diffusion basis function methods perform under clinical scanning conditions. our experiments indicate that it is feasible to apply some of these methods in clinical data sets.
mean q-ball strings obtained by constrained procrustes analysis with point sliding. the idea underpinning the work we present herein is to design robust and objective tools for brain white matter (wm) morphometry. we focus on wm tracts, and propose to represent them by their mean lines, to which we associate the attributes derived from high-angular resolution diffusion imaging (hardi). the definition of the tract mean line derives directly from the geometry of the tract fibres. we determine the fibre point correspondences and impact factors of individual fibres, upon which we estimate average hardi models along the tract mean lines. this way we obtain a compact tract representation that exploits all the available information, and is at the same time free of the outlier influence and undesired tract edge effects.
spectral clustering as a diagnostic tool in cross-sectional mr studies: an application to mild dementia. structural imaging investigations commonly apply a segmentation step followed by the extraction of feature data that can be used to compare or discriminate groups. we present a framework for such a study based on automated multi-atlas segmentation followed by the extraction of low-level morphological features, volumes and overlaps, for classification. a spectral analysis step is used to transform pairwise overlap information into feature data that relate to individual subjects. applying the framework to a group of controls and patients with mild dementia, we compare the volume- and overlap-based classification performance using both supervised and unsupervised classifiers. the results indicate that unsupervised classification following a spectral analysis of label overlaps performs very well, outperforming classifiers that use volumes alone.
computational atlases of severity of white matter lesions in elderly subjects with mri. mri of cerebral white matter may show regions of signal abnormalities. these changes may be associated with hypertension, inflammation, or ischemia, as well as altered brain function. the goal of this work has been to construct computational atlases of white matter lesions that represent both their severity as well as the frequency of their occurrence in a population to achieve a better classification of white matter disease. an atlas is computed with a pipeline that uses 4t flair and 4t t1-weighted (t1w) brain images of a group of subjects. the processing steps include intensity correction, lesion extraction, intra-subject flair to t1w rigid registration, and seamless replacement of lesions in t1w images with synthetic white matter texture. subsequently, the t1w images and lesion images of different subjects are registered non-rigidly to the same space. the decrease in t1w intensities is used to obtain severity information. atlases were constructed for two groups of subjects, elderly normal controls or with mild cognitive impairment, and subjects with cerebrovascular disease. the lesion severities of the two groups have a significant statistical difference with the severity in the atlas of cerebrovascular disease being higher.
cardiac electrophysiology model adjustment using the fusion of mr and optical imaging. despite important recent efforts in cardiac electrophysiology modelling, there is still a strong need for validating macroscopic models, that are well suited for diagnosis and treatment planning. in this paper we present a method to adjust the parameters of a macroscopic electrophysiology model on depolarisation and repolarisation maps obtained ex-vivo from optical imaging. with this imaging technique, optical fluorescence data are recorded with high spatial and temporal resolution on a large healthy porcine heart. a model of the myocardium is built from the mr images of the same heart, which also integrates the myocardial fibre orientation measured with dti. we then present the first quantitative adjustment of a personalised volumetric model of the myocardium.
surface-based vector analysis using heat equation interpolation: a new approach to quantify local hippocampal volume changes. analysis of surface-based displacement vectors using spherical harmonic description (spharm) localizes shape changes accurately. however, it does not allow differentiating volume variations from shifting and/or bending. we propose a new approach to quantify local volume changes by computing the surface-based jacobian determinant. this measurement is computed on the displacement vector fields estimated by a heat equation interpolation on the displacement vectors produced by spharm. data simulation showed that the surface-based jacobian determinant enables accurate quantification of local volume changes without interference of shifting/bending. in patients with temporal lobe epilepsy and left hippocampal atrophy, spharm detected widespread inward deformation related to atrophy in the hippocampal head and body, and showed areas of mirrored inward/outward deformations mostly at the level of the hippocampal tail. in these areas, the surface-based jacobian determinant showed atrophy. our method facilitates the interpretation of spharm because it allows decomposing volume changes and shifting/bending. furthermore, it provides a better delineation of the extent of hippocampal atrophy.
robust segmentation and anatomical labeling of the airway tree from thoracic ct scans. a method for automatic extraction and labeling of the airway tree from thoracic ct scans is presented and extensively evaluated on 150 scans of clinical dose, low dose and ultra-low dose data, in inspiration and expiration from both relatively healthy and severely ill patients. the method uses adaptive thresholds while growing the airways and it is shown that this strategy leads to a substantial increase in the number, total length and number of correctly labeled airways extracted. from inspiration scans on average 170 branches are found, from expiration scans 59.
dynamic probabilistic atlas of functional brain regions for transcranial magnetic stimulation. transcranial magnetic stimulation (tms) is a technique to stimulate the brain non-invasively. the applications range from accurate localization of the primary motor areas to potential treatment of disorders such as tinnitus, severe depression, and pain. stereotactic guidance requires individual mr images of the subject's head, which is in some applications typically omitted due to financial motivations. in this paper, we introduce a method that offers improved tms pulse targeting also to those subjects who do not have mr examinations. a probabilistic brain model was constructed by spatially normalizing the locations of the functional brain areas in a study population, and modeling the distributions and estimates of the locations of the functional brain regions using probabilistic methods. the application of the probabilistic brain model to the target subject was based on a point set determined from the scalp and facial skin of the target subject. the methods were evaluated using data from four functional brain areas from 56 healthy subjects. the accuracy of the estimates of the locations of the functional brain regions was about nine millimeters.
a novel method for cortical sulcal fundi extraction. sulcal fundi are 3d curves along the bottom of sulcal regions of the human cerebral cortex. in this paper, we propose a novel automatic method for extraction of sulcal fundi from triangulated cortical surface. compared to existing methods, the proposed method can find accurate sulcal fundi using curvatures and curvature derivatives without manual interaction. given a triangulated cortical surface, our method is composed of four steps: estimating curvatures and curvature derivatives for each vertex, detecting the sulcal fundi segments in each triangle, linking the sulcal fundi segments and combining of adjacent sulcal fundi, and connecting breaking sulcal fundi and smoothing using the fast marching method on the cortical surface. the proposed sulcal fundi extraction method is applied to ten normal brain inner cortical surfaces. we quantitatively validated the proposed method of sulcal fundi extraction using manually labeled sulcal fundi by experts as the ground truth.
mri bone segmentation using deformable models and shape priors. this paper addresses the problem of automatically segmenting bone structures in low resolution clinical mri datasets. the novel aspect of the proposed method is the combination of physically-based deformable models with shape priors. models evolve under the influence of forces that exploit image information and prior knowledge on shape variations. the prior defines a principal component analysis (pca) of global shape variations and a markov random field (mrf) of local deformations, imposing spatial restrictions in shapes evolution. for a better efficiency, various levels of details are considered and the differential equations system is solved by a fast implicit integration scheme. the result is an automatic multilevel segmentation procedure effective with low resolution images. experiments on femur and hip bones segmentation from clinical mri depict a promising approach (mean accuracy: 1.44±1.1 mm, computation time: 2mn43s).
fast marker based c-arm pose estimation. to estimate the pose of a c-arm during interventions therapy we have developed a small sized x-ray target including a special set of beads with known locations in 3d space. since the patient needs to remain in the x-ray path for all feasible poses of the c-arm during the intervention, we cannot construct a single marker which is entirely visible in all images. therefore finding 2d-3d point correspondences is a non-trivial task. the marker pattern has to be chosen in a way such that its projection onto the image plane is unique in a minimal-sized window for all relevant poses of the c-arm. we use a two dimensional adaption of a linear feedback shift register (lfsr) to generate a two-dimensional pattern with unique sub-patterns in a certain window range. thereby uniqueness is not achieved by placing unique 2d sub patterns side by side but by the code property itself. the code is designed in a way that any sub window of a minimal size guarantees uniqueness and that even occlusions from medical instruments can be handled. experiments showed that we were able to estimate the c-arm's pose from a single image within one second with a precision below one millimeter and one degree.
evaluation of a cardiac ultrasound segmentation algorithm using a phantom. this paper evaluates the performance of a level set algorithm for segmenting the endocardium in short-axis ultrasound images. the evaluation is carried out using an anthropomorphic ultrasound phantom. details of the phantom design, including comparison of the ultrasound parameters with in-vitro measurements, are included.in addition to measuring segmentation accuracy, the effectiveness of the energy minimization scheme is also determined. it is argued that using the phantom along with global minimization algorithms (simulated annealing and random search) makes is possible to assess the minimization strategy.
a novel explicit 2d+t cyclic shape model applied to echocardiography. in this paper, we propose a novel explicit 2d+t cyclic shape model that extends the point distribution model (pdm) to shapes like myocardial contours with cyclic dynamics. we also propose an extension to procrustes alignment that removes pose and subject size variability while maintaining dynamic effects. our model draws on ideas from principal component analysis (pca), multidimensional scaling (mds) and kernel pca (kpca) and solves 3 shortcomings of previous implicit models: 1) cardiac cycles in the data set do not each need to have the same number of frames, 2) the required number of subjects for statistically significant results is substantially reduced and 3) the displacement of contour points incorporates time as an explicit variable. we illustrate our method by computing models of the myocardium in the 4 principal planes of 2d+t echocardiography data.
identifying regional cardiac abnormalities from myocardial strains using spatio-temporal tensor analysis. myocardial deformation is a critical indicator of many cardiac diseases and dysfunctions. the goal of this paper is to use myocardial deformation patterns to identify and localize regional abnormal cardiac function in human subjects. we have developed a novel tensor-based classification framework that better conserves the spatio-temporal structure of the myocardial deformation pattern than conventional vector-based algorithms. in addition, the tensor-based projection function keeps more of the information of the original feature space, so that abnormal tensors in the subspace can be back-projected to reveal the regional cardiac abnormality in a more physically meaningful way. we have tested our novel method on 41 human image sequences, and achieved a classification rate of 87.80%. the recovered regional abnormalities from our algorithm agree well with the patient's pathology and doctor's diagnosis and provide a promising avenue for regional cardiac function analysis.
joint segmentation of thalamic nuclei from a population of diffusion tensor mr images. several recent studies explored the use of unsupervised segmentation methods for segmenting thalamic nuclei from diffusion tensor images. these methods provide a plausible segmentation on individual subjects; however, they do not address the problem of consistently identifying the same functional areas in a population. the lack of correspondence between the segmented nuclei make it more difficult to use the results from the unsupervised segmentation tools for morphometry. in this paper we present a novel segmentation algorithm to automatically segment the gray matter nuclei while ensuring consistency between subjects in a population. this new algorithm, referred to as consistency clustering, finds correspondence between the nuclei as the segmentation is achieved through a single model for the whole population, similar to the brain atlases experts use to identify thalamic nuclei.
unbiased stratification of left ventricles. image based quantitative stratification of the left ventricles (lv) across a population helps in unraveling the structure-function symbiosis of the heart. an unbiased, reference less grouping scheme that automatically determines the number of clusters and a physioanatomically relevant strategy that aligns the intra cluster lv shapes would enable the robust construction of pathology stratified cardiac atlas. this paper achieves this hitherto elusive stratification and alignment by adapting the conventional strategies routinely followed by clinicians. the individual lv shape models (n=127) are independently oriented to an "attitudinally consistent orientation" that captures the physioanatomic variations of the lv morphology. affinity propagation technique based on the automatically identified inter-lv_landmark distances is used to group the lv shapes. the proposed algorithm is computationally efficient and, if the inter cluster variations are linked to pathology, could provide a clinically relevant cardiac atlas.
multivariate statistical analysis of whole brain structural networks obtained using probabilistic tractography. this paper presents a new framework for the analysis of anatomical connectivity derived from diffusion tensor mri. the framework has been applied to estimate whole brain structural networks using diffusion data from 174 adult subjects. in the proposed approach, each brain is first segmented into 83 anatomical regions via label propagation of multiple atlases and subsequent decision fusion. for each pair of anatomical regions the probability of connection and its strength is then estimated using a modified version of probabilistic tractography. the resulting brain networks have been classified according to age and gender using non-linear support vector machines with gentleboost feature extraction. classification performance was tested using a leave-one-out approach and the mean accuracy obtained was 85.4%.
lumbar disc localization and labeling with a probabilistic model on both pixel and object features. repeatable, quantitative assessment of intervertebral disc pathology requires accurate localization and labeling of the lumbar region discs. to that end, we propose a two-level probabilistic model for such disc localization and labeling. our model integrates both pixel-level information, such as appearance, and object-level information, such as relative location. utilizing both levels of information adds robustness to the ambiguous disc intensity signature and high structure variation. yet, we are able to do efficient (and convergent) localization and labeling with generalized expectation-maximization. we present accurate results on 20 normal cases (96%) and a promising extension to a pathology case.
semi-supervised nasopharyngeal carcinoma lesion extraction from magnetic resonance images using online spectral clustering with a learned metric. in this paper, we consider the extraction of nasopharyngeal carcinoma lesion from mr images as a region segmentation problem. we propose a semi-supervised segmentation approach to segment the lesion in two steps. first, a metric is learned in a supervised fashion, which maximizes the separation between two groups of pixels (tumor or non-tumor) with minimal user interaction. second, the learned metric is used to complete extraction of tumor region in an unsupervised fashion. several experiments were conducted to evaluate the performance of similar methods with learned metrics for grouping or classifying pixels to form the tumor region. it is observed that the spectral clustering-based method performs well and the performance is comparable or marginally better than the discriminative svm-based method.
prediction of biomechanical parameters of the proximal femur using statistical appearance models and support vector regression. fractures of the proximal femur are one of the principal causes of mortality among elderly persons. traditional methods for the determination of femoral fracture risk use methods for measuring bone mineral density. however, bmd alone is not sufficient to predict bone failure load for an individual patient and additional parameters have to be determined for this purpose. in this work an approach that uses statistical models of appearance to identify relevant regions and parameters for the prediction of biomechanical properties of the proximal femur will be presented. by using support vector regression the proposed model based approach is capable of predicting two different biomechanical parameters accurately and fully automatically in two different testing scenarios.
dynamic cardiac mapping on patient-specific cardiac models. minimally invasive techniques for electrophysiological cardiac data mapping and catheter ablation therapy have been driven through advancements in computer-aided technologies, including magnetic tracking systems, and virtual and augmented-reality environments. the objective of this work is to extend current cardiac mapping techniques to collect and display data in the temporal domain, while mapping on patient-specific cardiac models. this paper details novel approaches to collecting spatially tracked cardiac electrograms, registering the data with a patient-specific cardiac model, and interpreting the data directly on the model surface, with the goal of giving a more comprehensive cardiac mapping system in comparison to current systems. to validate the system, laboratory studies were conducted to assess the accuracy of navigating to both physical and virtual landmarks. subsequent to the laboratory studies, an in-vivo porcine experiment was conducted to assess the systems overall ability to collect spatial tracked electrophysiological data, and map directly onto a cardiac model. the results from these experiments show the new dynamic cardiac mapping system was able to maintain high accuracy of locating physical and virtual landmarks, while creating a dynamic cardiac map displayed on a dynamic cardiac surface model.
dynamic model-driven quantitative and visual evaluation of the aortic valve from 4d ct. aortic valve disease is an important cardio-vascular disorder, which affects 2.5% of the global population and often requires elaborate clinical management. experts agree that visual and quantitative evaluation of the valve, crucial throughout the clinical workflow, is currently limited to 2d imaging which can potentially yield inaccurate measurements. in this paper, we propose a novel approach for morphological and functional quantification of the aortic valve based on a 4d model estimated from computed tomography data. a physiological model of the aortic valve, capable to express large shape variations, is generated using parametric splines together with anatomically-driven topological and geometrical constraints. recent advances in discriminative learning and incremental searching methods allow rapid estimation of the model parameters from 4d cardiac ct specifically for each patient. the proposed approach enables precise valve evaluation with model-based dynamic measurements and advanced visualization. extensive experiments and initial clinical validation demonstrate the efficiency and accuracy of the proposed approach. to the best of our knowledge this is the first time such a patient specific 4d aortic valve model is proposed.
automatic detection of calcified coronary plaques in computed tomography data sets. the detection of calcified plaques is an essential step in the assessment of coronary heart diseases. however, manual plaque segmentation is subjected to intra- and inter-observer variability. we present a novel framework for the automatic detection of calcified coronary plaques in computed tomography images. in contrast to the state-of-the-art, both the native and the angio data sets are included to gain additional information about each plaque for its detection and subsequent assessment. the framework was successfully tested on 127 patients where 85.5% of the calcified and 96% of the obstructive plaques have been detected.
bone segmentation and fracture detection in ultrasound using 3d local phase features. 3d ultrasound (us) is increasingly considered as a viable alternative imaging modality in computer-assisted orthopaedic surgery (caos) applications. automatic bone segmentation from us images, however, remains a challenge due to speckle noise and various other artifacts inherent to us. in this paper, we present intensity invariant three dimensional (3d) local image phase features, obtained using 3d log-gabor filter banks, for extracting ridge-like features similar to those that occur at soft tissue/bone interfaces. our contributions include the novel extension of 2d phase symmetry features to 3d and their use in automatic extraction of bone surfaces and fractured fragments in 3d us. we validate our technique using phantom, in vitro, and in vivo experiments. qualitative and quantitative results demonstrate remarkably clear segmentations results of bone surfaces with a localization accuracy of better than 0.62mm and mean errors in estimating fracture displacements below 0.65mm, which will likely be of strong clinical utility.
on-the-fly motion-compensated cone-beam ct using an a priori motion model. respiratory motion causes artifacts in slow-rotating cone-beam (cb) computed tomography (ct) images acquired for example for image guidance of radiotherapy. respiration-correlated cbct has been proposed to correct for the respiratory motion, but the use of a subset of the cb projections to reconstruct each frame of the 4d cbct image limits their quality, thus requiring a longer acquisition time. another solution is motion-compensated cbct which consists of reconstructing a single 3d cbct image at a reference position from all the cb projections by using an estimate of the respiratory motion in the reconstruction algorithm. in this paper, we propose a method for motion-compensated cbct which allows to reconstruct the image on-the-fly, i.e. concurrent with acquisition. before the cb acquisition, a model of the patient motion over the respiratory cycle is estimated from the planning 4d ct. the respiratory motion is then computed on-the-fly from this model using a respiratory signal extracted from the cb projections and incorporated into the motion-compensated cbct reconstruction algorithm. the proposed method is evaluated on 26 cbct scans of 3 patients acquired with two protocols used for static and respiration-correlated cbct respectively. our results show that this method provides cbct images within a few seconds after the end of the acquisition where most of the motion artifacts have been removed.
noninvasive functional imaging of volumetric cardiac electrical activity: a human study on myocardial infarction. identification of infarct substrates provides necessary guidance to the prevention and treatment of cardiac arrhythmias. compared to diagnostic criteria of body surface potentials (bsp) or electrophysiological information on heart surfaces, the underlying volumetric cardiac electrical activity is of more direct clinical relevance in exhibiting patient-specific arrhythmic dynamics and arrhythmogenic substrates. we have developed a paradigm for noninvasive imaging of volumetric myocardial transmembrane potential from bsps. in this paper, we present a human study for a patient with acute myocardial infarction. using patient mri and bsp data, the framework is able to reconstruct details of the complete arrhythmic electrical activity on the 3d myocardium of the patient. exploring a subset of the results, the extent, centroid and affected segments of the infarct is correctly evaluated, with comparable performance to existent best results. this human study demonstrates the potential of the presented paradigm as a noninvasive functional imaging technique for patient-specific volumetric cardiac electrical activity in practice.
discovering structure in the space of activation profiles in fmri. we present a method for discovering patterns of activation observed through fmri in experiments with multiple stimuli/tasks. we introduce an explicit parameterization for the profiles of activation and represent fmri time courses as such profiles using linear regression estimates. working in the space of activation profiles, we design a mixture model that finds the major activation patterns along with their localization maps and derive an algorithm for fitting the model to the fmri data. the method enables functional group analysis independent of spatial correspondence among subjects. we validate this model in the context of category selectivity in the visual cortex, demonstrating good agreement with prior findings based on hypothesis-driven methods.
symmetric log-domain diffeomorphic registration: a demons-based approach. modern morphometric studies use non-linear image registration to compare anatomies and perform group analysis. recently, log-euclidean approaches have contributed to promote the use of such computational anatomy tools by permitting simple computations of statistics on a rather large class of invertible spatial transformations. in this work, we propose a non-linear registration algorithm perfectly fit for log-euclidean statistics on diffeomorphisms. our algorithm works completely in the log-domain, i.e. it uses a stationary velocity field. this implies that we guarantee the invertibility of the deformation and have access to the true inverse transformation. this also means that our output can be directly used for log-euclidean statistics without relying on the heavy computation of the log of the spatial transformation. as it is often desirable, our algorithm is symmetric with respect to the order of the input images. furthermore, we use an alternate optimization approach related to thirion's demons algorithm to provide a fast non-linear registration algorithm. first results show that our algorithm outperforms both the demons algorithm and the recently proposed diffeomorphic demons algorithm in terms of accuracy of the transformation while remaining computationally efficient.
shape-based alignment of hippocampal subfields: evaluation in postmortem mri. this paper estimates the accuracy of hippocampal subfield alignment via shape-based normalization. evaluation takes place in postmortem mri dataset acquired at 9.4 tesla with many averages and approximately 0.01,mm3 voxel resolution. continuous medial representations (cm-reps) are used to establish geometrical correspondences between hippocampal formations in different images; the extent to which these correspondences match up subfields is evaluated and compared to normalization driven by image forces. shape-based normalization is shown to perform only slightly worse than image-based normalization; this is encouraging because the former is more applicable to in vivo mri, which typically lacks features that distinguish hippocampal subfields.
spherical demons: fast surface registration. we present the fast spherical demons algorithm for registering two spherical images. by exploiting spherical vector spline interpolation theory, we show that a large class of regularizers for the modified demons objective function can be efficiently implemented on the sphere using convolution. based on the one parameter subgroups of diffeomorphisms, the resulting registration is diffeomorphic and fast --- registration of two cortical mesh models with more than 100k nodes takes less than 5 minutes, comparable to the fastest surface registration algorithms. moreover, the accuracy of our method compares favorably to the popular freesurfer registration algorithm. we validate the technique in two different settings: (1) parcellation in a set of in-vivo cortical surfaces and (2) brodmann area localization in ex-vivo cortical surfaces.
a discriminative model-constrained graph cuts approach to fully automated pediatric brain tumor segmentation in 3-d mri. in this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-d magnetic resonance images. it is a top-down segmentation approach based on a markov random field (mrf) model that combines probabilistic boosting trees (pbt) and lower-level segmentation via graph cuts. the pbt algorithm provides a strong discriminative observation model that classifies tumor appearance while a spatial prior takes into account the pair-wise homogeneity in terms of classification labels and multi-spectral voxel intensities. the discriminative model relies not only on observed local intensities but also on surrounding context for detecting candidate regions for pathology. a mathematically sound formulation for integrating the two approaches into a unified statistical framework is given. the proposed method is applied to the challenging task of detection and delineation of pediatric brain tumors. this segmentation task is characterized by a high non-uniformity of both the pathology and the surrounding non-pathologic brain tissue. a quantitative evaluation illustrates the robustness of the proposed method. despite dealing with more complicated cases of pediatric brain tumors the results obtained are mostly better than those reported for current state-of-the-art approaches to 3-d mr brain tumor segmentation in adult patients. the entire processing of one multi-spectral data set does not require any user interaction, and takes less time than previously proposed methods.
automatic subcortical segmentation using a contextual model. automatically segmenting subcortical structures in brain images has the potential to greatly accelerate drug trials and population studies of disease. here we propose an automatic subcortical segmentation algorithm using the auto context model. unlike many segmentation algorithms that separately compute a shape prior and an image appearance model, we develop a framework based on machine learning to learn a unified appearance and context model. we trained our algorithm to segment the hippocampus and tested it on 83 brain mris (of 35 alzheimer's disease patients, 22 with mild cognitive impairment, and 26 normal healthy controls). using standard distance and overlap metrics, the auto context model method significantly outperformed simpler learning-based algorithms (using adaboost alone) and the freesurfer system. in tests on a public domain dataset designed to validate segmentation [1] , our new algorithm also greatly improved upon a recently-proposed hybrid discriminative/generative approach [2], which was among the top three that performed comparably in a recent head-to-head competition.
measuring brain lesion progression with a supervised tissue classification system. brain lesions, especially white matter lesions (wmls), are associated with cardiac and vascular disease, but also with normal aging. quantitative analysis of wml in large clinical trials is becoming more and more important. in this paper, we present a computer-assisted wml segmentation method, based on local features extracted from conventional multi-parametric magnetic resonance imaging (mri) sequences. a framework for preprocessing the temporal data by jointly equalizing histograms reduces the spatial and temporal variance of data, thereby improving the longitudinal stability of such measurements and hence the estimate of lesion progression. a support vector machine (svm) classifier trained on expert-defined wml's is applied for lesion segmentation on each scan using the adaboost algorithm. validation on a population of 23 patients from 3 different imaging sites with follow-up studies and wmls of varying sizes, shapes and locations tests the robustness and accuracy of the proposed segmentation method, compared to the manual segmentation results from an experienced neuroradiologist. the results show that our cad-system achieves consistent lesion segmentation in the 4d data facilitating the disease monitoring.
multi-level classification of emphysema in hrct lung images using delegated classifiers. emphysema is a common chronic respiratory disorder characterized by the destruction of lung tissue. it is a progressive disease where the early stages are characterized by diffuse appearance of small air spaces and later stages exhibit large air spaces called bullae. a bullous region is a sharply demarcated region of emphysema. in this paper, we show that an automated texture-based system based on delegated classifiers is capable of achieving multiple levels of emphysema extraction in high resolution computed tomography (hrct) images. the key idea of delegation is that a cautious classifier makes predictions that meet a minimum level of confidence, and delegates the difficult or uncertain predictions to a more specialized classifier. in this paper, we design a two-step scenario where a first classifier chooses the examples to classify on and delegates the more difficult examples to a second classifier. we compare this technique to well known emphysema classification techniques and ensemble methods such as bagging and boosting. comparison of the results shows that the techniques presented here are more accurate. from a medical standpoint, the classifiers built at different iterations appear to show an interesting correlation with different levels of emphysema.
weights and topology: a study of the effects of graph construction on 3d image segmentation. graph-based algorithms have become increasingly popular for medical image segmentation. the fundamental process for each of these algorithms is to use the image content to generate a set of weights for the graph and then set conditions for an optimal partition of the graph with respect to these weights. to date, the heuristics used for generating the weighted graphs from image intensities have largely been ignored, while the primary focus of attention has been on the details of providing the partitioning conditions. in this paper we empirically study the effects of graph connectivity and weighting function on the quality of the segmentation results. to control for algorithm-specific effects, we employ both the graph cuts and random walker algorithms in our experiments.
modelling childbirth: comparing athlete and non-athlete pelvic floor mechanics. there is preliminary evidence that athletes involved in high-intensity sports for sustained periods have a higher probability of experiencing a prolonged second stage of labour compared to non-athletes. the mechanisms responsible for these differences are not clear, although it is postulated that muscle hypertrophy and increased muscle tone in athletes may contribute to difficulties in vaginal delivery. in order to test these hypotheses, we have constructed individual-specific finite element models of the female pelvic floor (one athlete and one non-athlete) and the fetal head to simulate vaginal delivery and enable quantitative analysis of the differences. the motion of the fetal head descending through the pelvic floor was modelled using finite deformation elasticity with contact mechanics. the force required to push the head was compared between the models and a 45% increase in peak force was observed in the athlete model compared to the non-athlete. in both cases, the overall maximum stretch was induced at the muscle insertions to the pubis. this is the beginning of a quantitative modelling framework that is intended to help clinicians assess the risk of natural versus caesarean birth by taking into account the possible mechanical response of pelvic floor muscles based on their size and activation patterns prior to labour.
texture classification in lung ct using local binary patterns. in this paper we propose to use local binary patterns (lbp) as features in a classification framework for classifying different texture patterns in lung computed tomography. image intensity is included by means of the joint lbp and intensity histogram, and classification is performed using the k nearest neighbor classifier with histogram similarity as distance measure.the proposed method is evaluated on a set of 168 regions of interest comprising normal tissue and different emphysema patterns, and compared to a filter bank based on gaussian derivatives. the joint lbp and intensity histogram, achieving a classification accuracy of 95.2%, shows superior performance to using the common approach of taking moments of the filter response histograms as features, and slightly better performance than using the full filter response histograms instead. classification results are better than some of those previously reported in the literature.
model-based segmentation of hippocampal subfields in ultra-high resolution in vivo mri. recent developments in mr data acquisition technology are starting to yield images that show anatomical features of the hippocampal formation at an unprecedented level of detail, providing the basis for hippocampal subfield measurement. because of the role of the hippocampus in human memory and its implication in a variety of disorders and conditions, the ability to reliably and efficiently quantify its subfields through in vivo neuroimaging is of great interest to both basic neuroscience and clinical research. in this paper, we propose a fully-automated method for segmenting the hippocampal subfields in ultra-high resolution mri data. using a bayesian approach, we build a computational model of how images around the hippocampal area are generated, and use this model to obtain automated segmentations. we validate the proposed technique by comparing our segmentation results with corresponding manual delineations in ultra-high resolution mri scans of five individuals.
robust image-based ivus pullbacks gating. intracoronary ultrasound (ivus) imaging allows to obtain high resolution images of internal part of coronary arteries. this tool is unique in the possibility to explore internal vessel structures of the coronary wall, being a powerful tool for diagnosis [1]. since the coronary vessel is moving due to the periodical contraction and expansion of heart muscles, the acquired images present different artifacts. one of the most severe problems is the longitudinal oscillation of the ivus catheter inside the vessel. to alleviate this problem, ecg-gating has been proposed. the goal of gating is to have subsequent frames that represent the internal vessel section in "stable" position and avoid the repetition of frames; that is to generate an image sequence in which the artifacts due to the heart beat have been removed while, possible translation due to vessel tortuosity can still be present. this paper presents a simple and efficient model of catheter longitudinal movement together with a fast and robust image based gating algorithm. experimental results on 9 sequences from 7 patients, plus a comparison with ecg gating are presented.
automatic delineation of sulci and improved partial volume classification for accurate 3d voxel-based cortical thickness estimation from mr. accurate cortical thickness estimation in-vivo is important for the study of many neurodegenerative diseases. when using magnetic resonance images (mri), accuracy may be hampered by artifacts such as partial volume (pv) as the cortex spans only a few voxels. in zones of opposed sulcal banks (tight sulci) the measurement can be even more difficult. the aim of this work is to propose a voxel-based cortical thickness estimation method from mr by integrating a mechanism for correcting sulci delineation after an improved partial volume classification. first, an efficient and accurate framework was developed to enhance partial volume classification with structural information. then, the correction of sulci delineation is performed after a homotopic thinning of a cost function image. integrated to our voxel-based cortical thickness estimation pipeline, the overall method showed a better estimate of thickness and a high reproducibility on real data (r 2 > 0.9). a quantitative analysis on clinical data from an alzheimer's disease study showed significant differences between normal controls and alzheimer's disease patients.
optimal feature point selection and automatic initialization in active shape model search. this paper presents a novel approach for robust and fully automatic segmentation with active shape model search. the proposed method incorporates global geometric constraints during feature point search by using inter-landmark conditional probabilities. the a* graph search algorithm is adapted to identify in the image the optimal set of valid feature points. the technique is extended to enable reliable and fast automatic initialization of the asm search. validation with 2-d and 3-d mr segmentation of the left ventricular epi-cardial border demonstrates significant improvement in robustness and overall accuracy, while eliminating the need for manual initialization.
segmentation of pathologic hearts in long-axis late-enhancement mri. we propose a new method to segment long-axis cardiac mr images acquired with a late-enhancement protocol. detecting the myocardium boundaries is difficult in these images because healthy myocardium appears dark while the intensity of enhanced areas ranges from gray to white, depending on the myocardial damage. in this context, geometrical template deformation, alternated with the update of a damaged tissue map, allows us to include abnormal myocardium parts in the final segmentation. the template and map are initialized using short-axis images and the deformation parameters are adapted according to the type of enhancement pattern. good segmentation results are obtained on a database of real pathologic heart images presenting various types of abnormal myocardium tissues.
contractile analysis with kriging based on mr myocardial velocity imaging. diagnosis and treatment of coronary artery disease requires a full understanding of the intrinsic contractile mechanics of the heart. mr myocardial velocity imaging is a promising technique for revealing intramural cardiac motion but its ability to depict 3d strain tensor distribution is constrained by anisotropic voxel coverage of velocity imaging due to limited imaging slices and the achievable snr in patient studies. this paper introduces a novel kriging estimator for simultaneously improving the tracking and dense inter-slice estimation of the myocardial velocity data. a harmonic embedding technique is employed to determine point correspondence between left ventricle models between subjects, allowing for a statistical shape model to be reconstructed. the use of different semivariograms is investigated for optimal deformation reconstruction. results from in vivo data demonstrate a marked improvement in tracking myocardial deformation, thus enhancing the potential clinical value of mr myocardial velocity imaging.
spatial weighed element based fem incorporating a priori information on bioluminescence tomography. bioluminescence tomography (blt) is a promising imaging technique which may dynamically and real-timely detect the molecular and cellular activity at the whole-body level in small animal studies. in view of the ill-posedness of the blt, it is hard to fully reconstruct source density. in addition, the uniqueness theorem on blt indicates that it is important to employ a priori information for accurate source reconstruction. hence, we adopt diffuse optical tomography (dot) technique to provide optical parameters of main tissues as a priori information. besides, we restrict the range of real source to a permissible region to raise the numerical stability and reduce the ill-posedness of blt. next, we forward spatial weighed element based finite element method and compare it's solutions with analytic formula and mose. numerical simulation of homogeneous and heterogeneous phantom demonstrates the source location and density with prior information is better than that not using a priori information.
averaging centerlines: mean shift on paths. generation of a reference standard from multiple manually annotated datasets is a non-trivial problem. this paper discusses the weighted averaging of 3d open curves, which we used to generate a reference standard for vessel tracking data. we show how weighted averaging can be implemented by applying the mean shift algorithm to paths, and discuss the details of our implementation. our approach can handle cases where the observer centerlines take different branches in a natural way. the method has been evaluated on synthetic data, and has been used to generate reference centerlines for evaluation of vessel tracking algorithms.
multi-attribute non-initializing texture reconstruction based active shape model (mantra). in this paper we present mantra (multi-attribute, non-initializing, texture reconstruction based active shape model) which incorporates a number of features that improve on the the popular active shape model (asm) algorithm. mantra has the following advantages over the traditional asm model. (1) it does not rely on image intensity information alone, as it incorporates multiple statistical texture features for boundary detection. (2) unlike traditional asms, mantra finds the border by maximizing a higher dimensional version of mutual information (mi) called combined mi (cmi), which is estimated from knn entropic graphs. the use of cmi helps to overcome limitations of the mahalanobis distance, and allows multiple texture features to be intelligently combined. (3) mantra does not rely on the mean pixel intensity values to find the border; instead, it reconstructs potential image patches, and the image patch with the best reconstruction based on cmi is considered the object border. our algorithm was quantitatively evaluated against expert ground truth on almost 230 clinical images (128 1.5 tesla (t) t2 weighted in vivo prostate magnetic resonance (mr) images, 78 dynamic contrast enhanced breast mr images, and 21 3t in vivo t1-weighted prostate mr images) via 6 different quantitative metrics. results from the more difficult prostate segmentation task (in which a second expert only had a 0.850 mean overlap with the first expert) show that the traditional asm method had a mean overlap of 0.668, while the mantra model had a mean overlap of 0.840.
streamline flows for white matter fibre pathway segmentation in diffusion mri. we introduce a fibre tract segmentation algorithm based on the geometric coherence of fibre orientations as indicated by a streamline flow model. the inference of local flow approximations motivates a pairwise consistency measure between fibre odf maxima. we use this measure in a recursive algorithm to cluster consistent odf maxima, leading to the segmentation of white matter pathways. the method requires minimal seeding compared to streamline tractography-based methods, and allows multiple tracts to pass through the same voxels. we illustrate the approach with a segmentation of the corpus callosum and one of the cortico-spinal tract, with each example seeded at a single voxel.
3d ultrasound-guided motion compensation system for beating heart mitral valve repair. beating heart intracardiac procedures promise significant benefits for patients, however, the fast motion of the heart poses serious challenges to surgeons. we present a new 3d ultrasound-guided motion (3dus) compensation system that synchronizes instrument motion with the heart. the system utilizes the fact that the motion of some intracardiac structures, including the mitral valve annulus, is largely constrained to translation along one axis. this allows the development of a real-time 3dus tissue tracker which we integrate with a 1 degree-of-freedom actuated surgical instrument, real-time 3dus instrument tracker, and predictive filter to devise a system with synchronization accuracy of 1.8 mm rmse. user studies involving the deployment of surgical anchors in a simulated mitral annuloplasty procedure demonstrate that the system increases success rates by over 100%. furthermore, it enables more careful anchor deployment by reducing forces to the tissue by 50% while allowing instruments to remain in contact with the tissue for longer periods.
new algorithms to map asymmetries of 3d surfaces. in this paper, we propose a set of new generic automated processing tools to characterise the local asymmetries of anatomical structures (represented by surfaces) at an individual level, and within/between populations. the building bricks of this toolbox are: 1) a new algorithm for robust, accurate, and fast estimation of the symmetry plane of grossly symmetrical surfaces, and 2) a new algorithm for the fast, dense, non-linear matching of surfaces. this last algorithm is used both to compute dense individual asymmetry maps on surfaces, and to register these maps to a common template for population studies. we show these two algorithms to be mathematically well-grounded, and provide some validation experiments. then we propose a pipeline for the statistical evaluation of local asymmetries within and between populations. finally we present some results on real data.
r-plus: a riemannian anisotropic edge detection scheme for vascular segmentation. in this paper, detection of edges in oriented fields is addressed. in some applications such as vessel segmentation because of the intrinsic orientation of the structures, edge detection is only demanded in a particular subspace. this is specially usefull when a curve evolution is chosen for segmentation since gradients in parallel to vessel orientation may stop the contour. an anisotropic edge detection scheme is generalized on a riemannian manifold using the local structure tensor. the method is the generalization of the plus operator proposed in [8] for accurate curved edge detection. examples are given and the comparison is made with the state-of-the-art flux maximizing flow which indicates that significant improvements in terms of leakage minimization and thiner vessel delineation is achievable using our methodology.
improving parenchyma segmentation by simultaneous estimation of tissue property t1 map and group-wise registration of inversion recovery mr breast images. the parenchyma tissue in the breast has a strong relation with predictive biomarkers of breast cancer. to better segment parenchyma, we perform segmentation on estimated tissue property t 1 map. to improve the estimation of tissue property (t 1) which is the basis for parenchyma segmentation, we present an integrated algorithm for simultaneous t 1 map estimation, t 1 map based parenchyma segmentation and group-wise registration on series of inversion recovery magnetic resonance (mr) breast images. the advantage of using this integrated algorithm is that the simultaneous t 1 map estimation (e-step) and group-wise registration (r-step) could benefit each other and jointly improve parenchyma segmentation. in particular, in e-step, t 1 map based segmentation could help perform an edge-preserving smoothing on the tentatively estimated noisy t 1 map, and could also help provide tissue probability maps to be robustly registered in r-step. meanwhile, the improved estimation of t 1 map could help segment parenchyma in a more accurate way. in r-step, for robust registration, the group-wise registration is performed on the tissue probability maps produced in e-step, rather than the original inversion recovery mr images, since tissue probability maps are the intrinsic tissue property which is invariant to the use of different imaging parameters. the better alignment of images achieved in r-step can help improve t 1 map estimation and indirectly the t 1 map based parenchyma segmentation. by iteratively performing e-step and r-step, we can simultaneously obtain better results for t 1 map estimation,t 1 map based segmentation, group-wise registration, and finally parenchyma segmentation.
model-based segmentation using graph representations. a generic supervised segmentation approach is presented. the object is described as a graph where the vertices correspond to landmarks points and the edges define the landmark relations. instead of building one single global shape model, a priori shape information is represented as a concatenation of local shape models that consider only local dependencies between connected landmarks. the objective function is obtained from a maximum a posteriori criterion and is build up of localized energies of both shape and landmark intensity information. the optimization problem is discretized by searching candidates for each landmark using individual landmark intensity descriptors. the discrete optimization problem is then solved using mean field annealing or dynamic programming techniques. the algorithm is validated for hand bone segmentation from rx datasets and for 3d liver segmentation from contrast enhanced ct images.
spatial consistency in 3d tract-based clustering statistics. we propose a novel technique for tract-based comparison of dti-indices between groups, based on a representation that is estimated while matching fiber tracts. the method involves a non-rigid registration based on a joint clustering and matching approach, after which a 3d-atlas of cluster center points is used as a frame of reference for statistics. patient and control fa-distributions are compared per cluster. spatial consistency is taken to reflect a significant difference between groups. accordingly, a non-parametric classification is performed to assess the continuity of pathology over larger tract regions. in a study to infant survivors treated for medulloblastoma with intravenous methotrexate and cranial radiotherapy, significant decreases in fa in major parts of the corpus callosum were found.
surface-based structural group analysis of fmri data. as structural and surface-based analyses gain interest for activation detection, morphometry and intersubject matching purposes, this paper proposes a method to perform structural group analyses directly on the cortical surface. scale-space blobs are extracted from surface-based functional maps and matched across subjects. the process aims at identifying activations within a population despite the various effects due to variability. results of the method are presented with simulated activations and with data from a somatotopy protocol.
a novel algorithm for heart motion analysis based on geometric constraints. recently, much attention has been focused on heart motion analysis for minimally invasive beating-heart surgery. unfortunately existing techniques usually require the camera(s) to be fixed during the motion analysis, which can restrict its usefulness during surgery. in this paper we present a novel method for heart motion analysis using geometric constraint, which can estimate the motion from a moving camera and employ multiple image features to improve robustness to noise. our approach combines the benefits of geometry estimation for obtaining an accurate and robust solution with the proper treatment of respiratory motion. the proposed method can be applied to not only beating heart surgery, but also to other procedures involving periodic organ motion, such as lung and liver.
particle-based shape analysis of multi-object complexes. this paper presents a new method for optimizing surface point correspondences for shape modeling of multiobject anatomy, or shape complexes. the proposed method is novel in that it optimizes correspondence positions in the full, joint shape space of the object complex. researchers have previously only considered the correspondence problem separately for each structure, thus ignoring the interstructural shape correlations that are increasingly of interest in many clinical contexts, such as the study of the effects of disease on groups of neuroanatomical structures. the proposed method uses a nonparametric, dynamic particle system to simultaneously sample object surfaces and optimize correspondence point positions. this paper also suggests a principled approach to hypothesis testing using the hotelling t 2 test in the pca space of the correspondence model, with a simulation-based choice of the number of pca modes. we also consider statistical analysis of object poses. the modeling and analysis methods are illustrated on brain structure complexes from an ongoing clinical study of pediatric autism.
comprehensive segmentation of cine cardiac mr images. a typical cardiac magnetic resonance (cmr) examination includes acquisition of a sequence of short-axis (sa) and long-axis (la) images covering the cardiac cycle. quantitative analysis of the heart function requires segmentation of the left ventricle (lv) sa images, while segmented la views allow more accurate estimation of the basal slice and can be used for slice registration. since manual segmentation of cmr images is very tedious and time-consuming, its automation is highly required. in this paper, we propose a fully automatic 2d method for segmenting lv consecutively in la and sa images. the approach was validated on 35 patients giving mean segmentation error smaller than one pixel, both for la and sa, and accurate lv volume measurements.
customized design of hearing aids using statistical shape learning. 3d shape modeling is a crucial component of rapid prototyping systems that customize shapes of implants and prosthetic devices to a patient's anatomy. in this paper, we present a solution to the problem of customized 3d shape modeling using a statistical shape analysis framework. we design a novel method to learn the relationship between two classes of shapes, which are related by certain operations or transformation. the two associated shape classes are represented in a lower dimensional manifold, and the reduced set of parameters obtained in this subspace is utilized in an estimation, which is exemplified by a multivariate regression in this paper. we demonstrate our method with a felicitous application to estimation of customized hearing aid devices.
automatic image analysis of histopathology specimens using concave vertex graph. automatic image analysis of histopathology specimens would help the early detection of blood cancer. the first step for automatic image analysis is segmentation. however, touching cells bring the difficulty for traditional segmentation algorithms. in this paper, we propose a novel algorithm which can reliably handle touching cells segmentation. robust estimation and color active contour models are used to delineate the outer boundary. concave points on the boundary and inner edges are automatically detected. a concave vertex graph is constructed from these points and edges. by minimizing a cost function based on morphological characteristics, we recursively calculate the optimal path in the graph to separate the touching cells. the algorithm is computationally efficient and has been tested on two large clinical dataset which contain 207 images and 3898 images respectively. our algorithm provides better results than other studies reported in the recent literature.
towards multi-directional oct for speckle noise reduction. multi-directional optical coherence tomography (md-oct) applies and extends the concept of angular compounding for speckle noise reduction to the area of oct imaging. oct images are acquired from a wide range of angles of view. averaging of the rotated images therefore requires compensation of the parallax which is achieved by simple image registration for image reconstruction. test measurements of a sample structure in a low and highly scattering environment show that the method improves the signal-to-noise ratio by a factor of 4 and hence reduces speckle noise significantly. experimental results also show that the proposed averaging increases the performance of common edge-detection algorithms.
on computing the underlying fiber directions from the diffusion orientation distribution function. in this work, a novel method for determining the principal directions (maxima) of the diffusion orientation distribution function(odf) is proposed. we represent the odf as a symmetric high-order cartesian tensor restricted to the unit sphere and show that the extrema of the odf are solutions to a system of polynomial equations whose coefficients are polynomial functions of the tensor elements. in addition to demonstrating the ability of our methods to identify the principal directions in real data, we show that this method correctly identifies the principal directions under a range of noise levels. we also propose the use of the principal curvatures of the graph of the odf function as a measure of the degree of diffusion anisotropy in that direction. we present simulated results illustrating the relationship between the mean principal curvature, measured at the maxima, and the fractional anisotropy of the underlying diffusion tensor.
kinetic modeling based probabilistic segmentation for molecular images. we propose a semi-supervised, kinetic modeling based segmentation technique for molecular imaging applications. it is an iterative, self-learning algorithm based on uncertainty principles, designed to alleviate low signal-to-noise ratio (snr) and partial volume effect (pve) problems. synthetic fluorodeoxyglucose (fdg) and simulated raclopride dynamic positron emission tomography (dpet) brain images with excessive noise levels are used to validate our algorithm. we show, qualitatively and quantitatively, that our algorithm outperforms state-of-the-art techniques in identifying different functional regions and recovering the kinetic parameters.
task-specific functional brain geometry from model maps. in this paper we propose model maps to derive and represent the intrinsic functional geometry of a brain from functional magnetic resonance imaging (fmri) data for a specific task. model maps represent the coherence of behavior of individual fmri-measurements for a set of observations, or a time sequence. the maps establish a relation between individual positions in the brain by encoding the blood oxygen level dependent (bold) signal over a time period in a markov chain. they represent this relation by mapping spatial positions to a new metric space, the model map. in this map the euclidean distance between two points relates to the joint modeling behavior of their signals and thus the co-dependencies of the corresponding signals. the map reflects the functional as opposed to the anatomical geometry of the brain. it provides a quantitative tool to explore and study global and local patterns of resource allocation in the brain. to demonstrate the merit of this representation, we report quantitative experimental results on 29 fmri time sequences, each with sub-sequences corresponding to 4 different conditions for two groups of individuals. we demonstrate that drug abusers exhibit lower differentiation in brain interactivity between baseline and reward related tasks, which could not be quantified until now.
segmenting brain tumors using pseudo-conditional random fields. locating brain tumor segmentation within mr (magnetic resonance) images is integral to the treatment of brain cancer. this segmentation task requires classifying each voxel as either tumor or non-tumor, based on a description of that voxel. unfortunately, standard classifiers, such as logistic regression (lr) and support vector machines (svm), typically have limited accuracy as they treat voxels as independent and identically distributed (iid). approaches based on random fields, which are able to incorporate spatial constraints, have recently been applied to brain tumor segmentation with notable performance improvement over iid classifiers. however, previous random field systems involved computationally intractable formulations, which are typically solved using some approximation. here, we present pseudo-conditional random fields (pcrfs), which achieve accuracy similar to other random fields variants, but are significantly more efficient. we formulate a pcrf as a regularized discriminative classifier that relaxes the classification decision for each voxel by considering the labels and features of neighboring voxels.
volume reconstruction by inverse interpolation: application to interleaved mr motion correction. we introduce in this work a novel algorithm for volume reconstruction from data acquired on an irregular grid, e.g., from multiple co-registered images. the algorithm, which is based on an inverse interpolation formalism, is superior to other methods in particular when the input images have lower spatial resolution than the reconstructed image. local intensity bounds are enforced by an l-bfgs-b optimizer, regularize the reconstruction problem, and preserve the intensity distribution of the input images. we demonstrate the usefulness of our method by applying it to retrospective motion correction in interleaved mr images.
a constrained non-rigid registration algorithm for use in prostate image-guided radiotherapy. a constrained non-rigid registration (cnrr) algorithm for use in updating prostate external beam image-guided radiotherapy treatment plans is presented in this paper. the developed algorithm is based on a multi-resolution cubic b-spline ffd transformation and has been tested and verified using 3d ct images from 10 sets of real patient data acquired from 4 different patients on different treatment days. the registration can be constrained to any combination of the prostate, rectum, bladder, pelvis, left femur, and right femur. the cnrr was tested with 5 different combinations of constraints and each test significantly outperformed both rigid and non-rigid registration at aligning constrained bones and critical organs. the cnrr was then used to update the treatment plans to account for articulated, rigid bone motion and non-rigid organ deformation. each updated treatment plan outperformed the original treatment plan by increasing radiation dosage to the prostate and lowering radiation dosage to the rectum and bladder.
detection of dti white matter abnormalities in multiple sclerosis patients. the emergence of new modalities such as diffusion tensor imaging (dti) is of great interest for the characterization and the temporal study of multiple sclerosis (ms). dti indeed gives information on water diffusion within tissues and could therefore reveal alterations in white matter fibers before being visible in conventional mri. however, recent studies generally rely on scalar measures derived from the tensors such as fa or md instead of using the full tensor itself. therefore, a certain amount of information is left unused.in this article, we present a framework to study the benefits of using the whole diffusion tensor information to detect statistically significant differences between each individual ms patient and a database of control subjects. this framework, based on the comparison of the ms patient dti and a mean dti atlas built from the control subjects, allows us to look for differences both in normally appearing white matter but also in and around the lesions of each patient. we present a study on a database of 11 ms patients, showing the ability of the dti to detect not only significant differences on the lesions but also in regions around them, enabling an early detection of an extension of the ms disease.
a global approach for automatic fibroscopic video mosaicing in minimally invasive diagnosis. recent developments in bio-photonics have called for the need of bringing cellular and molecular imaging modalities to an in vivo --- in situ setting to allow for real-time tissue characterization and functional assessment. before such techniques can be used effectively in routine clinical environments, it is necessary to address the visualization requirement for linking point based optical biopsy to large area tissue visualization. this paper presents a novel approach for fibered endoscopic video mosaicing that permits wide region tissue visualization. a feature-based registration method is used to register the frames of the endoscopic video sequence by taking into account the characteristics of fibroscopic imaging such as non-linear lens distortion and high-frequency fiber optic facet pattern. the registration is combined with an efficient optimization scheme in order to align all input frames in a globally consistent way. an evaluation on phantom and ex vivo tissue images allowing free-hand camera motion is presented.
findings in schizophrenia by tract-oriented dt-mri analysis. this paper presents a tract-oriented analysis of diffusion tensor (dt) images of the human brain. we demonstrate that unlike the commonly used roi-based methods for population studies, our technique is sensitive to the local variation of diffusivity parameters along the fiber tracts. we show the strength of the proposed approach in identifying the differences in schizophrenic data compared to controls. statistically significant drops in fractional anisotropy are observed along the genu and bilaterally in the splenium, as well as an increase in principal eigenvalue in uncinate fasciculus. this is the first tract-oriented clinical study in which an anatomical atlas is used to guide the algorithm.
dynamic thermal modeling of the normal and tumorous breast under elastic deformation. to quantify the complex relationships between (1) the temperature, and temperature differences, on the surface of the breast as recorded by infrared thermal imaging and (2) the underlying physiological and pathological factors, we have developed a dynamic finite element method for comprehensive modeling of both the thermal and elastic properties of normal and tumorous breast tissues. in the steady state, the gravity-induced deformation is found to cause markedly asymmetric surface temperatures even though all thermal-elastic properties are symmetrical. in the dynamic state, the time course of breast thermal imaging in cold-stress and thermal-recovery procedures is found to be useful in characterizing the origins of the thermal contrast on the breast surface. the tumor-induced thermal contrast has slower temporal behavior than the deformation-induced thermal contrast on the breast surface, which may lead to improvements in breast-tumor diagnosis.
toward unsupervised classification of calcified arterial lesions. there is growing evidence that calcified arterial deposits play a crucial role in the pathogenesis of cardiovascular disease. this paper investigates the challenging problem of unsupervised calcified lesion classification. we propose an algorithm, us-calc (unsupervised calcified arterial lesion classification), that discriminates arterial lesions from non-arterial lesions. the proposed method first mines the characteristics of calcified lesions using a novel optimization criterion and then identifies a subset of lesion features which is optimal for classification. second, a two stage clustering is deployed to discriminate between arterial and non-arterial lesions. a histogram intersection distance measure is incorporated to determine cluster proximity. the clustering hierarchies are carefully validated and the final clusters are determined by a new intra-cluster compactness measure. experimental results indicate an average accuracy of approximately 80% on a database of electron beam ct heart scans.
motion robust magnetic susceptibility and field inhomogeneity estimation using regularized image restoration techniques for fmri. in functional mri, head motion may cause dynamic nonlinear field-inhomogeneity changes, especially with large out-of-plane rotations. this may lead to dynamic geometric distortion or blurring in the time series, which may reduce activation detection accuracy. the use of image registration to estimate dynamic field inhomogeneity maps from a static field map is not sufficient in the presence of such rotations. this paper introduces a retrospective approach to estimate magnetic susceptibility induced field maps of an object in motion, given a static susceptibility induced field map and the associated object motion parameters. it estimates a susceptibility map from a static field map using regularized image restoration techniques, and applies rigid body motion to the former. the dynamic field map is then computed using susceptibility voxel convolution. the method addresses field map changes due to out-of-plane rotations during time series acquisition and does not involve real time field map acquisitions.
automatic tracking of escherichia coli bacteria. in this paper, we present an automatic method for estimating the trajectories of escherichia coli bacteria from in vivo phase-contrast microscopy videos. to address the low-contrast boundaries in cellular images, an adaptive kernel-based technique is applied to detect cells in sequence of frames. then a novel matching gain measure is introduced to cope with the challenges such as dramatic changes of cells' appearance and serious overlapping and occlusion. for multiple cell tracking, an optimal matching strategy is proposed to improve the handling of cell collision and broken trajectories. the results of successful tracking of escherichia coli from various phase-contrast sequences are reported and compared with manually-determined trajectories, as well as those obtained from existing tracking methods. the stability of the algorithm with different parameter values is also analyzed and discussed.
cortical surface thickness as a classifier: boosting for autism classification. we study the problem of classifying an autistic group from controls using structural image data alone, a task that requires a clinical interview with a psychologist. because of the highly convoluted brain surface topology, feature extraction poses the first obstacle. a clinically relevant measure called the cortical thickness has shown promise but yields a rather challenging learning problem --- where the dimensionality of the distribution is extremely large and the training set is small. by observing that each point on the brain cortical surface may be treated as a "hypothesis", we propose a new algorithm for lpboosting (with truncated neighborhoods) for this problem. in addition to learning a high quality classifier, our model incorporates topological priors into the classification framework directly --- that two neighboring points on the cortical surface (hypothesis pairs) must have similar discriminative qualities. as a result, we obtain not just a label { + 1, ¿ 1} for test items, but also an indication of the "discriminative regions" on the cortical surface. we discuss the formulation and present interesting experimental results.
interactive separation of segmented bones in ct volumes using graph cut. we present a fast, interactive method for separating bones that have been collectively segmented from a ct volume. given user-provided seed points, the method computes the separation as a multi-way cut on a weighted graph constructed from the binary, segmented volume. by properly designing and weighting the graph, we show that the resulting cut can accurately be placed at bone-interfaces using only a small number of seed points even when the data is noisy. the method has been implemented with an interactive graphical interface, and used to separate the 12 human foot bones in 10 ct volumes. the interactive tool produced compatible result with a ground-truth separation, generated by a completely manual labelling procedure, while reducing the human interaction time from a mean of 2.4 hours per volume in manual labelling down to approximately 18 minutes.
diffusion tensor image registration using tensor geometry and orientation features. this paper presents a method for deformable registration of diffusion tensor (dt) images that integrates geometry and orientation features into a hierarchical matching framework. the geometric feature is derived from the structural geometry of diffusion and characterizes the shape of the tensor in terms of prolateness, oblateness, and sphericity of the tensor. local spatial distributions of the prolate, oblate, and spherical geometry are used to create an attribute vector of geometric feature for matching. the orientation feature improves the matching of the wm fiber tracts by taking into account the statistical information of underlying fiber orientations. these features are incorporated into a hierarchical deformable registration framework to develop a diffusion tensor image registration algorithm. extensive experiments on simulated and real brain dt data establish the superiority of this algorithm for deformable matching of diffusion tensors, thereby aiding in atlas creation. the robustness of the method makes it potentially useful for group-based analysis of dt images acquired in large studies to identify disease-induced and developmental changes.
interactive simulation of embolization coils: modeling and experimental validation. coil embolization offers a new approach to treat aneurysms. this medical procedure is namely less invasive than an open-surgery as it relies on the deployment of very thin platinum-based wires within the aneurysm through the arteries. when performed intracranially, this procedure must be particularly accurate and therefore carefully planned and performed by experienced radiologists. a simulator of the coil deployment represents an interesting and helpful tool for the physician by providing information on the coil behavior. in this paper, an original modeling is proposed to obtain interactive and accurate simulations of coil deployment. the model takes into account geometric nonlinearities and uses a shape memory formulation to describe its complex geometry. an experimental validation is performed in a contact-free environment to identify the mechanical properties of the coil and to quantitatively compare the simulation with real data. computational performances are also measured to insure an interactive simulation.
regularized discriminative direction for shape difference analysis. the "discriminative direction" has been proven useful to reveal the subtle difference between two anatomical shape classes. when a shape moves along this direction, its deformation will best manifest the class difference detected by a kernel classifier. however, we observe that such a direction cannot maintain a shape's "anatomical" correctness, introducing spurious difference. to overcome this drawback, we develop a regularized discriminative direction by requiring a shape to conform to its population distribution when it deforms along the discriminative direction. instead of iterative optimization, an analytic solution is provided to directly work out this direction. experimental study shows its superior performance in detecting and localizing the difference of hippocampal shapes for sex. the result is supported by other independent research in the same domain.
group statistics of dti fiber bundles using spatial functions of tensor measures. we present a framework for hypothesis testing of differences between groups of dti fiber tracts. an anatomical, tract-oriented coordinate system provides a basis for estimating the distribution of diffusion properties. the parametrization of sampled, smooth functions is normalized across a population using dti atlas building. functional data analysis, an extension of multivariate statistics to continuous functions is applied to the problem of hypothesis testing and discrimination. b-spline models of fractional anisotropy (fa) and frobenius norm measures are analyzed jointly. plots of the discrimination direction provide a clinical interpretation of the group differences. the methodology is tested on a pediatric study of subjects aged one and two years.
a symmetry-based method for the determination of vertebral rotation in 3d. in the past, a number of methods were proposed for quantitative assessment of vertebral rotation from three-dimensional (3d) images. however, these methods were based on manual identification of distinctive anatomical landmarks, required manual determination of cross-sections from 3d images, and measured only axial vertebral rotation instead of the rotation in 3d. in this paper, we propose an automated method for quantitative assessment of vertebral rotation in 3d that is based on finding the planes of vertebral symmetry by matching image intensity gradients on both sides of each plane. the method was evaluated on 28 images of normal and pathological vertebrae, obtained by computed tomography (ct) and magnetic resonance (mr). for each vertebra, final angle displacements of 200 initial angle displacements, uniformly distributed within 30° from manually obtained reference angles, were obtained. the results show that by the proposed method, vertebral rotation can be successfully estimated in 3d with an average accuracy of 1.0° and precision of 0.5°.
adaptive boundary conditions for physically based follow-up breast mr image registration. this paper presents an algorithm for non-rigid registration of breast mri follow-up images that compensates for differences in patient positioning while maintaining real anatomical and pathological changes. the proposed method uses a biomechanical model to constrain the deformation of the internal breast tissue according to elastic continuum mechanics, which is driven by suitable boundary conditions that align the breast surfaces in the images to be registered. typically, such boundary conditions impose one-to-one surface point correspondences that are established a priori. we investigate alternative, more flexible boundary conditions that do not depend on fixed point correspondences and do not assume completely accurate breast surface segmentation in both images. more specifically, we allow for sliding motion of one surface over the other during deformation as well as for restricted motion perpendicular to the initially segmented boundary surface, based on the internal elastic forces and local intensity information. we evaluate the impact of different boundary conditions on registration quality from the subtraction images obtained for repeated scans of healthy volunteers with intermediate repositioning, using rigid body and free form whole volume intensity based registration for comparison, and also present initial results for actual patient data. our results demonstrate a drastic reduction in subtraction artifacts using our model, without compromising the biomechanical validity of the deformation field such as unrealistically large local volume changes as with traditional voxel intensity based registration.
brain mr image segmentation using local and global intensity fitting active contours/surfaces. in this paper, we present an improved region-based active contour/surface model for 2d/3d brain mr image segmentation. our model combines the advantages of both local and global intensity information, which enable the model to cope with intensity inhomogeneity. we define an energy functional with a local intensity fitting term and an auxiliary global intensity fitting term. in the associated curve evolution, the motion of the contour is driven by a local intensity fitting force and a global intensity fitting force, induced by the local and global terms in the proposed energy functional, respectively. the influence of these two forces on the curve evolution is complementary. when the contour is close to object boundaries, the local intensity fitting force became dominant, which attracts the contour toward object boundaries and finally stops the contour there. the global intensity fitting force is dominant when the contour is far away from object boundaries, and it allows more flexible initialization of contours by using global image information. the proposed model has been applied to both 2d and 3d brain mr image segmentation with promising results.
level set based surface capturing in 3d medical images. brain aneurysm rupture has been reported to be directly related to the size of aneurysms. the current method used to determine aneurysm size is to manually measure the width of the neck and height of the dome on a computer screen. because aneurysms usually have complicated shapes, using the size of the aneurysm neck and dome may not be accurate and may overlook important geometrical information. in this paper we present a level set based illusory surface algorithm to capture the aneurysms from the vascular tree. since the aneurysms are described by level set functions, not only the volume but also the curvature of aneurysms can be computed for medical studies. experiments and comparisons with models used for capturing illusory contours in 2d images are performed. this includes applications to clinical image data demonstrating the procedure of accurately capturing a middle cerebral artery aneurysm.
a new stochastic framework for accurate lung segmentation. new techniques for more accurate unsupervised segmentation of lung tissues from low dose computed tomography (ldct) are proposed. in this paper we describe ldct images and desired maps of regions (lung and the other chest tissues) by a joint markov-gibbs random field model (mgrf) of independent image signals and interdependent region labels but focus on most accurate model identification. to better specify region borders, each empirical distribution of signals is precisely approximated by a linear combination of discrete gaussians (lcdg) with positive and negative components. we modify a conventional expectation-maximization (em) algorithm to deal with the lcdg and develop a sequential em-based technique to get an initial lcdg-approximation for the modified em algorithm. the initial segmentation based on the lcdg-models is then iteratively refined using a mgrf model with analytically estimated potentials. experiments on real data sets confirm high accuracy of the proposed approach.
real-time 3d reconstruction for collision avoidance in interventional environments. with the increased presence of automated devices such as c-arms and medical robots and the introduction of a multitude of surgical tools, navigation systems and patient monitoring devices, collision avoidance has become an issue of practical value in interventional environments. in this paper, we present a real-time 3d reconstruction system for interventional environments which aims at predicting collisions by building a 3d representation of all the objects in the room. the 3d reconstruction is used to determine whether other objects are in the working volume of the device and to alert the medical staff before a collision occurs. in the case of c-arms, this allows faster rotational and angular movement which could for instance be used in 3d angiography to obtain a better reconstruction of contrasted vessels. the system also prevents staff to unknowingly enter the working volume of a device. this is of relevance in complex environments with many devices. the recovered 3d representation also opens the path to many new applications utilizing this data such as workflow analysis, 3d video generation or interventional room planning. to validate our claims, we performed several experiments with a real c-arm that show the validity of the approach. this system is currently being transferred to an interventional room in our university hospital.
combination of intraoperative 5-aminolevulinic acid-induced fluorescence and 3-d mr imaging for guidance of robotic laser ablation for precision neurosurgery. a combination of 5-aminolevulinic acid (5-ala)-induced fluorescence and three-dimensional (3-d) magnetic resonance imaging (mri) of a brain tumor has been incorporated into a robotic laser ablation neurosurgery system. 5-ala is a non-fluorescent prodrug that leads to intracellular accumulation of fluorescent protoporphyrins ix (ppix) in malignant glioma. the ppix tends to accumulate in pathological lesions, and emits red fluorescence when excited by blue light. this fluorescence is illuminated with laser excitation, enables intra-operative identification of the position of a tumor and provides guidance for resection with laser photocoagulation. the information provided by the mri is enhanced by the 5-ala fluorescence data, and this enhanced information is integrated into a robotic laser ablation system. the accuracy of the fluorescent measurement of the tumor is improved using high-precision spectral analysis. the fluorescence assists in the detection of malignant brain tumors intraoperatively and improves their removal rate.
colon unfolding via skeletal subspace deformation. we present an efficient method to digitally straighten a colon volume using mesh skinning, a technique well known in computer graphics to deform a polygonal mesh attached to a skeleton hierarchy. in our case, the colon centerline is used as the skeleton structure and the polyhedral model of the lumen as the skin that is to be deformed as the centerline is straightened. once the colon has been straightened, we use standard rendering techniques to compute the virtual dissection. our approach is significantly more efficient than previously proposed techniques.
non-uniform gradient prescription for precise angular measurements using dti. diffusion tensor imaging (dti) calculates a tensor for each voxel, representing the mean diffusive characteristics in volume-averaged tissue. gradients that phase-encode spins according to the amount of their diffusion are usually applied uniformly over a sphere during a dti procedure for minimal bias of tensor information. if prior knowledge of diffusion direction exists, the angular precision for determining the principle eigenvector of cylindrically-symmetric ("prolate") tensors can be improved by specifying gradients non-uniformly. improvements in precision of 30-40% can be achieved using a restricted band of zenith angle values for gradient directions. sensitivity to the a priori angular range of the principle eigenvector can be adjusted with the width of the band. simulations and phantom data are in agreement; a preliminary validation is presented.
automatic intra-operative generation of geometric left atrium/pulmonary vein models from rotational x-ray angiography. pre-procedural imaging with cardiac ct or mr has become popular for guiding complex electrophysiology procedures such as those used for atrial fibrillation ablation therapy. electroanatomical mapping and ablation within the left atrium and pulmonary veins (lapv) is facilitated using such data, however the pre-procedural anatomy can be quite different from that at the time of intervention. recently, a method for intra-procedural lapv imaging has been developed based on contrast-enhanced 3-d rotational x-ray angiography (3-d ra). these intraprocedural data now create a compelling need for rapid and automated extraction of the lapv geometry for catheter guidance. we present a new approach to automatic intra-procedural generation of lapv surfaces from 3-d ra volumes. using model-based segmentation, our technique is robust to imaging noise and artifacts typical of 3-d ra imaging, strongly minimizes the user interaction time required for segmentation, and eliminates inter-subject variability. our findings in 33 patients indicate that intra-procedural lapv surface models accurately represent the anatomy at the time of intervention and are comparable to pre-procedural models derived from cta or mra.
motion correction in respiratory gated cardiac pet/ct using multi-scale optical flow. respiratory motion is a source of degradation in positron emission tomography. as the patients cannot hold breath during the pet acquisition, spatial blurring and motion artifacts are unavoidable which may lead to wrong quantification of the data. a solution based on respiratory-gating and optical flow based correction of the pet data is proposed. this includes deformation of the ct data for accurate attenuation and listmode based reconstruction. all methods are applied to real patient data and are evaluated with respect to three criteria.
3d brain segmentation using active appearance models and local regressors. we describe an efficient and accurate method for segmenting sets of subcortical structures in 3d mr images of the brain. we first find the approximate position of all the structures using a global active appearance model (aam). we then refine the shape and position of each structure using a set of individual aams trained for each. finally we produce a detailed segmentation by computing the probability that each voxel belongs to the structure, using regression functions trained for each individual voxel. the models are trained using a large set of labelled images, using a novel variant of `groupwise' registration to obtain the necessary image correspondences. we evaluate the method on a large dataset, and demonstrate that it achieves results comparable with some of the best published.
fast musculoskeletal registration based on shape matching. this paper presents a new method for computing elastic and plastic deformations in the context of discrete deformable model-based registration. internal forces are estimated by averaging local transforms between reference and current particle positions. our technique can accommodate large non-linear deformations, and is unconditionally stable. moreover, it is simple to implement and versatile. we show how to tune model stiffness and computational cost, which is important for efficient registration, and demonstrate our technique in the complex problem of inter-patient musculoskeletal registration.
a statistical motion model based on biomechanical simulations for data fusion during image-guided prostate interventions. a method is described for generating a patient-specific, statistical motion model (smm) of the prostate gland. finite element analysis (fea) is used to simulate the motion of the gland using an ultrasound-based 3d fe model over a range of plausible boundary conditions and soft-tissue properties. by applying principal component analysis to the displacements of the fe mesh node points inside the gland, the simulated deformations are then used as training data to construct the smm. the smm is used to both predict the displacement field over the whole gland and constrain a deformable surface registration algorithm, given only a small number of target points on the surface of the deformed gland. using 3d transrectal ultrasound images of the prostates of five patients, acquired before and after imposing a physical deformation, to evaluate the accuracy of predicted landmark displacements, the mean target registration error was found to be less than 1.9mm.
modelling mammographic compression of the breast. we have developed a biomechanical model of the breast to simulate compression during mammographic imaging. the modelling framework was applied to a set of mr images of the breasts of a volunteer. images of the uncompressed breast were segmented into skin and pectoral muscle, from which a finite element (fe) mesh of the left breast was generated using a nonlinear geometric fitting process. the compression plates within the breast mr coil were used to compress the volunteer's breasts by 32% in the latero-medial direction and the compressed breasts were subsequently imaged using mri. the fe geometry of the uncompressed left breast was used to numerically simulate compression based on finite deformation elasticity coupled with contact mechanics, and individual-specific tissue properties. accuracy of the simulated fe model was analysed by comparing the predicted surface data, and locations of three internal features within the compressed breast, with the equivalent experimental observations. model predictions of the surface deformation yielded a rms error of 1.5 mm. the euclidean errors in predicting the locations of three internal features were 4.1 mm, 4.1 mm and 6.5 mm. whilst the model reliably reproduced the compressive deformation, further investigations are required in order to test the validity of the underlying modelling assumptions. a reliable biomechanical model will provide a multi-modality imaging registration tool to help identify potential tumours observed between mammograms and other imaging modalities such as mri or ultrasound.
optimal feature selection applied to multispectral fluorescence imaging. recent rapid developments in multi-modal optical imaging have created a significant clinical demand for its in vivo - in situ application. this offers the potential for real-time tissue characterization, functional assessment, and intra-operative guidance. one of the key requirements for in vivo consideration is to minimise the acquisition window to avoid tissue motion and deformation, whilst making the best use of the available photons to account for correlation or redundancy between different dimensions. the purpose of this paper is to propose a feature selection framework to identify the best combination of features for discriminating between different tissue classes such that redundant or irrelevant information can be avoided during data acquisition. the method is based on a bayesian framework for feature selection by using the receiver operating characteristic curves to determine the most pertinent data to capture. this represents a general technique that can be applied to different multi-modal imaging modalities and initial results derived from phantom and ex vivo tissue experiments demonstrate the potential clinical value of the technique.
segmentation of vessels cluttered with cells using a physics based model. segmentation of vessels in biomedical images is important as it can provide insight into analysis of vascular morphology, topology and is required for kinetic analysis of flow velocity and vessel permeability. intravital microscopy is a powerful tool as it enables in vivo imaging of both vasculature and circulating cells. however, the analysis of vasculature in those images is difficult due to the presence of cells and their image gradient. in this paper, we provide a novel method of segmenting vessels with a high level of cell related clutter. a set of virtual point pairs ("vessel probes") are moved reacting to forces including vessel vector flow (vvf) and vessel boundary vector flow (vbvf) forces. incorporating the cell detection, the vvf force attracts the probes toward the vessel, while the vbvf force attracts the virtual points of the probes to localize the vessel boundary without being distracted by the image features of the cells. the vessel probes are moved according to newtonian physics reacting to the net of forces applied on them. we demonstrate the results on a set of five real in vivo images of liver vasculature cluttered by white blood cells. when compared against the ground truth prepared by the technician, the root mean squared error (rmse) of segmentation with vvf and vbvf was 55% lower than the method without vvf and vbvf.
an atlas-based segmentation propagation framework using locally affine registration - application to automatic whole heart segmentation. in this paper, we present a novel registration algorithm for locally affine registrations. this method preserves the anatomical and intensity class relationships between the local regions. a regularisation procedure is used to maintain a global diffeomorphic transformation. combined with a novel generic method for accurately inverting the final deformation field, we include our techniques within an atlas-based segmentation propagation framework. we applied our method to automatically segment the whole heart from cardiac magnetic resonance images from a cohort of 18 volunteers (acquisition resolution 2 × 2 × 2 mm). the results show that the proposed method provides a robust initialisation for the atlas-based segmentation propagation framework refined with a fluid registration. we validated our approach against other registration strategies, and demonstrated that we improved the accuracy of the whole heart segmentations (1.8 ± 0.42 mm).
simulations of needle insertion by using a eulerian hydrocode fem and the experimental validations. in this paper, simulations for needle insertion were performed by using a novel eulerian hydrocode fem, which was adaptive for large deformation and tissue fracture. we also performed experiments for the same needle insertion with silicon rubbers and needles, which had conical tips of different angles in order to investigate the accuracy of the simulations. the resistance forces in the simulations accurately followed those in the experiments until the conical portion of the needle was inside the rubbers, and the validation of the eulerian hydrocode was revealed. however, the present simulation showed that after the conical portion was inside the tissue, the simulated resistance forces became lower than the experimental ones. the proportional increase of the friction forces and the roughly flatness of the tip force along the time were simulated. it was predicted that the tightening force along the needle side was underestimated.
image thickness correction for navigation with 3d intra-cardiac ultrasound catheter. in this paper we present an algorithm to correct 3d reconstruction errors of 3d ultrasound catheter caused by ultrasound image thickness. we also provide a method to quickly measure ultrasound image plane's thickness. with thickness correction registration accuracy of navigation system using 3d ultrasound catheters can be improved by 20%.
modeling and online recognition of surgical phases using hidden markov models. the amount of signals that can be recorded during a surgery, like tracking data or state of instruments, is constantly growing. these signals can be used to better understand surgical workflow and to build surgical assist systems that are aware of the current state of a surgery. this is a crucial issue for designing future systems that provide context-sensitive information and user interfaces.in this paper, hidden markov models (hmm) are used to model a laparoscopic cholecystectomy. seventeen signals, representing tool usage, from twelve surgeries are used to train the model. the use of a model merging approach is proposed to build the hmm topology and compared to other methods of initializing a hmm. the merging method allows building a model at a very fine level of detail that also reveals the workflow of a surgery in a human-understandable way. results for detecting the current phase of a surgery and for predicting the remaining time of the procedure are presented.
cardiac medial modeling and time-course heart wall thickness analysis. the medial model is a powerful shape representation method that models a 3d object by explicitly defining its skeleton (medial axis) and deriving the boundary geometry according to medial geometry. it has been recently extended to model complex shapes with multi-figures, i.e., shapes whose skeletons can not be described by a single sheet in 3d. this paper applied the medial model to a 2-chamber heart data set consisting of 428 cardiac shapes from 90 subjects. the results show that the medial model can capture the heart shape accurately. to demonstrate the usage of the medial model, the changes of the heart wall thickness over time are analyzed. we calculated the mean heart wall thickness map of 90 subjects for different phases of the cardiac cycle, as well as the mean thickness change between phases.
optimized conformal parameterization of cortical surfaces using shape based matching of landmark curves. in this work, we find meaningful parameterizations of cortical surfaces utilizing prior anatomical information in the form of anatomical landmarks (sulci curves) on the surfaces. specifically we generate close to conformal parametrizations that also give a shape-based correspondence between the landmark curves. we propose a variational energy that measures the harmonic energy of the parameterization maps, and the shape dissimilarity between mapped points on the landmark curves. the novelty is that the computed maps are guaranteed to give a shape-based diffeomorphism between the landmark curves. we achieve this by intrinsically modelling our search space of maps as flows of smooth vector fields that do not flow across the landmark curves, and by using the local surface geometry on the curves to define a shape measure. such parameterizations ensure consistent correspondence between anatomical features, ensuring correct averaging and comparison of data across subjects. the utility of our model is demonstrated in experiments on cortical surfaces with landmarks delineated, which show that our computed maps give a shape-based alignment of the sulcal curves without significantly impairing conformality.
label space: a coupled multi-shape representation. richly labeled images representing several sub-structures of an organ occur quite frequently in medical images. for example, a typical brain image can be labeled into grey matter, white matter or cerebrospinal fluid, each of which may be subdivided further. many manipulations such as interpolation, transformation, smoothing, or registration need to be performed on these images before they can be used in further analysis. in this work, we present a novel multi-shape representation and compare it with the existing representations to demonstrate certain advantages of using the proposed scheme. specifically, we propose label space, a representation that is both flexible and well suited for coupled multi-shape analysis. under this framework, object labels are mapped to vertices of a regular simplex, e.g the unit interval for two labels, a triangle for three labels, a tetrahedron for four labels, etc. this forms the basis of a convex linear structure with the property that all labels are equally spaced. we will demonstrate that this representation has several desirable properties: algebraic operations may be performed directly, label uncertainty is expressed equivalently as a weighted mixture of labels or in a probabilistic manner, and interpolation is unbiased toward any label or the background. in order to demonstrate these properties, we compare label space to signed distance maps as well as other implicit representations in tasks such as smoothing, interpolation, registration, and principal component analysis.
real-time simulation of 4d lung tumor radiotherapy using a breathing model. in this paper, we present a real-time simulation and visualization framework that models a deformable surface lung model with tumor, simulates the tumor motion and predicts the amount of radiation doses that would be deposited in the moving lung tumor during the actual delivery of radiation. the model takes as input a subject-specific 4d computed tomography (4d ct) of lungs and computes a deformable lung surface model by estimating the deformation properties of the surface model using an inverse dynamics approach. once computed, the deformable model is used to simulate and visualize lung tumor motion that would occur during radiation therapy accounting for variations in the breathing pattern. a radiation treatment plan for the lung tumor is developed using one of the 4d ct phases. during the simulation of radiation delivery, the dose on the lung tumor is computed for each beam independently.
active volume models with probabilistic object boundary prediction module. we propose a novel active volume model (avm) which deforms in a free-form manner to minimize energy. unlike snakes and level-set active contours which only consider curves or surfaces, the avm is a deforming object model that has both boundary and an interior area. when applied to object segmentation and tracking, the model alternates between two basic operations: deform according to current object prediction, and predict according to current appearance statistics of the model. the probabilistic object prediction module relies on the bayesian decision rule to separate foreground (i.e. object represented by the model) and background. optimization of the model is a natural extension of the snakes model so that region information becomes part of the external forces. the avm thus has the efficiency of snakes while having adaptive region-based constraints. segmentation results, validation, and comparison with gvf snakes and level set methods are presented for experiments on noisy 2d/3d medical images.
fieldmap-free retrospective registration and distortion correction for epi-based functional imaging. we describe a method for correcting the distortions present in echo planar images (epi) and registering the epi to structural mri. a fieldmap is predicted from an air / tissue segmentation of the mri using a perturbation method and subsequently used to unwarp the epi data. shim and other missing parameters are estimated by registration. we obtain results that are similar to those obtained using fieldmaps, however neither fieldmaps, nor knowledge of shim coefficients is required.
parallelized hybrid tgrappa reconstruction for real-time interactive mri. real-time parallel mri reconstruction was demonstrated using a hybrid implementation of the tgrappa algorithm. the grappa coefficients were calculated in k-space and applied in the image domain after appropriate transformation, thereby achieving improved speed and excellent image quality. adaptive b1-weighted combining of the per coil images permitted use of pre-calculated composite image domain weights providing significant decrease in computation. the weight calculation was decoupled from the real-time image reconstruction as a parallel processing thread which was updated in an adaptive manner to speed convergence in the event of interactive change in scan plane. the computation was parallelized and implemented on a general purpose multi-core architecture. reconstruction speeds of 65-70 frames per second were achieved with a matrix of 192x144 with 15 coils.
symmetric nonrigid image registration: application to average brain templates construction. image registration aims at estimating a consistent mapping between two images. common techniques consist in choosing arbitrarily one image as a reference image and the other one as a floating image, thus leading to the estimation of inconsistent mappings. we present a symmetric formulation of the registration problem that maps the two images in a common coordinate system halfway between them. this framework has been considered to devise an efficient strategy for mapping a large set of images in a common coordinate system. some results are presented in the context of 3-d nonrigid brain mr image registration for the construction of average brain templates.
weight preserving image registration for monitoring disease progression in lung ct. we present a new image registration based method for monitoring regional disease progression in longitudinal image studies of lung disease. a free-form image registration technique is used to match a baseline 3d ct lung scan onto a following scan. areas with lower intensity in the following scan compared with intensities in the deformed baseline image indicate local loss of lung tissue that is associated with progression of emphysema. to account for differences in lung intensity owing to differences in the inspiration level in the two scans rather than disease progression, we propose to adjust the density of lung tissue with respect to local expansion or compression such that the total weight of the lungs is preserved during deformation. our method provides a good estimation of regional destruction of lung tissue for subjects with a significant difference in inspiration level between ct scans and may result in a more sensitive measure of disease progression than standard quantitative ct measures.
a new method for creating electrophysiological maps for dbs surgery and their application to surgical guidance. electrophysiological maps based on a gaussian kernel have been proposed as a means to visualize response to stimulation in deep brain stimulation (dbs) surgeries. however, the gaussian model does not represent the underlying physiological phenomenon produced by stimulation. we propose a new method to create physiological maps, which relies on spherical shell kernels. we compare our new maps to those created with gaussian kernels and show that, on simulated data, this new approach produces more realistic maps. experiments we have performed with real patient data show that our new maps correlate well with the underlying anatomy. finally, we present preliminary results on an ongoing study assessing the value of these maps as pre-operative planning and intra-operative guidance tools.
discovering modes of an image population through mixture modeling. we present icluster, a fast and efficient algorithm that clusters a set of images while co-registering them using a parameterized, nonlinear transformation model. the output is a small number of template images that represent different modes in a population. this is in contrast with traditional approaches that assume a single template to construct atlases. we validate and explore the algorithm in two experiments. first, we employ icluster to partition a data set of 416 whole brain mr volumes of subjects aged 18-96 years into three sub-groups, which mainly correspond to age groups. the templates reveal significant structural differences across these age groups that confirm previous findings in aging research. in the second experiment, we run icluster on a group of 30 patients with dementia and 30 age-matched healthy controls. the algorithm produced three modes that mainly corresponded to a sub-population of healthy controls, a sub-population of patients with dementia and a mixture group that contained both types. these results suggest that the algorithm can be used to discover sub-populations that correspond to interesting structural or functional "modes."
atlas-based auto-segmentation of head and neck ct images. treatment planning for high precision radiotherapy of head and neck (h&n) cancer patients requires accurate delineation of many structures and lymph node regions. manual contouring is tedious and suffers from large inter- and intra-rater variability. to reduce manual labor, we have developed a fully automated, atlas-based method for h&n ct image segmentation that employs a novel hierarchical atlas registration approach. this registration strategy makes use of object shape information in the atlas to help improve the registration efficiency and robustness while still being able to account for large inter-subject shape differences. validation results showed that our method provides accurate segmentation for many structures despite difficulties presented by real clinical data. comparison of two different atlas selection strategies is also reported.
fast motion tracking of tagged mri using angle-preserving meshless registration. fast tracking of motion is the key step towards tagged mri-based quantitative cardiac analysis. existing motion tracking approaches, including the widely used harp method, are either time consuming or qualitatively inconsistent, or both. we present in this paper a new fast motion tracking method based on a meshless kernel. for mr image sequences containing multiple image frames, tag intersections are automatically detected in all frames and indexed in the first frame. then a thin plate spline approach is used to establish a point-to-point correspondence between tag intersections in the initial and the current frame. lastly, we use a meshless registration kernel to generate a dense displacement map that minimizes the residual of sparse motion at intersections. to further improve the motion tracking, we develop a special technique to preserve tangential angles of tags at tag intersections. we tested our new method on both numerical phantoms and in vivo heart data. the motion tracking results are evaluated against the ground truth and manually drawn tags. clinical application potential is demonstrated by cardiac strain analysis based on the proposed methodology.
an active contour-based atlas registration model applied to automatic subthalamic nucleus targeting on mri: method and validation. this paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (stn) targeting in deep brain stimulation (dbs) surgery. in a previous work, we demonstrated that the stn position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. a stn targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. our simultaneous segmentation and registration model shows mean stn localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.
path planning and workspace determination for robot-assisted insertion of steerable electrode arrays for cochlear implant surgery. in previous works, the authors showed that using robot-assisted steerable electrode array insertions can significantly reduce the insertion forces compared to non-steerable electrode arrays. in addition to steering the electrode array, it is possible to change its angle of approach with respect to the scala tympani. this paper focuses on determining the relevance of changing the angle of approach of the electrode array by comparing steerable electrode array insertions using a two degrees-of-freedom (dof) robot versus a four dof robot. optimal insertion path planning strategies are presented for both two and four dof insertions. simulation results and experiments show that the four dof insertions can improve over two dof insertions. moreover, changing the angle of approach can further reduce the insertion forces. the simulation results also provide the workspace requirements for designing a custom parallel robot for robot-assisted cochlear implant surgery.
a theoretical comparison of different target registration error estimators. estimation of target registration error (tre), a common measure of the registration accuracy, is an important issue in computer assisted surgeries. within the last decade, several new approaches have been developed to estimate either the mean squared value of tre or the distribution of tre under different noise conditions. in this paper, we theoretically demonstrate that all the proposed algorithms converge to a general maximum likelihood (ml) solution. numerical simulations are performed to validate our derivations. using experimentally measured fiducial localization error, we provide an example of tre prediction in the presence of anisotropic noise.
needle insertion study using ultrasound-based 2d motion tracking. needle insertion simulators are in demand to train physicians for surgical procedures such as prostate brachytherapy. in order to design a needle insertion simulator, a needle-tissue interaction model is necessary. such a model can be identified using force and displacement data measured during the insertion of the needle. in this paper, an experiment is conducted in which a needle is inserted into a two-layered pvc phantom, while the needle position and insertion forces are measured and the tissue is imaged using a trans-rectal probe in the sagittal plane. a 2d block matching algorithm is used to estimate tissue deformation from the envelope of the recorded radio-frequency signals. this algorithm can be used to estimate the rotation and displacement of the prostate during prostate brachytherapy. the block matching method was validated in an independent experiment. with the measured force, needle position and tissue displacements, a finite element simulation was conducted to identify the parameters of a needle-tissue force distribution model and young's moduli of each part of the tissue phantom.
toward a flexible and portable ct scanner. the very hot and power-hungry x-ray filaments in today's computed tomography (ct) scanners constrain their design to be big and stationary. what if we built a ct scanner that could be deployed at the scene of a car accident to acquire tomographic images before moving the victim? recent developments in nanotechnology have shown that carbon nanotubes can produce x-rays at room temperature, and with relatively low power needs. we propose a design for a portable and flexible ct scanner made up of an addressable array of tiny x-ray emitters and detectors. in this paper, we outline a basic design, propose a strategy for reconstruction, and demonstrate the concept using a software simulation of the scanner. we also raise a number of issues that still need to be overcome to build such a scanner.
real-time liver motion compensation for mrgfus. mr-guided focused ultrasound (mrgfus) is a non-invasive method by which tissue is ablated using ultrasound energy focused on a point. the procedure has proven effective for stationary targets (e.g. uterine fibroids) but has not yet been used for liver lesion treatment due to organ motion. we describe a method to compensate for organ motion to enable continuous application of ultrasound energy in the presence of target movement in the liver. the method involves tracking several salient features (typically blood vessels) in the vicinity of the target location. the location of the target point(s) themselves are updated using a thin plate spline (tps) interpolation scheme. we demonstrate sub-pixel tracking accuracy on synthetic sequences and additionally show results on mri sequences acquired on human subjects. per-feature tracking times were measured to be 5.7ms with a standard deviation of 1.6ms, sufficient for real-time use.
fast, adaptive expectation-maximization alignment for cryo-em. cryo-em is a method for reconstructing 3d structure of proteins without crystallization. the expectation-maximization (em) algorithm is used in the alignment step of cryo-em reconstructions. the em step is often a serious computational bottleneck for 3d reconstructions. this paper proposes a computationally adaptive version of the em algorithm that speeds up the algorithm by a factor of 20 ¿ 30. experiments with noisy real-world data are included to show that the algorithm achieves this speedup without any significant loss of accuracy. such speed ups are significant, allowing the reconstruction to converge in cpu-days rather than cpu-months.
3d dendrite reconstruction and spine identification. in neuron-biology, 3d neuron dendrite reconstruction followed by spine identification is indispensable for the study of neuronal functions and biophysical properties. in this paper, we propose an automatic dendrite reconstruction method to with a surface representation of the neuron on the basis of a novel level set approach. our novel level set approach can effectively tackle the problem of segmentation under blurring and intensity in-homogeneity. then spines are detected based on dendrite medial axis and a label-based thinning strategy is proposed to accurately extract the dendrite skeleton for spine identification. experimental results reveal that our method works well.
real-time simulation of medical ultrasound from ct images. medical ultrasound interpretation requires a great deal of experience. real-time simulation of medical ultrasound provides a cost-effective tool for training and easy access to a variety of cases and exercises. however, fully synthetic and realistic simulation of ultrasound is complex and extremely time-consuming. in this paper, we present a novel method for simulation of ultrasound images from 3d ct scans by breaking down the computations into a preprocessing and a run-time phase. the preprocessing phase produces detailed fixed-view 3d scattering images and the run-time phase generates view-dependent ultrasonic artifacts for a given aperture geometry and position within a volume of interest. we develop a simple acoustic model of the ultrasound for the run-time phase, which produces realistic ultrasound images in real-time when combined with the previously computed scattering image.
using curve-fitting of curvilinear features for assessing registration of clinical neuropathology with in vivo mri. traditional neuropathological examination provides information about neurological disease or injury of a patient at a high-resolution level. correlating this type of post mortem diagnosis with in vivo image data of the same patient acquired by non-invasive tomographic scans greatly complements the interpretation of any disease or injury. we present the validation of a registration method for correlating macroscopic pathological images with mr images of the same patient. this also allows for 3-d mapping of the distribution of pathological changes throughout the brain. as the validation deals with datasets of widely differing sampling, we propose a method using smooth curvilinear anatomical features in the brain which allows interpolation between wide-spaced samples. curvilinear features are common anatomically, and if selected carefully have the potential to allow determination of the accuracy of co-registration across large areas of a volume of interest.
a nonrigid image registration framework for identification of tissue mechanical parameters. we present a modular framework for mechanically regularized nonrigid image registration of 3d ultrasound and for identification of tissue mechanical parameters. mechanically regularized deformation fields are computed from sparsely estimated local displacements. we enforce image-based local motion estimates by applying concentrated forces at mesh nodes of a mechanical finite-element model. the concentrated forces are generated by the elongation of regularization springs connected to the mesh nodes as their free ends are displaced according to local motion estimates. the regularization energy corresponding to the potential energy stored in the springs is minimized when the mechanical response of the model matches the observed response of the organ. we demonstrate that this technique is suitable for identification of material parameters of a nonlinear viscoelastic liver model and demonstrate its benefits over traditional indentation methods in terms of improved volumetric agreement between the model response and the experiment.
mr navigated breast surgery: method and initial clinical experience. 3d dynamic contrast enhanced magnetic resonance (mr) images may help to reduce the high re-excision rate associated with breast conserving surgery. however these images are acquired prone, whilst surgery is performed supine which results in a large deformation that limits their usefulness. we describe here a registration technique based on a biomechanical model to account for soft tissue deformation between prone mr imaging and surgery. the accuracies of the individual registration steps are assessed off-line. we then report our first clinical experience with an image-guided surgery system which incorporates these algorithms. the system's accuracy is assessed against tracked ultrasound images, and is determined to be around 5mm for this case.
evaluation of rigid and non-rigid motion compensation of cardiac perfusion mri. although the evaluation of cardiac perfusion using mri could be of crucial importance for the diagnosis of ischemic heart diseases, it is still not a routinely used technique. the major difficulty is that mr perfusion images are often corrupted by inconsistent myocardial motion. although motion compensation methods have been studied throughout the past decade, no clinically accepted solution has emerged. this is partly due to the lack of comprehensive validation. to address this deficit we collected a large multi-centre mr perfusion dataset and used this to characterize typical myocardial motion and confirmed that under clinically relevant conditions motion correction is a frequent requirement (67% of all 586 cases). we then developed a proposed solution which includes both rigid/affine and the non-rigid image registration. quantitative validation has been conducted using 6 different statistics to provide a comprehensive evaluation, showing the proposed techniques to be highly robust to different myocardial anatomy and motion patterns as well as to mr imaging acquisition parameters.
wall motion classification of stress echocardiography based on combined rest-and-stress data. in this paper, we represent a new framework that performs automated local wall motion analysis based on the combined information derived from a rest and stress sequence (a full stress echocardiography study). since cardiac data inherits time-varying and sequential properties, we introduce a hidden markov model (hmm) approach to classify stress echocardiography. a wall segment model is developed for a normal and an abnormal heart and experiments are performed on rest, stress and rest-and-stress sequences. in an assessment using n=44 datasets, combined rest-and-stress analysis shows an improvement in classification (84.17%) over individual rest (73.33%) and stress (68.33%).
automatic deformable diffusion tensor registration for fiber population analysis. in this work, we propose a novel method for deformable tensor---to---tensor registration of diffusion tensor images. our registration method models the distances in between the tensors with geode-sic---loxodromes and employs a version of multi-dimensional scaling (mds) algorithm to unfold the manifold described with this metric. defining the same shape properties as tensors, the vector images obtained through mds are fed into a multi---step vector---image registration scheme and the resulting deformation fields are used to reorient the tensor fields. results on brain dti indicate that the proposed method is very suitable for deformable fiber---to---fiber correspondence and dti---atlas construction.
robotic system for transapical aortic valve replacement with mri guidance. this paper reports our work on developing a robotic surgical system for transapical beating heart aortic valve replacement (avr) under interactive real-time magnetic resonance imaging (rtmri) guidance. our system integrates a real-time mri system, a compound mri robot, as well as an interface for the surgeon to plan the procedure and manipulate the robot. the compound robot consists of a positioning module and a valve delivery module. a 5-dof innomotion positioning arm provides and maintains direct access to the native aortic valve. a newly developed 3-dof robotic valve delivery module allows the surgeon to remotely control bioprosthetic valve delivery with mri guidance. preliminary evaluation of the parameters of the robotic system demonstrates it can provide sufficient capability to successfully assist the surgeon.
bidirectional segmentation of three-dimensional cardiac mr images using a subject-specific dynamical model. statistical model-based segmentation of the left ventricles has received considerable attention these years. while many statistical models have been shown to improve segmentation results, most of them either belong to (1) static models (sm) that neglect the temporal coherence of a cardiac sequence, or (2) generic dynamical models (gdm) that neglect the individual differences of cardiac motion. in this paper, we propose a subject-specific dynamical model (ssdm) that can simultaneously handle inter-subject variability and temporal cardiac dynamics (intra-subject variability). we also design a dynamic prediction algorithm that can progressively predict the shape of a new cardiac sequence at a given frame based on the shapes observed in earlier frames. furthermore, to reduce the accumulation of the segmentation errors throughout the entire sequence, we take into account the periodic nature of cardiac motion and perform bidirectional segmentation from a certain frame in a cardiac sequence. "leave-one-out" validation on 32 sequences show that our algorithm can capture local shape variations and suppress the propagation of segmentation errors.
a tensor-based morphometry study of genetic influences on brain structure using a new fluid registration method. we incorporated a new riemannian fluid registration algorithm into a general mri analysis method called tensor-based morphometry to map the heritability of brain morphology in mr images from 23 monozygotic and 23 dizygotic twin pairs. all 92 3d scans were fluidly registered to a common template. voxelwise jacobian determinants were computed from the deformation fields to assess local volumetric differences across subjects. heritability maps were computed from the intraclass correlations and their significance was assessed using voxelwise permutation tests. lobar volume heritability was also studied using the ace genetic model. the performance of this riemannian algorithm was compared to a more standard fluid registration algorithm: 3d maps from both registration techniques displayed similar heritability patterns throughout the brain. power improvements were quantified by comparing the cumulative distribution functions of the p-values generated from both competing methods. the riemannian algorithm outperformed the standard fluid registration.
assessment of reliability of multi-site neuroimaging via traveling phantom study. this paper describes a framework for quantitative analysis of neuroimaging data of traveling human phantoms used for cross-site validation. we focus on the analysis of magnetic resonance image data including intra- and inter-site comparison. locations and magnitude of geometric deformation is studied via unbiased atlas building and metrics on deformation fields. variability of tissue segmentation is analyzed by comparison of volumes, overlap of tissue maps, and a new kullback-leibler divergence on tissue probabilities, with emphasis on comparing probabilistic rather than binary segmentations. we show that results from this information theoretic measure are highly correlated with overlap. reproducibility of automatic, atlas-based segmentation of subcortical structures is examined by comparison of volumes, shape overlap and surface distances. variability among scanners of the same type but also differences to a different scanner type are discussed. the results demonstrate excellent reliability across multiple sites that can be achieved by the use of the today's scanner generation and powerful automatic analysis software. knowledge about such variability is crucial for study design and power analysis in new multi-site clinical studies.
entropy-optimized texture models. in order to robustly match a statistical model of shape and appearance (e.g. aam) to an unseen image, it is crucial to employ a robust model fittness measure. dense sampling of texture over the region covered by the shape of interest makes comparison of model and image in principle robust. however, when merely texture differences are taken into account, problems with low contrast regions, fuzzy features, global intensity variations, and irregularly varying structures occur.in this paper we introduce a novel entropy-optimized texture model (etm). we map gray values of training images such that pixels represent anatomical structures optimally in terms of information entropy. we match the etm to unseen images employing bayes' law.we validate our approach using four training sets (hearts in basal region, hearts in mid region, brain ventricles, and lumbar vertebrae) and conclude that etms perform better than aams. not only they reduce the average point-to-contour error, they are better suited to cope with large texture variances due to different scanners and even modalities.
preoperative surgery planning for percutaneous hepatic microwave ablation. a novel preoperative surgery planning method is proposed for percutaneous hepatic microwave ablation. an iterative framework for necrosis field simulation and 3d necrosis zone reconstruction is introduced here, and the necrosis model is further superimposed to patient anatomy structures using advanced gpu-accelerated visualization techniques. the full surgery planning is performed by the surgeon in an interactively way, until the optimal surgery plan is achieved. experiments have been performed on realistic patient with hepatic cancer and the actual necrosis zone are measured in postoperative ct images for patient. results show that this method is relative accurate for preoperative trajectory plan and could be used as an assistant to the clinical practice.
construction of a statistical surgical plan atlas for automated 3d planning of femoral component in total hip arthroplasty. the problem of automating preoperative planning of the femoral component (stem) for total hip arthroplasty (tha) is addressed. in our previous method, time-consuming trial-and-error processes were involved in parameter tuning of the objective function. this problem prevents application in different stem systems. to overcome this problem, a statistical surgical plan atlas (sspa) is constructed from training datasets of stem planning. the sspa represents the average and variance of the distance distribution on the stem surface to the femoral canal surface. that is, it encodes the distribution of the degree of contact preferred by the surgeon. automated planning is performed by minimizing the squared difference between distributions of the sspa and planning solution. the proposed method involves no parameter tuning to define the objective function that evaluates differences from the planning the surgeon prefers. experimental evaluations showed that the proposed method renders parameter tuning unnecessary while it still provides comparable accuracy to the previous method.
physically-based validation of deformable medical image registration. we propose a new approach for validating deformable image registration algorithms. since difference images do not necessarily reflect the 3d correspondence of organs, we propose to use the deformation fields generated in our fem-based simulations to assess the displacement resulted from other registration methods. unlike traditional fem-based registration methods, the boundary condition for the target organ is not given explicitly. instead it is driven by inter-organ contact forces generated by boundary conditions on surrounding organs to reduce the uncertainty induced by geometry-based surface matching. to validate our system, real ct images of the male pelvis are analyzed, and the prostate can be reasonably registered without matching its surface to the image. several registration methods are then evaluated using our system.
harmonic surface mapping with laplace-beltrami eigenmaps. in this paper we propose a novel approach for the mapping of 3d surfaces. with the reeb graph of laplace-beltrami eigenmaps, our method automatically detects stable landmark features intrinsic to the surface geometry and use them as boundary conditions to compute harmonic maps to the unit sphere. the resulting maps are diffeomorphic, robust to natural pose variations, and establish correspondences for geometric features shared across population. in the experiments, we demonstrate our method on three subcortical structures: the hippocampus, putamen, and caudate nucleus. a group study is also performed to generate a statistically significant map of local volume losses in the hippocampus of patients with secondary progressive multiple sclerosis.
effective incorporation of spatial information in a mutual information based 3d-2d registration of a ct volume to x-ray images. this paper addresses the problem of estimating the 3d rigid pose of a ct volume of an object from its 2d x-ray projections. we use maximization of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. however, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. in this paper, instead of directly maximizing mutual information, we propose to use a variational approximation derived from the kullback-leibler bound. spatial information is then incorporated into this variational approximation using a markov random field model. the newly derived similarity measure has a least-squares form and can be effectively minimized by a multi-resolution levenberg-marquardt optimizer. experimental results are presented on x-ray and ct datasets of a plastic phantom and a cadaveric spine segment.
reducing motion artifacts in 3-d breast ultrasound using non-linear registration. automated full-field 3-d breast ultrasound (3dbus) has a high potential as a reproducible method for screening and intervention. consecutive linear transducer scans yield a consistent breast ultrasound volume, yet individual slices are prone to tissue deformation and motion. to compensate resulting image distortions, we propose an efficient non-rigid registration method applied sequentially to pairs of 3dbus volume slices, optionally either on-line or in post-processing. a quantitative evaluation of the method on synthetic deformations shows subvoxel registration accuracy. first application to clinical breast us images and preliminary results confirmed effectiveness and accuracy of the method.
the zernike expansion - an example of a merit function for 2d/3d registration based on orthogonal functions. current merit functions for 2d/3d registration usually rely on comparing pixels or small regions of images using some sort of statistical measure. problems connected to this paradigm the sometimes problematic behaviour of the method if noise or artefacts (for instance a guide wire) are present on the projective image. we present a merit function for 2d/3d registration which utilizes the decomposition of the x-ray and the drr under comparison into orthogonal zernike moments; the quality of the match is assessed by an iterative comparison of expansion coefficients. results in a imaging study on a physical phantom show that --- compared to standard cross-correlation --- the zernike moment based merit function shows better robustness if histogram content in images under comparison is different, and that time expenses are comparable if the merit function is constructed out of a few significant moments only.
quantification of edematic effects in prostate brachytherapy interventions. we present a quantitative model to analyze the detrimental effects of edema on the quality of prostate brachytherapy implants. we account for both tissue expansion and implant migration by mapping intra-operative ultrasound and post-implant ct. we pre-process the ultrasound with a phase congruency filter, and map it to the volume ct using a b-spline deformable mutual information similarity metric. to test the method, we implanted a standard training phantom with 48 seeds, imaged the phantom with ultrasound and ct and registered the two for ground truth. edema was simulated by distorting the ct volume by known transformations. the objective was to match the distorted implant to the intra-operative ultrasound. performance was measured relative to ground truth. we successfully mapped 100% of deformed seeds to ground truth under edematic expansion up to 40% of volume growth. seed matching performance was 98% with random seed migration of 3mm superimposed on 10% edematic volume growth. this method promises to be clinically applicable as the first quantitative analysis tool to measure edematic implant deformations occurring between the operating room and post-operative ct imaging.
probabilistic anatomo-functional parcellation of the cortex: how many regions?. understanding brain structure and function entails the inclusion of anatomical and functional information in a common space, in order to study how these different informations relate to each other in a population of subjects. in this paper, we revisit the parcellation model and explicitly combine anatomical features, i.e. a segmentation of the cortex into gyri, with a functional information under the form of several cortical maps, which are used to further subdivide the gyri into functionally consistent regions. a probabilistic model is introduced, and the parcellation model is estimated using a variational bayes approach. the number of regions in the model is validated based on cross-validation. it is found that about 250 patches of cortex can be delineated both in the left and right hemisphere based on this procedure.
visualization tools for high angular resolution diffusion imaging. there is a major effort in medical imaging to develop algorithms to extract information from dti and hardi, which provide detailed information on brain integrity and connectivity. as the images have recently advanced to provide extraordinarily high angular resolution and spatial detail, including an entire manifold of information at each point in the 3d images, there has been no readily available means to view the results. this impedes developments in hardi research, which need some method to check the plausibility and validity of image processing operations on hardi data or to appreciate data features or invariants that might serve as a basis for new directions in image segmentation, registration, and statistics. we present a set of tools to provide interactive display of hardi data, including both a local rendering application and an off-screen renderer that works with a web-based viewer. visualizations are presented after registration and averaging of hardi data from 90 human subjects, revealing important details for which there would be no direct way to appreciate using conventional display of scalar images.
dynamic view expansion for enhanced navigation in natural orifice transluminal endoscopic surgery. natural orifice transluminal endoscopic surgery (notes) is an emerging surgical technique with increasing global interest. it has recently transcended the boundaries of clinical experiments towards initial clinical evaluation. although profound benefits to the patient have been demonstrated, notes requires highly skilled endoscopists for it to be performed safely and successfully. this predominantly reflects the skill required to navigate a flexible endoscope through a spatially complex environment. this paper presents a method to extend the visual field of the surgeon without compromising on the safety of the patient. the proposed dynamic view expansion uses a novel parallax correction scheme to provide enhanced visual cues that aid the navigation and orientation during notes surgery in periphery, while leaving the focal view undisturbed. the method was validated using a natural orifice simulated surgical environment and demonstrated on in vivo porcine data.
fast virtual stenting with deformable meshes: application to intracranial aneurysms. intracranial stents are medical devices that are becoming increasingly popular in the treatment of intracranial aneurysms. a methodology that predicts the released stent configuration prior to intervention has the potential to support the physician in the selection of the optimal approach for a specific patient. this paper proposes a fast virtual stenting technique based on constrained simplex deformable models that is able to virtually release stents in arbitrarily shaped vessel and aneurysm models. the technique effectively embeds the geometrical properties of the stent (cell design, strut size and shape and angles between struts) and achieves favorable execution times of the order of one minute.
software strategy for robotic transperineal prostate therapy in closed-bore mri. a software strategy to provide intuitive navigation for mri-guided robotic transperineal prostate therapy is presented. in the system, the robot control unit, the mri scanner, and open-source navigation software are connected to one another via ethernet to exchange commands, coordinates, and images. six states of the system called "workphases" are defined based on the clinical scenario to synchronize behaviors of all components. the wizard-style user interface allows easy following of the clinical workflow. on top of this framework, the software provides features for intuitive needle guidance: interactive target planning; 3d image visualization with current needle position; treatment monitoring through real-time mri. these features are supported by calibration of robot and image coordinates by the fiducial-based registration. the performance test shows that the registration error of the system was 2.6 mm in the prostate area, and it displayed real-time 2d image 1.7 s after the completion of image acquisition.
passive ventricular mechanics modelling using mri of structure and function. patients suffering from dilated cardiomyopathy or myocardial infarction can develop left ventricular (lv) diastolic impairment. the lv remodels its structure and function to adapt to pathophysiological changes in geometry and loading conditions and this remodeling process can alter the passive ventricular mechanics. in order to better understand passive ventricular mechanics, a lv finite element model was developed to incorporate physiological and mechanical information derived fromin vivo magnetic resonance imaging (mri) tissue tagging, in vivo lv cavity pressure recording and ex vivo diffusion tensor mri (dtmri) of a canine heart. mri tissue tagging enables quantitative evaluation of cardiac mechanical function with high spatial and temporal resolution, whilst the direction of maximum water diffusion (the primary eigenvector) in each voxel of a dtmri directly correlates with the myocardial fibre orientation. this model was customized to the geometry of the canine lv during diastasis by fitting the segmented epicardial and endocardial surface data from tagged mri using nonlinear finite element fitting techniques. myofibre orientations, extracted from dtmri of the same heart, were incorporated into this geometric model using a free form deformation methodology. pressure recordings, temporally synchronized to the tissue tagging mri data, were used to simulate the lv deformation during diastole. simulation of the diastolic lv mechanics allowed us to estimate the stiffness of the passive lv myocardium based on kinematic data obtained from tagged mri. this integrated physiological model will allow more insight into the regional passive diastolic mechanics of the lv on an individualized basis, thereby improving our understanding of the underlying structural basis of mechanical dysfunction in pathological conditions.
an incremental method for registering electroanatomic mapping data to surface mesh models of the left atrium. we present a method for registering position and orientation data collected from an electroanatomic mapping system (ems) to a surface mesh based on segmented computed tomography (ct) or magnetic resonance (mr) images of the left atrium. our algorithm is based on the unscented particle filter (upf) for stochastic state estimation. using an intracardiac echo (ice) ultrasound catheter with mounted mapping sensor, we acquire ultrasound images of the atrium from multiple configurations and iteratively determine the catheter's pose with respect to anatomy. after considering less than a minute's worth of ice data, the algorithm converges to an accurate pose estimate which, in turn, yields the registration parameters transforming ems coordinates to mesh coordinates. the iterative framework of the upf allows us to be robust to unmodeled ems noise and drift, problems which complicate traditional registration methods assuming regularity in image data structure.
gpu accelerated non-rigid registration for the evaluation of cardiac function. we present a method for the fast and efficient tracking of motion in cardiac magnetic resonance (cmr) cines. a gpu accelerated levenberg-marquardt non-linear least squares optimization procedure for finite element non-rigid registration was implemented on an nvidia graphics card using the opengl environment. points were tracked from frame to frame using forward and backward incremental registration. the inner (endocardial) and outer (epicardial) boarders of the heart were tracked in six short axis cines with ~25 frames through the cardiac cycle in 36 patients with vascular disease. contours placed by two independent expert observers using a semi-automatic ventricular analysis program (cim version 4.6) were used as the gold standard. the method took 0.5 seconds per frame, and the maximum hausdorff errors were less than 2 mm on average which was of the same order as the expert inter-observer error. in conclusion, gpu accelerated levenberg-marquardt non-linear optimization enables fast and accurate tracking of cardiac motion in cmr images.
the effect of automated marker detection on in vivo volumetric stent reconstruction. new drug eluting stents are less radiopaque than bare metal stents and therefore difficult to see with conventional x-ray coronary angiography. 2d stentboost and intravascular ultrasound (ivus) are routinely used to evaluate stent deployment and vessel apposition during a percutaneous coronary intervention. ivus images give cross-sectional information about the stent lumen and surrounding tissue. 2d stentboost is a boosted angiogram sequence and visualizes the geometry of the deployed stent from a fixed viewing direction. three-dimensional motion compensated volumetric stent reconstruction has been developed to give insight into the 3d geometry of the stent. markers on the balloon wire are used to motion compensate cardiac rotational angiography acquisitions. in this paper we present the effect of automated marker detection on in vivo volumetric cardiac stent reconstructions. automated or semi-automated marker detection reduces user interaction, potentially reduces total processing time, and increases detection results which leads to higher quality of stent reconstructions.
models of normal variation and local contrasts in hippocampal anatomy. we develop a model of continuous spherical shapes and use it to analyze the anatomy of the hippocampus. to account for the geometry of bends and folds, the model relies on a geodesic metric that is sensitive to first-order deformations. we construct an atlas of the hippocampus as a mean shape and develop statistical models to characterize quantitative and qualitative normal shape variation. we also develop a localization tool to identify local contrasts in the anatomy of different populations. the tool is applied to the detection, characterization and visualization of anatomical differences such as local enlargement and gains in volume on the right hippocampus of blind subjects.
a robot assisted hip fracture reduction with a navigation system. a fracture reduction robot is described as assisting in safe and precise fracture reduction. the robot is connected with pins that are inserted into the patient's bone fragments, together with a customized jig. the robot has six degrees of freedom with high precision, so that precise fracture reduction can be conducted. the failsafe unit of the fracture reduction robot can mitigate excessive reduction force that may cause complications such as avascular necrosis. we have integrated the fracture reduction robot with a navigation system that tracks the relative position of the bone fragments and generates the reduction path. the integrated system is evaluated with the simulated fracture reduction of a hip fracture model (n=8). three-dimensional parameters related to the mechanical axis-the proximal femur angle, the distal femur angle, and the length of the mechanical axis-were evaluated by comparing the normal values with those after reduction; these average differences are 1.76°, 0.28° and 0.76mm, respectively. the automated fracture reduction feature makes it possible for medical staff to work at a distance from radiation sources; for patients, the integrated fracture reduction system has the potential to reduce fractures with high precision.
mri compatibility of robot actuation techniques - a comparative study. this paper reports an experimental evaluation of the following three different mri-compatible actuators: a shinsei ultrasonic motor, a nanomotion ultrasonic motor and a pneumatic cylinder actuator. we report the results of a study comparing the effect of these actuators on the signal to noise ratio (snr) of mri images under a variety of experimental conditions. evaluation was performed with the controller inside and outside the scanner room and with both 1.5t and 3t mri scanners. pneumatic cylinders function with no loss of snr with controller both inside and outside of the scanner room. the nanomotion motor performs with moderate loss of snr when moving during imaging. the shinsei is unsuitable for motion during imaging. all may be used when motion is appropriately interleaved with imaging cycles.
gaze-contingent 3d control for focused energy ablation in robotic assisted surgery. the use of focused energy delivery in robotic assisted surgery for atrial fibrillation requires accurate prescription of ablation paths. in this paper, an original framework based on fusing human and machine vision for providing gaze-contigent control in robotic assisted surgery is provided. with the proposed method, binocular eye tracking is used to estimate the 3d fixations of the surgeon, which are further refined by considering the camera geometry and the consistency of image features at reprojected fixations. nonparametric clustering is then used to optimize the point distribution to provide an accurate ablation path. for experimental validation, a study where eight subjects prescribe an ablation path on the right atrium of the heart using only their gaze control is presented. the accuracy of the proposed method is validated using a phantom heart model with known 3d ground truth.
sparse approximation of currents for statistics on curves and surfaces. computing, processing, visualizing statistics on shapes like curves or surfaces is a real challenge with many applications ranging from medical image analysis to computational geometry. modelling such geometrical primitives with currents avoids feature-based approach as well as point-correspondence method. this framework has been proved to be powerful to register brain surfaces or to measure geometrical invariants. however, if the state-of-the-art methods perform efficiently pairwise registrations, new numerical schemes are required to process groupwise statistics due to an increasing complexity when the size of the database is growing. statistics such as mean and principal modes of a set of shapes often have a heavy and highly redundant representation. we propose therefore to find an adapted basis on which mean and principal modes have a sparse decomposition. besides the computational improvement, this sparse representation offers a way to visualize and interpret statistics on currents. experiments show the relevance of the approach on 34 sets of 70 sulcal lines and on 50 sets of 10 meshes of deep brain structures.
physical-space refraction-corrected transmission ultrasound computed tomography made computationally practical. transmission ultrasound computed tomography (ct) is strongly affected by the acoustic refraction properties of the imaged tissue, and proper modeling and correction of these effects is crucial to achieving high-quality image reconstructions. a method that can account for these refractive effects solves the governing eikonal equation within an iterative reconstruction framework, using a wave-front tracking approach. excellent results can be obtained, but at considerable computational expense. here, we report on the acceleration of three eikonal solvers (fast marching method (fmm), fast sweeping method (fsm), fast iterative method (fim)) on three computational platforms (commodity graphics hardware (gpus), multi-core and cluster cpus), within this refractive transmission ultrasound ct framework. our efforts provide insight into the capabilities of the various architectures for acoustic wave-front tracking, and they also yield a framework that meets the interactive demands of clinical practice, without a loss in reconstruction quality.
3d surface matching and registration through shape images. in this paper, we present a novel and efficient surface matching framework through shape image representation. this representation allows us to simplify a 3d surface matching problem to a 2d shape image matching problem. furthermore, we present a shape image diffusion-based method to find the most robust features to construct the matching and registration of surfaces. this is particularly important for inter-subject surfaces from medical scans of different subjects since these surfaces exhibit the inherited physiological variances among subjects. we conducted extensive experiments on real 3d human neocortical surfaces, which demonstrate the excellent performance of our approach in terms of accuracy and robustness.
volumetric ultrasound panorama based on 3d sift. the reconstruction of three-dimensional (3d) ultrasound panorama from multiple ultrasound volumes can provide a wide field of view for better clinical diagnosis. registration of ultrasound volumes has been a key issue for the success of this panoramic process. in this paper, we propose a method to register and stitch ultrasound volumes, which are scanned by dedicated ultrasound probe, based on an improved 3d scale invariant feature transform (sift) algorithm. we propose methods to exclude artifacts from ultrasound images in order to improve the overall performance in 3d feature point extraction and matching. our method has been validated on both phantom and clinical data sets of human liver. experimental results show the effectiveness and stability of our approach, and the precision of our method is comparable to that of the position tracker based registration.
precision radiotherapy for small animal research. preclinical research using well characterized small animal models has provided tremendous benefits to medical research, enabling low cost, large scale trials with high statistical significance of observed effects. the goal of the small animal radiation research platform (sarrp) is to make those models available for the development and evaluation of novel radiation therapies. sarrp demonstrates the capabilities of delivering high resolution, sub-millimeter, optimally planned conformal radiation with on-board cone-beam ct (cbct) guidance. the system requires accurate calibration of the x-ray beam for both imaging and radiation treatment. in this paper, we present a novel technique using an x-ray camera for calibration of the treatment beam. this technique does not require precise positioning or calibration of the x-ray camera.
3d dynamic roadmapping for abdominal catheterizations. despite rapid advances in interventional imaging, the navigation of a guide wire through abdominal vasculature remains, not only for novice radiologists, a difficult task. since this navigation is mostly based on 2d fluoroscopic image sequences from one view, the process is slowed down significantly due to missing depth information and patient motion. we propose a novel approach for 3d dynamic roadmapping in deformable regions by predicting the location of the guide wire tip in a 3d vessel model from the tip's 2d location, respiratory motion analysis, and view geometry. in a first step, the method compensates for the apparent respiratory motion in 2d space before backprojecting the 2d guide wire tip into three dimensional space, using a given projection matrix. to countervail the error connected to the projection parameters and the motion compensation, as well as the ambiguity caused by vessel deformation, we establish a statistical framework, which computes a reliable estimate of the guide wire tip location within the 3d vessel model. with this 2d-to-3d transfer, the navigation can be performed from arbitrary viewing angles, disconnected from the static perspective view of the fluoroscopic sequence. tests on a realistic breathing phantom and on synthetic data with a known ground truth clearly reveal the superiority of our approach compared to naïve methods for 3d roadmapping.the concepts and information presented in this paper are based on research and are not commercially available.
a maximal mass confinement principle for rigid and locally rigid image registration. in this paper we propose (1) to set the problem of image registration as a contour/region-template-to-image matching problem using so-called confiners --- also called blobs or components --- as template regions, (2) to select the confiners of one of the images by passing through the hierarchical structure which they define and registering them successively rigidly form coarse-to-fine to the other image, the target image, and (3) we propose a maximum mass confinement (mmc) principle for contour-to-image registration. this principle allows us to derive a similarity measure assessing how well the confiner fits into the target image simply by calculating the gray value mass confined by its contour. by optimizing this measure for rigid transformations we obtain our mmc algorithm registering a contour locally rigid to the target image. we illustrate that by proceeding based on (1-3) problems can be avoided which were related to previous registration algorithms based on confiners. we compare our mmc algorithm with another template matching algorithm based on normalized mutual information. equally, we compare our hierarchical image registration strategy with b-spline based non-rigid registration using normalized mutual information. we performed our evaluation on real and simulated images in terms of robustness, accuracy and computation speed. we show that both, mmc template matching on its own and hierarchical image registration using mmc, in most cases outperform the respective alternative method.
prostate brachytherapy seed localization with gaussian blurring and camera self-calibration. a tomosynthesis-based prostate brachytherapy seed localization method is described. gaussian-blurred images are computed from a limited number of x-ray images, and a 3-d volume is reconstructed by backprojection. candidate seed locations are extracted from the reconstructed volume and false positive seeds are removed by optimizing a local cost function. in case where the estimated pose error is large, a self-calibration process corrects the estimation error of the intrinsic camera parameters and the translation of the pose in order to improve the reconstruction. simulation and phantom experiment results imply that the implanted seed locations can be estimated from four or five images depending on the number of seeds. the algorithm was also validated using patient data, successfully localizing the implanted seeds.
bayesian analysis of fmri data with ica based spatial prior. spatial modeling is essential for fmri analysis due to relatively high noise in the data. earlier approaches have been primarily concerned with the spatial coherence of the bold response in local neighborhoods. in addition to a smoothness constraint, we propose to incorporate prior knowledge of brain activation patterns learned from training samples. this spatially informed prior can significantly enhance the estimation process by inducing sensitivity to task related regions of the brain. as fmri data exhibits intersubject variability in functional anatomy, we design the prior using independent component analysis (ica). due to the non-gaussian assumption, ica does not regress to the mean activation pattern and thus avoids suppressing intersubject differences. results from a real fmri experiment indicate that our approach provides statistically significant improvement in estimating activation compared to the standard general linear model (glm) based methods.
intraoperative navigation of an optically tracked surgical robot. this paper presents an adaptive control scheme for improving the performance of a surgical robot when it executes tasks autonomously. a commercial tracking system is used to correlate the robot with the preoperative plan as well as to correct the position of the robot when errors between the real and planned positions are detected. due to the noisy signals provided by the tracking system, a kalman filter is proposed to smooth the variations and to increase the stability of the system. the efficiency of the approach has been validated using rigid and flexible endoscopic tools, obtaining in both cases that the target points can be reached with an error less than 1mm. these results make the approach suitable for a range of abdominal procedures, such as autonomous repositioning of endoscopic tools or probes for percutaneous procedures.
location registration and recognition (lrr) for longitudinal evaluation of corresponding regions in ct volumes. the algorithm described in this paper takes (a) two temporally-separated ct scans, i 1 and i 2, and (b) a series of locations in i 1, and it produces, for each location, an affine transformation mapping the locations and their immediate neighborhood from i 1 to i 2. it does this without deformable registration by using a combination of feature extraction, indexing, refinement and decision processes. together these essentially "recognize" the neighborhoods. we show on lung ct scans that this works at near interactive speeds, and is at least as accurate as the diffeomorphic demons algorithm [1]. the algorithm may be used both for diagnosis and treatment monitoring.
long bone x-ray image stitching using camera augmented mobile c-arm. x-ray images are widely used during surgery for long bone fracture fixation. mobile c-arms provide x-ray images which are used to determine the quality of trauma reduction, i.e. the extremity length and mechanical axis of long bones. standard x-ray images have a narrow field of view and can not visualize the entire long bone on a single image. in this paper, we propose a novel method to generate panoramic x-ray images in real time by using the previously introduced camera augmented mobile c-arm [1]. this advanced mobile c-arm system acquires registered x-ray and optical images by construction, which facilitates the generation of panoramic x-ray images based on first stitching the optical images and then embedding the x-ray images. we additionally introduce a method to reduce the parallax effect that leads to the blurring and measurement error on panoramic x-ray images. visual marker tracking is employed to automatically stitch the sequence of video images and to rectify images. our proposed method is suitable for intra-operative usage generating panoramic x-ray images, which enable metric measurements, with less radiation and without requirement of fronto-parallel setup and overlapping x-ray images. the results show that the panoramic x-ray images generated by our method are accurate enough (errors less than 1%) for metric measurements and suitable for many clinical applications in trauma reduction.
robust brain registration using adaptive probabilistic atlas. elastic image registration is widely used to adapt brain images to a common template space, and, in complementary fashion, to adapt an anatomical template to a subject's anatomy. although hammer is a very accurate image-registration algorithm, it requires a 3-class segmentation step prior to registration, and its performance is affected by segmentation quality. we here propose a new framework to improve this algorithm's robustness to poor initial segmentation. our new framework is based on adaptive generalized expectation maximization (agem) for unified segmentation and registration, in which we use an adaptive strategy to incorporate spatial information from a probabilistic atlas to improve segmentation and registration simultaneously. our experiments using real mr brain images indicate that our integrated approach improves registration accuracy; we have also found that our iterative approach renders hammer robust to low tissue contrast, which hinders 3-class segmentation.
detecting informative frames from wireless capsule endoscopic video using color and texture features. despite emerging technology, wireless capsule endoscopy needs high amount of diagnosis-time due to the presence of many useless frames, created by turbid fluids, foods, and faecal materials. these materials and fluids present a wide range of colors and/or bubble-like texture patterns. we, therefore, propose a cascade method for informative frame detection, which uses local color histogram to isolate highly contaminated non-bubbled (hcn) frames, and gauss laguerre transform (glt) based multiresolution norm-1 energy feature to isolate significantly bubbled (sb) frames. supervised support vector machine is used to classify hcn frames (stage-1), while automatic bubble segmentation followed by threshold operation(stage-2) is adopted to detect informative frames by isolating sb frames. an experiment with 20,558 frames from the three videos shows 97.48 % average detection accuracy by the proposed method, when compared with methods adopting gabor based-(75.52%) and discrete wavelet based features (63.15%) with the same color feature.
joint lmmse estimation of dwi data for dti processing. we propose a new methodology for linear minimum mean square error (lmmse) filtering of diffusion weighted imaging (dwi). we consider each voxel as an n-dimensional vector that comprises all the dwi volumes, and then compute the lmmse estimator for the whole dwi data set jointly, taking into account the underlying tensor model. our experiments, both with phantom and real data, show that this is a more convenient approach compared to the separate processing of each dwi, that translates to better removal of noise and preservation of structural information. besides, our model has a simple algebraic formulation which makes the overall computational complexity very close to that of the scalar case, and it does not need multiple samples per dwi.
human vocal tract analysis by in vivo 3d mri during phonation: a complete system for imaging, quantitative modeling, and speech synthesis. we present a complete system for image-based 3d vocal tract analysis ranging from mr image acquisition during phonation, semi-automatic image processing, quantitative modeling including model-based speech synthesis, to quantitative model evaluation by comparison between recorded and synthesized phoneme sounds. for this purpose, six professionally trained speakers, age 22-34y, were examined using a standardized mri protocol (1.5 t, t1w flash, st 4mm, 23 slices, acq. time 21s). the volunteers performed a prolonged (¿21s) emission of sounds of the german phonemic inventory. simultaneous audio tape recording was obtained to control correct utterance. scans were made in axial, coronal, and sagittal planes each. computer-aided quantitative 3d evaluation included (i) automated registration of the phoneme-specific data acquired in different slice orientations, (ii) semi-automated segmentation of oropharyngeal structures, (iii) computation of a curvilinear vocal tract midline in 3d by nonlinear pca, (iv) computation of cross-sectional areas of the vocal tract perpendicular to this midline. for the vowels /a/,/e/,/i/,/o/,/ø/,/u/,/y/, the extracted area functions were used to synthesize phoneme sounds based on an articulatory-acoustic model. for quantitative analysis, recorded and synthesized phonemes were compared, where area functions extracted from 2d midsagittal slices were used as a reference. all vowels could be identified correctly based on the synthesized phoneme sounds. the comparison between synthesized and recorded vowel phonemes revealed that the quality of phoneme sound synthesis was improved for phonemes /a/, /o/, and /y/, if 3d instead of 2d data were used, as measured by the average relative frequency shift between recorded and synthesized vowel formants (p<0.05, one-sided wilcoxon rank sum test). in summary, the combination of fast mri followed by subsequent 3d segmentation and analysis is a novel approach to examine human phonation in vivo. it unveils functional anatomical findings that may be essential for realistic modelling of the human vocal tract during speech production.
comparison of epi distortion correction methods in diffusion tensor mri using a novel framework. diffusion weighted images (dwis) are commonly acquired with echo-planar imaging (epi). b0 inhomogeneities affect epi by producing spatially nonlinear image distortions. several strategies have been proposed to correct epi distortions including b0 field mapping (b0m) and image registration. in this study, an experimental framework is proposed to evaluation the performance of different epi distortion correction methods in improving dt-derived quantities. a deformable registration based method with mutual information metric and cubic b-spline modeled constrained deformation field (bsp) is proposed as an alternative when b0 mapping data are not available. bsp method is qualitatively and quantitatively compared to b0m method using the framework. both methods can successful reduce epi distortions and significantly improve the quality of dt-derived quantities. overall, b0m was clearly superior in infratentorial regions including brainstem and cerebellum, as well as in the ventral areas of the temporal lobes while bsp was better in all rostral brain regions.
semi-automatic reference standard construction for quantitative evaluation of lung ct registration. an algorithm is presented for the efficient semi-automatic construction of a detailed reference standard for registration in thoracic ct. a well-distributed set of 100 landmarks is detected fully automatically in one scan of a pair to be registered. using a custom-designed interface, observers locate corresponding anatomic locations in the second scan. the manual annotations are used to learn the relationship between the scans and after approximately twenty manual marks the remaining points are matched automatically. inter-observer differences demonstrate the accuracy of the matching and the applicability of the reference standard is demonstrated on two different sets of registration results over 19 ct scan pairs.
estimation of ground-glass opacity measurement in ct lung images. we propose to measure quantitatively the opacity property of each pixel in a ground-glass opacity tumor from ct images. our method results in an opacity map in which each pixel takes opacity value of $[0\textrm{-}1]$. given a ct image, our method accomplishes the estimation by constructing a graph laplacian matrix and solving a linear equations system, with assistance from some manually drawn scribbles for which the opacity values are easy to determine manually. our method resists noise and is capable of eliminating the negative influence of vessels and other lung parenchyma. experiments on 40 selected ct slices of 11 patients demonstrate the effectiveness of this technique. the opacity map produced by our method is invaluable in practice. from this map, many features can be extracted to describe the spatial distribution pattern of opacity and used in a computer-aided diagnosis system.
optimal acquisition schemes in high angular resolution diffusion weighted imaging. the recent challenge in diffusion imaging is to find acquisition schemes and analysis approaches that can represent non-gaussian diffusion profiles in a clinically feasible measurement time. in this work we investigate the effect of b-value and the number of gradient vector directions on q-ball imaging and the diffusion orientation transform (dot) in a structured way using computational simulations, hardware crossing-fiber diffusion phantoms, and in-vivo brain scans. we observe that dot is more robust to noise and independent of the b-value and number of gradients, whereas q-ball dramatically improves the results for higher b-values and number of gradients and at recovering larger angles of crossing. we also show that laplace-beltrami regularization has wide applicability and generally improves the properties of dot. knowledge of optimal acquisition schemes for hardi can improve the utility of diffusion weighted mr imaging in the clinical setting for the diagnosis of white matter diseases and presurgical planning.
identification of atherosclerotic lesion-prone sites through patient-specific simulation of low-density lipoprotein accumulation. we present a patient-specific model of low-density lipoprotein (ldl) transport from blood into arterial walls. to this end, the arterial endothelium is represented by a shear-stress dependent three-pore model taking into account blood plasma and ldl passage through the vesicular pathway, normal junctions and leaky junctions. we virtually remove atherosclerotic plaque from an in-vivo left coronary artery computed tomography (ct) dataset to obtain an approximation of the artery anatomy in its healthy state. by applying our model, we show that the location of the plaque in the diseased state corresponds to one of the two sites with predicted high ldl concentration in the healthy state. we further show that in the diseased state, the site with high ldl concentration has shifted distally, which is in agreement with the clinical observation that plaques generally grow in downstream direction.
deformable ultrasound registration without reconstruction. ultrasound (us) imaging is often proposed as an interoperative imaging modality. this use nearly always requires that the collected data be registered to preoperative data of another modality. existing intensity-based registration approaches all begin by reconstructing a 3d us volume from the collected 2d slices. we propose to directly register the set of 2d slices to the preoperative images. we argue this has a number of advantages, including the omission of the potentially complex reconstruction step, greater adaptability of the similarity measures, and easier parallelization. we describe a system for performing this task and present results on phantom data that show that our slice based method consistently outperforms a reconstruction based method in both speed and accuracy.
anatomy-preserving nonlinear registration of deep brain rois using confidence-based block-matching. brain atlases are commonly used in a number of applications such as mri segmentation and surgery targetting. our goal is to register a basal ganglia atlas to a subject using mr image registration. existing registration methods are for the most part either too constrained (linear registration) or can deform deep brain rois into implausible anatomical shapes.we developed a block-matching registration method suitable for atlas registration, using a new confidence-based regularization of the vector field. the method was used to register a set of 17 manually segmented mri onto one subject. results show that basal ganglia structures were better registered than when using an affine registration method.
spatiotemporal decomposition in object-space along reconstruction in emission tomography. emission tomography has provided a new insight in brain mechanisms past years. although reconstructions are nowadays mostly static, trend is going toward dynamic acquisitions and reconstructions. this opens a new range of investigations, for instance for drugs discovery. indeed new drugs are studied through the dynamic ability of tissues to catch them. however, it is required to know radiotracer concentration of blood that irrigates tissues in order to draw conclusions on potentials of these drugs. this concentration is called 'input function' and this paper presents a new method for measuring it in a non-invasive way.our new method relies on simultaneous estimations of vessels kinetics and vessels spatial distribution. these estimations are performed during the reconstruction process and take into account the statistical nature of measured signals. indeed, this method is based on the maximisation of the likelihood of counts in detectors. it takes advantages of a non-negative matrix factorisation which separate spatial and temporal components. results are very promising, since it estimates arterial input function accurately although object emits just a limited amount of photons, especially within the first minutes.
efficient computation of pdf-based characteristics from diffusion mr signal. we present a general method for the computation of pdf-based characteristics of the tissue micro-architecture in mr imaging. the approach relies on the approximation of the mr signal by a series expansion based on spherical harmonics and laguerre-gaussian functions, followed by a simple projection step that is efficiently done in a finite dimensional space. the resulting algorithm is generic, flexible and is able to compute a large set of useful characteristics of the local tissues structure. we illustrate the effectiveness of this approach by showing results on synthetic and real mr datasets acquired in a clinical time-frame.
computational pathology analysis of tissue microarrays predicts survival of renal clear cell carcinoma patients. renal cell carcinoma (rcc) can be diagnosed by histological tissue analysis where exact counts of cancerous cell nuclei are required. we propose a completely automated image analysis pipeline to predict the survival of rcc patients based on the analysis of immunohistochemical staining of mib-1 on tissue microarrays. a random forest classifier detects cell nuclei of cancerous cells and predicts their staining. the classifier training is achieved by expert annotations of 2300 nuclei gathered from tissues of 9 different rcc patients. the application to a test set of 133 patients clearly demonstrates that our computational pathology analysis matches the prognostic performance of expert pathologists.
constitutive modeling of human liver based on in vivo measurements. in vivo aspiration experiments on human livers are analyzed and material parameters for a non-linear-viscoelastic constitutive model are determined. a novel procedure is applied for the inverse analysis that accounts for the initial tissue deformation in the experiment and for the non-homogeneity of liver tissue. a numerical model is used consisting of a surface layer (capsule) and an underlying non-linear-viscoelastic solid (parenchyma). the capsule is modeled as hyperelastic membrane using data from measurements on bovine and human tissue. in a two step optimization procedure the set of constitutive model parameters for the "average" response of liver parenchyma is obtained. the proposed model is in line with literature values of high strain rate elastic modulus obtained from dynamic elastography. the model can be used to predict the nonlinear, time dependent behavior of human liver in computer simulations related to surgery training and planning.
exploring the use of proper orthogonal decomposition for enhancing blood flow images via computational fluid dynamics. obtaining high quality patient-specific flow velocity information is not an easy task. available clinical data are usually poorly resolved and contain a significant amount of noise. we propose a novel approach to integrate computational fluid dynamics with measurement data to overcome this difficulty. by performing a proper orthogonal decomposition of simulated blood flow patterns for a given vascular location with various anatomical configurations it is possible to obtain a basis model for flow reconstruction. this is used to interpolate imaging data intelligently without having to perform a full flow simulation for each individual patient. this work focuses on assessing the feasibility of such a method.
real-time nonlinear fem with neural network for simulating soft organ model deformation. this paper presents a new method for simulating the deformation of organ models by using a neural network. the proposed method is based on the idea proposed by chen et al. [2] that a deformed model can be estimated from the superposition of basic deformation modes. the neural network finds a relationship between external forces and the models deformed by the forces. the experimental results show that the trained network can achieve a real-time simulation while keeping the acceptable accuracy compared with the nonlinear fem computation.
impact of rician adapted non-local means filtering on hardi. in this paper we study the impact of denoising the raw high angular resolution diffusion imaging (hardi) data with the non-local means filter adapted to rician noise (nlmr). we first show that nlmr filtering improves robustness of apparent diffusion coefficient (adc) and orientation distribution function (odf) reconstructions from synthetic hardi datasets. our results suggest that the nlmr filtering improve the quality of anisotropy maps computed from adc and odf and improve the coherence of q-ball odfs with the underlying anatomy while not degrading angular resolution. these results are shown on a biological phantom with known ground truth and on a real human brain dataset. most importantly, we show that multiple measurements of diffusion-weighted (dw) images and averaging these images along each direction can be avoided because nlmr filtering of the individual dw images produces better quality generalized fractional anisotropy maps and more accurate odf fields than when computed from the averaged dw datasets.
detection of deformable objects in 3d images using markov-chain monte carlo and spherical harmonics. we address the problem of segmenting 3d microscopic volumetric intensity images of a collection of spatially correlated objects (such as fluorescently labeled nuclei in a tissue). this problem arises in the study of tissue morphogenesis where cells and cellular components are organized in accord with biological role and fate. we formulate the image model as stochastically generated based on biological priors and physics of image formation. we express the segmentation problem in terms of bayesian inference and use data-driven markov chain monte carlo to fit the image model to data. we perform an initial step in which the intensity volume is approximated as an expansion in 4d spherical harmonics, the coefficients of which capture the general organization of objects. since cell nuclei are membrane-bound their shapes are subject to membrane lipid bilayer bending energy, which we use to constrain individual contours. moreover, we parameterize the nuclear contours using spherical harmonic functions, which provide a shape description with no restriction to particular symmetries. we demonstrate the utility of our approach using synthetic and real fluorescence microscopy data.
patch-based markov models for event detection in fluorescence bioimaging. the study of protein dynamics is essential for understanding the multi-molecular complexes at subcellular levels. fluorescent protein (xfp)-tagging and time-lapse fluorescence microscopy enable to observe molecular dynamics and interactions in live cells, unraveling the live states of the matter. original image analysis methods are then required to process challenging 2d or 3d image sequences. recently, tracking methods that estimate the whole trajectories of moving objects have been successfully developed. in this paper, we address rather the detection of meaningful events in spatio-temporal fluorescence image sequences, such as apparent stable "stocking areas" involved in membrane transport. we propose an original patch-based markov modeling to detect spatial irregularities in fluorescence images with low false alarm rates. this approach has been developed for real image sequences of cells expressing xfp-tagged rab proteins, known to regulate membrane trafficking.
a local mutual information guided denoising technique and its application to self-calibrated partially parallel imaging. the application of partially parallel imaging (ppi) techniques to regular clinical magnetic resonance imaging (mri) studies has brought about the benefit of significantly faster acquisitions but at the cost of amplified and spatially variant noise, especially, for high parallel imaging acceleration rates. a local mutual information (lmi) weighted total variation (tv) based model is proposed to remove non-evenly distributed noise while preserving image sharpness. for self-calibrated ppi, such as generalized auto-calibration partially parallel acquisition (grappa) and modified sensitivity encoding (msense), a low spatial resolution high signal to noise ratio (snr) image is available besides the reconstructed high spatial resolution low snr image. the lmi between these two images is used to detect the noise distribution and the location of edges automatically, and is then applied as guidance for denoising. to better preserve sharpness, bregman iteration scheme is utilized to add the removed signal back to the denoised image. entropy of the residual map is used to automatically terminate iteration without using any information of the golden standard or real noise. results of the proposed algorithm on synthetic and in vivo mr images indicate that the proposed technique preserves image edges and suppresses noise well in the images reconstructed by grappa. the comparison with some existing techniques further confirms the advantages. this algorithm can be applied to enhance the clinical applicability of self-calibrated ppi. potentially, it can be extended to denoise general images with spatially variant noise.
rician noise removal by non-local means filtering for low signal-to-noise ratio mri: applications to dt-mri. diffusion-weighted mri (dw-mri) is subject to random noise yielding measures that are different from their real values, and thus biasing the subsequently estimated tensors. the non-local means (nlmeans) filter has recently been proposed to denoise mri with high signal-to-noise ratio (snr). this filter has been shown to allow the best restoration of image intensities for the estimation of diffusion tensors (dt) compared to state-of-the-art methods. however, for dw-mr images with high b-values (and thus low snr), the noise, which is strictly rician-distributed, can no longer be approximated as additive white gaussian, as implicitly assumed in the classical formulation of the nlmeans. high b-values are typically used in high angular resolution diffusion imaging (hardi) or q-space imaging (qsi), for which an optimal restoration is critical. in this paper, we propose to adapt the nlmeans filter to rician noise corrupted data. validation is performed on synthetic data and on real data for both conventional mr images and dt images. our adaptation outperforms the original nlmeans filter in terms of peak-signal-to-noise ratio (psnr) for dw-mri.
towards regional elastography of intracranial aneurysms. weak spots in the aneurysm could be identified estimating the regional stiffness of the wall. our approach consists in defining a parametric biomechanical model of the vessel which, given the patient's vascular morphology and the blood in- and outflow obtained from non-invasive imaging as well as parameters describing the local elasticity of the wall, enables the computation of the theoretical deformed wall position. the distance between this latter and the one obtained from the aneurysm pulsation is iteratively minimized in order to estimate the optimal set of stiffness parameters. in order to reduce the number of variables to estimate, the aneurysm morphology is clustered into a limited number of regions with uniform stiffness. a random noise perturbation (<5mm) is applied to the reference deformations and strains, showing that the robustness of the clustering decreases to 75% and errors of the stiffness estimates remain below 10% of the reference values.
gaze-contingent motor channelling and haptic constraints for minimally invasive robotic surgery. the use of master-slave surgical robots for minimally invasive surgery (mis) has created a physical separation between the surgeon and the patient. reconnecting the essential visuomotor sensory feedback is important for the safe practice of robotic assisted mis procedures. this paper introduces a novel gaze contingent framework with real-time haptic feedback by transforming visual sensory information into physical constraints that can interact with the motor sensory channel. we demonstrate how motor tracking of deforming tissue can be made more effective and accurate through the concept of gaze-contingent motor channelling. the method also uses 3d eye gaze to dynamically prescribe and update safety boundaries during robotic assisted mis without prior knowledge of the soft-tissue morphology. initial validation results on both simulated and robotic assisted phantom procedures demonstrate the potential clinical value of the technique.
registration of 4d time-series of cardiac images with multichannel diffeomorphic demons. in this paper, we propose a generic framework for inter-subject non-linear registration of 4d time-series images. in this framework, spatio-temporal registration is defined by mapping trajectories of physical points as opposed to spatial registration that solely aims at mapping homologous points. first, we determine the trajectories we want to register in each sequence using a motion tracking algorithm based on the diffeomorphic demons algorithm. then, we perform simultaneously pairwise registrations of corresponding time-points with the constraint to map the same physical points over time. we show this trajectory registration can be formulated as a multichannel registration of 3d images. we solve it using the diffeomorphic demons algorithm extended to vector-valued 3d images. this framework is applied to the inter-subject non-linear registration of 4d cardiac ct sequences.
tag separation in cardiac tagged mri. in this paper we introduce a tag separation method for better cardiac boundary segmentation and tag tracking. our approach is based on two observations in the cardiac tagged mr images: 1) the tag patterns have a regular texture; 2) the cardiac images without tag patterns are piecewise smooth with sparse gradients. these observations motivate us to use two dictionaries, one based on the discrete cosine transform for representing tag patterns and the other based on the wavelet transform for representing the underlying cardiac image without tag patterns. the two dictionaries are built such that they can lead to sparse representations of the tag patterns and of the piece-wise smooth regions without tag patterns. with the two dictionaries, a new tag separation approach is proposed to simultaneously optimize w.r.t. the two sparse representations, where optimization is directed by the total variation regularization scheme. while previous methods have focused on tag removal, our approach to acquiring both optimally-decomposed tag-only image and the cardiac image without tags simultaneously can be used for better tag tracking and cardiac boundary segmentation. we demonstrate the superior performance of the proposed approach through extensive experiments on large sets of cardiac tagged mr images.
automatic guidance of an ultrasound probe by visual servoing based on b-mode image moments. we propose a new visual servo approach to automatically control in real-time the full motion of a 2d ultrasound (us) probe held by a medical robot in order to reach a desired image of motionless soft tissue object in b-mode ultrasound imaging. combinations of image moments of the observed object cross-section are used as feedback information in the visual control scheme. these visual features are extracted in real-time from the us image thanks to a fast image segmentation method. simulations performed with a static us volume containing an egg-shaped object, and ex-vivo experiments using a robotized us probe that interacts with a motionless rabbit heart immersed in water, show the validity of this new approach and its robustness to different perturbations. this method shows promise for a variety of us-guided medical interventions that require real-time servoing.
efficient 3d tracking for motion compensation in beating heart surgery. the design of physiological motion compensation systems for robotic-assisted cardiac minimally invasive surgery (mis) is a challenging research topic. in this domain, vision-based techniques have proven to be a practical way to retrieve the motion of the beating heart. however due to the complexity of the heart motion and its surface characteristics, efficient tracking is still a complicated task. in this paper, we propose an algorithm for tracking the 3d motion of the beating heart, based on a thin-plate splines (tps) parametric model. the novelty of our approach lies in that no explicit matching between the stereo camera images is required and consequently no intermediate steps such as rectification are needed. experiments conducted on ex-vivo and in-vivo tissue show the effectiveness of the proposed algorithm for tracking surfaces undergoing complex deformations.
how does the camera assistant decide the zooming ratio of laparoscopic images? analysis and implementation. an important factor for defining a good image during laparoscopic surgery is the zooming ratio, which corresponds to the depth of insertion of the laparoscope along its longitudinal axis. however, it is not clear how surgeons (camera assistants) decide the zooming ratio of laparoscopic images during surgery. conventional automatic camera positioning systems define the zooming ratio "uniformly" based on simple heuristics. however, because the most adequate zooming ratio varies widely during surgery, these conventional systems may not offer the specific view that the surgeon wants. therefore, we first investigated how the camera assistant decides the zooming ratio of laparoscopic images by fully analyzing the positional relationship between the laparoscope and the surgical instrument during laparoscopic surgery. then, we extracted the zooming behavior and implemented it in the robotic laparoscope positioner that we previously developed. as a result, the zooming behavior of our robotic system became very similar to that of the human camera assistant. it was found that the proposed zooming motion of our robotic system may be suitable for fast and compact operations during surgery.
deformable mosaicing for whole-body mri. whole-body magnetic resonance imaging is an emerging application gaining vast clinical interest during the last years. although recent technological advances shortened the longish acquisition time, this is still the limiting factor avoiding its wide-spread clinical usage. the acquisition of images with large field-of-view helps to relieve this drawback, but leads to significantly distorted images. therefore, we propose a deformable mosaicing approach, based on the simultaneous registration to linear weighted averages, to correct for distortions in the overlapping area. this method produces good results on in-vivo data and has the advantage that a seamless integration into the clinical workflow is possible.
consensus-locally linear embedding (c-lle): application to prostate cancer detection on magnetic resonance spectroscopy. locally linear embedding (lle) is a widely used non-linear dimensionality reduction (nldr) method that projects multi-dimensional data into a low-dimensional embedding space while attempting to preserve object adjacencies from the original high-dimensional feature space. a limitation of lle, however, is the presence of free parameters, changing the values of which may dramatically change the low dimensional representations of the data. in this paper, we present a novel consensus-lle (c-lle) scheme which constructs a stable consensus embedding from across multiple low dimensional unstable lle data representations obtained by varying the parameter (&kappa;) controlling locally linearity. the approach is analogous to breiman's bagging algorithm for generating ensemble classifiers by combining multiple weak predictors into a single predictor. in this paper we demonstrate the utility of c-lle in creating a low dimensional stable representation of magnetic resonance spectroscopy (mrs) data for identifying prostate cancer. results of quantitative evaluation demonstrate that our c-lle scheme has higher cancer detection sensitivity (86.90%) and specificity (85.14%) compared to lle and other state of the art schemes currently employed for analysis of mrs data.
bayesian motion recovery framework for myocardial phase-contrast velocity mri. detailed assessment of myocardial motion provides a key indicator of ventricular function, enabling the early detection and assessment of a range of cardiac abnormalities. existing techniques for myocardial contractility analysis are complicated by a combination of factors including resolution, acquisition time, and consistency of quantification results. phase-contrast velocity mri is a technique that provides instantaneous, in vivo measurement of tissue velocity on a per-voxel basis. it allows for the direct derivation of contractile indices with minimal post-processing. for this method to be clinically useful, snr and image artifacts need to be addressed. the purpose of this paper is to present a maximum a posteriori (map) restoration technique for high quality myocardial motion recovery. it employs an accurate noise modeling scheme and a generalized gaussian markov random field prior tailored for the myocardial morphology. the quality of the proposed method is evaluated with both simulated myocardial velocity data with known ground truth and in vivo phase-contrast mr velocity acquisitions from a group of normal subjects.
autogate: fast and automatic doppler gate localization in b-mode echocardiogram. in this paper, we propose an algorithm for fast and automatic doppler gate localization in spectral doppler echocardiography using the b-mode image information. the algorithm has two components: 1) cardiac standard view classification and 2) gate location inference. for cardiac view classification, we incorporate the probabilistic boosting network (pbn) principle to local-structure-dependent object classification, which speeds up the processing time as it breaks down the computational dependency on the number of classes. the gate location is computed using a data-driven shape inference approach. clinical evaluation was performed by implementing the algorithm on an ultrasound system. experiment results show that the performance of the proposed algorithm is comparable to the doppler gate placement by an expert user. to the best of our knowledge, this is the first algorithm that provides a real time solution to the automated doppler gate placement in the clinical environment.
a variational level set approach to segmentation and bias correction of images with intensity inhomogeneity. this paper presents a variational level set approach to joint segmentation and bias correction of images with intensity inhomogeneity. our method is based on an observation that intensities in a relatively small local region are separable, despite of the inseparability of the intensities in the whole image caused by the intensity inhomogeneity. we first define a weighted k-means clustering objective function for image intensities in a neighborhood around each point, with the cluster centers having a multiplicative factor that estimates the bias within the neighborhood. the objective function is then integrated over the entire domain and incorporated into a variational level set formulation. the energy minimization is performed via a level set evolution process. our method is able to estimate bias of quite general profiles. moreover, it is robust to initialization, and therefore allows automatic applications. the proposed method has been used for images of various modalities with promising results.
human brain myelination from birth to 4.5 years. the myelination of white matter from birth through the first years of life has been studied qualitatively and it is well know the myelination occurs in a orderly and predictable manner, proceeding in a caudocranial direction, from deep to superficial and from posterior to anterior. even if the myelination is a continuous process, it is useful to characterize myelination evolution in normal brain development in order to better study demyelinating diseases. the quantification of myelination has only been studied for neonates. the original contribution of this study is to develop a method to characterize and visualize the myelination pattern using mri data from a group of normal subjects from birth to just over 4 years of age. the method includes brain extraction and tissue classification in addition to the analysis of t2 relaxation times to attempt to separate myelinated and unmyelinated white matter. the results agree previously published qualitative observations.
influence of organ motion and contrast enhancement on image registration. we present an exploration of the interplay between the extent of organ motion and contrast-enhancement on image registration success. a model of a dce mri of the liver incorporating an isotropic elastic non-rigid deformation is used to simulate both breathing and breath-hold data, a volume-preserving modification for tumour regions is included. contrast enhancement is simulated by applying a pharmacokinetic model. for each simulated dataset, a direct fluid registration of each image to the first in the dataset is compared to a contrast-enhancement guided method known as progressive principal component registration (ppcr). analysis of the correction to the deformation fields, tumour volume change and dispersion of joint image histograms are used to show the importance of motion type on ppcr success and of enhancement level on direct fluid registration success. for breathing motion, ppcr registers groups of images to separate locations, but maintains enhancing tumour volume. this is not the case for direct registration with volume changes of up to 7%. for inconsistent breath-hold depth, ppcr out-performs direct registration, particularly for large enhancement levels. analysis of the joint histograms suggests that the generation of target images using ppcr reduces dispersion due to contrast enhancement. since this distinction is not made using direct registration, it is unable to register images when large enhancement intensity changes are present.
localization of pelvic anatomical coordinate system using us/atlas registration for total hip replacement. in total hip replacement (thr) procedures, misalignment of the acetabular component can lead to dislocation and impingement. for the successful alignment of acetabular component, precise estimation of pelvic anatomical coordinate system is necessary. conventional navigation systems use ct scan or fluoroscopy, or involve implanted bone fiducials or invasive probing of bony landmarks to locate the anatomical coordinate. in this paper, an ultrasound-based approach is proposed that exploits prior knowledge about the anatomy of the pelvis in the form of a 3d surface atlas. tracked ultrasound images are utilized to extract sample points from the surface of the pelvis. a generic coordinate system in the specific patient is localized by registering these points to a statistical atlas of the pelvis in which a canonical anatomical coordinate system had been defined. this technique has been evaluated using simulation, dry bone, and cadaver experiments and was able to localize the anatomical coordinate system with the accuracy of about 1 degree.
adaptive discriminant wavelet packet transform and local binary patterns for meningioma subtype classification. the inherent complexity and non-homogeneity of texture makes classification in medical image analysis a challenging task. in this paper, we propose a combined approach for meningioma subtype classification using subband texture (macro) features and micro-texture features. these are captured using the adaptive wavelet packet transform (adwpt) and local binary patterns (lbps), respectively. these two different textural features are combined together and used for classification. the effect of various dimensionality reduction techniques on classification performance is also investigated. we show that high classification accuracies can be achieved using adwpt. although lbp features do not provide higher overall classification accuracies than adwpt, it manages to provide higher accuracy for a meningioma subtype that is difficult to classify otherwise.
cooperative robot assistant for retinal microsurgery. this paper describes the development and results of initial testing of a cooperative robot assistant for retinal microsurgery. in the cooperative control paradigm, the surgeon and the robot share control of a tool attached to the robot through a force sensor. the system senses forces exerted by the operator on the tool and uses this information in various control modes to provide smooth, tremor-free, precise positional control and force scaling. the robot manipulator is specifically designed with retinal microsurgery in mind, having high efficacy, flexibility and ergonomics while meeting the accuracy and safety requirements of microsurgery. we have tested this robot on a biological model and we report the results for reliably cannulating ~80 μm diameter veins (equivalent in size to human retinal veins). we also describe improvements to the robot and the experimental setup facilitating more advanced set of experiments.
modelling dynamic fronto-parietal behaviour during minimally invasive surgery - a markovian trip distribution approach. learning to perform minimally invasive surgery (mis) requires considerable attention, concentration and spatial ability. theoretically, this leads to activation in executive control (prefrontal) and visuospatial (parietal) centres of the brain. a novel approach is presented in this paper for analysing the flow of fronto-parietal haemodynamic behaviour and the associated variability between subjects. serially acquired functional near infrared spectroscopy (fnirs) data from fourteen laparoscopic novices at different stages of learning is projected into a low-dimensional `geospace', where sequentially acquired data is mapped to different locations. a trip distribution matrix based on consecutive directed trips between locations in the geospace reveals confluent fronto-parietal haemodynamic changes and a gravity model is applied to populate this matrix. to model global convergence in haemodynamic behaviour, a markov chain is constructed and by comparing sequential haemodynamic distributions to the markov's stationary distribution, inter-subject variability in learning an mis task can be identified.
belief propagation for depth cue fusion in minimally invasive surgery. in minimally invasive surgery, dense 3d surface reconstruction is important for surgical navigation and integrating pre- and intra-operative data. despite recent developments in 3d tissue deformation techniques, their general applicability is limited by specific constraints and underlying assumptions. the need for accurate and robust tissue deformation recovery has motivated research into fusing multiple visual cues for depth recovery. in this paper, a markov random field (mrf) based bayesian belief propagation framework has been proposed for the fusion of different depth cues. by using the underlying mrf structure to ensure spatial continuity in an image, the proposed method offers the possibility of inferring surface depth by fusing the posterior node probabilities in a node's markov blanket together with the monocular and stereo depth maps. detailed phantom validation and in vivo results are provided to demonstrate the accuracy, robustness, and practical value of the technique.
cohabitation and cooperation of chorus and macos. this paper describes experimental work on cohabitation and cooperation between a distributed operating system (chorus1) and an event driven operating system (macos2). our aims were to exploit the graphical and the musical capabilities of macintosh hardware and software directly from chorus applications, while minimizing our efforts in the field of device drivers and hardware interfaces. the work was carried out in four major stages. the first stage was to port the chorus kernel on the macintosh hardware. in the second stage we changed the way chorus managed the hardware in order to keep the macos system alive. conversely, we modified slightly the way chorus was booted so as to present it as an application to macos. this led us to the third stage, which was to share system events (e.g. hardware interrupts) between the two systems. the chorus system allows one to have multiple functions connected to an interrupt. this feature was used to connect both an internal chorus driver and a low level function to an interrupt. the low level function leads to the macos interrupt driver. the fourth stage is currently being carried out. it consists in the design and implementation of an interface permitting user level events (as system calls) to cross the borders of the two systems. this paper describes each stage and draws lessons about system software cohabitation and reusability.
from v to vanguard: the evolution of a distributed object-oriented microkernel interface. the vanguard operating system kernel was designed and implemented as a research testbed for distributed applications and higher-level operating system services. using the design of the v-system as a starting point, we developed an extensible set of operating system services, organized in an object type hierarchy. we also implemented a modular os (micro) kernel that implements these services. an important part of any microkernel design is its exported interface, as the design of this interface affects the ease with which programmers can develop higher-level operating system services on top of the kernel. in this paper we describe several notable features of the vanguard microkernel interfacein particular, its process and object model, its object identification scheme, and its use of group communication. we show how these features lead to a simple yet powerful interface that avoids the need to provide an excessive number of operations.
object-oriented transaction processing in the keykos microkernel. three major technological directions in computer technology are transaction processing, object orientation, and microkernel operating systems. the keykos operating system and the keytxf transaction processing system combine all three of these technologies. the design of keykos directly provides operating system level objects on a microkernel base. in order to maintain the integrity of these objects, keykos takes periodic checkpoints of the entire system. in addition, keykos provides facilities for transaction processing which achieve very high transaction rates. object oriented technology facilitates construction and reuse of transaction applications. this paper describes how these ideas are combined in the keykos system.
a flexible external paging interface. in this paper we describe an aspect of the spring virtual memory system that was influenced by the distributed object-oriented architecture of spring. the virtual memory system supports external pagers like those provided in the mach operating system, yet the architecture is more flexible and provides better caching opportunities than is possible in other systems. a novel aspect of the architecture is the separation of the memory abstraction from the interface that provides the paging operations. this separation provides considerable caching opportunities in our file system, and it facilitates our extensible stackable file system architecture. the virtual memory architecture described in this paper is implemented and has been in use for over three years as part of the experimental spring operating system.
kernel support for the wisconsin wind tunnel. this paper describes a kernel interface that provides an untrusted user-level process (an executive) with protected access to memory management functions, including the ability to create, manipulate, and execute within subservient contexts (address spaces). page motion callbacks not only give the executive limited control over physical memory management, but also shift certain responsibilities out of the kernel, greatly reducing kernel state and complexity. the executive interface was motivated by the requirements of the wisconsin wind tunnel (wwt), a system for evaluating cache-coherent shared-memory parallel architectures. wwt uses the executive interface to implement a fine-grain user-level extension of li's shared virtual memory on a thinking machines cm-5, a message-passing multicomputer. however, the interface is sufficiently general that an executive could act as a multiprogrammed operating system, exporting an alternative interface to the threads running in its subservient contexts. the executive interface is currently implemented as an extension to cmost, the standard operating system for the cm-5. in cmost, policy decisions are made on a central, distinct control processor (cp) and broadcast to the processing nodes (pns). the pns execute a minimal kernel sufficient only to implement the cp's policy. while this structure efficiently supports some parallel application models, the lack of autonomy on the pns restricts its generality. adding the executive interface provides limited autonomy to the pns, creating a structure that supports multiple models of application parallelism. this structure, with autonomy on top of centralization, is in stark contrast to most microkernel-based parallel operating systems in which the nodes are fundamentally autonomous.
user level ipc and device management in the raven kernel. the increasing bandwidth of networks and storage devices in recent years has placed greater emphasis on the performance of low level operating system services. data must be delivered between hardware devices and user applications in an efficient matter. motivated by the need for low overhead operating system services, the raven kernel utilizes user level implementation techniques to reduce kernel intervention for many common services. in particular, our user level send/receive/reply communication implementation generates no kernel interactions per iteration in the best case, and two kernel interactions in the worst case. in more general cases, we observe approximately one kernel interaction for every two send/receive/reply iterations. device driver support is also done entirely at the user level reducing copy costs and context switching.
fast interrupt priority management in operating system kernels. in this paper we describe a new, low-overhead technique for manipulating processor interrupt state in an operating system kernel. both uniprocessor and multiprocessor operating systems protect against uniprocessor deadlock and data corruption by selectively enabling and disabling interrupts during critical sections. this happens frequently during latency-critical activities such as ipc, scheduling, and memory management. unfortunately, the cycle cost of modifying the interrupt mask has increased by an order of magnitude in recent processor architectures. in this paper we describe optimistic interrupt protection, a technique which substantially reduces the cost of interrupt masking by optimizing mask manipulation for the common case of no interrupts. we present results for the mach 3.0 microkernel_operating_system,_although_the technique is applicable to other kernel architectures, both micro and monolithic, that rely on interrupts to manage devices.
design and implementation of an object-oriented 64-bit single address space microkernel. in the mid eighties, the system architecture research centre at city university developed a message-passing, unix compliant micro kernel (meshix) for our own scalable distributed memory architecture (topsy). over the last two years we have been engaged in a research programme aimed at learning from this experience, and developing a new operating system based on these lessons. the result is the angel microkernel. this paper sets out the lessons we have learnt from meshix, how this has influenced the design of angel and outlines our current design of angel and its c++ implementation. we will also describe our future plans and hopes for angel, and the lessons that we have learnt from the design and implementation process.
identifying cognates by phonetic and semantic similarity. i present a method of identifying cognates in the vocabularies of related languages. i show that a measure of phonetic similarity based on multivalued features performs better than "orthographic" measures, such as the longest common subsequence ratio (lcsr) or dice's coefficient. i introduce a procedure for estimating semantic similarity of glosses that employs keyword selection and wordnet. tests performed on vocabularies of four algonquian languages indicate that the method is capable of discovering on average nearly 75% percent of cognates at 50% precision.
chunking with support vector machines. we apply support vector machines (svms) to identify english base phrases (chunks). svms are known to achieve high generalization performance even with input data of high dimensional feature spaces. furthermore, by the kernel principle, svms can carry out training with smaller computational overhead independent of their dimensionality. we apply weighted voting of 8 svms-based systems trained with distinct chunk representations. experimental results show that our approach achieves higher accuracy than previous approaches.
a corpus-based account of regular polysemy: the case of context-sensitive adjectives. in this paper we investigate polysemous adjectives whose meaning varies depending on the nouns they modify (e.g., fast). we acquire the meanings of these adjectives from a large corpus and propose a probabilistic model which provides a ranking on the set of possible interpretations. we identify lexical semantic information automatically by exploiting the consistent correspondences between surface syntactic cues and lexical meaning. we evaluate our results against paraphrase judgments elicited experimentally from humans and show that the model's ranking of meanings correlates reliably with human intuitions: meanings that are found highly probable by the model are also rated as plausible by the subjects.
a finite-state approach to machine translation. the problem of machine translation can be viewed as consisting of two subproblems (a) lexical selection and (b) lexical reordering. we propose stochastic finite-state models for these two subproblems in this paper. stochastic finite-state models are efficiently learnable from data, effective for decoding and are associated with a calculus for composing models which allows for tight integration of constraints from various levels of language processing. we present a method for learning stochastic finite-state models for lexical choice and lexical reordering that are trained automatically from pairs of source and target utterances. we use this method to develop models for english-japanese translation and present the performance of these models for translation on speech and text. we also evaluate the efficacy of such a translation model in the context of a call routing task of unconstrained speech utterances.
learning optimal dialogue management rules by using reinforcement learning and inductive logic programming. developing dialogue systems is a complex process. in particular, designing efficient dialogue management strategies is often difficult as there are no precise guidelines to develop them and no sure test to validate them. several suggestions have been made recently to use reinforcement learning to search for the optimal management strategy for specific dialogue situations. these approaches have produced interesting results, including applications involving real world dialogue systems. however, reinforcement learning suffers from the fact that it is state based. in other words, the optimal strategy is expressed as a decision table specifying which action to take in each specific state. it is therefore difficult to see whether there is any generality across states. this limits the analysis of the optimal strategy and its potential for re-use in other dialogue situations. in this paper we tackle this problem by learning rules that generalize the state-based strategy. these rules are more readable than the underlying strategy and therefore easier to explain and re-use. we also investigate the capability of these rules in directing the search for the optimal strategy by looking for generalization whilst the search proceeds.
identifying user corrections automatically in spoken dialogue systems. we present results of machine learning experiments designed to identify user corrections of speech recognition errors in a corpus collected from a train information spoken dialogue system. we investigate the predictive power of features automatically computable from the prosody of the turn, the speech recognition process, experimental conditions, and the dialogue history. our best performing features reduce classification error from baselines of 25.70-28.99% to 15.72%.
unsupervised learning of name structure from coreference data. we present two methods for learning the structure of personal names from unlabeled data. the first simply uses a few implicit constraints governing this structure to gain a toehold on the problem --- e.g., descriptors come before first names, which come before middle names, etc. the second model also uses possible coreference information. we found that coreference constraints on names improve the performance of the model from 92.6% to 97.0%. we are interested in this problem in its own right, but also as a possible way to improve named entity recognition (by recognizing the structure of different kinds of names) and as a way to improve noun-phrase coreference determination.
edit detection and parsing for transcribed speech. we present a simple architecture for parsing transcribed speech in which an edited-word detector first removes such words from the sentence string, and then a standard statistical parser trained on transcribed speech parses the remaining words. the edit detector achieves a misclassification rate on edited words of 2.2%. (the null-model, which marks everything as not edited, has an error rate of 5.9%.) to evaluate our parsing results we introduce a new evaluation metric, the purpose of which is to make evaluation of a parse tree relatively indifferent to the exact tree position of edited nodes. by this metric the parser achieves 85.3% precision and 86.5% recall.
multipath translation lexicon induction via bridge languages. this paper presents a method for inducing translation lexicons based on transduction models of cognate pairs via bridge languages. bilingual lexicons within languages families are induced using probabilistic string edit distance models. translation lexicons for arbitrary distant language pairs are then generated by a combination of these intra-family translation models and one or more cross-family on-line dictionaries. up to 95% exact match accuracy is achieved on the target vocabulary (30-68% of inter-family test pairs). thus substantial portions of translation lexicons can be generated accurately for languages where no bilingual dictionary or parallel corpora may exist.
corpus-based np modifier generation. this paper describes how we annotated and analysed the np modifiers in a corpus of museum descriptions to discover rules for the selection and realisation of such modifiers, in particular non-referring ones. we implemented the regularities into an extension of the ilex system to generate complex nps capable of serving multiple communicative goals.
class-based probability estimation using a semantic hierarchy. this paper concerns the acquisition of a particular kind of lexical knowledge, namely the knowledge of which noun senses can fill argument slots of predicates. probabilities are used to represent the knowledge, and classes from a semantic hierarchy are used to estimate the probabilities. there is a particular focus on the problem of how to determine a suitable class, or level of generalisation, in the hierarchy. a pseudo disambiguation task is used to compare different class-based estimation methods.
information-based machine translation. this paper describes an approach to machine translation that places linguistic information at its foundation. the difficulty of translation from english to japanese is illustrated with data that shows the influence of various linguistic contextual factors. next, a method for natural language transfer is presented that integrates translation examples (represented as typed feature structures with source-target indices) with linguistic rules and constraints. the method has been implemented, and the results of an evaluation are presented.
transformation based learning in the fast lane. transformation-based learning has been successfully employed to solve many natural language processing problems. it achieves state-of-the-art performance on many natural language processing tasks and does not overtrain easily. however, it does have a serious drawback: the training time is often intorelably long, especially on the large corpora which are often used in nlp. in this paper, we present a novel and realistic method for speeding up the training time of a transformation-based learner without sacrificing performance. the paper compares and contrasts the training time needed and performance achieved by our modified learner with two other systems: a standard transformation-based learner, and the ica system (hepple, 2000). the results of these experiments show that our system is able to achieve a significant improvement in training time while still achieving the same performance as a standard transformation-based learner. this is a valuable contribution to systems and algorithms which utilize transformation-based learning at any part of the execution.
an algorithm for aspects of semantic interpretation using an enhanced wordnet. an algorithm for semantic interpretation is explained. the algorithm is based on predicates defined for wordnet verb classes. the algorithm is driven by the definition of these predicates whose thematic roles are linked to the wordnet ontology for nouns and to the syntactic relations that realize them. the algorithm has been tested in the identification of the meaning of the verb, thematic roles, and temporal and spatial adjuncts.
generating training data for medical dictations. in automatic speech recognition (asr) enabled applications for medical dictations, corpora of literal transcriptions of speech are critical for training both speaker independent and speaker adapted acoustic models. obtaining these transcriptions is both costly and time consuming. non-literal transcriptions, on the other hand, are easy to obtain because they are generated in the normal course of a medical transcription operation. this paper presents a method of automatically generating texts that can take the place of literal transcriptions for training acoustic and language models. atrs is an automatic transcription reconstruction system that can produce near-literal transcriptions with almost no human labor. we will show that (i) adapted acoustic models trained on atrs data perform as well as or better than adapted acoustic models trained on literal transcriptions (as measured by recognition accuracy) and (ii) language models trained on atrs data have lower perplexity than language models trained on non-literal data.
why inverse document frequency? inverse document frequency (idf) is a popular measure of a word's importance. the idf invariably appears in a host of heuristic measures used in information retrieval. however, so far the idf has itself been a heuristic. in this paper, we show idf to be optimal in a principled sense. we show that idf is the optimal weight of a word with respect to minimization of a kullback-leibler distance suitably generalized to nonnegative functions which need not be probability distributions. this optimization problem is closely related to maximum entropy problem. we show that the idf is the optimal weight associated with a word-feature in an information retrieval setting where we treat each document as the query that retrieves itself. that is, idf is optimal for document self-retrieval.
a decision tree of bigrams is an accurate predictor of word sense. this paper presents a corpus-based approach to word sense disambiguation where a decision tree assigns a sense to an ambiguous word based on the bigrams that occur nearby. this approach is evaluated using the sense-tagged corpora from the 1998 senseval word sense disambiguation exercise. it is more accurate than the average results reported for 30 of 36 words, and is more accurate than the best results for 19 of 36 words.
a probabilistic earley parser as a psycholinguistic model. in human sentence processing, cognitive load can be defined many ways. this report considers a definition of cognitive load in terms of the total probability of structural options that have been disconfirmed at some point in a sentence: the surprisal of word wi given its prefix wo...i-1 on a phrase-structural language model. these loads can be efficiently calculated using a probabilistic earley parser (stolcke, 1995) which is interpreted as generating predictions about reading time on a word-by-word basis. under grammatical assumptions supported by corpus-frequency data, the operation of stolcke's probabilistic earley parser correctly predicts processing phenomena associated with garden path structural ambiguity and with the subject/object relative asymmetry.
text and knowledge mining for coreference resolution. traditionally coreference is resolved by satisfying a combination of salience, syntactic, semantic and discourse constraints. the acquisition of such knowledge is time-consuming, difficult and error-prone. therefore, we present a knowledge minimalist methodology of mining coreference rules from annotated text corpora. semantic consistency evidence, which is a form of knowledge required by coreference, is easily retrieved from wordnet. additional consistency knowledge is discovered by a meta-bootstrapping algorithm applied to unlabeled texts.
re-engineering letter-to-sound rules. using finite-state automata for the text analysis component in a text-to-speech system is problematic in several respects: the rewrite rules from which the automata are compiled are difficult to write and maintain, and the resulting automata can become very large and therefore inefficient. converting the knowledge represented explicitly in rewrite rules into a more efficient format is difficult. we take an indirect route, learning an efficient decision tree representation from data and tapping information contained in existing rewrite rules, which increases performance compared to learning exclusively from a pronunciation lexicon.
do cfg-based language models need agreement constraints? many people are now routinely building grammar-based language models for interactive spoken language applications; these language models are typically ad hoc semantic grammars which ignore many standard linguistic constraints, in particular grammatical agreement. we describe a series of experiments in which we took three cfg-based language models from non-trivial implemented systems, and in each case contrasted the performance of a version which included agreement constraints against a version which ignored them. our findings suggest that inclusion of agreement constraints significantly improves performance in terms of both word error rate and semantic error rate.
applying co-training methods to statistical parsing. we propose a novel co-training method for statistical parsing. the algorithm takes as input a small corpus (9695 sentences) annotated with parse trees, a dictionary of possible lexicalized structures for each word in the training set and a large pool of unlabeled text. the algorithm iteratively labels the entire data set with parse trees. using empirical results based on parsing the wall street journal corpus we show that training a statistical parser on the combined labeled and unlabeled data strongly out-performs training only on the labeled data.
knowledge-free induction of inflectional morphologies. we propose an algorithm to automatically induce the morphology of inflectional languages using only text corpora and no human input. our algorithm combines cues from orthography, semantics, and syntactic distributions to induce morphological relationships in german, dutch, and english. using celex as a gold standard for evaluation, we show our algorithm to be an improvement over any knowledge-free algorithm yet proposed.
tree-cut and a lexicon based on systematic polysemy. this paper describes a lexicon organized around systematic polysemy: a set of word senses that are related in systematic and predictable ways. the lexicon is derived by a fully automatic extraction method which utilizes a clustering technique called tree-cut. we compare our lexicon to wordnet cousins, and the inter-annotator disagreement observed between wordnet semcor and dso corpora.
a structured language model based on context-sensitive probabilistic left-corner parsing. recent contributions to statistical language modeling for speech recognition have shown that probabilistically parsing a partial word sequence aids the prediction of the next word, leading to "structured" language models that have the potential to outperform n-grams. existing approaches to structured language modeling construct nodes in the partial parse tree after all of the underlying words have been predicted. this paper presents a different approach, based on probabilistic left-corner grammar (plcg) parsing, that extends a partial parse both from the bottom up and from the top down, leading to a more focused and more accurate, though somewhat less robust, search of the parse space. at the core of our new structured language model is a fast context-sensitive and lexicalized plcg parsing algorithm that uses dynamic programming. preliminary perplexity and word-accuracy results appear to be competitive with previous ones, while speed is increased.
instance-based natural language generation. this paper presents a bottom-up generator that makes use of information retrieval techniques to rank potential generation candidates by comparing them to a data base of stored instances. we introduce two general techniques to address the search problem, expectation-driven search and dynamic grammar rule selection, and present the architecture of an implemented generation system called igen. our approach uses a domain-specific generation grammar that is automatically derived from a semantically tagged treebank. we then evaluate the efficiency of our system.
spot: a trainable sentence planner. sentence planning is a set of inter-related but distinct tasks, one of which is sentence scoping, i.e. the choice of syntactic structure for elementary speech acts and the decision of how to combine them into one or more sentences. in this paper, we present spot, a sentence planner, and a new methodology for automatically training spot on the basis of feedback provided by human judges. we reconceptualize the task into two distinct phases. first, a very simple, randomized sentence-plan-generator (spg) generates a potentially large list of possible sentence plans for a given text-plan input. second, the sentence-plan-ranker (spr) ranks the list of output sentence plans, and then selects the top-ranked plan. the spr uses ranking rules automatically learned from training data. we show that the trained spr learns to select a sentence plan whose rating on average is only 5% worse than the top human-ranked sentence plan.
inducing multilingual pos taggers and np bracketers via robust projection across aligned corpora. this paper investigates the potential for projecting linguistic annotations including part-of-speech tags and base noun phrase bracketings from one language to another via automatically word-aligned parallel corpora. first, experiments assess the accuracy of unmodified direct transfer of tags and brackets from the source language english to the target languages french and chinese, both for noisy machine-aligned sentences and for clean hand-aligned sentences. performance is then substantially boosted over both of these baselines by using training techniques optimized for very noisy data, yielding 94-96% core french part-of-speech tag accuracy and 90% french bracketing f-measure for stand-alone monolingual tools trained without the need for any human-annotated data in the given language.
a comparative study on language model adaptation techniques using new evaluation metrics. this paper presents comparative experimental results on four techniques of language model adaptation, including a maximum a posteriori (map) method and three discriminative training methods, the boosting algorithm, the average perceptron and the minimum sample risk method, on the task of japanese kana-kanji conversion. we evaluate these techniques beyond simply using the character error rate (cer): the cer results are interpreted using a metric of domain similarity between background and adaptation domains, and are further evaluated by correlating them with a novel metric for measuring the side effects of adapted models. using these metrics, we show that the discriminative methods are superior to a map-based method not only in terms of achieving larger cer reduction, but also of being more robust against the similarity of background and adaptation domains, and achieve larger cer reduction with fewer side effects.
using sketches to estimate associations. we should not have to look at the entire corpus (e.g., the web) to know if two words are associated or not. a powerful sampling technique called sketches was originally introduced to remove duplicate web pages. we generalize sketches to estimate contingency tables and associations, using a maximum likelihood estimator to find the most likely contingency table given the sample, the margins (document frequencies) and the size of the collection. not unsurprisingly, computational work and statistical accuracy (variance or errors) depend on sampling rate, as will be shown both theoretically and empirically. sampling methods become more and more important with larger and larger collections. at web scale, sampling rates as low as 10-4 may suffice.
a semi-supervised feature clustering algorithm with application to word sense disambiguation. in this paper we investigate an application of feature clustering for word sense disambiguation, and propose a semisupervised feature clustering algorithm. compared with other feature clustering methods (ex. supervised feature clustering), it can infer the distribution of class labels over (unseen) features unavailable in training data (labeled data) by the use of the distribution of class labels over (seen) features available in training data. thus, it can deal with both seen and unseen features in feature clustering process. our experimental results show that feature clustering can aggressively reduce the dimensionality of feature space, while still maintaining state of the art sense disambiguation accuracy. furthermore, when combined with a semi-supervised wsd algorithm, semi-supervised feature clustering outperforms other dimensionality reduction techniques, which indicates that using unlabeled data in learning process helps to improve the performance of feature clustering and sense disambiguation.
learning what to talk about in descriptive games. text generation requires a planning module to select an object of discourse and its properties. this is specially hard in descriptive games, where a computer agent tries to describe some aspects of a game world. we propose to formalize this problem as a markov decision process, in which an optimal message policy can be defined and learned through simulation. furthermore, we propose back-off policies as a novel and effective technique to fight state dimensionality explosion in this framework.
mining key phrase translations from web corpora. key phrases are usually among the most information-bearing linguistic structures. translating them correctly will improve many natural language processing applications. we propose a new framework to mine key phrase translations from web corpora. we submit a source phrase to a search engine as a query, then expand queries by adding the translations of topic-relevant hint words from the returned snippets. we retrieve mixed-language web pages based on the expanded queries. finally, we extract the key phrase translation from the second-round returned web page snippets with phonetic, semantic and frequency-distance features. we achieve 46% phrase translation accuracy when using top 10 returned snippets, and 80% accuracy with 165 snippets. both results are significantly better than several existing methods.
blanc: learning evaluation metrics for mt. we introduce blanc, a family of dynamic, trainable evaluation metrics for machine translation. flexible, parametrized models can be learned from past data and automatically optimized to correlate well with human judgments for different criteria (e.g. adequacy, fluency) using different correlation measures. towards this end, we discuss acs (all common skip-ngrams), a practical algorithm with trainable parameters that estimates reference-candidate translation overlap by computing a weighted sum of all common skip-ngrams in polynomial time. we show that the bleu and rouge metric families are special cases of blanc, and we compare correlations with human judgments across these three metric families. we analyze the algorithmic complexity of acs and argue that it is more powerful in modeling both local meaning and sentence-level structure, while offering the same practicality as the established algorithms it generalizes.
speeding up training with tree kernels for node relation labeling. we present a method for speeding up the calculation of tree kernels during training. the calculation of tree kernels is still heavy even with efficient dynamic programming (dp) procedures. our method maps trees into a small feature space where the inner product, which can be calculated much faster, yields the same value as the tree kernel for most tree pairs. the training is sped up by using the dp procedure only for the exceptional pairs. we describe an algorithm that detects such exceptional pairs and converts trees into vectors in a feature space. we propose tree kernels on marked labeled ordered trees and show that the training of svms for semantic role labeling using these kernels can be sped up by a factor of several tens.
training neural network language models on very large corpora. during the last years there has been growing interest in using neural networks for language modeling. in contrast to the well known back-off n-gram language models, the neural network approach attempts to overcome the data sparseness problem by performing the estimation in a continuous space. this type of language model was mostly used for tasks for which only a very limited amount of in-domain training data is available.in this paper we present new algorithms to train a neural network language model on very large text corpora. this makes possible the use of the approach in domains where several hundreds of millions words of texts are available. the neural network language model is evaluated in a state-of-the-art real-time continuous speech recognizer for french broadcast news. word error reductions of 0.5% absolute are reported using only a very limited amount of additional processing time.
collective content selection for concept-to-text generation. a content selection component determines which information should be conveyed in the output of a natural language generation system. we present an efficient method for automatically learning content selection rules from a corpus and its related database. our modeling framework treats content selection as a collective classification problem, thus allowing us to capture contextual dependencies between input items. experiments in a sports domain demonstrate that this approach achieves a substantial improvement over context-agnostic methods.
on coreference resolution performance metrics. the paper proposes a constrained entity-alignment f-measure (ceaf) for evaluating coreference resolution. the metric is computed by aligning reference and system entities (or coreference chains) with the constraint that a system (reference) entity is aligned with at most one reference (system) entity. we show that the best alignment is a maximum bipartite matching problem which can be solved by the kuhn-munkres algorithm. comparative experiments are conducted to show that the widely-known muc f-measure has serious flaws in evaluating a coreference system. the proposed metric is also compared with the ace-value, the official evaluation metric in the automatic content extraction (ace) task, and we conclude that the proposed metric possesses some properties such as symmetry and better interpretability missing in the ace-value.
domain-specific sense distributions and predominant sense acquisition. distributions of the senses of words are often highly skewed. this fact is exploited by word sense disambiguation (wsd) systems which back off to the predominant sense of a word when contextual clues are not strong enough. the domain of a document has a strong influence on the sense distribution of words, but it is not feasible to produce large manually annotated corpora for every domain of interest. in this paper we describe the construction of three sense annotated corpora in different domains for a sample of english words. we apply an existing method for acquiring predominant sense information automatically from raw text, and for our sample demonstrate that (1) acquiring such information automatically from a mixed-domain corpus is more accurate than deriving it from semcor, and (2) acquiring it automatically from text in the same domain as the target domain performs best by a large margin. we also show that for an all words wsd task this automatic method is best focussed on words that are salient to the domain, and on words with a different acquired predominant sense in that domain compared to that acquired from a balanced corpus.
evita: a robust event recognizer for qa systems. we present evita, an application for recognizing events in natural language texts. although developed as part of a suite of tools aimed at providing question answering systems with information about both temporal and intensional relations among events, it can be used independently as an event extraction tool. it is unique in that it is not limited to any pre-established list of relation types (events), nor is it restricted to a specific domain. evita performs the identification and tagging of event expressions based on fairly simple strategies, informed by both linguistic-and statistically-based data. it achieves a performance ratio of 80.12% f-measure.
word-sense disambiguation for machine translation. in word sense disambiguation, a system attempts to determine the sense of a word from contextual features. major barriers to building a high-performing word sense disambiguation system include the difficulty of labeling data for this task and of predicting fine-grained sense distinctions. these issues stem partly from the fact that the task is being treated in isolation from possible uses of automatically disambiguated data. in this paper, we consider the related task of word translation, where we wish to determine the correct translation of a word from context. we can use parallel language corpora as a large supply of partially labeled data for this task. we present algorithms for solving the word translation problem and demonstrate a significant improvement over a baseline system. we then show that the word-translation system can be used to improve performance on a simplified machine-translation task and can effectively and accurately prune the set of candidate translations for a word.
speech-based information retrieval system with clarification dialogue strategy. this paper addresses a dialogue strategy to clarify and constrain the queries for speech-driven document retrieval systems. in spoken dialogue interfaces, users often make utterances before the query is completely generated in their mind; thus input queries are often vague or fragmental. as a result, usually many items are matched. we propose an efficient dialogue framework, where the system dynamically selects an optimal question based on information gain (ig), which represents reduction of matched items. a set of possible questions is prepared using various knowledge sources. as a bottom-up knowledge source, we extract a list of words that can take a number of objects and potentially causes ambiguity, using a dependency structure analysis of the document texts. this is complemented by top-down knowledge sources of metadata and hand-crafted questions. an experimental evaluation showed that the method significantly improved the success rate of retrieval, and all categories of the prepared questions contributed to the improvement.
a shortest path dependency kernel for relation extraction. we present a novel approach to relation extraction, based on the observation that the information required to assert a relationship between two named entities in the same sentence is typically captured by the shortest path between the two entities in the dependency graph. experiments on extracting top-level relations from the ace (automated content extraction) newspaper corpus show that the new shortest path dependency kernel outperforms a recent approach based on dependency tree kernels.
a semantic scattering model for the automatic interpretation of genitives. this paper addresses the automatic classification of the semantic relations expressed by the english genitives. a learning model is introduced based on the statistical analysis of the distribution of genitives' semantic relations on a large corpus. the semantic and contextual features of the genitive's noun phrase constituents play a key role in the identification of the semantic relation. the algorithm was tested on a corpus of approximately 2,000 sentences and achieved an accuracy of 79%, far better than 44% accuracy obtained with c5.0, or 43% obtained with a naive bayes algorithm, or 27% accuracy with a support vector machines learner on the same corpus.
mboi: discovery of business opportunities on the internet. we propose a tool for the discovery of business opportunities on the web, more specifically to help a user find relevant call for tenders (cft), i.e. invitations to contractors to submit a tender for their products/services. simple keyword-based information retrieval do not capture the relationships in the data, which are needed to answer the complex needs of the users. we therefore augment keywords with information extracted through natural language processing and business intelligence tools. as opposed to most systems, this information is used at all stages in the back-end and interface. the benefits are twofold: first we obtain higher precision of search and classification, and second the user gains access to a deeper level of information.
a backoff model for bootstrapping resources for non-english languages. the lack of annotated data is an obstacle to the development of many natural language processing applications; the problem is especially severe when the data is non-english. previous studies suggested the possibility of acquiring resources for non-english languages by bootstrapping from high quality english nlp tools and parallel corpora; however, the success of these approaches seems limited for dissimilar language pairs. in this paper, we propose a novel approach of combining a bootstrapped resource with a small amount of manually annotated data. we compare the proposed approach with other bootstrapping methods in the context of training a chinese part-of-speech tagger. experimental results show that our proposed approach achieves a significant improvement over em and self-training and systems that are only trained on manual annotations.
composition of conditional random fields for transfer learning. many learning tasks have subtasks for which much training data exists. therefore, we want to transfer learning from the old, general-purpose subtask to a more specific new task, for which there is often less data. while work in transfer learning often considers how the old task should affect learning on the new task, in this paper we show that it helps to take into account how the new task affects the old. specifically, we perform joint decoding of separately-trained sequence models, preserving uncertainty between the tasks and allowing information from the new task to affect predictions on the old task. on two standard text data sets, we show that joint decoding outperforms cascaded decoding.
enhanced answer type inference from questions using sequential models. question classification is an important step in factual question answering (qa) and other dialog systems. several attempts have been made to apply statistical machine learning approaches, including support vector machines (svms) with sophisticated features and kernels. curiously, the payoff beyond a simple bag-of-words representation has been small. we show that most questions reveal their class through a short contiguous token subsequence, which we call its informer span. perfect knowledge of informer spans can enhance accuracy from 79.4% to 88% using linear svms on standard benchmarks. in contrast, standard heuristics based on shallow pattern-matching give only a 3% improvement, showing that the notion of an informer is non-trivial. using a novel multi-resolution encoding of the question's parse tree, we induce a conditional random field (crf) to identify informer spans with about 85% accuracy. then we build a meta-classifier using a linear svm on the crf output, enhancing accuracy to 86.2%, which is better than all published numbers.
using mona for querying linguistic treebanks. mona is an automata toolkit providing a compiler for compiling formulae of monadic second order logic on strings or trees into string automata or tree automata. in this paper, we evaluate the option of using mona as a treebank query tool. unfortunately, we find that mona is not an option. there are several reasons why the main being unsustainable query answer times. if the treebank contains larger trees with more than 100 nodes, then even the processing of simple queries may take hours.
parallelism in coordination as an instance of syntactic priming: evidence from corpus-based modeling. experimental research in psycholinguistics has demonstrated a parallelism effect in coordination: speakers are faster at processing the second conjunct of a coordinate structure if it has the same internal structure as the first conjunct. we show that this phenomenon can be explained by the prevalence of parallel structures in corpus data. we demonstrate that parallelism is not limited to coordination, but also applies to arbitrary syntactic configurations, and even to documents. this indicates that the parallelism effect is an instance of a general syntactic priming mechanism in human language processing.
translating with non-contiguous phrases. this paper presents a phrase-based statistical machine translation method, based on non-contiguous phrases, i.e. phrases with gaps. a method for producing such phrases from a word-aligned corpora is proposed. a statistical translation model is also presented that deals such phrases, as well as a training method based on the maximization of translation accuracy, as measured with the nist evaluation metric. translations are produced by means of a beam-search decoder. experimental results are presented, that demonstrate how the proposed method allows to better generalize from the training data.
inner-outer bracket models for word alignment using hidden blocks. most statistical translation systems are based on phrase translation pairs, or "blocks", which are obtained mainly from word alignment. we use blocks to infer better word alignment and improved word alignment which, in turn, leads to better inference of blocks. we propose two new probabilistic models based on the inner-outer segmentations and use em algorithms for estimating the models' parameters. the first model recovers ibm model-1 as a special case. both models outperform bidirectional ibm model-4 in terms of word alignment accuracy by 10% absolute on the f-measure. using blocks obtained from the models in actual translation systems yields statistically significant improvements in chinese-english smt evaluation.
local phrase reordering models for statistical machine translation. we describe stochastic models of local phrase movement that can be incorporated into a statistical machine translation (smt) system. these models provide properly formulated, non-deficient, probability distributions over reordered phrase sequences. they are implemented by weighted finite state transducers. we describe em-style parameter re-estimation procedures based on phrase alignment under the complete translation model incorporating reordering. our experiments show that the reordering model yields substantial improvements in translation performance on arabic-to-english and chinese-to-english mt tasks. we also show that the procedure scales as the bitext size is increased.
accurate function parsing. in this paper, we extend an existing parser to produce richer output annotated with function labels. we obtain state-of-the-art results both in function labelling and in parsing, by automatically relabelling the penn treebank trees. in particular, we obtain the best published results on semantic function labels. this suggests that current statistical parsing methods are sufficiently general to produce accurate shallow semantic annotation.
query expansion with the minimum user feedback by transductive learning. query expansion techniques generally select new query terms from a set of top ranked documents. although a user's manual judgment of those documents would much help to select good expansion terms, it is difficult to get enough feedback from users in practical situations. in this paper we propose a query expansion technique which performs well even if a user notifies just a relevant document and a non-relevant document. in order to tackle this specific condition, we introduce two refinements to a well-known query expansion technique. one is application of a transductive learning technique in order to increase relevant documents. the other is a modified parameter estimation method which laps the predictions by multiple learning trials and try to differentiate the importance of candidate terms for expansion in relevant documents. experimental results show that our technique outperforms some traditional query expansion methods in several evaluation measures.
extracting personal names from email: applying named entity recognition to informal text. there has been little prior work on named entity recognition for "informal" documents like email. we present two methods for improving performance of person name recognizers for email: email-specific structural features and a recall-enhancing method which exploits name repetition across multiple documents.
detection of entity mentions occuring in english and chinese text. in this paper, we describe an integrated approach to entity mention detection that yields a monolithic, almost language independent system. it is optimal in the sense that all categorical constraints are simultaneously considered. the system is compact and easy to develop and maintain, since only a single set of features and classifiers are needed to be designed and optimized. it is implemented using one-versus-all support vector machine (svm) classifiers and a number of feature extractors at several linguistic levels. svms are well known for their ability to handle a large set of overlapping features with theoretically sound generalization properties. data sparsity might be an important issue as a result of a large number of classes and relatively moderate training data size. however, we report results that the integrated system performs as good as a pipelined system that decomposes the problem into a few smaller sub-tasks. we conduct all our experiments using ace 2004 data, evaluate the systems using ace metrics and report competitive performance.
using random walks for question-focused sentence retrieval. we consider the problem of question-focused sentence retrieval from complex news articles describing multi-event stories published over time. annotators generated a list of questions central to understanding each story in our corpus. because of the dynamic nature of the stories, many questions are time-sensitive (e.g. "how many victims have been found?") judges found sentences providing an answer to each question. to address the sentence retrieval problem, we apply a stochastic, graph-based method for comparing the relative importance of the textual units, which was previously used successfully for generic summarization. currently, we present a topic-sensitive version of our method and hypothesize that it can outperform a competitive baseline, which compares the similarity of each sentence to the input question via idf-weighted word overlap. in our experiments, the method achieves a trdr score that is significantly higher than that of the baseline.
combining deep linguistics analysis and surface pattern learning: a hybrid approach to chinese definitional question answering. we explore a hybrid approach for chinese definitional question answering by combining deep linguistic analysis with surface pattern learning. we answer four questions in this study: 1) how helpful are linguistic analysis and pattern learning? 2) what kind of questions can be answered by pattern matching? 3) how much annotation is required for a pattern-based system to achieve good performance? 4) what linguistic features are most useful? extensive experiments are conducted on biographical questions and other definitional questions. major findings include: 1) linguistic analysis and pattern learning are complementary; both are required to make a good definitional qa system; 2) pattern matching is very effective in answering biographical questions while less effective for other definitional questions; 3) only a small amount of annotation is required for a pattern learning system to achieve good performance on biographical questions; 4) the most useful linguistic features are copulas and appositives; relations also play an important role; only some propositions convey vital facts.
inducing a multilingual dictionary from a parallel multitext in related languages. dictionaries and word translation models are used by a variety of systems, especially in machine translation. we build a multilingual dictionary induction system for a family of related resource-poor languages. we assume only the presence of a single medium-length multitext (the bible). the techniques rely upon lexical and syntactic similarity of languages as well as on the fact that building dictionaries for several pairs of languages provides information about other pairs.
the mit spoken lecture processing project. we will demonstrate the mit spoken lecture processing server and an accompanying lecture browser that students can use to quickly locate and browse lecture segments that apply to their query. we will show how lecturers can upload recorded lectures and companion text material to our server for automatic processing. the server automatically generates a time-aligned word transcript of the lecture which can be downloaded for use within a browser. we will also demonstrate a browser we have created which allows students to quickly locate and browse audio segments that are relevant to their query. these tools can provide students with easier access to audio (or audio/visual) lectures, hopefully improving their educational experience.
incremental ltag parsing. we present a very efficient statistical incremental parser for ltag-spinal, a variant of ltag. the parser supports the full adjoining operation, dynamic predicate coordination, and non-projective dependencies, with a formalism of provably stronger generative capacity as compared to cfg. using gold standard pos tags as input, on section 23 of the ptb, the parser achieves an f-score of 89.3% for syntactic dependency defined on ltag derivation trees, which are deeper than the dependencies extracted from ptb alone with head rules (for example, in magerman's style).
the use of metadata, web-derived answer patterns and passage context to improve reading comprehension performance. a reading comprehension (rc) system attempts to understand a document and returns an answer sentence when posed with a question. rc resembles the ad hoc question answering (qa) task that aims to extract an answer from a collection of documents when posed with a question. however, since rc focuses only on a single document, the system needs to draw upon external knowledge sources to achieve deep analysis of passage sentences for answer sentence extraction. this paper proposes an approach towards rc that attempts to utilize external knowledge to improve performance beyond the baseline set by the bag-of-words (bow) approach. our approach emphasizes matching of metadata (i.e. verbs, named entities and base noun phrases) in passage context utilization and answer sentence extraction. we have also devised an automatic acquisition process for web-derived answer patterns (ap) which utilizes question-answer pairs from trec qa, the google search engine and the web. this approach gave improved rc performances for both the remedia and chunghwa corpora, attaining humsent accuracies of 42% and 69% respectively. in particular, performance analysis based on remedia shows that relative performances of 20.7% is due to metadata matching and a further 10.9% is due to the application of web-derived answer patterns.
using the web as an implicit training set: application to structural ambiguity resolution. recent work has shown that very large corpora can act as training data for nlp algorithms even without explicit labels. in this paper we show how the use of surface features and paraphrases in queries against search engines can be used to infer labels for structural ambiguity resolution tasks. using unsupervised algorithms, we achieve 84% precision on pp-attachment and 80% on noun compound coordination.
automatically learning cognitive status for multi-document summarization of newswire. machine summaries can be improved by using knowledge about the cognitive status of news article referents. in this paper, we present an approach to automatically acquiring distinctions in cognitive status using machine learning over the forms of referring expressions appearing in the input. we focus on modeling references to people, both because news often revolve around people and because existing natural language tools for named entity identification are reliable. we examine two specific distinctions---whether a person in the news can be assumed to be known to a target audience (hearer-old vs hearer-new) and whether a person is a major character in the news story. we report on machine learning experiments that show that these distinctions can be learned with high accuracy, and validate our approach using human subjects.
a maximum entropy word aligner for arabic-english machine translation. this paper presents a maximum entropy word alignment algorithm for arabic-english based on supervised training data. we demonstrate that it is feasible to create training material for problems in machine translation and that a mixture of supervised and unsupervised methods yields superior performance. the probabilistic model used in the alignment directly models the link decisions. significant improvement over traditional word alignment techniques is shown as well as improvement on several machine translation tests. performance of the algorithm is contrasted with human annotation performance.
extracting product features and opinions from reviews. consumers are often forced to wade through many on-line reviews in order to make an informed product choice. this paper introduces opine, an unsupervised information-extraction system which mines reviews in order to build a model of important product features, their evaluation by reviewers, and their relative quality across products.compared to previous work, opine achieves 22% higher precision (with only 3% lower recall) on the feature extraction task. opine's novel use of relaxation labeling for finding the semantic orientation of words in context leads to strong performance on the tasks of finding opinion phrases and their polarity.
opine: extracting product features and opinions from reviews. consumers have to often wade through a large number of on-line reviews in order to make an informed product choice. we introduce opine, an unsupervised, high-precision information extraction system which mines product reviews in order to build a model of product features and their evaluation by reviewers.
webexperimenter for multiple-choice question generation. automatic generation of multiple-choice questions is an emerging topic in application of natural language processing. particularly, applying it to language testing has been proved to be useful (sumita et al., 2005).
a self-learning context-aware lemmatizer for german. accurate lemmatization of german nouns mandates the use of a lexicon. comprehensive lexicons, however, are expensive to build and maintain. we present a self-learning lemmatizer capable of automatically creating a full-form lexicon by processing german documents.
data-driven approaches for information structure identification. this paper investigates automatic identification of information structure (is) in texts. the experiments use the prague dependency treebank which is annotated with is following the praguian approach of topic focus articulation. we automatically detect t(opic) and f(ocus), using node attributes from the treebank as basic features and derived features inspired by the annotation guidelines. we present the performance of decision trees (c4.5), maximum entropy, and rule induction (ripper) classifiers on all tectogrammatical nodes. we compare the results against a baseline system that always assigns f(ocus) and against a rule-based system. the best system achieves an accuracy of 90.69%, which is a 44.73% improvement over the baseline (62.66%).
word sense disambiguation using sense examples automatically acquired from a second language. we present a novel almost-unsupervised approach to the task of word sense disambiguation (wsd). we build sense examples automatically, using large quantities of chinese text, and english-chinese and chinese-english bilingual dictionaries, taking advantage of the observation that mappings between words and meanings are often different in typologically distant languages. we train a classifier on the sense examples and test it on a gold standard english wsd dataset. the evaluation gives results that exceed previous state-of-the-art results for comparable systems. we also demonstrate that a little manual effort can improve the quality of sense examples, as measured by wsd accuracy. the performance of the classifier on wsd also improves as the number of training sense examples increases.
handling biographical questions with implicature. traditional question answering systems adopt the following framework: parsing questions, searching for relevant documents, and identifying/generating answers. however, this framework does not work well for questions with hidden assumptions and implicatures. in this paper, we describe a novel idea, a cascading guidance strategy, which can not only identify potential traps in questions but further guide the answer extraction procedure by recognizing whether there are multiple answers for a question. this is the first attempt to solve implicature problem for complex qa in a cascading fashion using n-gram language models as features. we here investigate questions with implicatures related to biography facts in a web-based qa system, power-bio. we compare the performances of decision tree, na&iuml;ve bayes, svm (support vector machine), and me (maximum entropy) classification methods. the integration of the cascading guidance strategy can help extract answers for questions with implicatures and produce satisfactory results in our experiments.
bidirectional inference with the easiest-first strategy for tagging sequence data. this paper presents a bidirectional inference algorithm for sequence labeling problems such as part-of-speech tagging, named entity recognition and text chunking. the algorithm can enumerate all possible decomposition structures and find the highest probability sequence together with the corresponding decomposition structure in polynomial time. we also present an efficient decoding algorithm based on the easiest-first strategy, which gives comparably good performance to full bidirectional inference with significantly lower computational cost. experimental results of part-of-speech tagging and text chunking show that the proposed bidirectional inference methods consistently outperform unidirectional inference methods and bidirectional memms give comparable performance to that achieved by state-of-the-art learning algorithms including kernel support vector machines.
discourse chunking and its application to sentence compression. in this paper we consider the problem of analysing sentence-level discourse structure. we introduce discourse chunking (i.e., the identification of intra-sentential nucleus and satellite spans) as an alternative to full-scale discourse parsing. our experiments show that the proposed modelling approach yields results comparable to state-of-the-art while exploiting knowledge-lean features and small amounts of discourse annotations. we also demonstrate how discourse chunking can be successfully applied to a sentence compression task.
automatically evaluating answers to definition questions. following recent developments in the automatic evaluation of machine translation and document summarization, we present a similar approach, implemented in a measure called pourpre, for automatically evaluating answers to definition questions. until now, the only way to assess the correctness of answers to such questions involves manual determination of whether an information nugget appears in a system's response. the lack of automatic methods for scoring system output is an impediment to progress in the field, which we address with this work. experiments with the trec 2003 and trec 2004 qa tracks indicate that rankings produced by our metric correlate highly with official rankings, and that pourpre outperforms direct application of existing metrics.
context-based morphological disambiguation with random fields. finite-state approaches have been highly successful at describing the morphological processes of many languages. such approaches have largely focused on modeling the phone- or character-level processes that generate candidate lexical types, rather than tokens in context. for the full analysis of words in context, disambiguation is also required (hakkani-t&uuml;r et al., 2000; haji&ccaron; et al., 2001). in this paper, we apply a novel source-channel model to the problem of morphological disambiguation (segmentation into morphemes, lemmatization, and pos tagging) for concatenative, templatic, and inflectional languages. the channel model exploits an existing morphological dictionary, constraining each word's analysis to be linguistically valid. the source model is a factored, conditionally-estimated random field (lafferty et al., 2001) that learns to disambiguate the full sentence by modeling local contexts. compared with baseline state-of-the-art methods, our method achieves statistically significant error rate reductions on korean, arabic, and czech, for various training set sizes and accuracy measures.
novelty detection: the trec experience. a challenge for search systems is to detect not only when an item is relevant to the user's information need, but also when it contains something new which the user has not seen before. in the trec novelty track, the task was to highlight sentences containing relevant and new information in a short, topical document stream. this is analogous to highlighting key parts of a document for another person to read, and this kind of output can be useful as input to a summarization system. search topics involved both news events and reported opinions on hot-button subjects. when people performed this task, they tended to select small blocks of consecutive sentences, whereas current systems identified many relevant and novel passages. we also found that opinions are much harder to track than events.
opinionfinder: a system for subjectivity analysis. opinionfinder is a system that performs subjectivity analysis, automatically identifying when opinions, sentiments, speculations, and other private states are present in text. specifically, opinionfinder aims to identify subjective sentences and to mark various aspects of the subjectivity in these sentences, including the source (holder) of the subjectivity and words that are included in phrases expressing positive or negative sentiments.
recognizing contextual polarity in phrase-level sentiment analysis. this paper presents a new approach to phrase-level sentiment analysis that first determines whether an expression is neutral or polar and then disambiguates the polarity of the polar expressions. with this approach, the system is able to automatically identify the contextual polarity for a large subset of sentiment expressions, achieving results that are significantly better than baseline.
pattern visualization for machine translation output. we describe a method for identifying systematic patterns in translation data using part-of-speech tag sequences. we incorporate this analysis into a diagnostic tool intended for developers of machine translation systems, and demonstrate how our application can be used by developers to explore patterns in machine translation output.
some computational complexity results for synchronous context-free grammars. this paper investigates some computational problems associated with probabilistic translation models that have recently been adopted in the literature on machine translation. these models can be viewed as pairs of probabilistic context-free grammars working in a 'synchronous' way. two hardness results for the class np are reported, along with an exponential time lower-bound for certain classes of algorithms that are currently used in the literature.
demonstrating an interactive semantic role labeling system. semantic role labeling (srl) is the task of performing a shallow semantic analysis of text (i.e., who did what to whom, when, where, how). this is a crucial step toward deeper understanding of text and has many immediate applications. preprocessed information on text, mostly syntactic, has been shown to be important for srl. current research focuses on improving the performance assuming that this lower level information is given without any attention to the overall efficiency of the final system, although minimizing execution time is a necessity in order to support real world applications. the goal of our demonstration is to present an interactive srl system that can be used both as a research and an educational tool. its architecture is based on the state-of-the-art system (the top system in the 2005 conll shared task), modified to process raw text through the addition of lower level processors, while achieving effective real time performance.
investigating unsupervised learning for text categorization bootstrapping. we propose a generalized bootstrapping algorithm in which categories are described by relevant seed features. our method introduces two unsupervised steps that improve the initial categorization step of the bootstrapping scheme: (i) using latent semantic space to obtain a generalized similarity measure between instances and features, and (ii) the gaussian mixture algorithm, to obtain uniform classification probabilities for unlabeled examples. the algorithm was evaluated on two text categorization tasks and obtained state-of-the-art performance using only the category names as initial seeds.
japanese speech understanding using grammar specialization. the most common speech understanding architecture for spoken dialogue systems is a combination of speech recognition based on a class n-gram language model, and robust parsing. for many types of applications, however, grammar-based recognition can offer concrete advantages. training a good class n-gram language model requires substantial quantities of corpus data, which is generally not available at the start of a new project. head-to-head comparisons of class n-gram/robust and grammar-based systems also suggest that users who are familiar with system coverage get better results from grammar-based architectures (knight et al., 2001). as a consequence, deployed spoken dialogue systems for real-world applications frequently use grammar-based methods. this is particularly the case for speech translation systems. although leading research systems like verbmobil and ne-spole! (wahlster, 2000; lavie et al., 2001) usually employ complex architectures combining statistical and rule-based methods, successful practical examples like phraselator and s-minds (phraselator, 2005; sehda, 2005) are typically phrasal translators with grammar-based recognizers.
part-of-speech tagging using virtual evidence and negative training. we present a part-of-speech tagger which introduces two new concepts: virtual evidence in the form of an "observed child" node, and negative training data to learn the conditional probabilities for the observed child. associated with each word is a flexible feature-set which can include binary flags, neighboring words, etc. the conditional probability of tag given word + features is implemented using a factored language-model with back-off to avoid data sparsity problems. this model remains within the framework of dynamic bayesian networks (dbns) and is conditionally-structured, but resolves the label bias problem inherent in the conditional markov model (cmm).
non-projective dependency parsing using spanning tree algorithms. we formalize weighted dependency parsing as searching for maximum spanning trees (msts) in directed graphs. using this representation, the parsing algorithm of eisner (1996) is sufficient for searching over all projective trees in o(n3) time. more surprisingly, the representation is extended naturally to non-projective parsing using chu-liu-edmonds (chu and liu, 1965; edmonds, 1967) mst algorithm, yielding an o(n2) parsing algorithm. we evaluate these methods on the prague dependency treebank using online large-margin learning techniques (crammer et al., 2003; mcdonald et al., 2005) and show that mst parsing increases efficiency and accuracy for languages with non-projective dependencies.
a discriminative matching approach to word alignment. we present a discriminative, large-margin approach to feature-based matching for word alignment. in this framework, pairs of word tokens receive a matching score, which is based on features of that pair, including measures of association between the words, distortion between their positions, similarity of the orthographic form, and so on. even with only 100 labeled training examples and simple features which incorporate counts from a large unlabeled corpus, we achieve aer performance close to ibm model 4, in much less time. including model 4 predictions as features, we achieve a relative aer reduction of 22% in over intersected model 4 alignments.
a semantic approach to recognizing textual entailment. exhaustive extraction of semantic information from text is one of the formidable goals of state-of-the-art nlp systems. in this paper, we take a step closer to this objective. we combine the semantic information provided by different resources and extract new semantic knowledge to improve the performance of a recognizing textual entailment system.
redundancy-based correction of automatically extracted facts. the accuracy of event extraction is limited by a number of complicating factors, with errors compounded at all sages inside the information extraction pipeline. in this paper, we present methods for recovering automatically from errors committed in the pipeline processing. recovery is achieved via post-processing facts aggregated over a large collection of documents, and suggesting corrections based on evidence external to the document. a further improvement is derived from propagating multiple, locally non-best slot fills through the pipeline. evaluation shows that the global analysis is over 10 times more likely to suggest valid corrections to the local-only analysis than it is to suggest erroneous ones. this yields a substantial overall gain, with no supervised training.
combining multiple forms of evidence while filtering. this paper studies how to go beyond relevance and enable a filtering system to learn more interesting and detailed data driven user models from multiple forms of evidence. we carry out a user study using a real time web based personal news filtering system, and collect extensive multiple forms of evidence, including explicit and implicit user feedback. we explore the graphical modeling approach to combine these forms of evidence. to test whether the approach can help us understand the domain better, we use graph structure learning algorithm to derive the causal relationships between different forms of evidence. to test whether the approach can help the system improve the performance, we use the graphical inference algorithms to predict whether a user likes a document based on multiple forms of evidence. the results show that combining multiple forms of evidence using graphical models can help us better understand the filtering problem, improve filtering system performance, and handle various data missing situations naturally.
word-level confidence estimation for machine translation using phrase-based translation models. confidence measures for machine translation is a method for labeling each word in an automatically generated translation as correct or incorrect. in this paper, we will present a new approach to confidence estimation which has the advantage that it does not rely on system output such as n-best lists or word graphs as many other confidence measures do. it is, thus, applicable to any kind of machine translation system.experimental evaluation has been performed on translation of technical manuals in three different language pairs. results will be presented for different machine translation systems to show that the new approach is independent of the underlying machine translation system which generated the translations. to the best of our knowledge, the performance of the new confidence measure is better than that of any existing confidence measure.
using question series to evaluate question answering system effectiveness. the original motivation for using question series in the trec 2004 question answering track was the desire to model aspects of dialogue processing in an evaluation task that included different question types. the structure introduced by the series also proved to have an important additional benefit: the series is at an appropriate level of granularity for aggregating scores for an effective evaluation. the series is small enough to be meaningful at the task level since it represents a single user interaction, yet it is large enough to avoid the highly skewed score distributions exhibited by single questions. an analysis of the reliability of the per-series evaluation shows the evaluation is stable for differences in scores seen in the track.
unsupervised large-vocabulary word sense disambiguation with graph-based algorithms for sequence data labeling. this paper introduces a graph-based algorithm for sequence data labeling, using random walks on graphs encoding label dependencies. the algorithm is illustrated and tested in the context of an unsupervised word sense disambiguation problem, and shown to significantly outperform the accuracy achieved through individual label assignment, as measured on standard sense-annotated data sets.
error detection using linguistic features. recognition errors hinder the proliferation of speech recognition (sr) systems. based on the observation that recognition errors may result in ungrammatical sentences, especially in dictation application where an acceptable level of accuracy of generated documents is indispensable, we propose to incorporate two kinds of linguistic features into error detection: lexical features of words, and syntactic features from a robust lexicalized parser. transformation-based learning is chosen to predict recognition errors by integrating word confidence scores with linguistic features. the experimental results on a dictation data corpus show that linguistic features alone are not as useful as word confidence scores in detecting errors. however, linguistic features provide complementary information when combined with word confidence scores, which collectively reduce the classification error rate by 12.30% and improve the f measure by 53.62%.
improving multilingual summarization: using redundancy in the input to correct mt errors. in this paper, we use the information redundancy in multilingual input to correct errors in machine translation and thus improve the quality of multilingual summaries. we consider the case of multi-document summarization, where the input documents are in arabic, and the output summary is in english. typically, information that makes it to a summary appears in many different lexical-syntactic forms in the input documents. further, the use of multiple machine translation systems provides yet more redundancy, yielding different ways to realize that information in english. we demonstrate how errors in the machine translations of the input arabic documents can be corrected by identifying and generating from such redundancy, focusing on noun phrases.
multi-way relation classification: application to protein-protein interactions. we address the problem of multi-way relation classification, applied to identification of the interactions between proteins in bioscience text. a major impediment to such work is the acquisition of appropriately labeled training data; for our experiments we have identified a database that serves as a proxy for training data. we use two graphical models and a neural net for the classification of the interactions, achieving an accuracy of 64% for a 10-way distinction between relation types. we also provide evidence that the exploitation of the sentences surrounding a citation to a paper can yield higher accuracy than other sentences.
a discriminative framework for bilingual word alignment. bilingual word alignment forms the foundation of most approaches to statistical machine translation. current word alignment methods are predominantly based on generative models. in this paper, we demonstrate a discriminative approach to training simple word alignment models that are comparable in accuracy to the more complex generative models normally used. these models have the the advantages that they are easy to add features to and they allow fast optimization of model parameters using small amounts of annotated data.
optimizing to arbitrary nlp metrics using ensemble selection. while there have been many successful applications of machine learning methods to tasks in nlp, learning algorithms are not typically designed to optimize nlp performance metrics. this paper evaluates an ensemble selection framework designed to optimize arbitrary metrics and automate the process of algorithm selection and parameter tuning. we report the results of experiments that instantiate the framework for three nlp tasks, using six learning algorithms, a wide variety of parameterizations, and 15 performance metrics. based on our results, we make recommendations for subsequent machine-learning-based research for natural language learning.
exploiting a verb lexicon in automatic semantic role labelling. we develop an unsupervised semantic role labelling system that relies on the direct application of information in a predicate lexicon combined with a simple probability model. we demonstrate the usefulness of predicate lexicons for role labelling, as well as the feasibility of modifying an existing role-labelled corpus for evaluating a different set of semantic roles. we achieve a substantial improvement over an informed baseline.
effective use of prosody in parsing conversational speech. we identify a set of prosodic cues for parsing conversational speech and show how such features can be effectively incorporated into a statistical parsing model. on the switchboard corpus of conversational speech, the system achieves improved parse accuracy over a state-of-the-art system which uses only lexical and syntactic features. since removal of edit regions is known to improve downstream parse accuracy, we explore alternatives for edit detection and show that pcfgs are not competitive with more specialized techniques.
posbiotm/w: a development workbench for machine learning oriented biomedical text mining system. the posbiotm/w is a workbench for machine-learning oriented biomedical text mining system. the postbiotm/w is intended to assist biologist in mining useful information efficiently from biomedical text resources. to do so, it provides a suit of tools for gathering, managing, analyzing and annotating texts. the workbench is implemented in java, which means that it is platform-independent.
context and learning in novelty detection. we demonstrate the value of using context in a new-information detection system that achieved the highest precision scores at the text retrieval conference's novelty track in 2004. in order to determine whether information within a sentence has been seen in material read previously, our system integrates information about the context of the sentence with novel words and named entities within the sentence, and uses a specialized learning algorithm to tune the system parameters.
bayesian learning in text summarization. the paper presents a bayesian model for text summarization, which explicitly encodes and exploits information on how human judgments are distributed over the text. comparison is made against non bayesian summarizers, using test data from japanese news texts. it is found that the bayesian approach generally leverages performance of a summarizer, at times giving it a significant lead over non-bayesian models.
measuring the relative compositionality of verb-noun (v-n) collocations by integrating features. measuring the relative compositionality of multi-word expressions (mwes) is crucial to natural language processing. various collocation based measures have been proposed to compute the relative compositionality of mwes. in this paper, we define novel measures (both collocation based and context based measures) to measure the relative compositionality of mwes of v-n type. we show that the correlation of these features with the human ranking is much superior to the correlation of the traditional features with the human ranking. we then integrate the proposed features and the traditional features using a svm based ranking function to rank the collocations of v-n type based on their relative compositionality. we then show that the correlation between the ranks computed by the svm based ranking function and human ranking is significantly better than the correlation between ranking of individual features and human ranking.
identifying semantic relations and functional properties of human verb associations. this paper uses human verb associations as the basis for an investigation of verb properties, focusing on semantic verb relations and prominent nominal features. first, the lexical semantic taxonymy germanet is checked on the types of classic semantic relations in our data; verb-verb pairs not covered by germanet can help to detect missing links in the taxonomy, and provide a useful basis for defining non-classical relations. second, a statistical grammar is used for determining the conceptual roles of the noun responses. we present prominent syntax-semantic roles and evidence for the usefulness of co-occurrence information in distributional verb descriptions.
extracting information about outbreaks of infectious epidemics. this work demonstrates the promed-plus epidemiological fact base. the facts are automatically extracted from plain-text reports about outbreaks of infectious epidemics around the world. the system collects new reports, extracts new facts, and updates the database, in real time. the extracted database is available on-line through a web server.
paradigmatic modifiability statistics for the extraction of complex multi-word terms. we here propose a new method which sets apart domain-specific terminology from common non-specific noun phrases. it is based on the observation that terminological multi-word groups reveal a considerably lesser degree of distributional variation than non-specific noun phrases. we define a measure for the observable amount of paradigmatic modifiability of terms and, subsequently, test it on bigram, trigram and quadgram noun phrases extracted from a 104-million-word biomedical text corpus. using a community-wide curated biomedical terminology system as an evaluation gold standard, we show that our algorithm significantly outperforms a variety of standard term identification measures. we also provide empirical evidence that our methodolgy is essentially domain- and corpus-size-independent.
bootstrapping without the boot. "bootstrapping" methods for learning require a small amount of supervision to seed the learning process. we show that it is sometimes possible to eliminate this last bit of supervision, by trying many candidate seeds and selecting the one with the most plausible outcome. we discuss such "strapping" methods in general, and exhibit a particular method for strapping word-sense classifiers for ambiguous words. our experiments on the canadian hansards show that our unsupervised technique is significantly more effective than picking seeds by hand (yarowsky, 1995), which in turn is known to rival supervised methods.
kernel-based approach for automatic evaluation of natural language generation technologies: application to automatic summarization. in order to promote the study of automatic summarization and translation, we need an accurate automatic evaluation method that is close to human evaluation. in this paper, we present an evaluation method that is based on convolution kernels that measure the similarities between texts considering their substructures. we conducted an experiment using automatic summarization evaluation data developed for text summarization challenge 3 (tsc-3). a comparison with conventional techniques shows that our method correlates more closely with human evaluations and is more robust.
a large-scale exploration of effective global features for a joint entity detection and tracking model. entity detection and tracking (edt) is the task of identifying textual mentions of real-world entities in documents, extending the named entity detection and coreference resolution task by considering mentions other than names (pronouns, definite descriptions, etc.). like ne tagging and coreference resolution, most solutions to the edt task separate out the mention detection aspect from the coreference aspect. by doing so, these solutions are limited to using only local features for learning. in contrast, by modeling both aspects of the edt task simultaneously, we are able to learn using highly complex, non-local features. we develop a new joint edt model and explore the utility of many features, demonstrating their effectiveness on this task.
a translation model for sentence retrieval. in this work we propose a translation model for monolingual sentence retrieval. we propose four methods for constructing a parallel corpus. of the four methods proposed, a lexicon learned from a bilingual arabic-english corpus aligned at the sentence level performs best, significantly improving results over the query likelihood baseline. further, we demonstrate that smoothing from the local context of the sentence improves retrieval over the query likelihood baseline.
mining context specific similarity relationships using the world wide web. we have studied how context specific web corpus can be automatically created and mined for discovering semantic similarity relationships between terms (words or phrases) from a given collection of documents (target collection). these relationships between terms can be used to adjust the standard vectors space representation so as to improve the accuracy of similarity computation between text documents in the target collection. our experiments with a standard test collection (reuters) have revealed the reduction of similarity errors by up to 50%, twice as much as the improvement by using other known techniques.
mindnet: an automatically-created lexical resource. we will demonstrate mindnet, a lexical resource built automatically by processing text. we will present two forms of mindnet: as a static lexical resource, and, as a toolkit which allows mindnets to be built from arbitrary text. we will also introduce a web-based interface to mindnet lexicons (mnex) that is intended to make the data contained within mindnets more accessible for exploration. both english and japanese mindnets will be shown and will be made available, through mnex, for research purposes.
prague dependency treebank as an exercise book of czech. there was simply linguistics at the beginning. during the years, linguistics has been accompanied by various attributes. for example corpus one. while a name corpus is relatively young in linguistics, its content related to a language - collection of texts and speeches - is nothing new at all. speaking about corpus linguistics nowadays, we keep in mind collecting of language resources in an electronic form. there is one more attribute that computers together with mathematics bring into linguistics - computational. the progress from working with corpus towards the computational approach is determined by the fact that electronic data with the "unlimited" computer potential give opportunities to solve natural language processing issues in a fast way (with regard to the possibilities of human being) on a statistically significant amount of data.listing the attributes, we have to stop for a while by the notion of annotated corpora. let us build a big corpus including all czech text data available in an electronic form and look at it as a sequence of characters with the space having dominating status -- a separator of words. it is very easy to compare two words (as strings), to calculate how many times these two words appear next to each other in a corpus, how many times they appear separately and so on. even more, it is possible to do it for every language (more or less). this kind of calculations is language independent -- it is not restricted by the knowledge of language, its morphology, its syntax. however, if we want to solve more complex language tasks such as machine translation we cannot do it without deep knowledge of language. thus, we have to transform language knowledge into an electronic form as well, i.e. we have to formalize it and then assign it to words (e.g., in case of morphology), or to sentences (e.g., in case of syntax). a corpus with additional information is called an annotated corpus.we are lucky. there is a real annotated corpus of czech -- prague dependency treebank (pdt). pdt belongs to the top of the world corpus linguistics and its second edition is ready to be officially published (for the first release see (haji&ccaron; et al., 2001)). pdt was born in prague and had arisen from the tradition of the successful prague school of linguistics. the dependency approach to a syntactical analysis with the main role of verb has been applied. the annotations go from the morphological level to the tectogrammatical level (level of underlying syntactic structure) through the intermediate syntactical-analytical level. the data (2 mil. words) have been annotated in the same direction, i.e., from a more simple level to a more complex one. this fact corresponds to the amount of data annotated on a particular level. the largest number of words have been annotated morphologically (2 mil. words) and the lowest number of words tectogramatically (0.8 mil. words). in other words, 0.8 million words have been annotated on all three levels, 1.5 mil. words on both morphological and syntactical level and 2 mil. words on the lowest morphological level.besides the verification of 'pre-pdt' theories and formulation of new ones, pdt serves as training data for machine learning methods. here, we present a system styx that is designed to be an exercise book of czech morphology and syntax with exercises directly selected from pdt. the schoolchildren can use a computer to write, to draw, to play games, to page encyclopedia, to compose music - why they could not use it to parse a sentence, to determine gender, number, case, ...? while the styx development, two main phases have been passed:1. transformation of an academic version of pdt into a school one. 20 thousand sentences were automatically selected out of 80 thousand sentences morphologically and syntactically annotated. the complexity of selected sentences exactly corresponds to the complexity of sentences exercised in the current textbooks of czech. a syntactically annotated sentence in pdt is represented as a tree with the same number of nodes as is the number of the words in the given sentence. it differs from the schemes used at schools (grepl and karl&iacute;k, 1998). on the other side, the linear structure of pdt morphological annotations was taken as it is -- only morphological categories relevant to school syllabuses were preserved.2. proposal and implementation of exercises. the general computer facilities of basic and secondary schools were taken into account while choosing a potential programming language to use. the styx is implemented in java that meets our main requirements -- platform-independent system and system stability.at least to our knowledge, there is no such system for any language corpus that makes the schoolchildren familiar with an academic product. at the same time, our system represents a challenge and an opportunity for the academicians to popularize a field devoted to the natural language processing with promising future.a number of electronic exercises of czech morphology and syntax were created. however, they were built manually, i.e. authors selected sentences either from their minds or randomly from books, newspapers. then they analyzed them manually. in a given manner, there is no chance to build an exercise system that reflects a real usage of language in such amount the styx system fully offers.
searching the audio notebook: keyword search in recorded conversation. mit's audio notebook added great value to the note-taking process by retaining audio recordings, e.g. during lectures or interviews. the key was to provide users ways to quickly and easily access portions of interest in a recording. several non-speech-recognition based techniques were employed. in this paper we present a system to search directly the audio recordings by key phrases. we have identified the user requirements as accurate ranking of phrase matches, domain independence, and reasonable response time. we address these requirements by a hybrid word/phoneme search in lattices, and a supporting indexing scheme. we will introduce the ranking criterion, a unified hybrid posterior-lattice representation, and the indexing algorithm for hybrid lattices. we present results for five different recording sets, including meetings, telephone conversations, and interviews. our results show an average search accuracy of 84%, which is dramatically better than a direct search in speech recognition transcripts (less than 40% search accuracy).
matching inconsistently spelled names in automatic speech recognizer output for information retrieval. many proper names are spelled inconsistently in speech recognizer output, posing a problem for applications where locating mentions of named entities is critical. we model the distortion in the spelling of a name due to the speech recognizer as the effect of a noisy channel. the models follow the framework of the ibm translation models. the model is trained using a parallel text of closed caption and automatic speech recognition output. we also test a string edit distance based method. the effectiveness of these models is evaluated on a name query retrieval task. our methods result in a 60% improvement in f1. we also demonstrate why the problem has not been critical in trec and tdt tasks.
maximum expected f-measure training of logistic regression models. we consider the problem of training logistic regression models for binary classification in information extraction and information retrieval tasks. fitting probabilistic models for use with such tasks should take into account the demands of the task-specific utility function, in this case the well-known f-measure, which combines recall and precision into a global measure of utility. we develop a training procedure based on empirical risk minimization / utility maximization and evaluate it on a simple extraction task.
using semantic relations to refine coreference decisions. we present a novel mechanism for improving reference resolution by using the output of a relation tagger to rescore coreference hypotheses. experiments show that this new framework can improve performance on two quite different languages - english and chinese.
integrating linguistic knowledge in passage retrieval for question answering. in this paper we investigate the use of linguistic knowledge in passage retrieval as part of an open-domain question answering system. we use annotation produced by a deep syntactic dependency parser for dutch, alpino, to extract various kinds of linguistic features and syntactic units to be included in a multi-layer index. similar annotation is produced for natural language questions to be answered by the system. from this we extract query terms to be sent to the enriched retrieval index. we use a genetic algorithm to optimize the selection of features and syntactic units to be included in a query. this algorithm is also used to optimize further parameters such as keyword weights. the system is trained on questions from the competition on dutch question answering within the cross-language evaluation forum (clef). we could show an improvement of about 15% in mean total reciprocal rank compared to traditional information retrieval using plain text keywords (including stemming and stop word removal).
pp-attachment disambiguation using large context. prepositional phrase-attachment is a common source of ambiguity in natural language. the previous approaches use limited information to solve the ambiguity -- four lexical heads -- although humans disambiguate much better when the full sentence is available. we propose to solve the pp-attachment ambiguity with a support vector machines learning model that uses complex syntactic and semantic features as well as unsupervised information obtained from the world wide web. the system was tested on several datasets obtaining an accuracy of 93.62% on a penn treebank-ii dataset; 91.79% on a framenet dataset when no manually-annotated semantic information is provided and 92.85% when semantic information is provided.
improving lsa-based summarization with anaphora resolution. we propose an approach to summarization exploiting both lexical information and the output of an automatic anaphoric resolver, and using singular value decomposition (svd) to identify the main terms. we demonstrate that adding anaphoric information results in significant performance improvements over a previously developed system, in which only lexical terms are used as the input to svd. however, we also show that how anaphoric information is used is crucial: whereas using this information to add new terms does result in improved performance, simple substitution makes the performance worse.
nooj: a linguistic annotation system for corpus processing. nooj is a new corpus processing system, similar to the intex software,1 and designed to replace it. nooj allows users to process large sets of texts in real time. users can build, accumulate and manage sophisticated concordances that correspond to morphological and syntactic grammars organized in re-usable libraries.
minimum sample risk methods for language modeling. this paper proposes a new discriminative training method, called minimum sample risk (msr), of estimating parameters of language models for text input. while most existing discriminative training methods use a loss function that can be optimized easily but approaches only approximately to the objective of minimum error rate, msr minimizes the training error directly using a heuristic training procedure. evaluations on the task of japanese text input show that msr can handle a large number of features and training samples; it significantly outperforms a regular trigram model trained using maximum likelihood estimation, and it also outperforms the two widely applied discriminative methods, the boosting and the perceptron algorithms, by a small but statistically significant margin.
disambiguation of morphological structure using a pcfg. german has a productive morphology and allows the creation of complex words which are often highly ambiguous. this paper reports on the development of a head-lexicalized pcfg for the disambiguation of german morphological analyses. the grammar is trained on unlabeled data using the inside-outside algorithm. the parser achieves a precision of more than 68% on difficult test data, which is 23% more than the baseline obtained by randomly choosing one of the simplest analyses. remarkable is the fact that precision drops to 52% without lexicalization.
making computers laugh: investigations in automatic humor recognition. humor is one of the most interesting and puzzling aspects of human behavior. despite the attention it has received in fields such as philosophy, linguistics, and psychology, there have been only few attempts to create computational models for humor recognition or generation. in this paper, we bring empirical evidence that computational approaches can be successfully applied to the task of humor recognition. through experiments performed on very large data sets, we show that automatic classification techniques can be effectively used to distinguish between humorous and non-humorous texts, with significant improvements observed over apriori known baselines.
an orthonormal basis for topic segmentation in tutorial dialogue. this paper explores the segmentation of tutorial dialogue into cohesive topics. a latent semantic space was created using conversations from human to human tutoring transcripts, allowing cohesion between utterances to be measured using vector similarity. previous cohesion-based segmentation methods that focus on expository monologue are reapplied to these dialogues to create benchmarks for performance. a novel moving window technique using orthonormal bases of semantic vectors significantly outperforms these benchmarks on this dialogue segmentation task.
ocr post-processing for low density languages. we present a lexicon-free post-processing method for optical character recognition (ocr), implemented using weighted finite state machines. we evaluate the technique in a number of scenarios relevant for natural language processing, including creation of new ocr capabilities for low density languages, improvement of ocr performance for a native commercial system, acquisition of knowledge from a foreign-language dictionary, creation of a parallel text, and machine translation from ocr output.
flexible text segmentation with structured multilabel classification. many language processing tasks can be reduced to breaking the text into segments with prescribed properties. such tasks include sentence splitting, tokenization, named-entity extraction, and chunking. we present a new model of text segmentation based on ideas from multilabel classification. using this model, we can naturally represent segmentation problems involving overlapping and non-contiguous segments. we evaluate the model on entity extraction and noun-phrase chunking and show that it is more accurate for overlapping and non-contiguous segments, but it still performs well on simpler data sets for which sequential tagging has been the best method.
differentiating homonymy and polysemy in information retrieval. recent studies into web retrieval have shown that word sense disambiguation can increase retrieval effectiveness. however, it remains unclear as to the minimum disambiguation accuracy required and the granularity with which one must define word sense in order to maximize these benefits. this study answers these questions using a simulation of the effects of ambiguity on information retrieval. it goes beyond previous studies by differentiating between homonymy and polysemy. results show that retrieval is more sensitive to polysemy than homonymy and that, when resolving polysemy, accuracy as low as 55% can potentially lead to increased performance.
multi-perspective question answering using the opqa corpus. we investigate techniques to support the answering of opinion-based questions. we first present the opqa corpus of opinion questions and answers. using the corpus, we compare and contrast the properties of fact and opinion questions and answers. based on the disparate characteristics of opinion vs. fact answers, we argue that traditional fact-based qa approaches may have difficulty in an mpqa setting without modification. as an initial step towards the development of mpqa systems, we investigate the use of machine learning and rule-based subjectivity and opinion source filters and show that they can be used to guide mpqa systems.
hidden-variable models for discriminative reranking. we describe a new method for the representation of nlp structures within reranking approaches. we make use of a conditional log-linear model, with hidden variables representing the assignment of lexical items to word clusters or word senses. the model learns to automatically make these assignments based on a discriminative training criterion. training and decoding with the model requires summing over an exponential number of hidden-variable assignments: the required summations can be computed efficiently and exactly using dynamic programming. as a case study, we apply the model to parse reranking. the model gives an f-measure improvement of &ap; 1.25% beyond the base parser, and an &ap; 0.25% improvement beyond the collins (2000) reranker. although our experiments are focused on parsing, the techniques described generalize naturally to nlp structures other than parse trees.
cross-linguistic projection of role-semantic information. this paper considers the problem of automatically inducing role-semantic annotations in the framenet paradigm for new languages. we introduce a general framework for semantic projection which exploits parallel texts, is relatively inexpensive and can potentially reduce the amount of effort involved in creating semantic resources. we propose projection models that exploit lexical and syntactic information. experimental results on an english-german parallel corpus demonstrate the advantages of this approach.
morphology and reranking for the statistical parsing of spanish. we present two methods for incorporating detailed features in a spanish parser, building on a baseline model that is a lexicalized pcfg. the first method exploits spanish morphology, and achieves an f1 constituency score of 83.6%. this is an improvement over 81.2% accuracy for the baseline, which makes little or no use of morphological information. the second model uses a reranking approach to add arbitrary global features of parse trees to the morphological model. the reranking model reaches 85.1% f1 accuracy on the spanish parsing task. the resulting model for spanish parsing combines an approach that specifically targets morphological information with an approach that makes use of general structural features.
classummary: introducing discussion summarization to online classrooms. this paper describes a novel summarization system, classummary, for interactive online classroom discussions. this system is originally designed for open source software (oss) development forums. however, this new application provides valuable feedback on designing summarization systems and applying them to everyday use, in addition to the traditional natural language processing evaluation methods. in our demonstration at hlt, new users will be able to direct this summarizer themselves.
learning a spelling error model from search query logs. applying the noisy channel model to search query spelling correction requires an error model and a language model. typically, the error model relies on a weighted string edit distance measure. the weights can be learned from pairs of misspelled words and their corrections. this paper investigates using the expectation maximization algorithm to learn edit distance weights directly from search query logs, without relying on a corpus of paired words.
learning mixed initiative dialog strategies by using reinforcement learning on both conversants. this paper describes an application of reinforcement learning to determine a dialog policy for a complex collaborative task where policies for both the system and a proxy for a user of the system are learned simultaneously. with this approach a useful dialog policy is learned without the drawbacks of other approaches that require significant human interaction. the specific task that the agents were trained on was chosen for its complexity and requirement that both conversants bring task knowledge to the interaction, thus ensuring its collaborative nature. the results of our experiment show that you can use reinforcement learning to create an effective dialog policy, which employs a mixed initiative strategy, without the drawbacks of large amounts of data or significant human input.
emotions from text: machine learning for text-based emotion prediction. in addition to information, text contains attitudinal, and more specifically, emotional content. this paper explores the text-based emotion prediction problem empirically, using supervised machine learning with the snow learning architecture. the goal is to classify the emotional affinity of sentences in the narrative domain of children's fairy tales, for subsequent usage in appropriate expressive rendering of text-to-speech synthesis. initial experiments on a preliminary data set of 22 fairy tales show encouraging results over a na&iuml;ve baseline and bow approach for classification of emotional versus non-emotional contents, with some dependency on parameter tuning. we also discuss results for a tripartite model which covers emotional valence, as well as feature set alternations. in addition, we present plans for a more cognitively sound sequential model, taking into consideration a larger set of basic emotions.
analyzing models for semantic role assignment using confusability. we analyze models for semantic role assignment by defining a meta-model that abstracts over features and learning paradigms. this meta-model is based on the concept of role confusability, is defined in information-theoretic terms, and predicts that roles realized by less specific grammatical functions are more difficult to assign. we find that confusability is strongly correlated with the performance of classifiers based on syntactic features, but not for classifiers including semantic features. this indicates that syntactic features approximate a description of grammatical functions, and that semantic features provide an independent second view on the data.
a practically unsupervised learning method to identify single-snippet answers to definition questions on the web. we present a practically unsupervised learning method to produce single-snippet answers to definition questions in question answering systems that supplement web search engines. the method exploits on-line encyclopedias and dictionaries to generate automatically an arbitrarily large number of positive and negative definition examples, which are then used to train an svm to separate the two classes. we show experimentally that the proposed method is viable, that it outperforms the alternative of training the system on questions and news articles from trec, and that it helps the search engine handle definition questions significantly better.
robust named entity extraction from large spoken archives. traditional approaches to information extraction (ie) from speech input simply consist in applying text based methods to the output of an automatic speech recognition (asr) system. if it gives satisfaction with low word error rate (wer) transcripts, we believe that a tighter integration of the ie and asr modules can increase the ie performance in more difficult conditions. more specifically this paper focuses on the robust extraction of named entities from speech input where a temporal mismatch between training and test corpora occurs. we describe a named entity recognition (ner) system, developed within the french rich broadcast news transcription program ester, which is specifically optimized to process asr transcripts and can be integrated into the search process of the asr modules. finally we show how some metadata information can be collected in order to adapt ner and asr models to new conditions and how they can be used in a task of named entity indexation of spoken archives.
neuralign: combining word alignments using neural networks. this paper presents a novel approach to combining different word alignments. we view word alignment as a pattern classification problem, where alignment combination is treated as a classifier ensemble, and alignment links are adorned with linguistic features. a neural network model is used to learn word alignments from the individual alignment systems. we show that our alignment combination approach yields a significant 20--34% relative error reduction over the best-known alignment combination technique on english-spanish and english-chinese data.
tell me what you do and i'll tell you what you are: learning occupation-related activities for biographies. biography creation requires the identification of important events in the life of the individual in question. while there are events such as birth and death that apply to everyone, most of the other activities tend to be occupation-specific. hence, occupation gives important clues as to which activities should be included in the biography. we present techniques for automatically identifying which important events apply to the general population, which ones are occupation-specific, and which ones are person-specific. we use the extracted information as features for a multi-class svm classifier, which is then used to automatically identify the occupation of a previously unseen individual. we present experiments involving 189 individuals from ten occupations, and we show that our approach accurately identifies general and occupation-specific activities and assigns unseen individuals to the correct occupations. finally, we present evidence that our technique can lead to efficient and effective biography generation relying only on statistical techniques.
alignment link projection using transformation-based learning. we present a new word-alignment approach that learns errors made by existing word alignment systems and corrects them. by adapting transformation-based learning to the problem of word alignment, we project new alignment links from already existing links, using features such as pos tags. we show that our alignment link projection approach yields a significantly lower alignment error rate than that of the best performing alignment system (22.6% relative reduction on english-spanish data and 23.2% relative reduction on english-chinese data).
a cost-benefit analysis of hybrid phone-manner representations for asr. in the past decade, several researchers have started reinvestigating the use of sub-phonetic models for lexical representations within automatic speech recognition systems. lest history repeat itself, it may be instructive to mine the further past for models of lexical representations in the lexical access literature. in this work, we re-evaluate the model of briscoe (1989), in which a hybrid strategy of lexical representation between phones and manner classes is promoted. while many of briscoe's assumptions do not match up with current asr processing models, we show that his conclusions are essentially correct, and that reconsidering this structure for asr lexica is an appropriate avenue for future asr research.
predicting sentences using n-gram language models. we explore the benefit that users in several application areas can experience from a "tab-complete" editing assistance function. we develop an evaluation metric and adapt n-gram language models to the problem of predicting the subsequent words, given an initial text fragment. using an instance-based method as baseline, we empirically study the predictability of call-center emails, personal emails, weather reports, and cooking recipes.
disambiguating toponyms in news. this research is aimed at the problem of disambiguating toponyms (place names) in terms of a classification derived by merging information from two publicly available gazetteers. to establish the difficulty of the problem, we measured the degree of ambiguity, with respect to a gazetteer, for toponyms in news. we found that 67.82% of the toponyms found in a corpus that were ambiguous in a gazetteer lacked a local discriminator in the text. given the scarcity of human-annotated data, our method used unsupervised machine learning to develop disambiguation rules. toponyms were automatically tagged with information about them found in a gazetteer. a toponym that was ambiguous in the gazetteer was automatically disambiguated based on preference heuristics. this automatically tagged data was used to train a machine learner, which disambiguated toponyms in a human-annotated news corpus at 78.5% accuracy.
the vocal joystick: a voice-based human-computer interface for individuals with motor impairments. we present a novel voice-based human-computer interface designed to enable individuals with motor impairments to use vocal parameters for continuous control tasks. since discrete spoken commands are ill-suited to such tasks, our interface exploits a large set of continuous acoustic-phonetic parameters like pitch, loudness, vowel quality, etc. their selection is optimized with respect to automatic recognizability, communication bandwidth, learnability, suitability, and ease of use. parameters are extracted in real time, transformed via adaptation and acceleration, and converted into continuous control signals. this paper describes the basic engine, prototype applications (in particular, voice-based web browsing and a controlled trajectory-following task), and initial user studies confirming the feasibility of this technology.
improving statistical mt through morphological analysis. in statistical machine translation, estimating word-to-word alignment probabilities for the translation model can be difficult due to the problem of sparse data: most words in a given corpus occur at most a handful of times. with a highly inflected language such as czech, this problem can be particularly severe. in addition, much of the morphological variation seen in czech words is not reflected in either the morphology or syntax of a language like english. in this work, we show that using morphological analysis to modify the czech input can improve a czech-english machine translation system. we investigate several different methods of incorporating morphological information, and show that a system that combines these methods yields the best results. our final system achieves a bleu score of .333, as compared to .270 for the baseline word-to-word system.
robust textual inference via graph matching. we present a system for deciding whether a given sentence can be inferred from text. each sentence is represented as a directed graph (extracted from a dependency parser) in which the nodes represent words or phrases, and the links represent syntactic and semantic relationships. we develop a learned graph matching approach to approximate entailment using the amount of the sentence's semantic content which is contained in the text. we present results on the recognizing textual entailment dataset (dagan et al., 2005), and show that our approach outperforms bag-of-words and tf-idf models. in addition, we explore common sources of errors in our approach and how to remedy them.
recognising textual entailment with logical inference. we use logical inference techniques for recognising textual entailment. as the performance of theorem proving turns out to be highly dependent on not readily available background knowledge, we incorporate model building, a technique borrowed from automated reasoning, and show that it is a useful robust method to approximate entailment. finally, we use machine learning to combine these deep semantic analysis techniques with simple shallow word overlap; the resulting hybrid model achieves high accuracy on the rte testset, given the state of the art. our results also show that the different techniques that we employ perform very differently on some of the subsets of the rte corpus and as a result, it is useful to use the nature of the dataset as a feature.
comparing and combining finite-state and context-free parsers. in this paper, we look at comparing high-accuracy context-free parsers with high-accuracy finite-state (shallow) parsers on several shallow parsing tasks. we show that previously reported comparisons greatly under-estimated the performance of context-free parsers for these tasks. we also demonstrate that context-free parsers can train effectively on relatively little training data, and are more robust to domain shift for shallow parsing tasks than has been previously reported. finally, we establish that combining the output of context-free and finite-state parsers gives much higher results than the previous-best published results, on several common tasks. while the efficiency benefit of finite-state models is inarguable, the results presented here show that the corresponding cost in accuracy is higher than previously thought.
automatic question generation for vocabulary assessment. in the reap system, users are automatically provided with texts to read targeted to their individual reading levels. to find appropriate texts, the user's vocabulary knowledge must be assessed. we describe an approach to automatically generating questions for vocabulary assessment. traditionally, these assessments have been hand-written. using data from wordnet, we generate 6 types of vocabulary questions. they can have several forms, including wordbank and multiple-choice. we present experimental results that suggest that these automatically-generated questions give a measure of vocabulary skill that correlates well with subject performance on independently developed human-written questions. in addition, strong correlations with standardized vocabulary tests point to the validity of our approach to automatic assessment of word knowledge.
cluster-specific named entity transliteration. existing named entity (ne) transliteration approaches often exploit a general model to transliterate nes, regardless of their origins. as a result, both a chinese name and a french name (assuming it is already translated into chinese) will be translated into english using the same model, which often leads to unsatisfactory performance. in this paper we propose a cluster-specific ne transliteration framework. we group name origins into a smaller number of clusters, then train transliteration and language models for each cluster under a statistical machine translation framework. given a source ne, we first select appropriate models by classifying it into the most likely cluster, then we transliterate this ne with the corresponding models. we also propose a phrase-based name transliteration model, which effectively combines context information for transliteration. our experiments showed substantial improvement on the transliteration accuracy over a state-of-the-art baseline system, significantly reducing the transliteration character error rate from 50.29% to 12.84%.
semantic similarity for detecting recognition errors in automatic speech transcripts. browsing through large volumes of spoken audio is known to be a challenging task for end users. one way to alleviate this problem is to allow users to gist a spoken audio document by glancing over a transcript generated through automatic speech recognition. unfortunately, such transcripts typically contain many recognition errors which are highly distracting and make gisting more difficult. in this paper we present an approach that detects recognition errors by identifying words which are semantic outliers with respect to other words in the transcript. we describe several variants of this approach. we investigate a wide range of evaluation measures and we show that we can significantly reduce the number of errors in content words, with the trade-off of losing some good content words.
knowitnow: fast, scalable information extraction from the web. numerous nlp applications rely on search-engine queries, both to extract information from and to compute statistics over the web corpus. but search engines often limit the number of available queries. as a result, query-intensive nlp applications such as information extraction (ie) distribute their query load over several days, making ie a slow, offline process.this paper introduces a novel architecture for ie that obviates queries to commercial search engines. the architecture is embodied in a system called knowitnow that performs high-precision ie in minutes instead of days. we compare knowitnow experimentally with the previously-published knowitall system, and quantify the tradeoff between recall and speed. knowitnow's extraction rate is two to three orders of magnitude higher than knowitall's.
using names and topics for new event detection. new event detection (ned) involves monitoring chronologically-ordered news streams to automatically detect the stories that report on new events. we compare two stories by finding three cosine similarities based on names, topics and the full text. these additional comparisons suggest treating the ned problem as a binary classification problem with the comparison scores serving as features. the classifier models we learned show statistically significant improvement over the baseline vector space model system on all the collections we tested, including the latest tdt5 collection.the presence of automatic speech recognizer (asr) output of broadcast news in news streams can reduce performance and render our named entity recognition based approaches ineffective. we provide a solution to this problem achieving statistically significant improvements.
a salience driven approach to robust input interpretation in multimodal conversational systems. to improve the robustness in multimodal input interpretation, this paper presents a new salience driven approach. this approach is based on the observation that, during multimodal conversation, information from deictic gestures (e.g., point or circle) on a graphical display can signal a part of the physical world (i.e., representation of the domain and task) of the application which is salient during the communication. this salient part of the physical world will prime what users tend to communicate in speech and in turn can be used to constrain hypotheses for spoken language understanding, thus improving overall input interpretation. our experimental results have indicated the potential of this approach in reducing word error rate and improving concept identification in multimodal conversation.
multi-lingual coreference resolution with syntactic features. in this paper, we study the impact of a group of features extracted automatically from machine-generated parse trees on coreference resolution. one focus is on designing syntactic features using the binding theory as the guideline to improve pronoun resolution, although linguistic phenomenon such as apposition is also modeled. these features are applied to the arabic, chinese and english coreference resolution systems and their effectiveness is evaluated on data from the automatic content extraction (ace) task. the syntactic features improve the arabic and english systems significantly, but play a limited role in the chinese one. detailed analyses are done to understand the syntactic features' impact on the three coreference systems.
the hiero machine translation system: extensions, evaluation, and analysis. hierarchical organization is a well known property of language, and yet the notion of hierarchical structure has been largely absent from the best performing machine translation systems in recent community-wide evaluations. in this paper, we discuss a new hierarchical phrase-based statistical machine translation system (chiang, 2005), presenting recent extensions to the original proposal, new evaluation results in a community-wide evaluation, and a novel technique for fine-grained comparative analysis of mt systems.
a robust combination strategy for semantic role labeling. this paper focuses on semantic role labeling using automatically-generated syntactic information. a simple and robust strategy for system combination is presented, which allows to partially recover from input parsing errors and to significantly boost results of individual systems. this combination scheme is also very flexible since the individual systems are not required to provide any information other than their solution. extensive experimental evaluation in the conll-2005 shared task framework supports our previous claims. the proposed architecture outperforms the best results reported in that evaluation exercise.
identifying sources of opinions with conditional random fields and extraction patterns. recent systems have been developed for sentiment classification, opinion recognition, and opinion analysis (e.g., detecting polarity and strength). we pursue another aspect of opinion analysis: identifying the sources of opinions, emotions, and sentiments. we view this problem as an information extraction task and adopt a hybrid approach that combines conditional random fields (lafferty et al., 2001) and a variation of autoslog (riloff, 1996a). while crfs model source identification as a sequence tagging task, autoslog learns extraction patterns. our results show that the combination of these two methods performs better than either one alone. the resulting system identifies opinion sources with 79.3% precision and 59.5% recall using a head noun matching measure, and 81.2% precision and 60.6% recall using an overlap measure.
a generalized framework for revealing analogous themes across related topics. this work addresses the task of identifying thematic correspondences across sub-corpora focused on different topics. we introduce an unsupervised algorithmic framework based on distributional data clustering, which generalizes previous initial works on this task. the empirical results reveal interesting commonalities of different religions. we evaluate the results through measuring the overlap of our clusters with clusters compiled manually by experts. the tested variants of our framework are shown to outperform alternative methods applicable to the task.
a methodology for extrinsically evaluating information extraction performance. this paper reports a preliminary study addressing two challenges in measuring the effectiveness of information extraction (ie) technology:&bull; developing a methodology for extrinsic evaluation of ie; and,&bull; estimating the impact of improving ie technology on the ability to perform an application task.the methodology described can be employed for further controlled experiments regarding information extraction.
hmm word and phrase alignment for statistical machine translation. hmm-based models are developed for the alignment of words and phrases in bitext. the models are formulated so that alignment and parameter estimation can be performed efficiently. we find that chinese-english word alignment performance is comparable to that of ibm model-4 even over large training bitexts. phrase pairs extracted from word alignments generated under the model can also be used for phrase-based translation, and in chinese to english and arabic to english translation, performance is comparable to systems based on model-4 alignments. direct phrase pair induction under the model is described and shown to improve translation performance.
securing web access with dce. internet tools, especially web browsers and servers, are being widely used for information access. however, these tools have some limitations in terms of the security available for those information accesses and of the robustness and availability of the infrastructure used to provide that security. this paper describes work done to utilize the security services and infrastructure of the open software foundation (osf) distributed computing environment (dce) to secure web accesses. this work was done as part of an advanced technology offering (ato) by the osf research institute jointly with gradient technologies inc. and other ato sponsors. a practical implementation has been completed. these combined technologies allow users to securely access both web documents and application servers from a variety of desktop systems using standard, off-the-shelf web browsers. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
reducing the cost of security in link-state routing. security in link-state routing protocols is a feature that is both desirable and costly. this paper examines the cost of security and presents two techniques for efficient and secure processing of link state updates. the first technique is geared towards a relatively stable internetwork environment while the second is designed with a more volatile environment in mind.
improved proxy re-encryption schemes with applications to secure distributed storage. in 1998, blaze, bleumer, and strauss (bbs) proposed an application called atomic proxy re-encryption, in which a semitrusted proxy converts a ciphertext for alice into a ciphertext for bob without seeing the underlying plaintext. we predict that fast and secure re-encryption will become increasingly popular as a method for managing encrypted file systems. although efficiently computable, the wide-spread adoption of bbs re-encryption has been hindered by considerable security risks. following recent work of dodis and ivan, we present new re-encryption schemes that realize a stronger notion of security and demonstrate the usefulness of proxy re-encryption as a method of adding access control to a secure file system. performance measurements of our experimental file system demonstrate that proxy re-encryption can work effectively in practice.
probable plaintext cryptanalysis of the ip security protocols. the internet engineering task force (ietf) is in the process of adopting standards for ip-layer encryption and authentication (ipsec). we describe how "probable plaintext" can be used to aid in cryptanalytic attacks, and analyze the protocol to show how much probable plaintext is available. we also show how traffic analysis is a powerful aid to the cryptanalyst. we conclude by outlining some likely changes to the underlying protocols that may strengthen them against these attacks.
an interface specification language for automatically analyzing cryptographic protocols. this paper describes a simple interface specification language (isl) for cryptographic protocols and their desired properties, and an automatic authentication protocol analyzer (aapa) that automatically either proves-using an extension of the gong, needham, yahalom (1990) belief logic-that specified protocols have their desired properties, or identifies precisely where these proof attempts fail. the isl and the aapa make it easy for protocol designers to incorporate formal analysis into the protocol design process, where they clarify designs and reveals a large class of common errors. the isl and the aapa have already shown potential deficiencies in published protocols and been useful in designing new protocols.
efficient distribution of key chain commitments for broadcast authentication in distributed sensor networks. broadcast authentication is a fundamental security service in distributed sensor networks. a scheme named $\mu$tesla has been proposed for efficient broadcast authentication in such networks. however, $\mu$tesla requires initial distribution of certain information based on unicast between the base station and each sensor node before the actual authentication of broadcast messages. due to the limited bandwidth in wireless sensor networks, this initial unicast-based distribution severely limits the application of $\mu$tesla in large sensor networks. this paper presents a novel technique to replace the unicast-based initialization with a broadcast-based one. as a result, $\mu$tesla can be used in a sensor network with a large amount of sensors, as long as the message from the base station can reach these sensor nodes. this paper further explores several techniques that improve the performance, the robustness, as well as the security of the proposed method. the resulting protocol satisfies several nice properties, including low overhead, tolerance of message loss, scalability to large networks, and resistance to replay attacks as well as some known denial of service (dos) attacks.
bluebox: a policy-driven, host-based intrusion detection system. detecting attacks against systems has, in practice, largely been delegated to sensors, such as network intrustion detection systems. however, due to the inherent limitations of these systems and the increasing use of encryption in communication, intrusion detection and prevention have once again moved back to the host systems themselves. in this paper, we describe our experiences with building bluebox, a host-based intrusion detection system. our approach, based on the technique of system call introspection, can be viewed as creating an infrastructure for defining and enforcing very fine-grained process capabilities in the kernel. these capabilities are specified as a set of rules (policies) for regulating access to system resources on a per executable basis. the language for expressing the rules is intuitive and sufficiently expressive to effectively capture security boundaries.we have prototyped our approach on linux operating system kernel and have built rule templates for popular daemons such as apache and wu-ftpd. our design has been validated by testing against a comprehensive database of known attacks. our system has been designed to minimize the kernel changes and performance impact and thus can be ported easily to new kernels. we describe the motivation and rationale behind bluebox, its design, implementation on linux, and how it relates to prior work on detecting and preventing intrusions on host systems.
blocking java applets at the firewall. this paper explores the problem of protecting a site on the internet against hostile external java applets while allowing trusted internal applets to run. with careful implementation, a site can be made resistant to current java security weaknesses as well as those yet to be discovered. in addition, we describe a new attack on certain sophisticated firewalls that is most effectively realized as a java applet.
performance analysis of tls web servers. tls is the protocol of choice for securing today's e-commerce and online transactions but adding tls to a web server imposes a significant overhead relative to an insecure web server on the same platform. we perform a comprehensive study of the performance costs of tls. our methodology is to profile tls web servers with trace-driven workloads, replace individual components inside tls with no-ops, and measure the observed increase in server throughput. we estimate the relative costs of each tls processing stage, identifying the areas for which future optimizations would be worthwhile. our results show that while the rsa operations represent the largest performance cost in tls web servers, they do not solely account for tls overhead. rsa accelerators are effective for e-commerce site workloads since they experience low tls session reuse. accelerators appear to be less effective for sites where all the requests are handled by a tls server because they have a higher session reuse rate. in this case, investing in a faster cpu might provide a greater boost in performance. our experiments show that having a second cpu is at least as useful as an rsa accelerator. our results seem to suggest that, as cpus become faster, the cryptographic costs of tls will become dwarfed by the cpu costs of the nonsecurity aspects of a web server. optimizations aimed at general purpose web servers should continue to be a focus of research and would benefit secure web servers as well.
an algebraic approach to ip traceback. we present a new solution to the problem of determining the path a packet traversed over the internet (called the traceback problem) during a denial-of-service attack. this article reframes the traceback problem as a polynomial reconstruction problem and uses algebraic techniques from coding theory and learning theory to provide robust methods of transmission and reconstruction.
misplaced trust: kerberos 4 session keys. one of the commonly accepted principles of software design for security is that making the source code openly available leads to better security. the presumption is that the open publication of source code will lead others to review the code for errors, however this openness is no guarantee of correctness. one of the most widely published and used pieces of security software in recent memory is the mit implementation of the kerberos authentication protocol. in the design of the protocol, random session keys are the basis for establishing the authenticity of service requests. because of the way that the kerberos version 4 implementation selected its random keys, the secret keys could easily be guessed in a matter of seconds. this paper discusses the difficulty of generating good random numbers, the mistakes that were made in implementing kerberos version 4, and the breakdown of software engineering that allowed this flaw to remain unfixed for ten years. we discuss this as a particularly notable example of the need to examine security-critical code carefully, even when it is made publicly available.
continuous assessment of a unix configuration: integrating intrusion detection and configuration analysis. computer security is a topic of growing concern because, on the one hand, the power of computers continues to increase at exponential speed and all computers are virtually connected to each other and because, on the other hand, the lack of reliability of software systems may cause dramatic and unrecoverable damage to computer systems and hence to the newly emerging computerized society. among the possible approaches to improve the current situation, expert systems have been advocated to be an important one. typical tasks that such expert systems attempt to achieve include finding system vulnerabilities and detecting malicious behaviors of users.in this paper, we extend our intrusion detection system asax with a deductive subsystem that allows us to assess the security level of a software configuration on a real time basis. by coupling the two subsystems --- intrusion detection and configuration analysis --- we moreover achieve a better tuning of the intrusion detection since the system has only to enable intrusion detection rules that are specifically required by the current state of the configuration. we also report some preliminary performance measurements, which suggest that our approach can be practical in real life contexts.
authentication and integrity in outsourced databases. in the outsourced database (odb) model, entities outsource their data management needs to a third-party service provider. such a service provider offers mechanisms for its clients to create, store, update, and access (query) their databases. this work provides mechanisms to ensure data integrity and authenticity for outsourced databases. specifically, this article provides mechanisms that assure the querier that the query results have not been tampered with and are authentic (with respect to the actual data owner). it investigates both the security and efficiency aspects of the problem and constructs several secure and practical schemes that facilitate the integrity and authenticity of query replies while incurring low computational and communication costs.
experimental results of covert channel limitation in one-way communication systems. with the increasing growth of electronic communications, it is becoming important to provide a mechanism for enforcing various security policies on network communications. this paper discusses our implementation of several previously proposed protocols that enforce the bell-lapadula (1973) security model. we also introduce a new protocol called "quantized pump" that offers several advantages, and present experimental results to support our claims.
file system design with assured delete. this paper describes a system that supports high availability of data, until the data should be expunged, at which time the system makes it impossible to recover the data. this design supports two types of assured delete; where the expiration time is known at file creation, and on-demand delete of individual files. the design assures previous work has described how to do this when the expiration time of a file is known at file creation time, and was particularly suited to supporting many independent clients. this paper reviews that work, but also describes how to support on-demand deletion of individual files.
distributed authentication in kerberos using public key cryptography. in this work we describe a method for fully distributed authentication using public key cryptography within the kerberos ticket framework. by distributing most of the authentication workload away from the trusted intermediary and to the communicating parties, significant enhancements to security and scalability can be achieved as compared to kerberos v5. privacy of kerberos clients is also enhanced. a working implementation of this extended protocol has been developed, and a migration plan is proposed for a transition from traditional to public key based kerberos.
securing the nimrod routing architecture. this paper describes the work undertaken to secure nimrod, a complex and sophisticated routing system that unifies interior and exterior routing functions. the focus of this work is countering attacks that would degrade or deny service to network subscribers. the work began with an analysis of security requirements for nimrod, based on a hybrid approach that refines top-down requirements generation with an understanding of attack scenarios and the capabilities and limitations of countermeasures. the countermeasures selected for use here include several newly developed sequence integrity mechanisms, plus a protocol for shared secret establishment. a novel aspect of this work is the protection of subscriber traffic in support of the overall communication availability security goal.
trust models in ice-tel. public key certification provides mechanisms that can be used to build truly scaleable security services, such as allowing people who have never met to have assurance of each others identity. authentication involves syntactic verification of a certificate chain followed by a semantic look at the policies under which the certificates were issued. this results in a level of assurance that the identity of the person to be authenticated is an accurate description of the person involved, and requires verifiers to specify who they trust and what they trust them to do. two widely discussed mechanisms for specifying this trust, the pem and pgp trust models, approach the problem from fundamentally different directions. the ec funded ice-tel project, which is deploying a security infrastructure and application set for the european research community, has described a new trust model that attempts to be equally applicable to organization-centric pem users and user-centric pgp users.
teapot: language support for writing memory coherence protocols. recent shared-memory parallel computer systems offer the exciting possibility of customizing memory coherence protocols to fit an application's semantics and sharing patterns. custom protocols have been used to achieve message-passing performance---while retaining the convenient programming model of a global address space---and to implement high-level language constructs. unfortunately, coherence protocols written in a conventional language such as c are difficult to write, debug, understand, or modify. this paper describes teapot, a small, domain-specific language for writing coherence protocols. teapot uses continuations to help reduce the complexity of writing protocols. simple static analysis in the teapot compiler eliminates much of the overhead of continuations and results in protocols that run nearly as fast as hand-written c code. a teapot specification can be compiled both to an executable coherence protocol and to input for a model checking system, which permits the specification to be verified. we report our experiences coding and verifying several protocols written in teapot, along with measurements of the overhead incurred by writing a protocol in a higher-level language.
selective interpretation as a technique for debugging computationally intensive programs. as part of rice university's project to build a programming environment for scientific software, we have built a facility for program execution that solves some of the problems inherent in debugging large, computationally intensive programs. by their very nature such programs do not lend themselves to full-scale interpretation. in moderation however, interpretation can be extremely useful during the debugging process. in addition to discussing the particular benefits that we expect from interpretation, this paper addresses how interpretive techniques can be effectively used in conjunction with the execution of compiled code. the same implementation technique that permits interpretation to be incorporated as part of execution will also permit the execution facility to be used for debugging parallel programs running on a remote machine.
analysis of pointers and structures. compilers can make good use of knowledge about the shape of data structures and the values that pointers assume during execution. we present results which show how a compiler can automatically determine some of this information. we believe that practical analyses based on this work can be used in compilers for languages that provide linked data structures. the analysis we present obtains useful information about linked data structures. we summarize unbounded data structures by taking advantage of structure present in the original program. the worst-case time bounds for a naive algorithm are high-degree polynomial, but for the expected (sparse) case we have an efficient algorithm. previous work has addressed time bounds rarely, and efficient algorithms not at all. the quality of information obtained by this analysis appears to be (generally) an improvement on what is obtained by existing techniques. a simple extension obtains aliasing information for entire data structures that previously was obtained only through declarations. previous work has shown that this information, however obtained, allows worthwhile optimization.
partial dead code elimination using slicing transformations. we present an approach for optimizing programs that uncovers additional opportunities for optimization of a statement by predicating the statement. in this paper predication algorithms for achieving partial dead code elimination (pde) are presented. the process of predication embeds a statement in a control flow structure such that the statement is executed only if the execution follows a path along which the value computed by the statement is live. the control flow restructuring performed to achieve predication is expressed through slicing transformations. this approach achieves pde that is not realizable by existing algorithms. we prove that our algorithm never increases the operation count along any path, and that for acyclic code all partially dead statements are eliminated. the slicing transformation that achieves predication introduces into the program additional conditional branches. these branches are eliminated in a branch deletion step based upon code duplication. we also show how pde can be used by acyclic schedulers for vliw processors to reduce critical path lengths along frequently executed paths.
an experimental analysis of self-adjusting computation. dependence graphs and memoization can be used to efficiently update the output of a program as the input changes dynamically. recent work has studied techniques for combining these approaches to effectively dynamize a wide range of applications. toward this end various theoretical results were given. in this paper we describe the implementation of a library based on these ideas, and present experimental results on the efficiency of this library on a variety of applications. the results of the experiments indicate that the approach is effective in practice, often requiring orders of magnitude less time than recomputing the output from scratch. we believe this is the first experimental evidence that incremental computation of any type is effective in practice for a reasonably broad set of applications.
abcd: eliminating array bounds checks on demand. to guarantee typesafe execution, java and other strongly typed languages require bounds checking of array accesses. because array-bounds checks may raise exceptions, they block code motion of instructions with side effects, thus preventing many useful code optimizations, such as partial redundancy elimination or instruction scheduling of memory operations. furthermore, because it is not expressible at bytecode level, the elimination of bounds checks can only be performed at run time, after the bytecode program is loaded. using existing powerful bounds-check optimizers at run time is not feasible, however, because they are too heavyweight for the dynamic compilation setting. abcd is a light-weight algorithm for elimination of array bounds checks on demand. its design emphasizes simplicity and efficiency. in essence, abcd works by adding a few edges to the ssa value graph and performing a simple traversal of the graph. despite its simplicity, abcd is surprisingly powerful. on our benchmarks, abcd removes on average 45% of dynamic bound check instructions, sometimes achieving near-ideal optimization. the efficiency of abcd stems from two factors. first, abcd works on a sparse representation. as a result, it requires on average fewer than 10 simple analysis steps per bounds check. second, abcd is demand-driven. it can be applied to a set of frequently executed (hot) bounds checks, which makes it suitable for the dynamic-compilation setting, in which compile-time cost is constrained but hot statements are known.
first-class data-type representations in schemexerox. in most programming language implementations, the compiler has detailed knowledge of the representations of and operations on primitive data typed and data-type constructors. in schemexerox, this knowledge is almost entirely external to the compiler, in ordinary, procedural user code. the primitive representations and operations are embodied in first-class &ldquo;representation types&rdquo; that are constructed and implemented in an abstract and high-level fashion. despite this abstractness, a few generally-useful optimizing transformations are sufficient to allow the schemexerox compiler to generate efficient code for the primitive operations, essentially as good as could be achieved using more contorted, traditional techniques.
fast, effective code generation in a just-in-time java compiler. a "just-in-time" (jit) java compiler produces native code from java byte code instructions during program execution. as such, compilation speed is more important in a java jit compiler than in a traditional compiler, requiring optimization algorithms to be lightweight and effective. we present the structure of a java jit compiler for the intel architecture, describe the lightweight implementation of jit compiler optimizations (e.g., common subexpression elimination, register allocation, and elimination of array bounds checking), and evaluate the performance benefits and tradeoffs of the optimizations. this jit compiler has been shipped with version 2.5 of intel's vtune for java product.
branch prediction for free. many compilers rely on branch prediction to improve program performance by identifying frequently executed regions and by aiding in scheduling instructions.profile-based predictors require a time-consuming and inconvenient compile-profile-compile cycle in order to make predictions. we present a program-based branch predictor that performs well for a large and diverse set of programs written in c and fortran. in addition to using natural loop analysis to predict branches that control the iteration of loops, we focus on heuristics for predicting non-loop branches, which dominate the dynamic branch count of many programs. the heuristics are simple and require little program analysis, yet they are effective in terms of coverage and miss rate. although program-based prediction does not equal the accuracy of profile-based prediction, we believe it reaches a sufficiently high level to be useful. additional type and semantic information available to a compiler would enhance our heuristics.
unification-based pointer analysis with directional assignments. this paper describes a new algorithm for flow and context insensitive pointer analysis of c programs. our studies show that the most common use of pointers in c programs is in passing the addresses of composite objects or updateable values as arguments to procedures. therefore, we have designed a low-cost algorithm that handles this common case accurately. in terms of both precision and running time, this algorithm lies between steensgaard's algorithm, which treats assignments bi-directionally using unification, and andersen's algorithm, which treats assignments directionally using subtyping. our &ldquo;one level flow&rdquo; algorithm uses a restricted form of subtyping to avoid unification of symbols at the top levels of pointer chains in the points-to graph, while using unification elsewhere in the graph. the method scales easily to large programs. for instance, we are able to analyze a 1.4 mloc (million lines of code) program in two minutes, using less than 200mb of memory. at the same time, the precision of our algorithm is very close to that of andersen's algorithm. on all of the integer benchmark programs from spec95, the one level flow algorithm and andersen's algorithm produce either identical or essentially identical points-to information. therefore, we claim that our algorithm provides a method for obtaining precise flow-insensitive points-to information for large c programs.
detection and recovery of endangered variables caused by instruction scheduling. instruction scheduling re-orders and interleaves instruction sequences from different source statements. this impacts the task of a symbolic debugger, which attempts to present the user a picture of program execution that matches the source program. at a breakpoint b, if the value in the run-time location of a variable v may not correspond to the value the user expects v to have, then this variable is endangered at b. this paper describes an approach to detecting and recovering endangered variables caused by instruction scheduling. we measure the effects of instruction scheduling on a symbolic debugger's ability to recover source values at a breakpoint. this paper reports measurements for three c programs from the spec suite and a collection of programs from the numerical recipes, which have been compiled with a variant of a commercial c compiler.
automatic predicate abstraction of c programs. model checking has been widely successful in validating and debugging designs in the hardware and protocol domains. however, state-space explosion limits the applicability of model checking tools, so model checkers typically operate on abstractions of systems. recently, there has been significant interest in applying model checking to software. for infinite-state systems like software, abstraction is even more critical. techniques for abstracting software are a prerequisite to making software model checking a reality. we present the first algorithm to automatically construct a predicate abstraction of programs written in an industrial programming language such as c, and its implementation in a tool &mdash; c2bp. the c2bp tool is part of the slam toolkit, which uses a combination of predicate abstraction, model checking, symbolic reasoning, and iterative refinement to statically check temporal safety properties of programs. predicate abstraction of software has many applications, including detecting program errors, synthesizing program invariants, and improving the precision of program analyses through predicate sensitivity. we discuss our experience applying the c2bp predicate abstraction tool to a variety of problems, ranging from checking that list-manipulating code preserves heap invariants to finding errors in windows nt device drivers.
software pipelining: an effective scheduling technique for vliw machines. the basic idea behind software pipelining was first developed by patel and davidson for scheduling hardware pipe-lines. as instruction-level parallelism made its way into general-purpose computing, it became necessary to automate scheduling. how and whether instructions can be scheduled statically have major ramifications on the design of computer architectures. rau and glaeser were the first to use software pipelining in a compiler for a machine with specialized hardware designed to support software pipelining. in the meantime, trace scheduling was touted to be the scheduling technique of choice for vliw (very long instruction word) machines. the most important contribution from this paper is to show that software pipelining is effective on vliw machines without complicated hardware support. our understanding of software pipelining subsequently deepened with the work of many others. and today, software pipelining is used in all advanced compilers for machines with instruction-level parallelism, none of which, except the intel itanium, relies on any specialized support for software pipelining.this paper shows that software pipelining is an effective and viable scheduling technique for vliw processors. in software pipelining, iterations of a loop in the source program are continuously initiated at constant intervals, before the preceding iterations complete. the advantage of software pipelining is that optimal performance can be achieved with compact object code.this paper extends previous results of software pipelining in two ways: first, this paper shows that by using an improved algorithm, near-optimal performance can be obtained without specialized hardware. second, we propose a hierarchical reduction scheme whereby entire control constructs are reduced to an object similar to an operation in a basic block. with this scheme, all innermost loops, including those containing conditional statements, can be software pipelined. it also diminishes the start-up cost of loops with small number of iterations. hierarchical reduction complements the software pipelining technique, permitting a consistent performance improvement be obtained.the techniques proposed have been validated by an implementation of a compiler for warp, a systolic array consisting of 10 vliw processors. this compiler has been used for developing a large number of applications in the areas of image, signal and scientific processing.
source-level debugging of scalar optimized code. although compiler optimizations play a crucial role in the performance of modern computer systems, debugger technology has lagged behind in its support of optimization. yet debugging the unoptimized translation is often impossible or futile, so handling of code optimizations in the debugger is necessary. but compiler optimizations make it difficult to provide source-level debugger functionality: global optimizations can cause the runtime value of a variable to be inconsistent with the source-level value expected at a breakpoint; such variables are called endangered variables. a debugger must detect and warn the user of endangered variables otherwise the user may draw incorrect conclusions about the program. this paper presents a new algorithm for detecting variables that are endangered due to global scalar optimization. our approach provides more precise classifications of variables and is still simpler than past approaches. we have implemented and evaluated our techniques in the context of the cmcc optimizing c compiler. we describe the compiler extensions necessary to perform the required bookkeeping of compiler optimization. we present measurements of the effect of optimizations on a debugger's ability to present the expected values of variables to the user.
improving balanced scheduling with compiler optimizations that increase instruction-level parallelism. traditional list schedulers order instructions based on an optimistic estimate of the load latency imposed by the hardware and therefore cannot respond to variations in memory latency caused by cache hits and misses on non-blocking architectures. in contrast, balanced scheduling schedules instructions based on an estimate of the amount of instruction-level parallelism in the program. by scheduling independent instructions behind loads based on what the program can provide, rather than what the implementation stipulates in the best case (i.e., a cache hit), balanced scheduling can hide variations in memory latencies more effectively.since its success depends on the amount of instruction-level parallelism in the code, balanced scheduling should perform even better when more parallelism is available. in this study, we combine balanced scheduling with three compiler optimizations that increase instruction-level parallelism: loop unrolling, trace scheduling and cache locality analysis. using code generated for the dec alpha by the multiflow compiler, we simulated a non-blocking processor architecture that closely models the alpha 21164. our results show that balanced scheduling benefits from all three optimizations, producing average speedups that range from 1.15 to 1.40, across the optimizations. more importantly, because of its ability to tolerate variations in load interlocks, it improves its advantage over traditional scheduling. without the optimizations, balanced scheduled code is, on average, 1.05 times faster than that generated by a traditional scheduler; with them, its lead increases to 1.18.
prefetch inection based on hardware monitoring and object metadata. cache miss stalls hurt performance because of the large gap between memory and processor speeds - for example, the popular server benchmark spec jbb2000 spends 45% of its cycles stalled waiting for memory requests on the itanium® 2 processor. traversing linked data structures causes a large portion of these stalls. prefetching for linked data structures remains a major challenge because serial data dependencies between elements in a linked data structure preclude the timely materialization of prefetch addresses. this paper presents mississippi delta (ms delta), a novel technique for prefetching linked data structures that closely integrates the hardware performance monitor (hpm), the garbage collector's global view of heap and object layout, the type-level metadata inherent in type-safe programs, and jit compiler analysis. the garbage collector uses the hpm's data cache miss information to identify cache miss intensive traversal paths through linked data structures, and then discovers regular distances (deltas) between these linked objects. jit compiler analysis injects prefetch instructions using deltas to materialize prefetch addresses.we have implemented ms delta in a fully dynamic profile-guided optimization system: the starjit dynamic compiler [1] and the orp java virtual machine [9]. we demonstrate a 28-29% reduction in stall cycles attributable to the high-latency cache misses targeted by ms delta and a speedup of 11-14% on the cache miss intensive spec jbb2000 benchmark.
grammatical abstraction and incremental syntax analysis in a language-based editor. processors for programming languages and other formal languages typically use a concrete syntax to describe the user's view of a program and an abstract syntax to represent language structures internally. grammatical abstraction is defined as a relationship between two context-free grammars. it formalizes the notion of one syntax being &ldquo;more abstract&rdquo; than another. two variants of abstraction are presented. weak grammatical abstraction supports (i) the construction during lr parsing of an internal representation that is closely related to the abstract syntax and (ii) incremental lr parsing using that internal representation as its base. strong grammatical abstraction tightens the correspondence so that top-down construction of incrementally-parsable internal representations is possible. these results arise from an investigation into language-based editing systems, but apply to any program that transforms a linguistic object from a representation in its concrete syntax to a representation in its abstract syntax or vice versa.
mimic: a fast system/370 simulator. software simulation of one computer on another tends to be slow. traditional simulators typically execute about 100 instructions on the host machine per instruction simulated. newer simulators reduce the expansion factor to about 10, by saving and reusing translations of individual instructions. this paper describes an experimental simulator which takes the progression one step further, translating groups of instructions as a unit. this approach, combined with flow analysis, reduces the expansion factor to about 4. the new simulator simulates system/370 on a risc, namely the ibm rt pc.
efficient and language-independent mobile programs. this paper evaluates the design and implementation of omniware: a safe, efficient, and language-independent system for executing mobile program modules. previous approaches to implementing mobile code rely on either language semantics or abstract machine interpretation to enforce safety. in the former case, the mobile code system sacrifices universality to gain safety by dictating a particular source language or type system. in the latter case, the mobile code system sacrifices performance to gain safety through abstract machine interpretation.omniware uses software fault isolation, a technology developed to provide safe extension code for databases and operating systems, to achieve a unique combination of language-independence and excellent performance. software fault isolation uses only the semantics of the underlying processor to determine whether a mobile code module can corrupt its execution environment. this separation of programming language implementation from program module safety enables our mobile code system to use a radically simplified virtual machine as its basis for portability. we measured the performance of omniware using a suite of four spec92 programs on the pentium, powerpc, mips, and sparc processor architectures. including the overhead for enforcing safety on all four processors, omnivm executed the benchmark programs within 21% as fast as the optimized, unsafe code produced by the vendor-supplied compiler.
efficient interpretation of prolog programs. the paper focuses on three ideas for solving problems with writing interpreters for the logic programming language prolog in prolog and how to combine these ideas to an interpreter for prolog which is both simple and efficient. the resulting interpreter system can be incorporated into a prolog based on warren's abstract machine and built mostly from existing parts of it. the interpreter has been implemented and is used in a prolog system developed at uppsala university.
effective synchronization removal for java. we present a new technique for removing unnecessary synchronization operations from statically compiled java programs. our approach improves upon current efforts based on escape analysis, as it can eliminate synchronization operations even on objects that escape their allocating threads. it makes use of a compact, equivalence-class-based representation that eliminates the need for fixed point operations during the analysis. we describe and evaluate the performance of an implementation in the marmot native java compiler. for the benchmark programs examined, the optimization removes 100% of the dynamic synchronization operations in single-threaded programs, and 0-99% in multi-threaded programs, at a low cost in additional compilation time and code growth.
compiler and runtime support for efficient software transactional memory. programmers have traditionally used locks to synchronize concurrent access to shared data. lock-based synchronization, however, has well-known pitfalls: using locks for fine-grain synchronization and composing code that already uses locks are both difficult and prone to deadlock. transactional memory provides an alternate concurrency control mechanism that avoids these pitfalls and significantly eases concurrent programming. transactional memory language constructs have recently been proposed as extensions to existing languages or included in new concurrent language specifications, opening the door for new compiler optimizations that target the overheads of transactional memory.this paper presents compiler and runtime optimizations for transactional memory language constructs. we present a high-performance software transactional memory system (stm) integrated into a managed runtime environment. our system efficiently implements nested transactions that support both composition of transactions and partial roll back. our jit compiler is the first to optimize the overheads of stm, and we show novel techniques for enabling jit optimizations on stm operations. we measure the performance of our optimizations on a 16-way smp running multi-threaded transactional workloads. our results show that these techniques enable transactional memory's performance to compete with that of well-tuned synchronization.
interprocedural conditional branch elimination. the existence of statically detectable correlation among conditional branches enables their elimination, an optimization that has a number of benefits. this paper presents techniques to determine whether an interprocedural execution path leading to a conditional branch exists along which the branch outcome is known at compile time, and then to eliminate the branch along this path through code restructuring. the technique consists of a demand driven interprocedural analysis that determines whether a specific branch outcome is correlated with prior statements or branch outcomes. the optimization is performed using a code restructuring algorithm that replicates code to separate out the paths with correlation. when the correlated path is affected by a procedure call, the restructuring is based on procedure entry splitting and exit splitting. the entry splitting transformation creates multiple entries to a procedure, and the exit splitting transformation allows a procedure to return control to one of several return points in the caller. our technique is efficient in that the correlation detection is demand driven, thus avoiding exhaustive analysis of the entire program, and the restructuring never increases the number of operations along a path through an interprocedural control flow graph. we describe the benefits of our interprocedural branch elimination optimization (icbe). our experimental results show that, for the same amount of code growth, the estimated reduction in executed conditional branches is about 2.5 times higher with the icbe optimization than when only intraprocedural conditional branch elimination is applied.
using integer sets for data-parallel program analysis and optimization. in this paper, we describe our experience with using an abstract integer-set framework to develop the rice dhpf compiler, a compiler for high performance fortran. we present simple, yet general formulations of the major computation partitioning and communication analysis tasks as well as a number of important optimizations in terms of abstract operations on sets of integer tuples. this approach has made it possible to implement a comprehensive collection of advanced optimizations in dhpf, and to do so in the context of a more general computation partitioning model than previous compilers. one potential limitation of the approach is that the underlying class of integer set problems is fundamentally unable to represent hpf data distributions on a symbolic number of processors. we describe how we extend the approach to compile codes for a symbolic number of processors, without requiring any changes to the set formulations for the above optimizations. we show experimentally that the set representation is not a dominant factor in compile times on both small and large codes. finally, we present preliminary performance measurements to show that the generated code achieves good speedups for a few benchmarks. overall, we believe we are the first to demonstrate by implementation experience that it is practical to build a compiler for hpf using a general and powerful integer-set framework.
garbage collection and local variable type-precision and liveness in java virtual machines. full precision in garbage collection implies retaining only those heap allocated objects that will actually be used in the future. since full precision is not computable in general, garbage collectors use safe (i.e., conservative) approximations such as reachability from a set of root references. ambiguous roots collectors (commonly called "conservative") can be overly conservative because they overestimate the root set, and thereby retain unexpectedly large amounts of garbage. we consider two more precise collection schemes for java virtual machines (jvms). one uses a type analysis to obtain a type-precise root set (only those variables that contain references); the other adds a live variable analysis to reduce the root set to only the live reference variables. even with the java programming language's strong typing, it turns out that the jvm specification has a feature that makes type-precise root sets difficult to compute. we explain the problem and ways in which it can be solved.our experimental results include measurements of the costs of the type and liveness analyses at load time, of the incremental benefits at run time of the liveness analysis over the type analysis alone, and of various map sizes and counts. we find that the liveness analysis often produces little or no improvement in heap size, sometimes modest improvements, and occasionally the improvement is dramatic. while further study is in order, we conclude that the main benefit of the liveness analysis is preventing bad surprises.
related field analysis. we present an extension of field analysis (sec [4]) called related field analysis which is a general technique for proving relationships between two or more fields of an object. we demonstrate the feasibility and applicability of related field analysis by applying it to the problem of removing array bounds checks. for array bounds check removal, we define a pair of related fields to be an integer field and an array field for which the integer field has a known relationship to the length of the array. this related field information can then be used to remove array bounds checks from accesses to the array field. our results show that related field analysis can remove an average of 50% of the dynamic array bounds checks on a wide range of applications. we describe the implementation of related field analysis in the swift optimizing compiler for java, as well as the optimizations that exploit the results of related field analysis.
load-reuse analysis: design and evaluation. load-reuse analysis finds instructions that repeatedly access the same memory location. this location can be promoted to a register, eliminating redundant loads by reusing the results of prior memory accesses. this paper develops a load-reuse analysis and designs a method for evaluating its precision.in designing the analysis, we aspire for completeness---the goal of exposing all reuse that can be harvested by a subsequent program transformation. for register promotion, a suitable transformation is partial redundancy elimination (pre). to approach the ideal goal of pre-completeness, the load-reuse analysis is phrased as a data-flow problem on a program representation that is path-sensitive, as it detects reuse even when it originates in a different instruction along each control flow path. furthermore, the analysis is comprehensive, as it treats scalar, array and pointer-based loads uniformly.in evaluating the analysis, we compare it with an ideal analysis. by observing the run-time stream of memory references, we collect all pre-exploitable reuse and treat it as the ideal analysis performance. to compare the (static) load-reuse analysis with the (dynamic) ideal reuse, we use an estimator algorithm that computes, given a data-flow solution and a program profile, the dynamic amount of reuse detected by the analysis. we developed a family of estimators that differ in how well they bound the profiling error inherent in the edge profile. by bounding the error, the estimators offer a precise and practical method for determining the run-time optimization benefit.our experiments show that about 55% of loads executed in spec95 exhibit reuse. of those, our analysis exposes about 80%.
on slicing programs with jump statements. program slices have potential uses in many software engineering applications. traditional slicing algorithms, however, do not work correctly on programs that contain explicit jump statements. two similar algorithms were proposed recently to alleviate this problem. both require the flowgraph and the program dependence graph of the program to be modified. in this paper, we propose an alternative algorithm that leaves these graphs intact and uses a separate graph to store the additional required information. we also show that this algorithm permits an extremely efficient, conservative adaptation for use with programs that contain only &ldquo;structured&rdquo; jump statements.
threads cannot be implemented as a library. in many environments, multi-threaded code is written in a language that was originally designed without thread support (e.g. c), to which a library of threading primitives was subsequently added. there appears to be a general understanding that this is not the right approach. we provide specific arguments that a pure library approach, in which the compiler is designed independently of threading issues, cannot guarantee correctness of the resulting code.we first review why the approach almost works, and then examine some of the surprising behavior it may entail. we further illustrate that there are very simple cases in which a pure library-based approach seems incapable of expressing an efficient parallel algorithm.our discussion takes place in the context of c with pthreads, since it is commonly used, reasonably well specified, and does not attempt to ensure type-safety, which would entail even stronger constraints. the issues we raise are not specific to that context.
dynamic program slicing. program slices are useful in debugging, testing, maintenance, and understanding of programs. the conventional notion of a program slice, the static slice, is the set of all statements that might affect the value of a given variable occurrence. in this paper, we investigate the concept of the dynamic slice consisting of all statements that actually affect the value of a variable occurrence for a given program input. the sensitivity of dynamic slicing to particular program inputs makes it more useful in program debugging and testing than static slicing. several approaches for computing dynamic slices are examined. the notion of a dynamic dependence graph and its use in computing dynamic slices is discussed. the dynamic dependence graph may be unbounded in length; therefore, we introduce the economical concept of a reduced dynamic dependence graph, which is proportional in size to the number of dynamic slices arising during the program execution.
constructive real interpretation of numerical programs. we explore the feasibility of providing exact real arithmetic for use in conventional numerical programs. we have built a prototype interpreter which replaces floating point operations with operations on constructive real numbers in the execution of conventional fortran programs. such a facility makes it unnecessary to concern oneself with issues of numerical stability in the solution of small problems. it also provides a useful tool for the development of larger numerical programs.we discuss the computability and algorithmic issues involved in the design of the interpreter, as well as some preliminary experiences and performance measurements.
interprocedural partial redundancy elimination and its application to distributed memory compilation. partial redundancy elimination (pre) is a general scheme for suppressing partial redundancies which encompasses traditional optimizations like loop invariant code motion and redundant code elimination. in this paper we address the problem of performing this optimization interprocedurally. we use interprocedural partial redundancy elimination for placement of communication and communication preprocessing statements while compiling for distributed memory parallel machines.
type inference in the presence of type abstraction. a number of recent programming language designs incorporate a type checking system based on the girard-reynolds polymorphic &lgr;-calculus. this allows the construction of general purpose, reusable software without sacrificing compile-time type checking. a major factor constraining the implementation of these languages is the difficulty of automatically inferring the lengthy type information that is otherwise required if full use is made of these languages. there is no known algorithm to solve any natural and fully general formulation of this &ldquo;type inference&rdquo; problem. one very reasonable formulation of the problem is known to be undecidable. here we define a restricted version of the type inference problem and present an efficient algorithm for its solution. we argue that the restriction is sufficiently weak to be unobtrusive in practice.
checking and inferring local non-aliasing. in prior work [15] we studied a language construct <tt>restrict</tt> that allows programmers to specify that certain pointers are not aliased to other pointers used within a lexical scope. among other applications, programming with these constructs helps program analysis tools locally recover strong updates, which can improve the tracking of state in flow-sensitive analyses. in this paper we continue the study of <tt>restrict</tt> and introduce the construct <tt>confine</tt>. we present a type and effect system for checking the correctness of these annotations, and we develop efficient constraint-based algorithms implementing these type checking systems. to make it easier to use <tt>restrict</tt> and <tt>confine</tt> in practice, we show how to automatically infer such annotations without programmer assistance. in experiments on locking in 589 linux device drivers, <tt>confine</tt> inference can automatically recover strong updates to eliminate 95% of the type errors resulting from weak updates.
space efficient conservative garbage collection. both type-accurate and conservative garbage collectors have gained in importance since the original paper was written. managing unnecessary retention by conservative collectors continues to be an important problem. there appear to be few reimplementations of the techniques we described, but significantly refined descendents of the original implementation are alive and well inside a large number of applications.there has been later work both on quantifying space retention by conservative collectors, and on theoretical bounds for such retention.we call a garbage collector conservative if it has only partial information about the location of pointers, and is thus forced to treat arbitrary bit patterns as though they might be pointers, in at least some cases. we show that some very inexpensive, but previously unused techniques can have dramatic impact on the effectiveness of conservative garbage collectors in reclaiming memory. our most significant observation is that static data that appears to point to the heap should not result in misidentified references to the heap. the garbage collector has enough information to allocate around such references. we also observe that programming style has a significant impact on the amount of spuriously retained storage, typically even if the collector is not terribly conservative. some fairly common c and c++ programming styles significantly decrease the effectiveness of any garbage collector. these observations suffice to explain some of the different assessments of conservative collection that have appeared in the literature.
better static memory management: improving region-based analysis of higher-order languages. static memory management replaces runtime garbage collection with compile-time annotations that make all memory allocation and deallocation explicit in a program. we improve upon the tofte/talpin region-based scheme for compile-time memory management[tt94]. in the tofte/talpin approach, all values, including closures, are stored in regions. region lifetimes coincide with lexical scope, thus forming a runtime stack of regions and eliminating the need for garbage collection. we relax the requirement that region lifetimes be lexical. rather, regions are allocated late and deallocated as early as possible by explicit memory operations. the placement of allocation and deallocation annotations is determined by solving a system of constraints that expresses all possible annotations. experiments show that our approach reduces memory requirements significantly, in some cases asymptotically.
optimal loop parallelization. parallelizing compilers promise to exploit the parallelism available in a given program, particularly parallelism that is too low-level or irregular to be expressed by hand in an algorithm. however, existing parallelization techniques do not handle loops in a satisfactory manner. fine-grain (instruction level) parallelization, or compaction, captures irregular parallelism inside a loop body but does not exploit parallelism across loop iterations. coarser methods, such as doacross [9], sacrifice irregular forms of parallelism in favor of pipelining iterations (software pipelining). both of these approaches often yield suboptimal speedups even under the best conditions-when resources are plentiful and processors are synchronous. in this paper we present a new technique bridging the gap between fine-and coarse-grain loop parallelization, allowing the exploitation of parallelism inside and across loop iterations. furthermore, we show that, given a loop and a set of dependencies between its statements, the execution schedule obtained by our transformation is time optimal: no transformation of the loop based on the given data-dependencies can yield a shorter running time for that loop.
simple garbage-collector-safety. a conservative garbage collector can typically be used with conventionally compiled programs written in c or c++. but two safety issues must be considered. first, the source code must not hide pointers from the garbage collector. this primarily requires stricter adherence to existing restrictions in the language definition. second, we must ensure that the compiler will not perform transformations that invalidate this requirement.we argue that the same technique can be used to address both issues. we present an algorithm for annotating source or intermediate code to either check the validity of pointer arithmetic in the source, or to guarantee that under minimal, clearly defined assumptions about the compiler, the optimizer cannot "disguise" pointers. we discuss an implementation based on a preprocessor for the gnu c compiler (gcc), and give some measurements of program slow down.
demystifying on-the-fly spill code. modulo scheduling is an effective code generation technique that exploits the parallelism in program loops by overlapping iterations. one drawback of this optimization is that register requirements increase significantly because values across different loop iterations can be live concurrently. one possible solution to reduce register pressure is to insert spill code to release registers. spill code stores values to memory between the producer and consumer instructions.spilling heuristics can be divided into two classes: 1) a posteriori approaches (spill code is inserted after scheduling the loop) or 2) on-the-fly approaches (spill code is inserted during loop scheduling). recent studies have reported obtaining better results for spilling on-the-fly. in this work, we study both approaches and propose two new techniques, one for each approach. our new algorithms try to address the drawbacks observed in previous proposals. we show that the new algorithms outperform previous techniques and, at the same time, reduce compilation time. we also show that, much to our surprise, a posteriori spilling can be in fact slitghtly more effective than on-the-fly spilling.
compiling c for vectorization, parallelization, and inline expansion. practical implementations of real languages are often an excellent way of testing the applicability of theoretical principles. many stresses and strains arise from fitting practicalities, such as performance and standard compatibility, to theoretical models and methods. these stresses and strains are valuable sources of new research and insight, as well as an oft-needed check on the egos of theoreticians. two fertile areas that are often explored by implementations are places where tractable models fail to match practice. this can lead to new models, and may also affect practice (e.g., the average programming language has become more context free over the last several decades). places where existing algorithms fail to deal with practical problems effectively, frequently because the problems are large in some dimension that has not been much explored. the present paper discusses the application of a much studied body of algorithms and techniques [alle 83, kklw 80, bane 76, wolf 78, wolf 82, kenn 80, lamp 74, huso 82] for vectorizing and optimizing fortran to the problem of vectorizing and optimizing c. in the course of this work some algorithms were discarded, others invented, and many were tuned and modified. the experience gave us insight into the strengths and weaknesses of the current theory, as well as into the strong and weak points of c on vector/parallel machines. this paper attempts to communicate some of those insights.
efficient algorithms for bidirectional debugging. this paper discusses our research into algorithms for creating an efficient bidirectional debugger in which all traditional forward movement commands can be performed with equal ease in the reverse direction. we expect that adding these backwards movement capabilities to a debugger will greatly increase its efficacy as a programming tool. the efficiency of our methods arises from our use of event counters that are embedded into the program being debugged. these counters are used to precisely identify the desired target event on the fly as the target program executes. this is in contrast to traditional debuggers that may trap back to the debugger many times for some movements. for reverse movements we re-execute the program (possibly using two passes) to identify and stop at the desired earlier point. our counter based techniques are essential for these reverse movements because they allow us to efficiently execute through the millions of events encountered during re-execution. two other important components of this debugger are its i/o logging and checkpointing. we log and later replay the results of system calls to ensure deterministic re-execution, and we use checkpointing to bound the amount of re-execution used for reverse movements. short movements generally appear instantaneous, and the time for longer movements is usually bounded within a small constant factor of the temporal distance moved back.
abstract debugging of higher-order imperative languages. abstract interpretation is a formal method that enables the static determination (i.e. at compile-time) of the dynamic properties (i.e. at run-time) of programs. we present an abstract interpretation-based method, called abstract debugging, which enables the static and formal debugging of programs, prior to their execution, by finding the origin of potential bugs as well as necessary conditions for these bugs not to occur at run-time. we show how invariant assertions and intermittent assertions, such as termination, can be used to formally debug programs. finally, we show how abstract debugging can be effectively and efficiently applied to higher-order imperative programs with exceptions and jumps to non-local labels, and present the syntox system that enables the abstract debugging of the pascal language by the determination of the range of the scalar variables of programs.
majic: compiling matlab for speed and responsiveness. this paper presents and evaluates techniques to improve the execution performance of matlab. previous efforts concentrated on source to source translation and batch compilation; majic provides an interactive frontend that looks like matlab and compiles/optimizes code behind the scenes in real time, employing a combination of just-in-time and speculative ahead-of-time compilation. performance results show that the proper mixture of these two techniques can yield near-zero response time as well as performance gains previously achieved only by batch compilers.
ownership types for safe region-based memory management in real-time java. the real time specification for java (rtsj) allows a program to create real-time threads with hard real-time constraints. real-time threads use region-based memory management to avoid unbounded pauses caused by interference from the garbage collector. the rtsj uses runtime checks to ensure that deleting a region does not create dangling references and that real-time threads do not access references to objects allocated in the garbage-collected heap. this paper presents a static type system that guarantees that these runtime checks will never fail for well-typed programs. our type system therefore 1) provides an important safety guarantee for real-time programs and 2) makes it possible to eliminate the runtime checks and their associated overhead.our system also makes several contributions over previous work on region types. for object-oriented programs, it combines the benefits of region types and ownership types in a unified type system framework. for multithreaded programs, it allows long-lived threads to share objects without using the heap and without memory leaks. for real-time programs, it ensures that real-time threads do not interfere with the garbage collector. our experience indicates that our type system is sufficiently expressive and requires little programming overhead, and that eliminating the rtsj runtime checks using a static type system can significantly decrease the execution time of real-time programs.
scheduling and mapping: software pipelining in the presence of structural hazards. recently, software pipelining methods based on an ilp (integer linear programming) framework have been successfully applied to derive rate-optimal schedules for architectures involving clean pipelines - pipelines without structural hazards. the problem for architectures beyond such clean pipelines remains open. one challenge is how, under a unified ilp framework, to simultaneously represent resource constraints for unclean pipelines, and the assignment or mapping of operations from a loop to those pipelines. in this paper we provide a framework which does exactly this, and in addition constructs rate-optimal software pipelined schedules. the proposed formulation and a solution method have been implemented and tested on a set of 1006 loops taken from various scientific and integer benchmark suites. the formulation found a rate-optimal schedule for 75% of the loops, and required a median time of only 2 seconds per loop on a sparc 10/30.
using lifetime predictors to improve memory allocation performance. dynamic storage allocation is used heavily in many application areas including interpreters, simulators, optimizers, and translators. we describe research that can improve all aspects of the performance of dynamic storage allocation by predicting the lifetimes of short-lived objects when they are allocated. using five significant, allocation-intensive c programs, we show that a great fraction of all bytes allocated are short-lived (> 90% in all cases). furthermore, we describe an algorithm for liftetime prediction that accurately predicts the lifetimes of 42&ndash;99% of all objects allocated. we describe and simulate a storage allocator that takes adavantage of lifetime prediction of short-lived objects and show that it can significantly improve a program's memory overhead and reference locality, and even, at times, improve cpu performance as well.
context-insensitive alias analysis reconsidered. recent work on alias analysis in the presence of pointers has concentrated on context-sensitive interprocedural analyses, which treat multiple calls to a single procedure independently rather than constructing a single approximation to a procedure's effect on all of its callers. while context-sensitive modeling offers the potential for greater precision by considering only realizable call-return paths, its empirical benefits have yet to be measured.this paper compares the precision of a simple, efficient, context-insensitive points-to analysis for the c programming language with that of a maximally context-sensitive version of the same analysis. we demonstrate that, for a number of pointer-intensive benchmark programs, context-insensitivity exerts little to no precision penalty. we also describe techniques for using the output of context-insensitive analysis to improve the efficiency of context-sensitive analysis without affecting precision.
implementation of the data-flow synchronous language signal. this paper presents the techniques used for the compilation of the data-flow, synchronous language signal. the key feature of the compiler is that it performs formal calculus on systems of boolean equations. the originality of the implementation of the compiler lies in the use of a tree structure to solve the equations.
garbage collection using a dynamic threatening boundary. generational techniques have been very successful in reducing the impact of garbage collection algorithms upon the performance of programs. however, all generational algorithms occasionally promote objects that later become garbage, resulting in an accumulation of garbage in older generations. reclaiming this tenured garbage without resorting to collecting the entire heap is a difficult problem. in this paper, we describe a mechanism that extends existing generational collection algorithms by allowing them to reclaim tenured garbage more effectively. in particular, our dynamic threatening boundary mechanism divides memory into two spaces, one for shortlived, and another for long-lived objects. unlike previous work, our collection mechanism can dynamically adjust the boundary between these two spaces either forward or backward in time, essentially allowing data to become untenured. we describe an implementation of the dynamic threatening boundary mechanism and quantify its associated costs. we also describe a policy for setting the threatening boundary and evaluate its performance relative to existing generational collection algorithms. our results show that a policy that uses the dynamic threatening boundary mechanism is effective at reclaiming tenured garbage.
efficient building and placing of gating functions. in this paper, we present an almost-linear time algorithm for constructing gated single assignment (gsa), which is ssa augmented with gating functions at &oslash;-nodes. the gating functions specify the control dependences for each reaching definition at a &oslash;-node. we introduce a new concept of gating path, which is path in the control flow graph from the immediate dominator u of a node v to v, such that every node in the path is dominated by u. previous algorithms start with &oslash;-function placement, and then traverse the control flow graph to compute the gating functions. by formulating the problem into gating path construction, we are able to identify not only a &oslash;-node, but also a gating path expression which defines a gating function for the &oslash;-node.
communication optimization and code generation for distributed memory machines. this paper presents several algorithms to solve code generation and optimization problems specific to machines with distributed address spaces. given a description of how the computation is to be partitioned across the processors in a machine, our algorithms produce an spmd (single program multiple data) program to be run on each processor. our compiler generated the necessary receive and send instructions, optimizes the communication by eliminating redundant communication and aggregating small messages into large messages, allocates space locally on each processor, and translates global data addresses to local addresses. our techniques are based on an exact data-flow analysis on individual array element accesses. unlike data dependence analysis, this analysis determines if two dynamic instances refer to the same value, and not just to the same location. using this information, our compiler can handle more flexible data decompositions and find more opportunities for communication optimization than systems based on data dependence analysis. our technique is based on a uniform framework, where data decompositions, computation decompositions and the data flow information are all represented as systems of linear inequalities. we show that the problems of communication code generation, local memory management, message aggregation and redundant data communication elimination can all be solved by projecting polyhedra represented by sets of inequalities onto lower dimensional spaces.
beltway: getting around garbage collection gridlock. we present the design and implementation of a new garbage collection framework that significantly generalizes existing copying collectors. the beltway framework exploits and separates object age and incrementality. it groups objects in one or more increments on queues called belts, collects belts independently, and collects increments on a belt in first-in-first-out order. we show that beltway configurations, selected by command line options, act and perform the same as semi-space, generational, and older-first collectors, and encompass all previous copying collectors of which we are aware. the increasing reliance on garbage collected languages such as java requires that the collector perform well. we show that the generality of beltway enables us to design and implement new collectors that are robust to variations in heap size and improve total execution time over the best generational copying collectors of which we are aware by up to 40%, and on average by 5 to 10%, for small to moderate heap sizes. new garbage collection algorithms are rare, and yet we define not just one, but a new family of collectors that subsumes previous work. this generality enables us to explore a larger design space and build better collectors.
automatic recognition of induction variables and recurrence relations by abstract interpretation. the recognition of recurrence relations is important in several ways to the compilation of programs. induction variables, the simplest form of recurrence, are pivotal in loop optimizations and dependence testing. many recurrence relations, although expressed sequentially by the programmer, lend themselves to efficient vector or parallel computation. despite the importance of recurrences, vectorizing and parallelizing compilers to date have recognized them only in an ad-hoc fashion. in this paper we put forth a systematic method for recognizing recurrence relations automatically. our method has two parts. first, abstract interpretation [cc77, cc79] is used to construct a map that associates each variable assigned in a loop with a symbolic form (expression) of its value. second, the elements of this map are matched with patterns that describe recurrence relations. the scheme is easily extensible by the addition of templates, and is able to recognize nested recurrences by the propagation of the closed forms of recurrences from inner loops. we present some applications of this method and a proof of its correctness.
exploiting hardware performance counters with flow and context sensitive profiling. a program profile attributes run-time costs to portions of a program's execution. most profiling systems suffer from two major deficiencies: first, they only apportion simple metrics, such as execution frequency or elapsed time to static, syntactic units, such as procedures or statements; second, they aggressively reduce the volume of information collected and reported, although aggregation can hide striking differences in program behavior.this paper addresses both concerns by exploiting the hardware counters available in most modern processors and by incorporating two concepts from data flow analysis--flow and context sensitivity--to report more context for measurements. this paper extends our previous work on efficient path profiling to flow sensitive profiling, which associates hardware performance metrics with a path through a procedure. in addition, it describes a data structure, the calling context tree, that efficiently captures calling contexts for procedure-level measurements.our measurements show that the spec95 benchmarks execute a small number (3--28) of hot paths that account for 9--98% of their l1 data cache misses. moreover, these hot paths are concentrated in a few routines, which have complex dynamic behavior.
automatic instruction scheduler retargeting by reverse-engineering. in order to generate high-quality code for modern processors, a compiler must aggressively schedule instructions, maximizing resource utilization for execution efficiency. for a compiler to produce such code, it must avoid structural hazards by being aware of the processor's available resources and of how these resources are utilized by each instruction. unfortunately, the most prevalent approach to constructing such a scheduler, manually discovering and specifying this information, is both tedious and error-prone. this paper presents a new approach which, when given a processor or processor model, automatically determines this information. after establishing that the problem of perfectly determining a processor's structural hazards through probing is not solvable, this paper proposes a heuristic algorithm that discovers most of this information in practice. this can be used either to alleviate the problems associated with manual creation or to verify an existing specification. scheduling with these automatically derived structural hazards yields almost all of the performance gain achieved using perfect hazard information.
improving data-flow analysis with path profiles. data-flow analysis computes its solutions over the paths in a control-flow graph. these paths---whether feasible or infeasible, heavily or rarely executed---contribute equally to a solution. however, programs execute only a small fraction of their potential paths and, moreover, programs' execution time and cost is concentrated in a far smaller subset of hot paths.this paper describes a new approach to analyzing and optimizing programs, which improves the precision of data flow analysis along hot paths. our technique identifies and duplicates hot paths, creating a hot path graph in which these paths are isolated. after flow analysis, the graph is reduced to eliminate unnecessary duplicates of unprofitable paths. in experiments on spec95 benchmarks, path qualification identified 2--112 times more non-local constants (weighted dynamically) than the wegman-zadek conditional constant algorithm, which translated into 1--7% more dynamic instructions with constant results.
effective partial redundancy elimination. partial redundancy elimination is a code optimization with a long history of literature and implementation. in practice, its effectiveness depends on issues of naming and code shape. this paper shows that a combination of global reassociation and global value numbering can increase the effectiveness of partial redundancy elimination. by imposing a discipline on the choice of names and the shape of expressions, we are able to expose more redundancies. as part of the work, we introduce a new algorithm for global reassociation of expressions. it uses global information to reorder expressions, creating opportunities for other optimizations. the new algorithm generalizes earlier work that ordered fortran array address expressions to improve otpimization [25].
coloring heuristics for register allocation. we describe an improvement to a heuristic introduced by chaitin for use in graph coloring register allocation. our modified heuristic produces better colorings, with less spill code. it has similar compile-time and implementation requirements. we present experimental data to compare the two methods.
debugging temporal specifications with concept analysis. program verification tools (such as model checkers and static analyzers) can find many errors in programs. these tools need formal specifications of correct program behavior, but writing a correct specification is difficult, just as writing a correct program is difficult. thus, just as we need methods for debugging programs, we need methods for debugging specifications.this paper describes a novel method for debugging formal, temporal specifications. our method exploits the short program execution traces that program verification tools generate from specification violations and that specification miners extract from programs. manually examining these traces is a straightforward way to debug a specification, but this method is tedious and error-prone because there may be hundreds or thousands of traces to inspect. our method uses concept analysis to automatically group the traces into highly similar clusters. by examining clusters instead of individual traces, a person can debug a specification with less work.to test our method, we implemented a tool, cable, for debugging specifications. we have used cable to debug specifications produced by strauss, our specification miner. we found that using cable to debug these specifications requires, on average, less than one third as many user decisions as debugging by examining all traces requires. in one case, using cable required only 28 decisions, while debugging by examining all traces required 224.
compilation of haskell array comprehensions for scientific computing. monolithic approaches to functional language arrays, such as haskell array comprehensions, define elements all at once, at the time the array is created, instead of incrementally. although monolithic arrays are elegant, a naive implementation can be very inefficient. for example, if a compiler does not know whether an element has zero or many definitions, it must compile runtime tests. if a compiler does not know inter-element data dependencies, it must resort to pessimistic strategies such as compiling elements as thunks, or making unnecessary copies when updating an array. subscript analysis, originally developed for imperative language vectorizing and parallelizing compilers, can be adapted to provide a functional language compiler with the information needed for efficient compilation of monolithic arrays. our contribution is to develop the number-theoretic basis of subscript analysis with assumptions appropriate to functional arrays, detail the kinds of dependence information subscript analysis can uncover, and apply that dependence information to sequential efficient compilation of functional arrays.
rematerialization. this paper examines a problem that arises during global register allocation &ndash; rematerialization. if a value cannot be kept in a register, the allocator should recognize when it is cheaper to recompute the value (rematerialize it) than to store and reload it. chaitin's original graph-coloring allocator handled simple instance of this problem correctly. this paper details a general solution to the problem and presents experimental evidence that shows its importance. our approach is to tag individual values in the procedure's ssa graph with information specifying how it should be spilled. we use a variant of wegman and zadeck's sparse simple constant algorithm to propagate tags throughout the graph. the allocator then splits live ranges into values with different tags. this isolates those values that can be easily rematerialized from values that require general spilling. we modify the base allocator to use this information when estimating spill costs and introducing spill code. our presentation focuses on rematerialization in the context of chaitin's allocator; however, the problem arises in any global allocator. we believe that our approach will work in other allocators&ndash;while the details of implementation will vary, the key insights should carry over directly.
design and implementation of the uw illustrated compiler. we have implemented an illustrated compiler for a simple block structured language. the compiler graphically displays its control and data structures, and so gives its viewers an intuitive understanding of compiler organization and operation. the illustrations were planned by hand and display information naturally and concisely.
a new approach to debugging optimized code. debugging optimized code is a desirable capability not provided by most current debuggers. users are forced to debug the unoptimized code when a bug occurs in the optimized version. current research offers partial solutions for a small class of optimizations, but not a unified approach that handles a wide range of optimizations, such as the sophisticated optimizations performed by supercomputer compilers. the trend with current research is to make the effects of optimization transparent, i.e., provide the same behavior as that of the unoptimized program. we contend that this approach is neither totally feasible nor entirely desirable. instead, we propose a new approach based on the premise that one should be able to debug the optimized code. this implies mapping the current state of execution back to the original source, tracking the location of variables, and mapping compiler-synthesized variables back to user-defined induction variables. to aid the user in understanding program behavior, various visual means are provided, e.g., different forms of highlighting and annotating of the source/assembly code. while this unavoidably requires the user to have a basic understanding of the optimizations performed, it permits the user to see what is actually happening, infer the optimizations performed, and detect bugs. an example illustrates the effectiveness of visual feedback. to support conventional debugger functionality for optimized code, the compiler must generate additional information. current compiler-debugger interfaces (cdis) were neither designed to handle this new information nor are they extensible in a straight forward manner. therefore, a new cdi was designed that supports providing visual feedback and the debugging of optimized code. this paper specifies the details of a new cdi and relates each feature back to the debugger functionality it supports.
social processes and proofs of theorems and programs, revisited. language-based security is a protection mechanism that allows software components to interact in a shared address space, such that each component is guaranteed to respect its interfaces and not steal or corrupt internal data of other components. this protection mechanism is complicated to implement correctly, so we might want a formal verification of it.but we know by a famous result of demillo, lipton, and perlis (popl 1978) that formal verification (1) is not what mathematicians do, (2) can never be practical, and (3) cannot tell us anything truly useful. is this still true 25 years later?the question is, then, how can we carefully skirt the legitimate objections of demillo et al. and successfully use formal verification in a context where it can do some good. i'll talk about foundational proof-carrying code, a machine-checked soundness proof for a protection mechanism usable in java-like virtual machines.
representing control in the presence of one-shot continuations. traditional first-class continuation mechanisms allow a captured continuation to be invoked multiple times. many continuations, however, are invoked only once. this paper introduces one-shot continuations, shows how they interact with traditional multi-shot continuations, and describes a stack-based implementation of control that handles both one-shot and multi-shot continuations. the implementation eliminates the copying overhead for one-shot continuations that is inherent in multi-shot continuations.
fast copy coalescing and live-range identification. this paper presents a fast new algorithm for modeling and reasoning about interferences for variables in a program without constructing an interference graph. it then describes how to use this information to minimize copy insertion for &fgr;-node instantiation during the conversion of the static single assignment (ssa) form into the control-flow graph (cfg), effectively yielding a new, very fast copy coalescing and live-range identification algorithm.this paper proves some properties of the ssa form that enable construction of data structures to compute interference information for variables that are considered for folding. the asymptotic complexity of our ssa-to-cfg conversion algorithm is where-is the number of instructions in the program.performing copy folding during the ssa-to-cfg conversion eliminates the need for a separate coalescing phase while simplifying the intermediate code. this may make graph-coloring register allocation more practical in just in time (jit) and other time-critical compilers for example, sun's hotspot server compiler already employs a graph-coloring register allocator[10].this paper also presents an improvement to the classical interference-graph based coalescing optimization that shows adecrease in memory usage of up to three orders of magnitude and a decrease of a factor of two in compilation time, while providing the exact same results.we present experimental results that demonstrate that our algorithm is almost as precise (within one percent on average) as the improved interference-graph-based coalescing algorithm, while requiring three times less compilation time.
real-time concurrent collection on stock multiprocessors. we've designed and implemented a copying garbage-collection algorithm that is efficient, real-time, concurrent, runs on commercial uniprocessors and shared-memory multiprocessors, and requires no change to compilers. the algorithm uses standard virtual-memory hardware to detect references to &ldquo;from space&rdquo; objects and to synchronize the collector and mutator threads. we've implemented and measured a prototype running on src's 5-processor firefly. it will be straightforward to merge our techniques with generational collection. an incremental, non-concurrent version could be implemented easily on many versions of unix.
printing floating-point numbers quickly and accurately. this paper presents a fast and accurate algorithm for printing floating-point numbers in both free- and fixed-format modes. in free-format mode, the algorithm generates the shortest, correctly rounded output string that converts to the same number when read back in, accommodating whatever rounding mode the reader uses. in fixed-format mode, the algorithm generates a correctly rounded output string using special # marks to denote insignificant trailing digits. for both modes, the algorithm employs a fast estimator to scale floating-point numbers efficiently.
optimal spilling for cisc machines with few registers. many graph-coloring register-allocation algorithms don't work well for machines with few registers. heuristics for live-range splitting are complex or suboptimal; heuristics for register assignment rarely factor the presence of fancy addressing modes; these problems are more severe the fewer registers there are to work with. we show how to optimally split live ranges and optimally use addressing modes, where the optimality condition measures dynamically weighted loads and stores but not register-register moves. our algorithm uses integer linear programming but is much more efficient than previous ilp-based approaches to register allocation. we then show a variant of park and moon's optimistic coalescing algorithm that does a very good (though not provably optimal) job of removing the register-register moves. the result is pentium code that is 9.5% faster than code generated by ssa-based splitting with iterated register coalescing.
register allocation using lazy saves, eager restores, and greedy shuffling. this paper presents a fast and effective linear intraprocedural register allocation strategy that optimizes register usage across procedure calls. it capitalizes on our observation that while procedures that do not contain calls (syntactic leaf routines) account for under one third of all procedure activations, procedures that actually make no calls (effective leaf routines) account for over two thirds of all procedure activations. well-suited for both caller-and calle-save registers, our strategy employs a &ldquo;lazy&rdquo; save mechanism that avoids saves for all effective leaf routines, an &ldquo;eager&rdquo; restore mechanism that reduces the effect of memory latency, and a &ldquo;greedy&rdquo; register shuffling algorithm that does a remarkbly good job of minimizing the need for temporaries in setting up procedure calls.
separate compilation for standard ml. languages that support abstraction and modular structure, such as standard ml, modula, ada, and (more or less) c++, may have deeply nested dependency hierarchies among source files. in ml the problem is particularly severe because ml's powerful parameterized module (functor) facility entails dependencies among implementation modules, not just among interfaces.to efficiently compile individual modules in such languages, it is useful (in ml, necessary) to infer, digest, and cache the static environment resulting from the compilation of each module. our system provides a simple model of compilation and linkage that supports incremental recompilation (a restricted form of separate compilation) with type-safe linkage. this model is made available to user programs in the form of a set of internal compiler modules, a feature that we call the &ldquo;visible compiler&rdquo;. the chief client of this interface is the irm incremental recompilation manager from cmu.
a framework for reducing the cost of instrumented code. instrumenting code to collect profiling information can cause substantial execution overhead. this overhead makes instrumentation difficult to perform at runtime, often preventing many known offline feedback-directed optimizations from being used in online systems. this paper presents a general framework for performing instrumentation sampling to reduce the overhead of previously expensive instrumentation. the framework is simple and effective, using code-duplication and counter-based sampling to allow switching between instrumented and non-instrumented code. our framework does not rely on any hardware or operating system support, yet provides a high frequency sample rate that is tunable, allowing the tradeoff between overhead and accuracy to be adjusted easily at runtime. experimental results are presented to validate that our technique can collect accurate profiles (93-98% overlap with a perfect profile) with low overhead (averaging 6% total overhead with a naive implementation). a jalape~ no-specific optimization is also presented that reduces overhead further, resulting in an average total overhead of 3%.
experiences creating a portable cedar. cedar is the name for both a language and an environment in use in the computer science laboratory at xerox parc since 1980. the cedar language is a superset of mesa, the major additions being garbage collection and runtime types. neither the language nor the environment was originally intended to be portable, and for many years ran only on d-machines at parc and a few other locations in xerox. we recently re-implemented the language to make it portable across many different architectures. our strategy was, first, to use machine-dependent c code as an intermediate language, second, to create a language-independent layer known as the portable common runtime, and third, to write a relatively large amount of cedar-specific runtime code in a subset of cedar itself. by treating c as an intermediate code we are able to achieve reasonably fast compilation, very good eventual machine code, and all with relatively small programmer effort. because cedar is a much richer language than c, there were numerous issues to resolve in performing an efficient translation and in providing reasonable debugging. these strategies will be of use to many other porters of high-level languages who may wish to use c as an assembler language without giving up either ease of debugging or high performance. we present a brief description of the cedar language, our portability strategy for the compiler and runtime, our manner of making connections to other languages and the unix* operating system, and some measures of the performance of our &ldquo;portable cedar&rdquo;.
static load classification for improving the value predictability of data-cache misses. while caches are effective at avoiding most main-memory accesses, the few remaining memory references are still expensive. even one cache miss per one hundred accesses can double a program's execution time. to better tolerate the data-cache miss latency, architects have proposed various speculation mechanisms, including load-value prediction. a load-value predictor guesses the result of a load so that the dependent instructions can immediately proceed without having to wait for the memory access to complete. to use the prediction resources most effectively, speculation should be restricted to loads that are likely to miss in the cache and that are likely to be predicted correctly. prior work has considered hardware- and profile-based methods to make these decisions. our work focuses on making these decisions at compile time. we show that a simple compiler classification is effective at separating the loads that should be speculated from the loads that should not. we present results for a number of c and java programs and demonstrate that our results are consistent across programming languages and across program inputs.
a static analyzer for large safety-critical software. we show that abstract interpretation-based static program analysis can be made efficient and precise enough to formally verify a class of properties for a family of large programs with few or no false alarms. this is achieved by refinement of a general purpose static analyzer and later adaptation to particular programs of the family by the end-user through parametrization. this is applied to the proof of soundness of data manipulation operations at the machine level for periodic synchronous safety critical embedded software.the main novelties are the design principle of static analyzers by refinement and adaptation through parametrization (sect. 3 and 7), the symbolic manipulation of expressions to improve the precision of abstract transfer functions (sect. 6.3), the octagon (sect. 6.2.2), ellipsoid (sect. 6.2.3), and decision tree (sect. 6.2.4) abstract domains, all with sound handling of rounding errors in oating point computations, widening strategies (with thresholds: sect. 7.1.2, delayed: sect. 7.1.3) and the automatic determination of the parameters (parametrized packing: sect. 7.2).
fast, effective dynamic compilation. dynamic compilation enables optimization based on the values of invariant data computed at run-time. using the values of these run-time constants, a dynamic compiler can eliminate their memory loads, perform constant propagation and folding, remove branches they determine, and fully unroll loops they bound. however, the performance benefits of the more efficient, dynamically-compiled code are offset by the run-time cost of the dynamic compile. our approach to dynamic compilation strives for both fast dynamic compilation and high-quality dynamically-compiled code: the programmer annotates regions of the programs that should be compiled dynamically; a static, optimizing compiler automatically produces pre-optimized machine-code templates, using a pair of dataflow analyses that identify which variables will be constant at run-time; and a simple, dynamic compiler copies the templates, patching in the computed values of the run-time constants, to produce optimized, executable code. our work targets general- purpose, imperative programming languages, initially c. initial experiments applying dynamic compilation to c programs have produced speedups ranging from 1.2 to 1.8.
corpus-based static branch prediction. correctly predicting the direction that branches will take is increasingly important in today's wide-issue computer architectures. the name program-based branch prediction is given to static branch prediction techniques that base their prediction on a program's structure. in this paper, we investigate a new approach to program-based branch prediction that uses a body of existing programs to predict the branch behavior in a new program. we call this approach to program-based branch prediction, evidence-based static prediction, or esp. the main idea of esp is that the behavior of a corpus of programs can be used to infer the behavior of new programs. in this paper, we use a neural network to map static features associated with each branch to the probability that the branch will be taken. esp shows significant advantages over other prediction mechanisms. specifically, it is a program-based technique, it is effective across a range of programming languages and programming styles, and it does not rely on the use of expert-defined heuristics. in this paper, we describe the application of esp to the problem of branch prediction and compare our results to existing program-based branch predictors. we also investigate the applicability of esp across computer architectures, programming languages, compilers, and run-time systems. averaging over a body of 43 c and fortran programs, esp branch prediction results in a miss rate of 20%, as compared with the 25% miss rate obtained using the best existing program-based heuristics.
efficient detection of all pointer and array access errors. we present a pointer and array access checking technique that provides complete error coverage through a simple set of program transformations. our technique, based on an extended safe pointer representation, has a number of novel aspects. foremost, it is the first technique that detects all spatial and temporal access errors. its use is not limited by the expressiveness of the language; that is, it can be applied successfully to compiled or interpreted languages with subscripted and mutable pointers, local references, and explicit and typeless dynamic storage management, e.g., c. because it is a source level transformation, it is amenable to both compile- and run-time optimization. finally, its performance, even without compile-time optimization, is quite good. we implemented a prototype translator for the c language and analyzed the checking overheads of six non-trivial, pointer intensive programs. execution overheads range from 130% to 540%; with text and data size overheads typically below 100%.
on bounding time and space for multiprocessor garbage collection. our paper described a real-time garbage collection algorithm for shared-memory multiprocessors. the work differed from previous work on multiprocessor garbage collection in that we were interested in placing hard bounds on pause times and memory usage. we felt this was important in justifying the term real-time, and for giving users a better handle on actual performance characteristics. although the paper presented an algorithm without an implementation, and made some simplifying assumptions, we put considerable effort into making key aspects of the algorithm practical. in later work [9, 8] we implemented the ideas, and demonstrated performance characteristics that were in line with the characteristics predicted by the theory.this paper presents the first multiprocessor garbage collection algorithm with provable bounds on time and space. the algorithm is a real-time shared-memory copying colector. we prove that the algorithm requires at most 2(r(1 + 2/k) + n + 5pd) memory locations, where p is the number of processors, r is the maximum reachable space during a computation (number of locations accessible from the root set), n is the maximum number of reachable objects, d is the maximum depth of any data object, and k is a parameter specifying how many locations are copied each time a location is allocated. furthermore we show that client threads are never stopped for more than time proportional to k non-blocking machine instructions. the bounds are guaranteed even with arbitrary length arrays. the collector only requires write-barriers (reads are unaffected by the collector), makes few assumptions about the threads that are generating the garbage, and allows them to run mostly asynchronously.
eliminating array bound checking through dependent types. we present a type-based approach to eliminating array bound checking and list tag checking by conservatively extending standard ml with a restricted form of dependent types. this enables the programmer to capture more invariants through types while type-checking remains decidable in theory and can still be performed efficiently in practice. we illustrate our approach through concrete examples and present the result of our preliminary experiments which support support the feasibility and effectiveness of our approach.
optimising aspectj. aspectj, an aspect-oriented extension of java, is becoming increasingly popular. however, not much work has been directed at optimising compilers for aspectj. optimising aop languages provides many new and interesting challenges for compiler writers, and this paper identifies and addresses three such challenges.first, compiling around advice efficiently is particularly challenging. we provide a new code generation strategy for around advice, which (unlike previous implementations) both avoids the use of excessive inlining and the use of closures. we show it leads to more compact code, and can also improve run-time performance. second, woven code sometimes includes run-time tests to determine whether advice should execute. one important case is the cflow pointcut which uses information about the dynamic calling context. previous techniques for cflow were very costly in terms of both time and space. we present new techniques to minimise or eliminate the overhead of cflow using both intra- and inter-procedural analyses. third, we have addressed the general problem of how to structure an optimising compiler so that traditional analyses can be easily adapted to the aop setting.we have implemented all of the techniques in this paper in abc, our aspectbench compiler for aspectj, and we demonstrate significant speedups with empirical results. some of our techniques have already been integrated into the production aspectj compiler, ajc 1.2.1.
improving register allocation for subscripted variables. most conventional compilers fail to allocate array elements to registers because standard data-flow analysis treats arrays like scalars, making it impossible to analyze the definitions and uses of individual array elements. this deficiency is particularly troublesome for floating-point registers, which are most often used as temporary repositories for subscripted variables.in this paper, we present a source-to-source transformation, called scalar replacement, that finds opportunities for reuse of subscripted variables and replaces the references involved by references to temporary scalar variables. the objective is to increase the likelihood that these elements will be assigned to registers by the coloring-based register allocators found in most compilers. in addition, we present transformations to improve the overall effectiveness of scalar replacement and show how these transformations can be applied in a variety of loop nest types. finally, we present experimental results showing that these techniques are extremely effective---capable of achieving integer factor speedups over code generated by good optimizing compilers of conventional design.
scalable cross-module optimization. large applications are typically partitioned into separately compiled modules. large performance gains in these applications are available by optimizing across module boundaries. one barrier to applying crossmodule optimization (cmo) to large applications is the potentially enormous amount of time and space consumed by the optimization process.we describe a framework for scalable cmo that provides large gains in performance on applications that contain millions of lines of code. two major techniques are described. first, careful management of in-memory data structures results in sub-linear memory occupancy when compared to the number of lines of code being optimized. second, profile data is used to focus optimization effort on the performance-critical portions of applications. we also present practical issues that arise in deploying this framework in a production environment. these issues include debuggability and compatibility with existing development tools, such as make. our framework is deployed in hewlett-packard's (hp) unix compiler products and speeds up shipped independent software vendors' applications by as much as 71%.
traceback: first fault diagnosis by reconstruction of distributed control flow. faults that occur in production systems are the most important faults to fix, but most production systems lack the debugging facilities present in development environments. traceback provides debugging information for production systems by providing execution history data about program problems (such as crashes, hangs, and exceptions). traceback supports features commonly found in production environments such as multiple threads, dynamically loaded modules, multiple source languages (e.g., java applications running with jni modules written in c++), and distributed execution across multiple computers. traceback supports first fault diagnosis-discovering what went wrong the first time a fault is encountered. the user can see how the program reached the fault state without having to re-run the computation; in effect enabling a limited form of a debugger in production code.traceback uses static, binary program analysis to inject low-overhead runtime instrumentation at control-flow block granularity. post-facto reconstruction of the records written by the instrumentation code produces a source-statement trace for user diagnosis. the trace shows the dynamic instruction sequence leading up to the fault state, even when the program took exceptions or terminated abruptly (e.g., kill -9).we have implemented traceback on a variety of architectures and operating systems, and present examples from a variety of platforms. performance overhead is variable, from 5% for apache running specweb99, to 16%-25% for the java specjbb benchmark, to 60% average for specint2000. we show examples of traceback's cross-language and cross-machine abilities, and report its use in diagnosing problems in production software.
java without the coffee breaks: a nonintrusive multiprocessor garbage collector. the deployment of java as a concurrent programming language has created a critical need for high-performance, concurrent, and incremental multiprocessor garbage collection. we present the recycler, a fully concurrent pure reference counting garbage collector that we have implemented in the jalape&ntilde;o java virtual machine running on shared memory multiprocessors. while a variety of multiprocessor collectors have been proposed and some have been implemented, experimental data is limited and there is little quantitative basis for comparison between different algorithms. we present measurements of the recycler and compare it against a non-concurrent but parallel load-balancing mark-and-sweep collector (that we also implemented in jalape&ntilde;o), and evaluate the classical tradeoff between response time and throughput. when processor or memory resources are limited, the recycler runs at about 90% of the speed of the mark-and-sweep collector. however, with an extra processor to run collection and with a moderate amount of memory headroom, the recycler is able to operate without ever blocking the mutators and achieves a maximum measured mutator delay of only 2.6 milliseconds for our benchmarks. end-to-end execution time is usually within 5%.
thin locks: featherweight synchronization for java. language-supported synchronization is a source of serious performance problems in many java programs. even single-threaded applications may spend up to half their time performing useless synchronization due to the thread-safe nature of the java libraries. we solve this performance problem with a new algorithm that allows lock and unlock operations to be performed with only a few machine instructions in the most common cases. our locks only require a partial word per object, and were implemented without increasing object size. we present measurements from our implementation in the jdk 1.1.2 for aix, demonstrating speedups of up to a factor of 5 in micro-benchmarks and up to a factor of 1.7 in real programs.
contaminated garbage collection. we describe a new method for determining when an object can be garbage collected. the method does not require marking live objects. instead, each object x is dynamically associated with a stack frame m, such that xis collectable when m pops. because x could have been dead earlier, our method is conservative. our results demonstrate that the method nonetheless identifies a large percentage of collectable objects. the method has been implemented in sun's java virtual machine interpreter, and results are presented based on this implementation
flow-sensitive interprocedural constant propagation. we present a flow-sensitive interprocedural constant propagation algorithm, which supports recursion while only performing one flow-sensitive analysis of each procedure. we present experimental results which show that this method finds substantially more constants than previous methods and is efficient in practice. we introduce new metrics for evaluating interprocedural constant propagation algorithms which measure the number of interprocedural constant values that are propagated. we use these metrics to provide further experimental results for our algorithm.
a generator for language-specific debugging systems. we present a system which generates interactive high-level debugging systems from formal language definitions. the language definer has to specify a denotational semantics augmented with a formal description of the language specific debugging facilities. the generated debugger offers the traditional features such as tracing programs, setting breakpoints, displaying variables etc; interaction with the user is always on language level rather than on machine level. the concept has been implemented as part of the psg-programming system generator, and has successfully been used to generate debuggers for pascal and modula-2. the core of the implementation consists of an interpreter for a functional language, which has been extended with the language-independent mechanisms needed in order to allow interaction with the user during program execution.
the atomos transactional programming language. atomos is the first programming language with implicit transactions, strong atomicity, and a scalable multiprocessor implementation. atomos is derived from java, but replaces its synchronization and conditional waiting constructs with simpler transactional alternatives.the atomos watch statement allows programmers to specify fine-grained watch sets used with the atomos retry conditional waiting statement for efficient transactional conflict-driven wakeup even in transactional memory systems with a limited number of transactional contexts. atomos supports open-nested transactions, which are necessary for building both scalable application programs and virtual machine implementations.the implementation of the atomos scheduler demonstrates the use of open nesting within the virtual machine and introduces the concept of transactional memory violation handlers that allow programs to recover from data dependency violations without rolling back.atomos programming examples are given to demonstrate the usefulness of transactional programming primitives. atomos and java are compared through the use of several benchmarks. the results demonstrate both the improvements in parallel programming ease and parallel program performance provided by atomos.
target-sensitive construction of diagnostic programs for procedure calling sequence generators. building compilers that generate correct code is difficult. in this paper we present a compiler testing technique that closes the gap between actual compiler implementations and correct compilers. using formal specifications of procedure calling conventions, we have built a target-sensitive test suite generator that builds test cases for a specific aspect of compiler code generators: the procedure calling sequence generator. by exercising compilers with these target-specific test suites, our automated testing tool has been able to expose and isolate 8 bugs in heavily used production-quality compilers. these bugs cause more than 700 test cases to fail.
the semantics of program dependence. optimizing and parallelizing compilers for procedural languages rely on various forms of program dependence graphs (pdgs) to express the essential control and data dependencies among atomic program operations. in this paper, we provide a semantic justification for this practice by deriving two different forms of program dependence graph &mdash; the output pdg and the def-order pdg&mdash;and their semantic definitions from non-strict generalizations of the denotational semantics of the programming language. in the process, we demonstrate that both the output pdg and the def-order pdg (with minor technical modifications) are conventional data-flow programs. in addition, we show that the semantics of the def-order pdg dominates the semantics of the output pdg and that both of these semantics dominate&mdash;rather than preserve&mdash;the semantics of sequential execution.
maya: multiple-dispatch syntax extension in java. we have designed and implemented maya, a version of java that allows programmers to extend and reinterpret its syntax. maya generalizes macro systems by treating grammar productions as generic functions, and semantic actions on productions as multimethods on the corresponding generic functions. programmers can write new generic functions (i.e., grammar productions) and new multimethods (i.e., semantic actions), through which they can extend the grammar of the language and change the semantics of its syntactic constructs, respectively. maya's multimethods are compile-time metaprograms that transform abstract syntax: they execute at program compile-time, because they are semantic actions executed by the parser. maya's multimethods can be dispatched on the syntactic structure of the input, as well as the static, source-level types of expressions in the input. in this paper we describe what maya can do and how it works. we describe how its novel parsing techniques work and how maya can statically detect certain kinds of errors, such as code that generates references to free variables. finally, to demonstrate maya's expressiveness, we describe how maya can be used to implement the multijava language, which was described by clifton et al. at oopsla 2000.
soft typing. type systems are designed to prevent the improper use of program operations. they can be classified as either static or dynamic depending on when they detect type errors. static type systems detect potential type errors at compile-time and prevent program execution. dynamic type systems detect type errors at run-time and abort program execution.static type systems have two important advantages over dynamic type systems. first, they help programmers detect a large class of program errors before execution. second, they extract information that a compiler can exploit to produce more efficient code. the price paid for these advantages, however, is a loss of expressiveness, generality, and semantic simplicity.this paper presents a generalization of static and dynamic typing---called soft typing---that combines the best features of both approaches. the key idea underlying soft typing is that a static type checker need not reject programs that contain potential type errors. instead, the type checker can insert explicit run-time checks around "suspect" arguments of primitive operations, converting dynamically typed programs into statically type-correct form. the inserted run-time checks identify program phrases that may be erroneous. for soft typing to be effective, the type system must avoid inserting unnecessary run-time checks. to accomplish this objective, we have developed an extension of the ml type system supporting union types and recursive types that assigns types to a wider class of programs than ml. we have also developed an algorithm for frugally inserting run-time checks in programs that do not type check.
dynamo: a transparent dynamic optimization system. we describe the design and implementation of dynamo, a software dynamic optimization system that is capable of transparently improving the performance of a native instruction stream as it executes on the processor. the input native instruction stream to dynamo can be dynamically generated (by a jit for example), or it can come from the execution of a statically compiled native binary. this paper evaluates the dynamo system in the latter, more challenging situation, in order to emphasize the limits, rather than the potential, of the system. our experiments demonstrate that even statically optimized native binaries can be accelerated dynamo, and often by a significant degree. for example, the average performance of -o optimized specint95 benchmark binaries created by the hp product c compiler is improved to a level comparable to their -o4 optimized version running without dynamo. dynamo achieves this by focusing its efforts on optimization opportunities that tend to manifest only at runtime, and hence opportunities that might be difficult for a static compiler to exploit. dynamo's operation is transparent in the sense that it does not depend on any user annotations or binary instrumentation, and does not require multiple runs, or any special compiler, operating system or hardware support. the dynamo prototype presented here is a realistic implementation running on an hp pa-8000 workstation under the hpux 10.20 operating system.
shared memory programming for large scale machines. this paper describes the design and implementation of a scalable run-time system and an optimizing compiler for unified parallel c (upc). an experimental evaluation on bluegene/l®, a distributed-memory machine, demonstrates that the combination of the compiler with the runtime system produces programs with performance comparable to that of efficient mpi programs and good performance scalability up to hundreds of thousands of processors.our runtime system design solves the problem of maintaining shared object consistency efficiently in a distributed memory machine. our compiler infrastructure simplifies the code generated for parallel loops in upc through the elimination of affinity tests, eliminates several levels of indirection for accesses to segments of shared arrays that the compiler can prove to be local, and implements remote update operations through a lower-cost asynchronous message. the performance evaluation uses three well-known benchmarks --- hpc randomaccess, hpc stream and nas cg --- to obtain scaling and absolute performance numbers for these benchmarks on up to 131072 processors, the full bluegene/l machine. these results were used to win the hpc challenge competition at sc05 in seattle wa, demonstrating that pgas languages support both productivity and performance.
composing security policies with polymer. we introduce a language and system that supports definition and composition of complex run-time security policies for java applications. our policies are comprised of two sorts of methods. the first is query methods that are called whenever an untrusted application tries to execute a security-sensitive action. a query method returns a suggestion indicating how the security-sensitive action should be handled. the second sort of methods are those that perform state updates as the policy's suggestions are followed.the structure of our policies facilitates composition, as policies can query other policies for suggestions. in order to give programmers control over policy composition, we have designed the system so that policies, suggestions, and application events are all first-class objects that a higher-order policy may manipulate. we show how to use these programming features by developing a library of policy combinators.our system is fully implemented, and we have defined a formal semantics for an idealized subset of the language containing all of the key features. we demonstrate the effectiveness of our system by implementing a large-scale security policy for an email client.
a portable global optimizer and linker. to reduce complexity and simplify their implementation, most compilers are organized as a set of passes or phases. each phase performs a particular piece of the compilation process. in an optimizing compiler, the assignment of function and order of application of the phases is a critical part of the design. a particularly difficult problem is the arrangement of the code generation and optimization phases so as to avoid phase ordering problems caused by the interaction of the phases. in this paper, we discuss the implementation of a compiler/linker that has been designed to avoid these problems. the key aspect of this design is that the synthesis phases of the compiler and the system linker share the same intermediate program representation. this results in two benefits. it permits the synthesis phases of the compiler to be performed in any order and repeatedly, thus eliminating potential phase ordering problems. second, it permits code selection to be invoked at any point during the synthesis phases as well as at link time. the ability to perform code selection at link time presents many opportunities for additional optimizations. measurements about the effectiveness of using this approach in a c compiler on two different machines are presented.
inducing heuristics to decide whether to schedule. instruction scheduling is a compiler optimization that can improve program speed, sometimes by 10% or more, but it can also be expensive. furthermore, time spent optimizing is more important in a java just-in-time (jit) compiler than in a traditional one because a jit compiles code at run time, adding to the running time of the program. we found that, on any given block of code, instruction scheduling often does not produce significant benefit and sometimes degrades speed. thus, we hoped that we could focus scheduling effort on those blocks that benefit from it.using supervised learning we induced heuristics to predict which blocks benefit from scheduling. the induced function chooses, for each block, between list scheduling and not scheduling the block at all. using the induced function we obtained over 90% of the improvement of scheduling every block but with less than 25% of the scheduling effort. when used in combination with profile-based adaptive optimization, the induced function remains effective but gives a smaller reduction in scheduling effort. deciding when to optimize, and which optimization(s) to apply, is an important open problem area in compiler research. we show that supervised learning solves one of these problems well.
diehard: probabilistic memory safety for unsafe languages. applications written in unsafe languages like c and c++ are vulnerable to memory errors such as buffer overflows, dangling pointers, and reads of uninitialized data. such errors can lead to program crashes, security vulnerabilities, and unpredictable behavior. we present diehard, a runtime system that tolerates these errors while probabilistically maintaining soundness. diehard uses randomization and replication to achieve probabilistic memory safety by approximating an infinite-sized heap. diehard's memory manager randomizes the location of objects in a heap that is at least twice as large as required. this algorithm prevents heap corruption and provides a probabilistic guarantee of avoiding memory errors. for additional safety, diehard can operate in a replicated mode where multiple replicas of the same application are run simultaneously. by initializing each replica with a different random seed and requiring agreement on output, the replicated version of die-hard increases the likelihood of correct execution because errors are unlikely to have the same effect across all replicas. we present analytical and experimental results that show diehard's resilience to a wide range of memory errors, including a heap-based buffer overflow in an actual application.
global communication analysis and optimization. reducing communication cost is crucial to achieving good performance on scalable parallel machines. this paper presents a new compiler algorithm for global analysis and optimization of communication in data-parallel programs. our algorithm is distinct from existing approaches in that rather than handling loop-nests and array references one by one, it considers all communication in a procedure and their interactions under different placements before making a final decision on the placement of any communication. it exploits the flexibility resulting from this advanced analysis to eliminate redundancy, reduce the number of messages, and reduce contention for cache and communication buffers, all in a unified framework. in contrast, single loop-nest analysis often retains redundant communication, and more aggressive dataflow analysis on array sections can generate too many messages or cache and buffer contention. the algorithm has been implemented in the ibm phpf compiler for high performance fortran. during compilation, the number of messages per processor goes down by as much as a factor of nine for some hpf programs. we present performance results for the ibm sp2 and a network of sparc workstations (now) connected by a myrinet switch. in many cases, the communication cost is reduced by a factor of two.
spill code minimization via interference region spilling. many optimizing compilers perform global register allocation using a chaitin-style graph coloring algorithm. live ranges that cannot be allocated to registers are spilled to memory. the amount of code required to spill the live range depends on the spilling heuristic used. chaitin's spilling heuristic offers some guidance in reducing the amount of spill code produced. however, this heuristic does not allow the partial spilling of live ranges and the reduction in spill code is limited to a local level. in this paper, we present a global technique called interference region spilling that improves the spilling granularity of any local spilling heuristic. our technique works above the local spilling heuristic, limiting the normal insertion of spill code to a portion of each spilled live range. by partially spilling live ranges, we can achieve large reductions in dynamically executed spill code; up to 75% in some cases and an average of 33.6% across the benchmarks tested.
customization: optimizing compiler technology for self, a dynamically-typed object-oriented programming language. dynamically-typed object-oriented languages please programmers, but their lack of static type information penalizes performance. our new implementation techniques extract static type information from declaration-free programs. our system compiles several copies of a given procedure, each customized for one receiver type, so that the type of the receiver is bound at compile time. the compiler predicts types that are statically unknown but likely, and inserts run-time type tests to verify its predictions. it splits calls, compiling a copy on each control path, optimized to the specific types on that path. coupling these new techniques with compile-time message lookup, aggressive procedure inlining, and traditional optimizations has doubled the performance of dynamically-typed object-oriented languages.
points-to analysis using bdds. this paper reports on a new approach to solving a subset-based points-to analysis for java using binary decision diagrams (bdds). in the model checking community, bdds have been shown very effective for representing large sets and solving very large verification problems. our work shows that bdds can also be very effective for developing a points-to analysis that is simple to implement and that scales well, in both space and time, to large programs.the paper first introduces bdds and operations on bdds using some simple points-to examples. then, a complete subset-based points-to algorithm is presented, expressed completely using bdds and bdd operations. this algorithm is then refined by finding appropriate variable orderings and by making the algorithm propagate sets incrementally, in order to arrive at a very efficient algorithm. experimental results are given to justify the choice of variable ordering, to demonstrate the improvement due to incrementalization, and to compare the performance of the bdd-based solver to an efficient hand-coded graph-based solver. finally, based on the results of the bdd-based solver, a variety of bdd-based queries are presented, including the points-to query.
making context-sensitive points-to analysis with heap cloning practical for the real world. context-sensitive pointer analysis algorithms with full "heapcloning" are powerful but are widely considered to be too expensive to include in production compilers. this paper shows, for the first time, that a context-sensitive, field-sensitive algorithm with fullheap cloning (by acyclic call paths) can indeed be both scalable and extremely fast in practice. overall, the algorithm is able to analyze programs in the range of 100k-200k lines of c code in 1-3 seconds,takes less than 5% of the time it takes for gcc to compile the code (which includes no whole-program analysis), and scales well across five orders of magnitude of code size. it is also able to analyze the linux kernel (about 355k linesof code) in 3.1 seconds. the paper describes the major algorithmic and engineering design choices that are required to achieve these results, including (a) using flow-insensitive and unification-basedanalysis, which are essential to avoid exponential behavior in practice;(b) sacrificing context-sensitivity within strongly connected components of the call graph; and (c) carefully eliminating several kinds of o(n2) behaviors (largely without affecting precision). the techniques used for (b) and (c) eliminated several major bottlenecks to scalability, and both are generalizable to other context-sensitive algorithms. we show that the engineering choices collectively reduce analysis time by factors of up to 10x-15xin our larger programs, and have found that the savings grow strongly with program size. finally, we briefly summarize results demonstrating the precision of the analysis.
iterative type analysis and extended message splitting: optimizing dynamically-typed object-oriented programs. object-oriented languages have suffered from poor performance caused by frequent and slow dynamically-bound procedure calls. the best way to speed up a procedure call is to compile it out, but dynamic binding of object-oriented procedure calls without static receiver type information precludes inlining. iterative type analysis and extended message splitting are new compilation techniques that extract much of the necessary type information and make it possible to hoist run-time type tests out of loops. our system compiles code on-the-fly that is customized to the actual data types used by a running program. the compiler constructs a control flow graph annotated with type information by simultaneously performing type analysis and inlining. extended message splitting preserves type information that would otherwise be lost by a control-flow merge by duplicating all the code between the merge and the place that uses the information. iterative type analysis computes the types of variables used in a loop by repeatedly recompiling the loop until the computed types reach a fix-point. together these two techniques enable our self compiler to split off a copy of an entire loop, optimized for the common-case types. by the time our self compiler generates code for the graph, it has eliminated many dynamically-dispatched procedure calls and type tests. the resulting machine code is twice as fast as that generated by the previous self compiler, four times faster than parcplace systems smalltalk-80,* the fastest commercially available dynamically-typed object-oriented language implementation, and nearly half the speed of optimized c. iterative type analysis and extended message splitting have cut the performance penalty for dynamically-typed object-oriented languages in half.
profile-guided proactive garbage collection for locality optimization. many applications written in garbage collected languages have large dynamic working sets and poor data locality. we present a new system for continuously improving program data locality at run time with low overhead. our system proactively reorganizes the heap by leveraging the garbage collector and uses profile information collected through a low-overhead mechanism to guide the reorganization at run time. the key contributions include making a case that garbage collection should be viewed as a proactive technique for improving data locality by triggering garbage collection for locality optimization independently of normal garbage collection for space, combining page and cache locality optimization in the same system, and demonstrating that sampling provides sufficiently detailed data access information to guide both page and cache locality optimization with low runtime overhead. we present experimental results obtained by modifying a commercial, state-of-the-art garbage collector to support our claims. independently triggering garbage collection for locality optimization significantly improved optimizations benefits. combining page and cache locality optimizations in the same system provided larger average execution time improvements (17%) than either alone (page 8%, cache 7%). finally, using sampling limited profiling overhead to less than 3%, on average.
data distribution support on distributed shared memory multiprocessors. cache-coherent multiprocessors with distributed shared memory are becoming increasingly popular for parallel computing. however, obtaining high performance on these machines mquires that an application execute with good data locality. in addition to making efiective use of caches, it is often necessary to distribute data structures across the local memories of the processing nodes, thereby reducing the latency of cache misses.we have designed a set of abstractions for performing data distribution in the context of explicitly parallel programs and implemented them within the sgi mipspro compiler system. our system incorporates many unique features to enhance both programmability and performance. we address the former by providing a very simple programmming model with extensive support for error detection. regarding performance, we carefully design the user abstractions with the underlying compiler optimizations in mind, we incorporate several optimization techniques to generate efficient code for accessing distributed data, and we provide a tight integration of these techniques with other optimizations within the compiler our initial experience suggests that the directives are easy to use and can yield substantial performance gains, in some cases by as much as a factor of 3 over the same codes without distribution.
exact analysis of the cache behavior of nested loops. we develop from first principles an exact model of the behavior of loop nests executing in a memory hicrarchy, by using a nontraditional classification of misses that has the key property of composability. we use presburger formulas to express various kinds of misses as well as the state of the cache at the end of the loop nest. we use existing tools to simplify these formulas and to count cache misses. the model is powerful enough to handle imperfect loop nests and various flavors of non-linear array layouts based on bit interleaving of array indices. we also indicate how to handle modest levels of associativity, and how to perform limited symbolic analysis of cache behavior. the complexity of the formulas relates to the static structure of the loop nest rather than to its dynamic trip count, allowing our model to gain efficiency in counting cache misses by exploiting repetitive patterns of cache behavior. validation against cache simulation confirms the exactness of our formulation. our method can serve as the basis for a static performance predictor to guide program and data transformations to improve performance.
prototyping fortran-90 compilers for massively parallel machines. massively parallel architectures, and the languages used to program them, are among both the most difficult and the most rapidly-changing subjects for compilation. this has created a demand for new compiler prototyping technologies that allow novel style of compilation and optimization to be tested in a reasonable amount of time. using formal specification techniques, we have produced a data-parallel fortran-90 subset compiler for thinking machines' connection machine/2 and connection machine/5. the prototype produces code from initial fortran-90 benchmarks demonstrating sustained performance superior to hand-coded lisp and competitive with thinking machines' cm fortran compiler. this paper presents some new specification techniques necessary to construct competitive, easily retargetable prototype compilers.
reducing noc energy consumption through compiler-directed channel voltage scaling. while scalable noc (network-on-chip) based communication architectures have clear advantages over long point-to-point communication channels, their power consumption can be very high. in contrast to most of the existing hardware-based efforts on noc power optimization, this paper proposes a compiler-directed approach where the compiler decides the appropriate voltage/frequency levels to be used for each communication channel in the noc. our approach builds and operates on a novel graph based representation of a parallel program and has been implemented within an optimizing compiler and tested using 12 embedded benchmarks. our experiments indicate that the proposed approach behaves better - from both performance and power perspectives - than a hardwarebased scheme and the energy savings it achieves are very close to the savings that could be obtained from an optimal, but hypothetical voltage/frequency scaling scheme.
shangri-la: achieving high performance from compiled network applications while enabling ease of programming. programming network processors is challenging. to sustain high line rates, network processors have extremely tight memory access and instruction budgets. achieving desired performance has traditionally required hand-coded assembly. researchers have recently proposed high-level programming languages for packet processing, but the challenges of compiling these languages into code that is competitive with hand-tuned assembly remain unanswered.this paper describes the shangri-la compiler, which accepts a packet program written in a c-like high-level language and applies scalar and specialized optimizations to generate a highly optimized binary. hot code paths identified by profiling are mapped across processing elements to maximize processor utilization. since our compilation target has no hardware caches, software-controlled caches are generated for frequently accessed application data structures. packet handling optimizations significantly reduce per-packet memory access and instruction counts. finally, a custom stack model maps stack frames to the fastest levels of the target processor's heterogeneous memory hierarchy.binaries generated by the compiler were evaluated on the intel ixp2400 network processor with eight packet processing cores and eight threads per core. our results show the importance of both traditional and specialized optimization techniques for achieving the maximum forwarding rates on three network applications, l3-switch, mpls and firewall.
a provably sound tal for back-end optimization. typed assembly languages provide a way to generate machine-checkable safety proofs for machine-language programs. but the soundness proofs of most existing typed assembly languages are hand-written and cannot be machine-checked, which is worrisome for such large calculi. we have designed and implemented a low-level typed assembly language (ltal) with a semantic model and established its soundness from the model. compared to existing typed assembly languages, ltal is more scalable and more secure; it has no macro instructions that hinder low-level optimizations such as instruction scheduling; its type constructors are expressive enough to capture dataflow information, support the compiler's choice of data representations and permit typed position-independent code; and its type-checking algorithm is completely syntax-directed.we have built a prototype system, based on standard ml of new jersey, that compiles most of core ml to sparc code. we explain how we were able to make the untyped back end in sml/nj preserve types during instruction selection and register allocation, without restricting low-level optimizations and without knowledge of any type system pervading the instruction selector and register allocator.
a parallel, real-time garbage collector. we describe a parallel, real-time garbage collector and present experimental results that demonstrate good scalability and good real-time bounds. the collector is designed for shared-memory multiprocessors and is based on an earlier collector algorithm [2], which provided fixed bounds on the time any thread must pause for collection. however, since our earlier algorithm was designed for simple analysis, it had some impractical features. this paper presents the extensions necessary for a practical implementation: reducing excessive interleaving, handling stacks and global variables, reducing double allocation, and special treatment of large and small objects. an implementation based on the modified algorithm is evaluated on a set of 15 sml benchmarks on a sun enterprise 10000, a 64-way ultrasparc-ii multiprocessor. to the best of our knowledge, this is the first implementation of a parallel, real-time garbage collector. the average collector speedup is 7.5 at 8 processors and 17.7 at 32 processors. maximum pause times range from 3 ms to 5 ms. in contrast, a non-incremental collector (whether generational or not) has maximum pause times from 10 ms to 650 ms. compared to a non-parallel, stop-copy collector, parallelism has a 39% overhead, while real-time behavior adds an additional 12% overhead. since the collector takes about 15% of total execution time, these features have an overall time costs of 6% and 2%.
modular interprocedural pointer analysis using access paths: design, implementation, and evaluation. in this paper we present a modular interprocedural pointer analysis algorithm based on access-paths for c programs. we argue that access paths can reduce the overhead of representing context-sensitive transfer functions and effectively distinguish non-recursive heap objects. and when the modular analysis paradigm is used together with other techniques to handle type casts and function pointers, we are able to handle significant programs like those in the speccint92 and speccint95 suites. we have implemented the algorithm and tested it on a pentium ii 450 pc running linux. the observed resource consumption and performance improvement are very encouraging.
generational stack collection and profile-driven pretenuring. this paper presents two techniques for improving garbage collection performance: generational stack collection and profile-driven pretenuring. the first is applicable to stack-based implementations of functional languages while the second is useful for any generational collector. we have implemented both techniques in a generational collector used by the til compiler (tarditi, morrisett, cheng, stone, harper, and lee 1996), and have observed decreases in garbage collection times of as much as 70% and 30%, respectively.functional languages encourage the use of recursion which can lead to a long chain of activation records. when a collection occurs, these activation records must be scanned for roots. we show that scanning many activation records can take so long as to become the dominant cost of garbage collection. however, most deep stacks unwind very infrequently, so most of the root information obtained from the stack remains unchanged across successive garbage collections. generational stack collection greatly reduces the stack scan cost by reusing information from previous scans.generational techniques have been successful in reducing the cost of garbage collection (ungar 1984). various complex heap arrangements and tenuring policies have been proposed to increase the effectiveness of generational techniques by reducing the cost and frequency of scanning and copying. in contrast, we show that by using profile information to make lifetime predictions, pretenuring can avoid copying data altogether. in essence, this technique uses a refinement of the generational hypothesis (most data die young) with a locality principle concerning the age of data: most allocations sites produce data that immediately dies, while a few allocation sites consistently produce data that survives many collections.
unified management of registers and cache using liveness and cache bypass. in current computer memory system hierarchy, registers and cache are both used to bridge the reference delay gap between the fast processor(s) and the slow main memory. while registers are managed by the compiler using program flow analysis, cache is mainly controlled by hardware without any program understanding. due to the lack of coordination in managing these two memory structures, significant loss of system performance results because: cache space is wasted to hold inaccessible copies of values in registers. inaccessible copies of values replace those accessible ones from cache. despite the fact that register allocation has long recognized the benefits of live range analysis, current cache management has completely ignored live range information. in this paper, we propose an unified management of registers and cache using liveness and cache bypass. by using a single model to manage these two memory structures, most redundant copies of values in cache can be eliminated. consequently, bus traffic and memory traffic in data cache are greatly reduced and cache effectiveness is improved.
efficient representations and abstractions for quantifying and exploiting data reference locality. with the growing processor-memory performance gap, understanding and optimizing a program's reference locality, and consequently, its cache performance, is becoming increasingly important. unfortunately, current reference locality optimizations rely on heuristics and are fairly ad-hoc. in addition, while optimization technology for improving instruction cache performance is fairly mature (though heuristic-based), data cache optimizations are still at an early stage. we believe the primary reason for this imbalance is the lack of a suitable representation of a program's dynamic data reference behavior and a quantitative basis for understanding this behavior. we address these issues by proposing a quantitative basis for understanding and optimizing reference locality, and by describing efficient data reference representations and an exploitable locality abstraction that support this framework. our data reference representations (whole program streams and stream flow graphs) are compact&mdash;two to four orders of magnitude smaller than the program's data reference trace&mdash;and permit efficient analysis&mdash;on the order of seconds to a few minutes&mdash;even for complex applications. these representations can be used to efficiently compute our exploitable locality abstraction (hot data streams). we demonstrate that these representations and our hot data stream abstraction are useful for quantifying and exploiting data reference locality. we applied our framework to several specint 2000 benchmarks, a graphics program, and a commercial microsoft database application. the results suggest significant opportunity for hot data stream-based locality optimizations.
cache-conscious structure definition. a program's cache performance can be improved by changing the organization and layout of its data---even complex, pointer-based data structures. previous techniques improved the cache performance of these structures by arranging distinct instances to increase reference locality. these techniques produced significant performance improvements, but worked best for small structures that could be packed into a cache block.this paper extends that work by concentrating on the internal organization of fields in a data structure. it describes two techniques---structure splitting and field reordering---that improve the cache behavior of structures larger than a cache block. for structures comparable in size to a cache block, structure splitting can increase the number of hot fields that can be placed in a cache block. in five java programs, structure splitting reduced cache miss rates 10--27% and improved performance 6--18% beyond the benefits of previously described cache-conscious reorganization techniques.for large structures, which span many cache blocks, reordering fields, to place those with high temporal affinity in the same cache block can also improve cache utilization. this paper describes bbcache, a tool that recommends c structure field reorderings. preliminary measurements indicate that reordering fields in 5 active structures improves the performance of microsoft sql server 7.0 2--3%.
dynamic hot data stream prefetching for general-purpose programs. prefetching data ahead of use has the potential to tolerate the grow ing processor-memory performance gap by overlapping long latency memory accesses with useful computation. while sophisti cated prefetching techniques have been automated for limited domains, such as scientific codes that access dense arrays in loop nests, a similar level of success has eluded general-purpose pro grams, especially pointer-chasing codes written in languages such as c and c++. we address this problem by describing, implementing and evaluating a dynamic prefetching scheme. our technique runs on stock hardware, is completely automatic, and works for general-purpose programs, including pointer-chasing codes written in weakly-typed languages, such as c and c++. it operates in three phases. first, the profiling phase gathers a temporal data reference profile from a running program with low-overhead. next, the profiling is turned off and a fast analysis algorithm extracts hot data streams, which are data reference sequences that frequently repeat in the same order, from the temporal profile. then, the system dynamically injects code at appropriate program points to detect and prefetch these hot data streams. finally, the process enters the hibernation phase where no profiling or analysis is performed, and the program continues to execute with the added prefetch instructions. at the end of the hibernation phase, the program is de-optimized to remove the inserted checks and prefetch instructions, and control returns to the profiling phase. for long-running programs, this profile, analyze and optimize, hibernate, cycle will repeat multiple times. our initial results from applying dynamic prefetching are promising, indicating overall execution time improvements of 5.19% for several memory-performance-limited specint2000 benchmarks running their largest (ref) inputs.
cache-conscious structure layout. hardware trends have produced an increasing disparity between processor speeds and memory access times. while a variety of techniques for tolerating or reducing memory latency have been proposed, these are rarely successful for pointer-manipulating programs.this paper explores a complementary approach that attacks the source (poor reference locality) of the problem rather than its manifestation (memory latency). it demonstrates that careful data organization and layout provides an essential mechanism to improve the cache locality of pointer-manipulating programs and consequently, their performance. it explores two placement techniques---clustering and coloring---that improve cache performance by increasing a pointer structure's spatial and temporal locality, and by reducing cache-conflicts.to reduce the cost of applying these techniques, this paper discusses two strategies---cache-conscious reorganization and cache-conscious allocation---and describes two semi-automatic tools---ccmorph and ccmalloc---that use these strategies to produce cache-conscious pointer structure layouts. ccmorph is a transparent tree reorganizer that utilizes topology information to cluster and color the structure. ccmalloc is a cache-conscious heap allocator that attempts to co-locate contemporaneously accessed data elements in the same physical cache block. our evaluations, with microbenchmarks, several small benchmarks, and a couple of large real-world applications, demonstrate that the cache-conscious structure layouts produced by ccmorph and ccmalloc offer large performance benefits---in most cases, significantly outperforming state-of-the-art prefetching.
cache-conscious coallocation of hot data streams. the memory system performance of many programs can be improved by coallocating contemporaneously accessed heap objects in the same cache block. we present a novel profile-based analysis for producing such a layout. the analysis achieves cacheconscious coallocation of a hot data stream h (i.e., a regular data access pattern that frequently repeats) by isolating and combining allocation sites of object instances that appear in h such that intervening allocations coming from other sites are separated. the coallocation solution produced by the analysis is enforced by an automatic tool, cminstr, that redirects a program's heap allocations to a run-time coallocation library comalloc. we also extend the analysis to coallocation at object field granularity. the resulting field coallocation solution generalizes common data restructuring techniques, such as field reordering, object splitting, and object merging, and allows their combination. furthermore, it provides insight into object restructuring by breaking down the coallocation benefit on a per-technique basis, which provides the opportunity to pick the "sweet spot" for each program. experimental results using a set of memory-performance-limited benchmarks, including a few specint2000 programs, and microsoft visualfoxpro, indicate that programs possess significant coallocation opportunities. automatic object coallocation improves execution time by 13% on average in the presence of hardware prefetching. hand-implemented field coallocation solutions for two of the benchmarks produced additional improvements (12% and 22%) but the effort involved suggests implementing an automated version for type-safe languages, such as java and c#.
region inference for an object-oriented language. region-based memory management offers several important potential advantages over garbage collection, including real-time performance, better data locality, and more efficient use of limited memory. researchers have advocated the use of regions for functional, imperative, and object-oriented languages. lexically scoped regions are now a core feature of the real-time specification for java (rtsj)[5].recent research in region-based programming for java has focused on region checking, which requires manual effort to augment the program with region annotations. in this paper, we propose an automatic region inference system for a core subset of java. to provide an inference method that is both precise and practical, we support classes and methods that are region-polymorphic, with region-polymorphic recursion for methods. one challenging aspect is to ensure region safety in the presence of features such as class subtyping, method overriding, and downcast operations. our region inference rules can handle these object-oriented features safely without creating dangling references.
semantic type qualifiers. we present a new approach for supporting user-defined type refinements, which augment existing types to specify and check additional invariants of interest to programmers. we provide an expressive language in which users define new refinements and associated type rules. these rules are automatically incorporated by an extensible typechecker during static typechecking of programs. separately, a soundness checkerautomatically proves that each refinement's type rules ensure the intended invariant, for all possible programs. we have formalized our approach and have instantiated it as a framework for adding new type qualifiers to c programs. we have used this framework to define and automatically prove sound a host of type qualifiers of different sorts, including pos and neg for integers, tainted and untainted for strings, and nonnull and unique for pointers, and we have applied our qualifiers to ensure important invariants on open-source c programs.
efficient and precise datarace detection for multithreaded object-oriented programs. we present a novel approach to dynamic datarace detection for multithreaded object-oriented programs. past techniques for on-the-fly datarace detection either sacrificed precision for performance, leading to many false positive datarace reports, or maintained precision but incurred significant overheads in the range of 3x to 30x. in contrast, our approach results in very few false positives and runtime overhead in the 13% to 42% range, making it both efficient and precise. this performance improvement is the result of a unique combination of complementary static and dynamic optimization techniques.
minimizing register usage penalty at procedure calls. inter-procedural register allocation can minimize the register usage penalty at procedure calls by reducing the saving and restoring of registers at procedure boundaries. a one-pass inter-procedural register allocation scheme based on processing the procedures in a depth-first traversal of the call graph is presented. this scheme can be overlaid on top of intra-procedural register allocation via a simple extension to the priority-based coloring algorithm. using two different usage conventions for the registers, the scheme can distribute register saves/restores throughout the call graph even in the presence of recursion, indirect calls or separate compilation. a natural and efficient way to pass parameters emerges from this scheme. a separate technique uses data flow analysis to optimize the placement of the save/restore code for registers within individual procedures. the techniques described have been implemented in a production compiler suite. measurements of the effects of these techniques on a set of practical programs are presented and the results analysed.
a new algorithm for partial redundancy elimination based on ssa form. a new algorithm, ssapre, for performing partial redundancy elimination based entirely on ssa form is presented. it achieves optimal code motion similar to lazy code motion [krs94a, ds93], but is formulated independently and does not involve iterative data flow analysis and bit vectors in its solution. it not only exhibits the characteristics common to other sparse approaches, but also inherits the advantages shared by other ssa-based optimization techniques. ssapre also maintains its output in the same ssa form as its input. in describing the algorithm, we state theorems with proofs giving our claims about ssapre. we also give additional description about our practical implementation of ssapre, and analyze and compare its performance with a bit-vector-based implementation of pre. we conclude with some discussion of the implications of this work.
region-based hierarchical operation partitioning for multicluster processors. clustered architectures are a solution to the bottleneck of centralized register files in superscalar and vliw processors. the main challenge associated with clustered architectures is compiler support to effectively partition operations across the available resources on each cluster. in this work, we present a novel technique for clustering operations based on graph partitioning methods. our approach incorporates new methods of assigning weights to nodes and edges within the dataflow graph to guide the partitioner. nodes are assigned weights to reflect their resource usage within a cluster, while a slack distribution method intelligently assigns weights to edges to reflect the cost of inserting moves across clusters. a multilevel graph partitioning algorithm, which globally divides a dataflow graph into multiple parts in a hierarchical manner, uses these weights to efficiently generate estimates for the quality of partitions. we found that our algorithm was able to achieve an average of 20% improvement in dsp kernels and 5% improvement in specint2000 for a four-cluster architecture.
unifying data and control transformations for distributed shared memory machines. we present a unified approach to locality optimization that employs both data and control transformations. data transformations include changing the array layout in memory. control transformations involve changing the execution order of programs. we have developed new techniques for compiler optimizations for distributed shared-memory machines, although the same techniques can be used for sequential machines with a memory hierarchy.our compiler optimizations are based on an algebraic representation of data mappings and a new data locality model. we present a pure data transformation algorithm and an algorithm unifying data and control transformations. while there has been much work on control transformations, the opportunities for data transformations have been largely neglected. in fact, data transformations have the advantage of being applicable to programs that cannot be optimized with control transformations. the unified algorithm, which performs data and control transformations simultaneously, offers improvement over optimizations obtained by applying data and control transformations separately.the experimental results using a set of applications on a parallel machine show that the new optimizations improve performance significantly. these results are further analyzed using locality metrics with instrumentation and simulation.
practicing judo: java under dynamic optimizations. a high-performance implementation of a java virtual machine (jvm) consists of efficient implementation of just-in-time (jit) compilation, exception handling, synchronization mechanism, and garbage collection (gc). these components are tightly coupled to achieve high performance. in this paper, we present some static anddynamic techniques implemented in the jit compilation and exception handling of the microprocessor research lab virtual machine (mrl vm), i.e., lazy exceptions, lazy gc mapping, dynamic patching, and bounds checking elimination. our experiments used ia-32 as the hardware platform, but the optimizations can be generalized to other architectures.
the jade interpreter: a risc interpreter for syntax directed editing. this paper describes key features of an interpreter for a language-based editor. the interpreter unites in a risc framework features which have been used in other domains. the paper examines each feature's integration into the risc framework.
how to read floating-point numbers accurately. converting decimal scientific notation into binary floating point is nontrivial, but this conversion can be performed with the best possible accuracy without sacrificing efficiency.consider the problem of converting decimal scientific notation for a number into the best binary floating point approximation to that number, for some fixed precision. this problem cannot be solved using arithmetic of any fixed precision. hence the ieee standard for binary floating-point arithmetic does not require the result of such a conversion to be the best approximation.this paper presents an efficient algorithm that always finds the best approximation. the algorithm uses a few extra bits of precision to compute an ieee-conforming approximation while testing an intermediate result to determine whether the approximation could be other than the best. if the approximation might not be the best, then the best approximation is determined by a few simple operations on multiple-precision integers, where the precision is determined by the input. when using 64 bits of precision to compute ieee double precision results, the algorithm avoids higher-precision arithmetic over 99% of the time.the input problem considered by this paper is the inverse of an output problem considered by steele and white: given a binary floating point number, print a correctly rounded decimal representation of it using the smallest number of digits that will allow the number to be read without loss of accuracy. the steele and white algorithm assumes that the input problem is solved; an imperfect solution to the input problem, as allowed by the ieee standard and ubiquitous in current practice, defeats the purpose of their algorithm.
proper tail recursion and space efficiency. the ieee/ansi standard for scheme requires implementations to be properly tail recursive. this ensures that portable code can rely upon the space efficiency of continuation-passing style and other idioms. on its face, proper tail recursion concerns the efficiency of procedure calls that occur within a tail context. when examined closely, proper tail recursion also depends upon the fact that garbage collection can be asymptotically more space-efficient than algol-like stack allocation.proper tail recursion is not the same as ad hoc tail call optimization in stack-based languages. proper tail recursion often precludes stack allocation of variables, but yields a well-defined asymptotic space complexity that can be relied upon by portable programs.this paper offers a formal and implementation-independent definition of proper tail recursion for scheme. it also shows how an entire family of reference implementations can be used to characterize related safe-for-space properties, and proves the asymptotic inequalities that hold between them.
generational garbage collection and the radioactive decay model. if a fixed exponentially decreasing probability distribution function is used to model every object's lifetime, then the age of an object gives no information about its future life expectancy. this radioactive decay model implies there can be no rational basis for deciding which live objects should be promoted to another generation. yet there remains a rational basis for deciding how many objects to promote, when to collect garbage, and which generations to collect.analysis of the model leads to a new kind of generational garbage collector whose effectiveness does not depend upon heuristics that predict which objects will live longer than others.this result provides insight into the computational advantages of generational garbage collection, with implications for the management of objects whose life expectancies are difficult to predict.
space-time trade-off optimization for a class of electronic structure calculations. the accurate modeling of the electronic structure of atoms and molecules is very computationally intensive. many models of electronic structure, such as the coupled cluster approach, involve collections of tensor contractions. there are usually a large number of alternative ways of implementing the tensor contractions, representing different trade-offs between the space required for temporary intermediates and the total number of arithmetic operations. in this paper, we present an algorithm that starts with an operation-minimal form of the computation and systematically explores the possible space-time trade-offs to identify the form with lowest cost that fits within a specified memory limit. its utility is demonstrated by applying it to a computation representative of a component in the ccsd(t) formulation in the nwchem quantum chemistry suite from pacific northwest national laboratory.
automatically closing open reactive programs. we study in this paper the problem of analyzing implementations of open systems --- systems in which only some of the components are present. we present an algorithm for automatically closing an open concurrent reactive system with its most general environment, i.e., the environment that can provide any input at any time to the system. the result is a nondeterministic closed (i.e., self-executable) system which can exhibit all the possible reactive behaviors of the original open system. these behaviors can then be analyzed using verisoft, an existing tool for systematically exploring the state spaces of closed systems composed of multiple (possibly nondeterministic) processes executing arbitrary code. we have implemented the techniques introduced in this paper in a prototype tool for automatically closing open programs written in the c programming language. we discuss preliminary experimental results obtained with a large telephone-switching software application developed at lucent technologies.
a certifying compiler for java. this paper presents the initial results of a project to determine if the techniques of proof-carrying code and certifying compilers can be applied to programming languages of realistic size and complexity. the experiment shows that: (1) it is possible to implement a certifying native-code compiler for a large subset of the java programming language; (2) the compiler is freely able to apply many standard local and global optimizations; and (3) the pcc binaries it produces are of reasonable size and can be rapidly checked for type safety by a small proof-checker. this paper also presents further evidence that pcc provides several advantages for compiler development. in particular, generating proofs of the target code helps to identify compiler bugs, many of which would have been difficult to discover by testing.
tile size selection using cache organization and data layout. when dense matrix computations are too large to fit in cache, previous research proposes tiling to reduce or eliminate capacity misses. this paper presents a new algorithm for choosing problem-size dependent tile sizes based on the cache size and cache line size for a direct-mapped cache. the algorithm eliminates both capacity and self-interference misses and reduces cross-interference misses. we measured simulated miss rates and execution times for our algorithm and two others on a variety of problem sizes and cache organizations. at higher set associativity, our algorithm does not always achieve the best performance. however on direct-mapped caches, our algorithm improves simulated miss rates and measured execution times when compared with previous work.
reverse interpretation + mutation analysis = automatic retargeting. there are three popular methods for constructing highly retargetable compilers: (1) the compiler emits abstract machine code which is interpreted at run-time, (2) the compiler emits c code which is subsequently compiled to machine code by the native c compiler, or (3) the compiler's code-generator is generated by a back-end generator from a formal machine description produced by the compiler writer.these methods incur high costs at run-time, compile-time, or compiler-construction time, respectively.in this paper we will describe a novel method which promises to significantly reduce the effort required to retarget a compiler to a new architecture, while at the same time producing fast and effective compilers. the basic idea is to use the native c compiler at compiler construction time to discover architectural features of the new architecture. from this information a formal machine description is produced. given this machine description, a native code-generator can be generated by a back-end generator such as beg or burg.a prototype automatic architecture discovery unit has been implemented. the current version is general enough to produce machine descriptions for the integer instruction sets of common risc and cisc architectures such as the sun sparc, digital alpha, mips, dec vax, and intel x86. the tool is completely automatic and requires minimal input from the user: principally, the user needs to provide the internet address of the target machine and the command-lines by which the c compiler, assembler, and linker are invoked.
dynamic path-based software watermarking. software watermarking is a tool used to combat software piracy by embedding identifying information into a program. most existing proposals for software watermarking have the shortcoming that the mark can be destroyed via fairly straightforward semantics-preserving code transformations. this paper introduces path-based watermarking, a new approach to software watermarking based on the dynamic branching behavior of programs. the advantage of this technique is that error-correcting and tamper-proofing techniques can be used to make path-based watermarks resilient against a wide variety of attacks. experimental results, using both java bytecode and ia-32 native code, indicate that even relatively large watermarks can be embedded into programs at modest cost.
ccured in the real world. ccured is a program transformation system that adds memory safety guarantees to c programs by verifying statically that memory errors cannot occur and by inserting run-time checks where static verification is insufficient.this paper addresses major usability issues in a previous version of ccured, in which many type casts required the use of pointers whose representation was expensive and incompatible with precompiled libraries. we have extended the ccured type inference algorithm to recognize and verify statically a large number of type casts; this goal is achieved by using physical subtyping and pointers with run-time type information to allow parametric and subtype polymorphism. in addition, we present a new instrumentation scheme that splits ccured's metadata into a separate data structure whose shape mirrors that of the original user data. this scheme allows instrumented programs to invoke external functions directly on the program's data without the use of a wrapper function.with these extensions we were able to use ccured on real-world security-critical network daemons and to produce instrumented versions without memory-safety vulnerabilities.
termination proofs for systems code. program termination is central to the process of ensuring that systems code can always react. we describe a new program termination prover that performs a path-sensitive and context-sensitive program analysis and provides capacity for large program fragments (i.e. more than 20,000 lines of code) together with support for programming language features such as arbitrarily nested loops, pointers, function-pointers, side-effects, etc.we also present experimental results on device driver dispatch routines from thewindows operating system. the most distinguishing aspect of our tool is how it shifts the balance between the two tasks of constructing and respectively checking the termination argument. checking becomes the hard step. in this paper we show how we solve the corresponding challenge of checking with binary reachability analysis.
interprocedural side-effect analysis in linear time. we present a new method for solving banning's alias-free flow-insensitive side-effect analysis problem. the algorithm employs a new data structure, called the binding multi-graph, along with depth-first search to achieve a running time that is linear in the size of the call multi-graph of the program. this method can be extended to produce fast algorithms for data-flow problems with more complex lattice structures.
enhanced code compression for embedded risc processors. this paper explores compiler techniques for reducing the memory needed to load and run program executables. in embedded systems, where economic incentives to reduce both ram and rom are strong, the size of compiled code is increasingly important. similarly, in mobile and network computing, the need to transmit an executable before running it places a premium on code size. our work focuses on reducing the size of a program's code segment, using pattern-matching techniques to identify and coalesce together repeated instruction sequences. in contrast to other methods, our framework preserves the ability to run program executables directly, without an intervening decompression stage. our compression framework is integrated into an industrial-strength optimizing compiler, which allows us to explore the interaction between code compression and classical code optimization techniques, and requires that we contend with the difficulties of compressing previously optimized code. the specific contributions in this paper include a comprehensive experimental evaluation of code compression for a risc-like architecture, a more powerful pattern-matching scheme for improved identification of repeated code fragments, and a new form of profile-driven code compression that reduces the speed penalty arising from compression.
design of an interpretive environment for turing. this paper presents the design of an interpreter structure for modern programming languages such as turing and modula ii that is modular and highly orthogonal while providing maximal flexibility and efficiency in implementation. at the outermost level, the structure consists of a front end, responsible for interaction with the user, and a back end, responsible for execution. the two are linked by a single database consisting of the tokenized statements of the user program. interfaces between the major modules of each part are defined in such a way as to maximize reusability, and each interface can service a range of plug-compatible modules implementing radically different semantics. the design accommodates a wide spectrum of interpreter types ranging from batch-oriented compiler-simulators to statement-by-statement interactive execution, and provides for a range of program editing tools from simple line editors through to modern language-directed programming environments. it has served as the basis for several interpretive systems including the production turing interpreter, the turing programming environment, and the turing tool software maintenance tool.
an lr substring parser for noncorrecting syntax error recovery. for a context-free grammar g, a construction is given to produce an lr parser that recognizes any substring of the language generated by g. the construction yields a conflict-free (deterministic) parser for the bounded context class of grammars (floyd, 1964). the same construction yields either a left-to-right or right-to-left substring parser, as required to implement non-correcting syntax error recovery as proposed by richter (1985). experience in constructing a substring parser for pascal is described.
type-dependent parameter inference. an algorithm is presented to infer the type and operation parameters of polymorphic functions. operation parameters are named and typed at the function definition, but are selected from the set of overloaded definitions available wherever the function is used. these parameters are always implicit, implying that the complexity of using a function does not increase with the generality of its type.
doc: a practical approach to source-level debugging of globally optimized code. as optimizing compilers become more sophisticated, the problem of debugging the source code of an application becomes more difficult. in order to investigate this problem, we implemented doc, a prototype solution for debugging optimized code. doc is a modification of the existing c compiler and source-level symbolic debugger for the hp9000 series 800. this paper describes our experiences in this effort. we show in an actual implementation that source-level debugging of globally optimized code is viable.
what is a recursive module? a hierarchical module system is an effective tool for structuring large programs. strictly hierarchical module systems impose an acyclic ordering on import dependencies among program units. this can impede modular programming by forcing mutually-dependent components to be consolidated into a single module. recently there have been several proposals for module systems that admit cyclic dependencies, but it is not clear how these proposals relate to one another, nor how one might integrate them into an expressive module system such as that of ml.to address this question we provide a type-theoretic analysis of the notion of a recursive module in the context of a "phase-distinction" formalism for higher-order module systems. we extend this calculus with a recursive module mechanism and a new form of signature, called a recursively dependent signature, to support the definition of recursive modules. these extensions are justified by an interpretation in terms of more primitive language constructs. this interpretation may also serve as a guide for implementation.
efficient accomodation of may-alias information in ssa form. we present an algorithm for incrementally including may-alias information into static single assignment form by computing a sequence of increasingly precise (and correspondingly larger) partial ssa forms. our experiments show significant speedup of our method over exhaustive use of may-alias information, as optimization problems converge well before most may-aliases are needed.
automatically partitioning packet processing applications for pipelined architectures. modern network processors employs parallel processing engines (pes) to keep up with explosive internet packet processing demands. most network processors further allow processing engines to be organized in a pipelined fashion to enable higher processing throughput and flexibility. in this paper, we present a novel program transformation technique to exploit parallel and pipelined computing power of modern network processors. our proposed method automatically partitions a sequential packet processing application into coordinated pipelined parallel subtasks which can be naturally mapped to contemporary high-performance network processors. our transformation technique ensures that packet processing tasks are balanced among pipeline stages and that data transmission between pipeline stages is minimized. we have implemented the proposed transformation method in an auto-partitioning c compiler product for intel network processors. experimental results show that our method provides impressive speed up for the commonly used npf ipv4 forwarding and ip forwarding benchmarks. for a 9-stage pipeline, our auto-partitioning c compiler obtained more than 4x speedup for the ipv4 forwarding pps and the ip forwarding pps (for both the ipv4 traffic and ipv6 traffic).
memory allocation and higher-order functions. this paper presents a constant-time marking-collecting algorithm to efficiently implement recursion with a general heap memory rather than with a vectorial stack, in a context of frequent captures of continuations. it has been seen to reduce the 80% garbage collection overhead to less than 5% on average.the algorithm has been built into a virtual machine to efficiently implement at the assembly level the actor language plasma, an actor-oriented version of prolog and a variant of scheme, currently in use on 8086, 68000 and vax.the rationale to use the heap memory is that continuations are available via a single pointer in a unified memory and can be shared optimally when recurrently captured, which is simply impossible using a strategy based on stack recopy. further, non-captured continuations can be incrementally garbage collected on the fly.part i describes the elementary recursive instructions of the virtual machine. part ii presents and proves the marking-collecting strategy. part iii safely generalizes the transformation "call + return = branch" in a way compatible with the possible capture of the current continuation. an appendix relates its integration in the virtual scheme machine supporting scheme 84.
esp: path-sensitive program verification in polynomial time. in this paper, we present a new algorithm for partial program verification that runs in polynomial time and space. we are interested in checking that a program satisfies a given temporal safety property. our insight is that by accurately modeling only those branches in a program for which the property-related behavior differs along the arms of the branch, we can design an algorithm that is accurate enough to verify the program with respect to the given property, without paying the potentially exponential cost of full path-sensitive analysis.we have implemented this "property simulation" algorithm as part of a partial verification tool called esp. we present the results of applying esp to the problem of verifying the file i/o behavior of a version of the gnu c compiler (gcc, 140,000 loc). we are able to prove that all of the 646 calls to .fprintf in the source code of gcc are guaranteed to print to valid, open files. our results show that property simulation scales to large programs and is accurate enough to verify meaningful properties.
cint: a risc interpreter for the c programming language. cint is an interpretation system for the c programming language. like most interpretation systems, it provides "load and go" type execution as well as enhanced debugging and performance analysis tools. cint consists of two phases--a translator and an interpreter. the translator compiles the source program into code for a virtual machine. the interpreter then loads and executes this code. while providing services similar to traditional interpreters, cint differs from them in two important ways. first, the virtual machine languages used by many interpreters are quite large; machines with 100 to 200 operations are common. in contrast, cint's virtual machine has only 63 operations. second, to achieve acceptable execution speeds, interpreters are often implemented in the assembly language of the host machine. cint, however, is written entirely in c and is therefore portable. in fact, it has been transported to four machines without modification. despite the compact size of the virtual machine language and the high-level language implementation, cint's execution speed is comparable to that of other interpreters. this paper describes the design of the virtual machine, the implementation of the interpreter, and the performance of the system.
memory access coalescing: a technique for eliminating redundant memory accesses. as microprocessor speeds increase, memory bandwidth is increasingly the performance bottleneck for microprocessors. this has occurred because innovation and technological improvements in processor design have outpaced advances in memory design. most attempts at addressing this problem have involved hardware solutions. unfortunately, these solutions do little to help the situation with respect to current microprocessors. in previous work, we developed, implemented, and evaluated an algorithm that exploited the ability of newer machines with wide-buses to load/store multiple floating-point operands in a single memory reference. this paper describes a general code improvement algorithm that transforms code to better exploit the available memory bandwidth on existing microprocessors as well as wide-bus machines. where possible and advantageous, the algorithm coalesces narrow memory references into wide ones. an interesting characteristic of the algorithm is that some decisions about the applicability of the transformation are made at run time. this dynamic analysis significantly increases the probability of the transformation being applied. the code improvement transformation was implemented and added to the repertoire of code improvements of an existing retargetable optimizing back end. using three current architectures as evaluation platforms, the effectiveness of the transformation was measured on a set of compute- and memory-intensive programs. interestingly, the effectiveness of the transformation varied significantly with respect to the instruction-set architecture of the tested platform. for one of the tested architectures, improvements in execution speed ranging from 5 to 40 percent were observed. for another, the improvements in execution speed ranged from 5 to 20 percent, while for yet another, the transformation resulted in slower code for all programs.
selective specialization for object-oriented languages. dynamic dispatching is a major source of run-time overhead in object-oriented languages, due both to the direct cost of method lookup and to the indirect effect of preventing other optimizations. to reduce this overhead, optimizing compilers for object-oriented languages analyze the classes of objects stored in program variables, with the goal of bounding the possible classes of message receivers enough so that the compiler can uniquely determine the target of a message send at compile time and replace the message send with a direct procedure call. specialization is one important technique for improving the precision of this static class information: by compiling multiple versions of a method, each applicable to a subset of the possible argument classes of the method, more precise static information about the classes of the method's arguments is obtained. previous specialization strategies have not been selective about where this technique is applied, and therefore tended to significantly increase compile time and code space usage, particularly for large applications. in this paper, we present a more general framework for specialization in object-oriented languages and describe a goal directed specialization algorithm that makes selective decisions to apply specialization to those cases where it provides the highest benefit. our results show that our algorithm improves the performance of a group of sizeable programs by 65% to 275% while increasing compiled code space requirements by only 4% to 10%. moreover, when compared to the previous state-of-the-art specialization scheme, our algorithm improves performance by 11% to 67% while simultaneously reducing code space requirements by 65% to 73%.
unfold/fold transformations and loop optimization of logic programs. programs typically spend much of their execution time in loops. this makes the generation of efficient code for loops essential for good performance. loop optimization of logic programming languages is complicated by the fact that such languages lack the iterative constructs of traditional languages, and instead use recursion to express loops. in this paper, we examine the application of unfold/fold transformations to three kinds of loop optimization for logic programming languages: recursion removal, loop fusion and code motion out of loops. we describe simple unfold/fold transformation sequences for these optimizations that can be automated relatively easily. in the process, we show that the properties of unification and logical variables can sometimes be used to generalize, from traditional languages, the conditions under which these optimizations may be carried out. our experience suggests that such source-level transformations may be used as an effective tool for the optimization of logic programs.
profile-guided code compression. as computers are increasingly used in contexts where the amount of available memory is limited, it becomes important to devise techniques that reduce the memory footprint of application programs while leaving them in an executable form. this paper describes an approach to applying data compression techniques to reduce the size of infrequently executed portions of a program. the compressed code is decompressed dynamically (via software) if needed, prior to execution. the use of data compression techniques increases the amount of code size reduction that can be achieved; their application to infrequently executed code limits the runtime overhead due to dynamic decompression; and the use of software decompression renders the approach generally applicable, without requiring specialized hardware. the code size reductions obtained depend on the threshold used to determine what code is "infrequently executed" and hence should be compressed: for low thresholds, we see size reductions of 13.7% to 18.8%, on average, for a set of embedded applications, without excessive runtime overhead.
task granularity analysis in logic programs. while logic programming languages offer a great deal of scope for parallelism, there is usually some overhead associated with the execution of goals in parallel because of the work involved in task creation and scheduling. in practice, therefore, the &ldquo;granularity&rdquo; of a goal, i.e. an estimate of the work available under it, should be taken into account when deciding whether or not to execute a goal concurrently as a separate task. this paper describes a method for estimating the granularity of a goal at compile time. the runtime overhead associated with our approach is usually quite small, and the performance improvements resulting from the incorporation of grainsize control can be quite good. this is shown by means of experimental results.
interprocedural may-alias analysis for pointers: beyond -limiting. existing methods for alias analysis of recursive pointer data structures are based on two approximation techniques: k-limiting, and store-based (or equivalently location or region-based) approximations, which blur distinction between elements of recursive data structures. although notable progress in inter-procedural alias analysis has been recently accomplished, very little progress in the precision of analysis of recursive pointer data structures has been seen since the inception of these approximation techniques by jones and muchnick a decade ago. as a result, optimizing, verifying and parallelizing programs with pointers has remained difficult. we present a new parametric framework for analyzing recursive pointer data structures which can express a new natural class of alias information not accessible to existing methods. the key idea is to represent alias information by pairs of symbolic access paths which are qualified by symbolic descriptions of the positions for which the alias pair holds. based on this result, we present an algorithm for interprocedural may-alias analysis with pointers which on numerous examples that occur in practice is much more precise than recently published algorithms [cwz90, he90, lr92, cbc93].
safecode: enforcing alias analysis for weakly typed languages. static analysis of programs in weakly typed languages such as c and c++ is generally not sound because of possible memory errors due to dangling pointer references, uninitialized pointers, and array bounds overflow. we describe a compilation strategy for standard c programs that guarantees that aggressive interprocedural pointer analysis (or less precise ones), a call graph, and type information for a subset of memory, are never invalidated by any possible memory errors. we formalize our approach as a new type system with the necessary run-time checks in operational semantics and prove the correctness of our approach for a subset of c. our semantics provide the foundation for other sophisticated static analyses to be applied to c programs with a guarantee of soundness. our work builds on a previously published transformation called automatic pool allocation to ensure that hard-to-detect memory errors (dangling pointer references and certain array bounds errors) cannot invalidate the call graph, points-to information or type information. the key insight behind our approach is that pool allocation can be used to create a run-time partitioning of memory that matches the compile-time memory partitioning in a points-to graph, and efficient checks can be used to isolate the run-time partitions. furthermore, we show that the sound analysis information enables static checking techniques that eliminate many run-time checks. our approach requires no source code changes, allows memory to be managedexplicitly, and does not use meta-data on pointers or individual tag bits for memory. using several benchmark s and system codes, we show experimentally that the run-time overheads are low (less than 10% in nearly all cases and 30% in the worst case we have seen).we also show the effectiveness of static analyses in eliminating run-time checks.
improving cache performance in dynamic applications through data and computation reorganization at run time. with the rapid improvement of processor speed, performance of the memory hierarchy has become the principal bottleneck for most applications. a number of compiler transformations have been developed to improve data reuse in cache and registers, thus reducing the total number of direct memory accesses in a program. until now, however, most data reuse transformations have been static---applied only at compile time. as a result, these transformations cannot be used to optimize irregular and dynamic applications, in which the data layout and data access patterns remain unknown until run time and may even change during the computation.in this paper, we explore ways to achieve better data reuse in irregular and dynamic applications by building on the inspector-executor method used by saltz for run-time parallelization. in particular, we present and evaluate a dynamic approach for improving both computation and data locality in irregular programs. our results demonstrate that run-time program transformations can substantially improve computation and data locality and, despite the complexity and cost involved, a compiler can automate such transformations, eliminating much of the associated run-time overhead.
predicting whole-program locality through reuse distance analysis. profiling can accurately analyze program behavior for select data inputs. we show that profiling can also predict program locality for inputs other than profiled ones. here locality is defined by the distance of data reuse. studying whole-program data reuse may reveal global patterns not apparent in short-distance reuses or local control flow. however, the analysis must meet two requirements to be useful. the first is efficiency. it needs to analyze all accesses to all data elements in full-size benchmarks and to measure distance of any length and in any required precision. the second is predication. based on a few training runs, it needs to classify patterns as regular and irregular and, for regular ones, it should predict their (changing) behavior for other inputs. in this paper, we show that these goals are attainable through three techniques: approximate analysis of reuse distance (originally called lru stack distance), pattern recognition, and distance-based sampling. when tested on 15 integer and floating-point programs from spec and other benchmark suites, our techniques predict with on average 94% accuracy for data inputs up to hundreds times larger than the training inputs. based on these results, the paper discusses possible uses of this analysis.
dynamic feedback: an effective technique for adaptive computing. this paper presents dynamic feedback, a technique that enables computations to adapt dynamically to different execution environments. a compiler that uses dynamic feedback produces several different versions of the same source code; each version uses a different optimization policy. the generated code alternately performs sampling phases and production phases. each sampling phase measures the overhead of each version in the current environment. each production phase uses the version with the least overhead in the previous sampling phase. the computation periodically resamples to adjust dynamically to changes in the environment.we have implemented dynamic feedback in the context of a parallelizing compiler for object-based programs. the generated code uses dynamic feedback to automatically choose the best synchronization optimization policy. our experimental results show that the synchronization optimization policy has a significant impact on the overall performance of the computation, that the best policy varies from program to program, that the compiler is unable to statically choose the best policy, and that dynamic feedback enables the generated code to exhibit performance that is comparable to that of code that has been manually tuned to use the best policy. we have also performed a theoretical analysis which provides, under certain assumptions, a guaranteed optimality bound for dynamic feedback relative to a hypothetical (and unrealizable) optimal algorithm that uses the best policy at every point during the execution.
compiler support for garbage collection in a statically typed language. we consider the problem of supporting compacting garbage collection in the presence of modern compiler optimizations. since our collector may move any heap object, it must accurately locate, follow, and update all pointers and values derived from pointers. to assist the collector, we extend the compiler to emit tables describing live pointers, and values derived from pointers, at each program location where collection may occur. significant results include identification of a number of problems posed by optimizations, solutions to those problems, a working compiler, and experimental data concerning table sizes, table compression, and time overhead of decoding tables during collection. while gc support can affect the code produced, our sample programs show no significant changes, the table sizes are a modest fraction of the size of the optimized code, and stack tracing is a small fraction of total gc time. since the compiler enhancements are also modest, we conclude that the approach is practical.
type-based alias analysis. this paper evaluates three alias analyses based on programming language types. the first analysis uses type compatibility to determine aliases. the second extends the first by using additional high-level information such as field names. the third extends the second with a flow-insensitive analysis. although other researchers suggests using types to disambiguate memory references, none evaluates its effectiveness. we perform both static and dynamic evaluations of type-based alias analyses for modula-3, a statically-typed type-safe language. the static analysis reveals that type compatibility alone yields a very imprecise alias analysis, but the other two analyses significantly improve alias precision. we use redundant load elimination (rle) to demonstrate the effectiveness of the three alias algorithms in terms of the opportunities for optimization, the impact on simulated execution times, and to compute an upper bound on what a perfect alias analysis would yield. we show modest dynamic improvements for (rle), and more surprisingly, that on average our alias analysis is within 2.5% of a perfect alias analysis with respect to rle on 8 modula-3 programs. these results illustrate that to explore thoroughly the effectiveness of alias analyses, researchers need static, dynamic, and upper-bound analysis. in addition, we show that for type-safe languages like modula-3 and java, a fast and simple alias analysis may be sufficient for many applications.
automatic inline allocation of objects. object-oriented languages like java and smalltalk provide a uniform object model that simplifies programming by providing a consistent, abstract model of object behavior. but direct implementations introduce overhead, removal of which requires aggressive implementation techniques (e.g. type inference, function specialization); in this paper, we introduce object inlining, an optimization that automatically inline allocates objects within containers (as is done by hand in c++) within a uniform model. we present our technique, which includes novel program analyses that track how inlinable objects are used throughout the program. we evaluated object inlining on several object-oriented benchmarks. it produces performance up to three times as fast as a dynamic model without inlining and roughly equal to that of manually-inlined codes.
an automatic object inlining optimization and its evaluation. automatic object inlining [19, 20] transforms heap data structures by fusing parent and child objects together. it can improve runtime by reducing object allocation and pointer dereference costs. we report continuing work studying object inlining optimizations. in particular, we present a new semantic derivation of the correctness conditions for object inlining, and program analysis which extends our previous work. and we present an object inlining transformation, focusing on a new algorithm which optimizes class field layout to minimize code expansion. finally, we detail a fuller evaluation on eleven programs and libraries (including xpdf, the 25,000 line portable document format (pdf) file browser) that utilizes hardware measures of impact on the memory system. we show that our analysis scales effectively to large programs, finding many inlinable fields (45 in xpdf) at acceptable cost, and we show that, on some programs, it finds nearly all fields for which object inlining is correct, and averages 40% of such fields across our benchmarks. we implement our analyses in an advanced analysis infrastructure, and we show that, compared to traditional 1-cfa, that infrastructure provides better results and lower and more scalable cost. across all programs, analysis identified about 30% of objects as inlinable on average. our transformation increases code size by only 20% while inlining this 30% of fields. inlining these objects eliminated on average 28% of field reads, 58% of object creations, 12% of all loads. further, the optimized programs have significantly improved memory reference behavior, producing 25% fewer l1 data cache misses and 25% fewer read stalls. on average the runtime improved by 14%.
a generational on-the-fly garbage collector for java. an on-the-fly garbage collector does not stop the program threads to perform the collection. instead, the collector executes in a separate thread (or process) in parallel to the program. on-the-fly collectors are useful for multi-threaded applications running on multiprocessor servers, where it is important to fully utilize all processors and provide even response time, especially for systems for which stopping the threads is a costly operation. in this work, we report on the incorporation of generations into an on-the-fly garbage collector. the incorporation is non-trivial since an on-the-fly collector avoids explicit synchronization with the program threads. to the best of our knowledge, such an incorporation has not been tried before. we have implemented the collector for a prototype java virtual machine on aix, and measured its performance on a 4-way multiprocessor. as for other generational collectors, an on-the-fly generational collector has the potential for reducing the overall running time and working set of an application by concentrating collection efforts on the young objects. however, in contrast to other generational collectors, on-the-fly collectors do not move the objects; thus, there is no segregation between the old and the young objects. furthermore, on-the-fly collectors do not stop the threads, so there is no extra benefit for the short pauses obtained by generational collection. nevertheless, comparing our on-the-fly collector with and without generations, it turns out that the generational collector performs better for most applications. the best reduction in overall running time for the benchmarks we measured was 25%. however, there were some benchmarks for which it had no effect and one for which the overall running time increased by 4%.
cssv: towards a realistic tool for statically detecting all buffer overflows in c. erroneous string manipulations are a major source of software defects in c programs yielding vulnerabilities which are exploited by software viruses. we present c string static verifyer (cssv), a tool that statically uncovers all string manipulation errors. being a conservative tool, it reports all such errors at the expense of sometimes generating false alarms. fortunately, only a small number of false alarms are reported, thereby proving that statically reducing software vulnerability is achievable. cssv handles large programs by analyzing each procedure separately. to this end procedure contracts are allowed which are verified by the tool.we implemented a cssv prototype and used it to verify the absence of errors in real code from eads airbus. when applied to another commonly used string intensive application, cssv uncovered real bugs with very few false alarms.
a cost-driven compilation framework for speculative parallelization of sequential programs. the emerging hardware support for thread-level speculation opens new opportunities to parallelize sequential programs beyond the traditional limits. by speculating that many data dependences are unlikely during runtime, consecutive iterations of a sequential loop can be executed speculatively in parallel. runtime parallelism is obtained when the speculation is correct. to take full advantage of this new execution model, a program needs to be programmed or compiled in such a way that it exhibits high degree of speculative thread-level parallelism. we propose a comprehensive cost-driven compilation framework to perform speculative parallelization. based on a misspeculation cost model, the compiler aggressively transforms loops into optimal speculative parallel loops and selects only those loops whose speculative parallel execution is likely to improve program performance. the framework also supports and uses enabling techniques such as loop unrolling, software value prediction and dependence profiling to expose more speculative parallelism. the proposed framework was implemented on the orc compiler. our evaluation showed that the cost-driven speculative parallelization was effective. our compiler was able to generate good speculative parallel loops in ten spec2000int benchmarks, which currently achieve an average 8% speedup. we anticipate an average 15.6% speedup when all enabling techniques are in place.
a practical data flow framework for array reference analysis and its use in optimizations. data flow analysis techniques have traditionally been restricted to the analysis of scalar variables. this retriction, however, imposes a limitation on the kinds of optimizations that can be performed in loops containing array references. we present a data flow framework for array reference analysis that provides the information needed in various optimizations targeted at sequential or fine-grained parallel architectures. the framework extends the traditional scalar framework by incorporating iteration distance values into the analysis to qualify the computed data flow solution during the fixed point iteration. analyses phrased in this framework are capable of discovering recurrent access patterns among array references that evolve during the execution of a loop. applications of our framework are discussed for register allocation, load/store optimizations, and controlled loop unrolling.
module-sensitive program specialisation. we present an approach for specialising large programs, such as programs consisting of several modules, or libraries. this approach is based on the idea of using a compiler generator (cogen) for creating generating extensions. generating extensions are specialisers specialised with respect to some input program. when run on some input data the generating extension produces a specialised version of the input program. here we use the cogen to tailor modules for specialisation. this happens once and for all, independently of all other modules. the resulting module can then be used as a building block for generating extensions for complete programs, in much the same way as the original modules can be put together into complete programs. the result of running the final generating extension is a collection of residual modules, with a module structure derived from the original program.
guardians in a generation-based garbage collector. this paper describes a new language feature that allows dynamically allocated objects to be saved from deallocation by an automatic storage management system so that clean-up or other actions can be performed using the data stored within the objects. the program has full control over the timing of clean-up actions, which eliminates several potential problems and often eliminates the need for critical sections in code that interacts with clean-up actions. our implementation is &ldquo;generation-friendly&rdquo; in the sense that the additional overhead within a generation-based garbage collector is proportional to the work already done there, and the overhead within the mutator is proportional to the number of clean-up actions actually performed.
vliw compilation techniques in a superscalar environment. we describe techniques for converting the intermediate code representation of a given program, as generated by a modern compiler, to another representation which produces the same run-time results, but can run faster on a superscalar machine. the algorithms, based on novel parallelization techniques for very long instruction word (vliw) architectures, find and place together independently executable operations that may be far apart in the original code. i.e., they may be separated by many conditional branches or belong to different iterations of a loop. as a result, the functional units in the superscalar are presented with more work that can proceed in parallel, thus achieving higher performance than the approach of using hardware instruction dispatch techniques alone.while general scheduling techniques improve performance by removing idle pipeline cycles, to further improve performance on a superscalar with only a few functional units requires a reduction in the pathlength. we have designed a set of new algorithms for reducing pathlength and removing stalls due to branches, namely speculative load-store motion out of loops, unspeculation, limited combining, basic block expansion, and prolog tailoring. these algorithms were implemented in a prototype version of the ibm rs/6000 xlc compiler and have shown significant improvement in spec integer benchmarks on the ibm power machines.also, we describe a new technique to obtain profiling information with low overhead, and some applications of profiling directed feedback, including scheduling heuristics, code reordering and branch reversal.
distributed garbage collection. there are two basic approachs to the problem of storage reclamation, process- and processor-based, named for the view point used to recognize when a particular piece of storage can be reclaimed. examples of the processor approach include mark/sweep and copying algorithms and their variants, while reference counting schemes use a process view of the collection. it is argued that the process approach is better suited for distributed computation where links between dynamically allocated objects may cross processor boundaries. in addition, the process approach allows the heap to be more conveniently shared with other processes in those cases when different processes might not have their own virtual address spaces. a new algorithm using the process approach is given. its space requirement per object is better than that for reference counting. in addition, a restricted form of pointer replacement is supported which allows circular structures so constructed to be properly collected.
a reduced multipipeline machine description that preserves scheduling constraints. high performance compilers increasingly rely on accurate modeling of the machine resources to efficiently exploit the instruction level parallelism of an application. in this paper, we propose a reduced machine description that results in faster detection of resource contentions while preserving the scheduling constraints present in the original machine description. the proposed approach reduces a machine description in an automated, error-free, and efficient fashion, moreover, it fully supports schedulers that backtrack and process operations in arbitrary order. reduced descriptions for the dec alpha 21064, mips r3000/r3010, and cydra 5 result in 4 to 7 times faster detection of resource contentions and require 22 to 90% of the memory storage used by the original machine descriptions. precise measurement for the cydra 5 indicates that reducing the machine description results in a 2.9 times faster contention query module.
efficient formulation for optimal modulo schedulers. modulo scheduling algorithms based on optimal solvers have been proposed to investigate and tune the performance of modulo scheduling heuristics. while recent advances have broadened the scope for which the optimal approach is applicable, this approach increasingly suffers from large execution times. in this paper, we propose a more efficient formulation of the modulo scheduling space that significantly decreases the execution time of solvers based on integer linear programs. for example, the total execution time is reduced by a factor of 8.6 when 782 loops from the perfect club, spec, and livermore fortran kernels are scheduled for minimum register requirements using the more efficient formulation instead of the traditional formulation. experimental evidence further indicates that significantly larger loops can be scheduled under realistic machine constraints.
vectorization for simd architectures with alignment constraints. when vectorizing for simd architectures that are commonly employed by today's multimedia extensions, one of the new challenges that arise is the handling of memory alignment. prior research has focused primarily on vectorizing loops where all memory references are properly aligned. an important aspect of this problem, namely, how to vectorize misaligned memory references, still remains unaddressed.this paper presents a compilation scheme that systematically vectorizes loops in the presence of misaligned memory references. the core of our technique is to automatically reorganize data in registers to satisfy the alignment requirement imposed by the hardware. to reduce the data reorganization overhead, we propose several techniques to minimize the number of data reorganization operations generated. during the code generation, our algorithm also exploits temporal reuse when aligning references that access contiguous memory across loop iterations. our code generation scheme guarantees to never load the same data associated with a single static access twice. experimental results indicate near peak speedup factors, e.g., 3.71 for 4 data per vector and 6.06 for 8 data per vector, respectively, for a set of loops where 75% or more of the static memory references are misaligned.
flick: a flexible, optimizing idl compiler. an interface definition language (idl) is a nontraditional language for describing interfaces between software components. idl compilers generate "stubs" that provide separate communicating processes with the abstraction of local object invocation or procedure call. high-quality stub generation is essential for applications to benefit from component-based designs, whether the components reside on a single computer or on multiple networked hosts. typical idl compilers, however, do little code optimization, incorrectly assuming that interprocess communication is always the primary bottleneck. more generally, typical idl compilers are "rigid" and limited to supporting only a single idl, a fixed mapping onto a target language, and a narrow range of data encodings and transport mechanisms.flick, our new idl compiler, is based on the insight that idls are true languages amenable to modern compilation techniques. flick exploits concepts from traditional programming language compilers to bring both flexibility and optimization to the domain of idl compilation. through the use of carefully chosen intermediate representations, flick supports multiple idls, diverse data encodings, multiple transport mechanisms, and applies numerous optimizations to all of the code it generates. our experiments show that flick-generated stubs marshal data between 2 and 17 times faster than stubs produced by traditional idl compilers, and on today's generic operating systems, increase end-to-end throughput by factors between 1.2 and 3.7.
vyrd: verifying concurrent programs by runtime refinement-violation detection. we present a runtime technique for checking that a concurrently-accessed data structure implementation, such as a file system or the storage management module of a database, conforms to an executable specification that contains an atomic method per data structure operation. the specification can be provided separately or a non-concurrent, "atomized" interpretation of the implementation can serve as the specification. the technique consists of two phases. in the first phase, the implementation is instrumented in order to record information into a log during execution. in the second, a separate verification thread uses the logged information to drive an instance of the specification and to check whether the logged execution conforms to it. we paid special attention to the general applicability and scalability of the techniques and to minimizing their concurrency and performance impact. the result is a lightweight verification method that provides a significant improvement over testing for concurrent programs.we formalize conformance to a specification using the notion of refinement: each trace of the implementation must be equivalent to some trace of the specification. among the novel features of our work are two variations on the definition of refinement appropriate for runtime checking: i/o and "view" refinement. these definitions were motivated by our experience with two industrial-scale concurrent data structure implementations: the boxwood project, a b-link tree data structure built on a novel storage infrastructure [10] and the scan file system [9]. i/o and view refinement checking were implemented as a verification tool named vryd (verifying concurrent programs by runtime refinement-violation detection). vyrd was applied to the verification of boxwood, java class libraries, and, previously, to the scan filesystem. it was able to detect previously unnoticed subtle concurrency bugs in boxwood and the scan file system, and the known bugs in the java class libraries and manually constructed examples. experimental results indicate that our techniques have modest computational cost.
context-sensitive interprocedural points-to analysis in the presence of function pointers. this paper reports on the design, implementation, and empirical results of a new method for dealing with the aliasing problem in c. the method is based on approximating the points-to relationships between accessible stack locations, and can be used to generate alias pairs, or used directly for other analyses and transformations. our method provides context-sensitive interprocedural information based on analysis over invocation graphs that capture all calling contexts including recursive and mutually-recursive calling contexts. furthermore, the method allows the smooth integration for handling general function pointers in c. we illustrate the effectiveness of the method with empirical results from an implementation in the mccat optimizing/parallelizing c compiler.
beg - a generator for efficient back ends. this paper describes a system that generates compiler back ends from a strictly declarative specification of the code generation process. the generated back ends use tree pattern matching for code selection. two methods for register allocation supporting a wide range of target architectures are provided. a general bottom-up pattern matching method avoids problems that occurred with previous systems using lr-parsing. the performance of compilers using generated back ends is comparable to very fast production compilers. some figures are given about the results of using the system to generate the back end of a modula-2 compiler.
vcode: a retargetable, extensible, very fast dynamic code generation system. dynamic code generation is the creation of executable code at runtime. such "on-the-fly" code generation is a powerful technique, enabling applications to use runtime information to improve performance by up to an order of magnitude [4, 8,20, 22, 23].unfortunately, previous general-purpose dynamic code generation systems have been either inefficient or non-portable. we present vcode, a retargetable, extensible, very fast dynamic code generation system. an important feature of vcode is that it generates machine code "in-place" without the use of intermediate data structures. eliminating the need to construct and consume an intermediate representation at runtime makes vcode both efficient and extensible. vcode dynamically generates code at an approximate cost of six to ten instructions per generated instruction, making it over an order of magnitude faster than the most efficient general-purpose code generation system in the literature [10].dynamic code generation is relatively well known within the compiler community. however, due in large part to the lack of a publicly available dynamic code generation system, it has remained a curiosity rather than a widely used technique. a practical contribution of this work is the free, unrestricted distribution of the vcode system, which currently runs on the mips, sparc, and alpha architectures.
stack caching for interpreters. an interpreter can spend a significant part of its execution time on accessing arguments of virtual machine instructions. this paper explores two methods to reduce this overhead for virtual stack machines by caching top-of-stack values in (real machine) registers. the dynamic method is based on having, for every possible state of the cache, one specialized version of the whole interpreter; the execution of an instruction usually changes the state of the cache and the next instruction is executed in the version corresponding to the new state. in the static method a state machine that keeps track of the cache state is added to the compiler. common instructions exist in specialized versions for several states, but it is not necessary to have a version of every instruction for every cache state. stack manipulation instructions are optimized away.
fast and flexible instruction selection with on-demand tree-parsing automata. tree parsing as supported by code generator generators like beg, burg, iburg, lburg and ml-burg is a popular instruction selection method. there are two existing approaches for implementing tree parsing: dynamic programming, and tree-parsing automata; each approach has its advantages and disadvantages. we propose a new implementation approach that combines the advantages of both existing approaches: we start out with dynamic programming at compile time, but at every step we generate a state for a tree-parsing automaton, which is used the next time a tree matching the state is found, turning the instruction selector into a fast tree-parsing automaton. we have implemented this approach in the gforth code generator. the implementation required little effort and reduced the startup time of gforth by up to a factor of 2.5.
optimizing indirect branch prediction accuracy in virtual machine interpreters. interpreters designed for efficiency execute a huge number of indirect branches and can spend more than half of the execution time in indirect branch mispredictions. branch target buffers are the best widely available form of indirect branch prediction; however, their prediction accuracy for existing interpreters is only 2%--50%. in this paper we investigate two methods for improving the prediction accuracy of btbs for interpreters: replicating virtual machine (vm) instructions and combining sequences of vm instructions into superinstructions. we investigate static (interpreter build-time) and dynamic (interpreter run-time) variants of these techniques and compare them and several combinations of these techniques. these techniques can eliminate nearly all of the dispatch branch mispredictions, and have other benefits, resulting in speedups by a factor of up to 3.17 over efficient threaded-code interpreters, and speedups by a factor of up to 1.3 over techniques relying on superinstructions alone.
static detection of dynamic memory errors. many important classes of bugs result from invalid assumptions about the results of functions and the values of parameters and global variables. using traditional methods, these bugs cannot be detected efficiently at compile-time, since detailed cross-procedural analyses would be required to determine the relevant assumptions. in this work, we introduce annotations to make certain assumptions explicit at interface points. an efficient static checking tool that exploits these annotations can detect a broad class of errors including misuses of null pointers, uses of dead storage, memory leaks, and dangerous aliasing. this technique has been used successfully to fix memory management problems in a large program.
bytecode compression via profiled grammar rewriting. this paper describes the design and implementation of a method for producing compact, bytecoded instruction sets and interpreters for them. it accepts a grammar for programs written using a simple bytecoded stack-based instruction set, as well as a training set of sample programs. the system transforms the grammar, creating an expanded grammar that represents the same language as the original grammar, but permits a shorter derivation of the sample programs and others like them. a program's derivation under the expanded grammar forms the compressed bytecode representation of the program. the interpreter for this bytecode is automatically generated from the original bytecode interpreter and the expanded grammar. programs expressed using compressed bytecode can be substantially smaller than their original bytecode representation and even their machine code representation. for example, compression cuts the bytecode for lcc from 199kb to 58kb but increases the size of the interpreter by just over 11kb.
adoption and focus: practical linear types for imperative programming. a type system with linearity is useful for checking software protocols andresource management at compile time. linearity provides powerful reasoning about state changes, but at the price of restrictions on aliasing. the hard division between linear and nonlinear types forces the programmer to make a trade-off between checking a protocol on an object and aliasing the object. most onerous is the restriction that any type with a linear component must itself be linear. because of this, checking a protocol on an object imposes aliasing restrictions on any data structure that directly or indirectly points to the object. we propose a new type system that reduces these restrictions with the adoption and focus constructs. adoption safely allows a programmer to alias objects on which she is checking protocols, and focus allows the reverse. a programmer can alias data structures that point to linear objects and use focus for safe access to those objects. we discuss how we implemented these ideas in the vault programming language.
partial online cycle elimination in inclusion constraint graphs. many program analyses are naturally formulated and implemented using inclusion constraints. we present new results on the scalable implementation of such analyses based on two insights: first, that online elimination of cyclic constraints yields orders-of-magnitude improvements in analysis time for large problems; second, that the choice of constraint representation affects the quality and efficiency of online cycle elimination. we present an analytical model that explains our design choices and show that the model's predictions match well with results from a substantial experiment.
scalable context-sensitive flow analysis using instantiation constraints. this paper shows that a type graph (obtained via polymorphic type inference) harbors explicit directional flow paths between functions. these flow paths arise from the instantiations of polymorphic types and correspond to call-return sequences in first-order programs. we show that flow information can be computed efficiently while considering only paths with well matched call-return sequences, even in the higher-order case. furthermore, we present a practical algorithm for inferring type instantiation graphs and provide empirical evidence to the scalability of the presented techniques by applying them in the context of points-to analysis for c programs.
a vhdl compiler based on attribute grammar methodology. this paper presents aspects of a compiler for a new hardware description language (vhdl) written using attribute grammar techniques. vhdl is introduced, along with the new compiler challenges brought by a language that extends an ada subset for the purpose of describing hardware. attribute grammar programming solutions are presented for some of the language challenges. the organization of the compiler and of the target virtual machine represented by the simulation kernel are discussed, and performance and code-size figures are presented. the paper concludes that attribute grammars can be used for large commercial compilers with excellent results in terms of rapid development time and enhanced maintainability, and without paying any substantial penalty in terms of either the complexity of the language that can be handled or the resulting compilation speed.
artemis: practical runtime monitoring of applications for execution anomalies. a number of hardware and software techniques have been proposed to detect dynamic program behaviors that may indicate a bug in a program. because these techniques suffer from high overheads they are useful in finding bugs in programs before they are released, but are significantly less useful in finding bugs in long-running programs on production systems -- the same bugs that are the most difficult to find using traditional techniques. in this paper we propose the artemis1 is the greek goddess of the hunt and wild animals. our framework guides the hunt for wild bugs. compiler-based instrumentation framework that complements many pre-existing runtime monitoring techniques. the artemis framework guides baseline monitoring techniques toward regions of the program where bugs are likely to occur, yielding a low asymptotic monitoring overhead. artemis also facilitates system-load aware runtime monitoring that allows the monitoring coverage to be dynamically scaled up to take advantage of extra cycles when the system load is low, and dynamically scaled down to monitor only the most suspicious regions when the system load is high. our experiments show that artemis' asymptotic overhead can outperform the performance floor overhead of random sampling for many tools, and that artemis can effectively guide a monitoring tool to the buggy regions of a program. our experimental results show that artemis applied to a hardware-based pc-invariance monitoring scheme and a value-based invariance detection and checking scheme significantly improves their runtime monitoring overhead (by up to 4.6 times) with moderate impact on their bug-detecting capabilities.
modular verification of assembly code with stack-based control abstractions. runtime stacks are critical components of any modern software--they are used to implement powerful control structures such as function call/return, stack cutting and unwinding, coroutines, and thread context switch. stack operations, however, are very hard to reason about: there are no known formal specifications for certifying c-style setjmp/longjmp, stack cutting and unwinding, or weak continuations (in c--). in many proof-carrying code (pcc) systems, return code pointers and exception handlers are treated as general first-class functions (as in continuation-passing style) even though both should have more limited scopes.in this paper we show that stack-based control abstractions follow a much simpler pattern than general first-class code pointers. we present a simple but flexible hoare-style framework for modular verification of assembly code with all kinds of stackbased control abstractions, including function call/return, tail call, setjmp/longjmp, weak continuation, stack cutting, stack unwinding, multi-return function call, coroutines, and thread context switch. instead of presenting a specific logic for each control structure, we develop all reasoning systems as instances of a generic framework. this allows program modules and their proofs developed in different pcc systems to be linked together. our system is fully mechanized. we give the complete soundness proof and a full verification of several examples in the coq proof assistant.
simple and effective link-time optimization of modula-3 programs. modula-3 supports development of modular programs by separating an object's interface from its implementation. this separation induces a runtime overhead in the implementation of objects, because it prevents the compiler from having complete information about a program's type hierarchy. this overhead can be reduced at link time, when the entire type hierarchy becomes available. we describe opportunities for link-time optimization of modula-3, present two link-time optimizations that reduce the runtime costs of modula-3's opaque types and methods, and show how link-time optimization could provide c++ which the benefits of opaques types at no additional runtime cost.our optimization techniques are implemented in mld, a retargetable linker for the mips, sparc, and intel 486, mld links a machine-independent intermediate code that is suitable for link-time optimization and code generation. linking intermediate code simplifies implementation of the optimizations and makes it possible to evaluate them on a wide range of architectures. mld's optimizations are effective: they reduce the total number of instructions executed by up to 14% and convert as many as 79% of indirect calls to direct calls.
pads: a domain-specific language for processing ad hoc data. pads is a declarative data description language that allows data analysts to describe both the physical layout of ad hoc data sources and semantic properties of that data. from such descriptions, the pads compiler generates libraries and tools for manipulating the data, including parsing routines, statistical profiling tools, translation programs to produce well-behaved formats such as xml or those required for loading relational databases, and tools for running xqueries over raw pads data sources. the descriptions are concise enough to serve as "living" documentation while flexible enough to describe most of the ascii, binary, and cobol formats that we have seen in practice. the generated parsing library provides for robust, application-specific error handling.
parallelizing complex scans and reductions. we present a method for automatically extracting parallel prefix programs from sequential loops, even in the presence of complicated conditional statements. rather than searching for associative operators in the loop body directly, the method rests on the observation that functional composition itself is associative. accordingly, we model the loop body as a multivalued function of multiple parameters, and look for a closed-form representation of arbitrary compositions of loop body instances. careful analysis of conditionals allows this search to succeed in cases where existing automatic methods fail. the method has been implemented and used to generate code for the iwarp parallel computer.
the design of a class mechanism for moby. typical class-based languages, such as c++ and java, provide complex class mechanisms but only weak module systems. in fact, classes in these languages incorporate many of the features found in richer module mechanisms. in this paper, we describe an alternative approach to designing a language that has both classes and modules. in our design, we rely on a rich ml-style module system to provide features such as visibility control and parameterization, while providing a minimal class mechanism that includes only those features needed to support inheritance. programmers can then use the combination of modules and classes to implement the full range of class-based features and idioms. our approach has the advantage that it provides a full-featured module system (useful in its own right), while keeping the class mechanism quite simple.we have incorporated this design in moby, which is an ml-style language that supports class-based object-oriented programming. in this paper, we describe our design via a series of simple examples, show how various class-based features and idioms are realized in moby, compare our design with others, and sketch its formal semantics.
type-based race detection for java. this paper presents a static race detection analysis for multithreaded java programs. our analysis is based on a formal type system that is capable of capturing many common synchronization patterns. these patterns include classes with internal synchronization, classes thatrequire client-side synchronization, and thread-local classes. experience checking over 40,000 lines of java code with the type system demonstrates that it is an effective approach for eliminating races conditions. on large examples, fewer than 20 additional type annotations per 1000 lines of code were required by the type checker, and we found a number of races in the standard java libraries and other test programs.
componential set-based analysis. set based analysis is a constraint-based whole program analysis that is applicable to functional and object-oriented programming language. unfortunately, the analysis is useless for large programs, since it generates descriptions of data flow relationships that grow quadratically in the size of the program.this paper presents componential set-based analysis, which is faster and handles larger programs without any loss of accuracy over set-based analysis. the design of the analysis exploits a number of theoretical results concerning constraint systems, including a completeness result and a decision algorithm concerning the observable equivalance of constraint systems. experimental results validate the practically of the analysis.
extended static checking for java. software development and maintenance are costly endeavors. the cost can be reduced if more software defects are detected earlier in the development cycle. this paper introduces the extended static checker for java (esc/java), an experimental compile-time program checker that finds common programming errors. the checker is powered by verification-condition generation and automatic theorem-proving techniques. it provides programmers with a simple annotation language with which programmer design decisions can be expressed formally. esc/java examines the annotated software and warns of inconsistencies between the design decisions recorded in the annotations and the actual code, and also warns of potential runtime errors in the code. this paper gives an overview of the checker architecture and annotation language and describes our experience applying the checker to tens of thousands of lines of java programs.
a type and effect system for atomicity. ensuring the correctness of multithreaded programs is difficult, due to the potential for unexpected and nondeterministic interactions between threads. previous work addressed this problem by devising tools for detecting race conditions, a situation where two threads simultaneously access the same data variable, and at least one of the accesses is a write. however, verifying the absence of such simultaneous-access race conditions is neither necessary nor sufficient to ensure the absence of errors due to unexpected thread interactions.we propose that a stronger non-interference property is required, namely atomicity. atomic methods can be assumed to execute serially, without interleaved steps of other threads. thus, atomic methods are amenable to sequential reasoning techniques, which significantly simplifies both formal and informal reasoning about program correctness.this paper presents a type system for specifying and verifying the atomicity of methods in multithreaded java programs. the atomic type system is a synthesis of lipton's theory of reduction and type systems for race detection.we have implemented this atomic type system for java and used it to check a variety of standard java library classes. the type checker uncovered subtle atomicity violations in classes such as <tt>java.lang.string</tt> and <tt>java.lang.string-buffer</tt> that cause crashes under certain thread interleavings.this paper proposes that a stronger non-interference property is required, namely atomicity, and presents a type system for verifying the atomicity of methods in multithreaded java programs. methods in a class can be annotated with the keyword <tt>atomic</tt>. clients of a well-typed class can then assume that each atomic method is executed in one step, thus significantly simplifying both formal and informal reasoning about the client's correctness.
the essence of compiling with continuations. in order to simplify the compilation process, many compilers for higher-order languages use the continuation-passing style (cps) transformation in a first phase to generate an intermediate representation of the source program. the salient aspect of this intermediate form is that all procedures take an argument that represents the rest of the computation (the "continuation"). since the na&iuml;ve cps transformation considerably increases the size of programs, cps compilers perform reductions to produce a more compact intermediate representation. although often implemented as a part of the cps transformation, this step is conceptually a second phase. finally, code generators for typical cps compilers treat continuations specially in order to optimize the interpretation of continuation parameters.a thorough analysis of the abstract machine for cps terms shows that the actions of the code generator invert the na&iuml;ve cps translation step. put differently, the combined effect of the three phases is equivalent to a source-to-source transformation that simulates the compaction phase. thus, fully developed cps compilers do not need to employ the cps transformation but can achieve the same results with a simple source-level transformation.
kill-safe synchronization abstractions. when an individual task can be forcefully terminated at any time, cooperating tasks must communicate carefully. for example, if two tasks share an object, and if one task is terminated while it manipulates the object, the object may remain in an inconsistent or frozen state that incapacitates the other task. to support communication among terminable tasks, language run-time systems (and operating systems) provide kill-safe abstractions for inter-task communication. no kill-safe guarantee is available, however, for abstractions that are implemented outside the run-time system.in this paper, we show how a run-time system can support new kill-safe abstractions without requiring modification to the run-time system, and without requiring the run-time system to trust any new code. our design frees the run-time implementor to provide only a modest set of synchronization primitives in the trusted computing base, while still allowing tasks to communicate using sophisticated abstractions.
units: cool modules for hot languages. a module system ought to enable assembly-line programming using separate compilation and an expressive linking language. separate compilation allows programmers to develop parts of a program independently. a linking language gives programmers precise control over the assembly of parts into a whole. this paper presents models of program units, mzscheme's module language for assembly-line programming. units support separate compilation, independent module reuse, cyclic dependencies, hierarchical structuring, and dynamic linking. the models explain how to integrate units with untyped and typed languages such as scheme and ml.
a theory of type qualifiers. we describe a framework for adding type qualifiers to a language. type qualifiers encode a simple but highly useful form of subtyping. our framework extends standard type rules to model the flow of qualifiers through a program, where each qualifier or set of qualifiers comes with additional rules that capture its semantics. our framework allows types to be polymorphic in the type qualifiers. we present a const-inference system for c as an example application of the framework. we show that for a set of real c programs, many more consts can be used than are actually present in the original code.
flow-sensitive type qualifiers. we present a system for extending standard type systems with flow-sensitive type qualifiers. users annotate their programs with type qualifiers, and inference checks that the annotations are correct. in our system only the type qualifiers are modeled flow-sensitively---the underlying standard types are unchanged, which allows us to obtain an efficient constraint-based inference algorithm that integrates flow-insensitive alias analysis, effect inference, and ideas from linear type systems to support strong updates. we demonstrate the usefulness of flow-sensitive type qualifiers by finding a number of new locking bugs in the linux kernel.
formal loop merging for signal transforms. a critical optimization in the domain of linear signal transforms, such as the discrete fourier transform (dft), is loop merging, which increases data locality and reuse and thus performance. in particular, this includes the conversion of shuffle operations into array reindexings. to date, loop merging is well understood only for the dft, and only for cooley-tukey fft based algorithms, which excludes dft sizes divisible by large primes. in this paper, we present a formal loop merging framework for general signal transforms and its implementation within the spiral code generator. the framework consists of ε-spl, a mathematical language to express loops and index mappings; a rewriting system to merge loops in ε-spl and a compiler that translates ε-spl into code. we apply the framework to dft sizes that cannot be handled using only the cooley-tukey fft and compare our method to fftw 3.0.1 and the vendor library intel mkl 7.2.1. compared to fftw our generated code is a factor of 2--4 faster under equal implementation conditions (same algorithms, same unrolling threshold). for some sizes we show a speed-up of a factor of 9 using bluestein's algorithm. further, we give a detailed comparison against the intel vendor library mkl; our generated code is between 2 times faster and 4.5 times slower.
automatic inference of models for statistical code compression. this paper describes experiments that apply machine learning to compress computer programs, formalizing and automating decisions about instruction encoding that have traditionally been made by humans in a more ad hoc manner. a program accepts a large training set of program material in a conventional compiler intermediate representation (ir) and automatically infers a decision tree that separates ir code into streams that compress much better than the undifferentiated whole. driving a conventional arithmetic compressor with this model yields code 30% smaller than the previous record for ir code compression, and 24% smaller than an ambitious optimizing compiler feeding an ambitious general-purpose data compressor.
finite-static code generation. this paper describes gburg, which generates tiny, fast code generators based on finite-state machine pattern matching. the code generators translate postfix intermediate code into machine instructions in one pass (except, of course, for backpatching addresses). a stack-based virtual machine---known as the lean virtual machine (lvm)---tuned for fast code generation is also described. gburg translates the two-page lvm-to-x86 specification into a code generator that fits entirely in an 8 kb i-cache and that emits x86 code at 3.6 mb/set on a 266-mhz p6. our just-in-time code generator translates and executes small benchmarks at speeds within a factor of two of executables derived from the conventional compile-time code generator on which it is based.
a fast fourier transform compiler. the fftw library for computing the discrete fourier transform (dft) has gained a wide acceptance in both academia and industry, because it provides excellent performance on a variety of machines (even competitive with or faster than equivalent libraries supplied by vendors). in fftw, most of the performance-critical code was generated automatically by a special-purpose compiler, called genfft, that outputs c code. written in objective caml, genfft can produce dft programs for any input length, and it can specialize the dft program for the common case where the input data are real instead of complex. unexpectedly, genfft "discovered" algorithms that were previously unknown, and it was able to reduce the arithmetic complexity of some other existing algorithms. this paper describes the internals of this special-purpose compiler in some detail, and it argues that a specialized compiler is a valuable tool.
the implementation of the cilk-5 multithreaded language. the fifth release of the multithreaded language cilk uses a provably good "work-stealing" scheduling algorithm similar to the first system, but the language has been completely redesigned and the runtime system completely reengineered. the efficiency of the new implementation was aided by a clear strategy that arose from a theoretical analysis of the scheduling algorithm: concentrate on minimizing overheads that contribute to the work, even at the expense of overheads that contribute to the critical path. although it may seem counterintuitive to move overheads onto the critical path, this "work-first" principle has led to a portable cilk-5 implementation in which the typical cost of spawning a parallel thread is only between 2 and 6 times the cost of a c function call on a variety of contemporary machines. many cilk programs run on one processor with virtually no degradation compared to equivalent c programs. this paper describes how the work-first principle was exploited in the design of cilk-5's compiler and its runtime system. in particular, we present cilk-5's novel "two-clone" compilation strategy and its dijkstra-like mutual-exclusion protocol for implementing the ready deque in the work-stealing scheduler.
checking type safety of foreign function calls. foreign function interfaces (ffis) allow components in different languages to communicate directly with each other. while ffis are useful, they often require writing tricky low-level code and include little or no static safety checking, thus providing a rich source of hard-to-find programming errors. in this article, we study the problem of enforcing type safety across the ocaml-to-c ffi and the java native interface (jni). we present o-saffire and j-saffire, a pair of multilingual type inference systems that ensure c code that uses these ffis accesses high-level data safely. our inference systems use representational types to model c's low-level view of ocaml and java values, and singleton types to track integers, strings, memory offsets, and type tags through c. j-saffire, our java system, uses a polymorphic flow-insensitive, unification-based analysis. polymorphism is important because it allows us to precisely model user-defined wrapper functions and the more than 200 jni functions. o-saffire, our ocaml system, uses a monomorphic flow-sensitive analysis because, while polymorphism is much less important for the ocaml ffi flow-sensitivity is critical to track conditional branches, which are used when pattern matching ocaml data in c. o-saffire also tracks garbage collection information to ensure that local c pointers to the ocaml heap are registered properly, which is not necessary for the jni. we have applied o-saffire and j-saffire to a set of benchmarks and found many bugs and questionable coding practices. these results suggest that static checking of ffis can be a valuable tool in writing correct multilingual software.
a timed petri-net model for fine-grain loop scheduling. efficient execution of loops is one of the most important obstacles facing high-performance computer architectures. loop scheduling involves handling a partially ordered set of operations which are to be performed repetitively over a number of iterations.in this paper we study loop scheduling using petri nets, due to their unique power for modeling both partial orders and cycles. the behavior of loops can be modeled by constructing, at compile time, a petri-net behavior graph which exhibits a repetitive firing sequence known as a cyclic frustum. from a cyclic frustum, a time-optimal schedule for the corresponding loop can be derived. a polynomial time bound for such a cyclic frustum to occur has been established. simulation results on a number of livermore loops, both with and without loop-carried dependences, have demonstrated the feasibility of determining the cyclic frustum at compile time.
a sparse algorithm for predicated global value numbering. this paper presents a new algorithm for performing global value numbering on a routine in static single assignment form. our algorithm has all the strengths of the most powerful existing practical methods of global value numbering; it unifies optimistic value numbering with constant folding, algebraic simplification and unreachable code elimination. it goes beyond existing methods by unifying optimistic value numbering with further analyses: it canonicalizes the structure of expressions in order to expose more congruences by performing global reassociation, it exploits the congruences induced by the predicates of conditional jumps (predicate inference and value inference), and it associates the arguments of acyclic &oslash; functions with the predicates controlling their arrival (&oslash; predication), thus enabling congruence finding on conditional control structures. finally, it implements an efficient sparse formulation and offers a range of tradeoffs between compilation time and optimization strength. we describe an implementation of the algorithm and present measurements of its strength and efficiency collected when optimizing the spec cint2000 c benchmarks.
language support for regions. region-based memory management systems structure memory by grouping objects in regions under program control. memory is reclaimed by deleting regions, freeing all objects stored therein. our compiler for c with regions, rc, prevents unsafe region deletions by keeping a count of references to each region. using type annotations that make the structure of a program's regions more explicit, we reduce the overhead of reference counting from a maximum of 27% to a maximum of 11% on a suite of realistic benchmarks. we generalise these annotations in a region type system whose main novelty is the use of existentially quantified abstract regions to represent pointers to objects whose region is partially or totally unknown. a distribution of rc is available at http://www.cs.berkeley.edu/~dgay/rc.tar.gz.
memory management with explicit regions. much research has been devoted to studies of and algorithms for memory management based on garbage collection or explicit allocation and deallocation. an alternative approach, region-based memory management, has been known for decades, but has not been well-studied. in a region-based system each allocation specifies a region, and memory is reclaimed by destroying a region, freeing all the storage allocated therein. we show that on a suite of allocation-intensive c programs, regions are competitive with malloc/free and sometimes substantially faster. we also show that regions support safe memory management with low overhead. experience with our benchmarks suggests that modifying many existing programs to use regions is not difficult.
the nesc language: a holistic approach to networked embedded systems. we present nesc, a programming language for networked embedded systems that represent a new design space for application developers. an example of a networked embedded system is a sensor network, which consists of (potentially) thousands of tiny, low-power "motes," each of which execute concurrent, reactive programs that must operate with severe memory and power constraints.nesc's contribution is to support the special needs of this domain by exposing a programming model that incorporates event-driven execution, a flexible concurrency model, and component-oriented application design. restrictions on the programming model allow the nesc compiler to perform whole-program analyses, including data-race detection (which improves reliability) and aggressive function inlining (which reduces resource consumption).nesc has been used to implement tinyos, a small operating system for sensor networks, as well as several significant sensor applications. nesc and tinyos have been adopted by a large number of sensor network research groups, and our experience and evaluation of the language shows that it is effective at supporting the complex, concurrent programming style demanded by this new class of deeply networked systems.
parallelism, persistence and meta-cleanliness in the symmetric lisp interpreter. symmetric lisp is a programming language designed around first-class environments, where an environment is a dictionary that associates names with definitions or values. in this paper we describe the logical structure of the symmetric lisp interpreter. in other interpreted languages, the interpreter is a virtual machine that evaluates user input on the basis of its own internal state. the symmetric lisp interpreter, on the other hand, is a simple finite-state machine with no internal state. its role is to attach user input to whatever environment the user has specified; such environments are transparent objects created by, maintained by and fully accessible to the user. the interpreter's semantics are secondary to the semantics of environments in symmetric lisp: it is the environment-object to which an expression is attached, not the interpreter, that controls the evaluation of expressions.this arrangement has several consequences. because environments in symmetric lisp are governed by a parallel evaluation rule, the symmetric lisp interpreter is a parallel interpreter. a symmetric lisp environment evaluates to another environment; a session with the interpreter therefore yields a well-defined environment object as its result. users are free to write routines that manage these interpreter-created objects - routines that list the elements of a namespace, coalesce environments, maintain multiple name definitions and so on precisely because environment objects may be freely inspected and manipulated. because a named environment may contain other named environments as elements, interpreter-created objects may be regarded as hierarchical file systems. because of the parallel evaluation semantics of environments, the interpreter is well-suited as an interface to a concurrent, language-based computer system that uses symmetric lisp as its base language. we argue that - in short - a basic semantic simplification in symmetric lisp promises a correspondingly basic increase in power at the user-interpreter interface.
taming the ixp network processor. we compile nova, a new language designed for writing network processing applications, using a back end based on integer-linear programming (ilp) for register allocation, optimal bank assignment, and spills. the compiler's optimizer employs cps as its intermediate representation; some of the invariants that this ir guarantees are essential for the formulation of a practical ilp model.appel and george used a similar ilp-based technique for the ia32 to decide which variables reside in registers but deferred the actual assignment of colors to a later phase. we demonstrate how to carry over their idea to an architecture with many more banks, register aggregates, variables with multiple simultaneous register assignments, and, very importantly, one where bank- and register-assignment cannot be done in isolation from each other. our approach performs well in practise---without causing an explosion in size or solve time of the generated integer linear programs.
field analysis: getting useful and low-cost interprocedural information. we present a new limited form of interprocedural analysis called field analysis that can be used by a compiler to reduce the costs of modern language features such as object-oriented programming, automatic memory management, and run-time checks required for type safety. unlike many previous interprocedural analyses, our analysis is cheap, and does not require access to the entire program. field analysis exploits the declared access restrictions placed on fields in a modular language (e.g. field access modifiers in java) in order to determine useful properties of fields of an object. we describe our implementation of field analysis in the swift optimizing compiler for java, as well a set of optimizations that exploit the results of field analysis. these optimizations include removal of run-time tests, compile-time resolution of method calls, object inlining, removal of unnecessary synchronization, and stack allocation. our results demonstrate that field analysis is efficient and effective. speedups average 7% on a wide range of applications, with some times reduced by up to 27%. compile time overhead of field analysis is about 10%.
on the importance of points-to analysis and other memory disambiguation methods for c programs. in this paper, we evaluate the benefits achievable from pointer analysis and other memory disambiguation techniques for c/c++ programs, using the framework of the production compiler for the intel&reg; itanium&trade; processor. most of the prior work on memory disambiguation has primarily focused on pointer analysis, and either presents only static estimates of the accuracy of the analysis (such as average points-to set size), or provides performance data in the context of certain individual optimizations. in contrast, our study is based on a complete memory disambiguation framework that uses a whole set of techniques including pointer analysis. further, it presents how various compiler analyses and optimizations interact with the memory disambiguator, evaluates how much they benefit from disambiguation, and measures the eventual impact on the performance of the program. the paper also analyzes the types of disambiguation queries that are typically received by the disambiguator, which disambiguation techniques prove most effective in resolving them, and what type of queries prove difficult to be resolved. the study is based on empirical data collected for the spec cint2000 c/c++ programs, running on the itanium processor.
dart: directed automated random testing. we present a new tool, named dart, for automatically testing software that combines three main techniques: (1) automated extraction of the interface of a program with its external environment using static source-code parsing; (2) automatic generation of a test driver for this interface that performs random testing to simulate the most general environment the program can operate in; and (3) dynamic analysis of how the program behaves under random testing and automatic generation of new test inputs to direct systematically the execution along alternative program paths. together, these three techniques constitute directed automated random testing, or dart for short. the main strength of dart is thus that testing can be performed completely automatically on any program that compiles -- there is no need to write any test driver or harness code. during testing, dart detects standard errors such as program crashes, assertion violations, and non-termination. preliminary experiments to unit test several examples of c programs are very encouraging.
generational reference counting: a reduced-communication distributed storage reclamation scheme. this paper describes generational reference counting, a new distributed storage reclamation scheme for loosely-coupled multiprocessors. it has a significantly lower communication overhead than distributed versions of conventional reference counting. although generational reference counting has greater computational and space requirements than ordinary reference counting, it may provide a significant saving in overall execution time on machines in which message passing is expensive. the communication overhead for generational reference counting is one message for each copy of an interprocessor reference (pointer). unlike conventional reference counting, when a reference to an object is copied no message is sent to the processor on which the object lies. a message is sent only when a reference is discarded. unfortunately, generational reference counting shares conventional reference counting's inability to reclaim cyclical structures. in this paper, we present the generational reference counting algorithm, prove it correct, and discuss some refinements that make it more efficient. we also compare it with weighted reference counting, another distributed reference counting scheme described in the literature.
interprocedural dataflow analysis in an executable optimizer. interprocedural dataflow information enables link-time and post-link-time optimizers to perform analyses and code transformations that are not possible in a traditional compiler. this paper describes the interprocedural dataflow analysis techniques used by spike, a post-linktime optimizer for alpha/nt executables. spike uses dataflow analysis to summarize the register definitions, uses, and kills that occur external to each routine, allowing spike to perform a variety of optimizations that require interprocedural dataflow information. because spike is designed to optimize large pc applications, the time required to perform interprocedural dataflow analysis could potentially be unacceptably long, limiting spike's effectiveness and applicability. to decrease dataflow analysis time, spike uses a compact representation of a program's intraprocedural and interprocedural control flow that efficiently summarizes the register definitions and uses that occur in the program. experimental results are presented for the spec95 integer benchmarks and eight large pc applications. the results show that the compact representation allows spike to compute interprocedural dataflow information in less than 2 seconds for each of the spec95 integer benchmarks. even for the largest pc application containing over 1.7 million instructions in 340 thousand basic blocks, interprocedural dataflow analysis requires just 12 seconds.
orchestrating interactions among parallel computations. many parallel programs contain multiple sub-computations, each with distinct communication and load balancing requirements. the traditional approach to compiling such programs is to impose a processor synchronization barrier between sub-computations, optimizing each as a separate entity. this paper develops a methodology for managing the interactions among sub-computations, avoiding strict synchronization where concurrent or pipelined relationships are possible. our approach to compiling parallel programs has two components: symbolic data access analysis and adaptive runtime support. we summarize the data access behavior of sub-computations (such as loop nests) and split them to expose concurrency and pipelining opportunities. the split transformation has been incorporated into an extended fortran compiler, which outputs a fortran 77 program augmented with calls to library routines written in c and a coarse-grained dataflow graph summarizing the exposed parallelism. the compiler encodes symbolic information, including loop bounds and communication requirements, for an adaptive runtime system, which uses runtime information to improve the scheduling efficiency of irregular sub-computations. the runtime system incorporates algorithms that allocate processing resources to concurrently executing sub-computations and choose communication granularity. we have demonstrated that these dynamic techniques substantially improve performance on a range of production applications including climate modeling and x-ray tomography, expecially when large numbers of processors are available.
division by invariant integers using multiplication. integer division remains expensive on today's processors as the cost of integer multiplication declines. we present code sequences for division by arbitrary nonzero integer constants and run-time invariants using integer multiplication. the algorithms assume a two's complement architecture. most also require that the upper half of an integer product be quickly accessible. we treat unsigned division, signed division where the quotient rounds towards zero, signed division where the quotient rounds towards -&infin;, and division where the result is known a priori to be exact. we give some implementation results using the c compiler gcc.
an evaluation of staged run-time optimizations in dyc. previous selective dynamic compilation systems have demonstrated that dynamic compilation can achieve performance improvements at low cost on small kernels, but they have had difficulty scaling to larger programs. to overcome this limitation, we developed dyc, a selective dynamic compilation system that includes more sophisticated and flexible analyses and transformations. dyc is able to achieve good performance improvements on programs that are much larger and more complex than the kernels. we analyze the individual optimizations of dyc and assess their impact on performance collectively and individually.
better extensibility through modular syntax. we explore how to make the benefits of modularity available for syntactic specifications and present rats!, a parser generator for java that supports easily extensible syntax. our parser generator builds on recent research on parsing expression grammars (pegs), which, by being closed under composition, prioritizing choices, supporting unlimited lookahead, and integrating lexing and parsing, offer an attractive alternative to context-free grammars. pegs are implemented by so-called packrat parsers, which are recursive descent parsers that memoize all intermediate results (hence their name). memoization ensures linear-time performance in the presence of unlimited lookahead, but also results in an essentially lazy, functional parsing technique. in this paper, we explore how to leverage pegs and packrat parsers as the foundation for extensible syntax. in particular, we show how make packrat parsing more widely applicable by implementing this lazy, functional technique in a strict, imperative language, while also generating better performing parsers through aggressive optimizations. next, we develop a module system for organizing, modifying, and composing large-scale syntactic specifications. finally, we describe a new technique for managing (global) parsing state in functional parsers. our experimental evaluation demonstrates that the resulting parser generator succeeds at providing extensible syntax. in particular, rats! enables other grammar writers to realize real-world language extensions in little time and code, and it generates parsers that consistently out-perform parsers created by two glr parser generators.
parallel compilation for a parallel machine. an application for a parallel computer with multiple, independent processors often includes different programs (functions) for the individual processors; compilation of such functions can proceed independently. we implemented a compiler that exploits this parallelism by partitioning the input program for parallel translation. the host system for the parallel compiler is an ethernet-based network of workstations, and different functions of the application program are compiled in parallel on different workstations. for typical programs in our environment, we observe a speedup ranging from 3 to 6 using not more than 9 processors. the paper includes detailed measurements for this parallel compiler; we report the system overhead, implementation overhead, as well as the speedup obtained when compared with sequential compilation.
region-based memory management in cyclone. cyclone is a type-safe programming language derived from c. the primary design goal of cyclone is to let programmers control data representation and memory management without sacrificing type-safety. in this paper, we focus on the region-based memory management of cyclone and its static typing discipline. the design incorporates several advancements, including support for region subtyping and a coherent integration with stack allocation and a garbage collector. to support separate compilation, cyclone requires programmers to write some explicit region annotations, but a combination of default annotations, local type inference, and a novel treatment of region effects reduces this burden. as a result, we integrate c idioms in a region-based framework. in our experience, porting legacy c to cyclone has required altering about 8% of the code; of the changes, only 6% (of the 8%) were region annotations.
interprocedural constant propagation: a study of jump function implementations. an implementation of interprocedural constant propagation must model the transmission of values through each procedure. in the framework proposed by callahan, cooper, kennedy, and torczon in 1986, this intraprocedural propagation is modeled with a jump function. while callahan et al. propose several kinds of jump functions, they give no data to help choose between them. this paper reports on a comparative study of jump function implementations. it shows that different jump functions produce different numbers of useful constants; it suggests a particular function, called the pass-through parameter jump function, as the most cost-effective in practice.
improving the cache locality of memory allocation. the allocation and disposal of memory is a ubiquitous operation in most programs. rarely do programmers concern themselves with details of memory allocators; most assume that memory allocators provided by the system perform well. this paper presents a performance evaluation of the reference locality of dynamic storage allocation algorithms based on trace-driven simualtion of five large allocation-intensive c programs. in this paper, we show how the design of a memory allocator can significantly affect the reference locality for various applications. our measurements show that poor locality in sequential-fit allocation algorithms reduces program performance, both by increasing paging and cache miss rates. while increased paging can be debilitating on any architecture, cache misses rates are also important for modern computer architectures. we show that algorithms attempting to be space-efficient by coalescing adjacent free objects show poor reference locality, possibly negating the benefits of space efficiency. at the other extreme, algorithms can expend considerable effort to increase reference locality yet gain little in total execution performance. our measurements suggest an allocator design that is both very fast and has good locality of reference.
combining abstract interpreters. we present a methodology for automatically combining abstract interpreters over given lattices to construct an abstract interpreter for the combination of those lattices. this lends modularity to the process of design and implementation of abstract interpreters.we define the notion of logical product of lattices. this kind of combination is more precise than the reduced product combination. we give algorithms to obtain the join operator and the existential quantification operator for the combined lattice from the corresponding operators of the individual lattices. we also give a bound on the number of steps required to reach a fixed point across loops during analysis over the combined lattice in terms of the corresponding bounds for the individual lattices. we prove that our combination methodology yields the most precise abstract interpretation operators over the logical product of lattices when the individual lattices are over theories that are convex, stably infinite, and disjoint.we also present an interesting application of logical product wherein some lattices can be reduced to combination of other (unrelated) lattices with known abstract interpreters.
a fresh look at optimizing array bound checking. this paper describes techniques for optimizing range checks performed to detect array bound violations. in addition to the elimination of range checks, the optimizations discussed in this paper also reduce the overhead due to range checks that cannot be eliminated by compile-time analysis. the optimizations reduce the program execution time and the object code size through elimination of redundant checks, propagation of checks out of loops, and combination of multiple checks into a single check. a minimal control flow graph (mcfg) is constructed using which the minimal amount of data flow information required for range check optimizations is computed. the range check optimizations are performed using the mcfg rather the cfg for the entire program. this allows the global range check optimizations to be performed efficiently since the mcfg is significantly smaller than the cfg. any array bound violation that is detected by a program with all range checks included, will also be detected by the program after range check optimization and vice versa. even though the above optimizations may appear to be similar to traditional code optimizations, similar reduction in the number of range checks executed can not be achieved by a traditional code optimizer. experimental results indicate that the number of range checks performed in executing a program is greatly reduced using the above techniques.
register allocation via clique separators. although graph coloring is widely recognized as an effective technique for global register allocation, the overhead can be quite high, not only in execution time but also in memory, as the size of the interference graph needed in coloring can become quite large. in this paper, we present an algorithm based upon a result by r. tarjan regarding the colorability of graphs which are decomposable using clique separators, that improves on the overhead of coloring. the algorithm first partitions program code into code segments using the notion of clique separators. the interference graphs for the code partitions are next constructed one at a time and colored independently. the colorings for the partitions are combined to obtain a register allocation for the program code. the technique presented is both efficient in space and time because the graph for only a single code segment needs to be constructed and colored at any given point in time. the partitioning of a graph using clique separators increases the likelihood of obtaining a coloring without spilling and hence an efficient allocation of registers for the program. for straight line code an optimal allocation for the entire program code can be obtained from optimal allocations for individual code segments. in the presence of branches, optimal allocation along one execution path and a near optimal allocation along alternative paths can be potentially obtained. since the algorithm is highly efficient, it eliminates the need for a local register allocation phase.
free-me: a static analysis for automatic individual object reclamation. garbage collection has proven benefits, including fewer memory related errors and reduced programmer effort. garbage collection, however, trades space for time. it reclaims memory only when it is invoked: invoking it more frequently reclaims memory quickly, but incurs a significant cost; invoking it less frequently fills memory with dead objects. in contrast, explicit memory management provides prompt low cost reclamation, but at the expense of programmer effort.this work comes closer to the best of both worlds by adding novel compiler and runtime support for compiler inserted frees to a garbage-collected system. the compiler's free-me analysis identifies when objects become unreachable and inserts calls to free. it combines a lightweight pointer analysis with liveness information that detects when short-lived objects die. our approach differs from stack and region allocation in two crucial ways. first, it frees objects incrementally exactly when they become unreachable, instead of based on program scope. second, our system does not require allocation-site lifetime homogeneity, and thus frees objects on some paths and not on others. it also handles common patterns: it can free objects in loops and objects created by factory methods.we evaluate free() variations for free-list and bump-pointer allocators. explicit freeing improves performance by promptly reclaiming objects and reducing collection load. compared to marksweep alone, free-me cuts total time by 22% on average, collector time by 50% to 70%, and allows programs to run in 17% less memory. this combination retains the software engineering benefits of garbage collection while increasing space efficiency and improving performance, and thus is especially appealing for real-time and space constrained systems.
a system and language for building system-specific, static analyses. this paper presents a novel approach to bug-finding analysis and an implementation of that approach. our goal is to find as many serious bugs as possible. to do so, we designed a flexible, easy-to-use extension language for specifying analyses and an efficent algorithm for executing these extensions. the language, metal, allows the users of our system to specify a broad class of analyses in terms that resemble the intuitive description of the rules that they check. the system, xgcc, executes these analyses efficiently using a context-sensitive, interprocedural analysis. our prior work has shown that the approach described in this paper is effective: it has successfully found thousands of bugs in real systems code. this paper describes the underlying system used to achieve these results. we believe that our system is an effective framework for deploying new bug-finding analyses quickly and easily.
combining events and threads for scalable network services implementation and evaluation of monadic, application-level concurrency primitives. this paper proposes to combine two seemingly opposed programming models for building massively concurrent network services: the event-driven model and the multithreaded model. the result is a hybrid design that offers the best of both worlds--the ease of use and expressiveness of threads and the flexibility and performance of events. this paper shows how the hybrid model can be implemented entirely at the application level using concurrency monads in haskell, which provides type-safe abstractions for both events and threads. this approach simplifies the development of massively concurrent software in a way that scales to real-world network services. the haskell implementation supports exceptions, symmetrical multiprocessing, software transactional memory, asynchronous i/o mechanisms and application-level network protocol stacks. experimental results demonstrate that this monad-based approach has good performance: the threads are extremely lightweight (scaling to ten million threads), and the i/o performance compares favorably to that of linux nptl. tens of thousands of simultaneous, mostly-idle client connections. such massively-concurrent programs are difficult to implement, especially when other requirements, such as high performance and strong security, must also be met.
combining region inference and garbage collection. this paper describes a memory discipline that combines region-based memory management and copying garbage collection by extending cheney's copying garbage collection algorithm to work with regions. the paper presents empirical evidence that region inference very significantly reduces the number of garbage collections; and evidence that the fastest execution is obtained by using regions alone, without garbage collection. the memory discipline is implemented for standard ml in the ml kit compiler and measurements show that for a variety of benchmark programs, code generated by the compiler is as efficient, both with respect to execution time and memory usage, as programs compiled with standard ml of new jersey, another state-of-the-art standard ml compiler.
dynamic variables. most programming languages use static scope rules for associating uses of identifiers with their declarations. static scope helps catch errors at compile time, and it can be implemented efficiently. some popular languages&mdash;perl, tel, tex, and postscript&mdash;offer dynamic scope, because dynamic scope works well for variables that &ldquo;customize&rdquo; the execution environment, for example. programmers must simulate dynamic scope to implement this kind of usage in statically scoped languages. this paper describes the design and implementation of imperative language constructs for introducing and referencing dynamically scoped variables&mdash;dynamic variables for short. the design is a minimalist one, because dynamic variables are best used sparingly, much like exceptions. the facility does, however, cater to the typical uses for dynamic scope, and it provides a cleaner mechanism for so-called thread-local variables. a particularly simple implementation suffices for languages without exception handling. for languages with exception handling, a more efficient implementation builds on existing compiler infrastructure. exception handling can be viewed as a control construct with dynamic scope. likewise, dynamic variables are a data construct with dynamic scope.
relaxing simd control flow constraints using loop transformations. many loop nests in scientific codes contain a parallelizable outer loop but have an inner loop for which the number of iterations varies between different iterations of the outer loop. when running this kind of loop nest on a simd machine, the simd-inherent restriction to single program counter common to all processors will cause a performance degradation relative to comparable mimd implementations. this problem is not due to limited parallelism or bad load balance, it is merely a problem of control flow. this paper presents a loop transformation, which we call loop flattening, that overcomes this limitation by letting each processor advance to the next loop iteration containing useful computation, if there is such an iteration for the given processor. we study a concrete example derived from a molecular dynamics code and compare performance results for flattened and unflattened versions of this kernel on two simd machines, the cm-2 and the decmpp 12000. we then evaluate loop flattening from the compiler's perspective in terms of applicability, cost, profitability, and safety. we conclude with arguing that loop flattening, whether performed by the programmer or by the compiler, introduces negligible overhead and can significantly improve the performance of scientific codes for solving irregular problems.
optimizing memory transactions. atomic blocks allow programmers to delimit sections of code as 'atomic', leaving the language's implementation to enforce atomicity. existing work has shown how to implement atomic blocks over word-based transactional memory that provides scalable multi-processor performance without requiring changes to the basic structure of objects in the heap. however, these implementations perform poorly because they interpose on all accesses to shared memory in the atomic block, redirecting updates to a thread-private log which must be searched by reads in the block and later reconciled with the heap when leaving the block.this paper takes a four-pronged approach to improving performance: (1) we introduce a new 'direct access' implementation that avoids searching thread-private logs, (2) we develop compiler optimizations to reduce the amount of logging (e.g. when a thread accesses the same data repeatedly in an atomic block), (3) we use runtime filtering to detect duplicate log entries that are missed statically, and (4) we present a series of gc-time techniques to compact the logs generated by long-running atomic blocks.our implementation supports short-running scalable concurrent benchmarks with less than 50\% overhead over a non-thread-safe baseline. we support long atomic blocks containing millions of shared memory accesses with a 2.5-4.5x slowdown.
efficient procedure mapping using cache line coloring. as the gap between memory and processor performance continues to widen, it becomes increasingly important to exploit cache memory eflectively. both hardware and aoftware approaches can be explored to optimize cache performance. hardware designers focus on cache organization issues, including replacement policy, associativity, line size and the resulting cache access time. software writers use various optimization techniques, including software prefetching, data scheduling and code reordering. our focus is on improving memory usage through code reordering compiler techniques.in this paper we present a link-time procedure mapping algorithm which can significantly improve the eflectiveness of the instruction cache. our algorithm produces an improved program layout by performing a color mapping of procedures to cache lines, taking into consideration the procedure size, cache size, cache line size, and call graph. we use cache line coloring to guide the procedure mapping, indicating which cache lines to avoid when placing a procedure in the program layout. our algorithm reduces on average the instruction cache miss rate by 40% over the original mapping and by 17% over the mapping algorithm of pettis and hansen [12].
using static single assignment form to improve flow-insensitive pointer analysis. a pointer-analysis algorithm can be either flow-sensitive or flow-insensitive. while flow-sensitive analysis usually provides more precise information, it is also usually considerably more costly in terms of time and space. the main contribution of this paper is the presentation of another option in the form of an algorithm that can be 'tuned' to provide a range of results that fall between the results of flow-insensitive and flow-sensitive analysis. the algorithm combines a flow-insensitive pointer analysis with static single assignment (ssa) form and uses an iterative process to obtain progressively better results.
incremental generation of parsers. an lr-based parser generator for arbitrary context-free grammars that generates parsers by need and handles modifications to its input grammar by updating the parser it has generated so far is described. the need for these techniques is discussed in the context of interactive language definition environments. all required algorithms are presented. measurements are given comparing their performance with that of conventional techniques.
a practical flow-sensitive and context-sensitive c and c++ memory leak detector. this paper presents a static analysis tool that can automatically find memory leaks and deletions of dangling pointers in large c and c++ applications.we have developed a type system to formalize a practical ownership model of memory management. in this model, every object is pointed to by one and only one owning pointer, which holds the exclusive right and obligation to either delete the object or to transfer the right to another owning pointer. in addition, a pointer-typed class member field is required to either always or never own its pointee at public method boundaries. programs satisfying this model do not leak memory or delete the same object more than once.we have also developed a flow-sensitive and context-sensitive algorithm to automatically infer the likely ownership interfaces of methods in a program. it identifies statements inconsistent with the model as sources of potential leaks or double deletes. the algorithm is sound with respect to a large subset of the c and c++ language in that it will report all possible errors. it is also practical and useful as it identifies those warnings likely to correspond to errors and helps the user understand the reported errors by showing them the assumed method interfaces.our techniques are validated with an implementation of a tool we call clouseau. we applied clouseau to a suite of applications: two web servers, a chat client, secure shell tools, executable object manipulation tools, and a compiler. the tool found a total of 134 serious memory errors in these applications. the tool analyzes over 50k lines of c++ code in about 9 minutes on a 2 ghz pentium 4 machine and over 70k lines of c code in just over a minute.
linear-time subtransitive control flow analysis. we present a linear-time algorithm for bounded-type programs that builds a directed graph whose transitive closure gives exactly the results of the standard (cubic-time) control-flow analysis (cfa) algorithm. our algorithm can be used to list all functions calls from all call sites in (optimal) quadratic time. more importantly, it can be used to give linear-time algorithms for cfa-consuming applications such as:&bull; effects analysis: find the side-effecting expressions in a program.&bull; k-limited cfa: for each call-site, list the functions if there are only a few of them (&le; k) and otherwise output "many".&bull; called-once analysis: identify all functions called from only one call-site.
demand-driven pointer analysis. known algorithms for pointer analysis are &ldquo;global&rdquo; in the sense that they perform an exhaustive analysis of a program or program component. in this paper we introduce a demand-driven approach for pointer analysis. specifically, we describe a demand-driven flow-insensitive, subset-based, con text-insensitive points-to analysis. given a list of pointer variables (a query), our analysis performs just enough computation to determine the points-to sets for these query variables. using deductive reachability formulations of both the exhaustive and the demand-driven analyses, we prove that our algorithm is correct. we also show that our analysis is optimal in the sense that it does not do more work than necessary. we illustrate the feasibility and efficiency of our analysis with an implementation of demand-driven points-to analysis for computing the call-graphs of c programs with function pointers. the performance of our system varies substantially across benchmarks - the main factor is how much of the points-to graph must be computed to determine the call-graph. for some benchmarks, only a small part of the points-to graph is needed (e.g pouray emacs and gcc), and here we see more than a 10x speedup. for other benchmarks (e.g. burlap and gimp), we need to compute most (> 95%) of the points-to graph, and here the demand-driven algorithm is considerably slower, because using the demand-driven algorithm is a slow method of computing the full points-to graph.
ultra-fast aliasing analysis using cla: a million lines of c code in a second. we describe the design and implementation of a system for very fast points-to analysis. on code bases of about million lines of unpreprocessed c code, our system performs field-based andersen-style points-to analysis in less than a second and uses less than 10mb of memory. our two main contributions are a database-centric analysis architecture called compile-link-analyze (cla), and a new algorithm for implementing dynamic transitive closure. our points-to analysis system is built into a forward data-dependence analysis tool that is deployed within lucent to help with consistent type modifications to large legacy c code bases.
the university of washington illustrating compiler. the university of washington illustrating compiler (uwpi) automatically illustrates the data structures used in simple programs written in a subset of pascal2. a uwpi user submits a program to uwpi, and can then watch a graphical display show time varying illustrations of the data structures and program source code. uwpi uses the information latent in the program to determine how to illustrate the program. uwpi infers the abstract data types directly from the declarations and operations used in the source program, and then lays out the illustration in a natural way by instantiating well-known layouts for the abstracts types. uwpi solves program illustration using compile-time pattern matching and type inferencing to link anticipated execution events to display events, rather than relying on user assistance or specialized programming techniques. uwpi has been used to automatically illustrate didactic sorting and searching examples, and can be used to help teach basic data structures, or to help when debugging programs.
type analysis of prolog using type graphs. type analysis of prolog is of primary importance for high-performance compilers, since type information may lead to better indexing and to sophisticated specializations of unification and built-in predicates to name a few. however, these optimizations often require a sophisticated type inference system capable of inferring disjunctive and recursive types and hence expensive in computation time. the purpose of this paper is to describe a type analysis system for prolog based on abstract interpretation and type graphs (i.e. disjunctive rational trees) with this functionality. the system (about 15,000 lines of c) consists of the combination of a generic fixpoint algorithm, a generic pattern domain, and a type graph domain. the main contribution of the paper is to show that this approach can be engineered to be practical for medium-sized programs without sacrificing accuracy. the main technical contributions to achieve this result are (1) a novel widening operator for type graphs which appears to be accurate and effective in keeping the sizes of the graphs, and hence the computation time, reasonably small; (2) the use of the generic pattern domain to obtain a compact representation of equality constraints between subterms and to factor out sure structural information.
race checking by context inference. software model checking has been successful for sequential programs, where predicate abstraction offers suitable models, and counterexample-guided abstraction refinement permits the automatic inference of models. when checking concurrent programs, we need to abstract threads as well as the contexts in which they execute. stateless context models, such as predicates on global variables, prove insufficient for showing the absence of race conditions in many examples. we therefore use richer context models, which combine (1) predicates for abstracting data state, (2) control flow quotients for abstracting control state, and (3) counters for abstracting an unbounded number of threads. we infer suitable context models automatically by a combination of counterexample-guided abstraction refinement, bisimulation minimization, circular assume-guarantee reasoning, and parametric reasoning about an unbounded number of threads. this algorithm, called circ, has been implemented in blast and succeeds in checking many examples of nesc code for data races. in particular, blast proves the absence of races in several cases where previous race checkers give false positives.
the embedded machine: predictable, portable real-time code. the embedded machine is a virtual machine that mediates in real time the interaction between software processes and physical processes. it separates the compilation of embedded programs into two phases. the first phase, the platform-independent compiler phase, generates e code (code executed by the embedded machine), which supervises the timing, not the scheduling of, application tasks relative to external events such as clock ticks and sensor interrupts. e code is portable and, given an input behavior, exhibits predictable (i.e., deterministic) timing and output behavior. the second phase, the platform-dependent compiler phase, checks the time safety of the e code, that is, whether platform performance (determined by the hardware) and platform utilization (determined by the scheduler of the operating system) enable its timely execution. we have used the embedded machine to compile and execute high-performance control applications written in giotto, such as the flight control system of an autonomous model helicopter.
the transactional manifesto: software engineering and non-blocking synchronization. computer architecture is about to undergo, if not another revolution, then a vigorous shaking-up. the major chip manufacturers have, for the time being, simply given up trying to make processors run faster. instead, they have recently started shipping "multicore" architectures, in which multiple processors (cores) communicate directly through shared hardware caches, providing increased concurrency instead of increased clock speed.as a result, system designers and software engineers can no longer rely on increasing clock speed to hide software bloat. instead, they must somehow learn to make effective use of increasing parallelism. this adaptation will not be easy. conventional synchronization techniques based on locks and conditions are unlikely to be effective in such a demanding environment. coarse-grained locks, which protect relatively large amounts of data, do not scale, and fine-grained locks introduce substantial software engineering problems.transactional memory is a computational model in which threads synchronize by optimistic, lock-free transactions. this synchronization model promises to alleviate many (perhaps not all) of the problems associated with locking, and there is a growing community of researchers working on both software and hardware support for this approach. this talk will survey the area, with a focus on open research problems.
garbage collection without paging. garbage collection offers numerous software engineering advantages, but interacts poorly with virtual memory managers. existing garbage collectors require far more pages than the application's working set and touch pages without regard to which ones are in memory, especially during full-heap garbage collection. the resulting paging can cause throughput to plummet and pause times to spike up to seconds or even minutes. we present a garbage collector that avoids paging. this bookmarking collector cooperates with the virtual memory manager to guide its eviction decisions. using summary information ("bookmarks") recorded from evicted pages, the collector can perform in-memory full-heap collections. in the absence of memory pressure, the bookmarking collector matches the throughput of the best collector we tested while running in smaller heaps. in the face of memory pressure, it improves throughput by up to a factor of five and reduces pause times by up to a factor of 45 over the next best collector. compared to a collector that consistently provides high throughput (generational mark-sweep), the bookmarking collector reduces pause times by up to 218x and improves throughput by up to 41x. bookmarking collection thus provides greater utilization of available physical memory than other collectors while matching or exceeding their throughput.
caching function calls using precise dependencies. this paper describes the implementation of a purely functional programming language for building software systems. in this language, external tools like compilers and linkers are invoked by function calls. because some function calls are extremely expensive, it is obviously important to reuse the results of previous function calls whenever possible. caching a function call requires the language interpreter to record all values on which the function call depends. for optimal caching, it is important to record precise dependencies that are both dynamic and fine-grained. the paper sketches how we compute such dependencies, describes the implementation of an efficient function cache, and evaluates our implementation's performance.
dynamic software updating. many important applications must run continuously and without interruption, yet must be changed to fix bugs or upgrade functionality. no prior general-purpose methodology for dynamic updating achieves a practical balance between flexibility, robustness, low overhead, and ease of use. we present a new approach for c-like languages that provides type-safe dynamic updating of native code in an extremely flexible manner (code, data, and types may be updated, at programmer-determined times) and permits the use of automated tools to aid the programmer in the updating process. our system is based on dynamic patches that both contain the updated code and the code needed to transition from the old version to the new. a novel aspect of our patches is that they consist of verifiable native code (e.g. proof-carrying code [17] or typed assembly language [16]), which is native code accompanied by annotations that allow on-line verification of the code's safety. we discuss how patches are generated mostly automatically, how they are applied using dynamic-linking technology, and how code is compiled to make it updateable. to concretely illustrate our system, we have implemented a dynamically-updateable web server, flashed. we discuss our experience building and maintaining flashed. performance experiments show that for flashed, the overhead due to updating is typically less than 1%.
representing control in the presence of first-class continuations. languages such as scheme and smalltalk that provide continuations as first-class data objects present a challenge to efficient implementation. allocating activation records in a heap has proven unsatisfactory because of increased frame linkage costs, increased garbage collection overhead, and decreased locality of reference. however, simply allocating activation records on a stack and copying them when a continuation is created results in unbounded copying overhead. this paper describes a new approach based on stack allocation that does not require the stack to be copied when a continuation is created and that allows us to place a small upper bound on the amount copied when a continuation is reinstated. this new approach is faster than the naive stack allocation approach, and it does not suffer from the problems associated with unbounded copying. for continuation-intensive programs, our approach is at worst a constant factor slower than the heap allocation approach, and for typical programs, it is significantly faster. an important additional benefit is that recovery from stack overflow is handled gracefully and efficiently.
debugging optimized code with dynamic deoptimization. self's debugging system provides complete source-level debugging (expected behavior) with globally optimized code. it shields the debugger from optimizations performed by the compiler by dynamically deoptimizing code on demand. deoptimization only affects the procedure activations that are actively being debugged; all other code runs at full speed. deoptimization requires the compiler to supply debugging information at discrete interrupt points; the compiler can still perform extensive optimizations between interrupt points without affecting debuggability. at the same time, the inability to interrupt between interrupt points is invisible to the user. our debugging system also handles programming changes during debugging. again, the system provides expected behavior: it is possible to change a running program and immediately observe the effects of the change. dynamic deoptimization transforms old compiled code (which may contain inlined copies of the old version of the changed procedure) into new versions reflecting the current source-level state. to the best of our knowledge, self is the first practical system providing full expected behavior with globally optimized code.
compiling real-time programs into schedulable code. we present a programming language with first-class timing constructs, whose semantics is based on time-constrained relationships between observable events. since a system specification postulates timing relationships between events, realizing the specification in a program becomes a more straightforward process. using these constraints, as well as those imposed by data and control flow properties, our objective is to transform the code so that its worst-case execution time is consistent with its real-time requirements. to accomplish this goal we first translate an event-based source program into intermediate code, in which the timing constraints are imposed on the code itself, and then use a compilation technique which synthesizes feasible code from the original source program.
alphonse: incremental computation as a programming abstraction. alphonse is a program transformation system that uses dynamic dependency analysis and incremental computation techniques to automatically generate efficient dynamic implementations from simple exhaustive imperative program specifications.
experience with cst: programming and implementation. cst is a programming language based on smalltalk-802 that supports concurrency using locks, asynchronous messages, and distributed objects. in this paper, we describe cst: the language and its implementation. example programs and initial programming experience with cst are described. our implementation of cst generates native code for the j-machine, a fine-grained concurrent computer. some compiler optimizations developed in conjunction with that implementation are also described.
identifying the semantic and textual differences between two versions of a program. text-based file comparators (e.g., the unix utility diff), are very general tools that can be applied to arbitrary files. however, using such tools to compare programs can be unsatisfactory because their only notion of change is based on program text rather than program behavior. this paper describes a technique for comparing two versions of a program, determining which program components represents changes, and classifying each changed component as representing either a semantic or a textual change.
dependence analysis for pointer variables. our concern is how to determine data dependencies between program constructs in programming languages with pointer variables. we are particularly interested in computing data dependencies for languages that manipulate heap-allocated storage, such as lisp and pascal. we have defined a family of algorithms that compute safe approximations to the flow, output, and anti-dependencies of a program written in such a language. our algorithms account for destructive updates to fields of a structure and thus are not limited to the cases where all structures are trees or acyclic graphs; they are applicable to programs that build cyclic structures. our technique extends an analysis method described by jones and muchnick that determines an approximation to the actual layouts of memory that can arise at each program point during execution. we extend the domain used in their abstract interpretation so that the (abstract) memory locations are labeled by the program points that set their contents. data dependencies are then determined from these memory layouts according to the component labels found along the access paths that must be traversed during execution to evaluate the program's statements and predicates. for structured programming constructs, the technique can be extended to distinguish between loop-carried and loop-independent dependencies, as well as to determine lower bounds on minimum distances for loop-carried dependencies.
interprocedural slicing using dependence graphs. a slice of a program with respect to a program point p and variable x consists of all statements of the program that might affect the value of x at point p. this paper concerns the problem of interprocedural slicing -- generating a slice of an entire program, where the slice crosses the boundaries of procedure calls. to solve this problem, we introduce a new kind of graph to represent programs, called a system dependence graph, which extends previous dependence representations to incorporate collections of procedures (with procedure calls) rather than just monolithic programs. our main result is an algorithm for interprocedural slicing that uses the new representation.the chief difficulty in interprocedural slicing is correctly accounting for the calling context of a called procedure. to handle this problem, system dependence graphs include some data-dependence edges that represent transitive dependencies due to the effects of procedure calls, in addition to the conventional direct-dependence edges. these edges are constructed with the aid of an auxiliary structure that represents calling and parameter-linkage relationships. this structure takes the form of an attribute grammar. the step of computing the required transitive-dependence edges is reduced to the construction of the subordinate characteristic graphs for the grammar's nonterminals.
the design, implementation, and evaluation of a compiler algorithm for cpu energy reduction. this paper presents the design and implementation of a compiler algorithm that effectively optimizes programs for energy usage using dynamic voltage scaling (dvs). the algorithm identifies program regions where the cpu can be slowed down with negligible performance loss. it is implemented as a source-to-source level transformation using the suif2 compiler infrastructure. physical measurements on a high-performance laptop show that total system (i.e., laptop) energy savings of up to 28% can be achieved with performance degradation of less than 5% for the specfp95 benchmarks. on average, the system energy and energy-delay product are reduced by 11% and 9%, respectively, with a performance slowdown of 2%. it was also discovered that the energy usage of the programs using our dvs algorithm is within 6% from the theoretical lower bound. to the best of our knowledge, this is one of the first work that evaluates dvs algorithms by physical measurements.
lifetime-sensitive modulo scheduling. this paper shows how to software pipeline a loop for minimal register pressure without sacrificing the loop's minimum execution time. this novel bidirectional slack-scheduling method has been implemented in a fortran compiler and tested on many scientific benchmarks. the empirical results&mdash;when measured against an absolute lower bound on execution time, and against a novel schedule-independent absolute lower bound on register pressure&mdash;indicate near-optimal performance.
a block-and-actions generator as an alternative to a simulator for collecting architecture measurements. to design a new processor or to modify an existing one, designers need to gather data to estimate the influence of specific architecture features on the performance of the proposed machine (pm). to obtain this data, it is necessary to measure on an existing machine (em) the dynamic behavior of typical programs. traditionally, simulators have been used to obtain measurements for pms. since several hundred em instructions are required to decode, interpret, and measure each simulated (pm) instruction, the simulation time of typical programs is prohibitively large. thus, designers tend to simulate only small programs and the results obtained might not be representative of a real system behavior. in this paper we present an alternative tool for collecting architecture measurements: the block-and-actions generator (bkgen). bkgen produces a version of the program being measured which is directly executable by the em. this executable version is obtained directly with the em compiler or with the pm compiler and a assembly-to-assembly translator. the choice between these alternatives depends on the em and pm compiler technology and the type of measurements to be obtained. bkgen also collects the pm events to be measured (called actions). each em block of instructions is associated with a pm block of actions so that when the program is executed, it collects the measurements associated with the pm. the main advantage of bkgen is that the execution time is substantially reduced compared to the execution time of a simulator while collecting similar data. thus, large typical programs (compilers, assemblers, word processors, ...) can be used by the designer to obtain meaningful measurements.
a general data dependence test for dynamic, pointer-based data structures. optimizing compilers require accurate dependence testing to enable numerous, performance-enhancing transformations. however, data dependence testing is a difficult problem, particularly in the presence of pointers. though existing approaches work well for pointers to named memory locations (i.e. other variables), they are overly conservative in the case of pointers to unnamed memory locations. the latter occurs in the context of dynamic, pointer-based data structures, used in a variety of applications ranging from system software to computational geometry to n-body and circuit simulations. in this paper we present a new technique for performing more accurate data dependence testing in the presence of dynamic, pointer-based data structures. we will demonstrate its effectiveness by breaking false dependences that existing approaches cannot, and provide results which show that removing these dependences enables significant parallelization of a real application.
stride prefetching by dynamically inspecting objects. software prefetching is a promising technique to hide cache miss latencies, but it remains challenging to effectively prefetch pointer-based data structures because obtaining the memory address to be prefetched requires pointer dereferences. the recently proposed stride prefetching overcomes this problem, but it only exploits inter-iteration stride patterns and relies on an off-line profiling method.we propose a new algorithm for stride prefetching which is intended for use in a dynamic compiler. we exploit both inter- and intra-iteration stride patterns, which we discover using an ultra-lightweight profiling technique, called object inspection. this is a kind of partial interpretation that only a dynamic compiler can perform. during the compilation of a method, the dynamic compiler gathers the profile information by partially interpreting the method using the actual values of parameters and causing no side effects.we evaluated an implementation of our prefetching algorithm in a production-level java just-in time compiler. the results show that the algorithm achieved up to an 18.9% and 25.1% speedup in industry-standard benchmarks on the pentium 4 and the athlon mp, respectively, while it increased the compilation time by less than 3.0%.
type declarations as subtype constraints in logic programming. this paper presents a type system for logic programs that supports parametric polymorphism and subtypes. this system follows most knowledge representation and object-oriented schemes in that subtyping is name-based, i.e., &tgr;1 is considered to be a subtype of &tgr;2 iff it is declared as such. we take this as a fundamental principle in the sense that type declarations have the form of subtype constraints. types are assigned meaning by viewing such constraints as horn clauses that, together with a few basic axioms, define a subtype predicate. this technique provides a (least) model for types and, at the same time, a sound and complete proof system for deriving subtypes. using this proof system, we define well-typedness conditions which ensure that a logic program/query respects a set of predicate types. we prove that these conditions are consistent in the sense that every atom of every resolvent produced during the execution of a well-typed program is consistent with its type.
a customizable substrate for concurrent languages. we describe an approach to implementing a wide-range of concurrency paradigms in high-level (symbolic) programming languages. the focus of our discussion is sting, a dialect of scheme, that supports lightweight threads of control and virtual processors as first-class objects. given the significant degree to which the behavior of these objects may be customized, we can easily express a variety of concurrency paradigms and linguistic structures within a common framework without loss of efficiency. unlike parallel systems that rely on operating system services for managing concurrency, sting implements concurrency management entirely in terms of scheme objects and procedures. it, therefore, permits users to optimize the runtime behavior of their applications without requiring knowledge of the underlying runtime system. this paper concentrates on (a) the implications of the design for building asynchronous concurrency structures, (b) organizing large-scale concurrent computations, and (c) implementing robust programming environments for symbolic computing.
flow-directed inlining. a flow-directed inlining strategy uses information derived from control-flow analysis to specialize and inline procedures for functional and object-oriented languages. since it uses control-flow analysis to identify candidate call sites, flow-directed inlining can inline procedures whose relationships to their call sites are not apparent. for instance, procedures defined in other modules, passed as arguments, returned as values, or extracted from data structures can all be inlined. flow-directed inlining specializes procedures for particular call sites, and can selectively inline a particular procedure at some call sites but not at others. finally, flow-directed inlining encourages modular implementations: control-flow analysis, inlining, and post-inlining optimizations are all orthogonal components. results from a prototype implementation indicate that this strategy effectively reduces procedure call overhead and leads to significant reduction in execution time.
an efficient approach to data flow analysis in a multi pass global optimizer. data flow analysis is a time-consuming part of the optimization process. as transformations are made in a multiple pass global optimizer, the data flow information must be updated to reflect these changes. various approaches have been used, including complete recalculation as well as partial recalculation over the affected area. the approach presented here has been designed for maximum efficiency. data flow information is completely calculated only once, using an interval analysis method which is slightly faster than a purely iterative approach, and which allows partial recomputation when appropriate. a minimal set of data flow information is computed, keeping the computation and update cost low. following each set of transformations, the data flow information is updated based on knowledge of the effect of each change. this approach saves considerable time over complete recalculation, and proper ordering of the various optimizations minimizes the amount of update required.
algorithm specialization in generic programming: challenges of constrained generics in c++. generic programming has recently emerged as a paradigm for developing highly reusable software libraries, most notably in c++. we have designed and implemented a constrained generics extension for c++ to support modular type checking of generic algorithms and to address other issues associated with unconstrained generics. to be as broadly applicable as possible, generic algorithms are defined with minimal requirements on their inputs. at the same time, to achieve a high degree of efficiency, generic algorithms may have multiple implementations that exploit features of specific classes of inputs. this process of algorithm specialization relies on non-local type information and conflicts directly with the local nature of modular type checking. in this paper, we review the design and implementation of our extensions for generic programming in c++, describe the issues of algorithm specialization and modular type checking in detail, and discuss the important design tradeoffs in trying to accomplish both.we present the particular design that we chose for our implementation, with the goal of hitting the sweet spot in this interesting design space.
path slicing. we present a new technique, path slicing, that takes as input a possibly infeasible path to a target location, and eliminates all the operations that are irrelevant towards the reachability of the target location. a path slice is a subsequence of the original path whose infeasibility guarantees the infeasibility of the original path, and whose feasibility guarantees the existence of some feasible variant of the given path that reaches the target location even though the given path may itself be infeasible. our method combines the ability of program slicing to look at several program paths, with the precision that dynamic slicing enjoys by focusing on a single path. we have implemented path slicing to analyze possible counterexamples returned by the software model checker blast. we show its effectiveness in drastically reducing the size of the counterexamples to less than 1% of their original size. this enables the precise verification of application programs (upto 100kloc), by allowing the analysis to focus on the part of the counterexample that is relevant to the property being checked.
code placement for improving dynamic branch prediction accuracy. code placement techniques have traditionally improved instruction fetch bandwidth by increasing instruction locality and decreasing the number of taken branches. however, traditional code placement techniques have less benefit in the presence of a trace cache that alters the placement of instructions in the instruction cache. moreover, as pipelines have become deeper to accommodate increasing clock rates, branch misprediction penalties have become a significant impediment to performance. we evaluate pattern history table partitioning, a feedback directed code placement technique that explicitly places conditional branches so that they are less likely to interfere destructively with one another in branch prediction tables. on spec cpu benchmarks running on an intel pentium 4, branch mispredictions are reduced by up to 22% and 3.5% on average. this reduction yields a speedup of up to 16.0% and 4.5% on average. by contrast, branch alignment, a previous code placement technique, yields only up to a 4.7% speedup and less than 1% on average.
context-sensitive domain-independent algorithm composition and selection. progressing beyond the productivity of present-day languages appears to require using domain-specific knowledge. domain-specific languages and libraries (dsls) proliferate, but most optimizations and language features have limited portability because each language's semantics are related closely to its domain. we explain how any dsl compiler can use a domain-independent ai planner to implement algorithm composition as a language feature. our notion of composition addresses a common dsl problem: good library designers tend to minimize redundancy by including only fundamental procedures that users must chain together into call sequences. novice users are confounded by not knowing an appropriate sequence to achieve their goal. composition allows the programmer to define and call an abstract algorithm (aa) like a procedure. the compiler replaces an aa call with a sequence of library calls, while considering the calling context. because ai planners compute a sequence of operations to reach a goal state, the compiler can implement composition by analyzing the calling context to provide the planner's initial state. nevertheless, mapping composition onto planning is not straightforward because applying planning to software requires extensions to classical planning, and procedure specifications may be incomplete when expressed in a planning language. compositions may not be provably correct, so our approach mitigates semantic incompleteness with unobtrusive programmer-compiler interaction. this tradeoff is key to making composition a practical and natural feature of otherwise imperative languages, whose users eschew complex logical specifications. compositions satisfying an aa may not be equal in performance, memory usage, or precision and require selection of a preferred solution. we examine language design and implementation issues, and we perform a case study on the bioperl bioinformatics library.
min-cut program decomposition for thread-level speculation. with billion-transistor chips on the horizon, single-chip multiprocessors (cmps) are likely to become commodity components. speculative cmps use hardware to enforce dependence, allowing the compiler to improve performance by speculating on ambiguous dependences without absolute guarantees of independence. the compiler is responsible for decomposing a sequential program into speculatively parallel threads, while considering multiple performance overheads related to data dependence, load imbalance, and thread prediction. although the decomposition problem lends itself to a min-cut-based approach, the overheads depend on the thread size, requiring the edge weights to be changed as the algorithm progresses. the changing weights make our approach different from graph-theoretic solutions to the general problem of task scheduling. one recent work uses a set of heuristics, each targeting a specific overhead in isolation, and gives precedence to thread prediction, without comparing the performance of the threads resulting from each heuristic. by contrast, our method uses a sequence of balanced min-cuts that give equal consideration to all the overheads, and adjusts the edge weights after every cut. this method achieves an (geometric) average speedup of 74% for floating-point programs and 23% for integer programs on a four-processor chip, improving on the 52% and 13% achieved by the previous heuristics.
dependence-based program analysis. program analysis and optimization can be speeded up through the use of the dependence flow graph (dfg), a representation of program dependences which generalizes def-use chains and static single assignment (ssa) form. in this paper, we give a simple graph-theoretic description of the dfg and show how the dfg for a program can be constructed in o(ev) time. we then show how forward and backward dataflow analyses can be performed efficiently on the dfg, using constant propagation and elimination of partial redundancies as examples. these analyses can be framed as solutions of dataflow equations in the dfg. our construction algorithm is of independent interest because it can be used to construct a program's control dependence graph in o(e) time and its ssa representation in o(ev) time, which are improvements over existing algorithms.
the program structure tree: computing control regions in linear time. in this paper, we describe the program structure tree (pst), a hierarchical representation of program structure based on single entry single exit (sese) regions of the control flow graph. we give a linear-time algorithm for finding sese regions and for building the pst of arbitrary control flow graphs (including irreducible ones). next, we establish a connection between sese regions and control dependence equivalence classes, and show how to use the algorithm to find control regions in linear time. finally, we discuss some applications of the pst. many control flow algorithms, such as construction of static single assignment form, can be speeded up by applying the algorithms in a divide-and-conquer style to each sese region on its own. the pst is also used to speed up data flow analysis by exploiting &ldquo;sparsity&rdquo;. experimental results from the perfect club and spec89 benchmarks confirm that the pst approach finds and exploits program structure.
static array storage optimization in matlab. static array storage optimization in matlab.
a semantics for imprecise exceptions. some modern superscalar microprocessors provide only imprecise exceptions. that is, they do not guarantee to report the same exception that would be encountered by a straightforward sequential execution of the program. in exchange, they offer increased performance or decreased chip area (which amount to much the same thing).this performance/precision tradeoff has not so far been much explored at the programming language level. in this paper we propose a design for imprecise exceptions in the lazy functional programming language haskell. we discuss several designs, and conclude that imprecision is essential if the language is still to enjoy its current rich algebra of transformations. we sketch a precise semantics for the language extended with exceptions.the paper shows how to extend haskell with exceptions without crippling the language or its compilers. we do not yet have enough experience of using the new mechanism to know whether it strikes an appropriate balance between expressiveness and performance.
denali: a goal-directed superoptimizer. this paper provides a preliminary report on a new research project that aims to construct a code generator that uses an automatic theorem prover to produce very high-quality (in fact, nearly mathematically optimal) machine code for modern architectures. the code generator is not intended for use in an ordinary compiler, but is intended to be used for inner loops and critical subroutines in those cases where peak performance is required, no available compiler generates adequately efficient code, and where current engineering practice is to use hand-coded machine language. the paper describes the design of the superoptimizer, and presents some encouraging preliminary results.
design, implementation and evaluation of the fnc-2 attribute grammar system. fnc-2 is a new attribute grammar processing system aiming at expressive power, efficiency, ease of use and versatility. its development at inria started in 1986, and a first running prototype is available since early 1989. its most important features are: efficient exhaustive and incremental visit-sequence-based evaluation of strongly (absolutely) non-circular ags; extensive space optimizations; a specially-designed ag-description language, with provisions for true modularity; portability and versatility of the generated evaluators; complete environment for application development. this paper briefly describes the design and implementation of fnc-2 and its peripherals. then preliminary experience with the system is reported.
reasoning about continuations with control effects. we present a new static analysis method for first-class continuations that uses an effect system to classify the control domain behavior of expressions in a typed polymorphic language. we introduce two new control effects, goto and comefrom, that describe the control flow properties of expressions. an expression that does not have a goto effect is said to be continuation following because it will always call its passed return continuation. an expression that does not have a comefrom effect is said to be continuation discarding because it will never preserve its return continuation for later use. unobservable control effects can be masked by the effect system. control effect soundness theorems guarantee that the effects computed statically by the effect system are a conservative approximation of the dynamic behavior of an expression. the effect system that we describe performs certain kinds of control flow analysis that were not previously feasible. we discuss how this analysis can enable a variety of compiler optimizations, including parallel expression scheduling in the presence of complex control structures, and stack allocation of continuations. the effect system we describe has been implemented as an extension to the fx-87 programming language.
incremental re-execution of programs. interpreters replace the edit/compile/run cyle with edit/run. dynamic computing environments, like spreadsheets, shorten this still more to just edit. so-called "visiprog" environments, such as maryland's xed, permit developing normal imperative programs in a dynamic computing environment, xed and similar environments, because they show the results of executing a program after every (reasonable) editing step, raise the issue of efficient incremental execution. incremental execution optimizations are also applicable to any programming situation, including batch/cards, in which nearly the same program is run many times on nearly the same data. however, the requirement of remembering large amounts of internal state between runs make incremental exectution most natural for interpreted languages. this paper examines some algorithms for incremental execution. based on the frequency of typical program editing changes, we predict the importance of optimizing certain kinds of incremental execution. we also examine actual speedups obtained in executing programs after subjecting them to these simulated incremental edits under these optimizations. the speedups range from factors of 1.1 to near 10. finally, we discuss the feasibility of including these optimizations in an actual dynamic computing environment like xed, and in more traditional programming environments.
effective sign extension elimination. computer designs are shifting from 32-bit architectures to 64-bit architectures, while most of the programs available today are still designed for 32-bit architectures. java&trade;, for example, specifies the frequently used int" as a 32-bit data type. if such java programs are executed on a 64-bit architecture, many 32-bit values must be sign-extended to 64-bit values for integer operations. this causes serious performance overhead. in this paper, we present a fast and effective algorithm for eliminating sign extensions. we implemented this algorithm in the ibm java just-in-time (jit) compiler for ia-64&trade;. our experimental results show that our algorithm effectively eliminates the majority of sign extensions. they also show that it significantly improves performance, while it increases jit compilation time by only 0.11%. we implemented our algorithm for programs in java, but it can be applied to any language requiring sign extensions.
ccal: an interpreted language for experimentation in concurrent control. concurrent control abstraction language, ccal, is an interpreted language which provides no particular control regime to the user. ccal instead supports five primitive operations which manipulate an abstract model of inter-procedural control. this model is intrinsically concurrent, and the user is allowed to construct high-level concurrent control operations from the primitives (hence, control abstraction). the primary use of ccal is as a vehicle by which rapid prototyping of application specific control forms may be done and as a tool for the construction and evaluation of novel control forms, especially control forms for highly concurrent and distributed systems. the ccal interpreter is implemented as a distributed program on a network of vaxen and sun-3 workstations under 4.2bsd and 4.3bsd unix1. ccal programs appear as multi-process programs in a shared memory system. both true and apparent concurrency are possible. this paper describes the control abstraction facilities offered by the ccal interpreter, its use, and implementation strategies in the distributed environment.
design and implementation of generics for the .net common language runtime. the microsoft.net common language runtime provides a shared type system, intermediate language and dynamic execution environment for the implementation and inter-operation of multiple source languages. in this paper we extend it with direct support for parametric polymorphism (also known as generics), describing the design through examples written in an extended version of the c# programming language, and explaining aspects of implementation by reference to a prototype extension to the runtime. our design is very expressive, supporting parameterized types, polymorphic static, instance and virtual methods, &ldquo;f-bounded&rdquo; type parameters, instantiation at pointer and value types, polymorphic recursion, and exact run-time types. the implementation takes advantage of the dynamic nature of the runtime, performing just-in-time type specialization, representation-based code sharing and novel techniques for efficient creation and use of run-time types. early performance results are encouraging and suggest that programmers will not need to pay an overhead for using generics, achieving performance almost matching hand-specialized code.
the compressor: concurrent, incremental, and parallel compaction. the widely used mark-and-sweep garbage collector has a drawback in that it does not move objects during collection. as a result, large long-running realistic applications, such as web application servers, frequently face the fragmentation problem. to eliminate fragmentation, a heap compaction is run periodically. however, compaction typically imposes very long undesirable pauses in the application. while efficient concurrent collectors are ubiquitous in production runtime systems (such as jvms), an efficient non-intrusive compactor is still missing.in this paper we present the compressor, a novel compaction algorithm that is concurrent, parallel, and incremental. the compressor compacts the entire heap to a single condensed area, while preserving the objects' order, but reduces pause times significantly, thereby allowing acceptable runs on large heaps. furthermore, the compressor is the first compactor that requires only a single heap pass. as such, it is the most efficient compactors known today, even when run in a parallel stop-the-world manner (i.e., when the program threads are halted). thus, to the best of our knowledge, the compressor is the most efficient compactor known today. the compressor was implemented on a jikes research rvm and we provide measurements demonstrating its qualities.
balanced scheduling: instruction scheduling when memory latency is uncertain. traditional list schedulers order instructions based on an optimistic estimate of the load delay imposed by the implementation. therefore they cannot respond to variations in load latencies (due to cache hits or misses, congestion in the memory interconnect, etc.) and cannot easily be applied across different implementations. we have developed an alternative algorithm, known as balanced scheduling, that schedules instructions based on an estimate of the amount of instruction level parallelism in the program. since scheduling decisions are program- rather than machine-based, balanced scheduling is unaffected by implementation changes. since it is based on the amount of instruction level parallelism that a program can support, it can respond better to variations in load latencies. performance improvements over a traditional list scheduler on a fortran workload and simulating several different machine types (cache-based workstations, large parallel machines with a multipath interconnect and a combination, all with non-blocking processors) are quite good, averaging between 3% and 18%.
fast breakpoints: design and implementation. in re-implementing fast breakpoints for stock hardware, i discovered the joys of putting self-modifying code to good use.by "fast breakpoints" i mean inserting transfers of control to change the behavior of a running program. i don't claim to have invented fast breakpoints: i have traced their use back to 1951 [1]. i didn't even put these breakpoints to novel uses. all i did was rediscover how easy it is to take statically compiled code and modify it at runtime to alter the semantics of programs. the most obvious application is to evaluate predicates and expressions for debugging, but other uses are possible.we have designed and implemented a fast breakpoint facility. breakpoints are usually thought of as a feature of an interactive debugger, in which case the breakpoints need not be particularly fast. in our environment breakpoints are often used for non-interactive information gathering; for example, procedure call count and statement execution count profiling [swinehart, et al.]. when used non-interactively, breakpoints should be as fast as possible, so as to perturb the execution of the program as little as possible. even in interactive debuggers, a conditional breakpoint facility would benefit from breakpoints that could transfer to the evaluation of the condition rapidly, and continue expeditiously if the condition were not satisfied. such conditional breakpoints could be used to check assertions, etc. program advising could also make use of fast breakpoints [teitelman]. examples of advising include tracing, timing, and even animation, all of which should be part of an advanced programming environment.we have ported the cedar environment from a machine with microcode support for breakpoints [lampson and pier] to commercial platforms running c code [atkinson, et al.]. most of our ports run under the unix* operating system, so one choice for implementing breakpoints for cedar was to use the breakpoint facility provided by that system. the breakpoints provided by the unix operating system are several orders of magnitude too slow (and also several process switches too complicated) for the applications we have in mind. so we designed a breakpoint system that was fast enough for our purposes.breakpoints for uni-processors running single threads of control used to be fast and simple to implement. this paper shows that breakpoints can still be fast, even with multiple threads of control on multi-processors. this paper describes problems in the design of a breakpoint package for modern computer architectures and programming styles, and our solutions to them for a particular architecture.
anatomy of a hardware compiler. programming-language compilers generate code targeted to machines with fixed architectures, either parallel or serial. compiler techniques can also be used to generate the hardware on which these programming languages are executed. in this paper we demonstrate that many compilation techniques developed for programming languages are applicable to compilation of register-transfer hardware designs. our approach uses a typical syntax-directed translation &rarr; global optimization &rarr; local optimization &rarr; code generation &rarr; peephole optimization method. in this paper we will describe ways in which we have both followed and diverged from traditional compiler approaches to these problems and compare our approach to other compiler oriented approaches to hardware compilation.
data specialization. given a repeated computation, part of whose input context remains invariant across all repetitions, program staging improves performance by separating the computation into two phases. an early phase executes only once, performing computations depending only on invariant inputs, while a late phase repeatedly performs the remainder of the work given the varying inputs and the results of the early computations.common staging techniques based on dynamic compilation statically construct an early phase that dynamically generates object code customized for a particular input context. in effect, the results of the invariant computations are encoded as the compiled code for the late phase.this paper describes an alternative approach in which the results of early computations are encoded as a data structure, allowing both the early and late phases to be generated statically. by avoiding dynamic code manipulation, we give up some optimization opportunities in exchange for significantly lower dynamic space/time overhead and reduced implementation complexity.
lazy code motion. we present a bit-vector algorithm for the optimal and economical placement of computations within flow graphs, which is as efficient as standard uni-directional analyses. the point of our algorithm is the decomposition of the bi-directional structure of the known placement algorithms into a sequence of a backward and a forward analysis, which directly implies the efficiency result. moreover, the new compositional structure opens the algorithm for modification: two further uni-directional analysis components exclude any unnecessary code motion. this laziness of our algorithm minimizes the register pressure, which has drastic effects on the run-time behaviour of the optimized programs in practice, where an economical use of registers is essential.
partial dead code elimination. a new aggressive algorithm for the elimination of partially dead code is presented, i.e., of code which is only dead on some program paths. besides being more powerful than the usual approaches to dead code elimination, this algorithm is optimal in the following sense: partially dead code remaining in the resulting program cannot be eliminated without changing the branching structure or the semantics of the program, or without impairing some program executions. our approach is based on techniques for partial redundancy elimination. besides some new technical problems there is a significant difference here: partial dead code elimination introduces second order effects, which we overcome by means of exhaustive motion and elimination steps. the optimality and the uniqueness of the program obtained is proved by means of a new technique which is universally applicable and particularly useful in the case of mutually interdependent program optimizations.
the power of assignment motion. assignment motion (am) and expression motion (em) are the basis of powerful and at the first sight incomparable techniques for removing partially redundant code from a program. whereas am aims at the elimination of complete assignments, a transformation which is always desirable, the more flexible em requires temporaries to remove partial redundancies. based on the observation that a simple program transformation enhances am to subsume em, we develop an algorithm that for the first time captures all second order effects between am and em transformations. under usual structural restrictions, the worst case time complexity of our algorithm is essentially quadratic, a fact which explains the promising experience with our implementation.
data-centric multi-level blocking. we present a simple and novel framework for generating blocked codes for high-performance machines with a memory hierarchy. unlike traditional compiler techniques like tiling, which are based on reasoning about the control flow of programs, our techniques are based on reasoning directly about the flow of data through the memory hierarchy. our data-centric transformations permit a more direct solution to the problem of enhancing data locality than current control-centric techniques do, and generalize easily to multiple levels of memory hierarchy. we buttress these claims with performance numbers for standard benchmarks from the problem domain of dense numerical linear algebra. the simplicity and intuitive appeal of our approach should make it attractive to compiler writers as well as to library writers.
the set constraint/cfl reachability connection in practice. many program analyses can be reduced to graph reachability problems involving a limited form of context-free language reachability called dyck-cfl reachability. we show a new reduction from dyck-cfl reachability to set constraints that can be used in practice to solve these problems. our reduction is much simpler than the general reduction from context-free language reachability to set constraints. we have implemented our reduction on top of a set constraints toolkit and tested its performance on a substantial polymorphic flow analysis application.
a global progressive register allocator. this paper describes a global progressive register allocator, a register allocator that uses an expressive model of the register allocation problem to quickly find a good allocation and then progressively find better allocations until a provably optimal solution is found or a preset time limit is reached. the key contributions of this paper are an expressive model of global register allocation based on multicommodity network flows that explicitly represents spill code optimization, register preferences, copy insertion, and constant rematerialization; two fast, but effective, heuristic allocators based on this model; and a more elaborate progressive allocator that uses lagrangian relaxation to compute the optimality of its allocations. our progressive allocator demonstrates code size improvements as large as 16.75% compared to a traditional graph allocator. on average, we observe an initial improvement of 3.47%, which increases progressively to 6.84% as more time is permitted for compilation.
load/store range analysis for global register allocation. live range splitting techniques improve global register allocation by splitting the live ranges of variables into segments that are individually allocated registers. load/store range analysis is a new technique for live range splitting that is based on reaching definition and live variable analyses. our analysis localizes the profits and the register requirements of every access to every variable to provide a fine granularity of candidates for register allocation. experiments on a suite of c and fortran benchmark programs show that a graph coloring register allocator operating on load/store ranges often provides better allocations than the same allocator operating on live ranges. experimental results also show that the computational cost of using load/store ranges for register allocation is moderately more than the cost of using live ranges.
elimination of redundant array subscript range checks. this paper presents a compiler optimization algorithm to reduce the run time overhead of array subscript range checks in programs without compromising safety. the algorithm is based on partial redundancy elimination and it incorporates previously developed algorithms for range check optimization. we implemented the algorithm in our research compiler, nascent, and conducted experiments on a suite of 10 benchmark programs to obtain four results: (1) the execution overhead of naive range checking is high enough to merit optimization, (2) there are substantial differences between various optimizations, (3) loop-based optimizations that hoist checks out of loops are effective in eliminating about 98% of the range checks, and (4) more sophisticated analysis and optimization algorithms produce very marginal benefits.
a fresh look at combinator graph reduction. we present a new abstract machine for graph reduction called tigre. benchmark results show that tigre's execution speed compares quite favorably with previous combinator-graph reduction techniques on similar hardware. furthermore, the mapping of tigre onto conventional hardware is simple and efficient. mainframe implementations of tigre provide performance levels exceeding those previously available on custom graph reduction hardware.
preference-directed graph coloring. this paper describes a new framework of register allocation based on chaitin-style coloring. our focus is on maximizing the chances for live ranges to be allocated to the most preferred registers while not destroying the colorability obtained by graph simplification. our coloring algorithm uses a graph representation of preferences called a register preference graph, which helps find a good register selection. we then try to relax the register selection order created by the graph simplification. the relaxed order is defined as a partial order, represented using a graph called a coloring precedence graph. our algorithm utilizes such a partial order for the register selection instead of using the traditional simplification-driven order so that the chances of honoring the preferences are effectively increased. experimental results show that our coloring algorithm is powerful to simultaneously handle spill decisions, register coalescing, and preference resolutions.
tools: a unifying approach to object-oriented language interpretation. the object-oriented paradigm is applied to the interpreting of programming languages. an intermediate representation of a program is created as a collection of objects representing various entities in the conceptual world of the source language. these objects cover both the static and the dynamic aspects of a program. as a major advantage of this approach, issues that are traditionally handled by very different techniques (like symbol table management and the generation and execution of intermediate code) can be treated in a unified manner. the specification language of an interpreter generator based on these principles is described.
implementation of a high-speed prolog interpreter. this paper describes the implementation of a high speed prolog interpreter on a standard microprocessor (50 klips on a 16 mhz mc68020). the interpreter is based on direct threaded code. by this method an interpreted program achieves the same speed as a compiled program, but uses only a tenth of memory. the first part of this paper describes the implementation of the interpreter. the second part compares the implementation, the runtime and the storage requirements with that of a compiler.
improving semi-static branch prediction by code replication. speculative execution on superscalar processors demands substantially better branch prediction than what has been previously available. in this paper we present code replication techniques that improve the accuracy of semi-static branch prediction to a level comparable to dynamic branch prediction schemes. our technique uses profiling to collect information about the correlation between different branches and about the correlation between the subsequent outcomes of a single branch. using this information and code replication the outcome of branches is represented in the program state. our experiments have shown that the misprediction rate can almost be halved while the code size is increased by one third.
mul-t: a high-performance parallel lisp. mul-t is a parallel lisp system, based on multilisp's future construct, that has been developed to run on an encore multimax multiprocessor. mul-t is an extended version of the yale t system and uses the t system's orbit compiler to achieve &ldquo;production quality&rdquo; performance on stock hardware &mdash; about 100 times faster than multilisp. mul-t shows that futures can be implemented cheaply enough to be useful in a production-quality system. mul-t is fully operational, including a user interface that supports managing groups of parallel tasks.
using annotation to reduce dynamic optimization time. dynamic compilation and optimization are widely used in heterogenous computing environments, in which an intermediate form of the code is compiled to native code during execution. an important trade off exists between the amount of time spent dynamically optimizing the program and the running time of the program. the time to perform dynamic optimizations can cause significant delays during execution and also prohibit performance gains that result from more complex optimization. in this research, we present an annotation framework that substantially reduces compilation overhead of java programs. annotations consist of analysis information collected off-line and are incorporated into java programs. the annotations are then used by dynamic compilers to guide optimization. the annotations we present reduce compilation overhead incurred at all stages of compilation and optimization as well as enable complex optimizations to be performed dynamically. on average, our annotation optimizations reduce optimized compilation overhead by 78% and enable speedups of 7% on average for the programs examined.
optimizing parallel programs with explicit synchronization. we present compiler analyses and optimizations for explicitly parallel programs that communicate through a shared address space. any type of code motion on explicitly parallel programs requires a new kind of analysis to ensure that operations reordered on one processor cannot be observed by another. the analysis, based on work by shasha and snir, checks for cycles among interfering accesses. we improve the accuracy of their analysis by using additional information from post-wait synchronization, barriers, and locks.we demonstrate the use of this analysis by optimizing remote access on distributed memory machines. the optimizations include message pipelining, to allow multiple outstanding remote memory operations, conversion of two-way to one-way communication, and elimination of communication through data re-use. the performance improvements are as high as 20-35% for programs running on a cm-5 multiprocessor using the split-c language as a global address layer.
permission-based ownership: encapsulating state in higher-order typed languages. today's module systems do not effectively support information hiding in the presence of shared mutable objects, causing serious problems in the development and evolution of large software systems. ownership types have been proposed as a solution to this problem, but current systems have ad-hoc access restrictions and are limited to java-like languages.in this paper, we describe system fown, an extension of system f with references and ownership. our design shows both how ownership fits into standard type theory and the encapsulation benefits it can provide in languages with first-class functions, abstract data types, and parametric polymorphism. by looking at ownership in the setting of systemf, we were able to develop a design that is more principled and flexible than previous ownership type systems, while also providing stronger encapsulation guarantees.
fast searches for effective optimization phase sequences. it has long been known that a fixed ordering of optimization phases will not produce the best code for every application. one approach for addressing this phase ordering problem is to use an evolutionary algorithm to search for a specific sequence of phases for each module or function. while such searches have been shown to produce more efficient code, the approach can be extremely slow because the application is compiled and executed to evaluate each sequence's effectiveness. consequently, evolutionary or iterative compilation schemes have been promoted for compilation systems targeting embedded applications where longer compilation times may be tolerated in the final stage of development. in this paper we describe two complementary general approaches for achieving faster searches for effective optimization sequences when using a genetic algorithm. the first approach reduces the search time by avoiding unnecessary executions of the application when possible. results indicate search time reductions of 65% on average, often reducing searches from hours to minutes. the second approach modifies the search so fewer generations are required to achieve the same results. measurements show that the average number of required generations decreased by 68%. these improvements have the potential for making evolutionary compilation a viable choice for tuning embedded applications.
esp: a language for programmable devices. this paper presents the design and implementation of event-driven state-machines programming (esp)&mdash;a language for programmable devices. in traditional languages, like c, using event-driven state-machine forces a tradeoff that requires giving up ease of development and reliability to achieve high performance. esp is designed to provide all of these three properties simultaneously. esp provides a comprehensive set of features to support development of compact and modular programs. the esp compiler compiles the programs into two targets&mdash;a c file that can be used to generate efficient firmware for the device; and a specification that can be used by a verifier like spln to extensively test the firmware. as a case study, we reimplemented vmmc firmware that runs on myrinet network interface cards using esp. we found that esp simplifies the task of programming with event-driven state machines. it required an order of magnitude fewer lines of code than the previous implementation. we also found that model-checking verifiers like spin can be used to effectively debug the firmware. finally, our measurements indicate that the performance overhead of using esp is relatively small.
zero-cost range splitting. this paper presents a new optimization technique that uses empty delay slots to improve code scheduling. we are able to split live ranges for free, by inserting spill code into empty delay slots. splitting a live range can reduce interferences with other live ranges and can sometimes free registers. live ranges no longer interfering with the split live range can sometimes make use of the extra register. our algorithm, as a final pass over the code, exploits empty delay slots that would remain unused if spill code was not inserted. this paper proposes a variety of optimizations that use the extra registers generated from live range splitting, including coalescing live ranges and improving code scheduling. we present an algorithm for improving code scheduling and present implementation results.
linear analysis and optimization of stream programs. as more complex dsp algorithms are realized in practice, there is an increasing need for high-level stream abstractions that can be compiled without sacrificing efficiency. toward this end, we present a set of aggressive optimizations that target linear sections of a stream program. our input language is streamit, which represents programs as a hierarchical graph of autonomous filters. a filter is linear if each of its outputs can be represented as an affine combination of its inputs. linearity is common in dsp components; examples include fir filters, expanders, compressors, ffts and dcts.we demonstrate that several algorithmic transformations, traditionally hand-tuned by dsp experts, can be completely automated by the compiler. first, we present a linear extraction analysis that automatically detects linear filters from the c-like code in their work function. then, we give a procedure for combining adjacent linear filters into a single filter, as well as for translating a linear filter to operate in the frequency domain. we also present an optimization selection algorithm, which finds the sequence of combination and frequency transformations that will give the maximal benefit.we have completed a fully-automatic implementation of the above techniques as part of the streamit compiler, and we demonstrate a 450% performance improvement over our benchmark suite.
a safe approximate algorithm for interprocedural pointer aliasing. during execution, when two or more names exist for the same location at some program point, we call them aliases. in a language which allows arbitrary pointers, the problem of determining aliases at a program point is p-space-hard [lan92]. we present an algorithm for the conditional may alias problem, which can be used to safely approximate interprocedural may alias in the presence of pointers. this algorithm is as precise as possible in the worst case and has been implemented in a prototype analysis tool for c programs. preliminary speed and precision results are presented.
incremental incrementally compacting garbage collection. a mixed-strategy garbage collection algorithm is presented, which combines mark-and-sweep and copy collection. the intent is to benefit from the compacting and linearizing properties of copy collection without losing computational use of half the memory. the stop-and-collect version of the algorithm is a simple and cheap technique to fight memory fragmentation. the collection strategy may be dynamically adapted to minimize the cost of collection, according to the amount of memory actually accessed by the computing process. the parallel version of the algorithm is to our knowledge the only parallel compacting collector for varisized cells, that leaves most (more than half) of the memory available for the computing process.
exploiting superword level parallelism with multimedia instruction sets. increasing focus on multimedia applications has prompted the addition of multimedia extensions to most existing general purpose microprocessors. this added functionality comes primarily with the addition of short simd instructions. unfortunately, access to these instructions is limited to in-line assembly and library calls. generally, it has been assumed that vector compilers provide the most promising means of exploiting multimedia instructions. although vectorization technology is well understood, it is inherently complex and fragile. in addition, it is incapable of locating simd-style parallelism within a basic block. in this paper we introduce the concept of superword level parallelism (slp) ,a novel way of viewing parallelism in multimedia and scientific applications. we believe slpp is fundamentally different from the loop level parallelism exploited by traditional vector processing, and therefore demands a new method of extracting it. we have developed a simple and robust compiler for detecting slpp that targets basic blocks rather than loop nests. as with techniques designed to extract ilp, ours is able to exploit parallelism both across loop iterations and within basic blocks. the result is an algorithm that provides excellent performance in several application domains. in our experiments, dynamic instruction counts were reduced by 46%. speedups ranged from 1.24 to 6.70.
whole program paths. whole program paths (wpp) are a new approach to capturing and representing a program's dynamic---actually executed---control flow. unlike other path profiling techniques, which record intraprocedural or acyclic paths, wpps produce a single, compact description of a program's entire control flow, including loop iteration and interprocedural paths.this paper explains how to collect and represent wpps. it also shows how to use wpps to find hot subpaths, which are the heavily executed sequences of code that should be the focus of performance tuning and compiler optimization.
detecting conflicts between structure accesses. two references to a record structure conflict if they access the same field and at least one modifies the location. because structures can be connected by pointers, deciding if two statements conflict requires knowledge of the possible aliases for the locations that they access. this paper describes a dataflow computation that produces a conservative description of the aliases visible at any point in a program. the data structure that records aliases is an alias graph. it also labels instances of structures so that the objects referenced at different points in a program can be compared. this paper shows how alias graphs can be used to detect potential conflicts.
eel: machine-independent executable editing. eel (executable editing library) is a library for building tools to analyze and modify an executable (compiled) program. the systems and languages communities have built many tools for error detection, fault isolation, architecture translation, performance measurement, simulation, and optimization using this approach of modifying executables. currently, however, tools of this sort are difficult and time-consuming to write and are usually closely tied to a particular machine and operating system. eel supports a machine- and system-independent editing model that enables tool builders to modify an executable without being aware of the details of the underlying architecture or operating system or being concerned with the consequences of deleting instructions or adding foreign code.
automatic pool allocation: improving performance by controlling data structure layout in the heap. this paper describes automatic pool allocation, a transformation framework that segregates distinct instances of heap-based data structures into seperate memory pools and allows heuristics to be used to partially control the internal layout of those data structures. the primary goal of this work is performance improvement, not automatic memory management, and the paper makes several new contributions. the key contribution is a new compiler algorithm for partitioning heap objects in imperative programs based on a context-sensitive pointer analysis, including a novel strategy for correct handling of indirect (and potentially unsafe) function calls. the transformation does not require type safe programs and works for the full generality of c and c++. second, the paper describes several optimizations that exploit data structure partitioning to further improve program performance. third, the paper evaluates how memory hierarchy behavior and overall program performance are impacted by the new transformations. using a number of benchmarks and a few applications, we find that compilation times are extremely low, and overall running times for heap intensive programs speed up by 10-25% in many cases, about 2x in two cases, and more than 10x in two small benchmarks. overall, we believe this work provides a new framework for optimizing pointer intensive programs by segregating and controlling the layout of heap-based data structures.
online performance auditing: using hot optimizations without getting burned. as hardware complexity increases and virtualization is added at more layers of the execution stack, predicting the performance impact of optimizations becomes increasingly difficult. production compilers and virtual machines invest substantial development effort in performance tuning to achieve good performance for a range of benchmarks. although optimizations typically perform well on average, they often have unpredictable impact on running time, sometimes degrading performance significantly. today's vms perform sophisticated feedback-directed optimizations, but these techniques do not address performance degradations, and they actually make the situation worse by making the system more unpredictable.this paper presents an online framework for evaluating the effectiveness of optimizations, enabling an online system to automatically identify and correct performance anomalies that occur at runtime. this work opens the door for a fundamental shift in the way optimizations are developed and tuned for online systems, and may allow the body of work in offline empirical optimization search to be applied automatically at runtime. we present our implementation and evaluation of this system in a product java vm.
lazy functional state threads. some algorithms make critical internal use of updatable state, even though their external specification is purely functional. based on earlier work on monads, we present a way of securely encapsulating stateful computations that manipulate multiple, named, mutable objects, in the context of a non-strict, purely-functional language.the security of the encapsulation is assured by the type system, using parametricity. intriguingly, this parametricity requires the provision of a (single) constant with a rank-2 polymorphic type.
optimizing programs over the constructive reals. the constructive reals provide programmers with a useful mechanism for prototyping numerical programs, and for experimenting with numerical algorithms. unfortunately, the performance of current implementations is inadequate for some potential applications. in particular, these implementations tend to be space inefficient, in that they essentially require a complete computation history to be maintained. some numerical analysts (cf. [3]) propose that the programmer instead be provided with variable precision interval arithmetic, and then be required to write code to restart a computation when the intervals become too inaccurate. though this model is no doubt appropriate at times, it is not an adequate replacement for exact arithmetic. the correct transformation from a program operating on the constructive reals to a reasonable program using iterated interval arithmetic can be nontrivial and error prone. here we present a technique based on program slicing to both automate this process and reduce the amount of reexecution. thus the programmer is still free to use the simpler abstraction of exact real arithmetic, but we can provide a more efficient interval arithmetic based implementation. some preliminary empirical results are presented.
optimizing ml with run-time code generation. we describe the design and implementation of a compiler that automatically translates ordinary programs written in a subset of ml into code that generates native code at run time. run-time code generation can make use of values and invariants that cannot be exploited at compile time, yielding code that is often superior to statically optimal code. but the cost of optimizing and generating code at run time can be prohibitive. we demonstrate how compile-time specialization can reduce the cost of run-time code generation by an order of magnitude without greatly affecting code quality. several benchmark programs are examined, which exhibit an average cost of only six cycles per instruction generated at run time.
using data groups to specify and check side effects. reasoning precisely about the side effects of procedure calls is important to many program analyses. this paper introduces a technique for specifying and statically checking the side effects of methods in an object-oriented language. the technique uses data groups, which abstract over variables that are not in scope, and limits program behavior by two alias-confining restrictions, pivot uniqueness and owner exclusion. the technique is shown to achieve modular soundness and is simpler than previous attempts at solving this problem.
automatically proving the correctness of compiler optimizations. we describe a technique for automatically proving compiler optimizations sound, meaning that their transformations are always semantics-preserving. we first present a domain-specific language, called cobalt, for implementing optimizations as guarded rewrite rules. cobalt optimizations operate over a c-like intermediate representation including unstructured control flow, pointers to local variables and dynamically allocated memory, and recursive procedures. then we describe a technique for automatically proving the soundness of cobalt optimizations. our technique requires an automatic theorem prover to discharge a small set of simple, optimization-specific proof obligations for each optimization. we have written a variety of forward and backward intraprocedural dataflow optimizations in cobalt, including constant propagation and folding, branch folding, full and partial redundancy elimination, full and partial dead assignment elimination, and simple forms of points-to analysis. we implemented our soundness-checking strategy using the simplify automatic theorem prover, and we have used this implementation to automatically prove our optimizations correct. our checker found many subtle bugs during the course of developing our optimizations. we also implemented an execution engine for cobalt optimizations as part of the whirlwind compiler infrastructure.
static single assignment form for machine code. static single assignment (ssa) is an effective intermediate representation in optimizing compilers. however, traditional ssa form and optimizations are not applicable to programs represented as native machine instructions because the use of dedicated registers imposed by calling conventions, the runtime system, and target architecture must be made explicit. we present a simple scheme for converting between programs in machine code and in ssa, such that references to dedicated physical registers in machine code are preserved. our scheme ignores all output- and anti-dependences imposed by physical registers while a program is in ssa form, but inserts compensation code during machine code reconstruction if any naming requirements have been violated. by resolving all mismatches between the two representations in separate phases, we are able to utilize existing ssa algorithms unaltered to perform machine code optimizations.
the implementation and evaluation of fusion and contraction in array languages. array languages such as fortran 90, hpf and zpl have many benefits in simplifying array-based computations and expressing data parallelism. however, they can suffer large performance penalties because they introduce intermediate arrays---both at the source level and during the compilation process---which increase memory usage and pollute the cache. most compilers address this problem by simply scalarizing the array language and relying on a scalar language compiler to perform loop fusion and array contraction. we instead show that there are advantages to performing a form of loop fusion and array contraction at the array level. this paper describes this approach and explains its advantages. experimental results show that our scheme typically yields runtime improvements of greater than 20% and sometimes up to 400%. in addition, it yields superior memory use when compared against commercial compilers and exhibits comparable memory use when compared with scalar languages. we also explore the interaction between these transformations and communication optimizations.
jedd: a bdd-based relational extension of java. in this paper we present jedd, a language extension to java that supports a convenient way of programming with binary decision diagrams (bdds). the jedd language abstracts bdds as database-style relations and operations on relations, and provides static type rules to ensure that relational operations are used correctly.the paper provides a description of the jedd language and reports on the design and implementation of the jedd translator and associated runtime system. of particular interest is the approach to assigning attributes from the high-level relations to physical domains in the underlying bdds, which is done by expressing the constraints as a sat problem and using a modern sat solver to compute the solution. further, a runtime system is defined that handles memory management issues and supports a browsable profiling tool for tuning the key bdd operations.the motivation for designing jedd was to support the development of whole program analyses based on bdds, and we have used jedd to express five key interrelated whole program analyses in our soot compiler framework. we provide some examples of this application and discuss our experiences using jedd.
storage assignment to decrease code size. dsp architectures typically provide indirect addressing modes with auto-increment and decrement. in addition, indexing mode is not available, and there are usually few, if any, general-purpose registers. hence, it is necessary to use address registers and perform address arithmetic to access automatic variables. subsuming the address arithmetic into auto-increment and auto-decrement modes improves the size of the generated code.in this paper we present a formulation of the problem of optimal storage assignment such that explicit instructions for address arithmetic are minimized. we prove that for the case of a single address register the decision problem is np-complete. we then generalize the problem to multiple address registers. for both cases heuristic algorithms are given. our experimental results indicate an improvement of 3.
bug isolation via remote program sampling. we propose a low-overhead sampling infrastructure for gathering information from the executions experienced by a program's user community. several example applications illustrate ways to use sampled instrumentation to isolate bugs. assertion-dense code can be transformed to share the cost of assertions among many users. lacking assertions, broad guesses can be made about predicates that predict program errors and a process of elimination used to whittle these down to the true bug. finally, even for non-deterministic bugs such as memory corruption, statistical modeling based on logistic regression allows us to identify program behaviors that are strongly correlated with failure and are therefore likely places to look for the error.
scalable statistical bug isolation. we present a statistical debugging algorithm that isolates bugs in programs containing multiple undiagnosed bugs. earlier statistical algorithms that focus solely on identifying predictors that correlate with program failure perform poorly when there are multiple bugs. our new technique separates the effects of different bugs and identifies predictors that are associated with individual bugs. these predictors reveal both the circumstances under which bugs occur as well as the frequencies of failure modes, making it easier to prioritize debugging efforts. our algorithm is validated using several case studies, including examples in which the algorithm identified previously unknown, significant crashing bugs in widely used systems.
a compiler framework for speculative analysis and optimizations. speculative execution, such as control speculation and data speculation, is an effective way to improve program performance. using edge/path profile information or simple heuristic rules, existing compiler frameworks can adequately incorporate and exploit control speculation. however, very little has been done so far to allow existing compiler frameworks to incorporate and exploit data speculation effectively in various program transformations beyond instruction scheduling. this paper proposes a speculative ssa form to incorporate information from alias profiling and/or heuristic rules for data speculation, thus allowing existing program analysis frameworks to be easily extended to support both control and data speculation. such a general framework is very useful for epic architectures that provide checking (such as advanced load address table (alat) [10]) on data speculation to guarantee the correctness of program execution. we use ssapre [21] as one example to illustrate how to incorporate data speculation in those important compiler optimizations such as partial redundancy elimination (pre), register promotion, strength reduction and linear function test replacement. our extended framework allows both control and data speculation to be performed on top of ssapre and, thus, enables more aggressive speculative optimizations. the proposed framework has been implemented on intel's open research compiler (orc). we present experimental data on some spec2000 benchmark programs to demonstrate the usefulness of this framework and how data speculation benefits partial redundancy elimination.
compiler analysis of irregular memory accesses. irregular array accesses are array accesses whose array subscripts do not have closed-form expressions in terms of loop indices. traditional array analysis and loop transformation techniques cannot handle irregular array accesses. in this paper, we study two kinds of simple and common cases of irregular array accesses: single-indexed access and indirect array access. we present techniques to analyze these two cases at compile-time, and we provide experimental results showing the effectiveness of these techniques in finding more implicit loop parallelism at compile-time and improved speedups.
promises: linguistic support for efficient asynchronous procedure calls in distributed systems. this paper deals with the integration of an efficient asynchronous remote procedure call mechanism into a programming language. it describes a new data type called a promise that was designed to support asynchronous calls. promises allow a caller to run in parallel with a call and to pick up the results of the call, including any exceptions it raises, in a convenient and type-safe manner. the paper also discusses efficient composition of sequences of asynchronous calls to different locations in a network.
parametric regular path queries. regular path queries are a way of declaratively expressing queries on graphs as regular-expression-like patterns that are matched against paths in the graph. there are two kinds of queries: existential queries, which specify properties about individual paths, and universal queries, which specify properties about all paths. they provide a simple and convenient framework for expressing program analyses as queries on graph representations of programs, for expressing verification (model-checking) problems as queries on transition systems, for querying semi-structured data, etc. parametric regular path queries extend the patterns with variables, called parameters, which significantly increase the expressiveness by allowing additional information along single or multiple paths to be captured and relate.this paper shows how a variety of program analysis and model-checking problems can be expressed easily and succinctly using parametric regular path queries. the paper describes the specification, design, analysis, and implementation of algorithms and data structures for efficiently solving existential and universal parametric regular path queries. major contributions include the first complete algorithms and data structures for directly and efficiently solving existential and universal parametric regular path queries, detailed complexity analysis of the algorithms, detailed analytical and experimental performance comparison of variations of the algorithms and data structures, and investigation of efficiency tradeoffs between different formulations of queries.
split-stream dictionary program compression. this paper describes split-stream dictionary (ssd) compression, a new technique for transforming programs into a compact, interpretable form. we define a compressed program as interpretable when it can be decompressed at basic-block granularity with reasonable efficiency. the granularity requirement enables interpreters or just-in-time (jit) translators to decompress basic blocks incrementally during program execution. our previous approach to interpretable compression, the byte-coded risc (brisc) program format [1], achieved unprecedented decompression speed in excess of 5 megabytes per second on a 450mhz pentium ii while compressing benchmark programs to an average of three-fifths the size of their optimized x86 representation. ssd compression combines the key idea behind brisc with new observations about instruction re-use frequencies to yield four advantages over brisc and other competing techniques. first, ssd is simple, requiring only a few pages of code for an effective implementation. second, ssd compresses programs more effectively than any interpretable program compression scheme known to us. for example, ssd compressed a set of programs including the spec95 benchmarks and microsoft word97 to less than half the size, on average, of their optimized x86 representation. third, ssd exceeds brisc's decompression and jit translation rates by over 50%. finally, ssd's two-phased approach to jit translation enables a virtual machine to provide graceful degradation of program execution time in the face of increasing ram constraints. for example, using ssd, we ran word97 using a jit-translation buffer one-third the size of word97's optimized x86 code, yet incurred only 27% execution time overhead.
call-cost directed register allocation. choosing the right kind of register for a live range plays a major role in eliminating the register-allocation overhead when the compiled function is frequently executed or function tails are on the most frequently executed paths. picking the wrong kind of register for a live range incurs a high penalty that may dominate the total overhead of register allocation. in this paper, we present three improvements, storage-class analysis, benefit-driven simplification, and preference decision that are effective in selecting the right kind of register for a live range. then we compare an enhanced chaitin-style register allocator (with these three improvements) with priority-based and optimistic coloring.
pin: building customized program analysis tools with dynamic instrumentation. robust and powerful software instrumentation tools are essential for program analysis tasks such as profiling, performance evaluation, and bug detection. to meet this need, we have developed a new instrumentation system called pin. our goals are to provide easy-to-use, portable, transparent, and efficient instrumentation. instrumentation tools (called pintools) are written in c/c++ using pin's rich api. pin follows the model of atom, allowing the tool writer to analyze an application at the instruction level without the need for detailed knowledge of the underlying instruction set. the api is designed to be architecture independent whenever possible, making pintools source compatible across different architectures. however, a pintool can access architecture-specific details when necessary. instrumentation with pin is mostly transparent as the application and pintool observe the application's original, uninstrumented behavior. pin uses dynamic compilation to instrument executables while they are running. for efficiency, pin uses several techniques, including inlining, register re-allocation, liveness analysis, and instruction scheduling to optimize instrumentation. this fully automated approach delivers significantly better instrumentation performance than similar tools. for example, pin is 3.3x faster than valgrind and 2x faster than dynamorio for basic-block counting. to illustrate pin's versatility, we describe two pintools in daily use to analyze production software. pin is publicly available for linux platforms on four architectures: ia32 (32-bit x86), em64t (64-bit x86), itanium®, and arm. in the ten months since pin 2 was released in july 2004, there have been over 3000 downloads from its website.
jungloid mining: helping to navigate the api jungle. reuse of existing code from class libraries and frameworks is often difficult because apis are complex and the client code required to use the apis can be hard to write. we observed that a common scenario is that the programmer knows what type of object he needs, but does not know how to write the code to get the object.in order to help programmers write api client code more easily, we developed techniques for synthesizing jungloid code fragments automatically given a simple query that describes that desired code in terms of input and output types. a jungloid is simply a unary expression; jungloids are simple, enabling synthesis, but are also versatile, covering many coding problems, and composable, combining to form more complex code fragments. we synthesize jungloids using both api method signatures and jungloids mined from a corpus of sample client programs.we implemented a tool, prospector, based on these techniques. prospector is integrated with the eclipse ide code assistance feature, and it infers queries from context so there is no need for the programmer to write queries. we tested prospector on a set of real programming problems involving apis; prospector found the desired solution for 18 of 20 problems. we also evaluated prospector in a user study, finding that programmers solved programming problems more quickly and with more reuse when using prospector than without prospector.
efficient incremental run-time specialization for free. availability of data in a program determines computation stages. incremental partial evaluation exploit these stages for optimization: it allows further specialization to be performed as data become available at later stages. the fundamental advantage of incremental specialization is to factorize the specialization process. as a result, specializing a program at a given stage costs considerably less than specializing it once all the data are available.we present a realistic and flexible approach to achieve efficient incremental run-time specialization. rather than developing specific techniques, as previously proposed, we are able to re-use existing technology by iterating a specialization process. moreover, in doing so, we do not lose any specialization opportunities. this approach makes it possible to exploit nested quasi-invariants and to speed up the run-time specialization process.this approach has been implemented in tempo, a specializer for c programs that is publicly available. a preliminary experiment confirm that incremental that incremental specialization can greatly speed up the specialization process.
asynchronous exceptions in haskell. asynchronous exceptions, such as timeouts are important for robust, modular programs, but are extremely difficult to program with &mdash; so much so that most programming languages either heavily restrict them or ban them altogether. we extend our earlier work, in which we added synchronous exceptions to haskell, to support asynchronous exceptions too. our design introduces scoped combinators for blocking and unblocking asynchronous interrupts, along with a somewhat surprising semantics for operations that can suspend. uniquely, we also give a formal semantics for our system.
delinearization: an efficient way to break multiloop dependence equations. exact and efficient data dependence testing is a key to success of loop-parallelizing compiler for computationally intensive programs. a number of algorithms has been created to test array references contained in parameter loops for dependence but most of them are unable to answer the following question correctly: are references c(i1 + 10j1) and c(i2 + 5), 0 &le; i1, i2 &le; 4, 0 &le; j1,j2 &le; 9 independent? the technique introduced in this paper recognizes that i1, i2 and j1, j2 make different order contributions to the subscript index, and breaks dependence equation i1 + 10j1 = i2 + 10j2 + 5 into two equations i1 = i2 and 10j1 = 10j2 which then can be solved independently. since resulting equations contain less variables it is less expensive to solve them. we call this technique delinearization because it is reverse of the linearization much discussed in the literature. in the introduction we demonstrate that linearized references are used not infrequently in scientific fortran and c codes. then we present a theorem on which delinearization algorithm is based and the algorithm itself. the algorithm is fairly simple and inexpensive. as a byproduct it tests equations it produces for independence as exactly as it is done by gcd-test and banerjee inequalities combined. the algorithm has been implemented at moscow state university in a vectorizer named vic.
scalable lock-free dynamic memory allocation. dynamic memory allocators (malloc/free) rely on mutual exclusion locks for protecting the consistency of their shared data structures under multithreading. the use of locking has many disadvantages with respect to performance, availability, robustness, and programming flexibility. a lock-free memory allocator guarantees progress regardless of whether some threads are delayed or even killed and regardless of scheduling policies. this paper presents a completely lock-free memory allocator. it uses only widely-available operating system support and hardware atomic instructions. it offers guaranteed availability even under arbitrary thread termination and crash-failure, and it is immune to deadlock regardless of scheduling policies, and hence it can be used even in interrupt handlers and real-time applications without requiring special scheduler support. also, by leveraging some high-level structures from hoard, our allocator is highly scalable, limits space blowup to a constant factor, and is capable of avoiding false sharing. in addition, our allocator allows finer concurrency and much lower latency than hoard. we use powerpc shared memory multiprocessor systems to compare the performance of our allocator with the default aix 5.1 libc malloc, and two widely-used multithread allocators, hoard and ptmalloc. our allocator outperforms the other allocators in virtually all cases and often by substantial margins, under various levels of parallelism and allocation patterns. furthermore, our allocator also offers the lowest contention-free latency among the allocators by significant margins.
a mechanism for efficient debugging of parallel programs. this paper addresses the design and implementation of an integrated debugging system for parallel programs running on shared memory multi-processors (smmp). we describe the use of flowback analysis to provide information on causal relationships between events in a program's execution without re-executing the program for debugging. we introduce a mechanism called incremental tracing that, by using semantic analyses of the debugged program, makes the flowback analysis practical with only a small amount of trace generated during execution. we extend flowback analysis to apply to parallel programs and describe a method to detect race conditions in the interactions of the co-operating processes.
generators and the replicator control structures in the parallel environment of alloy. the need for searching a space of solutions appears often. many problems, such as iteration over a dynamically created domain, can be expressed most naturally using a generate-and-process style. serial programming languages typically support solutions of these problems by providing some form of generators or backtracking. a parallel programming language is more demanding since it needs to be able to express parallel generation and processing of elements. failure driven computation is no longer sufficient and neither is multiple-assignment to generated values. we describe the replicator control operator used in the high level parallel programming language alloy. the replicator control operator provides a new view of generators which deals with these problems.
the pointer assertion logic engine. we present a new framework for verifying partial specifications of programs in order to catch type and memory errors and check data structure invariants. our technique can verify a large class of data structures, namely all those that can be expressed as graph types. earlier versions were restricted to simple special cases such as lists or trees. even so, our current implementation is as fast as the previous specialized tools. programs are annotated with partial specifications expressed in pointer assertion logic, a new notation for expressing properties of the program store. we work in the logical tradition by encoding the programs and partial specifications as formulas in monadic second-order logic. validity of these formulas is checked by the mona tool, which also can provide explicit counterexamples to invalid formulas. to make verification decidable, the technique requires explicit loop and function call invariants. in return, the technique is highly modular: every statement of a given program is analyzed only once. the main target applications are safety-critical data-type algorithms, where the cost of annotating a program with invariants is justified by the value of being able to automatically verify complex properties of the program.
principled scavenging. proof-carrying code and typed assembly languages aim to minimize the trusted computing base by directly certifying the actual machine code. unfortunately, these systems cannot get rid of the dependency on a trusted garbage collector. indeed, constructing a provably type-safe garbage collector is one of the major open problems in the area of certifying compilation. building on an idea by wang and appel, we present a series of new techniques for writing type-safe stop-and-copy garbage collectors. we show how to use intensional type analysis to capture the contract between the mutator and the collector, and how the same method can be applied to support forwarding pointers and generations. unlike wang and appel (which requires whole-program analysis), our new framework directly supports higher-order funtions and is compatible with separate compilation; our collectors are written in provably type-safe languages with rigorous semantics and fully formalized soundness proofs.
managing stack frames in smalltalk. the smalltalk programming language allows contexts (stack frames) to be accessed and manipulated in very general ways. this sometimes requires that contexts be retained even after they have terminated executing, and that they be reclaimed other than by lifo stack discipline. the authoritative definition of smalltalk [goldberg and robson 83] uses reference counting garbage collection to manage contexts, an approach found to be inadequate in practice [krasner, et al. 83]. deutsch and schiffman have described a technique that uses an actual stack as much as possible [deutsch and schiffman 84]. here we offer a less complex technique that we expect will have lower total overhead and reclaim many frames sooner and more easily. we are implementing our technique as part of a state of the art smalltalk interpreter. the approach may apply to other languages that allow indefinite lifetimes for execution contexts, be they interpreted or compiled.
avoiding unconditional jumps by code replication. this study evaluates a global optimization technique that avoids unconditional jumps by replicating code. when implemented in the back-end of an optimizing compiler, this technique can be generalized to work on almost all instances of unconditional jumps, including those generated from conditional statements and unstructured loops. the replication method is based on the idea of finding a replacement for each unconditional jump which minimizes the growth in code size. this is achieved by choosing the shortest sequence of instructions as a replacement. measurements taken from a variety of programs showed that not only the number of executed instructions decreased, but also that the total cache work was reduced (except for small caches) despite increases in code size. pipelined and superscalar machines may also benefit from an increase in the average basic block size.
effective static race detection for java. we present a novel technique for static race detection in java programs, comprised of a series of stages that employ a combination of static analyses to successively reduce the pairs of memory accesses potentially involved in a race. we have implemented our technique and applied it to a suite of multi-threaded java programs. our experiments show that it is precise, scalable, and useful, reporting tens to hundreds of serious and previously unknown concurrency bugs in large, widely-used programs with few false alarms.
profile-based global live-range splitting. live-range splitting is a technique to split the live range of a given variable into multiple subranges, each of which can be assigned to a different register or spilled out to memory in order to improve results of coloring register allocation. previous techniques, such as aggressive live-range splitting, tend to produce extra spill code in the frequently executed (called hot) regions of the code, since they don't distinguish hot regions from others. we propose a new live-range splitting algorithm, which can reduce the amount of spill code in hot regions by coalescing the live ranges based on profile information after splitting the live ranges at every join and fork point in the control-flow graph. our experimental results have shown that our new algorithm improved the performance of specjvm98 by up to 33% over aggressive live-range splitting and 7% over the base coloring algorithm without any live-range splitting.
practical dynamic software updating for c. software updates typically require stopping and restarting an application, but many systems cannot afford to halt service, or would prefer not to. dynamic software updating (dsu) addresses this difficulty by permitting programs to be updated while they run. dsu is appealing compared to other approaches for on-line upgrades because it is quite general and requires no redundant hardware. the challenge is in making dsu practical: it should be flexible, and yet safe, efficient, and easy to use.in this paper, we present ginseng, a dsu implementation for c that aims to meet this challenge. we compile programs specially so that they can be dynamically patched, and generate most of a dynamic patch automatically. ginseng performs a series of analyses that when combined with some simple runtime support ensure that an update will not violate type-safety while guaranteeing that data is kept up-to-date. we have used ginseng to construct and dynamically apply patches to three substantial open-source server programs---very secure ftp daemon, openssh sshd daemon, and gnu zebra. in total, we dynamically patched each program with three years' worth of releases. though the programs changed substantially, the majority of updates were easy to generate. performance experiments show that all patches could be applied in less than 5 ms, and that the overhead on application throughput due to updating support ranged from 0 to at most 32%.
translation validation for an optimizing compiler. we describe a translation validation infrastructure for the gnu c compiler. during the compilation the infrastructure compares the intermediate form of the program before and after each compiler pass and verifies the preservation of semantics. we discuss a general framework that the optimizer can use to communicate to the validator what transformations were performed. our implementation however does not rely on help from the optimizer and it is quite successful by using instead a few heuristics to detect the transformations that take place. the main message of this paper is that a practical translation validation infrastructure, able to check the correctness of many of the transformations performed by a realistic compiler, can be implemented with about the effort typically required to implement one compiler pass. we demonstrate this in the context of the gnu c compiler for a number of its optimizations while compiling realistic programs such as the compiler itself or the linux kernel. we believe that the price of such an infrastructure is small considering the qualitative increase in the ability to isolate compilation errors during compiler testing and maintenance.
the design and implementation of a certifying compiler. this paper presents the design and implementation of a compiler that translates programs written in a type-safe subset of the c programming language into highly optimized dec alpha assembly language programs, and a certifier that automatically checks the type safety and memory safety of any assembly language program produced by the compiler. the result of the certifier is either a formal proof of type safety or a counterexample pointing to a potential violation of the type system by the target program. the ensemble of the compiler and the certifier is called a certifying compiler.several advantages of certifying compilation over previous approaches can be claimed. the notion of a certifying compiler is significantly easier to employ than a formal compiler verification, in part because it is generally easier to verify the correctness of the result of a computation than to prove the correctness of the computation itself. also, the approach can be applied even to highly optimizing compilers, as demonstrated by the fact that our compiler generates target code, for a range of realistic c programs, which is competitive with both the cc and gcc compilers with all optimizations enabled. the certifier also drastically improves the effectiveness of compiler testing because, for each test case, it statically signals compilation errors that might otherwise require many executions to detect. finally, this approach is a practical way to produce the safety proofs for a proof-carrying code system, and thus may be useful in a system for safe mobile code.
real-time replication garbage collection. we have implemented the first copying garbage collector that permits continuous unimpeded mutator access to the original objects during copying. the garbage collector incrementally replicates all accessible objects and uses a mutation log to bring the replicas up-to-date with changes made by the mutator. an experimental implementation demonstrates that the costs of using our algorithm are small and that bounded pause times of 50 milliseconds can be readily achieved.
optimal tracing and incremental reexecution for debugging long-running programs. debugging requires execution replay. locations of bugs are rarely known in advance, so an execution must be repeated over and over to track down bugs. a problem arises with repeated reexecution for long-running programs and programs that have complex interactions with their environment. replaying long-running programs from the start incurs too much delay. replaying programs that interact with their environment requires the difficult (and sometimes impossible) task of exactly reproducing this environment (such as the connections over a one-day period to an x server). we solve these problems by incremental checkpointing and replay. by periodically checkpointing parts of the execution''s state, it can be restarted from intermediate points, bounding the delay to replay any part of the execution and allowing parts of the execution to be skipped. we present adaptive tracing strategies that provide bounded-time incremental replay and that are nearly optimal. our techniques track reads and writes to memory using space-efficient two-level bitvectors. our implementation on a sparc 10 traces less than 15 kilobytes/sec for cpu-intensive programs and for interactive programs the slowdown is low enough that tracing can be left on all the time.
programming ad-hoc networks of mobile and resource-constrained devices. ad-hoc networks of mobile devices such as smart phones and pdas represent a new and exciting distributed system architecture. building distributed applications on such an architecture poses new design challenges in programming models, languages, compilers, and runtime systems. this paper discusses spatialviews, a high-level language designed for programming mobile devices connected through a wireless ad-hoc network. spatialviews allows specification of virtual networks with nodes providing desired services and residing in interesting spaces. these nodes are discovered dynamically with user-specified time constraints and quality of result (qor). the programming model supports "best-effort" semantics, i.e., different executions of the same program may result in "correct" answers of different quality. it is the responsibility of the compiler and runtime system to produce a high-quality answer for the particular network and resource conditions encountered during program execution. four applications, which exercise different features of the spatialviews language, are presented to demonstrate the expressiveness of the language and the efficiency of the compiler generated code. the applications are an application that collects and aggregates sensor data in network, an application that performs dynamic service installation, a mobile camera application that supports computation offloading for image understanding, and an augmented-reality (ar) pacman game. the efficiency of the compiler generated code is verified through simulation and physical measurements. the reported results show that spatialviews is an expressive and effective language for ad-hoc networks. in addition, compiler optimizations can significantly improve response times and energy consumption.
graph coloring register allocation for processors with multi-register operands. though graph coloring algorithms have been shown to work well when applied to register allocation problems, the technique has not been generalized for processor architectures in which some instructions refer to individual operands that are comprised of multiple registers. this paper presents a suitable generalization.
register allocation over the program dependence graph. this paper describes rap, a register allocator that allocates registers over the program dependence graph (pdg) representation of a program in a hierarchical manner. the pdg program representation has been used successfully for scalar optimizations, the detection and improvement of parallelism for vector machines, multiple processor machines, and machines that exhibit instruction level parallelism, as well as debugging, the integration of different versions of a program, and translation of imperative programs for data flow machines. by basing register allocation on the pdg, the register allocation phase may be more easily integrated and intertwined with other optimization analyses and transformations. in addition, the advantages of a hierarchical approach to global register allocation can be attained without constructing an additional structure used solely for register allocation. our experimental results have shown that on average, code allocated registers via rap executed 2.7% faster than code allocated registers via a standard global register allocator.
enhancement through extension: the extension interpreter. the ability to extend programs dynamically has clear advantages. however, providing efficient yet sufficiently flexible support for such capabilities system-wide presents significant challenges. we describe a design and implementation of an extension mechanism that depends heavily on interpretive techniques, including call arbitration, dynamic linking, and multilanguage extensions. we discuss these mechanisms in the context of our extension interpreter, which embodies our ideas and provides a framework for discussing the efficiency and generality of the implementation. our current implementation runs under bsd unix 4.2 and 4.3 on vaxes and sun workstations. extensions can be written in both c and in icon, demonstrating our ability to address problems both of compiled and interpreted languages.
auto-vectorization of interleaved data for simd. most implementations of the single instruction multiple data (simd) model available today require that data elements be packed in vector registers. operations on disjoint vector elements are not supported directly and require explicit data reorganization manipulations. computations on non-contiguous and especially interleaved data appear in important applications, which can greatly benefit from simd instructions once the data is reorganized properly. vectorizing such computations efficiently is therefore an ambitious challenge for both programmers and vectorizing compilers. we demonstrate an automatic compilation scheme that supports effective vectorization in the presence of interleaved data with constant strides that are powers of 2, facilitating data reorganization. we demonstrate how our vectorization scheme applies to dominant simd architectures, and present experimental results on a wide range of key kernels, showing speedups in execution time up to 3.7 for interleaving levels (stride) as high as 8.
a recursive interpreter for the icon programming language. the implementation of the icon programming language is more interesting and difficult than the implementation of many other programming languages because an expression in icon can generate a sequence of results. the implementation therefore must support control backtracking in expression evaluation. there also are several novel control structures related to generators. because expression evaluation is limited lexically, a full coroutine mechanism is not needed and expression evaluation can be handled in a stack-like fashion.the implementation of icon consists of a virtual machine with a stack-based architecture and an interpreter that executes the virtual machine instructions. there have been several different interpreters for icon's virtual machine. this paper describes a new approach in which the interpreter is called recursively whenever the context for expression evaluation changes. this recursive interpreter has the advantage of being conceptually clear and flexible without sacrificing efficiency.
the design and implementation of home. home is a version of smalltalk which can be efficiently executed on a multiprocessor and can be executed in parallel by combining a smalltalk process with a mach thread and executing the process on the thread. home is nearly the same as ordinary smalltalk except that multiple processes may execute in parallel. thus, almost all applications running on ordinary smalltalk can be executed on home without changes in their code. home was designed and implemented based on the following fundamental policies: (1) theoretically, an infinite number of processes can become active; (2) the moment a process is scheduled, it becomes active; (3) no process switching occurs; (4) home is equivalent to ordinary smalltalk except for the previous three policies. the performance of the current implementation of home running on omron luna-88k, which had four processors, was measured by benchmarks which execute in parallel with multiple processes. in all benchmarks, the results showed that home's performance is much better than hps on the same workstation.
a parallel, incremental and concurrent gc for servers. multithreaded applications with multi-gigabyte heaps running on modern servers provide new challenges for garbage collection (gc). the challenges for "server-oriented" gc include: ensuring short pause times on a multi-gigabyte heap, while minimizing throughput penalty, good scaling on multiprocessor hardware, and keeping the number of expensive multi-cycle fence instructions required by weak ordering to a minimum. we designed and implemented a fully parallel, incremental, mostly concurrent collector, which employs several novel techniques to meet these challenges. first, it combines incremental gc to ensure short pause times with concurrent low-priority background gc threads to take advantage of processor idle time. second, it employs a low-overhead work packet mechanism to enable full parallelism among the incremental and concurrent collecting threads and ensure load balancing. third, it reduces memory fence instructions by using batching techniques: one fence for each block of small objects allocated, one fence for each group of objects marked, and no fence at all in the write barrier. when compared to the mature well-optimized parallel stop-the-world mark-sweep collector already in the ibm jvm, our collector prototype reduces the maximum pause time from 284 ms to 101 ms, and the average pause time from 266 ms to 66 ms while only losing 10% throughput when running the specjbb2000 benchmark on a 256 mb heap on a 4-way 550 mhz pentium multiprocessor.
simplification of array access patterns for compiler optimizations. existing array region representation techniques are sensitive to the complexity of array subscripts. in general, these techniques are very accurate and efficient for simple subscript expressions, but lose accuracy or require potentially expensive algorithms for complex subscripts. we found that in scientific applications, many access patterns are simple even when the subscript expressions are complex. in this work, we present a new, general array access representation and define operations for it. this allows us to aggregate and simplify the representation enough that precise region operations may be applied to enable compiler optimizations. our experiments show that these techniques hold promise for speeding up applications.
multiprocessor smalltalk: a case study of a multiprocessor-based programming environment. we have adapted an interactive programming system (smalltalk) to a multiprocessor (the firefly). the task was not as difficult as might be expected, thanks to the application of three basic strategies: serialization, replication, and reorganization. serialization of access to resources disallows concurrent access. replication provides multiple instances of resources when they cannot or should not be serialized. reorganization allows us to restructure part of the system when the other two strategies cannot be applied. we serialized i/o, memory allocation, garbage collection, and scheduling, we replicated the interpreter process, software caches, and a free-list, and we reorganized portions of the scheduling system to deal with some deep-seated assumptions. our changes yielded a fairly low static overhead. we attribute our success to the choice of a small, flexible operating system, a set of constraints which simplified the problem, and the versality of the three strategies for dealing with concurrency. the current system has a moderate amount of overhead when parallelism is being used&mdash;25% to 65%. it is acceptable, but we believe it can be improved.
escape analysis on lists. higher order functional programs constantly allocate objects dynamically. these objects are typically cons cells, closures, and records and are generally allocated in the heap and reclaimed later by some garbage collection process. this paper describes a compile time analysis, called escape analysis, for determining the lifetime of dynamically created objects in higher order functional programs, and describes optimizations that can be performed, based on the analysis, to improve storage allocation and reclamation of such objects. in particular, our analysis can be applied to programs manipulating lists, in which case optimizations can be performed to allow cons cells in spines of lists to be either reclaimed immediately or reused without incurring any garbage collection overhead. in a previous paper on escape analysis [10], we had left open the problem of performing escape analysis on lists. escape analysis simply determines when the argument (or some part of the argument) to a function call is returned by that call. this simple piece of information turns out to be sufficiently powerful to allow stack allocation of objects, compile-time garbage collection, reduction of run-time storage reclamation overhead, and other optimizations that are possible when the lifetimes of objects can be computed statically. our approach is to define a high-level non-standard semantics that, in many ways, is similar to the standard semantics and captures the escape behavior caused by the constructs in a functional language. the advantage of our analysis lies in its conceptual simplicity and portability (i.e. no assumption is made about an underlying abstract machine).
accurate static branch prediction by value range propagation. the ability to predict at compile time the likelihood of a particular branch being taken provides valuable information for several optimizations, including global instruction scheduling, code layout, function inlining, interprocedural register allocation and many high level optimizations. previous attempts at static branch prediction have either used simple heuristics, which can be quite inaccurate, or put the burden onto the programmer by using execution profiling data or source code hints.this paper presents a new approach to static branch prediction called value range propagation. this method tracks the weighted value ranges of variables through a program, much like constant propagation. these value ranges may be either numeric of symbolic in nature. branch prediction is then performed by simply consulting the value range of the appropriate variable. heuristics are used as a fallback for cases where the value range of the variable cannot be determined statically. in the process, value range propagationsubsumes both constant propagation and copy propagation.experimental results indicate that this approach produces significantly more accurate predictions than the best existing heuristic techniques. the value range propagation method can be implemented over any &ldquo;factored&rdquo; dataflow representation with a static single assignment property (such as ssa form or a dependence flow graph where the variables have been renamed to achieve single assignment). experimental results indicate that the technique maintains the linear runtime behavior of constant propagation experienced in practice.
implementing type classes. we describe the implementation of a type checker for the functional programming language haskell that supports the use of type classes. this extends the type system of ml to support overloading (ad-hoc polymorphism) and can be used to implement features such as equality types and numeric overloading in a simple and general way. the theory of type classes is well understood, but the practical issues involved in the implementation of such systems have not received a great deal of attention. in addition to the basic type checking algorithm, an implmenentation of type classes also requires some form of program transformation. in all current haskell compilers this takes the form of dictionary conversion, using functions as hidden parameters to overloaded values. we present efficient techniques for type checking and dictionary conversion. a number of optimizations and extensions to the basic type class sytems are also described.
profile guided code positioning. this paper presents the results of our investigation of code positioning techniques using execution profile data as input into the compilation process. the primary objective of the positioning is to reduce the overhead of the instruction memory hierarchy. after initial investigation in the literature, we decided to implement two prototypes for the hewlett-packard precision architecture (pa-risc). the first, built on top of the linker, positions code based on whole procedures. this prototype has the ability to move procedures into an order that is determined by a &ldquo;closest is best&rdquo; strategy. the second prototype, built on top of an existing optimizer package, positions code based on basic blocks within procedures. groups of basic blocks that would be better as straight-line sequences are identified as chains. these chains are then ordered according to branch heuristics. code that is never executed during the data collection runs can be physically separated from the primary code of a procedure by a technique we devised called procedure splitting. the algorithms we implemented are described through examples in this paper. the performance improvements from our work are also summarized in various tables and charts.
higher-order abstract syntax. we describe motivation, design, use, and implementation of higher-order abstract syntax as a central representation for programs, formulas, rules, and other syntactic objects in program manipulation and other formal systems where matching and substitution or unification are central operations. higher-order abstract syntax incorporates name binding information in a uniform and language generic way. thus it acts as a powerful link integrating diverse tools in such formal environments. we have implemented higher-order abstract syntax, a supporting matching and unification algorithm, and some clients in common lisp in the framework of the ergo project at carnegie mellon university.
apt: a data structure for optimal control dependence computation. the control dependence relation is used extensively in restructuring compilers. this relation is usually represented using the control dependence graph; unfortunately, the size of this data structure can be quadratic in the size of the program, even for some structured programs. in this paper, we introduce a data structure called the augmented post-dominator tree (apt) which is constructed in space and time proportional to the size of the program, and which can answer control dependence queries in time proportional to the size of the output. therefore, apt is an optimal representation of control dependence. we also show that using apt, we can compute ssa graphs, as well as sparse dataflow evaluator graphs, in time proportional to the size of the program. finally, we put apt in perspective by showing that it can be viewed as a factored representation of control dependence graph in which filtered search is used to answer queries.
two-level hybrid interpreter/native code execution for combined space-time program efficiency. a two-level programming model permits the applications programmer to write programs that benefit both from the code density of interpreted virtual machines and from the speed of native code execution. a well-defined boundary between the native code and the virtual machine facilitates the development of translators to be used at both levels.
optimizing direct-threaded code by selective inlining. achieving good performance in bytecoded language interpreters is difficult without sacrificing both simplicity and portability. this is due to the complexity of dynamic translation ("just-in-time compilation") of bytecodes into native code, which is the mechanism employed universally by high-performance interpreters.we demonstrate that a few simple techniques make it possible to create highly-portable dynamic translators that can attain as much as 70% the performance of optimized c for certain numerical computations. translators based on such techniques can offer respectable performance without sacrificing either the simplicity or portability of much slower "pure" bytecode interpreters.
tcc: a system for fast, flexible, and high-level dynamic code generation. tcc is a compiler that provides efficient and high-level access to dynamic code generation. it implements the 'c ("tick-c") programming language, an extension of ansi c that supports dynamic code generation [15]. 'c gives power and flexibility in specifying dynamically generated code: whereas most other systems use annotations to denote run-time invariants. 'c allows the programmer to specify and compose arbitrary expressions and statements at run time. this degree of control is needed to efficiently implement some of the most important applications of dynamic code generation, such as "just in time" compilers [17] and efficient simulators [10, 48, 46].the paper focuses on the techniques that allow tcc to provide 'c's flexibility and expressiveness without sacrificing run-time code generation efficiency. these techniques include fast register allocation, efficient creation and composition of dynamic code specifications, and link-time analysis to reduce the size of dynamic code generators. tcc also implements two different dynamic code generation strategies, designed to address the tradeoff of dynamic compilation speed versus generated code quality. to characterize the effects of dynamic compilation, we present performance measurements for eleven programs compiled using tcc. on these applications, we measured performance improvements of up to one order of magnitude.to encourage further experimentation and use of dynamic code generation, we are making the tcc compiler available in the public domain. this is, to our knowledge, the first high-level dynamic compilation system to be made available.
locksmith: context-sensitive correlation analysis for race detection. one common technique for preventing data races in multi-threaded programs is to ensure that all accesses to shared locations are consistently protected by a lock. we present a tool called locksmith for detecting data races in c programs by looking for violations of this pattern. we call the relationship between locks and the locations they protect consistent correlation, and the core of our technique is a novel constraint-based analysis that infers consistent correlation context-sensitively, using the results to check that locations are properly guarded by locks. we present the core of our algorithm for a simple formal language λ> which we have proven sound, and discuss how we scale it up to an algorithm that aims to be sound for all of c. we develop several techniques to improve the precision and performance of the analysis, including a sharing analysis for inferring thread locality; existential quantification for modeling locks in data structures; and heuristics for modeling unsafe features of c such as type casts. when applied to several benchmarks, including multi-threaded servers and linux device drivers, locksmith found several races while producing a modest number of false alarm.
static conflict analysis for multi-threaded object-oriented programs. a compiler for multi-threaded object-oriented programs needs information about the sharing of objects for a variety of reasons: to implement optimizations, to issue warnings, to add instrumentation to detect access violations that occur at runtime. an object use graph (oug) statically captures accesses from different threads to objects. an oug extends the heap shape graph (hsg), which is a compile-time abstraction for runtime objects (nodes) and their reference relations (edges). an oug specifies for a specific node in the hsg a partial order of events relevant to the corresponding runtime object(s). relevant events include read and write access, object escape, thread start and join.ougs have been implemented in a java compiler. initial experience shows that ougs are effective to identify object accesses that potentially conflict at runtime and isolate accesses that never cause a problem at runtime. the capabilities of ougs are compared with an advanced program analysis that has been used for lock elimination. for the set of benchmarks investigated here, ougs report only a fraction of shared objects as conflicting and reduce the number of compile-time reports in terms of allocation sites of conflicting objects by 28--92% (average 64%). for benchmarks of up to 30 kloc, the time taken to construct ougs is, with one exception, in the order of seconds.the information collected in the oug has been used to instrument java programs with checks for object races. ougs provide precise information about object sharing and static protection, so runtime instrumentation that checks those cases that cannot be disambiguated at compile-time is sparse, and the total runtime overhead of checking for object races is only 3--86% (average 47%).
simple and efficient burs table generation. a simple and efficient algorithm for generating bottom-up rewrite system (burs) tables is described. a small prototype implementation produces tables 10 to 30 times more quickly than the best current techniques. the algorithm does not require novel data structures or complicated algorithmic techniques. previously published methods for the on-the-fly elimination of states are generalized and simplified to create a new method, triangle trimming, that is employed in the algorithm.
simple translation of goal-directed evaluation. this paper presents a simple, powerful and flexible technique for reasoning about and translating the goal-directed evaluation of programming language constructs that either succeed (and generate sequences of values) or fail. the technique generalizes the byrd box, a well-known device for describing prolog backtracking.
probalistic register allocation. a new global register allocation technique, probabilistic register allocation, is described. probabilistic register allocation quantifies the costs and benefits of allocating variables to registers over live ranges so that excellent allocation choices can be made. local allocation is done first, and then global allocation is done iteratively beginning in the most deeply nested loops. because local allocation precedes global allocation, probabilistic allocation does not interfere with the use of well-known, high-quality local register allocation and instruction scheduling techniques.
counting solutions to presburger formulas: how and why. we describe methods that are able to count the number of integer solutions to selected free variables of a presburger formula, or sum a polynomial over all integer solutions of selected free variables of a presburger formula. this answer is given symbolically, in terms of symbolic constants (the remaining free variables in the presburger formula). for example, we can create a presburger formula who's solutions correspond to the iterations of a loop. by counting these, we obtain an estimate of the execution time of the loop. in more complicated applications, we can create presburger formulas who's solutions correspond to the distinct memory locations or cache lines touched by a loop, the flops executed by a loop, or the array elements that need to be communicated at a particular point in a distributed computation. by counting the number of solutions, we can evaluate the computation/memory balance of a computation, determine if a loop is load balanced and evaluate message traffic and allocate message buffers.
compressing java class files. java class files are often distributed as jar files, which are collections of individually compressed class files (and possibility other files). jar files are typically about 1/2 the size of the original class files due to compression. i have developed a wire-code format for collections of java class files. this format is typically 1/2 to 1/5 of the size of the corresponding compressed jar file (1/4 to 1/10 the size of the original class files).
two-directional record layout for multiple inheritance. much recent work in polymorphic programming languages allows subtyping and multiple inheritance for records. in such systems, we would like to extract a field from a record with the same efficiency as if we were not making use of subtyping and multiple inheritance. methods currently used make field extraction 3-5 times slower, which can produce a significant overall performance slowdown. we describe a record layout algorithm that allows us to assign a fixed offset to each field name. this allows field extraction to done just as quickly as in systems that do not provide multiple inheritance. assigning fixed offsets may require us to leave gaps in some records (and waste space). however, by placing fields at both positive and negative offsets we can drastically reduce the amount of wasted space. finding an optimal layout is np-hard, so we propose and analyze heuristic algorithms for producing good two-direction record layouts. in a trial run, our algorithm produced a fixed layout for the instance variables of the 563 flavors of a lisp flavors system; this fixed layout only wastes 6% of the total space consumed by a collection of one instance of each flavor.
eliminating false data dependences using the omega test. array data dependence analysis methods currently in use generate false dependences that can prevent useful program transformations. these false dependences arise because the questions asked are conservative approximations to the questions we really should be asking. unfortunately, the questions we really should be asking go beyond integer programming and require decision procedures for a sublcass of presburger formulas. in this paper, we describe how to extend the omega test so that it can answer these queries and allow us to eliminate these false data dependences. we have implemented the techniques described here and believe they are suitable for use in production compilers.
kiss: keep it simple and sequential. the design of concurrent programs is error-prone due to the interaction between concurrently executing threads. traditional automated techniques for finding errors in concurrent programs, such as model checking, explore all possible thread interleavings. since the number of thread interleavings increases exponentially with the number of threads, such analyses have high computational complexity. in this paper, we present a novel analysis technique for concurrent programs that avoids this exponential complexity. our analysis transforms a concurrent program into a sequential program that simulates the execution of a large subset of the behaviors of the concurrent program. the sequential program is then analyzed by a tool that only needs to understand the semantics of sequential execution. our technique never reports false errors but may miss errors. we have implemented the technique in kiss, an automated checker for multithreaded c programs, and obtained promising initial results by using kiss to detect race conditions in windows device drivers.
mitosis compiler: an infrastructure for speculative threading based on pre-computation slices. speculative parallelization can provide significant sources of additional thread-level parallelism, especially for irregular applications that are hard to parallelize by conventional approaches. in this paper, we present the mitosis compiler, which partitions applications into speculative threads, with special emphasis on applications for which conventional parallelizing approaches fail.the management of inter-thread data dependences is crucial for the performance of the system. the mitosis framework uses a pure software approach to predict/compute the thread's input values. this software approach is based on the use of pre-computation slices (p-slices), which are built by the mitosis compiler and added at the beginning of the speculative thread. p-slices must compute thread input values accurately but they do not need to guarantee correctness, since the underlying architecture can detect and recover from misspeculations. this allows the compiler to use aggressive/unsafe optimizations to significantly reduce their overhead. the most important optimizations included in the mitosis compiler and presented in this paper are branch pruning, memory and register dependence speculation, and early thread squashing.performance evaluation of mitosis compiler/architecture shows an average speedup of 2.2.
profile-directed optimization of event-based programs. events are used as a fundamental abstraction in programs ranging from graphical user interfaces (guis) to systems for building customized network protocols. while providing a flexible structuring and execution paradigm, events have the potentially serious drawback of extra execution overhead due to the indirection between modules that raise events and those that handle them. this paper describes an approach to addressing this issue using static optimization techniques. this approach, which exploits the underlying predictability often exhibited by event-based programs, is based on first profiling the program to identify commonly occurring event sequences. a variety of techniques that use the resulting profile information are then applied to the program to reduce the overheads associated with such mechanisms as indirect function calls and argument marshaling. in addition to describing the overall approach, experimental results are given that demonstrate the effectiveness of the techniques. these results are from event-based programs written for x windows, a system for building guis, and cactus, a system for constructing highly configurable distributed services and network protocols.
data flow frequency analysis. conventional dataflow analysis computes information about what facts may or will not hold during the execution of a program. sometimes it is useful, for program optimization, to know how often or with what probability a fact holds true during program execution. in this paper, we provide a precise formulation of this problem for a large class of dataflow problems --- the class of finite bi-distributive subset problems. we show how it can be reduced to a generalization of the standard dataflow analysis problem, one that requires a sum-over-all-paths quantity instead of the usual meet-overall-paths quantity. we show that kildall's result expressing the meet-over-all-paths value as a maximal-fixed-point carries over to the generalized setting. we then outline ways to adapt the standard dataflow analysis algorithms to solve this generalized problem, both in the intraprocedural and the interprocedural case.
a member lookup algorithm for c++. the member lookup problem in c++ is the problem of resolving a specified member name in the context of a specified class. member lookup in c++ is complicated by the presence of virtual inheritance and multiple inheritance. in this paper, we present an efficient algorithm for member lookup in c++. we also present a formalism for the multiple inheritance mechanism of c++, which we use as the basis for deriving our algorithm. the formalism may also be of use as a formal basis for deriving other c++ compiler algorithms.
relocating machine instructions by currying. relocation adjusts machine instructions to account for changes in the locations of the instructions themselves or of external symbols to which they refer. standard linkers implement a finite set of relocation transformations, suitable for a single architecture. these transformations are enumerated, named, and engraved in a machine-dependent object-file format, and linkers must recognize them by name. these names and their associated transformations are an unnecessary source of machine-dependence.the new jersey machine-code toolkit is an application generator. it helps programmers create applications that manipulate machine code, including linkers. guided by a short instruction-set specification, the toolkit generates the bit-manipulating code. instructions are described by constructors, which denote functions mapping lists of operands to instructions' binary representations. any operand can be designated as "relocatable," meaning that the operand's value need not be known at the time the instruction is encoded. for instructions with relocatable operands, the toolkit computes relocating transformations. tool writers can use the toolkit to create machine-independent software that relocates machine instructions. mld, a retargetable linker built with the toolkit, needs only 20 lines of c code for relocation, and that code is machine-independent.the toolkit discovers relocating transformations by currying encoding functions. an attempt to encode an instruction with a relocatable operand results in the creation of a closure. the closure can be applied when the values of the relocatable operands become known. currying provides a general, machine-independent method of relocation.currying rewrites a &lambda;-term into two nested &lambda;-terms. the standard implementation has the first &lambda; allocate a closure and store therein its operands and a pointer to the second &lambda;. using this strategy in the toolkit means that, when it builds an application, the toolkit generates code for many different inner &lambda;-terms---one for each instruction that uses a relocatable address. hoisting some of the computation out of the second &lambda; into the first makes many of the second &lambda;s identical---a handful are enough for a whole instruction set. this optimization reduces the size of machine-dependent assembly and linking code by 15--20% for the mips, sparc, and powerpc, and by about 30% for the pentium. it also makes the second &lambda;s equivalent to relocating transformations named in standard object-file formats.
a retargetable debugger. we are developing techniques for building retargetable debuggers. our prototype, 1db, debugs c programs compiled for the mips r3000, motorola 68020, sparc, and vax architectures. it can use a network to connect to faulty processes and can do cross-architecture debugging. 1db's total code size is about 16,000 lines, but it needs only 250&ndash;550 lines of machine-dependent code for each target. 1db owes its retargetability to three techniques: getting help from the compiler, using a machine-independent embedded interpreter, and choosing abstractions that minimize and isolate machine-dependent code. 1db reuses existing compiler function by having the compiler emit postscript code that 1db later interprets; postscript works well in this unusual context.
a single intermediate language that supports multiple implementations of exceptions. we present mechanisms that enable our compiler-target language, c--, to express four of the best known techniques for implementing exceptions, all within a single, uniform framework. we define the mechanisms precisely, using a formal operational semantics. we also show that exceptions need not require special treatment in the optimizer; by introducing extra dataflow edges, we make standard optimization techniques work even on programs that use exceptions. our approach clarifies the design space of exception-handling techniques, and it allows a single optimizer to handle a variety of implementation techniques. our ultimate goal is to allow a source-language compiler the freedom to choose its exception-handling policy, while encapsulating the architecture-dependent mechanisms and their optimization in an implementation of c--that can be used by compilers for many source languages.
storage assignment optimizations to generate compact and efficient code on embedded dsps. dsp architectures typically provide dedicated memory address generation units and indirect addressing modes with auto-increment and auto-decrement that subsume address arithmetic calculation. the heavy use of auto-increment and auto-decrement indirect addressing require dsp compilers to perform a careful placement of variables in storage to minimize address arithmetic instructions to generate compact and efficient dsp code. liao et al. formulated the problem of storage assignment as the simple offset assignment problem (soa) and the general offset assignment problem (goa), and proposed heuristic solutions.the storage allocation of variables critically depends on the sequence of variable accesses. in this paper we present techniques to optimize the access sequence of variables by applying algebraic transformations (such as commutativity and associativity) on expression trees to obtain the least cost offset assignment. we develop a new formulation of this problem as the least cost access sequence problem (lcas). based on the proposed framework, we develop heuristic algorithms that determine empirically near-optimal solutions resulting in fewer address arithmetic instructions. we have implemented the proposed heuristic algorithms by extending the storage assignment optimization in the spam compiler back-end targeted for the tms320c25 dsp. in the case of soa, experimental results for programs from the dspstone benchmark suite show an average improvement of 3.36% in static code size and an average relative speed-up of 7.28% over results obtained using existing soa algorithms. the average code size reduction over code compiled with a naive storage assignment algorithm is 7.04%. the proposed framework has also been applied to the goa problem and shows average code size reductions of 2.04% over results obtained using existing goa algorithms, and average code size reductions of 10.84% over a naive goa algorithm. code size reduction and improvement in dynamic instruction counts could be valuable given limited memory and real-time response requirements placed on embedded systems.
register allocation for software pipelined loops. software pipelining is an important instruction scheduling technique for efficiently overlapping successive iterations of loops and executing them in parallel. this paper studies the task of register allocation for software pipelined loops, both with and without hardware features that are specifically aimed at supporting software pipelines. register allocation for software pipelines presents certain novel problems leading to unconventional solutions, especially in the presence of hardware support. this paper formulates these novel problems and presents a number of alternative solution strategies. these alternatives are comprehensively tested against over one thousand loops to determine the best register allocation strategy, both with and without the hardware support for software pipelining.
the lrpd test: speculative run-time parallelization of loops with privatization and reduction parallelization. current parallelizing compilers cannot identify a significant fraction of parallelizable loops because they have complex or statically insufficiently defined access patterns. as parallelizable loops arise frequently in practice, we advocate a novel framework for their identification: speculatively execute the loop as a doall and apply a fully parallel data dependence test to determine if it had any cross-iteration dependences; if the test fails, then the loop is reexecuted serially. since, from our experience, a significant amount of the available parallelism in fortran programs can be exploited by loops transformed through privatization and reduction parallelization, our methods can speculatively apply these transformations and then check their validity at run-time. another important contribution of this paper is a novel method for reduction recognition which goes beyond syntactic pattern matching: it detects at run-time if the values stored in an array participate in a reduction operation, even if they are transferred through private variables and/or are affected by statically unpredictable control flow. we present experimental results on loops from the perfect benchmarks, which substantiate our claim that these techniques can yield significant speedups which are often superior to those obtainable by inspector/executor methods
cache performance of garbage-collected programs. as processor speeds continue to improve relative to main-memory access times, cache performance is becoming an increasingly important component of program performance. prior work on the cache performance of garbage-collected programs either argues or assumes that conventional garbage-collection methods will yield poor performance, and has therefore concentrated on new collection algorithms designed specifically to improve cache-level reference locality. this paper argues to the contrary: many programs written in garbage-collected languages are naturally well-suited to the direct-mapped caches typically found in modern computer systems. garbage-collected programs written in a mostly-functional style should perform well when simple linear storage allocation and an infrequently-run generational compacting collector are employed; sophisticated collectors intended to improve cache performance are unlikely to be necessary. as locality becomes ever more important to program performance, programs of this kind may turn out to have a significant performance advantage over programs written in traditional languages.
optimizing data permutations for simd devices. the widespread presence of simd devices in today's microprocessors has made compiler techniques for these devices tremendously important. one of the most important and difficult issues that must be addressed by these techniques is the generation of the data permutation instructions needed for non-contiguous and misaligned memory references. these instructions are expensive and, therefore, it is of crucial importance to minimize their number to improve performance and, in many cases, enable speedups over scalar code.although it is often difficult to optimize an isolated data reorganization operation, a collection of related data permutations can often be manipulated to reduce the number of operations. this paper presents a strategy to optimize all forms of data permutations. the strategy is organized into three steps. first, all data permutations in the source program are converted into a generic representation. these permutations can originate from vector accesses to non-contiguous and misaligned memory locations or result from compiler transformations. second, an optimization algorithm is applied to reduce the number of data permutations in a basic block. by propagating permutations across statements and merging consecutive permutations whenever possible, the algorithm can significantly reduce the number of data permutations. finally, a code generation algorithm translates generic permutation operations into native permutation instructions for the target platform. experiments were conducted on various kinds of applications. the results show that up to 77% of the permutation instructions are eliminated and, as a result, the average performance improvement is 48% on vmx and 68% on sse2. for several applications, near perfect speedups have been achieved on both platforms.
synchronous operations as first-class values. synchronous message passing via channels is an interprocess communication (ipc) mechanism found in several concurrent languages, such as csp, occam, and amber. such languages provide a powerful selective i/o operation, which plays a vital role in managing communication with multiple processes. because the channel ipc mechanism is &ldquo;operation-oriented,&rdquo; only procedural abstraction techniques can be used in structuring the communication/synchronization aspects of a system. this has the unfortunate effect of restricting the use of selective i/o, which in turn limits the communication structure. we propose a new, &ldquo;value-oriented&rdquo; approach to channel-based synchronization. we make synchronous operations first-class values, called events, in much the same way that functions are first-class values in functional programming languages. our approach allows the use of data abstraction techniques for structuring ipc. we have incorporated events into pml, a concurrent functional programming language, and have implemented run-time support for them as part of the pegasus system.
simple objects for standard ml. we propose a new approach to adding objects to standard ml (sml) based on explicit declarations of object types, object constructors, and subtyping relationships, with a generalization of the sml case statement to a "typecase" on object types. the language, called object ml (oml), has a type system that conservatively extends the sml type system, preserves sound static typing, and permits type inference. the type system sacrifices some of the expressiveness found in recently proposed schemes, but has the virtue of simplicity. we give examples of how features found in other object-oriented languages can be emulated in oml, discuss the formal properties of oml, and describe some implementation issues.
commutativity analysis: a new analysis framework for parallelizing compilers. this paper presents a new analysis technique, commutativity analysis, for automatically parallelizing computations that manipulate dynamic, pointer-based data structures. commutativity analysis views the computation as composed of operations on objects. it then analyzes the program at this granularity to discover when operations commute (i.e. generate the same final result regardless of the order in which they execute). if all of the operations required to perform a given computation commute, the compiler can automatically generate parallel code. we have implemented a prototype compilation system that uses commutativity analysis as its primary analysis framework. we have used this system to automatically parallelize two complete scientific computations: the barnes-hut n-body solver and the water code. this paper presents performance results for the generated parallel code running on the stanford dash machine. these results provide encouraging evidence that commutativity analysis can serve as the basis for a successful parallelizing compiler.
data transformations for eliminating conflict misses. many cache misses in scientific programs are due to conflicts caused by limited set associativity. we examine two compile-time data-layout transformations for eliminating conflict misses, concentrating on misses occuring on every loop iteration. inter-variable padding adjusts variable base addresses, while intra-variable padding modifies array dimension sizes. two levels of precision are evaluated. padlite only uses array and column dimension sizes, relying on assumptions about common array reference patterns. pad analyzes programs, detecting conflict misses by linearizing array references and calculating conflict distances between uniformly-generated references. the euclidean algorithm for computing the gcd of two numbers is used to predict conflicts between different array columns for linear algebra codes. experiments on a range of programs indicate padlite can eliminate conflicts for benchmarks, but pad is more effective over a range of cache and problem sizes. padding reduces cache miss rates by 16% on average for a 16k direct-mapped cache. execution times are reduced by 6% on average, with some spec95 programs improving up to 15%.
the illinois functional programming interpreter. the illinois functional programming (ifp) language is a modified version of backus' fp(1). ifp has the same side-effect free combinator style of backus fp, while introducing an algol-like syntax and structure. while ifp superficially appears to be an inefficient language to execute, its simplicity makes it quick to interpret. functions are always monadic and there are no variable or parameter names. furthermore, combinator-style languages allow common housekeeping operations to be condensed into efficient machine-language primitives.by reference-counting, the interpreter can often convert call-by-value to destructive call-by-reference while preserving referential transparency. the interpreter has an expression cache which can improve the asymptotic time of some combinatorial functions. ifp function definitions are stored as unix files, so much of unix's functionality is immediately borrowed into the ifp environment, e.g. ls, more, and grep.benchmarks indicate that ifp is an order of magnitude faster than berkeley fp[2], and is competitive with interpreted von-neumann languages such as basic. the interpreter can parallel process on shared-memory multiprocessors, e.g. the encore multimax. ifp currently runs on machines as varied as the ibm pc, vax, and cray-xmp.
process decomposition through locality of reference. in the context of sequential computers, it is common practice to exploit temporal locality of reference through devices such as caches and virtual memory. in the context of multiprocessors, we believe that it is equally important to exploit spatial locality of reference. we are developing a system which, given a sequential program and its domain decomposition, performs process decomposition so as to enhance spatial locality of reference. we describe an application of this method - generating code from shared-memory programs for the (distributed memory) intel ipsc/2.
register allocation for software pipelined multi-dimensional loops. software pipelining of a multi-dimensional loop is an important optimization that overlaps the execution of successive outermost loop iterations to explore instruction-level parallelism from the entire n-dimensional iteration space. this paper investigates register allocation for software pipelined multi-dimensional loops.for single loop software pipelining, the lifetime instances of a loop variant in successive iterations of the loop form a repetitive pattern. an effective register allocation method is to represent the pattern as a vector of lifetimes (or a vector lifetime using rau's terminology) and map it to rotating registers. unfortunately, the software pipelined schedule of a multi-dimensional loop is considerably more complex, and so are the vector lifetimes in it.in this paper, we develop a way to normalize and represent vector lifetimes in multi-dimensional loop software pipelining, which capture their complexity, while exposing their regularity that enables us to develop a simple, yet powerful solution. our algorithm is based on the development of a metric, called distance, that quantitatively determines the degree of potential overlapping (conflicts) between two vector lifetimes. we show how to calculate and use the distance, conservatively or aggressively, to guide the register allocation of the vector lifetimes under a bin-packing algorithm framework. the classical register allocation for software pipelined single loops is subsumed by our method as a special case.the method has been implemented in the orc compiler and produced code for the itanium architecture. we report the effectiveness of our method on 134 loop nests with 348 loop levels. several strategies for register allocation are compared and analyzed.
off-line variable substitution for scaling points-to analysis. most compiler optimizations and software productivity tools rely on information about the effects of pointer dereferences in a program. the purpose of points-to analysis is to compute this information safely, and as accurately as is practical. unfortunately, accurate points-to information is difficult to obtain for large programs, because the time and space requirements of the analysis become prohibitive. we consider the problem of scaling flow- and context-insensitive points-to analysis to large programs, perhaps containing hundreds of thousands of lines of code. our approach is based on a variable substitution transformation, which is performed off-line, i.e., before a standard points-to analysis is performed. the general idea of variable substitution is that a set of variables in a program can be replaced by a single representative variable, thereby reducing the input size of the problem. our main contribution is a linear-time algorithm which finds a particular variable substitution that maintains the precision of the standard analysis, and is also very effective in reducing the size of the problem. we report our experience in performing points-to analysis on large c programs, including some industrial-sized ones. experiments show that our algorithm can reduce the cost of andersen's points-to analysis substantially: on average, it reduced the running time by 53% and the memory cost by 59%, relative to an efficient baseline implementation of the analysis.
symbolic bounds analysis of pointers, array indices, and accessed memory regions. this article presents a novel framework for the symbolic bounds analysis of pointers, array indices, and accessed memory regions. our framework formulates each analysis problem as a system of inequality constraints between symbolic bound polynomials. it then reduces the constraint system to a linear program. the solution to the linear program provides symbolic lower and upper bounds for the values of pointer and array index variables and for the regions of memory that each statement and procedure accesses. this approach eliminates fundamental problems associated with applying standard fixed-point approaches to symbolic analysis problems. experimental results from our implemented compiler show that the analysis can solve several important problems, including static race detection, automatic parallelization, static detection of array bounds violations, elimination of array bounds checks, and reduction of the number of bits used to store computed values.
pointer analysis for multithreaded programs. this paper presents a novel interprocedural, flow-sensitive, and context-sensitive pointer analysis algorithm for multithreaded programs that may concurrently update shared pointers. for each pointer and each program point, the algorithm computes a conservative approximation of the memory locations to which that pointer may point. the algorithm correctly handles a full range of constructs in multithreaded programs, including recursive functions, function pointers, structures, arrays, nested structures and arrays, pointer arithmetic, casts between pointer variables of different types, heap and stack allocated memory, shared global variables, and thread-private global variables.we have implemented the algorithm in the suif compiler system and used the implementation to analyze a sizable set of multithreaded programs written in the cilk multithreaded programming language. our experimental results show that the analysis has good precision and converges quickly for our set of cilk programs.
replay for concurrent non-deterministic shared memory applications. replay of shared-memory program execution is desirable in many domains including cyclic debugging, fault tolerance and performance monitoring. past approaches to repeatable execution have focused on the problem of re-executing the shared-memory access patterns in parallel programs. with the proliferation of operating system supported threads and shared memory for uniprocessor programs, there is a clear need for efficient replay of concurrent applications. the solutions for parallel systems can be performance prohibitive when applied to the uniprocessor case. we present an algorithm, called the repeatable scheduling algorithm, combining scheduling and instruction counts to provide an invariant for efficient, language independent replay of concurrent shared-memory applications. the approach is shown to have trace overheads that are independent of the amount of sharing that takes place. an implementation for cyclic debugging on mach 3.0 is evaluated and benchmarks show typical performance overheads of around 10%. the algorithm implemented is compared with optimal event-based tracing and shown to do better with respect to the number of events monitored or number of events logged, in most cases by several orders of magnitude.
is continuation-passing useful for data flow analysis? the widespread use of the continuation-passing style (cps) transformation in compilers, optimizers, abstract interpreters, and partial evaluators reflects a common belief that the transformation has a positive effect on the analysis of programs. investigations by nielson [13] and burn/filho [5,6] support, to some degree, this belief with theoretical results. however, they do not pinpoint the source of increased abstract information and do not explain the observation of many people that continuation-passing confuses some conventional data flow analyses. to study the impact of the cps transformation on program analysis, we derive three canonical data flow analyzers for the core of an applicative higher-order programming language. the first analyzer is based on a direct semantics of the language, the second on a continuation-semantics of the language, and the last on the direct semantics of cps terms. all analyzers compute the control flow graph of the source program and hence our results apply to a large class of data flow analyses. a comparison of the information gathered by our analyzers establishes the following points:1. the results of a direct analysis of a source program are incomparable to the results of an analysis of the equivalent cps program. in other words, the translation of the source program to a cps version may increase or decrease static information. the gain of information occurs in non-distributive analyses and is solely due to the duplication of the analysis of the continuation. the loss of information is due to the confusion of distinct procedure returns.2. the analyzer based on the continuation semantics produces more accurate results than both direct analyzers, but again only in non-distributive analyses due to the duplication of continuations along every execution path. however, when the analyzer explicitly accounts for looping constructs, the results of the semantic-cps analysis are no longer computable.in view of these results, we argue that, in practice, a direct data flow analysis that relies on some amount of duplication would be as satisfactory as a cps analysis.
scannerless nslr(1) parsing of programming languages. the disadvantages of traditional two-phase parsing (a scanner phase preprocessing input for a parser phase) are discussed. we present metalanguage enhancements for context-free grammars that allow the syntax of programming languages to be completely described in a single grammar. the enhancements consist of two new grammar rules, the exclusion rule, and the adjacency-restriction rule. we also present parser construction techniques for building parsers from these enhanced grammars, that eliminate the need for a scanner phase.
register allocation across procedure and module boundaries. this paper describes a method for compiling programs using interprocedural register allocation. a strategy for handling programs built from multiple modules is presented, as well as algorithms for global variable promotion and register spill code motion. these algorithms attempt to address some of the shortcomings of previous interprocedural register allocation strategies. results are given for an implementation on a single register file risc-based architecture.
determining average program execution times and their variance. this paper presents a general framework for determining average program execution times and their variance, based on the program's interval structure and control dependence graph. average execution times and variance values are computed using frequency information from an optimized counter-based execution profile of the program.
a general framework for iteration-reordering loop transformations. this paper describes a general framework for representing iteration-reordering transformations. these transformations can be both matrix-based and non-matrix-based. transformations are defined by rules for mapping dependence vectors, rules for mapping loop bound expressions, and rules for creating new initialization statements. the framework is extensible, and can be used to represent any iteration-reordering transformation. mapping rules for several common transformations are included in the paper.
a new algorithm for scalar register promotion based on ssa form. we present a new register promotion algorithm based on static single assignment (ssa) form. register promotion is aimed at promoting program names from memory locations to registers. our algorithm is profile-driven and is based on the scope of intervals. in cases where a complete promotion is not possible because of the presence of function calls or pointer references, the proposed algorithm is capable of eliminating loads and stores on frequently executed paths by placing loads and stores on less frequently executed paths. we also describe an efficient method to incrementally update ssa form when new definitions are cloned from an existing name during register promotion. on specint95 benchmarks, our algorithm removes about ~12% of memory operations which access scalar variables.
exploiting idle floating-point resources for integer execution. in conventional superscalar microarchitectures with partitioned integer and floating-point resources, all floating-point resources are idle during execution of integer programs. palacharla and smith [26] addressed this drawback and proposed that the floating-point subsystem be augmented to support integer operations. the hardware changes required are expected to be fairly minimal.to exploit these idle floating resources, the compiler must identify integer code that can be profitably offloaded to the augmented floating-point subsystem. in this paper, we present two compiler algorithms to do this. the basic scheme offloads integer computation to the floating-point subsystem using existing program loads/stores for inter-partition communication. for the specint95 benchmarks, we show that this scheme offloads from 5% to 29% of the total dynamic instructions to the floating-point subsystem. the advanced scheme inserts copy instructions and duplicates some instructions to further offload computation. we evaluate the effectiveness of the two schemes using timing simulation. we show that the advanced scheme can offload from 9% to 41% of the total dynamic instructions to the floating-point subsystem. in doing so, speedups from 3% to 23% are achieved over a conventional microarchitecture.
control cpr: a branch height reduction optimization for epic architectures. the challenge of exploiting high degrees of instruction-level parallelism is often hampered by frequent branching. both exposed branch latency and low branch throughput can restrict parallelism. control critical path reduction (control cpr) is a compilation technique to address these problems. control cpr can reduce the dependence height of critical paths through branch operations as well as decrease the number of executed branches. in this paper, we present an approach to control cpr that recognizes sequences of branches using profiling statistics. the control cpr transformation is applied to the predominant path through this sequence. our approach, its implementation, and experimental results are presented. this work demonstrates that control cpr enhances instruction-level parallelism for a variety of application programs and improves their performance across a range of processors.
facile: a language and compiler for high-performance processor simulators. architectural simulators are essential tools for computer architecture and systems research and development. simulators, however, are becoming frustratingly slow, because they must now model increasingly complex micro-architectures running realistic workloads. previously, we developed a technique called fast-forwarding, which applied partial evaluation and mermoization to improve the performance of detailed architectural simulations by as much as an order of magnitude [14]. while writing a detailed processor simulator is difficult, implementing fast-forwarding is even more complex. this paper describes facile, a domain-specific language for writing detailed, accurate micro-architecture simulators. architectural descriptions written in facile can be compiled, using partial evaluation techniques, into fast-forwarding simulators that achieve significant performance improvements with far less programmer effort. facile and its compiler make this performance-enhancing technique accessible to computer architects.
on-the-fly detection of access anomalies. access anomalies are a common class of bugs in shared-memory parallel programs. an access anomaly occurs when two concurrent execution threads both write (or one thread reads and the other writes) the same shared memory location without coordination. approaches to the detection of access anomalies include static analysis, post-mortem trace analysis, and on-the-fly monitoring.a general on-the-fly algorithm for access anomaly detection is presented, which can be applied to programs with both nested fork-join and synchronization operations. the advantage of on-the-fly detection over post-mortem analysis is that the amount of storage used can be greatly reduced by data compression techniques and by discarding information as soon as it becomes obsolete. in the algorithm presented, the amount of storage required at any time depends only on the number v of shared variables being monitored and the number n of threads, not on the number of synchronizations. data compression is achieved by the use of two techniques called merging and subtraction. upper bounds on storage are shown to be v x n2 for merging and v x n for subtraction.
an optimizer for ada - design, experiences and results. in this paper we describe the design of a global machine independent low level optimizer for the karlsruhe ada compiler. we give a short overview on the optimizations and data structures used in the optimizer as well as some experiences with the optimizer. detailed measurements are provided for a collection of benchmarks. the average improvement of code speed is 40%.
heap profiling for space-efficient java. we present a heap-profiling tool for exploring the potential for space savings in java programs. the output of the tool is used to direct rewriting of application source code in a way that allows more timely garbage collection (gc) of objects, thus saving space. the rewriting can also avoid allocating some objects that are never used. the tool measures the difference between the actual collection time and the potential earliest collection time of objects for a java application. this time difference indicates potential savings. then the tool sorts the allocation sites in the application source code according to the accumulated potential space saving for the objects allocated at the sites. a programmer can investigate the source code surrounding the sites with the highest savings to find opportunities for code rewriting that could save space. our experience shows that in many cases simple code rewriting leads to actual space savings and in some cases also to improvements in program runtime. experimental results using the tool and manually rewriting code show average space savings of 18% for the specjvm98 benchmark suite. results for other benchmarks are also promising. we have also classified the program transformations that we have used and argue that in many cases improvements can be achieved by an optimizing compiler.
a type-based compiler for standard ml. compile-time type information should be valuable in efficient compilation of statically typed functional languages such as standard ml. but how should type-directed compilation work in real compilers, and how much performance gain will type-based optimizations yield? in order to support more efficient data representations and gain more experience about type-directed compilation, we have implemented a new type-based middle end and back end for the standard ml of new jersey compiler. we describe the basic design of the new compiler, identify a number of practical issues, and then compare the performance of our new compiler with the old non-type-based compiler. our measurement shows that a combination of several simple type-based optimizations reduces heap allocation by 36%; and improves the already-efficient code generated by the old non-type-based compiler by about 19% on a decstation 500.
automatic design and implementation of language data types. language implementation is in need of automation. although compiler construction has long been aided by parser generators and other tools, interpreters and runtime systems have been neglected, even though they constitute a large component of languages like lisp, prolog, and smalltalk. of the several parts of a runtime system, the primitive datatype definitions present some of the most difficult decisions for the implementor. the effectiveness of type discrimination schemes, interactions between storage allocation and virtual memory, and general time/space tradeoffs are issues that have no simple resolution-they must be evaluated for each implementation. a formalism for describing implementations has been developed and used in a prototype designer of primitive data structures. the designer is a collection of heuristic rules that produce multiple designs of differing characteristics. cost evaluation on machine code derived from those designs yields performance formulas, which are then used to estimate the designs' effect on benchmark programs.
control-flow analysis in scheme. traditional flow analysis techniques, such as the ones typically employed by optimizing fortran compilers, do not work for scheme-like languages. this paper presents a flow analysis technique &mdash; control flow analysis &mdash; which is applicable to scheme-like languages. as a demonstration application, the information gathered by control flow analysis is used to perform a traditional flow analysis problem, induction variable elimination. extensions and limitations are discussed. the techniques presented in this paper are backed up by working code. they are applicable not only to scheme, but also to related languages, such as common lisp and ml.
continuations and transducer composition. on-line transducers are an important class of computational agent; we construct and compose together many software systems using them, such as stream processors, layered network protocols, dsp networks and graphics pipelines. we show an interesting use of continuations, that, when taken in a cps setting, exposes the control flow of these systems. this enables a cps-based compiler to optimise systems composed of these transducers, using only standard, known analyses and optimisations. critically, the analysis permits optimisation across the composition of these transducers, allowing efficient construction of systems in a hierarchical way.
essential language support for generic programming. concepts are an essential language feature for generic programming in the large. concepts allow for succinct expression of constraints on type parameters of generic algorithms, enable systematic organization of problem domain abstractions, and make generic algorithms easier to use. in this paper we present the design of a type system and semantics for concepts that is suitable for non-type-inferencing languages. our design shares much in common with the type classes of haskell, though our primary influence is from best practices in the c++ community, where concepts are used to document type requirements for templates in generic libraries. concepts include a novel combination of associated types and same-type constraints that do not appear in type classes, but that are similar to nested types and type sharing in ml.
handling control. non-local control transfer and exception handling have a long tradition in higher-order programming languages such as common lisp, scheme and ml. however, each language stops short of providing a full and complementary approach&mdash;control handling is provided only if the corresponding control operator is first-order. in this work, we describe handlers in a higher-order control setting. we invoke our earlier theoretical result that all denotational models of control languages invariably include capabilities that handle control. these capabilities, when incorporated into the language, form an elegant and powerful higher-order generalization of the first-order exception-handling mechanism.
di: an interactive debugging interpreter for applicative languages. the di interpreter is both a debugger and interpreter of sisal programs. its use as a program interpreter is only a small part of its role; it is designed to be a tool for studying compilation techniques for applicative languages. di interprets dataflow graphs expressed in the if1 and if2 languages, and is heavily instrumented to report the activity of dynamic storage activity, reference counting, copying and updating of structured data values. it also aids the sisal language evaluation by providing an interim execution vehicle for sisal programs. di provides determinate, sequential interpretation of graph nodes for sequential and parallel operations in a canonical order. as a debugging aid, di allows tracing, breakpointing, and interactive display of program data values. di handles creation of sisal and if1 error values for each data type and propagates them according to a well-defined algebra. we have begun to implement if1 optimizers and have measured the improvements with di.
a generalized algorithm for graph-coloring register allocation. graph-coloring register allocation is an elegant and extremely popular optimization for modern machines. but as currently formulated, it does not handle two characteristics commonly found in commercial architectures. first, a single register name may appear in multiple register classes, where a class is a set of register names that are interchangeable in a particular role. second, multiple register names may be aliases for a single hardware register. we present a generalization of graph-coloring register allocation that handles these problematic characteristics while preserving the elegance and practicality of traditional graph coloring. our generalization adapts easily to a new target machine, requiring only the sets of names in the register classes and a map of the register aliases. it also drops easily into a well-known graph-coloring allocator, is efficient at compile time, and produces high-quality code.
a compiler approach to fast hardware design space exploration in fpga-based systems. the current practice of mapping computations to custom hardware implementations requires programmers to assume the role of hardware designers. in tuning the performance of their hardware implementation, designers manually apply loop transformations such as loop unrolling. designers manually apply loop transformations. for example, loop unrolling is used to expose instruction-level parallelism at the expense of more hardware resources for concurrent operator evaluation. because unrolling also increases the amount of data a computation requires, too much unrolling can lead to a memory bound implementation where resources are idle. to negotiate inherent hardware space-time trade-offs, designers must engage in an iterative refinement cycle, at each step manually applying transformations and evaluating their impact. this process is not only error-prone and tedious but also prohibitively expensive given the large search spaces and with long synthesis times. this paper describes an automated approach to hardware design space exploration, through a collaboration between parallelizing compiler technology and high-level synthesis tools. we present a compiler algorithm that automatically explores the large design spaces resulting from the application of several program transformations commonly used in application-specific hardware designs. our approach uses synthesis estimation techniques to quantitatively evaluate alternate designs for a loop nest computation. we have implemented this design space exploration algorithm in the context of a compilation and synthesis system called defacto, and present results of this implementation on five multimedia kernels. our algorithm derives an implementation that closely matches the performance of the fastest design in the design space, and among implementations with comparable performance, selects the smallest design. we search on average only 0.3% of the design space. this technology thus significantly raises the level of abstraction for hardware design and explores a design space much larger than is feasible for a human designer.
programming by sketching for bit-streaming programs. this paper introduces the concept of programming with sketches, an approach for the rapid development of high-performance applications. this approach allows a programmer to write clean and portable reference code, and then obtain a high-quality implementation by simply sketching the outlines of the desired implementation. subsequently, a compiler automatically fills in the missing details while also ensuring that a completed sketch is faithful to the input reference code. in this paper, we develop streambit as a sketching methodology for the important class of bit-streaming programs (e.g., coding and cryptography).a sketch is a partial specification of the implementation, and as such, it affords several benefits to programmer in terms of productivity and code robustness. first, a sketch is easier to write compared to a complete implementation. second, sketching allows the programmer to focus on exploiting algorithmic properties rather than on orchestrating low-level details. third, a sketch-aware compiler rejects "buggy" sketches, thus improving reliability while allowing the programmer to quickly evaluate sophisticated implementation ideas.we evaluated the productivity and performance benefits of our programming methodology in a user-study, where a group of novice streambit programmers competed with a group of experienced c programmers on implementing a cipher. we learned that, given the same time budget, the ciphers developed in streambit ran 2.5x faster than ciphers coded in c. we also produced implementations of des and serpent that were competitive with hand optimized implementations available in the public domain.
new tiling techniques to improve cache temporal locality. tiling is a well-known loop transformation to improve temporal locality of nested loops. current compiler algorithms for tiling are limited to loops which are perfectly nested or can be transformed, in trivial ways, into a perfect nest. this paper presents a number of program transformations to enable tiling for a class of nontrivial imperfectly-nested loops such that cache locality is improved. we define a program model for such loops and develop compiler algorithms for their tiling. we propose to adopt odd-even variable duplication to break anti- and output dependences without unduly increasing the working-set size, and to adopt speculative execution to enable tiling of loops which may terminate prematurely due to, e.g. convergence tests in iterative algorithms. we have implemented these techniques in a research compiler, panorama. initial experiments with several benchmark programs are performed on sgi workstations based on mips r5k and r10k processors. overall, the transformed programs run faster by 9% to 164%.
dynascope: a tool for program directing. this paper introduces program directing, a new way of program interaction. directing enables one program, the director, to monitor and to control another program, the executor. one important application of program directing is human interaction with complex computer simulations. the dynascope programming environment is designed specifically to support directing in traditional, compiled languages. it provides a framework and building blocks for easy construction of sophisticated directors. directors are regular programs that perform the directing of executors through dynascope primitives. dynascope is built around the concept of the execution stream which provides a complete description of the executor's computational behavior. the source code of executors requires no changes in order to be subjected to directing. this paper gives an overview of the dynascope system. sample applications are presented: debugging register allocation, animation of procedure calls, and a complex artificial life simulation. the performance of dynascope is illustrated by real time measurements.
realistic compilation by partial evaluation. two key steps in the compilation of strict functional languages are the conversion of higher-order functions to data structures (closures) and the transformation to tail-recursive style. we show how to perform both steps at once by applying first-order offline partial evaluation to a suitable interpreter. the resulting code is easy to transliterate to low-level c or native code. we have implemented the compilation to c; it yields a performance comparable to that of other modern scheme-to-c compilers. in addition, we have integrated various optimizations such as constant propagation, higher-order removal, and arity raising simply by modifying the underlying interpreter. purely first-order methods suffice to achieve the transformations. our approach is an instance of semantics-directed compiler generation.
two for the price of one: composing partial evaluation and compilation. one of the flagship applications of partial evaluation is compilation and compiler generation. however, partial evaluation is usually expressed as a source-to-source transformation for high-level languages, whereas realistic compilers produce object code.we close this gap by composing a partial evaluator with a compiler by automatic means. our work is a successful application of several meta-computation techniques to build the system, both in theory and in practice. the composition is an application of deforestation or fusion.the result is a run-time code generation system built from existing components. its applications are numerous. for example, it allows the language designer to perform interpreter-based experiments with a source-to-source version of the partial evaluator before building a realistic compiler which generates object code automatically.
eventrons: a safe programming construct for high-frequency hard real-time applications. while real-time garbage collection has achieved worst-case latencies on the order of a millisecond, this technology is approaching its practical limits. for tasks requiring extremely low latency, and especially periodic tasks with frequencies above 1 khz, java programmers must currently resort to the noheaprealtimethread construct of the real-time specification for java. this technique requires expensive run-time checks, can result in unpredictable low-level exceptions, and inhibits communication with the rest of the garbage-collected application. we present eventrons, a programming construct that can arbitrarily preempt the garbage collector, yet guarantees safety and allows its data to be visible to the garbage-collected heap. eventrons are a strict subset of java, and require no run-time memory access checks. safety is enforced using a data-sensitive analysis and simple run-time support with extremely low overhead. we have implemented eventrons in ibm's j9 java virtual machine, and present experimental results in which we ran eventrons at frequencies up to 22 khz (a 45 μs period). across 10 million periods, 99.997% of the executions ran within 10 μss of their deadline, compared to 99.999% of the executions of the equivalent program written in c.
a framework for interprocedural optimization in the presence of dynamic class loading. dynamic class loading during program execution in the java programming language is an impediment for generating code that is as efficient as code generated using static whole-program analysis and optimization. whole-program analysis and optimization is possible for languages, such as c++, that do not allow new classes and/or methods to be loaded during program execution. one solution for performing whole-program analysis and avoiding incorrect execution after a new class is loaded is to invalidate and recompile affected methods. runtime invalidation and recompilation mechanisms can be expensive in both space and time, and, therefore, generally restrict optimization. to address these drawbacks, we propose a new framework, called the extant analysis framework, for interprocedural optimization of programs that support dynamic class (or method)loading. given a set of classes comprising the closed world, we perform an offline static analysis which partitions references into two categories:(1) unconditionally extant references which point only to objects whose runtime type is guaranteed to be in the closed world; and (2) conditionally extant references which point to objects whose runtime type is not guaranteed to be in the closed world. optimizations solely dependent on the first categorycan be statically performed, and are guaranteed to be correct even with any future class/method loading. optimizations dependent on the second category are guarded by dynamic tests, called extant safety tests, for correct execution behavior.we describe the properties for extant safety tests, and provide algorithms for their generation and placement.
a new framework for exhaustive and incremental data flow analysis using dj graphs. we present a new elimination-based framework for exhaustive and incremental data flow analysis using the dj graph representation of a program. unlike the previous approaches to elimination-based incremental data flow analysis, our approach can handle arbitrary non-structural and structural changes to program flowgraphs, including those causing irreducibility. we show how our approach is related to (iterated) dominance frontiers, and exploit this relationship to establish the complexity of our exhaustive analysis and to aid the design of our incremental analysis.
refinement-based context-sensitive points-to analysis for java. we present a scalable and precise context-sensitive points-to analysis with three key properties: (1) filtering out of unrealizable paths, (2) a context-sensitive heap abstraction, and (3) a context-sensitive call graph. previous work [21] has shown that all three properties are important for precisely analyzing large programs, e.g., to show safety of downcasts. existing analyses typically give up one or more of the properties for scalability. we have developed a refinement-based analysis that succeeds by simultaneously refining handling of method calls and heap accesses, allowing the analysis to precisely analyze important code while entirely skipping irrelevant code. the analysis is demanddriven and client-driven, facilitating refinement specific to each queried variable and increasing scalability. in our experimental evaluation, our analysis proved the safety of 61% more casts than one of the most precise existing analyses across a suite of large benchmarks. the analysis checked the casts in under 13 minutes per benchmark (taking less than 1 second per query) and required only 35mb of memory, far less than previous approaches.
atom - a system for building customized program analysis tools. atom (analysis tools with om) is a single framework for building a wide range of customized program analysis tools. it provides the common infrastructure present in all code-instrumenting tools; this is the difficult and time-consuming part. the user simply defines the tool-specific details in instrumentation and analysis routines. building a basic block counting tool like pixie with atom requires only a page of code.atom, using om link-time technology, organizes the final executable such that the application program and user's analysis routines run in the same address space. information is directly passed from the application program to the analysis routines through simple procedure calls instead of inter-process communication or files on disk. atom takes care that analysis routines do not interfere with the program's execution, and precise information about the program is presented to the analysis routines at all times. atom uses no simulation or interpretation.atom has been implemented on the alpha axp under osf/1. it is efficient and has been used to build a diverse set of tools for basic block counting, profiling, dynamic memory recording, instruction and data cache simulation, pipeline simulation, evaluating branch prediction, and instruction scheduling.
link-time optimization of address calculation on a 64-bit architecture. compilers for new machines with 64-bit addresses must generate code that works when the memory used by the program is large. procedures and global variables are accessed indirectly via global address tables, and calling conventions include code to establish the addressability of the appropriate tables. in the common case of a program that does not require a lot of memory, all of this can be simplified considerably, with a corresponding reduction in program size and execution time.we have used our link-time code modification system om to perform program transformations related to global address use on the alpha axp. though simple, many of these arewhole-program optimizations that can be done only when we can see the entire program at once, so link-time is an ideal occasion to perform them.this paper describes the optimizations performed and shows their effects on program size and performance. relatively modest transformations, possible without moving code, improve the performance of spec benchmarks by an average of 1.5%. more ambitious transformations, requiring an understanding of program structure that is thorough but not difficult at link-time, can do even better, reducing program size by 10% or more, and improving performance by an average of 3.8%.even a program compiled monolithically with interprocedural optimization can benefit nearly as much from this technique, if it contains statically-linked pre-compiled library code. when the benchmark sources were compiled in this way, we were still able to improve their performance by 1.35% with the modest transformations and 3.4% with the ambitious transformations.
how to print floating-point numbers accurately. we present algorithms for accurately converting floating-point numbers to decimal representation. the key idea is to carry along with the computation an explicit representation of the required rounding accuracy. we begin with the simpler problem of converting fixed-point fractions. a modification of the well-known algorithm for radix-conversion of fixed-point fractions by multiplication explicitly determines when to terminate the conversion process; a variable number of digits are produced. the algorithm has these properties: no information is lost; the original fraction can be recovered from the output by rounding. no &ldquo;garbage digits&rdquo; are produced. the output is correctly rounded. it is never necessary to propagate carries on rounding. we then derive two algorithms for free-formal output of floating-point numbers. the first simply scales the given floating-point number to an appropriate fractional range and then applies the algorithm for fractions. this is quite fast and simple to code but has inaccuracies stemming from round-off errors and oversimplification. the second algorithm guarantees mathematical accuracy by using multiple-precision integer arithmetic and handling special cases. both algorithms produce no more digits than necessary (intuitively, the &ldquo;1.3 prints as 1.2999999&rdquo; problem does not occur). finally, we modify the free-format conversion algorithm for use in fixed-format applications. information may be lost if the fixed format provides too few digit positions, but the output is always correctly rounded. on the other hand, no &ldquo;garbage digits&rdquo; are ever produced, even if the fixed format specifies too many digit positions (intuitively, the &ldquo;4/3 prints as 1.333333328366279602&rdquo; problem does not occur).
meta optimization: improving compiler heuristics with machine learning. compiler writers have crafted many heuristics over the years to approximately solve np-hard problems efficiently. finding a heuristic that performs well on a broad range of applications is a tedious and difficult process. this paper introduces meta optimization, a methodology for automatically fine-tuning compiler heuristics. meta optimization uses machine-learning techniques to automatically search the space of compiler heuristics. our techniques reduce compiler design complexity by relieving compiler writers of the tedium of heuristic tuning. our machine-learning system uses an evolutionary algorithm to automatically find effective compiler heuristics. we present promising experimental results. in one mode of operation meta optimization creates application-specific heuristics which often result in impressive speedups. for hyperblock formation, one optimization we present in this paper, we obtain an average speedup of 23% (up to 73%) for the applications in our suite. furthermore, by evolving a compiler's heuristic over several benchmarks, we can create effective, general-purpose heuristics. the best general-purpose heuristic our system found for hyperblock formation improved performance by an average of 25% on our training set, and 9% on a completely unrelated test set. we demonstrate the efficacy of our techniques on three different optimizations in this paper: hyperblock formation, register allocation, and data prefetching.
bitwidth analysis with application to silicon compilation. this paper introduces bitwise, a compiler that minimizes the bitwidth the number of bits used to represent each operand for both integers and pointers in a program. by propagating 70 static information both forward and backward in the program dataflow graph, bitwise frees the programmer from declaring bitwidth invariants in cases where the compiler can determine bitwidths automatically. because loop instructions comprise the bulk of dynamically executed instructions, bitwise incorporates sophisticated loop analysis techniques for identifying bitwidths. we find a rich opportunity for bitwidth reduction in modern multimedia and streaming application workloads. for new architectures that support sub-word data-types, we expect that our bitwidth reductions will save power and increase processor performance. this paper also applies our analysis to silicon compilation, the translation of programs into custom hardware, to realize the full benefits of bitwidth reduction. we describe our integration of bitwise with the deepc silicon compiler. by taking advantage of bitwidth information during architectural synthesis, we reduce silicon real estate by 15 - 86%, improve clock speed by 3 - 249%, and reduce power by 46 - 73%. the next era of general purpose and reconfigurable architectures should strive to capture a portion of these gains.
support for garbage collection at every instruction in a java compiler. a high-performance implementation of a java virtual machine1 requires a compiler to translate java bytecodes into native instructions, as well as an advanced garbage collector (e.g., copying or generational). when the java heap is exhausted and the garbage collector executes, the compiler must report to the garbage collector all live object references contained in physical registers and stack locations. typical compilers only allow certain instructions (e.g., call instructions and backward branches) to be gc-safe; if gc happens at some other instruction, the compiler may need to advance execution to the next gc-safe point. until now, no one has ever attempted to make every compiler-generated instruction gc-safe, due to the perception that recording this information would require too much space. this kind of support could improve the gc performance in multithreaded applications. we show how to use simple compression techniques to reduce the size of the gc map to about 20% of the generated code size, a result that is competitive with the best previously published results. in addition, we extend the work of agesen, detlefs, and moss, regarding the so-called "jsr problem" (the single exception to java's type safety property), in a way that eliminates the need for extra runtime overhead in the generated code.
debugging concurrent processes: a case study. we present a case study that illustrates a method of debugging concurrent processes in a parallel programming environment. it uses a new approach called speculative replay to reconstruct the behavior of a program from the histories of its individual processes. known time dependencies between events in different processes are used to divide the histories into dependence blocks. a graphical representation called a concurrency map displays possibilities for concurrency among processes. the replay technique preserves the known dependencies and compares the process histories generated during replay with those that were logged during the original program execution. if a process generates a replay history that does not match its original history, replay backs up. an alternative ordering of events is created and tested to see if it produces process histories that match the original histories. successively more controlled replay sequences are generated, by introducing additional dependencies. we describe ongoing work on tools that will control replay without reconstructing the entire space of possible event orderings. the case study presents a miniature example of shared-queue management that can be examined in detail. it demonstrates the replay technique and the construction and use of the concurrency map. using our techniques, we detect a failure to which a standard algorithm for shared-queue management is susceptible.
compile-time composition of run-time data and iteration reorderings. many important applications, such as those using sparse data structures, have memory reference patterns that are unknown at compile-time. prior work has developed run-time reorderings of data and computation that enhance locality in such applications.this paper presents a compile-time framework that allows the explicit composition of run-time data and iteration-reordering transformations. our framework builds on the iteration-reordering framework of kelly and pugh to represent the effects of a given composition. to motivate our extension, we show that new compositions of run-time reordering transformations can result in better performance on three benchmarks.we show how to express a number of run-time data and iteration-reordering transformations that focus on improving data locality. we also describe the space of possible run-time reordering transformations and how existing transformations fit within it. since sparse tiling techniques are included in our framework, they become more generally applicable, both to a larger class of applications, and in their composition with other reordering transformations. finally, within the presented framework data need be remapped only once at runtime for a given composition thus exhibiting one example of overhead reductions the framework can express.
a region-based compilation technique for a java just-in-time compiler. method inlining and data flow analysis are two major optimization components for effective program transformations, however they often suffer from the existence of rarely or never executed code contained in the target method. one major problem lies in the assumption that the compilation unit is partitioned at method boundaries. this paper describes the design and implementation of a region-based compilation technique in our dynamic compilation system, in which the compiled regions are selected as code portions without rarely executed code. the key part of this technique is the region selection, partial inlining, and region exit handling. for region selection, we employ both static heuristics and dynamic profiles to identify rare sections of code. the region selection process and method inlining decision are interwoven, so that method inlining exposes other targets for region selection, while the region selection in the inline target conserves the inlining budget, leading to more method inlining. thus the inlining process can be performed for parts of a method, not for the entire body of the method. when the program attempts to exit from a region boundary, we trigger recompilation and then rely on on-stack replacement to continue the execution from the corresponding entry point in the recompiled code. we have implemented these techniques in our java jit compiler, and conducted a comprehensive evaluation. the experimental results show that the approach of region-based compilation achieves approximately 5% performance improvement on average, while reducing the compilation overhead by 20 to 30%, in comparison to the traditional function-based compilation techniques.
the type inference and coercion facilities in the scratchpad ii interpreter. the scratchpad ii system is an abstract datatype programming language, a compiler for the language, a library of packages of polymorphic functions and parametrized abstract datatypes, and an interpreter that provides sophisticated type inference and coercion facilities. although originally designed for the implementation of symbolic mathematical algorithms, scratchpad ii is a general purpose programming language. this paper discusses aspects of the implementation of the interpreter and how it attempts to provide a user friendly and relatively weakly typed front end for the strongly typed programming language.
a study of dead data members in c++ applications. object-oriented applications may contain data members that can be removed from the application without affecting program behavior. such "dead" data members may occur due to unused functionality in class libraries, or due to the programmer losing track of member usage as the application changes over time. we present a simple and efficient algorithm for detecting dead data members in c++ applications. this algorithm has been implemented using a prototype version of the ibm visualage c++ compiler, and applied to a number of realistic benchmark programs ranging from 600 to 58,000 lines of code. for the non-trivial benchmarks, we found that up to 27.3% of the data members in the benchmarks are dead (average 12.5%), and that up to 11.6% of the object space of these applications may be occupied by dead data members at run-time (average 4.4%).
compiling dataflow analysis of logic programs. abstract interpretation is a technique extensively used for global dataflow analyses of logic programs. existing implementations of abstract interpretation are slow due to interpretive or transforming overhead and the inefficiency in manipulation of global information. since abstract interpretation mimics standard interpretation, it is a promising alternative to compile abstract interpretation into the framework of the wam (warren abstract machine) for better performance. in this paper, we show how this approach can be effectively implemented in a low-cost manner. to evaluate the possible benefits of this approach, a prototype dataflow analyzer has been implemented for inference of mode, type and variable aliasing information of logic programs. for a subset of benchmark programs in [15], it significantly improves the performance by a factor of over 150 on the average.
til: a type-directed optimizing compiler for ml. the goal of the til project was to explore the use of typed intermediate languages to produce high-performance native code from standard ml (sml). we believed that existing sml compilers were doing a good job of conventional functional language optimizations, as one might find in a lisp compiler, but that inadequate use was made of the rich type information present in the source language. our goal was to show that we could get much greater performance by propagating type information through to the back end of the compiler, without sacrificing the advantages afforded by loop-oriented and other optimizations.we also confirmed that using typed intermediate languages dramatically improved the reliability and maintainability of the compiler itself. in particular, we were able to use the type system to express critical invariants, and enforce those invariants through type checking. in this respect, til introduced and popularized the notion of a certifying compiler, which attaches a checkable certificate of safety to its generated code. in turn, this led directly to the idea of certified object code, inspiring the development of proof-carrying code and typed assembly language as certified object code formats.
a unified framework for schedule and storage optimization. we present a unified mathematical framework for analyzing the tradeoffs between parallelism and storage allocation within a parallelizing compiler. using this framework, we show how to find a good storage mapping for a given schedule, a good schedule for a given storage mapping, and a good storage mapping that is valid for all legal schedules. we consider storage mappings that collapse one dimension of a multi-dimensional array, and programs that are in a single assignment form with a one-dimensional schedule. our technique combines affine scheduling techniques with occupancy vector analysis and incorporates general affine dependences across statements and loop nests. we formulate the constraints imposed by the data dependences and storage mappings as a set of linear inequalities, and apply numerical programming techniques to efficiently solve for the shortest occupancy vector. we consider our method to be a first step towards automating a procedure that finds the optimal tradeoff between parallelism and storage space.
quality and speed in linear-scan register allocation. a linear-scan algorithm directs the global allocation of register candidates to registers based on a simple linear sweep over the program being compiled. this approach to register allocation makes sense for systems, such as those for dynamic compilation, where compilation speed is important. in contrast, most commercial and research optimizing compilers rely on a graph-coloring approach to global register allocation. in this paper, we compare the performance of a linear-scan method against a modern graph-coloring method. we implement both register allocators within the machine suif extension of the stanford suif compiler system. experimental results show that linear scan is much faster than coloring on benchmarks with large numbers of register candidates. we also describe improvements to the linear-scan approach that do not change its linear character, but allow it to produce code of a quality near to that produced by graph coloring.
a framework for unrestricted whole-program optimization. procedures have long been the basic units of compilation in conventional optimization frameworks. however, procedures are typically formed to serve software engineering rather than optimization goals, arbitrarily constraining code transformations. techniques, such as aggressive inlining and interprocedural optimization, have been developed to alleviate this problem, but, due to code growth and compile time issues, these can be applied only sparingly.this paper introduces the procedure boundary elimination (pbe) compilation framework, which allows unrestricted whole-program optimization. pbe allows all intra-procedural optimizations and analyses to operate on arbitrary subgraphs of the program, regardless of the original procedure boundaries and without resorting to inlining. in order to control compilation time, pbe also introduces novel extensions of region formation and encapsulation. pbe enables targeted code specialization, which recovers the specialization benefits of inlining while keeping code growth in check. this paper shows that pbe attains better performance than inlining with half the code growth.
gum: a portable parallel implementation of haskell. gum is a portable, parallel implementation of the haskell functional language. despite sustained research interest in parallel functional programming, gum is one of the first such systems to be made publicly available.gum is message-based, and portability is facilitated by using the pvm communications harness that is available on many multi-processors. as a result, gum is available for both shared-memory (sun sparcserver multiprocessors) and distributed-memory (networks of workstations) architectures. the high message-latency of distributed machines is ameliorated by sending messages asynchronously, and by sending large packets of related data in each message.initial performance figures demonstrate absolute speedups relative to the best sequential compiler technology. to improve the performance of a parallel haskell program gum provides tools for monitoring and visualising the behaviour of threads and of processors during execution.
compiling programs for a linear systolic array. this paper describes an al compiler for the warp systolic array. al is a programming language in which the user programs a systolic array as if it were a sequential computer and relies on the compiler to generate parallel code. this paper introduces the notion of data relations in compiling programs for systolic arrays. unlike dependence relations among statements of a program, data relations define compatibility relations among data objects of a program. the al compiler uses data relations to compute data compatibility classes, determine data distribution, and distribute loop iterations. the al compiler can generate efficient parallel code almost identical to what the user would have written by hand. for example, the al compiler generates parallel code for the linpack lu decomposition (sgefa) and qr decomposition (sqrdc) routines with a nearly 8-fold speedup on the 10-cell warp array for matrices of size 180 &times; 180.
the liberty structural specification language: a high-level modeling language for component reuse. rapid exploration of the design space with simulation models is essential for quality hardware systems research and development. despite striking commonalities across hardware systems, designers routinely fail to achieve high levels of reuse across models constructed in existing general-purpose and domain-specific languages. this lack of reuse adversely impacts hardware system design by slowing the rate at which ideas are evaluated. this paper presents an examination of existing languages to reveal their fundamental limitations regarding reuse in hardware modeling. with this understanding, a solution is described in the context of the design and implementation of the liberty structural specification language (lss), the input language for a publicly available high-level digital-hardware modeling tool called the liberty simulation environment. lss is the first language to enable low-overhead reuse by simultaneously supporting static inference based on hardware structure and flexibility via parameterizable structure. through lss, this paper also introduces a new type inference algorithm and a new programming language technique, called use-based specialization, which, in a manner analogous to type inference, customizes reusable components by statically inferring structural properties that otherwise would have had to have been specified manually.
correctness-preserving derivation of concurrent garbage collection algorithms. constructing correct concurrent garbage collection algorithms is notoriously hard. numerous such algorithms have been proposed, implemented, and deployed - and yet the relationship among them in terms of speed and precision is poorly understood, and the validation of one algorithm does not carry over to others.as programs with low latency requirements written in garbagecollected languages become part of society's mission-critical infrastructure, it is imperative that we raise the level of confidence in the correctness of the underlying system, and that we understand the trade-offs inherent in our algorithmic choice.in this paper we present correctness-preserving transformations that can be applied to an initial abstract concurrent garbage collection algorithm which is simpler, more precise, and easier to prove correct than algorithms used in practice--but also more expensive and with less concurrency. we then show how both pre-existing and new algorithms can be synthesized from the abstract algorithm by a series of our transformations. we relate the algorithms formally using a new definition of precision, and informally with respect to overhead and concurrency.this provides many insights about the nature of concurrent collection, allows the direct synthesis of new and useful algorithms, reduces the burden of proof to a single simple algorithm, and lays the groundwork for the automated synthesis of correct concurrent collectors.
using node merging to enhance graph coloring. a chaitin-style register allocator often blocks during its simplification phase because no node in the interference graph has a degree that is sufficiently small. typically, this is handled by node-splitting, or by optimistically continuing---and hoping that a legal n-coloring will still be found. we observe that the merging of two nodes in a graph causes a reduction in the degree of any node that had been adjacent to both. we have enhanced chaitin's coloring algorithm so that it attempts node-merging during graph simplification; this often allows simplification to continue, while still guaranteeing a coloring for the graph. we have tested this algorithm using appel's database of register-coloring graphs, and have compared it with chaitin's algorithm. the merge-enhanced algorithm yields a better coloring about 8% of the time, and a worse coloring less than 0.1% of the time.
precise and efficient static array bound checking for large embedded c programs. in this paper we describe the design and implementation of a static array-bound checker for a family of embedded programs: the flight control software of recent mars missions. these codes are large (up to 280 kloc), pointer intensive, heavily multithreaded and written in an object-oriented style, which makes their analysis very challenging. we designed a tool called c global surveyor (cgs) that can analyze the largest code in a couple of hours with a precision of 80%. the scalability and precision of the analyzer are achieved by using an incremental framework in which a pointer analysis and a numerical analysis of array indices mutually refine each other. cgs has been designed so that it can distribute the analysis over several processors in a cluster of machines. to the best of our knowledge this is the first distributed implementation of static analysis algorithms. throughout the paper we will discuss the scalability setbacks that we encountered during the construction of the tool and their impact on the initial design decisions.
a framework for construction and evaluation of high-level specifications for program analysis techniques. abstract interpretation introduced the notion of formal specification of program analyses. denotational frameworks are convenient for reasoning about such specifications. however, implementation considerations make denotational specifications complex and hard to develop. we present a framework that facilitates the construction and understanding of denotational specifications for program analysis techniques. the framework is exemplified by specifications for program analysis techniques from the literature and from our own research. this approach allows program analysis techniques to be incorporated into automatically generated program synthesizers by including their specifications with the language definition.
incrementalized pointer and escape analysis. we present a new pointer and escape analysis. instead of analyzing the whole program, the algorithm incrementally analyzes only those parts of the program that may deliver useful results. an analysis policy monitors the analysis results to direct the incremental investment of analysis resources to those parts of the program that offer the highest expected optimization return. our experimental results show that almost all of the objects are allocated at a small number of allocation sites and that an incremental analysis of a small region of the program surrounding each site can deliver almost all of the benefit of a whole-program analysis. our analysis policy is usually able to deliver this benefit at a fraction of the whole-program analysis cost.
higher-order attribute grammars. a new kind of attribute grammars, called higher order attribute grammars, is defined. in higher order attribute grammars the structure tree can be expanded as a result of attribute computation. a structure tree may be stored in an attribute. the term higher order is used because of the analogy with higher order functions, where a function can be the result or parameter of another function. a relatively simple method, using oags, is described to derive an evaluation order on the defining attribute occurrences which comprises all possible direct and indirect attribute dependencies. as in oags, visit-sequences are computed from which an efficient algorithm for attribute evaluation can be derived.
incremental analysis of real programming languages. a major research goal for compilers and environments is the automatic derivation of tools from formal specifications. however, the formal model of the language is often inadequate; in particular, lr(k) grammars are unable to describe the natural syntax of many languages, such as c++ and fortran, which are inherently non-deterministic. designers of batch compilers work around such limitations by combining generated components with ad hoc techniques (for instance, performing partial type and scope analysis in tandem with parsing). unfortunately, the complexity of incremental systems precludes the use of batch solutions. the inability to generate incremental tools for important languages inhibits the widespread use of language-rich interactive environments.we address this problem by extending the language model itself, introducing a program representation based on parse dags that is suitable for both batch and incremental analysis. ambiguities unresolved by one stage are retained in this representation until further stages can complete the analysis, even if the reaolution depends on further actions by the user. representing ambiguity explicitly increases the number and variety of languages that can be analyzed incrementally using existing methods.to create this representation, we have developed an efficient incremental parser for general context-free grammars. our algorithm combines tomita's generalized lr parser with reuse of entire subtrees via state-matching. disambiguation can occur statically, during or after parsing, or during semantic analysis (using existing incremental techniques); program errors that preclude disambiguation retsin multiple interpretations indefinitely. our representation and analyses gain efficiency by exploiting the local nature of ambiguities: for the spec95 c programs, the explicit representation of ambiguity requires only 0.5% additional space and less than 1% additional time during reconstruction.
accurate static estimators for program optimization. determining the relative execution frequency of program regions is essential for many important optimization techniques, including register allocation, function inlining, and instruction scheduling. estimates derived from profiling with sample inputs are generally regarded as the most accurate source of this information; static (compile-time) estimates are considered to be distinctly inferior. if static estimates were shown to be competitive, however, their convenience would outweigh minor gains from profiling, and they would provide a sound basis for optimization when profiling is impossible.we use quantitative metrics to compare estimates from static analysis to those derived from profiles. for c programs, simple techniques for predicting branches and loop counts suffice to estimate intraprocedural frequency patterns with high accuracy. to determine inter-procedural estimates successfully, we combine function-level information with a markov model of control flow over the call graph to produce arc and basic block frequency estimates for the entire program.for a suite of 14 programs, including the c programs from the spec92 benchmark suite, we demonstrate that static estimates are competitive with those derived from profiles. using simple heuristics, we can determine the most frequently executed blocks in each function with 81% accuracy. with the markov model, we identify 80% of the frequently called functions. combining the two techniques, we identify 76% of the most frequently executed call sites.
practical data breakpoints: design and implementation. a data breakpoint associates debugging actions with programmer-specified conditions on the memory state of an executing program. data breakpoints provide a means for discovering program bugs that are tedious or impossible to isolate using control breakpoints alone. in practice, programmers rarely use data breakpoints, because they are either unimplemented or prohibitively slow in available debugging software. in this paper, we present the design and implementation of a practical data breakpoint facility. a data breakpoint facility must monitor all memory updates performed by the program being debugged. we implemented and evaluated two complementary techniques for reducing the overhead of monitoring memory updates. first, we checked write instructions by inserting checking code directly into the program being debugged. the checks use a segmented bitmap data structure that minimizes address lookup complexity. second, we developed data flow algorithms that eliminate checks on some classes of write instructions but may increase the complexity of the remaining checks. we evaluated these techniques on the sparc using the spec benchmarks. checking each write instruction using a segmented bitmap achieved an average overhead of 42%. this overhead is independent of the number of breakpoints in use. data flow analysis eliminated an average of 79% of the dynamic write checks. for scientific programs such the nas kernels, analysis reduced write checks by a factor of ten or more. on the sparc these optimizations reduced the average overhead to 25%.
register windows versus register allocation. a large register set can be exploited by keeping variables and constants in registers instead of in memory. hardware register windows and compile-time or link-time global register allocation are ways to do this. a measure of the effectiveness of any of these register management schemes is how thoroughly they remove loads and stores. this measure must also count extra loads and stores executed because of window overflow or conflicts between procedures.by combining profiling, instrumentation, and in-line simulation, we measured the effectiveness of several register management schemes. these included compile-time and link-time schemes for allocating registers, and register window schemes using fixed-size or variable-sized windows. link-time allocation based on profile information was the clear winner in some cases and did about as well as windows in the rest. even link-time allocation based on an estimated profile was about as good as windows. variable-sized windows sometimes did better than fixed-sized windows, but the difference was usually small.register windows require extra logic in the data path, which may slow the machine cycle slightly, and often use more chip real estate for additional registers. proponents of windows suppose that they trade these drawbacks for a reduction in the number of memory references they must make. our results show that this tradeoff should be made the other way. keep the hardware simple, because a link-time register allocator can nearly duplicate the improvement in memory reference frequency. then the cycle time can be as small as possible, resulting in faster programs overall.
predicting program behavior using real or estimated profiles. there is a growing interest in optimizations that depend on or benefit from an execution profile that tells where time is spent. how well does a profile from one run describe the behavior of a different run, and how does this compare with the behavior predicted by static analysis of the program? this paper defines two abstract measures of how well a profile predicts actual behavior. according to these measures, real profiles indeed do better than estimated profiles, usually. a perfect profile from an earlier run with the same data set, however, does better still, sometimes by a factor of two. unfortunately, using such a profile is unrealistic, and can lead to inflated expectations of a profile-driven optimization.
functional reactive programming from first principles. functional reactive programming, or frp, is a general framework for programming hybrid systems in a high-level, declarative manner. the key ideas in frp are its notions of behaviors and events. behaviors are time-varying, reactive values, while events are time-ordered sequences of discrete-time event occurrences. frp is the essence of fran, a domain-specific language embedded in haskell for programming reactive animations, but frp is now also being used in vision, robotics and other control systems applications. in this paper we explore the formal semantics of frp and how it relates to an implementation based on streams that represent (and therefore only approximate) continuous behaviors. we show that, in the limit as the sampling interval goes to zero, the implementation is faithful to the formal, continuous semantics, but only when certain constraints on behaviors are observed. we explore the nature of these constraints, which vary amongst the frp primitives. our results show both the power and limitations of this approach to language design and implementation. as an example of a limitation, we show that streams are incapable of representing instantaneous predicate events over behaviors.
precise compile-time performance prediction for superscalar-based computers. optimizing compilers (particularly parallel compilers) are constrained by their ability to predict performance consequences of the transformations they apply. many factors, such as unknowns in control structures, dynamic behavior of programs, and complexity of the underlying hardware, make it very difficult for compilers to estimate the performance of the transformations accurately and efficiently. in this paper, we present a performance prediction framework that combines several innovative approaches to solve this problem. first, the framework employs a detailed, architecture-specific, but portable, cost model that can be used to estimate the cost of straight line code efficiently. second, aggregated costs of loops and conditional statements are computed and represented symbolically. this avoids unnecessary, premature guesses and preserves the precision of the prediction. third, symbolic comparison allows compilers to choose the best transformation dynamically and systematically. some methodologies for applying the framework to optimizing parallel compilers to support automatic, performance-guided program restructuring are discussed.
parametric analysis for adaptive computation offloading. many programs can be invoked under different execution options, input parameters and data files. such different execution contexts may lead to strikingly different execution instances. the optimal code generation may be sensitive to the execution instances. in this paper, we show how to use parametric program analysis to deal with this issue for the optimization problem of computation offloading.computation offloading has been shown to be an effective way to improve performance and energy saving on mobile devices. optimal program partitioning for computation offloading depends on the tradeoff between the computation workload and the communication cost. the computation workload and communication requirement may change with different execution instances. optimal decisions on program partitioning must be made at run time when sufficient information about workload and communication requirement becomes available.our cost analysis obtains program computation workload and communication cost expressed as functions of run-time parameters, and our parametric partitioning algorithm finds the optimal program partitioning corresponding to different ranges of run-time parameters. at run time, the transformed program self-schedules its tasks on either the mobile device or the server, based on the optimal program partitioning that corresponds to the current values of run-time parameters. experimental results on an hp ipaq handheld device show that different run-time parameters can lead to quite different program partitioning decisions.
reverse if-conversion. in this paper we present a set of isomorphic control transformations that allow the compiler to apply local scheduling techniques to acyclic subgraphs of the control flow graph. thus, the code motion complexities of global scheduling are eliminated. this approach relies on a new technique, reverse if-conversion (ric), that transforms scheduled if-converted code back to the control flow graph representation. this paper presents the predicate internal representation, the algorithms for ric, and the correctness of ric. in addition, the scheduling issues are addressed and an application to software pipelining is presented.
efficient interpretation of synchronizable series expressions. the benefits of programming in a functional style are well known. for example, algorithms which are expressed as compositions of functions operating on series/vectors/streams of data elements are much easier to understand and modify than equivalent algorithms expressed as loops. unfortunately, many programmers hesitate to use series expressions because they are typically implemented very inefficiently-the prime source of inefficiency being the creation of intermediate series objects.a restricted class of series expressions, obviously synchronizable series expressions, is defined which can be evaluated very efficiently because they do not require the creation of any intermediate series objects. a common lisp macro package has been implemented which supports obviously synchronizable series expressions. using this macro package, programmers can obtain the advantages of expressing computations as series expressions without incurring any runtime overhead. obviously synchronizable series expressions could be straightforwardly supported in any programming language.
program analysis using binary relations. this paper presents a method called relational constraint for finding binary relations among the variables and constants of a program. the method constructs a table of binary relations and treats the program as a collection of constraints on tuples of relations in the table. an experimental optimizer called thinner uses this method to analyze programs of size n in o(n2) time.
programmable syntax macros. lisp has shown that a programmable syntax macro system acts as an adjunct to the compiler that gives the programmer important and powerful abstraction facilities not provided by the language. unlike simple token substitution macros, such as are provided by cpp (the c preprocessor), syntax macros operate on abstract syntax trees (asts). programmable syntax macro systems have not yet been developed for syntactically rich languages such as c because rich concrete syntax requires the manual construction of syntactically valid program fragments, which is a tedious, difficult, and error prone process. also, using two languages, one for writing the program, and one for writing macros, is another source of complexity. this research solves these problems by having the macro language be a minimal extension of the programming language, by introducing explicit code template operators into the macro language, and by using a type system to guarantee, at macro definition time, that all macros and macro functions only produce syntactically valid program fragments. the code template operators make the language context sensitive, which requires changes to the parser. the parser must perform type analysis in order to parse macro definitions, or to parse user code that invokes macros.
cloning-based context-sensitive pointer alias analysis using binary decision diagrams. this paper presents the first scalable context-sensitive, inclusion-based pointer alias analysis for java programs. our approach to context sensitivity is to create a clone of a method for every context of interest, and run a context-insensitive algorithm over the expanded call graph to get context-sensitive results. for precision, we generate a clone for every acyclic path through a program's call graph, treating methods in a strongly connected component as a single node. normally, this formulation is hopelessly intractable as a call graph often has 10 14 acyclic paths or more. we show that these exponential relations can be computed efficiently using binary decision diagrams (bdds). key to the scalability of the technique is a context numbering scheme that exposes the commonalities across contexts. we applied our algorithm to the most popular applications available on sourceforge, and found that the largest programs, with hundreds of thousands of java bytecodes, can be analyzed in under 20 minutes.this paper shows that pointer analysis, and many other queries and algorithms, can be described succinctly and declaratively using datalog, a logic programming language. we have developed a system called bddbddb that automatically translates datalog programs into highly efficient bdd implementations. we used this approach to develop a variety of context-sensitive algorithms including side effect analysis, type analysis, and escape analysis.
run-time code generation and modal-ml. this paper presents a typed programming language and compiler for run-time code generation. the language, called ml', extends ml with modal operators in the style of the mini-ml'e language of davies and pfenning. ml' allows programmers to use types to specify precisely the stages of computation in a program. the types also guide the compiler in generating target code that exploits the staging information through the use of run-time code generation. the target machine is currently a version of the categorical abstract machine, called the ccam, which we have extended with facilities for run-time code generation.this approach allows the programmer to express the staging that he wants directly to the compiler. it also provides a typed framework in which to verify the correctness of his staging intentions, and to discuss his staging decisions with other programmers. finally, it supports in a natural way multiple stages of run-time specialization, so that dynamically generated code can be used in the generation of yet further specialized code.this paper presents an overview of the language, with several examples of programs that illustrate key concepts and programming techniques. then, it discusses the ccam and the compilation of ml' programs into ccam code. finally, the results of some experiments are shown, to demonstrate the benefits of this style of run-time code generation for some applications.
optimal instruction scheduling using integer programming. this paper presents a new approach to local instruction scheduling based on integer programming that produces optimal instruction schedules in a reasonable time, even for very large basic blocks. the new approach first uses a set of graph transformations to simplify the data-dependency graph while preserving the optimality of the final schedule. the simplified graph results in a simplified integer program which can be solved much faster. a new integer-programming formulation is then applied to the simplified graph. various techniques are used to simplify the formulation, resulting in fewer integer-program variables, fewer integer-program constraints and fewer terms in some of the remaining constraints, thus reducing integer-program solution time. the new formulation also uses certain adaptively added constraints (cuts) to reduce solution time. the proposed optimal instruction scheduler is built within the gnu compiler collection (gcc) and is evaluated experimentally using the spec95 floating point benchmarks. although optimal scheduling for the target processor is considered intractable, all of the benchmarks' basic blocks are optimally scheduled, including blocks with up to 1000 instructions, while total compile time increases by only 14%.
efficient context-sensitive pointer analysis for c programs. this paper proposes an efficient technique for context-sensitive pointer analysis that is applicable to real c programs. for efficiency, we summarize the effects of procedures using partial transfer functions. a partial transfer function (ptf) describes the behavior of a procedure assuming that certain alias relationships hold when it is called. we can reuse a ptf in many calling contexts as long as the aliases among the inputs to the procedure are the same. our empirical results demonstrate that this technique is successful&mdash;a single ptf per procedure is usually sufficient to obtain completely context-sensitive results. because many c programs use features such as type casts and pointer arithmetic to circumvent the high-level type system, our algorithm is based on a low-level representation of memory locations that safely handles all the features of c. we have implemented our algorithm in the suif compiler system and we show that it runs efficiently for a set of c benchmarks.
demonic memories for process histories. demonic memory is a form of reconstructive memory for process histories. as a process executes, its states are regularly checkpointed, generating a history of the process at low time resolution. following the initial generation, any prior state of the process can be reconstructed by starting from a checkpointed state and re-executing the process up through the desired state, thereby exploiting the redundancy between the states of a process and the description of that process (i.e., a computer program). the reconstruction of states is automatic and transparent. the history of a process may be examined as though it were a large two-dimensional array, or address space-time, with a normal address space as one axis and steps of process time as the other. an attempt to examine a state that is not physically stored triggers a &ldquo;demon&rdquo; which reconstructs that memory state before access is allowed. regeneration requires an exact description of the original execution of the process. if the original process execution depends on non-deterministic events (e.g., user input), these events are recorded in an exception list, and are replayed at the proper points during re-execution. while more efficient than explicitly storing all state changes, such a checkpointing system is still prohibitively expensive for many applications; each copy (or snapshot) of the system's state may be very large, and many snapshots may be required. demonic memory saves both space and time by using a virtual copy mechanism. (virtual copies share unchanging data with the objects that they are copies of, only storing differences from a prototype or original [mibk86].) in demonic memory, the snapshot at each checkpoint is a virtual copy of the preceding checkpoint's snapshot. hence it is called a virtual snapshot. in order to make the virtual snapshot mechanism efficient, state information is initially saved in relatively large units of space and time, on the order of pages and seconds, with single-word/single-step regeneration undertaken only as needed. this permits the costs of indexing and lookup operations to be amortized over many locations.
debugging of globally optimized programs using data flow analysis. advanced processor and machine architectures need optimizing compilers to be efficiently programmed in high level languages. therefore the need for source level debuggers that can handle optimized programs is rising. one difficulty in debugging optimized code arises from the problem to determine the values of source code variables. to ensure correct debugger behaviour with optimized programs, the debugger not only has to determine the variable's storage location or associated register. it must also verify that the variable is current, i.e. the value determined from that location is really the value that the variable would have in unoptimized code. we will deduce requirements on algorithms for currentness determination and present an algorithm meeting this requirements that is more general than previous work. we will also give first experiences with an implementation. to our knowledge this is the first implementation of a currentness determination algorithm for globally optimized code.
beyond induction variables. induction variable detection is usually closely tied to the strength reduction optimization. this paper studies induction variable analysis from a different perspective, that of finding induction variables for data dependence analysis. while classical induction variable analysis techniques have been used successfully up to now, we have found a simple algorithm based on the static single assignment form of a program that finds all linear induction variables in a loop. moreover, this algorithm is easily extended to find induction variables in multiple nested loops, to find nonlinear induction variables, and to classify other integer scalar assignments in loops, such as monotonic, periodic and wrap-around variables. some of these other variables are now classified using ad hoc pattern recognition, while others are not analyzed by current compilers. giving a unified approach improves the speed of compilers and allows a more general classification scheme. we also show how to use these variables in data dependence testing.
a concurrent compiler for modula-2+. in this paper we describe a collection of techniques for the design and implementation of concurrent compilers. we begin by describing a technique for dividing a source program into many streams so that each stream can be compiled concurrently. we discuss several compiler design issues unique to concurrent compilers including source program partitioning, symbol table management, compiler task scheduling and information flow constraints. the application of our techniques is illustrated by a complete design for a concurrent modula-2+ compiler. after describing the structure of this compiler's performance that demonstrates that significant improvements in compilation time can be achieved through the use of concurrency.
a new framework for debugging globally optimized code. with an increasing number of executable binaries generated by optimizing compilers today, providing a clear and correct source-level debugger for programmers to debug optimized code has become a necessity. in this paper, a new framework for debugging globally optimized code is proposed. this framework consists of a new code location mapping scheme, a data location tracking scheme, and an emulation-based forward recovery model. by taking over the control early and emulating instructions selectively, the debugger can preserve and gather the required program state for the recovery of expected variable values at source breakpoints. the framework has been prototyped in the impact compiler and gdb-4.16. preliminary experiments conducted on several spec95 integer programs have yielded encouraging results. the extra time needed for the debugger to calculate the limits of the emulated region and to emulate instructions is hardly noticeable, while the increase in executable file size due to the extra debug information is on average 76% of that of the executable file with no debug information.
compile-time dynamic voltage scaling settings: opportunities and limits. with power-related concerns becoming dominant aspects of hardware and software design, significant research effort has been devoted towards system power minimization. among run-time power-management techniques, dynamic voltage scaling (dvs) has emerged as an important approach, with the ability to provide significant power savings. dvs exploits the ability to control the power consumption by varying a processor's supply voltage (v) and clock frequency (f). dvs controls energy by scheduling different parts of the computation to different (v, f) pairs; the goal is to minimize energy while meeting performance needs. although processors like the intel xscale and transmeta crusoe allow software dvs control, such control has thus far largely been used at the process/task level under operating system control. this is mainly because the energy and time overhead for switching dvs modes is considered too large and difficult to manage within a single program.in this paper we explore the opportunities and limits of compile-time dvs scheduling. we derive an analytical model for the maximum energy savings that can be obtained using dvs given a few known program and processor parameters. we use this model to determine scenarios where energy consumption benefits from compile-time dvs and those where there is no benefit. the model helps us extrapolate the benefits of compile-time dvs into the future as processor parameters change. we then examine how much of these predicted benefits can actually be achieved through optimal settings of dvs modes. this is done by extending the existing mixed-integer linear program (milp) formulation for this problem by accurately accounting for dvs energy switching overhead, by providing finer-grained control on settings and by considering multiple data categories in the optimization. overall, this research provides a comprehensive view of compile-time dvs management, providing both practical techniques for its immediate deployment as well theoretical bounds for use into the future.
spl: a language and compiler for dsp algorithms. we discuss the design and implementation of a compiler that translates formulas representing signal processing transforms into efficient c or fortran programs. the formulas are represented in a language that we call spl, an acronym from signal processing language. the compiler is a component of the spiral system which makes use of formula transformations and intelligent search strategies to automatically generate optimized digital signal processing (dsp) libraries. after a discussion of the translation and optimization techniques implemented in the compiler, we use spl formulations of the fast fourier transform (fft) to evaluate the compiler. our results show that spiral, which can be used to implement many classes of algorithms, produces programs that perform as well as &ldquo;hard-wired&rdquo; systems like fftw.
a serializability violation detector for shared-memory server programs. we aim to improve reliability of multithreaded programs by proposing a dynamic detector that detects potentially erroneous program executions and their causes. we design and evaluate a serializability violation detector (svd) that has two unique goals: (i) triggering automatic recovery from erroneous executions using backward error recovery (ber), or simply alerting users that a software error may have occurred; and (ii) helping debug programs by revealing causes of error symptoms.two properties of svd help in achieving these goals. first, to detect only erroneous executions, svd checks serializability of atomic regions, which are code regions that need to be executed atomically. second, to improve usability, svd does not require a priori annotations of atomic regions; instead, svd approximates them using a heuristic. experimental results on three widely-used multithreaded server programs show that svd finds real bugs and reports modest false positives. the goal of this paper is to develop a detector suitable for (i) ber-based avoidance of erroneous program executions; and (ii) alerting users as software errors occur. we argue that such a detector should have the following two properties.
safety checking of machine code. we show how to determine statically whether it is safe for untrusted machine code to be loaded into a trusted host system. our safety-checking technique operates directly on the untrusted machine-code program, requiring only that the initial inputs to the untrusted program be annotated with typestate information and linear constraints. this approach opens up the possibility of being able to certify code produced by any compiler from any source language, which gives the code producers more freedom in choosing the language in which they write their programs. it eliminates the dependence of safety on the correctness of the compiler because the final product of the compiler is checked. it leads to the decoupling of the safety policy from the language in which the untrusted code is written, and consequently, makes it possible for safety checking to be performed with respect to an extensible set of safety properties that are specified on the host side. we have implemented a prototype safety checker for sparc machine-language programs, and applied the safety checker to several examples. the safety checker was able to either prove that an example met the necessary safety conditions, or identify the places where the safety conditions were violated. the checking times ranged from less than a second to 14 seconds on an ultrasparc machine.
verifying safety properties using separation and heterogeneous abstractions. in this paper, we show how separation (decomposing a verification problem into a collection of verification subproblems) can be used to improve the efficiency and precision of verification of safety properties. we present a simple language for specifying separation strategies for decomposing a single verification problem into a set of subproblems. (the strategy specification is distinct from the safety property specification and is specified separately.) we present a general framework of heterogeneous abstraction that allows different parts of the heap to be abstracted using different degrees of precision at different points during the analysis. we show how the goals of separation (i.e., more efficient verification) can be realized by first using a separation strategy to transform (instrument) a verification problem instance (consisting of a safety property specification and an input program), and by then utilizing heterogeneous abstraction during the verification of the transformed verification problem.
improving performance by branch reordering. the conditional branch has long been considered an expensive operation. the relative cost of conditional branches has increased as recently designed machines are now relying on deeper pipelines and higher multiple issue. reducing the number of conditional branches executed can often result in a substantial performance benefit. this paper describes a code-improving transformation to reorder sequences of conditional branches. first, sequences of branches that can be reordered are detected in the control flow. second, profiling information is collected to predict the probability that each branch will transfer control out of the sequence. third, the cost of performing each conditional branch is estimated. fourth, the most beneficial ordering of the branches based on the estimated probability and cost is selected. the most beneficial ordering often included the insertion of additional conditional branches that did not previously exist in the sequence. finally, the control flow is restructured to refflect the new ordering. the results of applying the transformation were significant reductions in the dynamic number of instructions and branches, as well as decreases in execution time.
inc: a language for incremental computations. an incremental computation is one that is performed repeatedly on nearly identical inputs. incremental computations occur naturally in many environments, such as compilers, language-based editors, spreadsheets, and formatters. this article describes a proposed tool for making it easy to write incremental programs. the tool consists of a programming language, inc, and a set of compile-time transformations for the primitive elements of inc. a programmer defines an algorithm in inc without regard to efficient incremental execution. the transformations automatically convert this algorithm into an efficient incremental algorithm. inc is a functional language. the implementation of an inc program is a network of processes. each inc function is transformed into a process that receives and transmits messages describing changes to its inputs and outputs. we give an overview to the language and illustrate the incremental techniques employed by inc. we present the static and incremental complexity bounds for the primitive inc functions. we also present some example programs illustrating inc's flexibility.
transforming loops to recursion for multi-level memory hierarchies. recently, there have been several experimental and theoretical results showing significant performance benefits of recursive algorithms on both multi-level memory hierarchies and on shared-memory systems. in particular, such algorithms have the data reuse characteristics of a blocked algorithm that is simultaneously blocked at many different levels. most existing applications, however, are written using ordinary loops. we present a new compiler transformation that can be used to convert loop nests into recursive form automatically. we show that the algorithm is fast and effective, handling loop nests with arbitrary nesting and control flow. the transformation achieves substantial performance improvements for several linear algebra codes even on a current system with a two level cache hierarchy. as a side-effect of this work, we also develop an improved algorithm for transitive dependence analysis (a powerful technique used in the recursion transformation and other loop transformations)that is much faster than the best previously known algorithm in practice.
pointer analysis for programs with structures and casting. type casting allows a program to access an object as if it had a type different from its declared type. this complicates the design of a pointer-analysis algorithm that treats structure fields as separate objects; therefore, some previous pointer-analysis algorithms "collapse" a structure into a single variable. the disadvantage of this approach is that it can lead to very imprecise points-to information. other algorithms treat each field as a separate object based on its offset and size. while this approach leads to more precise results, the results are not portable because the memory layout of structures is implementation dependent.this paper first describes the complications introduced by type casting, then presents a tunable pointer-analysis framework for handling structures in the presence of casting. different instances of this framework produce algorithms with different levels of precision, portability, and efficiency. experimental results from running our implementations of four instances of this framework show that (i) it is important to distinguish fields of structures in pointer analysis, but (ii) making conservative approximations when casting is involved usually does not cost much in terms of time, space, or the precision of the results.
a comparison of empirical and model-driven optimization. empirical program optimizers estimate the values of key optimization parameters by generating different program versions and running them on the actual hardware to determine which values give the best performance. in contrast, conventional compilers use models of programs and machines to choose these parameters. it is widely believed that model-driven optimization does not compete with empirical optimization, but few quantitative comparisons have been done to date. to make such a comparison, we replaced the empirical optimization engine in atlas (a system for generating a dense numerical linear algebra library called the blas) with a model-driven optimization engine that used detailed models to estimate values for optimization parameters, and then measured the relative performance of the two systems on three different hardware platforms. our experiments show that model-driven optimization can be surprisingly effective, and can generate code whose performance is comparable to that of code generated by empirical optimizers for the blas.
improved spill code generation for software pipelined loops. software pipelining is a loop scheduling technique that extracts parallelism out of loops by overlapping the execution of several consecutive iterations. due to the overlapping of iterations, schedules impose high register requirements during their execution. a schedule is valid if it requires at most the number of registers available in the target architecture. if not, its register requirements have to be reduced either by decreasing the iteration overlapping or by spilling registers to memory. in this paper we describe a set of heuristics to increase the quality of register-constrained modulo schedules. the heuristics decide between the two previous alternatives and define criteria for effectively selecting spilling candidates. the heuristics proposed for reducing the register pressure can be applied to any software pipelining technique. the proposals are evaluated using a register-conscious software pipeliner on a workbench composed of a large set of loops from the perfect club benchmark and a set of processor configurations. proposals in this paper are compared against a previous proposal already described in the literature. for one of these processor configurations and the set of loops that do not fit in the available registers (32), a speed-up of 1.68 and a reduction of the memory traffic by a factor of 0.57 are achieved with an affordable increase in compilation time. for all the loops, this represents a speed-up of 1.38 and a reduction of the memory traffic by a factor of 0.7.
timestamped whole program path representation and its applications. a whole program path (wpp) is a complete control flow trace of a program's execution. recently larus [18] showed that although wpp is expected to be very large (100's of mbytes), it can be greatly compressed (to 10's of mbytes) and therefore saved for future analysis. while the compression algorithm proposed by larus is highly effective, the compression is accompanied with a loss in the ease with which subsets of information can be accessed. in particular, path traces pertaining to a particular function cannot generally be obtained without examining the entire compressed wpp representation. to solve this problem we advocate the application of compaction techniques aimed at providing easy access to path traces on a per function basis. we present a wpp compaction algorithm in which the wpp is broken in to path traces corresponding to individual function calls. all of the path traces for a given function are stored together as a block. ability to construct the complete wpp from individual path traces is preserved by maintaining a dynamic call graph. the compaction is achieved by eliminating redundant path traces that result from different calls to a function and by replacing a sequence of static basic block ids that correspond to a dynamic basic block by a single id. we transform a compacted wpp representation into a timestamped wpp (twpp) representation in which the path traces are organized from the perspective of dynamic basic blocks. twpp representation also offers additional opportunities for compaction. experiments show that our algorithm compacts the wpps by factors ranging from 7 to 64. at the same time information is organized in a highly accessible form which speeds up the responses to queries requesting the path traces of a given function by over 3 orders of magnitude.
cost effective dynamic program slicing. although dynamic program slicing was first introduced to aid in user level debugging, applications aimed at improving software quality, reliability, security, and performance have since been identified as candidates for using dynamic slicing. however, the dynamic dependence graph constructed to compute dynamic slices can easily cause slicing algorithms to run out of memory for realistic program runs. in this paper we present the design and evaluation of a cost effective dynamic program slicing algorithm. this algorithm is based upon a dynamic dependence graph representation that is highly compact and rapidly traversable. thus, the graph can be held in memory and dynamic slices can be quickly computed. a compact representation is derived by recognizing that all dynamic dependences (data and control) need not be individually represented. we identify sets of dynamic dependence edges between a pair of statements that can share a single representative edge. we further show that the dependence graph can be transformed in a manner that increases sharing and sharing can be performed even in the presence of aliasing. experiments show that transformed dynamic dependence graphs explicitly represent only 6% of the dependence edges present in the full dynamic dependence graph. when the full graph sizes range from 0.84 to 1.95 gigabytes in size, our compacted graphs range from 20 to 210 megabytes in size. average slicing times for our algorithm range from 1.74 to 36.25 seconds across several benchmarks from specint2000/95.
pruning dynamic slices with confidence. given an incorrect value produced during a failed program run (e.g., a wrong output value or a value that causes the program to crash), the backward dynamic slice of the value very frequently captures the faulty code responsible for producing the incorrect value. although the dynamic slice often contains only a small percentage of the statements executed during the failed program run, the dynamic slice can still be large and thus considerable effort may be required by the programmer to locate the faulty code.in this paper we develop a strategy for pruning the dynamic slice to identify a subset of statements in the dynamic slice that are likely responsible for producing the incorrect value. we observe that some of the statements used in computing the incorrect value may also have been involved in computing correct values (e.g., a value produced by a statement in the dynamic slice of the incorrect value may also have been used in computing a correct output value prior to the incorrect value). for each such executed statement in the dynamic slice, using the value profiles of the executed statements, we compute a confidence value ranging from 0 to 1 - a higher confidence value corresponds to greater likelihood that the execution of the statement produced a correct value. given a failed run involving execution of a single error, we demonstrate that the pruning of a dynamic slice by excluding only the statements with the confidence value of 1 is highly effective in reducing the size of the dynamic slice while retaining the faulty code in the slice. our experiments show that the number of distinct statements in a pruned dynamic slice are 1.79 to 190.57 times less than the full dynamic slice. confidence values also prioritize the statements in the dynamic slice according to the likelihood of them being faulty. we show that examining the statements in the order of increasing confidence values is an effective strategy for reducing the effort of fault location.
array regrouping and structure splitting using whole-program reference affinity. while the memory of most machines is organized as a hierarchy, program data are laid out in a uniform address space. this paper defines a model of reference affinity, which measures how close a group of data are accessed together in a reference trace. it proves that the model gives a hierarchical partition of program data. at the top is the set of all data with the weakest affinity. at the bottom is each data element with the strongest affinity. based on the theoretical model, the paper presents k-distance analysis, a practical test for the hierarchical affinity of source-level data. when used for array regrouping and structure splitting, k-distance analysis consistently outperforms data organizations given by the programmer, compiler analysis, frequency profiling, statistical clustering, and all other methods we have tried.
symbolic pointer analysis revisited. pointer analysis is a critical problem in optimizing compiler, parallelizing compiler, software engineering and most recently, hardware synthesis. while recent efforts have suggested symbolic method, which uses bryant's binary decision diagram as an alternative to capture the point-to relation, no speed advantage has been demonstrated for context-insensitive analysis, and results for context-sensitive analysis are only preliminary.in this paper, we refine the concept of symbolic transfer function proposed earlier and establish a common framework for both context-insensitive and context-sensitive pointer analysis. with this framework, our transfer function of a procedure can abstract away the impact of its callers and callees, and represent its point-to information completely, compactly and canonically. in addition, we propose a symbolic representation of the invocation graph, which can otherwise be exponentially large. in contrast to the classical frameworks where context-sensitive point-to information of a procedure has to be obtained by the application of its transfer function exponentially many times, our method can obtain point-to information of all contexts in a single application. our experimental evaluation on a wide range of c benchmarks indicates that our context-sensitive pointer analysis can be made almost as fast as its context-insensitive counterpart.
communication optimizations for parallel c programs. this paper presents algorithms for reducing the communication overhead for parallel c programs that use dynamically-allocated data structures. the framework consists of an analysis phase called possible-placement analysis, and a transformation phase called communication selection.the fundamental idea of possible-placement analysis is to find all possible points for insertion of remote memory operations. remote reads are propagated upwards, whereas remote writes are propagated downwards. based on the results of the possible-placement analysis, the communication selection transformation selects the "best" place for inserting the communication, and determines if pipelining or blocking of communication should be performed.the framework has been implemented in the earth-mccat optimizing/parallelizing c compiler, and experimental results are presented for five pointer-intensive benchmarks running on the earth-manna distributed-memory parallel architecture. these experiments show that the communication optimization can provide performance improvements of up to 16% over the unoptimized benchmarks.
balancing register allocation across threads for a multithreaded network processor. modern network processors employ multi-threading to allow concurrency amongst multiple packet processing tasks. we studied the properties of applications running on the network processors and observed that their imbalanced register requirements across different threads at different program points could lead to poor performance. many times application needs demand some threads to be more performance critical than others and thus by controlling the register allocation across threads one could impact the performance of the threads and get the desired performance properties for concurrent threads. this prompts our work.our register allocator aims to distribute available registers to different threads according to their needs. the compiler analyzes the register needs of each thread both at the point of a context switch as well as internally. compiler then designates some registers as shared and some as private to each thread. shared registers are allocated across all threads explicitly by the compiler. values that are live across a context switch can not be kept in shared registers due to safety reasons; thus, only those live ranges that are internal to the context switch can be safely allocated to shared registers. spill can cause a context switch. and thus, the problems of context switch and allocation are closely coupled and we propose a solution to this problem. the proposed interference graphs (gig,big,iig) distinguish variables that must use a thread's private registers from those that can use shared registers. we first estimate the register requirement bounds, then reduce from the upper bound gradually to achieve a good register balance among threads. to reduce the register needs, move insertions are inserted at program points that split the live ranges or the nodes on the interference graph. we show that the lower bound is reachable via live range splitting and is adequate for our benchmark programs for simultaneously assigning them on different threads. as our objective, the number of move instructions is minimized.empirical results show that the compiler is able to effectively control the register allocation across threads by maximizing the number of shared registers. speed-up for performance critical threads ranges from 18 to 24% whereas degradation for performance of non-critical threads ranges only from 1 to 4%.
differential register allocation. micro-architecture designers are very cautious about expanding the number of architected registers (also the register field), because increasing the register field adds to the code size, raises i-cache and memory pressure, complicates processor pipeline. especially for low-end processors, encoding space could be extremely limited due to area and power considerations. on the other hand, the number of architected registers exposed to the compiler could directly affect the effectiveness of compiler analysis and optimization. for high performance computers, register pressure can be higher than the available registers in some regions, e.g. due to optimizations like aggressive function inlining, software pipelining etc. the compiler cannot effectively perform compilation and optimization if only a small number of registers are exposed through the isa. therefore, it is crucial that more architected registers are available at the compiler's disposal without expanding the code size significantly.in this paper, we look at a new register encoding scheme called differential encoding that allows more registers to be addressed in the operand field of instructions than the direct encoding currently being used. we show it can be implemented with very low overhead. based upon differential encoding, we apply it in several ways such that the extra architected registers can benefit the performance. three schemes are devised to integrate differential encoding with register allocation. we demonstrate that differential register allocation is helpful in improving the performance of both high-end and low-end processors. moreover, we can combine it with software pipelining to provide more registers and reduce spills.our results show that differential encoding significantly reduces the number of spills and speeds up program execution. for a low-end configuration, we achieve over 12% speedup while keeping code size almost unaffected. for optimization on loops, it significantly speeds up loops with high register pressure (over 70% speedup).
accurate, efficient, and adaptive calling context profiling. calling context profiles are used in many inter-procedural code optimizations and in overall program understanding. unfortunately, the collection of profile information is highly intrusive due to the high frequency of method calls in most applications. previously proposed calling-context profiling mechanisms consequently suffer from either low accuracy, high overhead, or both. we have developed a new approach for building the calling context tree at runtime, called adaptive bursting. by selectively inhibiting redundant profiling, this approach dramatically reduces overhead while preserving profile accuracy. we first demonstrate the drawbacks of previously proposed calling context profiling mechanisms. we show that a low-overhead solution using sampled stack-walking alone is less than 50% accurate, based on degree of overlap with a complete calling-context tree. we also show that a static bursting approach collects a highly accurate profile, but causes an unacceptable application slowdown. our adaptive solution achieves 85% degree of overlap and provides an 88% hot-edge coverage when using a 0.1 hot-edge threshold, while dramatically reducing overhead compared to the static bursting approach.
towards locating execution omission errors. execution omission errors are known to be difficult to locate using dynamic analysis. these errors lead to a failure at runtime because of the omission of execution of some statements that would have been executed if the program had no errors. since dynamic analysis is typically designed to focus on dynamic information arising from executed statements, and statements whose execution is omitted do not produce dynamic information, detection of execution omission errors becomes a challenging task. for example, while dynamic slices are very effective in capturing faulty code for other types of errors, they fail to capture faulty code in presence of execution omission errors. to address this issue relevant slices have been defined to consider certain static dependences (called potential dependences) in addition to dynamic dependences. however, due to the conservative nature of static analysis, overly large slices are produced. in this paper, we propose a fully dynamic solution to locating execution omission errors using dynamic slices. we introduce the notion of implicit dependences which are dependences that are normally invisible to dynamic slicing due to the omission of execution of some statements. we design a dynamic method that forces the execution of the omitted code by switching outcomes of relevant predicates such that those implicit dependences are exposed and become available for dynamic slicing. dynamic slices can be computed and effectively pruned to produce fault candidate sets containing the execution omission errors. we solve two main problems: verifying the existence of a single implicit dependence through predicate switching, and recovering the implicit dependences in a demand driven manner such that a small number of verifications are required before the root cause is captured. our experiments show that the proposed technique is highly effective in capturing execution omission errors.
type-preserving compilation for large-scale optimizing object-oriented compilers. type-preserving compilers translate well-typed source code, such as java or c#, into verifiable target code, such as typed assembly language or proof-carrying code. this paper presents the implementation of type-preserving compilation in a complex, large-scale optimizing compiler. compared to prior work, this implementation supports extensive optimizations, and it verifies a large portion of the interface between the compiler and the runtime system. this paper demonstrates the practicality of type-preserving compilation in complex optimizing compilers: the generated typed assembly language is only 2.3% slower than the base compiler's generated untyped assembly language, and the type-preserving compiler is 82.8% slower than the base compiler.
profile-driven energy reduction in network-on-chips. reducing energy consumption of a network-on-chip (noc) is a critical design goal, especially for power-constrained embedded systems.in response, prior research has proposed several circuit/architectural level mechanisms to reduce noc power consumption. this paper considers the problem from a different perspective and demonstrates that compiler analysis can be very helpful for enhancing the effectiveness of a hardware-based link power management mechanism by increasing the duration of communication links' idle periods. the proposed profile-based approach achieves its goal by maximizing the communication link reuse through compiler-directed, static message re-routing. that is, it clusters the required data communications into a small set of communication links at any given time, which increases the idle periods for the remaining communication links in the network. this helps hardware shut down more communication links and their corresponding buffers to reduce leakage power. the current experimental evaluation, with twelve data-intensive embedded applications, shows that the proposed profile-driven compiler approach reduces leakage energy by more than 35% (on average) as compared to a pure hardware-based link power management scheme.
xmem: type-safe, transparent, shared memory for cross-runtime communication and coordination. developers commonly build contemporary enterprise applications using type-safe, component-based platforms, such as j2ee, and architect them to comprise multiple tiers, such as a web container, application server, and database engine. administrators increasingly execute each tier in its own managed runtime environment (mre) to improve reliability and to manage system complexity through the fault containment and modularity offered by isolated mre instances. such isolation, however, necessitates expensive cross-tier communication based on protocols such as object serialization and remote procedure calls. administrators commonly co-locate communicating mres on a single host to reduce communication overhead and to better exploit increasing numbers of available processing cores. however, state-of-the-art mres offer no support for more efficient communication between co-located mres, while fast inter-process communication mechanisms, such as shared memory, are widely available as a standard operating system service on most modern platforms. to address this growing need, we present the design and implementation of xmem ? type-safe, transparent, shared memory support for co-located mres. xmem guarantees type-safety through coordinated, parallel, multi-process class loading and garbage collection. to avoid introducing any level of indirection, xmem manipulates virtual memory mapping. in addition, object sharing in xmem is fully transparent: shared objects are identical to local objects in terms of field access, synchronization, garbage collection, and method invocation, with the only difference being that sharedto-private pointers are disallowed. xmem facilitates easy integration and use by existing communication technologies and software systems, such as rmi, jndi, jdbc, serialization/xml, and network sockets. we have implemented xmem in the open-source, productionquality hotspot java virtual machine. our experimental evaluation, based on core communication technologies underlying j2ee, as well as using open-source server applications, indicates that xmem significantly improves throughput and response time by avoiding the overheads imposed by object serialization and network communication.
improved error reporting for software that uses black-box components. an error occurs when software cannot complete a requested action as a result of some problem with its input, configuration, or environment. a high-quality error report allows a user to understand and correct the problem. unfortunately, the quality of error reports has been decreasing as software becomes more complex and layered. end-users take the cryptic error messages given to them by programsand struggle to fix their problems using search engines and support websites. developers cannot improve their error messages when they receive an ambiguous or otherwise insufficient error indicator from a black-box software component. we introduce clarify, a system that improves error reporting by classifying application behavior. clarify uses minimally invasive monitoring to generate a behavior profile, which is a summary of the program's execution history. a machine learning classifier uses the behavior profile to classify the application's behavior, thereby enabling a more precise error report than the output of the application itself. we evaluate a prototype clarify system on ambiguous error messages generated by large, modern applications like gcc, la-tex, and the linux kernel. for a performance cost of less than 1% on user applications and 4.7% on the linux kernel, the proto type correctly disambiguates at least 85% of application behaviors that result in ambiguous error reports. this accuracy does not degrade significantly with more behaviors: a clarify classifier for 81 la-tex error messages is at most 2.5% less accurate than a classifier for 27 latex error messages. finally, we show that without any human effort to build a classifier, clarify can provide nearest-neighbor software support, where users who experience a problem are told about 5 other users who might have had the same problem. on average 2.3 of the 5 users that clarify identifies have experienced the same problem.
online optimizations driven by hardware performance monitoring. hardware performance monitors provide detailed direct feedback about application behavior and are an additional source of infor-mation that a compiler may use for optimization. a jit compiler is in a good position to make use of such information because it is running on the same platform as the user applications. as hardware platforms become more and more complex, it becomes more and more difficult to model their behavior. profile information that captures general program properties (like execution frequency of methods or basic blocks) may be useful, but does not capture sufficient information about the execution platform. machine-level performance data obtained from a hardware performance monitor can not only direct the compiler to those parts of the program that deserve its attention but also determine if an optimization step actually improved the performance of the application. this paper presents an infrastructure based on a dynamic compiler+runtime environment for java that incorporates machine-level information as an additional kind of feedback for the compiler and runtime environment. the low-overhead monitoring system provides fine-grained performance data that can be tracked back to individual java bytecode instructions. as an example, the paper presents results for object co-allocation in a generational garbage collector that optimizes spatial locality of objects on-line using measurements about cache misses. in the best case, the execution time is reduced by 14% and l1 cache misses by 28%.
sound, complete and scalable path-sensitive analysis. we present a new, precise technique for fully path- and context-sensitive program analysis. our technique exploits two observations: first, using quantified, recursive formulas, path- and context-sensitive conditions for many program properties can be expressed exactly. to compute a closed form solution to such recursive constraints, we differentiate between observable and unobservable variables, the latter of which are existentially quantified in our approach. using the insight that unobservable variables can be eliminated outside a certain scope, our technique computes satisfiability- and validity-preserving closed-form solutions to the original recursive constraints. we prove the solution is as precise as the original system for answering may and must queries as well as being small in practice, allowing our technique to scale to the entire linux kernel, a program with over 6 million lines of code.
automatic volume management for programmable microfluidics. microfluidics has enabled lab-on-a-chip technology to miniaturize and integrate biological and chemical analyses to a single chip comprising channels, valves, mixers, heaters, separators, and sensors. recent papers have proposed programmable labs-on-a-chip as an alternative to traditional application-specific chips to reduce design effort, time, and cost. while these previous papers provide the basic support for programmability, this paper identifies and addresses a practical issue, namely, fluid volume management. volume management addresses the problem that the use of a fluid depletes it and unless the given volume of a fluid is distributed carefully among all its uses, execution may run out of the fluid before all its uses are complete. additionally, fluid volumes should not overflow (i.e., exceed hardware capacity) or underflow (i.e., fall below hardware resolution). we show that the problem can be formulated as a linear programming problem (lp). because lp's complexity and slow execution times in practice may be a concern, we propose another approach, called dagsolve, which over-constrains the problem to achieve linear complexity while maintaining good solution quality. we also propose two optimizations, called cascading and static replication, to handle cases involving extreme mix ratios and numerous fluid uses which may defeat both lp and dagsolve. using some real-world assays, we show that our techniques produce good solutions while being faster than lp.
dataflow analysis for concurrent programs using datarace detection. dataflow analyses for concurrent programs differ from their single-threaded counterparts in that they must account for shared memory locations being overwritten by concurrent threads. existing dataflow analysis techniques for concurrent programs typically fall at either end of a spectrum: at one end, the analysis conservatively kills facts about all data that might possibly be shared by multiple threads; at the other end, a precise thread-interleaving analysis determines which data may be shared, and thus which dataflow facts must be invalidated. the former approach can suffer from imprecision, whereas the latter does not scale. we present radar, a framework that automatically converts a dataflow analysis for sequential programs into one that is correct for concurrent programs. radar uses a race detection engine to kill the dataflow facts, generated and propagated by the sequential analysis, that become invalid due to concurrent writes. our approach of factoring all reasoning about concurrency into a race detection engine yields two benefits. first, to obtain analyses for code using new concurrency constructs, one need only design a suitable race detection engine for the constructs. second, it gives analysis designers an easy way to tune the scalability and precision of the overall analysis by only modifying the race detection engine. we describe the radar framework and its implementation using a pre-existing race detection engine. we show how radar was used to generate a concurrent version of a null-pointer dereference analysis, and we analyze the result of running the generated concurrent analysis on several benchmarks.
efficient program execution indexing. execution indexing uniquely identifies a point in an execution. desirable execution indices reveal correlations between points in an execution and establish correspondence between points across multiple executions. therefore, execution indexing is essential for a wide variety of dynamic program analyses, for example, it can be used to organize program profiles; it can precisely identify the point in a re-execution that corresponds to a given point in an original execution and thus facilitate debugging or dynamic instrumentation. in this paper, we formally define the concept of execution index and propose an indexing scheme based on execution structure and program state. we present a highly optimized online implementation of the technique. we also perform a client study, which targets producing a failure inducing schedule for a data race by verifying the two alternative happens-before orderings of a racing pair. indexing is used to precisely locate corresponding points across multiple executions in the presence of non-determinism so that no heavyweight tracing/replay system is needed.
inferring locks for atomic sections. atomic sections are a recent and popular idiom to support the development of concurrent programs. updates performed within an atomic section should not be visible to other threads until the atomic section has been executed entirely. traditionally, atomic sections are supported through the use of optimistic concurrency, either using a transactional memory hardware, or an equivalent software emulation (stm). this paper explores automatically supporting atomic sections using pessimistic concurrency. we present a system that combines compiler and runtime techniques to automatically transform programs written with atomic sections into programs that only use locking primitives. to minimize contention in the transformed programs, our compiler chooses from several lock granularities, using fine-grain locks whenever it is possible. this paper formally presents our framework, shows that our compiler is sound (i.e., it protects all shared locations accessed within atomic sections), and reports experimental results.
a study of concurrent real-time garbage collectors. concurrent garbage collection is highly attractive for real-time systems, because offloading the collection effort from the executing threads allows faster response, allowing for extremely short deadlines at the microseconds level. concurrent collectors also offer much better scalability over incremental collectors. the main problem with concurrent real-time collectors is their complexity. the first concurrent real-time garbage collector that can support fine synchronization, stopless, has recently been presented by pizlo et al. in this paper, we propose two additional (and different) algorithms for concurrent real-time garbage collection: clover and chicken. both collectors obtain reduced complexity over the first collector stopless, but need to trade a benefit for it. we study the algorithmic strengths and weaknesses of clover and chicken and compare them to stopless. finally, we have implemented all three collectors on the bartok compiler and runtime for c# and we present measurements to compare their efficiency and responsiveness.
deriving linearizable fine-grained concurrent objects. practical and efficient algorithms for concurrent data structures are difficult to construct and modify. algorithms in the literature are often optimized for a specific setting, making it hard to separate the algorithmic insights from implementation details. the goal of this work is to systematically construct algorithms for a concurrent data structure starting from its sequential implementation. towards that goal, we follow a construction process that combines manual steps corresponding to high-level insights with automatic exploration of implementation details. to assist us in this process, we built a new tool called paraglider. the tool quickly explores large spaces of algorithms and uses bounded model checking to check linearizability of algorithms. starting from a sequential implementation and assisted by the tool, we present the steps that we used to derive various highly-concurrent algorithms. among these algorithms is a new fine-grained set data structure that provides a wait-free contains operation, and uses only the compare-and-swap (cas) primitive for synchronization.
exochi: architecture and programming environment for a heterogeneous multi-core multithreaded system. future mainstream microprocessors will likely integrate specialized accelerators, such as gpus, onto a single die to achieve better performance and power efficiency. however, it remains a keen challenge to program such a heterogeneous multicore platform, since these specialized accelerators feature isas and functionality that are significantly different from the general purpose cpu cores. in this paper, we present exochi: (1) exoskeleton sequencer(exo), an architecture to represent heterogeneous acceleratorsas isa-based mimd architecture resources, and a shared virtual memory heterogeneous multithreaded program execution model that tightly couples specialized accelerator cores with generalpurpose cpu cores, and (2) c for heterogeneous integration(chi), an integrated c/c++ programming environment that supports accelerator-specific inline assembly and domain-specific languages. the chi compiler extends the openmp pragma for heterogeneous multithreading programming, and produces a single fat binary with code sections corresponding to different instruction sets. the runtime can judiciously spread parallel computation across the heterogeneous cores to optimize performance and power. we have prototyped the exo architecture on a physical heterogeneous platform consisting of an intel® core™ 2 duo processor and an 8-core 32-thread intel® graphics media accelerator x3000. in addition, we have implemented the chi integrated programming environment with the intel® c++ compiler, runtime toolset, and debugger. on the exo prototype system, we have enhanced a suite of production-quality media kernels for video and image processing to utilize the accelerator through the chi programming interface, achieving significant speedup (1.41x to10.97x) over execution on the ia32 cpu alone.
sound and precise analysis of web applications for injection vulnerabilities. web applications are popular targets of security attacks. one common type of such attacks is sql injection, where an attacker exploits faulty application code to execute maliciously crafted database queries. bothstatic and dynamic approaches have been proposed to detect or prevent sql injections; while dynamic approaches provide protection for deployed software, static approaches can detect potential vulnerabilities before software deployment. previous static approaches are mostly based on tainted information flow tracking and have at least some of the following limitations: (1) they do not model the precise semantics of input sanitization routines; (2) they require manually written specifications, either for each query or for bug patterns; or (3) they are not fully automated and may require user intervention at various points in the analysis. in this paper, we address these limitations by proposing a precise, sound, and fully automated analysis technique for sql injection. our technique avoids the need for specifications by consideringas attacks those queries for which user input changes the intended syntactic structure of the generated query. it checks conformance to this policy byconservatively characterizing the values a string variable may assume with a context free grammar, tracking the nonterminals that represent user-modifiable data, and modeling string operations precisely as language transducers. we have implemented the proposed technique for php, the most widely-used web scripting language. our tool successfully discovered previously unknown and sometimes subtle vulnerabilities in real-world programs, has a low false positive rate, and scales to large programs (with approx. 100k loc).
immix: a mark-region garbage collector with space efficiency, fast collection, and mutator performance. programmers are increasingly choosing managed languages for modern applications, which tend to allocate many short-to-medium lived small objects. the garbage collector therefore directly determines program performance by making a classic space-time tradeoff that seeks to provide space efficiency, fast reclamation, and mutator performance. the three canonical tracing garbage collectors: semi-space, mark-sweep, and mark-compact each sacrifice one objective. this paper describes a collector family, called mark-region, and introduces opportunistic defragmentation, which mixes copying and marking in a single pass. combining both, we implement immix, a novel high performance garbage collector that achieves all three performance objectives. the key insight is to allocate and reclaim memory in contiguous regions, at a coarse block grain when possible and otherwise in groups of finer grain lines. we show that immix outperforms existing canonical algorithms, improving total application performance by 7 to 25% on average across 20 benchmarks. as the mature space in a generational collector, immix matches or beats a highly tuned generational collector, e.g. it improves jbb2000 by 5%. these innovations and the identification of a new family of collectors open new opportunities for garbage collector design.
copy coalescing by graph recoloring. register allocation is always a trade-off between live-range splitting and coalescing. live-range splitting generally leads to less spilling at the cost of inserting shuffle code. coalescing removes shuffle code while potentially raising the register demand and causing spilling. recent research showed that the live-range splitting of the ssa form's æ-functions leads to chordal interference graphs. this improves upon two long-standing inconveniences of graph coloring register allocation: first, chordal graphs are optimally colorable in quadratic time. second, the number of colors needed to color the graph is equal to the maximal register pressure in the program. however, the inserted shuffle code incurred by the æ-functions can slow down the program severely. hence, to make such an approach work in practice, a coalescing technique is needed that removes most of the shuffle code without causing further spilling. in this paper, we present a coalescing technique designed for, but not limited to, ssa-form register allocation. we exploit that a valid coloring can be easily obtained by an ssa-based register allocator. this initial coloring is then improved by recoloring the interference graph and assigning shuffle-code related nodes the same color. thereby, we always keep the coloring of the graph valid. hence, the coalescing is safe, i. e. no spill code will be caused by coalescing. comparing to iterated register coalescing, the state of the art in safe coalescing, our method is able to remove 22.5% of the costs and 44.3% of the copies iterated coalescing left over. the best solution possible, found by a colaescer using integer linear programming (ilp), was 35.9% of the costs and 51.9% of the copies iterated coalescing left over. the runtime of programs compiled with our heuristic matches that of the programs compiled with the ilp technique.
checking race freedom via linear programming. we present a new static analysis for race freedom and race detection. the analysis checks race freedom by reducing the problem to (rational) linear programming. unlike conventional static analyses for race freedom or race detection, our analysis avoids explicit computation of locksets and lock linearity/must-aliasness. our analysis can handle a variety of synchronization idioms that more conventional approaches often have difficulties with, such as thread joining, semaphores, and signals. we achieve efficiency by utilizing modern linear programming solvers that can quickly solve large linear programming instances. this paper reports on the formal properties of the analysis and the experience with applying an implementation to real world c programs.
discovering properties about arrays in simple programs. array bound checking and array dependency analysis (for parallelization) have been widely studied. however, there are much less results about analyzing properties of array contents. in this paper, we propose a way of using abstract interpretation for discovering properties about array contents in some restricted cases: one-dimensional arrays, traversed by simple "for" loops. the basic idea, borrowed from [grs05], consists in partitioning arrays into symbolic intervals (e.g., [1,i -- 1], [i,i], [i + 1,n]), and in associating with each such interval i and each array a an abstract variable ai; the new idea is to consider relational abstract properties ψ(ai, bi, ...) about these abstract variables, and to interpret such a property pointwise on the interval i: ∀l ∈ i, ψ(a[l], b[l],...). the abstract semantics of our simple programs according to these abstract properties has been defined and implemented in a prototype tool. the method is able, for instance, to discover that the result of an insertion sort is a sorted array, or that, in an array traversal guarded by a "sentinel", the index stays within the bounds.
program analysis as constraint solving. a constraint-based approach to invariant generation in programs translates a program into constraints that are solved using off-the-shelf constraint solvers to yield desired program invariants. in this paper we show how the constraint-based approach can be used to model a wide spectrum of program analyses in an expressive domain containing disjunctions and conjunctions of linear inequalities. in particular, we show how to model the problem of context-sensitive interprocedural program verification. we also present the first constraint-based approach to weakest precondition and strongest postcondition inference. the constraints we generate are boolean combinations of quadratic inequalities over integer variables. we reduce these constraints to sat formulae using bitvector modeling and use off-the-shelf sat solvers to solve them. furthermore, we present interesting applications of the above analyses, namely bounds analysis and generation of most-general counter-examples for both safety and termination properties. we also present encouraging preliminary experimental results demonstrating the feasibility of our technique on a variety of challenging examples.
a practical automatic polyhedral parallelizer and locality optimizer. we present the design and implementation of an automatic polyhedral source-to-source transformation framework that can optimize regular programs (sequences of possibly imperfectly nested loops) for parallelism and locality simultaneously. through this work, we show the practicality of analytical model-driven automatic transformation in the polyhedral model -- far beyond what is possible by current production compilers. unlike previous works, our approach is an end-to-end fully automatic one driven by an integer linear optimization framework that takes an explicit view of finding good ways of tiling for parallelism and locality using affine transformations. the framework has been implemented into a tool to automatically generate openmp parallel code from c program sections. experimental results from the tool show very high speedups for local and parallel execution on multi-cores over state-of-the-art compiler frameworks from the research community as well as the best native production compilers. the system also enables the easy use of powerful empirical/iterative optimization for general arbitrarily nested loop sequences.
conditional correlation analysis for safe region-based memory management. region-based memory management is a popular scheme in systems software for better organization and performance. in the scheme, a developer constructs a hierarchy of regions of different lifetimes and allocates objects in regions. when the developer deletes a region, the runtime will recursively delete all its subregions and simultaneously reclaim objects in the regions. the developer must construct a consistent placement of objects in regions; otherwise, if a region that contains pointers to other regions is not always deleted before pointees, an inconsistency will surface and cause dangling pointers, which may lead to either crashes or leaks. this paper presents a static analysis tool regionwiz that can find such lifetime inconsistencies in large c programs using regions. the tool is based on an analysis framework that generalizes the relations and constraints over regions and objects as conditional correlations. this framework allows a succinct formalization of consistency rules for region lifetimes, preserving memory safety and avoiding dangling pointers. regionwiz uses these consistency rules to implement an efficient static analysis to compute the conditional correlation and reason about region lifetime consistency; the analysis is based on a context-sensitive, field-sensitive pointer analysis with heap cloning. experiments with applying regionwiz to six real-world software packages (including the rc compiler, apache web server, and subversion version control system) with two different region-based memory management interfaces show that regionwiz can reason about region lifetime consistency in large c programs. the experiments also show that regionwiz can find several previously unknown inconsistency bugs in these packages.
full functional verification of linked data structures. we present the first verification of full functional correctness for a range of linked data structure implementations, including mutable lists, trees, graphs, and hash tables. specifically, we present the use of the jahob verification system to verify formal specifications, written in classical higher-order logic, that completely capture the desired behavior of the java data structure implementations (with the exception of properties involving execution time and/or memory consumption). given that the desired correctness properties include intractable constructs such as quantifiers, transitive closure, and lambda abstraction, it is a challenge to successfully prove the generated verification conditions. our jahob verification system uses integrated reasoning to split each verification condition into a conjunction of simpler subformulas, then apply a diverse collection of specialized decision procedures, first-order theorem provers, and, in the worst case, interactive theorem provers to prove each subformula. techniques such as replacing complex subformulas with stronger but simpler alternatives, exploiting structure inherently present in the verification conditions, and, when necessary, inserting verified lemmas and proof hints into the imperative source code make it possible to seamlessly integrate all of the specialized decision procedures and theorem provers into a single powerful integrated reasoning system. by appropriately applying multiple proof techniques to discharge different subformulas, this reasoning system can effectively prove the complex and challenging verification conditions that arise in this context.
certifying low-level programs with hardware interrupts and preemptive threads. hardware interrupts are widely used in the world's critical software systems to support preemptive threads, device drivers, operating system kernels, and hypervisors. handling interrupts properly is an essential component of low-level system programming. unfortunately, interrupts are also extremely hard to reason about: they dramatically alter the program control flow and complicate the invariants in low-level concurrent code (e.g., implementation of synchronization primitives). existing formal verification techniques---including hoare logic, typed assembly language, concurrent separation logic, and the assume-guarantee method---have consistently ignored the issues of interrupts; this severely limits the applicability and power of today's program verification systems. in this paper we present a novel hoare-logic-like framework for certifying low-level system programs involving both hardware interrupts and preemptive threads. we show that enabling and disabling interrupts can be formalized precisely using simple ownership-transfer semantics, and the same technique also extends to the concurrent setting. by carefully reasoning about the interaction among interrupt handlers, context switching, and synchronization libraries, we are able to---for the first time---successfully certify a preemptive thread implementation and a large number of common synchronization primitives. our work provides a foundation for reasoning about interrupt-based kernel programs and makes an important advance toward building fully certified operating system kernels and hypervisors.
path invariants. the success of software verification depends on the ability to find a suitable abstraction of a program automatically. we propose a method for automated abstraction refinement which overcomes some limitations of current predicate discovery schemes. in current schemes, the cause of a false alarm is identified as an infeasible error path, and the abstraction is refined in order to remove that path. by contrast, we view the cause of a false alarm -the spurious counterexample- as a full-fledged program, namely, a fragment of the original program whose control-flow graph may contain loops and represent unbounded computations. there are two advantages to using such path programs as counterexamples for abstraction refinement. first, we can bring the whole machinery of program analysis to bear on path programs, which are typically small compared to the original program. specifically, we use constraint-based invariant generation to automatically infer invariants of path programs-so-called path invariants. second, we use path invariants for abstraction refinement in order to remove not one infeasibility at a time, but at once all (possibly infinitely many) infeasible error computations that are represented by a path program. unlike previous predicate discovery schemes, our method handles loops without unrolling them; it infers abstractions that involve universal quantification and naturally incorporates disjunctive reasoning.
checkfence: checking consistency of concurrent data types on relaxed memory models. concurrency libraries can facilitate the development of multi-threaded programs by providing concurrent implementations of familiar data types such as queues or sets. there exist many optimized algorithms that can achieve superior performance on multiprocessors by allowing concurrent data accesses without using locks. unfortunately, such algorithms can harbor subtle concurrency bugs. moreover, they requirememory ordering fences to function correctly on relaxed memory models. to address these difficulties, we propose a verification approach that can exhaustively check all concurrent executions of a given test program on a relaxed memory model and can verify that they are observationally equivalent to a sequential execution. our checkfence prototype automatically translates the c implementation code and the test program into a sat formula, hands the latter to a standard sat solver, and constructs counter example traces if there exist incorrect executions. applying checkfence to five previously published algorithms, we were able to (1) find several bugs (some not previously known), and (2) determine how to place memory ordering fences for relaxed memory models.
certified self-modifying code. self-modifying code (smc), in this paper, broadly refers to anyprogram that loads, generates, or mutates code at runtime. it is widely used in many of the world's critical software systems tosupport runtime code generation and optimization, dynamic loading and linking, os boot loader, just-in-time compilation, binary translation,or dynamic code encryption and obfuscation. unfortunately, smc is alsoextremely difficult to reason about: existing formal verification techniques-including hoare logic and type system-consistentlyassume that program code stored in memory is fixedand immutable; this severely limits their applicability and power. this paper presents a simple but novel hoare-logic-like framework that supports modular verification of general von-neumann machine code with runtime code manipulation. by dropping the assumption that code memory is fixed and immutable, we are forced to apply local reasoningand separation logic at the very beginning, and treat program code uniformly as regular data structure. we address the interaction between separation and code memory and show how to establish the frame rules for local reasoning even in the presence of smc. our frameworkis realistic, but designed to be highly generic, so that it can support assembly code under all modern cpus (including both x86 andmips). our system is expressive and fully mechanized. we prove itssoundness in the coq proof assistant and demonstrate its power by certifying a series of realistic examples and applications-all of which can directly run on the spim simulator or any stock x86 hardware.
practical memory leak detection using guarded value-flow analysis. this paper presents a practical inter-procedural analysis algorithm for detecting memory leaks in c programs. our algorithm tracks the flow of values from allocation points to deallocation points using a sparse representation of the program consisting of a value flow graph that captures def-use relations and value flows via program assignments. edges in the graph are annotated with guards that describe branch conditions in the program. the memory leak analysis is reduced to a reachability problem over the guarded value flowgraph. our implemented tool has been effective at detecting more than 60 memory leaks in the spec2000 benchmarks and in two open-source applications, bash and sshd, while keeping the false positive rate below 20%. the sparse program representation makes the tool efficient in practice, and allows it to report concise error messages.
a certified type-preserving compiler from lambda calculus to assembly language. we present a certified compiler from the simply-typed lambda calculus to assembly language. the compiler is certified in the sense that it comes with a machine-checked proof of semantics preservation, performed with the coq proof assistant. the compiler and the terms of its several intermediate languages are given dependent types that guarantee that only well-typed programs are representable. thus, type preservation for each compiler pass follows without any significant "proofs" of the usual kind. semantics preservation is proved based on denotational semantics assigned to the intermediate languages. we demonstrate how working with a type-preserving compiler enables type-directed proof search to discharge large parts of our proof obligations automatically.
proving thread termination. concurrent programs are often designed such that certain functions executing within critical threads must terminate. examples of such cases can be found in operating systems, web servers, e-mail clients, etc. unfortunately, no known automatic program termination prover supports a practical method of proving the termination of threads. in this paper we describe such a procedure. the procedure's scalability is achieved through the use of environment models that abstract away the surrounding threads. the procedure's accuracy is due to a novel method of incrementally constructing environment abstractions. our method finds the conditions that a thread requires of its environment in order to establish termination by looking at the conditions necessary to prove that certain paths through the thread represent well-founded relations if executed in isolation of the other threads. the paper gives a description of experimental results using an implementation of our procedureon windows device drivers and adescription of a previously unknown bug found withthe tool.
offline compression for on-chip ram. we present offline ram compression, an automated source-to-source transformation that reduces a program's data size. statically allocated scalars, pointers, structures, and arrays are encoded and packed based on the results of a whole-program analysis in the value set and pointer set domains. we target embedded software written in c that relies heavily on static memory allocation and runs on harvard-architecture microcontrollers supporting just a few kb of on-chip ram. on a collection of embedded applications for avr microcontrollers, our transformation reduces ram usage by an average of 12%, in addition to a 10% reduction through a dead-data elimination pass that is also driven by our whole-program analysis, for a total ram savings of 22%. we also developeda technique for giving developers access to a flexible spectrum of tradeoffs between ram consumption, rom consumption, and cpu efficiency. this technique is based on a model for estimating the cost/benefit ratio of compressing each variable and then selectively compressing only those variables that present a good value proposition in terms of the desired tradeoffs.
static error detection using semantic inconsistency inference. inconsistency checking is a method for detecting software errors that relies only on examining multiple uses of a value. we propose that inconsistency inference is best understood as a variant of the older and better understood problem of type inference. using this insight, we describe a precise and formal framework for discovering inconsistency errors. unlike previous approaches to the problem, our technique for finding inconsistency errors is purely semantic and can deal with complex aliasing and path-sensitive conditions. we have built a nullde reference analysis of c programs based on semantic inconsistency inference and have used it to find hundreds of previously unknown null dereference errors in widely used c programs.
software behavior oriented parallelization. many sequential applications are difficult to parallelize because of unpredictable control flow, indirect data access, and input-dependent parallelism. these difficulties led us to build a software system for behavior oriented parallelization (bop), which allows a program to be parallelized based on partial information about program behavior, for example, a user reading just part of the source code, or a profiling tool examining merely one or few executions. the basis of bop is programmable software speculation, where a user or an analysis tool marks possibly parallel regions in the code, and the run-time system executes these regions speculatively. it is imperative to protect the entire address space during speculation. the main goal of the paper is to demonstrate that the general protection can be made cost effective by three novel techniques: programmable speculation, critical-path minimization, and value-based correctness checking. on a recently acquired multi-core, multi-processor pc, the bop system reduced the end-to-end execution time by integer factors for a lisp interpreter, a data compressor, a language parser, and a scientific library, with no change to the underlying hardware or operating system.
goldilocks: a race and transaction-aware java runtime. data races often result in unexpected and erroneous behavior. in addition to causing data corruption and leading programs to crash, the presence of data races complicates the semantics of an execution which might no longer be sequentially consistent. motivated by these observations, we have designed and implemented a java runtime system that monitors program executions and throws a dataraceexception when a data race is about to occur. analogous to other runtime exceptions, the dataraceexception provides two key benefits. first, accesses causing race conditions are interruptedand handled before they cause errors that may be difficult to diagnose later. second, if no dataraceexception is thrown in an execution, it is guaranteed to be sequentially consistent. this strong guarantee helps to rule out many concurrency-related possibilities as the cause of erroneous behavior. when a dataraceexception is caught, the operation, thread, or program causing it can be terminated gracefully. alternatively, the dataraceexception can serve as a conflict-detection mechanism inoptimistic uses of concurrency. we start with the definition of data-race-free executions in the java memory model. we generalize this definition to executions that use transactions in addition to locks and volatile variables for synchronization. we present a precise and efficient algorithm for dynamically verifying that an execution is free of data races. this algorithm generalizes the goldilocks algorithm for data-race detectionby handling transactions and providing the ability to distinguish between read and write accesses. we have implemented our algorithm and the dataraceexception in the kaffe java virtual machine. we have evaluated our system on a variety of publicly available java benchmarks and a few microbenchmarks that combine lock-based and transaction-based synchronization. our experiments indicate that our implementation has reasonable overhead. therefore, we believe that inaddition to being a debugging tool, the dataraceexception may be a viable mechanism to enforce the safety of executions of multithreaded java programs.
liquid types. we present logically qualified data types, abbreviated to liquid types, a system that combines hindley-milner type inference with predicate abstraction to automatically infer dependent types precise enough to prove a variety of safety properties. liquid types allow programmers to reap many of the benefits of dependent types, namely static verification of critical properties and the elimination of expensive run-time checks, without the heavy price of manual annotation. we have implemented liquid type inference in dsolve, which takes as input an ocaml program and a set of logical qualifiers and infers dependent types for the expressions in the ocaml program. to demonstrate the utility of our approach, we describe experiments using dsolve to statically verify the safety of array accesses on a set of ocaml benchmarks that were previously annotated with dependent types as part of the dml project. we show that when used in conjunction with a fixed set of array bounds checking qualifiers, dsolve reduces the amount of manual annotation required for proving safety from 31% of program text to under 1%.
efficient static analysis of xml paths and types. we present an algorithm to solve xpath decision problems under regular tree type constraints and show its use to statically type-check xpath queries. to this end, we prove the decidability of a logic with converse for finite ordered trees whose time complexity is a simple exponential of the size of a formula. the logic corresponds to the alternation free modal μ-calculus without greatest fixpoint, restricted to finite trees, and where formulas are cycle-free. our proof method is based on two auxiliary results. first, xml regular tree types and xpath expressions have a linear translation to cycle-free formulas. second, the least and greatest fixpoints are equivalent for finite trees, hence the logic is closed under negation. building on these results, we describe a practical, effective system for solving the satisfiability of a formula. the system has been experimented with some decision problems such as xpath emptiness, containment, overlap, and coverage, with or without type constraints. the benefit of the approach is that our system can be effectively used in static analyzers for programming languages manipulating both xpath expressions and xml type annotations (as input and output types).
thread-modular shape analysis. we present the first shape analysis for multithreaded programs that avoids the explicit enumeration of execution-interleavings. our approach is to automatically infer a resource invariant associated with each lock that describes the part of the heap protected by the lock. this allows us to use a sequential shape analysis on each thread. we show that resource invariants of a certain class can be characterized as least fixed points and computed via repeated applications of shape analysis only on each individual thread. based on this approach, we have implemented a thread-modular shape analysis tool and applied it to concurrent heap-manipulating code from windows device drivers.
shape analysis with inductive recursion synthesis. separation logic with recursively defined predicates allows for concise yet precise description of the shapes of data structures. however, most uses of separation logic for program analysis rely on pre-defined recursive predicates, limiting the class of programs analyzable to those that manipulate only a priori data structures. this paper describes a general algorithm based on inductive program synthesis that automatically infers recursive shape invariants, yielding a shape analysis based on separation logic that can be applied to any program. a key strength of separation logic is that it facilitates, via explicit expression of structural separation, local reasoning about heap where the effects of altering one part of a data structure are analyzed in isolation from the rest. the interaction between local reasoning and the global invariants given by recursive predicates is a difficult area, especially in the presence of complex internal sharing in the data structures. existing approaches, using logic rules specifically designed for the list predicate to unfold and fold linked-lists, again require a priori knowledge about the shapes of the data structures and do not easily generalize to more complex data structures. we introduce a notion of "truncation points" in a recursive predicate, which gives rise to generic algorithms for unfolding and folding arbitrary data structures.
the ant and the grasshopper: fast and accurate pointer analysis for millions of lines of code. pointer information is a prerequisite for most program analyses, and the quality of this information can greatly affect their precision and performance. inclusion-based (i.e. andersen-style) pointer analysis is an important point in the space of pointer analyses, offering a potential sweet-spot in the trade-off between precision and performance. however, current techniques for inclusion-based pointer analysis can have difficulties delivering on this potential. we introduce and evaluate two novel techniques for inclusion-based pointer analysis---one lazy, one eager1---that significantly improve upon the current state-of-the-art without impacting precision. these techniques focus on the problem of online cycle detection, a critical optimization for scaling such analyses. using a suite of six open-source c programs, which range in size from 169k to 2.17m loc, we compare our techniques against the three best inclusion-based analyses--described by heintze and tardieu [11], by pearce et al. [21], and by berndl et al. [4]. the combination of our two techniques results in an algorithm which is on average 3.2 xfaster than heintze and tardieu's algorithm, 6.4 xfaster than pearce et al.'s algorithm, and 20.6 faster than berndl et al.'s algorithm. we also investigate the use of different data structures to represent points-to sets, examining the impact on both performance and memory consumption. we compare a sparse-bitmap implementation used in the gcc compiler with a bdd-based implementation, and we find that the bdd implementation is on average 2x slower than using sparse bitmaps but uses 5.5x less memory.
quantitative information flow as network flow capacity. we present a new technique for determining how much information about a program's secret inputs is revealed by its public outputs. in contrast to previous techniques based on reachability from secret inputs (tainting), it achieves a more precise quantitative result by computing a maximum flow of information between the inputs and outputs. the technique uses static control-flow regions to soundly account for implicit flows via branches and pointer operations, but operates dynamically by observing one or more program executions and giving numeric flow bounds specific to them (e.g., "17 bits"). the maximum flow in a network also gives a minimum cut (a set of edges that separate the secret input from the output), which can be used to efficiently check that the same policy is satisfied on future executions. we performed case studies on 5 real c, c++, and objective c programs, 3 of which had more than 250k lines of code. the tool checked multiple security policies, including one that was violated by a previously unknown bug.
fair stateless model checking. stateless model checking is a useful state-space exploration technique for systematically testing complex real-world software. existing stateless model checkers are limited to the verification of safety properties on terminating programs. however, realistic concurrent programs are nonterminating, a property that significantly reduces the efficacy of stateless model checking in testing them. moreover, existing stateless model checkers are unable to verify that a nonterminating program satisfies the important liveness property of livelock-freedom, a property that requires the program to make continuous progress for any input. to address these shortcomings, this paper argues for incorporating a fair scheduler in stateless exploration. the key contribution of this paper is an explicit scheduler that is (strongly) fair and at the same time sufficiently nondeterministic to guarantee full coverage of safety properties.we have implemented the fair scheduler in the chess model checker. we show through theoretical arguments and empirical evaluation that our algorithm satisfies two important properties: 1) it visits all states of a finite-state program achieving state coverage at a faster rate than existing techniques, and 2) it finds all livelocks in a finite-state program. before this work, nonterminating programs had to be manually modified in order to apply chess to them. the addition of fairness has allowed chess to be effectively applied to real-world nonterminating programs without any modification. for example, we have successfully booted the singularity operating system under the control of chess.
mace: language support for building distributed systems. building distributed systems is particularly difficult because of the asynchronous, heterogeneous, and failure-prone environment where these systemsmust run. tools for building distributed systems must strike a compromise between reducing programmer effort and increasing system efficiency. we present mace, a c++ language extension and source-to-source compiler that translates a concise but expressive distributed system specification into a c++ implementation. mace overcomes the limitations of low-level languages by providing a unified framework for networking and event handling, and the limitations of high-level languages by allowing programmers to write program components in a controlled and structured manner in c++. by imposing structure and restrictions on how applications can be written, mace supports debugging at a higher level, including support for efficient model checking and causal-path debugging. because mace programs compile to c++, programmers can use existing c++ tools, including optimizers, profilers, and debuggers to analyze their systems.
regularly annotated set constraints. a general class of program analyses area combination of context-free and regular language reachability. we define regularly annotated set constraints, a constraint formalism that captures this class. our results extend the class of reachability problems expressible naturally in a single constraint formalism, including such diverse applications as interprocedural dataflow analysis, precise type-based flow analysis, and pushdown model checking.
reliable and efficient programming abstractions for wireless sensor networks. it is currently difficult to build practical and reliable programming systems out of distributed and resource-constrained sensor devices. the state of the art in today's sensornet programming is centered around a component-based language called nesc. nesc is a node-level language-a program is written for an individual node in the network-and nesc programs use the services of an operating system called tinyos. we are pursuing an approach to programming sensor networks that significantly raises the level of abstraction over this practice. the critical change is one of perspective: rather than writing programs from the point of view of an individual node, programmers implement a central program that conceptually has access to the entire network. this approach pushes to the compiler the task of producing node-level programs that implement the desired behavio. we present the pleiades programming language, its compiler, and its runtime. the pleiades language extends the c language with constructs that allow programmers to name and access node-local state within the network and to specify simple forms of concurrent execution. the compiler and runtime system cooperate to implement pleiades programs efficiently and reliably. first, the compiler employs a novel program analysis to translate pleiades programs into message-efficient units of work implemented in nesc. the pleiades runtime system orchestrates execution of these units, using tinyos services, across a network of sensor nodes. second, the compiler and runtime system employ novel locking, deadlock detection, and deadlock recovery algorithms that guarantee serializability in the face of concurrent execution. we illustrate the readability, reliability and efficiency benefits of the pleiades language through detailed experiments, and demonstrate that the pleiades implementation of a realistic application performs similar to a hand-coded nesc version that contains more than ten times as much code.
expressive and safe static reflection with morphj. recently, language extensions have been proposed for java and c# to support pattern-based reflective declaration. these extensions introduce a disciplined form of meta-programming and aspect-oriented programming to mainstream languages: they allow members of a class (i.e., fields and methods) to be declared by statically iterating over and pattern-matching on members of other classes. such techniques, however, have been unable to safely express simple, but common, idioms such as declaring getter and setter methods for fields. in this paper, we present a mechanism that addresses the lack of expressiveness in past work without sacrificing safety. our technique is based on the idea of nested patterns that elaborate the outer-most pattern with blocking or enabling conditions. we implemented this mechanism in a language, morphj. we demonstrate the expressiveness of morphj with real-world applications. in particular, the morphj reimplementation of dstm2, a software transactional memory library, reduces 1,107 lines of java reflection and bytecode engineering library calls to just 374 lines of morphj code. at the same time, the morphj solution is both high level and safer, as morphj can separately type check generic classes and catch errors early. we present and formalize the morphj type system, and offer a type-checking algorithm.
explaining failures of program analyses. with programs getting larger and often more complex with each new release, programmers need all the help they can get in understanding and transforming programs. fortunately, modern development environments, such as eclipse, incorporate tools for understanding, navigating, and transforming programs. these tools typically use program analyses to extract relevant properties of programs. these tools are often invaluable to developers; for example, many programmers use refactoring tools regularly. however, poor results by the underlying analyses can compromise a tool's usefulness. for example, a bug finding tool may produce too many false positives if the underlying analysis is overly conservative, and thus overwhelm the user with too many possible errors in the program. in such cases it would be invaluable for the tool to explain to the user why it believes that each bug exists. armed with this knowledge, the user can decide which bugs are worth pursing and which are false positives. the contributions of this paper are as follows: (i) we describe requirements on the structure of an analysis so that we can produce reasons when the analysis fails; the user of the analysis determines whether or not an analysis's results constitute failure. we also describe a simple language that enforces these requirements; (ii) we describe how to produce necessary and sufficient reasons for analysis failure; (iii) we evaluate our system with respect to a number of analyses and programs and find that most reasons are small (and thus usable) and that our system is fast enough for interactive use.
sketching concurrent data structures. we describe psketch, a program synthesizer that helps programmers implement concurrent data structures. the system is based on the concept of sketching, a form of synthesis that allows programmers to express their insight about an implementation as a partial program: a sketch. the synthesizer automatically completes the sketch to produce an implementation that matches a given correctness criteria. psketch is based on a new counterexample-guided inductive synthesis algorithm (cegis) that generalizes the original sketch synthesis algorithm from solar-lezama et.al. to cope efficiently with concurrent programs. the new algorithm produces a correct implementation by iteratively generating candidate implementations, running them through a verifier, and if they fail, learning from the counterexample traces to produce a better candidate; converging to a solution in a handful of iterations. psketch also extends sketch with higher-level sketching constructs that allow the programmer to express her insight as a "soup" of ingredients from which complicated code fragments must be assembled. such sketches can be viewed as syntactic descriptions of huge spaces of candidate programs (over 108 candidates for some sketches we resolved). we have used the psketch system to implement several classes of concurrent data structures, including lock-free queues and concurrent sets with fine-grained locking. we have also sketched some other concurrent objects including a sense-reversing barrier and a protocol for the dining philosophers problem; all these sketches resolved in under an hour.
optimistic parallelism requires abstractions. irregular applications, which manipulate large, pointer-based data structures like graphs, are difficult to parallelize manually. automatic tools and techniques such as restructuring compilers and run-time speculative execution have failed to uncover much parallelism in these applications, in spite of a lot of effort by the research community. these difficulties have even led some researchers to wonder if there is any coarse-grain parallelism worth exploiting in irregular applications. in this paper, we describe two real-world irregular applications: a delaunay mesh refinement application and a graphics application thatperforms agglomerative clustering. by studying the algorithms and data structures used in theseapplications, we show that there is substantial coarse-grain, data parallelism in these applications, but that this parallelism is very dependent on the input data and therefore cannot be uncoveredby compiler analysis. in principle, optimistic techniques such asthread-level speculation can be used to uncover this parallelism, but we argue that current implementations cannot accomplish thisbecause they do not use the proper abstractions for the data structuresin these programs. these insights have informed our design of the galois system, an object-based optimistic parallelization system for irregular applications. there are three main aspects to galois: (1) a small number of syntactic constructs for packaging optimistic parallelism as iteration over ordered and unordered sets, (2)assertions about methods in class libraries, and (3) a runtime scheme for detecting and recovering from potentially unsafe accesses to shared memory made by an optimistic computation. we show that delaunay mesh generation and agglomerative clustering can be parallelized in a straight-forward way using the galois approach, and we present experimental measurements to show that this approach is practical. these results suggest that galois is a practical approach to exploiting data parallelismin irregular programs.
searching for type-error messages. advanced type systems often need some form of type inference to reduce the burden of explicit typing, but type inference often leads to poor error messages for ill-typed programs. this work pursues a new approach to constructing compilers and presenting type-error messages in which the type-checker itself does not produce the messages. instead, it is an oracle for a search procedure that finds similar programs that do type-check. our two-fold goal is to improve error messages while simplifying compiler construction. our primary implementation and evaluation is for caml, a language with full type inference. we also present a prototype for c++ template functions, where type instantiation is implicit. a key extension is making our approach robust even when the program has multiple independent type errors.
bootstrapping: a technique for scalable flow and context-sensitive pointer alias analysis. we propose a framework for improving both the scalability as well as the accuracy of pointer alias analysis, irrespective of its flow or context-sensitivities, by leveraging a three-pronged strategy that effectively combines divide and conquer, parallelization and function summarization. a key step in our approach is to first identify small subsets of pointers such that the problem of computing aliases of any pointer can be reduced to computing them in these small subsets instead of the entire program. in order to identify these subsets, we first apply a series of increasingly accurate but highly scalable (context and flow-insensitive) alias analyses in a cascaded fashion such that each analysis ai works on the subsets generated by the previous one ai-1. restricting the application of ai to subsets generated by ai-1, instead of the entire program, improves it scalability, i.e., ai is bootstrapped by ai-1. once these small subsets have been computed, in order to make our overall analysis accurate, we employ our new summarization-based flow and context-sensitive alias analysis. the small size of each subset offsets the higher computational complexity of the context-sensitive analysis. an important feature of our framework is that the analysis for each of the subsets can be carried out independently of others thereby allowing us to leverage parallelization further improving scalability.
model checking transactional memories. model checking software transactional memories (stms) is difficult because of the unbounded number, length, and delay of concurrent transactions and the unbounded size of the memory. we show that, under certain conditions, the verification problem can be reduced to a finite-state problem, and we illustrate the use of the method by proving the correctness of several stms, including two-phase locking, dstm, tl2, and optimistic concurrency control. the safety properties we consider include strict serializability and opacity; the liveness properties include obstruction freedom, livelock freedom, and wait freedom. our main contribution lies in the structure of the proofs, which are largely automated and not restricted to the stms mentioned above. in a first step we show that every stm that enjoys certain structural properties either violates a safety or liveness requirement on some program with two threads and two shared variables, or satisfies the requirement on all programs. in the second step we use a model checker to prove the requirement for the stm applied to a most general program with two threads and two variables. in the safety case, the model checker constructs a simulation relation between two carefully constructed finite-state transition systems, one representing the given stm applied to a most general program, and the other representing a most liberal safe stm applied to the same program. in the liveness case, the model checker analyzes fairness conditions on the given stm transition system.
ucc: update-conscious compilation for energy efficiency in wireless sensor networks. wireless sensor networks (wsn), composed of a large number of low-cost, battery-powered sensors, have recently emerged as promising computing platforms for many non-traditional applications. the preloaded code on remote sensors often needs to be updated after deployment in order for the wsn to adapt to the changing demands from the users. post-deployment code dissemination is challenging as the data are transmitted via battery-powered wireless communication. recent studies show that the energy for sending a single bit is about the same as executing 1000 instructions in awsn. therefore it is important to achieve energy efficiency in code dissemination. in this paper, we propose novel update-conscious compilation(ucc) techniques for energy-efficient code dissemination in wsns. an update-conscious compiler, when compiling the modified code, includes the compilation decisions that were made when generating the old binary. the compiler employs a detailed energy model and strives to match the old decisions for a more energy-efficient result. in most cases, matching the previous decisions improves the binary code similarity, reduces the amount of data to be transmitted to remote sensors, and thus, consumes less energy. in this paper, we develop update-conscious register allocation and data layout algorithms. our experimental results show that they can achieve great improvements over the traditional, update-oblivious approaches.
a general framework for certifying garbage collectors and their mutators. garbage-collected languages such as java and c# are becoming more and more widely used in both high-end software and real-time embedded applications. the correctness of the gc implementation is essential to the reliability and security of a large portion of the world's mission-critical software. unfortunately, garbage collectors--especially incremental and concurrent ones--are extremely hard to implement correctly. in this paper, we present a new uniform approach to verifying the safety of both a mutator and its garbage collector in hoare-style logic. we define a formal garbage collector interface general enough to reason about a variety of algorithms while allowing the mutator to ignore implementation-specific details of the collector. our approach supports collectors that require read and write barriers. we have used our approach to mechanically verify assembly implementations of mark-sweep, copying and incremental copying gcs in coq, as well as sample mutator programs that can be linked with any of the gcs to produce a fully-verified garbage-collected program. our work provides a foundation for reasoning about complex mutator-collector interaction and makes an important advance toward building fully certified production-quality gcs.
automatic inversion generates divide-and-conquer parallel programs. divide-and-conquer algorithms are suitable for modern parallel machines, tending to have large amounts of inherent parallelism and working well with caches and deep memory hierarchies. among others, list homomorphisms are a class of recursive functions on lists, which match very well with the divide-and-conquer paradigm. however, direct programming with list homomorphisms is a challenge for many programmers. in this paper, we propose and implement a novel systemthat can automatically derive cost-optimal list homomorphisms from a pair of sequential programs, based on the third homomorphism theorem. our idea is to reduce extraction of list homomorphisms to derivation of weak right inverses. we show that a weak right inverse always exists and can be automatically generated from a wide class of sequential programs. we demonstrate our system with several nontrivial examples, including the maximum prefix sum problem, the prefix sum computation, the maximum segment sum problem, and the line-of-sight problem. the experimental results show practical efficiency of our automatic parallelization algorithm and good speedups of the generated parallel programs.
iterative context bounding for systematic testing of multithreaded programs. multithreaded programs are difficult to get right because of unexpected interaction between concurrently executing threads. traditional testing methods are inadequate for catching subtle concurrency errors which manifest themselves late in the development cycle and post-deployment. model checking or systematic exploration of program behavior is a promising alternative to traditional testing methods. however, it is difficult to perform systematic search on large programs as the number of possible program behaviors grows exponentially with the program size. confronted with this state-explosion problem, traditional model checkers perform iterative depth-bounded search. although effective for message-passing software, iterative depth-bounding is inadequate for multithreaded software. this paper proposes iterative context-bounding, a new search algorithm that systematically explores the executions of a multithreaded program in an order that prioritizes executions with fewer context switches. we distinguish between preempting and nonpreempting context switches, and show that bounding the number of preempting context switches to a small number significantly alleviates the state explosion, without limiting the depth of explored executions. we show both theoretically and empirically that context-bounded search is an effective method for exploring the behaviors of multithreaded programs. we have implemented our algorithmin two model checkers and applied it to a number of real-world multithreaded programs. our implementation uncovered 9 previously unknown bugs in our benchmarks, each of which was exposed by an execution with at most 2 preempting context switches. our initial experience with the technique is encouraging and demonstrates that iterative context-bounding is a significant improvement over existing techniques for testing multithreaded programs.
automatically classifying benign and harmful data racesallusing replay analysis. many concurrency bugs in multi-threaded programs are due to dataraces. there have been many efforts to develop static and dynamic mechanisms to automatically find the data races. most of the prior work has focused on finding the data races and eliminating the false positives. in this paper, we instead focus on a dynamic analysis technique to automatically classify the data races into two categories - the dataraces that are potentially benign and the data races that are potentially harmful. a harmful data race is a real bug that needs to be fixed. this classification is needed to focus the triaging effort on those data races that are potentially harmful. without prioritizing the data races we have found that there are too many data races to triage. our second focus is to automatically provide to the developer a reproducible scenario of the data race, which allows the developer to understand the different effects of a harmful data race on a program's execution. to achieve the above, we record a multi-threaded program's execution in a replay log. the replay log is used to replay the multi-threaded program, and during replay we find the data races using a happens-before based algorithm. to automatically classify if a data race that we find is potentially benign or potentially harmful, were play the execution twice for a given data race - one for each possible order between the conflicting memory operations. if the two replays for the two orders produce the same result, then we classify the data race to be potentially benign. we discuss our experiences in using our replay based dynamic data race checker on several microsoft applications.
valgrind: a framework for heavyweight dynamic binary instrumentation. dynamic binary instrumentation (dbi) frameworks make it easy to build dynamic binary analysis (dba) tools such as checkers and profilers. much of the focus on dbi frameworks has been on performance; little attention has been paid to their capabilities. as a result, we believe the potential of dbi has not been fully exploited. in this paper we describe valgrind, a dbi framework designed for building heavyweight dba tools. we focus on its unique support for shadow values-a powerful but previously little-studied and difficult-to-implement dba technique, which requires a tool to shadow every register and memory value with another value that describes it. this support accounts for several crucial design features that distinguish valgrind from other dbi frameworks. because of these features, lightweight tools built with valgrind run comparatively slowly, but valgrind can be used to build more interesting, heavyweight tools that are difficult or impossible to build with other dbi frameworks such as pin and dynamorio.
exterminator: automatically correcting memory errors with high probability. programs written in c and c++ are susceptible to memory errors, including buffer overflows and dangling pointers. these errors, whichcan lead to crashes, erroneous execution, and security vulnerabilities, are notoriously costly to repair. tracking down their location in the source code is difficult, even when the full memory state of the program is available. once the errors are finally found, fixing them remains challenging: even for critical security-sensitive bugs, the average time between initial reports and the issuance of a patch is nearly one month. we present exterminator, a system that automatically correct sheap-based memory errors without programmer intervention. exterminator exploits randomization to pinpoint errors with high precision. from this information, exterminator derives runtime patches that fix these errors both in current and subsequent executions. in addition, exterminator enables collaborative bug correction by merging patches generated by multiple users. we present analytical and empirical results that demonstrate exterminator's effectiveness at detecting and correcting both injected and real faults.
fault-tolerant typed assembly language. a transient hardware fault occurs when an energetic particle strikes a transistor, causing it to change state. although transient faults do not permanently damage the hardware, they may corrupt computations by altering stored values and signal transfers. in this paper, we propose a new scheme for provably safe and reliable computing in the presence of transient hardware faults. in our scheme, software computations are replicated to provide redundancy while special instructions compare the independently computed results to detect errors before writing critical data. in stark contrast to any previous efforts in this area, we have analyzed our fault tolerance scheme from a formal, theoretical perspective. to be specific, first, we provide an operational semantics for our assembly language, which includes a precise formal definition of our fault model. second, we develop an assembly-level type system designed to detect reliability problems in compiled code. third, we provide a formal specification for program fault tolerance under the given fault model and prove that all well-typed programs are indeed fault tolerant. in addition to the formal analysis, we evaluate our detection scheme and show that it only takes 34% longer to execute than the unreliable version.
static specification inference using predicate mining. the reliability and correctness of complex software systems can be significantly enhanced through well-defined specifications that dictate the use of various units of abstraction (e.g., modules, or procedures). often times, however, specifications are either missing, imprecise, or simply too complex to encode within a signature, necessitating specification inference. the process of inferring specifications from complex software systems forms the focus of this paper. we describe a static inference mechanism for identifying the preconditions that must hold whenever a procedure is called. these preconditions may reflect both data flow properties (e.g., whenever p is called, variable x must be non-null) as well as control-flow properties (e.g., every call to p must bepreceded by a call to q). we derive these preconditions using a ninter-procedural path-sensitive dataflow analysis that gathers predicates at each program point. we apply mining techniques to these predicates to make specification inference robust to errors. this technique also allows us to derive higher-level specifications that abstract structural similarities among predicates (e.g., procedure p is called immediately after a conditional test that checks whether some variable v is non-null.) we describe an implementation of these techniques, and validate the effectiveness of the approach on a number of large open-source benchmarks. experimental results confirm that our mining algorithms are efficient, and that the specifications derived are both precise and useful-the implementation discovers several critical, yet previously, undocumented preconditions for well-tested libraries.
parameterized tiled loops for free. parameterized tiled loops-where the tile sizes are not fixed at compile time, but remain symbolic parameters until later--are quite useful for iterative compilers and "auto-tuners" that produce highly optimized libraries and codes. tile size parameterization could also enable optimizations such as register tiling to become dynamic optimizations. although it is easy to generate such loops for (hyper) rectangular iteration spaces tiled with (hyper) rectangular tiles, many important computations do not fall into this restricted domain. parameterized tile code generation for the general case of convex iteration spaces being tiled by (hyper) rectangular tiles has in the past been solved with bounding box approaches or symbolic fourier motzkin approaches. however, both approaches have less than ideal code generation efficiency and resulting code quality. we present the theoretical foundations, implementation, and experimental validation of a simple, unified technique for generating parameterized tiled code. our code generation efficiency is comparable to all existing code generation techniques including those for fixed tile sizes, and the resulting code is as efficient as, if not more than, all previous techniques. thus the technique provides parameterized tiled loops for free! our "one-size-fits-all" solution, which is available as open source software can be adapted for use in production compilers.
automatic inference of optimizer flow functions from semantic meanings. previous work presented a language called rhodium for writing program analyses and transformations, in the form of declarative flow functions that propagate instances of user-defined dataflow fact schemas. each dataflow fact schema specifies a semantic meaning, which allows the rhodium system to automatically verify the correctness of the user's flow functions. in this work, we have reversed the roles of the flow functions and semantic meanings: rather than checking the correctness of the user-written flow functions using the facts' semantic meanings, we automatically infer correct flow functions solely from the meanings of the dataflow fact schemas. we have implemented our algorithm for inferring flow functions from fact schemas in the context of the whirlwind compiler, and have used this implementation to infer flow functions for a variety of fact schemas. the automatically generated flow functions cover most of the situations covered by an earlier suite of handwritten rules.
orchestrating the execution of stream programs on multicore platforms. while multicore hardware has become ubiquitous, explicitly parallel programming models and compiler techniques for exploiting parallelism on these systems have noticeably lagged behind. stream programming is one model that has wide applicability in the multimedia, graphics, and signal processing domains. streaming models execute as a set of independent actors that explicitly communicate data through channels. this paper presents a compiler technique for planning and orchestrating the execution of streaming applications on multicore platforms. an integrated unfolding and partitioning step based on integer linear programming is presented that unfolds data parallel actors as needed and maximally packs actors onto cores. next, the actors are assigned to pipeline stages in such a way that all communication is maximally overlapped with computation on the cores. to facilitate experimentation, a generalized code generation template for mapping the software pipeline onto the cell architecture is presented. for a range of streaming applications, a geometric mean speedup of 14.7x is achieved on a 16-core cell platform compared to a single core.
foundations of the c++ concurrency memory model. currently multi-threaded c or c++ programs combine a single-threaded programming language with a separate threads library. this is not entirely sound [7]. we describe an effort, currently nearing completion, to address these issues by explicitly providing semantics for threads in the next revision of the c++ standard. our approach is similar to that recently followed by java [25], in that, at least for a well-defined and interesting subset of the language, we give sequentially consistent semantics to programs that do not contain data races. nonetheless, a number of our decisions are often surprising even to those familiar with the java effort:we (mostly) insist on sequential consistency for race-free programs, in spite of implementation issues that came to light after the java work. we give no semantics to programs with data races. there are no benign c++ data races. we use weaker semantics for trylock than existing languages or libraries, allowing us to promise sequential consistency with an intuitive race definition, even for programs with trylock. this paper describes the simple model we would like to be able to provide for c++ threads programmers, and explain how this, together with some practical, but often under-appreciated implementation constraints, drives us towards the above decisions.
ditto: automatic incrementalization of data structure invariant checks (in java). we present ditto, an automatic incrementalizer for dynamic, side-effect-free data structure invariant checks. incrementalization speeds up the execution of a check by reusing its previous executions, checking the invariant anew only the changed parts of the data structure. ditto exploits properties specific to the domain of invariant checks to automate and simplify the process without restricting what mutations the program can perform. our incrementalizer works for modern imperative languages such as java and c#. it can incrementalize,for example, verification of red-black tree properties and the consistency of the hash code in a hash table bucket. our source-to-source implementation for java is automatic, portable, and efficient. ditto provides speedups on data structures with as few as 100 elements; on larger data structures, its speedups are characteristic of non-automatic incrementalizers: roughly 5-fold at 5,000 elements,and growing linearly with data structure size.
enforcing isolation and ordering in stm. transactional memory provides a new concurrency control mechanism that avoids many of the pitfalls of lock-based synchronization. high-performance software transactional memory (stm) implementations thus far provide weak atomicity: accessing shared data both inside and outside a transaction can result in unexpected, implementation-dependent behavior. to guarantee isolation and consistent ordering in such a system, programmers are expected to enclose all shared-memory accesses inside transactions. a system that provides strong atomicity guarantees isolation even in the presence of threads that access shared data outside transactions. a strongly-atomic system also orders transactions with conflicting non-transactional memory operations in a consistent manner. in this paper, we discuss some surprising pitfalls of weak atomicity, and we present an stm system that avoids these problems via strong atomicity. we demonstrate how to implement non-transactional data accesses via efficient read and write barriers, and we present compiler optimizations that further reduce the overheads of these barriers. we introduce a dynamic escape analysis that differentiates private and public data at runtime to make barriers cheaper and a static not-accessed-in-transaction analysis that removes many barriers completely. our results on a set of java programs show that strong atomicity can be implemented efficiently in a high-performance stm system.
sketching stencils. performance of stencil computations can be significantly improved through smart implementations that improve memory locality, computation reuse, or parallelize the computation. unfortunately, efficient implementations are hard to obtain because they often involve non-traditional transformations, which means that they cannot be produced by optimizing the reference stencil with a compiler. in fact, many stencils are produced by code generators that were tediously handcrafted. in this paper, we show how stencil implementations can be produced with sketching. sketching is a software synthesis approach where the programmer develops a partial implementation--a sketch--and a separate specification of the desired functionality given by a reference (unoptimized) stencil. the synthesizer then completes the sketch to behave like the specification, filling in code fragments that are difficult to develop manually. existing sketching systems work only for small finite programs, i.e.,, programs that can be represented as small boolean circuits. in this paper, we develop a sketching synthesizer that works for stencil computations, a large class of programs that, unlike circuits, have unbounded inputs and outputs, as well as an unbounded number of computations. the key contribution is a reduction algorithm that turns a stencil into a circuit, allowing us to synthesize stencils using an existing sketching synthesizer.
thin slicing. program slicing systematically identifies parts of a program relevant to a seed statement. unfortunately, slices of modern programs often grow too large for human consumption. we argue that unwieldy slices arise primarily from an overly broad definition of relevance, rather than from analysis imprecision. while a traditional slice includes all statements that may affect a point of interest, not all such statements appear equally relevant to a human. as an improved method of finding relevant statements, we propose thin slicing. a thin slice consists only of producer statements for the seed, i.e., those statements that help compute and copy avalue to the seed. statements that explain why producers affect the seed are excluded. for example, for a seed that reads a value from a container object, a thin slice includes statements that store the value into the container, but excludes statements that manipulate pointers to the container itself. thin slices can also be hierarchically expanded to include statements explaining how producers affect the seed, yielding a traditional slice in the limit. we evaluated thin slicing for a set of debugging and program understanding tasks. the evaluation showed that thin slices usually included the desired statements for the tasks (e.g., the buggy statement for a debugging task). furthermore, in simulated use of a slicing tool, thin slices revealed desired statements after inspecting 3.3 times fewer statements than traditional slicing for our debugging tasks and 9.4 times fewer statements for our program understanding tasks. finally, our thin slicing algorithm scales well to relatively large java benchmarks, suggesting that thin slicing represents an attractive option for practical tools.
the exovm system for automatic vm and application reduction. embedded systems pose unique challenges to java application developers and virtual machine designers. chief among these challenges is the memory footprint of both the virtual machine and the applications that run within it. with the rapidly increasing set of features provided by the java language, virtual machine designers are often forced to build custom implementations that make various tradeoffs between the footprint of the virtual machine and the subset of the java language and class libraries that are supported. in this paper, we present the exovm, a system in which an application is initialized in a fully featured virtual machine, and then the code, data, and virtual machine features necessary to execute it are packaged into a binary image. key to this process is feature analysis, a technique for computing the reachable code and data of a java program and its implementation inside the vm simultaneously. the exovm reduces the need to develop customized embedded virtual machines by reusing a single vm infrastructure and automatically eliding the implementation of unused java features on a per-program basis. we present a constraint-based instantiation of the analysis technique, an implementation in ibm's j9 java vm, experiments evaluating our technique for the eembc benchmark suite, and some discussion of the individual costs of some of java's features. our evaluation shows that our system can reduce the non-heap memory allocation of the virtual machine by as much as 75%. we discuss vm and language design decisions that our work shows are important in targeting embedded systems, supporting the long-term goal of a common vm infrastructure spanning from motes to large servers.
cgcexplorer: a semi-automated search procedure for provably correct concurrent collectors. concurrent garbage collectors are notoriously hard to design, implement, and verify. we present a framework for the automatic exploration of a space of concurrent mark-and-sweep collectors. in our framework, the designer specifies a set of "building blocks" from which algorithms can be constructed. these blocks reflect the designer's insights about the coordination between the collector and the mutator. given a set of building blocks, our framework automatically explores a space of algorithms, using model checking with abstraction to verify algorithms in the space. we capture the intuition behind some common mark-and-sweep algorithms using a set of building blocks. we utilize our framework to automatically explore a space of more than 1,600,000 algorithms built from these blocks, and derive over 100 correct fine-grained algorithms with various space, synchronization, and precision tradeoffs.
effective automatic parallelization of stencil computations. performance optimization of stencil computations has been widely studied in the literature, since they occur in many computationally intensive scientific and engineering applications. compiler frameworks have also been developed that can transform sequential stencil codes for optimization of data locality and parallelism. however, loop skewing is typically required in order to tile stencil codes along the time dimension, resulting in load imbalance in pipelined parallel execution of the tiles. in this paper, we develop an approach for automatic parallelization of stencil codes, that explicitly addresses the issue of load-balanced execution of tiles. experimental results are provided that demonstrate the effectiveness of the approach.
register allocation by puzzle solving. we show that register allocation can be viewed as solving a collection of puzzles. we model the register file as a puzzle board and the program variables as puzzle pieces; pre-coloring and register aliasing fit in naturally. for architectures such as powerpc, x86, and strongarm, we can solve the puzzles in polynomial time, and we have augmented the puzzle solver with a simple heuristic for spilling. for spec cpu2000, the compilation time of our implementation is as fast as that of the extended version of linear scan used by llvm, which is the jit compiler in the opengl stack of mac os 10.5. our implementation produces x86 code that is of similar quality to the code produced by the slower, state-of-the-art iterated register coalescing of george and appel with the extensions proposed by smith, ramsey, and holloway in 2004.
race directed random testing of concurrent programs. bugs in multi-threaded programs often arise due to data races. numerous static and dynamic program analysis techniques have been proposed to detect data races. we propose a novel randomized dynamic analysis technique that utilizes potential data race information obtained from an existing analysis tool to separate real races from false races without any need for manual inspection. specifically, we use potential data race information obtained from an existing dynamic analysis technique to control a random scheduler of threads so that real race conditions get created with very high probability and those races get resolved randomly at runtime. our approach has several advantages over existing dynamic analysis tools. first, we can create a real race condition and resolve the race randomly to see if an error can occur due to the race. second, we can replay a race revealing execution efficiently by simply using the same seed for random number generation--we do not need to record the execution. third, our approach has very low overhead compared to other precise dynamic race detection techniques because we only track all synchronization operations and a single pair of memory access statements that are reported to be in a potential race by an existing analysis. we have implemented the technique in a prototype tool for java and have experimented on a number of large multi-threaded java programs. we report a number of previously known and unknown bugs and real races in these java programs.
iterative optimization in the polyhedral model: part ii, multidimensional time. high-level loop optimizations are necessary to achieve good performance over a wide variety of processors. their performance impact can be significant because they involve in-depth program transformations that aim to sustain a balanced workload over the computational, storage, and communication resources of the target architecture. therefore, it is mandatory that the compiler accurately models the target architecture as well as the effects of complex code restructuring. however, because optimizing compilers (1) use simplistic performance models that abstract away many of the complexities of modern architectures, (2) rely on inaccurate dependence analysis, and (3) lack frameworks to express complex interactions of transformation sequences, they typically uncover only a fraction of the peak performance available on many applications. we propose a complete iterative framework to address these issues. we rely on the polyhedral model to construct and traverse a large and expressive search space. this space encompasses only legal, distinct versions resulting from the restructuring of any static control loop nest. we first propose a feedback-driven iterative heuristic tailored to the search space properties of the polyhedral model. though, it quickly converges to good solutions for small kernels, larger benchmarks containing higher dimensional spaces are more challenging and our heuristic misses opportunities for significant performance improvement. thus, we introduce the use of a genetic algorithm with specialized operators that leverage the polyhedral representation of program dependences. we provide experimental evidence that the genetic algorithm effectively traverses huge optimization spaces, achieving good performance improvements on large loop nests.
sharc: checking data sharing strategies for multithreaded c. unintended or unmediated data sharing is a frequent cause of insidious bugs in multithreaded programs. we present a tool called sharc (short for sharing checker) that allows a user to write lightweight annotations to declare how they believe objects are being shared between threads in their program. sharc uses a combination of static and dynamic analyses to check that the program conforms to this specification. sharc allows any type to have one of five "sharing modes" -- private to the current thread, read-only, shared under the control of a specified lock, intentionally racy, or checked dynamically. the dynamic mode uses run-time checking to verify that objects are either read-only, or only accessed by one thread. this allows us to check programs that would be difficult to check with a purely static system. if the user does not give a type an explicit annotation, then sharc uses a static type-qualifier analysis to infer that it is either private or should be checked dynamically. sharc allows objects to move between different sharing modes at runtime by using reference counting to check that there are no other references to the objects when they change mode. sharc's baseline dynamic analysis can check any c program, but is slow, and will generate false warnings about intentional data sharing. as the user adds more annotations, false warnings are reduced, and performance improves.we have found in practice that very few annotations are needed to describe all sharing and give reasonable performance. we ran sharc on 6 legacy c programs, summing to over 600k lines of code, and found that a total of only 60 simple annotations were needed to remove all false positives and to reduce performance overhead to only 2-14%.
velodrome: a sound and complete dynamic atomicity checker for multithreaded programs. atomicity is a fundamental correctness property in multithreaded programs, both because atomic code blocks are amenable to sequential reasoning (which significantly simplifies correctness arguments), and because atomicity violations often reveal defects in a program's synchronization structure. unfortunately, all atomicity analyses developed to date are incomplete in that they may yield false alarms on correctly synchronized programs, which limits their usefulness. we present the first dynamic analysis for atomicity that is both sound and complete. the analysis reasons about the exact dependencies between operations in the observed trace of the target program, and it reports error messages if and only if the observed trace is not conflict-serializable. despite this significant increase in precision, the performance and coverage of our analysis is competitive with earlier incomplete dynamic analyses for atomicity.
grammar-based whitebox fuzzing. whitebox fuzzing is a form of automatic dynamic test generation, based on symbolic execution and constraint solving, designed for security testing of large applications. unfortunately, the current effectiveness of whitebox fuzzing is limited when testing applications with highly-structured inputs, such as compilers and interpreters. these applications process their inputs in stages, such as lexing, parsing and evaluation. due to the enormous number of control paths in early processing stages, whitebox fuzzing rarely reaches parts of the application beyond those first stages. in this paper, we study how to enhance whitebox fuzzing of complex structured-input applications with a grammar-based specification of their valid inputs. we present a novel dynamic test generation algorithm where symbolic execution directly generates grammar-based constraints whose satisfiability is checked using a custom grammar-based constraint solver. we have implemented this algorithm and evaluated it on a large security-critical application, the javascript interpreter of internet explorer 7 (ie7). results of our experiments show that grammar-based whitebox fuzzing explores deeper program paths and avoids dead-ends due to non-parsable inputs. compared to regular whitebox fuzzing, grammar-based whitebox fuzzing increased coverage of the code generation module of the ie7 javascript interpreter from 53% to 81% while using three times fewer tests.
an ant colony optimization approach to the probabilistic traveling salesman problem. the probabilistic traveling salesman problem (ptsp) is a tsp problem where each customer has a given probability of requiring a visit. the goal is to find an a-priori tour of minimal expected length over all customers, with the strategy of visiting a random subset of customers in the same order as they appear in the a-priori tour. we address the question of whether and in which context an a-priori tour found by a tsp heuristic can also be a good solution for the ptsp. we answer this question by testing the relative performance of two ant colony optimization algorithms, ant colony system (acs) introduced by dorigo and gambardella for the tsp, and a variant of it (pacs) which aims to minimize the ptsp objective function. we show in which probability configuration of customers pacs and acs are promising algorithms for the ptsp.
learning heuristics for obdd minimization by evolutionary algorithms. ordered binary decision diagrams (obdd) are the state-of-the-art data structure in cad for ics. obdds are very sensitive to the chosen variable ordering, i. e. the size may vary from linear to exponential. in this paper we present an evolutionary algorithm (ea) that learns good heuristics for obdd minimization starting from a given set of basic operations. the difference to other previous approaches to obdd minimization is that the ea does not solve the problem directly. instead, it develops strategies for solving the problem. to demonstrate the efficiency of our approach experimental results are given. the newly developed heuristics are more efficient than other previously presented methods.
an evolutive approach for the delineation of local labour markets. given a territory composed of basic geographical units, the delineation of local labour market areas (llmas) can be seen as a problem in which those units are grouped subject to multiple constraints. in previous research, standard genetic algorithms were not able to find valid solutions, and a specific evolutionary algorithm was developed. the inclusion of multiple ad hoc operators allowed the algorithm to find better solutions than those of a widely-used greedy method. the experimentation process showed that the rate of success of each operator in generating good individuals is different and evolves with time. we therefore propose different adaptive alternatives that modify the probabilities of application of each operator throughout the evolutionary process, and compare the results of such adaptive approaches with previous results and a greedy method.
implementation of standard genetic algorithm on mimd machines. genetic algorithms (gas) have been implemented on a number of multiprocessor machines. in many cases the ga has been adapted to the hardware structure of the system. this paper describes the implementation of a standard genetic algorithm on several mimd multiprocessor systems. it discusses the data dependencies of the different parts of the algorithm and the changes necessary to adapt the serial version to the parallel versions. timing measurements and speedups are given for a common problem implemented on all machines.
explicit filtering of building blocks for genetic algorithms. genetic algorithms are often applied to building block problems. we have developed a simple filtering algorithm that can locate building blocks within a bit-string, and does not make assumptions regarding the linkage of the bits. a comparison between the filtering algorithm and genetic algorithms reveals some interesting insights, and we discuss how the filtering algorithm can be used to build a powerful hybrid genetic algorithm.
evolutionary air traffic flow management for large 3d-problems. we present an evolutionary tool to solve free-route air traffic flow management problems within a three-dimensional air space. this is the first evolutionary tool which solves free-route planning problems involving a few hundred aircraft. we observe that the importance of the recombination operator increases as we scale to larger problem instances. the evolutionary algorithm is based on a variant of the elitist recombinationalgorithm. we show a theoretical analysis of the problem, and present the results of experiments.
nonsynonymous to synonymous substitution ratio ka/ks: measurement for rate of evolution in evolutionary computation. measuring fitness progression using numeric quantification in an evolutionary computation (ec) system may not be sufficient to capture the rate of evolution precisely. in this paper, we define the rate of evolution r e in an ec system based on the rate of efficient genetic variations being accepted by the ec population. this definition is motivated by the measurement of "amino acid to synonymous substitution ratio" k a/k s in biology, which has been widely accepted to measure the rate of gene sequence evolution. experimental applications to investigate the effects of four major configuration parameters on our rate of evolution measurement show that r e well reflects how evolution proceeds underneath fitness development and provides some insights into the effectiveness of ec parameters in evolution acceleration.
metaheuristics for group shop scheduling. the group shop scheduling problem (gsp) is a generalization of the classical job shop and open shop scheduling problems. in the gsp there are m machines and n jobs. each job consists of a set of operations, which must be processed on specified machines without preemption. the operations of each job are partitioned into groups on which a total precedence order is given. the problem is to order the operations on the machines and on the groups such that the maximal completion time (makespan) of all operations is minimized. the main goal of this paper is to provide a fair comparison of five metaheuristic approaches (i.e., ant colony optimization, evolutionary algorithm, iterated local search, simulated annealing, and tabu search) to tackle the gsp. we guarantee a fair comparison by a common definition of neighborhood in the search space, by using the same data structure, programming language and compiler, and by running the algorithms on the same hardware.
evolutionary market agents for resource allocation in decentralised systems. we introduce self-interested evolutionary market agents, which act on behalf of service providers in a large decentralised system, to adaptively price their resources over time. our agents competitively co-evolve in the live market, driving it towards the bertrand equilibrium, the non-cooperative nash equilibrium, at which all sellers charge their reserve price and share the market equally. we demonstrate that this outcome results in even load-balancing between the service providers.our contribution in this paper is twofold; the use of on-line competitive co-evolution of self-interested service providers to drive a decentralised market towards equilibrium, and a demonstration that load-balancing behaviour emerges under the assumptions we describe.unlike previous studies on this topic, all our agents are entirely self-interested; no cooperation is assumed. this makes our problem a non-trivial and more realistic one.
actuation constraints and artificial physics control. swarm systems for multiagent control rely on natural models of behavior. such models both predict simulated natural behavior and provide control instructions to the underlying agents. these two roles can differ when, for example, controlling nonholonomic robots incapable of executing some control suggestions from the system. we consider a simple physicomimetics system and examine the effects of actuation constraint on that system in terms of its ability to stabilize in regular formations, as well as the impact of such constraints on learning control parameters. we find that in the cases we considered, physicomimetics is surprisingly robust to certain types of actuation constraint.
supervised and evolutionary learning of echo state networks. a possible alternative to topology fine-tuning for neural network (nn) optimization is to use echo state networks (esns), recurrent nns built upon a large reservoir of sparsely randomly connected neurons. the promises of esns have been fulfilled for supervised learning tasks, but unsupervised ones, e.g. control problems, require more flexible optimization methods --- such as evolutionary algorithms. this paper proposes to apply cma-es, the state-of-the-art method in evolutionary continuous parameter optimization, to the evolutionary learning of esn parameters. first, a standard supervised learning problem is used to validate the approach and compare it to the standard one. but the flexibility of evolutionary optimization allows us to optimize not only the outgoing weights but also, or alternatively, other esn parameters, sometimes leading to improved results. the classical double pole balancing control problem is then used to demonstrate the feasibility of evolutionary (i.e. reinforcement) learning of esns. we show that the evolutionary esn obtain results that are comparable with those of the best topology-learning methods.
qfcs: a fuzzy lcs in continuous multi-step environments with continuous vector actions. this paper introduces the qfcs, a new approach to fuzzy learning classifier systems. qfcs can solve the multistep reinforcement learning problem in continuous environments and with a set of continuous vector actions. rules in the qfcs are small fuzzy systems. qfcs uses a q-learning algorithm to learn the mapping between inputs and outputs. this paper presents results that show that qfcs can evolve rules to represent only those parts of the input and action space where the expected values are important for making decisions. results for the qfcs are compared with those obtained by q-learning with a high discretization to show that the new approach converges in a way similar to how q-learning does for one-dimension problems with an optimal solution, and for two dimensions qfcs learns suboptimal solutions while it is difficult for q-learning to converge due to that high discretization.
extreme value based adaptive operator selection. credit assignment is an important ingredient of several proposals that have been made for adaptive operator selection. instead of the average fitness improvement of newborn offspring, this paper proposes to use some empirical order statistics of those improvements, arguing that rare but highly beneficial jumps matter as much or more than frequent but small improvements. an extreme value based credit assignment is thus proposed, rewarding each operator with the best fitness improvement observed in a sliding window for this operator. this mechanism, combined with existing adaptive operator selection rules, is investigated in an ec-like setting. first results show that the proposed method allows both the adaptive pursuit and the dynamic multi-armed bandit selection rules to actually track the best operators along evolution.
comparison of adaptive approaches for differential evolution. the evaluation of optimization algorithms and especially the analysis of adaptive variants is often complicated because several features are modified concurrently. for differential evolution these features may be adaptation of parameters, adjustment of the strategy and addition of local search or other special operators. thus, it is difficult to analyze which of these procedures is actually responsible for changes in the performance. therefore, in this work several adaptive algorithms are studied in-depth by monitoring performance changes for individual components of these algorithms to examine their effectiveness. the results show among others that the performance can be significantly improved by employing strategy control.
evolution strategies for direct policy search. the covariance matrix adaptation evolution strategy (cma-es) is suggested for solving problems described by markov decision processes. the algorithm is compared with a state-of-the-art policy gradient method and stochastic search on the double cart-pole balancing task using linear policies. the cma-es proves to be much more robust than the gradient-based approach in this scenario.
sub-tree swapping crossover, allele diffusion and gp convergence. we provide strong evidence that sub-tree swapping crossover when applied to tree-based representations will cause alleles (node labels) to diffuse within length classes. for a-ary trees we provide further confirmation that all programs are equally likely to be sampled within any length class when sub-tree swapping crossover is applied in the absence of selection and mutation. therefore, we propose that this form of search is unbiased - within length classes - for a-ary trees. unexpectedly, however, for mixed-arity trees this is not found and a more complicated form of search is taking place where certain tree shapes, hence programs, are more likely to be sampled than others within each class. we examine the reasons for such shape bias in mixed arity representations and provide the practitioner with a thorough examination of sub-tree swapping crossover bias. the results of this, when combined with crossover length bias research, explain genetic programming's lack of structural convergence during later stages of an experimental run. several operators are discussed where a broader form of convergence may be detected in a similar way to that found in genetic algorithm experimentation.
improved lower limits for pheromone trails in ant colony optimization. ant colony optimization algorithms were inspired by the foraging behavior of ants that accumulate pheromone trails on the shortest paths to food. some aco algorithms employ pheromone trail limits to improve exploration and avoid stagnation by ensuring a non-zero probability of selection for all trails. the max-min ant system (mmas) sets explicit pheromone trail limits while the ant colony system (acs) has implicit pheromone trail limits. stagnation still occurs in both algorithms with the recommended pheromone trail limits as the relative importance of the pheromone trails increases (¿> 1). improved estimates of the lower pheromone trail limit (¿ min ) for both algorithms help avoid stagnation and improve performance for ¿> 1. the improved estimates suggest a general rule to avoid stagnation for stochastic algorithms with explicit or implicit limits on exponential values used in proportional selection.
large-scale optimization of non-separable building-block problems. this paper presents principled results demonstrating how the identification and exploitation of variable dependencies by means of artificial neural network powered online model building, combined with a model based local-search, opens the way towards large-scale optimization of hard, non-separable building-block problems.
optimization of feature processing chain in music classification by evolution strategies. in this paper a new method based on evolution strategies (es) is presented to optimize a classifier for personal music categories. the user assigns songs to multiple personal music categories: examples from each category are selected in order to train a category-specific classifier using musical features as input. the classifier then ranks all songs according to their similarity to the category examples. since an exhaustive search for parameters maximizing the classifier performance is not feasible an es is applied. the experiments show a significant performance increase for various music categories due to the es optimization.
a memetic algorithm for the delineation of local labour markets. given a territory composed of basic geographical units, the delineation of local labour market areas (llmas) can be seen as a problem in which those units are grouped subject to multiple constraints. in previous research, standard genetic algorithms were not able to find valid solutions, and a specific evolutionary algorithm was developed. the inclusion of multiple ad hoc operators allowed the algorithm to find better solutions than those of a widely-used greedy method. however, the percentage of invalid solutions was still very high. in this paper we improve that evolutionary algorithm through the inclusion of (i) a reparation process, that allows every invalid individual to fulfil the constraints and contribute to the evolution, and (ii) a hillclimbing optimisation procedure for each generated individual by means of an appropriate reassignment of some of its constituent units. we compare the results of both techniques against the previous results and a greedy method.
nature-inspired synthesis of rational protocols. rational cryptography is an emerging field which combines aspects traditionally related to security with concepts described in economic theoretical frameworks. for example, it applies game theory concepts to address security problems arising when executing cryptographic protocols. the aim is to replace the assumption of a worst---case attacker by the notion of rational agents that try to maximize their payoffs. in this work, we define a formal framework and a meta---heuristic technique for the automated synthesis of multi---party rational exchange security (m---res) protocols. we provide experimental results for a simple scenario where a 3---party rational exchange protocol is automatically designed.
a set-based particle swarm optimization method. the representation used in particle swarm optimization (pso) is an n-dimensional vector. if you want to apply the pso method, you have to encode your problem as fix-sized vector. but many problem domains have solutions of unknown sizes as for instance in data clustering where you often don't know the number of clusters in advance.in this paper a set-based pso is proposed which replaces the position and velocity vectors by position and velocity sets realizing this way a pso with variable length representation. all operations of the pso update equations are redefined in an appropriate manner. additionally, an operator reducing set bloating effects is introduced.the presented approach is applied to well-known data clustering problems and performs better as other algorithms on them.
runtime analyses for using fairness in evolutionary multi-objective optimization. it is widely assumed that evolutionary algorithms for multi-objective optimization problems should use certain mechanisms to achieve a good spread over the pareto front. in this paper, we examine such mechanisms from a theoretical point of view and analyze simple algorithms incorporating the concept of fairness introduced by laumanns et al.[7]. this mechanism tries to balance the number of offspring of all individuals in the current population. we rigorously analyze the runtime behavior of different fairness mechanisms and present showcase examples to point out situations where the right mechanism can speed up the optimization process significantly.
evolving xslt stylesheets for document transformation. this paper presents a new version of an evolutionary algorithm that creates xslt programs from its intended input and output. xslt is a general purpose, document-oriented functional language, generally used to transform xml documents (or, in general, solve any problem that can be coded as an xml document). previously, a solution that solved the problem efficiently was proposed. in this paper, we improve on those results by testing different fitness functions, adding a new operator and changing the type of desired output document that can be obtained. the experiments show that the best results are obtained without considering the xslt length and including this new operator.
evaluation and diversity in co-evolution. this paper studies the performance of four alternative evaluation methods; two instances of the exponential moving average, the elo-rating and the glicko-rating method. these methods are tested in a co-evolutionary setup using the lint-game, which is known to be problematic under co-evolutionary conditions. besides the different evaluation approaches, two methods aimed at preserving diversity are tested. by using the objective fitness correlation as an analytical tool for monitoring accuracy of evaluation, it is shown that actual performance of an evaluation method strongly depends on whether co-evolutionary failure occurs and that a multi-modal approach to the lint-problem is effective in maintaining stable progress over time.
a study of convergence speed in multi-objective metaheuristics. an open issue in multi-objective optimization is designing metaheuristics that reach the pareto front using a low number of function evaluations. in this paper, we adopt a benchmark composed of three well-known problem families (zdt, dtlz, and wfg) and analyze the behavior of six state-of-the-art multi-objective metaheuristics, namely, nsga-ii, spea2, paes, omopso, abyss, and mocell, according to their convergence speed, i.e., the number of evaluations required to obtain an accurate pareto front. by using the hypervolume as a quality indicator, we measure the algorithms converging faster, as well as their hit rate over 100 independent runs. our study reveals that modern multi-objective metaheuristics such as mocell, omopso, and abyss provide the best overall performance, while nsga-ii and mocell achieve the best hit rates.
lower bounds for evolution strategies using vc-dimension. we derive lower bounds for comparison-based or selection-based algorithms, improving existing results in the continuous setting, and extending them to non-trivial results in the discrete case. this is achieved by considering the vc-dimension of the level sets of the fitness functions; results are then obtained through the use of sauer's lemma. in the special case of optimization of the sphere function, improved lower bounds are obtained by bounding the possible number of sign conditions realized by some systems of equations.
spam: set preference algorithm for multiobjective optimization. this paper pursues the idea of a general multiobjective optimizer that can be flexibly adapted to arbitrary user preferences--assuming that the goal is to approximate the pareto-optimal set. it proposes the set preference algorithm for multiobjective optimization (spam) the working principle of which is based on two observations: (i) current multiobjective evolutionary algorithms (moeas) can be regarded as hill climbers on set problems and (ii) specific user preferences are often (implicitly) expressed in terms of a binary relation on pareto set approximations. spam realizes a (1 + 1)-strategy on the space of pareto set approximations and can be used with any type of set preference relations, i.e., binary relations that define a total preorder on pareto set approximations. the experimental results demonstrate for a range of set preference relations that spam provides full flexibility with respect to user preferences and is effective in optimizing according to the specified preferences. it thereby offers a new perspective on preference-guided multiobjective search.
on the run-time dynamics of a peer-to-peer evolutionary algorithm. in this paper we propose an improvement on a fully distributed peer-to-peer (p2p) evolutionary algorithm (ea) based on autonomous selection. autonomous selection means that individuals decide on their own state of reproduction and survival without any central control, using instead estimations about the global population state for decision making. the population size varies at run-time as a consequence of such a decentralized reproduction and death of individuals. in order to keep it stable, we propose a self-adjusting mechanism which has been shown successful in three different search landscapes. key are the estimations about fitness and size of the population as provided by a gossiping algorithm. such an algorithm requires several rounds to collect the information while the individuals have to wait for synchronization. as an improvement, we propose a completely asynchronous ea which does not need waiting times. the results show that our approach outperforms quantitatively the execution time of the synchronous version.
particle filter with swarm move for optimization. we propose a novel generalized algorithmic framework to utilize particle filter for optimization incorporated with the swarm move method in particle swarm optimization (pso). in this way, the pso update equation is treated as the system dynamic in the state space model, while the objective function in optimization problem is designed as the observation/measurement in the state space model. particle filter method is then applied to track the dynamic movement of the particle swarm and therefore results in a novel stochastic optimization tool, where the ability of pso in searching the optimal position can be embedded into the particle filter optimization method. finally, simulation results show that the proposed novel approach has significant improvement in both convergence speed and final fitness in comparison with the pso algorithm over a set of standard benchmark problems.
a local search based evolutionary multi-objective optimization approach for fast and accurate convergence. a local search method is often introduced in an evolutionary optimization technique to enhance its speed and accuracy of convergence to true optimal solutions. in multi-objective optimization problems, the implementation of a local search is a non-trivial task, as determining a goal for the local search in presence of multiple conflicting objectives becomes a difficult proposition. in this paper, we borrow a multiple criteria decision making concept of employing a reference point based approach of minimizing an achievement scalarizing function and include it as a search operator of an emo algorithm. simulation results with nsga-ii on a number of two to four-objective problems with and without the local search approach clearly show the importance of local search in aiding a computationally faster and more accurate convergence to pareto-optimal solutions. the concept is now ready to be coupled with a faster and more accurate diversity-preserving procedure to make the overall procedure a competitive algorithm for multi-objective optimization.
formally testing liveness by means of compression rates. we present a formal method to determine whether there exist living creatures in a given computational environment. our proposal is based on studying the evolution of the entropy of the studied system. in particular, we check whether there exist entities decreasing the entropy in some parts, while increasing it in the rest of the world, which fits into the well-known maximum entropy production principle. the entropy of a computational environment is measured in terms of its compression rate with respect to some compression strategy. some life-related notions such as biodiversity are quantified as well. these ideas are presented by means of formal definitions. a toy example where a simple living structure is identified in a video stream is presented, and some results are reported.
how single ant aco systems optimize pseudo-boolean functions. we undertake a rigorous experimental analysis of the optimization behavior of the two most studied single ant aco systems on several pseudo-boolean functions. by tracking the behavior of the underlying random processes rather than just regarding the resulting optimization time, we gain additional insight into these systems. a main finding is that in those cases where the single ant aco system performs well, it basically simulates the much simpler (1+1) evolutionary algorithm.
enhancing the performance of maximum-likelihood gaussian edas using anticipated mean shift. many estimation---of---distribution algorithms use maximum-likelihood (ml) estimates. for discrete variables this has met with great success. for continuous variables the use of ml estimates for the normal distribution does not directly lead to successful optimization in most landscapes. it was previously found that an important reason for this is the premature shrinking of the variance at an exponential rate. remedies were subsequently successfully formulated (i.e. adaptive variance scaling (avs) and standard---deviation ratio triggering (sdr)). here we focus on a second source of inefficiency that is not removed by existing remedies. we then provide a simple, but effective technique called anticipated mean shift (ams) that removes this inefficiency.
theoretical analysis of initial particle swarm behavior. in this paper, particle trajectories of pso algorithms in the first iteration are studied. we will prove that many particles leave the search space at the beginning of the optimization process when solving problems with boundary constraints in high-dimensional search spaces. three different velocity initialization strategies will be investigated, but even initializing velocities to zero cannot prevent this particle swarm explosion. the theoretical analysis gives valuable insight into pso in high-dimensional bounded spaces, and highlights the importance of bound handling for pso: as many particles leave the search space in the beginning, bound handling strongly influences particle swarm behavior. experimental investigations confirm the theoretical results.
diversity maintenance mechanism for multi-objective genetic algorithms using clustering and network inversion. one of the major issues in applying multi-objective genetic algorithms to real-world problems is how to reduce the large number of evaluations. the simplest approach is a search with a small population size. however, the diversity of solutions is often lost with such a search. to overcome this difficulty, this paper proposes a diversity maintenance mechanism using clustering and network inversion that is capable of preserving diversity by relocating solutions. in addition, the proposed mechanism adopts clustering of training data sets to improve the accuracy of relocation. the results of numerical experiments on test functions and diesel engine emission and fuel economy problems showed that the proposed mechanism provided solutions with high diversity even when the search was performed with a small number of solutions.
preventing premature convergence in a simple eda via global step size setting. when a simple real-valued estimation of distribution algorithm (eda) with gaussian model and maximum likelihood estimation of parameters is used, it converges prematurely even on the slope of the fitness function. the simplest way of preventing premature convergence by multiplying the variance estimate by a constant factor k each generation is studied. recent works have shown that when increasing the dimensionality of the search space, such an algorithm becomes very quickly unable to traverse the slope and focus to the optimum at the same time. in this paper it is shown that when isotropic distributions with gaussian or cauchy distributed norms are used, the simple constant setting of k is able to ensure a reasonable behaviour of the eda on the slope and in the valley of the fitness function at the same time.
covariance matrix adaptation revisited - the cmsa evolution strategy -. the covariance matrix adaptation evolution strategy (cma-es) rates among the most successful evolutionary algorithms for continuous parameter optimization. nevertheless, it is plagued with some drawbacks like the complexity of the adaptation process and the reliance on a number of sophisticatedly constructed strategy parameter formulae for which no or little theoretical substantiation is available. furthermore, the cma-es does not work well for large population sizes. in this paper, we propose an alternative --- simpler --- adaptation step of the covariance matrix which is closer to the "traditional" mutative self-adaptation. we compare the newly proposed algorithm, which we term the cmsa-es, with the cma-es on a number of different test functions and are able to demonstrate its superiority in particular for large population sizes.
virus evolution strategy for vehicle routing problems with time windows. this paper proposes a new solution to the vehicle routing problem with time windows using an evolution strategy adopting viral infection. the problem belongs to the np-hard class and is very difficult to solve within practical time limits using systematic optimization techniques. in conventional evolution strategies, a schema with a high degree-of-fitness produced in the process of evolution may not be inherited when the fitness of the individual containing the schema is low. the proposed method preserves the schema as a virus and uses it by the infection operation in successive generations. experimental results using extended solomon's benchmark problems with 1000 customers proved that the proposed method is superior to conventional methods in both its rates of searches and the probability of obtaining solutions.
on multiplicative noise models for stochastic search. in this paper we investigate multiplicative noise models in the context of continuous optimization. we illustrate how some intrinsic properties of the noise model imply the failure of reasonable search algorithms for locating the optimum of the noiseless part of the objective function. those findings are rigorously investigated on the (1 + 1)-es for the minimization of the noisy sphere function. assuming a lower bound on the support of the noise distribution, we prove that the (1 + 1)-es diverges when the lower bound allows to sample negative fitness with positive probability and converges in the opposite case. we provide a discussion on the practical applications and non applications of those outcomes and explain the differences with previous results obtained in the limit of infinite search-space dimensionality.
driving cars by means of genetic algorithms. the techniques and the technologies supporting automatic vehicle guidance are an important issue. automobile manufacturers view automatic driving as a very interesting product with motivating key features which allow improvement of the safety of the car, reducing emission or fuel consumption or optimizing driver comfort during long journeys. car racing is an active research field where new advances in aerodynamics, consumption and engine power are critical each season. our proposal is to research how evolutionary computation techniques can help in this field. as a first goal we want to automatically learn to drive, by means of genetic algorithms, optimizing lap times while driving through three different circuits.
approximating the knee of an mop with stochastic search algorithms. in this paper we address the problem of approximating the 'knee' of a bi-objective optimization problem with stochastic search algorithms. knees or entire knee-regions are of particular interest since such solutions are often preferred by the decision makers in many applications. here we propose and investigate two update strategies which can be used in combination with stochastic multi-objective search algorithms (e.g., evolutionary algorithms) and aim for the computation of the knee and the knee-region, respectively. finally, we demonstrate the applicability of the approach on two examples.
the generalisation ability of a selection architecture for genetic programming. as an alternative to various existing approaches to incorporating modular decomposition and reuse in genetic programming (gp), we have proposed a new method for hierarchical evolution. based on a division of the problem's test case inputs into subsets, it employs a program structure that we refer to as a selection architecture. although the performance of gp systems based on this architecture has been shown to be superior to that of conventional systems, the nature of evolved programs is radically different, leading to speculation as to how well such programs may generalise to deal with previously unseen inputs. we have therefore performed additional experimentation to evaluate the approach's generalisation ability, and have found that it seems to stand up well against standard gp in this regard.
a blend of markov-chain and drift analysis. in their seminal article [theo. comp. sci. 276(2002):51---82] droste, jansen, and wegener present the first theoretical analysis of the expected runtime of a basic direct-search heuristic with a global search operator, namely the (1+1) evolutionary algorithm (ea), for the class of linear functions over the search space {0,1} n . in a rather long and involved proof they show that, for any linear function, the expected runtime of the ea is o(nlogn), i.e., that there are two constants c and n¿ such that, for n ¿ n¿, the expected number of iterations until a global optimum is generated is bound above by c·nlogn. however, neither c nor n¿ are specified --- they would be pretty large. here we reconsider this optimization scenario to demonstrate the potential of an analytical method that makes use not only of the drift (w.r.t. a potential function, here the number of bits set correctly), but also of the distribution of the evolving candidate solution over the search space {0,1} n : an invariance property of this distribution is proved, which is then used to derive a significantly better lower bound on the drift. finally, this better estimate of the drift results in an upper bound on the expected number of iterations of 3.8 nlog2 n + 7.6log2 n for n ¿ 2.
a convergence criterion for multiobjective evolutionary algorithms based on systematic statistical testing. a systematic approach for determining the generation number at which a specific multi-objective evolutionary algorithm (moea) has converged for a given optimization problem is introduced. convergence is measured by the performance indicators generational distance, spread and hypervolume. the stochastic nature of the moea is taken into account by repeated runs per generation number which results in a highly robust procedure. for each generation number the moea is repeated a fixed number of times, and the kolmogorow-smirnov-test is used in order to decide if a significant change in performance is gained in comparison to preceding generations. a comparison of different moeas on a problem with respect to necessary generation numbers becomes possible, and the understanding of the algorithm's behaviour is supported by analysing the development of the indicator values. the procedure is illustrated by means of standard test problems.
the impact of global structure on search. population-based methods are often considered superior on multimodal functions because they tend to explore more of the fitness landscape before they converge. we show that the effectiveness of this strategy is highly dependent on a function's global structure. when the local optima are not structured in a predictable way, exploration can misguide search into sub-optimal regions. limiting exploration can result in a better non-intuitive global search strategy.
ignoble trails - where crossover is provably harmful. beginning with the early days of the genetic algorithm and the schema theorem it has often been argued that the crossover operator is the more important genetic operator. the early royal road functions were put forth as an example where crossover would excel, yet mutation based eas were subsequently shown to experimentally outperform gas with crossover on these functions. recently several new royal roads have been introduced and proved to require expected polynomial time for gas with crossover, while needing exponential time to optimize for mutation-only eas. this paper does the converse, showing proofs that gas with crossover require exponential optimization time on new ignoble trail functions while mutation based eas optimize them efficiently.
costs and benefits of tuning parameters of evolutionary algorithms. we present an empirical study on the impact of different design choices on the performance of an evolutionary algorithm (ea). four ea components are considered--parent selection, survivor selection, recombination and mutation--and for each component we study the impact of choosing the right operator, and of tuning its free parameter(s). we tune 120 different combinations of ea operators to 4 different classes of fitness landscapes, and measure the cost of tuning. we find that components differ greatly in importance. typically the choice of operator for parent selection has the greatest impact, and mutation needs the most tuning. regarding individual eas however, the impact of design choices for one component depends on the choices for other components, as well as on the available amount of resources for tuning.
combination of natural and numerical optimization methods at the example of an internal gas turbine cooling channel. iceformation phenomena can be observed in many natural and technical processes. a naturally grown ice layer aspires in steady state to a minimum of energy dissipation. driven by this goal, this phenomena can be used to optimize complex geometric configurations in a natural manner. but since this state of minimum energy dissipation is seldom the desired goal function in technical applications, this natural experimental optimization method is combined with a subsequent classical numerical optimization using evolutionary algorithms at the example of an internal cooling channel of a gas turbine blade.
evolutionary algorithms for dynamic environments: prediction using linear regression and markov chains. in this work we investigate the use of prediction mechanisms in evolutionary algorithms for dynamic environments. these mechanisms, linear regression and markov chains, are used to estimate the generation when a change in the environment will occur, and also to predict to which state (or states) the environment may change, respectively. different types of environmental changes were studied. a memory-based evolutionary algorithm empowered by these two techniques was successfully applied to several instances of the dynamic bit matching problem.
the influence of mutation on protein-ligand docking optimization: a locality analysis. evolutionary approaches to protein-ligand docking typically use a real-value encoding and mutation operators based on gaussian and cauchy distributions. the choice of mutation is important for an efficient algorithm for this problem. we investigate the effect of mutation operators by locality analysis. high locality means that small variations in the genotype imply small variations in the phenotype. results show that gaussian-based operators have stronger locality than cauchy-based ones, especially if an annealing scheme is used to control the variance.
on the use of projected gradients for constrained multiobjective optimization problems. recent works have shown how hybrid variants of gradient-based methods and evolutionary algorithms perform better than a pure evolutionary method both for single-objective and multiobjective optimization. this same idea has been used with evolutionary multiobjective optimization (emo), obtaining also very promising results. in most cases, gradient information is used as part of the mutation operator (and only for unconstrained mops), in order to move every generated point to the exact pareto front. in our approach, we use the karush-kuhn-tucker optimality condition for constrained optimization problems to combine the information provided by the gradient vector of each objective function and the gradient vectors of constraint functions to obtain a feasible movement direction in those points near the border. in our approach, gradients of the objective functions will be approximated using quadratic regressions, trying to avoid local optima. the proposed algorithm is able to converge on several nonlinear constrained multiobjective optimization problems obtained from a benchmark, consuming few objective function evaluations (between 150 and 1000). our results indicate that our proposed scheme may produce a significant reduction in the computational cost, while producing results of good quality, when it is incorporated into a hybrid moea or when it is used to seed an emo algorithm.
a simple modification in cma-es achieving linear time and space complexity. this paper proposes a simple modification of the covariance matrix adaptation evolution strategy (cma-es) for high dimensional objective functions, reducing the internal time and space complexity from quadratic to linear. the covariance matrix is constrained to be diagonal and the resulting algorithm, sep-cma-es, samples each coordinate independently. because the model complexity is reduced, the learning rate for the covariance matrix can be increased. consequently, on essentially separable functions, sep-cma-es significantly outperforms cma-es . for dimensions larger than a hundred, even on the non-separable rosenbrock function, the sep-cma-es needs fewer function evaluations than cma-es .
bio-inspired search and distributed memory formation on power-law networks. in this paper, we report a novel and efficient algorithm for searching p2p networks having a power law topology. inspired by the natural immune system, it is a completely decentralized algorithm where each peer searches by sending out random walkers to a limited number of neighbors. as it finds other peers having similar content, it restructures its own neighborhood with the objective of bringing them closer. this restructuring leads to clustering of nodes with similar content, thus forming p2p communities. alongside, the search algorithm also adapts its walk strategy in order to take advantage of the community thus formed. this search strategy is more than twice as efficient as pure random walk on the same network.
readable and accurate rulesets with orga. a key task for data mining is to produce accurate and descriptive models. `human readable' models are often necessary to enable understanding, potentially leading to further insight, and also inducing trust in the user. rules, or decision trees (if not too numerous or large) are readable, unlike, for example svm models. however, descriptiveness and accuracy normally conflict; a challenge is to find algorithms that have both high accuracy and high readability. we introduce orga (optimized ripper using genetic algorithm) which hybridizes evolutionary search with the ripper ruleset algorithm. ripper is effective at producing accurate and readable rulesets, and we show that orga provides significant further improvement. orga outperforms overall a suitable set of comparative algorithms including implementations of ripper, c4.5 and part. on a majority of the datasets, orga's outperformance of the other algorithms is spectacular, and it is rarely dominated in terms of both accuracy and readability.
mixed-integer evolution strategies with dynamic niching. mixed-integer evolution strategies (mies) are a natural extension of standard evolution strategies (es) for addressing optimization of various types of variables --- continuous, ordinal integer, and nominal discrete --- at the same time. like most evolutionary algorithms (eas), they experience problems in obtaining the global optimum in highly multimodal search landscapes. niching methods, the extension of eas to multimodal domains, are designed to treat this issue. in this study we present a dynamic niching technique for mixed-integer evolution strategies, based upon an existing es niching approach, which was developed recently and successfully applied to continuous landscapes. the new approach is based on the heterogeneous distance measure that addresses search space similarity in a way consistent with the mutation operators of the mies. we apply the proposed dynamic niching mies framework to a test-bed of artificial landscapes and show the improvement on the global convergence in comparison to the standard mies algorithm.
evolvable agents in static and dynamic optimization problems. this paper investigates the behaviour of the evolvable agent model (evag) in static and dynamic environments. the evag is a spatially structured genetic algorithm (ga) designed to work on peer-to-peer (p2p) systems in which the population structure is a small-world graph built by newscast, a p2p protocol. additionally to the profits in computing performance, evag maintains genetic diversity at the small-world relationships between individuals in a sort of social network. experiments were conducted in order to assess how evag scales on deceptive and non-deceptive trap functions. in addition, the proposal was tested on dynamic environments. the results show that the evag scales and adapts better to dynamic environments than a standard ga and an improved version of the well-known random immigrants genetic algorithm.
investigations into the effect of multiobjectivization in protein structure prediction. physics-based potential energy functions used in protein structure prediction are composed of several energy terms combined in a weighted sum. `multiobjectivization' -- splitting up the energy function into its components and optimizing the components as a vector using multiobjective methods -- may have beneficial effects for tackling these difficult problems. in this paper we investigate the hypotheses that multiobjectivization can (i) reduce the number of local optima in the landscapes, as seen by hillclimbers, and (ii) equalize the influence of different energy components that range over vastly different energy scales and hence usually swamp each other's search gradients. the investigations use models of two real molecules, the alanine dipeptide and metenkephalin under the amber99 energy function, and consider hillclimbers with a range of mutation step sizes. our findings support the hypotheses and also indicate that multiobjectivization is competitive with alternative methods of escaping local optima.
a proposal to hybridize multi-objective evolutionary algorithms with non-gradient mathematical programming techniques. the hybridization of multi-objective evolutionary algorithms (moeas) with mathematical programming techniques has gained increasing popularity in the specialized literature in the last few years. however, such hybrids normally rely on the use of gradients and, therefore, normally consume a high number of extra objective function evaluations in order to estimate the gradient information required. the use of direct (nonlinear) optimization techniques has been, however, less common in the specialized literature, although several hybrids of this sort have been proposed for single-objective evolutionary algorithms. this paper proposes a hybridization between a well-known moea (the nsga-ii) and two direct search methods (nelder and mead's method and the golden section algorithm). the aim of the proposed approach is to combine the global search mechanisms of the evolutionary algorithm with the local search mechanisms provided by the aforementioned mathematical programming techniques, such that a more efficient (i.e., with a lower number of objective function evaluations) approach can be produced.
functional-specialization multi-objective real-coded genetic algorithm: fs-moga. this paper presents a genetic algorithm (ga) for multi-objective function optimization. in multi-objective function optimization, we believe that ga should adaptively switch search strategies in the early stage and the last stage for effective search. non-biased sampling and family-wise alternation are suitable to overcome local pareto optima in the early stage of search, and extrapolation-directed sampling and population-wise alternation are effective to cover the pareto front in the last stage. these situation-dependent requests make it difficult to keep good performance through the whole search process by repeating a single strategy. we propose a new ga that switches two search strategies, each of which is specialized for global and local search, respectively. this is done by utilizing the ratio of non-dominated solutions in the population. we examine the effectiveness of the proposed method using benchmarks and a real-world problem.
when does quasi-random work?. [10,22] presented various ways for introducing quasi-random numbers or derandomization in evolution strategies, with in some cases some spectacular claims on the fact that the proposed technique was always and for all criteria better than standard mutations. we here focus on the quasi-random trick and see to which extent this technique is efficient, by an in-depth analysis including convergence rates, local minima, plateaus, non-asymptotic behavior and noise. we conclude to the very stable, efficient and straightforward applicability of quasi-random numbers in continuous evolutionary algorithms.
uncertainty handling in model selection for support vector machines. we consider evolutionary model selection for support vector machines. hold-out set-based objective functions are natural model selection criteria, and we introduce a symmetrization of the standard cross-validation approach. we propose the covariance matrix adaptation evolution strategy (cma-es) with uncertainty handling for optimizing the new randomized objective function. our results show that this search strategy avoids premature convergence and results in improved classification accuracy compared to strategies without uncertainty handling.
ea-powered basin number estimation by means of preservation and exploration. when using an evolutionary algorithm on an unknown problem, properties like the number of global/local optima must be guessed for properly picking an algorithm and its parameters. it is the aim of current paper to put forward an ea-based method for real-valued optimization to provide an estimate on the number of optima a function exhibits, or at least of the ones that are in reach for a certain algorithm configuration, at low cost. we compare against direct clustering methods applied to different stages of evolved populations; interestingly, there is a turning point (in evaluations) after which our method is clearly better, although for very low budgets, the clustering methods have advantages. consequently, it is argued in favor of further hybridizations.
optimal nesting of species for exact cover: many against many. experiments with resource-defined fitness sharing (rfs) applied to shape nesting problems indicate a remarkable ability to discover exact covers of resources [1, 2]. these exact covers are represented by a maximally sized set of cooperating (non-competing) species. recent papers by horn [3, 4] introduce the first formal analyses of this empirical phenomenon. in [3], a minimal case of two species, a and b, against a third, c, is considered: the two-against-one scenario. it is shown that if the team of a and b form an exact cover, then c will be extinct at niching equilibrium. in [4], this result is generalized to the case of two-against-many: if a and b form an exact cover against an arbitrary number of competing species, under very general assumptions, a and b will be the only survivors at niching equilibirum. in the current paper, we extend these results to the most general scenario: many-against-many. we prove that, under certain very general assumptions, any size team of species forming an exact cover will dominate a population with any number of competing species: at niching equilibirum, all such competitors will be extinct. the results are more general than shape-nesting problems, applying as well to the np-complete problem exact cover by k-sets.
a scalable formal framework for analyzing the behavior of nature-inspired routing protocols. nature-inspired routing algorithms for fixed networks is an active area of research. in these algorithms, ant- or bee-agents are deployed for collecting the state of a network and providing them to autonomous and fully distributed controllers at each network node. in these routing systems the agents, through local interactions, self-organize to produce system-level behaviors which show adaptivity to changes and perturbations in the network environment. the formal modeling of such fully self-organizing, distributed and adaptive routing systems is a difficult task. in this paper, we propose a scalable formal framework that has following desirable features: (1) it models important performance metrics: throughput, delay and goodness of links, (2) it is scalable to any size of topology, (3) it is robust to changing network traffic conditions. the proposed framework is utilized to model a well-known beehive protocol which is further validated on nttnet (a 57 node topology). to the best of our knowledge, this is the first formal framework that has been validated on such a large topology.
optimizing real-time ordered-data broadcasts in pervasive environments using evolution strategy. we consider the problem of real-time data broadcast scheduling in pervasive systems with soft deadlines and constraints on the order in which data items should be broadcast to be useful. the broadcast schedule needs to be generated to provide a certain level of quality of service. thus, the real-time scheduler has to effectively trade-off between its running time and the quality of schedules generated. we use an evolution strategy to solve the problem. the variants tested includes (1 + ¿)-es, (1,¿)-es, and a (2 + 1)-es with a modified syswerda recombination operator, as well as a genetic algorithm.
evolving regular expressions for genechip probe performance prediction. affymetrix high density oligonuclotide arrays (hdona) simultaneously measure expression of thousands of genes using millions of probes. we use correlations between measurements for the same gene across 6685 human tissue samples from ncbi's geo database to indicated the quality of individual hg-u133a probes. low concordance indicates a poor probe. regular expressions can be data mined by a backus-naur form (bnf) context-free grammar using strongly typed genetic programming written in gawk and using egrep. the automatically produced motif is better at predicting poor dna sequences than an existing human generated re, suggesting runs of cytosine and guanine and mixtures should all be avoided.
testing the intermediate disturbance hypothesis: effect of asynchronous population incorporation on multi-deme evolutionary algorithms. in p2p and volunteer computing environments, resources are not always available from the beginning to the end, getting incorporated into the experiment at any moment. determining the best way of using these resources so that the exploration/exploitation balance is kept and used to its best effect is an important issue. the intermediate disturbance hypothesis states that a moderate population disturbance (in any sense that could affect the population fitness) results in the maximum ecological diversity. in the line of this hypothesis, we will test the effect of incorporation of a second population in a two-population experiment. experiments performed on two combinatorial optimization problems, mmdp and p-peaks, show that the highest algorithmic effect is produced if it is done in the middle of the evolution of the first population; starting them at the same time or towards the end yields no improvement or an increase in the number of evaluations needed to reach a solution. this effect is explained in the paper, and ascribed to the intermediate disturbance produced by first-population immigrants in the second population.
a distributed memetic algorithm for the routing and wavelength assignment problem. the routing and wavelength assignment problem deals with the routing of telecommunication traffic in all-optical networks. extending existing algorithms, we present a memetic algorithm (ma) for the static rwa by introducing a recombination operator and a scheme for distributing the computation. compared to previously achieved results for this problem, our ma significantly improves the solution quality. we find provably optimal results for previously unsolved problem instances. the distributed variant using epidemic algorithms allows to find solutions of quality comparable to the ma in less real-time.
enhancing the efficiency of the ecga. in this paper we show preliminary results of two efficiency enhancements proposed for extended compact genetic algorithm. first, a model building enhancement was used to reduce the complexity of the process from o(n 3) to o(n 2), speeding up the algorithm by 1000 times on a 4096 bits problem. then, a local-search hybridization was used to reduce the population size by at least 32 times, reducing the memory and running time required by the algorithm. these results are the first steps toward a competent and efficient genetic algorithm.
learning walking patterns for kinematically complex robots using evolution strategies. manually developing walking patterns for kinematically complex robots can be a challenging and time-consuming task. in order to automate this design process, a learning system that generates, tests, and optimizes different walking patterns is needed, as well as the ability to accurately simulate a robot and its environment. in this work, we describe a learning system that uses the cma-es method from evolutionary computation to learn walking patterns for a complex legged robot. the robot's limbs are controlled using parametrized distorted sine waves, and the evolutionary algorithm optimizes the parameters of these waveforms, testing the walking patterns in a physical simulation. the best solutions evolved by this system has been transferred to and tested on a real robot, and has resulted in a gait that is superior to those previously designed by a human designer.
a feasibility-preserving crossover and mutation operator for constrained combinatorial problems. this paper presents a feasibility-preserving crossover and mutation operator for evolutionary algorithms for constrained combinatorial problems. this novel operator is driven by an adapted pseudo-boolean solver that guarantees feasible offspring solutions. hence, this allows the evolutionary algorithm to focus on the optimization of the objectives instead of searching for feasible solutions. based on a proposed scalable testsuite, six specific testcases are introduced that allow a sound comparison of the feasibility-preserving operator to known methods. the experimental results show that the introduced approach is superior to common methods and competitive to a recent state-of-the-art decoding technique.
coevolving cellular automata with memory for chemical computing: boolean logic gates in the bz reaction. we propose that the behaviour of non-linear media can be controlled automatically through coevolutionary systems. by extension, forms of unconventional computing, i.e., massively parallel non-linear computers, can be realised by such an approach. in this study a light-sensitive sub-excitable belousov-zhabotinsky reaction is controlled using various heterogeneous cellular automata. a checkerboard image comprising of varying light intensity cells is projected onto the surface of a catalyst-loaded gel resulting in rich spatio-temporal chemical wave behaviour. the coevolved cellular automata are shown to be able to control chemical activity through dynamic control of the light intensity. the approach is demonstrated through the creation of a number of simple boolean logic gates.
evolving neural networks for online reinforcement learning. for many complex reinforcement learning problems with large and continuous state spaces, neuroevolution (the evolution of artificial neural networks) has achieved promising results. this is especially true when there is noise in sensor and/or actuator signals. these results have mainly been obtained in offline learning settings, where the training and evaluation phase of the system are separated. in contrast, in online reinforcement learning tasks where the actual performance of the systems during its learning phase matters, the results of neuroevolution are significantly impaired by its purely exploratory nature, meaning that it does not use (i. e. exploit) its knowledge of the performance of single individuals in order to improve its performance during learning. in this paper we describe modifications which significantly improve the online performance of the neuroevolutionary method evolutionary acquisition of neural topologies (eant) and discuss the results obtained on two benchmark problems.
simplified drift analysis for proving lower bounds in evolutionary computation. drift analysis is a powerful tool used to bound the optimization time of evolutionary algorithms (eas). various previous works apply a drift theorem going back to hajek in order to show exponential lower bounds on the optimization time of eas. however, this drift theorem is tedious to read and to apply since it requires two bounds on the moment-generating (exponential) function of the drift. a recent work identifies a specialization of this drift theorem that is much easier to apply. nevertheless, it is not as simple and not as general as possible. the present paper picks up hajek's line of thought to prove a drift theorem that is very easy to use in evolutionary computation. only two conditions have to be verified, one of which holds for virtually all eas with standard mutation. the other condition is a bound on what is really relevant, the drift. applications show how previous analyses involving the complicated theorem can be redone in a much simpler and clearer way. therefore, the simplified theorem is also a didactical contribution to the runtime analysis of eas.
many objective optimisation: direct objective boundary identification. this paper describes and demonstrates a new and highly innovative technique that identifies an approximation of the entire bounding surface of the feasible objective region directly, including deep concavities, disconnected regions and the edges of interior holes in the feasible areas. the pareto front is a subset of the surface of the objective boundary and can be extracted easily. importantly, if the entire objective boundary is known, breaks and discontinuities in the pareto front may be identified using automated methods; even with high objective dimensionality. this paper describes a proof-of-principle evolutionary algorithm that implements the new and unique direct objective boundary identification (dobi) method.
team algorithms based on ant colony optimization - a new multi-objective optimization approach. this paper proposes a novel team algorithm (ta) approach based on ant colony optimization (aco) for multi-objective optimization problems. the proposed method has shown a significant cooperative effect of different algorithms combined in a team of algorithms, achieving robustness in the resolution of a set of various combinatorial problems. experimentally, the proposed approach has verified a balance on different performance measures in problems as the traveling salesman problem (tsp), the quadratic assignment problem (qap) and the vehicle routing problem with time windows (vrptw). robustness and balance are achieved due to a novel classification and selection of the algorithms to be used by the team, considering pareto concept.
using ants' task division for better game engines - a contribution to game accessibility for impaired players. designing a relevant artificial intelligence engine for video games does not always consist in finding the best solution (best opponent, best path, etc.): it can sometimes consist in offering the player the best gaming experience. such a good experience is linked with the difficulty level of the proposed challenge. a game that is too easy will be boring whereas a game that is too difficult will be stressful. so, to be interesting for everyone, an artificial intelligence engine should provide an adaptive game level for every player. this game tuning is particularly prominent in the especial case of accessible games for impaired player. in this paper we show that the task division model based on ant colonies can be an interesting way to provide adaptive behaviors in game engines for simple one-player games.
parameter control methods for selection operators in genetic algorithms. parameter control is still one of the main challenges in evolutionary computation. this paper is concerned with controlling selection operators on-the-fly. we perform an experimental comparison of such methods on three groups of test functions and conclude that varying selection pressure during a ga run often yields performance benefits, and therefore is a recommended option for designers and users of evolutionary algorithms.
adaptive encoding: how to render search coordinate system invariant. this paper describes a method for rendering search coordinate system independent, adaptive encoding. adaptive encoding is applicable to any iterative search algorithm and employs incremental changes of the representation of solutions. one attractive way to change the representation in the continuous domain is derived from covariance matrix adaptation (cma). in this case, adaptive encoding recovers the cma evolution strategy, when applied to an evolution strategy with cumulative step-size control. consequently, adaptive encoding provides the means to apply cma-like representation changes to any search algorithm in the continuous domain. experimental results confirm the expectation that cma-based adaptive encoding will generally speed up a typical evolutionary algorithm on non-separable, ill-conditioned problems by orders of magnitude.
multiobjectivization by decomposition of scalar cost functions. the term `multiobjectivization' refers to the casting of a single-objec-tive optimization problem as a multiobjective one, a transformation that can be achieved by the addition of supplementary objectives or by the decomposition of the original objective function. in this paper, we analyze how multiobjectivization by decomposition changes the fitness landscape of a given problem and affects search. we find that decomposition has only one possible effect: to introduce plateaus of incomparable solutions. consequently, multiobjective hillclimbers using no archive `see' a smaller (or at most equal) number of local optima on a transformed problem compared to hillclimbers on the original problem. when archived multiobjective hillclimbers are considered this effect may partly be reversed. running time analyses conducted on four example functions demonstrate the (positive and negative) influence that both the multiobjectivization itself, and the use vs. non-use of an archive, can have on the performance of simple hillclimbers. in each case an exponential/polynomial divide is revealed.
a compass to guide genetic algorithms. parameter control is a key issue to enhance performances of genetic algorithms (ga). although many studies exist on this problem, it is rarely addressed in a general way. consequently, in practice, parameters are often adjusted manually. some generic approaches have been experimented by looking at the recent improvements provided by the operators. in this paper, we extend this approach by including operators' effect over population diversity and computation time. our controller, named compass, provides an abstraction of ga's parameters that allows the user to directly adjust the balance between exploration and exploitation of the search space. the approach is then experimented on the resolution of a classic combinatorial problem (sat).
niche radius adaptation with asymmetric sharing. in the field of genetic algorithms, niching techniques have been invented with the aim to induce speciation on multimodal fitness landscapes. unfortunately, they often rely on a problem-dependent niche radius parameter. this is the niche radius problem. in recent research, the possibilities to transfer niching techniques to the field of evolution strategies (es) have been studied. first attempts were carried out to learn a good value for the niche radius through self-adaptation. in this paper we introduce a new niching method for es with self-adaptation of the niche radius: asymmetric sharing. it is a form of fitness sharing. in contrast to earlier studies, it does not depend on coupling the niche radius to other strategy parameters. experimental results indicate that asymmetric sharing performs well in comparison to traditional sharing, without relying on problem-dependent parameters.
ga-net: a genetic algorithm for community detection in social networks. the problem of community structure detection in complex networks has been intensively investigated in recent years. in this paper we propose a genetic based approach to discover communities in social networks. the algorithm optimizes a simple but efficacious fitness function able to identify densely connected groups of nodes with sparse connections between groups. the method is efficient because the variation operators are modified to take into consideration only the actual correlations among the nodes, thus sensibly reducing the research space of possible solutions. experiments on synthetic and real life networks show the capability of the method to successfully detect the network structure.
solving three-objective optimization problems using a new hybrid cellular genetic algorithm. in this work we present a new hybrid cellular genetic algorithm. we take mocell as starting point, a multi-objective cellular genetic algorithm, and, instead of using the typical genetic crossover and mutation operators, they are replaced by the reproductive operators used in differential evolution. an external archive is used to store the nondominated solutions found during the search process and the spea2 density estimator is applied when the archive becomes full. we evaluate the resulting hybrid algorithm using a benchmark composed of three-objective test problems, and we compare the results with several state of the art multi-objective metaheuristics. the obtained results show that our proposal outperforms the other algorithms according to the two considered quality indicators.
a multiobjective evolutionary algorithm for the linear shelf space allocation problem. this paper presents a multiobjetive approach to solve the linear shelf space allocation problem (lissap), which consists on allocating lengths of shelves in a given shop to specific products or groups of products. previously we gave the first steps towards the development of a commercially viable tool that used evolutionary computation to address the problem; in this paper we introduce melissa, standing for multiobjective evolutionary linear shelf-space allocation, and test it on two real problem configurations, yielding very good results.
approximating minimum multicuts by evolutionary multi-objective algorithms. it has been shown that simple evolutionary algorithms are able to solve the minimum cut problem in expected polynomial time when using a multi-objective model of the problem. in this paper, we generalize these ideas to the np-hard minimum multicut problem. given a set of k terminal pairs, we prove that evolutionary algorithms in combination with a multi-objective model of the problem are able to obtain a k-approximation for this problem in expected polynomial time.
fitness expectation maximization. we present fitness expectation maximization (fem), a novel method for performing `black box' function optimization. fem searches the fitness landscape of an objective function using an instantiation of the well-known expectation maximization algorithm, producing search points to match the sample distribution weighted according to higher expected fitness. fem updates both candidate solution parameters and the search policy, which is represented as a multinormal distribution. inheriting em's stability and strong guarantees, the method is both elegant and competitive with some of the best heuristic search methods in the field, and performs well on a number of unimodal and multimodal benchmark tasks. to illustrate the potential practical applications of the approach, we also show experiments on finding the parameters for a controller of the challenging non-markovian double pole balancing task.
reinforcement learning: insights from interesting failures in parameter selection. we investigate reinforcement learning methods, namely the temporal difference learning td(¿) algorithm, on game-learning tasks. small modifications in algorithm setup and parameter choice can have significant impact on success or failure to learn. we demonstrate that small differences in input features influence significantly the learning process. by selecting the right feature set we found good results within only 1/100 of the learning steps reported in the literature. different metrics for measuring success in a reproducible manner are developed. we discuss why linear output functions are often preferable compared to sigmoid output functions.
adding probabilistic dependencies to the search of protein side chain configurations using edas. the problem of finding an optimal positioning for the side chain residues of a protein is called the side chain placement or side chain prediction problem. it can be posed as an optimization problem in the discrete domain. in this paper we use an estimation of distribution algorithm to address this optimization problem. using a set of 50 difficult protein instances, it is shown that the addition of dependencies between the variables in the probabilistic model can improve the quality of the solutions achieved for most of the instances considered. however, we also show that only when information about the known interactions between the residues is considered in the creation of the probabilistic model, the addition of the dependencies contributes to improve the quality of the solutions obtained.
imitation learning in uncertain environments. this paper describes a new evolutionary learning method to handle the fast adaptation of a group of agents in an uncertain environment. the method is a result of our research towards the generation of intelligent agents in computer games and is inspired by the idea of social learning or cultural evolution. thus, the agents try to adapt by the exchange of information about advantageous behaviours within the population. this paper evaluates the new approach by addressing the generation of competitive artificial players in a real-time action game.
enhancing efficiency of hierarchical boa via distance-based model restrictions. this paper analyzes the effects of restricting probabilistic models in the hierarchical bayesian optimization algorithm (hboa) by defining a distance metric over variables and disallowing dependencies between variables at distances greater than a given threshold. we argue that by using prior problem-specific knowledge, it is often possible to develop a distance metric that closely corresponds to the strength of interactions between variables. this distance metric can then be used to speed up model building in hboa. three test problems are considered: 3d ising spin glasses, random additively decomposable problems, and the minimum vertex cover.
cooperation in co-evolving networks: the prisoner's dilemma and stag-hunt games. interactions giving rise to dilemmas are widespread in society. starting from the observation that individuals interact through networks of acquaintances, we study the co-evolution of the agents' strategies and of the social network itself using two prototypical games: the prisoner's dilemma and the stag hunt. we find that cooperation and coordination can be achieved through the self-organization of the social network into strong and stable clusters of identical strategies.
age-p: a platform for open evolution. smart-appliances ensembles are highly dynamic device collections in which devices can leave and join at any time without notice. due to the high system dynamics, such ensembles cannot employ standard evolutionary algorithms for their internal self-organization processes. therefore, this paper proposes a new evolutionary framework, called the appliances-go-evolution platform (age-p). the simulation experiments indicate that age-p is able to properly cope with the peculiarities of smart-appliances ensembles and that it is thus a suitable option for their self-organization processes.
modeling human expertise on a cheese ripening industrial process using gp. industrial agrifood processes often strongly rely on human expertise, expressed as know-how and control procedures based on subjective measurements (color, smell, texture), which are very difficult to capture and model. we deal in this paper with a cheese ripening process (of french camembert), for which experimental data have been collected within a cheese ripening laboratory chain. a global and a monopopulation cooperative/coevolutive gp scheme (parisian approach) have been developed in order to simulate phase prediction (i.e. a subjective estimation of human experts) from microbial proportions and ph measurements. these two gp approaches are compared to bayesian network modeling and simple multilinear learning algorithms. preliminary results show the effectiveness and robustness of the parisian gp approach.
on the behaviour of the (1+1)-es for a simple constrained problem. this paper studies the behaviour of the (1 + 1)-es when applied to a linear problem with a single linear constraint. it goes beyond previous work by considering constraint planes that do not contain the gradient direction. the behaviour of the distance of the search point from the constraint plane forms a markov chain. the limit distribution of that chain is approximated using an exponential model, and progress rates and success probabilities are derived. consequences for the working of step length adaptation mechanisms based on success probabilities are discussed.
learning fuzzy rules with evolutionary algorithms - an analytic approach. this paper provides an analytical approach to fuzzy rule base optimization. while most research in the area has been done experimentally, our theoretical considerations give new insights to the task. using the symmetry that is inherent in our formulation, we show that the problem of finding an optimal rule base can be reduced to solving a set of quadratic equations that generically have a one dimensional solution space. this alternate problem specification can enable new approaches for rule base optimization.
genetic repair for optimization under constraints inspired by arabidopsis thaliana. it has recently been proposed that the model plant, arabidopsis thaliana (thale cress), uses a newly discovered genetic repair system to repair errors at the genetic level. a. thaliana uses information from the grandparent's genes as a basis for this correction --- so genetic information appears to skip a generation. we apply this gene repair strategy to a combinatory optimization problem, firstly comparing the performance of parent and grandparent based repair. subsequent experiments expand our understanding of the generepair algorithm, by examining the parameters of fitness and direction involved in the generepair process. our results point to a tentative explanation as to why a. thaliana might have evolved such an apparently complex inheritance process.
premature convergence in constrained continuous search spaces. the optimum of numerical problems quite often lies on the constraint boundary or even in a vertex of the feasible search space. in such cases the evolutionary algorithm (ea) frequently suffers from premature convergence because of a low success probability near the constraint boundaries. we analyze premature fitness stagnation and the success rates experimentally for an ea using self-adaptive step size control. for a (1+1)-ea with a rechenberg-like step control mechanism we prove premature step size reduction at the constraint boundary. the proof is based on a success rate analysis considering a simplified mutation distribution model. from the success rates and the possible state transitions, the expected step size change can be derived at each step. we validate the theoretical model with an experimental analysis.
testing the cax on a real-world problem and other benchmarks. intrigued by the interesting context aware crossover (cax) operator proposed by majeed and ryan in a number of recent papers, this operator was tried on a real problem (solid catalysts optimisation) where unfortunately, no improvement was detected. an implementation of the benchmarks used in [mr06b] seems to show that the cax is mostly an exploitation operator, boosting the average fitness of the population.
dynamic cooperative coevolutionary sensor deployment via localized fitness evaluation. we propose an innovative cooperative co-evolutionary computation framework, dynamic cooperative coevolution (dcc), which provides dynamic coupling of neighboring species for the fitness evaluation of individuals. one feature of dcc is the utilization of local fitness to achieve a global optimum, which makes it possible for co-evolutionary algorithms to be applied in localized distributed environments, such as network computing. this work is motivated by our interest in autonomous sensor deployment, where a sensor can only communicate with those within a limited range. our experiments show that dcc is effective in obtaining good solutions under such distributed and localized conditions.
improved multilabel classification with neural networks. this paper considers the multilabel classification problem, which is a generalization of traditional two-class or multi-class classification problem. in multilabel classification a set of labels (categories) is given and each training instance is associated with a subset of this label-set. the task is to output the appropriate subset of labels (generally of unknown size) for a given, unknown testing instance. some improvements to the existing neural network multilabel classification algorithm, named bp-mll, are proposed here. the modifications concern the form of the global error function used in bp-mll. the modified classification system is tested in the domain of functional genomics, on the yeast genome data set. experimental results show that proposed modifications visibly improve the performance of the neural network based multilabel classifier. the results are statistically significant.
distance based ranking in many-objective particle swarm optimization. optimization problems with many objectives open new issues for multi-objective optimization algorithms and particularly particle swarm optimization. many of the existing algorithms are able to solve problems of low number of objectives, but as soon as we increase the number of objectives, their performances get even worse than random search methods. this paper gives an overview on multi-objective particle swarm optimization when having many objectives and parameters. furthermore, two new variants of mopso are proposed which are based on ranking of the non-dominated solutions. the proposed distance based ranking in mopso improves the quality of the solutions for even very large objective and parameter spaces. the quality of the new proposed mopso methods has been tested and compared to the random search and nsga-ii methods. the tests cover 3 to 20 objectives and 20 to 100 parameters.
a developmental approach to the uncapacitated examination timetabling problem. the paper describes a new approach, based on cell biology, to the uncapacitated examination timetabling problem. this approach begins with a single cell which is developed into a fully grown organism through the processes of cell division, cell interaction and cell migration. the mature organism represents a solution to the particular timetabling problem. the paper discusses the performance of this method on the carter set of benchmark problems. this data set is comprised of real-world timetabling problems. the results obtained using the developmental approach are compared to that obtained by other biologically inspired algorithms applied to the same set of benchmarks and the best results cited in the literature for the carter data set.
approximate solutions in space mission design. in this paper, we address multi-objective space mission design problems. we argue that it makes sense from the practical point of view to consider in addition to the `optimal' trajectories (in the pareto sense) also approximate or nearly optimal solutions since this can lead to a significant larger variety for the decision maker. for this, we suggest a novel moea which is a modification of the well-known nsga-ii algorithm equipped with a recently proposed archiving strategy which aims for the storage of the set of approximate solution of a given mop. using this algorithm we will examine several space missions and demonstrate the benefit of the novel approach.
how a generative encoding fares as problem-regularity decreases. it has been shown that generative representations, which allow the reuse of code, perform well on problems with high regularity (i.e. where a phenotypic motif must be repeated many times). to date, however, generative representations have not been tested on irregular problems. it is unknown how they will fare on problems with intermediate and low amounts of regularity. this paper compares a generative representation to a direct representation on problems that range from having multiple types of regularity to one that is completely irregular. as the regularity of the problem decreases, the performance of the generative representation degrades to, and then underperforms, the direct encoding. the degradation is not linear, however, yet tends to be consistent for different types of problem regularity. furthermore, if the regularity of each type is sufficiently high, the generative encoding can simultaneously exploit different types of regularities.
analyzing hypervolume indicator based algorithms. indicator-based methods to tackle multiobjective problems have become popular recently, mainly because they allow to incorporate user preferences into the search explicitly. multiobjective evolutionary algorithms (moeas) using the hypervolume indicator in particular showed better performance than classical moeas in experimental comparisons. in this paper, the use of indicator-based moeas is investigated for the first time from a theoretical point of view. we carry out running time analyses for an evolutionary algorithm with a (μ + 1)-selection scheme based on the hypervolume indicator as it is used in most of the recently proposed moeas. our analyses point out two important aspects of the search process. first, we examine how such algorithms can approach the pareto front. later on, we point out how they can achieve a good approximation for an exponentially large pareto front.
examining the effect of elitism in cellular genetic algorithms using two neighborhood structures. elitism has a large effect on the search ability of evolutionary algorithms. many studies, however, did not discuss its different implementations in cellular algorithms. usually a replacement policy called "replace-if-better" is applied to each cell in cellular algorithms as a kind of elitism. in this paper, we examine three implementations of elitism. one is global elitism where a prespecified number of the best individuals in the entire population are viewed as being the elite. the replace-if-better policy is applied only to the globally best individuals. another scheme is local elitism where an individual is viewed as being the elite if it is the best among its neighbors. the replace-if-better policy is applied only to the locally best individuals. the other scheme is cell-wise elitism where the replace-if-better policy is applied to all individuals. effects of elitism are examined through computational experiments using a cellular genetic algorithm with two neighborhood structures. one is for local competition among neighbors. this competition neighborhood is used in the local elitism to determine the locally best individuals. the other is for local selection of parents. this selection neighborhood is also called the mating neighborhood. since we have the two neighborhood structures, we can specify the size of the competition neighborhood for the implementation of the local elitism independent of the selection neighborhood for mating. experimental results show that the use of the replace-if-better policy at all cells is not always the best choice.
fast multi-objective scheduling of jobs to constrained resources using a hybrid evolutionary algorithm. the problem tackled here combines three properties of scheduling tasks, each of which makes the basic task more challenging: job scheduling with precedence rules, co-allocation of restricted resources of different performances and costs, and a multi-objective fitness function. as the algorithm must come up with results within a few minutes runtime, ea techniques must be tuned to this limitation. the paper describes how this was achieved and compares the results with a common scheduling algorithm, the giffler-thompson procedure.
a steady-state genetic algorithm with resampling for noisy inventory control. noisy fitness functions occur in many practical applications of evolutionary computation. a standard technique for solving these problems is fitness resampling but this may be inefficient or need a large population, and combined with elitism it may overvalue chromosomes or reduce genetic diversity. we describe a simple new resampling technique called greedy average sampling for steady-state genetic algorithms such as genitor. it requires an extra runtime parameter to be tuned, but does not need a large population or assumptions on noise distributions. in experiments on a well-known inventory control problem it performed a large number of samples on the best chromosomes yet only a small number on average, and was more effective than four other tested techniques.
convergence analysis of evolution strategies with random numbers of offspring. hitting times of the global optimum for evolutionary algorithms are usually available for simple unimodal problems or for simplified algorithms. in discrete problems, the number of results that relate the convergence rate of evolution strategies to the geometry of the optimisation landscape is restricted to a few theoretical studies. this article introduces a variant of the canonical (μ + ¿)-es, called the poisson-es, for which the number of offspring is not deterministic, but is instead sampled from a poisson distribution with mean ¿. after a slight change on the rank-based selection for the μ parents, and assuming that the number of offspring is small, we show that the convergence rate of the new algorithm is dependent on a geometric quantity that measures the maximal width of adaptive valleys. the argument of the proof is based on the analogy of the poisson-es with a basic mutation-or-selection evolutionary strategy introduced in a previous work.
an iterated local search approach for finding provably good solutions for very large tsp instances. meta-heuristics usually lack any kind of performance guarantee and therefore one cannot be certain whether the resulting solutions are (near) optimum solutions or not without relying on additional algorithms for providing lower bounds (in case of minimization).in this paper, we present a highly effective hybrid evolutionary local search algorithm based on the iterated lin-kernighan heuristic combined with a lower bound heuristic utilizing 1-trees. since both upper and lower bounds are improved over time, the gap between the two bounds is minimized by means of effective heuristics. in experiments, we show that the proposed approach is capable of finding short tours with a gap of 0.8% or less for tsp instances up to 10 million cities. hence, to the best of our knowledge, we present the first evolutionary algorithm and meta-heuristic in general that delivers provably good solutions and is highly scalable with the problem size. we show that our approach outperforms all existing heuristics for very large tsp instances.
new approaches to coevolutionary worst-case optimization. many real-world optimization problems involve uncertainty. in this paper, we consider the case of worst-case optimization, i.e., the user is interested in a solution's performance in the worst case only. if the number of possible scenarios is large, it is an optimization problem by itself to determine a solution's worst case performance. in this paper, we apply coevolutionary algorithms to co-evolve the worst case test cases along with the solution candidates. we propose a number of new variants of coevolutionary algorithms, and show that these techniques outperform previously proposed coevolutionary worst-case optimizers on some simple test problems.
use of heuristic local search for single-objective optimization in multiobjective memetic algorithms. this paper proposes an idea of using heuristic local search procedures specific for single-objective optimization in multiobjective genetic local search (mogls). a large number of local search techniques have been studied for various combinatorial optimization problems. thus we may have a situation where a powerful local search procedure specific for a particular objective is available in multiobjective optimization. such a local search procedure, however, can improve only a single objective. moreover, it may have severe side-effects on the other objectives. for example, in a scheduling problem, an insertion move of a job with the maximum delay to an earlier position in a current schedule is likely to improve only the maximum tardiness. in this paper, we assume a situation where each objective has its own heuristic local search procedure. first we explain our mogls algorithm, which is the hybridization of nsga-ii and weighted sum-based local search. next we propose an idea of using heuristic local search procedures specific for single-objective optimization in mogls. then we implement the proposed idea as a number of variants of mogls. these variants are different from each other in the choice of a heuristic local search procedure. we examine three schemes: random, probabilistic and deterministic. finally we examine the performance of each variant through computational experiments on multiobjective 0/1 knapsack problems with two, three and four objectives. it is shown that the use of heuristic local search procedures and their appropriate choice improve the performance of mogls.
the parallel predator-prey model: a step towards practical application. in this paper, we apply the parallel predator-prey model for multi-objective optimization to a combinatorial problem for the first time: exemplarily, we optimize sequences of 50 jobs for an instance of the bi-criteria scheduling problem 1|d j | ¿ c j ,l max with this approach. the modular building block architecture of the predator-prey system and the distribution of acting entities enables the analysis of separated problem knowledge and the design of corresponding variation operators. the actual modules are derived from local heuristics that tackle fractions of the complete problem. we unveil that it is possible to cover different areas of the pareto-front with special property operators and make evident that the whole front can be covered if those operators are applied simultaneously to the spatial population. further, we identify open problems that arise when the predator-prey model is applied to combinatorial problems which have not yet occurred for real-valued optimization problems.
rigorous runtime analysis of inversely fitness proportional mutation rates. artificial immune systems (ais) are an emerging new field of research in computational intelligence that are applied to many areas of application, e.g., optimization, anomaly detection and classification. for optimization tasks, the use of hypermutation operators constitutes a common concept in ais. by now, only little theoretical work has been done in this field. in this paper, we present a detailed theoretical runtime analysis that gives an insight into the dynamics of fitness based hypermutation processes. two specific mutation rates are considered using a simple immune inspired algorithm. our main focus lies thereby on the influence of parameters embedded in popular immune inspired hypermutation operators from the literature. our theoretical findings are accompanied by some empirical results.
countering poisonous inputs with memetic neuroevolution. applied to certain problems, neuroevolution frequently gets stuck in local optima with very low fitness; in particular, this is true for some reinforcement learning problems where the input to the controller is a high-dimensional and/or ill-chosen state description. evidently, some controller inputs are "poisonous", and their inclusion induce such local optima. previously, we proposed the memetic climber, which evolves neural network topology and weights at different timescales, as a solution to this problem. in this paper, we further explore the memetic climber, and introduce its population-based counterpart: the memetic es. we also explore which types of inputs are poisonous for two different reinforcement learning problems.
hunger for new technologies, metrics, and spatiotemporal models in functional genomic (abstract only). functional genomics, as a field, is applying genomic self-improvement protocols (cost-effective, comprehensive, precise, accurate, and useful) to the kinetics of complex cellular systems. radical surgery in functional biology aims to mimic the success of structural biology along all five of those axes. technologies of recombinant dna and automation have brought costs down exponentially (100-fold in ten years) in structural studies. that combined with definitions of completeness push the second axis (to better than 99.99 the third axis by the beautiful, brute force of repetition. to reduce systematic errors requires more finesse. models allow integration of wildly different experimental methods (e.g. models based on the genetic code plus phylogeny provide quite independent checks of models based on dna electrophoretic images). model interchange specifications and metrics for model comparison mutually reinforce one another and provide one path along the fifth axis, that of utility, via killer-applications such as homology searches. this combination of modeling and searching provides serendipity and &ldquo;functional hypothesis generation&rdquo; in abundance. it instantly connects previously separately studied processes and organisms. statistical assessment of agreement between experiment and calculation can lead to improvement of the types of model parameter as well as parameter values. what are the analogous metrics and models for functional genomics? how can we estimate possible lower limits to costs? how do we define completion and accuracy? finally, how to we create and assess searches (not just on data but on models) and the utility of applications in general? how do these feed back to experimental design and feed forward to bioengineering? the functional genomics measures that are now thought to be prime for automation, miniaturization, and multiplexing include electrophoresis, molecular microarrays, mass-spectrometry, microscopy. microscopy is well suited for non-destructive time series, measures concerning spatial effects and stochastic kinetics of systems of one or a few of any critical molecule. the other methods currently offer richer signatures for multiplex (measure many molecules from the same source atonce). such extensive multiplexing can reduce errors due to misalignment of the (unmultiplexed) measures in space and/or time. these misalignments are dramatic, but by no means limited to unplanned (meta) comparisons between literature values. in the spirit of eliminating systematic errors, we see a major role for models as integrating as disparate a set of measures as possible. the dynamic and spatial biomodels of yore thought doomed by some by lack of data, will soon promote fresh study in the glaring light of overdetermination, i.e. more datapoints than adjustable parameters and feedback to the experiments justification for even more data for even more accuracy. we illustrate the above themes in the context of stress responses in wildtype and mutant human erythrocytes, e.coli and yeast time series. we assess measures of up to 19 metabolites, 400 proteins, and over 7000 rnas. these measures touch most of the critical 34 metabolites in erythrocytes but only a tiny fraction of the over 1200 in e.coli. they so far quantitate fewer than 10 often have unknown covalent structure). for the rnas (assayed with a dense set of oligon ucleotides) we see a rich, probably comprehensive set, including many unpredicted transcripts. so what are the next steps? spatial effects seen for dna-motifs at a few bp, hundreds, and thousands of bp (for three separate reasons) can be found by automatable methods. time-series of molecular concentration data can be aligned by discrete and/or interpolative dynamic programming. components of regulatory networks evident in time-series can be assessed by these independent models. the components of decay as well as steady-state levels have been modeled for a complete rna sets. these time series benefit from the sharp specific transitions that can be achieved through conditional mutants and drugs (chemical biology in general). overarching questions remain as to how we will systematize (automate) kinetic modeling and applications to a point analogous with strucural data modeling all the while connecting with issues of global quality of life?
comprehensive statistical method for protein fold recognition. we present a protein fold recognition method that uses a comprehensive statistical interpretation of structural hidden markov models (hmms). the structure/fold recognition is done by summing the probabilities of all sequence-to-structure alignments conventionally, boltzmann statistics dictate that the optimal alignment can give an estimate of the lowest free energy of the sequence conformation imposed by the structural model. the alignment is optimized for a scoring function that is interpreted as a free energy of an amino acid in a structural environment. near-optimal alignments are ignored, regardless of how likely they might be compared to the optimal alignment. here we investigate an alternative view. a structure model can be seen as a statistical representation of an ensemble of similar structures. the optimal alignment is always the most probable, but sub-optimal alignments may have comparable probabilities. these sub-optimal alignments can be interpreted as optimal alignments to the &ldquo;other&rdquo; structures from the ensemble or optimal alignments under minor fluctuations in the scoring function. summing probabilities for all alignments gives an estimate of sequence-model compatibility. we have built a set of structural hmms for 188 protein structures, and have compared two methods for identifying the structure compatible with a sequence: by the optimal alignment probability and by the total probability. fold recognition by total probability was 40% more accurate than fold recognition by the optimal alignment probability.
haplotype phase inference. most of the information being collected on dna variation among people does not identify which of the two parents transmitted which of the two copies of each gene. even worse, the parent of origin is often scrambled for each single nucleotide polymorphism (snp) that is identified, so that each gene may be represented by hundreds of pairs of snp vectors or haplotypes. collection of a population sample of this kind of genotype data, however, does contain information about these haplotypes, and inference of the haplotype pairs from this kind of data is referred to has haplotype phase inference. the problem has a rich geometric representation, and has spawned a wealth of algorithms that span graph theoretic to bayesian approaches. good solutions to this problem are strongly motivated by the efforts seeking to identify genes that underlie complex genetic disorders. the latest efforts in this area will be described and reviewed.
on the predictive power of sequence similarity in yeast. perhaps the most direct way to infer functional linkage of proteins is through structural similarity. however, structure determination lags behind dna sequencing. here we show that sequence similarity based on nucleotide sequences alone between orfs in yeast is indicative of the corresponding genes being of the same functional group, having a similar gene expression pattern or of being involved in a protein-protein interaction. in particular, we compare the nucleotide sequences corresponding to the 6280 yeast orfs using blast, and then cluster them together using a simple neighbor-joining algorithm. this, in effect, gives us hierarchical clustering of 53 levels, where higher levels have bigger clusters. we compare the clustering to large databases that are not based a-priori on sequence information to get a notion of how well our clustering is correlated with this data. for functional annotation we use the sgd database that gives one of 540 annotations for about half the yeast genes. for all pairs that appear within a cluster, we test the hypothesis that almost all genes within the same cluster have the same function. we get very high percentage rates of correct annotation at the lower levels of the hierarchy, which decreases gradually at higher ones. from the results of the large scale gene expression experiments we generate a list of pairs of genes, whose expression is highly correlated (&nge;0.9). we then go over this list of pairs, and count how many of them are contained within a cluster as opposed to the expected number by a random model. we estimate the significance of our results using simulation, and get for all levels p-value&nle;&nle;0.001. the third type of data obtained from the protein-protein interaction database that is given as a list of airs of proteins involved in interaction. as before, we count how many pairs are contained within a cluster, and get much better results than expected by a random model, with p-values&nle;0.001 for almost all levels. in summary, we show that successful functional predictions and functional annotations can be applied at a genomic scale. this can be achieved by combining a naive hierarchical clustering method that creates sets of clusters at different levels of granularity with statistical validation tools.
computational structural proteomics and virtual ligand screening. large scale discovery of new human genes, gene families and isozymes creates an exciting biomedical opportunity. advanced modeling by homology techniques can be employed to generate 3d models for most of the interesting new gene family members. this opens many new opportunities for structural structure based functional annotation and molecular design. several key computational technologies enable structural protein modeling and rational drug design: sequence-structure relationships, multiple sequence alignments, threading molecular mechanics; global energy optimization; protein modeling by homology; structure based protein functional annotation (e.g. prediction of possible active sites, small molecule binding sites, protein-protein interaction sites, flexibility annotation); protein design and redesign using structure prediction algorithms; structural immunology, e.g. derivation and design of peptide sequence specific for a particular hla presenting molecule based on the hla structure; peptide-protein docking; protein-protein docking; small molecule docking and virtual ligand screening; cheminformatics algorithms and virtual chemistry.we have been developing the internal coordinate mechanics approach to structure prediction for the last 16 years. it is aimed at de novo prediction of large structural rearrangements. to achieve that goal an icm program has been developed and combined accurate energy functions with powerful global optimization algorithm in the internal coordinate space.the most recent developments include on-the-fly calculations of accurate poisson electrostatics using the efficient boundary element algorithm based on the analytical molecular surface. this allows to predict de novo a solution structure of a 23-residue peptide.new computational technology for virtual ligand screening allows to generate alternative receptor conformations and perform flexible docking of hundreds of thousands of virtual compounds to the binding site. the success of this technology is demonstrated on several benchmarks and in six experimental projects which tested the prediction results. for well defined binding pockets only about the initial compound set actually needs to be synthesized and tested. using icm docking and scoring technology we have identified new ligands in a number of cases, including cases in which a model was used instead of a crystallographic structure and a case in which protein-protein interaction has been targeted.the most interesting recent results tested experimentally include: the de novo design of novel antagonists of thyroid hormone receptor, for which no antagonists were known before and, consequently, no antagonist-bound structure was known; de novo design of ligands targeting ephrin-ephrin receptor interactions.
algorithms for phylogenetic footprinting. phylogenetic footprinting is a technique that identifies regulatory elements by finding unusually well conserved regions in a set of orthologous non-coding dna sequences from multiple species. in an earlier paper, we presented an exact algorithm that identifies the most conserved region of a set of sequences. here, we present a number of algorithmic improvements that produce a 1000 fold speedup over the original algorithm. we also show how prior knowledge can be used to identify weaker motifs, and how to handle data sets in which only an unknown subset of the sequences contain the regulatory element. each technique is implemented and successfully identifies a large number of known binding sites, as well as several highly conserved but uncharacterized regions.
a comparative analysis method for detecting binding sites in coding regions. while the problem of predicting transcription factor binding sites in a gene's promoter region has been extensively studied, binding sites located in coding regions are also crucial for regulating gene expression but are more difficult to detect. coding region binding sites are mostly involved in splicing regulation, but also in transcriptional and post-transcriptional regulation. we consider the problem of predicting such binding sites by comparative analysis. comparative analysis is based on the idea that functional sequences tend to evolve at slower rate than nonfunctional sequence, making unusually well conserved regions likely to be of interest. the difficulty in applying comparative analysis to the detection of binding sites located in coding sequence is that the whole sequence is under selective pressure, because it needs to code for a functional protein. we present a technique to distinguish between conservation due to constraints on the amino acid product and conservation due to constraints imposed by regulatory factors. more precisely, we show how to calculate the probability of observing a certain degree of conservation among the nucleotides of given set of orthologous codons, given a set of constraints on the amino acids they need to encode. the algorithms described are implemented in a program called cosmo, available at http://bio.cs.washington.edu. we ran cosmo on several genes known to contain exonic splicing enhancers and report the results.
the sequence of the human genome (abstract only). a consensus sequence of the euchromatic portion of human genome has been generated by the whole genome shot-gun sequencing method that was developed while sequencing the genomes of haemophilus influenzae and drosophila melanogaster. the 2.9 billion bp sequence, was generated over nine months from 27,271,853 high quality sequence reads (&nsim;5x coverage of the genome) from both ends of plasmid clones made from the dna of five individuals: three females and two males of african-american, asian-chinese, hispanic and caucasian ethnicity. the coverage of the genome in cloned dna represented by paired end-sequences exceeds 37x. two assembly methods, a whole genome assembly and a regional hybrid assembly were utilized, combining bac data from genbank with celera data. over 90 assemblies of 500,000 bp or greater and 2510 million bp or larger. analysis of the genome sequence reveals - 26,178 protein-encoding genes for which there is strong corroborating evidence and an additional 12,000 computationally derived genes with mouse homologues or other weak supporting evidence. comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, tissue-specific developmental regulation, and in the hemostasis and immune systems. dna sequence comparisons among the five individuals provided locations of 2.6 million single nucleotide polymorphisms (snps). the haploid genomes of a randomly drawn pair of humans differ at a rate of one per 1,250 bp on average but there is marked heterogeneity in the level of polymorphism across the genome. only 0.75% of the snps led to possibly dysfunctional proteins.
tissue classification with gene expression profiles. constantly improving gene expression profiling technologies are expected to provide understanding and insight into cancer related cellular processes. gene expression data is also expected to significantly and in the development of efficient cancer diagnosis and classification platforms. in this work we examine two sets of gene expression data measured across sets of tumor and normal clinical samples one set consists of 2,000 genes, measured in 62 epithelial colon samples [1]. the second consists of &ap; 100,000 clones, measured in 32 ovarian samples (unpublished, extension of data set described in [26]). we examine the use of scoring methods, measuring separation of tumors from normals using individual gene expression levels. these are then coupled with high dimensional classification methods to assess the classification power of complete expression profiles. we present results of performing leave-one-out cross validation (loocv) experiments on the two data sets. employing svm [8], adaboost [13] and a novel clustering based classification technique. as tumor samples can differ from normal samples in their cell-type composition we also perform loocv experiments using appropriately modified sets of genes, attempting to eliminate the resulting bias. we demonstrate success rate of at least 90% in tumor vs normal classification, using sets of selected genes, with as well as without cellular contamination related members. these results are insensitive to the exact selection mechanism, over a certain range.
efficient extraction of mapping rules of atoms from enzymatic reaction data. extraction of mapping rules of atoms from enzymatic reaction data is useful for drug design, simulation of tracer experiments and consistency checking of pathway databases. most of previous methods for this problem are based on maximal common subgraph algorithms. in this paper, we propose a novel approach based on graph partition and graph isomorphism. we show that this problem is np-hard in general, but can be solved in polynomial time for wide classes of enzymatic reactions. we also present an o(n1.5) time algorithm for a special but fundamental class of reactions, where n is the maximum size of compounds appearing in a reaction. we develop practical polynomial time algorithms in which the morgan algorithm is used for computing the normal form of a graph, where it is known that the morgan algorithm works correctly for most chemical structures. computational experiments are performed for these practical algorithms using the chemical reaction data stored in the kegg/ligand database. the results of computational experiments suggest that practical algorithms are useful in many cases.
on approximation algorithms for local multiple alignment. this paper studies the local multiple alignment problem, which is also known as the general consensus patterns problem. local multiple alignment is, given protein or dna sequences, to locate a region (i.e., a substring) of fixed length from each sequence so that the score determined from the set of regions is optimized. we consider the following scoring schemes. the score indicating the average information content, the score defined by li et al, and the sum-of-pairs score we prove that multiple local alignment is np-hard under each of these scoring schemes. in addition, we prove that multiple local alignment is apx-hard under the average information content scoring. it implies that unless p = np there is no polynomial time algorithm whose worst case approximation error can be arbitrarily specified (precisely, a polynomial time approximation scheme). several related theoretical results are provided. we also made computational experiments on approximation algorithms for local multiple alignment under the average information content scoring. the results suggest that the gibbs sampling algorithm proposed by lawrence et al. is the best.
algorithms for identifying boolean networks and related biological networks based on matrix multiplication and fingerprint function. due to the recent progress of the dna microarray technology, a large number of gene expression profile data are being produced. how to analyze gene expression data is an important topic in computational molecular biology several studies have been done using the boolean network as a model of a genetic network this paper proposes efficient algorithms for identifying boolean networks of bounded indegree and related biological networks, where identification of a boolean network can be formalized as a problem of identifying many boolean functions simultaneously. for the identification of a boolean network, an o(mnd+1) time naive algorithm and a simple o(mnd) time algorithm are known, where n denotes the number of nodes, m denotes the number of examples, and d denotes the maximum indegree. this paper presents an improved o(mw-2nd + mnd+w-3) time monte-carlo type randomized algorithm, where w is the exponent of matrix multiplication (currently, w < 2376). the algorithm is obtained by combining fast matrix multiplication with the randomized fingerprint function for string matching. although the algorithm and its analysis are simple, the result is non-trivial and the technique can be applied to several related problems.
predicting the beta-helix fold from protein sequence data. a method is presented that uses &bgr;-strand interactions to predict the right-handed &bgr;-helix super-secondary structural motif in protein sequences. a program called betawrap implements this method, and is shown to score known &bgr;-helices above non-&bgr;-helices in the protein data bank in cross-validation. it is demonstrated that betawrap learns each of the seven known scop &bgr;-helix families, when trained on the the known &bgr;-helices from outside the family. betawrap also predicts many bacterial proteins of unknown structure that play a role in human infectious disease to &bgr;-helices; in particular, these proteins serve as virulence factors, adhesins and toxins in bacterial pathogenesis, and include cell surface proteins from chlamydia and the intestinal bacterium helicobacter pylori. the computational method used here may generalize to other &bgr; structures for which strand topology and profiles of residue accessibility are well conserved.
trilogy: discovery of sequence-structure patterns across diverse proteins. we describe a new computer program, trilogy, for the automated discovery of sequence-structure patterns in proteins. trilogy implements a pattern discovery algorithm that begins with an exhaustive analysis of flexible three-residue patterns; a subset of these patterns are selected as seeds for an extension process in which longer patterns are identified. a key feature of the method is explicit treatment of both the sequence and structure components of these motifs: each trilogy pattern is a pair consisting of a sequence pattern and a structure pattern. matches to both these component patterns are identified independently, allowing the program to assign a significance score to each sequence-structure pattern that assesses the degree of correlation between the corresponding sequence and structure motifs. trilogy identifies several thousand high-scoring patterns that occur across protein families. these include both previously identified and novel motifs. we expect that these sequence-structure patterns will be useful in predicting protein structure from sequence, annotating newly determined protein structures, and identifying novel motifs of potential functional or structural significance.
a combinatorial approach to protein docking with flexible side-chains. rigid body docking approaches are not sufficient to predict the structure of a protein complex from the unbound (native) structures of the two proteins. accounting for side&mdash;chain flexibility is an important step towards fully flexible protein docking. this work describes an approach that allows conformational flexibility for the side&mdash;chains while keeping the protein backbone rigid. starting from candidates created by a rigid docking algorithm, we demangle the side&mdash;chains of the docking site, thus creating reasonable approximations of the true complex structure. these structures are ranked with respect to the binding free energy. we present two new techniques for side&mdash;chain demangling. both approaches are based on a discrete representation of the side&mdash;chain conformational space by the use of a rotamer library. this leads to a combinatorial optimization problem. for the solution of this problem we propose a fast heuristic approach and an exact, albeit slower method using branch&mdash;&&mdash;cut techniques. as a test set we use the unbound structures of three proteases and the corresponding protein inhibitors. for each of the examples the highest&mdash;ranking conformation produced was a good approximation of the true complex structure.
information processing by cells and biologists (abstract only). the core agenda of post-wwii molecular biology has been defined as the molecular understanding of how genetic information was transmitted and read out (see for example stent 1968), and, by the 1950's, the analogy between the tape in a turing machine and the linear sequence of nucleotides in dna was apparent to both computer scientists and biologists. in the early 21st century, it may be that molecular biology can fruitfully return to these roots, by recasting part of its agenda in terms of the need to understand how biological information is processed. in a somewhat more modern formulation, cells can be though of as machines that process and make decisions on three kinds of information: 1) information stored in the genome 2) information about intracellular events (for example from heckpoint mechanisms) and 3) information external to the cell. in many cases the machinery that cells use to make decisions is reasonably well understood at a qualitative level. however, in no case do we possess a corresponding quantitative understanding, and, reflecting this, nor are we very capable of predicting the outcomes of perturbations to the genome, the internal workings of the cell, or its external environment. one path to understanding the behavior of these ensembles of components clearly lies in construction of mechanism-based quantitative models representing cellular processes. building such models requires solution of numerous computational and experimental biological challenges. i will detail some of these. another path may involve computation on the qualitative biological knowledge that now exists. expert biologists reason on this qualitative information to make statements about the consequences of perturbations, but expert systems that do the same in the main do not exist. here, although the need is clear, the relative opacity (to me) of much of the seemingly relevant computer science literature has made it more difficult to figure out first steps. finally, note that information theory (shannon 1948) has its roots in the 20th century need to understand transmission of electrical signals through channels. it is not immediately clear that the representations of biological processes used by biologists map well to concepts that come from this theory. to give only one example, one is hard pressed to define or find, inside a cell that is processing signals from the outside, either the signal or the &ldquo;bits&rdquo; (tukey, 1946) that might make it up. there may be thus be an opportunity here for new theory to guide thinking and further experiment.
using motion planning to map protein folding landscapes and analyze folding kinetics of known native structures. we present a novel approach for studying the kinetics of protein folding. the framework has evolved from robotics motion planning techniques called probabilistic roadmap methods (prms) that have been applied in many diverse fields with great success. in our previous work, we used a prm-based technique to study protein folding pathways of several small proteins and obtained encouraging results. in this paper, we describe how our motion planning framework can be used to study protein folding kinetics. in particular, we present a refined version of our prm-based framework and describe how it can be used to produce potential energy landscapes, free energy landscapes, and many folding pathways all from a single roadmap which is computed in a few hours on a desktop pc. results are presented for 14 proteins. our ability to produce large sets of unrelated folding pathways may potentially provide crucial insight into some aspects of folding kinetics, such as proteins that exhibit both two-state and three-state kinetics, that are not captured by other theoretical techniques.
provably sensitive indexing strategies for biosequence similarity search. the field of algorithms for pairwise biosequence similarity search is dominated by heuristic methods of high efficiency but uncertain sensitivity. one reason that more formal string matching algorithms with sensitivity guarantees have not been applied to biosequences is that they cannot directly find similarities that score highly under substitution score functions such as the dnapam-tt [20], pam [9], or blosum [12] families of matrices. we describe a general technique, score simulation, to map ungapped similarity search problems using these score functions into the problem of finding pairs of strings that are close in hamming space. score simulation leads to indexing schemes for biosequences that permit efficient ungapped similarity searches with formal guarantees of sensitivity using arbitrary score functions. in particular, we introduce the lsh-all-pairs-sim algorithm for finding local similarities in large biosequence collections and show that it is both computationally feasible and sensitive in practice.
designing seeds for similarity search in genomic dna. large-scale comparison of genomic dna is of fundamental importance in annotating functional elements of genomes. to perform large comparisons efficiently, blast (methods: companion methods enzymol 266 (1996) 460, j. mol. biol. 215 (1990) 403, nucleic acids res. 25(17) (1997) 3389) and other widely used tools use seeded alignment, which compares only sequences that can be shown to share a common pattern or ''seed'' of matching bases. the literature suggests that the choice of seed substantially affects the sensitivity of seeded alignment, but designing and evaluating seeds is computationally challenging. this work addresses the problem of designing a seed to optimize performance of seeded alignment. we give a fast, simple algorithm based on finite automata for evaluating the sensitivity of a seed in a markov model of ungapped alignments, along with extensions to mixtures and inhomogeneous markov models. we give intuition and theoretical results on which seeds are good choices. finally, we describe mandala, a software tool for seed design, and show that it can be used to improve the sensitivity of alignment in practice.
finding motifs using random projections. pevzner and sze [23] considered a precise version of the motif discovery problem and simultaneously issued an algorithmic challenge: find a motif m of length 15, where each planted instance differs from m in 4 positions. whereas previous algorithms all failed to solve this (15,4)-motif problem. pevzner and sze introduced algorithms that succeeded. however, their algorithms failed to solve the considerably more difficult (14,4)-, (16,5)-, and (18,6)-motif problems. we introduce a novel motif discovery algorithm based on the use of random projections of the input's substrings. experiments on simulated data demonstrate that this algorithm performs better than existing algorithms and, in particular, typically solves the difficult (14,4)-, (16,5)-, and (18,6)-motif problems quite efficiently. a probabilistic estimate shows that the small values of d for which the algorithm fails to recover the planted (l, d)-motif are in all likelihood inherently impossible to solve. we also present experimental results on realistic biological data by identifying ribosome binding sites in prokaryotes as well as a number of known transcriptional regulatory motifs in eukaryotes.
an analytic approach to significance assessment in local sequence alignment with gaps. a detailed study of the smith-waterman alignment algorithm is performed in order to find an analytical approach to the problem of assessing the statistical significance of local alignments with gaps. the significance is shown to be given in terms of an eigenvalue equation which captures the dynamics of the much simpler global alignment algorithm. this eigenvalue equation is then explicitly solved for a simple scoring system and the resulting significance estimations are verified by a comparison to extensive numerical simulations
rapid significance estimation in local sequence alignment with gaps. in order to assess the significance of sequence alignments it is crucial to know the distribution of alignment scores of pairs of random sequences. for gapped local alignment it is empirically known that the shape of this distribution is of the gumbel form. however, the determination of the parameters of this distribution is a computationally very expensive task. we present a new algorithmic approach which allows to estimate the more important of the gumbel parameters at least five times faster than the traditional methods. actual runtimes of our algorithm between less than a second and a few minutes on a workstation bring significance estimation into the realm of interactive applications.
stochastic roadmap simulation: an efficient representation and algorithm for analyzing molecular motion. classic techniques for simulating molecular motion, such as the monte carlo and molecular dynamics methods, generate individual motion pathways one at a time and spend most of their time trying to escape from the local minima of the energy landscape of a molecule. their high computational cost prevents them from being used to analyze many pathways. we introduce stochustic roadmap sirrrcllation (srs), a new approach for exploring the kinetics of molecular motion by simultaneously examining multiple pathways encoded compactly in a graph, called a roadmap. a roadmap is computed by sampling a molecule's conformation space at random. the computation does not suffer from the localminima problem encountered with existing methods. each path in the roadmap represents a potential motion pathway and is associated with a probability indicating the likelihood that the molecule follows this pathway. by viewing the roadmap as a markov chain, we can efficiently compute kinetic properties of molecular motion over the entire molecular energy landscape. we also prove that, in the limit, srs converges to the same distribution as monte carlo simulation. to test the effectiveness of our approach, we apply it to the computation of the transmission coefficients for protein folding, an important order parameter that measures the "kinetic distance" of a protein's conformation to its native state our computational studies show that srs obtains more accurate results and achieves several orders- of- magnitude reduction in computation time, compared with monte carlo simulatio.
optimal amnesic probabilistic automata or how to learn and classify proteins in linear time and space. statistical modeling of sequences is a central paradigm of machine learning that finds multiple uses in computational molecular biology and many other domains. the probabilistic automata typically built in these contexts are subtended by uniform, fixed-memory markov models. in practice, such automata tend to be unnecessarily bulky and computationally imposing both during their synthesis and use. in [8], much more compact, tree-shaped variants of probabilistic automata are built which assume an underlying markov process of variable memory length. in [3, 4], these variants, called probabilistic suffix trees (psts) were successfully applied to learning and prediction of protein families. the process of learning the automaton from a given training set s of sequences requires &thgr; (ln2) worst-case time, where n is the total length of the sequences in s and l is the length of a longest substring of s to be considered for a candidate state in the automaton. once the automaton is built, predicting the likelihood of a query sequence of m characters may cost time &thgr; (m2) in the worst case. the main contribution of this paper is to introduce automata equivalent to psts but having the following properties: learning the automaton takes o (n) time. prediction of a string of m symbols by the automaton takes o (m) time. along the way, the paper presents an evolving learning sheme, and addresses notions of empirical probability and related efficient computation,possibly a by-product of more general interest.
monotony of surprise and large-scale quest for unusual words. the problem of characterizing and detecting recurrent sequence patterns such as substrings or motifs and related associations or rules is variously pursued in order to compress data, unveil structure, infer succinct descriptions, extract and classify features, etc. in molecular biology, exceptionally frequent or rare words in bio-sequences have been implicated in various facets of biological function and structure. the discovery, particularly on a massive scale, of such patterns poses interesting methodological and algorithmic problems, and often exposes scenarios in which tables and synopses grow faster and bigger than the raw sequences they are meant to encapsulate. in previous study, the ability to succinctly compute, store, and display unusual substrings has been linked to a subtle interplay between the combinatorics of the subwords of a word and local monotonicities of some scores used to measure the departure from expectation. in this paper, we carry out an extensive analysis of such monotonicities for a broader variety of scores. this supports the construction of data structures and algorithms capable of performing global detection of unusual substrings in time and space linear in the subject sequences, under various probabilistic models.
dna sequence evolution with neighbor-dependent mutation. we introduce a model of dna sequence evolution which can account for biases in mutation rates that depend on the identity of the neighboring bases. an analytic solution for this class of models is developed by adopting well-known methods of nonlinear dynamics. results are presented for the cpg-methylation-deamination process which dominates point substitutions in vertebrates. the dinucleotide frequencies generated by the model (using empirically obtained mutation rates) match the overall pattern observed in non-coding dna. a web-based tool has been constructed to compute single- and dinucleotide frequencies for arbitrary neighbor-dependent mutation rates. also provided is the backward procedure to infer the mutation rates using maximum likelihood analysis given the observed single- and dinucleotide frequencies. reasonable estimates of the mutation rates can be obtained very efficiently, using generic non-coding dna sequences as input, after masking out long homonucleotide subsequences. our method is much more convenient and versatile to use than the traditional method of deducing mutation rates by counting mutation events in carefully chosen sequences. more generally, our approach provides a more realistic but still tractable description of non-coding genomic dna, and may be used as a null model for various sequence analysis applications.
regulatory element detection using correlation with expression (abstract only). we present a new computational method for discovering cis- regulatory elements which circumvents the need to cluster genes based on their expression profiles. based on a model in which upstream motifs contribute additively to the expression level of a gene, it requires a single genome-wide set of expression ratios and the upstream sequence for each gene, and outputs statistically significant motifs. analysis of publicly available expression data for sac charomyes cerevisiae reveals several new putative regulatory elements, some of which plausibly control the early, transient induction of genes during sporulation. known motifs generally have high statistical significance.
a new approach to sequence comparison: normalized sequence alignment. the smith-waterman algorithm for local sequence alignment is one of the most important techniques in computational molecular biology. this ingenious dynamic programming approach was designed to reveal the highly conserved fragments by discarding poorly conserved initial and terminal segments. however, the existing notion of local similarity has a serious flaw: it does not discard poorly conserved intermediate segments. the smith-waterman algorithm finds the local alignment with maximal score but it is unable to find local alignment with maximum degree of similarity (e.g., maximal percent of matches). moreover, there is still no efficient algorithm that answers the following natural question: do two sequences share a (sufficiently long) fragment with more than 70% of similarity? as a result, the local alignment sometimes produces a mosaic of well-conserved fragments artificially connected by poorly-conserved or even unrelated fragments. this may lead to problems in comparison of long genomic sequences and comparative gene prediction as recently pointed out by zhang et al., 1999 [33]. in this paper we propose a new sequence comparison algorithm (normalized local alignment) that reports the regions with maximum degree of similarity. the algorithm is based on fractional programming and its running time is &ogr;(n2 log n). in practice, normalized local alignment is only 3-5 times slower than the standard smith-waterman algorithm.
recent advances on the manipulation of single biomolecules. over the last ten years, a number of new approaches have emerged that have made it possible for scientists to mechanically manipulate individual molecules. these methods are proving themselves quite powerful to investigate the molecular mechanisms underlying many dynamic biochemical processes. because molecules are studied one at a time, single molecule manipulation techniques avoid the ensemble average characteristic of bulk studies. this feature is particularly useful to follow complex dynamic processes in time where the presence of multiple species in solution blurs the dynamical description of the system. moreover, many processes in the cell are known to be mechanical in nature and mechanical force is one of the "products" of the reaction. it follows that forces applied to the molecules undergoing these processes can be used to alter the extent and in some cases even the fate of the reactions, thus helping to reveal the molecular mechanisms by which force is generated in them. in this presentation, i will illustrate the use of optical tweezers with three different examples taken from my own research.
gene tree reconstruction and orthology analysis based on an integrated model for duplications and sequence evolution. gene tree and species tree reconstruction, orthology analysis and reconciliation, are problems important in multigenome-based comparative genomics and biology in general. in the present paper, we advance the frontier of these areas in several respects and provide important computational tools. first, exact algorithms are given for several probabilistic reconciliation problems with respect to the probabilistic gene evolution model, previously developed by the authors. until now, those problems were solved by mcmc estimation algorithms. second, we extend the gene evolution model to the gene sequence evolution model, by including sequence evolution. third, we develop mcmc algorithms for the gene sequence evolution model that, given gene sequence data allows: (1) orthology analysis, reconciliation analysis, and gene tree reconstruction, w.r.t. a species tree, that balances a likely/unlikely reconciliation and a likely/unlikely gene tree and (2) species tree reconstruction that balance a likely/unlikely reconciliation and a likely/unlikely gene trees. these mcmc algorithms take advantage of the exact algorithms for the gene evolution model. we have successfully tested our dynamical programming algorithms on real data for a biogeography problem. the mcmc algorithms perform very well both on synthetic and biological data.
identifying conserved gene clusters in the presence of orthologous groups. current biological evidence suggests a correlation between the function and the position of genes in chromosomes. examples include operon structure in prokaryotic genomes and similar expression patterns of neighboring genes in some eukaryotic genomes. in this paper, we present a new model and algorithm for identifying conserved gene clusters from pairwise genome comparison. this generalizes a recent model called "gene teams." a gene team is a set of orthologous genes that appear in two or more species, possibly in a different order yet with the distance of adjacent genes in the team for each chromosome always no more than a certain threshold. we remove the constraint in the original model that each gene must have a unique copy in the chromosomes, and thus allow the analysis on complex prokaryotic or eukaryotic genomes with extensive paralogs. our algorithm runs in o(mn) time and uses o(m+n) space, where m and n are the number of common genes in each chromosomes. we used this approach to study two bacterial genomes, e. coli and b. subtilis and successfully identified 85 conserved clusters, including clusters containing uncharacterized genes and a large cluster consisting of 21 ribosomal proteins. our implementation is publicly available at http://euler.slu.edu/~goldwasser/cogteams/.
on de novo interpretation of tandem mass spectra for peptide identification. the correct interpretation of tandem mass spectra is a difficult problem, even when it is limited to scoring peptides against a database. de novo sequencing is considerably harder, but critical when sequence databases are incomplete or not available. in this paper we build upon earlier work due to dancik et al., and chen et al. to provide a dynamic programming algorithm for interpreting de novo spectra. our method can handle most of the commonly occurring ions, including a; b; y, and their neutral losses. additionally, we shift the emphasis away from sequencing to assigning ion types to peaks. in particular, we introduce the notion of core interpretations, which allow us to give confidence values to individual peak assignments, even in the absence of a strong interpretation. finally, we introduce a systematic approach to evaluating de novo algorithms as a function of spectral quality. we show that our algorithm, in particular the core-interpretation, is robust in the presence of measurement error, and low fragmentation probability.
haplotypes and informative snp selection algorithms: don't block out information. it is widely hoped that variation in the human genome will provide a means of predicting risk of a variety of complex, chronic diseases. a major stumbling block to the successful identification of association between human dna polymorphisms (snps) and variability in risk of complex diseases is the enormous number of snps in the human genome (4,9). the large number of snps results in unacceptably high costs for exhaustive genotyping, and so there is a broad effort to determine ways to select snps so as to maximize the informativeness of a subset.in this paper we contrast two methods for reducing the complexity of snp variation: haplotype tagging, i.e. typing a subset of snps to identify segments of the genome that appear to be nearly unrecombined (haplotype blocks), and a new block-free model that we develop in this report. we present a statistic for comparing haplotype blocks and show that while the concept of haplotype blocks is reasonably robust there is substantial variability among block partitions. we develop a measure for selecting an informative subset of snps in a block free model. we show that the general version of this problem is np-hard and give efficient algorithms for two important special cases of this problem.
discovering local structure in gene expression data: the order-preserving submatrix problem. this paper concerns the discovery of patterns in gene expression matrices, in which each element gives the expression level of a given gene in a given experiment. most existing methods for pattern discovery in such matrices are based on clustering genes by comparing their expression levels in all experiments, or clustering experiments by comparing their expression levels for all genes. our work goes beyond such global approaches by looking for local patterns that manifest themselves when we focus simultaneously on a subset g of the genes and a subset t of the experiments. specifically, we look for order-preserving submatrices (opsms), in which the expression levels of all genes induce the same linear ordering of the experiments (we show that the opsm search problem is np-hard in the worst case). such a pattern might arise, for example, if the experiments in t represent distinct stages in the progress of a disease or in a cellular process, and the expression levels of all genes in g vary across the stages in the same way.we define a probabilistic model in which an opsm is hidden within an otherwise random matrix. guided by this model we develop an efficient algorithm for finding the hidden opsm in the random matrix. in data generated according to the model the algorithm recovers the hidden opsm with very high success rate. application of the methods to breast cancer data seems to reveal significant local patterns.our algorithm can be used to discover more than one opsm within the same data set, even when these opsms overlap. it can also be adapted to handle relaxations and extensions of the opsm condition. for example, we may allow the different rows of g x t to induce similar but not identical orderings of the columns, or we may allow the set t to include more than one representative of each stage of a biological process.
lymphocyte turnover in hiv-1 infection and the role of the thymus in siv infection. we investigated the dynamics of lymphocyte turnover in normal subjects as well as in hiv-1-infected patients using a novel labeling technique based on the administration of deuterium-containing glucose. a new mathematical model was also used to interpret the results. this approach provided direct determination of lymphocyte proliferation and death rates. we believe our findings convincingly demonstrate the increased turnover (3-6 fold) of both cd4 and cd8 lymphocytes in hiv-1 infection. furthermore, we also noted that the heightened t-cell turnover reverted toward normal upon effective combination antiretroviral therapy. collectively, these data show that the lymphocyte depletion seen in aids is not a consequence of a t-cell regenerative failure.we have also assessed the role of thymus in contributing to t lymphocyte homeostasis with and without siv infection. upon thymectomy in rhesus macaques, we noted a very gradual decline in the number of recent thymic emigrants as measured by the number of t-cell receptor excision circles. these results suggest that the normal thymic output in monkeys is small, and that recent thymic emigrants typically have a prolonged lifespan. we have also found relatively little impact of thymectomy on the outcome of siv infection. again, these findings indicate that thymus does not play a major role in the lymphocyte depletion observed in siv or hiv infection.
a random graph approach to nmr sequential assignment. nuclear magnetic resonance (nmr) spectroscopy allows scientists to study protein structure, dynamics, and interactions in solution. a necessary first step for such applications is determining the resonance assignment, mapping spectral data to atoms and residues in the primary sequence. automated resonance assignment algorithms rely on information regarding connectivity (e.g. through-bond atomic interactions) and amino acid type, typically using the former to determine strings of connected residues and the latter to map those strings to positions in the primary sequence. significant ambiguity exists in both connectivity and amino acid type, and different algorithms have combined the information in two phases (find short unambiguous strings then align) or simultaneously (align while extending strings). this paper focuses on the information content available in connectivity alone, allowing for ambiguity rather than handling only unambiguous strings, and complements existing work on the information content in amino acid type.in this paper, we develop a novel random-graph theoretic framework for algorithmic analysis of nmr sequential assignment. our random graph model captures the structure of chemical shift degeneracy (a key source of connectivity ambiguity). we then give a simple and natural randomized algorithm for finding an optimum sequential cover. the algorithm naturally and efficiently reuses substrings while exploring connectivity choices; it overcomes local ambiguity by enforcing global consistency of all choices. we employ our random graph model to analyze our algorithm, and show that it can provably tolerate a relatively large ambiguity while still giving expected optimal performance in polynomial time. to study the algorithm's performance in practice, we tested it on experimental data sets from a variety of proteins and experimental set-ups. the algorithm was able to overcome significant noise and local ambiguity and consistently identify significant sequential fragments.
class discovery in gene expression data. recent studies (alizadeh et al, [1]; bittner et al,[5]; golub et al, [11]) demonstrate the discovery of putative disease subtypes from gene expression data. the underlying computational problem is to partition the set of sample tissues into statistically meaningful classes. in this paper we present a novel approach to class discovery and develop automatic analysis methods. our approach is based on statistically scoring candidate partitions according to the overabundance of genes that separate the different classes. indeed, in biological datasets, an overabundance of genes separating known classes is typically observed. we measure overabundance against a stochastic null model. this allows for highlighting subtle, yet meaningful, partitions that are supported on a small subset of the genes. using simulated annealing we explore the space of all possible partitions of the set of samples, seeking partitions with statistically significant overabundance of differentially expressed genes. we demonstrate the performance of our methods on synthetic data, where we recover planted partitions. finally, we turn to tumor expression datasets, and show that we find several highly pronounced partitions.
dna segmentation as a model selection process. previous divide-and-conquer segmentation analyses of dna sequences do not provide a satisfactory stopping criterion for the recursion. this paper proposes that segmentation be considered as a model selection process. using the tools in model selection, a limit for the stopping criterion on the relaxed end can be determined. the bayesian information criterion, in particular, provides a much more stringent stopping criterion than what is currently used. such a stringent criterion can be used to delineate larger dna domains. a relationship between the stopping criterion and the average domain size is empirically determined, which may aid in the determination of isochore borders.
the noesy jigsaw: automated protein secondary structure and main-chain assignment from sparse, unassigned nmr data. high-throughput, data-directed computational protocols for structural genomics (or proteomics) are required in order to evaluate the protein products of genes for structure and function at rates comparable to current gene-sequencing technology. this paper presents the jigsaw algorithm, a novel high-throughput, automated approach to protein structure characterization with nuclear magnetic resonance (nmr). jigsaw consists of two main components: (1) graph-based secondary structure pattern identification in unassigned heteronuclear nmr data, and (2) assignment of spectral peaks by probabilistic alignment of identified secondary structure elements against the primary sequence. jigsaw''s deferment of assignment until after secondary structure identification differs greatly from traditional approaches, which begin by correlating peaks among dozens of experiments. by deferring assignment, jigsaw not only eliminates this bottleneck, it also allows the number of experiments to be reduced from dozens to four, none of which requires 13c-labeled protein. this in turn dramatically reduces the amount and expense of wet lab molecular biology for protein expression and purification, as well as the total spectrometer time to collect data. our results for three test proteins demonstrate that we are able to identify and align approximately 80 percent of alpha-helical and 60 percent of beta-sheet structure. jigsaw is extremely fast, running in minutes on a pentium-class linux workstation. this approach yields quick and reasonably accurate (as opposed to the traditional slow and extremely accurate) structure calculations, utilizing a suite of graph analysis algorithms to compensate for the data sparseness. jigsaw could be used for quick structural assays to speed data to the biologist early in the process of investigation, and could in principle be applied in an automation-like fashion to a large fraction of the proteome.
interface surfaces for protein-protein complexes. protein-protein interactions, which form the basis for most cellular processes, result in the formation of protein interfaces. believing that the local shape of proteins is crucial, we take a geometric approach and present a definition of an interface surface formed by two or more proteins. we also present an algorithm and study the geometric and topological properties of these surfaces, thus paving the way for future biochemical studies of protein-protein interactions.
multiple organism gene finding by collapsed gibbs sampling. the gibbs sampling method has been widely used for sequence analysis after it was successfully applied to the problem of identifying regulatory motif sequences upstream of genes. since then numerous variants of the original idea have emerged, however in all cases the application has been to finding short motifs in collections of short sequences (typically less than 100 nucleotides long). in this paper we introduce a gibbs sampling approach for identifying genes in multiple large genomic sequences up to hundreds of kilobases long. this approach leverages the evolutionary relationships between the sequences to improve the gene predictions, without explicitly aligning the sequences. we have applied our method to the analysis of genomic sequence from 14 genomic regions, totaling roughly 1.8mb of sequence in each organism. we show that our approach compares favorably with existing ab-initio approaches to gene finding, including pairwise comparison based gene prediction methods which make explicit use of alignments. furthermore, excellent performance can be obtained with as little as 4 organisms, and the method overcomes a number of difficulties of previous comparison based gene finding approaches: it is robust with respect to genomic rearrangements, can work with draft sequence, and is fast (linear in the number and length of the sequences). it can also be seamlessly integrated with gibbs sampling motif detection methods.
gene-finding via tandem mass spectrometry. we propose a new gene-finding methodology that combines high performance liquid chromatograph (hplc)-tandem mass spectrometry experiments with a fast computer algorithm to locate coding regions and introns. proteins are first extracted from cells and digested by enzymes, and then the resulting peptides are separated and analyzed by hplc-tandem mass spectrometry. we designed an algorithm to find dna coding sequences, corresponding to open reading frames (orf), in the genome such that their translated amino acid sequences are optimally correlated with these tandem mass spectra. in this algorithm, we also allow one gap, corresponding to an intron, between two dna coding sequences, such that their concatenation becomes one coding sequence. finally, the algorithm assembles these candidate coding sequences and introns into gene structures. our algorithm was implemented to predict genes on 4 contigs with a total of 123 kbps using two sets of simulated digestion- hplc-tandem mass spectrometry data of 2523 caenorhabditis elegans chromosome iv proteins, digested by trypsin and asp-n respectively. among 15 annotated genes in the forward strand, all 98 exons are hit by the predicted no-gap coding sequences, and 60 out of 83 introns are correctly predicted. we also tested gene structure prediction in a contig containing 3 genes. combining splicing site predictions with predicted coding sequences and introns, we found all 3 gene structures.
gene selection criterion for discriminant microarray data analysis based on extreme value distributions. an important issue commonly encountered in the analysis of microarray data is to decide which and how many genes should be selected for further studies. for discriminant microarray data analyses based on statistical models, such as the logistic regression model, this gene selection can be accomplished by a comparison of the maximum likelihood of the model given the real data, l(d|m), and the expected maximum likelihood of the model given an ensemble of surrogate data, l(d0|m). typically, the computational burden for obtaining l(d0|m) is immense, often exceeding the limits of available resources by orders of magnitude. here, we propose an approach that circumvents such heavy computations by mapping the simulation problem to an extreme value problem, which can be easily solved by numerical simulation. we choose three classification problems from two publicly available microarray datasets to illustrate that approach.
a new approach to analyzing gene expression time series data. we present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved time-points, clustering, and dataset alignment. each expression profile is modeled as a cubic spline (piecewise polynomial) that is estimated from the observed data and every time point influences the overall smooth expression curve. we constrain the spline coefficients of genes in the same class to have similar expression patterns, while also allowing for gene specific parameters. we show that unobserved time-points can be reconstructed using our method with 10-15% less error when compared to previous best methods. our clustering algorithm operates directly on the continuous representations of gene expression profiles, and we demonstrate that this is particularly effective when applied to non-uniformly sampled data. our continuous alignment algorithm also avoids difficulties encountered by discrete approaches. in particular, our method allows for control of the number of degrees of freedom of the warp through the specification of parameterized functions, which helps to avoid overfitting. we demonstrate that our algorithm produces stable low-error alignments on real expression data and further show a specific application to yeast knockout data that produces biologically meaningful results.
notung: dating gene duplications using gene family trees. large scale gene duplication is a major force driving the evolution of genetic functional innovation. whole genome duplications are widely believed to have played an important role in the evolution of the maize, yeast and vertebrate genomes. the use of evolutionary trees to analyze the history of gene duplication and estimate duplication times provides a powerful tool for studying this process. many studies in the molecular evolution literature have used this approach on small data sets, using analyses performed by hand. the rapid growth of genetic sequence data will soon allow similar studies on a genomic scale but such studies will be limited unless the analysis can be automated. even existing data sets admit alternative hypotheses that would be too tedious to consider without automation. in this paper, we describe a toolbox called notung that facilitates large scale analysis, using both rooted and unrooted trees. when tested on trees analyzed in the literature, notung consistently yielded result that agree with the assessments in the original publications. thus, notung provides a basic building block for inferring duplication dates from gene trees automatically and can also be used as an exploratory analysis tool for evaluating alternative hypotheses.
modeling dependencies in protein-dna binding sites. the availability of whole genome sequences and high-throughput genomic assays opens the door for in silico analysis of transcription regulation. this includes methods for discovering and characterizing the binding sites of dna-binding proteins, such as transcription factors. a common representation of transcription factor binding sites is a position specific score matrix (pssm). this representation makes the strong assumption that binding site positions are independent of each other. in this work, we explore bayesian network representations of binding sites that provide different tradeoffs between complexity (number of parameters) and the richness of dependencies between positions. we develop the formal machinery for learning such models from data and for estimating the statistical significance of putative binding sites. we then evaluate the ramifications of these richer representations in characterizing binding site motifs and predicting their genomic locations. we show that these richer representations improve over the pssm model in both tasks.
context-specific bayesian clustering for gene expression data. the recent growth in genomic data and measurement of genome-wide expression patterns allows to examine gene regulation by transcription factors using computational tools. in this work, we present a class of mathematical models that help in understanding the connections between transcription factors and functional classes of genes based on genetic and genomic data. these models represent the joint distribution of transcription factor binding sites and of expression levels of a gene in a single model. learning a combined probability model of binding sites and expression patterns enables us to improve the clustering of the genes based on the discovery of putative binding sites and to detect which binding sites and experiments best characterize a cluster. to learn such models from data, we introduce a new search method that rapidly learns a model according to a bayesian score. we evaluate our method on synthetic data as well as on real data and analyze the biological insights it provides.
probabilistic discovery of overlapping cellular processes and their regulation. many of the functions carried out by a living cell are regulated at the transcriptional level, to ensure that genes are expressed when they are needed. thus, to understand biological processes, it is thus necessary to understand the cell's transcriptional network. in this paper, we propose a novel probabilistic model of gene regulation for the task of identifying overlapping biological processes and the regulatory mechanism controlling their activation. a key feature of our approach is that we allow genes to participate in multiple processes, thus providing a more biologically plausible model for the process of gene regulation. we present an algorithm to learn this model automatically from data, using only genome-wide measurements of gene expression as input. we compare our results to those obtained by other approaches, and show significant benefits can be gained by modeling both the organization of genes into overlapping cellular processes and the regulatory programs of these processes. moreover, our method successfully grouped genes known to function together, recovered many regulatory relationships that are known in the literature, and suggested novel hypotheses regarding the regulatory role of previously uncharacterized proteins.
towards optimally multiplexed applications of universal dna tag systems. we study a design and optimization problem that occurs, for example, when single nucleotide polymorphisms (snps) are to be genotyped using a universal dna tag array. the problem of optimizing the universal array to avoid disruptive cross-hybridization between universal components of the system was addressed in a previous work. however, cross-hybridization can also occur assay-specifically, due to unwanted complementarity involving assay-specific components. here we examine the problem of identifying the most economic experimental configuration of the assay-specific components that avoids cross-hybridization. our formalization translates this problem into the problem of covering the vertices of one side of a bipartite graph by a minimum number of balanced subgraphs of maximum degree 1. we show that the general problem is np-complete. however, in the real biological setting the vertices that need to be covered have degrees bounded by d. we exploit this restriction and develop an o(d)-approximation algorithm for the problem. we also give an o(d)-approximation for a variant of the problem in which the covering subgraphs are required to be vertex-disjoint. in addition, we propose a stochastic model for the input data and use it to prove a lower bound on the cover size. we complement our theoretical analysis by implementing two heuristic approaches and testing their performance on simulated and real snp data.
efficient rule-based haplotyping algorithms for pedigree data. we study haplotype reconstruction under the mendelian law of inheritance and the minimum recombination principleon pedigree data. we prove that the problem of finding a mini-mum-recombinant haplotype configuration (mrhc) is in general np-hard. this is the first complexity result concerning the problem to our knowledge. an iterative algorithm based on blocks of consecutive resolved marker loci (called block-extension) is proposed. it is very efficient and can be used for large pedigrees with a large number of markers, especially for those data sets requiring few recombinants (or recombination events). a polynomial-time exact algorithm for haplotype reconstruction without recombinants is also presented. this algorithm first identifies all the necessary constraints based on the mendelian law and the zero recombinant assumption, and represents them using a system of linear equations over the cyclic group z2. by using a simple method based on gaussian elimination, we could obtain all possible feasible haplotype configurations. we have tested the block-extension algorithm on simulated data generated on three pedigree structures. the results show that the algorithm performs very well on both multi-allelic and biallelic data, especially when the number of recombinants is small.
the restriction scaffold problem. most shotgun sequencing projects undergo a long and costly phase of finishing, in which a partial assembly forms several contigs whose order, orientation and relative distance is unknown. we propose here a new technique that supplements the shotgun assembly data by cheap and simple complete restriction digests of the target. by computationally combining information from the contig sequences and the fragment sizes measured for several different enzymes, we seek to form a "scaffold" on which the contigs will be placed in their correct orientation, order and distance. we give a heuristic search algorithm for solving the problem and report on promising preliminary simulation results. the key to the success of the search scheme is the very rapid solution of its two time-critical subproblems that are solved precisely in linear time.our simulations indicate that with noise levels of some 3% relative error in measuring fragment sizes, using five enzymes, most datasets of 20 contigs can be correctly ordered, and the remaining ones have most of their pairs of neighboring contigs correct. hence, the technique has a potential to provide real help to finishing. even when the target clone remains unfinished, the ability to order and orient the contigs correctly makes the partial assembly both more accessible and more useful for biologists.
an exact solution for finding minimum recombinant haplotype configurations on pedigrees with missing data by integer linear programming. we study the problem of reconstructing haplotype configurations from genotypes on pedigree data with missing alleles under the mendelian law of inheritance and the minimum recombination principle, which is important for the construction of haplotype maps and genetic linkage/association analysis. our previous results show that the problem of finding a minimum-recombinant haplotype configuration (mrhc) is in general np-hard. the existing algorithms for mrhc either are heuristic in nature and cannot guarantee optimality, or only work under some restrictions (on e.g. the size and structure of the input pedigree, the number of marker loci, the number of recombinants in the pedigree, etc.). in addition, most of them cannot handle data with missing alleles and, for those that do consider missing data, they usually do not perform well in terms of minimizing the number of recombinants when a significant fraction of alleles are missing. in this paper, we develop an effective integer linear programming (ilp) formulation of the mrhc problem with missing data and a branch-and-bound strategy that utilizes a partial order relationship (and some other special relationships) among variables to decide the branching order. the partial order relationship is discovered in the preprocessing of constraints by considering unique properties in our ilp formulation. a directed graph is built based on the variables and their partial order relationship. by identifying and collapsing the strongly connected components in the graph, we may greatly reduce the size of an ilp instance. non-trivial (lower and upper) bounds on the optimal number of recombinants are introduced at each branching node to effectively prune the search tree. when multiple solutions exist, a best haplotype configuration is selected based on a maximum likelihood approach. our results on simulated data show that the algorithm could recover haplotypes with 50 loci from a pedigree of size 29 in seconds on a standard pc. its accuracy is more than 99.8% for data with no missing alleles and 98.3% for data with 20% missing alleles in terms of correctly recovered phase information at each marker locus. as an application of our algorithm to real data, we present some test results on reconstructing haplotypes from a genome-scale snp data set consisting of 12 pedigrees that have 0.8% to 14.5% missing alleles.
human and mouse gene structure: comparative analysis and application to exon prediction. we describe a novel analytical approach to gene recognition based on cross-species comparison we first undertook a comparison of orthologous genomic look from human and mouse, studying the extent of similarity in the number, size and sequence of exons and introns we then developed an approach for recognizing genes within such orthologous regions, by first aligning the regions using an iterative global alignment system and then identifying genes based on conservation of exonic features at aligned positions in both species the alignment and gene recognition are performed by new programs called glass and rosetta, respectively rosetta performed well at exact identification of coding exons in 117 orthologous pairs tested.
algorithms for identifying protein cross-links via tandem mass spectrometry. cross-linking technology combined with tandem mass spectrometry (ms-ms) is a powerful method that provides a rapid solution to the discovery of protein-protein interactions and protein structures. we studied the problem of detecting cross-linked peptides and cross-linked amino acids from tandem mass spectral data. our method consists of two steps: the first step finds two protein subsequences whose mass sum equals a given mass measured from the mass spectrometry; and the second step finds the best cross-linked amino acids in these two peptide sequences that are optimally correlated to a given tandem mass spectrum. we designed fast and space-efficient algorithms for these two steps, and implemented and tested them on experimental data of cross-linked hemoglobin proteins.
a compression algorithm for dna sequences and its applications in genome comparison. we present a lossless compression algorithm, gen-compress, for dna sequences, based on searching for approximate repeats. our algorithm achieves the best compression ratios for benchmark dna sequences, comparing to other dna compression programs [3, 7]. significantly better compression results show that the approximate repeats are one of the main hidden regularities in dna sequences. we then describe a theory of measuring the relatedness between two dna sequences. we propose to use d(x, y) = 1 &mdash; k(x) - k(x|y)/k(xy to measure the distance of any two sequences, where k stands for kolmogorov complexity [5]. here, k(x) - k(x|y) is the mutual information shared by x and y. but mutual information is not a distance, there is no triangle inequality. the distance d(x, y) is symmetric. it also satisfies the triangle inequality, and furthermore, it is universal [4]. it has not escaped our notice that the distance measure we have postulated can be immediately used to construct evolutionary trees from dna sequences, especially those that cannot be aligned, such as complete genomes. with more and more genomes sequenced, constructing trees from genomes becomes possible [1, 2, 6, 8]. kolmogorov complexity is not computable. we use gencompress to approximate it. we present strong experimental support for this theory, and demonstrate its applicability by correctly constructing a 16s (18s) rrna tree, and a whole genome tree for several species of bacteria. larger scale experiments are underway at the university of waterloo, with very promising results.
universal dna tag systems: a combinatorial design scheme. custom-designed dna arrays offer the possibility of simultaneously monitoring thousands of hybridization reactions these arrays show great potential for many medical and scientific applications such as polymorphism analysis and genotyping. relatively high costs are associated with the need to specifically design and synthesize problem specific arrays. recently, an alternative approach was suggested that utilizes fixed, universal arrays. this approach presents an interesting design problem&mdash;the arrays should contain as many probes as possible, while minimizing experimental errors caused by cross-hybridization. we use a simple thermodynamic model to cast this design problem in a formal mathematical framework. employing new combinatorial ideas, we derive an efficient construction for the design problem, and prove that our construction is near-optimal.
significance of inter-species matches when evolutionary rate varies. we develop techniques to estimate the statistical significance of gap-free alignments between two genomic dna sequences, using human-mouse alignments as an example. the sequences are assumed to be sufficiently similar that some but not all of the neutrally evolving regions (i.e., those under no evolutionary constraint) can be reliably aligned. our goal is to model the situation in which the neutral rate of evolution, and hence the extent of the aligning intervals, varies across the genome. in some cases, this permits the weaker of two matches to be judged as less likely to have arisen by chance, provided it lies in a genomic interval with a high level of background divergence. we employ a hidden markov model to capture variations in divergence rates, and assign probability values to gap-free alignments using techniques related to those used for the same purpose by blast. our methods are illustrated in detail using a 1.49 mb genomic region. preliminary results using all of human chromosome 22 indicate that these techniques will work for the entire human genome.
learning multiple evolutionary pathways from cross-sectional data. we introduce a mixture model of trees to describe evolutionary processes that are characterized by the accumulation of permanent genetic changes. the basic building block of the model is a directed weighted tree that generates a probability distribution on the set of all patterns of genetic events. we present an em-like algorithm for learning a mixture model of k trees and show how to determine k with a maximum likelihood approach. as a case study we consider the accumulation of mutations in the hiv-1 reverse transcriptase that are associated with drug resistance. the fitted model is statistically validated as a density estimator and the stability of the model topology is analyzed. we obtain a generative probabilistic model for the development of drug resistance in hiv that agrees with biological knowledge. further applications and extensions of the model are discussed.
an optimal procedure for gap closing in whole genome shotgun sequencing. tettelin et. al. proposed a new method for closing the gaps in whole genome shotgun sequencing projects. the method uses a multiplex pcr strategy in order to minimize the time and effort required to sequence the dna in the missing gaps. this procedure has been used in a number of microbial sequencing projects including streptococcus pneumoniae and other bacteria. in this paper we describe a theoretical framework for this problem and propose an improved method that guarantees to minimize the number of steps involved in the gap closure procedures. in given particular collection of n/2 dna fragments we describe a strategy that requires. 0.75 log n work in eight parallel rounds of experiment closely matching a corresponding lower bound 0.5 log of n
efficient exact value computation and applications to biosequence analysis. like other fields of life sciences, bioinformatics has turned to capture biological phenomena through probabilistic models, and to analyse these models using statistical methodology. a central computational problem in applying useful statistical procedures such as various hypothesis testing procedures is the computation of p-values. in this paper, we devise a branch and bound approach to efficient exact p-value computation, and apply it to a likelihood ratio test in a frequency table setting. by recursively partitioning the sample domain and bounding the statistic we avoid the explicit exhaustive enumeration of all possible outcomes which is currently carried by the standard statistical packages. the convexity of the test statistic is further utilized to confer additional speed-up.empirical evaluation demonstrates a reduction in the computational complexity of the algorithm, even in worst case scenarios, significantly extending the practical range for performing the exact test. we also show that speed-up greatly improves the sparser the underlying null hypothesis is; that computation precision actually increases with speed-up; and that computation time is very moderately affected by the magnitude of the computed p-value. these qualities make our algorithm an appealing alternative to the exhaustive test, the χ2 asymptotic approximation and monte carlo samplers in the respective regimes.the proposed method is readily extendible to other tests and test statistics of interest. we survey several examples of established biosequence analysis methods, where small sample size and sparseness do occur, and to which our computational framework could be applied to improve performance. we briefly demonstrate this with two applications, measuring binding site positional correlations in dna, and detecting compensatory mutation events in functional rna.
phylogenetically and spatially conserved word pairs associated with gene expression changes in yeasts. background. transcriptional regulation in eukaryotes is often multifactorial, involving multiple transcription factors binding to the same transcription control region (e.g., upstream activating sequences and enhancers), and to understand the regulatory content of eukaryotic genomes it is necessary to consider the co-occurrence and spatial relationships of individual binding sites. the identification of sequences conserved among related species (often known as phylogenetic footprinting) has been successfully used to identify individual transcription factor binding sites. here, we extend this concept of functional conservation to higher-order features of transcription control regions involved in the multifactorial control of gene expression.results. we used the genome sequences of four yeast species of the genus saccharomyces to identify sequences potentially involved in multifactorial control of gene expression. we found 1,117 potential regulatory "templates": pairs of hexameric sequences that are jointly conserved in transcription regulatory regions and also exhibit non-random relative spacing. many of the individual sequences in these templates correspond to known transcription factor binding sites, and the sets of genes containing a particular template in their transcription control regions tend to be differentially expressed in conditions where the corresponding transcription factors are known to be active.conclusions. the incorporation of both joint conservation and spacing constraints of sequence pairs predicts groups of target genes that were specific for common patterns of gene expression. our work suggests that positional information, especially the relative spacing between transcription factor binding sites, may represent a common organizing principle of transcription control regions.
finding motifs for insufficient number of sequences with strong binding to transcription facto. finding motifs is an important problem in computational biology. our paper makes two major contributions to this problem. firstly, we better characterize the types of problem instances that cannot be solved by most existing methods of finding motifs. secondly, we introduce a different method, which is shown to succeed for various problem instances for which popular existing methods fail.most existing computational methods to finding motifs are based on the strong-signal model wherein only strong-signal sequences (i.e. those that are known to contain binding sites very similar to the motif) are considered as input and weak-signal sequences (i.e. those do not contain any sub-string similar to the motif) are disregarded.buhler and tompa have studied the limitations of methods based on the strong-signal model. they characterized the problem instances for which the motif is unlikely to be found in terms of the number of input (strong-signal) sequences needed under the assumption that each input sequence contains exactly one binding site. they further gave a method to calculate the minimum number of input sequences required.we re-characterize the limitations of the strong-signal model in terms of the minimum total number of binding sites, rather than the minimum number of strong-signal sequences, required to be in the input data set. we use a probability matrix to represent a motif instead of a string pattern to calculate the minimum total number of binding sites required. this new characterization is shown to be more general and realistic.next, we introduce a more general and realistic energy-based model, which considers all available sequences (including weak-signal sequences) with varying degrees of binding strength to the transcription factors (as measured experimentally by observed color intensity). given varying degrees of binding strength, our model can consider sequences ranging from those that contain more than one binding site to those that are weak sequences. by treating sequences with different degrees of binding strength differently, we develop a heuristic algorithm called ebmf (energy-based motif finding algorithm) using an em-like approach to find motifs under our model. this ebmf algorithm can find motifs for data sets that do not even have the required minimum number of binding sites as previously derived for the strong-signal model. our algorithm compares favorably with common motif-finding programs alignace and meme, which are based on the strong-signal model. in particular, for some simulated and real data sets, our algorithm finds the motif when both alignace and meme fail to do so.
multiple maxima of likelihood in phylogenetic trees: an analytic approach. maximum likelihood (ml) is a widely used criterion for selecting optimal evolutionary trees. however, little is known on the nature of the likelihood surface for trees, especially as to the frequency of multiple optima. we initiate an analytic study for identifying sequences that generate multiple optima. we report a new approach to calculating ml directly, which we have used to find large families of sequences that have multiple optima, including sequences with a continuum of optimal points. such datasets are best supported by different (two or more) phylogenies that vary significantly in their timings of evolutionary events some standard biological processes can lead to data with multiple optima and consequently the field needs further investigation. our results imply that hill climbing techniques, as currently implemented in various software packages, cannot guarantee to find the global ml point, even if it is unique.
maximum likelihood on four taxa phylogenetic trees: analytic solutions. maximum likelihood (ml) is increasingly used as an optimality criterion for selecting evolutionary trees (felsenstein, 1981), but finding the global optimum is a hard computational task. because no general analytic solution is known, numeric techniques such as hill climbing or expectation maximization (em), are used in order to find optimal parameters for a given tree. so far, analytic solutions were derived only for the simplest model - three taxa, two state characters, under a molecular clock (mc). quoting ziheng yang (2000), who initiated the analytic approach, "this seems to be the simplest case, but has many of the conceptual and statistical complexities involved in phylogenetic estimation".in this work, we give analytic solutions for four taxa, two state characters under a molecular clock. the change from three to four taxa incurs a major increase in the complexity of the underlying algebraic system, and requires novel techniques and approaches. we start by presenting the general maximum likelihood problem on phylogenetic trees as a constrained optimization problem, and the resulting system of polynomial equations. in full generality, it is infeasible to solve this system, therefore specialized tools for the mc case are developed.four taxa rooted trees have two topologies -- the fork (two subtrees with two leaves each) and the comb (one subtree with three leaves, the other with a single leaf). we combine the ultrametric properties of mc trees with the hadamard conjugation (hendy and penny, 1993) to derive a number of topology dependent identities. employing these identities, we substantially simplify the system of polynomial equations. we finally use tools from algebraic geometry (e.g. grobner bases, ideal saturation, resultants) and employ symbolic algebra software to obtain closed form analytic solutions (expressed parametrically in the input data) for the fork topology, and analytic solutions for the comb. we show that in contrast to the fork, the comb has no closed form solutions (expressed by radicals in the input data). in general, four taxa trees can have multiple ml points (steel, 1994, chor et. al., 2001). in contrast, we can now prove that under the mc assumption, both the fork and the comb topologies have a unique (local and global) ml point.
designing rna structures: natural and artificial selection. messenger rna (mrna) sequences serve as templates for proteins according to the triplet code, in which each of the 43 = 64 different codons (sequences of three consecutive nucleotide bases) in rna either terminate transcription or map to one of the 20 different amino acids (or residues) which build up proteins. because there are more codons than residues, there is inherent redundancy in the coding. certain residues (e.g. tryptophan) have only a single corresponding codon, while other residues (e.g. arginine) have as many as six corresponding codons. this freedom implies that the number of possible rna sequences coding for a given protein grows exponentially in the length of the protein.thus nature has wide latitude to select among mrna sequences which are informationally equivalent, but structurally and energetically divergent. in this paper, we explore how nature takes advantage of this freedom, and how to algorithmically design structures more energetically favorable than have been built through natural selection. in particular:natural selection, -- we perform the first large-scale computational experiment comparing the stability of mrna sequences from a variety of organisms to random synonymous sequences which respect the codon preferences of the organism. this experiment was conducted on over 27,000 sequences from 34 microbial species with 36 genomic structures. we provide evidence that in all genomic structures highly stable sequences are disproportionately abundant, and in 19 of 36 cases highly unstable sequences are disproportionately abundant. this suggests that the stability of mrna sequences is subject to natural selection.artificial selection -- motivated by these biological results, we examine the algorithmic problem of designing the most stable and unstable mrna sequences which code for a target protein. we give a polynomial-time dynamic programming solution to the most stable sequence problem (mssp), which is asymptotically no more complex than secondary structure prediction. we show that the corresponding least stable sequence problem (lssp) is np-complete, and develop two heuristics for the construction of such sequences.we have implemented these algorithms, and present experimental results placing the high/low stability sequences in context with both wildtype and random encodings. our implementation has already been applied to the design of rna "code-words" creating little or no secondary structure in rna computing [1, 12], and we anticipate a variety of other applications of this work to sequence design problems [16].
fast recovery of evolutionary trees with thousands of nodes. we present a novel distance-based algorithm for evolutionary tree reconstruction. our algorithm reconstructs the topology of a tree with n leaves in o(n2) time using o(n) working space. in the general markov model of evolution the algorithm recovers the topology successfully with (1 &mdash; &ogr;(1)) probability from sequences with polynomial length in n. moreover, for almost all trees, our algorithm achieves the same success probability on polylogarithmic sample sizes. the theoretical results are supported by simulation experiments involving trees with 500, 1895, and 3135 leaves. the topologies of the trees are recovered with high success from 2000 bp dna sequences.
handling long targets and errors in sequencing by hybridization. sequencing by hybridization (sbh) is a dna sequencing technique, in which the sequence is reconstructed using its k-mer content. this content, which is called the spectrum of the sequence, is obtained by hybridization to a universal dna array. standard universal arrays contain all k-mers for some fixed k, typically 8 to 10. currently, in spite of its promise and elegance, sbh is not competitive with standard gel-based sequencing methods. this is due to two main reasons: lack of tools to handle realistic levels of hybridization errors, and an inherent limitation on the length of uniquely reconstructible sequence by standard universal arrays.in this paper we deal with both problems. we introduce a simple polynomial reconstruction algorithm which can be applied to spectra from standard arrays and has provable performance in the presence of both false negative and false positive errors. we also propose a novel design of chips containing universal bases, that differs from the one proposed by preparata et al. we give a simple algorithm that uses spectra from such chips to reconstruct with high probability random sequences of length lower only by a squared log factor compared to the information theoretic bound. our algorithm is very robust to errors, and has a provable performance even if there are both false negative and false positive errors. simulations indicate that its sensitivity to errors is also very small in practice.
perfect phylogeny and haplotype assignment. this paper is concerned with the reconstruction of perfect phylogenies from binary character data with missing values, and related problems of inferring complete haplotypes from haplotypes or genotypes with missing data. in cases where the problems considered are np-hard we assume a rich data hypothesis under which they become tractable. natural probabilistic models are introduced for the generation of character vectors, haplotypes or genotypes with missing data, and it is shown that these models support the rich data hypothesis. the principal results include: a near-linear time algorithm for inferring a perfect phylogeny from binary character data (or haplotype data) with missing values, under the rich data hypothesis; a quadratic-time algorithm for inferring a perfect phylogeny from genotype data with missing values with high probability, under certain distributional assumptions; demonstration that the problems of maximum-likelihood inference of complete haplotypes from partial haplotypes or partial genotypes can be cast as minimum-entropy disjoint set cover problems; in the case where the haplotypes come from a perfect phylogeny, a representation of the set cover problem as minimum-entropy covering of subtrees of a tree by nodes; an exact algorithm for minimum-entropy subtree covering, and demonstration that it runs in polynomial time when the subtrees have small diameter; demonstration that a simple greedy approximation algorithm solves the minimum-entropy subtree covering problem with relative error tending to zero when the number of partial haplotypes per complete haplotype is large; an asymptotically consistent method of estimating the frequencies of the complete haplotypes in a perfect phylogeny, under an iid model for the distribution of missing data; computational results on real data demonstrating the effectiveness of a the greedy algorithm for inferring haplotypes from genotypes with missing data, even in the absence of a perfect phylogeny..
systematic and automated discovery of patterns in prosite families. prosite is a method for protein classification which relies on a database of biologically significant sites and patterns in protein sequences. most patterns in prosite have been gathered by a a labor intensive combination of experimental characterization of functional residues and sequence alignment. in this paper we present a new and efficient supervised learning procedure, based on the splash deterministic pattern discovery algorithm and on a framework to assess the statistical significance of patterns. we demonstrate its application to the fully automatic discovery of patterns in 974 prosite families. for these families, splash generates patterns with better specificity and/or sensitivity in 28%, identical statistics in 48%, and worse statistics in 15% of the cases; for the remaining families, patterns exhibited mixed behavior. second, we have characterized the amount of overlap, on the sequences, between newly discovered patterns and those in prosite. in about 75% of the cases, splash patterns identify sequence sites that overlap more than 50% with those reported in prosite. of the 272 patterns which perform strictly better than the corresponding prosite pattern, 178 show more than 70% overlap with the prosite pattern. third, our results suggest that the statistical significance of discovered patterns correlates well with their biological significance. finally, we use the trypsin subfamily of serine proteases to illustrate the use of this method to exhaustively discover all motifs in a family that are statistically and biologically significant. the complete analysis is sufficiently rapid, taking less than a day for all prosite families, to enable the use this methodology for routine curation of existing motif and profile databases.
haplotyping as perfect phylogeny: conceptual framework and efficient solutions. the next high-priority phase of human genomics will involve the development of a full haplotype map of the human genome [12]. it will be used in large-scale screens of populations to associate specific haplotypes with specific complex genetic-influenced diseases. a prototype haplotype mapping strategy is presently being finalized by an nih working-group. the biological key to that strategy is the surprising fact that genomic dna can be partitioned into long blocks where genetic recombination has been rare, leading to strikingly fewer distinct haplotypes in the population than previously expected [12, 6, 21, 7].in this paper we explore the algorithmic implications of the key (and now realistic) "no-recombination in long blocks" observation, for the problem of inferring haplotypes in populations. we observe that the no-recombination assumption is very powerful. this assumption, along with the standard population-genetic assumption of infinite sites [23, 14] imposes severe combinatorial constraints on the permitted solutions to the haplotype inference problem, leading to an efficient deterministic algorithm to deduce all features of the permitted haplotype solution(s) that can be known with certainty. the technical key is to view haplotype data as disguised information about paths in an unknown tree, and the haplotype deduction problem as a problem of reconstructing the tree from that path information. this formulation allows us to exploit deep theorems and algorithms from graph and matroid theory to efficiently find one permitted solution to the haplotype problem; it gives a simple test to determine if it is the unique solution; if not, we can implicitly represent the set of all permitted solutions so that each can be efficiently created.
stochastic models inspired by hybridization theory for short oligonucleotide arrays. high density oligonucleotide expression arrays are a widely used tool for the measurement of gene expression on a large scale. affymetrix genechip arrays appear to dominate this market. these arrays use short oligonucleotides to probe for genes in an rna sample. due to optical noise, non-specific hybridization, probe-specific effects, and measurement error, ad-hoc measures of expression, that summarize probe intensities, can lead to imprecise and inaccurate results. various researchers have demonstrated that expression measures based on simple statistical models can provide great improvements over the ad-hoc procedure offered by affymetrix. recently, physical models based on molecular hybridization theory, have been proposed as useful tools for prediction of, for example, non-specific hybridization. these physical models show great potential in terms of improving existing expression measures. in this paper we suggest that the system producing the measured intensities is too complex to be fully described with these relatively simple physical models and we propose empirically motivated stochastic models that compliment the above mentioned molecular hybridization theory to provide a comprehensive description of the data. we discuss how the proposed model can be used to obtain improved measures of expression useful for the data analysts.
computational analysis of the human and other mammalian genomes. working drafts are now available for the human, mouse and rat genomes, and other mammalian genome sequences are on the way. we discuss some of the key bioinformatic analysis problems presented by this data, including the problems of assembling the sequence, finding the genes and other functional elements, and reconstructing the evolutionary history of the genomes. recent comparisons between the human and mouse genomes have revealed that approximately 5% of the human genome appears to be more conserved with the orthologous regions in mouse than can be explained assuming neutral evolution. is this the portion of the genome under selection for specific functions? how can we use comparative genomics to further pinpoint functional elements? how accurately can we reconstruct the evolutionary history of key parts of the human genome? we briefly outline some recent work (described in more detail in adam siepel's talk) combining hidden markov models, used in bioinformatics to analyse dna from a single species, with continuous time markov models of molecular evolution, used to reconstruct evolutionary history of several species. while still a long way from answering these questions, these methods may contribute to such investigations.
an integrated probabilistic model for functional prediction of proteins. we develop an integrated probabilistic model to combine protein physical interactions, genetic interactions, highly correlated gene expression network, protein complex data, and domain structures of individual proteins to predict protein functions. the model is an extension of our previous model for protein function prediction based on markovian random field theory. the model is flexible in that other protein pairwise relationship information and features of individual proteins can be easily incorporated. two features distinguish the integrated approach from other available methods for protein function prediction. one is that the integrated approach uses all available sources of information with different weights for different sources of data. it is a global approach that takes the whole network into consideration. the second feature is that the posterior probability that a protein has the function of interest is assigned. the posterior probability indicates how confident we are about assigning the function to the protein. we apply our integrated approach to predict functions of yeast proteins based upon mips protein function classifications and upon the interaction networks based on mips physical and genetic interactions, gene expression profiles, tandem affinity purification (tap) protein complex data, and protein domain information. we study the sensitivity and specificity of the integrated approach using different sources of information by the leave-one-out approach. in contrast to using mips physical interactions only, the integrated approach combining all of the information increases the sensitivity from 57% to 87% when the specificity is set at 57%-an increase of 30%. it should also be noted that enlarging the interaction network greatly increases the number of proteins whose functions can be predicted.
inferring domain-domain interactions from protein-protein interactions. protein-protein interactions are important events in cellular and biochemical processes within a cell. several researchers have undertaken the task of analyzing protein-protein interactions covering all genes of an organism by using yeast two-hybrid assays. protein-protein interactions involve physical interactions between protein domains. therefore, understanding protein interactions at the domain level gives a global view of the protein interaction network, and possibly extends functions of proteins. in this study, we present a maximum likelihood approach to infer domain-domain interactions from the 5719 yeast protein-protein interactions obtained in the high throughput two-hybrid experiments by uetz et al., 2000 and ito et al., 2001. the accuracies of our predictions are measured at the protein level. our study includes the following three results: (1) using the inferred domain-domain interactions, we predict interactions between proteins and achieve 39.0% specificity and 79.7% sensitivity; (2) our predicted protein-protein interactions have a significant overlap with the mips(http://mips.gfs.de) protein-protein interactions obtained by methods other than the two-hybrid systems; and (3) the mean correlation coefficient of the gene expression profiles for our predicted interacting pairs is significantly higher than that for random pairs as well as that of interacting pairs in uetz's and ito's experimental data. our method has shown robustness in analyzing incomplete data sets and dealing with various experimental errors. we find several novel protein-protein interactions such as rps0a interacting with apg17 and taf40 interacting with spt3, which are consistent with the functions of the proteins.
tree fitting: an algebraic approach using profile distances. distance methods play a central role in the field of phylogeny reconstruction, providing fast, efficient algorithms which yield reliable trees. the taxonomy problem is; given a set of dna or amino acid sequences from several species, accurately reconstruct a phylogenetic tree representing their evolutionary history. distance methods approach this problem by inferring a distance matrix of species-to-species evolutionary distances, and finding a tree which approximates the distance matrix. our results consider the approach of using profile distances instead of leaf-to-leaf distances. we consider the vector space of tree metrics with regard to a basis generated by profile distances given a fixed tree topology, we show how to project edge weights onto a topology based upon its set of profile distances. the projected edge weights provide topological insight, as negative edge weights will point to false edges in the topology. although the presence of such negative edge weights is not guaranteed, we show that if the test tree is sufficiently close to the target tree in topology, negative edge weights will highlight the false edges. an algorithm is presented which uses this information to accurately reconstruct tree metrics.
sequencing by hybridization using direct and reverse cooperating spectra. dna sequencing by hybridization, proposed about a decade ago as an alternative to standard electrophoresis-based sequencing techniques, is relevant not only to sequencing per se but also to diagnostics and therapeutics. the inherent structural inadequacy of traditional probe patterns and well-known hybridization shortcomings had for some time deflated the interest in this approach. renewed interest for this topic has been generated by our recent discovery of a novel probing scheme whose performance for the first time asymptotically meets the information theory bound. after settling the question of asymptotic performance, due to the sizable volume of potential applications, the research focus has naturally shifted to issues of algorithmic fine tunings aimed at improving the performance "constants". in this paper, we introduce as a figure of merit the nucleotide-per-feature ratio (for a given confidence level), i.e., the length of a reliabily reconstructible (random) sequence divided by the number of probes placed on the sequencing array, regardless of the fabrication technology, and we explore the capabilities offered by the joint use of multiple different arrays in sequencing the same dna sequence. in particular we consider a probing scheme based on the use of the spectra pertaining to a given probing pattern and to its reversal (referred to here as tandem spectra), and we show analytically and experimentally a performance improvement per unit of microarray area of about 4/3 (in a representative instance) over the conventional single-spectrum approach. the proposed tandem-spectrum reconstruction, in conjunction with a "voting provision" discussed elsewhere (whereby one of two competing alternatives is chosen if the corresponding probes are less numerous in the current prefix of the reconstructive sequence), is the best known technique for sequencing by hybridization.
contig selection in physical mapping. in physical mapping one orders a set of genetic landmarks or a library of cloned fragments of dna according to their position in the genome. this is a preparatory step for efficient sequencing. our approach to physical mapping divides the problem into smaller and easier subproblems by partitioning the probe set into independent parts (contigs). the focus is on the selection of probe sets which can be grouped together into contigs. we introduce a new distance function between probes, the averaged rank distance (ard). the ard measures the reliability of certain probe configurations in physical maps which are generated by bootstrap resampling of the raw data. this mimics an independent experiment repetition in silico. the ard measures the distances of probes within a contig and smoothes the distances of probes in different contigs. it shows distinct jumps at contig borders. this makes it appropriate for contig selection by clustering. we designed a physical mapping algorithm that makes use of these observations and seems to be particularly well suited to the delineation of reliable contigs. we evaluated our method on data sets from two physical mapping projects. in comparison to a physical map of pasteurella haemolytica that was computed using simulated annealing, the newly computed map is considerably cleaner. on data from xylella fastidiosa the contigs produced by the new method could be compared to a map produced by a group of experts and the two maps largely agree in the definition of the contigs. the results of our method have already proven helpful for the design of experiments aiming at further improving the quality of a map.
analysis of gene expression profiles: class discovery and leaf ordering. we approach the class discovery and leaf ordering problems using spectral graph partitioning methodologies. for class discovery or clustering, we present a min-max cut hierarchical clustering method and show it produces subtypes quite close to human expert labeling on the lymphoma dataset with 6 classes. on optimal leaf ordering for displaying the gene expression data, we present a sequential ordering method that can be computed in o(n2) time which also preserves the cluster structure. we also show that the well known statistic methods such as f-statistic test and the principal component analysis are very useful in gene expression analysis.
accurate detection of very sparse sequence motifs. protein sequence alignments are more reliable the shorter the evolutionary distance. here, we align distantly related proteins using many closely spaced intermediate sequences as stepping stones. such transitive alignments can be generated between any two proteins in a connected set, whether they are direct or indirect sequence neighbours in the underlying library of pairwise alignments. we have implemented a greedy algorithm, maxflow, using a novel consistency score to estimate the relative likelihood of alternative paths of transitive alignment. in contrast to traditional profile models of amino acid preferences, maxflow models the probability that two positions are structurally equivalent and retains high information content across large distances in sequence space. thus, maxflow is able to identify sparse and narrow active-site sequence signatures which are embedded in high-entropy sequence segments in the structure-based multiple alignment of large diverse enzyme superfamilies. in a challenging benchmark, maxflow yields better reliability and double coverage compared to available sequence alignment software. this promises to increase information returns from functional and structural genomics, where reliable sequence alignment is a bottleneck to transferring the functional or structural characterization of model proteins to entire protein families and superfamilies.
a data-analysis pipeline for large-scale gene expression analysis. in this article we describe a method for characterization of large cdna clone libraries based on oligonucleotide fingerprints (ofps). the main advantage of this technique lies in that, without sequencing, each clone is tagged in an almost unique way, which has a couple of interesting applications, e.g. clustering of clones that belong to the same gene or gene family followed by sequencing of representative clones for each cluster. moreover, small clusters are likely to represent rarely expressed genes, which are difficult to find by common approaches. we will demonstrate that in the est projects carried out in our lab the global redundancy is very low compared to similar projects described in the literature, and simultaneously the number of unknown (novel) genes detected using this method is very high. in addition ofps can be used directly for data base mining, since the sequences of the oligos matching a specific clone is known recent results are presented, which underline the potential of our method in finding novel genes or genes homologous to known data. we will also address future applications in gene expression profiling, and give an outline of the various bioinformatics tools, which have been developed so far and which are used for automated data processing and analysis.
fifty years of sequence analysis: what have we learned? in 1955, not quite fifty years ago, sanger's group published the first amino acid sequence of a protein, bovine insulin. later that year, they reported sequences from sheep and pig, each of which showed a small number of differences from the bovine. even earlier, sequences of several polypeptide hormones had been worked out, and their similarities and differences had already caught the eye of evolutionists. from this tiny amount of data sprang the hope, considered unrealistic by many at the time, that the histories of all living organisms might be reconstructed. shortly thereafter, the notion that gene duplications were the source of most proteins was given a boost when the sequences of the alpha and beta chains of hemoglobin were reported to be more than 40 percent identical. by the 1960's, amino acid sequence analysis had taken hold as the major tool for determining the divergences of both creatures and their proteins. the obvious similarities of bacterial and eukaryotic enzyme sequences lent hope that the routes leading to all the major groups of organisms could be established, and the observation that proteins with different functions could have similar sequences showed that radical changes of function were possible. the paradigm that "all new proteins came from old proteins" became the dogma of the day. by the 1970's, the rna sequencing of certain rna moieties was almost routine, and the sequencing of numerous small subunit rrnas revealed unexpectedly that there were three domains of life, now referred to as archaea, bacteria and eukarya. the finding framed one of the major mysteries of all biology: which group came first and how are the others related to it? to this day the question has not been satisfactorily resolved. the advent of dna sequencing in the late 1970's ushered in a new era, the deluge of data making all previous work seem trivial, even if fundamental questions remained. the campaign in the 1980's to sequence the human genome changed the nature of biological inquiry in a major way. comparative genomics may indeed reveal the patterns of how the major life forms have evolved. among recent successes using the genomic approach has been the unraveling and intertwining of proteins involved in photosynthesis and nitrogen fixation and their spread through the prokaryotic world. on another front, the history of protein folds is being analyzed with surprising clarity. the technological advances that have made all this possible--computers, robotics, photochemistry, and much more--are as mind-numbing as the results. but where are we going? what do we want to know? although some of the evolutionary questions framed fifty years ago have been answered in part, many remain. what were the primordial proteins and how did they arise? what was the nature of the first cells? although sequence analysis alone may not tell all, it has given us a great beginning. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
computing life and global technologies (abstract only). the view &ldquo;biology is an informational science&rdquo; is now widely accepted&mdash;certainly catalyzed in part by the success of the human genome project. there are three levels of biological information: 1-dimensional information of dna, the 3-dimensional information of proteins, and the 4-dimensional (time variant) information of biological systems and networks. the key to deciphering biological information at each of these levels are the global technologies which analyze many genes, dnas or proteins at one time. i will discuss several new and pioneering global technologies for genomics and proteomics. information at each of these levels poses striking computational challenges, which will be discussed. the importance of the need for intimate interactions between biologists, computer scientists and mathematicians will also be discussed, as well as a new approach for teaching biology that may be effective for cross-disciplinary communication.
a bayesian approach to transcript estimation from gene array data: the beam technique. we present a new statistically optimal approach to estimate transcript levels and ratios from one or more gene array experiments. the bayesian estimation of array measurements (beam) technique uses a model of measurement noise and prior information to estimate biological expression levels. it provides a principled method to deal with negative expression level measurements, combine multiple measurements, and identify changes in expression level. beam is more flexible than existing techniques, because it does not assume a specific functional form for noise and prior models. rather, it uses a more accurate noise model developed from experimental data, a process we illustrate here using affymetrix yeast chips.
mining protein family specific residue packing patterns from protein structure graphs. finding recurring residue packing patterns, or spatial motifs, that characterize protein structural families is an important problem in bioinformatics. we apply a novel frequent subgraph mining algorithm to three graph representations of protein three-dimensional (3d) structure. in each protein graph, a vertex represents an amino acid. vertex-residues are connected by edges using three approaches: first, based on simple distance threshold between contact residues; second using the delaunay tessellation from computational geometry, and third using the recently developed almost-delaunay tessellation approach.applying a frequent subgraph mining algorithm to a set of graphs representing a protein family from the structural classification of proteins (scop) database, we typically identify several hundred common subgraphs equivalent to common packing motifs found in the majority of proteins in the family. we also use the counts of motifs extracted from proteins in two different scop families as input variables in a binary classification experiment. the resulting models are capable of predicting the protein family association with the accuracy exceeding 90 percent. our results indicate that graphs based on both almost-delaunay and delaunay tessellations are sparser than the contact distance graphs; yet they are robust and efficient for mining protein spatial motif.
tests for gene clustering. comparing chromosomal gene order in two or more related species is an important approach to studying the forces that guide genome organization and evolution. linked clusters of similar genes found in related genomes are often used to support arguments of evolutionary relatedness or functional selection. however, as the gene order and the gene complement of sister genomes diverge progressively due to large scale rearrangements, horizontal gene transfer, gene duplication and gene loss, it becomes increasingly difficult to determine whether observed similarities in local genomic structure are indeed remnants of common ancestral gene order, or are merely coincidences.a rigorous comparative genomics requires principled methods for distinguishing chance commonalities, within or between genomes, from genuine historical or functional relationships. in this paper, we construct tests for significant groupings against null hypotheses of random gene order, taking incomplete clusters, multiple genomes and gene families into account. we consider both the significance of individual clusters of pre-specified genes, and the overall degree of clustering in whole genomes.
geometric algorithms for the analysis of 2d-electrophoresis gels. in proteomics 2-dimensional gel electrophoresis (2-de) is a separation technique for proteins. the resulting protein spots can be identified by either using picking robots and subsequent mass spectrometry or by visual cross inspection of a new gel image with an already analyzed master gel. difficulties especially arise from inherent noise and irregular geometric distortions in 2-de images. aiming at the automated analysis of large series of 2-de images, or at the even more difficult interlaboratory gel comparisons, the bottleneck is to solve the two most basic algorithmic problems with high quality: identifying protein spots and computing a matching between two images. for the development of the analysis software carol at freie universit&auml;t berlin we have reconsidered these two problems and obtained new solutions which rely on methods from computational geometry. their novelties are: 1. spot detection is also possible for complex regions formed by several &ldquo;merged&rdquo; (usually saturated) spots; 2. user-defined landmarks are not necessary for the matching. furthermore, images for comparison are allowed to represent different parts of the entire protein pattern, which only partially &ldquo;overlap&rdquo;. the implementation is done in a client server architecture to allow queries via the internet. we also discuss and point at related theoretical questions in computational geometry.
recent duplication, evolution and assembly of the human genome. it has been estimated that 5% of the human genome consists of interspersed duplicated material that has arisen over the last 30 million years of evolution. two categories of recent duplicated segments can be distinguished: segmental duplications between non-homologous chromosomes (transchromosomal duplications) and duplications largely restricted to a particular chromosome (chromosome-specific duplications). a large proportion of these duplications exhibit an extraordinarily high degree of sequence identity at the nucleotide level (>95%) spanning large (1--100 kb) genomic distances. through processes of paralogous recombination, these same regions are targets for rapid evolutionary turnover among the genomes of closely related primates. the dynamic nature of these regions in terms of recurrent chromosomal structural rearrangement and their ability to create fusion genes from juxtaposed cassettes suggests that duplicative transposition has been an important force in the evolution of our genome. cycles of segmental duplication over periods of evolutionary time may provide the underlying mechanism for domain accretion and the increased modular complexity of the vertebrate proteome. further, our data suggest that a small fraction of important human genes may have emerged recently through duplication processes and will not possess definitive orthologues in the genomes of model organisms. i will discuss computational methods developed in my laboratory to 1) unambiguously identify recent genomic duplicates within the human genome and 2) to assess their importance in hominoid gene innovation. the impact of this chromosomal architecture for assembly of the final draft sequence will be discussed.
the greedy path-merging algorithm for sequence assembly. two different approaches to determining the human genome are currently being pursued: one is the &ldquo;clone-by-clone&rdquo; approach, employed by the publicly-funded. human genome project, and the other is the &ldquo;whole genome shotgun&rdquo; approach, favored by researchers at celera genomics. an interim strategy employed at celera, called hierarchical assembly, makes use of preliminary data produced by both approaches. this paper introduces the bactig ordering problem, which is a key problem that arises in this context, and presents an efficient heuristic called the greedy path-merginq algorithm that performs well on real data.
approximate matching of secondary structures. several methods have been developed for identifying more or less complex rna structures in a genome. whatever the method is, it is always based on the search of conserved primary and secondary structures. while various efficient methods have been developed for searching motifs of the primary structure, usually represented as regular expressions, few effort has been expended in the efficient search of secondary structure signals. by a helix, we mean a structure defined by a combination of sequence and folding constraints. we present a flexible algorithm that searches for all approximate matches of a helix in a genome. helices are represented by special regular expressions, that we call secondary expressions. the method is based on an alignment graph constructed from several copies of a pushdown automaton, arranged one on top of another. the worst time complexity is o(rpn), where n is the size of the genome, p the size of the secondary expression, and r its number of union symbols. we present our results of searching for specific signals of the trna and rnase p rna in two genomes.
protein similarity from knot theory and geometric convolution. shape similarity is one of the most elusive and intriguing questions of nature and mathematics. proteins provide a rich domain in which to test theories of shape similarity. proteins can match at different scales and in different arrangements. sometimes the detection of common local structure is sufficient to infer global alignment of two proteins; at other times it provides false information. proteins with very low sequence identity may share large substructures, or perhaps just a central core. there are even examples of proteins with nearly identical primary sequence in which α-helices have become β-sheets.shape similarity can be formulated (i) in terms of global metrics, such as rmsd or hausdorff distance, (ii) in terms of subgraph isomorphisms, such as the detection of shared substructures with similar relative locations, or (iii) purely topologically, in terms of the cohomology induced by structure preserving transformations. existing protein structure detection programs are built on the first two types of similarity. the third forms the foundations of knot theory.the thesis of this paper is: protein similarity detection leads naturally to an algorithm operating at the metric, relational, and homotopic scales. the paper introduces a definition of similarity based on atomic motions that preserve local backbone topology without incurring significant distance errors. such motions are motivated by the physical requirements for rearranging subsequences of a protein. similarity detection then seeks rigid body motions able to overlay pairs of substructures, each related by a substructure-preserving motion, without necessarily requiring global structure preservation. this definition is general enough to span a wide range of questions: one can ask for full rearrangement of one protein into another while preserving global topology, as in drug design; or one can ask for rearrangements of sets of smaller substructures, each of which preserves local but not global topology, as in protein evolution.in the appendix, we exhibit an algorithm for answering the general question. that algorithm has the complexity of robot motion planning. in the text, we consider a more common case in which one seeks protein similarity by rearrangements of relatively short peptide segments. we exhibit an algorithm based on writhing numbers that runs in time o(n2) to o(n4). we define and use a new datastructure, called geometric self-convolution, within this algorithm.contributions: we believe that this is the first paper to consider carefully the need for combining metric and homotopic qualities in seeking protein similarity. we provide a parameterized definition of similarity that leads naturally to a metric in protein space. we exhibit algorithms for computing the metric and detecting similarity. we report results obtained with three pairs of proteins, each pair exhibiting different typical characteristics.
from profiles to patterns and back again: a branch and bound algorithm for finding near optimal motif profiles. an important part of deciphering gene regulatory mechanisms is discovering transcription factor binding sites. in many cases, these sites can be detected because they are often overrepresented in genomic sequences. the detection of the overrepresented signals in sequences, or motif-finding has become a central problem in computational biology. there are two major computational frameworks for attacking the motif finding problem which differ in their representation of the signals. the most popular is the profile or pssm (position specific scoring matrix) representation. the goal of these algorithms is to obtain probabilistic representations of the overrepresented signals. another is the consensus pattern or pattern with mismatches representation which represents a signal as discrete consensus pattern and allows some mismatches to occur in each instance of the pattern. the advantage of profiles is the expressiveness of their representation while the advantage of the consensus pattern approach is the existence of efficient algorithms that guarantee discovery of the best patterns. in this paper we present a unified framework for motif finding which encompasses both the profile representation and the consensus pattern representation. we prove that the problem of discovering the best profiles can be solved by considering a degenerate version of the problem of finding the best consensus patterns. the main advantage of our framework is that it motivates a novel algorithm, mitra-pssm, which discovers profiles, yet provides some of the guarantees of discovering the best signals. the algorithm searches for best profiles with respect to information content which is the same criterion of popular algorithms such as meme and consensus. mitra-pssm is specifically designed for searching for profiles in this framework and introduces a novel notion of scoring consensus patterns, discrete information content. mitra-pssm is available for public use via webserver at http://www.calit2.net/compbio/mitra/.
new algorithms for the duplication-loss model. we consider the problem of constructing a species tree given a number of gene trees. in the frameworks introduced by goodman et al. [3], page [10], and guig&oacute;, muchnik, and smith [5] this is formulated as an optimization problem; namely, that of finding the species tree requiring the minimum number of duplications and/ or losses in order to explain the gene trees. in this paper, we introduce the width k duplication-loss and width k duplication problems. a gene tree has width k w.r.t. a species tree, if the species tree can be reconciled with the gene tree using at most k simultaneously active copies of the gene along its branches. we explain w.r.t. to the underlying biological model, why this width is typically very small in comparison to the total number of duplications and losses. we show polynomial time algorithms for finding optimal species trees having bounded width w.r.t. at least one of the input gene trees. furthermore, we present the first algorithm for input gene trees that are unrooted. lastly, we apply our algorithms to a dataset from [5] and show a species tree requiring significantly fewer duplications and fewer duplications/losses than the trees given in the original paper.
discovering temporal relations in molecular pathways using protein-protein interactions. the availability of large-scale protein-protein interaction data provides us with many opportunities to study molecular pathways involving proteins. in this paper we propose to mine temporal relations in molecular pathways by protein-protein interaction data. in particular, we model the assembly pathways of protein complexes with interval graphs and determine the temporal order of joining the pathway for proteins by ordering the vertices in the interaction graph. we develop a tool called xronos to perform such a computation. we then apply xronos to the ribosome assembly pathway and present validation results for the obtained ordering. the results are promising and show the potential usage for xronos in the study of molecular pathways.
dna sequence variation among humans and apes (abstract only). in order to shed light on the rate and mode of evolution of dna sequence evolution in the germ line of humans and chimpanzees, we have sequenced 136 kb around the human zfy gene as well as a total of 180 kb of genomic dna surrounding the zfx and zfy genes on the chimpanzee x and y chromosome, respectively. the comparison of the orthologous sequences on the human and chimpanzee sex chromosomes show that whereas the zfx region display 0.8% substitutional differences between the two species, the zfy region display 1.5% differences. by contrast, insertions and deletions show no difference between the two regions. interestingly, transversions show a much more drastic preponderance in the male germ line than transitions, and the insertion of retroviral-like elements seem to occur more frequently in the male than in the female germ line. while data on nucleotide sequence variation in the human nuclear genome have begun to accumulate through comparative sequencing projects at several diseases-associated genes, little is known about genomic variation in non-coding parts of the human genome and practically nothing about the variation in chimpanzee genome. in order to begin to gauge the extent and pattern of point substitutional variation in the non-transcribed parts of the human genome, we have sequenced 10 kb of non-coding dna in a region of low recombination at xq13.3 from 70 humans representing all major language groups of the world. in addition, the same sequence has been determined from 30 chimpanzees, representing all major subspecies, as well as bonobos. comparison to humans reveals an almost four-fold higher diversity and a three-fold greater age of the most recent common ancestor of the chimpanzee sequences. phylogenetic analyses show the sequences from the different chimpanzee subspecies to be intermixed and the distance between some chimpanzee sequences to be greater than the distance between them and the bonobo sequences. these data, as well as preliminary work in the other great apes, indicate that the human genome is unique in carrying extremely little nucleotide diversity.
engineering a scalable placement heuristic for dna probe arrays. design of dna arrays for very large-scale immobilized polymer synthesis (vlsips) [8] seeks to minimize effects of unintended illumination during mask exposure steps. [9, 14] formulate this requirement as the border minimization problem and give methods for placement (at array sites) and embedding (in the mask sequence) of probes in both synchronous and asynchronous regimes. these previous methods do not address several practical details of the application and, more critically, are not scalable to the o(108) probes contemplated for next-generation probe arrays. in this work, we make two main contributions:we give improved dynamic programming algorithms that perform probe embedding to minimize the number border conflicts while accounting for distance- and position-dependent border conflict weights, as well as the presence of polymorphic probes in the instance. we describe and experimentally validate the "engineering" of a scalable, high-quality asynchronous placement heuristic (which is moreover easily parallelizable) for dna array design. our heuristic is enabled by a novel approach for simultaneous re-placement and optimal re-embedding of an "independent set" of probes within a small window of the array..
analysis techniques for microarray time-series data. we introduce new methods for the analysis of short-term time-series data, and apply them to gene expression data in yeast. these include (1) methods for automated period detection in a predominately cycling data set and (2) phase detection between phase-shifted cyclic data sets. we show how to properly correct for the problem of comparing correlation coefficents between pairs of sequences of different lengths and small alphabets. in particular, we show that the correlation coefficient of sequences over alphabets of size two can exhibit very counter-intuitive behavior when compared with the hamming distance. finally, we address the predictability of known regulators via time-series analysis, and show that less than 20% of known regulatory pairs exhibit strong correlations in the cho/spellman data sets. by analyzing known regulatory relationships, we designed an edge detection function which identified candidate regulations with greater fidelity than standard correlation methods.
rnai, genome ultrastructure, and other unexpected tales from the analysis of genetic silencing. the genetic landscape faced by a living cell is constantly changing. developmental transitions, environmental shifts, and pathogenic invasions lend a dynamic character to both the genome and its activity pattern. a variety of natural mechanisms are utilized by cells adapting to genetic change. these include normal developmental mechanisms and a subset of defense systems for responding to pathogens. at the root of these studies are questions of how a cell can distinguish "self" versus "nonself" and "wanted" versus "unwanted" gene expression.investigations of gene silencing in our lab and elswhere have identified a number of structural features that provide an indication of unwanted nucleic acid. one of these features has been double stranded rna (dsrna). absent during "normal" gene expression, dsrna is an essential component in the life cycle of most viruses. by flagging dsrna as an indicator of unwanted rna replication, and by scrupulously avoiding the production of dsrna during most normal gene expression, the cell acquires a modicum of protection from viral infection. the mechanism by which dsrna segments are utilized to trigger silencing of homologous genes, termed rnai, has been a focus of intensive work at many different institutions over the last seven years. this talk will describe aspects of this mechanism, with particular emphasis on the biological role and chemical logic of the interference reaction. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
whole-genome comparative annotation and regulatory motif discovery in multiple yeast species. in [13] we reported the genome sequences of s. paradoxus, s. mikatae and s. bayanus and compared these three yeast species to their close relative, s. cerevisiae. genome-wide comparative analysis allowed the identification of functionally important sequences, both coding and non-coding. in this companion paper we describe the mathematical and algorithmic results underpinning the analysis of these genomes.we developed statistical methods for the systematic de-novo identification of regulatory motifs. without making use of co-regulated gene sets, we discovered virtually all previously known dna regulatory motifs as well as several noteworthy novel motifs. with the additional use of gene ontology information, expression clusters and transcription factor binding profiles, we assigned candidate functions to the novel motifs discovered.our results demonstrate that entirely automatic genome-wide annotation, gene validation, and discovery of regulatory motifs is possible. our findings are validated by the extensive experimental knowledge in yeast, confirming their applicability to other genomes.
optimizing exact genetic linkage computations. genetic linkage analysis is a challenging application which requires bayesian networks consisting of thousands of vertices. consequently, computing the likelihood of data, which is needed for learning linkage parameters, using exact inference procedures calls for an extremely efficient implementation that carefully optimizes the order of conditioning and summation operations. in this paper we present the use of stochastic greedy algorithms for optimizing this order. our algorithm has been incorporated into the newest version of superlink, which is currently the fastest genetic linkage program for exact likelihood computations in general pedigrees. we demonstrate an order of magnitude improvement in run times of likelihood computations using our new optimization algorithm, and hence enlarge the class of problems that can be handled effectively by exact computations.
efficient algorithms for lateral gene transfer problems. this paper develops a model for lateral gene transfer events (a.k.a. horizontal gene transfer events) between a set of gene trees t1, t2, &hellip;, tk and a species tree s. to the best of our knowledge, this model possesses a higher degree of biological and mathematical soundness than any other model proposed in the literature. among other biological considerations, the model respects the partial order of evolution implied by s. within our model, we identify an activity parameter that measures the number of genes that are allowed to be simultaneously active in the genome of a taxa and show that finding the most parsimonious scenario that reconciles the disagreeing gene trees with the species tree is doable in polynomial time when the activity level and number of transfers are small, but intractable in general. to the best of our knowledge, all other models proposed in the literature assume implicitly that the activity is one. finally, using a dataset of bacterial gene sequences from [4], our implementations found 5 optimal scenarios; one of which is the scenario proposed by the authors in [4].
association mapping of complex diseases with ancestral recombination graphs: models and efficient algorithms. association, or ld (linkage disequilibrium), mapping is an intensely-studied approach to gene mapping (genome-wide or in candidate regions) that is widely hoped to be able to efficiently locate genes influencing both complex and mendelian traits. the logic underlying association mapping implies that the best possible mapping results would be obtained if the genealogical history of the sampled individuals were explicitly known. such a history would be in the form of an "ancestral recombination graph (arg)". but despite the conceptual importance of genealogical histories to association mapping, few practical association mapping methods have explicitly used derived genealogical aspects of args. two notable exceptions are [35] and [23]. in this paper we develop an association mapping method that explicitly constructs and samples minargs (args that minimize the number of recombinations). we develop an arg sampling method that provably samples minargs uniformly at random, and that is practical for moderate sized datasets. we also develop a different, faster, arg sampling method that still samples from a well-defined subspace of args, and that is practical for larger sized datasets. we present novel efficient algorithms on extensions of the "phenotype likelihood" problem, a key step in the method in [35]. we also prove that computing the phenotype likelihood for a different natural extension of the penetrance model in [35] is np-hard, answering a question unresolved in that paper. finally, we put all of these results into practice, and examine how well the implemented methods perform, compared to the results in [35]. the empirical results show great speed ups, and definite but sometimes small, improvements in mapping accuracy. speed is particularly important in doing genome-wide scans for causative mutations.
optimizing for success: a new score function for distantly related protein sequence comparison. the exponential growth of the sequence data produced by the genome projects motivates the development of better ways of inferring structural and functional information about those newly sequenced proteins. looking for homologies between these probe protein sequences and other protein sequences in the database has proved to be one of the most useful current techniques. this procedure, known as sequence comparison, relies on the use of an appropriate score function that discriminates homologs from non-homologs. current score functions have difficulty identifying distantly-related homologs with low sequence similarity. as a result, there is an increased demand for a new score function that yields statistically-significant higher scores for all the pairs of homologous protein sequences including such distantly-related homologs. we present a new method for generating a score function by optimizing it for successful discrimination between homologous and unrelated proteins. the new score function (optima) out-performs other commonly used substitution matrices for the detection of distantly related protein sequences.
using bayesian networks to analyze expression data. dna hybridization arrays simultaneously measure the expression level for thousands of genes. these measurements provide a &ldquo;snapshot&rdquo; of transcription levels within the cell. a major challenge in computational biology is to uncover, from such measurements, gene/protein interactions and key biological features of cellular systems. in this paper, we propose a new framework for discovering interactions between genes based on multiple expression measurements this framework builds on the use of bayesian networks for representing statistical dependencies. a bayesian network is a graph-based model of joint multi-variate probability distributions that captures properties of conditional independence between variables. such models are attractive for their ability to describe complex stochastic processes, and for providing clear methodologies for learning from (noisy) observations. we start by showing how bayesian networks can describe interactions between genes. we then present an efficient algorithm capable of learning such networks and statistical method to assess our confidence in their features. finally, we apply this method to the s. cerevisiae cell-cycle measurements of spellman et al. [35] to uncover biological features
a structural em algorithm for phylogenetic inference. a central task in the study of evolution is the reconstruction of a phylogenetic tree from sequences of current-day taxa. a well supported approach to tree reconstruction performs maximum likelihood (ml) analysis. unfortunately, searching for the maximum likelihood phylogenetic tree is computationally expensive. in this paper, we describe a new algorithm that uses structural-em for learning maximum likelihood trees. this algorithm is similar to the standard em method for estimating branch lengths, except that during iterations of this algorithms the topology is improved as well as the branch length. the algorithm performs iterations of two steps. in the e-step, we use the current tree topology and branch lengths to compute expected sufficient statistics, which summarize the data. in the m-step, we search for a topology that maximizes the likelihood with respect to these expected sufficient statistics. as we show, searching for better topologies inside the m-step can be done efficiently, as opposed to standard search over topologies. we prove that each iteration of this procedure increases the likelihood of the topology, and thus the procedure must converge. we evaluate our new algorithm on both synthetic and real sequence data, and show that it is both dramatically faster and finds more plausible trees than standard search for maximum likelihood phylogenies.
large scale reconstruction of haplotypes from genotype data. critical to the understanding of the genetic basis for complex diseases is the modeling of human variation. most of this variation can be characterized by single nucleotide polymorphisms (snps) which are mutations at a single nucleotide position. to characterize an individual's variation, we must determine an individual's haplotype or which nucleotide base occurs at each position of these common snps for each chromosome. in this paper, we present results for a highly accurate method for haplotype resolution from genotype data. our method leverages a new insight into the underlying structure of haplotypes which shows that snps are organized in highly correlated "blocks". the majority of individuals have one of about four common haplotypes in each block. our method partitions the snps into blocks and for each block, we predict the common haplotypes and each individual's haplotype. we evaluate our method over biological data. our method predicts the common haplotypes perfectly and has a very low error rate (0.47%) when taking into account the predictions for the uncommon haplotypes. our method is extremely efficient compared to previous methods, (a matter of seconds where previous methods needed hours). its efficiency allows us to find the block partition of the haplotypes, to cope with missing data and to work with large data sets such as genotypes for thousands of snps for hundreds of individuals. the algorithm is available via webserver at http://www.cs.columbia.edu/compbio/hap.
optimal sequencing by hybridization in rounds. sequencing by hybridization (sbh) is a method for reconstructing a sequence over a small finite alphabet from a collection of probes (substrings). substring queries can be arranged on an array (sbh chip) and then a combinatorial method is used to construct the sequence from its collection of probes. technological constraints limit the number of substring queries that can be placed on a single sbh chip. we develop an idea of margaritis and skiena and propose an algorithm that uses a series of small sbh chips to sequence long strings while the number of probes used matches the information theoretical lower bound up to a constant factor.
algorithms for inferring cis-regulatory structures and protein interaction networks. a major focus of functional genomics today is the discovery of the interactions between genes and proteins that regulate the transcription of genes and the responses of cells to external signals. the speaker will describe his recent efforts with several coworkers to solve pieces of this puzzle. the work divides into several parts: a new approach to the recognition of transcription-factor binding sites, based on the principle that transcription factors divide naturally into families such as the leucine zippers and the zinc fingers, and that the binding site motifs for transcription factors within the same family have common features. these features may be obscure at the sequence level, but can be characterized at a higher level of description. by discovering and modeling such meta-sequence features one can improve the sensitivity and specificity with which binding sites can be determined for transcription factors within a family. [5], [6] an algorithm and an associated web-based tool for finding recurrent cis-regulatory modules in the promoter regions of human genes. each such module consists of a set of transcription factors that often bind to the same promoter regions and collectively enhance or inhibit the transcription of the corresponding genes. [4] an algorithm for minimizing the number of gene perturbation experiments required to reconstruct signal transduction pathways whose regulatory structures can be described within the mathematical framework of chain functions. [1] algorithms for discovering protein complexes and regulatory pathways that are conserved in evolution, using protein sequence data and protein-protein interaction data for two or more organisms. [2], [3].
applied computational genomics: polymorphism prediction, data mining and genomic analysis. with the "completion" of the first genome, the daily analysis of genomic variation and the transcriptome, and new technologies amassing proteome data, the need for computational tools, inspired by biomedical insight and need are being developed by many groups to help everybody reduce this data to knowledge. to attain understanding from this data, several things are now required for progress; applied computational tools, access to phenotype presenting patients/biological material (and their genotype), and experts to assimilate this information. in this talk, i will describe efforts within our laboratory to develop and then validate some applied computational tools that are then used by our expert collaborators and us. these include: 1) computer algorithms and codes that inspect the genome (coding and intronic) for highly probable simple sequence repeat and single nucleotide polymorphisms; 2) techniques and applications to better identify information in text databases; 3) software to integrate data from some of the many valuable public databases with experimental data (expression and polymorphism), and 4) software to do integrated analysis and interactive visualization of genomic sequence dat.each of our software applications is applied to biomedical problems to validate their utility and verify their accuracy, which can only be done by returning to the wet laboratory. the biomedical areas under investigation include cancer, cardiac disease, development, inflammation and infection. this approach has led to gene discoveries, phenotype causing polymorphisms and has inspired research directions for which the final answer is not yet in.bioinformatics tools often can generate many more "leads" than are possible to pursue with existing technology. this has required us to develop some new technologies and laboratory techniques. for example, we have developed a method and apparatus that is in daily use for the synthesis of custom, software-directed high-density oligonucleotide arrays used for re-sequencing, methlyation analysis and comparative genomic hybridization. this device, called doc (digital optical chemistry), enables us to manufacture "affymetrix-style" arrays with up to 192,000 features. other apparatus, such as high-throughput oligo synthesizers, hyperspectral imaging scanners/microscopes and array spotting robots were also created as needed.this presentation will focus on our applied computational tools and the biomedical observations made with them and touch on how some of the hardware technologies have accelerated that process.much of the software and databases we develop are available for public use via our www site at http://innovation.swmed.edu/. this work is supported by the nih, the state of texas and the p.o'b. montgomery distinguished chair.
separtating repeats in dna sequence assembly. one of the key open problems in large-scale dna sequence assembly is the correct reconstruction of sequences that contain repeats. a long repeat can confound a sequence assembler into falsely overlaying fragments that sample its copies, effectively compressing out the repeat in the reconstructed sequence. we call the task of correcting this compression by separating the overlaid fragments into the distinct copies they sample, the repeat separation problem. we present a rigorous formulation of repeat separation in the general setting without prior knowledge of consensus sequences of repeats or their number of copies. our formulation decomposes the task into a series of four subproblems, and we design probabilistic tests or combinatorial algorithms that solve each subproblem. the core subproblem separates repeats using the so-called k-median problem in combinatorial optimization, which we solve using integer linear-programming. experiments with an implementation show we can separate fragments that are overlaid at 10 times the coverage with very few mistakes in a few seconds of computation, even when the sequencing error rate and the error rate between copies are identical. to our knowledge this is the first rigorous and fully general approach to separating repeats that directly addresses the problem.
aligning alignments exactly. a basic computational problem that arises in both the construction and local-search phases of the best heuristics for multiple sequence alignment is that of aligning the columns of two multiple alignments. when the scoring function is the sum-of-pairs objective and induced pairwise alignments are evaluated using linear gap-costs, we call this problem aligning alignments. while seemingly a straightforward extension of two-sequence alignment, we prove it is actually np-complete. as explained in the paper, this provides the first demonstration that minimizing linear gap-costs, in the context of multiple sequence alignment, is inherently hard.we also develop an exact algorithm for aligning alignments that is remarkably efficient in practice, both in time and space. even though the problem is np-complete, computational experiments on both biological and simulated data show we can compute optimal alignments for all benchmark instances in two standard datasets, and solve very-large random instances with highly-gapped sequences.
finding motifs in the twilight zone. we introduce the notion of a multiprofile and use it for finding subtle motifs in dna sequences. multiprofiles generalize the notion of a profile and allow one to detect subtle consensus sequences that escape detection by the standard profiles. our multiprofiler algorithm outperforms other leading motif finding algorithms in a number of synthetic models. moreover, it can be shown that in some previously studied motif models, multiprofiler is capable of pushing the performance envelope to its theoretical limits.
maximum likelihood resolution of multi-block genotypes. we present a new algorithm for the problems of genotype phasing and block partitioning. our algorithm is based on a new stochastic model, and on the novel concept of probabilistic common haplotypes. we formulate the goals of genotype resolving and block partitioning as a maximum likelihood problem, and solve it by an em algorithm. when applied to real biological snp data, our algorithm outperforms two state of the art phasing algorithms. our algorithm is also considerably more sensitive and accurate than a previous method in predicting and identifying disease association.
invited presentation: introns and modules in ancient conserved genes (abstract only). we study the correlation between introns and modules, compact regions of protein structure, in genes whose products have a known 3-dimensional structre and which are homologous between bacteria and eukaryotes. using two definitions of modules, we show that phase zero introns, those that lie between the codons, are significantly correlated with the boundaries of modules while introns that lie in phases one and two, that interrupt the codons are not so correlated. furthermore, intron positions that are philogenetically ancient, matching between two kingdomes, are more correlated with module boundaries than are other positions. we will discuss the significance of these findings, which suggest that some of the phase zero introns are residues of the original construction of the genes while the phase one and two introns may have been added later in evolution. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
finding recurrent sources in sequences. many genomic sequences and, more generally, (multivariate) time series display tremendous variability. however, often it is reasonable to assume that the sequence is actually generated by or assembled from a small number of sources, each of which might contribute several segments to the sequence. that is, there are h hidden sources such that the sequence can be written as a concatenation of k > h pieces, each of which stems from one of the h sources. we define this (k,h)-segmentation problem and show that it is np-hard in the general case. we give approximation algorithms achieving approximation ratios of 3 for the l1 error measure and √5 for the l2 error measure, and generalize the results to higher dimensions. we give empirical results on real (chromosome 22) and artificial data showing that the methods work well in practice.
evolutionary features of genomes as disclosed by comparative analysis of complete genome sequences (abstract only). our comparisons of complete genome sequences revealed that the genome structures have been extensively shuffled among eubacteria, particularly when the orders of orthologous genes were examined. moreover, archaebacterial and eukaryotic genome structures were found to be unstable, too, as were the cases of eubacteria. we then turned our attention to operon structures, which were expected to be well conserved during evolution because of their regulatory importance. surprisingly enough, however, we found that even within operons, gene orders have not been conserved, with exception to only a few cases such as ribosomal operons. when we reconstructed the ancestral genome structure of eubacteria and archaebacteria, and examined the relative instability of the genome structures among eubacteria, we found that there were differences in the degree of the genome instability among the examined species. the genome instability appears to be correlated with the number of insertion sequences. interestingly enough, the intensity of the intrastrand bias of nucleotide composition (g-c skew) was found to be affected by the genome instability, implying that accumulation of strand-specific mutations depends heavily upon the stability of a genome. these findings imply that the gene orders have not been essential for survival of microbes in long-term evolution, and that the evolutionary instability of the genome structures is an intrinsic nature common to eubacteria, archaebacteria and eukaryotes. for eukaryotic genomes, we found that a lot of gene fusion events might have happened in the early evolution of eukaryotes so as to compensate for the loss of bacterial operon structures. the evolutionary instability of the genome structures can be one of the most important factors in understanding the evolutionary processes of the genome evolution.
efficient algorithms for protein sequence design and the analysis of certain evolutionary fitness landscapes. protein sequence design is a natural inverse problem to protein structure prediction: given a target structure in three dimensions, we wish to design an amino acid sequence that is likely fold to it. a model of sun, brem, chan, and dill casts this problem as an optimization on a space of sequences of hydrophobic (h) and polar (p) monomers; the goal is to find a sequence which achieves a dense hydrophobic core with few solvent-exposed hydrophobic residues. sun et al. developed a heuristic method to search the space of sequences, without a guarantee of optimality or near-optimality; hart subsequently raised the computational tractability of constructing an optimal sequence in this model as an open question. here we resolve this question by providing an efficient algorithm to construct optimal sequences; our algorithm has a polynomial running time, and performs very efficiently in practice. we illustrate the implementation of our method on structures drawn from the protein data bank. we also consider extensions of the model to larger amino acid alphabets, as a way to overcome the limitations of the binary h/p alphabet. we show that for a natural class of arbitrarily large alphabets, it remains possible to design optimal sequences efficiently. finally, we analyze some of the consequences of this sequence design model for the study of evolutionary fitness landscapes. a given target structure may have many sequences that are optimal in the model of sun et al.; following a notion raised by the work of j. maynard smith, we can ask whether these optimal sequences are ``connected'''' by successive point mutations. we provide a polynomial-time algorithm to decide this connectedness property, relative to a given target structure. we develop the algorithm by first solving an analogous problem expressed in terms of submodular functions, a fundamental object of study in combinatorial optimization.
reconciliation problems for duplication, loss and horizontal gene transfer. this paper presents a model of reconciling a species tree and a gene tree in an extended duplication-loss model. in the first part the definition of a model is introduced. in the second the horizontal transfer is defined and a new polynomial reconciliation algorithm is presented. we prove np-completeness of the important problem related to the reconstruction of the species relationships with transfers from a given set of gene family trees. some new problems are stated. we present a simple biological example.
a nmr-spectra-based scoring function for protein docking. a well studied problem in the area of computational molecular biology is the so-called protein-protein docking problem (ppd) that can be formulated as follows: given two proteins a and b that form a protein complex, compute the 3d-structure of the protein complex ab. protein docking algorithms can be used to study the driving forces and reaction mechanisms of docking processes. they are also able to speed up the lenghty process of experimental structure elucidation of protein complexes by proposing potential structures. in this paper, we are discussing a variant of the ppd-problem where the input consists of the tertiary structures of a and b plus an unassigned 1h-nmr spectrum of the complex ab. we present a new scoring function for evaluating and ranking potential complex structures produced by a docking algorithm. the scoring function computes a &ldquo;theoretical&rdquo; 1h-nmr spectrum for each tentative complex structure and subtracts the calculated spectrum from the experimental spectrum. the absolute areas of the difference spectra are then used to rank the potential complex structures. in contrast to formerly published approaches (e.g. morelli et. al. [38]) we do not use distance constraints (intermolecular noe constraints). we have tested the approach with the bound conformations of four protein complexes whose three-dimensional structures are stored in the pdb data bank [5] and whose 1h-nmr shift assignments are available from the bmrb database (biomagresbank [47]). in all examples, the new scoring function produced very good rankings of the structures. the best result was obtained for an example, where all standard scoring functions failed completely. here, our new scoring function achieved an almost perfect separation between good approximations of the true complex structure and false positives. unfortunately, the number of complexes with known structure and available spectra is very small. nevertheless, these experiments indicate that scoring functions based on comparisons of one- or multi-dimensional nmr spectra might be a good instrument to improve the reliability and accuracy of docking predictions and perhaps also of protein structure predictions (threading).
model-based inference of haplotype block variation. the uneven recombination structure of human dna has been highlighted by several recent studies. knowledge of the haplotype blocks generated by this phenomenon can be applied to dramatically increase the statistical power of genetic mapping. several criteria have already been proposed for identifying these blocks, all of which require haplotypes as input. we propose a comprehensive statistical model of haplotype block variation and show how the parameters of this model can be learned from haplotypes and/or unphased genotype data. using real-world snp data, we demonstrate that our approach can be used to resolve genotypes into their constituent haplotypes with greater accuracy than previously known methods.
simultaneous identification of duplications and lateral transfers. this paper introduces a combinatorial model that incorporates duplication events as well as lateral gene transfer events (a.k.a. horizontal gene transfer events). to the best of our knowledge, this is the first such model containing both of these events. a so-called dt-scenario is used to explain differences between a gene tree t and species trees s. the model is biologically as well as mathematically sound. among other biological considerations, the model respects the partial order of evolution implied by s by demanding that the dt-scenarios are "acyclic". we present fixed parameter tractable algorithms that count the minimum number of duplications and lateral transfers, and more generally can compute the set of pairs (t,d) where d is the minimum number of duplications required by any explanation that requires t lateral transfers. this allows us to also compute a weighted parsimony score. we also show how gene loss events can be incorporated into our model. we also give an $np$-completeness proof which suggests that the intractability is due to the demand that the dt-scenarios be acyclic. when this condition is removed, we can show that the problem is computable in polynomial time via dynamic programming. by generating "synthetic" gene and species trees via a birth-death process, we explored the capacity of our algorithms to faithfully reconstruct the actual number of events taken place. the results are positive.
reconstructing distances in physical maps of chromosomes with nonoverlapping probes. we present a new method for reconstructing the distances between probes in physical maps of chromosomes constructed by hybridizing pairs of clones under the so-called sampling-without-replacement protocol. in this protocol, which is simple, inexpensive, and has been used to successfully map several organisms, equal-length clones are hybridized against a clone-subset called the probes. the probes are chosen by a sequential process that is designed to generate a pairwise-nonoverlapping subset of the clones. we derive a likelihood function on probe spacings and orders for this protocol under a natural model of hybridization error, and describe how to reconstruct the most likely spacing for a given order under this objective using continuous optimization. the approach is tested on simulated data and real data from chromosome vi of aspergillus nidulans. on simulated data we recover the true order and close to the true spacing; on the real data, for which the true order and spacing is unknown, we recover a probe order differing significantly from the published one. to our knowledge this is the first practical approach for computing a globally-optimal maximum-likelihood reconstruction of interprobe distances from clone-probe hybridization data.
joint classifier and feature optimization for cancer diagnosis using gene expression data. recent research has demonstrated quite convincingly that accurate cancer diagnosis can be achieved by constructing classifiers that are designed to compare the gene expression profile of a tissue of unknown cancer status to a database of stored expression profiles from tissues of known cancer status. this paper introduces the jcfo, a novel algorithm that uses a sparse bayesian approach to jointly identify both the optimal nonlinear classifier for diagnosis and the optimal set of genes on which to base that diagnosis. we show that the diagnostic classification accuracy of the proposed algorithm is superior to a number of current state-of-the-art methods in a full leave-one-out cross-validation study of two widely used benchmark datasets. in addition to its superior classification accuracy, the algorithm is designed to automatically identify a small subset of genes (typically around twenty in our experiments) that are capable of providing complete discriminatory information for diagnosis. focusing attention on a small subset of genes is not only useful because it produces a classifier with good generalization capacity, but also because this set of genes may provide insights into the mechanisms responsible for the disease itself. a number of the genes identified by the jcfo in our experiments are already in use as clinical markers for cancer diagnosis; some of the remaining genes may be excellent candidates for further clinical investigation. if it is possible to identify a small set of genes that is indeed capable of providing complete discrimination, inexpensive diagnostic assays might be widely deployable in clinical settings.
101 optimal pdb structure alignments: a branch-and-cut algorithm for the maximum contact map overlap problem. structure comparison is a fundamental problem for structural genomics. a variety of structure comparison methods were proposed and several protein structure classification servers e.g., scop, dali, cath, were designed based on them, and are extensively used in practice. this area of research continues to be very active, being energized bi-annually by the casp folding competitions, but despite the extraordinary international research effort devoted to it, progress is slow. a fundamental dimension of this bottleneck is the absence of rigorous algorithmic methods. a recent excellent survey on structure comparison by taylor et.al. [23] records the state of the art of the area: in structure comparison, we do not even have an algorithm that guarantees an optimal answer for pairs of structures &hellip; in this paper we provide the first rigorous algorithm for structure comparison. our method is based on developing an effective integer linear programming (ip) formulation of protein structure contact maps overlap (cmo), and a branch-and-cut strategy that employs lower-bounding heuristics at the branch nodes. our algorithms identified a gallery of optimal and near-optimal structure alignments for pairs of proteins from the protein data bank with up to 80 amino acids and about 150 contacts each &mdash; problems of instance size of about 300. although these sizes also reflect our current limitations, these are the first provable optimal and near-optimal algorithms in the literature for a measure of structure similarity which sees extensive practical use. at the heart of our success in finding optimal alignments is a reduction of the cmo optimization to the maximum independent set (mis) problem on special graphs. for cmo instances of size 300, the corresponding mis graph instance contains about 10,000 nodes. while our algorithms are able to solve to optimality mis problem of these sizes, the known optimal algorithms for the mis on general graphs can at present only solve instances with up to a few hundred nodes. this is the first effective use of ip methods in protein structure comparison; the biomolecular structure literature contains only one other effective ip method devoted to rna comparison, due to lenhof et.al. [18]. the hybrid heuristic approach that worked well for providing lower bounds in the branch and cut algorithm was tried on large proteins in a test set suggested by jeffrey skolnick. it involved 33 proteins classified into four families: flavodoxin-like fold chey-related, plastocyanin, tim barrel, and ferratin. out of the set of all 528 pairwise structure alignments, we have validated the clustering with a 98.7% accuracy (1.3% false negatives and 0% false positives).
extracting structural information using time-frequency analysis of protein nmr data. high-throughput, data-directed computational protocols for structural genomics (or proteomics) are required in order to evaluate the protein products of genes for structure and function at rates comparable to current gene-sequencing technology. to develop such methods, new algorithms are required that can quickly extract significantly more structural information from sparse experimental data. this paper presents a new class of signal processing algorithms for nuclear magnetic resonance (nmr) structural biology, based on time-frequency analysis of chemical shift dynamics. a novel approach to multidimensional nmr analysis is proposed in which the data are interpreted in the time-frequency domain, as opposed to the traditional frequency domain. time-frequency analysis (tfa) exposes behavior orthogonal to the magnetic coherence transfer pathways, thus affording new avenues of nmr discovery. an implementation yielding new biophysical results is discussed. in particular, we demonstrate the heretofore unknown presence of through-space inter-atomic distance information within 15n-edited heteronuclear single-quantum coherence(15n hsqc) data. a biophysical model explains these results, and is supported by further experiments on simulated spectra.
large a polynomial-time nuclear vector replacement algorithm for automated nmr resonance assignments. high-throughput nmr structural biology can play an important role in structural genomics. we report an automated procedure for high-throughput nmr resonance assignment for a protein of known structure, or of an homologous structure. these assignments are a prerequisite for probing protein-protein interactions, protein-ligand binding, and dynamics by nmr. assignments are also the starting point for structure determination and refinement. a new algorithm, called nuclear vector replacement (nvr) is introduced to compute assignments that optimally correlate experimentally-measured nh residual dipolar couplings (rdcs) to a given a priori whole-protein 3d structural model. the algorithm requires only uniform 15n-labelling of the protein, and processes unassigned hn-15n hsqc spectra, hn-15n rdcs, and sparse hn-hn noe's dnns), all of which can be acquired in a fraction of the time needed to record the traditional suite of experiments used to perform resonance assignments. nvr runs in minutes and efficiently assigns the (hn,15n) backbone resonances as well as the dnns of the 3d \nfif-noesy spectrum, in o(n3) time. the algorithm is demonstrated on nmr data from a 76-residue protein, human ubiquitin, matched to four structures, including one mutant (homolog), determined either by x-ray crystallography or by different nmr experiments (without rdcs). nvr achieves an average assignment accuracy of over 90%. we further demonstrate the feasibility of our algorithm for different and larger proteins, using nmr data for hen lysozyme (129 residues, 98% accuracy) and streptococcal protein g (56 residues, 95% accuracy), matched to a variety of 3d structural models. finally, we extend nvr to a second application, 3d structural homology detection, and demonstrate that nvr is able to identify structural homologies between proteins with remote amino acid sequences using a database of structural models.
phase-independent rhythmic analysis of genome-wide expression patterns. we introduce a model-based analysis technique for extracting and characterizing rhythmic expression profiles from genome-wide dna microarray hybridization data. these patterns are clues to discovering rhythmic genes implicated in cell-cycle, circadian, and other biological processes. the algorithm, implemented in a program called rage (rhythmic analysis of gene expression), decouples the problems of estimating a pattern's periodicity and phase. our algorithm is linear-time in frequency and phase resolution, an improvement over previous quadratic-time approaches. unlike previous approaches, rage uses a true distance metric for measuring expression profile similarity, based on the hausdorff distance. this results in better clustering of expression profiles for rhythmic analysis. the confidence of each frequency estimate is computed using z-scores. we demonstrate that rage is superior to other techniques on synthetic and actual dna microarray hybridization data. we also show how to replace the discretized phase search in our method with an exact (combinatorially precise) phase search, resulting in a faster algorithm with no complexity dependence on phase resolution.
checking homogeneity of motifs' distribution in heterogenous sequences. studying the distribution of a motif along sequences may help to understand its biological function, or to detect regions of interest. a statistical model is needed to assess the significancy of the observed distribution. we propose an heterogenous compound poisson process to model the possibility of overlap between occurrences and some heterogeneity of the sequence a priori known. the parameters estimation procedure is described and tests of homogenous sub-models are proposed. we also consider the detection of rich regions using either cumulated distances or moving intervals, via an homogenization technique. illustrations of the method are given with applications to bacterial genomes.
a structural perspective on genome evolution. at ucl we have developed several automated protocols for generating protein family resources (cath; gene3d). these resources can be used to perform comparative genome analyses in order to understand the evolution of protein families. also to identify biologically and/or medically interesting families for which no structural data currently exists and which may therefore be important targets for structure genomics initiatives.the cath domain structure database, established by orengo and thornton in 1993, now contains a significant proportion of protein structures from the pdb clustered into 1400 evolutionary families. relationships have been identified using robust structure comparison methods (ssap, cathedral). we have also benchmarked and optimised various 1d-profiles and hmm based protocols for assigning genome sequences to families within the resource (e.g. sam-t99, samosa, cath-isl).in this way we can assign structural data to a large proportion (up to 60%) of whole or partial sequences in completed genomes and >80% of genes coding for enzymes and other proteins in biochemical pathways. however, in order to include all families regardless of whether their structure is known or not, a new protein family resource has been developed (gene3d). in gene3d, complete genes have been clustered according to sequence similarity alone, using a robust clustering method (pfscape). 120 completed genomes from all kingdoms have been clustered into 220,000 gene families, 70,000 of which contain 2 or more sequences. subsequently, we have labelled those gene families for which cath structural or pfam functional domain annotations can be provided for all or part of the gene.preliminary analysis of the genome annotations reveals that a significant proportion (up to 70%) of cath annotated genes or gene regions in genomes are assigned to domain families that are common to all three kingdoms of life. however, only 20% of the genome sequences are assigned to gene families common to all kingdoms. since a large proportion of these genes are multidomain proteins this supports the view that a great deal of functional diversity within the genomes has been achieved by combining domain modules in different ways.in collaboration with professor janet thornton, we have analysed a subset of 56 bacterial genomes to determine the recurrence of specific domain structure families within the genomes. this revealed a small but essential group of universal, and in some cases, highly recurring domain families. for some size-dependent families, domain recurrence is highly correlated with increase in genome size, whilst in other size-independent families no correlation is observed. statistical analysis allowed us to distinguish three groups. within the size-dependent families we differentiated two groups: linearly-distributed and non-linearly-distributed. functional annotation using the cogs revealed that these domains were predominantly involved in metabolism and regulation, respectively. whilst a third group of evenly-distributed size independent domains are primarily involved in protein translation and biosynthesis.by mapping cath and pfam domains families onto all the genome sequences in gene3d we observe that a few hundred highly recurrent families are dominating at least 50% of whole or partial genome sequences. many of these families are common to both prokaryotes and eukaryotes and are performing essential generic functions. in many of the largest families, significant divergence in sequence has been accompanied by modifications in structure and function. targetting representatives in these families for structure determination will allow the structure genomics initiatives to map both fold and function space and reveal the mechanisms by which divergence in protein families promotes evolution of new functions.
a complete and effective move set for simplified protein folding. we present new lowest energy configurations for several large benchmark problems for the two-dimensional hydrophobic-hydrophilic model. we found these solutions with a generic implementation of tabu search using an apparently novel set of transformations that we call pull moves. our experiments show that our algorithm can find these best solutions in 3 to 14 hours, on average. pull moves appear quite effective and may also be useful for other local search algorithms for the problem. additionally, we prove that pull moves are complete; that is, any pair of valid configurations are mutually reachable through a sequence of pull moves. our implementation was developed with the human-guided search (hugs) middleware, which allows rapid development of interactive optimization systems.
invited: prediction of protein function. a genome sequence embodies the potential life of an organism, but implementation of genetic information depends on the functions of the proteins that it encodes. many proteins of known sequence and even of known structure present challenges to understanding their function. in some cases genes responsible for diseases have been identified but their specific functions are unknown. annotation of a genome involves assignment of functions to gene products, in most cases on the basis of amino acid sequence alone, in the absence of experimental information. protein structures from structural genomics projects are invaluable for function assignment. nevertheless, prediction of protein function remains a difficult problem. some methods provide reasonable guesses, but no method is foolproof. moreover, even when it is possible to ascribe a particular function to a gene product, the protein may have multiple functions. an underlying problem has been that function is in many cases an ill-defined concept.
a class of edit kernels for svms to predict translation initiation sites in eukaryotic mrnas. the prediction of translation initiation sites (tiss) in eukaryotic mrnas has been a challenging problem in computational molecular biology. in this paper, we present a new algorithm to recognize tiss with a very high accuracy. our algorithm includes two novel ideas. first, we introduce a class of new sequence-similarity kernels based on string edit, called the edit kernels, for use with support vector machines (svms) in a discriminative approach to predict tiss. the edit kernels are simple and have significant biological and probabilistic interpretations. second, we convert the region of an input mrna sequence downstream to a putative tis into an amino acid sequence before applying svms to avoid the high redundancy in the genetic code. the algorithm has been implemented and tested on previously published data. our experimental results on real mrna data show that both ideas improve the prediction accuracy greatly and our method performs significantly better than those based on neural networks and svms with polynomial kernels or salzberg kernel.
haplotype reconstruction from snp alignment. in this paper we describe a method for statistical reconstruction of haplotypes from a set of aligned snp fragments. we consider the case of a pair of homologous human chromosomes, one from the mother and the other from the father. after fragment assembly and snp detection, we wish to reconstruct the two haplotypes of the parents. given a set of snp sites inferred from the assembly alignment, we wish to divide the fragment set into two subsets, each of which represents one chromosome. our method is based on a statistical model of sequencing errors, compositional information and haplotype memberships.we calculate probabilities of different haplotypes conditional on the alignment. due to computational complexity, we first determine phases for neighboring snps. then we connect them and construct haplotype segments. also we compute the accuracy or confidence of the reconstructed haplotypes. we discuss other issues such as alternative methods, parameter estimation, computational efficiency, and relaxation of assumptions.
combining pairwise sequence similarity and support vector machines for remote protein homology detection. one key element in understanding the molecular machinery of the cell is to understand the meaning, or function, of each protein encoded in the genome. a very successful means of inferring the function of a previously unannotated protein is via sequence similarity with one or more proteins whose functions are already known. currently, one of the most powerful such homology detection methods is the svm-fisher method of jaakkola, diekhans and haussler (ismb 2000). this method combines a generative, profile hidden markov model (hmm) with a discriminative classification algorithm known as a support vector machine (svm). the current work presents an alternative method for svm-based protein classification. the method, svm-pairwise, uses a pairwise sequence similarity algorithm such as smith-waterman in place of the hmm in the svm-fisher method. the resulting algorithm, when tested on its ability to recognize previously unseen families from the scop database, yields significantly better remote protein homology detection than svm-fisher, profile hmms and psi-blast.
a novel ensemble-based scoring and search algorithm for protein redesign, and its application to modify the substrate specificity of the gramicidin synthetase a phenylalanine adenylation enzyme. realization of novel molecular function requires the ability to alter molecular complex formation. enzymatic function can be altered by changing enzyme-substrate interactions via modification of an enzyme's active site. a redesigned enzyme may either perform a novel reaction on its native substrates or its native reaction on novel substrates. a number of computational approaches have been developed to address the combinatorial nature of the protein redesign problem. these approaches typically search for the global minimum energy conformation among an exponential number of protein conformations. we present a novel algorithm for protein redesign, which combines a statistical mechanics-derived ensemble-based approach to computing the binding constant with the speed and completeness of a branch-and-bound pruning algorithm. in addition, we developed an efficient deterministic approximation algorithm, capable of approximating our scoring function to arbitrary precision. in practice, the approximation algorithm decreases the execution time of the mutation search by a factor of ten. to test our method, we examined the phe-specific adenylation domain of the non-ribosomal peptide synthetase gramicidin synthetase a (grsa-phea). ensemble scoring, using a rotameric approximation to the partition functions of the bound and unbound states for grsa-phea, is first used to predict binding of the wildtype protein and a previously described mutant (selective for leucine), and second, to switch the enzyme specificity toward leucine, using two novel active site sequences computationally predicted by searching through the space of possible active site mutations. the top scoring in silico mutants were created in the wetlab and dissociation / binding constants were determined by fluorescence quenching. these tested mutations exhibit the desired change in specificity from phe to leu. our ensemble-based algorithm which flexibly models both protein and ligand using rotamer-based partition functions, has application in enzyme redesign, the prediction of protein-ligand binding, and computer-aided drug design.
edit distance between two rna structures. arc-annotated sequences are useful in representiug the structural information of rna sequences. typically, rna secondary and tertiary structures could be represented by a set of nested arcs and a set of crossing arcs, respectively. as the specified rna functions are determined by the specified molecular confirmation and therefore the specified secondary and tertiary structures, the comparison between rna secondary and tertiary structures have received much attention recently. in this paper, we propose the notion of edit distance to measure the similarity between two rna secondary and tertiary structures, by incorporating the various edit operations performing on both bases and arcs (base-pairs). several algorithms are presented to compute the edit distance two rna sequences with various arc structures and under various score schemes, either exactly or approximately. preliminary experimental tests confirm that our definition of edit distance and the computation model are among the most reasonable ones ever studied in the literature.
genetics and genemoics: impact on drug discovery and development. complex diseases is limited by a still rudimentary understanding of the molecular basis of disease as well as of drug action. at the heart of this is our current inability to account for inter-individual differences in disease etiology and drug response. these inter-individual differences are determined, to a large extent, by inherited predispositions and susceptibilities. knowledge of the genetic differences that explain these individual characteristics, and based upon it, the development of specific diagnostics and therapeutics, will therefore be critical for the successful transition to a future progress in health care. the impact of genetics and genomics will leave its mark along all steps involved in the creation of a new medicine: in the discovery of new targets that carry-inherently, because genetic linkage implies causation-a greater likelihood of success; in the discovery phase of a new drug aimed at an existing target, where the knowledge of molecular variation of this target (snps) may provide clues to achieve higher selectivity; where genetic epidemiology studies will provide added value by validating the target; and where large scale gene expression profiling (gene chips) will help select compounds with a higher likelihood for ultimate success at an early stage; and in the development phase of an drug undergoing clinical evaluation, where pharmacogenetic studies, and genotype-specific patient selection may allow recognition and definition of drug-responders and non-responders, or help decrease the likelihood of adverse events. although the impact of genetic and genomic investigation will certainly accelerate progress in biomedical research, we believe it will do so in an evolutionary fashion, and as a logical extension of the history of medical progress towards a more detailed understanding of disease and the resultant more refined differential diagnosis as well as more accurate prospective risk assessment. if any, the fundamental change we are going to witness in the years to come is a (paradigmatic) shift from today's largely clinical disease definition and diagnosis to a molecular definition and diagnosis of disease. this shift is likely to greatly increase the importance of in-vitro diagnostics and will mandate, much more than is the case today, an integrated approach of diagnostics and therapeutics. ultimately, we expert to derive the benefit of more successful, and more cost-effective medicines, and of possibly being able to prevent (or delay), rather than treat disease. it is important to realize that genetic research and testing are areas of great public concern, and that a more comprehensive dialogue between scientists and the public is urgently needed to address the societal, ethical, legal issues that are being raised. only then will we be able to truly take advantage of the significant advances in medical knowledge that genetic research will make possible, and fully realize the potential of these approaches towards the ultimate goal of all our striving, improving the human condition. the utility of most drugs prescribed today for common, complex diseases is limited by a still rudimentary understanding of the molecular basis of disease as well as of drug action. at the heart of his is our current inability to account for inter-individual differences in disease etiology and drug response. these inter-individual differences are determined, to a large extent, by inherited predispositions and susceptibilities. knowledge of the genetic differences that explain these individual characteristics, and based upon it, the development of specific diagnostics and therapeutics, will therefore be critical for the successful transition to a future progress in health care. the impact of genetics and genomics will leave its mark along all steps involved in the creation of a new medicine: in the discovery of new targets that carry-inherently, because genetic linkage implies causation-a greater likelihood of success; in the discovery of a new drug aimed at an existing target, where the knowledge of molecular variation of this target (snps) may provide clues to achieve higher selectivity; where genetic apidemiology studies will provide added value by validating the target; and where large scale gene expression profiling (gene chips) will help select compounds with a higher likelihood for ultimate success at an early stage; and in the development phase of an drug undergoing clinical evaluation, where pharmacogenetic studies, and genotype-specific patient selection may allow recognition and definition of drug-responders and non-responders, or help decrease the likelihood of adverse events. although the impact of genetic and genomic investigation will certainly accelerate progress in biomedical research, we believe it will do so in an evolutionary fashion, and as a logical extension of the history of medical progress towards a more detailed understanding of disease and the resultant more refined differential diagnosis as well as more accurate prospective risk assessment. if any, the fundamental change we are going to witness in the years to come is a (paradigmatic) shift from today's largely clinical disease definition and diagnosis to a molecular definition and diagnosis of disease. this shift is likely to greatly increase the importance of in-vitro diagnostics and will mandate, much more than is the case today, an integrated approach of diagnostics and therapeutics. ultimately, we expect to derive the benefit of more successful, and more cost-effective medicines, and of possibly being able to prevent (or delay), rather than treat disease. it is important to realize that genetic research and testing are areas of great public concern, and that a more comprehensive dialogue between scientists and the public is urgently needed to address the societal, ethical, legal issues that are being raised. only then will we be able to truly take advantage of the significant advances in medical knowledge that genetic research will make possible, and fully realize the potential of these approaches towards the ultimate goal of all our striving, improving the human condition.
finding anchors for genomic sequence comparison. recent sequencing of the human and other mammalian genomes has brought about the necessity to align them, to identify and characterize their commonalities and differences. programs that align whole genomes generally use a seed-and-extend technique, starting from exact or near-exact matches and selecting a reliable subset of these, called anchors, and then filling in the remaining portions between the anchors using a combination of local and global alignment algorithms, but their choices for the parameters so far have been primarily heuristic. we present a statistical framework and practical methods for selecting a set of matches that is both sensitive and specific and can constitute a reliable set of anchors for a one-to-one mapping of two genomes from which a whole-genome alignment can be built. starting from exact matches, we introduce a novel per-base repeat annotation, the $z$-score, from which noise and repeat filtering conditions are explored. dynamic programming-based chaining algorithms are also evaluated as context-based filters. we apply the methods described here to the comparison of two progressive assemblies of the human genome, ncbi build 28 and build 34 http://genome.ucsc.edu), and show that a significant portion of the two genomes can be found in selected exact matches, with very limited amount of sequence duplication.
pseudoknots in rna secondary structures. rna molecules are sequences of nucleotides that serve as more than mere intermediaries between dna and proteins, e.g. as catalytic molecules. computational prediction of rna secondary structure is among the few structure prediction problems that can be solved satisfactory in polynomial time. most work has been done to predict structures that do not contain pseudoknots. allowing pseudoknots introduce modelling and computational problems. in this paper we consider the problem of predicting rna secondary structure when certain types of pseudoknots are allowed. we first present an algorithm that in time &ogr;(n5) and space &ogr;(n3) predicts the secondary structure of an rna sequence of length n in a model that allows certain kinds of pseudoknots. we then prove that the general problem of predicting rna secondary structure containing pseudoknots is np-complete for a large class of reasonable models of pseudoknots.
the role of computational chemistry in translating genomic information into bioactive small molecules (abstract only). although genomic information provides many potential targets for drug discovery, the challenge is to convert this information into drugs that cure human disease. workers in computer assisted molecular design and chemometrics have developed a number of techniques to aid this process. examples include selecting diverse compounds for high throughput screening, designing universal or targeted combinatorial libraries, and using a variety of computational techniques to forecast binding affinitiy and bioavailability of compounds. this lecture will summarize recent advances in these areas.
evolutionary change in developmental genetic networks. the different combinations of genes that are active in different cells control the development and diversity of multicellular organisms. the codes that control this process, written in both cis-regulatory and protein-coding dna sequence, are poorly understood. decoding those sequences will require many experimental and bioinformatic approaches. one approach that will be useful is discovering the nodal control points that change when genetic networks evolve to change form and function. recent discoveries will be described on the molecular changes in a network that modifies limb number during arthropod evolution. another important experimental approach useful to decoding is the determination of precise gene expression patterns during model organism development, including which expression patterns are conserved and which are variable. a new approach has been developed that involves assigning spectral barcodes to many different nascent transcripts in developing animal nuclei. this will allow the rapid determination of precise spatial domains of transcriptional activation, and the construction of virtual embryos with complete maps of combinatorial gene expression. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
wrap-and-pack: a new paradigm for beta structural motif recognition with application to recognizing beta trefoils. a method is presented that uses β-strand interactions at both the sequence and the atomic level, to predict the beta-structural motifs in protein sequences. a program called wrap-and-pack implements this method, and is shown to recognize β-trefoils, an important class of globular β-structures, in the protein data bank with 92% specificity and 92.3% sensitivity in cross-validation. it is demonstrated that wrap-and-pack learns each of the ten known scop β-trefoil families, when trained primarily on β-structures that are not β-trefoils, together with 3d structures of known β-trefoils from outside the family. wrap-and-pack also predicts many proteins of unknown structure to be β-trefoils. the computational method used here may generalize to other β-structures for which strand topology and profiles of residue accessibility are well conserved.
the evolutionary capacity of protein structures. in nature, one finds large collections of different protein sequences exhibiting roughly the same three-dimensional structure, and this observation underpins the study of structural protein families. in studying such families at a global level, a natural question to ask is how close to "optimal" the native sequences are in terms of their energy. we therefore define and compute the evolutionary capacity of a protein structure as the total number of sequences whose energy in the structure is below that of the native sequence. an important aspect of our definition is that we consider the space of all possible protein sequences, i.e. the exponentially large set of all strings over the 20-letter amino acid alphabet, rather than just the set of sequences found in nature.in order to make our approach computationally feasible, we develop randomized algorithms that perform approximate enumeration in sequence space with provable performance guarantees. we draw on the area of rapidly mixing markov chains, by exhibiting a connection between the evolutionary capacity of proteins and the number of feasible solutions to the knapsack problem. this connection allows us to design an algorithm for approximating the evolutionary capacity, extending a recent result of morris and sinclair on the knapsack problem. we present computational experiments that show the method to be effective in practice on large collections of protein structures. in addition, we show how to use approximations to the evolutionary capacity to compute a statistical mechanics notion of "evolutionary temperature" on sequence space.
revealing protein structures: a new method for mapping antibody epitopes. a recent idea for determining the three-dimensional structure of a protein uses antibody recognition of surface structure and random peptide libraries to map antibody epitope combining sites. antibodies that bind to the surface of the protein of interest can be used as "witnesses" to report the structure of the protein as follows: proteins are composed of linear polypeptide chains that come together in complex spatial folding patterns to create the native protein structures and these folded structures form the binding sites for the antibodies. short amino acid probe sequences, which bind to the active region of each antibody, can be selected from random sequence peptide libraries. these probe sequences can often be aligned to discontinuous regions of the one-dimensional target sequence of a protein. such alignments indicate how pieces of the protein sequence must be folded together in space and thus provide valuable long-range constraints for solving the overall 3-d structure. this new approach is applicable to the very large number of proteins that are refractory to current approaches to structure determination and has the advantage of requiring very small amounts of the target protein. the binding site of an antibody is a surface, not just a linear sequence, so the epitope mapping alignment problem is outside the scope of classical string alignment algorithms, such as smith-waterman. we formalize the alignment problem that is at the heart of this new approach, prove that the epitope mapping alignment problem is np-complete, and give some initial results using a branch-and-bound algorithm to map two real-life cases.
comparing sequence scaffolds. the dna sequence assembler we built for the whole genome shotgun assembly of the human genome, utilizes end-reads of inserts to order and orient assembled contigs into scaffolds for which the distances between consecutive contigs are statistically characterized. we consider the problem of comparing two such scaffolds. applications include comparison of two distinct assemblies for mutual confirmation, and comparison of scaffold assemblies of bacs to determine a whole genome tiling of the bacs. we formalize the problem and develop efficient algorithms for a number of variations of the problem, the essential result being a sparse algorithm that refines gap estimates based on the overlap evidence.
a multi-expert system for the automatic detection of protein domains from sequence information. we describe a novel method for detecting the domain structure of a protein from sequence information alone. the method is based on analyzing multiple sequence alignments that are derived from a database search. multiple measures are defined to quantify the domain information content of each position along the sequence, and are combined into a single predictor using a neural network. the output is further smoothed and post-processed using a probabilistic model to predict the most likely transition or boundary positions between domains. the method was assessed using the domain definitions in scop for proteins of known structures and was compared to several other existing methods. our method improves significantly over the best method available, the semi-manual pfam domain database, while being fully automatic. our method can also be used to verify domain partitions based on structural data. few examples of predicted domain definitions and alternative partitions, as suggested by our method, are also discussed.
human genome analysis and medicine in the 21st century (abstract only). the human genome project is now considered to be the most important project in biological and medical research. the discovery of entire human genes that are estimated to be 70,000-150,000 in our genome, through this project must revolutionize biological medicine including molecular diagnosis of various diseases and development or novel treatment. dna sequences of an entire human genome consisting of 3x109 nucleotides will be completely determined by 2003, and 90% of our genes will be identified by 2001 although it will take 10-20 years to obtain the information of their biological functions. such information will accelerate discovery of genes susceptible to or causing various diseases and should contribute to screening of novel drugs that target these disease-gene products. in this regard, analysis of expression profiles and snps (single nucleotide polymorphisms) using microarray or dna-chip is quite important. microarray or dna chip technology has made it possible to examine expression levels of thousands of genes and genotype a huge number of snps by a single experiment. we have been applying microarray analysis for screening of genes involving in colorectal, hepatocellular, and ovarian carcinogenesis as well as those related to responsiveness to anti-cancer drugs and those involving in various signal trunsduction pathways of medical importance. we have so far established a system to analyze 15,000 genes and are accumulating the expression profile data of various types of cancer cells. for example, we analyzed cancer tissues of 13 esophageal cancer patients who were treated by the same chemotherapy after their operation. although all of them had an advanced cancer and could not have curative operation, four patients achieved a very long survival of 43-103 months, indicating that the chemotherapy was very efficient to these four patients. in contrast, four patients had very short survival of 4-12 months. a comparison of expression profiles of the patients with very short or very long survivals has disclosed that the expression levels of nearly 50 genes may be associated with responsiveness of the chemotherapy. this result implies that examination of expression levels of a set of genes may be a good predictor for a certain anti-cancer treatment. at present, a large number of cancer patients are treated with anti-cancer drugs without any knowing whether the drugs are effective to their cancer cells and a significant proportion of them suffered from side-effects without no effect. hence, our approach must contribute to predict the effect before the patients start to have treatment with anti-cancer drugs. secondary, we have also been examining genes which are up-regulated or down-regulated in a certain biological condition by means of microarray coupled with laser-captured microdissection (lcm). a comparison of expression levels of normal mucosal cells, adenoma cells, and cancer cells from the same patients with colorectal tumor, we identified dozens of genes whose expression levels were significantly increased or decreased in tumor cells. the results clearly indicated that the microarray analysis is a very powerful tool to examine genes involving in carcinogenesis. in addition to the expression profile analysis, the recent world-wide effort of the snp (single nucleotide polymorphism) project that aims to discover 300,000 or more genetic variations in our genome will generate very valuable resources. we undertook a systematic survey of genomic dna for snps located not only in coding sequences but also in non-coding regions (e.g introns and 5' flanking regions) of genes of medical interest. using dna samples from japanese patients with rheumatoid arthritis (ra) or myocardial infarction (mi) as templates, we surveyed 82 genes that represent candidates for ra or mi, screening a total of 224 kb of dna (107 kb of coding sequences and 117 kb of non-coding dna). within this 224-kb genomic sequences we identified 329 snps (1 per 680 bases on average), 50 insertions or deletions. fifty-two percent of the coding snps were non-synonymous substitutions, and non-conservative amino acid changes were observed in a quarter of those. allelic frequencies of some of the polymorphisms were significantly different from those reported in european populations. for example, the q506r substitution in the coagulation factor v gene, the so-called &ldquo;leiden mutation&rdquo;, has a reported frequency of 2.3% in europeans, but we detected the leiden mutation in none of the japanese genomes we investigated. the allelic frequencies of the 33 &mdash; a>g snp in the thrombomodulin gene were also very different; this allele occurred at 12% frequency in the japanese patients we examined, although it had been detected in none of 82 caucasians reported previously. these data support the hypothesis that some snps are specific to particular ethnic groups. in the meeting, i introduce the recent progress and future direction of human genome analysis and its impact on the medical science. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
reconstructing reticulate evolution in species: theory and practice. we present new methods for reconstructing reticulate evolution of species due to events such as horizontal transfer or hybrid speciation; both methods are based upon extensions of wayne maddison's approach in his seminal 1997 paper. our first method is a polynomial time algorithm for constructing phylogenetic networks from two gene trees contained inside the network. we allow the network to have an arbitrary number of reticulations, but we limit the reticulation in the network so that the cycles in network are node-disjoint ("galled"); we prove accuracy guarantees for our first method by presenting a formal characterization of the set of gene trees defined by a species network. our second method is a polynomial time algorithm for constructing networks with one reticulation, where we allow for errors in the estimated gene trees. using simulations, we demonstrate improved performance of this method over both neighbornet and maddison's method.
fast and simple character classes and bounded gaps pattern matching, with application to protein searching. the problem of fast searching of a pattern that contains classes of characters and bounded size gaps (cbg) in a text has a wide range of applications, among which a very important one is protein pattern matching (for instance, one prosite protein site is associated with the cbg [rk] &mdash; x(2, 3) &mdash; [de] &mdash; x(2, 3) &mdash; y, where the brackets match any of the letters inside, and x(2, 3) a gap of length between 2 and 3). currently, the only way to search a cbg in a text is to convert it into a full regular expression (re). however, a re is more sophisticated than a cbg, and searching it with a re pattern matching algorithm complicates the search and makes it slow. this is the reason why we design in this article two new practical cbg matching algorithms that are much simpler and faster than all the re search techniques. the first one looks exactly once at each text character. the second one does not need to consider all the text characters and hence it is usually faster than the first one, but in bad cases may have to read the same text character more than once. we then propose a criterion based on the form of the cbg to choose a-priori the fastest between both. we performed many practical experiments using the prosite database, and all them show that our algorithms are the fastest in virtually all cases.
simulating boolean circuits on a dna computer. we demonstrate that dna computers can simulate boolean circuits with a small overhead. boolean circuits embody the notion of massively parallel signal processing and are frequently encountered in many parallel algorithms. many important problems such as sorting, integer arithmetic, and matrix multiplication are known to be computable by small size boolean circuits much faster than by ordinary sequential digital computers. this paper shows that dna chemistry allows one to simulate large semi-unbounded fan-in boolean circuits with a logarithmic slowdown in computation time. also, for the class nc$^1$, the slowdown can be reduced to a constant. in this algorithm we have encoded the inputs, the boolean and gates, and the or gates to dna oligonucleotide sequences. we operate on the gates and the inputs by standard molecular techniques of sequence-specific annealing, ligation, separation by size, limited amplification, sequence-specific cleavage, and detection by size. preliminary biochemical experiments on a small test circuit have produced encouraging results. further confirmatory experiments are in progress.
determining contact energy function for continuous state models of globular protein conformations. one of the approaches to protein structure prediction is to obtain energy functions which can recognize the native conformation of a given sequence among a zoo of conformations. the discriminations can be done by assigning the lowest energy to the native conformation, with the guarantee that the native is in the zoo. well-adjusted functions, then, can be used in the search for other (near-) natives. here the aim is the discrimination at relatively high resolution (rmsd difference between the native and the closest nonnative is around 1 &aring;) by pairwise energy potentials. the results show that the potential can be trained to discriminate between the native conformation of one protein as the (near-) global minimum, and other nonnatives, including energy-minimized ones (or local minima). this potential function is able to identify the native conformation of another protein, too.
set association analysis of snp case-control and microarray data. common heritable diseases ("complex traits") are assumed to be due to multiple underlying susceptibility genes. while genetic mapping methods for mendelian disorders have been very successful, the search for genes underlying complex traits has been difficult and often disappointing. one of the reasons may be that most current gene mapping approaches are still based on conventional methodology of testing one or a few snps at a time. here we demonstrate a simple strategy that allows for the joint analysis of multiple disease-associated snps in different genomic regions. our set-association method combines information over snps by forming sums of relevant single-marker statistics. this approach successfully addresses the "curse of dimensionality" problem - too many variables should be estimated with a comparatively small number of observations. we also extend our method to microarray expression data, where expression levels for large numbers of genes should be compared between two tissue types. in applications to experimental expression data our approach turned out to be highly efficient.
applications of generalized pair hidden markov models to alignment and gene finding problems. hidden markov models (hmms) have been successfully applied to a variety of problems in molecular biology, ranging from alignment problems to gene finding and annotation. alignment problems can be solved with pair hmms, while gene finding programs rely on generalized hmms in order to model exon lengths. in this paper we introduce the generalized pair hmm (gphmm), which is an extension of both pair and generalized hmms. we show how gphmms, in conjunction with approximate alignments, can be used for cross-species gene finding, and describe applications to dna-cdna and dna-protein alignment. gphmms provide a unifying and probabilistically sound theory for modeling these problems.
picking alignments from (steiner) trees. the application of needleman-wunsch alignment techniques to biological sequences is complicated by two serious problems when the sequences are long: the running time, which scales as the product of the lengths of sequences, and the difficulty in obtaining suitable parameters that produce meaningful alignments. the running time problem is often corrected by reducing the search space, using techniques such as banding, or chaining of high scoring pairs. the parameter problem is more difficult to fix, partly because the probabilistic model, which needleman-wunsch is equivalent to, does not capture a key feature of biological sequence alignments, namely the alternation of conserved blocks and seemingly unrelated non-conserved segments. we present a solution to the problem of designing efficient search spaces for pair hidden markov models that align biological sequences by taking advantage of their associated features. our approach leads to an optimization problem, for which we obtain a 2-approximation algorithm, and that is based on the construction of manhattan networks, which are close relatives of steiner trees. we describe the underlying theory and show how our methods can be applied to alignment of dna sequences in practice, succesfully reducing the viterbi algorithm search space of alignment phmms by three orders of magnitude.
gene functional classification from heterogeneous data. in our attempts to understand cellular function at the molecular level, we must be able to synthesize information from disparate types of genomic data. we consider the problem of inferring gene functional classifications from a heterogeneous data set consisting of dna microarray expression measurements and phylogenetic profiles from whole-genome sequence comparisons. we demonstrate the application of the support vector machine (svm) learning algorithm to this functional inference task. our results suggest the importance of exploiting prior information about the heterogeneity of the data. in particular, we propose an svm kernel function that is explicitly heterogeneous. we also show how to use knowledge about heterogeneity to aid in feature selection.
resolution of haplotypes and haplotype frequencies from snp genotypes of pooled samples. recent efforts to characterize genetic variation indicate that humans share large chromosomal blocks, along which little to no recombination is observable. thus, on a segment-by-segment basis, only a handful of haplotypes account for most human genotypes. currently, the challenge of registering haplotypes and their frequencies is met by genotyping individuals one by one, a process which is overall resource intensive. instead, we propose utilizing the ability of current genotyping technologies to pool dna samples and output allele frequencies of snp markers. we enable inference of haplotypes and haplotype frequencies from such pooled data, by novel computational methods. this strategy harnesses the economics of pooling for the task of haplotyping, potentially offering a 10-20-fold saving in genotyping reactions performed.we show that a small number of pools can be used to accurately and cost-effectively reconstruct a haplotype block and determine haplotype frequencies.
comparing rna expression patterns of embryos. in situ staining of a target mrna at several time points during the development of a d. melanogaster embryo gives one a detailed spatio-temporal view of the expression pattern of a given gene. we have developed algorithms and software for analyzing a database of such images with the goal of being able to identify coordinately expressed genes and further our understanding of cis-regulatory control during embryogenesis. our approach combines measures of similarity at both the global and local levels, based on gaussian mixture model (gmm) decompositions. at the global level, the observed distribution of pixel values is quantized using an adaptive gmm decomposition and then quantized images are compared using mutual information. at the local level, we decompose quantized images into 2-dimensional gaussian kernels or "blobs" and then develop a blob-set matching method to search for the best matching traits in different pattern-images. a hybrid scoring method is proposed to combine both global and local matching results. we further develop a voting scheme to search for genes with similar spatial staining patterns over the time course of embryo development. to evaluate the effectiveness of our approach, we compare it with several global image matching schemes and a controlled vocabulary method. we then apply our method to 4400 images of 136 genes to detect potentially co-regulated genes that have similar spatio-temporal patterns, using expert-annotation to evaluate our results.
mutation-tolerant protein identification by mass-spectrometry. database search in tandem mass spectrometry is a powerful tool for protein identification. high-throughput spectral acquisition raises the problem of dealing with genetic variation and peptide modifications within a population of related proteins. a method that cross-correlates and clusters related spectra in large collections of uncharacterized spectra (i.e from normal and diseased individuals) would be extremely valuable in functional proteomics. this problem is far from being simple since very similar peptides may have very different spectra. we introduce a new notion of spectral similarity that allows one to identify related spectra even if the corresponding peptides have multiple modifications/mutations. based on this notion we developed a new algorithm for mutation-tolerant database search as well as a method for cross-correlating related uncharacterized spectra. the paper describes this new approach and its applications in functional proteomics.
transforming men into mice: the nadeau-taylor chromosomal breakage model revisited. although analysis of genome rearrangements was pioneered by dobzhansky and sturtevant 65 years ago, we still know very little about the rearrangement events that produced the existing varieties of genomic architectures. the genomic sequences of human and mouse provide evidence for a larger number of rearrangements than previously thought and shed some light on previously unknown features of mammalian evolution. in particular, they reveal extensive re-use of breakpoints from the same relatively short regions. our analysis implies the existence of a large number of very short "hidden" synteny blocks that were invisible in comparative mapping data and were not taken into account in previous studies of chromosome evolution. these blocks are defined by closely located breakpoints and are often hard to detect. our result is in conflict with the widely accepted random breakage model of chromosomal evolution. we suggest a new "fragile breakage" model of chromosome evolution that postulates that breakpoints are chosen from relatively short fragile regions that have much higher propensity for rearrangements than the rest of the genome.
repeat classification and fragment assembly. repetitive sequences make up a significant fraction of almost any genome and an important and still open question in bioinformatics is how to represent all repeats in dna sequences. we propose a radically new approach to repeat classification that is motivated by the fundamental topological notion of quotient spaces. a torus or klein bottle are examples of quotient spaces that can be obtained from a square by gluing some points. our new repeat classification algorithm is based on the observation that the alignment-induced quotient space of a dna sequence compactly represents all sequence repeats. this observation leads to a simple and efficient solution of the repeat classification problem as well as new approaches to fragment assembly and multiple alignment.
a new approach to fragment assembly in dna sequencing. for the last twenty years fragment assembly in dna sequencing followed the &ldquo;overlap - layout - consensus&rdquo; paradigm that is used in all currently available assembly tools. although this approach proved to be useful in assembling clones, it faces difficulties in genomic shotgun assembly: the existing algorithms make assembly errors and are often unable to resolve repeats even in prokaryotic genomes. biologists are well-aware of these errors and are forced to carry additional experiments to verify the assembled contigs. we abandon the classical &ldquo;overlap - layout - consensus&rdquo; approach in favor of a new eulerian superpath approach that, for the first time, resolves the problem of repeats in fragment assembly. our main result is the reduction of the fragment assembly to a variation of the classical eulerian path problem. this reduction opens new possibilities for repeat resolution and allows one to generate error-free solutions of the large-scale fragment assembly problems. the major improvement of euler over other algorithms is that it resolves all repeats except long perfect repeats that are theoretically impossible to resolve without additional experiments.
structured motifs search. in this paper we describe an algorithm for the localization of structured models, i.e. sequences of (simple) motifs and distance constraints. it basically combines standard pattern matching procedures with a constraint satisfaction solver, and it has the ability, not present in similar tools, to search for partial matches. a significant feature of our approach, especially in terms of efficiency for the application context, is that the (potentially) exponentially many solutions to the considered problem are represented in compact form as a graph. moreover, the time and space necessary to build the graph are linear in the number of occurrences of the component patterns.
probabilities for having a new fold on the basis of a map of all protein sequences. it is a major problem in the study of protein structure to predict which proteins have new, currently unknown structural folds. in an attempt to address this problem we studied the location of all proteins with solved structures within the map of all known protein sequences provided by protomap. the mutual distances in this map among solved structures are used to derive a probabilistic model from which we infer an estimate for the probability of an unsolved protein to have a new fold. the probabilities were based on data from scop release 1.37. the results were evaluated against the more recent scop pre-release 1.41. our predicted probabilities for unsolved proteins to have a new fold are very well correlated with the proportion of new folds among recently released structures. thus, information about the structure of proteins can be inferred from a global relational view of protein sequences. finally, the same procedure was applied to estimate probabilities on the basis of scop 1.41. a list of the highest scoring proteins is provided: these are about 80 non-membranous proteins that belong to clusters with more than 5 proteins and achieve the highest probability to have a new fold. a rational selection for 3d determination of those targets is expected to accelerate the pace of new fold discovery.
sequencing-by-hybridization at the information-theory bound: an optimal algorithm. in a recent paper [pfu99) we have introduced a novel probing scheme for dna sequencing by hybridization (sbh). the new gapped-probe scheme combines natural and universal bases in a well defined periodic pattern. it was shown in [pfu99] that the performance of the gapped-probe scheme (in terms of the length of a sequence that can be uniquely reconstructed using a given library size of probes) is significantly better than the standard scheme based on oligomer probes. in this paper we present and analyze a new, more powerful, sequencing algorithm for the gapped-probe scheme. we prove that the new algorithm exploits the full potential of the sbh technology with high-confidence performance, that comes within a small constant factor (about 2) of the information-theory bound. moreover, this performance is achieved while maintaining running time linear in the target sequence length.
imposing specificity by regulated localization (abstract only). many biologically important enzymes &mdash; rna polymerases, rna splicing enzymes, ubiquinating enzymes, certain kinases and proteases &mdash; are &ldquo;`regulated&rdquo;' by being brought to one or another of many potential substrates by auxiliary docking proteins (e.g. transcriptional activators). these regulatory interactions require interactions between simple adhesive (but specific) surfaces. this kind of regulation is highly `evolvable' : new and expanded meanings to signals are readily generated by simple changes in protein surfaces.
string barcoding: uncovering optimal virus signatures. there are many critical situations when one needs to rapidly identify an unidentified pathogen from among a given set of previously sequenced pathogens. dna or rna hybridization chips can be designed for such identifications. each cell in the chip can report the presence or absence of a specific substring of dna in the unidentified pathogen. properly designed, the collection of reports obtained from the cells can uniquely identify any pathogen in the set, or determine that the unidentified pathogen is not in the set. there is a limit to the number of cells on a chip, and a range of substring lengths that a cell can handle. so, given the full sequences of a set of pathogens, the problem is to design the chip by selecting the smallest set of substrings of the appropriate lengths, so that each pathogen in the set has a unique set of cells that report a substring. for any given pathogen, the set of reporting cells is its signature, and hence the entire system is a "barcode" system for the pathogens.previous work addressed this problem [1], but focused on pathogens of bacterial size, and hence had to make many compromises for the sake of efficiency. the substrings lengths were severely restricted, and no optimality or near-optimality was guaranteed. in this paper, we focus on viral-size pathogens. we show that for genomes of this size, it is practical to solve the barcode design problem optimally, or near-optimally, without artificially constraining the problem. we also efficiently find barcodes that provide a level of redundancy, tolerating a number of errors or mutations. the key technical ideas are the use of suffix trees to identify the critical substrings, integer-linear programming (ilp) to express the minimization problem, and a simple idea that dramatically reduces the size of the ilp, allowing it to be solved efficiently by the commercial ilp solver cplex. we report extensive tests of our approach on various collections of virus dna and rna sequences.
scoring two-species local alignments to try to statistically separate neutrally evolving from selected dna segments. we construct several score functions for use in locating unusually conserved regions in a genome-wide search of aligned dna from two species. we test these functions on regions of the human genome aligned to the mouse genome. these score functions are derived from properties of neutrally evolving sites on the mouse and human genome, and can be adjusted to the local background rate of conservation. the aim of these functions is to try to identify regions of the human genome that are conserved by evolutionary selection, because they have an important function, rather than by chance. we use them to get a very rough estimate of the amount of dna in the human genome that is under selection.
biological and computational annotation of the drosophila genome sequence. the nucleotide sequence of the drosophila melanogaster genome is now available and efforts are ongoing to improve its accuracy and annotation. the value of these sequence data will be enormously enhanced if we can provide for each gene information on: (1) the structure and expression pattern of its transcripts; (2) the mechanisms and logic used to control their expression; and (3) the functions of their protein products. my presentation will be directed toward the challenges of obtaining and interpreting such information for the fruit fly. gene sequence and expression pattern databases will be extremely powerful tools. however, the function of a protein in a multicellular organism depends on context and will almost certainly need to be determined by experimental analysis. collection of the required large datasets will be difficult and neither the intellectual framework nor experimental tools for analyzing complex gene networks are currently in place. nevertheless, there is reason for cautious optimism that the complete genomic sequence of organisms will enable the necessary global approaches to study gene function and regulation. the conservation of gene structure and function during evolution will allow for the linking and sharing of information garnered in different experimental systems. but what data should be collected and how to interpret these data are much less clear. i will describe recent attempts by the berkeley drosophila genome project to address some of these issues.
early eukaryote evolution based on mitochondrial gene order breakpoints. we present a general heuristic for the median problem for induced breakpoints on genomes with unequal gene content and incorporate this into a routine for estimating optimal gene orders for the ancestral genomes in a fixed phylogeny. the routine is applied to a phylogenetic study of an up-to-date set of completely sequenced protist mitochondrial genomes, confirming some of the recent sequence-based groupings which have been proposed and, conversely, confirming the usefulness of the breakpoint method as a phylogenetic tool even for small genomes.
chromosomal breakpoint re-use in the inference of genome sequence rearrangement. in order to apply gene-order rearrangement algorithms to the comparison of genome sequences, pevzner and tesler [9] bypass gene finding and ortholog identification, and use the order of homologous blocks of unannotated sequence as input. the method excludes blocks shorter than a threshold length and ignores small block-internal rearrangements. here we investigate possible biases introduced by eliminating and amalgamating short blocks, focusing on the notion of "breakpoint re-use" introduced by these authors. analytic and simulation methods show that re-use is very sensitive to threshold size and to parameters of the rearrangement process. as is pertinent to the comparison of mammalian genomes, large thresholds in the context of high rates of small rearrangements risk randomizing the comparison completely. we suggest a number of mathematical, algorithmic and statistical lines for further developing the pevzner-tesler approach.
towards predicting coiled-coil protein interactions. protein-protein interactions play a central role in many cellular functions, and as whole-genome data accumulates, computational methods for predicting these interactions become increasingly important. computational methods have already proven to be a useful first step for rapid genome-wide identification of putative protein structure and function, but research on the problem of computationally determining biologically relevant partners for given protein sequences is just beginning. in this paper, we approach the problem of predicting protein-protein interactions by focusing on the 2- stranded coiled-coil motif. we introduce a computational method for predicting coiled-coil protein interactions, and give a novel framework that is able to use both genomic sequence data and experimental data in making these predictions. cross-validation tests show that the method is able to predict many aspects of protein-protein interactions mediated by the coiled-coil motif, and suggest that this methodology can be used as the basis for genome-wide prediction of coiled-coil protein interactions.
discriminative motifs. this paper takes a new view of motif discovery, addressing a common problem in existing motif finders. a motif is treated as a feature of the input promoter regions that leads to a good classifier between these promoters and a set of background promoters. this perspective allows us to adapt existing methods of feature selection, a well studied topic in machine learning, to motif discovery. we develop a general algorithmic framework that can be specialized to work with a wide variety of motif models, including consensus models with degenerate symbols or mismatches, and composite motifs. a key feature of our algorithm is that it measures over-representation while maintaining information about the distribution of motif instances in individual promoters. the assessment of a motif's discriminative power is normalized against chance behaviour by a probabilistic analysis. we apply our framework to two popular motif models, and are able to detect several known binding sites in sets of co-regulated genes in yeast.
approximation of protein structure for fast similarity measures. it is shown that structural similarity between proteins can be decided well with much less information than what is used in common similarity measures. the full cα representation contains redundant information because of the inherent chain topology of proteins and a limit on their compactness due to excluded volume. a wavelet analysis on random chains and proteins justifies approximating subchains by their centers of mass. for not too compact chain-like structures in general, and proteins in particular, similarity measures that use this approximation are highly correlated to the exact similarity measures and are therefore useful, e.g., as fast filters. experimental results with such simplified similarity measures in two applications, nearest neighbor search and automatic structural classification show a significant speed up.
class prediction and discovery using gene expression data. classification of patient samples is a crucial aspect of cancer diagnosis and treatment. we present a method for classifying samples by computational analysis of gene expression data. we consider the classification problem in two parts: class discovery and class prediction. class discovery refers to the process of dividing samples into reproducible classes that have similar behavior or properties, while class prediction places new samples into already known classes. we describe a method for performing class prediction and illustrate its strength by correctly classifying bone marrow and blood samples from acute leukemia patients. we also describe how to use our predictor to validate newly discovered classes, and we demonstrate how this technique could have discovered the key distinctions among leukemias if they were not already known. this proof-of-concept experiment paves the way for a wealth of future work on the molecular classification and understanding of disease.
from promoter sequence to expression: a probabilistic framework. we present a probabilistic framework that models the process by which transcriptional binding explains the mrna expression of different genes. our joint probabilistic model unifies the two key components of this process: the prediction of gene regulation events from sequence motifs in the gene's promoter region, and the prediction of mrna expression from combinations of gene regulation events in different settings. our approach has several advantages. by learning promoter sequence motifs that are directly predictive of expression data, it can improve the identification of binding site patterns. it is also able to identify combinatorial regulation via interactions of different transcription factors. finally, the general framework allows us to integrate additional data sources, including data from the recent binding localization assays. we demonstrate our approach on the cell cycle data of spellman et al., combined with the binding localization information of simon et al. we show that the learned model predicts expression from sequence, and that it identifies coherent co-regulated groups with significant transcription factor motifs. it also provides valuable biological insight into the domain via these co-regulated "modules" and the combinatorial regulation effects that govern their behavior.
probabilistic hierarchical clustering for biological data. biological data, such as gene expression profiles or protein sequences, is often organized in a hierarchy of classes, where the instances assigned to "nearby" classes in the tree are similar. most approaches for constructing a hierarchy use simple local operations, that are very sensitive to noise or variation in the data. in this paper, we describe probabilistic abstraction hierarchies (pah) [11], a general probabilistic framework for clustering data into a hierarchy, and show how it can be applied to a wide variety of biological data sets. in a pah, each class is associated with a probabilistic generative model for the data in the class. the pah clustering algorithm simultaneously optimizes three things: the assignment of data instances to clusters, the models associated with the clusters, and the structure of the pah approach is that it utilizes global optimization algorithms for the last two steps, substantially reducing the sensitivity to noise and the propensity to local maxima. we show how to apply this framework to gene expression data, protein sequence data, and hiv protease sequence data. we also show how our framework supports hierarchies involving more than one type of data. we demonstrate that our method extracts useful biological knowledge and is substantially more robust than hierarchical agglomerative clustering.
a discriminative model for identifying spatial cis-regulatory modules. transcriptional regulation is mediated by the coordinated binding of transcription factors to the upstream region of genes. in higher eukaryotes, the binding sites of cooperating transcription factors are organized into short sequence units, called cis-regulatory modules. in this paper we propose a method for identifying modules of transcription factor binding sites in a set of co-regulated genes, using only the raw sequence data as input. our method is based on a novel probabilistic model that describes the mechanism of cis-regulation, including the binding sites of cooperating transcription factors, the organization of these binding sites into short sequence modules, and the regulation of a gene by its modules. we show that our method is successful in discovering planted modules in simulated data and known modules in yeast. more importantly, we applied our method to a large collection of human gene sets, and found 83 significant cis-regulatory modules, which included 36 known motifs and many novel ones. thus, our results provide one of the first comprehensive compendiums of putative cis-regulatory modules in human.
using motion planning to study protein folding pathways. we present a framework for studying protein folding pathways and potential landscapes which is based on techniques recently developed in the robotics motion planning community. in particular, our work uses probabilistic roadmap (prm) motion planning techniques which have proven to be very successful for problems involving high-dimensional configuration spaces. our results applying prm techniques to several small proteins (60 residues) are very encouraging. the framework enables one to easily and efficiently compute folding pathways from any denatured starting state to the native fold. this aspect makes our approach ideal for studying global properties of the protein's potential landscape. for example, our results show that folding pathways from different starting denatured states sometimes share some common `gullies', mainly when they are close to the native fold. such global issues are difficult to simulate and study with other methods. our focus in this work is to study the protein folding mechanism assuming we know the native fold. therefore, instead of performing fold prediction, we aim to study issues related to the folding process, such as the formation of secondary and tertiary structure, and the dependence on the initial conformation. our results indicate that for some proteins, secondary structure clearly forms first while for others the tertiary structure is obtained more directly, and moreover, these situations seem to be differentiated in the distributions of the conformations sampled by our technique. we also find that the formation order is independent of the starting denatured conformation. we validate our results by comparing the secondary structure formation order on our paths to known pulse-labeling experimental results. this indicates the promise of our approach for studying proteins for which experimental results are not available.
large scale sequencing by hybridization. sequencing by hybridization is a method for reconstructing a dna sequence based on its k-mer content. this content, called the spectrum of the sequence, can be obtained from hybridization with a universal dna chip. however, even with a sequencing chip containing all 49 9-mers and assuming no hybridization errors, only about 400 bases-long sequences can be reconstructed unambiguously. drmanac et al. suggested sequencing long dna targets by obtaining spectra of many short overlapping fragments of the target, inferring their relative positions along the target and computing spectra of subfragments that are short enough to be uniquely recoverable. drmanac et al. do not treat the realistic case of errors in the hybridization process. in this paper we study the effect of such errors. we show that the probability of ambiguous reconstruction in the presence of (false negative) errors is close to the probability in the errorless case. more precisely, the ratio between these probabilities is 1 + &ogr;(p/(1 - p)4 &middot; 1/d) where d is the average distance between neighboring subfragments, and p is the probability of a false negative. we also obtain lower and upper bounds for the probability of unambiguous reconstruction based on errorless spectrum. for realistic chip sizes, these bounds are tighter than those given by arratia et al. finally, we report results on simulations with real dna sequences, showing that even in the presence of 50% false negative errors, a target of cosmid length can be recovered with less than 0.1% miscalled bases.
identification of protein complexes by comparative analysis of yeast and bacterial protein interaction data. mounting evidence shows that many protein complexes are conserved in evolution. here we use conservation to find complexes that are common to yeast s. cerevisiae and bacteria h. pylori. our analysis combines protein interaction data, that are available for each of the two species, and orthology information based on protein sequence comparison. we develop a detailed probabilistic model for protein complexes in a single species, and a model for the conservation of complexes between two species. using these models, one can recast the question of finding conserved complexes as a problem of searching for heavy subgraphs in an edge- and node-weighted graph, whose nodes are orthologous protein pairs.we tested this approach on the data currently available for yeast and bacteria and detected 11 significantly conserved complexes. several of these complexes match very well with prior experimental knowledge on complexes in yeast only, and serve for validation of our methodology. the complexes suggest new functions for a variety of uncharacterized proteins. by identifying a conserved complex whose yeast proteins function predominantly in the nuclear pore complex, we propose that the corresponding bacterial proteins function as a coherent cellular membrane transport system. we also compare our results to two alternative methods for detecting complexes, and demonstrate that our methodology obtains a much higher specificity.
rna biology and the genome (abstract only). the sequence of vertebrate genome is expressed by rna splicing producing mrna. interpreting the genome requires understanding the sequences recognized by the nuclear factors and spliceosomia executing removal of introns. the status of this area of science will be reviewed. conversely, genome sequences can be searched for sequences which specify rna splicing and are common of many genes. the availability of genome sequences from a variety of species will make the latter approach much more powerful. the recently discovered rna interference (rnai) process is evolutionarily old and related processes are important for control of expression of repetitive genes in some organisms. rnai can be initiated by conversion of double strand rna into 21-23 nucleotide rnas which can base pair with mrnas and direct their cleavage. these short rnas may also direct silencing of genes by other mechanisms. over half of the genome of many organisms is composed of repetitive sequences and it is possible that rnai may silence these sequences.
matching simulation and experiment (extended abstract): a new simplified model for simulating protein folding. simulations of simplified protein folding models have provided much insight into solving the protein folding problem. we propose here a new off-lattice bead model, capable of simulating several different fold classes of small proteins. we present the sequence for an &agr;/&bgr; protein resembling the igg-binding proteins l and g. the thermodynamics of the folding process for this model are characterized using the multiple multi-histogram method combined with constant-temperature langevin simulations. the folding is shown to be highly cooperative, with chain collapse nearly accompanying folding. two parallel folding pathways are shown to exist on the folding free energy landscape. one pathway contains an intermediate&mdash;similar to experiments on protein g, and one pathway contains no intermediates&mdash;similar to experiments on protein l. the folding kinetics are characterized by tabulating mean-first passage times, and we show that the onset of glasslike kinetics occurs at much lower temperatures than the folding temperature. this model is expected to be useful in many future contexts; investigating questions of the role of local versus non-local interactions in various fold classes, addressing the effect of sequence mutations affecting secondary structure propensities, and providing a computationally feasible model for studying the role of solvation forces in protein folding.
multiple sequence alignment based on profile alignment of intermediate sequences. despite considerable efforts, it remains difficult to obtain accurate multiple sequence alignments. by using additional hits from database search of the input sequences, a few strategies have been proposed to significantly improve alignment accuracy, including the construction of profiles from the hits while performing profile alignment, the inclusion of high scoring hits into the input sequences, the use of intermediate sequence search to link distant homologs, and the use of secondary structure information. we develop an algorithm that integrates these strategies to further improve alignment accuracy by modifying the pair-hmm approach in probcons to incorporate profiles of intermediate sequences from database search and utilize secondary structure predictions as in spem. we test our algorithm on a few sets of benchmark multiple alignments, including balibase, homstrad, prefab and sab-mark, and show that it significantly outperforms mafft and probcons, which are among the best multiple alignment algorithms that do not utilize additional information, and spem, which is among the best multiple alignment algorithms that utilize additional hits from database search. the improvement in accuracy over spem can be as much as 5 to 10% when aligning divergent sequences. a software program that implements this approach (ispalign) is at http://faculty.cs.tamu.edu/shsze/ispalign.
an algorithm to enumerate all sorting reversals. the problem of estimating evolutionary distance from differences in gene order has been distilled to the problem of finding the reversal distance between two signed permutations. during the last decade, much progress was made both in computing reversal distance and in finding a minimum sequence of sorting reversals. for most problem instances, however, many minimum sequences of sorting reversals exist, and obtaining the complete set can be useful in exploring the space of genome rearrangements (e.g., in pursuit of solutions to higher-level problems). the problem of finding all minimum sequences of sorting reversals reduces easily to the problem of finding all sorting reversals of one permutation with respect to another. we derive an efficient algorithm to solve this latter problem, and present experimental results indicating that our algorithm offers a dramatic improvement over the best known alternative. it should be noted that in asymptotic terms the new algorithm does not represent a significant improvement: it requires o(n3) time (where n is the permutation size), while the problem can now be solved trivially in &thgr;(n3) time.
combining phylogenetic and hidden markov models in biosequence analysis. a few models have appeared in recent years that consider not only the way substitutions occur through evolutionary history at each site of a genome, but also the way the process changes from one site to the next. these models combine phylogenetic models of molecular evolution, which apply to individual sites, and hidden markov models, which allow for changes from site to site. besides improving the realism of ordinary phylogenetic models, they are potentially very powerful tools for inference and prediction---for gene finding, for example, or prediction of secondary structure. in this paper, we review progress on combined phylogenetic and hidden markov models and present some extensions to previous work. our main result is a simple and efficient method for accommodating higher-order states in the hmm, which allows for context-sensitive models of substitution---that is, models that consider the effects of neighboring bases on the pattern of substitution. we present experimental results indicating that higher-order states, autocorrelated rates, and multiple functional categories all lead to significant improvements in the fit of a combined phylogenetic and hidden markov model, with the effect of higher-order states being particularly pronounced.
computational identification of evolutionarily conserved exons. phylogenetic hidden markov models (phylo-hmms) have recently been proposed as a means for addressing a multi-species version of the ab initio gene prediction problem. these models allow sequence divergence, a phylogeny, patterns of substitution, and base composition all to be considered simultaneously, in a single unified probabilistic model. here, we apply phylo-hmms to a restricted version of the gene prediction problem in which individual exons are sought that are evolutionarily conserved across a diverse set of species. we discuss two new methods for improving prediction performance: (1) the use of context-dependent phylogenetic models, which capture phenomena such as a strong cpg effect in noncoding regions and a preference for synonymous rather than nonsynonymous substitutions in coding regions; and (2) a novel strategy for incorporating insertions and deletion (indels) into the state-transition structure of the model, which captures the different characteristic patterns of alignment gaps in coding and noncoding regions. we also discuss the technique, previously used in pairwise gene predictors, of explicitly modeling conserved noncoding sequence to help reduce false positive predictions. these methods have been incorporated into an exon prediction program called exoniphy, and tested with two large data sets. experimental results indicate that all three methods produce significant improvements in prediction performance. in combination, they lead to prediction accuracy comparable to that of some of the best available gene predictors, despite several limitations of our current models.
designing multiple simultaneous seeds for dna similarity search. the challenge of similarity search in massive dna sequence databases has inspired major changes in blast-style alignment tools, which accelerate search by inspecting only pairs of sequences sharing a common short "seed," or pattern of matching residues. some of these changes raise the possibility of improving search performance by probing sequence pairs with several distinct seeds, any one of which is sufficient for a seed match. however, designing a set of seeds to maximize their combined sensitivity to biologically meaningful sequence alignments is computationally difficult, even given recent advances [16, 6] in designing single seeds.this work describes algorithmic improvements to seed design that address the problem of designing a set of n seeds to be used simultaneously. we give a new local search method to optimize the sensitivity of seed sets. the method relies on efficient incremental computation of the probability that an alignment contains a match to a seed π, given that it has already failed to match any of the seeds in a set π. we demonstrate experimentally that multi-seed designs, even with relatively few seeds, can be significantly more sensitive than even optimized single-seed designs.
ab initio whole genome shotgun assembly with mated short reads. next generation sequencing (ngs) technologies are capable of reading millions of short dna sequences both quickly and cheaply. while these technologies are already being used for resequencing individuals once a reference genome exists, it has not been shown if it is possible to use them for ab initio genome assembly. in this paper, we give a novel network flow-based algorithm that, by taking advantage of the high coverage provided by ngs, accurately estimates the copy counts of repeats in a genome. we also give a second algorithm that combines the predicted copy-counts with mate-pair data in order to assemble the reads into contigs. we run our algorithms on simulated read data from e. coli and predict copy-counts with extremely high accuracy, while assembling long contigs.
using a mixture of probabilistic decision trees for direct prediction of protein function. we study the direct relationship between basic protein properties and their function. our goal is to develop a new tool for functional prediction that can be used to complement and support other techniques based on sequence or structure information. in order to define this new measure of similarity between proteins we collected a set of 453 features and properties that characterize proteins and are believed to be correlated and related to structural and functional aspects of proteins. among these properties are the composition and fraction of different groups of amino acids, predicted secondary structure content, molecular weight, average hydrophobicity, isoelectric point and others, as well as a set of properties that are extracted from database records of known protein sequences, such as subcellular location, tissue specificity, and others.we introduce the mixture model of probabilistic decision trees to learn the set of potentially complex relationships between features and function. to study these correlations, trees are created and tested on the pfam sequence-based classification of proteins and the ec classification of enzyme families. the model is very effective in learning highly diverged protein families or families that are not defined based on sequence. the resulting tree structure indicates the properties that are strongly correlated with structural and functional aspects of protein families, and can be used to suggest a concise definition of a protein family.
modeling transcription programs: inferring binding site activity and dose-response model optimization. the modeling of transcription regulation programs is a major focus of today's biology. the challenge is to utilize diverse high-throughput data (gene expression, promoter binding site localization assays, protein expression) in order to infer the mechanistic models of transcription control. we propose a new model which integrates transcription factor-gene affinities, protein abundance and gene expression levels. transcription factor binding site activity is represented by a dose-affinity-response function, and regulation is assumed to be a combinatorial function of the activities of the binding sites in the gene's promoter sites.we develop algorithms that infer the model given complete data and give a fast polynomial time algorithm under reasonable assumptions. we also show how to assess initial values of missing data (notably protein abundance) using a novel framework for active motif detection, which may be of independent interest. we test the various components of the framework on gene expression data related to carbohydrate metabolism in yeast. the results demonstrate the high specificity and sensitivity of the approach and its advantages over extant motif activity detection methods. we are also able to predict new active motifs in the galactose pathway.a key feature of our method is the global approach to transcription factor activity and to the relation between this activity and promoter signals. we use dozens of genes, with many different promoter signals and expression levels in order to draw conclusions on the function of a single transcription factor. this provides us the robustness necessary in order to overcome the considerable level of noise in the data.
using motion planning to study rna folding kinetics. we propose a novel, motion planning based approach to approximately map the energy landscape of an rna molecule. our method is based on the successful probabilistic roadmap motion planners that we have previously successfully applied to protein folding. the key advantage of our method is that it provides a sparse map that captures the main features of the landscape and which can be analyzed to compute folding kinetics. in this paper, we provide evidence that this approach is also well suited to rna. we compute population kinetics and transition rates on our roadmaps using the master equation for a few moderately sized rna and show that our results compare favorably with results of other existing methods.
zinc finger gene clusters and tandem gene duplication. zinc finger genes in mammalian genomes are frequently found to occur in clusters with cluster members appearing in a tandem array on the chromosome. it has been suggested that in situ gene duplication events are primarily responsible for the evolution of such clusters. the problem of inferring the series of duplication events responsible for producing clustered families is different from the standard phylogeny problem. in this paper we study this inference problem using a graph called duplication model that captures the series of duplication events while taking into account the observed order of the genes on the chromosome. we provide algorithms to reconstruct a duplication model for a given data set. we use our method to hypothesise the series of duplication events that may have produced the znf45 family that appears on human chromosome 19.
pdb_isl: an intermediate sequence library for protein structure assignment. for large scale structural assignment to sequences, as in computational structural genomics, a fast yet sensitive homology search procedure is essential. a new approach using intermediate sequences was tested as a shortcut to iterative multiple sequence search methods such as psi-blast and hidden markov models. a library containing potential intermediate sequences for proteins of known structure (pdb_isl) was constructed. the sequences in the library were collected from a large sequence database using the sequences of the domains of proteins of known structure as the query sequences and the program psi-blast. sequences of proteins of unknown structure can be matched to distantly related proteins of known structure by using any pairwise sequence comparison methods to find homologues in pdb_isl. searches of pdb_isl were calibrated, and the number of correct matches found at a given error rate was the same as that found by psi_blast. the advantage of this library is that it uses pairwise sequence comparison methods, such as fasta or blast2, and can, therefore, be searched easily and, in many cases, much more quickly than an iterative multiple sequence comparison method. the procedure is roughly twenty times faster than psi-blast for small genomes and several hundred times for large genomes such as c. elegans. sequences can be submitted to the pdb_isl servers at http://stash.mrc-lmb.cam.ac.uk/pdb_isl/ ftp://ftp.ebi.ac.uk/pub/databases/pdb_isl/
a dimensionality reduction approach to modeling protein flexibility. proteins are involved either directly or indirectly in all biological processes in living organisms. it is now widely accepted that conformational changes of proteins can critically affect their ability to bind other molecules and that any progress in modeling protein motion and flexibility will contribute to the understanding of key biological functions. however, modeling protein flexibility has proven a very difficult task. experimental laboratory methods such as x-ray crystallography produce rather few structures, while computational methods such as molecular dynamics are too slow for routine use with large systems. a medium sized protein typically has a few thousands of degrees of freedom. this paper shows how to obtain a reduced basis representation of protein flexibility. we use the principal component analysis method, a dimensionality reduction technique, to transform the original high dimensional representation of protein motion into a lower dimensional representation that captures the dominant modes of motions of the protein. although there is inevitably some loss in accuracy, we show that we can obtain conformations that have been observed in laboratory experiments, starting from different initial conformations and working in a drastically reduced search space.
a gibbs sampling method to detect over-represented motifs in the upstream regions of co-expressed genes. microarray experiments can reveal useful information on the transcriptional regulation. we try to find regulatory elements in the region upstream of translation start of coexpressed genes. here we present a modification to the original gibbs sampling algorithm [12]. we introduce a probability distribution to estimate the number of copies of the motif in a sequence. the second modification is the incorporation of a higher-order background model. we have successfully tested our algorithm on several data sets. first we show results on two selected data set: sequences from plants containing the g-box motif and the upstream sequences from bacterial genes regulated by o2-responsive protein fnr. in both cases the motif sampler is able to find the expected motifs. finally, the sampler is tested on 4 clusters of coexpressed genes from a wounding experiment in arabidopsis thaliana. we find several putative motifs that are related to the pathways involved in the plant defense mechanism.
toward a proteome atlas for c. elegans. the availability of complete genome sequences suggests new approaches for biological research to complement conventional genetics and biochemistry. in this context, the goals of this laboratory are to generate a comprehensive protein-protein interaction, or interactome, map for c. elegans and develop new concepts to integrate this map with other functions such as expression profiles (transcriptome), global phenotypic analysis (phenome), localization of expression projects localizome, etc... the resulting atlas of integrated maps should be valuable for the development of a systems biology approach to the study of development.
a more efficient approximation scheme for tree alignment. we present a new polynomial time approximation scheme (ptas) for tree alignment, which is an important variant of multiple sequence alignment. as in the existing ptass in the literature, the basic approach of our algorithm is to partition the given tree into overlapping components of a constant size and then apply local optimization on each such component. but the new algorithm uses a clever partitioning strategy and achieves a better efficiency for the same performance ratio. for example, to achieve approximation ratios 1.6 and 1.5, the best existing ptas has to spend time o(kdn5) and o(kdn9), respectively, where n is the length of each leaf sequence and d,k are the depth and number of leaves of the tree, while the new ptas only has to spend time o(kdn4) and o(kdn5). moreover, the performance of the ptas is more sensitive to the size of the components, which basically determines the running time, and we obtain an improved approximation ratio for each size. some experiments of the algorithm on simulated and real data are also given.
faster genome annotation of non-coding rna families without loss of accuracy. non-coding rnas (ncrnas) are functional rna molecules that do not code for proteins. covariance models (cms) are a useful statistical tool to find new members of an ncrna gene family in a large genome database, using both sequence and, importantly, rna secondary structure information. unfortunately, cm searches are slow. this paper shows how to make cms faster while provably sacrificing none of their accuracy. specifically, based on the cm, our software builds a profile hidden markov model (hmm), which filters the genome database. this hmm is a gorous filter i.e., its filtering eliminates only sequences that provably could not be annotated as homologs. the cm is run only on what remains. optimizing the hmm for filtering involves minimizing an exponential objective function with linear inequality constraints. for most known ncrna families, this allows an 8-gigabase database to be scanned in 2-20 days instead of years, and yields new family members missed by other techniques to improve cm speed.
finding approximate tandem repeats in genomic sequences. an efficient algorithm is presented for detecting approximate tandem repeats in genomic sequences. the algorithm is based on a flexible statistical model which allows a wide range of definitions of approximate tandem repeats. the ideas and methods underlying the algorithm are described and examined and its effectiveness on genomic data is demonstrated.
systems biology and malaria. malaria is the cause of significant global morbidity and mortality with 300-500 million cases annually. despite its disease burden relatively little is known about the molecular biology of the pathogen that causes malaria. for example, the completion of the genome sequence of plasmodium falciparum, the species responsible for the most severe form of human malaria revealed that only 35% of the genes code for proteins with an identifiable function. in addition, little is known about how transcription and translation are regulated. the absence of routine genetic tools for studying plasmodium parasites suggests that these numbers are unlikely to change quickly if conventional, serial, biological methods are used to study the parasite. we are using high-density oligonucleotide arrays and informatic methods to study the genome of the malaria parasite with the goals of understanding how expression is regulated, functionally cataloging the genome, discovering allelic variation and identifying new therapeutic targets. we have shown that genes with highly correlated levels and temporal patterns of expression are often involved in similar functions or cellular processes suggesting that expression profiling can be used to rapidly predict function. in addition we find that there is good correlation between protein levels and transcript levels, suggesting that regulation of expression occurs transcriptionally. analysis of whole-genome transcription patterns reveals that the chromosome is organized into regions that are transcriptionally active and transcriptionally silent in the intraerythrocytic stage of the parasite's lifecycle. thus, both the timing and the relative level of transcription in the parasite is organized into position-dependent domains suggesting that transcription may be regulated at least partially at the level of chromatin structure.
protein structure determination using protein threading and sparse nmr data (extended abstract). it is well known that the nmr method for protein structure determination applies to small proteins and that its effectiveness decreases very rapidly as the molecular weight increases beyond about 30 kd. we have recently developed a method for protein structure determination that can fully utilize partial nmr data as calculation constraints. the core of the method is a threading algorithm that guarantees to find a globally optimal alignment between a query sequence and a template structure, under distance constraints specified by nmr/noe data. our preliminary tests have demonstrated that a small number of nmr/noe distance restraints can significantly improve threading performance in both fold recognition and threading-alignment accuracy, and can possibly extend threading's scope of applicability from structural homologs to structural analogs. an accurate backbone structure generated by nmr-constrained threading can then provide a significant amount of structural information, equivalent to that provided by the nmr method with many nmr/noe restraints; and hence can greatly reduce the amount of nmr data typically required for accurate structure determination. our prelimenary study suggest that a small number of noe restraints may suffice to determine adequately the all-atom structure when those restraints are incorporated in a procedure combining threading, modeling of loops and sidechains, and molecular dynamics simulation. potentially, this new technique can expand nmr's capability to larger proteins.
physical network models and multi-source data integration. we develop a new framework for inferring models of transcriptional regulation. the models in this approach, which we call physical models, are constructed on the basis of verifiable molecular attributes of the underlying biological system. the attributes include, for example, the existence of protein-protein and protein-dna interactions in gene regulatory processes, the directionality of signal transduction in protein-protein interactions, as well as the signs of the immediate effects of these interactions (e.g., whether an upstream gen activates or represses the downstream genes). each attribute is included as a variable in the model, and the variables define a collection of annotated random graphs. possible configurations of these variables (realizations of the underlying biological system) are constrained by the available data sources. some of the data sources such as factor-binding data (location data) involve measurements that are directly tied to the variables in the model. other sources such as gene knock-outs are functional in nature and provide only indirect evidence about the (physical) variables. we associate each knock-out effect in the deletion mutant data with a set of causal paths (molecular cascades) that could in principle explain the effect, resulting in aggregate constraints about the physical variables in the model. the most likely setting of all the variables is found by the max-product algorithm. by testing our approach on datasets related to the pheromone response pathway in s. cerevisiae, we demonstrate that the resulting transcriptional models are consistent with previous studies about the pathway. moreover, we show that the approach is capable of predicting gene knock-out effects with high degree of accuracy in a cross-validation setting. the method also implicates likely molecular cascades responsible for each observed knock-out effect. the inference results are robust against variations in the model parameters. we can extend the approach to include other data sources such as time course expression profiles. we also discuss coordinated regulation and the use of automated experiment design
maximum entropy modeling of short sequence motifs with applications to rna splicing signals. we propose a framework for modeling sequence motifs based on the maximum entropy principle (mep).we recommend approximating short sequence motif distributions with the maximum entropy distribution (med) consistent with low-order marginal constraints estimated from available data, which may include dependencies between non-adjacent as well as adjacent positions.finally, we suggest mechanistically-motivated ways of comparing models.
a unified sequence-structure classification of protein sequences: combining sequence and structure in a map of the protein space. we analyze all known protein sequences in search for a global map of protein space that is consistent in terms of both sequence and structure. our goal is to define clusters of homologous protein domains, beyond those detected by sequence-based methods alone, and then to build a three-dimensional (3d) model for each of the sequences that are homologous to sequences of known 3d structure. this analysis uses both sequence and structure based metrics in the analysis of all protein sequences in a non-redundant (nr) database, comprising all major sequence databases. the analysis starts from the sequences of the scop database domains, which have known three-dimensional structures these sequences are clustered first into families based on sequence similarity alone, without incorporating any information from the scop classification. each sequence-based family is represented by a profile, and this profile is used to search the nr database, using psi-blast. since psi-blast can lead to false similarities, several different indices of validity are used to control the procedure each of the detected sequences is marked and a profile is built for the whole cluster of similar sequences. a 3d model is then built for each sequence in the cluster using an alignment made using the profile as well as the known structures of the scop representatives in the cluster clusters based on scop domains are called type-i clusters in all we find 1421 type-i clusters with total of 168,431 sequences (44.5% of our nr database) after all members of type-i clusters have been marked, we analyze the remaining sequences. the psi-blast procedure is applied repeatedly, each time with a different query, to search what is left over from the previous run. this give type-ii clusters, which may overlap. type-i and type-ii clusters are then grouped using higher level measures of similarity. those pairs of clusters that contain the same common protein (significant overlap in membership), are marked first. the pairs of clusters are then compared using either a structure metric (when 3d structures are known) or a novel sequence profile metric, and clustered into superfamilies and &ldquo;fold&rdquo; families. this analysis avoids the limitation of classifications that are based just on sequence comparison, and allows us to construct a 3d model for a substantial portion of the sequences in the nr database.
a simple iterative approach to parameter optimization. various bioinformatics problems require optimizing several different properties simultaneously. for example, in the protein threading problem, a linear scoring function combines the values for different properties of possible sequence-to-structure alignments into a single score to allow for unambigous optimization. in this context, an essential question is how each property should be weighted. as the native structures are known for some sequences, the implied partial ordering on optimal alignments may be used to adjust the weights. to resolve the arising interdependence of weights and computed solutions, we propose a novel approach: iterating the computation of solutions (here: threading alignments) given the weights and the estimation of optimal weights of the scoring function given these solutions via a systematic calibration method. we show that this procedure converges to structurally meaningful weights, that also lead to significantly improved performance on comprehensive test data sets as measured in different ways. the latter indicates that the performance of threading can be improved in general.
dynamic programming algorithms for haplotype block partitioning: applications to human chromosome 21 haplotype data. recent studies have shown that the human genome has a haplotype block structure such that it can be divided into discrete blocks of limited haplotype diversity. patil et al. [6] and zhang et al. [12] developed algorithms to partition haplotypes into blocks with minimum number of tag snps for the entire chromosome. however, it is not clear how to partition haplotypes into blocks with restricted number of snps when only limited resources are available. in this paper, we first formulated this problem as finding a block partition with a fixed number of tag snps that can cover the maximal percentage of a genome. then we solved it by two dynamic programming algorithms, which are fairly flexible to take into account the knowledge of functional polymorphism. we applied our algorithms to the published snp data of human chromosome 21 combining with the functional information of these snps and demonstrated the effectiveness of them. statistical investigation of the relationship between the starting points of a block partition and the coding and non-coding regions illuminated that the snps at these starting points are not significantly enriched in coding regions. we also developed an efficient algorithm to find all possible long local maximal haplotypes across a subset of samples. after applying this algorithm to the human chromosome 21 haplotype data, we found that samples with long local haplotypes are not necessarily globally similar.
finding short dna motifs using permuted markov models. many short dna motifs such as transcription factor binding sites (tfbs) and splice sites exhibit strong local as well as non-local dependence. we introduce permuted variable length markov models (pvlmm) which could capture the potentially important dependencies among positions, and apply them to the problem of detecting splice and tfb sites. they have been satisfactory from the viewpoint of prediction performance, and also give ready biological interpretations of the sequence dependence observed. the issue of model selection is also studied.
microarrays: how many do you need? we estimate the number of microarrays that is required in order to gain reliable results from a common type of study: the pairwise comparison of different classes of samples. current knowlegde seems to suffice for the construction of models that are realistic with respect to searches for individual differentially expressed genes. such models allow to investigate the dependence of the required number of samples on the relevant parameters: the biological variability of the samples within each class; the fold changes in expression; the detection sensitivity of the microarrays; and the acceptable error rates of the results. we supply experimentalists with general conclusions as well as a freely accessible java applet at http://cartan.gmd.de/~zien/classsize/ for fine tuning simulations to their particular actualities. since the situation can be assumed to be very similar for large scale proteomics and metabolomics studies, our methods and results might also apply there.
support vector training of protein alignment models. sequence to structure alignment is an important step in homology modeling of protein structures. incorporation of features like secondary structure, solvent accessibility, or evolutionary information improve sequence to structure alignment accuracy, but conventional generative estimation techniques for alignment models impose independence assumptions that make these features difficult to include in a principled way. in this paper, we overcome this problem using a support vector machine (svm) method that provides a well-founded way of estimating complex alignment models with hundred-thousands of parameters. furthermore, we show that the method can be trained using a variety of loss functions. in a rigorous empirical evaluation, the svm algorithm outperforms the generative alignment method ssaln, a highly accurate generative alignment model that incorporates structural information. the alignment model learned by the svm aligns 47% of the residues correctly and aligns over 70% of the residues within a shift of 4 positions.
shift-invariant adaptive double threading: learning mhc ii - peptide binding. specificity of mhc binding to short peptide fragments from cellular as well as pathogens' proteins has been found to correlate with disease outcome and pathogen or cancer evolution. the large variation in mhc class ii epitope length has complicated training of predictors for binding affinities compared to mhc class i. in this paper, we treat the relative position of the peptide inside the mhc protein as a hidden variable, and model the ensemble of different binding configurations. the training procedure iterates the predictions with re estimation of the parameters of a binding groove model. we show that the model generalizes to new mhc class ii alleles, which were not a part of the training set. to the best of our knowledge, our technique outperforms all previous approaches to mhc ii epitope prediction. we demonstrate how our model can be used to explain previously documented associations between mhc ii alleles and disease.
improved ranking functions for protein and modification-site identifications. there are a number of computational tools for assigning identifications to peptide tandem mass spectra, but many fewer tools for the crucial next step of integrating spectral identifications into higher-level identifications, such as proteins or modification sites. here we describe a new program called combyne for scoring and ranking higher-level identifications. we compare combyne to existing algorithms on several complex biological samples, including a sample of mouse blood plasma spiked with known concentrations of human proteins. a web interface to our software is at http://bio.parc.xerox.com.
qnet: a tool for querying protein interaction networks. molecular interaction databases can be used to study the evolution of molecular pathways across species. querying such pathways is a challenging computational problem, and recent efforts have been limited to simple queries (paths), or simple networks (forests). in this paper, we significantly extend the class of pathways that can be efficiently queried to the case of trees, and graphs of bounded treewidth. our algorithm allows the identification of non-exact (homeomorphic) matches, exploiting the color coding technique of alon et al. we implement a tool for tree queries, called qnet, and test its retrieval properties in simulations and on real network data. we show that qnet searches queries with up to 9 proteins in seconds on current networks, and outperforms sequence-based searches.we also use qnet to perform the first large scale cross-species comparison of protein complexes, by querying known yeast complexes against a fly protein interaction network. this comparison points to strong conservation between the two species, and underscores the importance of our tool in mining protein interaction networks.
tools for simulating and analyzing rna folding kinetics. it has recently been found that some rna functions are determined by the actual folding kinetics and not just the rna's nucleotide sequence or its native structure. we present new computational tools for simulating and analyzing rna folding kinetic metrics such as population kinetics, folding rates, and the folding of particular subsequences. our method first builds an approximate representation (called a map) of the rna's folding energy landscape, and then uses specialized analysis techniques to extract folding kinetics from the map. we provide a new sampling strategy called probabilistic boltzmann sampling (pbs) that enables us to approximate the folding landscape with much smaller maps, typically by several orders of magnitude. we also describe a new analysis technique, map-based monte carlo (mmc) simulation, to stochastically extract folding pathways from the map. we demonstrate that our technique can be applied to large rna (e.g., 200+ nucleotides), where representing the full landscape is infeasible, and that our tools provide results comparable to other simulation methods that work on complete energy landscapes. we present results showing that our approach computes the same relative functional rates as seen in experiments for the relative plasmid replication rates of cole1 rnaii and its mutants, and for the relative gene expression rates of ms2 phage rna and its mutants.
production-passage-time approximation: a new approximation method to accelerate the simulation process of enzymatic reactions. given the substantial computational requirements of stochastic simulation, approximation is essential for efficient analysis of any realistic biochemical system. this paper introduces a new approximation method to reduce the computational cost of stochastic simulations of an enzymatic reaction scheme which in biochemical systems often includes rapidly changing fast reactions with enzyme and enzyme-substrate complex molecules present in very small counts. our new method removes the substrate dissociation reaction by approximating the passage time of the formation of each enzyme-substrate complex molecule which is destined to a production reaction. this approach skips the firings of unimportant yet expensive reaction events, resulting in a substantial acceleration in the stochastic simulations of enzymatic reactions. additionally, since all the parameters used in our new approach can be derived by the michaelis-menten parameters which can actually be measured from experimental data, applications of this approximation can be practical even without having full knowledge of the underlying enzymatic reaction. furthermore, since our approach does not require a customized simulation procedure for enzymatic reactions, it allows biochemical systems that include such reactions to still take advantage of standard stochastic simulation tools. here, we apply this new method to various enzymatic reaction systems, resulting in a speedup of orders of magnitude in temporal behavior analysis without any significant loss in accuracy.
accounting for non-genetic factors improves the power of eqtl studies. the recent availability of large scale data sets profiling single nucleotide polymorphisms (snps) and gene expression across different human populations, has directed much attention towards discovering patterns of genetic variation and their association with gene regulation. the influence of environmental, developmental and other factors on gene expression can obscure such associations. we present a model that explicitly accounts for non-genetic factors so as to improve significantly the power of an expression quantitative trait loci (eqtl) study. our method also exploits the inherent block structure of haplotype data to further enhance its sensitivity. on data from the hapmap project, we find more than three times as many significant associations than a standard eqtl method.
baycis: a bayesian hierarchical hmm for cis-regulatory module decoding in metazoan genomes. the transcriptional regulatory sequences in metazoan genomes often consist of multiple cis-regulatory modules (crms). each crm contains locally enriched occurrences of binding sites (motifs) for a certain array of regulatory proteins, capable of integrating, amplifying or attenuating multiple regulatory signals via combinatorial interaction with these proteins. the architecture of crm organizations is reminiscent of the grammatical rules underlying a natural language, and presents a particular challenge to computational motif and crm identification in metazoan genomes. in this paper, we present baycis, a bayesian hierarchical hmm that attempts to capture the stochastic syntactic rules of crm organization. under the baycis model, all candidate sites are evaluated based on a posterior probability measure that takes into consideration their similarity to known bss, their contrasts against local genomic context, their first-order dependencies on upstream sequence elements, as well as priors reflecting general knowledge of crm structure. we compare our approach to five existing methods for the discovery of crms, and demonstrate competitive or superior prediction results evaluated against experimentally based annotations on a comprehensive selection of drosophila regulatory regions. the software, database and supplementary materials will be available at http://www.sailing.cs. cmu.edu/baycis.
bubbles: alternative splicing events of arbitrary dimension in splicing graphs. eukaryotic splicing structures are known to involve a high degree of alternative forms derived from a premature transcript by alternative splicing (as). with the advent of new sequencing technologies, evidence for new splice forms becomes more and more easily available-- bit by bit revealing that the true splicing diversity of "as events" often comprises more than two alternatives and therefore cannot be sufficiently described by pairwise comparisons as conducted in analyzes hitherto. further challenges emerge from the richness of data (millions of transcripts) and artifacts introduced during the technical process of obtaining transcript sequences (noise)--especially when dealing with singleread sequences known as expressed sequence tags (ests). we describe a novel method to efficiently predict as events in different resolutions (i.e., dimensions) from transcript annotations that allows for combination of fragmented est data with full-length cdnas and can cope with large datasets containing noise. applying this method to estimate the real complexity of alternative splicing, we found in human thousands of novel as events that either have been disregarded or mischaracterized in earlier works. in fact, the majority of exons that are observed as "mutually exclusive" in pairwise comparisons truly involve at least one other alternative splice form that disagrees with their mutual exclusion. we identified four major classes that contain such "optional" neighboring exons and show that they clearly differ from each other in characteristics, especially in the length distribution of the middle intron.
detecting disease-specific dysregulated pathways via analysis of clinical expression profiles. we present a method for identifying connected gene subnetworks significantly enriched for genes that are dysregulated in specimens of a disease. these subnetworks provide a signature of the disease potentially useful for diagnosis, pinpoint possible pathways affected by the disease, and suggest targets for drug intervention. our method uses microarray gene expression profiles derived in clinical case-control studies to identify genes significantly dysregulated in disease specimens, combined with protein interaction data to identify connected sets of genes. our core algorithm searches for minimal connected subnetworks in which the number of dysregulated genes in each diseased sample exceeds a given threshold. we have applied the method in a study of huntington's disease caudate nucleus expression profiles and in a meta-analysis of breast cancer studies. in both cases the results were statistically significant and appeared to home in on compact pathways enriched with hallmarks of the diseases.
the statistical power of phylogenetic motif models. one component of the genomic program controlling the transcriptional regulation of genes are the locations and arrangement of transcription factors bound to the promoter and enhancer regions of a gene. because the genomic locations of the functional binding sites of most transcription factors is not yet known, predicting them is of great importance. unfortunately, it is well known that the low specificity of the binding of transcription factors to dna makes such prediction, using position-specific probability matrices (motifs) alone, subject to huge numbers of false positives. one approach to alleviating this problem has been to use phylogenetic "shadowing" or "footprinting" to remove unconserved regions of the genome from consideration. another approach has been to combine a phylogenetic model and the site-specificity model into a single, predictive model of conserved binding sites. both of these approaches are based on alignments of orthologous genomic regions from two or more species. in this work, we use a simplified, theoretical model to study the statistical power of the later approach to the prediction of features such as transcription factor binding sites. we investigate the question of the number of genomes required at varying evolutionary distances to achieve specified levels of accuracy (false positive and false negative prediction rates). we show that this depends strongly on the information content of the position-specific probability matrix and on the evolutionary model. we explore the effects of modifying the structure of the phylogenetic model, and conclude that placing the target genome at the root of the tree has a negligible effect on the power predicted by the model. hence, as it is much easier to calculate, we can use this as an approximation to phylogenetic motif scanning using real trees. finally we perform an empirical study and demonstrate that the performance of current phylogenetic motif scanning programs is far from the theoretical limit of their power, leaving ample room for improvement.
framework for identifying common aberrations in dna copy number data. high-resolution array comparative genomic hybridization (acgh) provides exon-level mapping of dna aberrations in cells or tissues. such aberrations are central to carcinogenesis and, in many cases, central to targeted therapy of the cancers. some of the aberrations are sporadic, one-of-a-kind changes in particular tumor samples; others occur frequently and reflect common themes in cancer biology that have interpretable, causal ramifications. hence, the difficult task of identifying and mapping common, overlapping genomic aberrations (including amplifications and deletions) across a sample set is an important one; it can provide insight for the discovery of oncogenes, tumor suppressors, and the mechanisms by which they drive cancer development. in this paper we present an efficient computational framework for identification and statistical characterization of genomic aberrations that are common to multiple cancer samples in a cgh data set. we present and compare three different algorithmic approaches within the context of that framework. finally, we apply our methods to two datasets - a collection of 20 breast cancer samples and a panel of 60 diverse human tumor cell lines (the nci-60). those analyses identified both known and novel common aberrations containing cancer-related genes. the potential impact of the analytical methods is well demonstrated by new insights into the patterns of deletion of cdkn2a (p16), a tumor suppressor gene crucial for the genesis of many types of cancer.
reconstructing the topology of protein complexes. recent advances in high-throughput experimental techniques have enabled the production of a wealth of protein interaction data, rich in both quantity and variety. while the sheer quantity and variety of data present special difficulties for modeling, they also present unique opportunities for gaining insight into protein behavior by leveraging multiple perspectives. recent work on the modularity of protein interactions has revealed that reasoning about protein interactions at the level of domain interactions can be quite useful. we present proctor, a learning algorithm for reconstructing the internal topology of protein complexes by reasoning at the domain level about both direct protein interaction data (y2h) and protein co-complex data (ap-ms). while other methods have attempted to use data from both these kinds of assays, they usually require that cocomplex data be transformed into pairwise interaction data under a spoke or clique model, a transformation we do not require. we apply proctor to data from eight highthroughput datasets, encompassing 5,925 proteins, essentially all of the yeast proteome. first we show that proctor outperforms other algorithms for predicting domain-domain and protein-protein interactions from y2h and ap-ms data. then we show that our algorithm can reconstruct the internal topology of ap-ms purifications, revealing known complexes like arp2/3 and rna polymerase ii, as well as suggesting new complexes along with their corresponding topologies.
computation of median gene clusters. whole genome comparison based on gene order has become a popular approach in comparative genomics. an important task in this field is the detection of gene clusters, i.e. sets of genes that occur colocalized in several genomes. for most applications it is preferable to extend this definition to allow for small deviations in the gene content of the cluster occurrences. however, relaxing the equality constraint increases the computational complexity of gene cluster detection drastically. existing approaches deal with this problem by using simplifying constraints on the cluster definition and/or allowing only pairwise genome comparison. in this paper we introduce a cluster concept named median gene clusters that improves over existing models and present efficient algorithms for their computation that allow for the detection of approximate gene clusters in multiple genomes.
an efficient method for dynamic analysis of gene regulatory networks and gene perturbation experiments. with the increasing availability of experimental data on gene-gene and protein-protein interactions, modeling of gene regulatory networks has gained a special attention lately. to have a better understanding of these networks it is necessary to capture their dynamical properties, by computing its steady states. various methods have been proposed to compute steady states but almost all of them suffer from the state space explosion problem with the increasing size of the networks. hence it becomes difficult to model even moderate sized networks using these techniques. in this paper, we present a new representation of gene regulatory networks, which facilitates the steady state computation of networks as large as 1200 nodes and 5000 edges. we benchmarked and validated our algorithm on the t helper model from [8] and performed in silico knock out experiments: showing both a reduction in computation time and correct steady state identification.
network motif discovery using subgraph enumeration and symmetry-breaking. the study of biological networks and network motifs can yield significant new insights into systems biology. previous methods of discovering network motifs - network-centric subgraph enumeration and sampling - have been limited to motifs of 6 to 8 nodes, revealing only the smallest network components. new methods are necessary to identify larger network sub-structures and functional motifs. here we present a novel algorithm for discovering large network motifs that achieves these goals, based on a novel symmetry-breaking technique, which eliminates repeated isomorphism testing, leading to an exponential speed-up over previous methods. this technique is made possible by reversing the traditional network-based search at the heart of the algorithm to a motif-based search, which also eliminates the need to store all motifs of a given size and enables parallelization and scaling. additionally, our method enables us to study the clustering properties of discovered motifs, revealing even larger network elements. we apply this algorithm to the protein-protein interaction network and transcription regulatory network of s. cerevisiae, and discover several large network motifs, which were previously inaccessible to existing methods, including a 29-node cluster of 15-node motifs corresponding to the key transcription machinery of s. cerevisiae.
comparative analysis of spatial patterns of gene expression in imaginal discs. determining the precise spatial extent of expression of genes across different tissues, along with knowledge of the biochemical function of the genes is critical for understanding the roles of various genes in the development of metazoan organisms. to address this problem, we have developed high-throughput methods for generating images of gene expression in drosophila melanogaster imaginal discs and for the automated analysis of these images. our method automatically learns tissue shapes from a small number of manually segmented training examples and automatically aligns, extracts and scores new images, which are analyzed to generate gene expression maps for each gene. we have developed a reverse lookup procedure that enables us to identify genes that have spatial expression patterns most similar to a given gene of interest. our methods enable us to cluster both the genes and the pixels that of the maps, thereby identifying sets of genes that have similar patterns, and regions of the tissues of interest that have similar gene expression profiles across a large number of genes.
beyond galled trees - decomposition and computation of galled networks. reticulate networks are a type of phylogenetic network that are used to represent reticulate evolution involving hybridization, horizontal gene transfer or recombination. the simplest form of these networks are galled trees, in which all reticulations are independent of each other. this paper introduces a more general class of reticulate networks, that we call galled networks, in which reticulations are not necessarily independent, but may overlap in a tree-like manner. we prove a decomposition theorem for these networks that has important consequences for their computation, and present a fixed-parameter-tractable algorithm for computing such networks from trees or binary sequences. we provide a robust implementation of the algorithm and illustrate its use on two biological datasets, one based on a set of three gene-trees and the other based on a set of binary characters obtained from a restriction site map.
deterministic pharmacophore detection via multiple flexible alignment of drug-like molecules. we present a novel highly efficient method for the detection of a pharmacophore from a set of ligands/drugs that interact with a target receptor. a pharmacophore is a spatial arrangement of physicochemical features in a ligand that is responsible for the interaction with a specific receptor. in the absence of a known 3d receptor structure, a pharmacophore can be identified from a multiple structural alignment of the ligand molecules. the key advantages of the presented algorithm are: (a) its ability to multiply align flexible ligands in a deterministic manner, (b) its ability to focus on subsets of the input ligands, which may share a large common substructure, resulting in the detection of both outlier molecules and alternative binding modes, and (c) its computational efficiency, which allows to detect pharmacophores shared by a large number of molecules on a standard pc. the algorithm was extensively tested on a dataset of almost 80 ligands acting on 12 different receptors. the results, which were achieved using a standard default parameter set, were consistent with reference pharmacophores that were derived from the bound ligand-receptor complexes. the pharmacophores detected by the algorithm are expected to be a key component in the discovery of new leads by screening large drug-like molecule databases.
free energy estimates of all-atom protein structures using generalized belief propagation. we present a technique for approximating the free energy of protein structures using generalized belief propagation (gbp). the accuracy and utility of these estimates are then demonstrated in two different application domains. first, we show that the entropy component of our free energy estimates can be useful in distinguishing native protein structures from decoys -- structures with similar internal energy to that of the native structure, but otherwise incorrect. our method is able to correctly identify the native fold from among a set of decoys with 87.5% accuracy over a total of 48 different immunoglobin folds. the remaining 12.5% of native structures are ranked among the top 4 of all structures. second, we show that our estimates of δδg upon mutation upon mutation for three different data sets have linear correlations between 0.63-0.70 with experimental values and statistically significant p-values. together, these results suggests that gbp is an effective means for computing free energy in all-atom models of protein structures. gbp is also efficient, taking a few minutes to run on a typical sized protein, further suggesting that gbp may be an attractive alternative to more costly molecular dynamic simulations for some tasks.
a bayesian model that links microarray mrna measurements to mass spectrometry protein measurements. an important problem in biology is to understand correspondences between mrna microarray levels and mass spectrometry peptide counts. recently, a compendium of mrna expression levels and protein abundances were released for the entire genome of the laboratory mouse, mus musculus. the availability of these two data sets facilitate using machine learning methods to automatically infer plausible correspondences between the gene products. knowing these correspondences can be helpful either for predicting protein abundances from microarray data or as an independent source of information that can be used for learning richer models such as regulatory networks. we propose a probabilistic model that relates protein abundances to mrna expression levels. using cross-mapped data from the above-mentioned studies, we learn the model and then score the genes for their strength of relationship by performing probabilistic inference in the learned model. while we gave a simplified outline of our technique in a publication aimed at biologists (cell 2006), in this paper, we give a complete description of the bayesian model and the computational technique used to perform inference. in addition, we demonstrate that the bayesian technique achieves mappings with higher statistical significance, compared to standard linear regression and a maximum likelihood version of the proposed model.
peptide retention time prediction yields improved tandem mass spectrum identification for diverse chromatography conditions. most tandem mass spectrum identification algorithms use information only from the final spectrum, ignoring precursor information such as peptide retention time (rt). efforts to exploit peptide rt for peptide identification can be frustrated by its variability across liquid chromatography analyses. we show that peptide rt can be reliably predicted by training a support vector regressor on a single chromatography run. this dynamically trained model outperforms a published statically trained model of peptide rt across diverse chromatography conditions. in addition, the model can be used to filter peptide identifications that produce large discrepancies between observed and predicted rt. after filtering, estimated true positive peptide identifications increase by as much as 50% at a false discovery rate of 3%, with the largest increase for non-specific cleavage with elastase.
rb-finder: an improved distance-based sliding window method to detect recombination breakpoints. recombination detection is important before inferring phylogenetic relationships. this will eventually lead to a better understanding of pathogen evolution, more accurate genotyping and advancements in vaccine development. in this paper, we introduce rb-finder, a fast and accurate distance-based window method to detect recombination in a multiple sequence alignment. our method introduces a more informative distance measure and a novel weighting strategy to reduce the window size sensitivity problem and hence improve the accuracy of breakpoint detection. furthermore, our method is faster than existing phylogenybased methods since we do not need to construct and compare complex phylogenetic trees. when compared with the current best method pruned-pdm, we are about a few hundred times more efficient. experimental evaluation of rb-finder using synthetic and biological datasets showed that our method is more accurate than existing phylogeny-based methods. we also show how our method has potential use in other related applications such as genotyping.
network legos: building blocks of cellular wiring diagrams. publicly-available data sets provide detailed and large-scale information on multiple types of molecular interaction networks in a number of model organisms. these multi-modal universal networks capture a static view of cellular state. an important challenge in systems biology is obtaining a dynamic perspective on these networks by integrating them with gene expression measurements taken under multiple conditions. we present a top-down computational approach to identify building blocks of molecular interaction networks by (i) integrating gene expression measurements for a particular disease state (e.g., leukaemia) or experimental condition (e.g., treatment with growth serum) with molecular interactions to reveal an active network, which is the network of interactions active in the cell in that disease state or condition and (ii) systematically combining active networks computed for different experimental conditions using set-theoretic formulae to reveal network legos, which are modules of coherently interacting genes and gene products in the wiring diagram. we propose efficient methods to compute active networks, systematically mine candidate legos, assess the statistical significance of these candidates, arrange them in a directed acyclic graph (dag), and exploit the structure of the dag to identify true network legos. we describe methods to assess the stability of our computations to changes in the input and to recover active networks by composing network legos. we analyse two human datasets using our method. a comparison of three leukaemias demonstrates how a biologist can use our system to identify specific differences between these diseases. a larger-scale analysis of 13 distinct stresses illustrates our ability to compute the building blocks of the interaction networks activated in response to these stresses.
nucleosome occupancy information improves motif discovery. a complete understanding of transcriptional regulatory processes in the cell requires identification of transcription factor binding sites on a genomewide scale. unfortunately, these binding sites are typically short and degenerate, posing a significant statistical challenge: many more matches to known transcription factor binding sites occur in the genome than are actually functional. chromatin structure is known to play an important role in guiding transcription factors to those sites that are functional. in particular, it has been shown that active regulatory regions are usually depleted of nucleosomes, thereby enabling transcription factors to bind dna in those regions [1]. in this paper, we describe a novel algorithm which employs an informative prior over dna sequence positions based on a discriminative view of nucleosome occupancy; the nucleosome occupancy information comes from a recently published computational model [2]. when a gibbs sampling algorithm with our informative prior is applied to yeast sequencesets identified by chip-chip [3], the correct motif is found in 50% more cases than with an uninformative uniform prior. moreover, if nucleosome occupancy information is not available, our informative prior reduces to a new kind of prior that can exploit discriminative information in a purely generative setting.
protein conformational flexibility analysis with noisy data. protein conformational changes play a critical role in biological functions such as ligand-protein and protein-protein interactions. due to the noise in structural data, determining salient conformational changes reliably and efficiently is a challenging problem. this paper presents an efficient algorithm for analyzing protein conformational changes, using noisy data. it applies a statistical flexibility test to all contiguous fragments of a protein and combines the information from these tests to compute a consensus flexibility measure for each residue of the protein. we tested the algorithm, using data from the protein data bank and the macromolecular movements database. the results show that our algorithm can reliably detect different types of salient conformational changes, including well-known examples such as hinge and shear, as well as the flap motion of hiv-1 protease. the software implementing our algorithm is available at http://motion.comp.nus.edu.sg/projects/ proflexana/proflexana.html.
reconstructing the phylogeny of mobile elements. the study of mobile element evolution yields valuable insights into the mechanism and history of genome rearrangement, and can help answer questions about our evolutionary history. however, because the mammalian genome contains millions of copies of mobile elements exhibiting a complex evolutionary history, traditional phylogenetic methods are ill-suited to reconstructing their history. new phylogenetic reconstruction algorithms which exploit the unique properties of mobile elements and handle large numbers of repeats are therefore necessary to better understand both mobile elements' evolution and our own. we describe a randomized algorithm for phylogenetic reconstruction that scales easily to a million or more elements. we apply our algorithm to human and chimpanzee alu and l1 elements, and to sine elements from 61 species, finding 32 new l1, 111 new sine, and over 1000 new alu subfamilies. our results suggest that the history of mobile elements is significantly more complex than we currently understand.
rearrangements in genomes with centromeres part i: translocations. a centromere is a special region in the chromosome that plays a vital role during cell division. every new chromosome created by a genome rearrangement event must have a centromere in order to survive. this constraint has been ignored in the computational modeling and analysis of genome rearrangements to date. unlike genes, the different centromeres are indistinguishable, they have no orientation, and only their location is known. a prevalent rearrangement event in the evolution of multi-chromosomal species is translocation, i.e., the exchange of tails between two chromosomes. a translocation may create a chromosome with no centromere in it. in this paper we study for the first time centromeres-aware genome rearrangements. we present a polynomial time algorithm for computing a shortest sequence of translocations transforming one genome into the other, where all of the intermediate chromosomes must contain centromeres. we view this as a first step towards analysis of more general genome rearrangement models that take centromeres into consideration.
design of compact, universal dna microarrays for protein binding microarray experiments. our group has recently developed a compact, universal protein binding microarray (pbm) that can be used to determine the binding preferences of transcription factors (tfs) [1]. this design represents all possible sequence variants of a given length k (i.e., all k-mers) on a single array, allowing a complete characterization of the binding specificities of a given tf. here, we present the mathematical foundations of this design based on de bruijn sequences generated by linear feedback shift registers. we show that these sequences represent the maximum number of variants for any given set of array dimensions (i.e., number of spots and spot lengths), while also exhibiting desirable pseudorandomness properties. moreover, de bruijn sequences can be selected that represent gapped sequence patterns, further increasing the coverage of the array. this design yields a powerful experimental platform that allows the binding preferences of tfs to be determined with unprecedented resolution.
multivariate segmentation in the analysis of transcription tiling array data. tiling dna microarrays extend current microarray technology by probing the non-repeat portion of a genome at regular intervals in an unbiased fashion. a fundamental problem in the analysis of these data is the detection of genomic regions that are differentially transcribed across multiple conditions. we propose a linear time algorithm based on segmentation techniques and linear modeling that can work at a user-selected false discovery rate. it also attains a four-fold sensitivity gain over the only competing algorithm when applied to a whole genome transcription data set spanning the embryonic development of drosophila melanogaster.
connectedness profiles in protein networks for the analysis of gene expression data. knowledge about protein function is often encoded in the form of large and sparse undirected graphs where vertices are proteins and edges represent their functional relationships. one elementary task in the computational utilization of these networks is that of quantifying the density of edges, referred to as connectedness, inside a prescribed protein set. for instance, many functional modules can be identified because of their high connectedness. since individual proteins can have very different numbers of interactions, a connectedness measure should be well-normalized for vertex degree. namely, its distribution across random sets of vertices should not be affected when these sets are biased for hubs. we show that such degree-robustness can be achieved via an analytical framework based on a model of random graph with given expected degrees. we also introduce the concept of connectedness profile, which characterizes the relation between adjacency in a graph and a prescribed order of its vertices. a straightforward application to gene expression data and protein networks is the identification of tissue-specific functional modules or cellular processes perturbed in an experiment. the strength of the mapping between gene-expression score and interaction in the network is measured by the area of the connectedness profile. deriving the distribution of this area under the random graph enables us to define degree-robust statistics that can be computed in o(m), m being the network size. these statistics can identify groups of microarray experiments that are pathway-coherent, and more generally, vertex attributes that relate to adjacency in a graph.
a fast and accurate algorithm for the quantification of peptides from mass spectrometry data. liquid chromatography combined with mass spectrometry (lc-ms) has become the prevalent technology in high-throughput proteomics research. one of the aims of this discipline is to obtain accurate quantitative information about all proteins and peptides in a biological sample. due to size and complexity of the data generated in these experiments, this problem remains a challenging task requiring sophisticated and efficient computational tools. we propose an algorithm that can quantify even low abundance peptides from lc-ms data. our approach is flexible and can be applied to preprocessed and raw instrument data. it is based on a combination of the sweep line paradigm with a novel wavelet function tailored to detect isotopic patterns. we evaluate our technique on several data sets of varying complexity and show that we are able to rapidly quantify peptides with high accuracy in a sound algorithmic framework.
a feature-based approach to modeling protein-dna interactions. transcription factor (tf) binding to its dna target site is a fundamental regulatory interaction. the most common model used to represent tf binding specificities is a position specific scoring matrix (pssm), which assumes independence between binding positions. in many cases this simplifying assumption does not hold. here, we present feature motif models (fmms), a novel probabilistic method for modeling tf-dna interactions, based on markov networks. our approach uses sequence features to represent tf binding specificities, where each feature may span multiple positions. we develop the mathematical formulation of our models, and devise an algorithm for learning their structural features from binding site data. we evaluate our approach on synthetic data, and then apply it to binding site and chip-chip data from yeast. we reveal sequence features that are present in the binding specificities of yeast tfs, and show that fmms explain the binding data significantly better than pssms.
gimscan: a new statistical method for analyzing whole-genome array cgh data. genetic instability represents an important type of biological markers for cancer and many other diseases. array comparative genome hybridization (acgh) is a high-throughput cytogenetic technique that can efficiently detect genome-wide genetic instability events such as chromosomal gain, loss, and more complex aneuploidity, collectively known as genome imbalance (gim). we propose a new statistical method, genome imbalance scanner (gimscan), for automatically decoding the underlying dna dosage states from acgh data. gimscan captures both the intrinsic (nonrandom) spatial change of genome hybridization intensities, and the prevalent (random) measurement noise during data acquisition; and it simultaneously segments the chromosome and assigns different states to the segmented dna. we tested the proposed method on both simulated data and real data measured from a colorectal cancer population, and we report competitive or superior performance of gimscan in comparison with popular extant methods.
pairwise global alignment of protein interaction networks by matching neighborhood topology. we describe an algorithm, isorank, for global alignment of two protein-protein interaction (ppi) networks. isorank aims to maximize the overall match between the two networks; in contrast, much of previous work has focused on the local alignment problem-- identifying many possible alignments, each corresponding to a local region of similarity. isorank is guided by the intuition that a protein should be matched with a protein in the other network if and only if the neighbors of the two proteins can also be well matched. we encode this intuition as an eigenvalue problem, in a manner analogous to google's pagerank method. we use isorank to compute the first known global alignment between the s. cerevisiae and d. melanogaster ppi networks. the common subgraph has 1420 edges and describes conserved functional components between the two species. comparisons of our results with those of a well-known algorithm for local network alignment indicate that the globally optimized alignment resolves ambiguity introduced by multiple local alignments. finally, we interpret the results of global alignment to identify functional orthologs between yeast and fly; our functional ortholog prediction method is much simpler than a recently proposed approach and yet provides results that are more comprehensive.
an efficient and accurate graph-based approach to detect population substructure. currently, large-scale projects are underway to perform whole genome disease association studies. such studies involve the genotyping of hundreds of thousands of snp markers. one of the main obstacles in performing such studies is that the underlying population substructure could artificially inflate the p-values, thereby generating a lot of false positives. although existing tools cope well with very distinct sub-populations, closely related population groups remain a major cause of concern. in this work, we present a graph based approach to detect population substructure. our method is based on a distance measure between individuals. we show analytically that when the allele frequency differences between the two populations are large enough (in the l2-norm sense), our algorithm is guaranteed to find the correct classification of individuals to sub-populations. we demonstrate the empirical performance of our algorithms on simulated and real data and compare it against existing methods, namely the widely used software method structure and the recent method eigenstrat. our new technique is highly efficient (in particular it is hundreds of times faster than structure), and overall it is more accurate than the two other methods in classifying individuals into sub-populations. we demonstrate empirically that unlike the other two methods, the accuracy of our algorithm consistently increases with the number of snps genotyped. finally, we demonstrate that the efficiency of our method can be used to assess the significance of the resulting clusters. surprisingly, we find that the different methods find population sub-structure in each of the homogeneous populations of the hapmap project. we use our significance score to demonstrate that these substructures are probably due to over-fitting.
locating multiple gene duplications through reconciled trees. we introduce the first exact and efficient algorithm for guigó et al.'s problem that given a collection of rooted, binary gene trees and a rooted, binary species tree, determines a minimum number of locations for gene duplication events from the gene trees on the species tree. we examined the performance of our algorithm using a set of 85 genes trees that contain genes from a total of 136 plant taxa. there was evidence of large-scale gene duplication events in populus, gossypium, poaceae, asteraceae, brassicaceae, solanaceae, fabaceae, and near the root of the eudicot clade. however, error in gene trees can produce erroneous evidence of large-scale duplication events, especially near the root of the species tree. our algorithm can provide hypotheses for precise locations of large-scale gene duplication events with data from relatively few gene trees and can complement other genomic approaches to provide a more comprehensive view of ancient large-scale gene duplication events.
estimating genome-wide copy number using allele specific mixture models. genomic changes such as copy number alterations are thought to be one of the major underlying causes of human phenotypic variation among normal and disease subjects [23,11,25,26,5,4,7,18]. these include chromosomal regions with so-called copy number alterations: instead of the expected two copies, a section of the chromosome for a particular individual may have zero copies (homozygous deletion), one copy (hemizygous deletions), or more than two copies (amplifications). the canonical example is down syndrome which is caused by an extra copy of chromosome 21. identification of such abnormalities in smaller regions has been of great interest, because it is believed to be an underlying cause of cancer. more than one decade ago comparative genomic hybridization (cgh) technology was developed to detect copy number changes in a highthroughput fashion. however, this technology only provides a 10 mb resolution which limits the ability to detect copy number alterations spanning small regions. it is widely believed that a copy number alteration as small as one base can have significant downstream effects, thus microarray manufacturers have developed technologies that provide much higher resolution. unfortunately, strong probe effects and variation introduced by sample preparation procedures have made single-point copy number estimates too imprecise to be useful. cgh arrays use a two-color hybridization, usually comparing a sample of interest to a reference sample, which to some degree removes the probe effect. however, the resolution is not nearly high enough to provide single-point copy number estimates. various groups have proposed statistical procedures that pool data from neighboring locations to successfully improve precision. however, these procedure need to average across relatively large regions to work effectively thus greatly reducing the resolution. recently, regression-type models that account for probe-effect have been proposed and appear to improve accuracy as well as precision. in this paper, we propose a mixture model solution specifically designed for single-point estimation, that provides various advantages over the existing methodology. we use a 314 sample database, constructed with public datasets, to motivate and fit models for the conditional distribution of the observed intensities given allele specific copy numbers. with the estimated models in place we can compute posterior probabilities that provide a useful prediction rule as well as a confidence measure for each call. software to implement this procedure will be available in the bioconductor oligo package (http://www.bioconductor.org).
variational upper bounds for probabilistic phylogenetic models. probabilistic phylogenetic models which relax the site independence evolution assumption often face the problem of infeasible likelihood computations, for example for the task of selecting suitable parameters for the model. we present a new approximation method, applicable for a wide range of probabilistic models, which guarantees to upper bound the true likelihood of data, and apply it to the problem of probabilistic phylogenetic models. the new method is complementary to known variational methods that lower bound the likelihood, and it uses similar methods to optimize the bounds from above and below. we applied our method to aligned dna sequences of various lengths from human in the region of the cftr gene and homologous from eight mammals, and found the upper bounds to be appreciably close to the true likelihood whenever it could be computed. when computing the exact likelihood was not feasible, we demonstrated the proximity of the upper and lower variational bounds, implying a tight approximation of the likelihood.
minimizing and learning energy functions for side-chain prediction. side-chain prediction is an important subproblem of the general protein folding problem. despite much progress in side-chain prediction, performance is far from satisfactory. as an example, the rosetta program that uses simulated annealing to select the minimum energy conformations, correctly predicts the first two side-chain angles for approximately 72% of the buried residues in a standard data set. is further improvement more likely to come from better search methods, or from better energy functions? given that exact minimization of the energy is np hard, it is difficult to get a systematic answer to this question. in this paper, we present a novel search method and a novel method for learning energy functions from training data that are both based on tree reweighted belief propagation (trbp). we find that trbp can find the global optimum of the rosetta energy function in a few minutes of computation for approximately 85% of the proteins in a standard benchmark set. trbp can also effectively bound the partition function which enables using the conditional random fields (crf) framework for learning. interestingly, finding the global minimum does not significantly improve sidechain prediction for an energy function based on rosetta's default energy terms (less than 0.1%), while learning new weights gives a significant boost from 72% to 78%. using a recently modified rosetta energy function with a softer lennard-jones repulsive term, the global optimum does improve prediction accuracy from 77% to 78%. here again, learning new weights improves side-chain modeling even further to 80%. finally, the highest accuracy (82.6%) is obtained using an extended rotamer library and crf learned weights. our results suggest that combining machine learning with approximate inference can improve the state-of-the-art in side-chain prediction.
reconstructing the evolutionary history of complex human gene clusters. clusters of genes that evolved from single progenitors via repeated segmental duplications present significant challenges to the generation of a truly complete human genome sequence. such clusters can confound both accurate sequence assembly and downstream computational analysis, yet they represent a hotbed of functional innovation, making them of extreme interest. we have developed an algorithm for reconstructing the evolutionary history of gene clusters using only human genomic sequence data. this method allows the tempo of large-scale evolutionary events in human gene clusters to be estimated, which in turn will facilitate primate comparative sequencing studies that will aim to reconstruct their evolutionary history more fully.
orchestration of dna methylation. dna methylation plays an important role in gene regulation. in order to gain a better understanding of the rules governing this epigenetic modification, we have used microarray technology to map dna methylation in the human genome. this analysis has helped decipher the dna sequences involved in setting up the basic global methylation pattern in the early embryo and has revealed the full range of methylation changes that occur in a programmed manner during development. these studies also help explain how specific cpg island genes are targeted for de novo methylation in cancer. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
identification of deletion polymorphisms from haplotypes. numerous efforts are underway to catalog genetic variation in human populations. while the majority of studies of genetic variation have focused on single base pair differences between individuals, i.e. single nucleotide polymorphisms (snps), several recent studies have demonstrated that larger scale structural variation including copy number polymorphisms and inversion polymorphisms are also common. however, direct techniques for detection and validation of structural variants are generally much more expensive than detection and validation of snps. for some types of structural variation, in particular deletions, the polymorphism produces a distinct signature in the snp data. in this paper, we describe a new probabilistic method for detecting deletion polymorphisms from snp data. the key idea in our method is that we estimate the frequency of the haplotypes in a region of the genome both with and without the possibility of a deletion in the region and apply a generalized likelihood ratio test to assess the significance of a deletion. application of our method to the hapmap phase i data revealed 319 candidate deletions, 142 of these overlap with variants identified in earlier studies, while 177 are novel. using phase ii hapmap data we predict 6730 deletions.
constructing level-2 phylogenetic networks from triplets. jansson and sung showed that, given a dense set of input triplets t (representing hypotheses about the local evolutionary relationships of triplets of taxa), it is possible to determine in polynomial time whether there exists a level-1 network consistent with t, and if so, to construct such a network [24]. here, we extend this work by showing that this problem is even polynomial time solvable for the construction of level-2 networks. this shows that, assuming density, it is tractable to construct plausible evolutionary histories from input triplets even when such histories are heavily nontree-like. this further strengthens the case for the use of triplet-based methods in the construction of phylogenetic networks. we also implemented the algorithm and applied it to yeast data.
a fragmentation event model for peptide identification by mass spectrometry. we present in this paper a novel fragmentation event model for peptide identification by tandem mass spectrometry. most current peptide identification techniques suffer from the inaccuracies in the predicted theoretical spectrum, which is due to insufficient understanding of the ion generation process, especially the b/y ratio puzzle. to overcome this difficulty, we propose a novel fragmentation event model, which is based on the abundance of fragmentation events rather than ion intensities. experimental results demonstrate that this model helps improve database searching methods. on ltq data set, when we control the false-positive rate to be 5%, our fragmentation event model has a significantly higher true positive rate (0.83) than sequest (0.73). comparison with mascot exhibits similar results, which means that our model can effectively identify the false positive peptide-spectrum pairs reported by sequest and mascot. this fragmentation event model can also be used to solve the problem of missing peak encountered by de novo methods. to our knowledge, this is the first time the fragmentation preference for peptide bonds is used to overcome the missing-peak difficulty.
panel construction for mapping in admixed populations via expected mutual information. mapping by admixture linkage disequilibrium (mald) is an economical and powerful approach for the identification of genomic regions harboring disease susceptibility genes in recently admixed populations. we develop an information-theory based measure, called emi (expected mutual information), that computes the impact of a set of markers on the ability to infer ancestry at each chromosomal location. we then present a simple and effective algorithm for the selection of panels that strives to maximize the emi score. finally, we demonstrate via well established simulation tools that our panels provide considerably more power and accuracy for inferring disease gene loci via the mald method in comparison to previous methods.
a fast, alignment-free, conservation-based method for transcription factor binding site discovery. as an increasing number of eukaryotic genomes are being sequenced, comparative studies aimed at detecting regulatory elements in intergenic sequences are becoming more prevalent. most comparative methods for transcription factor (tf) binding site discovery make use of global or local alignments of orthologous regulatory regions to assess whether a particular dna site is conserved across related organisms, and thus more likely to be functional. since binding sites are usually short, sometimes degenerate, and often independent of orientation, alignment algorithms may not align them correctly. here, we present a novel, alignment-free approach for incorporating conservation information into tf motif discovery. we relax the definition of conserved sites: we consider a dna site within a regulatory region to be conserved in an orthologous sequence if it occurs anywhere in that sequence, irrespective of orientation. we use this definition to derive informative priors over dna sequence positions, and incorporate these priors into a gibbs sampling algorithm for motif discovery. our approach is simple and fast. it does not require sequence alignments, nor the phylogenetic relationships between the orthologous sequences, and yet it is more effective on real biological data than methods that do.
constructing treatment portfolios using affinity propagation. a key problem of interest to biologists and medical researchers is the selection of a subset of queries or treatments that provide maximum utility for a population of targets. for example, when studying how gene deletion mutants respond to each of thousands of drugs, it is desirable to identify a small subset of genes that nearly uniquely define a drug 'footprint' that provides maximum predictability about the organism's response to the drugs. as another example, when designing a cocktail of hiv genome sequences to be used as a vaccine, it is desirable to identify a small number of sequences that provide maximum immunological protection to a specified population of recipients. we refer to this task as 'treatment portfolio design' and formalize it as a facility location problem. finding a treatment portfolio is np-hard in the size of portfolio and number of targets, but a variety of greedy algorithms can be applied. we introduce a new algorithm for treatment portfolio design based on similar insights that made the recently-published affinity propagation algorithm work quite well for clustering tasks. we demonstrate this method using the two problems described above: selecting a subset of yeast genes that act as a drug-response footprint, and selecting a subset of vaccine sequences that provide maximum epitope coverage for an hiv genome population.
compostbin: a dna composition-based algorithm for binning environmental shotgun reads. a major hindrance to studies of microbial diversity has been that the vast majority of microbes cannot be cultured in the laboratory and thus are not amenable to traditional methods of characterization. environmental shotgun sequencing (ess) overcomes this hurdle by sequencing the dna from the organisms present in a microbial community. the interpretation of this metagenomic data can be greatly facilitated by associating every sequence read with its source organism. we report the development of compostbin, a dna composition-based algorithm for analyzing metagenomic sequence reads and distributing them into taxon-specific bins. unlike previous methods that seek to bin assembled contigs and often require training on known reference genomes, compostbin has the ability to accurately bin raw sequence reads without need for assembly or training. compostbin uses a novel weighted pca algorithm to project the high dimensional dna composition data into an informative lower-dimensional space, and then uses the normalized cut clustering algorithm on this filtered data set to classify sequences into taxon-specific bins. we demonstrate the algorithm's accuracy on a variety of low to medium complexity data sets.
on the inference of ancestries in admixed populations. inference of ancestral information in recently admixed populations, in which every individual is composed of a mixed ancestry (e.g., african americans in the us), is a challenging problem. several previous model-based approaches have used hidden markov models (hmm) to model the problem, however, the markov chain monte carlo (mcmc) algorithms underlying these models converge slowly on realistic datasets. while retaining the hmm as a model, we show that a combination of an accurate fast initialization and a local hill-climb in likelihood results in significantly improved estimates of ancestry.we studied this approach in two scenarios--the inference of locus-specific ancestries in a population that is assumed to originate from two unknown ancestral populations, and the inference of allele frequencies in one ancestral population given those in another.
systems metabolic engineering. metabolic engineering allows purposeful modification of metabolic and cellular network towards achieving several goals including enhanced production of various bioproducts, production of novel products, and broadening the substrate utilization range. traditional metabolic engineering has been performed by manipulating a handful of genes and pathways based on known literature information and our rational thinking. advances in omics technology, computational bioscience, and systems biology are now providing us with new information and knowledge that had not been possible to obtain using traditional approaches. systems biology is allowing us to elucidate the metabolism and physiology of cells and organisms at the global levels. metabolic engineering based on the systems-level analysis of cells and organisms, termed systems metabolic engineering, is now offering a new powerful way of designing and developing strains having improved performance. in this lecture, i will present the general strategies of systems metabolic engineering. also, several examples of applying systems metabolic engineering for the production of amino acids, primary metabolite (succinic acid) and secondary metabolite (lycopene) will be presented. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
rapid and accurate protein side chain prediction with local backbone information. high-accuracy protein structure modeling demands accurate and very fast side chain prediction since such a procedure must be repeatedly called at each step of structure refinement. many known side chain prediction programs, such as scwrl and treepack, depend on the philosophy that global information and pairwise energy function must be used to achieve high accuracy. these programs are too slow to be used in the case when side chain packing has to be used thousands of times, such as protein structure refinement and protein design. we present an unexpected study that local backbone information can determine side chain conformations accurately. localpack, our side chain packing program which is based on only local information, achieves equal accuracy as scwrl and treepack, yet runs 4-14 times faster, hence providing a key missing piece in our efforts to high-accuracy protein structure modeling.
high-resolution modeling of cellular signaling networks. a central challenge in systems biology is the reconstruction of biological networks from high-throughput data sets. a particularly difficult case of this is the inference of dynamic cellular signaling networks. within signaling networks, a common motif is that of many activators and inhibitors acting upon a small set of substrates. here we present a novel technique for high-resolution inference of signaling networks from perturbation data based on parameterized modeling of biochemical rates. we also introduce a powerful new signal-processing method for reduction of batch effects in microarray data. we demonstrate the efficacy of these techniques on data from experiments we performed on the drosophila rho-signaling network, correctly identifying many known features of the network. in comparison to existing techniques, we are able to provide significantly improved prediction of signaling networks on simulated data, and higher robustness to the noise inherent in all high-throughput experiments. while previous methods have been effective at inferring biological networks in broad statistical strokes, this work takes the further step of modeling both specific interactions and correlations in the background to increase the resolution. the generality of our techniques should allow them to be applied to a wide variety of networks.
protein function prediction based on patterns in biological networks. in this paper, we propose a pattern-based protein function annotation framework, employing protein interaction networks, to predict annotation functions of proteins. more specifically, we first detect patterns that appear in the neighborhood of proteins with a particular functionality, and then transfer annotations between two proteins only if they have similar annotation patterns. we show that, in comparison with other techniques, our approach predicts protein annotations more effectively. our technique (a) produces the highest prediction accuracy of 70-80% precision and recall for different organism specific datasets, and (b) is robust to false positives in protein interaction networks.
algorithms for joint optimization of stability and diversity in planning combinatorial libraries of chimeric proteins. in engineering protein variants by constructing and screening combinatorial libraries of chimeric proteins, two complementary and competing goals are desired: the new proteins must be similar enough to the evolutionarily-selected wild-type proteins to be stably folded, and they must be different enough to display functional variation. we present here the first method, staversity, to simultaneously optimize stability and diversity in selecting sets of breakpoint locations for site-directed recombination. our goal is to uncover all "undominated" breakpoint sets, for which no other breakpoint set is better in both factors. our first algorithm finds the undominated sets serving as the vertices of the lower envelope of the two-dimensional (stability and diversity) convex hull containing all possible breakpoint sets. our second algorithm identifies additional breakpoint sets in the concavities that are either undominated or dominated only by undiscovered breakpoint sets within a distance bound computed by the algorithm. both algorithms are efficient, requiring only time polynomial in the numbers of residues and breakpoints, while characterizing a space defined by an exponential number of possible breakpoint sets. we applied staversity to identify 2-10 breakpoint sets for three different sets of parent proteins from the pure family of biosynthetic enzymes. the average normalized distance between our plans and the lower bound for optimal plans is around 1 percent. our plans dominate most (60-90% on average for each parent set) of the plans found by other possible approaches, random sampling or explicit optimization for stability with implicit optimization for diversity. the identified breakpoint sets provide a compact representation of good plans, enabling a protein engineer to understand and account for the trade-offs between two key considerations in combinatorial chimeragenesis.
an integrative network approach to map the transcriptome to the phenome. although many studies have been successful in the discovery of cooperating groups of genes, mapping these groups to phenotypes has proved a much more challenging task. in this paper, we present the first genome-wide mapping of gene coexpression modules onto the phenome. we annotated coexpression networks from 136 microarray datasets with phenotypes from the unified medical language system (umls). we then designed an efficient graph-based simulated annealing approach to identify coexpression modules frequently and specifically occurring in datasets related to individual phenotypes. by requiring phenotypespecific recurrence, we ensure the robustness of our findings. we discovered 9,183 modules specific to 47 phenotypes, and developed validation tests combining gene ontology, generif and umls. our method is generally applicable to any kind of abundant network data with defined phenotype association, and thus paves the way for genome-wide, gene network-phenotype maps.
more efficient algorithms for closest string and substring problems. the closest string and substring problems find applications in pcr primer design, genetic probe design, motif finding, and antisense drug design. for their importance, the two problems have been extensively studied recently in computational biology. unfortunately both problems are np-complete. researchers have developed both fixed-parameter algorithms and approximation algorithms for the two problems. in terms of fixed-parameter, when the radius d is the parameter, the best-known fixed-parameter algorithm for closest string has time complexity o(ndd+1), which is still superpolynomial even if d = o(log n). in this paper we provide an o(n|σ|o(d)) algorithm where σ is the alphabet. this gives a polynomial time algorithm when d = o(log n) and σ has constant size. using the same technique, we additionally provide a more efficient subexponential time algorithm for the closest substring problem. in terms of approximation, both closest string and closest substring problems admit polynomial time approximation schemes (ptas). the best known time complexity of the ptas is o(no(ɛ-2 log 1/ɛ)). in this paper we present a ptas with time complexity o(no(ɛ-2)). at last, we prove that a restricted version of the closest substring has the same parameterized complexity as closest substring, answering an open question in the literature.
bcl-2: from translocation to therapy. impaired apoptosis is a critical step in the development of cancer and a major impediment to effective therapy. bcl-2, the oncoprotein activated by chromosome translocation in human follicular lymphoma, inhibits cells from undergoing apoptosis in response to many cytotoxic agents. exciting recent developments suggest that small molecules which neutralise bcl-2 and its anti-apoptotic homologues will be effective cancer therapeutics. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
fast and accurate alignment of multiple protein networks. comparative analysis of protein networks has proven to be a powerful approach for elucidating network structure and predicting protein function and interaction. a fundamental challenge for the successful application of this approach is to devise an efficient multiple network alignment algorithm. here we present a novel framework for the problem. at the heart of the framework is a novel representation of multiple networks that is only linear in their size as opposed to current exponential representations. our alignment algorithm is very efficient, being capable of aligning 10 networks with tens of thousands of proteins each in minutes. we show that our algorithm outperforms a previous strategy for the problem that is based on progressive alignment, and produces results that are more in line with current biological knowledge.
bootstrapping the interactome: unsupervised identification of protein complexes in yeast. protein interactions and complexes are major components of biological systems. recent genome-wide applications of tandem affinity purification (tap) in yeast have increased significantly the available information on such interactions. from these experiments, protein complexes were predicted with different approaches first from the individual experiments only and later from their combination. the resulting predictions showed surprisingly little agreement and all of the corresponding methods rely on additional training data. in this article, we present an unsupervised algorithm for the identification of protein complexes which is independent of the availability of additional complex information. based on a bootstrap approach, we calculated intuitive confidence scores for interactions which are more accurate than previous scoring metrics. the complexes determined from this confidence network are of similar quality as the complexes identified by the best supervised approaches. despite the similar quality of the latest predictions and our predictions, considerable differences are still observed between all of them. nevertheless, the set of consistently identified complexes is more than four times as large as for the first two studies. our results illustrate that meaningful and reliable complexes can be determined from the purification experiments alone. as a consequence, the approach presented in this article is easily applicable to large-scale tap experiments for any organism.
computational biology: its challenges past, present, and future. the recognition of the role of mathematics and computer science in modern biology has led to new terminology, as did chemistry with biochemistry, and physics with biophysics. we need to think only of bioinformatics, computational biology, and even system biology and genomics for example. these terms seem to strongly suggest that this is all rather new. yet a short review of the work of those such as j.b.s. haldane, sewell wright, darcy thompson and r.a. fisher, to say nothing of scientists like luria and delbrueck or hodgkin and huxley or thomas hunt morgan, is useful. their work and foresight set the stage for modern applications of mathematical modeling and statistics in the biological sciences. it has often been said that the only difference between now and then is the increase in data-a lot more data. this is clearly not the full story. in addition, we have computational power unimaginable to these earlier researchers, as well as to anyone only forty years ago. so what are our challenges? some are clear, including the modeling and analysis of biologys complex systems such as a cells signaling, metabolic and differentiation. also needed are analysis and models of complex neural systems and ecological structures. the latter, for example, will require a nearly full revamping of the early field of population genetics and evolution in order to exploit both modern genomics and new field studies of multiple species and environmental interactions. and there will be more, much of which will only become apparent as new data and questions arise. one example would be rnai and micro-arrays inducing the development of new analysis tools.
a bayesian approach to protein inference problem in shotgun proteomics. the protein inference problem represents a major challenge in shotgun proteomics. here we describe a novel bayesian approach to address this challenge that incorporates the predicted peptide detectabilities as the prior probabilities of peptide identification. our model removes some unrealistic assumptions used in previous approaches and provides a rigorious probabilistic solution to this problem. we used a complex synthetic protein mixture to test our method, and obtained promising results.
spectrum fusion: using multiple mass spectra for de novo peptide sequencing. we report on a new algorithm for combining the information from several mass spectra of the same peptide. the algorithm automatically learns peptide fragmentation patterns, so that it can handle spectra from any instrument and fragmentation technique. we demonstrate the utility of the algorithm, and the power of multiple spectra, by showing that combining pairs of spectra (one cid and one etd) greatly improves de novo sequencing success rates.
de novo sequencing of nonribosomal peptides. while nonribosomal peptides (nrps) are of tremendous pharmacological importance, there is currently no technology capable of high-throughput sequencing of nrps. difficulties in sequencing nrps slow down the progress in elucidating the non-ribosomal genetic code and negatively affect various screening programs aimed at the discovery of natural compounds of medical importance. we propose to employ multi-stage mass-spectrometry (msn) for the data acquisition, followed by alignment-based heuristic algorithms for data analysis. since mass spectrometry based analysis of nrps is fast and inexpensive, this approach opens the possibility of high-throughput sequencing of many unknown nrps accumulated in large screening programs.
accurate computation of likelihoods in the coalescent with recombination via parsimony. understanding the variation of recombination rates across a given genome is crucial for disease gene mapping and for detecting signatures of selection, to name just a couple of applications. a widely-used method of estimating recombination rates is the maximum likelihood approach, and the problem of accurately computing likelihoods in the coalescent with recombination has received much attention in the past. a variety of sampling and approximation methods have been proposed, but no single method seems to perform consistently better than the rest, and there still is great value in developing better statistical methods for accurately computing likelihoods. so far, with the exception of some twolocus models, it has remained unknown how the true likelihood exactly behaves as a function of model parameters, or how close estimated likelihoods are to the true likelihood. in this paper, we develop a deterministic, parsimony-based method of accurately computing the likelihood for multi-locus input data of moderate size. we first find the set of all ancestral configurations (acs) that occur in evolutionary histories with at most k crossover recombinations. then, we compute the likelihood by summing over all evolutionary histories that can be constructed only using the acs in that set. we allow for an arbitrary number of crossing over, coalescent and mutation events in a history, as long as the transitions stay within that restricted set of acs. for given parameter values, by gradually increasing the bound k until the likelihood stabilizes, we can obtain an accurate estimate of the likelihood. at least for moderate crossover rates, the algorithm-based method described here opens up a new window of opportunities for testing and fine-tuning statistical methods for computing likelihoods.
dlight - lateral gene transfer detection using pairwise evolutionary distances in a statistical framework. this paper presents an algorithm to detect lateral gene transfer (lgt) on the basis of pairwise evolutionary distances. the prediction is made from a likelihood ratio derived from hypotheses of lgt versus no lgt, using multivariate normal theory. in contrast to approaches based on explicit phylogenetic lgt detection, it avoids the high computational cost and pitfalls associated with gene tree inference, while maintaining the high level of characterization obtainable from such methods (species involved in lgt, direction, distance to the lgt event in the past). we validate the algorithm empirically using both simulation and real data, and compare its predictions with standard methods and other studies.
disruption of a transcriptional regulatory pathway contributes to phenotypes in carriers of ataxia telangiectasia. ataxia telangiectasia, at, is a recessive disorder caused by mutations in the atm gene. although it is a recessive disorder, population-based studies have shown that carriers of at have increased risks of breast cancer and other diseases compared to non-carriers. the goal of this study is to characterize phenotypes in at carriers. since expression level of genes is a major determinant of cellular phenotypes, we studied gene expression in at carriers and identified regulatory mechanisms that influence these expression phenotypes. we found gene expression phenotypes that showed a recessive pattern, where at carriers are similar to non-carriers but differ from at patients. however, there are also expression phenotypes that showed a dominant pattern where at carriers are similar to at patients but differ from non-carriers. one of the dominant gene expression phenotypes is that of tnfsf4. we showed that atm regulates tnfsf4 expression through a transcriptional regulatory pathway that includes transcription factors and mirnas. in at carriers and at patients, this pathway is disrupted, resulting in higher expression of tnfsf4. in this presentation, i will describe this atm-mediated pathway, and show that the disruption of this pathway leads to increased risk of breast cancer and cardiac death in at carriers. the integration of molecular and computational analyses of gene and microrna expression revealed the complex consequences of a human gene mutation.
a combined expression-interaction model for inferring the temporal activity of transcription factors. methods suggested for reconstructing regulatory networks can be divided into two sets based on how the activity level of transcription factors (tfs) is inferred. the first group of methods relies on the expression levels of tfs assuming that the activity of a tf is highly correlated with its mrna abundance. the second treats the activity level as unobserved and infers it from the expression of the genes the tf regulates. while both types of methods were successfully applied, each suffers from drawbacks that limit their accuracy. for the first set, the assumption that mrna levels are correlated with activity is violated for many tfs due to post-transcriptional modifications. for the second, the expression level of a tf which might be informative is completely ignored. here we present the post-transcriptional modification model (ptmm) that unlike previous methods utilizes both sources of data concurrently. our method uses a switching model to determine whether a tf is transcriptionally or post-transcriptionally regulated. this model is combined with a factorial hmm to fully reconstruct the interactions in a dynamic regulatory network. using simulated and real data we show that ptmm outperforms the other two approaches discussed above. using real data we also show that ptmm can recover meaningful tf activity levels and identify post-transcriptionally modified tfs, many of which are supported by other sources.
at the origin of life: how did folded proteins evolve? proteins are essential building blocks of living cells; indeed, life can be viewed as resulting substantially from the chemical activity of proteins. because of their importance, it is hardly surprising that ancestors for most proteins observed today were already present at the time of the 'last common ancestor', a primordial organism from which all life on earth is descended. yet folded proteins are too complex to have arisen de novo. how then did they evolve? we are pursuing the hypothesis that folded proteins evolved by fusion and recombination from an ancestral set of peptides, which emerged in the context of rna-dependent replication and catalysis (the "rna world"). systematic studies should allow a description of this ancient peptide set in the same way in which ancient vocabularies have been reconstructed from the comparative study of modern languages.
automatic parameter learning for multiple network alignment. we developed græmlin 2.0, a new multiple network aligner with (1) a novel scoring function that can use arbitrary features of a multiple network alignment, such as protein deletions, protein duplications, protein mutations, and interaction losses; (2) a parameter learning algorithm that uses a training set of known network alignments to learn parameters for our scoring function and thereby adapt it to any set of networks; and (3) an algorithm that uses our scoring function to find approximate multiple network alignments in linear time. we tested græmlin 2.0's accuracy on protein interaction networks from intact, dip, and the stanford network database.we show that, on each of these datasets, græmlin 2.0 has higher sensitivity and specificity than existing network aligners. græmlin 2.0 is available under the gnu public license at http://graemlin.stanford.edu.
automatic recognition of cells (arc) for 3d images of c. elegans. the development of high-resolution microscopy makes possible the high-throughput screening of cellular information, such as gene expression at single cell resolution. one of the critical enabling techniques yet to be developed is the automatic recognition or annotation of specific cells in a 3d image stack. in this paper, we present a novel graph-based algorithm, arc, that determines cell identities in a 3d confocal image of c. elegans based on their highly stereotyped arrangement. this is an essential step in our work on gene expression analysis of c. elegans at the resolution of single cells. our arc method integrates both the absolute and relative spatial locations of cells in a c. elegans body. it uses a marker-guided, spatially-constrained, two-stage bipartite matching to find the optimal match between cells in a subject image and cells in 15 template images that have been manually annotated and vetted. we applied arc to the recognition of cells in 3d confocal images of the first larval stage (l1) of c. elegans hermaphrodites, and achieved an average accuracy of 94.91%.
learning models for aligning protein sequences with predicted secondary structure. accurately aligning distant protein sequences is notoriously difficult. a recent approach to improving alignment accuracy is to use additional information such as predicted secondary structure. we introduce several new models for scoring alignments of protein sequences with predicted secondary structure, which use the predictions and their confidences to modify both the substitution and gap cost functions. we present efficient algorithms for computing optimal pairwise alignments under these models, all of which run in near-quadratic time. we also review an approach to learning the values of the parameters in these models called inverse alignment. we then evaluate the accuracy of these models by studying how well an optimal alignment under the model recovers known benchmark reference alignments. our experiments show that using parameters learned by inverse alignment, these new secondary-structure-based models provide a significant improvement in alignment accuracy for distant sequences. the best model improves upon the accuracy of the standard sequence alignment model for pairwise alignment by as much as 15% for sequences with less than 25% identity, and improves the accuracy of multiple alignment by 20% for difficult benchmarks whose average accuracy under standard tools is less than 40%.
shared peptides in mass spectrometry based protein quantification. in analyzing the proteome using mass spectrometry, the mass values help identify the molecules, and the intensities help quantify them, relative to their abundance in other samples. peptides that are shared across different protein sequences are typically discarded as being uninformative w.r.t each of the parent proteins.in this paper, we investigate the use of shared peptides which are ubiquitous (~50% of peptides) in mass spectrometric data-sets. in many cases, shared peptides can help compute the relative amounts of different proteins that share the same peptide. also, proteins with no unique peptide in the sample can still be analyzed for relative abundance. our paper is the first attempt to use shared peptides in protein quantification, and makes use of combinatorial optimization to reduce the error in relative abundance measurements. we describe the topological and numerical properties required for robust estimates, and use them to improve our estimates for ill-conditioned systems. extensive simulations validate our approach even in the presence of experimental error. we apply our method to a model of arabidopsis root knot nematode infection, and elucidate the differential role of many protein family members in mediating host response to the pathogen.
a robust bayesian two-sample test for detecting intervals of differential gene expression in microarray time series. understanding the regulatory mechanisms that are responsible for an organism's response to environmental changes is an important question in molecular biology. a first and important step towards this goal is to detect genes whose expression levels are affected by altered external conditions. a range of methods to test for differential gene expression, both in static as well as in time-course experiments, have been proposed. while these tests answer the question whether a gene is differentially expressed, they do not explicitly address the question when a gene is differentially expressed, although this information may provide insights into the course and causal structure of regulatory programs. in this article, we propose a two-sample test for identifying intervals of differential gene expression in microarray time series. our approach is based on gaussian process regression, can deal with arbitrary numbers of replicates and is robust with respect to outliers. we apply our algorithm to study the response of arabidopsis thaliana genes to an infection by a fungal pathogen using a microarray time series dataset covering 30,336 gene probes at 24 time points. in classification experiments our test compares favorably with existing methods and provides additional insights into time-dependent differential expression.
simultaneous alignment and folding of protein sequences. accurate comparative analysis tools for low-homology proteins remains a difficult challenge in computational biology, especially sequence alignment and consensus folding problems. we presentpartifold-align, the first algorithm for simultaneous alignment and consensus folding of unaligned protein sequences; the algorithm's complexity is polynomial in time and space. algorithmically,partifold-align exploits sparsity in the set of super-secondary structure pairings and alignment candidates to achieve an effectively cubic running time for simultaneous pairwise alignment and folding. we demonstrate the efficacy of these techniques on transmembrane β-barrel proteins, an important yet difficult class of proteins with few known three-dimensional structures. testing against structurally derived sequence alignments,partifold-align significantly outperforms state-of-the-art pairwise sequence alignment tools in the most difficult low sequence homology case and improves secondary structure prediction where current approaches fail. importantly, partifold-align requires no prior training. these general techniques are widely applicable to many more protein families. partifold-align is available at http://partifold.csail.mit.edu.
phylogenies without branch bounds: contracting the short, pruning the deep. we introduce a new phylogenetic reconstruction algorithm which, unlike most previous rigorous inference techniques, does not rely on assumptions regarding the branch lengths or the depth of the tree. the algorithm returns a forest which is guaranteed to contain all edges that are: 1) sufficiently long and 2) sufficiently close to the leaves. how much of the true tree is recovered depends on the sequence length provided. the algorithm is distance-based and runs in polynomial time.
combinatorial algorithms for structural variation detection in high throughput sequenced genomes. recent studies show that, along with single nucleotide polymorphisms and small indels, larger structural variants among human individuals are common. these studies have typically been based high-cost library generation and sanger sequencing; however, recent introduction of next-generation sequencing (ngs) technologies is changing how research in this area is conducted in a significant way. highthroughput sequencing technologies such as 454, illumina, helicos, and ab solid produce shorter reads than the traditional capillary sequencing, yet they reduce the cost (and/or the redundancy) by a factor of 10 - 100 and perhaps even more. those ngs technologies with the capability of sequencing paired-ends (or matepairs) of a clone insert (which follows a tight length distribution) have made it feasible to perform detailed and comprehensive genome variation and rearrangement studies. unfortunately, the few existing algorithms for identifying structural variation among individuals using paired-end reads have not been designed to handle the short read lengths and the errors implied by these platforms. here, we describe, for the first time, algorithms for identifying various forms of structural variation between a paired-end ngs sequenced genome and a reference genome.
detecting the presence and absence of causal relationships between expression of yeast genes with very few samples. inference of biological networks from high-throughput data is a central problem in bioinformatics. particularly powerful for network reconstruction is data collected by recent studies that contain both genetic variation information and gene expression profiles from genetically distinct strains of an organism. various statistical approaches have been applied to these data to tease out the underlying biological networks that govern how individual genetic variation mediates gene expression and how genes regulate and interact with each other. extracting meaningful causal relationships from these networks remains a challenging but important problem. in this paper we use causal inference techniques to infer the presence or absence of causal relationships between yeast gene expressions in the framework of graphical causal models. we evaluate our method using a well studied dataset consisting of both genetic variation information and gene expressions collected over yeast strains. our predictions of causal regulators are consistent with previously known experimental evidence. in addition, our method can distinguish between direct and indirect effects of variation on a gene expression level.
haplotype inference in complex pedigrees. despite the desirable information contained in complex pedigree datasets, analysis methods struggle to efficiently process these datasets. the attractiveness of pedigree data sets is their power for detecting rare variants, particularly in comparison with studies of unrelated individuals. in addition, rather than assuming individuals in a study are unrelated, knowledge of their relationships can avoid spurious results due to confounding population structure effects. however, a major challenge for the applicability of pedigree methods is the ability handle complex pedigrees, having multiple founding lineages, inbreeding, and half-sibling relationships.a key ingredient in association studies is imputation and inference of haplotypes from genotype data. existing haplotype inference methods either do not efficiently scales to complex pedigrees or their accuracy is limited. in this paper, we present algorithms for efficient haplotype inference and imputation in complex pedigrees. our method, phyloped, leverages the perfect phylogeny model, resulting in an efficient method with high accuracy. in addition, phyloped effectively combines the founder haplotype information from different lineages and is immune to inaccuracies in prior information about the founders.
lifting prediction to alignment of rna pseudoknots. prediction and alignment of rna pseudoknot structures are np-hard. nevertheless, several efficient prediction algorithms by dynamic programming have been proposed for restricted classes of pseudoknots. we present a general scheme that yields an efficient alignment algorithm for arbitrary such classes. moreover, we show that such an alignment algorithm benefits from the class restriction in the same way as the corresponding structure prediction algorithm does. we look at five of these classes in greater detail. the time and space complexity of the alignment algorithm is increased by only a linear factor over the respective prediction algorithm. for four of the classes, no efficient alignment algorithms were known. for the fifth, most general class, we improve the previously best complexity of o(n 5 m 5) time to o(nm 6), where n and m denote sequence lengths. finally, we apply our fastest algorithm with o(nm 4) time and o(nm 2) space to comparative de-novo pseudoknot prediction.
optimizing pcr assays for dna based cancer diagnostics. somatically acquired dna rearrangements are characteristic of many cancers. the use of these mutations as diagnostic markers is challenging, because tumor cells are frequently admixed with normal cells, particularly in early stage tumor samples, and thus the samples contain a high background of normal dna. detection is further confounded by the fact that the rearrangement boundaries are not conserved across individuals, and might vary over hundreds of kilobases. here, we present an algorithm for designing pcr primers and oligonucleotide probes to assay for these variant rearrangements. specifically, the primers and probes tile the entire genomic region surrounding a rearrangement, so as to amplify the mutant dna over a wide range of possible breakpoints and robustly assay for the amplified signal on an array. our solution involves the design of a complex combinatorial optimization problem, and also includes a novel alternating multiplexing strategy that makes efficient detection possible. simulations show that we can achieve near-optimal detection in many different cases, even when the regions are highly non-symmetric. additionally, we prove that the suggested multiplexing strategy is optimal in breakpoint detection.we applied our technique to create a custom design to assay for genomic lesions in several cancer cell-lines associated with a disruption in the cdkn2a locus. the cdkn2a deletion has highly variable boundaries across many cancers. we successfully detect the breakpoint in all cell-lines, even when the region has undergone multiple rearrangements. these results point to the development of a successful protocol for early diagnosis and monitoring of cancer.
an online approach for mining collective behaviors from molecular dynamics simulations. collective behavior involving distally separate regions in a protein is known to widely affect its function. in this paper, we present an online approach to study and characterize collective behavior in proteins as molecular dynamics simulations progress. our representation of md simulations as a stream of continuously evolving data allows us to succinctly capture spatial and temporal dependencies that may exist and analyze them efficiently using data mining techniques. by using multi-way analysis we identify (a) parts of the protein that are dynamically coupled, (b) constrained residues/ hinge sites that may potentially affect protein function and (c) time-points during the simulation where significant deviation in collective behavior occurred. we demonstrate the applicability of this method on two different protein simulations for barnase and cyclophilin a. for both these proteins we were able to identify constrained/ flexible regions, showing good agreement with experimental results and prior computational work. similarly, for the two simulations, we were able to identify time windows where there were significant structural deviations. of these time-windows, for both proteins, over 70% show collective displacements in two or more functionally relevant regions. taken together, our results indicate that multi-way analysis techniques can be used to analyze protein dynamics and may be an attractive means to automatically track and monitor molecular dynamics simulations.
sorting signed permutations by inversions in o(nlogn) time. the study of genomic inversions (or reversals) has been a mainstay of computational genomics for nearly 20 years. after the initial breakthrough of hannenhalli and pevzner, who gave the first polynomial-time algorithm for sorting signed permutations by inversions, improved algorithms have been designed, culminating with an optimal linear-time algorithm for computing the inversion distance and a subquadratic algorithm for providing a shortest sequence of inversions--also known as sorting by inversions. remaining open was the question of whether sorting by inversions could be done in o(nlogn) time.in this paper, we present a qualified answer to this question, by providing two new sorting algorithms, a simple and fast randomized algorithm and a deterministic refinement. the deterministic algorithm runs in time o(nlogn + kn), where k is a data-dependent parameter. we provide the results of extensive experiments showing that both the average and the standard deviation for k are small constants, independent of the size of the permutation. we conclude (but do not prove) that almost all signed permutations can be sorted by inversions in o(nlogn) time.
spatial clustering of multivariate genomic and epigenomic information. the combination of fully sequence genomes and new technologies for high density arrays and ultra-rapid sequencing enables the mapping of gene-regulatory and epigenetics marks on a global scale. this new experimental methodology was recently applied to map multiple histone marks and genomic factors, characterizing patterns of genome organization and discovering interactions among processes of epigenetic reprogramming during cellular differentiation. the new data poses a significant computational challenge in both size and statistical heterogeneity. understanding it collectively and without bias remains an open problem. here we introduce spatial clustering - a new unsupervised clustering methodology for dissection of large, multi-track genomic and epigenomic data sets into a spatially organized set of distinct combinatorial behaviors. we develop a probabilistic algorithm that finds spatial clustering solutions by learning an hmm model and inferring the most likely genomic layout of clusters. application of our methods to meta-analysis of combined chip-seq and chip-chip epigenomic datasets in mouse and human reveals known and novel patterns of local co-occurrence among histone modification and related factors. moreover, the model weaves together these local patterns into a coherent global model that reflects the higher level organization of the epigenome. spatial clustering constitutes a powerful and scalable analysis methodology for dissecting even larger scale genomic dataset that will soon become available.
overlapping pools for high throughput targeted resequencing. resequencing genomic dna from pools of individuals is an effective strategy to detect new variants in targeted regions and compare them between cases and controls. there are numerous ways to assign individuals to the pools on which they are to be sequenced. the naïve, disjoint pooling scheme (many individuals to one pool) in predominant use today, offers insight into allele frequencies, but does not offer the identity of an allele carrier. we present a framework for overlapping pool design, where each individual sample is resequenced in several pools (many individuals to many pools). upon discovering a variant, the set of pools where this variant is observed reveals the identity of its carrier. we formalize the mathematical framework for such pool designs, and list the requirements from such designs. next, we build on the theory of error-correcting codes to design arrangements that overcome pitfalls of pooled sequencing. specifically, three practical concerns of low coverage sequencing are investigated: (1) false positives due to errors introduced during amplification and sequencing; (2) false negatives due to undersampling particular alleles aggravated by non-uniform coverage; and consequently (3) ambiguous identification of individual carriers in the presence of errors. we show that in practical parameters of resequencing studies, our designs guarantee high probability of unambiguous singleton carrier identification, while maintaining the features of naïve pools in terms of sensitivity, specificity, and the ability to estimate allele frequencies. we demonstrate the ability of our designs by extracting rare variations on pooled short read data of 12 individuals from the 1000 genome pilot 3 project.
new perspectives on gene family evolution: losses in reconciliation and a link with supertrees. reconciliation between a set of gene trees and a species tree is the most commonly used approach to infer the duplication and loss events in the evolution of gene families, given a species tree. when a species tree is not known, a natural algorithmic problem is to infer a species tree such that the corresponding reconciliation minimizes the number of duplications and/or losses. in this paper, we clarify several theoretical questions and study various algorithmic issues related to these two problems. (1) for a given gene tree t and species tree s, we show that there is a single history explaining t and consistent with s that minimizes gene losses, and that this history also minimizes the number of duplications. we describe a simple linear-time and space algorithm to compute this parsimonious history, that is not based on the lowest common ancestor (lca) mapping approach; (2) we show that the problem of computing a species tree that minimizes the number of gene duplications, given a set of gene trees, is in fact a slight variant of a supertree problem; (3) we show that deciding if a set of gene trees can be explained using only apparent duplications can be done efficiently, as well as computing a parsimonious species tree for such gene trees. we also characterize gene trees that can be explained using only apparent duplications in terms of compatible triplets of leaves.
a statistical framework for the functional analysis of metagenomes. metagenomicstudies consider the genetic makeup of microbial communities as a whole, rather than their individual member organisms. the functional and metabolic potential of microbial communities can be analyzed by comparing the relative abundance of gene families in their collective genomic sequences (metagenome) under different conditions. such comparisons require accurate estimation of gene family frequencies. we present a statistical framework for assessing these frequencies based on the lander-waterman theory developed originally for whole genome shotgun (wgs) sequencing projects. we also provide a novel method for assessing the reliability of the estimations which can be used for removing seemingly unreliable measurements. we tested our method on a wide range of datasets, including simulated genomes and real wgs data from sequencing projects of whole genomes. results suggest that our framework corrects inherent biases in accepted methods and provides a good approximation to the true statistics of gene families in wgs projects.
detection of locally over-represented go terms in protein-protein interaction networks. high-throughput methods for identifying protein-protein interactions produce increasingly complex and intricate interaction networks. these networks are extremely rich in information, but extracting biologically meaningful hypotheses from them and representing them in a human-readable manner is challenging. we propose a method to identify gene ontology terms that are locally over-represented in a subnetwork of a given biological network. specifically, we propose two methods to evaluate the degree of clustering of proteins associated to a particular go term and describe four efficient methods to estimate the statistical significance of the observed clustering. we show, using monte carlo simulations, that our best approximation methods accurately estimate the true p-value, for random scale-free graphs as well as for actual yeast and human networks. when applied to these two biological networks, our approach recovers many known complexes and pathways, but also suggests potential functions for many subnetworks.
boosting protein threading accuracy. protein threading is one of the most successful protein structure prediction methods. most protein threading methods use a scoring function linearly combining sequence and structure features to measure the quality of a sequence-template alignment so that a dynamic programming algorithm can be used to optimize the scoring function. however, a linear scoring function cannot fully exploit interdependency among features and thus, limits alignment accuracy.this paper presents a nonlinear scoring function for protein threading, which not only can model interactions among different protein features, but also can be efficiently optimized using a dynamic programming algorithm. we achieve this by modeling the threading problem using a probabilistic graphical model conditional random fields (crf) and training the model using the gradient tree boosting algorithm. the resultant model is a nonlinear scoring function consisting of a collection of regression trees. each regression tree models a type of nonlinear relationship among sequence and structure features. experimental results indicate that this new threading model can effectively leverage weak biological signals and improve both alignment accuracy and fold recognition rate greatly.
searching protein 3-d structures in linear time. finding similar structures from 3-d structure databases of proteins is becoming more and more important issue in the post-genomic molecular biology. to compare 3-d structures of two molecules, biologists mostly use the rmsd (root mean square deviation) as the similarity measure. we propose new theoretically and practically fast algorithms for the fundamental problem of finding all the substructures of structures in a structure database of chain molecules (such as proteins), whose rmsds to the query are within a given constant threshold. we first propose a breakthrough linear-expected-time algorithm for the problem, while the previous best-known time complexity was o(nlogm), where n is the database size and m is the query size. for the expected time analysis, we propose to use the random-walk model (or the ideal chain model) as the model of average protein structures. we furthermore propose a series of preprocessing algorithms that enable faster queries. we checked the performance of our linear-expected-time algorithm through computational experiments over the whole pdb database. according to the experiments, our algorithm is 3.6 to 28 times faster than previously known algorithms for ordinary queries. moreover, the experimental results support the validity of our theoretical analyses.
cross species expression analysis of innate immune response. the innate immune response is the first line of host defense against infections. this system employs a number of different types of cells which in turn activate different sets of genes. microarray studies of human and mouse cells infected with various pathogens identified hundreds of differentially expressed genes. however, combining these datasets to identify common and unique response patterns remained a challenge. we developed methods based on probabilistic graphical models to combine expression experiments across species, cells and pathogens. our method analyzes homologous genes in different species concurrently overcoming problems related to noise and orthology assignments. using our method we identified both core immune response genes and genes that are activated in macrophages in both human and mouse but not in dendritic cells, and vice versa. our results shed light on immune response mechanisms and on the differences between various types of cells that are used to fight infecting bacteria.supporting website: http://www.cs.cmu.edu/~lyongu/pub/immune/
an adaptive and memory efficient algorithm for genotype imputation. genome wide association studies have proven to be a highly successful method for identification of genetic loci for complex phenotypes in both humans and model organisms. these large scale studies rely on the collection of hundreds of thousands of single nucleotide polymorphisms (snps) across the genome. standard high-throughput genotyping technologies capture only a fraction of the total genetic variation. recent efforts have shown that it is possible to "impute" with high accuracy the genotypes of snps that are not collected in the study provided that they are present in a reference data set which contains both snps collected in the study as well as other snps. we here introduce a novel hmm based technique to solve the imputation problem that addresses several shortcomings of existing methods. first, our method is adaptive which lets it estimate population genetic parameters from the data and be applied to model organisms that have very different evolutionary histories. compared to traditional methods, our method is up to ten times more accurate on model organisms such as mouse. second, our algorithm scales in memory usage in the number of collected markers as opposed to the number of known snps. this issue is very relevant due to the size of the reference data sets currently being generated. we compare our method over mouse and human data sets to existing methods and show that each has either comparable or better performance and much lower memory usage. the method is available for download at http://genetics.cs.ucla.edu/eminim .
the multi-state perfect phylogeny problem with missing and removable data: solutions via integer-programming and chordal graph theory. the multi-state perfect phylogeny problem is an extension of the binary perfect phylogeny problem, allowing characters to take on more than two states. in this paper we consider three problems that extend the utility of the multi-state perfect phylogeny model: the missing data (md) problem where some entries in the input are missing and the question is whether (bounded) values for the missing data can be imputed so that the resulting data has a multi-state perfect phylogeny; the character-removal (cr) problem where we want to minimize the number of characters to remove from the data so that the resulting data has a multi-state perfect phylogeny; and the missing-data character-removal (mdcr) problem where the input has missing data and we want to impute values for the missing data to minimize the solution to the resulting character-removal problem.we detail integer linear programming (ilp) solutions to these problems for the special case of three permitted states per character and report on extensive empirical testing of these solutions. then we develop a general theory to solve the md problem for an arbitrary number of permitted states, using chordal graph theory and results on minimal triangulation of non-chordal graphs. this establishes new necessary and sufficient conditions for the existence of a perfect phylogeny with (or without) missing data. we implement the general theory using integer linear programming, although other optimization methods are possible. we extensively explore the empirical behavior of the general solution, showing that the methods are very practical for data of size and complexity that is characteristic of many current applications in phylogenetics. some of the empirical results for the md problem with an arbitrary number of permitted states are very surprising, suggesting the existence of additional combinatorial structure in multi-state perfect phylogenies.
a probabilistic graphical model for ab initio folding. despite significant progress in recent years, ab initio folding is still one of the most challenging problems in structural biology. this paper presents a probabilistic graphical model for ab initio folding, which employs conditional random fields (crfs) and directional statistics to model the relationship between the primary sequence of a protein and its three-dimensional structure. different from the widely-used fragment assembly method and the lattice model for protein folding, our graphical model can explore protein conformations in a continuous space according to their probability. the probability of a protein conformation reflects its stability and is estimated from psi-blast sequence profile and predicted secondary structure. experimental results indicate that this new method compares favorably with the fragment assembly method and the lattice model.
evaluating between-pathway models with expression data. between-pathway models (bpms) are network motifs consisting of pairs of putative redundant pathways. in this paper, we show how adding another source of high-throughput data, microarray gene expression data from knockout experiments, allows us to identify a compensatory functional relationship between genes from the two bpm pathways. we evaluate the quality of the bpms from four different studies, and we describe how our methods might be extended to refine pathways.
incorporating nucleosomes into thermodynamic models of transcription regulation. transcriptional control is central to many cellular processes and consequently, much effort has been devoted to understanding its underlying mechanisms. recently, it has become evident that the organization of nucleosomes along promoter regions has an important role in transcriptional control, since most transcription factors cannot bind to sequences bound by nucleosomes, and thus compete with nucleosomes for dna access. this competition is governed by the relative concentrations of nucleosomes and transcription factors and by their respective sequence binding preferences. even though competition of nucleosomes and transcription factors may have significant effects on transcription, a mechanistic understanding of its quantitative consequences for gene expression is still missing. here we employ a thermodynamic framework based on fundamental principles of statistical mechanics to theoretically explore the effect that different nucleosome organizations along promoters have on the activation dynamics of promoters in response to varying concentrations of the regulating transcription factors. we show that even simple landscapes of nucleosome organization reproduce experimental results regarding the effect of nucleosomes as general repressors and as generators of obligate binding cooperativity between transcription factors. our modeling framework also allows us to characterize the effects that various sequence elements of promoters will have on the induction threshold and on the shape of the promoter activation curves.
on the relationship between dna periodicity and local chromatin structure. dna periodicity and its relationship to the formation of nucleosomes has been investigated extensively using autocorrelation and fourier transform methods. we provide a precise treatment of the mathematical foundation for this type of analysis, and we apply the resulting method to quantify dinucleotide periodicity in several datasets. we begin by demonstrating, via simulation, the sensitivity of our method relative to previous methods. we then provide evidence of pervasive ~10 bp periodicity in s. cerevisiae, with stronger periodicity in sequences associated with positioned nucleosomes. in human, although repeat-masked sequences do not exhibit significant periodicity on average, we find that experimentally determined nucleosome positions show a periodicity of the aa dinucleotide similar to that found in s. cerevisiae. furthermore, transcription start sites in the human genome are marked by a sharp drop in the 10 bp periodicity of the aa dinucleotide, while occupied ctcf sites are surrounded by a local increase.
identification and frequency estimation of inversion polymorphisms from haplotype data. structural rearrangements, including copy-number alterations and inversions, are increasingly recognized as an important contributor to human genetic variation. copy number variants are readily measured via array-based techniques like comparative genomic hybridization, but copy-neutral variants such as inversion polymorphisms remain difficult to identify without whole genome sequencing. we introduce a method to identify inversion polymorphisms and estimate their frequency in a population using readily available single nucleotide polymorphism (snp) data. our method uses a probabilistic model to describe a population as a mixture of forward and inverted chromosomes and identifies putative inversions by characteristic differences in haplotype frequencies around inversion breakpoints. on simulated data, our method accurately predicts inversions with frequencies as low as 25% in the population and reliably estimates inversion frequencies over a wide range. on the human hapmap phase 2 data, we predict between 88 and 142 inversion polymorphisms with frequency ranging from 20 to 92 percent. many of these correspond to known inversions or have other evidence supporting them, and the predicted inversion frequencies largely agree with the limited information presently available.
how many bootstrap replicates are necessary?. phylogenetic bootstrapping (bs) is a standard technique for inferring confidence values on phylogenetic trees that is based on reconstructing many trees from minor variations of the input data, trees called replicates. bs is used with all phylogenetic reconstruction approaches, but we focus here on the most popular, maximum likelihood (ml). because ml inference is so computationally demanding, it has proved too expensive to date to assess the impact of the number of replicates used in bs on the quality of the support values. for the same reason, a rather small number (typically 100) of bs replicates are computed in real-world studies. stamatakis et al. recently introduced a bs algorithm that is 1---2 orders of magnitude faster than previous techniques, while yielding qualitatively comparable support values, making an experimental study possible.in this paper, we propose stopping criteria, that is, thresholds computed at runtime to determine when enough replicates have been generated, and report on the first large-scale experimental study to assess the effect of the number of replicates on the quality of support values, including the performance of our proposed criteria. we run our tests on 17 diverse real-world dna, single-gene as well as multi-gene, datasets, that include between 125 and 2,554 sequences. we find that our stopping criteria typically stop computations after 100---500 replicates (although the most conservative criterion may continue for several thousand replicates) while producing support values that correlate at better than 99.5% with the reference values on the best ml trees. significantly, we also find that the stopping criteria can recommend very different numbers of replicates for different datasets of comparable sizes.our results are thus two-fold: (i) they give the first experimental assessment of the effect of the number of bs replicates on the quality of support values returned through bootstrapping; and (ii) they validate our proposals for stopping criteria. practitioners will no longer have to enter a guess nor worry about the quality of support values; moreover, with most counts of replicates in the 100---500 range, robust bs under ml inference becomes computationally practical for most datasets. the complete test suite is available at http://lcbb.epfl.ch/bs.tar.bz2 and bs with our stopping criteria is included in raxml 7.1.0.
protein fragment swapping: a method for asymmetric, selective site-directed recombination. this paper presents a new approach to site-directed recombination, swapping combinations of selected discontiguous fragments from a source protein in place of corresponding fragments of a target protein. by being both asymmetric (differentiating source and target) and selective (swapping discontiguous fragments), our method focuses experimental effort on a more restricted portion of sequence space, constructing hybrids that are more likely to have the properties that are the objective of the experiment. furthermore, since the source and target need to be structurally homologous only locally (rather than overall), our method supports swapping fragments from functionally important regions of a source into a target "scaffold"; e.g., to humanize an exogenous therapeutic protein. a protein fragment swapping plan is defined by the residue position boundaries of the fragments to be swapped; it is assessed by an average potential score over the resulting hybrid library, with singleton and pairwise terms evaluating the importance and fit of the swapped residues. while we prove that it is np-hard to choose an optimal set of fragments under such a potential score, we develop an integer programming approach, which we call swagmer, that works very well in practice. we demonstrate the effectiveness of our method in two types of swapping problem: selective recombination between beta-lactamases and activity swapping between glutathione transferases. we show that the selective recombination approach generates a better plan (in terms of resulting potential score) than a traditional site-directed recombination approach. we also show that in both cases the optimized experiment is significantly better than one that would result from stochastic methods.
storage and retrieval of individual genomes. a repetitive sequence collection is one where portions of a base sequence of length n are repeated many times with small variations, forming a collection of total length n. examples of such collections are version control data and genome sequences of individuals, where the differences can be expressed by lists of basic edit operations. flexible and efficient data analysis on a such typically huge collection is plausible using suffix trees. however, suffix tree occupies o(n logn) bits, which very soon inhibits in-memory analyses. recent advances in full-text self-indexing reduce the space of suffix tree to o(n log¿) bits, where ¿ is the alphabet size. in practice, the space reduction is more than 10-fold, for example on suffix tree of human genome. however, this reduction factor remains constant when more sequences are added to the collection.we develop a new family of self-indexes suited for the repetitive sequence collection setting. their expected space requirement depends only on the length n of the base sequence and the number s of variations in its repeated copies. that is, the space reduction factor is no longer constant, but depends on n/n.we believe the structures developed in this work will provide a fundamental basis for storage and retrieval of individual genomes as they become available due to rapid progress in the sequencing technologies.
finding biologically accurate clusterings in hierarchical tree decompositions using the variation of information. hierarchical clustering is a popular method for grouping together similar elements based on a distance measure between them. in many cases, annotations for some elements are known beforehand, which can aid the clustering process. we present a novel approach for decomposing a hierarchical clustering into the clusters that optimally match a set of known annotations, as measured by the variation of information metric. our approach is general and does not require the user to enter the number of clusters desired. we apply it to two biological domains: finding protein complexes within protein interaction networks and identifying species within metagenomic dna samples. for these two applications, we test the quality of our clusters by using them to predict complex and species membership, respectively. we find that our approach generally outperforms the commonly used heuristic methods.
parameter synthesis in nonlinear dynamical systems: application to systems biology. the dynamics of biological processes are often modeled as systems of nonlinear ordinary differential equations (ode). an important feature of nonlinear odes is that seemingly minor changes in initial conditions or parameters can lead to radically different behaviors. this is problematic because in general it is never possible to know/measure the precise state of any biological system due to measurement errors. the parameter synthesis problem is to identify sets of parameters (including initial conditions) for which a given system of nonlinear odes does not reach a given set of undesirable states. we present an efficient algorithm for solving this problem that combines sensitivity analysis with an efficient search over initial conditions. it scales to high-dimensional models and is exact if the given model is affine. we demonstrate our method on a model of the acute inflammatory response to bacterial infection, and identify initial conditions consistent with 3 biologically relevant outcomes.
coe: a general approach for efficient genome-wide two-locus epistasis test in disease association study. the availability of high density single nucleotide polymorphisms (snps) data has made genome-wide association study computationally challenging. two-locus epistasis (gene-gene interaction) detection has attracted great research interest as a promising method for genetic analysis of complex diseases. in this paper, we propose a general approach, coe, for efficient large scale gene-gene interaction analysis, which supports a wide range of tests. in particular, we show that many commonly used statistics are convex functions. from the observed values of the events in two-locus association test, we can develop an upper bound of the test value. such an upper bound only depends on single-locus test and the genotype of the snp-pair. we thus group and index snp-pairs by their genotypes. this indexing structure can benefit the computation of all convex statistics. utilizing the upper bound and the indexing structure, we can prune most of the snp-pairs without compromising the optimality of the result. our approach is especially efficient for large permutation test. extensive experiments demonstrate that our approach provides orders of magnitude performance improvement over the brute force approach.
topology-free querying of protein interaction networks. in the network querying problem, one is given a protein complex or pathway of species a and a protein---protein interaction network of species b; the goal is to identify subnetworks of b that are similar to the query. existing approaches mostly depend on knowledge of the interaction topology of the query in the network of species a; however, in practice, this topology is often not known. to combat this problem, we develop a topology-free querying algorithm, which we call torque. given a query, represented as a set of proteins, torque seeks a matching set of proteins that are sequence-similar to the query proteins and span a connected region of the network, while allowing both insertions and deletions. the algorithm uses alternatively dynamic programming and integer linear programming for the search task. we test torque with queries from yeast, fly, and human, where we compare it to the qnet topology-based approach, and with queries from less studied species, where only topology-free algorithms apply. torque detects many more matches than qnet, while in both cases giving results that are highly functionally coherent.
deep sequencing of a genetically heterogeneous sample: local haplotype reconstruction and read error correction. we present a computational method for analyzing deep sequencing data obtained from a genetically diverse sample. the set of reads obtained from a deep sequencing experiment represents a statistical sample of the underlying population. we develop a generative probabilistic model for assigning observed reads to unobserved haplotypes in the presence of sequencing errors. this clustering problem is solved in a bayesian fashion using the dirichlet process mixture to define a prior distribution on the unknown number of haplotypes in the mixture. we devise a gibbs sampler for sampling from the joint posterior distribution of haplotype sequences, assignment of reads to haplotypes, and error rate of the sequencing process to obtain estimates of the local haplotype structure of the population. the method is evaluated on simulated data and on experimental deep sequencing data obtained from hiv samples.
optimization-based peptide mass fingerprinting for protein mixture identification. in current proteome research, the most widely used method for protein mixture identification is probably peptide sequencing. peptide sequencing is based on tandem mass spectrometry (ms/ms) data. the disadvantage is that ms/ms data only sequences a limited number of peptides and leaves many more peptides uncovered.peptide mass fingerprinting (pmf) has been widely used to identify single purified proteins from single-stage ms data. unfortunately, this technique is less accurate than the peptide sequencing method and can not handle protein mixtures, which hampers the widespread use of pmf.in this paper, we tackle the problem of protein mixture identification from an optimization point of view. we show that some simple heuristics can find good solutions to the optimization problem. as a result, we obtain much better identification results than previous methods. through a comprehensive simulation study, we identify a set of limiting factors that hinder the performance of pmf-based protein mixture identification. we argue that it is feasible to remove these limitations and pmf can be a powerful tool in the analysis of protein mixtures, especially in the identification of low-abundance proteins which are less likely to be sequenced by ms/ms scanning.availability: the source codes, data and supplementary documents are available at http://bioinformatics.ust.hk/pmfmixture.rar
post-partition reconciliation protocols for maintaining consistency. this paper addresses design exploration for protocols that are employed in systems with availability-consistency tradeoffs. distributed data is modelled as states of objects replicated across a network, and whose updates require satisfaction of integrity constraints over multiple objects. upon detection of a partition, such a network will continue to provide delivery of services in parallel partitions; but only for updates with non-critical integrity constraints. once the degraded mode ends, the parallel network partitions are reconciled to arrive at one partition.using a formal treatment of the reconciliation process, three algorithms are proposed and studied in terms of their influence on service outage duration. the longer the reconciliation time, the lower is system availability; since the interval in which no services are provided is longer. however, the reconciliation time in turn is affected by the time to construct the post-partition system state. the shorter the construction time the higher is the number of updates that took place in the degraded mode but that will not be taken up in the reconciled partition. this will lead to a longer interval for rejecting/redoing these operations and thereby increase reconciliation time.
automatic interpretation of soccer video for highlights extraction and annotation. broadcasters are demonstrating interest in systems that ease the process of annotation the huge amount of live and archived video materials. exploitation of such assets is considered a key method for the improvement of production quality, and sport videos are one of the most marketable assets. in particular, in europe, soccer is one of the most relevant sport types. this paper deals with detection and recognition of soccer highlights, using an approach based on temporal logic models.
authentication of lz-77 compressed data. the formidable dissemination capability allowed by the current network technology makes it increasingly important to devise new methods to ensure authenticity. nowadays it is common practice to distribute documents in compressed form. in this paper, we propose a simple variation on the classic lz-77 algorithm that allows one to hide, within the compressed document, enough information to warrant its authenticity. the design is based on the unpredictability of a certain class of pseudo-random generators, in such a way that the hidden data cannot be retrieved in a reasonable amount of time by an attacker (unless the secret bit-string key is known). since it can still be decompressed by the original lz-77 algorithm, the embedding is completely "transparent". preliminary experiments show also the degradation in compression due to the embedding is almost negligible.
efficient aes implementations for arm based platforms. the advanced encryption standard (aes) contest, started by the u.s. national institute of standards and technology (nist), saw the rijndael [13] algorithm as its winner [11]. although the aes is fully defined in terms of functionality, it requires best exploitation of architectural parameters in order to reach the optimum performance on specific architectures. our work concentrates on arm cores [1] widely used in the embedded industry. most promising implementation choices for the common arm instruction set architecture (isa) are identified, and a new implementation for the linear mixing layer is proposed. the performance improvement over current implementations is demonstrated by a case study on the intel strongarm sa-1110 microprocessor [2]. further improvements based on exploitation of memory hierarchies are also described, and the corresponding performance figures are presented.
self-manifestation of composite multimedia objects to satisfy security constraints. a composite multimedia object (cmo) is comprised of different media components such as text, video, audio and image, with a variety of constraints that must be adhered to. these constraints include synchronization and spatial relationships between components, as well as the confidentiality and integrity requirements on each component. while spatial and synchronization constraints are to preserve the semantics of the cmo, the security (confidentiality and integrity) constraints are to represent the access control policies and fidelity requirements. a subject (user) requesting access for a cmo may not possess the required credentials to meet the confidentiality constraints, or his computer system the desired capabilities to meet the integrity constraints. this necessitates modification to the original cmo.in this paper, we present a self-manifestation approach in which composite multimedia objects automatically manifest themselves to cater to the subjects' credentials, and the capabilities of their computer systems. we accomplish this in two steps. first, we present a logical model which is an enhanced petri net model, called multimedia color-time petri net (mmctpn) to represent the components as well as the constraints of the cmo. we then demonstrate how mmctpn lends itself to automatic manifestation of the cmo when subject's credentials and capabilities activate it. second, we show how the petri net behavior can be implemented using the synchronized multimedia integration language (smil): smil, which is an extension of xml, supports specification of synchronization of the multimedia components and facilitates automatic rendering. when credentials are specified with digital certificates in some xml format, our system automatically modifies the smil document to satisfy the security constraints. we avoid multiple certificate verifications at the component sources by generating a single security token, when multiple credentials are required to view a component.
organizational modeling in uml and xml in the context of workflow systems. workflow technology plays a key role as an enabler in e-commerce applications, such as supply chains. until recently the major share of the attention of workflow systems researchers has gone to the exchange of information in cross-organizational processes. increasingly the focus is shifting from the exchange of data to support for interorganizational workflow processes. one of the initiatives in this direction has been xrl (exchangeable routing language), an extendible instance-based language having an xml syntax and petri-net semantics. in this paper, we move to the next level by extending xrl with organizational entities, structures, and rules. hence, we describe an organizational model first in uml and then convert it into an xml dtd. our organizational model allows for the specification of non-human resources, collections of resources (e.g., departments, teams, etc.), availability of resources, delegation, and role inheritance. additional features of our proposal are the tight integration of organizational concepts and routing concepts. an important goal of this work is to create standard for organizational modeling much like the x. 500 standard for directories.
using dijkstra's algorithm to incrementally find the k-nearest neighbors in spatial network databases. one of the most important kinds of queries in spatial network databases (sndb) to support location-based services (lbs) is the k-nearest neighbors (k-nn) query. given a point in a network, e.g. a location of a car on a road network, and a set of points of interests, e.g. hotels, gas stations, etc., the k-nn query returns the k points of interest closest to the query point. the network distance is used in such a query instead of the euclidean distance. dijkstra's algorithm is a well known solution to this problem. in this paper, we propose a storage schema with a set of index structures to support an efficient execution of a slightly modified version of the dijkstra's algorithm. we show in an experimental evaluation with generated data sets that our proposal is more efficient than the state-of-the-art solution to this problem.
temporal analysis of infectious diseases: influenza. a bayesian network is developed to embed the probabilistic reasoning dependencies of the demographics on the incidence of infectious diseases. influenza epidemics occur every year in both hemispheres during the winter. the bayesian learning paradigm is used to create synthetic data sets that simulate an outbreak of influenza for a geographic area. the bayesian prior and posterior probabilities can be altered to represent an outbreak for various demographics in different geographic regions. epidemic curves are generated, via time series analysis of the data sets, for the temporal flow of influenza on different variants of the demographics. the analysis of the demographic-based epidemic curves facilitates in the identification of the risk levels among the different demographic sections. spread vaccination lowers the impact of the epidemic, depending on the efficacy of the vaccine. our model is equipped to analyze the effects of spread vaccination and design vaccination strategies, that optimize the use of public health resources, by identifying high-risk demographic groups. our results show that application of the vaccine in the order of risk levels will further lower the epidemic impact as compared to uniform spread vaccination.
a grid-based architecture for earth observation data access. a huge quantity of earth observation (eo) and geospatial data is daily produced by several organizations. these heterogeneous data are very useful in several scientific, civil, military and industrial applications.securely and transparently storing, managing and accessing this huge quantity of data spread over distributed systems is a challenging problem. grid computing offers today a way to achieve secure access to geographically spread storage and computational resources.in this paper we present the distributed earth observation system information service (deosis) a distributed information service, developed by cact/isufi at the university of lecce which aims at managing and accessing eo and geospatial heterogeneous data sources, in a grid environment.
automated recognition of event scenarios for digital forensics. the authors have previously developed the ecf (event correlation for forensics) framework for scenario matching in the forensic investigation of activity manifested in digital transactional logs. ecf incorporated a suite of log parsers to reduce event records from heterogeneous logs to a canonical form for lodging in an sql database. this paper presents work since then, the auto-ecf system, which represents significant advances on ecf. the paper reports on the development and implementation of the new event abstraction and scenario specification methodology and on the development of the auto-ecf system which builds on that to achieve the automated recognition of event scenarios. the paper also reports on the evaluation of auto-ecf using three scenarios including one from the well known darpa test data.
on the numerical solution to linear problems using stochastic arithmetic. it has been recently shown that computation with stochastic numbers as regard to addition and multiplication by scalars can be reduced to computation in familiar vector spaces. this result allows us to solve certain practical problems with stochastic numbers and to compare algebraically obtained results with practical applications of stochastic numbers, such as the ones provided by the cestac method. such comparisons give additional information related to the stochastic behavior of random roundings in the course of numerical computations. a number of original numerical experiments are presented that agree with the expected theoretical results.
monitoring and synchronization for teamwork in gpgp. this paper addresses the problem of coordinating a group of agents involved in a team. to achieve flexible teamwork, agents should synchronize their work and monitor their performance to avoid redundant work. generalized partial global planning (gpgp) is one of the most common techniques used in coordinating cooperative agents, however, no technique is without limitations. our work adopts some concepts of steam to overcome some of gpgp limitations. in particular, we suggest adding coordination mechanisms to gpgp and extending taems, the model underlying gpgp, to facilitate such mechanisms. the work has successfully been implemented using jaf architecture. the coordination mechanisms are written as soar rules where we implemented a jaf component that implements the soar engine. analysis of a case study is presented along with experimental results to illustrate the power of the proposed work.
an evidential approach in ensembles. in this paper, we describe an approach to modeling the general process of combining decisions involved in ensembles of classifiers as an evidential reasoning process. this work proposes a novel structure, theoretical properties and manipulation mechanisms for representing classifier decisions as pieces of evidence. the advantage of the representation formalism is that it not only facilitates the distinguishing of trivial focal elements from important ones, resulting in the improvement of the ensemble performance, but it also effectively reduces the computation-time from exponential (as required in the conventional process of combining multiple pieces of evidence) to linear. we have conducted a comparative analysis on the effectiveness of the proposed evidence representation formalism in the text categorization domain. by comparing this method with majority voting and the previous results, we also demonstrate the advantage of this novel approach in combining classifiers.
property-oriented testing: a strategy for exploring dangerous scenarios. property-oriented testing uses the specification of a property to drive the testing process. the aim is to validate a program with respect to a target property, that is, to exercise the program and observe whether the property is violated or not. the paper defines a test strategy for safety properties in cyclic control systems. it consists of the stepwise construction of test scenarios. each step explores possible continuations of the dangerous scenarios found at the previous step, using black-box sampling techniques. the feasibility of the strategy is illustrated on a stem boiler case study. the target property is the "non explosion" of the boiler in presence of faults in the physical devices. the experimental results are promising since four different explosive scenarios have been identified.
constructive negation by bottom-up computation of literal answers. in this paper, we present a new proposal for an efficient implementation of constructive negation. in our approach the answers for a literal are bottom-up computed by solving equality constraints, instead of by handling frontiers of subsidiary computation trees. the required equality constraints are given by shepherdson's operators which are, in a sense, similar to bottom-up immediate consequence operators. however, in order to make the procedure efficient two main techniques are applied. first, we restrict our constraints to a class of success-answers (resp. fail-answers) which are easy to manipulate and to solve (or to prove their unsatisfiability). and, second, we take advantage of the monotonic nature of shepherdson's operators to make the procedure incremental and to avoid recalculations that are typical in frontiers-based methods. then, goal computation is made in the usual top-down clp scheme of collecting the answers for the selected literal into the constraint of the goal. the procedural mechanism for constructive negation is designed not only to generate every correct answer of a goal, but also to detect failure. that is, in spite of the bottom-up nature of the calculation of literal answers, goal computation is not necessarily infinite. the operational semantics that makes use of these ideas, called bcn, is sound and complete with respect to three-valued program completion for the whole class of normal logic programs. a prototype implementation of this approach has been developed and the experimental results are very promising.
a unified security framework for networked applications. various security models have been proposed for different types of applications and numerous types of execution environments. these models are typically reinforced by adding code to the application, which authenticates principals, authorises operations and establishes secure communication among distributed software components (e.g., clients and servers). this code is often application and context-specific, which makes it difficult to integrate an application with other each other.in this paper we propose a new unified access control mechanism that supports most of the existing security models and offers a number of additional controls that are not normally provided by security mechanisms. moreover, the proposed mechanism integrates well with existing programming paradigms for distributed application, e.g., client/server technology and component based programming. this means that it can be seamlessly integrated with most existing distributed applications. we have implemented the proposed mechanism in a framework, that can be instantiated to implement different security models and policies. we present a qualitative evaluation that demonstrates the framework's ability to support a wide range of security policies and a preliminary performance evaluation of the framework.
naive bayes vs decision trees in intrusion detection systems. bayes networks are powerful tools for decision and reasoning under uncertainty. a very simple form of bayes networks is called naive bayes, which are particularly efficient for inference tasks. however, naive bayes are based on a very strong independence assumption. this paper offers an experimental study of the use of naive bayes in intrusion detection. we show that even if having a simple structure, naive bayes provide very competitive results. the experimental study is done on kdd'99 intrusion data sets. we consider three levels of attack granularities depending on whether dealing with whole attacks, or grouping them in four main categories or just focusing on normal and abnormal behaviours. in the whole experimentations, we compare the performance of naive bayes networks with one of well known machine learning techniques which is decision tree. moreover, we compare the good performance of bayes nets with respect to existing best results performed on kdd'99.
smart-tv: a fast and scalable nearest neighbor based classifier for data mining. k-nearest neighbors (knn) is the simplest method for classification. given a set of objects in a multi-dimensional feature space, the method assigns a category to an unclassified object based on the plurality of category of the k-nearest neighbors. the closeness between objects is determined using a distance measure, e.g. euclidian distance. despite its simplicity, knn also has some drawbacks: 1) it suffers from expensive computational cost in training when the training set contains millions of objects; 2) its classification time is linear to the size of the training set. the larger the training set, the longer it takes to search for the k-nearest neighbors. in this paper, we propose a new algorithm, called smart-tv (small absolute difference of total variation), that approximates a set of potential candidates of nearest neighbors by examining the absolute difference of total variation between each data object in the training set and the unclassified object. then, the k-nearest neighbors are searched from that candidate set. we empirically evaluate the performance of our algorithm on both real and synthetic datasets and find that smart-tv is fast and scalable. the classification accuracy of smart-tv is high and comparable to the accuracy of the traditional knn algorithm.
cycle embedding in faulty hierarchical cubic networks. a hierarchical cubic network was proposed as an alternative to the hypercube. we use hcn(n) to denote the hierarchical cubic network that contains 2n n-dimensional hypercubes. in this paper, using gray codes, we construct fault-free hamiltonian cycles in an hcn(n) with n-1 link faults. since the hcn(n) is regular of degree n+1, the result is optimal. we also construct longest fault-free cycles of length 22n-1 in an hcn(n) with one node fault, and fault-free cycles of length at least 22n-2f in an hcn(n) with f node faults, where 22n is the number of nodes in the hcn(n), f&le;n-1 if n=3 or 4, and f&le;n if n&ge;5.
verification caching: towards efficient and secure mobile code execution environments. in the mobile code paradigm for distributed systems (as well as in the active networks and agents frameworks), programs from possibly unknown hosts interact with the resources local to the host. while this model offers great potential, it also raises difficult security and performance issues. the mobile code unit should be guaranteed to be safe (not to abuse the resources of the host) in a limited time (since the acquisition of the code happens in real time --- e.g., a java applet). existing host security schemes can be classified as: (i) discretion based: accept certificate of authenticity at your discretion; and (ii) verification based: formally prove the safety. verification provides the desired level of security; however, it comes at a large performance delay while discretion is efficient, but limited and relies on blind trust. we present an optimization, verification caching, for enhancing the performance of verification-based security methods. secure indexing of previously encountered code units is established by using message digest algorithm (e.g., md 5) to generate a fingerprint of the code. we characterize the performance and security of this scheme and investigate optimizations to lower the cost of generating the fingerprint (by indexing on small, partial, fingerprints and generating the full fingerprint only if there is a cache hit). in addition, we generalize the approach to allow multiple trusting nodes to distribute caching among them, sharing experiences and effectively increasing the cache size.
implementation of a proactive load sharing scheme. this paper presents a proactive approach to load sharing and describes the architecture of a scheme, concert, based on this approach. a proactive approach is characterized by a shift of emphasis from reacting to load imbalance to avoiding its occurrence. in contrast, in a reactive load sharing scheme, activity is triggered when a processing node is either overloaded or underloaded. the main drawback of this approach is that a load imbalance is allowed to develop before costly corrective action is taken. concert is a load sharing scheme for loosely-coupled distributed systems. under this scheme, load and task behaviour information is collected and cached in advance of when it is needed. concert uses linux as a platform for development. implemented partially in kernel space and partially in user space, it achieves transparency to users and applications whilst keeping the extent of kernel modifications to a minimum. non-preemptive task transfers are used exclusively, motivated by lower complexity, lower overheads and faster transfers. the goal is to minimize the average response-time of tasks. concert is compared with other schemes by considering the level of transparency it provides with respect to users, tasks and the underlying operating system.
implementing the essence of reflection: a reflective run-time environment. computational reflection provides the developers with a programming mechanism devoted to favorite code extensibility, reuse and maintenance. notwithstanding that, it has not achieved developers' unanimous acceptance and its full potential yet. in our opinion, this depends on the intrinsic complexity of most of the reflective approaches that hinders their efficient implementation. the aim of this paper consists of defining the essence of reflection, that is, to identify the minimal set of characteristics that a software system must have to be considered reflective. the consequence is the realization of a run-time environment supporting the essence of reflection without affecting the programming language and with a minimal impact on the programming system design. this achievement will improve reflective system performances reducing the impact of one of the most diffuse criticism about reflection: low performance.
finding differentially expressed genes: pattern generation using q-values. in this paper, we consider finding differentially expressed genes in a dataset of microarray experiments for pattern generation. we developed two methods which are mainly based on the q-values approach; the first is a direct extension of the q-values approach, while the second uses two approaches: q-values and maximum-likelihood. we present two algorithms for the second method, one for error minimization and the other for confidence bounding. also, we show how the method called patterns from gene expression (page) [7] can benefit from q-values. finally, we conducted some experiments to demonstrate the effectiveness of the proposed methods; experimental results on a selected dataset (brca1 vs brca2 tumor types) are provided.
efficient fault-tolerant routing algorithm for otis-cube using unsafety vectors. for the first time this paper proposes a new fault-tolerant routing algorithm for the well known class of network, otis-cube. in this new proposed algorithm, each node a starts by computing the first level unsafety set, sa1, composed of the set of unreachable direct neighbours. it then performs m-1 exchanges with its neighbours to determine the k-level unsafety sets sak for all 1 &le; k &le; m, where m is an adjustable parameter between 1 and 2n+1. equipped with these unsafety sets we show how each node calculates numeric unsafety vectors and uses them to achieve efficient fault-tolerant routing. the paper presents also a performance analysis through extensive simulation experiments proving the superiority of the proposed algorithm using the set of unsafety vectors by showing how the destination is reached by using these sets of unsafety vectors. the simulation results are obtained in terms of routing distances and percentage of reachability.
a dynamic load distribution strategy for systems under high task variation and heavy traffic. several approaches have been proposed to deal with the issue of load distribution, however they all have similar limitations, such as: (i) tasks are executed in an arbitrary order (which may cause large tasks to be delayed), (ii) the task dispatcher does not take into consideration the server processing capacity (which may cause a large task to be assigned to a server with low processing power) or (iii) they do not consider task deadlines (which if not met, may cause task starvation). this paper proposes an extension of lff (least flow-time first) task assignment policy [9], called lff-priority, to deal with these limitations. lff-priority dynamically computes two priorities, namely task size and task size priorities, and put them in a priority based multi-section queue. the testing results clearly show that lff-priority out performs existing load distribution strategies (that are based on heavy tailed distribution). the testing results also show that more than 80% of tasks meet their task deadline under lff-priority.
using latent semantic indexing to filter spam. past research has explored the effectiveness of a na&iuml;ve bayesian classifier when filtering unsolicited bulk email (spam). results have shown that the degree of precision of this approach is generally superior to the degree of recall. this study evaluates the effectiveness of a classifier incorporating latent semantic indexing (lsi) to filter spam email on corpus used in previous studies. results show that email classifiers using lsi to filter spam enjoy a very high degree of both recall and precision, no matter if the corpus is treated using a stop list or a lemmatizer. while using lsi leads to precision roughly equal to that of using a na&iuml;ve bayesian approach, the lsi technique has a substantially higher recall and is more effective under certain conditions.results show that incorporating lsi into an anti-spam filter is viable, particularly in implementations when misclassified legitimate messages are not arbitrarily deleted. other inferences are drawn to the applicability of this method to other text mining tasks.
smartgate: a smart push-pull approach to support role-based security in web gateways. efficient and effective web gateways or proxy servers are important to control the access privileges of users and protect private networks that are connected to the internet, thus providing a productive and safe web environment. access control in the form of complex access rules based on users or user sets (groups) has been studied extensively. the objective of this work is to provide role-based (rb) security for web gateways utilizing role-based access control (rbac). rb security reduces the administrative burden, provides fine grained access control and supports various constraints such as context-aware and temporal seamlessly.in this paper we elaborate on the problems, issues that need to be addressed, and our approach for providing rb security for web gateways by leveraging the flexibility and expressiveness of rbac. our approach enables the proxy server to act smarter, rather than just allow or deny access based on access rules, meanwhile preserving the principle of least privileges.
neighborhood based detection of anomalies in high dimensional spatio-temporal sensor datasets. the behavior of spatial objects is under the influence of nearby spatial processes. therefore in order to perform any type of spatial analysis we need to take into account not only the spatial relationships among objects but also the underlying spatial processes and other spatial features in the vicinity that influence the behavior of a given spatial object. in this paper, we address the outlier detection by refining the concept of a neighborhood of an object, which essentially characterizes similarly behaving objects into one neighborhood. this similarity is quantified in terms of the spatial relationships among the objects and other semantic relationships based on the spatial processes and spatial features in their vicinity. these spatial features could be natural such as a stream, and vegetation, or man-made such as a bridge, railroad, and chemical factory. the paper also addresses the identification of spatio-temporal outliers in high dimensions, in their neighborhood.
editorial message: special track on object oriented programming language and systems. today's large scale software systems are typically designed and implemented using the object-oriented (oo) methodology and paradigm. however, there is still a need for existing oo languages and architectures to continuously adapt in response to demands for new features and innovative approaches. a few examples of new features are unanticipated software evolution, security, safety, distribution, and interoperability.
extracting refactoring trends from open-source software and a possible solution to the 'related refactoring' conundrum. refactoring, as a software engineering discipline has emerged over recent years to become an important aspect of maintaining software. refactoring refers to the restructuring of software according to specific mechanics and principles. in this paper, we describe a tool that allows refactoring data across multiple versions of seven open-source software systems to be collected. the tool automates the identification of refactorings as program transformations between consecutive software releases. the same tool thus allowed an empirical analysis of software development across versions from the perspective of those transformations. we describe results for the systems analysed and point to key conclusions from our analysis. in particular, we investigate a problematic empirical question as to whether certain refactorings are related, i.e., they cannot be undertaken in isolation without other refactorings being undertaken in parallel. in this context, we focus specifically on the four most common refactorings identified by the tool from three of the open-source systems and use a dependency graph to inform conclusions about the empirical data extracted by the tool. an interesting result relating to some common refactorings is described.
editorial message: special track on object oriented programming languages and systems. today's large scale software systems are typically designed and implemented using the object-oriented (oo) methodology and paradigm. however, there is still a need for existing oo languages and architectures to continuously adapt in response to demands for new features and innovative approaches. a few examples of new features are unanticipated software evolution, security, safety, distribution, and interoperability.
mobile agent based pervasive systems manager for enterprise network. mobile wireless devices are rapidly becoming part of the personal computing with advances in the broadband wireless networks. these devices though, have serious resource constraints to perform truly complex enterprise tasks such as managing an enterprise network. a distributed adaptive systems infrastructure is needed to enable these mobile devices as extensions of the enterprise-computing platform. this paper presents a pervasive systems manager that enables mobile devices to manage mid sized enterprise networks from anywhere, anytime. mobile agents based pervasive systems manager allows device to initiate complex customized management actions. the paper describes architecture, implementation and experimental results of management action initiation, execution and dispatch of the enterprise systems management information to mobile devices.
editorial message: special track on object oriented programming languages and systems. today's large scale software systems are typically designed and implemented using the object-oriented (oo) methodology and paradigm. however, there is still a need for existing oo languages and architectures to continuously adapt in response to demands for new features and innovative approaches. a few examples of new features are unanticipated software evolution, security, safety, distribution, and interoperability.
topological mapping: a dimensionality reduction method for efficient video search. in this paper, we present a novel approach for efficient search of shots by the colors of objects that exist in the wanted shots. the idea is to map the color histogram, which represents the color content, of each object in the shot from the high-dimensional feature space into a point in a low-dimensional distance space. then, a spatial access method, such as an r-tree, is used to cluster these points based on their distances in the low-dimensional space. our mapping method, called topological mapping, guarantees no false dismissals in the result of a query. however, the result of a query might contain some false alarms. hence, two refinement steps are performed to remove these false alarms. comparative experiments show the superiority in efficiency of the topological mapping method over other methods.
modelling and filtering of mpeg-7-compliant meta-data for digital video. the recent mpeg-7 standard specifies a semi-structured meta-data format for open interoperability of multimedia. however, the standard refrains from specifying how the meta-data is to be used or how meta-data inappropriate to user requirements may be filtered out. consequently, we propose cosmos-7, which produces structured mpeg-7-compliant meta-data for digital video and enables content-based hybrid filtering of that meta-data.
a zkp-based identification scheme for base nodes in wireless sensor networks. most of the published work on authentication mechanisms for wireless sensor networks establishes secure authentication for sensor nodes, but not for the base node that is in fact required to authenticate other nodes in the same network. this situation can lead to an attack whereby a malicious party masquerades as the base station and fraudulently authenticates other legitimate nodes to capture and/or inject messages within the network. the trust assumption in the existing literature with regard to base stations (i.e., implicitly trusting the base station) presents a serious security loophole. we address this problem by proposing a protocol that will help build a base station authentication mechanism in the framework of a one-hop mesh network and later extend it to a multi-hop framework. our network would consist of a commissioning/installation device, and several forests of nodes (a base node and other nodes). the installation device would be responsible for deploying nodes in an area selected and would distribute information to them as necessary. we shall use a modification of the guillou-quisquater identification scheme as our zero-knowledge (zk) protocol in conjunction with the &mu;tesla protocol for authenticated broadcast, to authenticate the base station.
mpeg-7 in action: end user experiences with cosmos-7 front end systems. mpeg-7 has become a key standard to multimedia research in searching, filtering and retrieval. understanding experiences of users when using mpeg-7-based tools is necessary if we are to improve how mpeg-7 metadata is applied in practice. cosmos-7 enables structured modeling and filtering of mpeg-7-compliant metadata for digital video. we describe two cosmos-7 front end systems: cosmosis, for modeling digital video metadata, and the filtering manager, for filtering digital video metadata. we then present an empirical evaluation of these front end systems undertaken with a sample set of end users from a london, uk, theater company. our results reveal that end users progress through a number of key stages when modeling and filtering video content.
selective compilation via fast code analysis and bytecode tracing. modern java virtual machines (jvm) commonly adopt just-in-time (jit) compilation to speed up the execution of java bytecode. however, the effort of compiling a region of code is only worth if the code is frequently executed. therefore, selective compilation is employed so that the jit compiler is only invoked on those regions of code where most of the computation is performed (hot spots). the core task in selective compilation is to correctly identify the hot spots in a program. in our selekaffe prototype virtual machine, we introduce two heuristics aimed at detecting hot spots both statically, via bytecode analysis, and dynamically, via profiling information. experimental results on a representative set of benchmarks show that our method selection strategy is more accurate than known strategies, and not significantly slower.
detection and prediction of distance-based outliers. in this paper we present an unsupervised distance-based outlier detection method designed to learn a model over the objects contained in a data set. the learned model, called solving set, is a small subset of the data set that is used to classify new unseen objects as outliers or not. we provide an algorithm that computes a solving set with sub-quadratic time requirements, and we give experimental evidence that the computed solving set is small and that the false positive rate, i.e. the fraction of new objects misclassified as outliers using the solving set instead of the overall data set, is negligible.
multi-objective co-exploration of source code transformations and design space architectures for low-power embedded systems. the exploration of the architectural design space in terms of energy and performance is of mainly importance for a broad range of embedded platforms based on the system-on-chip approach. this paper proposes a methodology for the co-exploration of the design space composed of architectural parameters and source program transformations. a heuristic technique based on pareto simulated annealing (psa) has been used to efficiently span the multi-objective co-design space composed of the product of the parameters related to the selected program transformations and the configurable architecture. the analysis of the proposed framework has been carried out for a parameterized superscalar architecture executing a selected set of benchmarks. the reported results show the effectiveness of the proposed co-exploration with respect to the independent exploration of the transformation and architectural spaces to efficiently derive approximate pareto curves.
segmentation and reconstruction of the lung volume in ct images. the automated extraction of the pulmonary parenchyma in ct images is the most crucial step in a computer-aided diagnosis (cad) system. actually, the following step of analysis of the lung's internal structure, aimed at lesion detection and diagnosis, works on the identified pulmonary regions.in this paper we describe a method, consisting of an appropriate combination of image processing techniques, for the automated identification of the pulmonary volume. we present and discuss the results of the method application to computed-tomography (ct) examinations performed in a screening program for early detection of lung cancer.
executable declarative business rules and their use in electronic commerce. business rules are statements which are used to run the activities of an organization. in the era of electronic commerce it is important for these rules to be represented explicitly, and to be automatically applicable. in this paper we argue that methods from the field of knowledge representation can be used for this purpose. in particular, we propose the use of defeasible reasoning, a simple but efficient reasoning method based on rules and priorities. we motivate the use of defeasible reasoning, give examples, describe two case studies, and outline current and future work in our research.
graph-based automatic suggestion of relationships among images of illuminated manuscripts. scientific research on illuminated manuscripts includes the disclosure of relationships among images belonging to different manuscripts. relationships can be modeled as typed links, which induce an hypertext over the archive. in this paper we present a formal model for annotations, which is the basis to build methods for automatically processing existing relationships among link types and exploiting the properties of the graph which models the hypertext. the result of this processing is twofold: new relationships can be suggested to help users in their research work, and the existing ones can be semantically validated to check for inconsistencies.
probability vectors: a new fault-tolerant routing algorithm for k-ary n-cubes. this paper describes a new fault-tolerant routing algorithm for the k-ary n-cube using the concept of "probability vectors". to compute these vectors, a node determines first its faulty set, which contains all its neighbouring nodes that are faulty or unreachable due to faulty nodes or links. each node then calculates a probability vector, where the i-th element represents the probability that a destination node at distance i cannot be reached using a minimal path due to a faulty node or link. the probability vectors are used by all the nodes to achieve an efficient fault-tolerant routing in the network. results from a performance analysis presented below show that the new algorithm exhibits good fault-tolerance properties in terms of the achieved percentage of reachablity and routing distances.
extended internet caching protocol: a foundation for building ubiquitous web caching. internet access by nomadic users roaming on a mobile network presents a scenario of access that is substantially different from the wired network. with current web caching technology, accessing the web while mobile is slow not only because of bandwidth limitations, but also due to moving away from the home web caching proxy. furthermore, current web caching strategies ignore web access patterns during periods of mobility. studies of such scenarios are scarce. in this paper, we propose an extended internet caching protocol (x-icp), in which the proxy server of the nomadic user's newly visited network can retrieve web objects from its home network proxy server. such a scheme decreases the response time for the requests by fetching an object from a usually nearby home network rather than from the origin site. we use trace-based analysis and analytic modeling methods to evaluate x-icp. we draw several conclusions, all suggesting that x-icp would be an effective web caching approach for nomadic users, especially in wireless lan environments.
an arabic programming environment. this work presents the interface design of an arabic programming environment (ape). the environment is an attempt to arabize the user interface for programming languages under ms-windows. it consists of two interrelated parts. the first part is the arabic environment that enables users to create and edit programs in arabic. the second part is the arabic compiler. this paper describes only the first part of this project. it also states the main characteristics of the arabic language that affects this work.
a new framework for clustering algorithm evaluation in the domain of functional genomics. clustering algorithms are widely used in the computational analysis of microarray data. however, due to the lack of domain knowledge, it is often difficult to judge their performance. in this paper, we introduce a new framework for the evaluation of clustering algorithms in application to regulatory pathway reconstruction. a pilot study was conducted on the hierarchical clustering algorithm for which we obtained qualitative characterizations of the number of samples needed as well as the denseness of the subnetwork required to achieve accurate partition. for experimental scientists, this evaluation framework provides a method to select and calibrate clustering algorithms. it can also provide a confidence measure to the results of a clustering algorithm when certain restrictions on the experimental setup, such as the number of samples available, are known in advance.
knowledge discovery from doctor-patient relationship. the relationship between doctors and their patients is gaining more and more importance in the health care providing. it determines the compliance of the treatment and a part of the curative process. in the psychiatry the therapeutic relationship has even more power. therefore having a general rule that could guide doctors towards a good relation with their patients would be very useful. this paper describes experiments in automated acquisition of such a rule by means of data mining techniques. decision rules are provided to analyze the patients' satisfaction regarding the therapeutic treatment and to recognize whether a patient belongs to a psychiatric ward or not. data mining techniques show very satisfactory results on the experiments done with four different algorithms.
forming resource-sharing coalitions: a distributed resource allocation mechanism for self-interested agents in computational grids. designing efficient resource allocation mechanism for computational grids is extremely challenging because the effective agents in computational grids are inherently self-interested due to their different ownerships. providing incentive for agents to share their resource with others is the key to make computational grids realistic. the global efficiency should be generated through the interactions among agents from the bottom up. in game theory, forming coalition is such a cooperative game among self-interested agents. we develop a distributed resource allocation mechanism for computational grids by forming resource-sharing coalitions among self-interested agents through automated multiparty negotiation. this mechanism is based on a task-oriented mechanism for measuring the economic value of computational resource usage. the simulation results show that the self-interests of agents in computational grids have considerable impact on the decisions of each agent about how to allocate their resource to appropriate tasks.
editorial message: special track on data streams. advances in data acquisition hardware and embedded systems have led to the data stream era. a growing number of emerging applications varying from business to scientific to industrial ones continuously generate open-ended data streams. in practice, such data cannot be stored but must be both queried and analyzed as they arrive, discarding it right away. in many cases, we need to extract some sort of knowledge from these continuous streams that challenge the scalability of several batch-learning methods. therefore, this new field has attracted researchers from different disciplines over the past few years. examples of data streams include customer click streams, networks event logs, telephone records, large sets of web pages, multimedia data, scientific data, and sets of retail chain transactions. applications include credit card fraud protection, target marketing, and intrusion detection, for which it is not possible to collect all relevant input data. in these environments, kdd systems have to operate online under memory and time limitations.
simulating evolutionary agent communities with oocsmp. this paper describes some extensions added to the continuous simulation language oocsmp to perform agent-oriented simulation. the extensions are tested by simulating the evolution of a colony of virtual ants (vants). in this simulation, each vant is modelled as an agent and is assigned a set of genes that control some aspects of its behaviour, such as its velocity, memory, communication abilities, scepticism, etc. some emergent properties of the swarm of vants have been observed.
a new signature scheme: joint-signature. a number of asymmetrical payment methods have been developed to enable mobile users to buy goods online by charging them to their mobile phone bills by their network operators. it has been recognized that these methods must be used in conjunction with the security services of authentication and non-repudiation of the origin of the request(s) sent from a mobile user so as to prevent fraudulent actions by the network operator or any other entities. this paper presents a novel joint-signature scheme that can be used as one of the security primitives to address the above security services. the scheme enables a mobile user to securely and efficiently instruct his/er network operator for m-payment related actions. it is based on the use of the one-way hash function and traditional digital signature method, but in a collaborative manner with the network operator. the joint-signature scheme achieves the same security services as those by a traditional digital signature scheme, i.e. message origin authentication, message integrity and non-repudiation of origin, but offers lower computational cost for the mobile user. in addition, it imposes lower communication cost in comparison with proxy/server-aided signature schemes.
editorial message: special track on data streams. databases are growing incessantly and many sources produce data continuously. in many cases, we need to extract some sort of knowledge from this continuous stream of data. example include customer click streams, telephone records, large sets of web pages, multimedia data, scientific data, and sets of retail chain transactions. these sources are called data streams. the goal of this track is to convene researches who deal with decision rules, decision trees, association rules, clustering, filtering pre/post-processing, feature selection, visualization techniques, etc. from data streams and related themes.
a discrete event based simulation environment for enhanced umts 3 generation networks. this paper presents a new system level simulator that has been developed to evaluate e-umts (enhanced universal mobile telecommunication systems) 3g networks. the article describes how the simulator supports different mobility, propagation, and traffic generation models and how this simulation framework can be used to evaluate new protocols, algorithms, or resource management mechanisms. specific models and performance details for a sample scenario of a business city center are also provided.
evaluation measures for business process models. this work presents a set of measures to evaluate the structural complexity of business process models at a conceptual level, and also the general plan of a family of experiments whose aim is to validate the measures proposed. we believe that the early evaluation of business process models would provide business process management with support which would make their maintenance tasks easier. this proposal is based on the standard notation for business process modelling bpmn and on the adoption and extension of the fmesp framework.
schedulers for rule-based constraint programming. we study here schedulers for a class of rules that naturally arise in the context of rule-based constraint programming. we systematically derive a scheduler for them from a generic iteration algorithm of apt [4]. we apply this study to so-called membership rules of apt and monfroy [5]. this leads to an implementation that yields for these rules a considerably better performance than their execution as standard chr rules.
framework for mining web content outliers. outliers are data objects with different characteristics compared to other data objects. exploring the diverse and dynamic web data for outliers is more interesting than finding outliers in numeric data sets. interestingly, the existing web mining algorithms have concentrated on finding patterns that are frequent while discarding the less frequent ones that are likely to contain the outlying data. this paper refers to outliers present on the web as web outliers to distinguish them from traditional outliers. web outliers are data objects that show significantly different characteristics than other web data. although the presence of web outliers appears obvious, there is neither formal definition for web outliers nor algorithms for mining them. secondly, traditional outlier mining algorithms designed solely for numeric data sets are inappropriate for mining web outliers. this paper establishes the presence of web outliers and discusses some practical applications of web outlier mining. finally, we present taxonomy for web outliers and propose a general framework for mining web content out.
mining web content outliers using structure oriented weighting techniques and n-grams. classifying text into predefined categories is a fundamental task in information retrieval (ir). ir and web mining techniques have been applied to categorize web pages to enable users to manage and use the huge amount of information available on the web. thus, developing user-friendly and automated tools for managing web information has been on a higher demand in web mining and information retrieval communities. text categorization, information routing, identification of junk materials, topic identification and structured search are some of the hot spots in web information management. a great deal of techniques exists for classifying web documents into categories. interestingly, almost none of the existing algorithms consider documents having 'varying contents' from the rest of the documents taken from the same domain (category) called web content outliers. in this paper, we take advantage of the html structure of web and n-gram technique for partial matching of strings and propose an n-gram-based algorithm for mining web content outliers. to reduce the processing time, the optimized algorithm uses only data captured in <meta> and <title> tags. experimental results using planted motifs indicate the proposed n-gram-based algorithm is capable of finding web content outliers. in addition, using texts captured in <meta> and <title> tags gave the same results as using text embedded in <meta>, <title>, and <body> tags.
design and implementation of a context-aware decision algorithm for heterogeneous networks. wireless networks and mobile terminals are evolving towards being heterogeneous. in this environment, intelligent handover decision, beyond traditional ones that are based on only signal strength, is needed so that terminals can select the best option available from diverse networks and services as per user requirements. in the process, it would enable user applications to switch automatically between active interfaces that best suit them based on application requirements and interface capabilities and to use multiple radio interfaces simultaneously ensuring the optimum usage of the network resources available to the terminal. to fulfill the above requirements, this paper proposes the design and implementation of a context-aware vertical handover decision algorithm suitable for multimode mobile devices in heterogeneous networks based on the analytic hierarchy process (ahp).
making xpath reach for the web-wide links. opting for link semantics in xml is almost like hyperlinks for html documents. xlink describes a standard way to add hyperlinks to an xml document. the current xpath technologies are restricted to follow id/idref(s) links for intra-document navigation only. we investigate the lightweight directory access protocol (ldap) that offers a rich collection of primitives to express links among distributed data collections in the network, and facilities to follow links when searching. in virtue of querying the underlying ldap model by referrals, we developed an extended xpath processor that is capable of addressing links of any type (idref(s), xlink) embedded in xml data on the web. links may be inter-document, or even traverse across different local or remote servers. we describe the internal ldap data representation and query model used by the processor for the storage and querying in xpath of xml documents based on links, and provide examples to illustrate them. we complement the discussion with experimental analyses that prove the efficiency of our query evaluation techniques. the latter confirms the relevance of our approach for applications that need to interact with interlinked xml document networks in an xpath-like fashion.
adaptive dynamic run-length coding for image segmentation. in this study, an adaptive image segmentation algorithm based on a modified dynamic window-based gray-level run-length coding (dw-rlc) is developed. we propose an adaptive method for determining the range which is used in the (dw-rlc) algorithm for image segmentation. first, the modes are estimated and identified from the image histogram automatically. secondly, the adaptive range (r) is calculated using the statistics estimated from the mode distribution. then, the actual interval for the segmentation is updated based on the seed pixel value and the adaptive range (r). the proposed adaptive algorithm can be categorized as a region growing method. the proposed method is compared with the mean shift and k-means algorithms. this method improves the dw-rlc algorithm by making it less dependent on the randomly chosen range for segmentation, hence more stable.
role-based authorization in decentralized health care environments. the formation of a distributed system is based on a collection of distributed components and it requires the ability for components to exchange syntactically well-formed messages. to simplify network programming for such interactions and to realize security services for those components, we need a component-based software architecture that enables software components to communicate directly over a network in a reliable and efficient manner. one of those models is distributed component object model (dcom) which is used for interacting with distributed components within the local intranet. in this paper, we overview an aspect of dcom concerning software architecture and access control. and we describe the concept of role-based access control (rbac) which began with multi-user and multi-application on-line systems pioneered in the 1970s. also we investigate how we can enforce the role-based access control as a security provider within the critical environment such as health care industry accessing distributed components legitimately. we demonstrate the feasibility of our approach through a proof-of-concept prototype implementation.
towards reliable osgi framework and applications. upcoming ubiquitous computing systems are required to operate in dynamic, diverse, unverified, and unpredictable operating environment. the osgi (open service gateway initiative) framework employs the service-oriented approach and the java classloader architecture for the runtime service deployment, that are well suited to the dynamic environment envisioned for home networking and ubiquitous computing. however, the current osgi framework does not provide full reliability measures, especially for failure conditions such as network, device, and application failures. this paper analyzes software reliability issues in osgi framework and proposes a proxy-based reliable extensions. the design concept is implemented and partly tested on an open source osgi platform, oscar, for the smart home residential gateway test-bed.
privacy-preserving demographic filtering. the use of recommender systems in e-commerce to guide customer choices presents a privacy protection problem that is twofold. we seek to protect the privacy interests of customers by trying to keep private their identity and demographic characteristics, and possibly also their buying preferences and behaviour. this can be desirable even if anonymity is used. furthermore, we want to protect the commercial interests of the e-commerce service providers by allowing them to make recommendations as accurate as possible, without unnecessarily revealing valuable information they have legitimately accumulated, such as market trends, to third parties.in this paper, we concentrate on recommender systems based on demographic filtering, which make recommendations based on feedback of previous users of similar demographic characteristics (such as age, sex, level of education, wealth, geographical location, etc.). we propose a system called alambic, which adequately achieves the above privacy-protection objectives in this kind of recommender systems. our system is based on a semi-trusted third party in which the users need only have limited confidence. a main originality of our approach is to split user data between that party and the service provider in such a way that neither can derive sensitive information from their share alone.
a branch-price-and-propagate approach for optimizing igp weight setting subject to unique shortest paths. an interior gateway protocol (igp) routes internet end-to-end traffic via the shortest paths according to a set of igp weights assigned to the network links. these weights, which can be re-set by the administrator, uniquely determine the traffic routes and thus the network performance. assigning and provisioning the igp weights incurring the minimum network congestion, is a common practice in traffic engineering. motivated by an application, this paper considers the problem of optimizing the igp weights so that the shortest paths are unique in the network. despite its relevance in the telecoms sector, the problem poses considerable modelling and optimization challenges which have yet to be addressed. we develop a constraint model for the problem, and show that even small instances are too difficult for traditional optimization approaches. our main contribution is a new hybrid optimizer that combines constraint programming and cut/column generation in order to exploit the model structure. our optimizer succeeds in solving most of a set of realistically sized benchmarks.
integrating similarity-based queries in image dbmss. until recently, issues in image retrieval have been handled in dbmss and in computer vision as separate research works. nowadays, the trend is towards integrating the two approaches (content- and metadata-based) for multi-criteria image retrieval. however, most existing works and proposals in this domain lack a formal framework to deal with a multi-criteria query. in this paper, we introduce a formal framework to address this subject of image retrieval under an ordbms model. we first propose an image data repository model interoperable with current popular standards. then, we present an algebraic formalism for content-based operators on image database. we study the properties of these operators and discuss query optimization issues. to demonstrate the use of our algebra, we implemented an extension of our prototype called emims. experimental evaluations on our proposed query optimization techniques used in emims are presented here.
a cost-oriented methodology for the design of web based it architectures. this paper proposes a design methodology of web-based it architectures tying organizational requirements to technical choices and costs. information system design and optimum sizing is the result of a reconciliation of several conflicting requirements, including technical performance and costs. web-based it architectures involve a number of design choices with significant cost implications: the adoption of thin clients executing web applications remotely, the choice of the number of architectural tiers over the web, the allocation of applications on physical machines and the total number of servers involved. the main goal of this paper is the identification of a sequence of design steps, from requirements analysis to physical implementation, that allows designers to estimate the cost implications of architectural choices and, by evaluating multiple design alternatives, determine the minimum-cost architectural solution. preliminary results from the empirical verification of the methodology indicate that for web-based architectures cost reductions can be significant and would support the practical use of a cost-oriented approach as a complement to traditional performance evaluations.
a cost-oriented approach for infrastructural design. the selection of a cost-minimizing combination of hardware and network components that satisfy organizational requirements is a complex design problem with multiple degrees of freedom. decisions must be made on how to distribute the overall computing load onto multiple computers, where to locate computers and how to take advantage of legacy components. the corresponding optimization problem not only embeds the structure of np-hard problems, but also represents a challenge with a well-structured heuristic approach. a scientific approach has been rarely applied to cost minimization and a rigorous methodological support to cost issues of infrastructural design is still lacking. the methodological contribution of this paper is the representation of complex infrastructural design issues as a single cost-minimization problem. the problem is decomposed in four interwined cost-minimization sub-prolems; optimization is accomplished by sequentially solving these sub-problems with a heuristic approach and tuning their solution with a final tabusearch step. results indicate that decomposition significantly reduces optimization time and solutions are also closer to the global optimum if results are compared to those identified without prior decomposition. cost reductions are also significant when practicioners' solutions, obtained by applying simplified design rules from the professional literature, are considered.
towards a scalable broadcast in wormhole-switched mesh networks. broadcast algorithms for wormhole---switched meshes have been widely reported in the literature. however, most of these algorithms handle broadcast in a sequential manner and do not scale well with the network size. as a consequence, many parallel applications cannot be efficiently supported using existing algorithms. motivated by these observations, this paper presents a new broadcast algorithm based on our previously proposed coded path routing (or cpr for short) [1]. the main feature of the proposed algorithm lies in its ability to perform broadcast operations with a high degree of parallelism. furthermore, its performance is insensitive to the network size, i.e., only two message-passing steps are required to implement a broadcast operation irrespective of the network size. results from a comparative analysis reveal that the new algorithm exhibits superior performance characteristics over those of the well-known recursive doubling, extending dominating node and network partitioning algorithms.
adaptive dissemination of dynamic information services in an extended data broadcast environment. considering that most information broadcast services generate data dynamically in practice, we devise in this paper an extended data broadcast mechanism which supports not only the original data broadcast scenario but also the dissemination of dynamic inforamtion services. furthermore, we design an on-line loan-based slot allocation and feedback technique to tolerate the dynamic changes of broadcast traffic and accordingly perform the adaptation of service classification, bandwidth allocation and broadcast schedule so as to enhance the performance. our experimental studies show that the extended data broadcast mechanism associated with the loan-based feedback technique is able to achieve a substantial saving in message traffic for dynamic information dissemination in wireless networks.
1-2pc: the one-two phase atomic commit protocol. this paper proposes a one-phase, two-phase commit (1-2pc) protocol that can be used to atomically commit internet transactions distributed across sites in a wide area network. the 1-2pc protocol is characterized by its ability to dynamically select between one-phase and two-phase atomic commit protocols depending on the behavior of transactions and the system requirements. thus, it offers the performance advantages of the one-phase atomic commit protocol whenever possible, while still providing the wide applicability of the two-phase commit protocol. this is achieved in spite of the incompatibilities between one-phase and two-phase commit protocols that lead to the general practice of having to adopt a single atomic commit protocol in any distributed database system.
a data mining approach for database intrusion detection. in this paper we proposed a data mining approach for detecting malicious transactions in a database system. our approach concentrates on mining data dependencies among data items in the database. a data dependency miner is designed for mining data correlations from the database log. the transactions not compliant to the data dependencies mined are identified as malicious transactions. the experiment illustrates that the proposed method works effectively for detecting malicious transactions provided certain data dependencies exist in the database.
reconciling diagrams after executing model transformations. in this paper we discuss how to create and update diagrams after the execution of a model transformation. this is achieved by creating an independent diagram reconciliation tool component that is based on a mapping language from the abstract syntax to the concrete syntax of a modeling language. this approach allows us to decouple model transformation from diagram handling in model transformation languages and tools.
applying model checking to bpel4ws business collaborations. web services are a very appropriate communication mechanism to perform distributed business processes among several organisations. these processes should be reliable, because a failure in them can cause high economic losses. in this work we propose a framework for the verification of business processes, called verbus. its aim is to help the designer to find errors in specifications at design time, thus increasing their reliability. contrary to verification frameworks previously proposed for business processes, verbus is a modular an extensible framework, in the sense that it is not tied to specific process definition languages or verification tools. this is achieved with the definition of an intermediate formalism that disconnects definition languages from verification tools. in this paper we present verbus, and its prototype, that integrates the bpel4ws definition language and the spin and smv verification tools.
solving the error correcting code problem with parallel hybrid heuristics. some telecommunication systems can not afford the cost of repeating a corrupted message. instead, the message should be somewhat "corrected" by the receiver. in these cases an error correcting code is suitable. the problem of finding an error correcting code of n bits and m codewords that corrects a given maximum number of errors is np-hard. for this reason the problem has been solved in the literature with heuristic techniques such as simulated annealing and genetic algorithms. in this paper we present a new local search algorithm for the problem: the repulsion algorithm. we further use a hybrid between parallel genetic algorithm and this new algorithm to solve the problem, and we compare it against a pure parallel genetic algorithm. the results show that an important improvement is achieved with the inclusion of the repulsion algorithm and the parallelism.
volume fractal dimensionality: a useful parameter for measuring the complexity of 3d protein spatial structures. a quantitative measure for estimating the complexity of 3d protein is proposed. the measurement is based on the fractal features of protein structures. a practical method for evaluating the volume fractal dimensionality (vfd) is described. our investigations on large data sets from pdb show that similar protein shapes have close vfd and vfd may therefore be used as a token of evolutional proteins, and for protein prediction.
agent technology for personalized information filtering: the pia-system. as today the amount of accessible information is overwhelming, the intelligent and personalized filtering of available information is a main challenge. additionally, there is a growing need for the seamless mobile and multi-modal system usage throughout the whole day to meet the requirements of the modern society ("anytime, anywhere, anyhow"). a personal information agent that is delivering the right information at the right time by accessing, filtering and presenting information in a situation-aware matter is needed. applying agent-technology is promising, because the inherent capabilities of agents like autonomy, pro- and reactiveness offer an adequate approach. we developed an agent-based personal information system called pia for collecting, filtering, and integrating information at a common point, offering access to the information by www, e-mail, sms, mms, and j2me clients. push and pull techniques are combined allowing the user to search explicitly for specific information on the one hand and to be informed automatically about relevant information divided in pre-, work and recreation slots on the other hand. in the core of the pia system advanced filtering techniques are deployed through multiple filtering agent communities for content-based and collaborative filtering. information-extracting agents are constantly gathering new relevant information from a variety of selected sources (internet, files, databases, web-services etc.). a personal agent for each user is managing the individual information provisioning, tailored to the needs of this specific user, knowing the profile, the current situation and learning from feedback.
specification and verification of agent interaction protocols in a logic-based system. in multiagent systems, agent interaction is ruled by means of interaction protocols. compliance to protocols can be hardwired in agent programs; however, this requires that only "certified" agents interact. in open societies, composed of autonomous and heterogeneous agents whose internal structure is, in general, not accessible, interaction protocols should be specified in terms of the agent observable behaviour, and compliance should be verified by an external entity.in this paper, we propose a java-prolog-chr system for verification of compliance of agents' behaviour to protocols specified in a logic-based formalism (social integrity constraints). we also present the application of the formalism and the system to the specification and verification of the fipa contract-net protocol.
hybridizing hierarchical and weighted linguistic rules. in this paper, we propose the hybridization of both hierarchical and weighted linguistic fuzzy rules to derive hierarchical systems of weighted linguistic rules. to do so, an evolutionary optimization process jointly performing a rule selection and the derivation of rule weights is developed.
pocket pc beacons: wi-fi based human tracking and following. the network-centric applied research team (n-cart) is continuing its work on an ambitious project known as the network-enabled powered wheelchair adaptor kit (nepwak) [25]. it introduces techniques for modifying and using powered wheelchairs as mobile platforms enabling communication and remote control. the wheelchair runs a pc104 based embedded server allowing both pc and pocketpc clients to connect in either infrastructure or ad-hoc mode. the clients receive audio, video and other sensory feedback from the wheelchair and can send control data for maneuvering the wheelchair. in this paper we present our preliminary work on a novel, inexpensive and coarse 'human tracking and following' system for nepwak. our approach uses a custom built highly directional steerable wi-fi antenna on the wheelchair that scans the wi-fi signal strength of its peer. this can be used to track and follow a person carrying a wi-fi enabled pocketpc.
realizing the leasing concept in corba-based applications. although in recent years the concept of leasing has become more and more popular in the field of distributed object-oriented systems, it has not yet been incorporated in the current specification of the widespread corba standard.in this paper, we present an approach to the problem of realizing the leasing concept in a corba environment. we examine different leasing variants, such as exclusive or shared leasing, leasing with or without prolongation, etc., describe different ways to implement these variants in corba, e.g., based on a specialized object adapter, a runtime library or framework, or a corba service, and we discuss the advantages and disadvantages of each approach.furthermore, we show how existing corbaservices such as naming, trading, and property service can benefit from leasing facilities. finally, we briefly present some architectural details of our own implementation of an exemplary corba leasing service.
evaluation of a language identification system for mono- and multilingual text documents. language identification is an important task for web information retrieval. this paper presents the implementation of a tool for language identification in mono- and multi-lingual documents. the tool implements four algorithms for language identification. furthermore, we present a n-gram approach for the identification of languages in multi-lingual documents. an evaluation for monolingual texts of varied length is presented. results for eight languages including ukrainian and russian are presented. it could be shown that n-gram-based approaches outperform word-based algorithms for short texts. for longer texts, the performance is comparable. the evaluation for multi-lingual documents is based on real world web documents. our tool is able to recognize the languages present in a document with reasonable accuracy.
viewpoint motion control by body position in immersive projection display. we have developed a vision-based interface based on body position for viewpoint control in an immersive projection display. the 3d position of the arms and head of the user are tracked by image processing without the need to attach devices to the user. this provides freedom of movement and increases the immersion in the virtual environment. images are captured using two high-sensitivity monochrome cameras suitable for the dark condition in the projection display. the edges of both hands and the top of the head are tracked in order to control the user's viewpoint by estimating the variance of the position. we evaluated the utility of the interface in an experiment where subjects performed walk-through trials in 3d space, comparing the body-position interface with a joystick. the results indicate that the performance of the body-position interface is comparable to that of the joystick in terms of viewpoint control, but enhances the sensation of speed. the developed system is applicable as a non-contact user interface for moving around in a virtual environment.
symbol representation in map image compression. we propose map image compression system, in which we separate text and symbol information from the rest of the data. the text and other symbols are stored as one bitmap for each symbol into a dictionary. the technical challenge of the work is to convert the symbol data directly to output format similar to that of the jbig2 standard. in this way, the text elements and special symbols are compressed more efficiently but we still have the maps in compatible raster image format.
where web engineering tool support ends: building usable websites. in this paper, two of the currently available web engineering solutions (uwe and oo-h) are analysed with regard to the question whether websites created with them and their tools have a high usability. additionally, the respective models are examined to see whether usability aspects can be expressed with them. in a small case study, an example website is created by converting a model to an implementation manually. special attention is paid to usability issues regarding both the generated pages and the development process. subsequently, the manual conversion is compared to a tool-supported process.
optimizing existential queries in stratifiable deductive databases. we reconsider query evaluation in stratifiable deductive databases using magic sets. on the basis of the soft stratification approach, a new solution to the problem of optimizing existential queries in a set-oriented database language like datalog is presented. to this end, the query answering process is optimized in such a way that after the generation of one appropriate answer fact with respect to a (derived) existential query, the redundant computations of alternative answer facts are avoided. the same technique can be employed for avoiding the generation of subsumed answers and sub-queries as well. it is shown that in presence of recursion or stratified negation this may considerably reduce the total number of facts generated.
towards low-perturbation anonymity preserving pattern discovery. it is generally believed that data mining results do not violate the anonymity of the individuals recorded in the source database. in fact, data mining models and patterns, in order to ensure a required statistical significance, represent a large number of individuals and thus conceal individual identities: this is the case of the minimum support threshold in association rule mining. we have recently shown [3], that the above belief is ill-founded: by shifting the concept of k-anonymity [8] from data to patterns, we have formally characterized the notion of a threat to anonymity in the context of frequent itemsets mining, and provided a methodology to efficiently and effectively identify such threats that might arise from the disclosure of a set of frequent itemsets. in our previous paper [2] we have introduced a first, na&iuml;ve strategy (named suppressive) to sanitize such threats. in this paper we develop a novel sanitization strategy, named additive, which outperforms the previous one in terms of the introduced distortion and has the interesting feature of maintaining the original set of frequent itemsets unchanged, while modifying only the corresponding support values.
an information retrieval model using the fuzzy proximity degree of term occurences. based on the idea that the closer the query terms in a document are, the more relevant this document is, we propose a mathematical model of information retrieval based on a fuzzy proximity degree of term occurences. our model is able to deal with boolean queries, but contrary to the traditional extensions of the basic boolean information retrieval model, it does not explicitly use a proximity operator. a single parameter allows to control the proximity degree required. with conjunctive queries, setting this parameter to low values requires a proximity at the phrase level and with high values, the required proximity can continuously be relaxed to the sentence or paragraph levels. we conducted some experiments and present the results.
design and implementation of a graphical interface to xquery. as the use of xml is rapidly growing, a growing number of users without programming skills will need to query xml data. although designed to be easily understood by humans, xquery, the xml standard query language, has the typical syntax of programming languages, which most users dislike. in this paper we describe a graphical language (xqbe) inspired by "query by example" (qbe), a popular relational query language used by ms access. xqbe covers a significant subset of xquery and is supported by a prototype enabling the formulation of queries on a graphical interface and their translation into xquery, thus providing non-trivial querying capabilities to a wide spectrum of users. simple queries are easily represented in xqbe, but many "complex" queries allow as well for an intuitive graphical representation.
multi-heuristic list scheduling genetic algorithms for task scheduling. scheduling tasks on a multi-processor system involves making a choice as to the order in which several tasks can be executed and assigned to processors. the problem is to find a schedule that will minimize the execution time of a program. because task scheduling on a multi-processor system is known to be an np-complete problem, many heuristics have been developed, each of which may find optimal or near optimal schedulings under different circumstances. list scheduling, in particular, employs heuristics to choose among all tasks that are ready to be executed, the combination of tasks that should be scheduled in the next cycle. it does this by keeping a list of "ready" tasks which is prioritized based on a particular heuristic. in this paper, we present four common heuristics used by list scheduling and compare their performance with that of our multi-heuristic based solution.the proposed solution is to use a genetic algorithm to find a combination of the four heuristics that, for a particular instance of the task scheduling problem, outperforms a scheduling based on only one of the four heuristics. we believe that, by using a mixture of the four heuristics, the size of the subset of all possible schedulings that we search increases and thus we have a higher chance of finding a better scheduling. the results of our experiments show that schedulings found with the proposed multi-heuristic list scheduling genetic algorithm outperforms those found with each one of the four list scheduling heuristics alone.
editorial message for the special track on embedded systems: applications, solutions, and techniques. recently, demand for high performance embedded computing has experienced an impressive growth. at the same time, embedded software has become more and more complex, posing new challenging issues never faced before in this application field. the need to timely tackle changes in the market pushes toward the employment of methodologies for shortening the development time and for driving the evolution of existing products. furthermore, the adoption of solutions already established in other areas of computer science (such as java technologies) can be made viable only through specific re-engineering processes. the solutions to new problems emerging in this setting call for a joint effort by academia and industry.
the agent-based programming language: apl. agent-based programming has been emerged as a new programming paradigm for the near future. there have been many research work in agent computing. however, the software engineering methodology and programming languages for agent computing are not yet sufficient and practical.this paper proposes a new programming language concept based on the bdi-agent model. the new concept has been prototyped by agent-based programming language (apl). the prototype system for apl translates the apl source into the java source codes, which can be run on the java virtual machine. this paper also describes our implementation scheme of the apl system. examples are also shown to utilize apl for the real-world banking application.
expanding domain-specific lexicons by term categorization. we discuss an approach to the automatic expansion of domain-specific lexicons by means of term categorization, a novel task employing techniques from information retrieval (ir) and machine learning (ml). specifically, we view the expansion of such lexicons as a process of learning previously unknown associations between terms and domains. the process generates, for each ci in a set c = {c1,..., cm} of domains, a lexicon li1, boostrapping from an initial lexicon li0 and a set of documents &theta; given as input. the method is inspired by text categorization (tc), the discipline concerned with labelling natural language texts with labels from a predefined set of domains, or categories. however, while tc deals with documents represented as vectors in a space of terms, we formulate the task of term categorization as one in which terms are (dually) represented as vectors in a space of documents, and in which terms (instead of documents) are labelled with domains.
editorial message for the special track on embedded systems: applications, solutions, and techniques. embedded systems can be regarded today as one of the most lively research and industrial targets. in this field, the ever-increasing demand for computing power and any sort of system resources continuously challenges state-of-the-art design methodologies and development techniques. the largest part of the most complex issues to be addressed during design and development phases can be related to the need to compromise among tight constrains on performance, memory size, code size, power consumption, appliance weight and dimension, possible real-time behaviors, maintainability, scalability, security, time-to-market and, last but not indubitably least, cost. the designer is continuously challenged by requirements modifications that must be timely addressed, operating at different levels of abstraction, e.g. from the proper adjustment of cpu internals to the scheduler structuring in rtoss, from the optimized exploitation of i/o devices to the employment of specialized compilation techniques. suitable solutions to emerging problems in this application field can be found via a joint effort by academia and industry.
editorial message: special track on the programming languages and object technologies. for the sac 2002, in the programming languages and object technologies track, papers were invited to address a wide range of topics from programming languages and object technologies. these included automatic programming, compiling techniques, domain-specific programming languages, formal semantics, meta and higher-order programming, new programming paradigms, practical experiences with programming languages, language design and implementations, security issues, standardization of languages, object-oriented programming languages and applications, object-oriented design and analysis, distributed object systems and architectures, languages for distributed object systems, quality of service in open environments, component-based software design, corba, rmi, dcom and related middleware, applications of distributed object computing, design patterns, and testing of object-oriented software. the call for papers was distributed through newsgroups, public and private mailing lists.
experimental aspect-oriented language - aspectcool. aspect-oriented programming (aop) is a programming technique for modularizing concerns that crosscut the basic functionality of programs. in aop, aspect languages are used to describe properties, which crosscut basic functionality, in a clean and a modular way. aop is currently supported mostly by aspect weavers, which require a source code for both components and aspects in order to create the final program. in this paper we have presented our approach to aspect weaving in order to achieve separate compilation. this approach to aspect weaving is used in the languages cool and aspectcool, which are also presented in the paper. with this approach it is possible to apply aspects on already compiled components.
evolution of business processes towards ebusiness using a critiquing approach. innovating the business processes of an enterprise requires their preliminary analysis and assessment. in particular, information on the performance and costs of activities and processes must be gathered in order to identify candidates for innovation. a critical point is finding suitable presentation means of the gathered data in order to support effectively the decision makers. this paper presents a strategy and supporting tools for business process innovation. the strategy integrates measurement, decision making, and critiquing techniques, for analyzing business processes, identifying activities and software systems that are candidate to innovation, and mapping critiques onto specific innovation actions. the strategy is supported by a toolkit, named webev+, that integrates the webev environment [2], for managing the assessment and evaluation tasks, and argouml [1], for modeling and critiquing business processes.
analysis of deployment dependencies in software components. administration and deployment of software systems become increasingly complex. this complexity results from the need of uniform access to applications from heterogeneous terminals through different communication infrastructures. moreover, applications consists in complex architectures of lot of small components connected together. a first step to simplify deployment is to have an unified and abstract model for representing deployment dependencies and managing them properly. therefore, we propose here a deployment model and a conceptual foundation for component installation. installation dependencies and installation rules are expressed in a logic language.
assessment and impact analysis for aligning business processes and software systems. business processes and existing software systems must be aligned so that software systems can adequately support the business processes in order to be effectively used within them. the alignment characteristic needs to be considered even during the execution of an evolution process. in particular, a strict relationship exists between the evolution of a legacy system and that of the supported business process. therefore, the requirements for evolving a software system embedded in a business process are to be defined on the basis of the change needing to be performed on the process activities. in fact, any modification performed in the business process activities and/or supporting software system may impact the process activities in terms of input/output and/or purpose of the software system and, therefore, cause misalignment. a coarse grained strategy is proposed for detecting misalignment between software systems and supported business processes when a change is executed. in addition, the strategy supports the identification of all the objects, either software system components or process activities, affected by a change and needing to be considered during the evolution process, for keeping the alignment and ensuring the technological support to the business process. the strategy proposes the exploitation of quality parameters, for codifying the alignment concept, and impact analysis techniques, for propagating the change and identifying all the objects affected by a change and requiring new evolution interventions.
interactive simulation of security policies. a general framework for simulating security policies interactively is developed by asms (gurevich's abstract state machines) and then mechanised by the asm workbench. the asm external functions make it possible to simulate under the environmental influence the behaviour of a policy. the interactive features of the workbench allow the simulation of the policy norms that apply to a given case study, facilitating their understanding. possible inconsistencies affecting the case study can be automatically detected during the simulation and widely documented. the framework is demonstrated on a published, example security policy. the findings support the claim that adding priorities to roles achieves the crucial goal of consistency.
a trust-enhanced recommender system application: moleskiing. recommender systems (rs) suggests to users items they will like based on their past opinions. collaborative filtering (cf) is the most used technique to assess user similarity between users but very often the sparseness of user profiles prevents the computation. moreover cf doesn't take into account the reliability of the other users. in this paper we present a real world application, namely moleskiing.it, in which both of these conditions are critic to deliver personalized recommendations. a blog oriented architecture collects user experiences on ski mountaineering and their opinions on other users. exploitation of trust metrics allows to present only relevant and reliable information according to the user's personal point of view of other authors trustworthiness. differently from the notion of authority, we claim that trustworthiness is a user centered notion that requires the computation of personalized metrics. we also present an open information exchange architecture that makes use of semantic web formats to guarantee interoperability between ski mountaineering communities.
availability of protocol goals. a new principle for prudent design of security protocols is developed to extend and complement the existing ones. called goal availability, the principle requires that a given protocol goal be confirmed by a formal guarantee that the principals can invoke in practice. in consequence, the guarantees must be based on assumptions that the principals are able to verify. analysing known protocols in the light of the new principle highlights unknown features. for example, an established ban-logic claim is undermined, and some weaknesses of a modern smart card protocol are discovered. our findings support the general claim that checking a protocol against goal availability helps discover unspotted lacks of explicitness in the protocol messages. the protocol analyses reported here are all machine assisted, but goal availability serves for protocol analysis in general.
applications of finite fields to dynamical systems and reverse engineering problems. we present a mathematical model: dynamical systems over finite sets (dsf), and we show that boolean and discrete genetic models are special cases of dfs, [1, 4, 10].in this paper, we prove that a function defined over finite sets with different number of elements can be represented as a polynomial function over a finite field. given the data of a function defined over different finite sets, we describe an algorithm to obtain all the polynomial functions associated to this data. as a consequence, all the functions defined in a regulatory network can be represented as a polynomial function in one variable or in several variables over a finite field. we apply these results to study the reverse engineering problem.
editorial message: special track on computer security. the proliferation of network computing and especially the ubiquity of the internet has made security one of the key areas in modern computing. this track aims at bringing together researchers working on applied issues in computer and information security, ranging from protocols and tools to policy and laws.security is a multidisciplinary topic related to almost every aspect of computer science. from information security to mobile computation, from artificial intelligence to wireless communication, it is difficult to find a computer science area that is not concerned with security directly or indirectly.the computer security track in the 2002 symposium on applied computing is a demonstration of the diversity. the track focus is on practical (applied) aspects of computer security so as to fit well with the general objectives of the symposium.
editoral message: special track on computer security. the security track, currently in its fifth edition, continues to raise large interest. this year's success is in large part due to the efforts of the expanded program committee, composed of 19 leading researchers coming from academia and industry:&bull; gail-joon ahn (university of north caroline at charlotte, usa)&bull; arslan br&ouml;mme (university of magdeburg, germany)&bull; david w chadwick (university of salford, uk)&bull; bruce christianson (university of hertfordshire, uk)&bull; nancy durgin (sandia national laboratories, usa)&bull; simon foley (university college cork, ireland)&bull; c&egrave;dric fournet (microsoft research cambridge, uk)&bull; dieter gollmann (technical university hamburg, germany)&bull; stefanos gritzalis (university of the aegean, greece)&bull; peter honeyman (university of michigan, usa)&bull; sokratis k katsikas (university of the aegean, greece)&bull; helmut kurth (atsec, germany)&bull; volkmar lotz (sap research, france)&bull; heiko mantel (rwth aachen university, germany)&bull; chris mitchell (royal holloway university of london, uk)&bull; david von oheimb (siemens ct ic, germany&bull; pierangela samarati (universit&aacute; di milano, italy)&bull; vitaly shmatikov (sri international, usa)&bull; kymie tan (carnegie-mellon university, usa)
analytical modelling of priority commit protocol for reliable web applications. web applications are vulnerable to failures and low performance due to the large population of users and the widespread distribution of internet. transaction technology provides web applications with high reliability and improved performance. this paper presents a novel approach for the efficient commit processing of web transactions. the proposed approach is based on the implementation of priority active network scheduling mechanism at each network node. it involves rigorous analysis of a network node with-finite capacity to accommodate messages, bursty arrival process to represent incoming multi-class messages, and the employment of a priority scheduling mechanism to give preferential treatment to high priority messages. this analytical solution provides closed from expressions for calculating the queuing delay per class involved in the commit processing of web transactions at each network node. the proposed approach significantly reduces the queuing delay for high priority messages such as commit, abort, and compensation of web transactions. consequently, performance of the commit processing of web transactions is improved as response time of the nodes responsible for making decision is reduced.
special track on computer security. the increasing importance of information security to society in the 21st century is widely acknowledged. this is reflected by the growing interest in the security track, which is now in its fourth edition. this year's success is in large part due to the efforts of the expanded program committee, composed of 18 leading researchers coming from academia and industry.
efficient comparison of enterprise privacy policies. enterprise privacy policies often reflect different legal regulations, promises made to customers, as well as more restrictive enterprise-internal practices. the notion of policy refinement is fundamental for privacy policies, as it allows one to check whether a company's policy fulfills regulations or adheres to standards set by customer organizations, to realize the "sticky policy paradigm" that addresses transferring data from one realm to another in a privacy-preserving way, and much more. although well-established in theory, the problem of how to efficiently check whether one policy refines another has been left open in the privacy policy literature. we present a practical algorithm for this task, concentrating on those aspects that make refinement of privacy policies more difficult than, for example refinement for access control policies, such as a more sophisticated treatment of deny rules and a suitable way for dealing with obligations and conditions on context information.
editorial message: special track on computer security. the security track, currently in its fifth edition, continues to raise large interest. this year's success is in large part due to the efforts of the expanded program committee, composed of 19 leading researchers coming from academia and industry:&bull; gail-joon ahn (university of north caroline at charlotte, usa)&bull; arslan br&ouml;mme (university of magdeburg, germany)&bull; david w chadwick (university of salford, uk)&bull; bruce christianson (university of hertfordshire, uk)&bull; nancy durgin (sandia national laboratories, usa)&bull; simon foley (university college cork, ireland)&bull; c&egrave;dric fournet (microsoft research cambridge, uk)&bull; dieter gollmann (technical university hamburg, germany)&bull; stefanos gritzalis (university of the aegean, greece)&bull; peter honeyman (university of michigan, usa)&bull; sokratis k katsikas (university of the aegean, greece)&bull; helmut kurth (atsec, germany)&bull; volkmar lotz (sap research, france)&bull; heiko mantel (rwth aachen university, germany)&bull; chris mitchell (royal holloway university of london, uk)&bull; david von oheimb (siemens ct ic, germany&bull; pierangela samarati (universit&aacute; di milano, italy)&bull; vitaly shmatikov (sri international, usa)&bull; kymie tan (carnegie-mellon university, usa)
efficiency of prefix and non-prefix codes in string matching over compressed databases on handheld devices. this paper shows the efficiency of prefix and non-prefix codes for searching over compressed handheld databases. byte pair encoding (bpe), tagged suboptimal code (tsc), and huffman encoding are the compression techniques used in the evaluation. by compressing handheld databases and searching over compressed text without needing to expand the databases, more data will be stored and more applications can be used. experimental results show that about 33% more space has been achieved in the compressed handhelds' databases when using searching over compressed text using bpe (sctb) or searching over compressed text using tsc (sctt) solutions. moreover, both solutions are 6.6 times faster than decompressing the databases followed by a linear search in all different sizes of databases. efficiency performance shows that sctb is the recommended solution for databases consisting of large-sized records and rarely updated, and sctt is the recommended method for frequently updated databases or consisting of small-sized records. tsc and bpe compression schemes could also be used to accelerate wireless connectivity, web clipping, or databases transfer between handheld devices and computers, since these databases are usually small in size.
implementing rule-based mechanisms for agent-based price negotiations. this note describes a sample implementation of automated negotiations in an e-commerce modeling multi-agent system. a specific set of rules is used for enforcing negotiation mechanisms. discussion of system design and implementation using jade and jess is provided. finally, an experiment involving multiple english auctions performed in parallel is discussed.
webuml: reverse engineering of web applications. web applications have become complex and crucial for many firms, especially when combined with areas such as crm (customer relationship management) and bpr (business process reengineering). since then the scientific community has focused attention to web application design, development, analysis, testing, by studying and proposing methodologies and tools. this paper describes an automatic tool for the construction of uml models from existing web applications. this tool, named webuml, generates class and state diagrams by analysing source code and by interacting with the web server. this reverse engineering tool is based on source code static analysis and also applies mutational techniques in order to exploit the server side execution engine to accomplish part of the dynamic analysis. this tool will be the core of a testing suite under construction at our laboratory. webuml generated models (diagrams) will be used as a base for test case generation and coverage analysis.
applying scheduling techniques to minimize the number of late jobs in workflow systems. ordering the cases in a workflow can result in significant decrease on the number of late jobs. but merging workflow and scheduling is not trivial. this paper presents some of the problems of using scheduling results in ordering cases in a workflow and tackles two of them: the uncertainties on the cases' processing times and routing. a new approach to modeling these uncertainties is also proposed: the guess and solve technique. it consists of making a guess on the execution times and routes the case will follow, and solving the corresponding deterministic scheduling problem using a suitable technique, in this paper genetic algorithms. simulation results show that for almost all workloads rules such as earliest due date first, and guess and solve (if the error in guessing is bound by 30%) are statistically significantly better than the commonly used fifo rule regarding the number of late jobs.
testuml: user-metrics driven web applications testing. web applications have become very complex and crucial, especially when combined with areas such as crm (customer relationship management) and bpr (business process reengineering), the scientific community has focused attention to web application design, development, analysis, and testing, by studying and proposing methodologies and tools. this paper describes techniques for semi-automatic test case definition and for user1-driven testing (based on statistical testing or coverage analysis) from web applications reverse engineered uml models. these techniques are implemented as tools in the waat project. webuml is a reverse engineering tool that generates class and state diagrams through static and dynamic web application analysis. testuml is a testing suite that uses generated models to define test cases, coverage testing criteria and also reliability analysis.
drc4.5: improving c4.5 by means of prior knowledge. classification is one of the most useful techniques for extracting meaningful knowledge from databases. classifiers, e.g. decision trees, are usually extracted from a table of records, each of which represents an example. however, quite often in real applications there is other knowledge, e.g. owned by experts of the field, that can be usefully used in conjunction with the one hidden inside the examples. as a concrete example of this kind of knowledge we consider causal dependencies among the attributes of the data records. in this paper we discuss how to use such a knowledge to improve the construction of classifiers. the causal dependencies are represented via bayesian causal maps (bcms), and our method is implemented as an adaptation of the well known c4.5 algorithm.
a multi-criteria model for electronic auctions. in this paper we present a multi-criteria model for electronic auctions, which is based on reference points. according to the model, the buyer must specify an aspiration point that expresses his desired values on the attributes of the item to be purchased and a reservation point that represents the minimal values required. negotiation takes place between software agents that negotiate on behalf of their human owners. the multi-criteria model allows the buyer agent to control the negotiation process on each attribute of the deal. we illustrate the use of this model by providing an auction mechanism based on an english reverse auction protocol.
an evaluation of resource description quality measures. an open problem for distributed information retrieval is how to represent large document repositories (known as resources) efficiently. to facilitate resource selection, estimated descriptions of each resource are required, especially when faced with non-cooperative distributed environments[1]. accurate and efficient resource description estimation is required as this can have an affect on resource selection, and as a consequence retrieval quality. query-based sampling (qbs) has been proposed as a novel solution for resource estimation[2], with proceeding techniques developed therafter[3]. however, the challenge to determine if one qbs technique is better at generating resource description than another is still an unresolved issue. the initial metrics tested and deployed for measuring resource description quality were the collection term frequency ratio (ctf) and spearman rank correlation coefficient (srcc)[2]. the former provides an indication of the percentage of terms seen, whilst the later measures the term ranking order, although neither consider the term frequency, which is important for resource selection. we re-examine this problem and consider measuring the quality of a resource description in context to resource selection, where an estimate of the probability of a term given the resource is typically required. we believe a natural measure for comparing the estimated resource against the actual resource is the kullback-leibler divergence (kl) measure. kl addresses the concerns put forward previously, by not over-representing low frequency terms, and also considering term order[2]. in this paper, we re-assess the two previous measures alongside kl. our preliminary investigation revealed that the former metrics display contradictory results. whilst, kl suggested a different qbs technique than that prescribed in [2], would provide better estimates. this is a significant result, because it now remains unclear as to which technique will consistently provide better resource descriptions. the remainder of this paper details the three measures, the experimental analysis of our preliminary study and outlines our points of concern along with further research directions.
on using oo techniques to establish workflow conformance. workflow schema are constantly changing [6][7] driven by new customer requirements or business processes re-engineering. schema evolution is less of a problem when no work-flow is active, which could be achieved by waiting until all workflows are terminated, or by aborting active ones. these are however not viable solutions, because workflows can be of long duration and comprise considerable amounts of work. this results in a number of variants that may become problematic to manage especially when creating new instances of the schema. however, many of these variants can be merged together to reduce the number of templates to choose from while instantiating a new workflow instance. merging can be accomplished only when two workflows are compatible or conformant. in this effort we aim at solving the problem of defining workflow conformance using oo concepts of inheritance and merging conformant workflows.the rest of this paper is organized as follows. we first formulate the problem and then present our solution which is based on task inheritance. we finally present some conclusions and opportunities for future work.
xspace: a tuple space for xml & its application in orchestration of web services. today's extended enterprise calls for the integration of several disparate systems built using multiple technologies and executing across firewall boundaries. the integration is usually done in the context of workflow orchestration and in its current incarnation, this extends across multiple enterprises over the internet. given the disparity of these systems that need to be integrated in the workflow, these systems are usually exposed as web services to bring about a common denominator. by implication, there is a need to transfer xml documents asynchronously from one system to another since xml is the language of web service interaction. an ideal way to accomplish this asynchronous interaction is to use the concept of tuple spaces which provide a distributive, associative shared memory concept. usually tuple spaces have dealt with the either simple types or language specific objects as tuple attributes and do not span enterprise boundaries but our need for exchanging xml documents over the internet forces us to reconsider how spaces are architected. in this paper, we present xspace - a tuple space that deals with xml documents natively and is distributed across the internet. we also show how it can serve as a vehicle to orchestrate web services by providing an asynchronous interaction paradigm.
a robust deception-free coalition formation model. we study two properties of coalition formation algorithms, very important for their application in real-life scenarios: robustness and tolerance to some agent misbehaviors. the study is performed for a previously proposed coalition formation model-based upon game theory for a class of task-oriented problems that guarantees an optimum task allocation and a stable (fair) profit division. the results show acceptable behavior and performance.
agent coordination for bus fleet management. this paper presents an abstract multiagent architecture useful for decision support systems (dss), and shows how this architecture can be instantiated to a particular real-world domain, bus fleet management (bfm). after discussing the benefits of adopting a multiagent approach for dss, the paper introduces the real world case study and analyzes it. next, an abstract mas architecture for dss in general, and specialized then for bfm case study is presented. the architecture includes a set of different agents which are in charge of different social roles, and what is needed for their coordination, the coordination facilitator and the coordination protocols. the paper is concentrated in this point showing a concrete example in the bfm domain.
sf-hme system: a hierarchical mixtures-of-experts classification system for spam filtering. many linear statistical models have been lately proposed in text classification related literature and evaluated against the unsolicited bulk email filtering problem. despite their popularity - due both to their simplicity and relative ease of interpretation - the non-linearity assumption of data samples is inappropriate in practice, due to its inability to capture the apparent non-linear relationships, which characterize these samples. in this paper, we propose the sf-hme, a hierarchical mixture-of-experts system, attempting to overcome limitations common to other machine-learning based approaches when applied to spam mail classification. by reducing the dimensionality of data through the usage of the effective simba algorithm for feature selection, we evaluated our sf-hme system with a publicly available corpus of emails, with very high similarity between legitimate and bulk email - and thus low discriminative potential - where the traditional rule based filtering approaches achieve considerable lower degrees of precision. as a result, we confirm the domination of our sf-hme method against other machine learning approaches, which appeared to present lesser degree of recall.
powerjava: ontologically founded roles in object oriented programming languages. in this paper we introduce a new view on roles in object oriented programming languages, based on an ontological analysis of roles. a role is always associated with an object instance playing the role and also to an object instance (its institution) which represents its context. the definition of a role depends on the definition of the institution. this property allows to endow role-players with powers that can modify the state of the institution and of the other roles defined in it. as an example, we introduce a role construct in java, where the abolve features are interpreted as follows. roles are implemented as classes, which can be instantiated only in presence of an instance of the player and of an instance of an institution. the definition of a class implementing a role is included in the class of the institution, the role belongs to. powers are methods which can access private fields and methods of the institution they belong to, and of the other roles of the same institution.
adaptive resolution modeling of regional air quality. we discuss an adaptive resolution system for modeling regional air pollution based on the chemical transport model stem. the grid adaptivity is implemented using the generic tool paramesh, which enables the grid management operations while harnessing the power of parallel computers. the computational algorithm is based on a decomposition of the domain, with the solution in different sub-domains being solved at different spatial resolutions. numerical experiments confirm that adaptive resolution leads to the decrease in spatial error with an acceptable increase in computational time. advantages and shortcomings of the present approach are also discussed.
management of unspecified semi-structured data in multi-agent environment. amounts of available heterogeneous semi-structured data grow rapidly on the web and other data repositories. this raises the need to provide simple and universal ways to access this data. to provide such an interface, we propose to exploit the notion of "unspecified ontologies", describing the data objects as a list of attributes and their respective values. in order to facilitate an efficient management of the unspecified data objects we use a multi-agent channeled multicast communication platform. the data objects are stored distributively, such that each attribute is assigned a designated channel. this allows performing efficient searches by parallel querying of the relevant channels only, and aggregating the partial results. moreover, the multi-agent platform facilitates advanced data management through extracting metadata from the data objects. we implemented a prototype system and experimented with a corpus of real-life e-commerce advertisements. our results demonstrate scalability of the proposed approach and the accuracy of the extracted meta-data.
advanced model transformation language constructs in the viatra2 framework. we present the model transformation language of the viatra2 framework, which provides a rule and pattern-based transformation language for manipulating graph models by combining graph transformation and abstract state machines into a single specification paradigm. this language offers advanced constructs for querying (e.g. recursive graph patterns) and manipulating models (e.g. generic and meta transformation rules) in unidirectional model transformations frequently used in formal model analysis to carry out powerful abstractions. in addition, powerful language constructs are provided for multi-level metamodeling to design modeling languages and template-based code generation.
a distributed stand-in agent based algorithm for opportunistic resource allocation. mobile ad-hoc networks (manet) are expected to form the basis of future mission critical applications such as combat and rescue operations. in this context, communication and computational tasks required by overlying applications will rely on the combined capabilities and resources provided by the underlying network nodes. this paper introduces an integrated flexfeed/a-globe technology and distributed algorithm for opportunistic resource allocation in resource-and policy-constrained mobile ad-hoc networks. the algorithm is based on agent negotiation for the bidding, contract and reservation of resources, relying primarily on the concept of remote presence. in the proposed algorithm, stand-in agents technology is used to create a virtual, distributed co-ordination component for opportunistic resource allocation in mobile ad-hoc networks.
compiling model transformations to ejb3-specific transformer plugins. we present a technique for compiling model transformations defined by a combination of graph transformation and abstract state machine rules (as used within the viatra2 framework) into stand-alone transformer plugins for the ejb 3.0 platform. as a result, the design of transformations can be separated from the execution of transformations. this also enables to run viatra2 model transformations on very large models stored in underlying relational databases or to integrate such transformations into existing business applications.
prediction of inherited and genetic mutations using the software model checker spin. genetic testing is becoming an important tool for detection of many genetic diseases. designing a genetic test requires accurate data and an efficient means of comparing sequences that are present in the databases. however, as prodigious amount of data continue to emerge, querying the database to make important predictions is becoming arduous. it is essential that better tools be designed to analyze these data. in this paper, a model-based approach to gene tests and the analysis of metabolic pathways is proposed. gene sequences and metabolic processes are modeled using formal language, and predictions are made through the verification mechanism of a software model checker. the technique is demonstrated with models of genes for cystic fibrosis tranmembrane conductance regulator protein and the map kinase pathway.
a product line architecture for web applications. increasingly, web applications are used in similar environments to fulfill similar tasks. sharing a common infrastructure and reusing assets to deploy recurrent services may be considered an advantage in terms of economic significance and overall quality. thus, it may be appropriate to design web applications as members of a product family.the paper illustrates koriandol, a product-line architecture designed to develop, deploy and maintain web application families. in contrast with usual component-based systems, koriandol prescribes that variability handling mechanisms are reflective and built-in into the components.
a framework for the classification and the reclassification of electronic catalogs. electronic marketplaces are virtual communities where buyers may meet proposals of several suppliers and make the best choice. the exponential increment of the e-commerce amplifies the proliferation of different standards and joint initiatives for the classification of products and services. therefore, b2b and b2c marketplaces have to classify products and goods according to different product classification standards. in this paper, we propose a framework to classify and reclassify electronic catalogs based on a semi-automatic methodology to define semantic mappings among different product classification standards and catalogs.
a secure method for signature delegation to mobile agents. this paper presents a novel method that allows the delegation of signature power to one or more entities that jointly play the role of a proxy signer. this work is different from other related proxy signature schemes in that in addition to providing confidentiality protection to the proxy key, the method provides non-repudiation services to all the parties involved. in particular, it protects against repudiation of signature delegation by the original signer, repudiation of proxy signature generation by the proxy signer, and repudiation of receipt of the proxy signature by the signature recipient. this feature is attractive for signature delegation in agent-based paradigm in which proxy signers are mobile agents that are executed in remote untrustworthy hosts.
impact of peer incentives on the dissemination of polluted content. recent studies have reported a new form of malicious behavior in file-sharing peer-to-peer systems: content pollution. the dissemination of polluted content in a p2p system has the detrimental effect of reducing content availability, and ultimately, decreasing the confidence of users in such systems. two potential strategies for polluting p2p content are decoy insertion, which consists of injecting corrupted copies of a file into the system, and hash corruption, which consists of injecting a corrupted file with the same hash code as a non-corrupted one. polluted content disseminates through p2p networks because users typically do not delete the corrupted files that they download.this paper investigates the effectiveness of peer incentives to delete corrupted files in reducing the dissemination of polluted content, considering the two aforementioned pollution mechanisms. our simulation results show that the effectiveness of incentives is highly dependent on the pollution mechanism. we show that for a pollution dissemintation techinique called hash corruption, only effective incentive mechanisms are able to avoid spreading of polluted content.
towards chemical coordination for grids. in [6], ian foster and karl kesselman explain that grids need "a rethinking of existing programming models and, most likely, new thinking about novel models". in this work, we investigate a "novel programming model" for grids based on the chemical metaphor.
profile and context filtering of streaming data for a mobile personal assistant. a key component in an ubiquitous computing environment is a personal assistant that can provide a link between devices and services and a human user. a large part of interactions in such an environment is expected to be using xml data. in this paper we present the use of profiles and context to obtain useful information from streaming documents. the user profile contains all the preferences and information on typical behavior for the user. this information can be entered by the user and learned over time. as the profile is never shared or transmitted, strict user privacy is maintained. context information includes current day and time, and the user's location. we have implemented our ideas in an intelligent personal assistant, ipa, within the context of mobile commerce.
a multi-agent system for remote psychological profiling with role playing games based tests. this paper describes a web-based computer system to support psychological evaluation for employee selection or assessment. candidate profiling is based on jungian psychology and the theory of archetypes. the test is proposed to the candidate in the form of a role playing game session to avoid repetitiveness and predictability, and therefore to increase its effectiveness. the profiling engine is a multi-agent system that dynamically builds the test, basing on the candidate's behaviour and on the kind of job he is being tested for, choosing between available story modules. information about psychological model, scenographic modules and operative data is stored in a object oriented dbms. the system provides a remote test interface for candidates and configuration tools as well.
three approaches to the coordination of multiagent systems. the engineering of the social aspects has been acknowledged as one of the principal issues in the realization of real-world multiagent systems. the literature proposes a number of solutions to this problem and in this paper we consider three of them and we discuss their relationships. first, we take into account hybrid coordination models based on tuple centres. then, we consider interaction protocols as a means to coordinate multiagent systems. finally, we address the implicit coordination that the semantics of classic agent communication languages propose. we base our discussion on the common ground of coordination models and we sketch a comparison between such approaches.
exploiting partial decision trees for feature subset selection in e-mail categorization. in this paper we propose partfs which adopts a supervised machine learning algorithm, namely partial decision trees, as a method for feature subset selection. in particular, it is shown that an aggressive reduction of the feature space can be achieved with partfs while still allowing for comparable classification results with conventional feature selection metrics. the approach is empirically verified by employing two different document representations and four different text classification algorithms that are applied to a document collection consisting of personal e-mail messages. the results show that a reduction of the feature space in the magnitude of ten is achievable without loss of classification accuracy.
a geolibrary for multimedia data sets: design and implementation issues. this paper describes the design and implementation issues of the steplib geolibrary. steplib aims to manipulate both spatiotemporal and multimedia data. currently, the steplib model supports maps, still images, video, audio and documents, as first class objects. this allows not only for the support of storage and presentation capabilities, but also for indexing and searching of these complex data types. metadata are used in the model to represent semantic abstraction of the underlying geo-objects, based on different layers of abstraction. spatiotemporal operations are performed at various levels, and data type specific operations are available for improving searching on multimedia data.
organizational engineering in public administrations: a method for process-oriented egovernment projects. in the move of egovernment, process analysis and optimization of administrative procedures are key prerequisites for successful organizational and technical re-structuring of municipal administrations. the full exploitation of the potential of information and communications technology can only be achieved through structured procedures. an integrated process view, which gives an overview of organization units, is vital in the context of any attempts at administration modernization. the high degree of complexity of process models, resulting from the multitude of modelling aims, objects, methods and users, requires both systematic preparation, and a methodical approach to the implementation of process-oriented e-government projects. therefore this article provides a procedure model for process-oriented organizational engineering, with reference to the example of local government building permission procedures.
a privacy preserving web recommender system. in this paper we propose a recommender system that helps users to navigate though the web by providing dynamically generated links to pages that have not yet been visited and are of potential interest. to this end, traditional recommender systems use web usage mining (wum) techniques in order to automatically extract knowledge from web usage data. thanks to wum techniques we are able to classify users and adaptively provide useful recommendations. the drawback of a user classification approach is that it makes the system prone to privacy breaches.our contribution here is &pi;suggest, a privacy enhanced recommender system that allows for creating serendipity recommendations without breaching users privacy. we will show that our system does not provide malicious users with any mean to track or detect users activity or preferences.
cyber-surfing: the state-of-the-art in client server browsing and navigation. modern network technology has spawned an entirely new cybernetic experience: cyberspace surfing. this surfing is as much a social experience as an information gathering resource. while providing the communication infrastructure for an ever-increasing percentage of the global population, it is also becoming the focal point of an identifiable sub-culture of cybernauts who are attracted to the internet as moths to light. there is every indication that the forthcoming cyberspace revolution will have an even more dramatic impact on society than the microcomputer revolution.in this paper we analyze the cyber-surfing experience from the point of view of the supportive client-server technologies involved. on the basis of this analysis and some emerging trends we speculate on the future of cyberspace.
on support thresholds in associative classification. associative classification is a well-known technique for structured data classification. most previous works on associative classification use support based pruning for rule extraction, and usually set the threshold value to 1%. this threshold allows rule extraction to be tractable and on the average yields a good accuracy. we believe that this threshold may be not accurate in some cases, since the class distribution in the dataset is not taken into account. in this paper we investigate the effect of support threshold on classification accuracy. lower support thresholds are often unfeasible with current extraction algorithms, or may cause the generation of a huge rule set. to observe the effect of varying the support threshold, we first propose a compact form to encode a complete rule set. we then develop a new classifier, named l3g, based on the compact form. taking advantage of the compact form, the classifier can be built also with rather low support rules. we ran a variety of experiments with different support thresholds on datasets from the uci machine learning database repository. the experiments showed that the optimal accuracy is obtained for variable threshold values, sometime lower than 1%.
learning query languages of web interfaces. this paper studies the problem of automatic acquisition of the query languages supported by a web information resource. we describe a system that automatically probes the search interface of a resource with a set of test queries and analyses the returned pages to recognize supported query operators. the automatic acquisition assumes the availability of the number of matches the resource returns for a submitted query. the match numbers are used to train a learning system and to generate classification rules that recognize the query operators supported by a provider and their syntactic encodings. these classification rules are employed during the automatic probing of new providers to determine query operators they support. we report on results of experiments with a set of real web resources.
associative text categorization exploiting negated words. associative classification has been recently applied to text document categorization. however, differently from classification of structured data, the quality of the generated classifier is rather low. this effect is mainly due to the poor precision of generated rules.to increase the precision of associative classifiers we propose the use of classification rules including negated words, i.e. words that the considered document should not contain. rules are in the form "if a document includes words a and b, but not word z, then it belongs to class c1". mining classification rules with negated words becomes quickly intractable when decreasing the support threshold. we tackle this problem by means of an opportunistic approach, where negated words are only generated to specialize rules that may wrongly classify training documents. hence precision is increased, without losing recall.experiments on the reuters corpus show that our classifier based on negated words achieves good precision and recall results, while yielding an easily interpretable model typical of associative classifiers.
imprecise rdql: towards generic retrieval in ontologies using similarity joins. traditional semantic web query languages support a logic-based access to the semantic web. they offer a retrieval (or reasoning) of data based on facts. on the traditional web and in databases, however, exact querying often provides an incomplete answer as queries are overspecified or the mix of multiple ontologies/modelling differences requires "interpretational flexibility." therefore, similarity measures or ranking approaches are frequently used to extend the reach of a query. this paper extends this idea to the semantic web. it introduces irdql---a semantic web query language with support for similarity joins. it is an extension of traditional rdql (rdf data query language) that enables the users to query for similar resources ranking the results using a similarity measure. we show how irdql allows to extend the reach of a query by finding additional results. we quantitatively evaluated four similarity measures for their usefulness in irdql in the context of an owl-s semantic web service retrieval test collection and compared the results to a specialized owl-s matchmaker. initial results of irdql indicate that it is indeed useful for extending the reach of queries and that it is able to improve recall without overly sacrificing precision. we also found that our generic irdql approach was only slightly outperformed by the specialized algorithm.
integrated resource management for data stream systems. data stream systems have to deal with massive data volumes. to perform several queries in parallel or to perform even a single query, resources must be planned carefully and the resulting quality-of-service (qos) is lower than the best one. typical qos measures are the output delay and the amount of data in the stream used for the processing. in this paper, we introduce a model which allows to describe stream operators and the streams between the operators of an operator graph belonging to a stream query. the model allows us to calculate the resources consumed by a query graph given a certain result quality. furthermore, it can be used to determine in advance if the quality-of-service requirement of a given query can be met with the actual available system resources. this model is the basis for building qos-guaranteeing systems.
checking security of java bytecode by abstract interpretation. we present a method to certify a subset of the java bytecode, with respect to security. the method is based on abstract interpretation of the operational semantics of the language. we define a concrete small-step enhanced semantics of the language, able to keep information on the flow of data and control during execution. a main point of this semantics is the handling of the influence of the information flow on the operand stack. we then define an abstract semantics, keeping only the security information and forgetting the actual values. this semantics can be used as a static analysis tool to check security of programs. the use of abstract interpretation allows, on one side, being semantics based, to accept as secure a wide class of programs, and, on the other side, being rule based, to be fully automated.
dynamic context adaptation in multimedia documents. multimedia documents are collections of media objects, synchronized by means of sets of temporal and spatial constraints. any multimedia document definition is valid as long as the referred media objects are available and the constraints are satisfiable. document validity depends on the context in which the document has to be presented. in this paper, we introduce a framework to characterize context adaptation, in the presence of both physical and user oriented context requirements. we define semantically equivalent presentation fragments as alternative to undeliverable ones. in the absence of equivalence, undeliverable media are replaced with candidates that minimize the loss of information/quality in the presentation.
java bytecode verification on java cards. a java program is usually translated into an intermediate language, known as java virtual machine language (jvml), which is then executed by a java virtual machine (jvm). before its execution a jvml program is verified to prevent a wide range of run-time errors. nowadays, java applets are available for various kinds of portable devices, including modern java smart cards. however, java cards cannot execute the classical verification algorithms, due to their very small amount of working memory.we present a new algorithm to verify a subset of the java bytecode language, suitable to be executed in low-memory environments, such as java smart cards. the method is based on abstract interpretation of the language operational semantics. we define an abstract small-step semantics of the language, able to keep information regarding the modifications of data during java constructs execution. we state the equivalence between our verification algorithm and the "standard" one. moreover, we discuss the low memory requirements of the algorithm.
applications of context-aware computing in hospital work: examples and design principles. context-awareness is a key concept in ubiquitous computing, which sometimes seems to be a technology looking for a purpose. in this paper we report on the application of context-aware computing for medical work in hospitals, which has appeared to be a strong case for applying context-aware computing. we present the design of a context-aware pill container and a context-aware hospital bed, both of which reacts and adapts according to what is happening in their context. the applications have been evaluated in a number of workshop with clinicians and patients. based on this empirical work of designing, developing, and evaluating context-aware clinical applications, the paper outlines some key design principles for a context-awareness framework, supporting the development and deployment of context-aware clinical computer applications.
first experiences on constraining consistency and adaptivity of w2000 models. the complexity of web applications is increasing almost every day. besides impacting the implementation phase, this complexity must also be suitably managed while modeling the application. the paper argues that a pure modeling notation, like w2000, is not enough to cope with such complexity and proposes an approach, based on meta-modeling and graph transformation, to enforce the consistency of produced artifacts and adapt them in a controlled way. the paper describes the approach, exemplifies it on some simple examples, and sketches the supporting framework on which we are working.
lessons from industrial design for software engineering through constraints identification, solution space optimisation and reuse. design is a complex activity that can be analysed from a wide variety of perspectives. this paper attempts to look at the individual problem solving process, taking into account psychological arguments. we characterise some of the phases involved in the design process, namely the constraints identification, the optimisation of solution space and the reuse process. we highlight a three-dimensional framework of how the constraints identification impacts on the solution space which, in turn, determines the range of the components that will be eligible for reuse. we discuss this argument through examples from both inside and outside the software engineering field.
graph transformation to infer schemata from xml documents. semi-structured data are characterized by the lack of a predefined schema. this heterogeneity simplifies the management of such data, but analysis and queries become more difficult and demand for schemata that describe these data. super-imposed structures cannot be as general as predefined ones, but ease the retrieval of the information embedded in such data. the paper adopts xml as the language to render semi-structured data and proposes an approach - based on graph transformation techniques - to infer the schemata of xml documents.
benefits of document maps for text access in knowledge management: a comparative study. analyzing, structuring and organizing documented knowledge is an important aspect of knowledge management. in order to ease the access to text collections, in literature so-called document maps have been proposed which visualize the inherently vague semantic similarity structure of a corpus of documents. in this paper we investigate a document map system which is specifically designed for typical text access tasks in knowledge management. based on an empirical task-model we present design, realization and results of a comparative laboratory study which evaluates the document map concept against an alternative text-access interface. we show that the graphical overview offers significant benefits over a text-based access interface for certain knowledge management tasks. we also discuss its drawbacks and point to further system improvements which promise to make the technology even more effective.
a structured documents retrieval method supporting attribute-based structure information. there are many studies on retrieval methods for structured documents but most of the studies are for those whose structure information is expressed by elements. but when elements are used to describe a document structure, the structure becomes static and difficult to expand. so describing a document structure using attributes is used in many standards. but most of the existing systems support mainly element-based structured documents and do not consider attribute-based ones. hence they do not support attribute-based structured documents well. so, we propose a new indexing method that supports attribute-based structured documents. in our index scheme, element-based structure information and attribute-based structure information are seamlessly integrated to describe a general document structure. also, we consider possible searching methods under the proposed index, and implement each method. and then, we experiment each method using the document actually being used in business, then analyze the results.
bts: a byzantine fault-tolerant tuple space. generative coordination is one of the most prominent coordination models for implementing open systems due to its spatial and temporal decoupling. recently, a coordination community effort have been trying to integrate security mechanisms to this model aiming to improve its robustness. in this context, this paper presents the bts coordination model, which provides a byzantine fault-tolerant tuple space. byzantine faults are commonly used to represent both process crashes and intrusions. as far as we know. bts is the first coordination model that supports this dependability level.
an xforms based solution for adaptable documents editing. the diversity of internet enabled terminals is increasing continuously. layout adaptation is becoming a crucial issue for the content providers. they have to support different client devices with minimal effort. this paper presents a document editing system that supports dynamic adaptation. it is implemented as a client-server application and uses cutting edge xml technologies.
the employment of xml standards in electronic judicial proceedings. the electronic court proceedings would provide many advantages: reducing time of justice, such a method to promote ease of transport, facilitating the drafting of subsequent judgements, at least, allowing a uniform and homogeneous judgement. the issue involves the knowledge of experts both in legal science and in computer science all over the world. this work would be analyse the role of xml standards and the xml signature standards in these electronic proceedings. the paper has to be seen as an attempt to identify the possible advantages offered by this technology, taking into consideration the "on line civil trial".
dynamic solver selection for an internet simulation backbone. this current research is to develop automated solver selection capabilities necessary to achieve a "simulation backbone" in which domain experts can plug in simulation solvers they have developed and have these automatically available for use to designers and researchers whose simulation requirements take them into that discipline. the ultimate goal is a one-button press execution of a simulation performed using the correct simulation solvers on machines distributed over the internet using software automatically taken from the internet.in order to achieve this objective, we have started to develop a framework to identify and characterize a system of computer-interpretable rules that describe when a theoretical and computational model is applicable to a design simulation. for example, if a design model comprises some geometric volume and fluid flow conditions are specified, a rule can indicate that the problem is in the discipline of fluid dynamics. depending on the specific shape and size of the volume and the velocity and viscosity of the fluid, rules can be used to further distinguish the problem as being in the sub-discipline of, for example, laminar, turbulent, or compressible flow. the existence of side effects, such as changes in heat transfer properties or aero-elastic effects, can also be inferred using rules that consider the results from a fluid dynamics simulation. the research scope has been limited to selected disciplines in mechanical engineering.
probabilistic multi-path vs. deterministic single-path protocols for dynamic ad-hoc network scenarios. we investigate the performance of different protocol stacks under various application scenarios. our method of choice is a full-fledged simulation in qualnet, testing the complete protocol stack over fairly large-scale networks. we find that the relative ranking of protocols strongly depends on the network scenario, the session load, the mobility level, and the choice of protocol parameters. we show that the parametric probabilistic protocols, which we generalize from their original definition, can outperform standard routing protocols, such as aodv or gossiping or shortest-path, in a variety of realistic scenarios.
a core calculus of higher-order mixins and classes. we present an object-oriented calculus based on higher-order mixin construction via mixin composition, where some software engineering requirements are modelled in a formal setting, allowing to prove the absence of message-not-understood run-time errors.
a mobility and traffic generation framework for modeling and simulating ad hoc communication networks. we present a generic mobility and traffic generation framework that can be incorporated into a tool for modeling and simulating large scale ad hoc networks. the basic framework consists of the following components:1. a mobility data generator (mdg) that generates positions and states of transceivers at specified times of the simulation clock. this module can support a variety of mobility models.2. a graph structure generator (gsg) that constructs the graph corresponding to the ad hoc network from the mobility data provided by mdg. this module can generate directed or undirected graphs depending on the radio range and propagation models.3. a terrain modification tool (tmt) that modifies the connectivity of the graph produced by gsg to allow for terrain effects or arbitrary obstructions.4. an activity data generator (adg) that generates sessions (i.e., packet transmission activities) for a specified fraction of the transceivers that are active at specified times of the simulation clock.the design allows a user to incorporate various realistic parameters crucial in simulating and modeling ad hoc communication networks. we illustrate the utility of our tool with two examples. the first example shows how purely synthetic movement patterns can be used in driving a simulation. the second example shows realistic movement patterns obtained via an urban population mobility modeling tool developed at los alamos.
safe and flexible objects. we design a calculus where objects are created by instantiating classes, as well as mixins. mixin-instantiated objects are "incomplete objects", that can be completed in object-based fashion. the combination of class-based features with object-based ones offers some flexible programming solutions. the fact that all objects are created from fully-typed constructs is a guarantee of controlled (therefore reasonably safe) behavior.
limited assignments: a new cutoff strategy for incomplete depth-first search. in this paper, we propose an extension of three incomplete depth-first search techniques, namely depth-bounded backtrack search, credit search, and iterative broadening, towards producing incomplete solutions. we also propose a new cutoff strategy for incomplete depth-first search motivated by a human style of problem solving. this technique, called limited assignment number (lan) search, is based on limiting the number of attempts tried to assign a value to the variable. a linear worst-case time complexity of lan search leads to promising stable time behavior in all accomplished experiments. the techniques are studied in the context of constraint satisfaction problems.
an infrastructure language for open nets. the structure of open nets, like the internet, is highly dynamic, as the topology of component networks continuously evolves. in this context, node connectivity is a key aspect and a language for distributed network-aware mobile applications should provide explicit mechanisms to handle it. in this paper, we address the problem of expressing dynamic changes of node connectivity at linguistic level and, in particular, we focus on a slight extension of the language klaim, that is targeted to this aim. the extension consists of the introduction of a new category of processes that, in addition to the standard process operations, can execute a few new coordination operations for establishing new connections, accepting connection requests and removing connections. our extension puts forward a clean separation between the coordinator level and the user level and, hence, it is modular enough to be easily applicable also to other network-aware languages. we will also show that our approach can be used as a guide for actual distributed (i.e. without a single centralized server) implementations of mobile systems.
software update via mobile agent based programming. we describe a system that permits maintaining the software installed on several heterogeneous computers distributed over a network by taking advantage of the mobile agent paradigm. the applications are installed and updated only on the central server. when a new release of an application is installed on the server, agents are scattered along the network to update the application on the clients.to build a prototype system we use x-klaim, a programming language specifically designed to program distributed systems composed of several components interacting through multiple tuple spaces and mobile code.
adapting software components by structure fragmentation. we present in this paper an approach aiming at adapting software components. it focuses on adapting component structures instead of adapting component services. among the motivations of this kind of adaptation, we note its possible application to permit flexible deployment of software components and flexible loading of component code according to the available resources (cpu, memory). our adaptation process is based on the analysis and the instrumentation of component codes. it respects the black-box property when it is implemented as a service provided by the component to be adapted. to support this structural adaptation technique, we developed an adaptation process which we have experimented using the java framework of the fractal component model.
method overloading and overriding cause encapsulation flaw: an experiment on assembly of heterogeneous components. based on an experiment using three languages under .net, this paper argues that the semantic differences between these languages regarding method overloading and overriding give rise to significant complexity and break encapsulation. we first recalls the various interpretations of overriding and overloading in object oriented languages through what we call language signatures. then, we realize an experimentation with .net components coded in different programming languages in order to observe the global behavior. from this, we show that overriding and overloading are not compatible with a key property of components: encapsulation. we conclude that, in the current state of the art, in order to build predictable assembly, components must expose their internal structure! we propose a solution to this problem.
towards a flexible, process-oriented it architecture for an integrated healthcare network. healthcare information systems play an important role in improving healthcare quality. as providing healthcare increasingly changes from isolated treatment episodes towards a continuous medical process involving multiple healthcare professionals and institutions, there is an obvious need for an information system to support processes and span the whole healthcare network. a suitable architecture for such an information system must take into account that it has to work as an integral part of a complex socio-technical system with changing conditions and requirements. we have surveyed the core requirements of healthcare professionals and analysed the literature for known problems and information needs. we consolidated the results to define use cases for an integrated information system as communication patterns, from which general implications on the required properties of a helathcare network information system could be derived. key issues are flexibility, adaptability, robustness, integration of existing systems and standards, semantic compatibility, security and process orientation. based on these results an it architecture is being designed that is capable of addressing the requirements mostly on the basis of well-established standards and concepts.
special track on model transformation (mt 2006). we are witnessing an increasing interest in the software engineering community towards the use of models for developing software systems. shifting intellectual property and business logic from source code into models, allows organizations to focus on the important aspects of their systems, which have traditionally been blurred by the usage of standard programming languages and underlying technologies.
semantic cores for representing documents in ir. this paper deals with the use of ontologies for information retrieval. roughly, the proposed approach consists in identifying important concepts in documents using two criterions, co-occurrence and semantic relatedness and then disambiguating them via an external general purpose ontology, namely wordnet. matching the ontology and a document results in a set of scored concept-senses (nodes) with weighted links. this representation, called semantic core of a document best reveals the semantic content of the document. we regard our approach, of which the first evaluation results are encouraging, as a short but strong step toward the long term goal of intelligent indexing and semantic retrieval.
adding spice to software development: a software development approach designed for rapidly changing environments. the office of military applications and stockpile support of the office of defense programs (dp-20) within the u.s. department of energy (doe) is responsible for managing nuclear materials. over the last five years, changes at home and abroad have had a dramatic effect on dp-20. the end of the cold war and the associated treaties have shifted much of dp-20 work from nuclear weapons production to the maintenance of a shrinking stockpile. the declassification of information has required dp-20 personnel to probe into data archived for decades. (you can't declassify information without having the information available.) finally, the election of a new president has led to the restructuring of doe and severe down-sizing of dp. these changes, and many others not mentioned, have made dp-20 a rapidly changing environment.
an optimized java interpreter for connected devices and embedded systems. the java virtual machine (jvm) is usually implemented by an interpreter or just-in-time (jit) compiler. jits provide the best performance, but interpreters have a number of advantages that make them attractive, especially for embedded systems. these advantages include simplicity, portability and low memory requirements. in this paper we describe a new interpreter core for cvm, sun microsystem's jvm for connected devices and embedded systems. the interpreter core is portable and programmed in c. an interpreter generator is used to apply a number of optimisations automatically to the source code. experimental results show that on benchmarks that spend almost all their time in the interpreter (rather than the run time system) it is 28% to 58% faster than the original cvm interpreter, and is only 5% to 9% slower than the highly-sophisticated, hand-tuned, assembly language interpreter in sun's desktop jvm.
hybrid ontology-based matchmaking for service discovery. the paper presents an ontology-based approach to service discovery, apt to support flexible and efficient matchmaking between service descriptions. we propose a hybrid approach that combines two matching strategies: a deductive strategy based on description logics with a reasoning procedure exploiting ontology knowledge to assess the type of match among services; a similarity-based strategy exploiting information retrieval metrics to measure the degree of match among services.
how to incorporate revocation status information into the trust metrics for public-key certification. in a traditional pki, the trust associated with a public key is expressed in binary either by 0 or 1. alternatively, several authors have proposed trust metrics to evaluate the confidence afforded by a public key. however their work has a static point of view and does not take into account the issue of public key revocation. in this paper, we make the first attempt to incorporate the revocation status information into the trust metrics for public key certification. to achieve our goal, we use a tailored form of a vector of trust model recently proposed. this would allow us to reason formally about when there is a need to check revocation status and how reliable the revocation mechanism should be in a given security application.
creation and management of versions in multiversion data warehouse. a data warehouse (dw) provides an information for analytical processing, decision making, and data mining tools. on the one hand, the structure and content of a data warehouse reflects a real world, i.e. data stored in a dw come from real production systems. on the other hand, a dw and its tools may be used for predicting trends and simulating a virtual business scenarios. this activity is often called the what-if analysis. traditional dw systems have static structure of their schemas and relationships between data, and therefore they are not able to support any dynamics in their structure and content. for these purposes, multiversion data warehouses seem to be very promising. in this paper we present a concept and an ongoing implementation of a multiversion data warehouse that is capable of handling changes in the structure of its schema as well as simulating alternative business scenarios.
sitelang: : edu: towards a context-driven e-learning content utilization model. current e-learning systems do not offer content customized for sophisticated learner characteristics. different learner types are supported only by means of varying presentation styles. methods for specifying learner-centered learning process are missing. for providing the right learning content in a proper context, in the right dosis and in the right moment, an e-learning system must follow the changes of learner's cognitive structures. this work presents sitelang::edu, a formal approach to specifying the learning process according to piaget's constructivistic theory. the approach allows to specify the learning process for learners with different learning styles. sitelang::edu specifications can be validated thanks to the operational semantics.
mace: lossless compression and analysis of microarray images. the ubiquity of microarray expression data in state-of-the-art biology has been well established. the widespread adoption of this technology coupled with the significant volume of image-based experimental data generated per experiment (averaging 40 mb), have led to significant challenges in storage and query-retrieval of primary data from microarray experiments. research in the yet nascent area of microarray data-compression seeks to address this problem. in this paper, we propose a conceptually novel approach that achieves significantly better lossless compression. unlike lossy compression, our algorithm is guaranteed against loss of information that may have potential biological relevance. the proposed method supports key operations such as automated grid and spot finding, histogram-based automatic thresholding for spot segmentation, and subsequent foreground and background separation. based on the proposed approach, we have developed a standardized format for storing microarray data that encapsulates all the relevant information, including both the cy3 and cy5 expression images significantly compressed. we have also developed a software application called mace (microarray compression and extraction application) to compress-decompress microarray data and generate the aforementioned format. compression-decompression results on a wide class of microarray experiments involving different spot layouts validate the effectiveness of our approach and its potential to significantly address the aforementioned challenges in storage and management of microarray data.
using genetic algorithms to find suboptimal retrieval expert combinations. a common problem of expert combination approaches in information retrieval (ir) is the selection of both, the experts to be combined and the combination function. in most studies the experts are selected from a rather small set of candidates using some heuristics. thus, only a reduced number of possible combinations is considered and other possibly better solutions are left out. in this paper we propose the use of genetic algorithms to find a suboptimal combination of experts for a document collection. our system automatically determines both, the experts to be combined and the parameters of the combination function. we test and evaluate the approach on four classical text collections. the results show that the learnt combination strategies perform better than any of the individual methods and that genetic algorithms provide a viable method to learn expert combinations.
secure mobile agent systems using java: where are we heading?. java is the predominant language for mobile agent systems, both for implementing mobile agent execution environments and for writing mobile agent applications. this is due to inherent support for code mobility by means of dynamic class loading and separable class name spaces, as well as a number of security properties, such as language safety and access control by means of stack introspection. however, serious questions must be raised whether java is actually up to the task of providing a secure execution environment for mobile agents. at the time of writing, it has neither resource control nor proper application separation. in this article we take an in-depth look at java as a foundation for secure mobile agent systems.
labrat lims: an extensible framework for developing laboratory information management, analysis, and bioinformatics solutions for microarrays. the biotechnology industry has long recognized the need for robust methods for tracking samples and data; however, it is only with the recent widespread adoption of genomic scale experiments that smaller academic facilities have also begun to appreciate the value of laboratory information management systems (lims) for use in tracking samples through the many procedures involved, including automated data collection and analysis. we have designed an extensible lims database backend collectively called labrat lims. the labrat lims database is an extremely flexible reference schema for implementing a generic lims system. additionally, we have created two front-end implementations for the labrat lims database: labrat lims web interface and microarray data portal for use in sample tracking and microarray data analysis, respectively. although designed primarily for microarray sample tracking and analysis, we believe that the flexibility of generic data management and multiple front-end interface architecture make labrat lims an extremely robust lims architecture. here we present the schema and implementation of this system.
web services for e-commerce: guaranteeing security access and quality of service. being e-commerce one of the most critical internet application, it is fundamental to employ technologies which guarantee not only secure transactions but also an adequate quality of service. in this paper we present a solution to this problem based on an extension of the emerging web service technology. in particular we introduce a new web service discovery protocol that extends standard uddi capability by addiing: (i) the discovery of web services at run-time supporting environment re-configurations, (ii) security access control to web services and (iii) a mechanism for distributing service invocations among several web services implementing (at different efficiency levels) the same task. discovery at run-time is realized by dynamically resorting to the discovery protocol (a web service itself) every time a service is invoked, access control is obtained by employing symmetric and asymmetric keys, while the different efficiency levels of service implementations are represented via weights. the proposal is formalized by employing a coordination platform, which is a probabilistic extension of the existing wssecspaces. such a platform is based on a data space, where data can be not only protected via access control mechanisms, like in wssecspaces, but also accessed probabilistically.
proxy viewpoints model-based requirements engineering. this paper addresses the problem of the "missing requirements" in software requirement specification (srs) expressed in natural language. due to rapid changes in technology and business frequently witnessed over time, the original srs documents often experience the problems of missing, not available, and hard-to-locate requirements. one of the flaws in earlier solutions to this problem has no consideration for missing requirements from multiple viewpoints. furthermore, since such srs documents represent an incomplete domain model, manual discovery (identification and incorporation) of missing requirements is highly labor intensive and error-prone. consequently, deriving and improving an efficient adaptation of srs changes remain a complex problem. in this paper, we present a new methodology entitled "proxy viewpoints model-based requirements discovery (pvrd)". through the requirements discovery and analysis process, pvrd methodology provides ways to construct proxy viewpoints model from legacy status requirements. requirements term expansion technique facilitates the retrieval process of requirements of interest based on the improved requirements representation space in proxy viewpoints model. the pvrd methodology provides an integrated environment that supports requirements discovery process as well as efficient management.
soft constraint propagation and solving in chrs. soft constraints are a generalization of classical constraints, where constraints and/or partial assignments are associated to preference or importance levels, and constraints are combined according to combinators which express the desired optimization criteria. constraint handling rules (chrs) constitute a high-level natural formalism to specify constraint solvers and propagation algorithms. in this paper we present a framework to design and specify soft constraint solvers by using chrs. in this way, we extend the range of applicability of chrs to soft constraints rather than just classical ones, and we provide a straightforward implementation for soft constraint solvers.
editorial message: special track on e-commerce technologies. the past few years have seen an exponential growth and dramatic changes in the field of e-commerce. the focus of this track is on novel applications for e-commerce, i.e., application that survived the dot-com crash in 2000 and that hold new promises for rapidly evolving electronic markets. a few years ago, e-commerce applications were focused primarily on handling transactions and managing catalogs. business requirements, however, are evolving beyond transaction support to include content management, mobile and pervasive computing, privacy and personalization, interoperability and integration. the track focuses on technologies currently employed in creating offerings, the latest developments in the electronic marketplace, on computational and deployment issues, architectural support, policies, and advanced solutions and practices. the track is intended to address the current needs of both researchers and practitioners, and to identify significant research challenges that will most beneficially impact the future use of e-commerce applications. the objective of the track is to provide a high quality forum for presentation and exchange of research results, ideas, and practical experiences among applied computer scientists and application developers working in the field of e-commerce. it also aims at bringing together academic and industrial researchers from various fields to discuss current challenges to e-commerce. it is our hope and expectation that the track is useful to the e-commerce research and development community and will help in finding promising future directions. as chairs we feel strongly that e-commerce will continue to be one of the most exciting fields in modern science.
modeling and detecting the cascade vulnerability problem using soft constraints. establishing network security is based not just on the security of its component systems but also on how they are configured to interoperate. in this paper we consider how soft constraints provide an approach to detecting the cascade vulnerability problem: whether system interoperation provides circuitous or cascading routes across the network that increase the risk of violation of multilevel security. taking the constraints approach means that we are building on techniques that have proven success in solving large-scale problems from other domains.
editorial message: special track on e-commerce technologies. the past few years have seen an exponential growth and dramatic changes in the field of e-commerce technologies. the focus of this track is on novel applications for e-commerce, i.e., applications that survived the dot-com crash in 2000 and that hold new promises for rapidly evolving electronic markets. a few years ago, e-commerce applications were focused primarily on handling transactions and managing catalogs. business requirements, however, are evolving beyond transaction support to include content management, mobile and pervasive computing, privacy and personalization, interoperability and integration. the track focuses on technologies currently employed in creating offerings, the latest developments in the electronic marketplace, on computational and deployment issues, architectural support, policies, and advanced solutions and practices. the track is intended to address the current needs of both researchers and practitioners, and to identify significant research challenges that will most beneficially impact the future use of e-commerce applications. the objective of the track is to provide a high quality forum for presentation and exchange of research results, ideas, and practical experiences among applied computer scientists and application developers working in the field of e-commerce. it also aims at bringing together academic and industrial researchers from various fields to discuss current challenges to e-commerce. it is our hope and expectation that the track is useful to the e-commerce research and development community and will help in finding promising future directions. as chairs we feel strongly that e-commerce will continue to be one of the most exciting fields in modem science.
editorial: special track on constraint solving and programming. constraints have emerged as the basis of a representational and computational paradigm that draws from many disciplines and can be brought to bear on many problem domains. given the increasing importance of the research field of constraints, organizing a special track dedicated to the topic was an ideal opportunity to showcase research from the field at acm sac-2005.
editorial message: special track on e-commerce technologies. the past few years have seen an exponential growth and dramatic changes in the field of e-commerce technologies. the focus of this track is on novel applications for e-commerce, i.e., applications that survived the dot-com crash in 2000 and that hold new promises for rapidly evolving electronic markets. a few years ago, e-commerce applications were focused primarily on handling transactions and managing catalogs. business requirements, however, are evolving beyond transaction support to include content management, mobile and pervasive computing, privacy and personalization, interoperability and integration. the track focuses on technologies currently employed in creating offerings, the latest developments in the electronic marketplace, on computational and deployment issues, architectural support, policies, and advanced solutions and practices. the track is intended to address the current needs of both researchers and practitioners, and to identify significant research challenges that will most beneficially impact the future use of e-commerce applications. the objective of the track is to provide a high quality forum for presentation and exchange of research results, ideas, and practical experiences among applied computer scientists and application developers working in the field of e-commerce. it also aims at bringing together academic and industrial researchers from various fields to discuss current challenges to e-commerce. it is our hope and expectation that the track is useful to the e-commerce research and development community and will help in finding promising future directions. as chairs we feel strongly that e-commerce will continue to be one of the most exciting fields in modem science.
special track editorial: constraint solving and programming. constraints have emerged as the basis of a representational and computational paradigm that draws from many disciplines and can be brought to bear on many problem domains. given the increasing importance of the research field of constraints, organising a special track dedicated to the topic was an ideal opportunity to showcase research from the field at acm sac-2006.
a conceptual framework for testing biometric algorithms within operating systems' authentication. this paper presents a conceptual framework for testing the implementation of biometric algorithms within unix and windows nt/2000 operating systems' login authentication. to support the analysis and evaluation of biometric algorithms, a data logging module will be used, enabling the collection of quantitative data, e.g. timestamps, biometric raw data, (pre)processed data, and return codes from each run of a biometric authentication. it is shown how biometric algorithms and a data logging module can be integrated into unix and windows nt/2000. in addition to the explained system components a human observer is necessary to collect extended data like user behavior and environmental conditions, which cannot be automatically recorded by the data logging module. from the combination of these two types of data, conclusions on the biometric algorithm in the context of its implementation in operating systems' authentication can be drawn. the resulting benefits for the development of appropriate biometric algorithms concerning aspects of robustness (security, safety), performance measures and usability will be discussed for iris-biometrics.
issues in augmenting image databases to improve processing content-based similarity searches. many current multimedia database management systems perform content-based retrieval of images by extracting a set of features from each data object inserted into the underlying database. this allows users to search the database for images that are similar to an input query image where the similarity is determined by comparing the previously extracted features. thus, the ability of the system to compare images depends upon the features it can extract from them. this also means that the system may fail to correctly match one of its stored images to the query image if their corresponding features do not sufficiently match. one approach to minimize the occurrences of these situations is to add modified versions of the stored image to the database and attempt to match the query image to any one of them. this paper discusses the advantages and applicability of this approach.
an architecture to support distributed data retrieval in specialized formats. raw data and processed information are essential to the development of software simulation systems used in the analysis of various application domains. in such domains, the dissemination and management of this information is a daunting task. this paper discusses software architectural and specification-driven approaches to data retrieval in custom formats. simulation developers use xml-based specification to request database results in any format.
use case-driven component specification: a medical applications perspective to product line development. modular and flexible software components can be useful for reuse across a class of domain-specific applications or product lines. by varying the composition of components suited to a particular product line, an assortment of applications can be developed to support differing operational needs. a top-down approach to the design components for a specific application may be effective, however a more evolutionary approach is needed to support the specification of components suited for a class of applications. in addition, such evolutionary approaches require support for the knowledge transfer that must occur from domain experts, who are not software experts, to skilled software engineers. by combining concepts from software product line development (spld) and other evolutionary design techniques, a new, use case-driven approach has been created called component-based product line analysis and design (c-plad). this approach was used to develop components in the domain of image-guided surgery applications.
exploiting contextual change in context-aware retrieval. information retrieval systems are usually unaware of the context in which they are being used. we believe that exploiting context information to augment existing retrieval methods can lead to increased retrieval precision. this approach is particularly important with the development of wireless mobile information appliances, such as pdas. many of these devices are aware of the user's physical context, and this has led to the evolution of context-aware applications. such applications can automatically utilise the user's current context, e.g. location or ambient temperature. context-aware retrieval is related to traditional information retrieval and information filtering, but is potentially more challenging due to the often continuous changes in user context. to meet these challenges we suggest a potential advantage of context-aware retrieval: this is that the current context is often changing gradually and semi-predictably. in this paper we suggest new methods based on a context-diary and caching aimed at improving both the precision of relevant retrieved information and the speed/availability of retrieval. the methods can be used, in principle, on top of existing retrieval systems.
video information retrieval using objects and ostensive relevance feedback. in this paper, we present a brief overview of current approaches to video information retrieval (ir) and we highlight its limitations and drawbacks in terms of satisfying user needs. we then describe a method of incorporating object-based relevance feedback into video ir which we believe opens up new possibilities for helping users find information in video archives. following this we describe our own work on shot retrieval from video archives which uses object detection, object-based relevance feedback and a variation of relevance feedback called ostensive rf which is particularly appropriate for this type of retrieval.
potential prevention of medical errors in casualty surgery by using information technology. recent studies on adverse events in medicine have shown that errors in medicine are not rare and may cause severe harm. quality problems in discharge letters may be a source of medical error. we have analyzed 150 discharge letters of an outpaitient clinic for casualty surgery in order to identify and to classify typical mistakes. a failure mode and effect analysis has been initiated in order to estimate the risk associated with different failure types. possible it solutions to prevent the identified problems have been assessed, focusing on expected effects and on feasibility. our analyses have shown that there is a need to improve the quality of discharge letters, and that it support based on the frequency and severity of certain error types has a good potential. we plan to introduce both pre-structured discharge letters and reminders in order to prevent the observed errors. they could improve both documentation quality and, if used during the patient visit, quality of treatment. moreover, they could produce training effects on less experienced physicians. to be able to rapidly integrate such an adapted it support into a comprehensive healthcare information system (his), it is important to establish a responsive it infrastructure.
strategic alignment in requirements analysis for organizational it: an integrated approach. we present an integrated approach to requirements engineering for organizational it to help ensure it-business strategy alignment. a single, unified model to enable validation of system requirements against business strategy is proposed. we use vmost analysis to deconstruct business strategy. we then model strategy using a goal-oriented requirements engineering notation; this is done within the framework for modeling an organization's business strategy proposed by the business rules group. we use jackson's problem frames to represent business model context. our approach is illustrated via an e-business case study of seven-eleven japan taken from the literature.
advanced modeling and browsing of technical documents. this article proposes three techniques for improving the modeling and browsing of electronic books for technical documents specified in xml. technical documents are for two reasons prime applications for electronic books. first, electronic devices are nowadays widely used for the distribution, storage, and updating of such documents. second, since most technical documents have rather complex semantics and structure, they might be easier to consult as electronic books with their advanced functionalities than as paper prints.the techniques proposed in this article are as follows. first, author's views are proposed as a means for grouping semantically related, yet different contents. second, browsing style sheets are proposed for distinguishing between the semantics of hypertext links and their traversal behavior more drastically than it is the case with current xml hypertext links. third, a tool called reader's view is described with which a reader can annotate and restructure an electronic book while exploring it. these techniques remind of former proposals made in the hypertext community. the focus of the present proposal is the smooth integration of the proposed techniques within the existing xml/html world so as to exploit existing standards and tools as far as possible.
reactivity on the web: paradigms and applications of the language xchange. reactivity on the web is an emerging issue. it is essential for upcoming web systems such as online marketplaces, adaptive, semantic web systems as well as web services and grids. this article first introduces the paradigms upon which the high-level language xchange for programming reactive behaviour and distributed applications on the web relies. then, it briefly presents the main syntactical constructs of xchange. finally, it sketches the implementation in xchange of a reactive web-based application.
agent-based services for information portals. web portals have a huge importance on today's internet. their purpose is to serve as an entry point to information on the web, by proposing search and classification related services. the usefulness of a web portal depends directly on the quality of service it offers. this paper presents the simat architecture which exploits a backbone of machines running a secure mobile agent platform to improve quality of service. the agents are programmed to reduce the latency of information retrieval and to support the personalization and security of information search requests.
an owl-s based approach to express grid services coordination. e-science and e-business share the need of a middleware that integrates dynamic services running on distributed, heterogeneous platforms. the grid community is addressing this problem by moving towards web services as it is proposed in the open grid service architecture (ogsa). in this paper we discuss the benefits of using an ontology driven approach to grid services in order to enhance their composability thus enabling the submission of multiple interoperating jobs. specifically we introduce an owl-s extension to describe relations among grid jobs in order to express coordination-related aspects. this enables to expose coordination requirements in an orthogonal way with respect to single jobs management. as a proof of concept we use this extension to express relations among jobs in order to support the automation of the matchmaking of resources.
warp: web application rapid prototyping. this paper describes an environment specifically tailored for the design and the rapid prototyping of web applications. the environment, named warp (web application rapid prototyping), offers a set of online software tools, which assist the designer and the user browsing of a web application, in all its different aspects.the environment is based upon models and techniques already used in the hypermedia, information systems, and software engineering fields, adapted and blended in an original mix. the foundation of the proposal is the conceptual design of web applications, starting from hdm, a notation for the specification of structure navigation, and presentation semantics.compared to existing tools, warp is an aid for analysis and design of web application because it introduces a new approach completely on-line (both the design and the execution environment). so the author can immediately formulate and evaluate requirements, specification and designs.a real-life experience of the use of the methodology and of the warp in academic context are reported.
replica placement in adaptive content distribution networks. adaptive content networking is a promising new approach aimed at scalable delivery of content to a pervasive client population. by adaptive content delivery networks (a-cdn) content is adapted, replicated and delivered to the clients in a cost-quality-optimized fashion. the integration of content adaptation into cdns minimizes the interference of adaptation with replication effectiveness.the paper presents ongoing research on replica placement in a-cdns. based on a static model for cost-quality-optimized adaptive content networking, algorithms to optimize the placement of replicas in the surrogates of an a-cdn are discussed. the dynamics of a real web scenario are not explicitly taken into account by the algorithms. whereas long-term dynamics are dealt with by periodic adjustments of the underlying model and recalculation of an optimal placement, short term dynamics are considered to result in inaccuracies in the system and load model. therefore, algorithms being tolerant to an imperfect underlying model are chosen.as adaptation path composition turns out to be a subproblem of replica placement in a-cdns, we also introduce an algorithm for optimal adaptation path composition.
automatic parallelism in differentiation of fourier transforms. for functions given in the form of a computer program, automatic differentiation is an efficient technique to accurately evaluate the derivatives of that function. starting from a given computer program, automatic differentiation generates another program for the evaluation of the original function and its derivatives in a fully mechanical way. while the efficiency of this black box approach is already high as compared to numerical differentiation based on divided differences, automatic differentiation can be applied even more efficiently by taking into account high-level knowledge about the given computer program. we show that, in the case where the function involves a fourier transform, the degree of parallelism in the program generated by automatic differentiation can be increased leading to a rich set of automatic parallelization strategies that are not available when employing a black box automatic parallelization approach. experiments of the new automatic parallelization approach are reported on a sunfire 6800 server using up to 20 processors.
efficient mass decomposition. we study the problem of decomposing a positive integer m over a (fixed and finite) weighted alphabet &sigma;: we want to find non-negative integers ci such that m = c1a1+...+ckak, where the ai are the positive integer weights of the individual characters and |&sigma;| = k. we refer to the vector (c1,...,ck) as a witness (of m over &sigma;), and denote by &gamma;(m) the number of distinct witnesses of m. we present a data structure of size o(ka1) that allows finding all witnesses of any query m in time o(ka1. &gamma;(m). to the best of our knowledge, this is the first algorithm for the problem with runtime independent of the size of the query m. construction of the data structure requires o(ka1) time and constant additional space, and is very easy to implement.the problem is motivated by mass spectrometry experiments, where peaks need to be mapped to sample molecules whose mass they could represent. our simulations show that the algorithm presented performs well on relevant applications.
efficient derivative computations in neutron scattering via interface contraction. for the solution of a minimization problem, a neutron scattering simulation needs accurate and efficient derivatives of an objective function in the form of a fortran 77 program with about 3,500 lines of code. we use the adifor system implementing the technology of automatic differentiation to transform the given computer code into another program capable of evaluating the objective function and its derivatives. compared to numerical differentiation, the derivatives obtained from applying automatic differentiation in this black-box fashion are free from truncation error and, in this application, their computation requires less time. to increase the efficiency of automatic differentiation further, a technique called interface contraction is used. the idea of interface contraction is to exploit the local structure of a given code by temporarily reducing the number of derivatives propagated through the code. by reporting performance results, we show the significance of interface contraction in the neutron scattering application. we also demonstrate the simplicity of the approach and argue that interface contraction should be incorporated into future automatic differentiation tools.
hiding complexity and heterogeneity of the physical world in smart living environments. continuous technological advances lead to computerize all the electronic devices and connect them in a network, so that in the future physical and virtual worlds will be integrated and interoperate each other at the point that browsing the reality will be similar to browsing the web. heterogeneous networked devices, services satisfying needs of people and living environments equipped with devices and services, will have to collaborate instead of working independently for offering to the end-user a better quality of the daily life. as a consequence, developers of ubiquitous computing and communication software infrastructures should address their efforts toward the abstraction of the implemented concepts. they have to abstract concepts from direct and immediate human needs in specific smart environments, avoid undue assumptions about the available devices or services and promote decoupling among distinctive, physical and functional features of devices and services.this paper briefly describes the extensible software architecture for smart environments the authors designed and implemented and presents the approach used for representing the physical world in a useful, comprehensible and more abstract manner and facilitating connections with the virtual world.
a class of openmp applications involving nested parallelism. today, openmp is the de facto standard for portable shared-memory programming supporting multiple levels of parallelism. unfortunately, most of the current openmp implementations are not capable of fully exploiting more than one level of parallelism. with the increasing number of processors available in high-performance computing resources, the number of applications that would benefit from multilevel parallelism is also increasing. applying automatic differentiation to openmp programs is introduced as a new class of openmp applications with nested parallelism.
architecture for user-controlled e-privacy. empowering users to make informed decision-making over online release of private data is a challenge in today's society. a large majority of users has rejected many e-privacy business models including lumeria's, zero-knowledge's, and microsoft's passport. in detailing privacy requirements for an architecture for user-controlled e-privacy, we provide some key reasons, mainly centered around user's perception of control, behind the apparent dismissal of business models for privacy based on trusted third parties. we describe an architecture, based on the p3p platform, that supports privacy requirements for enhanced user control of privacy. privacy management issues that are addressed include the identification of data repositories and their purposes, user agents and their roles and interactions, and the separation of persona profile information from user preference information.
accelerating approximate similarity queries using genetic algorithms. searching for the exact answer to a similarity query is an expensive process considering computational resources, such as memory and processing time requirements. moreover, comparison operations over multimedia data is even more expensive than over traditional data such as numbers and small character strings. therefore, when comparing multimedia data, the comparison computations usually consider some properties extracted from the data elements. in this way, exact queries involving this kind of data return data that is exact regarding the properties compared, but not necessarily exact regarding the multimedia data itself. for example, searching for similar images regarding their colors return images whose color histogram are the most similar, but the retrieved images can be very different regarding, for instance, the shape the objects pictured. therefore, for applications dealing with complex data types, trading exact answering with query time response can be worthwhile. in this paper we propose to use techniques based on genetic algorithms to allow retrieving data indexed in a metric access methods within a limited, user-defined, amount of time. we show that these techniques lead to much faster execution, without reducing the quality of the answer. we also present experimental evaluation using real datasets, showing that suitable results can be obtained in a fraction of the time required to obtain the exact answer.
provably faithful evaluation of polynomials. we provide sufficient conditions that formally guarantee that the floating-point computation of a polynomial evaluation is faithful. to this end, we develop a formalization of floating-point numbers and rounding modes in the program verification system (pvs). our work is based on a well-known formalization of floating-point arithmetic in the proof assistant coq, where polynomial evaluation has been already studied. however, thanks to the powerful proof automation provided by pvs, the sufficient conditions proposed in our work are more general than the original ones.
software agents for process monitoring and notification. safety and efficiency are primary concerns in chemical processing facilities, though the complexity of many such systems often makes it difficult for operators to detect abnormal conditions before they compromise throughput or become hazardous. in this paper, we report initial results from the application of multi-agent systems to monitor complex chemical processes and flexibly and appropriately notify key plant personnel about off-nominal conditions.
conceptual process configurations in enterprise knowledge management systems. in this paper we will present the results of research into the semantics of modeling constructs for the process-oriented perspective for the conceptual modeling of enterprise subject areas. the set of modeling constructs that are defined in this paper are fully 'compatible' with the models in the data-oriented perspective in the fact oriented school of conceptual modeling. we will derive the 'semantic' bridges for the conceptual modeling methodology for enterprises in the process-oriented perspective.
an integrated tool for microarray data clustering and cluster validity assessment. in this paper we present a data mining system, which allows the application of different clustering and cluster validity algorithms for dna microarray data. this tool may improve the quality of the data analysis results, and may support the prediction of the number of relevant clusters in the microarray datasets. this systematic evaluation approach may significantly aid genome expression analyses for knowledge discovery applications. the developed software system may be effectively used for clustering and validating not only dna microarray expression analysis applications but also other biomedical and physical data with no limitations. the program is freely available for non-profit use on request at http://www.cs.tcd.ie/nadia.bolshakova/machaon.html
java bytecode specification and verification. we propose a framework for establishing the correctness of untrusted java bytecode components w.r.t. to complex functional and/or security policies. to this end, we define a bytecode specification language (bcsl) and a weakest precondition calculus for sequential java bytecode. bcsl and the calculus are expressive enough for verifying non-trivial properties of programs, and cover most of sequential java bytecode, including exceptions, subroutines, references, object creation and method calls. our approach does not require that bytecode components are provided with their source code. nevertheless, we provide a means to compile jml annotations into bcsl annotations by defining a compiler from the java modeling language (jml) to bcsl. our compiler can be used in combination with most java compilers to produce extended class files from jml-annotated java source programs. all components, including the verification condition generator and the compiler are implemented and integrated in the java applet correctness kit (jack).
multilingual semantic elaboration in the dose platform. from the early world wide web exploitation until contemporary semantic web generation, global communication has become an essential need for many people on the internet. globalization means ease of information exchange and of resource sharing, and requires convenient ways to bridge the gap between actual cultural and linguistic barriers. this paper introduces a simple approach to multilingual semantic elaboration in the dose distributed open semantic elaboration platform. the proposed approach uses a single, language independent ontology coupled with many language specific concepts definitions and sets of lexical entities (synsets) to characterize modeled concepts. a simple experimental setup is described in order to assess the approach viability and further experimentation issues are discussed.
automatic learning of text-to-concept mappings exploiting wordnet-like lexical networks. a great jump towards the advent of the semantic web will take place when a critical mass of web resources is available for use in a semantic way. this goal can be reached by the creation of semantic meta-data in the publication workflow, or by the development of systems and applications able to associate semantics to resources (i.e., annotating them) automatically. those applications should analyze the content of a web page and should be able to associate some ontology classes to it. one particular issue in this context is to define a suitable relationship between each concept of the ontology and some words (or, more in general, strings) which are expected to appear in resources dealing with that concept, playing the role of "triggers" suggesting the relevance of a given text fragment to a concept.we hereby propose an approach that, starting from a set of textual representations created by experts (synsets), is able to automatically widen their lexical coverage by computing new, larger synsets, increasing the capability of a semantic application to correctly recognize the ontology classes a document is related to. in such approach, the initial textual representations are integrated and augmented by exploiting lexical networks like wordnet, which contain syntactic information connected through semantic relationships. some algorithms are proposed to avoid misleading terms and consequently to perform sense disambiguation in wordnet.
the advent of trusted computing: implications for digital forensics. the release of computer hardware devices based on "trusted computing" technologies is heralding a paradigm shift that will have profound implications for digital forensics. in this paper, we map out the contours of a trusted environment in order to establish the context for the paper. this is followed by the main components of the tc architecture with an emphasis on the trusted platform and the trusted platform module (tpm). the next section presents a synopsis based on three threat models, viz., (i) pc owner-centric, (ii) trusted computing-centric, and (iii) digital forensics-centric and then briefly touches on the implications and unintended consequences of trusted computing for digital forensics. finally, the last section of the concludes with a recommendation on how to mitigate the negative effects of trusted computing.
quiescent consensus in mobile ad-hoc networks using eventually storage-free broadcasts. we solve the consensus problem using a new class of broadcasts that are very appropriate to ad-hoc networking: every broadcast message is eventually ensured to be garbage-collected, thus freeing buffers in the resource-constrained mobile devices. we identify an impossibility result, the conditions in which a consensus protocol that assumes normal, message-keeping broadcasts can work using the new broadcast, and the adaptation such a protocol would require when these conditions do not hold. the cost of achieving quiescent consensus, estimated through simulations, is shown to be affordable for hosting practical dependable applications.
proxy-based security protocols in networked mobile devices. we describe a resource discovery and communication system designed for security and privacy. all objects in the system, e.g., appliances, wearable gadgets, software agents, and users have associated trusted software proxies that either run on the appliance hardware or on a trusted computer. we describe how security and privacy are enforced using two separate protocols: a protocol for secure device-to-proxy communication, and a protocol for secure proxy-to-proxy communication. using two separate protocols allows us to run a computationally-inexpensive protocol on impoverished devices, and a sophisticated protocol for resource authentication and communication on more powerful devices.we detail the device-to-proxy protocol for lightweight wireless devices and the proxy-to-proxy protocol which is based on spki/sdsi (simple public key infrastructure / simple distributed security infrastructure). a prototype system has been constructed, which allows for secure, yet efficient, access to networked, mobile devices. we present a quantitative evaluation of this system using various metrics.
agent factory: generative migration of mobile agents in heterogeneous environments. in most of today's agent systems migration of agents requires homogeneity in the programming language and/or agent platform in which an agent has been designed. in this paper an approach is presented with which heterogeneity is possible: agents can migrate between non-identical platforms, and need not be written in the same language. instead of migrating the "code" (including data and state) of an agent, a blueprint of an agent's functionality and its state is transferred. an agent factory generates new code on the basis of this blueprint. this approach of generative mobility not only has implications for interoperability but also for security, as discussed in this paper.
peerspaces: data-driven coordination in peer-to-peer networks. shared dataspaces &agrave; la linda, and the underlying data-driven coordination model, have been successfully exploited in the development of a huge variety of applications, going from parallel computing to web-based collaborative work. in this paper we consider a novel class of applications, namely those developed for peer-to-peer networks &agrave; la gnutella or freenet. we discuss the problems which arise when trying to exploit the original linda coordination model in this new scenario. in order to address these problems, we introduce peerspaces, a new coordination model particularly suited for the realm of peer-to-peer network applications, and we present a prototypical implementation of this coordination model based on the jxta peer-to-peer technology.
flexible querying of web documents. in this paper we present a flexible query language for expressing both conditions on the documents structure and conditions on the topics of interest. the first condition acts as a soft filter so as to reduce the set of documents on which to evaluate the second condition. flexibility is achieved by allowing users to specify both a linguistic quantifier such as most for qualifying the global composition of the documents into a number of sections and preferences on the desired documents sections.
extending sql with customizable soft selection conditions. users of information systems are aware that databases can be a mine of useful information, and would like to express flexible queries over the data possibly retrieving, not perfect" items when the perfect ones, those exactly matching the selection conditions, are not available. most commercial dbmss are still based on the sql for querying. thus providing some flexibility to sql can help users to improve their interaction with the systems without requing them to learn a completely novel language. in our approach we allow vague selection conditions based on linguistic predicates, i.e. soft conditions. this topic has been considered in previous works, specifically in sql/f which is a proposal for extending sql with soft conditions; however, we think that sql/f does not completely solve the problem mainly because it does not provide any practical means to customize the meanings of soft conditions to fit specific application domains. based on these considerations, we propose an extension of sql which supports customizable soft selection conditions which admit degrees of satisfaction; customizable soft conditions can be defined by users for their specific needs and application domains by means of an sql like operator. specifically, this paper proposes an extension of the basic sql select operator for specifying soft conditions; introduces a new operator for customizing the semantics of the linguistic predicates, provides the formal semantics for the proposed extension of selection conditions.
on the serializability of transactions in shared dataspaces with temporary data. several coordination platforms based on the shared dataspace approach introduces, besides the typical linda-like coordination primitives (used to produce, consume, and test for the presence/absence of data in a common repository), a transaction mechanism provided to group coordination primitives which should be executed in such a way that either all succeed or none of them is performed. in this paper we continue the investigation of the serializability of transactions in shared dataspace coordination languages that has been initiated in [2]. the new contribution consists of the analysis of the interplay between transactions and temporary data, ie., data with an associated expiration time.
a pivot-based index structure for combination of feature vectors. we present a novel indexing schema that provides efficient nearest-neighbor queries in multimedia databases consisting of objects described by multiple feature vectors. the benefits of the simultaneous usage of several (statically or dynamically) weighted feature vectors with respect to retrieval effectiveness have been previously demonstrated. support for efficient multi-feature vector similarity queries is an open problem, as existing indexing methods do not support dynamically parameterized distance functions. we present a solution for this problem relying on a combination of several pivot-based metric indices. we define the index structure, present algorithms for performing nearest-neighbor queries on these structures, and demonstrate the feasibility by experiments conducted on two real-world image databases. the experimental results show a significant performance improvement over existing access methods.
experimenting with sta, a tool for automatic analysis of security protocols. we present sta (symbolic trace analyzer), a tool for the analysis of security protocols. sta relies on symbolic techniques that avoid explicit construction of the whole, possibly infinite, state-space of protocols. this results in accurate protocol modeling, increased efficiency and more direct formalization, when compared to finite-state techniques. we illustrate the use of sta by analyzing the well-known asymmetric needham schroeder protocol. we discuss the results of this analysis, and contrast them with previous work based on finite-state model checking.
finding maximum independent sets in graphs arising from coding theory. new results are presented concerning binary correcting codes, such as deletion-correcting codes, transposition-correction codes, and codes for the z-channel. these codes are important due to the possibility of packet loss and corruption on internet transmissions. it is known that the problem of finding the largest correcting codes can be reduced to a well-known combinatorial optimization problem on graphs, the maximum independent set problem. a general scheme of organizing a local search for the maximum independent set problem is discussed. based on the developed heuristics, an exact branch-and-bound algorithm is proposed, which is able to find exact solutions for graphs with over 500 vertices within a reasonable time.
a pattern-based development methodology for communication protocols. patterns help to improve software quality and reduce development cost by documenting the experience of experts so that good solutions to recurring problems can be reused. in this paper, we propose a pattern-based software development methodology for communication protocols, particularly focusing on the specification and validation of message interactions. for the description of communication protocols, we propose a set of patterns. a complex protocol can be obtained by composing such patterns. to provide confidence in the protocol description, we validate the pattern-based specification by using the spin model checker. the validation phase needs model construction for the specification and checks the desired properties of the developing protocol. to show the feasibility of our methodology, we have conducted several case studies on real protocols.
about possibilistic queries against possibilistic databases. this paper is situated in the area of the so-called fuzzy databases, i.e., databases containing imprecise information. it is now recognized that querying databases containing imperfect information raises several problems, including complexity. in this paper, we consider a specific kind of queries, called possibilistic queries, of the form "to what extent is it possible that a given tuple t belongs to the answer of q (a regular relational query)". the major objective is to show that a reasonable complexity can be expected for a specific (although not too restricted) subset of possibilistic queries.
transforming ocl constraints: a context change approach. integrity constraints (ics) play a key role in the definition of conceptual schemas. in the uml, ics are usually specified as invariants written in the ocl. however, due to the high expressiveness of the ocl, the designer has different syntactic alternatives to express each ic, mainly depending on the type used as a context of the constraint. the method presented in this paper assists the designer during the definition of ics by means of automatically transforming the initially defined constraints into equivalent alternatives. the method is also useful in the context of the mda, where the choice of a particular alternative has a direct effect on the efficiency of the automatically generated implementation.
rail: code instrumentation for .net. code instrumentation is a mechanism that allows modules of programs to be completely rewritten at runtime. with the advent of virtual machines, this type of functionality is becoming more interesting because it allows the introduction of new functionality after an application has been deployed, easy implementation of aspect-oriented programming, performing security verifications, dynamic software upgrading, among others.the runtime assembly instrumentation library (rail) is one of the first frameworks to implement code instrumentation in the .net platform. it specifically addresses the limitations that exist between the reflection capabilities of .net and its code emission functionalities. rail gives the programmer an object-oriented vision of the code of an application, allowing assemblies, modules, classes, references and even intermediate code to be easily manipulated.this paper addresses the design of an implementation of rail along with the difficulties and lessons learned while building a framework for code instrumentation in .net.
enabling mobile agents to dynamically assume roles. agent-based application development must face the issues related to the interactions among agents. in fact, their sociality allows decomposing large applications into collaborating agents, while open environments, such as the internet, require agents belonging to different applications to compete to gain resources. in the brain framework, interactions among agents are fruitfully modeled and implemented on the basis of roles. this approach achieves several advantages, from separation of concerns between the algorithmic issues and the interaction issues, to the reuse of solutions and experiences in different applications. in this paper we propose a mechanism to enable java agents to dynamically assume roles at runtime. our approach is based on the modification of the bytecode of java agents, in order to implement an appropriate interface and to add the related methods. an application example and the comparison with other approaches show the effectiveness of our approach.
strong agent mobility for aglets based on the ibm jikesrvm. mobility enables agents to migrate among several hosts, becoming active entities of networks. java is today one of the most exploited languages to build mobile agent systems, thanks to its object-oriented support, portability and network facilities. nevertheless, java does not support strong mobility, i.e., the mobility of threads along with their execution state; thus developers cannot develop agents as real mobile entities. this paper reports our approach for java thread strong migration, based on the ibm jikes research virtual machine, presenting our results and proposing an enrichment of the aglets mobile agent platform in order to exploit strong agent mobility.
model transformations for hypertext modeling on web information systems. in response to the lack of suitable methods to build the navigation model of web information systems (wis), we presented in past works hm3, the hypertext modeling method of midas, a methodological framework for the agile development of wis. we proposed a method to obtain the navigation model of a wis, starting from the conceptual data model and the user requirements, collected in the use case model. in this work, continuing with the mda approach for wis development that we are following with hm3, we define the model to model transformations needed at the pim level to get the hypertext model from the behavioral and content models. firstly we specify the transformation rules with natural language to later map them to graph transformation rules.
an abstract architecture for semantic service coordination in agent-based intelligent peer-to-peer environments. intelligent agent-based peer-to-peer (ip2p) environment provide a means for pervasively providing and flexibly co-ordinating ubiquitous business application services to the mobile users and workers in the dynamically changing contexts of open, large-scale, and pervasive settings. we present an abstract architecture for service delivery and coordination in ip2p environments that has been developed within the cascom project.
editorial message: special track on web technologies and applications. the special track on web technologies and applications is already at its fourth edition and has seen a constant evolution in the research issues. currently, web applications are required to rely on open, flexible, adaptable, and distributed infrastructure and to be ubiquitous, highly scalable, reliable, accessible from different devices, and personalized with respect to various user requirements. web applications are becoming increasingly complex thereby creating a need for appropriate theoretical foundations, development methodologies, and supporting technology, drawing on different areas of computer science such as databases, artificial intelligence, programming languages, distributed computing, information retrieval, semantic modeling, human-computer interaction, etc.
using roles and business objects to model and understand business processes. business process modeling focus on describing how activities interact with other business objects while sustaining the organization's strategy. business objects are object-oriented representations of organizational concepts, such as resources and actors, which collaborate with one another in order to achieve business goals. these objects exhibit different behavior according to each specific collaboration context. this means the perception of a business object depends on its collaborations with other objects. business process modeling techniques do not clearly separate the multiple collaborative aspects of a business object from its internal aspects, making it difficult to understand objects which are used in different contexts, thus hindering reuse. to cope with such issues, this paper proposes using role modeling as a separation of concerns mechanism to increase the understandability and reusability of business process models. the approach divides a business process model into a business object model and a role model. the business object models deals with specifying the structure and intrinsic behavior of business objects while the role model specifies its collaborative aspects.
modeling organizational actors and business processes. finding suitable actors to perform specific activities is a common problem in knowledge-oriented organizations. to address this problem, this paper outlines the concepts required to represent organizational actor's skills and the services that are required by business process activities. these concepts are used within a marketplace-based model that enables dynamically managing actors and activities according to competence supply and demand.
solving weighted max-sat optimization problems using a taboo scatter search metaheuristic. in the last three decades, many researchers have focused on the satisfiability problem and on many of its variants, in particular, on the weighted maximum satisfiability problem (max-w-sat). the latter is known to be difficult to solve, due to a high number of local minima present in its search space. in this work, we present a metaheuristic based on taboo search (ts) procedure that makes use of the scatter search (ss) paradigm. our objective is to support a ts by a ss add-on to explore the influence of a population and combination strategies on the ability of generating high quality solutions.
adaptive testing of software components. software components are popular in nowadays software industries. however, how to test software components is a problem since the source code of the software component under test may not be available for the third-party user. in this paper we show that the software component should be tested in an adaptive manner in the sense that the software defect detection rates are estimated on-line by using testing data collected during testing to improve test case selections. in doing so, we use a recursive least squares estimation method to do on-line parameter estimations. this paper further justifies the advantages of the controlled markov chain (cmc) approach to software testing in particular, and the practicality of the idea of software cybermetics in general.
incremental adaptive filtering: profile learning and threshold calibration. this paper proposes an adaptive filtering process. adaptive filtering consists on receiving documents over time and compare them to the user profile. filtering is improved over time by updating the user profile and the dissemination threshold, the profile and the threshold are the principle elements in the filtering decision function. in this paper, a linear system under constraints is resolved when a relevant document is retrieved, the solution to this system is used to improve the user profile. this allows to reinforce the relevance of each relevant retrieved document. the constraints are a form of tf*idf (term frequency*inverse document frequency). a gradient distribution approach is used, based on information extracted from relevant filtered documents to update the dissemination threshold. experiments are undertaken into a dataset provided by trec (text retrieval conference) in order to simulate and evaluate a filtering process.
a robust watermarking system based on compression. digital watermarking can be used to protect the intellectual property for multimedia data. in this paper, we introduce an image watermarking scheme based on the svd (singular value decomposition) compression. in particular, we divide the cover image into blocks and apply the svd to each block; the watermark is embedded in all the non-zero singular values according to the local features of the cover image so as to balance embedding capacity with distortion. the watermarking system we propose is robust against typical attacks, including low-pass and high-pass filtering, as evaluated by the checkmark benchmarking tool [19].
using a hybrid evolutionary-taboo algorithm to solve job shop problem. in this paper, we propose a new hybrid algorithm to solve the job shop problem. our algorithm, called evoluntionary-taboo uses an evolutionary algorithm (ea) to enhance results obtained by one of the best taboo algorithms for this problem. we tested the algorithm on the benchmark problems for which the taboo algorithm returned its worst results. on average, we improved taboo results by 2.9%. the results were under one percent from the best known results for these problems.
using multimedia to emphasize the development of professional abilities. this paper presents the content of a lesson unit issued from the television distance education course information technology. it is a mandatory course of the undergraduate program of computer science from universit&eacute; laval. several television programs were used to favor the development of professional abilities needed in the workplace. the first part of this paper summarizes the knowledge that students must acquire. the second part emphasizes the use of television to favor the emergence of the needed professional abilities.
automatic fitting of cochlear implants with evolutionary algorithms. this paper presents an optimisation algorithm designed to perform in-situ automatic fitting of cochlear implants.all patients are different, which means that cochlear parametrisation is a difficult and long task, with results ranging from perfect blind speech recognition to patients who cannot make anything out of their implant and just turn it off.the proposed method combines evolutionary algorithms and medical expertise to achieve autonomous interactive fitting through a personal digital assistant (pda).
supporting e-commerce systems formalization with choreography languages. e-commerce as well as b2b applications are essentially based on interactions between different people and organizations (e.g. industry, banks, customers) that usually exploit the internet as communication media. web services provide a mean to deal with these aspects. in this paper we show, via a case study, how choreography and orchestration languages allow us to express behaviour policies between the involved entities (interactions modalities, interdependencies, security requirements); in particular we consider that they can be used not only for describing behavioural rules but also for designing and testing whether the involved entities move according with system specifications.
marshaling and unmarshaling models using the entity-relationship model. software systems are usually designed and documented with the aid of visual modeling notations. visual modeling notations keep evolving over the years in tandem with visual modeling tools, and the tight binding in between impedes the exchanging of modeling assets, which causes a spatial isolation of the models. another problem with legacy software models is that they are isolated temporally in the early phases of the software engineering life cycle without reaching out to the later phases. this paper presents an approach for breaking both spatial and temporal isolation of software models by marshaling and unmarshaling models using the entity-relationship (er) model, thus providing a promising way for evolving model-driven software development.
an interactive evolutionary algorithm for cochlear implant fitting: first results. in a previous sac-compahec paper[1], a method was presented using an interactive evolutionary algorithm for cochlear implants fitting.the method has recently been put to test, with very unexpected and encouraging results: in a few words, it seems that the algorithm is capable to obtain much better results than an expert practitioner in many cases.the solutions proposed by the algorithm are counter-intuitive, yet they improve speech recognition drastically. if these preliminary results are confirmed by many more cases, it could mean that experts have been deterministically tuning cochlear implants the wrong way for many years.however, it seems that the very good results obtained by the algorithm depend a lot on the acoustic environment in which the fitting is performed. a broader fitting scheme has therefore been implemented that should overcome this problem, by allowing the patient to sample typical background noises for which the prosthesis should be specifically tuned.in the future, a piece of software will be added to the cochlear implant signal processor that will automatically choose the best setting depending on the kind of sound environment picked up by the microphone.
approximate xml document matching. regular hedge grammar is a formal method to specify xml schema. xml document can be viewed as an ordered labeled tree. computing the approximate matching between an xml document with a schema with minimum cost is not only theoretically interesting. this problem can be modeled as: given an ordered labeled tree f and a regular hedge grammar p, how to compute the minimum edit distance to transform the forest f into f' so that f' is exactly matched by p. in this paper, with the introduction of leaf forest, we gave an algorithm for this problem in o(f2p(f + log p)) time, where f is the size of the forest and p is the size of the grammar. from the authors' knowledge, this is the first algorithm to transform an xml document (ordered labeled tree) to conform to a schema (tree grammar).
supporting change request assignment in open source development. software repositories, such as cvs and bugzilla, provide a huge amount of data regarding, respectively, source code and change request history. in this paper we propose a study on how change requests have been assigned to developers involved in an open source project and a method to suggest the set of best candidate developers to resolve a new change request. the method is based on the hypothesis that, given a new change request, developers that have resolved similar change requests in the past are the best candidates to resolve the new one. the suggestion can be useful for project managers in order to choose the best candidate to resolve a particular change request and/or to construct a competence database of developers working on software projects. we use the textual description of change requests stored in software repositories to index developers as documents in an information retrieval system. an information retrieval method is then applied to retrieve the candidate developers using the textual description of a new change request as a query.case and evaluation study of the analysis and the methods introduced in this paper has been conducted on two large open source projects, mozilla and kde.
keynote address: towards secure systems programming languages. the modern world is increasingly dependent on software, and yet the software we use is often manifestly insecure and unreliable. it seems only a matter of time until a "cyber-pearl harbor" occurs. as a result, we can expect future systems to be programmed in safer, higher-level languages. we discuss characteristics of such systems and languages, and how they help obtain the apparently conflicting goals of flexibility and reliability.
confirming the influence of educational background in pair-design knowledge through experiments. the sharing of tacit knowledge is a strategic factor for the success of software process, from a number of perspectives: training, project assimilation, and reducing noise in knowledge transfer. pair programming is supposed to be a practice suitable for this purpose. unfortunately, the building of tacit knowledge is determined by factors that are difficult to isolate and capture because they concern personal attitude and capability. thus, we have focused on the possible causes forming the individual ability, that can be isolated and studied, such as the individual education background. we have applied the practice of working in pairs to the design phase. we have made an experiment and a replica in academic environment, in order to understand the relationship between the building of knowledge through the practice and the individual background. in this paper we discuss the replica and compare the results with the first experiment's ones.
discovering interesting information in xml data with association rules. data mining algorithms are designed to extract interesting information from large amounts of data. they usually assume that source data are in relational (tabular) from. however, the recent success of xml as a standard to represent semi-structured data and the increasing amount of data available in xml pose new challenges to the data mining community. in this paper we introduce association rules for xml data. to accomplish this, we propose a new operator, based on xpath and inspired by the syntax of xquery, which allows us to express complex mining tasks, compactly and intuitively. the operator can indifferently (and simultaneously) target both the content and the structure of the data, since the distinction in xml is slight.
a control theory based framework for dynamic adaptable systems. the increasingly complex environments in which systems need to execute has lead to the need for tools and techniques to systematically design dynamically adaptable systems. a new framework for the design of these adaptive systems is proposed here. the framework, named smart (state model adaptive run time), is based on the mathematics of control theory and system identification techniques. this foundation allows the system to accurately predict constraint violations in the environment, such as a memory overflow, and avert them by selecting components that better utilize a particular resource. the result is a more robust system. an example of the application of smart is presented to show the need and applicability of the framework. experimental results demonstrate the framework has an 86% accuracy in predicting and averting memory constraint violations. these results indicate the smart framework is feasible and has the potential to be a useful design solution for dynamic adaptable systems. improvements to the framework are proposed as future work.
method construction - a core approach to organizational engineering. dominated by the behavioral science approach for a long time, information systems research increasingly acknowledges design science as a complementary approach. while primarily information systems instantiations, but also constructs and models have been discussed quite comprehensively, the design of methods is addressed rarely. but methods appear to be of utmost importance particularly for organizational engineering. this paper justifies method construction as a core approach to organizational engineering. based on a discussion of fundamental scientific positions in general and approaches to information systems research in particular, appropriate conceptualizations of 'method' and 'method construction' are presented. these conceptualizations are then discussed regarding their capability of supporting organizational engineering. our analysis is located on a meta level: method construction is conceptualized and integrated from a large number of references. method instantiations or method engineering approaches however are only referenced and not described in detail.
investigating 'internet crimes against children' (icac) cases in the state of florida. the purpose of this article is to highlight efforts by the computer crime center at the florida department of law enforcement (fdle) to prosecute icac cases under their jurisdiction. section 1 presents an overview of the fdle icac initiative, a project funded by the florida department of children and families (dcf) with respect to: (i) project goals and objectives, (ii) agent/analyst training and deployment, (iii) collaboration with other law enforcement agencies, (iv) arrest rates, and (v) community education programs. section 2 focuses on the internet and how it is contributing to the rising incidence of sexual exploitation of children by online predators. in particular, this section underscores the computer's appeal for both the offender and the victim. section 3 describes noteworthy cases that have been investigated by the fdle computer crime center. the first three sections provide the context for the last two sections which focus exclusively on the type of forensics required to successfully prosecute icac cases. in section 4, the main investigative steps are delineated. to illustrate how icac cases are handled, the article depicts the two main components of an investigation: first, subpoenas are issued, search warrants are served and executed, and then, once the evidence is acquired, law enforcement officials conduct a forensic exam on the computers and other digital evidence that may have been seized during an investigation. finally, section 5 concludes with a set of recommendations on 'best practices' for prosecuting icac cases.
a comparison of several predictive algorithms for collaborative filtering on multi-valued ratings. the basic objective of a predictive algorithm for collaborative filtering (cf) is to suggest items to a particular user based on his/her preferences and other users with similar interests. many algorithms have been proposed for cf, and some works comparing sub-sets of them can be found in the literature; however, more comprehensive comparisons are not available. in this work, a meaningful sample of cf algorithms widely reported in the literature were chosen for analysis; they represent different stages in the evolutive process of cf, starting from simple user correlations, going through online learning, up to methods which use classification techniques. our main purpose is to compare these algorithms when applied on multi-valued ratings.experiments were conducted on three well-known datasets with different characteristics, using two protocols and four evaluation metrics, representing coverage, accuracy, reliability and agreement of predictions with respect to real values. results from such experiments showed that the memory-based method is a good option because its results are more precise and reliable compared with the other methods. online learning methods exhibit a good level of accuracy with low variation, which makes them reliable models. on the other hand, support vector machines generate predictions with acceptable agreement; however, their accuracy depends on the characteristics of the input data. finally, dependency networks did not offer good results when applied on multi-valued rankings. the run experiments confirm that the characteristics of datasets keep being an important factor in the performance of methods.
static analysis of time bounded reactive properties of boolean symbols. we present a method for checking if macro-definitions written in c respect their specification. we are interested in simple time-bounded reactive properties. we use the abstract interpretation framework and a compact representation of sets of traces to provide a formalization of the specification, the semantics and the algorithms allowing us to build a representation of the set of traces.
discovery and regeneration of hidden emails. the popularity of email has triggered researchers to look for ways to help users better organize the enormous amount of information stored in their email folders. one challenge that has not been studied extensively in text mining is the reconstruction of hidden emails. a hidden email is an original email that has been quoted in subsequent emails but is not itself present in the folder; it may have been deleted or may never have been received. this paper proposes a method for reconstructing hidden emails using the embedded quotations found in messages further down the thread hierarchy. to do so, we model all the quoted fragments in a precedence graph, from which hidden emails are regenerated as bulletized documents. the bulletized model is our solution to the situation when a total ordering of fragment is not possible. we give a necessary and sufficient condition for each component of the precedence graph to be captured in a single bulletized email, and we develop heuristics that minimize the number of regenerated emails when the condition is not met. finally, we present empirical results showing the scalability of our approach.
an efficient time representation for real-time embedded systems. real-time systems should provide a time representation mechanism which allows to specify timing constraints in a wide range and with sufficiently high resolution. moreover, the system lifetime (that is, the longest absolute time that can be handled by the system) should be as long as possible, or possibly infinite. in powerful architectures, this goal is achieved by representing time through variables with a large number of bits. unfortunately, in real-time embedded systems with small memory requirements, such a solution cannot be used, and a trade off needs to be found for memory, system resolution and the longest representable timing constraint. in such systems, the runtime overhead introduced by the time representation mechanism is also crucial and needs to be taken into account.in this paper we present an efficient method for time representation suited for small embedded systems. the method allows to achieve an infinite lifetime, high resolution and deal with sufficiently large timing constraints. the proposed approach is compared with other methods proposed in the literature and it is proved to be more efficient in terms of both overhead and memory requirements. the method allows an efficient implementation of deadline-based scheduling algorithms (such as edf) and time accounting mechanisms for capacity based servers and resource reservation policies. the proposed technique has also been implemented and tested in two real-time kernels for small embedded microcontrollers.
differences between the iterated prisoner's dilemma and the chicken game under noisy conditions. the prisoner's dilemma has evolved into a standard game for analyzing the success of cooperative strategies in repeated games. with the aim of investigating the behavior of strategies in some alternative games we analyzed the outcome of iterated games for both the prisoner's dilemma and the chicken game. in the chicken game, mutual defection is punished more strongly than in the prisoner's dilemma, and yields the lowest fitness. we also ran our analyses under different levels of noise. the results reveal a striking difference in the outcome between the games. iterated chicken game needed more generations to find a winning strategy. it also favored nice, forgiving strategies able to forgive a defection from an opponent. in particular the well-known strategy tit-for-tat has a poor successrate under noisy conditions. the chicken game conditions may be relatively common in other sciences, and therefore we suggest that this game should receive more interest as a cooperative game from researchers within computer science.
high throughput reliable message dissemination. we consider applications that require high rate, reliable message dissemination in a many-to-many environment. examples of such applications include stock market centers and synchronized server clusters. as network capacity increases, the achievable throughput of messaging applications becomes bounded by processing times rather than communication speed. to reduce processing times we suggest the use of message aggregation. we consider performing message aggregation at either the sender, a message-server, or a network switch. the performance of each of these methods in terms of throughput and delay is analytically evaluated and compared against that of a naive implementation that does not perform message aggregation. we show that in typical real-world messaging applications, performing message aggregation can increase throughput by order of magnitude.we base our results on experiments that have been conducted using various operating systems running on different hardware platforms. our results indicate that the achievable throughput of messaging applications is determined by the number of packets-per-second, rather than bytes-per-second, a receiver or a transmitter should handle.
wireless spatio-semantic transactions on multimedia datasets. advances in spatially enabled semantic computing can provide situation aware assistance for mobile users. this intelligent and context-aware technology presents the right information at the right time, place and situation by exploiting semantically referenced data for knowledge discovery. the system takes advantage of new metadata standards to enable semantic, user, and device adapted transactions on multimedia datasets. information accessed in the past and the activities planned by the user, the situation dependencies (e.g. location) of these activities are used to infer future information requirements. the focus of this paper describes an application of the above functionalities for performing mobile context-aware queries and updating of a multimedia spatial database of cultural heritage artifacts concerning early 20th century dublin. it aims to exploit current consumer trends in mobile device usage by opening new markets for the increasing number of visitors to dublin's streets. an ongoing development of this technology, the project mocha (mobile cultural heritage adventures), will allow the mobile cultural heritage consumer to explore a personally tailored view of dublin's treasured artefacts, historical events and districts in an interactive and intuitive way directly on their spatially enabled pda.
using mobile agents as roaming security guards to test and improve security of hosts and networks. this paper discusses the design and implementation details of mast (mobile agent-based security tool), a new mobile agent-based network security approach. mast has been designed to support flexible and customizable network security tasks and training. this paper focuses on the implementation details and security aspects of mast's components, services, and mobile-agent architecture
coordinating functional processes with haskell. this paper presents haskell#, a parallel functional language based on coordination. haskell# supports lazy stream communication and facilities, at coordination level, to the specification of data parallel programs. haskell# supports a clean and complete, semantic and syntactic, separation between coordination and computation levels of programming, with several benefits to parallel program engineering. the implementation of some well-known applications in haskell# is presented, demonstrating its expressiveness, allowing for elegant, simple, and concise specification of any static pattern of parallel, concurrent or distributed computation.
a parallel algorithm for the extraction of structured motifs. in this work we propose a parallel algorithm for the efficient extraction of binding-site consensus from genomic sequences. this algorithm, based on an existing approach, extracts structured motifs, that consist of an ordered collection of p &ge; 1 boxes with sizes and spacings between them specified by given parameters. the contents of the boxes, which represent the extracted motifs, are unknown at the start of the process and are found by the algorithm using a suffix tree as the fundamental data structure. by partitioning the structured motif searching space we divide the most demanding part of the algorithm by a number of processors that can be loosely coupled. in this way we obtain, under conditions that are easily met, a speedup that is linear on the number of available processing units. this speedup is verified by both theoretical and experimental analysis, also presented in this paper.
a chat interface for human-agent interaction in mast. in this paper we introduce a group-messaging interface that allows humans to efficiently interact with a group of agents through a hierarchical and customizable text protocol. our approach is presented in the context of the mast mobile agent-based framework for security and administration of large scale computer networks. the mast framework is primarily human-centric and directly supports human-agent interaction that enables customized agents to notify administrators and react to abnormal environmental conditions. the proposed irc-like interface was developed and tested in the context of mast. in this paper we present the group-manager interface in contrast with other agent interfaces currently available in the mast framework.
combining queueing networks and web usage mining techniques for web performance analysis. the growing interest in web applications that satisfy end-to-end quality of service (qos) requirements is leading many organizations to build and analyze performance behavior models. in this direction, web usage mining techniques may help in the automatic construction of user profiles from web access logs. however, their use has been mainly limited to customer relationship management (crm) issues and to market analyses. the aim of this paper is to explain how web usage mining can be combined with queueing networks for effective web capacity planning. after introducing a new general relative cosine similarity measure, we define a performance-oriented similarity for web usage data. a methodology to devise the input parameters of a queueing network from the resulting clusters is also presented. finally, the proposed approach is illustrated on a simple case study.
xeai-rules: executable models to simulate enterprise application cooperation. we propose an approach to create application-cooperation executable uml models by performing transformations on high-level business rule models. business rules are defined, using activity diagrams, then, they are transformed to an annotated pim to, finally, be transformed into an executable uml (xuml) model. the xuml model along side with a set of test cases enables us to validate that applications, whose cooperation is described in the rules, maintain consistency and integrity. because this validation is based on a non-distributed, platform-independent simulation the cost and effort of its development and testing is reduced; early detection of flaws can help avoid expensive modifications on a concrete platform specific implementation.
design time support for adaptive behavior in web sites. adaptive web sites are sites that automatically improve their internal organization and/or presentation by observing user-browsing behavior. in this paper we argue that adaptive behavior of websites should be controlled in order to keep the website manageable. we believe that adaptive behavior may be a useful complement to a good website design method on the condition that the adaptations are limited and according to the modeling approach followed during design. therefore, we allow a website designer to specify at design time the adaptive behavior that will be allowed at runtime. to accomplish this goal, an adaptation specification language is defined that allows designers to specify at the level of the navigational model, which adaptations could be performed at runtime. the language is event based, i.e. a collection of rules is used to specify the adaptation operations to be carried out if certain conditions are satisfied. the approach proposed is elaborated in the context of wsdm, an audience driven website design method, but is generally applicable to other design methodologies.
a component-based implementation of multiple sequence alignment. this paper addresses the efficient execution of a multiple sequence alignment (msa) method, in particular the progressive alignment-based clustal w algorithm, on a cluster of workstations. we describe a scalable component-based implementation of clustal w program targeting distributed memory machines and multiple query workloads. we look at the effect of data caching on the performance of the data server. we present a distributed, persistent cache approach for caching intermediate results for reuse in subsequent or concurrent queries. our initial results show that the cache-enabled clustal w program scales well on a cluster of workstations.
sharing scientific models in environmental applications. environmental applications have been stimulating the cooperation among scientists from different disciplines. there are many examples where this cooperation takes place through exchanging scientific resources, such as data, programs and mathematical models. finding the right model to apply in an environmental problem is a difficult task. usually, this decision is based on previous experience. to facilitate the exchange and dissemination of information we propose a scientific resources architecture, where scientists may share their data, programs and models. we also present a scientific publishing metamodel for scientific resources description. the main goal of the proposed architecture is to provide scientific metadata support to effective model sharing, representing an innovative contribution to environmental applications. scientific experiments and workflows are also considered as scientific resources that need to be shared. we believe that the proposed scientific publishing metamodel could be naturally extended to include these other scientific resources.
an implicit segmentation-based method for recognition of handwritten strings of characters. this paper describes an implicit segmentation-based method for recognition of strings of characters (words or numerals). in a two-stage hmm-based method, an implicit segmentation is applied to segment either words or numeral strings, and in the verification stage, foreground and background features are combined to compensate the loss in terms of recognition rate when segmentation and recognition are performed in the same process. a rigorous experimental protocol shows the performance of the proposed method for isolated characters, numeral strings, and words.
automated test scenarios generation for an e-barter system. this paper presents a formal specification of an e-barter system and a set of scenarios to test the conformance of a given implementation to some targeted system functionalities. the functionalities of the e-barter system are inspired from those presented in [7] that are based on intelligent agents using utility functions to represent customer preferences but also integrating transaction and shipping costs. the system specification is performed using the sdl language. it includes two markets representing two cities, both cities containing several agents representing the customers preferences. agents are different instances of the same process, allowing the dynamic inclusion of new agents and of new resources. the scenarios are generated from the specification and from some test purposes using a tool developed at int [1]. the test purposes express specific system properties and are used to guide the test generation procedure that is completely automated. in this paper, we also present the experimentation results of the application of our tool to the e-barter system.
a framework to simulate uml models: moving from a semi-formal to a formal environment. this paper presents a simulation framework for uml models based upon a mapping schema of uml metamodel elements into abstract state machines (asms). structural model elements are translated into an asm vocabulary as collections of domains and functions, whereas the dynamic view is captured by multi-agent asms reflecting the behavior modeled by uml state machines.in the toolkit presented, input uml models can be drawn using any uml case tool able to produce the xmi format for diagrams. this textual representation is exploited to initialize the asm model for uml state machines which can be symbolically executed by asmgofer, an advanced abstract state machine programming system.tool features are described through the simulation of a simple stack-printer uml model showing the interactions among state machines by signals exchange and operation calls.
emergent situations in interactive storytelling. interactive storytelling can either be based on explicit plot representations or on the autonomous behaviour of artificial characters. in such a character-based approach, the dynamic interaction between characters generates the actual plot from a generic storyline. characters' behaviours are implemented through real-time search-based planning techniques. however, the top-down planning systems that control artificial actors need to be complemented with appropriate mechanisms dealing with emerging ("bottom-up") situations of narrative relevance. after discussing the determinants of plot variability and the mechanisms that account for the emergence of narrative situations, we introduce additional mechanisms for coping with these situations. these comprise situated reasoning and action repair: we most specifically illustrate the latter through a detailed example.
addressing e-business privacy concerns: the roles of trust and value compatibility. collecting information is an important part of knowing the customer and growing a business. understanding the factors that affect a person's willingness to disclose personal information is crucial for learning how to collect and utilize that information. in this paper, a privacy model is proposed in which trust and the compatibility of the values of an individual and an organization are expected to enhance a person's willingness to disclose personal information. a survey is conducted to examine the impact of value compatibility on trust, the impact of trust on information disclosure, and the impact of value compatibility on information disclosure. strong empirical support is found for the effect of value compatibility on trust and for the effect of trust on information disclosure. conditional support is found for the effect of value compatibility on information disclosure, dependent on the sensitivity levels of the information items.
smartmethod: an efficient replacement for method. in the last few years the interest in reflection has grown and many modern programming languages/architectures have provided the programmer with reflective mechanisms. as well as any other novelty also reflection has detractors. they rightly or wrongly accuse reflection to be too inefficient to be used with real profit. in this work, we have investigated about the performance of java reflection library (especially of the class method and of its method invoke) and realized a mechanism which improves its performances. our mechanism consists of a class, named smartmethod and of a parser contributing to transform reflective invocations into direct call carried out by the standard invocation mechanism of java. the smartmethod class is compliant --- that is, it provides exactly the same services ---, with the class method of the standard java core reflection library but it provides a more efficient reflective method invocation.
[a]c#: c# with a customizable code annotation mechanism. reflective programming is becoming popular due to the increasing set of dynamic services provided by execution environments like jvm and clr. with custom attributes microsoft introduced an extensible model of reflection for clr: they can be used as additional decorations on element declarations. the same notion has been introduced in java 1.5. the extensible model proposed in both platforms limits annotations to class members. in this paper we describe [a]c#,1 an extension of the c# programming language, that allows programmers to annotate statements or code blocks and retrieve these annotations at run-time. we show how this extension can be reduced to the existing model. a set of operations on annotated code blocks to retrieve annotations and manipulate bytecode is introduced. finally, we discuss how to use [a]c# to annotate programs giving hints on how to parallel a sequential method and how it can be implemented by means of the abstractions provided by the run-time of the language.
towards a model-driven join point model. aspect-oriented programming (aop) is increasingly being adopted by developers to better modularize object-oriented design by introducing crosscutting concerns. however, due to tight coupling of existing approaches with the implementing code and to the poor expressiveness of the pointcut languages a number of problems became evident. we believe that such problems could be solved shifting the focus of software development from a programming language specific implementation to application design. this work presents a possible solution based on modeling aspects at a higher level of abstraction which are, in turn, transformed to specific targets.
aop for software evolution: a design oriented approach. in this paper, we have briefly explored the aspect-oriented approach as a tool for supporting the software evolution. the aim of this analysis is to highlight the potentiality and the limits of the aspect-oriented development for software evolution. from our analysis follows that in general (and in particular for aspectj) the approach to join points, pointcuts and advices definition are not enough intuitive, abstract and expressive to support all the requirements for carrying out the software evolution. we have also examined how a mechanism for specifying pointcuts and advices based on design information, in particular on the use of uml diagrams, can better support the software evolution through aspect oriented programming. our analysis and proposal are presented through an example.
editorial: track reliable computations and their applications. many numerical computations, be they solutions to systems of differential equations or optimization problems coming from applied areas like protein folding, do not provide us with guaranteed computation results. in many situations, we have numerical solutions, we may even have a theorem guaranteeing that, eventually, this numerical solution tends to the actual precise one, but the algorithm itself does not provide us with guaranteed bounds on the difference between the numerical approximate solution and the desired actual one. therefore, in some practical situations, numerical solutions are much farther from the actual (unknown) precise solutions than the users assume.
editorial: track reliable computations and their applications. many numerical computations, be they solutions to systems of differential equations or optimization problems coming from applied areas like protein folding, do not provide us with guaranteed computation results. in many situations, we have numerical solutions, we may even have a theorem guaranteeing that, eventually, this numerical solution tends to the actual precise one, but the algorithm itself does not provide us with guaranteed bounds on the difference between the numerical approximate solution and the desired actual one. therefore, in some practical situations, numerical solutions are much farther from the actual (unknown) precise solutions than the users assume.
modeling sociotechnical specifics using architectural concepts. in this paper we focus on architectural concepts for complex sociotechnical systems. first we claim that there is a great need for model-based reasoning about systemic properties concerning questions of system design and the definition of long-term management policies. after this we take our starting point from formal methods, requirements engineering, and software architecture. we provide special extensions for these methods which are well-suited for the description of the behavioral relevance of cognitive parameters in sociotechnical systems. we maintain the visual style of modeling concepts as known from software architecture and provide an easy to use notation for reasoning about the features of specific decision situations. finally we provide concepts to deal with uncertain system behavior and human error.
data visualization using kernel density estimation to examine patterns of physician practice. studies have shown that examinations of physician practices and variation can improve patient care while reducing costs. however, most of the studies rely more on physician consensus than on data analysis. the existence of large hospital databases allows for the examination of the relationship between practice and outcome. because it is generally not known beforehand which practice optimizes outcome, particularly given the variability in patient risk, data mining techniques are ideal to examine the relationship. in particular, this paper uses the data visualization technique of kernel density estimation to explore and define physician practices. three physician practices were examined at a hospital during 2001--2002. the first physician practice identified was the administering of heparin to 100 patients as an anti-coagulant during angioplasty to open blocked coronary arteries. the second practice examined was two different open-heart procedures: one done on a cardiopulmonary bypass pump, the other done off bypass pump. the third physician practice examined the prescribing of antibiotics for patients undergoing open-heart surgery.
carrying on the e-learning process with a workflow management engine. in recent years e-learning systems have promised to change the way people learn. however open issues still remain, in particular actual e-learning environments do not consider learning activities as part of the process of learning. thus, it is not possible to define structured courses and specify precise learning paths apt to guide learners through learning materials. in our approach, we define courses as workflows. by so doing we can exploit powerful procedural rules in order to define precise while flexible learning paths. in this paper we present virtual campus, a research project sponsored by microsoft research (uk) and developed at politecnico di milano, that exploits a workflow engine to enacts the fruition of structured courses. our platform provides both an authoring and a fruition environment. the former allows teachers to define and customize learning paths, publishing them as workflows. the fruition environment enacts the workflows and guides learners through the related learning paths. we also describe an experience in using the platform during a software engineering course composed by heterogeneous activities (lectures, studying activities, cooperative sessions of work, and exams).
box-set consistency for interval-based constraint problems. as opposed to finite domain csps, arc consistency cannot be enforced, in general, on csps over the reals, including very simple instances. in contrast, a stronger property, the so-called box-set consistency, that requires a no-split condition in addition to arc consistency, can be obtained on a much larger number of problems.to obtain this property, we devise a lazy algorithm that combines hull consistency filtering, interval union projection, and intelligent domain splitting. it can be applied to any numerical csp, and achieves box-set consistency if constraints are redundancy-free in terms of variables. this holds even if the problem is not intervalconvex. the main contribution of our approach lies in the way we bypass the non-convexity issue, which so far was a synonym for either a loss of accuracy or an unbounded growth of label size.we prove the correctness of our algorithm and through experimental results, we show that, as compared to a strategy based on a standard bisection, it may lead to gains while never producing an overhead.
a heuristic approach for solving decentralized-pomdp: assessment on the pursuit problem. defining the behaviour of a set of situated agents, such that a collaborative problem can be solved is a key issue in multi-agent systems. in this paper, we formulate this problem from the decision theoretic perspective using the framework of decentralized partially observable markov decision processes (dec-pomdp). formulating the coordination problem in this way provides a formal foundation for study of cooperation activities. but, as it has been recently shown solving dec-pomdp is nexp-complete and thus it is not a realistic approach for the design of agent cooperation policies. however, we demonstrate in this paper that it is not completely desperate. indeed, we propose an heuristic approach for solving dec-pomdp when agents are memory-less and when the global reward function can be broken up into a sum of local reward functions. we demonstrate experimentally on an example (the so-called pursuit problem) that this heuristic is efficient within a few iteration steps.
a learning-based approach for fetching pages in webvigil. the world wide web is an omni-present and an ever-expanding source of data. data on the web is constantly increasing and changing. many a times, users are interested in specific changes to the data on the web. currently, in order to detect changes of interest, users have to poll the pages periodically and check for the changes of interest. webvigil is a general-purpose information monitoring and notification system. it handles the specification, intelligent fetch, detection, and propagation of changes as requested by a user while meeting the quality of service requirements. we use the active capability in the form of event-condition-action (eca) rules, and a combination of push/pull paradigm for change monitoring. in this paper, we present an overview of the specification language and the run time management of sentinels. we discuss in detail the use of eca rules for fetching and the adaptive learning algorithm used for fetching pages. we conclude with the implementation status of webvigil.
visualization of association rules over relational dbmss. the focus of this paper is the association rule visualization system that we have designed and developed. the rules produced by the mining algorithm are assumed to be stored in tables. the alternatives for visualization include tabular form, interactive two-dimensional, and three-dimensional graphics. by providing sorting and filtering abilities, the rule visualization system proposed in this paper provides a flexible, efficient, and easier way to manage and understand large number of association rules. as a result, this visualization system becomes an essential part of our association rule mining subsystem. we compare our association rule software with intelligent miner from ibm in various aspects, such as data accessibility, user interface, input/output, and rule visualization.
integrating smart card access to web-based medical information system. this paper examines the application of smart cards in the development of distributed medical information systems. the pocket mobility and security features of smart cards make them an ideal medium for storing the critical medical records of individual. however, the lack of interoperability and support for distributed operation has limited the development and usage of smart cards in a networked environment. this paper highlights the benefits of combining the world wide web and smart card technologies to support the development of highly robust health information system, while leveraging on the rich benefits of the web technology. in particular, we describe an approach of using the webcard service model as a common interface to communicate and access the medical records residing in a smart card that seamlessly integrates to existing web infrastructure. importantly, by employing http as the baseline protocol to access information on the smart card, webcard promotes the use of de facto standard web browsers as the common client user interface. the initial implementation of the framework and development of a case example of a web-based medical information site have demonstrated the feasibility of the concept of webcard.
cookies on-the-move: managing cookies on a smart card. despite the widespread use and adoption of cookies as the basis for web applications to keep state information, cookies present some design issues that are yet to be fully addressed. the fact that cookies are stored on client-side's memory means that they are tightly coupled to the machine that is interacting with the web server. yet often, these cookies are initiated by web applications to identify user's preferences and identifications. as the user moves across different machines to access the same site, the information previously recorded is lost and the web application has no way of restoring the state, unless the user revisits the same client machine, where the original cookies were set. this paper presents a novel solution to address the need for cookies to be "mobile" by leveraging on smart card to manage cookies, with the benefit of mobility in a pocket. we describe the design and implementation of the cookiescard framework that uses smart card as a secure and mobile storage media to manage personalized cookies. the article presents the development of the cookiescard proxy that directly interacts with the smart card to provide cookies management, while acting as an intermediatary between the client browser and a web server.
bluepoint: a bluetooth-based architecture for location-positioning services. mobile computing has induced a class of killer applications recently by extending the paradigm of parallel and distributed computing across a mobile environment. a very important class of applications involves the location-awareness of a mobile user. two major issues must be addressed to deliver appropriate services to mobile users. one is the availability of a good location-positioning system and the second is an infrastructure that enables the positions to be tracked for the perusal of user applications. in this paper, we propose the bluepoint architecture that allows mobile user locations to be managed effectively and transparently. this is realized through a middleware for the application developers, shielding the applications from the distribution and heterogeneity of the underlying communication networks and the locating infrastructures. the middleware offers a set of location-based support functions and high-level apis to the application programmers. other useful components are built around the architecture. we built a prototype of bluepoint, with some sample applications set in the context of a hospital environment. in this paper, we will focus on the middleware-based architecture of bluepoint, providing services which are integrated seamlessly to the user applications. services provided in the middleware include location information management, location information retrieval, location event notification and access control on mobile units.
multiple related document summary and navigation using concept hierarchies for mobile clients. mobile clients have limited display and navigation capabilities. to browse a set of documents, an intuitive method is to navigate through concept hierarchies. to reduce semantic loading for each term that represents the concepts and the cognitive loading of users due to the limited display, similar documents are grouped together before concept hierarchies are constructed for each document group. since the concept hierarchies only represent the salient concepts in the documents, term extraction is necessary. our pilot experiments showed that an unconventional combination of term frequency and inverse document frequency yielded similar performance (i.e. 71%) to previous work and the use of terms in titles achieved better performance than previous work (i.e. 82%). our preliminary results of building concept hierarchies after clustering compared to that without is encouraging (c.f. 82% and 67%). we believe that further research can enhance the performance of concept hierarchies to a level for commercial deployment for mobile clients.
image retrieval with embedded region relationships. image retrieval based on content from digital libraries, multimedia databases, the internet, and other sources has been an important problem addressed by several researchers. in this regard, one cannot overestimate the use of appropriate features such as color, texture, and shape. it has also become increasingly evident that the decomposition of images into regions is critical for useful results.in this paper we further study region-based image retrieval. we argue that a relationship between regions (such as a tiger amongst yellowish-green grass, or a plane against the blue sky with mountains in the background) is also important. our local segmentation algorithm is used to detect regions a priori. further, while searching for a match for an 'object' in the database, we allow for probabilistic 'multiple matches,' which are later pruned based on global consistent information. we provide a simple, fast algorithm implemented as an internet thin client connecting to a web server. experimental results indicate that our method has high precision, is robust towards translation, rotation, and scale changes, can handle partial occlusion, as well as many popular image transformations (such as shear and blur) much the way humans can.
event-driven scheduling for dynamic workload scaling in uniprocessor embedded systems. many embedded systems are designed to take timely reactions to the occurrences of interested scenarios. sometimes transient overloads might be experienced due to hardware malfunctions or workload bursts. thus a mechanism to focus system attention on urgent events could be a key to provide reasonably stable service. in this paper, we propose a new approach for workload scaling in uniprocessor real-time embedded systems. a deterministic algorithm is adopted to selectively fed hardware events into a system, and an event-driven task model is introduced to formulate complex precedence constraints among tasks. such a new approach removes the need for the adjustments of task periods and task phasing, which is crucial for many time-driven systems. the proposed approach was implemented in a real-time surveillance system, for which good accuracy and responsiveness were obtained under stressing workloads.
a new cell-based clustering method for large, high-dimensional data in data mining applications. recently data mining applications require a large amount of high-dimensional data. however, most clustering methods for data miming do not work efficiently for dealing with large, high-dimensional data because of the so-called 'curse of dimensionality'[1] and the limitation of available memory. in this paper, we propose a new cell-based clustering method which is more efficient for large, high-dimensional data than the existing clustering methods. our clustering method provides an efficient cell creation algorithm using a space-partitioning technique and uses a filtering-based index structure using an approximation technique. finally, we compare the performance of our cell-based clustering method with the clique method in terms of cluster construction time, precision, and retrieval time. the experimental results show that our clustering method achieves better performance on cluster construction time and retrieval time.
an efficient management scheme for large-scale flash-memory storage systems. flash memory is among the top choices for storage media in ubiquitous computing. with a strong demand of high-capacity storage devices, the usages of flash memory quickly grow beyond their original designs. the very distinct characteristics of flash memory introduce serious challenges to engineers in resolving the quick degradation of system performance and the huge demand of main-memory space for flash-memory management when high-capacity flash memory is considered. although some brute-force solutions could be taken, such as the enlarging of management granularity for flash memory, we showed that little advantage is received when system performance is considered. this paper proposes a flexible management scheme for large-scale flash-memory storage systems. the objective is to efficiently manage high-capacity flash-memory storage systems based on the behaviors of realistic access patterns. the proposed scheme could significantly reduce the main-memory usages without noticeable performance degradation.
enhanced object management for high performance web proxies. the dramatic increase of www traffic on the internet has led to the wide use of web proxy. the web proxies can be used to improve security, save network bandwidth and reduce network latency. however, as the network bandwidth increased, the general-purpose file system is rapidly becoming the performance bottleneck of web proxies. in this paper, we propose an enhanced object management, called unified, which is a user-level technique for improving the performance of web proxy. in unified method, several techniques are developed to improve the disk i/o performance. instead of the traditional trace-driven simulation, we employ polygraph 2.5.4 with polymix-3 workload to evaluate our system realistically. to investigate how the proxy performance depends on the equipped disk, we offer two sets of test machines. one is equipped with one ide disk and the other is equipped with five scsi disks. experimental results show that, in both tests, our method can improve the proxy performance dramatically by reducing the overhead associated with disk i/o.
developing component based adaptive applications in mobile environments. today, although the system supports for developing distributed applications become mature, they are inadequate for mobile environments where the runtime resources vary considerably or even disappear spontaneously. the objective of our work is to provide appropriate supports to facilitate the development of applications that adapt their behaviors to mobile environment changes. in this paper we present a framework based on a structured adaptive component model and two underlying middleware services, respectively, for monitoring environment variations and for coordinating adaptation actions of several components. we demonstrate the validity of our ideas through an adaptive video on demand application based on a prototype implementation of our framework. we also give the benefit and overhead of the proposed adaptation mechanisms.
a new algorithm for computing transitive closures. in this paper, we propose a new algorithm for computing transitive closures. it needs only o(e&middot;b) time and o(n&middot;b) space, where n represents the number of the nodes of a dag (directed acyclic graph), e the numbers of the edges, and b the dag's breadth.
a new approach for gene prediction using comparative sequence analysis. the availability of large fragments of genomic dna makes it possible to apply comparative genomics for identification of protein-coding regions. in this work, a comparative analysis is conducted on homologous genomic sequences of organisms with different evolutionary distances and the conservation of the non-coding regions between closely related organisms is found. in contrast, more distance shows much less intron similarity but less conservation on the exon structures. this study sought to illuminate the impact of evolutionary distances on the performance of the proposed gene-finding program based on the cross-species sequence comparison. base on the finding from comparative study and training of data sets, we proposed a model by which coding sequence could be identified by comparing sequences of multiple species, both close and approximately distant. the reliability of the proposed method is evaluated in terms of sensitivity and specificity, and results are compared to those obtained by other popular gene prediction programs. provided sequences can be found from other species at appropriate evolutionary distances, this approach could be applied in newly sequenced organisms where no species-dependent statistical models are available.
similar_join: extending dbms with a bio-specific operator. existing sequence comparison software applications lack adequate automation, abstraction, performance, and flexibility. users need a new way of studying and applying sequence comparisons in the post-genomics era. we invented and developed a new bio-specific database management system (dbms) operator, similar_join, to abstract the labor-intensive batch sequence similarity search task into a syntactically concise database operation. we implemented the similar_join operator as part of a relational operator package. this implementation enabled us to write simple pl/sql scripts within the dbms to accomplish routine sequence similarity searches conveniently, for example, a "batch blast" that compares 7,000 human genes against 500,000 human expressed sequence tags (est) in a few hours. we also implemented a simple version of similar_join as a database operator in the extended data cartridge of oracle 8i object-relational dbms. when fully integrated into sql language extensions, we demonstrated this operator could enable biology users to achieve interesting complex biological queries previously impossible inside the dbms.
signature file hierarchies and signature graphs: a new index method for object-oriented databases. in this paper, we propose a new index structure for object-oriented databases. the main idea of this is a graph structure, called a signature graph, which is constructed over a signature file generated for a class and improves the search of a signature file dramatically. in addition, the signature files (accordingly, the signature graphs) can be organized into a hierarchy according to the nested structure (called the aggregation hierarchy) of classes in an object-oriented database, which leads to another significant improvements.
on the transitive closure representation and adjustable compression. a composite object represented as a directed graph (digraph for short) is an important data structure that requires efficient support in cad/cam, case, office systems, software management, web databases, and document databases. it is cumbersome to handle such objects in relational database systems when they involve ancestor-descendant relationships (or say, recursive relationships). in this paper, we present a new encoding method to label a digraph, which reduces the footprints of all previous strategies. this method is based on a tree labeling method and the concept of branchings that are used in graph theory for finding the shortest connection networks. a branching is a subgraph of a given digraph that is in fact a forest, but covers all the nodes of the graph. on the one hand, the proposed encoding scheme achieves the smallest space requirements among all previously published strategies for recognizing recursive relationships. on the other hand, it leads to a new algorithm for computing transitive closures for dags (directed acyclic graph) in o(e&middot;b) time and o(n&middot;b) space, where n represents the number of the nodes of a dag, e the numbers of the edges, and b the dag's breadth. the method can also be extended to graphs containing cycles. especially, based on this encoding method, a multi-level compression is developed, by means of which the space for the representation of a transitive closure can be reduced to o((b/dk)&middot;n), where k is the number of compression levels and d is the average outdegree of the nodes.
a complex biological database querying method. many biological information systems rely on relational database management systems (rdbms) to manage high-throughput biological data. while keeping these data well archived, organized, and integrated in a common repository is still a challenging task, performing complex queries, i.e., explorative and abstract ad hoc user questions in biology, is an even formidable task often substituted by writing complicated software programs. in this work, we propose a "complex query modeling" method to address the challenge of complex querying in biological domains. query modeling consists of four distinct but interdependent phases of activities: representation of high-level problems, transformation of problems into connected query interfaces, designing database query structures, and translating query plans into high-performing sql statements. at each stage, we use different notations and query modeling practices. using gene indexing project as a case study, we show that query modeling enables prototypical development of high-quality sql solutions to an inherently abstract and vague user query question, which requires genechip designers to sift through millions of database records, process data in dozens of steps, and make myriads of intermediate decisions. we believe our "complex query modeling" method is applicable to other bioinformatics domains with needs for complex database queries.
an automated negotiation mechanism based on co-evolution and game theory. the problems associated with current automated negotiation approaches are of little feasibility in practical industry applications. this paper describes a new method that combines a game theory approach and a co-evolutionary approach to support an effective negotiation model for agents to resolve conflict. under this proposed method, the agents without knowing the other agent's strategies and payoffs, produce an optimised resolution that complies nash equilibrium and pareto efficiency concepts. we use a finitely repeated prisoner's dilemma game to demonstrate the proposed method.
real-time task scheduling anomaly: observations and prevention. this research is motivated by the practical needs in the porting of embedded software over platforms and the well-known multiprocessor anomaly [2, 3]. in particular, we consider the task scheduling problem when the system configuration changes. we show that new violations of the timing constraints of tasks might occur even when a more powerful processor or device is adopted. the concept of scheduler stability and rules are then proposed to prevent scheduling anomaly from happening for task executions that might be involved with task synchronization or i/o access. finally, we explore policies in bounding the the duration time of scheduling anomaly.
a new method of generating synchronizable test sequences that detect output-shifting faults based on multiple uio sequences. the objective of testing is to determine the conformance between a system and its specification. when testing distributed systems, the existence of multiple testers brings out the possibility of synchronization problems among remote testers and the possibility that output-shifting faults go undetected. this paper proposes a new method of generating minimal synchronizable test sequences that detect output-shifting faults based on multiple uio sequences. the procedure of test generation involves two steps: constructing several auxiliary digraphs from a given specification and finding a rural chinese post tour (rcpt) in the resultant digraph. when constructing the auxiliary digraphs, different from all the former methods, we use vertices to denote transitions and edges to represent two consecutive transitions. in terms of property and application, the proposed method can construct a relatively simple digraph which makes test generation easily. after applying it to practice, we got hold of better results than the existing methods.
combining supervised and unsupervised monitoring for fault detection in distributed computing systems. fast and accurate fault detection is becoming an essential component of management software for mission critical systems. a good fault detector makes possible to initiate repair actions quickly, increasing the availability of the system. the contribution of this paper is twofold. first a new concept of supervised and unsupervised monitoring is proposed for system fault detection. we use a statistical method, canonical correlation analysis (cca), to model the contextual dependencies between system inputs u and internal behavior x. by means of cca, the space x is transformed into two subsets of variables, which are monitored in a supervised and unsupervised manner respectively. by doing so, our approach can reduce the false alarms resulting from unusual workload changes, and hence achieve high fault detection rate. second, in order to test the performance of our approach, we simulate a variety of system faults in a real e-commerce application based on the multi-tiered j2ee architecture. experimental results demonstrate that the cca based approach can detect injected failures at their early stages when unusual phenomenon is very weak, and hence contribute to enormous time and cost savings in managing large scale distributed systems.
profit-driven uniprocessor scheduling with energy and timing constraints. energy-aware scheduling has received much attention in recent years, especially for systems with serious considerations on energy consumption. while most previous work focuses on the minimization of energy consumption, this paper exploits the maximization of the entire system profit under energy and timing constraints. we propose a greedy approximation algorithm with a 2-approximation ratio. a fully polynomial time approximation scheme (fptas) is also proposed, which is an optimal approximation algorithm unless p = np. for each specified amount of error tolerant to users, the approximation algorithm could provide trade-offs among the specified error, the running time, the approximation ratio, and the memory space complexity. it provides ways for system engineers to trade performance with implementation constraints.
cluster rendering of skewed datasets via visualization. information visualization is commonly recognized as a useful method for understanding sophistication in large datasets. in this paper, we introduce a flexible clustering approach with visualization techniques, aiming at the datasets that have skewed cluster distribution. this paper has three contributions. first, we propose a framework vista that incorporates information visualization methods into the clustering process in order to enhance the understanding of the intermediate clustering results and allow user to revise the clustering results easily. second, we develop a visualization model that maps multidimensional dataset to 2d visualizations while preserving or partially preserving clusters. third, based on the visualization model, a set of operating rules are proposed to guide the user rendering clusters efficiently. experiments show that the vista system can yield lower error rates for real datasets than typical automated algorithms.
an integrated computational proteomics method to extract protein targets for fanconi anemia studies. fanconi anemia (fa) is a rare autosomal genetic disease with multiple birth defects and severe childhood complications for its patients. the lack of sequence homology of the entire fa complementation group proteins in such as fancc, fancg, fanca makes them extremely difficult to characterize using conventional bioinformatics methods. in this work, we describe how to use computational methods to extract protein targets for fa, using protein interaction data set collected for fanc group c protein (fancc). we first generated an initial set of 130 fa-interacting proteins as "fancc seed proteins" by merging an in-house experimental set of fancc tandem affinity purification (tap) pulldown proteomics data identified from mass spectrometry methods with publicly available human fancc-interacting proteins. next, we expanded the fancc seed proteins using a nearest-neighbor method to generate a fancc protein interaction subnetwork of 948 proteins in 903 protein interactions. we show that this network is statistically significant, with high indices of aggregation and separations. we also show a visualization of the network, support the evidence that many well-connected proteins exists in the network. further, we developed and applied an interaction network protein scoring algorithm, which allows us to calculate a ranked list of significant fa proteins. our result has been supporting further biological investigations of disease biologists on our team. we believe our method can be generalized to other disease biology studies with similar problems.
tree inclusion algorithm, signatures and evaluation of path-oriented queries. in this paper, a method to evaluate path-oriented queries in document databases is proposed. the main idea of this method is to handle the evaluation of a path-oriented query as a tree inclusion problem. a new algorithm for tree-inclusion is discussed, which integrates a top-down process into a bottom-up searching strategy. on the one hand, the algorithm can be arranged to access the data on disk page-wise and fits therefore within a database environment. on the other hand, the algorithm can be combined with the signature indexing technique to cut off useless subtree inclusion checking as early as possible. experiments have been conducted to compare this method with some existing approaches, which shows that the integration of the signatures into the top-down tree inclusion is highly promising.
hierarchical model-based clustering of relational data with aggregates. this paper proposes a propositional method for hierarchical model-based clustering of relational data. we define a new type of aggregate -- frequency aggregate, which has a vector data type and can be used to record not only the observed values but also the distribution of the values of an attribute. a hierarchical agglomerative clustering algorithm with log-likelihood distance is then applied to cluster the aggregated data tentatively, and a mixture model-based method with the em algorithm is developed to perform a further relocation clustering, in which bayes information crieterion is used to determine the optimal number of clusters.
template detection for large scale search engines. templates in web sites hurt search engine retrieval performance, especially in content relevance and link analysis. current template removal methods suffer from processing speed and scalability when dealing with large volume web pages. in this paper, we propose a novel two-stage template detection method, which combines template detection and removal with the index building process of a search engine. first, web pages are segmented into blocks and blocks are clustered according to their style features. second, similar contents sharing the common layout style are detected during the index building process. the blocks with similar layout style and content are identified as templates and deleted. our experiment on eight popular web sites shows that our method achieves 20-40% faster than shingle and sst methods with close accuracy.
the bitmap-based feature selection method. cbr(case-based reasoning) is a problem solving technique that reuses past cases and experiences to find a solution to current problems. a critical issue in case-based reasoning is to select the correct and enough features to represent a case. however, this task is difficult to carry out since such knowledge is often exhaustively captured and cannot be represented successfully. in this paper, the new, efficient feature selection method originated from bitmap indexing and rough set techniques will be proposed. the bitmap-based feature selection method is proposed for discovering the optimal feature sets for decision-making problems. and the corresponding indexing and selecting algorithms for such feature selection method are also proposed. finally, some experiments and comparisons are given and the result shows the efficiency and accuracy of our proposed method.
deontic relevant logic as the logical basis for legal information systems. this paper discusses why classical mathematical logic, its various classical conservatives extensions, or its non-classical alternatives are not suitable candidates for the right fundamental logic to underlie legal information systems, and show that deontic relevant logic is a more hopeful candidate for the right fundamental logic.
arcats: a scalable compositional analysis tool suite. automatic verification techniques, which analyze all processes at once, typically do not scale well for large, complex concurrent software systems because of the theoretic barrier - pspace complexity in worst case. in this paper, we present our tool named arcats (architecture refactoring and compositional analysis tool suite). arcats consists a set of tools to combat state explosion in a divide-and-conquer, hierarchical manner, which is also known as compositional analysis. we build these tools to seek out best combinations to scale the verification to larger software systems.
tinygals: a programming model for event-driven embedded systems. networked embedded systems such as wireless sensor networks are usually designed to be event-driven so that they are reactive and power efficient. programming embedded systems with multiple reactive tasks is difficult due to the complex nature of managing the concurrency of execution threads and consistency of shared states. this paper describes a globally asynchronous and locally synchronous model (tinygals) for programming event-driven embedded systems. software components are composed locally through synchronous method calls to form modules, and asynchronous message passing is used between modules to separate the flow of control. in addition, a guarded yet synchronous model (tinyguys) is designed to allow thread-safe sharing of global state by multiple modules without explicitly passing messages. this programming model is structured such that all asynchronous message passing code and module triggering mechanisms can be automatically generted from a high-level specification. we have implemented the programming model and code generation facilities on a wireless sensor network platform known as the berkeley motes. as an example, we have redesigned a multi-hop ad hoc communication protocol using the tinygals model.
providing resource allocation and performance isolation in a shared streaming-media hosting service. the trend toward media content hosting is seeing a significant growth as more rich media is used in the enterprise environment and as it becomes mission critical for businesses. a shared media hosting service supports the illusion that each hosted service has its own media server, when, in reality, multiple "logical hosts" may share one physical host. for such a shared media hosting service, the ability to guarantee a specified share of server resources to a particular hosted service is very important. we present sharedmediaguard - a shared media hosting infrastructure that can efficiently allocate the predefined shares of server resources to the hosted media services. the proposed solution is based on a unified cost function that uses a single value to reflect the combined resource requirement such as cpu, bandwidth and memory necessary to support a particular media stream depending on the stream bit rate and type of access (memory file access or disk file access). our evaluation of sharedmediaguard compared to the traditional, disk-based allocation strategy that assumes all content must be served from disk reveals a factor of two improvement in server throughput while providing performance isolation and qos guarantees among the hosted services.
mamview: a visual tool for exploring and understanding metric access methods. the mamview framework is a data exploration tool that allows developers and users of metric access methods (mams) to explore and share dynamic and interactive 3d presentations of a mam, making the understanding of those structures easier. it is able to create visual representations of metric datasets, including high-dimensional and non-dimensional information. this is achieved by using an extension of the fastmap algorithm. this framework was developed as a practical tool that has been successfully applied to study existing mams, helping both new and experienced users to better understand them. the mamview was also applied to a new under development mam. with mamview in hands, the development team of this mam was able to drill-down its algorithms, quickly finding problems and also potential points for improvement and optimizations. our focus on this work is on proposing an intuitive yet powerful visualization framework that can be easily employed to build intuitive visual presentations that can bypass the drawback of mams dealing with datasets with no spatial representation. besides mamview being a powerful visualization tool, its greatest strengths are the ability to interactively explore a visual presentation of a mam at any level of detail, and the ability to seamlessly query and produce graphical representations in xml format that can be straightforward executed. this paper presents the mamview framework and its main techniques, describes the current tool, and reports on our experiences in applying it to real applications.
contour-based partial object recognition using symmetry in image databases. this paper discusses the problem of partial object recognition in image databases. we propose the method to reconstruct and estimate partially occluded shapes and regions of objects in images from overlapping and cutting. we present the robust method for recognizing partially occluded objects based on symmetry properties, which is based on the contours of objects. our method provides simple techniques to reconstruct occluded regions via a region copy using the symmetry axis within an object. based on the estimated parameters for partially occluded objects, we perform object recognition on the classification tree. since our method relies on reconstruction of the object based on the symmetry rather than statistical estimates, it has proven to be remarkably robust in recognizing partially occluded objects in the presence of scale changes, rotation, and viewpoint changes.
on utility accrual processor scheduling with wait-free synchronization for embedded real-time software. we present the first wait-free utility accrual (ua) real-time scheduling algorithms for embedded real-time systems. ua scheduling algorithms allow application activities to be subject to time/utility function (tuf) time constraints, and optimize criteria such as maximizing the sum of the activities' attained utilities. we present ua algorithms that use wait-free synchronization for mutually exclusively accessing shared data objects. we derive lower bounds on the possible accrued utility with wait-free over their lock-based counterparts, while incurring the minimum possible additional space costs. our implementation measurements on a posix rtos reveal that (during under-loads), the wait-free algorithms yield optimal utility for step tufs and significantly higher utility (than lock-based) for non-step tufs.
design and implementation of a kernel resource protector for robustness of linux module programming. loadable kernel modules supported by linux provides lots of benefits such as a small-sized kernel, on-demand loading, and easy software upgrading. however, since modules are executed in a privileged mode, trivial misuses in a module may cause critical system halts or deadlock situations. this paper presents a kernel resource protector which prevents kernel from faults generated by modules. the protector models the system in two objects: module object and resource object. by observing the interrelations between the two objects, the protector can detect misuses of modules and take actions to resolve the erroneous situations. implementation study has shown that the protector can find out memory leaks wasted by modules and can reclaim leaks without degrading system performance. the proposed protector makes linux more robust, which is required indispensably in the system equipped with nvram (non volatile ram) such as fram and pram.
an extension of dead end elimination for protein side-chain conformation using merge-decoupling. a two-phase strategy is widely adopted to solve the side-chain conformation prediction (sccp) problem. phase one is a fast reduction phase removing large numbers of rotamers not existing in the gmec. phase two (optimization phase) uses heuristics or exhaustive search to find a good/optimal solution. presently, dee (dead end elimination) is the only deterministic reduction method for phase one. however, to achieve convergence in phase two using dee, the strategy of forming super-residues is used. this quickly leads to a combinatorial explosion, and becomes inefficient in this paper, an improvement of the dee process by forming super-residues efficiently is proposed for phase one. the method basically merges residues into pairs based on some merging criteria. simple goldstein is then applied until no more elimination is possible. a decoupling process then reforms the original residues sans removed rotamers and rotamer pairs. the process of merging and elimination is repeated until no more elimination is possible. initial experiments have shown the method, called merge-decoupling dee, can fix up to 25% of the unfixed residues coming out of simple goldstein dee.
creating and shareing web notes via a standard browser. today practitioners in education actively publish their instructional materials as html documents, using a variety of media. yet, in most cases, third parties can only passively read the documents displayed in their browsers. this partly accounts for why students in web-based courses continue to take notes and get feedback on assignments from their teachers on paper documents [9]. in this paper, we describe an intuitve web annotation environment that allows users to annotate directly on any dhtml-compliant portions of web page using a standard browser, for private, group or public use along with support for voice synthesis and notification. in makes extensive use of dhtml to realize the interactive markup effects and offers capabilities not available in existing systems. our implementation is among the few systems currently available that make use of dhtml for creating a wide range of group services within web browsers.
coordination middleware for xml-centric applications. this paper focuses on coordination middleware for distributed applications based on active documents and xml technologies. it introduces the main concepts underlying active documents and xml then, the paper goes into details about the problem of defining a suitable middleware architecture to effectively support coordination activities in applications including active documents and mobile agents, by specifically focusing on the role played by xml technologies in that context. according to a simple taxonomy, the characteristics of several middleware systems are analyzed and evaluated. this analysis enables us to identify the advantages and the shortcoming of the different approaches, and to identify the basic requirements of a middleware for xml-centric applications.
weaving concerns in model based development of data-intensive web applications. the last decade witnessed a pervasive growth of web applications intended as environments for distributed applications. many design methodologies have been proposed to cope with the technical intricacy of such systems. although each of them proposes its own constructs, they share a common metamodel enabling the designer to describe web applications under three different views: data, navigation and presentation. while the constructs can be unified in such a metamodel, consistency among the views is guaranteed by less formal relations being essentially based on name conventions and/or ad-hoc tool support.this paper proposes explicit weaving models to define rigorous connections between the different artifacts produced during a system development, in order to enhance their reuse and maintenance and perform operations based on the connection semantics. these structural mappings do not interfere with the definition of the views on either side, achieving a clear separation of views and their connections and enabling the use of general purpose theories and tools.
dana (digital archive network for anthropology): a model for digital archiving. this is a report of work on an internet-based digital library called the digital archive network for anthropology (dana). dana provides a model for a generalized method for implementing digital archives. this federation of databases will link researchers, students, and the general public to distributed databases that include realistic, accurate, three-dimensional (3d), visual representations of artifacts, fossils, and other objects, along with 2d digitized documents (e.g., maps, plan views, excavation profiles, and photographs) and various associated data. dana will have a strong data mining component which will allow users to find relationships in the data which correspond to facts about the actual artifacts and fossils. the data mining techniques involve a new spatial data mining structure called the ptree. dana is being created through development and implementation of cross-platform, open standards that will facilitate interoperability and exchange of information between remote systems. dana enables dynamic use of digital models, virtual measurement tools, and an array of data supplied by contributing content providers (collaborators) for education and scholarly research.
disentangling the implementation of local-to-global transformations in a rewrite rule transformation system. transformation rules are often used to implement compilers for domain-specific languages. in an ideal situation, each transformation rule is a modular unit transforming one input element of the source program into a new element of the output program. however, in practice, transformation rules must be written which take one input element and produce several new elements belonging to various locations in the output program, the so-called local-to-global transformations. the implementation of such transformations is very complex and tightly coupled which imposes severe constraints on maintenance and evolvability. in this paper, we propose a transformation architecture on top of rewrite rules to loosen this coupling. the resulting transformation system combines the simplicity and modularity properties of rewrite rules with a new semi-automatic composition system that enables the implementation of local-to-global transformations without hampering maintenance and future evolutions.
from collective knowledge to e-books. this paper describes a new way of creating electronic books through the unsupervised collaborative work of several authors. for this aim a web-based groupware system for knowledge construction is proposed. this system allows building web sites that can be described as electronic books where relevant and structured knowledge about some area or topic can be found.these electronic books are adaptive: they are in continuous evolution as a response to user contributions. users that are interacting with the electronic book form a virtual community that is in charge of the creation of the structure and the contents of the book in an unsupervised way.the system has being tested with several groups of students at universidad autonoma de madrid, who have constructed electronic books about some of their academic courses.
a software framework for efficient system-level performance evaluation of embedded systems. the sesame environment provides modeling and simulation methods and tools for the efficient design space exploration of heterogeneous embedded multimedia systems. in this paper we describe the sesame software system and demonstrate its capabilities using several examples. we show that sesame significantly reduces model construction time through the use of modeling component libraries, hierarchy, and advanced model structure description features.
towards differentiation-enabled fortran 95 compiler technology. we present a novel approach to generating derivative code for mathematical models implemented as fortran 95 programs using automatic differentiation inside a compiler. this technique allows us to combine the advantages of both operator overloading and source transformation based tools for automatic differentiation. furthermore, the compiler's infrastructure for syntactic, semantic, and static data flow analysis can be built on.
on contracting different behavioral properties in component-based systems. using different specification formalisms together is necessary to leverage better reliability on component-based systems. the confract system provides a contracting system for hierarchical software components, but currently, only executable assertions are supported. in this paper, we describe how to integrate other kinds of formalism in confract. we propose a domain specific language and integration tools that enable designers to describe the observations needed to appropriately verify their specifications.
a uml 2-compatible language and tool for formal modeling real-time system architectures. architrio is a formal language, which complements uml 2.0 concepts with a formal, logic-based notation that allows users to state system-wide properties, both static and dynamic, including real-time constraints. this paper summarizes the architrio approach, and presents the core elements of a tool supporting it, called architrident, which is currently under development. this tool is a plugin of the trio-based editing and verification trident tool suite.
knowledge based approach to semantic composition of teams in an organization. finding rapidly suitable experts in an organization to compose a team able to solve specific tasks is a typical problem in large consulting firms. in this paper we present a description logics approach to the semantic-based composition of ad-hoc teams based on individuals skill profiles and on task description. the selection process is carried out using a novel concept covering algorithm that exploits the recently proposed concept abduction inference service in description logics. the approach has been deployed as part of a skill management system that takes text files with curricula and project specifications as inputs and extracts from them available individual profiles and task descriptions, according to an ontology modeling skills.
editorial message: special track on web and e-business applications. the world wideweb has become the standard computing platform for the development of new-generation information systems. a new tide of web-based e-business applications (such as corporate portals, network-based supply chains and market places, etc.) is driving the need for a more open, flexible and distributed infrastructure, together with appropriate development methodologies and theoretical settings. today's web applications involve skills from many different areas of computer science, including databases, ai and agent based applications, programming languages and algorithms, distributed computing, information retrieval, semantic modeling, etc. for this reason we proposed a track on web and e-business applications based on the following main topics: data models for the world wide web, web data management, languages for the world wide web and xml, e- business and web services, transactions on the world wide web, security and integrity issues for the www, query systems for the world wide web, management and storage of web information, information retrieval and search engines for the web, web semantics, data integration over the world wide web, data-intensive applications on the world wide web, web architectures.we received 30 submissions, which were extensively reviewed for originality, significance, technical soundness and clarity of presentation. the submitted papers covered most of the proposed topics. the number of submissions distributed on each continent has been the following: 16 from europe (53%), 9 from north america (30%), 3 from asia (10%), 1 from africa (3%) and 1 from australia (3%). 12 papers corresponding to the 40% of the submitted papers have been selected for presentation at the conference, with the following distribution: 7 from europe, 3 from america, 1 from asia and 1 from australia.
angular measures for feature selection in text categorization. text categorization, which consists of automatically assigning documents to a set of categories, usually involves the management of a huge number of features. most of them are irrelevant or introduce noise which misleads the classifiers. thus, feature reduction is often performed in order to increase the efficiency and effectiveness of the classification. in this paper we propose to select relevant features by means of what we call angular measures, which are simpler than other usual measures applied for this purpose. we carry out experiments over two different corpora and find that the proposed measures perform equal or better than some of the existing ones.
conceptual modeling of xml data. in this paper, we propose a conceptual model for building schemata for xml documents. in particular, we define the conceptual model uxs (uml & xml schema), which is based on uml and provides several graphical constructs to help the programmer to define complex xml schemata. the model is completed by the support of several translation approaches for building the xml schema code, corresponding to the defined conceptual schema. a prototype has been developed, and allows the conceptual definition of xml schemata by using the introduced approach.
specifying temporal data models for semistructured data by a constraint-based approach. in the past few years some models for semistructured temporal data, which propose different strategies to deal with temporal dimensions, have been defined. in this paper we analyze these models by applying the recently proposed meta-model gsmm (general semistructured meta-model) for semistructured information. gsmm allows us to represent semistructured temporal data models with a unifying formalism; constraints that are specified in these models are also represented and classified on the basis of their expressiveness.
architectures for a temporal workflow management system. workflows describe business processes as the coordinated execution of simple activities (tasks) by human or automatic executors (agents). workflow management systems (wfms) are software systems supporting the automatic execution of workflows. most wfmss rely on database management systems (dbms) where temporal aspects, which are relevant for the execution of a workflow, are managed explicitly. in this paper we discuss different architectures for a temporal wfms: then we propose yet another workflow system which novelly manages temporal aspects via a temporal database system, composed by a temporal layer on top of a relational dbms (oracle). the adoption of a temporal database system both benefitted the development of the engine and increased its efficiency by allowing some additional features, as the management of process model evolution and the selection of executing agents via a workload balance over time.
a parallel index for semistructured data. database systems are increasingly being used to manage semistructured data, which may not have a fixed structure or set of relationships between data items. indexes which use tree structures to manage semistructured data become unbalanced and difficult to parallelize due to the complex nature of the data. we propose a mechanism by which an unbalanced vertical tree is managed in a balanced way by additional layers of horizontal index. then, the vertical tree can be partitioned among parallel computing nodes in a balanced fashion. we discuss how to construct, search and update such a horizontal structure using the example of a patricia trie index. we also present simulation results that demonstrate the speedup offered by such parallelism, for example, with three-way parallelism, our techniques can provide almost a factor of three speedup.
automatic test program generation for pipeline processors. the continuous advances in microelectronics design are creating a significant challenge to design validation in general, but tackling piplined microprocessors is remarkably more demanding. this paper presents a methodology to automatically induce a test program for a microprocessor maximizing a given verification metric. the approach exploits a new evolutionary algorithm, close to genetic programming, able to cultivate effective assembly-language programs. the proposed methodology was used to verify the dlx/pii, an open-source processor with a 5-stage pipeline. code-coverage was adopted in the paper, since it can be considered the required starting point for any simulation-based functional verification processes. experimental results clearly show the effectiveness of the approach.
an evolutionary algorithm for reducing integrated-circuit test application time. the cost for testing integrated circuits represents a growing percentage of the total cost for their production. the former strictly depends on the length of the test session, and its reduction has been the target of many efforts in the past. this paper proposes a new method for reducing the test length by adopting a new architecture and exploiting an evolutionary optimization algorithm. a prototype of the proposed approach was tested on iscas standard benchmarks and the experimental results show its effectiveness.
operating system multilevel load balancing. this paper describes an algorithm that allows linux to perform multilevel load balancing in numa computers. the linux scheduler implements a load balancing algorithm that uses structures called sched domains to build a hierarchy that represents the machine's topology. although sched domains implementation allows linux to build a multilevel hierarchy to represent multilevel machines, the generic code of the current kernel version builds no more than two levels in the sched domains hierarchy. thus, for numa systems with three or more memory access levels, the constructed hierarchy does not represent correctly the machine's topology. when linux load balancing algorithm uses an incorrect sched domains hierarchy, process execution time can increase, because processes can be moved to nodes that are distant from their memory areas. in order to solve this problem, we have implemented an algorithm to build multilevel sched domains hierarchies for numa computers. our proposed algorithm uses acpi slit table data to recognize how many memory access levels a machine contains. then, it builds an n-level sched domains hierarchy, where n is the number of memory access levels. through benchmarking and simulation results we demonstrate that the linux load balancing performance when the sched domains hierarchy is built using our proposed algorithm is better than using the current linux algorithm.
software performance model-driven architecture. model transformations in mda mostly aim at stepping from a platform independent model (pim) to a platform specific model (psm) from a functional viewpoint. in order to develop high quality software products, non-functional attributes (such as performance) must be taken into account. in this paper we extend the canonical view of the mda approach to embed additional types of models that allow to structure a model driven approach keeping into account performance issues. we define the relationships between mda typical models and the newly introduced models, as well as relationships among the latter ones. in this extended framework new types of model-to-model transformations also need to be devised. we place an existing methodology for transforming software models into performance models within the scope of this framework.
a reflective middleware architecture to support adaptive mobile applications. mobile applications are required to operate in environments in which the availability for resources and services may change significantly during system operation. as a result, mobile applications need to be capable of adapting to these changes to offer the best possible level of service to their users. however conventional middleware is limited in its capability of adapting to the environment changes and different users requirements. computational reflection applied to middleware design has introduced a new research field, reflective middleware. in this paper we propose a reflective middleware architecture which can be used to develop adaptive mobile applications. in order to validate the architecture proposed we developed a prototype using the web services technology which focuses on the problem of adapting on a set of attributes in a coordinated manner.
incremental collaborative filtering for mobile devices. this paper describes how collaborative filtering can be used for mobile devices. when the user is connected to a central repository, the algorithm selects a subset of profiles to store on the device. when the user is not connected to the repository, the predictions can be incrementally updated to reflect new or updated ratings. experiments on a movie data set show that the method can dramatically reduce the data needed while still performing nearly as good as a centralized approach.
classifying biological articles using web resources. text classification systems on biomedical literature aim to select relevant articles to a specific issue from large corpora. most systems with an acceptable accuracy are based on domain knowledge, which is very expensive and does not provide a general solution. this paper presents a novel approach for text classification on biomedical literature, involving the use of information extracted from related web resources. we validated this approach by implementing the proposed method and testing it on the kdd2002 cup challenge: bio-text task. results show that our approach can effectively improve efficiency on text classification systems for biomedical literature.
a contingency view of organizational infrastructure requirements engineering. delivery of it projects in today's rapidly changing business environment is a challenge. conventional investment approaches result in lumpy capital allocations, which encourage managers to include many potential future business requirements in each capital request. this locks in the delivery of future requirements despite high market uncertainty. the resulting projects are large and complex from both a technical and management perspective. in the management literature, new frameworks are emerging that draw on real options valuations to justify early infrastructure investment and provide fine-grained control over business initiatives in an uncertain world. business managers can then build on the infrastructure by selecting business initiatives to maximise option value. however, this requires engineering approaches that separates infrastructure and business requirements and minimises their dependencies. this paper explores a contingency approach to requirements engineering (re) to minimise initial requirements and maximise future strategic options, challenging the research community's dominant paradigm of completeness, correctness and consistency.
protein classification using transductive learning on phylogenetic profiles. phylogenetic profiles of proteins - strings of ones and zeros encoding respectively the presence and absence of proteins in a group of genomes - have recently been used to identify homologous proteins and/or proteins that are functionally linked, such as participating in a metabolic pathway. we proposed a novel learning method for protein classification based on phylogenetic profiles, which takes into account both the phylogenetic tree structure and the likelihood of proteins presence in genomes. the method consists of a mechanism to extend the profiles with extra bits encoding the phylogenetic tree, whose interior nodes, representing hypothetical ancestral genomes, are scored in a way to reflect their chances of developing divergence in the descendants. the scoring scheme also incorporates the likelihood of proteins presence in genomes as weighting factors, which are collected from the training data initially and integrated as part of kernel of a support vector machine. in a transductive learning scheme, when the svm is used for classifying test data, the weighting factors are updated iteratively using the predicted results. we tested our method on the proteome of saccharomyces cerevisiae and used the mips classification as a benchmark. the results showed that the classification accuracy was greatly increased.
bootstrapping multi-party ad-hoc security. in pervasive-computing scenarios users may wish to achieve some degree of security in their interaction with other people or equipment, in contexts where they cannot be confident of the others' long-term identities and where there may be no reliable pki. we examine the problem of bootstrapping security in an ad-hoc network formed by a group of users.in [4] a number of protocols using low-bandwidth channels involving the human agent(s) "in the loop" to bootstrap secure communication over an untrusted infrastructure were presented, the point being that the attacker's powers are more limited with regard to these empirical channels in one or more respects than in the standard dolev-yao view. the two-party protocols proved easy to verify [3] (relative to those weakened powers) by adapting the csp/fdr-based approach of casper[9], but the multi-party network-formation protocol (based on a combination of low bandwidth non-forgeable channels and an ordinary dolev-yao communication medium) proved more problematic.addressing the verification of this protocol [11] led to consideration of a number of simplified variants, which appear interesting in their own right.
wrapping-oriented classification of web pages. data extraction from html web pages is performed by software programs called wrapper. writing wrappers is a costly and labor intensive task; recently several proposal have attacked the problem of automatically generating wrappers. in this paper, we study a problem related to the automation of the wrapping generation process: given a portion of a web site to wrap, we develop techniques to cluster its html pages into page classes with homogeneous organization and layout; these classes can become the input to the wrapper generation process. also, once a wrapper library has been generated for a bunch of web sites, our techniques can be used in order to select, for any new page downloaded from these site, the right wrapper in the library. based on the proposed techniques we have developed a software prototype, and conducted several experiments on html pages from real-life web sites.
editorial message: special track on information access and retrieval. information access technologies, like for example information retrieval (ir) and information filtering (if), aim at modelling, designing and implementing systems able to provide fast and effective content-based access to a large amount of information. information can be of any kind: textual, visual, or auditory. the aim of such systems is to estimate the relevance of documents to a user information need. this is a very hard and complex task for many different reasons than a large volume of research has attempted to explain and tackle. nowadays, research in information access includes modelling, document classification and categorization, system architecture, user interfaces, data visualisation, languages, topic detection, etc.
editorial message: special track on information access and retrieval. information access technologies, like for example information retrieval (ir) and information filtering (if), aim at modelling, designing and implementing systems able to provide fast and effective content-based access to a large amount of information. information can be of any kind: textual, visual, or auditory. the aim of such systems is to estimate the relevance of documents to a user information need. this is a very hard and complex task for many different reasons than a large volume of research has attempted to explain and tackle. nowadays, research in information access includes modelling, document classification and categorization, system architecture, user interfaces, data visualisation, languages, topic detection, etc.
editorial message: special track on information access and retrieval. information retrieval (ir) aims at modelling, designing and implementing systems able to provide fast and effective content-based access to a large amount of information. information can be of any kind: textual, visual, or auditory. the aim of such systems is to estimate the relevance of documents to a user information need. this is a very hard and complex task for many different reasons that a large volume of research has attempted to explain and tackle. nowadays, research in information retrieval is central to the design and development of advanced information access technologies and spans a number of research topics including document modelling, document classification and categorization, system architecture, user interfaces, data visualisation, languages, topic detection, etc.
evaluating adaptive hypermedia authoring while teaching adaptive systems. in this paper we present an interesting experiment of combining teaching and research: the testing of mot, an adaptive hypermedia authoring tool based on the laos adaptive hypermedia authoring framework, via a class of about twenty graduate students from the eindhoven university of technology, taking a two week intensive course in adaptive systems and user modeling. we will show what the incentives of the experiment were, by giving a short description of laos, the theoretical background; then we will sketch mot, the on-line system gradually implementing laos. the focus of the paper will be the experiment itself, with its parameters: the setting and initial planning, the actual implementation and the results. finally, we will comment on the results and interpret them. moreover, we will discuss what we have learned from these results and how they pointed us to new ways of improving mot.
minimizing the reconfiguration overhead in content-based publish-subscribe. the publish-subscribe model provides strong decoupling among the components of a distributed application. this makes it amenable to highly dynamic environments. nevertheless, publish-subscribe systems exploiting a distributed event dispatcher are typically not able to rearrange dynamically their operations to adapt to changes which impact the topology of the dispatching infrastructure. this paper presents a description and analysis of a novel algorithm to deal with this kind of reconfiguration. the strength of this algorithm is its ability to minimize the portion of the system affected by the reconfiguration by exploiting a novel concept we refer to as the reconfiguration path. simulations compare our approach with two others and show a significant reduction (up to 76%) in the overhead caused by reconfiguration.
topic activation analysis for document streams based on document arrival rate and relevance. with the advance of network technology in recent years, the dissemination and exchange of massive documents has become commonplace. accordingly, the importance of content analysis techniques is increasing. topic analysis in large-scale document streams such as e-mails and news articles is an important research issue. this paper addresses techniques for "topic activation analysis" for document streams. for example, when news articles with a strong relationship to a given topic arrive frequently in a news stream, we can regard the activation level of the topic as high. in [1], kleinberg proposed a method for analyzing document streams. although the main objective of his method was to detect bursts of topics, it can also be used for topic activation analysis. his method, however, has a serious limitation in that it only looks at the arrival rate of documents and ignores the degree of relevance for each document. another limitation is that his method is "batch-oriented." this paper first proposes a novel topic activation analysis scheme that incorporates both document arrival rate and relevance to address the first problem. it then presents an incremental scheme more appropriate for a document streaming environment. the proposed schemes are validated by experiments using real cnn news articles.
analysis of an evolutionary algorithm with hypermacromutation and stop at first constructive mutation heuristic for solving trap functions. the paper presents a theoretical analysis, along with experimental studies, on a new evolutionary algorithm (ea) to optimize basic and complex trap functions. the designed evolutionary algorithm uses perturbation operators based on hypermacromutation and stop at first constructive mutation heuristic. the experimental and theoretical results show that the algorithm successfully achieves its goal in facing this computational problem. the low number of evaluations to solutions expected through the theoretical analysis of the ea have been fully confirmed by the experimental results. to our knowledge the designed ea is the state-of-art algorithm to face trap function problems.
real coded clonal selection algorithm for unconstrained global optimization using a hybrid inversely proportional hypermutation operator. numerical optimization of given objective functions is a crucial task in many real-life problems. this paper introduces a new immunological algorithm for continuous global optimization problems, called opt-immalg; it is an improved version of a previously proposed clonal selection algorithm, using a real-code representation and a new inversely proportional hypermutation operator.we evaluate and assess the performance of opt-immalg and several others algorithms, namely opt-ia, pso, arpso, de, and sea with respect to their general applicability as numerical optimization algorithms. the experiments have been performed on 23 widely used benchmark problems.the experimental results show that opt-immalg is a suitable numerical optimization technique that, in terms of accuracy, outperforms the analyzed algorithms in this comparative study. in addition it is shown that opt-immalg is also suitable for solving large-scale problems.
an accuracy-aware compression technique for multidimensional data cubes. a novel data cube compression technique, based on the well-known lsa method, is presented in this paper, along with its experimental evaluation against state-of-the-art approximate query answering techniques. particularly, the proposed technique is able to drive the lsa-based compression process in dependence on the accuracy (i.e., the quality of the approximate answers) required from olap users/applications, thus drawing new scenarios for delivering summarized knowledge extracted from huge amounts of multidimensional data.
configuring software, reconfiguring memories: the influence of integrated systems on knowledge storage, retrieval and reuse. the recent diffusion of integrated enterprise software systems has created an incentive for firms to codify and standardise their knowledge and practices. codification, and the subsequent delegation of organisational 'memory' to software entails radical structural transformations to knowledge and routines as these are reconfigured in the form of new, computer-embedded representations, which are reproduced across the organisation. we argue that, while intended to improve the integration of data and efforts as well as reducing the heterogeneity of actions and viewpoints across the organisation, the software-induced standardisation highlights existing organisational idiosyncrasies as well as creating new sources of conflict. this holds important implications for the dependability of the wider software-organisation system. our evidence, based on participant observation, is presented in the form of a case study focusing on the implementation of product data manager (pdm) software at a leading automotive organisation.
bridging aop to smp: turning gcc into a metalanguage preprocessor. this article presents an strategy to combine important software engineering techniques, static metaprogramming (smp) and generic programming (gp) with aspect oriented programming (aop). these rely on specific language tools that, today, cannot be deployed in conjunction, thus imposing limitations on the software development process. our strategy consists in adapting the c++ compiler to act as a smp preprocessor. this preprocessor is able to parse the input program, execute eventual metaprograms, and output the resulting single-level program for further processing by an aspect weaver.
seamless integration of rule-based knowledge and object-oriented functionality with linguistic symbiosis. software applications often contain implicit knowledge in addition to functionality which is inherently object-oriented. many approaches and systems exist that focus on separating rule-based knowledge from object-oriented functionality and representing it explicitly in a logic reasoning system. support for seamless integration of this knowledge with the object-oriented functionality improves software development and evolution. our hypothesis is that a linguistic symbiosis is required between the logic reasoning and object-oriented programming paradigms in order to achieve seamless integration.this paper presents a symbiotic extension of soul, a system which implements a logic programming language and a production system in smalltalk. the presence of these two logic reasoning systems in soul ensures a comprehensive coverage of rule-based reasoning styles, more specifically forward and backward chaining. our approach is evaluated by means of two case studies. we summarise a comprehensive survey, which shows that existing systems do not fully support seamless integration.
optimal placement of nak-suppressing agents for reliable multicast: a partial deployment case. in reliable multicast, receivers use negative acknowledgments (naks) to inform the sender about their packet loss. the growth in the number of nak messages received by the sender results in the well-known feedback (or nak) implosion problem. therefore, one important issue for reliable multicast protocols is to utilize an effective mechanism to collect nak messages from the receivers. one way to avoid feedback implosion at the sender site is to place nak-suppression agents on the internal nodes (routers) of the network. these agents will forward a single copy of the incoming nak messages toward the sender site and will suppress additional redundant copies coming from the receivers.in this paper, we consider an agent placement (activation) problem for reliable multicast. first, we assume a network environment where a number of internal nodes (routers) have nak-suppression capabilities. then, we try to select a subset of these nodes for nak suppression task for a given reliable multicast application. our main selection criteria is to choose a minimum number of such nodes for the task and have a notion of load-balancing among them. in this context, we study two agent activation problems: the load-balanced agent activation problem (lbaap) and the budgeted agent activation problem (baap) and present efficient algorithms for optimal activation of agents. the problems that we consider in this paper are generalized versions of the respective problems introduced by daescu et al. [3].
design and evaluation of catpa: curation and alignment tool for protein analysis. we present a new application for experimental biologists, the curation alignment tool for protein analysis (catpa), that allows for the efficient and effective creation, storage, management, querying, and visualizing of experimentally curated protein families. protein families in general include paralogs having diverged from a duplication and orthologs. there is more than two decades worth of biological information and more data emerging, but there has not yet been an effective means of dealing with this data. it is our contention that an information system could be created whose appearance was suitable to the visual nature-particularly through alignments-of the information while the underpinnings were formal and followed standard software engineering principles. thus, biologists can interact with the system easily because the data is in the form that they are accustomed to, but they can be assured that there is a sound data model underneath. it is our hope that this will allow biologists to spend more time on the biological science and less time on the information science. in order to help evaluate the utility of this system, we have performed a formal quantitative and qualitative usability study. usability evaluation of catpa was performed to compare the performance of catpa with a similar tool, and users were found to to significantly more efficient using catpa for a number of different types of tasks.
circle: design and implementation of a classifier based on circuit minimization. we present circle, a classification algorithm based on the priciples of boolean function minimization. this classification process uses a recursive method to generate a set of implicants (or rules). the novelty of this algorithm is in the fact that the rules generated contain information about not only presence of features, but also their absence in determining class values. although function minimization is inherently exponential on the number of attributes, we introduce several optimization techniques to reduce the complexity.
on the verification of open distributed systems. a logic and proof system is introduced for specifying and proving properties of open distributed systems. key problems that are addressed include the verification of process networks with a changing interconnection structure, and where new processes can be continuously spawned. to demonstrate the results in a realistic setting we consider a core fragment of the erlang programming language. roughly this amounts to a first-order actor language with data types, buffered asynchronous communication, and dynamic process spawning. our aim is to verify quite general properties of programs in this fragment. the specification logic extends the first-order $\mu$-calculus with erlang-specific primitives. for verification we use an approach which combines local model checking with facilities for compositional verification. we give a specification and verification example based on a billing agent which controls and charges for user access to a given resource.
architectural issues for a location-aware role-based access control system. an increasingly important category of location-based services (lbs) responding to the demands of mobility in organizations is represented by enterprise lbs (e-lbs). e-lbs pose challenging requirements, including the need of selective access to the services based on the position of mobile users and spatially-bounded organizational functions. to address these requirements a general architectural framework for an access control system based on location-aware roles is introduced.
re-classification and multi-threading: . in this paper we consider re-classification in the presence of multi-threading. to this aim we define a multi-threaded extension of the language fickle, that we call ficklemt. we define an operational semantics and a type and effect system for the language. each method signature carries the information on the possible effects of the method execution. the type and effect system statically checks this information. the operational semantics uses this information in order to delay the execution of some threads when this could cause messagenotunderstood errors. we prove that in the execution of a well-typed expression such delays do not produce deadlock.
a method for assessing the reusability of object-oriented code using a validated set of automated measurements. a method for judging the reusability of c++ code components and for assessing indirect quality attributes from the direct attributes measured by an automated tool was demonstrated. the method consisted of two phases. the first phase identified and analytically validated a set of measurements for assessing direct quality attributes based on measurement theory. an automated tool was used to compute actual measures for a repository of c++ classes. a taxonomy relating reuse, indirect quality attributes, and measurements identified and validated during the first part of this research was defined. the second phase consisted of identifying and validating a set of measurements for assessing indirect quality attributes. a case study of the feasibility of applying direct measurements to assess the indirect quality attributes was conducted. the comparison and analysis of indirect quality attributes measured by human analysis with direct quality attributes measured by the automated tool provided empirical evidence that the two sets of quality attributes, direct and indirect, do correlate.
on the computational limits of infinite satisfaction. we study the computational limits of constraint satisfaction problems (csp's) allowing infinitely, or unboundedly, many indexed variables as in, e.g., xi > xi+2 for each i = 1, 2,.... we refer to these csp's as infinite csp's (icsp's). these problems arise in contexts in which the number of variables is unknown a priori as well as in optimization problems wrt the number of variables satisfying a given finite set of constraints.in particular, we investigate the decidability of the satisfiability problem for icsp's wrt (a) the first-order theory specifying the indices of variables and (b) the dimension of the indices. we first show that (1) if the indices are one-dimensional and specified in the theory of the natural numbers with linear order (the theory of (n, 0, succ, <)) then the satisfiability problem is decidable. we then prove that, in contrast to (1), (2) if we move to the two-dimensional case then the satisfiability problem is undecidable for indices specified in (n, 0, succ, <) and even in (n, 0, succ). finally, we show that, in contrast to (1) and (2), already in the one-dimensional case (3) if we also allow addition, we get undecidability. i.e., if the one-dimensional indices are specified in presburger arithmetic (i.e., the theory of (n, 0, succ, <, +)) then satisfiability is undecidable.
quantum versions of k-csp algorithms: a first step towards quantum algorithms for interval-related constraint satisfaction problems. in data processing, we input the results xi of measuring easy-to-measure quantities xi and use these results to find estimates y = f (x1, . . ., xn) for difficult-to-measure quantities y which are related to xi by a known relation y = f(x1, . . ., xn). due to measurement inaccuracy, the measured values xi are, in general, different from the (unknown) actual values xi of the measured quantities, hence the result y of data processing is different from the actual value of the quantity y.in many practical situations, we only know the bounds &delta;i on the measurement errors &delta;xi [equation] xi - xi. in such situations, we only know that the actual value xi belongs to the interval [xi - &delta;i, xi + &delta;i], and we want to know the range of possible values of y. the corresponding problems of interval computations are np-hard, so solving these problems may take an unrealistically long time. one way to speed up computations is to use quantum computing, and quantum versions of interval computations algorithms have indeed been developed.in many practical situations, we also know some constraints on the possible values of the directly measured quantities x1, . . ., xn. in such situations, we must combine interval techniques with constraint satisfaction techniques. it is therefore desirable to extend quantum interval algorithms to such combinations. as a first step towards this combination, in this paper, we consider quantum algorithms for discrete constraint satisfaction problems.
reliability analysis of mobile agent-based systems. in this paper we propose an algorithm for estimating the reliability of mobile agent systems, based on the conditions of the underlying computer network. we use the concept of restricted random walks in graph theory for generating a random static route strategy for mobile agents. the complexity of the mobile agent networks makes it hard to obtain the reliability of the system theoretically; instead we estimate it using the monte carlo approach. we assume that the system consists of a number of independent agents operating simultaneously. the results we have achieved demonstrate the robustness of the proposed algorithm.
an approach to integrating semi-formal and formal notations in software specification. in this paper the integration of graphical, semi-formal modeling languages with formal notations for software specification purposes is discussed and a proposal for a procedural frame based on the combined use of uml and z++ is presented. this procedural frame, organized in stages and steps, provides the methodological basis for a pragmatic and rigorous object-oriented modeling approach aimed at the construction of larger software systems, including real-time systems. within the proposed frame a regular flow of modeling activities is suggested and alternative modeling scenarios are considered. a brief presentation of the harmony integrated specification environment, a tool designed to support the proposed approach, is also included in the paper.
effects of changing requirements: a tracking mechanism for the analysis workflow. managing the effects of changing requirements remains one of the greatest challenges of enterprise software development. the iterative and incremental model provides an expedient framework for addressing such concerns. this paper presents a set of metrics - mutation index, component set, dependency index - and a methodology to measure the effects of requirement changes in the analysis workflow from one iteration to another. results from a sample case study are included to highlight a usage scenario. future directions of our work based on this mechanism are also discussed.
a simple and energy-efficient routing protocol for radio networks. a radio network (rn) is a distributed system where each node is a small hand-held commodity device called a station, running on batteries. each station spends energy while transmitting or receiving a message i.e., when the station is awake. a station conserves power by going into a sleep mode. since it is not possible to recharge batteries when the stations are on a mission, it is extremely important that the stations spend energy only when it is necessary. in this paper, we design an energy-efficient protocol for permutation routing on a single-hop radio network, where each station is within the transmission range of all other stations. an instance of the permutation routing problem involves p stations of an rn, each storing n/p packets. each packet has a unique destination address which is the identity of the destination station to which the packet should be sent. our goal is to route all the packets to their destinations while spending as little energy as possible. from simulation results, it is clear that our protocol performs better than an existing protocol by nakano et al. [12], when each station routes packets with random destination addresses. we also assume that k &laquo; p &laquo; n, where, n, p and k are respectively the number of packets, number of stations and number of channels in the network.
comparing approaches to predict transmembrane domains in protein sequences. there are today several systems for predicting transmembrane domains in membrane protein sequences. as they are based on different classifiers as well as different pre- and post-processing techniques, it is very difficult to evaluate the performance of the particular classifier used. we have developed a system called memmic for predicting transmembrane domains in protein sequences with the possibility to choose between different approaches to pre- and post-processing as well as different classifiers. therefore it is possible to compare the performance of each classifier in a certain environment as well as the different approaches to pre- and post-processing. we have demonstrated the usefulness of memmic in a set of experiments, which shows, e.g., that the performance of a classifier is very dependent on which pre- and post-processing techniques are used.
a multi-agent system architecture for coordination of just-in-time production and distribution. a multi-agent system architecture for coordination of just-in-time production and distribution is presented. the problem to solve is twofold: first the right amount of resources at the right time should be produced, then these resources should be distributed to the right consumers. in order to solve the first problem, which is hard when the production and&#x002f;or distribution time is relatively long, each consumer is equipped with an agent that makes predictions of future needs that it sends to a production agent. the second part of the problem is approached by forming clusters of consumers within which it is possible to redistribute resources fast and at a low cost in order to cope with discrepancies between predicted and actual consumption. redistribution agents are introduced (one for each cluster) to manage the redistribution of resources. the suggested architecture is evaluated in a case study concerning management of district heating systems. results from a simulation study show that the suggested approach makes it possible to control the trade-off between quality of service and degree of surplus production. we also compare the suggested approach to a reference control scheme (approximately corresponding to the current approach to district heating management), and conclude that it is possible to reduce the amount of resources produced while maintaining the quality of service. finally, we describe a simulation experiment where the relation between the size of the clusters and the quality of service was studied.
armed e-bunny: a selective dynamic compiler for embedded java virtual machine targeting arm processors. this paper presents a new selective dynamic compilation technique targeting arm 16/32-bit embedded system processors. this compiler is built inside the j2me/cldc (java 2 micro edition for connected limited device configuration) platform [8]. the primary objective of our work is to come up with an efficient, lightweight and low-footprint accelerated java virtual machine ready to be executed on embedded machines. this is achieved by implementing a selective arm dynamic compiler called armed e-bunny into sun's kilobyte virtual machine (kvm) [9]. in this paper, we present the motivations, the requirements, the architecture, the design, the implementation and debugging issues of armed e-bunny. the modified kvm is ported on an embedded-linux pda and is tested using standard j2me benchmarks. the experimental results on its performance demonstrate that a speedup of 360% over the last version of sun's kvm is accomplished with a footprint overhead that does not exceed 119kb.
automatic extraction of informative blocks from webpages. search engines crawl and index webpages depending upon their informative content. however, webpages --- especially dynamically generated ones --- contain items that cannot be classified as the "primary content", e.g., navigation side-bars, advertisements, copyright notices, etc. most end-users search for the primary content, and largely do not seek the non-informative content. a tool that assists an end-user or application to search and process information from webpages automatically, must separate the "primary content blocks" from the other blocks. in this paper, two new algorithms, contentextractor, and featureextractor are proposed. the algorithms identify primary content blocks by i) looking for blocks that do not occur a large number of times across webpages and ii) looking for blocks with desired features respectively. they identify the primary content blocks with high precision and recall, reduce the storage requirement for search engines, result in smaller indexes and thereby faster search times, and better user satisfaction. while operating on several thousand webpages obtained from 11 news websites, our algorithms significantly outperform the entropy-based algorithm proposed by lin and ho [7] in both accuracy and run-time.
supervised term weighting for automated text categorization. the construction of a text classifier usually involves (i) a phase of term selection, in which the most relevant terms for the classification task are identified, (ii) a phase of term weighting, in which document weights for the selected terms are computed, and (iii) a phase of classifier learning, in which a classifier is generated from the weighted representations of the training documents. this process involves an activity of supervised learning, in which information on the membership of training documents in categories is used. traditionally, supervised learning enters only phases (i) and (iii). in this paper we propose instead that learning from training data should also affect phase (ii), i.e. that information on the membership of training documents to categories be used to determine term weights. we call this idea supervised term weighting (stw). as an example, we propose a number of "supervised variants" of t f idf weighting, obtained by replacing the idf function with the function that has been used in phase (i) for term selection. we present experimental results obtained on the standard reuters-21578 benchmark with one classifier learning method (support vector machines), three term selection functions (information gain, chi-square, and gain ratio), and both local and global term selection and weighting.
reflective middleware for wireless sensor networks. wireless sensor networks (wsns) are distributed systems whose main goal is to collect and deliver data to applications. this paper proposes a reflective, service-oriented middleware for wsn. the middleware provides an abstraction layer between applications and the underlying network infrastructure and it also keeps the balance between application qos requirements and the network lifetime. it monitors both network and application execution states, performing a network adaptation whenever it is needed. simulation results show that the network residual energy can be increased in more than 100% when adopting an adaptation strategy, while the application qos requirement is respected.
a portable virtual machine for program debugging and directing. directors are reactive systems that monitor the run-time environment and react to the emitted events. typical examples of directors are debuggers and tools for program analysis and software visualization. in this paper we describe a cross-platform virtual machine that provides advanced facilities for implementing directors with low effort.
branchless cycle prediction for embedded processors. modern embedded processors access the branch target buffer (btb) every cycle to speculate branch target addresses. such accesses, quite often, are unnecessary as there is no branch instruction among those fetched.in this work we introduce branchless cycle prediction (blcp) to exploit this design inefficiency. blcp uses a simple power efficient structure to predict cycles where there is no branch instruction among those fetched, at least one cycle in advance. we avoid accessing btb during such cycles.we show that, by using blcp, it is possible to reduce btb power dissipation by 32% while paying a negligible performance cost (average: 0.2%).
patterns for blended, person-centered learning: strategy, concepts, experiences, and evaluation. within the last few years, e-learning has become a focal point in several universities and organizations. while much research has been devoted to producing e-content, describing it with metadata, and to constructing e-learning platforms, less attention has been paid to using technology to improve the learning process in terms of depth and scope. our research is targeted at filling this gap by considering learning support from a technical as well as socio-psychological perspective. we investigate how these two worlds can be brought together to result in maximum cross-fertilization. in this paper we focus on conceptual modeling of successful blended learning processes, their semi-formal description as patterns, and on the use of patterns as sources for the derivation of web-based templates. we report on experiences and evaluations of employing patterns in the context of blended, person-centered learning in technical subjects. our major conclusion is that blended learning has added value only if designed thoughtfully and accompanied by high interpersonal skills of instructors.
a probability analysis for candidate-based frequent itemset algorithms. this paper explores the generation of candidates, which is an important step in frequent itemset mining algorithms, from a theoretical point of view. important notions in our probabilistic analysis are success (a candidate that is frequent), and failure (a candidate that is infrequent). for a selection of candidate-based frequent itemset mining algorithms, the probabilities of these events are studied for the shopping model where all the shoppers are independent and each combination of items has its own probability, so any correlation between items is possible. the apriori algorithm is considered in detail; for ais, eclat, fp-growth and the fast completion apriori algorithm, the main principles are sketched. the results of the analysis are used to compare the behaviour of the algorithms for a variety of data distributions.
cl_matcont: a continuation toolbox in matlab. cl_matcont is a matlab continuation package for the numerical study of a range of parameterized nonlinear problems. in the case of odes it allows to compute curves of equilibria, limit point, hopf points, limit cycles and period doubling bifurcation points of limit cycles. all curves are computed by the same function that implements a prediction-correction continuation algorithm based on the moore - penrose matrix pseudo-inverse. the continuation of bifurcation points of equilibria and limit cycles is based on bordering methods and minimally extended systems. hence no additional unknowns such as singular vectors and eigenvectors are used and no artificial sparsity in the systems is created.the inherent sparsity of the discretized systems for the computation of limit cycles and their bifurcation points is exploited by using the standard matlab sparse matrix methods.cl_matcont furthermore allows to compute solution branches to underdetermined systems of nonlinear equations and parameterized boundary value problems.
automatic verification of the tls handshake protocol. e-commerce is based on transactions between client and server agents. these transactions require a protocol that provides privacy and reliability between these two agents. a widely used protocol on e-commerce is transport layer security (tls). in this paper we present a way to use formal methods to ensure the e-commerce properties of this protocol. specifically we use a known tool for model checking (uppaal) to describe and analyze the behaviour of the protocol (by means of timed automata). thus, with this tool we can make an automatic verification of tls.
an approach to handle real time and probabilistic behaviors in e-commerce: validating the set protocol. in this work we describe an approach to deal with systems having at the same time probabilistic and real-time behaviors. the main goal in the paper is to show the automatic translation from a real time model based on uppaal tool, which makes automatic verification of real time systems, to the rapture tool, which makes verification of probabilistic systems.furthermore, this approach allows us to use the best techniques developed in both tools (abstraction, refinement, state space reduction, etc). finally, this translation is applied to verify a case study, the set internet protocol.
inter-organizational document exchange: facing the conversion problem with xml. information exchange processes are often characterized by the need of translating from one data format into another in order to achieve compatibility between information systems. a conversion problem often arises when exchanging files between applications of different software vendors or when incorporating legacy business data into new standard software. in this paper we want to survey the conversion problem in the field of multi-organizational networks, since participants often use different data formats. we examine, to what extent xml is able to support the inter-organizational exchange of business documents. thereby, we concentrate on the problem of converting different data and examine different approaches for solving the transformation problem. we show how xml can actually be implemented for a web-based integration in multi-organizational networks. moreover, we present a java-based prototype that enables document exchange over the internet using xml business vocabularies for document representation, xslt for document conversion and presentation, and both dom and sax for processing and integrating documents into in-house-systems.
blomind-protein property prediction by property proximity profiles. we present the infrastructure of a bioinformation system called biomind, which exploits the close relationship between the structural and functional properties of proteins. the scheme presented here views proteins as composite entities with structural and functional properties, and searches are based on distances along each property axis. explicitly, this allows one to frame complex queries using quantitative criteria that confer more discerning power than systems based on a text-matching approach. implicitly, and more importantly, this has the potential to reveal patterns of convergence in properties of proteins and improve our ability to approximate the unknown properties of a protein, given a set of known properties.
computational analysis of microwave heating patterns in resonant multimode cavities. computational results for the microwave heating patterns in singlefed multimode empty and loaded cavities are presented in this paper. combined finite difference time domain (fdtd) and finite volume (fv) methods are used to solve the equations that describe the electromagnetic field and heat transfer in the processed samples. the coupling between the two schemes is through a change in dielectric properties which are assumed to be temperature dependent. the model takes into account the changing effect of the load's properties on the electric field and modal patterns. a study of the modes and their corresponding field pattern inside a resonant cavity is presented computationally using the fdtd solver. the coupled algorithm is then used to investigate heat distribution by observing the occurrence of resonant conditions which are responsible for achieving high heating levels.
assisted verification of elementary functions using gappa. the implementation of a correctly rounded or interval elementary function needs to be proven carefully in the very last details. the proof requires a tight bound on the overall error of the implementation with respect to the mathematical function. such work is function specific, concerns tens of lines of code for each function, and will usually be broken by the smallest change to the code (e.g. for maintenance or optimization purpose). therefore, it is very tedious and error-prone if done by hand. this article discusses the use of the gappa proof assistant in this context. gappa has two main advantages over previous approaches: its input format is very close to the actual c code to validate, and it automates error evaluation and propagation using interval arithmetic. besides, it can be used to incrementally prove complex mathematical properties pertaining to the c code. yet it does not require any specific knowledge about automatic theorem proving, and thus is accessible to a wider community. moreover, gappa may generate a formal proof of the results that can be checked independently by a lower-level proof assistant like coq, hence providing an even higher confidence in the certification of the numerical code.
decision tree classification of spatial data streams using peano count trees. many organizations have large quantities of spatial data collected in various application areas, including remote sensing, geographical information systems (gis), astronomy, computer cartography, environmental assessment and planning, etc. these data collections are growing rapidly and can therefore be considered as spatial data streams. for data stream classification, time is a major issue. however, these spatial data sets are too large to be classified effectively in a reasonable amount of time using existing methods. in this paper, we developed a new method for decision tree classification on spatial data streams using a data structure called peano count tree (p-tree). the peano count tree is a spatial data organization that provides a lossless compressed representation of a spatial data set and facilitates efficient classification and other data mining techniques. using p-tree structure, fast calculation of measurements, such as information gain, can be achieved. we compare p-tree based decision tree induction classification and a classical decision tree induction method with respect to the speed at which the classifier can be built (and rebuilt when substantial amounts of new data arrive). experimental results show that the p-tree method is significantly faster than existing classification methods, making it the preferred method for mining on spatial data streams.
k-nearest-neighbor consistency in data clustering: incorporating local information into global optimization. nearest neighbor consistency is a central concept in statistical pattern recognition, especially the knn classification methods and its strong theoretical foundation. in this paper, we extend this concept to data clustering, requiring that for any data point in a cluster, its k-nearest neighbors and mutual nearest neighbors should also be in the same cluster. we study properties of the cluster k-nearest neighbor consistency and propose knn and kmn consistency enforcing and improving algorithms. extensive experiments on internet newsgroup datasets using the k-means clustering algorithm with knn consistency enhancement show that knn / kmn consistency can be improved significantly (about 100% for 1mn and 1nn consistencies) while the clustering accuracy is improved simultaneously. this indicates the local consistency information helps the global cluster objective function optimization.
the p-tree algebra. the peano count tree (p-tree) is a quadrant-based lossless tree representation of the original spatial data. the idea of p-tree is to recursively divide the entire spatial data, such as remotely sensed imagery data, into quadrants and record the count of 1-bits for each quadrant, thus forming a quadrant count tree. using p-tree structure, all the count information can be calculated quickly. this facilitates efficient ways for data mining. in this paper, we will focus on the algebra and properties of p-tree structure and its variations. we have implemented fast algorithms for p-tree generation and p-tree operations. our performance analysis shows p-tree has small space and time costs compared to the original data. we have also implemented some data mining algorithms using p-trees, such as association rule mining, decision tree classification and k-clustering.
ubicollab: collaboration support for mobile users. shared workspaces have emerged as one of the most successful applications of computer supported cooperative work (cscw). important aspects of shared workspaces are presence and awareness information, flexible sharing of work material, and support for communication among group members. one of the shortcomings of existing shared workspaces is their lack of support for mobility. in this paper we will discuss the need for mobile shared workspaces as well as an experimental platform for ubiquitous collaboration and a number of shared workspace implementations for both formal and informal collaboration.
solving first-order constraints in the theory of finite or infinite trees: introduction to the decomposable theories. we present in this paper an algorithm in the theory t of possibly infinite trees for solving general constraints represented by full first-order formulas, with equality as the only relation and functional symbols taken from an infinite set f. the algorithm consists of a set of 11 rewriting rules. it transforms a first-order formula p in a conjunction q of solved formulas, equivalent in t, such that: (1) the conjunction q is the formula true if p is always true in t, and the formula &not;true if p is always false in t. moreeover, if p or its negation has a finite base of solutions in a model of t, then these solutions or non-solutions have to be explicit in q. (2) each solved formula of q has not new free variables and can be transformed immediately in a boolean combination of basic formulas whose length does not exceed twice the length of the solved formula. the basic formulas are particular cases of existentially quantified conjunctions of equations. the correctness of the algorithm gives another proof of the completeness of t demonstrated by michael maher. we test our algorithm on benchmarks realized by an implementation, solving formulas on two-partners games in t with more than 160 nested alternated quantifiers.finally, we show then that we can generalize this algorithm by introducing a new class of theories that we call decomposable. we show that t is decomposable and give a general algorithm for solving first-order constraint in any decomposable theory. the correctness of our algorithm shows the completeness of the decomposable theories.
co-evolving an effective fitness sample: experiments in symbolic regression and distributed robot control. we investigate two techniques for co-evolving and sampling from a population of fitness cases, and compare these with a random sampling technique. we design three symbolic regression problems on which to test these techniques, and also measure their relative performance on a modular robot control problem. the methods have varying relative performance, but in all of our experiments, at least one of the co-evolutionary methods outperforms the random sampling method by guiding evolution, with substantially fewer fitness evaluations, toward solutions that generalize best on an out-of-sample test set.
representing the applications and compositions of design patterns in uml. design patterns capture the distilled experience of expert designers. the compositions of design patterns may reuse design experience and solve a set of problems. design patterns and their compositions are usually modeled using uml. when a design pattern is applied or composed with other patterns, the pattern-related information may be lost because uml does not track this information. thus, it is hard for a designer to identify a design pattern when it is applied or composed. the benefits of design patterns are compromised because the designers cannot communicate with each other in terms of the design patterns they use when the design patterns are applied or composed. in this paper, we present notations to explicitly represent each pattern in the applications and compositions of design patterns. the notations allow us to maintain pattern-related information. thus, a design pattern is identifiable and traceable from its application and composition with others.
text classification based on data partitioning and parameter varying ensembles. support vector machines (svm) are among the best text classifiers so far. meantimes, ensembles of classifiers are proven to be effective on many domains. it is expected that ensembles of svm classifiers could achieve better performance. in this paper two types of ensembles on svm classifiers, the data partitioning ensembles and heterogeneous ensembles, have been proposed and experimentally evaluated on three well-accepted collections. major conclusions are that disjunct partitioning ensembles with stacking could achieve the best performance, and that the parameter varying ensembles are proven to be effective, meanwhile have the advantage of being deterministic.
embedded predictive modeling in a parallel relational database. a methodology for embedding predictive modeling algorithms in a commercial parallel database is described; specifically, the parallel editions of ibm db2 universal database, although many aspects of the overall approach can be used with other commercial parallel databases. this parallelization approach was implemented in the version 8.2 release of db2 intelligent miner modeling to support a new predictive modeling algorithm called transform regression. this database-embedded mining algorithm provides all the usual benefits, including easier integration into large enterprise applications, the ability to perform entire data mining workflows directly from an sql-based programming interface, reduced data transfer costs between the database and the data mining application, and faster, parallel data access during query processing. however, in addition to the these benefits, a significant part of the data mining computations are also parallelized without the use of any sophisticated parallel programming constructs, or any specialized message passing and parallel synchronization libraries.
ontology-based integration for relational databases. in this paper, we show that representation and reasoning techniques used in traditional knowledge engineering and the emerging semantic web can play an important role for heterogeneous database integration. our ontograte architecture combines ontology-based schema representation, first order logic inference, and some sql wrappers to integrate two sample relational databases. we define inferential data integration as the theoretical framework for our approach. the performance evaluation for query answering shows that ontograte reformulates conjunctive queries and retrieves over 100,000 answers from a target database in under 30 seconds. in addition to query answering, the system translates 40,000 database facts from source to target in under 30 seconds.
synthesis of c++ software for automated teller from cspm specifications. csp++ is an object-oriented application framework for execution of csp specifications that have been automatically translated into c++ source code by a tool called cspt. this approach makes csp specifications directly executable, and extensible via the ability to incorporate user-coded functions. designers can exploit "selective formalism" to code some system functionality in csp for formal verification purposes, and other functionality directly in c++. the translator has now been enhanced to accept input in cspm syntax, the same dialect processed by the commercial verification tool, fdr2, and we demonstrate this with a new atm case study.
combining speech and pen input for effective interaction in mobile geospatial environments. relatively little research has been conducted into designing interfaces that allow gis users to interact effectively with geospatial data in mobile environments. users on the move are faced with limited interaction modalities. the standard mode of input on mobile devices is the pen or stylus, which some users may find difficult or too time-consuming to use. voice commands, combined with pen input, can provide an attractive alternative for interacting with mobile gis, as speech is a natural form of interaction. however, the idea of combining speech and pen input in mobile gis is relatively unexplored. to this effect, we have developed a multimodal interface to a mobile gis, providing users with the ability to freely switch between modalities to suit current tasks or environments.
enhancing network intrusion detection systems with interval methods. two main approaches for network intrusion detection are misuse detection [6] and anomaly detection [11]. the limitation of the misuse approach is that cannot effectively detect new patterns of intrusions that are not precisely encoded in the system [11]. the anomaly detection approach usually produces a large number of false alarms [1, 7]. in addition, anomaly detection requires intensive computations on a large amount of training data to characterize normal behavior patterns.in this paper, we try to apply interval technology to enhance network intrusion detection systems (ids). by storing network state data into interval valued bi-temporal database, we better sample the stream of network states. we represent the likelihood of intrusions associated with an m x n interval valued rule matrix that can be obtained from the database with relatively low computational complexity. by grouping nearby patterns with intervals, we may significantly reduce false alarms. the o(n) computational cost of maintaining the rules makes it possible to integrate the ids with network management systems for almost real-time automatic network control. our probabilistic approach with the rule matrix model can be further applied to study the pattern evolution of network intrusions.
a treecode algorithm for computing ewald summation of dipolar systems. we present a treecode algorithm for efficiently computing the real space part of ewald summation in periodic dipolar systems. the algorithm uses multipole expansion in cartesian coordinates to approximate the real space interaction between a dipole and a distant cluster of dipoles. the necessary taylor coefficients are computed efficiently using recurrence relations. two divide-and-conquer evaluation procedures are described. test results are presented for systems of randomly generated dipoles.
conformational statistics of the nitrogen linkage in glycopeptides using umbrella sampling. the conformational statistics of the glycosylated dipeptide n - acetyl - &delta; - n - (2 - acetamido - &beta; - d - glucopyranosyl) - l - asparaginyl - n' - methyl amide (glcnac-asn), a model of n-linked glycopeptides, was determined using umbrella sampling. the use of umbrella sampling allowed the importance sampling algorithm to accept new conformations with probabilities exceeding 40%. the satisfactory acceptance rate generated a chain of conformations and a set of properties suitable for comparison with available experimental results. comparison of calculated structures for glcnac-asn with those determined experimentally by nmr, circular dichroism spectroscopy, and x-ray crystallography showed that the momany-scheraga conformation energy (ecepp) over-emphasized non-bonded repulsions. based on the experimentally determined structures, an effective two-fold potential barrier was imposed on the anomeric linkage. predictions based on conformational statistics were sensitive to the choice of a three-fold or two-fold torsional barrier at the anomeric linkage.
a deterministic technique for extracting keyword based grammar rules from programs. this paper presents a technique for extracting grammar rules, given a set of programs and an approximate grammar. grammar is an important artifact used in the generation of tools for program analysis, modification, etc. current grammar extraction techniques are heuristic in nature. this work proposes a deterministic technique for extracting keyword based grammar rules. the technique uses cyk-parser and lr-parser to build a set of possible rules. for each rule it checks whether the grammar after including that rule is able to parse all the programs or not. as this results in a large set of possible rules, a set of optimizations are proposed to reduce the search space of possible rules. the proposed optimizations utilize the knowledge from multiple programs and exploit the abundance of unit productions in the grammar of programming languages. the proposed approach and optimizations are experimentally checked on a set of input programs.
security status display and browser interframe communication. we argue that current www protocols are anticompetitive and favor larger www retailers and service providers. consumer confidence has been recognized as an impediment to the development of smaller www based businesses and the growth of online transactions. consumers are understandably concerned about using their credit card number to make www purchases.our assertion is that the development of standards which would allow payment providers to interface with vendors and consumers to interface with vendors with confidence has been made difficult by current browser standards. we suggest that changes can reasonably be made which would make the task of developing such interface protocols easier while enhancing consumer confidence. changes in the direction we suggest could assist in enhancing competition, consumer security and privacy, as well as confidence. in addition, it would be easier to develop protocols to allow consumer choice of payment providers, shippers, and other services ancillary to an online transaction.
the effects of two replacement strategies on a genetic algorithm for scheduling jobs on computational grids. computational grid (cg) represents a new computational framework whose efficient use requires schedulers that allocate user's tasks to the grid resources in an acceptable amount of time. in this paper, we study the effects of two replacement strategies on a ga for job scheduling on computational grids, namely steady-state ga (ssga) and struggle ga (sga). considering the makespan, the experimental results show the improvement obtained by sga over ssga for moderate size instances. however, the time needed by the sga to reach makespan values obtained by the ssga rapidly increases as more jobs and machines are added to the cg.
convrel: relationship conversion to xml nested structures. this paper addresses the problem of efficiently transforming relational schemas into nested-based xml schemas. the proposed conversion algorithm considers preserving the structural constraints, cardinality and participation ratios, by analyzing each relation in relationship to others. several candidate xml structures are proposed for each type of relationship according to its structural constraints from which the optimum one is chosen in terms of compact nested xml structure and determining the smallest xml data file
a "go with the winners" approach to finding frequent patterns. in their seminal work on go with the winners (gww) algorithms, d. aldous and u. vazirani [3] proved a sufficient condition for the number of particles needed for reaching the bottom of a tree with high probability via a gww random walk. however, to use this result in practice would require knowledge of the entire search tree which is infeasible for most problems. in this paper we improve slightly on this situation by deriving a recurrence relation that provides an upper-bound for a tree's imbalance in terms of the imbalance between tree levels that are close to one another, provided that these latter imbalances can be measured with sufficient accuracy.we then turn our attention to the problem of finding both frequent and infrequent patterns in a database. one of the most widely used algorithms for finding frequent patterns in memory-resident databases is a randomized algorithm first proposed by gunopulos et al. [12]. we show that such an algorithm is precisely one for which the gww paradigm was designed to improve on. experimental results using the splice-junction gene sequences database [4] are also provided and lend empirical evidence of the benefits of using gww.
genetic programming for data classification: partitioning the search space. when genetic programming is used to evolve decision trees for data classification, search spaces tend to become extremely large. we present several methods using techniques from the field of machine learning to refine and thereby reduce the search space sizes for decision tree evolvers. we will show that these refinement methods improve the classification performance of our algorithms.
authentication and access delegation with user-released certificates. we propose an authentication and access delegation system based on an unconventional use of x.509 certificates. it allows users to connect from any untrusted machine and to define dynamically a group of trusted co-workers. it is low cost, doesn't need unusual software nor hardware on the client's side, and offers a good degree of security without requiring that the user be too careful. the underlying idea is to enable users to release their own certificates with very short life span (or usable just once) to authenticate themselves to the server.
anonymity and certification: e-mail, a case study. awareness of legal constraints regarding the use and provision of electronic systems, leads us to question the feasibility and applicability of technical solutions that take into account security and privacy regulations. we discuss the issue with reference to directives of the european community and italian legislation. in particular we study the case of e-mail, proposing a protocol that retains as many characteristics of the e-mail as possible, yet allowing for complete anonymity and proofs of correct deploy. we discuss the implications of taking anonymity to the extremes and evaluate the limits of the protocol.
a flexible approach to user-defined symbolic granularities in temporal databases. user-defined granularities, calendars and periodicities are gaining an increasing relevance in the area of temporal databases (tdb). in this paper, we discuss the advantages of adopting for tdbs a modular framework, based on a family of symbolic languages, defined starting from a set of mutually orthogonal properties that characterize periodicity. first, we show that one of the languages covers the notion of granularity (as defined in the tdb glossary), so that it can be used in order to define validity times of facts in a tdb. second, we discuss the usefulness of using more expressive languages in the family to achieve such a goal. third, we explore how such languages can be used in order to deal in an intensional way with infinite periodic data in temporal (relational) databases.
ontology-focused crawling of web documents. the web, the largest unstructured database of the world, has greatly improved access to documents. however, documents on the web are largely disorganized. due to the distributed nature of the world wide web it is difficult to use it as a tool for information and knowledge management. therefore, users doing the difficult task of exploring the web have to be supported by intelligent means.this paper proposes an approach for document discovery building on a comprehensive framework for ontology-focused crawling of web documents. our framework includes means for using a complex ontology and associated instance elements. it defines several relevance computation strategies and provides an empirical evaluation which has shown promising results.
behavioral pattern analysis: towards a new representation of systems requirements based on actions and events. requirements are descriptions of the application domain, of the problems to be solved there, and of the system(s) to be built in that domain to solve these problems. many projects have failed because their requirements were inadequately analyzed or described. use cases have offered analysts and developers an approach for capturing the end-user requirements in an object-oriented fashion. however, experience is showing some problems with use cases such as lack of a precise definition that led most companies to re-invent their own version, lack of notion of atomicity, and lack of addressing all interaction types. this research is concerned with developing a more effective alternative to use case analysis (uca) for modeling the functional requirements of human-machine safety-critical real-time systems. the new alternative modeling approach, behavioral pattern analysis (bpa), is an event-oriented approach in which events are considered the primary entities of the world domain requirements model. while the term 'event' is used in uml, and in almost all of the other modeling approaches, to mean an occurrence of stimulus that can trigger a state transition, the event described in bpa is a real-life conceptual entity that is unrelated to any implementation. it describes what, who, how, when, where, and why for an interaction or set of interactions between entities. the appeal to events is natural in the definition of requirements because events provide more complete and clearer understanding of the defined requirements. such completeness and clarity are keys to the effectiveness of requirements modeling. it is the researcher's belief that the system model should be event driven rather than use case driven. three real-life applications were used to validate the effectiveness of the new bpa approach in modeling the functional requirements of safety-critical real-time systems. both, the uca and the bpa approaches were used to model the functional requirements of these applications. to validate the bpa approach improved effectiveness, the first application was used in a pilot case study by the researcher to provide a proof of concept, and the other two applications were used in another sixteen case studies that were arranged for the evaluation purpose. in all of these case studies, the resulting models from both approaches were compared using safety, cmm repeatability, and the ansi/ieee std 830-1984 effectiveness standards as the basis of the comparison. the case studies result indicated that at least eighty seven percent (87%) of the participating subject matter experts (smes) believe that bpa is more effective than uca in the definition of requirements of safety-critical and real-time systems. (abstract shortened by umi.)
application of fuzzy logic to multiple criteria decision making in aquacultural planning. the field of regional planning is characterized by the large number of issues and attributes involved, and regional planning for aquaculture development is no exception. moreover, aquacultural plans do not have clearly defined objectives and require information that, if exist, is often imprecise and uncertain.this paper applies fuzzy set theory to multiple criteria decision making (mcdm) in aquaculture planning. in effect, the paper demonstrates how fuzzy set theory can be used to explicitly account for the inherent uncertainty encountered when planning for aquaculture development in a given region. a case study for regional aquaculture planning in northern egypt demonstrates the proposed fuzzy mcdm framework.
dynamic consistency checking for temporal and spatial relations in multimedia presentations. creating complex multimedia presentations involves the specification of temporal and spatial relations in the form of constraints. however, some of these constraints could contradict each other and hence lead to an inconsistency. the user may not be aware of this inconsistency while authoring. hence this inconsistency has to be identified and removed by the presentation process prior to the play-out. in this paper, we examined an existing work based on graph theory for consistency checking. we propose a modification to this approach which simplifies the algorithm, reduces its total running time, and helps to make it dynamic. another salient feature of our paper is the introduction of new temporal and spatial operators with higher expressive power than traditional ones. thus, this paper presents a multimedia presentation mechanism, which dynamically maintains a consistent and complete set of constraints during authoring and play-out of the presentation.
a hybrid approach for multiresolution modeling of large-scale scientific data. simulations of complex scientific phenomena involve the execution of massively parallel computer programs. these simulation programs generate large-scale multidimensional data sets over the spatio-temporal region. analyzing such massive data sets is an essential step in helping scientists glean new information. to this end, efficient and effective data models are needed. in this paper, we present a hybrid approach for constructing data models from large-scale multidimensional scientific data sets. our models not only provide descriptive information about the data but also allow users to subsequently examine the data by querying the data models. our approach combines a multiresolution-topological model of the data with a multivariate-physical model of the data to generate one hierarchical data model that efficiently captures both the spatio-temporal and the physical aspects of the data. in particular, this hybrid approach consists of three phases. in the first phase, we build a multiresolution model that encapsulates the data set's spatial information (i.e., topology and spatial connectivity). in the second phase, we build a multivariate model from the physical dimensions of the data set. physical dimensions refer to those dimensions that are neither spatial (x, y, z) nor temporal (time). the exclusion of the spatial-temporal dimensions from the clustering phase is important since "similar" characteristics could be located (spatially) far from each other. finally, in the third phase, we connect the multivariate-physical model to the multiresolution-topological model by utilizing ideas from information retrieval. the third phase is essential since the multivariate-physical model does not contain any topological information (without which the model does not have accurate spatial context information). experimental evaluations on two large-scale multidimensional scientific data sets illustrate the value of our hybrid approach.
evaluating collaborative software in supporting organizational learning with bayesian networks. many collaborative software tools have been developed in the recent years to accelerate the growing interest of many organizations to become learning organizations. selecting a collaborative tool that best suits an organization's needs is a challenging task, given that there are no evaluation criteria against which these tools could be evaluated with respect to various organizational learning concepts. the objective of this paper is twofold. first, it derives a generic set of criteria required to evaluate the suitability of a given collaborative tool in supporting the mental model concept of organizational learning. second, it investigates the possibility of using bayesian networks as an evaluation methodology to rate the suitability of a given collaborative tool with respect to how well it meets the derived evaluation criteria.
infofilter: a system for expressive pattern specification and detection over text streams. information filtering includes monitoring text streams to detect patterns that are more complex than those handled by search engines. text stream monitoring and pattern detection have far reaching applications such as tracking information flow among terrorist outfits, web parental control, and business intelligence. pattern characterization requirements of applications entail an expressive language for specifying patterns than what is currently provided by information retrieval query languages (irqls) and current information filtering systems. pattern specification alone does not suffice, as detecting these complex patterns is equally important in order to use these systems for real-world applications.infofilter, a content-based information filtering system, presented in this paper, allows users to specify complex patterns and detects these patterns in incoming text streams from various sources such as news feed, emails, web pages and caption text from streaming videos. complex patterns such as combinations of sequential, structural patterns, wild cards, word frequencies, proximity, boolean operators and synonyms are formulated using the expressive pattern specification language, psl, proposed in this paper. once specified, these complex patterns are detected using a data flow paradigm over pattern detection graphs (pdgs).
compiling regular patterns to sequential machines. pattern matching combined with regular expressions has many applications including semistructured data matching and lexical analysis in compilers. variables in patterns allow one to refer to parts of the matching input. but some regular patterns suffer from inherent ambiguity, yielding more than one valid result. a match policy like shortest or longest match can disambiguate such patterns.in this paper, we show that regular pattern matching corresponds to sequential transduction. we derive straightforward ways to optimally compile regular patterns to sequential machines and to decide when regular patterns are unambiguous. unambiguous patterns can be matched in a single traversal of the input. ambiguities in patterns correspond to nondeterminism in sequential machines. applying the match policy optimally yields two deterministic sequential machines, which produce the shortest match in two consecutive runs.
code generation techniques for developing light-weight xml web services for embedded devices. this paper presents specialized code generation techniques and runtime optimizations for developing light-weight xml web services for embedded devices. the optimizations are implemented in the gsoap web services development environment for c and c++. the system supports the industry-standard xml-based web services protocols that are intended to deliver universal access to any networked application that supports xml. with the standardization of the web services protocols and the availability of toolkits such as gsoap for developing embedded web services, new opportunities emerge to integrate embedded systems into larger frameworks of interconnected applications and systems accessing dynamic resources on the web ranging from hand-held and embedded devices to databases, clusters, and grids.
editorial message: special track on distributed systems and grid computing. it is a great pleasure to welcome you to the 21st annual acm symposium on applied computing, special track on distributed systems and grid computing (dsgc) in dijon, france. the objective of the dsgc track is to provide a forum for scientists, engineers and practitioners in academia, industry and research institutes to share technical ideas, experiences and results and to present their latest findings in any aspects of parallel, distributed, and grid computing. the topics of the track emphasize the design, architecture, and software of distributed systems and grid computing environments with their scientific and engineering applications.
validation of code-improving transformations for embedded systems. programmers of embeded systems often develop software in assembly code due to inadequate support from compilers and the need to meet critical speed and/or space constraints. many embeded applications are being used as a component of an increasing number of critical systems. while achieving high performance for these systems is important, ensuring that these systems execute correctly is vital. one portion of this process is to ensure that code-improving transformations applied to a program will not change the program's semantic behavior, which may be jeopardized when transformations are specified manually. this paper describes a general approach for validation of many low-level code-improving transformations made either by a compiler or specified by hand. initially, we associate a region of the program representation with a code-improving transformation. afterwards, we calculate the region's effects on the rest of the program before and after the transformation. the transformation is considered valid when the effects before and after the transformation are identical. we implemented an automatic validation system in the vpo compiler. the system is currently able to validate all code-improving transformations in vpo except transformations that affect blocks across loop levels.
wsbus: a framework for reliable web services interactions. as web services start to be deployed across enterprise boundaries and for collaborative e-business scenarios, reliable inter-application messaging and failure management becomes a critical issue to insure guaranteed and ordered delivery even in the case of system or network failures or temporary unavailability of services. this paper presents wsbus, a lightweight integration framework for dependable web services interactions. we discuss the system features and architecture as well as initial performance results.
quad and correctly rounded double precision math functions: portable and optimized for intel architectures. a fundamental part of a system's quad floating-point precision support is its companion mathematical library. we developed a hierarchical c macro based methodology for implementing the quad precision elementary functions both portable and optimized for intel&reg; architectures. when two or three floating-point values natively supported in the hardware are packed together, we are able to leverage the extra precision provided to attain high accuracy and yield measurable performance gains over traditional integer-based implementations. our high-level language codes are unified for several platforms, while native floating-point arithmetic sequences are the computational elements that underlie the macros and exploit the features of particular architecture. this significantly reduces the library maintenance cost and allows providing high performance quad functions for the new processors. we also show how language extensions in the intel&reg; c/c++ compiler allow additional performance improvements on intel&reg; architectures. finally, our experiments based on recent advances of de dinechin, defour and lauter demonstrate that using methodology developed for quad precision functions we can attain correctly rounded double precision routines with significant performance improvements compared with algorithms based on generic multi-precision packages for a low implementation cost.
scalable, efficient epidemiological simulation. we describe the design and implementation of a system for simulating the spread of disease among individuals in a large urban population over the course of several weeks. in contrast to traditional approaches, we do not assume uniform mixing among large sub-populations or split the population into spatial or demographic subpopulations determined a priori. instead, we rely on empirical estimates of the social network, or contact patterns, that are produced by transims, a large-scale simulation of transportation systems.
kala: kernel aspect language for advanced transactions. transaction management is a known cross-cutting concern. previous research has been conducted to express this concern as an aspect. however, this work uses general-purpose aspect languages which lack a formal foundation and are unable to express advanced models for transaction management. in contrast, we designed a domain-specific aspect language for advanced transaction management, called kala, that is based on a formalism for advanced transactions. as a result, kala covers the field of advanced transaction management while obtaining a much higher level of abstraction than is achieved with general-purpose aspect languages. in this paper we detail the creation process of kala.
graphical rule-based representation of signal-transduction networks. the process by which a cell senses and responds to its environment, as in signal transduction, is often mediated by a network of protein-protein interactions, in which proteins combine to form complexes and undergo post-translational modifications, which regulate their enzymatic and binding activities. a typical signaling protein contains multiple sites of protein interaction and modification and may contain catalytic domains. as a result, interactions of signaling proteins have the potential to generate a combinatorially large number of complexes and modified states, and representing signal-transduction networks can be challenging. representation, in the form of a diagram or model, usually involves a tradeoff between comprehensibility and precision: comprehensible representations tend to be ambiguous or incomplete, whereas precise representations, such as a long list of chemical species and reactions in a network, tend to be incomprehensible. here, we develop conventions for representing signal-transduction networks that are both comprehensible and precise. labeled nodes represent components of proteins and their states, and edges represent bonds between components. binding and enzymatic reactions are described by reaction rules, in which left graphs define the properties of reactants and right graphs define the products that result from transformations of reactants. the reaction rules can be evaluated to derive a mathematical model.
modeling multiple class loaders by a calculus for dynamic linking. in a recent paper we proposed a calculus for modeling dynamic linking independently of the details of a particular programming environment.here we use a particular instantiation of this calculus to encode a toy language, called mcl, which provides an abstract view of the mechanism of dynamic class loading with multiple loaders as in java.the aim is twofold. on one hand, we show an example of application of the calculus in modeling existing loading and linking policies, showing in particular that java-like loading with multiple loaders can be encoded without exploiting the full expressive power of the calculus. on the other hand, we provide a simple formal model which allows a better understanding of java-like loading mechanisms and also shows an intermediate solution between the rigid approach based only on the class path and that which allows arbitrary userdefined loaders, which can be intricate and error-prone.
a new variable-length genome genetic algorithm for data clustering in semeiotics. this paper focuses on the introduction of a new evolutionary algorithm for data clustering, the self-sizing genome genetic algorithm. it is akin to a messy genetic algorithm and does not use a priori information about the number of clusters. a new recombination operator, gene-pooling, is introduced, while fitness is based on simultaneously maximizing intra-cluster homogeneity and inter-cluster separability. this algorithm is applied to clustering in dermatological semeiotics. moreover, a pathology addressing index is defined to quantify utility of found clusters in unambiguously addressing towards pathologies. comparison with other clustering tools is performed.
a novel grammar-based genetic programming approach to clustering. most of the classical methods for clustering analysis require the user setting of number of clusters. to surmount this problem, in this paper a grammar-based genetic programming approach to automatic data clustering is presented. an innovative clustering process is conceived strictly linked to a novel cluster representation which provides intelligible information on patterns. the efficacy of the implemented partitioning system is estimated on a medical domain by exploiting expressly defined evaluation indices. furthermore, a comparison with other clustering tools is performed.
inductive inference of chaotic series by genetic programming: a solomonoff-based approach. a genetic programming approach to inductive inference of chaotic series, with reference to solomonoff complexity, is presented. it consists in evolving a population of mathematical expressions looking for the 'optimal' one that generates a given chaotic data series. validation is performed on the logistic, the henon and the mackey-glass series. the method is shown effective in obtaining the analytical expression of the first two series, and in achieving very good results on the third one.
digital geometry image analysis for medical diagnosis. this paper describes a new medical image analysis technique for polygon mesh surfaces of human faces for a medical diagnosis application. the goal is to explore the natural patterns and 3d facial features to provide diagnostic information for fetal alcohol syndrome (fas). our approach is based on a digital geometry analysis framework that applies pattern recognition techniques to digital geometry (polygon mesh) data from 3d laser scanners and other sources. novel 3d geometric features are extracted and analyzed to determine the most discriminatory features that best represent fas characteristics. as part of the nih consortium for fasd, the techniques developed here are being applied and tested on real patient datasets collected by the nih consortium both within and outside the us.
boundary surface extraction and rendering for volume datasets. traditional iso-surface techniques focus on the extraction and rendering of contour surfaces. boundary surfaces, however, are often more interesting and useful to the applications as they are more natural representations of the objects embedded in the dataset. this paper describes an efficient boundary surface extraction and rendering approach for volume datasets. a volume dataset is first filtered using a laplacian of gaussian (log) filter to generate a zero-crossing field, from which boundary surface information is extracted. two types of surfaces can be generated: (1) zero-crossing surface; and (2) iso-surface boundaries. the zero-crossing surface can be extracted directly from the zero-crossing field as an iso-surface with a zero iso-value. original intensity values will then be attached to the vertices of the polygon mesh for flexible rendering. iso-surface boundaries are the iso-surfaces from the original volume that best approximate the zero-crossing boundaries. the iso-values of these iso-surface boundaries are obtained through a histogram analysis of the zero-crossing boundaries in a multi-scale space. the new approach provides a more efficient and accurate surface navigation technique for volume data exploration.
visualization of unstructured text sequences of nursing narratives. this paper presents a keyword-based information visualization technique for nursing record sequences. visualizing the trend information rooted in unstructured and fragmented abstract text data is a largely unaddressed problem. in our technique, multiple hierarchical keyword based visualizations are used to explore unstructured text data from nursing records. first, each text data set is broken up into a list of keywords to enable the visualization of keyword occurrences over time and the relative distribution of keywords. a graphical user interface is provided to enable selection and classification of keywords. users may select one or more data sets to compare, in addition to one or more groups of keywords to add to the visualization. colors are used to distinguish quickly and easily between groups of keywords present in the visualization. at the second level of hierarchy, keywords for visualization are discovered through a predetermined automatic detection and scoring based mechanism. the aggregate frequency trend of keywords from all data sets is also provided in both hierarchies as a way to visualize overall trends and analyze various events in time.
the recursive transpose-connected cycles (rtcc) interconnection network for multiprocessors. in this paper, we propose a new modular topology for interconnection networks, the recursive transpose-connected cycles (rtcc). the rtcc has a recursive definition quite similar to that of fractal graphs having interesting topological characteristics, making it suitable for utilization as the base topology of large-scale multicomputer interconnection networks. we study important properties of this topology such as diameter, bisection width and issues related to implementation, such as routing algorithms and the average message latency under vlsi layout constraints. in addition, we prove that the rtcc is a hamiltonian graph. we conclude that, insight of most of the above-mentioned properties, the rtcc is superior to conventional topologies such as the mesh and k-ary n-cube.
on the relationship between roles and power: preliminary report. this paper discusses a formal analysis of multi-agent systems based on organizational and normative concepts. social agents (individuals and groups) and multi-agent systems have an underlying structure which is underpinned by roles. power is legitimized within a social context and it stems from a role. in other words, agents draw their power from the authority positions that they hold in relation to other agents. how roles are intertwined with commitments, obligations, power, rights and authority relations is discussed.
efficient discovery of loosely structured motifs in biological data. in the last few years, the completion of the human genome sequencing showed up a wide range of new challenging issues involving raw data analysis. in particular, the discovery of information implicitly encoded in biological sequences is assuming a prominent role in identifying genetic diseases and in deciphering biological mechanisms. this information is usually represented by patterns frequently occurring in the sequences, also called motifs. because of biological observations, the class of structured motifs have received much attention. this paper gives a contribution in this setting by providing an efficient algorithm for the identification of novel classes of structured motifs, where several kinds of "exceptions" (whose biological relevance recently emerged in the literature) may be tolerated in pattern repetitions.
msa: a memory-aware utility accrual scheduling algorithm. whereas fairness can be the basis for general-purpose operating system scheduling policies, timeliness is the primary concern for real-time systems. as such, real-time schedulers permit uninterrupted, exclusive access to the cpu by a specific task to ensure its timely completion of execution. only a subset of tasks, however, can satisfy their timing constraints during processor overload conditions in a real-time system. utility accrual (ua) scheduling disciplines assure scalability and graceful performance degradation by identifying the subset of tasks to be granted the heavily contended system resources.furthermore, whereas general-purpose operating systems treat memory monolithically and indiscriminately service dynamic allocation requests, ua-schedulers can benefit from special memory management considerations during memory overload conditions. msa, the scheduling algorithm here presented is the first of its kind to treat memory as a ua-scheduler-managed resource. the scheduler is made aware of memory allocation requirements of each task throughout runtime and accordingly makes appropriate cpu and resource scheduling decisions. the algorithm is well-suited for use in resource-constrained embedded systems in a soft real-time environment.we have implemented msa in a posix real-time operating environment and measured its performance under various load conditions. our experimental results show overall performance gains over other memory-unaware ua scheduling algorithms during memory overload.
transformation of b specifications into uml class diagrams and state machines. we propose a rule-based approach for transforming b abstract machines into uml diagrams. we believe that important insight into the structure underlying a b model can be gained by representing it in uml, for example in order to explain the model to stakeholders that are not experts in the b formalism. we focus on the generation of class diagram and state machines. our approach does not prescribe a mechanic algorithm for translation, giving the modeler choices to adapt the resulting uml models as appropriate.
limits in modelling evolving computer-based systems. this paper explores the limitations of one technique for modelling computer-based systems with evolving requirements. a case study is introduced which highlights the importance of taking a multi-perspective on dependable computer-based systems. this should be reflected in the modelling technique. such considerations motivate our ongoing research agenda.
comparing images with distance functions based on attribute interaction. this paper presents two new families of distance functions for image comparison through their feature vectors. these families concern with the effects of the interaction of attributes when two images are compared. experiments were executed in order to corroborate the effectiveness of the new functions, leading to very promising results.
effective shape-based retrieval and classification of mammograms. this paper presents a new approach to support computer-aided diagnosis (cad) aiming at assisting the task of classification and similarity retrieval of mammographic mass lesions, based on shape content. we have tested classical algorithms for automatic segmentation of this kind of image, but usually they are not precise enough to generate accurate contours to allow lesion classification based on shape analyses. thus, in this work, we have used zernike moments for invariant pattern recognition within regions of interest (rois), without previous segmentation of images. a new data mining algorithm that generates statistical-based association rules is used to identify representative features that discriminate the disease classes of images. in order to minimize the computational effort, an algorithm based on fractal theory is applied to reduce the dimension of feature vectors. k-nearest neighbor retrieval was applied to a database containing images excerpted from previously classified digitalized mammograms presenting breast lesions. the results reveal that our approach allows fast and effective feature extraction and is robust and suitable for analyzing this kind of image.
a new similarity measure for histograms applied to content-based retrieval of medical images. this paper presents a new similarity measure to compare gray-level histograms, aiming at reducing both false positive and false negative results, in the context of medical images.
an improved hybrid genetic algorithm for the generalized assignment problem. we consider the generalized assignment problem in which the objective is to find a minimum cost assignment of a set of jobs to a set of agents subject to resource constraints. the presented new approach is based on a previously published, successful hybrid genetic algorithm and includes as new features two alternative initialization heuristics, a modified selection and replacement scheme for handling infeasible solutions more appropriately, and a heuristic mutation operator. tests are performed on standard test instances from the literature and on newly created, larger and more difficult instances. the presented genetic algorithm with its two initialization variants is compared to the previous genetic algorithm and to the commercial general purpose branch-and-cut system cplex. results indicate that cplex is able to solve relatively large instances of the general assignment problem to provable optimality. for the largest and most difficult instances, however, the proposed genetic algorithm yields on average the best results in shortest time.
time-frequency feature detection for time-course microarray data. gene clustering based on microarray data provides useful functional information to the working biologists. many current gene-clustering algorithms rely on euclidean-based distance metrics and fail to capture the time-dependent features of the data, usually corrupted by high levels of experimental noise. here we propose an algorithm capable of dealing with the noise through a time-frequency approach and related measure of correlation between time-course expressions of different genes (trajectories). the approach makes use of fast multi-resolution feature classification algorithms and allows for the desired functional characteristics (such as phase delay, activation/repression etc.) to be enhanced and detected.we have applied our algorithm to time-course microarray data of drosophila melanogaster (arbeitman et al., science, sep 27, 2002, page 2270--2275). we examined various relations among homeodomain genes (referred to as group h) and regulators of homeodomain genes (group rh) as follows: after normalization, the trajectories were projected on to cosbell wavelet basis. the four genes in group rh form two clusters: three of them stayed close to each other, and the last one, cg8651 (trithorax), was singled out. the group h genes, forming four clusters, showed functional features that are more similar to trithorax than the other three. we further analyzed ten homeodomain genes that have good correlations with trithorax in the wavelet basis. literature search showed that there are five genes thought to be in the downstream pathway of trithorax. although only two of these five genes were in the dataset available to the algorithm, it was able to identify both of these. our study suggests that timefrequency analysis provides a powerful tool for discovering the underlying regulatory networks when applied to time-course microarray data.
exploit sequencing to accelerate hot xml query pattern mining. speeding up query evaluation in large xml repositories becomes a challenging and all-important problem with vast xml-related applications arising. upon discovery of hot xml query patterns, indexing and caching can be effectively adopted for query performance enhancement. previous algorithms for finding hot query patterns basically introduced a straightforward generate-and-test strategy. in this paper, we present, solaria, an efficient algorithm for mining hot xml query patterns without candidate maintenance and costly tree-containment checking. efficient algorithm of sequence mining is involved in discovering frequent tree-structured patterns, which aims at replacing expensive containment testing with cheap parent-child checking in sequences. solaria deeply prunes unrelated search space for frequent pattern enumeration by parent-child relationship constraint. with the motivation of indexing and caching in xml query optimization, we also propose the derived algorithm solaria for mining hot "closed" xml query patterns which provide compact and complete structure information. by a thorough experimental study on various real-life data, we demonstrate the efficiency and scalability of solaria over the previous known alternative. solaria is also linearly scalable in terms of xml queries' size.
a methodology to provide and use interchangeable services. computing today requires the use of many software packages, but only a few packages are used on a daily basis. this infrequent usage pattern often does not justify purchasing full licenses and therefore motivates a need for a more flexible way to use and pay for the usage of software. this paper describes a design philosophy in which similar services provide the same interface to clients. services based on this design are interchangeable, allow payment per use, handle payment conveniently, are platform independent, and frequently do not require local installation. clients can therefore easily utilize resources based on application needs and services available at the time that the application is executing. an example implementation using this methodology is also discussed.
a new cache management algorithm for multimedia storage systems. every storage platform intended to fit the requirements of the multimedia systems must incorporate a disk scheduling mechanism and a cache architecture that can handle their special needs. on the other hand, the general trend is to make integrated storage platforms that meet the requirements of deterministic applications, multimedia systems, and traditional best-effort applications altogether. in this paper we propose a new multimedia cache algorithm that imposes several optimizations to the state of the art. this algorithm has been designed to become part of an integrated storage system, including a proposal for an admission control algorithm that ensures the response time of the system for the accepted requests. this paper also presents an evaluation of the algorithm and compares it with other algorithms described in the bibliography.
an analysis of modeling flaws in hl7 and jahis. health level 7 (hl7), one of the ansi standards organizations has a mission to provide standards for the execution, management, and integration of data to support clinical patient care. hl7 will play an important role in the implementation of the hipaa regulations. hl7 has developed a reference information model (rim), an object-oriented model of clinical data. jahis is a japanese organization that has developed extensions to this rim. instead of using the unified modeling language (uml), the standard notation for object-oriented software development, these two organizations have developed specialized object-oriented models. this has resulted in languages which are incompatible with the current use of uml. the consequences of this choice are the loss of the possible use of a large variety of existing models and patterns. what is worse, it will be difficult to add security specifications in their models, a critical aspect in the electronic interchange of medical records. we discuss here the shortcomings of hl7 and jahis as modeling languages and as languages in which to add security specifications. we also propose some solutions to this situation.
a debugging calculus for mobile ambients. advancements in network-aware computing has prompted the study of novel programming languages with advanced programming abstractions to support various forms of mobility and to coordinate and monitor the use of resources. this work addresses the issue of designing debuggers for network-aware programming languages. in our approach a debugger is viewed as being an extension of the underlying programming language with suitable debugging abstractions. we apply this idea to cardelli and gordon's ambient calculus [3]. the resulting debugger is designed to monitor and trace executions of mobile ambients by keeping track of causal informations about events of computations.
blinded-key signatures: securing private keys embedded in mobile agents. we present a new cryptographic primitive, the blinded-key signature, which allows the inclusion of private keys in autonomous mobile agents. this novel approach can be applied to many well-known digital signature schemes, such as rsa and elgammal.
prototype-based mining of numeric data streams. great organizations collect open-ended and time-changing data received at a high speed. the possibility of extracting useful knowledge from these potentially infinite databases is a new challenge in data mining. in this paper we propose an anytime incremental learning algorithm for mining numeric data streams. within supervised learning, our approach is based on prototypes and hypercubic decision rules, concerning with the simplicity of the model provided and the time complexity as primary goals. experimental results with synthetic databases of 100 gigabytes show a good performance from streams of data in continuous transformation.
discovering decision rules from numerical data streams. this paper presents a scalable learning algorithm to classify numerical, low dimensionality, high-cardinality, time-changing data streams. our approach, named scallop, provides a set of decision rules on demand which improves its simplicity and helpfulness for the user. scallop updates the knowledge model every time a new example is read, adding interesting rules and removing out-of-date rules. as the model is dynamic, it maintains the tendency of data. experimental results with synthetic data streams show a good performance with respect to running time, accuracy and simplicity of the model.
incremental rule learning based on example nearness from numerical data streams. mining data streams is a challenging task that requires online systems based on incremental learning approaches. this paper describes a classification system based on decision rules that may store up-to-date border examples to avoid unnecessary revisions when virtual drifts are present in data. consistent rules classify new test examples by covering and inconsistent rules classify them by distance as the nearest neighbor algorithm. in addition, the system provides an implicit forgetting heuristic so that positive and negative examples are removed from a rule when they are not near one another.
data streams classification by incremental rule learning with parameterized generalization. mining data streams is a challenging task that requires online systems based on incremental learning approaches. this paper describes a classification system based on decision rules that may store up--to--date border examples to avoid unnecessary revisions when virtual drifts are present in data. consistent rules classify new test examples by covering and inconsistent rules classify them by distance as the nearest neighbor algorithm. in addition, the system provides an implicit forgetting heuristic so that positive and negative examples are removed from a rule when they are not near one another.
the syntactic and semantic correctness of pictorial configurations to query geographic databases by pql. in the field of geographic information systems, one important issue is related to define a sound method of syntactic and semantic correctness analysis for queries which can lead to multiple interpretations for the system and for the user. in this paper, we propose an approach in order to determine the exact syntactic and semantic interpretations of geographic configurations that are involved in queries for a pictorial query language. this language, called pql, supports interactive manipulation of geographic elements letting users directly to express a query by drawing. we put in evidence and underline all the syntactically correct pictorial configurations among geographic objects which represent the topological relationships. then, upon such analysis we determine the semantic correctness of configurations depending on the stored geographic data, and the detection of the ambiguities. we propose different solutions to determine the semantic correctness integrating the result of such approach to the set of pql operators. finally, we show the capability of such approach to resolve the ambiguities which arise from the formulation of complex queries involving multiple geographic objects.
design and implementation of component-based adaptive web presentations. engineering adaptive web applications implies the development of content that can be automatically adjusted to varying client devices and user preferences. to meet this requirement, the amacont project recently introduced a component-based xml document format. configurable document components encapsulating adaptive behavior and layout are used on different abstraction levels in order to support flexible reuse for effective web page generation. this paper focuses on the process of designing and implementing such component-based adaptive web presentations. based on the model-driven specification framework from the hera project, different phases of adaptation design are identified and their realization using amacont components is explained. finally, a pipeline-based document generator for dynamically publishing component structures to different web output formats is described.
a modular approach to build structured event-based systems. event-based systems are developed and used as a coordination model to integrate components in loosely coupled systems. research and product development focused so far on efficiency issues but neglected methodological support to build such systems. in this paper, we present the modular design and implementation of an event system which supports scopes and event mappings, two new and powerful structuring methods that facilitate engineering and coordination of components in event-based systems. the approach is based on a trace-based specification method adapted from temporal logic.
verification of coordinated exception handling. an important challenge faced by the developers of fault-tolerant distributed systems is to build fault tolerance mechanisms that are reliable. to achieve the desired levels of reliability, the development of mechanisms for detecting and handling errors should be rigorous or formal. in this paper, we present an approach to modeling and verifying fault-tolerant distributed systems that use exception handling as the main fault tolerance mechanism. the proposed approach is based on a formal model for specifying the structure of a system in terms of cooperating participants that handle exceptions in a coordinated manner. we use a medical control system as a case study to validate the proposed approach.
an extensible architecture-based framework for coordination languages. the dynamic and heterogeneous nature of distributed systems make the development of distributed applications a difficult task. various tools, such as middleware systems, component systems, and coordination languages, offer support to the application developer at different levels.there are several coordination systems that integrate such tools into a complete environment to build applications from heterogeneous components. to achieve extensibility they usually have a layered architecture: an application is first mapped to a middle layer and then to a target system. but this approach hides the specific features of a target system from the developer, as they are not represented in the middle layer, and often induces additional run-time overhead.in this paper we introduce the extensible coordination framework ecf that allows developers to build efficient distributed applications which exploit the specific features of the target systems. support for target systems and application domains are encapsulated by extension modules. modules can be built on top of other modules to support refined functionality.
automated terrain generation using lidar and waterbody survey data. lidar data provides a dense and precise sampling of ground elevations on land, but not of bathymetric elevations in a waterway. by supplementing lidar data with densely interpolated waterway survey data, terrain models can be generated to approximate lidar-derived topography combined with waterway bathymetry. three-dimensional interpolation techniques are used to generate a dense waterway bathymetry, as well as the bounding region to clip and fill the lidar data with this bathymetry. consequently, the resulting terrain is fit for both visualization and further processing in hydraulic and hydrological models.
reflection-based implementation of java extensions: the double-dispatch use-case. reflection-based libraries could sometimes be used to extend the expressive power of java without modifying the language nor the virtual machine. in this paper, we present the advantages of this approach together with general guidelines allowing such implementations to be practicable. then, we show how these principles have been applied to implement an efficient and general double-dispatch solution for java.
a content classification and filtering server for the internet. the amazing growth of the web in recent years, which includes content inappropriate for some classes of users, has gone hand in hand with increasingly sophisticated mobile access devices (e.g., cell phones). in this context, a major challenge is the dynamic adaptation of content, which allows these devices to access any given content independently of its original format, allied to a number of added value services such as virus scanning, language translation and content filtering. this article proposes and implements a content classification and filtering server inserted into a content adaptation architecture based on the internet content adaptation protocol (icap). the proposed solution does not depend on hardware or software characteristics of access devices, for the service is done externally through edge devices (e.g., proxies).
from modeling to enactment of distributed workflows: an agent-based approach. this paper proposes an agent-based approach which seamlessly supports the phases of modeling and enactment of distributed workflows. an agent-based distributed workflow model is basically obtained by instantiating a mas (multi-agent system) meta-model for the management of distributed workflows by means of a workflow schema based on the workflow patterns. in order to enact an obtained agent-based model, a jade-based workflow enactment framework, directly designed upon the mas meta-model, was developed.
multi-coordination of mobile agents: a model and a component-based architecture. this paper proposes a model along with a reference software architecture enabling multi-coordination between distributed and mobile software agents. multi-coordination allows agents to choose among a variety of different coordination spaces and patterns which best fit their dynamic communication and synchronization needs. it can be fruitfully exploited by agents in heterogeneous and dynamic environments like the internet where the mutable conditions of communications and computing usually affect both the currently agreed workflow and the performances of agent-based applications. the proposed model centers on high-level events which can be locally emitted and/or received by agents and which unify access to and exploitation of underlying coordination spaces and agent server resources. the model is supported by a component-based architecture which provides agent management and notably agent coordination through a coordination context dynamically assembled with a set of different local and/or global coordination spaces. a prototypical implementation of the architecture was also carried out using java and the voyager orb middlewares.
lemp: lightweight efficient multicast protocol for video on demand. in this paper, we propose a new scalable application-layer protocol, specifically designed for data streaming applications with large client sets. this is based upon a control hierarchy of successive levels for the clients, has minimal overhead with constant number of messages per client, and is robust to client and network failures, making it suitable for wireless environments. the video server bandwidth utilization is also significantly reduced. we present an analysis and simulation results, showing that lemp is near optimum in terms of performance.
visualization of neuronal fiber connections from dt-mri with global optimization. diffusion tensor mri (dt-mri) provides valuable 3d data describing diffusion characteristics of water molecules in the human brain. from dt-mri, it is hoped that neuronal fiber connections among cortical regions can be reliably extracted and adequately interpreted. to achieve this goal, several significant challenges persist. in this paper, by means of dynamic programming we have developed a global fiber reconstruction algorithm enabling efficient visualization of neuronal connections queried by both the start and end points on the fly. besides an inherent ability to handle noisy datasets, our algorithm also naturally addresses situations where neuronal fibers branch or cross each other. we demonstrate the efficacy of our approach with visualization of neuronal connections among activated brain cortical regions detected by functional mri (fmri).
time-varying, multivariate volume data reduction. large-scale supercomputing is revolutionizing the way science is conducted. a growing challenge, however, is understanding the massive quantities of data produced by large-scale simulations. the data, typically time-varying, multivariate, and volumetric, can occupy from hundreds of gigabytes to several terabytes of storage space. transferring and processing volume data of such sizes is prohibitively expensive and resource intensive. although it may not be possible to entirely alleviate these problems, data compression should be considered as part of a viable solution, especially when the primary means of data analysis is volume rendering. in this paper we present our study of multivariate compression, which exploits correlations among related variables, for volume rendering. two configurations for multidimensional compression based on vector quantization are examined. we emphasize quality reconstruction and interactive rendering, which leads us to a solution using graphics hardware to perform on-the-fly decompression during rendering.
methods for learning classifier combinations: no clear winner. this work compares two approaches to finding effective topic-independent classifier combinations. we suggest a new federated approach and compare it against the global approach. our results indicate that the relative effectiveness of these approaches depends on the measure used to evaluate them. we suggest explanations for these results.
authenticity in a reliable protocol for mobile computing. we consider a known protocol for reliable multicast in distributed mobile systems where mobile hosts communicate with a wired infrastructure by means of wireless technology. the original specification of the protocol does not take into consideration any notion of computer security: an adversary may eavesdrop on communications between hosts and inject packets over the wireless links. we suggest a secured version of the protocol providing authenticity and integrity of packets over the wireless links. the secure mechanisms introduced rely on two different techniques: secure wireless channels and 1-time signature schemes. further, we outline the formal verification of part of the secured protocol.
echo-cardiography on the web: design and set-up of a virtual community of experts. nowadays digital ultrasound-cardiovascular devices are able to send out directly digital images and films (still and loop modes). thanks to the large adoption of such devices, the echocardiographic world is facing new ways of exchanging images and collaborate. what we present in this paper is a digital echo-lab system composed by a web site, supporting and coordinating the work of specialists and a teleconsulting desktop application for second opinion (carolin), designed around echo-cardiography needs. the web solution is suitable for echocardiography because stored loops have dimensions, which are compatible (in terms of mbytes) with present internet bandwidth limitations. the web site is integrated with a largely adopted peer-2-peer telemedicine teleconsultation tool (carolin) allowing it to act as a bridge between carolin's world and on-line web information sharing (suitable for students or virtual communities). we will also discuss the modeling process adopted to catch real users' needs: in most cases users do not have clear visions of how such technologies could improve their work and also developers do not know details of physicians work, that is why we need a precise modeling process.
node splitting algorithms in tree-structured high-dimensional indexes for similarity search. content-based searches and retrievals in multimedia and image databases use high-dimensional indexing structures for organizing the features of the objects. most of those index structures are tree-structured whose nodes have a limit on the number of entries describing the subtrees rooted at those nodes. when index trees are built by repeated insertion of entries, nodes need to be split and the tree balanced accordingly. node-splitting algorithms eventually determine the final structure of the tree which will have a profound effect on the search performance. this paper presents a comparative study of several node splitting algorithms for a typical high-dimensional indexing structure. the algorithms are implemented and tested on an image database and the results are presented.
response order rearrangement on a caching proxy for reducing www latency. recently, the explosive growth of the www (world wide web) has been causing serious performance degradation on the internet. one of the approaches of addressing this problem is the use of proxy caching, where a proxy cache is placed close to a set of clients and delivers web content to them faster than the origin server. on the other hand, the ability of http/1.1 (hypertext transfer protocol) has been enhanced by the introduction of pipelined requests, which allow a client to make multiple requests without waiting for each response. however, previous research on proxy caching has not fully investigated the impact of pipelined requests. in this paper, we propose 'http-ror (http with response order rearrangement)', a new approach toward reducing the user-perceived latency, and consider pipelined requests to caching proxies. we then show analytical performance evaluations and practical evaluations in several experimental environments.
towards system software for physical space applications. in ubiquitous computing era, the notion of context-awareness will play an important role. an application should be aware of its operating context for supporting and enriching human activities. such contextual information is required to be captured as seamlessly as possible through interaction between users and surrounding environments. this leads to the need for dealing with a wide variety of contextual information from a physical world.in this paper, we propose a conceptual framework, bazaar, for modeling the physical world and for manipulating the model. it constructs the model with self-descriptive objects represented as a set of triples. also, a programming model allows a developer to intuitively manipulate the model and develop an application. moreover, we report experiences with building sample applications.
"take me with you!": a case study of context-aware application integrating cyber and physical spaces. context-awareness is one of the exciting research topics in a ubiquitous computing environment, which is expected to create some new business and/or services by using sensors and actuators. especially, context information from cyber space allows a system to extend its information space both temporalily and spatially. however, many applications do not regard context information from cyber space as a information source of future tense. this keeps applications from being aware of a wide variety of context.we have developed a system software "contextdistillery", which enables an application developer to obtain context information incrementally without taking account of descriptive information, meta-context information. next, we have built an application "take me with you!", which exemplifies the notion of physical/cyber space integration.this paper reports a case study of the application development. discussions of findings through the application development are presented. moreover, an architecture for realizing more practical notions of context-awareness is introduced based on the discussions.
hierarchical binary histograms for summarizing multi-dimensional data. the need to compress data into synopses of summarized information often arises in many application scenarios, where the aim is to retrieve aggregate data efficiently, possibly trading off the computational efficiency with the accuracy of the estimation. a widely used approach for summarizing multi-dimensional data is the histogram-based representation scheme, which consists in partitioning the data domain into a number of blocks (called buckets), and then storing summary information for each block. in this paper, a new histogram-based summarization technique which is very effective for multi-dimensional data is proposed. this technique exploits a multi-resolution organization of summary data, on which an efficient physical representation model is defined. the adoption of this representation model (based on a hierarchical organization of the buckets) enables some storage space to be saved w.r.t. traditional histograms, which can be invested to obtain finer grain blocks, thus approximating data with more detail. experimental results show that our technique yields higher accuracy in retrieving aggregate information from the histogram w.r.t. traditional approaches (classical multi-dimensional histograms as well as other types of summarization technique).
an adaptive three-dimensional dct compression based on motion analysis. in this paper, we propose an adaptive 3d-dct compression technique, which dynamically determines an optimal size of the video cube based on the motion analysis. the technique consists of two steps: (a) it analyses the motion within a small (16x16) video cube of eight successive frames, and (b) it selects the size of the cube based on the motion analysis and applies the 3d-dct algorithm on the selected video cube. the effectiveness of the proposed technique is illustrated by implementing it to a number of video sequences with low, medium, and high motion.
a framework for resource-aware knowledge discovery in data streams: a holistic approach with its application to clustering. mining data streams is a field of increase interest due to the importance of its applications and dissemination of data stream generators. most of the streaming techniques developed so far have not addressed the need of resource-aware computing in data stream analysis. the fact that streaming information is often generated or received onboard resource-constrained computational devices such as sensors and mobile devices motivates the need for resource-awareness in data stream processing systems. in this paper, we propose a generic framework that enables resource-awareness in streaming computation using algorithm granularity settings in order to change the resource consumption patterns periodically. this generic framework is applied to a novel threshold-based micro-clustering algorithm to test its validity and feasibility. we have termed this algorithm as ra-cluster. ra-custer is the first stream clustering algorithm that can adapt to the changing availability of different resources. the experimental results showed the applicability of the framework and the algorithm in terms of resource-awareness and accuracy.
hardware/software 2d-3d backprojection on a sopc platform. the reduction of image reconstruction time is needed to spread the use of pet for research and routine clinical practice. in this purpose, this article presents a hardware/software architecture for the acceleration of 3d backprojection based upon an efficient 2d backprojection. this architecture has been designed in order to provide a high level of parallelism thanks to an efficient management of the memory accesses which would have been otherwise strongly slowed by the external memory. the reconstruction system is embedded in a sopc platform (system on programmable chip), the new generation of reconfigurable circuit. the originality of this architecture comes from the design of a 2d adaptative and predictive cache (2d-ap cache) which has proved to be an efficient way to overcome the memory access bottleneck. thanks to a hierarchical use of this cache, several backprojection operators can run in parallel, accelerating in this manner noteworthy the reconstruction process. this 2d reconstruction system will next be used to speed up 3d image reconstruction.
a functional architecture for self-aware routers. in this paper, we first present the concept of self-configuration and self-provisioning applied into the scope of the ip routers. a global view of the concepts which are addressed in this document is given, considering the automation level of the operations, and their communication schemes. the node characteristics that are taken into account in the definition of self-configuration and self-provisioning mechanisms are also detailed, introducing the second part of the paper. in this part, a reference architecture for a self-configuration router is given, allowing the community to have a common understanding on the expected functionalities by such routers. an evaluation of the existing proposals to address part of all the issues raised by self-configuration is also presented.
using xml to implement abstraction for model checking. model checking has become one of the most powerful methods for automatic verification of software systems. however it is widely accepted that this technique is only usable when the behavior of the system to be analyzed is given by small models, in order to avoid the state explosion problem. the paper presents &alpha;spin, an xml-based tool for obtaining abstract versions from a given model written in promela, which can be verified with the model checker spin. this tool follows the theoretical basis presented in [9].
forest trees for on-line data. this paper presents an hybrid adaptive system for induction of forest of trees from data streams. the ultra fast forest tree system (ufft) is an incremental algorithm, with constant time for processing each example, works online, and uses the hoeffding bound to decide when to install a splitting test in a leaf leading to a decision node. our system has been designed for continuous data. it uses analytical techniques to choose the splitting criteria, and the information gain to estimate the merit of each possible splitting-test. the number of examples required to evaluate the splitting criteria is sound, based on the hoeffding bound. for multiclass problems, the algorithm builds a binary tree for each possible pair of classes, leading to a forest of trees. during the training phase the algorithm maintains a short term memory. given a data stream, a fixed number of the most recent examples are maintained in a data-structure that supports constant time insertion and deletion. when a test is installed, a leaf is transformed into a decision node with two descendant leaves. the sufficient statistics of these leaves are initialized with the examples in the short term memory that will fall at these leaves. we study the behavior of ufft in different problems. the experimental results shows that ufft is competitive against a batch decision tree learner in large and medium datasets.
learning decision trees from dynamic data streams. this paper presents a system for induction of forest of functional trees from data streams able to detect concept drift. the ultra fast forest of trees (ufft) is an incremental algorithm, that works online, processing each example in constant time, and performing a single scan over the training examples. it uses analytical techniques to choose the splitting criteria, and the information gain to estimate the merit of each possible splitting-test. for multi-class problems the algorithm grows a binary tree for each possible pair of classes, leading to a forest of trees. decision nodes and leaves contain naive-bayes classifiers playing different roles during the induction process. naive-bayes in leaves are used to classify test examples, naive-bayes in inner nodes can be used as multivariate splitting-tests if chosen by the splitting criteria, and used to detect drift in the distribution of the examples that traverse the node. when a drift is detected, all the sub-tree rooted at that node will be pruned. the use of naive-bayes classifiers at leaves to classify test examples, the use of splitting-tests based on the outcome of naive-bayes, and the use of naive-bayes classifiers at decision nodes to detect drift are directly obtained from the sufficient statistics required to compute the splitting criteria, without no additional computations. this aspect is a main advantage in the context of high-speed data streams. this methodology was tested with artificial and real-world data sets. the experimental results show a very good performance in comparison to a batch decision tree learner, and high capacity to detect and react to drift.
discretization from data streams: applications to histograms and data mining. in this paper we propose a new method to perform incremental discretization. the basic idea is to perform the task in two layers. the first layer receives the sequence of input data and keeps some statistics on the data using many more intervals than required. based on the statistics stored by the first layer, the second layer creates the final discretization. the proposed architecture processes streaming examples in a single scan, in constant time and space even for infinite sequences of examples. we experimentally demonstrate that incremental discretization is able to maintain the performance of learning algorithms in comparison to a batch discretization. the proposed method is much more appropriate in incremental learning, and in problems where data flows continuously, as in most of the recent data mining applications.
semi-supervised outlier detection. outlier detection has been extensively researched in the context of unsupervised learning. but the learning results are not always satisfactory, which can be significantly improved using supervision of some labeled points. in this paper, we are concerned with employing supervision of limited amount of label information to detect outliers more accurately. the key of our approach is an objective function that punishes poor clustering results and deviation from known labels as well as restricts the number of outliers. the outliers can be found as a solution to the discrete optimization problem regarding the objective function. by this way, this method can detect meaningful outliers that can not be identified by existing unsupervised methods.
location dependent query proxy. in a mobile environment, the result of queries often depends on the client's location. these queries are called location dependent queries (ldq). applying the concept of caching to ldqs provides a means for efficient processing when queries exhibit both semantic similarity and spatial locality. existing ldq caching schemes require database (db) servers to provide validity regions (vr) for ldq results, which introduces significant processing and/or storage overhead. as a result, db servers may only provide the validity information conditionally or do not provide it at all. we propose a novel ldq proxy scheme that can estimate the vr if db servers do not provide such information. the simulation results show that the ldq proxy reduces both the ldq response time and the database workload.
editorial message: technical track on geometric computing and reasoning. geometric computing and reasoning (gcr) is a new track of sac and it is dedicated to the recent trends in the domain of geometric constraint solving and automated, or computer aided, deduction in geometry.
quality-driven evaluation of trigger conditions on streaming time series. for many applications, it is important to evaluate trigger conditions on time series streams. in a resource constrained environment, users' needs should ultimately decide how the evaluation system balances the competing factors such as evaluation speed, result precision, and load shedding level. this paper presents a basic framework for evaluation algorithms that takes user-specified quality requirements into consideration. three optimization algorithms, each under a different set of quality requirements, are developed in the framework: (1) minimize the response time given accuracy requirements and without load shedding; (2) minimize the load shedding given a response time limit and accuracy requirements; and (3) minimize one type of accuracy errors given a response time limit and without load shedding. experiments show that these optimization algorithms effectively achieve their optimization goals while satisfying the corresponding user-specified quality requirements.
analysis of distributed routing balancing behavior. distributed routing balancing (drb) is a method developed to uniformly balance communication traffic over the interconnection network. drb takes a similar approach to communications as load balancing does to processes in a distributed environment. the key ideas behind drb are to distribute communication load based on limited and load-controlled path expansion, in order to maintain low message latency. in this paper, we present an exhaustive evaluation of drb that shows that the method presents low overhead and is robust with respect to the accuracy of the monitoring information it uses, and we compare its latency performance against other state-of-the-art routing methods.
concurrency control for distributed cooperative engineering applications. distributed cooperative engineering applications require consistent and long-term sharing of large volumes of data, which may cause conflicts due to concurrent read/write operations. therefore designing concurrency control for underlying middleware systems is a difficult issue.current transactional solutions, even if based on an optimistic approach, do not solve the problem because such applications access shared data for long periods of time performing a large number of read/write operations. typically, a large set of modifications has to be discarded and this is unacceptable given the amount of work lost.in this paper, we describe the design and implementation of concurrency control mechanisms aimed at both reducing the amount of such conflicts and supporting the consistent long-term sharing of data. the mechanism of visibility depth allows the programmer to specify the consistency of shared data w.r.t. different sets of sites. we also provide other mechanisms: private-copy that allows data to be read/written without being considered as part of a transaction and reordering transaction history to avoid transaction aborts. we evaluate these techniques on a prototypical middleware system called perdis and show that: (i) the concurrency control mechanisms are well adapted to support long-lived data sharing in local or wide-area networks, and (ii) performance is acceptable.
evaluating the use of profiling by a region-based register allocator. in a region-based compilation framework, the compiler builds regions to provide the best compilation unit for scheduling and optimization. the compiler uses execution frequency information gained from profiling to place frequently executed blocks in the same region. this paper investigates the use of profiling in a region-based compilation framework and measures its impact on the register allocation phase. the profiling information can be used by the register allocator to assign values to physical registers based on the execution frequency of the regions. register allocation can be performed on the most frequently executed regions first so that any spilling that occurs causes memory accesses in less frequently executed regions. the experimental study indicates that profile assisted region formation and register allocation can result in code that executes faster than the code that was compiled without using profiling information and the amount of spill code executed can be reduced significantly.
delay-based circuit authentication and applications. we describe a technique to reliably identify individual integrated circuits (ics), based on a prior delay characterization of the ic.we describe a circuit architecture for a key card for which authentication is delay based, rather than based on a digital secret key. we argue that key cards built in this fashion are resistant to many known kinds of attacks.since the delay of ics can vary with environmental conditions such as temperature, we develop compensation schemes and show experimentally that reliable authentication can be performed in the presence of significant environmental variations.the delay information that is extracted from the ic can also be used to generate keys for use in classical cryptographic primitives. applications that rely on these keys for security would be less vulnerable to physical attack.
incorporating fuzziness in xml and mapping fuzzy relational data into fuzzy xml. in this paper, we present an approach for incorporating fuzzy and imprecise data in xml documents. we describe the ways to introduce fuzziness using both possibility theory and similarity relations. we then show how to map the data from a fuzzy relational database into a fuzzy xml document, with the corresponding xml schema. this approach will aid in liberating the data stored in fuzzy relational databases onto the web as fuzzy xml documents.
modeling of component-based adaptive distributed applications. a challenge in distributed system design is to cope with the dynamic nature of the execution environment. in this paper, we present an approach for modeling adaptation of component based distributed applications. the approach supports component-based design of different variants of the applications, and a framework for selecting proper variants based on the current state of the execution environment and the user preferences. xml is used as the specification language. transformation of the xml based design specifications to programming languages like java is also discussed.
a framework for data mining and kdd. the kdd process is a non-trivial, iterative, interactive and multi-step process, that requires the development of a unifying model. this model have to ensure an uniform description of data and patterns and the control of the manipulation of the data and patterns. thus, the model defines operations within the pattern and data, as well as transition operations between data and patterns.this paper proposes a framework consisting of a model view, a data view and a process view. it focuses on the model and data view. the model view contains a set of mining models, which contain all information of a data mining result, that are based on constraints. the proposed model algebra uses concepts of constraint databases as well as collective and parallel data mining. the whole process is supported by using operations between data and model view.
an initial investigation of test driven development in industry. test driven development (tdd) is a software development practice in which unit test cases are incrementally written prior to code implementation. in our research, we ran a set of structured experiments with 24 professional pair programmers. one group developed code using tdd while the other a waterfall-like approach. both groups developed a small java program. we found that the tdd developers produced higher quality code, which passed 18% more functional black box test cases. however, tdd developer pairs took 16% more time for development. a moderate correlation between time spent and the resulting quality was established upon analysis. it is conjectured that the resulting high quality of code written using the tdd practice may be due to the granularity of tdd, which may encourage more frequent and tighter verification and validation. lastly, the programmers which followed a waterfall-like process often did not write the required automated test cases after completing their code, which might be indicative of the tendency among practitioners toward inadequate testing. this observation supports that tdd has the potential of increasing the level of testing in the industry as testing as an integral part of code development.
combining state and model-based approaches for mobile agent load balancing. an approach for dynamic load balancing of mobile agents is described. we demonstrate this approach for a multi-agent system operating on an active digital library composed of multi-spectral images of the earth, as part of the synthetic aperture radar atlas (sara)[25]. in the proposed architecture specialized stationary agents are used to gather system state information and make decisions on the distribution of mobile agents among the servers. our approach is based on a combination of a state and model-based approaches to load balancing.
a scalable algorithm for high-quality clustering of web snippets. we consider the problem of partitioning, in a highly accurate and highly efficient way, a set of n documents lying in a metric space into k non-overlapping clusters. we augment the well-known furthest-point-first algorithm for k-center clustering in metric spaces with a filtering scheme based on the triangular inequality. we apply this algorithm to web snippet clustering, comparing it against strong baselines consisting of recent, fast variants of the classical k-means iterative algorithm. our main conclusion is that our method attains solutions of better or comparable accuracy, and does this within a fraction of the time required by the baselines. our algorithm is thus valuable when, as in web snippet clustering, either the real-time nature of the task or the large amount of data make the poorly scalable, traditional clustering methods unsuitable.
an information theoretic histogram for single dimensional selectivity estimation. we study the problem of one dimensional selectivity estimation in relational databases. we introduce a new type of histogram based on information theory. we compare our histogram against a large number of other techniques and on a wide array of datasets. we observe our histograms to have the overall best accuracy on the real datasets. we also observe that the accuracy ranking of all methods varies significantly across datasets. as such, we observe results not consistent with several conclusions drawn in past literature. thus, we believe a gap exists in the past accuracy characterization.
high performance xsl-fo rendering for variable data printing. high volume print jobs are getting more common due to the growing demand for personalized documents. in this context, variable data printing (vdp) has become a useful tool for marketers who need to customize messages for each customer in promotion materials or marketing campaigns. vdp allows the creation of documents based on a template with variable and static portions. the rendering engine must be capable of transforming the variable portion into a resulting composed format, or pdl (page description language) such as pdf, ps or svg. the amount of variable content in a document is dependant on the publication layout. in addition, the features and the amount of the content to be rendered may vary according to the data loaded from the database. therefore, the rendering process is invoked repeatedly and it can quickly become a bottleneck, especially in a production environment, compromising the entire document generation. in this scenario, high performance techniques appear to be an interesting alternative to increase the rendering phase throughput. this paper introduces a portable and scalable parallel solution for the apache's rendering tool fop (formatting objects processor) which is used to render variable content expressed in xsl-fo (extensible stylesheet language-formatting objects). xsl-fo is extracted from a print job expressed in ppml (personalized print markup language), which is, in turn, obtained by the merging variable data in a template. the vdp template is expressed using ppml/t (personalized print markup language template).
mining sequences with temporal annotations. in this paper we propose an extension of the sequence mining paradigm to (temporally-)annotated sequential patterns, where each transition in a sequential pattern is annotated with a typical transition time derived from the source data. then, we present a basic solution for the novel mining problem based on the combination of sequential pattern mining and clustering, and assess this solution on two realistic datasets, illustrating how potentially useful patterns of the new form are extracted.
challenges in the compilation of a domain specific language for dynamic programming. many combinatorial optimization problems in biosequence analysis are solved via dynamic programming. to increase programming productivity and program reliability, a domain specific language embedded in haskell has been suggested. we point out several shortcomings of this approach, and report on some challenges in the (ongoing) project of migrating this domain specific language from its host language to a directly compiled implementation. most of these challenges are domain specific optimizations, which not only improve significant constant factors of runtime and space requirements, but also affect asymptotic efficiency. we report on our solutions to some of these problems, and point out others that are still open.
dynamic service discovery and mediation in the insurance industry. businesses today are facing increasing pressure to innovate and deliver more value to their customers and partners. unfortunately, hard-wired, silo-based it applications and infrastructures are aging and inflexible, making it very difficult, expensive and time consuming to modify business practices and processes. service oriented architecture (soa) has addressed many of these issues, but still has major shortcoming with regard to data mediation and service selection.
multiclass text categorization for automated survey coding. survey coding is the task of assigning a symbolic code from a predefined set of such codes to the answer given in response to an open-ended question in a questionnaire (aka survey). we formulate the problem of automated survey coding as a text categorization problem, i.e. as the problem of learning, by means of supervised machine learning techniques, a model of the association between answers and codes from a training set of pre-coded answers, and applying the resulting model to the classification of new answers. in this paper we experiment with two different learning techniques, one based on na&iuml;millve bayesian classification and the other one based on multiclass support vector machines, and test the resulting framework on a corpus of social surveys. the results we have obtained significantly outperform the results achieved by previous automated survey coding approaches.
an efficient data structure for decision rules discovery. the increasing amount of information available is encouraging the search for efficient techniques to improve the data mining methods, especially those which consume great computational resources. we present a novel structure, called ees, which helps the data mining algorithms which generate decision rules to reduce the aforementioned cost. given that decision rules establish conditions for database attributes, ees stores the information in such a way that the search can be carried out by attributes instead of by examples. ees could be useful for any method which generates decision rules. moreover, it is of particular interest when the search for the solution involves a great many hypothetical solutions. thus, this structure is designed for speeding up the rule-evaluation process in methods based on evolutionary algorithms. the traditional structure, based on vectors of examples (in which the database is stored) is evaluated and compared with ees, including the costs for a stratified set of cases. finally, the experimental results demonstrate the quality of our proposal, reducing the computational cost by approximately 50%.
memory issues in frequent itemset mining. during the past decade, many algorithms have been proposed to solve the frequent itemset mining problem, i.e. find all sets of items that frequently occur together in a given database of transactions. although very efficient techniques have been presented, they still suffer from the same problem. that is, they are all inherently dependent on the amount of main memory available. moreover, if this amount is not enough, the presented techniques are simply not applicable anymore, or significantly need to pay in performance. in this paper, we give a rigorous comparison between current state of the art techniques and present a new and simple technique, based on sorting the transaction database, resulting in a sometimes more efficient algorithm for frequent itemset mining using less memory.
developing the extended enterprise with the fadee. in realizing business-to-business integration, much communication among persons with different backgrounds is needed. we affirm that enterprise architecture descriptions are an important part of the necessary communication in information systems development and maintenance. this article is about categorizing the models that describe business-to-business integration (b2bi) practices, and identifying the numerous ways b2bi issues could and should be described. the framework we propose is based on lessons learnt from proven architecture description frameworks. the zachman framework forms the basis of the framework for the architectural description of the extended enterprise (the fadee) presented in this paper. it changes the communication between cio and ceo, what results in more involvement of the cio in the strategy making process.
call me e-mail: arranging the keyboard with a permutation-coded genetic algorithm. keyboard design is a combinatorial problem of perennial interest to those who work with computers. an evolutionary algorithm can search a space of key arrangements for one that is easy to use. its genotypes represent candidate keyboards, and its fitness function measures the difficulty of typing a specified body of text. here, a genetic algorithm seeks to arrange the twenty-six letter and six punctuation marks (four of the latter in two pairs) on three rows of ten keys each. it encodes keyboards as permutations of key positions. its evaluation function considers the relative loads on the hands, consecutive keystrokes by one hand or finger, and the relative difficulties of using individual fingers as it simulates typing a block of text. in tests using a concatenated body of text and its three components (a collection of message logs, moby dick, and the king james bible), the ga consistently evolved keyboards with markedly better evaluations than either the qwerty or dvorak keyboards, though the ga's keyboards differed depending on the text it used in its evaluation function.
individual-based simulation of the clustering behaviour of epidermal growth factor receptors. this paper describes ongoing work on a project to simulate the behaviour of epidermal growth factor receptors. these are structures which can be found on the surface of cells in the body, which receive and process chemical signals concerned with cell growth. we describe the implementation of a program which simulates the stimulation and clustering behaviour of these structures, discuss how we scale up this simulation so that we can simulate a whole cell on a tractable timescale, and discuss ongoing work in which we are calibrating our simulation against results from experiments.
a branch and prune algorithm for the approximation of non-linear ae-solution sets. non-linear ae-solution sets are a special case of parametric systems of equations where universally quantified parameters appear first. they allow to model many practical situations. a new branch and prune algorithm dedicated to the approximation of non-linear ae-solution sets is proposed. it is based on a new generalized interval (intervals whose bounds are not constrained to be ordered) parametric hansen-sengupta operator. in spite of some restrictions on the form of the ae-solution set which can be approximated, it allows to solve problems which were before out of reach of previous numerical methods. some promising experimentations are presented.
managing duplicates in a web archive. crawlers harvest the web by iteratively downloading documents referenced by urls. it is frequent to find different urls that refer to the same document, leading crawlers to download duplicates. hence, web archives built through incremental crawls waste space storing these documents. in this paper, we study the existence of duplicates within a web archive and discuss strategies to eliminate them at storage level during the crawl. we present a storage system architecture that addresses the requirements of web archives and detail its implementation and evaluation. the system is now supporting an archive for the portuguese web replacing previous nfs-based storage servers. experimental results showed that the elimination of duplicates can improve storage throughput. the web storage system outperformed nfs based storage by 68% in read operations and by 50% in write operations.1
defining coordination in multi-agent systems within an agent oriented software engineering methodology. though interactions could be considered a key entity in the design and implementation of coordination in a multi-agent system (mas), interactions alone do not suffice to capture the coordination view of a mas. they are related with the evolution of agent mental states, through the execution of tasks, and determined by the context of the organization to which agents belong. therefore, a complete specification of interactions should be more that a mere definition of a set of ordered messages. in this paper we present a semiformal description of interactions as first-class entities, and the contribution of other components of a mas to this definition. also, we present its computational realization, as a tool to animate and monitor the execution of specifications.
meta-models for building multi-agent systems. this paper reports the experience of using meta-models for improving analysis and design activities in multi-agent system engineering. four meta-models describing different views of the mas such as organization view, agent, goals/tasks, and interactions are presented. meta-models are described in uml mof which make them compatible with current software engineering formalisms. engineers may instantiate the meta- models to produce the entities that may appear in concrete mas. these meta-models have been derived from several experimentations in mas, which are briefly described in the paper. engineering experience in using the meta-models for building mas applications is also reported in the conclusions.
architect-r: a system for reconfigurable robots design. an increasing interest in the design of mobile robots has been observed in recent years, which is mainly motivated by technological advances that may allow their application to consumer markets, in addition to industrial areas.although sophisticated techniques have been developed, choosing the appropriate hardware-software partitioning and programming robot functions are still very complex tasks.current approaches often involve the design and implementation of hardwired solutions, with the associated problems of a long development cycle and inflexibility.in this paper we present a framework called architect-r, which aims to design and program specialized hardware for robots based on fpgas. we also present the first results obtained using this framework.
a coarse-grain parallel genetic algorithm for finding ramsey numbers. ramsey theory studies the existence of highly regular patterns within a large system or a set of randomly selected points or numbers. the role of ramsey numbers is to quantify some of the general existential theorems in ramsey theory. attempting to find ramsey numbers has been an arduous task that is too often unfruitful. only a handful of specific numbers are known. genetic algorithms (ga), which are based on the idea of optimizing by simulating the natural processes of evolution, have proven successful in solving complex problems that are not easily solved through conventional methods. however, premature convergence is an inherent characteristic of traditional gas that makes them incapable of searching numerous points in a problem domain. parallel ga (pga) is an extension of the classical ga that takes advantage of a ga's inherent parallelism to improve its time performance and reduce the likelihood of premature convergence. a cgga (coarse-grain ga) maintains a number of independent populations and allows for the occasional interchange of individuals. in this manner, a cgga increases the diversity of search paths and helps to stop premature convergence to nonoptimal solutions. given this motivation, a tool was developed, called sipagar (simulated parallel genetic algorithm for finding ramsey numbers), that allows us to verify and validate the superior performance of cggas over traditional gas applied to the problem of improving the bounds of classical ramsey numbers. significant differences between the simulated cgga and traditional ga were observed in both the premature convergence rate and the quality of the results. this leads us to the conclusion that future cgga-based attempts to improve the bounds of ramsey numbers will probably be more promising than those based on traditional gas.
empirical evaluation of openccm for java-based distributed, real-time, and embedded systems. component technology can overcome many limitations of conventional object request brokers (orbs) in developing distributed, real-time, and embedded (dre) applications. component technology has particular advantages for building large-scale dre systems. the corba component model (ccm) enables the composition and reuse of software components and the configuration of key non-functional aspects of dre systems such as timing, fault-tolerance, and security. however, the ccm can introduce additional overhead to the runtime performance and code size of middleware. hence, the overhead for using the ccm needs to be evaluated to determine if the ccm can be effectively employed in the design of high-reliability dre applications. in this paper, we empirically evaluated the performance of openccm, a java-based implementation of the ccm standard, when configured with two java orbs: with zen, a real-time java orb, and with openorb, a desktop java orb. we measured throughput, latency, and jitter of method invocations for both orbs configured with and without openccm. we also measured the additional memory requirement introduced by the ccm implementation. we concluded that openccm adds some overhead to both java orbs, affecting openorb's performance more than zen's. more development of the ccm may be necessary to bring its advantages to high-performance dre systems.
controlling data movement in global computing applications. we present a programming notation aiming at protecting the secrecy of both host and agent data in global computing applications. the approach exploits annotations with sets of node addresses, called regions. a datum can be annotated with a region that specifies the network nodes that are allowed to interact with it. network nodes come eqipped with two region annotations specifying the nodes that can send data and spawn processes over them. the langauge semantics guarantees that computation proceeds according to these region constraints. to minimize the overhead of runtime checks, a static compilation phase is exploited. the proposed approach is largely independent of a specific programming language; however, to put it in concrete form, here we focus on its integration within the process language &mu;klaim. we prove that in compiled &mu;klaim nets, data can be manipulated only by authorized users. we also give a more local formulation of this property, where only a subnet is compiled. finally, we use our theory to model the secure behaviour of a unix-like multiuser system.
editorial message: special track on dependable and adaptive distributed systems. distributed systems and databases are at the core of the information society and increasingly pervade many aspects of our daily lives. while mobility and pervasiveness require support for systems that adapt themselves to changing environments, the middleware infrastructures become more and more heterogeneous and complex. in addition, we can see an increasing demand for dependability of such systems, taking into account the software as well as the surrounding environment. generally, adaptiveness can either satisfy a change in user requirements or seek to fulfill the same requirements in a changing system context and environment. in particular, adaptation is also a means to achieve dependability in a computing infrastructure with dynamically varying structure and properties. fault tolerance can consequently be seen as a special case, where the adaptation seeks to overcome an otherwise negative effect of a change in the computing infrastructure that can be classified as a fault. however, dependability can not only be achieved by fault tolerance, but also by other means like fault avoidance (e.g. through formal methods). therefore, future middleware needs to support adaptiveness and dependability while maintaining scalability and mastering complexity. still, software legacy must be integrated in a way, such that open and standardized interfaces support not only functional integration, but also a seamless integration of non-functional aspects. moreover, service-oriented architectures need coordination in order to achieve dependability and can further benefit from context-aware approaches.
interface utilization in the java development kit. interfaces as defined in the java programming language can enhance both decoupling and comprehensibility of large code bases. several researchers have pointed out this key role of interfaces in object-oriented programming, but so far only little insight as to how interfaces are actually used in practice has been made avilable. we fill this gap by applying a special metrics suite to one of the most popular pieces of software, the java development kit, and present interesting results.
a quantitative analysis of implicational paradoxes in classical mathematical logic. classical mathematical logic includes a lot of ''implicational paradoxes'' as its logic theorems. this paper uses the property of strong relevance as the criterion to identify implicational paradoxes in logical theorems of classical mathematical logic, and enumerates logical theorem schemata of classical mathematical logic that do not satisfy the strong relevance. this quantitative analysis shows that classical mathematical logic is by far not a suitable logical basis for automated forward deduction.
on considering an interval constraint solving algorithm as a free-steering nonlinear gauss-seidel procedure. we show that a classical interval constraint propagation algorithm enforcing box consistency may be interpreted as a free-steering nonlinear gauss-seidel procedure. this suggests that the choice of a transversal in the incidence matrix associated with the problem to solve is paramount to the efficiency of the algorithm. we present experimental evidences that it is indeed so, and we suggest an heuristics to compute good transversals. the improved interval constraint algorithm is compared with a classical one and with standard methods such as hansen-sengupta on some well-known benchmarks.
controlled propagation in continuous numerical constraint networks. local consistency is usually enforced on continuous constraints by decomposing them beforehand into so-called primitive constraints. it has long been observed that such a decomposition drastically slows down the computation of solutions. five years ago, benhamou et al. introduced an algorithm that avoids formally decomposing constraints, and whose efficiency is often on a par with state-of-the-art methods. it is shown here that this algorithm implements a strategy to enforce on a continuous constraint a consistency akin to directional bounds consistency as introduced by dechter and pearl for discrete problems. the actual impact of decomposition is also thoroughly analyzed by means of new experimental results.
automatic code generation for executing tiled nested loops onto parallel architectures. this paper presents a novel approach for the problem of generating tiled code for nested for-loops using a tiling transformation. tiling or supernode transformation has been widely used to improve locality in multi-level memory hierarchies as well as to efficiently execute loops onto non-uniform memory access architectures. however, automatic code generation for tiled loops can be a very complex compiler work due to non-rectangular tile shapes and iteration space bounds. our method considerably enhances previous work on rewriting tiled loops by considering parallelepiped tiles and arbitrary iteration space shapes. the complexity of code generation for tiling transformation is now reduced to the complexity of code generation for any linear transformation. experimental results which compare all so far presented approaches, show that the proposed approach for generating tiled code is significantly accelerated.
automatic parallel code generation for tiled nested loops. this paper presents an overview of our work, concerning a complete end-to-end framework for automatically generating message passing parallel code for tiled nested for-loops. it considers general parallelepiped tiling transformations and general convex iteration spaces. we address all problems regarding both the generation of sequential tiled code and its parallelization. we have implemented our techniques in a tool which automatically generates mpi parallel code and conducted several series of experiments, concerning the compilation time of our tool, the efficiency of the generated code and the speedup attained on a cluster of pcs. apart from confirming the value of our techniques, our experimental results show the merit of general parallelepiped tiling transformations and verify previous theoretical work on scheduling-optimal tile shapes.
double- and triple-step incremental linear interpolation. incremental linear interpolation determines the set of n+1 equidistant points on an interval [a,b] where all variables involved (n, a, b, and the set of equidistant points) are integers and n
pseudozero set of interval polynomials. interval polynomials are useful to describe perturbed polynomials. we present a graphical tool to describe how perturbations of the polynomial coefficients affect its zeros without using interval arithmetic nor matrix representation. this tool implements real pseudozero set that differ from the well known complex pseudozero set restricting perturbations to be real and applied to real polynomials. we introduce a computable formula for this real pseudozero set and compare complex and real pseudozero sets. we propose a graphical matlab interface to draw zeros of such interval polynomials.
improving the compensated horner scheme with a fused multiply and add. several different techniques and softwares intend to improve the accuracy of results computed in a fixed finite precision. here we focus on a method to improve the accuracy of the polynomial evaluation. it is well known that the use of the fused multiply and add operation available on some microprocessors like intel itanium improves slightly the accuracy of the horner scheme. in this paper, we propose an accurate compensated horner scheme specially designed to take advantage of the fused multiply and add. we prove that the computed result is as accurate as if computed in twice the working precision. the algorithm we present is fast since it only requires well optimizable floating point operations, performed in the same working precision as the given data.
inner approximation of distance constraints with existential quantification of parameters. this paper presents and compares two methods for checking if a box is included inside the solution set of an equality constraint with existential quantification of its parameters. we focus on distance constraints, where each existentially quantified parameter has only one occurrence, because of their usefulness and their simplicity. the first method relies on a specific quantifier elimination based on geometric considerations whereas the second method relies on computations with generalized intervals (interval whose bounds are not constrained to be ordered). we show that on two dimensions problems, the two methods yield equivalent results. however, when dealing with higher dimensions, generalized intervals are more efficient.
parallel hypothesis driven video content analysis. extraction of features from images, followed by pattern classification, is a promising approach to automatic video analysis. however, a parallel processing environment is typically required for real-time performance. still, single-cpu bayesian network systems for hypothesis driven feature extraction have been able to classify image content real-time --- the expected information value and processing cost of features are measured, and only efficient features are extracted. the goal in this paper is to combine the processing benefits of parallel and hypothesis driven approaches. we use dynamic bayesian networks to specify video analysis tasks and the particle filter (pf) for approximate inference, i.e., feature selection and classification. the inference accuracy of any given pf is determined by the number of particles it maintains. to increase the number of particles maintained without reducing the processing rate, we apply multiple pfs distributed in a lan, and a pooling system to coordinate their output. our resulting multi-pf architecture supports three video frame processing phases: a parallelized feature selection phase, followed by a parallelized feature extraction- and classification phase. unfortunately, we observe a loss of inference accuracy when splitting a single pf into multiple independent pfs. to reduce this loss, we let the pooled pfs exchange particles across the lan. an object tracking simulation demonstrates the ability of our architecture to select efficient features as well as the effectiveness of our particle exchange scheme --- we observe a significant increase in inference accuracy compared to the tested non-parallel pf.
secs: scalable edge-computing services. we present the architecture of a scalable and dynamic intermediary infrastructure for developing and deploying advanced edge computing services, by using a cluster of heterogeneous machines. our main goal is to address the challenges of the next-generation internet services: scalability, high availability, fault-tolerance and robustness. moreover, secs offers an easy, "on-the-fly" and per-user configuration of services. the architecture is based on ibm's web based intermediaries (wbi) [8, 9].
on designing a low-power garbage collector for java embedded devices: a case study. this paper presents an energy consumption comparison between two well-known garbage collection algorithms---mark-sweep-compact and reference counting. our goal is to evaluate the suitability of reference counting as an algorithm for memory-constrained java embedded devices. we hypothesize that reference counting would be suitable because it has higher data locality, which should reduce the number of data-cache misses, and so reduce energy consumption. however, this benefit could be offset by the extra instructions required for each reference update, a basic requirement of reference counting. to test our hypothesis, we implement, into sun's kvm, a hybrid scheme that combines a standard mark-sweep-compact collector and limited-field reference counting. our hybrid scheme is then compared against the default kvm with only mark-sweep-compact. we investigate several performance metrics that contribute to the performance of the system, including number of garbage collections, instructions, level-1 instruction and data cache misses, and total energy consumption.based on our observations, the hybrid scheme yields three important benefits: (a) the hybrid scheme reclaims most memory quickly, resulting in less mark-sweep garbage collection invocations, (b) the reduction in garbage collection improves cache locality and reduces the number of main memory accesses, and (c) the reduction in memory accesses ultimately results in lower energy consumption, since a memory access can be energy-intensive. our results confirm our hypothesis, with the hybrid scheme requiring up to 59% less energy than the default kvm.
automatic generation of application-specific systems based on a micro-programmed java core. this paper describes a co-design based approach for automatic generation of application specific systems, suitable for fpga-centric embedded applications. the approach augments a processor core with hardware accelerators extracted automatically from a high-level specification (java) of the application, to obtain a custom system, optimised for the target application. we advocate herein the use of a microprogrammed core as the basis for system generation in order to hide the hardware access operations in the micro-code, while conserving the core data-path (and clock frequency). to prove the feasibility of our approach, we also present an implementation based on a modified version of the java optimized processor soft core on a xilinx virtex-ii fpga.
editorial message: special track on software engineering: methods, practices, and tools. for the third time in a sequence the annual acm sac symposium is hosting this software engineering track. a few changes have taken place since last year: from the original se team only stefan gruner is continuing to organise this track whilst alessandra cavarra and sung shin have come in as new members of the team. also the tracks original subtitle, "applications, practices and tools", has been modified to "methods, practices and tools" in order to emphasise our focus on sound solutions.
tool support for plagiarism detection in text documents. we propose a software tool that supports the detection of plagiarism. the application domain of the tool are those cases in which a stylometric approach seems appears viable. the tool is language-sensitive. it takes as input two sufficiently long pieces of english text under the hypothesis that they stem from different authors, and it raises a plagiarism warning in case that significant stylistic similarities in the two texts can be found.
editorial message. for the fourth time in a sequence the annual acm-sac symposium is hosting this software engineering track. a few changes have taken place since last year: from last year's se-track team only sung shin and stefan gruner are continuing to organise this track and, at the occasion of the 21st sac symposium, the track's previous subtitle "methods, practices and tools" was modified to "sound solutions for the 21st century". moreover: for the very first time this track is not only supported by the acm via the sac symposium but also endorsed by two further software engineering societies, namely formal methods europe (fme) and the european association of software science and technology (easst).
improving courseware quality through life-cycle encompassing quality assurance. the quality of courseware development is affected by four factors: content and instructional issues; managment; technical and graphical issues; and concerns of the customer. in this paper we describe intview, a courseware development method that integrates these four factors throughout the whole development life-cycle. by combining existing courseware quality assurance methodologies with software engineering techniques such as inspections and tests the interests of the participating roles are balanced. both the intview methodology and the quality assurance techniques are described and the results of some preliminary case studies are reported.
a formal framework to generate xpdl specifications from uml activity diagrams. the xml process definition language (xpdl) is a standardized language allowing process definitions interchange between a variety of tools ranging from workflow management systems to modeling and simulation tools. on the other hand, uml activity diagrams offer a convenient notation to depict synthetic and intuitive views of systems that facilitate stakeholder communication. however, there is currently no tool able to animate activity diagrams using workflow management systems. moreover, despite standardization efforts, diagram interchange across different modeling tools remains an issue. hence, transforming uml activity diagrams into xpdl specifications would preserve stakeholder communication while enabling animation tool support. this paper presents a formal and optimal transformation of uml activity diagrams into xpdl specifications. this mapping is described through a set of formal translation rules defined from the uml activity metamodel to the xpdl metamodel. we demonstrate that the defined mapping process preserves some structural properties specified on the translated uml activity diagram.
multilure active contours. this paper presents a variation of the classic algorithm of active contours in order to improve the visualization of 3d reconstruction of anatomical structures in medicine. this 3d reconstructions are made from the obtained contours. this variation of active contour enables a better behavior of them.other authors have already used snakes (active contours) for segmenting shapes in medical images. but they usually fail in accurately adjust to the desired contour.the proposed variation introduce a new kind of energy in the classical formula of active contours. this new energy is based in the computation of distance to several supervised lures that attract the snake points. once the lures are selected, the active contours work in a fully automated way. this new variation of active contours have been tested on ct medical images to segment contours of different bone structures. the results show that the proposed active contour is superior in results to the classical method. we have used a multiple criteria decision making framework for obtaining the final conclusions of this survey.the new variation proposed for active contours works better for detecting vertebrae contours in ct images. in addition, a new energy and use of lures for active contours have been introduced.
design and implementation of a real-time notification service within the context of embedded orb and the can bus. many distributed real-time and embedded (dre) applications require a scalable event-driven communication model that decouples suppliers from consumers and simultaneously supports advanced quality of service (qos) properties. this article focuses on the design of such a service complying with the omg notification service standard. it is optimized for the can bus, a widely used interconnect, where real-time characteristics are a requirement. a new protocol for the efficient distribution of events in a can-based distributed control system is presented, a protocol which is tailored to the can bus and produces very low overhead by utilizing can-specific features.
mocha-pi, an exogenous coordination calculus based on mobile channels. in this paper we present mocha-&pi;, an exogenous coordination calculus that is based on mobile channels. a mobile channel is a coordination primitive that allows anonymous point-to-point communication between processes. our calculus is an extension of the well-known &pi;-calculus. the novelty of mocha-&pi; is that its channels are a special kind of process that allow other processes to communicate with each other and impose exogenous coordination through user defined channel types. also new, is the fact that in our calculus channels are viewed as resources. processes must compete with each other in order to gain access to a particular channel. this makes the calculus more in line with existing systems. an immediate application of this calculus is the modeling of the mocha middleware, a distributed system that coordinates components using mobile channels.
mode-directed preferences for logic programs. preference logic programming (plp) is an extension of constraint logic programming for declaratively specifying problems requiring optimization or comparison and selection among alternative solutions to a query. plp essentially separates the programming of a problem itself from the criteria specification of its solution selection. in this paper we provide a syntax for plp based upon mode-directed preferences and a semantics based upon herbrand models and fixed-point theory. our method uses mode declarations to designate certain predicates as optimization predicates, and uses preference rules for stating the criteria for determining their optimal solutions. this paper also presents an elegant and easy method of executing preference logic programs in terms of tabled prolog. automatic transformation is applied to embed the preferences into the problem specification for efficient evaluation. we show that the procedural semantics of a preference logic program is equivalent to its declarative semantics.
on the use of spectral filtering for privacy preserving data mining. randomization has been a primary tool to hide sensitive private information during privacy preserving data mining. the previous work based on spectral filtering, show the noise may be separated from the perturbed data under some conditions and as a result privacy can be seriously compromised. in this paper, we explicitly assess the effects of perturbation on the accuracy of the estimated value and give the explicit relation on how the estimation error varies with perturbation. in particular, we derive one upper bound for the frobenius norm of reconstruction error. this upper bound may be exploited by attackers to determine how close their estimates are from the original data using spectral filtering technique, which imposes a serious threat of privacy breaches.
fingerprinting relational databases. in this paper, we propose a fingerprinting solution to protect valuable numeric relational data from illegal duplications and redistributions. we introduce a twice-embedding scheme. in the first embedding process, we embed a unique fingerprint to identify each recipient to whom the relational data is distributed. the embedding process is controlled by a secret key. meanwhile, the fingerprint can be detected using the same secret key to prove ownership at a numerical confidence level. the second embedding process is designed for verifying the extracted fingerprint and giving a numerical confidence level. thus, once a suspect copy is found, numerical confidence level can be provided both to identify the owner and the illegal distributor. the experiment shows that our solution is effective and robust to various attacks.
experiments with una for solving linear constraints in real variables. linear constraints arise in formulation of several computationally challenging problems such as weather modeling, underground water modeling, air pollution modeling etc. the constraints may correspond to multiple observations that place upper or lower bounds on linear combinations of variables. computing a feasible solution or solving these inequalities in least squares sense is a fundamental problem in many applications.in this paper, we present a strikingly simple numerical algorithm called una (unified numerical approach) that computes a feasible solution of linear inequalities or solves them in a least squares sense in case they are inconsistent. we compare the performance of una with bramley-winnicka algorithm, which is the best known algorithm to solve linear inequalities in a least squares sense. we also give experimental performance comparison of una with commercial linear programming based packages xa and cplex. our experiments show that una algorithm is faster than bramley-winnicka algorithm for solving large constraint sets in least squares sense. our experiments also show that for large constraint sets although cplex performs better than una, una performs far better than xa. in addition, the una algorithm is so simple that its implementation in c programming language is only 170 lines of code and its implementation using matlab is 80 lines of matlab script. our results show that in-spite of its simplicity, it is a powerful algorithm for solving linear inequalities in real variables.
modelling organisational practice in user requirements. modelling of organisational practice is an important yet notoriously difficult aspect of requirements engineering. this paper presents an approach which utilises "lightweight" ethnographic analyses in modelling the knowledge that exists in an organisation, together with how and where knowledge is communicated amongst organisational members. we view organisational practice in terms of the tasks that the organisation carries out, modelling and analysing what knowledge is required to perform these tasks.
dynamic on-demand updating of data in real-time database systems. the amount of data handled by real-time and embedded applications is increasing. also, applications normally have constraints with respect to freshness and timeliness of the data they use, i.e., results must be produced within a dead-line using accurate data. this calls for data-centric approaches when designing embedded systems, where data and its meta-information (temporal correctness requirements etc) are stored centrally. the focus of this paper is on maintaining data freshness in soft real-time embedded systems and the target application is vehicular systems. the contributions of this paper are three-fold. we (i) define a specific notion of data freshness by adopting data similarity in the value-domain of data items using data validity bounds that express required accuracy of data, (ii) present a scheme for managing updates in response to changes in the data items; and (iii) present a new on-demand scheduling algorithm, on-demand depth-first traversal denoted oddft, for enforcing data freshness by scheduling and executing update transactions. performance experiments show that, by using our updating scheme and introduced notion of data freshness in the value-domain, computational work imposed by updates is reduced for both the new oddft and well-established on-demand algorithms. moreover, oddft improves the consistency of produced results compared to well-established algorithms.
a semantic model for safe protocol interaction. most communication subsystems support modular and reconfigurable communication protocols based on the lego block model. in this model, complex protocols are built as collections of simpler protocols. however, protocol behavior is often expressed via informal descriptions and few work has been done to develop the underlying semantics that enables us to model and reason about protocol interactions. without it, it is very difficult to identify critical properties that must be met for correct operation. in this paper we present a communication framework based on a semantic model of distributed object reflection and we illustrate how this model can be used to formalize and reason about interactions between communication protocols. we evaluate the overhead and feasibility of our approach by developing an abstract executable specification of the communication framework in maude [3] and a maude api to systematically translate maude code into java. this gives us two versions of our model to play with: an abstract one for analysis and a concrete one for real-world applications.
two-phase clustering strategy for gene expression data sets. in the context of genome research, the method of gene expression analysis has been used for several years. related microarray experiments are conducted all over the world, and consequently, a vast amount of microarray data sets are produced. having access to this variety of repositories, researchers would like to incorporate this data in their analyses to increase the statistical significance of their results. in this paper, we present a new two-phase clustering strategy which is based on the combination of local clustering results to obtain a global clustering. the advantage of such a technique is that each microarray data set can be normalized and clustered separately. the set of different relevant local clustering results is then used to calculate the global clustering result. furthermore, we present an approach based on technical as well as biological quality measures to determine weighting factors for quantifying the local results proportion within the global result. the better the attested quality of the local results, the stronger their impact on the global result.
sequence modelling for sentence classification in a legal summarisation system. we describe a set of experiments using a wide range of machine learning techniques for the task of predicting the rhetorical status of sentences. the research is part of a text summarisation project for the legal domain for which we use a new corpus of judgments of the uk house of lords. we present experimental results for classification according to a rhetorical scheme indicating a sentence's contribution to the overall argumentative structure of the legal judgments using four learning algorithms from the weka package (c4.5, na&iuml;ve bayes, winnow and svms). we also report results using maximum entropy models both in a standard classification framework and in a sequence labelling framework. the svm classifier and the maximum entropy sequence tagger yield the most promising results.
reusable subsystems: domain-based approach. the goal of achieving a generic architecture for reusable software subsystems remains elusive. this work proposes a model, based on domain engineering, to support improved technique for designing reusable subsystems. the model is based on the concepts of "atomic domain" and the "wrapper" of an atomic domain. an atomic domain signifies a reusable subsystem, and it exhibits specific properties that serve as a basis for building reusable subsystems. the wrapper supports software reuse and management through a number of interface mechanisms, including taxonomy, application programmer interface, manager, communication, and control. implementations of illustrative atomic domains are provided.
video summarization by k-medoid clustering. in this paper, we propose a video summarization algorithm by multiple extractions of key frames in each shot. this algorithm is based on the k-medoid clustering algorithms to find the best representative frame for each video shot. this algorithm, which is applicable to all types of descriptors, consists of extracting key frames by similarity clustering according to the given index. in our proposal, the distance between frames is calculated using a fast full search block matching algorithm based on the frequency domain. the proposed approach is computationally tractable and robust with respect to sudden changes in mean intensity within a shot. additionally, this approach produces different key frames even in the presence of large motion. the experiments results show that our algorithm extracts multiple representatives frames in each video shot without visual redundancy, and thus it is an effective tool for video indexing and retrieval.
translating the object constraint language into the java modelling language. the object constraint language ocl is a textual specification language that could be used for constraining the modelling elements that occur in uml diagrams. typical constraints include class invariants and preconditions and postconditions of operations. the java modelling language (jml) is a behavioural interface specification language designed for specifying java classes and interfaces. this paper defines a translation of ocl expressions and constraints into the java modelling language. the objective of this translation is to be able to map uml object-oriented designs with ocl constraints to java classes and interfaces annotated with jml specifications, and to carry out logical reasoning about such classes and interfaces using jml tools which include a run time assertion checker and an interactive prover based on pvs.
rule-based word clustering for document metadata extraction. text classification is still an important problem for unlabeled text; citeseer, a computer science document search engine, uses automatic text classification methods for document indexing. text classification uses a document's original text words as the primary feature representation. however, such representation usually comes with high dimensionality and feature sparseness. word clustering is an effective approach to reduce feature dimensionality and feature sparseness, and improve text classification performance. this paper introduces a domain rule-based word clustering method for cluster feature representation. the clusters are formed from various domain databases and the word orthographic properties. besides significant dimensionality reduction, such cluster feature representations show a 6.6% absolute improvement on average on classification performance of document header lines and a 8.4% absolute improvement on the overall accuracy of bibliographic fields extraction, in contrast to feature representation just based on the original text words. our word clustering even outperforms the distributional word clustering in the context of document metadata extraction.
a hierarchical naive bayes mixture model for name disambiguation in author citations. because of name variations, an author may have multiple names and multiple authors may share the same name. such name ambiguity affects the performance of document retrieval, web search, database integration, and may cause improper attribution to authors. this paper presents a hierarchical naive bayes mixture model, an unsupervised learning approach, for name disambiguation in author citations. this method partitions a collection of citations1 into clusters, with each cluster containing only citations authored by the same author, thus disambiguating authorship in citations to induce author name identities. three types of citation features are used: co-author names, paper title words, and journal or proceeding title words. the approach is illustrated with 16 name datasets that are constructed based on the publication lists collected from author homepages and dblp computer science bibliography.
aspect-specification based on structural type information. aspects developed in aspect-oriented systems often need to hook onto multiple objects that share common structural characteristics - such as attributes and operations. in strongly-typed aspect-oriented systems like aspectj these objects need to be of common type so that pointcuts may designate them and pieces of advice may interact with them. such type-systems are typically based on nominal types, therefore, aspects cannot interact with objects according to their structural information in a common way. this paper argues that specifying aspects based on a nominal type system is not sufficient and shows that aspect-specifications based on structural characteristics overcome this problem. a corresponding extension of the nominal type systems is proposed and illustrated by means of structural types and compound types.
location management of data items in mobile ad hoc networks. in this paper, we address techniques to manage locations of data items or replicas in mobile ad hoc networks and efficiently forward access requests to the locations. in order to manage locations of data items efficiently, a key issues is predicting the locations of data items that dynamically change. to predict the locations of data items, we use the information on replica allocation at every relocation time and the logs of past data accesses.
iterative querying in web-based database applications. web applications are increasingly relying on databases. the traditional method offered by most web sites of submitting a query across the internet and getting a response from a server packed in a hyper text markup language page is no longer satisfying [1][3][4][5]. this is due to the result set: it is often too large or empty. this forces the user to try and guess which constraints should be relaxed or tightened in order to obtain the desired result set. and so, the user goes through several submit/response cycles. web applications that require this sort of interactive exploration of databases need to use a model that is different from the submit/respond model described above. in this work, we propose an iterative querying model that integrates querying with result browsing.
editorial message: special track on database theory, technology, and applications. the world nowadays revolves around dealing with data presented in various formats. so it is inevitable that researchers focus their work on advancing the state of managing information. from here, the importance of database technology ranks amongst the hottest areas of research. this year the track has received many papers covering different areas of databases.
editorial message: special track on database theory, technology, and applications. the world nowadays revolves around dealing with data presented in various formats. so it is inevitable that researchers focus their work on advancing the state of managing information. from here, the importance of database technology ranks amongst the hottest areas of research. this year the track has received many papers covering different areas of databases.
a spanning tree-based genetic algorithm for some instances of the rectilinear steiner problem with obstacles. given sets of points and obstacles in the plane, the rectilinear steiner problem with obstacles seeks to connect the points with a rectilinear steiner tree---a tree made up of vertical and horizontal line segments---that avoids the obstacles and has minimum total length. we consider only rectangular obstacles and further restrict the problem by requiring that it be possible to connect every point to the tree via exactly one vertical and one horizontal segment. rectilinear steiner trees that conform to this restriction can be represented by spanning trees augmented to specify the rectilinear segments. a genetic algorithm that uses a spanning-tree-based coding of rectilinear steiner trees outperforms a greedy heuristic on 45 instances of the problem, of up to 469 points and 325 obstacles. however, the coding cannot represent arbitrary rectilinear steiner trees, so it cannot address the unrestricted case, and in the case considered here, it leaves some potentially shorter trees unexamined.
building knowledge discovery into a geo-spatial decision support system. the emergence of remote sensing, scientific simulation, telescope scanning, and other survey technologies has dramatically enhanced our capabilities to collect spatio-temporal data. however, the explosive growth in data makes the management, analysis, and use of data difficult and expensive. in decision support applications with spatio-temporal data, it is important to study the temporal relationships of the parameters that influence the decision. because multiple spatio-temporal data sets contain volumes of data, and often there is a delay between the occurrence of an event and its influence on the dependent variables, finding interesting patterns can be difficult.this paper presents a layered architecture for a distributed gdss that uses temporal rule discovery to aid the decision-making process. data mining algorithms are used to identify temporal relationships between multiple spatio-temporal data sets where time lags may exist between the related events. these algorithms allow the user to specify target events, to prune rules that are not of interest to the current decision-making problem. a geo-spatial decision support system for drought risk management is used to demonstrate the effectiveness of building knowledge discovery into a gdss.
route profiling: putting context to work. intelligent transportation systems are characterised by a requirement for detailed information on extensive transport networks. this information is typically gathered from sensors deployed throughout the network and is used for management and maintenance operations.in this paper we present the design and prototype implementation of a context-aware route profiling application intended for use by road management authorities in the republic of ireland. our design allows data from a variety of sources to be combined to generate detailed information on traffic flow and journey times along the national road network. this information can be tagged with relevant context data reflecting the conditions under which sensor data was collected. the set of relevant contextual information includes details on temporal, spatial, weather and road usage pattern contexts.the prototype implementation relies on gps data from a fleet of probe vehicles. an evaluation of this prototype is presented along with a discussion on the benefits of using context-aware computing techniques in a real world scenario.
a hypothesis driven approach to condition specific transcription factor binding site characterization in s.c.. we demonstrate a computational process by which transcription factor binding sites can be elucidated using genome-wide expression and binding profiles. the profiles direct us to the intergenic locations likely to contain the promoter regions for a given factor. these sequences are multiply and locally aligned to give an anchor motif from which further characterization can take place. we present bases for and assumptions about the variability within these motifs which give rise to potentially more accurate motifs, capture complex binding sites built upon the basis motif, and eliminate the constraints of the currently employed promoter searching protocols. we also present a measure of motif quality based on the occurrence of the putative motifs in regions observed to contain the binding sites. the assumptions, motif generation, quality assessment and comparison allow the user as much control as their a priori knowledge allows.
a diagnostic system based on a multi-decision approximate rules model. modified rough sets (mrs)-based diagnostic systems eliminated many of the limitations of rough sets (rs)-based, statistical-based, and decision tree-based systems and because of that, they have a better performance. in contrast with the other systems, mrs-based diagnostic systems have potential to handle multi-decision approximate (mda) rules. in this paper, we (1) develop a diagnostic model based on mda rules and (2) evaluate the classification power of the model.
identifying and testing of signatures for non-volatile biomolecules using tandem mass spectra. identification of volatile and semi-volatile molecules using traditional electron ionization mass spectrometry has been successful. the major contributor to this success is the reproduceability of the mass spectra, which allow identification of components based on comparison of fragmentation patterns within very large databases. however, this approach is not useful for the identification of typical nonvolatile biomolecules. tandem mass spectrometry with collision induced dissociation (cid) has the potential to provide structure-specific fragmentation from non-volatile biomolecules.the recognition of these molecules based on cid is not an easy task, since the spectra generated for a given molecule are not as reproducible as in traditional electron ionization mass spectrometry. also, the rules governing the formation of cid produced ions are not completely understood.in this study we investigate the use of the kohonen self-organized mapping (som) neural network to generate and test signatures (fragmentation patterns) for a given set of non-volatile biomolecules using spectra generated by tandem mass spectrometry with cid. the signatures then may be used as a discriminator for identifying unknown non-volatile biomolecules.
a neural network for speedy trials. in recent years, the case loads of judges have increased, while speedy trial laws place a time limit between the defendant's arrest and trial dates. because of this time constraint, it seems that for minor cases, judges pass sentences based on a set of certain factors (patterns) not based on the individual merits of each case. patterns may be learned by a neural network. in this paper, we investigate the credibility of the neural network approach as a viable tool in the sentencing process and we show its superiority over the id3 approach.
simplified access to structured databases by adapting keyword search and database selection. this paper presents a tool that enables non-technical (naive) end-users to use free-form queries in exploring distributed relational databases with simple and direct technique, in a fashion similar to using search engines to search text files on the web. this allows web designers and database developers to publish their databases for web browsers exploring. the proposed approach can be used for both internet and intranet application areas. our approach depends on identifying first databases that are most likely to provide useful results to the raised query, and then search only the identified databases. in our work, we developed and extended an estimation technique to assess the usefulness measure of each database. our technique has been borrowed from the similar techniques used for information retrieval (ir), mainly for text and document databases; it supports working smoothly with the structured information stored in relational databases. such a usefulness measure enables nave users to make decisions about databases to search and in what order.
modeling the workflow of prescription writing. computerizing the delivery of prescription medication, particularly in hospitals, has had many recent success stories. while the safeguards that computers can provide in preventing the incorrect administration of medications cannot be denied, little attention has been paid to the requirements engineering process in workflow automation. this paper discusses some of the techniques of workflow modeling that hold promise for medical informatics. this paper demonstrates that clinical workflows can be modeled using existing modeling tools.
grid-based management of biomedical data using an xml-based distributed data management system. this paper presents the application of a generic, xml-based distributed data management system for grid-enabled management and integration of biomedical data, including image, molecular, and outcome data. we discuss the use of this system in three inter-related application scenarios: management of large-scale image data, access to data from internet-based bioinformatic data repositories, and integrating clinical data stored in an enterprise information warehouse into translational research.
ontology and rule based retrieval of sound objects in augmented audio reality system for museum visitors. ec(h)o is an "augmented reality interface" utilizing spatialized soundscapes and a semantic web approach to information. the initial prototype is designed for a natural history and science museum. the platform is designed to create a museum experience that consists of a physical installation and an interactive virtual layer of three-dimensional soundscapes that are physically mapped to the museum displays. the source for the audio data is digital sound objects. the digital objects originate in a network of object repositories that connect digital content from one museum with other museums collections. the interface enables people to interact with the system by movement and object manipulation-based gestures without the direct use of a computer device. the focus of this paper is the retrieval mechanism for the sound objects for the museum visitor. the retrieval mechanism is built on the user model and conceptual descriptions of the sound object and museum artifacts in the form of ontologies for sound and psychoacoustics, topic ontology and conceptual reference model for museum information. the retrieval criteria are represented as inference rules that represent knowledge from psychoacoustics, cognitive domain and composition aspects of interaction. the system will be demonstrated in exhibition space in nature museum in ottawa in january 2003.
the edusource communication language: implementing open network for learning repositories and services. interoperability is one of the main issues in creating a networked system of repositories the approaches range from simply forcing one metadata standard on all participating repositories to highly sophisticated semantic web based architectures with full semantic mapping capabilities between different schemas. the edusource project in its holistic approach to building a network of learning object repositories in canada is implementing an open network for learning services. its openness is supported by an edusource communication protocol (ecl) which closely implements the ims digital repository interoperability (dri) specification and architecture, and by connection middleware that enables any service providers to join the network. edusource is open to external initiatives as it explicitly supports an extensible bridging mechanism between edusource and other major initiatives. this paper focuses on the design of ecl as an implementation of ims dri and supporting infrastructure and middleware. we also present two applications used in evaluating our approach: a gateway for connecting between edusource and the nsdl initiative, and a federated search connecting edusource, edna and smete.
sesam: searching supported by analysis of metadata. this paper presents a novel approach for database searching where the user is assisted in locating relevant objects in query results. this is made possible by an active user interface which asks the user dynamically generated questions based on collected information of the properties of the objects in the result. the answers to these questions are used to retain only objects with the indicated properties, thereby improving precision. sesam, a world wide web-based prototype based on this approach, is presented. it has been successfully tested using a large, real-life database.
terracost: a versatile and scalable approach to computing least-cost-path surfaces for massive grid-based terrains. this paper addresses the problem of computing least-cost-path surfaces for massive grid-based terrains. our approach follows a modular design, enabling the algorithm to make efficient use of memory, disk, and grid computing environments. we have implemented the algorithm in the context of the grass open source gis system and---using our cluster management tool---in a distributed environment. we report experimental results demonstrating that the algorithm is not only of theoretical and conceptual interest but also performs well in practice. our implementation outperforms standard solutions as dataset size increases relative to available memory and our distributed solver obtains near-linear speedup when preprocessing large terrains for multiple queries.
service-oriented grid computation for large-scale parameter estimation in complex environmental modeling. complex environmental modeling often involves a large number of unknown physical and ecological parameters. parameter estimation is one of the most difficult steps in many modeling activities. in this paper we present a service-oriented framework, named ggpe-g (grid-enabled global optimization for general parameter estimation), for efficient parameter estimation in heterogeneous, distributed systems. being presented as services, the optimization algorithms, the physical and ecological process models and clients can interact with each other by xml message interactions. the proposed approach supports a generic parameter estimation procedure and can be easily applied to different modeling environment. in this paper, we explain the design, architecture, and implementation of ggpe-g in details. we also apply ggpe-g to a complex soil-water-atmosphere-plant modeling system to demonstrate its utility and efficiency.
to infinity and beyond or, avoiding the infinite in security protocol analysis. we investigate conditions under which an infinite set of atomic messages can be replaced with one or two values without affecting the correctness of a security protocol. the work is conducted using the strand spaces formalism, but the results apply to all protocol analysis techniques, and should be of particular value to those using model checking.the implications of the central result are discussed.
virtual namespace functions: an alternative to virtual member functions in c++ and advice in aspectc++. virtual namespace functions (vnfs) are introduced as c++ functions defined at global or namespace scope which can be redefined similar to virtual member functions. even though this is a relatively simple concept, hardly more complex than ordinary c functions, it is shown that vnfs subsume object-oriented single, multiple, and predicate-based method dispatch as well as aspect-oriented before, after, and around advice. their implementation by means of a "lazy" precompiler for c++ is briefly described.
wavelet density estimators over data streams. density estimation is a building block of many data analysis techniques. a recently examined approach based on wavelets promises to be superior to traditional density estimation techniques. for possibly infinite data streams, however, this approach is not feasible due to the limited resources, e.g. memory. in this paper, we propose a new technique for computing wavelet density estimators over data streams that only requires a fixed amount of memory. our estimators are updated in an online manner such that a continuous analysis of data streams is supported during runtime.
the overhead model of word-level and page-level incremental checkpointing. generally, word-level granularity for incremental checkpointing may reduce the checkpoint file size, and hence get better the performance. however, word-level granularity may not always be more efficient than page-level granularity, because word-level granularity may sometimes increase the checkpointing overhead for finding the differences between two checkpoints and for writing the address of the modified word to stable storage. in this paper, we make the overhead model and find factors which produce an effect on the over-head. we also show that the model and the factors are fairly reasonable via experimental results from linux kernel-level incremental checkpointing facility.
space-efficient page-level incremental checkpointing. incremental checkpointing, which is intended to minimize checkpointing overhead, saves only the modified pages of a process. however, the cumulative size of incremental checkpoints increases at a steady rate over time because many updated values may be saved for the same page. in this paper, we present a comprehensive overview of pickpt, which is a page-level incremental checkpointing facility. pickpt provides space-efficient techniques for minimizing the use of disk space. for our experiments, the results show that the use of disk space of pickpt was significantly reduced compared with existing incremental checkpointing.
trust-enhanced visibility for personalized document recommendations. documents are recommended by computer-based systems normally according to their prominence in the document reference network. based on the requirements identified in a concrete use case for recommending scientific publications, the paper claims that merely measuring prominence is insufficient for high quality recommendations. we propose to use information from a trust network in addition to the document network in order to improve and to personalize recommendations. a trust-enhanced visibility measure integrates trust information and the classical reference based measures. a simulation study applies the new visibility measure to the presented use case.
computational adjustable autonomy for nasa personal satellite assistants. we will describe a simulator and simulated teamwork among a number of personal satellite assistants (psa) onboard the simulated space station patrolling for problem detection and isolation. psas reason about autonomies of potential helpers while helpers reason about their autonomies for deciding to help or to break away from prior commitments to help. we describe algorithms for computing psa autonomies when there are concurrent and conflicting situations. we also offer empirical results about qualities of help a recruiting psa receives when there are multiple, concurrent problems.
evaluating cost-sensitive unsolicited bulk email categorization. in the recent years, unsolicited bulk email has became an increasingly important problem, with a big economic impact. in this paper, we discuss cost-sensitive text categorization methods for ube filtering. in concrete, we have evaluated a range of machine learning methods for the task (c4.5, naive bayes, part, support vector machines and rocchio), made cost sensitive through several methods (threshold optimization, instance weighting, and meta-cost). we have used the receiver operating characteristic convex hull method for the evaluation, that best suits classification problems in which target conditions are not known, as it is the case. our results do not show a dominant algorithm nor method for making algorithms cost-sensitive, but are the best reported on the test collection used, and approach real-world hand-crafted classifiers accuracy.
content-based music filtering system with editable user profile. information filtering systems, which recommend appropriate information to users from enormous amount of information, are becoming popular. one method of information filtering is content-based filtering that compares a user profile with a content model. many systems using content-based filtering deal with text data, and few systems deal with music data. we propose a content-based filtering system for music data by using a decision tree. compared with other filtering methods, a decision tree can eliminate noise features, which are not related to the user's preference, and can allow the user to edit the learned user profile. we conduct an experiment by using real music data and users to validate the effectiveness of our system compared with other filtering methods.
an adaptive distance computation technique for image retrieval systems. for more than a decade query-by-one-example (qbe) has been a popular query system for content-based image retrieval (cbir). however, recent research has shown that a single image is not sufficient to form its semantics or concept of the intended query. searching concept "car," for instance, one might need many examples of car images in various colors. the color feature is then understood as a non-factor in the distance metric. in our approach, users can query by using groups of query images. there are three possible groups: relevant (positive), irrelevant (negative) or neutral groups. we define the range for each feature within these groups of query images, and use them to adjust the weights of the features. as a result, some features may be cancelled out from the similarity computation. the measure then becomes a dynamic metric for image retrieval. our approach achieves a higher degree of precision and recall and, at the same time, significantly reduces the time complexity of matching. the proposed approach is tested against the imagegrouper method. the results show that this approach is an effective and efficient technique for qbe.
editorial message: special track on operating systems and adaptive applications. the purpose of this track is to bring together researchers, designers, and developers who are interested in methodology for the design and analysis of operating systems and adaptive applications. it is motivated by a tremendous growth on the demands for high-performance operating systems in recent years. such an observation comes with the fact that many adaptive applications become more and more complex, and it imposes new challenging issues never faced before in this application field. it is thus clear that nowadays the development and design of operating systems must rely, even more than that in the recent past, on specific solutions both in the hardware and in the software components. moreover, the needs to timely tackle changes in the market pushes toward the employment of methodologies to shorten the development time and to drive the evolution of existing products. the solutions to new problems emerging in this setting call for a joint effort from the academics and industry.
health level-7 compliant clinical patient records system. we present the design and implementation of a health level-7 (hl7)-compliant web-based clinical patient records system (cprs). hl7 is one of the leading standards for exchange of clinical and administrative data among healthcare information systems. since the passage of the health insurance portability and accountability act of 1996 (hipaa) by us government, the security of electronic medical clinical records systems is of paramount importance. hipaa requires that various technical, physical and administrative security measures be combined to protect the privacy, integrity, and availability of patients' clinical records. the hl7 standard for clinical documents, clinical document architecture (cda), incorporates the hipaa guidelines. our cprs data schema is derived from cda that makes it naturally in compliance with the hipaa guidelines.cprs provides a unique web based interface for the caregivers to browse and edit universal patient records (upr) of their patients. to our knowledge, cprs is one of the first applications that have implemented an hl7-compliant upr. using cprs caregivers can access and edit the clinical documents of their patients from anywhere in the world.
formal verification of replication on a distributed data space architecture. we investigate the formal verification of safety-critical systems on top of the distributed data space architecture splice. in splice each component has its own local data space which can be kept small using keys, time stamps and selective over-writing. we use two complementary formal tools: first the &micro;crl tool set for a rapid investigation of alternatives by a limited verification with state space exploration techniques; next the most promising solutions are verified in general by means of the interactive theorem prover of pvs. these formal techniques are used to investigate transparent replication of certain components on top of splice. we prove that a convenient solution can be obtained by means of a slight extension of the write primitive of splice.
effective rule induction from labeled graphs. labeled graphs provide a natural way of representing objects and the way they are connected. they have various applications in different fields, such as for example in computational chemistry. they can be represented by relational structures and thus stored in relational databases. acyclic conjunctive queries form a practically relevant fragment of database queries that can be evaluated in polynomial time. we propose a top-down induction algorithm for learning acyclic conjunctive queries from labeled graphs represented by relational structures. the algorithm allows the use of building blocks which depend on the particular application considered. to compensate for the reduced expressive power of the hypothesis language and thus the potential loss in predictive performance, we combine acyclic conjunctive queries with confidence-rated boosting. in the empirical evaluation of the method we show that it leads to excellent prediction accuracy on the domain of mutagenicity.
hierarchical nonlinear constraint satisfaction. constraint programming is a method of problem solving that allows declarative specification of relations among objects. it is important to allow preferences of constraints since it is often difficult for programmers to specify all constraints without conflicts. in this paper, we propose a numerical method for solving nonlinear constraints with hierarcical preferences (i.e., constraint hierarchies) in a least-squares manner. this method finds sufficiently precise local optimal solutions by appropriately processing hierarchical preferences of constraints. to evaluate the effectiveness of our method, we present experimental results obtained with a prototype constraint solver.
a high-dimensional approach to interactive graph visualization. graph layout is an information visualization technology for illustrating relations between objects. interactive graph layout is often important since it is difficult to statically lay out complex graphs such as general undirected graphs. in this paper, we propose a novel approach to interactive layout of general undirected graphs. the basic idea of our approach is to use static graph layouts in high-dimensional spaces to dynamically find two-dimensional layouts according to user interaction. the resulting method that we present exhibits the following two characteristics: (1) it efficiently updates two-dimensional graph layouts during user interaction; (2) it follows users' node dragging operations by actively moving other closely related nodes. our method adopts eigenvector-based multidimensional scaling to compute high-dimensional graph layouts, and performs constraint satisfaction to determine appropriate two-dimensional planes onto which the high-dimensional layouts will be projected.
solving linear and one-way constraints for web document layout. the development of information systems such as web browsers based on open standards is becoming more and more important. to clearly formalize and appropriately implement document layout methods for web browsers, researchers have proposed an approach that uses constraint programming and solving. however, it is still difficult for existing standard constraint solving techniques to handle web document layout methods. to tackle this problem, we propose a new algorithm called duplex that solves hybrid systems of linear constraints and one-way constraints.
immunity-based intrusion detection system design, vulnerability analysis, and genertia's genetic arms race. the genertia red team uses a genetic algorithm to perform vulnerability analysis in an effort to discover holes in an intrusion detection system. this paper demonstrates how a genertia blue team generates detectors to patch those holes discovered by the grt. the gbt uses a novel approach to generate detectors that have different coverage in order to reduce the amount of overlap of detectors created by random generation and negative selection.
efficient on-line identification of hot data for flash-memory management. hot-data identification for flash-memory storage systems not only imposes great impacts on flash-memory garbage collection but also strongly affects the performance of flashmemory access and its life time (due to wear-levelling). in this research, we propose a highly efficient method for online hot-data identification with limited space requirements. different from the past work, multiple independent hash functions are adopted to reduce the chance of false identification of hot data and provide predictable and excellent performance for hot-data identification. we not only propose an efficient implementation of the proposed framework but also conduct a series of experiments to verify the performance of the proposed method, in which very encouraging results are presented.
admire: an algebraic approach to system performance analysis using data mining techniques. system performance analysis is a very difficult problem. traditional tools rely on manual operations to analyze data. consequently, determining which system resources to examine is often a lengthy process, where many problems are elusive, even when using data mining tools. we address this problem by introducing the analyzer for data mining results (admire) technique as a natural and flexible means to further interpret data mining outcome. in our scheme, regression analysis is first applied to performance data to discover correlations between parameters. regression rules are defined to represent this output in a format suitable for admire. admire expressions are then used to manipulate these sets of rules, revealing information about combined, common and different features of varying configurations. this knowledge would be unavailable if regression output were considered in isolation. admire was tested with performance data collected from a tpc-c (transaction processing performance council) test on an oracle database system, under various configurations, to demonstrate the effectiveness of our technique.
overlay multicast for video on demand on the internet. patching is an attractive technique for building efficient video-on-demand systems. however, since patching assumes the existence of ip multicast, implementing patching on the current internet is a challenging task because the internet is based on ip unicast only. in this paper, we propose an overlay technique called vcast for enabling multicast services on the application layer, as a way to support the implementation of patching. unlike earlier overlay multicast schemes, vcast does not introduce any global topology for the overlay and therefore avoids control overhead to maintain it. vcast can configure itself adaptively to the changing network traffic, and is tolerant to failures prone to happen frequently in dynamic environments such as the internet. in addition, vcast provides load balancing among network nodes by employing the round-robin approach in selecting delivery paths for clients.
grid-enabled parallel divide-and-conquer: theory and practice. this paper presents a general methodology for the communication-efficient parallelization of graph algorithms using the divide-and-conquer approach. the algorithm is communication-free in the conquer stage and uses only a small amount of messages while partitioning the input. specifically, a practical parallel algorithm with full scalability, based on the bsp model, for finding hamiltonian paths in tournaments is presented.experiments have been carried out on two architecturally different systems, which stand for the possible site variety of a computational grid. these include a distributed-memory system: a solaris cluster of 32 sun ultra5 computers on myrinet network and a distributed shared-memory system: an sgi origin 2000 with 32 r10000 processors, using mpich-gm and mpt, respectively. both implementations are compatible with the grid-enabled mpi implementation, mpich-g2.
broadcast program generation for unordered queries with data replication. we study in this paper the problem of broadcasting dependent data for unordered queries. however, most prior studies on dependent data broadcasting are limited to the premise of no data replication. different from other prior studies, we investigate the effect of data replication in this paper. specifically, we first derive several theoretical properties for the average access time by analyzing the model of dependent data broadcasting. on the basis of the theoretical results, we develop a genetic algorithm to generate broadcast programs with replication. in order to compare the performance of the proposed algorithm and the prior studies, several experiments are conducted. our experimental results show that with the analytical results derived, the theoretical results derived are able to guide the search of the genetic algorithm very effectively, and lead to solution broadcast programs of higher quality than those of the prior studies.
an approximation algorithm for haplotype inference by maximum parsimony. this paper studies haplotype inference by maximum parsimony using population data. we define the optimal haplotype inference (ohi) problem as given a set of genotypes and a set of related haplotypes, find a minimum subset of haplotypes that can resolve all the genotypes. we prove that ohi is np-hard and can be formulated as an integer quadratic programming (iqp) problem. to solve the iqp problem, we propose an iterative semi-definite programming based approximation algorithm, (called sdphapinfer). we show that this algorithm finds a solution within a factor of o(logn) of the optimal solution, where n is the number of genotypes. this algorithm has been implemented and tested on a variety of simulated and biological data. in comparison with three other methods: hapar, haplotyper, and phase, the experimental results indicate that sdphapinfer and haplotyper have similar error rates. in addition, the results generated by phase have lower error rates on some data but higher error rates on others. the error rates of hapar are higher than the others on biological data. in terms of efficiency, sdphapinfer, haplotyper, and phase output a solution in a stable and consistent way, and they run much faster than hapar when the number of genotypes becomes large.
a proxy-based adaptive flow control scheme for media streaming. based on the layered video streaming technique, we proposed a proxy-based traffic flow control scheme that adjusts the presentation quality according to the currently available bandwidth, i.e., dropping/adding some video layers when the network situation gets congested/smooth. additionally, the proposed traffic flow control provides layered video stream buffering control to smoothen video playout. a re-transmission technique is also adopted to reduce the lost possibility of some important video frames. with the proposed traffic flow control scheme, the coming server-proxy-client multimedia presentation systems can have a better bandwidth utilization and presentation quality.
qos support for ieee-1394 requests. ieee-1394 is widely adopted in various commercial products for computing, communication, and entertainment. although many services with quality of service (qos) supports are now available in systems over ieee-1394, little work is done for qos-based resource allocation. in this paper, we aim at the design of a bandwidth reservation mechanism and its policy for isochronous requests, such as those from cameras. we then address the qos support issue for asynchronous requests, such as those from disks, and then an analytic framework for probability-based qos analysis. the capability of the proposed methodology and the analytic framework is evaluated by a series of experiments over a linux-based system prototype.
extending noninterference properties to the timed world. most previous work on information flow in process algebras has been based on untimed models of concurrency. it is obvious, however, that an observer might well use time to gain information about what a high-level user of the system is doing. we use the priority tock view (a discrete timed model) to extend several traditional untimed noninterference properties to the timed world. these are the determinism-based conditions of [14], [15] and [17], and forster's local noninterference properties [6], [7].
a clustering-based approach for prediction of cardiac resynchronization therapy. this paper presents a method for predicting pacing sites in the left ventricle of a heart and its result can be used to assist device programming in cardiac resynchronization therapy (crt), which is a widely adopted therapy for heart failure patients. in a traditional crt device deployment, pacing sites are selected without quantitative prediction. that runs the risk of suboptimal benefits. in this work, a surface tracking method is proposed to describe the ventricular wall motion and a hierarchical agglomerative clustering technique is applied to radial motion series to find candidate pacing sites. using clinical mri data in our experiments, we show that the proposed method performs as well as we expect. our approach can not only effectively identify suitable pacing sites, but also distinguish patients from normals perfectly to help medical diagnosis.
two-level client caching and disconnected operation of notebook computers in distributed systems. data caching in distributed file systems has been studied with regard to performance and availability [7,9,14,15]. the most common place for the cached data is the server's main memory. this type of caching is referred to as server caching, as opposed to client caching when the cached data is stored on the client (remote workstation) site. although server caching improves performance considerably since it eliminates disk transfer time for each access, it has two drawbacks: it still suffers from a network transfer delay and is very vulnerable to server's failures. server's failure renders the whole system virtually inoperable.
editorial message: special track on artificial intelligence, computational logic and image analysis. this special track on artificial intelligence, computational logic and image analysis for sac '05 is a forum for engineers, researchers and practitioners throughout the world to share technical ideas and experiences relating to implementation and application of artificial intelligence (ai). the crowning achievement of ai was evidenced in may 1997, when the program deep blue defeated mr. garry kasparov, the world chess champion. deep blues, like the majority of efforts in ai, simulate symptoms of intelligent behavior as observed in humans.
scheduling dependent items in data broadcasting environments. most of the prior research works in data broadcasting are based on the assumption that the disseminated items are independent of one another. since in many applications, a mobile user will be interested in more than one item simultaneously, we discuss in this paper the issue of dependency in generating a broadcast program. algorithm pba, standing for placement-based allocation, is proposed to generate a broadcast program with high quality and low complexity in the dependent data broadcasting environment. the experimental results show that the proposed placement-based allocation for scheduling dependent items leads to better execution efficiency and solution quality than those by prior works.
features of the concurrent programming language aldwych. this paper describes a concurrent programming language, aldwych. the language has a simple operational model where any variable has exactly one process that can write to it but any number that can read it. once a variable has been written to its value cannot be changed, but a tuple value can be written to a variable, and variables within the tuple written to later. processes consist of a set of rules which are triggered when variables are given values.we show how this underlying model can be extended using a number of derived forms so that aldwych has features of imperative, object-oriented and functional programming.
an agent based approach to site selection for wireless networks. the location of transmission infrastructure for wireless communication networks is an important engineering problem involving competing objectives. a minimal selection of locations (or sites) are required subject to providing adequate area coverage for users. in this paper we present a general model for this problem, related to circle packing and set covering. we show that the pattern matching algorithm known as stochastic diffusion search can be applied to identify suitable solutions even for large problem instances.
an empirical evaluation of communication effectiveness in autonomous reactive multiagent systems. this paper describes an experiment designed to measure the effect of collaborative communication on task performance of a multiagent system. a simulation of a multiagent environment modeled after a bee colony examined the effects of collaboration through communication for various numbers of agents and environment sizes. results show that collaboration enables a smaller number of agents to perform as well as a significantly larger number of agents without coordination. in particular, results indicate that the biologically inspired communication model of the bee is a particularly effective method of agent communication and collaboration.
the future of systematic information protection. information plays a critical role in global economics as well as our security, safety, and quality of life. there is a growing disparity between the value of information and our capability to manage and protect it. technical and policy research is needed to address this disparity. fundamentally, we can not answer the following question, "how much security is enough?" we lack the capability to quantify the value of information, particularly information that has been processed and aggregated. we also face many difficulties when attempting to measure information security, characterize threats, understand vulnerabilities, or even formulate and sustain any specific security posture. as a result, we can not measure our risk and therefore can not manage it. our efforts to address this problem can be divided into two categories, legal/policy and technical. owners of physical assets, such as cash or gold, have the legal and technical means to augment fortification protections with armed guards and lethal force. from a legal perspective, protection of information is limited to fortification, in part because we lack sufficient attribution. from a technical perspective, we have built complex mountains of computer code on top of hardware architectures that will attempt to execute any arbitrary instructions. these systems cannot be effectively analyzed for vulnerabilities so as to ensure trustworthy and secure operation. research is needed to address the systematic protection of information including information valuation, security metrics, strong attribution, trustworthy computing, sustainable security processes, and legal devices that will support comprehensive protection and risk management. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
agent-based mobility add-in feature for object transaction service (ots). service session mobility is a new concept in the next telecom service generation. it allows users to move from one terminal in one network to another terminal in another network with service continuity. this concept requires migrating the current service execution related information, including service context, service data, etc, from one terminal to another. for services that execute within transactions, transaction context is a part of service context and must be migrated too. this paper presents our work on this problem, based on corba object transaction service. mobile agent is the enabling technology, which enhances the transaction service with mobility features.this model was initially designed for vhe architecture of vesper, a european project to design a model for virtual home environment in the next generation of telecom network. however, it can be applied to any other architecture, which require to solve the problem of service session mobility with transaction.
slide edge algorithm. the traveling salesman problem is one of the most well known problems in the class of optimization problems and is still a challenge for many computer scientists today. one approach used to attack this problem is the use of neighborhood search techniques (or improvement algorithms) that improve a solution by making a move to a neighbor if it is a better solution. neighborhood search techniques are used either independently itself or plugged in other algorithms such as iterated algorithm, local search, or evolutionary algorithm. at the same time, the running time gets slower quickly as the size of neighborhood grows exponentially. in this paper, we introduce the slide edge algorithm (sea), which is supposed not to find a move as neighborhood search techniques do but to improve the quality of a move that a neighborhood search technique finds out. while the time to find a move is exponential, the time of sea is approximately to linear. in experiment results, with the support of sea in improving a have-just-found move, neighborhood search techniques achieve a better quality of the tour in a reasonable amount of time.
prioritization of enterprise resource planning (erp) systems success measures: viewpoints of two organizational stakeholder groups. business organizations worldwide are adopting enterprise resource planning (erp) systems. a number of studies deliberate the adoption and implementation of erp, but few investigate the success of the system. to our knowledge, this is the first study of its kind to investigate the perspectives of key organizational stakeholders with respect to the success of their erp software. using postal surveys in finland and estonia, two small northern european countries, we obtained empirical data from 44 private organizations in diverse industries. our objective was to determine whether differences exist between two organizational stakeholder groups (top- and mid-level managers) concerning their prioritization and evaluation of measures relating to the success of their erp software. despite their distinct roles and influence, we did not notice any significant statistical differences between the two groups in this regard. however, each group evaluated measures such as "accuracy" and "reliability" differently. this paper discusses the implications of the study for both practice and research.
union types for object-oriented programming. we propose union types for statically typed class-based object-oriented languages as a means to enhance the flexibility of subtyping. as its name suggests, a union type can be considered a set union of instances of several types and behaves as their least common supertype. it also plays the role of an interface that 'factors out' commonality of given types---fields of the same name and methods with similar signatures. union types can be useful for implementing heterogeneous collections and for grouping independently developed classes with similar interfaces, which has been considered difficult in languages like java. to rigorously show the safety of union types, we formalize them on top of featherweight java and prove that the type system is sound.
retrieving lightly annotated images using image similarities. users' search needs are often represented by words and images are retrieved according to such textual queries. annotation words assigned to the stored images are most useful to connect queries to the images. however, due to annotation cost, quite limited amount of annotation words are available in many cases. when annotations are not given at all, there needs to be some techniques that assign annotations automatically. when only a few annotation words are given to each image (lightly annotated), there need to be some enhancement techniques that best use the available annotations. we address the later problem by estimating word associations to fill in the lexical gap between queries and annotations. the model of word associations can be learned from the data. however, since images are only lightly annotated, their sparseness in computing word associations becomes crucial. to compensate the sparseness, we propose a novel data exploration technique in which image similarities contribute to the estimation of word associations on the assumption that similar images have similar semantic concepts. we experimentally show the potential benefit of our approach.
a declarative framework for adaptable applications in heterogeneous environments. in this paper we present an approach for developing adaptable software applications. the problem we are facing is that of a (possibly mobile) user who wants to download and execute an application from a remote server. the user's hosting device can be of different kinds (laptops, personal digital assistants, cellular phones, communicators, etc.) with specific hardware and software capabilities. the problem is to be able to decide whether the user's current device characteristics are compatible with the application requirements in order to prevent execution failures. in the negative case we want to identify the reasons that determined the incompatibility and perform an automatic adaptation of the application, so that it can match the user's device capabilities. we adopt a declarative approach: we provide each device with a declarative description of its characteristics and, possibly, context constraints. inspired by proof carrying code (pcc), we use first-order logic formulae to model both the behavior of the code, with respect to the properties of interest, and the execution context. the adaptation process is carried out by using theorem proving techniques, in particular, the proof assistant hol4. the aim is to derive a formal proof which asserts that the behavior of the code can be correctly adapted to the given context. by construction, the proof, if it exists, gives information on how the adaptation has to be done. on the application side, java2 micro edition (j2me) is the chosen reference application development environment.
using xml and related standards to support location based services. location based services can be considered as the most rapidly expanding field of the mobile communications sector. the proliferation of the mobile/wireless internet, the constantly increasing use of handheld, mobile devices and positioning technologies and the emergence of mobile computing, prepared the grounds for the introduction of this new type of services with impressively large application domain and use range. the combination of position fixing mechanisms with location-dependent, georgraphical information, can offer truly customized personal communication services through the mobile phone or other type of devices. web services have emerged as a set of open standards and gained a lot of momentum during the recent past. many software vendors are announcing web service initiatives and adoption in their products. many organizations are involved in the refinement of web service standards. moreover, xml has become the de facto standard for data interchange on the web and its emergence is having an enormous impact on web development. motivated by the technology advances in the aforementioned areas in this paper we discuss the exploitation of web services and xml to build a generic platform for delivering location based services (lbs) to the nomadic user.
an adaptive index allocation scheme for reliable data retrieval and provision in peer-to-peer networks. file-sharing peer-to-peer systems are effective for autonomous data retrieval and provision over the networks. however, the previous data retrieval schemes such as gnutella and local indices have bad performance and large overhead. in order to solve these drawbacks, this paper proposes an adaptive scheme for data retrieval and provision, in which indices are dynamically allocated in appropriate nodes adaptively to variation of traffic patterns caused by query messages. the simulation experimental results show that the proposed scheme has good performance with reasonable overhead even when the traffic patterns vary as time proceeds.
an integrated model of workflows, e-contracts and solution implementation. electronic-contracts (e-contracts) are structured models of business contracts. business transactions between enterprises can be supported by inter-workflows based on standards. however, exceptions, namely problematic situations whose solutions are not specified in the workflow design, are not well supported in the proposed models. such exceptions need to be resolved observing e-contracts. discussion and decision-making by participants are necessary for interpreting e-contracts and agreeing on a solution. in this paper, we propose workflow-contract-solution model (wcs model) to support such e-contract oriented execution of business processes.
data logistics as a means of integration in healthcare applications. information integration is still a crucial issue in healthcare applications. most clinical applications are determined by a huge variety of heterogeneous and independent work places, most of them equipped with specialized clinical hardware. due to this it is almost impossible -- at least not feasible -- to run a common database system storing all relevant data of a clinical application. nevertheless these clinical applications have to share their data. our solution to this integration problem is to facilitate so called process based data logistics. this approach is based on the integration capabilities of process management; however it does not coordinate the staff working in the healthcare domain in a restricting sense, but coordinates data sources and data sinks of these applications.
using the structure of documents to improve the discovery of unexpected information. in this paper we are interested in taking into account the structure of the documents during the discovery of unexpected information in textual databases. following a work that aimed at designing and integrating, in the unexpectedminer system, some measures for the evaluation of the unexpectedness of documents, we wanted to improve the system by taking into account the structure of the documents processed. each part of the documents are weighted by some coefficients whose values are determined by optimization techniques. those coefficients are then used by the system in the unexpectedness measures to determine if a document contains some unexpected information or not. the efficiency of our new system is then evaluated and the experiments put forward the improvements induced by the use of the structure of the documents.
adaptive and fault tolerant medical vest for life-critical medical monitoring. in recent years, exciting technological advances have been made in development of flexible electronics. these technologies offer the opportunity to weave computation, communication and storage into the fabric of the every clothing that we wear, therefore, creating intelligent fabric. this paper presents a medical vest which has sensors for physiological readings and software-controlled, electrically-actuated trans-dermal drug delivery elements. furthermore, computational elements are embedded in the vest for collecting data from sensors, processing them and driving actuation elements. since this vest will be used for medical, life-critical applications, the single most critical requirement of such a vest is an extremely high level of robustness and fault tolerance. meantime, the key technological constraint for these mobile systems is their power consumption. our target application for our medical vest is the detection of possibly fatal heart problems, specifically unstable angina pectoris or ischemia. we illustrate the design stages of our medical vest as well as the technical details of both software and network reconfiguration schemes (to enhance the robustness and the performance of our system). we also discuss the details of ischemia detection algorithm employed in our vest. moreover, we evaluate the robustness of our system with existence of various faults. finally we measure the performance of our algorithm as well the power consumption of several configurations of our vest.
efficient placement and routing in grid-based networks. this paper presents an efficient technique for placement and routing of sensors/actuators and processing units in a grid network. our system requires an extremely high level of robustness and efficient power optimization techniques. by modeling the faults, we evaluate the probability of having failures in network. then we study two problems of placement and routing in the sensor networks such that the fault tolerance is maximized while the power consumption is minimized. we develop efficient methodology to address these problems and perform both placement and routing simultaneously. this ensures that the solution is a lower bound for both problems. we evaluate the effectiveness of our proposed techniques on a variety of benchmarks.
modere: the model-checking engine of rebeca. rebeca is an actor-based language with formal semantics that can be used in modeling concurrent and distributed software and protocols. automatic verification of these systems in the design stage helps develop error free systems. in this paper, we describe the model checking tool developed for verification of rebeca models. this tool uses partial order reduction technique for reducing the size of the state space generated for a given model. using this tool for model checking rebeca yields much better results than the previous attempts for model checking rebeca.
a comparison on information fusion methods for air target identification. we compared the performance of bayes theory, fuzzy set theory, heuristic method and dempster-shafer theory in the identification of aircrafts by using the information from different sensors. from the results of the simulation, the fuzzy method produces the best result. the final identification could be improved if specific features of each type of aircraft are available. to get more accurate object identification, the results from each method can be combined with the best assignment of values for each method.
an agent design method promoting separation between computation and coordination. the development of (internet) agents is often a tedious and error-prone task resulting in poorly reusable designs, since both the internal computation of the agent as well as the coordination support are developed in an ad hoc fashion. to improve the process of agent-oriented software development, we propose an agent design method that imposes the separation of internal computation from coordination aspects. this method comprises two dimensions: a design formalism and an agent design process. as an illustration of the presented method, we present the design of an internet agent that is entitled to deploy a distributed service in a computer network, without breaking the consistency of that network. the presented design method has resulted in the development of acf (agent composition framework), a component framework to build flexible internet agents. we argue that the presented design method combined with this infrastructure can promote a modular and easy to manage approach to the design and development of internet agent applications.
object-oriented middleware for location-aware systems. location-based systems are often aiming at the separation of the concept of location to a particular system, or, alternatively, treat location as yet another issue that should be fit into a larger prescribed application framework. this may lead to increasingly complex system architectures, when application logic uses location only as a facility. as a solution that gathers the best sides of both approaches, we propose an approach where object-oriented middleware is used for handling location-based issues in applications that run in mobile devices. in this paper, we will introduce distribution of software and hardware components, as well as sketch the internal architecture of the middleware in terms of the most relevant interfaces. towards the end of the paper, a sample application is also introduced.
generating association graphs of non-cooccurring text objects using transitive methods. in this paper we discuss text data mining (tdm) mainly in the context of the biomedical domain, where we extract associations from medline text articles and construct association graphs. we explore two techniques, the co-occurrence method and transitive method. we propose a novel transitive method of finding associations that does not rely on meta-data, and compare the results with another known transitive method that uses metadata in text, to find a link/relationship between objects of interest. co-occurrence of these terms (objects) is not required in the transitive methods to find out that they are associated. the results show that our proposed new method is as accurate as the known method that uses meta-data. this, in turn, implies that relationships can be discovered even when meta-data is not available or incomplete. a case study of a transitive association between a pair of genes (brcai---stati) is also carried out to illustrate the effective hypothesis generating ability of our method. based on the results, we conclude that our method can be used effectively for association extraction and also for hypothesis generation, which can later be validated through biological experimental analysis.
l0 buffer energy optimization through scheduling and exploration. clustered l0 buffers are an interesting alternative to reduce energy consumption in the instruction memory hierarchy of embedded vliw processors. currently, the synthesis of l0 clusters is performed as a hardware optimization, where the compiler generates a schedule and based on the given schedule l0 clusters are generated. however, the cluster synthesis is sensitive to the given schedule. this offers an interesting design space to explore the effects on clustering by altering the schedule to increase energy efficiency. in this paper we present a preliminary study indicating the potentials offered by scheduling for l0 clusters in terms of l0 buffer energy reduction. a list scheduler is extended to recognize the l0 clusters and based on a few simple heuristics operations are assigned to clusters. an iterative methodology is employed to explore the design space. the simulation results indicate that up to 10% of l0 buffer energy can potentially be reduced by scheduling for l0 clusters with a simple heuristic.
performance evaluation for a compressed-vliw processor. this paper presents a new ilp processor architecture called compressed vliw (cvliw). the cvliw processor constructs a sequence of long instructions by removing nearly all nops (no operations) and lnops (long nops) from vliw code. the cvliw processor individually schedules each instruction within long instructions using functional unit and dynamic scheduler pairs. every dynamic scheduler in the cvliw processor individually checks for data dependencies and resource collisions while scheduling each instruction. in this paper, we simulate the architecture and show that the cvliw processor performs better than the vliw processor for a wide range of cache sizes and across various numerical benchmark applications. these performance gains of the cvliw processor result from individual instruction scheduling and size reduction of object code. even though we assume a cache with a zero miss rate, the cvliw's performance is still 9%~15% higher than that of the vliw processor regardless of benchmark applications.
cosar: commitment-oriented "sense and respond" system for microelectronic manufacturing. microelectronic manufacturing is a discipline of supply chain management, and deals with the efficient coordination of manufacturing processes and owning enterprise along a value chine to provide products to customers. the systems for microelectronic manufacturing processes are usually linear, rigid and producing solutions that are far from optimal. this paper presents a commitment-oriented "sense and respond" system, called cosar, for microelectronic manufacturing. cosar enables the development of adaptive and configurable manufacturing systems. we will explain both the concept of commitment and also the foundation and architecture of cosar.
gis, sinks, fill, and disappearing wetlands: unintended consequences in algorithm development and use. geographic information systems (gis) software has become an important computational tool in several fields. gis software ranges from command line processors, with maximal control over internal model decisions, to gui versions with point-and-click access to pre-set modules. based on the output from this software, some gis users make important decisions to plan and manage landscapes (e.g., cities, parks, forests) with real consequences for the managed ecosystems. we discuss a programming decision in a gis algorithm originally used to discern flow direction in hydrological modeling: a first step in mapping streams and rivers. topographic depressions ("sinks") are "filled" in the algorithm to map water flow downstream; otherwise, the gis algorithm cannot solve the flow direction. unfortunately, sinks are often "isolated" wetlands which provide essential habitat for many species not commonly found elsewhere. thus the algorithmic filling of sinks can make these wetlands "disappear" in gis output and land-use decisions based on this output.this algorithmic detail may have potentially devastating real-world consequences for numerous wetlands because land-use plans made in ignorance cannot adequately conserve these unique habitats and the vital ecosystem services that wetlands provide. these consequences were not anticipated by the programmers who originally implemented the flow direction algorithm and may not be known to gis users. we offer several strategies to reduce the impact of these consequences for gis programmers, users, and policy makers who depend on gis data when making decisions.
generating web-based systems from specifications. the amount of web-based systems is growing rapidly and the complexity of the developed systems is increasing as well, and in the literature one speaks about a web crises.many web-based systems have a structure where users via a browser can perform operations on a database. we show that major parts of the software of such applications can be generated and verified from specifications of the functional requirements and specifications of the navigation.in particular, we show how to generate a modular software architecture, which is type safe in the sense that it enforces that functions throughout the application are applied to arguments of the correct type, and navigation safe taking e.g. into account consistency among user groups, functions and reachable web pages, and type consistency of web pages wrt. to functions on links.a default implementation of the functional requirements is generated allowing e.g. the navigation to be validated at an early stage of the development.a full implementation is obtained from the generated software architecture by implementing the functional requirements only, and this is done using a strongly-typed language.
prototype system for method materialisation and maintenance in object-oriented databases. the efficient execution of a method has a great impact on a system response time. optimising access to data returned by methods is difficult as methods are written in high-level programming languages. moreover, estimating a method's execution cost is another serious problem because of the complexity of a method's code. a promising technique to tackle the problem of optimising execution of methods is based on method materialisation. within our project we developed, so called, hierarchical method materialisation technique. in this paper we present a prototype system for hierarchical materialisation of methods and for the management of their results in an object-oriented database.
adaptation point analysis for computation migration/checkpointing. finding the appropriate location of adaptation points for computation migration/checkpointing is critical since the distance between two consecutive adaptation points determines the migration/checkpointing scheme's sensitivity and overheads. this paper proposes a heuristic adaptation point placement algorithm to improve the computation migration/checkpointing schemes' performance in terms of sensitivity and flexibility. this heuristic algorithm enables automatic and transparent insertion of checkpoints in user's source code.
tough constraint-based frequent closed itemsets mining. mining frequent itemsets has been one of the hot topics in data mining. candidate generation-and-test approaches such as apriori have been proved to be effective. however, in practical applications, we will face a lot of intractable frequent itemsets under the preset minimum support. in order to solve the problem, we have two methods: constraint-based mining and frequent closed itemsets mining. to the best of our knowledge, it has not been studied how to combine one of the complex constraint, tough constraint, with the frequent closed itemsets mining. in this paper, we show the benefits of combining the two technologies through the tc-based fcm algorithm. we also discuss the following two problems: 1) which one should be put in advance, select process or filter process? 2) how to make full use of the information from the upper level.
data stream management system for mavhome. mavhome project provides rich applications for addressing various issues associated with stream data processing. in this paper, we present our approach for building a data stream management system (dsms) for the above smart home project. we further summarize our primitive solutions for continuous query processing, quality of service(qos) management, and mapping a trigger mechanism to a stream processing system.
symmetry in event structures. a notion of symmetry for event structures is defined, which are based on permutation groups. given an event structure and a permutation group over it, we introduce the quotient model of the event structure and show that the quotient model is trace, bisimulation and pomset equivalent to the original event structure.
protein threading with residue-environment matching by artificial neural networks. protein threading programs align a probe amino acid sequence onto a library of representative folds of known protein structure to identify a structural homology. a scoring function is usually formulated in terms of the threading energy to evaluate protein sequence-structure fitness. the structure that yields the lowest total energy is considered the leading template of the probe protein. an alternative approach is to predict the probabilities of observing amino acid side-chains in structural environment without considering the energy of contacts. in this paper, a model named tes is proposed on building a new environment-specific protein sequence-structure mapping with artificial neural network. the decoy sets obtained from the web are used to test the proposed tes method on discrimination of native and decoy protein three-dimensional structure. the verified approach shows that the performance of the proposed method is comparable to those of knowledge-based potential energy function.
covatm: a transaction model for cooperative applications. it has been widely recognized that traditional transaction models with acid(atomicity, consistency, isolation and durability) properties generally are not applicable to cooperative applications. though many advanced transaction models have been proposed to address the problems, they are too database-centered or too rigid to be useful in real environments. this paper presents a new transaction model named covatm, which provides sophisticated but flexible control over cooperative process as well as support for error recovery and exception handling. the most distinguished feature of this model is that user intervention is explicitly introduced into transaction processing. this paper details the features and structural elements of this model. an example is also given to illustrate how it works in real world settings.
sanitizing using metadata in metaxquery. metadata plays an important role in describing and proscribing data in both traditional and xml applications. in this paper, we present an extension of the xml data model and xquery query language to certify the reachability of data and to sanitize data with the existence of metadata, especially proscriptive metadata. the data model extension is called metadom, and the query language is called metaxquery. this paper describes a certify function to check if the metadata in the data model is correctly embedded, in other words, whether all of the data nodes are reachable from the root. it also describes a sanitize function that automatically corrects the data model if it is invalid. the sanitize function can also be used to generate a view of the data from a specific metadata perspective.
efficient query routing for information retrieval in semantic overlays. a fundamental problem in peer-to-peer networks is how to locate appropriate peers efficiently to answer a specific query request. this paper proposes a model in which semantically similar peers form a semantic overlay network and a query can be routed or forwarded to appropriate peers instead of broadcasting or random selection. we apply latent semantic indexing (lsi) in information retrieval to reveal semantic subspaces of feature spaces from documents stored on peers. after producing semantic vectors through lsi, we train a support vector machine (svm) to classify the peers into different categories based on the extracted vectors. peers with close categories are defined as semantic similarity and form a semantic overlay. experimental results show the model is efficient and performs better than other non-semantic retrieval models with respect to accuracy. in addition, our approach improves the recall rate nearly 100% while reducing message traffic dramatically compared with gnutella.
a new approach to the bdi agent-based modeling. intelligent agents have been regarded as a new notion to build complex software systems. in this paper, we propose an agent-based software development process based on belief-desire-intention (bdi) agent model as a new software development process. the belief-desire-intention (bdi) model has been used as a fundamental ingredient to the new agent-based modeling method. in our agent system proposed here, each agent is made flesh by assigning its own belief, desire and intention. here we have shown a seamless software development modeling technique consistently based on the bdi model. even though there are many valuable arguments to define agents beside the bdi model, we currently use the bdi model only to simplify the agent modeling because we try to develop a more realistic agent-based modeling technique. we will extend this work to support other key concepts in agent computing.here we propose a new approach comparing it with our previous approach to support the bdi agent-based modeling techniques. the previous approach finds intentions, desires and beliefs from two different kinds of use cases - external use cases and internal use cases - and supporting tools. the new approach finds in sequence desires, intentions and beliefs by using not only different kinds of use cases, sequence diagram, activity diagrams, and dataflow diagrams. to prove the usability of our software development process, we also provide a case study to clarify the description of our bdi agent software development process. this paper also introduces a brief structure of a case tool that we are currently developing to support the bdi agent software development process.
editorial: programming languages track. programming languages are programmers' most basic tools. with appropriate programming languages one can drastically reduce the cost of building new applications as well as maintaining existing ones. in the last decade programming languages have made a large shift from procedural and structured programming towards new programming paradigms such as logic, functional and object-oriented programming. the main driving force was and will continue being to better express programmer's ideas. therefore, research in programming languages is an endless activity and the core of computer science. new language features, new programming paradigms, better compile-time and run-time mechanisms can be foreseen in the future. the pl track aims at providing researchers and practitioners with opportunities to present their ideas and experience in designing new programming concepts and implementing programming languages.
editorial message: programming languages track. programming languages are notations for describing our thoughts on computers. as the ways of thinking the problems and solutions have evolved in many different ways, many different programming languages have been invented to describe our solutions based on the different approaches.
a dialogue on responsibility, moral agency, and it systems. the dialogue that follows was written to express some of our ideas and remaining questions about it systems, moral agency, and responsibility. we seem to have made some progress on some these issues, but we haven't come to anything close to agreement on several important points. while the issues are becoming more clearly drawn, what we have discovered so far is closer to a web of connecting ideas, than to formal claims or final conclusions.
hierarchical presentation of expansion terms. different presentations of candidate expansion terms have not been fully explored in interactive query expansion (iqe). most existing systems that offer an iqe facility use a list form of presentation. this paper examines an hierarchical presentation of the expansion terms which are automatically generated from a set of retrieved documents, organised in a general to specific manner, and visualised by cascade menus. to evaluate the effectiveness of the presentation, a user test was carried out to compare the hierarchical form with the conventional list form. this shows that users of the hierarchy can complete the expansion task in less time and with fewer terms over those using the lists. relations between initial query terms and selected expansion terms were also investigated.
language support for incremental integration of independently developed components in java. the aim of component-based software development is to assembly applications from existing components, writing as little extra code as possible. for programmers, assembly of applications from existing components should increase reuse, thus allowing them to concentrate on value-added tasks and to produce high-quality software within a shorter time. for users, component-based software development promises tailor made functionality from the adaptaion of ready-made components. however, this ideal scenario has not yet become reality: today, many applications are still developed from scratch, and there are still relatively few ready-made components that can be easily reused in new applications. why is it so? we believe that part of the answer is that current object-oriented programming languages are missing support for non-invasive dynamic adaptation that works at the level of multiple objects simultaneously. such support would allow unanticipated, incremental modifications of a system's components at runtime. in this paper we propose lasagne/j an extension of the java programming language that helps programmers to overcome many of the integration problems that they face when assembling new applications from components developed by independent component vendors.
on the architectural alignment of atl and qvt. transforming models is a critical activity in model driven engineering (mde). with the expected adoption of the omg qvt standard for model transformation language it is anticipated that the experience in applying model transformations in various cases will increase. however, the qvt standard is just one possible approach to solving model transformation problems. in parallel with the qvt activity many research groups and companies have been working on their own model transformation approaches and languages. it is important for software developers to be able to compare and select the most suitable languages and tools for a particular problem. this paper compares the proposed qvt language and the atlas transformation language (atl) as a step in the direction of gathering knowledge about the existing model transformation approaches. the focus is on the major language components (sublanguages and their features, execution tools, etc.) and how they are related. both languages expose a layered architecture for organizing their components. the paper analyzes the layers and compares them according to various categories. furthermore, motivations for interoperability between the languages and the related tools are given. possible solutions for interoperability are identified and discussed.
exploiting fast ethernet performance in multiplatform cluster environment. as the communication subsystem largely determines the overall performance and the characteristics of cluster systems, it must face diverging demands such as bandwidth, latency, quality of service and cost. in this paper we investigate the performance and improvement possibilities of a portable tcp/ip based communication subsystem that aims to integrate heterogeneous nodes. the cluster is built up from standard pcs connected with low-cost network, where nodes may have different processor speed, memory size and may even run different operating systems. we present and compare application level end-to-end latencies measured under different conditions varying the number of simultaneous connections, processing threads and the types of operating systems. our experiments show that message latencies are overwhelmingly dominated by software overheads, which can be hidden or eliminated by different methods, thus pc clusters can take good advantage of the bandwidth of a fast ethernet connection even with smaller message sizes. finally, based on the results, we draw the attention to a domain of inaccuracy of the standard communication models in pc cluster environment, and we suggest a new formula to describe the latency of concurrent message channels over the same medium.
editorial message: special track on applications of evolutionary computation. the mechanisms that drive biological evolution are reproduction with variation, reproductive success proportional to fitness, and repetition. in any system where these mechanisms are active, populations of objects-biological or artificial-will evolve. among such systems are evolutionary algorithms, which apply techniques inspired by biological evolution to search for good solutions to computationally difficult problems.
editorial message: track on applications of evolutionary computation. many computational techniques are inspired by biological models; for example, neural networks by nervous systems and expert systems by the if-then rules of expert reasoning. among these biologically-inspired techniques is evolutionary computation, whose motivating ideas are the mechanisms that drive evolution: reproduction with variation, reproductive success proportional to fitness, and repetition. evolutionary algorithms have been applied to a wide variety of problems of search and optimization.
two hybrid evolutionary algorithms for the rectilinear steiner arborescence problem. given a collection of points in the first quadrant, a rectilinear steiner arborescence is a tree made up of horizontal and vertical line segments on the points and the origin in which every path from the origin leads only up and to the right. the minimum rectilinear steiner arborescence problem seeks such a tree of minimum total length.a greedy heuristic due to rao et al. [13] builds short arborescences and can be implemented to require time that is o(n log n). two evolutionary encodings of rectilinear steiner arborescences represent them as permutations of points and as strings of perturbations of point locations. a decoder in the style of prim's algorithm identifies the arborescence that a permutation represents; the heuristic of rao et al. identifies the arborescence corresponding to a string of perturbations.in tests on twenty instances of the problem of 50 to 250 points, a genetic algorithm using the permutation coding is unable to compete with the greedy heuristic, but a ga using the perturbation coding almost always improves on the heuristic's results, though in general the improvement is small.
initialization is robust in evolutionary algorithms that encode spanning trees as sets of edges. evolutionary algorithms (eas) that search spaces of spanning trees can encode candidate trees as sets of edges. in this case, edge-sets for an ea's initial population should represent spanning trees chosen with uniform probabilities on the graph that underlies the target problem instance. however, the generation of random spanning trees is not as simple as it might appear. mechanisms based on prim's and kruskal's minimum spanning tree algorithms are not uniform, and uniform mechanisms are slow, not guaranteed to terminate, or require that the underlying graph be complete.however, a non-uniform initial population of spanning trees need not harm an ea's performance. trials of a crossover-only ea for the one-max-tree problem, using prim-based, kruskal-based, and uniform initialization, indicate that the distribution of edges in the initial population is far more important than the distribution of trees. a skewed distribution of edges in its initial population damages the ea's performance, but this is remedied by a reasonable amount of mutation.
a uml statecharts semantics with message-passing. we give a formal semantics for one of the main uml diagram types for dynamical system behavior: statechart diagrams. this is the first semantics which explicitly models message-passing between different diagrams. it therefore lays a first foundation for executable uml modeling, allowing whole systems of uml specifications (rather than single diagrams) to be simulated.
using umlsec and goal trees for secure systems development. today many software systems need to take into account security considerations. while software engineering has been quite successful in ensuring that systems satisfy non-functional requirements such as dependability, less work has been done wrt. security requirements.in this work we present a software engineering method aiming to facilitate secure systems development, which is based on an extension of uml called umlsec.
avoiding data conversions in embedded media processors. complex application-specific media instructions and kernels are emulated with simple to implement extended subword instructions. we show that assuming extended register file entries to accommodate intermediate results and by implementing a few simple instructions, packing/unpacking, saturation, and frequently used complex instructions can be practically eliminated. it is shown that in most emulations there is a potential performance improvement, making the proposed scheme suitable for embedded processors with a limited hardware budget.
describing dynamic software architectures using an extended uml model. in this paper, we propose a new uml2.0 profile to describe the change of software architectures. the profile introduces a set of stereotypes for modeling the structural and the dynamic aspect as well as architectural constraints. we adapt the component diagrams metamodel on specific purposes by extending existing metaclasses. the adaptations are defined using stereotypes which are grouped in a profile. the profile offers to the architects an intuitive and complete way to specify the software architecture based on visual notations.
a particle swarm model for swarm-based networked sensor systems. swarm behavior as demonstrated by flocks of birds, schools of fish, and swarms of insects provide a useful method for implementing a distributed network of mobile sensor platforms. such mobile sensor swarm systems are useful for various search or surveillance activities. swarm behavior ensures safe separation between swarm members while enforcing a level of cohesion. these two properties, when considered in the context of sensors and wireless communications, provide for low redundancy coverage and a robust and reliable communications system. this paper examines particle swarm behavior through simulation with respect to such a sensor network. analysis of swarm behavior for various parameter settings indicate a classification methodology. this provides a foundation for a proposed taxonomy.
a framework for implicit and explicit service activation based on service level specification. internet protocol-based applications are the prevailing trend of the telecommunications market, but the path towards the "ip over everything" target is not unhampered. the main shortcoming of the ip protocol is its incapability of providing guaranteed quality of service (qos), although significant effort is spent within different standardization bodies and organizations. we propose architecture for the implicit and explicit service activation of internet services with guaranteed qos, based on existing service level specification (sls). the supported level of qos is according to the customer's demands and the network supportability defined within the terms of a signed service level agreement (sla). the main idea is that the service provider can perform service management effectively in an aggregated manner while the customer is provided with an uncomplicated interface to specify his service request.
delivering attribute certificates over gprs. attribute certificates (acs) have been developed and standardized by the ansi x9 committee as an alternative and better approach, to x.509 public key certificates, for carrying authorization information. attribute authorities (aa) bind the characteristics of an entity (called attributes) to that entity by signing the appropriate ac. therefore, acs can be used for controlling access to system resources and employing role-based authorization and access controls policies accordingly. although acs are widely used and standardized, to the best of our knowledge, no mobile infrastructure or service currently utilizes them. in this paper, we first examine how basic public key infrastructure (pki) can be incorporated into mobile networks and especially the universal mobile telecommunications system (umts). as a case study, we then experiment with acs in the gprs network, using a prototype implementation. in particular, we investigate and measure the performance in terms of service and transfer times when acs are introduced in the mobile environment. our measurements show that acs technology not only is feasible to implement in present and future mobile networks, but at the same time can deliver flexible and relatively fast services to the subscribers, without compromising security.
editorial message: special track on ubiquitous computing. ubiquitous technologies, infrastructures, applications and services that operate across physical environments (e.g. neighbourhood, home, car etc) will soon be spanning all the different spheres of everyday life. ubiquitous computing places humans in the center of environments saturated with computing and wireless communications capabilities, yet gracefully integrated, so that technology recedes in the background of everyday activities. the ubiquitous computing world is largely defined by applications, which present an altogether new set of requirements. in order to assess the impact of ubiquitous computing and discover caveats as early in the adoption process as possible, we need to study and analyze working prototypes applied in real-life settings and scenarios. the special track on ubiquitous computing applications, now in its third year, provides a forum for the discussion of all types of ubiquitous computing applications and related specialized infrastructures built for the deployment of targeted applications. individual papers place applications within their use context and introduce novel and appropriate interaction paradigms while at the same time addressing related technical and business aspects and consequently identify novel opportunities or constraints.
selective method combination in mixin-based composition. a mixin is a reusable module that provides uniform extensions and modifications to classes. it is an abstract subclass that is composable with a variety of superclasses. in mixin-based composition, however, the problem of accidental overriding arises. a method declared in a mixin may accidentally overrides its superclasses' method. to tackle this problem, we propose a new approach of method lookup that allows selective method combination; that is, when we have multiple methods with the same name and the same formal parameter types in a composition, we can select which method to execute, and which method is called when there exists a method call to super. this proposal is an extension of hygienic mixins with stronger expressive power. this proposal is implemented in mcjava, an extension of java with mixintypes. its compilation is achieved by source code translation to java thus making it runnable on a standard java virtual machine.
the effectiveness of combining information retrieval strategies for european languages. building an effective information retrieval system requires various design choices, ranging from the weighting scheme of the type of morphological normalization. the combination of runs has become a standard technique to reap the benefits of different run types. until now, systematic studies of the effectiveness of combination strategies have only been carried out for english. this paper provides an exploratory overview of the effectiveness of combination methods in nine european languages. we demonstrate that the combination of effective information retrieval strategies can lead to significant improvements of retrieval effectiveness. furthermore, we analyze the relative impact of retrieving more relevant documents and of improved ranking of relevant documents. the experimental evidence is obtained using the 2003 testsuite of the cross-language evaluation forum (clef).
transactional agent model for fault-tolerant object systems. a transactional agent is a mobile agent which manipulates objects in multiple computers by autonomously finding a way to visit the computers. the transactional agent commits only if its commitment condition like atomicity is satisfied in presence of faults of computers. on leaving a computer, an agent creates a surrogate agent which holds objects manipulated. a surrogate can recreate a new incarnation of the agent if the agent itself is faulty. if a destination computer is faulty, the transactional agent finds another operational computer to visit. after visiting computers, a transactional agent makes a destination on commitment according to its commitment condition. we discuss design and implementation of the transactional agent which is tolerant of computer faults.
smoothed fetching: bridging the data layout and transmission schemes in multimedia servers. typical block placement schemes generally assume ctl (constant time length) block size, one block read for each stream in a round, round-robin striping, and peak rate-based admission control. traditional smoothing schemes for stored continuous media objects do not consider the block layout of the storage system. hence, the combination of schemes from the two domains can introduce new challenges. in this paper, we present a server transmission delay problem that arises when traditional block placement and smoothing schemes are used at the same time in a continuous media server. to resolve the problem, we first present two simple straightforward solutions, server-side block prefetching and multiple block read, and then propose a new solution smoothed fetching. sf overcomes the defects of the other two schemes by exploiting a smoothing technique when retrieving blocks from disks and using a tight admission control algorithm. simulation results show that sf achieves the best performance among the three solutions.
text-based summarization and visualization of gene clusters. we present a system named medsummarizer which uses biomedical literature information to assign biological meaning to a cluster of genes. using relevant pubmed citations, it creates a ranked list of important biological concepts that describes the gene list. further, based on the assigned concepts, it computes similarity between each pair of genes and displays this using a graph based visualization technique. the system allows use of human curated index (e.g. mesh terms) as well as automatic annotations derived from free-text. we compare the results obtained using these two types of terms.
the time diversification monitoring of a stock portfolio: an approach based on the fractal dimension. diversification is a technique used to reduce the risk of investment and is accomplished by including uncorrelated and independent stocks in one's portfolio. by diversifying, the investor aims to reduce the risk of an entire portfolio depreciating in value, if a few of the assets within the portfolio are depreciated. in the past, the correlation coefficient has been used as a basis for diversification. however, the correlation coefficient is problematic since it can not capture nonlinear dependency, and analyzing pair-by-pair stocks in the portfolio does not always give the best estimation of diversification for the entire portfolio.in this paper we present a simple, but efficient methodology for monitoring portfolio diversification, which can capture most of the nonlinear phenomena in a portfolio. we propose a measurement of portfolio diversification through the fractal dimension parameter. monitoring this parameter in a time domain represents the basis for automatic detection of significant changes in portfolio diversification. when the fractal dimension is significantly reduced, the algorithm eliminates stocks that are highly correlated and adds new uncorrelated stocks to the portfolio. we tested our method using real historical stock data and obtained significant improvements in the time diversification of selected stock portfolios.
an adaptive tdma slot assignment protocol in ad hoc sensor networks. due to its ability to provide collision-free packet transmission regardless of the traffic load, tdma (time division multiple access) has been applied in ad hoc sensor networks. we have previously proposed a tdma slot assignment protocol that utilizes the channel bandwidth effectively in ad hoc sensor networks. however, in this protocol, the channel bandwidth cannot be fully utilized because the frame length across the whole network tends to increase. in this paper, we extend this protocol to further improve channel utilization. the extended protocol prevents the excessive increase of unassigned slots by minimizing each node's frame length. furthermore, we verify the effectiveness of our proposed protocols by simulation experiments. the results show that our extended protocol improves channel utilization dramatically in comparison with our previous protocol.
a call admission control scheme using genetic algorithms. next generation wireless systems (ngws) will provide a variety of services to mobile users including high speed data, real-time applications and real-time multimedia support with a certain quality of service (qos) level. an efficient handoff management is one of the key issues in order to support global roaming of the mobile users among different network architectures of the ngws.in this paper, a new call admission control scheme, genetic-based call admission control (gac), is proposed for ngws. the gac scheme uses genetic algorithms to achieve high network utilization, minimum cost, minimum handoff latency and mobile terminal's (mt) qos requirements. performance analysis is provided to assess the efficiency of the proposed gac scheme. simulation results show a significant improvement in handoff latencies and costs over the heuristic approach and other cac schemes.
semi-automatic design of agent organisations. multi-agent systems can be viewed as organisations of individual agents. designing an agent organisation is a complex process involving defining the structural relationships among agents, the lines of inter-agent communication, and the agent functionality. existing approaches to agent organisation design are difficult to apply in practice since they require designers to make decisions while working at a low level of abstraction.this paper contributes towards designing agent organisations in a practical and effective manner by proposing to semi-automate the organisational design process. the proposed semi-automatic approach enables agent system designers to reason at a high abstraction level and conveniently re-use previous design decisions. this semi-automatic approach to agent organisation design uses role modelling and a role algebra which captures a number of basic relations among roles. the role algebra's semantics are formally defined using a two-sorted algebra.the applicability of the semi-automatic agent organisation design approach is demonstrated by an example drawn from a case study involving telephone repair service teams.
enhancement of wavelet-based medical image retrieval through feature evaluation using an information gain measure. medical image retrieval covers a major application area, providing significant assistance in medical diagnosis. in this paper, several parameters for a wavelet-based retrieval system for hrct lung images are analyzed, in order to improve the performance of the system in terms of precision and retrieval time. the information gain measure is used to evaluate extracted features to find the features that have the most discriminating power across image disease classes. a weighted similarity metric based on the evaluation is used for image retrieval. the number of levels for wavelet decomposition is studied for 2 types of wavelets, haar and daubechies-8. a filtering criteria based on the features with the highest information gain is used to enhance the retrieval time. experiements on hrct lung images that cover 8 disease classes show that the weighted approach achieves about 10% improvement in the average disease class precision, and 4.75% in the average total system precision, over the unweighted approach. retrieval time is much enhanced while still maintaining high precision ratios.
sds-rules and association rules. the association rule expresses the relation between premise (antecedent) and consequence (succedent). the relation is given by a truth-condition, which can be verified on a given four-fold contingency table denoting the frequencies of objects in some matrix of analyzed data (not-)satisfying antecedent and succedent. this method is more general than the "classical" association rules mined by a-priori algorithm. various types of implication or equivalency can be expressed as well as relations corresponding to statistical hypotheses tests.this notion of association rules can be modified to describe interesting relations in couples of associated disjoint sets. let's have two boolean attributes defining two disjoint sets a and b and the third attribute describing some property of the objects. the sds-rule describes a relation among the sets a and b and the given property. the usual application (interpretation) is to find couples of sets that significantly differ in the given attribute or to find strong differences between given sets a and b. this paper describes the motivation of sds-rules, similarity with association rules and introduces some sds-quantifiers. later it describes how to define disjoint sets a and b using derived attributes of analyzed data matrix and gives some results of this method applied to medical data.
active electronic mail. network infrastructures have evolved tremendously over the last years, offering new capabilities to the applications in higher levels. email is a widely used communication tool that could benefit of an intelligent and active underlying network in order to support sophisticated services. we explore in this paper an infrastructure based on intelligent mobile agents and active networks, and point out how and where advanced features can be introduced to our current passive email platform in order to make it more flexible, open, secure, intelligent, and ubiquitous as possible.
an innovative approach to intelligent information filtering. information filtering is one of the most useful and challenging tasks for effective information access. it is concerned with dynamically adapting the distribution of information where both evolving user's interests and new incoming information are taken into account. in this paper, we present an innovative approach to text filtering based on the novelty detection principle. this approach relies on a specific learning model which allows both accurate online learning of user's profile and evaluation of the coherency of user's behaviour during his interaction with the system.we empirically analyse our approach and present experimental results on the reuters-21578 benchmark. the obtained results bring out a significant enhancement of performance as compared to the widely used rocchio's learning algorithm.
clustering of diverse genomic data using information fusion. genome sequencing projects and high-throughput technologies like dna and protein arrays have resulted in a very large amount of information-rich data. microarray experimental data are a valuable, but limited source for inferring gene regulation mechanisms on a genomic scale. additional information such as promoter sequences of genes/ dna binding motifs, gene ontologies, and location data, when combined with gene expression analysis can increase the statistical significance of the finding. this paper introduces a machine learning approach to information fusion for combining heterogeneous genomic data. this algorithm uses an unsupervised joint learning mechanism that identifies clusters of genes using the combined data. the correlation between gene expression time-series patterns obtained from different experimental conditions and the presence of several distinct and repeated motifs in their upstream sequences is examined here using publicly available yeast cellcycle data. the results show that the combined learning approach taken here identifies correlated genes effectively. the algorithm provides an automated clustering method, but allows the user to specify apriori the influence of each data type on the final clustering using probabilities.
solving the maximum clique problem by k-opt local search. this paper presents a local search algorithm based on variable depth search, called the k-opt local search, for the maximum clique problem. the k-opt local search performs add and drop moves, each of which can be interpreted as 1-opt move, to search a k-opt neighborhood solution at each iteration until no better k-opt neighborhood solution can be found. to evaluate our k-opt local search algorithm, we repeatedly apply the local search for each of dimacs benchmark graphs and compare with the state-of-the-art metaheuristics such as the genetic local search and the iterated local search reported previously. the computational results show that in spite of the absence of major metaheuristic components, the k-opt local search is capable of finding better (at least the same) solutions on average than those obtained by these metaheuristics for all the graphs.
reinforcement learning agents with primary knowledge designed by analytic hierarchy process. this paper presents a novel model of reinforcement learning agents. a feature of our learning agent model is to integrate analytic hierarchy process (ahp) into a standard reinforcement learning agent model, which consists of three modules: state recognition, learning, and action selecting modules. in our model, ahp module is designed with primary knowledge that human intrinsically should have in order to attain a goal state. this aims at increasing promising actions of agent especially in the earlier stages of learning instead of completely random actions as in the standard reinforcement learning algorithms. we adopt profit-sharing as a reinforcement learning algorithm and demonstrate the potential of our approach on two learning problems of a pursuit problem and a sokoban problem with deadlock in the grid-world domains, where results indicate that the learning time can be decreased considerably for the problems and our approach efficiently avoids the deadlock for the sokoban problem. we also show that bad effect that can be usually observed by introducing a priori knowledge into reinforcement learning process can be restrained by a method that decreases a rate of using knowledge during learning.
caching in web memory hierarchies. web cache replacement algorithms have received a lot of attention during the past years. though none of the proposed algorithms deals efficiently with all the particularities of the web environment, namely, relatively weak temporal locality (due to filtering effects of caching hierarchies), heterogeneity in size and origin of request streams. in this paper, we present the crf replacement policy, whose development is mainly motivated by two factors. the first is the filtering effects of web caching hierarchies and the second is the intention of achieving a balance between hit and byte hit rates. crf's decisions for replacement are based on a combination of the recency and frequency criteria in a way that requires no tunable parameters.
application modeling using reverse engineering techniques. in this work we present techniques and tools that enable effective reverse engineering procedures for web applications that were developed using the promising asp.net technology. we deal with model-driven development in its reverse aspect by implementing reverse engineering methods. our implemented methods model web applications using a well-known, web oriented and robust language, namely webml. this is, to the authors' best knowledge, a novel re-engineering transformation. in this paper we propose a method to reverse engineer web applications in order to extract their conceptual model using webml notation. moreover, we present an efficient tool we have developed in order to implement the proposed method, along with a study of the application of our tool to an exemplar, content-management web application. the overall results are quite encouraging and indicate that our approach is efficient.
a markov random field model of microarray gridding. dna microarray hybridisation is a popular high through-put technique in academic as well as industrial functional genomics research. in this paper we present a new approach to automatic grid segmentation of the raw fluorescence microarray images by markov random field (mrf) techniques. the main objectives are applicability to various types of array designs and robustness to the typical problems encountered in microarray images, which are contaminations and weak signal.we briefly introduce microarray technology and give some background on mrfs. our mrf model of microarray gridding is designed to integrate different application specific constraints and heuristic criteria into a robust and flexible segmentation algorithm. we show how to compute the model components efficiently and state our deterministic mrf energy minimization algorithm that was derived from the 'highest confidence first' algorithm by chou et al. since mrf segmentation may fail due to the properties of the data and the minimization algorithm, we use supplied or estimated print layouts to validate results.finally we present results of tests on several series of microarray images from different sources, some of them test sets published with other microarray gridding software. our mrf grid segmentation requires weaker assumptions about the array printing process than previously published methods and produces excellent results on many real datasets.an implementation of the described methods is available upon request from the authors.
modeling organizational goals: analysis of current methods. organizational change, whether it involves the development of a computerized system or the re-engineering of business processes, is a purposive activity driven by the goals of the involved stakeholders. its effectiveness depends on being able to make good decisions about what goals to pursue and on selecting the appropriate strategies for achieving the desired goals.this paper presents an analysis of existing goal modeling methods in terms of their focus, cognitive and social approach. the main findings include that (a) the applicability of each method depends on the characteristics of the particular organizational context and (b) additional benefits can be gained by integrating different methods.
emunet: a real-time network emulator. new protocols and network applications must be extensively tested before deployment on the internet. in this paper, we describe the design and implementation of emunet, a lightweight, portable, configurable, and extendable network emulator, which can be used to emulate a wide variety of network characteristics and conditions inside a laboratory environment. protocols and applications can be tested, without modification, directly on top of the emulated network. the emulator can be used to test protocols under a variety of conditions, such as bit rate limitation, network delay and jitter, bit error rate, different queuing schemes, etc. we show two examples of the use of the emulator to study the performance of voice-over-ip with asymmetric satellite links, and the impact of web caching and traffic compression on the experience of gprs users.
information agents cooperating with heterogenous data sources for customer-order management. as multi-agent systems and information agents obtain an increasing acceptance by application developers, existing legacy enterprise resource planning (erp) systems still provide the main source of data used in customer, supplier and inventory resource management. in this paper we present a multi-agent system, comprised of information agents, which cooperates with a legacy erp in order to carry out orders posted by customers in an enterprise environment. our system is enriched by the capability of producing recommendations to the interested customer through agent cooperation. at first, we address the problem of information workload in an enterprise environment and explore the opportunity of a plausible solution. secondly we present the architecture of our system and the types of agents involved in it. finally, we show how it manipulates retrieved information for efficient and facile customer-order management and illustrate results derived from real-data.
evaluating unstructured peer-to-peer lookup overlays. unstructured peer-to-peer lookup systems incur small constant overhead per single join or leave operation, and can easily support keyword searches. hence, they are suitable for dynamic failure-prone environments. in this paper, we define metrics for evaluating unstructured overlays for peer-to-peer lookup systems. these metrics capture the search dependability and efficiency, and the granularity at which one can control the tradeoff between the two, as well as fairness. according to these metrics, we evaluate different graphs and overlays, including a gnutella graph, a power law random graph, normal random graphs, a 3-regular random graph, and a 3-araneola overlay. our study shows that, according to our metrics, a 3-araneola overlay achieves the best results, and hence it is an excellent solution for flooding-based peer-to-peer lookup system.
architecture to support dynamic composition of math lesson plans. in this work we describe an architeture that supports the composition of web based lesson plans for math learning based on a database of fine grained mathematical components that can be tailored for communities of users. for this research, the principal target community of users is middle school mathematics teachers. our goal is to build a web accessible resource of pedagogical material for grades k-12 math that can be used and reused in a variety of contexts from teacher remediation to lesson preparation through to student use of the lesson. the web based lessons are generated on the fly from a database of fine grained components that include explanations, interactive activities, worksheets, images, videos, audio, faq's, online questions and challenges.
mona: an extensible framework for web document monitoring. this work presents an extensible architecture for fully-automated long-term monitoring of documents on the web. the framework enables easy coupling of existing search services of different kind, making the approach suitable for mixed environments (e.g. classic web and semantic web).the proposed architecture supports a process for repeated querying and classifying of documents based on a model of the domain of interest. in doing so, a well-organized version-controlled repository of documents is gradually built up.
web service selection mechanisms in the web service execution environment (wsmx). semantic web services provide a step forward in the search for automated integration of business partners. research in the area is mainly focused on describing, finding and using semantic web services. a major area that has received little attention is the process of choosing one service from a list of services that are known to fulfill the required functionality. this process is very important as different services may be available at different prices with different levels of reliability, security, accuracy etc. the selection of which service to use depends upon the requirements of the user, while one user may require high quality another may need low price. this paper presents a vision of selection mechanisms in the web service execution environment (wsmx), that can be used by individuals and the business community alike.
sec: a search engine for component based software development. the successfulness of the component-based development(cbd) process relies on several factors including the structuration of the component repositories and the comparison procedures for interface exploring while comparing the expected and the provided services. both functional and non-functional aspects should be considered. this paper presents a discovery ontology to organize components in a repository and an integration ontology to integrate a component into an application. in addition, we propose a search engine, called sec for cbd, which uses the discovery ontology to automatically locates and presents a list of software components that could be used in the current development situation. this search engine consists of a persistent and an intelligent component which automatically generates a query from developer specification and indexes a repository of software components. sec is not only suitable to discover components, but also able to automatically classify the selected components using the subsumption notion.
scalable security and accounting services for content-based publish/subscribe systems. content-based publish/subscribe systems offer an interaction scheme that is appropriate for a variety of large scale dynamic applications. however, widespread use of these systems is hindered by a lack of suitable security services. in this paper we present scalable solutions for confidentiality, integrity, and authentication for these systems. we also provide usage-based accounting services, which are required for e-commerce and e-business applications that use publish/subscribe systems. our solutions are applicable in a setting where publishers and subscribers may not trust the publish/subscribe infrastructure.
sels: a secure e-mail list service. exchange of private information content among a large number of users via e-mail list services is becoming increasingly common. in this paper we address security requirements in that setting and develop a new protocol, sels (a secure e-mail list service) that provides confidentiality, integrity, and authentication for e-mails exchanged via lists. in addition, sels also protects against the use of lists for e-mail spamming. we have developed a prototype of sels in java, and integrated it with the eudora e-mail client.
performance bottleneck in time-series subsequence matching. this paper addresses a performance bottleneck in time-series subsequence matching. first, we analyze the disk access and cpu processing times required during the index searching and post-processing steps of subsequence matching through preliminary experiments. based on their results, we show that the post-processing step is a main performance bottleneck in subsequence matching. in order to resolve the performance bottleneck, we propose a simple yet quite effective method that processes the post-processing step. by rearranging the order of candidate subsequences to be compared with a query sequence, our method completely eliminates the redundancies of disk accesses and cpu processing occurring in the post-processing step. we show that our method is optimal and also does not incur any false dismissal. also, we justify the effectiveness of our method by extensive experiments.
optimization of subsequence matching under time warping in time-series databases. this paper discusses effective processing of subsequence matching under time warping in time-series databases. time warping is a transformation that enables finding of sequences with similar patterns even when they are of different lengths. through a preliminary experiment, we first point out that naive-scan, a basic method for processing of subsequence matching under time warping, has its performance bottleneck in the cpu processing step. for optimizing this step, in this paper, we propose a novel method that eliminates all possible redundant calculations. it is verified that this method is not only an optimal one for processing naive-scan, but also does not incur any false dismissals. our experimental results showed that the proposed method can make great improvement in performance of subsequence matching under time warping. especially, naive-scan, which has been known to show the worst performance, performs much better than lb-scan as well as st-filter in all the cases by employing the proposed method for cpu processing. this result is interesting and valuable in that the performance inversion among naive-scan, lb-scan, and st-filter has occurred by optimizing the cpu processing step, which is their common performance bottleneck.
an effective document clustering method using user-adaptable distance metrics. document clustering is inherently an unsupervised learning process that organizes document (or text) data into distinct groups without depending on pre-specified knowledge. however, real-world applications, such as building a topical hierarchy for a large document collection, need to perform clustering under various kinds of constraints. this paper presents a new type of supervised clustering to organize information in a way that reflects knowledge provided by a user. as a means by which external human knowledge can be incorporated into the clustering process, a quadratic form distance metric is employed that contains a weight matrix. also, we propose a way of representing knowledge to guide the clustering process and a variant of the gradient descent search technique to find a user-specific weight matrix under the hierarchical clustering strategy.
xquery speedup using replication in mapping xml into relations. in this paper, we introduce some replication methods that reduce the query cost incurred when reconfiguring xml documents from divided xml data. the fundamental idea is that query performance can be enhanced by analyzing query patterns and replicating data essential for the query performance. several practical and effective replication methods are formulated. a translation process in which xquery is rewritten into sql using this replication information is performed by a heuristic method, which shows that existing methods, such as the sorted outer union, may be extended to utilize the replicas. finally, some experiments show that these replication methods can be very useful.
similarity measurement for aggregation of spatial objects. svg (scalable vector graphics) is increasingly important to display multimedia data over the internet. although svg is powerful in exchange, transformation, and rendering of image data, it has still the weakness of content-based component-sensitive image search mainly because it does not provide yet the descriptors of (component) image objects and their spatial relationships. also, although similarity matches have been studied for long, similarity measurements for images that contain component image objects are not successfully developed. in this paper, we describe a new approach of a similarity measurement of aggregated image objects.
shape-based retrieval of similar subsequences in time-series databases. this paper deals with the problem of shape-based retrieval in time-series databases. the shape-based retrieval is defined as the operation that searches for the (sub)sequences whose shapes are similar to that of a given query sequence. in this paper, we propose an effective and efficient approach for shape-based retrieval of subsequences. we first introduce a new similarity model for shape-based retrieval that supports various combinations of transformations such as shifting, scaling, moving average, and time warping. for efficient processing of the shape-based retrieval, we also propose the indexing and query processing methods. to verify the superiority of our approach, we perform extensive experiments with the real-world s&p 500 stock data. the results reveal that our approach successfully finds all the subsequences that have the shapes similar to that of the query sequence, and also achieves significant speedup over the sequential scan method.
strong pseudonymous communication for peer-to-peer reputation systems. in this paper we present a novel approach to enable untraceable communication between pseudonyms. our work provides strong sender and recipient anonymity by eliminating the need to know of each other's address.we use a variation of chaum mixes to achieve unlinkability between sender and recipient and introduce a concept called extended destination routing (edr) which relies on routing headers constructed in multiple layers of encryption and published in a distributed hash table (dht). in order to communicate, a sender requests from the dht the recipient's routing header, which is extended and used for routing the message via a mix cascade to this recipient.this work was performed in the context of the unitec reputation system and describes the functionality of its anonymous communication layer, which is completely independent of the other unitec layers. although trust and reputation systems in general are typical application areas for our contribution, the presented concepts are suitable for various other application areas as well. we have implemented a prototype of unitec and present the first results from an ongoing evaluation in our network emulation testbed.
vistaclara: an interactive visualization for exploratory analysis of dna microarrays. we have created vistaclara to explre the effectiveness of applying an extended permutation matrix to the task of exploratory data analysis of multi-experiment microarray studies. the permutation matrix is a visualization technique for interactive exploratory analysis of tabular data that permits both row and column rearrangement, and fits well with the tabular forms of data characteristic of gene expression studies. however, this technique has been largely overlooked by current bioinformatics research. our implementation supports direct incorporation of supplemental data and annotations into the matrix view. this enables visually searching for patterns in gene expression measurements that correlate with other types of relevant data (disease classes, clinical, histological, drug treatments, etc.). the heatmap visualization common in microarray analysis is extended to provide a novel alternative using size as well as color to graphically represent experimental values, thus allowing more effective quantitative comparisons. methods to sort rows or columns by similarity extend the possible permutation operations, and allow more efficient searching for biologically relevant patterns in very large data sets. based on overview+detail principles, a dynamic compressed heatmap view of the entire data set provides the user with overall context, including possible correlations not currently visible in the more detailed view. combined, these techniques make it possible to perform highly interactive ad hoc visual explorations of microarray.
noxes: a client-side solution for mitigating cross-site scripting attacks. web applications are becoming the dominant way to provide access to on-line services. at the same time, web application vulnerabilities are being discovered and disclosed at an alarming rate. web applications often make use of javascript code that is embedded into web pages to support dynamic client-side behavior. this script code is executed in the context of the user's web browser. to protect the user's environment from malicious javascript code, a sand-boxing mechanism is used that limits a program to access only resources associated with its origin site. unfortunately, these security mechanisms fail if a user can be lured into downloading malicious javascript code from an intermediate, trusted site. in this case, the malicious script is granted full access to all resources (e.g., authentication tokens and cookies) that belong to the trusted site. such attacks are called cross-site scripting (xss) attacks.in general, xss attacks are easy to execute, but difficult to detect and prevent. one reason is the high flexibility of html encoding schemes, offering the attacker many possibilities for circumventing server-side input filters that should prevent malicious scripts from being injected into trusted sites. also, devising a client-side solution is not easy because of the difficulty of identifying javascript code as being malicious. this paper presents noxes, which is, to the best of our knowledge, the first client-side solution to mitigate cross-site scripting attacks. noxes acts as a web proxy and uses both manual and automatically generated rules to mitigate possible cross-site scripting attempts. noxes effectively protects against information leakage from the user's environment while requiring minimal user interaction and customization effort.
context-aware filtering for collaborative web systems: adapting the awareness information to the user's context. we propose a context-based filtering process which aims at adapting the awareness information delivered to mobile users by collaborative web systems. this filtering process relies on a model of context which integrates both a physical and an organizational dimensions and allows to represent the user's current context as well as general profiles. these profiles are descriptions of user's potential contexts and express the awareness information filtering rules to apply when the user's current context matches one of them. these rules reflect the user's preferences given a context. we describe how the filtering process performs in two steps, one for identifying the general profiles that apply, and a second for selecting the awareness information. we also discuss the patterns matching algorithms used in the filtering process to compare the contexts descriptions.
compensating creativity in the digital world: reconciling technology and culture. new proposals on compensatory mechanisms and viability of traditional practices for online environment is currently being considered by the european union and are subject of heated academic debate. simultaneously new business models for distribution of intellectual property online are emerging rapidly. the paper focuses on the failures of the current compensatory mechanisms, as well as new proposals to compensate the creative in the online environment, including current online distribution practices, universal levy proposals -- internet access and traffic levies, blank media levies, voluntary compensation systems, as well as traditional practices of the collecting societies, effects of the content protection technologies (drm) on the accessibility and fair use of information online. the paper suggests the set of features for the new compensatory system, including socio-economic aspects of the different societies, and the need of uniform and worldwide compensatory system. conclusions support the necessity to revise current compensatory mechanisms, centering on the proposed features, rather than just technological mechanisms, which dominate the current political agenda.
an evaluation system for news video streams and blogs. when we want information on current events, we often view news programs on tv or news streams on web sites. a news video stream consists of several scenes, and viewers often gain a broad understanding of the news by viewing scenes in the given order. since a viewer's opinion of a news topic will depend on the scene order, we have developed a method for extracting blog entries expressing a particular point of view regarding news topics where we use a form of evaluation and categorization similar to that based on news scene order. in this paper, we describe our method of news evaluation based on news scene order and explain how a blog search can be done using a news stream.
an architecture for information retrieval over semi-collaborating peer-to-peer networks. peer-to-peer (p2p) networking is aimed at exploiting the potential of widely distributed information pools and its effortless access and retrieval irrespectively of underlying networking protocols, operating systems of devices. however, prohibiting limitations have been identified and perhaps the most important one is the successful location of relevant information sources and the efficient query routing in large, highly distributed p2p networks. in this paper, a novel, cluster-based architecture for ir over p2p networks is presented and its evaluation is focused on retrieval effectiveness. we reason in favour of using clustering for p2p ir, by considering two fundamental hypotheses drawn from current p2p file-sharing systems. we also study the potential usefulness of a simplified version of dempster-shafer (d-s) theory of evidence combination for results fusion in the network. we simulated the ir behavior of the system by using the trec 6 and 7 ad-hoc track. the proposed architecture bears very promising results in terms of precision and recall.
nicemeetvr: facing professional baseball pitchers in the virtual batting cage. in this paper, we introduce a new virtual baseball batting training system called nicemeet vr, which enable batters to face a variety of baseball pitchers. the pitching motions are obtained using the video-based motion capture system called krops, which enable users to capture the 3d human motion from a single view video sequences. the batter holds a bat with a reflector attached to the sweet spot, and stands in front of the screen where the pitching motions are projected. no real baseball is actually thrown. instead, a 3d virtual ball is rendered over the screen. the batter swings the bat toward the ball when it reaches the home-base. the trajectory of the swung bat is analyzed using dual supply photoelectric sensors behind the screen, that cast and also detect the infra red beam reflected by the bat. using our system, the player can practice batting against any pitcher, such as top professional major league pitchers, or famous pitchers in the past by capturing their motion from videos.
multidimensional support vector machines for visualization of gene expression data. dna microarray technology has helped us to understand the biological system because of its ability to monitor the expression levels of thousands of genes simultaneously. since dna microarray experiments provide us with huge amount of gene expression data, they should be analyzed with statistical methods to extract the meanings of experimental results.for visualization and class prediction of gene expression data, we have developed a new svm-based method called multidimensional svms, that generate multiple orthogonal axes. this method projects high dimensional data into lower dimensional space to exhibit properties of the data clearly and to visualize the distribution of the data roughly. furthermore, the multiple axes can be used for class prediction. the basic properties of conventional svms are retained in our method: solutions of mathematical programming are sparse, the optimal solutions can always be found due to its convexity, and nonlinear classification is implemented implicitly through the use of kernel functions. the application of our method to the experimentally obtained gene expression datasets for patients' samples indicates that our algorithm is efficient and useful for visualization and class prediction.
bias-free hypothesis evaluation in multirelational domains. in machine learning one typically assumes that the true classification of an object depends only on the object itself and given the object, is independent of the classification of other objects. in this case, setting aside a sufficiently large and randomly chosen part of the training data as a test set, the observed sample error on the test set is an unbiased estimator of true error. however, in many application settings, those mainstream approaches to model evaluation might be inappropriate. as pointed out by [2], among others, whenever there is autocorrelation, i.e., whenever the target value of one object depends not only on the object itself, but also on other objects' classifications or information that is shared between objects, observed error on a randomly chosen test set may not be an unbiased estimator anymore. we introduce a sampling technique, generalized subgraph sampling, that avoids a bias in error estimation by establishing the required amount of linked objects in the test set.
statistical properties of the simulated time horizon in conservative parallel discrete-event simulations. we investigate the universal characteristics of the simulated time horizon of the basic conservative parallel algorithm when implemented on regular lattices. this technique [1, 2] is generically applicable to various physical, biological, or chemical systems where the underlying dynamics is asynchronous. employing direct simulations, and using standard tools and the concept of dynamic scaling from non-equilibrium surface/interface physics, we identify the universality class of the time horizon and determine its implications for the asymptotic scalability of the basic conservative scheme. our main finding is that while the simulation converges to an asymptotic nonzero rate of progress, the statistical width of the time horizon diverges with the number of pes in a power law fashion. this is in contrast with the findings of ref. [3]. this information can be very useful, e.g., we utilize it to understand optimizing the size of a moving "time window" to enforce memory constraints.
computing the cube of an interval matrix is np-hard. in many practical applications, we are interested in computing the product of given matrices and/or a power of a given matrix. in some cases, the initial matrices are only known with interval uncertainty. it turns out that under this uncertainty, there is a principal difference between the product of two matrices and the product of three (or more) matrices:&bull; on the one hand, it is more or less known that the problems of computing the exact range for the product of two matrices - and for the square of a matrix - are computationally feasible;&bull; on the other hand, we prove that the problems of computing the exact ranges for the product of three matrices - and for the third power of a matrix - are np-hard.
a constraint solver for sequences and its applications. constraint programming techniques are successfully used in various areas of software engineering for industry, commerce, transport, finance etc. constraint solvers for different data types are applied in validation and verification of programs containing data elements of these types. a general constraint solver for sequences is necessary to take into account this data type in the existing validation and verification tools. in this work, we present an original constraint solver for sequences implemented in chr and based on t. fr&uuml;hwirth's solver for lists with the propagation of two constraints: generalized concatenation and size. the applications of the solver (with the validation and verification tool bztt) to different software engineering problems are illustrated by the example of a waiting room model.
structured information retrieval in xml documents. query languages that take advantage of the xml document structure already exist. however, the systems that have been developed to query xml data explore the xml sources from a database perspective. this paper examines an xml collection from the viewpoint of information retrieval (ir). as such, we view the xml documents as a collection of text documents with additional tags and we attempt to adapt existing ir techniques to achieve more sophisticated search on xml documents. we employ a class of queries that support path expressions and suggest an efficient index, which extends the inverted file structure to search xml documents. this is accomplished by integrating the xml structure in the inverted file by combining the inverted file with a path index. the proposed structure is a lexicographical index, which may be used for the evaluation of queries that involve path expressions. moreover, this paper discusses a ranking scheme based on both the term distribution and document structure. some performance remarks are also presented.
bambootrust: practical scalable trust management for global public computing. global public computing platforms, such as planetlab, grid computing systems, and xenoservers, require facilities for managing trust to allow their participants to interact effectively in an open and untrusted environment. in this paper, we describe bambootrust, a practical, high-performance distributed trust management system for global public computing platforms. we present our peer-to-peer architecture, based on the xenotrust model and the bamboo distributed hash table. we describe the initial bambootrust implementation and deployment, and demonstrate that the system performs and scales more than adequately well by means of experimental evaluation.
field study on methods for elicitation of preferences using a mobile digital assistant for a dynamic tour guide. knowing tourists' individual preferences provides the possibility to offer personalized tours. the challenge is to capture these preferences using a mobile device. during a field study in g&ouml;rlitz three methods for elicitation were evaluated by computing the correlation between the tourists' and the algorithms' rankings. the results served to clarify fundamental questions en route to develop a personal tour guide. 1) is it possible to seed a general interest profile in the mobile context with all its distractions that allows the accurate prediction of actual rankings of sights? 2) are the interest profiles sufficiently diverse to base personalized tours on individual interest profiles instead of interest prototypes? 3) how do personalized tours affect the spatial behavior of tourists, do they really visit a broader set of attractions than before? analyzing the interest profiles gives an insight into their actual diversity, discusses their necessity and helps simulating an improved distribution of tourists at a destination.
ubiquitous presence systems. instant messaging has become a part of our daily live. instant communication, either with a mobile device or with a computer based application, is an increasingly used form of communication. in this paper we analyze how current instant messaging can be extended to a new and more general form of what we call 'ubiquitous presence systems'. we discuss how ubiquitous presence systems become a part of our daily live, extending the current systems, which only use states like 'online' and 'away', to location- and context-aware systems. we present the design space for ubiquitous presence systems together with a classification of those systems. we discuss information acquisition and also shortly address related privacy issues. we present an architecture for connecting arbitrary devices into the presence system, according to the vision of ubiquitous computing. we conclude the paper by presenting a fully working and deployed prototypical implementation following the developed architecture.
cathedrals, libraries and bazaars. the open source and open standards movements are sometimes confused and sometimes clash. this seems unfortunate as they are both vital to the growing acceptance of technology and have much to offer each other. expanding on the metaphors offered by eric raymond in his paper "the cathedral and the bazaar," this essay describes the similarities and differences between the concepts of open source and open standards. openness has a very different meaning as applied to software programs or technical standards. as this essay attempts to explain, the open source and open standards movements are most closely related by their desire to allow competition to thrive based on merit, not market dominance.
application run time estimation: a quality of service metric for web-based data mining services. the emergence of application service providers (asp) hosting internet-based data mining services is being seen as a viable alternative for organisations that value their knowledge resources but are constrained by the high cost of data mining software. response time is an important quality of service (qos) metric for web-based data mining service providers. the ability to estimate the response time of data mining algorithms apriori benefits both clients and service providers. the advantage for the clients is that it helps to impose qos constraints on the service level agreements and the benefit for the service-providers is that it facilitates optimising resource utilisation and scheduling. in this paper we present a novel rough sets based technique for identifying similarity templates to estimate application run times. we also present experimental results and analysis of this technique.
service specific anomaly detection for network intrusion detection. the constant increase of attacks against networks and their resources (as recently shown by the codered worm) causes a necessity to protect these valuable assets. firewalls are now a common installation to repel intrusion attempts in the first place. intrusion detection systems (ids), which try to detect malicious activities instead of preventing them, offer additional protection when the first defense perimeter has been penetrated. id systems attempt to pin down attacks by comparing collected data to predefined signatures known to be malicious (signature based) or to a model of legal behavior (anomaly based).anomaly based systems have the advantage of being able to detect previously unknown attacks but they suffer from the difficulty to build a solid model of acceptable behavior and the high number of alarms caused by unusual but authorized activities. we present an approach that utilizes application specific knowledge of the network services that should be protected. this information helps to extend current, simple network traffic models to form an application model that allows to detect malicious content hidden in single network packets. we describe the features of our proposed model and present experimental data that underlines the efficiency of our systems.
reducing borders of k-disjunction free representations of frequent patterns. a number of concise lossless representations of frequent patterns were proposed. except for closed patterns, all other representations of patterns consist of a main component and a border. recently, a unifying framework was introduced that treats border representations as particular cases of so called k-disjunction free representations. it was shown that careful splitting of borders into subgroups allows deletion of some of such subgroups without making the representations lossy. in this paper, we propose a new method of border reduction. our method consists in identifying patterns in the main representation's component that uniquely determine a possibly maximal subset of patterns from the group under reduction. such itemsets are redundant and can be deleted from border's groups. the performed experiments show that the new method reduces border representations by up to two orders of magnitude.
biomap: toward the development of a knowledge base of biomedical literature. biological literature databases continue to grow rapidly with vital information that is important for conducting sound biomedical research. as data and information space continue to grow exponentially, the need for rapidly surveying the published literature, synthesizing, and discovering the embedded "knowledge" is becoming critical to allow the researchers to conduct "informed" work, avoid repetition, and generate new hypotheses. knowledge, in this case, is defined as one-to-many and many-to-many relationships among biological entities such as gene, protein, drug, disease, etc. the knowledge discovery process basically involves identification of biological object names, reference resolution, ontology and synonym discovery, and finally extracting object-object relationships. the overall goal of this work is to investigate and develop a complete knowledge base, called biomap, using the entire medline collection of (over 12 million) bibliographic citations and author abstracts from over 4600 biomedical journals worldwide and to develop an interactive knowledge network for users to access this secondary knowledge (biomap) along with its primary databases such as the medline. in this paper we present the organization of a distributed database system to maintain the knowledge base of biomap and some preliminary results on biological object name identification problem based on an initial set of 30,000 medline abstracts.
evaluation of rule-based modularization in model transformation languages illustrated with atl. this paper studies ways for modularizing transformation definitions in current rule-based model transformation languages. two scenarios are shown in which the modular units are identified on the base of the relations between source and target metamodels and on the base of generic transformation functionality. both scenarios justify modularization by requiring adaptability and reusability in transformation definitions. to enable representation and composition of the identified units, a transformation language must provide proper modular constructs and mechanisms for their integration. we evaluate several implementations of the scenarios by applying different transformation techniques: usage of explicit and implicit rule calls, and usage of rule inheritance. atlas transformation language (atl) is used to illustrate these implementations. the experience with these scenarios shows that current languages provide a reasonably full set of modular constructs but may have problems in handling some composition tasks.
text mining agent for net auction. net auctions have been widely utilized with the recent development of the internet. however, it is a problem that there are too many items for bidders to select the most suitable one. we aim at supporting the bidders on net auctions by automatically generating a table which contains the features of several items for comparison. we construct a system called ntm-agent(net auction text mining agent). the system collects web pages of items and extracts the items' features from the pages. after that, it generates a table which contains the extracted features. this research focuses on two problems in the process. the first problem is that if the system collects items automatically, the results contain the items which is different from the items of the user's target. the second problem is that the descriptions in net auctions are not uniform (there are different formats such as sentences, items and tables. the subjects of some sentences are omitted.). therefore, it is difficult to extract the information from the descriptions by conventional methods of information extraction. this research proposes methods to solve the problems. for the first problem, ntm-agent filters the items by correlation rules about the keywords in the titles and the item descriptions. these rules are created semi-automatically by a support tool. for the second problem, ntm-agent extracts the information by distinguishing the formats. it also learns the feature values from plain examples for the future extraction.
a case study on building cots-based system using aspect-oriented programming. more and more software projects are using cots (commercial-off-the-shelf) components. using cots components brings both advantages and risks. to manage some risks in using cots components, it is necessary to increase the reusability of the glue-code so that the problematic cots components can easily be replaced by other components. aspect-oriented programming (aop) claims to make it easier to reason about, develop, and maintain certain kinds of application code. to investigate whether aop can help to build an easy-to-change cots-based system, a case study was performed by comparing changeability between an object-oriented application and its aspect-oriented version. results from this study show that integrating cots component using aop may help to increase the changeability of the cots component-based system, if the cross-cutting concerns in the glue-code are homogenous (i.e., consistent application of the same or very similar policy in multiple places). extracting heterogeneous or partial homogenous crosscutting concerns in glue-code as aspects does not provide benefits. results also show that some limitations in aop tools may make it impossible to use aop in cots-based development.
light-weight service-oriented grid application toolkit. grid has been focused in a distributed computing community. there has been a lot of research in these areas, especially for design and development of grid middleware. more recently, the service-oriented architecture based on web services rapidly became a major issue. the service-oriented architecture provides a modularized functionality to grid applications. however, this new technology has some limitations. web services basically works with the soap protocol, but it is not suitable for massive scientific data. in this paper, we propose mage, modular and adaptive grid environment, which is uses dynamically reconfigurable component architecture with interfaces. mage provides several level of transparency to the grid application development, and it can dynamically reconfigure its architecture to adapt to heterogeneous grid environments.
inference of transcriptional regulation relationships from gene expression data. we propose a new method for finding potential regulatory relationships between pairs of genes from microarray time series data and apply it to expression data for cell-cycle related genes in yeast. we compare our algorithm, dubbed the event method, with the earlier correlation method and the edge detection method by filkov et al. when tested on known transcriptional regulation genes, all three methods are able to find similar numbers of true positives. the results indicate that our algorithm is able to identify true positive pairs that are different from those found by the two other methods. we also compare the correlation and the event methods using synthetic data and find that typically, the event method obtains better results.
another step towards a smart compilation manager for java. in a recent work we have proposed a compilation strategy (that is, a way to decide which unchanged sources have to be recompiled) for a substantial subset of java which has been shown to be sound and minimal. that is, an unchanged source is recompiled if and only if its recompilation produces a different binary or an error. however, that model does not handle two features of java, namely, compile-time constant fields (static final fields initialized by a compile-time constant of a primitive type or string) and unreachable code, which turn out to be troublesome for having a sound and minimal compilation strategy. to our best knowledge these two features, probably because of their low-level nature, have been omitted in all models of java separate compilation written so far. yet, a compilation strategy for full java has to deal with them. thus, in this paper we analyze the implications of handling compile-time constant fields and unreachable code, and extend our previous model in order to handle these two features as well.
introducing safe unknown types in java-like languages. most mainstream object-oriented languages, like c++, java and c#, are statically typed. in recent years, untyped languages, in particular scripting languages for the web, have gained a lot of popularity notwithstanding the fact that the advantages of static typing, such as earlier detection of errors, are widely accepted. we think that one of the main reasons for their widespread adoption is that, in many situations, the ability of ignoring types can be handy to write simpler and more readable code.we propose an extension of java-like languages which allows developers to forget about typing in strategic places of their programs without losing type-safety. that is, we allow programmers to write simpler code without sacrificing the advantages of static typing. this is achieved by means of inferred type constraints. these constraints describe the implicit requirements on untyped code to be correctly invoked.this flexibility comes at a cost: field accesses and method invocations on objects of unknown types are less efficient than regular field accesses and method invocations. also, our type system is currently more restrictive than it should be; its extension is the subject of ongoing work. however, the novel approach presented here is quite interesting on its own, as it supports separate compilation and there is zero runtime overhead on code which does not take advantage of the new features.
cost efficient broadcast based cache invalidation for mobile environments. to improve the performance of mobile computers, a number of broadcast based cache invalidation schemes have been proposed in the past to support object locality. however most of these schemes have focused on providing support for client disconnection and reducing query delay. the size of invalidation reports and the effect of invalidating items cached by many clients are also important issues that must be addressed in order to provide cost-efficient cache invalidation in a mobile environment. in this paper, we propose two techniques, validation-invalidation reports (vir) and the delayed requests scheme (drs) to address these issues. vir uses a combination of validation and invalidation reports, allowing the server to construct and broadcast smaller reports at each interval, thus improving downlink channel utilization. drs addresses the problem where multiple clients request for the same data items. it introduces a "cool down" period after an invalidation, to reduce the number of uplink requests sent by clients. simulation results show that compared to the original ts approach [1], the proposed schemes lower transmission cost associated with cache invalidation by between 5%-25% in the downlink channel and between 10%-40% in the uplink channel.
from satisfiability to consistency through certificates: application to partially defined constraints. in this paper, we propose a method to automatically derive a filtering algorithm from a constraint expressed by its satisfiability function. we give an application of the technique in the field of machine learning in which partially defined constraints are learned by decision trees.
bbq: group-based querying in a ubiquitous environment. the cost of sending queries to a server is high for mobile ubiquitous hosts. to address this, we adopt query consolidation mechanism, by exploiting the knowledge of similar queries generated by neighboring hosts to the server, especially in location-dependent applications. we propose a group-based query processing scheme, where group members are close in location and moving direction, to collectively deliver the aggregate querying need from members to the server. a leader or boss elected within each group is responsible for gathering and consolidating data requests from members, within an adaptive query listening period. we conducted simulated experiments to study the performance improvement with our scheme.
solving strategies using a hybridization model for local search and constraint propagation. hybridization of local search and constraint programming techniques for solving constraint satisfaction problems is generally restricted to some kind of master-slave combinations for specific classes of problems. in this paper we study combination strategies at a finer hybridization grain, based on a theoretical model for hybridization of local search and constraint propagation. in this framework, hybrid resolution can be achieved as the computation of a fixpoint of some specific reduction functions. some experimental results show the interest of the model to design such hybridizations.
trading services in ontology-driven markets. in order to realize the vision of a full-fletched service oriented architecture efficient service discovery and allocation is required to coordinate the interplay between service providers and requesters. this paper presents the architecture of an ontology-driven market for trading semantic web services. an auction schema is enriched by a set of components enabling semantics based matching as well as price-based allocations. moreover, an approach for reducing the complexity of the auction system by means of background knowledge is proposed.
a ubiquitous computing environment for aircraft maintenance. ubiquitous computing bears a high potential in the area of aircraft maintenance. extensive requirements regarding quality, safety, and documentation as well as high costs for having aircrafts idle during maintenance demand for an efficient execution of the process. major weaknesses that impact the efficiency of the process are an inadequate tool management, human erros, and labour intensive manual documentation and check procedures. in this paper we propose a solution using ubiquitous computing technologies that improves aircraft maintence and provides a high level of usability. a scenario, a systems architecture, and maintenance applications are presented. the smart toolbox and the smart tool inventory were implemented as proof of concept.
innovative computational methods for transcriptomic data analysis. the tools of molecular biology and the evolving tools of genomics can now be exploited to study the genetic regulatory mechanisms that control cellular responses to a wide variety of stimuli. these responses are highly complex, and involve many genes and gene products. the main objectives of this paper are to describe a novel research program centered on understanding these responses by developing powerful graph algorithms that generate distilled gene sets, producing high performance implementations utilizing cutting-edge platforms, employing these implementations to identify gene sets suggestive of coregulation, and performing sequence analysis and genomic data mining to examine, winnow and highlight the most promising gene sets for more detailed investigation. as a case study, we describe our work aimed at elucidating genetic regulatory mechanisms that control cellular responses to low dose ionizing radiation (ir). we use genome-scale gene expression data after ir exposure in vivo to identify the pathways that are activated or repressed as a tissue responds to the radiation insult. knowledge of these pathways should help clarify and interpret physiological responses to ir, which will advance our understanding of how ir exposures pose an increased risk to human health.
person identification from heavily occluded face images. in numerous occasions there is need to identify subjects shown in heavily occluded face images. typical examples include the recognition of criminals whose facial images are captured by surveillance cameras. in such cases a significant part of the subjects face is occluded making the process of identification extremely difficult, both for automatic face recognition systems and human observers. in this paper we propose a face recognition algorithm, which can be used for identifying individuals with hidden facial parts. during the face recognition procedure, occluded facial regions are detected so that the model-based face recognition algorithm implemented makes use of information only from the non-occluded facial regions. with our approach information from occluded facial regions is not utilized during the process of face recognition hence the occlusions do not destruct the recognition process and as a result the probability of achieving correct identification is improved.
applying information visualization techniques to capture and explore the course of cognitive behavioral therapy. tracking and especially comparing psychotherapeutic processes is a complex task involving a large number of individual and complexly related parameters. therefore, descriptive and classical statistical methods are only suited for partial analyses. to overcome these limitations we introduce linkvis, a new information visualization (infovis) tool used to visualize and evaluate psychotherapeutic processes. linkvis is developed and clinically tested on the basis of cognitive behavioral therapy treating anorectic girls. the user gets new insight into the data under investigation due to the combination of three different visualization techniques: scatterplots, chernoff faces, and parallel coordinates. linkvis supports exploring of complex time-dependent data in order to gain more information about the psychotherapeutic process, especially when comparing different patients and groups.
building the functional performance model of a processor. in this paper, we present an efficient procedure for building a piecewise linear function approximation of the speed function of a processor with hierarchical memory structure. the procedure tries to minimize the experimental time used for building the speed function approximation. we demonstrate the efficiency of our procedure by performing experiments with a matrix multiplication application and a cholesky factorization application that use memory hierarchy efficiently and a matrix multiplication application that uses memory hierarchy inefficiently on a local network of heterogeneous computers.
a multi-agent approach for solving optimization problems involving expensive resources. in this paper, we propose a multi-agent approach for solving a class of optimization problems involving expensive resources, where monolithic local search schemes perform miserably. more specifically, we study the class of bin-packing problems. under our proposed fine-grained agent system scheme, rational agents work both collaboratively and selfishly based on local search and mimic physics-motivated systems. we apply our approach to a generalization of bin-packing - the inventory routing problem with time windows - which is an important logistics problem, and demonstrate the efficiency and effectiveness of our approach.
personalizing information gathering for mobile database clients. mobile agents are ideal for mobile computing environments because of their ability to support asynchronous communication and flexible query processing since tasks can be delegated to mobile agents when a mobile client is disconnected. this paper explores the use of mobile agents in personalizing information gathering for mobile database clients. personalized data take the form of materialized views and personalization is provided in the form of view maintenance options. these options, expressed using an extended sql create view command, offer a finer grain of control and balance between data availability and currency, the amount of wireless communication and the cost of maintaining consistency. the paper defines recomputational consistency and introduces new levels of materialized view consistency to better characterize the mobile client view currency customizations.
breaking value symmetries in matrix models using channeling constraints. multi-aspect assignment problems (maps) can be naturally formulated into various matrix models of constraint satisfaction problems (csps), which can contain both variable and value symmetries, using different viewpoints. while variable symmetry breaking constraints can be expressed relatively easily and executed efficiently by enforcing lexicographic ordering, value symmetry breaking constraints are difficult to formulate. we show when value symmetries in one viewpoint correspond to variable symmetries in another, and when symmetry breaking constraints in two viewpoints are consistent. our results allow tackling value symmetries efficiently using additional viewpoints and channeling constraints. experiments on the social golfer problem and a variant of the quasigroup existence problem confirm the benefits of our proposal against conventional methods.
investigating software measures to improve product reliability. inevitably, faults are introduced whilst software is being developed. if we can catch the faults before the system goes live we can improve the quality of the system and reduce the cost of maintaining the system. in this paper we have calculated software metrics from the testing and maintenance phases of the development of a software system. we are going to analyse this data and suggest some improvements that can be made to the software process to reduce the number of faults that are getting into the maintenance phase.
trasformers-by-example: pushing reuse in conceptual web application modelling. when defining a scheme of a web application, modelers repeatedly perform modelling tasks like "after having defined an entity type, add a page class for displaying the entity type's content". thereby, a scheme is extended again and again in a similar manner. it would therefore be convenient for modelers to have transformers that, when applied to a scheme, perform such tasks.in this paper, we present the language tbe (transformers-by-example) which allows defining transformers for webml schemes by example, i.e. by giving an example of what is desired instead of specifying operations for achieving the result. the notation of transformers is thereby similar to one with which modelers are familiar. further, each application of a transformer to a scheme can be parameterized such that the corresponding modelling task will be performed only within a specified part of the scheme. this makes it easy for modelers to define and apply transformers.
automated conversion from requirements documentation to an object-oriented formal specification language. in software engineering there have been very few attempts to automate the translation from a requirements document written in a natural language (nl) to one of the formal specification languages. one of the major reasons for this challenge comes from the ambiguity of the nl requirements documentation because nl depends heavily on context. we use contextual natural language processing (cnlp) to overcome the ambiguity in nl, and two-level grammar (tlg) to construct a bridge between a nl requirements specification and a formal specification in vdm++, an object-oriented extension of the vienna development method. the result is a system for mapping natural language requirements documents into an object-oriented formal specification language.
on optimal temporal locality of stencil codes. iterative solvers such as the jacobi and gauss-seidel relaxation methods are important, but time-consuming building blocks of many scientific and engineering applications. the performance problems are largely due to cache misses, and can be reduced by tiling the codes. whereas previous research has shown the usefulness of tiling by experimentally comparing the run times of tiled and original codes, it did not tackle the question as to whether further improvements are possible. in this paper, we give a negative answer, regarding the exploitation of temporal locality in one step of a 2-dimensional stencil code. we derive upper and lower bounds that match up to a factor of about 1 + 2/m, where m is the cache size. for the upper bounds, we investigate some modifications of tiling.
geographical information access for non-structured data. this paper presents the virtual itineraries in pyrenees (piv) project. spatial and temporal unified models are proposed to give a formal representation to geographical information. the aim is to improve the access to local cultural and heritage document collections. the models take into account characteristics of heterogeneous human expression modes: written language and captures of drawings, maps, pictures, etc. semantic treatments have been built to automatically manage spatial and temporal information from non-structured data. these treatments are added to classical information extraction (ie) approaches. then, geographical information retrieval processing is based on geographical information systems (gis) algorithms. these algorithms look for any relations between formal representations of geographic information in documents collections and similar representations in a user query. finally we propose a prototype implementing such geographic ie and geographic information retrieval (ir).
a framework of individually-focused teleconferencing (ift) via an efficient 3d reprojection technique. in this paper, we propose a framework on individually-focused teleconferencing (ift) which is supported by an efficient 3d reprojection technique. the goal of designing ift is to provide sufficient 3d pose information to each teleconference participant in order to establish lively communication in a teleconference on low-bandwidth internet. a novel ift deployment and an efficient 3d reprojection technique are two major contributions of this paper. our 3d reprojection technique uses a mirror reference view in three-view epipolar geometry. it overcomes the inefficiency in previous techniques and provides visually good recovery of pose information of teleconference participants even though it is theoretically an approximation scheme.
identify amino acid candidates critical for function of rat imidase by cross-reference voting in imidase superfamily. it is a useful strategy to understand structure-function relationship of proteins by aligning and analyzing their sequences. database search techniques that can extract the functional or structural information from amino acid sequence are urgently needed. imidase superfamily provides an interesting case for developing such method. imidase super family contains a variety of related proteins that differ in functions and sequence identities. we developed a cross-reference voting algorithm with complexity o(nm2), where n is the number of total sequences and m is the maximum lenght of the sequence, to identify amino acid candidates that are critical for function of rat imidase. after analyzing more than 80 members of imidase superfamily, several amino acid residues of rat imidase are selected and examined. his67, his69, lys159, his192, his248 and asp326 of rat imidase are found corresponding to critical residues of hydantoinase studied by site-directed mutagenesis and structure information of hydantoinase. his67, his69, asp100, his217, his248, his420 and his459 of rat imidase are found corresponding to critical residues of dihydroorotase and allantoinase in separate studies. these results indicated that our algorithm could successfully extract functionally related amino acid candidates in imidase superfamily.
a concurrent reactive esterel processor based on multi-threading. esterel is a concurrent synchronous language for developing reactive systems. as an alternative to the classical software and hardware synthesis paths, the reactive processing approach uses a specialized processor with an instruction set tailored to esterel. a principal difficulty when compiling onto a reactive processor is the faithful, efficient implementation of concurrency. this paper presents a novel reactive processor architecture based on multi-threading, which allows the arbitrary nesting of preemption and concurrency, and is scalable to very high degrees of concurrency.
missing requirements and relationship discovery through proxy viewpoints model. this paper addresses the problem of "missing requirements" in software requirements specification (srs) expressed in natural language. due to rapid changes in technology and business frequently witnessed over time, the original srs documents often experience the problems of missing, not available, and hard-to-locate requirements. one of the flaws in earlier solutions to this problem has no consideration for missing requirements from multiple viewpoints. furthermore, since such srs documents represent an incomplete domain model, mannual discovery (identification and incorporation) of missing requirements and relationships is highly labor intensive and error-prone. consequently, deriving and improving an efficient adaptation of srs changes remain a complex problem. in this paper, we present a new methodology entitled "proxy viewpoints model-based requirements discovery (pvrd)". the pvrd methodology provides an integrated framework to construct proxy viewpoints model from legacy status requirements and supports requirements discovery process as well as efficient management.
efficient discovery of unique signatures on whole-genome est databases. expressed sequence tags (est) are widely used for the discovery of new genes, particularly those involved in human disease processes. a subsequence in an est dataset is unique if it appears only in one est sequence of the dataset but does not appear in any other est sequence. the unique subsequences can be regarded as signatures that distinguish an est from all the others, and provide valuable information for many applications, such as pcr primer designs and microarray experiments. the discoveries of unique signatures on large-scale est datasets are previously computational challenges. in this paper, we propose two efficient algorithms to extract the unique signatures from est databases. the algorithms perform impressive discovery efficiencies in the experiments on real human ests.
a seriate coverage filtration approach for homology search. the homology search within genomic databases is a fundamental and crucial work in biological knowledge discovery. with exponentially increasing size and access of databases, the issues of efficient retrieval become more essential in bioinformatics. due to the varieties of biological data, similar sequences are not only under some error tolerance, but are also above some seriate coverage level. in this paper, we propose a seriate coverage filtration approach to extract the homologies from the databases efficiently. our approach performs a lossless filtration and can be implemented as a preprocess of the existing search heuristics. our method converts a user's requests for error and seriate coverage levels to some thresholds of interest. accordingly, we transform the work of homology discovery to a variation of the longest increasing subsequence problem, and design an efficient counterpart algorithm. in the performance test, it is found that our approach has an attractive quality of filtration.
xvm: xml virtual machine. xml is an emerging standard for data representation and data exchange on the internet. xml-based web applications have been widely used in e-commerce and enterprise information management. in this paper, we propose an extensible, integrated xml processing architecture, the xml virtual machine (xvm). the xvm provides a framework for processing xml data, developing and deploying xml-based applications. by using a component-based technique, the xvm provides a high degree of modularity and reusability. xvm components are dynamically loaded and composed during xml data processing. new components can be easily added to existing applications and new applications can reuse existing components without difficulty. these features enable an xml application to keep up with requirements and schema evolution and to process compound documents. both client-side and server-side xml applications can be developed and deployed in an integrated way. also in this paper, we present an xml application container built on top of the xvm, along with several sample applications.
rearranging data objects for efficient and stable clustering. when a partitional structure is derived from a data set using a data mining algorithm, it is not unusual to have a different set of outcomes when it runs with a different order of data. this problem is known as the order bias problem. to overcome this problem, the first clustering process proceeds to construct an initial partition. the partition is expected to imply the possible range in the number of final clusters. we apply center sorting to the data objects in the clusters of the partition to rearrange them in a new order. the same clustering procedure is reapplied to the newly arranged data set to build a new partition. we have developed an algorithm, reit, that achieves both efficiency and reliability. a number of experiments have been performed to show that the algorithm helps minimize the order bias effects.
local search with annealing-like restarts to solve the vehicle routing problem with time windows. in this paper, we propose a metaheuristic based on annealing-like restarts to diversify and intensify local searches for solving the vehicle routing problem with time windows (vrptw). using the solomon's benchmark instances for the problem, our method obtained 7 new best results and equaled 19 other best results. extensive comparisons indicate that our method is comparable to the best published literatures.
data sharing protocols for smt processors. although there are many real-time task synchronization protocols designed for uniprocessor and multiprocessor systems, most of them do not fit the needs in accommodating simultaneous multithreading (smt). real-time synchronization protocols are expected to bound the maximum number of priority inversions and to meet task deadlines. synchronization protocols for simultaneous processing need to explore the possibility in executing multiple tasks at the same time to increase the system concurrency level to utilize the abundant computing resources, of simultaneous multithreading computer systems. this work proposes the concept of "lp-time inheritance" to manage the period of blocking time without significantly decreasing the level of task parallelism. the schedulability tests for the proposed protocol are also presented.
distributed ipv6 addressing technique for mobile ad-hoc networks. connecting to the internet through the nodes of an ad-hoc network is very challenging and necessary. we studied a manet topology in which all nodes in this manet need to be connected to the internet through a special node called the internet gateway. traditional ipv6 duplicate address detection(dad) process cannot be applied for this topology without any modification. in this paper, we propose a stateful ipv6 auto-configuration scheme that can replace dhcpv6 for ad-hoc networks. our simulation shows that this scheme is lighter and faster than dhcpv6.
a hybrid ai approach for nurse rostering problem. this paper presents a hybrid ai approach for a class of overconstrained nurse rostering problems. our approach comes in two phases. the first phase solves a relaxed version of problem which only includes hard rules and part of nurses' requests for shifts. this involves using a forward checking algorithm with non-binary constraint propagation, variable ordering, random value ordering and compulsory backjumping. in the second phase, adjustments with descend local search and tabu search are applied to improved the solution. this is to satisfy the preference rules as far as possible. experiments show that our approach is able to solve this class of problems well.
evaluation of current architecture frameworks. with the growing importance of enterprise architecture the discussion about how to create or choose the right enterprise architecture framework for a specific organization arose quickly. but it is not only a question of choosing the right framework for describing or developing an enterprise architecture. it is more important to discover whether the chosen architecture framework meets the defined requirements or not. in this paper, we describe which requirements currently existing architecture frameworks should meet to constitute a useful procedure that enables to develop, describe and keep up an enterprise architecture. our evaluation of current frameworks shows their lacks and identifies further improvement.
implementing an embedded gpu language by combining translation and generation. dynamic languages typically allow programs to be written at a very high level of abstraction. but their dynamic nature makes it very hard to compile such languages, meaning that a price has to be paid in terms of performance. however under certain restricted conditions compilation is possible. in this paper we describe how a domain specific language for image processing in python can be compiled for execution on high speed graphics processing units. previous work on similar problems have used either translative or generative compilation methods, each of which has its limitations. we propose a strategy which combine these two methods thereby achieving the benefits of both.
a multi-agent algorithm for vehicle routing problem with time window. many existing algorithms for solving the vehicle routing problem with time windows (vrptw) first construct initial tours and then apply a tour optimization algorithm to refine the solution. in this two-stage approach, the tour optimization stage is often hampered by the tour construction phase that produce initial solutions that are skewed, namely, the initial tours are very good, but the later tours are often very poor. this often leads to difficulties in the tour-optimization stage that often get trapped in local optimal quickly. in this paper, we propose a new multi-agent algorithm for solving the vrptw that involves the uses a distributed, multi agent approach for the tour-optimization phase. our approach can be considered as a combination of multi-agent system and heuristic local search. a prototype system has been developed and extensive experimentation on the solomon benchmarks show that our multi-agent approach is effective and has comparable performance to the best results in the literature.
use of correctness assertions in declarative diagnosis. we use assertions to reduce the quantity of queries in declarative diagnosis of logic programs. we first present a declarative diagnoser for normal logic programs. given a bug symptom, the diagnoser first constructs a tree that models the execution of the bug symptom and then searches the tree for the bug that causes the bug symptom. we then incorporate into the diagnoser three tree transformations that prune the tree before it is searched. these transformations make use of two kinds of assertion about the correctness of the program and maintain the soundness and completeness of the diagnoser. these transformations reduce the size of the tree and thus reduce the quantity of queries imposed on the oracle.
on the fuzzy bayesian inference of population annoyance level caused by noise exposure. too many people suffer from noise levels that scientists and health experts consider to be unacceptable, where most people become annoyed, where sleep is disturbed and where adverse health effects are to be feared. the present paper centers on inferring individuals annoyance level caused by noise exposure. the starting point of our thoughts is the impossibility of assigning an exact number to observed values. observed sound level values are imprecise. although sound level meters are more and more accurate, they cannot assign yet an exact number to an observed value. really, we assume that actually, no exact number can be assigned to a sound level observed value. if our interest lies in maximum effects of the propagation of this imprecision, an interval-based approach seems to be adequate. anyway, although in a nearly future we could fill these gaps, it seems better to think about a time interval and its associated data-interval corresponding to the observed sound level range. although we revised a maximum likelihood solution, the aim of this paper is to discuss how imprecision of observation values is propagated when fuzzy bayesian inference for these non-precise observations is carried out.
grid resource discovery based on semantic p2p communities. grid technologies enable the sharing of a wide variety of resources. the full use of these resources requires effective resource discovery mechanisms. however, the complicated and dynamic characteristics of grid resources make sharing and discovering them a challenge. in this paper, we propose a semantic community approach to enable efficient resource discovery in grids. the system clusters nodes into communities according to their semantic properties. the community construction and maintenance is fully decentralized and self-organizing. this structure helps prune the searching space and reduce the cost of searching. the system exhibits many desirable properties: it supports complex queries and is fully decentralized, scalable, and efficient. our simulation results show how searching the grids can take advantage of semantic communities to reduce searching costs and improve the quality of results.
mobile real-time read-only transaction processing in data broadcast environments. data broadcast is a widely accepted data dissemination method for mobile computing systems. when data broadcast is used to deliver frequently updated data to mobile read-only transactions, we call it updates dissemination. existed updates dissemination protocols are unsuitable for mobile real-time read-only transaction processing since they neglect the time constraints on both data and transactions. in this paper a new updates dissemination protocol called hybrid forward multi-version data broadcast (hfmvb) is proposed. hfmvb not only guarantees the consistency of read-only transactions, it also provides higher data currency and lower miss rate by shortening the consistency interval, instantly broadcasting updates and making use of broadcast on-demand.
editorial message: special track on mobile computing and applications. riding on the success of the 2003 and 2004 mobile computing and applications track, we are pleased to present the 2005 mobile computing and applications track that features research papers drawn from a highly diversified spectrum of mobile computing. we have continued to receive a significant number of submissions this year. the papers collected in this track cover three different and yet complementary areas: mobile data management that realizes the applications of the mobile computing paradigm, under the system integration efforts provided by middleware to support mobile computing, that necessarily depends on the concrete mobile data communication research work. in particular, special attention was dedicated to draw upon research efforts and expertise from different areas of research, so as to promote better synergy and to bring forth not only core communication and sensor technologies that lay the research foundation, but also important research applications to realize the benefits of anywhere, any place and anytime pervasive and ubiquitous computing.
editorial message: special track on mobile computing and applications. riding on the success of the 2003 and 2004 mobile computing and applications track, we are pleased to present the 2005 mobile computing and applications track that features research papers drawn from a highly diversified spectrum of mobile computing. we have continued to receive a significant number of submissions this year. the papers collected in this track cover three different and yet complementary areas: mobile data management that realizes the applications of the mobile computing paradigm, under the system integration efforts provided by middleware to support mobile computing, that necessarily depends on the concrete mobile data communication research work. in particular, special attention was dedicated to draw upon research efforts and expertise from different areas of research, so as to promote better synergy and to bring forth not only core communication and sensor technologies that lay the research foundation, but also important research applications to realize the benefits of anywhere, any place and anytime pervasive and ubiquitous computing.
using recursive classification to discover predictive features. finding most predictive features for statistical classification is a challenging problem and has important applications. support vector machines (svms), for example, have been found successful with a recursive procedure in selecting most important genes for cancer prediction. it is not well understood, however, how much the success depends on the choice of the classifier, and how much on the recursive procedure. we answer this question by examining multiple classifiers (svm, ridge regression and rocchio) with feature selection in recursive and non-recursive settings, on a dna microarray dataset (amlall) and a text categorization benchmark (reuters-21578). we found recursive ridge regression most effective: its best classification performance (zero error) on the amlall dataset was obtained when using only 3 genes (selected from over 7000), which is more impressive than the best published result on the same benchmark - zero error of recursive svm using 8 genes. on reuters-21578, recursive ridge regression also achieves the best result ever published (the improvement was verified in a significance test). an in-depth analysis of the experimental results shows that the choice of classifier heavily influences the recursive feature selection process: the ridge regression classifier tends to penalize redundant features to a much larger extent than the svm does.
editorial message: special track on mobile computing and applications. riding on the success of the previous mobile computing and applications track in 2003 to 2005, we are delighted to present the 2006 mobile computing and applications track that features research papers drawn from a highly diversified spectrum of mobile computing. we have continued to receive a significant number of submissions this year. the papers collected in this track cover three different and yet complementary areas: mobile communications that forms the basis for higher level applications, inclusive of mobile data management as a support for practical mobile applications. in particular, special attention was dedicated to draw upon research efforts and expertise from different areas of research, so as to promote better synergy and to bring forth not only core communications and modeling that support data management policies to lay the foundation for application development, but also important research applications to realize the benefits of anywhere, any place and anytime pervasive and ubiquitous computing.
improving the performances of proxy cache replacement policies by considering infrequent objects. in this paper, we perform a careful study of the effect of infrequent objects on the performance of many well-known web proxy cache replacement policies including lru, lfu, gdsf, and lfd (an offline policy). using a "frequency-aware" version of these policy (one that is aware of these infrequent objects), we show that significant improvement in the performance (hit rates and byte hit rates) can potentially be achieved. we also present lru-pred, which is a modified lru replacement policy that attempts to predict single access objects that it will not cache. the algorithm, though simple, achieve better performance than lru. the results are encouraging and point to more research on designing more sophisticated replacement policies that can predict infrequent objects.
mining maximal frequent intervals. many real world data are associated with intervals of time or distance. mining frequent intervals from such data allows the users to group transactions with similar behavior together. previous work only focuses on the problem of mining frequent intervals in a discrete domain. this paper first proposes the notion of maximal frequent intervals, which are superior to frequent intervals in many perspectives, and then provides a method for mining maximal frequent intervals in either a discrete domain or a continuous domain. experimental results indicate that our method outperforms previous method for mining frequent intervals, and improves the runtime by two orders of magnitude for databases with a large number of distinct endpoints.
a new distributed data mining model based on similarity. distributed data mining (ddm) has been very active and enjoying a growing amount attention since its inception. current ddm techniques regard the distributed data sets as a single virtual table and assume there exists a global model which could be generated if the data were combined/centralized. this paper proposes a similarity-based distributed data mining(sbddm) framework which explicitly take the differences among distributed sources into consideration. a new similarity measure is introduced and its effectiveness is then evaluated and validated. this paper also illustrates the limitations of current ddm techniques through three concrete case studies. finally distributed clustering within the sbddm framework is also discussed.
adaptive data dissemination and caching for edge service architectures built with the j2ee. the deployment of distributed enterprise applications and e-business solutions, that leverage edge service architectures across wide area networks, require flexible and adaptable models for data dissemination and caching. in this paper we present the design of an architecture that streamlines the integration of proactive data dissemination and caching into e-commerce solutions built with the java 2 enterprise edition. the utilization of an adaptive push and pull approach combined with the flexible and transparent design leads to an infrastructure that facilitates the development of efficient communication strategies for business participants. well defined interfaces significantly simplify the evaluation and analysis of adaptive data dissemination and caching strategies that utilize application specific semantics to minimize network traffic and maximize temporal coherency.
using a genetic algorithm to optimize the gape of a snake jaw. ga's have more success with optimizing a single configuration than with optimizing multiple configurations with connectivity constraints tying them together, i.e., variable geometry problems such as designing the variable geometry wings of a plane. this paper describes a ga based approach to solve variable geometry optimization problems where (a) the connectivity requirement cannot be easily specified or tested, (b) the space of configurations is made up of multiple disconnected spaces, thus making it likely that a ga would find sets of configurations that are not connected and (c) the cost of testing for connectivity, while examining each pair of configurations, is prohibitive. the approach has been tested and evaluated on a problem from computational biology, modeling the bones of a snake jaw.
manpower scheduling with time windows. in this paper, we propose a manpower allocation model with time windows which is of practical interest to serviceman scheduling operations. specifically, this problem originates from peculiar port yard scheduling needs where demand is generated from locations in the yard for servicemen who are dispatched from a central point and where the objectives are to minimize the number of servicemen scheduled, travel distances, travel times and waiting times at each location. although closely related to the well-known vehicle routing problem, this problem is different while its solution could provide insight to the latter. we develop solutions using metaheuristic methods, and in particular provide tabu-embedded simulated annealing and squeaky wheel optimization with local search algorithms for this problem. we apply these newly-developed metaheuristics with adaptations for solutions to the manpower allocation problem, while our analysis throws light on how these work. computational results are reported which show the effectiveness of our approach when applied to the manpower allocation problem.
the container loading problem. this paper addresses single and multiple container loading problems. we propose to use dynamic prioritization to handle awkward box types. the box type with a higher priority will be packed onto lower surfaces of the container, or packed in earlier containers. the solution found in one iteration of the algorithm is analyzed, and the priorities are updated to be used in the next iteration. our algorithm outperformed all previous methods using standard benchmark data sets. we found the existing test data for the multiple container loading problem to be deficient and supplemented them by generating new test data consisting of 2800 test cases. the results from our algorithm using this data set are excellent.
heuristic methods for graph coloring problems. in this work, the graph coloring problem and its generalizations - the bandwidth coloring problem, the multicoloring problem and the bandwidth multicoloring problem - are studied. a squeaky wheel optimization with tabu search heuristic is developed and experiments using benchmark geometric test cases show that the algorithm performs well for these problems and achieves results for the bandwidth multicoloring problem which improve on results obtained by other researchers.
a back-end for ghc based on categorical multi-combinators. &mu;tcmc is an abstract graph reduction machine for the implementation of lazy functional languages. categorical multi-combinators served as a basis for the evaluation model of &mu;tcmc. this paper presents the implementation of a haskell compiler, using the front-end of the glasgow haskell compiler (ghc) and a new back-end based on the &mu;tcmc abstract machine. a number of code optimisations are introduced to &mu;tcmc. the performance of our implementation is benchmarked against the glasgow haskell compiler, one of the most efficient haskell compilers available.
maximum likelihood based classification for the microstructure of human sleep. in this paper a classifier for the microstructure paradigm of human sleep, the cyclic alternating pattern sequence (caps), is presented. sleep electroencephalogram (eeg) is the signal used for the scoring. an eeg model makes the feature extraction (pre-processing). the caps phases are then detected using maximum likelihood (ml) estimation. a final processing block checks caps context rules. this system was tested with good results on the record of 8 hours sleep of a normal adult subject.
web services: separation of concerns: computation coordination communication. the purpose of this paper is to investigate the use of a new concept in component communication, expressed by the channel based coordination language called &rho;ε&omega; in the coordination of web services. the role of &rho;ε&omega; is to construct and manage connectors. connectors are patterns of connected channel communicators. the communication and coordination of components lying over a distributed address space has been dealt so far with stream or datagram connections created and controlled by the participating calculation and coordination components. web services can take advantage of the &rho;ε&omega; channel system that separates the communication issue using components that have independent sink and source ports that can be attached to web services components, thus overcoming the problem of compatibility in distributed systems. the flow of information is entirely regulated by the channel interconnections.
editorial message: special track on handheld computing. handheld computing is an emerging mobile computing paradigm that promotes using handheld wireless devices (or mobile devices) such as cellular phones and personal digital assistants (pdas) to accomplish various computing tasks. as handheld devices continue to appear in many forms with diverse functionalities, handheld computing will become the dominant computing paradigm in many fields including education, enterprises, and healthcare.
special track on handheld computing. handheld computing is an emerging mobile computing paradigm that promotes using handheld wireless devices (or mobile devices) such as cellular phones and personal digital assistants (pdas) to accomplish various computing tasks. as handheld devices continue to appear in many forms with diverse functionalities, handheld computing will become the dominant computing paradigm in many fields including education, enterprises, and healthcare.
supporting efficient query processing on compressed xml files. xml has been widely accepted as the de facto format for data representation and exchange. however, it is also known for the excessive information redundancy in its representation. while various compression schemes have been proposed and some of them can support query processing over compressed files, it is usually inevitable to perform partial (or full) data decompression which is expensive and in some cases may dominate the query processing time.in this paper, we propose a new xml compression scheme based on the sequitur compression algorithm. by organizing the compression result as a set of context free grammar rules, the scheme supports efficient processing of xpath queries without decompression. the experimental results show that this scheme achieves comparable compression ratio as gzip while its query processing time is among the best of existing algorithms.
network traffic anomaly detection based on packet bytes. hostile network traffic is often "different" from benign traffic in ways that can be distinguished without knowing the nature of the attack. we describe a two stage anomaly detection system for identifying suspicious traffic. first, we filter traffic to pass only the packets of most interest, e.g. the first few packets of incoming server requests. second, we model the most common protocols (ip, tcp, telnet, ftp, smtp, http) at the packet byte level to flag events (byte values) that have not been observed for a long time. this simple system detects 132 of 185 attacks in the 1999 darpa ids evaluation data set [5] with 100 false alarms, after training on one week of attack-free traffic.
on handling conflicts between rules with numerical features. rule conflicts can arise in machine learning systems that utilise unordered rule sets. a rule conflict is when two or more rules cover the same example but differ in their majority classes. this conflict must be solved before a classification can be made. the standard methods for solving this type of problem are to use naive bayes to solve the conflict or using the most frequent class (cn2). this paper studies the problem of rule conflicts in the area of numerical features. a novel family of methods, called distance based methods, for solving rule conflicts in continuous domains is presented. an empirical evaluation between a distance based method, cn2 and naive bayes is made. it is shown that the distance based method significantly outperforms both naive bayes and cn2.
editorial message: special track on document engineering. document engineering is a discipline within computer science that investigates systems for documents in any form and in all media. document engineering is concerned with principles, tools and processes that improve our ability to create, manage, store, compact, access and maintain documents. the fields of document recognition and retrieval have grown rapidly in recent years. this development has been fueled by the emergence of new application areas such as the world wide web (www), digital libraries, and video- and camera-based ocr. the use of ocr is spreading from high-volume, niche domains to more general tasks, including the processing of noisy "real-world" documents, photocopies, and faxes.
a process for separation of crosscutting grid concerns. this paper describes how to explicitly separate crosscutting grid concerns in a parallel java application. this process, named gridaspecting, uses a restricted subset of the java threads model for application decomposition, and aspect-oriented programming for allowing parallel execution of the application's threads as grid tasks. as a result of the process, all grid-related code is encapsulated in aspects, thus improving the application's modularity. in addition, by relying on java's native concurrency abstractions the process simplifies the grid programming model and makes it possible to test a grid application even without the grid.
editorial message: special track on document engineering. document engineering is a discipline within computer science that investigates systems for documents in any form and in all media. document engineering is concerned with principles, tools and processes that improve our ability to create, manage, store, compact, access and maintain documents. the fields of document recognition and retrieval have grown rapidly in recent years. this development has been fueled by the emergence of new application areas such as the world wide web (www), digital libraries, and video- and camera-based ocr. the use of ocr is spreading from high-volume, niche domains to more general tasks, including the processing of noisy "real-world" documents, photocopies, and faxes.
dynamic structuring of web information for access visualization. the internet has led to the formation of a global information infrastructure. to explore a web site, a site map would be useful as a short cut for a user to locate for the target information in a structured and efficient manner, rather than drilling into the web site following hyperlinks, reading possibly irrelevant information. useless information impacts a mobile web environment, where mobile clients are only connected with unreliable wireless channels of limited bandwidth. structured web page organization at the web server proxy is an important issue to resolve to provide efficient browsing experience for web clients, while minimizing the browsing of unrelated pages or sites. in this paper, we adopt the document information extraction mechanism to construct a document cluster dynamically and intelligently with respect to a requested root web page. the document cluster works like a dynamic site map, spanning across several web sites. the clusters are generated and stored in xml format at proxy server so that it can potentially benefit a large number of mobile clients. clients process the xml clusters and transform them to be visualized through vrml or dom. for vrml, a transformer is built at the client-side to support a three-dimensional modeling view. for dom, javascript is used for accessing the parsed xml data to produce a two-dimensional tree output.
automatic language identification of written texts. language identification is one of the search keys of most widespread use in the internet. this article describes efficient and easily extensible solutions to the problem of identifying the language of written texts based on closed grammatical classes. an identification tool was developed for recognizing texts written in portuguese, spanish, french and english.
comparisons of file formats for image transmission through networks. this paper presents a comparative analysis of the three most important progressive file formats: png, jpeg and jpeg2000.
a small-world model of the human mind. we propose a model of the human mind from first principles and introspection. we then try to represent that model as a semantic network. finally, we hypothesize that the key for the intelligent processing of information might be to consider that the semantic network graph to be a kind of small-world.
supporting transparent evolution of component interfaces. component-oriented programming facilitates the development of reusable application parts encapsulated by well-defined interfaces. there is however a tension between compatibility and evolution, since the interface of a component may constrain refactoring or require manual development of multiple, ad-hoc adaptation layers when an interface is evolved. we here present the declarative language vidl for specifying component interface evolution. vidl allows evolution of components with automatic generation of efficient adapter code that statically guarantees interface compatibility with other components that rely on anterior versions of the interface.
a uml model consistency verification approach based on meta-modeling formalization. uml language provides a promising way to overcome software system complexity. in particular, uml is a unified language that handles different aspects of software modeling. however, its features are not independent which is the source of numerous inconsistencies. present consistency checking techniques are limited either to certain uml features or to certain kinds of inconsistencies. our study aims at developing a unified checker which is able to handle all inconsistencies on all uml features. this paper develops the translation from uml models to clp (constraint logic programming) clauses taking advantage of meta-modeling techniques. clp is also used to express consistency rules. then clp solver can automatically detect inconsistencies.
modeling and execution of e-learning resources. this poster tries to motivate a specific part of a holistic modeling approach for e-learning with the help of business engineering on a technical level. business engineering defines generic and holistic methodologies and modeling methods for constructing an organizational memory for a complex environment. not only aspects of how to run a business from an organizational point of view have to be modeled but also techniques of how to implement business processes technically. emerging technologies coming from the semantic web and web-services communities leverage great potential to support the execution of business engineering environments especially when thinking of business-to-business contracts integrating business and supply-chain flows among several trading partners. with the help of advisor&copy; - an e-learning modeling platform with a visual modeling interface - a specific part of the engineering lifecycle within an e-learning scenario can be realized: advisor&copy; is able to transform the modeled learning pool into rdf compliant resources. prototypical test-beds to process the modeled learning resources with the help of a web-services execution environment enable queries of any soap enabled requestor - regardless of the platform.
dl-cotf: an xml based digital library for u. s. navy's operational test and evaluation force. this paper describes the development of the xml based digital library (dl-cotf) for the united states navy's operational test and evaluation command (comoptevfor). comoptevor tests new systems (weapons, ships, aircraft, etc.) that industry develops and dependent upon test results, the navy purchases. each development spans several years and has a large number of documents in various formats. these related documents that all belong to a specific program are required to be available electronically to aid workflow, provide controlled dissemination, facilitate document discovery, and ensure achieves are maintained as personnel leave the organization. as a solution we have developed xmlcot, an xml based language, to describe the family of files related to a specific programs as digital objects with a complex structure. the search tools to permit secondary users to find specific the files, retrieve them and simultaneously view the storage structure that provides addition meaning also use the same structure. to support interoperability with other digital libraries, the dl-cotf will present its metadata in compliance with the open archive initiative (oai). a key feature of this digital library environment is its ability to publish, search (discovery), navigate the complex digital objects and dynamically tailor the objects structure within the digital library.
recursive, object-oriented structures for molecular modeling. in this paper, we present a molecular modeling approach based on recursive object-oriented class instances. our approach allows ease of use by the scientist and includes a heuristic for evaluating molecular interaction and rendering at multiple levels of detail. our implementation in c++ employs abstractions to encapsulate the implementation and details of the computations. visualization is accomplished with opengl or the visualization toolkit (vtk), an application-independent scientific visualization library.
making tuple spaces physical with rfid tags. in this paper, we describe the design and implementation of a tuple-based distributed memory realized with the use of rfid technology. the key idea - rooted in a more general scenario of pervasive and mobile computing - is that our everyday environments will be soon pervaded by rfid-tagged objects. by accessing in a wireless way the re-writable memory of such rfid tags according to a tuple-based access model, it is possible to enforce mobile and pervasive coordination and improve our interactions with the physical world. an application example is presented to outline the potential of the approach.
an evaluation of conceptual business process modelling languages. conceptual business process modelling languages (bpmls) express certain aspects of processes (e.g. activities, roles, interactions, data, etc.) and address different application areas. to evaluate bpmls, a general framework is required. although a lot of bpmls are available in research and industry, an established evaluation framework as well as a comprehensive evaluation of bpmls is missing. to bridge this gap, we propose a generic meta-model that captures a wide range of process concepts and evaluate seven bpmls based on this meta-model.
self-maintained distributed tuples for field-based coordination in dynamic networks. field-based coordination is a very promising approach for a wide range of application scenarios in modern dynamic networks. to implement such an approach, one can rely on distributed tuples injected in a network and propagated to form a distributed data structure to be sensed by application agents. however, to gain the full benefits from such a coordination approach, it is important to enable the distributed tuples to preserve their structures despite the dynamics of the network. in this paper, we show how a variety of self-maintained distributed tuple structures for field-based coordination can be easily programmed in the tota middleware. several examples clarify the approach, and performance data is presented to verify its effectiveness.
towards a corporate performance measurement system. corporate performance measurement is focused too strongly on the traditional functional structure of an organisation and business processes are not measured systematically. basically, business processes are designed to transform organisational strategies into operation and create a result of value to customers. as a business process is performed by a group of organisational units, processes and the organisational structure are interdependent. consequently, their performance must not be measured in isolation. this paper illustrates how a data warehouse can be used to facilitate a corporate performance measurement system by the integration of business process performance information into a traditional data warehouse that generally represents only the functional organisation. the corporate performance measurement system provides a single source of information on the performance of the company. as a proof of concept in a business environment, a feasibility study has been implemented in the insurance sector. this performance measurement approach fully supports a modern organisational structure: the customer-oriented process perspective coexisting with the traditional functional structure.
a strategy for selecting multiple components. this paper presents a systematic method for simultaneously defining a software architecture and selecting off-the-shelf components for reuse. the method builds upon existing techniques for component selection and architecture evaluation. we identify architectural decisions that have a large effect on the components used early in the process so that different ways of building the system can be investigated. the result of applying the method is a partial definition of a system's architecture along with a set of components that could be incorporated.
two-level assurance of qos requirements for distributed real-time and embedded systems. assuring quality of service (qos) requirements is critical when assembling a distributed real-time and embedded (dre) system from a repository of existing software and hardware components. this paper presents a two-level approach for assuring satisfaction of qos requirements in the context of a reduced design space for dre systems. techniques from artificial intelligence and statistics are used to fulfill these collective objectives at system assembly time. the result not only lessens the overhead of validation of qos requirements at run-time, but also reduces the development and integration cost of dre systems.
similarity-based clustering of web transactions. we introduce a measure to compute similarity between two sequences containing accesses to web pages, to be exploited in a clustering approach for grouping sessions of accesses to a web site. the notion of sequence similarity is parametric to the sequence topology, and the similarity among web pages within the sequences. in our formalization, two web pages are similar if they can be considered synonymies not only from a content point of view, but also from a usage point of view, i.e., if users exhibit the same behavior on both pages. the refined notion of page similarity, as well as the related notion of sequence siilarity, are envisaged to be effective in the application of a centroid-based clustering technique to the personalization of web experience.
large-scale flow field visualization for aneurysm treatment. an important medical problem of the non-invasive treatment of brain aneurysm has attracted growing interest. aneurysm surgery remains dangerous because surgeons have limited knowledge of blood flow patterns and complex 3d geometry of aneurysms. this information is essential to determine if the aneurysm is suitable for a certain surgical technique. therefore, a virtual aneurysm (va) research was initiated to make it possible for medical specialists to obtain such detailed information.here we discuss two schemes relating to the realization and efficiency of va system. the first is a scheme of data storage and management technique. it is aimed not only to achieve higher access efficiency and storage utilization but also to reduce the stress of memory resources. the second is the scheme of the branching simulation approach attempting to lessen the computational burden at visualization. these schemes illustrated by va system, requiring minimal run-time computing or memory, are suggested so as to best exploit the performance for the simulation and visualization. while there is no intrinsic difference when applied to other scientific and engineering areas, these schemes are more beneficial to typical biomedical visualizations when the data already push the limits of the simulation and visualization environment.
detection and segmentation of tables and math-zones from document images. we propose an algorithm to separate out tables and math-zones from document images. the algorithm relies on the spatial characteristics of tables and math-zones in a document. it has been observed that tables have distinct columns which imply that gaps between the fields are substantially larger than the gaps between the words in text lines and in math-zones the characters and symbols are less dense in comparison to normal text lines. these deceptively simple observations have led us to design a simple but powerful table and math-zone detection system with low computation cost.
knowledge-based query expansion to support scenario-specific retrieval of medical free text. in retrieving medical free text, users are often interested in answers pertinent to certain scenarios that correspond to common tasks performed in medical practice, e.g., treatment or diagnosis of a disease. a major challenge in handling such queries is that scenario terms in the query (e.g., treatment) are often too general to match specialized terms in relevant documents (e.g., chemotherapy). in this paper, we propose a knowledge-based query expansion method that exploits the umls knowledge source to append the original query with additional terms that are specifically relevant to the query's scenario(s). we compared the proposed method with traditional statistical expansion that expands terms which are statistically correlated but not necessarily scenario specific. our study on two standard testbeds shows that the knowledge-based method, by providing scenario-specific expansion, yields notable improvements over the statistical method in terms of average precision-recall. on the ohsumed testbed, for example, the improvement is more than 5% averaging over all scenario-specific queries studied and about 10% for queries that mention certain scenarios, such as treatment of a disease and differential diagnosis of a symptom/disease.
editorial message: special track on applications of spatial simulation of discrete entities. many important phenomena result from localized interactions including: population dynamics and epidemics, cell and tissue modeling, mobile computing and wireless networks. modeling these systems can reduce experimentation costs or enable non-destructive in silica experimentation.simulation models can be classified depending on how they represent reality, in particular time, space and simulated entities (objects). the simplest to described are models based on ordinary differential equations, which are aspatial and they may have either single time step for all objects, making time synchronous, or different time steps for different entities, making time asynchronous. simulation entities are also described by a set of read valued parameters, so they are treated as continuous. it is well known that spatially explicit models can exhibit qualitatively different results than their aspatial counterparts [5]. this makes the models based on partial differential equations very common and popular. in this track however, we focus on a different category of models. to make this difference clear, we start with the following categorization of all models based on how they treat the three orthogonal aspects of simulations: simulation objects (entities) and the world that they inhabit (time and space). the categorization is shown in table 1.the field of numerical computing is well studied, with numerous forums for extensive work and publication of spatial models using continuous time and treating entities as continuous (e.g. diffusion models [3, 1] or finite element method approaches [6, 11]. traditionally, techniques for spatial modeling of discrete systems have tended to be published in application specific forums. in forming this track, we hoped to provide a unique forum for researchers in this area to come together and discuss various applications and approaches to spatial modeling.
moral responsibility and it for human enhancement. what can be said against a moral obligation to use it for enhancement purposes? some have argued - and it is very well conceivable that this is an increasingly common conception - that we may have a moral obligation to use it for enhancing human bodies and human decision-making, for instance by using computers for moral decision-making in cases in which we are dealing with a high level of (moral) complexity such as euthanasia decisions. in this paper i will formulate some objections against the suggestion made by some that it tools can and ought to be used for human enhancement, in the sense of improving moral decision-making.if we were to use it for enhancement purposes, what would be the problems? in this paper i will discuss some problems, such as moral deskilling, epistemic dependence, the allocation of responsibility for it support, and epistemic paternalism. the conclusion is that it is questionable whether we can speak of a moral obligation to use it tools for human enhancement. it is certainly extremely helpful in improving decision-making and improving the quality of life as conceived by some. however, speaking of a moral obligation seems too strong of a claim or at least it should be reconsidered in light of the issues here discussed.
a comparison of two view materialization approaches for disease surveillance system. the effectiveness of a disease surveillance system such as rods depends heavily on the performance of the underlying data management components. given that such system's core functionality is to support decision making and data mining, the response time of complex queries involving aggregation requires special attention. traditionally, materialized views have been advocated to address this issue. the question that this paper examines is which approach implementing materialized views is more suitable in a disease surveillance environment. our comparison focuses on the two most common approaches, namely, the cache tables approach and the data warehousing approach. our evaluation shows that the choice of an approach is not limited by the cost-performance but by the cost-flexibility of usage as well.
the effect of named entities on effectiveness in cross-language information retrieval evaluation. the large number of experiments carried out within evaluation initiatives for information retrieval has led to an invaluable source for further research and meta-analysis. in this study, an analysis of the results of the cross language evaluation forum (clef) campaigns for the years 2000 to 2003 is presented. this study considers the performance of the systems for each individual topic. it is dedicated to the influence of named entities on retrieval performance. named entities in topics lead to significant improvement of the retrieval quality in general and for most systems and tasks. the performance of systems varies for topics without, with one or two and with three or more named entities. this knowledge gained by data mining on the evaluation results can be exploited for the improvement of retrieval systems as well as for the design of topics for future clef campaigns.
efficient target search with relevance feedback for large cbir systems. recent content-based image retrieval (cbir) techniques were designed around query refinement based on relevance feedback. they suffer from slow convergence, high disk i/o, and do not even guarantee to find intended targets. in this paper, we identify the cause of these problems and propose several efficient target search methods to address these drawbacks. our complexity analysis shows that our approach is able to reach any given target image with fewer iterations in the worst and average cases. we evaluated our techniques on large datasets in simulated and realistic environments. the results show that our approach significantly reduces the number of iterations and improves overall retrieval performance. the experiments also confirm that our approach can always retrieve intended targets even with poor selection of initial query points and can be used to improve the effectiveness of existing cbir systems with relevance feedback.
a model for mining outliers from complex data sets. to solve the outlier mining problems where outliers are highly intermixed with normal data, a general variance-based outlier mining model (vomm) is presented, in which the information of data is decomposed into normal and abnormal components according to their variances. with minimal loss of normal information in the vomm, outliers are viewed as the top k samples holding maximal abnormal information in a dataset. and then, the principal curve that is a smooth nonparametric curve passing through the "middle" of the dataset and that provides a good nonlinear summary of the data is introduced as an algorithm of the vomm. experiments carried out on abnormal returns detection in stock market show that the vomm is feasible and performs better than that of gaussian model and garch (generalized auto-regressive conditional heteroscedasticity) model.
netaffx: affymetrix probeset annotations. one challenge in microarray experiments is assessing when the results are biologically significant. this assessment can be aided by detailed annotation of the probeset target sequences, including gene function or category, protein product, and pathway information. netaffx compiles public and in-house annotations for all affymetrix chip sets. public annotations are collected from unigene, locuslink and swiss-prot. in-house annotations are produced by generalized rapid automated protein analysis (grapa), a high-accuracy hmm method for protein annotation. grapa has been used to generate novel annotations under three classification schemes: structural classification of proteins (scop), enzyme commission (ec), and g protein coupled receptors (gpcr). in addition, annotations are generated by searching pfam and blocks databases. these annotation schemes have been applied to diverse genomes including human, mouse, rat, drosophila, and yeast, then mapped onto affymetrix microarray probesets. the combination of protein-level annotations with public source annotations creates a powerful description of genes at both the genomic and protein levels. users can collect information on a target sequence, or cluster microarray probe sets according to a given domain or functional category. netaffx is available on the web at http://www.netaffx.com/.
cost-efficient processing of min/max queries over distributed sensors with uncertainty. the rapid development in micro-sensors and wireless networks has made large-scale sensor networks possible. however, the wide deployment of such systems is still hindered by their limited energy which quickly runs out in case of massive communication. in this paper, we study the cost-efficient processing of aggregate queries that are generally communication-intensive. in particular, we focus on min/max queries that require both identity and value in the answer. we study how to provide an error bound to such answers, and how to design an "optimal" sensor-contact policy that minimizes communication cost in reducing the error to a user-tolerable level.
automatic code generation for a convection scheme. traditional design and implementation of large atmospheric models is a difficult, tedious and error prone task. with the ctadel project we investigate a new method of code generation, where the designer describes the model in an abstract high-level specification language which is translated into highly optimized fortran code. this is applied to a convection scheme as used in a numerical weather prediction model (nwp). we address problems like how to generate efficient code for conditional expressions by using polymorphic templates. finally, we compare the generated code for the convection scheme with the hand-written reference code.
approximating module semantics with constraints. in this paper we present a generic constraint domain for symbolic modular analysis. the idea is that the semantics of a module can be approximated by a set of relations symbolically linking the input, output and local variables. we show how this result is correct w.r.t. a trace semantics, and how it can be used to perform an (incremental) modular analysis. we claim that our construction generalizes existing modular analyses by showing how well-known modular analyses can be instantiated in our framework.
using semi-lagrangian formulations with automatic code generation for environmental modeling. an import issue for numerical weather prediction modes (nwp) is the time it takes to produce a valid forecast. one factor, which greatly influences this simulation time is the size of the time step. however, time step size is often limited by the numerical stability of the used advection schemes. available schemes include semiimplicit eulerian and semi-lagrangian schemes. in principal, semi-lagrangian formulations result in irregular communications on parallel architectures. in this paper we describe automatic code generation for a semi-implicit scheme with a semi-lagrangian formulation. we describe how code can be generated from a mathematical specification of the advection model, the embedding of the formulations in the ctadel code generation tool and we show the parallelization of the code. finally, we show results from preliminary experiments we have conducted with the generated code and the reference code from a production nwp on a number of different architectures.
a method for the dynamic generation of virtual versions of evolving documents. document evolution is usually performed by creating a new document which explicitly details changes to specific paragraphs inside other document content. obtaining (virtual) document versions corresponding to its state at a specific date is left to document users, who manually extract from library collections, and compose, the pieces of text needed to obtain the desired version. but this can be a very tedious and difficult task when changes are numerous. we propose a solution to dynamically generate virtual document versions on user demand, respecting the library documents integrity. references to other documents and modification relationships can be automatically detected and are modelled as typed links -modelled with xlink- in a relationship graph. in this paper, we focus on the version generation process, consisting in a dynamic document composition based on a graph traversal. this solution has already shown its adequacy with a legislative digital library.
estimating manifold dimension by inversion error. video and image datasets can often be described by a small number of parameters, even though each image usually consists of hundreds or thousands of pixels. this observation is often exploited in computer vision and pattern recognition by the application of dimensionality reduction techniques. in particular, there has been recent interest in the application of a class of nonlinear dimensionality reduction algorithms which assume that an image dataset has been sampled from a manifold.from this assumption, it follows that estimating the dimension of the manifold is the first step in analyzing an image dataset. typically, this estimate is obtained either by using a priori knowledge, or by applying one of the various statistical and geometrical methods available. once an estimate is obtained, it is used as a parameter for the nonlinear dimensionality reduction algorithm.in this paper, we consider reversing this approach. instead of estimating the dimension of the manifold in order to obtain a low dimensional representation, we consider producing low dimensional representations in order to estimate of the dimensionality of the manifold. by varying the dimensionality parameter, we obtain different low dimensional representations of the original dataset. the dimension of the best representation should then correspond to the actual dimension of the manifold.in order to determine the best representation, we propose a metric based on inversion. in particular, we propose that a good representation should be invertible, in that we should be able to reverse the reduction algorithm's transformation to obtain the original dataset. by coupling this metric with any reduction algorithm, we can estimate the dimensionality of an image manifold. we apply our method in the context of locally linear embedding (lle) and isomap to six frequently used examples and two image datasets.
browsing image databases with galois' lattices. we divide image querying paradigms into three categories: formal querying, interactive search, and browsing. the first two paradigms have been largely investigated in the literature, whereas the last one has not been as much studied. we propose a browsing technique based on concept lattices. the result is a kind of hypertext of images that mixes classification and visualisation issues in a high-dimensionnality space.
identification of parameters and restoration of motion blurred images. this paper proposes a technique for restoring the motion blurred images. restoration of blurred images is very important problem in tracking and identification of criminals, where image of a human face or number plate of a running vehicle taken in hit and run situation gets blurred due to relative motion between the imaging system and object/face. for restoration of motion blurred images, knowledge of the point spread function (psf) is very important. the motion blur psf is characterized by two parameters, namely blur direction and blur length. this paper also presents a method to identify the parameters of the psf from the blurred and noisy images using the log spectrum of the blurred images. these parameters are used to restore the images. the experimental results demonstrate that the image can successfully be restored from the image with substantial amount of natural and artificial blur.
language identification in web pages. this paper discusses the problem of automatically identifying the language of a given web document. previous experiments in language guessing focused on analyzing "coherent" text sentences, whereas this work was validated on texts from the web, often presenting harder problems. our language "guessing" software uses a well-known n-gram based algorithm, complemented with heuristics and a new similarity measure. both fast and robust, the software has been in use for the past two years, as part of a crawler for a search engine. experiments show that it achieves very high accuracy in discriminating different languages on web pages.
morphogenetic constraint-satisfaction based approach for organizational engineering. organizations are modeled using several approaches namely behavioral-science approach, design-science approach [march and smith 1995], classification approach [zachman 1993], etc. can all these different approaches be consistently reconciled? can this reconciliation be systemic, based on principles that support analyses of organizations? we present a solution to these questions through a morphogenetic constraint-satisfaction based approach.in our view, the hallmark of this approach is that it systemically unifies the functional, cross-functional and behavioral views of organizations.
stability vs. optimality tradeoff in game theoretic mechanisms for qos provision. we study noncooperative games whose players are selfish, distributed users of a network and the game's objective is to optimize quality of service (qos). our classes of games are based on generally accepted realistic microeconomic market models of qos provision, and unlike most other games that have been recently studied in this context, stability is not guaranteed for our class of games. stability here refers to whether the game reaches a nash equilibrium. optimality is a measure of how close a nash equilibrium is to optimizing a given objective function defined on game configuration. the overall goal is to determine a minimal set of static game rules based on pricing that result in stable and optimal qos provision. the combination of stability and optimality opens an interesting direction of investigation. we give a new and general technique to establish stability and demonstrate a close trade-off between stability and optimality for our game classes. additionally, these results directly give a simple, computationally efficient, self-organizing mechamism for stable and optimal qos provision in natural cases.
a multi-agent system for e-barter including transaction and shipping costs. an e-barter multi-agent system consists of a set of agents exchanging goods. in contrast to e-commerce systems, transactions do not necessarily involve the exchange of money. agents are equipped with a utility function to simulate the preferences of the customers that they are representing. they are grouped into local markets, according to the localities of the corresponding customers. once these markets are saturated (i.e. no more exchanges can be performed) new agents, representing those local markets, are generated and combined into new markets. by reiteratively applying this process we finally get a global market.even though a formalism to define e-barter architectures has been already introduced, that framework had a strong drawback: neither transaction nor shipping costs were considered. in this paper we extend that framework to deal with systems where fees have to be paid to the owner of the system. these fees depend on the goods involved in the corresponding exchanges. in addition, shipping costs have also to be paid. these modifications complicate the setting because the utility that customers receive after exchanging goods is not directly given by the original utility function. that is, the returned utility after an exchange is performed has to be computed as a combination of the former utility and the derived costs. in particular, some exchanges may be disallowed because those costs exceed the increase of utility returned by the new basket of goods.
health care information systems. health care information systems (hcis) have provided the opportunity and tools to estimate, interpret, observe and better understand newest health care problems. in this way, information and communication technologies permit researchers to sustain greater benefits such as decision support systems, protecting sensitive patient data, integration of complex health care data, 3d visualization of anatomical structures, etc.
encouraging knowledge exchange in discussion forums by market-oriented mechanisms. discussion forums are one of the simplest, while successful, internet-based systems to promote the spread of knowledge. unfortunately, they sometimes lack appropriate incentives to encourage users participation. in this paper we discuss a simple market-oriented mechanism to promote the knowledge exchange activity in discussion forums. the proposed solution departs from other market-oriented approaches since the scarce resource we deal with, the effort to create information, has important peculiarities which must be taken into account. in addition to the basic framework, we have also developed a method to dynamically improve the performance of the system. this method uses statistics about users behavior in order to minimize the reponse time in which questions are satisfactorily answered.
optimizing subset queries: a step towards sql-based inductive databases for itemsets. storing sets and querying them (e.g., subset queries that provide all supersets of a given set) is known to be difficult within relational databases. we consider that being able to query efficiently both transactional data and materialized collections of sets by means of standard query language is an important step towards practical inductive databases. indeed, data mining query languages like mine rule extract collections of association rules whose components are sets into relational tables. post-processing phases often use extensively subset queries and cannot be efficiently processed by sql servers. in this paper, we propose a new way to handle sets from relational databases. it is based on a data structure that partially encodes the inclusion relationship between sets. it is an extension of the hash group bitmap key proposed by morzy et al. [8]. our experiments show an interesting improvement for these useful subset queries.
performance evaluation for text processing of noisy inputs. we investigate the problem of evaluating the performance of text processing algorithms on inputs that contain errors as a result of optical character recognition. a new hierarchical paradigm is proposed based on approximate string matching, allowing each stage in the processing pipeline to be tested, the error effects analyzed, and possible solutions suggested.
experiments on using fuzzy quantified sentences in adhoc retrieval. in this work we implement and evaluate a fuzzy approach to information retrieval whose query language incorporates fuzzy quantifiers. fuzzy quantified sentences are suitable for imposing additional restrictions in the retrieval process which are not typical in classic information retrieval. moreover, fuzzy quantifiers can be implemented in different relaxed ways leading to a wide range of methods for combining query terms. the large-scale evaluation conducted here shows clearly the practical benefits obtained in terms of retrieval performance. these empirical results strengthen previous theoretical works that already advanced the adequacy of fuzzy quantifiers for modeling information needs.
query reformulation for an xml-based data integration system. the main objective of a mediator-based data integration system is to provide a unified view of several distributed and heterogeneous data sources. this view, called mediation schema, corresponds to a set of elements computed from data available on the local data sources. one of the biggest challenges facing a data integration system consists in answering a user query submitted in terms of the mediation schema given that the data is at the sources. this problem consists mainly in reformulating the query in terms of the source schemas and in integrating the corresponding answers. in this paper we address the problem of query reformulation in the context of an xml-based data integration system. our solution is based on algorithms that generate a set of source queries considering a given user query and a set of mappings between the mediation schema and the data source schemas.
evolutionary segmentation of yeast genome. segmentation algorithms differ from clustering algorithms with regard to how to deal with the physical location of genes throughout the sequence. therefore, segments have to keep the original positions of consecutive genes, which is not a constraint for clustering algorithms. it has been proven that exist functional relations among neighbour-genes, so the localization of the boundaries between these functionally similar groups of genes has turned out an important challenge. in this paper, we present an evolutionary algorithm to segment the yeast genome.
devopt: a distributed architecture supporting heuristic and metaheuristic optimization methods. this paper presents a distributed software architecture that allows the cooperation among research institutions in the field of combinatorial optimization --- devopt: distributed evolutionary optimization centers. it has as main aims to share existing algorithms for optimization problems, to allow the easy testing of these algorithms with existing instances, to provide fast and better ways to design new algorithms, and to share computational power among the cooperating institutions. this is achieved respecting the autonomy and heterogeneity of the cooperating institutions. the distributed architecture is discussed here and also a case study of a parallel memetic algorithm to solve the asymmetric traveling salesman problem (atsp) running on this environment is analyzed.
a precise schedulability test algorithm for scheduling periodic tasks in real-time systems. rate monotonic analysis (rma) has been shown to be effective in the schedulability analysis of various types of system. this paper focuses on reducing the run time of each rma-tested system. based on a new concept of tasks, denoted by the lift-utilization tasks, we propose a novel method to reduce the number of iterative calculations in the derivation of the worst-case response time of each task in its rma test. the capability of the proposed method was evaluated and compared to related work, which revealed that our method produced savings of 26-33% in the number of rma iterations.
cooperative active contour model and its application to remote sensing. we propose a decentralized cooperative processing applied to the active contour model "snake", which applies multiple snakes to a single region, to improve its detection accuracy. we verify the effectiveness of our proposal in the cases of multi-snakes with different parameter sets and multi-snakes applied to rgb-decomposed images. we then apply it to multi-spectral remote sensing, and show that multi-snakes detected the boundary with enough accuracy.
pollock: automatic generation of virtual web services from web sites. as the usage of web services proliferates dramatically, new tools to help quickly generate web services are needed. in this paper, we propose a methodology that helps to automatically generate web services from the form-based query interfaces of a web site. since the majority of web data are rather "hidden" behind such a form interface, we believe turning such a human-oriented query interface into machine-oriented web services is an important problem. toward this goal, we adopt the wrapper technology successfully developed and deployed in database community, and demonstrate how to generate web services components (e.g., wsdl, uddi, soap) automatically. we present the overall architecture of our developed prototype and a few showcases based on real web sites.
fgka: a fast genetic k-means clustering algorithm. in this paper, we propose a new clustering algorithm called fast genetic k-means algorithm (fgka). fgka is inspired by the genetic k-means algorithm (gka) proposed by krishna and murty in 1999 but features several improvements over gka. our experiments indicate that, while k-means algorithm might converge to a local optimum, both fgka and gka always converge to the global optimum eventually but fgka runs much faster than gka.
feature-based distributed object search using signatures in peer-to-peer environments. peer-to-peer (p2p) technology has attracted a lot of attention in recent years. efficient object search is an important research issue in p2p environments, especially in those without centralized global indexes. although a number of hash-based basic object search schemes are known to alleviate the problem, they cannot provide flexible feature-based object searches. this paper proposes a novel object search method using distributed frame sliced signatures, and looks at an appropriate choice of parameters to adapt the configuration to the object search and registration workload. it shows object search and registration schemes that take into account the number of messages and response times. effectiveness of these schemes is evaluated through simulation experiments.
implementation of fast rsa key generation on smart cards. although smart cards are becoming used in an increasing number of applications, there is small literature of the implementation issues for smart cards. this paper describes the issues and considerations that need to be taken into account when implementing the key generation step of a cryptographic algorithm widely used nowadays, rsa.smart cards are used in many applications that require a tamper resistant area. therefore, smart cards that use cryptography have to provide encryption, decryption, as well as key generation inside its security perimeter. rsa key generation is a concern for on-card implementation of rsa cryptosystem, as it usually takes a long time. in this paper, two simple but efficient key generation algorithms are evaluated, in addition to a simple but not very efficient algorithm. the paper discusses in detail how to build fast implementations for the three algorithms presented, using smart cards with crypto-coprocessor.
security considerations for active messages. messages are generally regarded as passive since they merely act as a conveyance for information. an active message triggers processing activities at each of its recipients. a discussion is provided on the different classes of processing activities that can occur for active messages. a mechanism for ensuring the security of an active message and its associated processing operations is also outlined.
wssecspaces: a secure data-driven coordination service for web services applications. web services standards and protocols (wsdl, uddi, soap, etc.) are the basis of a novel technology supporting web based applications. web services are components offering ports at which service invocations can be sent using xml-based protocols. the tools currently proposed for specifying and programming the interdependencies among web services (bpel, biztalk, etc.) support the description of the flow of service invocation needed among collaborating web services in order to complete a specific task. in this paper we discuss the design and the implementation of a higher-level interaction model for web services that follows the tradition of data-driven coordination: web services do not coordinate via direct service invocation, but their interaction is mediated by a coordination space where shared data are stored and retrieved. moreover, our proposal extends the traditional data-driven coordination model with a more sophisticated pattern matching mechanism that supports a controlled access to the shared data.
enforcing path uniqueness in internet routing. often an ip network administrator will desire to provision unique paths for traffic demands while avoiding network congestion. under destination based shortest path protocols this must be achieved indirectly via careful selection of link metrics. we demonstrate that current approaches to metric optimisation cannot reliably produce such unique-path routings. we present two methods of enhancing the capability of local search algorithms for optimising these metrics to produce unique-path solutions: a more intelligent move operator and adaptive penalisation schemes. these approaches are evaluated on four real-world ip backbones, and are shown to reliably produce unique-path routings. by appropriate choice of parameters, unique-path solutions may be found either quicker or of better quality than those produced by fixed penalty schemes.
learning system to introduce gis to civil engineers. a web-based e-learning system to facilitate the integration of geographical information systems (gis) into the civil engineering curriculum is described in this paper. the principal learning goal is to encourage students to apply and integrate foundational knowledge in the solution of "real world" comprehensive civil engineering problems. sharable content objects, designed in accordance with the adl/scorm standards, contain basic knowledge components in the form of web-viewable hypermedia coupled with an assessable learning outcome thereby forming a learning object.
medic: mobile diagnosis for improved care. hospitals everywhere are taking advantage of the flexibility and speed of wireless computing to improve the quality and reduce the cost of healthcare. caregivers equipped with mobile computers now have levels of interaction at the bedside not possible with traditional paper charts, and they can access accurate real-time information (patient records, medication and medical imagery) at the point-of-care to make decisions, diagnose and treat patients with greater speed and efficiency. greater and more immediate information access, however, is giving rise to challenges in how to effectively select and present the most relevant aspects for given patient care tasks, as well as how to take advantage of the collaborative opportunities afforded by medical community connection. we propose a system that enables doctors to efficiently query, analyse and annotate patient information, in particular medical imagery, using current mobile technologies. the system allows entire profiles with known diagnoses to be retrieved and can be used to compare diagnosis and treatments for patients with similar symptoms or care records. the application can be employed by caregivers either working in the hospital setting or working remotely and off-site as well as a useful tool to facilitate education and training of medical staff.
discovering parametric clusters in social small-world graphs. we present a strategy for analyzing large, social small-world graphs, such as those formed by human networks. our approach brings together ideas from a number of different research areas, including graph layout, graph clustering and partitioning, machine learning, and user interface design. it helps users explore the networks and develop insights concerning their members and structure that may be difficult or impossible to discover via traditional means, including existing graph visualization and/or statistical methods.
content management on server farm with layer-7 routing. service replication on a server farm is becoming increasingly widespread as the explosive growth of the web is straining the architecture of many internet sites. layer-7 routing, routing packets based on requested content, has been recognized as a powerful approach to distribute workload among these server farms. however, little attention has been given to how to configure content-related knowledge into the layer-7 routing mechanisms. in addition, the used data structures for storing content-related knowledge and lookup operation for making routing decisions are also unclear. this paper presents a management system that can support a configurable and high-performance server farm with layer-7 routing. in this system, we devised a data structure termed url table to hold content-related information for making content-aware routing decisions. we also propose a novel idea termed "url formalization", which provide a scalable solution to speedup the content-aware request routing.
efficient interactive configuration of unbounded modular systems. interactive configuration guides a user searching through a large combinatorial space of solutions to a system of constraints. we investigate a class of very expressive underlying constraint satisfaction problems: modular recursive constraint systems of unbounded size. a precomputation step is used to obtain a configuration algorithm for such systems that supports the user efficiently with bounded response time. this precomputation step determines all solutions for each module, which are computed and stored in compact data structures such as binary decision diagrams (bdds), in order to eliminate run-time search. the precomputation step also detects ill-behaved module collections that have no finite solutions. the runtime interaction algorithm scales well as its response time only depends on the amount of the information passed locally between the modules, and not on the size of the entire configured structure. our algorithm was implemented and tested on an industrial example, and gives good response times. we believe this is the first known sound and complete algorithm for solving unbounded interactive configuration problems, with bounded response time per interaction.
on the composition of java frameworks control-flows. object oriented programming languages provide, in principle, mechanisms to enhance code reuse, as an effort of designing object oriented software, design patterns and frameworks are recognised as good techniques for reuse. frameworks are of particular interest as design and code reuse are achieved. despite of that, most frameworks were designed to be adapted to applications and not to be composed with other frameworks. as a result, problems such as control-flow composition, legacy components composition, frameworks gap, entities overlap and composition of frameworks behaviour arise. the present work is a study on the composition of java frameworks control-flows, where a third framework is created from two existing ones. with this study we have checked the potential problems that may appear as two control-flows are composed via message passing.
a novel data mining algorithm for reconstructing gene regulatory networks from microarray data. in this paper, we propose a novel data mining algorithm for reconstructing gene regulatory networks (grns) from microarray data. by making use of the proposed probabilistic measure, it is able to mine noisy, high dimensional expression data for interesting association patterns of genes without the need for additional feature selection procedures. moreover, it can make explicit hidden patterns discovered for possible biological interpretation and also predict gene expression patterns in the unseen tissue samples. experimental results on real expression data show that it is very effective and the discovered association patterns reveal biologically meaningful regulatory relationships of genes that could help users reconstructing the underlying structures of grns.
a code compression advisory tool for embedded processors. we present a tool which is designed to be used as a code compression advisory system for object code to be run on an embedded processor. all the compression schemes support run-time random decompression. given the machine instruction set architecture, the encoding of instructions, and a set of object programs to be compressed, the tool analyzes the code, gathers statistics about static instruction frequencies and other relevant information, and performs a relative evaluation of a suite of compression strategies. the tool produces as output, the sizes of the compressed code, the line address table (if one is required), and the dictionary (if there is only one) or the sizes of all dictionaries if there are several, for various choices of parameters input by the user. the final result helps one to decide a code compression strategy for the input processor. we have used the tool to evaluate alternate schemes for a suite of benchmarks for the ti tms320c62x instruction set architecture and the intel strongarm processor and report results.
query length impact on misuse detection in information retrieval systems. misuse is the abuse of privileges by an authorized user and is the second most common form of computer crime after viruses. earlier we proposed a misuse detection approach for information retrieval systems that relied on relevance feedback. the central idea focused on the building of a user profile containing both query and feedback terms from prior queries. our algorithm matched new activities to existing profiles and assigned a likelihood of misuse to an activity. only initial evaluation was provided.we now expand and evaluate our system using both short and long queries noting the effect of query length in the accuracy of the detection. the results indicate an overall precision of 83.9% when short queries are used, and 82.2% for long queries. the rate of the undetected misuse for short queries is less than 2% and for long queries less than 6%. although higher precision score configurations result in a lower false alarm rate, unfortunately, they increase the rate of undetected misuse both for short and long queries. given this tradeoff, for any particular application constraint, system behavior can be tuned to minimize either false alarms or undetected misuse.
long time step molecular dynamics using targeted langevin stabilization. we introduce the b-spline mollified impulse (molly) and the targeted molly (tm) for molecular dynamics (md). tm uses targeted langevin coupling to stabilize b-spline molly. results show that with a proper choice of parameters, the radial distribution function can be correctly recovered and the self-diffusion co-efficient can be correctly estimated from md simulations of flexible waters using tm with outer time step of 16 fs, and a six-fold speedup is obtained. the basis of comparison is leapfrog with time step of 1 fs the overhead associated with mollification is low. extention to handle larger molecules is discussed.
transformation of yepc business process models to yawl. model transformations are frequently applied in business process modeling to bridge between languages on a different level of abstraction and formality. in this paper, we define a transformation between yepcs which is an extension to the popular event-driven process chain (epc) and yawl, a formal workflow language that is able to capture all of the 20 workflow patterns reported in [1]. we illustrate the transformation challenges and present a suitable transformation algorithm. the benefit of the transformation is threefold. first, it clarifies the semantics of yepcs via a mapping to yawl. second, the deployment of yepc business process models as workflows is simplified. thirdly, yepc models can be analyzed with yawl verification tools.
nonlinear instability in multiple time stepping molecular dynamics. this paper discusses additional stability limitations of multiple time stepping (mts) integrators for molecular dynamics (md) that attempt to bridge time scales. in particular, it is shown that when constant-energy (nve) simulations of newton's equations of motion are attempted using the verlet-i/r-respa/impulse, there are nonlinear instabilities when the longest step size is one third and possibly one fourth of the period(s) of the fastest motion(s) in the system. this is demonstrated both thorough the analysis of a nonlinear model problem and through a through set of numerical simulations.
optimization of a language for data mining. constraint-based mining has attracted in recent years the interest of the data mining research community because it increases the relevance of the result set, reduces its volume and the amount of workload. however, constrained-based mining will be completely feasible only when efficient optimizers for mining languages will be available.this paper is a first step towards the construction of optimizers for a constraint-based mining language. it provides the guidelines for the comparison of classes of statements by means of the relationships existing between their result sets. furthermore it identifies as useful information to the optimization the presence of unique constraints and functional dependencies in the schema of the database. we show the practical implications of the discussed principles with a set of algorithms designed for a specific mining language. these algorithms use also a new designed index, called mining index that allows to reduce the portion of the database to be read in response to some classes of queries. in these cases the workload of the mining engine is greatly reduced or completely avoided in a significant subset of the cases.
generating correct epcs from configured c-epcs. process reference models play an important role for the alignment and configuration of commercial off-the-shelf enterprise systems to requirements of an organization. recently, configurable event-driven process chains (c-epcs) have been proposed as a language to support the model-driven configuration of such enterprise systems. while some problems of generating correct epcs from a configured c-epc have been discussed, up to now there is no implementation of an algorithm available to automate the configuration task. this paper presents a configuration algorithm that is guided by a minimality criterion. it details and extends a previous algorithm that has only been sketched so far. as a proof-of-concept the algorithm has been implemented.
an empirical evaluation of client-side server selection policies for accessing replicated web services. replicating web services at geographically distributed servers can offer client applications with a number of benefits, including higher service availability and improved response time. however, selecting the "best" server to invoke at the client side is not a trivial task, as this decision needs to account for (and is affected by) a number of factors, such as local connection capacity, external network conditions and servers workload. this paper presents the results of an experiment in which we implemented and empirically evaluated the performance of five server selection policies for accessing replicated web services. the experiment involved two client stations, with different connection capacities, continuously applying the five policies to invoke a real-world web service replicated over four servers in three continents. our results show that, in addition to the individual performance of each server, service response time using the five policies is affected mainly by client differences in terms of connection capacity and workload distribution throughout the day.
a web services composition approach based on software agents and context. we present an agent-based and context-oriented approach for web services composition. a web service is an accessible application that other applications and humans can discover and trigger to satisfy various needs. due to the complexity of web services composition, we consider two concepts to reduce this complexity: software agent and context. a software agent is an autonomous entity that acts on behalf of users, whereas context is any information relevant to characterize a situation. during composition, software agents engage conversations with their peers to agree on the web services that will participate in the composition.
propositional planning in bdi agents. this paper aims to describe the relationship between propositional planning systems and the process of means-end reasoning used by bdi agents. to show such relationship, we define a mapping from bdi mental states to propositional planning problems and from propositional plans back to mental states. in order to test the viability of such mapping, we have implemented it in an extension of a bdi agent model through the use of graphplan as the propositional planning algorithm. the implementation was applied to model a case study of an agent controlled production cell.
intelligent agents for patient monitoring and diagnostics. this paper describes intelligent monitor agents (im-agents), a project that utilizes intelligent multiagents to assist patient health care. clinicians must simultaneously audit and interpret an overwhelming amount of information regarding a patient during the process of monitoring, performing diagnostics and determining therapeutic intervention. multiple im-agents coordinate as a team with each agent performing specialized monitor and diagnostic tasks. fuzzy logic, connection networks, trend analysis and qualitative logic methods are used within the dynamic decision modules of all im-agents. the agents are autonomous, interactive, mobile and capable of performing dynamic intelligent inference during execution. decision functionality is demonstrated in preliminary prototype test cases involving emergency trauma scenarios, particularly focusing on stabilizing hemorrhagic shock.
self-organization and computer security: a case study in adaptive coordination. one frequently hears stories about security breeches. despite all the money that has been fed into research in computer security, it looks like researchers are loosing the battle against attackers. this paper argues that one basic problem in security systems is their staticness, and suggests they should be dynamic in nature. this paper describes two cases where adaptiveness based on self-organization may lead to dynamic solutions to malicious code protection and security policy distribution.
editorial message: special track on coordination models, languages and applications. in last few years, the field of coordination models and languages has earned the respect of other computer science researchers as they recognized that the understanding of how parts can be efficiently organized as a ensemble is of prime importance to the design of distributed complex systems. the proliferation of network computing and mobile computation, and especially the ubiquity of the internet has made coordination one of the key areas in modern computing. this track aims at bringing together researchers working on applied issues in coordination, ranging from new models to applications.
a new approach to scalable linda-systems based on swarms. natural forming multi-agent systems (aka swarms) have the ability to grow to enormous sizes without requiring any of the agents to oversee the entire system. the success of these systems comes from the fact that agents are simple and the interaction with the environment and neighboring agents is local in nature. in this paper we look at abstractions in the field of swarms and study their applicability in the context of coordination systems. in particular, we focus on the problematic issue of scalability of linda systems.
the fading concept in tuple-space systems. tuple-space systems based on the linda model have been in use in distributed systems for nearly two decades. an area that has recently received attention from the distributed systems community is swarm intelligence (si) --- si has been successfully used in fields such as robotics and optimisation. recently its properties have started to attract research in distributed systems. in this paper we merge si concepts into the linda model to provide an adaptive approach to time which is unrelated to external (real) time: the result is the introduction of an adaptive concept of time into the system, without changing the linda model --- we call it fading. some potential applications of this concept are discussed, along with implications for feasible implementation.
an adaptive energy efficient cache invalidation scheme for mobile databases. this paper presents adaptive energy efficient cache invalidation scheme (aeecis) for the wireless mobile environment. the algorithm is adaptive since it changes the data dissemination strategy based on the current conditions. to reduce the bandwidth requirement, the server transmits in one of three modes: slow, fast or super-fast. the mode is selected based on thresholds specified for time and the number of clients requesting updated objects. an efficient implementation of aeecis is presented and simulations have been carried out to evaluate its caching effectiveness. the results demonstrate that it can substantially improve mobile caching by reducing the communication bandwidth for query processing. compared to previous ir-based schemes, aeecis can significantly improve bandwidth consumption and the number of uplink requests.
a mobile agent approach for global database constraint checking. integrity constraints are valuable tools for enforcing consistency of data in a database. global integrity constraints ensure integrity and consistency of data spanning multiple databases. in this paper, we propose a general framework of a mobile agent based approach for checking global constraints. an insert/update/delete initiated on single site, say s1 may cause the violation of a global constraint. the check for such violation involves accessing related data from multiple sites, say s2...sn. constraint checker on site s1 generates sub constraint checks on sites s2...sn and sends multiple remote agents, rmagent2...rmagentn to sites s2...sn respectively for checking the sub constraints. these remote agents carry with them data processing code to be executed at remote sites. constraint checker gathers results from the remote agents and decides if any constraint is violated. the constraint checking mechanism is much faster as the sub constraint checks are executed in parallel.
our guest agents are welcome to your agent platforms. multiagent applications will appear more and more in open, heterogeneous, evolving and distributed environments, such as the internet. in order to run in such environments, agents will need to adapt themselves to new platforms and protocols. we propose a model of agents that are able to run, communicate and move between different multiagent platforms. this model is based on a middleware between such agents and platforms. it has been implemented on a kind of agents called guest which can be used the same way regardless of what kind of servers they run on, notably, through tools such as a graphical management tool or a server launcher. also, we provide a mechanism based on plug-ins that allows modification of basic agent behaviors like manipulation of messages, control of migration, etc. lastly, we propose two kinds of dynamic agent hierarchies based on plug-ins or middleware.
a multi-agent system for efficiently managing query answering in an e-government scenario. this paper aims at studying the exploitation of the intelligent agent technology for supporting citizens in their access to e-government services. it appears particularly suited in the present e-government scenario characterized by a huge amount of heterogeneous data and services, delivered by government agencies, that makes difficult to quickly answer citizen queries. in this paper we show that the exploitation of the intelligent agent technology facilitates the search of information on government data sources in such a way to completely and precisely satisfy citizen queries. our system creates and maintains suitable profiles of involved users, representing their preferences and exigencies; in addition, it adopts suitable algorithms that exploit information stored in citizen profiles for producing recommendations.
supplier network management: evaluating and rating of strategic supply networks. based on changing market conditions and pressure on cost and productivity, companies in different industries have started do concentrate on their core competencies and to decrease vertical range of manufacture which leads to an increasing outsourcing of business processes. with this outsourcing the dependency of companies on their business partners rises significantly forming so called value networks. supplier relationship management (srm) offers methods and tools to manage direct suppliers. in order to perform well in these value networks srm needs to be extended towards supply network management (snm) by methods and tools to identify, evaluate, rate and select strategic suppliers located not only in tier one, but also in the subsequent tiers. the selection of adequate supply networks, satisfying different evaluation criteria, is therefore of main importance and builds the topic of this paper. the paper is based on preparatory work done in the area of strategic supply network development (ssnd), where the identification of strategic supply networks has been elaborated, and focuses on the evaluation and ranking of strategic supply networks providing the base for supply network selection.
can a parser be generated from examples? one of the open problems in the area of domain-specific languages is how to make domain-specific language development easier for domain experts not versed in a programming language design. possible approaches are to build a domain-specific language from parameterized building blocks or by language (grammar) induction. this paper uses an evolutionary approach to grammar induction. grammar-specific genetic operators for crossover and mutation are proposed to achieve this task. suitability of the approach is shown by small experiments where underlying grammars are successfully genetically obtained and parsers are than automatically generated.
k-gram based software birthmarks. software birthmarking relies on unique characteristics that are inherent to a program to identify the program in the event of suspected theft. in this paper we present and empirically evaluate a novel birthmarking technique which uniquely identifies a program through instruction sequences. to evaluate the strength of the birthmarking technique we examine two properties: credibility and resilience to semantics-preserving transformations. we show that the technique provides both high credibility and resilience. additionally, it complements previously proposed static birthmarking techniques.
a bayesian approach for protein classification. in this work, we propose a new approach for protein classification based on bayesian classifiers. our goal is to predict the functional family of novel protein sequences based on their motif composition. for this purpose, datasets extracted from prosite, a curated protein family database, are used as training datasets. in the conducted experiments, the performance of our classifier is compared to other known data mining approaches. the computational results have shown that the proposed method outperforms the other ones and looks very promising for problems with characteristics similar to the problem addressed here.
approaches to comprehension-preserving graphical reduction of program visualizations. past research efforts on the educational effectiveness of software animations agree in the necessity of active involvement of users, i.e. students and teachers. however, one of the main obstacles is the technical difficulty to produce them. our approach seeks to generate software animations analogously to the generation of documents in office applications. the availability of static visualizations allows the user to define animations friendly; thus, he/she can select the most relevant ones to illustrate meaningfully the algorithm. the selection is facilitated if (ideally) all the static visualizations are simultaneously shown to the user. this sets a novel problem: reducing the size of visualizations while preserving their comprehensibility. in this paper we describe the problem and identify the main difficulties. we think that there is no single solution to the problem. we describe several approaches to this problem, as well as our first, qualitative findings.
planning spatial workflows to optimize grid performance. in many scientific workflows, particularly those that operate on spatially oriented data, jobs that process adjacent regions of space often reference large numbers of files in common. such workflows, when processed using workflow planning algorithms that are unaware of the application's file reference pattern, result in a huge number of redundant file transfers between grid sites and consequently perform poorly. this work presents a generalized approach to planning spatial workflow schedules for grid execution based on the spatial proximity of files and the spatial range of jobs. we evaluate our solution to this problem using the file access pattern of an astronomy application that performs co-addition of images from the sloan digital sky survey. we show that, in initial tests on grids of 5 to 25 sites, our spatial clustering approach eliminates 50% to 90% of the file transfers between grid sites relative to the next-best planning algorithms we tested that were not "spatially aware". at moderate levels of concurrent file transfer, this reduction of redundant network i/o improves the application execution time by 30% to 70%, reduces grid network and storage overhead and is broadly applicable to a wide range of spatially-oriented problems.
evolutionary image enhancement with user behaviour modeling. in this paper we present a novel method for image enhancement of gray-scale images based on the simulation of evolution. our method employs genetic algorithms to evolve the shape of the contrast curve in the image, while attempting to partially automate the subjective process of image evaluation (e.g. user behavior) by performing multiple regression on fitness values. results obtained show the robustness and efficiency of the evolutive method for image enhancement. for several images in the test set our method obtains better results than the classical histogram equalization technique. extensive statistics performed, shows that multiple regression can be effectively applied to model the user behavior.
handheld devices for cooperative educational activities. this paper presents a framework that aims to support several steps of learning activities. working either on mobile and non-mobile devices, test-it, allows users to learn ubiquitously and to proceed with their work at any time and place. it approaches both teaching and learning activities, allowing teachers and students to cooperate using common mobile devices to transfer information between each other.we describe the requirements for using such tool on mobile devices and comment some of the current approaches. the design process and the framework's components, focusing particularly on the user interface and usability issues, are addressed.we also focus on the flexibility provided by test-it, allowing users to create specific applications, according to their field or subject of expertise.
fsm-hume: programming resource-limited systems using bounded automata. hume is a novel domain-specific programming language targeting resource-bounded computations, such as real-time embedded systems or mobile code. it is based on generalised concurrent automata, controlled by transitions characterised by pattern matching on inputs and (recursive) function generation on outputs. this paper discusses trade-offs between expressibility and decidability in the design of fsm-hume, a subset of hume (or hume layer) based on generalised linear bounded automata with statically determinable time and space use. we illustrate our approach with reference to space costing of a simple real-time simulation of a line-following automous vehicle.
contentions-conscious dynamic but deterministic scheduling of computational and communication tasks. real time operating systems (rtos) for multiprocessor system-on-chip (mpsoc) are not well tackling with the scheduling of communication load between the tasks running on different processors. traditionally communications and computations are considered separately leading to a great complexity in the analysis of the system behavior. we have explicitly scheduled the inter-processor communication (ipc) on the shared medium considering all the parameters affecting its cost i.e. link contention, node contention and synchronization overhead. we have proposed a dynamic but deterministic communication model and have embedded it with the scheduling of the tasks on processors (rtos kernel services) to get the deterministic behavior of the application.
distributed context management in a mobility and adaptation enabling middleware (madam). as computing devices are getting smaller, we tend to bring them everywhere. consequently the operating conditions of the devices are constantly changing (e.g. changing user requirements, change in the system context and environment context). in order to be usable and dependable, applications and services need to self-adapt to changes in context. this work describes a context management approach for reducing the complexity of context aggregation and utilisation. the context manager is a core component in the madam (mobility and adaptation enabling middleware) project.
how to reuse exisiting interactive applications in ubiquitous computing environments? in ubiquitous computing environments, we will access various devices and appliances from a variety of mobile devices such as mobile phones, pdas and wearable devices.however, we need to reuse existing interactive applications that adopt traditional gui toolkits that assume to use mouses and keyboards, and these applications should be operated from the mobile interaction devices.our approach enables us to use existing gui-based interactive applications although a variety of interaction devices can be adopted to control the applications. therefore, the approach allows us to use traditional gui toolkits to build ubiquitous computing applications that choose appropriate interaction devices dynamically. the paper describes the design and implementation of our middleware to realize the approach. we also present some examples to show the effectiveness of our approach.
fuzzy approach to outsourcing of information technology services. the paper proposes a new approach for tackling the uncertainty and imprecision in outsourcing and evaluating information technology services. identifying suitable outsourcing options, evaluating them and choosing the best one are regarded as multiple decision criteria decision making problems under uncertainty, where the imprecise decision-maker's judgments are represented as fuzzy numbers. a fuzzy modification of the analytic hierarchy process is applied as an evaluation technique. unlike the known fuzzy prioritization techniques, the proposed method derives crisp weights from consistent and inconsistent fuzzy comparison matrices, which eliminates the need of additional aggregation and ranking procedures. a detailed numerical example, illustrating the application of our approach to outsourcing evaluation and selection is given.
handling run-time updates in distributed applications. the server side of business software systems is commonly implemented today by an ensemble of java classes distributed over several hosts. in this scenario, it is often necessary, for performance tuning or bug fixing, to update the code or change the location of some classes. since business systems must typically stay on-line 24 hours a day, changes and updates should be made without stopping system execution.this paper proposes a distributed software architecture which clearly separates the functionalities of the server-side application from its on-line adaptation capabilities. as a result, developers are freed from considering adaptation concerns, which are instead provided by separate, application-independent, transparently integrated components. the latter analyse data related to the operational conditions of the application, and, based on available statistics and expected behaviour, trigger changes on the application classes.the bytecode of classes expected to need on-line updating is modified at load time, so as to insert hooks that will support run-time changes. no tampering with class files is required. particular care has been taken to ensure the type-compatibility of classes thus manipulated.
the inheritance anomaly: ten years after. the term inheritance anomaly was coined in 1993 by matsuoka and yonezawa [15] to refer to the problems arising by the coexistence of inheritance and concurrency in concurrent object oriented languages (cools). the quirks arising by such combination have been observed since the early eighties, when the first experimental cools were designed [3]. in the nineties cools turned from research topic to widely used tools in the everyday programming practice, see e.g. the java [9] experience. this expository paper extends the survey presented in [15] to account for new and widely used cools, most notably java and c# [19]. specifically, we illustrate some innovative approaches to cool design relying on the aspect oriented programming paradigm [13] that aim at better, more powerful abstraction for concurrent oop, and provide means to fight the inheritance anomaly.
user adaptive content delivery mechanism on the world wide web. to reduce the user-perceived latency in web content delivery, many techniques have been proposed. one is a transmission time control mechanism that automatically adjusts the quality of inline objects, such as images on a web page, according to the client network bandwidth. another is a transmission order control mechanism that can transmit inline objects in a specified order preferred by users. in this paper, we describe the development of a user adaptive content delivery mechanism that integrates transmission time control and transmission order control. based on the user's preference profile, it dynamically prioritizes inline objects in terms of content quality and delivery order, and provides user with adapted inline objects. a prototype system has been implemented in java, and gives an example of adapted content delivery.
alternative source coding model for mobile text communication. this paper presents a new source coding model for the efficient transmission of mobile text messages. unlike conventional text messages, which are sent in the form of character sequences, the proposed method uses key-code sequences that reflect the user's typing history for authoring the message. the key-code representation can be as efficient as 4 bits per key-code by utilizing existing dictionary-based text entry systems and mobile phones equipped with the standard reduced keyboard. experiments that use an optimal dictionary show that the key-code representation can save 2.95 bits per character compared to the conventional ascii representation. further, computation of the entropy shows that the optimal code-word length of the ascii representation in kth-order approximation, where probability distributions of blocks of k symbols are given, cannot be comparable to that of the key-code in (k-l)-order approximation.
synchronization analysis for decentralizing composite web services. web services are emerging as the standard mechanism for making information and software available programmatically via the internet, and as building blocks for applications. a composite web service may be built using multiple component web services. once its specification has been developed, the composite service may be orchestrated either using a centralized engine or in a decentralized fashion. decentralized orchestration improves scalability and concurrency. dynamic binding coupled with decentralized orchestration adds high availability and fault tolerance to the system. in this paper, we categorize different forms of concurrency and provide an algorithm to identify these forms in a composite service specification. we also consider the impact of dynamic binding and faults on synchronization constructs.
pointer analysis of multithreaded java programs. this paper presents a context-sensitive and path-sensitive, intra-thread and inter-thread solution to combined pointer analysis, escape analysis and data dependence analysis of multithreaded java programs which uses a sparse representation. we build and maintain a complete static single assignment (ssa) form even for fields variables. we show how to compute inter-thread dependencies for multithreaded programs with structured fork-join constructs, open-ended threads, recursively generated threads, monitors, and wait-notify synchronization. we have implemented our algorithm in a slicer for java programs. our experimental results show that a sparse representation improves the analysis time and strong updates on field variables improves the precision.
a framework for collaborative control of applications. highly interactive applications are increasingly being used in decision support systems. highly interactive applications are increasingly being used in decision support systems. frequently these applications are run in collaborative environments in which interdisciplinary working groups participate to define scenarios, run simulations, and visualize the results. it is most expeditious if participants are able to simply "grab hold" of an application running in the shared environment to make some sort of basic adjustment, query, etc. without the need to move around the room to get to the keyboard and mouse. in this paper we describe the "remote application controller" (rac), a java-swing application running on a personal device that can launch, communicate with, and control a shared set of interactive applications running on various machines in a network. jini is used for application discovery and to establish basic communication between the rac and an application. to participate fully in the shared environment, an application is written using the remote user interface (rui) toolkit, a simple c++-based toolkit that creates standard gui controls on the host device, if appropriate, as well as a platform-independent xml-based description that is exported to requesting personal input devices. we describe the overall architecture of the system, the specifics of the rui toolkit, and then illustrate the system by describing some sample applications.
a service-oriented customizable digital library. web services represent the new methodological and technological challenge in the area of web-based systems, but they raise problems of discovery, interoperability, security. in this paper we address the problem of web service interoperability, proposing a digital library system that allows for the integration of services offered by different providers. farthermore, the services provided to the digital library user community can be customized according to user profiles. the proposed system represents a prototype example of a service-oriented integration architecture dynamically evolving as new services become available to be integrated.
communication delay in hypercubic networks with lrd traffic. realistic network traffic can exhibit the long-range dependent (lrd) feature which is characterised by a hyperbolically decaying correlation function and has strong effects on the performance of communication networks. as the convergence of simulations to a steady state under lrd workloads is often very slow, analytical models become cost-effective and versatile tools that can help designers to investigate system performance. this paper designs an analytical performance model for computing communication delay in adaptively routed hypercubic networks in the presence of lrd traffic. the model is derived in the context of pipelined circuit switching. the tractability and reasonable accuracy of the analytical model make it a practical and cost-effective evaluation tool to study the performance behaviour of hypercubic networks under lrd traffic.
color-based image retrieval using binary signatures. we propose two variations of a new image abstraction technique based on signature bit-strings as well as an appropriate similarity metric for color-based image retrieval. performance evaluation on a heterogeneous database of 20,000 images demonstrated that the proposed technique outperforms well-known approaches while still saving substantial amount of storage space, making it possible to store/search an image database of reasonable size using a few megabytes of main memory (e.g., 4 mbytes for 100,000 images).
performance prediction of wormhole switching in hypercubes with bursty traffic pattern. wormhole switching has been extensively deployed in the current-generation of high-end parallel systems. the performance of wormhole switching in hypercubes has been primarily investigated under the assumption that traffic load follows a poisson arrival process. however, many studies have shown that traffic in parallel computation environments can exhibit a high degree of burstiness and the poisson arrival process is unable to model the behaviour of bursty traffic. this paper proposes a new analytical model for wormhole-switched hypercubes under bursty traffic. simulation experiments demonstrate that the proposed model exhibits a good degree of accuracy under various operating conditions.
verification of a scheduler in b through a timed automata specification. this paper proposes a methodology for specifying and verifying schedulers using the b method. it is based on the refinement mechanism. the specification must manage time through clocks, whereas the natural modeling of schedulers exploits only stopwatches.
a relatedness-based data-driven approach to determination of interestingness of association rules. the presence of unrelated or weakly related item-pairs can help in identifying interesting association rules (ars) in a market basket. we introduce three measures for capturing the extent of mutual interaction, substitutive and complementary relationships between two items. item-relatedness, a composite of these relationships, can help to rank interestingness of an ar. the approach presented, is intuitive and can complement and enhance classical objective measures of interestingness.
efficient evaluation of relevance feedback for multidimensional all-pairs retrieval. new retrieval applications support flexible comparison for all-pairs best match operations based on a notion of similarity or distance. the distance between items is determined by some arbitrary distance function. users that pose queries may change their definition of the distance metric as they progress. the distance metric change may be explicit or implicit in an application (e.g., using relevance feedback). recomputing from scratch the results with the new distance metric is wasteful. in this paper, we present an efficient approach to recomputing the all-pairs best match (join) operation using the new distance metric by re-using the work already carried out for the old distance metric. our approach reduces significantly the work required to compute the new result, as compared to a naive re-evaluation.
looking for monotonicity properties of a similarity constraint on sequences. constraint-based mining techniques on sequence databases have been studied extensively the last few years and efficient algorithms enable to compute complete collections of patterns (e.g., sequences) which satisfy conjunctions of monotonic and/or anti-monotonic constraints. studying new applications of these techniques, we believe that a primitive constraint which enforces enough similarity w.r.t a given reference sequence would be extremely useful and should benefit from such a recent algorithmic breakthrough. a non trivial similarity constraint is however neither monotonic nor anti-monotonic. therefore, we have studied its definition as a conjunction of two constraints which satisfy the desired monotonicity properties: a pattern is called similar to a reference pattern x when its longest common subsequence with x (lcs) is large enough (i.e., a monotonic part) and when the number of deletions such that it becomes the lcs is small enough (i.e., an anti-monotonic part). we provide an experimental validation which confirms the added value of this approach on a biological database. classical issues like scalability and pruning efficiency are discussed.
using object-level run-time metrics to study coupling between objects. in this paper we present an investigation into the run-time behaviour of objects in java programs, using specially adapted coupling metrics. we identify objects from the same class that exhibit non-uniform coupling behaviour when measured dynamically.we define a number of object level run-time metrics, based on the static chidamber and kemerer coupling between objects (cbo) measure. these new metrics seek to quantify coupling at different layers of granularity, that is at class-class and object-class level. we outline our method of collecting such metrics and present a study of the programs from the jolden benchmark suite as an example of their use.a number of statistical techniques, principally agglomerative hierarchical clustering analysis, are used to facilitate the identification of such objects.
an architecture for supporting vicarious learning in a distributed environment. existing software systems designed to support learning do not adequately provide for vicarious learning in a cross-institutional collaborative environment. we have developed an architecture based on role-based access control, which provides the necessary security, robustness, flexibility, and explicit formulation of policy. such an architecture is general enough to be used in a variety of educational institutions and settings, yet flexible enough to allow a wide range of policies within a single system.
design and development of a multiversion olap application. this paper proposes a temporal version mapping concept and a sql query rewriting technique to support the olap query analysis in multidimensional database (mdb) systems modeled on multiversion schema. based on our proposed model, an integration solution of mdb schema change and multiversion olap query analysis performed over the changed database schema are taken into account. in addition, we present the system design and implementation of our prototype system to demonstrate our research idea.
a study for provisioning of web-based services to the end-user. although qos provision has been researched extensively for b-isdn (atm based) networks and it is also under research for ip networks (internet), until recently there was no real service environment to provide such qos to end users. demonstrators and laboratory experiments aimed mainly at proving specific technologies and architectures. recent advances in the commercialisation of technology and respective standardisation effort have changed the scenery. end to end networks, capable of qos support, are in a maturity status that will enable commercial deployment within the next few years. still, there are no applications to take advantage of such services. it would be most desirable to enhance the way users use current applications (such as the established web browser), than to try to introduce new application s/w. this paper proposes a method based on the open service gateway initiative (osgi) specification [1] that enables the quality of service (qos) for bandwidth demanding applications such as multimedia applications, by introducing s/w modules as enhancements into the existing applications. this method targets to the end-user, when using the network topolgy that is being standarised by the full services access network (fsan) [2].
schemata theory for the real coding and arithmetical operators. the schemata theory analyzes the effect of the selection process, mutation and crossover over the number of individuals that belong to a given schema, within generations. this analysis considers, in its original form, the binary coding and operators. in this article, we present an analogous study, focusing on the real number coding and arthmetical operators. unfortunately, the conventional schema definition is tightly dependent on discrete alphabets. therefore, following a generalization of the concept of schema, we present a particular definition that suits better the continuous domain. using this new definition, we reach an expression similar to the fundamental theorem of genetic algorithms [6] valid for the real coding of chromosomes.
a memory subsystem with comparator arrays for main memory database operations. we propose hardware supported intelligent memory access schemes for high performance database operations. a comparator array is installed in a memory module to help database operations, which allows simple predicate matching to be processed in the memory to reduce traffic between the cpu and the main memory. in this paper, we evaluate the query processing performance using introduced memory access schemes and show that hardware support memory accesses improve the performance of the main memory database operations.
policies translation for integrated management of grids and networks. computing grids require the underlying network infrastructure to be properly configured in order to have appropriate communications among the grids' nodes. the management of networks and the management of grids are currently executed by different tools operated by different administrative personnel. eventually, the grid communication requirements will need corresponding support from the network management tools, but such requirements are fulfilled only when grid administrators manually asks network administrators for corresponding configurations. in this paper we propose a policy translation mechanism that creates network policies given grid requirements expressed in grid policies. we also present a system prototype that allows (a) grid administrators to define grid policies, and (b) network administrators to define translating rules. these rules are used by the proposed translation mechanism to generate the necessary underlying network configuration policies.
cluc: a natural clustering algorithm for categorical datasets based on cohesion. we propose a clustering algorithm for categorical datasets, called cluc (clustering with cohesion), which uses a novel similarity measure, called cohesion, to determine the degree with which items/objects stick to clusters. we have implemented cluc and carried out extensive experiments on real-life and synthetic datasets. the results of experiments and their analyses indicate that cluc generates high quality clusters in that they conform to expert's opinion. our experiments on large synthetic data confirm that cluc is scalable when the dataset grows in the number of objects and/or dimensions. we also repeated the experiments with different orders of the items in the datasets. the results show that the proposed algorithm is order insensitive
terminology-driven mining of biomedical literature. in this paper we present an overview of an integrated framework for terminology-driven mining from biomedical literature. the framework integrates the following components: automatic term recognition, term variation handling, acronym acquisition, automatic discovery of term similarities and term clustering. the term variant recognition is incorporated into terminology recognition process by taking into account orthographical, morphological, syntactic, lexico-semantic and pragmatic term variations. in particular, we address acronyms as a common way of introducing term variants in biomedical papers. term clustering is based on the automatic discovery of term similarities. we use a hybrid similarity measure, where terms are compared by using both internal and external evidence. the measure combines lexical, syntactical and contextual similarity. experiments on terminology recognition and structuring performed on a corpus of biomedical abstracts are presented.
fair certified e-mail delivery. communication by e-mail has become a vital part of everyday business and has replaced most of the conventional ways of communicating. important business correspondence may require certified e-mail delivery, analogous to that provided by conventional mail service. this paper presents a novel certified e-mail delivery protocol that provides non-repudiation of origin and non-repudiation of receipt security services to protect communicating parties from each other's false denials that the e-mail has been sent and received. the protocol provides strong fairness to ensure that the recipient receives the e-mail if and only if the sender receives the receipt. the protocol makes use of an off-line and transparent trusted third party only in exceptional circumstances, i.e. when the communicating parties fail to complete the e-mail for receipt exchange due to a network failure or a party's misbehaviour. considerations have been taken in the protocol design to reduce the use of expensive cryptographic operations for better efficiency and cost-effectiveness.
simulation of a distributed recommendation system for pervasive networks. new networks based on short-range radio are emerging where mobile devices interact in a spontaneous and short-lived fashion. such pervasive networks involve devices approaching and finding each other, interacting to exchange some information or use some shared service, before disconnecting and leaving radio range. as such, they involve lots of potentially risky interactions with strangers. due to the lack of any infrastructure in these networks, using a distributed recommendation system to improve security is an attractive option. this paper describes a simulation of a simple distributed recommendation system running in such a network. these networks can be modeled as social networks and the simulation builds on an existing algorithm that has been shown to model social networks accurately. the results of the simulation suggest that with a relatively small overhead, the trust information can move effectively in such networks and the system can deliver a substantial decrease in the level of risk these spontaneous interactions involve.
the necklace-hypercube: a well scalable hypercube-based interconnection network for multiprocessors. in this paper, we introduce a new interconnection network, namely the necklace-hypercube, based on the binary cube with an array of processors (as a necklace of processors) attached to each two adjacent nodes of the hypercube network. topological properties of the proposed network are studied. some important basic operations such as optimal routing and vlsi layout in necklace-hypercubes are also addressed here. moreover, a comparison between the necklace-hypercube and some other popular networks is conducted. the comparison is based on vlsi layout, scalability, and other static topological properties. area-efficient vlsi layout and network scalability of the necklace-hypercube make it an attractive alternative to the well-known hypercube network topology, while keeping most of desirable properties of the hypercube.
email classification for contact centers. the explosive growth of the internet has made email an integral part of business communication. therefore, business customer service centers, or contact centers, are processing larger amounts of email interactions with customers. in this paper we discuss a preliminary email routing and classification system that filters and classifies incoming email messages upon their content. a module first attempts to identify and filter those email messages that do not require immediate (if any) responses. we call such email messages single messages. the emails that do require immediate responses are called root messages. a second module classifies messages in categories that characterize the type of interaction between the contact center operators and the customers. emails that are involved in such interactions form a thread and can be classified broadly into one of three categories: root, inner, and leaf. root messages are those that start a thread while a leaf message is the final email sent in an interaction. all other emails in the interaction are considered to be inner messages.
basic components for constraint solver cooperations. we propose a predefined set of basic components for designing and implementing constraint solver cooperations and solver cooperation languages. combining these components into patterns enables one to manage computation, control, and coordination needed for solver cooperations. our framework has been implemented with the chr language. we then used it to implement some cooperation primitives, and some constraint propagation with cooperative components.
learning the risk board game with classifier systems. the goal is to produce agents that are able to play the board game efficiently. classifier systems (cs) were chosen to learn the task at hand. cs were used to learn how to classify a set of (state, action) pairs. these pairs represent a game situation and the action a sensible player should execute when faced with such a situation. results show that the cs agents perform poorly when compared to humans, but can hold their own in specific situations against computer agents with a fixed, pre-programmed strategy.
a new table interpretation methodology with little knowledge base: table interpretation methodology. in this paper, a new methodology for table-form interpretation with little previous knowledge is presented. the first module performs the identification of line intersections in a table-form, the second module detects and corrects wrong intersections produced by fault intersection segments or by table artefacts (smudges, overlapping of handwritten data and fault segments). the third module performs the table-form cell extraction. the features used to interpret the table-form are directly extracted from the image itself by means of morphological tools. the evaluation of the efficiency is carried out from a total of 305 table-form images. experiments showed significant and promising results. the proposed approach reached a success rate over than 87% on average. the main advantage of the proposed methodology is requiring little knowledge from documents, being able to apply for a table-form majority.
a generic serializer for mobile devices. in this paper we describe a serializer component completely realized in .net managed code, able to run on a stripped versions of the .net platform (e.g., compact framework) and still generic enough to be used on .net or other cli compatible frameworks. such a component is not normally provided with stock libraries in their compact version, since its implementation is quite tricky when relying on reduced reflection services. however, this component makes easier the development of distributed applications involving mobile devices and desktop computers or mainframes. our implementation faced several problems ranging from lack of features in the base classes to the inter-framework portability problem, since the same object could have different implementation. the resulting product shows satisfactory performance figures and has a modular and flexible architecture.
finding optimal linear measures for feature selection in text categorization. a common way of performing feature selection in text categorization consists in keeping the features with highest score according to certain measures, like linear ones which have been successfully proposed in [1]. its disadvantage is that they need to previously determine the parameter which defines them. until now, this drawback has been overcome by taking manually a set of values for such parameter. this paper proposes a method for automatically determining optimal values of the parameter by means of solving a univariate maximization problem.
order relations and rigor in computing. rigor in computing depends in many ways on the integrity of order relations. commonly used hardware floating-point arithmetic can destroy that integrity. an available remedy is discussed with examples.
integrative approach for computationally inferring protein domain interactions. the current need for high-throughput protein interaction detection has resulted in interaction data being generated en masse, using experimental methods such as yeast-two-hybrids and protein chips. such data can be errorful and they often do not provide adequate functional information for the detected interactions; it is therefore useful to develop an in silico approach to further validate and annotate the detected protein interactions. given that protein-protein interactions involve physical interactions between protein domains, domain-domain interaction information can be useful for validating, annotating, and even predicting protein interactions. however, large-scale experimentally determined domain-domain interaction data do not exist; as such, we describe an integrative approach to computationally derive putative domain interactions from multiple data sources, including rosetta stone sequences, protein interactions, and protein complexes. we show the usefulness of such an integrative approach by applying the derived domain interactions to predict and validate protein-protein interactions.
order relations and rigor in computing. rigor in computing depends in many ways on the integrity of order relations. commonly used hardware floating-point arithmetic can destroy that integrity. an available remedy is discussed with examples.
a space aware agent-based modeling process for the study of hierarchical complex systems. complex systems are composed of many heterogeneous elements organized in a hierarchical way, whose mutual interactions make emergent collective behaviors to appear at the highest levels of observation. in biology, as shown by the integrative physiology theory [2], space and geometry have a significant role in the simulation results. in this paper we expose a process, and its set of formalisms, for modeling and simulation of complex system, going from structural modeling to dynamic simulation while integrating geometrical information in behavior study. our solution relies on three kind of concepts and techniques: hierarchical graphs for modeling the system structure and organization, zeigler's formalisms for the specification of components [6] and a space aware multi agent system for agent-based simulation.
a fault-tolerant directory service for mobile agents based on forwarding pointers. a reliable communication layer is an essential component of a mobile agent system. we present a new fault-tolerant directory service for mobile agents, which can be used to route messages to them. the directory service, based on a technique of forwarding pointers, introduces some redundancy in order to ensure resilience to stopping failures of nodes containing forwarding pointers; in addition, it avoids cyclic routing of messages, and it supports a technique to collapse chains of pointers that allows direct communications between agents. we have formalised the algorithm and derived a fully mechanical proof of its correctness using the proof assistant coq; we report on our experience of designing the algorithm and deriving its proof of correctness. the complete source code of the proof is made available from the www.
formal modeling and quantitative analysis of klaim-based mobile systems. klaim is an experimental language designed for modeling and programming distributed systems composed of mobile components where distribution awareness and dynamic system architecture configuration are key issues. in this paper we propose stocklaim, a stochastic extension of cklaim, the core subset of klaim. cklaim includes process distribution, process mobility, and asynchronous communication. the extension makes it possible to integrate the modeling of quantitative aspects of mobile systems--- e.g. performance---with the functional specification of such systems. we present a formal operational semantics of stocklaim, which associates a labeled transition system to each stocklaim network and a translation to continuous time markov chains for quantitative analysis. we also show how stocklaim can be used by means of a simple example, i.e. the modeling of the spreading of a virus.
a negotiation support system based on a multi-agent system: specificity and preference relations on arguments. in this paper, we propose a negotiation support system based on a multi-agent system. each agent assists a user in multi-criteria decision making and negotiates according to this decision-modelling with other agents, each of them representing a user. moreover agents assist users in the debate to negotiate a joint representation of the problem and automatically justify proposals with this joint representation.
induction of compact decision trees for personalized recommendation. we propose a method for induction of compact optimal recommendation policies based on discovery of frequent item-sets in a purchase database, followed by the application of standard decision tree learning algorithms for the purposes of simplification and compaction of the recommendation policies. experimental results suggest that the structure of such policies can be exploited to partition the space of customer purchasing histories much more efficiently than frequent itemset discovery algorithms alone would allow.
optimized transitive association rule: mining significant stopover between events. we consider a problem of finding optimized transitive association rules. a transitive association rule is a transitive sequence of different events. each of two consecutive events in a transitive association rule is a conventional association rule. transitive confidence is the product of confidence values of all the association rules in the event sequence. the optimized transitive association rule from a cause event to an effect event is the optimal sequence of events whose transitive confidence is maximum among all possible sequences from the cause to the effect. in this paper, we present space efficient algorithms for computing all of the optimized transitive association rules between events, whose transitive confidence is not less than a user specified minimum confidence value.
a security specification verification technique based on the international standard iso/iec 15408. this paper proposes a security specification verification technique based on the international standard iso/iec 15408. we formalized the security criteria of iso/iec 15408 and developed the verification technique of security specifications based on the formalized criteria with formal methods. with the technique, one can formally verify whether or not specifications satisfy the security criteria of iso/iec 15408. ambiguity and/or oversight about security in specifications written in natural language can also be detected.
community viewer: visualizing community formation on personal digital assistants. mobile computing has been mainly utilized for point-to-point communication services, such as e-mail or fax among people. to advance this field, the challenge is to encourage group communication by providing information that encourages community formation. as the first step towards this goal, we experimentally implemented the community viewer, which dynamically visualizes the communication interaction among people in the community. to design the community viewer, we introduced (1) the party room metaphor, which provides a virtual place for representing various community activities, and (2) the reflector icon, which reflects the activity of the corresponding individual while protecting his/her privacy. the static relationship among people and their dynamic activities are displayed in the spatial arrangement of reflector icons in the party room. we report our experiments on implementing and testing the community viewer in an international conference using 100 personal digital assistants.
using agents for multi-target search on the web. in this paper we present an approach to support multi-target search over a set of web nodes. multi-target search allows users to specify multiple interdependent search objectives. such objectives are then fulfilled by transparently contacting multiple information sources. we present a runtime platform and a language supporting extraction and assembly of information according to users' needs. the language is based on a xml query language and adapts it to the case where information is obtained by aggregating parts distributed over multiple sites. the platform is based on mobile agents and acts as an intermediary between users and information providers.
a framework for content-based image retrieval fully exploiting the semantics of annotation. we present a framework and an application for semantic-based retrieval of images. our approach adopts a two-level ontology structure in a subset of owl-dl. in the core ontology only generic spatial relations are represented, while domain ontologies are specific for the image collection. the approach allows semantic-based relevence ranking and results explanation for query refinement, by exploiting standard and non-standard inferences in description logics.
editorial message: semantic-based resource discovery, retrieval and composition track. a resource is a broad term comprising goods in electronic commerce, information available in remote sites, services announced through internet, learning objects, digital images, to mention a few. whatever their nature, the term "resource" is used in a general sense for whatever might be identified atomically and univocally. hence, the problem of resource matching and retrieval arises in several scenarios.
semantic matchmaking in a p-2-p electronic marketplace. matchmaking is the problem of matching offers and requests, such as supply and demand in a marketplace, services and customers in a service agency, etc., where both partners are peers in the transaction. peer-to-peer (p-2-p) e-commerce calls for an infrastructure treating in a uniform way supply and demand, which should base the match on a common ontology for describing both supply and demand. knowledge representation --- in particular description logics --- can deal with this uniform treatment of knowledge from vendors and customers, by modelling both as generic concepts to be matched. we propose a logical approach to supply-demand matching in p-2-p e-commerce, which allows us to clearly distinguish between exact, potential and partial match, and to define a ranking within the categories. the approach is deployed in a prototype system implemented for a particular case study (but easily generalizable) and is based on classic, a well-known knowledge representation system.
a hardware/software kernel for system on chip designs. as part of the soc design process, the application is partitioned between implementation in hardware and implementation in software. while it is customarily the application that is subject to partitioning, it is also possible to partition the software kernel. in this paper, a uniprocessor real-time kernel that implements the earliest deadline first (edf) scheduling policy is partitioned. it is partitioned by moving the edf scheduler into a coprocessor. the coprocessor size and performance are analyzed. a metric is then proposed that measures a coprocessor's impact on application feasibility. this metric permits a unified comparison of kernel coprocessors and application coprocessors during design partitioning.
preliminary performance evaluation of an adaptive dynamic extensible processor for embedded applications. in this research we investigate an approach for adaptive dynamic instruction set extension, tuning processors to specific applications after fabrication.
semantic analysis of web site audience. with the emergence of the world wide web, analyzing and improving web communication has become essential to adapt the web content to the visitors' expectations. web communication analysis is traditionally performed by web analytics software, which produce long lists of page-based audience metrics. these results suffer from page synonymy, page polysemy, page temporality, and page volatility. in addition, the metrics contain little semantics and are too detailed to be exploited by organization managers and chief editors, who need summarized and conceptual information to take high-level decisions. to obtain such metrics, we mine the content of the web pages output by the web server. for a given taxonomy covering the web site knwoledge domain, we compute the term weights in the output pages and we aggregate them using olap tools, in order to obtain concept-based metrics representing the audience of the web site topics. to demonstrate how our approach solves the cited problems, we actually compute concept-based metrics with sql server olap analysis service and our prototype wasa for a number of case studies. finally, we validate our results against a popular web analytics tool.
temporal query operators in xml databases. the contents of an xml database or an xml/web data warehouse is seldom static. new documents are created, documents are deleted, and more important: documents are updated. in many cases, we want to be able to search in historical versions, retrieve documents valid at a certain time, query changes to documents, etc. this can be supported by extending the system with temporal database features. in this paper we describe the new query operators needed in order to support an xml query language which supports temporal operations.
dynamic memory allocation strategies for parallel query execution. in the decision support queries which manipulate large data volumes, it is frequent that a query constituted by several joins can not be computed completely in memory. in this paper, we propose three strategies allowing to assign the memory of a shared-nothing parallel architecture to operation clones of a query. the performance evaluation of the three strategies shows that the strategies which favor the operation clones using a lot of memory obtain a better response time than the strategy which favors the clones using little memory. the main contribution of this paper is to take into account the available memory sizes on every processor and to avoid allotting the same processor to two operation clones that must run in parallel.
exploiting labels in structural operational semantics. structural operational semantics (sos) allows transitions to be labelled. this is fully exploited in sos descriptions of concurrent systems, but usually not at all in conventional descriptions of sequential programming languages.this paper shows how the use of labels can provide significantly simpler and more modular descriptions of programming languages. however, the full power of labels is obtained only when the set of labels is made into a category, as in the recently-proposed msos variant of sos.
automated assembly of software components based on xml-coded instructions. many approaches to reducing the cost, complexity and development time of software applications have been explored. several techniques, most recently the object oriented paradigm, have been developed to facilitate the reuse of code. even when these techniques employ the notion of components, they do so only in a limited way within the language's environment at development time. within the field of software engineering, the study of software architecture has emerged to provide language support for building configurations of components into runable systems. in this paper we present an xml architecture development meta-language. the specification is programming language independent. we discuss a prototype engine that uses this meta-language for the automated assembly of software applications.
concatenate feature extraction for robust 3d elliptic object localization. developing an efficient object localization system for complicated industrial objects is an important, yet difficult robotic task. to tackle this problem, we have developed a system consisting first of a vision model acquisition editor, where the object salient features are acquired through a human-in-the-loop approach. subsequently, two feature extraction algorithms, region-growing and edge-grouping, are applied to the object scene. finally, by kalman filter estimation of a proper ellipse representation, our object localization system successfully generates ellipse hypotheses by grouping edge fragments in the scene. the proposed system is validated by experiments using actual industrial objects.
acquisition of modulation pulses for a multi-robot system using genetic algorithm. ultrasonic sensors (sonars) are widely used in mobile robotics research for local environment perception and mapping. mobile robot platforms equipped with multiple sonars have been build and used by many researchers. a significant problem with the use of multiple sonars is that, when the sonars are operated concurrently, signal interference occurs, making it difficult to determine which received signal is an echo of the signal transmitted by a given sonar. one way of solving the problem of signal interference is to use different pulse patterns to modulate the signals emitted by the sonars. furthermore, in order to reduce the time taken to perform measurements, a concurrently operated sonar system is desirable. in this paper, a technique for acquiring suitable modulation pulses for signals emitted in a multi-sonar system is presented. in order to optimize the length of modulation signal, we propose a technique to reduce the probability of erroneous operation due to interference, using the niched pareto genetic algorithm (npga). the basic technique is illustrated for the case where two or more robots equipped with multiple sonars operate in the same environment.
training needs analysis: the first step in authoring e-learning content. online training and e-learning are becoming increasingly pervasive but some sectors are being left behind, particularly small to medium enterprises (smes). there are many reasons for this -- technical, organisational, resource related and cultural. commercially available e-learning courses that are aimed at a mass market do not match sme needs. one solution to these limitations is for companies to author their own e-learning so as to meet their own needs. most sme's do not have the expertise to do this and are reluctant to employ outside services solely for this purpose. training needs analysis (tna) provides a means to enable companies to identify areas where their employees require training. it can also be extended to produce a set of guidelines so they can author their own e-learning content through a structured design process. conducting a comprehensive training needs analysis is a large undertaking requiring a significant time and expertise. this paper outlines the generation of a generic online tna tool for smes allowing them to identify training requirements and assisting them to specify their own e-learning content in a structured manner.
timid acquisition of constraint satisfaction problems. in this paper we view interactive constraint acquisition as the process of learning constraints from examples and focus on the roles played by both the user and the system during an interactive session. we consider our user as a teacher who provides positive examples to an automated constraint acquisition system. each positive example represents a solution to the target constraint network we are trying to acquire. in this paper we compare a number of ways in which users can choose examples to be presented to a constraint acquisition system and identify the best strategy for the user to adopt. we recognize that not every user will naturally be able to assume the best profile and therefore present an assistant that can help a user construct good examples. we show that the assistant helps, in a significant manner, a human user trying to describe a target constraint network using a very small number of examples.
strategies for personal process improvement a comparison. every so often, a new methodology is launched onto the software engineering landscape with all the force of a religious crusade. from its humble beginnings software process improvement (spi) has spread its wings into virtually every sector of the software engineering community and in the process has transformed itself from a bag of tools and techniques, into a serious set of methodologies for enhancing organisational effectiveness and competitive success. in the latter half of the 1990's, individual spi methodologies such as psp [1] and pipsi [2] were promulgated as approaches to make the individual a better software engineer.surveys of european software organisations [3] have shown support for spi. in europe to date, spi programmes have concentrated at the organisational level, with less adoption at the level of the individual. this paper explores the role of individual-level methodologies in a european context and details the results of a series of experiments conducted by the authors.
eliciting coordination policies from requirements. software coordination models and languages describe how agents, resources and processes work together to implement a software system. one of their limitations is that they are used late in the software development and they are not integrated in a typical software development process.what we claim, with our research, is that if coordination becomes explicit and formalized as soon as possible in the life cycle, then it is possible to create coordinated-aware software systems. moreover, it is possible to verify the adequacy of a software architecture model (or of the code itself) with respect to these dynamic constraints as well as refine or disambiguate coordination requirements themselves.in previous work, we presented a uml-based development process to elicit, describe, analyze and validate system coordination properties that might be then specified with a suitable coordination language. in this general picture, the aim of this paper is to implement the first step, i.e., to elicit and formalize coordination policies. we propose a five steps approach that incrementally identifies the elements to be coordinated (i.e., static coordination) and how these entities may be coordinated (i.e., dynamic coordination).
agent technology and reconfigurable computing for mobile devices. next-generation mobile devices will be multifunctional and be expected to execute a broad range of compute-intensive applications. they are constraint by their device and mobility characteristics in achieving these expectations. reconfigurable logic has vast potential to facilitate mobile devices in meeting these future system performance requirements. this paper proposes incorporating reconfigurable computing and agent technology into mobile device environments. agent technology is an ideal middleware for mobile device management enabling effective utilization of reconfigurable resources. reconfigurable logic is integrated into the environment of a mobile device i.e. both into the physical device and into surrounding adaptive servers. an outline of the overall strategy is described. a detailed examination of enabling a client mobile device to dynamically offload reconfigurable hardware-software based computations to neighboring adaptive servers is presented. in addition, the paper details an initial demonstrator system within a medical environment.
towards scalability in tuple spaces. applications in ecommerce and ubiquitous computing ask for coordination of highly distributed and heterogenous data sources and services. tuple spaces offer a data-driven coordination model, hence they may be used for this purpose. however, research on distributed tuple spaces has not resolved yet how to render tuple spaces scalable. this is partly due to their informal conception. this paper formalizes tuple spaces and introduces a new concept for achieving scalability. it generalizes existing concepts and may lead to scalability in some application areas.
an hybridization of an ant-based clustering algorithm with growing neural gas networks for classification tasks. conventional ant-based clustering algorithms and growing neural gas networks are combined to produce an unsupervised classification algorithm that exploits the strengths of both techiques. the ant-based clustering algorithm detects existing classes on a training data set, and at the same time, trains several growing neural gas networks. on a second stage, these networks are used to classify previously unseen input vectors into the classes detected by the ant-based algorithm. the proposed algorithm eliminates the need of changing the number of agents and the dimensions of the environment when dealing with large databases.
supporting efficient dynamic aspects through reflection and dynamic compilation. as systems grow more and more complex, raising severe evolution and management difficulties, computationnal reflection and aspect-orientation have proven to enforce separation of concerns principles and thus to address those issues. however, most of the existing solutions rely either on a static source code manipulation or on the introduction of extra-code (and overhead) to support dynamic adaptation. whereas those approaches represent the extreme of a spectre, developpers are left with this rigid tradeoff between performance and dynamism. a first step toward a solution was the introduction of specialized virtual machines to support dynamic aspects into the core of the execution engine. however, using such dedicated runtimes limits applications' portability and interoperability.in order to reconcile dynamism and performance without introducing portability and interoperability issues, we propose a dynamic reflexive runtime that uses reflection and dynamic compilation to allow application-specific dynamic weaving strategics, whithout introducing extra-overhead compared to static monolithic weavers.
unstructured agent matchmaking: experiments in timing and fuzzy matching. we investigate distributed matchmaking within an multi-agent system in which agents communicate in a peer-to-peer fashion with a limited set of neighbors. we compare the performance of a system with synchronized time to that of systems using several different models of continuous time. we find little difference between the two, indicating that the ordering of events does not play a part in computation. we also compare a system in which matches are made deterministically between discrete task categories to one in which task matches are made non-deterministically between continuous task categories. we consider several possible matching functions and show that their support is proportional to the spread of categories tolerable. this holds for matching probabilities as low as 0.01. we further show that the matching function's 'height' relates to the speed at which the system finds matches. for instance, we show that for a triangular matching function, doubling the probability of each service matching results in about a 1.6 times speedup.
hierarchical video indexing based on changes of camera and object motions. since an entire video stream is too coarse as a level of abstraction, it is decomposed into a number of shots in general. a shot, which is defined as a collection of frames recorded from a single camera operation, is a basic unit for indexing video data. the existing video indexing models try to index these shots using either low-level (i.e., color, motion), or high-level (i.e., human interpretations) features. recently, hybrid approach to combine these low-level and high-level features for indexing purpose has been proposed to take advantages from both of them. in this paper, we extend our previous works for shot boundary detecting and indexing, and propose a new shot indexing technique to be fit into the hybrid environment. it supports in-depth classification of various kinds of shots according to camera motions and object movements. the results from preliminary experiments can confirm the effectiveness of the proposed techniques.
revisiting 1-copy equivalence in clustered databases. recently renewed interest in scalable database systems for shared nothing clusters has been supported by replication protocols based on group communication that are aimed at seamlessly extending the native consistency criteria of centralized database management systems. by using a read-one/write-all-available approach and avoiding the fine-grained synchronization associated with traditional distributed locking, one needs just a single distributed interaction step for each update transaction. therefore the system can easily be scaled to a large number of replicas, especially, with read intensive loads typical of web server support environments.in this paper we point out that 1-copy equivalence for causal consistency, which is subsumed by both serializability and snapshot isolation criteria, depends on basic session guarantees that are costly to ensure in clusters, especially in a multi-tier environment. we then point out a simple solution that guarantees causal consistency in the database state machine protocol and evaluate its performance, thus highlighting the cost of seamlessly providing common consistency criteria of centralized databases in a clustered environment.
a-brain: the multiple problems solver. intelligence is strongly related to the ability of solving different problems by a single system. general problems solvers such as artificial neural networks, evolutionary algorithms, particle swarm etc, have traditionally been tested against one problem at one time. the purpose of this research is to build a complex and adaptive system able to solve multiple (and different) problems. the proposed system, called a-brain, consists of several connected components (a decision maker, a trainer and several problem solvers) which provide a base for building complex problem solvers. the a-brain system is applied for solving some well-known problems in the field of symbolic regression. numerical experiments show that a-brain system is able to perform very well on the considered test problems.
an efficient single-pass query evaluator for xml data streams. data streams might be preferable to data stored in memory in contexts where the data is too large or volatile, or a standard approach to data processing based on data parsing and/or storing is too time or space consuming. emerging applications such as publish-subscribe systems, data monitoring in sensor networks [6], financial and traffic monitoring, and routing of mpeg-7 [7] call for querying data streams. in many such applications, xml streams are arguably more appropriate than flat data streams, for xml data is record-like, though not precluding multiple occurrences of fields with the same name. evaluating selection queries against xml streams is especially challenging because xml data is structured (like records) and might have unbounded size.this paper proposes an efficient single-pass evaluator of xpath queries against xml data streams unbounded (possibly infinite) in size. the evaluator is based on networks of independent deterministic pushdown transducers and it is especially suitable for implementation on devices with low-memory and simple logic as used, e.g., in mobile computing.
editorial message: special track on coordination models, languages and applications. the notion of coordination is more and more pervading many research fields both inside and outside computer science. many research areas such as software engineering, intelligent systems, agent technologies, internet applications, programming languages, parallel and distributed computing, all raise issues that concern the interaction among different sorts of entities --- processes, objects, components, agents --- as well as its management. despite their apparent diversity, this wide and heterogeneous range of problems actually exhibit large overlaps, and can be effectively faced and solved using a relatively reduced set of conceptual tools --- the notion of coordination model among the main ones. the purpose of a coordination model is represent and shape the space of interaction among entities --- whatever they are, however they interact. >from an engineering viewpoint, coordination languages and systems should enable engineers to integrate a number of possibly heterogeneous components, and to govern their interaction so as to form a (potentially distributed) software system with desired characteristics and functionalities.accordingly, the special track on coordination models, languages and applications takes deliberately a broad view of what is coordination. besides the traditional areas covering data-driven, control-driven, and hybrid models and languages, the track invited contributions from several areas where the concept of coordination is relevant, such as multiagent systems, web applications, software architectures, middleware platforms, knowledge-based systems, groupware and workflow management, etc.in response to the call for papers, 42 high quality submissions from 18 different countries were submitted to this special track, and fed into the reviewing process. altogether, there were more than 100 reviewers, and over 235 reviews were submitted by them --- an average of more than 5 reviews for each paper. based on the reviewers' reports, the general acm sac guidelines for acceptance and rejection of submissions, and the unavoidable time and space constraints associated with any conference, it was possible to select only 16 of these submissions as regular papers for presentation at the track. in the process, a number of good and interesting papers had to be rejected. among the papers presented at the special track, a further selection and revision process will lead to the publication of a special issue on coordination and knowledge engineering that will appear on the knowledge engineering review (http://uk.cambridge.org/journals/ker/).
integrating objective & subjective coordination in multi-agent systems. subjective and objective coordination can be integrated and exploited fruitfully in the same context. in this paper we investigate such integration in multi-agent systems, in particular taking as a reference context fipa agents - typically adopting subjective approaches - aiming at exploiting the coordination services provided by tucson objective coordination infrastructure.
declarative control of the future home environment. in this paper, we show how declarative rules, and declarative programming, are used to control a complex, heterogeneous system where rules from disparate sources must interoperate. we show how imperative codes can be automatically generated from declarative rules to bind with the resources in the execution environment. our approach shows how declarative programming can be used to effectively compose disparate systems together. we apply our approach to the control and co-ordination of home devices.
a model for association rules based on clustering. association rules and clustering are fundamental data mining techniques used for different goals. we propose a unifying theory by proving association support and rule confidence can be bounded and estimated from clusters on binary dimensions. three support metrics are introduced: lower, upper and average support. three confidence metrics are proposed: lower, upper and average confidence. clusters represent a simple model that allows understanding and approximating association rules, instead of searching for them in a large transaction data set.
a new algorithm for gap constrained sequence mining. the sequence mining problem consists in finding frequent sequential patterns in a database of time-stamped events. several application domains require limiting the maximum temporal gap between events occurring in the input sequences. however pushing down such constraint is critical for most sequence mining algorithms.in this paper we describe ccsm (cache-based constrained sequence miner), a new level-wise algorithm that overcomes the troubles usually related to this kind of constraints. ccsm adopts an innovative approach based on k-way intersections of idlists to compute the support of candidate sequences. our k-way intersection method is enhanced by the use of an effective cache that stores intermediate idlists for future reuse. the reuse of intermediate results entails a surprising reduction in the actual number of join operations performed on idlists.ccsm has been experimentally compared with cspade, a state of the art algorithm, on several synthetically generated datasets, obtaining better or similar results in most cases.
interval-based robust statistical techniques for non-negative convex functions, with application to timing analysis of computer chips. in chip design, one of the main objectives is to decrease its clock cycle. on the design stage, this time is usually estimated by using worst-case (interval) techniques, in which we only use the bounds on the parameters that lead to delays. this analysis does not take into account that the probability of the worst-case values is usually very small; thus, the resulting estimates are over-conservative, leading to unnecessary over-design and under-performance of circuits. if we knew the exact probability distributions of the corresponding parameters, then we could use monte-carlo simulations (or the corresponding analytical techniques) to get the desired estimates. in practice, however, we only have partial information about the corresponding distributions, and we want to produce estimates that are valid for all distributions which are consistent with this information.in this paper, we develop a general technique that allows us, in particular, to provide such estimates for the clock time.
an enablement detection algorithm for open multiparty interactions. coordination amongst an arbitrary number of entities has become an important issue in recent years in fields such as e-commerce, web-based applications and so on. traditionally, classical client/server primitives have been used to implement synchronisation and communication. but, when more than two entities need to coordinate by means of those primitives, the coordination must be decomposed into a number of client/server biparty interactions, leading the programmer to the need of thinking in terms of the protocols needed to achieve properties like livenes, atomicity and so on. in this paper, we present an algorithm to perform enablement detection to implement open multiparty interactions. this primitive provides a high level of abstraction since the programmer can implement multiparty coordination without the need of thinking in terms of protocols.
graphical modelling for aspect oriented sa. aspect-oriented programming (aop) has emerged in recent years as a new paradigm for software development. prisma is an approach for developing complex and large software systems. it combines the aspect-oriented software development (aosd) and the component-based software development (cbsd) in an elegant and novel way achieving a better management of crosscutting-concerns and software reusability. prisma approach proposes the separation of concerns from the very beginning of the software life-cycle in order to introduce them as reusable aspects of software architecture. in this paper, we focus on how the prisma modelling tool supports the graphical modelling of aspects and weavings.
an initial analysis and presentation of malware exhibiting swarm-like behavior. the slammer, which is currently the fastest computer worm in recorded history, was observed to infect 90 percent of all vulnerable internets hosts within 10 minutes. although the main action that the slammer worm takes is a relatively unsophisticated replication of itself, it still spreads so quickly that human response was ineffective. most proposed countermeasures strategies are based primarily on rate detection and limiting algorithms. however, such strategies are being designed and developed to effectively contain worms whose behaviors are similar to that of slammer.in our work, we put forth the hypothesis that next generation worms will be radically different, and potentially such techniques will prove ineffective. specifically, we propose to study a new generation of worms called "swarm worms", whose behavior is predicated on the concept of "emergent intelligence". emergent intelligence is the behavior of systems, very much like biological systems such as ants or bees, where simple local interactions of autonomous members, with simple primitive actions, gives rise to complex and intelligent global behavior. in this manuscript we will introduce the basic principles behind the idea of "swarm worms", as well as the basic structure required in order to be considered a "swarm worm". in addition, we will present preliminary results on the propagation speeds of one such swarm worm, called the zachik worm. we will show that zachik is capable of propagating at a rate 2 orders of magnitude faster than similar worms without swarm capabilities.
pine - podium incremental neighbor evaluator for classifying spatial data. given a set of training data, nearest neighbor classification predicts the class value for an unknown tuple x by searching the training set for the k nearest neighbors to x and then classifying x according to the most frequent class among the k neighbors. each of the k nearest neighbors casts an equal vote for the class of x. in this paper, we propose a new algorithm, podium incremental neighbor evaluator (pine), in which nearest neighbors are weighted for voting. a metric called hobbit is used as the distance metric, and a data structure, the p-tree, is used for efficient implementation of the pine algorithm on spatial data. our experiments show that by using a gaussian podium function, pine outperforms the k-nearest neighbor (knn) method in terms of classification accuracy for spatial data. in addition, in the pine algorithm, all the instances are potential neighbors so that the value of k need not be pre-specified as in knn methods. by assigning high weights to the nearest neighbors and low (even zero) weights to other neighbors, high classification accuracy can be achieved.
editoral message: special track on coordination models, languages and applications. in last few years, the field of coordination models and languages has earned the respect of other computer science researchers as they recognized that the understanding of how parts can be efficiently organized as a ensemble is of prime importance to the design of distributed complex systems. the proliferation of network computing and mobile computation, and especially the ubiquity of the internet has made coordination one of the key areas in modern computing. this track aims at bringing together researchers working on applied issues in coordination, ranging from new models to applications.coordination is a multidisciplinary topic related to almost every aspect of computer science. from information security to mobile computation, from artificial intelligence to wireless communication, it is difficult to find a computer science field in which coordination does not play a central role. the glue between the many research agendas in the coordination field is the notion of a coordination model that represents and shapes the space of interaction among entities.the coordination track at the 2004 symposium on applied computing deliberately acknowledges this diversity, taking a broad perspective on the coordination topic. throughout the years, the track has served as a forum for cutting edge research on coordination. yet, the track's main focus is on practical (applied) aspects of coordination so as to fit well with the general objectives of the symposium.
special track on coordination models, languages and applications. in last few years, the field of coordination models and languages has earned the respect of other computer science researchers as they recognized that the understanding of how parts can be efficiently organized as a ensemble is of prime importance to the design of distributed complex systems. the proliferation of network computing and mobile computation, and especially the ubiquity of the internet has made coordination one of the key areas in modern computing. this track aims at bringing together researchers working on applied issues in coordination, ranging from new models to applications.
hybrid lagrangian relaxation for bandwidth-constrained routing: knapsack decomposition. to deliver quality of service, internet service providers are seeking effective solutions to optimize their networks. one of the main tasks is to optimally route a set of traffic demands, each along a single path, while satisfying their bandwidth requirements and without exceeding edge capacities. this is an integer multicommodity flow problem, which is known to be np-hard. to solve this problem efficiently, a new complete and scalable hybrid solver (hlr) integrating lagrangian relaxation and constraint programming has been proposed. it exploits the shortest path decomposition of the problem and has been shown to yield significant benefits over several other algorithms, such as cplex and well-known routing heuristics. in this paper we explore an alternative dualization within the same hybrid. we present a variant of hlr, adapted to the knapsack decomposition of the problem. although this relaxation seems less natural, experimental results show that it has some advantages. the paper provides an interesting insight of where the benefits may lie, in particular for larger and harder cases where the ratio of total demand to available capacity is higher.
handwritten character skeletonisation for forensic document analysis. a new method of skeletonisation (stroke extraction) of handwritten character images is presented. the method has been designed to extract the skeleton which is very close to human perception of the original pen tip trajectory. the need in such skeletonisation arises from feature extraction algorithms which are sensitive to inaccuracies in positions of skeleton curves. one class of such algorithms are those for extraction of features used in forensic analysis of handwriting. the skeleton is constructed in three steps directly from the grayscale image and is represented as a set of curves, which, in turn, are represented as cubic b-splines. such representation also eases feature extraction.experiments have been performed on 150 images of grapheme "th" written by different writers. the assessment of the skeletonisation results are presented.
an improved formal specification of the internet open trading pprotocol. the internet open trading protocol (iotp) is an electronic commerce protocol being developed by the internet engineering task force. the core of iotp is a set of electronic transactions that reflect common trading activities such as purchasing goods or depositing funds. we use coloured petri nets (cpns) to specify iotp. we enhance our previous specifications to include procedures for error handling and arbitrary transaction cancellation. this provides a complete specification of iotp's authentication and payment related transactions. modularity and re-use are also improved. the new specification conforms to the narrative description of iotp and allows us to analyse the protocol throughly.
mtree: an xml xpath graph index. this paper introduces the mtree index algorithm, a special purpose xml xpath index designed to meet the needs of the hierarchical xpath query language. with the increasing importance of xml, xpath, and xquery, several methods have been proposed for creating xml structure indexes and many variants using relational technology have been proposed. this work proposes a new xml structure index, called mtree, which is designed to be optimal for traversing all xpath axes. the primary feature of mtree lies in its ability to provide the next subtree root node in document order, for all axes, to each context node in o(1). mtree is a special purpose xpath index structure that matches the special purpose query requirements for xpath. this approach is in contrast to other approaches that map the problem domain into general purpose index structures such as b-tree that must reconstruct the xml tree from those structures for every query. mtree supports modification operations such as insert and delete. mtree has been implemented both in memory and on disk, and performance results using xmark benchmark data are presented showing up to two orders of magnitude improvement over other well-known implementations.
relevance feedback methods for logo and trademark image retrieval on the web. relevance feedback is the state-of-the-art approach for adjusting query results to the needs of the users. this work extends the existing framework of image retrieval with relevance feedback on the web by incorporating text and image content into the search and feedback process. some of the most powerful relevance feedback methods are implemented and tested on a fully automated web retrieval system with more than 250,000 logo and trademark images. this evaluation demonstrates that term re-weighting based on text and image content is the most effective approach.
a benchmark on soap's transport protocols performance for mobile applications. handheld mobile devices with wireless capability are gaining popularity. soap is a text-based protocol for web services, but it has high overhead and its suitability for resource-constrained devices over wireless networks needs to be reevaluated. soap uses http; http in turn uses tcp as the underlying transport protocol for transmitting messages. however, tcp has a high overhead and high network latency. in this paper, a benchmark of the performance of different underlying transport protocols for soap is reported. we show that soap-over-http and soap-over-tcp are inefficient and lead to high latency and transmission overhead for wireless networks. the results also show that soap-over-udp provides much higher throughput compared to soap-over-http.
active contour on the basis of inertia. this paper present a method for image segmentation, which is an adaptation of the classical active contours algorithm, also called "snakes", using a new internal energy approach. the classical model computes the energy function based on changes in gradient values, thus determining the detection of the object's edges. in the proposed model, the active contour moves attracted or repelled by its mass center, thus keeping the inertia towards shape compression or expansion. this represents an intuitive, simple and efficient scheme that constitutes an alternative to classical segmentation methods.
lights: a lightweight, customizable tuple space supporting context-aware applications. the tuple space model inspired by linda has recently been rediscovered by distributed middleware. moreover, some researchers also applied it in the challenging scenarios involving mobility and more specifically context-aware computing. context information can be stored in the tuple space, and queried like any other data.nevertheless, it turns out that conventional tuple space implementations fall short of expectations in this new domain. on one hand, many of the available systems provide a wealth of features, which make the resulting implementation unnecessarily bloated and incompatible with the tight resource constraints typical of this field. moreover, the traditional linda matching semantics based on value equality are not appropriate for context-aware computing, where queries are often formulated over value ranges, and where there is a prominent need to deal with imprecise information coming from multiple sources.in this paper, we describe a new tuple space implementation called lights. originally developed as the tuple space core of the lime [11] system, lights provides a flexible framework that makes it easy to introduce extensions to the tuple space and in general to customize the tuple space implementation. the design and programming interface of lights is presented, and its flexibility demonstrated by illustrating extensions that proved useful in the development of context-aware applications.
high-integrity extreme programming. we assess the applicability of extreme programming practices to engineering high-integrity systems, focusing on the characteristics of this problem domain that distinguish it from those considered more traditional for agile development. we suggest that extreme programming needs both extension and modification to be applicable to engineering high-integrity systems, and discuss promising extensions.
a black-box approach for web application sla. web servers nowadays have to cope with unprecedented amounts of workload, due to increasing popularity and complexity; in particular, dynamically generated content becomes the standard, hence the term web application. providing enough resources to sustain these workloads is a grand challenge, thus the application's runtime environment is often trusted to third-party hosting providers. to optimize resource utilization, hosting providers tend to share server machines between several applications. in such context, it is desirable to make sure that hosted applications are guaranteed a predictable level of performance, in other words implement service-level agreements (slas).in this paper, we present an approach to web application sla, based on profiling and geared at black-box server components, which allows us to express slas using application-level metrics, such as request rates. we conducted experiments in the context of a two-tiers server architecture shared by two e-commerce applications, and were able to enforce performance guarantees expressed as a number of concurrent user sessions.
an action semantics for mof 2.0. we show how to extend mof 2.0 to include an action semantics to support behavioural modelling. we explain why such an extension is useful, particularly for model transformation and consistency checking.
an intelligent biological information management system. as biomedical researchers are amassing a plethora of information in a variety of forms resulting from the advancements in biomedical research, there is a critical need for innovative information management and knowledge discovery tools to sift through these vast volumes of heterogeneous data and analysis tools. in this paper we present a general model for an information management system that is adaptable and scalable, followed by a detailed design and implementation of one component of the model. the prototype, called biosifter, was applied to problems in the bioinformatics area. the results indicate that biosifter is a powerful tool for biological researchers to automatically retrieve relevant text documents from biological literature based on their interest profile. the paper also presents experimental studies with real users to illustrate the efficacy of the approach.
using genetic programming for the induction of novice procedural programming solution algorithms. this paper describes a genetic programming system for the induction of solutions to novice procedural programming problems. this genetic programming system will form part of a generic architecture for the development of intelligent programming tutors for the procedural and object-oriented programming paradigms. an account of the primitives and system parameters needed for the derivation of solutions to problems for each of the introductory procedural programming topics is provided. this is followed by an analysis of the solutions induced by the genetic programming system. finally, the paper discusses the future work that will be carried as part of the initiative to evaluate genetic programming as a means of inducing solutions to novice procedural and object-oriented programming problems.
editorial message: special track on bioinformatics. advances in bioinformatics are providing the foundations for the convergence of agribusiness, healthcare, pharmaceuticals, computing and other fields, into what promises to be the largest industry in the world, the life sciences industry. much of the information to support biology research is available from online databases in a multitude of formats. the challenge is to obtain information and knowledge from these databases using innovative computational approaches to predict and explain phenomena in many application fields. one example of this computational challenge is to identify biological pathways using data, information, and knowledge scattered over heterogeneous databases. computational tools using system-theoretic approaches are needed to model metabolic pathways, signal-transduction pathways, genetic regulatory circuits and biological systems modeling. by identifying conserved genomes and pathways across several species at a high level, we hope to understand how stable biological systems have evolved. over the last few years, very high throughput techniques, such as microarray analysis, have provided many insights into genomes, metabolmes and transcriptomes and into cellular function. these data are now increasingly complemented by mass spectrometry technology, providing insights into proteomes. this computational analysis technique poses many new challenges.
morphing of image represented objects using a physical methodology. this paper presents a methodology to do morphing between image represented objects, attending to their physical properties. it can be used amongst images of different objects, or otherwise, between different images of the same object.according to the used methodology the given objects are modelled by the finite element method, and some nodes are matched by modal analysis. then, by solving the dynamic equilibrium equation the displacement field is determined, which allows the simulation of the objects' deformation.this physical approach also allows the computation of the involved strain energy, therefore the estimated morphing can be represented by the local or global strain energy values.this paper also describes the solution used to simulate only the non-rigid components of the involved deformation.
editorial message: special track on bioinformatics. advances in bioinformatics are providing the foundations for the convergence of agribusiness, healthcare, pharmaceuticals and computing into what promises to be the largest industry in the world, the life sciences industry. a large part of the information to support biology research is available on large number of heterogeneous databases in both structured and unstructured formats. the challenge is to obtain information and knowledge from these databases using innovative computational approaches to support and promote biomedical research. one example of such a computational challenge is in identifying biological pathways using data, information, and knowledge scattered over heterogeneous databases. computational tools using system-theoretic approaches are needed to model metabolic pathways, signal-transduction pathways, genetic regulatory circuits and biological systems modeling. by comparing the genomes and pathways of several species at a high level, we hope to understand how stable biological systems have evolved. over the last few years, microarray data have provided many insights into the transcriptome and into cellular function. these data are now increasingly complemented by mass spectrometry data of the proteome, whose analysis poses new computational challenges.
fite-trt: a high quality translation technique for oov words. we devised a novel statistical technique for the identification of the translation equivalents of source words obtained by transformation rule based translation (trt). the effectiveness of the devised fite (frequency-based identification of translation equivalents) technique was tested using biological and medical cross-lingual spelling variants and oov words in spanish-english and finnish-english trt. for spanish-english, translation recall was 89.2%-91.0% and for finnish-english 71.9%-72.9%. for both language pairs fite-trt achieved high translation precision, i.e., 97.0%-98.8%. the technique also reliably identified native source language words, i.e., source words that cannot be correctly translated by trt. dictionary-based clir augmented with fite-trt performed substantially better than dictionary-based clir where oov keys were kept intact.
support to the management of clinical activities in the context of protocol-based care. in this paper we describe the system smart (supporting medical activities in real-time). the goal of the system is real-time assistance to physicians who execute diagnostic or therapeutic protocols in a clinical context. smart is able to retrieve a protocol from its knowledge base and to monitor its execution step by step for a single patient. different protocols for different patients can be followed at the same time in a health care structure.the prototype realized supports the execution of protocols for evaluating surgical risks. it has been implemented according to the specifications given by the 4th surgical clinic of "policlinico umberto i" and reflects the activities actually performed in that hospital. however, the protocol model defined is general-purpose and we envisage an easy application to other contexts and therefore to the informatization of other protocols.
statistical properties of transactional databases. most of the complexity of common data mining tasks is due to the unknown amount of information contained in the data being mined. the more patterns and corelations are contained in such data, the more resources are needed to extract them. this is confirmed by the fact that in general there is not a single best algorithm for a given data mining task on any possible kind of input dataset. rather, in order to achieve good performances, strategies and optimizations have to be adopted according to the dataset specific characteristics. for example one typical distinction in transactional databases is between sparse and dense datasets. in this paper we consider frequent set counting as a case study for data mining algorithms. we propose a statistical analysis of the properties of transactional datasets that allows for a characterization of the dataset complexity. we show how such characterization can be used in many fields, from performance prediction to optimization.
file system framework for organizing sensor networks. we present a filesystem based framework to support common operations and applications in the sensor networks domain. the framework uses virtual filesystems to encapsulate resources at various levels of the sensor network hierarchy that are exported to clients who can then use common file operations to interact with the network. our approach is scalable, supports concurrent access of sensors and is compatible with lightweight sensor architectures. in this paper we introduce file representation of sensor networks, describe the general architecture used in implementing the framework and illustrate its use in supporting common sensor network operations.
a constraint logic programming approach to 3d structure determination of large protein complexes. the paper describes a novel framework, constructed using constraint logic programming and parallelism, to determine the association between parts of the primary sequence of a protein and &alpha;-helices extracted from 3-dimensional low-resolution descriptions of large protein complexes. the association is determined by extracting constraints from the 3d information, regarding length, relative position, and connectivity of helices, and solving these constraints with the guidance of a secondary structure prediction algorithm. parallelism is employed to enhance performance on large proteins. the framework provides a fast, inexpensive alternative to determine the exact tertiary structure of unknown proteins.
: flash crowds alleviation network. with the rapid spread of information and ubiquitous access of browsers, flash crowd, a sudden, unanticipated surge in the volume of request rates, has become the bane of many internet websites. this paper models and presents fcan, an adaptive cdn network that dynamically optimizes the system structure between peer-to-peer (p2p) and client-server(c/s) configurations to alleviate flash crowds effect. fcan constructs p2p overlay on cache proxy layer to distribute the flash traffic from origin web server. it uses policy-configured dns redirection to route the client requests in balance, and adopts strategy load detection to monitor and react the load changes. our preliminary simulation result shows that the system is overall well behaved, which validates the correctness of our basic design and points the way for the future research.
a hardware extension of the risc microprocessor for attribute grammar evaluation. conventional implementations of attribute grammar (ag) evaluators in embedded systems today, are solely of software nature. a compiler transforms the parser's specification along with the declarative attribute evaluation rules into a behaviorally equivalent procedural program to be executed on the microprocessor. this approach affects the final system's performance as well as the complexity of the final implementation. efforts in presenting hardware implementations of ag evaluators, although efficient enough in terms of performance, are usually fully implemented in hardware and as a consequence restricted to a single application. we exploit hw/sw codesign methods in the effort of presenting a hardware implementation of ag evaluators that is both reprogrammable and increases the desired system's performance. we achieve that by extending a conventional risc microprocessor by combining it with a programmable implementation of a hardware parser to propose a fully programmable ag evaluator that supports the execution of hybrid combinations of declarative-procedural code. the hardware parser increases design efficiency of tree derivations while the risc microprocessor handles the attribute evaluation computations. as a result, performance is increased while design flexibility required in embedded system applications is preserved.
optimizing syntax patterns for discovering protein-protein interactions. we propose a method for automated extraction of protein-protein interactions from scientific text. our system matches sentences against syntax patterns typically describing protein interactions. we define a set of 22 patterns, each a regular expression consisting of anchor positions and parameterizable constraints. this small set is then refined and optimized using a genetic algorithm on a training set. no heuristic definitions are necessary, and the final pattern set can be generated completely without manual curation. our method can be applied to any syntax pattern-based protein-protein interaction system and thus complements related work on building comprehensive sets of such patterns. the application of different fitness-functions during evolution provides an easy way to tune the system either toward precision, recall, or f-measure. we evaluate our system on two samples, one derived from the biocreative corpus, the other from references in the dip. the automatic refinement of patterns adds up to 16% to the precision, and 5% to the recall of our system. we additionally study the impact of a proper protein name recognition, which could improve precision by about 17% and recall by 12%.
a procedure to model the frequency response. modeling the frequency response of a component or system is a suitable approach in different engineering applications in order to analyze its behavior. sometimes it is also very interesting to model actual devices or systems in order to check their performance. in these cases, some measurements (either in the time or in the frequency domain) must be obtained from the devices or systems.a procedure of modeling the frequency response is presented in this paper. a modeling tool has been developed based on this procedure which could be adapted to different engineering applications. some experimental results have been obtained on checking the health of an electrical transformer working in the utility grid.
extended data dependency approach: a robust way of rebuilding database. attack on information systems through electronic media has become epidemic with the explosion of internet technologies and their applications. it is vital to start the assessment and recovery efforts immediately after an attack is detected. in this research, we consider dependency among data items to assess the damage. but the existing data dependency method is extremely limited. therefore, in this paper, we have provided the theory and concepts needed to make this approach more robust and general. these include: classifications of read and write operations, a new definition of transaction and a new representation of the scheduler. based on this developed theory, we have proposed an algorithm for damage assessment and recovery in a database that has suffered from information attack.
the meta-object facility typed. the object managment group's meta-object facility (mof) [9] is a semiformal approach to writing models and metamodels (models of models). the mof was developed to enable systematic model/metamodel interchange and integration. the approach is problematic, unless metamodels are correctly specified: an error in a metamodel specification will propagate throughout instantiating models and final model implementations. an important open question is how to develop provably correct metamodels. this paper outlines a solution to the question, in which the mof meta-modelling approach is formalized within constructive type theory.
svd-based collaborative filtering with privacy. collaborative filtering (cf) techniques are becoming increasingly popular with the evolution of the internet. such techniques recommend products to customers using similar users' preference data. the performance of cf systems degrades with increasing number of customers and products. to reduce the dimensionality of filtering databases and to improve the performance, singular value decomposition (svd) is applied for cf. although filtering systems are widely used by e-commerce sites, they fail to protect users' privacy. since many users might decide to give false information because of privacy concerns, collecting high quality data from customers is not an easy task. cf systems using these data might produce inaccurate recommendations. in this paper, we discuss svd-based cf with privacy. to protect users' privacy while still providing recommendations with decent accuracy, we propose a randomized perturbation-based scheme.
fitting standard software to non-standard organisations. this paper investigates the increasing trend within organisations and institutions of adopting pre-built, standardised management and administrative computer systems. the particular focus is on enterprise resource planning (erp) systems in the context of higher education, and the further development of university specific functionality - the 'campus management' (cm) module. we investigate this software as it adapted to the needs of a university in the uk (whom we are calling 'big_civic') and a potential global market. drawing on ideas from the sociology of science and technology we argue that in order to understand the 'dependability' and 'fit' (we tentatively conflate these two terms) of such systems we should attempt to study their 'biographies': this is the process of describing artefacts as they move around and are adapted and redefined according to the needs of each new place.
stochastic scheduling of active support vector learning algorithms. active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. in the past, simple active learning algorithms like random learning and query learning have been proposed for the design of support vector machine (svm) classifiers. in random learning, examples are chosen randomly, while in query learning examples closer to the current separating hyperplane are chosen at each learning step. however, it is observed that a better scheme would be to use random learning in the initial stages (more exploration) and query learning in the final stages (more exploitation) of learning. here we present two novel active sv learning algorithms which use adaptive mixtures of random and query learning. one of the proposed algorithms is inspired by online decision problems, and involves a hard choice among the pure strategies at each step. the other extends this to soft choices using a mixture of instances recommended by the individual pure strategies. both strategies handle the exploration-exploitation trade-off in an efficient manner. the efficacy of the algorithms is demonstrated by experiments on benchmark datasets.
geographical information recognition and visualization in texts written in various languages. in this paper, we describe a system that recognises place names in natural language text and produces geographic maps and animations showing the geographical coverage of texts about a certain subject as it changes over time. as the system is built to analyse texts in many different languages, it restricts the usage of linguistic analysis tools to the minimum. instead, it relies on a gazetteer containing place names in different languages and uses heuristics for disambiguation purposes.
dspxplore: design space exploration methodology for an embedded dsp core. high mask and production costs for the newest cmos silicon technologies increase the pressure to develop hardware platforms useable for different applications or variants of the same application. to provide flexibility for these platforms the need on software programmable embedded processors is increasing. to close the gap concerning consumed silicon area and power dissipation between optimized hardware implementations and software based solutions, it is necessary to adapt the subsystem of the embedded processor to application specific requirements. dspxplore can be used to explore the design space of risc based embedded core architectures. at an early stage of the project the main architectural requirements of the application code can be identified in order to meet the area and power dissipation requirements. during the development process dspxplore supports fine-tuning of the subsystem architecture (e.g. modifications of the binary coding of instructions). dspxplore is part of a development project for a configurable dsp core.
the intensity level reduction in radiation therapy. in this paper, we study an interesting intensity level reduction (ilr) problem, which is crucial for solving the "step-and-shoot" delivery planning problem in intensity-modulated radiation therapy (imrt). imrt aims to deliver a highly conformal radiation dose to a target tumor while sparing the surrounding normal tissues. effective intensity level reduction approaches significantly reduce the patient's exposure under the radiation and improve the treatment efficiency. we propose a new intensity level reduction method for step-and-shoot delivery planning, and further model the intensity level reduction problem as computing a set of shortest monotone paths (smps) in certain specific geometric graphs, called multi-column graphs, of pseudo-polynomial sizes. based on a judicious characterization of the intrinsic geometric structures of the graphs, we develop a novel graph pruning scheme and compute the smps without explicitly constructing the graphs, yielding an efficient o(mn logn) time algorithm for solving the intensity level reduction problem on an intensity map (specifying a radiation dose prescription) of size m x n.
domotic house gateway. this paper presents a domotic house gateway capable of seamlessly interacting with different devices from heterogeneous domotic systems and appliances. such a gateway also provides the possibility to automate device cooperation through an embedded rule-based engine, which can be dynamically and automatically updated to accommodate necessities and anticipate users' actions. some practical applications will show the effectiveness of the system.
aspect oriented programming for a component-based real life application: a case study. aspect oriented programming, a relatively new programming paradigm, earned the scientific community's attention. the paradigm is already evaluated for traditional oop and component-based software development with remarkable results. however, most of the published work, while of excellent quality, is mostly theoretical or involves evaluation of aop for research oriented and experimental software. unlike the previous work, this study considers the aop paradigm for solving real-life problems, which can be faced in any commercial software. we evaluate aop in the development of a high-performance component-based web-crawling system, and compare the process with the development of the same system without aop. the results of the case study mostly favor the aspect oriented paradigm.
a relational approach to the capture of dicom files for grid-enabled medical imaging databases. the standard for digital imaging and communications in medicine (dicom) specifies a non-proprietary digital imaging format, file structure and data interchange protocols for the transfer of biomedical images and non-image data related to such images--it is a specification of the components that are required in order to achieve inter-operability between biomedical imaging computer systems. in this paper we describe how a grid-enabled medical imaging database---ediamond--employs an object-relational approach to the storage of dicom files. although the work described has been carried out within the context of a particular mammography related project, the underlying principles are applicable to other medical imaging systems dealing either with other modalities or with other diseases.
automatically discovering design patterns and assessing concern separations for applications. in this paper we present a tool that assists in the automated analysis of a java application, aimed at two purposes: (i) identifying class structure and, within this, micro-architectures that conform to known design patterns; (ii) providing visual representations of classes, concerns and their relationships. this affords a more abstract view of the analysed application, letting its structure emerge more clearly and its components be separately understood. as a result, it becomes easier for developers to assess whether well-known desirable characteristics, notably those favouring modularity and concern separation, or rather bad design choices, have been incorporated into the application.the proposed approach can be helpful both within the undertaking of a new development effort, and reverse engineering of an existing application in view of its evolution.
protecting sensitive patient data via query modification. it is well understood that a conflict between functionality and confidentiality exists within the context of medical research databases: while patients' rights must be preserved, restricting access to data can reduce the value of the data that is available to the researcher. as such, limiting access so that confidentiality is preserved without reducing functionality more than is necessary should be a key aim of every designer of medical research databases. in this paper we investigate the application of query modification for the protection of sensitive patient data with a view to preserving functionality as much as possible. the work has been conducted within the context of the e-diamond research project.
distributed query adaptation and its trade-offs. adaptive query processing in large distributed systems has seen increasing importance due to the rising environmental fluctuations in a growing internet. we describe ginga, an adaptive query processing engine that combines proactive (compile-time) alternative query plan generation with reactive (run-time) monitoring of network delays. the core of ginga approach is the notion of adaptation space and mechanisms for coordinating and integrating different kinds of query adaptation. an adaptation space consists of a set of adaptation triggers and a set of adaptation cases associated with the triggers. each adaptation case describes a specific adaptation opportunity of the query execution when changes to the runtime environment are detected. our experimental results show that ginga query adaptation can achieve significant performance improvements (up to 40% of response time gain) for processing distributed queries over the internet.
towards model-based generation of self-priming and self-checking conformance tests for interactive systems. this paper describes a model-based approach to generate conformance tests for interactive applications. our method builds on existing work to address generation of: (1) small yet effective set of test frames for testing individual operations, (2) a set up sequence that brings the system under test in an appropriate state for a test frame (self-priming), (3) a verification sequence for expected output and state changes (self-checking), and, (4) negative test cases in the presence of exceptions. our method exploits a novel mutation scheme applied to operations specified as pre-, and postconditions on parameters and state variables; a set of novel abstraction techniques which result in a compact finite state automaton; and search techniques to automatically generate the set up and verification sequences. we illustrate our method with a simple atm application.
on using collection for aggregation and association relationships in xml object-relational storage. xml data can be stored in different databases including object-relational database (ordb). using ordb, we get the benefit of the relational maturity and the richness of oo modeling. one modeling concept that can be captured is the collection. collection structures frequently occur in xml documents especially in two relationship types: aggregation and association. however, very often when the data is stored in a database repository, the collection is flattened. we believe that preserving the collection semantics in the logical and the implementation level will create a better solution.in this paper we propose methods to preserve the collection in xml data into ordb using the concept of collection types. we use the semantic network diagram to represent the collection of the aggregation and the association in xml data. each of these relationship types will then be transformed into storage in an ordb environment. for aggregation, we propose different methods based on the hierarchy constraint. for association, our method is differentiated based on the cardinality.
fluid: supporting a transportable and adaptive web service. web services introduce new capabilities in the distributed application development model. this model is built on widely used internet standards, thereby presenting interoperability among different platforms. however, there are still several restrictions within the current standards, for instance, lack of the capability to react swiftly given poor-performance or requirements of maintenance on the host that is executing the web service. this paper proposes a nomadic and resource-aware web service framework, which provides the capabilities of migrating a web service to different hosts dynamically and adjusting itself to the available resources of the new host. therefore, allowing web services to react as a result of run-time requirements and poor-performance of hosts, as well as placing itself closer to the group of clients that frequently accesses the web service for performance enhancement. such an approach is applicable to ad-hoc networks of individually resource-poor mobile devices. implementation issues are also discussed and demonstrated.
automatic construction of drama school timetables based on a generic evolutionary framework for allocation and scheduling problems. we present the application of the generic framework evalloc for the solution of allocation and scheduling problems (asps) to a real-world problem. the solution engine integrated in the framework is based on an evolutionary algorithm (ea). the general design of the java framework allows for application to all asps, whose problem data description can be fit into the generic data representation of evalloc. the framework can be transformed into different applications by loading single xml (extended markup language) problem definition files. experimental results for the real-world application, timetabling of the complete teaching activities at the institute for drama at the mozarteum university of music and dramatic arts in salzburg, austria, are presented.
visual exploration of genetic likelihood space. linkage analysis is used to localize human disease genes on the genome and it can involve the exploration and interpretation of a seven-dimensional genetic likelihood space. existing genetic likelihood exploration techniques are quite cumbersome and slow, and do not help provide insight into the shape and features of the high-dimensional likelihood surface. the objective of our visualization is to provide an efficient visual exploration of the complex genetic likelihood space so that researchers can assimilate more information in the least possible time. in this paper, we present new visualization tools for interactive and efficient exploration of the multi-dimensional likelihood space. our tools provide interactive manipulation of active ranges of the six model parameters determining the dependent variable, scaled genetic likelihood, or hlod. using filtering, color, and an approach inspired by "worlds-within-worlds" [5, 6], researchers can quickly obtain a more informative and insightful visual interpretation of the space.
a network independent broker for obtaining the position of nomadic users. positioning is an essential component for the deployment of the evolving context-aware concepts. information society technologies (ist) project polos investigates existing schemes for location-based services, geographical information systems, positioning techniques and network interfaces, in order to design and implement a platform catering for the majority of location based services issues. facilitating towards this direction, polos' positioning component (pos) is introduced as a generic, scalable portable, open, modular and efficient qos enabled framework, offering independence from the underlying heterogeneous network infrastructures and positioning techniques.
continuous spatial queries via wireless data broadcast. this paper proposes a generic framework for continuous range queries via wireless data broadcast. this framework distinguishes itself from existing work by being the first to address the continuous spatial query issue, without an index, making effective use of the low wireless bandwidth, and therefore being ideal for achieving maximal scalability with the fastest access time. the task of the query processor is to selectively monitor the wireless broadcast channel, as the data items are disseminated according to their location by the server.
dynamic scheduling of scientific workflow applications on the grid: a case study. the existing grid workflow scheduling projects do not handle recursive loops which are characteristic to many scientific problems. we propose a hybrid approach for scheduling directed graph (dg)-based workflows in a grid environment with dynamically changing computational and network resources. our dynamic scheduling algorithm is based on the iterative invocation of classical static directed acyclic graphs (dags) scheduling heuristics generated using well-defined cycle elimination and task migration techniques. we approach the static scheduling problem as an application of a modular optimisation tool using genetic algorithms. we report successful implementation and experimental results on a pilot real-world material science workflow application.
compression of mammograms for medical practice. this paper considers effective compression methods for mammogram storing and interchange. a controversy problem of irreversible compression of medical images is studied in clinical tests to check usefulness and possibility of acceptance of wavelet-based compression for clinical applications. diagnostic accuracy is measured in abnormality detection tests with roc-based analysis, and by subjective rating of diagnostically important image features affecting lesion symptoms and image ordering according to preserved diagnostic accuracy. the efficiency of the most approved lossless coders is compared to efficiency of irreversible wavelet coding in acceptable rate range. general conclusion is that more effective irreversible compression of mammograms up to 1bpp is safe (i.e. preserves diagnostic accuracy), according to opinions of radiologists participating the experiments and presented results.
extending invalid-access prevention policy protocols for mobile-client data caching. due to the proliferation of multimedia objects and the subsequent need for managing a large number of multimedia objects within mobile client/server computing environments, there may exist multiple physical copies of the same data object in client caches at the same time with the server as the primary owner of all data objects. this brings new challenges of dealing with caching multimedia data for mobile clients. invalid-access prevention policy protocols developed in traditional dbms environment have to be extended to ensure that the serializability involving data updates is achieved in mobile environments. toward this goal, we have performed analysis, proposed three extended protocols, and conducted experimental studies under the invalid-access prevention policy in mobile environments, to meet the serializability requirement in a mobile client/server environment that deals with multimedia objects. these three protocols, referred to as extended server-based two phase locking (es2pl), extended call back locking (ecbl), and extended optimistic two phase locking (eo2pl) protocols, have included additional attributes to ensure multimedia object serializability in mobile client/server computing environments. in this paper, the rationale of developing these extended protocols, the basic idea behind the extension, a sketch of experimental studies, as well as the overall observation, are presented.
a top down approach for mas protocol descriptions. when the protocol of a complex multi-agent system (mas) needs to be developed, the top-down approach emphasises to start with abstract descriptions that should be refined incrementally until we achieve the detail level necessary to implement it. unfortunately, there exist a semantic gap in protocol description methodologies because most of them first identify which tasks have to be performed, and then use low level descriptions such as sequences of messages to detail them. in this paper, we propose an approach to bridge this gap. we model mas protocols using several abstract views of the tasks to be performed, and provide a systematic method to simplify them. tasks are represented by means of interactions that may be refined into lower-level interactions with the techniques proposed in this paper (simpler interactions are easier to describe and implement using message passing.) unfortunately, deadlocks may appear due to protocol design mistakes or due to the refinement process. thus, we also propose an algorithm to ensure that protocols are deadlock free.
methods for ranking information retrieval systems without relevance judgments. in this paper we present some new methods of ranking information retrieval systems without relevance judgement. the common ground of these methods is using a measure we called reference count. an extensive experimentation was conducted to evaluate the effectiveness of the proposed methods using various different standards information retrieval evaluation measures for the ranking, like average precision, r-precision, and precision and different document levels. we also compared the effectiveness of the proposed methods with the method proposed by soboroff et al. the experimental results showed that the proposed methods are effective, and in many cases are more effective than soboroff at al.'s method.
particle swarm optimization method in multiobjective problems. this paper constitutes a first study of the particle swarm optimization (pso) method in multiobjective optimization (mo) problems. the ability of pso to detect pareto optimal points and capture the shape of the pareto front is studied through experiments on well-known non-trivial test functions. the weighted aggregation technique with fixed or adaptive weights is considered. furthermore, critical aspects of the vega approach for multiobjective optimization using genetic algorithms are adapted to the pso framework in order to develop a multi-swarm pso that can cope effectively with mo problems. conclusions are derived and ideas for further research are proposed.
shadow document methods of resutls merging. in distributed information retrieval systems, document overlaps occur frequently across results from different databases. this is especially the case for meta-search engines which merge results from several general-purpose web search engines. this paper addresses the problem of merging results which contain overlaps in order to achieve better performance. several algorithms for merging results are proposed, which take advantage of the use of duplicate documents in two ways: one correlates scores from different results; the other regards duplicates as increasing evidence of being relevant to the given query. a variety of experiments have demonstrated that these methods are effective.
a method to define an enterprise architecture using the zachman framework. the proliferation of it and its consequent dispersion is an enterprise reality, however, most organizations do not have adequate tools and/or methodologies that enable the management and coordination of their information systems. the zachman framework provides a structured way for any organization to acquire the necessary knowledge about itself with respect to the enterprise architecture. zachman proposes a logical structure for classifying and organizing the descriptive representations of an enterprise, in different dimensions, and each dimension can be perceived in different perspectives.in this paper, we propose a method for achieving an enterprise architecture framework, based on the zachman framework business and is perspectives, that defines the several artifacts for each cell, and a method which defines the sequence of filling up each cell in a top-down and incremental approach. we also present a tool developed for the purpose of supporting the zachman framework concepts. the tool: (i) behaves as an information repository for the framework's concepts; (ii) produces the proposed artifacts that represent each cell contents, (iii) allows multi-dimensional analysis among cell's elements, which is concerned with perspectives (rows) and/or dimensions (columns) dependency; and (iv) finally, evaluate the integrity, dependency and, business and information systems alignment level, through the answers defined for each framework dimension.
undue influence: eliminating the impact of link plagiarism on web search rankings. link farm spam and replicated pages can greatly deteriorate link-based ranking algorithms such as hits. in order to identify and neutralize link farm spam and replicated pages, we look for sufficient material copied from one page to another. in particular, we focus on the use of "complete hyperlinks" to distinguish link targets by the anchor text used. we build and analyze the bipartite graph of documents and their complete hyperlinks to find pages that share anchor text and link targets. link farms and replicated pages are identified in this process, permitting the influence of problematic links to be reduced in a weighted adjacency matrix. experiments and user evaluations show significant improvement in the quality of results produced using hits-like methods.
identifying topological predicates for vague spatial objects. many geographical applications deal with spatial objects that cannot be adequately described by determinate, crisp concepts because of their intrinsically indeterminate and vague nature. gis and spatial database systems are currently unable to handle this kind of data. based on recent work on vague spatial data types, which are part of a formal data model called vasa (vague spatial algebra) and which leverage exact models of crisp spatial data types, this paper introduces a general mechanism for identifying topological predicates for vague spatial objects by means of topological predicates for crisp spatial objects. we illustrate this mechanism by deducing these predicates for vague points.
the social network of java classes. several works in literature have analyzed the link structure of programs in relation with software engineering: it has been observed that the programming standards caused small-world networks to emerge among classes in object-oriented programming. the need for coherent design and the coding conventions introduce regular patterns in the link structure of code.in this work, we study the social network naturally emerging from unrelated software projects. we studied the links present among java classes coming from different contexts. in this case, any observable patterns come from social behaviors, rather than software engineering practices.in our analysis, we could observe a regular social network, organized according to a power-law distribution that is typical, for instance, of links among web pages. we give a positive value to class links, which we consider a sign of relevance and acceptance. out of this, we propose a way of ranking classes, and we present our prototype search engine for java classes.
an adjustment model in a geometric constraint solving problem. an interesting problem related to geometric constraint solving is the choice of the "good" solution. the suitability and effectiveness of genetic algorithms applied to this problem has been demonstrated but their performance depends on the values assigned to their control parameters. although there are recommendations in the specialised technical literature about values for these parameters, their optimal settings depend on the problem at hand. therefore it would be interesting to define a model that automatically adjusts the values of the evolutive parameters as a function of the geometric problem.this paper proposes a meta-model that generates the recommendations for the right parameter values in genetic algorithms operating as a selector mechanism in constructive geometric constraint solvers. it should be stressed that the proposed model is general and automatic. this means that it is applicable to any context and works without the need for any user supervision.
enterprise architecture: business and it alignment. organizations have existing systems infrastructure that are the result of decades of one-by-one implementations of specific solutions. as organizations, products, customers and technologies continue to change at an increasingly rapid rate, managers have sought overviews that will allow them to understand how business and it within their organization fits together. enterprise architecture is a representation of the organization to enable the planning of the organization changes. it includes the current and future business objectives, goals, visions, strategies, informational entities, business processes, people, organization structures, application systems, technological infrastructures, and so on.in this paper, we show how the alignment between business and it can be disaggregated into four different dimensions and we present some heuristics to ensure such alignment.
the impact of sample reduction on pca-based feature extraction for supervised learning. "the curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimensions. in this paper, different feature extraction (fe) techniques are analyzed as means of dimensionality reduction, and constructive induction with respect to the performance of na&iuml;ve bayes classifier. when a data set contains a large number of instances, some sampling approach is applied to address the computational complexity of fe and classification processes. the main goal of this paper is to show the impact of sample reduction on the process of fe for supervised learning. in our study we analyzed the conventional pca and two eigenvector-based approaches that take into account class information. the first class-conditional approach is parametric and optimizes the ratio of between-class variance to the within-class variance of the transformed data. the second approach is a nonparametric modification of the first one based on the local calculation of the between-class covariance matrix. the experiments are conducted on ten uci data sets, using four different strategies to select samples: (1) random sampling, (2) stratified random sampling, (3) kd-tree based selective sampling, and (4) stratified sampling with kd-tree based selection. our experiments show that if the sample size for fe model construction is small then it is important to take into account both class information and data distribution. further, for supervised learning the nonparametric fe approach needs much less instances to produce a new representation space that result in the same or higher classification accuracy than the other fe approaches.
core selection with end-to-end qos support. core-based routing with quality of service (qos) support is essential to facilitate multi-sender multimedia multicast applications such as video conferencing and virtual collaboration applications. in this paper, we introduce (i) a new application-level service class framework that allows group members to easily indicate their desired service quality and (ii) the use of as many cores per group as necessary in corebased routing to maximize the number of group members with satisfied qos requirements. under the service class framework, we formulate the novel core selection problem that selects as many cores as necessary while maximizing the number of satisfied group members. we propose a new core selection algorithm to address the problem and provide a complete core selection protocol using the algorithm. experimental results show that our core selection algorithm performs as well as the optimal algorithm and significantly outperforms a recent core selection algorithm with qos support using a single core.
similarity between euclidean and cosine angle distance for nearest neighbor queries. understanding the relationship among different distance measures is helpful in choosing a proper one for a particular application. in this paper, we compare two commonly used distance measures in vector models, namely, euclidean distance (eud) and cosine angle distance (cad), for nearest neighbor (nn) queries in high dimensional data spaces. using theoretical analysis and experimental results, we show that the retrieval results based on eud are similar to those based on cad when dimension is high. we have applied cad for content based image retrieval (cbir). retrieval results show that cad works no worse than eud, which is a commonly used distance measure for cbir, while providing other advantages, such as naturally normalized distance.
interval and dynamic time warping-based decision trees. this work presents decision trees adequate for the classification of series data. there are several methods for this task, but most of them focus on accuracy. one of the requirements of data mining is to produce comprehensible models. decision trees are one of the most comprehensible classifiers. the use of these methods directly on this kind of data is, generally, not adequate, because complex and inaccurate classifiers are obtained. hence, instead of using the raw features, new ones are constructed.this work presents two types of trees. in interval-based trees, the decision nodes evaluate a function (e.g., the average) in an interval and the result is compared to a threshold. for dtw-based trees each decision node has a reference example. the distance from the example to classify to the reference example is calculated and then it is compared to a threshold.the method for obtaining these trees it is based on 1) to develop a method that obtains for a 2-class data set a classifier formed by a new feature (a function in an interval or the distance to a reference example) and a threshold, 2) to use the boosting method to obtain an ensemble of these classifiers, and 3) to use a method for constructing decision trees using as data set the features selected by boosting.
a customizable hybrid approach to data clustering. most current data clustering algorithms in data mining are based on a distance calculation in certain metric space. for spatial database systems (sdbs), the euclidean distance between two data points is often used to represent the relationship between data points. however, in some spatial settings and many other applications, distance alone is not enough to represent all the attributes of the relation between data points. we need a more powerful model to record more relational information between data objects. this paper adopts a graph model by which a database is regarded as a graph: each vertex of the graph represents a data point, and each edge, weighted or unweighted, is used to record the relation between two data points connected by the edge. based on the graph model, this paper presents a set of cluster analysis criteria to guide data clustering. the criteria can be used to measure clustering results and help improving the quality of clustering. further, a customizable algorithm using the criteria is proposed and implemented. this algorithm can produce clusters according to users' specifications. preliminary experiments show encouraging results.
implementing private vickrey auctions. vickrey auctions have the interesting property of eliminating any incentive for bidders to bid values that are different from their reserve prices (i.e., the true value they give to the item being auctioned). for several reasons, it is desirable that bidders keep private their reserve price. in [2] a protocol to implement a vickrey auction was presented. its main feature is that bids are kept private without the necessity of any trusted third party. in particular, after the auction is finished only the value of the second highest bid and the identity of the highest bidder are publicly revealed. however, in that paper several questions about the applicability of the protocol were left unanswered. in particular, all the presentation was theoretical and no implementation was provided. besides, the analysis of collusion risk was too brief. in this paper we address these issues in a deeper way. in addition, we present and analyze an implementation of the protocol, and we consider its practical applicability.
graphzip: a fast and automatic compression method for spatial data clustering. spatial data mining presents new challenges due to the large size and the high dimensionality of spatial data. a common approach to such challenges is to perform some form of compression on the initial databases and then process the compressed data. this paper presents a novel spatial data compression method, called graphzip, to produce a compact representation of the original data set. graphzip has two advantages: first, the spatial pattern of the original data set is preserved in the compressed data. second, arbitrarily dimensional data can be processed efficiently and automatically. applying graphzip to huge databases can enhance both the effectiveness and the efficiency of spatial data clustering. on one hand, performing a clustering algorithm on the compressed data set requires less running time while the pattern can still be discovered. on the other hand, the complexity of clustering is dramatically reduced. a general hierarchical clustering method using graphzip is proposed in this paper. the experimental studies on four benchmark spatial data sets produce very encouraging results.
the role of visualization in effective data cleaning. using visualization techniques to assist conventional data mining tasks has attracted considerable interest in recent years. this paper addresses a challenging issue in the use of visualization for data mining: choosing appropriate parameters for spatial data cleaning methods. on one hand, algorithm performance is improved through visualization. on the other hand, characteristics and properties of methods and features of data are visualized as feedbacks to the user. a 3-d visualization model, called waterfall, is proposed to assist spatial data cleaning in four important aspects: dimension-independent data visualization, visualization of data quality, algorithm parameter selection, and measurement of noise removing methods on parameter sensitiveness.
spatial contextual noise removal for post classification smoothing of remotely sensed images. extracting accurate land use and land cover information from remote sensing data is a challenging problem due to the gap between theoretically available information in remote sensing imagery and the limited classification ability based on spectral analysis. traditional classification techniques based on spectral analysis of single pixel usually produce "noisy" results that contain many wrongly classified pixels. this paper presents a novel post classification method to detect the pixels that are wrongly classified and reassign them to correct fields in spatial context. the strategy is demonstrated through the classification of a benchmark digital aerial photograph. the experimental results show that the proposed approach can produce a more accurate classification than previous approaches.
development of a collaborative environment applied to pediatric oncology. this project aims to brighten up those problems in the brazilian area of pediatric oncology, making possible the simultaneous collaboration of medical information between professionals of childhood cancer remotely located. it's the implementation of a collaborative environment in which the users can benefit itself with resources as chat, video-conference, bi-dimensional collaborative blackboard and collaborative volumetric visualization of medical images, also being able to get second medical opinion for diagnosis at distance for one or more cases of childhood cancer.
reliability in three-tier systems without application server coordination and persistent message queues. when dealing with fault tolerance in three-tier systems, two major problems need to be addressed, that is how to prevent duplicate transaction executions when classical timeout based retransmission logics are employed, and how to ensure the agreement among the back-end databases despite failures (a transaction needs to be aborted or committed at all the involved databases independently of the failure scenario). in this paper we address these problems by proposing a fault tolerant protocol that, unlike previous solutions, (i) avoids the additional phase of storing the client request into a persistent message queue and (ii) avoids explicit coordination of middle tier application servers (during both normal behavior and fail-over). our protocol reduces therefore the overhead imposed on the end-to-end interaction, thus improving user perceived responsiveness, and provides better scalability.
strudel: supporting trust in the dynamic establishment of peering coalitions. the coalition peering domain (cpd) is a recent innovation within the field of mesh networking. it facilitates the management of community-area networks in a distributed and scalable form, allowing devices to pool their network resources (particularly egress links) to the common good. however, as in p2p systems, this form of cooperative sharing architecture raises significant concerns about the effect of free-riders: nodes that utilise the bandwidth of others without providing an adequate return to the community. to address this problem, we propose strudel, a distributed framework that tackles the problem of free-riders and consists of: (i) a mechanism for the detection of malicious peers; (ii) a formal bayesian trust model, to assess peers' trustworthiness; (iii) a forwarding mechanism based on the maximisation of trust-informed utility.
hybrid log segmentation for assured damage assessment. a database log is the primary resource for damage assessment and recovery after an electronic attack. the log is a sequential file stored in the secondary storage and it can grow to humongous proportions in course of time. to make the process of damage assessment and recovery more efficient, segmenting the log based on different criteria has been proposed before. but the trade off is that, either segmenting the log involves a lot of computation or damage assessment is a complicated process. in this research we propose to strike a balance through hybrid log segmentation. our method will reduce the time taken to perform damage assessment while still segmenting the log fast enough so that no intricate computation is necessary. we build our model from a log that was previously segmented based on number of transactions, a time window for transactions to commit or space occupied by committed transactions. while performing damage assessment, we re-segment the log based on transaction dependency. thus during repeated damage assessment procedures, we create new segments with dependent transactions in them so that the process of damage assessment becomes faster when there are repeated attacks on the system. we have discussed various cases that are applicable and also presented algorithms for each of the cases discussed.
orchestrating document-based workflows with x-folders. this paper introduces x-folders: a software environment for multi-party document-based processes that aims at supporting the implementation of workflow processes involving multiple users that interact by means of documents stored in special, reactive, folders. when the documents inside a folder reach a given state a task is triggered, tasks orchestrate a set of web services in order to enact the workflow. x-folders is based on a model that promotes the implementation of applications distributed among peer sites and is based on internet standards: the document folders are accessible via webdav and via soap, external components can be invoked as web services; this enhances the interoperability of the workflow processes with external components and makes it possible to interact with the system even without specific clients.
an optimized approach for knn text categorization using p-trees. the importance of text mining stems from the availability of huge volumes of text databases holding a wealth of valuable information that needs to be mined. text categorization is the process of assigning categories or labels to documents based entirely on their contents. formally, it can be viewed as a mapping from the document space into a set of predefined class labels (aka subjects or categories); f: d&larr; {c1, c2...cn} where f is the mapping function, d is the document space and {c1, c2...cn} is the set of class labels. given an unlabeled document d, we need to find its class label, ci, using the mapping function f where f(d) = ci. in this paper, an optimized k-nearest neighbors (knn) classifier that uses intervalization and the p-tree1 technology to achieve a high degree of accuracy, space utilization and time efficiency is proposed: as new samples arrive, the classifier finds the k nearest neighbors to the new sample from the training space without a single database scan.
incremental interactive mining of constrained association rules from biological annotation data with nominal features. data arising from genomic and proteomic experiments is amassing at high speeds resulting in huge amounts of raw data; consequently, the need for analyzing such biological data --- the understanding of which is still lagging way behind --- has been prominently solicited in the post-genomic era we are currently witnessing. in this paper we attempt to analyze annotated genome data by applying a very central data-mining technique known as association rule mining with the aim of discovering rules capable of yielding deeper insights into this type of data. we propose a new technique capable of using domain knowledge in the form of queries in order to efficiently mine only the subset of the associations that are of interest to researcher in an incremental and interactive mode.
performance analysis framework for large software-intensive systems with a message passing paradigm. the launch of new features for mobile phones is increasing and the product life cycle symmetrically decreasing in duration as higher levels of sophistication are reached. therefore, the optimization of resources is particularly important in embedded systems where cpu power and memory space are limited. in this context, performance engineers must be able to predict and analyze the performance of the software architecture in order to support its evolution and its new requirements. in this paper i describe a framework for the analysis of the performance of a software architecture where the architectural elements communicate using message based communication services. using instrumentation traces i have extracted the run-time events i considered significant for the study. i have created a set of architectural views to reconstruct the dynamic and the static views of the architecture. understanding the connections and the relationships between them guide the performance analyst to a clear comprehension of how the architecture works and subsequently how it can be optimized. the performance analysis framework described constitute an essential set. the next challenge is to enhance the integration of the tools and the synchronization of the views and to facilitate the entry barrier to novice performance engineers.
replica selection in grid environment: a data-mining approach. grid technology is developed to share data across many organizations in different geographical locations. the idea of replication is to store data into different locations to improve data access performance. when different sites hold replicas, there are significant benefits realized when selecting the best replica. current research shows that both network bandwidth and disk i/o plays major role in file transfer. in this paper, we describe a new optimization technique that considers both disk throughput and network latencies when selecting the best replica. previous history of data transfer can help in predicting the best site that can hold replica. the k-nearest neighbor rule is one such predictive technique. in this technique, when a new request arrives for the best replica, it looks at all previous data to find a subset of previous file requests that are similar to it and uses them to predict the best site that can hold the replica. in this work, we implement and test k-nearest algorithm for various file access patterns and compare results with the traditional replica catalog based model. the results demonstrate that our model outperforms the traditional model for sequential and unitary random file access requests.
detecting identifiable areas in mobile environments. location-based applications and services are getting increasingly important for mobile users. they take into account a mobile user's current location and provide a location-dependent output. to support developers of location-based services, the nimbus framework hides specific details of positioning systems and provides uniform output containing physical as well as symbolic location information, which often are more suitable for applications and users. one basic problem solved by nimbus is the distributed location resolution problem: given a location; which identifiable areas cover this location, if the area information is distributed among different servers. this paper presents a solution of this problem that runs in the distributed, self-organizing nimbus infrastructure. the effectiveness is demonstrated with the help of performance analyses.
trust-decisions on the base of maximal information of recommended direct-trust. nowadays the concept of trust in computer communications starts to get more and more popular. while the idea of trust in human interaction seems to be obvious and understandable it is very difficult to find adequate and precise definitions of the trust-term. even more difficult is the attempt to find computable models of trust, particularly if one tries to keep all psycho-sociological morality from the real life out of the model. but, apart from all these problems, some approaches have been introduced more or less successful.in this paper, we do not create a new definition of trust. like many others we start with the simplest definition of trust as a probability of expected positive behaviour. our focus lies on the question, how far recommended trust-information is suitable to be the base of a trust-decision.our concept is based on the definition, that individual experiences are essential for a directional direct-trust relation between an entity and an opposite entity. recommendation-trust is a special direct-trust-relation. in order to be able to make trust-decisions on the base of recommended trust-information, our solution does not try to condense the chains of recommendation to only one value, but keeps the information untouched. we introduce trust-decisions as the final step of a randomly chosen path in a decision-tree where the weighted edges of the tree consist of recommended trust-values or the new introduced certainty-values, and of leafs with direct-trust-values or sections of total inexperience. a trust-decision is positive when a trust-threshold is exceeded by the determined value of the process. the calculation of the new introduced certainty-values, indicating the probability of the procedure to reach a direct-trust-value inside a sub-tree, plays a big part in this approach.one advantage of the procedure to induce the trust-decisions on the base of randomness lies in the higher resistance against false information from malicious entities because with a probability, paths through the tree will be chosen which exclude information of these entities.besides the new approach of trust-decisions on the base of recommended trust-information, we show how far (meaning with how many recommenders) it is reasonable to recommend trust-information. we will give suggestions how to optimize the tree of recommendation, certainty, and direct-trust, so that in an adequate time trust-decisions are possible and we show the influence of bad and malicious entities on the results of the trust-decision.
a distributed content-based search engine based on mobile code. current search engines crawl the web, download content, and digest this content locally. for multimedia content, this involves considerable volumes of data. furthermore, this process covers only publicly available content because content providers are concerned that they otherwise loose control over the distribution of their intellectual property. we present the prototype of our secure and distributed search engine, which dynamically pushes content based feature extraction to image providers. thereby, the volume of data that is transported over the network is significantly reduced, and the concerns mentioned above are alleviated. the distribution of feature extraction and matching algorithms is done by mobile software agents. we give a description of the search engine's architecture and implementation, quantitative evaluation results, and a discussion of related security mechanism for content protection and server security.
greedy heuristics and an evolutionary algorithm for the bounded-diameter minimum spanning tree problem. given a connected, weighted, undirected graph g and a bound d, the bounded-diameter minimum spanning tree problem seeks a spanning tree on g of lowest weight in which no path between two vertices contains more than d edges. this problem is np-hard for 4 < d < n - 1, where n is the number of vertices in g. an existing greedy heuristic for the problem, called ottc, is based on prim's algorithm. ottc usually yields poor results on instances in which the triangle inequality approximately holds; it always uses the lowest-weight edges that it can, but such edges do not in general connect the interior nodes of low-weight bounded-diameter trees. a new randomized greedy heuristic builds a bounded-diameter spanning tree from its center vertex or vertices. it chooses each next vertex at random but attaches the vertex with the lowest-weight eligible edge. this algorithm is faster than ottc and yields substantially better solutions on euclidean instances. an evolutionary algorithm encodes spanning trees as lists of their edges, augmented with their center vertices. it applies operators that maintain the diameter bound and always generate valid offspring trees. these operators are efficient, so the algorithm scales well to larger problem instances. on 25 euclidean instances of up to 1000 vertices, the ea improved substantially on solutions found by the randomized greedy heuristic.
hierarchical organization of a set of gaussian mixture speaker models for scaling up indexing and retrieval in audio documents. this work considers the case of spoken radio archives, in which a continuous ow of speech is introduced into the indexing system. to retrieval segments originating from a given speaker, scanning the set of enrolled speaker is needed. we propose a technique for organizing hierarchically the set of speaker models, to reduce the cost of speaker identification. this organization can be obtained and updated at low cost, thanks to a particular algorithm that exploits the gaussian mixture form of each speaker model. this parcimony is due to having computations carried out of model parameters rather than feature vectors. a first validation on real data illustrates the proposal.
a comparison of randomized and evolutionary approaches for optimizing base station site selection. it is increasingly important to optimally select base stations in the design of cellular networks, as customers demand cheaper and better wireless services. from a set of potential site locations, a subset needs to be selected which optimizes two critical objectives: service coverage and financial cost. as this is an np-hard optimization problem, heuristic approaches are required for problems of practical size. our approach consists of two phases which act upon a set of candidate site permutations at each generation. firstly, a sequential greedy algorithm is designed to commission sites from an ordering of candidate sites, subject to satisfying an alterable constraint. secondly, an evolutionary optimization technique, which is tested against a randomized approach, is used to search for orderings of candidate sites which optimize multiple objectives. the two-phase strategy is vigorously tested and the results delineated.
editorial message: special track on ubiquitous computing. ubiquitous computing places humans in the center of environments saturated with computing and wireless communications capabilities, yet gracefully integrated, so that technology recedes in the background of everyday activities. the ubiquitous computing world then, is a world largely defined by applications. but such applications present an altogether new set of requirements. the special track on ubiquitous computing applications, first introduced in acm sac 2004 and running for the second time in acm sac 2005, provides a forum for the discussion of all types of ubiquitous computing applications and related specialized infrastructures built for the deployment of targeted applications. individual papers place applications within their use context and introduce novel and appropriate interaction paradigms while at the same time addressing related technical and business aspects and consequently identify novel opportunities or constraints.
editorial message: special track on ubiquitous computing. ubiquitous computing places humans in the center of environments saturated with computing and wireless communications capabilities, yet gracefully integrated, so that technology recedes in the background of everyday activities. the ubiquitous computing world then, is a world largely defined by applications. but such applications present an altogether new set of requirements. the special track on ubiquitous computing applications, first introduced in acm sac 2004, provides a forum for the discussion of all types of ubiquitous computing applications and related specialized infrastructures built for the deployment of targeted applications. individual papers place applications within their use context and introduce novel and appropriate interaction paradigms while at the same time addressing related technical and business aspects and consequently identify novel opportunities or constraints.
mining and analyzing the topological structure of protein-protein interaction networks. we report a comprehensive evaluation of the topological structure of protein-protein interaction (ppi) networks by mining and analyzing graphs constructed from the publicly available popular data sets to the bioinformatics research community. we compare the topology of these networks across different species, at different confidence levels, and from different experimental systems. our results confirm the well-accepted claim that the degree distribution follows a power law. however, further statistical analysis shows that the residues are not independent on the fit values, indicating that the power law model may be inadequate. our results also show that the dependence of the average clustering coefficient on the vertices degree is far from a power law, contradicting many published results. for the first time, we report that the average vertex density exhibits a strong power law dependence on the vertices degree for all the networks studied, regardless of species, confidence levels, and experimental systems.
access-controlled resource discovery for pervasive networks. networks of the future will be characterized by a variety of computational devices that display a level of dynamism not seen in traditional wired networks. because of the dynamic nature of these networks, resource discovery is one of the fundamental problems that must be faced. while resource discovery systems are not a novel concept, securing these systems in an efficient and scalable way is challenging. this paper describes the design and implementation of an architecture for access-controlled resource discovery. this system achieves this goal by integrating access control with the intentional naming system (ins), a resource discovery and service location system. the integration is scalable, efficient, and fits well within a proxy-based security framework designed for dynamic networks. we provide performance experiments that show how our solution outperforms existing schemes. the result is a system that provides secure, access-controlled resource discovery that can scale to large numbers of resources and users.
the user as social actor: a focus on systems development methodology enactment. this paper provides an innovative example for understanding systems development method (sdm) enactment by conceptualizing the it worker as a social actor and method user. the paper shows how it workers can be seen as acting in constrained ways, rather than as simple "users" of the sdm; and secondly shows the potential contribution of social actor theory.
concurrent and distributed programming using constraint logic programs. we describe a coordination language for high-level distributed programming. its roots are in concurrent constraint programming where there is a shared constraint store and synchronization is achieved via constraint entailment. a system is modeled as: (a) a set of processes, and (b) a set of constraints which capture the concurrent behavior of the system. the key advantages are that (1) there is a clear separation of the concurrency and the functionality aspects of the system, (2) processes are coordinated explicitly by a declarative formalism, i.e. constraints, and (3) the processes-agents are programming language independent.
pumas: a framework based on ubiquitous agents for accessing web information systems through mobile devices. in this paper, we describe pumas [3], a framework based on ubiquitous agents for accessing web information systems (wis) through mobile devices (md). the objective of pumas is to adapt the information delivered to a nomadic user (who often changes her/his location) according to her/his preferences, intentions and history in the system and, to the limited capacities of her/his md. we use some auml (agent unified modelling language) [11] diagrams for representing the messages exchange between the agents and the pumas components.
information retrieval and spelling correction: an inquiry into lexical disambiguation. in a preliminary study, we show the effect of spelling errors on an ad hoc information retrieval task. then, we report on the comparison of different strategies for correcting spelling errors resulting in non-existent words. unlike interactive spelling checkers, where usually only the left context is available, the system we developed takes advantage of the entire context surrounding misspelling. moreover, unlike traditional systems, based exclusively on a string-to-string edit distance and a word language model, we explore the use of the part-of-speech for selecting candidates. in conclusion, we show that spelling correction improves by extending the context. the best results are obtained when combining a part-of-speech filter with a word language model, and using both the left and right adjacent contexts.
frequent free tree discovery in graph data. in recent years, researchers in graph mining have been exploring linear paths as well as subgraphs as pattern languages. in this paper, we are investigating the middle ground between these two extremes: mining free (that is, unrooted) trees in graph data. the motivation for this is the need to upgrade linear path patterns, while avoiding complexity issues with subgraph patterns. starting from such complexity considerations, we are defining free trees and their canonical form, before we present freetreeminer, an algorithm making efficient use of this canonical form during search. experiments with two datasets from the national cancer institute's developmental therapeutics program (dtp), anti-hiv and anti-cancer screening data, are reported.
websogo: a global ontology for describing web sources. based on the limitations raised by existing approaches in the context of the semantic web, we propose a formalism, web sources global ontology (websogo), a data meta-model for the description of web sources in terms of content, query-processing capabilities, service and navigation information. websogo is formalized in the object-oriented paradigm using the unified modeling language (uml). we also describe websogo-s, a multi-layered system that will allow agents to discover, execute and compose web sources through queries against a websogo catalog of source ontologies. the uml specification of websogo has been mapped to the object-relational (or) model in oracle; we define an oracle cartridge with a list of types and methods that allow the specification of sql queries against the websogo catalog. by using the jdbc and odbc drivers provided by oracle, any agent or application will be able to contact websogo-s.
interactive mobile 3d graphics for on-the-go visualization and walkthroughs. developing interactive 3d graphics for mobile java applications is now a reality. recently, the mobile 3d graphics (m3g) api (also known as jsr-184) was proposed to provide an efficient 3d graphics environment suitable for the j2me platform. however, new services and applications using interactive 3d graphics, which have already achieved reasonable standards on the desktop, do not exist for resource-constrained handheld devices yet. in this work, a generic architecture for visualizing and navigating through 3d worlds in a mobile setting was designed and implemented. in particular, a 3d virtual tour application was developed based on the proposed architecture, where multiple mobile clients using m3g navigate through and interact with each other in a shared 3d space.
efficient processing of past-future spatiotemporal queries. spatiotemporal databases emerge as an evolving scientific field due to a great variety of applications, tracking mobile objects being one of them. for this purpose, a number of methods have been proposed to efficiently organize and index moving objects and answer spatiotemporal queries. the majority of all these methods are addressing either the past or the future movement of the moving objects. up until now, addressing both the past and the future movement of the objects in an integrated manner has rarely appeared in the literature. in the current paper, based on a spatiotemporal access method, the xbr-tree, we propose algorithms for the efficient processing of spatiotemporal window (past) and timestamp (past, present and future) queries. moreover, we experimentally study the efficiency of processing these queries based on the xbr-tree against using an existing structure, the rppf-tree.
analysis of the set e-commerce protocol using a true concurrency process algebra. a formal specification of the purchase phase in the set protocol (secure electronic transaction), an e-commerce protocol by visa and mastercard, is presented. it is modelled by means of a true concurrency timed process algebra called btc which takes into account that the (limited amount of) available resources in a system have to be shared by all the processes. we have considered heterogeneous resources and we extend the algebra with the intention of representing the actions which use the shared resources and how many resources of each type the system has at its disposal.
finding saddle points using stability boundaries. the task of finding saddle points on potential energy surfaces plays a crucial role in understanding the dynamics of a micro-molecule as well as in studying the folding pathways of macro-molecules like proteins. this paper primarily focusses on computing saddle points on potential energy surfaces. a stability boundary based approach that explores the dynamic and geometric characteristics of stability boundaries of a nonlinear dynamical system has been used to compute saddle points. a novel ray-adjustment procedure is used to trace the stability boundary. a simpler version of the algorithm has also been used to find the saddle points of symmetric systems. our approach was also successful in finding saddle points on higher dimensional energy surfaces.
an approach for adaptable learning systems with respect to psychological aspects. content delivered by multimedia-rich learning courses supported by passive media such as videos are not appropriate to guide students until the end of a learning course. research identified the necessity to make learning systems more user-centric in order to prevent frustration and drop outs of students. for this, the presented approach integrates psychological factors in an adaptable learning system which is based on meta data enriched learning objects. an adaptation framework is introduced to show the interaction of the discussed concepts to fulfill the request for individualized learning systems.
survey of semantic annotation platforms. the realization of the semantic web requires the widespread availability of semantic annotations for existing and new documents on the web. semantic annotations are to tag ontology class instance data and map it into ontology classes. the fully automatic creation of semantic annotations is an unsolved problem. instead, current systems focus on the semi-automatic creation of annotations. the semantic web also requires facilities for the storage of annotations and ontologies, user interfaces, access apis, and other features to fully support annotation usage. this paper examines current semantic web annotation platforms that provide annotation and related services, and reviews their architecture, approaches and performance.
towards the prioritization of regression test suites with data flow information. regression test prioritization techniques re-order the execution of a test suite in an attempt to ensure that defects are revealed earlier in the test execution phase. in prior work, test suites were prioritized with respect to their ability to satisfy control flow-based and mutation-based test adequacy criteria. in this paper, we propose an approach to regression test prioritization that leverages the all-dus test adequacy criterion that focuses on the definition and use of variables within the program under test. our prioritization scheme is motivated by empirical studies that have shown that (i) tests fulfilling the all-dus test adequacy criteria are more likely to reveal defects than those that meet the control flow-based criteria, (ii) there is an unclear relationship between all-dus and mutation-based criteria, and (iii) mutation-based testing is significantly more expensive than testing that relies upon all-dus.in support of our prioritization technique, we provide a formal statement of the algorithms and equations that we use to instrument the program under test, perform test suite coverage monitoring, and calculate test adequacy. furthermore, we examine the architecture of a tool that implements our novel prioritization scheme and facilitates experimentation. the use of this tool in a preliminary experimental evaluation indicates that, for three case study applications, our prioritization can be performed with acceptable time and space overheads. finally, these experiments also demonstrate that the prioritized test suite can have an improved potential to identify defects earlier during the process of test execution.
biochain: lexical chaining methods for biomedical text summarization. lexical chaining is a technique for identifying semantically-related terms in text. we propose concept chaining to link semantically-related concepts within biomedical text together. the resulting concept chains are then used to identify candidate sentences useful for extraction. the extracted sentences are used to produce a summary of the biomedical text. the concept chaining process is adapted from existing lexical chaining approaches, which focus on chaining semantically-related terms, rather than semantically-related concepts. the unified medical language system (umls) metathesaurus and semantic network are used as semantic resources. the umls metamap transfer tool is used to perform text-to-concept mapping. the goal is to propose concept chaining and develop a novel concept chaining system for the biomedical domain using umls lexicon and the ideas of lexical chaining. the resulting concept chains from the full-text are evaluated against the concepts of a human summary (the paper's abstract). precision is measured at 0.90 and recall at 0.92. the resulting concept chains are used to summarize the text. we also evaluate generated summaries using existing summarization systems using sentence matching, and confirm the generated summaries are useful to a domain expert. our results show that the proposed concept chaining is a promising methodology for biomedical text summarization.
a formal logic-based language and an automated verification tool for computer forensic investigation. in this paper, a formal logic-based language, called s-tla+, is proposed for computer forensic investigation. it allows an unambiguous description of evidences, a modeling of the forensic expert knowledge in the form of hacking scenarios fragments, and a reasoning capability with uncertainty by filling in potential lack of data with hypotheses. the proposal is complemented by an automated formal verification tool, called s-tlc which helps exploring additional evidences and checks whether there are plausible hacking scenarios that meet the available evidences.
service interface: a new abstraction for implementing and composing protocols. in this paper we compare two approaches to the design of protocol frameworks -- tools for implementing modular network protocols. the most common approach uses events as the main abstraction for a local interaction between protocol modules. we argue that an alternative approach, that is based on service abstraction, is more suitable for expressing modular protocols. it also facilitates advanced features in the design of protocols, such as dynamic update of distributed protocols. we then describe an experimental implementation of a service-based protocol framework in java.
honeynet based distributed adaptive network forensics and active real time investigation. network forensics and honeynet systems have the same features of collecting information about the computer misuses. honeynet system can lure attackers and gain information about new types of intrusions. network forensics system can analysis and reconstruct the attack behaviors. these two systems integrating together can help to build an active self-learning and response system to profile the intrusion behavior features and investigate the attack original source. in this paper, we present a design of honeynet based active network intrusion response system. the features of our system are distributed adaptive network forensics and active real time network investigation.
multimedia and visualization track. the multimedia and visualization (mmv) track has been a popular track because of its appeal for the current trends in daily life applications. visualization is the key to comprehending the continuously changing complex phenomena around us. multimedia combines information from local and remote sources. the users may view this information on on_demand basis. there are many issues associated with this: data manipulation, display, motion, security etc. this track attracts investigators from pure research to applications in wide variety of areas. some of the papers included were: video indexing, visualization techniques for data mining and surface modeling, video on demand, security.
web metasearch: rank vs. score based rank aggregation methods. given a set of rankings, the task of ranking fusion is the problem of combining these lists in such a way to optimize the performance of the combination. the ranking fusion problem is encountered in many situations and, e.g., metasearch is a prominent one. it deals with the problem of combining the result lists returned by multiple search engines in response to a given query, where each item in a result list is ordered with respect to a search engine and a relevance score. several ranking fusion methods have been proposed in the literature. they can be classified based on whether: (i) they rely on the rank; (ii) they rely on the score; and (iii) they require training data or not. our paper will make the following contributions: (i) we will report experimental results for the markov chain rank based methods, for which no large experimental tests have yet been made; (ii) while it is believed that the rank based method, named borda count, is competitive with score based methods, we will show that this is not true for metasearch; and (iii) we will show that markov chain based methods compete with score based methods. this is especially important in the context of metasearch as scores are usually not available from the search engines.
multimedia and visualization track. the multimedia and visualization (mmv) track has been a popular track because of its appeal for the current trends in daily life applications. visualization is the key to comprehending the continuously changing complex phenomena around us. multimedia combines information from local and remote sources. the users may view this information on on_demand basis. there are many issues associated with this: data manipulation, display, motion, security etc. this track attracts investigators from pure research to applications in wide variety of areas. some of the papers included were: video indexing, visualization techniques for data mining and surface modeling, video on demand, security.
automatic structured query transformation over distributed digital libraries. structured data and complex schemas are becoming the main way to represent the information many digital libraries provide, thus impacting the services they offer. when searching information among distributed digital libraries with heterogeneous schemas, the structured query with a given schema (the global or target schema) has to be transformed into a query over the schema of the digital library it will be submitted to (the source schema). schema mappings define the rules for this query transformation. schema matching is the problem of learning these mappings.in this paper we address the issue of automatically learning these mappings and transforming a structured query over the target schema into a new structured query over the source schema. we propose a simple and effective schema matching method based on the well known cori selection algorithm and two ways of applying it. by evaluating the effectiveness of the obtained structured queries we show that the method works well in accessing distributed, heterogeneous digital libraries.
from spontaneous total order to uniform total order: different degrees of optimistic delivery. a total order protocol is a fundamental building block in the construction of distributed fault-tolerant applications. unfortunately, the implementation of such a primitive can be expensive both in terms of communication steps and of number of messages exchanged. this problem is exacerbated in large-scale systems, where the performance of the algorithm may be limited by the presence of high-latency links.optimistic total order protocols have been proposed to alleviate this problem. however, different optimistic protocols offer quite distinct services. this paper makes an overview of different optimistic approaches and shows how they can be combined in a single adaptive protocol.
implementing fuzzy expert system for intelligent buildings. in this paper we present the design of an intelligent dome, as well as the design and implementation of the fuzzy expert system for the module controlling ventilation and air conditioning. the system was designed as a client/server, blackboard architecture, implemented in fuzzyclips, and intensively tested under different conditions. we describe here all the design and implementation stages as well as some of the results obtained.
does object coupling really affect the understanding and modifying of ocl expressions? early and precise models started to play an increasingly relevant role since models themselves become the primary focus in recent initiatives of model-driven engineering (such as model-driven development and model-driven architecture). however, a precise model cannot be obtained through the use of unified modeling language (uml), due to the limited expressiveness of diagram-based uml notation. a textual add-on to the uml diagrams is needed, such as the object constraint language (ocl), for reaching complete and consistent models and avoiding underspecification. aware of the proliferation of measures for uml-based models and the lack of measures to capture the quality aspects of uml/ocl combined models we defined a set of measures for measuring the structural properties of ocl expressions. this paper carefully describes an experiment we have conducted to confirm the conclusions and strengthen the external validity of a previous family of experiments, with the purpose of investigating the relationship between object coupling in ocl expressions and the understandability and modifiability of ocl expressions. empirical evidence that such a relationship exists is reaffirmed and consolidated.
a timed extension of respect. among the existing extensions to the basic tuple space coordination model, the tuple centre approach has been introduced to allow for the flexible programming of a tuple space behaviour, so as to encapsulate coordination laws directly as behaviour of the coordination medium. in particular, the logic-based language respect has been used for programming tuple centres in the tucson coordination infrastructure [11, 9].however, among the application contexts that can be suitably engineered with agents and coordination infrastructures, some involve coordination processes where the notion of time and duration play a relevant role. examples include distributed control systems, protocol-based interactions as in auctions, and in general all the coordination contexts where high dynamism and openness are concerned, which call for time-aware coordination artifacts supporting timed system engineering.accordingly, in this work we discuss how the basic respect tuple centre model has been extended to support the definition and enaction of time-aware coordination policies. several examples are provided to show the expressiveness of the language to model temporal coordination primitives and laws.
multimedia and visualization track. the multimedia and visualization (mmv) track has been a popular track because of its appeal for the current trends in daily life applications. visualization is the key to comprehending the continuously changing complex phenomena around us. multimedia combines information from local and remote sources. the users may view this information on on-demand basis. there are many issues associated with this: data manipulation, display, motion, security etc. this track attracts investigators from pure research to applications in wide variety of areas. some of the papers included were: consistency checking and temporal relations, digital watermarking, multimedia information representation, scientific visualization with genetic algorithms, security, video indexing, video on demand, volume visualization, visualization techniques for data mining and surface modeling.
an iterative rating method: application to web-based conference management. given a large set of items and a set of users, we consider the problem of collecting user preferences - or ratings - on items. the paper describes a simple method which provides an approximate solution to the problem without requiring each user to rate each item. the method relies on an iterative process. each step, or ballot, requires each user to rate a sample of the items. a collaborative filtering algorithm is then performed to predict the missing ratings as well as their level of confidence (which is initially 0). perfoming a new ballot allows to improve the accuracy of predictions. the administrator of the system is responsible for stopping the iteration when a satisfactory level is reached.we apply this method to the assignment of reviewers to papers prior to the review phase of conference management, and describe its implementation in the myreview web-based system.
understanding access restriction of variant parametric types and java wildcards. variant parametric types [8] have been introduced to provide a flexible subtyping mechanism for generic types, and are recently being developed into java wildcards [15], shipped worldwide with the jdk 1.5 release. the two approaches, which are strictly related, retain safety by providing rather peculiar and non-trivial mechanisms to restrict access to a class functionalities (methods and fields). in this paper we aim at studying a unified framework to describe this issue in detail, and to facilitate the understanding and exploitation of this new programming concept.our work is both technical and conceptual. on the one hand, we provide formal rules to access restriction and specialise them for the two approaches, so as to emphasise similarities and differences. on the other hand, we show that such rules promote a natural description and understanding of access restriction in terms of the ability of (instances of) a generic class to produce/consume elements of the abstracted type.
rule discovery from textual data based on key phrase patterns. this paper proposes a new method for discovering rules from textual data. the method decomposes textual data into word sets by using lexical analysis, generates training examples from both key phrase relations extracted from the word sets by using key phrase patterns and text classes given by the user, and acquires key phrase relation rules from the examples by using a fuzzy inductive learning algorithm. the method is also able to deal with textual data that requires word segmentation, such as japanese text. this paper reports on the application of the method to e-mail analysis tasks for a customer center. the e-mails are written in japanese and have two analytical criteria: a product criterion and a contents criterion. we evaluate the acquired rules in each criterion.
formal specification of autonomous commerce agents. reliability is a key challenge in e-commerce platforms in general and in autonomous commerce multi-agent systems in particular. most formal methods proposed to check reliability of these systems focus on checking low-level details such as the communication protocols among agents. in this paper we present a formalism to specify autonomous commerce agents as well as systems made of them. this formalism focuses on describing the high-level behavior of agents. thus, agents are considered economic entities that have different preferences along time and must perform transactions according to them. besides, we specify systems as environments where all the agents fulfill their own specification. these formalisms can be applied to check the reliability of an agent or system by comparing its behavior with that of its specification.
improving address space randomization with a dynamic offset randomization technique. address space randomization (asr) techniques randomize process layout to prevent attackers from locating target functions. prior asr techniques have considered single-target attacks, which succeed if the attacker can locate a single, powerful system library function. these techniques are not sufficient to defend against chained return-into-lib(c) attacks, each of which calls a sequence of system library functions in order.in this paper, we propose a new asr technique, code islands, that randomizes not only the base pointers of memory mapping (mmapping), but also relative distances between functions, maximally and dynamically. our technique can minimize the utility of information gained in early probes of a chained return-into-lib(c) attack, for later stages of that attack. with a pre-defined rerandomization thresh-old, our code islands technique not only is exponentially more effective than any prior asr technique in defending against brute-force searches for locations of multiple targets---a key component of chained return-into-lib (c) attacks, but can also maintain high service availability even under attack. our overhead measurement on some well-known gnu applications shows that it takes less than 0.05 second to load/rerandomize a process with the necessary c system library functions using code islands, and our technique introduces a 3-10% run-time overhead from inter-island control transfers. we conclude that the code island technique is well-suited to dedicated multi-threaded servers.
elicitation and conversion of hidden objects and restrictions in a database schema. mapping a database schema from one model into another, with a higher semantic capacity, is a current research subject with application in several development fields, such as schema integration and translation, migration from legacy systems and reengineering of poor quality or no-longer accurate data models. inclusion dependencies are one of the most important concepts in relational databases and they are the key to perform some reengineering of database schemas. referential integrity restrictions (rir), a particular case of an inclusion constraint, requires that the set of distinct values occurring in some specified column, simple or composite (foreign key), must be a subset of the set of distinct primary key values drawn from the same domain. pure inclusion dependencies (id), however, may apply between other pairs of attributes also (alternate keys or non-keys). database schemas containing ids frequently reveal the presence of hidden objects and misrepresented relationships and, as a consequence, increase the effort to develop program applications and maintain the integrity. this work presents a heuristics for the conversion of schemas with ids into equivalent schemas with only rirs. in case some irreducible ids remain, a semantic interpretation of their necessity and maintenance is given.
adaptive linkage crossover. problem-specific knowledge is often implemented in search algorithms using heuristics to determine which search paths are to be explored at any given instant. as in other search methods, utilizing this knowledge will more quickly lead a genetic algorithm (ga) towards better results. in many problems, crucial knowledge is not found in individual components, but in the interrelations between those components. for such problems, we develop an interrelation (linkage) based crossover operator that has the advantage of liberating gas from the constraints imposed by the fixed representations generally chosen for problems. the strength of linkages between components of a chromosomal structure can be explicitly represented in a linkage matrix and used in the reproduction step to generate new individuals. for some problems, such a linkage matrix is known a priori from the nature of the problem. in other cases, the linkage matrix may be learned by successive minor adaptations during the execution of the evolutionary algorithm. this paper demonstrates the success of such an approach for several problems.
a methodology for the efficient architectural exploration of energy-delay trade-offs for embedded systems. the main goal of this paper is to identify the best architecture of an embedded system by considering at the same time energy and delay, avoiding the comprehensive analysis of the architectural design space. we adopt the energy-delay product (edp) as the evaluation metric to compare the alternative architectures of the target system. the paper analyzes an extended adaptive random search algorithm (adgreed) to efficiently explore the architectural design space. the adgreed algorithm is a pseudo-random optimisation algorithm that combines the best potentialities of the adaptive random search (adras) and the greedy deterministic algorithm. the analysis has been carried out through the architectural optimisation of the memory sub-system of a real-word embedded system executing the set of mediabench benchmarks for multimedia applications. the reported experimental results have shown a reduction up to one order of magnitude of the number of design alternatives analyzed during the exploration phase, while maintaining very high accuracy.
user-defined view automation of genomic databases. this paper presents a solution to the problem of creating a subset database from the public genome databases, also known as a database view. while the techniques to generate views are well established already in the database system there are still some problems found where applying this technique in the genome database environment. the main problems that exist in the current methods of view creation are missing relevant results, returning irrelevant results and view creation processes are generally very time consuming for the user. the solution presented within provides an automated approach aimed at reducing the time needed to create a view, which is usually done by hand. the solution improves the searching method needed for view creation by the addition of two extra phases; the first, expanding the keyword search so that it captures all relevant results and second, a filtering phase to remove all the extra irrelevant results. the whole process is done in the background so that the user isn't required to spend much time fixing the results of inadequate search tools.
j-ortho: an open-source orthodontic treatment simulator. an interactive computer-based training tool for using in orthodontics is aimed at students and experienced professionals who need to predict orthodontic treatment outcomes. usually, treatment planning and the choice of a proper appliance model are based exclusively on clinician expertise, and most orthodontists work on a trial and error basis, estimating an "ideal" loading condition that can lead to a precise and aimed tooth movement. therefore, the orthodontist and patient have a strong need for methods that enable them to compute realistic pictures of the expected teeth positioning to circumvent unexpectedly situations that may occur in practice. in this paper we present j-ortho, an open-source orthodontic treatment simulator. to validate it, we use a one-year follow-up orthodontic treatment. based on the data provided by this study, j-ortho generates the 3d anatomical structures and appliance models from dental cast, x-rays, and photographic records of the virtual patient. morphing approaches and a 3d tooth movement simulator are implemented to represent the changes in shape that the dental arch performs. initial investigation has proved that we have been able to set up the system to demonstrate behaviour that closely replicates real teeth movements, similar to our experimental studies. we expect our prototype to be a useful environment for training orthodontists, residents and students giving experience in both simulation and actual dental images as well as to explore and verify in practice the temporal evolution of the planned treatment.
the structuring of a wireless internet application for a music-on-demand service on umst devices. developing enhanced wireless internet applications is becoming one of the upcoming challenges for mobile radio networks operators. in this paper we introduce and discuss the general software architecture of a wireless internet-based application we have designed and implemented to support the distribution of mp3-based musical songs to umts devices. we have examined the effects that internet traffic has on the performance of wireless umts networks, due to the distribution of mp3 files by means of our wireless application. the download time measurements we have experimentally obtained have shown that an appropriate structuring of the internet-based wireless application may be very helpful to surmount the problems caused by the internet standard protocols which were not especially designed for wireless environments.
a comprehensive model for arbitrary result extraction. within the realms of workflow management and grid computing, scheduling of distributed services is a central issue. most schedulers balance time and cost to fit within a client's budget, while accepting explicit data dependencies between services as the best resolution for scheduling. results are extracted from one service in total, and then simply forwarded to the next service. however, distributed objects and remote services adhere to various standards for data delivery and result extraction. there are multiple means of requesting results and multiple ways of delivering those results. by examining several popular and idiosyncratic methods, we have developed a comprehensive model that combines the functionality of all component models. this model for arbitrary result extraction from distributed objects provides increased flexibility for object users, and an increased audience for module providers. in turn, intelligent schedulers may leverage these result extraction features.
discretizing aerosol dynamics with b-splines. this paper presents a discretization technique for particle dynamics equation based on the b-spline interpolation of the solution. the method is developed in the general framework recently proposed by the authors. numerical tests include the coagulation-growth of the exponential distribution and of a cosine hill in logarithmic coordinates.
short inversions and conserved gene clusters. two independent sets of recent observations on newly sequenced microbial genomes pertain to the prevalence of short inversion as a gene order rearrangement process and to the lack of conservation of gene order within conserved gene clusters. we propose a model of inversion where the key parameter is the length of the inverted fragment. we show that there is a qualitative difference in the pattern of evolution when the inversion length is small with respect to the cluster size and when it is large. this suggests an explanation of the lack of parallel gene order in conserved clusters and raises questions about the statistical validity of putative functionally selected gene clusters if these have only been tested against inappropriate null hypotheses.
navigating with inheritance in hypermedia presentations. due to significant improvements in networking, providing multimedia presentations has become a real commercial issue and a technical challenge for web tv, e-learning, commercial presentations. hyperlink in html has been designed for hyperdocuments navigation, but the actual use of hyperlinks lacks of relevant features to play continuous media such as videos. the main two issues in using hyperlink and multimedia in a web context are:(a) navigation and continuity of streamed hypermedia. in a multimedia presentation, when switching from one point to another, if the continuity of streamed media is required, then a video should not stop.(b) adaptability of the presentation in response to the user's reaction. in our approach, we consider spatial regions whose positions can change according to the user's wishes, as well as spatial regions that can appear in the presentation and preserve the continuity of streamed media.this paper addresses these two issues by considering an object oriented vision of a multimedia presentation structure. we propose a new xml based language for multimedia presentations, called arm. in this multimedia document format, we introduce the notions of spatial and temporal inheritance, and of overloading. spatial inheritance together with overloading allows to keep the same spatial structure between two or more documents, or to change this spatial shape in response to the user's activity. additionally, the temporal inheritance allows the continuity of streamed media even in the case of multiple hyperlinks (i.e., hyperlinks with more than one target).
gd-ghost: a goal-oriented self-tuning caching algorithm. a popular solution to internet performance problems is the widespread caching of data. many caching algorithms have been proposed in the literature, most attempting to optimize for one criteria or another, and recent efforts have explored the automation and self-tuning of caching algorithms in response to observed workloads. we extend these efforts to consider the goal of optimizing for selectable performance criteria. with our proposed algorithm, we have shown performance matching and exceeding the best performance of the known greedy dual-size algorithms for either object or byte hit ratios across different web workloads. gd-ghost consistently outperforms the other algorithms tested, at its worst observed performance gd-ghost exhibited equivalent miss rates to those of the best applicable greedy-dual variant, while achieving miss rates that were 25% lower than the worst performing variant. for byte miss rates, gd-ghost consistently demonstrated rates lower than the best applicable greedy-dual variant. at its best, gd-ghost offered byte miss rates 10% lower than the best variant.
a simple mathematical model of adaptive routing in wormhole k-ary n-cubes. many fully-adaptive algorithms have been proposed for k-ary n-cubes over the past decade. the performance characteristics of most of these algorithms have been analysed by means of software simulation only. this paper proposes a simple yet reasonably accurate analytical model to predict message latency in wormhole-routed k-ary n-cubes with fully adaptive routing. this model requires a running time of o(1) which is the fastest model yet reported in the literature while maintaining reasonable accuracy.
computer-aided law and advanced technologies. the connection between law and new advanced technologies comes from discussions originated in the different regions and nations of the world and also to create new legal models suitable with the new technology such as electronic platform for public or private services or electronic courts proceedings. said reliances are relevant in electronic commerce, whose development depends in a decisive way upon the trust of users, which is a factor of the success of innovative technologies, such as software agents and new business methods, such as marketplaces.
editorial message: special track on computer-aided law and advanced technologies. computer-aided law and advanced technology is focussed on law and advanced technologies for representing a broad and diverse forum for the discussion of research in computer-aided law, one that can provide synergies when aligned with other areas within the sac. the track has the specific objectives of joining the technical materials to legal framework with the aim to build the necessary infrastructure for preparing socio-legal, economic and statistical studies and organisational and regulatory proposals (rules of law, standards and codes of conduct). the hope is to develope modules in ict law and the technical platform both legal issues and computer science and engineers issues.
efficient first-class generics on stock java virtual machines. the second-class formulation of generics in java 5.0 discards generic type information during compilation. as a result, java 5.0 prohibits run-time type-dependent operations, generates unavoidable unchecked warnings (type errors) during compilation, and causes unexpected behavior during execution. the nextgen generic java compiler eliminates these pathologies by retaining parametric type information at runtime and customizing the code in generic classes and polymorphic methods where necessary to support (parametric) type-dependent operations. nextgen is a production compiler for the entire java 5.0 language; it executes on standard jvms and is backward compatible with existing libraries and other binaries. benchmarks show that the first-class implementation of generic types in nextgen has essentially the same performance as java 5.0 and significanlty outperforms alternative first-class implementation architectures.
accessee controlled type selection for a multiple-type object. inada is an enhanced c++ persistent programming language, compliant with odmg standard. inada supports multiple-type objects facility which enables any persistent objects to obtain any type at any time the type is needed, and to lose any unnecessary types dynamically. using the facility, we can model changes in roles/aspects which a real-world entity possesses. access to a multiple-type object needs to select one from among its own types. the selection is conventionally left to an object accessing a multiple-type object. a real-world entity is, however, flexible enough to decide its roles/aspects depending on a meeting entity whom it exchanges messages with. from the consideration, this paper proposes <u>a</u>ccess<u>ee</u> controlled type selection (aee) method in which a multiple-type object selects one from among its own types depending on an object accessing it. the implementation of aee method in inada is also presented, which does not need any modification to the language specification and the processing system of inada.
xml retrieval: what about using contextual relevance? the aim of this study is to evaluate the impact of context to better identify relevant elements in xml retrieval. context is represented here by clues on whole document relevance. we represent context according to different points of view: by introducing document dimension while computing terms weights, by using document relevance when evaluating elements relevance or by ranking elements on document relevance. experiments were undertaken on inex collection, and results showed the interest of contextual relevance and a relative high precision of our proposal comparing to inex official results.
mining dependence rules by finding largest itemset support quota. in the paper a new data mining algorithm for finding the most interesting dependence rules is described. dependence rules are derived from the itemsets with support significantly different from its expected value and therefore considered interesting. since such itemsets are distributed non-monotonically in the lattice of all itemsets the support monotonicity property cannot be used for their search. instead we estimate upper/lower bounds for the support to find itemsets with large interval of possible support values called support quota. since the support quota is known to be monotonically decreasing the search space can be effectively restricted. strongly dependent itemsets are selected by computing their expected support using iterative proportional fitting algorithm and comparing it with the real itemset support.
grouping and aggregation in the concept-oriented data model. in the paper we describe the problem of grouping and aggregation in the concept-oriented data model. the model is based on ordering its elements within a hierarchical multidimensional space. this order is then used to define all its main properties and mechanisms. in particular, it is assumed that elements positioned higher are interpreted as groups for their lower level elements. two operations of projection and de-projection are defined for one-dimensional and multidimensional cases. it is demonstrated how these operations can be used for multidimensional analysis.
light stemming approaches for the french, portuguese, german and hungarian languages. this paper describes and evaluates various general stemming approaches for the french, portuguese (brazilian), german and hungarian languages. based on the clef test-collections, we demonstrate that light stemmers for the french, portuguese and hungarian languages perform well, and reasonably well for the german language. variations in mean average precision among the different stemming approaches are also evaluated and sometimes they are found statistically significant.
are multiagent algorithms relevant for real hardware? a case study of distributed constraint algorithms. researchers building multi-agent algorithms typically work with problems abstracted away from real applications. the abstracted problem instances allow systematic and detailed investigations of new algorithms. however, a key question is how to apply algorithm, developed on an abstract problem, in a real application. in this paper, we report on what was required to apply a particular distributed resource allocation algorithm developed for an abstract coordination problem in a real hardware application. a probabilistic representation of resources and tasks was used to deal with uncertainty and dynamics and local reasoning was used to deal with delays in the distributed resource allocation algorithm. the probabilistic representation and local reasoning enabled the use of the multi-agent algorithm which, in turn, improved the overall performance of the system.
separation, review and supervision controls in the context of a credit application process: a case study of organisational control principles. this paper presents a case study of the organisational control principles present in a credit application process at the branch level of a bank. the case study has been performed in the context of an earlier suggested formal framework [6] for organisational control principles based on the alloy predicate logic and its facilities for automated formal analysis and exploration [2].in particular, we establish and validate the novel concepts of specific and general obligations. the delegation of these two kinds of obligations must be controlled by means of review and supervision controls. the example of a credit application process is used to discuss these organisational controls.
a case study of separation of duty properties in the context of the austrian "elaw" process. over the last few years rapid progress has been made in moving from conceptual studies, "whitepapers" and initiatives to the actual deployment of e-government systems [13]. in this paper we present the case study of an existing e-government system (elaw) which already supports key legislative processes in the country of austria1. the study has been performed in the context of the eu fp6 project "ejustice".we present a detailed system and workflow representation referring to the example process of changing a federal law in austria. since such processes and their results, i.e. the laws of a country, have an enormous impact on society, they need to be secured against external and internal alteration, be it inadvertent or malicious. this is even more important in the electronic world.instead of discussing the obvious security requirements like virus protection or network-level access control, our focus is on an often neglected form of organisational security and control properties called separation of duties. we will analyse and discuss a set of these in terms of the described elaw process.
extending the business engineering framework for application integration purposes. current concepts of enterprise application integration often focus on technical issues only. previous, more holistic approaches of deriving information system concepts from business requirements often addressed the development of a new information system replacing the existing, not integrated systems. in this paper, we describe an extension of the business engineering framework for application integration purposes.
a posteriori defensive programming: an annotation toolkit for dos-resistant component-based architectures. denial-of-service (dos) attacks are a major concern for modern distributed applications. they exploit weakness in the software in order to make it unavailable to well-behaved users. building dos resistant software is still an issue. solutions relying on the use of annotations have been proposed. nevertheless, they require modifying the source code of the application, and must thus be applied at design time. in this paper, we propose an annotation toolkit that allows building dos resistant component-based systems. the solution we propose does not require any modification of the source code of the application. moreover it can be applied at deployment time. its implementation relies on the use of aspect-oriented programming techniques together with java 1.5 annotations.
bulkloading and maintaining xml documents. the popularity of xml as a exchange and storage format brings about massive amounts of documents to be stored, maintained and analyzed --- a challenge that traditionally has been tackled with database management systems (dbms). to open up the content of xml documents to analysis with declarative query languages, efficient bulk loading techniques are necessary.database technology has traditionally been offering support for these tasks but yet falls short of providing efficient automation techniques for the challenges that large collections of xml data raise. as storage back-end, many applications rely on relational databases, which are designed towards large data volumes. this paper studies the bulk load and update algorithms for xml data stored in relational format and outlines opportunities and problems. we investigate both (1) bulk insertion and deletion as well as (2) updates in the form of edit scripts which heavily use pointer-chasing techniques which often are considered orthogonal to the algebraic operations relational databases are optimized for. to get the most out of relational database systems, we show that one should make careful use of edit scripts and replace them with bulk operations if more than very small portion of the database is updated.we implemented our ideas on top of the monet database system and benchmarked their performance.
integrated querying of xml data in rdbmss. this paper proposes a way to integrate cleanly relational databases and xml documents. the main idea is to draw a clear line of demarcation between the two concepts by modelling xml documents as a new atomic sql type. the standardised xml tools like xpath, xquery, xslt are then user-defined functions that operate on this type. well-defined interoperability is guaranteed by, on the one hand, defining a standard way to markup sql relations as xml documents and, thus, to make them accessible to the xml tools; on the other hand, xpath and xquery queries run against the xml portion of the database can use the same predefined schema to make their results accessible to the sql language for further processing. additionally, a method for set-oriented evaluation of regular path expressions is presented that integrates into our implementation framework.
methods and guidelines for the design and development of domestic ubiquitous computing applications. in our research we investigate how applications can be conceived, designed, and implemented that fit into people's home environments. in particular we describe our method of how user centred design and participatory design can be appropriated to find users' requirements and design ideas for ubiquitous computing applications for the home. in our example we focus on information presentation and display appliances. in the process we go from individual solutions, fitting a single persona each, to more generic prototypes. based on this we provide a set of guidelines for the design of display appliances in the home environment.
expanding the taxonomies of bibliographic archives with persistent long-term themes. as document collections accummulate over time, some of the discussion subjects in them become outfashioned, while new ones emerge. in this paper, we address the challenge of finding such emerging and persistent "themes", i.e. subjects that live long enough to be incorporated into a taxonomy or ontology describing the document collection. our method is based on similarity-based clustering and cluster label construction and focusses on the identification of cluster labels that "survive" changes in the constitution of the underlying population of documents, including changes in the feature space of dominant words. we conducted a set of promising experiments on the identification of themes that manifested themselves in the acm library within the last decade.
a knowledge based system for content-based retrieval of scalable vector graphics documents. scalable vector graphics (svg), the novel xml based language for describing two-dimensional graphics, is now a w3c standard and it is likely to become popular on the internet, due to its inherent advantages over raster image formats in several domains. we present a system for semantic based retrieval by content of svg. the system is endowed of a web crawler for documents search and a graphical interface for query by sketch. the approach adopted in the system implements a simple description logic devised for the semantic indexing and retrieval of complex objects. its syntax allows to describe basic shapes and complex objects as compositions of basic ones, and transformations. its extensional semantics, which is compositional, allows to define retrieval, classification, and subsumption services. an experimental evaluation is also presented, which shows results obtained in terms of precision and recall, but also points out that there are still few svg documents available on the web.
a relational approach to software metrics. there is still no standardization of software measures and metrics extraction tools have to be updated frequently to handle the changes. a possible solution is represented by using an intermediate abstraction layer to decouple the information extraction process from the use of the information. in this way a metrics researcher do not have to deal with language parsing production concepts such as declarations, class specifiers, and base clauses. this paper presents webmetrics, an automated tool for software metrics collection. the tool uses, as intermediate layer, a set of intuitive relations to describe the source code structure. these relations are stored in a database in order to calculate metrics directly by performing sql queries. to test the architecture, we applied the tool to the source code of an opensource project in order to compute ck metrics suite.
trust enhanced ubiquitous payment without too much privacy loss. computational models of trust have been proposed for use in ubicomp environments for deciding whether to allow customers to pay with an e-purse or not. in order to build trust in a customer, a means to link transactions using the same e-purse is required. roughly, trust is a result of knowledge. as the number of transactions increases, the resulting increase in knowledge about the user of the e-purse threatens privacy due to global profiling. we present a scheme (and its prototype) that mitigates this loss of privacy without forbidding the use of trust for smoothing payment by giving the opportunity to the user to divide trust (i.e. transactions) according to context (e.g. location, user's current activity or subset of shops).
editorial message special track on trust, recommendations, evidence and other collaboration know-how (treck). computational models of trust and mechanisms based on the human notion of trust have been gaining momentum over the last couple of years. one reason for this is that traditional security mechanisms are challenged by open, large scale and decentralised environments. the use of an explicit trust management component goes beyond security though. trust has been used in reputation systems, collaborative filtering, social/business networking services, dynamic coalitions and virtual organizations. two very successful real-world applications based on computational trust are googletm's pageranktm trust metric, where the entities are the web pages and their trust relationships are the hyperlinks between the pages, and ebay@'s user profile score, which represents the trustworthiness of a user according to recommendations about past transactions.
editorial message: second special track on trust, recommendations, evidence and other collaboration know-how (treck'06). with the emerging wave of web 2.0 applications and their core decentralised user-centric pillar, there is an increased need for mechanisms to deal with uncertainty to still reap the benefits of collaboration and filter; facilitate and support decision-making; filter and secure the large scale number of the interconnected elements of these new popular applications. for example, peer-to-peer file sharing needs mechanisms to avoid downloading risky files and to optimise performance in a decentralised way.
learning temporal patterns for anomaly intrusion detection. for the last decade an explosive spread of computer systems and computer networks has resulted in a society that is increasingly dependent on information stored on these systems. a computer system connected to the network is accessible from another computer in this network regardless of its geographical position. along with providing many benefits for legitimate users this technology creates almost unlimited opportunities for malicious persons, which using software vulnerabilities may successfully penetrate the networked computer systems. in order to eliminate potential devastating consequences caused by breaches in computer systems, more and more attention is drawn to the information security problems. however, despite these efforts, the occurrences of the security violations in the computer networks became increasingly frequent. in this paper we discuss an approach to detect the intrusions. being able to accurately recognize its legitimate users a system may effectively detect masqueraders. the paper particularly focuses on the question of temporal pattern extraction from user behavior and shows that sequential patterns are not the only ones that may be found in user events sequences. there are also temporal patterns present in user behavior, which together with sequential may be used for efficient user recognition.
designing and specifying mobility within the multiagent systems engineering methodology. recently, researchers have created many platforms and applications for mobile agents; however, current agent-oriented software engineering (aose) methodologies have yet not fully integrated the unique properties of these mobile agents. this paper attempts to bridge the gap between current aose methodologies and mobile agent systems by incorporating mobility into the established multiagent systems engineering (mase) methodology. we accomplished this by adding a move command to the mase analysis models and then defined the required transformations to incorporate the required functionality into the design. finally, we translated the design models into java-based agents that operate within a mobile agent environment.
stochastic study of real-time transactions success ratio. the well-known and accepted criterion for measuring real-time database systems (rtdbss) performances is to maximize the transactions success ratio. in this paper, we focus on a stochastic study of firm real-time transactions, i.e, transactions which are aborted and discarded as soon as they have missed their deadlines. the results we obtained is the reasonable approximation of this ratio behavior by a probabilistic distribution with defined parameters. to achieve this objective and due to the lack of real data, we have designed a simulator based on components including probabilistic characteristics: a transactions generator and a conflicts generator. the latter is based on data conflicts level. after testing two kinds of concurrency control protocols, a pessimistic and an optimistic one, simulation results have helped us to determine load conditions where a kind of protocol is better than the other.
infotainment across access devices: the perceptual impact of multimedia qos. the introduction of multimedia on pervasive and mobile communication devices raises a number of perceptual quality issues. however, limited work has been done examining the 3-way interaction between use of equipment, user perceptual quality and quality of service. our work measures user perceptual quality with the quality of preception (qop) metrics which comprises levels of informational transfer (objective) and user satisfaction (subjective) when users are presented with multimedia video clips at three different frame rates, using four different display devices. finally, our results will show that variation in frame-rate does not impact a user's level of information assimilation (ia), however, does impact a users' perception of multimedia video 'quality'.
a semantic framework for the recursive specification of interaction protocols. this paper addresses two major problems concerning the specification of interaction protocols: the lack of an established semantic framework which precisely identifies the modelling elements that different kind of specification techniques may exploit in their specifications; and the lack of techniques which allow designers to reuse pre-specified protocols by specialising them in more specific domains. we deal with these issues in the context of the organisational framework provided by the rica theory, and propose a new formalism based on so-called interaction state machines, which will be applied to the re-design of some protocols of the fipa ipl.
communication delay in wormhole-routed torus networks. a new analytical model for predicting message delay in wormhole-routed torus is presented. unlike previous wormhole routing models, which mainly have been developed for uniform traffic, the model introduced in this paper computes message latency in the wormhole-routed torus in the presence of broadcast traffic. results obtained through simulation experiments show that the model exhibits a good degree of accuracy in predicting message latency under different working conditions.
depth-first frequent itemset mining in relational databases. data mining on large relational databases has gained popularity and its significance is well recognized. however, the performance of sql based data mining is known to fall behind specialized implementation since the prohibitive nature of the cost associated with extracting knowledge, as well as the lack of suitable declarative query language support. we investigate approaches based on sql for the problem of finding frequent patterns from a transaction table, including an algorithm that we recently proposed, called propad (pro-jection pattern discovery). propad fundamentally differs from an apriori-like candidate set generation-and-test approach. this approach successively projects the transaction table into frequent itemsets to avoid making multiple passes over the large original transaction table and generating a huge sets of candidates. we have made performance evaluation on dbms (ibm db2 udb eee v8) and compared the performance results with k-way join approach proposed in [11] and sql based fp-tree approach proposed in [13]. the experimental results show that our algorithm can get efficient performance.
sql based frequent pattern mining without candidate generation. scalable data mining in large databases is one of today's real challenges to database research area. the integration of data mining with database systems is an essential component for any successful large-scale data mining application. a fundamental component in data mining tasks is finding frequent patterns in a given dataset. most of the previous studies adopt an apriori-like candidate set generation-and-test approach. however, candidate set generation is still costly, especially when there exist prolific patterns and/or long patterns. in this study we present an evaluation of sql based frequent pattern mining with a novel frequent pattern growth (fp-growth) method, which is efficient and scalable for mining both long and short patterns without candidate generation. we examine some techniques to improve performance. in addition, we have made performance evaluation on commercial dbms (ibm db2 udb eee v8).
a framework for (re)deploying components in distributed real-time and embedded systems. this paper describes the resource allocation and control engine (race) that integrates multiple resource management algorithms for (re) deploying and managing performance of application components in distributed real-time and embedded (dre) systems. race enables dre systems to (re) configure allocation and control algorithms depending on application characteristics and environmental conditions. it also enables developers to focus on algorithm logic, while reusing many mechanisms used to (re)configure and (re)deploy the algorithms on distributed computing nodes.
study of the usefulness of known and new implicit indicators and their optimal combination for accurate inference of users interests. explicit relevance feedback involves explicit ratings of documents or terms by users and disrupts their browsing and searching. the alternative non-disruptive method is implicit feedback inferring users' needs and interests by monitoring their regular interaction with the system. some implicit indicators of interest, such as reading time, have been investigated in previous studies and were found indicative to the relevance of documents but not sufficiently accurate [1,2,3,4]. in this paper we present and examine several new relative implicit feedback indicators, and study the effect of combining several implicit indicators. the paper describes a large-scale user study on which users' searches were observed by a specially developed browser that recorded their behavior (implicit indicators) as well as their explicit ratings. we analyzed the relationship between implicit indicators and explicit ratings and found that a certain combination of implicit indicators achieved higher correlation with the explicit ratings than any of the individual indicators. we have also found that the relative indicators are more indicative to the level of interest of a user item than the non-relative indicators.
constructing web search queries from the user's information need expressed in a natural language. this paper focuses on improving the quality of information retrieval on the web through the use of long queries. long queries allow use of natural language and provide for a more complete description of the user's information need. we propose and analyze several novel algorithms dealing with long query information retrieval on the web. these algorithms include selecting of search terms, constructing multiple query formulations, merging and ranking search results. we developed a meta-search engine, incorporating the proposed algorithms, and conducted a series of experiments to evaluate the performance of various algorithms. we also compared search results of the new engine with the results of popular search engines on the web. these experiments clearly demonstrate that using long queries in the web environment is practical and can substantially improve the quality of information retrieval.
ubicomp assistant: an omnipresent customizable service using marks (middleware adaptability for resource discovery, knowledge usability and self-healing). due to the pervasive nature of current short range, low-power wireless connectivity and easy availability of low-cost light weight mobile devices, it is necessary to have an omnipresent customizable service. it can be used by different types of users different fields such as education, healthcare, marketing, or business, at any time, and at any place. these devices can reach ubiquitously to neighboring devices using a free short range ad hoc network. unfortunately, to the best of our knowledge, no one has designed such a service. in this paper, we present the details of the ubicomp assistant (ua), which is designed to accomplish the above objectives. to evaluate the design, we have developed an application which uses ua as a service. it uses marks (middleware adaptability for resource discovery, knowledge usability and self-healing) as an underlying core service provider.
igrocer- a ubiquitous and pervasive smart grocery shopping system. emerging smart phones are poised to give a whole new dimension to the way we shop, bank, and go about many of our everyday activities. igrocer is a smart grocery shopping assistant, that re-defines grocery shopping. it is capable of maintaining nutrition profiles of its users. particularly useful for elders and disabled shoppers, igrocer can aid and advice users on what products to buy and what to avoid based on nutrition criteria and price constraints. implemented on a smart phone with a barcode scanner accessory, igrocer has a number of killer features that include: (1) ubiquitous shopping list: adding items to the shopping list by different means (e.g. simply scanning them when near empty, scanning and storing manufacturer coupons, planning the weekly menu right on the phone or through the web, and shopping for the necessary ingredient of a particular recipe, (2) quick and assisted in-store shopping: while shopping in the grocery store, igrocer maps out the shortest shopping path with a map indicating the location of the next item on the list, and (3)automated check-out: igrocer is capable of acting on behalf of the store and the customer to perform a trusted queue-less checkout. in this "application-oriented" paper, we present the igrocer concept and give details of its architecture and implementation. we also summarize the lessons learnt throughout its development and testing phases.
assessing the effect of failure severity, coincident failures and usage-profiles on the reliability of embedded control systems. the increasingly ubiquitous use of embedded systems to manage and control our technologically (ever-increasing) complex lives makes us more vulnerable than ever before. knowing how reliable such systems are is absolutely necessary especially for safety, mission and infrastructure critical applications. this paper presents a structured compositional modeling method for assessing reliability based on characteristic data and stochastic models. we illustrate this using a classic embedded control system (sensor-inputs | processing | actuator-outputs), anti-lock braking system (abs) and empirical data. special emphasis is laid on modeling extra-functional characteristics of severity of failures, coincident failures and usage-profiles with the goal of developing a modeling strategy that is realistic, generic and extensible. the validation approach compares the results from the two separate models. the results are comparable and indicate the effect of coincident failures, failure severity and usage-profiles is predictable.
an alternative routing algorithm for the pyramid structures. a pyramid structure of size n has a diameter of log n, which immediately leads to an optimal routing algorithm, using only parent-child links. however, shortest paths between nodes may be unavailable because of the existence of faulty nodes. on the other hand, there exist many other potential communication paths using links in the associated meshes.in this paper, we present an alternative routing algorithm making use of both mesh links and parent-child links, and study a set of bypassing paths associated with this algorithm.
an optimal broadcasting schema for multidimensional mesh structures. we present a local broadcasting schema for the multidimensional mesh structures, which will transmit a message to all the nodes within the minimal amount of time. we will also study the average amount of time it takes for such a schema to send a message to an arbitrary but fixed node in the structure.
a fuzzy model for reasoning about reputation in web services. reputation systems are typically based on ratings given by the users. when there are no mechanisms in place to detect collusion and deception, combining user testimonies as such to form a provider's reputation may not give an accurate assessment, especially if the context of the ratings is not known. moreover, such systems are vulnerable to manipulations by malicious users. hence it becomes essential to establish the validity of the ratings prior to using them in formulating reputation based on such ratings. it is important to identify the rationale behind the ratings so that similar ratings (or ratings pertaining to a context) can be aggregated to obtain a reputation value meaningful in that context. we propose a fuzzy approach to analyze user rating behavior to infer the rationale for ratings in a web services environment. this inference of rationale facilitates the system to validate ratings, detect deception and collusion, identify user preferences and provide recommendations to users.
alter: first step towards dependable grids. this paper presents alter, an adaptive failure detection service, which incorporates the technique of unreliable failure detection service and the idea of r-gma. alter is organized in a hierarchical structure and it can be adaptive to the system conditions and user requirements with changing the system parameters and system organizations. with mathematical evaluation, alter shows good scalability and flexibility, which is suitable for grid environments.
a role administration system in role-based authorization infrastructures - design and implementation. in this paper we describe a system whose purpose is to help establish a valid set of roles and role hierarchies with assigned users and associated permissions. we have designed and implemented the system, called ra system, which enables role administrators to build and configure various components of a role-based access control (rbac) model, thereby making it possible to lay a foundation for role-based authorization infrastructures. three methodological constituents for our purpose are introduced, together with the design and implementation issues. the system has a role-centric view for easily managing constrained roles as well as assigned users and permissions. an ldap-accessible directory service was used for a role database. we show that the system can be seamlessly integrated with an existing privilege-based authorization infrastructure. we finally discuss our plans for future development of the system.
cost effective transcoding for qos adaptive multimedia streaming. transcoding is a core technique that is used in providing quality-of-service (qos) adaptive multimedia streaming service. many studies have examined how best to perform transcoding and reduce computation overhead. however, the issue of when to transcode has not been adequately studied in previous research. this paper addresses this issue and presents a simple and intelligent approach that can be used to reduce both disk bandwidth and space requirements. our approach determines the optimum time to apply transcoding by considering the potential benefits that can be realized. for instance, in order to save disk bandwidth for frequently accessed content, it pre-creates and stores multiple qos versions. on the other hand, in order to save disk space for rarely accessed content, it stores only a single qos version and performs transcoding on the fly. the key is to find the optimal threshold between pre-created multiple qos versions and on-demand transcoding. we compute the optimal threshold by using a mathematical model. a simulation-based experiment to evaluate the effectiveness of our new approach highlights three advantages. first, our method effectively reduces both disk bandwidth and space requirements. second, our technique is more efficient for skewed access patterns. third, the threshold computed by our mathematical model results in improved performance regardless of environmental parameters.
efficient mediators through dynamic code generation: a method and an experiment. mediators are well-known software components in the construction of distributed systems and applications, with clear advantages when adding functionality to legacy code. however, mediators that must handle dynamic interfaces (i.e., those that may change at run-time such as callback functions) are not easy to build in most imperative languages such as c, due to the many variants implied by the dynamic interfaces. we call his kind of mediators intermediators. we propose a systematic implementation method based on the concept of closures to implement intermediators using the tempo run-time specializer for c programs. to illustrate this method, we implemented a unified user authentication intermediator for unix and windows 2000 called gina-im. gina-im gets the password entries from a unix nis server and performs user authentication based on the gina model (graphical identification and authentication) of windows 2000. the code of gina-im is a quarter of the code size of a conventional component written without our tools. gina-im is in production use at authors' university by two thousands of freshmen in class and several thousands of students daily.
supporting real-time visualization with the hdov tree. we propose the hierarchical degree-of-visibility (hdov) tree to support real-time visualization of large ves. each node in an hdov tree represents a spatial region in the scene, and contains a precomputed degree-of-visibility value. in run-time, the dov values can be used to update rapidly the dov of each node when the viewing region changes. each node is also associated with the lods of the object(s). we propose two techniques to traverse the hdov tree for real-time visualization. we also propose a method to compute the degree of visibility. we report experimental results of a prototype implementation that show the effectiveness of the proposed techniques.
a model for the configurable composition and synchronization of complex trading activities. with the increasing number of market places and potential trading partners across the e-commerce environment, it will become natural for multiple trading activities to be deployed as part of single trading strategy. this paper describes a multi-process model for controlling interrelated trading activities. the model includes a powerful generic synchronization construct for building a variety of executable trading engines. the modular design of the construct enables the realization of complex trading schemes, including a number of well known strategies from the financial trading domain. a homogeneous interface is defined to allow seamless integration of control modules built using this construct with elementary trading tasks which directly interact with the trading partners using various negotiation protocols. the model also enables iterative negotiation capabilities, which are essential in any complex trading environment. in addition, the model is designed to be orthogonal to the reasoning model so that any reasoning mechanism can be plugged into it.
towards multisensor data fusion for dos detection. in our present work we introduce the use of data fusion in the field of dos anomaly detection. we present dempster-shafer's theory of evidence (d-s) as the mathematical foundation for the development of a novel dos detection engine. based on a data fusion paradigm, we combine multiple evidence generated from simple heuristics to feed our d-s inference engine and attempt to detect flooding attacks.our approach has as its main advantages the modeling power of theory of evidence in expressing beliefs in some hypotheses, the ability to add the notions of uncertainty and ignorance in the system and the quantitative measurement of the belief and plausibility in our detection results.we evaluate our detection engine prototype through a set of experiments, that were conducted with real network traffic and with the use of common ddos tools. we conclude that data fusion is a promising approach that could increase the dos detection rate and decrease the false alarm rate.
j2ee server scalability through ejb replication. with the development of internet-based business, web applications are becoming increasingly complex. the j2ee specification aims at enabling the design of such web application servers. these servers have to ensure scalability and availability of the supported applications. scalibility can be achieved using replication techniques or partitionning techniques. the aim of this paper is to compare these approaches. in a j2ee web application server, one important component is the ejb tier. in this context, the jonas web application server provides an example of ejb replication system called cmi (cluster method invocation). in a first step, this paper presents a performance evaluation of cmi. it then introduces incrementally an alternative scheme based on partitionning and shows the performance benefits compared to cmi.
object-oriented design for the specification of the blood clotting cascade: a class-structured view of bio-computing processes. we describe a very intricate case of interlocked bio-processes: the blood clotting cascade, by using a set of tools from object-oriented design (ood). originally, ood has been designed for the abstract specification of complex software prior to programming. ood brings a handful of concepts such as modularity, classes, methods and their inheritance hierarchies for concurrent process synchronization and cooperation. it appears that the set of ood methods can be a very fruitful tool for the abstract description of biological processes apparently quite far away from software engineering. we give a moderately detailed view of the blood clotting cascade using the standard tool of ood: unified modeling language (uml) and its extension: real-time uml.
object-oriented wound healing in the liver: a class-structured view of fibrogenesis and a glimpse of its evolution. we describe a very intricate case of highly correlated bio-processes: the liver fibrogenic cascade, by using a set of tools from object-oriented design (ood). ood methods were designed for the abstract specification of complex software prior to programming. it appears that ood methods can be a fruitful tool for the abstract description of biological processes apparently quite far away from software engineering. we give a detailed view of the fibrogenic cascade within the liver using the now standard tool of ood: unified modeling language (uml) and one extension: real-time uml.ood methods enforce the important role of concepts such as modularity, classes, methods and their inheritance hierarchies as well as primitives for concurrent process synchronization and cooperation. these concepts are surprisingly quite relevant for specifying bio-processes, and unexpectedly, they suggest an extension of the strict evolutionary explanation of the processes involved. as well as describing bio-structures and their interactions, we could consider evolutionary description of classes and processes. in particular, the ood inheritance concept seems to be significant as an extension to gradualism. it suggests that dna could encode, in universal-turing-machine like fashion, the hierarchies of classes of molecular structures and perhaps the process templates associated with methods.
diagnosis of lung nodule using gini coefficient and skeletonization in computerized tomography images. this paper uses the gini coefficient and a set of skeleton measures, with the purposes, with the purpose of characterizing lung nodules as malignant or benign in computerized tomography images.based on a sample of 31 nodules, 25 benign and 6 malignant, these methods are first analyzed individually and then jointly, with classfication and analysis techniques (linear stepwise discriminant analysis, leave-one-out and roc curve). we have concluded that the individual measures and their combinations produce good results in the diagnosis of lung nodules.
binarizing and filtering historical documents with back-to-front interference. this paper presents a new segmentation-based method for generating high-quality monochromatic images of historical documents. the proposed segmentation algorithm is based on the entropy of the histogram of the image. the algorithm eliminates back-to-front interference in documents written on both sides on translucent paper.
a framework for result handling in bioinformatics: an application to computer assisted drug design. bioinformatics is an area that demands the management of large amounts of data. one example is computer assisted drug design (cadd) where it is necessary to organize the results of a large number of protein-ligand interaction simulations. projects such as the united devices cancer research project, the smallpox grid project and fightaids@home use grid computing to gather results from a large number of computers. these projects, nonetheless, have particular solutions, developed by commercial companies, to distribute and rank the results. due to the need for handling large amounts of data in specific formats, this work presents a framework dedicated to handling biological data with a case study on cadd. to validate the implementation, an open source approach was employed using the xtremweb platform to distribute the tasks, and the software autodock 3.0 for simulating protein-ligand interactions. the xtremweb dispatcher was adapted to call the proposed result handling framework, which analyzes the results from the protein-ligand interaction outputs in order to extract and organize the relevant information.
an open source and web based framework for geographic and multidimensional processing. the development of business intelligence (bi) systems has been the destination of high investments made by several enterprises. the motivation is because an efficient decision support environment brings them several business world advantages, mainly if it provides integrated functionalities for the geographical and/or multidimensional processing. the intended goal is to provide users with a system capable of processing both geographic and multidimensional data in a seamless way, by abstracting the complexity of separately querying and analyzing these data in a decision making process. however, this integration may not be fully achieved yet or may be built using proprietary technologies. this paper presents an open source and web based framework for geographic and multidimensional decision support. our approach uses a geographical data warehouse, a metadata source, a query language and a geographical and multidimensional engine for processing queries sent by a web based client application.
exploring an open, distributed multimedia framework to design and develop an adaptive middleware for interactive digital television systems. interactive digital television systems should provide concepts of middleware for harmonizing and abstracting discrepancies related to hardware and operating systems issues. in such a context, this paper explores a framework for configuration and management of open, distributed multimedia systems with the purpose of designing and developing a component-based adaptive middleware for interactive digital television systems, which incorporates mechanisms for specification, configuration, management and reuse of resources and components.
x-arm: an asset representation model for component repository systems. nowadays, one of the most challenging tasks in component-based software development processes is to discover suitable reusable assets that fulfill the requirements of a particular software system under development. in such a context, this paper presents an xml-based asset representation model for describing all kinds of software assets that can be produced or reused within component-based software development processes. the proposed model is based on asset metadata that provides effective means for developing universal repository systems that can deal with discovery, retrieval and composition of software components.
distributed approximate mining of frequent patterns. this paper discusses a novel communication efficient distributed algorithm for approximate mining of frequent patterns from transactional databases. the proposed algorithm consists in the distributed exact computation of locally frequent itemsets and an effective method for inferring the local support of locally unfrequent itemsets. the combination of the two strategies gives a good approximation of the set of the globally frequent patterns and their supports. several tests on publicly available datasets were conducted, aimed at evaluating the similarity between the exact result set and the approximate ones returned by our distributed algorithm as well as the scalability of the proposed method.
assigning document identifiers to enhance compressibility of web search engines indexes. granting efficient accesses to the index is a key issue for the performances of web search engines (wse). in order to enhance memory utilization and favor fast query resolution, wses use inverted file (if) indexes where the posting lists are stored as sequences of d_gaps (i.e. differences among successive document identifiers) compressed using variable length encoding methods. this paper describes the use of a lightweight clustering algorithm aimed at assigning the identifiers to documents in a way that minimizes the average values of d_gaps. the simulations performed on a real dataset, i.e. the google contest collection, show that our approach allows to obtain an if index which is, depending on the d_gap encoding chosen, up to 23% smaller than the one built over randomly assigned document identifiers. moreover, we will show, both analytically and empirically, that the complexity of our algorithm is linear in space and time.
on tracker attacks in health grids. the utilisation of grid computing to support healthcare research is becoming increasingly widespread, as is the use of it to support healthcare delivery. furthermore, it seems that the two areas are on an inevitable convergence path as clinical communities in several countries start to investigate how real data stored in electronic patient records can be utilised to facilitate research. the use of it within healthcare gives rise to unique social and ethical challenges; the area of grid computing has given rise to significant novel security challenges; and the anticipated convergence of these two fields will inevitably give a new lease of life to established challenges. in this paper we consider the phenomenon of tracker attacks in this emerging context, and outline a potential approach to addressing the problem.
the pegasus portal: web based grid computing. pegasus is a planning framework for mapping abstract workflows for execution on the grid. this paper presents the implementation of a web-based portal for submitting workflows to the grid using pegasus. the portal also includes components for generating abstract workflows based on a metadata description of the desired data products and application-specific services. we describe our experiences in using this portal for two grid applications. a major contribution of our work is in introducing several components that can be useful for grid portals and hence should be included in grid portal development toolkits.
compiler optimizations for java aglets in distributed data intensive applications. code migration in light of distributed data intensive computing poses interesting compilation issues. in this work, we first define a small extension to the aglet model to allow data distribution. in our aglet program, data is distributed over the network using annotations (this is similar to high performance fortran (hpf) where the programmer specifies data distributions through annotations). we analyze the program using the annotations and use the 'owner computes' rule to determine where a given computation should take place. the compiler then schedules the aglet through the network and also determines the data it should carry during its migration. determining efficient schedule of the aglet and which data to carry during migration poses interesting issues.we propose two strategies to optimize the aglet schedule. the first strategy called take all live data: (tald) attempts to carry all the live definitions of variables from a given node when visited. the second strategy take only needed data (tond) attempts to carry only those definitions whose uses are in the destination node. the goal of the first strategy is to minimize the number of migrations which are expensive due to high serialization overheads the second strategy aims to minimize bandwidth consumption during a migration. this could significantly reduce the communication overhead due to minimal amount of data carried during each migration. we have implemented both the strategies in the jikes compiler from ibm. we have evaluated it on a distributed database application and show benefits of both the strategies on large and small databases. the results show that strategies generated by our compiler analysis reduce the overheads and improve execution time.
grammar based off line generation of disposable credit card numbers. context free grammars present the desirable cryptographic property that it is easy to generate and validate strings from a given grammar, however it is hard to identify a grammar given only the strings generated by it. the algorithm used in the authentication protocol proposed in this paper makes use of context free grammars. this authentication protocol is a perfect candidate for the offline generation and validation of a disposable credit card number. the proposed protocol can be used alone and it does not rely on any other cryptographic protocols like ssl for its security. this paper presents and analyses the protocol with respect to its robustness against malicious attacks.
solving the brachytherapy seed localization problem using geometric and linear programming techniques. we propose a technique to solve the brachytherapy seed localization problem in prostate brachytherapy. our algorithm is based on novel geometric approaches to exploit the special structure of the problem combined with a number of key observations which help us formulate it as an integer program. we solve the equivalent linear program and present a variant of randomized rounding to yield an integral solution to our problem. the algorithm is efficient and performs extremely well in practice. we discuss in detail the underlying theory and performance evaluations based on our implementation.
augmenting descriptive scenario analysis for improvements in human reliability design. it is typical for cycles of iteration to be used to refine the current state of the design of a system so that it more closely meets its requirements. such refinements are in terms of the original requirements specification and any new requirements that have been identified during this process. however, not all defined requirements are equally essential, particularly in high consequence systems where there are issues of dependability. although descriptive methods for scenario analysis can be used to highlight new requirements, it can be difficult to evaluate the impact of these new requirements.in this paper, we exemplify this problem and investigate how numeric methods can be used to highlight the impact of consequences identified by descriptive scenario analysis. an example from the context of human reliability analysis is presented and dependability issues for system design are considered.
performance analysis of small fddi networks. fiber distributed data interface (fddi) networks offer a standardized, high-speed interconnection between components in a distributed computer system. extensive research has been conducted on the performance of fddi networks consisting of hundreds of stations distributed over an area of several hundred square meters. this paper extends the prior work to the case of small networks; for example 10 stations distributed around a single room laboratory. the characteristics for these smaller networks differ in some instances from the behavior of larger networks - these differences can be significant in applications where high performance is demanded from a small fddi based network.
selecting parameters of svm using meta-learning and kernel matrix-based meta-features. the support vector machine (svm) algorithm is sensitive to the choice of parameter settings, which makes it hard to use by non-experts. it has been shown that meta-learning can be used to support the selection of svm parameter values. previous approaches have used general statistical measures as meta-features. here we propose a new set of meta-features that are based on the kernel matrix. we test them on the problem of setting the width of the gaussian kernel for regression problems. we obtain significant improvements in comparison to earlier meta-learning results. we expect that with better support in the selection of parameter values, svm becomes accessible to a wider range of users.
standardising the business vocabulary of standards. in the area of standardisation for inter-organisational business processes, terminology confusion is slowly emerging. the meaning of the concept "standard" is not as clear as many people and organisations seem to assume. this paper looks into the various definitions of a standard and four similarly used concepts: specification, recommendation, framework and pattern. when examining the various definitions, four different definitions types were identified: the item itself; the process of creating the item; the document describing how to create the item; and the process of creating this particular document. furthermore, the standardisation efforts described in this paper for the most cases do not define their business vocabulary, meaning that there is some risk for terminology confusion. the conclusion is that there is a need to perform thorough concepts definitions and conceptual modelling in this area.
evaluating database selection algorithms for distributed search. we investigate algorithms of database selection and evaluate their performance by modelling a distributed search system. the evaluation is done using a 10 gigabyte document collection divided into 857 document databases. we have also investigated various evaluation criteria and put forward a new metrics for evaluating database selection algorithms.
decentralized routing algorithms for automated guided vehicles. automated guided vehicles (agvs) are driverless vehicles that are becoming a popular means for material handling. existing methods for routing agvs are generally based on centralized control. the central controller is potentially a bottleneck of communication and the single point of weakness of the system. moreover, the computational cost required to preplan all agv routes may be too high as to affect the scalability of the solution. our project aims to design and develop decentralized routing strategies for an agv system deployed within a container port. two routing algorithms were developed: row-first and semi-random. the goal is to minimize deadlocks and congestion and maximize throughput. the performance of the algorithms were monitored and compared with each other using a graphics based computer simulator called sim-port.
development of a standard format for ebooks. since an electronic book (ebook) has various advantages over a paper-based book, there is a growing interest in ebooks. ebook industries are using different document formats creating difficulties in the interoperability and interchangeability of ebooks. the u.s. and japan have realized the importance of a standard format for ebooks and developed such standards. recently, korea has also developed a standard format based on xml. the primary goal of this standard is to support the interchangeability of ebooks, reflect the characteristics of the korean publication environment, simplify the creation process, and promote compatibility with other standards. it includes an extension mechanism for various document classes, and supports advanced style control such as vertical writing and multi-column based on xsl.
formal specification of role-based security policies for clinical information systems. many healthcare organizations have transited from their old and disparate business models based on ink and paper to a new, consolidated ones based on electronic patient records. there are significant demands on secure mechanisms for collaboration and data sharing among clinicians, patients and researchers through clinical information systems. in order to fulfil the high demands of data protection in such systems, we believe that access control policies play an important role to reduce the risks to confidentiality, integrity, and availability of medical data. in this paper, we attempt to formally specify access control policies in clinical information systems which are highly dynamic and complex environments. we leverage characteristics of temporal linear first-order logic to cope with dynamic access control policies in clinical information systems.
finding frequent itemsets by transaction mapping. in this paper, we present a novel algorithm for mining complete frequent itemsets. this algorithm is referred to as the tm algorithm from hereon. in this algorithm, we employ the vertical representation of a database. transaction ids of each itemset are mapped and compressed to continuous transaction intervals in a different space thus reducing the number of intersections. when the compression coefficient becomes smaller than the average number of comparisons for intervals intersection, the algorithm switches to transaction id intersection. we have evaluated the algorithm against two popular frequent itemset mining algorithms -- fp-growth and declat using a variety of data sets with short and long frequent patterns. experimental data show that the tm algorithm outperforms these two algorithms.
packageblast: an adaptive multi-policy grid service for biological sequence comparison. in this paper, we propose an adaptive task allocation framework to perform blast searches in a grid environment against sequence database segments. the framework, called packageblast, provides an infrastructure to choose or incorporate task allocation strategies. furthermore, we propose a mechanism to compute grid nodes execution weight, adapting the chosen allocation policy to the current computational power of the nodes. our results present very good speedups and also show that no single allocation strategy is able to achieve the lowest execution times for all scenarios.
proactive resilience through architectural hybridization. in a recent work, we have shown that it is not possible to dependably build any type of distributed f fault or intrusion-tolerant system under the asynchronous model. this result follows from the fact that in an asynchronous environment one cannot guarantee that the system terminates its execution before the occurrence of more than the assumed number of faults.some systems resorted to proactive recovery as a way to address this problem, by attempting to ensure that no more than f faults ever occur: nodes are periodically rejuvenated to remove the effects of faults or malicious attacks. however, asynchronous systems with proactive recovery also suffer from the same problem. in fact, proactive recovery protocols usually require stronger assumptions (e.g., synchrony, security) than the system that is proactively recovered.to solve this contradiction, we work with a hybrid distributed system model. we propose proactive resilience as a new and more resilient approach to proactive recovery, based on architectural hybridization: proactive recovery functions are encapsulated in architectural devices that meet the required stronger assumptions, and have a well-defined interface with the recovered system.we present the proactive resilience model (prm) and describe a design methodology under the prm. this methodology is a way of building systems which guaranteedly do not suffer more than the assumed number of faults, and we use it to derive a distributed intrusion-tolerant secret sharing system.
evaluating the intrinsic dimension of evolving data streams. data streams are fundamental in several data processing applications involving large amount of data generated continuously as a sequence of events. frequently, such events are not stored, so the data is analyzed and queried as they arrive and discarded right away. in many applications these events are represented by a predetermined number of numerical attributes. thus, without loss of generality, we can consider events as elements from a dimensional domain. a sequence of events in a data stream can be characterized by its intrinsic dimension, which in dimensional datasets is usually lower than the embedding dimensionality. as the intrinsic dimension can be used to improve the performance of algorithms handling dimensional data (specially query optimization) measuring it is relevant to improve data streams processing and analysis as well. moreover, it can also be useful to forecast data behavior. hence, we present an algorithm able to measure the intrinsic dimension of a data stream on the fly, following its continuously changing behavior. we also present experimental studies, using both real and synthetic data streams, showing that the results on well-understood datasets closely follow what is expected from the known behavior of the data.
a solution for the location problem in arbitrary computer networks using generic dominating sets. many problems exist related to the location problems of resources in a computer network to accommodate client demands subject to constraints imposed on the clients and the servers. for example, one classical location problem consists of computing the dominating sets (ds) of a network. a ds is a set of nodes in the network (called dominating nodes) such that the remaining nodes in the network are adjacent to at least one dominating node. the problem of finding a ds of minimum cardinality is known to be np-complete. a variety of conditions may be imposed on the dominating set d in a graph g = (v, e). among them, we have multiple domination and distance domination. multiple domination requires that each vertex in v --- d be dominated by at least k vertices in d for a fixed positive integer k. distance domination requires that each vertex in v --- d be within distance r of at least one vertex in d for a fixed positive integer r. we refer to the problem of computing ds when these two conditions are taken into account as the generic dominating sets (gds) problem. prior work on solving the gds problem focuses on interval graphs (ig), which can represent only a few network topologies. we present the first solutions to the gds problem for arbitrary graphs. simulation results regarding several configurations are presented.
dynamic instantiation-checking components. parameterization is an effective technique for building flexible, reusable software. when dealing with parameterized components, an important concern is the time at which parameters are bound. many languages provide syntactic support for parameterized components; this mode of parameterization can be called static parameterization. in order to be able to support dynamic reconfiguration, the service facility pattern has been proposed as an enabling technology for dynamic parameterization. however, static parameterization has the advantage of strong type-checking that dynamic parameterization does not. in this paper, we present dyninstacheck --- a tool that automatically instruments dynamically bound parameterized components with run-time checking code that ensures type-safe parameter binding. the source instrumentation is done in a non-intrusive way, using aspect-oriented programming.
discovery of interesting episodes in sequence data. there is considerable body of work on sequence mining of transactional data. most of the related work on point data (not significant intervals) makes several passes over the entire dataset in order to discover frequently occurring (sequential) patterns. but hybrid apriori, proposed in this paper, as the name implies is an apriori-class of mining algorithm in sql and takes a different approach. significant intervals for each event (or device) is computed first and used for detecting frequent event patterns. the advantages of this approach are that the data set is compressed to find significant intervals thereby reducing the size of input used. also, each event/device is processed individually allowing for parallel computation of individual events. then the hybrid apriori algorithm works on the significant intervals using an apriori-style algorithm adapted to intervals. our approach has significant advantages over the traditional mining algorithms in terms of its efficiency, scalability and storage requirements.
supporting transparent model update in distributed case tool integration. model driven architecture (mda) is a software development approach that focuses on models. in order to support mda, a lot of case tools have emerged; each of them provides a different set of modeling services (operations for automating model manipulation). we have proposed an open environment called modelbus, which enables the integration of heterogeneous and distributed case tools. modelbus enables tools to invoke the modeling services provided by other tools. in this paper, we focus on supporting a particular kind of modeling services: services that update models (i.e. they have inout parameters). our contribution is to enable a tool to update models owned by another tool. we propose a parameter passing mechanism that hides the complexity of model update from tools. first, it enables a tool to update models transparently to heterogeneous model representations. second, it enables a tool to update models located in the memory of another remote tool transparently, as if the models were local. third, it ensures the integrity between the updated models and the tool that owns the models.
extending the epc network: the potential of rfid in anti-counterfeiting. the international chamber of commerce estimates that seven percent of the world trade is in counterfeit goods, with the counterfeit market being worth 500 billion usd in 2004. many companies already use overt anti-counterfeiting measures like holograms to confine counterfeiting and product piracy. however, current techniques are not suited for automated tests of product authenticity as required in warehouses, or do not provide the required level of security. in this context, radio frequency identification (rfid) is a promising approach, providing an extensible, flexible and secure measure against counterfeiting. unique product identification numbers together with an infrastructure to seamlessly share rfid-related data over the internet are a basis of efficient track & trace applications. an emerging infrastructure is the epc network, which can be used to provide pedigree information of products and makes plausibility checks possible. in this paper, we propose a solution for products requiring authentication mechanisms that go beyond track & trace. therefore, the evolving epc network should comprehend the functionality to handle tags which support strong cryptography. we suggest extending the upcoming epc network infrastructure with an epc product authentication service. moreover, the development of cost-effective, dedicated authentication devices as well as the belonging standardization is motivated.
a fast program for maximum likelihood-based inference of large phylogenetic trees. the computation of large phylogenetic trees with maximum likelihood is computationally intensive. in previous work we have introduced and implemented algorithmic optimizations in paxml. the program shows run time improvements > 25% over parallel fastdnaml yielding exactly the same results. this paper is focusing on computations of large phylogenetic trees (> 100 organisms) with maximum likelihood. we propose a novel, partially randomized algorithm and new parsimony-based rearrangement heuristics, which are implemented in a sequential and parallel program called raxml.we provide experimental results for real biological data containing 101 up to 1000 sequences and simulated data containing 150 to 500 sequences, which show run time improvements of factor 8 up to 31 over paxml yielding equally good trees in terms of likelihood values and rf distance rates at the same time. finally, we compare the performance of the sequential version of raxml with a greater variety of available ml codes such as fastdnaml, axml and mrbayes. raxml is a freely available open source program.
color patterns for pictorial content description. in this paper, we propose a new type of image feature, which consists of patterns of colors and intensities that capture the latent associations among images and primitive features in such a way that the noise and redundancy are minimized. incorporating our feature model into a content-based image retrieval (cbir) system moves the research in image retrieval beyond simple matching of images based on their primitive features and creates a ground for learning image semantics from visual content. a system developed using our proposed feature model, will have the capability of learning associations between not only semantic concepts and images, but also between semantic concepts and patterns. we evaluated the performance of our system based on the retrieval accuracy and on the perceptual similarity order among retrieved images. when compared to standard image retrieval methods, our preliminary results show that, even if the feature space was reduced to a significantly lower dimensional space, the accuracy and perceptual similarity for our system remain the same or better depending on the category of images.
distributed evaluation of generalized path queries. nowadays, we are required to deal with more complex data, prime examples of which are data on the web, xml data, biological data, etc. there are already proposed abstractions to handle these kinds of data, in particular in terms of semistructured data models. a semistructured model conceives a database essentially as a finite directed labeled graph whose nodes represent objects, and whose edges represent relationships between objects. in this paper, we focus on path queries, which are considered the basic querying mechanism for semistructured data. in essence, such queries are used to navigate, or discover paths that conform to specifications captured by regular expressions. in order to make the navigation more useful, we consider generalized path queries, in which the symbols could optionally be weighted by numbers. such numbers can express a variety of information about the data that the query could possibly match or navigate.motivated by the plethora of today's applications utilizing web services and peer-to-peer architectures, we present a distributed algorithm for evaluating generalized path queries. we follow a realistic model with distributed (non-shared) memory and message-passing between processors. an optimal solution to the problem lies in the intersection of ideas related to distributed query evaluation, distributed shortest path computation, and queueing systems.
metrics for evaluating concern separation and composition. this paper discusses an approach to evaluating the separation of concerns for an object-oriented software system. for assessing this separation, the developer is asked to specify the nature of classes through annotations. automatic identification of some structural characteristics (e.g., inheritance, libraries, synchronisation) is used to appraise the composition and intertwining of concerns inside a class.
enforcing agent communication laws by means of a reflective framework. agent coordination contexts (accs) have been proposed as virtual environments where agents live and interact. in this way, as in a human society, interactions may be subjected to conventions and laws depending on their context. this is obtained by a suitable acc that embeds the communication laws relevant to a specific application and checks whether they are fulfilled as interactions take place.context modelling, while representing a communication aspect relevant for all the agents of an application, is a crosscutting concern with respect to the design of the activities of each agent. in this paper, we propose an approach allowing a separate design and implementation of, respectively, behaviour and the interaction aspects constituting the context. once the latter have been formalised in a specification consisting of communication laws, a tool generates the necessary management and checking code from the specification.moreover, we automate the way laws are enforced on agent communication by suitably redirecting any interaction between agents, so as to ensure that the constraints specified by the laws are respected by the interaction, and the actions required by some laws are taken before it actually takes place. redirection is accomplished by means of computational reflection, which transparently changes the meaning of the communication primitives normally used by agents programmers.
collaborative attack modeling. avoidance and discovery of security vulnerabilities in information systems requires awareness of typical risks and a good understanding of vulnerabilities and their exploitations. in this paper we compare common methods of sharing security related knowledge with regard to their ability to support avoidance and discovery of vulnerabilities. we suggest a new method of collaborative attack modeling that is especially suitable for this purpose. this method combines a graph-based attack modeling technique with ideas of a web-based collaboration tool.
decoupling classes with inferred interfaces. using small, context-specific interfaces in variable declarations serves the decoupling of classes and increases a program's flexibility. to minimize its interface, a thorough analysis of the protocol needed from a variable is required. currently available refactorings for the extraction of interfaces leave the programmer alone with the decision which methods to include or, more problematically, which to omit: they let him choose manually from the protocol of an existing type, and only then offer to use the new interface where (if) possible. to aid the programmer in defining a new interface, we have developed a new refactoring that infers it from a variable's declaration and automatically inserts it into the code.
a lightweight java taskspaces framework for scientific computing on computational grids. a prototype taskspaces framework for grid computing of scientific computing problems that require intertask communication is presented. the taskspaces framework is characterized by three major design choices: decentralization provided by an underlying tuple space concept, enhanced direct communication between tasks by means of a communication tuple space distributed over the worker hosts, and object orientation and platform independence realized by implementation in java. grid administration tasks, for example resetting worker nodes, are performed by mobile agent objects. we report on large-scale grid computing experiments for iterative linear algebra applications showing that our prototype framework scales well for scientific computing problems that require neighbor-neighbor intertask communication. it is shown in a computational fluid dynamics simulation using a lattice boltzmann method that the taskspaces framework can be used naturally in interactive collaboration mode. the scalable taskspaces framework runs fully transparently on heterogeneous grids while maintaining a low complexity in terms of installation, maintenance, application programming and grid operation. it thus offers a promising roadway to push scientific grid computing with intertask communication beyond the experimental research setting.
terascale simulation of cumulus convection on asci white. this talk presents three-dimensional numerical simulations of oceanic trade cumulus clouds underlying stratocumulus clouds. they use a case studied in a global energy and water experiment cloud system study (gcss) model intercomparison that is loosely based on observed conditions during the atlantic trade cumulus experiment (atex). this case study is motivated by the importance of this cloud type to global cloud radiative forcing, and their role as a feeder system for deep convection in the topics. this study focuses on the sensitivity of the modeled cloud field to the domain size and the grid spacing. domain widths from 6.5 to 20 kilometers and horizontal grid spacings ranging from 10 to 80 meters, with corresponding vertical grid spacing ranging from 5 to 40 m, are studied, involving domains with over 1000 gridpoints in each horizontal dimension.the combination of large domain size and small grid resolution (up to 2.5 billion grid-cells) provides an unprecedented perspective on this type of convection. this is in contrast to prior les simulations which have often used domains a few kilometers wide. the larger domain size considered here is comparable to the grid resolution of a typical current mesoscale model (a similar resolution will soon be achieved in some global weather forecast models), and can better represent the potential horizontal variability achievable within a mesoscale grid cell. these simulations are made possible by massively parallel computations using 1.3 terabytes of memory and over 1000 processors.
http redirection for replica catalogue lookups in data grids. data distribution and replication in distributed systems require special purpose middleware tools for accessing replicated data. data grids, special forms of systems distributed over wide-area networks, need to handle data management issues like distribution and replication of large amounts of data in the tera- and petabyte scale. replica catalogues are used for cataloguing and locating replicated files in distributed sites all around the globe. we present a novel and administratively scalable approach for distributing a replica catalogue and resolving file location information by using http redirection. http redirection servers managing local file catalogues allow for greater flexibility and local file management autonomy whereas a global replica catalogue provides the necessary mapping of logical files to individual sites. by distributing the catalogues a site can autonomously move files for load balancing within a site without notifying a global replica catalogue. our approach scales well in terms of catalogue administration to a large number of sites and file entries and thus establishes a powerful middleware service. we present the design and implementation of our catalogue redirection servers and report on promising experimental results.
migrating data-intensive web sites into the semantic web. the semantic web is intended to enable machine processability of web content and seems to be a solution for many drawbacks of the current web. it is based on metadata that describe the formal semantics of web contents. we present a novel, integrated and automated approach for migrating data-intensive web applications into the semantic web. this approach can be applied to a broad range of today's business web sites.
model refactorings through rule-based inconsistency resolution. the goal of model-driven engineering is to raise the level of abstraction by shifting the focus to models. as a result, complex software development activities move to the modelling level as well. one such activity is model refactoring, a technique for restructuring the models in order to improve some quality attributes of the models. as a first contribution of this paper, we argue and show that refactoring a model is enabled by inconsistency detection and resolution. inconsistencies in or between models occur since models typically describe a software system from different viewpoints and on different levels of abstraction. a second contribution of this paper is rule-based inconsistency resolution, which enables reuse of different inconsistency resolutions across model refactorings and manages the flow of inconsistency resolution steps automatically.
efficient diffie-hellmann two-party key agreement protocols based on elliptic curves. key agreement protocols are of fundamental importance for ensuring the confidentiality of communications between two (or more) parties over an insecure network. in this paper we review existing two-party protocols whose security rests upon the intractability of diffie-hellmann and discrete logarithm problems over elliptic curve groups. in addition, we propose a new two-party mutual authenticated key agreement protocol and collectively evaluate the security and performance of all the schemes considered. elliptic curve techniques are used to minimise the computational workload on resource-constrained devices and to afford security levels with possibly fewer bits.
an anonymous bonus point system for mobile commerce based on word-of-mouth recommendation. next generation mobile devices will allow users to share and pass information within anonymous groups of people in an ad hoc manner. this will smooth the path for many kinds of new mobile commerce applications. in this paper we present a mobile commerce application that is part of the iclouds research project. it allows the dissemination of digital advertisements among interested mobile users. to create an incentive, an anonymous bonus point system rewards users who help to carry an advertisement from a merchant to a customer. this work includes a formal description of our bonus point model, a thorough discussion of the security goals, their realization and some first results about crypto-operation runtime behavior on a state-of-the-art pda.
lost in just the translation. this paper describes the design and implementation of a scheme for hiding information in translated natural language text, and presents experimental results using the implemented system. unlike the previous work, which required the presence of both the source and the translation, the protocol presented in this paper requires only the translated text for recovering the hidden message. this is a significant improvement, as transmitting the source text was both wasteful of resources and less secure. the security of the system is now improved not only because the source text is no longer available to the adversary, but also because a broader repertoire of defenses (such as mixing human and machine translation) can now be used.
semantic enrichment for improving systems interoperability. the overall goal addressed in this paper is to improve semantic interoperability in heterogeneous systems by means of establishing mappings between relevant domain ontologies. the mappings are discovered based on the technique of semantic enrichment through extension analysis, i.e. using instance information of the ontology to enrich the original ontology and further to calculate similarities between concepts in two ontologies. text categorization is used to automatically assign instance to the concepts in the ontology. information retrieval techniques are used to calculate similarity between concepts. based on the similarities measure, a heuristic method is used to establish mapping assertions for the two ontologies. the method is illustrated using a product catalogue scenario.
contradictions and critical issues during system evolution. in this paper the issue of system evolution is addressed. activity theory and the concept of exapansive cycles are reviewed as theories to explain systemic evolution. contradictions often manifest themselves in deviating human behaviour or in modifications to external artefacts, i.e., they result in a form of systemic behaviour which has often been treated as undesirable. it is shown that contradictions within activity systems are both catalysts and opportunities for system change. in the context of safety-related systems this is put at the centre of investigation in the form of critical issues. an example from an industrial case study is reported, where this approach was applied, and where with this approach affective and communicational problems were identified.
an approach to acquire semantic relationships between terms. this paper focuses on the automatic acquisition of semantic relationships from chinese corpus, motivated by improving the performances of our qa systems named nl-was. linguistic patterns designed for chinese sentences are applied to a collection of texts to extract synonymy relationship, hyponymy relationship, and meronymy relationship. patterns are broken down into unambiguous and ambiguous, and different strategies are adopted to refine the candidates extracted using this two kinds of patterns. compared to other previous works, we apply not only strict unambiguous patterns but also loose unambiguous patterns to extract relationships and proposed efficient approach to refine the outputs of these patterns for the sake of high recall and high precision. the experimental result shows that the proposed method can delete most noisy pairs of terms and improve accuracy and efficiency of nl-was. at the same time, our method is complementary to statistically based approaches that find semantic relationships between terms.
scalable and lock-free concurrent dictionaries. we present an efficient and practical lock-free implementation of a concurrent dictionary that is suitable for both fully concurrent (large multi-processor) systems as well as pre-emptive (multi-process) systems. many algorithms for concurrent dictionaries are based on mutual exclusion. however, mutual exclusion causes blocking which has several drawbacks and degrades the system's overall performance. non-blocking algorithms avoid blocking, and are either lockfree or wait-free. our algorithm is based on the randomized sequential list structure called skiplist, and implements the full set of operations on a dictionary that is suitable for practical settings. in our performance evaluation we compare our algorithm with the most efficient non-blocking implementation of dictionaries known. the experimental results clearly show that our algorithm outperforms the other lockfree algorithm for dictionaries with realistic sizes, both on fully concurrent as well as pre-emptive systems.
type-safe covariance in c++. we present a programming technique for implementing type safe covariance in c++. in a sense, we implement most of bruce's matching approach to the covariance dilemma in c++. the appeal in our approach is that it relies on existing mechanisms, specifically templates, and does not require any modification to the existing language. the practical value of the technique was demonstrated in its successful incorporation in a large software body. we identify the ingredients of a programming language required for applying the technique, and discuss extensions to other languages.
finding an optimum edit script between an xml document and a dtd. finding an optimum edit script between data plays an important role in data retrieval and data transformation. many methods for finding an optimum edit script between two xml documents have been proposed so far, but few studies on finding an optimum edit script between an xml document and a dtd have been made. in this paper, we first show a polynomial-time algorithm that finds an optimum edit script between an xml document (modeled as an ordered tree) and a dtd. we next prove that, if the cost of an operation on a node in a tree may depend on the other nodes, then the corresponding decision problem becomes strongly np-complete.
mobile delivery of news using hierarchical query-biased summaries. this paper presents the results of a study aimed at measuring the usefulness of presenting the results of an information retrieval search on wap mobile phones. the experimentation focuses on presenting automatically-generated summaries of newspaper articles of increasing length on a mobile phone interface and in studying the differences in users' perception of relevance of the retrieved documents. the aim is to study experimentally how users' perception of relevance varies depending on the length of the summary, and in relation to the specific characteristic of the mobile interface that content is presented. experimental results suggest that hierarchical query biased summaries are useful when dealing with small screens and assist users in making correct relevance judgments.
investigating the use of summarisation for interactive xml retrieval. as the number of components in xml documents is much larger than that of 'flat' documents, we believe it is essential to provide users of xml information retrieval systems with overviews of the content of retrieved elements. in this paper, we investigate the use of summarisation in xml retrieval as a means of helping users in their searching process.
implicit environment-based coordination in pervasive computing. by immersing computational systems into the physical world, pervasive computing brings us from traditional desktop computing interactions into a form closer to human interactions, which are characterized by their dependance on the environment. furthermore, acting within the environment can contribute in many cases to a form of implicit interaction in which no explicit communication message is exchanged. however, this way of interacting cannot be achieved without a shared common knowledge with a well defined semantic. this appeals to explore a new approach of interaction mediated by the environment, closer to human interactions, and therefore, more suitable to achieve the intended silent computation of pervasive computing.to address this issue, we present in this paper xcm; a generic coordination model for pervasive computing. xcm is organized around few abstract concepts (entity, environment, social law and port) and is expressed as an ontology. while the abstract concepts of xcm deal with the environmental representation and context-dependency, the ontological representation allows to achieve knowledge sharing and context reasoning.
email classification for automated service handling. we describe the experience and lessons learned from developing a range of electronic services for a specialist engineering company. we are using a custom workflow management system as the base for a range of services which are offered via a multi-modal portal, using a language-based approach to extracting information from html forms, email, and sms. we describe the email classification experiments we have carried out and discuss the development of customer services based on automatic email classification.
an improvement on binary-swap compositing for sort-last parallel rendering. sort-last parallel rendering is a good rendering scheme on distributed memory multiprocessors. this paper presents an improvement on the binary-swap (bs) method, which is an efficient image compositing algorithm for sort-last parallel rendering. our compositing method uses three acceleration techniques, compared to the original bs method. through the use of the three techniques, our method balances the compositing load among processors, exploits more sparsity of the image, and reduces the cost of communication. we also show some experimental results on a pc cluster. the results show that our method completes the image compositing faster than the original bs method, and its speedup to the original increases with the number of processors.
certificates for mobile code security. the problem of protecting mobile code from malicious hosts is an important security issue, for which many solutions have been proposed. we describe a method to adapt an existing technique, execution tracing, to enhance its flexibility in deployment for a large scale mobile agent system. this is achieved through the introduction of a trusted third party, the verification server, which undertakes the verification of execution traces on behalf of the platform launching the agent. the server constructs a certificate that testifies to the capability of a particular host platform to undertake the correct execution of a mobile agent. in this sense, the server assumes a role analogous of a certificate authority (ca) in a pki. we briefly discuss the issues associated with such a framework.
efficient implementation of fingerprint verification for mobile embedded systems using fixed-point arithmetic. fingerprint sensors are getting small enough to be included in mobile devices to enable fingerprint verification be employed as an authentication tool when using the mobile devices for secure transactions. fingerprint verification, however, is a computing intensive technology that requires a lot of floating-point computation. unfortunately, the embedded processors in most mobile devices do not support floating-point hardware. in this paper, we present the implementation of a fingerprint verification process in an embedded system environment based the strongarm processor and the embedded linux operating system. the success of the implementation relies on the use of a fixed-point arithmetic only. the fingerprint verification component, the fixed-point component as well as the technique employed to pair up the two components are described in details. in particular, we estimated the required precisions in the fixed-point representations before conducting experiments. through our results, we further show that not only the fixed-point implementation achieves the goal of significant speed improvement but is almost as reliable as the floating-point counterparts.
an artificial immune system approach to document clustering. it has recently been shown that artificial immune systems (ais) can be successfully used in many machine learning tasks. the ainet, one such ais algorithm exploiting the biologically-inspired features of the immune system, performs well on elementary clustering tasks. this paper proposes the use of the ainet to more complex tasks of document clustering. based on the immune network and affinity maturation principles, the ainet performs an evolutionary process on the raw data, which removes data redundancy and retrieves good clustering results. also, principal component analysis is integrated into this method to reduce the time complexity. the results are compared with some classical document clustering methods - hierachical agglomerative clustering and k-means.
organizing and visualizing software repositories using the growing hierarchical self-organizing map. a software repository, a place where reusable components are stored and searched for, is a key ingredient for instituting and popularizing software reuse. it is vital that a software repository should be well-organized and provide efficient tools for developers to locate reusable components that meet their requirements. the growing hierarchical self-organizing map (ghsom), an unsupervised learning neural network, is a powerful data mining technique for the clustering and visualization of large and complex data sets. the resulting maps, serving as retrieval interfaces, can be beneficial to developers in obtaining better insight into the structure of a software repository and increasing their understanding of the relationships among software components. the ghsom, which is an improvement over the basic self-organizing map (som), can adapt its architecture during its learning process and expose the hierarchical structure that exists in the original data. in this paper, we demonstrate the potential of the ghsom for the organization and visualization of a collection of reusable components stored in a software repository, and compare the results with the ones obtained by using the traditional som.
agent oriented logic programming in jinni 2004. jinni 2004 [1, 2, 3] (available from http://www.binnetcorp.com/jinni) expresses various agent programming constructs in terms of an object oriented logic programming layer implemented on top of a java-based prolog compiler. the architecture provides a high degree of compositionality through the use of a small set of orthogonal programming language constructs.
knowledge-based conversational agents and virtual storytelling. we describe an architecture for building speech-enabled conversational agents, deployed as self-contained web services, with ability to provide inference processing on very large knowledge bases and its application to voice enabled chatbots in a virtual storytelling environment. the architecture integrates inference engines, natural language pattern matching components and story-specific information extraction from rdf/xml files. our web interface is dynamically generated by server side agents supporting multi-modal interface components (speech and animation). prolog refactorings of the wordnet lexical knowledge base, framenet and the open mind common sense knowledge repository are combined with internet meta-search to provide high-quality knowledge sources to our conversational agents. an example of conversational agent with speech capabilities is deployed on the web at http://logic.csci.unt.edu:8080/wordnet_agent/frame.html. the agent is also accessible for live multi-user text-based chat, through a yahoo instant messenger protocol adaptor, from wired or wireless devices, as the jinni_agent yahoo im "handle".
semantic document engineering with wordnet and pagerank. this paper describes natural language processing techniques for document engineering in combination with graph algorithms and statistical methods. google's pagerank and similar fast-converging recursive graph algorithms have provided practical means to statically rank vertices of large graphs like the world wide web. by combining a fast java-based pagerank implementation with a prolog base inferential layer, running on top of an optimized wordnet graph, we describe applications to word sense disambiguation and evaluate their accuracy on standard benchmarks.
an xml-based conversational protocol for web services. soap is used to communicate with web services. it defines the a messaging framework (the envelope), encoding rules and a binding protocol over the http protocol. however soap, as it is, does not deal with conversations. to provide full interoperability, clients need to not only know the correct data formats to pass, but also the conversation level protocol involving those messages for any required web service. this must also include the valid responses, where multiple responses are possible, and the starting and ending states of the conversation.this paper describes an xml-based conversational protocol for web services. each server site publishes details enabling client agents to interact with the server. this involves the publication of protocol specifications representing a finite state machine (fsm). a client agent downloads this specification, validate it for correctness, and then implement the protocol dynamically, as a state machine. this can be viewed as a negotiation of protocols where the client negotiates to implement all requirements of a server.
a digital conference like software tool for pdp programs. digital conference is a software package, which allows people at different locations to exchange information and simultaneously share a running program through a network. it motivates us to create a digital conference like software for parallel and distributed processing programs. the dc-like pdp allows a group to discuss and operate the same pdp model without having all members present at the same computer site. the software has potential to facilitate teaching and research in our institution. this paper presents a complete methodology to develop the dc-like pdp. two solution models using client/server computing are presented. a decision table approach is proposed to facilitate system analysis and design. the table is ultimately encoded as macro rules in source programs. the approach improves program readability, reduces the size of source codes, and enforces consistent maintenance.
cafiss: a complex adaptive framework for immune system simulation. currently most reported immune system simulations in literature involve the use of differential equations, genetic algorithm-based searching or simple cellular automata models. this limits the diversity in results obtained and thus provides fewer avenues for experimenting with behavioral responses of the immune system entities under exogenous stimulations. complex adaptive systems (or cas) by holland provide a way of modeling natural systems with complex aggregation and nonlinear interactions to exhibit emergent behaviours. the immune system, being a powerful and flexible information processing system is particularly suited to being modeled using cas. this paper describes a java-based implementation of a framework for modeling the immune system, particularly human immunodeficiency virus (or hiv) attack, using a cas model. the credibility of the system is established through comparisons against available viral dynamics data. we show that it is feasible to achieve relatively accurate predictions of viral pathogenesis through agent-based discrete event simulations, the first steps towards improved automation of hypothesis verification.
incremental profile learning based on a reinforcement method. this paper presents a profile learning method in an adaptive information filtering. the learning method is an incremental profile learning based on a reinforcement algorithm. the basic idea consists in building, when a document is selected and judged as relevant, the temporary profile which makes it possible to find this document with a strong score, then integrating this profile, using a logarithmic function, in the global profile. the proposed method is compared to two ir learning methods, query expansion method used in okapi and rocchio's algorithm. experiments carried out on trec1-2002 collection showed the effectiveness of the reinforcement method.adaptive filtering, profile learning, reinforcement method
load balancing for the management of service performance in open service markets: a customer-oriented approach. in open service markets customers can choose between several providers offering similar services. to survive in the arising competition, service providers are compelled to satisfy their customers by not only offering services for a reasonable price but additionally deploy them in an efficient way regarding e.g. performance and availability. because in a service provision process application, network, and system aspects are involved, new management concepts are needed. this paper discusses a mechanism for the management of services in distributed environments to reduce the probability of a performance decrease or a connection loss in service provision. to support a customer in choosing a service, a service trader is used as a central component. this trader considers the global state of the distributed system's resources using a load balancer. to fulfil quality characteristics of a mediated service at usage time, management proxies encapsulate services or service groups to observe their performance and availability characteristics. this approach only causes a small involvement of service providers and customers in the selection and management process.
towards a reference model management system for business engineering. the central idea in reference modeling is the reutilization of the business knowledge contained in reference models for the construction of specific models. the orientation on the content of a reference model can increase the efficiency of processes in business engineering projects. despite this, the use of reference models in the field of business engineering has not established itself in practice. this is due to the field of conflict between research and practice, in which reference modeling is at home. there is still a deficit in knowledge about the use and problems inherent in the implementation of reference models despite the array of theoretical concepts. accordingly, in the past years the supply-sided development of reference models predominant in the science world has distanced itself from their demand-sided use in business practice. the article analyses this problem and presents an approach to the management of reference models. the task to be mastered using the proposed approach will be conceptually concretized with a framework and prototypically implemented in the form of a reference model management system.
a framework for the development of information appliances. this paper provides a framework for the design and development of personal information appliances - interactive technologies which aim to assist users in managing personal information in organisational, group and environmental contexts. the emphasis is on integration, both in terms of the development of integrated families of appliances and in terms of way in which appliances provide an integration of the diverse media necessary to support the management of personal information.
software security vulnerability testing in hostile environments. traditional black box software testing can be effective at exposing some classes of software failures. security class failures, however, do not tend to manifest readily using these techniques. the problem is that many security failures occur in stressed environments, which appear in the field, but are often neglected during testing because of the difficulty to simulate these conditions. software can only be considered secure if it behaves securely under all operating environments. hostile environment testing must thus be a part of any overall testing strategy. this paper describes this necessity and a black box approach for creating such environments in order to expose security vulnerabilities.
simplifying transformation of software architecture constraints. the heterogeneity of the architectural constraint languages makes difficult the transformation of constraints throughout the development process. indeed they have significantly different metamodels, which make the definition of mapping rules complex. in this paper, we present an approach that aims at simplifying transformations of architectural constraints. it is based on an architectural constraint language (acl), which includes one core constraint expression language and different profiles. each profile is defined upon a metamodel, which represents the architectural abstractions manipulated at each stage in the development process.
mobile agents for network management: when and when not! in order to fully realise the potential of mobile agent technology to address the needs of the network management domain, it is imperative to establish the conditions where mobile agent-based (ma) nms or snmp-based nms should be employed to achieve the optimal performance in term of overhead traffic generated. this paper presents mathematical models to approximate the overhead traffic created by the ma-based nms and snmp-based nms on the production network, based on the complexity of the management task involved. through our analysis and experimentation, we establish that there is range (of the number of nodes involved) wherein it is advantageous to use mobile agents. furthermore, we demonstrate through our analytical model that this range can be estimated a priori, thereby facilitating a decision on when to deploy mobile agents and when not to.
a coordination model for the semantic web. the semantic web foresees a web of machine-processable knowledge interacted with by clients in an operationalized manner. at web scale, the coordination between clients will be vital for ensuring the success of their interactions. in this paper we consider how a coordination model for the semantic web would look, as a precursor to the design and implementation of semantic web spaces, a middleware platform for real-world semantic web applications.
programming distributed systems with the delegation-based object-oriented language dself. common middleware platforms rely on a class-based object model. however, this model introduces several dependencies that are disadvantageous for distributed systems. the family of class-less delegation-based languages offers an alternative object model with lesser such dependencies. dself is an extension to the delegation-and prototype-based object-oriented language self. it adds distributed objects and transparent remote reference resolution to the language. in consequence, dself facilitates distributed inheritance and instantiation mechanisms. we describe the conception and implementation of dself and give examples where the flexibility of dself can be used with benefit as a middleware concept for programming distributed systems.
axes-based visualizations with radial layouts. in the analysis of multidimensional data sets questions involving detection of extremal events, correlations, patterns and trends play an increasingly important role in a variety of applications. axes-based visualizations like parallel or star coordinates are useful tools for the analysis of multidimensional data sets. in this paper, we present several interactive axes, which can be used to analyze data in an intuitive manner. furthermore, we present two novel radial visual arrangements of such axes - the timewheel and the multicomb. they focus on data sets with one variable of reference. timewheel and multicomb in combination with interactive axes are part of an interactive framework called visaxes, which can be used for enhanced multidimensional data browsing and analysis.
adding wildcards to the java programming language. this paper describes wildcards, a new language construct designed to increase the flexibility of object-oriented type systems with parameterized classes. based on the notion of use-site variance, wildcards provide a type safe abstraction over different instantiations of parameterized classes, by using '?' to denote unspecified type arguments. thus they essentially unify the distinct families of classes often introduced by parametric polymorphism. wildcards are implemented as part of the upcoming addition of generics to the java&trade; programming language, and will thus be deployed world-wide as part of the reference implementation of the java compiler javac available from sun microsystems, inc. by providing a richer type system, wildcards allow for an improved type inference scheme for polymorphic method calls. moreover, by means of a novel notion of wildcard capture, polymorphic methods can be used to give symbolic names to unspecified types, in a manner similar to the "open" construct known from existential types. wildcards show up in numerous places in the java platform apis of the upcoming release, and some of the examples in this paper are taken from these apis.
towards an intelligent mobile travel assistant. travel has many situations where context-aware computing can bring important benefits. in this paper, we describe an approach for integrating context-aware computing to a mobile travel assistant. travel plans, generated using reality [2], are enriched within compact and powerful structures, called user task models. these structures are transferred to a mobile device enabling the support for the traveler during his trip.
reality: a scalable intelligent travel planner. many information systems are used in a problem solving context. examples are travel planning systems, catalogs in electronic commerce, or agenda planning systems. they can be made more useful by integrating problem-solving capabilities into the information systems. this poses the challenge of scalability: when hundreds of users access a server at the same time, it is important to avoid excessive computational load.in this paper, we present an approach, called reality, that allows to significantly extend the reach of electronic commerce in travel. our application addresses in particular the challenge of modeling customers' personal preferences and providing solutions that are tailored to just those preferences. in contrast to existing technology, which allow to optimize only a small and predefined set of preferences, our tool allows a wide variety that can accurately model the preferences of different customers.
replicated declustering for arbitrary queries. declustering have attracted a lot of interest over the couple of years. recently, declustering using replication is proposed to reduce the additive overhead of declustering. most of the work on declustering focuses on spatial range queries. however, in many scenarios including multi-user environments, query shapes can be arbitrary. in this paper, we explore replicated declustering for arbitrary queries. replication reduces the cost of arbitrary queries to manageable levels. first, we investigate theoretically what is possible using replication for arbitrary queries. then, we propose a 2-copy replication strategy that achieves the theoretical limit and therefore is the best possible scheme. using proposed scheme, an arbitrary query containing b buckets requires disk accesses bounded by [&radic;b] this is a significant improvement especially for small queries because using a single copy b buckets require min (b, n) disk accesses in the worst case even for small queries. proposed scheme works for nonuniform data as well as uniform data. finally, we extend the proposed scheme to a partial replication scheme to achieve best performance using limited replication.
performance analysis of mpi-i/o primitives on a pc cluster. cluster computing is an area of growing interest to support parallel and distributed applications. many of these applications are i/o intensive and the limited bandwidth of the i/o subsystem of the cluster is an important bottleneck usually ignored. thus, the performance of parallel i/o primitives is critical for the overall cluster performance. in this work, we try to characterize i/o routines supported by the standard mpi-2 on a pc cluster using the nfs and pvfs file systems in order to detect weak spots in the use of these routines and to predict their impact on the application's performance.
an evaluation of qinna, a component-based qos architecture for embedded systems. component-based software engineering (cbse) is quickly becoming a mainstream approach to software development. at the same time, there is a massive shift from desktop applications to handheld systems: it is especially the case for multimedia applications such as video player, games, etc. moreover, these applications have several quality of service (qos) constraints which must be reached. a key issue of cbse in embedded systems is its ability to integrate qos management. in this paper, we demonstrate the feasibility of integrating qos concepts to cbse. the demonstration is based on qinna, a component-based qos architecture integrating the main qos concepts. moreover, qinna respects separation of concerns and can be easily reused thanks to its identified components.
image domain formalization for content-based image retrieval. this paper proposes a formal representation of the operations required to perform content-based image retrieval (cbir) in large relational databases, using similarity queries. in this paper, we consider similarity as a numerical value obtained comparing a pair of images, which is calculated by a distance (dissimilarity) function. distance functions usually rely on a set of features extracted from each image through a set of image processing algorithms called feature extractors. before extracting features, other image processing algorithms are usually employed to pre-process each image, preparing it for the extractors. usually there are several criteria that can be considered when measuring how much two images are similar. therefore, to compare images in current cbir environments one must define (1) the criteria, (2) the image pre-processing needed before the extractors can be executed, (3) which are those extractors, (4) which features must be considered, (5) and which distance function must be used. all of these definitions must have been set before a comparison can be performed. the complexity of defining how to compare images has lead to the development of systems aiming cbir that allow relatively few options to configure the image comparison operations. moreover, no formal representation of the entire cbir process exists. in this paper we present such a formal environment, where all above-mentioned definitions are represented, entailing the development of flexible and highly-configurable cbir systems. we also report a system developed using this formalism that enables the content-based retrieval of medical images from a hospital database, thus showing results of applying the presented formalism in a real environment.
a transition-based strategy for object-oriented software testing. though time-to-market has become the primary criterion that drives most current software development projects, quality still remains the key concern of critical software development projects, for which the cost of a single bug may involve serious loss or damages. meeting the higher quality level required for such kinds of systems may be achieved only by using sound and rigorous test practices. we present in this paper an integrated platform that uses a formalized version of uml statechart as the basis for rigorous testing of object-oriented programs. the platform adapts and integrates systematic test data generation strategies and associated tools for object-oriented program testing.
a protection scheme for collaborative environments. in collaborative working environments where multiple users use and/or provide multiple services, a more flexible security model is needed. security must be enforced in such environments without affecting usability, scalability, and performance. in this paper, we propose a flexible protection scheme based on the lattice security model that combines information flow and access control mechanisms in order to address privacy and integrity requirements in scalable collaborative environments.
an integrated framework for formal development of open distributed systems. this paper contributes to the discussion on issues related to the formal development of open distributed systems (ods). the deficiencies of traditional formal notations in this setting are highlighted. we argue that there is no single formalism exhibiting all the features required to capture properties of odss. as a solution, we propose an integrated development framework that involves two notations: the unified modeling language (uml) and the prototype verification system (pvs). we discuss the motivation for the choice of these notations, provide an overview of a case tool we have developed to support the proposed framework, and present a case study to demonstrate our approach.
the mt model transformation language. model transformations are recognised as a vital part of model driven development, but current approaches are often simplistic, with few distinguishing features, and frequently lack an implementation. the practical difficulties of implementing an approach inhibit experimentation within the paradigm. in this paper, i present the mt model transformation language which was implemented as a low-cost dsl in the converge programming language. although mt shares several aspects in common with other model transformation languages, an ability to rapidly experiment with the implementation has led mt to contain a number of new features, insights and differences from other approaches.
transparency for polygon based cloud rendering. for the local tv presentation of weather forecast data it is important to have high-quality and fast visualisation of clouds. in this paper we present surface-based transparency computation methods for the high performance visualisation of clouds from data produced by a routine meteorological weather simulation. in contrast to the state-of-the-art volume cloud visualisation we use only hardware-supported polygon-based transparency computation.
plan validation via petri nets in the real-time performers java framework. the real-time performers (rtp) architecture is a framework to design distributed soft real-time systems based on timed plans. timed plans - they define system workflow - contain actions to be executed by distributed components at specified times. an rtp system is controlled by a strategist that may modify plans to adapt system behavior to environment conditions. when a timed plan is changed it may be checked for coherency. this paper presents techniques used in rtp to check timed plans validity through petri nets (pns). these techniques are based on the definition of mappings from rtp topology and plans to pns. once pns are generated, structural and behavioural properties can be calculated and mapped back to the rtp system.
editorial message: special track on organizational engineering. dominated by the behavioral science approach for a long time, information systems research increasingly acknowledges design science as a complementary approach. the systematic design ("engineering") of artifacts is not restricted to information systems components. being the conceptual foundations for information systems requirements, artifacts on the strategic and organizational level have to be engineered as well.
editorial message: special track on organizational engineering (oe). dominated by the behavioral science approach for a long time, information systems research increasingly acknowledges design science as a complementary approach. the systematic design of artifacts is not restricted to information systems components. being the conceptual foundations for information systems requirements, artifacts on the strategic and organizational level have to be engineered as well.
verification of behavioural elements of uml models using b. this paper describes the formal verification of behavioural elements of uml models using b abstract machines. we transform the uml metamodel of behavioural diagrams to b and automatically check proof obligations generated by using the b prover. the correctness of the properties of behavioural elements of uml models is ensured by the well-formedness rules in the uml semantics which are transformed to b as the invariants of abstract machines. we address collaboration diagrams, state-chart diagrams of uml models and study the behavioural elements package (collaboration and state machine) of the uml metamodel as well as well-formedness rules of these packages. we illustrate our approach by a case study.
disclosure risk measures for the sampling disclosure control method. in this paper, we introduce three microdata disclosure risk measures (minimal, maximal and weighted) for sampling disclosure control method. the minimal disclosure risk measure represents the percentage of records that can be correctly identified by an intruder based on prior knowledge of key attribute values. the maximal disclosure risk measure considers the risk associated with probabilistic record linkage for records that are not unique in the masked microdata. the weighted disclosure risk measure allows the data owner to compute the risk of disclosure based on weights associated with different clusters of records. the weights allow a flexible specification of the relative importance of varying cluster sizes in probabilistic record linkage. we show that weighted disclosure risk measure is always between the values of minimal and maximal disclosure risk measures, and moreover for certain values of the weights, the weighted disclosure risk measure is equal to one of the other two measures. using simulated medical data in our experiments, we show that the proposed disclosure risk measures perform as expected in real-life situations.
mining and prediction of temporal navigation patterns for personalized services in e-commerce. with the rapid development of e-commerce, the topic of mining and predicting users' navigation patterns has attracted significant attention due to the wide applications like personalized services in e-commerce. although a number of studies have been done on this topic, few of them take into account the temporal property for web user's navigation patterns. in this paper, we propose a novel method named temporal n-gram (tn-gram) for constructing prediction models of web user navigation by considering the temporality property in web usage evolution. moreover, three kinds of new measures are proposed for evaluating the temporal evolution of navigation patterns under different time periods. through experimental evaluation on both of real-life and simulated datasets, the proposed tn-gram model is shown to outperform other approaches like n-gram modeling in terms of the prediction precision, in particular when the web user's navigating behavior changes with temporal evolution.
an efficient method for mining associated service patterns in mobile web environments. this research presents a new data mining method that can efficiently discover associated service patterns requested by users in mobile web environments. although there exist some studies on data mining in mobile systems in recent years, they were mostly focused on topics like moving path mining or service request log mining and the issue of discovering user's associated service patterns with the locations has not been explored. in particular, this problem becomes more complex when the hierarchical concepts of locations and services are considered. in this work, we propose a new data mining method named two-dimensional multi-level association rules mining, which can efficiently discover the associated service request patterns by taking into account the hierarchical characteristics of the location and service concept. to our best knowledge, this is the first work resolving this research issue. through detailed experimental evaluations under various system conditions, our method was shown to deliver excellent performance in terms of accuracy, completeness, execution efficiency and scalability.
an extendible multidimensional array system for molap. in molap systems, multidimensional arrays are employed to store fact tables dumped from the frontend relational database. on these fact tables, various kinds of statistical computations such as aggregate operations can be performed efficiently by utilizing the fast random accessing capability of arrays. this capability depends on that the size of an employed multidimensional array is fixed in every dimension, so a simple addressing function can be used to access array elements. but, if a new column value emerges after constructing the fact table, the existing fixed size multidimensional array cannot involve the value. in this paper, we provide an extendible multidimensional array system for molap. such an array can extend its size dynamically along an arbitrary dimension without any relocation of existing data. this property enables incremental aggregate operations without relocating any data dumped at the latest time. some problems in making this system work as a basis for molap are stated, and their countermeasures are proposed.
dominance and ranking issues applying interval techniques in pre-negotiations for services. the study looks at the application of preference programming approaches and techniques for decision support during prenegotiations over services. in hierarchical decision analysis models the need for multi-attribute evaluation techniques that may incorporate uncertainties directly in the modeling phase has resulted in the use of the 'interval' approach. with such an approach, preference judgments are presented as ranges including all possible value estimates. this paper reports the results of applying an interval preference programming approach and technique in decision support scenarios for reasoning during pre-negotiations over services. the aim has been to critically evaluate the approach and establish its applicability for ranking multi-dimensional service offers. our experimental results using interval smart, in pre-negotiation decision making scenarios, showed that while the dominance relations among alternatives remained unchanged following the introduction of uncertainty intervals, the rank order and dominance relations of the alternatives may vary as a result of the addition or dropping of new alternatives with inferior values.
som - feature extraction from patient discharge summaries. in each canadian province, hospitals collect information, at discharge, on the hospital stay of each patient. the information is collected in the form of a patient discharge abstract (pda) and sent to the canadian institute for health information. the patient discharge abstract uses the icd-10-ca code standard to outline the assigned diagnoses for the patient's condition and the procedures that were performed. one compulsory piece of information in the patient discharge abstract is the identification of the "most responsible diagnosis" (mrdx) -- that diagnosis considered to be the most significant condition of the patient that caused the greatest length of stay in hospital. this research investigates the potential for automating the process of feature extraction from a narrative patient discharge summary to support the classification of the mrdx for a patient discharge abstract. unsupervised neural networks -- self-organizing maps (som) -- are effective for classification tasks based on noisy input patterns. here a hierarchical architecture of soms is used to identify semantic similarities encoded in the original information and visualize the characteristics of an mrdx.
a framework for automatic generation of web-based data entry applications based on xml. this paper presents a framework for web-based data entry applications. it introduces a method for the conceptional and the navigational design based on a textual specification in the form of an xml-application. this forms the input to a code generation environment allowing for real automated prototyping. the environment produces fully functional skeletons for the web pages. together with the framework classes they can be utilized for testing and for requirements review. they also form the starting point for the work of the presentation design. the main advantage of the framework is a clear separation between the presentation and the business logic. this allows work on each aspect to proceed in parallel along relatively independent but cooperating tracks. the framework has been implemented using java servlets and java server pages.
automated generation of monitors for pattern contracts. while the informal style used to describe design patterns has proven valuable, it is also imprecise. to ensure that patterns are applied correctly, we must also have precise pattern characterizations, and tools for determining whether the appropriate implementation requirements are satisfied. to address this problem, we first present a specification language that captures pattern requirements precisely, as well as the ways in which patterns are specialized for use. second, we present a tool that generates a set of aspect-oriented monitors for a system based on the specifications of the patterns used in its design. the generated aspects are used to monitor the system at runtime to determine whether the appropriate implementation requirements are satisfied.
implications of the topological properties of internet traffic on traffic engineering. in this paper we study the behavior of internet traffic on the as-level topology and discuss its implications on interdomain traffic engineering. we rely on two notable interdomain traffic traces, the first is one month long and the other is one day long. this study shows that interdomain paths are stable for a large majority of the traffic from a routing viewpoint. we show that the aggregation of the traffic occurring on the as-level graph is essentially limited to direct peers, with almost no aggregation occurring at larger as hop distances. furthermore, only part of the as paths of the as-level topology that see a lot of traffic are stable, when considering their presence among the largest as paths on a hourly basis. relying on the largest as paths in traffic over a time window to capture the traffic over the next time interval discloses the important variability of the traffic seen by the largest as paths in traffic. interdomain traffic engineering is hence due to be difficult because of the limited traffic aggregation on the as-level topology and the important topological variability of the traffic for a significant percentage of the total traffic.
fine-grained power management for multithreaded processor cores. we propose a new hardware-based power management technique that is made possible by a multithreaded processor core. a processor-internal scheduler manages frequency and voltage scaling based on the current processor utilization given in percentage of the total performance.
an agreement centric access control mechanism for business to business e-commerce. we argue that matrix-based models are inadequate for regulating business to business (or b2b, for short) e-commerce due to the diversity, complexity and potential large number of commercial agreements that have to be supported. to deal with these issues, we propose in this paper an agreement-centric access control model. the paper introduces the concept of communication agreement (car) as a means for specifying contractual terms, and presents the car enforcement mechanism. we explore the expressive power of the model and show that it can implement regulations which cannot expressed using conventional mechanisms alone. the paper also describes a prototype implementation; the preliminary performance results indicate that the enforcement mechanism is quite affordable, even in its present, experimental stage.
efficient support for enterprise delegation policies. delegation, whereby an entity gives some of its rights to other entities, is considered the cornerstone of decentralized authorization, and many access control frameworks proposed recently make delegation its central tenet. in these frameworks, delegation is commonly viewed as a transfer between two autonomous agents---the grantor and the grantee. but the situation can be considerably more complex, and more challenging, in the case the grantor belongs to an organization. generally, employees are not autonomous agents, but their actions are subject to the regulations of their enterprise. in particular, if an employee transfers his rights to another agent, this transfer is subject to the enterprise delegation policies.in delegation frameworks, authorizing a request requires finding a valid chain of credentials that delegates the authority from the source (the local policy of the entity that serves the request) to the requester. unfortunately, chain discovery is a computationally expensive and time consuming task. it was shown that, in the general case, chain discovery is undecidable, and in more restrictive cases, it is polynomial in the number of credentials available to the server. verifying compliance with the terms of a delegation policy adds a considerable overhead to request authorization.this paper presents a framework that considerably reduces the time required to authorize a request. in this framework, a delegation chain is condensed into a single credential, called chained delegation certificate (cdc). a cdc attests that the owner has a certain right, and serves as proof that every link in the chain complies with the policy governing delegation of the right in question. when cdcs are used for authorization, a server does not need to verify compliance with the delegation policy, nor does it need to perform the chain discovery step, and therefore requests are served considerably faster.
class-dependent assignment in cluster-based servers. a cluster-based server consists of a front-end dispatcher and several back-end servers. the dispatcher receives incoming requests, and then assigns them to back-end servers for processing. our goal is to devise an assignment policy that has good response time performance, and is practical to implement in that the amount of information used by the dispatcher is relatively small, so that the attendant computation and communication overheads are low. in contrast to extant assignment policies that apply the same assignment policy to all incoming jobs, our approach calls for the dispatcher to classify incoming jobs as long or short, and then use class-dependent assignment policies. specifically, we propose a policy, called cda (class dependent assignment), where short jobs are assigned in round-robin manner as soon as they arrive, while long jobs are deferred and assigned only when a back-end server becomes idle. furthermore, when processing a long job, a back-end server is not assigned any other jobs.our approach is motivated by empirical evidence suggesting that the sizes of files traveling on the internet follow power-law distributions, where long jobs constituting a small fraction of all incoming jobs actually account for a large fraction of the overall load. to gauge the performance of the proposed policy, we exercised it on empirical data traces measured at internet sites serving the 1998 world cup. since the assignment of long jobs incurs computational overhead as well as extra communication overhead, we studied the performance of cda as function of the fraction of jobs classified as long. our study shows that classification of even a small fraction of jobs as long can have a profound impact on overall response time performance. more speciafically, our experimental results show that if less than 3% of the jobs are classified as long, then cda outperforms traditional policies, such as round-robin, by two orders of magnitude. from an implementation viewpoint, these results support our contention that cda-based assignment is a practical policy combining low overhead and greatly improved performance.
eronto: a tool for extracting ontologies from extended e/r diagrams. realization of semantic web requires structuring of web data using domain ontologies. most data intensive websites are powered by relational databases whose design process involves developing conceptual model using e/r or extended e/r diagrams. this paper discusses the implementation details of a tool that builds domain ontologies in owl (ontology web language) from extended e/r diagrams. ontology development being a knowledge intensive task, our tool would be helpful in reducing the developmental efforts by automating the process. we bring out the differences and the similarities between the expressive capabilities of the two conceptual modeling methods, namely owl and extended e/r diagrams.
preventing race condition attacks on file-systems. race condition attacks occur when a process performs a sequence of operations on a file, under the assumption that the operations are being executed "atomically". this can be exploited by a malicious process which changes the characteristics of that file between two successive operations on it by a victim process, thus, inducing the victim process to operate on a modified or diflerent file. in this paper we present a practical approach to detect and prevent such race condition attacks. we monitor file operations and enforce policies which prevent the exploitation of the temporal window between any consecutive file operations by a process. our approach does not rely on knowledge of previously known attacks. in addition, our experiments on linux demonstrated that attacks can be detected with false alarms of less than 3% with performance overheads less than 8% of the processes execution time.
an architecture for biological information extraction and representation. technological advances in biomedical research are generating a plethora of heterogeneous data at a high rate. there is a critical need for extraction, integration and management tools for information discovery and synthesis from these heterogeneous data. in this paper, we present a general architecture, called alfa, for information extraction and representation from diverse biological data. the alfa architecture consists of: (i) a networked, hierarchical object model for representing information from heterogeneous data sources in a standardized, structured format; and (ii) a suite of integrated, interactive software tools for information extraction and representation from diverse biological data sources. as part of our research efforts to explore this space, we have currently prototyped the alfa object model and a set of interactive software tools for searching, filtering, and extracting information from scientific text. in particular, we describe bioferret, a meta-search tool for searching and filtering relevant information from the web, and alfa text viewer, an interactive tool for user-guided extraction, disambiguation, and representation of information from scientific text. we further demonstrate the potential of our tools in integrating the extracted information with experimental data and diagrammatic biological models via the common underlying alfa representation.
an anomaly-driven reverse proxy for web applications. careless development of web-based applications results in vulnerable code being deployed and made available to the whole internet, creating easily-exploitable entry points for the compromise of entire networks. to ameliorate this situation, we propose an approach that composes a web-based anomaly detection system with a reverse http proxy. the approach is based on the assumption that a web site's content can be split into security sensitive and non-sensitive parts, which are distributed to different servers. the anomaly score of a web request is then used to route suspicious requests to copies of the web site that do not hold sensitive content. by doing this, it is possible to serve anomalous but benign requests that do not require access to sensitive information, sensibly reducing the impact of false positives. we developed a prototype of our approach and evaluated its applicability with respect to several existing web-based applications, showing that our approach is both feasible and effective.
experimenting with a real-size man-hill to optimize pedagogical paths. this paper describes experiments aimed at adapting ant colony optimization (aco) techniques to an e-learning environment, thanks to the fact that the available on-line material can be organized in a graph by means of hyperlinks between educational topics. the structure of this graph is to be optimized in order to facilitate the learning process for students.aco is based on an ant-hill metaphor. in this case, however, the agents that move on the graph are students who unconsciously leave pheromones in the environment depending on their success or failure. in the paper, the whole process is therefore referred to as a "man-hill."compared to the [13, 14] papers that were providing guidelines for this problem, real-size tests have been performed, showing that man-hills behave differently from ant-hills. the notion of pheromone erosion (rather than evaporation) is introduced.
an authorization model for temporal xml documents. we here describe an access control model for securing temporal xml document. our approach is based on a temporal data model allowing to represent both transactional and valid time dimensions of xml documents. the authorization model allows the specification of temporal conditions on the two considered time dimensions and on the validity of the authorizations.
authenticated multicast immune to denial-of-service attack. authentication of multicast streams has attracted a lot of attention in the last few years. however, two important issues, namely multicast denial-of-service and access control, have been ignored in previous proposals. in this paper, we propose two internet protocol multicast authentication schemes by making use of the multicast tree as an essential authentication mechanism. our schemes are efficient and immune to multicast denial-of-service attack. they allow the receivers to immediately authenticate the packets regardless of the packet loss characteristics of the underlying network.
schemes for sr-tree packing. modern database applications like geographic information systems, multimedia databases, and digital libraries dealing with huge volumes of high dimensional data, make use of multidimensional index structures. among them, sr-tree has been shown to outperform the r-tree and its variants and the ss-tree. for static datasets, packed index structures provide better retrieval performance. this paper presents schemes for sr-tree packing based on different pre-processing techniques. the results show that these schemes consistently outperform packed r-tree and conventional sr-tree structures in terms of storage space and query performance.
intelligent file management in ubiquitous environments. the paradigm of ubiquitous computing seeks to build a computing environment that responds to user context. an ideal file system for the ubiquitous environment is one that can successfully recognize the present context and automate file management. the intelligence in the ubiquitous file management is achieved by applying a heuristics based clustering approach to the system. the applied heuristics are those that are used on file attributes by users to manually manage files in a traditional file system. file attributes can be used to relate files to the most appropriate work-context and also draw inter-file relationships. we discuss methods to harness the given file information from the file-system to form a context-relation wrapper over disparate files. this enables management of files as context related working sets rather than as individual files. a survey was conducted among regular computer users and the compiled results supported our context based file clustering approach. the experiments also showed promising results that confirm our model on the file heuristics, thus finding semantic relations between those files.
nextgen extreme porting: structured by automation. "maintenance is really the normal state of an xp project" - beck. thus porting is a natural candidate for extreme programming and we present a novel tool-based xp methodology for porting c/c++ programs. the structure provided by our tooling is designed for scalability, to enable xp on large projects porting enterprise-scale codebases. overall planning and iteration planning of the methodology are assisted by a novel, first-of-its-kind migration orchestrator tool. automated test, debugging, and audit function are provided as unified support by our refactoring tool framework. we focus on the orchestrator tool and offer preliminary benchmarks with encouraging results.
a framework and analysis for cooperative search using uav swarms. we design and analyze the performance of cooperative search strategies for unmanned aerial vehicles (uavs) searching for moving, possibly evading, targets in a hazardous environment. rather than engaging in independent sensing missions, the sensing agents (uavs with sensors) "work together" by arranging themselves into a flight configuration that optimizes their integrated sensing capability. if a uav is shot down by enemy fire, the team adapts by reconfiguring its topology to optimally continue the mission with the surviving assets. we presetn a cooperative search methodology that integrates the multiple agents into an advantageous formation that distinctively enhances the sensing and detection operations of the system while minimizing the transmission of excessive control information for adaptation of the team's topology. after analyzing our strategy to determine the performance tradeoff between search time and number of uavs employed, we present an algorithm that selects the minimum number of uavs to deploy in order to meet a targeted search time within probabilistic guarantees.
a spatiotemporal uncertainty model of degree 1.5 for continuously changing data objects. to support emerging database applications that deal with continuously changing (or moving) data objects (ccdo), one requires an efficient data management system that can store, update, and retrieve large sets of ccdos. although actual ccdos can continuously change, computer systems cannot deal with continuously occurring infinitesimal changes. thus, in the data management system, each object's spatiotemporal values are always associated with a certain degree of uncertainty at every point in time, and the queries are mostly processed over estimates characterizing the uncertainty. unfortunately, there is a marked lack of formal explication of the uncertainty of multidimensional ccdos in space-time. this paper presents our logical and mathematical bases for capturing, representing, and processing ccdos of varying dimensionality.
a mesh update requirement for hierarchical adaptive meshes in mesh-based motion tracking. this paper presents a mesh update requirement for hierarchical adaptive meshes in mesh-based motion tracking. the requirement states that since hierarchical adaptive meshes are constructed according to the video contents of a predicted frame, constructing a different mesh topology for each predicted frame is necessary in order to most accurately describe the video contents in a predicted frame. it has been statistically verified in the analysis section of this paper that if the requirement is not satisfied, the prediction quality would be lowered. the analysis is performed on different qcif benchmark sequences.
from buddyspace to cititag: large-scale symbolic presence for community building and spontaneous play. in this paper we discuss the conceptual framework and principles that guide our work in the design of large-scale informal environments for collaborative work, learning and play, aiming to foster social bonds and to provide an exciting testbed for emergent social behaviours. we present three different applications we have developed: buddyspace, an instant messaging environment for community building, bumpercars, an online presence-based multiplayer game and cititag, an experimental wireless mixed reality game.
outlier elimination in construction of software metric models. software metric models are models relating various software metrics of software projects. such models' purpose is to predict some of these metrics for certain future projects given the other metrics for those projects. the construction of software metric models derives such relationships and is usually based on data samples of concerned software metrics for past software projects. often, in such a data sample, there are inevitably a few very extreme projects which have relationships among their metrics deviating substantially from those among the metrics for the remaining "mainstream" bulk of projects in the data sample. such "outlier" projects exert considerable undue influence on the derivation of the said relationships during model construction in that the relationships so derived cannot candidly reflect the true "mainstream" relationships. the direct consequence is degraded prediction accuracy of the constructed models for future projects. to overcome this problem, we proposed a methodology to identify and thus eliminate such outliers prior to model construction. our methodology makes use of the least of median squares (lms) regression to uncover such outliers and is applicable irrespective of any subsequent model construction approaches. we also did a case study to apply our methodology, and the results prove our methodology being able to improve the prediction accuracy of most models experimented with in the study. thus, our methodology is recommended for any further software metric model construction. this paper documents such a methodology and the successful case study.
an effective nn search protocol in wireless broadcast environments. data broadcasting provides an effective way to disseminate information in a wireless mobile environment. how to provide the service of k nearest neighbors (knn) search using data broadcasting is studied in this paper. given a data set d and a query point p, the knn search finds k data points in d closest to p. by assuming that the data is indexed by an r-tree, we propose an efficient protocol for knn search on the broadcast r-tree in terms of the tuning time which is the amount of time spent listening to the broadcast, latency which is time elapsed between issuing and termination of the query, and memory usage on the clients. we last validate the proposed protocol by experiments and present our findings.
repweb: replicated web with referential integrity. replication of web content, through mirroring of web sites or browsing off-line content, is one of the most used techniques to increase content availability, reduce network bandwidth usage and minimize browsing delays in the world-wide-web.the world-wide-web does not support referential integrity, i.e., broken links do exist. this has been considered, for some years now, one of the most serious problems of the web. this is true in various fields, e.g.: i) if a user pays for some service in the form of web pages, he requires such pages to be reachable all the time, and ii) archived web resources, either scientific, legal or historic, that are still referenced, need to be preserved and remain available.current approaches to the broken-link problem are not able to preserve referential integrity on the web and, simultaneously, support replication and minimize storage waste due to memory leaks. some of them also impose specific authoring and management systems. thus, the limitations of current systems reside in three issues: transparency, completeness and safety.we propose a system, repweb, comprised of an application to access and manage replicated web content and an implementation of an acyclic distributed garbage collection algorithm for wide-area replicated memory, that satisfies all these requirements. it supports replication, enforces referential integrity on the web and minimizes storage waste.
issues of pedagogy and design in e-learning systems. the purpose of this paper is to discuss some pedagogical issues surrounding e-learning systems. we have been involved in distance education and e-learning for the last 15 years and developed education and training delivered to a wide range of audiences. based on our experiences, results from evaluation studies we conducted, and the literature in the field we provide a constructive critique of lms and discuss some guidelines for future developments of e-learning systems. the emphasis will be on the needs of the online teacher and how these needs can best be supported by the design of appropriate technologies.
improving image retrieval effectiveness in query-by-example environment. query-by-example is the most popular query model for today's image retrieval systems. a typical query image contains not only relevant objects (e.g., eiffel tower), but also irrelevant image areas (e.g., the background). the latter, referred to as noise in this paper, has limited the effectiveness of existing image retrieval systems. we present here a similarity model for noise-free queries (nfqs), and investigate indexing techniques for this new environment. our query model is more expressive than the standard query-by-example. the user can draw a contour around a number of objects to specify spatial (relative distance) and scaling (relative size) constraints among them, or use separate contours to disassociate these objects. our experimental results confirm that traditional approaches, such as local color histogram and correlogram, suffer from noisy queries. in contrast, our method can leverage nfqs to offer significantly better performance. this is achieved using only a fraction of the storage overhead required by the compared techniques.
comparing semantic frameworks for coordination: on the conformance issue for coordination media. a fundamental issue in the engineering of coordination models is to design coordination abstractions that are correct with respect to the specification of the coordination model they implement. the traditional semantic framework for coordination is focused on describing the admissible evolutions over time of a coordinated system, and is particularly suitable for specifying the laws of a coordination model. on the other hand, formally describing run-time aspects of an implementation requires a different framework, capturing as fundamental idea the interactive behavior of a coordination medium.in this paper, these two frameworks are compared by tackling a crucial issue of coordination models, that is, the conformance of an implementation with respect to a specification. in particular, a definition of conformance is introduced that is shown to be compatible with the standard notion of implementation by horizontal refinement promoted in the context of process algebras.
implementing type-based constructive negation. this paper presents an implementation of a constructive negation method. the constructive negation method makes use of type dependencies between arguments of a predicate to rewrite negative goals in a logic program. the constructive negation method is first reformulated as a derivation rule. then an algorithm for efficiently implementing the derivation rule is presented and its complexity is analyzed.
issues in parallelizing multiobjective evolutionary algorithms for real world applications. the concepts of efficiency and effectiveness must be addressed in conducting research into using a evolutionary algorithm (ea) for optimization problems. the increased use of evolutionary approaches for real-world applications, containing multiple objectives and high dimensionality, has led to the design and generation of a number of multiobjective evolutionary algorithms (moea). when analyzing these algorithms, the issues of effectiveness and efficiency are extremely important and typically drive the urge to parallelize these algorithms. the parallelization of moeas is a relatively new concept, with few researchers contributing work in this area. this parallelization process is not a simple task and involves the analysis of various parallel models and the parameters associated with these models. this paper presents a thorough analysis of the various parallel moea models, the issues associated with these models and recommendations for using these models in moeas. in particular, these parallelization concepts are applied to the multiobjective messy genetic algorithm ii.
red with dynamic thresholds for improved fairness. we investigate the fair bandwidth sharing among responsive and unresponsive traffic flows. when these flows compete for the same output link in a router, unresponsive flows tend to occupy more than their fair share of the link capacity. we propose a new active queue management algorithm named random early detection with dynamic thresholds (red-dt) that dynamically adapts queue parameters to achieve a more fair distribution of the link capacity.
a recursive connectionist approach for predicting disulfide connectivity in proteins. we are interested in the prediction of disulfide bridges in proteins, a structural feature that conveys important information about the protein conformation and that can therefore help towards the solution of the folding problem. we assume here that the disulfide bonding state of cysteines is known and we focus on the subsequent problem of disulfide bridges pairings assignment. in this paper, disulfide connectivity is modeled by undirected graphs. a graphspace search algorithm is employed to explore alternative disulfide bridges patterns and prediction consists of selecting the 'best' graph in the search space. the core of the proposed method is a recursive neural network architecture trained to score candidate graphs. we report experiments on previously published data showing that our algorithm outperforms the known alternative methods for most proteins. furthermore, we assess the generalization capabilities testing the model on previously unpublished data.
a java based xml browser for consumer devices. next generation consumer devices will all have an internet connection. thus, one vision is that the future multimedia services will be browser based. extensible markup language (xml) is the most likely markup language. in this paper, we introduce a java based xml browser called x-smiles. it is intended for consumer devices and supports multimedia services. the main advantage of the x-smiles browser is that it supports most of the xml related specifications. different xml based languages can be mixed freely in applications. in addition, the x-smiles has special user interfaces for different kinds of devices (e.g., digital television, personal digital assistants, and mobile phones). these user interfaces can be used as so called virtual prototypes of the real devices. the x-smiles browser is available as open source at http://www.x-smiles.org.
motion estimation performance of the tm3270 processor. motion estimation constitutes a significant computational part of video standards such as mpeg2, mpeg4, and h264/avc. this paper evaluates the performance of a motion estimation algorithm on the tm3270, a low-cost media-processor. in order to improve performance, the tm3270 processor provides architectural enhancements over previous trimedia processors. we quantify the speedup of the proposed new operations to motion estimation performance. we show that the new operations incorporated in the tm3270 improve performance by a factor between 3 and 4. furthermore, we quantify the speedup of data prefetching. we show that prefetching can improve performance up to 30%. by applying all tm3270 architectural enhancements, we show that standard resolution motion estimation can be performed in less than 5% of the available processor performance.
interactive computation and visualization of fetch using standard computer graphics hardware. fetch is a measure of unobstructed wind exposure over open water. depending on prevailing conditions, it may necessitate considering wind exposure from many directions. applications in geography may require visualization of fetch over an entire body of water. impossible by hand and computationally demanding even on a computer, this paper describes a new method which accelerates the process to interactive speeds. the speedup is obtained by reformulating the problem to one of graphics rendering and making use of commonly available computer graphics hardware through opengl, a widely support graphics standard.
tucupi: a flexible workflow system based on overridable constraints. this work presents the idea and a prototype of workflow systems whose definition is based on constraints. the flexibility is reached through the less rigid definition of workflow definitions - the workflow is defined as a set of pre and post conditions of activities, which are selected dynamically as the process instance unfolds. the workflow system besides dispatching activities that have all their preconditions fulfilled to be executed, also helps users to decide which activity to chose through what if scenarios. the system also includes an access control model which not only represents which users have the authority to chose and execute the activities but also the authority to override the constraints. in particular, overriding constraints is itself an activity and thus may have pre and post conditions defined in other constraints. the paper present tucupi, a prototype of such constraint based wfms.
protected transmission of biometric user authentication data for oncard-matching. since fingerprint data are no secrets but of public nature, the verification data transmitted to a smartcard for oncard-matching need protection by appropriate means in order to assure data origin in the biometric sensor and to prevent bypassing the sensor. for this purpose, the verification data to be transferred to the user smartcard is protected with a cryptographic checksum that is calculated within a separate security module controlled by a tamper resistant card terminal with integrated biometric sensor.
surface reconstruction using shadow profilometry. digital image analysis has rich potential in application to post-disaster forensic investigations. the underlying concept is to reconstruct the exterior surfaces of object fragments that failed under load or were torn apart because of explosive forces. the surface reconstruction technique must be sufficiently accurate to capture detailed characteristics of small samples for identification and classification of the object under examination. this paper presents an inexpensive technique for constructing a digital image of a three dimensional surface of very small objects which preserves the minor details via two dimensional slices produced using shadow profilometry.
cleaning microarray expression data using markov random fields based on profile similarity. this paper proposes a method for cleaning the noise found in microarray expression data sets. while other methods either concentrate on the image processing phase, or apply normalization techniques to the resulting microarray raw expression values, we introduce a method based on markov random fields for the data set. the cleaning process is guided by genes with similar expression profiles. as a result, data cleaning is conducted using biological similarity of genes.
the loop fallacy and serialization in tracing intrusion connections through stepping stones. network based intruders seldom attack directly from their own hosts, but rather stage their attacks through intermediate "stepping stones" to conceal their identity and origin. to identify attackers behind stepping stones, it is necessary to be able to trace through the stepping stones and construct the correct intrusion connection chain.a complete solution to the problem of tracing stepping stones consists of two complementary parts. first, the set of correlated connections that belongs to the same intrusion connection chain has to be identified; second, those correlated connections need to be serialized in order to construct the accurate and complete intrusion connection chain. existing approaches to the tracing problem of intrusion connections through stepping stones have focused on identifying the set of correlated connections that belong to the same connection chain and have overlooked the serialization of those correlated connections.in this paper, we use set theoretic approach to analyze the theoretical limits of the correlation-only approach and demonstrate the gap between the perfect correlation-only approach and perfect solution to the tracing problem of stepping stones. in particular, we identify the serialization problem and the loop fallacy in tracing connections through stepping stones. we formally demonstrate that even with perfect correlation solution, which gives us all and only those connections that belong to the same connection chain, it is still not adequate to serialize the correlated connections in order to construct the complete intrusion path deterministically. we further show that correlated connections, even with loops, could be serialized deterministically without synchronized clock. we present an efficient intrusion path construction method based on adjacent correlated connection pairs.
modeling and analyzing applications with domain-specific languages by reflective rewriting: a case study. in this paper, we propose to model and analyze applications with domain-specific languages by reflection. we argue that both tasks can be significantly simplified by using a reflective modeling language. to make our arguments, we model and analyze a model checker in the reflective language maude. the simplicity of our methodology suggests our methodology is useful for such applications.
a density based approach to classification. this paper presents a novel method for classification, which is density based and makes use of the models built by the lattice machine (lm) [5, 7]. density is a natural concept to use in clustering and the lm is a relatively new method for supervised learning developed in recent years. the lm approximates data resulting in, as a model of data, a set of hyper tuples that are equilabelled, supported and maximal. the method presented in this paper uses the lm model of data to classify new data with a view to maximising the density of the model. in order for the method to have wide applicability a measure of density is introduced for hyper tuples and relations.experiments were carried out with both public and proprietary data. experimental results show that our method outperforms the classification method in the lm literature and it is comparable to the c5.0 classification algorithm. it is also shown that our method works quite well in an application-stock market data mining.
hyperrelations in version space. a version space is a set of all hypotheses consistent with a given set of training examples, delimited by the specific boundary and the general boundary. in existing studies [4, 5, 3] a hypothesis is a conjunction of attribute-value pairs, which is shown to have limited expressive power [6].in this paper we investigate version space in a more expressive hypothesis space, where a hypothesis is a hyperrelation, which is in effect a disjunction of conjunctions of disjunctions of attribute-value pairs. we propose to use an inductive bias, e-set, which turns our attention to equilabelled, supported, and maximal hypertuples. we characterise version space in such a hypothesis space under this bias and show the relationship between the specific boundary and general boundary with respect to unequivocal data, a special subset of the data space. we present experimental results on some public datasets.
guiding motif discovery by iterative pattern refinement. in this paper, we demonstrate that the performance of a motif discovery algorithm can be significantly improved by embedding it into a novel framework that effectively guides the motif discovery process. the framework is also general enough to allow any statistical motif discovery algorithm to be used. motivation for this research comes from the fact that the statistical significance of patterns depends on the background probability which is largely determined by input sequences. our framework guides motif discovery by inputting subsequences to an existing motif discovery algorithm, rather than using entire sequences. subsequences are determined by motifs discovered using existing motif discovery and search algorithms. then this technique is iteratively applied until convergence. a starting set of patterns is discovered by a simple, but effective pattern set generation algorithm. our framework was implemented using meme and mast and tested with 108 prosite patterns. the result demonstrates that our framework significantly improves the performance of meme.
rapidly prototyping implementation infrastructure of domain specific languages: a semantics-based approach. domain specific languages (dsls) are high level languages designed for solving problems in a particular domain, and have been suggested as means for developing reliable software systems. however, designing of a domain specific language is a difficult task. the design of a domain specific language will evolve as it is used more and more and experienced is gained by its designers. being able to rapidly develop the implementation infrastructure (interpreter, compiler, debugger, profiler, etc.) of a domain specific language is thus of utmost importance so that as the language evolves, the implementation infrastructure can keep pace. in this paper we present a framework for automatically generating interpreters, compilers, debuggers, and profilers from semantic specification of a domain specific language. we illustrate our approach via the scr language, a language used by the us defense department for developing control systems.
aodv compatible routing with extensive use of cache information in ad-hoc networks. recently, there has been an increasing interest in ad-hoc networks, which are dynamically constructed by collections of mobile hosts without using any existing network infrastructure or centralized administration. each mobile host plays a role of a router and relays packets for multihop network communications. a recent trend in ad-hoc network routing is the reactive on-demand philosophy where routes are established only when required. most of the protocols in this category, however, show a long latency in route discovery since the cached routing information will be invalidated even if it is still effective. in this paper, we propose a scheme which is compatible to the existing ad-hoc on-demand distance vector (aodv) protocol and prevents the cached routing information from becoming invalidated without using any extra control message. we also verify the effectiveness of the newly proposed scheme by simulation experiments.
tree-based clustering for gene expression data. data clustering methods have been proven to be a successful data mining technique in analysis of gene expression data and many other types of data. however, some concerns and challenges still remain, e.g., in gene expression clustering. in this paper, we propose an efficient clustering method using attractor trees. the combination of the density-based approach and the similarity-based approach considers clusters with diverse shapes, densities, and sizes. experiments on gene expression datasets demonstrate that our approach is efficient and scalable with competitive accuracy.
distributed collaborative filtering for peer-to-peer file sharing systems. collaborative filtering requires a centralized rating database. however, within a peer-to-peer network such a centralized database is not readily available. in this paper, we propose a fully distributed collaborative filtering method that is self-organizing and operates in a distributed way. similarity ranks between multimedia files (items) are calculated by log-based user profiles and are stored locally at these items in so-called buddy tables. this intuitively creates a semantic overlay to organize multimedia files. based on this semantic overlay and the items that a user has downloaded previously (indicating the profile of the user), recommendations can be performed and the recommended items can be easily located. we have tested our distributed collaborative filtering approach and compared it to centralized collaborative filtering, showing that it has similar performance. it is therefore a promising technique to facilitate filtering for relevant multimedia data in p2p networks.
variable selection and ranking for analyzing automobile traffic accident data. variable ranking and feature selection are important concepts in data mining and machine learning. this paper introduces a new variable ranking technique named sum max gain ratio (smgr). the new technique is evaluated within the domain of traffic accident data and against a more generalized dataset. in certain cases, smgr is empirically shown to provide similar results to established approaches with significantly better runtime performance.
escape analysis for synchronization removal. in this paper we introduce our escape analysis framework for java, which is a kind of flow-insensitive, inter-procedural, and context-sensitive data flow analysis. and we present an efficient static intra-procedural algorithm for inferring the set of types that can occur at runtime for each object. with intra-procedural type information, virtual method resolution, callee-stub inline, exception analysis, and thread allocation site analysis are implemented. virtual method resolution and callee-stub inline effectively reduce the call graph and scc (strongly connected components). in exception analysis, we present a more precise analysis algorithm, especially in the inter-procedural exception in scc.our escape analysis can be applied to the whole java program and java libraries to identify unnecessary synchronization in java and remove them. we have developed an implementation on intel's open runtime platform. for our benchmarks, 7.3% to 99% (with an average of 54%) of synchronization operations are eliminated.
an approach for identifying attribute correspondences in multilingual schemas. in this paper, we focus on a new problem in database integration---attribute correspondence identification in multilingual schemas, and give a rule-based method for the problem. attribute correspondence identification in multilingual schemas involves the study of integrating schemas, designed in various languages, and returns the correspondences among those schemas. we first analyze the problem through two schemas of a large financial corporate of china. based on the relationships of the attribute names of the schemas, a method of name-based attribute correspondence identification is proposed. and we give a computer-aided system to deal with the problem according to the method. the components and identifying procedure of the method have been discussed in detail in the paper. we have implemented a prototype, and the tool shows its effectiveness in application.
optimizing relational store for e-catalog queries: a data mining approach. a frequent use of database management systems in electronic commerce is to provide electronic product catalogs (e-catalogs) that allow users to search for products of interest via constraints on attributes. an intuitively straightforward representation of e-catalogs is to use one table for the whole e-catalog as it is conceptually easy to maintain and query. however, for any e-commerce business with a reasonably large number of products and product types, its e-catalog usually involves a large number of attributes due to the great variety of the products, and at the same time, contains a large number of null values due to the fact that each product only has values under a relatively small number of attributes. because of these properties, the above intuitive method does not work well in current relational database systems. techniques have been proposed in the literature to deal with this problem, namely binary and vertical schemas. however, these techniques fail to take advantage of inherent properties of realistic e-catalogs to provide superior performance. this paper proposes a novel decomposition method for e-catalogs based on association rule discovery, a data mining technique. the method discovers groups of attributes that frequently appear together, i.e., are frequently used together to describe products, and generates schemas that contain these groups. this paper also reports experimental results showing the efficiency of the method.
reordering b-tree files. in this investigation, we address a reordering technique that improves sequential processing to b-tree files dramatically. we show conventional reorganization is not fully helpful, and propose reordering of blocks reflecting logical order. first we obtain all the data in a logical order, and then we put them into pre-order. here we show some experimental results that says how this technique works well.
comparing table views for small devices. users expect access to web data from a wide range of devices, both wired and wireless. many users switch back and forth between devices, including laptops and personal data assistants (pdas), and expect to be able to continue working with that data. the goal of this research is to inform the design of applications that support the user by providing reasonably seamless migration of web data among internet-compatible devices with minimal loss of effectiveness and efficiency. earlier studies concentrated on the dynamic transformation of text content, lists, and forms embedded in web pages for access on a range of devices from desktop to handheld. this study focuses on the transformation of large tables onto small mobile devices. in this paper we report on the results of two user studies that examine effectiveness and efficiency of three basic models for the display of tables, originally intended for use on larger screen, on pda size screens for both simple and complex tasks.
combining analysis and synthesis in a model of a biological cell. we have previously described a top-down analytical approach, cell assembly kit (cellak), based on the object-oriented (oo) paradigm and the unified modeling language (uml) and real-time object-oriented methodology (room) formalisms, for developing models and simulations of cells and other biological entities. in this approach, models consist of a hierarchy of containers (ex: cytosol), active objects with behavior (ex: enzymes, lipid bilayers, transport proteins), and passive small molecules (ex: glucose, pyruvate). in this paper we describe the substrate catalyst link (scl) bottom-up synthesis approach [17], the concept of autopoiesis on which it is based, and what we have learned in trying to integrate this approach into cellak. the enhanced cellak architecture consists of a network of active objects (polymers), each of which has behavior that causally depends partly on its own fine-grained structure (monomers), where this structure is constantly changing through interaction with other active objects.
identification of fundamental building blocks in protein sequences using statistical association measures. protein sequence data is abundant, yet derivation of structural features from sequence alone is generally restricted to prediction of domain architecture, secondary structure elements and motifs. precise feature boundaries cannot be determined reliably, and it is unknown to what extent these features constitute fundamental building blocks of protein sequences, a question with particular relevance to protein folding. here we propose a statistical approach using mutual information, a measure of association, to predict feature boundaries. in this approach, proteins are viewed as strings of adjacent, non-overlapping features, where each feature is a subsequence of the protein, and the union of the features is the entire protein. mutual information values are measured between nearby amino acids along sequences, and low values are indicators for feature boundaries. these boundaries are then predicted using a flexible partitioning algorithm. the algorithms presented in this paper were tested on the gpcr protein family and subfamilies. a comparison with segment boundaries implied indirectly from secondary structure prediction and expert knowledge demonstrates that the algorithm can be used to statistically predict feature positions in protein sequences generically, without assumptions on the feature type to be detected. access to the data used and algorithms presented in this paper are available at flan.blm.cs.cmu.edu.
policy-driven reflective enforcement of security policies. practical experience has shown that separating security enforcement code from functional code using separation of concerns techniques such as behavioural reflection leads to improvements in code undestandability and maintainability. however, using these techniques at requires providing a consistent and declarative way to specify policies. we have developed a prototype tool that allows the use of ponder policies that are enforced by the kava metaobject protocol. this prototype translates high-level policies into configuration files used to enforce the policies upon java applications.
improving collaborative filtering with trust-based metrics. despite its success, similarity-based collaborative filtering suffers from some significant limitations, such as scalability and sparsity. this paper introduces trust to the domain of collaborative filtering to overcome these limitations. compared with the similarity-based cf, introduction of trust does improve the performance of cf in terms of coverage, prediction accuracy, and robustness in the presence of attacks. experimental results based on a real dataset are illustrated as evidences to support our claim.
profiling and mapping of parallel workloads on network processors. network processors are embedded system-on-a-chip multiprocessors that are optimized to perform simple packet processing tasks at data rates of several gigabits per second. to meet the performance demands of increasing link speeds and more complex network applications, network processors are implemented with several dozens of processor cores and execute multiple packet processing applications in parallel. the complexity of such systems makes it increasingly difficult for application developers to map applications to the various system resources and achieve optimal performance. we propose an automated profiling and mapping methodology for these highly parallel, embedded systems that starts out with a simple uniprocessor implementation of the networking application. an architecture independent representation of the runtime behavior of the application is used to map and schedule different processing steps to the underlying hardware. an analytic performance model is used in the process to estimate system performance and to find an near-optimal solution through iteration.
pvin: a scalable and flexible system for visualizing pedigree databases. we describe the design and implementation of pvin (pedigree visualization and navigation), a scalable and flexible software system that enables the visualization, analysis, and printing of hierarchical relations typically stored in relational databases. although the concept of visualizing and printing pedigree databases is not new, we have developed a novel implementation based on modern approaches for several important reasons: (1) our university's center of hereditary diseases has accumulated very large amounts of hereditary information from various populations for ongoing research projects, and has difficulty managing and effectively printing the associated pedigree trees with legacy fortran software; (2) the size of some of these databases (over 40,000 entries covering seven generations) is too large for existing commercial pedigree software to handle; and (3) our researchers and support staff need more effective ways to perform visual analysis tasks, such as the comparison of multiple pedigrees and the cross-referencing of individuals that appear in multiple families (through re-marriage.) the pvin system addresses these fundamental problems while also providing a number of additional features and functions, including: context-free drawing routines that enable rendering onto screen and printer contexts interchangeably; a generic framework that allows the system to interface with multiple databases and database servers; a multiple view user interface that provides side-by-side comparisons and "focus+context" rendering; and advanced node searching and cross-referencing capabilities.
using operational distributions to judge testing progress. although most software test data adequacy criteria proposed as a way to assess the progress of testing rely on the coverage of the code, the coverage of the specification, or the percentage of the input domain that has been exercised, none of these are really good indicators of how thoroughly the software has been tested. instead we propose that the assessment be based on the percentage of the probability mass associated with the test suite. this requires that data be collected to determine how the software is used in practice over a period of time, so that this can be properly assessed. in that way a project is able to accurately determine how testing is progressing.
neutralizing windows-based malicious mobile code. mobile code---executable programs that get copied from computer-to-computer via e-mail, web browsers, etc.---is a popular way to stage malicious attacks against users. the windows operating system is often the target of such attacks, in part because of its ubiquity and in part because of the vast functionality it provides. some of this functionality, like executable e-mail attachments and scripting, provides opportunity for mobile code to cause significant damage to a host system. one obvious solution is to disable such features in windows. however, many users find such features a convenient and productive way to conduct their business. thus, techniques that can protect against mobile code without sacrificing functionality are needed.but even disabling functionality such as scripting will not provide complete security; it only catches the most sophomoric exploits. all operating systems, including windows, are vulnerable to malicious use at their lowest level of operation: executing compiled code. mobile programs, just like local programs, can access operating system components in ways that damage a users' data or render their computer useless. these programs can be written in system-level languages such as c and assembly, which are capable of compiling os components directly into their binaries and writing directly to interrupt vectors. disabling such functionality will mean an operating system that simply doesn't work.this paper investigates techniques to protect windows-based systems from malicious mobile code while minimizing functionality loss. our solution involves writing a layer of protective code that is able to detect mobile code running on a system and then monitors its behavior. behaviors deemed benign are allowed to execute; behaviors deemed malicious are either shutdown, quarantined or logged (so that restoration procedures can be constructed). we describe new techniques for identifying. monitoring and neutralizing malicious mobile code. we demonstrate the techniques by testing our "vaccine" against a number of the most notorious windows viruses and worms. further, we demonstrate how our solution maintains functionality while minimizing false positives during execution of benign programs.
value-oriented design of service coordination processes: correctness and trust. the rapid growth of service coordination languages creates a need for methodological support for coordination design. coordination design differs from workflow design because a coordination process connects different businesses that can each make design decisions independently from the others, and no business is interested in supporting the business processes of others. in multi-business cooperative design, design decisions are only supported by all businesses if they contribute to the profitability of each participating business. so in order to make coordination design decisions supported by all participating businesses, requirements for a coordination process should be derived from the business model that makes the coordination profitable for each participating business. we claim that this business model is essentially a model of intended value exchanges. we model the intended value exchanges of a business model as e3 -value value models and coordination processes as uml activity diagrams. the contribution of the paper is then to propose and discuss a criterion according to which a service coordination process must be correct with respect to a value exchange model. this correctness is necessary to gain business support for the process. finally, we discuss methodological consequences of this approach for service coordination process design.
the "look and feel" of an ebook: considerations in interface design. this paper asks, "how should an electronic textbook look and feel?" the results of the visual book and the web book experiments, both of which address this question, are discussed, and the eboni (electronic book on-screen interface) project's evaluations involving students and lecturers in uk higher education are outlined. it is proposed that, in terms of the on-screen appearance of information, certain aspects of the paper book metaphor should be retained and that text should be made more "scannable" to suit the electronic medium. in terms of the look and feel of the physical object, issues such as display technology, size, weight and ergonomics should be taken into account. these considerations will form the basis of eboni's best practice guidelines for designing electronic textbooks.
evaluating the usability of portable electronic books. this paper outlines the methodology and results of the eboni project's evaluation of portable electronic books, in which staff from uk academia were provided with a selection of book readers and asked to report back on their experiences. a set of issues of importance to users of electronic books is uncovered, and compared with concerns arising from other experiments in the same field. finally, recommendations for successful ebook design are made.
a study into the usability of e-encyclopaedias. this paper describes a usability study performed on three different e-encyclopaedias, all of which were available on the web, contained similar content and targeted similar audiences, but differed in their styles of presentation. the purpose of the study was to discover the effectiveness of each design in terms of overall usability and subjective satisfaction, to extract general guidelines for the successful design of e-encyclopaedias, and to examine the requirements of different user groups.
information requirements engineering for data warehouse systems. information requirements analysis for data warehouse systems differs significantly from requirements analysis for conventional information systems. based on interviews with project managers and information systems managers, requirements for a methodological support of information requirements analysis for data warehouse systems are derived. existing approaches are reviewed with regard to these requirements. using the method engineering approach, a comprehensive methodology that supports the entire process of determining information requirements of data warehouse users, matching information requirements with actual information supply, evaluating and homogenizing resulting information requirements, establishing priorities for unsatisfied information requirements, and formally specifying the results as a basis for subsequent phases of the data warehouse development (sub)project has been proposed. the most important sources for methodology components were four in-depth case studies of information requirements analysis practices observed in data warehousing development projects of large organizations. in this paper, these case studies are presented and the resulting consolidated methodology is summarized. while an application of the proposed methodology in its entirety is still outstanding, its components have been successfully applied in actual data warehouse development projects.
reference modeling and method construction: a design science perspective. due to its importance for the development and the implementation of standard software applications in organizations, reference modeling has gained intensive coverage by is researchers as well as by practitioners. method engineering is covered less, in particular by is practice. there is evidence that the basic construction and application principles for reference models and methods are similar. the goal of this paper is to analyze reuse potentials. as a conceptual basis, the state-of-the-art of reference modeling and reference model application as well as the state-of-the-art of method engineering and method application are presented. reuse potentials are systematically analyzed, and future research directions in this area are outlined.
a framework for geometric constraint satisfaction problem. this article presents a metalanguage called gcml which allows the description of geometric constraint problems. in the spirit of algebraic specifications, it constitutes a framework to accompany a geometric problem from its expression to its solution. its originality is to provide a problem with its framework called geometric universe, a tuple (syntax, semantic) which allows to get rid of ambiguities and limitations concerning description which is then freed from any software restriction. moreover, distinction between syntax and semantic allows pre and post treatments in order to generate tools while adopting different semantic points of view in the following fields: modeling, visualization, resolution and documentation. pragmatically, this metalanguage is based upon xml which is a language of terminology description, and allows to embed other terminologies to express different semantics.
jelly view: a technology for arbitrarily advanced queries within rdbms. data processing capabilities of relational database management systems are limited. in particular, the following two categories of problems are hard to solve: traversal of structurally complex data structures (such as graphs, trees, terms, lists etc.) and search for admissible solutions under specified constraints (finding specific subsets of a given set, generation of structural solutions satisfying specific constraints etc.) this paper covers a part of the jelly view technology, which provides a new, practical methodology for knowledge decomposition, storage, and retrieval within rdbms. it also briefly presents a prototype system implementing the jelly view technology called redares. the technology tackles the above problems by introducing rule-based processing (intensional knowledge processing) to the database systems. to express intensional knowledge the prolog language syntax is used in the form of clauses. the clauses of prolog code are decomposed and stored in the rdbms founding reusable components of logic program. the database becomes a complete source of knowledge, both extensional and intensional. furthermore, to process intensional knowledge, an inference engine is coupled with the rdbms. the results of the inference process are visible as regular views, accessible through sql. the state of the view is generated dynamically, on-demand by the inference engine. from the end-user point of view the processing capability becomes unlimited (arbitrarily complex queries can be constructed), while the most external queries are expressed with standard sql. the relational database is extended with intensional knowledge, and coupled with an inference engine, which provides functionality analogous to that of the deductive databases.
good/fast/cheap: contexts, relationships and professional responsibility during software development. engineering requires tradeoffs [23]. when engineering computer applications, software engineers should consider the costs and benefits to humans as an integral part of the software development process. in this paper we focus on reliability, a central aspect of software quality, and the influence of relationships and various software development contexts on the software developer.
classification of ad hoc multi-lateral collaborations based on local workflow models. establishing multi-lateral collaborations based on local workflows without having a global workflow is complicated, because the set of requirements used for the searching and matchmaking of trading partners is underspecified. the issue is to consider inter-dependencies of trading partners within a local workflow on the one hand side and between services on the other hand side. within this paper, we suggest to develop an abstract model for establishing multi-lateral collaborations and propose a classification schema based on this model. the classification later on can be used to focus on particular aspects of the problem space and to develop solutions for different clusters within the problem domain.
facial emotion recognition by adaptive processing of tree structures. we present an emotion recognition system based on a probabilistic approach to adaptive processing of facial emotion tree structures (fets). fets are made up of localized gabor features related to the facial components according to the facial action coding system. the proposed model is an extension of the probabilistic based recursive neural network model applying in face recognition by cho and wong [1]. the robustness of the model in an emotion recognition system is evaluated by testing with known and unknown subjects with different emotions. the experiment results shows that the proposed model significantly improved the recognition rate in terms of generalization.
efficient management of xml contents over wireless environment by xstream. in this paper we investigated the issues pertaining to streaming generalized xml documents over the wireless environment. we highlight the disadvantages of employing existing approach to fragment and manage the transfer of xml contents across a wireless environment. in particular, existing approach of fragmenting data takes no consideration of the structure and semantics of the xml data. also, using the connection-oriented transport protocol, such as tcp, will result in lower throughput due to the head-of-line blocking and inefficient error control mechanisms operating in an error-prone environment. we proposed xstream to focus on the flexible management of xml data operating over the wireless environment. xstream leverages the structural characteristics of xml documents to fragment xml contents into autonomous units called xstream data unit (xdu). also, it incrementally sends fragments over a wireless link and performs look-ahead processing of the document. this facilitates the efficient use of scarce bandwidth. in this paper we describe the xstream framework and the techniques involved. a complete deployment and setup of xstream is discussed and the empirical performances are evaluated to verify the benefits of streaming xml documents using xstream.
source code-based software risk assessing. the more complex a software system is, the more likely it is that programmers will make mistakes that introduce faults which can lead to execution failures. a risk in a software system can be viewed as a potential problem, and a problem is a risk that has manifested. in order to reduce the risk of software operations, code which has the potential to cause problems has to be identified so that necessary actions (e.g., performing a more thorough testing on such code) can be taken to prevent any such problems from occurring. consequently, this can help programmers detect faults in the software before it is deployed and reduce the overall maintenance code. in this paper, we propose a static and a dynamic risk model using metrics collected based on the source code; more specifically, metrics which are either related to the static structure of the source code or the dynamic test coverage of the code. the computation of the risk of code is automated at different granularity levels ranging from basic blocks to functions. an experiment to demonstrate the feasibility of using our method is reported. high risk code, so identified by our method, can be integrated with information collected from other software quality assurance practices to further ensure the safe operation of software applications.
applying statistical methodology to optimize and simplify software metric models with missing data. during the construction of a software metric model, the decision on whether a particular predictor metric should be included is most likely based on an intuitive or experience based assumption that the predictor metric has an impact on the target metric with a statistical significance. however, a model constructed based on such an assumption may contain redundant predictor metric(s) and/or unnecessary predictor metric complexity. this is because the assumption made before the model construction is not verified after the model is constructed. to resolve the first problem (i.e., possible redundant predictor metric(s)), we propose a statistical hypothesis testing methodology to verify "retrospectively" the statistical significance of the impact of each predictor metric on the target metric. if the variation of a predictor metric does not correlate enough with the variation of the target metric, the predictor metric should be deleted from the model. for the second problem (i.e., unnecessary predictor metric complexity), we use "goodness-of-fit" to determine whether certain categories of a categorical predictor metric should be combined together. in addition, missing data often appear in the data sample used for constructing the model. we use a modified k-nearest neighbors (k-nn) imputation method to deal with this problem. a study using data from the "repository data disk - release 6" is reported. the results indicate that our methodology can be useful in trimming redundant predictor metrics and identifying unnecessary categories initially assumed for a categorical predictor metric in the model.
separation of concerns in compiler development using aspect-orientation. a major difficulty in compiler development regards the proper modularization of concerns among the various compiler phases. the traditional object-oriented development paradigm has difficulty in providing an optimal solution towards modularizing the analysis phases of compiler development, because implementation of each phase often crosscuts the class hierarchy defined by language syntax constructs. object-oriented design patterns, such as the visitor pattern, also cannot solve the crosscutting problem adequately because an object is not a natural representation of a collection of operations. this paper demonstrates the benefits of applying aspect-oriented programming languages (e.g., aspectj) and principles to compiler design and implementation. the experience result shows that the various language constructs in aspectj (e.g., inter-type declaration, pointcut-advice model, static aspect members and aspect inheritance) fit well with the various computation needs of compiler development, which results in a compiler implementation with improved modularity and better separation of concerns. the ideas utilized in this paper can also be generalized to other software systems with a tree-like structure.
vcr indexing for fast event matching for highly-overlapping range predicates. fast matching of events against a large number of range predicates is important for many applications. we present a novel vcr indexing scheme for highly-overlapping 2d range predicates. vcr stands for virtual construct rectangle. each predicate is decomposed into one or more vcrs, which are then considered to be activated. the predicate id is then stored in the id lists associated with these activated vcrs. event matching is conceptually simple. for each event point, the search result is stored in the id lists associated with the activated vcrs that cover the event point. however, it is computationally nontrivial to identify the activated covering vcrs. we define a covering vcr set for each event point and present an algorithm for fast event matching. simulations are conducted to study the performance of vcr indexing.
towards value disclosure analysis in modeling general databases. the issue of confidentiality and privacy in general databases has become increasingly prominent in recent years. a key element in preserving privacy and confidentiality of sensitive data is the ability to evaluate the extent of all potential disclosure for such data. this is one major challenge for all existing perturbation or transformation based approaches as they conduct disclosure analysis on the perturbed or transformed data, which is too large, considering many organizational databases typically contain a huge amount of data with a large number of categorical and numerical attributes. instead of conducting disclosure analysis on perturbed or transformed data, our approach is to build an approximate statistical model first and analyze various potential disclosure in terms of parameters of the model built. as the model learned is the only means to generate data for release, all confidential information which snoopers can derive is contained in those parameters.
weaving a debugging aspect into domain-specific language grammars. a common trend in programming language specification is to generate various tools (e.g., compiler, editor, profiler, and debugger) from a grammar. in such a generative approach, it is desirable to have the definition of a programming language be modularized according to specific concerns specified in the grammar. however, it is often the case that the corresponding properties of the generated tools are scattered and tangled across the language specification. in this paper, separation of concerns within a programming language specification is demonstrated by considering debugging support within a domain-specific language (dsl). the paper first describes the use of aspectj to weave the debugging semantics into the code created by a parser generator. the paper outlines several situations when the use of aspectj is infeasible at separating language specification properties. to accommodate such situations, a second approach is presented that weaves the debugging support directly into a grammar specification using a program transformation engine. a case study for a simple dsl is presented to highlight the benefits of weaving across language specifications defined by grammars.
efficient initialization and crash recovery for log-based file systems over flash memory. while flash memory has been widely adopted for storage systems for various embedded systems, issues on performance and reliability have started receiving growing attention in recent years. how to provide efficient roll back and quick mounting for flash-memory file systems has become important research topics in recent years, in addition to the work on effective garbage collection and superb run-time performance. such an observation motivates our work on the investigation of efficient initialization and crash recovery of flash-memory file systems based on log structures. a methodology is proposed for the acceleration of mounting and crash recovery for log-based file systems. a system prototype based on a well-known flash-memory file system yaffs was implemented with performance evaluation. the experimental results show that the proposed methodology can reduce the mounting time significantly, regardless of whether the file system is properly unmounted.
a two-dimensional separation of concerns for compiler construction. during language evolution, compiler construction is usually performed along two dimensions: defining new abstract syntax tree (ast) classes, or adding new operations. in order to facilitate such changes, two software design patterns (i.e., the inheritance pattern and the visitor pattern) are widely used to help modularize the language constructs. however, as each design pattern is only suitable for one dimension of extension, neither of these two patterns can independently fulfill the evolution needs during the compiler construction process. in this paper, we analyze two dimensions of concerns in compiler construction and develop a paradigm allowing compiler evolution across these two dimensions using both object-orientation and aspect-orientation. moreover, this approach provides an ability to perform pattern transformation based on pluggable aspects. a simple implementation of an expression language and its possible extension is demonstrated using java and aspectj.
on bounding energy consumption in dynamic, embedded real-time systems. we present a cpu scheduling algorithm, called the <u>e</u>nergy-<u>b</u>ounded <u>u</u>tility <u>a</u>ccrual algorithm (or ebua). ebua is a polynomial-time algorithm that satisfies bounds on system-level energy consumption and activities' accrued timeliness utility. we analytically establish several timeliness properties of ebua. our simulation experiments using amd's (dvs-enabled) k6 processor model confirm the algorithm's effectiveness and superiority.
a dynamic data/currency protocol for mobile database design and reconfiguration. this paper presents flexible protocols for dynamic database design and reconfiguration, enabling mobile database to be designed in such a way that data location, replication and even use semantics can be changed dynamically. in particular, a dual data/currency hoarding and synchronization protocol, a metadata protocol and currency redistribution protocol are proposed. metadata records the changing characteristics of replicas and currencies are dynamically redistributed to fit the target. primaries may be diluted, concentrated and transferred in the system. traditional distributed database is included as home of data. an ad-hoc database may check out its desired data/currency and check them back in when they are no longer accessed by the mobile users. we demonstrate that the flexibility of this approach can significantly improve commit performance under dynamic access and mobility behavior.
indexing continuously changing data with mean-variance tree. constantly evolving data arise in various mobile applications such as location-based services and sensor networks. the problem of indexing the data for efficient query processing is of increasing importance. due to the constant changing nature of the data, traditional indexes suffer from a high update overhead which leads to poor performance. in this paper, we propose a novel index structure, the mvtree, which is built based on the mean and variance of the data instead of the actual data values that are in constant flux. since the mean and variance are relatively stable features compared to the actual values, the mvtree significantly reduces the index update cost. the distribution interval and probability distribution function of the data are not required to be known a priori. the mean and variance for each data item can be dynamically adjusted to match the observed fluctuation of the data. experiments show that compared to traditional index schemes, the mvtree substantially improves index update performance while maintaining satisfactory query performance.
on unit task linear-nonlinear two-cluster scheduling problem. in parallel and distributed processing, tasks are ordinarily clustered and assigned to different processors or machines before they are scheduled. the assignment of tasks to processors is called clustering. the ordering of tasks for execution is called cluster scheduling. the set of tasks is typically modelled as a directed acyclic task graph (dag). as a result of the clustering process, the set of tasks in each cluster either forms a total ordering, called linear, or it doesn't, called nonlinear, with respect to the dag. it has been shown that two-cluster scheduling with one cluster being linear and the other nonlinear is strongly np-hard. in this paper, we develop an exact algorithm to compute an optimal schedule for the above problem in o(e + &alpha;(n)n) time when tasks are restricted to unit tasks, where n is the number of nodes, e is the number of edges, and &alpha;(n) is similar to inverse ack-erman function. we also show that when both clusters are nonlinear, even when tasks are restricted to unit-tasks and task graphs are restricted to those having no path of length more than three, the problem remains np-complete in the strong sense.
enhancing program verifications by restricting object types. object types are abstract specifications of object behaviors; object behaviors are abstractly indicated by object component interdependencies; and program verifications are based on object behaviors. in conventional object type systems, object component interdependencies are not taken into account. as a result, distinct behaviors of objects are confused, which can lead to fundamental typing/subtyping loopholes and program verification troubles. in this paper, we first identify a program verification problem which is caused by the loose conventional object typing/subtyping which is in turn caused by the overlooking of object component interdependencies. then, as a new object typing scheme, we introduce object type graphs (otg) in which object component interdependencies are integrated into object types. finally, we show how the verification problem can be resolved under otg.
computing edit distances between an xml document and a schema and its application in document classification. in this paper, we present an algorithm to find a sequence of top-down edit operations with minimum cost that transforms an xml document such that it conforms to a schema. it is shown that the algorithm runs in o(p x log p x n), where p is the size of the schema(grammar) and n is the size of the xml document (tree). we have also shown that edit distance with restricted top-down edit operations can be computed the same way.we will also show how to use the edit distances in document classification. experimental studies have shown that our methods are effective in structure-oriented classification for both real and synthesized data sets.
mining concept associations for knowledge discovery in large textual databases. in this paper, we describe a new approach for mining concept associations from large text collections. the concepts are short sequences of words that occur frequently together across the text collections. it is these concepts that convey most of the meaning in any language. our goal is to extract interesting associations among concepts that co-occur within the text collections. interesting association between the concepts is mined using association rule mining algorithm. finally we construct directed graph from current rules. the experimental result shows that our approach can efficiently find interesting concept associations in large text collections.
further extensions of fipa contract net protocol: threshold plus doa. being easily understood and implemented for resource allocation or task assignment, fipa contract net protocol (cnp) has been widely applied to kinds of multi-agent system (mas). basing on a typical extension to the original cnp, which was named as contract net with confirmation protocol (cncp), this paper made two further extensions to cnp by the ideas of threshold and degree of availability (doa). cncp enabled the agents to make proposals or accept offers in a continuous time, but it also increased the risk of getting sub-optimal deal or nothing for individual agent. our research is just aiming at relieving this risk. the idea of threshold comes from the fact that: no matter how much proposals one agent sent out, it will get only one task to do at last. by setting a proper threshold, we can save many unnecessary computational costs in making or evaluating proposals. the concept of doa is derived from the principle of maximum expected-utility (meu). with this concept, one agent will evaluate proposals not only by the required costs, it also takes the doa of a participant as an important factor in choosing its best deal, so initiators can act in a more rational way. we also presented an under-consideration idea "deadline", which might become another feasible way to increase system effectiveness and efficiency.
semantic-based information retrieval of biomedical data. in this paper, we propose to improve the effectiveness of biomedical information retrieval via a medical thesaurus. we analyzed the deficiencies of the existing medical thesauri and reconstructed a new thesaurus, called medthes, which follows the ansi/niso z39.19-2003 standard. medthes also endows the users with fine-grained control of information retrieval by providing functions to calculate the semantic similarity between words. we demonstrate the usage of medthes through an existing data search engine.
a uniform meta-model for modeling integrated cooperation. process modeling is a central topic of research on computer supported cooperative work (cscw). uniformity and flexibility in work representation and process enactment are two primary goals. we develop a novel meta-model capable of modeling uniformly a wide range of cooperation scenarios. we will discuss the key elements of the model and its computerized formalism, the cova programming language, and its runtime system. we will describe in this language several typical cooperation scenarios to illustrate how integrated cooperation and other cooperation scenarios can be described and supported with our model.
the t-detectors maturation algorithm based on match range model. negative selection algorithm is used to generate detector for change detection, anomaly detection. but it can not be adapted to the change of self data because the match threshold must be set at first. in this paper, inspired from the maturation of t-cells, a match range model is proposed. base on the model, a novel algorithm composed of positive selection and negative selection is proposed to generate t-detectors and the match threshold is not needed. genetic algorithm is used to evolve the detectors with self-adapted match range. the proposed algorithm is tested by simulation experiment for anomaly detection and compared with the negative selection algorithm. the results show that the proposed algorithm is more effective than the negative selection algorithm and match range is self-adapted.
mediation security specification and enforcement for heterogeneous databases. information sharing among heterogeneous databases requires increasing attention and poses a pressing need. successful protection of information by an effective access control mechanism is a basic requirement for interoperation among heterogeneous data sources. however, most existing work on access control focuses on access control model and security related information, little effort is devoted to exploring access control on the semantic-related heterogeneous databases. no current work resolves the security challenges faced by heterogeneous databases, i.e., context-aware authorization, semantic heterogeneity of databases and policy specification at different points. this paper proposes a mediation security system that secures the information sharing among heterogeneous databases with the promise to meet the above requirements. the proposed system models the flexible access control requirements specific to mediation security while providing uniform access for heterogeneous data sources.
mediation framework modeling and verification by sam. the architecture-level design of mediation systems requires rigorous modeling and analysis techniques to assure the correctness the behaviors of the architecture. the software architecture model (sam) is a formal systematic software architecture specification and analysis methodology that is able to define and analyze different system aspects using different formalisms to improve understandability and reduce complexity. this paper proposes an adaptive mediation framework that provides an easily extensible, decentralized environment for sharing data from heterogeneous databases. we demonstrate how to apply sam to specify the mediation architecture and analyze the temporal properties of the proposed architecture.
image texture classification using datagrams and characteristic views. this paper addresses the problem of image texture classification. a novel texture feature called "characteristic view", which is directly extracted from a kernel corresponding to each texture class, was developed. the k-views template method was used to classify the texture pixels based on these features. the characteristic view concept is based on the assumption that an image taken from the nature scenes, a specific texture class in this image will frequently reveal the repetitions of some certain patterns of features. different "views" can be obtained as features from different spatial locations. the datagram concept is developed in this paper. experimental results using datagrams are provided.
implementation of a dynamic adjustment mechanism with efficient replica selection in data grid environments. the co-allocation architecture was developed in order to enable parallel downloading of datasets from multiple servers. several co-allocation strategies have been coupled and used to exploit rate differences among various client-server links and to address dynamic rate fluctuations by dividing files into multiple blocks of equal sizes. however, a major obstacle, the idle time of faster servers having to wait for the slowest server to deliver the final block, makes it important to reduce differences in finishing time among replica servers. in this paper, we propose a dynamic co-allocation scheme, namely recursive-adjustment co-allocation scheme, to improve the performance of data transfer in data grids. our approach reduces the idle time spent waiting for the slowest server and decreases data transfer completion time. we also provide an effective scheme for reducing the cost of reassembling data blocks.
an approach to secure information flow on object oriented role-based access control model. in this paper, we conclude that confinement problem may occur on the object oriented role-based access control model (orbac). in order to solve the problem, a technique called information flow analysis is proposed. moreover, based on the information flow technique and the principle of mandatory access control principles, a message filtering algorithm and a role set assignment method are developed to deal with the confinement problem on orbac.
nfp-based nesting algorithm for irregular shapes. this paper presents a new 2d irregular-shaped nesting algorithm, which is based on a new nfp (no fit polygon) algorithm and a new piece placement policy named as lowest-gravity-center policy. compared with existing algorithms, the proposed nfp algorithm has lower time-complexity and higher robustness due to the introduction of trace lines. the proposed lowest-gravity-center policy places a piece to the position which has the lowest gravity center based on nfp. compared with the bottom-left piece placement policy, the proposed lowest-gravity-center policy results in a relatively flat boundary for the pieces. the proposed nesting algorithm can deal with pieces with arbitrary rotation and holes. it achieved competitive layout solutions both in nesting pattern height and area-utilization ratio.
on search in peer-to-peer file sharing systems. we consider the problem of information retrieval in a peer-to-peer file sharing system. we assume that peers are unreliable, metadata are sparse, and queries are short. in light of this, the question becomes whether there exists a combination of metadata management and ranking techniques that can consistently improve query results. we try several alternatives, and, through analysis and simulation, show a combination that generally yields the best results.
adaptive page-level incremental checkpointing based on expected recovery time. incremental checkpointing, which is intended to minimize checkpointing overhead, saves only the modified pages of a process. this means that in incremental checkpointing, the time consumed for checkpointing varies according to the amount of modified pages. thus, an efficient interval of checkpointing have to be determined on run-time of a process. in this paper, we present an efficient and adaptive page-level incremental checkpointing facility that is based on the interval determination mechanism for minimizing the expected execution time. our simulation results show that the expected execution time was significantly reduced compared with existing periodic page-level incremental checkpointing.
a fast start-up technique for flash memory based computing systems. flash memory based embedded computing systems are becoming increasingly prevalent. these systems typically have to provide an instant start-up time. however, we observe that mounting a file system for flash memory takes 1 to 25 seconds mainly depending on the flash capacity. since the flash chip capacity is doubled in every year, this mounting time will soon become the most dominant reason of the delay of system start-up time. therefore, in this paper, we present instant mounting techniques for flash file systems by storing the in-memory file system metadata to flash memory when unmounting the file system and reloading the stored metadata quickly when mounting the file system. these metadata snapshot techniques are specifically developed for nor- and nand-type flash memories, while at the same time, overcoming their physical constraints. the proposed techniques check the validity of the stored snapshot and use the proposed fast crash recovery techniques when the snapshot is invalid. based on the experimental results, the proposed techniques can reduce the flash mounting time by about two orders of magnitude over the existing de facto standard flash file system.
dynamic group communication in mobile peer-to-peer environments. this paper presents an approach to integrate publish/subscribe semantics with on-demand multicast in wireless ad hoc networks, providing dynamic group communication with fine-grained subscriptions. a prototype application 'pgm golf forum' is developed, which enables a dynamic publish/subscribe system among the gallery during a golf tournament. dynamic construction of an event dissemination structure to route events from event publishers to subscribers is important, especially to support rapidly changing multi-hop topologies over wireless links. the proposed approach aggregates content-based subscriptions in a compact data format (bloom filters), and odmrp (on-demand multicast routing protocol) is extended to use this context from the middleware-tier to construct an optimized dynamic dissemination mesh. it operates dynamic multicast grouping by aggregated subscriptions applying clustering techniques. cooperation between middleware-tier and network components provides reliable finegrained publish/subscribe by odmrp's mesh topology.
interactive 3d visualization of highly connected ecological networks on the www. food webs describe who eats whom among species within a habitat. these networks depict interlinked food chains and have long been a central ecological paradigm for studying biocomplexity. as food-web data encompasses more species, the network structure of the feeding links among those species results in a highly connected network that is difficult to visualize in 2d. such simple representations often obscure important details critical for understanding the structure and function of ecosystems. graph layout is thus critically important for enhanced understanding of complex food webs. in this paper, we describe 3d visualizations of food webs that use intuitive node placement, minimal edge-crossing and link length, hierarchical node aggregation, and analysis tool integration. we also describe our deployment of "webs on the web" (wow) visualization and analysis tools on the www. these tools will facilitate food-web research, collaboration, and education. given the variety of 3d visualization technologies on the www, our wow visualization pipeline supports diverse formats and adapts to users' preferences by employing xml and a flexible architecture. currently, wow uses xml to semantically markup food-web data (foodwebml), extracts visual information into x3d format, and then uses the information to create a direct display on vrml/x3d browsers or feed a shockwave 3d visualization.
using an object oriented model for resolving representational differences between heterogeneous systems. one of the major concerns in the study of software interoperability is the inconsistent representation of the same real world entity in various legacy software products. this paper proposes an object-oriented model to provide the architecture to consolidate two legacy schemas in order that corresponding systems may share attributes and methods through use of an automated translator. a federation interoperability object model (fiom) is built to capture the information and operations shared between different systems. an automatic wrapper-based translator is discussed that utilizes the model to bridge data representation and operation implementation differences between heterogeneous distributed systems.
semantically enhanced enforcement of mobile consumer's privacy preferences. in such applications as location-based advertising, merchants use consumers' information to send them personalized advertisements. these applications provide convenience to consumers and competitive advantage to merchants. however, the improper use of consumers' information presents a serious threat to their privacy. it is also important to observe that among the motives for the consumers to accept advertisements is the incentive offered by the merchant. therefore, such incentive should become a criterion upon which consumers decide to grant or deny access to their information. we propose modeling mobile consumer preferences including incentive-related preferences in an ontology using the ontology web language (owl) and enforcing these preferences using reasoning techniques. we present modeling of consumer preferences and merchant queries in that ontology and describe how to match them. moreover, we present a prototype implementation and an evaluation study that shows that query size is more significant than the ontology size.
privacy-preserving svm using nonlinear kernels on horizontally partitioned data. traditional data mining and knowledge discovery algorithms assume free access to data, either at a centralized location or in federated form. increasingly, privacy and security concerns restrict this access, thus derailing data mining projects. what we need is distributed knowledge discovery that is sensitive to this problem. the key is to obtain valid results, while providing guarantees on the non-disclosure of data. support vector machine classification is one of the most widely used classification methodologies in data mining and machine learning. it is based on solid theoretical foundations and has wide practical application. this paper proposes a privacy-preserving solution for support vector machine (svm) classification, pp-svm for short. our solution constructs the global svm classification model from the data distributed at multiple parties, without disclosing the data of each party to others. we assume that data is horizontally partitioned -- each party collects the same features of information for different data objects. we quantify the security and efficiency of the proposed method, and highlight future challenges.
a methodology for comparing classifiers that allow the control of bias. this paper presents false positive-critical classifiers comparison a new technique for pairwise comparison of classifiers that allow the control of bias. an evaluation of na&iuml;ve bayes, k-nearest neighbour and support vector machine classifiers has been carried out on five datasets containing unsolicited and legitimate e-mail messages to confirm the advantage of the technique over receiver operating characteristic curves. the evaluation results suggest that the technique may be useful for choosing the better classifier when the roc curves do not show comprehensive differences, as well as to prove that the difference between two classifiers is not significant, when roc suggests that it might be. spam filtering is a typical application for such a comparison tool, as it requires a classifier to be biased toward negative prediction and to have some upper limit on the rate of false positives. finally the particular evaluation summary is presented, which confirms that support vector machines out-perform other methods in most cases, while the na&iuml;ve bayes classifier works well in a narrow, but relevant range of false positive rate.
abstract non-interference in a fragment of java bytecode. this work presents a program analyzer for checking abstract non-interference in a fragment of java bytecode. abstract non-interference is an information flow property which is weaker and more general than standard non-interference, since it can allow some selected parts of secret information to flow into the public part of a program. the motivation for such a weakening is that some flows are indeed useful in real-life applications. the amount of allowed flows is encoded into abstract domains, which characterize the degree of precision of a potential attacker in observing data; flows are forbidden as long as they can be observed and exploited by attackers. abstract values describe possible values of programs in different executions. basic features of java bytecode are considered; advanced topics, such as method calls, objects and exceptions, are also discussed. a program is said to be secure if analysis computes a state which does not contain private information in public places; information flows can exist only as long as the attacker has not enough observational power to see and exploit them.
unsupervised learning techniques for an intrusion detection system. with the continuous evolution of the types of attacks against computer networks, traditional intrusion detection systems, based on pattern matching and static signatures, are increasingly limited by their need of an up-to-date and comprehensive knowledge base. data mining techniques have been successfully applied in host-based intrusion detection. applying data mining techniques on raw network data, however, is made difficult by the sheer size of the input; this is usually avoided by discarding the network packet contents.in this paper, we introduce a two-tier architecture to overcome this problem: the first tier is an unsupervised clustering algorithm which reduces the network packets payload to a tractable size. the second tier is a traditional anomaly detection algorithm, whose efficiency is improved by the availability of data on the packet payload content.
recommendation-based browsing assistance for corporate knowledge portals. the management of knowledge, i.e. knowing what is known and the ability to exploit it is a burning issue for most organizations. though knowledge management has a strong social perspective, information technology supports knowledge management strategies by providing tools that store codified knowledge and allow its retrieval. the value of knowledge management derives from the wide use of the stored knowledge, its annotation and refinement as well as its application in business practices. we support this issue of information browsing and retrieval by adapting and applying recommendation technology to reduce access barriers towards corporate knowledge portals. for this purpose we exploit domain heuristics to improve collaborative filtering techniques in order to cope with the problem of low numbers of users the knowledge portals have.
dynamically generating web application fragments from page templates. web-based applications are typically required to be highly customizable and configurable. new application requirements have to be introduced rapidly, often without stopping the running application process. moreover, in many cases the same business logic has to be presented to different channels and/or user interfaces. in this paper we present a dynamic page template architecture for decomposing configurable and representational fragments of the application from the business logic. page templates consist of static xml files and of dynamic class definitions. the xml-based page templates can be used for declarative definitions of configurable fragments, say, by the end-user with a graphical tool. the page template classes can be used for behavior specification, say, for defining common styles of decoration of the presented pages. both parts are dynamically loaded into the web application environment and composed with the web objects. thus, the configurable and representational fragments of web objects are dynamically generated from the changeable and extensible descriptions in the page templates. the concepts presented are applied in various larger software systems. we will present a highly customizable conference management system as an example case.
statistical buffering for streaming media data access in a mobile environment. streaming media (e.g., music or video) data access has been a research problem over the past few years, and the problem becomes tougher when the clients are mobile devices whose limited storage spaces prevent the clients from holding a large cache. a practical solution for the cellular system is to buffer the streaming data on the base stations, serving as the "cache" to the mobile devices. however, when mobile devices move from one cell to another, the cached data should also be migrated to the corresponding base station in order that users can view the media smoothly. when the number of requests increases, stations may face heavy data migration and storage burden. in this paper, we propose a statistical buffering mechanism by adapting saa search which makes use of prior knowledge (statistical data) to predict the trend of user movement among cells. experimental studies show that, with an acceptable complexity, our algorithms can obtain good performance on buffering streaming media data.
migration to web services oriented architecture: a case study. the rapid emerging of web-services technology is dramatically changing the scenario of web application design and development. this paper presents a web-services oriented architecture. as a case study, the paper reports on an on-going project on the design and development of a pass-through authentication web-services for on-line electronic payment applications. this is a first step towards an electronic payment web-service.
towards increasing web application productivity. in this paper we present and discuss a template/meta-data based partial code generation system supporting web application development. seamlessly incorporating the recent top-notch technologies, the framework maximally exploits the capabilities of the underlying implementation technologies. our approach primarily benefits the framework and code developers. in addition, the complete separation of data model, navigation model, and presentation model reflects on a more general conceptual process that would decouple the technique and methodology from its underlying technology choices. the decoupling between the generated code and the code that is necessarily added later on through other development pathways than the generator deals with the incremental changes and adaptations of the models in the face of an operational system, therefore further enhances the extensibility, maintainability, and reusability of the generated applications.
spatial geometric constraint solving based on k-connected graph decomposition. we propose a geometric constraint solving method based on connectivity analysis in graph theory, which can be used to decompose a well-constrained problem into some smaller ones if possible. we also show how to merge two rigid bodies if they share two or three geometric primitives in a bi-connected or tri-connected graph respectively. based on this analysis, problems similar to the "double banana problem" could be easily detected.
a tabu search algorithm for the safe transportation of hazardous materials. in this work, we study the problem of the safe transportation of hazardous materials, which is an important operational problem and has been studied extensively in the literature. we outline previous work and propose a new model that is a variant of the vehicle routing problem with time windows (vrptw). the objective is to find a schedule to guarantee the safety of all vehicles. we propose a tabu search (ts) heuristic with a dynamic penalty mechanism to obtain good solutions. a realistic data generation mechanism is also presented and the elaborate computational results show the strengths of our algorithms.
ubidata: ubiquitous mobile file service. one of the most challenging objectives of mobile data management is the ubiquitous, any time, anywhere access. this objective is very difficult to meet due to several network and mobile device limitations. optimistic data replication is a generally agreed upon approach to alleviating the difficulty of data access in the adverse mobile environment. however, the two currently most popular models, both client/server and peer-to-peer models, do not adequately meet the ubiquity objectives. in our views, mobile data management should adequately support access to any data source, from any mobile device. it should also eliminate user involvement by automating data selection, hoarding, and synchronization, regardless of the mobile device chosen by the user. in this paper, we present ubidata: an application-transparent, double-middleware architecture that addresses these challenges. ubidata supports access and update to data from heterogeneous sources (e.g. files belonging to different file systems). it provides for the automatic and device-independent selection, hoarding, and synchronization of data. we present the ubidata architecture and system component, and evaluate the effectiveness of ubidata's automatic data selection and hoarding mechanisms.
personalization and visualization on handheld devices. the small screen size of handheld mobile devices poses an inherent problem in visualizing data: very often it is too difficult and unpleasant to navigate through the plethora of presented information. this paper presents a novel approach to personalized and adaptive content presentation for handheld devices, which has been implemented in a mobile financial application system based on a 3-tier architecture. the approach is independent of wireless networks and mobile devices. it utilizes a combination of user profiling, data clustering, and visualization techniques (fisheye and semantic zooming), enhancing the understandability of the data and improving the usability of the device.
an attribute-based access matrix model. in traditional access control models like mac, dac, and rbac, authorization decisions are determined according to identities of subjects and objects, which are authenticated by a system completely. modern access control practices, such as drm, trust management, and usage control, require flexible authorization policies. in such systems, a subject may be only partially authenticated according to one or more attributes. in this paper we propose an attribute-based access matrix model, named abam, which extends the access matrix model. we show that abam enhances the expressive power of the access matrix model by supporting attribute-based authorizations. specifically, abam is comprehensive enough to encompass traditional access control models as well as some usage control concepts and specifications. on the other side, expressive power and safety are two fundamental but conflictive objectives in an access control model. we study the safety property of abam and conclude that the safety problem is decidable for a restricted case where attribute relationships allow no cycles. the restricted case is shown to be reasonable enough to model practical systems.
privacy preserving learning in negotiation. machine learning techniques are widely used in negotiation systems. to get more accurate and satisfactory learning results, negotiation parties have the desire to employ learning techniques on the union of their past negotiation records. however, negotiation records are usually confidential and private, and owners may not want to reveal the details of these records. in this paper, we introduce a privacy preserving negotiation learning scheme that incorporate secure multiparty computation techniques into negotiation learning algorithms to allow negotiation parties to securely complete the learning process on a union of distributed data sets. as an example, a detailed solution for secure negotiation q-learning is presented based on two secure multiparty computations: weighted mean and maximum. we also introduce a novel protocol for the secure maximum operation.
a fast and effective steganalytic technique against jsteg-like algorithms. detection of hidden messages in images, also known as image steganalysis, is of great significance to network information security. in this paper, we propose a fast and effective steganalytic technique based on statistical distributions of dct coefficients which is aimed at two kinds of popular jsteg-like steganographic systems, sequential jsteg and random jsteg for jpeg images. our approach can not only determine the existence of hidden messages in jpeg images reliably, but also estimate the amount of hidden messages exactly. its advantages also include simplicity, computational efficiency and easy implementation of real-time detection. experiment results show the superiority of our approach over other steganalytic techniques.
effort and accuracy analysis of choice strategies for electronic product catalogs. one crucial task for e-commerce systems is to help buyers find products that not only satisfy their preferences but also reduce their search effort. usually the amount of available products is far beyond the upper limit that any individual could process by hand; thus product search tools are employed to generate target product (s) by eliciting the buyer's preferences and then executing some kind of choice strategies. we propose in this paper an extended effort-accuracy framework for measuring the performance of various choice strategies in terms of cognitive effort, elicitation effort and decision accuracy. the performance of a variety of basic choice strategies is further studied by theoretical analysis as well as empirical simulations. it shows that the performance of a given choice strategy is a tradeoff between choice accuracy and effort required from the users. the proposed framework also suggests a new efficient method of evaluating the user interfaces of e-commerce systems by analyzing the performance of the underlying choice strategies.
an efficient implementation of parametric line and polygon clipping algorithm. an improved parametric line clipping algorithm is presented. the line clipping algorithm is extended to polygon clipping. the implementations of both the algorithms are novel and outperform many previous algorithms in the literature. this is supported by theoretical consideration and experimental results on randomly selected lines and polygons. the algorithms are implemented in java. the java applet allows the user to visualize the experimental results by comparing the existing algorithms and the new algorithms.
a decision-theoretic approach for designing proactive communication in multi-agent teamwork. techniques that support effective communication during teamwork processes are of particular importance. psychological study shows that an effective team often can anticipate information exchange among the team and communicate relevant information proactively. proactive communication is crucial for understanding and sharing common goals and for cooperative actions. communication can be valuable if it assists agents with new and timely information; it also has cost because it consumes network resources such as bandwidth. to address these issues, we present a new model that uses information production and need to capture the complex multi-agent communication process and a dynamic decision-theoretic determination of communication strategies. we also introduce a generic utility function and an algorithm, dtpc (decision-theoretic proactive communication), that focuses on representing information production and need of team members and resolving decision interactions among them for making decisions.
applying agent technology to software process modeling and process-centered software engineering environment. the software processes can be analyzed, designed, and maintained as if it is a piece of software. this view enables the application of software engineering technologies to software process modeling (spm) and process-centered software engineering environment (psee). one reason for the relatively few applications of spms and psees technologies in the software industry is that traditional software engineering technologies applied to the spms and psees are not suitable for modeling software processes which are human-centered. this paper proposes an approach for applying agent technology, which has been accepted as a novel software engineering paradigm, to spm and psee. in this approach, software processes are viewed as the collaboration of a group of process agents that know how to manage the software development activities and can act in the way software developers go about planning, enacting and reflecting on their work. an agent-based psee for enacting software processes under the proposed approach is also given in this paper.
selecting the best valid scopes for wireless dissemination of location-dependent data. mobility of user poses new challenges to research on spatial data access. spatial data cached in the mobile client may become invalid because of the movement of the client. to increase the reusability of the cached data, we can identify the valid scope of the spatial data (i.e., the spatial area within which the data is known to be valid) and save the valid scope as well as the data in the cache. in this paper, we study issues on the dissemination of spatial data and valid scopes in a wireless environment. we investigate methods for representing valid scopes and their impacts on system performance. a generic representation method, called the invalidation-efficiency-based (ieb) method, is proposed. simulation experiments are conducted to compare the performance of ieb with other representation methods. result shows that ieb is superior to the other methods because it tries to balance the precision and overhead of valid scopes.
node clustering based on link delay in p2p networks. peer-to-peer (p2p) has become an important computing model because of its adaptation, self-organization and autonomy etc. but efficient organization of the nodes in p2p networks is still a challenge needs to be addressed. node clustering is a mechanism that aims to provide an optimal infrastructure to organize the nodes in a p2p network. this paper describes an approach to implement node clustering based on link delay of node communications in the p2p network. this approach is completely distributed, in which each node only depends on its neighbors to implement node clustering. in this approach, we propose two distributed algorithms: t-closure algorithm and hierarchical node clustering algorithm to find node clusters automatically in a p2p network. we explore the node connectivity together with the connection quality. as a result, the link delay of communication between the super-node and the peer-node in node clustering can be limited, which will improve the overall performance of p2p networks.
dynamic interactive spatial similarity retrieval in iconic image databases using enhanced digraph. similarity-based retrieval of images is an important task in many image database applications. interactive similarity retrieval is one way to resolve the fuzzy area involving psychological and physiological factors of individuals during the retrieval process. a good interactive similarity system is not only dependent on a good measure system, but also closely related to the structure of the image database and the retrieval process based on the respective image database structure. in this paper, we propose to use a dynamic similarity measure on top of the enhanced digraph index structure for interactive iconic image similarity retrieval. our approach makes use of the multiple feedbacks from the user to get the hidden subjective information during the retrieval process, and avoids the high cost of re-computation of an interactive retrieval algorithm.
approaches to text mining for clinical medical records. clinical medical records contain a wealth of information, largely in free-text form. means to extract structured information from free-text records is an important research endeavor. in this paper, we describe a medical information extraction (medie) system that extracts and mines a variety of patient information with breast complaints from free-text clinical records. medie is a part of medical text mining project being conducted in drexel university. three approaches are proposed to solve different ie tasks and very good performance (precision and recall) was achieved. a graph-based approach which uses the parsing result of link-grammar parser was invented for relation extraction; high accuracy was achieved. a simple but efficient ontology-based approach was adopted to extract medical terms of interest. finally, an nlp-based feature extraction method coupled with an id3-based decision tree was used to perform text classification.
regularized b-spline network and its application to heart arrhythmia classification. this paper presents an effective learning scheme that combines b-spline modeling and regularized neural networks. essential issues of structural design and learning process are discussed. regularization theory is leveraged to design the topological structure of the network. a training algorithm is derived for the learning of both synaptic weights and b-spline coefficients. the approach is then applied to the medical problem of heart arrhythmia detection, particularly the detection of premature ventricular contraction. promising results demonstrate the potential benefits of the proposed method.
boundary extraction in thermal images by edge map. extracting object boundaries in thermal images is a challenging task because of the amorphous nature of the images and the lack of sharp boundaries. classical edge-based segmentation methods have the drawback of not connecting edge segments to form a distinct and meaningful boundary. many level set approaches, which can deal with changes of topology and the presence of corners, have been developed to extract object boundaries. previous researchers have used image gradient, edge strength, area minimization and region intensity to define the speed function. our approach uses edge direction and magnitude, called an edge map, as the main component of the speed function. the edge map points toward the nearest boundary; its magnitude represents the total gradient energy in the half plane. the experimental results are significantly superior to those obtained using edge magnitude alone.
data driven approach to designing minimum hamming distance polychotomizer. a polychotomous classifier assigns an observation to one of the k categories with k > = 3. multiple binary classifiers (k = 2) such as the popular support vector machines can be combined to achieve multi-class classification. commonly used approaches include the one-vs-others scheme and the one-vs-one (pairwise coupling) scheme. while literature reported better performance from pairwise coupling than one-vs-others, the number of base learners required by pairwise coupling is quadratic in k. alternatively, error correcting output codes (ecoc) provides a more general framework for designing polychotomizers. it associates each class with a codeword, which provides the capability to unify the traditional schemes. however, the design of an effective "coding matrix" remains an open problem. we study one kind of ecoc polychotomizer that decodes using minimum hamming distance. we propose a novel data-driven way to design the codewords based on inter-cluster distance. it provides a systematic way to extend the traditional schemes and construct effective polychotomizers. experiments are conducted on synthetic data and real world applications including uci repository problems and cenparmi handwritten numerals. experiments show that the proposed scheme can achieve competitive accuracy compared with both traditional schemes, and the number of base learners is typically much less than the requirement of the pairwise scheme.
measuring structural complexity for class diagrams: an information theory approach. in the object-oriented analysis phase, class diagrams are used to represent the static structure of objects in a system and the kinds of static relationships that exist among them, which lay the foundation for all later design and development. therefore, their complexity has a significant impact on the quality of the ultimate system. for quantifying the structural complexity of a class diagram precisely, this paper presents a structural complexity model called weighted class dependence graph (wcdg), in which almost all relationships among classes/interfaces that can be found during the object-oriented analysis phase are represented and their degrees are characterized by weights. based on the wcdg, this paper depicts the occurrence of the outgoing and incoming edges by two discrete random variables and then uses entropy distance to derive a novel structural complexity measure called edc. we believe that edc is flexible and could evaluate the structural complexity of class diagrams more objectively.
recognizing the relations between web pages using artificial neural network. semantic web shows us the potential infrastructure of the next generation web. web information will be understandable to machines in this infrastructure. our research work has the aim of embedding machine-understandable semantic information in ordinary html files automatically given the domain ontology. we focus on automatically acquiring the instances of concepts and relations defined in domain ontology from web pages. this paper describes how to recognize the relation between web pages (a kind of relation instance) by using artificial neural network (ann). the input vector of ann is determined by the type of web pages, the number and type of hyperlinks between the web pages, and the similarity in web pages' contents. we also show the initial results got by our prototype system.
streaming of divx avi movies. in recent years the mpeg-4 iso compression standard has gained much attention. with its high compression ratio it promises to make broadband streaming more feasible. however, currently there are only a limited number of fully iso standard compliant mpeg-4 systems widely available (apple's quicktime 6 is one of the first). some partial implementations, such as the mpeg-4 style codec "divx" are popular for encoding video content into avi (audio video interleave) files. the avi file format was originally not intended for streaming. in this report we document our efforts to enable streaming of divx avi files across broadband ip based networks. this will allow the large number of existing avi files to be made available in streaming applications.
coordination-based distributed constraint solving in dice. dice (distributed constraint environment) is a framework for the construction of distributed constraint solvers from software components in a number of predefined categories. the framework is implemented using the manifold coordination language, and delivers coordination services to these components. the coordination services implement existing protocols for constraint propagation, termination detection and splitting of constraint satisfaction problems. dice combines these protocols with support for parallel search and the grouping of closely related components into cooperating solvers. in addition to these facilities, the paper describes the dice framework architecture, and gives a report on its implementation.
an agent model for fault-tolerant systems. this paper describes the use of fault tolerance in a multi-agent system. such an approach is based on the modeling of autonomous agents with planning capabilities. these capabilities are used by the agent to recover from faults occurring in its surrounding environment, e.g. hardware faults, or in its internal representation thereof, e.g. software faults. the expected fault-tolerant behavior is tested using fault injection either in the system described by the agent or in the environment in which the agent (system) is embedded into.
on the semantics and expressive power of datalog-like languages for np search and optimization problems. it has been shown that np (decision, search and optimization) problems can be expressed by means of datalog (datalog with unstratified negation) queries under stable model semantics. anyhow, the use of unrestricted negation is often neither simple nor intuitive and, besides, datalog does not allow to optimize queries and to discipline the expressive power. this paper analyzes the power of datalog-like languages in expressing np search and optimization problems. in more detail, in this paper we study the expressive power of several languages obtained by extending positive datalog with intuitive and efficient constructs, i.e. stratified negation, constraints and (exclusive) disjunction. finally, we investigate a further restricted language, called np datalog, which uses disjunction only to define (nondeterministically) partitions of relations and which, in addition, captures the power of datalog in expressing search and optimization problems.
component based trust management in the context of a virtual organization. one of the difficulties in evaluating the trustworthiness of an object in a virtual organization is the lack of sufficient information to study how the object was formed and to what level its components should be trusted. if a subject could be provided with detailed information about the ingredients of a compound object, then the subject would be able to evaluate the trust level of that compound object with higher confidence. this paper introduces a scheme using labels associated with each object within the domain of a virtual organization to facilitate trust management. each label supplies certain information regarding the originality of the associated object. thus, partial trust (also called component trust) can be integrated to evaluate the composite trust of the compound object. re-labeling enables object information update to accommodate the dynamic nature of a virtual organization. indirect trust between two subjects can be calculated based on a trust network. different subjects may view the same object with different trust values because they trust the components of the object to different degrees. this model uses recommendations supplied by other subjects to provide a dynamic and flexible way to adjust the trustworthiness of an object for a certain subject.
information trustworthiness evaluation based on trust combination. publishing information in a virtual organization (vo) has become too easy due to low barriers; hence development of novel mechanisms to assess the quality of collected information has become a necessity. an evaluator makes such an assessment based on the trust he/she places on the information. this paper presents a model for evaluating information trustworthiness in a data-intensive vo.when some information is derived from various data items gathered from multiple sources (each data item is called an object as used together with the term, subject), it is possible that no data value (called a version of the object) satisfies an evaluator's requirement with regard to information quality, if they are evaluated separately. according to the principle of object trust combination, if the final values of an object calculated by using significantly different methods are similar, then the evaluator places higher level of trust in the results. intuitively, different versions of the same object that are calculated in different ways but have similar values provides "multiple-proofs" towards their correctness. we assume that a subject has no conflicting information on a given object.this paper uses a formal data structure to represent how a given piece of information (object version) has been formed and develops algorithms (see section 4) to compare the component structure similarity/dissimilarity between two object versions. this helps in calculating the final trust values of the object.
a new local consistency for weighted csp dedicated to long domains. the weighted constraint satisfaction problem (wcsp) is a soft constraint framework with a wide range of applications. most current complete solvers can be described as a depth-first branch and bound search that maintains some form of local consistency during the search. however, the known consistencies are unable to solve problems with huge domains because of their time and space complexities. in this paper, we adapt the 2b-consistency, a weaker form of arc consistency well-known in classic csps, into the bound arc consistency and we provide several algorithms to enforce it.
a dissimilarity measure for alc concept descriptions. this work presents a dissimilarity measure for description logics that are the theoretical counterpart of the standard representations for ontological knowledge. the focus is on the definition of a dissimilarity measure for alc concept descriptions, based both on the syntax and on the semantics of the descriptions. an extension of the measure is proposed for involving individuals and then for evaluating their dissimilarity.
days mobile: a location based data broadcast service for mobile users. location dependent wireless data dissemination has become an integral part of our day-to-day activities. most available applications are actually location aware which find restaurants, hotels, and millions of other points of interests (poi). recent advances in global positioning systems (gps) technology has led to the development of smart and efficient navigation systems with voice prompted turn by turn directions to the destination. deployment of wireless broadband services like evolution data optimized (evdo) has motivated the development of ubiquitous data distribution systems or wireless broadcast of location based services (lbs). days (data in your space) mobile discusses a broadcast based lbs which tends to decrease access latency [4] for location dependent data (ldd) when the number of mobile users is significantly large. we create a broadcast platform to disseminate commonly used ldd like weather, traffic, stocks, flight information, etc., and develop and deploy a java based mobile application in a mobile device which accesses the broadcasted ldd. our experiments and results show that a broadcast based lbs can be highly efficient as compared to the present generation of request-response type lbs.
software product line evolution method based on approach. continuing optimal product line development needs to evolve core assets in response to market, technology or organization changes. in this paper, we propose a product line evolution method based on the kaizen approach. kaizen is a continuous improvement method that is adopted in japanese industry. the important points of the kaizen are to prepare a work standard and continue to improve processes by correcting the differences between the standard and actual results. our core asset kaizen method provides a standard that includes core asset types based on simple metrics, kaizen patterns representing expertise, and kaizen processes for continuous improvement.
formal modelling and verification of a component model using coloured petri nets and model checking. component based software engineering has been claimed as a suitable approach to improve the flexibility and reuse in software development. in this context, the compor infrastructure provides mechanisms to promote the dynamic composition of software systems, addressing applications with support for unanticipated requirement changes. in this paper, the formal modelling and verification of the compor component model is presented. hierarchical colored petri nets are used for modelling and simulation, purposing to show the correct behavior for some scenarios. model checking is used to prove that the scenarios analyzed with simulation are correct for all possible behaviors of the model.
representing organizational competencies. business activities within the organization are performed by a number of human or automated actors. for the organization to adapt to internal or external changes it must be able to understand how and why actors are related to and assigned to processes. this requires a consistent representation of the services required by the organization's processes and those provided by its actors. this paper focuses on defining the concepts that allow structurally aligning human actors and business processes through the description of the organizational competencies required to perform processes' activities. these structures can then be used dynamically within a marketplace-based model, supporting the management of actors and activities according to the supply and demand of competencies.
selecting a distributed agreement algorithm. when component parts of distributed systems need to reach agreement, arriving at consensus is difficult if some components don't behave properly. the byzantine generals problem described by lamport and others exemplifies the difficulty. in a real situation, components don't know which of their peers are faulty and hence they cannot apply the algorithms of lamport et al, nor even decide if a suitable algorithm exists. this paper discusses options available in this situation and describes how a good expectation of arriving at a consensus can be achieved without knowing for certain which or how many participants are behaving badly.
on the stochastic constraint satisfaction framework. stochastic constraint satisfaction is a framework that allows to make decisions taking into account possible futures. we study two challenging aspects of this framework: (1) variables in stochastic csp are ordered sequentially, which is adequate for the representation of a number of problems, but is not a natural choice for the modeling of problems in which the future can follow different branches (2) the framework was designed to allow multi-objective decision-making, yet this issue has been treated only superficially in the literature. we bring a number of clarifications to these two aspects. in particular, we show how minor modifications allow the framework to deal with non-sequential forms, we identify a number of technicalities related to the use of the sequential ordering of variables and of the use of multiple objectives, and in addition we propose the first search algorithm that solves multi-objective stochastic problems in polynomial space.
raas: a reliable analyzer and archiver for snort intrusion detection system. one of the primary challenges in ids alerts analysis is controlling and archiving the huge amount of alerts that have been triggered mainly in attack periods. we have developed a self-adaptive controlling mechanism which archives the snort generated alerts in a well-formed abstracted format. an appropriate hashing technique along with a full-automated time-based hierarchical archiving approach has been used to reach this end. the developed system prevents the snort database size to grow uncontrollably and unexpectedly. results obtained from experiments and test cases show that especially in critical attack situations the system responds to queries well in a reasonable amount of time. the developed analyzer with new archiving approach is also able to compress the generated alerts effectively and generate statistical reports fast. the developed system is platform independent and can be deployed on mid-range servers and workstations. also employing it does not require much degree of security expertise.
query optimizing on a decentralized web search engine. currently, most web search engines perform search on nearly a whole copy of the web corpus. there are also tools to add search functionality to a single site. nonetheless, there is little research into search related to online communities: set of related websites or weblogs. to fill this gap, a peer-to-peer search engine is presented in this paper. this p2p search engine is designed to provide small- and middle-scale online communities such as blog sites and news sites the ability to perform text search within the community. it organizes nodes on a distributed hash table (dht) based peer-to-peer network. communities are formed in a self-organizing style. p2p ir systems may cause increased internal traffic among nodes in answering a multi-term query. in this paper, we focused on this issue and proposed several techniques to optimize the multi-term query process in a p2p framework. our proposed algorithms are evaluated by simulation. the simulation results show that our proposed algorithms have good scalability and can improve performance of the system by about two orders of magnitude in the best case.
-bound gsi: a flexible database replication protocol. several previous works have proven that there is no way of guaranteeing a snapshot isolation level in symmetrical replicated database systems without blocking transactions when they are started. as a result of this, the generalized snapshot isolation (gsi) level was defined, relaxing a bit the freshness of the snapshot being taken when a transaction is initiated in its local replica. this enhances performance, since transactions do not need to get blocked, but in some cases will increase the abortion rate. this paper proposes a flexible protocol that is able to bound the degree of snapshot outdateness from a relaxed gsi to the strict one-copy equivalent si. additionally, it proposes an optimistic solution where transactions do not block, and only need to be re-initiated when their optimistic start fails. such re-initialization is made very soon and only rolls back the first transaction accesses, without waiting for the transaction completion. finally, if 1csi is not enough, this protocol is also able to manage transactions with serializable isolation, if such a level is requested.
applying ontology in architecture-based self-management applications. context-awareness is the premise of self-management applications. in this paper, a middleware for adaptive coordination (mac) architecture is proposed. it supports the cycle from modeling and reasoning about the context knowledge to planned architecture-based self-management actions. one of the key elements of our approach is the explicit modeling of context by web ontology language based on which the logic reasoning is performed. besides, an internal object-oriented architectural self-management mechanism is proposed. a prototype of mac is also given followed by a case study with quantitative evaluations.
reflective layer activation in contextl. expressing layer dependencies in context-oriented programming is cumbersome because until now no facility has been introduced to control the activation and deactivation of layers. this paper presents a novel reflective interface that provides such control without compromising efficiency. this allows expressing complex application-defined dependencies between layers where the activation or deactivation of a layer requires the activation or deactivation of another one. the activation or deactivation of specific layers can also be prohibited based on application-defined conditions.
generalizing recognition of an individual dialect in program analysis and transformation. we present a novel method for generalizing the recognition capability of a tool from one dialect of a language to other dialects. the framework defines a novel base-dialect-specific map layer for representing program geography as recognised/unrecognised program zones in terms of an annotated preprocessor token stream. error call stacks generated in the front-end syntax-analysis are also stored in the map for invoking programmable, error handling and repair transformations to obtain recognizable constructs from un-recognized ones. an iterative process is followed, wherein for each transformation, reversion-identifying edits are also stored in the map to provide a handle on (and preserved semantics of) the unchanged, original form. to advance unconstrained dialect variation from the recognised base dialect, the map's edit components and all transformations are defined on text form, for which a novel datatype minimizing transformation conflict is defined denotationally. the datatype, anchored text, gives primacy to locations in the initial sources, independently of the code located thereat. this results in greater commutativity of software transformations. a case study of the approach in generalizing a sequential dialect of c to upc (unified parallel c) is carried out.
integrating a certified memory management runtime with proof-carrying code. software systems today are built from collections of interacting components written in different languages at varying levels of abstraction from the machine hardware. the ability to integrate certified components from different levels of a software architecture is a necessary part of the process of developing a dependable and secure computing infrastructure. in this paper we present a prototype system in the context of proof-carrying code that allows for the integration of safety proofs derived from a high-level type system with a certified, low-level memory management runtime library.
improved structural modeling based on conserved domain clusters and structure-anchored alignments. in this paper, we presented a method to improve structural modeling based on conserved domain clusters and structure-anchored alignments. we first constructed a template library of structural clusters for all conserved sequence domains. then, for each cluster, we built the profile using the structure and sequence information. finally we use the profile and structural alignments as anchors to increase the alignment accuracy between a query and its templates. our preliminary results show that this method can be used for the partial prediction for a majority of known protein sequences with better qualities.
real-time java processor optimized for rtsj. due to the preeminent work of the real-time specification for java(rtsj), java is increasingly expected to become the leading programming language in real-time systems. to provide a java platform suitable for real-time applications, a real-time java processor can execute java bytecode directly is proposed in this paper. this processor provides efficient support in hardware for mechanisms specified in the rtsj and offers a simpler programming model through ameliorating the scoped memory of the rtsj. the most important characteristic of the processor is that its wcet(worst case execution time) of the bytecode execution is predictable. it is vital for the real-time systems.
an efficient dual caching strategy for web service-enabled pdas. pdas have evolved over the years from resource constrained devices that supported only the most basic tasks to powerful handheld computing devices. however, the most significant step in the evolution of pdas was the introduction of wireless connectivity which enabled them to host applications that require internet connectivity like email, web browsers and maybe most importantly smart/rich clients. being able to host smart clients allows the users of pdas to seamlessly access the it resources (e.g. legacy apps) of their organizations. one increasingly popular way of enabling access to it resources is by using web services (ws) [14]. this trend has been aided by the rapid availability of web service (ws) packages/tools, most notably the efforts of the apache group [1] and ide vendors (e.g., microsoft's visual studio [2], ibm's eclipse [3]). using ide tools and other software packages it is fairly easy for programmers to expose application interfaces and/or consume existing interfaces leading to a gradual replacement of the current web server centric approaches (e.g. asp, jsp, servlets, cgi scripts) with ws centric approach. this paper focuses on the challenges of enabling pdas to host web services consumers and introduces a dual caching approach to overcome problems arising from temporarily loss of connectivity and fluctuations in bandwidth.
fast tracking of hierarchical partitions with approximate kl-divergence for geo-temporal organization of personal images. usage of camera-equipped mobile devices raises the need for automatically organizing large personal image collections. we propose here a technique based on a two-level hierarchy of mixture models to automatically organize such a collection with the geo-temporal meta-data attached to each pictures.
reporting leadership patterns among trajectories. widespread availability of location aware devices (such as gps receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. in this paper we investigate spatio-temporal movement patterns in large tracking data sets. we present a natural definition of the pattern 'one object is leading others', and discuss how such leadership patterns can be computed from a group of moving entities. the proposed definition is based on behavioural patterns discussed in the behavioural ecology literature. we also present several algorithms for computing the pattern, and they are analysed both theoretically and experimentally.
an architectural co-synthesis algorithm for energy-aware network-on-chip design. network-on-chip (noc) has been proposed to overcome the complex on-chip communication problem of soc (system-on-chip) design in deep submicron. a complete noc design contains exploration on both hardware and software architectures. the hardware architecture includes the selection of pes (processing elements) with multiple types and their topology. the software architecture contains the allocation of tasks to pes, scheduling of tasks and their communications. to find the best hardware design for the target tasks, both hardware and software architectures need to be considered simultaneously. previous works on noc design have concentrated on solving for only one or two design parameters at a time. in this paper, we propose a hardware-software co-synthesis algorithm for a heterogeneous noc architecture. the design goal is to minimize energy consumption while meeting the real-time requirements commonly seen in the embedded applications.
applying genetic algorithms to economy market using iterated prisoner's dilemma. this paper investigates the use of genetic algorithms (ga) to evolve cooperative agents in a competitive market environment using iterated prisoner's dilemma (ipd). our study seeks to follow axelrod's research of computer simulations of the ipd game which is generally regarded as a benchmark for the studies on evolution of cooperation. however, we are of the opinion that his work was a little restrictive and lack of a genuine real-world component. in this paper, we report on a simulation study that attempts to bridge the gap by applying ga to a market model. we examine how well ga could perform against the ipd strategies, and explore the strategic interactions among the agents that represent firms in a coevolving population. we also report on the influence of the genetic operators on the performance of ga. our experimental results show that cooperation can be evolved in such non-cooperative environment using ga. we conclude that with proper tuning of parameters, ga could be extremely useful for optimizing the outcome of an economy market.
distortion-constrained compression of vector maps. an algorithm for lossy compression of vector maps for given error tolerance was developed. the algorithm is based on optimal polygonal approximation and dynamic quantization of vector data. a near optimal distortion-constrained quantizer with step defined by the tolerance level was constructed. the proposed algorithm performed well compared to other approaches.
a mechanism for replicated data consistency in mobile computing environments. mobile computing allows for the development of new and sophisticated database applications. such applications require the reading of current and consistent data. in order to improve data availability, increase performance and maximize throughput, data replication is used. however, due to inherent limitations in mobile and other loosely-coupled environments, the concurrency control and replica control mechanisms must be revisited. this paper proposes a new protocol that guarantees the consistency of replicated data in a mobile computing environment, while provide high data availability and ensure an eventual replica convergence towards a strongly consistent state.
olindda: a cluster-based approach for detecting novelty and concept drift in data streams. a machine learning approach that is capable of treating data streams presents new challenges and enables the analysis of a variety of real problems in which concepts change over time. in this scenario, the ability to identify novel concepts as well as to deal with concept drift are two important attributes. this paper presents a technique based on the k-means clustering algorithm aimed at considering those two situations in a single learning strategy. experimental results performed with data from various domains provide insight into how clustering algorithms can be used for the discovery of new concepts in streams of data.
towards reusable and modular aspect-oriented concurrency control. information systems based on the world wide web increased the impact of concurrent programs. such increase demands the definition of methods for obtaining safe and efficient implementations of concurrent programs, since the complexity of implementation and tests in concurrent environments is bigger than in sequential environments. this work defined guidelines to restructure object-oriented software in order to modularize concurrency control using aspect-oriented programming. those guidelines are supported by a concurrency control implementation that guarantees system correctness without redundant concurrency control, both increasing performance and guaranteeing safety. we define abstract aspects that constitute a simple aspect framework that can be reused to implement concurrency control in other applications. the achieved modularization makes the concurrency control easy to evolve and decreases the complexity of other parts of the software, such as business and data management modules, by decoupling concurrency control code from them.
a randomized knot insertion algorithm for outline capture of planar images using cubic spline. the proposed work, in this paper, is concerned with an efficient technique of curve fitting using cubic splines. the technique has various phases including extracting outlines of images, detecting corner points from the detected outline, addition of extra knot points if needed. the last phase makes a significant contribution by making the technique automated. it uses the idea of knot insertion in a randomized manner. the proposed algorithm is an iterative one. the algorithm proposed is computationally efficient as compared to least square approach.
online resource management in a multiprocessor with a network-on-chip. we propose an online resource allocation solution for multiprocessor systems-on-chip, that executes several real-time, streaming media jobs simultaneously. the system consists of up to 24 processors connected by an aethereal [7] network-on-chip (noc) of 4 to 12 routers. a job is a set of processing tasks connected by fifo channels. each job can be independently started or stopped by the user. each job is annotated with resource budgets per computation task and communication channel which have been computed at compile-time. when a job is requested to start, resources that meet the required resource budgets have to be found. because it is done online, allocation must be done with low-complexity algorithms. we do the allocation in two-steps. first, tasks are assigned to virtual tiles (vts), while trying to minimise the total number of vts and the total bandwidth used. in the second step, these vts are mapped to real tiles, and network bandwidth allocation and routing are performed simultaneously. we show with simulations that introducing randomisation in the processing order yields a significant improvement in the percentage of mapping succdesses. in combination, these techniques allow 95% of the processor resources to be allocated while handling a large number of job arrivals and departures.
web image annotation by fusing visual features and textual information. in this paper, we propose a novel web image annotation method, namely fmd (fused annotation by mixed model graph and decision tree), which combines visual features and textual information to conceptualize the web images. the fmd approach consists of three main processes: 1) construct the visual-based model, namely modelmmg, 2) construct the textual-based model, namely modeldt, and 3) fuse modelmmg and modeldt as modelfmd for annotating the images. the purpose of visual-based annotation model is to objectify the image not only by the global content of the image but also by its local content of composing objects. the textual-based annotation model is to handle the problems of user-specified dependency of keywords and the complex computation due to high dimensionalities in text features. the experimental results reveal that the proposed fmd method is very effective for web image annotation in terms of accuracy through the integration of two different types of features.
enhancing qos metrics estimation in multiclass networks. this paper discusses the problematic of qos monitoring, suggesting the use of on-line multipurpose active monitoring in multiclass networks as a powerful tool to efficiently assist and enhance the control of multiple service levels. to improve the simultaneous estimation of one-way qos metrics, we propose a flexible probing source able to adjust probing patterns to the measurement requirements of each service class, exploring pattern coloring to better sense packet loss. the proof-of-concept provided shows that the proposed solution improves the estimation accuracy of multiple qos metrics significantly, with a reduced probing overhead.
using text search for personal photo collections with the mediassist system. the mediassist system enables organisation and searching of personal digital photo collections based on contextual information, content-based analysis and semi-automatic annotation. one mode of user interaction uses automatically extracted features to create text surrogates for photos, which enables text search of photo collections without manual annotation. our evaluation shows that this text search facility is effective for known-item search.
a computation environment for automated negotiation: a case study in electronic tourism. the automated negotiation topic plays an important role in e-commerce research. however, despite considerable work on automated negotiation, few research efforts have aimed at software engineering facilities such a reuse and flexibility. to address this issue, we propose a novel computation environment for building agents with flexible negotiation strategies to function in various virtual business domains. regarding the negotiation strategies, some decision taking assistance techniques may be used in group, e.g. rule-based reasoning and techniques to machine learning. considering the flexibility of acting in various business domains, a specific agent can be programmed to work in as many business domains as necessary, and essentially, it will also be possible to reconfigure the agent's business domains at execution time. all the experiments in this work were idealized in the terms of a tourism negotiation package. results from these experiments demonstrate effectiveness of our proposal.
mining communities of acquainted mobile users on call detail records. in a telecommunication system, call detail records (i.e., cdrs) are generated automatically for tracking and billing purposes when mobile users having calls. to further investigate the information buried in huge amounts of cdrs, relationship among mobile users can be organized. specifically, communities of acquainted mobile users can be effectively discovered from collected cdrs through our approach proposed in this paper. note that understanding the communities and corresponding calling behaviors are of great importance to telecommunication companies. to conduct proper community mining on cdrs, techniques of data transformation and social network analysis are fully exploited. our study shows that the proposed approach is practically feasible.
his-kcwater: context-aware geospatial data and service integration. the nature of today's geographically and managerially distributed geospatial information sources makes the interoperability across different sources from different organizations difficult. the integration of real-time water quality assurance data with geographic data is even more challenging. in this paper, we present a context-aware geospatial data and service integration framework that is based on the combination of a syntactic model, a semantic model and a pragmatic model using semantic web technologies. this model is context-aware, with the ability to analyze existing dependencies, predict causes and effects and provide context-aware services (which information services are relevant, how to perform the services, how often they are needed, etc). as a proof of concept, we demonstrate the his-kcwater system for supporting users in analyzing real time watershed data, predicting the water quality using hydrologic model simulators, interpreting the results, dynamically forecasting problems and generating alerts about water quality issues.
modeling mirna data. as a sub-type of ncrna genes, micro rna (mirna) produces rna that is implicated in the regulation of gene translation and expression. human diseases can result from alternation in such non-coding rna. building a consolidated mirna database repository thus becomes a crucial element for mirna-related research. we have set up a dual objective in our work: to explore alternative approaches for mirna data modeling, and to consolidate mirna data in an integrated repository for future retrieval and analysis of mirna data. we have explored three approaches for mirna data modeling. for the same source data, we have implemented a relational database (converted from an initial entity-relationship diagram), an xml database, and an integrated xml-relational database. we have also compared their performance on the criteria of query performance and design flexibility. though using entity-relationship modeling of the data provides access to the strength and stability of relational databases, our work concludes that xml information modeling and native xml databases provide geneticists the adaptability and flexibility required to model a complex, constantly changing domain such as mirna research.
a quantitative method for assessing algorithms to remove back-to-front interference in documents. documents written on both sides on translucent paper make visible the ink from one side on the other. this artifact is called "back-to-front interference", "bleeding" or "show-through". the direct binarization of documents with such interference yields unreadable documents. the literature presents several algorithms for suitably removing such artifact. this paper presents a method to assess algorithms to remove back-to-front interference.
how to detect semantic business process model variants? precise modeling of business processes has paved the way to realize process aware information systems that include allocations of resources, communication services, or hardware devices to users. changes in business strategies or new business opportunities may result in modifications of implemented functionalities of information systems and their underlying business process models. the result of these modifications are business process model variants. in this paper, we propose an algorithm for determining linguistic similarities between business process model variants in order to faciliate process redesign.
tube (text-cube) for discovering documentary evidence of associations among entities. user-driven discovery of associations among entities, and documents that provide evidence for these associations, is an important search task conducted by researchers and do-main information specialists. entities here refer to real or abstract objects such as people, organizations, ideologies, etc. associations are the inter-relationships among entities. most current works in query-driven document retrieval and finding representative subgraphs are ill-suited for the task as they lack an awareness of entity types as well as an intuitive representation of associations. we propose the tube model, a text cube approach for discovering associations and documentary evidence of these associations. the model consists of a multi-dimensional view of document data, a flexible representation of multi-document summaries, and a set of operations for data manipulation. we conduct a case study on real-life data to illustrate its applicability to the above task and compare it with the non-tube approach.
a flexible representation of controllers for physically-based animation of virtual humans. in this paper, we propose a representation of controllers that uses high-level sensors and possesses a general and intuitive structure that offers several types of parameters, which can be modified by the animator or automatically. this structure, with the feedback signals provided by its sensors, allows several state machines to act simultaneously on the model, or in a subset of its actuators. the sensors can be optimized, facilitating their definition and use. the representation also permits the animator to define procedures with more general instructions in order to be automatically executed by the controller during the dynamics simulation.
learning rules with negation for text categorization. this paper describes olex, a novel method for the automatic construction of rule-based text classifiers. olex relies on an optimization algorithm whereby a set of (both positive and negative) discriminating terms is generated for the category being learned. such terms are then used to construct a classifier of the form "if term t1 or ... term tn occurs in document d, and none of terms tn--1, &middot; &middot; &middot; tn--m occurs in d, then d belongs to category c". the proposed method is simple and elegant. despite this, the results of a systematic experimentation performed on both the reuters-21578 and the ohsumed data collections show that olex is both effective and efficient.
separation of concerns in translational semantics for dsls in model engineering. development of domain specific languages (dsls) in the context of model driven engineering is gaining more and more popularity. as evolution lies in the heart of every software system, the major requirement for dsls is that they should be modular and resilient to changes. mde-based dsl frameworks should enable a modular specification of language translational semantics and the composition of the modules into languages. ultimately, the availability of such techniques should make the dsl development faster. separation of concerns is a sound software engineering principle used to obtain better modularity, reusability, and adaptability of systems. however, this principle must be supported by proper tools that allow the separation achieved at a conceptual level to be preserved in the language specification. in mde, the mainstream tools for specifying translations are model transformation languages. in this paper we evaluate a class of model transformation languages regarding their applicability for capturing the translational semantics of dsls in a modular way. we found that the concepts in the domain of translational semantics significantly mismatch with the language constructs of the transformation language. we suggest that this problem may be better approached by a domain-specific transformation language.
a phasing mechanism for model transformation languages. in recent years a great effort has been devoted to understanding the nature of model transformations. as a result, several mechanisms to improve model transformation languages have been proposed. phasing has been proposed in some works as a rule scheduling or organization mechanism, but without any detail. in this paper, we present a phasing mechanism a we explain in detail how it can be integrated in a transformation language and when its usage is appropriate. the mechanism we propose can be seen as an internal transformation composition mechanism. first, we motivate the work, and then we describe in depth the mechanism. finally, we show four examples of application and give some conclusions.
a priority assignment strategy of processing elements over an on-chip bus. the number of bus transactions in system-on-chip (soc) grows significantly in recent years. because of different timing constraints for different applications, how to find a proper priority assignment for processing elements (pes) of soc becomes very challenging. in this paper, we first show that the priority assignment problem with one unique priority for each pe is np-complete. when each bus transaction can have one unique priority, we propose an optimal priority assignment algorithm for a given workload. we then propose a priority assignment strategy based on simulated annealing (sa) for pes, where bus arbitration is done in a priority-driven fashion. the objective is to minimize the number of priorities needed for each pe and to satisfy the timing constraints of applications. the experimental results show some encouraging results in priority assignment.
software customization in model driven development of web applications. model driven development (mdd) of complex software systems can require manual adaptations of the generated artifacts. in fact, in order to cope with unforeseen requirements which are not completely satisfiable by means of the involved modeling languages, developer interventions could be needed. the optimal solution to deal with this issue, is based on the expressiveness improvement of the involved metamodels and refinement of the used model transformations. nevertheless, these adaptations are not always possible or cost-effective especially if the new functionalities that have to be introduced affect only the single application being developed. this paper discusses and attempt to hand-tune the generated code by providing an approach supporting its merging with hand written modifications. for this purpose, the behaviour model of the system under study is considered to graphically specify the injection points where the modifications have to occur. the discussions are based on a running example consisting of a simple web application.
using constraint techniques for a safe and fast implementation of optimality-based reduction. optimality-based reduction attempts to take advantage of the known bounds of the objective function to reduce the domain of the variables, and thus to speed up the search of a global optimum. however, the basic algorithm is unsafe, and thus, the overall process may no longer be complete and may not reach the actual global optimum. recently, kearfott has proposed a safe implementation of optimality-based reduction. unfortunately, his method suffers from some limitations and is rather slow. in this paper, we show how constraint programming filtering techniques can be used to implement optimality-based reduction in a safe and efficient way.
a scalable overlay framework for internet anycasting service. this study presents ias, a scalable and efficient global overlay routing framework for internet anycasting service. we introduce a new routing group concept and adopt the overlay network mechanism to achieve scalable and efficient inter-domain anycast routing. we show that the routing table size of an anycast router can be bounded by o(&radic;n), where n denotes the number of anycast groups. we conduct simulations on a as topology to verify this bound and show that routes found by ias are very close to the shortest path when the size of anycast group is reasonably large.
structural similarity in geographical queries to improve query answering. the paper proposes a method for query approximation in geographic information systems. in particular, the problem of matching a query with imprecise or missing data is analyzed and an approach for the relaxation of query constraints is proposed. query approximation is performed by relaxing structural constraints, according to an extension of a previous proposal for evaluating concept similarity in an ontology management system [1] inspired by the maximum weighted matching problem in bipartite graphs. in our approach, we start from a weighted hierarchy of geographical objects evaluated using wordnet, a lexical database for the english language available on the internet. if a concept contained in a query has no match in the database, the query is approximated using a structural similarity graph that connects all geographical concepts by the lowest structural distance. the aim of the proposed methodology is to relax structural query constraints, in order to obtain meaningful answers for imprecise or missing data.
a framework for corba interoperability in ad hoc networks. the increasing popularity of wireless-enabled pdas, laptops and smart mobile phones, in addition to an explosion in the number of mobile services and networks, makes necessary the use of supporting frameworks to assist the development of distributed applications in ad hoc networks. starting from omg's standards on wireless access in mobile environments, this paper focuses on additional architectural requirements for adapting and extending corba's interoperability model so that it can be used to transparently handle giop message exchanges among objects across ad hoc networks. the proposed architecture, based on federations of specialized name servers, is described along with a strategy for routing the messages. finally, implementation details and strategies along with performance and scalability issues are discussed.
directed filter for dominant direction fuzzy set in content-based image retrieval. this paper presents a new directed filter that is performed on the dominant directions. the dominant directions are computed by the cluster algorithm and fuzzy set theory. the dominance of those dominant directions is computed and used for similarity measurement. the experiments show that the proposed filter fits for particular image domains very much.
certain trust: a trust model for users and agents. one of the challenges for ubiquitous computing and p2p systems is to find reliable partners for interactions. we believe that this problem can be solved by assigning trust values to entities and allowing them to state opinions about the trust-worthiness of others. in this paper, we develop a new trust model, called certain trust, which can easily be interpreted and adjusted by users and software agents. a key feature of certain trust is that it is capable of expressing the certainty of a trust opinion, depending on the context of use. we show how the trust values can be expressed using different representations (one for users and one for software agents) and present an automatic mapping to change between the representations.
enhancing adaptive random testing in high dimensional input domains. adaptive random testing (art) is an enhancement of random testing (rt). it can detect failures more effectively than rt when failure-causing inputs are clustered. having test cases both randomly selected and evenly spread is the key to the success of art. recently, it has been found that the dimensionality of the input domain could have an impact on the effectiveness of art. the effectiveness of some art methods may deteriorate when the dimension is high. in this paper, we work on one particular art method, namely fixed-sized-candidate-set art (fscs-art) and show how it can be enhanced for high dimensional domains. since the cause of the problems for fscs-art may also be valid for some other art methods, our solutions to the high dimension problems of fscs-art may be applicable for improving other art methods.
energy-efficient disk replacement and file placement techniques for mobile systems with hard disks. mobile systems have usually used hard disks as the secondary storage devices because of their high capacity per cost and high i/o throughput. however, their high power consumption is the main limiting factor for extending their adoptions in mobile systems. in this paper, we propose enhanced file placement techniques for mobile platforms with multiple smaller disks (instead of a single large disk). we investigate that how many smaller disks are necessary to obtain energy saving while maintaining the required performance using both a simplified energy model and a realistic trace-based simulator under the proposed multiple disk configurations. we also propose energy-efficient file placement techniques, which aggregate files with common attributes the same set of disks. by skewing i/o operations, the proposed techniques achieve additional energy saving. experimental results show that the proposed techniques can reduce the energy consumption by up to 43% when eight 1" disks are used instead of a single 2.5" disk with an acceptable increase in the average response time.
instance-based retrieval by analogy. this work presents a method for retrieval in knowledge bases expressed in description logics, founded in the instance-based learning. the procedure implements the disjunctive version space approach exploiting a notion of semantic difference. the method can be employed both to answer to class-membership queries, even though the answers are not logically entailed by the knowledge base, e.g. there are some inconsistent assertions due to heterogeneous sources. in addition, it may also predict/suggest new assertions the method has been implemented and tested in an experimentation, where we show that it is sound and effective.
an approach for indexing, storing and retrieving domain knowledge. in this short paper, we present our solution to index, store and retrieve the domain knowledge. the main principle exploits lucene to index the domain knowledge under guide of the domain schema. the method to map domain knowledge structure into lucene index structure, store and update the indices, and to transfer rdf-based query into lucene's query are presented.
automatic classification of digestive organs in wireless capsule endoscopy videos. wireless capsule endoscopy (wce) allows a physician to examine the entire small intestine without any surgical operation. with the miniaturization of wireless and camera technologies the ability comes to view the entire gestational track with little effort. although wce is a technical break-through that allows us to access the entire intestine without surgery, it is reported that a medical clinician spends one or two hours to assess a wce video, it limits the number of examinations possible, and incur considerable amount of costs. to reduce the assessment time, it is critical to develop a technique to automatically discriminate digestive organs such as esophagus, stomach, small intestinal (i.e., duodenum, jejunum, and ileum) and colon. in this paper, we propose a novel technique to segment a wce video into these anatomic parts based on color change pattern analysis. the basic idea is that the each digestive organ has different patterns of intestinal contractions that are quantified as the features. we present the experimental results that demonstrate the effectiveness of the proposed method.
why do successful search systems fail for some topics. this paper describes and evaluates the vector-space and probabilistic ir models used to retrieve news articles from a corpus written in the french language. based on three clef test-collections and 151 queries, we classify the poor retrieval results of difficult topics under 6 categories. the explanations we obtain from this analysis differ from those suggested a priori by our students. we use the web to manually or automatically find related search terms to the original query. we evaluate these two query expansion strategies in order to improve mean average precision (map) and to reduce the number of topics for which no pertinent responses are listed among the top ten references returned.
a clustering entropy-driven approach for exploring and exploiting noisy functions. linear, gaussian, fitness proportional, clustering, and rosca entropies are succinct measures of diversity that have been applied to balance exploration and exploitation in evolutionary algorithms. in previous studies, an entropy-driven approach using linear entropy explicitly balances and/or searches optimal solutions for the selected unimodal and multimodal functions excluding noisy functions. this paper investigates the reasons for such an exception and introduces a clustering entropy-driven approach to solve the problem. such an approach provides a coarse-grained diversity measure that filters the noise of functions, varies cluster size and categorizes individuals at the genotype level. the experimental results show that the clustering entropy-driven approach further improves the searching results of noisy functions by one more degree.
sesame: space-efficient stack allocation mechanism for multi-threaded sensor operating systems. this paper proposes a sesame, which is a space-efficient stack allocation mechanism for multi-threaded sensor operating systems. it adaptively adjusts the stack size by allocating or releasing additional stack frame based on the amount of each function's stack usage information. our experimental results show that the sesame significantly minimizes spatial overhead of thread's stacks with tolerable time overhead compared with fixed stack allocation mechanism of the multi-threaded sensor operating systems.
nl sampler: random sampling of web documents based on natural language with query hit estimation. random sampling of documents is a substantial supporting function for research in information science, content-related research (like content adaptation), or social sciences. looking for an appropriate method to get a random sample of microsoft office files for research on presentation sharing applications, we found out, that the two main approaches random walk and random search are not appropriate to find formatted documents. both approaches are designed for the purpose of large scale web analysis and do not fit more special requirements. in this paper, we adopt and extend the random search approach first described by bharat and broder to a more universal random sampling method based on natural language lexica called nl sampler, that can be used in a wide range of application domains. it supports parameters like file type or dns domain restrictions while preserving representativeness. we implemented and evaluated the approach and found a zipf-like distribution of average hits per query which enables estimation of query hits for a certain set of parameters and thus can be used in a lot more application areas than the approaches previously published. estimation functions are given for microsoft word and powerpoint documents.
effects of inconsistently masked data using rpt on cf with privacy. randomized perturbation techniques (rpt) are applied to perturb the customers' private data to protect privacy while providing accurate referrals. in the rpt-based collaborative filtering (cf) with privacy schemes, proposed so far, users disguise their ratings in the same way to achieve consistently perturbed data. however, since users might have different levels of concerns about their privacy, the customers might decide to perturb their private data differently, which causes inconsistently masked data. how, then, can e-companies present referrals using such data and how can inconsistent data disguising affect accuracy and privacy?
hybrid retrieval from the unified web. the goal of semantic web initiative is to make the semantics of web content accessible to machines. the semantic web has been evolving into a web of data separate from the existing html web. our work focuses on establishing and exploiting connections between the two webs, especially hyperlink connections from the html web pages to the semantic web nodes, so as to enhance both data and document retrieval. we propose the unified web model to integrate the two webs, and a hybrid query language to retrieve data and documents from the unified web. specifically, the query language amalgamates graph-based reasoning over rdf with keyword-based search.
on efficient wear leveling for large-scale flash-memory storage systems. flash memory won its edge over many other storage media for embedded systems, because it provides better tolerance to the extreme environments which embedded systems are exposed to. in this paper, techniques referred to as wear leveling for the lengthening of flash-memory overall lifespan are considered. this paper presents the dual-pool algorithm, which realizes two key ideas: to cease the wearing of blocks by storing cold data, and to smartly leave alone blocks until wear leveling takes effect. the proposed algorithm requires no complicated tuning, and it resists changes of spatial locality in workloads. extensive evaluation and comparison were conducted, and the merits of the proposed algorithm are justified in terms of wear-leveling performance and resource conservation.
a customizable multi-agent system for distributed data mining. we present a general multi-agent system framework for distributed data mining based on a peer-to-peer model. agent protocols are implemented through message-based asynchronous communication. the framework adopts a dynamic load balancing policy that is particularly suitable for irregular search algorithms. a modular design allows a separation of the general-purpose system protocols and software components from the specific data mining algorithm. the experimental evaluation has been carried out on a parallel frequent subgraph mining algorithm, which has shown good scalability performances.
adaptive broadcast by distributed protocol switching. adaptation is a desirable requirement in a distributed system since it helps the system to perform gracefully under different scenarios. there are many adaptive algorithms for different problems. however the techniques are often application specific. in many distributed systems it may happen that the same problem has multiple protocols, each of which performs differently under different environments. in such cases adaptation can be achieved by dynamically switching between them as the environment changes. in this paper we illustrate the idea of designing adaptive distributed system using protocol switching by presenting an adaptive broadcast protocol that uses either a bfs tree or a dfs tree depending on the load of the system, both trees being rooted at the broadcast source. at low load a bfs tree is used as it reduces the broadcast delay (since the distance of any node from the root is always minimum in a bfs tree) while still keeping the load on any one node low. however at higher load a dfs tree is used to reduce the load on any one node since the degree of a node in a dfs tree is generally lower than that in a bfs tree. so the broadcast adapts to the network load by dynamically switching between a bfs tree and a dfs tree. in the proposed scheme, the switching is done by a middleware layered below the broadcast protocol. this separates the adaptation from the application and no change is needed in the application. we also ensure the application layer property that every broadcast message is correctly delivered to all the nodes, including messages sent when the switching is in progress. we assume the asynchronous model of distributed system with reliable but non-fifo channels. also it is assumed that no failure occurs during the switching. the message complexity of the algorithm that switches to a dfs tree is o(|e|) and is presented in the next section. the algorithm that switches to a bfs tree needs o(|v||e|) messages and is omitted in this paper due to lack of space.
exploiting the efficiency of generational algorithms for hardware-supported real-time garbage collection. generational garbage collectors are more efficient than their non-generational counterparts. unfortunately, however, generational algorithms require both write barriers and write barrier handlers and therefore degrade worst-case performance. in this paper, we present novel hardware support for generational garbage collection. in contrast to previous work, we introduce a hardware write barrier that does not only detect inter-generational pointers, but also executes all related book-keeping operations entirely in hardware. for the first time, write barrier detection and handling occur completely in parallel to instruction execution, so that the runtime overhead of generational garbage collection is reduced to near zero. for evaluation purposes, we extended a system with hardware-supported real-time garbage collection with our hardware support for generational garbage collection. measurements of java programs on an fpga-based prototype show that the generational extensions reduce the total duration of garbage collection activities by a factor of 5 and the memory traffic caused by the collector by a factor of 4 on average.
scalable coordination for sensor networks in challenging environments. in sensor networks, the unpredictable dynamics caused by the disruption of communication in harsh environments, the depletion of battery resources, and node mobility make coordination between sensor nodes more challenging than coordination between nodes in typical wired and wireless networks. while the literature is rich in coordination protocols for sensor networks and routing protocols for ad-hoc wireless networks, they assume relatively static environments. using these protocols in highly dynamic environments leads to increased coordination traffic, high energy-consumption, increased event loss, and excessive latency in reporting events. in this paper we propose swift, a coordination protocol that reacts to changes in nodes' connectivity with a local repair process, significantly reducing the coordination traffic. swift eliminates routing loops through a combination of avoidance and detection mechanisms; and does not require gps support, which cannot be used in closed environments and consumes significant energy resources. experimental results reveal that swift outperforms existing protocols and achieves significant energy efficiency, reduces event loss, and the latency in reporting events under various network dynamics.
a metadata-based architectural model for dynamically resilient systems. designing open and distributed systems that can dynamically adapt in a predictable way to unexpected events is a challenging issue still not solved. achieving this objective is a very complex task since it implies reasoning at run-time, explicitly and in a combined way, on a system's functional and non-functional characteristics. this paper proposes a service-oriented architectural model allowing the dynamic enforcement of formally expressed metadata-based resilience policies. it also describes preliminary dynamic resilience experiments acting as proof of concept.
software reengineering with architecture decomposition. software reengineering involves the activities of studying target system's architecture. however, enterprise legacy software systems tend to be large and complex. the analysis of system architecture therefore becomes a difficult task. to solve the problem, we propose an approach that decomposes software architecture to reduce the complexity associated with analyzing large scale architecture artifacts. our study has shown that architecture decomposition is an efficient way to limit the complexity and risk associated with the re-engineering activities of a large legacy system. it divides the system into a collection of meaningful modular parts with low coupling, high cohesion, and minimizes the interface, thus to facilitate the incremental approach to implement the progressive software re-engineering process. to fulfill this goal, we have developed two major techniques to decompose legacy system architecture. in this paper, we present them in detail. the approach is also supported by our automated reverse engineering tools, and the preliminary experimental result shows our approach is very promising.
extending reusable asset specification to improve software reuse. even though many approaches for reuse have been introduced, software engineers are still hesitating to reuse existing software components. two problems are the root cause of this situation. one is the difficulty in knowing whether the required software components are available. the other is the lack of information as to how to reuse the acquired components. to solve this problem, we introduce an extension to reusable asset specification (ras) and a process for supporting efficient reuse. we explain the process with a case study and evaluate through feedback from software engineers participating the case study.
towards semantic tuplespace computing: the semantic web spaces system. in this paper we introduce semantic web spaces, a middleware for coordinating knowledge processes on the semantic web. co-ordination is an important aspect of any type of interaction between computer agents, but we find especially so on the semantic web in which the communication contains knowledge rather than data and correct inferences can only be made when the right knowledge is available at the right time. because of this we have identified tuplespace computing as a relevant paradigm for agent communication on the semantic web and have prototypically realized a system based on a linda-inspired coordination model and on core semantic technologies such as rdf, ontologies and reasoning.
an edit operation-based approach to the inclusion problem for dtds. xml documents on a database should be revalidated whenever a dtd is updated, since the documents may no longer be valid against the dtd. solving the inclusion problem for dtds is essential to avoiding such an expensive revalidation, but the problem is shown to be pspace-complete. in this paper, we propose a subproblem of the inclusion problem in terms of edit operations to regular expressions, and show a polynomial-time algorithm for solving the subproblem. then we consider the recognizability of the algorithm.
global intrusion detection and tolerance in networked systems. this paper presents an architecture for a global intrusion detection and tolerance such as global detection, global correlation, and intrusion tolerance. global intrusion detection and tolerance system (gidts). the cooperation proposed by the gidts solution allows the detection of complex attacks at their early stages. this cooperation is performed based on the output of several detection components located at different levels (wire network, wireless network, host, and disk). in addition, major detection and tolerance capabilities are protected against intruders attempts since they are performed by compromise independent components, located at the disk level. the gidts components implement different functions based on formal models proposed in this paper including, especially, alert correlation, storage requests, and tolerance strategy models. to enhance detection and tolerance capabilities, each gidts is assumed to cooperate with any other gidtss via a neighbor identification protocol. to illustrate gidts behavior, we propose an environment that integrates the flight management system, which represents a distributed application.
variadic templates for c++. generic functions and classes accepting a variable number of type arguments have proven to be a very useful, but missing, feature of c++. numerous foundational libraries rely on clever template and preprocessor tricks to emulate such variadic templates. by several measures these emulations are inadequate. this paper describes how c++ can be extended with variadic templates, significantly improving existing implementations of widely used c++ libraries in terms of code size, quality of error diagnostics, compilation speed, and generality. furthermore, variadic templates enable new applications, such as type-safe implementations of functions like printf, and improved support for generic mixin classes. we have implemented variadic templates as an extension of a production quality c++ compiler.
a hypermap framework for computer-aided proofs in surface subdivisions: genus theorem and euler's formula. this paper presents a new framework to conduct formal proofs concerning the topology of surface subdivisions. the subdivisions are modeled by hypermaps specified through the calculus of inductive constructions. proofs are computer-aided using the coq system. a significant example is emphasized: the proof of the genus theorem and of the euler formula for hypermaps.
verification of web service descriptions using graph-based traversal algorithms. service discovery and composition techniques require a careful and accurate specification of the functional and behavioural descriptions of services. otherwise, the located services may not provide the requested functionality and composite services may incorporate services that are incompatible and uncomposable. this paper proposes two formalisms for accurately specifying functional and behavioural descriptions and a technique for detecting errors in the specifications. unlike existing frameworks, functional descriptions created with the proposed formalism enable the purpose of a service, and the data transformations and state transitions performed by it to be modelled together. the behavioural description formalism is capable of accurately representing the effects of interactions and the temporal relationships between them. the technique is developed by extending a pre-order depth-first search algorithm, which traverses through the interaction protocol of a service and determines whether the valid terminal state of the service can be derived from its initial state. a sample case study in which we detect errors in the functional and behavioural descriptions of a service by verifying them using the proposed technique is provided.
use of hardware z-buffered rasterization to accelerate ray tracing. ray tracing is a rendering technique for producing realistic 3d computer graphics. compared to traditional scan-line rendering which is generally adopted by graphics pipeline, ray tracing can simulate more realistic global illumination, however, with the cost of expensive computation. in this paper, we implement a ray tracer that combines advantages of both rendering schemes: efficiency of scan-line rendering and reality of ray tracing. we first use hardware-accelerated rasterization with z-buffer to quickly determine the first ray-triangle hit of eye rays on the gpu. secondary rays such as reflective and shadow rays are then traced to generate global illumination on the cpu with a bounding volume hierarchy (bvh) which plays the role of our acceleration structure. the experiments show that rasterization is much more efficient in finding the first hit and can completely replace the traditional ray casting procedure.
reconfigurable split data caches: a novel scheme for embedded systems. this paper shows that even very small reconfigurable data caches, when split to serve data streams exhibiting temporal and spatial localities, can improve performance of embedded applications without consuming excessive silicon real estate or power. it also shows that neither higher set-associativities nor large block sizes are necessary with reconfigurable split cache organizations. we use benchmark programs from the mibench suite to show that our cache organization outperforms an 8k unified data cache in terms of miss rates, access times, energy consumption and silicon area. finally we show how the saved area can be utilized for supporting techniques for improving performance of embedded systems. our design enables the cache to be divided into multiple partitions that can be used for different processor activities other than conventional caching. in this paper we have evaluated one of those options to support "prefetching".
using software product lines to manage model families in model-driven engineering. the relationship between software product lines (spl) and model-driven engineering (mde) is not new in the literature. it mainly focuses on the use of domain-specific languages to specify application families, rather than using the more classic feature models. however, more recent works propose another important synergy: the use of feature models to specify model families. in this paper we propose a domain-specific transformation language (dstl) that helps in the creation of spls to manage model families. moreover, we show the benefits coming from taking a new approach to dstl development. in this approach, dstl instances are not compiled into source code but transformed onto general-purpose transformation languages in order to be executed using already existent transformation engines.
three-dimensional segmentation of brain tissues using markov random fields and genetic algorithms. this work addresses the segmentation of brain tissue in mr images by means of markov random fields and genetic algorithms. a genetic algorithm is employed to estimate initial parameters, aiming at improving the segmentation process. the results of the segmentation process also make it possible to classify structures and determine new parameters, which are useful in the creation of three dimension images of the brain.
memory-efficient content filtering hardware for high-speed intrusion detection systems. content filtering-based intrusion detection systems have been widely deployed in enterprise networks, and have become a standard measure to protect networks and network users from cyber attacks. although several solutions have been proposed recently, finding an efficient solution is considered as a difficult problem due to the limitations in resources such as a small memory size, as well as the growing link speed. in this paper, we present a novel content filtering technique called table-driven bottom-up tree (tbt), which was designed i) to fully exploit hardware parallelism to achieve real-time packet inspection, ii) to require a small memory for storing signatures, iii) to be flexible in modifying the signature database, and iv) to support complex signature representation such as regular expressions. we configured tbt considering the hardware specifications and limitations, and implemented it using a fpga. simulation based performance evaluations showed that the proposed technique used only 350 kilobytes of memory for storing the latest version of snort rule consisting of 2770 signatures. in addition, unlike many other hardware-based solutions, modification to signature database does not require hardware re-compilation in tbt.
implementing a practical declarative logic-based model transformation engine. declarative approaches to specifying model-model transformation are an attractive approach because they can offer implicit source model traversal, automatic traceability management, implicit target object creation, and implicit rule ordering. however, when proposing such a declarative logic-based transformation language, there are two common objections. one is programmer unfamiliarity with declarative style, and the other is that of perceived performance problems. in this paper we address these issues, discussing the design of specific features of the tefkat transformation engine intended to facilitate writing and debugging declarative transformation specifications, and describing important implementation techniques used to avoid performance problems.
continuation-passing enactment of distributed recoverable workflows. scalability, reliability and adaptability are among the key requirements for the enactment of distributed workflows. in addition, system resources should be efficiently utilized. central workflow engines and static workflow instantiation are some of the important obstacles to meeting these requirements. we propose a fully decentralized approach to workflow enactment that is not subject to these obstacles. in addition, it supports automatic recovery. the approach is of continuation-passing style, where continuations, or the reminder of the executions, are passed along with asynchronous messages for workflow enactment. two continuations are associated to an execution: a success continuation and a failure continuation. recovery plans for workflows are automatically generated and included in failure continuations at runtime. a prototype is implemented.
modeling deceptive information dissemination using a holistic approach. this research studies deceptive information dissemination based on the information flow network and the web of trust. we present an information dissemination model that illustrates the prerequisite for information propagation based on the subject and object trusts. to evaluate the spread of deceptive data accurately, we offer two quantitative models that are utilized to calculate the degree to which the subjects in the information flow network are affected. the algorithms for evaluating information dissemination for these two models are provided and the time complexities of the algorithms are also analyzed. our experiments illustrate the characteristics of the web of trust that affect the dissemination of the deceptive information.
semantically enhanced user modeling. content-based implicit user modeling techniques usually employ a traditional term vector as a representation of the user's interest. however, due to the problem of dimensionality in the vector space model, a simple term vector is not a sufficient representation of the user model as it ignores the semantic relations between terms. in this paper, we present a novel method to enhance a traditional term-based user model with wordnet-based semantic similarity techniques. to achieve this, we use word definitions and relationship hierarchies in wordnet to perform word sense disambiguation and employ domain-specific concepts as category labels for the derived user models. we tested our method on windows to the universe, a public educational website covering subjects in the earth and space sciences, and performed an evaluation of our semantically enhanced user models against human judgment. our approach is distinguishable from existing work because we automatically narrow down the set of domain specific concepts from initial domain concepts obtained from wikipedia and because we automatically create semantically enhanced user models.
an implementation and performance analysis of slave-side arbitration schemes for the ml-ahb busmatrix. the slave-side arbitration is different from the master-side arbitration based on the request and grant signals. the slave-side arbitration uses the response signals of slave for arbitration. also, the arbitration overhead of the slave-side arbitration is 10% smaller than that of the master-side arbitration. in this paper, we implement and analyze the slave-side arbitration schemes for the ml-ahb busmatrix. we implemented the ml-ahb busmatrixes with fixed priority, round robin and dynamic priority arbitration schemes. our busmatrix implementation particularly reduces area and clock period by 17% and 19% respectively, compared with those of busmatrix of arm by virtue of the masking mechanism. with the performance simulations, we observed that when there are few masters with long job length in a bus system, the dynamic priority based arbitration shows the maximum performance and in other cases the arbitration based on round robin shows the highest performance. in addition, the arbitration scheme with transaction based multiplexing shows higher performance than the same arbitration scheme with single transfer based switching in an application with frequent accesses to the long latency devices or memories such as sdram. the improvements of the arbitration scheme with transaction based multiplexing are 26%, 42% and 51%, respectively when the latency times of sdram are 1, 2 and 3 clock cycles.
querying and browsing xml and relational data sources. a lightweight method for querying and browsing multiple relational and xml data sources is presented. the approach is based on a simple abstraction of relational and xml data models. a query language for the abstraction to which xpath and sql map to naturally is introduced. a unique feature of the query language is that it unifies structured queries and keyword-based searches.
an adaptive randomized search protocol in peer-to-peer systems. search problem, which is to identify the peer that has a target resource object, is an important problem in peer-to-peer (p2p) file sharing systems. since p2p systems maintain large and dynamic sets of peers, the search protocol is desired to be scalable and adaptive. in this paper we propose a new p2p search protocol, called adaptive randomized search protocol (arsp), which is an efficient extension of the quorum-based protocol for searching objects in peer-to-peer networks. arsp minimizes the communication cost of the protocol by popularity-based index dissemination of objects. the protocol works in a self-adaptive manner: it automatically adapts to the dynamics of network environments.
eigen-distribution on assignments for game trees with random properties. in this paper, we investigate a special distribution, called eigen-distribution, on assignments for game tree tk2 with random properties. there are two cases, where the assignments to leaves are independently distributed (id) and correlated distributed (cd). in id setting, we prove that the distributional probability ϱ belongs to [equation] and ϱ is a strictly increasing function on rounds [equation]. in cd setting, we propose a reverse assigning technique (rat) to form 1-set and 0-set, then show that e1-distribution (namely, a particular distribution on assignments of 1-set such that the complexity of any deterministic algorithm is equal) is the unique eigen-distribution.
modeling web service composition and execution via a requirements-driven approach. the increasing popularity of web services for application integration has strengthened the need for automated web service composition and joint execution. a lot of attention has been paid recently towards techniques for creating a composite web service from individual web services based on user requirements, and driven by a variety of criteria. however, the major lacuna so far in web service composition is the lack of a holistic requirements-driven approach for modeling the web service execution lifecycle. in this paper we present such an approach based on our earlier work on context-driven web service modeling. in particular, we separate requirements into two parts - functional and extrafunctional requirements (frs and efrs, respectively). we express frs as commitments made by individual web ser-vices towards the composite web service, and efrs as rules that constrain the behavior of the individual web services while they execute against their frs. we also present a conceptual model that can be used for tracking requirements during web service execution.
stigmergic optimization in dynamic binary landscapes. hereafter we introduce a novel algorithm for optimization in dynamic binary landscapes. the binary ant algorithm (baa) mimics some aspects of real social insects' behavior. like ant colony optimization (aco), baa acts by building pheromone maps over a grid of possible trails that represent solutions to an optimization problem. main differences rely on the way this search space is represented and provided to the colony in order to explore/exploit it. then, by a process of pheromone reinforcement and evaporation the artificial insect trails converge to regions near the problem solution or extrema. the negative feedback granted by the evaporation mechanism provides the self-organized system with population diversity and self-adaptive characteristics, allowing baa to be particularly suitable for hard dynamic optimization problems (dop), where extrema continuously changes at severe speeds.
decentralized enforcement of security policies for distributed computational systems. the shift from single server environments to globally distributed systems presents a great challenge in terms of defining and enforcing appropriate security policies. this is, among other things, due to the fact that the actual order between events in an asynchronous distributed environments is not always defined. in addition, security policies often depend on the actual information exchange among the distributed entities. in this paper we study the problem of adapting security policies to distributed environments such as grids and mobile code systems. we define global security policy and indicate some of the difficulties in translating local policies to the distributed environment. then, we propose an efficient and scalable decentralized security mechanism for the enforcement of global stateful security policies in distributed computational systems. the mechanism is based on multiple instances of execution monitors (smart sandboxes) running on the distributed entities and on efficient security information sharing among them. we show that the subclasses of em policies enforceable by this mechanism contain useful and real live security policies such as global information flow policies.
logical and algebraic view of huzita's origami axioms with applications to computational origami. we describe huzita's origami axioms from the logical and algebraic points of view. observing that huzita's axioms are statements about the existence of certain origami constructions, we can generate basic origami constructions from those axioms. origami construction is performed by repeated application of huzita's axioms. we give the logical specification of huzita's axioms as constraints among geometric objects of origami in the language of the first-order predicate logic. the logical specification is then translated into logical combinations of algebraic forms, i.e. polynomial equalities, disequalities and inequalities, and further into polynomial ideals (if inequalities are not involved). by constraint solving, we obtain solutions that satisfy the logical specification of the origami construction problem. the solutions include fold lines along which origami paper has to be folded. the obtained solutions both in numeric and symbolic forms make origami computationally tractable for further treatments, such as visualization and automated theorem proving of the correctness of the origami construction.
cristore: dynamic storage system for heterogeneous devices in off-site ubiquitous communities. most researches for ubiquitous services have been interested in constructing intelligent environments in physical spaces such as conference hall, meeting room, home, and campus. in these spaces people are able to share data easily. however, as cooperative works from a distance make a social issue, we need a data sharing system for an "off-site" community that is a group of people with a common interest and purpose in different ubiquitous places like a remote conference/meeting. in this paper, we propose a dynamic storage system, cristore for heterogenous devices of the off-site communities, which autonomously builds a distributed shared data space and keeps a flexible overlay topology of the participant devices according to the devices' capabilities. cristore also performs file operations fitted to the capabilities.
a petri net semantics for web service choreography. many web service standards of orchestration and choreography are designed to reduce their inherent complexity of composing web services. existing standards all remain at the descriptive level, without providing any formal semantics and method for verifying important properties. web service choreography interface (wsci) describes the flow of messages exchanged by a web service which participates in choreographed interactions with other services. due to many advantages of petri nets, an extended one is used to formalize wsci in this paper. we show several nets to represent the activity, process and interface respectively. our formal model remarkably focuses on the wsci concept of message exchange and the context which describes the environment. this paper proposes some properties and introduces technique for checking them to ensure its correct deployment.
a set of schedulers for grid networks. central to grid processing is the scheduling of application tasks to resources. schedulers need to consider heterogeneous computational and communication resources, producing the shortest possible schedule under time constraints dictated by both the application needs and the frequency of fluctuation of resource availability. this paper introduces a set of schedulers with such characteristics.
sensitivity of software system reliability to usage profile changes. usage profiles are an important factor in software system reliability estimation. to assess the sensitivity of a system's reliability to changes in the usage profile, a markov based system model is used. with the help of this model, the statistical sensitivity to many independent changes can be estimated. the theory supports both absolute and relative changes and can be used for systems with or without a terminal state. with this approach it is possible to very quickly estimate the uncertainty on the predicted reliability calculated from a markov model based upon the uncertainty on the usage profile. finally the theory is applied to an example to illustrate its use and to show its validity.
projection function for driver fatigue monitoring with monocular camera. the image projection has been proven to be an effective method for extracting image features. this paper utilizes multiple facial cues extracted by the projection function for driver vigilance monitoring. to measure vigilance, we calculate two metrics: perclos and perrotat from facial state estimation. the main advantage of the presented system in contrast to existing ones is the usage of cheap equipment (only one monocular camera) to achieve a good cost-performance ratio and fast computation time.
a decentralized infrastructure for query answering over distributed ontologies. in this paper we describe an infrastructure for query answering over distributed ontologies on the semantic web. this infrastructure addresses (i) the coordination of multiple nodes using metadata about the provided resources managed in a decentralized registry and (ii) the mediation between heterogeneous ontologies via an expressive mapping formalism along with corresponding reasoning algorithms for query answering. our approach is based on a virtual integration that exhibits a semantics as if all ontologies were integrated locally. practically, the distributed ontologies still reside on the remote peers, and only the parts relevant for answering the query need to be retrieved to the local node. experimental evaluations with the implementation in kaonp2p show that the approach is very promising, as the performance of query answering is essentially dominated by the size of the data, and only slightly affected by the degree of distribution and heterogeneity.
classstruggle: a clustering based text segmentation. this paper describes classstruggle, an algorithm for linear text segmentation on general corpuses. it relies on an initial clustering of the sentences of the text. this preliminary partitioning provides a global view on the sentences relations existing in the text, considering the similarities in a group rather than individually. classstruggle is based on the distribution of the occurrences of the members of each class. during the process, the clusters then evolve, by considering a notion of proximity and of layout in the text, in the aim to create groups that contain only sentences related to a same topic development. finally, boundaries are created between sentences belonging to two different classes. first experimental results are promising, classstruggle appears to be very competitive compared with existing methods.
new specialist tools for medieval document xml markup. the digitalization of historical text documents as a basis of data mining and information retrieval for the purpose of progress in the history sciences is urgently needed. we present a novel, specialist xml tool-suite supporting the working historian in the transcription of original medieval charters into a machine-readable form.
towards evolution of strategic it requirements. the scope of requirements engineering must include high-level business objectives and strategies to achieve traceability between it and business needs in order to ensure alignment. however, we must also deal with the evolution of business strategy. enterprise it evolution is a complex task. this paper presents the first steps in a research project that integrates two requirements engineering methodologies, b-scp and map, in order to manage evolution of strategic it. the approach is tested on a case study of seven eleven japan. we found that there are semantic similarities between b-scp and map, which facilitated their combination. map also has a gap analysis process inbuilt so this saves on the overhead of inventing a new approach. in addition, map extends b-scp's capability by the addition of non-deterministic process modelling.
web services choreography and orchestration in reo and constraint automata. currently web services constitute one of the most important topics in the realm of the world wide web. composition of web services lets developers create applications on top of service-oriented computing platforms. current web services choreography and orchestration proposals, such as bpelaws, wscdl, and wsci, provide notations for describing the message flows in web service interactions. however, such proposals remain at the description level, without providing any kind of formal reasoning mechanisms or tool support for checking the compatibility of web services based on the proposed notations. in this paper, we present our work on compositional construction of web services using the reo coordination language and constraint automata. reo is an exogenous coordinational language based on channels. we investigate the possibility of representing the behaviour of web services using constraint automata as black-box components within reo circuits. we describe the orchestration of web services by the product of corresponding constraint automata, and use reo circuits for choreography of web services. we investigate the issues of description, orchestration, and choreography of web services at a unifying abstract level, based on constraint automata, which have been used as the semantics of the coordination language reo, allowing us to derive a natural correspondence relationship between orchestration and choreography.
hierarchical alignment graph for gene teams finding on whole genomes. a new computational issue is to detect gene knowledge from comparison of two or more genomes. many researchers have studied these methods to try identify clusters of orthologous genes that have the same function in several genomes. these researches often seem simple, but the genes closely placed in the genomes of different species are produced proteins that interact each other. the problem of previous approaches is the order of genes in a gene cluster and the gaps between adjacent genes in the cluster are less than a given threshold. previous approaches between two or more genomes consider the noisy genes between two adjacent genes. we propose a new method for detecting gene clusters in two genomes using hierarchical alignment graph.
fast, accurate design space exploration of embedded systems memory configurations. the memory hierarchy is often a critical component of an embedded system. an embedded system's memory hierarchy can have dramatic impact on the overall cost, performance, and power consumption of the system. consequently, designers spend considerable time evaluating potential memory system designs. unfortunately, the range of options in the memory hierarchy (e.g., number, size, and type of caches, on-chip sram, dram, eprom, etc.) makes thorough exploration of the design space using typical simulation techniques infeasible. this paper describes a fast, accurate technique to estimate an application's average memory latency on a set of memory hierarchies. the technique is fast---two orders of magnitude faster than a full simulation. it is also accurate---extensive measurements show that 70% of the estimates were within 1 percentage point of the actual cycle count while over 99% of all estimates were within 10 percentage points of the actual cycle count. this fast, accurate technique provides the embedded system designer the ability to more fully explore the design space of potential memory hierarchies and select the one that best meets the system's design requirements.
evaluating peer-to-peer recommender systems that exploit spontaneous affinities. the validation of a recommender system is always a quite hazardous task, because of the difficulty of modeling the tastes of a given user. novel (decentralized) recommender systems are proposed and evaluated by way of well known logs of user profiles and buddy tables, that contain lists of items with feedback ratings assigned by a given set of users. these information are cross linked, and the precision of the recommendation is compared with other well known (centralized) systems. this evaluation approach cannot be applied in the actual peer-to-peer domain: it is difficult, if not impossible, to build and maintain user profiles, and users are not required to give feedbacks to a data collector entity. moreover, objects are poorly or not structured, and meta-information, when present, cannot be trusted because of fake files and incomplete item descriptions. in this paper, we present an evaluation process based on a 10-fold cross validation task, that we applied to estimate accuracy of the suggestions of a p2p recommender system recently proposed in [2]. the complexity of the evaluation of this peculiar recommender is increased because of "spontaneous affinities" between users that are used instead of classical knowledge representation based strategies.
engineering active behavior of embedded software to improve performance and evolution: an aspect-oriented approach. in this paper we propose a novel aspect-oriented scheme for implementing active behavior in embedded software with requirements on data freshness. the scheme improves system performance by combining active behavior in terms of event-condition-action (eca) rules and on-demand updating. we design and implement the scheme in terms of aspects, thereby exploiting aspect-oriented programming technology to efficiently handle crosscutting nature of active behavior. the benefits of our approach are demonstrated using a case study of an embedded database system called comet. namely, simulations on the comet database indicate that its performance increases by incorporating our scheme. furthermore, using the comet example we show that aspect-oriented implementation of active behavior has benefits when it comes to easier evolution of the system.
wellness assistant: a virtual wellness assistant using pervasive computing. the number of people over age 65 will almost double by 2030 and as they age, they generally prefer to remain in their home or go to a nursing home. there are a variety of reasons for their decision, such as convenience or a need for security or privacy. so, it is time to break through the physical boundaries of hospitals, and bring the hospital information to the homes of the elderly rather than bringing elderly folks to the hospital. despite growing requests by people to be able to take a more active part in managing their own health, wireless or internet-based healthcare devices have not been accepted for use in this area. this is probably due to the reluctance of this age group to make use of new technology, as well as the lack of reliable, individualized, or user friendly interfaces. in this paper, we discuss the challenges of developing wellness assistant (wa), software which is looking to solve some of these problems. the assistant will use pervasive computing technologies because of the availability of inexpensive handheld devices such as pdas, cell phones, and wrist watches with short range wireless capabilities. the wa can also be used by people with obesity, diabetes, or high blood pressure, conditions which need constant monitoring.
finding hierarchical heavy hitters in network measurement system. focused on identifying hierarchical heavy hitters (hhh) in multiple dimensions from network management perspective, this paper presents a framework of finding hhhs in network measurement systems and proposes a heuristic algorithm on finding static and dynamic hhh in two dimensions. our algorithm dramatically reduces the space and time complexity comparing with other previous algorithms. we implement and test it in a typical local network and the experimental results verify the effectiveness and efficiency of the algorithm.
rfid data management for effective objects tracking. radio frequency identification (rfid) applications are emerging as key components in object tracking and supply chain management systems. in next future almost every major retailer will use rfid systems to track the shipment of products from suppliers to warehouses. due to rfid readings features this will result in a huge amount of information generated by such systems when costs will be at a level such that each individual item could be tagged thus leaving a trail of data as it moves through different locations. we define a technique for efficiently detecting anomalous data in order to prevent problems related to inefficient shipment or fraudulent actions. since items usually move together in large groups through distribution centers and only in stores do they move in smaller groups we exploit such a feature in order to design our technique. the preliminary experiments show the effectiveness of our approach.
log-based indexing to improve web site search. despite the success of global search engines, web site search is still problematic in its retrieval accuracy. in this paper, we try to improve the performance of the site search by combining a new source of evidence from web server logs. we propose a novel approach of using server log analysis to extract terms to build the web page index. then, this log-based index is combined with the text-based and anchor-based index to provide a more complete view on the page content. experiments have shown that it could improve the effectiveness of the web site search significantly.
towards decentralized service orchestrations. there are several independent motivations for the implementation of decentralized execution settings for business processes that subject service compositions. this paper reports a new approach to truly decentralized orchestration of service compositions. precisely, we provide an efficient process transformation technique that converts a process conceived for centralized execution to a set of nested processes to be deployed on dynamically bound services. following the motivation that services are invokable with relevant processes, our proposition enables services to establish direct interconnections as analogous to p2p computing.
precise dynamic slicing using execution-summary. dynamic slicing helps to identify the program statements that affect a given criterion-point. existing precise slicing algorithms, like the limited-preprocessing (lp) algorithm by zhang et al. (icse 2003), operate on stored execution trace, requires much time and space if the trace is large even if the source program is small. in this paper we present a forward dynamic slicing algorithm for structured programs that reduces the overhead of slicing in the long run. for long running programs that iterates heavily on some loop, our algorithm is expected to perform faster by re-using the already computed dependences in the loop.
bionic autonomic nervous system and self-healing for nasa ants-like missions. the pam (prospecting asteroid mission) submission of the nasa concept mission ants (autonomous nano-technology swarm) involves the launch of a swarm of 1,000 autonomous pico-class spacecraft that will explore the asteroid belt. i this paper, we describe the development of a novel bans (bionic autonomic nervous system) technology with the potential to be deployed as part of the ants mission. the bans is analogous to the biological nervous system, which consists of basic modules such as cyber axons, cyber neurons, the cyber peripheral nervous system and the cyber central nervous system. equipped with the bans, the ants system would be able to self-diagnose and self-heal faults/failures and avoid possible damage or collisions. an implementation and experimental results of the bans exhibits the effectiveness and efficiency of the self-healing functions.
unichos: a full system simulator for thin client platform. thin client is a kind of interactive and graphics device in client/server and browser/server environment, which combines local and remote computing resources. the applications on the thin client (e.g., browsers) often heavily rely on the support of operating system and the functionalities of network and graphics. hence, traditional performance evaluation methods, such as instrumentation and application-level simulation, cannot help due to their inherent limitation. this paper presents the design and implementation of unichos, a full system simulator for thin client platform. unichos models the complete target hardware system in object-oriented structure, and supports the unmodified linux 2.4 kernel and graphics and network applications. unichos is the first full system simulator, which focuses on portability for more architectures of thin client platforms by combining the retargetable instruction template and the extensible device model. finally, we present the unichos performance under detailed simulation status and introduce two case studies which demonstrate the advantages of unichos for performance evaluation.
exploiting inter-gene information for microarray data integration. microarray data integration is an important yet challenging problem. usually, direct integration of microarrays after normalization is ineffective because of the diverse types of experiment specific variations. to address this issue, two novel integration approaches were proposed in recent microarray studies. the first study[16] presented a cancer classification technique which identifies gene pairs whose expression orders are consistent within class and different across classes. the other study[18] presented a promising gene expression analysis technique which utilizes pairwise correlations of gene expressions across different microarray datasets. interestingly, we observe that both of the independently developed techniques rely on inter-gene information and noise filtering strategy to achieve satisfactory performance in microarray integration. motivated by this observation, we propose in this paper a formal data model for microarray integration using inter-gene information and effective filtering, which generalizes the previous two frameworks. we also show how the proposed model can handle a broader range of problems than the previous frameworks.
a self-organising solution to the collective sort problem in distributed tuple spaces. coordination languages and models are recently moving towards the application of techniques coming from the research context of complex systems: adaptivity and self-organisation are exploited in order to tackle typical features of systems to coordinate, such as openness, dynamism and unpredictability. in this paper we focus on a paradigmatic problem we call collective sort, where autonomous agents are assigned the task of moving tuples across different tuple spaces with the goal of reaching perfect clustering: tuples of the same kind are to be collected in the same, unique tuple space. we describe a self-organising solution to this problem, where each agent moves tuples according to partial observations, still making complete sorting emerge from any initial tuple configuration.
primitives for the dynamic evolution of component-based applications. due to the coarse granularity of components-based applications, components platforms are good candidates for enabling dynamic software evolution. the luckyj platform was designed to allow the dynamic evolution of applications. it implements the three primitives load, remove and replace to modify the components set. the design and implementation of a web server outlined several evolution patterns that should be integrated in luckyj to ease the task of maintainers and developers of applications that evolve dynamically. this leads to the definition of additional primitives as well as a language that could be used to automate the updating process in such a dynamic setting.
exploiting bibliographic web services with citex. most digital libraries make extended document metadata available for the purpose of citation. this metadata has commonly been provided in human readable format, but more and more digital libraries are beginning to offer this information in convenient machine readable formats. at the same time, many advances have been made in cataloging and accessing documents and their associated metadata. we are witnessing the early evolution of bibliographic web services. in this paper we introduce an application (citex) for compiling bibliographies dynamically from bibliographic web services as they currently exist and we explore some of the challenges associated with providing bibliographic information, suggesting future paths for bibliographic web services.
using rt-uml for modelling web services. rt-uml is a uml profile for modeling real time systems, which can be used in particular to describe web services orchestration with time constraints. for that purpose, we can use a classical uml diagram, namely, the sequence diagram. our goal in this paper is the design of web services with time restriction by using rt-uml. we introduce a translation of the main elements of rt-uml into web services business process execution language.
greic data gather service: a step towards p2p production grids. current production grids involve hundreds of sites and thousands of machines. in this context, p2p solutions are well suited - with regard to existing centralized and hierarchical approaches - to implement highly scalable, decentralized, reliable and manageable grid services. in this paper we describe the greic data gather service from an architectural and technological point of view. this service has been developed within the grid relational catalog (greic) project, at the center for advanced computational technologies (cact) of the university of lecce. the greic data gather architecture aims at integrating transparently and securely distributed and geographically spread heterogeneous grid data sources through data gather service nodes connected in a p2p fashion.
on construction of a biogrid platform for parallel bioinformatics applications. in this paper, we report on implementing an experimental distributed computing application for bioinformatics consisting of basic high-performance computing environments (grid and pc cluster systems), multiple interfaces at user portals that provide useful graphical interfaces to enable biologists who are not it specialists to benefit directly from the use of high-performance technology.
a lightweight indoor location model for sentient artefacts using sentient artefacts. our approach towards context awareness is to use sensor augmented daily life objects surrounding us for extracting context information and for providing ambient services. some of these artefacts are static in nature and have designated location, like a bed in the bedroom, a refrigerator in the kitchen, etc. utilizing this characteristics, we present "spreha", a light weight hierarchical location model where static artefacts are used as reference points for identifying mobile artefacts like a chair, a watch, a lamp, etc. the model is organized in a tree structure representing the containment relationship and is independent of underlying sensing infrastructure. a prototype implementation of the model has been constructed as a pluggable module of a generic middleware using bluetooth technology. this paper discusses about the design, architecture and findings of the prototype implementation.
analysis and verification of an automatic document feeder. modern copying machines are versatile and complex systems in which embedded software plays an essential role. the progress towards faster and more stable machines that can satisfy ever growing customers' needs, places strict requirements on the efficiency and quality of such software. in order to meet these requirements, the software should be well-designed and free of errors. using modern formal verification techniques, software designs can be checked for errors and deadlocks so that their quality can be assessed and improved at an early stage of the development process. in this paper, we analyze the embedded software of an automatic document feeder (adf). adfs are important components of copier machines. the adf studied here is a prototype developed by oc&eacute;-technologies b.v., a company that develops professional printing systems. we construct a model of the adf in &mu;crl, a process algebra-based specification language, and express the system's requirements in the modal &mu;-calculus. next, we use the &mu;crl and cadp tool sets to check whether the system meets its requirements. this analysis reveals important errors in the adf and we propose solutions to these problems. also, we show that some requirements that engineers assumed to be valid, are too strict. we present slightly weaker versions of these requirements and show that these do hold. in this sense, in addition to finding errors in the adf, our analysis also led to a better understanding of the behaviour the system.
co-evolving application code and design models by exploiting meta-data. evolvability and adaptability are intrinsic properties of today's software applications. unfortunately, the urgency of evolving/adapting a system often drives the developer to directly modify the application code neglecting to update its design models. even, most of the development environments support the code refactoring without supporting the refactoring of the design information. refactoring, evolution and in general every change to the code should be reflected into the design models, so that these models consistently represent the application and can be used as documentation in the successive maintenance steps. the code evolution should not evolve only the application code but also its design models. unfortunately, to co-evolve the application code and its design is a hard job to be carried out automatically, since there is an evident and notorious gap between these two representations. we propose a new approach to code evolution (in particular to code refactoring) that supports the automatic co-evolution of the design models. the approach relies on a set of predefined metadata that the developer should use to annotate the application code and to highlight the refactoring performed on the code. then, these meta-data are retrieved through reflection and used to automatically and coherently update the application design models.
privacy preserving itemset mining through fake transactions. this work investigates the problem of privacy-preserving mining of association rules. specifically, a fake transaction randomization method is presented to protect the privacy of data. this method ensures the privacy of data by mixing real transactions with fake transactions. an algorithm for reconstructing frequent itemsets from the mixture of both fake transactions and real transactions is then proposed. the proposed algorithm can use any off-the-shelf tool to mine frequent itemsets without rewriting their codes, making this algorithm quite easy to implement. the performance of this algorithm is validated against several real datasets. similar to earlier approaches, this algorithm does not always reconstruct a set of frequent itemsets that is anti-monotonic. this work uses this property to further improve the quality of the mining results.
a model for terrain coverage inspired by ant's alarm pheromones. when looking at science and technology today, we find a recurrent problem to many fields: how to cover a search space consistently and uniformly. this problem is encountered in robotics (searching for targets), optimization (searching for solutions), mathematics and computer science (graph traversals), and even in software engineering (the main motivation for this research). in insect societies, and in particular ant colonies, one can find the concept of alarm pheromones used to indicate an important event to the society (e.g. a threat). alarm pheromones enable the society to have a uniform spread of its individuals, probably as a survival mechanism --- the more uniform the spread the better the changes of survival at the colony level. this paper proposes a model of this ant behavior which can be used to solve the aforementioned problem. the model, called alarm is inspired primarily by aco and from observations of ants alarm behavior. we compare the model with a random walk, to demonstrate a significant improvement over this approach.
deriving components from genericity. there is a growing recognition that programming platforms should support the decomposition of programs into components: independent units of compiled code that are explicitly "linked" to form complete programs. this paper describes how to formulate a general component system for a nominally typed object-oriented language supporting first-class generic types simply by adding appropriate annotations and syntactic sugar. the fundamental semantic building blocks for constructing, type-checking and manipulating components are provided by the underlying first-class generic type system. to demonstrate the simplicity and utility of this approach to supporting components, we have designed and implemented an extension of java called component nextgen (cgen). cgen, which is based on the sun java 5.0 javac compiler, is backward-compatible with existing code and runs on current java virtual machines.
comparison of two activity analyses for automatic differentiation: context-sensitive flow-insensitive vs. context-insensitive flow-sensitive. automatic differentiation (ad) is a family of techniques to generate derivative code from a mathematical model expressed in a programming language. ad computes partial derivatives for each operation in the input code and combines them to produce the desired derivative by applying the chain rule. activity analysis is a compiler analysis used to find active variables in automatic differentiation. by lifting the burden of computing partial derivatives for passive variables, activity analysis can reduce the memory requirement and run time of the generated derivative code. this paper compares a new context-sensitive flow-insensitive (csfi) activity analysis with an existing context-insensitive flow-sensitive (cifs) activity analysis in terms of execution time and the quality of the analysis results. our experiments with eight benchmarks show that the new csfi activity analysis runs up to 583 times faster and overestimates up to 18.5 times fewer active variables than does the existing cifs activity analysis.
snet: skip graph based semantic web services discovery. this paper presents the design of snet system, which is a p2p overlay for semantic web services discovery. snet differs from previous p2p web services discovery systems in that it supports complex search with its locality-preserving feature based on skip graph. to guarantee efficient and semantic service discovery, snet schemes wsdl-s as semantic web services description language and extracts its semantic attributes as indexing keys in skip graph so that similar keys are aggregated to keep the leverage between peer nodes. our evaluation showed that the snet system performs considerable service discovery efficiency.
ic-service: a service-oriented approach to the development of recommendation systems. recommendation systems have proven to be useful in various application domains. however, current solutions are usually ad-hoc systems which are tightly-coupled with the application domain. we present the ic-service, a recommendation service that can be included in any system in a loosely coupled way. the implementation follows the principles of service oriented computing and provides a solution to various problems arising in recommendation systems, e.g. to the problem of meta-recommendation systems development. moreover, when properly configured, the ic-service can be used by different applications (clients), and several independent instances of the ic-service can collaborate to produce better recommendations. service architecture and communication protocols are presented. the paper describes also ongoing work and applications based on the ic-service.
a crime simulation model based on social networks and swarm intelligence. experience in the domain of criminology has shown that spatial data distribution of crime in urban centers follows a zipf law in which few places concentrate most of the crimes while several other places have few crimes. in order to reproduce and better understand the nuances of such a crime distribution profile, we introduce in this paper a novel multi-agent-based crime simulation model that is directly inspired by the swarm intelligence paradigm. in this model, criminals are regarded as distributed entities endowed with the capability to pursue self-organizing behavior by considering their individual (local) activities as well as the influence of other criminals. through controlled experiments with the simulation model, we could indeed observe that self-organization phenomena (i.e. criminal behavior toward crime) emerge as the result of both individual and social learning factors. at the same time, our experiments reveal that the spatial distribution of crime achieved by experimenting with the simulation model closely follows the real crime data distribution as expected.
model transformation for object-relational database development. in this paper we define and formalize the model transformations that complete the methodological approach for the development of object-relational (or) databases (db) proposed in midas, a model driven methodology for the development of web information systems. in this proposal the platform independent model is the conceptual data model while the platform specific model is the object-relational model that represents the or db schema. since both of them will be represented in uml, we also summarize an uml profile for or db modeling. in this work we focus on the formalization of the mappings needed to get the or db schema from the conceptual data model. we have first specified them with natural language to later formalize them with graph transformation rules.
automatic enactment of message exchange pattern for web services. message exchange pattern (mep) is a challenging problem in the interaction of web services. however, by means of the non-formal descriptions, such as in soap and wsdl, it is impossible to conduct precise definition of meps, thus leading to potential ambiguities that can degrade the interoperability of web services. moreover, it is difficult to enact the meps automatically, which means the web services infrastructure has to hard-code the support for various meps and it is also difficult to be extended. in this paper, we propose an automatic enactment of meps for web services. the enactment consists of two parts. the first part is the formal description method for meps, which is used to define mep accurately with no ambiguities. the second part is the automatic enactment framework, which will automatically enact a new mep through a mep process machine that is generated according to the mep definition. new meps would become easy to be engaged in web services.
developing event-condition-action rules in real-time active database. traditional event-condition-action (eca) rules in real-time active database (rtadb) lack the capabilities to express complicated quantitative temporal information in the system. to solve this problem, in this paper, we present graphical eca rules with a set of novel temporal events to specify real-time constraints. smart home applications are used to validate the proposed rules.
mechanized proofs for the parameter abstraction and guard strengthening principle in parameterized verification of cache coherence protocols. chou, mannava, and park proposed a novel method for verification of safety properties of cache protocols, which is underpinned by the principle of parameter abstraction and guard strengthening. however, no one has formally proved the correctness of this method itself. in this work, we want to fill the gap in the literature. we believe that our work provides an alternative to formally justify this method. the key points of our theory are symmetry and the introduction of an intermediate guard strengthening protocol. we mechanize our theory in isabelle/hol.
how sensitive is your personal information? the sensitivity of personal information is one of the most important factors in determining the individual's perception of privacy. a "gradation" of sensitivity of personal information can be used in many applications, such as deciding the security level that controls access to data and developing a measure of trust when self-disclosing personal information. this paper introduces a theoretical analysis of personal information sensitivity and defines its scope and puts forward possible methods of gradation. a methodology is proposed that can be used for developing a classification scheme of personal information.
building automatic mapping between xml documents using approximate tree matching. the extensible markup language (xml) is becoming the standard format for data exchange on the internet, providing interoperability among web applications. it is important to provide efficient algorithms and tools to manipulate xml documents that are ubiquitous on the web. in this paper, we present a novel system for automating the transformation of xml documents based on structural mapping with the restriction that the leaf text information are exactly the same in the source and target documents. firstly, tree edit distance algorithm is used to find the mapping between a pair of source and target documents. with the introduction of tree partition, the efficiency of the tree matching algorithm has been improved significantly. secondly, template rules for transformation are inferred from the mapping using generalization. thirdly, a template matching component is used to process new documents. experimental studies have shown that our methods are very promising and can be widely used for web document cleaning, information filtering, and other applications.
horizontal fragmentation as a technique to improve the performance of drill-down and roll-up queries. in this paper, we focus on the horizontal fragmentation of data warehouses. our main contribution is the proposal of the mhf-dha algorithm, which is aimed at improving the performance of drill-down and roll-up queries by horizontally fragmenting data warehouses organized in different levels of aggregation. besides allowing that multiple dimensions be used as a basis for the fragmentation, the algorithm also explores the hierarchical structure of these dimensions. the performance tests carried out using the tpc-h benchmark showed that the proposed fragmentation provides a huge improvement on the query performance, with a reduction in elapsed time and disk accesses between 71% and 99%.
different conceptions in software project risk assessment. during software project risk management, a number of decisions are taken based on discussions and subjective opinions about the importance of identified risks. in this paper, different people's opinions about the importance of identified risks are investigated in a controlled experiment through the use of utility functions. engineering students participated as subjects in the experiment. differences have been found with respect to the perceived importance, although the experiment could not explain the differences based on undertaken role in a development course.
using cp-nets as a guide for countermeasure selection. in this paper we present a qualitative approach for the selection of security countermeasures able to protect an it system from attacks. for this purpose, we model security scenarios by using defense trees (an extension of attack trees) and preferences over countermeasure using conditional preference networks (cp-nets for short). in particular, we introduce two different methods for the composition of preferences: the and-composition and the or-composition. the first one is used to determine a preference order in the selection of countermeasures able to mitigate the risks produced by conjunct attacks. the second one is used to determine a preference order over sets of countermeasures able to mitigate the risks produced by alternative attacks.
integrating gene ontology into discriminative powers of genes for feature selection in microarray data. one of the main challenges in the classification of microarray gene expression data is the small sample size compared with the large number of genes, so feature selection is an essential step to remove genes not relevant to class labels. most feature selection methods are solely based on expression values to determine discriminative values of genes and remove redundancy. however, due to the characteristics of microarray technology, some values may not be accurately measured. this may reduce the effectiveness of these models. to cope with this problem, in this paper, we integrate gene ontology (go) annotations into gene selection. the novelty of our work is to evaluate genes based on not only their individual discriminative powers but also the powers of go terms that annotate them. this strategy implicitly verifies the accuracies of the measurements and reduces redundancy. experimental results in four public datasets demonstrate the effectiveness of the proposed method.
improved svd-dwt based digital image watermarking against watermark ambiguity. singular value decomposition (svd) has been used as a valuable transform technique for robust digital watermarking. this arises from the fact that, changing singular values (sv) of an image slightly does not affect the image quality much. in some svd based methods, svs of the watermark are embedded into svs of the cover image. then in detection, the watermark is constructed by using original singular vectors. if the singular vectors of another image rather than the original watermark are used, that image is constructed as the embedded watermark, causing the false positive probability to be one. in this paper, we propose a technique against this ambiguity by embedding the singular vectors of the watermark image as a control parameter. we discuss the performance of the proposed method against some attacks.
mapping visual notations to mof compliant models with qvt relations. model-centric methodologies rely on the definition of domain-specific modeling languages for being able to create domain-specific models. with mof the omg adopted a standard which provides the essential constructs for the definition of semantic language constructs (abstract syntax). however, there are no specifications on how to define the notations (concrete syntax) for abstract syntax elements. usually, the concrete syntax of mof compliant languages is described informally. we propose to define mof-based metamodels for abstract syntax and concrete syntax and to connect them by model transformations specified with qvt relations in a flexible, declarative way. using a qvt based transformation engine one can easily implement a model view controller architecture by integrating modeling tools and metadata repositories
deriving cse-specific live forensics investigation procedures from forza. performing live forensics investigation becomes a trend in digital forensics. different vendors and software developer implement their own investigation procedures. by applying forza framework -- a digital forensics investigation framework, investigation requirement could be translated and formulated into criteria in applying appropriate forensics investigation requirement. through this model, only necessary searching would be applied to live investigation process instead of simply passing all investigation process to live investigation unintentionally. in this paper, the forza framework that applied to live forensics investigation will be presented and illustrated using the investigation of the first bt illegal movie upload investigation.
a framework for prioritized reasoning based on the choice evaluation. this work addresses the issue of prioritized reasoning in the context of logic programming. the case of preference conditions involving atoms is considered and a refinement of the comparison method of the answer set optimization semantics [4] is presented. the paper introduces the concept of choice, as a set of preference rules describing common choice options in different contexts. thus, intuitively, in the proposed approach the preference rules are not evaluated separately; but the subset of rules, related to the same choice are individuated and the choice instead of rule satisfaction is considered. the role of constraints in the feasibility of choice options is then investigated and an alternative semantics, evaluating choices on the basis of their really possible (allowed) options, is developed. complexity analysis is also performed showing that the introduction of choices does not increase the complexity of computing preferred stable models.
parallel algorithms on geometric constraint solving. in this paper, we try to speed up geometric constraint solving with parallel techniques. we propose parallel algorithms for building rule-bases, judging the under(over)-constrained problems, and finding construction sequences of geometric constraint problems. experiment results show that the parallel algorithm can improve the efficiency of geometric constraint solving.
investigating adaptive mutation in the generalized generation gap (g3) algorithm for unconstrained global optimization. for function optimization problems in continuous search spaces, one of the main difficulties currently faced is that of locating high quality solutions. this problem is particularly pertinent for continuous multimodal problems where the quality rather than computational efficiency is more important as a test of the solver's ability to escape local optima and finding solutions near the global optimum [3]. moreover, this difficulty is further compounded when the function involves large numbers of variables, which translates into a highly deceptive fitness landscape with very large numbers of local optima [2].
compact sequential aggregate signatures. in this paper, a new notion which we call compact sequential aggregate signatures is introduced and formalized. informally, a compact sequential aggregate signature states the following thing: for a given message vector m=(m1, &middot; &middot; &middot; m&iota;), a public key vector pk=(pk1, &middot; &middot; &middot; , pk&iota;) and a path p=(v1, &middot; &middot; &middot; , v&iota;), where vi=(idi, pki), the size of the third component &sigma; in a sequential aggregate signature (m, p, &sigma;) is independent of the path length &iota; we propose a novel implementation of rsa-based regular signature scheme that works in an extended domain, and then transform it into a compact sequential aggregate signature scheme that works in a common domain such that the size of overflow bits is independent of the path length &iota; finally, we show that our implementation is provably secure in the random oracle model assuming that the rsa problem is hard.
web service orchestration and verification using msc and cp nets. designing web services-based processes (wsp) requires striking the balance between intuitive and easy to understand process representation for the interactive domain user and consolidated formal mathematical specification. an easy to understand process representation facilitates conformance of process correctness where as the formal mathematical specification ensures formal verification of service orchestration for executing the process. orchestration of services involves overall service design, service selection, and composition of services to achieve the overall goal. in this paper we present a novel approach to service orchestration that combines an effective diagrammatic modeling, an appropriate formal framework and an implementation process for dynamic wsp and complex web service composition and verification. specifically we introduce a new approach for wsp design and verification comprising of service orchestration using high level message sequence charts (hmsc) and colored petri nets (cp nets) that provides a methodology for analysis and verification at a process level as well as the service level.
semi-supervised single-label text categorization using centroid-based classifiers. in this paper we study the effect of using unlabeled data in conjunction with a small portion of labeled data on the accuracy of a centroid-based classifier used to perform single-label text categorization. we chose to use centroid-based methods because they are very fast when compared with other classification methods, but still present an accuracy close to that of the state-of-the-art methods. efficiency is particularly important for very large domains, like regular news feeds, or the web. we propose the combination of expectation-maximization with a centroid-based method to incorporate information about the unlabeled data during the training phase. we also propose an alternative to em, based on the incremental update of a centroid-based method with the unlabeled documents during the training phase. we show that these approaches can greatly improve accuracy relatively to a simple centroid-based method, in particular when there are very small amounts of labeled data available (as few as one single document per class). using one synthetic and three real-world datasets, we show that, if the initial model of the data is sufficiently precise, using unlabeled data improves performance. on the other hand, using unlabeled data degrades performance if the initial model is not precise enough.
incremental discretization, application to data with concept drift. in this paper we present a method for incremental discretization able to be adapted to gradual changes in the target concept. the proposed method is based on the partition incremental discretization (pid for short). the algorithm divides the discretization task in two layers. the first layer receives the sequence of input data and retains some statistics of the data using more intervals than required. the second layer computes the final discretization, based in the statistics stored by the first layer. the method is able to process streaming examples in a single scan, in constant time and space even for infinite sequences of examples. in dynamic environments the target concept can gradually change over time. past examples may not reflect the actual status of the problem. to accommodate concept drift we use an exponential decay that smoothly reduces the importance of older examples. experimental evaluation on a benchmark problem for drift environments, clearly illustrates the benefits of the weighting examples technique.
modeling business processes in web applications: an analysis framework. the addition of business processes to modern web applications entails new challenges to be faced when developing them, hence the need for suitable methodologies to be adopted in the design phase. in response to this need, most of the design methodologies for web application available in the literature include a proper solution. in this paper we propose a framework for analyzing and comparing web application design methodologies with regard to their support for modeling business processes. the analysis framework has proved to be useful for assessing the ability of each considered methodology to deal with the design of business processes in web applications. the framework also provides suggestions on how to possibly enhance a given methodology.
remotefs: accessing remote file systems for desktop grid computing. we propose a remote file system for use in desktop grid applications. the proposed system provides programs with the ability to query and update files on remote machines without requiring any changes to the program code. the system (a) generates a profile of the program file operations and (b) uses the profile to implement collective and pre-fetched i/o.
toward a first-order extension of prolog's unification using chr: a chr first-order constraint solver over finite or infinite trees. prolog, which stands for programming in logic, is the most widely used language in the logic programming paradigm. one of its main concepts is unification. it represents the mechanism of binding the contents of variables and can be seen as solving conjunctions of equations over finite or infinite trees. we present in this paper an idea of a first-order extension of prolog's unification by giving a general algorithm for solving any first-order constraint in the theory t of finite or infinite trees, extended by a relation which allows to distinguish between finite and infinite trees. the algorithm is given in the form of 16 rewriting rules which transform any first-order formula &phi; into an equivalent disjunction &phiv; of simple formulas in which the solutions of the free variables are expressed in a clear and explicit way. we end this paper describing a chr implementation of our algorithm. chr (constraint handling rules) has originally been developed for writing constraint solvers, but the constraints here go much beyond implicitly quantified conjunctions of atomic constraints and are considered as arbitrary first-order formulas built on the signature of t. we discuss how we implement nested local constraint stores and what programming patterns and language features we found useful in the chr implementation of our algorithm.
automatic web pages categorization with relieff and hidden naive bayes. a great challenge of web mining arises from the increasingly large web pages and the high dimensionality associated with natural language. since classifying web pages of an interesting class is often the first step of mining the web, web page categorization/classification is one of the essential techniques for web mining. one of the main challenges of web page classification is the high dimensional text vocabulary space. in this research, we propose a hidden naive bayes based method for web page classification. we also propose to use the relieff feature selection method for selecting relevant words to improve the classification performance. comparisons with traditional techniques are provided. results on benchmark dataset show that the proposed methods are promising for accurate web page classification.
extending business process management to determine efficient it investments. in many sectors, companies model and optimize their business processes in order to better manage the external value that comes from these processes. supporting the execution of corporate business processes with an optimal set of it investments is crucial to a company's success. however, existing business process management (bpm) approaches do not integrate methods for evaluating and selecting efficient it investments and traditional evaluation methods are often inadequate. this paper proposes an extension that aims at a more adequate valuation, allocation, and selection of it investments with respect to the requirements of the given corporate business processes. such an extension allows decision makers in process-oriented organizations to interactively determine and continually optimize it investments. at the same time, the extension improves the decision makers' awareness of the efficiency of their investments and, thus, reduces the gap between technology and business by further completing the traditional bpm methodology. this paper implements such an approach in a decision support system and illustrates its application by means of an example.
handling heterogeneity in rosettanet messages. we present a semantic b2b gateway based on the wsmx semantic service-oriented architecture to tackle heterogeneities in rosettanet messages. we develop a rich rosettanet ontology and use the axiomatised knowledge and rules to resolve data heterogeneities and to unify unit conversions. we use adaptive executable choreography definitions to easily integrate new sellers into existing rosettanet collaborations.
integration of it service management into enterprise architecture. enterprise architecture supports organizational engineering in many ways. service orientation is regarded as dominant operations model for service providers -- within and beyond it. as a consequence, it is important to integrate service management and service orientation into enterprise architecture. this paper proposes an enterprise architecture extension that achieves such an integration. it service management is defined according to itil. based on the integration of service management into enterprise architecture, the integration of service oriented architecture is discussed as a further extension. the research is based on the business engineering approach and the guidelines of method engineering.
design of a simple and effective object-to-relational mapping technique. currently, most object-oriented applications use relational databases to meet their needs for persistent storage. however, object-oriented and relational paradigms represent information in manners that are quite different from each other. this results in two different models for representing the same information, thus increasing the design and maintenance efforts. several attempts have been made to overcome this impedance mismatch but all of them have fallen short of providing satisfactory results from one aspect or the other. this paper outlines a simple and straightforward approach to effectively overcome this challenge. our methodology yields a data model that is mechanically derived from the object model without compromising the performance of the system. the physical schema and the basic object persistence and population operations are automatically generated, thus, resulting in a system that makes design and maintenance much easier tasks than before.
an efficient dynamic memory allocator for sensor operating systems. dynamic memory allocation mechanism is important aspect of operating system, because an efficient dynamic memory allocator improves the performance of operating systems. in wireless sensor networks, sensor nodes have miniature computing device, small memory space and very limited battery power. therefore, sensor operating systems should be able to operate efficiently in terms of energy consumption and resource management. and the role of dynamic memory allocator in sensor operating system is more important than one of general operating system. in this pager, we propose new dynamic memory allocation scheme that solves problems of existing dynamic memory allocators. we implement our scheme on nano-qplus which is a sensor operating system base on multi-threading. our experimental results show our scheme performs efficiently in both time and space compared with existing memory allocation mechanism.
a global marking scheme for tracing cyber attacks. tracing complex attacks is among the research topics that are currently under development. limiting tracing to network traffic has allowed the reconstruction of the attack paths of a few attacks, but appears to be insufficient to trace complex attacks. in this paper, we propose a new tracing scheme that extends marking to additional malicious activities related to system running processes and modification actions operated at the host level, making use of compromise independent disk based components. these components are involved in the marking and the tracing process. the behavior of the new scheme for marking and tracing is illustrated against a sample attack scenario that integrates several techniques in order to increase the complexity of the attack. our scheme plays an important role in investigation and provides evidences that help an investigator determining the attacker and the actions he performed.
three integration approaches for map and b-scp requirements engineering techniques. integration of requirements engineering techniques has been common and proven beneficial. map is a strategy-driven modelling technique that elicits requirements in terms of intentions and strategies. b-scp is an approach to address alignment between requirements and business strategy. to address the problem of strategic requirements evolution in b-scp, we have previously proposed the possibility of integrating map with b-scp. in this paper, we present three integration approaches for map and b-scp and evaluate their usefulness for two case studies: seven eleven japan (sej) and commsec australia. sej presents an enterprise problem domain, while commsec australia presents a simple application domain. we find that each integration approach has advantages and disadvantages. we also conclude that the usefulness of each integration approach varies depending on the complexity of application domain and the nature of modelled requirements.
checking software component behavior using behavior protocols and spin. using software components is a modern approach for building extensible and reliable applications. to ensure high dependability, a component application should undergo verification, e.g. model checking, to prove it has certain properties. the implementation of an application is usually too complex to be verified at a formal level; therefore, a model being an abstraction of the implementation is to be used. behavior protocols [11] are a platform for modeling of software component behavior. in this paper, we propose a method for translation behavior protocols to promela [7], which is consequently used as the input for the spin model checker [7]. having the promela code describing the component behavior, one can efficiently check for the behavior compatibility and ltl (linear temporal logic) properties of cooperating software components.
formal verification of security specifications with common criteria. this paper proposes a formalization and verification technique for security specifications, based on common criteria. generally, it is difficult to define reliable security properties that should be applied to validate an information system. therefore, we have applied security functional requirements that are defined in the iso/iec 15408 common criteria to the formal verification of security specifications. we formalized the security criteria of iso/iec 15408 and developed a process, using z notation, for verifying security specifications. we also demonstrate some examples of the verification instances using the theorem prover z/eves. in the verification process, one can verify strictly whether specifications satisfy the security criteria defined in iso/iec 15408.
energy management for interactive applications in mobile handheld systems. the usage of interactive applications increases in handheld systems. in this paper, we describe a system-level dynamic power management scheme that considers interaction between the cpu and the wnic, and interactive applications to reduce the energy consumption of handheld systems. previous research efforts considered the cpu and the wnic separately to reduce energy consumption. the proposed scheme reduces the energy consumption of handheld systems by using the information gathered from the wnic to control the cpu voltage and frequency when interactive applications are executed. experimental results show that on average the proposed scheme reduces energy consumption by 46% when compared to dvfs (dynamic voltage and frequency scaling) for the cpu and dpm (dynamic power management) for the wnic.
trust-based service provider selection in open environments. the problem of selecting correct counterparts to interact with is of particular relevance in open and dynamic environments. this problem increases when third parties may vary their behaviour at will. in this paper we examine the problem of service provider selection using trust and reputation techniques. most approaches to service provider selection are based on the client's proper experiences about particular services from particular providers. a problem arises when no previous experience is available. to solve this problem, previous approaches have proposed that clients obtain the required reputation information from their acquaintances. in contrast, our work advocates an experience-based approach for service provider selection, in which clients use trust and reputation mechanisms to infer expectations of future providers' behaviour from past experiences in similar situations. we present some experimental results that support our proposal.
combining cybernetics and conceptual modeling: the concept of variety in organizational engineering. organizational engineering addresses various aspects of changing organizations in order to create and keep the alignment between business and information technology (it). in this paper, we show how the combination of cybernetic theories with conceptual modeling contributes to the analysis and design of information systems and organizations. based on the discussion of a language-driven understanding of information systems as socio-technical systems, we show how conceptual models can significantly contribute to organizational engineering if used in combination with the concept of variety, an established theory from cybernetics. within an it controlling case, we show how our approach can be applied to the diagnosis of an it controlling and reporting system in the german subsidiary of a large european bank.
designing a trust chain for a thin client on a live linux cd. cd-boot linuxi is a live linux environment, which is easy to use because it is not installed in the hard disk, but simply boots directly from a cd. this helps protect the sensitive information because a clean environment can be prepared at boot time. to insure this environment protects sensitive information, we adapted the trusted computing technology to define a trustworthy environment.
reifying wildcards in java using the ego approach. providing runtime information about generic types---that is, reifying generics---is a challenging problem studied in several research papers in the last years. however, the quest for finding effective and efficient solutions specifically targeted to the java programming language is still open. in particular, the new mechanism of wildcards introduced in java 5.0 significantly complicates the overall semantics of generics: its reification aspects are currently unexplored and pose serious implementation issues. in this paper we analyse such issues and study how they have been supported in the context of the ego compiler. ego is an approach for efficiently supporting runtime generics at compile-time in java: synthetic code is automatically added to the source code by the compiler, so as to create generic runtime type information on a by-need basis, store it into object instances, and retrieve it when necessary in type-dependent operations. we show how the design of ego has been completely and successfully extended to represent wildcard types, and how we deal with subtle issues concerning subtyping, capture conversion and wildcards capture in method calls.
mining itemsets in the presence of missing values. missing values make up an important and unavoidable problem in data management and analysis. in the context of association rule and frequent itemset mining, however, this issue never received much attention. nevertheless, the well known measures of support and confidence are misleading when missing values occur in the data, and more suitable definitions typically don't have the crucial monotonicity property of support. in this paper, we overcome this problem and provide an efficient algorithm, xminer, for mining association rules and frequent itemsets in databases with missing values. xminer is empirically evaluated, showing a clear gain over a straightforward baseline-algorithm.
fighting pollution dissemination in peer-to-peer networks. recent studies reported a new form of malicious behavior in popular file-sharing peer-to-peer (p2p) systems, namely, content pollution, which reduces content availability, decreasing the confidence of users in such systems. this paper proposes scrubber, a new descentralized peer reputation system that imposes severe and quick punishment to content polluters but also promotes peer rehabilitation. we evaluate the efficiency of scrubber in reducing pollution dissemination via simulation, comparing it against the previously proposed credence object reputation system as well as a system without reputation. two pollution mechanisms, namely, decoy insertion and identifier corruption, are considered. our results show that, for various scenarios, scrubber is able to quickly reduce the fraction of daily downloads to polluted content to a small percentage. if compared to credence, scrubber has a much better convergence and competitive maximum efficiency, unless the fraction of peers that delete their polluted content in response to punishment (i.e., download request refusals) is very small (under 25%). in this case, credence achieves a slightly higher efficiency in the long run.
defining personalized therapies for handheld devices. this paper presents a framework that provides psychotherapists with means to tailor specific therapies for their patients. used artifacts can be easily adapted to the patient's problem, to his evolution rhythm, therapy stage or even to possible filling in situations. furthermore, the artifacts can be configured to proactively adapt to the patient's behavior, according to previously defined rules, extending the therapist's motivating role. the framework ranges from desktop computers, to mobile devices (e.g. pdas and tabletpcs) covering therapeutic tasks for both patient and therapist.
biased box sampling - a density-biased sampling for clustering. this paper presents the bbs - biased box sampling algorithm, a technique that combines dimensionality reduction with biased sampling, which aims at keeping the skewed clustering from the original data.
towards resource-certified software: a formal cost model for time and its application to an image-processing example. visual tracking requires sophisticated algorithms working in real-time, and often space-limited, settings. while the input streams may be regular in structure, the algorithms are not, and must often deal with probabilistic metrics. to ensure progress in algorithm design without incurring excessive development costs, we propose a high-level programming approach married with predictable and compositional performance metrics. this enables the combination of independently developed program components into coherent software architecture, with certified resource use guarantee. here, we present our approach and discuss its application to the development and resource analysis of a space bound mean shift algorithm for motion tracking, using the new embedded system-oriented language hume.
an additive-attack-proof watermarking mechanism for databases' copyrights protection using image. this paper discusses the feasibility of embedding a bit map image (bmp file) into the relational databases for protecting data's copyrights and the term of wdi (watermarking databases using image) is proposed. an error correction approach of bch (bose-chaudhuri-hocquenhem) coding is used for enhancing the robustness of the algorithms. and a trusted third party (ttp), which can trigger watermarking mobile agents to insert and detect watermark, is introduced to resist the additive attack and invertibility attack. further more, we also analyze the resilience of the algorithm theoretically based on the principles of statistics in detail. experiments showed that the approach proposed in this paper is robust to many kinds of attacks so that the copyrights can be effectively protected.
dimensionality reduction for long duration and complex spatio-temporal queries. in this paper we present an approach to mine and query spatio-temporal data with the aim of finding interesting patterns and understanding the underlying data generating process. an important class of queries is based on the flock pattern. a flock is a large subset of objects moving along paths close to each other for a certain pre-defined time. one approach to process a "flock query" is to map spatio-temporal data into a high dimensional space and reduce the query into a sequence of standard range queries which can be presented using a spatial indexing structure. however, as is well known, the performance of spatial indexing structures drastically deteriorates in high dimensional space. in this paper we propose a preprocessing strategy which consists of using a random projection to reduce the dimensionality of the transformed space. our experimental results show, for the first time, the possibility of breaking the curse of dimensionality in a spatio-temporal setting.
using control-flow patterns for specifying business processes in cooperative environments. the representation and execution of business processes have generated some important challenges in computer science. an important related concern is the choosing of the best formal foundation to specify processes behavior, mainly representing control-flow patterns in cooperative environments. the first contribution of this research is the complete definition of the navigation plan definition language (npdl) as an alternative for business process managing in cooperative environments. the second contribution is a complete implementation of control-flow patterns using npdl. these control-flow patterns have been proposed by aalst's group. our experience in applying suggestion of aalst's group to use control-flow patterns as a basis for comparison among control-flow specification languages shows that this comparison method is feasible and the results are useful. the simplicity of npdl representations shows the advantages of npdl as a process specification language. npdl uses a declarative specification (similar to process algebra) to describe the workflow and adds new operators to compensate for the limitations of process algebra and petri nets. npdl also increases the modeling flexibility by allowing the reuse of process expressions in relational data-base systems.
providing context-awareness to virtual file system. in ubiquitous environment, adaptive applications require the context-aware data access. this paper proposes a backward-compatible, context-aware virtual file system (cavfs). users can find a file by the context without remembering full path. since cavfs supports the full backward compatibility, users can even browse hierarchically with the legacy path name, and the legacy applications can access the flies in a context-aware way. we implement cavfs in linux kernel 2.6.7-21. the experiments show that the overhead to maintain the context is reasonably small.
towards secure resource sharing for impromptu collaboration in pervasive computing. access control in mobile and pervasive computing is a complex issue, with many aspects relating to the establishment, management, and enforcement of methods and policies that allow mobile devices to share resources with each other. communication between mobile devices can arise spontaneously, involve the sharing of few resources between heterogeneous platforms, and only need to be maintained for a short time. additionally, the devices often communicate with each other a single time, and have no pre-shared secret or a priori knowledge of the other device. in this paper we propose a secure solution for providing controlled access to local resources in mobile and pervasive computing environments. our solution incorporates demonstrative verification of security credentials, a key-based capability delegation, and easy to use access control features in order to provide simple access with low maintenance costs. it is particularly designed for one-time-only communication between mobile-to-mobile or mobile-to-kiosk devices.
supporting effective unexpected exceptions handling in workflow management systems. this paper proposes a novel architectural framework handling effective unexpected exceptions in workflow management systems (wfms). effective unexpected exceptions are events for which the organizations lack handling strategies. unstructured human interventions are necessary to overcome these situations, but clash with the type of model control currently exercised by wfms. the proposed framework uses the notion of map guidance to orchestrate these human interventions. map guidance empowers users with contextual information about the wfms and environment, enables the interruption of model control on the affected instances, supports collaborative exception handling and facilitates regaining model control after the exception has been resolved. the framework implementation in the open symphony open source platform is also described.
extending the epc with performance measures. the event-driven process chain (epc) is designed for modelling business processes, but does not yet include any means for measuring the performance of a business process. thus, we extend the metamodel of the epc with performance measures to make them conceptually visible. the extensions are tested with an example business process.
fat-miner: mining frequent attribute trees. data that can conceptually be viewed as tree structures abounds in domains such as bio-informatics, web logs, xml databases and multi-relational databases. besides structural information such as nodes and edges, tree structured data also often contains attributes, that represent properties of nodes. current algorithms for finding frequent patterns in structured data, do not take these attributes into account, and hence potentially useful information is neglected. we present fat-miner, an algorithm for frequent pattern discovery in tree structured data with attributes. to illustrate the applicability of fat-miner, we use it to explore the properties of good and bad loans in a well-known multi-relational financial database.
efficient code size reduction without performance loss. for many embedded applications, program code size is a critical design factor for its relationship with limited memory, energy and communication bandwidth. while pursuing better code redundancy elimination in compilation time, people also began to focus on better encoding. some risc processors, such as arm, mips and unicore, support a 32bit/16bit dual-width instruction set. mixed code generation is introduced in expectation of achieving both higher code density from the 16-bit instruction set and good performance from the 32-bit one, with little extra cost. we describe a new fine-grained mixed code generation scheme in this paper. we introduce into the 32-bit isa a new 16-bit mode-changing instruction set which has the following features: firstly, the operation of the instructions are very common in unicore32 programs and are appropriate to be coded into 16 bits; secondly, they can switch the current processor mode while performing their own operations. we implement the mixed code generation at link time in our compilation toolchain. our experiments show that this scheme is successful in better encoding a program's computations to reduce code size without sacrificing performance. in addition, there are little modifications to micro-architecture, ensuring good compatibility with the original instruction set architecture.
exploring olap aggregates with hierarchical visualization techniques. this paper presents an approach to exploring multidimensional data cubes with hierarchical visualization techniques. analysts interact with data in a predominantly "drill-down" fashion, i.e. from coarse grained aggregates towards the desired level of detail. we suggest that visual hierarchies are adequate for mapping the multiscale nature of decomposition as they preserve the results of the entire interaction. we introduce a class of visual structures called enhanced decomposition tree. every tree level is created by a disaggregation step along a chosen dimension, the nodes contain the corresponding sub-aggregates arranged into a chart and the edges are labeled with their dimensional values. various layouts are proposed to account for different analysis tasks. data cubes are queried using a schema-based browser which presents dimensions by the hierarchies of their granularity levels, thus offering an efficient way of generating hierarchical visualizations. multiple data cubes may be explored in parallel along their shared dimensions. the power of our approach is exemplified using a real-world study from the domain of academic administration.
passwords decay, words endure: secure and re-usable multiple password mnemonics. research on password authentication systems has repeatedly shown that people choose weak passwords because of the difficulty of remembering random passwords. moreover, users with multiple passwords for unrelated activities tend to choose almost similar passwords for all of them. many password schemes have been proposed to alleviate this problem, but they either require modification to the password entry and processing infrastructure (e.g., graphical passwords) or they require the user to have some trusted computing power (e.g., smartcard-like portable devices, browser plugins, etc). we propose a scheme that is applicable to any existing system without any modification, as it does not require any form of involvement from the service provider (e.g., bank, brokerage). nor does it require the user to have any computing device at hand (not even a calculator). our approach consists of generating a mnemonic sentence that helps the users remember a multiplicity of truly random passwords, which are independently selected. the scheme is such that changes to passwords do not necessitate a change in the mnemonic sentence that the user memorizes. hence, passwords can be changed without any additional burden on the memory of the user, thereby increasing the system's security. an adversary who breaks one of the passwords encoded in the mnemonic sentence does not gain information about the other passwords. a key idea is to split a password in two parts: one part is written down on a paper (helper card), another part is encoded in the mnemonic sentence. both of these two parts are required for successfully reproducing the password, and the password reconstruction from these two parts is done using only simple table lookups. passwords' renewal requires only the re-generation of the helper card. our scheme resolves the apparent contradictory requirements from most password policies: that the password should be random, and that it should be memorized and never written down. this makes possible passwords that are more secure against an adversary who illicitly gains access to the password file, as a dictionary attack is now unlikely to succeed (the attacker now needs to carry out a more daunting brute force enumerative attack). even if the adversary somehow obtains the helper card, it gets quantifiably limited information about the passwords of the user (so the helper card may be lost or stolen without disaster immediately striking the user). we quantify the time period required for this adversary to successfully crack the password.
maintenance of maximal frequent itemsets in large databases. there have been many studies on efficient discovery of maximal frequent itemsets in large databases. however, it is nontrivial to maintain such discovered itemsets if more and more data is inserted into the database as the insertions may invalidate some existing maximal frequent itemsets and also create some new ones. in this paper, we clearly address the relationships between old and new maximal frequent itemsets and propose an algorithm imfi, which is based on these relationships to reuse previously discovered knowledge. the algorithm follows a top-down mechanism rather than traditional bottom-up methods to produce fewer candidates. moreover, we integrate sg-tree into imfi to improve the counting efficiency, which is faster than those methods based on vertical bitmap database representation. evaluations on imfi have been performed using both synthetic and real databases. preliminary results show that applying imfi is always much faster than an available incremental mfi mining algorithm, especially when it is equipped with sg-tree.
constructing machine emulator on portable microkernel. in this paper, we present a new model of virtual execution environment, a flexible machine emulator with dynamic translator constructed on a portable microkernel. our model offers both high portability and compatibility. moreover, its flexible interface could be reconfigured to support various types of hardware interfaces.
modeling biomedical assertions in the semantic web. we present an enhanced version of an ontological framework called machineprose that is meant to represent the evolving knowledge resulting from biomedical research. this framework bridges the semantic gap between the use of keywords or controlled vocabularies to index articles and the expressive free-text content of research papers. the benefits of the framework are the ability to carry out precise searches to retrieve relevant literature, and novel abilities to provide answers to questions. we illustrate machineprose with a case study of its application to evidence based medicine.
zoning and metaclasses for character recognition. the contribution of this paper is twofold. first we investigate the use of the confusion matrices in order to get some insight to better define perceptual zoning for character recognition. the features considered in this work are based on concavities/convexities deficiencies, which are obtained by labeling the background pixels of the input image. four different perceptual zoning (symmetrical and non-symmetrical) are discussed. experiments show that this mechanism of zoning could be considered as a reasonable alternative to exhaustive search algorithms. the second contribution is a methodology to define metaclasses for the problem of handwritten character recognition. the proposed approach is based on the disagreement among the characters and it uses euclidean distance computed between the confusion matrices. through comprehensive experiments we demonstrate that the use of metaclasses can improve the performance of the system.
regression testing for component-based software via built-in test design. component-based software technology is expected to be an effective and widely used method of constructing software system. however, some specialties of component bring a great challenge for testing the systems built by externally-provided components, especially for regression testing. built-in test design is a fairly effective way to improve component's testability. in this paper, we present an improved regression testing method based on built-in test design for component-based systems. it needs the mutual collaboration between the component developers and users. component developers are responsible for analyzing the affected methods and constructing the corresponding testing-interfaces in the new component version, and then component users can conveniently pick out the subset of test cases for regression testing with these testing-interfaces. through employing preliminary experiments on some medium scale systems, our regression testing method based on built-in test design has been proven to be fairly feasible and cost-effective in practice.
a software framework for automated verification. this paper describes a software framework supporting the automated verification of models. the framework allows analyzing different kinds of behavioral models of software systems and business processes like uml activity diagrams and bpel models. to extend the applicability of the verification tools, a variety of transformation tools have been integrated in the framework.
text classification based on partial least square analysis. latent semantic indexing (lsi) is a favorite feature extraction method used in text classification. since when important global features for all the classes can be determined by lsi, important local features for small classes may be ignored, this leads to poor performance on these small classes. to solve this problem, a novel method based on partial least square (pls) analysis is proposed by integrating class information into the latent classification structure. important features are extracted according to both their descriptive power of document contents as in lsi, and their capacity of discriminating classes. the extracted features are applied to several classification algorithms: svm, knn, c4.5 and smo. experiments on reuters prove that the features extracted by our method outperform those extracted by lsi in all the cases. in particular, the gain obtained by our method is the most apparent on small classes.
an efficient tdma slot assignment protocol in mobile ad hoc networks. because of its ability to provide the collision-free packet transmission regardless of the traffic load, tdma has been applied effectively in ad hoc networks. until now, assuming a stationary ad hoc network, a tdma slot assignment protocol which achieves the high channel utilization has been proposed. in this paper, we extend the protocol to accomodate the dynamic topology change due to the movement of nodes. in our protocol, since each node autonomously detects a change in network topology and assigns a slot to itself, the high channel utilization in the previous protocol can be kept even when nodes in a network move. furthermore, we verify the effectiveness of the protocol by simulation experiments. the results show that our protocol improves channel utilization in comparison to conventional protocols.
component-based version management for embedded computing system design. nowadays, the development of modern computing devices involves a substantial and growing part of software development. a great challenge for engineers is to manage the evolution of a system with several components in the face of mounting complexity due to concurrent hardware and software development. the key limitations of existing version control tools used for a hardware software co-design process include their inadequacy in representing semantics of design models and inability to manage versions of both hardware designs and associated software components in a cohesive manner. thus, it is difficult to track the logical interdependencies between the changes to hardware and software components in an embedded computing system over time. this paper presents an application of a well-known software engineering approach to the management of embedded systems design artifacts. our novel component-based version management mechanism is capable of capturing and versioning the underlying logical contents of components in system design models and their associated software artifacts in a cohesive manner. this paper also illustrates our approach in creating a versioning system, named emvc, for a hardware software co-design process.
towards an automated test generation for the verification of model transformations. it is widely accepted that model transformations play an important role in the mda approach. as for any software, the validation and verification are essential in the life cycle of a model transformation. the proposition of an automatic approach that is based on functional testing techniques for the verification of model transformations reveals three main issues: the automatic generation of test data, the verification criteria, and the definition of the test oracle. the scope of this paper is restricted to the automatic generation of test data issue of the verification process. we first present a background on essential methods for test case generation and we argue their adaptation for the verification of model transformations. for an automated generation of test data we propose a formal language to be used for the specification of model transformations. we also propose a data partitioning technique that focuses on the structure of models in order to take into account the structural aspect of models when generating input test models. our partitioning technique is to be combined with existing techniques to cover the whole characteristics of the value a model.
a cp-lp approach to network management in ospf routing. in this paper, we consider a routing problem related to the widely used open shortest path first (ospf) protocol, which is considered a challenge within the constraint programming (cp) community. we address the special version of ospf which requires unique and symmetrical paths. to solve this problem, we propose a novel hybrid approach which combines cp and linear programming (lp). our approach employs a new global constraint with problem-specific filtering algorithms to efficiently remove inconsistent values from partial solutions. moreover, this constraint employs two lp relaxations which are used to indicate in-feasible partial solutions due either to network capacity constraints, or to protocol-specific routing constraints. we show the efficiency of our complete approach on backbone networks with hundreds of different demands to route.
an olap system for network-constrained moving objects. the continued advances in mobile devices, geo-location wireless sensors and positioning technologies have led to a profusion of moving object (mo) data. however, conventional on-line analytical processing (olap) systems cannot be applied to mo analysis because the position dimension evolves continuously over time. in this paper, we consider the representation of network-constrained mos in olap systems and make the three following contributions: (i) we introduce a logical model to support continuous dimensions and facts. (ii) we propose an efficient data structure to index moving objects. (iii) based on this index structure, we describe an algorithm which optimizes olap queries for analyzing mos.
constraint propagation for loose constraint graphs. in this paper we investigate how to improve propagation-based finite domain constraint solving by making use of the constraint graph to choose propagators to execute in a better order. if the constraint graph is not too densely connected we can build an underlying tree of bi-connected components, and use this to order the choice of propagator. our experiments show that there exist problems where handling biconnected components can substantially improve the propagation performance.
improving the performance of log-structured file systems with adaptive block rearrangement. log-structured file system (lfs) is famous for its optimization for write performance. because of its append-only nature, garbage collection is needed to reclaim the space occupied by the obsolete data. the cleaning overhead could significantly decrease the performance of file system. however, traditional cleaning policies do not consider the storage location where the valid data in the cleaned segments should be placed and rewritten to. in this paper, we propose a new method called r-lfs to dynamically reorganize data in disk to approximate the organ pipe heuristic that can place data in disk optimally. basically, frequently accessed data are dynamically clustered and placed toward the center of disk, whereas less accessed data are moved and placed toward the edges of disk to reduce disk seek time. the essence of r-lfs is that r-lfs takes advantage of the chance of data reorganization during segment cleaning and data writing, no extra overhead is incurred for this data reorganization. besides, because hot data and cold data are in nature separately clustered under r-lfs, cleaning overhead can be substantially reduced as well. performance evaluation under both trace-driven simulation and practical implementation on netbsd/lfs shows that r-lfs can effectively improve the performance of lfs.
weaving models in conflict detection specifications. increasingly, model driven development is being accepted as the new vision for designing software. in fact, shifting the focus from a code-centric standpoint to a model-centric one enables a better specification and understanding of domain specific concerns. since a software system undergoes to several refinement steps during its life cycle, last years have witnessed a growing demand for model versioning support. in this respect, the operation of merging different modifications and the related conflict management are of crucial relevance. usually, diverging modifications are detected by assuming a predefined set of situations; however, not always it is possible to predict all the problems since they cannot be detected only syntactically. hence, in this position paper it is proposed to leverage conflict detection and resolution by adopting design-oriented descriptions endowed with custom conflict specifications.
frequent pattern mining for kernel trace data. operating systems engineers have developed tracing tools that log details about process execution at the kernel level. these tools make it easier to understand the actual execution that takes place on real systems. unfortunately, uncovering certain types of useful information in kernel trace data is nearly impossible through manual inspection of a trace log. to detect interesting interprocess communication patterns and other recurring runtime execution patterns in operating system trace logs, we employ data mining techniques, in particular, frequent pattern mining. we present a framework for mining kernel trace data, making use of frequent pattern mining in conjunction with special considerations for the temporal characteristics of kernel trace data. we report our findings using our framework to isolate processes responsible for systemic problems on a linux system and demonstrate our framework is versatile and efficient.
towards security monitoring patterns. runtime monitoring is performed during system execution to detect whether the system's behaviour deviates from that described by requirements. to support this activity we have developed a monitoring framework that expresses the requirements to be monitored in event calculus - a formal temporal first order language. following an investigation of how this framework could be used to monitor security requirements, in this paper we propose patterns for expressing three basic types of such requirements, namely confidentiality, integrity and availability. these patterns aim to ease the task of specifying confidentiality, integrity and availability requirements in monitorable forms by non-expert users. the paper illustrates the use of these patterns using examples of an industrial case study.
a relative cost model for xquery. xquery is a functional query language for xml. we propose a relative xquery cost model that is able to estimate the performance gain during source level transformation. this research facilitates the evaluation of various rewriting techniques without introducing real engines. the cost model consists of simple recursive functions based on functional language constructs. they are determined using formal semantics and other known efficient algorithms. analytic comparison of costs between expressions before and after transformation is possible in an engine-independent manner. the relativity of the model allows uninterpreted components within, which do not affect the mathematical proof of the comparison. moreover, it can be tailored to reflect engine specific evaluation strategies such as the order of evaluation of operands.
worldsens: a fast and accurate development framework for sensor network applications. in this article, we present worldsens, a fast and accurate development framework for sensor network applications. world-sens offers an integrated platform for the design, development, performance evaluation and profiling of applications. it relies on two simulators, wsnet and wsim, which are used throughout the application design and implementation, from the high level design choices to the implementation validation. wsnet is a modular event-driven wireless network simulator while wsim is a full platform hardware simulator which takes the target binary code as input and uses instruction cycles as time reference. wsnet and wsim can be used in conjunction to offer a distributed simulation of sensor networks with instruction and radio byte accuracy.
dual proximity neighbour selection method for peer-to-peer-based discovery service. in this paper, we propose a new, dual method for self-optimization of a pervasive, dht-based discovery service. this method addresses the topology mismatch problem. on one hand, it selects close neighbours based on static, readily available information (the ip addresses of the nodes) and thus does not require costly periodic probing of many nodes. on the other hand, it enables the overlay network to optimize its topology in run-time in a cost-effective manner. we prove the effectiveness of our method by statistical and experimental verification.
a self-organizing neural network for detecting novelties. in order to detect new events, a system must support on-line learning, adapting to pattern dynamic characteristics. studies of such adaptation have originated the novelty detection area, which aims at identifying unexpected or unknown patterns. these researches have motivated this work to propose the on-line and unsupervised self-organizing novelty detection (sonde) neural network. in this network, the creation of new neurons points out novelties. experiments evaluated the influence of sonde parameters and their capability to detect novelty events. these evaluations considered the datasets biomed, all-aml leukemia and dlbcl. results are compared to others from gwr.
a table-form extraction with artefact removal. we present a novel methodology for extracting the structure of handwritten filled table-forms. the method identifies the table-form line intersections, detecting and correcting wrong intersections produced by faulty line segments or by table artefacts. examples of artefacts are overlapping data, broken segments, and smudges. a novel method for artefact identification and deletion is also proposed. the last step performs the extraction of table-form cells. a database of 350 table-form images was used for evaluation, showing that the artefact identification method improves the performance of the table-forms structure extractor. the proposed approach reached a success rate of 85%.
mining and processing category ranking. as more and more data are becoming accessible, a naive retrieval of such data may often result in too many answers, as we commonly call "information overload".
fca-based approach for mining contextualized folksonomy. we present a novel approach to build the contextualized folksonomy and concept hieracrhies from tags of blogosphere based on formal concept analysis. our approach is based on the assumption that if a blog has the relationships with others, they would use the similar set of tags. we collect the sample data from blogosphere randomly and then build the concept hierarchies on the basis of the inclusion relations(tags) between the extensions(bloggers). we propose the formalization of the contextualized folksonomy in terms of formal concept analysis and show how our approach can be used to create the contextualized folksonmy for blogosphere. we evaluate our approach by considering an already existing tags of blogosphere.
an approach to evaluating structural pattern conformance of uml models. this paper describes an approach to evaluating the structural conformance of a uml class diagram to a design pattern. a design pattern is specified in an extension of the uml that defines the pattern as a family of models. a pattern specification consists of a set of pattern roles where a role specifies the properties of a pattern participant. the approach uses a divide-and-conquer method to evaluate pattern conformance. in the approach a pattern and the model being evaluated are decomposed into blocks. then, the model blocks are evaluated for conformance to the role blocks in the pattern. when all individual role blocks are satisfied by the model blocks, the pattern as a whole is considered to evaluate the entire conformance of the model. a major benefit of this approach is the support for variations of pattern realizations through the notion of pattern roles. we illustrate the approach using the visitor pattern and a price calculator, and demonstrate a prototype tool that supports the approach.
exploiting types for improved schema mapping. schema mapping in life sciences is complicated by several factors - heterogeneity and non-standard naming of scientific objects. traditional mapping techniques fail completely in many instances. this article suggests that exploiting type information and heuristic layout mining help map schemas in life science applications. in some cases, this method appears to be only approach that makes mapping possible in this area.
a connected component labeling algorithm for grayscale images and application of the algorithm on mammograms. a new algorithm for connected component labeling is presented in this paper. this algorithm requires only one scan through an image for labeling connected components. once this algorithm encounters a starting pixel of a component, it completely traces all the contour pixels and all internal pixels of that particular component. this algorithm recognizes components one at a time in the image while scanning in raster order. this property will be very useful in areas such as image matching, image registration and content-based information retrieval etc. this algorithm is also capable of extracting contour pixels of an image and storing them in the order of clock-wise direction which will provide very useful information in many applications. also this algorithm assigns consecutive label numbers for different components and hence needs a minimum number of labels. as our main research is on mammography image analysis for diagnosing breast cancers, we applied this algorithm to mammograms and measured performance of the algorithm in terms of processing time. this will be a useful algorithm in medical image analysis as a preprocessing tool.
graph-based text representation and knowledge discovery. for information retrieval and text-mining, a robust scalable framework is required to represent the information extracted from documents and enable visualization and query of such information. one very widely used model is the vector space model which is based on the bag-of-words approach. however, it suffers from the fact that it loses important information about the original text, such as information about the order of the terms in the text or about the frontiers between sentences or paragraphs. in this paper, we propose a graph-based text representation, which is capable of capturing (i) term order (ii) term frequency (iii) term co-occurrence (iv) term context in documents. we also apply the graph model into our text mining task, which is to discover unapparent associations between two and more concepts (e.g. individuals) from a large text corpus. counterterrorism corpus is used to evaluate the performance of various retrieval models, which demonstrates feasibility and effectiveness of graphic text representation in information retrieval and text mining.
supporting reconfigurable object distribution for customized web applications. in current practice, web applications are tightly coupled with the platforms that a particular service provider intends to support and the execution scenario envisioned at the design time. the resulting applications do not adapt well to all clients and runtime execution contexts. the goal of our research is to develop methods and software to support recon-figurable distributed applications which can be customized to specific requirements. we view a web application as a composition of actors, i.e. distributed active objects, and apply techniques of generative programming to develop a virtual application framework which separates the logic of objects from aspects relevant to object distribution on different platforms. we describe actorspec, a specification system allowing programmers to express desired object distribution and assisting application generators to produce highly customized versions of an application. the resulting flexibility facilitates the development of customizable web applications on an increasingly complex web infrastructure.
a model for managing collections of patterns. data mining algorithms are now able to efficiently deal with huge amount of data. various kinds of patterns may be discovered and may have some great impact on the general development of knowledge. in many domains, end users may want to have their data mined by data mining tools in order to extract patterns that could impact their business. nevertheless, those users are often overwhelmed by the large quantity of patterns extracted in such a situation. moreover, some privacy issues, or some commercial one may lead the users not to be able to mine the data by themselves. thus, the users may not have the possibility to perform many experiments integrating various constraints in order to focus on specific patterns they would like to extract. post processing of patterns may be an answer to that drawback. thus, in this paper we present a framework that could allow end users to manage collections of patterns. we propose to use an efficient data structure on which some algebraic operators may be used in order to retrieve or access patterns in pattern bases.
featherweight wrap java. we present an extension for a java like language with a mechanism for dynamically extending object behaviors. our approach consists in moving the addition of new features from class (static) level to object (dynamic) level: the basic features of entities (representing their structure) are separated from the additional ones (wrapper classes whose instances represent run-time added behaviors). at run-time, these entities can be dynamically composed by instantiating wrapper objects which are attached to basic entities. we formalize our extension by adding the new constructs to featherweight java; the core language so extended (featherweight wrap java) is type safe.
preattentive processing: using low-level vision psychology to encode information in visualisations. this paper explores the effects of two preattentive visual features, closure and depth, when performing the preattentive task of boundary detection. testing was performed on human subjects and the data was collected using a preattentive perception experiment. the post experimental questionnaire allowed subjects to indicate their estimate of the usefulness of each preattentive visual feature. the results indicate that both depth and closure are effective when performing boundary detection task. however, depth proved to be a more dominant than closure.
an mda approach to develop systems based on components and aspects. model-driven development and aspect oriented software development offer excellent support to modular reasoning, which can be used to develop component-based systems favouring a better software evolution. a development process based on model driven architecture (mda) to integrate components and aspects is presented in this paper. in order to do this, a uml profile to model systems based on components and aspects is suggested. then a set of model-to-model transformations at design level including the weaving among components and aspects, allow us to obtain the final system based on uml profile for the corba component model. the ccm code for the final systems is obtained by a model-to-code transformation. a specific tool (eclipse plugin) has been developed to support the software development based on aspect component based software development (acbse).
decentralized authorization and data security in web content delivery. the fast development of web services, or more broadly, service-oriented architectures (soas), has prompted more organizations to move contents and applications out to the web. softwares on the web allow one to enjoy a variety of services, for example translating texts into other languages and converting a document from one format to another. in this paper, we address the problem of maintaining data integrity and confidentiality in web content delivery when dynamic content modifications are needed. we propose a flexible and scalable model for secure content delivery based on the use of roles and role certificates to manage web intermediaries. the proxies coordinate themselves in order to process and deliver contents, and the integrity of the delivered content is enforced using a decentralized strategy. to achieve this, we utilize a distributed role lookup table and a role-number based routing mechanism. we give an efficient secure protocol, ideliver, for content processing and delivery, and also describe a method for securely updating role lookup tables. our solution also applies to the security problem in web-based workflows, for example maintaining the data integrity in automated trading, contract authorization, and supply chain management in large organizations.
square: scalable quorum-based atomic memory with local reconfiguration. internet-scale applications require more and more resources to satisfy the unpredictable clients needs. specifically, such applications must ensure quality of service despite bursts of load. distributed dynamic self-organized systems present an inherent adaptiveness that can face unpredictable bursts of load. nevertheless quality of service, and more particularly data consistency, remains hardly achievable in such systems since participants (i.e., nodes) can crash, leave, and join the system at arbitrary time. atomic consistency guarantees that any read operation returns the last written value of a data and is generalizable to data composition. to guarantee atomic consistency in message-passing model, mutually intersecting sets (a.k.a. quorums) of nodes are used. the solution presented here, namely square, uses self-adaptiveness and load-balancing to provide atomic consistency in large-scale dynamic distributed systems. this paper presents the square algorithm and uses extensive simulation to show it achieves its desirable properties.
a protocol to preserve a code of conduct. to fight community abuse, we introduce in this paper a set of simple, yet powerful, trust protocols, aimed at enforcing on a p2p network a boolean code of conduct verifiable by the network agents themselves. having a boolean code of conduct which honest agents never violate allows effective enforcing of it. a formal model for trust protocol definition and analysis is also defined, and properties of these protocols are formally defined and proved according to this model.
a weighted cache replacement policy for location dependent data in mobile environments. developing widely useful mobile computing applications presents difficult challenges. on one hand, mobile users demand intuitive user interfaces, fast response times, and deep relevant content. on the other hand, mobile devices have limited processing, storage, power, display, and communication resources. caching frequently accessed data items on the mobile client is an effective technique to improve the system performance in mobile environment. due to cache size limitation, the choice of cache replacement technique to find a suitable subset of items for eviction from cache becomes important. in this paper, we propose a new cache replacement policy for location dependent data in mobile environment. the proposed policy selects the predicted region based on client's movement and uses it to calculate the weighted data distance of an item. this makes the policy adaptive to client's movement pattern and provides importance to the regions around client's position. this is unlike earlier policies that consider the directional/non-directional data distance only. we call our policy the weighted predicted region based cache replacement policy (wprrp). simulation results show that the proposed policy significantly improves the system performance in comparison to previous schemes in terms of cache hit ratio.
semantic deep web: automatic attribute extraction from the deep web data sources. "deep web" refers to the rich information and data hidden in backend databases, etc., that search engines or web crawlers cannot access. it is mostly accessible through manual query interfaces. this paper introduces the semantic deep web, utilizing an ontology to determine relevance of query interface attributes to access the deep web. in addition, we present a novel approach to automatically extracting attributes from query interfaces in order to address the current limitations in accessing deep web data sources. our automatic attribute extraction method (1) identifies attributes that are used by query web page designers, called programmer viewpoint attributes, and (2) attributes that are presented as labels to users, called user viewpoint attributes. an ontology enriches the candidate query attributes by providing synonyms and by supporting the attributes used by designers and users. our experimental results in several e-commerce domains show that the attributes obtained by our algorithm compare favorably with manually determined attributes to be used for deep web queries.
evaluation of the qos of crash-recovery failure detection. crash failure detection is a key topic in fault tolerance, and it is important to be able to assess the qos of failure detection services. most previous work on crash failure detectors has been based on the crash-stop or fail-free assumption. in this paper we study and model a crash-recovery service which has the ability to recover from the crash state. we analyse the qos bounds for such a crash-recovery failure detection service. our results show that the dependability metrics of the monitored service will have an impact on the qos of the failure detection service. our results are corroborated by simulation results, showing bounds on the qos.
a preliminary design for digital forensics analysis of terabyte size data sets. digital forensics is computationally intensive and current analysis systems do not handle the multiple terabyte size data sets that are now becoming a major issue for analysis. for these data sets, raid file system analysis, parallel computing, collaboration, and visualization will be essential. here we outline the preliminary design for a parallel digital forensics framework that is being developed to handle multiple terabyte size data set analysis.
on-the-fly data integration models for biological databases. the web is a universal repository of information where there is an excellent opportunity to exploit the integration of online biological resources for knowledge discovery. a major challenge is to support the effective flow of information among the sources and services on the web and their interconnection with legacy systems that are designed to operate with traditional relational databases. to address this problem, a possible strategy is to combine information from disparate data sources and display it in a single integrated framework to the user without having to populate local databases. this is called online or on-the-fly data integration. bioxbase is a user-centric biological query system which extracts user requested query information over internet from multiple biological sources and organizes a wide variety of information into a homogeneous unified view to the user after data is cleaned, processed and integrated. bioxbase system has improved the results retrieved approximately by 30% compared to a system that has only a local database. the bioxbase system is further enhanced by 20% while combining the results of both biomap (a local database) and bioxbase (on the fly system), making the results more significant in biological domain. the results were validated by statistical methods such as precision, recall and power-law degree distribution analysis.
a machine learning approach to semi-automating workflow staff assignment. staff assignment is an important aspect of workflow resource management. in many current workflow applications, staff assignment is still performed manually by resource assigners like process initiator or process monitor. in this paper, we present a semi-automated approach intended to ease the burden of staff assigner. our approach applies a machine learning algorithm to workflow event log to learn various kinds of activities each actor undertakes. when a new process is initiated, the classifiers generated by the machine learning technique suggest a suitable actor to undertake the specified activities. with this approach, we have achieved an average prediction accuracy of 85.8% and 80.1% on two car manufacturing enterprises respectively. we report on the result of our experiment and discuss issues and improvement of our approach.
modeling component based embedded systems applications with explicit connectors in uml 2.0. when building a system by connecting components, the connection itself, the connector, becomes a hot-spot of abstraction for any interaction. in contrary to most existing component models, we introduce explicit connectors as first class architectural entities. they materialize detailed contracts regarding composition, deployment and interaction and hence provide fine granular information on composed structures. using explicit connectors results in customtailored and consequently light-weight middleware, as any interaction logic is contained within them. modeling component architectures with explicit connectors allows the usage of off-the-shelf connector libraries. thereby, developing a distributed component based application becomes less complex and more competitive due to reduced costs and increased reliability. we contribute by adopting a model driven development process for the use of explicit connectors by extending the syntax of uml 2.0 and defining a set of required model transformations.
using a knowledge base to disambiguate personal name in web search results. results of queries by personal names often contain documents related to several people because of the namesake problem. in order to differentiate documents related to different people, an effective method is needed to measure document similarities and to find documents related to the same person. some previous researchers have used the vector space model or have tried to extract common named entities for measuring similarities. we propose a new method that uses web directories as a knowledge base to find shared contexts in document pairs and uses the measurement of shared contexts to determine similarities between document pairs. experimental results show that our proposed method outperforms the vector space model method and the named entity recognition method.
personalized ranking: a contextual ranking approach. as data of an unprecedented scale are becoming accessible on the web, personalization, of narrowing down the retrieval to meet the user-specific information needs, is becoming more and more critical. for instance, in the context of text retrieval, in contrast to traditional web search engines retrieving the same results for all users, major commercial search engines are starting to support personalization, improving the search quality by adapting to the user-specific retrieval contexts, e.g., prior search history or other application contexts. this paper studies how to enable such personalization in the context of structured data retrieval. in particular, we adopt context-sensitive ranking model to formalize personalization as a cost-based optimization over context-sensitive rankings collected. with this formalism, personalization is essentially retrieving the context-sensitive ranking matching the specific user's retrieval context and generating a personalized ranking accordingly. in particular, we adopt a machine learning approach, to effectively and efficiently identify the ideal personalized ranked results for this specific user. our empirical evaluations over real-life data validate both the effectiveness and efficiency of our framework.
an efficient implementation of rc4 cipher for encrypting multimedia files on mobile devices. abstract. in this paper, we implement and evaluate an efficient rc4 stream cipher, called key-pooled rc4, to transfer securely multimedia files in the wireless mobile network. in key-pooled rc4, a 1mb-sized key stream pool, which consists of 2048 or 8192, or 32768 key stream frames, is created uniquely for each client device in the registration step. when a client requests a multimedia file, the server delivers the file after encrypting it using the sequence of key stream frames which are randomly selected from the corresponding key stream pool. our experimental results show that the proposed scheme is more time efficient than the normal rc4. moreover, the key-pooled rc4 scheme is more secure than normal rc4.
on using user query sequence to detect off-topic search. retrieving off-topic documents to a user's pre-defined area of interest via a search engine is potentially a violation of access rights and is a concern to every private, commercial, and governmental organization. we improve content-based off-topic search detection approaches by using a sequence of user queries versus the individual queries. in this approach, we reevaluate how off-topic a query is, based on the sequence of queries that preceded it. our empirical results show that using the information from the queries in a given query window, the false alarm rate is reduced by a statistically significant amount.
finding putative core promoter elements with position-dependent consensuses. so far, within the core promoter region, only five known core promoter elements were found to be involved in the transcription initiation. in this paper, we proposed a framework for finding putative core promoter elements in the core promoter sequences. after implementing the framework, we used epd promoters as the datasets in the experiments, and identified the putative core promoter elements with functional positions. the experimental results demonstrated that our system is feasible and reliable, regardless of whatever species are.
balancing energy consumption and memory usage in sensor data processing. algorithms for data processing in sensor nodes of wireless sensor networks should be able to handle the resource limitations the nodes face (i.e. energy and memory). an important issue to be considered is that the materialization of large amounts of data in sensor nodes may cause memory overflows and consequently data losses. on the other hand, the excessive sending of data packets to other nodes may result in unacceptable energy consumption levels. some alternatives to save energy and also avoid memory overflows involve in-network aggregation and reductions in sensor activities (when sensor nodes experience resource constraints). in this paper we study energy-memory tradeoffs in sensor nodes and how they affect the accuracy of query results in wireless sensor networks. we propose an adaptive data processing strategy to balance energy consumption and memory usage at sensor node level. our goal is to maximize sensor lifetime while also maintaining the accuracy of query results. we implemented our approach by means of an algorithm called adaga (adaptive aggregation algorithm for sensor networks), which process in-network aggregation in sensor nodes. adaga is able to adapt its behavior according to energy and memory availabilities by dynamically adjusting data collection and data sending intervals. the results on the efficiency of our approach are also presented at the end of the paper.
applying a component-based framework to develop multi-agent environments: case study. this paper introduces an infrastructure for engineering environments for multi-agent systems. such an infrastructure is based on a component model specification, named cms, which promotes dynamic unanticipated evolution of software. we propose an agent model specification (ams), focusing on environment engineering issues. moreover, we present a java framework that implements ams and a case study to exemplify the application of our approach.
an efficient indexing structure for content based multimedia retrieval with relevance feedback. this paper proposes an efficient indexing structure for cbmr (content-based multimedia retrieval), called hbi (hierarchical bitmap index), in which each object is represented as a bitmap of size 2 &middot; d &middot; l bits, where d is the number of dimensions of object's feature vector and l is the number of bitmaps. in this bitmap representation, the feature (or attribute) value of object at each dimension is represented with a set of two bits each of which indicates whether it is relatively high ('11'), low ('00'), or neither ('01') compared to the feature values of other objects at a hierarchical organized interval. using these compact representations of feature vectors, a lot of irrelevant objects could be quickly filtered-out by a couple of simple xor operations, and it helps to reduce the filtering process of similarity search in high-dimensional data space. it also presents an optimization algorithm, called fqd (filtering by query difference), for the similarity search with relevance feedback that reuses the previously calculated distances between the original query and all objects in the database when filtering the irrelevant objects in the successive search with modified query. it helps to further reduce the search time of cbmr with relevance feedback. experimental results show that the similarity search using hbi is about 2 ~ 3 times faster than va-file while guaranteeing the exact solutions, and fqd for relevance feedback helps to further reduce the elapsed time of successive similarity search compared to the one for the first search.
reversing guis to ximl descriptions for the adaptation to heterogeneous devices. the spread of personal wireless devices (pwds) has raised the need to migrate existing applications to these new environments. desktop applications often exhibit complex user interfaces and are too large and resource demanding to be executed on devices with limited resources without changing the application code. current research efforts are mainly focused on web applications whose user interfaces are specifically designed for multi-platform environments through platform-independent models. on the contrary, little effort has been made to support the migration of applications with component-based guis towards pwd environments. this paper presents a tool for reverse engineering java guis through their transformations to ximl-based abstract descriptions. the resulting descriptions are used by the tcpte framework to be rendered into different guis, which are dynamically adapted to heterogeneous devices on the basis of their profile communicated at request time.
towards a synthetic analysis of user's information need for more effective personalized filtering services. the consideration of underlying analysis of user's information need is a key requirement in an intelligent filtering environment. however, the majority of current approaches to filtering are relevance-oriented, rather than user-oriented. this is partly because they are issued from fields that have somewhat different perspectives from that of information filtering, but also because of the difficulty of understanding and measuring user's motivations and the way in which the user expects the system to respond. this paper presents an original approach to information analysis and filtering inspired by the novelty detection theory. as well as being able to accurately learn user's information need, the approach has an analytical capacity for better understanding user's need. it provides a new way of looking at user's need in terms of precise, broad, and contradictory profile-contributing criteria. these criteria go on to estimate the relative importance the user might attach to precision and recall. the filtering threshold is then adjusted taking into account this knowledge about user's need. experimental results on the standard reuters-21578 collection prove the effectiveness of the approach and confirm the potential usefulness of adapting the filtering results according to the knowledge acquired about user's need.
a solver for quantified boolean and linear constraints. we make a number of contributions to the understanding and practical resolution of quantified constraints. unlike previous work in the cp literature that was essentially focused on constraints expressed as binary tables, we focus on presburger arithmetics, i.e., boolean combinations of linear constraints. from a theoretical perspective, we clarify the problem of the treatment of universal quantifiers by proposing a "symmetric" version of the notion of quantified consistency. this notion imposes to maintain two constraint stores, which will be used to reason on universal and existential variables, respectively. we then describe a branch & bound algorithm that integrates both forms of propagation. its implementation is, to the best of our knowledge, the first cp solver for this class of quantified constraints.
towards context-aware and resource-driven self-adaptation for mobile handheld applications. mobile handheld computing is gaining momentum as more and more wireless handheld devices are being used to accomplish various computing tasks. context-awareness can help to adapt and personalize applications or to optimize resource usage. however, many existing context infrastructures by themselves impose heavy resource requirements for deployment or highly affect the limited autonomy of the mobile device. in this paper we describe how resource-driven self-adaptation is used in our layered context-driven application middleware in order to enable deployment on a mobile device and optimize resource usage. our evaluation shows that the introspection and intercession capabilities of the self-adapting middleware provide the necessary flexibility to achieve a balanced resource usage between the context-driven application middleware and the context-aware applications, and that the resource-driven self-adaptation is able to more than double the battery lifetime in real life scenarios.
a mof metamodel for the development of context-aware mobile applications. context-aware mobile applications are increasingly attracting interest of the research community. to facilitate the development of this class of applications, it is necessary that both applications and support platforms share a common context metamodel. this paper presents a metamodel defined using the omg meta object facility (mof). this metamodel has been used as basis for the development of context-aware applications and an associated service platform.
a fair scheduling scheme for a time-sensitive traffic over the dual-channel wireless network. this paper proposes a message scheduling scheme capable of improving both throughput and fairness on the dual-channel wireless network. based on the time-slotted access mechanism for each channel within a single cell, the coordinator schedules the transmission of the first channel by edf (earliest deadline first) discipline that can maximize the actual throughput, while gdf (greatest degradation first) discipline is exploited for the second channel to improve the fairness factor. during runtime, with the support of channel estimation mechanism, the coordinator can dynamically switch the channel between the two scheduled streams. the simulation result shows that the proposed scheme improves the actual throughput by 7.2 % compared with edf, while the fairness is improved by 2.4 % compared with gdf.
enhancing traceability using ontologies. traceability refers to the ability to link information in a process chain. this paper proposes the integration of ontologies into the unified process (up) [1] to provide concept-based traceability throughout the software lifecycle. this approach allows the integration of the different models of a software system including business, requirements, analysis and design models in a lower granularity degree than conventional requirements traceability approaches. to assist the designers in creating the ontology and linking concepts to artifacts we provide a tool integrated with an uml modeler.
evolution of iterated prisoner's dilemma strategies with different history lengths in static and cultural environments. we investigate evolutionary approaches to generate well-performing strategies for the iterated prisoner's dilemma (ipd) with different history lengths in static and cultural environments. the length of the history determines the number of the most recent moves of both players taken into account for the current move decision. the static environment constituting the opponents of the evolved players is made up of ten standard strategies known from the literature. the cultural environment starts with the standard strategies and gradually increases by addition of the best evolved players representing a culture. the performance of the various evolved strategies is compared in specific tournaments. also, the behavior of an evolved player is analyzed in more detail by looking at the specific game sequences (and corresponding decisions), which out of all possible sequences are actually utilized in a tournament.
the detection and assessment of possible rna secondary structure using multiple sequence alignment. we here devise a new method for detecting and assessing rna secondary structure by using multiple sequence alignment. the central idea of the method is to first detect conserved stems in the alignment using a special matrix and then assess them by evaluating the ratio of the signal to the noise. we tested the method on data sets composed of pairwise and three-way alignments of known ncrnas. for the pairwise tests, our method has sensitivity 61.42% and specificity 97.05% for structural alignments, and sensitivity 42.05% and specificity 98.15% for blast alignments. for the three-way tests, our method has sensitivity 65.17% and specificity 97.96% for structural alignments, and sensitivity 40.70% and specificity 97.87% for clustalw alignments. our method can detect conserved secondary structures in gapped or ungapped rna alignments.
shared-stack cooperative threads. multithreaded sensor operating systems provide the paradigm of threads which enables programmers to program and maintain their applications more easily. however, a lot of memory space can be wasted due to the fact that a fixed-size stack is allocated for each thread. in this paper, we propose the shared-stack cooperative threads which can combine the simplicity of the multithreaded programming with the performance and scalability of event-driven systems. our experimental results show that shared-stack cooperative threads utilize memory space more efficiently with some affordable context switching overhead for threading while providing programmers with the ease of multithreaded programming.
translation disambiguation in web-based translation extraction for english-chinese clir. dictionary based translation is a traditional approach in use by cross-language information retrieval systems. however, significant performance degradation is often observed when queries contain words that do not appear in the dictionary. this is called the out of vocabulary (oov) problem. in recent years, web-based translation extraction was shown to be one of the more effective approaches to the solution of this problem. previous work focussed on selecting the correct translation from a set of web extracted terms. the common methods for translation selection for web-based translation always rely on word frequency calculation but the results are not always satisfactory. in this paper we present our approach to the selection of terms in a more accurate manner. our experiments show improvement in translation accuracy over other commonly used approaches.
dynamic adaptation of corba component-based applications. an important requirement for pervasive computing systems is the ability to adapt at runtime to handle varying resources, user mobility, and changing user needs. in this paper, we present an innovative approach to adapt the corba component-based applications. this approach proposes to extend the corba deployment model to describe the variability of the architecture of applications and to extend the corba execution model in order to support adaptation at runtime. the originality of this approach is to consider the adaptation activities as non-functional aspects and to integrate them in the corba container.
sim and usim filesystem: a forensics perspective. the main purpose of this paper is to describe the real filesystem of sim and usim cards, enlightening what the official standard reference does not say. by analyzing the full filesystem of such embedded devices, it is possible to find a lot of undocumented files usable to conceal sensitive and arbitrary information that are unrecoverable with the standard tools normally used in a forensic field. in order to understand how it is possible to use a sim/usim for data hiding purposes, the paper will present a tool capable of extracting the entire observable memory of these devices together with the effective filesystem structure. further, some practical examples regarding the data hiding procedure as a proof of concept will be analyzed and discussed.
injection/withdrawal scheduling for natural gas storage facilities. control decisions for gas storage facilities are made in the face of extreme uncertainty over future natural gas prices on world markets. we examine the problem faced by owners of storage contracts of how to manage the injection/withdrawal schedule of gas, given past price behavior and a predictive model of future prices. real options theory provides a framework for making such decisions. we describe the theory behind our model and a software application that seeks to optimize the expected value of the storage facility, given capacity and deliverability constraints, via monte-carlo simulation. our approach also allows us to determine an upper bound on the expected valuation of the remaining storage facility contract and the gas stored therein.
an analytical model for generalized processor sharing scheduling with heterogeneous network traffic. implementation of differentiated quality-of-service (qos) in next-generation computer networks has received increasing research interests from both academia and industry. the generalized processor sharing (gps) scheduling strategy has been widely studied as a promising way to provide differentiated qos due to its service protection feature. most of the previous studies reported in the literature, however, have focused on the analysis of gps under either short range dependent (srd) or long range dependent (lrd) traffic only, neither of which is able to capture the heterogeneous properties of realistic traffic in multi-service networks solely. to fill this gap, this paper develops a new analytical performance model for gps systems subject to both lrd self-similar traffic and srd poisson traffic. more specifically, using an approach based on large deviation principles, this study contributes to performance modelling and evaluation of gps scheduling by deriving the analytical upper and lower bounds of the aggregate and individual queue length distributions of heterogeneous traffic flows. the comparisons between analytical bounds and extensive simulation results validate the accuracy and merits of the analytical model which can be adopted as a practical and cost-effective evaluation tool for investigating the performance behaviour of gps systems under heterogeneous network traffic with various parameter settings.
guarding security sensitive content using confined mobile agents. mobile code and mobile agents are generally associated with security vulnerabilities, rather than with increased security. this paper describes an approach in which mobile agents are confined, in order to allow content providers to retain control over how their data is exported while allowing agents to search the full content of this data locally. this approach offers increased control and security compared to the traditional client-server technologies commonly used for building distributed systems. we describe a new system, called mansion, which implements confinement of mobile agents, and describe a number of applications of the confinement model to illustrate its potential.
transforming system operations' interactions into a design class diagram. this work reports the results of the development of a model transformation realized in kermeta. this transformation accepts a domain model and a set of communication diagrams containing the design of system operations corresponding to the same use-case. the result is a design class diagram expressing the class structure that part of a system should logically exhibit in order to enable the occurrence of the interactions specified in the communication diagrams. to that end, along with specific meta-models for input models and for the output model, an executable model for the transformation was defined. this paper reviews the elements involved in the development of this transformation, and describes the design of its structure and behavior. the transformation was applied to a case study taken from the bibliography and the results are presented and discussed.
propagating dense systems of integer linear equations. in interval propagation approaches to solving non-linear constraints over reals it is common to build stronger propagators from systems of linear equations. this, as far as we are aware, is not pursued for integer finite domain propagation. in this paper we show how we can add preconditioning gauss-seidel based propagators to an integer propagation solver. the gauss-seidel based propagators make use of interval arithmetic which is substantially slower than integer arithmetic. we show how we can build new integer propagators from the result of preconditioning that no longer require interval arithmetic to be performed. although the resulting propagators may be slightly weaker than the original gauss-seidel propagation, they are substantially faster. we show on standard integer benchmarks how these new propagators can substantially improve propagation performance, in terms of strength of propagation and speed.
ontology based annotation of text segments. this work exploits the logical structure of information rich texts to automatically annotate text segments contained within them using a domain ontology. the underlying assumption behind this work is that segments in such documents embody self contained informative units. another assumption is that segment headings coupled with a document's hierarchical structure offer informal representations of segment content; and that matching segment headings to concepts in an ontology/thesaurus can result in the creation of formal labels/meta-data for these segments. when an encountered heading can not be matched with any concepts in the ontology, the hierarchical structure of the document is used to infer where a new concept represented by this heading should be added in the ontology. so, in this work the bootstrap ontology is also enriched by new concepts encountered within input documents. this paper also presents issues/problems related to matching textual entities to concepts in an incomplete ontology. the approach presented in this paper was applied to a set of agricultural extension documents. the results of carrying out this experiment demonstrates that the proposed approach is capable of automatically annotating segments with concepts that describe a segment's content with a high degree of accuracy.
general dominant relationship analysis based on partial order models. due to the importance of skyline query in many applications, it has been attracted much attention recently. given an n-dimensional dataset d, a point p is said to dominate another point q if p is better than q in at least one dimension and equal to or better than q in the remaining dimensions. recently, li et al. [9] proposed to analyze more general dominant relationship in a business model that, users are more interested in the details of the dominant relationship in a dataset, i.e., a point p dominates how many other points. in this paper, we further generalize this problem that, users are more interested in whom these dominated points are. we show that the framework proposed in [9] can not efficiently solve this problem. we find the interrelated connection between the partial order and the dominant relationship. based on this discovery, we propose efficient algorithms to answer the general dominant relationship queries by querying the partial order representation of spatial datasets. extensive experiments illustrate the effectiveness and efficiency of our methods.
dual agreement virtual subnet protocol for mobile ad-hoc networks. the byzantine agreement (ba) plays a key role in fault-tolerant distributed system design. more existing ba protocols are designed for wired networks. in practice, wireless and mobile computing are becoming increasingly popular; the topology of network is trending wireless and provides support for mobile computing. mobile ad-hoc network (manet) is a kind of popular wireless network. the proposed protocol can make each fault-free mobile processor reach an agreement value to cope with the faulty component in the virtual subnet of manet.
a cooperative classification mechanism for search and retrieval software components. this paper presents the use of folksonomy concepts in a software component search engine as an alternative to improve the search result quality, covering from specification to implementation. a case study was performed in order to evaluate its performance and viability. additionally, a set of requirements to perform component search and retrieval with folksonomy are presented, beyond the architectural and implementation aspects that accomplishes the tool. the case study indicates the suit of different search techniques is better than using separately. the engine's current version combines keyword, facet-based and folksonomy search techniques.
a high performance nids using fpga-based regular expression matching. a network intrusion detection system (nids) monitors all incoming packets in the network and detects packets that are malicious to the internal system. the nids should also have ability to update the detection rules because new attack patterns are unpredictable. incorporating fpgas into the nids is one of the best solutions that can provide both high performance and high flexibility comparing to the other approaches such as software solutions. in this paper we propose a novel approach to design the parallel comparator of nids that can not only minimize additional resources but also maximize the processing performance. the performance and resource tradeoff due to the implementation of the parallel comparator in the prefix sharing is also analyzed.
optimizing hypergraph transversal computation with an anti-monotone constraint. finding hypergraph transversals is a major algorithmic issue having many relationships with the data mining area. by defining a new galois connection, we show how it is possible to use data mining results on pattern condensed representations and the levelwise framework to improve the hypergraph transversals computation. we present a new algorithm mtminer and experiments showing its efficiency.
virtual framework for testing the reliability of system software on embedded systems. system software development and testing on embedded systems can be quite difficult and time consuming. in this paper, we propose a cost effective method, namely virtual testing framework that can be used easily to test the reliability of system software. the framework consists of three layers; virtual platform layer, system software layer, and test environment layer. the virtual platform layer emulates a variety of embedded hardware on which any system software can be run and is used to verify its capability in handling faults injected by the test environment layer. we use the framework to verify the reliability of the file system and ftl (flash translation layer) by injecting faults that may be found in flash memory. we discuss experimental results that we gained using this framework to gather post-fault behavior of the system software of interest.
smask: preventing injection attacks in web applications by approximating automatic data/code separation. web applications employ a heterogeneous set of programming languages: the language that was used to write the application's logic and several supporting languages. supporting languages are e.g., server-side languages for data management like sql and client-side interface languages such as html and javascript. these languages are handled as string values by the application's logic. therefore, no syntactic means exists to differentiate between executable code and generic data. this circumstance is the root of most code injection vulnerabilities: attackers succeed in providing malicious data that is executed by the application as code. in this paper we introduce smask, a novel approach towards approximating data/code separation. by using string masking to persistently mark legitimate code in string values, smask is able to identify code that was injected during the processing of an http request. smask works transparently to the application and is implementable either by integration in the application server or by source-to-source translation using code instrumentation.
evaluation of interval-based dynamic voltage scaling algorithms on mobile linux system. during the last several years, dynamic voltage scaling (dvs) algorithms are being used for energy consumption on real, fully functional battery supplied devices, adjusting the clock speed and supply voltage dynamically. most dvs algorithms are investigated in interval-based and task-based strategies. task-based algorithms consider task information, especially task deadline, on deciding what speed to choose at any given time. interval-based algorithms predict the cpu speed of the upcoming interval based on observations of the cpu utilization of previous intervals, and then set the speed for that interval based on this prediction. most dvs algorithms have only been tested in simulation environments. in this paper, those interval-based dvs algorithms are modified with different parameters on different workloads, and evaluated to know which one saves the most energy while not degrading computer performance.
an effective cost model for similarity queries in metric spaces. this short paper presents an effective cost model to estimate the number of disk accesses (i/o cost) and the number of distance calculations (cpu cost) to process similarity range queries over data indexed by metric access methods.
a taxonomy of mobile and pervasive applications. in this paper we present a taxonomy for characterizing pervasive applications. this taxonomy focuses on abstracting <u>application</u> characteristics, independent of the characteristics of the middleware or infrastructure that support the application, and provides a controlled vocabulary for thinking about the application. we provide an informal verification for the taxonomy by using it to categorize a range of pervasive applications, culled from the literature and from projects we are involved in, and showing that the taxonomy is (a) <u>consistent and complete</u> - similar applications are categorized similarly and applications that are different are not similarly categorized and (b) <u>useful</u> - each characteristic provides new information about applications not explained by the other characteristics. finally, we present concrete uses for the taxonomy.
requirements for information systems model-based testing. in order to develop systems with a high level of quality and low costs it is necessary to have adequate testing tools and methods. we believe that the definition of a requirements catalog is one of the steps in such direction. this work presents a requirements catalog for information systems model-based testing that can be used as a basis for improving methods as well as a guide for the development of new methods and tools. the catalog was prepared based on the literature of the area and on the experience of several information systems developers.
mojohon: a channel-driven communication architecture for applications deployed on the internet. we present a layered architecture, named mojohon, designed to allow the communication among two or more instances of a distributed application while maintaining a high level of abstraction with respect to the communication facilities available. mojohon, which encompasses distributed modules for transmission, reception, reflection, adaptation, monitoring and configuration, has been defined so as to be used by applications to exchange control and data messages even when instances of the applications are unable to directly address each other -- for instance, when one or more instances are running behind nat. we also present a proof-of-concept multimedia application, developed using mojohon, which uses an asynchronous communication middleware for control message exchange and rtp/udp datagrams for data exchange.
tracking multiple mobile objects using ieee 802.15.4-based ultrasonic sensor devices. an ultrasound tracking system is an inexpensive and accurate technique for indoor object tracking. in this paper, we describe an ieee 802.15.4-based active tracking system that tracks multiple mobile objects effectively. we analyze the problems of the active tracking system with multiple objects and propose an adaptive beaconing algorithm as the solution. in our algorithm, mobile nodes overhear the beacon messages of other mobile nodes and adaptively adjust their beaconing periods to avoid a simultaneous ultrasound pulse. we implemented the tracking system in a real environment and measured the performance of the system. the experimental results show that our algorithm successfully works with multiple mobile nodes and improves performance on the success rate.
integration of well posedness analysis in software engineering. this paper advocates the use of well posedness analysis as a tool to use in software engineering. well posedness analysis as a problem solving tool has seen too little use, especially in computer science and software engineering. a problem is well posed if and only if: (1) at least one solution exists, (2) at most one solution exists, and (3) the solution is stable. here well posedness analysis is described as an augmentation to software engineering as an approach to improving software quality.
off-line signature verification based on forensic questioned document examination approach. there are different methods for signature verification proposed in the literature. most of them, take into account a personal model, i.e., they need a considerable number of genuine signatures of the same writer to correctly train the model. this is the main drawback of this kind of approach, since in real applications we have small number of samples available for training. in this paper we propose an off-line signature verification method based on forensic questioned document examination approach. this kind of strategy reduces any classification problem to a 2-class problem, hence, makes it possible to build robust signature verification systems even when few signatures per writer are available. comprehensive results on a database composed of 240 writers (40 samples per writer) demonstrate the efficiency of the proposed method.
a java code annotation approach for model checking software systems. many works related to the verification of software systems using model checking integrated to development environments have been proposed. jpf [7] and bandera [1] are examples of such works that abstract the model to be verified from the java code. an alternative way for jpf and bandera approaches is to provide mechanisms for describing the model during the programming task. thus, it is possible to integrate such mechanisms to the development environment and hide the model checking task from the programmer.
a mobile sensor control method for sparse sensor networks. due to the ability to construct a large-scale sensing system by the cooperative behaviors of multiple sensor nodes, sensor networks are expected to be applied to many applications such as environmental monitoring. on the other hand, with the development of robotics technology in recent years, there has been many studies on sensors with a moving function (mobile sensors). in this paper, we propose an effective mobile sensor control method for sparse sensor networks. our method uses two types of sensor nodes, fixed node and mobile node. the data acquired by nodes are accumulated on a fixed node before transferred to the sink node. in addition, our method transfers the accumulated data efficiently by constructing the communication route of multiple mobile nodes between fixed nodes. we also conducted simulation experiments to evaluate the performance of our method.
a framework and a tool for robustness testing of communicating software. robustness testing aims at verifying the acceptable behavior of a system under unexpected conditions. in this paper we propose a framework and a tool for robustness test cases generation. our framework consists of two phases: (1) construction of an increased specication by integrating hazards in the nominal specification model written in sdl. the rule of the increased specification is to specify the acceptable behavior in presence of hazards. (2) a specific method to generate robustness test cases (in ttcn-3) from the increased specification and a robustness test purpose. we also give some experimental results on the tcp protocol.
-anonymization incremental maintenance and optimization techniques. new privacy regulations together with ever increasing data availability and computational power have created a huge interest in data privacy research. one major research direction is built around k-anonymity property, which is required for the released data. although many k-anonymization algorithms exist for static data, a complete framework to cope with data evolution (a real world scenario) has not been proposed before. in this paper, we introduce algorithms for the maintenance of k-anonymized versions of large evolving datasets. these algorithms incrementally manage insert/delete/update dataset modifications. our results showed that incremental maintenance is very efficient compared with existing techniques and preserves data quality. the second main contribution of this paper is an optimization algorithm that is able to improve the quality of the solutions attained by either the non-incremental or incremental algorithms.
va-tcp: a vertical handoff-aware tcp. a vertical handoff occurs when a multi-homed mobile host roams from a network to another heterogeneous network. nevertheless, the network before and after a vertical handoff usually have drastic different characteristics. in this paper, we proposed an end-to-end based vertical-handoff aware tcp, called va-tcp, which promptly adapts tcp behavior during a vertical handoff. when entering a new network, on the basis of packet-pair algorithm, va-tcp dynamically estimates the new network bandwidth and round-trip time by using out-of-band icmp messages. after that, by the estimated bandwidth and round-trip time, va-tcp adjusts the tcp parameters including congestion window size, slow-start threshold, retransmission timer and rtts to respond to the new network environment. from the experimental result, the tcp throughput by the proposed va-tcp scheme is around 2 times that by the original tcp.
gradual transition towards autonomic software systems based on high-level communication specification. while management of today's software systems is usually performed by humans using some user interface (ui), autonomic systems would be self-managed. they would typically consist of a managed element, which provides actual system functionality, and an autonomic manager performing system management. however, truly self-managed systems are hard to achieve and not (yet) in wide-spread use. during the transition towards autonomic software systems it is more realistic to manage a large and complex software system partly by humans and partly by an autonomic manager. for facilitating this approach, the communication between the managed element and human administrators on the one hand and the communication between the managed element and the autonomic manager on the other, should be unified and specified on the same semantic level. however, there is no scientific basis for such a unified communication approach. we present a unified specification of this communication in a high-level discourse model based on insights from theories of human communication. this approach would make this communication "natural" for humans to define and to understand. in addition, we propose to use the same specification for the automated generation of user interfaces for management by human administrators. as a consequence, a smooth and gradual transition towards self-managed software systems will be facilitated, where the portion managed by human administrators becomes smaller and smaller.
a fast algorithm to binarize and filter documents with back-to-front interference. whenever one finds documents written on both sides on translucent paper there is a "back-to-front interference". the direct binarization of such documents yields unreadable documents. this paper presents a fast segmentation-based method for generating high-quality binarized images of documents with back-to-front interference. the proposed segmentation algorithm is based on the entropy of the histogram of the image.
context-aware feature-oriented modeling with an aspect extension of vdm. separation of concerns is important to reduce the complexity of software design. this paper examines a software development method starting with the feature-oriented modeling method to have vdm-based formal design. in order to overcome the problem that a feature may be scattered over the vdm design description, the notion of the aspect is adapted to propose aspect vdm. the identified features are concisely represented in aspect vdm to demonstrate modular descriptions of cross-cutting concerns in vdm.
an adaptive data prefetching scheme for biosequence database search on reconfigurable platforms. searching on dna and protein databases using sequence comparison algorithms has become one of the most powerful techniques to better understand the functionality of particular biological sequences. however, the requirements to process the biological data exceed the ability of general-purpose processor. the core of sequence alignment algorithm was implemented as fine-grained parallel architecture that was running on a commercial-off-the-shelf (cots) fpga board, where supercomputer performance has been achieved. however, reconfigurable computing platforms have utilized a pci bus as the communications channel, limiting the communication speed between the host processor and the fpga. this communication bottleneck often offsets the application speedup enabled by fpga. in this paper we present an adaptive data prefetching scheme to avoid reconfigurable coprocessor stalls due to data unavailability through profiling techniques and quantitative analysis. experimental results satisfied time constraints with various query sequences and show that we can effectively eliminate a major portion of data access penalty.
self-organizing broker topologies for publish/subscribe systems. distributed publish/subscribe systems are usually deployed on top of an overlay network that enables complex routing strategies implemented in the application layer. up to now, only little effort has been spent on the design of the broker overlay network assuming that it is either static or manually administered. as publish/subscribe systems are increasingly targeted at dynamic environments where client behavior and network characteristics vary over time, static overlay networks lead to suboptimal performance. in this paper, we present a self-organizing broker overlay infrastructure that adapts dynamically to achieve a better efficiency on both, the application and the network layer. this is obtained by taking network metrics as well as notification traffic into account.
a progressive learning method for symbols recognition. this paper deals with a progressive learning method for symbols recognition which improves its own recognition rate when new symbols are recognized in graphics documents. we propose a discriminant analysis method which provides allocation rules from learning samples with known classes. however a discriminant analysis method is efficient only if learning samples and data are defined in the same conditions but it is rare in real life. in order to overcome this problem, a conditional vector is added to each observation to take into account the parasitic effects between the data and the learning samples. we propose also an adaptation to consider the user feedback.
semi-automatic model integration using matching transformations and weaving models. model transformations are at the heart of model driven engineering (mde) and can be used in many different application scenarios. for instance, model transformations are used to integrate very large models. as a consequence, they are becoming more and more complex. however, these transformations are still developed manually. several code patterns are implemented repetitively, increasing the probability of programming errors and reducing code reusability. there is not yet a complete solution that automates the development of model transformations. in this paper we propose a novel approach that uses matching transformations and weaving models to semi-automate the development of transformations. matching transformations are a special kind of transformations that implement heuristics and algorithms to create weaving models. weaving models are models that capture different kinds of relationships between models. our solution enables to rapidly implement and to customize these heuristics. we combine different heuristics, and we propose a new metamodel-based heuristic that exploits metamodel data to automatically produce weaving models. the weaving models are derived into model integration transformations.
automating model transformation by example using inductive logic programming. model transformation by example [18] is a novel approach in model-driven software engineering to derive model transformation rules from an initial prototypical set of interrelated source and target models, which describe critical cases of the model transformation problem in a purely declarative way. in the current paper, we automate this approach using inductive logic programming [14] which aims at the inductive construction of first-order clausal theories from examples and background knowledge.
system support for mobile augmented reality services. developing and deploying augmented reality (ar) services in pervasive computing environments is quite difficult because almost of all current systems require heavy and bulky head-mounted displays (hmds) and are based on inflexible centralized architectures for detecting service locations and superimposing ar images. we propose a light-weight mobile ar service framework that combines personal mobile devices most of people own nowadays, visual tags as inexpensive ar techniques, and mobile code that enables easy-to-deploy environments. our framework enables developers to easily deploy mobile ar services in pervasive computing environments and users to interact them in a both of practical and intuitive way.
quorum-based consistency management among replicas in ad hoc networks with data update. in this paper, we propose a consistency management method that constructs quorums with a small number of mobile hosts in ad hoc networks. in this method, when a mobile host discovers paths to other mobile hosts that construct quorums, it restricts the propagation area of query packets. as a result, this method can reduce the communication overhead while keeping the strict consistency among replicas.
capturing data usefulness and privacy protection in k-anonymisation. k-anonymisation is an approach to protecting privacy contained within a data set. a good k-anonymisation algorithm should anonymise a data set in such a way that private information contained within it is hidden, yet anonymised data is still useful in intended applications. maximising both data usefulness and privacy protection in k-anonymisation is however difficult. in this paper, we suggest a metric that attempts to quantify these two properties and introduce a clustering based algorithm that can achieve a balance between them in k-anonymisation.
bounded-distance multi-coverage backbones in wireless sensor networks. topology control can improve the performance of wireless sensor network (wsn) by allowing only a subset of nodes to be active at any time with guaranteed network coverage. we present the first centralized and distributed solutions for computing bounded-distance multi-coverage backbones in wsns. the solutions are based on the (k, r)-cds problem from graph theory for computing backbones in which any regular node is covered by at least k backbone members within distance r, offering a variable degree of redundancy and reliability. applications that require reliable data gathering with bounded-delays are the intended targets for such structures. given that the centralized solution is unsuitable for wsns, because of the incurred control overhead, it is used as a lower bound for evaluating the performance of the distributed solution. the distributed solution is source-based in the sense that usually the base-station (or sink) is the focus of attention in a wsn. the two approaches are evaluated through extensive simulations, and it is shown that even though the distributed solution builds larger backbones, it does not incur on much control overhead.
an aspect-generated approach for the integration of applications into grid. updating legacy applications to let them properly run in a grid environment generally requires a noticeable development effort. the approach proposed in this work is intended to reduce this effort through the automated generation of aspects that, once incorporated into legacy applications, ensure integration with the globus grid environment. the generated aspects encapsulate concerns handling the interaction with globus services, thus keeping the relevant code separated from application classes.
a component-based framework for the internet content adaptation domain. small mobile devices for accessing the internet through wireless access networks have become increasingly common in recent years. in this new context, a major challenge is the adaptation of content to these devices, satisfying their capabilities and user preferences and optimizing the use of wireless access networks. this paper therefore presents a framework based on component reuse for the development of applications for internet content adaptations.
videolib: a video digital library with support to spatial and temporal dimensions. nowadays, a large amount of digital video can be found on the web, and this number is increasing rapidly. metadata should be associated to video in order to enable an efficient identification, indexing and semantic representation of it, so that effective video information retrieval tools can be built. both dublin core and mpeg-7 standards provide a metadata set which enables the description of multimedia content. this paper presents a video digital library, known as videolib, which utilizes dublin core and mpeg-7 audiovisual descriptions to provide video content retrieval. mainly, videolib enhances video retrieval by introducing spatial and temporal operators.
a new adaptive accrual failure detector for dependable distributed systems. the detection of failures in distributed environments is a crucial part for developing dependable, robust, and self-healing systems. the contribution of this paper is a new failure detection algorithm that can be described as an adaptive accrual algorithm coupled with features to increase flexiblity and decrease computation costs. furthermore our evaluation results show a very good detection quality in the case of message losses.
mass edge detection in mammography based on plane fitting and dynamic programming. in this paper an automatic and effective method was proposed for mass segmentation in mammography. based on the facts that mass edges are continuous and closed curves consisted of points which have larger gradient transformation, a plane fitting method and a dynamic programming technique were applied. the regions of interest (rois) used in this study were extracted from ddsm. the preliminary experimental results show that the segmentation algorithm performs well for various types of masses.
la-tinyos: a locality-aware operating system for wireless sensor networks. a number of wsn (wireless sensor networks) applications have been deployed to monitor the environment periodically and identify anomalous events. anomalous events occur rarely. however, when an anomaly event occurs, it often carries temporal and spatial locality. observations of such events are improved by reducing the period of monitoring to increase the frequency. a task is said to be locality-aware if it supports temporal and spatial locality to automatically adjust its monitoring period. this work implements locality-aware tinyos or la-tinyos as the first locality-aware wsn operating system. with locality-aware features embedded in a kernel component, la-tinyos provides a reliable and efficient framework for developing locality-aware applications. the novel la-tinyos has significantly (more than 80%) reduce the lines of user code to perform such a task, than does tinyos. finally, we use la-tinyos to develop a locality-aware monitoring application using two dozen micaz sensors. this system is currently deployed in the reading room of public library at our university to record noise violation events.
multidimensional querying in wireless ad hoc networks. as mobile ad hoc networks (manets) become more present, new ways of data exchange become feasible. this paper presents the case of multidimensional querying in wireless ad hoc networks. new challenges both in comparison with querying of relational data in manets and respective multidimensional querying in infrastructure based wireless networks are outlined. the main objective is the optimal execution of a multidimensional query, in terms of generated traffic, access time and energy consumption overhead. in order to address these topics, we introduce a simple and collaborative query propagation and data dissemination protocol, exclusively tailored for multidimensional data. extensive performance evaluation validates the efficiency and robustness of the proposed protocol.
using hypothesis margin to boost centroid text classifier. centroid classifier is a simple and yet efficient method for text categorization. however it often suffers from the inductive bias or model misfit incurred by its assumption. in order to address this issue, training-set errors as well as training-set margins are regarded as training criterions. based on these two criterions, an overall (or global) objective function over all training examples is constructed, and optimized to produce a refined centroid classification model. the empirical assessment conducted on four benchmark collections evidence that proposed method performs comparably to state-of-the-art svm classifier in classifying performance, as well as beats it in running time.
large scale news video database browsing and retrieval via information visualization. in this paper, we have developed a novel framework to enable more effective visual analysis and retrieval of large-scale news videos via interactive visualization, so that the audiences can find news stories of interest at first glance. keyframes and keywords are automatically extracted from news video clips and visually represented according to their interestingness measurement and relations. a computational approach is also developed to quantify the interestingness measurement of video clips. our experimental results have shown that our techniques for intelligent news video analysis have the capacity to enable more effective visualization and retrieval of large-scale news videos. our visualization-based news video analysis and retrieval system is very useful for security applications and for general audiences to quickly find the news stories of interest from large-scale news videos among many channels.
solving conditional and composite constraint satisfaction problems. constraint satisfaction problems (csps) have been widely used to solve combinatorial problems. in order to deal with dynamic csps where the information regarding any possible change is known a priori and can thus be enumerated beforehand, conditional constraints and composite variables have been studied in the past decade. indeed, these two concepts allow the addition of variables and their related constraints in a dynamic manner during the resolution process. more precisely, a conditional constraint restricts the participation of a variable in a feasible scenario while a composite variable allows us to express a disjunction of variables where only one will be added to the problem to solve. in this paper we introduce a unique csp framework including conditional constraints and composite variables. we call this model, a conditional and composite csp (or cccsp). in order to solve a cccsp, we propose two methods respectively based on stochastic local search (sls) and backtrack search with constraint propagation. the experimental comparison of these two methods, on randomly generated consistent cccsps, demonstrates the efficiency of the exact method based on constraint propagation in the case of middle and under constrained problems while the sls based method is the technique of choice for highly constrained problems and also in case we want to trade search time for the quality of the solution returned (number of solved constraints).
semi-mechanization method for a unsolved optimization problem in combinatorial geometry. this paper presents a new semi-mechanization method for proving the validity of an inequality conjecture about convex n-gon when n = 8 and gaining headway in proving it when n = 9. this conjecture is generally converted into a global optimization problem which is related to heilbronn triangular problem. for solving it, the bottleneck is the complexity increasing very quickly with n. in the proposed algorithm, to reduce the dimension of freedom we first analyze the properties of the optimal configurations and try to obtain the strict polynomial inequality and equality conditions as many as possible. after the precondition, the mechanization method can be implemented to solve this nonlinear optimization problem, so we call the overall approach as semi-mechanization method. we hope our algorithm will be useful for proving the conjecture with larger value of n.
equivalent disk allocations. declustering techniques reduce query response times through parallel i/o by distributing data among multiple devices. except for a few cases it is not possible to find declustering schemes that are optimal for all spatial range queries. as a result of this, most of the research on declustering have focused on finding schemes with low worst case additive error. number-theoretic declustering techniques provide low additive error and high threshold. in this paper, we investigate equivalent disk allocations and focus on number-theoretic declustering. most of the disk allocations are equivalent and provide the same additive error and threshold. investigation of equivalent allocations offer many advantages. by keeping one of the equivalent disk allocations, we can reduce the complexity of search for good disk allocations under various criteria such as additive error and threshold. probabilistic approaches to finding good declustering schemes is feasible using equivalent allocations.
mining multiple private databases using a knn classifier. modern electronic communication has collapsed geographical boundaries for global information sharing but often at the expense of data security and privacy boundaries. distributed privacy preserving data mining tools are increasingly becoming critical for mining multiple databases with a minimum information disclosure. we present a framework including a general model as well as multi-round algorithms for mining horizontally partitioned databases using a privacy preserving k nearest neighbor (knn) classifier. a salient feature of our approach is that it offers a trade-off between accuracy, efficiency and privacy through multi-round protocols.
performance monitor unit design for an axi-based multi-core soc platform. as the physical gate-count in system-on-chip (soc) system increases and system design complexity grows steadily, it becomes more and more difficult to achieve good resource utilization by assigning each task to certain hardware ip and tracing the execution patterns of each task efficiently. therefore, the performance monitoring feature is getting more and more important to provide the ease of system monitoring and performance debugging. in this paper, we present a performance monitoring unit (pmu) for the amba advanced extensible interface (axi) bus. the pmu has capability to measure major performance metrics, such as bus latency for the specific master requests and amount of memory traffic for specific durations. it can also measure the contention of the bus masters and slaves in the soc. we present the distributor and the synchronization method to use multiple performance counting units as well. the performance monitoring unit has been verified in the platform fpga board with 9 by 4 axi interconnect configuration. these monitoring features can give the insight to system design architect by helping to find and analyze the performance bottleneck of target system.
towards an homogeneous handling of under-constrained and well-constrained systems of geometric constraints. most of the geometric constraints solvers consider systems of constraints well-constrained modulo the rigid motions group, and either halt on error when they encounter under-constrained sub-systems, or attempt to add parameterized constraints so as to get rid of the under-constriction. we studied transformations groups making well-constrained some problems that are usually considered as under-constrained. this leads to new algorithms which allow an homogeneous handling of systems of geometric constraints and thus a better adaptation to the needs of the user.
a methodology for the separation of foreground/background in arabic historical manuscripts using hybrid methods. this paper presents a new color document image segmentation system suitable for historical arabic manuscripts. our system is composed of a hybrid method which couple together background light intensity normalization algorithm and k-means clustering with maximum likelihood (ml) estimation, for foreground/background separation. firstly, the background normalization algorithm performs separation between foreground and background. this foreground is used in later steps. secondly, our algorithm proceeds on luminance and distort the contrast. these distortions are corrected with a gamma correction and contrast adjustment. finally, the new enhanced foreground image is segmented to foreground/background on the basis of ml estimation. the initial parameters for the ml method are estimated by k-means clustering algorithm. the segmented image is used to produce a final restored document image. the techniques are tested on a set of arabic historical manuscripts documents from the national tunisian library. the performance of the algorithm is demonstrated on by real color manuscripts distorted with show-through effects, uneven background color and localized spot.
extending the arc model with generative coordination. the arc (actor, role, coordinator) model extends the actor model with roles and coordinators to achieve a behavior-based coordination model that preserves the semantics of the actor model. an arc role coordinates a dynamic set of actors whose intensional representation and membership criteria are defined by a static description of abstract behavior. an arc coordinator enacts role-based coordination policies expressed in terms of arc roles. in this paper, we focus on the satisfaction of functional coordination requirements via the generation and manipulation of actor messages by role and coordinator actors in the arc model.
federated directories of semantic web services. this paper presents a federated directory system called ws-dir, which allows registration and discovery of semantic web services. the system is designed and implemented as a federation: directory services form its atomic units, and the federation emerges from the registration of directory services in other directory services. directories are virtual clusters of service entries stored in one or more directory services. to create the topology, policies are defined on all possible operations to be called on directories.
performance problem localization in self-healing, service-oriented systems using bayesian networks. in distributed, service-oriented environments, performance problem localization is required to provide self-healing capabilities and deliver the desired quality of service (qos). this paper presents an automated approach to identifying system elements causing performance problems. applying probabilistic inference to collected response time and elapsed time data, the approach 1) infers elapsed time for services where data is missing, 2) estimates the response time degradation caused by different services using the duration, abnormality and response time correlation of their elapsed times, and 3) identifies the services that are the most important causes of slow response time and yield the most benefit if recovered. the approach has been used to localize a performance problem on the test bed of a real-world service-oriented grid. evaluation using simulations shows that the approach consistently achieves better accuracy than traditional techniques in various service-oriented settings.
dynamic populations in genetic algorithms. biological populations are dynamic in both space and time, that is, the population size of a species fluctuates across their habitats over time. there are rarely any static or fixed size populations in nature. in evolutionary computation (ec), population size is one of the most important parameters and it received attention from ec pioneers from the very beginning. despite many attempts to optimize the population sizing, the prevailing scheme in ec is still possibly the simplest --- the fixed size population. this is in strong contrast with population entities in nature. in this paper, we explore the effects of dynamic (fluctuating) populations on the performance of genetic algorithms (ga). in particular, we test five dynamic population-sizing patterns: random fluctuating population, increasing population, decreasing population, bell-shaped population, and inverse bell-shaped population and compare them against the fixed size population. our experiment shows very promising results that the dynamic populations perform more efficiently than the traditional fixed size populations, in terms of the number of fitness function evaluations and memory space requirements. we also analyze why the dynamic populations should perform superior to the fixed size populations from the biological perspective.
decentralized web service orchestration: a reflective approach. web service orchestration is widely spread for the creation of composite web services using standard specifications such as bpel4ws. the myriad of specifications and aspects that should be considered in orchestrated web services are resulting in increasing complexity. this complexity leads to software infrastructures difficult to maintain with interwoven code involving different aspects such as security, fault tolerance, distribution, etc. in this paper, we present zen-flow a reflective bpel engine that enables to separate the implementation of different aspects among them and from the implementation of the regular orchestration functionality of the bpel engine. we illustrate its capabilities and performance exercising the reflective interface through a decentralized orchestration use case.
engineering intuitive and self-explanatory smart products. one of the main challenges in ubiquitous computing is making users interact with computing appliances in an easy and natural manner. in this paper we discuss how to turn ordinary devices into smart products that are more intuitive to use and are self-explanatory. we present a general architecture and a distributed runtime environment for building such smart products and discuss a number of user interaction issues. as an example, we describe our smart coffee machine and its validation through systematic user testing.
bwt-based efficient shape matching. effective shape-based image retrieval requires an appropriate representation of object shape contours. such a representation should be invariant under certain transformations, such as those due to rotation, scaling, partial occlusion, noise in the image, or changes in the viewing geometry. given a shape boundary, we decompose it into primitive shape segments that capture the saliency of object parts, and perform retrieval based on the primitives. motivated by the sorted contexts of the burrows-wheeler transform, we present an algorithm for efficient shape matching, suitable for large-scale shape databases, when the shape boundaries are represented as a sequence of shape primitives. given a query shape, the algorithm can locate all the potential areas in the database where a match could occur in time that is logarithmic with respect to the database size. the potential matches are then verified in time that is linear with respect to the number of potential matches. performance of the proposed algorithm is evaluated using both synthetic and real shape databases.
modular multiple dispatch with multiple inheritance. overloaded functions and methods with multiple dispatch are useful for extending the functionality of existing classes in an object-oriented language. however, such functions introduce the possibility of ambiguous calls that cannot be resolved at run time, and modular static checking that such ambiguity does not exist has proved elusive in the presence of multiple implementation inheritance. we present a core language for defining overloaded functions and methods that supports multiple dispatch and multiple inheritance, together with a set of restrictions on these definitions that can be statically and modularly checked. we have proved that these restrictions guarantee that no undefined nor ambiguous calls occur at run time, while still permitting various kinds of overloading.
self-healing for autonomic pervasive computing. self-healing is one of the main challenges to growing autonomic pervasive computing. fault detection and recovery are the main steps of self-healing. due to the characteristics of pervasive computing the self-healing becomes difficult. in this paper, the challenges of self-healing have been addressed and an approach to develop a self-healing service for autonomic pervasive computing is presented. the self-healing service has been developed and integrated into the middleware named marks+ (middleware adaptability for resource discovery, knowledge usability, and self-healing). the self-healing approach is being evaluated on a test bed of pdas. an application is being developed by using the proposed service.
semantic distance of concepts within a unified framework in the biomedical domain. this paper presents a cross-ontology approach, as an extension of the cluster-based approach, to measure semantic distance between concepts within single ontology or between concepts dispersed in multiple ontologies in a unified framework in the biomedical domain. the experimental results (with ~0.81 correlation with human scores) confirmed that the proposed approach is effective and has great potential in measuring semantic distance using multiple ontologies in a unified framework.
sipre: a partial database replication protocol with si replicas. database replication has been researched as a solution to overcome the problems of performance and availability of distributed systems. full database replication, based on group communication systems, is an attempt to enhance performance that works well for a reduced number of sites. if application locality is taken into consideration, partial replication, i.e. not all sites store the full database, also enhances scalability. on the other hand, it is needed to keep all copies consistent. if each dbms provides si, the execution of transactions has to be coordinated so as to obtain generalized-si (gsi). in this paper, a partial replication protocol providing gsi is introduced that gives a consistent view of the database, providing an adaptive replication technique and supporting the failure and recovery of replicas.
a hybrid web recommender system based on q-learning. different efforts have been made to address the problem of information overload on the internet. recommender systems aim at directing users through this information space, toward the resources that best meet their needs and interests. web content recommendation has been an active application area for information filtering, web mining and machine learning research. recent studies show that combining the conceptual and usage information can improve the quality of web recommendations. in this paper we exploit this idea to enhance a reinforcement learning framework, primarily devised for web recommendations based on web usage data. a hybrid web recommendation method is proposed by making use of the conceptual relationships among web resources to derive a novel model of the problem, enriched with semantic knowledge about the usage behavior. with our hybrid model for the web page recommendation problem we show the apt and flexibility of the reinforcement learning framework in the web recommendation domain, and demonstrate how it can be extended in order to incorporate various sources of information. we evaluate our method under different settings and show how this method can improve the overall quality of web recommendations.
neural network based systems for computer-aided musical composition: supervised x unsupervised learning. this ongoing project describes neural network applications for helping musical composition using as inspiration the natural landscape contours. we propose supervised and unsupervised learning approaches, by using back-propagation-through-time (bptt) and self organizing maps (som) neural networks. in the supervised learning, the network learns certain aspects of musical structure by means of measure examples taken from melodies of the training set and uses these measures learned to compose new melodies using as input the extracted data of the landscapes contour. in the unsupervised learning, the network also uses measure examples as input during training and the extracted data of the landscapes contour in the composition stage. the obtained results show the viability of both approaches.
universal concurrent constraint programing: symbolic semantics and applications to security. we introduce the universal timed concurrent constraint programming (utcc) process calculus; a generalisation of timed concurrent constraint programming. the utcc calculus allows for the specification of mobile behaviours in the sense of milner's &pi;-calculus: generation and communication of private channels or links. we first endow utcc with an operational semantics and then with a symbolic semantics to deal with problematic operational aspects involving infinitely many substitutions and divergent internal computations. the novelty of the symbolic semantics is to use temporal constraints to represent finitely infinitely-many substitutions. we also show that utcc has a strong connection with pnueli's temporal logic. this connection can be used to prove reachability properties of utcc processes. as a compelling example, we use utcc to exhibit the secrecy flaw of the needham-schroeder security protocol.
a self-balancing striping scheme for nand-flash storage systems. to use multiple memory banks in parallel is a nature approach to boost the performance of flash-memory storage systems. however, realistic data-access localities unevenly load each memory bank and thus the benefits of parallelism is severely limited. in this work, we propose to encode popular data with redundancy by means of erasure codes. load balancing is thus achieved by accessing only lightly loaded banks, because to retrieve a subset of data blocks and code blocks sufficiently reconstructs the requested data. the technical issues pertain to redundancy allocation, redundancy placement, and request scheduling. by experiments, we found that, by offering 10% extra redundant space, the read response time is largely improved by 30%.
k-means discriminant maps for data visualization and classification. over the years, many dimensionality reduction algorithms have been proposed for learning the structure of high dimensional data by linearly or non-linearly transforming it into a low-dimensional space. some techniques can keep the local structure of data, while the others try to preserve the global structure. in this paper, we propose a linear dimensionality reduction technique that characterizes the local and global properties of data by firstly applying k-means algorithm on original data, and then finding the projection by simultaneously globally maximizing the between-cluster scatter matrix and locally minimizing the within-cluster scatter matrix, which actually keeps both local and global structure of data. low complexity and structure preserving are two main advantages of the proposed technique. the experiments on both artificial and real data sets show the effectiveness and novelty of proposed algorithm in visualization and classification tasks.
organizational modeling with a semantic wiki. this paper presents a basic set of modeling primitives with the purpose of enabling the construction of semantically rich and coherently integrated organizational models, in the context of enterprise engineering and architecture. this set, called "semantic bootstrap for organizational modeling", is being operationalized through the use of a semantic wiki. this tool's paradigm has a number of key advantages that seem to allow it to function as a master blue print or aggregation tool for the several different blue prints (views) that one can elicit from an organization.
revisiting exact combinational circuit synthesis. the paper revisits exact combinational circuit synthesis with logic programming tools. our focus is finding a minimal cost circuit that matches a specification - a notoriously hard nondeterministic search problem. after an exhaustive expressiveness comparison of various minimal libraries, two asymmetrical operations, logical implication "&rarr;" and strict boolean inequality "<" turn out to consistently outperform their more popular symmetrical couterparts nand and nor, while having comparably small transistor count implementations. the code of the synthetizer and various libraries is available at http://logic.csci.unt.edu/tarau/research/2007/isyn.zip.
middleware of taiwan unigrid. taiwan unigrid (taiwan <u>uni</u>versity <u>grid</u>) is a grid computing platform, which is founded by a community of educational and research organizations interested in grid computing technologies in taiwan. in this paper, we present the design and development of a middleware for taiwan unigrid. taiwan unigrid middleware consists of three primary modules: 1) unigrid portal, 2) computing service, and 3) data service. we explain the major design issues that we suffered from the development of these three modules and propose the corresponding approaches to them. the detailed system architecture, software components and features are elaborated. finally, an example of a workflow consisting of mpi parallel jobs demonstrates that users can utilize grid resources with ease via our middleware platform.
lambda functions for c++0x. a "functional" style of programming has become common in c++, following the introduction of the "standard template library" (stl) into c++'s standard library. c++ is, however, notably lacking in its support for this style and thus cannot take full advantage of its own standard libraries. c++'s mechanisms for defining functions or objects to pass to stl algorithms are overly verbose. the effective use of modern c++ libraries calls for lambda functions in the language. this paper describes a design and implementation of built-in lambda functions for c++. c++'s compilation model, where activation records are maintained in a stack, and the lack of automatic object lifetime management, make safe lambda functions and closures challenging: if a closure outlives its scope of definition, references stored in a closure dangle. our design is careful to balance between conciseness of syntax and explicit annotations to guarantee safety. lambda functions can be declared without annotating their parameter types. c++0x, the forthcoming revision of standard c++, supports constrained templates and modular type checking. we describe how to infer parameter types of lambda functions from the constraints of generic functions in order to support modular type checking in the presence of lambda functions. our design is currently under consideration for adoption to c++0x.
exploiting semantic information on a message exchanging middleware. in this paper we present our efforts on including semantic information on a middleware for message exchanging. the middleware configuration module makes use of a rule-based reasoner that infers the best module to be used on a given configuration of network and application. we have learned that a semantic-enabled message exchanging middleware is useful to decouple not only the application from the underlying communication facilities, but also the middleware itself from the task of selecting the appropriate module for a given configuration of application and underlying network.
a strategy for memory traffic management of bitmap fonts for text visualization in mobile devices. document viewer and browser applications have gained attention in the mobile scenario due to the improvement on accessibility and portability of different kinds of information. however, mobile devices are still limited in relation to memory size, processing capacity and battery. due to these limitations, software engineers that develop mobile applications must find ways to adequate them to the available. in this paper, we describe a strategy to safely manage memory traffic for mobile applications that intensively use bitmap font files, such as a document viewer.
secure deletion for nand flash file system. in most file systems, if a file is deleted, only the metadata of the file is deleted or modified and the file's data is still stored on the physical media. some users require that deleted files no longer be accessible. this requirement is more important in embedded systems that employ flash memory as a storage medium. in this paper, we have designed a nand flash file system that has a secure deletion functionality. we modified yaffs to support secure deletion. our method uses encryption to delete files and forces all keys of a specific file to be stored in the same block. therefore, only one erase operation is required to securely delete a file. the proposed method securely deletes not only keys but also all of the metadata of that file. our simulation results show that the number of block erases due to file creation and file modification is very low and the amortized number of block erases is lower than the simple encryption method. even though we applied our method only to the yaffs, our method can be easily applied to other nand flash file systems.
towards a complete scm ontology: the case of ontologising rosettanet. this paper presents a methodology to derive a supply chain management ontology based on the rosettanet specification framework. a prototype to mechanically derive a core ontology spanning all new partner interface processes in the rosettanet framework is developed and its algorithms to reconcile the ontology structure and to generate a proper subsumption hierarchy are presented. we further present how we designed and referenced outer layer ontologies we analysed to be required to resolve the remaining disparities in the core ontology. the resulting ontology framework enables to more easily deal with different message structures in dynamic business-to-business collaborations and thus ensures a better interoperability for the partners involved.
modular java web applications. as java ee applications increase in size and complexity the constraints imposed by the existing component model restrict their utility. in this paper, we describe a solution to the problem related to building modular and evolvable server-side applications in java. we use eclipse's osgi runtime as a basis for solving the problem and describe its integration in a java ee application server environment.
empirical evaluation of a new structure for adaboost. we propose a mixed structure to form cascades for adaboost classifiers, where parallel strong classifiers are trained for each layer. the structure allows for rapid training and guarantees high hit rates without changing the original threshold. we implemented and tested the approach for two datasets from uci [1], and compared results of binary classifiers using three different structures: standard adaboost, a cascade classifier with threshold adjustments, and the proposed structure.
supporting self-organization for hybrid grid resource scheduling. increasing scale, dynamism, and complexity of hybrid grids make traditional grid resource scheduling approaches difficult. in such grids, where resource volatility and dynamism is common, self-organization is a key technique for autonomous grid nodes to follow basic rules to minimize human participation, and administrative bottlenecks. this paper presents experimental results with a framework for distributed grid resource scheduling. in particular, we study information dissemination, which distributes information about dynamic grid resource states to remote schedulers. the framework helps each autonomous grid node self-organize by (1) self-configuring its operational parameters based on dynamic grid characteristics, and (2) self-adjusting its dissemination behavior by taking feedback from the system. the framework also helps distributed grid schedulers to find the tradeoff between two important performance parameters: dissemination overhead, and query satisfaction rates. we show by simulation that autonomous grid nodes that self-organize into small groups, and compare their local state to the states of other peer nodes, can perform comparable to both (1) similar dissemination protocols that are statically configured for each specific case, and (2) a theoretical central metascheduler that operates on complete knowledge of available resource and offered load states.
hermes: a semantic web-based news decision support system. the emergence of the web has made more and more news items available, however only a small subset of these news items are relevant in a decision making process. therefore decision makers need an information system that is capable of extracting a set of relevant news items automatically. this paper proposes a framework that provides decision makers with the ability to extract a set of news items related to specific concepts of interest. this is accomplished by creating a knowledge base and developing a system that classifies news with respect to the knowledge base.
bolos: blast & ontology linked-homologue stars. the growing number of protein sequences in databases has lead to, among other issues, an increase in redundancy, since many of the new sequences are similar to others already in the databases. while a comprehensive view of the protein space is essential, redundancy hampers large scale searches (such as blast) or studies (comparative genomics, functional genomics). one of the solutions to eliminate redundancy in the protein space is through clustering methods, which group redundant proteins into single entities (clusters). in this work we present bolos, a web tool that combines a clustered protein space with molecular function go term annotations, directed for functional genomics. it allows searches over the cluster space with a raw sequence, a swiss-prot protein or a molecular function go term, and provides three go-based parameters which allow the assessment of cluster quality and biological validity. the user can also chose one of the twelve different significance level cluster spaces available. for each cluster, bolos provides the essential information (name and accession number) about proteins and go terms it contains, as well as relevant statistics, while linking to external databases to allow the users to access further information. bolos is available at: http://xldb.di.fc.ul.pt/biotools/bolos/
configuring features with stakeholder goals. goal models are effective in capturing stakeholder needs at the time when features of the system-to-be have not yet been conceptualized. relating goals to solution-oriented features gives rise to a requirement traceability problem. in this paper, we present a new model-driven extension to an early requirements engineering tool (openome) that generates an initial feature model of the system-to-be from stakeholder goals. enabled by such generative mapping, configuration constraints among variability features can be obtained by reasoning about stakeholder goals.
type-based information flow analysis for bytecode languages with variable object field policies. static, type-based information flow analysis techniques targeted at java and jvm-like code typically assume a global security policy on object fields: all fields are assigned a fixed security level. in essence they are treated as standard variables. however different objects may be created under varying security contexts, particularly for widely used classes such as wrapper or collection classes. this entails an important loss in precision of the analysis. we present a flow-sensitive type system for statically detecting illegal flows of information in a jvm-like language that allows the level of a field to vary at different object creation points. also, we prove a noninterference result for this language.
a wireless hybrid contention/tdma-based mac for real-time mobile application. wireless communication has been successfully used in a variety of mobile applications, including those with real-time requirements. in such systems, timing guarantees are normally obtained by using a tdma-based medium access control (mac) protocol, relying in a coordinator node in charge of time-slots allocation. however, certain applications cannot make use of such coordinator because it simply does not exist, normally due to restrictions in the operation environment. to solve this problem we present in this paper a mac protocol that operates without a central coordinator, with minimum global information, and with no previous assignments of roles to nodes nor resource reservations. our proposed hybrid contention/tdma-based (hct) mac is specially designed to work with ad-hoc wireless networks organized in clusters, providing timely bounded communications both inside and outside the clusters. this paper presents a detailed description of the resource reservation procedure of hct, including an analytical analysis of its expected performance.
special track on geometric constraints and reasoning: editorial message. geometric computing and reasoning (gcr) aims at emphasizing recent trends in the domain of geometric constraint solving and automated, or computer aided deduction in geometry. this year sees the third edition of this technical track of sac.
special track on computer applications in health care: editorial message. in the last few years we have observed the evolution and a growing interest in the application of computer systems in the health care area, opening new possibilities of visualization of medical images, manipulation of medical data, interaction and communication among professional and patients, besides new ways for training and updating professional's knowledge.
special track on mobile computing and applications: editorial message. riding on the success of the previous mobile computing and applications track in 2003 to 2007, we are delighted to present the 2008 mobile computing and applications track that features research papers drawn from a highly diversified spectrum of mobile computing. we have been receiving an increasing number of submissions, hitting again a record high. the papers collected in this track cover three different and yet complementary areas: mobile applications that are supported by virtue of appropriate architectures and protocols, operating under specific mobile networks and devices. in particular, special attention was dedicated to draw upon research efforts and expertise from different areas of research, so as to promote better synergy and to bring forth not only core mobile communications and networking protocols for application development, but also important research applications to realize the benefits of anywhere, any place and anytime pervasive and ubiquitous computing.
collaborative software engineering on large-scale models: requirements and experience in modelbus. this work presents an approach for realizing model-driven software engineering in the distributed and multi-developers context. it particularly focuses on the scalability problems in a complex software project involving a large set of inter-connected models: (1) how to manipulate large data volume with limited computing resources, and (2) how to maintain consistency of inter-model links in a large model set, facing to concurrent model updates. as a solution, we propose the scalable copy-modify-merge mechanism, which allows each developer to copy only a model subset from the entire model set, to manipulate this subset locally, and to merge it back to the repository. this mechanism ensures the global consistency of the model set, particularly against dangling links. our approach is generic: it is applicable to all model types (uml and domain-specific models). also, it offers interoperability with existing, heterogeneous case tools. its prototype implementation in the modelbus environment is now available on the eclipse project "mddi".
a c++ environment for dynamic unanticipated software evolution. in this paper, we introduce a c++ environment for dynamic unanticipated software evolution. such an environment is composed of a c++ framework called ccf and a c++ application server called ccas. ccf is a framework for developing component based software supporting dynamic unanticipated evolution. such a framework implements the compor component model specification, which provides mechanisms to evolve applications at runtime, even for unpredicted changes. ccas manages the applications implemented through the ccf. we describe the ccf and ccas design and main implementation issues. in order to validate the proposed environment, we implemented an application for a linux based mobile device that encodes/decodes files using the djvu format.
a decision model for implementing product lines variabilities. software product lines (spls) encompass a family of software systems developed from reusable assets. one issue during spl development is the decision about which technique should be used to implement variabilities and improve the separation of concerns (soc) of the spl. in this paper, we present an initial decision model based on both qualitative and quantitative analysis to guide developers on choosing suitable techniques for implementing spl variabilities.
a lifecycle approach to soa governance. due to the distributed nature of service-oriented architectures (soa), maintaining control in a soa environment becomes more difficult as services spread over different lines-of-business. the concept of soa governance has emerged as a way to implement control mechanisms in a soa. in this paper we identify a lifecycle based approach for executing soa governance. this approach consists of defining a soa strategy, aligning the organization, managing the service portfolio, controlling the service lifecycle, enforcing policies and managing service levels. by incorporating a maturity model in this approach, it is possible to minimize the required effort while still having sufficient governance. from a series of interviews that have been carried out we could conclude that most current soa projects - although relatively limited in their scope - raise governance issues that need to be addressed to prevent future problems.
deciding what to observe next: adaptive variable selection for regression in multivariate data streams. variable selection can be valuable in the analysis of streaming data with costly measurements, as in intensive care monitoring or battery-powered sensor networks. in the presence of drift, selections must be constantly revised, calling for adaptive variable selection schemes. an important and novel problem arises from the fact that non-selected variables become missing variables, which induces bias upon subsequent decisions. here, we consider adaptive variable selection in the context of linear regression, using only a fraction of the available regressors per timepoint. we suggest a scheme that fits a multivariate gaussian over a sliding window using the em algorithm and selects which variables to observe next using the lasso algorithm. we experiment with simulated and real data to demonstrate that very high prediction accuracy may be retained using as little as 10% of the data.
designing ic structures by variety engineering. value creation increasingly relies on the bundling of physical products and services from different providers in networks such as supply chains. the complexity that arises from this cooperation is of utmost importance for management since the provision of an undisturbed flow of information affects the performance of the whole network. in this paper we develop a method for the analysis and design of information and communication structures. building on the design science research framework and using an exemplary case, we show how coordination complexity can be analyzed and measured. the results are combined with theoretical concepts from management cybernetics and create the foundation for the constructed method.
workflow management versus case handling: results from a controlled software experiment. business process management (bpm) technology has become an important instrument for improving process performance. when considering its use, however, enterprises typically have to rely on vendor promises or qualitative reports. what is still missing and what is also demanded by it decision makers are quantitative evaluations based on empirical and experimental research. this paper picks up this demand and illustrates how experimental research can be applied in the bpm field. the conducted experiment compares efforts for implementing a sample business process either based on standard workflow technology or on a case handling system. we motivate and describe the experiment design, discuss threats for the validity of experiment results (as well as risk mitigations), and present experiment results. in general, more experimental research is needed in order to obtain more valid data on the various aspects and effects of bpm technology and tools.
cprm: a chronic patient's management model based on the concepts of customer's relationship. this paper presents a chronic patient follow-up and attendance model based on the concepts of customers' relationship used in companies, mainly those available in crm technology (customer relationship management). the model was designated as chronic patient's relationship management (cprm). the cprm model, by using the crm concept on patient attendance, presents a strategy to follow-up and monitoring the chronic patient different from the usual traditional medical approach, which many times consists only in illness treatment. in the same way as the crm, this model is able to reach clients of every condition through its communication channels; and suggests the use of the same technology in order to guarantee an effective and suitable follow-up for all social layers. to implement the cprm model, the creation of relationship centers for chronic patients, thus building the model's infrastructure when properly connecting the information exchange, campaigns, and data processing and transmitting, for the purpose of improving the relationship with the patient through telephone and computing technology.
sensor stream reduction for clustered wireless sensor networks. this work presents the use of sensor stream reduction algorithms in clustered wireless sensor networks (wsns), where the cluster head node is responsible to reduce the amount of data generated by the nodes in its cluster. moreover, a formal description to sensor stream reduction problem is proposed and an analytical model is adapted to show that when our solutions are adopted in cluster based organization, they have a superior performance to that observed when they are used in a non-clustered organization.
a novel modeling language for tool-based business process engineering. business processes modeled with performance nets can be simulated, and therefore verified on their effectiveness and efficiency, before their implementation. modules and basic functions of a performance net-based software prototype called performancesimulator2010, designed to support the complete life cycle of performance indicator-based business process engineering are briefly presented.
parametric cepstral analysis for pathological voice assessment. traditional methods to diagnose laryngeal pathologies such as laryngoscopy are considered invasive and uncomfortable. methods based on acoustic analisys of speech signals have been investigated in order to diminish the number of laryngoscopical exams. digital signal processing techniques have been used to perform an acoustic analysis for vocal quality assessment due to the simplicity and the non-invasive nature of the measurement procedures. their employment is of special interest, as they can provide an objective diagnosis of pathological voices, and may be used as complementary tool in laryngoscopy. the degree of reliability and effectiveness of discriminating process of pathological voices from normal ones depends on the characteristics and parameters of voice used to train the employed classifier. this paper aims at evaluating the performance of the linear prediction coding (lpc)-based cepstral analysis to discriminate pathological voices of speakers affected by vocal fold edema. for this purpose, lpc, cepstral, weighted cepstral, delta cepstral weighted delta cepstral mel-cepstral coefficients and are used. a vector-quantizing-trained distance classifier is used in the discrimination process.
orthosearch: a scientific workflow approach to detect distant homologies on protozoans. managing bioinformatics experiments is challenging due to the orchestration and interoperation of tools with semantics. an effective approach for managing those experiments is through workflow management systems (wfms). we present several wfms features for supporting genome homology workflows and discuss relevant issues for typical genomic experiments. in our evaluation we used orthosearch, a real genomic pipeline originally defined as a perl script. we modeled it as a scientific workflow and implemented it on kepler wfms. we show a case study detecting distant homologies on trypanomatids metabolic pathways. our results reinforce the benefits of wfms over script languages and point out challenges to wfms in distributed environments.
on delegation and workflow execution models. workflow systems have long been of interest to computer science researchers due to their practical relevance. supporting delegation mechanisms in workflow systems is receiving increasing research interest. in this paper, we conduct a comprehensive study of user delegation operations in computerized workflow systems. in a workflow system, the semantics of a delegation operation are largely based on three factors: the underlying workflow execution model, task type and delegation type. we describe three different workflow execution models and examine the effect of various delegation operations in each workflow execution model. we then extend our workflow execution models to examine the effect of various delegation operations in different role-based workflow execution models.
stacked dependency networks for layout document structuring. we address the problems of structuring and annotation of layout-oriented documents. we model the annotation problems as the collective classification on graph-like structures with typed instances and links that capture the domain-specific knowledge. we use the relational dependency networks (rdns) for the collective inference on the multi-typed graphs. we then describe a variant of rdns where a stacked approximation replaces the gibbs sampling in order to accelerate the inference. we report results of evaluation tests for both the gibbs sampling and stacking inference on two document structuring examples.
perspective rectification of camera-based document images using local linear structure. this paper addresses the problem of perspective distortion rectification of camera-based document images. a perspective rectification method using local linear structure is proposed. in this work, only local structure information such as characters, text lines, and strokes are involved in perspective parallel line detection. horizontal lines are detected from the baselines of words or text lines, and vertical lines are detected from vertical strokes. an iterative method is used to locate vanishing points from perspective line bundles. finally, the perspective image is rectified by a quadrilateral-rectangle pair constructed by horizontal and vertical vanishing point. not using global information such as document boundary, paragraph format, this method has good generalization and is able to rectify partial documents or sparse documents.
g: a graph-based technique for resolving ambiguity in query translation candidates. in the field of cross-language information retrieval (clir), the resolution of lexical ambiguity is a key challenge. common mechanisms for the translation of query terms from one language to another typically produce a set of possible translation candidates, rather than some authoritative result. correctly reducing a list of possible candidates down to a single translation is an enduring problem. thus far, solutions have concentrated upon the use of the use of term co-occurrence information to guide the process of resolving translation-based ambiguity. in this paper we introduce a new disambiguation strategy which employs a graph-based analysis of generated co-occurrence data to determine the most appropriate translation for a given term.
ubicomp secretary: a web service based ubiquitous computing application. due to the extensive availability of wireless internet connectivity and low cost light weight mobile devices, an omnipresent customizable service is not a vision anymore. if this type of service can be made a reality, it can be used by different types of users in different fields such as education, tourism, shopping or business, at any time and at any place. in this paper, we present the details of ubicomp secretary (us), which is designed and developed to accomplish the above objectives. us is developed upon the web services based architecture which asserts its adherence to all the required features of an ubiquitous computing application. its evaluation by different means establishes these facts as well as its wide range of acceptability.
using ambiguity measure feature selection algorithm for support vector machine classifier. with the ever-increasing number of documents on the web, digital libraries, news sources, etc., the need of a text classifier that can classify massive amount of data is becoming more critical and difficult. the major problem in text classification is the high dimensionality of feature space. the support vector machine (svm) classifier is shown to perform consistently better than other text classification algorithms. however, the time taken for training a svm model is more than other algorithms. we explore the use of the ambiguity measure (am) feature selection method that uses only the most unambiguous keywords to predict the category of a document. our analysis shows that am reduces the training time by more than 50% than the scenario when no feature selection is used, while maintaining the accuracy of the text classifier equivalent to or better than using the whole feature set. we empirically show the effectiveness of our approach in outperforming seven different feature selection methods using two standard benchmark datasets.
entity ranking in wikipedia. the traditional entity extraction problem lies in the ability of extracting named entities from plain text using natural language processing techniques and intensive training from large document collections. examples of named entities include organisations, people, locations, or dates. there are many research activities involving named entities; we are interested in entity ranking in the field of information retrieval. in this paper, we describe our approach to identifying and ranking entities from the inex wikipedia document collection. wikipedia offers a number of interesting features for entity identification and ranking that we first introduce. we then describe the principles and the architecture of our entity ranking system, and introduce our methodology for evaluation. our preliminary results show that the use of categories and the link structure of wikipedia, together with entity examples, can significantly improve retrieval effectiveness.
model-driven development of component-based adaptive distributed applications. this paper introduces an approach to develop component-based adaptive distributed applications. our approach separates the communication and the functional aspects of a distributed application and specifies the communication part as an abstract distributed component called the communication component. we then introduce a model-based process for automatically building many evolutionary variants of this component at deployment level, and integrating these variants into the target adaptive application that can dynamically select the running variant in order to adapt to the changing context. thanks to an adaptation guide generated by the process, the adaptive application can coordinate distributed adaptations to (1) consistently transfer data of the replaced variant to the new one and (2) maintain the architectural coherence between distributed parts of the application. hence, the target adaptive application can correctly adapt at runtime without loss of data. in this paper, we present the principle of our approach, illustrate it with an example, and show how we have automated the development process by model transformations.
history offset implementation scheme for large scale multidimensional data sets. a novel implementation scheme for large scale multidimensional datasets is proposed and evaluated. the scheme implements a multidimensional dataset by employing multidimensional arrays. using multidimensional arrays provides many advantages, but suffers from some problems. the proposed history offset implementation scheme solves these problems by an efficient scheme of record encoding based on the notion of extendible array. in this paper, some solutions are presented against an essential problem of address space overflow in handling large scale multidimensional datasets. our proposed schemes will be proved to exhibit good performance in space and time costs.
special track on ubiquitous computing: ubiquitous and pervasive ecommerce and ebusiness: editorial message. ubiquitous computing has emerged as one of the principal information and communication technologies that could lead to the achievement of the ambient intelligence (ami) vision. ambient intelligence places human beings at the centre of the future knowledge-based society and implies a seamless environment of computing, advanced networking technology and unobtrusive interfaces: interaction should be relaxing and enjoyable for people. in an ami environment, humans will be surrounded by intelligent interfaces supported by computing and networking technology that is embedded in everyday objects such as furniture, clothes, vehicles, roads and smart materials - even particles of decorative substances like paint. the ami world then, is a world largely defined by ubiquitous computing applications, which are designed and developed to operate at the background, to disappear in the different layers of the physical world, in order to serve the needs of people unobtrusively.
a hybrid real-time component model for reconfigurable embedded systems. increasing capabilities of modern microcontrollers greatly increase their applicability to more and more unstable and complex environments. dynamic reconfiguration provides a powerful mechanism to adapt in such environments. however, the implementation of dynamic reconfiguration is still challenging for embedded real-time control software systems. in this paper, we present our real-time component framework which simultaneously supports hard real-time control and non-real-time adaption management while keeping the implementation as lean as possible. our contribution is the hybrid component model in which one part is designed to support the real-time task while its non-real-time counterpart deals with component adaptation and management functions. a detailed analysis of the intra-component management interface was provided. xml was employed to describe and configure real-time task. we also designed an interface between real-time objects to achieve an inter-real-time task communication scheme based on global shared memory. in the non real-time domain, by mapping much of the management functions to the osgi system service, we realized the components management service. our framework can achieve complex component management while providing hard real-time assurance.
phalanx: a graph-theoretic framework for test case prioritization. test case prioritization for regression testing can be performed using different metrics (e.g., statement coverage, path coverage) depending on the application context. employing different metrics requires different prioritization schemes (e.g., maximum coverage, dissimilar paths covered). this results in significant algorithmic and implementation complexity in the testing process associated with various metrics and prioritization schemes. in this paper, we present a novel approach to the test case prioritization problem that addresses this limitation. we devise a framework, phalanx, that identifies two distinct aspects of the problem. the first relates to metrics that define ordering relations among test cases; the second defines mechanisms that implement these metrics on test suites. we abstract the information into a test-case dissimilarity graph -- a weighted graph in which nodes specify test cases and weighted edges specify user-defined proximity measures between test cases. we argue that a declustered linearization of nodes in the graph results in a desirable prioritization of test cases, since it ensures that dissimilar test cases are applied first. we explore two mechanisms for declustering the test case dissimilarity graph -- fiedler (spectral) ordering and a greedy approach. we implement these orderings in phalanx, a highly flexible and customizable testbed, and demonstrate excellent performance for test-case prioritization. our experiments on test suites available from the subject infrastructure repository (sir) show that a variety of user-defined metrics can be easily incorporated in phalanx.
special track on autonomic computing: editorial message. with the widespread use of distributed computing in the enterprise, there have been significant advances in development paradigms for distributed computing applications. server side component models have considerably simplified development and the complexity has instead shifted to the operational side of these applications. the increase in operational complexity has reached a point where it is no longer feasible for humans to manage the applications required to run an enterprise. this coupled with the lack of skills and skyrocketing costs associated with application management make it imperative to develop techniques to allow applications to manage themselves. the initial steps to provide self-managing applications are now being taken a paradigm known as "autonomic computing" is in its infancy of evolution. it has also been identified as one of the "grand challenges" of computer applications for the next decade. in addition, the exponential growth of handheld devices (e.g. pdas, laptops, smart phones etc.) pose additional challenges since these devices themselves suffer from a number of limitations such as inadequate processing capability, restricted battery life, limited memory space, frequent line disconnection, and confined host bandwidth. lack of fixed infrastructure support and the aforementioned limitations augment the complexity of the problems in autonomic computing.
organizational engineering in public administration: the state of the art on egovernment domain modeling. society nowadays demands processes in public organizations to be reengineered so that they become more flexible, effective and efficient. public administration (pa) is a huge organization with several different activities, with stakeholders that may have conflicting interests or different priorities etc. the application of the organizational engineering approaches in the pa domain can help towards its modernization. one initial step to this direction is to create the appropriate domain models as generic and reusable representations so as to use them as blueprints for modeling the organizations of interest. in this work, we have included the state-of-the-art in egovernment domain models. we have grouped these initiatives to the following three categories depending on their modeling perspective: object, process and holistic and assess their pros and cons.
hiv drug resistance analysis tool based on process algebra. the increasing number of drugs used in hiv patient treatment and the mutations associated with drug resistance make the inference of drug resistance a complex task that demands computational systems. furthermore, the software development/update can generate an extra level of complexity in the process drug resistance analysis. an alternative to handle the complexity of drug resistance and software development is to use a formal representation of involved processes, such as process algebra. this allows mathematical reasoning about the analysis process, a precise description of system behavior, more advanced computational approaches, as concurrent/parallel execution and (semi) automatic software development. the first contribution of this research is a mapping of drug resistance algorithms rules into expressions of process algebra which facilitates the computational manipulation of theses rules. the second contribution is the hivdag (hiv drug analysis generator) system. this software supports the definition, generation and analyses of genotypic drug resistance tests based on process algebra expressions. therefore, the users can easily create/update their own drug resistance algorithms any time and independent of software development.
spatially non-homogeneous potts model parameter estimation on higher-order neighborhood systems by maximum pseudo-likelihood. this paper addresses the problem of maximum pseudo-likelihood estimation of the non-homogeneous potts image model parameters using higher-order non-causal neighborhood systems in a computationally efficient way. the motivation is the development of a new methodology for contextual classification that uses combination of sub-optimal mrf algorithms for multispectral image classification, which requires accurate parameters estimation. our objective is to make multispectral image contextual classification fully operational without human intervention. the results show that the method is consistent with real data and in the presence of random noise.
restoring images with a multiscale neural network based technique. this paper describes a neural network based multiscale image restoration approach in which multilayer perceptrons are trained with artificial images of degraded gray level cocentered circles. the main objective of this approach is to make the neural network learn inherent space relations of the degraded pixels in the restoration of the image. in the conducted experiment, the degradation is simulated by submitting the image to a low pass gaussian filter and the addition of noise to the pixels at pre-established rates. the degraded image pixels make the input and the non-degraded image pixels make the output for the supervised learning process. the neural network performs an inverse operation by recovering a quasi non-degraded image in terms of least squared. the main difference of the approach to existing ones relies on the fact that the space relations are taken from different scales, thus providing relational space data to the neural network. the approach is an attempt to develop a simple method that may lead to a good restored version of the image, without the need of a priori knowledge of the possible degradation cause. considering different window sizes around a pixel simulates the multiscale operation. in the generalization phase the neural network is exposed to indoor, outdoor, and satellite degraded images following the same steps use for the artificial circle image. the neural network restoration results show the proposed approach performs similarly to existing methods with the advantage it does not require a priori knowledge of the degradation causes.
a new approach to control a population of mobile robots using genetic programming. this paper describes a new evolutionary control system (ecs) able to control a population of mobile robots. the system has two main modules: the first one, called emss (execution, management and supervision system), is the system responsible for managing all the evolutionary process that takes place in an embedded fashion in each robot. the second module, called dgp (distributed genetic programming), is an extension of classical genetic programming algorithm to support the control system evolution for the robots that are part of the mobile robots population. simulation experiments of the dgp algorithm are presented and their results are compared with the classical gp algorithm.
using unlabeled data to handle domain-transfer problem of semantic detection. due to highly domain-specific nature, supervised sentiment classifiers typically require a large number of new labeled training data when transferred to another domain. this is so-called domaintransfer problem. in this work, we attempt to tackle this problem by combining old-domain labeled examples with new-domain unlabeled ones. the basic idea is to use old-domain-trained classifier to label some informative unlabeled examples in new domain, and train the base classifier again. the experimental results demonstrate that proposed method dramatically boosts the accuracy of the base sentiment classifier on new domain.
ontology-based utterance interpretation for intelligent conversational interfaces. in this paper, we present an ontology-based utterance interpretation mechanism for intelligent conversational interfaces. we describe how this mechanism was embedded in a conversational interface applied to personal assistant agents. the main goal of such approach is to offer a system capable of performing tasks through an intuitive interface, allowing experienced and less experienced users to interact with it in an easy and comfortable way. in this mechanism, ontologies are used for syntactic and semantic interpretation. we present how to design an ontology for semantic interpretation and how the interpretation process use it for semantic analysis.
the utilization bound of uniprocessor preemptive slack-monotonic scheduling is 50%. consider the problem of scheduling a set of sporadically arriving implicit-deadline tasks to meet deadlines on a uniprocessor. static-priority scheduling is considered using the slack-monotonic priority-assignment scheme. we prove that its utilization bound is 50%.
efficient compilation of lua for the clr. microsoft's common language runtime offers a target environment for compiler writers that provides a managed execution environment and type system, garbage collection, access to os services, multithreading, and a just-in-time compiler. but the clr uses a statically typed intermediate language, which is a problem for efficient compilation of dynamically typed languages in general, and the lua language in particular. this paper presents a way to implement a lua compiler for the clr that generates efficient code. the code this compiler generates outperforms the same code executed by the lua interpreter and similar code generated by microsoft's ironpython compiler. it approaches the performance of lua code compiled to native code by luajit.
a generic mobile agent framework for ambient intelligence. the purpose of this paper is to introduce an innovative framework for implementation of ambient intelligence (ami) environments. compared to the existing state-of-the-art approaches, this framework creates a more decentralized and distributed ami environment. in addition, the proposed approach is not limited to one specific domain, unlike many others. the openness of the presented architecture allows it to support a variety of devices ranged from small-embedded sensors to complex computing facilities. finally, given that this approach is formulated based on multi-agent standard concepts, it can be easily implemented as add-on for existing software agent platforms to achieve rapid deployment. implications for the development of this framework and future directions are discussed.
the effect of correlation coefficients on communities of recommenders. recommendation systems, based on collaborative filtering, offer a means of sifting through the enourmous amounts of content on the web by composing user ratings in order to generate predicted ratings for other users. these kinds of systems can be viewed as a network of interacting peers, where each user is a node and the links to all other nodes are weighted according to how similar the corresponding users are. predicted ratings are generated for a user for unknown items by requesting and aggregating rating information from the surrounding neighbors. however, the different methods of computing user similarity, or weighting the network links, very often do not agree with each other, and, as a result, the structure of the network of recommenders changes completely. in this work we perform an analysis of a range of similarity measures, comparing their performance in terms of prediction accuracy and coverage. this allows us to understand the effect that similarity measures have on predicted ratings. based on the obtained results, we argue that user-similarity may not sufficiently capture the relationships that recommenders could otherwise share in order to maximise the utility of these communities.
the minimization of hardware size in reconfigurable embedded platforms. to minimize the hardware fabrications in reconfigurable devices, this paper explores hardware synthesis to derive reconfiguration plans during the design time based on schedules derived by cad tools, where a schedule includes the starting time, the execution time, and the intertask data transmissions for each task. we propose scheduling algorithms to derive optimal solutions for hardware descriptions with the same reconfiguration latency based on backward configuration and backward ordering strategies. for general cases, where a hardware description might be shared by tasks, we develop an algorithm based on a duplication merging strategy with performance evaluations. our proposed algorithms could be applied after the hardware/software co-design procedures of task partitioning and scheduling to optimize the hardware requirements during the design time.
web page genre classification. in this paper we present an automatic genre-based web page classification system. unlike subject or topic based classifications, genre-based classifications focus on functional purposes and classify web pages into categories such as online shopping, technical paper, or discussion forum. until now, the genre classifications are not well developed due to the subjectivities and difficulties to define the genre, the features, and even the categories. in this paper, we define five top-level genre categories, each of which has several subcategories, and develop new methods to extract 31 features from web pages to identify the categories. we analyze not only the contents of the web pages, but also the urls, html tags, java scripts, and vb scripts. we developed a genre classification system that achieved average accuracy of 93%. in addition, we combined this genre classification with our subject-based classification to produce a comprehensive web page classification system.
on the conceptual tag refinement. social tagging is a well known approach of assigning keywords to (web) documents in order to share the personal meaning of users about the content. however, the ambiguity of the assigned keywords hinders the knowledge sharing process. in this paper we present an approach for supporting tagging process by interpreting the keywords (tags) using a conceptual tag model, which leads to a semantic tagging process. moreover, the approach introduces the tag refinement process that proposes extensions of given tags in order to help the user to better express his/her "tagging" need. we present several evaluation studies in order to demonstrate the efficiency of the approach.
towards trace semantics for ws-cdl with alignments. ws-cdl (web service choreography description language) provides a global view to describe the interactive behaviors between multiple participants of web services. although the alignment property plays an important role in the ws-cdl specification, little attention has been paid on the research of alignments. in this paper, we aim at exploring the essence of alignment property and providing formal semantics for ws-cdl with alignments. to achieve this goal, we first define a formal language cdla, which includes the basic components in ws-cdl. we then discuss the influence of alignment property to the semantics of these components and propose five possible local action based trace semantics for cdla.
scheduling grid tasks under uncertain demands. the uncertainty of the demands of grid applications can cause unpredicted performance and, consequently, can make ineffective schedules derived for target demand values. to produce effective results, schedulers need to take into account the difficulty in estimating the demands of applications. in this paper, a scheduler based on fuzzy optimization is proposed to deal with such uncertainties. it is shown, via numerical results, that the proposed scheduler presents advantages when compared to classical schedulers.
author identification using writer-dependent and writer-independent strategies. in this work we discuss author identification for documents written in portuguese. two different approaches were compared. the first is the writer-independent model which reduces the pattern recognition problem to a single model and two classes, hence, makes it possible to build robust system even when few genuine samples per writer are available. the second is the personal model, which very often performs better but needs a bigger number of samples per writer. we also introduce a stylometric feature set based on the conjunctions and adverbs of the portuguese language. experiments on a database composed of short articles from 30 different authors and support vector machine (svm) as classifier demonstrate that the proposed strategy can produced results comparable to the literature.
building secure e-business systems: technology and culture in the uae. over the past few years, internet-enabled business, or e-business, has drastically improved efficiency and revenue growth of companies. information is in the center of everything, and it is constantly under threat from many sources. without proper protection, e-business applications can be susceptible to attacks or unauthorized activity. security has been an elemental concern in e-business since its beginning in middle east region and especially in united arab emirates (uae). it is argued that e-business cannot attain its potential until the security concerns are addressed adequately. the survey results have been discussed in respect of security measures and their contribution towards consumers' decision-making processes.
an evaluation of a model-based testing method for information systems. this work presents an experimental study of a model-based testing method. we evaluate the use of the method and its tool, during the development of part of an information system. in this study we verified that the use of the method can generate benefits related to cost reduction, from the reduction of test effort and, at the same time, benefits related to test quality, from the failure detection capability improvement.
a framework for execution and 3d visualization of situated cellular agent based crowd simulations. this paper presents a framework supporting the definition and implementation of crowd simulation systems based on interacting situated agents. the framework supports the specification and execution of visually rich 3d virtual environment endowed by the presence of mobile agents acting and interacting inside it according to a multi-agent model that also supports the definition of agents' environment and its relevant elements. the paper introduces the multi-agent model underlying the framework and its basic architecture. sample applications are also described so as to show the potential of the framework in executing models comprising several hundreds of agents producing an effective visualization of the generated dynamics.
power-efficient and scalable load/store queue design via address compression. this paper proposes an address compression technique for load/store queue (lsq) to improve the scalability and power efficiency. a load/store queue (lsq) typically needs a fully-associative cam structure to search the address for collision and consequently poses scalability challenges of power consumption and area cost. using the proposed approach, the lsq can reduce the area cost ranging from 32% to 66% and power consumption ranging from 38% to 71%, depending on the compression parameter. the approach can provide 3.08% overall processor energy reduction and causes only 0.22% performance loss at an optimal configuration.
improving denial of service resistance using dynamic local adaptations. we improve the resistance of gossip-based multicast to (distributed) denial of service (dos) attacks using dynamic local adaptations at each node. each node estimates the current state of the attack on the system, and then adapts its behavior according to this local estimation. the adaptation is achieved through modeling the problem of propagating messages under a dos attack as an optimization problem, and solving it using linear programming, independently at each node. simulation results show that when the system is under attack, the local decisions each node takes bring the system to a stable point, which is the solution of the linear programming problem. the adaptation leads to propagation times that are 30% faster than those of existing dos-resistant gossip-based protocols.
spatial vagueness and imprecision in databases. the impossibility of current spatial database systems and gis to handle spatial vagueness and imprecision has been recognized as an important problem in the spatial database domain. for years, researchers have focused on identifying the appropriate concepts that are necessary to effectively and efficiently deal with the vagueness and imprecision that not seldomly appears, but is widespread amongst spatial objects (especially those that are naturally occurring such as forests, mountains, and rivers). in this paper, we analyze the most popular formalisms for dealing with spatial uncertainty in databases. the analysis in this paper is centered around the definition of our vague spatial algebra (vasa) which exemplifies a complete approach to handle vagueness in spatial databases. we compare vasa with existing concepts based on rough set theory and fuzzy set theory.
electricity market simulation: multiagent system approach. this paper suggests a multiagent system (mas) approach for market simulation. this is achieved through analysis, modeling, implementation and simulation of artificial markets populated by software agents that represent economic self interested agents. software agents are the constructs of a complex system, an artificial market that model a real existing market or an outline of a market design. the interest in simulating a market is multiple: exploiting existing market rules, searching for market design flaws and loopholes, and supporting decision making during a market mechanism design process. the main aim of the suggested approach is to analyze the behavior that emerges from the interaction of self interested agents acting in an artificial market. aemas (artificial economy multiagent system), a multiagent system architecture inspired by the market oriented programming (mop) approach is defined. in different economical sectors, e.g. energy markets, there is no consensus about which structures lead to social welfare maximization outcomes. an approach to find adequate architectures allows different market structure instances to be created and simulated, to ease the design and analysis of alternative structures. these alternatives can then be compared and potential design flaws eventually risen by simulation identified. taking the electricity market as an example, two instances of the proposed architecture are presented, corresponding to the centralized dispatch arrangement common to non restructured markets, and the auction based pool, common to restructured markets.
implementing an autonomic architecture for fault-tolerance in a wireless sensor network testbed for at-scale experimentation. the wireless sensor networking (wsn) community has increasingly grown to rely on experimentation with large-scale test-beds as a means of verifying protocols, middleware and applications. these testbeds need to be highly available in order to support this community, but are themselves complex, and complex to manage, being prone to faults in hardware, software specification and software implementation. in this paper we report on our experience in designing kansei, a wsn testbed for experimentation at scale, to be autonomic - i.e. self-healing and self-managing. we implement autonomic management in kansei through an architecture that consists of a hierarchy of self-contained components, extended with detectors for discovering faults and correctors for subsequent stabilization. we find that our invariant based architecture is well suited for large complex systems with unpredictable fault model and its fault monitoring framework can be extended to include user programs.
filtering drowsy instruction cache to achieve better efficiency. leakage power in cache memories represents a sizable fraction of total power consumption, and many techniques have been proposed to reduce it. as a matter of fact, during a fixed period of time, only a small subset of cache lines is used. previous techniques put unused lines, for example, to drowsy in order to save power. our idea is to adaptively select the most used cache lines. in the case of instruction cache, we found that this can automatically achieved by coupling a tiny cache acting as a filter cache (ilo cache) with a drowsy-cache. our experiments, with complete mibench suite for arm based processor, show a 25% improvement in leakage saving versus drowsy.
optimizing code through iterative specialization. code specialization is a way to obtain significant improvement in the performance of an application. it works by exposing values of different parameters in source code. the availability of these specialized values enables the compilers to generate better optimized code. although most of the efficient source code implementations contain specialized code to benefit from these optimizations, the real impact of specialization may however vary depending upon the value of the specializing parameter. in this paper, we suggest the specialization of code to acquire an iterative approach. for some specialized code, we search for a better version of code by re-specializing the code, followed by a low-level code analysis. the specialized versions fulfilling the required criteria are then transformed to generate another equivalent version of the original specialized code. the approach has been tested on itanium-ii architecture using icc compiler. the results show significant improvement in the performance of different behchmarks.
generation of continuous random networks by simulated annealing. this work presents a new approach for the computational treatment of amorphous materials. simulated annealing has been used for generating carbon continuous random networks. unlike other methods, it is possible to define a priori the percentage of sp3, sp2 and sp hibridized carbon atoms in the final structure. using grid computing resources, several structures were generated simultaneously. in this way, we can easily scan all the range of amorphous materials with different proportions between the possible hibridizations of carbon.
how robust are multilingual information retrieval systems? the results of information retrieval evaluations are often difficult to apply to practical challenges. recent research interest in the robustness of information systems tries to facilitate the application of research results for practical environments. this paper analyzes a large amount of evaluation experiments from the cross language evaluation forum (clef). robustness can be interpreted as stressing the importance of difficult topics and is usually measured with the geometric mean of the topic results. our analysis shows that a small decrease of performance of bi-and multi-lingual retrieval goes along with a tremendous difference between the geometric mean and the average of topics. consequently, robustness is an important issue especially for cross-language retrieval system evaluation.
conversion of generalization hierarchies and union types from extended entity-relationship model to an xml logical model. this short paper proposes alternative rules for converting generalization/specialization hierarchies and union types, defined in the extended entity-relationship model, to an xml logical model. our approach considers all the possible constraints and constructs for generalization and union types, generating abstract schemas for the logical design of xml documents.
an approach to mobile collaborative mapping. with the advent of web 2.0, users now expect to be able to customise, edit and share information from any online device. these capabilities are unavailable in many geographic information applications and where it is, it is far too difficult to use. satellite navigation devices and software are also not flexible enough in this regard. current satellite navigation technology enables users to view maps and navigate easily. however, it does not support information sharing and marking-up maps with symbols other than routes and locations. currently, a popular desktop solution to this problem is web 2.0 mashups, which enable implementers to correlate information from several web data sources into one coherent application. mashups also have their caveats, as they are beyond the capabilities of lay users and, being web-based, they are not location aware and do not support mobility. this paper presents mobile collaborative mapping (mcm), a browser-based location-aware collaborative map editor to address these shortcomings through a simplified editing system and revision based storage server and discusses its application in an e-science scenario of use and the capabilities of the current mcm prototype.
agent-based simulation of electronic marketplaces with decision support. this paper presents a multi-agent market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. the system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agents reactions.
trajectory retrieval with latent semantic analysis. the problem of trajectory similarity has been recently attracted research interest considerably, due to its importance in diverse fields. in this work, we study trajectory similarity by attacking the problem taking an information retrieval perspective. trajectories are first decomposed by using a grid and each trajectory is mapped to a multidimensional space where latent semantic analysis is applied. distance measures like euclidean distance or cosine distance are applied to process similarity queries (range queries, k-nn queries). performance evaluation results, based on real-life data sets, show the simplicity and effectiveness of the proposed scheme.
flagellink: a decision support system for distributed flagellar data using data warehouse. combining different types of data from multiple databases (dbs) is a key feature in bioinformatics, particularly due to the problem that each of these db resources usually contains different subsets of biological knowledge and only answers questions in its domain, nether helping with questions that span domain boundaries nor considering them. as bioinformatics dbs grow in size and as biological questions grow in scope, better solutions will inevitably consist in preserving the autonomy and diversity of dbs and developing new systems to offer an integrated and transparent access to existing distributed data sources (ds). in this paper, we present a decision support system (dss), called flagellink, to provide access to a set of distributed information about a particular domain (the flagellum, a cellular organelle responsible for motility). it employs useful bioinformatics tools (such as blast, muscle, hmmer, etc) in an exclusive data warehouse (dw) through terminology and ontology resources (semantic-driven) to maintain an actual dss for a specific knowledge domain. flagellink (available at http://flagellink.nugen.uece.br/flagellink) has a unified, ondemand integration approach that merges the identified ontological knowledge (which means a defined number of test cases and scenarios of genes and proteins all involved in flagellar activities) with traditional and ontology-based information integration techniques.
an improved approach for set-associative instruction cache partial analysis. the current worst case execution time (wcet) computation methods are usually applied to whole programs, this may drive to scalability limitations as the program size becomes bigger. a solution could be to split programs into components that could support separated partial analyses to decrease the computation time. the componentization is also consistent with the more and more frequent use of component off the shelf (cots). consequently, we need algorithms to perform analyses on component-wise applications. in this paper, we focus on the partial analysis of set-associative instruction caches, based on the categorization method described by m. alt et al. we have first evaluated a. rakib et al.'s approach to this problem and we have shown that, while correct, this approach can be greatly improved by a better estimation of the component effect on the cache. the version we have developed addresses the identified shortcomings and the experimentation results have been evaluated according to two criteria: (1) overestimation of the wcet and (2) computation time gain against the whole program analysis approach.
a remote display system for java-based mobile applications. remote presentation is an interesting model for executing applications in mobile devices, since applications can be executed on a server and their interfaces displayed on mobile clients. this paper describes a non-invasive and transparent remote presentation system for legacy j2me applications called rda (remote display using aspects). rda relies on aspect-oriented programming to instrument j2me applications with remote presentation code. our first performance results demonstrate that remote presentation is a promising solution for executing cpu-intensive applications in mobile devices or for running applications demanding resources not available in such devices.
ielr(1): practical lr(1) parser tables for non-lr(1) grammars with conflict resolution. there has been a recent effort in the literature to reconsider grammar-dependent software development from an engineering point of view. as part of that effort, we examine a deficiency in the state of the art of practical lr parser table generation. specifically, lalr sometimes generates parser tables that do not accept the full language that the grammar developer expects, but canonical lr is too inefficient to be practical. in response, many researchers have attempted to develop minimal lr parser table generation algorithms. in this paper, we demonstrate that a well known algorithm described by david pager and implemented in menhir, the most robust minimal lr(1) implementation we have discovered, does not always achieve the full power of canonical lr(1) when the given grammar is non-lr(1) coupled with a specification for resolving conflicts. we also outline an original minimal lr(1) algorithm, ielr(1), which we have implemented as an extension of gnu bison and which does not exhibit this deficiency. finally, using our implementation, we demonstrate the relevance of this deficiency for several real-world grammars, and we show that our implementation is feasible for generating minimal lr(1) parsers for those grammars.
special track on applications of evolutionary computation: editorial message. evolutionary algorithms (eas) are inspired by the mechanisms that underlie biological evolution: reproduction with variation, selection according to fitness, and repetition. an ea maintains a population of data structures that encode candidate solutions to the target problem instance. these data structures are usually strings of symbols and are called chromosomes. associated with each chromosome is a numerical fitness that indicates the quality of the solution it represents, and chromosomes of better fitness are selected to be parents. operators abstracted from genetic crossover and mutation, and bearing those names, generate novel chromosomes from the selected parents. as generations of chromosomes follow each other, representations of better solutions evolve. the algorithm halts and returns the best solution represented in its population after a specified number of generations or when the algorithm identifies a solution of adequate fitness.
ifox: interface for ordered xquery an algebraic oriented tool for ordered xquery visualization. even though xquery has become a standard for querying semi-structured data, its syntax is too complex for occasional users. this paper describes a user friendly interface called ifox (interface for ordered xquery) that enables non experienced users to build easily complex xqueries. to that end, we use an algebraic-like representation to build xqueries. this representation is based on the xalgebra described in [17]. moreover, many applications require answers to queries to be order sensitive. for example, in a biomedical application where a set of genes is stored in a xml file, the order in the output when querying these data is crucial. with issue in mind, we propose a normalization process which not only preserves order in answers to queries but also enables optimization techniques.
special track on e-business applications: editorial message. the increasing popularity and advances in e-business environment are enabling the development of new classes of applications and the emergence of new trends in the design of online business systems.
cosmos: a middleware platform for sensor networks and a u-healthcare service. we studied the middleware platform, i.e. cosmos (common system for middleware of sensor network) as a national project in korea, for various types of sensor networks such as the zigbee wireless sensor network (wsn), the cdma cellular network, rfid and ip-usn based on the 6lowpan. our project is focused on sensor network abstraction for various ubiquitous sensor networks (usn). we defined standard interfaces between usn middleware and usn networks as well as application services. we implemented several usn services such as u-healthcare services to consider important issues such as data quality, realtime data aggregation and performance analysis for accessibility.
mining fault-tolerant frequent patterns efficiently with powerful pruning. the mining of frequent patterns in databases has been studied for several years. however, the real-world data tends to be dirty and frequent pattern mining which extracts patterns that are absolutely matched is not enough. an approach, called fault-tolerant frequent pattern (ft-pattern) mining, is more suitable for extracting interesting information from real-world data that may be polluted by noise. in our approach, the problems of mining proportional and fixed ft-patterns are considered. in proportional ft-pattern mining, the number of faults tolerable in a pattern is proportional to the length of the pattern. and the number of faults tolerable in different length of patterns is fixed in fixed ft-pattern mining. a new graph structure, ft-association graph, is proposed to help us filtering out impossible candidates with high efficiency. the experimental results show that the proposed algorithms of our approach are highly efficient for mining both proportional and fixed ft-patterns.
runtime concepts for the c standard template library. a key benefit of generic programming is its support for producing modules with clean separation. in particular, generic algorithms are written to work with a wide variety of unmodified types. the runtime concept idiom extends this support by allowing unmodified concrete types to behave in a runtime polymorphic manner. in this paper, we describe one implementation of the runtime concept idiom, in the domain of the c++ standard template library (stl). we describe and measure the performance of runtime-polymorphic analogs of several stl algorithms. we augment the runtime concept idiom by employing a dispatch mechanism that considers both type and concept information to maximize performance when selecting algorithm implementations. we use our implementation to demonstrate the effects of different compile-time vs. run-time algorithm selection choices, and we indicate where improved language and compiler support would be useful.
fast self-healing gradients. we present crf-gradient, a self-healing gradient algorithm that provably reconfigures in o(diameter) time. self-healing gradients are a frequently used building block for distributed self-healing systems, but previous algorithms either have a healing rate limited by the shortest link in the network or must rebuild invalid regions from scratch. we have verified crf-gradient in simulation and on a network of mica2 motes. our approach can also be generalized and applied to create other self-healing calculations, such as cumulative probability fields.
a method for defining the implementation order of software projects under uncertainty. this article proposes a method for obtaining the optimal implementation order of software units in an information technology development project.
special track on object-oriented languages and systems: editorial message. today's large scale software systems are typically designed and implemented using the object-oriented (oo) methodology and paradigm. however, there is still a need for existing oo languages and architectures to continuously adapt in response to demands for new features and innovative approaches.
eyelid measurements using digital video processing. the aim of this paper is to present an automatic eyelid measurement system based on digital video processing techniques. currently, the protocol to measure the palpebral fissure (pf) and the marginal reflex distance (mrd) requires the use of a millimetric ruler. this procedure is subject to error and the accuracy and reproducibility of the results depend on the experience of the examiner. the computer vision system introduced in this paper uses two near infrared light sources synchronized with the camera to robustly detect and track the pupil, and then segment the limbus and the eyelids. the corneal reflection generated by the light sources are used to create a reference point that is used to define the vertical line along which the measurements are taken, and to determine when the patient is actually looking at the camera. our experimental results show that the system is robust to the presence of eyelashes, glasses, and contact lenses, and the measurements can be accurate to tenths of millimeters.
expected energy consumption minimization in dvs systems with discrete frequencies. energy-efficiency has been an important system issue in hardware and software designs to extend operation duration or out power bils. this research explores systems with probabilistic distribution on the execution time of real-time tasks for systems with discrete frequencies. most previous studies consider dvs systems with continuous frequencies for the minimization of expected energy consumption under timing constraints. however, these approaches cannot guarantee the minimization of expected energy consumption when only discrete frequencies are available. this paper presents new approaches to minimize the expected energy consumption. by applying intra-task frequency scheduling, we develop an efficient algorithm to derive optimal frequency scheduling for a single task. the algorithm is then extended to cope with periodic real-time tasks with different power characteristics. with inter-task and intra-task frequency scheduling, we present a linear-programming approach to derive optimal solutions for frame-based real-time tasks and an on-line algorithm for periodic real-time tasks. experimental results show that the proposed algorithms can effectively reduce the expected energy consumption.
capturing business transaction requirements in use case models. a significant portion of our modern economy is dependent on the reliability and usability of enterprise applications (eas) of which business transactions and concurrency management are central concepts. the correct orchestration of subordinate system transactions forming a business transaction, as well as proper concurrency conflict resolution strategies are crucial factors. in this paper we argue that modeling business transactions and concurrency management are a domain activity and as such, are to be analyzed and documented during the requirements phase. failing to do so can have a significant negative effect on the usability of an application. driven by our own experiences in writing use cases for eas, we demonstrate how business transactions can be modeled within use case specifications. concrete examples and usage guidelines are offered as well as a demonstration of how our approach helps contribute to the difficult task of requirements elicitation.
toward quality requirements analysis based on domain specific quality spectrum. it is difficult to identify whether quality requirements are defined adequately or not, but there are few methods to support this kind of requirements analysis. in this paper, we propose a method based on software quality spectrum, that shows a ratio of quality characteristics embedded in a software engineering artifact, such as a requirements specification, a manual and so on. we assume similar kinds of software systems have similar spectrum, thus we can identify the adequacy of quality requirements for a new system by using spectrum of already existing similar systems. we confirmed the assumption above by analyzing actual software systems, i.e., web browsers and drawing tools.
a multi-agent system for the support of producer coalition formation in electricity markets. all over the world distributed generation is seen as a valuable help to get cleaner and more efficient electricity. to get negotiation power and advantages of scale economy, distributed producers can be aggregated giving place to a new concept: the virtual power producer. virtual power producers are multi-technology and multi-site heterogeneous entities. virtual power producers should adopt organization and management methodologies so that they can make distributed generation a really profitable activity, able to participate in the market. in this paper we address the development of a multi-agent market simulator -- mascem -- able to study alternative coalitions of distributed producers in order to identify promising virtual power producers in an electricity market.
including the user in the knowledge discovery loop: interactive itemset-driven rule extraction. we introduce a user-driven approach to mining association rules, integrated into a visualization system, called i2e, that allows miners to depart from a reduced and representative subset of rules to interactively explore the whole rule space. a visualization of the space of k-itemsets displayed after each iteration of apriori allows the miner to guide rule extraction by exploring the space of itemsets. miners can discard itemsets considered not relevant and define clusters of related itemsets to perform rule filtering, so that uninteresting rules are removed while preserving itemset coverage in the resulting rule set. this reduced set provides a starting point to explore the rule space with an interface that supports pairwise comparisons between rules, according to some defined criteria. we describe the results obtained from applying the proposed approach and its supporting system on a case study with a real dataset containing information on cattle commercialized in brazil.
framework composition conformance via refinement checking. a major challenge related to the composition of software frameworks is to ensure that certain services provided by the frameworks are preserved. since, in general, such a composition might involve heterogeneous frameworks with incompatible interfaces (distinct signatures or protocols), some glue code is usually needed for an integration. naturally, the right design of the glue code is critical because otherwise the composition might exercise the original frameworks only partially, and the original services may malfunction in subtle ways. the notion of conformance of these services does not directly correspond to standard refinement. in this paper, we build on a systematic strategy for framework composition based on the csp process algebra. we propose notions of conformance for behaviour preservation based on failures refinement for csp and show how conformance can be mechanically checked using a csp model checker (fdr).
on to formal semantics for path expression pointcuts. in aspect-oriented programming (aop), the join point selection depends heavily on the context exposed to aspects by means of special pointcut constructs. this context is either local to the join point (e.g. target of method calls) or non-local (e.g. call-stack). path expression pointcut (pep) is a special kind of pointcut that provides aspects with the access to non-local object information. in order to implement pep, a well-defined unambiguous semantics for pep is needed. this paper proposes a denotational semantics for pep, which unambiguously describes the result of evaluating the pep. moreover, it helps to guide future developments of the pep and its integration with aop system.
preeme: preemptive real-time task management for event-driven sensor operating systems. this paper proposes preeme, which is a preemptive realtime task management scheme for event-driven sensor operating systems. by efficiently allocating independent stack space for each task, preeme enables the preemptive task management for the event-driven systems. the size of the minimal stack space for each task is determined at compiletime, and dynamic stack allocation is performed at run-time. simulation results show that preeme significantly reduces scheduling latency with small execution overhead.
selectivity estimation in spatial networks. modern applications requiring spatial network processing pose many interesting query optimization challenges. in many cases, query processing depends on the corresponding graph size (number of nodes and edges) and other graph parameters. in this paper, we present novel methods to estimate the number of nodes in regions of interest in spatial networks, towards predicting the space and time requirements of range queries. we examine all methods by using real-life and synthetic spatial networks. experimental results show that the number of nodes can be estimated efficiently and accurately with small space requirements, thus providing useful information to the query optimizer.
requirements engineering process improvement: a knowledge transfer experience. in the last decade, research in requirements engineering has achieved great advances. several methods, techniques and processes have been proposed in the literature. however, the pace of requirements engineering technology transfer has been slow. this paper presents a technology transfer project to improve the requirements engineering process in four software companies. we discuss this experience from the perspective of researchers and practitioners from one participating company.
evaluating the partial deployment of an as-level ip traceback system. distributed denial of service (ddos) attacks currently represent a serious threat to the appropriate operation of internet services. we propose an ip traceback system to be deployed at the level of autonomous systems (ases) to deal with this threat. our proposed as-level ip traceback system contrasts with previous work as it requires a priori no knowledge of the network topology while allowing single packet traceback and incremental deployment. we also investigate and evaluate the strategic placement of our systems, showing that the partial deployment offered by our proposed system provides relevant results in ip traceback, rendering it feasible for large-scale networks such as the internet.
context addressing using context-aware flooding. due to the proliferation of small networked mobile devices, the number of (indirectly) interconnected services in pervasive computing environments may grow without bound. the network contains a potentially enormous amount of context aware services that sense, gather and distribute context information. without a central context repository, or a central server that locates the context information, it is a challenge to address parts of the environment that contain relevant context information. in this paper, we propose a model for addressing context and an algorithm for context gathering and distribution that imposes a virtual structure on the network, that aligns with the actual context information within a pervasive computing environment. distribution of context uses an adapted form of flooding, that is context aware. our evaluation shows that the algorithm performs substantially better than bounded flooding, if address accuracy is at least 30%.
special track on information access and retrieval: editorial message. there is a growing need to access and retrieve relevant information across media, across languages and across modalities. the research context concerning information access and retrieval aims at modelling, designing and implementing systems able to provide a fast and effective content-based access to a large amount of multimedia information. the aim of such systems is to estimate the relevance of documents to a user information need. this is a very hard and complex task due to several distinct reasons that a large volume of research has attempted to analyse and tackle. information retrieval (ir) can be considered as the first historical research area aimed at defining systems for the automatic access to huge amounts of information (together with dbmss whose main aim is to manage and access huge amounts of data).
decentralized coordination strategies for the vehicle routing problem. modern software control systems must cope with uncertainty, manage dynamic environments, as well as provide greater flexibility. distributed agent-based control systems are the ideal candidates to manage such dynamic and unpredictable application domains, like transportation systems. this paper shows how to implement a decentralized decision strategy, based on an extended version of the probability collective (pc) framework.
isometry group, words and proofs of geometric theorems. this paper shows that considering the group generated by orthogonal symmetries relatively to lines may give very short and readable proofs of geometric theorems. a short and readable proof of the fundamental pascal's theorem is provided for illustration.
on the control of adaptation in ubiquitous computing. a core subclass of ubiquitous computing (ubicomp) applications comprises those that are context-aware, which adapt their behavior to the prevailing resource availability levels aiming to optimize and enrich user-environment interactions and to reduce the demand for user intervention. the problem of adaptation control is related to the orchestration of adaptations carried out by concurrent applications. in this process, the adaptation controller needs to promote system stability and should consider other desirable properties: resource consumption, reactiveness etc. in this paper we introduce actus, an on-going proposal of generic framework for building adaptation controllers targeting ubicomp.
privacy preservation services: challenges and solutions. the current internet architecture was designed at a time when many of the current network applications did not even exist. as a result, it has become increasingly difficult to deploy new and secure services on the internet. hence, a new internet architecture is required to address the security and usability issues that affect the current internet. in this paper, we examine the current internet architecture from various security and user perspectives using two privacy services and propose some architectural guidelines and principles for the future internet architecture. the two aforementioned privacy services that we chose are: i) anonymous communication services and ii) identity management systems. we examine the challenges in implementing anonymous communication services, and identity management systems and identify the problems with existing solutions for these challenges. based on the problems identified in the current internet architecture, we propose a virtualization-motivated set of architectural principles and design rules for the future internet.
enterprise ontology in enterprise engineering. originating from quite different fields of theory and practice, the terms "enterprise ontology" and "enterprise architecture" currently belong to the standard vocabulary of those professionals who are concerned with (re) designing and (re) engineering enterprises, thereby exploiting modern information and communication technologies for innovating products and services as well as for optimizing operational performance. because of the inherent characteristics of modern enterprises, often operating within networks of cooperating enterprises, the task of these professionals can rightly be characterized as having to master unprecedented high complexity. the statement, put forward in the paper, that the current notion of enterprise ontology does not offer satisfactory help and thus needs to evolve into an effective conceptual tool, is clarified in a historical context. a standard is recently set by demo (design and engineering methodology for organizations). in this methodology, enterprise ontology is conceptually defined as the implementation independent essence of an enterprise, understood from a holistic systemic point of view. operationally, it consists of a complete, consistent and coherent set of ontological aspect models, by which a reductio of complexity is achieved of well over 90%. the new, evolved notion of enterprise ontology is clarified and illustrated using a case example.
mining disease-specific molecular association profiles from biomedical literature: a case study. we developed a new literature mining paradigm with the ultimate goal of enabling knowledge discovery in molecular association profiles generated from literature and prior knowledge. we show how to implement the paradigm by building a prototype literature mining framework and performing molecule-biogist association mining. the framework consists of two modules. the first module, textual data mining, takes the synonym-expanded disease-related molecule names and outputs a list of biogist list. the second module, structured data mining, takes two inputs, initial disease-related molecular query terms and extracted biogist list from the first module, and outputs a molecule-biogist association matrix. our approach is novel because biomedical literature mining is used here not only as an "information retrieval" tool, but also as a "hypothesis generation and validation" platform. we applied the framework to a molecular pharmacology study of breast cancer. based on 214 breast cancer-related proteins, 429,067 medline abstracts were retrieved, and 4,491 drug compounds were identified as biogists. we evaluated 172 hydrocarbons in the above biogist list, and found that more than 82.5% hydrocarbons were verified to be related to breast cancer. brca1 and brca2 were found to have similar profiles in drug compound studies, whereas "doxorubicin", "etoposide", and "paclitaxel" were identified to have similar pharmacological profiles to treat breast cancer.
using adaptive distinguishing sequences in checking sequence constructions. a number of methods have been published to construct checking sequences for testing from finite state machine-based specifications. many of these methods require the existence of a preset distinguishing sequence in the model. in this paper, we show that usually an adaptive distinguishing sequence is sufficient for these methods to work. this result is significant because adaptive distinguishing sequences are strictly more common and up to exponentially shorter than preset ones.
autonomic trust reasoning enables misbehavior detection in olsr. ad hoc networks do not rely on any centralized administration or fixed network infrastructure and their nodes establish a routing structure in a self-organized way, by means of an ad hoc routing protocol such as olsr. ad hoc route discovery and maintenance introduce specific security problems for routing protocols to prevent, detect or respond. solutions to secure these routing protocols using some centralized units or trusted third-parties actually constrain the self-organization of ad hoc networks. in this paper, we propose for olsr the integration of trust reasonings into each node behavior, so as to allow a self-organized trust-based control to help nodes to detect misbehavior attacks. our analysis of olsr brings out the trust rules that characterize this protocol and allows us to express formally the trust-related properties that can be verified by each node to assess the correct behavior of the other nodes. simulation of olsr with nodes reasoning on trust allows us to demonstrate the effectiveness of our approach and to compare trust-based routing choices with the bare olsr reachability-based choices.
implementing secure document circulation: a prototype. interoperable e-business applications are essential for increasing efficiency in the digital economy. we present an infrastructure based on our secure document circulation architecture model, designed for securing information flow for interorganisational workflows. we view this initial prototype as simply a proof-of-concept, and plug in various software tools to implement the prototype components. a simple example, based on a loan application workflow, is discussed to indicate the potential of this work.
special track on document engineering: editorial message. document engineering is a discipline within computer science that investigates systems for documents in any form and in all media. document engineering is concerned with principles, tools and processes that improve our ability to create, manage, store, compact, access, and maintain documents. the fields of document recognition and retrieval have grown rapidly in recent years. this development has been fueled by the emergence of new application areas such as the world wide web (www), digital libraries, and video- and camera-based ocr. the use of ocr is spreading from high-volume, niche domains to more general tasks, including the processing of noisy "real-world" documents, photocopies, and faxes.
introducing self-adaptability into transaction processing. in a database system, the scheduler has the goal of synchronizing operations belonging to several concurrent transactions. in order to achieve its goal, the scheduler implements a concurrency control protocol, which may have either conservative or aggressive behavior. this paper presents a self-adaptable scheduler, called intelligent transaction scheduler (its), which has the ability of dynamically changing its behavior (from conservative to aggressive and vice-versa) to adapt itself to the characteristics of the computing environment (e.g., the aborted transaction rate and conflicting operation rate). the proposed scheduler adapts its behavior without any human interference by using an expert system based on fuzzy logic. in order to evaluate its, it was applied in a mobile database community (mdbc). an mdbc can be characterized as a dynamically configurable environment, since an mdbc is a dynamic collection of autonomous mobile databases, interconnected through a mobile ad hoc network (manet). therefore, self-adaptability plays a key role for schedulers running in dynamically configurable environments. the experimentation results show the efficiency of its for synchronizing transactions in mdbcs
removing useless variables in cost analysis of java bytecode. automatic cost analysis has interesting applications in the context of verification and certification of mobile code. for instance, the code receiver can use cost information in order to decide whether to reject mobile code which has too large cost requirements in terms of computing resources (in time and/or space) or billable events (smss sent, bandwidth required). existing cost analyses for a variety of languages describe the resource consumption of programs by means of cost equation systems (cess), which are similar to, but more general than recurrence equations. cess express the cost of a program in terms of the size of its input data. in a further step, a closed form (i.e., non-recursive) solution or upper bound can sometimes be found by using existing computer algebra systems (cass), such as maple and mathematica. in this work, we focus on cost analysis of java bytecode, a language which is widely used in the context of mobile code and we study the problem of identifying variables which are useless in the sense that they do not affect the execution cost and therefore can be ignored by cost analysis. we identify two classes of useless variables and propose automatic analysis techniques to detect them. the first class corresponds to stack variables that can be replaced by program variables or constant values. the second class corresponds to variables whose value is cost-irrelevant, i.e., does not affect the cost of the program. we propose an algorithm, inspired in static slicing which safely identifies cost-irrelevant variables. the benefits of eliminating useless variables are two-fold: (1) cost analysis without useless variables can be more efficient and (2) resulting cess are more likely to be solvable by existing cass.
profile based comparative analysis for aose methodologies evaluation. this study focuses on the analysis and evaluation of agent-oriented methodologies. different studies have been proposed for the evaluation of agent-oriented methodologies adopting specifics types of evaluation and criteria. the present work proposes to adopt the profile analysis technique for comparing evaluations carried out by different authors (perhaps using different evaluation frameworks) with the aim of improving the acceptability of agent-oriented methodologies evaluation in the agent community. to exemplify the proposal, we present the application of the profile analysis technique on a case study.
special track on multimedia and visualization track: editorial message. the multimedia and visualization (mmv) track has been a popular track because of its appeal for the current trends in daily life applications. visualization is the key to comprehending the continuously changing complex phenomena around us. multimedia combines information from local and remote sources. the users may view this information on on-demand basis. there are many issues associated with this: data manipulation, display, motion, security etc. this track attracts investigators from pure research to applications in wide variety of areas. some of the papers included were: consistency checking and temporal relations, digital watermarking, digital ink, multimedia information representation, rule based visualization techniques, scientific visualization with genetic algorithms, security, video indexing, video on demand, volume visualization, visualization techniques for data mining and surface modeling.
using formal methods to develop a complex information system: a practical/theoretical experience. in this paper we apply a new model to formally represent complex information systems. we show how this formalism, based on finite state machines, has been used as the basis to develop a real information system. this exercise convinced us that a formal approach to develop complex systems can facilitate some of the development phases.
message from the software engineering track chairs: editorial. welcome to the software engineering track of acm sac 2008 -- the 23nd annual acm symposium on applied computing. this year we have a special focus on "emerging techniques for dependable software development". the objective is to provide researchers and practitioners with an embedded forum for presenting and discussing their ideas and experiences with technologies, theories, and tools used for producing highly dependable software more efficiently asnd effectively. the software engineering track is big enough to represent major topics in software engineering, but also small enough to provide an in-depth representation of theory and practice in these areas. it provides an opportunity for academic researchers and industry participants to share their ideas and practices. it not only allows the software engineering academic community to understand the areas that are vital to the software industry, but it also gives software engineering practitioners an opportunity to express their needs.
control of system calls from outside of virtual machines. a virtual machine monitor (vmm) can isolate virtual machines (vms) for trusted programs from vms for untrusted ones. the security of vms for untrusted programs can be enhanced by monitoring and controlling the behavior of the vms with security systems running in a vm for trusted programs. however, programs running outside of a monitored vm usually obtain only low-level events and states such as interrupts and register values. therefore, it is not straight-forward for the programs to understand the high-level behavior of an operating system in a monitored vm and to control resources managed by the operating system. in this paper, we propose a security system that controls the execution of processes from the outside of vms. it consists of a modified vmm and a program running in a trusted vm. the system intercepts system calls invoked in a monitored vm and controls the execution according to a security policy. to fill the semantic gap between low-level events and high-level behavior, the system uses knowledge of the structure of a given operating system kernel. the user creates the knowledge with a tool when building an operating system. we implemented the system using xen, and measured the overhead through experiments using microbenchmarks and a benchmark for the apache web server.
a model-based semi-quantitative approach for evaluating security of enterprise networks. a challenging issue in enterprise risk management (erm) is to quantify network attributes with respect to security. this paper presents a model-based semi-quantitative approach for evaluating the security of enterprise networks. instead of focusing on particular attacks/intrusions, our approach aims at characterizing attacker behaviors by examining attacker intent, objective, and attack consequence, which are essential for enforcing an attack scheme. in particular, an attack scheme involving several atomic attacks is formulated as a partially observable markov decision process: a goal-directed attacker takes a sequence of actions to achieve the malicious goal, and a reward signal is used as feedback to integrate the attacker's intent, cost and objective and guides its advances. it is also used to measure attack impact, from security analyst's economic perspective, by considering the significance of network assets. our approach provides network administrators a useful tool for performing better countermeasures during the risk management process. we carry out a real trace study to demonstrate its feasibility in practice and validate its performance.
special track on adaptive techniques in operating systems: editorial message. the purpose of this track is to bring together researchers, designers, and developers who are interested in methodology for the design and analysis of operating systems and adaptive applications. it is motivated by a tremendous growth on the demands for high-performance operating systems in recent years. such an observation comes with the fact that many adaptive applications become more and more complex, and it imposes new challenging issues never faced before in this application field. it is thus clear that nowadays the development and design of operating systems must rely, even more than that in the recent past, on specific solutions both in the hardware and in the software components. moreover, the needs to timely tackle changes in the market pushes toward the employment of methodologies to shorten the development time and to drive the evolution of existing products. the solutions to new problems emerging in this setting call for a joint effort from the academics and industry.
an adaptation of the collections framework, reflection and object cloning from j2se to j2me. the jargon used by sun microsystems related to the java technology "write once, run anywhere" does not match the reality when it comes to devices with distinct memory and processing capability as can be evidenced by software engineers in migration projects between j2se and j2me platforms. this work proposes a solution on how to port conventional desktop-tailored codes to less capable mobile devices, achieving the same results, with comparative examples that use the collections framework classes, and the object cloning and reflection resources. moreover, this paper shows a case study where the proposed process is applied.
verifiable anonymous vote submission. this paper describes a new architecture for supporting the anonymous submission of votes in the revs voting system. furthermore, it enables voters to verify during the election that the electoral system processed correctly their anonymously submitted vote. this verification is a weak proof that the vote was effectively considered in the final tally. but since malicious electoral servers have no means to choose which votes should not be considered in the tally, the weak proof is strong enough for ensuring voters that the outcome of the election was not manipulated by the servers towards a particular outcome. in spite have been conceived for the revs system, our anonymizing architecture can be used in other voting systems as well. the only requirement is that it should be possible to submit the same vote several times and to detect and drop vote replicas at the tallying phase, which is valid for other blind signature voting protocols.
a wrapper generation system for pdf documents. the widespread use of the pdf format for exchanging print-oriented documents raises new challenges in the research field of information extraction. in this paper we present a novel wrapper generation system for extracting information from pdf documents. objects in a pdf document are accessible by their position, thus we exploit spatial constraints for driving the extraction of relevant information according to a set of group type definitions. moreover, using fuzzy logic based conditions enables effectively handling uncertainty on the comprehension of the layout structure of pdf documents. the experimental results shown in the paper state a good accuracy of our pdf wrapping system.
similarity estimation module for owscis. semantic interoperability based on ontologies is nowadays becoming a great challenge. we propose an architecture for semantic-based cooperation called owscis (ontology and web service based cooperation of information sources). it allows to map various information sources using ontologies and to answer users' queries over the cooperation. in this paper we focus on the similarity estimation service of the owscis architecture which allows to discover mappings between different ontologies. it relies on various mappings methods which are combined and refined to semi-automatically generate mappings between a local and a reference ontologies.
epml: an executable process modeling language for process-aware applications. process modeling and process enactment are becoming a prominent concern for a large class of modern applications. this is witnessed by the increasing number of modeling languages and software tools designed to assist the development of the so called process-aware applications. most of these languages and tools are targeted to different application domains (workflow management, web service orchestration, business process management, etc.) and also differ about the way coordination is achieved. this forces software designers to address the very same concern, process coordination, with different, albeit often similar, languages when moving across application domains. epml is a process modeling language that, along with its enactment engine, can be used to address process coordination across different application domains. this result is achieved with high expressive power and by promoting an effective separation of concerns that increases software composability.
redesigning business networks: reference process, network and service map. driven by factors like globalization, increased competition, and declining customer loyalty, the financial industry is facing a structural transformation. operating in a changing market, the (re)design of business models and thus also the business network is a mayor challenge for financial institutions. one way of succeeding in this endeavor is to focus on core competencies. banks therefore adjust their business models in order to reduce their degree of vertical integration by outsourcing complementary activities. this business redesign requires an integrated approach to align the future business model with the involved processes and information systems while also taking the surrounding conditions of the company and its market into account. present approaches show a restricted usability as they focus either on strategic aspects or process-efficiency only. moreover, these procedures often lack methodological support so that they are rarely applicable in practice. this paper introduces an integrated approach of business network redesign for the financial industry that covers the layers strategy, process and systems. the methodology considers the necessity for a common understanding of the underlying processes when reshaping the business model / network. since research is still in progress, this paper concentrates on the basic instruments which are used to describe a distinct business environment: a reference network and a reference service map both derived from a reference process. as the research focuses on the financial services sector, the paper exemplifies these reference models for the investment process from a bank's point of view. finally, the instruments are applied to a case study to verify their content and examine their applicability.
a constraint hierarchies approach to geometric constraints on sketches. we propose an approach that uses preferences on the constraints in order to deal with over-constrained geometric constraint problems. this approach employs constraint hierarchies, a paradigm that has close relations with the traditional graph-based approaches used in geometric constraint solving. we also remark that any geometric constraint problem defined by imposing relations on a sketch becomes overconstrained as soon as the sketch is imposed as a weak constraint representing the designers intents. as a result our method appears very appropriate in cad/cam tools.
increasing trust through the use of 3d e-commerce environment. existing 2d e-commerce internet websites provide users with only relatively simple, browser-based interface to access available products and services. these websites often lack in the emulation of real-life human representative which is an important factor in establishing consumer's trust. 3d e-commerce environments with 3d virtual space and human-like avatar facilitating the sale of real-world products may add the human factor to the shopping experience and might therefore enhance the relation of social trust in these environments. this paper explains the concept of 3d e-commerce environments and their roles in increasing consumer's trust and in enhancing e-business profitability.
towards automatic feature vector optimization for multimedia applications. we systematically evaluate a recently proposed method for unsupervised discrimination power analysis for feature selection and optimization in multimedia applications. a series of experiments using real and synthetic benchmark data is conducted, the results of which indicate the suitability of the method for unsupervised feature selection and optimization. we present an approach for generating synthetic feature spaces of varying discrimination power, modeling main characteristics from real world feature vector extractors. a simple, yet powerful visualization is used to communicate the results of the automatic analysis to the user.
extending rup to develop fault tolerant software. software reliability is generally considered a critical requirement in distributed systems such as web-based systems and real-time embedded systems. reliability can be obtained using fault tolerance techniques during the software development process. however, most of the software development processes do not provide suitable support for the construction of a software system that needs to meet fault tolerance requirements. the development processes as such rup were proposed before the recognition of this concern and they still lack appropriate support. rup (rational unified process) is a well-known software engineering process that provides a disciplined approach to assigning tasks and responsibilities. the paper aims to present an extension to rup for the development of fault tolerant software. the fault tolerance is embodied in rup as a knowledge area (discipline) with activities and roles defined according to the architecture of process engineering uma (unified method architecture). an example was elaborated to clarify and show the feasibility of the proposal.
special track on the semantic web and applications: editorial message. the technical track "the semantic web and applications (swa)" focuses on the topics related to semantic web technologies and their applications. the semantic web is a next generation web. the current web content is not easy to be processed by machines. on the other hand, the web content in the semantic web can be processed easily by machines. the techniques to realize and/or utilize the semantic web are discussed in this track.
scheduling distributable real-time threads in the presence of crash failures and message losses. we consider the problem of scheduling distributable realtime threads under run-time uncertainties including those on thread execution times, thread arrivals, node failures, and message losses. we present a distributed scheduling algorithm called acua that is designed under a partially synchronous model, allowing for probabilistically-described message delays. we show that acua satisfies thread time constraints in the presence of crash failures and message losses, is early-deciding, and has an efficient message and time complexity. the algorithm has also better "best-effort" real-time property than past thread scheduling algorithms.
propagating multitrust within trust networks. we suggest the concept of multitrust, which is aimed at computing trust by collectively involving a group of trustees at the same time: the trustor needs the concurrent support of multiple individuals to accomplish its task. we propose soft constraint logic programming based on semirings as a mean to quickly represent and evaluate trust propagation for this scenario. to attain this, we model the trust network adapting it to a weighted and-or graph, where the weight on a connector corresponds to the trust feedback value among the connected nodes. semirings are the parametric and flexible structures used to appropriately represent trust metrics.
a behavior priority driven approach for resource reservation scheduling. in this paper a behavioral distinction of soft real-time tasks is introduced. the distinction is based on the behavior of the previous instance of each task and it is used to propose a scheduling algorithm. the algorithm, called bids, uses well-known server mechanisms with an extension to handle two priority queues within each server. the priority of a server is managed accordingly to the result that its associated task produce. along with the formal presentation of the algorithm and the proofs of its properties some performance evaluations based on simulations are included.
applying markup language resources in the specification of visual alphabets and visual sentences. visual language systems are electronic artifacts that provide information in a graphical and dynamical way. in this article we propose an approach for visual language system specification based on visual alphabets and grammars where xml documents and schemas are specialized to specify visual language systems. in addition, we define how to manipulate and extract visual language information from these documents and schemas through xml resources. this approach was formally specified and as a proof of concept we implement our ideas in a visual language system generator.
citywalker: a mobile gps for walking travelers. global positioning system (gps) is widely used in vehicle navigation; however, they are unusable for pedestrians. problems include inadequate information for optimized path-planning in the pedestrian level; and the human-computer interface (hci) for vehicles basically does not work for walking user. this paper presents solutions to solve these problems through experiments. a new design of gps based human navigation aid, called "city walker", is proposed. citywalker uses a digital fluxgate compass to rotate the map automatically, according to user's orientation. city-walker thus provides a low-cost solution for building a gps based, human oriented navigation tool on various mobile platforms.
a performance comparison of pso and ga in scheduling hybrid flow-shops with multiprocessor tasks. applications in industry and computing require a proper scheduling of tasks to achieve good performance. the algorithms presented in this paper tackles task scheduling problem in a multi layer multiprocessor environment. using the scheduling terminology, problem is defined as multiprocessor task scheduling in hybrid flow-shops. this paper presents a particle swarm optimization (pso) algorithm for the solution. in order to improve the performance of pso, hybrid techniques were also employed. the performance results, compared with other well known meta-heuristics from the literature, are reported. results show that pso and hybrid methods have merits in solving multiprocessor task scheduling in hybrid flow-shop environment.
combination of decomposability and propagation for solving first-order constraints in decomposable theories. over the last decade, first-order constraints have been efficiently used in the constraint programming world to model many kinds of complex problems such as: scheduling, resource allocation, computer graphics and bio-informatics. recently, a new property called "decomposability" has been introduce and many first-order theories have been proved to be decomposable: finite or infinite trees, rational and real numbers, linear dense order, ... etc. a decision procedure in the form of 5 rewriting rules has also been developed but this later can only decide if a formula without free variables is true or not in any decomposable theory t. unfortunately, this decision procedure is not enough when we want to find the values of the free variables of any first-order constraint &phiv; so that &phiv; is true in any decomposable theory t. these kind of problems are generally known as first-order constraint satisfaction problems. we present in this paper not only a decision procedure but a full first-order constraint solver for any decomposable theory t. our solver is given in the form of six rewriting rules which transform any first-order constraint (which can possibly contain free variables) into an equivalent solved formula which is either the formula true, or the formula false or a formula having at least one free variable and written in a very simple and explicit solved form. we also show the efficiency of our solver by solving complex first-order constraints containing a huge number of imbricated quantifiers and negations. this is the first full first-order constraint solver over any decomposable theory.
xedge: clustering homogeneous and heterogeneous xml documents using edge summaries. in this paper we propose a unified clustering algorithm for both homogeneous and heterogeneous xml documents. depending on the type of the xml documents, the proposed algorithm modifies its distance metric in order to properly adapt to the special structural characteristics of homogeneous and heterogeneous xml documents. we compare the quality of the formed clusters with those of one of the latest xml clustering algorithms and show that our algorithm outperforms it in the case of both homogeneous and heterogeneous xml documents.
bigbatch: a document processing platform for clusters and grids. bigbatch is an image processing environment designed to process batches of thousands of monochromatic documents. one of the flexibilities and pioneer aspects of bigbatch is offering the possibility of working in distributed environments such as clusters and grids. this paper presents the bigbatch tool and the results of a comparative analysis between cluster and grid configurations. the results obtained show almost no difference in total execution times, indicating that performance is not a primary criterion for choosing between the use of a cluster or a grid. however, there are other, qualitative, aspects that may impact this choice. this paper also considers these aspects and provides a general picture of how to successfully use bigbatch to process document images employing many computers for this task.
performability evaluation of mobile client-server systems. recent advances in mobile computing have made it possible for customers carrying handheld devices to have access to data and information services regardless of their physical location. customers expect the same level of service in terms of availability and performance from the mobile applications as with their non-mobile counterparts. different types of client-server computing architectures are used today that facilitates such mobile access of data. in order to achieve high performance and availability, replicas of data servers are usually added to tolerate failures and balance workloads. this paper introduces a modeling technique to evaluate combined performance and availability that not only considers the failures of the mobile (i.e. wireless) links, mobile devices and the data servers but also takes into account the rate of mobility of the clients. it demonstrates the applicability of the model by building and analyzing models for two client-server architectures.
tag-aware recommender systems by fusion of collaborative filtering algorithms. recommender systems (rs) aim at predicting items or ratings of items that the user are interested in. collaborative filtering (cf) algorithms such as user- and item-based methods are the dominant techniques applied in rs algorithms. to improve recommendation quality, metadata such as content information of items has typically been used as additional knowledge. with the increasing popularity of the collaborative tagging systems, tags could be interesting and useful information to enhance rs algorithms. unlike attributes which are "global" descriptions of items, tags are "local" descriptions of items given by the users. to the best of our knowledge, there hasn't been any prior study on tag-aware rs. in this paper, we propose a generic method that allows tags to be incorporated to standard cf algorithms, by reducing the three-dimensional correlations to three two-dimensional correlations and then applying a fusion method to re-associate these correlations. additionally, we investigate the effect of incorporating tags information to different cf algorithms. empirical evaluations on three cf algorithms with real-life data set demonstrate that incorporating tags to our proposed approach provides promising and significant results.
code-carrying theory. code-carrying theory (cct) is an alternative to the proof-carrying code (pcc) approach to secure delivery of code. with pcc, code is accompanied by assertions and a proof of correctness or of other required properties. the code consumer does not accept delivery unless it first succeeds in generating theorems, called verification conditions, from the code and assertions and checking that the supplied proof proves these theorems. with cct, instead of transmitting code explicitly, only assertions and proofs are transmitted to the consumer. if proof checking succeeds, code is then obtained by applying a simple tool called codegen to the resulting theory. this paper explains the design and implementation of cct and shows how it can be used to achieve secure delivery of code with required correctness or safety properties. all the tools used in the verification steps are implemented in athena, which is both a traditional programming language and a deduction language.
special track on artificial intelligence in space applications: editorial message. the special track on artifical intelligence in space applications was part of the 2008 acm symposium on applied computing, which was held in march 16--20, 2008, in fortaleza, cear&aacute;, brazil.
houston, we have a problem...: a survey of actual problems in computer games development. this paper presents a survey of problems found in the development process of electronic games. these problems were collected mainly from game postmortems and specialized litterature on game development, allowing a comparison with respect to well-known problems in the traditional software industry.
handle local optimum traps in cbir systems. existing cbir systems, designed around query refinement based on relevance feedback, suffer from local optimum traps. that is, when the user is examining a relevant cluster surrounded by less relevant images, essentially the same set of images will be returned for the user to provide relevance feedback. since the user would select the same query images again, the relevance feedback process gets trapped in a local optimum. this local-optimum trap problem may severely impair the overall retrieval performance of today's cbir systems. in this paper, we therefore propose a simulated annealing-based approach to address this important issue. when a stuck-at-a-local-optimum occurs, we employ a neighborhood search technique (i.e., simulated annealing) to escape from the local optimum. we also propose an index structure to speed up such neighborhood search. our experimental study confirms that our approach can efficiently address the local-optimum trap problem, and therefore can improve the effectiveness of existing cbir systems.
special track on agent-oriented programming, systems, languages, and applications (apsla): editorial message. the requirements of distributed software systems become increasingly complex. among the aspects that characterize such a complexity are the inherent distribution of resources and activity - that makes global control practically infeasible and emphasizes the need for decentralized control - and the highly dynamic and changing operating conditions in which today's distributed applications operate - that calls for open and adaptive software.
combining symbolic and numerical solvers to simplify indecomposable systems solving. in computer-aided design, solvers always attempt to decompose geometric constraint systems into smaller ones in order to make faster the resolution. however, this scheme often fails in the case of 3d geometric constraint systems since they are hardly decomposable. we have studied a new method which uses jointly two solvers, a symbolic one and a numerical one, in order to solve a system s: system s is transformed into a parametric system s' "almost" equivalent to s and such that system s" is symbolically solvable and the numerical solver computes solutions of s from solutions of s".
using simplified event calculus in digital investigation. in a hypothesis-based approach to digital investigation, the investigator formulates his hypothesis about which events took place, and tests them using the evidence available. a formalism for the description of the investigated system is useful in the hypothesis formulation and testing. simplified event calculus, a form of propositional logic, can be used to define and test hypotheses in a digital investigation. when a system is modelled in this logic, observed states can be used to find action hypotheses and test them in the model. this can assist investigators and fact-finders in reconstruction of events from digital evidence. the logic can also be used to derive invariants for a system that can be utilized in tools checking evidence from these systems for consistency.
semi-supervised visual clustering for spherical coordinates systems. in this paper we propose a method that combines the advanced data analysis of the automatic statistical methods and the flexibility and manual parameter tuning of interactive visual clustering. we present the semi-supervised visual clustering (ssvc) interface; its main contribution is the learning of the optimal projection distance metric for the star and spherical coordinate visualization systems. beyond the conventional manual setting, it couples the visual clustering with the automatic setting where the projection distance metric is learned from the available set of user feedbacks in the form of either item similarities or direct item annotations. moreover, ssvc interface allows for the hybrid setting where some parameters are manually set by the user while the remaining parameters are determined by the optimal distance algorithm.
anomaly detection algorithms in logs of process aware systems. today, there is a variety of systems that support business process as a whole or partially. however, normative systems are not appropriate for some domains (e.g. health care) as a flexible support is needed to the participants. on the other hand, while it is important to support flexibility in these systems, security requirements can not be met whether these systems do not offer extra control. this paper presents and assesses two anomaly detection algorithms in logs of process aware systems (pas). the detection of an anomalous trace is based on the "noise" which a trace makes in a process model discovered by a process mining algorithm. this paper argues that these methods can support the coexistence of security and flexibility when aggregated to a pas.
segmentation technique for detecting suspect masses in dense breast digitized images as a tool for mammography cad schemes. breast cancer is one of the most important cause to mortality rate among women. computer-aided detection (cad) schemes have been developed as a tool in detecting early breast cancer. this can be an important tool in mammography since previous studies have been indicated that the detection of breast cancer can be increased up to 20% when assisted by a cad scheme. one of the main stages of such process is thus the segmentation of structures of interest, as the suspect masses. however, when evaluating mammograms obtained from dense breasts, a cad scheme efficacy can be very reduced due to the poor contrast of such type of image. this work attempts hence to this challenge, by describing a methodology for segmenting suspect masses in dense breast images as a part of a cad scheme under development. this methodology is based on the watershed transformation, which is combined with two other procedures -- a histogram equalization, working as pre-processing for enhance images contrast, and a labeling procedure intended to reduce noise. tests with a set of 252 regions of interest extracted from 130 digitized mammograms have registered a scheme sensibility of 92% with about 90% of specificity. these results are promising when applied to dense breast images, which can improve significantly the performance of a processing scheme for such type of cases in mammography.
events must be complete in event processing! current event detection systems are based on event completeness, which alone is insufficient for supporting new and advanced applications. in this paper, we discuss the need for events that are not complete. we briefly discuss their modeling and specification.
processing complex similarity queries in peer-to-peer networks. similarity search for content-based retrieval (where content can be any combination of text, image, audio/video, etc.) has gained importance in recent years, also because of the advantage of ranking the retrieved results according to their proximity to a query. however, to use similarity search in real world applications, we need to tackle the problem of huge volumes of such mixed multimedia data (e.g., coming from web sites) and the problem of their distribution on multiple cooperating nodes. the proposed approach is being used in two running projects: sapir and nep4b. in this paper we approach this problem by considering a scenario of a network of autonomous peers maintaining a local collection of metric objects (i.e., mixed mode multimedia content). this network forms a distributed peer-to-peer (p2p) search engine for similarity search based on the paradigm of routing index. each peer in the network thus maintains both an index of its local resources and a table for every neighbor, summarizing the objects that are reachable from it. the paper presents techniques that aim to make our p2p similarity-based search system viable, trading approximate results for scalable solutions. results of simulations that use real collections of images are discussed.
using association rules for energy conservation in wireless sensor networks. frequent radio transmissions among sensors, or from sensors to the basestation, have always been a major energy drain. one of the approaches to reduce the data transmitted to the basestation is to shift the bulk of data processing to networked sensor nodes; for instance, sensors to send only data aggregates to reduce the overall amount of data exchanged. sensor nodes, however, are quite limited in terms of their energy and processing power, and as such, traditional centralised data mining algorithms are infeasible to be directly implemented on sensors. in this paper, we modify apriori to find strong rules from sensor readings in a sensor network and using these rules, autonomously control sensor network operations or supplement sensor operations with a rule knowledge base. for example, triggers activated from the rules could be used to sleep sensors or reduce data transmissions to conserve sensor energy. our work here includes a detailed implementation of a lightweight rule learning algorithm for a resource-constrainted sensor network, with simulation results for a group node setup running the algorithm.
towards the composition of stateful and independent semantic web services. most of the work on automated semantic web service composition has focused so far on two main levels of composition i.e., functional level and process level composition (respectively flc and plc from now). the former level of composition considered web services as atomic components that can be executed in a single request-response step whereas the latter level studies in more details the protocol and the behavioural features of web services. since plc i.e., a time and particularly space consuming level of composition makes difficult the scalability of composition-based applications, it seems interesting to restrict the composition of stateful but (only) independent web services. such a restriction make possible the composition of a large number of web services in industrial scenarios, the whole with convincing results. in this paper we suggest to study the advantages to apply flc together with &beta;-composition in order to perform an automated end to end composition of stateful and independent services. in particular we focus on computational complexity results concerning the two models of composition i.e., the well-known plc vs. the newest flc+&beta;-composition. moreover we prove that flc is an interesting and necessary level of composition to significantly reduce computational complexity not only in space but also in time.
web service security management using semantic web techniques. the importance of the web service technology for business, government, among other sectors, is growing. its use in these sectors demands security concern. the web services security standard is a step towards satisfying this demand. however, in the current security approach, the mechanism used for describing security properties of web services restricts security policy specification and intersection. in environments that include loosely-coupled components, a rich description of components is needed to determine whether they can interact in a secure manner. the goal of this paper is to propose a security approach for web services, which combines web services policy framework policies and a web ontology language ontology to overcome the limitation of the current syntactic approach. the main contribution of this paper is an extended approach based on semantics-enriched security policies.
multiprocessor frequency locking for real-time task synchronization. energy-efficient real-time task scheduling is complicated by the deployment of co-processors. the problem complexity comes from the complexity in multiprocessor task scheduling and the difficulty in the trading of priority inversion with energy consumption. in this paper, a multiprocessor task synchronization protocol is proposed by locking the frequency of each (co-)processor and synchronizing resource sharing of tasks in a systematic way and with cross-(co)processor considerations. the well-known priority ceiling protocol is taken as an example for its extension on energy-efficient real-time multiprocessor scheduling. the objective is to minimize the energy consumption of a task set and, at the same time, meet the task deadlines. the capability of the proposed methodology is evaluated by a series of experiments, for which encouraging results are presented.
supporting the development of context-aware agent-based systems for mobile networks. distributed applications involving mobile devices interconnected by wireless networks may benefit both from multiagent technology and context-aware programming techniques. we present a system running on a agent platform to allow access to services that support the development of context-aware applications for mobile devices. the resulting middleware supports the easy and fast development of context-aware applications based on the multi-agent paradigm.
uml-based design test generation. in this paper we investigate and propose a fully automated technique to perform conformance checking of java implementations against uml class diagrams. in our approach, we reused the designwizard java api that allows us to write design rules as junit tests, i.e., to write them as code directly in the programming language. we fully pursued mda as the approach for generating the design tests and hence we used several mda artifacts, such as metamodels, models and transformations. a proof of concept of the technique has been implemented and evaluated. we performed several experiments on simple scenarios. simple designs involving classes, associations, inheritance have been checked. compared to previous related work, the advantage of our approach lies in the fact that we automatically generate design tests from uml class diagrams to java code that play the dual role of design test and implementation language. thus, we check the conformance between the design and the implementation.
contextualizing normative open multi-agent systems. open mass can be extremely dynamic due to heterogeneous agents that migrate among them to obtain resources or services not found locally. in order to prevent malicious actions and to ensure agent trust, open mas should be enhanced with normative mechanisms. however, it is not reasonable to expect that foreign agents will know in advance all the norms of the mas in which they will execute. thus this paper presents dynacrom, our approach for addressing these issues. from the individual agents' perspective, dynacrom is an information mechanism so that agents become context norm-aware; from the system developers' perspective, dynacrom is a methodology for norm management in regulated mass. notwithstanding the ultimate goal of a regulated mas is to have an enforcement mechanism, we also present in the paper the integration of dynacrom and scaar. scaar is the current solution of dynacrom for norm enforcement.
atmospheric temperature retrieval from satellite data: new non-extensive artificial neural network approach. in this paper, vertical temperature profiles are inferred by neural networks based inverse procedure from satellite data, non-linear function estimation. a new approach to classical radial basis function neural network is trained using data provided by the direct model characterized by the radiative transfer equation (rte). the neural network results are compared to the ones obtained from classical neural networks radial basis function and traditional method to solve inverse problems, the regularization. in addition, real radiation data from the hirs/2 - high resolution infrared radiation sounder - is used as input for the neural networks to generate temperature profiles that are compared to measured temperature profiles from radiosonde. analysis of the new approach results reveals the generated profiles closely approximate the results obtained with classical neural networks and regularized inversions, [5] [15], thus showing adequacy of neural network based models in solving the inverse problem of temperature retrieval from satellite data. the advantages of using neural network based systems are related to their intrinsic features of parallelism; after trained, the networks are much faster than regularized approaches, and hardware implementation possibilities that may imply in very fast processing systems.
integrating coercion with subtyping and multiple dispatch. coercion can greatly improve the readability of programs, especially in arithmetic expressions. however, coercion interacts with other features of programming languages, particularly subtyping and overloaded functions and operators, in ways that can produce surprising behavior. we study examples of such surprising behavior in existing languages. this study informs the design of the coercion mechanism of fortress, an object-oriented language with multiple dynamic dispatch, multiple inheritance and user-defined coercion. we describe this design and show how its restrictions on overloaded declarations prevent ambiguous calls due to coercion.
application of divide-and-conquer algorithm paradigm to improve the detection speed of high interaction client honeypots. we present the design and analysis of a new algorithm for high interaction client honeypots for finding malicious servers on a network. the algorithm uses the divide-and-conquer paradigm and results in a considerable performance gain over the existing sequential algorithm. the performance gain not only allows the client honeypot to inspect more servers with a given set of identical resources, but it also allows researchers to increase the classification delay to investigate false negatives incurred by the use of artificial time delays in current solutions.
automated segmentation and volumetric analysis of brain components on mr imaging. as the world population has been growing old, the incidence of several brain diseases, including dementia, has risen. as a consequence, a greater demand for automated segmentation methods and volumetric analysis of the brain structure and its components has increased. this work is based on the use of image processing algorithms and previous knowledge statistical models for automated segmentation over 386 magnetic resonance exams. we analyze brain components considering two different image subsets: non-demented and demented individuals. our results demonstrate gray and white matter loss, and csf enlargement with aging.
mining spam email to identify common origins for forensic application. in recent years, spam email has become a major tool for criminals to conduct illegal business on the internet. therefore, in this paper we describe a new research approach that uses data mining techniques to study spam emails with the focus on law enforcement forensic analysis. after we retrieve useful attributes from spam emails, we use a connected components clustering algorithm to form relationships between messages. these initial clusters are then refined by using a weighted edges model where membership in the cluster requires the weight to exceed a chosen threshold. the results of the cluster membership are validated by whois data, by the ip address of the computer hosting the advertised sites, and through comparison of graphical images of website fetches. this technique has been successful in identifying relationships between spam campaigns that were not identified by human researchers, enabling additional data to be brought into a single investigation.
digital audio watermarking evaluation within the application field of perceptual hashing. digital watermarking is a growing research area to mark digital content by embedding information into the content itself. perceptual hashing is used to identify a specific content or to identify integrity violation up to a specific threshold. the evaluation of digital watermarking algorithms provides a fair and automated analysis of specific watermarking schemes for selected application fields. in this paper, we enhance an existing theoretical framework to provide normalized comparable application oriented evaluation results of embedding transparency and we present first practical evaluation results of digital audio watermarking schemes in the application scenario of perceptual hashing. thereby, the internals of the evaluation profile for the embedding transparency of the digital watermarking schemes are enhanced with a normalized perceptual hash difference grade, used to provide an objectively comparison and to give a recommendation of the usability and applicability of the digital audio watermarking schemes within the application scenario of perceptual hashing. first evaluation results are presented with an inter algorithm evaluation and analysis for five exemplary selected digital audio watermarking schemes, working in time, frequency and wavelet domain, and they give an objective recommendation for their applicability within this application scenario.
a web-based system for the collection and analysis of spectra signals for early detection of voice alterations. voice is the result of the coordination of the whole pneumophonoarticulatory apparatus. the analysis of the voice allows the identification of the diseases of the vocal apparatus and currently is carried out from an expert doctor through methods based on the auditory analysis. this paper presents a web-based system for the acquisition and automatic analysis of vocal signals. vocal signals are submitted by the users through a simple web-interface and are analyzed in real-time by using state-of-the art signal processing techniques, providing first-level information on possible voice alterations. the system offers different analysis functions to the doctors that may analyze suspected cases in detail. the system is currently being tested in the otorhinolaryngologist setting to carry out mass prevention via screening at a regional scale.
special track on software verification: editorial message. these are the proceedings of the software verification track at the 2008 acm symposium on applied computing. we had 33 submitted papers and only 10 have been selected for publication. the high number of submissions is a success for our track and shows the interest of the scientific community towards software verification.
a programming environment for web services. pews is a programming language for the definition of web service interfaces. pews programs can be used for the description of both simple and composite web services. simple web services can be built from scratch, by the combination of (wsdl) operations. each operation must be implemented as a java method. composite web services are constructed from the combination of existing web services, accessed by using their wsdl descriptions. pews combinators help to define the order in which web services and operations will be performed. pews has a human-readable syntax as well as a xml version, called xpews. the human-readable language is intended to help in the design of web services and in the formal reasoning about programs. xpews is used as an interface language between the front-end and back-end of the pews language processor. this paper presents the development of a computational environment for pews. the front-end of the environment is an eclipse plug-in. the use of the front-end can help reducing the time for development of the compositions, by the verification of codification errors and the generation xpews documents. the back-end of pews is responsible for the implementation of the web services described in a xpews document. the back-end produces java&trade; code (skeletons) to call the web service operations and performs them in the order defined by the xpews document.
secured tag identification using edsa (enhanced distributed scalable architecture). rfid technology has become increasingly popular in todays society and plays an important role in daily life. however, the exploitation of this technology requires practical and secure solutions to overcome certain issues. in the case of rfid systems, privacy protection and scalability are two conflicting goals. nevertheless, in this paper we propose a hexagonal cell based distributed architecture which ensures improved scalability while maintaining privacy. the hexagonal architecture allows readers to co-operate with one another to identify tags without compromising scalability. furthermore, this architecture uses serverless protocols for security assurance, cutting down set up and maintenance cost as well as traffic to server. to the best of our knowledge, we propose a combination of servered and serverless techniques within the same distributed architecture for the first time. our proposed distributed scalable architecture together with the secure serverless protocols can be used in numerous real life situations.
borboleta: a mobile telehealth system for primary homecare. public homecare programs such as the brazilian family health program, initiated in the late 1990s, have proven to be a very effective tool for preventive medicine. the goal of these programs is to bring physicians, nurses, and social workers to the homes of the lower income population in lesser-attended regions within multi-million people metropolis. however, there is practically no it support for the operation of these programs, leading to inefficiencies. for example, in a particular primary homecare program our group is involved with, nurses visit the homes of their patients carrying a pencil and a piece of paper and, during their visits, found themselves isolated from the primary healthcare center, the university hospital, and the physicians who could provide them with important information to improve the quality of the services they provide. each visit associated with the program results in a three-page report, which is handwritten and stored in cabinets, with no possibility for information summarization, statistical analysis, or data mining. in this paper, we describe the architectural design, the prototype implementation, and our preliminary experiences with the borboleta system, whose goal is to use mobile computing technologies to promote digital inclusion as well as to improve the quality of preventive healthcare services offered by the public sector. we focus primarily in developing software that runs on pdas used by health professionals while providing home healthcare. currently, nurses of the primary healthcare center are testing the system and starting to use it on medical visits.
spem on test: the soda case study. in the software engineering (se) research field, several efforts are underway aimed at developing appropriate meta-models for se methodologies. meta-models are meant to check and verify both the software development process and the completeness and expressiveness of methodologies. in this context, in order to provide a uniform way to represent, compare and reuse methodologies, software process engineering meta-model (spem) -- an omg object-oriented standard -- is a natural candidate. in order to put the spem meta-modelling power to test, and emphasise its benefits and limitations, in this paper we apply spem to a more articulated context than the object-oriented one where it was initially conceived -- that is, agent-oriented software engineering (aose) methodologies. in particular, we take the soda methodology as a significant case study in order to assess strengths and limitations of spem, given the peculiar soda focus on the modelling and engineering of (i) social issues and (ii) application environment -- essential aspects in the engineering of complex software systems.
the volume in focus: hardware-assisted focus and context effects for volume visualization. in many volume visualization applications there is some region of specific interest where we wish to see fine detail - yet we do not want to lose an impression of the overall picture. in this research we apply the notion of focus and context to texture-based volume rendering. a framework has been developed that enables users to achieve fast volumetric distortion and other effects of practical use. the framework has been implemented through direct programming of the graphics processor and integrated into a volume rendering system. our driving application is the effective visualization of aneurysms, an important issue in neurosurgery. we have developed and evaluated an easy-to-use system that allows a neurosurgical team to explore the nature of cerebral aneurysms, visualizing the aneurysm itself in fine detail while still retaining a view of the surrounding vasculature.
an approach for supporting system-level test scenarios generation from textual use cases. this paper presents an approach for system-level test scenarios generation from use cases in text form. test scenarios are linear sequences of events used as intermediate representations toward complete test cases. a restricted form of natural language is used for use cases description. we start by generating control flow-based state machines from each use case. these state machines are then connected in a global system-level state machine according to derived sequencing relations between use cases. we infer sequencing relations based on a comparison of use cases pre-conditions and post-conditions. test scenarios are generated using depth-first traversal of the generated control flow-based state machines according to criteria inspired from traditional white-box code coverage.
vhdl vs. bluespec system verilog: a case study on a java embedded architecture. this paper compares two hardware design flows, based on the classic vhdl on one side and the relatively new blue-spec system verilog (bsv) on the other side. the comparison is based on a case study of a java embedded architecture, comprising a java native processor and a memory management unit. the processor is a micro-programmed, pipelined, java-optimized processor (jop), initially written in vhdl, and its bsv re-designed match bluejep. its memory management unit implements the bytecodes dealing with memory allocation, along with a mark-compact garbage collector. the two design flows are examined from several points of view, including both quantitative and qualitative measures. based on this design experience, we conclude that the new high-abstraction level languages, such as bsv, offer in comparison to register-transfer (rt) level classic approaches roughly the same trade-offs that c++ offers vs. assembly language in the software world.
automatic test data generation using particle systems. the simulated repulsion algorithm, which is based on particle systems, is used for the automatic generation of diversity oriented test sets (dots). these test sets are generated by taking randomly generated test sets and iteratively improving their diversity (the level of variability among values for the test data) towards dots. the results of a simulation performed to evaluate characteristics of dots indicate improvement, with respect to fault detection, of these test sets over the standard random test sets.
percolation analyses in a swarm based algorithm for shortest-path finding. in this paper we show that the convergence in the ant colony optimization (aco) algorithm can be described as a "phase- transition" phenomenon. the analysis of the aco with the percolation theory approach includes: the pheromone evaporation and the number of agents parameters, so, for a given routing environment, it is possible to select these parameters in order to ensure convergence and to avoid overhead in the algorithm. the objective of this work is to present some experiments that support our hypothesis and to show the methodology used to correlate some algorithm parameters and how they influence in its general performance.
context distribution for supporting composition of applications in ubiquitous computing. devices and applications reacting to each other and to the environment in which they reside is a very important part of ambient intelligent systems. such context-aware systems require mechanisms to react to changes in their surrounding environment.
a detectability analysis of fault classes for boolean specifications. the detectability hierarchies of fault classes for specification-based testing have been established to prioritize test cases so as to achieve earlier detection of more faults. this paper extends and complements the existing studies by analyzing detectability of fault classes for boolean specifications in general form. the monotonicity of detectability is discovered that a fault occurs at literal is more difficult to detect than the corresponding one occurs at other positions. furthermore, a strong detectability relationship is introduced to overcome the flaw of traditional approach. it can help identify stronger faults and skip weaker faults during testing. as a result, two detectability hierarchies are established on the detection conditions of fault classes.
modeling and verifying bpel using synchronized net. web service composition, which is an application of the service-oriented architecture, refers to combining existing web services to a new one. bpel (business process execution language) is a language describing the composition of web services. the process of composition is error-prone. in order to guarantee the correctness of service composition, the idea of modeling and verifying bpel in different levels, the logic level and the semantic level, is put forward. this can not only assure modeling the processes properly, but also lower the complexity of models and verifications. in the logic level, some elements of bpel, according to the mapping rules, are mapped to wsl_net, which is a special synchronized net. properties such as sound and efficient guarantee the correctness of the basic control flows in bpel process and avoid unnecessary resource consuming. the construction and verification of the model of the semantic level, in which more elements of bpel will be introduced, will be given in later papers.
a cost-driven approach to role engineering. in recent years role-based access control (rbac) has been spreading within organizations. however, companies still have considerable difficulty migrating to this model, due to the complexity involved in identifying a set of roles fitting the real needs of the company. all the various role engineering methods proposed thus far lack a metric for measuring the "quality" of candidate roles produced. this paper proposes a new approach guided by a cost-based metric, where "cost" represents the effort to administer the resulting rbac. further, we propose ream (role-based association-rule mining), an algorithm leveraging the cost metric to find candidate role-sets with the lowest possible administration cost. for a specific parameter set, rbam behaves as already existing role mining algorithms and is, worst case, np-complete. yet, we will provide several examples showing the sensibility of assumptions made by the algorithm. further, application of the algorithm to real data will highlight the improvements over current solutions. finally, we comment on the direction of future research.
a group management scheme for an efficient location-based service. this paper proposes and evaluates the performance of a cooperative position fix scheme built on top of a group management mechanism supported typically in the embedded operating system. the main goal is to enhance the accuracy of map matching and thus the quality of diverse lbss without an extra equipment. designed on the telematics network consist of many in-vehicle telematics devices moving on the road network, the proposed scheme enables each device to collect the gps readings from its neighbors through the air interface when necessary. with at least 3 affirmative points having a unique segment to match, the gps deviation can be calculated from a system of indeterminate equations, and then used to improve positioning accuracy. the performance measurement result shows that the proposed scheme can reduce ambiguous points from 32.0 % to 20.6 %, while the number of points having affirmity larger than 3.0 was also increased from 61.0 % to 71.2 %, sharpening the gap between the best two matches.
a pull-based e-mail architecture. conventional e-mail systems are prone to problems that impact their scalability and dependability. e-mail systems operate following a "push-based" approach: the sender side server pushes the e-mails it wants to send to the corresponding receivers' servers. this approach can impose processing and storage overhead on the receiver side. this paper presents an e-mail architecture in which messages are sent directly from senders to receivers using a "pull-based" approach. the sender stores locally all e-mails it intends to send, and notify their receivers using a global, distributed notification service. receivers can then retrieve such notifications and decide if they want to receive the corresponding e-mails. if so, e-mails can be retrieved directly from their senders. this proposal is inspired from file sharing peer-to-peer systems, in which users locate and retrieve the contents they are looking for. a prototype was built to show the feasibility of the proposal.
software frameworks for information systems integration based on web services. in this work, we discuss the development of software frameworks to support information systems integration based on web services. as our main contribution, we introduce a set of requirements that these frameworks should address and present some relevant aspects of a framework called business application support through software services (bass) that was developed considering these requirements.
agent and ontology based information gathering on restricted web domains with agathe. due to web size and diversity of information, relevant information gathering on the web is a very complex task. the main problem with most information retrieval approaches is neglecting the context of the pages, mainly because search engines are based on keyword indexing. considering restricted domain, the policy of taking into account context may lead to more relevant information gathering in this paper, a specific cooperative information gathering approach based on the use of software agents and ontologies is proposed. to implement this approach, a generic software architecture, named agathe system, based on early prototype, the master-web system, permitting development of specific restricted-domain information gathering systems is presented in detail, with a focus on the extraction subsystem.
a statistical approach for prediction of projects based on simulation. the definition of imprecise estimates is one of the crucial problems of software industry. in this context, this work presents an approach for prediction of stated periods of projects based on simulation, using statistical methods. the simulation is used to provide more confidence to the estimates defined by the project manager, so that they can reflect the organization's reality. based on the estimates provided by the simulator, statistical methods are used to predict an interval, to which the end of the project, in practice, will have chances to belong to. a case study was performed in the end of the research attesting, statistically, the potential of the approach defined in this work.
a continuous facility location problem and its application to a clustering problem. we consider a new problem, which we denote by continuous facility location (confl), and its application to the k-means problem. problem confl is a natural extension of the uncapacitated facility location problem where a facility can be any point in rq. the proposed algorithms are based on a primal-dual technique for spaces with constant dimensions. for the confl problem, we present algorithms with approximation factors 3 + &epsilon; and 1.861 + &epsilon; for euclidean distances and 9 + &epsilon; for squared euclidean distances. for the k-means problem (that is restricted to squared euclidean distance), we present an algorithm with approximation factor 54+ &epsilon;. all algorithms have good practical behaviour in small dimensions. comparisons with known algorithms show that the proposed algorithms have good practical behaviour.
online detection of malicious data access using dbms auditing. this paper proposes a mechanism that allows concurrent detection of malicious data access through the online analysis of the database management systems (dbms) audit trail. the proposed mechanism uses a directed graph representing the profile of valid transactions to detect illegal accesses to data, which are seen as unauthorized sequences of structured query language (sql) commands. the paper proposes a generic algorithm that learns the graph representing the profile of the transactions executed by the users. this mechanism can be used to protect traditional database applications from data attacks as well as web based applications from sql injection types of attacks. the proposed mechanism is generic and can be used in most commercial dbms, adding concurrent detection of malicious data access to classical database security mechanisms. the paper presents a practical example of the implementation of the proposed mechanism using oracle 10g. the transaction processing performance council benchmark c (tpc-c) and a real database installation were used to assess the detection mechanism and learning algorithm.
adding background knowledge to formal concept analysis via attribute dependency formulas. we present a way to add user's background knowledge to formal concept analysis. the type of background knowledge we deal with relates to relative importance of attributes in the input data. we introduce ad-formulas which represent this type of background knowledge. the background knowledge serves as a constraint. the main aim is to make extraction of clusters from the input data more focused by taking into account the background knowledge. particularly, only clusters which are compatible with the background knowledge are extracted from data. as a result, the number of extracted clusters becomes smaller, leaving out non-interesting clusters. we present illustrative examples and results on entailment of background knowledge such as efficient testing of entailment and a complete systems of deduction rules.
dynamically tuning the population size in particle swarm optimization. in this paper, we investigate the benefits of dynamically varying the population size in the particle swarm optimization (pso) model. for this purpose, two well-known population resizing techniques, originally developed for genetic algorithms (gas), were adapted to the pso context, giving birth to the appso and profipso variants. contrary to some previous work that has indicated that the pso model is not sensitive to the population dimension, the simulation results we have obtained over some benchmark numerical optimization problems suggest that the dynamic variation of the number of particles may be instrumental for bringing about performance improvements in long-term runs, mainly when considering high-dimensional problem instances. in general, the novel pso variants have compared more favorably to their ga counterparts in targeting the optimal solutions. however, regarding profipso specifically, the price to be paid in terms of resources used to reach the optimum point is as a rule very high.
towards verification and testing of java programs. testing object-oriented programs is still a hard task, despite many studies on criteria to better cover the test space. test criteria establish requirements one want to achieve in testing programs to help in finding software defects. on the other hand, program verification guarantees that a program preserves its specification but it is not very straightforwardly applicable in many cases. both program testing and verification are expensive tasks and could be used to complement each other. this paper presents a study on using formal verification to reduce the space of program testing. as properties are checked using program model checkers, programs are traced. information from these traces can be used to realize how much testing criteria have been satisfied, reducing the further program test space. the present work is a study on how much the test space of concurrent java programs can be reduced if deadlockfreedom is checked prior to testing.
logical and physical data collection of windows ce based portable devices. nowadays, small-scale embedded devices are becoming more and more pervasive, reaching levels of diffusion not previously seen for other hardware platforms. these kinds of devices are able to contain plenty of information, which can be really precious in an investigative scenario. from a digital forensics perspective it is necessary to have a framework of best practices which can be used for collecting all the observable memory within such devices. in this paper we will pinpoint how to collect such digital data from a logical and physical perspective, by portraying the peculiarities of embedded devices which use the windows ce operating system (os). moreover, we will outline the implications related to data hiding at the firmware level, giving also some guidelines which can be used by forensics practitioners in an investigative field.
data stream mining for market-neutral algorithmic trading. in algorithmic trading applications, a large number of co-evolving financial data streams are observed and analyzed. a recurrent and important task is to determine how a given stream depends on others, over time, accounting for dynamic dependence patterns and without imposing any probabilistic law governing this dependence. we demonstrate how flexible least squares (fls), a penalized version of ordinary least squares that accommodates for dynamic regression coefficients, can be deployed successfully in this context. we describe a market-neutral algorithmic trading system based on a combined use of on-line feature extraction and recursive regression. the system has been proved to perform successfully when trading the s&p 500 futures index.
special track on engineering large-scale distributed systems: editorial message. social phenomena like youtube and flickr are incontrovertible evidence of users' migration to a new web overwhelmed by multimedia. in fact, images, videos, music, and other kinds of multimedia objects today constitute about 99% of the web. nonetheless, users' chances of a successful search in such a large portion of information are not proportionally supported. web search is dominated by giants like google, yahoo! and microsoft that exploit centralized text-only indices enriched by an endless toolbox of smart ranking algorithms. their interest in riding this new tide is witnessed by the acquisition of both flickr and youtube. on the other hand, content-based search for image, music and videos has been deeply studied in the last years but it is not yet adopted by the industry because of its cost.
attaining soft real-time constraint and energy-efficiency in web servers. m/m/1 queues have been traditionally used to model several systems like phone calls at a call center, banking services and so on. however, recent studies showed that it does not model properly a web server system. in this paper we investigate the impact of this assumption in providing timeliness constraint in an energy-efficient web server. although energy efficiency is a key issue, it should not be attained at the expense of a poor quality of service. the work proposed here describes a technique that uses queueing theory results to balance energy consumption and adequate application response times in heterogeneous cpu-intensive server clusters. moreover, we investigate the i/o impact on a purely cpu-oriented energy saving strategy. this proposal shows that the assumption of a poisson process is a good approximation to model a web server.
managing data quality in a terabyte-scale sensor archive. sensor networks collect vast amounts of real-time information about the environment, business processes, and systems. archived sensor data is valuable for long-term analysis and decision making, which requires it be suitably archived, indexed, and validated. in this paper, we describe a general approach to managing and improving data quality by the generation and validation of metadata and the logging of workflow events. the approach has been implemented within a system archiving terabytes of u.s. weather radar data. the data quality system has resulted in the detection of data errors while simplifying the administration of the complex archive system.
towards self-configuration and management of e-service provisioning in dynamic value constellations. networked value constellations are collections of enterprises that jointly satify complex consumer needs. increasingly, such needs are satisfied by e-services, i.e. commercial services that can be ordered and provisioned via the internet. current research in dynamic web-service composition has yielded run-time platforms to dynamically compose complex web services, but there is still a considerable gap between web services and commercial e-services. to compose e-services, an estimation of commercial profitability must be made, which is absent from web service composition. in this paper, we extend our earlier approach to e-service composition with a dynamic part, that ensures that a commercial e-service can be dynamically composed from other commercial e-services, and can be mapped on a web service composition process composition of lower-level web services. we propose a skeleton-oriented approach, that first composes a network of enterprises, jointly satisfying need, based on commercial considerations. second, given a set of such candidate value constellations, the business processes providing the services can be dynamically configured. we illustrate this skeleton-driven composition of networked value constellations by using a case study of clearing and repartitioning of intellectual property rights (ipr).
extending an ontology-based search with a formalism for spatial reasoning. with the objective of extending an existing ontology-based search with a formalism for spatial reasoning two approaches to a representation of the region connection calculus (rcc) in owl dl are explored. the exploration results in a representation which is minimal yet still allows inferring the relations between all connecting regions in any of the different rcc species using a sound and complete calculus. the theoretical results are demonstrated in a sample application. the scale of the representation in the sample application is discussed. while the successful approach can be applied to small applications, we conclude that further research is required before applying it to large applications.
an algorithm for the tracing problem using interval analysis. we give an algorithm for the tracing problem in dynamic geometry that uses interval arithmetic. in this work, we focus on an algebraic model. here the objects are real or complex numbers with the operations +, --, .,/, and &radic;. originally, geometric objects like points, lines, or circles have been considered. our algorithm proceeds stepwise and detects (potential) critical points in advance. for each step, the algorithm computes a steplength that is small enough to handle the ambiguity of the root function. this is achieved by using interval arithmetic. after the detection of a critical point, the singularity is avoided by a detour through the complex plane c.
aggregation languages for moving object and places of interest. we address aggregate queries over gis data and moving object data, where non-spatial information is stored in a data warehouse. we propose a formal data model and query language to express complex aggregate queries. next, we study the compression of trajectory data, produced by moving objects, using the notions of stops and moves. we show that stops and moves are expressible in our query language and we consider a fragment of this language, consisting of regular expressions to talk about temporally ordered sequences of stops and moves. this fragment can be used not only for querying, but also for expressing data mining and pattern matching tasks over trajectory data.
system level power profile analysis and optimization for smart cards and mobile devices. the steadily increasing performance of rf-powered devices implies also a rise in power consumption. to counteract this trend, it is mandatory to accomplish power optimizations at every stage in the hw/sw co-design process. since the momentarily available energy depends on the power profile of anterior tasks, the behavior of the rf-interface has to be considered in the optimization process to achieve a maximum of efficiency by maintaining the system stability. this paper introduces an accurate discrete-time model of the energy source of rf-powered devices. based on this model, a power profile analysis tool has been developed, which identifies automatically critical regions for the energy source in the current profile of the system. the use of this framework is illustrated in a software optimization process, which intends to eliminate the detected critical areas.
supporting ethnographic studies of ubiquitous computing in the medical grand round experience. ethnography is a research method to understand how people carry out their tasks in real-world experiences. medical grand rounds are quotidian, formal meeting experiences where physicians discuss clinical problems of patients. this paper presents an ethnographic study of medical grand rounds that has driven the design and development of a ubiquitous computing prototype to address the lack of a proper documentation of medical grand rounds. we have learnt that ethnography is a powerful means of understanding tacit knowledge about physicians' needs, behaviors and rituals
a umls interoperable solution to support collaborative diagnosis decision making over the internet. hospitals can supply clinical decision support systems with electronic healthcare record provided by different users and stored in different computer systems. this way, during a diagnosis decision a user can be supported by a remote knowledge database constructed by other users, like, for instance, a reference specialist discussion board. usually, medical applications scenarios like this use different terminology systems leading to terminological interoperability problems. still, clinical applications frequently make use of different clinical ontology systems that do not provide semantic types necessary to create a structure to carry shared knowledge database. the lack of this semantic types brings ontology interoperability problems which difficult the support of collaborative clinical decision-making. this paper presents a umls interoperable solution to promote clinical applications development intended to contribute with collaborative diagnosis decision, in a distributed computer environment based on service-oriented architecture. this paper still presents a case study to demonstrate ddsont usability through the development of a system prototype integrated to a collaborative and multimedia communication distance-learning environment.
strategies for qos improvement on the time-interval scheduling. in this paper we analyze the interference among the non-preemptive segments in the time-interval problem. also, we explore the subject of fixed priority assignment for those segments through a suboptimal algorithm. consequently, the offline feasibility test becomes less pessimistic resulting in higher qos values comparing to previous studies.
context-aware information retrieval on a ubiquitous medical learning environment. this paper proposes an information retrieval process that employs a relevance feedback approach based on implicit evidences provided by contextual information and explicit evidences provided by the user behavior during interaction. this process takes advantage of semantic information processing enabled by the use of ontologies to build semantic indexes, to represent context and domain knowledge and to aid interactions mediated by mobile devices.
semantic mapping and k-means applied to hybrid som-based document organization system construction. in this paper, we present and evaluate a hybrid document organization system based on self-organizing maps. the proposed system uses semantic mapping to dimensionality reduction and k-means to volume reduction of document vectors of a medium text collection. the vectors obtained after dimensionality and volume reduction steps are used to train the document maps with the som algorithm, thus the training time is reduced without compromising the quality of the generated map. we compare experimentally the hybrid system with the correspondent som system in organization of documents of reuters-21758 v1.0 collection. the performances of the systems were measured in terms of classification error in text categorization and training time. the experimental results show that the proposed system generates pretty good document maps with smallest training time.
a hierarchical model-based approach to co-clustering high-dimensional data. we propose a hierarchical, model-based co-clustering framework for handling high-dimensional datasets. the technique views the dataset as a joint probability distribution over row and column variables. our approach starts by clustering tuples in a dataset, where each cluster is characterized by a different probability distribution. subsequently, the conditional distribution of attributes over tuples is exploited to discover natural co-clusters in the data. an intensive empirical evaluation highlights the effectiveness of our approach.
automatic software fault localization using generic program invariants. despite extensive testing in the development phase, residual defects can be a great threat to dependability in the operational phase. this paper studies the utility of low-cost, generic invariants ("screeners") in their capacity of error detectors within a spectrum-based fault localization (sfl) approach aimed to diagnose program defects in the operational phase. the screeners considered are simple bit-mask and range invariants that screen every load/store and function argument/return program point. their generic nature allows them to be automatically instrumented without any programmer-effort, while training is straightforward given the test cases available in the development phase. experiments based on the siemens program set demonstrate diagnostic performance that is similar to the traditional, development-time application of sfl based on the program pass/fail information known before-hand. this diagnostic performance is currently attained at an average 14% screener execution time overhead, but this overhead can be reduced at limited performance penalty.
modeling adversary scheduling with qcsp. we consider cumulative scheduling problems in the presence of an adversary. in such setting the scheduler tries to manage the available resources in so as to meet the scheduling deadline, while the adversary is allowed to change some parameters---like the resource consumption of some tasks---up to a certain limit. we ask whether a robust schedule exists, i.e., one that is guaranteed to work whatever (malicious) actions the opponent may take. we propose to model this family of decision problems using a variant of quantified constraint satisfaction problems called qcsp+, and to solve them by using the solver qecode.
face recognition using dct coefficients selection. this paper presents a face recognition method based on discrete cosine transform (dct) coefficient's selection. without a normalization phase, the proposed method uses, in its feature selection stage, a technique based only on the dct coefficients amplitudes. three coefficient selection criterions were analyzed: the first one is the average of the coefficients' amplitudes; the second one is based on counting the occurrence of each coefficient, which are stored in a set of lists containing the most significant coefficients; finally, the third criterion is based on the average position of the coefficients in a list of coefficients ordered by amplitude. experimental tests on the orl face database [1] achieved 99.00% of recognition accuracy using only 50 dct coefficients, with low computational cost. additionally, the method achieved 100.00% of recognition accuracy when the correct face is within a range of eight returned faces.
coordination schemes in distributed simulation of relativistic particle transport. in distributed simulation, overheads of coordinating operations across computing nodes could counteract the benefit of having extra machines. meanwhile, some scientific applications such as relativistic particle transport exhibit strong data dependency among events. this paper proposed several coordination schemes to reduce communication frequency and volume, overlap computation and communication operations, and arrange event simulation speculatively. performance gains are expected.
on the meaning of modes in uniprocessor real-time systems. one way to manage the complexity of the design and the implementation of large and adaptive real-time systems is to partition the design into modes of operation. this approach allows designers to break down the complexity of these systems into a number of layers of control (modes), which are then multiplexed in time (by means of mode changes) during system operation. however, due to a lack of a uniform view of modes within the literature, the task of successfully designing complex real-time systems with modes of operation becomes more difficult, if not compromised [1]. in this paper we consider the following recurring issues of modes in real-time systems, both from the application and design concerns: 1) what is a mode of operation, i.e. which features are exclusive to a particular mode of operation that allow its identification and distinction from other modes? 2) what can be understood by the concept of mode changes in realtime systems? the examination of these issues is lacking in the literature and will facilitate the analysis, design and construction of the next generation of complex real-time systems.
consistent privacy preferences (cpp): model, semantics, and properties. the platform for privacy preferences (p3p) is a w3c specification that can be used to build useful protocols and services for protecting user privacy on the semantic web. an outstanding issue is the need for a simple and efficient representation and management of consistent sets of rules for user privacy preferences. thus we describe a model for privacy preference representation and management that has a number of desirable properties which are lacking in privacy preference models proposed thus far. we detail semantics and properties of matching preference rules with requests. we specify the properties of a consistent set of privacy preferences, and propose maintenance operations. finally, we describe an implementation of our proposal that uses owl (web ontology language) and the jena reasoning engine to illustrate the practicality of managing consistent user preferences in privacy rule-sets. an important advantage of our approach is that the user is encouraged to clarify privacy preferences as he/she modifies them as part of a back-end management task, as opposed to mainly at website interaction times.
exploiting program cyclic behavior to reduce memory latency in embedded processors. in this work we modify the conventional row buffer allocation mechanism used in ddr2 sdram banks to improve average memory latency and overall processor performance. our method assigns row buffers to different banks dynamically and by taking into account program cyclic behavior and bank row buffer demand. as we show in this work, memory requests go through several phases. in each phase, programs tend to access a single bank most of the time. we exploit this repetitive behavior and improve the concurrency level for memory read and write operations. we do so by assigning idle row buffers to more demanding banks during specific program phases. this improves average memory latency and processor performance by 12.7% and 7.6% respectively.
improving network management with mobile agents in peer-to-peer networks. regarding the size and the complexity growth of today's networks, several network management models have been studied and proposed. furthermore, new requirements emerge with the interaction among entities that compose the management system, such as interoperability, collaboration among managers geographically separated, resources sharing, load balancing and inter-domain manager. it occurs that many of these models don't worry about the network logical configuration. in this paper, we present an improvement in the network management by combining p2p-based management system and mobile agents. the idea is to provide a mobile agent system extension for its integration with an architecture of network management based on peer-to-peer (p2p) networks. the mobile agent system makes it possible to have a more robust and self-organized network, together with the distributed system benefits.
path-based verification for composition of semantic web services. this paper proposes a novel approach to the verification for composition of web services annotated by ontology-based input, output, precondition and effect. in this approach, implicit inconsistency and explicit inconsistency may be detected on a path. firstly, a normal form for the description of precondition and effect is defined, then an algorithm for automatically determining the accumulated effects of ordered services is given out. thirdly, an algorithm for verifying a single path extracted from the composition is illustrated. on the basis of the approach, some experiments for verifying a single path are demonstrated. eventually an e-business example is presented to demonstrate the approach.
borderline detection by bayes vector quantizers. borderline detection is the problem of finding samples falling near the decision boundary. it has many applications, related to the fact that for these samples small variations of feature values, due for instance to the presence of noise, can completely change their classification. in this paper, we propose an approach to borderline detection based on the geometric characteristics of labeled vector quantizers. the approach is based on the estimation of the true decision boundary by means of the bayes vector quantizer (bvq) algorithm. bvq is a stochastic gradient algorithm for the minimization of the misclassification risk, hence it guarantees the accurate approximation of the optimal decision boundary. the features of the approach are discussed in comparison with support vector machines (svm), that is the best boundary hunting technique known in the literature.
reachability analysis of generalized polygonal hybrid systems. a polygonal hybrid system (spdis) is a planar hybrid system, whose dynamics is defined by constant differential inclusions, for which the reachability problem is decidable. the decidability result is based, among other things, on the fact that a trajectory cannot enter and leave a given region through the same edge. spdis without such an assumption are called generalized spdis (gspdis). in this paper we show that in general it is not possible to reduce gspdi reachability to spdi reachability. furthermore, we provide a terminating algorithm implementing a semi-test for gspdi reachability, based on that for spdis.
automated classification of change messages in open source projects. source control systems permit developers to attach a free form message to every committed change. the content of these change messages can support software maintenance activities. we present an automated approach to classify a change message as either a bug fix, a feature introduction, or a general maintenance change. researchers can study the evolution of project using our classification. for example, researchers can monitor the rate of bug fixes in a project without having access to bug reporting databases like bugzilla. a case study using change messages from several open source projects, shows that our approach produces results similar to a manual classifications performed by professional developers. these findings are similar to ones reported by mockus and votta for commercial projects.
using process algebra to control the execution of business processes. integrating information systems with tools that manage workflows and business processes is not always a simple task. this difficulty becomes more accentuated when the execution control assumes countless business processes. this work presents an alternative to control the execution of business processes. this alternative consists in a library of functions, called navigationplantool, which can be easily integrated into the information systems and uses navigation plan definition language (npdl) as the language to define business processes. npdl is a language for business processes specification that uses process algebra as formal foundation. the navigationplantool implements npdl language as a sql extension and offers two other important services: processes instantiation and process instances execution monitor. the navigationplantool combines the process algebra features with a relational database model to provide a scalable and reliable control in the execution of business processes.
an anomaly intrusion detection method using the csi-knn algorithm. machine learning-based anomaly detection approaches have attracted increasing attention in the network intrusion detection community because of their intrinsic capabilities in discovering novel attacks. however, most of today's anomaly-based idss generate high false positive rates and miss many attacks because of a deficiency in their ability to discriminate attacks from legitimate behaviors. in this paper, we propose an anomaly intrusion detection method using the combined strangeness and isolation measure k-nearest neighbors (csi-knn) algorithm. the intrusion detection algorithm analyzes different characteristics of network data by employing two measures: strangeness and isolation. based on these measures, a correlation unit raises intrusion alerts with associated confidence estimates. multiple csi-knn classifiers work in parallel to deal with different types of network services so that the csi-knn-based nids can work more efficiently than processing all network services together.
analyzing the impact of churn and malicious behavior on the quality of peer-to-peer web search. in an attempt to increase the spectrum of searchable information while attenuating scalability issues, peer-to-peer (p2p) networks have been viewed as an alternative way to design new web search engines. however, the effectiveness of p2p web searching may be severely limited by characteristics commonly observed in real p2p systems such as peer churn and malicious behavioral patterns. this paper analyzes the impact of each such issue on the effectiveness of p2p web searching. in order to estimate boundaries, we focus our analysis on p2p network models with very high and low levels of peer collaboration. our findings reveal that such patterns could strongly affect the effectiveness of p2p web searching. in networks with a high level of peer collaboration, a significant fraction of queries suffer an impact on the quality of search of at least 24% and 26% even in slightly insecure and unstable scenarios. we also confirm that the impact of each such issue in real-world, less collaborative networks can be even more intense (73% and 75%). thus, together with the high autonomy of peers and the absence of file-sharing benefits in replicating documents into the network, we argue that effectiveness of p2p web search engines would strongly depend on new, application-specific reputation and incentive mechanisms.
embedding sparql into xquery/xslt. the tree-based languages xquery and xslt for xml are widely supported. many tools do not yet support the new rdf graph query language sparql. we propose to embed sparql subqueries into xquery/xslt, such that xquery and xslt benefit from the graph query language constructs of sparql, and sparql benefits from features of xquery/xslt, which sparql does not support. the embedding enables xquery/xslt tools to handle at the same time xml queries and sparql subqueries, and xml and rdf data.
doxels in context for retrieval: from structure to neighbours. we propose in this paper a new way of considering retrieval of structured documents, by exploiting non-structural relations between structured document elements (doxels). these relations may be defined by human beings (e.g. by the authors of the documents for navigation or reference purposes), but may also be created by the information retrieval system (e.g. using knn). unlike pagerank or hits that separate features link and content features, we integrate these two aspects by defining a relative specificity and a relative exhaustivity between doxels. we use these features, as well as the doxel content, in a comprehensive matching process. one concern here is to facilitate the exploration of the result space by selecting the relevant doxels, and by indicating potential good neighbours to access from one doxel. results of experiments on the inex2005 test collection are presented.
enhancing web service selection by qos-based ontology and ws-policy. the service oriented architecture enables the development of flexible large scale-applications in open environments by dynamically combining web services. nevertheless, current techniques fail to address the problem of selecting adequate services to meet service consumer needs. service selection must take into account non-functional parameters especially the quality of service (qos). in this work we propose a web service selection approach based on qos attributes. we extend the ws-policy to represent qos policies. we apply ontological concepts to ws-policy in order to enable semantic matching. publishing qos policies is also examined in this work. we propose to extend the uddi register to handle qos-based policies.
a biologically inspired generation of virtual characters. a number of techniques for generating geometric models of human head and body are in use nowadays. models of human characters are useful in computer games, virtual reality, and many other applications. the complexities involved in generating such models, however, impose heavy limitations on the variety of characters produced. in this paper, diploid reproduction is mimicked to produce an unlimited number of character models, which inherit traits from two parent models. the meshes of all models are constructed based on control parameters that are distributed as genes among a group of chromosomes. thus, the technique consists of distributing pre-selected characteristics, represented as control parameters, over a pre-determined number of chromosome pairs for both parents; followed by a simulated generation of the father's and the mother's gametes; which are randomly combined in a simulated fecundation. the diversity is ensured in four random processes: the random exchange of segments during crossover; the random alignment of homologous chromosomes at metaphases i and ii of meiosis; and the random union of male and female gametes during fecundation.
decision-making coordination in collaborative product configuration. in software product lines (spls), product configuration is a decision-making process in which a group of stakeholders choose features for a product. unfortunately, current configuration technology is essentially single-user-based in which user requirements are interpreted and translated into configuration decisions by a single role commonly referred to as the product manager. this process can be error-prone and time-consuming as it commonly requires back-and-forth interactions between the product manager and the stakeholders to cope with decision conflicts. in this paper, we propose an approach to collaborative product configuration (cpc) that aims at providing effective support for coordinating teamwork decision-making in the context of product configuration. the approach builds on well-known concepts in the spl arena such as feature models. the contributions of the paper include the cpc approach and the illustration of its application in a real-world product line.
integrating goal modeling and execution in adaptive complex enterprises. complex enterprises consistently struggle with successfully gaining benefits from enterprise architecture (ea) initiatives for a variety of reasons, one of them being an end-to-end integration between enterprise goals and operations that links goals to the dynamic operations of the organization. in this paper we describe (a) our conceptualization of the adaptive complex enterprise (b) our integrative notation and semantics for goal modeling and linking for such organizations and their operations and (c) an example drawn from an embedded industry project.
track on advances in spatial and image-based information systems (asiis): editorial message. in the past few years, there has been a lot of interest on spatial and image based information systems. these emerging systems and applications raise challenges in spatial data modelling, query processing and optimization and data semantics. they create the need for novel concepts for designing complex geo spatial systems. the acm sac track on advances in spatial and image-based information systems (asiis) is a forum for interdisciplinary discussions and research on various aspects of spatial and image based information systems, focusing on both theoretical research contributions and practical design solutions.
softmon: programmable software monitoring with minimum overhead by helper-threading. in practice, in-house testing is not guaranteed to detect all software errors. a plan for extensive testing is often constrained by resources like cost and time. so, the need for continuous monitoring software programs in production runs is always strong. software monitoring, however, suffers from the performance overhead of the probing techniques. unless the overhead for probing is tolerable, the code inserted for probing is typically cleaned from the released programs. in production runs, programmers can only rely on observable effects produced by the programs to examine problems. in this paper, a prototype tool called softmon is proposed to monitor a computer program with minimum overhead. softmon uses a helper thread to monitor programs on a separate cpu without inserting code in the middle of programs. the body of the helper thread is programmable in a language called mcml. by compiling the mcml script, a helper thread is instrumented into a program automatically and transparently.
knowledge-based semantic clustering. users of the web are increasingly interested in tracking the appearance of new postings rather than locating existing knowledge. coupled with this is the emergence of the web 2.0 movement (where everyone effectively publishes and subscribes), and the concept of the "internet of things". these trends bring into sharp focus the need for efficient distribution of information. however to date there has been few examples of applying ontology-based techniques to achieve this. knowledge-based networking (kbn) involves the forwarding of messages across a network based not just on the contents of the messages but also on the semantics of the associated metadata. in this paper we examine the scalability problems of such a network that would meet the needs of internet-scale semantic-based event feeds. this examination is conducted by evaluating an implemented extension to an existing pub-sub content-based networking (cbn) algorithm to support matching of notification messages to client subscription filters using ontology-based reasoning. we also demonstrate how the clustering of ontologies leads to increased efficiencies in the subscription forwarding tables used, which in turn results in increased scalability of the network.
ontology-based wom extraction service from weblogs. in this paper, we introduce a web-based service that extracts reputations of a product from the internet. if a user inputs the product name, the service first collects articles reviewing the product from weblogs, bbs, and so on. also, it analyzes their contents using metadata and ontologies with conventional nlp techniques. then, it indicates the reputations (positive or negative) from the overall and several pre-defined aspects, and other related products that are the subject of much discussion in the articles. this paper illustrates two technical points regarding use of metadata and ontologies with nlp, and summarizes evaluations in a case that we applied it to a market research for a vehicle.
a generic xml language for characterising objects to support digital preservation. the dominance of digital objects in today's information landscape has changed the way humankind creates and exchanges information. however, it has also brought an entirely new problem: the longevity of digital objects. due to the fast changes in technologies, digital documents have a short lifespan before they become obsolete. digital preservation, i.e. actions to ensure longevity of digital information, thus has become a pressing challenge. different strategies such as migration and emulation have been proposed; however, the decision between available tools for format migration is very complex. preservation planning supports decision makers in reaching accountable decisions by evaluating potential strategies against well-defined requirements. especially the evaluation of different migration tools for digital preservation has to rely on validating the converted objects and thus on an analysis of the logical structure and the content of documents. this paper presents the extensible characterisation languages (xcl) that support the automatic validation of document conversions and the evaluation of migration quality by hierarchically decomposing a document and representing documents from different sources in an abstract xml language. we present the context of the development of these languages and tools and describe the overall concept and features of the languages and how they can be applied to the evaluation of digital preservation solutions.
accessing and aggregating legacy data sources for healthcare research, delivery and training. the aggregation of data from disparate sources offers clear benefits for healthcare researchers and practitioners. such aggregation, however, must satisfy ethical, legal and social requirements: data ownership must be respected; patient privacy must not be compromised; data storage and transfer must be secure; etc. in this paper we describe the query aspects of sif (for service-oriented interoperability framework), a system which has been developed to support healthcare-related applications that depend upon the secure aggregation of data from multiple legacy databases. importantly, the system allows the federation of data stored in varying database management systems utilising varying schemas.
automatic feedback, control-based, stress and load testing. stress and load testing are of special interest to many segments of the software industry. however, existing approaches present limitations with respect to automation and applicability. while some approaches present an automated solution, they lack in terms of applicability. a fully automated approach with high applicability is proposed here. the approach is based on the use of a pid controller to automatically drive the inputs and to achieve a pre-specified level of stress/load for resources of interest. the approach also allows for automatic identification of inputs impacting the resources. an experiment along with multiple simulation runs are presented as an indication of the applicability and accuracy of the proposed approach.
dynamic configuration of application-specific implicit instructions for embedded pipelined processors. in this paper, we propose the dynamic configuration of application specific implicit instructions for pipelined processors to better exploit the available parallelism at instruction level. given the target application, the compiler selects a set of candidate instructions to be implicitly executed - i.e. their execution is controlled through a data-driven model, which avoids explicit instruction fetch. consequently, the clock cycles usually required for the explicit issues are saved, thus improving the performance and reducing the code size. the compiler generates the reconfiguration operations to properly setup the data-path. the processor pipeline has been optimized to support the parallel execution of implicitly issued instructions, requiring a limited hardware overhead. the proposed technique has a negligible impact on the processor isa - only reconfiguration instructions are added - which also benefits the compiler development times, since the optimization can be almost seamlessly added to an existing compilation tool-chain. the proposed approach has been applied to dsp and multimedia kernel loops, comparing its performance with those of two different baseline architectures: a scalar mips processor and a 4-issue vliw processor of the lx family provided by stmicroelectronics [5]. experimental results show a speedup ranging from 10 to 35%, and an average code size reduction of 19%.
umltrust: towards developing trust-aware software. as users in software systems depend on each other for achieving goals, performing tasks, and utilizing resources, the trust relationships in the systems need to be considered to identify the opportunities and vulnerabilities these relationships bring. however, the problem with specifying a trust relationship is that there is no precise and a priori criteria to be satisfied. the main objective of this work is towards incorporating trust from the very beginning of a software development process. a framework is presented for specifying trust scenarios using an extension of unified modeling language (uml) called umltrust (uml for trust scenarios). a trust scenario combines interested parties based on a context and thus helps in building a trust relationship. suitable trust rules can be generated from the trust scenarios to monitor the trustworthiness of specific trust relationships. in this way, we can avoid conflicting, ambiguous, and redundant trust requirements in a software development life cycle (sdlc). the applicability of the approach has been illustrated using examples from file sharing applications.
synchronization of strongly pulse-coupled oscillators with refractory periods and random medium access. the weakly pulse-coupled oscillator framework has proven to be a valuable resource for the development of peer-to-peer synchronization algorithms [9]. but leveraging it in a practical implementation (e.g. in wireless ad hoc/sensor networks) is problematic due to the difficulty in achieving precise coordination of broadcast messages. we found that a pseudo-random medium access control (mac) protocol produces a super-linear increase in the number of messages required per node with increasing network size, which would normally discourage its use. however, introducing a "refractory period" reduces this growth to linear with a small constant (verified by numerical simulations). furthermore, the refractory period allows for an increase in the coupling constant, effectively making the network "strongly" pulse-coupled. we show that the combination of the refractory period, strong coupling, and probabilistic medium access results in a significant decrease in the average number of messages required per node in several practical network topologies (and as much as ~ 90% over the original idealistic mechanism in line topologies).
a pattern to design crosscutting frameworks. a pattern that can be used to design aspect-oriented frameworks that require data from a base code is presented. the framework design is explicitly separated into two parts when this pattern is used: one dealing with the composition mechanisms and another dealing with the functional variabilities. regarding the composition part, there are several com alternatives facilitating the coupling to an existing base code as well as increasing the reuse levels. the functional part can be designed using classical object oriented patterns. the reuse process of the framework is also facilitated because the application and domain engineer can deal with both composition and functional parts separately.
pattern ranking for semi-automatic ontology construction. when developing semantic applications, the construction of ontologies is a crucial part. we are developing a semiautomatic ontology construction approach, ontocase, relying on ontology patterns as additional resources. a crucial part of this approach is how to select the appropriate patterns based on the input representation extracted from a text corpus. in this paper, we suggest a pattern ranking and selection approach with the ability to partially bridge the gap between abstract patterns and specific terms, as well as being specifically tuned to the characteristics of ontology patterns. compared to existing ontology ranking schemes our approach adds indirect matching of terms as well as relation matching. an initial experiment indicates that ontocase ranking performs better, especially when ranking small and abstract patterns, than existing ranking approaches.
encephalic nmr image analysis by textural interpretation. the novel technologies used in different application domains allow to obtain digital images with a high complex informative content. these meaningful information are expressed by textural skin that covers the objects represented inside the images. the textural information can be exploited to interpret the semantic meaning of the images themselves. this paper provides a mathematical characterization, based on texture analysis, of the basic objects contained in the layout of the nmr encephalic images (cerebral tissue, rest of skull, eventual abnormal mass, and background). by this characterization a prototype has been developed, which has allowed the achievement of three different targets: segmentation of the image layout in basic objects, identification of the eventual abnormal masses, characterization of the morphologic structures of the cerebral tissue.
the tale of the weather worm. how humans behave when faced with a disaster, natural or man-made, can be exploited automatically by news-aware malicious software. we introduce weather worms, worms that can automatically identify abnormal events and their location, and target computers at that physical location. such worms could be used to take advantage of poorly-defended computers in a disaster zone, and could amplify the effects of a physical attack. defenses against weather worms require examination of policy and presentation of information on the internet.
model and infrastructure for decentralized workflow enactment. today, enactment of web service flows -- the process of evaluating control flow and executing activities a workflow is composed of -- is typically done by a centralized workflow enactment service as part of a workflow management system. this exhibits a number of drawbacks with regard to process adaptability and process fragmentation among a number of participating partners. in order to overcome the deficiencies of centralized process navigation, we propose a model for flexible and adaptable distributed processes as orchestrations of a set of self-coordinating components, without the need for central coordination. furthermore, we provide key characteristics and an architecture for the development of a supporting infrastructure that facilitates both, deployment and management of distributed components as well as decentralized workflow enactment.
pentagons: a weakly relational abstract domain for the efficient validation of array accesses. we introduce pentagons (pntg), a weakly relational numerical abstract domain useful for the validation of array accesses in byte-code and intermediate languages (il). this abstract domain captures properties of the form of x &epsilon; [a, b]&and;x < y. it is more precise than the well known interval domain, but it is less precise than the octagon domain. the goal of pntg is to be a lightweight numerical domain useful for adaptive static analysis, where pntg is used to quickly prove the safety of most array accesses, restricting the use of more precise (but also more expensive) domains to only a small fraction of the code. we implemented the pntg abstract domain in clousot, a generic abstract interpreter for .net assemblies. using it, we were able to validate 83% of array accesses in the core runtime library mscorlib.dll in less than 8 minutes.
a formal architectural model for exception handling coordination. architectures based on coordinated atomic action (ca action) concepts have been used to build concurrent fault-tolerant systems. this conceptual model combines concurrent exception handling with action nesting to provide a general mechanism for both enclosing interactions among system components and coordinating forward error recovery measures. this paper proposes an architectural model to guide the formal specification of concurrent fault-tolerant systems. this architecture provides built-in csp (communicating sequential process) processes and predefined channels to coordinate exception handling of the user-defined components. as a result, a formal and general architecture supporting software fault-tolerance are ready to be used.
towards a model-driven engineering approach for developing embedded hard real-time software. model-driven engineering (mde) has been advocated as an effective way to deal with today's software complexity. mde can be seen as an integrative approach combining existing techniques such as domain-specific modeling languages (dsml) and transformation engines. this paper presents the ezrealtime, an mde-based tool that relies on the time petri net (tpn) formalism and defines a dsml to provide an easy-to-use environment for specifying embedded hard real-time (ehrt) system and for synthesizing timely and predictable scheduled c code. the ezrealtime adopts the universal xml-based transfer syntax for petri nets, named as pnml. the main idea of this work is to propose a generative programming method and tool to boost code quality and improve developer productivity with automated software synthesis. the ezrealtime tool reads and automatically translates the specification to a time petri net model through composition of building blocks with the purpose of providing a complete model of all tasks in the system. therefore, this model is used to find a feasible schedule by applying a depth-first search algorithm. finally, the scheduled code is generated by traversing the feasible schedule, and replacing transition's instances by the respective code segments. we also present the application of the proposed method in a case study.
aggregate similarity queries in relevance feedback methods for content-based image retrieval. content-based image retrieval techniques rely on automatic features extracted from images to process similarity queries. usually low-level features are extracted, and when they are used to compare images stored in a database to a reference image (through single center selection queries), they often lack the ability to convey to the users what they understand as similarity. to deal with the gap between what the user expects and what the system can automatically provide, relevance feedback techniques have been employed. in this paper we present a generalization of the single center similarity queries over data in metric spaces, taking into account both range and k-nearest neighbors. allowing a query to include multiple query centers, it straightforwardly attends the relevance feedback requirements. thus, we analyze how well our new approach contribute to relevance feedback methods for content-based image retrieval.
surework: a super-peer reputation framework for p2p networks. reputation systems are proved mechanisms used to help nodes to decide whom to trust, to maintain the overall credibility of the system and to promote collaboration. this paper presents surework, a reputation framework based on super-peers. in surework, peers form clusters around super-reputation-peers (sure-peers) who help to increase the reputation knowledge. surework introduces incentives in order to promote that nodes with higher capabilities become super-peers and assume more tasks than normal peers. reciprocity is also promoted by encouraging peers to provide better services to most reputable client peers.
an intelligent editor for multi-presentation user interfaces. in ubiquitous computing, interactive applications are shipped with different variations of its user interface depending on the constraints imposed by the context in which they are running, such as the user, the computing platform and environment. a multi-presentation user interface is composed of a series of interconnected user interfaces for the same task to be carried out in different contexts of use. when access to software applications must be guaranteed in more than one context of use, it is necessary to automatically adapt the interface in order to preserve their usability when context switching occurs, for instance, a switch from a desktop to a pocket computer. to achieve this goal, this paper proposes a model and a visualization technique to express and manipulate the plasticity domains of a multi-presentation user interface. the plasticity domain denotes the set of contexts of use it is able to cover while preserving its usability. this paper focuses primarily on one aspect of the context of use: the computing platform and its screen size: when the dimensions of a graphical user interface change, the multi-presentation interface automatically switches to the presentation which is the most adapted to this screen. the model supports the definition of this plasticity domain in terms of window size and location. the visualization technique helps in both making observable the set of presentations that fit the available space, and perceiving which operations could help in switching from one presentation to another one. the model has been integrated into a user interface description language and is supported by an intelligent editor, because it infers from plasticity domains all the constraints and conditions required for context switching.
towards the generation of explanations for semantic web services in owl-s. in this article we define a system, called xplains that automatically generates an infrastructure for providing explanations of semantic web services described in owl-s. xplains has a strategy for generating production rules from a flow where several levels of distribution of the services exist.
continuous k-dominant skyline computation on multidimensional data streams. skyline queries are important due to their usefulness in many application domains. however, by increasing the number of attributes, the probability that a tuple dominates another one is reduced significantly. to attack this problem, k-dominant skylines have been proposed, relaxing the definition of domination. in this paper, we study the problem of continuous monitoring of k-dominant skylines, where multiple queries are running concurrently. the proposed method divides the space in pairs of attributes. for each pair, we compute skyline tuples and we exploit them to eliminate candidates tuples of the queries and we combine the partial results. the proposed scheme uses only simple domination checks and it is applicable to the streaming case as well as to ad-hoc insertions and deletions. experiments, based on different data distributions, show the efficiency of the proposed scheme in comparison to existing methods.
computing h/d-exchange speeds of single residues from data of peptic fragments. determining the hydrogen-deuterium exchange speeds of single residues from data for peptic fragments obtained by ft-ics ms is currently mainly done by manual interpretation. we provide an automated method based on combinatorial optimization. more precisely, we present an algorithm that enumerates all possible exchange speeds for single residues that explain the observed data of the peptic fragments.
multi-level biomedical ontology-enabled service broker for web-based interoperation. web services have recently become a new trend for gathering biomedical information. however, it is not easy to integrate and obtain a concise/complete query result among hundreds of services. in this paper, we propose a multi-level ontology-enabled service broker architecture for dynamically integrating web services in the biomedical domain. by incorporating temporal concept, new enhanced qos parameters allow service requesters to control more querying factors in order to precisely invoke corresponding service operations. we also define a unified biomedical service interface (ubsi) as a service deployment standard. our ultimate goal is to construct a public, scalable, and interoperable biomedical service platform based on ubsi to benefit scientists in data searching and publishing.
on the performance of tcp, udp and dccp over 802.11 g networks. this paper presents an experimental study of streaming multimedia packets using dccp transport protocol over 802.11 g networks. our main focus is to study the behavior of dccp flows over real-time multimedia applications. the approach taken was to use dccp flows in the presence of tcp and udp flows, then analyze the behavior of each protocol, mainly in regards to the congestion control algorithms of both protocols. furthermore, we also considered end-points mobility requirements, such as hand-off between multiples access points. needless to say, the dccp protocol was recently standardized by ietf as an alternative for streaming multimedia flows on computer networks. the results presented in this paper show that tcp and dccp protocols can share the network bandwidth without affecting each other. on the other hand, udp flows can aggressively degrade tcp and dccp flows due to the absence of any kind of flow control. although udp flows reach high bandwidth throughput, it loses a considerable amount of data taking into account limited bandwidth channels, such as 802.11g networks. finally, this work also shows that tcp and dccp can think of loss of packets as network congestion while experimenting hand-offs, thus decreasing their throughput.
adaptive data anonymization against information fusion based privacy attacks on enterprise data. privacy preservation is currently one of the key challenges in enterprise data management. data anonymization techniques address this by sanitizing and releasing anonymized data such that enterprises can share and disseminate sensitive information without compromising consumer privacy. however, current anonymization techniques are prone to attacks where-in an intruder can fuse external information with the anonymized data to infer sensitive information. in this paper, we pose and formulate the problem of information fusion based privacy attack. we experimentally demonstrate such an attack on a publicly available data set. we propose adaptive anonymization schemes to address this problem and experimentally demonstrate a prototype solution.
elements for a modular dynamic geometry system. dynamic geometry systems are tools for geomotric visualization. they allow the user to define geometric elements, establish relationships between them and explore the dynamic behavior of the remaining geometric elements when one of them is moved. in this work we propose a modular architecture for dynamic geometry systems built upon a set of functional units which will allow to apply some well known results from the geometric constraint solving field.
kernel-mode scheduling server for cpu partitioning: a case study using the windows research kernel. the ability to partition available computing power lays the foundation for predictable computing in different domains (e.g. multimedia applications or virtual machine execution). fine-grained computing power control can be used to implement applications which adapt themselves to changing performance requirements. the scheduling server concept can be used for implementing fine-grained cpu partitioning. in the past, several user-mode implementations of this idea were realized without any kernel modification. this paper describes a kernel-mode implementation and compares two different design alternatives. experiences of using the windows research kernel (wrk) for experiments with the scheduler are given. furthermore, benchmark results and possible applications are described.
using annotations in the naked objects framework to explore data requirements. the creation of conceptual data design that appropriately represents specific application domain is one of the main challenges in requirements engineering. an initiative to help designers is the naked objects framework, where it is possible to interact with conceptual model in a limited way. the interactions are restricted to entity creations and single object-relations. we created an extension of the naked objects framework using annotations to allow manipulation of higher level abstractions as specialization and object-relationship. these abstractions allow better interactions between the domain specialist and designers. the use of our approach to explore and validate data requirements has several benefits: 1) it reduces conceptual specification problems (like poorly data requirements identification); 2) it narrows the distance among domain and design specialists; 3) it allows the simultaneous exploration of the conceptual data design and the system requirements.
formal specification of dsp gateway for data transmission between processor cores of omap platform. in this article, formal models for the data transmission mechanism between arm and dsp cores of omap platform 161x via dsp gateway are presented. these models are represented as timed automata. the automata for the behavior of tasks running in the dsp when receiving requests of read or write operations from arm are described. data transmission between arm and dsp is modelled according to the mechanism offered by toklibios, the system kernel at dsp side. the formal model presented in this work helps developers to understand the communication mechanisms of dsp gateway and facilitates its usage and future development.
assessing the best integration between distance-function and image-feature to answer similarity queries. the retrieval of multimedia data relies on a feature extractor to provide the intrinsic characteristics (features) from the data, and a measure to quantify the similarity between them. a challenge in multimedia database systems is how to best integrate these two key aspects in order to improve the quality of the retrieved selection when answering similarity queries. in this paper, we analyze and compare a set of distance functions and feature extractors with regard to the association and dependencies among them. the results show that the most widely used and well-known distance functions, such as the euclidean distance, do not reach a desirable similarity assessment, and reveal that a careful choice of a distance function considerably improves the retrieval of multimedia data, which in our experiments reached up to 92%.
whom should i trust?: the impact of key figures on cold start recommendations. generating adequate recommendations for newcomers is a hard problem for a recommender system (rs) due to lack of detailed user profiles and social preference data. empirical evidence suggests that the incorporation of a trust network among the users of the rs can leverage such 'cold start' (cs) recommendations. hence, new users should be encouraged to connect to the network as soon as possible. but whom should new users connect to? given the impact this choice has on the delivered recommendations, it is critical to guide newcomers through this early stage connection process. in this paper, we identify key figures in the trust network (in particular mavens, connectors and frequent raters) and investigate their influence on the coverage and accuracy of a collaborative filtering rs. using a dataset from epinions.com, we demonstrate that the generated recommendations for new user are more beneficial if they connect to an identified key figure compared to a random user.
a nervous system model for direct dynamics animation control based on evolutionary computation. in this paper, we approach the relevant problem of controlling locomotion of articulated figures taking physics into account. the model proposed in this work determines the forces that actuate the articulated figure in order to obtain a desired locomotion goal. the controller developed for that purpose is based on some of the works on control of neuro-musculoskeletal representations of articulated figures and on neural oscillators encountered in the literature. our model, however, takes a more generic approach using evolutionary computation and is capable of automatically generating motion gaits while maintaining stability independently of the environment and of the controlled articulated figure. the limitations of the proposed controller are also discussed.
computational approach to biological validation of protein-protein interactions discovered using literature mining. in this paper we describe a computational technique to validate protein-protein interactions discovered using biomap, a literature mining system. two experiments were carried out to validate the interactions pairs. in this study, we used a total of 32,693 documents with 193,738 sentences related to multiple sclerosis from the medline literature database. from these sentences, biomap found 1004 explicit and 15,000 implicit protein interaction pairs of which 271 explicit and 16 implicit interactions were validated using the proposed techniques. these results indicate that the proposed methods can be effectively used for biological verification of protein-protein interactions that are obtained through literature mining.
elaboration of use case specifications: an approach based on use case fragments. use case description has gained a wide acceptance among the many techniques available for information systems requirements specification. however, piecing up all the details required for the production of a high quality use case can be a daunting task, especially for students and novice requirements professionals. this paper presents an approach aiming at reducing the time required for the elaboration of high quality use case specifications. the basis of the approach is to write a use case text using the composition of set of pre-defined fragments, where each fragment represents a recurring set of interactions required to achieve a sub-goal. each fragment can then be customized to meet use case goals. since each fragment is coded using the best practices for writing use case steps, both the fragment text and the final use case text will be well composed. we believe that this approach will allow novice requirements professional to write high quality use cases in less time than it would be necessary using the other approaches. our experience on writing use cases for business information systems using a catalogue of use case fragments suggested that they can be a facilitator in several aspects, not only improving the writing speed, but also leading to standardization and concision of use case specifications.
making colors worth more than a thousand words. content-based image retrieval (cbir) is a challenging task. common techniques use only low-level features. however, these solutions can lead to the so-called 'semantic gap' problem: images with high feature similarities may be different in terms of user perception. in this paper, our objective is to retrieve images based on color cues which may present some affine transformations. for that, we present csir: a new method for comparing images based on discrete distributions of distinctive color and scale image regions. we validate the technique using images with a large range of viewpoints, partial occlusion, changes in illumination, and various domains.
cat: a context-aware trust model for open and dynamic systems. the requirements for spontaneous interactions in open and dynamic systems create security issues and necessitate the incorporation of trust management into each software entity to make decisions. trust encompasses various quality attributes (e.g., security, competence, honesty) and helps in making appropriate decisions. in this paper, we present cat, an interaction-based context-aware trust model for open and dynamic systems by considering services as contexts. we identify a number of trust properties including context and risk awareness and address those in the proposed model. a context-similarity parameter is proposed to make decisions in similar situations. a time-based ageing parameter is introduced to change trust values over time without any further interaction. we present direct and indirect recommendations and apply path-based ageing on indirect recommendations. a mechanism to calculate the accuracy of recommendations is described. this accuracy is used to differentiate between reliable and unreliable recommendations in the total trust calculation.
exploring social annotations for web document classification. social annotation via so-called collaborative tagging describes the process by which many users add metadata in the form of unstructured keywords to shared content. in this paper, we explore and study social annotations and tagging with regard to their usefulness for web document classification by an analysis of large sets of real-world data. we are interested in finding out which kinds of documents are annotated more by end users than others, how users tend to annotate these documents, and in particular how this user-generated folk-sonomy compares with a top-down taxonomy maintained by classification experts for the same set of documents. we describe what can be deduced from the results for further research and development in the areas of document classification and information retrieval.
interoperability testing of a manet routing protocol using a node self-similarity approach. interoperability testing for ad hoc routing protocols is crucial to the reliability of wireless mobile ad hoc networks. nevertheless, most of the works in this area are devoted to simulations analyzing the performance of such protocols without taking into account their formal requirements and specifications. our works deal with formal methods to test the interoperability of a manet routing protocol, dsr. from previous works, many inconclusive verdicts were obtained on some test cases. we present therefore in this paper, a node self-similarity approach in order to improve the interoperability testing by reducing the number of these in conclusive verdicts.
a reliable b-tree implementation over flash memory. flash memory has been widely used in various embedded computing systems and portable devices in recent years because of its small size, shock-resistance, low-power consumption and non-volatile properties. to hide the disadvantages of flash memory such as out-of-place update, a flash translation layer (ftl) is usually used for providing transparent block-device emulation. but when index structures are implemented over ftl, intensive overwrite operations caused by record inserting, deleting, modifying and index reorganizing could not only degrade the performance significantly but also reduce the life of flash memory. to address the problem, bftl and ibsf are proposed. however, neither of them could avoid the loss of records and incompatibilities when system crash occurs. in this paper, a reliable b-tree implementation called rbftl is presented for flash-memory storage systems. it is placed between the application layer and ftl. rbftl could minimize the loss of data and eliminate incompatibilities effectively and efficiently when system crashes. the experimental results also show that rbftl yields a better performance than ftl.
partnering structure definition for networked businesses. rapidly changing market demands and increasing competitive pressure cause many businesses decide to collaborate with other businesses, forming what we call a 'networked business'. for the participants in a networked business to be able to promptly react to their customers' needs, they must set up as cornerstone a well-defined collaborative partnering structure. in this paper we discuss the partnering structure of networked businesses and present a framework for its formalization. using an example, we illustrate that existing approaches for value modeling, roles specification, and responsibilities definition can be used successfully if employed in a unifying way to address this structure concept.
flash memory management based on predicted data expiry-time in embedded real-time systems. flash memory based embedded systems are becoming increasingly prevalent. garbage collection mechanism is a critical issue in these systems, especially in embedded real-time systems. therefore, in this article, we discuss the influence of the capacity utilization (percentage of fullness) of the flash memory on allocating and recycling, and propose a new flash memory management technique, namely petfm. the proposed technique improves the performance of garbage collection mechanism by allocating free pages from different allocated-blocks for data to be updated, based on their predicted expiry-time. the analytical and experimental results show that garbage collection of petfm is more efficient and effective under high capacity utilization in embedded real-time systems.
knowledge-free discovery of domain-specific multiword units. the discovery of multiword units is one of the key steps in the preprocessing of raw text. in this paper, we propose a know ledge-free approach for the discovery on such entities- it does not only outperform state-of-the-art approaches, but is also fully unsupervised. furthermore, it does not demand the setting of any threshold, making it appropriate for usage by non-experts. the approach proposed is evaluated against five other metrics on a medical corpus.
visualization of rule-based programming. in this paper, we present the rule-maker system, which is a visualization approach of rule-based programming. compared to traditional rule-based programming, rule-maker provides an intuitive graphical interface to reduce programming effort and help developers focus on rule structure rather than rule syntax. programmers can implement graphical modules of algorithms. by connecting with lrr (laboratory for rapid rewriting), the visualization approach hides the computation detail information from the developer.
using traditional loop unrolling to fit application on a new hybrid reconfigurable architecture. this paper presents a strategy to modify a sequential implementation of an h.264/avc motion estimation to run on a new reconfigurable architecture called rosa. the modifications aim to provide more parallelism that will be exploited by the architecture. in the strategy presented in this paper we used traditional loop unrolling and profile information as techniques to modify the application and to generate a best fit solution to rosa architecture.
performance comparison of flow aware networking (fan) architectures under gridftp traffic. grid networks are large distributed systems that share and virtualize heterogeneous resources. quality of service (qos) is a key and complex issue for grid services provisioning. currently, most grid networks offer best-effort (be) services. thus, qos architectures initially developed for internet such as diffserv (ds) have been adapted to grid environment. since the widespread of internet, many grid networks will be deployed in the years to come over this technology. in this paper, we propose to compare two flow-aware networking (fan) architectures, mainly from the second generation (2gfan). the purpose is to answer the question of which 2gfan architecture performs better under grid traffic. fan is a promising option to ds for qos provisioning in internet networks. ds provides qos differentiation through explicit packet marking and classification whereas fan consist on per-flow admission control and implicit flow differentiation through priority fair queuing. the main difference between the two 2gfan architectures is the fair queuing algorithm. thus; to the knowledge of the authors, this is the first time two priority per-flow fair queuing algorithms are compared under grid traffic. a gridftp session may be seen as a succession of parallel tcp flows with large volumes of data transfers. metrics used are average delay, average goodput and the average rejection rate.
an approach based on metrics for monitoring web accessibility in brazilian municipalities web sites. monitoring and measuring the accessibility of government web sites is an important challenge for regulators and policy makers. moreover, over the next few years, e-government (e-gov) services are expected to expand and it is necessary to ensure access for everyone. in this paper, we present a metric based approach for evaluating municipalities web pages using automatic accessibility evaluation tools. the sampling of the pages was done by the tool e-govmeter, and the accessibility evaluation and generation of the metrics was done by means of an adaptation of the tool hera. the results show that much work should be done to improve the accessibility of brazilian municipalities web sites. although it has limitations, the use of automatically generated accessibility metrics is a powerful tool for helping measuring and monitoring the accessibility of e-gov web sites.
pathological voice discrimination based on entropy measurements. digital signal processing techniques have been used to analyze vocal disorders caused by laryngeal pathologies. laryngoscopical exams commonly used for detection of these diseases are invasive methods that cause discomfort to the patients. because of its noninvasive nature, acoustical analysis of the temporal and spectral features of the voice signal can be used as an auxiliary technique in laringoscopical exams. this analysis may be applied for detection of vocal diseases and the evaluation of the vocal quality of patients subjected to surgical processes or medical treatments in the vocal folds. this work aims at investigating the behavior of entropy measures in disordered voices influenced by the presence of pathologies in the vocal folds. for this purpose, the shannon entropy and the relative entropy are implemented, and their behavior for normal and pathological voices affected by vocal fold edemas is observed. the measurement of the entropy efficiency in discriminating between normal and pathological voices is obtained.
flexible pointer analysis using assign-fetch graphs. we propose a new abstraction for pointer analysis that represents reads and writes to memory instead of traditional points-to relations. compared to points-to graphs, our assign-fetch graph (afg) leads to concise procedure summaries that can be used in any calling context. also, its flexibility supports new analysis techniques with different trade-offs between speed and precision. for efficiency, we build a summary for each procedure that assumes distinct pointers from the environment are not aliased and restore soundness when the summary is used in a context with aliases. we present two pointer analysis techniques based on our afg. the first takes the flow-insensitive view adopted by many authors; the second considers statement ordering. in addition to being more precise, we find that this "flow-aware" analysis runs faster. we conclude with experimental results showing it is practical.
inkteractors: interacting with digital ink. digital inking systems accept pen-based input from the user, process and archive the resulting data as digital ink. however, the reviewing techniques currently available for such systems are limited. in this paper we formalize operators that model the user interaction during digital ink capture. such operators can be applied in situations where it is important to have a customized view of the inking activity. we describe the implementation of a player that allows the user, by selecting the desired operators, to interact with digitally annotated documents while reviewing them.
medical image analysis using mobile devices. mobile devices are increasingly being incorporated onto picture archiving and communication systems (pacs). previous work on medical image access using mobile devices essentially focuses on enabling the visualization of the medical images at the mobile devices. in contrast, we propose and develop a distributed system that allows medical image analysis using mobile devices. as a proof-of-concept, based on our distributed system, we develop a tool for dental implant simulation using mobile devices. we also discuss the perspectives of extending the current system to incorporate computer aided diagnosis (cad) algorithms in it.
tips: wrapping the sockets api for seamless ip mobility. tips (transparent ip sockets) is a wrapping implementation of specific functions of the bsd sockets api to provide support for transparent ip mobility at the application level. implemented on top of the transport layer it allows udp and tcp communications to be immune to both client and server terminal migration (single and double jump). location independent identification, and lossless data transmissions are provided with reduced overhead. the use of a distributed hash table for keeping terminal location information also allows for scalable operation.
on filtering irrelevant results in peer-to-peer search. to improve peer-to-peer (p2p) search accuracy, we identify multiword entities in user queries using an entity corpus constructed based on n-gram statistics collected from limewire users. we show that by using a statistical function, we can build a reliable corpus and successfully parse each user query to its correct entities. our hypothesis: with entity matching, overall precision can be significantly improved, while only slightly decreasing recall.
a framework for performance evaluation and functional verification in stochastic process algebras. despite its relatively short history, a wealth of formalisms exist for algebraic specification of stochastic systems. the goal of this paper is to give such formalisms a unifying framework for performance evaluation and functional verification. to this end, we propose an approach enabling a provably sound transformation from some existing stochastic process algebras, e.g., pepa and mtipp, to a generic form in the mcrl2 language. this way, we resolve the semantic differences among different stochastic process algebras themselves, on one hand, and between stochastic process algebras and classic ones, such as mcrl2, on the other hand. from the generic form, one can generate a state space and perform various functional and performance-related analyses, as we illustrate in this paper.
scenario oriented program slicing. slicing is an important decomposition technique for program understanding. however, traditional slicing methods tend to produce too large slices for human inspection as modern programs are often huge and static program analyses are hard to be precise enough. one possible solution to such problem could be combining other program decomposition techniques together with program slicing. with such inspiration, this paper proposes a scenario oriented program slicing method to slice programs under specified execution scenarios. the scenarios provide a clear and easy understanding functional decomposition for the system, while the new slicing method can help figure out how a computation is implemented in a given scenario by effectively reducing the amount of code that a user needs to inspect.
the impact of term selection in genre-aware focused crawling. the genre-aware approach to focused crawling aims at crawling pages related to specific topics that can be expressed in terms of both genre and content information. such an approach requires an expert to specify a set of terms that describe the genre and the content of the pages of interest. in this paper, we analyze the impact of term selection on this approach. thus, we have performed an experimental study in which we vary the number of genre and content terms used in focused crawling processes aimed at crawling pages related to syllabi (genre) of computer science courses (subject) and sale offers (genre) of computer equipments (subject). this experimental study showed that a small set of terms selected by an expert is usually enough to produce good results. in addition, we propose and experimentally evaluate a strategy for semi-automatic generation of terms to be used in such an approach. the results of these experiments showed that such a strategy is very effective and provides a means to assist an expert in the task of specifying the sets of required terms.
special track on programming languages: editorial message. the programming languages (pl) track provides researchers and practitioners with a forum to present their ideas and experience in designing new programming concepts and implementing programming languages. it includes the topics of compiling techniques, domain-specific languages, formal semantics and syntax, garbage collection, language design and implementation, languages for modeling, model-driven development and model transformation, new programming language ideas and concepts, new programming paradigms, practical experiences with programming languages, program analysis and verification, program generation and transformation, programming languages from all paradigms (agent-oriented, aspect-oriented, functional, logic, object-oriented, etc.), and visual programming languages.
dependence graphs for verifications of web service compositions with pews. pews is an interface description language for both individual and composed web services. we propose an approach for verifying pews compositions which exploits dependence graphs (equivalent to trace systems). the introduction of a synchronization based on dependence graphs allows more efficient algorithms for testing composition properties.
the qos-mo ontology for semantic qos modeling. this paper presents the qos-mo ontology. this ontology enables the specification of qos requirements for semantic web services and can easily be combined with owl-s in order to fully describe web services. the qos specifications created using the qos-mo ontology may be employed on the design and development of web services and on the publication and discovery of web services on the semantic web.
selecting beam directions in radiotherapy with an evolutionary algorithm. radiotherapy treatment planning aims at delivering high doses in the target volume while taking care to do not overdose other organs at risk. thus, it is an important issue to design a process for finding out ideal balances between those contradictory goals. in this paper a multi-objective programming model and a transgenetic algorithm are proposed for the 3d conformal radiotherapy treatment design. the algorithm is compared with a multi-objective genetic algorithm. results of a computational experiment are reported for four real cases.
supporting multimedia capture in mobile computing environments through a peer-to-peer platform. we present a p2p-based multimedia ubiquitous capture platform tailored to support co-located collaborative work.
compressing electrocardiogram signals using parameterized wavelets. a compression method, based on the choice of a wavelet that matches the electrocardiogram signal to be compressed, is proposed in this paper. the scaling filter that minimizes the distortion of the compressed signal are used to determine the wavelet. the scaling filter is used to generate the coefficients of projection of the ecg signal in the scaling and wavelet subspaces, and only the most significant coefficients are retained. coding methods are applied to the retained coefficients in order to improve the compression.
privacy-preserving link discovery. link discovery is a process of identifying association(s) among different entities included in a complex network structure. these association(s) may represent any interaction among entities, for example between people or even bank accounts. the need for link discovery arises in many applications including law enforcement, counter-terrorism, social network analysis, intrusion detection, and fraud detection. given the sensitive nature of information that can be revealed from link discovery, privacy is a major concern from the perspective of both individuals and organizations. for example in the context of financial fraud detection, linking transaction may reveal sensitive information about other individuals not involved in any fraud. in this paper, we propose an approach for link discovery in a privacy-preserving manner. we show how the problem can be reduced to finding the transitive closure of a graph. a secure split-matrix multiplication protocol based on secure scalar product computations is proposed to find the transitive closure. we analyze the performance and usability of the proposed approach.
a language-independent, open-vocabulary system based on hmms for recognition of ultra low resolution words. in this paper, we introduce and evaluate a system capable of recognizing ultra low resolution words extracted from images such as those frequently embedded on web pages. the design of the system has been driven by the following constraints. first, the system has to recognize small font sizes where antialiasing and resampling procedures have been applied. such procedures add noise on the patterns and complicate any a priori segmentation of the characters. second, the system has to be able to recognize any words in an open vocabulary setting, potentially mixing different languages. finally, the training procedure must be automatic, i.e. without requesting to extract, segment and label manually a large set of data. these constraints led us to an architecture based on ergodic hmms where states are associated to the characters. we also introduce several improvements of the performance increasing the order of the emission probability estimators and including minimum and maximum duration constraints on the character models. the proposed system is evaluated on different font sizes and families, showing good robustness for sizes down to 6 points.
st-guide: a framework for the implementation of automatic clinical guidelines. this paper presents st-guide, a state/transition approach to the representation of computer interpretable clinical guidelines for primary and secondary care. details of the representation language, which is based on finite state machines, and the execution model are presented. we claim that because it is geared towards primary care clinical guidelines, specially for chronic diseases, the representation language is simpler than general guideline representation languages that have been proposed in the literature. guidelines for tuberculosis, hepatitis c, hypertension, and the treatment of germ cell cancer in children were implemented in st-guide.
enterprise architecture governance: the need for a business-to-it approach. the importance of enterprise architecture is not only understood in corporate is/it departments. the numerous usage potentials for corporate planning as well as for compliance management, business continuity management, risk management etc. are successively discovered by the business side. in order to provide an aligned support instrument for is/it departments as well as business units and the corporate center, enterprise architecture management has to be anchored in is/it as well as in business. clear and effective governance is required to assure consistency and timeliness of enterprise architecture process outputs. based on a business-to-it approach to enterprise architecture, governance practices in industry are analyzed, and initial findings are consolidated which contribute to design requirements for effective enterprise architecture governance.
a pattern-driven security process for soa applications. soa enables the design of flexible and modular software applications that can be used in a crossorganization context. unfortunately, those qualities have a negative impact on the security of the software application. in this paper, we investigate the production of secure soa applications. in particular, we provide an approach to build secure soa applications that takes into account the new security issues introduced by the complexity of soa-based applications. we build upon two different approaches to secure soa applications: model-driven development and the use of security patterns.
an inference system for detecting firewall filtering rules anomalies. firewalls are crucial equipments for protecting private networks. however by only deploying firewalls, administrators are far from securing their enterprises networks. bad configurations may cause serious security breaches and network vulnerabilities. in particular, conflicting filtering rules lead to block legitimate traffic or to accept unwanted packets. we present in this paper a new classification method to detect overlaps between packet filters within one firewall. our method processes a set of filtering rules that have a variable number of fields. a field has a range of values, represented by an interval or a variable length bit string, that may intersect with the corresponding field ranges of other rules. in order to detect overlaps we organize the conditions of each filtering rule in such a way that we can quickly separate non overlapping rules. this strategy allows us to avoid considering the entire rule header in many cases.
replica identification using genetic programming. identifying and handling replicas are important to guarantee the quality of the information made available by modern data storage services. there has been a large investment from companies and governments in the development of effective methods for removing replicas from large databases. typically, this investment has produced significant results, since cleaned replica-free databases not only allow the retrieval of higher-quality information but also lead to a more concise data representation and to potential savings in computational time and resources to process and maintaining this data. in this paper, we propose a gp-based approach to automatic replica identification that combines evidence based on the data content in order to find a similarity function that is able to identify whether two entries in a repository are replicas or not. as shown by our experiments, our approach outperforms an svm-based method used as baseline by at least 6.5%. moreover, the suggested functions are computationally less demanding since they use fewer evidence. in addition, our approach is capable to automatically adapt to any given replica identification boundary.
brain registration and subtraction - improved localization for spect analysis (b.r.a.s.i.l.): a computer-aided diagnosis in epilepsy tool kit. surgery is an important option in the treatment of patients with medically intractable epilepsy. traditional techniques for the localization of the epileptogenic zone (ez), e.g. surface electroencephalography (eeg) and magnetic resonance (mr) imaging, allow accurate localization in a significant number of epileptic patients. besides, in many situations, the single photon emission computed tomography (spect) images have played a very important role in ez localization. however, the identification of the ez based on the visual interpretation side-by-side of the ictal and periictal images is in general a difficult task. to improve spect analysis, computational techniques have been developed focusing on the registration and fusion of ictal and periictal spect images. the combination of image registration and subtraction of spect images can improve the selective detection of brain regions with functional activation during epileptic seizures. the proposed methodology shown high sensitivity to detect hyperperfusion higher than 10%, in this article we apresents the techniques implemented, the methodology used to test and some initial results obtained with our own developed software b.r.a.s.i.l. ("brain registration and subtraction: improved localization for spect analysis").
checking the alignment of value-based business models and it functionality. business--it alignment is an ongoing activity of high importance for the success of a business. this is a hard task, especially in the context of value webs in which multiple businesses collaborate with each other to reach a common goal. value models, as the outcome of the value web exploration phase, represent solutions for business people, but not for software engineers. the latter ones have to come up with a blueprint for the implementation at application level. this can have two faces: either there are no systems at all and everything needs to be designed from scratch, or it is desired to use as many existing systems as possible. in the latter case, on which we focus in this paper, it must be checked which functionality existing systems should provide and whether they are usable for the given value web context. this affords several design activities, as well as checking consistency between different models. our approach can be viewed as an alignment checking method and also as a gap analysis, in case existing systems miss a given functionality.
integrating functional metrics, cocomo ii and earned value analysis for software projects using pmbok. nowadays, function point and use case point metrics have been largely adopted in the software industry to measure the size of the development work of the project. metrics should be used in conjunction with estimating techniques such as cocomo. there has been an increasing interest in monitoring and controlling project performance. earned value analysis present itself as an easy-to-understand technique that helps to monitor and control project's performance. this article presents a sequence of steps which allows the integration of software functional sizing metrics, cocomo ii and earned value analysis in the processes recommended by the pmbok for planning and controlling software development projects. the goal of such a sequence of steps is to help project managers to plan, monitor and control software development projects using the pmbok and software functional metrics. the two metrics were chosen as the basic units due to their large acceptance by industry. cocomo is a technique largely adopted in the software engineering area. a case study using an actual software project data was undertaken to evaluate our proposal. an add-in for microsoft project tool was developed to support that such a sequence of steps can be automated and integrated.
a framework to process complex biodiversity queries. tackling biodiversity information is essentially a distributed effort. data handled are inherently heterogeneous, being provided by distinct research groups and using different vocabularies. queries in biodiversity systems require to correlate these data, using many kinds of knowledge on geographic, biologic and ecological issues. available biodiversity systems can only cope with part of these queries, and end users must perform several manual tasks to derive the desired correlations, because of semantic mismatches among data sources and lack of appropriate operators. this paper presents a solution based on web services to meet these challenges. it relies on ontologies to retrieve the query contexts and uses the terms of this context to discover suitable sources in data repositories. this approach is being tested using real data, with new services.
fourth special track on trust, recommendations, evidence and other collaboration know-how (treck'08): editorial message. computational trust and online reputation services are reaching the mass market with pioneering startup reputation companies such as venyo (http://www.venyo.org). the trust models and metrics used in those reputation services can again benefit from the treck track contributions, especially regarding their combination with recommender systems and their context-awareness aspects.
error estimation in wireless sensor networks. we present an analogy between the operation of a wireless sensor network and the sampling and reconstruction of a signal. we measure the impact of three factors on the quality of the reconstructed data, namely, the granularity of the process under study, the spatial distribution of sensors, and the protocol for clustering and data aggregation. in order to quantify this influence, a monte carlo study is performed for estimating the error introduced by the observation process. the phenomenon being observed is described by a gaussian random field with varying scale, the distribution of sensors is modeled by a new point process and two protocols are assessed: leach and skater. we show that skater performs better than leach, at the expense of using the sampled data on the clustering stage.
certifying an embedded remote method invocation protocol. this paper describes an approach to formally prove that an implementation of the java card remote method invocation protocol on smart cards fulfills its functional and security specification. for that, we refine the specification in two intermediate formal models: the functional specification and the high level design. these two models are both defined upon an existing complete formal model of the java card virtual machine, allowing to formalize all the security requirements. we focus on certifying the java code portion since the native portion has been handled in a previous work. the correctness is showed to be preserved while composing the native and java codes. our refinement scheme has been designed to fulfill the requirements of a high-level common criteria security evaluation.
lts-bt: a tool to generate and select functional test cases for embedded systems. automation of model-based testing for embedded systems is discussed. the focus is on feature and feature interruption test case generation and selection from behavioral specifications. for this, the lts-bt tool is presented. the tool has been designed to suit embedded systems by focusing on selected notations for behavior specification and tailored techniques for test case generation and selection. this is motivated by the particularities of these systems that challenge cost-effective testing.
ecg data provisioning for telehomecare monitoring. the latest computer and communication technologies in combination with an enhanced ecg analysis system can be used to improve cardiac patient's follow-up out-of-hospital. in this way, real-time transmission of the so-called ambulatory electrocardiogram (aecg) to a remote health application with awareness of the patient's context can support decision making as well as to allow efficient emergency attendance. however, the effectiveness of such a service requires tackling challenges of hardware and software beyond the common issues normally addressed in the literature. this paper proposes an ecg provisioning system that handles advanced issues such as flexibility and interoperability in pervasive scenarios as much as the well-known need for efficient transmission. this system architecture embraces an ecg analysis system based on hidden markov models and makes use of an original ecg markup language.
k-rnn: k-relational nearest neighbour algorithm. the amount of data collected and stored in databases is growing considerably in almost all areas of human activity. in complex applications the data involves several relations and proposionalization is not a suitable approach. multi-relational data mining algorithms can analyze data from multiple relations, with no need to transform the data into a single table, but are computationally more expensive. in this paper a novel relational classification algorithm based on the k-nearest neighbour algorithm is presented and evaluated.
implementing java modeling language contracts with aspectj. the java modeling language (jml) is a behavioral interface specification language (bisl) designed for java. it was developed to improve functional software correctness of java applications. however, instrumented object program generated by the jml compiler use the java reflection mechanism and data structures not supported by java me applications. to deal with this limitation, we propose the use of aspectj to implement a new jml compiler, which generates an instrumented bytecode compliant with both java se and java me applications. the paper includes a comparative study to demonstrate the quality of the final code generated by our compiler. the size of the code is compared against the code generated by an existent jml compiler. moreover, we evaluate the amount of additional code required to implement the jml assertions in java applications. results indicate that the overhead in code size produced by our compiler is very small, which is essential for java me applications.
requirements engineering for cots-based software systems. large software systems are often deployed putting together many commercial-off-the-shelf software components (cots). the selection of the cots to be integrated is driven by the software system requirements. in this paper, we propose the recss method aimed at supporting requirements elicitation and analysis in the context of cots-based software systems. recss builds a goal model of the system environment which identifies the external elements that interact with it. next, the system is decomposed into actors for which iso/iec-based quality models are built. as part of the process, environmental and platform characteristics that influence the behaviour of the system are identified. last, the resulting artefacts are used to analyse and refine the system requirements.
evaluation of priority based real time scheduling algorithms: choices and tradeoffs. real time scheduling algorithms like rm and edf have been analyzed extensively in the literature. many recent works on scheduling address energy consumption as a performance metric. in this work we analyze priority scheduling algorithms rm, edf, and llf along with a few power-aware scheduling algorithms: mllf, rm_rcs and edf_rcs. our analysis addresses the following metrics: response time, response time jitter, latency, time complexity, preemptions, and energy consumption. we extend past work in this direction by characterizing the performance of the scheduling algorithms -- theoretically as well as experimentally. results of our analysis can be used to control design choices for real time systems.
applying a semantic layer in a source code search tool. a fundamental principle for reusing software assets is providing means to access them. information retrieval mechanisms assisted by semantic initiatives, play a very important role in finding relevant reusable assets. in this context, this paper presents a semantic search tool in order to improve the precision of search returns. furthermore, the requirements, the decomposition of architectural module and aspects of implementation are presented.
an algorithm for effective deletion and a new optimization technique for metric access methods. in our work we developed an algorithm to effectively remove elements from a metric tree, using the mam slim-tree as a case study. we also propose a new optimization technique for the structure, based on the deletion algorithm.
pffs: a scalable flash memory file system for the hybrid architecture of phase-change ram and nand flash. in this paper, we present the scalable and efficient flash file system using the combination of nand and phase-change ram (pram). until now, several flash file systems have been developed considering the physical characteristics of nand flash. however, previous flash file systems still have a high performance overhead and a scalability problem of the mounting time and the memory usage because, in most case, the metadata is written with several words at a single update even though the writes in nand flash must be performed in terms of page, which is typically 2 kib. the proposed flash file system called pffs uses pram to mitigate the limitation of nand flash. the pram is a next generation non-volatile memory and good for dealing with word level read/write of a small size of data. pffs hence separates the metadata from the regular data in a file system and saves them into pram. consequently, the pffs manages all the files and directories in the pram and outperforms other flash file systems. the experimental results show that the performance of pffs is 25% better than yaffs2 for small-file writes while matching yaffs2 performance for large writes and the mouting time and the memory usage of pffs are o(1).
towards an assl specification model for nasa swarm-based exploration missions. nasa swarm-based exploration missions represent a new class of concept missions based on the cooperative nature of a hive culture. a mission of this class requires an autonomic system, comprising a set of autonomous mobile units. the design and implementation of such systems requires specific engineering approaches, including new formal specification methods and techniques. this article presents an introduction to our research towards a formal specification of nasa concept swarm-based missions. the autonomic system specification language (assl) is a framework for formally specifying and generating autonomic systems. with assl, we can specify high-level behavior policies, as part of overall system behavior, which shows that assl is a very appropriate language for specifying the autonomic behavior of swarm-based missions. we show how assl can be used to specify self-configuring, self-healing, and safety properties of nasa swarm-based missions.
special track on organizational engineering: editorial message. dominated by the behavioral science approach for a long time, information systems research increasingly acknowledges design science as a complementary approach. the systematic design of artifacts is not restricted to information systems components. being the conceptual foundations for information systems requirements, artifacts on the strategic and organizational levels have to be engineered as well.
a study of terrain coverage models. the ability to cover a terrain has numerous applications to our everyday lives: from spell checking to web crawling, from surveillance to automated vacuuming. indeed, these applications require different approaches to solving the coverage problem because they are based on different ways of evaluating the goodness of the coverage; a good terrain coverage to vacuuming may not be desirable in web crawling. to better understand the issues, this paper divides the terrain coverage problem into two classes (temporal and spatial) and discusses the performance of standard and self-organized algorithms as means of solving both classes of coverage problem. in order to perform the comparison the paper introduces suitable metrics to evaluate the goodness of a coverage (temporal or spatial).
self and non-self discrimination agents. the goal of this work is to study emergent mechanisms that could possibly be embedded in multiagents systems in order to solve complex problems of distributed diagnosis. we assume the hypothesis that emergent functionalities share important structural and constitutive aspects, independently of the domain from which they emerge. the challenge of understanding self-organizing mechanisms (which allow that emergence occurs in nature) is important to develop systems able to better learn and adapt. following such perspective we have been studying the human immune system (his) as a metaphor to solve problems where complexity and distribution are crucial constraints. work in this paper reflects how characteristics from the his can be applied to conceive diagnosis systems. an application was implemented to student diagnosis in the context of an educational environment for learning basic programming skills.
scara3d: 3-dimensional hri integrated to a distributed control architecture for remote and cooperative actuation. during the last years, service robots have been widely applied in home and office automation tasks. the major challenge faced at present by researchers in this area lies on the capability of humans and robots to share the same environment safely. despite the feet that several solutions for this problem involving service robots have already been presented, this subject is rarely discussed involving industrial manipulators. in this paper we present a new approach of multilayer architecture for distributed control of manipulator robots. the proposed model describes layers to implement cooperative and collaborative behaviors among robots and human beings based on an appropriate model of rules. the scara3d, a human-robot interface, is presented as an application for the architecture's virtual environment creator layer.
a hybrid software-based self-testing methodology for embedded processor. software-based self-test (sbst) is emerging as a promising technology for enabling at-speed testing of high-speed embedded processors testing in an soc system. for sbst, test routine development or generation can base on deterministic and random methodology. the deterministic test methodology develops the test program for a pipeline processor using the information abstracted from its architecture model, rtl descriptions, and gate-level net-list for different types of processor circuits. the random test methodology tries to make the pseudo-exhaustive testing possible using random instructions or patterns. the proposed methodology improves coverage for structural faults using both deterministic and random development of the test code. not only can the deterministic test program test lots of faults using very small code size, but also the random test program can help detect some of the faults that the deterministic test program is difficult to test. we demonstrated the feasibility of the proposed methodology by the achieved fault coverage, test program size, and testing cycle count on a complex pipeline processor core. comparisons with previous work are also made. experimental results show its potential as an effective method for practical use.
discovering relationships among categories using misclassification information. knowledge of relationships among categories is of the interest in different domains such as text classification, content analysis, and text mining. we propose and evaluate approaches to effectively identify relationships among document categories. our proposed novel method capitalizes on the misclassification results of a text classifier to identify potential relationships among categories. we demonstrate that our system detects such relationships, even those relationships that assessors failed to identify in manual evaluation. furthermore, we favorably compare the effectiveness of our methods with the state of art method and demonstrate a significant improvement in precision (34%) and recall (5%).
designing and architecting process-aware web applications with epml. an emerging class of web applications is driving the evolution of the web toward a business system. these applications allow the participation of several actors to complex enterprise-wide (or even multi-enterprise) business processes and pose new challenges to the software designer and to the software architect. in this paper we show how, promoting an effective separation of concerns, a process modeling language and its enactment engine can be used in the modeling and in the implementation of process-aware web applications.
usage-based ranking of distributed xml data. in this article we consider the issue of ranking xml data and data sources in a distributed xml data warehouse. our ranking model applies to service-oriented data management applications where web services store and exchange xml fragments. each service publishes a set of operations implemented as parameterized queries on a local xml data warehouse integrating locally generated data and query results received from other services. we propose a new way for ranking distributed data and data sources taking into consideration their usage for the evaluation of queries. the main results are a formal ranking model of data, queries and services and an implementation on a data warehouse.
cref: a central-residue-fragment-based method for predicting approximate 3-d polypeptides structures. in silico prediction of protein tertiary structure is one of the most important and unsolved problems in current structural bioinformatics. in this article, we describe cref, a central-residue-fragment-based method to predict approximate 3-d polypeptides structures. with cref we expect to obtain approximate 3-d structures which can then be used as starting conformations in refinement procedures employing state-of-the-art molecular mechanics methods such as molecular dynamics simulations. cref does not make use of entire fragments, but only the phi, psi torsion angle information of the central residue in the template fragments obtained from pdb. after applying clustering techniques to these data, and guided by a consensus secondary structure prediction of the target sequence, we build approximate conformations for the target sequence. the method is very fast. we illustrate its efficacy in three case studies of polypeptides whose sizes vary from 34 to 70 amino acids. as indicated by the rmsd values, our initial results show that the predicted conformations adopt a fold similar to the experimental structures. starting from these approximate conformations, the search space is expected to be greatly reduced and the refinement steps can consequently demand a much reduced computational effort to achieve a more accurate polypeptide 3-d structure.
general type-2 fuzzy classifiers to land cover classification. this paper proposes a fuzzy classifier based on type-2 fuzzy sets to be applied in land cover classification. the classifier is built from the available data and considers the merging of information acquired from different experts. the data regards a thematic mapper representing the land cover of a real plain cultivated area. the experts are represented by different bands which discretize the spectral sensor information. the new method proposed to design the classifier as well as the use of general type-2 fuzzy sets allows the modeling of input-output relations and minimize the effects of uncertainties in the usual fuzzy rule-based classifiers. the experiments carried out attest the efficiency of the proposed general type-2 fuzzy classifier.
accurate histogram-based xml summarization. in this paper, we propose the use of histograms to characterize node set distributions in an xml document, which then can be recursively evaluated for query optimization tasks. we identify and deal with special cases for effectively using histograms to summarize structural aspects of xml documents. to reveal the potential of our approach, we perform comparative experiments on our native xml database management system called xtc.
enabling ontology-based document classification and management in ebxml registries. document management systems (dmss) are a key component in modern enterprises. for successful document search and retrieval, an adequate metadata set should be defined in order to describe documents with sufficient detail. however, often a single metadata set is not sufficient throughout the whole dms, as different document types require different attributes to be properly characterized. in this paper, we introduce ontologies as a modeling technology for structured metadata definition within dmss. focusing on the ebxml registry standard, we show an approach to enhance dmss for semantic content management and then we propose a method to exploit this new capability for automated document characterization.
an evaluation of a collision handling system using sphere-trees for plausible rigid body animation. collision handling plays a fundamental role for achieving realism and interactivity in 3d graphical systems. nevertheless, it is still one of the bottlenecks of such systems. in this work, we use the sweep & prune algorithm and sphere-tree approximations of the objects to perform the collision detection. besides, we show how to compute the contact data for the narrow phase out of the overlapping leaf spheres from the sphere-trees. for collision response, we have implemented a simple, yet efficient and accurate, impulse-based method. a number of experiments in virtual scenarios with objects falling in a static plane were conducted. the results show that when sphere-trees with 2 levels are used for scenarios with a great number of objects (up to 200 falling objects) and simultaneous contacts among them (up to 16381.50 contacts at each frame on average), our system is capable of generating real time plausible rigid body animation, with always more than 30 frames per second (fps) on average.
adaptive caching with heterogeneous devices in mobile peer to peer network. in the (upcoming) 3g age, many applications such as multimedia streaming, file sharing and so on will be widely used in the wireless environments. in such a mobile environment, users may carry heterogeneous mobile devices with different transmission ranges, latency, and even cache sizes. these devices not only can get services from a mobile support station (mss), but also they can form/generate a mobile peer-to-peer (p2p) network to provide services to each other. for such a mobile p2p network, an effective cache framework that can handle heterogeneous devices is required. in this paper, we propose a flexible cache scheme which is adaptive to the actual device condition and that of its neighbors. our scheme encourages the "strong" peers to keep hot data and do service, and meanwhile to protect and best utilize the "weak" nodes with their limited cache space. simulation and mathematic analysis results show the effectiveness of our scheme.
query by example for web services. web services have acquired enormous popularity among software developers and researchers due to the increasing levels of flexibility required by current distributed applications. however, service search facilities are still rather difficult to use. this paper presents wsqbe, a search method that aims at assisting service discoverers by generating a short list of candidate services and easing query specification. in contrast with previous approaches, wsqbe discovery process is based on a novel search space reduction mechanism. experimental evaluations of our approach are also reported.
a predictive framework for retrieving the best answer. in a question answering (qa) system, each user interaction with the system is different and since there are a variety of arguably correct answers to complex questions, identifying factors for improving the quality of the retrieved answer is difficult. this research aims to develop a framework that identifies predictive variables for the best quality answer in a qa system. it was found that accuracy, completeness and relevance were predictors of best answer. we believe that these findings can serve to guide future developments in the answer extraction modules in the qa systems.
offline count-limited certificates. in this paper, we present the idea of offline count-limited certificates (or clics for short), and show how these can be implemented using minimal trusted hardware functionality already widely available today. offline count-limited certificates are digital certificates that: (1) specify usage conditions that depend on irreversible counters, and (2) are used in a protocol that guarantees that any attempt to use them in violation of these usage conditions will be detected even if the user of the certificate and the verifying party have no contact at all with the outside world at the time of the transaction. such certificates enable many interesting applications not possible with traditional (unlimited use) certificates, including count-limited delegation and access, offline commerce and trading using cashlike migratable certificates, and others. we show how all these applications can be made possible by using only a simple trusted timestamping device (ttd), which can in turn be implemented using existing trusted hardware devices such as smartcards, and the trusted platform module (tpm) chips embedded in pcs available today. significantly, our solutions do not require trust in any other components in the host machines aside from the ttd itself; they remain tamper-evident as long as the ttd is not compromised, even if the entire host system, including the bios, cpu, os and memory, is compromised. this not only provides better security by minimizing the required trusted computing base, but also makes implementation possible on present-day machines without requiring a particular kind of os. we demonstrate all these ideas by implementing a prototype application that runs under both linux and windows, and presenting experimental performance results.
&eacute;nfasis: a model for local variable crosscutting. crosscutting on local variable is suitable for all problem domains where local variables provide a natural implementation of sequential algorithms. however, local variable crosscutting has been neglected, resorting to refactoring on fields as a better implementation option, conveying severe short-comings and inefficiencies. this paper introduces &eacute;nfasis, a join point model for local variable crosscutting along with its experimental framework written in java. &eacute;nfasis formal model is based on a notion of join point that supports an operational interpretation suitable for pointcut composition and a straightforward implementation. the implementation demonstrates the importance of fine grained resolution in join point selection with advising mechanisms, automatic passing context, thisjoinpoint variable and pattern matching of local variables.
a small extension to java for class refinement. this paper presents an extended java language in which users can refine a class definition to a certain degree. they can statically or dynamically redefine methods and append a new method, field, and interfaces to the class like dynamic languages. a unique feature of this language, named gluonj, is that users can use a standard java ide (integrated development environment) to exploit coding support by the ide. this is significant for the industrial acceptability of a new language. a gluonj program is written in standard java with additional java annotations. gluonj was carefully designed so that the ide can recognize a gluonj program and reflect it on the coding support such as the code assist of eclipse. moreover, a gluonj program never throws a runtime exception reporting that an undefined method is called. guaranteeing this property is not straightforward because gluonj allows users to refine a class definition at runtime.
on the conformity of models: a transducer-based approach for model transformation. model transformation is one of the main operations in model engineering. it consists of transforming a source model to a target one. any transformation needs to satisfy some basic requirements, namely the conformity of a model to its meta-model. such model is thus said to be valid. in the litterature, several approaches and languages have been proposed. while they exhibit important features, they unfortunately suffer from a main drawback. indeed, it is difficult to check whether the target model is valid or not. the paper advances the state of the art by proposing a new approach for model transformation that palliates the above limitation. the basic idea behind this approach is to define model transformation as a binary relation, captured by a transducer, between two domains. the use of transducer makes it possible to both translate models and to validate them. note that the proposed approach establishes a bridge from model space to grammar space.
a space-identifying ubiquitous infrastructure and its application for tour-guiding service. in this paper, a novel tour-guiding system is introduced, based on our space-identifying ubiquitous infrastructure, where positioning devices are deployed ubiquitously to identify the place of users. in this infrastructure, we can flexibly construct information service related to the places of interest in the city by modeling the space of the real world as a set of relations among the discrete places, and attaching space-identifying devices to them. our developed tour-guiding system introduces many art works in a large commercial complex in japan. based on the benefit of the infrastructure, this system can provide detailed navigation service as well as art introduction service in both indoor and outdoor environments, and can guide the users to reach their interested art works. currently, this system is already used in practice for a commercial service. in this paper, the design of this system is described and its navigation capability is verified through a user test in the real environment to discuss the effectiveness of our approach.
when a mismatch can be good: large vocabulary speech recognition trained with idealized tandem features. this paper explores tandem feature extraction used in a large-vocabulary speech recognition system. in this framework a multi-layer perceptron estimates phone probabilities which are treated as acoustic observations in a traditional hmm-gmm system. to determine a lower error bound, we simulated an idealized classifier based on alignment of reference transcriptions. this cheating experiment demonstrated a best-case scenario for tandem feature extraction, highlighting the potential for dramatic system improvement. more importantly, we discovered a way to exploit the result without cheating: using the simulated classifier during training and a mlp classifier at test, the performance improved despite the mismatched tandem features.
a clustering-based approach for discovering interesting places in trajectories. because of the large amount of trajectory data produced by mobile devices, there is an increasing need for mechanisms to extract knowledge from this data. most existing works have focused on the geometric properties of trajectories, but recently emerged the concept of semantic trajectories, in which the background geographic information is integrated to trajectory sample points. in this new concept, trajectories are observed as a set of stops and moves, where stops are the most important parts of the trajectory. stops and moves have been computed by testing the intersections of trajectories with a set of geographic objects given by the user. in this paper we present an alternative solution with the capability of finding interesting places that are not expected by the user. the proposed solution is a spatio-temporal clustering method, based on speed, to work with single trajectories. we compare the two different approaches with experiments on real data and show that the computation of stops using the concept of speed can be interesting for several applications.
web service access management for integration with agent systems. the agent paradigm includes the notion that agents interact with services. this paper identifies the need for controlled access to such services, from the perspective of agent systems (and not as is generally the case by web service providers). mediating between web service requests from (virtual) organizations of agents, the web service gateway proposed regulates (i.e., monitors and controls) web service access according to the slas and organizational policies that are in effect. in addition to a model for web service access regulation, an implementation of a middleware component for web services access regulation based on soap and described in wsdl is presented.
a ga-based feature selection and parameters optimization for support vector regression applied to software effort estimation. the precision of the estimation of the effort of software projects is very important for the competitiveness of software companies. machine learning methods have recently been applied for this task, included methods based on support vector regression (svr). this paper proposes and investigates the use of a genetic algorithm approach for simultaneously (1) select an optimal feature subset and (2) optimize svr parameters, aiming to improve the precision of the software effort estimates. we report on experiments carried out using two datasets of software projects. in both datasets, the simulations have shown that the proposed ga-based approach was able to improve substantially the performance of svr and outperform some recent results reported in the literature.
special track on requirements engineering: editorial message. requirements eengineering is a branch of computer science that encompasses tasks that go into determining the requirements of a new or altered system, taking into account the possibly conflicting requirements of the various stakeholders, such as end users. the existing methods for requirements specification are far from being completely satisfactory, and requirements analysis is critical to the success of a project. requirements must be measurable, testable, related to identified business needs or opportunities, and defined to a level of detail sufficient for system design. independently of the nature of the software, the elicitation, analysis, negotiation, specification, validation and management of requirements are fundamental for the development of quality in complex software.
special track on embedded systems: applications, solutions, and techniques: editorial message. high performance embedded computing has recently become more and more present in devices used in everyday life. a wide variety of applications, from consumer electronics to biomedical systems, require building up powerful yet cheap embedded devices. embedded software has tumed out to be more and more complex, posing new challenging issues: the adoption of further flexible programming paradigms/architectures is becoming almost mandatory. nonetheless, embedded systems development nowadays must rely on a tight coupling of hardware and software components. in this scenario, efficient solutions can be proposed at different levels of abstraction, making use of an assortment of tools and methodologies: researchers and practitioners have a chance to propose new ideas and to compare experimentations. the focus of this conference track is on the application of both novel and well-known techniques to the embedded systems development. particular attention is paid to solutions that require expertise in different fields (e.g. computer architecture, os, compilers, security, software engineering, simulation). the track benefits also from direct experiences in the employment of embedded devices in unconventional application areas, so to show up new challenges in the system design/development process. in this setting, researchers, and practitioners from academia and industry get a chance to keep in touch with problems, open issues and future directions in the field of development of dedicated applications for embedded systems.
discrete wavelet transform-based multivariate exploration of tissue via imaging mass spectrometry. mass spectral imaging (msi) or imaging mass spectrometry is a developing technology that combines spatial information with traditional mass spectrometry. it enables researchers to study the spatial distribution of biomolecules such as proteins, peptides, and metabolites throughout organic tissue sections. msi has particular merit in exploratory settings where there is no prior hypothesis of relevant target molecules. it is rapidly becoming a potent exploratory instrument for tissue biomarker studies. msi is a high-throughput technique that mines massive amounts of measurements from a single tissue section. as various parameters such as the covered tissue surface area, the spatial resolution, and the extent of the mass range grow, msi data sets rapidly become very large, making analysis from a computational and memory standpoint increasingly difficult. in this paper we introduce the discrete wavelet transform (dwt) as a means of reducing the dimensionality of the data, while retaining a maximum amount of biochemical information. the dwt delivers a more compact description of each mass spectrum, expressed as wavelet coefficients. the efficacy of performing analyses directly in the dwt-reduced space is illustrated using unsupervised trend detection via principal component analysis (pca) on the msi measurement of a sagittal section of mouse brain.
an objective way to evaluate and compare binarization algorithms. the choice of the best binarization algorithm is very critical for any document image processing system, since it is one of the first tasks and any mistake it performs will be carried through the whole system. here, a new technique for the validation of document binarization algorithms is proposed. our method is simple in its implementation and it can be applied to any binarization algorithm since it doesn't require anything more than the binarization stage. it is based on the use of synthetic images from pdf document. then the binarization algorithm is applied and the result is compared with the original pdf.
a requirements specification case study with projectit-studio/requirements. the early stages of the software development process are crucial to overcome the generalized unsuccess among it projects. therefore, we embraced the goal of creating a case tool for requirements specification. our approach is based on a controlled natural language, seeking to achieve a higher level of rigor and quality of requirements specifications. moreover, this tool belongs to a broader workbench, which covers the software development life-cycle, providing guidance according to se best practices. this paper presents an illustrative specification case study, emphasizing the tool's support and its advantages.
an efficient feature ranking measure for text categorization. a major obstacle that decreases the performance of text classifiers is the extremely high dimensionality of text data. to reduce the dimension, a number of approaches based on rough-set theory have been proposed. however, these works often suffer from two problems: the first is that they cannot directly deal with continuous text features; the second is that they often incur considerable running time. to deal with the first issue, we make some extensions to discernibility matrix so that it can work with continuous features. to cut down running time, we employ centroids rather than examples to construct discernibility matrix, which reduce the time complexity from o(t2w) to o(k2w) where t denotes the size of training examples, k denotes the number of training classes and w denotes the size of vocabulary. the experimental results indicate that proposed method not only yields much higher accuracy than information gain when the number of selected features is smaller than 6000, but also incurs much smaller cpu time than information gain.
an integrated view on business- and it-architecture. the paper outlines the domains of enterprise architecture and fundamental design techniques. the consolidation of architecture description to three basic views is proposed. the component view describes the elements of architecture and their relationships. the communication view shows how the elements interact with one another. the distribution view describes how the elements are distributed in terms of location or organizational assignment. key element of architecture design is to account for interdependencies among the building blocks of architecture. blueprints are introduced as a means in planning the deployment of architecture on a large scale. they give a comprehensive view on the building blocks and how the interact. blueprints show the effects of architecture design between business-, application-, and infrastructure architecture, thus providing an integrated view on architecture. the techniques introduced for architecture design are illustrated by using a selection of real life examples from an architecture design project.
special track on programming for separation of concerns: editorial message. complex systems are intrinsically expensive to develop because several concerns must be addressed simultaneously. once the development phase is over, these systems are often hard to reuse and evolve because their concerns are intertwined and making apparently small changes forces programmers to modify many parts. moreover, legacy systems are difficult to evolve due the following problems: the lack of a well defined architecture, use of several programming languages and paradigms, etc.
special track on database theory, technology, and applications: editorial message. the world nowadays revolves around dealing with data presented in various formats. so it is inevitable that researchers focus their work on advancing the state of managing information. from here, the importance of database technology ranks amongst the hottest areas of research. this year the track has received many papers covering different areas of databases.
enterprise systems modeling: the erp5 development process. the design and implementation of an erp system involves capturing the information necessary for implementing the system's structure and behavior that support enterprise management. this process should start on the enterprise modeling level and finish at the coding level, going down through different abstraction layers. for the case of free/open source erp, the lack of proper modeling methods and tools jeopardizes the advantages of source code availability. moreover, the distributed, decentralized decision-making, and source-code driven development culture of open source communities, generally doesn't rely on methods for modeling the higher abstraction levels necessary for an erp solution. the aim of this paper is to present a model driven development process for the open source erp erp5. the proposed process covers the different abstraction levels involved, taking into account well established standards and common practices, as well as new approaches, by supplying enterprise, requirements, analysis, design, and implementation workflows.
symbiosis in logic-based pointcuts over a history of join points. within aspect-oriented programming, the quality of aspect code depends on the readability and expressiveness of pointcut languages. readability is increased by using specialized, declarative pointcut languages. for such languages, their expressiveness is increased if they offer an integration with the base code language. as has previously been shown, offering access to the past history of the base program also increases pointcut expressiveness. a logical desire then is creating pointcut languages that combine both features, but taken to the extreme this is not implementable. we discuss the unimplementable ideal model of declarative history-based logic pointcut languages, and the possible approximations that can be made that are still implementable and what limits they impose on the ideal expressiveness.
restoration of vibro-acoustography images. vibro-acoustography (va) is an imaging modality that produces an image of the mechanical response of an object to a localized dynamic radiation force of an ultrasound field. this technique has been studied and used in clinical applications as to image calcification in breast tissue and arteries. this paper presents the application of restoration algorithms to va images.
hierarchical memory system design for a heterogeneous multi-core processor. multi-core architecture has become hot issue recently both for performance and power consideration. memory system is the bottleneck under this circumstance. a multi-core architecture using simple cores based on transport triggered architecture is proposed. this architecture has a uniform programming view. the memory system design exploration and optimization is done and a hierarchical memory system is designed. a balanced memory bandwidth is provided to the multi-core architecture.
designing semantic web services using conceptual model. there are emerging technologies such as sawsdl or wsmo that extend the current web services technologies to so called semantic web services by combining the structural and semantic descriptions of web services. in this paper, we identify problems that can arise when using these technologies for the design and management of semantic web services and we show that using a conceptual model instead of these technologies can help to solve these problems. we also show how to automatically derive the description of semantic web services represented with existing technologies, concretely with sawsdl, from the conceptual level because this representation brings other advantages.
tcm-knn scheme for network anomaly detection using feature-based optimizations. with the rapid increase of network threats and cyber attacks, network security problem is becoming more and more serious. network anomaly detection is a key technique to secure information systems and resist cyber attacks. in this paper, we first propose an efficient network anomaly detection technique based on tcm-knn scheme. secondly, we emphasize the feature-based optimizations for our tcm-knn. we employ feature selection and feature weight mechanisms to optimize tcm-knn as a promising lightweight and on-line anomaly detection technique both in reducing its computational cost and in boosting its detection performance. a series of experiments on well-known intrusion detection dataset kdd cup 1999 demonstrate the effectiveness of our methods presented in this paper.
securing aspect composition. although research in aop is increasing in maturity there remain many unresolved issues. while current aop languages offer ever-increasing levels of flexibility, they still fail to offer a sufficient discipline of application to ensure that advanced aop facilities are used safely and appropriately. researchers have recognised the need to control aspect composition and have started to explore mechanisms to achieve this [2, 3, 4, 5]. in this paper we aim to provide a novel approach to control aspect composition (using aspectj as reference) and we employ the concept of roles from role based access control models [1] to characterise aspects in terms of both their internal behaviour and their external composition. then, using policies, we express invariants and constraints on the associated advice and pointcuts.
the architecture and design of a malleable object-oriented prolog engine. the implementation of prolog systems has a long history, from the first interpreter written in 1972 to de facto standard model of the warren abstract machine. although many architectural variations have been proposed, object-oriented design was left mostly unexplored, favoring other factors such as execution time and memory storage optimizations. however, today complex software systems are typically built as aggregates of heterogeneous components, where logic programming may effectively help facing key issues such as intelligence of components and management of interaction. in this scenario, implementation of logic languages could just aim at reasonable - rather than maximum - efficiency, requiring instead configurable and flexible architectures to allow for extensions and tailoring for different application domains. tuprolog is an object-oriented prolog engine which has been designed to feature a malleable architecture at its core, and to exhibit the typical properties of basic components for complex dynamic systems and intelligent infrastructures---such as easy deployability, lightness, and configurability. in this paper, we first describe tuprolog's malleable architecture, composed by a set of managers controlling sensible parts of the system, and operating around a minimal interpreter shaped as a finite state machine. then, we support the malleability claim by discussing two possible architectural extension of the engine.
towards temporal web search. this paper shifts the focus of web search towards finding and exploiting small text nuggets, rather than full-length documents, assumming that the type of targeted information (e.g., date) is specified in the queries. each nugget is a document sentence fragment that encodes open-domain factual information associated to some entity. the entities are dates (e.g., 1971) when the events captured by the nuggets must have occurred. the nuggets are extracted from the unstructured text of web documents, based on lightweight text processing. since per-document time stamps are available only in restricted collections such as news articles, but not in arbitrary web documents, the extraction of the relevant dates relies on simple, local text analysis. the resulting time-stamped text nuggets have immediate applications in web search, as direct results for queries asking about the date of an event explicitly (e.g., "when was the transistor invented") or implicitly (e.g., "golden gate bridge built").
multi-purpose proactive m-artifacts. paper-based artifacts (e.g., forms, manuals, questionnaires) are used ubiquitously and pervasively to support a wide set of activities. education and health care are major examples of such endeavor. however, given the passiveness of the medium itself, several problems (e.g., communication, adjustment, lack of interactivity) are usually encountered within these activities which hinder human efficiency or prevent users from achieving desired goals. this paper presents a framework that provides common users with tools to create interactive and adjustable digital artifacts for mobile devices. the artifacts can be adjusted to the users' needs, introducing different configurations regarding their look, interaction and behavior, providing support to various purposes by coping with and enhancing different procedures. the framework has been validated through two case studies by providing support to mobile learning, and within psychotherapy, by offering means to achieve ubiquitous cognitive behavioral therapy.
learning to identify emotions in text. this paper describes experiments concerned with the automatic analysis of emotions in text. we describe the construction of a large data set annotated for six basic emotions: anger, disgust, fear, joy, sadness and surprise, and we propose and evaluate several knowledge-based and corpusbased methods for the automatic identification of these emotions in text.
an architecture of services for session management and contents adaptation in ubiquitous medical environments. advances in wireless technologies and mobile devices have made possible a wide range of efficient and powerful healthcare environments. ubiquitous computing concepts meet healthcare principles, enabling physicians to connect to and use healthcare systems almost anytime, anywhere. this paper proposes a service architecture based on a context-aware middleware, which provides session management and content adaptation for ubiquitous medicine environments. by using simple applications on top of the proposed middleware services, associated physicians join a network of services, so called uhs (ubiquitous health services) that provide ubiquitous access for its users from any point of the network, with different kinds of devices.
using the rrt algorithm to optimize classification systems for handwritten digits and letters. multi-objective genetic algorithms have been often used to optimize classification systems, but little is discussed on their computational cost to solve such problems. this paper optimizes a classification system with an annealing based approach, the record-to-record travel algorithm. results obtained are compared to those obtained with a multi-objective genetic algorithm in the same approach. experiments are performed with isolated handwritten digits and uppercase letters, demonstrating both the effectiveness and lower computational cost of the annealing based approach.
uml state machine diagram driven runtime verification of java programs for message interaction consistency. in object-oriented programs, we often need to set some restrictions on the temporal orders of the message receiving for objects, which forms a class of safety requirements. in this paper, we use uml state machine diagrams as design specifications, and present an approach to runtime verification of java programs, which is focused on the temporal order of message receiving based consistency verification between the behavior of state machine diagrams and the program execution traces. in the approach, we first instrument the program under verification so as to gather the program execution traces related to a given state machine diagram. then we drive the instrumented program by random test cases so as to generate the program execution traces. finally we check if the collected program execution traces are consistent with the behavior of the state machine diagram, which means that the temporal orders of the message receiving occurring in the program traces are consistent with the ones occurring in the state machine diagram. our approach can be used to detect not only the program bugs resulting from the wrong temporal orders of message receiving, but also the imperfect state machine models constructed in reverse engineering for legacy systems, and leads to a testing tool which may proceed in a fully automatic fashion.
a method for semantics-based conceptual expansion of ontology. for the past few years, automatic ontology construction and expansion is one of the most important research subjects in the field of knowledge engineering. compared with the traditional term frequency method, we propose a semantics-based method to extract concepts from a large corpus of text documents and expand the concepts of the known ontology based on the semantic relations between two terms. the proposed method explores how to identify the candidate concepts, and how to give suggestions to knowledge engineers on where the concepts should be inserted in a given ontology. the effectiveness of the proposed approach is demonstrated by experiments on a traditional chinese medicine text corpus.
population genetics of human copy number variations: models and simulation of their evolution along and across the genomes. population genetic models play a significant role in human genetic research, since they promise to provide a better understanding of both evolution of normal variations of the genomes as well as development of disease promoting genomic segments. in this paper, we propose and computationally simulate a model of evolution for unique and segmentally duplicated regions of human genome, which manifest in genome-wide variations in copy number. copy number variations (cnvs) are known for their possible association with genomic diseases and predisposition to various health conditions, and yet, the underlying population genetic models, needed for association studies, have remained largely undeveloped. additionally, segmentally duplicated (sd) regions of the human genome are of a specific interest, since they exhibit a complex behavior of copy number changes and are specifically known for catalyzing pathogenic and unstable genomic rearrangements. our main contribution is in suggesting mechanisms for evolution of copy number changes in regions of segmental duplication of the human genome, which is essential for association studies involving cnv markers and estimation of parameters of stochastic diffusion that determine asymptotic behavior of such evolutionary processes.
towards design patterns for ontology alignment. aligning ontologies is a crucial and tedious task. matching algorithms and tools provide support to facilitate the task of the user in defining correspondences between ontologies entities. however, automatic matching is actually limited to the detection of simple one to one correspondences to be further refined by the user. we propose in this paper the use of correspondence patterns as a tool to assist the design of ontology alignments. based on existing research on patterns in the fields of software and ontology engineering, we propose a pattern template as an helper to develop a correspondence patterns library. we give ways towards the representation of patterns using an appropriate correspondence representation formalism: the alignment ontology.
examining the motivations of defection in large-scale open systems. in large-scale open systems such as ebay one of the key concerns in increasing the utility of users is having a trustworthy method for users to determine which interactions will be satisfactory and which are liable to lead to disappointment. rather than starting from the point of assuming there are good and bad users we will examine why we can make such a distinction in this context and how humans mitigate some of the problems which seem endemic to such a system through game modification. we then demonstrate a use of this model of behaviour in simulating a particular agent choice in order to show the conditions under which different reputation systems affect an agent's trustworthiness, before briefly describing possible future directions of research to deal with the truly disenfranchised agents.
test generation and minimization with "basic" statecharts. model-based testing as a black-box testing technique has grown in importance. the models used represent the relevant features of the system under consideration (suc), and can also be used as a basis for generating test case sets. in this work we introduce a novel representation of state-charts which subsumes common features of different state-chart variants. based on this model and well-defined test criteria, efficient algorithms are introduced for generating test case sets. those test case sets are minimized to cover both the model of suc and its inversion, i.e., the complementary model.
c-saw---contextual semantic alignment of ontologies: using negative semantic reinforcement. understanding the meaning of each term in an ontology is essential for successfully integrating and aligning ontologies. much ontology integration research to date is focused on syntactic, structural and semantic matching where the actual meaning of the concepts is disregarded. the c-saw approach to ontology alignment is based on the contextualizing the concepts by using a set of semantic alignment words (c-saw). the c-saw approach is enhanced by negative semantic reinforcement (nsr), where additional semantic meaning can be added to the set of semantic alignment words, by considering words which are unrelated to the concept.
track on computer networks: editorial message. on behalf of the program committee of the track on computer networks of the 23rd annual acm symposium on applied computing (acm sac 2008), it is our great pleasure to welcome you to the acm sac 2008, held from march 16 to march 20, 2008, in fortaleza, cear&aacute;, brazil. in recent years, significant advances in computer networks have been made throughout the world. this track aims to be a forum for scientists, engineers and practitioners, in academia and industry to share new ideas, experiences and results, and to present their latest findings in any aspects of computer networks.
evaluating genetic algorithms with different population structures on a lot sizing and scheduling problem. this paper studies the use of different population structures in a genetic algorithm (ga) applied to lot sizing and scheduling problems. the population approaches are divided into two types: single-population and multi-population. the first type has a non-structured single population. the multi-population type presents non-structured and structured populations organized in binary and ternary trees. each population approach is tested on lot sizing and scheduling problems found in soft drink companies. these problems have two interdependent levels with decisions concerning raw material storage and soft drink bottling. the challenge is to simultaneously determine the lot sizing and scheduling of raw materials in tanks and products in lines. computational results are reported allowing determining the better population structure for the set of problem instances evaluated.
a genetic algorithm for sensor deployment based on two-dimensional operators. in this paper, we propose a novel and efficient genetic algorithm to the optimal sensor placement of nodes for a wireless sensor network designed to monitor enemy vehicles in a hostile region. a notable feature of our genetic algorithm is the combination of mutation derived from physics and crossover in which heterogeneity between genes is removed by pairing nearest two-dimensional genes. making experiments by a new simulator that is developed to improve time performance of the sensor deployment simulator based on the geographic information system, we demonstrated the superiority of the proposed genetic algorithm.
a graph-based profile similarity calculation method for collaborative information retrieval. collaborative information retrieval (cir) is one of the popular social-based ir approaches. a cir system registers the previous user interactions to response to the subsequent user queries more efficiently. but cir suffers from the personalization problem because the goals and the characteristics of two users may be different; so when they send the same query to a cir system, they may be interested in two different lists of documents. we have developed a personalized cir system, called percirs, to solve this problem. selecting an efficient method to calculate the similarity between user profiles is a key factor for enhancing percirs's efficiency. in this paper, we propose a new graph-based method for user profile similarity calculation. finally, by introducing an evaluation method, we will show that this new method is more efficient than the previous methods.
dynamic support to transactional remote invocations over multiple transports. xactor is a distributed transaction manager that affords transactional remote invocations over an open-ended set of transports. its support to transactional interactions is dynamic, in the sense that the transaction manager fully exploits a collection of rmi mechanisms and transport protocols that grows with the addition of plug-in modules to running instances of xactor. a distributed transaction can employ any combination of the transports that the currently installed plug-ins provide. two-phase commit (logging and failure recovery included) runs over any such combination of transports. aimed at server-side application containers, xactor can be integrated with those systems in a way that allows its plug-in modules to take advantage of the dynamic deployment facilities of the container environment.
special track on computer security: editorial message. it is a pleasure to announce that the security track at the 2008 acm symposium on applied computing has reached its seventh year, and therefore stands amongst the tracks with the longest tradition. the program committee was enriched also this year, and as usual features passionate researchers affiliated to industrial or academic institutions in the entire world. here they are, in alphabetical order.
a farsi part-of-speech tagger based on markov model. this paper describes applying a part-of-speech (pos) tagging system on an unreported farsi corpus by using a markov model. some aspects of farsi morphology and some issues in developing a tagging system are offered. by simulation we evaluate this method on the corpus. to our knowledge, this is first time that a statistical pos tagger is applied on a farsi corpus.
a qos-oriented external scheduler. quality of service (qos) related objectives are used in many current applications, like grid-based systems and e-commerce applications. network managers, application servers and grid resource managers are examples of software that is often qos-enabled. on the other hand, database servers usually provide a best-effort model, answering each query as fast as possible. thus, they are not prepared to provide qos differentiation for incoming queries. in this work, we present an external control system for qos-oriented scheduling of database requests. our external system prioritizes queries and automatically adjusts the number of queries that are concurrently executed (degree of multi-programming) in order to achieve user-specified service level objectives (slo). there are works on external schedulers, admission control systems and on the specification of the degree of multi-programming, but most focus on best-effort models and do not consider service level objectives. our experimental results show that our approach is effective and that using a specialized scheduler for achieving slo is very important.
slack time evaluation with rtsj. we address in this paper the problem of jointly scheduling hard periodic tasks and soft aperiodic events using the real-time specification for java (rtsj). we present the programming constraints of rtsj and propose slack time evaluation and utilization algorithms which take these constraints into account. we evaluate these algorithms and compare their performances with the background scheduling (bs) through simulations.
serpentine: adaptive middleware for complex heterogeneous distributed systems. adaptation of system parameters is acknowledged as a requirement to scalable and dependable distributed systems. unfortunately, adaptation cannot be effective when provided solely by individual system components as the correct decision is often tied to the composition itself and the system as a whole. in fact, proper adaption is a cross-cutting issue: diagnostic and feedback operations must target multiple components and do it at different abstraction levels. we address this problem with the serpentine middleware platform. by relying on the industry standard jmx as a service interface, it can monitor and operate on a wide range of distributed middleware and application components. by building on a jmx-enabled osgi runtime, serpentine is able to control the life-cycle of components themselves. the scriptable stateless server and cascading architecture allow for increased dependability and flexibility.
version control in crosscutting framework-based development. crosscutting frameworks are a type of aspect-oriented framework, which includes only one crosscutting concern, such as persistence, distribution or security. this type of framework is currently being researched in-depth, however little attention has been given to the version control of these frameworks and of the applications developed with their support. version control concerning the development based on crosscutting frameworks is more complex than in traditional development. moreover, it is more complex than in the development based on traditional frameworks, which require suitable techniques to control the evolution of both the frameworks and developed applications. thus, in this paper we present guidelines and a tool which aims to control the versions of crosscutting frameworks, as well as the applications which are developed with their support.
an approach for specification construction using property-preserving refinement patterns. this paper proposes a refinement method based on a set of formal refinement patterns for software architecture design using software architecture model (sam). first, an approach for specification construction through property-preserving refinement patterns is discussed. the refinement patterns are categorized into connector refinement, component refinement and high-level petri nets refinement. then, modeling and refining a life insurance system is used to demonstrate how to applying the refinement patterns for software architecture design using sam. the results demonstrate that a refinement method is an effective way to develop a high assurance system. our result can be easily generalized to other formal methods as well.
special track on middleware engineering (me): editorial message. welcome to the middleware engineering (me) track of 23rd annual acm symposium on applied computing (acm sac 2008). research in middleware systems has evolved from simple client server models to distributed systems, peer-to-peer (p2p) systems, mobile devices, service oriented computing, grid computing, agent based computing, smart environment, and sensors network. each of the above areas in distributed computing, peer-to-peer computing, service oriented computing, grid computing, agent based computing and smart devices, and sensor networks, poses its own unique challenges in the design, development and deployment of middleware, its components and applications using such middleware. the main objective of the middleware engineering track is to bring together researchers and practitioners working in middleware systems with topics ranging from different areas from the afore mentioned areas under one roof with an aim of encouraging exchange of ideas and experiences among these diverse communities.
large-scale simulation of v2v environments. providing vehicles with enhanced ability to communicate and exchange real-time data with neighboring vehicles opens up a variety of complex challenges that can only be met by combining different research fronts such as wireless communications, information processing, self-organization protocols and collaborative optimization. the difficulty in performing real tests in this area forces the use of computer simulation. in this paper we introduce an efficient simulation framework for large scale vehicle-to-vehicle (v2v) networks in urban environments. our main contribution is a sophisticated traffic simulator, which is oriented towards simulating car-to-car communications, and relies on a global positioning server in order to convey location information for micro-simulated vehicles. to illustrate the various studies made possible by our simulation system, we provide a preliminary characterization of how the wireless transmission range in an urban-like environment affects the freshness and inter-vehicle propagation characteristics of real-time mobility information.
providing dependability for web services. web services have been widely employed to allow interoperability among applications and/or technologies. however, the standard technologies and protocols which provide the foundation for web services do not address issues such as fault tolerance and dependability of services. aiming to solve this limitation, this paper proposes a software architecture for providing dependability for web services. this architecture is responsible for increasing service availability and maintaining all replicas of a service in a consistent state, having as main characteristic the separation of these replicas in groups.
an onboard knowledge representation tool for satellite autonomous applications. artificial intelligence planning and scheduling (aips) techniques have been used both in ground-based and onboard space applications. aips relies on model-based domain knowledge representation systems, which is of value for many other applications, such as diagnosis systems and satellite simulators. this paper reports the development of an autonomous satellite onboard planner developed at inpe, and how this project lead us to start creating a more structured knowledge representation tool. the tool can be used not only by a planning application, but also by diagnosis and prognosis systems, satellite simulators and more, both in onboard and ground-based environments, and even outside the space field.
a validation methodology for agent-based simulations. validity forms the basic prerequisite for every simulation model, therefore also for reasonable usage of the agent-based simulation paradigm. however, models based on the multi-agent system metaphor tend to need some particular approaches. in this paper, i propose a process for validating agent-based simulation models that combines face validation, sensitivity analysis, calibration and statistical validation.
hardware implementation for network intrusion detection rules with regular expression support. signature-based network intrusion detection systems (nidss), such as snort and bro, rely on a rule database that describes traffic patterns for known attacks. they examine each packets flowing through a network segment and report suspicious packets to assure security. an attack signature may be represented in terms of fields in a packet such as source/destination ip addresses, source/destination ports, protocols, specific contents in payload, etc. typically, a perl compatible regular expression (pcre) is used to describe a specific content in the payload which may identify an attack. our study shows that over 60% of the execution time in an nids is found to perform string comparisons against a signature database of over 5,950 tokens and over 1,763 pcres. this paper proposes to extend a bit-parallel algorithm to support multi-byte processing and pcre. this design takes a segment of bytes from the payload of a packet and detects all possible tokens including those crossing text segment boundaries. a tool is designed to generate vhdl code from a rule set automatically. performance results are reported.
learning activities on health care supported by common sense knowledge. this paper discusses how common sense knowledge can be used by teachers for planning learning activities on health care. using common sense statements which were automatically collected, we are developing software that can be used to support the teaching and learning process, in a more contextualized form. when teachers consider the knowledge that learners already have, taking into account their common sense knowledge, they can devote their attention to correcting misconceptions, covering ignored topics and avoiding the obvious. also teachers can consider the common sense knowledge from a group of interest, preparing learners to interact with this group by calling their attention to topics which might be discussed with the group. through the experiment described here, we demonstrate that common sense can be useful to support the nursing education process, helping teachers to develop learning activities on the health care domain.
a novel protocol to prevent malicious nodes from misdirecting forward ants in antnet algorithm. antnet is an adaptive multi-agent routing algorithm inspired by ants' behavior, which can be used for the management of highly dynamic networks such as internet and wireless networks. making use of their ability to autonomously migrate from one node to another, antnet's forward ants explore the current condition of the network and then backward ants update the routing information stored on each node accordingly [3]. although in comparison with other routing algorithms, antnet have a better performance, especially regarding the load balancing factor, they are vulnerable against several security threats [8]. one important security threat is that a malicious node (router) can easily misdirect a forward ant to a node which is not located in the best path towards the destination node of that ant. in this paper this threat is precisely described and a protocol to mitigate it is suggested and to some extent analyzed. it is important to note that this threat arises from the nature of free-roaming mobile agents and thus, it exists in other routing algorithms utilizing such agents as well.
modelling adaptive services for distributed systems. there exists a growing class of distributed applications that require adaptive middleware services, i.e., services that are able to monitor changes in the execution environment and in the user's requirements, reacting to these changes by adapting their behaviour. this paper proposes modelling primitives that allow to describe the adaptation logic of distributed applications that use reconfigurable service compositions.
special track on data streams: editorial message. nowadays, very large databases are required to store massive amounts of data (we have daily giga bytes of data from radio telescopes and billions of telephone calls, emails, sms, satellite data, ip network traffic) that are continuously inserted, and queried. in several applications, data are better modelled not as persistent tables but rather as transient data streams. in some applications, it is not feasible to load the arriving data into a traditional database management systems (dbms), once traditional dbms are not designed to directly support the continuous queries required in these applications. these sources of data are called data streams. many researchers coming from different areas (databases, data mining, machine learning, olap, etc.) are designing new approaches or adapting some of the traditional algorithms to support data streams. the goal of this workshop is to convene researchers who deal with data streams models, processing continuous queries, sampling techniques and/or mining decision rules, decision trees, association rules, clustering, filtering, preprocessing, post processing, feature selection, visualization techniques, etc. from data streams and related issues.
on the design and performance evaluation of notification support for p2p-based network management. in this paper we present the design of a notification service used in a peer-to-peer (p2p) based network management solution called manp2p. the notification service is based on the publish/subscribe paradigm, and implemented over a p2p overlay that carry the notification messages using soap, the web services basic protocol. the performance of the notification service is evaluated considering the network traffic, the delivery delay, and the processing power required to forward notifications from physical devices (e.g., router, switches) to interested network managers. the results show that the notification service performs better if an increasing number of intermediate elements called mid-level managers is used between a notification source and destination.
special track on coordination models, languages and architectures: editorial message. for the tenth edition of the special track on coordination models, languages and architectures, interaction and coordination are among the main dimensions characterizing any modern notion of computing, deeply affecting the engineering of concurrent and distributed applications. there, the issue about how to put several heterogeneous components (processes, objects, services, agents, humans) together within a working system to integrate them fruitfully in an open and dynamic environments can be considered today among the most important and challenging issues.
extending peer-to-peer networks for approximate search. this paper proposes a way to enable approximate queries in a peer-to-peer network by using a special encoding function and error correcting codes. the encoding function maintains neighborhood relationships so that two similar inputs will result in two similar outputs. the error correcting code is then used to group the similar encoded values around special codewords. in this manner, similar content is located as close as possible in the network. the algorithm is tested in a simulated environment on a hypercube network overlay.
applying case-based reasoning in the evolution of deforestation patterns in the brazilian amazonia. patterns of deforestation in brazilian amazonia are often associated with different actors, their economic activities and their land use and land cover change strategies. these patterns are often analyzed as static landscape objects, they are not treated as objects evolving along the time. this paper proposes to apply the case-based reasoning (cbr) technique to establish rules and detect object deforestation evolution in an amazonia region. the objects were analyzed in a sequence of images from different periods creating the base and rules to apply cbr. the application of cbr can help the specialist to understand how different landscape objects evolve, to establish object trajectories and to represent that evolution.
interacting urns processes: for clustering of large-scale networks of tiny artifacts. we analyze a distributed variation on the p&oacute;lya urn process in which a network of tiny artifacts manages the individual urns. neighboring urns interact by repeatedly adding the same colored ball based on previous random choices. we discover that the process rapidly converges to a definitive random ratio between the colors in every urn and that the rate of convergence of the process at a given node depends on the global topology of the network. in particular, the same ratio appears for the case of complete communication graphs. surprisingly, this effortless random process supports useful applications, such as clustering and pseudo-coordinate computation. we present preliminary numerical studies that validate our theoretical predictions.
an audio wiki supporting mobile collaboration. wikis have proved to be very effective collaboration and knowledge management tools in large variety of fields thanks to their simplicity and flexible nature. another important development for the internet is the emergence of powerful mobile devices supported by fast and reliable wireless networks. the combination of these developments begs the question of how to extend wikis on mobile devices and how to leverage mobile devices' rich modalities to supplement current wikis. realizing that composing and consuming through auditory channel is the most natural and efficient way for mobile device user, this paper explores the use of audio as the medium of wiki. our work, as the first step towards this direction, creates a framework called mobile audio wiki which facilitates asynchronous audio-mediated collaboration on the move. in this paper, we present the design of mobile audio wiki. as a part of such design, we propose an innovative approach for a light-weight audio content annotation system for enabling group editing, versioning and cross-linking among audio clips. to elucidate the novel collaboration model introduced by mobile audio wiki, its four usage modes are identified and presented in storyboard format. finally, we describe the initial design for presentation and navigation of mobile audio wiki.
autonomic management policy specification in tune. distributed software environments are increasingly complex and difficult to manage, as they integrate various legacy software with specific management interfaces. moreover, the fact that management tasks are performed by humans leads to many configuration errors and low reactivity. this is particularly true in medium or large-scale distributed infrastructures. to address this issue, we explore the design and implementation of an autonomic management system. the main principle is to wrap legacy software pieces in components in order to administrate a software infrastructure as a component architecture. however, we observed that the interfaces of a component model are too low-level and difficult to use. therefore, we introduced higher-level formalisms for the specification of deployment and management policies. this paper overviews these specification facilities that are provided in the tune autonomic management system.
proposing metrics of difficulty of domain knowledge using usecase diagrams. in a system development, the knowledge of a target business is very important factor for the success of a development. the needed part of such knowledge is different for each stakeholder. therefore, we need a method to measure the level of understanding of a stakeholder and a method to categorize business knowledge. this paper proposes the metric of difficulty level in order to measure the business knowledge. moreover, we performed the experiment to confirm the suitability of the proposed metric.
a novel approach for test suite reduction based on requirement relation contraction. the goal of test suite reduction is to satisfy all testing requirements with the minimum number of test cases. existing techniques can be applied well on the constructed test suite. however, it is possible and necessary to optimize testing requirements before test case generation. in this paper test suite reduction is solved by testing requirement optimization. a requirement relation graph is proposed to minimize the requirement set by graph contraction. an experiment on specification-based testing is designed and implemented. the empirical studies show that the testing requirements can be optimized by the graph contraction methods effectively.
a new approach for interactive semantic image retrieval using the high level semantics. content-based image retrieval and text-based image retrieval are two fundamental approaches in the field of image retrieval. recently, the researchers use the combining approaches and semiautomatic image retrieval, using the user interaction in the retrieval cycle. in this paper, an image retrieval approach is introduced that provides the retrieval process semi-automatically using the relevance feedbacks of the user and the novel similarity metrics for related high level semantic labels to the images. the proposed approach can reply different requests in the image retrieval domain based on a hierarchical semantic network and doing a new kind of learning process by the feedbacks given by user. according to experiments, our proposed approach concludes considerable accuracy for retrieval results.
conflict-aware load-balancing techniques for database replication. middleware-based database replication protocols are more portable and flexible than kernel-based protocols, but have coarser-grain information about transaction access data, resulting in reduced concurrency and increased aborts. this paper proposes conflict-aware load-balancing techniques to increase the concurrency and reduce the abort rate of middleware-based replication protocols. experimental evaluation using a prototype of our system running the tpc-c benchmark showed that aborts can be reduced with no penalty in response time.
mdsd light for erp. fully-fledged model-driven software development is often too expensive for small and medium sized enterprises (smes). therefore we propose mdsd light which reduces the available adjustment possibilities, but offers an easy way of workflow and process management. we introduce a tool-suite which realizes the aspects of mdsd light and show the advantages of this approach in a short example.
improving the neural meshes algorithm for 3d surface reconstruction with edge swap operations. the reconstruction of a three-dimensional surface from a set of unorganized points is a fundamental process in a lot of applications, including laser range scanners, medical imaging, and others. this work presents a modified version of the neural meshes algorithm for surface reconstruction from point cloud, called neural meshes with edge swap, or neural meshes es. from the original basic neural meshes algorithm we developed a new heuristic that include an edge-swap operation, making the algorithm less sensible to parameters variation, improving the quality of the generated surfaces. the results show that the edge-swap operation is able to avoid a series of incorrect reconstructed areas in the mesh, mainly in the concave structures.
an integrated web system to facilitate personalized web searching algorithms. generic web searching often turns out impersonal and frustrating due to lack of adaptivity to user preferences. these problems can be alleviated in the presence of a solution to assist personalization in an effective manner. such a tool is presented within the context of this paper that enables personalization on the client's browser and is supported by a web service based backend system that implement a number of different personalization approaches as an option. our aim is to provide a generic platform based on web technologies a) for end-user personalization and b) for assistance in the research & development evaluation of existing or novel personalization techniques. the solution is further underpinned with novel personalization techniques. the latter have emerged as fine-grained and improved alternatives to provably efficient personalization methods previously presented in [10]. the solution altogether has been experimentally evaluated and proved effective.
splitting heuristics for disjunctive numerical constraints. numerical constraint solving techniques operate in a branch & prune fashion, using consistency enforcement techniques to prune the search space and splitting operations to explore it. extensions address disjunctions of constraints as well, but usually in a restrictive case and not fitting well the branch&prune scheme. on the other hand, ratschan has recently proposed a general framework for first-order formulas whose atoms are numerical constraints. it extends the notion of consistency to logical terms, but little is done with respect to the splitting operation. in this paper, we explore the potential of splitting heuristics that exploit the logical structure of disjunctive numerical constraint problems in order to simplify the problem along the search. first experiments on cnf formulas show that interesting solving time gains can be achieved by choosing the right splitting points.
a service architecture for sensor data provisioning for context-aware mobile applications. one of the main issues that inhibit the development of context-aware mobile applications is the lack of systematic methods for sensor data acquisition. this lack, however, is a result of the diversity of sensor data and its acquisition devices. in face of this, there is a need for general engineering solutions in order to address the common sensor data acquisition concerns. this paper presents a service-oriented architecture that allows the rapid prototyping of sensor data provisioning systems. this architecture is then applied to the healthcare domain for providing cardiac signals in the scope of a context-aware telemonitoring system. the architecture is defined by entity and behavior models through a service-oriented design (sod) language that has tool support.
crime scene classification. in this paper we provide a study about crime scenes and its features used in criminal investigations. we argue that the crime scene provides a large set of features that can be used to corroborate the conclusions emitted by the experts. we also propose a set of features to classify the violent crime considering two classes: attack from inside or outside of the scene. the classification stage is based on conventional mlp (multiple-layer perceptron) neural network and svm (support vector machine). the experimental results reveal an error rate of 30.3% (mlp), 22.8% (svm-linear), and 19.4% (svm-polynomial) using a database composed of 400 crime scenes.
special track on web technologies: editorial message. the internet and other related technologies have created an interconnected world in which information can be easily exchanged, tasks can be collaboratively processed, communities of users with similar interests can be instantly formed to achieve efficiency and improve performance, while security threats are present more than ever before. this second edition of web technologies track is intended to bring together researchers who are actively engaged both in theoretical and practical aspects of database interoperability.
an environment for the rapid development of embedded file systems. this paper describes an environment for the rapid development of embedded file systems. it has been designed to take into account embedded real-time systems concerns such as predictability and memory footprint. the environment described here uses an abstract file system (afs) to generate c source code for a custom file system (cfs) intended for a specific application. also a software tool was created to act as a front-end and to simplify the task of cfs creation. the main advantage of this environment is reduction in both cost and time needed to develop a product, which leads to a smaller time to market.
a fast and effective method to detect multiple least significant bits steganography. in this paper, we propose a fast and effective lsb steganalysis for detecting the existence of hidden message and estimating hidden message length when the embedding is performed using both of two distinct embedding paradigms in one or more than one lsb. the method is based on the analysis of image statistics and quadratic equation. compared with weighted stego-image based method, ker's method and luo et.al.'s method, the detection accuracy is high. experimental results and theoretical verification show that the proposed method is an effective method of lsb steganalysis.
ivesta: an interactive visualization and evaluation system for drive test data. drive test data (dtd) evaluation intends to provide first-hand mobile phone performance assessment such that different parties, including phone manufacturers and network providers, can review the phone and network performance, e.g., service coverage and voice quality, from different perspectives. due to many uncertainties involved in the test environments, e.g., terrain, interference, vehicle speed, and network delay, it is crucial to properly digest the dtd data such that users can draw valid conclusions like "phone a outperforms phone b in the suburb area". we argue that because of the inherent complexity of the test environments, dtd collected from the fields suffer from low quality, low integrity, high uncertainty, and low interpretability. an evaluation tool should consider all such reality issues in order to develop a practical product. for this purpose, we report, in this paper, an integrative data visualization system ivesta (<u>i</u>nteractive <u>v</u>isualization and <u>e</u>valuation <u>s</u>ystem for driven <u>t</u>est d<u>a</u>ta) for iden (integrated digital enhanced network [1]) drive test data. our objective is to project high dimensional dtd data onto well-organized web pages, such that users can visually study phone performance with respect to different factors. ivesta employs a web-based architecture which enables users to upload dtd and immediately visualize the test results and observe phone and network performances with respect to factors such as dropped call rate, signal quality, vehicle speed, handover and network delays. ivesta provides a practical test environment for phone manufacturers and network service providers to perform comprehensive study on their products from the real-world dtd.
strangeness-based feature weighting and classification of gene expression profiles. achieving high classification accuracy is a major challenge in the diagnosis of cancer types based on gene expression profiles. these profiles are notoriously noisy in that a large number of genes might be irrelevant to or weakly associated with disease phenotypes such as tumors. assigning different weights to genes could decrease or diminish the influences of those "noisy" signals, and thereby improve classification accuracy. we propose an intuitive and simple approach to cancer classification with feature weighting. our strangeness-based feature weighting method learns weights for different genes based on their classification performance. those genes with large weights can be used as discriminative genes. we demonstrate that our implementation of k-nn classifier achieved high classification accuracy on two benchmark cancer data sets. in the case of relatively low accuracy, the proposed method could be used as a feature filter. with combined feature weighting and adaboost, we achieved a better classification accuracy (100%) than using strangeness-based k-nn alone.
emerging cooperation in a public goods game with competition. in public goods games individuals contribute to create a benefit for a group. unfortunately they also attract free-riders who enjoy the benefits without contributing. despite this, in reality, cooperation does not collapse. several explanations exist for this phenomenon. in our work, individual behavioral rules play an important role in the emergence of a global, cooperative behavior. in our setting, the individual contribution depends on the motivational level of the individual, which depends on the wealth of neighbors. this in turn is associated with the wealth of the whole society. previous works have used global persistence to analyze that wealth. here we introduce new elements in the study of the public goods game, trying to bring the model closer to real world situations. we start by analysing the behavior of agents when they interact in a grid. further, we introduce competition in the game, i.e. agents can select to contribute to two public goods, instead of just one. results show an increase in wealth, hence in cooperation, when agents perform coordinated selections of goods, and when they imitate the neighbor with highest wealth.
semi-supervised dimensionality reduction in image feature space. image feature space is typically complex due to the high dimensionality of data. effective handling of this space has prompted many research efforts in the study of dimensionality reduction in the image domain. in this paper, we propose a semi-supervised reduction method that leverages relevance feedback information in the retrieval process to learn suitable linear and orthogonal embeddings. in the reduced space constructed by the proposed embedding, relevant images are kept close to each other, while irrelevant ones are dispersed far apart. the experimental results demonstrate the superiority of our method.
reachability analysis using multiway decision graphs in the hol theorem prover. in this paper, all the necessary infrastructure is provided to define a state exploration approach within the hol theorem prover. while related work has tackled the same problem by representing primitive binary decision diagram (bdd) operations as inference rules added to the core of the theorem prover, the presented approach is based on the multiway decision graphs (mdgs). mdg generalizes bdd to represent and manipulate a subset of first-order logic formulae. considering mdg instead of bdd will raise the abstraction level of what can be verified using states exploration within a theorem prover. a canonic mdgs is defined in hol as well-formed directed formulae. then, the basic mdg operations is formalized following a deep embedding approach and the correctness proof for each operation is derived. finally, the reachability analysis is implemented as a tactic that uses the mdg theory within hol.
evaluating uncertain location-based spatial queries. location-based spatial queries (lbsq) are becoming more and more useful in location-based services such as those provided by cell-phones, wireless lan and gps technologies. they support the access to information resources by taking into account the spatial context of the user when submitting the query, and the spatial location of the searched resources (instances). in fact, in a lbsq the key-selection condition is generally a constraint on the distance of the resources in the database (instances) from the user location. one deficiency of current approaches is the fact that they do not manage the uncertainty that often characterizes the knowledge of either the user location or the searched instances. a model for representing and evaluating uncertain location-based spatial queries is proposed in which besides location uncertainty also the spatial condition can be imprecise. a two-step evaluation procedure of lbsqs is outlined based on a filter and on a refinement phase.
a case-based reasoning approach for materializing software architectures onto object-oriented designs. software architectures enable to capture early design decisions in the software design process. architecture designs are materialized onto object-oriented elements trying to realize the functional and quality requirements they prescribe. the materialization of software architectures is a very complex task and requires developers with an important background of design knowledge and expertise. in practice, developers derive object-oriented counterparts of architectural elements by recalling previous design solutions used in the past to solve new similar problems. in this paper, we propose a new approach called same (software architecture materialization explorer) to assist and guide developers (particularly novice ones) in the materialization process. the approach relies on the case-based reasoning metaphor in which developers' experiences are codified into a knowledge repository so that they can be reused, by means of a systematic reasoning procedure, to derive new architecture materializations.
xbird/d: distributed and parallel xquery processing using remote proxy. in this paper, we focus on an aspect of distributed xquery processing that involves data exchanges between processor elements. we first address problems of distributed xml query processing and explain how the problems differ from traditional database problems. then, in order to achieve efficient and transparent data exchange, we adopt the use of remote proxy, in which each shipped data is wrapped in a proxy sequence, and the proxy sequence is returned to the remote peer. when accessing the proxy sequence, actual results (possibly partial results) are fetched from a data provider, and then the data provider evaluates its entity sequence in a call-by-need fashion. our scheme allows parallel query execution and reduces network traffic and redundant buffer utilization by exchanging required data directly between a consumer and a provider.
special track on real-time systems: editorial message. real-time systems are gradually turning into a public "utility"' in people's daily life. the advances in micro electro mechanical systems (mems), wireless networking, and the growth in semiconductor technology and the miniaturization of energy capacity have served as a catalyst in this process. with more and more emerging applications and architectures it is essential to revitalize and enrich the real-time systems arena. the focus of this track is on the application of both novel and well-known techniques in real-time systems design and development.
the virtual reality challenges in the health care area: a panoramic view. this paper presents a general view of computational applications in the health area, highlighting the use of virtual reality technology resources in brazil and other countries. from this initial survey, suggestions for improvements in this area were presented along with the relevant research needed to make these improvements and overcome the current obstacles.
sql-ids: a specification-based approach for sql-injection detection. vulnerabilities in web applications allow malicious users to obtain unrestricted access to private and confidential information. sql injection attacks rank at the top of the list of threats directed at any database-driven application written for the web. an attacker can take advantages of web application programming security flaws and pass unexpected malicious sql statements through a web application for execution by the back-end database. this paper proposes a novel specification-based methodology for the detection of exploitations of sql injection vulnerabilities. the new approach on the one hand utilizes specifications that define the intended syntactic structure of sql queries that are produced and executed by the web application and on the other hand monitors the application for executing queries that are in violation of the specification. the three most important advantages of the new approach against existing analogous mechanisms are that, first, it prevents all forms of sql injection attacks; second, its effectiveness is independent of any particular target system, application environment, or dbms; and, third, there is no need to modify the source code of existing web applications to apply the new protection scheme to them. we developed a prototype sql injection detection system (sql-ids) that implements the proposed algorithm. the system monitors java-based applications and detects sql injection attacks in real time. we report some preliminary experimental results over several sql injection attacks that show that the proposed query-specific detection allows the system to perform focused analysis at negligible computational overhead without producing false positives or false negatives. therefore, the new approach is very efficient in practice.
icer: a tool for finding errors in a uml model. detecting errors in an early phase of software development can help to reduce the cost of software systems. many research attempts presented a fixed set of rules to help finding errors in a model. however, flexibility is one of the characteristics during software development. the correctness of a model usually depends on many factors such as development environments. the predefined rules usually fail to provide such flexibility. this paper will apply the idea from yacc/bison to allow software engineers to define the validity of their application models in a profile. central to the profile mechanism is the instance-of relation, which is established between an application model and a profile. as a result, engineers can first define the validity of an application in a profile and thus find errors in a model when the model is not a valid instance of the profile. based on the profile mechanism, we build a tool, called icer, which can automatically help developers to check the instance-of relation between a profile and an application model. as an example, we apply the reification of the factory method pattern to illustrate how the icer tool helps to support error detection.
fuzzy and neuro-fuzzy estimates of the total height of eucalyptus trees. because of its many uses, including for paper, cellulose, and energy production, the eucalyptus is an economically important tree. the estimate of eucalyptus total height is useful for forest handling and predicting production. the objective of this work is to study the relation between a eucalyptus tree's diameter at breast height (dbh) and age to its total height. based on this data, we present decision systems developed using fuzzy logic and neuro-fuzzy systems. both proposed models are compared with classical mathematical models; the neuro-fuzzy system has the highest accuracy and precision.
service sharing with trust in pervasive environment: now it's time to break the jinx. in such as a highly dynamic and open environment, it has become a challenge to deploy multiple context-sensitive services due to the unwillingness of service provider to share resources. this apprehension to share resources stems mainly from a lack of trust. sometimes infrastructure plays pivotal role to solve this issue with dynamic access control to replace traditional static policies. but when it comes to effective resource sharing in an infrastructure-less environment we face problems such as poor storage and computational capability. in this paper, we have developed a lightweight and distributed trust model based on recommendation, which will guarantee that service providers can securely share an unlimited number of resources, limited only by their hardware and bandwidth limitations. the multi-hop recommendation protocol incorporates a flexible behavioral model to handle interactions during service sharing and usage. this protocol will also assess risk using recommendations from context-sensitive services, in the trust framework, to help ensure smooth access to resources and services.
integrating java and prolog through generic methods and type inference. p@j is a framework, based on the tuprolog open-source engine, allowing prolog code to be used as possible implementation of a java method: java annotations are used for specifying all the necessary information to fill the java-prolog gap. this framework is useful to inject a declarative, logic-based paradigm into mainstream object-oriented programming, so as to easily code functionalities related to automatic reasoning, adaptivity, and conciseness in expressing algorithms. in this paper, an extension of p@j is presented which improves the invocation technique for such prolog-implemented methods. java type inference of generic method calls is intensively used to automatically infer all the necessary paradigm mismatch information: this results in an elegant and concise invocation style, which further reduces the gap between prolog goal satisfaction and java method invocation. this new approach inspires some interesting applications: we show examples related to the implementation of abstract data types and parsers for context-free grammars.
an infrastructure for developing context aware applications in pervasive environments. this paper presents the lotus, an infrastructure to develop context-aware applications, providing the mechanisms for acquiring, representing, reasoning and delivering of contextual information. this infrastructure consists of a framework, which is composed by an api and a middleware, a language to represent contextual information and a mechanism to share and delivery contextual information.
texture feature extraction and description using fuzzy set of main dominant directions of variable scales in content-based medical image retrieval. the paper presents a new method for texture feature extraction and description. gabor wavelet transform, statistical method and fuzzy logic are used together to compute the fuzzy set of main dominant directions of variable scales of medical images of the same kind and the membership degree of dominance of each element in the fuzzy set. texture feature vector of each image is computed based on the fuzzy set. moreover, the dominance of each element in the fuzzy set is introduced into the similarity measure as weight. experiments show that the method proposed in this paper reduces the dimension of texture feature vector and alleviates heavy computation while keeping and even improving the retrieval performance.
optimized dynamic semantic composition of services. this paper proposes a design for the optimized dynamic (re)composition of services that supports various user requests and accounts for changes in user's context. the composition mechanism relies on semantic descriptions of services' functionality to compose services at runtime. the design-time component of our solution is a domain ontology that is used by the composition service for deriving different composition possibilities and for finding the appropriate similarity relations between different semantic constructs representing the user request and service descriptions. the composition mechanism combines a greedy optimization for the initial selection of candidate constituent services and a global optimization for reaching the final composition.
imputation-boosted collaborative filtering using machine learning classifiers. as data sparsity remains a significant challenge for collaborative filtering (cf, we conjecture that predicted ratings based on imputed data may be more accurate than those based on the originally very sparse rating data. in this paper, we propose a framework of imputation-boosted collaborative filtering (ibcf), which first uses an imputation technique, or perhaps machine learned classifier, to fill-in the sparse user-item rating matrix, then runs a traditional pearson correlation-based cf algorithm on this matrix to predict a novel rating. empirical results show that ibcf using machine learning classifiers can improve predictive accuracy of cf tasks. in particular, ibcf using a classifier capable of dealing well with missing data, such as na&iuml;ve bayes, can outperform the content-boosted cf (a representative hybrid cf algorithm) and ibcf using pmm (predictive mean matching, a state-of-the-art imputation technique), without using external content information.
improving flow-insensitive solutions for non-separable dataflow problems. flow-insensitive solutions to dataflow problems have been known to be highly scalable; however also hugely imprecise. for non-separable dataflow problems this solution is further degraded due to spurious facts generated as a result of dependence among the dataflow facts. we propose an improvement to the standard flow-insensitive analysis by creating a generalized version of the dominator relation that reduces the number of spurious facts generated. in addition, the solution obtained contains extra information to facilitate the extraction of a better solution at any program point, very close to the flow-sensitive solution. to improve the solution further, we propose the use of an intra-block variable renaming scheme. we illustrate these concepts using two classic non-separable dataflow problems --- points-to analysis and constant propagation.
cluster-based novel concept detection in data streams applied to intrusion detection in computer networks. in this paper, a cluster-based novelty detection technique capable of dealing with a large amount of data is presented and evaluated in the context of intrusion detection. starting with examples of a single class that describe the normal profile, the proposed technique detects novel concepts initially as cohesive clusters of examples and later as sets of clusters in an unsupervised incremental learning fashion. experimental results with the kdd cup 1999 data set show that the technique is capable of dealing with data streams, successfully learning novel concepts that are pure in terms of the real class structure.
special track on enterprise information systems: editorial message. enterprise information systems are those intended to support business in the contemporary knowledge-based global economy. therefore, developing and deploying these systems means to deal with complex and cross-disciplinary enterprise integration issues. eis area embraces a plethora of subjects that range from enterprise resources planning (erp), enterprise content management (ecm) and customer relationship management (crm) to decision support systems and business intelligence. this track complements other sac'2008 tracks such as database theory, technology, and applications, data mining, data streams, document engineering, e-business applications, information access and retrieval, organizational engineering, requirement engineering, software engineering, and computer security, by stressing technology and business integration issues.
information systems implementation: the big picture. the ability to adapt to changes has emerged as a new paradigm for successful business operations. the paper outlines an approach for the deployment of enterprise information systems taking organizational transformation into account. a framework for enterprise architecture is introduced which links business-, application-, and infrastructure architecture. it is the core reference for the construction of the business and it landscape. blueprints give a comprehensive view on the building blocks of architecture and how the interact and provide the fundamental decision basis for the deployment of enterprise information systems. furthermore criteria and process how to analyze the adaptability of information systems are described. based on the assessment principal strategies for information system deployment are pointed out.
sscm: middleware for structure-based service collaboration. the collaboration of services scattered over the internet is often required in solving a complicated scientific problem or finishing a complex business process. centralized client/server architecture used in traditional service collaboration mechanism such as workflow has exhibited many weaknesses. we adopt the concept from peer-to-peer computing and synergetics, and introduce an innovative middleware for structured-based service collaboration, in which each service node belongs to one or more structured collaboration organizations and is allowed to join and leave (planned departure or sudden failure) freely. we also propose neighborhood-based maintenance mechanism to cope with the dynamics of collaboration organization structure in a decentralized manner.
enterprise ontology based splitting and contracting of organizations. our research program aims at finding and testing principles for deciding on organization splits and starting cooperation over the split. we tested a method to make underpinned choices on the organization split and to ensure completeness in contracting. using actors from enterprise ontology as organization building blocks of a dutch governmental agency, experts constructed their own gut feeling organization split and systematically listed (a) ownership of assets (b) quality of business and information services and (c) critical chain-dependencies. the proposed organization split is, confirming an earlier experiment, quite close to graph theory based calculated alternatives. the listing of contracting items helped to determine in a fast and shared way subsequent implementation steps, e.g., ensuring mutual information supply and formulating performance indicators.
ppepr: plug and play electronic patient records. the integration of electronic patient record (epr) systems is at the centre of many of the new regional and national initiatives to integrate clinical processes across department, region, and national levels. web service technologies offer significant solutions to provide an interoperable communication infrastructure but are unable to support precise definitions for healthcare messages, functionality, and standards, required for making meaningful integration. the lack of interoperability within healthcare standards adds complexity to the initiatives. this heterogeneity exists within two versions of same standard (e.g. hl7), and also between standards (e.g. hl7, openehr, cen tc/251 13606). we therefore introduce an integration platform ppepr (plug and play electronic patient records), which is based on the principles of a semantic service-oriented architecture (ssoa). ppepr solves the problem of interoperability at the semantic level. a key focus of ppepr is that once a patient information is captured, should be available for use across all potential care processes.
a system for modal and deontic defeasible reasoning. defeasible reasoning is a well-established nonmonotonic reasoning approach that has recently been combined with semantic web technologies. this paper describes modal and deontic extensions of defeasible logic, and shows how these extensions can bbe used for modelling multi-agent systems and policies.
a software architecture for ontology-driven situation awareness. human operators of large-scale control systems face the problem of information overload induced by the large amount of information provided by multiple heterogeneous and highly-dynamic information sources. situation-aware information systems support operators by the aggregation of the available information to meaningful situations. ontologies are a promising technology for realizing such systems, because of their semantically-rich kind of knowledge representation. the cross-cutting role of ontologies and the streaming character of situation awareness, however, challenge the design of an appropriate software architecture. in this paper, we propose a domain-independent software architecture based on a core ontology for situation awareness which leverages the reusability and the scalability of involved software components. this is achieved by the application of the well-known software architecture pattern pipes-and-filters. the proposed architecture is demonstrated by examples from the field of road traffic management. in addition, we contribute several lessons learned which should be helpful for developing ontology-driven information systems in general.
a new algorithm for data discretization and feature selection. data discretization and feature selection are two important tasks that can be performed prior to the learning phase of data mining algorithms and can significantly reduce the processing effort of the learning algorithm. in this paper, we present a new algorithm, called omega, for data preprocessing. our proposed algorithm performs simultaneously data discretization and feature selection. some experiments were performed to validate the effects of the preprocessing performed by the omega algorithm in the results of the c4.5 algorithm (a well-known decision tree-based classifier). the results indicates that the proposed algorithm omega is well-suited to both, data discretization and feature selection, being appropriate for data pre-processing.
efficient concept clustering for ontology learning using an event life cycle on the web. ontology learning integrates many complementary techniques, including machine learning, natural language processing, and data mining. specifically, clustering techniques facilitate the building of interrelationships between terms by exploiting similarities of concepts. with the rapid growth of the web, online information has become one of the major information sources. the ontology learning process where traditional clustering algorithms are involved tends to be slow and computationally expensive when the dataset is as large as the web. to address this problem, we present an efficient concept clustering technique for ontology learning that reduces the number of required pairwise term similarity computations without a loss of quality. our approach is to identify relevant terms using a computationally inexpensive similarity metric based on an event life cycle in online news articles. then, we perform more sophisticated similarity computations. hence, we can build clusters with high precision/recall and high speed. without a loss of clustering quality, our framework reduces the number of required computations from o(n2) to (n + l2) (l &laquo; n) where n is the number of candidate concepts. our experimental results show that clustering based on our similarity framework can construct concept clusters 1541.07% faster than clustering with all term pair similarity computations.
on the performance of employing presence services in p2p-based network management systems. the use of notifications to report the status of underlying communication networks has a crucial impact on the performance of the managed network itself. presence services, which are implemented using notification messages, have been designed with the objective to provide ways of delivering accurate presence information to interested parties. however, up to now, the use of presence services in the network management discipline has not been properly addressed. is this paper, we propose an architecture that introduces presence services into traditional network management processes. we evaluated, through a system prototype implementation, the feasibility of using diverse presence services solutions as management tools and compare their performance against to each other. we present the results of a set of experiments regarding the propagation delay of the two main steps of a presence service, i.e., registration and notification. those results allows a network administrator to choose which presence service solution is more adequate for the administrator's necessities, thus helping to improve the notification process.
a requirements refinement framework. requirements refinement is not only a process to derive specifications, but also a necessary means towards preparing architectural designs. in this paper, we present a novel refinement framework, comprising methods and process, to move from requirements to design. the framework consists of multiple abstraction levels capturing requirements of different kind and granularity, allows the derivation of designer and user perspectives separately, introduces stages of activities to be carried out in the process, includes refactoring-based methods to carry out the refinement, and provides a structure that allows easy traceability between requirements.
towards an integrative human pathway database for systems biology applications. while there are more than 217 online pathway databases of different coverage and quality as of september 2007, our knowledge of human pathways is still far from complete. it has been challenging to develop pathway tools and database resources that could expand the coverage of existing annotated pathway data by integrating these resources both at the syntactic and semantic levels. while developing the human pathway database (hpd), we use data warehousing techniques and a unified pathway data model to integrate a total of 1,895 pathways and 10,631 molecular entities from four different annotated and predicted pathway resources in human. hpd provides a comprehensive and integrated view linking human proteins, genes, rnas, signaling reactions, gene regulatory events for future systems biology applications. we studied pathways in the database for their merging potentials and showed a preliminary pathway merging result as 2-d clusters. we also examined pathway scale and the distribution of pathway-spanning proteins, pathway characteristics that suggest small pathways and large pathways may still be under-represented in the hpd. we also found many proteins with important energy metabolism, cell growth, and cell differentiation functions span across vast number of pathways. the raw data for hpd can be queried at: http://discover.uits.indiana.edu:8340/spathway/s_pathway/
designing interaction behaviour in service-oriented enterprise application integration. in this paper we present an approach for designing interaction behaviour in service-oriented enterprise application integration. the approach enables business analysts to actively participate in the design of an integration solution. in this way, we expect that the solution meets its integration goal and business requirements. the approach consists of four steps: (i) represent the existing services to be integrated in platform-independent models; (ii) derive the models of the goals and business requirements of the services; (iii) check whether an abstract interaction representing the integration goal may occur between the services; and (iv) if so, (recursively) refine the interaction into a realisable design. the approach is characterised by an early check on the possibility of an integration solution, clear expressions of the integration goal and business requirements, and explicit use of the descriptions of the existing services as bottom-up knowledge during refinement. to support the approach, we present a set of patterns of interaction refinement as guidelines in refining abstract interactions.
context-aware middleware architecture for vertical handover support to multi-homed nomadic mobile services. to accommodate the requirements such as high usability and personalization of 4g (mobile) networks, conventional handheld single network-interface mobile devices are evolving into multi-homed devices. moreover, owing to the recent advances in the mobile middleware technologies, hardware technologies and association with the human user, handheld mobile devices are evolving into data producers and in turn acting as nomadic mobile service (nms) providers. for these devices, a vertical handover support is essential for the improved and reliable nms delivery. also, the fulfillment of the required qos by the nms is bounded by the end-to-end qos (e2eqos) provided by the underlying heterogeneous networks. to deal with these aspects, we propose a context-aware middleware architecture supporting vertical handover for the nmss hosted on the handheld mobile devices. we emphasize the following features of the proposed middleware: 1) context-aware computing based approach which uses an extensive set of context information collected from the mobile device and a fixed network; 2) provisioning of and interaction with the end-to-end qos (e2eqos) predictions context source in the fixed network to obtain near-accurate estimation of the e2eqos at a certain geographic location and to reduce unnecessary power usage in searching for available networks.
optical flow using color information: preliminary results. optical flow cannot be completely determined only from brightness information of images, without introducing some assumptions about the nature of movements in the scene. color is an additional natural source of information that facilitates the solution of this problem. this work aims to illustrate the improvement in the optical flow estimation by using color information through experimental results.
towards a service-based middleware layer for runtime environments. natively compiled, binary-code application programs are typically thought of as executing on the "raw" operating system. however, they do in fact utilize a bare-bones middleware layer---the dynamic linker. this paper presents a service-based view of an expanded run-time environment in which the current dynamic linker is only a core service, and other middleware-type services are available to the application and its components (shared libraries). this paper then describes a prototype implementation of such an environment, called sbrt, or service-based run-time. sbrt also contains a unified event-based interface that allows for customized middleware services by means of an extension mechanism.
a location-aware information browser implemented on brew-based mobile phones. we present a method to implement a location-aware information browser on mobile phones. our location-aware information browser is designed to look for nearby hidden points of interests in mobile computing environments. the method we developed provides two benefits: the first benefit is to improve the performance of transforming and rendering a map by combining filtering techniques of a spatial database and fixed-point arithmetic techniques. our method is designed to deal with two kinds of minimum bounding rectangles to apply such conventional effective processing techniques of a spatial database to our browser. the second benefit is to handle large or long map elements in brew-based computing environments by clipping techniques of computer graphics. we clarified the feasibility and effectiveness of our method by several experiments.
special track on advances in computer simulation (acs): editorial message. computer simulation approaches have established as fundamental conceptual and practical instruments for the analysis of growingly complex systems, both for industry and business applications as well as in the scientific research context. computational models and simulators are currently employed in the most different application areas, ranging from urban modeling and planning to logistics and production, from biology to social sciences. consequently, the adopted modeling approaches and methodologies, as well as simulation project life-cycles, techniques for the evaluation and interpretation of simulation results are often very distant.
advanced preference query processing for e-commerce. travel and tourism represents the leading domain for applications in b2c e-commerce. thus, it deserves highest attention. due to insufficient search engines, however, arranging a trip on current online travel portals is often not as easy as it seems. we present a novel approach for an advanced processing of database queries dealing with individual as well as global preferences of customers. our approach also comprises the deployment of existing preference search technology to the tourism domain of electronic commerce. consequently, the tedious empty-result-effect is avoided. thereby, a novel, personalized search process delivering custom-tailored products is enabled for tourism and in general for e-commerce, respectively. a first prototype implementing our advanced search has shown promising results.
an efficient algorithm for a sharp approximation of universally quantified inequalities. this paper introduces a new algorithm for solving a subclass of quantified constraint satisfaction problems (qcsp) where existential quantifiers precede universally quantified inequalities on continuous domains. this class of qcsps has numerous applications in engineering and design. we propose here a new generic branch and prune algorithm for solving such continuous qcsps. standard pruning operators and solution identification operators are specialized for universally quantified inequalities. special rules are also proposed for handling the parameters of the constraints. first experimentation show that our algorithm outperforms the state of the art methods.
computing the real variety of an ideal: a real algebraic and symbolic-numeric algorithm. solving systems of polynomial equations is a classical problem of mathematics with an emerging number of modern applications, such as coding theory, robotics, computational statistics, etc. its importance is reflected by the broad literature that deals with algorithms, ranging from numerical continuation methods to exact methods based e.g. on gr&ouml;bner or border bases; see e.g. the monograph [1] and the references therein. however in many practical applications one is only interested in real solutions. the literature tailored to the problem of real solving systems of polynomials is by far not as broad.
publish/subscribe architecture for mobile ad hoc networks. publish/subscribe architectures have been widely studied and applied in wired networks. however, their deployment on mobile ad hoc networks still presents a lot of challenges. this work proposes and analyzes a solution for such networks using the nodes' movement to disseminate publications to the whole network with few transmissions. our proposal does not build dissemination trees which incur in a high cost to keep them updated due to constant changes in the topology, and does not even require beacons exchanges in order to sustain a neighborhood table. our experiments show that we are able to achieve better results than a gossip-based algorithm and other solutions found in the literature.
total order broadcast on pervasive systems. total order broadcast protocols are important tools to ensure coherence across distributed systems. contrarily to classical distributed systems, pervasive systems bring important constraints related to the performance and reliability of the network and the availability of the devices (laptops, pdas and cellular telephones). we propose in this paper a self-stabilizing group membership service that helps a token-based total order broadcast protocol to progress in a volatile environment. this group membership service is organized in two hierarchical levels so that unstable nodes are kept in the group without interfering with the total order broadcast protocol. as a result, we avoid expensive membership view changes while keeping the coherence among the nodes.
ranking with tagging as quality indicators. as more and more web documents are getting tagged, using tags to enhance the quality of retrieval has become an emerging challenge in the retrieval. in a clear contrast to traditional retrieval techniques solely focusing on content-based relevance to query keyword, we aim at enhancing the retrieval with additional contextual information obtained from tags, e.g., popularity or reliability of the document. toward the goal, this paper views a tag as a "quality indicator" and classifies tags with various characteristics adopting the taxonomy proposed in data quality modeling literatures. we then develop a unified framework for supporting arbitrary quality indicators in the taxonomy and evaluate its effectiveness and efficiency over both real-life and synthetic data.
data sharing vs. message passing: synergy or incompatibility?: an implementation-driven case study. one reasonable categorization of coordination models is into data sharing or message passing, based on whether the information necessary to coordination is persistently stored and shared, or instead is only transiently available during communication. generally speaking, approaches based on data sharing are more expressive and provide full decoupling in space and time. the alternative approach requires the simultaneous presence of the coordinated parties, but is typically more scalable. prominent examples are, respectively, tuple spaces and publish-subscribe. an open research question is whether it is possible to exploit in synergy the best of these two approaches, e.g. by implementing the more complex data sharing coordination on top of the more lightweight message passing one. in this paper, we seek an answer to this question in a pragmatic way: we analyze an implementation of the lime tuple space middleware on top of reds, an open source publish-subscribe system. our implementation-driven style of investigation forces us to face details that do not surface when reasoning in the abstract about the nature and expressiveness of the models. we report about lessons we learned in this experience, and propose an extension to the publish-subscribe model that, albeit useful per se, constitutes a more effective foundation for data sharing coordination models.
comparing keywords and taxonomies in the representation of users profiles in a content-based recommender system. this work investigates the use of keywords and classes to represent user's profiles in order to improve a content-based recommender system. the techniques were implemented and tested in a recommender system for a website that gathers commercial ads. ads are posted by individuals and contain a title and a textual description. profiles are created and maintained through the analysis of ads seen by the user during a certain period of time and may be represented by classes, keywords or both kinds. keywords are automatically extracted from the textual description of the ads. classes come from a taxonomy defined by the website. ads must be posted within a leaf class of the taxonomy. the items to be recommended are ads containing keywords associated to the user in his/her profile and/or ads classified in the leaf-classes present in the user's profile. the paper demonstrates that the combination of both techniques (keywords and classes) outperforms the use of each one separately.
a vehicular waiting time heuristic for dynamic vehicle routing problem. in the last years, the vehicle routing problem (vrp) has been receiving increasing a special attention due its importance in the distribution of products. considering demands that can appear during the service day, this work solves the dynamic vrp (dvrp) with support of the environment simulator, capable to emulate the behavior of the vehicular fleet in a geographic 2d space. this work presents two main contributions: (i) the environment simulator that can be used to standardize dvrp test cases; and (ii) a vehicular waiting time heuristic (vwth), that delays the attendance of demand with the meaning of reducing the total distance traveled by vehicular fleet. the proposed heuristic is tested by four optimization algorithms (simulated annealing, grasp, memetic algorithm and hill climbing), and submitted to statistical tests for better conclusions. the tests showed, with 95% of confidence, that the vwth is able to improve significantly the metaheuristics results.
a ubiquitous computing environment for medical education. this paper proposes a ubiquitous computing environment for medical education, whose kernel is a web-based system with collaborative tools, to support the interactions and computational tasks among different actors involved in the medical education process. in order to allow this environment to be ubiquitous, the web pages of this system are adapted, through a content adaptation architecture, so they can be accessed by a huge variety of small mobile devices (e.g., cell phones, smart phones, tablets, personal digital assistants).
information extraction from scanned documents by stochastic page layout analysis. we propose a stochastic context-free grammar for extracting information from scanned document images. the grammar is designed to disambiguate layout analysis and utilize both layout and text features. we applied this grammar to the problem of extracting bibliographic information from scanned academic papers and found that it can accurately extract information.
template design and automatic generation of controllers for industrial robots. the basic theory of supervisory control of discrete-event systems is extended with the notion of templates, which simplifies the modeling of controllers since one can work with conceptual designs. in this work, software which provides support for the new design approach is presented along with its application to a robotic testbed.
semantic web services selection improved by application ontology with multiple concept relations. being able to determine and quantify the semantic similarity between ontological concepts is a key requirement for the discovery, selection, and composition of semantic web services. especially concept similarity is calculated between different service ontologies, it is still a problem. in this paper, we propose an ontology-based approach for semantic service selection which takes into account the heterogeneity of service descriptions. the approach is based on an application ontology (ao), which is merged by different service ontologies and constructed as a semantic net with multiple concept relations. empirically the proposed method is shown to improve the quality of service selection.
on the performance of persistent connection in modern web servers. in the development of http protocol, the technique to overlap multiple http requests and replies on single tcp connection, called 'keep-alive' or 'persistent connection', has won great success. it is already verified that, persistent connection could help to save the cost of frequently creating tcp connection, and could also reduce the number of operations such like forking and destroying process. many years passed, persistent connection mechanism has been implemented widely to support all kinds of web services. however recently, dramatic changes to networking conditions and server computing capacity challenge the motivations of such mechanism and reveal some of its drawbacks. this paper models the connection management procedure in concurrent web servers with petri nets, and determines the parameters for the model by measuring a bunch of key metrics in modern web servers and networks. plus, experiments are carried out in real modern test-bed with real traffic. the analytical results yielded by the model, along with experimental results, help us to clarify the negative role that persistent connection actually plays in modern web servers, especially in those busy ones.
a light-weight feedback method for reconstructing a document vector space on a feature extraction model. in this paper, we propose a document retrieval system with a light-weight feedback method for reconstructing a document vector space, which is developed on a feature extraction model (fem). fem makes it possible to realize a light-weight creation of vector spaces by feature terms extracted from the pre-prepared documents and we can apply the feedback method dynamically to reconstruct the vector spaces based on intensions of users. retrieval results can be improved through the proposed feedback process because the distributions of documents on the reconstructed vector space are arranged properly according to purposes and interests of users.
design pattern detection by template matching. in this paper, we adopt a template matching method to detect design patterns from a software system by calculating their normalized cross correlation. because design patterns document flexible design ideas, there can be various ways of implementing them. in our approach, not only the exact matches of pattern instances are detected from system source code, but also the variations of pattern candidates can be identified. based on our method, we provide tool support and perform experiments on different large open-source systems.
a framework for dependable qos adaptation in probabilistic environments. distributed protocols executing in uncertain environments, like the internet, had better adapt dynamically to environment changes in order to preserve qos. in a previous work, it was shown that qos adaptation should be dependable, if correctness of protocol properties is to be maintained. in this paper we provide concrete strategies and methodologies to improve the implementation of dependable qos adaptation. during its lifetime, a system alternates periods where its temporal behavior is well characterized, with transition periods where a variation of the environment conditions occurs. our method is based on the following: if the environment is generically characterized in analytical terms, and we can detect the alternation of these stable and transient phases, we can drastically improve the effectiveness of dependable qos adaptation. to prove our point, we conduct an evaluation based on "synthetic" data flows generated from one or more probabilistic distributions, and we show that the proposed strategies can indeed be effective and still dependable in the considered cases.
special track on dependable and adaptive distributed systems: editorial message. distributed systems, services and databases are at the core of the information society and increasingly pervade many aspects of our daily lives. while mobility and pervasiveness require support for systems that adapt themselves to changing environments, resources, and user needs, the middleware infrastructures become more and more heterogeneous and complex. this trend is further fueled by the emergence of service oriented computing. in addition, we can see an increasing demand for dependability and security of such systems, taking into account the software as well as the surrounding environment. this mismatch between increasing demand for dependability on one hand and a degradation of dependability caused by complexity, scale, and dynamics has recently been termed by laprie as the "dependability gap".
repart: a reputation-based simulation tool for partnership formation. reputation is a concept diffused among several research fields, such as social sciences and economics. recently, it has been used in the multi-agent systems field, and several different models for its calculation have been proposed. this work presents a simulation tool, named repart, whose goal is the study of partnership formation based on reputation.
user interface derivation from business processes: a model-driven approach for organizational engineering. this paper defines a model-driven approach for organizational engineering in which user interfaces of information systems are derived from business processes. this approach consists of four steps: business process modeling in the context of organizational engineering, task model derivation from the business process model, task refinement, and user interface model derivation from the task model. each step contributes to specify and refine mappings between the source and the target model. in this way, each model modification could be adequately propagated in the rest of the chain. by applying this model-driven approach, the user interfaces of the information systems are directly meeting the requirements of the business processes and are no longer decoupled from them. this approach has been validated on a case study in a large bank-insurance company.
formal definition of measures for uml statechart diagrams using ocl. the informal definition of a measure in natural language is ambiguous, so it must be accompanied by a precise and formal definition, for avoiding misunderstanding and misinterpretation. in this paper we show the formal definition of measures for uml statechart diagrams using ocl, upon the uml statechart metamodel. the use of a formal definition upon a metamodel (where the main concepts and relationships are modelled) assure that measures capture the concepts they intend for and could facilitate the implementation of measures extraction tools.
augmented vision for medical applications. computer vision techniques for tracking real objects as surgical tools and organs of patients are been integrated in medical scenarios. we present a marker-based approach followed by a rigid registration procedure to align real and virtual objects. a maxillofacial surgery is being used as case study and our method provides virtual and augmented aid to the surgeon while performing osteotomy tasks. results reached with the proposed system shows to be acceptable when compared with previous work.
a reusable object-oriented design to support self-testable autonomic software. as the enabling technologies of autonomic computing continue to advance, it is imperative for researchers to exchange the details of their proposed techniques for designing, developing, and validating autonoinic systems. many of the software engineering issues related to building dependable autonomic systems can only be revealed by studying detailed designs and prototype implementations. in this paper we present a reusable object-oriented design for developing self-testable autonoinic software. our design aims to reduce the effort required to develop autonomic systems that are capable of runtime testing. furthermore, we provide low-level implementation details of a case study, autonomic job scheduler (ajs), developed using the proposed design.
cross-organizational erp management: how to create a successful business case? this paper deals with the development and use of business cases in support of cross-organizational enterprise resource planning (erp)-enabled e-business integration initiatives. in order to ensure that such a project starts successfully, we will focus on pre-implementation activities. we propose a set of business case guidelines that emphasize the importance of benefits management during erp implementations.
topology determination and isolation for implicit plane curves. a method is proposed to generate an isolation for a plane curve, which is a set of boxes covering the curve, having the same topology as the curve, and approximating the curve to any given precision. the method uses symbolic computation to guarantee correctness and uses interval analysis whenever possible to enhance efficiency. this leads to a quite effective hybrid method for plane curve isolation.
simulating antigenic drift and shift in influenza a. computational models of the immune system and pathogenic agents have several applications, such as theory testing and validation, or as a complement to first stages of drug trials. one possible application is the prediction of the lethality of new influenza a strains, which are constantly created due to antigenic drift and shift. here, we present an agent-based model of immune-influenza a dynamics, with focus on low level molecular antigen-antibody interactions, in order to study antigenic drift and shift events, and analyze the virulence of emergent strains. at this stage of the investigation, results are presented and discussed from a qualitative point of view against recent and generally recognized immunology and influenza literature.
knowledge-based coordination with a reliable semantic subscription mechanism. semantic technologies promise to solve challenging problems of current enterprise information systems, e.g., the integration of heterogeneous information clients and the evaluation of complex data dependencies. as many of these problems also apply to coordination applications, recent research initiatives have proposed to integrate coordination models with semantic technology. in this paper, we present such an integrated coordination model which combines logic-based reasoning with a reliable semantic subscription mechanism. we present a formal definition of the model's behavioral semantics and investigate the added value of using semantic technologies. finally, we draw first conclusions about the practical applicability of the proposed approach based on performance benchmarks of a prototype implementation.
a flexible qos-aware routing protocol for infrastructure-less b3g networks. current mobile devices support multiple network technologies and network composition via such devices can enable service provisioning across heterogeneous networks. one of the key challenges for realizing this view is inter-domain routing. indeed, given the diversity of involved network technologies and infrastructures, a flexible routing protocol that takes into account their quality properties and dynamics is an important requirement. in this paper, we present a flexible quality-aware routing protocol for infrastructure-less b3g environments that enables discovery of routes with optimal bandwidth, delay or cost according to the preference of each client. the protocol is based on the optimized link-state routing (olsr) protocol and is designed to enable computation of quality-aware routes in multi-network environments. we detail the protocol, discuss its deployment and provide experimental results.
length-lex bound consistency for knapsack constraints. this paper considers the length-lex domain for set-variables in constraint programming which includes not only membership but also cardinality and lexicographic information. the paper studies how to enforce bound consistency on a knapsack constraint over a set variable in this domain and proposes a bound-consistency algorithm which runs in o(c log n) time with a one-time preprocessing cost o(cn2) when the constraint is posted.
an extensible source-level debugger. standard debuggers are limited in the amount of analysis that they perform in order to assist with debugging. this paper presents udb, a source-level debugger for the unicon programming language with a novel architecture and capabilities. udb combines classical debugging techniques such as those found in gdb with a growing set of automatic debugging extensions. udb tests the hypotheses that a debugger built on top of a high-level framework enables better debugging capabilities as well as easier and more efficient extension than ordinary debuggers.
building a self-healing embedded system in a multi-os environment. in this paper we describe our approach to improve dependability of a commodity os for embedded systems. usually it is too difficult for end-users to resolve the problem inside a single os, especially for embedded systems. we propose a self-healing mechanism for linux kernel to improve the system dependability without any operations by administrators. this paper presents our white box approach for monitoring and recovering linux kernel. key components are a system monitor and a virtual machine monitor. the system monitor is used to detect the inconsistency of data structures inside linux kernel. the virtual machine monitor provides a multi-os environment and it isolates the system monitor from linux kernel. in a multi-os environment, the system monitor is able to resolve failures inside linux kernel without stopping crucial services running on another os. we have developed a prototype for an embedded system to verify our approach. the experiment results show that our system can remove hidden processes and reload buggy kernel modules. the performance evaluation results show that our self-healing mechanism can be used even when linux kernel is heavily-loaded and the overhead of the system monitor is vanishingly small in actual use.
an optimistic technique for transactions control using rest architectural style. soa is a service oriented architecture that allows development of software with interoperability and weak coupling. nowadays ws-* is the most used soap-based specification set for constructing web services. rest is an architectural style that permits the development of services in a simpler way and obeys the soa's paradigm, however, it does not provide standardized support to address some nonfunctional requirements of services, for instance, security, reliability, transaction control. this article proposes a technique, based on rest, to support the web services transactional control implementation. the technique uses the optimistic method to control distributed systems transactions. an example of application was implemented to show its feasibility.
an implementation substrate for languages composing modularized crosscutting concerns. we present the implementation of several programming languages with support for multi-dimensional separation of concerns (mdsoc) on top of a common delegation-based substrate, which is a prototype for a dedicated mdsoc virtual machine. the supported mdsoc language constructs range from aspects, pointcuts and advice to dynamically scoped and activated layers. the presented language implementations show that the abstractions offered by the substrate are a viable target for high-level language compilers.
applying semantic web technology to feature modeling. feature models are models used to capture differences and commonalities between software features, enabling the representation of variability within software. there are many variations of feature models and different notations are often used to represent the same information. currently support for validating or integrating feature models is missing. in this paper, we provide an ontology framework for feature modeling which consists of an ontology that formally provides a specification for feature models. in addition, we provide means to integrate segmented feature models and provide a rule based model consistency check and conflict detection. we use swrl rules to implement the rules and a dl reasoner to evaluate the rules and infer extra interesting information regarding the variability of the software.
hivsetsubtype: software for subtype classification of hiv-1 sequences. an automated web based tool for assigning hiv-1 pure and recombinant subtypes within unaligned sequences is presented. the system combines the blast search algorithm and the recombination identification program for genetic subtyping of hiv-1. the software was validated through combined analysis of simulated and other hiv-1 real data.
architecture-driven requirements engineering. this paper discusses the impact of the enterprise architecture paradigm on requirements engineering. these ideas have been refined and validated during a case study performed at a large dutch insurance provider. an account of the preliminary results from this case study is also included.
simulating business processes with epml.sim. business process simulation (bps) is widely acknowledged as an effective technique to increase the chance for success of business process (re-)engineering projects and, in general, to drive strategic business decisions. business processes are complex entities resulting from the coordination of several users and software systems, potentially spanning across different organizations. simulating a business process is then not just about modeling the structure of the process but also its logic (the decisions that have to be taken during a process), the structure of the interested organization(s) and the environment the process operates in. most of the existing bps tools, however, assume rather simple models which can turn out to be a limiting factor when they do not fit the real world business process that has to be simulated. in this paper we present a tool that can be used to simulate business processes with complex structure and logic and eases the interaction with complex organizational and environment models, addressing the limitations of the existing simulation tools.
celling shim: compiling deterministic concurrency to a heterogeneous multicore. parallel architectures are the way of the future, but are notoriously difficult to program. in addition to the low-level constructs they often present (e.g., locks, dma, and non-sequential memory models), most parallel programming environments admit data races: the environment may make nondeterministic scheduling choices that can change the function of the program. we believe the solution is model-based design, where the programmer is presented with a constrained higher-level language that prevents certain unwanted behavior. in this paper, we describe a compiler for the shim scheduling-independent concurrent language that generates code for the cell broadband heterogeneous multicore processor. the complexity of the code our compiler generates relative to the source illustrates how difficult it is to manually write code for the cell. we demonstrate the efficacy of our compiler on two examples. while the shim language is (by design) not ideal for every algorithm, it works well for certain applications and simplifies the parallel programming process, especially on the cell architecture.
uncertainty apportionment for air quality forecast models. effective environmental protection policy making depends on comprehensive and accurate air quality model (aqm) prediction results. the confidence level associated with the model prediction, as well as the uncertainty sources that contribute to the prediction uncertainty are important information that should not be neglected when interpreting simulation results. in this work, we explore the capability of the polynomial chaos (pc) method for uncertainty quantification (uq) and propose a uncertainty apportionment (ua) approach that can be easily applied to any forecast models. the numerical tests on the stem (sulfur transport eulerian model) for the northeast region of the united states provide a categorization for the major uncertainty sources that contribute to the uncertainty in the ozone concentration prediction. this information can be used to guide the optimal investment decisions as to which input measurement accuracy should be improved to make the maximum impact on reducing the uncertainty in the prediction result.
semi-supervised co-training and active learning based approach for multi-view intrusion detection. although there is immense data available from networks and hosts, a very small proportion of this data is labeled due to the cost of obtaining expert labels. this proves to be a significant bottle-neck for developing supervised intrusion detection systems that rely solely on labeled data. in spite of the data being collected from real network environments and hence potentially holding valuable information for intrusion detection, such systems can not exploit the remaining unlabeled data. in this work, we intelligently leverage both labeled and unlabeled data. also, intrusion detection tasks naturally lend themselves into a multi-view scenario, and can benefit significantly if these multiple views are combined meaningfully. in this paper, we propose a co-training method framework for intrusion detection, which is a semi-supervised learning method and can not only utilize unlabeled data, but can also combine multi-view data. we also employ an active learning framework where statistically ambiguous parts of the unlabeled data are identified, which can then be labeled by an expert. this allows for minimal expert labeling while ensuring that the labels obtained from the expert are most informative. in our experiments, we demonstrate that leveraging the unlabeled data using our proposed method significantly reduces the error rate as compared to using the labeled data alone. in addition, our proposed multi-view method has a lower error rate than using a single view.
impact of nvram write cache for file system metadata on i/o performance in embedded systems. file systems make use of part of dram as the buffer cache to enhance its performance in traditional systems. in this paper, we consider the use of non-volatile ram (nvram) as a write cache for metadata of the file system in embedded systems. nvram is a state-of-the-art memory that provides characteristics of both non-volatility and random byte addressability. by making nvram a write cache for dirty metadata, we retain the same integrity of a file system that always synchronously writes its metadata to storage, while at the same time improving file system performance to the level of a file system that always writes asynchronously. to show quantitative results, we develop an embedded board with nvram and modify the vfat file system provided in linux 2.6.21 to accommodate the nvram write cache. the experimental results show that substantial reductions in execution time are possible from an application viewpoint. another consequence of the write cache is its benefits at the ftl layer, leading to improved wear leveling of flash memory and increased energy savings, which are important measures in embedded systems.
applying test-driven code search to the reuse of auxiliary functionality. software developers spend considerable effort implementing auxiliary functionality used by the main features of a system (e.g. compressing/decompressing files, encryption/decription of data, scaling/rotating images). with the increasing amount of open source code available on the internet, time and effort can be saved by reusing these utilities through informal practices of code search and reuse. however, when this type of reuse is performed in an ad hoc manner, it can be tedious and error-prone: code results have to be manually inspected and extracted into the workspace. in this paper we introduce the use of test cases as an interface for automating code search and reuse and evaluate its applicability and performance in the reuse of auxiliary functionality. we call our approach test-driven code search (tdcs). test cases serve two purposes: (1) they define the behavior of the desired functionality to be searched; and (2) they test the matching results for suitability in the local context. we present codegenie, an eclipse plugin that performs tdcs using a code search engine called sourcerer. our evaluation presents evidence of the applicability and good performance of tdcs in the reuse of auxiliary functionality.
bayesian bot detection based on dns traffic similarity. bots often are detected by their communication with a command and control (c&c) infrastructure. to evade detection, botmasters are increasingly obfuscating c&c communications, e.g., by using fastflux or peer-to-peer protocols. however, commands tend to elicit similar actions in bots of a same botnet. we propose and evaluate a bayesian approach for detecting bots based on the similarity of their dns traffic to that of known bots. experimental results and sensitivity analysis suggest that the proposed method is effective and robust.
defending online reputation systems against collaborative unfair raters through signal modeling and trust. online feedback-based rating systems are gaining popularity. dealing with collaborative unfair ratings in such systems has been recognized as an important but difficult problem. this problem is challenging especially when the number of honest ratings is relatively small and unfair ratings can contribute to a significant portion of the overall ratings. in addition, the lack of unfair rating data from real human users is another obstacle toward realistic evaluation of defense mechanisms. in this paper, we propose a set of methods that jointly detect smart and collaborative unfair ratings based on signal modeling. based on the detection, a framework of trust-assisted rating aggregation system is developed. furthermore, we design and launch a rating challenge to collect unfair rating data from real human users. the proposed system is evaluated through simulations as well as experiments using real attack data. compared with existing schemes, the proposed system can significantly reduce the impact from collaborative unfair ratings.
workflow management for high volume supernova search. observational astrophysics has recently become a data-intensive science after many decades of relative data poverty. as a result, many of the algorithms developed for processing astronomical data, although well established for low-volume data capture, do not scale well to today's high-volume sky surveys and transient searches. specifically, problems may occur with data transfer, workflow management, efficient parallelization, and integration of legacy code. observational astrophysics workflows present computational challenges unique in high performance computing, including 24/7 operations, time-critical processing, and very large numbers of relatively small data files which must all be processed and archived. we present a case study based on sunfall, a distributed, parallel scientific workflow system we built for the nearby supernova factory, the largest data-volume supernova search currently in existence. we describe innovative techniques for data transfer and workflow management, and discuss lessons learned in building a large-scale observational astrophysics workflow management system.
an algorithm for optimal comma free codes with isomorphism rejection. a general algorithm for finding optimal comma-free codes and deriving upper bounds on the minimum redundancy of comma-free codes that implements the idea of isomorphism rejection is presented, together with tables with bounds on the minimum redundancy computed by using this algorithm.
a systematic method for generating quality requirements spectrum. spectrum analysis for quality requirements is useful for measuring and tracking them, but current spectrum analysis largely depends on expertise of each analyst. therefore, it takes a lot of efforts to perform the analysis and is hard to reuse experiences for such analysis. we introduce domain knowledge called term-characteristic map to improve current spectrum analysis for quality requirements. through several experiments, we evaluated the improved method for spectrum analysis.
parameterless outlier detection in data streams. outlyingness is a subjective concept relying on the isolation level of a (set of) record(s). clustering-based outlier detection is a field that aims to cluster data and to detect outliers depending on their characteristics (small, tight and/or dense clusters might be considered as outliers). existing methods require a parameter standing for the "level of outlyingness", such as the maximum size or a percentage of small clusters, in order to build the set of outliers. unfortunately, manually setting this parameter in a streaming environment should not be possible, given the fast time response usually needed. in this paper we propose wod, a method that separates outliers from clusters thanks to a natural and effective principle. the main advantages of wod are its ability to automatically adjust to any clustering result and to be parameterless.
leveraging owl for gis interoperability: rewards and pitfalls. information systems often require combining datasets available in different formats, and geographical information systems are no exception. while semantic technologies have been used before to enable interoperability between relational databases, little research has yet been done for the special case of geographical information systems, despite their applications in active areas of research such as location-based services. in this paper we present an owl-based system for seamless conversion between geographical file formats. while implementing this system we reached the complexity limits of current description logics reasoners and had to design custom algorithms to compute the logical inferences we needed. this process suggested interesting approaches to enable scalable reasoning on the semantic web.
high-level specification of a middleware framework for mobile ad hoc networks: spontaneousware case. the number of distributed applications developed atop mobile wireless ad hoc networks (manet) is rapidly increasing. at the same time, middleware systems that provide services and communication facilities to these applications have become popular. like other distributed environments, the development of middleware systems is not a trivial task. however, this complexity increases when the middleware must execute in a manet due to a dynamic number of members, intermittent connectivity, bandwidth variation, device heterogeneity and so on. in this context, we propose a middleware framework, named spontaneousware, specially designed for aiding developers in the middleware systems development for manet. in order to define a high-level specification for this framework, the requirements and architecture were documented.
practical distributed voter-verifiable secret ballot system. in this paper we propose an end-to-end voter-verifiable system, which is more transparent than existing solutions. its distributed nature permits its use both for supervised voting at a polling place and for online remote voting. we use chaum's blind signatures to ensure voter anonymity. in particular, voters can verify that their votes are recorded exactly as cast, and all ballots can be made public so that anyone can verify the election results. we further address key security issues such as server corruption in the proposed system. the case is made that this can be the basis of a practical voting system.
an empirical study of incorporating cost into test suite reduction and prioritization. software developers use testing to gain and maintain confidence in the correctness of a software system. automated reduction and prioritization techniques attempt to decrease the time required to detect faults during test suite execution. this paper uses the harrold gupta soffa, delayed greedy, traditional greedy, and 2-optimal greedy algorithms for both test suite reduction and prioritization. even though reducing and reordering a test suite is primarily done to ensure that testing is cost-effective, these algorithms are normally configured to make greedy choices with coverage information alone. this paper extends these algorithms to greedily reduce and prioritize the tests by using both test cost (e.g., execution time) and the ratio of code coverage to test cost. an empirical study with eight real world case study applications shows that the ratio greedy choice metric aids a test suite reduction method in identifying a smaller and faster test suite. the results also suggest that incorporating test cost during prioritization allows for an average increase of 17% and a maximum improvement of 141% for a time sensitive evaluation metric called coverage effectiveness.
a destination prediction method using driving contexts and trajectory for car navigation systems. car navigation systems provide the best route to a destination quickly and effectively. however, during daily driving, this information is not necessary since drivers already know the route to the destination very well. in addition, it is time-consuming for drivers to input the destination. thus, our research group has proposed a new car navigation system that provides information related to the destination by predicting the user's destination automatically. we propose the use of a new method that predicts the destination on the basis of the driving trajectory and the contexts in which the user drives. a system that uses our method knows the destination without user interaction and provides information related to the correct destination.
using process mining to business process distribution. service oriented architecture (soa) is by far the most pervasive architecture which includes several building blocks among which orchestration engine is under special focus. although, there are a number of centralized orchestration engines to execute business processes described by bpel language in soa, you may find several decentralized orchestration engines and their purpose is decomposing a bpel process to several software agents to improve quality factors such as adaptability, performance and so forth. as these process distribution methods break a bpel process to its building activities and encapsulate each activity in one agent, it results in producing a lot of agents whose interactions and resource usage would degrade the run-time environment. this paper proposes an intelligent process distribution (ipd) based on a process mining approach in which the selection of activities that should be encapsulated in agents, depends on the previous behavior of process instances. the recommended ipd approach will improve three aspects of system quality. first; is the amelioration of business process adaptability with run-time environment, second; choosing the best agent granularity based on detecting most relevant activities and encapsulating them in agents and third; is decreasing of resource usage due to reduced and improved number of produced agents and messages. furthermore, we proved our method using a mathematical approach.
formalizing the notion of adaptive system behavior. in computer science the notion of adaptive systems has been used in different contexts for many years now. although there is some intuitive, common understanding of the notion, a precise and universally practicable definition is still missing. more precisely, previous definitions fail to strictly differentiate between adaptive and non-adaptive systems. we investigate the intuitions and propose a precise definition that comprises most informal explanations. methodical implications arising from our definition are discussed as well.
impact of function inlining on resource-constrained embedded systems. with the development of computer systems, function inlining schemes were used to reduce execution time while increasing codes. in embedded systems such as wireless sensor nodes, there are extreme limitations on memory space and battery power. this is the reason why function inlining is useful for maximizing memory utilization while minimizing energy consumption of embedded systems. in the previous works, basic inlining schemes were proposed, which were adapted to systems with code memory constraints. however, they were too coarse-grained, and did not evaluate the impact of function inlining in terms of both energy consumption and code memory utilization in actual systems. in this paper, we propose a fine-grained function inlining scheme. we also present the impact of function inlining schemes on resource-constrained embedded systems, in terms of energy consumption and code memory overhead. based on experimental results, we demonstrate that fine-grained function inlining can improve the energy efficiency of embedded systems while maximizing code memory utilization.
a holistic mechanism against file pollution in peer-to-peer networks. content pollution is pervasive in the current peer-to-peer file sharing systems. many previous reputation models have been proposed to address this problem, however, such models strongly rely on the participants' feedback. in this paper, we bring forward a new holistic mechanism which integrates the reputation model, inherent file-source-based information and the statistical data reflecting the diffusion state to defend against pollution attack. first, we deploy a redundancy mechanism to assure that the file requester receives the correct indices that accord with the information published by the file provider. second, we complement the reputation information with the diffusion data to help the file requester select the authentic file for downloading. finally, we introduce a block-oriented probabilistic verification protocol to help the file requester discern the polluted files during the downloading with a low cost. we perform a simulation which shows that our holistic mechanism can perform very well and converge to a high accuracy rapidly, even in a highly malicious environment.
a passive conformance testing approach for a manet routing protocol. in this paper we propose a passive conformance testing technique applied to a mobile ad hoc network (manet) routing protocol, olsr, that is characterized by a dynamically changing topology and lack of centralized management. this makes it necessary to investigate new ways to test complex scenarios and configurations. the work here proposes a formal passive testing method to test the conformance and reliability of the protocol. the method developed has been performed on a real case study showing that the approach can be successful applied and that it allows reducing inconclusive verdicts often observed using other methods.
a real-time message scheduler support for dual-sink mobile ad-hoc sensor networks. this paper designs and measures the performance of a message scheduling scheme for the mobile sensor network employing two sinks. for the purpose of enhancing the successful delivery ratio for time-sensitive sensor messages and also avoiding congestion around the sinks, the proposed scheme keeps their loads different, and makes each sensor node send the urgent message to the low-load sink. for a neutral node, the urgency of a message is estimated by comparing the slack value of the message and slack distribution of overall messages observed at the node. with this information, each node decides the destination of each message. the simulation performed via ns-2 reveals that the proposed scheme, called chop partition, can improve the deadline meet ratio of real-time messages by up to 7.2% for aodv case and 8.2% for dsdv case, compared with the random selection scheme, or even partition, for the given experiment parameters.
exploiting stack distance to estimate worst-case data cache performance. this paper proposes an approach to safely and tightly bounding data cache performance by computing the worst-case stack distance of data cache accesses. our approach can not only be applied to direct-mapped caches, but also be used for set-associative or even fully-associative caches without increasing the complexity of analysis. moreover, the proposed approach can statically categorize worst-case data cache misses into cold, conflict, and capacity misses, which can provide useful insights for designers to enhance the worst-case data cache performance. our evaluation shows that the proposed data cache timing analysis technique can safely and accurately estimate the worst-case data cache performance, and the overestimation as compared to the observed worst-case data cache misses is within 1% on average.
algebraic specification techniques for parametric types with logic-based constraints. mainstream object-oriented languages now offer capabilities of generic types with bounded type parameters, but they typically do not provide support for specifying semantic requirements on the type parameters' methods beyond conformance of signatures. regrettably, even object-oriented assertion languages, such as jml, have nontrivial limitations in this regard. yet many interesting parameterized types require additional semantic features if they are to function as intended. we illustrate the issues with a case study of project scheduling based on the project management institute's generic characterization of task breakdowns. we consider algebraic techniques for instantiating parametric types in such a way that the semantic requirements expressed by logic-based constraints propagate to the instantiating types. these techniques argue for more general bindings of actual type parameters for the formal ones which do not have the restrictions of current programming languages. we show that types equipped with constraints should be viewed as theories, and the bindings as morphisms of types as theories. we translate these software specifications into theories in the pvs specification language. these proposals lead to conclusions about language features for more general, semantic bindings of the actual for the formal type parameters, at least in the assertion languages.
incremental board: a grid-based space for visualizing dynamic data sets. in information visualization, adding and removing data elements can strongly impact the underlying visual space. we introduce a chess board analogy for displaying (projecting) objects from a dynamic set on a 2d space, considering their similarity in a higher dimensional space. our solution is inherently incremental and maintains a coherent disposition of elements, even for completely renewed sets. the algorithm considers relative positions, rather than raw dissimilarity. it has low computational cost, and its complexity depends only on the size of the currently viewed subset, v. thus, a set of size n can be sequentially displayed in o(n) time, reaching at most o(n2) only if viewing the whole set at once. consistent results were obtained as compared to (non-incremental) multidimensional scaling solutions. moreover, the corresponding visualization is not susceptible to occlusion. the technique was tested in different domains, being particularly adequate to display dynamic corpora.
a taxonomy and adversarial model for attacks against network log anonymization. in recent years, it has become important for researchers, security incident responders and educators to share network logs, and many log anonymization tools and techniques have been put forth to sanitize this sensitive data source in order to enable more collaboration. unfortunately, many new attacks have been created, in parallel, that try to exploit weaknesses in the anonymization process. in this paper, we present a taxonomy that relates similar kinds of attacks in a meaningful way. we also present a new adversarial model which we can map into the taxonomy by the types of attacks that can be perpetrated by a particular adversary. this has helped us to negotiate the trade-offs between data utility and trust, by giving us a way to specify the strength of an anonymization scheme as a measure of the types of adversaries it protects against.
a framework of a logic-based question-answering system for the medical domain (loqas-med). question-answering systems that provide precise answers to questions, by combining techniques for information retrieval, information extraction, and natural language processing, are seen as the next-generation search engines. due to the growth and real-world impact of biomedical information, the need for question-answering systems that can aid medical researchers and health care professionals in their information search is acutely felt. in order to provide users with accurate answers, such systems need to go beyond lexico-syntactic analysis to semantic analysis and processing of texts and knowledge resources. moreover, question-answering systems equipped with reasoning capabilities can derive more adequate answers by using inference. research on question answering in the medical and health care domain is still in its inception stage. while several recent approaches to medical question answering have explored use of semantic knowledge, few approaches have exploited the utility of logic formalisms and of inference mechanisms. in this paper, we present a framework for a logic-based question-answering system for the medical domain, which uses description logic as the formalism for knowledge representation and reasoning. as a first step toward building the proposed system, we present semantic analysis and classification of medical questions.
towards a maturity model for corporate data quality management. high-quality corporate data is a prerequisite for world-wide business process harmonization, global spend analysis, integrated service management, and compliance with regulatory and legal requirements. corporate data quality management (cdqm) describes the quality oriented organization and control of a company's key data assets such as material, customer, and vendor data. with regard to the aforementioned business drivers, companies demand an instrument to assess the progress and performance of their cdqm initiative. this paper proposes a reference model for cdqm maturity assessment. the model is intended to be used for supporting the build process of cdqm. a case study shows how the model has been successfully implemented in a real-world scenario.
genqa: automated addition of architectural quality attribute support for java software? non-functional requirements for software systems are typically specified using informal notations such as quality attribute scenarios. further, implementation strategies for such non-functional attributes are frequently common across systems with quite different functional requirements. in such cases, the time invested in implementing these quality attributes could be salvaged, thereby reducing the project lifetime and increasing software quality. in this paper, we present the design and prototype implementation of a tool and associated framework that enables software engineers to effectively capture non-functional requirements, and then automatically generate implementations of these requirements to be added to the application being built. the quality attribute implementations are generated as aspects (aspectj in the prototype) that can be weaved in with the application code (java) with minimal development effort.
formalizing motivational patterns based on colors and their cultural meanings for developing web applications. collaborative work via web tends to increase due to professionals' teams separated by distance and time, demanding more effort and stronger commitment from each person. it is noticed that many times the collaborative work via web is not effective, generating lack of motivation and no engagement, few effective collaboration and no commitment with the results. it should be considered the cultural differences among the team's members, what interfere on each individual's performance, misunderstanding the task (for instance, the adopted vocabulary) and not motivating to reach the goals (for instance, how the environment looks). this research aims at discussing the process of motivational pattern formalizing using common sense knowledge to associate the appropriate colors for the environment to the emotions that these colors can provoke people into engaging, culturally motivating people through significant and appropriate colors in the collaborative environment.
message-passing and local heuristics as decimation strategies for satisfiability. decimation is a simple process for solving constraint satisfaction problems, by repeatedly fixing variable values and simplifying without reconsidering earlier decisions. we investigate different decimation strategies, contrasting those based on local, syntactic information from those based on message passing, such as statistical physics based survey propagation (sp) and the related and more well-known belief propagation (bp). our results reveal that once we resolve convergence issues, bp itself can solve fairly hard random k-sat formulas through decimation; the gap between bp and sp narrows down quickly as k increases. we also investigate observable differences between bp/sp and other common csp heuristics as decimation proceeds, exploring the hardness of the decimated formulas and identifying a somewhat unexpected feature of message passing heuristics, namely, unlike other heuristics for satisfiability, they avoid unit propagation as variables are fixed.
a smart clustering algorithm for photo set obtained from multiple digital cameras. the use of digital cameras is prevalent. although the cost of digital photographs is low, managing numerous digital photos is burdensome to most users. an intelligent management tool for digital photos is needed. we propose a novel clustering algorithm for concurrent digital photos obtained from multiple cameras. since previous photo clustering methods can be applied to a single camera, a group of photos obtained from different cameras cannot be classified to meet user preference. we newly define temporal/spatial combined clustering for the set of group photos taken from different cameras to solve this situation. we define a new spatial similarity using block alignment for two independent photos. if a user submits photo clustering that shows preference between spatial and temporal clustering, then we can cluster other photo sets according to the reference clustering characteristics. in this method, the exif metadata plays an essential role. we tested more than one thousand photos taken by tourist groups. the final result was satisfactory compared to previous methods based on temporal (spatial) criteria only.
evaluation of vr medical training applications under the focus of professionals of the health area. this paper presents part of the implementation of a virtual reality (vr) framework, involving the building of an interaction module with support to conventional and non-conventional devices, and the evaluation of a system prototype, considering computational and human aspects. the proposal of the evaluation is to improve the framework, and consequently, the applications generated by it, following ideas and opinions of health's professionals (doctors and students), who are the target public of this project.
symmetric encapsulated multi-methods to abstract over application structure. in object systems, classes take the role of modules, and interfaces consist of methods. because methods are encapsulated in objects, interfaces in object systems do not allow abstracting over where methods are implemented. this implies that any change to the implementation structure may cause a rippling effect. sometimes this unduly restricts the scope of software evolution, in particular for methods with multiple parameters where there is no clear owner. we propose a simple scheme where symmetric methods may be defined in the classes of any of their parameters. this allows client code to be oblivious of what class contains a method implementation, and therefore immune against it changing. when combined with multiple dynamic dispatch, this scheme allows for modular extensibility (but not modular type-checking) where a method defined in one class is overridden by a method defined in a class that is not its subtype. in this paper, we illustrate the scheme by extending a core calculus of class-based languages with these symmetric encapsulated multi-methods, and prove the result sound.
model-based reasoning on the achievement of business goals. business process modeling has been realized as a methodology for the optimization of workflows in enterprises. process models help to formalize the actual workflow by describing the activities that are required to achieve a specific business goal. in order to make business processes compliant with laws and regulations, it is necessary in practice to rewrite them in a way such that they guarantee the compliance with the identified security properties. our research towards automated process rewriting for compliance enforcement has revealed that an essential building block is the ability for reasoning on the achievement of business goals: rewriting is only practically applicable (regardless whether it is performed manually or automatically) if the resulting process still achieves the desired business goals. this paper presents an approach for the automated reasoning on the achievement of business goals based on semantic congruence relations.
situated tuple centres in respect. coordination languages and models can play a key role in the engineering of environment in mas (multiagent systems). in this paper, we take the respect coordination language for programming tuple centres, and extend it so as to govern interactions between agents and environment. in particular, we show how its event model can be generalised to support the management of general environment events and make tuple centres situated. to this end, first a case study is sketched where it is shown how the extended respect can be adopted to coordinate a system for sensing and controlling environmental properties. then the syntax and semantics of the extended version of respect is discussed.
creating a mobile web application platform: the lively kernel experiences. the software industry is currently in the middle of two transitions -- towards web-based software and towards web-enabled mobile devices. in this paper, we summarize our experiences in porting the sun labs lively kernel - an interactive web programming environment developed at sun microsystems laboratories - onto a nokia n810 mobile device. we report our experiences based on two different approaches that were used. first, we ported the system onto a regular web browser running in the mobile device. second, we developed a custom-built native execution environment that provides more direct and extensive access to the underlying resources of the system. based on these experiments, we will discuss the lessons learned as well as provide directions and guidance for future work.
seamless access of home theater personal computers for mobile devices. this paper presents the mompt project, an open source project developed to allow access to multimedia content and to control multiple htpcs remotely using mobile devices. the main contribution in the context of this project is its reference design, which allows the access of htpc functionalities using different technologies, such as upnp and xml-rpc. in this paper the reference design as well as its main components are detailed. also, we describe one developed solution for the mediaportal htpc. it is discussed how it was developed, and the evaluation scenario with mobile devices, more specifically an internet tablet.
softening gcc and regular with preferences. in this paper, we present the soft global constraints &sigma;-gcc and &sigma;-regular which are the soft versions with preferences of well-known global constraints gcc and regular. for each of them, we introduce a new violation based semantic which takes into account preferences and propose algorithms to enforce hyperarc consistency in polynomial time, making use of flow theory.
mapping uml sequence diagram to time petri net for requirement validation of embedded real-time systems with energy constraints. requirements validation is a critical task in any embedded real-time system project. normally, these systems have stringent timing constraints that must be satisfied for the correct functioning, since violation might be catastrophic, such as loss of human lives. in addition, there are systems where energy is another constraint that must also be satisfied. hence, early detection of potential problems may reduce risks of faults propagations from early specification to the final code. this paper presents the mapping process of uml sequence diagram into a time petri net with energy constraints (etpn) so as to validate timing and energy requirements in early phases of the embedded system development life-cycle. besides, the estimates obtained from the model are 95% close to the respective measures obtained from the real hardware platform.
task based visualization of 5d brain eit data. visualization is vital for medical research and clinical applications to interpret information presented in medical imaging data. eit (electrical impedance tomography) is a recently developed medical imaging technique, which is able to collect 5d spectral-temporal-spatial data. visualization of multi-dimensional medical imaging data is still a challenge. making use of the tmdv (task-based multi-dimensional visualization) method and cte (cubic task explore) model, a task based prototype system, eit5dvis, is developed for the visualization of 5d brain eit data in this paper. the evaluation result demonstrates the usability of eit5dvis prototype visualization system and the effectiveness of the tmvd method and cte model for the visualization of multi-dimensional medical imaging data.
key processes to start software process improvement in small companies. to support small software enterprises -- vses-- when they are dealing with the first processes that must be considered as they undertake a project of software process improvement --spi--, we have defined a set of processes which we consider to be of high-priority when initiating the implementation of an improvement project in vses. this paper introduces this set of processes and the way in which they have been obtained, based on the analysis and synthesis of three research works carried out within the context of the competisoft project. it also describes our experience of the application of both the process selection and the prioritization strategy in four vses. the result of implementing the proposal shows that it is feasible to implement it in vses and that it can be done with an expense of effort that is suitable for them.
daraw: a new write buffer to improve parallel i/o energy-efficiency. in the past decades, parallel i/o systems have been used widely to support scientific and commercial applications. new data centers today employ huge quantities of i/o systems, which consume a large amount of energy. most large-scale i/o systems have an array of hard disks working in parallel to meet performance requirements. traditional energy conservation techniques attempt to place disks into low-power states when possible. in this paper we propose a novel strategy, which aims to significantly conserve energy while reducing average i/o response times. this goal is achieved by making use of buffer disks in parallel i/o systems to accumulate small writes to form a log, which can be transferred to data disks in a batch way. we develop an algorithm - dynamic request allocation algorithm for writes or daraw - to energy efficiently allocate and schedule write requests in a parallel i/o system. daraw is able to improve parallel i/o energy efficiency by the virtue of leveraging buffer disks to serve a majority of incoming write requests, thereby keeping data disks in low-power state for longer period times. buffered requests are then written to data disks at a predetermined time. experimental results show that daraw can significantly reduce energy dissipation in parallel i/o systems without adverse impacts on i/o performance.
towards a compositional approach to model transformation for software development. model transformation plays an important role in model-driven software development that aims to introduce significant efficiencies and rigor to the theory and practice of software development. although models may have different notations and representations, they are basically graphs, and model transformations are thus nothing but graph transformations. despite a large amount of theoretical work and a lot of experience with research prototypes on graph-based model transformations, it remains an open issue how to compose model transformations. in this paper, we report our first attempt at a compositional framework for graph-based model transformations using the graph querying language unql. the main idea of unql is that graph queries are fully captured by structural recursion that is suitable for efficient composition. we show that the idea can be applied to graph-based model transformations. we have implemented a prototype of the framework and tested it with several nontrivial examples. our new framework supports systematic development of model transformation "in the large" with the advantage that it can automatically remove inefficiencies arising from their composition.
origami fold as algebraic graph rewriting. we formalize paper fold (origami) by graph rewriting. origami construction is abstractly described by a rewriting system (o, ↬), where o is the set of abstract origami's and ↬ is a binary relation on o, called fold. an abstract origami is a triplet (&pi;, ∽, ≻), where &pi; is a set of faces constituting an origami, and ≻ and are binary relations on &pi;, each representing adjacency and superposition relations between the faces. we then address representation and transformation of abstract origami's and further reasoning about the construction for computational purposes. we present a hypergraph of origami and define origami fold as algebraic graph transformation. the algebraic graph-theoretic formalism enables us to reason about origami in two separate domains of discourse, i.e. pure combinatoric domain and geometric domain r x r, and thus helps us to further tackle challenging problems in computational origami research.
automatic discovery of technology trends from patent text. patent text is a rich source to discover technological progresses, useful to understand the trend and forecast upcoming advances. for the importance in mind, several researchers have attempted textual-data mining from patent documents. however, previous mining methods are limited in terms of readability, domain-expertise, and adaptability. in this paper, we first formulate the task of technological trend discovery and propose a method for discovering such a trend. we complement a probabilistic approach by adopting linguistic clues and propose an unsupervised procedure to discover technological trends. based on the experiment, our method is promising not only in its accuracy, 77% in r-precision, but also in its functionality and novelty of discovering meaningful technological trends.
a framework for text visualization using memory traffic management for mobile devices. graphical user interfaces (guis) of document viewers have gained attention with the increase on the number of mobile applications that uses it. however, mobile devices are still limited in relation to the available functionalities for text exhibition. other limitations of these devices are the memory size, processing capacity and battery. this paper describes a framework for text visualization that safely manages memory traffic for mobile applications that intensively use bitmap font files, such as a document viewer. the main goal is to diversify the functionalities concerning to text exhibition in mobile devices, but also minimizing memory traffic.
planning for remarshaling in an automated container terminal using cooperative coevolutionary algorithms. the productivity of a container terminal is highly dependent on the efficiency of loading the containers onto the vessels. the efficiency of container loading depends on how the containers are stacked in the storage yard. remarshaling refers to the preparatory task of rearranging the containers to maximize the efficiency of loading. in this paper, we propose cooperative coevolutionary algorithms (cceas) to derive a plan for remarshaling in an automated container terminal. cceas efficiently search for a solution in a reduced search space by decomposing a problem into subproblems. our ccea decomposes the problem into two subproblems: one for determining where to move the containers and the other for determining the movement priority. simulation experiments show that our ccea can derive a better plan in terms of the efficiency of both loading and remarshaling than other methods which are not based on the notion of problem decomposition.
a novel approach to detect copy number variation using segmentation and genetic algorithm. among many forms of genomic variations, copy-number variations (cnvs) can be defined as gains or losses of several kilobases to hundreds of kilobases of genomic dna. since many cnvs include genes that result in differential levels of gene expression, cnvs may account for a significant proportion of normal phenotypic variation. some scientists demonstrated that a large portion of overlapping, currently known common human cnvs, were smaller in his dataset. however, previous experimental studies, performed primarily by a-cgh techniques, are limited to detection of cnvs of large-sized cnvs. efficient algorithms for finding small-sized cnvs are essential. in our paper, we propose a novel approach to find small-sized cnvs on a-cgh data which is a sequential 2-dimensional clustering method. the algorithm we propose is robust to some level of noise. and regardless of the size of probes, our algorithm can find cnvs consisting of small number of probes.
fuzzy data modeling based on xml schema. interest in xml has been growing over the last few years and xml has been the de-facto standard of information representation and exchange over the web. however, the real world is filled with imprecision and uncertainty. classical databases have been extended to deal with imprecise and uncertain data. in this paper, we investigate how to incorporate fuzzy data into xml. we identify multiple granularity of data fuzziness in xml. based on possibility distribution theory, we have possibilities associated with elements as well as attribute values of elements in xml. a fuzzy xml data model that addresses all of the fuzziness is developed based on xml schema.
extending passi to model multi-agent systems product lines. multi-agent system product lines (mas-pls) have emerged to integrate software product lines (spls) and agent-oriented software engineering techniques by incorporating their respective benefits and helping the industrial exploitation of agent technology. in this paper, we present a new approach for modeling mas-pls, focusing the domain analysis stage. our approach is based on passi methodology and incorporates some extensions to address agency variability.
implicit relevance feedback for context-aware information retrieval in ubilearning environments. ubiquitous learning (ubilearning) environments heavily employ mobile devices to empower users with mobility and tooling support to learn anytime, anywhere. introducing mobile devices in educational settings imposes constraints on search behavior due to limited resources on these devices such as small screens and restricted input functionalities. targeting this scenario, this paper proposes an architecture for implicit relevance feedback which considers users' work context to expand search queries in order to satisfy information needs with greater precision. evaluation results conducted over a local test collection enriched with contextual features reveal improvements on average precision when compared to a pseudo relevance feedback baseline.
an improved shrinkage estimator to infer regulatory networks with gaussian graphical models. gaussian graphical models (ggms) are widely used to tackle the important and challenging problem of inferring genetic regulatory networks from expression data. these models have gained much attention as they encode full conditional relationships between variables, i.e. genes. as a consequence, structure learning of a ggm requires an invertible and well-conditioned covariance matrix. unfortunately, the usual estimator---the sample covariance matrix---is ill-suited in the "small n, large p" setting characteristic of microarray data. as an alternative, [9] proposed a shrinkage estimator that is both statistically efficient and computationally fast. the effectiveness of this estimator in bioinformatics has been illustrated by [12] who successfully used it to infer genetic regulatory networks from microarray data. unfortunately, this improved estimator requires the shrinkage intensity to be estimated from the data, which is problematic in the "small n, large p" setting. indeed, we show that the optimal shrinkage intensity estimator used in [9, 12] is biased. we propose a parametric bootstrap approach to estimate this bias and derive a "bias-corrected" shrinkage estimator. the applicability and usefulness of our estimator are demonstrated on both simulated and real expression data.
cross-layer cooperation between membership estimation and routing. mobile ad hoc networks are characterised by the absence of a centralised infrastructure and node heterogeneity. due to size and mobility requirements of the nodes that make up such a network the protocols employed often must deal with limited bandwith and avoid high power consumption. in classical layered protocol stacks, services are run in isolation. we argue, that in order to save band-with, reduce power and improve performance, various services that are running on a node may co-operate. we have identified two services in particular that can benefit greatly from such a co-operation: the routing protocol, which is responsible for discovering routes between nodes in the system and the membership estimation service, which is responsible for providing an estimation of the current composition of the system. the two services are the fundamental building blocks for distributed algorithms and applications at a higher level. in this paper we show how these two basic protocols can cooperate. the membership estimation service can provide useful information to the routing protocol, whereas routing may aid to maintain the membership estimation updated. we describe an implementation of a cross layer architecture, in which the dynamic source routing protocol (dsr) and our gossip-based membership estimation service share information. we show results of performacne experiments reflecting how this cooperation improves the performance of both services. finally, we identify scenarios in which the interaction is of most benefit.
precise generalized contact point and normal determination for rigid body simulation. modeling contact for rigid body simulation requires accurate determination of time of contact, contact points, and contact normals. existing collision detection methods for rigid body simulation can be grouped into one of three categories: convexity-based discrete methods, a posteriori discrete methods, and continuous methods. our proposed method combines the advantages of all three types: operating on arbitrary geometric representations, running in asymptotic linear time in the number of polyhedral features, having a parameterizable precision (a variation is guaranteed to miss no collisions), and avoiding simplex/simplex tests that are difficult to implement robustly. the algorithm is demonstrated on a pathological example involving both polyhedra and polygon soups.
using a product line for creating component systems. component systems have become a wide-spread technology and found their place in several application domains. each component system has its specifics and particularities that reflect its focus and the application domain it is intended for. although important, the diversity of component systems leads to a number of problems including having different tools for each systems, unnecessary duplication of functionality and problems with integration when several domains are to be targeted. based on categorization of component application domains, we propose a "meta-component system", which provides a software product line for creating custom component systems. we focus especially on the deployment and execution environment, which is where most diversities are found. we demonstrate the usage of the "meta-component system" and propose how it is to be realized by two core concepts of sofa 2, namely connector generator and microcomponents.
structuring a process management center of excellence. in view of the growing complexity and scope of processes in organizations, it is increasingly necessary to structure their process management tasks. organizations have sought guidelines to structure a process center of excellence - pce. however, there is still no consensus on how to structure this kind of organizational unit. this paper proposes the organizational structure and main macro-processes entailed in setting up a pce.
a sentence level probabilistic model for evolutionary theme pattern mining from news corpora. some recent topic model-based methods have been proposed to discover and summarize the evolutionary patterns of themes in temporal text collections. however, the theme patterns extracted by these methods are hard to interpret and evaluate. to produce a more descriptive representation of the theme pattern, we not only give new representations of sentences and themes with named entities, but we also propose a sentence-level probabilistic model based on the new representation pattern. compared with other topic model methods, our approach not only gets each topic's distribution per term, but also generates candidate summary sentences of the themes as well. consequently, the results are easier to understand and can be evaluated using the top sentences produced by our probabilistic model. experimentation with the proposed methods on the tsunami dataset shows that the proposed methods are useful in the discovery of evolutionary theme patterns.
ubiquitous services in home networks offered through digital tv. this paper presents some industry proposals for the interoperability between devices in home environments and reports our efforts on exploiting the computational aspects related to the offer of ubiquitous services in the context of household environments. it explores the communication ability between the set-top box and other devices of household environments and of personal use through the development of a software module for transparent replication of audiovisual digital tv content, in home networks based on universal plug and play (upnp&trade;) / digital living network alliance (dlna). the implementation was carried out on an environment emulating a set-top box according to the brazilian standard for dtv.
exploiting join cardinality for faster hash joins. hash joins combine massive relations in data warehouses, decision support systems, and scientific data stores. faster hash join performance significantly improves query throughput, response time, and overall system performance. in this work, we demonstrate how using join cardinality improves hash join performance. the key contribution is the development of an algorithm to determine join cardinality in an arbitrary query plan. we implemented early hash join and the join cardinality algorithm in postgresql. experimental results demonstrate that early hash join has an immediate response time that is an order of magnitude faster than the existing hybrid hash join implementation. one-to-one joins execute up to 50% faster and perform significantly fewer i/os, and one-to-many joins have similar or better performance over all memory sizes.
gpu-based computation of distance functions on road networks with applications. we present a gpu-based algorithm for computing discretized distance functions on road networks. as applications, we provide algorithms for computing discrete order-k network voronoi diagrams and for approximately solving k-nearest neighbor queries and aggregate k-nearest neighbor queries on road networks. finally, we present experimental results obtained with the implementation of our algorithms.
thin client architecture in support of remote radiology learning. we implemented a system for remote radiology learning which provides immediate feedback to the learner. using a thin remote client, expert readers are asked to answer questions about specified radiological findings. these scans are presented as realtime 2d and 3d presentations which allow the user to freely manipulate them using a thin java client with all 3d rendering performed on the server side. answers are stored on the server and are used to provide feedback to learners who are presented with the same questions, using the remote client. learners can practice on real datasets while receiving immediate feedback on their diagnosis and measurements. novel concepts introduced are (1) the use of server-side rendering in radiology learning, (2) providing immediate and specific feedback to trainees, (3) the ability to provide useful feedback when a definitive gold standard does not exist and (4) a thin, highly compatible client that runs on common, existing hardware which allows to have more people participating in very complex radiological evaluations, even if there are not at the same site.
integrating standardized transaction protocols in service-oriented wireless sensor networks. despite much research in the area of wireless sensor networks in recent years, the programming of sensor nodes is still time-consuming and tedious. a new paradigm which seems to be qualified to simplify the programming of sensor networks is the service oriented architecture. the composition of simple services to more complex ones can be a convenient way to design applications. to enable the sophisticated techniques known from service oriented architectures like replication and migration of services, a transaction model for sensor networks is required. in this paper, we study the applicability of the standard commit protocols two phase commit (2pc) and transaction commit on timeout and show in experiments with real sensor nodes that 2pc can enable consistent service migration in wireless sensor networks.
improved spam filtering by extraction of information from text embedded image e-mail. the increase of image spam, a kind of spam in which the text message is embedded into an attached image to defeat spam filtering techniques, is becoming an increasingly major problem. for nearly a decade, content based filtering using text classification or machine learning has been a major trend of antispam filtering systems. a key technique being used by spammers is to embed text into image(s) in spam email. in [4], we proposed two levels of ontology spam filters: a first level global ontology filter and a second level user-customized ontology filter. however, that previous system handles only text e-mail and the percentage of attached images is increasing sharply. the contribution of the paper is that we add an image e-mail handling capability to the previous anti-spam filtering system, enhancing the effectiveness of spam filtering.
sqlprob: a proxy-based architecture towards preventing sql injection attacks. sql injection attacks (sqlias) consist of maliciously crafted sql inputs, including control code, used against database-connected web applications. to curtail the attackers' ability to generate such attacks, we propose an sql proxy-based blocker (sqlprob). sqlprob harnesses the effectiveness and adaptivity of genetic algorithms to dynamically detect and extract users' inputs for undesirable sql control sequences. compared to state-of-the-art protection mechanisms, our method does not require any code changes on either the client, the web-server or the back-end database. rather, our system uses a proxy that seamlessly integrates with existing operational environments offering protection to front-end web servers and back-end databases. to evaluate the overhead and the detection performance of our system, we implemented a prototype of sqlprob which we tested using real sql attacks. our experimental results show that we can detect all sql injection attacks while maintaining very low resource utilization.
an efficient and accurate lattice for pricing derivatives under a jump-diffusion process. derivatives are popular financial instruments that play essential roles in financial markets. however, most derivatives have no analytical formulas and must be priced by numerical methods such as lattice models. the pricing results generated by a lattice converge to the theoretical values, but they may converge slowly or even oscillate significantly due to the nonlinearity error. according to empirical studies, a lognormal diffusion process, which has been widely studied, does not capture the real world phenomena well. to address these problems, this paper proposes a novel lattice under the jump-diffusion processes. our lattice is accurate because it suppresses the nonlinearity error. it is more efficient due to the fact that the time complexity of our lattice is lesser than those of the other existing lattice models. numerous numerical calculations confirm the superior performance of our lattice model to the other existing methods.
self-organizing collaborative filtering in global-scale massive multi-user virtual environments. due to the huge amount of available information in today's society, it becomes more and more difficult for the consumer to locate the most useful information for a specific topic. recommender systems using collaborative filtering (cf) are a popular technique for reducing information overload and finding useful information on the internet. however, in massive global-scale multi-user virtual environments different approaches are required from those used within the currently dominant centralized infrastructures or lately investigated p2p approaches. within this paper we present a novel collaborative filtering algorithm used within the hyperverse -- a p2p-based self-organizing middleware service for massively distributed virtual worlds -- to generate and manage recommendations for hyperverse object favorites. due to its global extent considering users and possible ratings, using a monolithic database-backed recommendation service or huge profile- or item-rating-matrices does not scale in our scenario. the decentralized approach presented within this paper creates per user ratings in an adaptive and transparent way by comparing public favorites of passer-by users with personal peer data, weighted by self-adjusting buddy lists.
fast networking with socket-outsourcing in hosted virtual machine environments. this paper proposes a novel method of achieving fast networking in hosted virtual machine (vm) environments. this method, called socket-outsourcing, replaces the socket layer in a guest operating system (os) with the socket layer of the host os. socket-outsourcing increases network performance by eliminating duplicate message copying in both the host os and the guest os. furthermore, socket-outsourcing significantly enhances inter-vm communication within the same host os since it enables network packets to bypass the protocol stack in guest oses. socket-outsourcing was implemented in two representative operating systems (linux and netbsd) and on two virtual machine monitors (linux kvm and pansyvm). these virtual machine monitors provided support for socket-outsourcing through shard memory, event queues, and vm-specific remote procedure call between a guest os and a host os. the experimental results revealed that a guest os outsourcing the socket layer achieved the same network throughput as a native os using up to four gigabit ethernet links. moreover, the benchmark results obtained from an n-tier web application that generated a significant amount of inter-vm communication indicated that socket-outsourcing improved performance by up to 45 percent compared with conventional hosted vm environments.
two-dimensional non-photorealistic drawings on mobile devices. this paper presents fast approaches to simulate four different 2d non-photorealistic drawing styles (i.e., daub, printmaking, line drawing and embossing) on mobile phones, through exploiting several image processing techniques. taking into careful consideration of the limited hardware support and capabilities of mobile phones, we keep the drawing methods of low complexity. to reduce computation, we consider only important features that best represent each drawing style, and select the corresponding image processing techniques that can achieve the desired effect.
ls(graph & tree): a local search framework for constraint optimization on graphs and trees. ls(graph & tree) is a local search framework which aims at simplifying the modeling of constraint satisfaction optimization problems on graphs (csop on graphs or gcsop). optimum constrained trees (oct) problems (a subclass of csop on graphs) in which we need to find an optimum subtree with additional constraints of a given weighted graph arise in many real-life applications. this paper introduces the ls(graph & tree) framework and local search abstractions for oct problems. these abstractions are applied to model and solve the edge weighted k-cardinality tree (kct) problem. the modeling as well as experimental results show the significance of the abstractions.
exploiting weak dependencies in tree-based search. in this work, our objective is to heuristically discover a simplified form of functional dependencies between variables called weak dependencies. once discovered, these relations are used to rank the variables. our method shows that these relations can be detected with some acceptable overhead during constraint propagation. more precisely, each time a variable y gets instantiated as a result of the instantiation of x, a weak dependency (x, y) is recorded. as a consequence, the weight of x is raised, and the variable becomes more likely to be selected by the variable ordering heuristic. experiments on a large set of problems show that on the average, the search trees are reduced by a factor 3 while runtime is decreased by 31% when compared against dom-wdeg, one of the best dynamic variable ordering heuristic.
sources of error in a rigid body simulation of rigid parts on a vibrating rigid plate. we present a simulation study of an important rigid body contact problem. the system in question is composed of a rigid plate and a single rigid body (or particle). the plate follows a prescribed periodic motion of small amplitude and high frequency, such that the net force applied to the part appears to be from a time-independent, position-dependent velocity field in the plane of the plate. theoretical results obtained by vose et al. were found to be in good agreement with simulation results obtained with the stewart-trinkle time-stepping method. in addition, simulations were found to agree with the qualitative experimental results of vose et al. after such verification of the simulation method, additional numerical studies were done that would have been impossible to carry out analytically. specifically, we were able to demonstrate the convergence of the method with decreasing step size (as predicted theoretically by stewart). further analytical and numerical studies will be carried out in the future to develop and select robust simulation methods that best satisfy the speed and accuracy requirements of different applications.
multi-step attack modelling and simulation (msams) framework based on mobile ambients. attackers take advantage of any security breach to penetrate an organisation perimeter and exploit hosts as stepping stones to reach valuable assets, deeper in the network. the exploitation of hosts is possible not only when vulnerabilities in commercial off-the-shelf (cots) software components are present, but also, for example, when an attacker acquires a credential on one host which allows exploiting further hosts on the network. finding attacks involving the latter case requires the ability to represent dynamic models. in fact, more dynamic aspects are present in the network domain such as attackers accumulate resources (i.e. credentials) along an attack, and users and assets may move from one environment to another, although always constrained by the ruling of the network. in this paper we address these dynamic issues by presenting msams (multi-step attack modelling and simulation), an implemented framework, based on mobile ambients, to discover attacks in networks. the idea of ambients fits naturally into this domain and has the advantage of providing flexibility for modelling. additionally, the concept of mobility allows the simulation of attackers exploiting opportunities derived either from the exploitation of vulnerable and non-vulnerable hosts, through the acquisition of credentials. it also allows expressing security policies embedded in the rules of the ambients.
capturing truthiness: mining truth tables in binary datasets. we introduce a new data mining problem: mining truth tables in binary datasets. given a matrix of objects and the properties they satisfy, a truth table identifies a subset of properties that exhibit maximal variability (and hence, complete independence) in occurrence patterns over the underlying objects. this problem is relevant in many domains, e.g., in bioinformatics where we seek to identify and model independent components of combinatorial regulatory pathways, and in social/economic demographics where we desire to determine independent behavioral attributes of populations. we outline a family of levelwise approaches adapted to mining truth tables, algorithmic optimizations, and applications to bioinformatics and political datasets.
htilde: scaling up relational decision trees for very large databases. nowadays, many organizations have relational databases with millions of records and an important question is how to extract information from them. this work proposes htilde (hoeffding tilde) to handle very large relational databases, based on the inductive logic programming (ilp) system tilde (top-down induction of logical decision trees) and the propositional very fast decision tree (vfdt) learner. it is an incremental and anytime algorithm that uses the hoeffding bound to find out the amount of examples that must be considered for choosing the best test for a node. the results show that, compared to tilde, htilde generates theories from very large relational datasets more efficiently without harming their quality measures (f-measure, precision, recall and accuracy). also, htilde learns less complex theories than tilde.
similarity measures for trajectory of moving objects in cellular space. while most gis (geographical information system) are based on euclidean space, cellular space can be used as an alternative type of space for a large number of gis applications. in order to analyze the pattern of moving objects in cellular space, we need new definitions of similarity between their trajectories since the trajectories in cellular space significantly differ from those in euclidean space. in this paper, we study the properties of moving object in cellular space. based on these observations, we propose several similarity measures between trajectories in cellular space. we analyze the differences of the proposed measures by experiments.
privacy-preserving linear programming. with the rapid increase in computing, storage and networking resources, data is not only collected and stored, but also analyzed. this creates a serious privacy problem which often inhibits the use of this data. in this paper, we focus on the problem of linear programming, which is the most important sub-class of optimization problems. we consider the case where the objective function and the constraints are partitioned between two parties with one party holding the objective while the other holds the constraints. we propose a very efficient and secure transformation based solution that has the significant added benefit of being independent of the specific linear programming algorithm used.
evolving morphologies and gaits of physically realistic simulated robots. this paper describes our research and experiments with autonomous robots, in which were used genetic algorithms to evolve stable gaits of simulated legged robots in a physically based simulation environment. in our approach, gaits are defined using two different methods: a finite state machine based on the joint angles of the robot legs; and an elman's recurrent neural network. the parameters for both methods are optimized using genetic algorithms, and the proposed model also allows the evolution of the robot body morphology. several experiments are described, and the obtained results show that it is possible to generate stable gaits and efficient morphologies using machine learning techniques.
improving functional verification of embedded systems using hierarchical composition and set theory. during functional verification, complex interactions between multiple modules that compose a digital circuit design can reveal hard-to-find bugs. functional coverage specifications must be precise to assure these interactions occur during the simulation. we are proposing a technique for improving the functional verification specification of individual modules, preserving the occurrence of these interactions scenarios in the composition phase. we obtain these new specifications in a deductive way, by means of set theory. using experimental results, we show how our work can contribute to error detection and save functional verification time.
a consumer/producer approach to risk-driven software reliability and testing. we introduce the concept of using both consumer software and producer software in the analysis of risk as it relates to test criteria and strategies. there are two different versions of the software, one representing the consumer's viewpoint, which requires reliable software at reasonable cost, and the other representing the producer's viewpoint, trying to produce adequate software with the lowest effort.
kvmsec: a security extension for linux kernel virtual machines. virtualization is increasingly being used in regular desktop pcs, data centers and server farms. one of the advantages of introducing this additional architectural layer is to increase overall system security. in this paper we propose an architecture (kvmsec) that is an extension to the linux kernel virtual machine aimed at increasing the security of guest virtual machines. kvmsec can protect guest virtual machines against attacks such as viruses and kernel rootkits. kvmsec enjoys the following features: it is transparent to guest machines; it is hard to access even from a compromised virtual machine; it can collect data, analyze them, and act consequently on guest machines; it can provide secure communication between each of the guests and the host; and, it can be deployed on linux hosts and at present supports linux guest machines. these features are leveraged to implement a real-time monitoring and security management system. further, differences and advantages over previous solutions are highlighted, as well as a concrete roadmap for further development.
a method to construct knowledge table-base in k-in-a-row games. in any k-in-a-row game, the player should always analyze each consecutive sequence in 4 directions, which consists of either the void intersections or the intersections occupied by the same color stones. although the difficult problem in k-in-a-row game is that any void intersection on board can be placed a stone on, just like go, however, the hints in k-in-a-row are far more than those in go. we find it is a good method to decrease the complexity of the k-in-a-row games by using connection to represent the states of the game position. then, a precise classification criterion for connection, as well as a precise classification for the intersections is given. as the high-level knowledge of games seems hard to be acquired, the program designers always resort to human masters. however, we can construct a good knowledge table-base based on above idea without masters.
lts semantics for use case models. formalization is a necessary precondition for the specification of precise and unambiguous use case models, which serve as reference points for the design and implementation of software systems. in this paper, we define a formal semantics for use case models. we build on an abstract syntax definition formalizing the sequencing of use case steps. as a semantic domain we have chosen labeled transition systems (ltss), which, we believe, intuitively capture the behavioral aspects of the use case model. the mapping into ltss is defined over the various structural elements of the use case model. the proposed formal semantics allows for various semantic checks such as detection of livelocks and validation of model refinement, an important property in an iterative software development lifecycle. we also introduce our tool "use case model analyzer".
optimal service level allocation in environmentally powered embedded systems. energy management is a critical concern in the design of embedded systems to prolong the lifetime or to maximize the performance under energy constraints. in particular, the emerging embedded systems with renewable energy sources rise new problems and trigger the revision of conventional energy management. if, e.g., the size of a solar cell limits the available power/energy of an electronic device, decisions like when to provide which service have to be made in order to satisfy the needs of the user as well as possible. in this paper, we explore how to maximize the system reward of diverse applications for an energy harvesting system. by utilizing the notion of rewards to express the different priorities of services, we answer the fundamental question of how to optimize the use of energy provided by a scarce and time-varying environmental source. for this purpose, we provide algorithms to optimally adjust service parameters dynamically. our work is supported by simulation results which are based on long-term measurements of the power generated by real solar cells. furthermore, we demonstrate how to dimension the embedded system, e.g., the battery capacity and elaborate on implementation details which are of practical importance.
privacy protection for rfid data. radio frequency identification (rfid) is a technology of automatic object identification. retailers and manufacturers have created compelling business cases for deploying rfid in their supply chains. yet, the uniquely identifiable objects pose a privacy threat to individuals. in this paper, we study the privacy threats caused by publishing rfid data. even if the explicit identifying information, such as name and social security number, has been removed from the published rfid data, an adversary may identify a target victim's record or infer her sensitive value by matching a priori known visited locations and timestamps. rfid data by default is high-dimensional and sparse, so applying traditional k-anonymity to rfid data suffers from the curse of high dimensionality, and would result in poor data usefulness. we define a new privacy model, develop an anonymization algorithm to accommodate special challenges on rfid data, and evaluate its performance in terms of data quality, efficiency, and scalability. to the best of our knowledge, this is the first work on anonymizing high-dimensional rfid data.
adaptive resource management architecture for distributed real-time embedded systems. avionic distributed real-time embedded (dre) systems execute in open environments where operational conditions, input workload, and resource availability cannot be characterized accurately a prior. we present adaptive resource management architecture for these systems to achieve end-to-end qos. the architecture contains two loops and adopts bottom-up philosophy to deal with workload/resource variations. the inner loop is established based on feedback control theory, and handles mild variations; while the outer one includes subtask allocation and migration algorithms, to cope with drastic variations.
music retrieval based on a multi-samples selection strategy for support vector machine active learning. in active learning based music retrieval systems, providing multiple samples to the user for feedback is very necessary. in this paper, we present a new multi-samples selection strategy designed for support vector machine active learning. aiming to reduce the redundancy between the selected samples, the strategy enforces the selected samples to be diverse by explicitly maximizing the distance between each other in the feature space. experimental results on a music genre database demonstrated the effectiveness of the proposed strategy in selecting relevant multiple samples for human feedback on them.
heuristic approach for automated shelf space allocation. shelf space allocation is the problem of efficiently arranging retail products on shelves in order to maximise profit, improve stock control, improve customer satisfaction, etc. most work reported in the literature on this problem has focused on the case of large retailers such as big supermarkets. the interest here is to tackle this problem in the context of small retail shops where different issues arise when compared to large retailers. this paper proposes a heuristic approach to automate shelf space allocation in small retail shops. several initialisation heuristics and local search moves are incorporated into the proposed method which generates high quality practical arrangements represented graphically as simple planograms.
approximate indexing in road network databases. in this paper, we address approximate indexing for efficient processing of k-nearest neighbor(k-nn) queries in road network databases. previous methods suffer from either serious performance degradation in query processing or large storage overhead because they did not employ indexing mechanisms based on their network distances. to overcome these drawbacks, we propose a novel method that builds an index on those objects in a road network by approximating their network distances and processes k-nn queries efficiently by using that index. also, we verify the superiority of the proposed method via extensive experiments using the real-life road network databases.
component-based metrics applying the strength of dependency between classes. component-based development (cbd) is an emerging discipline for promoting practical reuse of software. in cbd, by building new software with independently developed components, we can gain the benefits promised by the software reuse such as quality improvement and rapid development. accordingly, to improve quality of components, we propose the component-based metrics applying the strength of dependency between classes to measure precisely. in addition, we prove the theoretical soundness of the proposed metrics by the axioms of briand et al. and suggest the accuracy and practicality of the proposed metrics through a comparison with the conventional metrics in component development phase.
specifying and checking protocols of multithreaded classes. in the design by contract (dbc) approach, programmers specify methods with pre and postconditions (also called contracts). earlier work added protocols to the dbc approach to describe allowed method call sequences for classes. we extend this work to deal with a variant of generic classes and multithreaded classes. we present the semantical foundations of our extension. we describe a new technique to check that method contracts are correct w.r.t. to protocols. we show how to generate programs that must be proven to show that method contracts are correct w.r.t. to protocols. because little support currently exists to help writing method contracts, our technique helps programmers to check their contracts early in the development process.
using minimum description length for process mining. in the field of process mining, the goal is to automatically extract process models from event logs. recently, many algorithms have been proposed for this task. for comparing these models, different quality measures have been proposed. most of these measures, however, have several disadvantages; they are model-dependent, assume that the model that generated the log is known, or need negative examples of event sequences. in this paper we propose a new measure, based on the minimal description length principle, to evaluate the quality of process models that does not have these disadvantages. to illustrate the properties of the new measure we conduct experiments and discuss the trade-off between model complexity and compression.
projecting code changes onto execution traces to support localization of recently introduced bugs. working collaboratively on complex software systems often leads to situations where a developer enhances or extends system functionality, thereby however, introducing bugs. at best the unintentional changes are caught immediately by regression tests. often however, the bugs are detected days or weeks later by other developers noticing strange system behavior while working on different parts of the system. then it is a highly time-consuming task to trace back this behavior change to code changes in the past. in this paper we propose a technique for identifying the recently introduced change that is responsible for the unexpected behavior. the key idea is to combine dynamic, static, and code change information on the system to reduce the possibly great amount of code modifications to those that may affect the system while running its faulty behavior. after having applied this massive automated filtering step, developers receive support in semi-automatically identifying the root cause change by means of a trace exploration frontend. within multiple synchronized views, developers explore when, how and why modified code locations are executed. the technique is implemented within a prototypical analysis tool that copes with large (> mloc) c/c++ software systems. we demonstrate the approach by means of industrial case studies.
operational control of service processes: modularization as precondition. managing business processes includes among others the normative, strategic, and operational control of processes. in case of a process performance deviation beyond a defined bandwidth, the process manager searches for short-term improvements within the operational control. however, the decision about improvements is limited because of the customer integration in the type of service processes. in this paper the modularization technique will be analyzed as a tool for eliminating the intense customer influence and for structuring the service process. for illustration purposes the loan approval process of a bank will be modularized and the modularization technique as precondition for the operational control will be discussed.
local reasoning for abstraction and sharing. the local reasoning provided by separation logic has been proven to be a good tool for the verification of programs with complex pointer manipulation. however, some problems arise when many structures share part of the heap since it becomes difficult to specify separately and it is even harder to preserve the abstractions that these structures provide. in this article, we present a generalization of separation logic which allows us to precisely specify complex abstract structures in the heap and the sharing relations among them. moreover, we provide also a compositional proof theory which can be used to verify programs in a modular way, even when a complete separation of the structures cannot be ensured.
cpref-sql: a query language supporting conditional preferences. nowadays, the need for incorporating preference querying in database technology is a very important issue in a variety of applications ranging from e-commerce to personalized search engines. a lot of recent research work has been dedicated to this topic in the artificial intelligence and database communities. several formalisms allowing preference reasoning and specification have been proposed in the ai field. on the other hand, in the database field the interest has been focused mainly in extending standard sql with preference facilities in order to provide personalized query answering. in this paper, we propose to build a bridge between these two approaches, by using a logic formalism originally designed to specify and reason with preference in order to extend sql with conditional preference constructors. such constructors allow to express a large class of preference statements with a ceteris-paribus semantics.
*-prefer: optimizing requirements elicitation process based on actor preferences. many software projects fail due to ill-defined requirements, or mismatch between system design and the preferences of involved actors in the environment. the quality and efficiency of requirements elicitation determines the ultimate quality of the system. in this paper, we propose to take the preferences of actors into consideration when making design decisions. furthermore, we use such preference information to help optimize the elicitation process. the requirements model is represented as an extension to the i* framework, called i*-prefer. major extension points are: (1) for each softgoal of an actor, a utility value is computed to depict actor's preferences; (2) a quantitative measurement is introduced to quantify the contribution of different design alternatives to each softgoal; (3) an evaluation process is used to compare the overall impact of different design strategies. a simplified seminar planning example is used to illustrate the proposed approach.
variable handling in time-based xml declarative languages. this paper focuses on time-based declarative languages. the use of declarative languages has the advantage of their simplicity and their high-level abstraction, usually requiring few or no programming skills. moreover, in general, declarative languages benefit portability and allow automatic control of application execution temporal flows, without author awareness. however, most time-based declarative languages have limited support for variable definition and manipulation, which causes developers to resort to imperative languages. this paper discusses and proposes an approach for variable handling in xml-based declarative languages used for temporal synchronization among media objects that balances flexibility and simplicity. an important goal is to resort to imperative languages only for those applications that require intensive algorithmic computation. the proposed solution was adopted by the ncl declarative language of the brazilian dtv system.
evaluating the affective tactics of an emotional pedagogical agent. this paper presents a quantitative (with students of a local middle school) and a qualitative evaluation (with teachers) of a lifelike and emotional pedagogical agent, called pat. pat has the goal of inferring students' emotions and applying affective tactics in order to adapt the learning environment. these tactics aim at motivating students and making them increase their efforts and their intrinsic motivation. pat attempts to achieve these goals by presenting emotional animated attitudes and encouragement messages that are chosen dynamically to compose its affective tactics.
refining spectrum-based fault localization rankings. spectrum-based fault localization is a statistical technique that aims at helping software developers to find faults quickly by analyzing abstractions of program traces to create a ranking of most probable faulty components (e.g., program statements). although spectrum-based fault localization has been shown to be effective, its diagnostic accuracy is inherently limited, since the semantics of components are not considered. in particular, components that exhibit identical execution patterns cannot be distinguished. to enhance its diagnostic quality, in this paper, we combine spectrum-based fault localization with a model-based debugging approach based on abstract interpretation within a framework coined deputo. the model-based approach is used to refine the ranking obtained from the spectrum-based method by filtering out those components that do not explain the observed failures when the program's semantics is considered. we show that this combined approach outperforms the individual approaches and other state-of-the-art automated debugging techniques.
a framework for dynamic adaptation of power-aware server clusters. this paper presents a framework to support dynamic adaptation of applications, which consists of a reusable infrastructure with standard elements to monitor and adapt running applications, and a contract-based adaptation language to enable one to express high-level adaptation policies. the proposed framework is used to introduce dynamic adaptation capabilities into a server cluster infrastructure, intended to address power and performance management concerns. by experimental evaluation, we demonstrate that our approach is useful and effective in providing the required support for describing and deploying typical power management contracts.
labeled images verification using gaussian mixture models. we are proposing in this paper an automated system to verify that images are correctly associated to labels. the novelty of the system is in the use of gaussian mixture models (gmms) as statistical modeling scheme as well as in several improvements introduced specifically for the verification task. our approach is evaluated using the caltech 101 database. starting from an initial baseline system providing an equal error rate of 27.4%, we show that the rate of errors can be reduced down to 13% by introducing several optimizations of the system. the advantage of the approach lies in the fact that basically any object can be generically and blindly modeled with limited supervision. a potential target application could be a post-filtering of images returned by search engines to prune out or reorder less relevant images.
collaborative modeling of business processes: a comparative case study. we study collaborative modeling of business processes with respect to the impact of tool support on the modeling process. for this purpose we compared model quality and modeling costs in two cases. the first was carried out with the help of a collaborative modeling tool; in the second case we kept all other parameters as closely as possible to the first one but conducted the modeling session in the usual way without tool support. we observed a marked increase in modeling time in the second case and a reduction in model quality.
quality of service management in gmpls-based grid obs networks. this paper proposes an architecture for the establishment of routes with absolute qos constraints for optical burst switched grid networks. this model uses traffic engineering provided by gmpls to build lsps that matches the required performance in response to a request made by the user/application of the grid. results show that the proposal is capable of enforcing qos by reducing the loss experienced by burst classes and allowing a better utilization of the computing resources.
an approach for semantic web services automatic discovery and composition with similarity metrics. with the emerging growth of web services tecnology, the web is now evolving to become a service provider. in this context, the semantic web services discovery and composition are hard tasks because injecting context into adaptive service integration raises a number of significant challenges, i.e. defining effective metrics to manage adaptation. this paper proposes an algorithm for semantic web services discovery and compositon which makes use of similarity metrics.
composing a high fidelity hla federation for littoral operations. modeling and simulation and synthetic environments have been widely popularized in the context of military applications. nonetheless, the design and development of some simulation systems still pose true conceptual and technical challenges. this is particularly compelling when the simulation requires the replication of complex systems (as airborne sensors) behavioral models with a high level of credibility. we faced this problem when developing a simulation for tactics development of air platforms. we focused on the integration of high fidelity assets, in terms of: the sensors suite modeling, operator reading and control of the sensors, the physical representation of the entities, and the surrounding terrain and natural environment (ocean, atmosphere). the resulting system combines both constructive and virtual entities, running in a hla setting with jsaf as the scenario generator, and highly sophisticated sensor models. this paper justifies the overall architecture of the simulation system, describes some of the technical integration details, and provides an insight into the resulting synthetic natural environment.
building a customizable embedded operating system with fine-grained joinpoints using the aox programming environment. aspect-oriented programming (aop) has been successful in modularizing crosscutting concerns in complex software systems. in this paper, we present our aspect-oriented approach to building a highly customizable embedded operating system. this is a challenging task since embedded operating systems consist of intertwined concerns often implemented using a mixture of multiple programming languages including an assembly language. furthermore, they often contain hand-optimized code that makes clear modularization extremely difficult. we provide a two-step approach that addresses these difficulties. first, we devised an aspect-oriented programming environment aox (aspect-oriented extension). it supports both modularization and customization of complex software via a set of aspect-oriented mechanisms. aox extends existing approaches in the sense that it is entirely programming language independent and provides finegrained joinpoints. second, using aox, we built a customizable embedded operating system we call the heart os. it is highly configurable and very user-friendly. aox has been implemented and integrated into the eclipse ide as a plug-in module. the heart os has also been implemented and ported to the xscale and x86 platforms. our experience with aox in building the heart os was very positive.
a new cross-training approach by using labeled data. we propose a new cross-training based learning algorithm in this paper. this algorithm generates three classifiers based on the three subsets of original labeled and unlabeled training set. the proposed algorithm is evaluated using data from the uci repository by the experiment. experimental results show that our algorithm can improve classification accuracy compared to those of other algorithms.
a real time financial system based on grid and cloud computing. cloud computing is gaining popularity to the extent that the new "xaas" service category introduced will gradually take the place of many types of computational and storage resources used today. in this regard, grid computing, on which the large scale supply of cloud services is based, will play a key role in defining how those services will be provided. this paper concerns the analysis and preliminary design of a real time financial system that relies on cloud computing technologies for performing macroeconomic analysis and forecasts of the financial markets and their instruments. cloud and grid paradigms generate different added values. some of these are examined in the paper, for instance the use of an instruction set to interact with the grid. this work uses the results obtained in the cybersar project managed by the cosmolab consortium (italy). the system analyzed and described herein will be implemented in the cybersar computational grid by autumn 2009.
optimal candidate generation in spatial co-location mining. existing level-wise spatial co-location algorithms suffer from generating extra, non-clique candidate instances and thus requires cliqueness checking at every level. in this paper, we propose a novel, spatial co-location mining algorithm which automatically generates co-located spatial features without generating any non-clique candidates at any level. subsequently our algorithm generates less candidates than other existing level-wise co-location algorithms without losing any information. the benefit of our algorithm has been clearly observed at an earlier stage in the mining process.
development of a biosignals framework for usability analysis. the understanding of human physical and physiological signals and expressions, together with a growing processing and control capacity allows for new approaches in interactive systems design. in this poster, we introduce constitutive elements and steps towards the integration of eeg (electroencephalography) signals in a system to analyze reading activities. the poster presents system design choices that include the software architecture and the feature extraction and classification techniques used in the first prototypes.
an optimized change-driven regression testing selection strategy for binary java applications. selective regression testing involves re-testing of software systems with a subset of the whole test suite to verify that modifications have not caused adverse impacts to existing functions complied with the requirements specifications. with the growing of globalization and individual testing services providers, many testing and development teams belong to different organizations, and often the testing teams only get a binary release of the application without access to its source code. this makes source code analysis based regression test selection strategy not applicable. meanwhile source code analysis based approach has scalability problem for large applications, which hinders its wide application in industry. this paper presents an optimized regression testing selection strategy based on binary java file change analysis, through which the problems around binary java applications are avoided. besides static regression test suite reduction and test prioritization factors, continuous and real time testing execution information are incorporated as fault-proneness indicator of the selected test cases to dynamically select and prioritize the regression test suites. in addition, the whole strategy is lightweight, making the regression test selection process more automated and effective. experiments show that this strategy can guarantee the change point coverage, reveal faults quickly, and scale to industry-size regression testing scenarios under resource and time constraints.
network protocol interoperability testing based on contextual signatures and passive testing. this paper presents a methodology for interoperability testing based on contextual signatures and passive testing with invariants. the concept of contextual signature offers a framework to add information on the states, the values of parameters, as well as logical connectors that increases the expressive power of invariants. this allows expressing horizontal and vertical interoperability properties, i.e., between layers of a protocol stack or end-to-end communication between distant entities. in order to test interoperability, we have defined a correlation algorithm between the events collected from different network views (client or network side). once the correlation has been performed, we apply the contextual signatures that characterize interoperability properties to check their validity. to illustrate the application of the proposed approach, a real case study is proposed: the wireless application (wap) protocol. the results of the experimentation performed on this protocol are also presented.
webflowah: an environment for ad-hoc specification and execution of web services-based processes. this paper presents webflowah, an environment for ad-hoc specifying and executing web services-based business processes. webflowah employs common domain ontology to describe both web services and business processes. it allows specifying processes in terms of users' goals or desires that are expressed based on the concepts of such common domain ontology. this approach allows processes to be specified in an abstract high-level way, unburdening the user from dealing with underlying details needed to effectively run the process workflow.
identifying vulnerabilities and critical requirements using criminal court proceedings. information systems governed by laws and regulations are subject to civil and criminal violations. in the united states, these violations are documented in court records, such as complaints, indictments, plea agreements, and verdicts, which thus constitute a source of real-world software vulnerabilities. this paper reports on an exploratory case study to identify legal vulnerabilities and provides guidance to practitioners in the analysis of court documents. as legal violations occur after system deployment, court records reveal vulnerabilities that were likely overlooked during software development. we evaluate established requirements engineering techniques, including sequence and misuse case diagrams and goal models, as applied to criminal court records to identify mitigating requirements that improve privacy protections. these techniques, when properly applied, can help organizations focus their risk-management efforts on emerging legal vulnerabilities. we illustrate our analysis using criminal indictments involving the u.s. health insurance portability and accountability act (hipaa).
nectar: a dtn routing protocol based on neighborhood contact history. there are a number of scenarios where connectivity is intermittent, and a given destination may not be reachable at the moment a message is sent. networks with these characteristics are known as delay and disruption tolerant networks (dtn). the nectar protocol proposed in this article is based on the contacts history in order to create a neighborhood index and then determine the most appropriated route for dtns. simulations performed with real data retrieved from mobile and wireless environments at dartmouth college in scenarios where the occurrence of highly-partitioned networks is frequent, and with the presence of resource constrained nodes show that nectar is able to deliver more messages than epidemic and prophet protocols with lower consumption of network resources.
integration of formal specification, review, and testing for software component quality assurance. the reliability of software components is the most important quality required for software systems constructed using component-based development paradigm. this paper describes an approach to integrating formal specification, review, and testing for software component quality assurance. in this approach, requirements errors can be removed and missing requirements can be identified by formalizing requirements into a formal specification, and the resulting specification can then be used as a firm foundation for a rigorous review and testing of the program that is intended to provide a correct implementation. we discuss how formalization, review, and testing work together at different levels of software development for improving software quality through detecting and removing errors in documentation.
incremental outlier detection in data streams using local correlation integral. in this paper, an incremental outlier detection technique capable of dealing with a large amount of data is presented and evaluated in the context of intrusion detection. the proposed method is based on the local correlation integral (loci for short). the detection technique consists of two parts. the first part named insertion receives the sequence of input point and updates multi-granularity deviation factor (mdef) of the point at intervals. the second part named deletion deletes one or a batch of points. this technique is able to process streaming data in a single scan. moreover, the number of updates in the incremental loci algorithm per insertion/deletion of a single data record does not depend on the total number of data records. experimental results with real life data sets show that the technique is capable of dealing with data streams, successfully detecting outlier.
taking total control of voting systems: firmware manipulations on an optical scan voting terminal. the firmware of an electronic voting machine is typically treated as a "trusted" component of the system. consequently, it is misconstrued to be vulnerable only to an insider attack by someone with an in-depth knowledge of the system and access to the source code. this case study focuses on the diebold/premier accuvote optical scan voting terminal (av-os) that is widely used in the usa elections. we present three low level manipulations of the above voting terminal's firmware resulting in divergence from its prescribed operation: (i) the first bestows the terminal with a powerful memory card dumping functionality, (ii) the second enables the terminal to leak the ballot details through its serial port thus violating voter privacy during the election, (iii) the final third firmware manipulation is a proof of concept attack that swaps the votes of two candidates thus permanently destroying the election outcome in an undetectable fashion. this demonstrates the extent to which the firmware of the av-os can be modified with no insider knowledge or access to the source code. our results underscore the importance of verifying the integrity of the firmware of electronic voting terminals accompanied by sound auditing procedures to maintain the candor of the electoral process. we also note that this work is performed solely with the purpose of security analysis of av-os, and the first and the second firmware manipulations we describe serve a dual purpose in assisting the technological audits of actual voting procedures conducted using av-os systems.
flexible features: making feature modules more reusable. a growing trend in software construction advocates the encapsulation of software building blocks as features which better match the specification of requirements. as a result, programmers find it easier to design and compose different variations of their systems. feature-oriented programming (fop) is the research domain that targets this trend. we argue that the state-of-the-art techniques for fop have shortcomings because they specify a feature as a set of building blocks rather than a transition that has to be applied on a software system in order to add that feature's functionality to the system. we propose to specify features as sets of first-class change objects which can add, modify or delete building blocks to or from a software system. we evaluate this approach by implementing a simple text editor in a feature-oriented way and use the implementation to produce four different program variations. this shows that our approach contributes to fop on three levels: expressiveness, composition verification and bottom-up feature-oriented development.
artificial intelligence applied to computer forensics. to be able to examine large amounts of data in a timely manner in search of important evidence during crime investigations is essential to the success of computer forensic examinations. the limitations in time and resources, both computational and human, have a negative impact in the results obtained. thus, better use of the resources available are necessary, beyond the capabilities of the currently used forensic tools. herein, we describe the use of artificial intelligence in computer forensics through the development of a multiagent system and case-based reasoning. this system is composed of specialized intelligent agents that act based on the experts knowledge of the technical domain. their goal is to analyze and correlate the data contained in the evidences of an investigation and based on its expertise, present the most interesting evidence to the human examiner, thus reducing the amount of data to be personally analyzed. the correlation feature helps to find links between evidences that can be easily overlooked by a human expert, specially due to the amount of data involved. this system has been tested using real data and the results were very positive when compared to those obtained by the human expert alone performing the same analysis.
assessing complexity of service-oriented computing using learning classifier systems. the design paradigm service-orientation combines several proven design elements - such as decentralization, and scalability - with design elements from recent technology evolution, in particular abstraction and loosely coupling. however, few work has been conducted to investigate the complexity associated with service-oriented systems. this work provides an overview on complexity in soc, outlines the challenges in assessing complexity in soc, and proposes an experiment-based approach to assess the impact of various inherent properties on the complexity of service-oriented systems.
cmc-umc: a framework for the verification of abstract service-oriented properties. cmc and umc are two prototypical instantiations of a common logical verification framework for the analysis of functional properties of service-oriented systems. the service-oriented socl logic is used to describe the required system properties. computational models of the system can be built either using the cows specification language or designing the system as a collection of interacting uml state machines, and an on-the-fly model checker can be used to verify the satisfaction of the requirements and possibly to generate counterexamples or witnesses for them. an automotive case study is used to illustrate the overall framework.
improving stream correlation attacks on anonymous networks. the level of anonymity offered by low latency, interactive, anonymous networks is unknown. this paper implements correlation attacks on the deployed tor network and a simulated tor network under defined network conditions. the accuracy of the attacks act as a metric for the networks anonymity in the face of a passive adversary. from observation of the deployed tor network, several techniques were developed to compensate for some of the modifications the tor protocol induces in traffic. these techniques increase correlation accuracy by 10% to 40% for differing correlation functions. almost 50% of traffic streams on the simulated network are identified immediately with 10% of experimental traffic on the real tor network identified.
erika and open-zb: an implementation for real-time wireless networking. ieee 802.15.4/zigbee and tinyos have been playing an important role in leveraging a new generation of large-scale networked embedded systems. however, based on previous experience on the implementation and use of the ieee 802.15.4/zigbee protocols over tinyos, several problems (producing loss of synchronization and even network failures) emerge due to some limitations of this os, namely related to the lack of task pre-emption and prioritization. when real-time guarantees are required, different software solutions must be used to support real-time services in such networked applications. this being our objective, we implemented the ieee 802.15.4 protocol over erika, a real-time operating system for resource-constrained embedded systems. the results attained so far, and summarized in this short paper, demonstrate that erika enables reliable network behaviour and improved network performance. this paper outlines the most important aspects of the software implementation and reports comparative experimental results based on real platforms.
a novel distance-based classifier built on pattern ranking. instance-based classifiers that compute similarity between instances suffer from the presence of noise in the training set and from over-fitting. in this paper we propose a new type of distance-based classifier that instead of computing distances between instances computes the distance between each test instance and the classes. both are represented by patterns in the space of the frequent itemsets. we ranked the itemsets by metrics of itemset significance. then we considered only the top portion of the ranking that leads the classifier to reach the maximum accuracy. we have experimented on a large collection of datasets from uci archive with different proximity measures and different metrics of itemsets ranking. we show that our method has many benefits: it reduces the number of distance computations, improves the classification accuracy of state-of-the art classifiers, like decision trees, svm, k-nn, naive bayes, rule-based classifiers and association rule-based ones and outperforms the competitors especially on noise data.
designing reliable real-time concurrent object-oriented software systems. coordinated atomic actions is a conceptual framework used to increase the reliability (by fault tolerance) of concurrent object-oriented software systems. an extension of this conceptual framework to support the modelling of real-time software systems has been proposed. in this work we present our proposal for improvements of this extension focusing on recovery process optimisation, non-determinism reduction and time-related constructs extension.
heterogeneous bipolar criteria satisfaction handling in geographical decision support systems: an lsp based approach. in decision making, it is sometimes more appropriate to express what has to be rejected rather than what is permitted. moreover, permitted and rejected cases do not necessarily have to mirror each other, which is called heterogeneous bipolarity. to efficiently deal with heterogeneous bipolarity in decision making, a new bipolar criteria satisfaction modelling framework is proposed in this paper. this framework is based on independent degrees of satisfaction and dissatisfaction. its use and advantages are illustrated within the context of suitability maps for geographical decision making. a suitability map reflects the overall suitability of a specific area for a selected type of use. in a general case, the suitability of a location depends on a variety of criteria that are specified using reasoning techniques that are typical for soft computing. these criteria are evaluated and their resulting satisfaction and/or dissatisfaction degrees are aggregated using graded logic functions within the framework of the lsp method.
information retrieval from visual databases using multiple representations and multiple queries. this paper deals with information retrieval from visual databases. we propose an approach based on multiple representations, multiple queries, and the fusion of results returned by these different representations and queries. the basic idea of data fusion in information retrieval is to use several models, several representations, several search strategies, several queries, etc., and then fuse (merge) the results returned by each model, representation, strategy or query in a unique list of results by using appropriate fusion models. doing so, retrieval effectiveness should be improved without necessarily altering, in an important way, retrieval efficiency. we consider both the general retrieval case as well as the invariant retrieval case. we consider the case of textures in particular. benchmarking carried out on two (2) image databases shows that retrieval relevance is improved in a very appreciable way with the fused model.
improving folksonomies quality by syntactic tag variations grouping. folksonomies offer an easy method to organize information in the current web. this fact and their collaborative features have derived in an extensive involvement in many social web projects. however they present important drawbacks regarding their limited exploring and searching capabilities, in contrast with other methods as taxonomies, thesauruses and ontologies. one of these drawbacks is an effect of its flexibility for tagging, producing frequently multiple variations of a same tag. in this paper we propose a method to group syntactic variations of tags using pattern matching techniques. we propose the utilization of a fuzzy similarity measure and we conclude that this technique offers better results than other classic techniques after comparing them on a large real dataset.
revealing common sources of image spam by unsupervised clustering with visual features. in this paper, we investigate image spam with data mining techniques in order to reveal the common sources of unsolicited emails. to identify the origins, a two-stage clustering method groups visually similar spam images by exploring their visual features, including color feature, layout feature, text layout, and background textures. we test the proposed approach under different settings and combinations of features and measure the performance with a modified f-measure.
augmented reality environment for life support training. the area of medical qualification in life support training is being constantly improved. however, many problems still have to be faced in the training sessions. during these sessions the students or physicians can repetitively practice patient care procedures in simulated scenarios using anatomical manikins, especially designed for this type of training. current manikins have several resources incorporated to allow and facilitate qualified training, such as pulse, arrhythmia and auscultation simulator. however, some deficiencies have been detected in the existing ls training structure. for example: automatic feedback to the students in consequence of their actions on the manikin, images like facial expressions and body injuries, and their combination with sounds that represent the clinical state of the patient. the main goal of the arlist project is to qualify the traditional training environment currently used for ls training, introducing image and sound resources into the training manikins. thought these features we can simulate some aspects such as facial expressions, skin color changes and scratches and skin injuries through image projection over the manikin body, and also play sounds like cries of pain or groans of an injured man.
a case study of pattern-based software framework to improve the quality of software development. in recent years, development of the software industry and demand for software systems have increased rapidly, but developers often does not know whose suggestion to follow regarding methodologies of software engineering. one reason for that is the difficulty in applying new software engineering technologies. developers take a long time to train. another reason is the difficulty in integrating case toolsets. so many indeterminate factors make the development process more and more complex. on the other hand, software development is too customized, and software reuse is difficult. the reasons above are the cause for software development and maintenance to become more complex and difficult to control. in this paper we explore the importation of a software pattern-based framework, and the development of an erp/support chain system. based on software patterns, developers can separate development and business so as to reduce problems caused by the developer's lack of business experience. the quality of the product can thus be enhanced, software development costs be reduced, and software maintenance be improved.
method for fast compression of program codes for remote updates in embedded systems. this paper presents the technology for remote system updating that allows software updates in embedded systems such as mobile phones and car navigation systems. software updates are carried out using binary difference, software construction, and fast compression technologies. in this paper, we focus on a fast bpe (byte pair encoding) method of encoding program codes in embedded systems and show the index of relations between the updating time and the downloaded data size.
applying reo to service coordination in long-running business transactions. this paper presents an approach to formal modeling of long-running business transactions. our solution is based on the channel-based exogenous coordination language reo, which is an expressive, compositional and semantically precise design language that admits formal reasoning.
reasoning about comprehensions with first-order smt solvers. this paper presents a technique for translating common comprehension expressions (sum, count, product, min, and max) into verification conditions that can be tackled by two off-the-shelf first-order smt solvers. since a first-order smt solver does not directly support the bound variables that occur in comprehension expressions, the challenge is to provide a sound axiomatisation that is strong enough to prove interesting programs and, furthermore, that can be used automatically by the smt solver. the technique has been implemented in the spec# program verifier. the paper also reports on the experience of using spec# to verify several challenging programming examples drawn from a textbook by dijkstra and feijen.
learning the ontological theory of an information extraction system in the multi-predicate ilp setting. in recent years, numerous works have been carried out to design information extraction (ie) systems able to extract genic interaction networks from text. usually, the extraction procedure is completed by so-called extraction patterns, which are often limited to map textual fragments to a single semantic relation. such poor representations do not take into account the complexity of the data processed by biologists. ie systems need sophisticated representations, encoded with ontologies, allowing the definition of multiple relations, and of the (possibly recursive) dependencies between them. up to now, machine learning techniques used to acquire extraction patterns, i.e. binary or multi-class learners, reflect those representation restrictions. they assume independence between target predicates, and do not handle recursion. in this paper, we use inductive logic programming in a multi-predicate setting to learn extraction patterns fitted to an ontological context. multi-predicate ilp is an important paradigm which allows to learn recursive theories. we experimented our framework on a bacillus subtilis bacterium text corpus, in which we reach a global recall of 67.7% and a precision of 75.5% in ten-fold cross-validation.
model interfaces for two-way obliviousness. a key problem in software development is producing systems that are maintainable even as the concerns at play evolve. aspect-oriented programming (aop) seeks to foster maintainability by isolating the specifications of cross-cutting concerns, allowing them to be modified in relative isolation from the rest of the system. research in aspect-oriented modeling (aom) aims to develop a model-layer analogue of aop, allowing integration with accepted modeling practices. aspects usually allow developers of the primary model to be oblivious to the aspects that modify the primary model; because of this, aspects can be closely coupled to potentially transient details of the primary model. when those details change, the aspects that depend on them may no longer have the desired effect. in this paper, we introduce model interfaces as a solution to the problem of obliviousness by extending a graph-transformational approach to aom.
conceptualization and implementation of a microscopic pedestrian simulation platform. this work reports on our first steps toward the implementation of a platform for pedestrian simulation in multimodal exchange interfaces. whereas most approaches in pedestrian simulation are aimed at studying interactions among people using a common environment with different purposes and under different mobility restrictions, our research is focused on how those interactions will ultimately affect transportation operations at multimodal stations. this paper starts with a general overview of pedestrian simulation, focusing on the microscopic representation of individuals and their interoperability that will be the basis for the system architecture briefly presented.
eliciting required characteristics for usable requirements engineering approaches. it has been reported that many software companies do not use existing requirements engineering approaches. this indicates that there is room and opportunity for improving the usability of existing requirements engineering approaches. this paper describes a market study intended to elicit a set of characteristics that could improve the usability of requirements engineering approaches. the survey is aimed toward software stakeholders such as developers, designers, customers, and managers at various software companies. the survey results are used to define a set of desirable characteristics for usable requirements engineering approaches and to suggest a set of guidelines that could help achieve the desirable characteristics.
preciso: a reengineering process and a tool for database modernisation through web services. a common trend in service oriented architecture (soa) is to consider information systems exposing software as services. this current approach is not only applied to new software developments, but also it is related to the maintenance of legacy systems. nowadays, a cornerstone of information systems are relational databases, which constitute meaningful sources of services. these services can provide database's information in soa scenarios. this paper presents a reengineering process to recover and implement web services in automatic manner from relational databases. this process follows the adm approach (architecture-driven modernization). in this paper authors present a case study that has been carried out using a tool built to support the process. this tool is used to generate a set of web services which are integrated into a web development allowing to modernise the legacy database in a soa context. this case study has been carried out in the context of software company indra.
a gradient oriented recombination scheme for evolution strategies. this paper proposes a novel recombination scheme for evolutionary algorithms, which can guide the new population generation towards the maximum increase of the objective function. given the current sample points and their function evaluations, the shepard's interpolation method is used to approximate the underlying objective function in that local region. we then compute the gradient of the estimated function which in consequence leads to an iterative process, called the mean shift, for searching the local function optimum. in each mean shift step, we calculate the weighted mean of sample points in the kernel window, followed by shifting the location of the kernel to the computed mean. such iterative process eventually converges to the point at which the estimated objective function has zero gradient. we use the converged point as the output of our recombination operator. experimental results show that such gradient based recombination scheme can improve the efficiency of optimization search in evolutionary algorithms.
jointly optimizing data acquisition and delivery in traffic monitoring vanets. vehicular ad hoc networks (vanets) are envisaged to become a flexible platform for monitoring road traffic, which will gradually replace more cumbersome fixed sensor deployments. the efficacy of vehicle-assisted traffic monitoring systems depends on the freshness of traffic data that they can deliver to users, and the bandwidth used to do so. clearly, high data freshness will allow users to estimate trip times accurately, and to select the fastest route to a destination. low bandwidth utilization will allow the traffic monitoring application to coexist symbiotically with a wide variety of vehicle-based applications, ranging from road safety to advertising and entertainment. in this paper, we investigate the problem of minimizing the bandwidth utilization of a vehicle-assisted traffic monitoring system, whilst adhering to user-defined requirements for data freshness. the novelty of our approach is that we jointly optimize two intertwined aspects of traffic monitoring: data acquisition and data forwarding. we investigate how their combined operation trades data freshness for bandwidth utilization, and we propose a novel mechanism that fine-tunes their parameters to optimize the overall system performance. our mechanism is evaluated using realistic vehicular traces on a real city map.
a new probabilistic generative model of parameter inference in biochemical networks. we present a new method for estimating rate coefficients and level of noise in models of biochemical networks from noisy observations of concentration levels at discrete time points. its probabilistic formulation, based on maximum likelihood estimation, is key to a principled handling of the noise inherent in biological data, and it allows for a number of further extensions, such as a fully bayesian treatment of the parameter inference and automated model selection strategies based on the comparison between marginal likelihoods of different models. we developed kinfer (knowlegde inference), a tool implementing our inference model. kinfer is downloadable for free at http://www.cosbi.eu.
privacy preserving churn prediction. churn prediction is an important component of customer retention to predict whether a current customer decides to take business elsewhere or voluntarily terminates service, so marketing campaigns can target at the potential churners for retention efforts. in this paper we provide a strategy to protect customers' privacy in churn prediction. first of all, we demonstrate how to use data distortion to mask a telecom customer dataset, and then apply churn prediction methods to the distorted data. since the distorted data are so different from the original data the privacy of customer is preserved, but the prediction methods we proposed will not compromise the accuracy of churn prediction. the performance of several data distortion methods are compared and evaluated.
mining functional associated patterns from biological network data. the recent development of high-throughput biological techniques for functional genomics have generated a large quantity of new biological network data. analyzing these networks provides novel insights in understanding basic mechanisms controlling cellular processes. in this paper, we integrate protein interaction and microarray data and transform the un-weighted protein-protein interaction network to its weighted correspondent. we then present a novel graph mining problem, mining functional associated patterns across the weighted genome-wide network. the central idea of the problem is to detect groups of objects having highly associated with each other in interaction networks, and hypothesize these groups denote function modules. we develop an efficient algorithm, maps, which exploits several pruning techniques to mine maximal functional associated patterns. a systematic performance study is reported on protein-protein interaction networks and gene coexpression data. the experimental results show that the proposed method is efficient and has good predictive performance.
simulating human intuitive decisions by q-learning. simulations have become a great tool for research in the natural sciences. however their potential has not been reached far enough in the social sciences. this is in part due to the difficulty in simulating human decision making and reproducing human-like behavior. recent advances in neo-classical decision making have defined specific differences between the decision making capabilities of rational agents and humans as well as speculations into the cause. presented is a q-learning model for simulating human-like decision making based upon the intuition deliberation model proposed by psychologists kahneman and tversky. the model is tested against the classic economic bargaining game. in this game humans and rational agents consistently converge onto distinctly different strategies. our experiments show that a selfish agent defers from the strategy of the rational agent and is more similar to human strategy.
the visual authoring tool of flash-based component for interactive item template. current on-line testing systems are lacks of supplying versatile interactive answering alternatives such as click and select, drag and drop, link, collide and magnetize. this research have integrated the reusable component and framework technology, and composed an interactive item template software component construction. each interactive item template component ("iitc" in abbreviation) which is created by using flash actionscript technology symbolizes a different operation and interactive scenario. we also define a script language in xml format to flatten or unflatten the item objects. meanwhile, c/c++ language was employed to develop corresponding visual item authoring system which can dynamically load iitc to add new types of item template to create new items. under our software component model, software component developer can easily cultivate iitc with the rich multimedia function provided by actionscript language. visual item authoring system with dynamic loading iitc offers user a simple way to use iitc. the script language of iitc has also added diversity to the interactive scenario of each iitc.
flexible self-healing gradients. self-healing gradients are distributed estimates of the distance from each device in a network to the nearest device designated as a source, and are used in many pervasive computing systems. with previous self-healing gradient algorithms, even the smallest changes in the source or network can produce small estimate changes throughout the network, leading to high communication and energy costs. we observe, however, that in many applications, such as routing and geometric restriction of processes, devices far from the source need only coarse estimates, and that a device need not communicate when its estimate does not change. we have therefore developed flex-gradient, a new self-healing gradient algorithm with a tunable trade-off between precision and communication cost. when distance is estimated using flex-gradient, the constraints between neighboring devices are flexible, allowing estimates to vary by an amount proportional to a device's distance to the source. frequent small changes in the network or source thus cause frequent estimate changes only within a distance proportional to the magnitude of the change, as verified in simulation on a network of 1000 devices. this can enable drastic reductions in the communication and energy cost of gradient-based algorithms.
mobility aware path maintenance in ad hoc networks. current research on routing in ad hoc networks consider route discovery as the main problem and literature describes numerous on-demand protocols that discover a path between a source-destination pair. in contrast, the route maintenance phase is relatively neglected, and most protocols resort to route discovery as a result of route failure. we argue that this approach is inefficient, due to the fact that these protocols treat route failures in the same way as route discovery, and hence, the quality of service suffers from the additional delays resulting from the route rediscovery overhead. for data sessions over long periods of time, there is a good chance that the initial route discovered will fail before the session ends. thus, an intelligent protocol should be more proactive in maintaining routes so that packets may be readily switched to an alternate route when the route failure occurs, rather than wait for the route to break to restart the route discovery process. in this paper, we describe an efficient protocol that carries out route maintenance using path reliability information, and analyze the effect of using reliability information in path selection. simulations results show that our approach outperforms aodv in terms of increased throughput and reduced overhead. our approach can be an useful enhancement to on-demand routing protocols to increase their overall efficiency.
heterogeneous real-time embedded software optimization considering hardware platform. this paper classifies embedded software into four models according to hardware platform and execution time. we propose an algorithm, cmpch (cost minimization with probability for configurable hardware) that efficiently solves the configurable hardware, no-fixed execution time model, which is the most complicated model among the four models we proposed according to hardware platform and execution time. cmpch can solve other three models also. our approach fully takes advantage of configurable hardware and the soft real-time feature to improve the system performance. experimental results show our approach achieves significant cost-reduction comparing with previous work.
a class of multistep sparse matrix strategies for concept decomposition matrix approximation. in information retrieval, text documents are usually modeled as a term-document matrix which has high dimensional and space vectors. to reduce the high dimensions, one of the various dimensionality reduction methods, concept decomposition, has been developed by [3]. this method is based on document clustering techniques and least-square matrix approximation to approximate the matrix of vectors. gao and zhang [4] have indicated that the retrieval accuracy from the concept decomposition can be comparable to that from latent semantic indexing. however the numerical computation is expensive. in this paper we presented a class of multistep spare matrix strategies for concept decomposition matrix approximation. in this approach, a series of simple sparse matrices are used to approximate the decompositions. our numerical experiments show the advantage of such an approach in terms of storage costs and query time compared with other approaches while maintaining comparable retrieval quality.
scene map on wireless mobile platform. mobile devices equipped with gps provide powerful tools for location-aware applications. adding views to locations further augments users' perception of spaces. this work proposes a systematic approach to establish scene maps of a city with local, route, and object panoramas. the scene map is an ideal digest to access spatial information. we design comprehensive visual indexes for virtual travel and real guidance of an area based on pdas. the extended fields of view of various panoramas enhance the understanding of spaces on small mobile devices. densely embedded indexes from views allow free transitions and exploration in the urban area.
frequent spatio-temporal patterns in trajectory data warehouses. in this paper we present an approach for storing and aggregating spatio-temporal patterns by using a trajectory data warehouse (tdw). in particular, our aim is to allow the analysts to quickly evaluate frequent patterns mined from trajectories of moving objects occurring in a specific spatial zone and during a given temporal interval. we resort to a tdw, based on a data cube model, having spatial and temporal dimensions, discretized according to a hierarchy of regular grids, and whose facts are sets of trajectories which intersect the spatio-temporal cells of the cube. the idea is to enrich such a tdw with a new measure: frequent patterns obtained from a data-mining process on trajectories. as a consequence these patterns can be analysed by the user at various levels of granularity by means of olap queries. the research issues discussed in this paper are (1) the extraction/mining of the patterns to be stored in each cell, which requires an adequate projection phase of trajectories before mining; (2) the spatio-temporal aggregation of patterns to answer roll-up queries, which poses many problems due to the holistic nature of the aggregation function.
an approach for component testing and its empirical validation. the lack of information limits component consumers to understand candidate components sufficiently in a way they can check if a given component fulfills its goal. thus, this paper presents an approach to support component testing aiming to reduce the lack of information between component producers and component consumers. additionally, the approach is covered by a case tool integrated in the development environment. an experimental study was performed in order to evaluate its efficiency and difficulties of its use. the experimental study indicates that the approach is viable and the tool support provides effort reduction to component producers and component consumers.
: a new function update scheme by arbitration between a remote call and a dynamic update for wireless sensor networks. in this paper, we propose arbiter-recall, which is a new kind of function code update management. when a function requires updating, arbiter-recall adaptively selects an energy-efficient method, deciding between a remote-call and a local-call after updating a function. the run-time decision is made by analyzing the cost of a remote-call, and a local-call with dynamic function update in terms of the energy consumption. simulation results show that arbiter-recall significantly reduces energy consumption compared to existing schemes.
constructing process views for service outsourcing. service outsourcing is a business paradigm in which an organization has a part of its business process performed by a service provider. the outsourced service can be specified in a public process view, which shields secret or irrelevant details from the internal business process of the provider. this way, the provider can reveal only public, relevant parts of its private business process to the client organization. to allow efficient monitoring and control by a consumer, a provider can offer a public activity as either invokable or observable.
shader space navigator: a turbo for an intuitive and effective shading process. in this paper, we first point out difficulties faced by cg artists in the shading process: (1) a lot of technical details on shaders required, (2) long rendering time, and (3) repeated cumbersome trial-and-errors. to make them overcome such difficulties, we propose shader space navigator, a system that efficiently searches for shaders similar to a given query shader. with shader space navigator, cg artists find quality shaders from the database that are very close to the final result shader, and thus complete the shading process easily by slightly tuning some attributes of those shaders. as a result, the cg artists can create their final shaders in an intuitive and efficient way thereby avoiding a large number of time-consuming rendering processes.
aspect-oriented procedural content engineering for game design. generally progressive procedural content in the context of 3d scene rendering is expressed as recursive functions where a finer level of detail gets computed on demand. typical examples of content procedurally generated are fractal images and noise textures. unfortunately, not always the content can be expressed in this way, developers and content creators need the data to have some peculiarity (like windows on a wall for a house 3d model) and a method to drive data simplification without losing relevant details. in this paper we discuss how aspect oriented (ao) techniques can be used to drive the content creation process by mapping each data peculiarity to the code to generate it. using aspects will let us to partially evaluate the code of the procedure improving the performance without losing the flow of the generation logic. we will also discuss how the use of ao can provide techniques to build simplified version of the data through code transformations.
a role-based enterprise architecture framework. organizations deal with contrasting domains such as people, strategy, business processes, and information systems as well as with their representation, alignment and governance. in this setting, different approaches to enterprise architecture have been introduced to address these concerns. this paper focuses on describing an enterprise architecture framework centered in three core concepts (role, entity and activity) from which domain-specific concepts are derived from. the framework abstracts the organization's domains as five architectural views (organization, business, information, application and technology) and captures the concept dependencies and relationships across the different domains.
failure management development for integrated automotive safety-critical software systems. nowadays the number of vehicles equipped with electronic components is increasing rapidly by replacing mechanical and hydraulic systems. the most advanced cars function appropriately via more than 50 electronic control units (ecus), sensors and actuators that exchange more than 2500 electronic signals among them. the electronic components are interconnected with automotive bus systems. there are several bus systems that have been developed or improved in automotive bus systems to meet the different requirements for automotive applications: local interconnection network (lin), controller area network (can), flexray and media oriented system transport (most). however, there are demands to combine these different bus systems to increase the efficiency and safety of the vehicle systems. failure management is a most challenging problem in car industry since the integrated automotive system needs to communicate with software/hardware components on the different bus systems in a car. the discussion on how to interconnect those automotive bus systems in a safety-critical way is addressed in the paper, where failure management should be applied.
measuring coherence between electronic and manual annotations in biological databases. the use of controlled structured vocabularies for annotation purposes, such as the gene ontology (go) is currently one of the strategies to cope with the increasingly cumbersome task of genome annotation. the gene ontology annotation database (goa) uses go to annotate gene products through curated literature analysis and uncurated electronic methods. although electronic annotations constitute the large majority of annotations (over 95%), most researchers are reluctant to use them in their studies, since they are regarded as having a lower quality than curated ones. assessing the quality of electronic annotations may help clarify the advantages and disadvantages of their use. this paper proposes a preliminary measure of electronic annotation quality based on the coherence between electronic and manual annotations. coherence is analysed both at the gene product and at the annotation level, based on semantic similarity of gene ontology terms. we have found that average annotation coherence values are around 60%, but can be as high as 81% for a less granular analysis. based on this analysis we propose meaningful coherence thresholds for electronic annotation selection and filtering, and for highlighting gene products for annotation revision.
semanticqa: web-based ontology-driven question answering. the ability to ask specific question to the internet using natural language and receiving answers instead of documents is highly desired. recent advancements in semantic web technologies make it possible to support such capability with more accuracy compared to existing non-semantic techniques. using our expertise in ontology building and semantic search and discovery we designed an ontology-driven question answering system that extracts answers from web documents. this system processes natural language queries using a background ontology and finds possible answer(s) to the question from web documents.
medical volume segmentation using bank of gabor filters. in this paper, we will present an unsupervised approach for segmenting medical volume images based on texture properties. the texture properties of the volume data are defined based on spatial frequencies as implemented using a statistical method known as gabor filters. each gabor filter in the bank is tuned to detect patterns of a specific frequency and orientation when convolved with a medical volume. the convolution is performed in the fourier domain and the resulting response image is a feature which is added to our feature vector. the feature vector is thus passed into a classification/segmentation algorithm.
partitioning web applications between the server and the client. web 2.0 and rich internet application technologies are offering more and more sophisticated means for building compelling applications. at the same time the development of applications is becoming increasingly complex. while web applications are commonly relying on server-side processing, we aim at implementing a "fat client" and running applications mostly on the client. with this in mind we can derive a set of guidelines on how the applications should be partitioned between the server and the client. by following these directives and leaning on the traditional principles of good software development, we can address the issues of complexity that have lately emerged in web development.
learners automated evaluation with the odala approach. we present in this paper odala approach (ontology-driven auto-evaluation for e-learning approach) for an automated evaluation of the learners state of knowledge. the context considered is computer based human learning environnement (cbhle) in a self-learning by doing mode. this approach, that we put in work and test in the setting of a self-learning system for an algorithmic language, is founded on the representation of the teaching domain as domain ontology on the one hand and on errors classification and detection on the other hand. the evaluation process that we recommend is structured in four stages, starting from the learner solution form analysis (that consists at this step of our research to a lexico-syntactic analysis) and finish with the update of the learner model, while passing by a semantic analysis and a marking process. after a brief introduction of the main aspects raising of the cbhle domain to which we refer here, we develop our approach of the learners evaluation problem, while especially insisting on its independence of the teaching domain and on the possibility to take in account answers to open questions, freely built by the learner. we also present, at the end, the results of the algorithmic self-learning system development, where the main stages of our evaluation approach are implemented.
searching for relevant software change artifacts using semantic networks. the discovery of software artifacts (files, documents, and datasets) relevant to a change request, can increase software reuse and reduce the cost of software development and maintenance. however, traditional search techniques often fail to provide the relevant documents because they do not consider relationships between software artifacts. we propose the creation of semantic networks which convey such relationships and assist in automatically discovering not only the requested artifacts based on a user query, but additional relevant ones that the user may not be aware of. subsequently, we increase the accuracy of the returned artifacts by applying appropriate contexts. experimental results show that this approach leads to better recall and precision compared to existing full-text search approaches.
kenro: a virtual machine monitor mostly described in haskell. we report on our experiences developing a tiny virtual machine monitor, named kenro, mostly in haskell as a concrete example of low-level, hardware-dependent system software. the development of kenro was greatly helped by features of haskell, including higher-order functions, strong static typing, and the automatic memory management. we describe the advantages and limitations of haskell studied through our development experience.
a new inter-layer prediction scheme for spatial scalability with different frame rates. to provide spatial, temporal and quality scalabilities, the scalable video coding (svc) offers several additional techniques. the inter-layer prediction is one of them to improve the coding efficiency. however, it is only applied to the enhancement layer when the base layer is available. because of this limited inter-layer prediction, it deteriorates the coding efficiency of enhancement layer. in this paper, we propose a new inter-layer prediction scheme for spatial scalability with different frame rates. it improves the coding efficiency using the information of the interpolation layer when the base layer is not available. the experimental results show that the proposed scheme reduces the bitrates by 2~10% and improves video quality by 0.01~0.4db compared with the reference software, jsvm 11.0.
towards a fast enterprise ontology based method for post merger integration. our research program aims at finding and testing method components for deciding on and implementing organizational splits and mergers. we tested a method to timely detect design & migration issues of a post merger integration. using actors from enterprise ontology as organization building blocks for two large operationally merging airliners, experts systematically listed per actor (a) its organizational implementations, (b) its quality of business and (c) its it implementations. the drafted demo construction model appeared to be the first neutral and shared language for describing the essence of the business. also the results needed for decision making (a) were experienced as a necessary and sufficient validation of operational integrity and (b) were delivered fast, yielding a high return on modeling effort.
certification of smart-card applications in common criteria. this paper describes the certification of smart-card applications in the framework of common criteria. in this framework, a smart-card application is represented by a model of its specification, a functional specification describing an input-output relationship, a low-level design, and implementation code. the certification process consists of the following tasks: (1) prove that the model, the functional specification, the low-level design, and the code satisfy security properties in the smart-card application's specification, and (2) prove that there is a representation correspondence between each two consecutive representations. for each task, a certificate or a collection of certificates are needed to certify the accomplishment of the task. all representations of a smart-card application are essentially programs and the representation correspondences are properties relating two programs. we show that a theory of program properties can be applied to the certification process. the theory provides foundations for describing and proving properties of a single program and properties relating two programs. the theory provides a notion of certificate that is essential to the certification process.
matching to subtyping. the notion of thistype has been proposed to promote typesafe reuse of binary methods and recently extended to mutually recursive definitions. it is well-known, however, that thistype does not match with subtyping well. in the current type systems, type safety is guaranteed by the sacrifice of subtyping, hence dynamic dispatch. in this paper, we propose two mechanisms, namely, nonheritable methods and local exactization to remedy the mismatch between thistype and subtyping. we rigorously prove their safety by modeling them in a small calculus.
a spatial bitmap-based index for geographical data warehouses. in this paper we propose the spatial bitmap index (sb-index), which is an index based on bitmap and minimum bounding rectangle (mbr) to provide efficient query processing in geographical data warehouses. the sb-index is built on the primary key of a spatial dimension table, and maintains the mbr of a given spatial attribute. query processing requires a scan on the index, which compares both the query spatial predicate and the current mbr. this scan supplies a set of candidate solutions to a refinement step that evaluates each candidate. finally, only the index entries from objects that satisfy the spatial predicate must be accessed, in order to answer the submitted query. comparisons between the sb-index and the star-join indexed with r-tree and gist showed significantly improvement of 25% up to 95% with regards to the query processing time. this performance gain occurs since sb-index restricts a set of candidates and avoids the star-join calculation.
self-organized control of knowledge generation in pervasive computing systems. pervasive computing devices (e.g., sensor networks, localization devices, cameras, etc.) are increasingly present in every aspect of our lives. these devices are able to generate enormous amounts of data, from which knowledge about situations and facts occurring in the world can be inferred; inference can also be done by combining data items and generating new (higher-level) ones. such data and knowledge is of extreme importance for to context-aware and mobile services. however, we are left with the problem that the possibly huge amount of data and knowledge generated can be very hard to be analyzed and made usable in real-time. the core of the problem in today's pervasive environments lies between the ability to extract meaningful (useful) knowledge from the data while making sure the total amount of data does not become overwhelming to the system. this paper focus on this trade-off using (without loss of generality) the w4 model for contextual data as a case study. starting from the basic mechanism by which the w4 model autonomously generate new knowledge, the paper shows how this can generate knowledge overflow, and propose a method to select---in a self-organizing way---what kinds of knowledge should be generated based on their importance; hence preventing knowledge overflow. experimental results are reported to support our arguments and proposals.
reconstructing strip-shredded documents using color as feature matching. this paper discusses the destroyed documents that have been strip-shredded, which is a often problem in forensic science. the proposed method first extracts features based on color of the boundaries and then computes the nearest neighbor algorithm to carry out the local reconstruction. in this way the overall complexity can be dramatically reduced because few features are used to perform the matching. the preliminary results reported in this paper, which take into account a two hundred documents database, demonstrate that color-matching-based method produces interesting results for the problem of document reconstruction and can be of interest to the forensic document examiners and provide some effective solutions for law enforcement practitioners.
alternatives to conjunctive query processing in peer-to-peer file-sharing systems. peer-to-peer file-sharing systems suffer from the over-specification of query results due to the fact that query processing is conjunctive and the descriptions of shared files are sparse. ultimately, longer queries, which should yield more accurate results, do the opposite. to alleviate this problem, we consider alternative means of query processing. that is, results are sent from the server to the client only if they are deemed relevant based on cosine similarity. based on our results, these alternatives can increase query accuracy by 40% at virtually no cost.
simulation supporting the design of self-organizing ambient intelligent systems. the ambient intelligence scenario depicts electronic environments that are sensitive and responsive to the presence of people. the aim of this kind of system is not necessarily to provide some form of electronic service to its users, but also to enhance the everyday experience of people moving inside the related physical environment. for this type of application, computer simulation represents a useful way to envision the behaviour of responsive environments without actually bringing them into existence in the real world. this paper will describe the simulation of an adaptive illumination facility, a physical environment endowed with a set of sensors that perceive the presence of humans (or other entities such as dogs, bicycles, cars) and interact with a set of actuators (lights) that coordinate their state to adapt the ambient illumination to the presence and behaviours of its users.
two lower bounds for self-assemblies at temperature 1. self-assembly is an autonomous process by which small simple parts assemble into larger and more complex objects. self-assembly occurs in nature, for example, when atoms combine to form molecules, and molecules combine to form crystals. it has been suggested that intricate self-assembly schemes will ultimately be useful for circuit fabrication, nanorobotics, dna computing, and amorphous computing [2, 7]. to study the process of self-assembly we use the tile assembly model proposed by rothemund and winfree [5]. this model considers the assembly of square blocks called "tiles" and a set of glues called "binding domains". each binding domain has a strength. each of the four sides of a tile can have a glue on it that determines interactions with neighbouring tiles. the two neighbouring tiles form a bond if the binding domains on the touching sides are the same. the strength of this bond is the strength of the matching binding domain. the process of self-assembly is initiated by a single seed tile and proceeds by attaching tiles one by one. a tile can only attach to the growing complex if it binds strongly enough, i.e., if the sum of the strengths of its bonds to the existing complex is at least the temperature &tau;. it is assumed that there is an infinite supply of tiles of each tile type. when this growing process stops, i.e., no tile can be attached to the existing complex, we say that the tile system has assembled this shape. a tile system is specified by the seed tile, the set of tile types, the strengths of glues and the temperature. the physical plausibility and relevance of this abstraction was demonstrated by simple self-assembling systems of tiles built out of certain types of dna molecules [3, 4]. in this paper we only consider self-assembly at temperature &tau; = 1. self-assemblies at temperature &tau; > 1 have been considered in [5, 6, 1]. a measure of complexity of self-assembly is the minimum number of distinct tile types needed to uniquely assemble a certain shape (assembles the shape but does not assemble any other shape). if we want to assemble any scaled version of a given shape, then the complexity depends on the expressibility (kolmogorov complexity) of the shape [6]. if we want to assemble a given shape with a prescribed size, then in [5] it was observed that assembling an n x n full square (a square where there is a bond between any two adjacent tiles) at &tau; = 1 requires n2 distinct tile types. in fact, one can see that any uniquely produced 2-connected full assembly with p tiles requires p tile types (all tiles must be distinct). if we do not require a bond between every two adjacent tiles of a uniquely produced assembly the number of used tile types can be significantly smaller. in particular, in [5] a tile system that uniquely assembles an n x n square using only 2n - 1 tile types was described. the construction is based on a comb-like backbone graph of the n x n square. moreover, it was conjectured in [5] that this is best possible.
lightweight monitoring of sensor software. wireless sensors are very small computers, and understanding the timing and behavior of software written for them is crucial to ensuring that they perform correctly. this paper outlines a lightweight method for gathering behavioral and timing information from simulated executions of software written in the nesc/tinyos environment. the resulting data is used to generate both behavioral and timing profiles of the software, using uml sequence diagrams to visualize the behavior and to present the timing information.
visualization of information flows in a very large social network. in this paper, we present our research result that enables users to navigate a very large social network and to take a look at information flows on the network. to this end, we devise two techniques; (i) mapping a very large social network to a 2-dimensional graph layout, and (ii) exploring the graph to all directions with zooming it in/out. with these methods, we can also look through information flows over social networks.
an approach to detection of uml-based ownership violation. in this paper, we study how to detect the ownership violation based on the unified modeling language (uml 2.0) in ibm eclipse modeling framework. we develop a novel technique for automatically detecting the ownership violation in a program against its design class diagram using a software model checker. specifically, given the fields that are intended to implement ownership in a uml class diagram, our approach checks the ownership property in two steps. first, the approach systematically generates all valid object diagrams, i.e. valid input program states. then, after a method to destroy the owner object is called on each object diagram, the approach checks whether all external links to the owned objects have been removed. central to this approach is how to prune away the large search space that includes all valid input program states.
the synergy of precise and fast abstractions for program verification. predicate abstraction is a powerful technique to reduce the state space of a program to a finite and affordable number of states. it produces a conservative over-approximation where concrete states are grouped together according to a given set of predicates. a precise abstraction contains the minimal set of transitions with regards to the predicates, but as a result is computationally expensive. most model checkers therefore approximate the abstraction to alleviate the computation of the abstract system by trading off precision with cost. however, approximation results in a higher number of refinement iterations, since it can produce more false counterexamples than its precise counterpart. the refinement loop can become prohibitively expensive for large programs. this paper proposes a new abstraction refinement technique that combines slow and precise predicate abstraction techniques with fast and imprecise ones. it allows computing the abstraction quickly, but keeps it precise enough to avoid too many refinement iterations. we implemented the new algorithm in a state-of-the-art software model checker. our tests with various real life benchmarks show that the new approach systematically outperforms both precise and imprecise techniques.
on scheduling soft real-time tasks with lock-free synchronization for embedded devices. in this paper, we consider minimizing the system-level energy consumption through dynamic voltage scaling for embedded devices, while a) allowing concurrent access to shared objects through lock-free synchronization b) meeting (m, k))-constraint, and c) completing as many high importance tasks as possible. we present a scheduling algorithm called lock-free utility accrual algorithm (or mk-lfua) to meet these goals. at offline stage, we set the optimal cpu speed to minimize system-level energy consumption. at run-time, the algorithm dynamically adjusts the cpu speed to compensate for slack time. our simulation studies on the intel pxa271 processor model illustrate mk-lfua's superiority over past work by 15-25%.
supporting recovery, privacy and security in rfid systems using a robust authentication protocol. rfid systems have been scrutinized nowadays as one of the emerging technologies in pervasive environment. and authentication becomes indispensible in applications where security and privacy are major concerns. besides thwarting some major attacks, rfid systems need to be able to recover from unexpected conditions during operation. in this paper, we propose a robust authentication protocol (roap) that supports not only security and privacy, but also recovery in rfid systems. the protocol can get back the desynchronized tags and readers to their normal state, and thus provides robustness. we also present a "safety ring" consisted of six major goals that have to ensure by each rfid system to be secured. this paper illustrates security and robustness analysis of the protocol. finally, we present the implementation of our authentication protocol.
incorporating accountability into internet email. email used to be the "number one killer application" of the internet. however, misuse and abuse such as spam, phishing, and malware attacks have plagued the email systems. considering deterrence as important as prevention and protection in countering misuse and abuse, we aim to improve the accountability in the email system beyond identification and non-repudiability. full accountability should be an intrinsic condition for trust, and it constitutes the basis of deterrence against email misuse and abuse. therefore, we propose to use a layered trust management framework to help email receivers eliminate their unwitting trust and provide them with accountability support. this helps systems to deter misuses and address wrongdoings. by describing and analyzing how our trust management facilitates email accountability, we also show that it can be used to improve the trustworthiness of the internet services as a whole.
using artificial life techniques for distributed grid job scheduling. grids are an emerging infrastructure providing distributed access to computational and storage resources. handling many incoming requests at the same time and distributing the workload efficiently is a challenge which load balancing algorithms address. current load balancing implementations for the grid are central in nature and therefore prone to the single point of failure problem. this paper introduces two distributed artificial life-inspired load balancing algorithms using ant colony optimization and particle swarm optimization. distributed load balancing stands out as a robust algorithm in regard to any topology changes in the network. the implementation details are given and evaluation results show the efficiency of the two distributed load balancing algorithms.
visual loop-closing with image profiles. this paper investigates the ability of image profiles, pixel-intensity sums across subsets of a video stream, to support the crucial robotic skill of place recognition through visual information alone. building from work in which image profiles are the fundamental image representation for a model of biological neural processing [3, 4, 5], this paper offers a conceptually simpler approach to simultaneous localization and mapping via a single camera (monocular slam). in contrast to feature-based approaches in which extraction and statistical post-processing dominate the computation, this work uses a representation suitable even for very simple autonomous platforms. experiments demonstrate the ability of our profile-based path segments to compensate for the inevitable inaccuracies in odometry when creating consistent world maps.
simplifying security policy descriptions for internet servers in secure operating systems. secure operating systems (secure oses) are widely used to limit the damage caused by unauthorized access to internet servers. however, writing a security policy based on the principle of least privilege for a secure os is a challenge for an administrator. considering that remote attackers can never attack a server before they establish connections to it, we propose a novel scheme that exploits phases to simplify security policy descriptions for internet servers. in our scheme, the entire system has two execution phases: an initialization phase and a protocol processing phase. the initialization phase is defined as the phase before the server establishes connections to its clients, and the protocol processing phase is defined as the phase after it establishes connections. the key observation is that access control should be enforced by the secure os only in the protocol processing phase to defend against remote attacks. thus, we can omit the access-control policy in the initialization phase, which effectively reduces the number of policy rules. our experimental results demonstrate that our scheme effectively reduces the number of descriptions; it eliminates 47.2%, 27.5%, and 24.0% of policy rules for http, smtp, and pop servers respectively, compared with an existing selinux policy that includes the initialization of the server.
tweast: a simple and effective technique to implement concrete-syntax ast rewriting using partial parsing. abstract syntax trees (asts) are commonly used to represent an input/output program in compilers and language processing tools. many of the tasks of these tools consist in generating and rewriting asts. such an approach can become tedious and hard to maintain for complex operations, namely program transformation, optimization, instrumentation, etc. on the other hand, concrete syntax provides a natural and simpler representation of programs, but it is not usually available as a direct feature of the aforementioned tools. we propose a simple technique to implement ast generation and rewriting in general purpose languages using concrete syntax. our approach relies on extensions made in the scanner and the parser and the use of objects supporting partial parsing called texts with embedded abstract syntax trees (tweasts). a compiler for a simple language (tiger) written in c++ serves as an example, featuring transformations in concrete syntax: syntactic desugaring, optimization, code instrumentation such as bounds-checking, etc. extensions of this technique to provide a full-fledged concrete-syntax rewriting framework are presented as well.
itrustu: a blog recommender system based on multi-faceted trust and collaborative filtering. blogs give users a channel to express their knowledge and feelings with individuals worldwide, explaining the exponential growth of new blogs. however, due to the diverse subjects covered by bloggers, bloggers/readers have difficulty in finding valuable articles from the hundreds of millions of blogs on the internet. to help ease information overload in the blogosphere, this work proposes a trust-enhanced collaborative filtering approach that integrates multi-faceted trust based on article type and user similarity. an online blog article recommender system, called itrustu, is also designed to evaluate the effectiveness of the proposed approach in terms of accuracy and quality of recommendations. results of a 45-day online experiment with 179 participants from the internet demonstrate that the proposed integrated approach yields a significantly higher accuracy than traditional approaches, especially for cold-start users. analysis results indicate that trust and similarity among bloggers/readers have a significantly positive correlation in the blogosphere. effective recommender systems can be achieved by exploiting trust relationships in a trust network. the proposed approach is applicable not only to the blogosphere, but also to online social communities when trust relationships already exist between users.
the unique solution for problem. in this paper, we make the study on the unique solution for the p3p problem. after partitioning the space into several regions, the parametric function and target function for each region are presented. under the condition of knowing the approximate relative position between center of perspective and control points, the unique solution can be obtained.
abstraction of multiple executions of object-oriented programs. recovering software behaviors from execution traces is useful in program comprehension and maintenance. multiple executions upon different test inputs can help to locate program behaviors related to a particular use case, i.e. a specific functionality. an abstraction and visualization environment abstracer was developed, and experiments have been performed on an open-source software, jhotdraw.
semi-automatic parallelization of direct and inverse problems for geothermal simulation. we describe a strategy for parallelizing a geothermal simulation package using the shared-memory programming model openmp. during the code development openmp is employed for the direct problem in such a way that, in a subsequent step, the openmp-parallelized code can be transformed via automatic differentiation into an openmp-parallelized code capable of computing derivatives for the inverse problem. performance results on a sun fire x4600 using up to 16 threads are reported demonstrating that, for the derivative computation, an approach using nested parallelism is more scalable than a single level of parallelism.
global-to-local representation and visualization of molecular surfaces using deformable models. macromolecules such as proteins and enzymes are responsible for most of cellular functionality. many molecular interactions, such as protein-protein interactions or protein-ligand binding, occur at what can be defined as the molecular surface. the topology of the molecular surface is often complex, containing various geometric features such as clefts, cavities, tunnels, and flat regions. these geometric features coupled with non-geometric physicochemical properties influence surface-based molecular interactions. consequently analysis of molecular surfaces is crucial in elucidating structure-property relationships of molecules. in this paper we propose a method for visualizing a molecular surface in a manner that preserves and elucidates salient features. the method involves mapping of a molecular surface to a standard spherical coordinate system. the ability to map arbitrary molecular surfaces to a standard coordinate system aids in comparison of surface features across different molecules. the mapping is accomplished by enclosing the molecular surface by a sphere, and then iteratively deforming the sphere until it converges by wrapping the entire molecular surface. this allows a one-to-one relationship to be established between points on the molecular surface and points on the surface of the sphere. the presence of discontinuities such as tunnels in the molecular surface can be identified by detecting collision between patches of the deforming sphere. subsequently, the deformable surface is restored back to the sphere, retaining the mapping. features and properties defined at the molecular surface are then mapped and visualized in the standard spherical coordinate system. the proposed approach has several key advantages. first, it allows a global-to-local visualization of molecular surfaces. second, it facilitates comparison of specific features as well as collection of features within and across molecules by mapping them to a common coordinate system. third, the method allows visualization of both geometric and non-geometric surface properties. fourth, specific molecular characteristics can be visualized individually or in combination on-demand. finally, and crucially the advantages offered by the proposed visualization do not involve simplification of the surface characteristics thereby ensuring that no loss of potentially important information occurs.
spam decisions on gray e-mail using personalized ontologies. e-mail is one of the most common communication methods among people on the internet. however, the increase of e-mail misuse/abuse has resulted in an increasing volume of spam e-mail over recent years. as spammers always try to find a way to evade existing spam filters, new filters need to be developed to catch spam. a statistical learning filter is at the core of many commercial anti-spam filters. it can either be trained globally for all users, or personally for each user. generally, globally-trained filters outperform personally-trained filters for both small and large collections of users under a real environment. however, globally-trained filters sometimes ignore personal data. globally-trained filters cannot retain personal preferences and contexts as to whether a feature should be treated as an indicator of legitimate e-mail or spam. gray e-mail is a message that could reasonably be considered either legitimate or spam. in this paper, a personalized ontology spam filter was implemented to make decisions for gray e-mail. in the future, by considering both global and personal ontology-based filters, we can show a significant improvement in overall performance.
stratified division queries involving ordinal user preferences. in this paper, we are interested in taking preferences into account for a family of queries inspired by the relational division. a division query aims at retrieving the elements associated with a specified set of values and usually the results remain not discriminated. so, we suggest the introduction of preferences inside such queries with the following specificities: i) the user gives his/her preferences in an ordinal way and ii) the preferences apply to the divisor which is defined as a hierarchy of sets. different uses of the hierarchy are investigated, which leads to queries conveying different semantics and the property of the result in terms of a quotient is studied. a special attention is paid to the implementation of such queries using a regular database management system and some experimental results illustrate the feasibility of the approach.
new content-aware request distribution policies in web clusters providing multiple services. due to the explosive growth of the internet and increasing service demands from all around the world, the cluster-based system that consists of one request-dispatching server and several request-handling servers has become a cost-effective way to serve the huge amount of service demands. nowadays, web servers have to handle more complex types of requests since requests from clients may be mixed with dynamic web pages, database processing, or multimedia stream data. therefore, a web cluster should be designed with intelligent request dispatching policies for supporting various types of service requests. in this paper, we have proposed two new content-aware request distribution policies named locality-aware request distribution with replication and classification (lard/rc) and grouped client-aware policy (gcap) to dispatch requests efficiently in web clusters providing multiple types of services and running in homogeneous or heterogeneous environments. we have implemented our proposed policies in the lvs-cad web cluster that can efficiently perform content-aware request dispatching. performance evaluation shows that our proposed lard/rc and gcap policies could dispatch requests of different types to proper back-end servers in a more efficient way to utilize system resources than the other existing policies in both homogeneous and heterogeneous environments.
visual navigation: image profiles for odometry and control. this paper investigates the extent to which image profiles, pixel-intensity sums across subsets of a video stream, offer a basis for autonomous robotics. building on previous work that uses image profiles for odometry, we introduce an improved algorithm for odometric estimation based on visual input alone. in addition, we extend prior results by showing how image profiles can support control and exploration tasks. we validate these new approaches through results implemented atop a low-cost vision-only vehicle consisting of a laptop and an irobot create.
robust scheduler for grid networks. imprecise input data imposes additional challenges to grid scheduling. this paper introduces a novel scheduler based on fuzzy optimization called ip-full-fuzzy which considers uncertainties of both application demands and of resource availability. the effectiveness of the proposed scheduler is compared to those of a non-fuzzy scheduler as well as to those of a fuzzy scheduler which considers only uncertainties of application demands. results evince the advantages of adopting the proposed scheduler.
facial image classification of mouse embryos for the animal model study of fetal alcohol syndrome. fetal alcohol syndrome (fas) is a developmental disorder caused by maternal drinking during pregnancy. computerize imaging techniques have been applied to study human facial dysmorphology associated with fas. this paper describes a new facial image analysis method based on a multi-angle image classification technique using micro-video images of mouse embryo. images taken from several different angles are analyzed separately, and the results are combined for classifications that separate embryos with and without alcohol exposures. analysis results from animal models provide critical references for the understanding of fas and potential therapy solutions for human patients.
an extensible simulation tool for overlay networks and services. research community on distributed systems, and in particular on peer-to-peer systems, needs tools for evaluating their own protocols and services, as well as against other protocols with the same preconditions. since a (tcp/ip) experimental evaluation is not always feasible, simulation tools appeared. in this paper we introduce planetsim, a discrete event-based simulation framework tool for overlay networks and services, as well as extensions from third parties that prove its true extensibility and adaptability to the researchers' needs. in addition, we introduce within planetsim a novel methodology for implementing peer-to-peer overlay protocols based on behaviors.
online annotation and prediction for regime switching data streams. regime switching models, in which the state of the world is locally stationary, are a useful abstraction for many continuous valued data streams. in this paper we develop an online framework for the challenging problem of jointly predicting and annotating streaming data as it arrives. the framework consists of three sequential modules: prediction, change detection and regime annotation, each of which may be instantiated in a number of ways. we describe a specific realisation of this framework with the prediction module implemented using recursive least squares, and change detection implemented using cusum techniques. the annotation step involves associating a label with each regime, implemented here using a confidence interval approach. experiments with simulated data show that this methodology can provide an annotation that is consistent with ground truth. finally, the method is illustrated with foreign exchange data.
geographical data collection in sensor networks with self-organizing transaction cluster-heads. this paper proposes 2g, a flexible and energy-efficient data collection protocol for sensor networks for increasing network lifetime. to this end, it integrates self-organizing data aggregation mechanisms based on geographical and cluster-based routing, and transaction cluster-head (tch). a tch is a location-based role, dynamically assigned to a node for the duration of handling a request-response transaction that targets its region of the network. tch nodes collect raw sensor readings from their local regions and forward the answers containing aggregated data using geographical routing. a prototype of 2g was implemented on micaz motes, and experimental results in realistic conditions proved that data collection reaches significantly higher delivery rates than with gear, the geographical routing protocol leveraged by 2g. additionally, simulation results for larger scale networks demonstrate that 2g outperforms gear in terms of network lifetime.
representing refactoring opportunities. approaches for the representation of refactoring opportunities and their association with refactorings are usually described in an informal basis. this informality can hamper the creation of catalogues and tools to represent and search for refactoring opportunities. we propose an unified way to represent both the conditions in which the application of a refactoring can be advantageous and the mechanisms to associate these conditions with refactorings. the resulting representation mechanisms can be used to express search criteria based on software metrics, structural problems, heuristics or improvements on the software quality.
data parallel dialect of scheme: outline of the formal model, implementation, performance. we outline new functional programming language and stack-based model of implicit parallel execution of programs. the language, called schemik, is high-level lexically-scoped implicitly-parallel dialect of scheme. schemik is designed as an implicitly parallel language, meaning that the parallel execution of programs is done independently of the programmer and each program written in schemik always produces the same results no matter which parts of the program are executed simultaneously. the execution of programs is formally described by transitions of a particular pushdown automaton working with two stacks. because of the limited scope of this paper, we just outline key ideas and postpone detailed description to a full version of this paper.
a personalized framework for trust assessment. the number of computational trust models has been increasing quickly in recent years yet their applications for automating trust evaluation are still limited. the main obstacle is the difficulties in selecting a suitable trust model and adapting it for particular trust modeling requirements, which varies greatly due to the subjectivity of human trust. the personalized trust framework (ptf) presented in this paper aims to address this problem by providing a mechanism for human users to capture their trust evaluation process in order for it to be replicated by computers. in more details, a user can specify how he selects a trust model based on information about the subject whose trustworthiness he needs to evaluate and how that trust model is configured. this trust evaluation process is then automated by the ptf making use of the trust models flexibly plugged into the ptf by the user. by so doing, the ptf enable users reuse and personalize existing trust models to suit their requirements without having to reprogram those models.
term distribution visualizations with focus+context. many text searches are meant to identify one particular fact or one particular section of a document. unfortunately, predominant search paradigms focus mostly on identifying relevant documents and leave the burden of within-document searching on the user. this research explores term distribution visualizations as a means to more clearly identify both the relevance of documents and the location of specific information within them. we present a set of term distribution visualizations and introduce a focus+context model for within-document search and navigation.
applying latent dirichlet allocation to group discovery in large graphs. this paper introduces lda-g, a scalable bayesian approach to finding latent group structures in large real-world graph data. existing bayesian approaches for group discovery (such as infinite relational models) have only been applied to small graphs with a couple of hundred nodes. lda-g (short for latent dirichlet allocation for graphs) utilizes a well-known topic modeling algorithm to find latent group structure. specifically, we modify latent dirichlet allocation (lda) to operate on graph data instead of text corpora. our modifications reflect the differences between real-world graph data and text corpora (e.g., a node's neighbor count vs. a document's word count). in our empirical study, we apply lda-g to several large graphs (with thousands of nodes) from pubmed (a scientific publication repository). we compare lda-g's quantitative performance on link prediction with two existing approaches: one bayesian (namely, infinite relational model) and one non-bayesian (namely, cross-association). on average, lda-g outperforms irm by 15% and cross-association by 25% (in terms of area under the roc curve). furthermore, we demonstrate that lda-g can discover useful qualitative information.
infinite bar-joint frameworks. some aspects of a mathematical theory of rigidity and flexibility are developed for general infinite frameworks and two main results are obtained. in the first sufficient conditions, of a uniform local nature, are obtained for the existence of a proper flex of an infinite framework. in the second it is shown how continuous paths in the plane may be simulated by infinite kempe linkages.
optimizing techniques for saturated arithmetic with first-order linear recurrence. saturated arithmetic is a typical operation in multimedia applications, most multimedia extensions in the instruction set architecture (isa) of modern processors provide saturation instructions for such operation. therefore, extensive researches have focused on how to utilize saturation instructions to optimize programs. previous algorithms mainly focus on purely saturated arithmetic, however saturated arithmetic is often mingled with first-order linear recurrence (folr) in real life applications. when flor pattern appears in the program, previous algorithms can not identify the saturated arithmetic as well. in fact, the saturated arithmetic with folr (sawf) is a new and significant pattern, especially, sawf with one as coefficient is frequently used in multimedia applications. hence, it is necessary to explore a method with which such pattern can be efficiently vectorized. this paper discusses how to vectorize sawf, explores the efficient method to vectorize sawf with one as coefficient and gives its evaluation and implement a library for the optimizing technique. such an implementation manner can make compilers are able to exploit it more easily. the experimental results shows the optimizing technique can achieve a speedup of 1.19 to 1.46 on pentium iv processor. at the same time, the optimizing techniques in this paper can also be used to develop a library for sawf so a programmer can benefit even without changing the compiler.
atm: an automatic trust monitoring algorithm for service software. while providing services to stakeholders, service software can be exploited by potentially untrustworthy users. given that, it is necessary to monitor the trust relationships between service providers and requestors for potential vulnerabilities they may invite to the total system. in this paper, we propose an automatic trust monitoring algorithm called atm based on the specification of trust relationships in trust scenarios and the quantification of the relationships through trust calculation schemes. trust rules are generated from the trust scenarios ready to be deployed at run-time. a service requestor is penalized for the violation of a trust rule and rewarded for no such violation. this analysis facilitates the quantification of the trustworthiness of service requestors and the accuracy of the recommendations from other service providers that can be used to make dynamic decisions on the corresponding requestors. the monitor is implemented in a prototype file sharing grid and evaluated using file sharing applications.
vector stream processing for effective application of heterogeneous parallelism. heterogeneous multicore chipsets with many levels of parallelism are becoming increasingly common in high-performance computing systems. effective use of parallelism in these new chipsets is paramount. we present a 3d chemical transport module optimized for the cell broadband engine architecture (cbea). by leveraging the heterogeneous parallelism of the cell with a method we call vector stream processing, our transport module achieves performance comparable to two nodes of an ibm bluegene/p, or eight xeon cores, on a single cell chip. performance of the module on two cbea systems, an ibm bluegene/p, and an eight-core shared-memory intel xeon workstation are given.
the sum-of-increments constraint in the consecutive-ones matrix decomposition problem. the combinatorial problem of decomposing an integer matrix into a small positive linear combination of binary matrices that have the consecutive-ones property arises in cancer radiotherapy delivery planning. a fast constraint programming approach for this problem exists. i present a propagation algorithm for a constraint in this approach that can speed up solving by an order of magnitude.
designing a distributed aop runtime composition model. in this paper we present damon, a new distributed aspect-oriented composition model. our model mimics the ccm and is based on computational reflection, component-based design, and separation of concerns. moreover, we benefit from the peer-to-peer substrate to implement these services in a decentralized and efficient way. damon aims to provide new distributed concerns (i.e. replication) to existent or new applications transparently. it reduces the complexity of application development and allows runtime reconfiguring. the innovative contributions of our approach are composition capabilities in design, load-time and runtime phases, including the definition of distributed aspects and meta-aspects.
designing of a system model for web 3d disabled access gis on web 2.0. this paper aims to propose our study of system model design for a web 3d disabled access gis. the disabled access gis provides the disabled with information on barriers and barrier-free modifications in consideration of their abilities and psychologies. we model the system for web-based accesses. it enhances its reusability and mash-up capability. our model clearly divides database access, server-side service and client-side user interface. we implemented desktop client and mobile phone client to examine the model.
adaptive optimal checkpoint interval and its impact on system's overall quality in soft real-time applications. soft real-time systems often have to consider both timing and probabilistic fault-tolerance requirements. when checkpointing techniques are used for fault tolerance purposes, the checkpointing frequency unyieldingly affects the system's overall quality measured by an integrated value of system qos properties, such as availability, task execution time, and task deadline miss probability. in this paper, we first formally analyze the relationships between checkpoint interval and system availability, task execution time, and task deadline miss probability, respectively by considering a poisson probabilistic fault model. we further define the system's overall quality as a weighted sum of these three qos measures, from which an optimization problem is formulated to decide the checkpoint interval that maximizes system's overall quality. also presented in the paper are a prototype implementation of a framework that allows adaptive checkpointing and a set of experiments executed upon the framework that further validate our analytical results.
requirements engineering using appreciative inquiry for an online community of caregivers of children with autism. appreciative inquiry, commonly used in organizational development, aims to build organizations, processes or systems based on success stories using a hopeful vision for an ideal future. it produces positive results with organizational change management. we adjusted the user requirements process for an online community of caregivers of children with autism and compared it with the traditional approach. based on case studies with 4 special education teachers, we found that appreciative inquiry was effective for obtaining meaningful requirements and extremely useful in encouraging buy-in with novice users. this outcome was in stark contrast to the traditional approach where our participants showed no interest in an online community. in addition to these results, we present lessons learned in adjusting the appreciative inquiry process for user requirements analysis.
forensic bite mark identification using image processing methods. forensic dentistry generally addresses the problem of identifying individuals based on the properties of teeth or identifying individuals based on bite mark impressions. it is legally relevant to accurately and reliably match a bite mark impression to place a criminal at the scene of a crime. therefore, a system which minimizes human interaction to conduct the comparison would be beneficial to ensure accuracy and reduce human bias. this paper describes experiments with developing a semi-automated method to compare 3d dental models taken from candidate humans and bite mark impression images left in the scene of the crime. once the contours from the bite mark image and the 3-dimensional dental model are captured, the ideal alignment is calculated by finding the transformation which minimizes a distance measure. the best match is then identified by performing this comparison to a set of candidate dental models. the results are compared to identification results by human forensic odontology experts.
response time analysis of software transactional memory-based distributed real-time systems. we consider distributed real-time systems where concurrency control is managed using software transactional memory (or stm). for such a method we propose an algorithm to compute an upper bound on the response time. we compare the result of the proposed algorithm to a simulation of the system being studied in order to determine its efficacy. the results of our study indicate that it is possible to provide timeliness assurances for systems programmed using stm.
a pointing method using two accelerometers for wearable computing. a variety of real-world situations are beneficial for wearable computing since it provides information services while users are doing other jobs. therefore, a simple and hands-free input interfaces have suitable for these computer operations. however, such interface has not been achieved with conventional input devices such as mice or track balls. although gesture or eye-gaze input techniques have also been developed for wearable computing, they also suffer from problems i.e., a slow pointing speed, difficulty in carrying devices, and complexity in parallel use when doing tasks. we propose a new method of pointing using input of simple gestures with two accelerometers. by dividing the specifications of two coordinates into a combination of two independent motions, we accomplish accurate and intuitive pointing. a user attaches two small accelerometers to both his/her hands or both elbows. the pointing is done by using the intersection of two straight lines, and the movement of the lines is synchronized with that of the accelerometers. in addition, we also propose a method of changing the position of objects being pointed at that is new approach. the results we obtained from our evaluation experiments confirmed that our method was effective.
on the verification of probabilistic i/o automata with unspecified rates. we consider the probabilistic i/o automata framework, for which we address the verification of reachability properties in case the rates (also called delay parameters) are unspecified. we show that the problem of finding (or even approximating) the supremum probability that a set of states is reached is undecidable. however, we give an algorithm to obtain a non-trivial over-estimation of this value. we explain why this over-estimation may result useful for many systems. finally, in order to compare our approach against markov decision processes, we study a simple protocol for anonymous fair service. in this case, the over-estimation computed over the pioa gives a more realistic result than the exact computation over the mdp.
an approach to identifying conversation dependency in service oriented system during dynamic evolution. dynamic evolution is required in soas (service oriented architecture) with complex business processes to adapt to the opening environment of internet and ever changing requirement of user. this paper proposes an approach to identifying conversation dependency between business processes to facilitate the dynamic evolution. in our approach, a business process is represented as a directed graph, and the matrix method is used to identify the execution order of activities in the business process, which determines the conversation dependency.
static type inference for ruby. many general-purpose, object-oriented scripting languages are dynamically typed, which provides flexibility but leaves the programmer without the benefits of static typing, including early error detection and the documentation provided by type annotations. this paper describes diamondback ruby (druby), a tool that blends ruby's dynamic type system with a static typing discipline. druby provides a type language that is rich enough to precisely type ruby code we have encountered, without unneeded complexity. when possible, druby infers static types to discover type errors in ruby programs. when necessary, the programmer can provide druby with annotations that assign static types to dynamic code. these annotations are checked at run time, isolating type errors to unverified code. we applied druby to a suite of benchmarks and found several bugs that would cause run-time type errors. druby also reported a number of warnings that reveal questionable programming practices in the benchmarks. we believe that druby takes a major step toward bringing the benefits of combined static and dynamic typing to ruby and other object-oriented languages.
bipolar query satisfaction using satisfaction and dissatisfaction degrees: bipolar satisfaction degrees. since many years, research on flexible querying of regular databases aims at making database systems better accessible, and this by allowing queries to be formulated in a more human consistent manner. in general, this is done by allowing the user to express preferences, which are not necessarily strict, but can be approximately specified. as a result, a satisfaction degree can be calculated for each record in the database, expressing the degree to which the particular record satisfies the users preferences. in addition to this, bipolar querying adds the notion of both positive and negative preferences in handling flexible queries. the reason for this is that it is sometimes more feasible for a user to express what is undesirable than to express what is desirable. moreover, satisfactory and unsatisfactory cases do not necessarily have to be each others reverse, which is called heterogeneous bipolarity. to deal with this heterogeneous bipolarity, this paper introduces a new bipolar query satisfaction modeling framework, where, besides a satisfaction degree, also an independent dissatisfaction degree is used.
requirements modelling and evaluation for digital preservation: a cots selection method based on controlled experimentation. most methods for the general problem of commercial-off-the-shelf component selection use goal-oriented requirements modelling and multi-criteria decision making techniques and are applicable across a wide range of domains. this usually implies high levels of complexity. recently a very specific selection problem emerged in the context of digital preservation. the selection of the most suitable tool to keep a type of digital object alive when the original technical environment ceases to exist is a highly complex domain-specific selection problem with several peculiarities: highly homogeneous functionality across tools, complex evaluation of quality across settings, and a high need for automation, standardisation, and documentation. this paper describes an evidence-based empirical methodology for cots component selection in digital preservation through controlled experimentation. we describe the specific selection problem, show how the process of utility analysis can be tailored to fit the problem space and describe the methodology, which is geared towards automated evaluation in an empirical setting. we outline existing tool support and discuss case studies and future directions.
opportunistic real-time routing in multi-hop wireless sensor networks. wireless sensor networks (wsns) are subject to significant resource constraints. particularly, routing protocols for low-rate wsns suffer from maintaining routing metrics and stable links of paths. even though opportunistic routing protocols are well-suited to wsns, they have some weaknesses for supporting real-time data and low power consumption. this paper proposes a new routing protocol called opportunistic real time routing (or ortr) that guarantees delivery of data under time constraints with efficient power consumption. in order to satisfy time requirements, an area where real-time data must be delivered is defined with effective transmission power and a relay node within the area is selected for the purpose of balancing overall energy levels. we compare existing routing protocols against ortr through a set of simulation experiments. our simulation results illustrate that ortr provides guaranteed real-time service with optimal transmission power without degrading the energy balance.
towards "wydiwys" for mimi using concept analysis. this paper presents a novel software engineering approach for developing a dynamic web interface that meets the quality criterion of "wydiwys" - what you do is what you see. this approach establishes an engineering procedure for applying formal concept analysis (fca) [3] in user requirement analysis, system design and implementation. the fca lattice diagrams facilitate the design of a role-based web interface by contributing to the analysis of relationships between roles, functionalities, and database access actions. as a result, they help identifying privileges that are needed by each role to perform required functionalities and page partials and views as web interface components. additionally, the relabeled fca lattices direct developers in adding privilege checks in the page partial or view components to help implement the desired access control architecture. the fca based approach is demonstrated in the development of mimi, a multi-modality, multi-resource, information integration environment for the nci-designated case comprehensive cancer center (case ccc). we present the resulting hierarchical lattice diagrams and show that the fca-based approach benefits the life-cycle development process for mimi's complex web interface.
foreground classification using active template in the scene context for visual surveillance. this paper presents an integrated framework for real-time target category recognition integrating the active template matching and the context of visual surveillance. the active templates are in the form of a dictionary of active features (bases), which are allowed to slightly shift at different locations and orientations. they can be learned for each object type from a small set of positive samples that roughly aligned. with these learned deformable templates, the moving foregrounds subtracted from background model are recognized through searching maximum matching likelihood. to avoid the exhaustive search for template matching and reduce the noise disturbance, a scheme to estimate target size and pose at specific location is developed based on the contextual information of scene geometry. this framework can be an independent module embedded into a visual surveillance system. its performance and benefit of using context are quantitatively demonstrated on public dataset with comparisons.
towards inference of more realistic xsds. the xml has undoubtedly become a standard for data representation and manipulation. but most of xml documents are still created without the respective description of their structure, i.e. an xml schema. hence, in this paper we focus on the problem of automatic inferring of an xml schema for a given sample set of xml documents. contrary to existing works, whose aim is to infer as concise schema as possible, we focus on inferring of a more realistic result, i.e. a schema that is closer to human-written ones and bears more precise information. for this purpose we extend and combine the existing verified techniques (such as aco heuristics or mdl principle) with a set of heuristics exploiting semantics of element/attribute names, thesauri or statistical analysis of input data. using a set of examples we show and discuss advantages of our proposal.
an ontology-based application in heart electrophysiology: representation, reasoning and visualization on the web. computational technologies have been increasingly explored to make biomedical knowledge and data more accessible for human understanding, comparison, analysis and communication. in this context, ontology has been recognized in the bioinformatics literature as a suitable technique for advancing knowledge and data representations in biomedicine. moreover, automated reasoning and visualization mechanisms can favor in providing support for human comprehensibility as well as in dealing with the complexity inherent to this domain. this paper elaborates on the application of ontology for heart electrophysiology representation, reasoning and visualization on the web. the ontology-based application we propose can be used to offer support for interactive learning in heart electrophysiology.
super-resolution image reconstruction using the generalized isotropic multi-level logistic model. high spatial resolution images are usually required in a great number of applications such as video surveillance, for instance. super-resolution reconstruction methods use image processing techniques to estimate a high-resolution image based on a set of low-resolution observations of the same scene. therefore, these methods are able to overcome cost and hardware limitations inherent to acquisition devices. this paper discusses a maximum a posteriori probability approach, characterizing the high-resolution estimation with the isotropic multi-level logistic model that incorporates pixel similarity in a meaningful way to the super-resolution context. following, the high-resolution estimation is derived by maximizing the local conditional probabilities sequentially with the iterated conditional modes algorithm. the proposed method was evaluated in a simulated framework using the normalized mean square error criterion, and in a real situation using video frames. the results indicate the effectiveness of our approach both by numerical and visual evaluation.
annotating uddi registries to support the management of composite services. the future of service-centric environments suggests that organizations will dynamically discover and utilize web services for new business processes particularly those that span multiple organizations. however, as service-oriented architectures mature, it may be impractical for organizations to discover services and orchestrate new business processes on a daily, case-by-case basis. it is more likely that organizations will naturally aggregate themselves into groups of collaborating partners that routinely share services. in such cases, there is a requirement to maintain an organizational memory with regards to the capabilities offered by other enterprises and how they fit within relevant business processes. as a result, registries must maintain information about past business processes (i.e. relevant web services and their performance, availability, and reliability). this paper discusses and evaluates several hybrid approaches for incorporating business process information into standards-based service registries.
improved adaboost.m1 of decision trees with confidence-rated predictions. this paper proposes an algorithm to integrate adaboost.m1 with the decision trees that output confidence-rated predictions, which is done by transforming decision trees from "expert" models to "specialist" models that may abstain when the confidence is less than 1/2. the confidence is used to update the instance weights during the boosting process, and it is also used to determine the vote weights of base classifiers in decision process. this makes the algorithm a "dynamic" one, in that: (1) for a given test instance, only those whose confidences are higher than 1/2 can vote on the decision making; and (2) the vote weight of each base classifier is dependent on the confidence that the classifier has on the target instance. experimental results with c4.5 decision tree learner as the base learning algorithm have shown that this algorithm has significantly outperformed both the base algorithm and the adaboost.m1 of the c4.5 decision trees with simple predictions.
from exponential to almost linear decomposability of finite or infinite trees. first-order constraints are first-order formulas built on a set of function and relation symbols using the following logical symbols: =, true, false, &not;, &and;, &or;, &rarr;, &harr;, &forall;, &exist;, (,). over the last decade, first-order constraints have been efficiently used in the artificial intelligence world to model many kinds of complex problems such as: scheduling, resource allocation, configuration, temporal and spatial reasoning, computer graphics, bio-informatics. while theory of finite or infinite trees t has played a fundamental role for both modeling and solving these problems, the complexity of solving first-order constraints with nested quantifiers and negations in t has been proved to be inherently huge (a tower of powers of two). however, a new property called decomposability has been recently introduced and used as a black-box to build many efficient first-order constraint solvers over t. we show in this paper that the algorithm which is used in this black-box (i.e. the algorithm which performs decomposability) has an exponential time and space complexity. we then present a much more efficient algorithm in the form of four rewriting rules which can perform the same decomposability in an almost-linear time and space complexity.
sink-oriented dynamic location service for shortest path relay with energy efficient global grid. portable wireless devices are increasing in popularity. mechanisms that allow information to be efficiently obtained through mobile wsns are of significant interest. however, a mobile sink introduces many challenges to data dissemination in large wsns. for example, it is important to efficiently identify the locations of mobile sinks and disseminate information from multi-source nodes to the multi-mobile sinks. in particular, a stationary dissemination path may no longer to effective in mobile sink applications, due to sink mobility. in this paper, we propose a sink-oriented dynamic location service (sdls) approach to handle sink mobility. in sdls, we propose an eight-direction anchor (eda) system that acts as a location service server. eda prevents intensive energy consumption at the border sensor nodes and thus provides energy balancing to all the sensor nodes. then we propose a location-based shortest relay (lsr) that efficiently forwards (or relays) data from a source node to a sink with minimal delay path. our results demonstrate that sdls not only provides an efficient and scalable location service, but also reduces the average data communication overhead in scenarios with multiple and moving sinks and sources.
load management in model-aware execution of composite web services. in the service oriented architecture services are computational units that can be published, discovered, consumed and aggregated in the platform and organization independent manner. the most widely accepted way to achieve service orientation (so) is with web services (wss), due to the standardization efforts and the wide range of available infrastructure. one of the most interesting aspects of wss is the ease with which they can be combined into composite web services (cwss). the most popular language to specify and implement cwss is bpel. while being easy to use, it also introduces difficulties to monitor and optimize cwss, specifically in the selection of optimal wss. this paper investigates the possibility to support this selection with dynamic load management, based on the alternative, model-aware, approach to orchestrate wss with the coloured petri nets (cpn) formalism. the use of the mathematically grounded formalism allows to model and verify properties of cwss and enables at runtime guidance of the execution of the cws. this paper presents how, during a model-aware execution of a cws, to predict and avoid some of the undesirable behaviors of wss. compared to bpel, the model-aware approach significantly improves the performance and manageability of cwss and thus opens up new deployment scenarios.
a recommendation system for browsing digital libraries. in this paper, a recommendation system for browsing large multimedia repositories is presented. in particular a combination of image processing algorithms and user behavior features is designed, implemented and tested. several experiments from a virtual museum scenario are carried out and discussed.
a lightweight 3d visualization and navigation system on handheld devices. this work presents a lightweight 3d visualization and navigation system we have proposed and implemented on handheld devices, using the open graphics library for embedded systems (opengl es api). the visibility algorithms view-frustum culling, backface culling (this one available in the opengl es api), and a combination of view-frustum culling and backface culling, associated to different depth levels of octrees (used to partition the 3d scene) were implemented and used to optimize the processing time required to render 3d graphics. the system was then tested using these combinations of algorithms and performance analyses were conducted for situations where the camera walks through an environment containing 6199 polygons. the results show that navigation at interactive rates of 10.07 and 30.61 frames per second can be obtained using the pock-etpc ipaq hx2490b and the mobile phone nokia n82, respectively.
a new k-view algorithm for texture image classification using rotation-invariant feature. this paper proposes a new k-view algorithm for texture image classification using rotation-invariant features. these features are statistically derived from characteristic view sets for each texture. unlike the existing k-view algorithm, all the views used are transformed into rotation-invariant features and the k views are selected randomly. in contrast, the existing k-view algorithm uses the k-means algorithm for choosing the k views. in this new algorithm the decision of determining a pixel to which texture class it belong to, is made by considering all the views which consist of the pixel being classified. in order to preserve the primitive information of a texture class as much as possible, the proposed algorithm randomly selects k views of the view set from each sample sub-image as the characteristic view set. experimental results show that the proposed algorithm is more robust and accurate compared with the results of the existing k-view algorithm.
visual detection of novel terrain via two-class classification. remote sensing of terrain characteristics is an important component for autonomous operation of mobile robots in natural terrain. often this involves classification of terrain into one of a set of a priori known terrain classes. situations can frequently arise, however, where an autonomous robot encounters a terrain class that does not belong to one of these known classes. this paper proposes an approach for visual detection of novel terrain based on a two-class support vector machine (svm) for situations when known terrain classes can be confidently associated with only a subset of the training data. experimental results from a four-wheeled mobile robot in mars analog terrain demonstrate the effectiveness of this approach.
cps-sim: configurable and accurate clock precision solid state drive simulator. nand flash memory is the most widely used storage medium in embedded systems today due to its many advantages such as light weight, low power consumption, and shock resistance. recently, solid state drives (ssds), which use nand flash memory to store data, are replacing conventional magnetic disks in laptops and some server computers. in the ssds, to achieve both high performance and large capacity, a number of flash memory chips are connected to multiple buses and ssd firmware exploits parallel accesses by using interleaving and overlapping techniques. however, it is still unclear how many buses or chips should be used and how to drive those chips and buses to satisfy performance that may be required. to help answer these questions, we have developed a clock precision ssd simulator (cps-sim) that simulates the internal behavior of an ssd and that reports timing and utilization information. from the accurate timing and utilization results of cps-sim, we can discover the optimal hardware configuration including the number of buses and chips and their interconnections in an ssd. also, it allows for fast development and verification of ssd firmware that runs an ftl (flash translation layer) optimized for an ssd. unlike ftls for embedded flash memory, the ftl for an ssd must utilize the concurrency of the multiple chips and buses. by supporting concurrency, our cps-sim provides a flexible environment for design of ssd firmware that drives the multiple flash memory chips and also that schedules data transmissions via the multiple buses.
visualization of clustered directed acyclic graphs with node interleaving. graph drawing and visualization represent structural information as diagrams of abstract graphs and networks. an important subset of graphs is directed acyclic graphs (dags). e-spring algorithm, extended from the popular spring embedder model, eliminates node overlaps in clustered dags by modeling nodes as charged particles whose repulsion is controlled by edges modeled as springs. the drawing process needs to reach a stable state when the average distances of separation between nodes are near optimal. this paper presents an enhancement to e-spring to introduce a stopping condition, which reduces equilibrium distances between nodes and therefore results in a significantly reduced area for dag visualization. it imposes an upper bound on the repulsive forces between nodes based on graph geometry. the algorithm employs node interleaving to eliminate any residual node overlaps. these new techniques have been validated by visualizing ebay buyer-seller relationships and resulted in overall area reductions in the range of 45% to 79%.
daily demand forecasting of new products utilizing diffusion models and genetic algorithms. new high technology consumer products are released frequently. the manufacturers have to avoid dead stock because the value of the products drops sharply after the launch of new products. thus, the importance of daily demand forecasting is increasing. in this paper, we propose a daily demand forecasting method for new products. the method uses diffusion models to forecast demand. a genetic algorithm (ga) is used to estimate the parameters of the model. in order to apply the diffusion model to daily demand forecast, we introduce time-variant parameters, which depend on the day of the week. the proposed method is applied to the daily demand forecasting of high technology consumer products. the result shows that the proposed method has an excellent daily demand forecasting ability.
where are your manners?: sharing best community practices in the web 2.0. the web 2.0 fosters the creation of communities by offering users a wide array of social software tools. while the success of these tools is based on their ability to support different interaction patterns among users by imposing as few limitations as possible, the communities they support are not free of rules (just think about the posting rules in a community forum or the editing rules in a thematic wiki). in this paper we propose a framework for the sharing of best community practices in the form of a (potentially rule-based) annotation layer that can be integrated with existing web 2.0 community tools (with specific focus on wikis). this solution is characterized by minimal intrusiveness and plays nicely within the open spirit of the web 2.0 by providing users with behavioral hints rather than by enforcing the strict adherence to a set of rules.
extending bayesian trust models regarding context-dependence and user friendly representation. successful collaboration between independent entities depends on the selection of trustworthy interaction partners. bayesian trust models provide a well-founded way for deriving trust from evidence. yet, current approaches lack an integration of context-dependent parameters and a graphical representation for users. we propose a modification of the bayesian approach that integrates context-dependent parameters in the prior knowledge and that allows to overcome the negative effects that are usually introduced with aging. furthermore, we propose a mapping of this approach to a more intuitive representation of trust.
automated device for determination of skin lesion regions. the elliptical excision is a basic cutaneous surgery commonly performed by physicians and that consists of drawing a spindle shape with pointed ends having a length-to-width ratio 3--4: 1 with 30&deg; angles at each of the poles to avoid the dog-ear formation upon sew up. physicians who perform such excisional procedures tend to estimate and visually mark the border of the cut making such a procedure inaccurate, thus resulting in either excessive or less cutting of the skin. we propose an automated device that provides a rapid and precise determination of the borders of the excision. in order to perform the required function, the device obtains a snapshot of the lesion, determines its area using image processing, computes the required area to be removed, and finally projects a light accordingly representing the desired elliptic shape. the device consists of three main subsystems: a camera, a processing module and a light system. the paper presents the detailed implementation of the device and the performance results.
parallel materialization of large aboxes. this paper is concerned with the efficient computation of materialization in a knowledge base with a large abox. we present a framework for performing this task on a shared-nothing parallel machine. the framework partitions tbox and abox axioms using a min-min strategy. it utilizes an existing system, like swiftowlim, to perform local inference computations and coordinates exchange of relevant information between processors. our approach is able to exploit parallelism in the axioms of the tbox to achieve speedup in a cluster. however, this approach is limited by the complexity of the tbox. we present an experimental evaluation of the framework using datasets from the lehigh university benchmark (lubm).
building an efficient preference xml query processor. today user-centered information acquisition over collections of complex xml documents is increasingly in demand. to this end, preferences have become an important paradigm enabling users to express individual interests and delivering personalized information. as the structure of xml documents plays a major part in retrieval, users often have specific preferences about the structure. for evaluation a query has to be unfolded into an entire set of queries filling the structure with more or less preferred values. since such structure expansions typically contain redundancies, it is important to identify and simplify necessary expansion queries for effective evaluation. to address these issues, we developed a preference query optimizer that not only determines an optimal set of expansion queries, but also preserves the specific ordering induced by the user preferences with respect to pareto optimality.
executing jml specifications of java card applications: a case study. executability provides an important mechanism for validating formal specifications and allows such specifications to serve as prototypes and test oracles. in this case study, we used the jmle tool to execute the jml specification of an electronic purse application written in the java card dialect of java. this effort resulted in numerous improvements to the specification and to the jmle tool itself, as well as insight into how executability can contribute to the use of formal methods in the software development process.
modular implementation of adaptive decisions in stochastic simulations. we present a modular approach to implement adaptive decisions with existing scientific codes. using a sophisticated system software tool based on the function call interception technique, an external code module is transparently combined with the given program without altering the original code structure, resulting in a newly composed application with extended behavior. this is useful for generalizing codes into using different parameter values or to switch algorithms or implementations at runtime. applying the proposed method on a biochemical stochastic simulation software package to implement a set of exemplary use cases, which includes changing program parameters, substituting random number generators, and dynamically changing the stochastic simulation method, we demonstrate how effectively new code modules can be plugged in to construct an application with enhanced capabilities.
troll, a language for specifying dice-rolls. dice are used in many games, and often in fairly complex ways that make it difficult to unambiguously describe the dice-roll mechanism in plain language. many role-playing games, such as dungeons & dragons, use a formalised notation for some instances of dice-rolls. this notation, once explained, make dice-roll descriptions concise and unambiguous. furthermore, the notation has been used in automated tools for pseudo-random dice-rolling (typically used when playing over the internet). this notation is, however, fairly limited in the types of dice-rolls it can describe, so most games still use natural language to describe rolls. even dungeons & dragons use formal notation only for some of the dice-roll methods used in the game. hence, a more complete notation is in this paper proposed, and a tool for pseudo-random rolls and (nearly) exact probability calculations is described. the notation is called "troll", combining the initial of the danish word for dice ("terninger") with the english word "roll". it is a development of the language roll described in an earlier paper. the present paper describes the most important features of troll and its implementation.
design and implementation on a pie menu interface for analog joysticks. there have been recently several input methods that combine pen-based input with a pie menu as an input interface in environments where working space is limited. however, they suffer from various problems in that input operation is difficult to learn where there are many items on the menu. in this research, we propose a new space-saving input interface that combines an analog joystick and a hierarchical pie menu. the proposed method employs a hierarchical pie menu to enhance the number of items, and a frequency-based area division algorithm that works to expand the area for important items. using our method, an intuitive input interface is achieved that is high speed and highly accurate.
modeling and integrating aspects with uml activity diagrams. dealing with crosscutting concerns has been a critical problem in software development processes. aspect-oriented programming (aop) provides a viable programming-level solution by separating crosscutting concerns from primary concerns. to facilitate handling crosscutting concerns at earlier software development phases, this paper proposes an aspect-oriented modeling and integration approach at the design level. in our approach, primary concerns are depicted with uml activity diagrams as primary models, whereas crosscutting concerns are described with aspectual extended activity diagrams as aspect models. each aspect model consists of pairs of pointcut and advice model. aspect models can be integrated into primary models automatically. to this end, a prototype tool called jasmine-aoi has been implemented as an eclipse plug-in. with the tool support, we have conducted two case studies, including 15 primary models and 8 aspect models. the case studies demonstrate that our approach can greatly facilitate reasoning about crosscutting concerns when a system is modeled with activity diagrams.
real-time scheduling for continuous queries with deadlines. many stream-based applications have real-time performance requirements for continuous queries over time-varying data streams. in order to address this challenge, a real-time continuous query model is presented to handle multiple queries with timing constraints. in this model, the execution of one tuple passing through an operator path is modeled as a real-time task instance. a fine-grained scheduling strategy named op-edf is proposed for real-time scheduling, which schedules the operator path with the earliest deadline of the waiting tuples at any time slot. the experimental results show that the proposed continuous query model and scheduling algorithm are effective in real-time query processing for data streams with bursty arrival rates.
on the persistence of deleted windows registry data structures. deleted entries in the windows registry remain in the hives that contain them but their space is marked as free for future use. in this paper we analyse the fragmentation of these deallocated blocks and how long they persist by surveying a number of hives over a long period of time. we formalise retrieval of data and define 'consistency' with respect to deleted keys. we illustrate how uninstallation programs may inadvertently corrupt the keys they are deleting in the uninstallation process by analysing the keys during the uninstallation of a popular media software suite.
resource sharing in behavioral based scheduling. in this paper, two main contributions are presented. first, the behavioral importance dual priority server (bids) reservation mechanism is extended to contemplate more than two importance levels. in fact, an integer-value function is used to postpone the reactivation of the server based on the last result obtained. second, a resource contention algorithm for bids is presented. although it may seem simple, the resource reservation paradigm may have certain anomalies while sharing resources. the proposal is an extension of the stack resource policy which is formally proved.
a mobility management scheme using sctp-sip for real-time services across heterogeneous networks. the session initiation protocol (sip) has been enhanced to support seamless mobility in heterogeneous networks. however, it still suffers from significant handoff delays and packet losses unacceptable for real-time multimedia services. in this paper, we propose a mobility management scheme for real-time services across heterogeneous networks that combines sip and stream control transmission protocol (sctp). our scheme ensures transport-layer continuance through the multi-homing functionality of sctp while maintaining location and network transparency through sip without the use of re-invite message signaling. an evaluation of our approach demonstrates that it provides seamless mobility while satisfying the quality of service (qos) requirements for real-time multimedia services without any changes in the underlying network infrastructure.
enhancing xml data warehouse query performance by fragmentation. xml data warehouses form an interesting basis for decision-support applications that exploit heterogeneous data from multiple sources. however, xml-native database systems currently suffer from limited performances in terms of manageable data volume and response time for complex analytical queries. fragmenting and distributing xml data warehouses (e.g., on data grids) allow to address both these issues. in this paper, we work on xml warehouse fragmentation. in relational data warehouses, several studies recommend the use of derived horizontal fragmentation. hence, we propose to adapt it to the xml context. we particularly focus on the initial horizontal fragmentation of dimensions' xml documents and exploit two alternative algorithms. we experimentally validate our proposal and compare these alternatives with respect to a unified xml warehouse model we advocate for.
diverse peer selection in collaborative web search. effective peer selection for intelligent query routing is a challenge in collaborative peer-based web search systems, especially unstructured networks that do not have any centralized control of peer document collections. in particular, routing a query to multiple peers that provide the same results is a waste of resources. to deal with overlapping document collections we propose a diverse peer selection approach for adaptive query routing. this approach takes into account not only which neighbors are the best resource providers for a given query, but also which combinations of neighbors can provide the least redundant results. we validate the feasibility of our proposed algorithm by presenting several simulation experiments conducted with different configurations of peer network environments. two novel evaluation measures, distributed precision and distributed recall, are also introduced to provide an effective comparison of different peer network systems. these two performance measures extend the well known ir measures of precision and recall by integrating network costs, namely bandwidth and latency. our algorithm finds results of equivalent quality using less time and generating less traffic in the presence of varying amounts of document duplication.
a practical solution for scripting language compilers. although scripting languages are becoming increasingly popular, even mature scripting language implementations remain interpreted. several compilers and reimplementations have been attempted, generally focusing on performance. based on our survey of these reimplementations, we determine that there are three important features of scripting languages that are difficult to compile or reimplement. since scripting languages are defined primarily through the semantics of their original implementations, they often change semantics between releases. they provide large standard libraries, which are difficult to re-use, and costly to reimplement. they provide c apis, used both for foreign-function-interfaces and to write third-party extensions. these apis typically have tight integration with the original implementation. finally, they support run-time code generation. these features make the important goal of correctness difficult to achieve. we present a technique to support these features in an ahead-of-time compiler for php. our technique uses the original php implementation through the provided c api, both in our compiler, and an our generated code. we support all of these important scripting language features, particularly focusing on the correctness of compiled programs. additionally, our approach allows us to automatically support limited future language changes. we present a discussion and performance evaluation of this technique, which has not previously been published.
preservation of ordering in a network of brokers. some distributed applications, such as online collaborative whiteboards, chat systems, multiplayer games and others, have a need for causal and total ordering. those applications exploit computer networks in order to connect publishers and subscribers of events, generally using a publish/subscribe middleware for that purpose. however, most state of the art pub-sub middlewares focus on best-effort services, without providing event ordering guarantees. this paper presents an overview of our proposed solution, which uses the distributed shared memory model to provide causal and total ordering of events in subject-based pub-sub middlewares. we also present a proof of concept for our architecture, an online collaborative whiteboard.
legal-tree: a lexicographic multi-objective genetic algorithm for decision tree induction. decision trees are widely disseminated as an effective solution for classification tasks. decision tree induction algorithms have some limitations though, due to the typical strategy they implement: recursive top-down partitioning through a greedy split evaluation. this strategy is limiting in the sense that there is quality loss while the partitioning process occurs, creating statistically insignificant rules. in order to prevent the greedy strategy and to avoid converging to local optima, we present a novel genetic algorithm for decision tree induction based on a lexicographic multi-objective approach, and we compare it with the most well-known algorithm for decision tree induction, j48, over distinct public datasets. the results show the feasibility of using this technique as a means to avoid the previously described problems, reporting not only a comparable accuracy but also, importantly, a significantly simpler classification model in the employed datasets.
multi-agent system adaptation in a peer-to-peer scenario. from a system's perspective ---as opposed to an individual agent perspective---, mas adaptation is now becoming an important topic, since it can help to obtain expected outcomes under changing circumstances. in this paper, we propose a mas architecture (2-lama) to adapt social conventions in dynamic systems. the proposed architecture consist of two layers: the conventional mas system (we call domain-level) and an additional layer or meta-level in charge of adaptation. a peer-to-peer scenario helps us to illustrate our approach. the resulting model changes participant organisation depending on environment and agent changes. finally, we present some preliminary results of the empirical evaluation of our approach.
prestige-based peer sampling service: interdisciplinary approach to secure gossip. the peer sampling service (pss) has been proposed as a method to initiate and maintain the set of connections between nodes in unstructured peer to peer (p2p) networks. the pss usually relies on gossip-style communication where participants exchange their links in a randomized way. however, the pss network organization can be easily modified by malicious nodes running a "hub attack", in which they achieve a leading structural position. from this prestigious status, the malicious nodes can severely affect the overlay and achieve several application dependent advantages. we present a novel method to overcome this attack and provide results from simulation experiments that validate our claim. this method is inspired by a simple technique used to detect social leaders in firm's organizations that is based on the social (structural) "prestige" of actors.
bulk based preconditioning for quantum dot computations. this article describes how to accelerate the convergence of preconditioned conjugate gradient (pcg) type eigensolvers for the computation of several states around the band gap of colloidal quantum dots. our new approach uses the hamiltonian from the bulk materials constituent for the quantum dot to design an efficient preconditioner for the folded spectrum pcg method. the technique described shows promising results when applied to cdse quantum dot model problems. we show a decrease in the number of iteration steps by at least a factor of 4 compared to the previously used diagonal preconditioner.
rpp: reference pattern based prefetching controller. we propose a prefetching technique that recognizes and exploits reference patterns. reference pattern based prefetching (rpp) detects sequential and non-sequential reference patterns and takes different prefetch action according to this information. beyond sequential detection, rpp recognizes repetitive occurences of consecutive sequences, and then exploits these repetitions. in this paper, we show that rpp results in favorable performance gains.
a robust and tractable contact model for dynamic robotic simulation. existing contact modeling in rigid body simulation is inadequate for robotics: no algorithms guarantee both convergence and nonpenetration at multiple contact points in the presence of coulomb friction. we present a convex optimization based algorithm that models simultaneous contact at multiple points, ensures nonpenetration, and yields coulomb friction effects. an example of simulated robotic grasping shows that the proposed algorithm is robust where most other methods fail.
a recommender system for requirements elicitation in large-scale software projects. in large and complex software projects, the knowledge needed to elicit requirements and specify the functional and behavioral properties can be dispersed across many thousands of stakeholders. unfortunately traditional requirements engineering techniques, which were primarily designed to support face-to-face meetings, do not scale well to handle the needs of larger projects. we therefore propose a semi-automated requirements elicitation framework which uses data-mining techniques and recommender system technologies to facilitate stakeholder collaboration in a large-scale, distributed project. our proposed recommender model is a hybrid one designed to manage the placement of stakeholders into highly focused discussion forums, where they can work collaboratively to generate requirements. in our approach, statements of need are first gathered from the project stakeholders; unsupervised clustering techniques are then used to identify cohesive and finely-grained themes and a users' profile is constructed according to the interests of the stakeholders in each of these themes. this profile feeds information to a collaborative recommender, which predicts stakeholders' interests in additional forums. the validity and effectiveness of the proposed recommendation framework is evaluated through a series of experiments using feature requests from three software systems.
: a scalable multicore code for rna secondary structure prediction. the prediction of the correct secondary structures of large rnas is one of the unsolved challenges of computational molecular biology. among the major obstacles is the fact that accurate calculations scale as o(n4), so the computational requirements become prohibitive as the length increases. existing folding programs implement heuristics and approximations to overcome these limitations. we present a new parallel multicore and scalable program called gtfold, which is one to two orders of magnitude faster than the de facto standard programs and achieves comparable accuracy of prediction. development of gtfold opens up a new path for the algorithmic improvements and application of an improved thermodynamic model to increase the prediction accuracy. in this paper we analyze the algorithm's concurrency and describe the parallelism for a shared memory environment such as a symmetric multiprocessor or multicore chip. in a remarkable demonstration, gtfold now optimally folds 11 picornaviral rna sequences ranging from 7100 to 8200 nucleotides in 8 minutes, compared with the two months it took in a previous study. we are seeing a paradigm shift to multicore chips and parallelism must be explicitly addressed to continue gaining performance with each new generation of systems. we also show that the exact algorithms like internal loop speedup can be implemented with our method in an affordable amount of time. gtfold is freely available as open source from our website.
secure web-based retrieval of documents with usage controls. usage controls enable the provider of some information to limit how recipients may use it. usage controls may be desirable in enterprise environments, e.g., for regulatory compliance or to protect intellectual property in collaborative endeavors. we contribute web protocol, server, and browser modifications for hardening existing software-based usage controls (e.g., pdf's) with trusted platform modules (tpms). tpms are low-cost secure coprocessors present in an increasing number of computers. we use the tpm to prevent untrusted software from opening usage-controlled files. we implemented the proposed solution on linux by adding a linux security module to the kernel and modifying apache and firefox. no modifications are necessary in applications used for authoring and displaying usage-controlled files (e.g., openoffice and xpdf). experiments show that the proposed scheme has modest impact on client response time and server cpu utilization.
banzai: a java framework for the implementation of high-performance servers. this paper presents banzai a java framework that uses the tatoo parser generator to simplify the implementation of high-performance servers based on plain-text protocols. this approach conciliates the use of formally defined grammars for protocol parsing and the efficiency of the implementation. we argue that the use of the formal grammars simplifies the implementation of the protocol and we show that an http server built using the banzai framework is as efficient as several existing ad-hoc high-performance http servers. the banzai framework relies on the ability of tatoo to produce push non-blocking parsers with a fixed memory footprint during parsing and on a generic and efficient server architecture.
a detecting and tracing algorithm for unauthorized internet-news plagiarism using spatio-temporal document evolution model. prevailing plagiarism among digital documents is one of the serious problems associated with the development of the internet. it is not difficult to find news articles which have been copied without authorization. internationally, newspapers may deal with the same event, and want to publish the article as soon as possible. so, a few internet-based news media plagiarize news articles of other companies, rather than writing their own articles, by sending a reporter or relying on syndication. this kind of news article plagiarism boosts the number of internet news articles, which are all mostly identical, due to text copying and pasting. and, these kinds of plagiarized articles prevent internet searching tools from collecting original articles. for example, it is known that more than 10--20% of articles collected by portal sites are nearly identical or quite similar. in order to deal with this problem we need a strict and stable tool for detecting internet news plagiarism. also, if possible, it is highly desirable to perform a trace back to reconstruct the history of plagiarism. in this paper, we suggest a new detection algorithm for unauthorized news article plagiarism using a spatio-temporal evolution model. using this model, we can reveal the sequence of plagiarism among news articles.
information-theoretic identification of content pages for analyzing user information needs and actions on the multimedia web. increasing use of media in web pages is fueling the metamorphosis of the www into a multimedia web. the development of information organization, analysis, and search technologies that enable people to efficiently find the specific information they require becomes especially important in this context. determining the information goal of a user is a critical step in this direction. however, the information goal is typically subjective and latent. its determination is further complicated in multimedia websites since the semantics of media-based information is context-based and emergent. furthermore, interaction modalities with media are, unlike static link-based browsing, complex to analyze. in this paper we address the problem of automatically determining the content pages given the browsing behavior of a user. the content pages contain the information the user came to the site to find. thus, their identification is a critical step in reasoning about user information goals. we propose an information theoretic approach that takes into account the organization of the web site, the multimedia information content, as well as the influence of a specific browsing pattern to identify one or more pages that putatively contain the information goal(s). this method can be used irrespective of whether the user has a single information goal or is looking to satisfy multiple information needs. experimental investigations on media rich sites illustrate the efficacy of the technique and its potential in modeling user information needs and actions in a multimedia web.
modeling and analyzing review information on the web focusing on credibility. in this paper we modeled review information to assess its credibility. we think the information to support users in credibility evaluation of reviews is necessary. this paper presents method for detecting reviewers' activity areas and biases. we also discuss the problem of glorified terms in online reviews. as these terms cause cognitive bias, supporting information that enables accurate understanding is needed.
a light-weight summarizer based on language model with relative entropy. a new method for sentence extraction on the basis of language model with relative entropy is presented in this paper. the proposed technique first builds a sentence language model and document cluster language model respectively for the sentence and the documents. the sentences are then ranked according to the relative entropies of the estimated document language model with respect to the estimated sentence language model. the overall results on duc and mse corpus demonstrate that the proposed approach outperforms some of the best reported results for generic multi-document summarization.
user-media interaction with interactive tv. watching tv is a practice many people enjoy and feel comfortable with. we propose the capture of the user interaction while interacting with a remote control to watch tv: such detailed information is most valuable to many applications and services. we discuss our proposed approach in the context of the brazilian interactive digital tv platform.
policy management architecture based on provisioning model and authorization certificates. the unified management of user rights and access control policies in a corporation with many units is not easy to implement. moreover, most of the distributed access control systems are complex and heterogeneous, making it hard to maintain a unified control over all fine grained policies employed by each unit. this paper proposes a unified administration of policies for corporation environments by applying a management scheme based on authorization certificates. these certificates allow the derivation of new fine grained policies in the domain of each unit, assuring that no corporation policies will be violated. these new policies update automatically the corporation repository, preserving the unified management of user rights, and then update the corresponding policy repository of each unit. our proposal provides a real loosely coupled policy management scheme using a serverless public key infrastructure and the web services technology. the prototype shows the proposal viability.
efficient mobile reasoning for pervasive discovery. semantic service discovery architectures that operate in mobile environments must cope with the significant challenges of finding relevant services rapidly, while facing constrained computational resources. this paper presents our m-tableaux algorithm for enabling cost-efficient and optimised semantic reasoning to support semantic service matching, on the device itself. we present a performance evaluation of the m-tableaux optimisation strategies which clearly demonstrate its operational feasibility on a mobile device. we also present comparative evaluations with other semantic reasoners and establish the improved performance of our engine.
body-and-cad geometric constraint systems. motivated by constraint-based cad software, we develop the foundation for the rigidity theory of a very general model: the body-and-cad structure, composed of rigid bodies in 3d constrained by pairwise coincidence, angle and distance constraints. we identify 21 relevant geometric constraints and develop the corresponding infinitesimal rigidity theory for these structures. the classical body-and-bar rigidity model can be viewed as a body-and-cad structure that uses only one constraint from this new class. as a consequence, we identify a new, necessary but not sufficient, counting condition for minimal rigidity of body-and-cad structures: nested sparsity. this is a slight generalization of the well-known sparsity condition of maxwell.
an approximate approach to constraint solving in soft sensing. soft sensing is usually presented as a constraint solving problem. in a manufacturing context, traditional methods of soft sensing have to face challenges in robustness and efficiency. in this paper, we proposed a granular-based approach to constraint solving for soft sensing. in our method, we first construct a granular-based soft sensing model, then estimate bounds of each granule, and finally solve this granulated problem with a smaller size. according to our analysis, this method is robust and efficient.
hsp-hmmer: a tool for protein domain identification on a large scale. hmmer is arguably the best tool for protein domain identification, which is essential for biological function prediction. there are many software and hardware enhancements of hmmer; however, most of them are not scalable to a large number of processors. the exponential growth of the number of protein sequences in public databases, which is currently set at more than 13 million, demands the use of hmmer on a very large scale. we have developed a highly scalable parallel (hsp) hmmer approach that enables identification of conserved functional domains in millions of proteins in less than a day using thousands of processing nodes on a supercomputer.
real-time multi-view vision systems using wsns. multi-view vision systems are collaborative distributed applications devoted to image processing. applications based on multi-view vision systems can recognize shapes, track moving targets, etc. to activate alarms, or to propogate information through the network. these systems require quality of service from the network and real-time support at the operating system level. wireless sensor networks (wsns) were born for monitoring applications providing best effort services in non-critical environments. nonetheless the recent evolution of hardware platforms, and the existence of real-time kernels as well as network stacks supporting real-time traffic let us envisage the deployment of wsns to new domains like that of multi-view vision. hereby we discuss the feasibility of an object detection system based on vision and deployed through a wsn. for such a purpose, we implemented in the real-time network simulator (rtns) a working model for image detection and in-network processing. referring to a simple star-shaped network scenario, we analyze the system performances from a real-time perspective.
the people, the process or the technology?: using the ace framework to make tradeoffs in service delivery improvement. in today's service-oriented economy there is a critical need for prescriptive and evolutionary methods to improve the performance of services in complex enterprises. the contribution here is the adaptive complex enterprise (ace) method for overall system improvement that integrates techniques from computer science and systems engineering. a case study of an it department within the healthcare industry is used to (a) characterize the service challenges, (b) analyze the tradeoffs and (c) make the systematic, continuous selection of improvements to achieve global lean through local behavior.
construct anticancer drug-drug correlation network. network biology methods have been promising in linking diseases, genes, and drugs. in this study, we propose a novel computational method to construct drug-drug correlation networks, which consist of drug compounds as network graph nodes and correlated protein-drug profiles above a pre-determined threshold as network graph edges. this computational method is based on extensions of related work on identifying disease-specific proteins within protein-protein sub-networks, and mining protein-drug association profiles from biomedical literature. our method provides a quantitative framework to compare how each drug compound from one therapeutic area is correlated with other drug compounds in other therapeutic areas, using a drug's protein-drug association profile mined from biomedical literature. we applied this method to the study of drug re-purposing and found that two breast cancer drugs "mitomycin" and "bleomycin" may be top drug candidates for treating pancreatic cancers.
a general service oriented approach for managing virtual machines allocation. virtualization is an essential enabling technology for building and controlling computing frameworks that can dynamically adapt available physical resources to transient tasks such as the temporary creation of a virtual computing center tailored to the needs of a virtual organization. in this paper we will report on our strategy for the creation of virtual computer clusters based on standard service-oriented architecture (soa) and hosts virtualization technologies. we will describe our infrastructure designed for dynamical allocation of resources to applications via a general control plane based on workflows of coordinated web services. the control plane is based on logically independent services that are responsible for physical resource management and virtual nodes deployment. the control plane is also responsible for operations on virtual clusters such as their creation, startup and control.
storage architecture and software support for slc/mlc combined flash memory. we propose a novel flash memory management software for slc/mlc combined flash memories which are recently introduced to provide flexible and cost-efficient embedded storage systems. to provide a fast and large capacity of flash memory, the proposed scheme utilizes the slc area as log buffer and the mlc area as data block. considering the high write cost of mlc flash, the garbage collection for the slc log buffer moves a page into the mlc data block only when the page is cold or the page invokes a small migration cost. we also propose the bypassing technique which sends a large sequential data into the mlc flash directly not through the slc log buffer. from the experiments, we can know that the proposed scheme utilizes the slc log buffer effectively providing better performance compared with the previous flash management schemes for the slc/mlc combined flash.1
runtime monitoring of web service choreographies using streaming xml. a wide range of web service choreography constraints on the content and sequentiality of messages can be translated into linear temporal logic (ltl). although they can be checked statically on abstractions of actual services, it is desirable that violations of these specifications be also detected at runtime. in this paper, we show that, given a suitable translation of ltl formul&aelig; into xquery expressions, such runtime monitoring of choreography constraints is possible by feeding the trace of messages to a streaming xquery processor. the forward-only fragment of ltl is introduced; it represents the fragment of ltl supported by available streaming engines.
organising mas: a formal model based on organisational mechanisms. in this paper, we propose a general formal framework for organising multiagent systems whose participants are rational agents. this model is based on the idea of organisational mechanisms. these are mechanisms introduced in a multiagent system with the aim of influencing the behaviour of the agents towards more effectiveness with regard to some objectives. we define two kinds of organisational mechanisms: i) informative mechanisms which provide additional information to agents, that may persuade agents to behave in a certain way, and ii) regulative mechanisms which produce changes in the environment of the agents, that may impose certain behaviours. we also define some properties of these mechanisms which will make it possible to prove certain characteristics of organised multiagent systems. finally, we present a discussion about how the social concepts proposed by different organisational paradigms can be considered as either informative or regulative organisational mechanisms.
analysis of the secure rtp protocol on voice over wireless networks using extended medqos. this paper presents an empirical investigation of the impact of secure rtp (srtp) on voip calls over wireless networks: 802.11 and bluetooth. for the purpose of evaluating this impact we developed an analysis tool based on e-model and security aspects of srtp which attempts to determine the balance of quality of service versus security. the results demonstrate that the impact of srtp to voip should not be disregarded. mos scores of secure calls computed from e-model pointed out an undesirable level of quality of service on single calls using wireless channels. this quality degradation also leads to the reduction of channel capacity to offer simultaneous calls. the developed analysis tool indicated three important factors to this degradation: time to encrypt, time to authenticate and time to form a cryptographic context for each srtp packet sent and received.
market-based coordination for intersection control. the control of large-scale open distributed systems, where many autonomous, intelligent entities interact with the environment and with each other, is not a trivial task. market-based methods have been applied to the design and the control of such systems, by defining the "rules of the game" in such a way that a desired global outcome is obtained without any centralized decision making. the future traffic control systems, where intelligent infrastructures with sensors and computing power will interact with millions of drivers commuting from their homes to their respective workplaces, are an example of such systems. in this paper we model the traffic as a computational economy, where drivers trade with the intelligent infrastructure in a virtual marketplace. we design market rules to align the "global profit" (revenues from the infrastructure use) with the "social welfare" (average travel time), in a way that, in situations of similar traffic load, an increase of the infrastructure's monetary benefit usually implies a decrease of the drivers' average travel time.
secure routing in peer-to-peer distributed hash tables. distributed hash tables (dhts) provide efficient and scalable lookup mechanisms for locating data in peer-to-peer (p2p) networks. several issues, however, prevent dht-based p2p networks from being widely deployed -- one of which is security. malicious peers may modify, drop, misroute lookup requests, or even collude to deny the availability of target data. to address these security concerns, we propose an extension to chord named sechord. the main idea is that the source can determine whether the next hop is valid or invalid by estimating how far the next hop is from its finger pointer. if the next hop is too far away from the finger pointer, especially compared to the average distance between two consecutive peers, the source can infer some ongoing malicious activities. our modifications require no trust between two nodes except node join. moreover, each node utilizes locally available information to evaluate hops encountered during the lookup routing process for validity. these modifications have been implemented and evaluated in the presence of malicious nodes. our results show that sechord significantly enhances the security of structured p2p systems at the expense of slightly increased hop count.
early phase requirements assessment of a teletreatment trial. this paper presents the early phase requirements elicitation of a teletreatment trial and the assessment of the requirements in respect of their importance to the trial and the feasibility of the corresponding adaptations of the telemedicine system within the trial project constraints. the elicitation approach and techniques adopt the particulars of the telemedicine working practices. the proposed approach not only uses the treatment description and scenario, it also utilizes the trial design. a trial design defines the settings of a trial and develops the treatment protocols such that treatment efficacy can be evaluated based on evidence. such a design has to be a priori approved by a medical ethical committee, which may impose additional constraints that influence the elicited requirements. the approach therefore involves stakeholders who are not necessarily the users of the system to be. in line with the telemedicine working practices, the approach is moreover based on the identification and analysis of the tasks and task objectives associated to the responsibilities of the involved stakeholders. furthermore, the elicitation is cyclic and applies a collection of known techniques and informal specification styles (e.g. tables and mock-ups). results of the cycles converge to a set of requirements understood and agreed upon by the trial designers, who are medical professionals, typically unaware of the methods and techniques applied by engineers, but who co-shape the telemedicine system to be. this way of working manages expectations better, necessary in a telemedicine collaboration.
computing data cubes using exact sub-graph matching: the sequential mcg approach. in this paper, we present a novel full cube computation and representation approach, named mcg. in a data cube, each cuboid can be viewed as a set of sub-graphs. in general, redundant sub-graphs are quite common in a data cube, but their elimination is a hard problem as some previous cube approaches demonstrate. the mcg approach differentiates significantly from previous approaches since it efficiently eliminates all common sub-graphs from the entire cube, based on an exact sub-graph matching solution. we propose a matching function to guarantee one-to-one mapping between sub-graphs. the function is computed incrementally, in a top-down fashion, and its computation uses a minimal amount of information to generate unique results, regardless of whether we are using distributive, algebraic or holistic measures. mcg performance analysis demonstrates a similar runtime when compared to star approach and very low memory consumption (94--98% reduction) when compared to a full cube representation.
characterizing 1-dof henneberg-i graphs with efficient configuration spaces. we define and study exact, efficient representations of realization spaces of a natural class of underconstrained 2d euclidean distance constraint systems (linkages or frameworks) based on 1-dof henneberg-i graphs. each representation corresponds to a choice of parameters and yields a different parametrized configuration space. our notion of efficiency is based on the algebraic complexities of sampling the configuration space and of obtaining a realization from the sample (parametrized) configuration. significantly, we give purely combinatorial characterizations that capture (i) the class of graphs that have efficient configuration spaces and (ii) the possible choices of representation parameters that yield efficient configuration spaces for a given graph. our results automatically yield an efficient algorithm for sampling realizations, without missing extreme or boundary realizations. in addition, our results formally show that our definition of efficient configuration space is robust and that our characterizations are tight. we choose the class of 1-dof henneberg-i graphs in order to take the next step in a systematic and graded program of combinatorial characterizations of efficient configuration spaces. in particular, the results presented here are the first characterizations that go beyond graphs that have connected and convex configuration spaces.
retrieving valid matches for xml keyword search. adapting keyword search to xml data has been attractive recently, generalized as xml keyword search (xks). its fundamental task is to retrieve meaningful and concise result for the given keyword query, and [1] is the latest work which returns the fragments rooted at the slca (smallest lca - lowest common ancestor) nodes. to guarantee the fragments only containing meaningful nodes, [1] proposed a contributor-based filtering mechanism in its maxmatch algorithm. however, the filtering mechanism is not sufficient. it will commit the false positive problem (discarding interesting nodes) and the redundancy problem (keeping uninteresting nodes). in this paper, we propose a new filtering mechanism to overcome those two problems. the fundamental concept is valid contributor. a child v is a valid contributor to its parent u, if (1) v's label is unique among all u's children; or (2) for the siblings with same label as v, v's content is not covered by any of them. our new filtering mechanism is: all the nodes in each retrieved fragment should be valid contributors to their parents. by doing so, it not only satisfies the axiomatic properties proposed by [1], but also ensures the filtered fragment more meaningful and concise. we implement our proposal in validmatch, and compare validmatch with maxmatch on real and synthetic xml data. the result verifies our claims, and shows the effectiveness of our valid-contributor-based filtering mechanism.
securing key issuing in peer-to-peer networks. compared with the public key infrastructure (pki) technique, identity based cryptography (ibc) can simplify the key management process in peer-to-peer (p2p) networks significantly. the identity of a peer (e.g., peer identifier or peer geometric coordinate) in p2p overlay networks is used to create its public key, thus avoiding the use of any certificates. these ibc-based systems are scalable, simple to administer, and each user can carry out anytime/anywhere encryption, establish secure communication channels, prove its identity to other nodes, verify protected messages and produce a form of signature with non-repudiation properties.
clustering malware-generated spam emails with a novel fuzzy string matching algorithm. in this paper, a fuzzy-matching clustering algorithm is introduced to group subjects found in spam emails which are generated by malware. a modified scoring strategy is applied in dynamic programming to find subjects that are similar to each other. a recursive seed selection strategy allows the algorithm to detect similar patterns even when the spammer creates a variation of the original pattern. a sliding threshold based on string length helps to minimize false-positives. the algorithm proves to be effective in detecting and grouping spam emails using templates. it also helps spam investigators to collect and sort large amount of malware-generated spam more efficiently without looking at the email content.
boosting the performance of computing systems through adaptive configuration tuning. good system performance depends on the correct setting of its configuration parameters. it is observed that such optimal configuration relies on the incoming workload of the system. in this paper, we utilize the markov decision process (mdp) theory and present a reinforcement learning strategy to discover the complex relationship between the system workload and the corresponding optimal configuration. considering the limitations of current reinforcement learning algorithms used in system management, we present a different learning architecture to facilitate the configuration tuning task which includes two units: the actor and critic. while the actor realizes a stochastic policy that maps the system state to the corresponding configuration setting, the critic uses a value function to provide the reinforcement feedback to the actor. both the actor and critic are implemented by multiple layer neural networks, and the error back-propagation algorithm is used to adjust the network weights based on the temporal difference error produced in the learning. experimental results demonstrate that the proposed learning process can identify the correct configuration tuning rule which in turn improves the system performance significantly.
hits algorithm improvement using anchor-related text extracted by dom structure analysis. kleinberg's hits algorithm is a popular algorithm to rank web pages. one of its problems is the topic drift problem. previous researchers have tried to solve this problem using anchor-related text. we proposed another type of anchor-related text in our previous study. this is found by executing a deep analysis on the dom structures of web pages. we call our anchor-related text dom-based anchor-related text (dom-text). in this paper, we investigate the effectiveness of using dom-text for improving the hits algorithm. we examine how much we can improve the hits algorithm. we also compare dom-text with anchor-related text of other kinds. the experimental results show that the use of dom-text is the best for improving the hits algorithm.
identifying discourse mistakes in web debates: moderation in the dcc. integrating consultative and deliberative environments for popular participation in democratic issues and creating virtual communities make it possible to model decision-making processes. for this reason, the democratic citizenship community (dcc) was developed, based on the government-citizen interactive model. in this model, debates are structured in a different manner and the moderator's participation in debates is based on discourse theory, in relation to discourse mistakes. this research analyzes the moderator's role by means of a case study.
evaluating algorithms that learn from data streams. learning from data streams is a research area of increasing importance. nowadays, several stream learning algorithms have been developed. most of them learn decision models that continuously evolve over time, run in resource-aware environments, and detect and react to changes in the environment generating data. one important issue, not yet conveniently addressed, is the design of experimental work to evaluate and compare decision models that evolve over time. in this paper we propose a general framework for assessing the quality of streaming learning algorithms. we defend the use of predictive sequential error estimates over a sliding window to assess performance of learning algorithms that learn from open-ended data streams in non-stationary environments. this paper studies properties of convergence and methods to comparatively assess algorithms performance.
semantic information and sensor networks. embedded networked sensing involves untethered, networked devices tightly coupled to the physical world, to monitor and interact with it. raw sensor observation can be annotated with semantic metadata to provide interpretation and context for it. in this paper, we discuss what, why and how of semantic sensor data and semantic sensor networks. specifically, we explore (i) benefits of augmenting sensor data with semantics, (ii) domain-specific and spatio-temporal problems to be addressed, (iii) role of knowledge representation and reasoning (semantic web technology), and (iv) standardization efforts underway to make sensor-related data and sensor observations widely available.
extended static checking in jml4: benefits of multiple-prover support. the implementations of many seemingly simple algorithms are beyond the ability of traditional extended static checking (esc) tools to verify. not being able to verify toy examples is often enough to turn users off of the idea of using formal methods. esc4, the esc component of the jml4 project, is able to verify many more kinds of methods in part because of its use of novel techniques which apply multiple theorem provers. in particular, we present offline user-assisted esc (oua-esc), a new form of verification that lies between esc and full static program verification (fspv), that allows users to control the level of completeness of the tool. esc4's improved performance should encourage greater use of static verification.
efficient maintenance of distributed data in highly dynamic opportunistic grids. opportunistic grids are a class of computational grids that can leverage the idle processing and storage capacity of shared workstations in laboratories, companies, and universities to perform useful computation. oppstore is a middleware that allows using the free disk space of machines from an opportunistic grid for the distributed storage of application data. but when machines depart from the grid, it is necessary to reconstruct the fragments that were stored in that machines. depending on the amount of stored data and the rate of machine departures, the generated traffic may make the distributed storage of data infeasible. in this work we present and evaluate a fragment recovery mechanism that makes viable to achieve redundancy and large data scale in a dynamic environment.
a comparative study of techniques to write customizable libraries. code libraries are characterized by feature-richness --- and, consequently, high overhead. the library specialization problem is the problem of obtaining a low-overhead version of library code when the rich feature set is not needed. a version of that problem is this: given a class with certain core functionality and some "optional" features, how can we offer the client a menu of features such that the specific class answering this request is unencumbered by fields or computation not needed for the requested features? this paper presents a comparative study of several approaches to this version of the library specialization problem. we evaluate object-oriented programming, feature-oriented programming, colored ide, aspect-oriented programming, c-style preprocessor directives, and fragment-oriented program generation. we find that all of these techniques have shortcomings.
simsoa: an approach for agent-based simulation and design-time assessment of soc-based it systems. by applying the paradigm of service-oriented computing (soc) to existing it infrastructures, companies aim at increasing flexibility and reducing complexity prevalent in their enterprise it. yet, introducing soa brings forward an soc-specific it complexity that - among other issues - has to be adressed by a company's it service management (itsm). to facilitate an itsm-based assessment of an soc-based enterprise it architecture at design-time, this paper presents an approach for an agent-based soa simulation system: simsoa. by conducting simulation runs, a design-time assessment of an it service architecture with respect to aspects of availability management, service level management and others is supported. this paper outlines the architecture of simsoa and its current state of implementation - and presents an experiment within which the capabilities of simsoa are analyzed against an itsm-related scenario.
an enhanced multi-view video compression using the constrained inter-view prediction. we propose a method that uses the restricted inter-view prediction for multi-view video coding. in the multi-view video, there exists occluded area because of the locations and angle of cameras. this increases the computational complexity, as it still uses both reference pictures for predicting the area which is not shown in the current frame. in this paper, we proposed a method that does not use the interview prediction in cases when macroblocks are occluded. experimental results show that benefits can be obtained compared with the conventional approaches.
a new multimedia synchronous distance learning system: the iva study case. this paper presents an innovative distance learning system named iva (interactive video and audio) which allows users to access video content, from any electronic device with enough processing capability and resources, aiming an ubiquitous application (anytime and anywhere) through synchronous or asynchronous communication. the paper raises and discusses real issues about multipoint multimedia transmission, taking into account adaptation to differnt devices and different networks. the paper also discusses the implemented solutions to overcome the faced problems. the paper's main focus is on live video transmission to many heterogeneous receivers, as this is the application which demands most resources from devices and network.
an implementation of the earliest deadline first algorithm in linux. recently, many projects have been started to introduce some real-time mechanisms into general purpose operating systems (gpos) in order to make them capable of providing the users with some temporal guarantees. many of these projects focused especially on linux for its capillary and widespread adoption throughout many different research and industrial environments. by tracking the kernel release cycle, we propose an efficient earliest deadline first implementation in the form of a patch-set against the 2.6.27 version, that is the latest released one, as of now. our implementation provides the user with the possibility to choose sched_edf as one of the possible scheduling policies for a task, with an enhanced version of the standard algorithm. in fact, we propose a new approach to shared resources' access which, differently from many other previous existing works, does not require the user to specify any parameters about the critical sections every task will enter during its execution.
using geo-spatial session tagging for smart multicast session discovery. ip multicast is increasingly seen as efficient mode of live content distribution in the internet to significantly large subscriber bases. despite its numerous benefits over ip unicast, multicast has not seen widespread deployment over modern networks. network complexity and session discovery issues have plagued ip multicast since its inception. the internet research community is in general agreement to move over to ssm (source specific multicast). with igmp v 3 (internet group management protocol) and ssm, the source discovery burden will rest with the end user. channel discovery is one of the few stumbling blocks remaining to be solved for successful and widespread deployment of multicast. in an earlier work a dns (domain name system) aware multicast session discovery architecture, mdns, has been proposed which is distributed, hierarchical and globally scalable. this paper proposes to leverage the mdns architecture by enabling multicast sessions to be tagged using geographical and spatial information based on the channel contents or service provider location. it further proposes automatic geo-coding of session registration information as the content provider registers session information with mdns. it also provides necessary design changes and gives data models and data structures to support seamless location sensitive session retrieval as part of search query results to be furnished to the end user. the paper includes envisaged scenarios in which geo-tagging would enhance end user experience and would enable smarter query result generation.
autonomous networked robots for the establishment of wireless communication in uncertain emergency response scenarios. during a disaster, emergency response operations can benefit from the establishment of a wireless ad hoc network. we propose the use of autonomous robots that move inside a disaster area and establish a network for two-way communication between trapped civilians with uncertain locations and an operation centre. our aim is to maximise the number of civilians connected to the network. we present a distributed algorithm which involves clustering possible locations of civilians according to their expected shortfall; clustering facilitates both connectivity within groups of civilians and exploration that is based on the uncertainty of these locations. to achieve efficient allocation in terms of time and energy, we also develop a modified algorithm according to which the robots consider the graph that the cluster centres form and follow its minimum spanning tree. we conduct simulations and discuss the efficiency and appropriateness of the two algorithms in different situations.
using probabilistic model checking and simulation for designing self-organizing systems. self-organization is a feasible metaphor for dealing with the growing complexity of today's software systems. self-organization makes desired global system's behavior appear as an emergent property from component local interactions. the corresponding dynamics is usually non-linear so that the adoption of stochastic simulation and probabilistic model checking becomes essential in the early design stage. in this paper, as a reference example, a possible application of such techniques is shown on a problem called collective sort, whose emergent properties were analyzed by relying on the prism probabilistic model checker.
using aspects and dynamic composition to provide context-aware adaptation for mobile applications. mobile systems characterize by dynamic environments, thus requiring adaptive and context aware mechanisms to perceive changes in the execution context and to dynamically adapt to them. we propose a framework for developing adaptive context aware applications which employs aspect-oriented techniques and dynamic composition to modularize the adaptive behavior and to keep apart the application logic from this behavior.
enhanced lattice-based adaptive random testing. adaptive random testing (art) has been proposed to improve the fault-detection capability of random testing (rt). lattice-based art (l-art) is a distinctive art method which generates test cases by systematically placing and then randomly shifting lattice nodes in the input domain. previous studies showed that l-art has a better fault-detection capability than rt, at the same generation cost. test cases of l-art however may be highly concentrated on certain parts of the input domain - a "skewed distribution of test cases". because of this skewed distribution, when failure regions coincidentally reside in the area where l-art selects a high density of test cases, l-art can have a better fault-detection capability than when failure regions are in the low density area. since failure regions can be in any part of the input domain, this dependency of fault-detection capability on the failure region location is undesirable. we have investigated the cause of such skewed test case distributions using l-art. based on our observations, we propose an enhancement to l-art, which not only has a less-skewed test case distribution, but also demonstrates better and more consistent fault-detection capability than the original l-art.
consistent and decentralized orchestration of bpel processes. scalability, consistency and reliability are among the key requirements for orchestration of bpel processes. in addition, system resources should be efficiently utilized. we present a fully decentralized approach to orchestration of bpel processes that achieves high scalability and supports automatic process recovery. the approach is of continuation-passing style, where continuations, or the reminder of the executions, are passed along with asynchronous messages for process orchestration. furthermore, we identify and address two consistency issues that are more challenging for decentralized orchestrations.
formalizing desargues' theorem in coq using ranks. formalizing geometry theorems in a proof assistant like coq is challenging. as emphasized in the literature, the non-degeneracy conditions leads to technical proofs. in addition, when considering higher-dimensions, the amount of incidence relations (e.g. point-line, point-plane, line-plane) induce numerous technical lemmas. in this paper, we present an original approach based on the notion of rank which allows to describe incidence and non-incidence relations such as equality, collinearity and coplanarity homogeneously. it allows to carry out proofs in a more systematic way. to validate this approach, we formalize in coq (using only ranks) one of the fundamental theorems of the projective space, namely desargues' theorem.
collaborative workflow assistant for organizational effectiveness. knowledge intensive process vary widely due to the variation in the specifics of the incoming request and uncertainty in handling and processing that request. traditional management systems with pre-defined workflows are less effective for enabling these kinds of organizational workflows. consequently, less structured tools for ad-hoc collaboration, such as email or activity management systems [8, 16] are used instead because of the flexibility they permit at execution time. however, these ad-hoc collaborative tools are not as capable of capturing best practice knowledge in a manner that is suitable for reuse in similar contexts and future executions of the workflow. we propose to mine knowledge-intensive workflow executions in order to capture and codify best practice knowledge that can be reused to assist and enhance decision making during future executions. we present a model of a dynamic system and a method for knowledge-intensive workflow enactment that captures ad-hoc applications of tacit knowledge as the work is carried out. our framework is illustrated using a critical and commonly occurring process in industry called the architecture life-cycle (alc) management process. this process reviews technological changes made to the installed information technology (it) architectures to meet the evolving requirements of the business. we illustrate how our framework allows participants to locally enhance the alc, by enabling each individual to perform their work in the best way and recording their intentions explicitly using framework mechanisms that relate activities, work products, transitions, and constraints. we illustrate the axioms that filter out best practices that have been observed during executions and feed them back to the collaborators to guide and improve future executions.
automatic product derivation of multi-agent systems product lines. multi-agent systems (mass) development and software product lines (spls) are two consolidated software engineering techniques. recent research work explores the integration between them by proposing new templates and adaptations to document spl variability in the context of mass. however, the automatic product derivation process is not addressed in these works. in this paper, we propose a new extension to our existing model-based product derivation tool, called genarch, in order to enable the automatic instantiation and customization of multiagent systems product lines (mas-pls). a case study illustrates how the proposed extension can be used to derive products (instances) from a mas-pl.
an orthogonal real-time scheduling architecture for responsiveness qos requirements in soa environments. this paper introduces a novel design approach for real-time multi-resource scheduling aimed at ensuring upper-bounded average response time in interactive computer services. by analyzing the properties of conventional heuristics, this work presents a new algorithm which combines resource and queue disciplines in an orthogonal scheduling architecture which extends recent results on stochastic real-time operations with applications on soa and pervasive computing environments. simulation experiments shows how the attributes of the proposed technique can outperform those of conventionally employed alternatives.
fast error-tolerant search on very large texts. we consider the following spelling variants clustering problem: given a list of distinct words, called lexicon, compute (possibly overlapping) clusters of words which are spelling variants of each other. this problem naturally arises in the context of error-tolerant full-text search of the following kind: for a given query, return not only documents matching the query words exactly but also those matching their spelling variants. this is the inverse of the well-known "did you mean: &hellip; ?" web search engine feature, where the error tolerance is on the side of the query, and not on the side of the documents. we combine various ideas from the large body of literature on approximate string searching and spelling correction techniques to a new algorithm for the spelling variants clustering problem that is both accurate and very efficient in time and space. our largest lexicon, containing roughly 10 million words, can be processed in about 16 minutes on a standard pc using 10 mb of additional space. this beats the previously best scheme by a factor of two in running time and by a factor of more than ten in space usage. we have integrated our algorithms into the completesearch engine in a way that achieves error-tolerant search without significant blowup in neither index size nor query processing time.
a method for developing uml state machines. while uml is one of the most used notation for describing a system to build, there are many issues to tackle to develop an appropriate uml model. in this work, we concentrate on the development of state machines describing the behaviour of a class. we show how relevant information can be searched for in the textual description and organized to obtain a behaviour description from which the state machine can be derived. our method is quite systematic and should help to prevent common mistakes in building state machines.
an evaluation of technologies for the pseudonymization of medical data. privacy is one of the fundamental issues in health care today. although, it is a fundamental right of every individual to demand privacy and a variety of laws were enacted that demand the protection of patients' privacy, approaches for protecting privacy often do not comply with legal requirements or basic security requirements. this paper highlights research directions currently pursued for privacy protection in e-health and evaluates common pseudonymization approaches against legal and technical criteria. thereby, it supports decision makers in deciding on privacy systems and researchers in identifying the gaps of current approaches for privacy protection as a basis for further research.
reduced parallel pnn algorithm for pc grid systems. parallel system with distributed memory is a promising platform to achieve a high performance computing with less construction cost. applications with few communications, such as a kind of parameter sweep applications (psa), can be efficiently carried out on such a parallel system, but some applications are not suitable for the parallel system due to a large communication cost. we focus on pnn (pairwise nearest neighbor) codebook generation algorithm for vq (vector quantization) compression algorithm and proposed a parallel version of the pnn algorithm suitable for the parallel system with distributed memory, called "multi-step parallel pnn". however, the computational complexity of the second half of this algorithm increases as the number of worker computers grows, so we apply a tree-distribution implementation to the second half in order to cope with this problem. we call this approach "reduced parallel pnn". we confirm the effectiveness of the reduced parallel pnn by the evaluation of the computational complexity of the algorithm and the experiment executed on a pc cluster system and a pc grid system.
attention driven visual processing for an interactive dialog robot. in this paper we propose an attention-based vision system for the jast interactive dialog robot. the robotic vision system incorporates three submodules: object recognition, gesture recognition and self recognition. the performance boost of our biologically inspired vision system is based on two assumptions: first, generally attention is attracted by regions of high intensity or hue gardients as well as scene dynamics (bottom-up attention attraction), and second, attentioninal focus can be directed by higher level modules, whether volitional or not, in an inhibitory or reinforcing way (top-down attention control). the system proposed in this paper is able to utilize these assumptions and organize its computational efforts accordingly. integrated into an efficient data management architecture, the vision system is capable of continuously publishing results to the cognitive layer of the robot and thus enables operations in realtime. furthermore, the modular system structure and the asynchronous communication paradigm allows for efficient integration of additional modules, be it visual or any other sensory input data. the main contribution of this work is the application of neuroscience findings and biologically plausible theories of attention based visual processing to a real-world robotic setup. here, our experimental results show tremendous speed-ups using either the bottom-up attention attractors or the principle of top-down attention control as input data filters for further visual analysis, reaching the peak in a combination of the two.
rt-replayer: a record-replay architecture for embedded real-time software debugging. recent embedded real-time software tends to be multithreaded and constrained by stringent timing requirements, thus often leading to serious faults depending on the precise timing of thread executions and event occurrences. a promising approach to debugging such complicated software is to log appropriate events during runtime and replay the same software execution based on them. this would allow one to effectively reproduce and track down the sources of faults. unfortunately, previous software-based replayers have not paid much attention to the precise timing of software execution, but largely focused on the relative order of software events. although some hardware-based replayers can provide such precise timing, they generally require a significant cost and are not available in usual development environments. in this paper, we present a software-based replayer, called rt-replayer. rt-replayer is based on two simple but effective software techniques, called virtual timestamps and instruction hooking, which enable faithful reproduction of the original software execution at instruction level accuracy.
discovery of time series in video data through distribution of spatiotemporal gradients. we propose a novel algorithm to extract time series from video to characterize the type of motion embedded in the video. our method relies on describing the motion exposed in a video as a collection of spatiotemporal gradients. each gradient models high variation in the respective region of the video both in space and time with respect to its spatiotemporal neighborhood. rather than obtaining a coarse sampling of the motion by taking one event per frame, we obtain a continuous function by considering all the events that fall in the short-time slicing window of time length equal to the value of the temporal variance. the result is a composed time series that represents the motion in the video independent of rotation and scale. as an empirical demonstration of the viability of our method, we are able to cluster human motions contained in 114 videos into hand-based motions and foot-based motions with the precision of 86.0% and 75.9% respectively.
a session based personalized search using an ontological user profile. within the information overload on the web and the diversity of the user interests, it is increasingly difficult for search engines to satisfy the user information needs. personalized search tackles this problem by considering the user profile during the search. this paper describes a personalized search approach involving a semantic graph-based user profile issued from ontology. user profile refers to the user interest in a specific search session defined as a sequence of related queries. it is built using a score propagation that activates a set of semantically related concepts and maintained in the same search session using a graph-based merging scheme. we also define a session boundary recognition mechanism based on tracking changes in the dominant concepts held by the user profile relatively to a new submitted query using the kendall rank correlation measure. then, personalization is achieved by re-ranking the search results of related queries using the user profile. our experimental evaluation is carried out using the hard 2003 trec collection and shows that our approach is effective.
a practical evaluation of large-memory data processing on a reliable remote memory system. this paper provides a preliminary performance evaluation to address the efficacy of a remote memory system (rms) by using a prototyped rms that has reliability functionality. the protyped rms is a practical kernel-level rms that supports large memory data processing, and it is built on inexpensive pcs and a high-speed network capable of remote direct memory access (rdma) operations. our experimental results suggest that an rms could be practical enough to support the rigorous demands of commercial inmemory database systems that have high data access locality, but it is not quite efficient in cpu-intensive applications due to the high page fault rate. our evaluation convinces us of the possibility that a reliable rms can satisfy both the high degree of reliability and efficiency for large memory data processing applications whose data access pattern has high locality.
a particle swarm optimization based algorithm for fuzzy bilevel decision making with constraints-shared followers. in a bilevel decision problem, decision making may involve multiple followers and fuzzy demands. this research focuses on the problem of fuzzy linear bilevel decision making with multiple followers who share common constraints (fbcsf). based on the ranking relationship among fuzzy sets defined by cut set and satisfactory degree &alpha;, a fbcsf model is presented and a particle swarm optimization based algorithm is developed. the experiments reveal that solutions obtained by this algorithm are reasonable and stable.
towards a landmark influence framework to protect location privacy. in this paper, we present a cloaking algorithm called directedcloaking to protect user's location privacy. there is a location anonymizer (la) to perform this cloaking. once this cloaked location data is provider by la, location based service provider (lbsp) can minimize and give relevant result-candidates for a given query. lbsp can also constrain the maximum possible candidates for a given query because of our definition of a possiblespace. we define, for the first time, landmark influence space (lis) and show that cloaking in lis can give the above-mentioned performance benefit to the user.
multivariate root finding with search space decomposition and randomisation. the paper presents a method for multivariate root finding that uses adaptive search space decomposition by generalised quad-trees and non-linear lagrange polynomials to interpolate the function inside the tree nodes. the method applies randomisation to achieve robustness. selection of start points for the newton-raphson like search is based on a heuristic rating of the decomposition cells. the algorithm tunes out found roots to find all solutions. although aimed at geometric constraint solving, where functions are only partially defined and no derivatives are available, the root finding method is applicable to a wider range of problems.
towards organizational agent-oriented operating systems. this work presents a new approach about modern operating systems construction based on technologies developed over the last years on software engineering. those technologies emphasize component-based architectures, distributed and network systems and, mainly, multiagent systems and organizational oriented multiagent systems. the advantages of using the agent technology on operating systems construction are exposed along this work. this technology generates an essential quality advance on the services those systems provide according to this design philosophy. the work is focused on the development of a design framework for a new generation of operating systems, based on the underlying principles of multi-agent systems and agreement technologies, in particular those, which utilise organisational principles, web services and interaction-based communication. the proposed approach integrates those middleware technologies as services for an operating system and explores the mechanisms of how such services can be globally offered to every operating system user.
a nonlinear mobile robot modeling applied to a model predictive controller. this paper presents a nonlinear modeling approach of an omnidirectional mobile robot to predict the robot behavior in a model-based predictive controller (mpc). parameters related to dynamic equations of the robot and restriction of the robot's motors are considered in the modeling. simulation results and real results of navigation are provided to demonstrate the performance of the proposed modeling approach.
a property-based verification approach in aspect-oriented modeling. aspect-oriented modeling (aom) techniques have been advocated as solutions to support separation of crosscutting features from other application design concerns. in an aom approach, crosscutting features are described by aspect models and other application features are described by a primary model [1]. however, composing an aspect model with a primary model can result in conflicts or compromised behaviors. therefore, a key issue in applying the aom approach is determining whether composition of an aspect model and a primary model produces a composed model that has desired properties. we extend the previous aspect composition approaches by france et al. [1] and song et al. [2] by supporting a way to generate proof obligations that must be discharged in order to establish that a desired property holds in the composed class model. fig. 1 shows an overview of our verifiable composition approach. the composition of a primary model class diagram and an aspect model class diagram (refer to the action (1) in fig. 1) is accomplished according to a named-based composition proposed by [1]. specifying the given property statement using the object constraint language (ocl) provides the property to be verified denoted as pprop (refer to (2)). the operation behavior in a composed model needs to be verified against this property. a proof obligation is generated and evaluated when a sequence diagram is derived from the operation specification in the composed class diagram (refer to (3)). if any faulty composition is notified during the evaluation, the current sequence diagram, which is partially derived at that point, and the current proof obligation may be used to determine at which part of the composition the property fails to hold. the information that is available when the composition stops, can be used by a developer to determine what needs to be done to correct the situation. otherwise, a sequence diagram is obtained. for details of the action (3) in fig. 1, refer to our earlier work in [3].
using web accessibility patterns for web application development. design of accessible web applications is a complex challenge. the presented concept demonstrates the potential of model-based and user-centered development. based on web accessibility patterns, a suitable solution is discussed which can be used to simplify the development process. using an established approach from web engineering, the use of patterns is demonstrated.
dynamic planning and weaving of dependability concerns for self-adaptive ubiquitous services. ubiquitous computing and service-oriented computing enable the development of a new trend of applications that can opportunely interact with services discovered in the surrounding landscape. although sporadic, this type of interaction requires the deployment of dependable mechanisms to ensure the correct completion of the interactions. however, the integration and the configuration of these mechanisms depends not only on the type of service accessed, but also on the surrounding environment. such a variability requires an extensive effort of the developers to support the alternative mechanisms. thus, to reduce this effort, we propose to integrate the aspect-oriented programming (aop) principles into the music planning-based adaptation middleware in order to dynamically plan and weave dependability concerns into the application depending on the execution context. in particular, this paper introduces our continuous support for aop, which includes i) a uniform model for describing the dependable application configurations and ii) a modular middleware platform for weaving and configuring the dependability concerns when necessary.
points-to analysis for javascript. javascript is widely used by web developers and the complexity of javascript programs has increased over the last year. therefore, the need for program analysis for javascript is evident. points-to analysis for javascript is to determine the set of objects to which a reference variable or an object property may point. points-to analysis for javascript is a basis for further program analyses for javascript. it has a wide range of applications in code optimization and software engineering tools. however, points-to analysis for javascript has not yet been developed. javascript has dynamic features such as the runtime modification of objects through addition of properties or updating of methods. we propose a points-to analysis for javascript which precisely handles the dynamic features of javascript. our work is the first attempt to analyze the points-to behavior of javascript. we evaluate the analysis on a set of javascript programs. we also apply the analysis to a code optimization technique to show that the analysis can be practically useful.
using dynamic bayesian networks to infer gene regulatory networks from expression profiles. two major challenges in inferring the sparse topological architecture of gene regulatory networks using computational methods are 1) the low accuracy of predicting connections between genes and 2) the excessive computational cost. in order to address these challenges, we have exploited some biological features of yeast cell cycle. one such feature is that, a high proportion of cell cycle regulated genes are periodically expressed; that is genes are maximally expressed to affect and control the regulation of other genes and on completing certain tasks; they are repressed by some other regulator genes. thus the whole cell cycle progresses systematically through the successive activation and inactivation of ccr genes. to use this feature, we have calculated the peak time of individual genes which falls into one/more phases of the cell cycle. therefore, genes that peak in the interval of the same phase of the cell cycle have been grouped together. finally, we have applied the dynamic bayesian network (dbn) algorithm within distinct phases of genes. as a consequence, both the accuracy and the computational cost of our learning algorithm have been improved in comparison with the existing dbn algorithms.
web-services in the dutch healthcare insurance sector: expected versus achieved benefits. the upcoming buzz words nowadays appear to be web service or open network environment [4]. this is the latest it-technology to support business processes which is embraced by an increasing number of companies, many of which are in the financial sector. this paper investigates if the promises made by technology providers and it strategists have been made true by looking at the actual business benefits of web services.
developing and evaluating web multimodal interfaces - a case study with usability principles. in this paper we describe an approach to facilitate the design of web multimodal interfaces aiming at improving the user experience and the user interface usability using speech recognition together with the usual graphical user interfaces. we present a proposal for usability evaluation based on the heuristic evaluation, which considers the multimodal principles identified during a case study. as a result of using the proposed approach in the case study and from literature review, we report our considerations for the design, development and improvement of the web multimodal interfaces.
adaptive finite element methods for nonlinear inverse problems. nonlinear inverse problems are usually formulated as optimization problems on function spaces constrained by partial differential equations. as a consequence, in realistic, three-dimensional cases, they become extraordinarily expensive to solve numerically, and advanced methods like adaptive mesh refinement become indispensible. in this contribution, we outline such an adaptive algorithm and demonstrate results using a realistic example from optical tomography.
expert system for supporting conformity inspections of software application interfaces to the iso 9241. usability assessment of products based on the iso 9241 standard has been usually carried out by using printed parts of this standard and its checklists. in this paper it is proposed a tool for supporting conformity inspections of software application user interfaces based upon iso 9241. the proposed expert system -- x-sci (expert software conformity inspection) -- aims to give support to user interface designers and evaluators in iso 9241 standard inspection processes. it will treat differently these categories of professionals by assigning different degrees of certainty to their choices in each stage of the inspection.
mapping semantically enriched formal tropos to business process models. in the context of semantic business process management (as defined by the super project), there is a current lack of requirements engineering methodologies to acquire correctly semantically annotated business process models. this paper meets this need by extending the existing formal tropos specification, originating from early phase requirements engineering, to embed semantic annotations. furthermore, detailed mappings are proposed to translate semantically enriched formal tropos scripts into business process modelling ontology (bpmo), which is a superset of business process modelling notation (bpmn) and event-deriven process chain (epc).
the device service bus: a solution for embedded device integration through web services. this paper presents a middleware infrastructure for integration of heterogeneous embedded devices in ubiquitous computing environments. the proposed infrastructure employs the devices profile for web services (dpws) as the underlying integration technology, allowing devices that adopt different networking standards to interact with each other, through the use of interconnection devices and software components responsible for building a communication path among them. a prototype implementation of this middleware infrastructure is also described, and results of performance measurements obtained with this prototype are presented.
latency-aware leader election. experimental studies have shown that electing a leader based on measurements of the underlying communication network can be beneficial. we use this approach to study the problem of electing a leader that is eventually not only correct (as captured by the &omega; failure detector abstraction), but also optimal with respect to the transmission delays to its peers. we give the definitions of this problem and a suitable model, thus allowing us to make an analytical analysis of the problem, which is in contrast to previous work on that topic.
architectural requirements prioritization and analysis applied to software technology evaluation. in this short paper, we summarize an industrial project in which we developed and applied the attribute hierarchy-based evaluation of architectural designs (ahead) method for selecting a software technology to form the basis for the next-generation architecture of a complex commercial software application. ahead leverages the software engineering institute's attribute-driven design (add) method and the analytic hierarchy process (ahp) for evaluating software technologies that have important architectural impact. the core activities of ahead include elicitation, prioritization, and analysis of architectural requirements. the goal of these requirements activities was to establish and apply objective criteria for selecting, prototyping, and evaluating software technology alternatives. we found that using ahead brought greater objectivity to prioritization of architectural requirements and to the technical judgments of the software technology options.
a generic library for gui reasoning and testing. graphical user interfaces (guis) make software easy to use by providing the user with visual controls. therefore, correctness of gui's code is essential to the correct execution of the overall software. models can help in the evaluation of interactive applications by allowing designers to concentrate on its more important aspects. this paper presents a generic model for language-independent reverse engineering of graphical user interface based applications, and we explore the integration of model-based testing techniques in our approach, thus allowing us to perform fault detection. a prototype tool has been constructed, which is already capable of deriving and testing a user interface behavioral model of applications written in java/swing.
on the practical importance of communication complexity for secure multi-party computation protocols. many advancements in the area of secure multi-party computation (smc) protocols use improvements in communication complexity as a justification. we conducted an experimental study of a specific protocol for a real-world sized problem under realistic conditions and it suggests that the practical performance of the protocol is almost independent of the network performance. we argue that our result can be generalized to a whole class of smc protocols.
a framework for modelling and implementing self-organising coordination. research fields like pervasive computing are showing that the interactions between components in large-scale, mobile, and open systems are highly affected by unpredictability: self-organising techniques are increasingly adopted within infrastructures aimed at managing such interactions in a robust and adaptive way. accordingly, in this paper we discuss the framework of self-organising coordination: coordination media spread over the network are in charge of managing interactions with each other and with agents solely according to local criteria, making interesting and fruitful global properties of the resulting system appearing by emergence---probability and timing typically playing a crucial role. we show that the tucson coordination infrastructure can be used as a general platform for enacting self-organising coordination; we put it to test on two cases: an inter-space application of adaptive tuple clustering, and a intra-space application of chemical-like coordination reactions.
decentralized coordination of homogeneous and heterogeneous agents by digital infochemicals. effective decentralized coordination mechanisms enabling self-organizing emergent solutions have to take into account the inherent heterogeneity of components involved in most of the problems such solutions are intended for. thus, versatile mechanisms take inspirations from coordination paradigms between homogeneous or heterogeneous organisms in biology using chemical stimuli. an economic engineering of such self-organizing emergent solutions however requires an expressive, abstract coordination model that allows for the combination of different digital chemical stimuli into coherent and efficient coordination mechanisms. this work discusses certain shortcomings of the existing abstract model as well as proposes and evaluates improvements to it.
improving classification based off-topic search detection via category relationships. the illegitimate access of documents by insiders (also known as off-topic search) is an increasingly prevalent and largely ignored problem. we propose an approach that uses text classification for off-topic search detection. our empirical results indicate that off-topic search detection effectiveness improves by considering only a subset of documents that are retrieved for a given user query. furthermore, we also show that the effectiveness of off-topic search detection improves by using the ontological information of document categories. our empirical results demonstrate that utilizing sibling relationship information and relationships derived from misclassification information statistically significantly improves the results over the baseline in most cases.
the current feasibility of gesture recognition for a smartphone using j2me. the need to improve communication between humans and computers has been instrumental in defining new communication models, and accordingly, new ways of interacting with machines. the use of gestures as a means of communication has been a challenging task. the latest generation of smartphones boasts powerful processors and built-in video cameras, making them capable of executing complex and computationally demanding applications. thus, the integration of gesture recognition systems in smartphone applications might be a close reality. in this paper, we present studies of a gesture recognition prototype system for smartphones. we use a number of tasks typically employed in gesture recognition systems which permit to assess the current feasibility of smartphones to implement this kind of systems. based on both the execution time and classification performance, we conclude that the latest smartphone generation is capable of executing complex image processing applications, with the most penalizing factor being camera performance regarding capture rates with the current j2me support.
link-based event detection in email communication networks. people's email communications can be modeled as graphs with vertices representing email accounts and edges representing email communications. email communication data usually comes in as continuous data stream. event detection aims to identify abnormal email communications that serve as analogs of real-world events imposed upon the data stream. the goal is to understand the communications behaviors of the subjects. the contents of emails are often not available or protected by privacy, which makes linkage information the only resource we can rely on. we propose a link-based event detection method that clusters vertices with similar communication patterns together and then, considers deviations from each vertex's individual profile, as well as its cluster profile. experiments show that this method performs well on both enron and our own email datasets.
fast mode decision for scalable video coding based on neighboring macroblock analysis. in this paper, we propose a fast mode decision for b frame in svc. it makes use of the mode distribution correlation between current mb and neighbor mbs. experimental results show that the proposed schemes save up to 57.8% of encoding time with a negligible coding loss and bit-rate increase.
interlaced euler scheme for stiff systems of stochastic differential equations. in deterministic as well as stochastic models, stiff systems, i.e., systems with vastly different time scales where the fast scales are stable, are very common. it is well known that the implicit euler method is well suited for stiff deterministic equations (modeled by odes) while the explicit euler is not. in particular, once the fast transients are over, the implicit euler allows for the choice of time steps comparable to the slowest time scales of the system. in stochastic systems (modeled by sdes) the picture is more complex. while the implicit euler has better stability properties over the explicit euler, it underestimates the stationary variance. in general, one may not expect any method to work successfully by taking time steps of the order of the slowest time scale. we explore the idea of interlacing large implicit euler steps with a sequence of small explicit euler steps. in particular, we present our study of a linear test system of sdes and demonstrate that such interlacing could effectively deal with stiffness. we also discuss the uniform convergence of mean and variance.
dostrack: a system for defending against dos attacks. denial of service (dos) attacks are one of the complex problems in the current internet. in this paper, we propose a system, dostrack, that can efficiently deal with the tcp syn and reflection distributed denial of service (ddos) attacks. we also describe a prototype implementation of our model with hp openview network node manager (nnm) and discuss how our model can be beneficial to the ddos victim and the isp.
exhaustion dominated performance: a first attempt. in this paper we present a first attempt to an analytical method to discover and understand how the available resources influence the execution time. our method is based on a piecewise linear model for dominating execution limitations and black-box observations. we verify this analysis method by a set of real-world experiments. finally, we conclude that the different effects follow a linear superposition within a certain range.
a new protein motif extraction framework based on constrained co-clustering. signal finding (pattern discovery) in biological sequences is a fundamental problem in both computer science and molecular biology. many approaches have been proposed for extracting interesting patterns (or motifs) from dna/rna and protein sequences. some approaches are based on simple and multiple alignment techniques, some use biological knowledge and others do not. in this paper, we propose a de novo framework that performs motifs identification and exploits a constrained co-clustering technique allowing one to simultaneously find associations between groups of protein sequences and groups of motifs. we show that the presented approach is able to group together protein sequences belonging to the same families and, at the same time to provide a set of characterizing motifs.
efficient processing of sparql joins in memory by dynamically restricting triple patterns. since there are a lot of similar or common properties between rdf and relational databases and between sparql and sql, many efforts focus on leveraging the research results of optimizing relational query languages for optimizing sparql queries. however, sparql has its own characteristics different from sql, which are not fully exploited by existing work. therefore, there is still much space for research on optimizing sparql queries. based on the triple nature of rdf data, we create 7 indices to retrieve rdf data quickly; based on the sparql-specific properties and the 7 indices, we develop a new, efficient approach to computing join by dynamically restricting triple patterns. our experimental results show the efficiency of our approach.
server push with instant messaging. server push is an essential part of modern web applications. with the ability of sending relevant information to users in reaction to new events, enables highly interactive applications on the www. user interfaces of desktop applications have had a two-way communication with an underlying software since their advent, but web applications are reaching the same state only now. in addition, currently, the push is usually emulated using the pull technology, since, with the http protocol alone, it is not possible to realize a real push. this paper evaluates how an instant messaging protocol, namely xmpp, can complement http-based web applications. we present a communication paradigm of a push system and an implementation of it. to evaluate the implementation, a use case is designed and realized with the system.
a method for clustering transient data streams. this paper describes a novel method for clustering single and multi-dimensional data streams. with incremental computation of the incoming data, our method determines if the cluster formation should change from an initial cluster formation. four main types of cluster evolutions are studied: cluster appearance, cluster disappearance, cluster splitting, and cluster merging. we present experimental results of our algorithms both in terms of scalability and cluster quality, compared with recent work in this area.
combining statistics and semantics via ensemble model for document clustering. incorporating background knowledge into data mining algorithms is an important but challenging problem. current approaches in semi-supervised learning require explicit knowledge provided by domain experts, knowledge specific to the particular data set. in this study, we propose an ensemble model that couples two sources of information: statistics information that is derived from the data set, and sense information retrieved from wordnet that is used to build a semantic binary model. we evaluated the efficacy of using our combined ensemble model on the reuters-21578 and 20newsgroups data sets.
adaptive burst detection in a stream engine. detecting bursts in data streams is an important and challenging task. due to the complexity of this task, usually burst detection cannot be formulated using standard query operators. therefore, we show how to integrate burst detection for stationary as well as non-stationary data into query formulation and processing, from the language level to the operator level. afterwards, we present fundamentals of threshold-based burst detection. we focus on the applicability of time series forecasting techniques in order to dynamically identify suitable thresholds for stream data containing arbitrary trends and periods. the proposed approach is evaluated with respect to quality and performance on synthetic and real-world sensor data using a full-fledged dsms.
a collaborative tool for designing and enacting design processes. today several approaches using situational method engineering paradigm exist, each of them proposes methods and techniques for developing ad-hoc design processes. in this context heavy efforts were spent in the construction of appropriate tools that could help method engineers in producing a specific design process and in using it. we developed a tool called metameth for supporting the design process definition and its enactment. metameth is implemented as a multi-agent system, where each agent is capable of reasoning and adapting itself in order to support the designer in performing different kinds of design activities.
swobe - embedding the semantic web languages rdf, sparql and sparul into java for guaranteeing type safety, for checking the satisfiability of queries and for the determination of query result types. the semantic web and its technologies become increasingly important. as more and more semantic web applications are being used, developing more stable semantic web applications becomes a key issue. the state-of-the-art in programming semantic web applications is using complex application programming interfaces of semantic web frameworks, where extensive tests are necessary for the detection of errors, although many types of errors could be detected already at compile time. in this paper, we propose an embedding of semantic web languages into the java programming language, such that semantic web data and queries can be transparently used, type safety is guaranteed, and already at compile time, syntax errors of semantic web data and queries are reported, unsatisfiable queries are detected and the types of query results are determined. a demonstration of our system is available online.
implementing rigorous web services with process algebra: navigation plan for web services. despite the popularity of standards such as bpel in business-critical applications, rigorous approaches to web service composition remain an open research problem. frameworks based on formal foundations (e.g., process algebra or petri nets) have emerged as promising approach to address these challenges. this work introduces the navigation plan for web services (npws), a system module, which extends a process algebra based workflow engine with a web service interface. we systematically combine the web service paradigm and comprehensive real-world workflow functionality while guaranteeing sound properties through formal process specification. process instantiation and execution monitoring are implemented with enterprise javabeans, sql extension, and java persistence api to ensure flexibility and scalable integration. our primary contribution is an applied approach to implementing complex web services with formal properties through a well-defined process algebraic core. we further illustrate our system with sample client applications and a case study based on an actual deployment in a library environment.
socially filtered web search: an approach using social bookmarking tags to personalize web search. today's knowledge workers are confronted with an ever increasing information overload while searching for needed information in the web. common search engines do not take into account the current work context of the user. but we consider context information as an effective means to implicitly narrow the information space of the web. in this paper we present a novel approach that increases the relevance of search results by considering the current work context. we track the user's web browsing behavior, store visited pages and build up a user model based on this information. as the user browses, the stored urls of the visited pages are enhanced with tags from social bookmarking sites. based on the user model and the retrieved bookmarks we developed an easy-to-use and easy-to-configure clientside web search engine that refines the original search query with these tags. our approach follows the design principle of non-intrusiveness. that means we present the context-sensitive personalized adapted search results together with the original non-adaptive search results. we developed an open architecture that allows the user to reconfigure the system to use different metadata providers and search engines. in order to prove our architecture we implemented a firefox add-on.
agenttool process editor: supporting the design of tailored agent-based processes. this paper describes the agenttool process editor (ape), an eclipse plug-in based on the eclipse process framework. the aim of ape is to facilitate the design, verification, and management of custom agent-oriented software development processes. ape provides five basic structures. the library is a repository of agent-oriented method fragments. a process editor allows the management of tailored processes. task constraints help process engineers specify guidelines to constrain how tasks can be assembled, while a process consistency mechanism verifies the consistency of tailored processes against those constraints. finally, the process management integrates ape with the agenttool iii development environment and provides a way to measure project progress using earned value analysis.
semantic web services: from owl-s via uml to mvc applications. owl-s is used to describe the semantics of web services so that the discovery, selection, invocation and composition of these services can be automated. prior research has shown that uml diagrams can be used to automatically generate semantic web service descriptions in owl-s. if complete web applications could be generated from owl-s descriptions, then a higher level of automation would be achieved. in this paper, we propose an approach for processing owls descriptions in order to produce mvc-based skeletons for web applications. the owl-s ontology goes through a series of transformations in order to generate an application whose model-view-controller structure is implemented by a combination of javabeans/jsp/servlets code, respectively.
bpr: a bit-level packet recovery in wireless sensor networks. in wireless sensor networks (wsns), the bit-error-rate (ber) is so high that the receiver requests retransmission frequently. packet recovery is an important technology to improve transmission performance. in this paper, we propose bpr, a bit-level packet recovery scheme in wsns. in bpr, if a packet is corrupted for two times, instead of request the whole packet, the receiver compares these two corrupted copies of the packets and determines which bit(s) should be retransmitted. bpr sits between mac sub-layer and logical link control (llc) sub-layer and can be compatible with most of current packet recovery schemes and is very easy to implement. the analysis shows that bpr can yield a gain of 364% compared with seda[1] and even more with 802.11 in high ber environments.
situated process engineering for integrating processes from methodologies to infrastructures. in the field of multi-agent systems (mass), methodologies and infrastructures have developed in the last years along two opposite paths: while agent-oriented methodologies have essentially undergone a top-down evolution, mas infrastructures have mostly followed a bottom-up path, producing a conceptual gap between methodologies and the available agent infrastructures. this paper aims at defining a method for filling such a gap, based on situational method engineering (sme) and spem (software process engineering meta-model). after highlighting the lack of sufficient research and understanding about the role of the infrastructures in the software engineering process, we show that infrastructures, like methodologies, have processes behind them, and propose a method based on the integration of the processes underpinning both methodologies and infrastructures. then, we validate such an approach by showing how the process of the soda methodology can be integrated with the process of the tucson infrastructure using sme and spem.
wireless communication glove apparatus for motion tracking, gesture recognition, data transmission, and reception in extreme environments. military personnel need better ways to communicate in hostile, noisy, silence-mandated, and/or extreme environments. typing on a keyboard is difficult and impractical while wearing comprehensive protective clothing. wireless data gloves were researched and developed to transmit and receive ascii code and other signals as hand gestures. two categories of glove prototypes were constructed: gloves with and without a haptic-io capability. all data gloves detect motion, such as gestures, using magnetic sensors. non-haptic gloves only transmit static and dynamic gestures. haptic gloves have vibro-mechanical devices on the fingertips for feedback about transmitted signals and for covert-signal reception. many potential communications applications include hazardous and covert military operations, space operations, fire fighting, mining, training, underwater use, and aids for the visually and hearing impaired.
isomorphisms, hylomorphisms and hereditarily finite data types in haskell. this paper is an exploration in a functional programming framework of isomorphisms between elementary data types (natural numbers, sets, bitstrings, finite functions) and their extension to hereditarily finite universes through hylomorphisms derived from ranking and unranking operations. the paper is part of a larger effort to cover in a declarative programming paradigm some fundamental combinatorial generation algorithms along the lines of knuth's recent work [10]. the self-contained source code of the paper, as generated from a literate haskell program, is available at http://logic.csci.unt.edu/tarau/research/2008/sfiso.zip.
efficient concept detection by fusing simple visual features. concept detection is one of the important tasks in video indexing due to its importance to bridging the semantic gap in multimedia retrieval. many methods have been proposed for this task, however finding a method which can generalize well for a large number of concepts and is scalable for processing huge video databases is still challenging. in this paper, we introduce a general framework for efficient and scalable concept detection by fusing svm classifiers trained by only simple visual features such as color moments, edge orientation histogram and local binary patterns. we evaluate the proposed framework for detecting a large number of concepts on various trecvid datasets with hundreds of hours of video. experimental results show that the proposed framework achieves good performance with a small computational cost.
management of requirements in erp development: a comparison between proprietary and open source erp. identification and specification of business requirements are extremely important when development of enterprise resource planning systems (erps) take place. it can be stated that this is still a problematic area not well researched and, as a result from that, it does not exist much guidance on how to deal with requirements. in this paper we discuss if existing problems of requirements management are the same or if they differ according to the type of development: closed source (proprietary) or open source erp. the reason is that it is possible that these two approaches can promote each other in how to improve the first phase in erp development. from the discussion about similarities and differences between the two approaches it is suggested further research in this area that could end up in some more practical guidelines on how to do the requirements definition so that the finally developed erps better support adopters' needs.
flashbox: a system for logging non-deterministic events in deployed embedded systems. the ability to postmortem failures in deployed systems due to non-deterministic events is useful in crash investigations. with this goal in mind, we propose flashbox - a system that acts as a black box for embedded systems, recording non-deterministic events (interrupts). the flashbox hardware consists of a microcontroller and flash memory. the flashbox software is an extension to a compiler, enabling recording capabilities at various granularities. there are no source code modifications required to use flashbox and no assumptions made on processor capabilities such as hardware counters. the flashbox log can be used for faithful replay with a goal to isolate faults and reason about failure. we present a prototype implementation of flashbox that logs non-deterministic events on an avr atmega169 microcontroller. the flashbox prototype consists of a 8051 microcontroller with flash memory. the avr-gcc compiler has been extended to log non-deterministic events. based on our experimental results, flashbox results in 10-23% overhead while providing capability to log non-deterministic events at instruction level granularity. with decreasing cost of flash memories, flashbox provides a low cost logging mechanism. the use of standard i/o communication protocols enhances portability, enabling ease of integration for different classes of embedded systems.
evaluation of visual attention models under 2d similarity transformations. the computational models of visual attention, originally proposed as cognitive models of human attention, nowadays are being used as front-ends to some robotic vision systems, like automatic object recognition and landmark detection. however, these kinds of applications have different requirements from those originally proposed. more specifically, a robotic vision system must be relatively insensitive to 2d similarity transformations of the image, as in-plane translations, rotations, reflections, and scales. in this paper several experiments with two visual attention models publicly available are described. the results show that the best known model, called nvt, is extremely sensitive to these 2d similarity transformations. therefore, a new visual attention model, called nlook, is proposed and validated with the same invariance criteria, and the results show that nlook is less sensitive to these kind of transformations than the other two models. besides, nlook can select better fixations according to a redundancy criterion. thus, the proposed model is an excellent tool to be used in robot vision systems.
towards the universal semantic assessment of accessibility. the ever increasing adoption of software technologies has bring closer technology to users with disabilities and users that interact with devices other than a pc. this diversification poses a real challenge to developers when creating software that has to cope with a myriad of interaction situations, as well as specific directives for ensuring an accessible interaction. in this paper we present saaf, the semantic accessibility assessment framework. saaf provides a set of constructs to describe the semantics of accessibility assessment procedures that can cope with different users, devices, and software technologies in a coherent and formalised way. saaf affords the description of users and devices, their constraints and requirements, in the light of different accessibility assessment procedures. we exemplify the usage of saaf by applying it in the context of the web and related accessibility best practices such as wcag.
on a discretizable subclass of instances of the molecular distance geometry problem. the molecular distance geometry problem can be formulated as the problem of finding an immersion in r3 of a given undirected, nonnegatively weighted graph g. in this paper, we discuss a set of graphs g for which the problem may also be formulated as a combinatorial search in discrete space. this is theoretically interesting as an example of "combinatorialization" of a continuous nonlinear problem. it is also algorithmically interesting because the natural combinatorial solution algorithm performs much better than a global optimization approach on the continuous formulation. we present a branch and prune algorithm which can be used for obtaining a set of positions of the atoms of protein conformations when only some of the distances between the atoms are known.
designing a multi-core hard real-time test bed for energy measurement experiments. this paper presents a systematic methodology to implement and validate schemes for energy-efficient task allocation and scheduling in multi-core hard real-time embedded systems. a real-life test bed comprising dual-core intel t2500 processor with dynamic voltage scaling (dvs) capability and running linux fedora 8 based hard real-time scheduling has been developed to accurately benchmark the energy-savings of various proposed scheduling schemes and the experience from implementation is summarized to serve as potential guidelines for other researchers and practitioners.
constraint-based modelling and analysis of organisations. modern organisations are characterised by a great variety of forms and often involve many actors with diverse goals, performing a wide range of tasks in changing environmental conditions. due to high complexity, mistakes and inconsistencies are not rare in organisations. to provide better insights into the organisational operation and to identify different types of organisational problems explicit specification of relations and rules, on which the structure and behaviour of an organisation are based, is required. before it is used, the specification of an organisation should be checked for internal consistency and validity w.r.t. the domain. to this end, the paper introduces a framework for formal specification of constraints that ensure the consistency and validity of organisational specifications. to verify the satisfaction of constraints, efficient and scalable algorithms have been developed and implemented. the framework presented here is based on the organisation modelling framework from [2] which defines four interrelated organisational views (or perspective) with their dedicated predicate logic-based languages: performance-oriented, process-oriented, organisation-oriented and agent-oriented. to express temporal relations, the dedicated languages of the views are embedded into the temporal trace language (ttl) [2], which is a variant of the order-sorted predicate logic. some of the examples given in the paper are from a case study in the air traffic domain.
a biochemical metaphor for developing eternally adaptive service ecosystems. in the near future, pervasive sensing and actuating devices will densely populate our everyday environments, and will be tightly integrated with telecom and internet networks---also eventually contributing to blur their distinction.
decomposing port automata. port automata are an operational model for component connectors in a coordination language such as reo. they describe which sets of ports can synchronize in each state of the connector being modelled. this paper presents decomposition theorems for port automata, namely that all (finite) port automata can be generated from a small set of primitive port automata. applying these results to component connectors means that all component connectors can be constructed from just two primitive connectors.
matraca: a tool to provide support for people with impaired vision when using the computer for simple tasks. this paper introduces a computational tool - matraca - developed for the purpose of minimizing accessibility constraints related to the use of computers by people with visual disabilities (low vision or blind users). matraca offers a text edition environment associated to a vocal spell checker and an interface with special graphical elements and sound elements manipulated by speech synthesizer and/or speech recognition. considering several aspects of accessibility, matraca provides several tasks that can be performed using the computer, where most of application are highly bounded to visual features, and dependence, considering the user profile. several quality technologies were included in matraca creating a flexible environment in an open source tool.
an intelligent video system for vehicle localization and tracking in police cars. this work aims at real-time in-car video analysis to detect several critical events in order to alarm and assist police action. particularly, detecting a tracked or stopped vehicle is a crucial task for further examination of suspects, protecting police safety, and remote monitoring from police station. this paper describes a comprehensive approach to localize targeted vehicles in the video under various environments and illumination conditions. the extracted geometry features on the moving objects and background are dynamically projected onto a 1d profile and are constantly tracked. we rely on temporal information of features for vehicle identification, which compensates for the complexity of vehicle shapes, colors and types. we investigated videos of day and night, and different types of roads, proving that our employed approach is robust and effective.
an adaptive block-set based management for large-scale flash memory. with rapid increase of the capacity of flash-memory storage systems, it becomes critical to provide efficient management for large-scale flash-memory. compared with ftl (flash translation layer), nftl (nand flash translation layer) provides less main-memory space requirements for large-scale flash memory. however, because each replacement block is exclusively used by a logical block, nftl exhibits poor space utilization of flash memory. in this paper, we present an adaptive block-set based flash memory management. the presented scheme adopts shared and exclusive replacement blocks, and allocates replacement blocks according to the update loads of logical blocks. the experimental results show that the presented scheme yields a better performance in garbage collection than nftl and fast (fully associative sector translation), keeping space utilization of flash memory at high level.
sosaa: a framework for integrating components & agents. modern computing systems require powerful software frameworks to ease their development and manage their complexity. these issues are addressed within both component-based software engineering and agent-oriented software engineering, although few integrated solutions exist. this paper discusses a novel integration strategy, which builds upon both paradigms to address their shortcomings while leveraging their different characteristics to define a complete software framework.
keeping diversity when exploring dynamic environments. this paper presents a new exploration mechanism based on a heterogeneous multi-agent system that combines attractive and repulsive agents. we provide experimental results about the performance of our mechanism in dynamic environments when resources continuously appear and disappear.
on-line adaptation of sequential mobile processes running concurrently. process management systems (pmss) are nowadays more and more used as a supporting tool for cooperative processes in pervasive and highly dynamic situations, such as emergency situations, pervasive healthcare or domotics/home automation. but in all such situations, designed processes can be easily invalidated since the execution environment may change continuously due to frequent unforeseeable events. in this work we deal with process adaptability, i.e., the ability of the pms to automatically cope with deviations, and we devise a sound and complete technique suitable for sequential processes running concurrently. the technique is based on a general framework which adopts the situation calculus, congolog and regression planning as basic elements. the applicability to the challenging scenario of emergency management is also shown.
remote software protection by orthogonal client replacement. in a typical client-server scenario, a trusted server provides valuable services to a client, which runs remotely on an untrusted platform. of the many security vulnerabilities that may arise (such as authentication and authorization), guaranteeing the integrity of the client code is one of the most difficult to address. this security vulnerability is an instance of the malicious host problem, where an adversary in control of the client's host environment tries to tamper with the client code. we propose a novel client replacement strategy to counter the malicious host problem. the client code is periodically replaced by new orthogonal clients, such that their combination with the server is functionally-equivalent to the original client-server application. the reverse engineering efforts of the adversary are deterred by the complexity of analysis of frequently changing, orthogonal program code. we use the underlying concepts of program obfuscation as a basis for formally defining and providing orthogonality. we also give preliminary empirical validation of the proposed approach.
concern-oriented business architecture engineering. organizations are subject to constant evolution and must systematically analyze and design the impact of change to implement it consistently across all organizational domains. a thorough understanding of all relevant business-related artifacts as well as their relationships is a prerequisite to achieve this. for many organizations, business architecture management is a means to ensure the correct and up-to-date documentation of these artifacts. one challenge of business architecture management is the development a company-specific business architecture meta model. two directions of existing work provide partial solutions: (1) generic (meta) modeling methods and (2) business architecture meta models and languages. we argue that these two approaches complement each other and should be applied in an integrated way. the goal of this contribution is to propose such an integrated approach to business architecture engineering. the development of this approach follows the design research process and is based on experiences gained in three industrial business architecture engineering projects.
discovering xml keys and foreign keys in queries. the xml has undoubtedly become a standard for data representation and manipulation. but most of xml documents are still created without the respective description of their structure, i.e. an xml schema. in this paper, we further enhance current methods for automatic inferring of an xml schema with discovering keys and foreign keys. we do not consider sample xml data for discovery but a set of queries in xquery and we show how constructs utilized in the queries can be used for the discovery.
open source vs. closed source software: towards measuring security. the increasing availability and deployment of open source software in personal and commercial environments makes open source software highly appealing for hackers, and others who are interested in exploiting software vulnerabilities. this deployment has resulted in a debate "full of religion" on the security of open source software compared to that of closed source software. however, beyond such arguments, only little quantitative analysis on this research issue has taken place. we discuss the state-of-the-art of the security debate and identify shortcomings. based on these, we propose new metrics, which allows to answer the question to what extent the review process of open source and closed source development has helped to fix vulnerabilities. we illustrate the application of some of these metrics in a case study on openoffice (open source software) vs. microsoft office (closed source software).
towards developing a trust-based security solution. wireless sensor network has emerged as a new information and data gathering paradigm based on the collaborative efforts of a large number of autonomous sensing devices. with small memories and processors, limited energy and tiny packets, sensor networks cannot afford traditional luxury security solutions; this limitation causes security threats. there are several important security challenges, including access control, message integrity and confidentiality, and trust solutions that require us to use a careful design of resource constraints for pursuing more enhanced security solutions for a wireless sensor network. in this paper, we present a new idea of persistent security solutions that support trust for general purpose wireless sensor networks.
routing and scheduling in multihop wireless networks with time-varying channels. we study routing and scheduling in multihop wireless networks. when data is transmitted from its source node to its destination node it may go through other wireless nodes as intermediate hops. the data transmission is node constrained, i.e. every node can transmit data to at most one neighboring node per time step. the transmission rates are time varying as a result of the changing wireless channel conditions.in this paper we assume that the data arrivals and transmission rates are governed by an adversary. the power of the adversary is limited by an admissibility condition which forbids the adversary from overloading any wireless node a priori. the node constrained transmission and the time-varying nature of the transmission rates make our model different from and harder than the standard adversarial queueing model which relates to wireline networks.for the case in which the adversary specifies the paths that the data must follow, we design scheduling algorithms that ensure network stability. these algorithms try to give priority to data that is closest to its source node. however, at each time step only a subset of the data queued at a node is eligible for scheduling. one of our algorithms is fully distributed.for the case in which the adversary does not dictate the data paths, we show how to route the data so that the admissibility condition is satisfied. we can then schedule data along the chosen paths using our stable scheduling algorithms. we conclude by discussing the performance of distributed load balancing algorithms for combined routing and scheduling.
weighted isotonic regression under the norm. isotonic regression, the problem of finding values that best fit given observations and conform to specific ordering constraints, has found many applications in biomedical research and other fields. when the constraints form a partial ordering, solving the problem under the l1 error measure takes o(n3) when there are n observations. the analysis of large-scale microarray data, which is one of the important tools in biology, using isotonic regression is hence expensive. this is because in microarray analysis, the same procedure is used for studying the fit of tens of thousands of genes to a given partial order. fast estimation for the fitting error is therefore highly desired to reduce the number of regression instances through pruning. in this paper, we present approximation algorithms to the isotonic regression problem under the l1 error measure. we relate the problem to an edge packing problem and in the special case when the observations are not weighted, we relate it to a weighted matching problem.
compact labeling schemes for ancestor queries. we consider the following problem. give a rooted tree t, label the nodes of t in the most compact way such that given the labels of two nodes one can determine in constant time, by looking only at the labels, if one node is an ancestor of the other. the best known labeling scheme is rather straightforward and uses labels of size at most 2 log n, where n is the number of vertices in the tree. our main result in this paper is a labeling scheme with maximum label size close to 3/2 log n. our motivation for studying this problem is enhancing the performance of web search engines. in the context of this application each indexed document is a tree and the labels of all trees are maintained in main memory. therefore even small improvements in the maximum label size are important. there are no lower bounds known for this problem except for an obvious lower bound of log n that follows from the fact that different vertices must have different labels. the question whether one can find even shorter labels remains an intriguing open question.
popular matchings. we consider the problem of matching a set of applicants to a set of posts, where each applicant has a preference list, ranking a nonempty subset of posts in order of preference, possibly involving ties. we say that a matching $m$ is popular if there is no matching $m'$ such that the number of applicants preferring $m'$ to $m$ exceeds the number of applicants preferring $m$ to $m'$. in this paper, we give the first polynomial-time algorithms to determine if an instance admits a popular matching and to find a largest such matching, if one exists. for the special case in which every preference list is strictly ordered (i.e., contains no ties), we give an $o(n + m)$ time algorithm, where $n$ is the total number of applicants and posts and $m$ is the total length of all of the preference lists. for the general case in which preference lists may contain ties, we give an $o(\sqrt{n}m)$ time algorithm.
comparison-sorting and selecting in totally monotone matrices. an m x n matrix a is called totally monotone if for all i1 < i2 and j1 < j2, a[i1, j1] > a[i1, j2 implies a[i2, j1] > a[i2, j2]. we consider the complexity of comparison-based selection and sorting algorithms in such matrices. although our selection algorithm counts only comparisons its advantage on all previous work is that it can also handle selection of elements of different (and arbitrary) ranks in different rows (or even selection of elements of several ranks in each row), in time which is slightly better than that of the best known algorithm for selecting elements of the same rank in each row. we also determine the decision tree complexity of sorting each row of a totally monotone matrix up to a factor of at most log n by proving a quadratic lower bound and by slightly improving the upper bound. no nontrivial lower bound was previously known for this problem. in particular for the case m = n we prove a tight &ohgr;(n2) lower bound. this bound holds for any decision-tree algorithm, and not only for a comparison-based algorithm. the lower bound is proved by an exact characterization of the bitonic totally monotone matrices, whereas our new algorithms depend on techniques from parallel comparison algorithms.
revenue maximization when bidders have budgets. we study the problem of maximizing revenue for auctions with multiple units of a good where bidders have hard budget constraints, first considered in [2]. the revenue obtained by an auction is compared with the optimal omniscient auction had the auctioneer known the private information of all the bidders, as in competitive analysis [7]. we show that the revenue of the optimal omniscient auction that sells items at many different prices is within a factor of 2 of the optimal omniscient auction that sells all the items at a single price, implying that our results will carry over to multiple price auctions. we give the first auction for this problem, to the best of our knowledge, that is known to obtain a constant fraction of the optimal revenue when the bidder dominance (the ratio between the maximum contribution of a single bidder in the optimal solution and the revenue of that optimal solution) is large (as high as 1/2). our auction is also shown to remain truthful if canceled upon not meeting certain criteria. on the negative side, we show that no auction can achieve a guarantee of 1/2-&epsilon; the revenue of the optimal omniscient multi-price auction. finally, if the bidder dominance is known in advance and is less than 1/5.828, we give an auction mechanism that raises a large constant fraction of the optimal revenue when the bidder dominance is large and is asymptotically close to the optimal omniscient auction as the bidder dominance decreases. we discuss the relevance of these results for related applications.
a general approach to online network optimization problems. we study a wide range of online graph and network optimization problems, focusing on problems that arise in the study of connectivity and cuts in graphs. in a general online network design problem, we have a communication network known to the algorithm in advance. what is not known in advance are the bandwidth or cut demands between nodes in the network. our results include an o(log m log n) competitive randomized algorithm for the online non-metric facility location and for a generalization of the problem called themulticast problem. in the non-metric facility location m is the number of facilities and n is the number of clients. the competitive ratio is nearly tight. we also present ano(log2 n log k) competitive randomized algorithm for the on-line group steiner problem in trees and an o(log3 n log k)competitive randomized algorithm for the problem in general graphs, where n is the number of vertices in the graph and k is the number of groups. finally, we design a deterministic o(log3 n log log n) competitive algorithm for the online multi-cut problem. our algorithms are based on a unified framework for designing online algorithms for problems involving connectivity and cuts. we first present a general o(log m)-deterministic algorithm for generating fractional solution that satisfies the online connectivity or cut demands, where m is the number of edges in the graph.
dynamizing static algorithms, with applications to dynamic trees and history independence. we describe a machine model for automatically dynamizing static algorithms and apply it to history-independent data structures. static programs expressed in this model are dynamized automatically by keeping track of dependences between code and data in the form of a dynamic dependence graph. to study the performance of such automatically dynamized algorithms we present an analysis technique based on trace stability. as an example of the use of the model, we dynamize the parallel tree contraction algorithm of miller and reif to obtain a history-independent data structure for the dynamic trees problem of sleator and tarjan.
the set-associative cache performance of search trees. we consider the costs of access to data stored in search trees assuming that those memory accesses are managed with a cache. our cache memory model is two-level, has a small degree of set-associativity, and uses lru replacement, and we consider the number of cache misses that a set of accesses incurs. for standard tree access--searches and traversals---changing the degree of set-associativity has no effect on performance.to explain this, we develop general stochastic access models, an adaptation of the independent reference model (irm), and analyze the expected number of cache hits and misses incurred by these types of access. the models and analyses are accurate: we are able to exactly predict the cache performance of tree data structures. in addition, we prove why set-associativity is of little or no benefit for these types of memory access and give examples where direct-mapping performs better than set-associativity.
exponential bounds for dpll below the satisfiability threshold. for each k &le; 4, we give &tau;k > 0 such that a random k-cnf formula f with n variables and &lfloor;rkn&rfloor; clauses is satisfiable with high probability, but ordered-dll takes exponential time on f with uniformly positive probability. using results of [2], this can be strengthened to a high probability result for certain natural backtracking schemes and extended to many other dpll algorithms.
improved fast integer sorting in linear space. we present improved fast deterministic algorithm for integer sorting in linear space. our algorithm sorts n integers in linear space in &ogr;(n log log n log log log n) time. this improves the &ogr;(n(log log n)3/2) time bound given in [6]. when the n integers in {0,1,&hellip;, m - 1} to be sorted satisfying log m &gne;(log n)2+&isin;, 0 < &isin; < 1, the time complexity for sorting can be further reduced to &ogr;(n log log n). these results are obtained by applying signature sorting on our previous result[6].
on the number of rectangular partitions. how many ways can a rectangle be partitioned into smaller ones? we study two variants of this problem: when the partitions are constrained to lie on n given points (no two of which are corectilinear), and when there are no such constraints and all we require is that the number of (non-intersecting) segments is n. in the first case, when the order (permutation) of the points conforms with a certain property, the number of partitions is the (n + 1)st baxter number, b(n + 1); the number of permutations conforming with the property is the (n - 1)st schr&ouml;der number; and the number of guillotine partitions is the nth schr&ouml;der number. in the second case, it is known [22] that the number of partitions and the number of guillotine partitions correspond to the baxter and schr&ouml;der numbers, respectively. our contribution is a bijection between permutations and partitions. our results provide interesting and new geometric interpretations to both baxter and schr&ouml;der numbers and suggest insights regarding the intricacies of the interrelations.
ordinal embeddings of minimum relaxation: general properties, trees, and ultrametrics. we introduce a new notion of embedding, called minimum-relaxation ordinal embedding, parallel to the standard notion of minimum-distortion (metric) embedding. in an ordinal embedding, it is the relative order between pairs of distances, and not the distances themselves, that must be preserved as much as possible. the (multiplicative) relaxation of an ordinal embedding is the maximum ratio between two distances whose relative order is inverted by the embedding. we develop several worst-case bounds and approximation algorithms on ordinal embedding. in particular, we establish that ordinal embedding has many qualitative differences from metric embedding, and we capture the ordinal behavior of ultrametrics and shortest-path metrics of unweighted trees.
is the internet fractal? one of the main benefits of multicast communication is the overall reduction of network load. to quantify this reduction, when compared to traditional unicast, experimental studies by chuang and sirbu indicated the so called power law which asserts that the ratio r(n) of the average number of links in a multicast delivery tree connecting n sites to the average number of links in a unicast path is &theta;(n0.8). our goal is to explain theoretically this behavior. claiming that the essence of the phenomenon lies in the geometry of the internet and its modeling assumptions, we introduce the model of self-similar trees with similarity factor 0 &le; &theta; < 1. under this assumption, we analyze r(n) and prove that it is &theta;(n1-&theta;). we also discuss some experimental results of real networks that confirm the power law and show that these networks have the self similar profile. in particular, we find experimentally that the power law holds with &theta;exp &asymp; 0.12. our theoretical findings are established by analytical techniques of the precise analysis of algorithms such as mellin transform and complex asymptotics.
smaller explicit superconcentrators. we present an explicit construction of an infinite family of n-superconcentrators of density 44. the most economical previously known explicit graphs of this type have density around 60.
collecting correlated information from a sensor network. a fundamental problem in the study of sensor networks is collecting data to a central server from a set of k distributed sensor nodes. a considerable amount of recent research in this area attempts to reduce the number of bits sent by the nodes by taking advantage of correlations between the data items collected from different nodes. in this paper, we study this problem in the following model: let d be a probability distribution over k binary strings of length n. a sample &xmacr; is drawn from d and the k strings of &xmacr; are revealed to the nodes, one string per node. the goal is to inform the server of all k strings of &xmacr;. our primary objective is to minimize the total number of bits sent by the nodes, but we also seek to minimize both the bits sent by the server and the number of rounds required. this problem is a natural parallelization of the model introduced in [2], and is also well motivated by recent work on distributed source coding for sensor networks. our main result is a protocol that allows the server to correctly determine &xmacr;. in this protocol, the nodes send o(h(d) + k) bits in expectation, where h(d) is the binary entropy of d; this is asymptotically optimal. the server sends o(kn + h(d) log n) bits in expectation, and the number of rounds is o(1 + log[h(d)]) in expectation. we also demonstrate that if the server is allowed to produce an incorrect result with probability up to &delta;, then the expected number of bits sent by the server can be reduced to o(k log(nk/&delta;) + h(d) log n), without increasing the other measures of performance.
guessing secrets efficiently via list decoding. we consider the guessing secrets problem defined by chung et al. [2001]. this is a variant of the standard 20 questions game where the player has a set of k > 1 secrets from a universe of n possible secrets. the player is asked boolean questions about the secret. for each question, the player picks one of the k secrets adversarially, and answers according to this secret. we present an explicit set of o(log n) questions together with an efficient (i.e., poly(log n) time) algorithm to solve the guessing secrets problem for the case of 2 secrets. this answers the main algorithmic question left unanswered by chung et al. [2001]. the main techniques we use are small &epsis;-biased spaces and the notion of list decoding. we also establish bounds on the number of questions needed to solve the k-secrets game for k > 2, and discuss how list decoding can be used to get partial information about the secrets, specifically to find a small core of secrets that must intersect the actual set of k secrets.
beating the logarithmic lower bound: randomized preemptive disjoint paths and call control algorithms. we consider the maximum disjoint paths problem and its generalization, the call control problem, in the on-line setting. in the maximum disjoint paths problem, we are given a sequence of connection requests for some communication network. each request consists of a pair of nodes, that wish to communicate over a path in the network. the request has to be immediately connected or rejected, and the goal is to maximize the number of connected pairs, such that no two paths share an edge. in the call control problem, each request has an additional bandwidth specification, and the goal is to maximize the total bandwidth of the connected pairs (throughput), while satisfying the bandwidth constraints (assuming each edge has unit capacity). these classical problems are central in routing and admission control in high speed networks and in optical networks.we present the first known constant-competitive algorithms for both problems on the line. this settles an open problem of garay et al. and of leonardi. moreover, to the best of our knowledge, all previous algorithms for any of these problems, are ω(log n)-competitive, where n is the number of vertices in the network (and obviously noncompetitive for the continuous line). our algorithms are randomized and preemptive. our results should be contrasted with the ω(log n) lower bounds for deterministic preemptive algorithms of garay et al. and the ω(log n) lower bounds for randomized non-preemptive algorithms of lipton and tomkins and awerbuch et al. interestingly, nonconstant lower bounds were proved by canetti and irani for randomized preemptive algorithms for related problems but not for these exact problems.
testing triangle-freeness in general graphs. in this paper we consider the problem of testing whether a graph is triangle-free, and more generally, whether it is h-free, for a fixed subgraph h. the algorithm should accept graphs that are triangle-free and reject graphs that are far from being triangle-free in the sense that a constant fraction of the edges should be removed in order to obtain a triangle-free graph. the algorithm is allowed a small probability of error.this problem has been studied quite extensively in the past, but the focus was on dense graphs, that is, when d = &theta;(n), where d is the average degree in the graph and n is the number of vertices. here we study the complexity of the problem in general graphs, that is, for varying d.our main finding is a lower bound of &omega;(n1/3) on the necessary number of queries that holds for every d < n1-&nu;(n), where &nu;(n) = o(1). since when d = &theta;(n) the number of queries sufficient for testing has been known to be independent of n, we observe an abrupt, threshold-like behavior of the complexity of testing around n. this lower bound holds for testing h-freeness of every non-bipartite subgraph h.additionally we provide sub-linear upper bounds for testing triangle-freeness that are at most quadratic in the stated lower bounds, and we describe a transformation from certain one-sided error lower bounds for testing subgraph-freeness to two-sided error lower bounds.finally, in the course of our analysis we show that dense random cayley graphs behave like quasi-random graphs in the sense that relatively large subsets of vertices have the "correct" edge density. the result for subsets of this size cannot be obtained from the known spectral techniques that only supply such estimates for much larger subsets.
lower bounds for asymmetric communication channels and distributed source coding. we prove nearly tight lower bounds on the number of rounds of communication required by efficient protocols over asymmetric channels between a server (with high sending capacity) and one or more clients (with low sending capacity). this scenario captures the common asymmetric communication bandwidth between broadband internet providers and home users, as well as sensor networks where sensors (clients) have limited capacity because of the high power requirements for long-range transmissions. an efficient protocol in this setting communicates n bits from each of the k clients to the server, where the clients' bits are sampled from a joint distribution d that is known to the server but not the clients, with the clients sending only o(h(d) + k) bits total, where h(d) is the entropy of distribution d. in the single-client case, there are efficient protocols using o(1) rounds in expectation and o(lg n) rounds in the worst case. we prove that this is essentially best possible: with probability 1/2o(t lg t), any efficient protocol can be forced to use t rounds. in the multi-client case, there are efficient protocols using o(lg k) rounds in expectation. we prove that this is essentially best possible: with probability &omega;(1), any efficient protocol can be forced to use &omega;(lg k/ lg lg k) rounds. along the way, we develop new techniques of independent interest for proving lower bounds in communication complexity.
testing satisfiability. let &phi; be a set of general boolean functions on n variables, such that each function depends on exactly k variables, and each variable can take a value from [1,d]. we say that &phi; is &epsilon;-far from satisfiable, if one must remove at least &epsilon;nk functions in order to make the set of remaining functions satisfiable. our main result is that if &phi; is &epsilon;-far from satisfiable, then most of the induced sets of functions, on sets of variables of size c(k,d)&epsilon;2, are not satisfiable, where c(k,d) depends only on k and d. using the above claim, we obtain similar results for k-sat and k-naeq-sat.assume we relax the decision problem of whether an instance of one of the above mentioned problems is satisfiable or not, to the problem of deciding whether an instance is satisfiable or &epsilon;-far from satisfiable. while the above decision problems are np-hard, our result implies that we can solve their relaxed versions, that is, distinguishing between satisfiable and &epsilon;-far from satisfiable instances, in randomized constant time.from the above result we obtain as a special case, previous results of alon and krivelevich [3] and of czumaj and sohler [8], concerning testing of graphs and hypergraphs colorability. we also discuss the problem of testing whether a graph g can be d-colored, such that it does not contain any copy of a colored graph from a fixed, given set of colored graphs.
on the capacity of information networks. we consider information networks in the absence of interference and noise, and present an upper bound on the rate at which information can be transmitted using network coding. our upper bound is based on combining properties of entropy with a strong information inequality derived from the structure of the network.the undirected k-pairs conjecture states that the information capacity of an undirected network supporting k point-to-point connections is achievable by multicommodity flows. our techniques prove the conjecture for a non-trivial class of graphs, and also yield the first known proof of a gap between the sparsity of an undirected graph and its capacity. we believe that these techniques may be instrumental in resolving the conjecture completely. we demonstrate the importance of the undirected k-pairs conjecture by connecting it with a long-standing open question in input/output (i/o) complexity. we also show that proving the conjecture would provide the strongest known lower bound for computation in the oblivious cell-probe model and give a non-trivial lower bound for two-tape oblivious turing machines.finally, we conclude by considering the capacity of directed information networks. we construct a family of directed graphs whose capacity is much larger than the rate achievable using only multicommodity flows. the gap that we exhibit is linear in the number of vertices, edges, and commodities of the graph, which is asymptotically optimal.
a characterization of easily testable induced subgraphs. let h be a fixed graph on h vertices. we say that a graph g is induced h-free if it does not contain any induced copy of h. let g be a graph on n vertices and suppose that at least εn2 edges have to be added to or removed from it in order to make it induced h-free. it was shown in [5] that in this case g contains at least f(ε, h)nh induced copies of h, where 1/f(ε, h) is an extremely fast growing function in 1/ε, that is independent of n. as a consequence, it follows that for every h, testing induced h-freeness with one-sided error has query complexity independent of n. a natural question, raised by the first author in [1], is to decide for which graphs h the function 1/f(ε, h) can be bounded from above by a polynomial in 1/ε. an equivalent question is for which graphs h, can one design a one-sided error property tester for testing induced h-freeness, whose query complexity is polynomial in 1/ε. we settle this question almost completely by showing that, quite surprisingly, for any graph other than the paths of lengths 1,2 and 3, the cycle of length 4, and their complements, no such property tester exists. we further show that a similar result also applies to the case of directed graphs, thus answering a question raised by the authors in [9]. we finally show that the same results hold even in the case of two-sided error property testers. the proofs combine combinatorial, graph theoretic and probabilistic arguments with results from additive number theory.
pricing multicasting in more practical network models. the problem of designing efficient algorithms for sharing the cost of multicasting has recently seen considerable attention. in this paper, we examine the effect on the complexity of pricing when two practical considerations are incorporated into the network model. in particular, we study a model where the session is offered at a number of different rates of transmission, and where there is a cost for enabling multicasting at each node of the network. we consider two techniques that have been used in practice to provide multiple rates: using a layered transmission scheme (called the layered paradigm) and using different multicast groups for each possible rate (called the split session paradigm). we demonstrate that the difference between these two paradigms has a significant impact on the complexity of pricing multicasting.for the layered paradigm, we provide a distributed algorithm for computing pricing efficiently in terms of local computation and message complexity. for the split session paradigm, on the other hand, we demonstrate that this problem can be solved in polynomial time if the number of possible rates is fixed, but if the number of rates is part of the input, then the problem becomes np-hard even to approximate. we also examine the effect of delivering the transmissions for the various rates from different locations within the network. we show that in this case, the pricing problem becomes np-hard for the split session paradigm even for a fixed constant number of possible rates, but if layering is used, then it can be solved in polynomial time by formulating the problem as a totally unimodular integer program.
linear equations, arithmetic progressions and hypergraph property testing. for a fixed k-uniform hypergraph d (k-graph for short, k &ge; 3), we say that a k-graph h satisfies property pd (resp. p*d) if it contains no copy (resp. induced copy) of d. our goal in this paper is to classify the k-graphs d for which there are property-testers for testing pd and p*d whose query complexity is polynomial in 1/&epsilon;. for such k-graphs, we say that pd (or p*d) is easily testable.for p*d, we prove that aside from a single 3-graph, p*d is easily testable if and only if d is a single k-edge. for large k, we obtain stronger lower bounds than those obtained for the general case on the query complexity of testing p*d for any d other than the single k-edge. these bounds are proved by applying a more sophisticated technique than the basic one that works for all k. these results extend and improve previous results about graphs [5] and k-graphs [18].for pd, we show that for any k-partite k-graph d, pd, is easily testable, by giving an efficient one-sided error-property tester, which improves the one obtained by [18]. we further prove a nearly matching lower bound on the query complexity of such a property-tester. finally, we give a sufficient condition for inferring that pd is not easily testable. though our results do not supply a complete characterization of the k-graphs for which pd is easily testable, they are a natural extension of the previous results about graphs [1].our proofs combine results and arguments from additive number theory, linear algebra and extremal hypergraph theory. we also develop new techniques, which are of independent interest. the first is a construction of a dense set of integers, which does not contain a subset that satisfies a certain set of linear equations. the second is an algebraic construction of certain extremal hypergraphs. we demonstrate the applicability of this last construction by resolving several cases of an open problem raised by brown, erd&ouml;s and s&oacute;s in 1973. these two techniques have already been applied in two recent subsequent papers [6], [27].
constructing worst case instances for semidefinite programming based approximation algorithms. semidefinite programming based approximation algorithms, such as the goemans and williamson approximation algorithm for the max cut problem, are usually shown to have certain performance guarantees using local ratio techniques. are the bounds obtained in this way tight? this problem was considered before by karloff and by alon and sudakov. here we further extend their results and show, for the first time, that the local analyses of the goemans and williamson max cut algorithm, as well as its extension by zwick, are tight for every possible relative size of the maximum cut. we also obtain similar results for several related problems. our approach is quite general and could possibly be applied to some additional problems and algorithms.
efficient algorithms for bichromatic separability. a closed solid body separates one point set from another if it contains the former and the closure of its complement contains the latter. we present a near-linear algorithm for deciding whether two sets of n points in 3-space can be separated by a prism, near-quadratic algorithms for separating by a slab or a wedge, and a near-cubic algorithm for separating by a double-wedge. the latter three algorithms improve the previous best known results by an order of magnitude, while the prism separability algorithm constitutes an improvement of two orders of magnitude.
labeling schemes for small distances in trees. we consider labeling schemes for trees, supporting various relationships between nodes at small distance. for instance, we show that given a tree t and an integer k we can assign labels to each node of t such that given the label of two nodes we can decide, from these two labels alone, if the distance between v and w is at most k and, if so, compute it. for trees with n nodes and $k\geq 2$, we give a lower bound on the maximum label length of $\log n + \omega(\log \log n)$ bits, and for constant k, we give an upper bound of log n + o(log log n). bounds for ancestor, sibling, connectivity, and bi- and triconnectivity labeling schemes are also presented.
an optimal dynamic interval stabbing-max data structure? in this paper we consider the dynamic stabbing-max problem, that is, the problem of dynamically maintaining a set s of n axis-parallel hyper-rectangles in rd, where each rectangle s &isin; s has a weight w(s) &isin; r, so that the rectangle with the maximum weight containing a query point can be determined efficiently. we develop a linear-size structure for the one-dimensional version of the problem, the interval stabbing-max problem, that answers queries in worst-case o(log n) time and supports updates in amortized o(log n) time. our structure works in the pointer-machine model of computation and utilizes many ingredients from recently developed external memory structures. using standard techniques, our one-dimensional structure can be extended to higher dimensions, while paying a logarithmic factor in space, update time, and query time per dimension. furthermore, our structure can easily be adapted to external memory, where we obtain a linear-size structure that answers queries and supports updates in o(logb n) i/os, where b is the disk block size.
improved labeling scheme for ancestor queries. we present a labeling scheme for rooted trees that supports ancestor queries. given a tree, the scheme assigns to each node a label which is a binary string. given the labels of any two nodes u and v, it can in constant time be determined whether u is ancestor to v alone from these labels. for trees of size n our scheme assigns labels of size bounded by log n + o(&radic;log n) bits to each node. this improves a recent result of abiteboul, kaplan and milo at soda'01, where a labeling scheme with labels of size 3/2log n + o(log log n) was presented. the problem is among other things motivated in connection with efficient representation of information for xml-based search engines for the internet.
matching planar maps. the subject of this paper are algorithms for measuring the similarity of patterns of line segments in the plane, a standard problem in, e.g., computer vision, geographic information systems, etc. more precisely, we define feasible distance measures that reflect how close a given pattern h is to some part of a larger pattern g. these distance measures are generalizations of the well-known fréchet distance for curves. we first give an efficient algorithm for the case that h is a polygonal curve and g is a geometric graph. then, slightly relaxing the definition of distance measure, we give an algorithm for the general case where both, h and g, are geometric graphs.
an efficient algorithm for the configuration problem of dominance graphs. dominance constraints are logical tree descriptions originating from automata theory that have multiple applications in computational linguistics. the satisfiability problem of dominance constraints is np-complete. in most applications, however, only normal dominance constraints are used. the satisfiability problem of normal dominance constraints can be reduced in linear time to the configuration problem of dominance graphs, as shown recently. in this paper, we give a polynomial time algorithm testing configurability of dominance graphs (and thus satisfiability of normal dominance constraints). previous to our work no polynomial time algorithms were known.
point containment in the integer hull of a polyhedron. we show that the point containment problem in the integer hull of a polyhedron, which is defined by m inequalities, with coefficients of at most &phis; bits can be solved in time o(m + &phis;) in the two-dimensional case and in expected time o(m + &phis;2 log m) in any fixed dimension. this improves on the algorithm which is based on the equivalence of separation and optimization in the general case and on a direct algorithm (soda 97) for the two-dimensional case.
computing the writhing number of a polygonal knot. the writhing number measures the global geometry of a closed space curve or knot. we show that this measure is related to the average winding number of its gauss map. using this relationship, we give an algorithm for computing the writhing number for a polygonal knot with n edges in time roughly proportional to n1.6. we also implement a different, simple algorithm and provide experimental evidence for its practical efficiency.
maintaining approximate extent measures of moving points. we present approximation algorithms for maintaining various descriptors of the extent of moving points in rd. we first describe a data structure for maintaining the smallest orthogonal rectangle containing the point set. we then use this data structure to maintain the approximate diameter, smallest enclosing disk, width, and smallest area or perimeter bounding rectangle of a set of moving points in r2 so that the number of events is only a constant. this contrasts with &ohgr;(n2) events that data structures for the maintenance of those exact properties have to handle.
computing steiner minimum trees in hamming metric. computing steiner minimum trees in hamming metric is a well studied problem that has applications in several fields of science such as computational linguistics and computational biology. among all methods for finding such trees, algorithms using variations of a branch and bound method developed by penny and hendy have been the fastest for more than 20 years. in this paper we describe a new pruning approach that is superior to previous methods and its implementation.
robust shape fitting via peeling and grating coresets. let p be a set of n points in &#x211d; d . a subset $\mathcal {s}$ of p is called a (k,&#x03b5;)-kernel if for every direction, the directional width of $\mathcal {s}$ &#x03b5;-approximates that of p, when k &#x201c;outliers&#x201d; can be ignored in that direction. we show that a (k,&#x03b5;)-kernel of p of size o(k/&#x03b5;(d&#x2212;1)/2) can be computed in time o(n+k2/&#x03b5;d&#x2212;1). the new algorithm works by repeatedly &#x201c;peeling&#x201d; away (0,&#x03b5;)-kernels from the point set. we also present a simple &#x03b5;-approximation algorithm for fitting various shapes through a set of points with at most k outliers. the algorithm is incremental and works by repeatedly &#x201c;grating&#x201d; critical points into a working set, till the working set provides the required approximation. we prove that the size of the working set is independent of n, and thus results in a simple and practical, near-linear &#x03b5;-approximation algorithm for shape fitting with outliers in low dimensions. we demonstrate the practicality of our algorithms by showing their empirical performance on various inputs and problems.
relative neighborhood graphs in three dimensions. the relative neighborhood graph (rng) of a set s of n points in r is a graph (s, e), where (p, q) &egr; e if and only if there is no point z &egr; s such that max {d(p, z), d(q,z)} < d(p,q). we show that in r , rng(s) has o(n4/3) edges. we present a randomized algorithm that constructs rng(s) in expected time o(n3/2+&egr;) assuming that the points of s are in general position. if the points of s are arbitrary, the expected running time is o(n7/4+&egr;). these algorithms can be made deterministic without affecting their asymptotic running time.
computing maximally separated sets in the plane and independent sets in the intersection graph of unit disks. let s be a set of n points in r2. given an integer 1 &le; k &le; n, we wish to find a maximally separated subset i &sube; s of size k; this is a subset for which the minimum among the (k2) pairwise distances between its points is as large as possible. the decision problem associated with this problem is to determine whether there exists i &sube; s, |i| = k, so that all (k2) pairwise distances in i are at least 2, say. this problem can also be formulated in terms of disk-intersection graphs: let d be the set of unit disks centered at the points of s. the disk-intersection graph g of d connects pairs of disks by an edge if they have nonempty intersection. i is then the set of centers of disks that form an independent set in the graph g. this problem is known to be np-complete if k is part of the input.in this paper we first present a linear-time approximation algorithm for any constant k. next we give o(n4/3polylog(n)) exact algorithms for the cases k = 3 and k = 4. we also present a simpler no(&radic;k)-time algorithm (as compared with the recent algorithm in [5]) for arbitrary values of k.
approximation algorithms for projective clustering. we consider the following two instances of the projective clustering problem: given a set s of n points in rd and an integer k > 0, cover s by k slabs (respectively d-cylinders) so that the maximum width of a slab (respectively the maximum diameter of a d-cylinder) is minimized. let w* be the smallest value so that s can be covered by k slabs (respectively d-cylinders), each of width (respectively diameter) at most w*. this paper contains three main results: (i) for d = 2, we present a randomized algorithm that computes o(k log k) strips of width at most w* that cover s. its expected running time is o(nk2log4n) if k2 log k ≤ n; for larger values of k, the expected running time is o(n2/3k8/3log14/3n). (ii) for d = 3, a cover of s by o(k log k) slabs of width at most w* can be computed in expected time o(n3/2k9/4polygon(n)).(iii) we compute a cover of s ⊂ rd by o(dk log k) d-cylinders of diameter at most 8w* in expected time o(dnk3 log4 n). we also present a few extensions of this result.
coins make quantum walks faster. we show how to search n items arranged on a &radic;n &times; &radic;n grid in time o(&radic;n log n), using a discrete time quantum walk. this result for the first time exhibits a significant difference between discrete time and continuous time walks without coin degrees of freedom. since it has been shown recently that such a continuous time walk needs time &omega;(n) to perform the same task. our result improves on a previous bound for quantum local search by aaronson and ambainis. we generalize our result to 3 and more dimensions where the walk yields the optimal performance of o(&radic;n) and give several extensions of quantum walk search algorithms and generic expressions for its performance for general graphs. the coin-flip operation needs to be chosen judiciously: we show that another "natural" choice of coin gives a walk that takes &omega;(n) steps. we also show that in 2 dimensions it is sufficient to have a two-dimensional coin-space to achieve the time o(&radic;n log n).
finding a line transversal of axial objects in three dimensions. an axial object in e3 is a box or rectangle, all of whose edges are parallel to the coordinate axes. a line transveral of a set of axial objects is a line that intersects every object. we present an algorithm which finds a line transversal, if one exists, in expected linear time. in the process, we generalize a randomized linear programming algorithm, and prove that the set of line transversals of axial objects has a constant number of connected components.
the hunting of the bump: on maximizing statistical discrepancy. anomaly detection has important applications in biosurveilance and environmental monitoring. when comparing measured data to data drawn from a baseline distribution, merely, finding clusters in the measured data may not actually represent true anomalies. these clusters may likely be the clusters of the baseline distribution. hence, a discrepancy function is often used to examine how different measured data is to baseline data within a region. an anomalous region is thus defined to be one with high discrepancy.in this paper, we present algorithms for maximizing statistical discrepancy functions over the space of axis-parallel rectangles. we give provable approximation guarantees, both additive and relative, and our methods apply to any convex discrepancy function. our algorithms work by connecting statistical discrepancy to combinatorial discrepancy; roughly speaking, we show that in order to maximize a convex discrepancy function over a class of shapes, one needs only maximize a linear discrepancy function over the same set of shapes.we derive general discrepancy functions for data generated from a one- parameter exponential family. this generalizes the widely-used kulldorff scan statistic for data from a poisson distribution. we present an algorithm running in o(1/&epsilon; n2 log2n) that computes the maximum discrepancy rectangle to within additive error &epsilon;, for the kulldorff scan statistic. similar results hold for relative error and for discrepancy functions for data coming from gaussian, bernoulli, and gamma distributions. prior to our work, the best known algorithms were exact and ran in time o(n4).
pseudo-line arrangements: duality, algorithms, and applications. a finite collection of x-monotone unbounded jordan curves in the plane is called a family of pseudo-lines if every pair of curves intersect in at most one point, and the two curves cross each other there. let l be such a collection of n pseudo-lines, and let p be a set of m points in $\reals^2$. extending a result of goodman [discrete math., 32 (1980), pp. 27--35], we define a duality transform that maps l to a set l* of points in $\reals^2$ and p to a set p* of (x-monotone) pseudo-lines in $\reals^2$, so that the incidence and the "above-below" relations between the points and the pseudo-lines are preserved. we present an efficient algorithm for computing the dual arrangement {\eus a}$(p^*)$ under an appropriate model of computation. we also present a dynamic data structure for reporting, in $o(m^\eps + k)$ time, all k points of p that lie below a query arc, which is either a circular arc or a portion of the graph of a polynomial of fixed degree. this result is needed for computing the dual arrangement for certain classes of pseudo-lines arising in several applications, but is also interesting in its own right. we present a few applications of our dual arrangement algorithm, such as computing incidences between points and pseudo-lines and computing a subset of faces in a pseudo-line arrangement.next, we present an efficient algorithm for cutting a set of circles into arcs so that every pair of arcs intersect in at most one point, i.e., the resulting arcs constitute a collection of pseudo-segments. by combining this algorithm with our algorithm for computing the dual arrangement of pseudo-lines, we obtain efficient algorithms for several problems involving arrangements of circles or circular arcs, such as reporting or counting incidences between points and circles and computing a set of marked faces in arrangements of circles.
pattern matching with address errors: rearrangement distances. historically, approximate pattern matching has mainly focused at coping with errors in the data, while the order of the text/pattern was assumed to be more or less correct. in this paper we consider a class of pattern matching problems where the content is assumed to be correct, while the locations may have shifted/changed. we formally define a broad class of problems of this type, capturing situations in which the pattern is obtained from the text by a sequence of rearrangements. we consider several natural rearrangement schemes, including the analogues of the @?"1 and @?"2 distances, as well as two distances based on interchanges. for these, we present efficient algorithms to solve the resulting string matching problems.
two-dimensional periodicity and its applications. string matching is rich with a variety of algorithmic tools. in contrast, multidimensional matching has a rather sparse set of techniques. this paper presents a new algorithmic technique for two-dimensional matching, that of periodicity analysis. periodicity in strings has been used to solve string matching problems. the success of these algorithms suggests that periodicity can be as important a tool in multidimensional matching. however, multidimensional periodicity is not as simple as it is in strings and was not formally studied or used in pattern matching. this paper's main contribution is defining and analysing two-dimensional periodicity in rectangular arrays. in addition, we introduce a new pattern matching paradigm - compressed matching. a text array t and a pattern array p are given in compressed forms c(t) and c(p). we seek all appearances of p in t, without decompressing t. by using periodicity analysis, we show that for the two-dimensional run-length compression there is a o(|c(t)|log|p|+|p|), or almost optimal algorithm that can achieve a search time that is sublinear in the size of the text |t|.
surface approximation and geometric partitions. motivated by applications in computer graphics, visualization, and scientific computation, we study the computational complexity of the following problem: given a set s of n points sampled from a bivariate function f(x,y) and an input parameter $\eps > 0$, compute a piecewise-linear function $\sigma(x,y)$ of minimum complexity (that is, an xy-monotone polyhedral surface, with a minimum number of vertices, edges, or faces) such that $| \sigma(x_p, y_p) \; - \; z_p | \:\:\leq\:\: \eps$ for all $(x_p, y_p, z_p) \in s$. we give hardness evidence for this problem, by showing that a closely related problem is np-hard. the main result of our paper is a polynomial-time approximation algorithm that computes a piecewise-linear surface of size o(ko log ko), where ko is the complexity of an optimal surface satisfying the constraints of the problem.the technique developed in our paper is more general and applies to several other problems that deal with partitioning of points (or other objects) subject to certain geometric constraints. for instance, we get the same approximation bound for the following problem arising in machine learning: given n "red" and m "blue" points in the plane, find a minimum number of pairwise disjoint triangles such that each blue point is covered by some triangle and no red point lies in any of the triangles.
applications of parametric searching in geometric optimization. we present several applications in computational geometry of megiddo's parametric searching technique. these applications include; (1) finding the minimum hausdorff distance in the euclidean metric between two polygonal regions under translation; (2) computing the biggest line segment that can be placed inside a simple polygon; (3) computing the smallest width annulus that can contain a given set of points in the plane; (4) solving the 1-segment center problem&mdash;given a set of points in the plane, find a placement for a given line segment (under translation and rotation) which minimizes the largest distance from the segment to the given points; (5) given a set of n points in 3-space, finding the largest radius r such that if we place a ball of radius r around each point, no segment connecting a pair of points is intersected by a third ball. besides obtaining efficient solutions to all these problems (which, in every case, either improve considerably previous solutions or are the first non-trivial solutions to these problems), our goal is to demonstrate the versatility of the parametric searching technique.
separable attributes: a technique for solving the sub matrices character count problem. the subsequence character count problem has as its input an array s = s1, &iexcl;&shy;, sn of symbols over alphabet &brvbar;&sup2; and a natural number m. its output is: for every i, i = 1, &iexcl;&shy;, n - m + 1, the number of different alphabet symbols occurring in the subsequence si, si+1, &iexcl;&shy;, si+m-1. the subsequence character count problem is a natural problem that has many uses. it can be solved in linear time for fixed finite alphabets and in time o(n log m) for infinite alphabets. in [1] the problem was used to solve the parameterized matching problem. the character count problem can be generalized to two dimensions and becomes the submatrix character count problem. its input is an n x n matrix t over alphabet &brvbar;&sup2; and a natural number m. its output is: for every i,j, i,j = 1, &iexcl;&shy;, n - m + 1, the number of different alphabet symbols occurring in the submatrix t[i + k,j + &ell;], k = 0, &iexcl;&shy;, m - 1;&ell; = 0, &iexcl;&shy;, m - 1. this problem was motivated by parameterized matching in two dimensions which is a good model for seeking a pattern in an image with a change of color map. the number of different colors in a subarea of an image is considered a "signature". there are many image processing tools that use this measure (see e.g. [5]). the straightforward one dimensional solution slides a window along the text adding an element and deleting an element at every step. the problem with two dimensions is that at every move of the window there are m elements added and m deleted. in this paper we present an alternate solution that generalizes to two dimensions. we achieve a o(n2) time solution to the submatrix character count problem over finite fixed alphabet and a o(n2 log m) solution over an infinite alphabet. the submatrix character count problem is a special case of the color range query problem, where one needs to preprocess a two dimensional nxn array t of symbols over alphabet &brvbar;&sup2; - the colors. subsequently we are interested in answers to queries of the type: given intervals [i1,j1] and [i2,j2], i1,i2,j1,j 2 &brvbar;&aring; {1, &iexcl;&shy;, n} and i1 &iexcl;&uuml; j1, i2 &iexcl;&uuml; j2 give the number of different alphabet symbols (colors) occurring in the submatrix t[k,&ell;], k = i1, &iexcl;&shy;,j1, &ell; = i2,&iexcl;&shy;,j2. jonardan and lopez [6] showed that with a o(n2 log2 n) preprocessing one can answer queries in time o(log2 n). this means that the submatrices character count problem can be solved in time o(n2 log2 n) by preprocessing and then querying, for every location, the m x m submatrix starting at that location. we are not aware of a faster direct approach for solving the submatrix character count problem. however, problems with a similar flavor, where the desired calculation is a convolution, are solved in electrical engineering by a method called separable convolutions or separable filters [4]. a similar notion was used by bird [3] and baker [2] to solve the two dimensional pattern matching problem. the contributions of this paper are two-fold. first, we generalize the notion of separable convolutions to separable attributes. we believe it is important to keep this method in mind as an element of the basic algorithmic toolkit. it has proven useful in the past and, we think, will prove useful for solving various two-dimensional problems in the future. secondly, we use the separable attributes method for providing the fastest algorithm yet for the submatrices character count problem. a full version of this paper can be found at http://www.cs.biu.ac.il/~amir/postscripts/sep.ps.
lower bound for sparse euclidean spanners. given a one-dimensional graph g such that any two consecutive nodes are unit distance away, and such that the minimum number of links between any two nodes (the diameter of g) is o(log n), we prove an &omega;(n log n/log log n) lower bound on the sum of lengths of all the edges (i.e., the weight of g). the problem is a variant of the widely studied partial sum problem. this in turn provides a lower bound on euclidean spanner graphs with small diameter and low weight, showing that the upper bound from [1] is almost tight.
self-improving algorithms. we investigate ways in which an algorithm can improve its expected performance by fine-tuning itself automatically with respect to an arbitrary, unknown input distribution. we give such self-improving algorithms for sorting and clustering. the highlights of this work: (i) a sorting algorithm with optimal expected limiting running time; and (ii) a k-median algorithm over the hamming cube with linear expected limiting running time. in all cases, the algorithm begins with a learning phase during which it adjusts itself to the input distribution (typically in a logarithmic number of rounds), followed by a stationary regime in which the algorithm settles to its optimized incarnation.
optimal parallel selection. we present an optimal parallel selection algorithm on the erew pram. this algorithm runs in o(log n) time with n/log n processors. this complexity matches the known lower bound for parallel selection on the erew pram model. we therefore close this problem which has been open for more than a decade.
overlap matching. we propose a new paradigm for string matching, namely structural matching. in structural matching, the text and pattern contents are not important. rather, some areas in the text and patterns are singled out, say intervals. a &ldquo;match&rdquo; is a text location where a specified relation between the text and pattern areas is satisfied. in particular we define the structural matching problem of overlap (parity) matching. we seek the text locations where all overlaps of the given pattern and text intervals have even length. we show that this problem can be solved in time &ogr;(n log m), where the text length is n and the pattern length is m. as an application of overlap matching, we show how to reduce the string matching with swaps problem to the overlap matching problem. the string matching with swaps problem is the problem of string matching in the presence of local swaps. the best known deterministic upper bound for this problem was &ogr;(nm1/3 log m log &sgr;) for a general alphabet &sum;, where &sgr; = min(m, &brvbar;&sum;&brvbar;). our reduction provides a solution to the pattern matching with swaps problem in time &ogr;(n log m log &sgr;).
bipartite roots of graphs. graph h is a root of graph g if there exists a natural number k such that xy &isin; e(g) &harr; dh(x, y) &le; k where dh(x, y) is the length of a shortest path in h from x to y. in such a case, h is a k-th root of g and we write g = hk and call g the k-th power of h. motwani and sudan proved that it is np-complete to recognize squares of graphs and believed it is also np-complete to recognize squares of bipartite graphs. in this paper, we show, rather surprisingly, that squares of bipartite graphs can be recognized in polynomial time. also, we show that counting the number of different bipartite square roots of a graph can be done in polynomial time although this number could be exponential in the size of the input graph. furthermore, we can generate all bipartite roots of a graph g in time o(max{&delta;(g) &middot; m, r(g)}) where &delta;(g) is the maximum degree of g, m is the time complexity to do matrix multiplication, and r(g) is the number of different bipartite square roots of g. by using the tools developed, we are able to give a new and simpler linear time algorithm to recognize squares of trees and a new algorithmic proof that tree square roots, when they exist, are unique up to isomorphism. finally, we prove the np-completeness of recognition of cubes of bipartite graphs.
the angular-metric traveling salesman problem. motivated by applications in robotics, we formulate the problem of minimizing the total angle cost of a tsp tour for a set of points in euclidean space, where the angle cost of a tour is the sum of the direction changes at the points. we establish the np-hardness of both this problem and its relaxation to the cycle cover problem. we then consider the issue of designing approximation algorithms for these problems and show that both problems can be approximated to within a ratio of o(log n) in polynomial time. we also consider the problem of simultaneously approximating both the angle and the length measure for a tsp tour. in studying the resulting tradeoff, we choose to focus on the sum of the two performance ratios and provide tight bounds on the sum. finally, we consider the extremal value of the angle measure and obtain essentially tight bounds for it. in this paper we restrict our attention to the planar setting, but all our results are easily extended to higher dimensions.
complexities for generalized models of self-assembly. in this paper, we extend rothemund and winfree's examination of the tile complexity of tile self-assembly [6]. they provided a lower bound of &omega;(log n/log log n) on the tile complexity of assembling an n &times; n square for almost all n. adleman et al. [1] gave a construction which achieves this bound. we consider whether the tile complexity for self-assembly can be reduced through several natural generalizations of the model. one of our results is a tile set of size o(&radic;log n) which assembles an n &times; n square in a model which allows flexible glue strength between non-equal glues (this was independently discovered in [3]). this result is matched by a lower bound dictated by kolmogorov complexity. for three other generalizations, we show that the &omega;(log n/log log n) lower bound applies to n &times; n squares. at the same time, we demonstrate that there are some other shapes for which these generalizations allow reduced tile sets. specifically, for thin rectangles with length n and width k, we provide a tighter lower bound of &omega;(n(1/k)/k) for the standard model, yet we also give a construction which achieves o(log n/log log n) complexity in a model in which the temperature of the tile system is adjusted during assembly. we also investigate the problem of verifying whether a given tile system uniquely assembles into a given shape, and show that this problem is np-hard.
faster algorithms for string matching with mismatches. the string matching with mismatches problem is that of finding the number of mismatches between a pattern p of length m and every length m substring of the text t. currently, the fastest algorithms for this problem are the following. the galil-giancarlo algorithm finds all locations where the pattern has at most k errors (where k is part of the input) in time o(nk). the abrahamson algorithm finds the number of mismatches at every location in time o(n√ m log m). we present an algorithm that is faster than both. our algorithm finds all locations where the pattern has at most k errors in time o(n√k log k). we also show an algorithm that solves the above problem in time o((n + (nk3)/m) log k).
knapsack auctions. we consider a game theoretic knapsack problem that has application to auctions for selling advertisements on internet search engines. consider n agents each wishing to place an object in the knapsack. each agent has a private valuation for having their object in the knapsack and each object has a publicly known size. for this setting, we consider the design of auctions in which agents have an incentive to truthfully reveal their private valuations. following the framework of goldberg et al. [10], we look to design an auction that obtains a constant fraction of the profit obtainable by a natural optimal pricing algorithm that knows the agents' valuations and object sizes.we give an auction that obtains a constant factor approximation in the non-trivial special case where the knapsack has unlimited capacity. we then reduce the limited capacity version of the problem to the unlimited capacity version via an approximately efficient auction (i.e., one that maximizes the social welfare). this reduction follows from generalizable principles.
inplace run-length 2d compressed search. the recent explosion in the amount of stored data has necessitated the storage and transmission of data in compressed form. the need to quickly access this data has given rise to a new paradigm in searching, that of compressed matching (proc. data compression conf, snow bird, ut, 1992, pp. 279-288; proc. 8th annu. symp. on combinatorial pattern matching (cpm 97), lecture notes in computer science, vol. 1264, springer, berlin, 1997, pp. 40-51; proc. 7th annu. symp. on combinatorial pattern matching (cpm 96), lecture notes in computer science, vol. 1075, springer, berlin, 1996, pp. 39-49). the goal of the compressed pattern matching problem is to find a pattern in a text without decompressing the text.the criterion of extra space is very relevant to compressed searching. an algorithm is called inplace if the amount of extra space used is proportional to the input size of the pattern. in this paper we present a 2d compressed matching algorithm that is inplace. let compressed(t) and compressed(p) denote the compressed text and pattern, respectively. the algorithm presented in this paper runs in time o(|compressed(t)| + |p|log σ) where σ is min(|p|,|σ), and σ is the alphabet, for all patterns that have no trivial rows (rows consisting of a single repeating symbol). the amount of space used is o(|compressed(p)|). the compression used is the 2d run-length compression, used in fax transmission.
optimal parallel sorting in multi-level storage. we adapt the sharesort algorithm of cypher and plaxton to run on various parallel models of multi-level storage, and analyze its resulting performance. sharesort was originally defined in the context of sorting n records on an n-processor hypercubic network. in that context, it is not known whether sharesort is asymptotically optimal. nonetheless, we find that sharesort achieves optimal time bounds for parallel sorting in multi-level storage, under a variety of models that have been defined in the literature.
inplace 2d matching in compressed images. the compressed matching problem is the problem of finding all occurrences of a pattern in a compressed text. in this paper we discuss the 2-dimensional compressed matching problem in lempel-ziv compressed images. given a pattern p of (uncompressed) size m × m, and a text t of (uncompressed) size n × n, both in 2d-lz compressed form, our algorithm finds all occurrences of p in t. the algorithm is strongly inplace, that is, the amount of extra space used is proportional to the best possible compression of a pattern of size m2. the best compression that the 2d-lz technique can obtain for a file of size m2 is o(m). the time for performing the search is o(n2) and the preprocessing time is o(m3). our algorithm is general in the sense that it can be used for any 2d compression which can be sequentially decompressed in small space.
fault-tolerant gathering algorithms for autonomous mobile robots. this paper studies fault tolerant algorithms for the problem of gathering n autonomous mobile robots. a gathering algorithm, executed independently by each robot, must ensure that all robots are gathered at one point within finite time. it is first observed that most existing algorithms fail to operate correctly in a setting allowing crash failures. subsequently, an algorithm tolerant against one crash-faulty robot in a system of three or more robots is presented. it is then shown that in an asynchronous environment it is impossible to perform a successful gathering in a 3-robot system with one byzantine failure. finally, in a fully synchronous system, an algorithm is provided for gathering n &ge; 3 robots with at most a single faulty robot, and a more general gathering algorithm is given in an n-robot system with up to f faults, where n &ge; 3 f +1.
coloring powers of planar graphs. we give nontrivial bounds for the inductiveness or degeneracy of power graphs gk of a planar graph g. this implies bounds for the chromatic number as well, since the inductiveness naturally relates to a greedy algorithm for vertex-coloring the given graph. the inductiveness moreover yields bounds for the choosability of the graph. we show that the inductiveness of a square of a planar graph g is at most $\lceil 9\delta /5 \rceil$, for the maximum degree $\delta$ sufficiently large, and that it is sharp. in general, we show for a fixed integer $k\geq1$ the inductiveness, the chromatic number, and the choosability of gk to be $o(\delta^{\lfloor k/2 \rfloor})$, which is tight.
on colorings of squares of outerplanar graphs. we investigate the clique number, the chromatic number and the inductiveness (or the degeneracy) of the square g2 of an outerplanar graph g, and bound as a function of the maximum degree &delta; of g. our main result is a tight bound of &delta; for the inductiveness of the square of any outerplanar graph g, when &delta; &ge; &tau;. this implies that a greedy algorithm yields an optimal coloring of such square graphs, and leads to an exact linear time algorithm that holds for any &delta;. we then derive optimal upper bounds on the three parameters for outerplanar graphs of smaller degree &delta; < &tau;, and in the case of chordal outerplanar graphs, classify exactly which graphs have parameters exceeding the absolute minimum. a co-product of the study is a characterization of all strongly simplicial elimination orderings of an arbitrary power of a tree.
random lifts of graphs. we describe here a simple probabilistic model for graphs that are lifts of a fixed base graph g, i.e., those graphs from which there is a covering man onto g. our aim is to investigate the properties of typical graphs in this class. in particular, we show that almost every lift of g is &dgr;(g)-connected where &dgr;(g) is the minimal degree of g. we calculate the typical edge expansion of lifts of the bouquet bd and
counting networks with arbitrary fan-out. it is shown that an acyclic smoothing network (and hence counting network) with fan-out n cannot be constructed from balancers of fan-out b1,..., bk, if there exists a prime factor p of n, such that p does not divide bi, for all i, 1 ≤ i ≤ k. this holds regardless of the depth, fan-in or size of the network, as long as they are finite. on the positive side, a simple construction of cyclic counting networks with fan-out n, for arbitrary n, is presented. an acyclic counting network with fan-in and fan-out p2k, for any integer k ≥ 0, is constructed out of 2-balancers and p-balancers.
a computational study of external-memory bfs algorithms. breadth first search (bfs) traversal is an archetype for many important graph problems. however, computing a bfs level decomposition for massive graphs was considered nonviable so far, because of the large number of i/os it incurs. this paper presents the first experimental evaluation of recent external-memory bfs algorithms for general graphs. with our stxxl based implementations exploiting pipelining and disk-parallelism, we were able to compute the bfs level decomposition of a web-crawl based graph of around 130 million nodes and 1.4 billion edges in less than 4 hours using single disk and 2.3 hours using 4 disks. we demonstrate that some rather simple external-memory algorithms perform significantly better (minutes as compared to hours) than internal-memory bfs, even if more than half of the input resides internally.
on distance scales, embeddings, and efficient relaxations of the cut cone. a central open problem in the field of finite metric spaces is to find an efficient relaxation of the cut cone---the collection of positive linear combinations of cut pseudo-metrics on a finite set. in particular, it has been asked how well squared-euclidean metrics (the so-called metrics of "negative type") embed into l1, and it is known that the answer to this question coincides with the integrality gap of a folklore semi-definite relaxation for computing the sparsest cut of a graph.bourgain's classical embedding theorem implies that any n-point metric space embeds into l2 with o(log n) distortion. we give the first embeddings for metrics of negative type which beat bourgain's bound. specifically, we show that for every &isin; > 0, there exists a &delta; > 0 such that every n-point metric of negative type embeds into l2+&isin;, with distortion o(log n)1-&delta;. we also exhibit the first o(log n) bounds on the euclidean distortion of finite subsets of lp, for 1 < p < 2. these spaces naturally interpolate between l1 and l2, and thus provide a necessary first step in resolving the long-standing open question on the euclidean distortion of finite subsets of l1.in proving these results, we introduce a number of new techniques for the construction of low-distortion embeddings. these include a generic gluing lemma which avoids the overhead that typically arises from the na&iuml;ve concatenation of different scales, and which provides new insights into the cut structure of finite graphs. we also exhibit the utility of lipschitz extension theorems from functional analysis to the embedding of finite metric spaces. finally, we prove the "big core" theorem---a significantly improved and quantitatively optimal version of the main structural theorem in [arv04] about random projections. the latter result offers a simplified hyperplane rounding algorithm for the computation of an o(&radic;logn)-approximation to the sparsest cut problem with uniform demands.
on the number of plane graphs. we investigate the number of plane geometric, i.e., straight-line, graphs, a set s of n points in the plane admits. we show that the number of plane graphs and connected plane graphs as well as the number of cycle-free plane graphs is minimized when s is in convex position. moreover, these results hold for all these graphs with an arbitrary but fixed number of edges. consequently, we provide simple proofs that the number of spanning trees, cycle-free graphs (forests), perfect matchings, and spanning paths is also minimized for point sets in convex position.in addition we construct a new extremal configuration, the so-called double zig-zag chain. most noteworthy this example bears &theta;*(&radic;72n) = &theta;*(8.4853n) triangulations and &theta;*(41.1889n) plane graphs (omitting polynomial factors in both cases), improving the previously known best maximizing examples.
competitive queueing policies for qos switches. we consider packet scheduling in a network providing differentiated services, where each packet is assigned a value. we study various queueing models for supporting qos (quality of service). in the nonpreemptive model, packets accepted to the queue will be transmitted eventually and cannot be dropped. the fifo preemptive model allows packets accepted to the queue to be preempted (dropped) prior to their departure, while ensuring that transmitted packets are sent in the order of arrival. in the bounded delay model, packets must be transmitted before a certain deadline, otherwise it is lost (while transmission ordering is allowed to be arbitrary). in all models the goal of the buffer policy is to maximize the total value of the accepted packets.let &alpha; be the ratio between the maximal and minimal value. for the non-preemptive model we derive a &theta;(log &alpha) competitive ratio, both exhibiting a buffer policy and a general lower bound. for the interesting case of two distinct values, we give an 2&alpha;--1/&alpha; competitive buffer policy, which exactly matches the lower bound. we also analyze a red-like policy and derive its competitive ratio, which is approximately 2&alpha;--0.5/&alpha; for two values and &theta;(log &alpha;) for multiple values. in addition we improve the previous known lower and upper bounds of the fixed partition and flexible partition policies.for the fifo preemptive model, we improve the general lower bound and show a tight bound for the special case of queue size 2. we prove that the bounded delay model with uniform delay 2 is equivalent to a modified fifo preemptive model with queue size 2. we then give improved upper and lower bounds on the 2-uniform bounded delay model. we also give lower bound for the 2-variable bounded delay model, which matches the previously known upper bound.
on-line scheduling of a single machine to minimize total weighted completion time. this paper considers the on-line scheduling of a single machine in which jobs arrive over time, and preemption is not allowed. the goal is to minimize the total weighted completion time. we show that a simple modification of the shortest weighted processing time rule has a competitive ratio of 2. this result is established using a new proof technique which does not rely explicitly on a lower bound on the optimal objective function value. since it is known that no on-line algorithm can have a competitive ratio of less than 2, we have resolved the open issue of determining the minimum competitive ratio for this problem.
dynamic routing on networks with fixed-size buffers. the combination of the buffer size of routers deployed in the internet and the internet traffic itself leads routinely to routers dropping packets. motivated by this, we initiate the rigorous study of dynamic store-and-forward routing on arbitrary networks in a model in which dropped packets must explicitly be taken into account. to avoid the uncertainties of traffic modeling, we consider arbitrary traffic on the network. we analyze and compare the effectiveness of several greedy, on-line, local-control protocols using a competitive analysis of the throughput. one goal of our approach is for the competitive results to continue to hold as a network grows without requiring the memory in the nodes to increase with the size of the network. thus, in our model, we have link buffers of fixed size, b, which is independent of the size of the network, and b becomes a parameter of the model.our results are in contrast to another adversarial traffic model known as adversarial queuing theory (aqt), which studies the stability and growth rate of queues as a function of the network and traffic parameters. for example, in aqt the furthest-to-go (ftg) protocol is stable for all networks whereas nearest-to-go (ntg) can be unstable for some networks. unlike aqt, in our setting ntg is preferable to ftg: we show that the ntg protocol is throughput-competitive on all networks whereas the ftg protocol has unbounded competitiveness whenever a network contains even small cycles.
the inverse nearest neighbor problem with astrophysical applications. this paper discusses algorithmic improvements to mature astrophysics applications as part of an on-going collaboration with astrophysicists. we present an efficient algorithm for a variation of the inverse nearest neighbor problem which is a basic computation in an astrophysical n-body simulation. we obtain empirical results demonstrating the improvements, which our algorithm offers to large-scale astrophysical simulations.
improved randomized on-line algorithms for the list update problem. the best randomized on-line algorithms known so far for the list update problem achieve a competitiveness of $\sqrt{3} \approx 1.73$. in this paper we present a new family of randomized on-line algorithms that beat this competitive ratio. our improved algorithms are called timestamp algorithms and achieve a competitiveness of $\max\{2-p, 1+p(2-p)\}$, for any real number $p\in[0,1]$. setting $p = (3-\sqrt{5})/2$, we obtain a $\phi$-competitive algorithm, where $\phi = (1+\sqrt{5})/2\approx 1.62$ is the golden ratio. timestamp algorithms coordinate the movements of items using some information on past requests. we can reduce the required information at the expense of increasing the competitive ratio. we present a very simple version of the timestamp algorithms that is \mbox{$1.68$-competitive}. the family of time\-stamp algorithms also includes a new deterministic 2-competitive on-line algorithm that is different from the move-to-front rule.
dynamic tcp acknowledgement: penalizing long delays. we study the problem of acknowledging a sequence of data packets that are sent across a tcp connection. previous work on the problem has focused mostly on the objective function that minimizes the sum of the number of acknowledgments sent and on the delays incurred for all of the packets. dooly, goldman, and scott presented a deterministic $2$-competitive online algorithm and showed that this is the best competitiveness of a deterministic strategy. recently karlin, kenyon, and randall developed a randomized online algorithm that achieves an optimal competitive ratio of $e/(e-1) \approx 1.58$.in this paper we investigate a new objective function that minimizes the sum of the number of acknowledgments sent and the maximum delay incurred for any of the packets. this function is especially interesting if a tcp connection is used for interactive data transfer between network nodes. the tcp acknowledgment problem with this new objective function is different in structure than the problem with the function considered previously. we develop a deterministic online algorithm that achieves a competitive ratio of $\pi^2/6 \approx 1.644$ and prove that no deterministic algorithm can have a smaller competitiveness. we also study a generalized objective function where delays are taken to the $p$th power for some positive integer $p$. again we give tight upper and lower bounds on the best possible competitive ratio of deterministic online algorithms. the competitiveness is 1 plus an alternating sum of riemann's zeta function and tends to 1.5 as $p\rightarrow \infty$. finally, we consider randomized online algorithms and show that, for our first objective function, no randomized strategy can achieve a competitive ratio smaller than $3/(3 - 2/e)\approx 1.324$. for the generalized objective function we show a lower bound of $2/(2-1/e) \approx 1.225$.
dynamic string searching. optimal bounds are presented for dynamic string searching. if the longest common prefix between a query key x and a currently stored string y is &ell; words, then finding the stored string lexicographically nearest to x takes optimal &thgr;(&radic;log n/log log n + &ell;) time. similarly, we can insert and delete strings from the stored set within this time bound. the space requirements is linear and the time bounds are worst-case.
on nash equilibria for a network creation game. we study a network creation game recently proposed by fabrikant, luthra, maneva, papadimitriou and shenker. in this game, each player (vertex) can create links (edges) to other players at a cost of &alpha; per edge. the goal of every player is to minimize the sum consisting of (a) the cost of the links he has created and (b) the sum of the distances to all other players.fabrikant et al. conjectured that there exists a constant a such that, for any &alpha; > a, all non-transient nash equilibria graphs are trees. they showed that if a nash equilibrium is a tree, the price of anarchy is constant. in this paper we disprove the tree conjecture. more precisely, we show that for any positive integer n0, there exists a graph built by n &ge; n0 players which contains cycles and forms a non-transient nash equilibrium, for any &alpha; with 1 < &alpha; &le; &radic;n/2. our construction makes use of some interesting results on finite affine planes. on the other hand we show that, for &alpha; &ge; 12n[log n], every nash equilibrium forms a tree.without relying on the tree conjecture, fabrikant et al. proved an upper bound on the price of anarchy of o(&radic;&alpha;), where &alpha; &isin; [2, n2]. we improve this bound. specifically, we derive a constant upper bound for &alpha; &isin; o(&radic;n) and for &alpha; &ge; 12n[log n]. for the intermediate values we derive an improved bound of o(1 + (min{&alpha;2/n, n2/&alpha;})1/3).additionally, we develop characterizations of nash equilibria and extend our results to a weighted network creation game as well as to scenarios with cost sharing.
improved parallel integer sorting without concurrent writing. we show that n integers in the range 1..n can be stably sorted on an erew pram using o((log n)1/2) time, o(n(log n)1/2(log log n)1/2) operations and o(n) space. in addition, we are able to stably sort n integers in the range 1..n on a deterministic crew pram in o((log n)3/2) time with o(n(log n)1/2) operations and o(n) space and to stably sort n arbitrary integers on a randomized crew pram within the same complexity bounds with high probability. in each case our algorithm is closer to optimality than all previous algorithms for the stated problem in the stated model, and our third result matches the operation count of the best known sequential algorithm. we also show that m integers in the range 1..m can be sorted in o((log n)2) time with o(n) operations on an erew pram using a nonstandard word length of o(log n log log n log m) bits, thereby greatly improving the upper bound on the word length necessary to sort integers with a linear time-processor product, even sequentially. our algorithms were inspired by, and in one case directly use, the fusion trees recently introduced by fredman and willard.
efficient algorithms for substring near neighbor problem. in this paper we consider the problem of finding the approximate nearest neighbor when the data set points are the substrings of a given text t. specifically, for a string t of length n, we present a data structure which does the following: given a pattern p, if there is a substring of t within the distance r from p, it reports a (possibly different) substring of t within distance cr from p. the length of the pattern p, denoted by m, is not known in advance. for the case where the distances are measured using the hamming distance, we present a data structure which uses &otilde;(n1+1/c) space1 and with &otilde;(n1/c + mno(1)) query time. this essentially matches the earlier bounds of [ind98], which assumed that the pattern length m is fixed in advance. in addition, our data structure can be constructed in time &otilde;(n1+1/c + n1+o(1)m1/3), where m is an upper bound for m. this essentially matches the preprocessing bound of [ind98] as long as the term &otilde;(n1+1/c) dominates the running time, which is the case when, e.g., c < 3.we also extend our results to the case where the distances are measured according to the l1 distance. the query time and the space bound are essentially the same, while the preprocessing time becomes &otilde;(n1+1/c + n1+o(1)m2/3).
instability of fifo in session-oriented networks. we show that the first-in-first-out (fifo) scheduling discipline can be unstable in the (σ,ρ) regulated session model for packet-switched networks. in this model packets are injected into the network in fixed sessions. the total size of the session-i packets injected during the time interval [x, y) is at most σi + ρi(y - x) for some burst parameter σi and rate ρi. the sum of the rates of sessions passing through a server is at most the server speed.previous work on fifo stability either allowed for dynamically changing session paths or else assumed that session-i packets are injected at a constant rate. our result shows that fifo can be unstable for static paths as long as the injections into a session can be temporarily suspended.
the effects of temporary sessions on network performance. we consider a packet network, in which packets are injected in sessions along fixed paths. packet movement is restricted by link bandwidth. in case of contention, a contention resolution protocol determines which packets proceed. in the permanent session model, a fixed set of connections is present in the network at all times. in the temporary session model, connections come and go over time. in this paper we compare network performance in these two models in terms of stability and end-to-end delay.we provide the first separation of the two models in terms of stability. in particular, we show that generalized processor sharing (gps) can be unstable with temporary sessions, whereas gps is known to be stable and have polynomial delay bounds with permanent sessions.we also observe that the relative performance of protocols can differ in the two models. for example, in the temporary session model the protocol farthest-to-go (ftg) is known to be stable and therefore outperforms gps. however, in the permanent session model we show that ftg can suffer exponential delays and is therefore outperformed by gps.although polynomial delay bounds are easy to obtain for permanent sessions, this is not the case when sessions can be temporary. we show that a common framework for bounding delays can only lead to superpolynomial bounds in the temporary session model. we also construct superpolynomial lower bounds on delay for a large class of deterministic, distributed protocols that includes the longest-in-system protocol.
scheduling protocols for switches with large envelopes. traditionally, switches make scheduling decisions on the granularity of a packet. however, this is becoming increasingly difficult since network bandwidth is growing rapidly whereas packet sizes remain largely unchanged. therefore the service time of an individual packet is decreasing rapidly. in this paper we study switches that make scheduling decisions on the granularity of an envelope which can be much larger than a packet in size.for an output-queued switch with envelope size e, each output chooses one input every e time steps and transmits packets from this chosen input during the next e steps. for an input-queued switch with envelope size e, one matching from the inputs to the outputs is computed every e steps and only the input---output pairs that are defined by this matching are allowed to transmit packets during the next e steps. traditional switches correspond to envelope size e = 1 and almost all previous scheduling work deals with this case exclusively.we first show how some stable protocols for scheduling networks of output-queued switches with e = 1 fail for arbitrary e when these protocols are generalized in the most straightforward manner. we then present an extremely simple protocol that does guarantee network stability for output-queued switches for any e ¿ 1.for input-queued switches we first present a max-weight matching protocol that is stable for a single switch with arbitrary e. we then present a more complex protocol that achieves stability for a network of input-queued switches for any e ¿ 1.
approximate classification via earthmover metrics. given a metric space (x, d), a natural distance measure on probability distributions over x is the earthmover metric. we use randomized rounding of earthmover metrics to devise new approximation algorithms for two well-known classification problems, namely, metric labeling and 0-extension.our first result is for the 0-extension problem. we show that if the terminal metric is decomposable with parameter &alpha; (e.g., planar metrics are decomposable with &alpha; = o(1)), then the earthmover based linear program (for 0-extension) can be rounded to within an o(&alpha;) factor.our second result is an o(log n)-approximation for metric labeling, using probabilistic tree embeddings in a way very different from the o(log k)-approximation of kleinberg and tardos. (here, n is the number of nodes, and k is the number of labels.) the key element is rounding the earthmover based linear program (for metric labeling) without increasing the solution's cost, when the input graph is a tree. this rounding method also provides an alternate proof to a result stated in chekuri et al., that the earthmover based linear program is integral when the input graph is a tree.our simple and constructive rounding techniques contribute to the understanding of earthmover metrics and may be of independent interest.
an approximate truthful mechanism for combinatorial auctions with single parameter agents. mechanism design seeks algorithms whose inputs are provided by selfish agents who would lie if advantageous. incentive compatible mechanisms compel the agents to tell the truth by making it in their self-interest to do so. often, as in combinatorial auctions, such mechanisms involve the solution of np-hard problems. unfortunately, approximation algorithms typically destroy incentive compatibility. randomized rounding is a commonly used technique for designing approximation algorithms. we devise a version of randomized rounding that is incentive compatible, giving a truthful mechanism for combinatorial auctions with single parameter agents (e.g., "single minded bidders") that approximately maximizes the social value of the auction. we discuss two orthogonal notions of truthfulness for a randomized mechanism, truthfulness with high probability and in expectation, and give a mechanism that achieves both simultaneously.we consider combinatorial auctions where multiple copies of many different items are on sale, and each bidder i desires a subset si. given a set of bids, the problem of finding the allocation of items that maximizes total valuation is the well-known setpacking problem. this problem is np-hard, but for the case of items with many identical copies the optimum can be approximated very well. to turn this approximation algorithm into a truthful auction mechanism we overcome two problems: we show how to make the allocation algorithm monotone, and give a method to compute the appropriate payments efficiently.
faster approximation algorithms for the minimum latency problem. in this paper, we give a 9.28-approximation algorithm for the minimum latency problem that uses only o(n log n) calls to the prize-collecting steiner tree (pcst) subroutine of goemans and williamson. a previous algorithm of goemans and kleinberg for the minimum latency problem requires an approximation algorithm for the k-mst problem which is called as a black box. their algorithm can achieve a performance guarantee of 10.77 while making o(n2 log n) pcst calls (via a k-mst algorithm of garg), or a performance guarantee of 7.18 + &epsilon; while using no(1/&epsilon;) pcst calls (via a k-mst algorithm of arora and karakostas). in order to match our approximation ratio (i.e. setting &epsilon; = 2.10), the latter version requires o(n5 log2 n) pcst calls, so our running time bound is faster by a factor of &theta;(n4 log n). since pcst can be implemented to run in o(n2) time, the overall running time of our algorithm is o(n3 log n).the basic idea for our improvement is that we do not treat the k-mst algorithm as a black box. thus we are able to take advantage of some situations in which the pcst subroutine delivers a k-mst with an improved performance guarantee.
optimal covering tours with turn costs. we give the first algorithmic study of a class of "covering tour" problems related to the geometric traveling salesman problem: find a polygonal tour for a cutter so that it sweeps out a specified region ("pocket") in order to minimize a cost that depends mainly on the number of turns. these problems arise naturally in manufacturing applications of computational geometry to automatic tool path generation and automatic inspection systems, as well as arc routing ("postman") problems with turn penalties. we prove the np-completeness of minimum-turn milling and give efficient approximation algorithms for several natural versions of the problem, including a polynomial-time approximation scheme based on a novel adaptation of the $m$-guillotine method.
the freeze-tag problem: how to wake up a swarm of robots. an optimization problem that naturally arises in the study of swarm robotics is the freeze-tag problem (ftp) of how to awaken a set of "asleep" robots, by having an awakened robot move to their locations. once a robot is awake, it can assist in awakening other slumbering robots. the objective is to have all robots awake as early as possible. while the ftp bears some resemblance to problems from areas in combinatorial optimization such as routing, broadcasting, scheduling, and covering, its algorithmic characteristics are surprisingly different. we consider both scenarios on graphs and in geometric environments. in graphs, robots sleep at vertices and there is a length function on the edges. awake robots travel along edges, with time depending on edge length. for most scenarios, we consider the offline version of the problem, in which each awake robot knows the position of all other robots. we prove that the problem is np-hard, even for the special case of star graphs. we also establish hardness of approximation, showing that it is np-hard to obtain an approximation factor better than 5/3, even for graphs of bounded degree. these lower bounds are complemented with several positive algorithmic results, including: &#x00b7; we show that the natural greedy strategy on star graphs has a tight worst-case performance of 7/3 and give a polynomial-time approximation scheme (ptas) for star graphs. &#x00b7; we give a simple o(log &#x03b4;)-competitive online algorithm for graphs with maximum degree &#x03b4; and locally bounded edge weights. &#x00b7; we give a ptas, running in nearly linear time, for geometrically embedded instances.
an efficiently computable metric for comparing polygonal shapes. a method for comparing polygons that is a metric, invariant under translation, rotation, and change of scale, reasonably easy to compute, and intuitive is presented. the method is based on the l/sub 2/ distance between the turning functions of the two polygons. it works for both convex and nonconvex polygons and runs in time o(mn log mn), where m is the number of vertices in one polygon and n is the number of vertices in the other. some examples showing that the method produces answers that are intuitively reasonable are presented.
optimal link path queries in a simple polygon. we develop a data structure for answering link distance queries between two arbitrary points in a simple polygon. the data structure requires o(n3) time and space for its construction and answers link distance queries in o(log n) time. our result extends to link distance queries between pairs of segments or polygons. we also propose a simpler data structure for computing a link distance approximately, where the error is bounded by a small additive constant. finally, we also present a scheme for approximating the link and the shortest path distance simultaneously.
temporary tasks assignment resolved. among all basic on-line load balancing problems, the only unresolved problem was load balancing of temporary tasks on unrelated machines. this open problem exists for almost a decade, see [borodin el-yaniv]. we resolve this problem by providing an unapproximability result. in addition, a newer open question is to identify the dependency of the competitive ratio on the durations of jobs in the case where durations are known. we resolve this problem by characterizing this dependency. finally, we provide a ptas for the off-line problem with a fixed number of machines and show a 2 unapproximability for the general case.
on approximating the depth and related problems. in this paper, we study the problem of finding a disk covering the largest number of red points, while avoiding all the blue points. we reduce it to the question of finding a deepest point in an arrangement of pseudodisks and provide a near-linear expected-time randomized approximation algorithm for this problem. as an application of our techniques, we show how to solve linear programming with violations approximately. we also prove that approximate range counting has roughly the same time and space complexity as answering emptiness range queries.
on geometric permutations induced by lines transversal through a fixed point. a line transversal of a family s of n pairwise disjoint convex objects is a straight line meeting all members of s. a geometric permutation of s is the pair of orders in which members of s are met by a line transversal, one order being the reverse of the other.in this note we consider a long-standing open problem in transversal theory, namely that of determining the largest number of geometric permutations that a family of n pairwise disjoint convex objects in rd can admit. we settle a restricted variant of this problem. specifically, we show that the maximum number of those geometric permutations to a family of n > 2 pairwise disjoint convex objects that are induced by lines passing through any fixed point is between k(n - 1, d - 1) and k(n,d - 1), where k(n,d) = &sigma;di=0 (n-1/i) = &theta;(nd) is the number of pairs of antipodal cells in a simple arrangement of n great (d - 1)-spheres in a d-sphere. by a similar argument, we show that the maximum number of connected components of the space of all lines transversal through a fixed point to a family of n > 2 possibly intersecting convex objects is k(n, d - 1). finally, we refute a conjecture of sharir and smorodinsky on the number of neighbor pairs in geometric permutations and offer an alternative conjecture which may be a first step towards solving the aforementioned general problem of bounding the number of geometric permutations.
a randomized online algorithm for bandwidth utilization. protocols for data transmission over an ip computer network should not only lead to efficient network utilization but also be fair to different users. current networks accomplish these goals by some form of end-to-end congestion control. existing protocols, however, assume somewhat altruistic behavior from hosts. karp et al. (2000) have initiated a study of whether or not a single host's optimum strategy (in a system where other hosts are well behaved) is altruistic. we carry this exploration further by developing an efficient randomized algorithm for bandwidth utilization in their model. the competitive ratio of this algorithm is optimal up to a constant factor. karp et al. had earlier studied the deterministic case and left open the randomized case. what may be of some interest is that our algorithm is essentially the classical multiplicative increase, multiplicative decrease strategy, which is very aggressive and non-altruistic.
local versus global properties of metric spaces. motivated by applications in combinatorial optimization, we initiate a study of the extent to which the global properties of a metric space (especially, embeddability in l1 with low distortion) are determined by the properties of small subspaces. we note connections to similar issues studied already in ramsey theory, complexity theory (especially pcps), and property testing. we prove both upper bounds and lower bounds on the distortion of embedding locally constrained metrics into various target spaces.
analyzing bittorrent and related peer-to-peer networks. we analyze protocols for disseminating a collection of data blocks over a network of peers with a view towards bit-torrent and related peer-to-peer networks. unlike previous work, we accurately model the distribution of the individual data blocks, a process which is critical to the parallelism that makes bittorrent successful in practice. we also consider multiple network topologies and routing algorithms. we first demonstrate several routing algorithms that distribute b data blocks on a network with diameter d and maximum degree d in o(d(b + d)) phases of concurrent downloads with high probability. this is tight within a factor of d. we also specialize to the networks used by bittorrent and we improve this bound to o(b ln n) phases where n is the number of clients. finally, we discuss several practical extensions to bittorrent, one of which improves the bound to a near-optimal o (b + (ln n)2) phases.
expected-case complexity of approximate nearest neighbor searching. most research in algorithms for geometric query problems has focused on their worst-case performance. however, when information on the query distribution is available, the alternative paradigm of designing and analyzing algorithms from the perspective of expected-case performance appears more attractive. we study the approximate nearest neighbor problem from this perspective.as a first step in this direction, we assume that the query points are sampled uniformly from a hypercube that encloses all the data points; however, we make no assumption on the distribution of the data points. we show that with a simple partition tree, called the sliding-midpoint tree, it is possible to achieve linear space and logarithmic query time in the expected case; in contrast, the data structures known to achieve linear space and logarithmic query time in the worst case are complex, and algorithms on them run more slowly in practice. moreover, we prove that the sliding-midpoint tree achieves optimal expected query time in a certain class of algorithms.
linear-size approximate voronoi diagrams. given a set s of n points in ird, a (t, &epsilon;)-approximate voronoi diagram (avd) is a partition of space into constant complexity cells, where each cell c is associated with t representative points of s, such that for any point in c, one of the associated representatives approximates the nearest neighbor to within a factor of (1 + &epsilon;). the goal is to minimize the number and complexity of the cells in the avd. we show that it is possible to construct an avd consisting of o(n/&epsilon;d) cells for t = 1, and o(n) cells for t = o(1/&epsilon;(d-1)/2). in general, for a real parameter 2 &le; &gamma; &le; 1/&epsilon;, we show that it is possible to construct a (t, &epsilon;)-avd consisting of o(n&gamma;d) cells for t = o(1/(&epsilon;&gamma;)(d-1)/2). the cells in these avds are cubes or differences of two cubes. all these structures can be used to efficiently answer approximate nearest neighbor queries. our algorithms are based on the well-separated pair decomposition and are very simple.
entropy-preserving cuttings and space-efficient planar point location. point location is the problem of preprocessing a planar polygonal subdivision s into a data structure in order to determine efficiently the cell of the subdivision that contains a given query point. given the probabilities pz that the query point lies within each cell z &isin; s, a natural question is how to design such a structure so as to minimize the expected-case query time. the entropy h of the probability distribution is the dominant term in the lower bound on the expected-case search time. clearly the number of edges n of the subdivision is a lower bound on the space required. there is no known approach that simultaneously achieves the goals of h + &ogr;(h) query time and &ogr;(n) space. in this paper we introduce entropy-preserving cuttings and show how to use them to achieve query time h + &ogr;(h), using only &ogr;(n log* n) space.
a simple entropy-based algorithm for planar point location. given a planar polygonal subdivision s, point location involves preprocessing this subdivision into a data structure so that given any query point q, the cell of the subdivision containing q can be determined efficiently. suppose that for each cell z in the subdivision, the probability pz that a query point lies within this cell is also given. the goal is to design the data structure to minimize the average search time. this problem has been considered before, but existing data structures are all quite complicated. it has long been known that the entropy h of the probability distribution is the dominant term in the lower bound on the average-case search time. in this article, we show that a very simple modification of a well-known randomized incremental algorithm can be applied to produce a data structure of expected linear size that can answer point-location queries in o(h) average time. we also present empirical evidence for the practical efficiency of this approach.
space-time tradeoffs for approximate spherical range counting. we present space-time tradeoffs for approximate spherical range counting queries. given a set s of n data points in rd along with a positive approximation factor &epsilon;, the goal is to preprocess the points so that, given any euclidean ball b, we can return the number of points of any subset of s that contains all the points within a (1 - &epsilon;)-factor contraction of b, but contains no points that lie outside a (1 + &epsilon;)-factor expansion of b.in many applications of range searching it is desirable to offer a tradeoff between space and query time. we present here the first such tradeoffs for approximate range counting queries. given 0 < &epsilon; &le; 1/2 and a parameter &gamma;, where 2 &le; &gamma; &le; 1/&epsilon;, we show how to construct a data structure of space o(n&gamma;d log (1/&epsilon;)) that allows us to answer &epsilon;-approximate spherical range counting queries in time o(log(n&gamma;) + 1/(&epsilon;&gamma;d-1). the data structure can be built in time o(n&gamma;d log (n/&epsilon;)) log (1/&epsilon;)). here n, &epsilon;, and &gamma; are asymptotic quantities, and the dimension d is assumed to be a fixed constant.at one extreme (low space), this yields a data structure of space o(n log (1/e)) that can answer approximate range queries in time o(logn + 1/(ed-1) which, up to a factor of o(n log (1/e) in space, matches the best known result for approximate spherical range counting queries. at the other extreme (high space), it yields a data structure of space o((n/ed) log(1/&epsilon;)) that can answer queries in time o(logn + 1/&epsilon;). this is the fastest known query time for this problem.we also show how to adapt these data structures to the problem of computing an &epsilon;-approximation to the kth nearest neighbor, where k is any integer from 1 to n given at query time. the space bounds are identical to the range searching results, and the query time is larger only by a factor of o(1/(&epsilon;&gamma;)).our approach is broadly based on methods developed for approximate voronoi diagrams (avds), but it involves a number of significant extensions from the context of nearest neighbor searching to range searching. these include generalizing avd node-separation properties from leaves to internal nodes of the tree and constructing efficient generator sets through a radial decomposition of space. we have also developed new arguments to analyze the time and space requirements in this more general setting.
matrix rounding under the lp-discrepancy measure and its application to digital halftoning. we study the problem of rounding a real-valued matrix into an integer-valued matrix to minimize an lp-discrepancy measure between them. to define the lp-discrepancy measure, we introduce a family ${\cal f}$ of regions (rigid submatrices) of the matrix and consider a hypergraph defined by the family. the difficulty of the problem depends on the choice of the region family ${\cal f}$. we first investigate the rounding problem by using integer programming problems with convex piecewise-linear objective functions and give some nontrivial upper bounds for the lp discrepancy. we propose "laminar family" for constructing a practical and well-solvable class of ${\cal f}$. indeed, we show that the problem is solvable in polynomial time if ${\cal f}$ is the union of two laminar families. finally, we show that the matrix rounding using l1 discrepancy for the union of two laminar families is suitable for developing a high-quality digital-halftoning software.
improved approximation algorithms for max sat. max sat (the maximum satisfiability problem) is stated as follows: given a set of clauses with weights, find a truth assignment that maximizes the sum of the weights of the satisfied clauses. in this paper, we consider approximation algorithms for max sat proposed by goemans and williamson and present a sharpened analysis of their performance guarantees. we also show that these algorithms, combined with recent approximation algorithms for max 2sat, max 3sat, and max sat due to feige and goemans, karloff and zwick, and zwick, respectively, lead to an improved approximation algorithm for max sat. by using the max 2sat and 3sat algorithms, we obtain a performance guarantee of 0.7846, and by using zwick's algorithm, we obtain a performance guarantee of 0.8331, which improves upon the performance guarantee of 0.7977 based on zwick's conjecture. the best previous result for max sat without assuming zwick's conjecture is a 0.770-approximation algorithm of asano. our best algorithm requires a new family of 3/4-approximation algorithms that generalize a previous algorithm of goemans and williamson.
inoculation strategies for victims of viruses and the sum-of-squares partition problem. we propose a simple game for modeling containment of the spread of viruses in a graph of n nodes. each node must choose to either install anti-virus software at some known cost c, or risk infection and a loss l if a virus that starts at a random initial point in the graph can reach it without being stopped by some intermediate node. the goal of individual nodes is to minimize their individual expected cost. we prove many game theoretic properties of the model, including an easily applied characterization of nash equilibria, culminating in our showing that allowing selfish users to choose nash equilibrium strategies is highly undesirable, because the price of anarchy is an unacceptable &theta;(n) in the worst case. this shows in particular that a centralized solution can give a much better total cost than an equilibrium solution. though it is np-hard to compute such a social optimum, we show that the problem can be reduced to a previously unconsidered combinatorial problem that we call the sum-of-squares partition problem. using a greedy algorithm based on sparse cuts, we show that this problem can be approximated to within a factor of o(log2 n), giving the same approximation ratio for the inoculation game.
towards understanding the predictability of stock markets from the perspective of computational complexity. this paper initiates a study into the century-old issue of market predictability from the perspective of computational complexity. we develop a simple agent-based model for a stock market where the agents are traders equipped with simple trading strategies, and their trades together determine the stock prices. computer simulations show that a basic case of this model is already capable of generating price graphs which are visually similar to the recent price movements of high tech stocks. in the general model, we prove that if there are a large number of traders but they employ a relatively small number of strategies, then there is a polynomial-time algorithm for predicting future price movements with high accuracy. on the other hand, if the number of strategies is large, market prediction becomes complete in two new computational complexity classes cpp and bcpp, where pnp[&ogr;(log n)] e bcpp e cpp = pp. these computational completeness results open up a novel possibility that the price graph of a actual stock could be sufficiently deterministic for various prediction goals but appear random to all polynomial-time prediction algorithms.
skip graphs. skip graphs are a novel distributed data structure, based on skip lists, that provide the full functionality of a balanced tree in a distributed system where elements are stored in separate nodes that may fail at any time. they are designed for use in searching peer-to-peer networks, and by providing the ability to perform queries based on key ordering, they improve on existing search tools that provide only hash table functionality. unlike skip lists or other tree data structures, skip graphs are highly resilient, tolerating a large fraction of failed nodes without losing connectivity. in addition, constructing, inserting new elements into, searching a skip graph and detecting and repairing errors in the data structure introduced by node failures can be done using simple and straight-forward algorithms.
dotted interval graphs and high throughput genotyping. we introduce a generalization of interval graphs, which we call dotted interval graphs (dig). a dotted interval graph is an intersection graph of arithmetic progressions (=dotted intervals). coloring of dotted intervals graphs naturally arises in the context of high throughput genotyping. we study the properties of dotted interval graphs, with a focus on coloring. we show that any graph is a dig but that digd graphs, i.e. digs in which the arithmetic progressions have a jump of at most d, form a strict hierarchy. we show that coloring digd, graphs is np-complete even for d = 2. for any fixed d, we provide a 7/8d approximation for the coloring of digd graphs.
on-line generalized steiner problem. the generalized steiner problem (gsp) is defined as follows. we are given a graph with non-negative edge weights and a set of pairs of vertices. the algorithm has to construct minimum weight subgraph such that the two nodes of each pair are connected by a path.off-line gsp approximation algorithms were given in agarwal et al. (siam j. comput. 24(3) (1995) 440) and goemans and williamson (siam j. comput. 24(2) (1995) 296). we consider the on-line gsp, in which pairs of vertices arrive on-line and are needed to be connected immediately.we show that the online min-cost (i.e. greedy) strategy for this problem has o(log2 n) competitive ratio. the previous best algorithm was o(√nlog n) competitive (workshop on algorithms and data structures, 1993, pp. 622-633). following this work a different (non-greedy) algorithm has been shown to achieve an o(log n) competitive ratio (proceedings of the 29th acm symposium on theory of computing, 1997, pp. 344-353).we also consider the network connectivity leasing problem which is a generalization of the gsp. here, edges of the graph can be either bought or leased for different costs. we provide simple randomized algorithm based on on-line generalized steiner algorithms whose competitive ratio is within a constant factor of the best competitive algorithm for the on-line gsp.
online client-server load balancing without global information. we consider distributed online algorithms for maximizing through-put in a network of clients and servers, modeled as a bipartite graph. unlike most prior work on online load balancing, we do not assume centralized control and seek algorithms and lower bounds for decentralized algorithms in which each participant has only local knowledge about the state of itself and its neighbors. our problem can be seen as analogous to the recent work on oblivious routing in [8, 14, 19], but with the objective of maximizing through-put rather than minimizing congestion. in contrast to that work, we prove a strong lower bound (polynomial in n, the size of the graph) on the competitive ratio of any oblivious algorithm. this is accompanied by simple algorithms achieving upper bounds which are tight in terms of k, the maximum throughput achievable by an omniscient algorithm. finally, we examine a restricted model in which clients, upon becoming active, must remain so for at least log(n) time steps. in contrast to the primarily negative results in the oblivious case, here we present an algorithm which is constant-competitive. our lower bounds justify the intuition, implicit in earlier work on the subject [2], that some such restriction (i.e. requiring some stability in the demand pattern over time) is necessary in order to achieve a constant --- or even polylogarithmic --- competitive ratio.
improved recommendation systems. we consider a model of competitive recommendation systems proposed by drineas et al. [4]. in recommendation systems (e.g., for books or movies), the system tracks which product each user chose in the past, and tries to deduce which other products an asking user is likely to be satisfied with. obviously, recommendation systems can be effective only for users who share preferences with many other users. such users are said to belong to a "dominant type." current approaches to on-line recommendation systems involve using singular value decomposition (svd), which is computationally intensive and, more important, often applicable only under additional strong conditions. specifically, correctness is guaranteed in [4] only if users of different dominant types essentially do not share a product they like ("type separability"), and only if the number of users in non-dominant types is significantly smaller than the number of users in dominant types ("gap assumption"). the complexity of that algorithm is o(mn), where m and n denote the number of users and products, respectively. in this paper, we show that in fact, very simple combinatorial algorithms can make good recommendations without using svd. our algorithms require neither the type separability nor the gap assumption, they are naturally amenable to distibuted computation, and their complexity is lower. in particular, the paper presents an o(m + n) time centralized algorithm and a distributed algorithm that can be implemented in a peer-to-peer model even in the presence of adaptively colluding malicious players, with only logarithmic over-head.
the hyperring: a low-congestion deterministic data structure for distributed environments. in this paper we study the problem of designing searchable concurrent data structures with performance guarantees that can be used in a distributed environment where data elements are stored in a dynamically changing set of nodes. searchable data structures are data structures that provide three basic operations: insert, delete, and search. in addition to searching for an exact match, we demand that for a data structure to be called "searchable", search also has to be able to search for the closest successor or predecessor of a data item. such a property has a tremendous advantage over just exact match, because it would allow to implement many data base applications.we are interested in finding a searchable concurrent data structure that has (1) a low degree, (2) requires a small amount of work for insert and delete operations, and (3) is able to handle concurrent search requests with low congestion and dilation.we present the first deterministic concurrent data structure, called hyperring, that can fulfill all of these objectives in a polylogarithmic way. in fact, the hyperring has a degree of o(log n), requires o(log3 n) work for insert and delete operations, and can handle concurrent search requests to random destinations, one request per node, with congestion and dilation o(log n) w.h.p.most of the previous solutions for distributed environments are not searchable (in our sense) but only provide exact lookup, and those that are searchable do not have proofs about the congestion caused by concurrent search requests.
the competitiveness of on-line assignments. consider the on-line problem where a number of servers are ready to provide service to a set of customers. each customer's job can be handled by any of a subset of the servers. customers arrive one-by-one and the problem is to assign each customer to an appropriate server in a manner that will balance the load on the servers. this problem can be modeled in a natural way by a bipartite graph where the vertices of one side (customers) appear one at a time and the vertices of the other side (servers) are known in advance. we derive tight bounds on the competitive ratio in both deterministic and randomized cases. let n denote the number of servers. in the deterministic case we provide an on-line algorithm that achieves a competitive ratio of k = [log2 n] (up to an additive 1) and prove that this is the best competitive ratio that can be achieved by any deterministic on-line algorithm. in a similar way we prove that the competitive ratio for the randomized case is k=ln(n) (up to an additive 1). we conclude that for this problem, randomized algorithms differ from deterministic ones by precisely a constant factor.
on the diameter of eulerian orientations of graphs. we compare the diameter of a graph with the directed diameter of its eulerian orientations. we obtain positive results under certain symmetry conditions.an eulerian orientation of a graph is an orientation such that each vertex has the same indegree and outdegree. a graph is vertex-transitive if its vertices are equivalent under automorphisms.we show that the directed diameter of an eulerian orientation of a finite vertex-transitive graph cannot be much larger than the undirected diameter; our bound on the directed diameter is o (d&delta; ln n) where d is the undirected diameter, &delta; is the (out)degree of the vertices, and n is the number of vertices. this implies that for eulerian orientations of vertex-transitive graphs-of bounded degree, the gap between the two diameters is at most quadratic.as a consequence, we are able to compare the word length and the positive word length of elements of a finite group in terms of a given set of generators; we show that the gap is at most nearly quadratic, where the term "nearly" refers to a factor, polylogarithmic in the order of the group.it follows that recent polynomial bounds on the diameter of certain large classes of cayley graphs of the symmetric group and certain linear groups automatically extend to directed cayley graphs. the result also shows that the directed and undirected versions of long standing conjectures regarding the diameter of cayley graphs of various classes of groups, including transitive permutation groups and finite simple groups, are equivalent.we also show that for edge-transitive digraphs, the directed diameter is o(d ln n).on the other hand, if we weaken the condition of vertex-transitivity to regularity (all vertices have the same degree), then the directed diameter is no longer polynomially bounded in terms of the undirected diameter and the maximum degree (and in n = o(d ln &delta;)).our upper bounds on the diameter raise the algorithmic challenge to find paths of the length guaranteed by these results. while for undirected graphs, most (but not all) relevant proofs are algorithmic, our bounds for the directed diameter are obtained via a pigeon-hole argument based on expansion and yield existence only.
deciding finiteness of matrix groups in las vegas polynomial time. let g be a group of matrices with integer entries, given by a list of generators. it is known that membership in such a group is undecidable, even for 4 x 4 integral matrices [mi]. in this paper we show that one can decide whether or not g is finite, in las vegas polynomial time. the key estimate derived makes the entire &ldquo;black box group&rdquo; theory ([bsz], [bcfls], [ba2], [bkl]) applicable to the finite groups of integral matrices. in particular it follows that in this case, structural properties such as solvability and nilpotence are decidable in monte carlo polynomial time; and membership, order, isomorphism, and a host of other problems are in the relatively low complexity class am &cap; coam [ba1]. we give two algorithms. the simpler one (monte carlo but not las vegas) employs a refinement of the random walk technique over groups, developed in [ba3] (applied here to infinite groups). the termination rule rests on a new estimate on the bit-size of the elements of finite groups g, obtained via polynomial time symbolic manipulation of representations over algebraic number fields using results of [br]. this symbolic manipulation technique is the basis of the las vegas algorithm. (a las vegas algorithm is a rnadomized algorithm which never errs; but with small probability, it may r eport failure.)
multiplicative equations over commuting matrices. we consider the solvability of the equation a_1^x_1 * ... * x_k^x_k = b and generalizations, where the a_i and b are given commuting matrices over an algebraic number field f. in the semigroup membership problem, the variables x_i are constrained to be nonnegative integers. while this problem is np-complete for variable k, we give a polynomial time algorithm if k is fixed. in the group membership problem, the matrices are assumed to be invertible, and the variables x_i may take on negative values. in this case we give a polynomial time algorithm for variable k and give an explicit description of the set of all solutions (as an affine lattice). the results generalize recent work of cai, lipton, and zalcstein [clz] where the case k=2 is solved using jordan normal forms (jnf). we achieve greater clarity simplicity, and generality by eliminating the use of jnf''s and referring to elementary concepts of the structure theory of algebras instead (notably, the radical and the local decomposition. partial solutions are combined using algorithms for (affine lattices. the special case of 1*1 matrices was recently solved by g. ge and we heavily rely on his results.
on the diameter of the symmetric group: polynomial bounds. we address the long-standing conjecture that all permutations have polynomially bounded word length in terms of any set of generators of the symmetric group. the best available bound on the maximum required word length is exponential in n log n. polynomial bounds on the word length have previously been established for very special classes of generating sets only.in this paper we give a polynomial bound on the word length under the sole condition that one of the generators fix at least 67% of the domain. words of the length claimed can be found in las vegas polynomial time.the proof involves a markov chain mixing estimate which permits us, apparently for the first time, to break the "element order bottleneck."as a corollary, we obtain the following average-case result: for a 1 -- &delta; fraction of the pairs of generators for the symmetric group, the word length is polynomially bounded. it is known that for almost all pairs of generators, the word length is less than exp(&radic;n ln n(1 + o(1))).
near-independence of permutations and an almost sure polynomial bound on the diameter of the symmetric group. we address the long-standing conjecture that all permutations have polynomially bounded word length in terms of any set of generators of the symmetric group sn this is equivalent to polynomial-time (o(nc)) mixing of the (lazy) random walk on sn where one step is multiplication by a generator or its inverse.we prove that the conjecture is true for almost all pairs of generators. specifically, our bound is &otilde;(n7). for almost all pairs of generators, words of this length representing any given permutation can be constructed in las vegas polynomial time. the best previous bound on the word length for a random pair of generators was ninn(1/2+o(1)) (babai-hetyei, 1992).we build on recent major progress by babai-beals-seress (soda, 2004), confirming the conjecture under the assumption that at least one of the generators has degree < 0.33n.the main technical contribution of the present paper is the following near-independence result for permutations. the first cycle of a permutation is the trajectory of the first element of the permutation domain. for a random permutation, the distribution of the length of the first cycle is uniform. we show that if &tau; &isin; sn is a given permutation of degree &ge; n3/4 and &sigma; &isin; sn is chosen at random, then the distributions of the length of the first cycle of &sigma; and the length of the first cycle in &sigma;&tau; are nearly independent. the ability of an essentially arbitrarily fixed permutation (&tau;) to "scramble" another permutation in this technical sense may be of independent interest and suggests new directions in the statistical theory of permutations pioneered by goncharov and erd&odblac;s-tur&aacute;n.
strong bias of group generators: an obstacle to the ``product replacement algorithm''. let g be a finite group. efficient generation of nearly uniformly distributed random elements in g, starting from a given set of generators of g, is a central problem in computational group theory. in this paper we demonstrate a weakness in the popular "product replacement algorithm," widely used for this purpose. the main results are the following. let nk(g) be the set of generating k-tuples of elements of g. consider the distribution of the first components of the k-tuples in nk(g) induced by the uniform distribution over nk(g). we show that there exist infinite sequences of gtoups g such that this distribution is very far from uniform in two different senses: (1) its variation distance from uniform is > 1 - ε and (2) there exists a short word (of length (loglog |g|)o(k)) which separates the two distributions with probability 1 - ε. the class of groups we analyze is direct powers of alternating groups. the methods used include statistical analysis of permutation groups, the theory of random walks, the aks sorting network, and a randomized simulation of monotone boolean operations by group operations, inspired by barrington's work on bounded-width branching programs. the problem is motivated by the product replacement algorithm which was introduced in [comm. algebra 23 (1995) 4931-4948] and is widely used. our results show that for certain groups the probability distribution obtained by the product replacement algorithm has a bias which can be detected by a short straight line program.
single-value combinatorial auctions and implementation in undominated strategies. in this paper we are interested in general techniques for designing mechanisms that approximately maximize the social welfare in the presence of selfish rational behavior. we demonstrate our results in the setting of combinatorial auctions (ca). our first main result is a general deterministic technique to decouple the algorithmic allocation problem from the strategic aspects, by a procedure that converts any algorithm to a dominant-strategy ascending mechanism. this technique works for any single value domain, in which each agent has the same value for each desired outcome, and this value is the only private information. in particular, for "single-value cas", where each player desires any one of several different bundles but has the same value for each of them, our technique converts any approximation algorithm to a dominant strategy mechanism that almost preserves the original approximation ratio. our second main result provides the first computationally efficient deterministic mechanism for the case of single-value multi-minded bidders (with private value and private desired bundles). the mechanism achieves an approximation to the social welfare which is close to the best possible in polynomial time (unless zpp=np). this mechanism is an implementation in undominated strategies, as well as an algorithmic implementation, notions that we justify and are of independent interest.
sampling from a moving window over streaming data. we introduce the problem of sampling from a moving window of recent items from a data stream and develop two algorithms for this problem. the first algorithm, "chain-sample", extends reservoir sampling to deal with the expiration of data elements from the sample. the expected memory usage of our algorithm is o(k) when maintaining a sample of size k over a window of the n most recent elements from the data stream, and with high probability the algorithm requires no more than o(k log n) memory.when the number of elements in the window is variable, as is the case when the size of the window is defined as a time duration rather than as a fixed number of data elements, the sampling problem becomes harder. our second algorithm, "priority-sample", works even when the number of elements in the window can vary dynamically over time. with high probability, the "priority-sample" algorithm uses no more than o(k log n) memory.
approximation algorithm for embedding metrics into a two-dimensional space. in this paper, we present a polynomial-time approximation algorithm for computing an embedding of an arbitrary metric into a two-dimensional space. the algorithm finds an embedding whose additive distortion is at most c&epsilon;*, where &epsilon;* is the smallest additive distortion possible and c is an absolute constant. to our knowledge, this is the first result of this type, i.e., it gives an algorithm that finds (approximately) optimal embedding of a given distance matrix into a fixed d-dimensional space, where d < 1 is low, under any standard definition of embedding (see related work).
smaller core-sets for balls. given a set of points p &sub; rd and value ∊ > 0, an ∊-core-set s &sub; p has the property that the smallest ball containing s is an ∊-approximation of the smallest ball containing p. this paper shows that any point-set has an ∊-core-set of size [2/∊]. we also give a fast algorithm that finds this core-set. these results imply the existence of small core-sets for solving approximate k-center clustering and related problems. the sizes of these core-sets are considerably smaller than the previously known bounds, and imply faster algorithms; one such algorithm needs o(dn/∊ + (l/∊)5) time to compute an ∊-approximate minimum enclosing ball (1-center) of n points in d dimensions. a simple gradient-descent algorithm is also given, for computing the minimum enclosing ball in o(dn/∊2) time. this algorithm also implies slightly faster algorithms for computing approximately the smallest radius k-flat fitting a set of points.
approximation algorithms for low-distortion embeddings into low-dimensional spaces. we present several approximation algorithms for the problem of embedding metric spaces into a line, and into the two-dimensional plane. among other results, we give an o(&radic;n)-approximation algorithm for the problem of finding a line embedding of a metric induced by a given unweighted graph, that minimizes the (standard) multiplicative distortion. we give an improved &otilde;(n1/3) approximation for the case of metrics generated by unweighted trees. this is the first result of this type.
approximation algorithms for data placement in arbitrary networks. we study approximation algorithms for placing replicated data in arbitrary networks. consider a network of nodes with individual storage capacities and a metric communication cost function, in which each node periodically issues a request for an object drawn from a collection of uniform-length objects. we consider the problem of placing copies of the objects among the nodes such that the average access cost is minimized. our main result is a polynomial-time constant-factor approximation algorithm for this placement problem. our algorithm is based on a careful rounding of a linear programming relaxation of the problem. we also show that the data placement problem is maxsnp-hard. we extend our approximation result to a generalization of the data placement problem that models additional costs such as the cost of realizing the placement. we also show that when object lengths are non-uniform, a constant-factor approximation is achievable if the capacity at each node in the approximate solution is allowed to exceed that in the optimal solution by the length of the largest object.
loop quantum gravity. one of the great challenges facing physics today is to reconcile quantum theory and general relativity. loop quantum gravity is an approach to this challenge that incorporates quantum theory into our description of spacetime from the very start. quantum states of the geometry of space are described by "spin networks" - graphs with certain labellings of their edges and vertices. the theory predicts that geometrical quantities such as area and volume take on a discrete spectrum of possible values, and it explains the entropy of black holes by associating information to each point at which a spin network edge punctures the event horizon. i will give a nontechnical introduction to these ideas, focussing on some computational challenges that arise in studying this theory. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
counting without sampling: new algorithms for enumeration problems using statistical physics. we propose a new type of approximate counting algorithms for the problems of enumerating the number of independent sets and proper colorings in low degree graphs with large girth. our algorithms are not based on a commonly used markov chain technique, but rather are inspired by recent developments in statistical physics in connection with correlation decay properties of gibbs measures and its implications to uniqueness of gibbs measures on infinite trees, reconstruction problems and local weak convergence methods. on a negative side, our algorithms provide &isin;-approximations only to the logarithms of the size of a feasible set (also known as free energy in statistical physics). but on the positive side, unlike markov chain based algorithms, our approach provides deterministic as opposed to probabilistic guarantee on approximations. moreover, for some regular graphs we obtain explicit values for the counting problem. for example, we show that every 4-regular n-node graph with large girth has asymptotically (1.494 ...)n independent sets, and in every r-regular graph with n nodes and large girth the number of q &ge; r + 1-proper colorings is asymptotically (q(1-1/q)r/2)n for large n. in statistical physics terminology, we compute explicitly the partition function (free energy) in these cases. we extend our results to random regular graphs graphs also. the explicit results obtained in this paper would be hard to derive via markov chain sampling technique.
almost-delaunay simplices: nearest neighbor relations for imprecise points. delaunay tessellations and voronoi diagrams capture proximity relationships among sets of points in any dimension. when point coordinates are not known exactly, as in the case of 3d points representing protein atom coordinates, the delaunay tessellation may not be robust; small perturbations in the coordinates may cause the delaunay simplices to change. in this paper, we define the almost-delaunay simplices, derive some of their properties, and give algorithms for computing them, especially for neighbor analysis in three dimensions. we sketch applications in proteins that will be described more fully in a companion paper in biology. http://www.cs.unc.edu/&sim;debug/papers/almdel.
edge-connectivity augmentation with partition constraints. in the well-solved edge-connectivity augmentation problem we must find a minimum cardinality set $f$ of edges to add to a given undirected graph to make it $k$-edge-connected. this paper solves the generalization where every edge of $f$ must go between two different sets of a given partition of the vertex set. a special case of this partition-constrained problem, previously unsolved, is increasing the edge-connectivity of a bipartite graph to $k$ while preserving bipartiteness. based on this special case we present an application of our results in statics. our solution to the general partition-constrained problem gives a min-max formula for $|f|$ which includes as a special case the original min-max formula of cai and sun \cite{cai} for the problem without partition constraints. when $k$ is even the min-max formula for the partition-constrained problem is a natural generalization of \cite{cai}. however this generalization fails when $k$ is odd. we show that at most one more edge is needed when $k$ is odd and we characterize the graphs that require such an extra edge. we give a strongly polynomial algorithm that solves our problem in time $o(n(m+n\log n)$ $\log n)$. here $n$ and $m$ denote the number of vertices and distinct edges of the graph respectively. this bound is identical to the best-known time bound for the problem without partition constraints. our algorithm is based on the splitting off technique of lov\''asz, like several known efficient algorithms for the unconstrained problem. however unlike previous splitting algorithms, when $k$ is odd our algorithm must handle ``obstacles'''' that prevent all edges from being split off. our algorithm is of interest even when specialized to \nopagebreak the unconstrained problem, because it produces an asymptotically optimum number of distinct splits.
on minimizing the total flow time on multiple machines. we consider the problem of minimizing the total flow time on multiple machines with preemption, where the flow time of a job is the time spent since it arrives until it finishes. our main result is a quasi-polynomial time approximation scheme for a constant number of machines (m). the result also extends to total weighted flow time where either the job weights or the job sizes are polynomially bounded by the number of jobs (n). we also show that the dependence on m cannot be substantially improved. in particular, obtaining an o(1) approximation for the weighted case (even when all weights and sizes are polynomially bounded by n) by an algorithm with running time npolylog(n,m) would imply that np &sub; dtime(npolylog(n)).
approximating the average response time in broadcast scheduling. we consider the problem of approximating the minimum average response time in on-demand data broadcasting systems. the best approximation factors known for this problem involve resource augmentation. we provide the first non-trivial approximation factors in the absence of resource augmentation, achieving an additive o(&radic;n)-approximation, where n is the number of distinct pages. our result can be extended, for any &epsilon; > 0, to a (1 + &epsilon;)-speed, additive o(1/&epsilon;)-approximation algorithm. prior to our work, no non-trivial approximation factor was known for the case of &epsilon; < 1.
improved approximation algorithms for broadcast scheduling. we consider two scheduling problems in the broadcast setting. the first is that of minimizing the average response time of requests. for the offline version of this problem we give an algorithm with an approximation ratio of o(log2 (n)/ log log(n)), where n is the total number of pages. this substantially improves the previously best known approximation factor of o(&radic;n) for the problem [3]. our second result is for the profit maximization version of the broadcast scheduling problem. here each request has a deadline and a profit which is obtained if the request is satisfied before its deadline. the goal is to maximize the total profit. we give an algorithm with an approximation ratio of 5/6, which improves the previously best known approximation guarantee of 3/4 for the problem [13].
minimizing weighted flow time. we consider the problem of minimizing weighted flow time on a single machine in the preemptive setting. our main result is an o(log w) competitive online algorithm where the maximum to the minimum ratio of weights is w. more generally our algorithm achieves a competitive ratio of k if there are k weight classes. this gives the first o(1)-competitive algorithm for constant k. no o(1) competitive algorithm was known previously even for the special case of k = 2. these results settle a question posed by chekuri et al [5] about the existence of a "truly" online algorithm with a non-trivial competitive ratio. we also give a "semi-online" algorithm with competitive ratio o(log n + log p), where p is ratio of the maximum to minimum job size. our second result deals with the non-clairvoyant setting where the job sizes are unknown (but the weight of the jobs are known). we consider the resource augmentation model, and give a non-clairvoyant online algorithm, which if allowed a (1 + &epsilon;) speed-up, is (1 + l/&epsilon;) competitive against an optimal offline, clairvoyant algorithm.
job shop scheduling with unit processing times. we consider randomized algorithms for the preemptive job shop problem, or equivalently, the case in which all operations have unit length. we give an α-approximation for the case of two machines where α o(log m/log log m) for an arbitrary number m of machines, and the first (2 + ε)-approximation for a constant number of machines. the first result is via an approximation algorithm for a string matching problem that is of independent interest.
new approximability and inapproximability results for 2-dimensional bin packing. we study the 2-dimensional generalization of the classical bin packing problem: given a collection of rectangles of specified size (width, height), the goal is to pack these into minimum number of square bins of unit size. a long history of results exists for this problem and its special cases [3, 14, 10, 18, 9, 1, 15]. currently, the best known approximation algorithm achieves a guarantee of 1.69 in the asymptotic case (i.e. when the optimum uses a large number of bins) [1]. however, an important open question has been whether 2-dimensional bin packing is essentially similar to the 1-dimensional case in that it admits an asymptotic polynomial time approximation scheme (aptas) [8, 13] or not? we answer the question in the negative and show that the problem is apx hard in the asymptotic case. on the other hand, we give an asymptotic ptas for the special case when all the rectangles to be packed are squares (or more generally hypercubes). this improves upon the previous best known guarantee of 1.454 for d = 2 [9] and 2 - (2/3)d for d > 2 [15], and settles the approximability for this special case.
scheduling unit tasks to minimize the number of idle periods: a polynomial time algorithm for offline dynamic power management. power management policies aim at reducing the amount of energy consumed by battery operated systems, while keeping the overall performance high. in this paper we focus on shut-down mechanisms that put a system into a sleep state when it is idle. a very small amount of energy is consumed in this state but, a fixed amount of energy is required when moving the system from the sleep state to the active state. the offline version of this problem consists in scheduling a set of unit execution tasks, with release dates and deadlines, on a single machine in order to minimize the number of idle time periods. we show that this problem can be solved in polynomial time by dynamic programming.
on-line navigation in a room. we consider the problem of navigating through an unknown environment in which the obstacles are disjoint oriented rectangles enclosed in an n x n square room. the task of navigating algorithm is to reach the center of the room starting from one of the corners. while there always exists a path of length n, the best previously known navigating algorithm finds paths of length n201nn . we give an efficient deterministic algorithm which finds a path of length o(n ln n); this algorithm uses tactile information only. moreover, we prove that any deterministic algorithm can be forced to traverse a distance of &ohgr;(n ln n), even if it uses visual information.
competitive on-line switching policies. a switch, or server, serves n input queues, processing messages arriving at these queues to a single output channel. at each time slot the switch can process a single message from one of the queues. the goal of a switching policy is to minimize the size of the buffers at the input queues that maintain the messages that have not yet been processed. this is a typical on-line setting in which decisions are made based on the current state without knowledge of future events. this general scenario models multiplexing tasks in various systems such as communication networks, cable modem systems, and traffic control. traditionally, researchers analyzed the performance of a given policy assuming some distribution on the arrival rates of messages at the input queues, or by assuming that the service rate is at least the aggregate of all the input rates. we use competitive analysis to analyze switching service policies, thus avoiding any prior assumptions on the input. specifically, we show o(log n)-competitive switching policies for the problem and demonstrate matching lower bounds.
throughput maximization of real-time scheduling with batching. we consider the following scheduling with batching problem that has many applications, e.g., in multimedia-on-demand and manufacturing of integrated circuits. the input to the problem consists of n jobs and k parallel machines. each job is associated with a set of time intervals in which it can be scheduled (given either explicitly or non-explicitly), a weight, and a family. each family is associated with a processing time. jobs that belong to the same family can be batched and executed together on the same machine. the processing time of each batch is the processing time of the family of jobs it contains. the goal is to find a non-preemptive schedule with batching that maximizes the weight of the scheduled jobs. we give constant factor (4 or 4 + &epsilon;) approximation algorithms for two variants of the problem, depending on the precise representation of the input. when the batch size is unbounded and each job is associated with a time window in which it can be processed, these approximation ratios reduce to 2 and 2 + &epsilon;, respectively. we also show exact algorithms for several special cases.
competitive on-line stream merging algorithms for media-on-demand. we consider the problem of minimizing the bandwidth needed by media-on-demand servers that use stream merging. we consider the on-line case where client requests are not known ahead of time. to facilitate stream merging, clients have the ability to receive data from two streams simultaneously and can buffer up to half of a full stream. we present a new family of on-line stream merging algorithms called dynamic tree algorithms. the bandwidth requirements of the best of these, the dynamic fibonacci tree algorithms, are within a factor of the minimum between logφ(n) + o(1) and logφ(1/(2d)) + o(1) from the off-line optimal, where n is the number of requests, d is the guaranteed maximum start-up delay measured as a fraction of the time for a full stream, and φ = (1 + √5)/2. the new on-line algorithms use a dynamic fibonacci tree to control how new arrivals should merge with existing streams. empirical studies show that the dynamic fibonacci tree algorithms perform much better than indicated by the analysis.
windows scheduling problems for broadcast systems. the windows scheduling problem is defined by the positive integers n, h, and w1, ...,wn. there are n pages where the window wi is associated with page i, and h is the number of slotted channels available for broadcasting the pages. a schedule that solves the problem assigns pages to slots such that the gap between any two consecutive appearances of page i is at most wi slots. we investigate two optimization problems. (i) the optimal windows scheduling problem: given w1, ..., wn find a schedule in which h is minimized. (ii) the optimal harmonic windows scheduling problem: given h find a schedule for the windows wi = i in which n is maximized. the former is a formulation of the problem of minimizing the bandwidth in push systems that support guaranteed delay, and the latter is a formulation of the problem of minimizing the startup delay in media-on-demand systems. for the optimal windows scheduling problem we present an algorithm that constructs asymptotically close to optimal schedules, and for the optimal harmonic windows scheduling problem we show how to achieve the largest known n's for all values of h.
scheduling techniques for media-on-demand. broadcasting popular media to clients is the ultimate scalable solution for media-on-demand. recently, it was shown that if clients can receive data at a rate faster than what they need for playback and if they can store later parts of the media in their buffers, then much higher scalability may be obtained. in the paper we focus on scheduling problems arising from these new systems for media-on-demand.for given amount of bandwidth, we improve the guaranteed start-up delay time for an uninterrupted playback. we achieve our results by introducing two techniques. in the first, the media is arranged on the channels such that clients gain from buffering later parts of the transmission before the actual start of the playback. in the second, segments of different media may be mixed together on the same channel. we introduce a simple class of recursive round-robin scheduling algorithms that implement our techniques.our results improve the best known asymptotic results. moreover, our scheduling algorithms outperform known results for "practical" values for number of media and number of broadcasting channels. for some specific small values, we present hand designed solutions that are better than those achieved by our algorithms.
windows scheduling as a restricted version of bin packing. given is a sequence of n positive integers w1;w2....,wn that are associated with the items 1, 2....n respectively. in the windows scheduling problem, the goal is to schedule all the items (equal length information pages) on broadcasting channels such that the gap between two consecutive appearances of page i on any of the channels is at most wi slots (a slot is the transmission time of one page). in the unit fractions bin packing problem, the goal is to pack all the items in bins of unit size where the size (width) of item i is 1/wi. the optimization objective is to minimize the number of channels or bins. in the off-line setting the sequence is known in advance whereas in the on-line setting the items arrive in order and assignment decisions are irrevocable. since a page requires at least 1=wi of the channel's bandwidth, it follows that windows scheduling without migration (all broadcasts of a page must be from the same channel) is a restricted version of unit fractions bin packing.let h = [&sigma;ni = 1 (1/wi)] be the obvious bandwidth lower bound on the required number of bins (channels). previously an h + o(ln h) off-line algorithm for the windows scheduling problem was known. this paper presents an h + 1 off-line algorithm to the unit fractions bin packing problem. in the on-line setting, this paper presents an h + o(&radic;h) algorithm to both problems where the one for the unit fractions bin packing problem is simpler. on the other hand, this paper shows that already for the unit fractions bin packing problem, any on-line algorithm must use at least h + &omega; (ln h) bins.
guaranteeing fair service to persistent dependent tasks. we introduce a new scheduling problem that is motivated by applications in the area of access and flow control in high-speed and wireless networks. an instance of the problem consists of a set of persistent tasks that have to be scheduled repeatedly. each task has a demand to be scheduled "as often as possible." there is no explicit limit on the number of tasks that can be scheduled concurrently. however, such limits are imposed implicitly because some tasks may be in conflict and cannot be scheduled simultaneously. these conflicts are presented in the form of a conflict graph. we define parameters which quantify the fairness and regularity of a given schedule. we then proceed to show lower bounds on these parameters and present fair and efficient scheduling algorithms for the case where the conflict graph is an interval graph. some of the results presented here extend to the case of perfect graphs and circular-arc graphs as well.
scheduling split intervals. we consider the problem of scheduling jobs that are given as groups of non-intersecting segments on the real line. each job jj is associated with an interval, ij, which consists of up to t segments, for some t &ge; 1, a positive weight, wj, and two jobs are in conflict if any of their segments intersect. such jobs show up in a wide range of applications, including the transmission of continuous-media data, allocation of linear resources (e.g. bandwidth in linear processor arrays), and in computational biology/geometry. the objective is to schedule a subset of non-conflicting jobs of maximum total weight.in a single machine environment, our problem can be formulated as the problem of finding a maximum weight independent set in a t-interval graph (the special case of t = 1 is an ordinary interval graph). we show that, for t &ge; 2, this problem is apx-hard, even for highly restricted instances. our main result is a 2t-approximation algorithm for general instances, based on a novel fractional version of the local ratio technique. previously, the problem was considered only for proper union graphs, a restricted subclass of t-interval graphs, and the approximation factor achieved was (2t - 1 + 1/2t). a bi-criteria polynomial time approximation scheme (ptas) is developed for the subclass of t-union graphs.in the online case, we consider uniform weight jobs that consist of at most two segments. we show that when the resulting 2-interval graph is proper, a simple greedy algorithm is 3-competitive, while any randomized algorithm has competitive ratio at least 2.5. for general instances, we give a randomized o(log2 r)-competitive (or o((log r)2+&epsilon;)-competitive) algorithm, where r is the known (unknown) ratio between the longest and the shortest segment in the input sequence.
incentive-compatible online auctions for digital goods. goldberg et al. [6] recently began the study of incentive-compatible auctions for digital goods, that is, goods which are available in unlimited supply. many digital goods, however, such as books, music, and software, are sold continuously, rather than in a single round, as is the case for traditional auctions. hence, it is important to consider what happens in the online version of such auctions. we define a model for online auctions for digital goods, and within this model, we examine auctions in which bidders have an incentive to bid their true valuations, that is, incentive-compatible auctions. since the best offline auctions achieve revenue comparable to the revenue of the optimal fixed pricing scheme, we use the latter as our benchmark. we show that deterministic auctions perform poorly relative to this benchmark, but we give a randomized auction which is within a factor o(exp&radic;log log h) of the benchmark, where h is the ratio between the highest and lowest bids. as part of this result, we also give a new offline auction, which improves upon the previously best auction in a certain class of auctions for digital goods. we also give lower bounds for both randomized and deterministic online auctions for digital goods.
reductions in streaming algorithms, with an application to counting triangles in graphs. we introduce reductions in the streaming model as a tool in the design of streaming algorithms. we develop the concept of list-efficient streaming algorithms that are essential to the design of efficient streaming algorithms through reductions.our results include a suite of list-efficient streaming algorithms for basic statistical primitives. using the reduction paradigm along with these tools, we design streaming algorithms for approximately counting the number of triangles in a graph presented as a stream.a specific highlight of our work is the first algorithm for the number of distinct elements in a data stream that achieves arbitrary approximation factors. (independently, trevisan [tre01] has solved this problem via a different approach; our algorithm has the advantage of being list-efficient.)
on the discrete bak-sneppen model of self-organized criticality. we propose a discrete variant of the bak-sneppen model for self-organized criticality. in this process, a configuration is an n-bit word, and at each step one chooses a random bit of minimum value (usually a zero) and replaces it and its two neighbors by independent bernoulli variables with parameter p. we prove bounds on the average number of ones in the stationary distribution and present experimental results.
adaptive intersection and t-threshold problems. consider the problem of computing the intersection of k sorted sets. in the comparison model, we prove a new lower bound which depends on the non-deterministic complexity of the instance, and implies that the algorithm of demaine, l&oacute;pez-ortiz and munro [2] is usually optimal in this "adaptive" sense. we extend the lower bound and the algorithm to the t-threshold problem, which consists in finding the elements which are in at least t of the k sets. these problems are motivated by boolean queries in text database systems.
a lower bound for hellbronn's triangle problem in dimensions. in this paper we show a lower bound for the generalization of heilbronn's triangle problem to d dimensions; namely, we show that there exists a set s of n points in the d-dimensional unit cube so that every d+1 points of s define a simplex of volume $\omega (\frac{1}{n^d})$. we also show a constructive incremental positioning of n points in a unit 3-cube for which every tetrahedron defined by four of these points has volume $\omega (\frac{1}{n^4})$.
straight-skeleton based contour interpolation. in this paper we present an efficient method for interpolating a piecewise-linear surface between two parallel slices, each consisting of an arbitrary number of (possibly nested) polygons that define 'material' and 'nonmaterial' regions. this problem has applications to medical imaging, geographic information systems, etc. our method is fully automatic and is guaranteed to produce non-self-intersecting surfaces in all cases regardless of the number of contours in each slice, their complexity and geometry, and the depth of their hierarchy of nesting. the method is based on computing cells in the overlay of the slices, that form the symmetric difference between them. then, the straight skeletons of the selected cells guide the triangulation of these cells. finally, the resulting triangles are lifted up in space to form an interpolating surface. we provide some experimental results on various complex examples to show the good and robust performance of our algorithm.
dynamic construction of bluetooth scatternets of fixed degree and low diameter. bluetooth is a promising recent radio technology for ad hoc networking. bluetooth networks are based on connecting together piconets, to form a scatternet. the structure of the scatternet, and the way the scatternet is built and maintained, are not part of the bluetooth specifications, but have a tremendous impact on the performance of the network. we present an efficient distributed algorithm for bluetooth scatternet construction. the resulting scatternet is scalable and our construction is dynamic in the sense that nodes can join and leave the network at their convenience. for fixed constant degree of nodes, the resulting diameter is polylogarithmic in the size of the network, and the connectivity of the masters is high. we also give a routing protocol adapted to the specific scatternet topology returned by our algorithm. this protocol does not require complicated path-discovery methods, but is based on a simple virtual labeling of the devices participating in the scatternet.
on page migration and other related task systems. this paper is concerned with the page migration (or file migration) problem (black and sleator, technical report cmu-cs-89-201, department of computer science, carnegie-mellon university, 1989) as part of a large class of on-line problems. the page migration problem deals with the management of pages residing in a network of processors. in the classical problem there is only one copy of each page which is accessed by different processors over time. the page is allowed to be migrated between processors. however a migration incurs higher communication cost than an access (proportionally to the page size). the problem is that of deciding when and where to migrate the page in order to lower access costs. a more general setting is the k-page migration problem where we wish to maintain k copies of the page. the page migration problems are concerned with a dilemma common to many on-line problems: determining when it is beneficial to make configuration changes. we deal with the relaxed task systems model which captures a large class of problems of this type, that can be described as the generalization of some original task system problem (borodin et al., j. acm 39(4) (1992) 745-763). given a c-competitive algorithm for a task system we show how to obtain a deterministic o(c2) and randomized o(c) competitive algorithms for the corresponding relaxed task system. the result implies deterministic algorithms for k-page migration by using k-server (manasse et al., j. algorithms 11(2) (1990) 208-230) algorithms, and for network leasing by using generalized steiner tree algorithms (awerbuch et al., proc 7th ann. acm-siam symp. on discrete algorithms, january 1996, pp. 68-74), as well as providing solutions for natural generalizations of other problems (e.g. storage rearrangement (fiat et al., proc. 36th ann. ieee symp. on foundations of computer science, october 1995, pp. 392-403)). we further study some special cases of the k-page migration problem and get optimal deterministic algorithms. for the classical page migration problem we present a deterministic algorithm that achieves a competitive ratio of ~ 4:086, improving upon the previously best competitive ratio of 7 (awerbuch et al., proc. 25th acm symp. on theory of computing, may 1993, pp. 164-173). (the current lower bound on the problem is ~ 3:148 (chrobak et al., j. algorithms 24(1) (1997) 124-157). copyright 2001 elsevier science b.v.
multiprocessor scheduling with rejection. we consider a version of multiprocessor scheduling with the special feature that jobs may be rejected at a certain penalty. an instance of the problem is given by $m$ identical parallel machines and a set of $n$ jobs, with each job characterized by a processing time and a penalty. in the on-line version the jobs become available one by one and we have to schedule or reject a job before we have any information about future jobs. the objective is to minimize the makespan of the schedule for accepted jobs plus the sum of the penalties of rejected jobs.the main result is a $1+\phi\approx 2.618$ competitive algorithm for the on-line version of the problem, where $\phi$ is the golden ratio. a matching lower bound shows that this is the best possible algorithm working for all $m$. for fixed $m$ we give improved bounds; in particular, for $m=2$ we give a $\phi\approx 1.618$ competitive algorithm, which is best possible.for the off-line problem we present a fully polynomial approximation scheme for fixed $m$ and a polynomial approximation scheme for arbitrary $m$. moreover, we present an approximation algorithm which runs in time $o(n\log n)$ for arbitrary $m$ and guarantees a $2-\frac{1}{m}$ approximation ratio.
multi-embedding and path approximation of metric spaces. metric embeddings have become a frequent tool in the design of algorithms. the applicability is often dependent on how high the embedding's distortion is. for example embedding into ultrametrics (or arbitrary trees) requires linear distortion. using probabilistic metric embeddings, the bound reduces to o(log nlog logn). yet, the lower bound is still logarithmic.we make a step further in the direction of bypassing this difficulty. we define "multi-embeddings" of metric spaces where a point is mapped onto a set of points, while keeping the target metric being of polynomial size and preserving the distortion of paths. the distortion obtained with such multi-embeddings into ultrametrics is at most o(log &delta; log log &delta;) where &delta; is the (normalized) diameter, and probabilistically o(log n log log log n). in particular, for expander graphs, we are able to obtain constant distortions embeddings into trees vs. the &omega;(logn) lower bound for all previous notions of embeddings.we demonstrate the algorithmic application of the new embeddings by obtaining improvements for two well-known problems: group steiner tree and metrical task systems.
dimension reduction for ultrametrics. we prove that an ultrametric on n points can be embedded in ldp with distortion at most 1 + ε, and d = o(ε-2 log n). this bound matches the best known bound for the special case of an equilateral space.
randomized -server algorithms for growth-rate bounded graphs. the k-server problem is a fundamental online problem where k mobile servers should be scheduled to answer a sequence of requests for points in a metric space as to minimize the total movement cost. while the deterministic competitive ratio is at least k, randomized k-server algorithms have the potential of reaching o(k) competitive ratios. this goal may be approached by using probabilistic metric approximation techniques. this paper gives the first results in this direction obtaining o(k) competitive ratio for a natural class of metric spaces, including d-dimensional grids, and wide range of k. prior to this work no result of this type was known beyond results for specific metric spaces.
kinetic collision detection between two simple polygons. we design a kinetic data structure for detecting collisions between two simple polygons in motion. in order to do so, we create a planar subdivision of the free space between the two polygons, called the external relative geodesic triangulation, which certifies their disjointness. we show how this subdivision can be maintained as a kinetic data structure when the polygons are moving, and analyze its performance in the kinetic setting.
maintaining all-pairs approximate shortest paths under deletion of edges. we present a hierarchical scheme for efficiently maintaining all-pairs approximate shortest paths in undirected unweighted graphs under deletions of edges.an &alpha;-approximate shortest-path between two vertices is a path of length at-most &alpha; times the length of the shortest path. for maintaining &alpha;-approximate shortest paths for all pairs of vertices separated by distance &le; d in a graph of n vertices, we present the first o(nd) update time algorithm based on our hierarchical scheme. in particular, the update time per edge deletion achieved by our algorithm is &otilde;(min{&radic;nd,(nd)2/3}) for 3-approximate shortest-paths, and &otilde;(min{&radic;nd,(nd)4/7}) for 7-approximate shortest-paths. for graphs with &theta;(n2) edges, we achieve even further improvement in update time : &otilde;(&radic;nd) for 3-approximate shortest-paths, and &otilde;(3&radic;nd2) for 5-approximate shortest-paths.for maintaining all-pairs approximate shortest-paths, weimprove the previous &otilde;(n3/2)bound on the update time per edge deletion for approximation factor &ge; 3. in particular, update time achieved by our algorithm is &otilde;(n10/9) for 3-approximate shortest-paths, &otilde;(n14/13) for 5-approximate shortest-paths, and &otilde;(n28/27) for 7-approximate shortest-paths.all our algorithms achieve optimal query time and are simple to implement.
new constructions of (alpha, beta)-spanners and purely additive spanners. an (&alpha;, &beta;)-spanner of an unweighted graph g is a subgraph h that approximates distances in g in the following sense. for any two vertices u, v: &delta;h (u, v) &le; &alpha;&delta;g(u, v) + &beta;, where &delta;g is the distance w.r.t. g. it is well known that there exist (multiplicative) (2k - 1, 0)-spanners of size o(n1+1/k) and that there exist (purely additive) (1, 2)-spanners of size o(n3/2). however no other (1, o(1))-spanners are known to exist.in this paper we develop a couple new techniques for constructing (&alpha;, &beta;)-spanners. the first result is a purely additive (1, 6)-spanner of size o(n4/3). our construction algorithm can be understood as an economical agent that assigns costs and values to paths in the graph, purchasing affordable paths and ignoring expensive ones, which are intuitively well-approximated by paths already purchased. this general approach should lead to new spanner constructions.the second result is a truly simple linear time construction of (k, k - 1)-spanners with size o(n1+1/k). in a distributed network the algorithm terminates in a constant number of rounds and has expected size o(n1+1/k). the new idea here is primarily in the analysis of the construction. we show that a few simple and local rules for picking spanner edges induce seemingly coordinated global behavior.
approximate distance oracles for unweighted graphs in õ(n) time. let g(v, e) be an undirected weighted graph with |v| = n, |e| = m. recently thorup and zwick introduced a remarkable data-structure that stores all pairs approximate distance information implicitly in o(n2) space, and yet answers any approximate distance query in constant time. they named this data-structure approximate distance oracle because of this feature. given an integer k < 1, a (2k-1)-approximate distance oracle requires o(kn1+1/k) space and answers a (2k-1)-approximate distance query in o(k) time. thorup and zwick showed that a (2k - 1)-approximate distance oracle can be computed in o(kmn1/k) time, and posed the following question : can (2k - 1)-approximate distance oracle be computed in &otilde;(n2) time?in this paper, we answer their question in affirmative for unweighted graphs. we present an algorithm that computes (2k -1)-approximate distance oracle for a given unweighted graph in &otilde;(n2) time. one of the new ideas used in the improved algorithm also leads to the first linear time algorithm for computing an optimal size (2, 1)-spanner of an unweighted graph.
oblivious string embeddings and edit distance approximations. we introduce an oblivious embedding that maps strings of length n under edit distance to strings of length at most n/r under edit distance for any value of parameter r. for any given r, our embedding provides a distortion of &otilde;(r1+&mu;) for some &mu; = o(1), which we prove to be (almost) optimal. the embedding can be computed in &otilde;(21/&mu;n) time.we also show how to use the main ideas behind the construction of our embedding to obtain an efficient algorithm for approximating the edit distance between two strings. more specifically, for any 1 > &epsilon; &ge; 0, we describe an algorithm to compute the edit distance d(s, r) between two strings s and r of length n in time &otilde;(n1+&epsilon;), within an approximation factor of min{n1-&epsilon;/3+o(1), (d(s, r/n&epsilon;)1/2+o(1)}. for the case of &epsilon; = 0, we get a &otilde;(n)-time algorithm that approximates the edit distance within a factor of min{n1/3+o(1), d(s, r)1/2+o(1)}, improving the recent result of bar-yossef et al. [2].
reconstructing strings from random traces. we are given a collection of m random subsequences (traces) of a string t of length n where each trace is obtained by deleting each bit in the string with probability q. our goal is to exactly reconstruct the string t from these observed traces. we initiate here a study of deletion rates for which we can successfully reconstruct the original string using a small number of samples. we investigate a simple reconstruction algorithm called bitwise majority alignment that uses majority voting (with suitable shifts) to determine each bit of the original string. we show that for random strings t, we can reconstruct the original string (w.h.p.) for q = o(1/ log n) using only o(log n) samples. for arbitrary strings t, we show that a simple modification of bitwise majority alignment reconstructs a string that has identical structure to the original string (w.h.p.) for q = o(1/n1/2+ε) using o(1) samples. in this case, using o(n log n) samples, we can reconstruct the original string exactly. our setting can be viewed as the study of an idealized biological evolutionary process where the only possible mutations are random deletions. our goal is to understand at what mutation rates, a small number of observed samples can be correctly aligned to reconstruct the parent string.in the process of establishing these results, we show that bitwise majority alignment has an interesting self-correcting property whereby local distortions in the traces do not generate errors in the reconstruction and eventually get corrected.
dynamic point location in general subdivisions. the dynamic planar point location problem is the task of maintaining a dynamic set s of n non-intersecting, except possibly at endpoints, line segments in the plane under the following operations: &bull;locate(q point): report the segment immediately above q, i.e., the first segment intersected by an upward vertical ray starting at q; &bull;insert(s segment): add segment s to the collection s segments; &bull;delete(s segment): remove segment s from the collection s of segments. we present a solution which requires space o(n), has query and insertion time o(log n loglog n) and deletion time o(log2 n). a query time below o(log2 n) was previously only known for monotone subdivisions and horizontal segments and required non-linear space.
sharing the cost more efficiently: improved approximation for multicommodity rent-or-buy. in the multicommodity rent-or-buy (mrob) network design problems, we are given a network together with a set of k terminal pairs (s1, t1), &hellip;, (sk, tk. the goal is to provision the network so that a given amount of flow can be shipped between si and ti for all 1 &le; i &le; k simultaneously. in order to provision the network, one can either rent capacity on edges at some cost per unit of flow, or buy them at some larger fixed cost. bought edges have no incremental, flow-dependent cost. the overall objective is to minimize the total provisioning cost. recently, gupta et al. [2003a] presented a 12-approximation for the mrob problem. their algroithm chooses a subset of the terminal pairs in the graph at random and then buys the edges of an approximate steiner forest for these pairs. this technique had previously been introduced [gupta et al. 2003b] for the single-sink rent-or-buy network design problem. in this article we give a 6.828-approximation for the mrob problem by refining the algorithm of gupta et al. and simplifying their analysis. the improvement in our article is based on a more careful adaptation and simplified analysis of the primal-dual algorithm for the steiner forest problem due to agrawal et al. [1995]. our result significantly reduces the gap between the single-sink and multisink case.
efficient proper 2-coloring of almost disjoint hypergraphs. let a be an n-uniform hypergraph. assume that the maximum degree of a is d = d(a) (local condition), and |a| = n = n(a) (global condition). by the lov&aacute;sz local lemma (l.l.l.), if d < 2n/8n, then a has a proper 2-coloring (i.e. there is no monochromatic edge) independently of the value of n (n can be infinite). unfortunately l.l.l. is a pure existence argument which does not give any clue of how to find a proper 2-coloring. a hypergraph with the property that any two edges have at most one point in common is called almost disjoint (e.g. a family of lines). assume that a is an n-uniform almost disjoint hypergraph. in this special case, we provide a polynomial time (in terms of n) algorithm to find a proper 2-coloring under the slightly weaker condition that d < (2 - &delta;)n and n is less than a doubly exponential function of n.
computing equilibria for congestion games with (im)perfect information. we study algorithmic questions concerning a basic microeconomic congestion game in which there is a single provider that offers a service to a set of potential customers. each customer has a particular demand of service and the behavior of the customers is determined by utility functions that are non-increasing in the congestion. customers decide whether to join or leave the service based on the experienced congestion and the offered prices. following standard game theory, we assume each customer behaves in the most rational way. if the prices of service are fixed, then such a customer behavior leads to a pure, not necessarily unique nash equilibrium among the customers. in order to evaluate marketing strategies, the service provider is interested in estimating its revenue under the best and worst customer equilibria. we study the complexity of this problem under different models of information available to the provider.&bull;we first consider the classical model in which the provider has perfect knowledge of the behavior of all customers. we present a complete characterization of the complexity of computing optimal pricing strategies and of computing best and worst equilibria. basically, we show that most of these problems are inapproximable in the worst case but admit an "average-case fpas." our average case analysis covers general distributions for customer demands and utility thresholds. we generalize our analysis to robust equilibria in which players change their strategies only when this promises a significant utility improvement.&bull;we extend our analysis to a more realistic model in which the provider has incomplete information. following the game theoretic framework of bayesian games introduced by harsanyi, we assume that the provider is aware of probability distributions describing the behavior of the customers and aims at estimating its expected revenue under best and worst equilibria. somewhat counterintuitive, we obtain an fpras for the equilibria problem in the model with imperfect information although the problem with perfect information is inapproximable under the worst case measures. in particular, the worst case complexity of the considered stochastic equilibria problems increases with the precision of the available knowledge.
probabilistic analysis of knapsack core algorithms. we study the average-case performance of algorithms for the binary knapsack problem. our focus lies on the analysis of so-called core algorithms, the predominant algorithmic concept used in practice. these algorithms start with the computation of an optimal fractional solution that has only one fractional item and then they exchange items until an optimal integral solution is found. the idea is that in many cases the optimal integral solution should be close to the fractional one such that only a few items need to be exchanged. despite the well known hardness of the knapsack problem on worst-case instances, practical studies show that knapsack core algorithms can solve large scale instances very efficiently. for example, they exhibit almost linear running time on purely random inputs.in this paper, we present the first theoretical result on the running time of core algorithms that comes close to the results observed in practical experiments. we prove an upper bound of o(npolylog(n)) on the expected running time of a core algorithm on instances with n items whose profits and weights are drawn independently, uniformly at random. a previous analysis on the average-case complexity of the knapsack problem proves a running time of o(n4), but for a different kind of algorithms. the previously best known upper bound on the running time of core algorithms is polynomial as well. the degree of this polynomial, however, is at least a large three digit number. in addition to uniformly random instances, we investigate harder instances in which profits and weights are pairwise correlated. for this kind of instances, we can prove a tradeoff describing how the degree of correlation influences the running time.
the knuth-yao quadrangle-inequality speedup is a consequence of total-monotonicity. there exist several general techniques in the literature for speeding up naive implementations of dynamic programming. two of the best known are the knuth-yao quadrangle inequality speedup and the smawk algorithm for finding the row-minima of totally monotone matrices. although both of these techniques use a quadrangle inequality and seem similar, they are actually quite different and have been used differently in the literature. in this article we show that the knuth-yao technique is actually a direct consequence of total monotonicity. as well as providing new derivations of the knuth-yao result, this also permits to solve the knuth-yao problem directly using the smawk algorithm. another consequence of this approach is a method for solving online versions of problems with the knuth-yao property. the online algorithms given here are asymptotically as fast as the best previously known static ones. for example, the knuth-yao technique speeds up the standard dynamic program for finding the optimal binary search tree of n elements from &theta;(n3) down to o(n2), and the results in this article allow construction of an optimal binary search tree in an online fashion (adding a node to the left or the right of the current nodes at each step) in o(n) time per step.
a constant-factor approximation algorithm for optimal terrain guarding. we present the first constant-factor approximation algorithm for a non-trivial instance of the optimal guarding (coverage) problem in polygons. in particular, we give an o(1)-approximation algorithm for placing the fewest point guards on a 1.5d terrain, so that every point of the terrain is seen by at least one guard. while polylogarithmic-factor approximations follow from set cover results, our new results exploit geometric structure of terrains to obtain a substantially improved approximation algorithm.
a locality-preserving cache-oblivious dynamic dictionary. this paper presents a simple dictionary structure designed for a hierarchical memory. the proposed data structure is cache-oblivious and locality-preserving. a cache-oblivious data structure has memory performance optimized for all levels of the memory hierarchy even though it has no memory-hierarchy-specific parameterization. a locality-preserving dictionary maintains elements of similar key values stored close together for fast access to ranges of data with consecutive keys.the data structure presented here is a simplification of the cache-oblivious b-tree of bender, demaine, and farach-colton. the structure supports search operations on n data items using o(logb n + 1) block transfers at a level of the memory hierarchy with block size b. insertion and deletion operations use o(logbn + log2 n/b + 1) amortized block transfers. finally, the data structure returns all k data items in a given search range using o(logb n + k/b + 1) block transfers.this data structure was implemented and its performance was evaluated on a simulated memory hierarchy. this paper presents the results of this simulation for various combinations of block and memory sizes.
improved bounds on sorting with length-weighted reversals. we study the problem of sorting integer sequences and permutations by length-weighted reversals. we consider a wide class of cost functions, namely f(l) = l&alpha; for all &alpha; &ge; 0, where l is the length of the reversed subsequence. we present tight or nearly tight upper and lower bounds on the worst-case cost of sorting by reversals. then we develop algorithms to approximate the optimal cost to sort a given input. furthermore, we give polynomial-time algorithms to determine the optimal reversal sequence for a restricted but interesting class of sequences and cost functions. our results have direct application in computational biology to the field of comparative genomics.
improved algorithms for stretch scheduling. we study the basic problem of preemptive scheduling of an online stream of jobs on a single processor. the ith job arrives at time r(i) and has processing time p(i) that is known at the time of its arrival. if c(i) is the completion time of job i, then the flow time is c(i) - r(i) and stretch of a job is the ratio of its flow time to its processing time; that is, c(i)-r(i)/p(i). flow time considers the time a job is in the system regardless of the service it requested; the stretch measure relies on the intuition that a job that requested long service must be prepared to wait longer than the small jobs.in this paper, we present improved algorithmic results in stretch scheduling. we first show that a simple online algorithm that takes amortized o(1) time per job arrival is o(&delta;1/2)-competitive with respect to maximum stretch, where &delta; is the ratio of the largest processing time to the smallest processing time. this is significantly more efficient than the best known online algorithm for this problem which takes &omega;(n2) per scheduling step (n is the number of jobs seen thus far). we next present a polynomial time approximation scheme for average stretch scheduling. the previous best polynomial-time algorithm is the shortest remaining processing time algorithm, which achieves a 2-approximation. finally, we consider the impact of incomplete knowledge of job sizes on the average stretch performance of scheduling algorithms. we show that a constant-factor competitive ratio for average stretch is achievable even if the processing times (or remaining processing times) of jobs are known only to within a constant factor of accuracy.
distributed selfish load balancing. suppose that a set of $m$ tasks are to be shared as equally as possible among a set of $n$ resources. a game-theoretic mechanism to find a suitable allocation is to associate each task with a &ldquo;selfish agent&rdquo; and require each agent to select a resource, with the cost of a resource being the number of agents that select it. agents would then be expected to migrate from overloaded to underloaded resources, until the allocation becomes balanced. recent work has studied the question of how this can take place within a distributed setting in which agents migrate selfishly without any centralized control. in this paper we discuss a natural protocol for the agents which combines the following desirable features: it can be implemented in a strongly distributed setting, uses no central control, and has good convergence properties. for $m \gg n$, the system becomes approximately balanced (an $\epsilon$-nash equilibrium) in expected time $o(\log \log m)$. we show using a martingale technique that the process converges to a perfectly balanced allocation in expected time $o(\log \log m + n^4)$. we also give a lower bound of $\omega(\max\{\log \log m, n\})$ for the convergence time.
vertical ray shooting and computing depth orders for fat objects. we present new results for three problems dealing with a set p of n convex constant-complexity fat polyhedra in 3-space. (i) we describe a data structure for vertical ray shooting in p that has o(log2 n) query time and uses o(n log2 n) storage. (ii) we give an algorithm to compute in o(n log3 n) time a depth order on p, if it exists. (iii) we give an algorithm to verify in o(n log4 n) time whether a given order on p is a valid depth order. all three results improve on previous results.
the fourth moment method. higher moment analysis has typically been used to upper bound certain functions. in this paper, we introduce a new combinatorial method to lower bound the expectation of the absolute value of a random variable x by the expectation of a quartic in x. in the special case where we are looking at the absolute value of a (weighted) sum of {-1,+1} unbiased random variables, we achieve tight bounds, using only a fourth moment, for the total discrepancy of a set system. because the fourth moment depends only on 4-wise independence, our bounds will hold over polynomially sized distributions, and so these bounds will be directly applicable in removing randomness to obtain nc algorithms. we obtain the first nc algorithms for the problems of total discrepancy, maximum acyclic subgraph, tournament ranking, the gale--berlekamp switching game, and edge discrepancy. we show that for most of these applications it is truly necessary to consider a fourth moment by exhibiting a 3-wise independent distribution which does not achieve the required bounds. our method is strong enough to give a new combinatorial bound on tournament ranking.
on the spread of viruses on the internet. we analyze the contact process on random graphs generated according to the preferential attachment scheme as a model for the spread of viruses in the internet. we show that any virus with a positive rate of spread from a node to its neighbors has a non-vanishing chance of becoming epidemic. quantitatively, we discover an interesting dichotomy: for a virus with effective spread rate &lambda;, if the infection starts at a typical vertex, then it develops into an epidemic with probability &lambda;&theta;(log(1/&lambda;)/log log(1/&lambda;), but on average the epidemic probability is &lambda;&theta;(1).
efficient dynamic traitor tracing. the notion of traitor tracing was introduced by chor, fiat, and naor [tracing traitors, lecture notes in comput. sci. 839, 1994, pp. 257--270] in order to combat piracy scenarios. recently, fiat and tassa [ tracing traitors, lecture notes in comput. sci. 1666, 1999, pp. 354--371] proposed a dynamic traitor tracing scenario, in which the algorithm adapts dynamically according to the responses of the pirate. let n be the number of users and p the number of traitors.our main result is an algorithm which locates p traitors, even if p is unknown, using a watermarking alphabet of size p+1 and an optimal number of $\theta(p^2 + p\log n)$ rounds. this improves the exponential number of rounds achieved by fiat and tassa in this case. we also present two algorithms that use a larger alphabet: for an alphabet of size p+c+1, $c\geq1$, an algorithm that uses o(p2/c+ p log n) rounds; for an alphabet of size pc+1, an algorithm that uses o(p logcn) rounds.our final result is a lower bound of $\omega(p^2/c+p\log_{c+1}n)$ rounds for any algorithm that uses an alphabet of size p+c, assuming that p is not known in advance.
slice and dice: a simple, improved approximate tiling recipe. we are given a two dimensional array a[1 &sdot;&sdot;&sdot; n, 1 &sdot;&sdot;&sdot; n] where each a[i, j] stores a non-negative number. a (rectangular) tiling of a is a collection of rectangular portions a[l &sdot;&sdot;&sdot; r, t &sdot;&sdot;&sdot; b], called tiles, such that no two tiles overlap and each entry a[i, j] is contained in a tile. the weight of a tile is the sum of all array entries in it.in the max-min problem, we are given a weight bound w and our goal is to find a tiling such that (a) each tile is of weight at least w (the min condition) and (b) the number of tiles is maximized (the max condition). in the min-max problem, we are given a weight bound w again and our goal is to find a tiling such that (a) each tile has weight at most w and (b) the number of tiles is minimized. these two basic problems have many variations depending on the weight functions, whether some areas of a must not be covered, or whether some portion of a may be discarded, etc. these problems are not only natural combinatorial problems, but also arise in a plethora of applications, e.g., in databases and data mining, video compression, load balancing, building index structures, manufacturing and so forth.both the above tiling problems (as well as all of their variations relevant to this paper) are known to be np-hard. in this paper, we present approximations algorithms for solving these problems based on epicurean methods : variations of a basic slice-and-dice technique. surprisingly, these simple algorithms yield small constant factor approximations for all these problems. for some of the problems, our results are the first known approximations; for others, our results improve the known algorithms significantly in approximation bounds and/or running time. of independent interest are the tight bounds we show for sizes of the binary space partition trees for isothetic rectangles.
improved approximation algorithms for rectangle tiling and packing. we provide improved approximation algorithms for several rectangle tiling and packing problems (rtile, drtile and d-rpack) studied in the literature. our algorithms are highly efficient since their running times are near-linear in the space input size rather than in the domain size. in addition, we improve the best known approximation ratios, in some cases quite significantly.
approximating minimum unsatisfiability of linear equations. we consider the following optimization problem: given a system of m linear equations in n variables over a certain field, a feasible solution is any assignment of values to the variables, and the minimized objective function is the number of equations that are not satisfied. for the case of the finite field gf[2], this problem is also known as the nearest codeword problem. in this note we show that for any constant c there exists a randomized polynomial time algorithm that approximates the above problem, called the minimum unsatisfiability of linear equations (min-unsatisfy for short), with n/(c log n) approximation ratio. our results hold for any field in which systems of linear equations can be solved in polynomial time.
optimizing misdirection. in this paper we consider the following problem. given a (d + 1)-claw free graph g = (v, e, w) where w : v &rarr; r+, maximize w(a) where a is an independent set in g. our focus is to minimize the approximation ratio (optimum/obtained) in polynomial time that does not depend on d. our approach is to apply local improvements of size 2, using a "misdirected" criterion, i.e. w&alpha;(a) rather than w(a). we find the optimal value of &alpha; for every d, and the resulting ratio is roughly 0.667d for d = 3, 0.651d for d = 4 and 0.646d for d > 4.
8/7-approximation algorithm for (1, 2)-tsp. we design a polynomial time 8/7-approximation algorithm for the traveling salesman problem in which all distances are either one or two. this improves over the best known approximation factor for that problem. as a direct application we get a 7/6-approximation algorithm for the maximum path cover problem, similarly improving upon the best known approximation factor for that problem. the result depends on a new method of consecutive path cover improvements and on a new analysis of certain related color alternating paths. this method could be of independent interest.
improved approximations for the steiner tree problem. for a set s contained in a metric space, a steiner tree of s is a tree that connects the points in s. finding a minimum cost steiner tree is an np-hard problem in euclidean and rectilinear metrics as well as in graphs. we give an approximation algorithm and show that the worst-case ratio of the cost of our solutions to the optimal cost is better than previously known ratios in graphs, and in rectilinear metric on the plane. our method offers a trade-off between the running time and the ratio; on one hand it always allows to improve the ratio, on the other it allows to obtain previously known ratios with much greater efficiency. we use properties of optimal rectilinear steiner trees to obtain significantly better ratio and running time in rectilinear metric.
computing the depth of a flat. we compute the regression depth of a k-flat in a set of n points in rd, in time &ogr;(nd-2 + n log n) for 1 &lne; k &lne; d - 2. this contrasts with a bound of &ogr;(nd-1 + n log n) when k = 0 or k = d - 1.
two tricks to triangulate chordal probe graphs in polynomial time. a graph g = (v,e) is chordal probe if its vertices can be partitioned into two sets p (probes) and n (non-probes) where n is a stable set and such that g can be extended to a chordal graph by adding edges between non-probes. the study of chordal probe graphs was originally motivated as a generalization of the interval probe graphs which occur in applications involving physical mapping of dna. however, chordal probe graphs also have their own computational biology application as a special case of constructing phylogenies, tree structures which model genetic mutations.we give several characterizations of chordal probe graphs, first in the case of a fixed given partition of the vertices into probes and non-probes, and second in the more general case where no partition is given. in both of these cases, our results are obtained by characterizing superclasses, namely, n-triangulatable graphs and cyclebicolorable graphs, which are first introduced here. we give polynomial time recognition algorithms for each class. the complexity is o (|p||e|), given a partition of the vertices into probes and non-probes, thus also providing a interesting tractible subcase of the chordal graph sandwich problem. if no partition is given in advance, the complexity of our recognition algorithm is o(|v|2|e|).
from valid inequalities to heuristics: a unified view of primal-dual approximation algorithms in covering problems. in recent years approximation algorithms based on primal-dual methods have been successfully applied to a broad class of discrete optimization problems. in this paper, we propose a generic primal-dual framework to design and analyze approximation algorithms for integer programming problems of the covering type that uses valid inequalities in its design. the worst-case bound of the proposed algorithm is related to a fundamental relationship (called strength) between the set of valid inequalities and the set of minimal solutions to the covering problems. in this way, we can construct an approximation algorithm simply by constructing the required valid inequalities. we apply the proposed algorithm to several problems, such as covering problems related to totally balanced matrices, cyclic scheduling, vertex cover, general set covering, intersections of polymatroids, and several network design problems attaining (in most cases) the best worst-case bound known in the literature.
computing homotopic shortest paths in the plane. we address the problem of computing homotopic shortest paths in the presence of obstacles in the plane. problems on homotopy of paths received attention very recently [cabello et al., in: proc. 18th annu. acm sympos. comput. geom., 2002, pp. 160-169; efrat et al., in: proc. 10th annu. european sympos. algorithms, 2002, pp. 411-423]. we present two output-sensitive algorithms, for simple paths and non-simple paths. the algorithm for simple paths improves the previous algorithm [efrat et al., in: proc. 10th annu. european sympos. algorithms, 2002, pp. 411-423]. the algorithm for non-simple paths achieves o(log2n) time per output vertex which is an improvement by a factor of o(n/log2n) of the previous algorithm [hershberger, snoeyink, comput. geom. theory appl. 4 (1994) 63-98], where n is the number of obstacles. the running time has an overhead o(n2+ε) for any positive constant ε. in the case k < n2+ε, where k is the total size of the input and output, we improve the running to o((n + k + (nk)2/3) logo(1) n).
sampling binary contingency tables with a greedy start. we study the problem of counting and randomly sampling binary contingency tables. for given row and column sums, we are interested in approximately counting (or sampling) 0/1 n x m matrices with the specified row/column sums. we present a simulated annealing algorithm with running time o((nm)2d3dmaxlog5(n+m)) for any row/column sums where d is the number of non-zero entries and dmax is the maximum row/column sum. this is the first algorithm to directly solve binary contingency tables for all row/column sums. previous work reduced the problem to the permanent, or restricted attention to row/column sums that are close to regular. the interesting aspect of our simulated annealing algorithm is that it starts at a non-trivial instance, whose solution relies on the existence of short alternating paths in the graph constructed by a particular greedy algorithm.
accelerating simulated annealing for the permanent and combinatorial counting problems. we present an improved &ldquo;cooling schedule&rdquo; for simulated annealing algorithms for combinatorial counting problems. under our new schedule the rate of cooling accelerates as the temperature decreases. thus, fewer intermediate temperatures are needed as the simulated annealing algorithm moves from the high temperature (easy region) to the low temperature (difficult region). we present applications of our technique to colorings and the permanent (perfect matchings of bipartite graphs). moreover, for the permanent, we improve the analysis of the markov chain underlying the simulated annealing algorithm. this improved analysis, combined with the faster cooling schedule, results in an $o(n^7\log^4{n})$ time algorithm for approximating the permanent of a $0/1$ matrix.
torpid mixing of simulated tempering on the potts model. simulated tempering and swapping are two families of sampling algorithms in which a parameter representing temperature varies during the simulation. the hope is that this will overcome bottlenecks that cause sampling algorithms to be slow at low temperatures. madras and zheng demonstrate that the swapping and tempering algorithms allow efficient sampling from the low-temperature mean-field ising model, a model of magnetism, and a class of symmetric bimodal distributions [10]. local markov chains fail on these distributions due to the existence of bad cuts in the state space.bad cuts also arise in the q-state potts model, another fundamental model for magnetism that generalizes the ising model. glauber (local) dynamics and the swendsen-wang algorithm have been shown to be prohibitively slow for sampling from the potts model at some temperatures [1, 2, 6]. it is reasonable to ask whether tempering or swapping can overcome the bottlenecks that cause these algorithms to converge slowly on the potts model.we answer this in the negative, and give the first example demonstrating that tempering can mix slowly. we show this for the 3-state ferromagnetic potts model on the complete graph, known as the mean-field model. the slow convergence is caused by a first-order (discontinuous) phase transition in the underlying system. using this insight, we define a variant of the swapping algorithm that samples efficiently from a class of bimodal distributions, including the mean-field potts model.
tight bounds for on-line tree embeddings. tree-structured computations are relatively easy to process in parallel. as leaf processes are recursively spawned they can be assigned to independent processors in a multicomputer network. however, to achieve good performance the on-line mapping algorithm must maintain load balance, i.e., distribute processes equitably among processors. additionally, the algorithm itself must be distributed in nature, and process allocation must be completed via message-passing with minimal communication overhead.this paper investigates bounds on the performance of deterministic and randomized algorithms for on-line tree embeddings. in particular, we study trade-offs between computation overhead (load imbalance) and communication overhead (message congestion). we give a simple technique to derive lower bounds on the congestion that any on-line allocation algorithm must incur in order to guarantee load balance. this technique works for both randomized and deterministic algorithms. we prove that the advantage of randomization is limited. optimal bounds are achieved for several networks, including multidimensional grids and butterflies.
simpler algorithm for estimating frequency moments of data streams. the problem of estimating the kth frequency moment fk over a data stream by looking at the items exactly once as they arrive was posed in [1, 2]. a succession of algorithms have been proposed for this problem [1, 2, 6, 8, 7]. recently, indyk and woodruff [11] have presented the first algorithm for estimating fk, for k > 2, using space &otilde;(n1-2/k), matching the space lower bound (up to poly-logarithmic factors) for this problem [1, 2, 3, 4, 13] (n is the number of distinct items occurring in the stream.) in this paper, we present a simpler 1-pass algorithm for estimating fk.
learning deterministic finite automata from smallest counterexamples. we show in this paper (which appeared in a preliminary form as an extended abstract in [proceedings of the 9th international acm--siam symposium on discrete algorithms, acm, 1998]) that deterministic finite automata (dfas) with n states and input alphabet $\sigma$ can efficiently be learned from less than $|\sigma|n^2$ smallest counterexamples. this improves on an earlier result of ibarra and jiang who required $|\sigma|n^3$ smallest counterexamples. we present a general strategy which learns a finite concept class ${\cal f}$ from $\lfloor\log{\cal f}\rfloor$ smallest counterexamples (but not necessarily efficiently). an application to dfas with at most $n$ states shows that $(1+o(1))|\sigma|n\log n$ smallest counterexamples are sufficient (if efficiency is not an issue). we show next that the special dfas operating on input words of an arbitrary but fixed length (the so-called leveled dfas) are efficiently learnable from $(1+o(1))|\sigma|n\log n$ smallest counterexamples. this improves on an earlier result of ibarra and jiang who required $|\sigma|n^2$ smallest counterexamples. furthermore, we present a general lower bound on the number of smallest counterexamples (required by any learning algorithm). this bound can be stated in terms of a (new) combinatorial dimension associated with the target class. a computation of this dimension for leveled or arbitrary dfas leads to a lower bound of the form $(\frac{1}{4}+o(1))|\sigma|n\log n$. this bound matches the aforementioned upper bounds modulo a constant of approximately 4. finally, we present a general conversion of algorithms learning from smallest counterexamples into algorithms performing self-directed learning. for the particular classes of leveled or arbitrary dfas, this conversion leads to self-directed learners making the smallest possible number of mistakes (modulo a constant of approximately 4). a similar remark is valid for the class of multiplicity automata (mas).
compact representations of ordered sets. we consider the problem of efficiently representing sets s of size n from an ordered universe u = {0,...,m-1}. given any ordered dictionary structure (or comparison-based ordered set structure) d that uses o(n) pointers, we demonstrate a simple blocking technique that produces an ordered set structure supporting the same operations in the same time bounds but with o(n log m+n/n) bits. this is within a constant factor of the information-theoretic lower bound. we assume the unit cost ram model with word size &omega;(log |u|) and a table of size o(m&alpha; log2 m) bits, for some constant &alpha; > 0. the time bound for our operations contains a factor of 1/&alpha;.we present experimental results for the stl (c++ standard template library) implementation of red-black trees, and for an implementation of treaps. we compare the implementations with blocking and without blocking. the blocking variants use a factor of between 1.5 and 10 less space depending on the density of the set.
dictionaries using variable-length keys and data, with applications. we consider the problem of maintaining a dynamic dictionary in which both the keys and the associated data are variable-length bit-strings. we present a dictionary structure based on hashing that supports constant time lookup and expected amortized constant time insertion and deletion. to store the key-data pairs (s1, t1) ... (sn, tn), our dictionary structure uses o(m) bits where m = &sigma;(max(|si| -- log n, 1) + |ti| and |si| is the length of bit string si. we assume a word length w > log m.we present several applications, including representations for semi-dynamic graphs, ordered sets for integers in a bounded range, cardinal trees with varying cardinality, and simplicial meshes of k dimensions. these results either generalize or simplify previous results.
compact representations of separable graphs. we consider the problem of representing graphs compactly while supporting queries efficiently. in particular we describe a data structure for representing n-vertex unlabeled graphs that satisfy an o(nc)-separator theorem, c < 1. the structure uses o(n) bits, and supports adjacency and degree queries in constant time, and neighbor listing in constant time per neighbor. this generalizes previous results for graphs with constant genus, such as planar graphs.we present experimental results using many "real world" graphs including 3-dimensional finite element meshes, link graphs of the web, internet router graphs, vlsi circuits, and street map graphs. compared to adjacency lists, our approach reduces space usage by almost an order of magnitude, while supporting depthfirst traversal in about the same running time.
an 8/13-approximation algorithm for the asymmetric maximum tsp. we present a polynomial time approximation algorithm for the asymmetric maximum traveling salesperson problem that achieves performance ratio 8/13 (1 - 1/n). the running time of our algorithm is o(n3).
a new approximation algorithm for the asymmetric tsp with triangle inequality. we present a polynomial time factor 0.999 &cdot; log n approximation algorithm for the asymmetric traveling salesperson problem with triangle inequality.
space-efficient finger search on degree-balanced search trees. we show how to support the finger search operation on degree-balanced search trees in a space-efficient manner that retains a worst-case time bound of o(log d), where d is the difference in rank between successive search targets. while most existing tree-based designs allocate linear extra storage in the nodes (e.g., for side links and parent pointers), our design maintains a compact auxiliary data structure called the "hand" during the lifetime of the tree and imposes no other storage requirement within the tree.the hand requires o(log n) space for an n-node tree and has a relatively simple structure. it can be updated synchronously during insertions and deletions with time proportional to the number of structural changes in the tree. the auxiliary nature of the hand also makes it possible to introduce finger searches into any existing implementation without modifying the underlying data representation (e.g., any implementation of red-black trees can be used). together these factors make finger searches more appealing in practice.our design also yields a simple yet optimal in-order walk algorithm with worst-case o(1) work per increment (again without any extra storage requirement in the nodes), and we believe our algorithm can be used in database applications when the overall performance is very sensitive to retrieval latency.
static optimality and dynamic search-optimality in lists and trees. adaptive data structures form a central topic of on-line algorithms research, beginning with the results of sleator and tarjan showing that splay trees achieve static optimality for search trees, and that move-to-front is constant competitive for the list update problem [st85a, st85b]. this paper is inspired by the observation that one can in fact achieve a 1 + &epsilon; ratio against the best static object in hindsight for a wide range of data structure problems via "weighted experts" techniques from machine learning, if computational decision-making costs are not considered.in this paper, we give two results. first, we show that for the case of lists, we can achieve a 1 + &epsilon; ratio with respect to the best static list in hindsight, by a simple efficient algorithm. this algorithm can then be combined with existing results to simultaneously achieve good static and dynamic bounds. second, for trees, we show a (computationally inefficient) algorithm that achieves what we call "dynamic search optimality": dynamic optimality if we allow the online algorithm to make free rotations after each request. we hope this to be a step towards solving the longstanding open problem of achieving true dynamic optimality for trees.
smoothed analysis of the perceptron algorithm for linear programming. the smoothed complexity [1] of an algorithm is the expected running time of the algorithm on an arbitrary instance under a random perturbation. it was shown recently that the simplex algorithm has polynomial smoothed complexity. we show that a simple greedy algorithm for linear programming, the perceptron algorithm, also has polynomial smoothed complexity, in a high probability sense; that is, the running time is polynomial with high probability over the random perturbation.
near-optimal online auctions. we consider the online auction problem proposed by bar-yossef, hildrum, and wu [4] in which an auctioneer is selling identical items to bidders arriving one at a time. we give an auction that achieves a constant factor of the optimal profit less an o(h) additive loss term, where h is the value of the highest bid. furthermore, this auction does not require foreknowledge of the range of bidders' valuations. on both counts, this answers open questions from [4, 5]. we further improve on the results from [5] for the online posted-price problem by reducing their additive loss term from o(h log h log log h) to o(h log log h). finally, we define the notion of an (offline) attribute auction for modeling the problem of auctioning items to consumers who are not a-priori indistinguishable. we apply our online auction solution to achieve good bounds for the attribute auction problem with 1-dimensional attributes.
online learning in online auctions. we consider the problem of revenue maximization in online auctions, that is, auctions in which bids are received and dealt with one-by-one. in this paper, we demonstrate that results from online learning can be usefully applied in this context, and we derive a new auction for digital goods that achieves a constant competitive ratio with respect to the optimal (offline) fixed price revenue. this substantially improves upon the best previously known competitive ratio for this problem of o(exp(√log log h)). we also apply our techniques to the related problem of designing online posted price mechanisms, in which the seller declares a price for each of a series of buyers, and each buyer either accepts or rejects the good at that price. despite the relative lack of information in this setting, we show that online learning techniques can be used to obtain results for online posted price mechanisms which are similar to those obtained for online auctions.
online algorithms for market clearing. in this article, we study the problem of online market clearing where there is one commodity in the market being bought and sold by multiple buyers and sellers whose bids arrive and expire at different times. the auctioneer is faced with an online clearing problem of deciding which buy and sell bids to match without knowing what bids will arrive in the future. for maximizing profit, we present a (randomized) online algorithm with a competitive ratio of ln(pmax &minus; pmin) &plus; 1, when bids are in a range [pmin, pmax], which we show is the best possible. a simpler algorithm has a ratio twice this, and can be used even if expiration times are not known. for maximizing the number of trades, we present a simple greedy algorithm that achieves a factor of 2 competitive ratio if no money-losing trades are allowed. we also show that if the online algorithm is allowed to subsidize matches---match money-losing pairs if it has already collected enough money from previous pairs to pay for them---then it can actually be 1-competitive with respect to the optimal offline algorithm that is not allowed subsidy. that is, for maximizing the number of trades, the ability to subsidize is at least as valuable as knowing the future. we also consider objectives of maximizing buy or sell volume and social welfare. we present all of these results as corollaries of theorems on online matching in an incomplete interval graph.we also consider the issue of incentive compatibility, and develop a nearly optimal incentive-compatible algorithm for maximizing social welfare. for maximizing profit, we show that no incentive-compatible algorithm can achieve a sublinear competitive ratio, even if only one buy bid and one sell bid are alive at a time. however, we provide an algorithm that, under certain mild assumptions on the bids, performs nearly as well as the best fixed pair of buy and sell prices, a weaker but still natural performance measure. this latter result uses online learning methods, and we also show how such methods can be used to improve our &ldquo;optimal&rdquo; algorithms to a broader notion of optimality. finally, we show how some of our results can be generalized to settings in which the buyers and sellers themselves have online bidding strategies, rather than just each having individual bids.
a new algorithm for normal dominance constraints. dominance constraints are logical descriptions of trees. efficient algorithms for the subclass of normal dominance constraints were recently proposed. we present a new and simpler graph algorithm solving these constraints more efficiently, in quadratic time per solved form. it also applies to weakly normal dominance constraints as needed for an application to computational linguistics. subquadratic running time can be achieved employing decremental graph biconnectivity algorithms.
on the combinatorial complexity of euclidean voronoi cells and convex hulls of d-dimensional spheres. in this paper we show an equivalence relationship between additively weighted voronoi cells in rd, power diagrams in rd and convex hulls of spheres in rd. an immediate consequence of this equivalence relationship is a tight bound on the complexity of: (1) a single additively weighted voronoi cell in dimension d; (2) the convex hull of a set of d-dimensional spheres. in particular, given a set of n spheres in dimension d, we show that the worst case complexity of both a single additively weighted voronoi cell and the convex hull of the set of spheres is &theta;(n[d/2]). the equivalence between additively weighted voronoi cells and convex hulls of spheres permits us to compute a single additively weighted voronoi cel1 in dimension d in worst case optimal time o(n log n+n[d/2]).
directed scale-free graphs. we introduce a model for directed scale-free graphs that grow with preferential attachment depending in a natural way on the in- and out-degrees. we show that the resulting in- and out-degree distributions are power laws with different exponents, reproducing observed properties of the worldwide web. we also derive exponents for the distribution of in- (out-) degrees among vertices with fixed out- (in-) degree. we conclude by suggesting a corresponding model with hidden variables.
sparse distance preservers and additive spanners. for an unweighted graph $g = (v,e)$, $g' = (v,e')$ is a subgraph if $e' \subseteq e$, and $g'' = (v'',e'',\omega)$ is a steiner graph if $v \subseteq v''$, and for any pair of vertices $u,w \in v$, the distance between them in $g''$ (denoted $d_{g''}(u,w)$) is at least the distance between them in $g$ (denoted $d_g(u,w)$).in this paper we introduce the notion of distance preserver. a subgraph (resp., steiner graph) $g'$ of a graph $g$ is a subgraph (resp., steiner) $d$-preserver of $g$ if for every pair of vertices $u,w \in v$ with $d_g(u,w) \ge d$, $d_{g'}(u,w) = d_g(u,w)$. we show that any graph (resp., digraph) has a subgraph $d$-preserver with at most $o(n^2/d)$ edges (resp., arcs), and there are graphs and digraphs for which any undirected steiner $d$-preserver contains $\omega(n^2/d)$ edges. however, we show that if one allows a directed steiner (disteiner) $d$-preserver, then these bounds can be improved. specifically, we show that for any graph or digraph there exists a disteiner $d$-preserver with $o({{n^2 \cdot \log d} \over {d \cdot \log n}})$ arcs, and that this result is tight up to a constant factor.we also study $d$-preserving distance labeling schemes, that are labeling schemes that guarantee precise calculation of distances between pairs of vertices that are at a distance of at least $d$ one from another. we show that there exists a $d$-preserving labeling scheme with labels of size $o({{n} \over {d}} \log^2 n)$, and that labels of size $\omega({{n} \over {d}} \log d)$ are required for any $d$-preserving labeling scheme.
(incremental) priority algorithms. we study the question of what optimization problems can be optimally or approximately solved by "greedy-like" algorithms. for definiteness, we will limit the present discussion to some well-studied scheduling problems although the underlying issues apply in a much more general setting. of course, the main benefit of greedy algorithms lies in both their conceptual simplicity and their computational efficiency. based on the experience from online competitive analysis, it seems plausible that we should be able to derive approximation bounds for "greedy-like" algorithms exploiting only the conceptual simplicity of these algorithms. to this end, we will provide a precise definition of what we mean by greedy and greedy-like. a full version of this paper is available at http://www.cs.toronto.edu/~ bor/priority.ps.
stability preserving transformations: packet routing networks with edge capacities and speeds. in the context of an adversarial input model, we consider the effect on stability results when edges in packet routing networks can have capacities and speeds/slowdowns. in traditional packet routing networks, every edge is considered to have the same unit capacity and unit speed. we consider both static modifications (i.e. where the capacity or speed of an edge is fixed) and dynamic modifications where either the capacity or the speed of an edge can be dynamically changing over time. amongst our results, we show that the universal stability of lis is not preserved when either the capacity or the speed is changing dynamically whereas many other common scheduling protocols do maintain their universal stability. in terms of universal stability of networks, stability is preserved for dynamically changing capacities and speeds. the situation for static modifications, is not as clear but we are able to show that (in contrast to the dynamic case) that any &ldquo;well defined&rdquo; universally stable scheduling rule maintains its universality under static capacities, and common scheduling rules also maintain their universal stability under static speeds.
an algorithm for maximum -flow in a directed planar graph. we give the first correct o(n log n) algorithm for finding a maximum st-flow in a directed planar graph. after a preprocessing step that consists in finding single-source shortest-path distances in the dual, the algorithm consists of repeatedly saturating the leftmost residual s-to-t path.
simultaneous diagonal flips in plane triangulations. simultaneous diagonal flips in plane triangulations are investigated. it is proved that every triangulation with n&thinsp;&ge;&thinsp;6 vertices has a simultaneous flip into a 4-connected triangulation, and that the set of edges to be flipped can be computed in $\cal o$(n) time. it follows that every triangulation has a simultaneous flip into a hamiltonian triangulation. this result is used to prove that for any two n-vertex triangulations, there exists a sequence of $\cal o$(logn) simultaneous flips to transform one into the other. moreover, &ohm;(log n) simultaneous flips are needed for some pairs of triangulations. the total number of edges flipped in this sequence is $\cal o$(n). the maximum size of a simultaneous flip is then studied. it is proved that every triangulation has a simultaneous flip of at least ${{1}\over{3}}({n}-{2})$ edges. on the other hand, every simultaneous flip has at most n - 2 edges, and there exist triangulations with a maximum simultaneous flip of ${{6}\over{7}}({n}-{2})$ edges. &copy; 2006 wiley periodicals, inc. j graph theory 54: 307&ndash;330, 2007 a preliminary version of this paper was published in the proceedings of the 17th annual acm-siam symposium on discrete algorithms (soda'06). research partially completed at carleton university and mcgill university (montr&eacute;al).
improved results for route planning in stochastic transportation. in the bus network problem, the goal is to generate a plan for getting from point x to point y within a city using buses in the smallest expected time. because bus arrival times are not determined by a fixed schedule but instead may be random, the problem requires more than standard shortest path techniques. in recent work, datar and ranade provide algorithms in the case where bus arrivals are assumed to be independent and exponentially distributed. we offer solutions to two important generalizations of the problem, answering open questions posed by datar and ranade. first, we provide a polynomial time algorithm for a much wider class of arrival distributions, namely those with increasing failure rate. this class includes not only exponential distributions but also uniform, normal, and gamma distributions. second, in the case where bus arrival times are independent and geometric discrete random variables, we provide an algorithm for transportation networks of buses and trains, where trains run according to a fixed schedule.
the relative worst order ratio applied to paging. the relative worst-order ratio, a relatively new measure for the quality of on-line algorithms, is extended and applied to the paging problem. we obtain results significantly different from those obtained with the competitive ratio. first, we devise a new deterministic paging algorithm, retrospective-lru, and show that, according to the relative worst-order ratio and in contrast with the competitive ratio, it performs better than lru. our experimental results, though not conclusive, are slightly positive and leave it possible that retrospective-lru or similar algorithms may be worth considering in practice. furthermore, the relative worst-order ratio (and practice) indicates that lru is better than the marking algorithm fwf, though all deterministic marking algorithms have the same competitive ratio. look-ahead is also shown to be a significant advantage with this new measure, whereas the competitive ratio does not reflect that look-ahead can be helpful. finally, with the relative worst-order ratio, as with the competitive ratio, no deterministic marking algorithm can be significantly better than lru, but the randomized algorithm mark is better than lru.
on-line restricted caching. we study the on-line caching problem in a restricted cache where each memory item can be placed in only a restricted subset of cache locations. examples of restricted caches in practice include victim caches, assist caches, and skew caches. to the best of our knowledge, all previous on-line caching studies have considered on-line caching in identical or fully-associative caches where every memory item can be placed in any cache location. in this paper, we focus on companion caches, a simple restricted cache that includes victim caches and assist caches as special cases. our results show that restricted caches are significantly more complex than identical caches. for example, we show that the commonly studied least recently used (lru) algorithm is not competitive unless cache reorganization is allowed while the performance of the first in first out (fifo) algorithm is competitive but not optimal. we then present two near optimal algorithms for this problem as well as some lower bound arguments.
single-minded unlimited supply pricing on sparse instances. we deal with the problem of finding profit-maximizing prices for a finite number of distinct goods, assuming that of each good an unlimited number of copies is available, or that goods can be reproduced at no cost (e.g., digital goods). consumers specify subsets of the goods and the maximum prices they are willing to pay. in the considered single-minded case every consumer is interested in precisely one such subset. if the goods are the edges of a graph and consumers are requesting to purchase paths in this graph, then we can think of the problem as pricing computer network connections or transportation links.we start by showing weak np-hardness of the very restricted case in which the requested subsets are nested, i.e., contained inside each other or non-intersecting, thereby resolving the previously open question whether the problem remains np-hard when the underlying graph is simply a line. using a reduction inspired by this result we present an approximation preserving reduction that proves apx-hardness even for very sparse instances defined on general graphs, where the number of requests per edge is bounded by a constant b and no path is longer than some constant l. on the algorithmic side we first present an o(log l + log b)-approximation algorithm that (almost) matches the previously best known approximation guarantee in the general case, but is especially well suited for sparse problem instances. using a new upper bounding technique we then give an o(l2)-approximation, which is the first algorithm for the general problem with an approximation ratio that does not depend on b.
competitive analysis of organization networks or multicast acknowledgement: how much to wait? we study, from the competitive analysis perspective, the trade off between communication cost and delay cost (or simply the send-or-wait dilemma) on a hierarchy (rooted tree). the problem is an abstraction of the message aggregation problem on communication networks and the organizational problem in network hierarchies. we consider the most natural variant of the problem, the distributed asynchronous regime, and give tight (within an additive constant) upper and lower bounds of the competitive ratio.we also consider the centralized version of the problem, where we combine the natural rent-to-buy strategy with prediction techniques to achieve the first constant competitive ratio algorithm for any non-trivial class of network topologies.
lower bounds for external memory dictionaries. we study trade-offs between the update time and the query time for comparison based external memory dictionaries. the main contributions of this paper are two lower bound trade offs between the i/o complexity of member queries and insertions: if n < m insertions perform at most &delta; &middot; n/b i/os, then (1) there exists a query requiring n/(m. &middot;~o(&delta;)) i/os, and (2) there exists a query requiring &omega;(log&delta;log2n ~ i/os when &delta; is o(b/log3 n) and n is at least m2. for both lower bound we describe data structures which give matching upper bounds for a wide range of parameters, thereby showing the lower bounds to be tight within these ranges.
cache-oblivious string dictionaries. we present static cache-oblivious dictionary structures for strings which provide analogues of tries and suffix trees in the cache-oblivious model. our construction takes as input either a set of strings to store, a single string for which all suffixes are to be stored, a trie, a compressed trie, or a suffix tree, and creates a cache-oblivious data structure which performs prefix queries in o(logbn + |p|/b) i/os, where n is the number of leaves in the trie, p is the query string, and b is the block size. this query cost is optimal for unbounded alphabets. the data structure uses linear space.
cache oblivious search trees via binary trees of small height. we propose a version of cache oblivious search trees which is simpler than the previous proposal of bender, demaine and farach-colton and has the same complexity bounds. in particular, our data structure avoids the use of weight balanced b-trees, and can be implemented as just a single array of data elements, without the use of pointers. the structure also improves space utilization.for storing n elements, our proposal uses (1 + &epsilon;)n times the element size of memory, and performs searches in worst case o(logb n) memory transfers, updates in amortized o((log2 n)/(&epsilon;b)) memory transfers, and range queries in worst case o(logb n + k/b) memory transfers, where k is the size of the output.the basic idea of our data structure is to maintain a dynamic binary tree of height log n+o(1) using existing methods, embed this tree in a static binary tree, which in turn is embedded in an array in a cache oblivious fashion, using the van emde boas layout of prokop.we also investigate the practicality of cache obliviousness in the area of search trees, by providing an empirical comparison of different methods for laying out a search tree in memory.
optimal construction of edge-disjoint paths in random graphs. given a graph g=(v,e) with n vertices, m edges, and a family of $\kappa$ pairs of vertices in $v$, we are interested in finding for each pair (ai, bi) a path connecting ai to bi such that the set of $\kappa$ paths so found is edge disjoint. (for arbitrary graphs the problem is ${\cal np}$-complete, although it is in ${\cal p}$ if $\kappa$ is fixed.)we present a polynomial time randomized algorithm for finding the optimal number of edge disjoint paths (up to constant factors) in the random graph gn,m for all edge densities above the connectivity threshold. (the graph is chosen first; then an adversary chooses the pairs of endpoints.) our results give the first tight bounds for the edge-disjoint paths problem for any nontrivial class of graphs.
multidimensional balanced allocations. we consider a multidimensional variant of the balls-and-bins problem, where balls correspond to random d-dimensional 0-1 vectors. this variant is motivated by a problem in load balancing documents for distributed search engines. we demonstrate the utility of the power of two choices in this domain.
worst case constant time priority queue. we present a new data structure of size 3m + &ogr;(m) bits for solving the &ldquo;discrete priority queue&rdquo; problem. when this data structure is used in combination with a new memory topology it provides an o(1) worst case time solution. in doing so we demonstrate how an unconventional, but practically implementable, memory architecture can be employed to sidestep a lower bound (of lg lg m) and achieve constant time performance.
improving table compression with combinatorial optimization. we study the problem of compressing massive tables within the partition-training paradigm introduced by buchsbaum et al. [2000], in which a table is partitioned by an off-line training procedure into disjoint intervals of columns, each of which is compressed separately by a standard, on-line compressor like gzip. we provide a new theory that unifies previous experimental observations on partitioning and heuristic observations on column permutation, all of which are used to improve compression rates. based on this theory, we devise the first on-line training algorithms for table compression, which can be applied to individual files, not just continuously operating sources; and also a new, off-line training algorithm, based on a link to the asymmetric traveling salesman problem, which improves on prior work by rearranging columns prior to partitioning. we demonstrate these results experimentally. on various test files, the on-line algorithms provide 35--55&percnt; improvement over gzip with negligible slowdown; the off-line reordering provides up to 20&percnt; further improvement over partitioning alone. we also show that a variation of the table compression problem is max-snp hard.
a data structure for arc insertion and regular path finding. if $g$ is a directed graph with labeled edges and $l$ is a fixed regular language, the {\em regular path problem}, given two nodes, $u$ and $v$, in $g$, is to find a path between $u$ and $v$ such that the labels on the arcs along that path form a string which is a member of $l$. we consider a dynamic version of this problem, adding arcs to and performing regular path queries on $g$ over $l$, and present a data structure that solves both problems in average time per operation linear in the number of nodes of the graph for any fixed regular language.
quantum property testing. a language $l$ has a property tester if there exists a probabilistic algorithm that given an input $x$ queries only a small number of bits of $x$ and distinguishes the cases as to whether $x$ is in $l$ and $x$ has large hamming distance from all $y$ in $l$. we define a similar notion of quantum property testing and show that there exist languages with good quantum property testers but no good classical testers. we also show there exist languages which require a large number of queries even for quantumly testing.
relating singular values and discrepancy of weighted directed graphs. various parameters have been discovered which give a measurement of the "randomness" of a graph. we consider two such parameters for directed graphs: the singular values of the (normalized) adjacency matrix and discrepancy (a measurement of how randomly edges have been placed). we will show that these two are equivalent by bounding one by the other so that if one is small then both are small. we will also give a related result for discrepancy of walks when the indegree and out-degree at each vertex is equal. both of these results follow from a more general discrepancy property of nonnegative matrices which we will state and prove.
many distances in planar graphs. let g be a planar graph with n vertices and non-negative edge-lengths. given a set of k pairs of vertices, we are interested in computing the distance in g between those k pairs of vertices. we describe how this can be achieved in o(n2/3k2/3 log n + n4/3log1/3 n) time, improving previous results for a large range of k. as possible applications, we show how this result speeds up previous algorithms for finding shortest non-contractible cycles for graphs on a bounded-genus surface or for computing the dilation of a geometric planar graph.
improved range-summable random variable construction algorithms. range-summable universal hash functions, also known as range-summable random variables, are binary-valued hash functions which can efficiently hash single values as well as ranges of values from the domain. they have found several applications in the area of data stream processing where they are used to construct sketches---small-space summaries of the input sequence.we present two new constructions of range-summable universal hash functions on n-bit strings, one based on reed-muller codes which gives k-universal hashing using o(nlog k) space and time for point operations and o(n2 log k) for range operations, and another based on a new subcode of the second-order reed-muller code, which gives 5-universal hashing using o(n) space, o(n log3 n) time for point operations, and o(n3) time for range operations.we also present a new sketch data structure using the new hash functions which improves several previous results.
approximation algorithms for the 0-extension problem. in the 0-extension problem, we are given a weighted graph with some nodes marked as terminals and a semi-metric on the set of terminals. our goal is to assign the rest of the nodes to terminals so as to minimize the sum, over all edges, of the product of the edge's weight and the distance between the terminals to which its endpoints are assigned. this problem generalizes the multiway cut problem of dahlhaus, johnson, papadimitriou, seymour, and yannakakis and is closely related to the metric labeling problem introduced by kleinberg and tardos. we present approximation algorithms for o-extension. in arbitrary graphs, we present an &ogr;(log k)-approximation algorithm, k being the number of terminals. we also give &ogr;(1)-approximation guarantees for weighted planar graphs. our results are based on a natural metric relaxation of the problem, previously considered by karzanov. it is similar in flavor to the linear programming relaxation of garg, vazirani, and yannakakis for the multicut problem and similar to relaxations for other graph partitioning problems. we prove that the integrality ratio of the metric relaxation is at least c&radic;lgk for a positive c for infinitely many k. our results improve some of the results of kleinberg and tardos and they further our understanding on how to use metric relaxations.
the list partition problem for graphs. we consider the problem of partitioning the vertex-set of a graph into at most k parts a1, a2,..., ak, where it may be specified that ai induce a stable set, a clique, or an arbitrary subgraph, and pairs ai, aj (i &ne; j) be completely non-adjacent, completely adjacent, or arbitrarily adjacent. this problem is generalized to the list version which specifies for each vertex a list of parts in which the vertex is allowed to be placed. many well-known graph problems can be formulated as list partition problems: e.g. 3-colourability, clique cutset, stable cutset, homogeneous set, skew partition, and 2-clique cutset. we classify, with the exception of two polynomially equivalent problems, each list partition problem with k = 4 as either solvable in polynomial time or np-complete. in doing so, we provide polynomial-time algorithms for many problems whose polynomial-time solvability was open, including the list 2-clique cutset problem. this also allows us to classify each list generalized 2-clique cutset problem and list generalized skew partition problem as solvable in polynomial time or np-complete.
the complexity of heaps. in this paper, we investigate the complexity of heaps. in particular, we study the construction problem and the search problem for heaps. we derive an adversary-based lower bound for the heap construction problem. it is shown that 1.5(n + 1)&ndash;log(n + 1)&ndash;2 comparisons are necessary to construct a heap of size n in the worst case. this is the first non-trivial adversary lower bound for this problem, which improves the previous best lower bound based on an information theoretical argument for the heap construction. furthermore, we prove fairly trivial tight upper and lower bounds on the number of comparisons needed to search for a given element in a heap. an optimal 3/4n-time search algorithm is presented. our lower bound for searching is also demonstrated by an adversary argument, which improves the information theory bound for the problem as well.
computing contour trees in all dimensions. we show that contour trees can be computed in all dimensions by a simple algorithm that merges two trees. our algorithm extends, simplifies, and improves work of tarasov and vyalyi and of van kreveld et al.
hill-climbing finds random planted bisections. we analyze the behavior of hill-climbing algorithms for the minimum bisection problem on instances drawn from the &ldquo;planted bisection&rdquo; random graph model, gn,p,q, previously studied in [3, 4, 10, 11, 14, 9, 7]. this is one of the few problem distributions for which various popular heuristic methods, such as simulated annealing, have been proven to succeed. however, it has been open whether these sophisticated methods were necessary, or whether simpler heuristics would also work. juels [14] made the first progress towards an answer by showing that simple hill-climbing does suffice for very wide separations between p and q. here we give a more complete answer. a simple, polynomial-time, hill-climbing algorithm for this problem is given and shown to succeed in finding the planted bisection with high probability if p - q = &ohgr; (n-&frac12;ln3n). for dense graphs, this matches the condition for optimality of the planted bisection to within a polylogarithmic factor. furthermore, we show that a generic randomized hill-climbing algorithm succeeds in finding the planted bisection in polynomial time if p - q = &ohgr; (n-&frac14; ln3 n), for any &isin; > 0. this algorithm, studied also by [14], is a degenerate case of both metropolis and go-with-the-winners, and the range here properly includes those analyzed in [11, 9, 14]. so this result implies, extends, and unifies those from [11, 9, 14]. thus, to get a provable distinction between simulated annealing and hill-climbing for natural problems will require considerable progress both on new positive results for sa and new negative results for hill-climbing methods.
an o(ve) algorithm for ear decompositions of matching-covered graphs. our main result is an o(nm)-time (deterministic) algorithm for constructing an ear decomposition of a matching-covered graph, improving on the previous best running time of o(nm2). where n and m denote the number of nodes and edges. the improvement in the running time comes from new structural results that give a sharpened version of lov&aacute;sz and plummer's two-ear theorem. our algorithm is based on o(nm)-time algorithms for two other fundamental problems in matching theory, namely, finding all the allowed edges of a graph, and finding the canonical partition of an elementary graph. (to the best of our knowledge, no faster deterministic algorithms are known for these two fundamental problems.)
the influence of search engines on preferential attachment. there is much current interest in the evolution of social networks, especially, the web graph, through time. "preferential attachment" and the "copying model" are well-known models which explain the observed degree distribution of the web graph reasonably closely. we claim that the presence of highly popular search engines like google substantially mediate the act of hyperlink creation by limiting the author's attention to a small set of "celebrity" urls. page authors (who are also web surfers) frequently (with probability p) locate pages using a search engine. then they link to popular pages among those they visit. we initiate an analysis of this more realistic process, and show that the celebrity nodes eventually accumulate a constant fraction of all links created whp, and that the degrees of the other nodes still follow a power-law distribution, but with a steeper power: pr(degree = k) &alpha; k-(1+2/(1-p)) whp. our analysis adds evidence to the recent concern that search engines offer new web pages a steep, self-sustaining barrier to entry to well-connected, entrenched web communities.
a deterministic near-linear time algorithm for finding minimum cuts in planar graphs. we present a simple deterministic o(n log2 n)-time divide-and-conquer algorithm for finding minimum cuts in planar graphs. this can be compared to a randomized algorithm for general graphs by karger that runs in time o(m log3 n) and also a deterministic algorithm for general graphs by nagamochi and ibaraki that runs in time o(mn + n2 log n). we use shortest paths in the dual graphs to partition the problem, and use the relationship between minimum cuts in primal graphs and shortest paths in dual graphs to find minimum cuts that cross the partitions efficiently.
semi-online maintenance of geometric optima and measures. we give the first nontrivial worst-case results for dynamic versions of various basic geometric optimization and measure problems under the semi-online model, where during the insertion of an object we are told when the object is to be deleted. problems that we can solve with sublinear update time include the hausdorff distance of two point sets, discrete 1-center, largest empty circle, convex hull volume in three dimensions, volume of the union of axis-parallel cubes, and minimum enclosing rectangle. the decision versions of the hausdorff distance and discrete 1-center problems can be solved fully dynamically. some applications are mentioned.
an optimal randomized algorithm for maximum tukey depth. we present the first optimal algorithm to compute the maximum tukey depth (also known as location or halfspace depth) for a non-degenerate point set in the plane. the algorithm is randomized and requires o(n log n) expected time for n data points. in a higher fiexed dimension d &ge; 3, the expected time bound is o(nd-1), which is probably optimal as well. the result is obtained using an interesting variant of the author's randomized optimization technique, capable of solving "implicit" linear-programming-type problems; some other applications of this technique are briefly mentioned.
on levels in arrangements of surfaces in three dimensions. a favorite open problem in combinatorial geometry is to determine the worst-case complexity of a level in an arrangement. up to now, nontrivial upper bounds in three dimensions are known only for the linear cases of planes and triangles. we propose the first technique that can deal with more general surfaces in three dimensions. for example, in an arrangement of n "pseudo-planes" or "pseudo-spheres" (where each triple of surfaces has at most two common intersections), we prove that there are at most o(n2.9986) vertices of any given level.
finding the shortest bottleneck edge in a parametric minimum spanning tree. the result. parametric optimization problems that concern graphs with continuously changing edge weights have been explored by numerous researchers, with motivation ranging from sensitivity analysis to mobile-data applications. for instance, dey [5] has shown that for an undirected graph with n vertices and m edges where the edge weights are linear functions in one parameter ("time"), the minimum spanning tree (mst) can undergo at most o(mn1/3) changes (edge swaps). agarwal et al. [1] have given data structures to maintain the mst over time, with a cost of o(n2/3 polylog n) per change. fernandez-baca et al. [7] have given an algorithm to compute all changes to the mst in o(mn log n) total time.
all-pairs shortest paths for unweighted undirected graphs in time. we revisit the all-pairs-shortest-paths problem for an unweighted undirected graph with n vertices and m edges. we present new algorithms with the following running times:[equation]these represent the best time bounds known for the problem for all m &lt; n1.376. we also obtain a similar type of result for the diameter problem for unweighted directed graphs.
a dynamic data structure for 3-d convex hulls and 2-d nearest neighbor queries. we present a fully dynamic randomized data structure that can answer queries about the convex hull of a set of n points in three dimensions, where insertions take o(log3 n) expected amortized time, deletions take o(log6 n) expected amortized time, and extreme-point queries take o(log2 n) worst-case time. this is the first method that guarantees polylogarithmic update and query cost for arbitrary sequences of insertions and deletions, and improves the previous o(n&epsilon;)-time method by agarwal and matou&scaron;ek a decade ago. as a consequence, we obtain similar results for nearest neighbor queries in two dimensions and improved results for numerous fundamental geometric problems (such as levels in three dimensions and dynamic euclidean minimum spanning trees in the plane).
on hierarchical routing in doubling metrics. we study the problem of routing in doubling metrics, and show how to perform hierarchical routing in such metrics with small stretch and compact routing tables (i.e., with small amount of routing information stored at each vertex). we say that a metric (x, d) has doubling dimension dim(x) at most &alpha; if every set of diameter d can be covered by 2&alpha; sets of diameter d/2. (a doubling metric is one whose doubling dimension dim(x) is a constant.) we show how to perform (1 + &tau;)-stretch routing on metrics for any 0 < t &le; 1 with routing tables of size at most (&alpha;/&tau;)o(&alpha;) log2 &delta; bits with only (&alpha;/&tau;)o(&alpha;) log &delta; entries, where &delta; is the diameter of the graph; hence the number of routing table entries is just &tau;-o(1) log &delta; for doubling metrics. these results extend and improve on those of talwar (2004).we also give better constructions of sparse spanners for doubling metrics than those obtained from the routing tables above; for &tau; > 0, we give algorithms to construct (1 + &tau;)-stretch spanners for a metric (x, d) with maximum degree at most (2 + 1/&tau;)o(dim(x)), matching the results of das et al. for euclidean metrics.
dynamic dictionary matching and compressed suffix trees. recent breakthrough in compressed indexing data structures has reduced the space for indexing a text (or a collection of texts) of length n from o(n log n) bits to o(n) bits, while allowing very efficient pattern matching [10, 13]. yet the compressed nature of such indices also makes them difficult to update dynamically. this paper presents the first o(n)-bit representation of a suffix tree for a dynamic collection of texts whose total length is n, which supports insertion and deletion of a text t in o(|t | log2 n) time, as well as all suffix tree traversal operations, including forward and backward suffix links. this work can be regarded as a generalization of the compressed representation of static texts. our new suffix tree representation serves as a core part in a compact solution for the dynamic dictionary matching problem, i.e., providing an o(d)-bit data structure for a dynamic collection of patterns of total length d that can support the dictionary matching query efficiently. when compared with the o(d log d)-bit suffix tree based solution of amir et al., the compact solution increases the query time by roughly a factor of log d only. in the study of the above results, we also derive the first o(n)-bit representation for maintaining n pairs of balanced parentheses in o(log n/log log n) time per operation, matching the time complexity of the previous o(n log n)-bit solution.
extra unit-speed machines are almost as powerful as speedy machines for competitive flow time scheduling. we study online scheduling of jobs to minimize the flow time and stretch on parallel machines. we consider algorithms that are given extra resources so as to compensate the lack of future information. recent results show that a modest increase in machine speed can provide very competitive performance; in particular, using o(1) times faster machines, the algorithm srpt (shortest remaining processing time) is 1-competitive for both flow time [23] and stretch [12], and hdf (highest density first) is o(1)-competitive for weighted flow time [6]. using extra unit-speed machines instead of faster machines is more challenging. this paper gives a non-trivial relationship between the extra-speed and extra-machine analysis. it shows that competitive results via faster machines can be transformed to similar results via extra machines, and hence giving the first algorithms that, using o(1) times unit-speed machines, are 1-competitive for flow time and stretch and o(1)-competitive for weighted flow time, respectively.
non-migratory online deadline scheduling on multiprocessors. in this paper we consider multiprocessor scheduling with hard deadlines and investigate the cost of eliminating migration in the online setting. let i be any set of jobs that can be completed by some migratory offline schedule on m processors. we show that i can also be completed by a non-migratory online schedule using m speed-5.828 processors (i.e., processors of 5.828 times faster). this result supplements the previous results that i can also be completed by a non-migratory offline schedule using 6m unit-speed processors [8] or a migratory online schedule using m speed-2 processors [13]. our result is based on a simple conservative scheduling algorithm called park which commits a processor to a job only when the processor has zero commitment before its deadline. a careful analysis of park further shows that the processor speed can be reduced arbitrarily close to 1 by exploiting more processors (say, using 16m speed-1.8 processors). park also finds application in overloaded systems; it gives the first online non-migratory algorithm that can exploit moderately faster processors to match the performance of any migratory offline algorithm.
the space complexity of pass-efficient algorithms for clustering. we present multiple pass streaming algorithms for a basic clustering problem for massive data sets. if our algorithm is allotted 2l passes, it will produce an approximation with error at most &epsilon; using &otilde;(k3/&epsilon;2/l) bits of memory, the most critical resource for streaming computation. we demonstrate that this tradeoff between passes and memory allotted is intrinsic to the problem and model of computation by proving lower bounds on the memory requirements of any l pass randomized algorithm that are nearly matched by our upper bounds. to the best of our knowledge, this is the first time nearly matching bounds have been proved for such an exponential tradeoff for randomized computation.in this problem, we are given a set of n points drawn randomly according to a mixture of k uniform distributions and wish to approximate the density function of the mixture. the points are placed in a datastream (possibly in adversarial order), which may only be read sequentially by the algorithm. we argue that this models, among others, the datastream produced by a national census of the incomes of all citizens.
on semidefinite programming relaxations for graph coloring and vertex cover. we investigate the power of a strengthened sdp relaxation for graph coloring whose value is equal to a variant of the lov&aacute;sz &thetasym;-function. we show families of graphs where the value of the relaxation is 2 + &epsilon; for any fixed &epsilon; > 0, yet the chromatic number is n&delta; for some fixed &delta; > 0, which is a function of &epsilon;. this demonstrates the bound provided by the sdp is not strong enough to color a 3-colorable graph with no(1) colors.kleinberg and goemans considered an sdp relaxation for vertex cover whose value is n - &thetasym;1/2 (&thetasym;1/2 being the variant of the &thetasym;-function introduced by schrijver). they asked whether this is within a ratio of 2 - &epsilon; of the optimal vertex cover for any &epsilon; > 0. our construction answers this question negatively.
spreading metrics for vertex ordering problems. we design approximation algorithms for the vertex ordering problems minimum linear arrangement, minimum containing interval graph, and minimum storage-time product, achieving approximation factors of o&radic;log n log log n), o&radic;log n log log n), and o&radic;log t log log t), respectively, the last running in time polynomial in t (t being the sum of execution times). the technical contribution of our paper is to introduce l22 spreading metrics" (that can be computed by semidefinite programming) as relaxations for both undirected and directed "permutation metrics," which are induced by permutations of {1, 2, . . ., n}. the techniques introduced in the recent work of arora, rao and vazirani can be adapted to exploit the geometry of such l22 spreading metrics, giving a powerful tool for the design of divide-and-conquer algorithms. in addition to their applications to approximation algorithms, the study of such l22 spreading metrics as relaxations of permutation metrics is interesting in its own right. we show how our results imply that, in a certain sense we make precise, l22 spreading metrics approximate permutation metrics on n points to a factor of o&radic;log n log log n).
a tight threshold for metric ramsey phenomena. in this paper, we examine the metric ramsey problem for the normed spaces lp: given some 1 &le; p &le; &infin;, &alpha; &ge; 1 and an integer n, we ask for the largest m such that every n-point metric space contains an m-point subspace which embeds into lp with distortion at most &alpha;. bartal, linial, mendel and naor show in [3] that in the case of 1 &le; p &le; 2, the dependence of m on &alpha; undergoes a phase transition at &alpha; = 2. the case of p > 2 was left as an open problem. we show that the phase transition occurs around &alpha; = 2 for all p &ge; 1. the basis of our result is a proof that there exist {1, 2} metrics which require distortion arbitrarily close to 2 for embedding into lp. in order to show this, we develop new tools for analyzing embeddings of random metrics into lp.
a robust maximum completion time measure for scheduling. one popular measure for evaluating the performance of scheduling algorithms, is the maximum response time of any job (makespan). typically the objective is to find a schedule that minimizes the maximum response time over all jobs. one drawback of this measure is that a relatively small number of jobs in the request set could cause the maximum response time to be very high. thus, this measure reflects local rather than global properties of the request set. in this paper we consider a robust generalization of this measure. our goal is to minimize t, such that a given fraction of jobs can be scheduled with a response time of at most t. we demonstrate the applicability of this measure in the context of broadcast scheduling. we show that in the online setting no constant factor online approximation is possible for the problem of minimizing the maximum response time for a given fraction of jobs in the context of broadcast scheduling. we give a factor 5, polynomial time offline approximation algorithm for the problem of minimizing the maximum response time for a given fraction of jobs in the context of broadcast scheduling.
minimizing wirelength in zero and bounded skew clock trees. an important problem in vlsi design is distributing a clock signal to synchronous elements in a vlsi circuit so that the signal arrives at all elements simultaneously. the signal is distributed by means of a clock routing tree rooted at a global clock source. the difference in length between the longest and shortest root-leaf path is called the skew of the tree. the problem is to construct a clock tree with zero skew (to achieve synchronicity) and minimal sum of edge lengths (so that circuit area and clock tree capacitance are minimized).we give the first constant-factor approximation algorithms for this problem and its variants that arise in the vlsi context. for the zero skew problem in general metric spaces, we give an approximation algorithm with a performance guarantee of 2e. for the l1 version on the plane, we give an (8/ln 2)-approximation algorithm.
algorithms for facility location problems with outliers. facility location problems are traditionally investigated with the assumption that all the clients are to be provided service. a significant shortcoming of this formulation is that a few very distant clients, called outliers, can exert a disproportionately strong influence over the final solution. in this paper we explore a generalization of various facility location problems (k-center, k-median, uncapacitated facility location etc) to the case when only a specified fraction of the customers are to be served. what makes the problems harder is that we have to also select the subset that should get service. we provide generalizations of various approximation algorithms to deal with this added constraint.
directed metrics and directed graph partitioning problems. the theory of embeddings of finite metrics has provided a powerful toolkit for graph partitioning problems in undirected graphs. the connection comes from the fact that the integrality gaps of mathematical programming relaxations for sparsest cut in undirected graphs is exactly equal to the minimum distortion required to embed certain metrics into l1. no analog of this metric embedding theory exists for directed (asymmetric) metrics, the natural distance functions that arise in considering mathematical relaxations for directed graph partioning problems. we initiate a study of metric embeddings for directed metrics, motivated by understanding directed variants of sparsest cut.it turns out that there are two different ways to formulate sparsest cut in directed graphs (depending on whether one insists on partitioning the graph into two pieces or not). different subclasses of directed metrics arise in the consideration of mathematical relaxations for these two formulations and the embedding questions that result are quite different. unlike in the undirected case, where the natural host space is l1, the host space in the directed case is not obvious and depends on the problem formulation. our work is a first step at understanding this space of directed metrics, the resulting embedding questions and their relationships to directed graph partitioning problems.
the complexity of quantitative concurrent parity games. we consider two-player infinite games played on graphs. the games are concurrent, in that at each state the players choose their moves simultaneously and independently, and stochastic, in that the moves determine a probability distribution for the successor state. the value of a game is the maximal probability with which a player can guarantee the satisfaction of her objective. we show that the values of concurrent games with &omega;-regular objectives expressed as parity conditions can be decided in np &cap; conp. this result substantially improves the best known previous bound of 3exptime. it also shows that the full class of concurrent parity games is no harder than the special case of turn-based stochastic reachability games, for which np &cap; conp is the best known bound.while the previous, more restricted np &cap; conp results for graph games relied on the existence of particularly simple (pure memoryless) optimal strategies, in concurrent games with parity objectives optimal strategies may not exist, and &epsilon;-optimal strategies (which achieve the value of the game within a parameter &epsilon; > 0) require in general both randomization and infinite memory. hence our proof must rely on a more detailed analysis of strategies and, in addition to the main result, yields two results that are interesting on their own. first, we show that there exist &epsilon;-optimal strategies that in the limit coincide with memoryless strategies; this parallels the celebrated result of mertens-neyman for concurrent games with limit-average objectives. second, we complete the characterization of the memory requirements for &epsilon;-optimal strategies for concurrent games with parity conditions, by showing that memoryless strategies suffice for &epsilon;-optimality for cob&uuml;chi conditions.
quantitative stochastic parity games. we study perfect-information stochastic parity games. these are two-player nonterminating games which are played on a graph with turn-based probabilistic transitions. a play results in an infinite path and the conflicting goals of the two players are &omega;-regular path properties, formalized as parity winning conditions. the qualitative solution of such a game amounts to computing the set of vertices from which a player has a strategy to win with probability 1 (or with positive probability). the quantitative solution amounts to computing the value of the game in every vertex, i.e., the highest probability with which a player can guarantee satisfaction of his own objective in a play that starts from the vertex.for the important special case of one-player stochastic parity games (parity markov decision processes) we give polynomial-time algorithms both for the qualitative and the quantitative solution. the running time of the qualitative solution is o(d &middot; m3/2) for graphs with m edges and d priorities. the quantitative solution is based on a linear-programming formulation.for the two-player case, we establish the existence of optimal pure memoryless strategies. this has several important ramifications. first, it implies that the values of the games are rational. this is in contrast to the concurrent stochastic parity games of de alfaro et al.; there, values are in general algebraic numbers, optimal strategies do not exist, and ε-optimal strategies have to be mixed and with infinite memory. second, the existence of optimal pure memoryless strategies together with the polynomial-time solution forone-player case implies that the quantitative two-player stochastic parity game problem is in np &cap; co-np. this generalizes a result of condon for stochastic games with reachability objectives. it also constitutes an exponential improvement over the best previous algorithm, which is based on a doubly exponential procedure of de alfaro and majumdar for concurrent stochastic parity games and provides only ε-approximations of the values.
on the tandem duplication-random loss model of genome rearrangement. we initiate the algorithmic study of a new model of genome rearrangement, the tandem duplication-random loss model, in which a genome evolves via successive rounds of tandem duplication of a contiguous segment of genes, followed by the loss of one copy of each of the duplicated genes. this model is well-known in the evolutionary biology literature, where it has been used to explain many of the known rearrangements in vertebrate mitochondrial genomes. based on the model, we formalize a notion of distance between two genomes and show how to compute it efficiently for two interesting regions of the parameter space. we then consider median problems (i.e. finding the point which minimizes the sum of distances to a given set of points under some distance function) in the context of maximum parsimony phylogenetic reconstruction for these two special cases. surprisingly, one of them turns out to correspond to the well-known rank aggregation problem, while the other corresponds to the biologically interesting case of whole genome duplication and loss, and we give an o(log log n) additive approximation algorithm for the latter.
embeddings of negative-type metrics and an improved approximation to generalized sparsest cut. in this article, we study metrics of negative type, which are metrics (v, d) such that &sqrt;d is an euclidean metric; these metrics are thus also known as &ell;2-squared metrics. we show how to embed n-point negative-type metrics into euclidean space &ell;2 with distortion d &equals; o(log3/4n). this embedding result, in turn, implies an o(log3/4k)-approximation algorithm for the sparsest cut problem with nonuniform demands. another corollary we obtain is that n-point subsets of &ell;1 embed into &ell;2 with distortion o(log3/4 n).
generating well-shaped delaunay meshed in 3d. a triangular mesh in 3d is a decomposition of a given geometric domain into tetrahedra. the mesh is well-shaped if the aspect ratio of every of its tetrahedra is bounded from above by a constant. it is delaunay if the interior of the circum-sphere of each of its tetrahedra does not contain any other mesh vertices. generating a well-shaped delaunay mesh for any 3d domain has been a long term outstanding problem. in this paper, we present an efficient 3d delaunay meshing algorithm that mathematically guarantees the well-shape quality of the mesh, if the domain does not have acute angles. the main ingredient of our algorithm is a novel refinement technique which systematically forbids the formation of shivers, a family of bad elements that none of the previous known algorithms can cleanly remove, especially near the domain boundary &mdash; needless to say, that our algorithm ensure that there is no sliver near the boundary of the domain.
the bloomier filter: an efficient data structure for static support lookup tables. we introduce the bloomier filter, a data structure for compactly encoding a function with static support in order to support approximate evaluation queries. our construction generalizes the classical bloom filter, an ingenious hashing scheme heavily used in networks and databases, whose main attribute---space efficiency---is achieved at the expense of a tiny false-positive rate. whereas bloom filters can handle only set membership queries, our bloomier filters can deal with arbitrary functions. we give several designs varying in simplicity and optimality, and we provide lower bounds to prove the (near) optimality of our constructions.
embedding k-outerplanar graphs into l1. we show that the shortest-path metric of any $k$-outerplanar graph, for any fixed $k$, can be approximated by a probability distribution over tree metrics with constant distortion and hence also embedded into $\ell_1$ with constant distortion. these graphs play a central role in polynomial time approximation schemes for many np-hard optimization problems on general planar graphs and include the family of weighted $k\times n$ planar grids. this result implies a constant upper bound on the ratio between the sparsest cut and the maximum concurrent flow in multicommodity networks for $k$-outerplanar graphs, thus extending a theorem of okamura and seymour [j. combin. theory ser. b, 31 (1981), pp. 75-81] for outerplanar graphs, and a result of gupta et al. [combinatorica, 24 (2004), pp. 233-269] for treewidth-2 graphs. in addition, we obtain improved approximation ratios for $k$-outerplanar graphs on various problems for which approximation algorithms are based on probabilistic tree embeddings. we conjecture that these embeddings for $k$-outerplanar graphs may serve as building blocks for $\ell_1$ embeddings of more general metrics.
edge disjoint paths revisited. the approximability of the maximum edge disjoint paths problem (edp) in directed graphs was seemingly settled by the &omega;(m1/2-&epsilon;)-hardness result of guruswami et al. [10] and the o(&radic;m) approximation achievable via both the natural lp relaxation [19] and the greedy algorithm [11, 12]. here m is the number of edges in the graph. however, we observe that the hardness of approximation shown in [10] applies to sparse graphs and hence when expressed as a function of n, the number of vertices, only an &omega;(n1/2-&epsilon;)-hardness follows. on the other hand, the o(&radic;m)-approximation algorithms do not guarantee a sub-linear (in terms of n) approximation algorithm for dense graphs. we note that a similar gap exists in the known results on the integrality gap of the natural lp relaxation: an &omega;(&radic;n) lower bound and an o(&radic;m) upper bound. motivated by this discrepancy in the upper and lower bounds we study algorithms for the edp in directed and undirected graphs obtaining improved approximation ratios. we show that the greedy algorithm has an approximation ratio of o(min(n2/3, &radic;m)) in undirected graphs and a ratio of o(min(n4/5, &radic;m)) in directed graphs. for ayclic graphs we give an o(&radic;n log n) approximation via lp rounding. these are the first sub-linear approximation ratios for edp. our results also extend to edp with weights and to the unsplittable flow problem with uniform edge capacities.
approximation algorithms for the metric labeling problem via a new linear programming formulation. we consider approximation algorithms for the metric labeling problem. this problem was introduced in a recent paper by kleinberg and tardos [20], and captures many classification problems that arise in computer vision and related fields. they gave an &ogr;(log k log log k) approximation for the general case where k is the number of labels and a 2-approximation for the uniform metric case. more recently, gupta and tardos [15] gave a 4-approximation for the truncated linear metric, a natural non-uniform metric motivated by practical applications to image restoration and visual correspondence. in this paper we introduce a natural integer programming formulation and show that the integrality gap of its linear relaxation either matches or improves the ratios known for several cases of the metric labeling problem studied until now, providing a unified approach to solving them. in particular, we show that the integrality gap of our lp is bounded by &ogr;(log k log log k) for general metric and 2 for the uniform metric thus matching the ratios in [20]. we also develop an algorithm based on our lp that achieves a ratio of 2 + &radic;2 &sime; 3.414 for the truncated linear metric improving the ratio given in [15]. our algorithm uses the fact that the integrality gap of our lp is 1 on a linear metric. we believe that our formulation has the potential to provide improved approximation algorithms for the general case and other useful special cases. finally, our formulation admits general non-metric distance functions. this leads to a non-trivial approximation guarantee for a non-metric case that arises in practice [21], namely the truncated quadratic distance function. we note here that there are non-metric distance functions for which no bounded approximation ratio is achievable.
approximation techniques for average completion time scheduling. we consider the problem of nonpreemptive scheduling to minimize average (weighted) completion time, allowing for release dates, parallel machines, and precedence constraints. recent work has led to constant-factor approximations for this problem based on solving a preemptive or linear programming relaxation and then using the solution to get an ordering on the jobs. we introduce several new techniques which generalize this basic paradigm. we use these ideas to obtain improved approximation algorithms for one-machine scheduling to minimize average completion time with release dates. in the process, we obtain an optimal randomized on-line algorithm for the same problem that beats a lower bound for deterministic on-line algorithms. we consider extensions to the case of parallel machine scheduling, and for this we introduce two new ideas: first, we show that a preemptive one-machine relaxation is a powerful tool for designing parallel machine scheduling algorithms that simultaneously produce good approximations and have small running times; second, we show that a nongreedy "rounding" of the relaxation yields better approximations than a greedy one. we also prove a general theorem relating the value of one-machine relaxations to that of the schedules obtained for the original m-machine problems. this theorem applies even when there are precedence constraints on the jobs. we apply this result to obtain improved approximation ratios for precedence graphs such as in-trees, out-trees, and series-parallel graphs.
on -median clustering in high dimensions. we study approximation algorithms for k-median clustering. we obtain small coresets for k-median clustering in metric spaces as well as in euclidean spaces. specifically, in rd, those coresets are of size with only polynomial dependency on d. this leads to a (1 + &epsilon;)-approximation algorithm for k-median clustering in rd, with running time o(ndk +2(k/&epsilon;)o(1)d2n&sigma;), for any &sigma; > 0. this is an improvement over previous results [5, 20, 21]. we also provide fast constant factor approximation algorithms for k-median clustering in finite metric spaces.we use those coresets to compute (1 + &epsilon;)-approximation k-median clustering in the streaming model of computation, using only o(k2de-2log8 n) space, where the points are taken from rd. this is the first streaming algorithm, for this problem, that has space complexity with only polynomial dependency on the dimension.
invadable self-assembly: combining robustness with efficiency. dna self-assembly is emerging as a key paradigm for nano-technology, nano-computation, and several related disciplines. in nature, dna self-assembly is often equipped with explicit mechanisms for both error prevention and error correction. for artificial self-assembly, these problems are even more important since we are interested in assembling large systems with great precision. so far, theoretical studies of dna self-assembly have primarily focused on the efficiency of the assembly process in terms of the program size and the running time. in this paper, we perform a preliminary study of algorithms for dna self-assembly that are both robust and efficient.strand invasion is an important error-correction mechanism observed in several natural self-assembling systems. we first define invadable self-assemblies as self-assembling systems which can effectively use the strand invasion mechanism for error-correction. we then show that o(log2 n/ log log n) tiles are sufficient to assemble an n &times; n square in this model. the running time of our system is &otilde; (n). we obtain our result by growing a counter which simulates chinese remaindering. the running time and the program size of our invadable system are within polylogarithmic factors of known lower bounds for general systems, i.e. the efficiency penalty for obtaining robustness is small in our model. we also show how to simulate an arbitrary turing machine using an invadable self-assembly system.
polygonal path approximation with angle constraints. we present efficient geometric algorithms for several problems of approximating an n-vertex polygonal path with angle constraints in the d-d space for any fixed d &gne; 2, improving significantly the corresponding graph- theoretic solutions based on known techniques (e.g., by (nearly) a factor of n for d = 2, 3). as a key step in our solutions, we formulate and solve an interesting problem called off-line ball exclusion search (olbes), that may be of interest on its own.
k-pair delay constrained minimum cost routing in undirected networks. we study a problem related to qos routing in an undirected network where each edge has a delay and a cost. given a k-pair routing request {(si, ti, di)&brvbar;i = l,&hellip;,k} where si is ith source node, ti is ith destination node, and di, is the ith delay tolerance, we want to compute a minimum cost network which contains an si-ti path whose delay is at most di for every i. we present an fptas for this problem when k is a constant.
constructing finite field extensions with large order elements. in this paper, we present an algorithm that, given a fixed prime power $q$ and a positive integer $n$, finds an integer $n \in [n, 2qn]$ and an element $\alpha \in \mbox{\bf f}_{q^n}$ of order greater than $ 5.8^{n / \log_q n}$, in time polynomial in $n$. we present another algorithm that finds an integer $n \in [n, n+o(n^{0.77})]$ and an element $\alpha \in \mbox{\bf f}_{q^n}$ of order at least $ 5.8^{\sqrt{n}}$, in time polynomial in $n$. our result is inspired by the recent aks primality testing algorithm [m. agrawal, n. kayal, and n. saxena, ann. of math. (2), 160 (2004), pp. 781-793] and the subsequent improvements [p. berrizbeitia, math. comp., 74 (2005), pp. 2043-2059, q. cheng, in proceedings of the 23rd annual international cryptology conference (crypto 2003), d. boneh, ed., lecture notes in comput. sci. 2729, springer-verlag, berlin, 2003, pp. 338-348, d. j. bernstein, math. comp., 76 (2007), pp. 389-403].
quality meshing with weighted delaunay refinement. delaunay meshes with bounded circumradius to shortest edge length ratio have been proposed in the past for quality meshing. the only poor quality tetrahedra, called slivers, that can occur in such a mesh can be eliminated by the sliver exudation method. this method has been shown to work for periodic point sets, but not with boundaries. recently a randomized point-placement strategy has been proposed to remove slivers while conforming to a given boundary. in this paper we present a deterministic algorithm for generating a weighted delaunay mesh which respects the input boundary and has no poor quality tetrahedron including slivers. as in previous work, we assume that no input angle is acute. our result is achieved by combining the weight pumping method for sliver exudation and the delaunay refinement method for boundary conformation.
dynamic skin triangulation. this paper describes an algorithm for maintaining an approximating triangulation of a deforming surface in r3. the triangulation adapts dynamically to changing shape, curvature, and topology of the surface.
manifold reconstruction from point samples. we present an algorithm to "reconstruct" a smooth k-dimensional manifold m embedded in an euclidean space rd from a "sufficiently dense" point sample from the manifold. the algorithm outputs a simplicial manifold that is homeomorphic and geometrically close to m. the running time is o(n log n) where n is the number of points in the sample (the multiplicative constant depends exponentially on the dimension though).
anisotropic surface meshing. we study the problem of triangulating a smooth closed implicit surface &sigma; endowed with a 2d metric tensor that varies over &sigma;. this is commonly known as the anisotropic surface meshing problem. we extend the 2d metric tensor naturally to 3d and employ the 3d anisotropic voronoi diagram of a set p of samples on &sigma; to triangulate &sigma;. we prove that a restricted dual, mesh p, is a valid triangulation homeomorphic to &sigma; under appropriate conditions. we also develop an algorithm for constructing p and mesh p. in addition to being homeomorphic to &sigma;, each triangle in mesh p is well-shaped when measured using the 3d metric tensors of its vertices. users can set upper bounds on the anisotropic edge lengths and the angles between the surface normals at vertices and the normals of incident triangles (measured both isotropically and anisotropically).
graded conforming delaunay tetrahedralization with bounded radius-edge ratio. we propose an algorithm to compute a conforming delaunay mesh of a polyhedral domain. arbitrarily small input angles are allowed. the output mesh is graded and has bounded radius-edge ratio everywhere.
motorcycle graphs and straight skeletons. we present a new algorithm to compute motorcycle graphs. it runs in $o(n \sqrt{n}\log n)$ time when n is the number of motorcycles. we give a new characterization of the straight skeleton of a nondegenerate polygon. for a polygon with n vertices and h holes, we show that it yields a randomized algorithm that reduces the straight skeleton computation to a motorcycle graph computation in expected $o(n\sqrt{h+1}\log^2 n)$ time. combining these results, we can compute the straight skeleton of a nondegenerate polygon with h holes and with n vertices, among which r are reflex vertices, in $o(n\sqrt{h+1}\log^2 n+r \sqrt{r} \log r)$ expected time. in particular, we cancompute the straight skeleton of a nondegenerate polygon with n vertices in $o(n\sqrt{n}\log^2n)$ expected time.
on finding a guard that sees most and a shop that sells most. we present a near-quadratic time algorithm that computes a point inside a simple polygon p having approximately the largest visibility polygon inside p, and near-linear time algorithm for finding the point that will have approximately the largest voronoi region when added to an n-point set. we apply the same technique to find the translation that approximately maximizes the area of intersection of two polygonal regions in near-quadratic time.
center and diameter problems in plane triangulations and quadrangulations. in this note, we present first linear time algorithms for computing the center and the diameter of several classes of face regular plane graphs: triangulations with inner vertices of degree &ge; 6, quadrangulations with inner vertices of degree &ge; 4 and the subgraphs of the regular hexagonal grid bounded by a simple circuit of this grid.
buckets, heaps, lists, and monotone priority queues. we introduce the heap-on-top (hot) priority queue data structure that combines the multilevel bucket data structure of denardo and fox with a heap. our data structure has superior operation bounds than either structure taken alone. we use the new data structure to obtain an improved bound for dijkstra's shortest path algorithm. we also discuss a practical implementation of hot queues. our experimental results in the context of dijkstra's algorithm show that this implementation of hot queues performs very well and is more robust than implementations based only on heap or multilevel bucket data structures.
orderly spanning trees with applications to graph encoding and graph drawing. the canonical ordering for triconnected planar graphs is a powerful method for designing graph algorithms. this paper introduces the orderly pair of connected planar graphs, which extends the concept of canonical ordering to planar graphs not required to be triconnected. let g be a connected planar graph. we give a linear-time algorithm that obtains an orderly pair (h,t) of g, where h is a planar embedding of g, and t is an orderly spanning tree of h. as applications, we show that the technique of orderly spanning trees yields (i) the best known encoding of g with query support, and (ii) the first area-optimal 2-visibility drawing of g.
a unified approach to dynamic point location, ray shooting, and shortest paths in planar maps. we describe a new technique for dynamically maintaining the trapezoidal decomposition of a connected planar map $\cal m$ with $n$ vertices and apply it to the development of a unified dynamic data structure that supports point-location, ray-shooting, and shortest-path queries in $\cal m$. the space requirement is $o(n\log n)$. point-location queries take time $o(\log n)$. ray-shooting and shortest-path queries take time $o(\log^3 n)$ (plus $o(k)$ time if the $k$ edges of the shortest path are reported in addition to its length). updates consist of insertions and deletions of vertices and edges, and take $o(\log^3 n)$ time (amortized for vertex updates). this is the first polylog-time dynamic data structure for shortest-path and ray-shooting queries. it is also the first dynamic point-location data structure for connected planar maps that achieves optimal query time.
a determinant-based algorithm for counting perfect matchings in a general graph. we present a simple estimator for the number of perfect matchings in a general (non-bipartite) graph. our estimator requires o(ε-23n/2) trials to obtain a (1 &plusmn; ε)-approximation of the correct value with high probability on a graph with 2n vertices in the worst case, and only a polynomial number (o(ε-2n&omega;(n)) of trials on random graphs, where &omega;(n) is any function tending to infinity.our algorithm is based on the following idea: for any graph g, construct its associated tutte matrix t, and derive a random matrix b from it by replacing each variable in t with &plusmn;1 uniformly at random; then output det b. this estimator is a natural generalization of the godsil--gutman estimator for matchings in a bipartite graph, and our analysis of its performance on random graphs borrows generously from frieze and jerrum's analysis of a similar estimator for bipartite graphs.
approximation for minimum triangulation of convex polyhedra. the minimum triangulation of a convex polyhedron is a triangulation that contains the minimum number of tetrahedra over all its possible triangulations. since finding the minimum triangulation of convex polyhedra was recently shown to be np-hard, it becomes significant to find algorithms that give good approximation. in this paper, we give a new triangulation algorithm with an improved approximation ratio 2 - &ohgr;(1/&radic;n). we also show that this is best possible for algorithms that only consider the combinatorial structure of the polyhedra.
approximation hardness of optimization problems in intersection graphs of -dimensional boxes. the maximum independent set problem in d-box graphs, i.e., in the intersection graphs of axis-parallel rectangles in rd, is a challenge open problem. for any fixed d &ge; 2 the problem is np-hard and no approximation algorithm with ratio o(logd-1 n) is known. in some restricted cases, e.g., for d-boxes with bounded aspect ratio, a ptas exists [17]. in this paper we prove apx-hardness (and hence non-existence of a ptas, unless p = np), of the maximum independent set problem in d-box graphs for any fixed d &ge; 3. we state also first explicit lower bound 443/442 on efficient approximability in such case. additionally, we provide a generic method how to prove apx-hardness for many np-hard graph optimization problems in d-box graphs for any fixed d &ge; 3. in 2-dimensional case we give a generic approach to np-hardness results for these problems in highly restricted intersection graphs of axis-parallel unit squares (alternatively, in unit disk graphs).
which formulae shrink under random restrictions? we show that the shrinkage exponent, under random restrictions, of formulae over a finite complete basis b of boolean functions is strictly greater than 1 if and only if all the functions in b are monotone increasing or monotone decreasing in each one of their variables. as a consequence, we get non-linear lower bounds on the formula complexity of the parity function over any basis composed only of monotone increasing or decreasing functions.
delaunay triangulation programs on surface data. the delaunay triangulation of a set of points in 3d can have size &theta;(n2) in the worst case, but this is rarely if ever observed in practice. we compare three production-quality delaunay triangulation programs on some 'real-world' sets of points lying on or near 2d surfaces.
external-memory exact and approximate all-pairs shortest-paths in undirected graphs. we present several new external-memory algorithms for finding all-pairs shortest paths in a v-node. e-edge undirected graph. for all-pairs shortest paths and diameter in unweighted undirected graphs we present cache-oblivious algorithms with o(v&middot;e/b log m/b e/b) i/os, where b is the block-size and m is the size of internal memory. for weighted undirected graphs we present a cache-aware apsp algorithm that performs o(v&middot;(&radic;ve/b+e/b log e/b)) i/os. we also present efficient cache-aware algorithms that find paths between all pairs of vertices in an unweighted graph with lengths within a small additive constant of the shortest path length.all of our results improve earlier results known for these problems. for approximate apsp we provide the first nontrivial results. our diameter result uses o(v + e) extra space, and all of our other algorithms use o(v2) space.
cache-oblivious dynamic programming. we present efficient cache-oblivious algorithms for several fundamental dynamic programs. these include new algorithms with improved cache performance for longest common subsequence (lcs), edit distance, gap (i.e., edit distance with gaps), and least weight subsequence. we present a new cache-oblivious framework called the gaussian elimination paradigm (gep) for gaussian elimination without pivoting that also gives cache-oblivious algorithms for floyd-warshall all-pairs shortest paths in graphs and 'simple dp', among other problems.
the wake-up problem in multi-hop radio networks. we study the problem of waking up a collection of n processors connected by a multi-hop ad-hoc ratio network with unknown topology, no access to a global clock, and no collision detection mechanism available. each node in the network wakes-up spontaneously, or it is activated by receiving a wake-up signal from another node. all active nodes transmit the wake-up signals according to a given protocol q. the running time of is the number of steps counted from the first spontaneous wake-up, until all nodes become activated.we provide two protocols for this problem. the first one is a deterministic protocol with running time o(n5/3log n). our protocol is based on a novel concept of a rotation-tolerant selector to which we refer as a synchronizer. the second protocol is randomized, and its expected running time is o(dlog2n), where d is the diameter of the network.subsequently we show how to employ our wake-up protocols to solve two other communication primitives: leader election and clock synchronization.
guessing secrets with inner product questions. suppose we are given some fixed (but unknown) subset x of a set &omega; = f2n, where f2 denotes the field of two elements. we would like to learn as much as possible about the elements x by asking certain binary questions. each "question" q is some element of &omega;, and the "answer" to q is just the inner product q&middot;x (in f2) for some x &epsilon; x. however, the choice of x is made by a truthful (but possibly malevolent) adversary a, whom we may assume is trying to choose answers so as to as yield as little information as possible about x. in this paper, we study various aspects of this problem. in particular, we are interested in extracting as much information as possible about x from a's answers. although a can prevent us from learning the identity of any particular element of x, with appropriate questions we can still learn a lot about x. we determine the maximum amount of information that can be recovered and discuss the optimal strategies for selecting questions. for the case that |x| = 2, we give an o(n3) algorithm for an optimal strategy. however, for the case that |x| &ge; 3, we show that no such polynomial-time algorithm can exist, unless p = np.
on the approximability of some network design problems. consider the following classical network design problem: a set of terminals t &equals; &lcub;ti&rcub; wishes to send traffic to a root r in an n-node graph g &equals; (v, e). each terminal ti sends di units of traffic and enough bandwidth has to be allocated on the edges to permit this. however, bandwidth on an edge e can only be allocated in integral multiples of some base capacity ue and hence provisioning k &times; ue bandwidth on edge e incurs a cost of &lceil;k&rceil; times the cost of that edge. the objective is a minimum-cost feasible solution. this is one of many network design problems widely studied where the bandwidth allocation is governed by side constraints: edges can only allow a subset of cables to be purchased on them or certain quality-of-service requirements may have to be met. in this work, we show that this problem and, in fact, several basic problems in this general network design framework cannot be approximated better than &omega;(log log n) unless np &sube; dtime (no(log log log n)), where &verbar;v&verbar; &equals; n. in particular, we show that this inapproximability threshold holds for (i) the priority-steiner tree problem, (ii) the (single-sink) cost-distance problem, and (iii) the single-sink version of an even more fundamental problem, fixed charge network flow. our results provide a further breakthrough in the understanding of the level of complexity of network design problems. these are the first nonconstant hardness results known for all these problems.
approximating k-median with non-uniform capacities. in this paper we give a constant factor approximation algorithm for the capacitated k-median problem. our algorithm produces a solution where capacities are exceeded by at most a constant factor, while the number of open facilities is at most k. this problem resisted attempts to apply the plethora of methods designed for the uncapacitated case. our algorithm is based on adding some new ingredients to the approach using the primal-dual schema and lagrangian relaxations.previous results on the capacitated k-median problem gave approximations where the number of facilities is exceeded by some constant factor. relaxing the constraint on the number of facilities seems to render k-median problems much simpler. in some applications it is important not to violate the constraint on the number of facilities, whereas relaxing the capacity constraints is a natural thing to do, as the capacities express rough estimates on cluster sizes.
recognizing dart-free perfect graphs. a graph g is called a berge graph if neither g nor its complement contains a chordless cycle whose length is odd and at least five; what we call a dart is the graph with vertices u,v,w,x,y and edges uv,vw,uy,vy,wy,xy; a graph is called dart-free if it has no induced subgraph isomorphic to the dart. we present a polynomial-time algorithm to recognize dart-free berge graphs; this algorithm uses as a subroutine the polynomial-time algorithm for recognizing claw-free berge graphs designed previously by chvátal and sbihi [j. combin. theory ser. b, 44 (1988), pp. 154--176].
on the competitive ratio of evaluating priced functions. let f be a function on a set of variables v. for each x &epsilon; v, let c(x) be the cost of reading the value of x. an algorithm for evaluating f is a strategy for adaptively identifying and reading a set of variables u &sube; v whose values uniquely determine the value of f. we are interested in finding algorithms which minimize the cost incurred to evaluate f in the above sense. competitive analysis is employed to measure the performance of the algorithms. we study two variants of the above problem. first we consider the classical setting in which one assumes that the algorithm knows the cost c(x), for each x &epsilon; v. for the case where f is a monotone boolean function which is representable by a threshold tree, we provide a polynomial time algorithm with the best possible competitive ratio &gamma;fc for each fixed cost function c(&middot;). remarkably, the best known result for the same class of functions is a pseudo-polynomial algorithm with competitiveness 2&gamma;fc. for the class of game tree functions our polynomial time algorithm attains, for each fixed cost function, the same competitiveness as the best known algorithm for the same class of functions, which instead runs in pseudo-polynomial time.in the second part of the paper, we study a novel variant of the problem. here, we assume that the cost function is not known in advance and some preemption is allowed in the reading operations. this model has applications, e.g., when reading a variable coincides with obtaining the output of a job on a cpu and the cost is the cpu time. in such a case, it is reasonable to assume that no exact knowledge of the cost is available. we define a new algorithm for this problem based on the solution of a linear program. we show the optimality of our algorithm for the class of monotone boolean functions representable by and-or-trees. we also show a sub-optimal implementation for general monotone boolean functions.
selective families, superimposed codes, and broadcasting on unknown radio networks. selective families, a weaker variant of superimposed codes [ks64, f92, 197, cr96], have been recently used to design deterministic distributed broadcast (ddb) protocols for unknown radio networks (a radio network is said to be unknown when the nodes know nothing about the network but their own label) [cggpr00, cgor00]. we first provide a general almost tight lower bound on the size of selective families. then, by reverting the selective families - ddb protocols connection, we exploit our lower bound to construct a family of &ldquo;hard&rdquo; radio networks (i.e. directed graphs). these networks yield an &ohgr;(n log d) lower bound on the completion time of ddb protocols that is superlinear (in the size n of the network) even for very small maximum eccentricity d of the network, while all the previous lower bounds (e.g. &ohgr;(d log n) [cggpr00]) are superlinear only when d is almost linear. on the other hand, the previous upper bounds are all superlinear in n independently of the eccentricity d and the maximum in-degree d of the network. we introduce a broadcast technique that exploits selective families in a new way. then, by combining selective families of almost optimal size with our new broadcast technique, we obtain an &ogr;(dd log3 n) upper bound that we prove to be almost optimal when d = &ogr;(n/d). this exponentially improves over the best known upper bound [cgr00) when d, d = &ogr;(polylogn). furthermore, by comparing our deterministic upper bound with the best known randomized one [bgi87] we obtain a new, rather surprising insight into the real gap between deterministic and randomized protocols. it turns out that this gap is exponential (as discovered in [bgi87]), but only when the network has large maximum in-degree (i.e. d = &ohgr;(na), for some constant a > o). we then look at the multibroadcast problem on unknown radio networks. a similar connection to that between selective families and (single) broadcast also holds between superimposed codes and multibroadcast. we in fact combine a variant of our (single) broadcast technique with superimposed codes of almost optimal size available in literature [eff85, hs87, i97, chi99]. this yields a multibroadcast protocol having completion time &ogr;(dd2 log3 n). finally, in order to determine the limits of our multibroadcast technique, we generalize (and improve) the best known lower bound [cr96] on the size of superimposed codes.
on the polynomial time computation of equilibria for certain exchange economies. the problem of computing equilibria for exchange economies has recently started to receive a great deal of attention in the theoretical computer science community. it has been shown that equilibria can be computed in polynomial time in various special cases, the most important of which are when traders have linear, cobb-douglas, or a range of ces utility functions. these important special cases are instances when the market satisfies a property called weak gross substitutability. classical results in economics, which theoretical computer scientists (including us) appear to have been hitherto unaware of, show that the equilibrium prices in such markets are characterized by an infinite number of linear inequalities and therefore form a convex set. in this paper, we show that under fairly general assumptions, there are polynomial-time algorithms to compute equilibria in such markets. to the best of our knowledge, these are the first polynomial-time algorithms for exchange markets under the general setting of weak gross substitutability. to show this result, we need to build on the proofs that characterize the equilibria as a convex set.as a consequence, we obtain alternative polynomial-time algorithms for computing equilibria with linear, cobb-douglas, a range of ces, as well as certain other non-homogeneous utility functions that satisfy weak gross substitutability. unlike previous polynomial-time algorithms, our approach does not make use of the specific form of these utility functions and is in this sense more general. we expect our framework to work or be readily adaptable to handle other exchange markets, provided that the utility functions satisfy weak gross substitutability.
leontief economies encode nonzero sum two-player games. we consider leontief exchange economies, i.e., economies where the consumers desire goods in fixed proportions. unlike bimatrix games, such economies are not guaranteed to have equilibria in general. on the other hand, they include suitable restricted versions which always have equilibria.we give a reduction from two-player games to a special family of leontief exchange economies, which are guaranteed to have equilibria, with the property that the nash equilibria of any game are in one-to-one correspondence with the equilibria of the corresponding economy.our reduction exposes a potential hurdle inherent in solving certain families of market equilibrium problems: finding an equilibrium for leontief economies (where an equilibrium is guaranteed to exist) is at least as hard as finding a nash equilibrium for two-player nonzero sum games.as a corollary of the one-to-one correspondence, we obtain a number of hardness results for questions related to the computation of market equilibria, using results already established for games [17]. in particular, among other results, we show that it is np-hard to say whether a particular family of leontief exchange economies, that is guaranteed to have at least one equilibrium, has more than one equilibrium.perhaps more importantly, we also prove that it is np-hard to decide whether a leontief exchange economy has an equilibrium. this fact should be contrasted against the known ppad-completeness result of [30], which holds when the problem satisfies some standard sufficient conditions that make it equivalent to the computational version of brouwer's fixed point theorem.on the algorithmic side, we present an algorithm for finding an approximate equilibrium for some special leontief economies, which achieves quasi-polynomial time whenever each trader does not demand too much more of any good than some other good.
approximation algorithms for extensible bin packing. in a variation of bin packing called extensible bin packing, the number of bins is specified as part of the input, and bins may be extended to hold more than the usual unit capacity. the cost of a bin is 1 if it is not extended, and the size if it is extended. the goal is to pack a set of items of given sizes into the specified number of bins so as to minimize the total cost. adapting ideas grötschel et al. (1981), grötschel et al. (1988), karmarkar and karp (1982), murgolo (1987), we give a fully polynomial time asymptotic approximation scheme (fptaas) for extensible bin packing. we close with comments on the complexity of obtaining stronger results.
efficient sequences of trials. we introduce a problem called sequential trial optimization, a generalization of the well studied set cover problem with a new objective function. we give a simple algorithm that achieves a constant factor approximation to this problem. sequential trial optimization naturally arises in heterogenous search environments such as peer to peer networks.
reachability and distance queries via 2-hop labels. reachability and distance queries in graphs are fundamental to numerous applications, ranging from geographic navigation systems to internet routing. some of these applications involve huge graphs and yet require fast query answering. we propose a new data structure for representing all distances in a graph. the data structure is distributed in the sense that it may be viewed as assigning labels to the vertices, such that a query involving vertices u and v may be answered using only the labels of u and v.our labels are based on 2-hop covers of the shortest paths, or of all paths, in a graph. for shortest paths, such a cover is a collection s of shortest paths such that, for every two vertices u and v, there is a shortest path from u to v that is a concatenation of two paths from s. we describe an efficient algorithm for finding an almost optimal 2-hop cover of a given collection of paths. our approach is general and can be applied to directed or undirected graphs, exact or approximate shortest paths, or to reachability queries.we study the proposed data structure using a combination of theoretical and experimental means. we implemented our algorithm and checked the size of the resulting data structure on several real-life networks from different application areas. our experiments show that the total size of the labels is typically not much larger than the network itself, and is usually considerably smaller than an explicit representation of the transitive closure of the network.
efficient estimation algorithms for neighborhood variance and other moments. the neighborhood variance problem is as follows. given a (directed or undirected) graph with values associated with each node, compute a data structure that for any given node v and r &ge; 0, would quickly produce an estimate of the variance of all values of nodes that lie within distance r from v. the problem can be generalized to other moment functions and to arbitrary distance-dependent decay.these problems are motivated by applications where the relevance of a measurement observed (or data present) at a certain location decreases with its distance, and thus the aggregate value varies by location. the centralized version of the problem is motivated by applications to query processing on graphical databases. the distributed version of the problem falls in a model we recently introduced for spatially decaying aggregation and is motivated by sensor or p2p networks.we present novel algorithms for the centralized and distributed versions of the problem. our algorithms are nearly optimal, the centralized version requires &otilde;(m) time and the distributed version requires polylogarithmic communication per node or edge (depending on assumptions).
a spectral heuristic for bisecting random graphs. the minimum bisection problem is to partition the vertices of a graph into two classes of equal size so as to minimize the number of crossing edges. the problem is np-hard in the worst case. in this paper we analyze a spectral heuristic for the minimum bisection problem on random graphs gn(p,p'), which are made up as follows. partition n vertices into two classes of equal size randomly, and then insert edges inside the two classes with probability p' and edges crossing the partition with probability p independently. if n(p'-p) &ge; c0&radic;np'in(np') for a certain constant c0 > 0, then with probability 1 - 0(1) as n &larr; &infin; the heuristic finds a minimum bisection of gn(p,p') along with a certificate of optimality in polynomial time. furthermore, we observe that the structure of the set of all minimum bisections of gn(p,p') undergoes a phase transition as n(p' - p) = &theta;(&radic;np' in n). the heuristic solves instances in the subcritical, the critical, and the supercritical phase of the phase transition optimally with probability 1-o(1). these results extend the work of boppana [5].
tight bounds on the complexity of the boyer-moore string matching algorithm. the problem of finding all occurrences of a pattern of length $m$ in a text of length $n$ is considered. it is shown that the boyer--moore string matching algorithm performs roughly $3n$ comparisons and that this bound is tight up to $o(n/m)$; more precisely, an upper bound of $3n - 3(n-m+1)/(m+2)$ comparisons is shown, as is a lower bound of $3n(1-o(1))$ comparisons, as $\frac{n}{m}\rightarrow\infty$ and $m\rightarrow\infty$. while the upper bound is somewhat involved, its main elements provide a simple proof of a $4n$ upper bound for the same algorithm.
bottleneck links, variable demand, and the tragedy of the commons. the price of anarchy, a measure of the inefficiency of selfish behavior, has been successfully analyzed in a diverse array of models over the past five years. the overwhelming majority of this work has studied optimization problems that sought an optimal way to allocate a fixed demand to resources whose performance degrades with increasing congestion. while fundamental, such problems overlook a crucial feature of many applications: the intrinsic coupling of the quality or cost of a resource and the demand for that resource. this coupling motivates allowing demand to vary with congestion, which in turn can lead to "the tragedy of the commons"---severe inefficiency caused by the overconsumption of a shared resource.allowing the demand for resources to vary with their congestion illuminates a second issue with existing studies of the price of anarchy: the standard additive method of aggregating the costs of different resources in a player's strategy is inappropriate for some important applications, including many of those with variable demand. for example, in networking applications a key performance metric is the achievable throughput along a path, which is controlled by its bottleneck (most congested) edge. this disconnect motivates consideration of nonlinear cost aggregation functions, such as the lp norms.in this paper, we initiate the study of the price of anarchy with variable demand and with broad classes of nonlinear aggregation functions. we focus on selfish routing in single- and multicommodity networks, and on the lp norms for 1 &le; p &le; &infin;; our main results are as follows.&bull; for a natural "prize-collecting" objective function, the price of anarchy in multicommodity networks with variable demand is no larger than that in fixed-demand networks. thus the inefficiency arising from the tragedy of the commons is no more severe than that from routing inefficiencies.&bull; using the lp norm with 1 < p < &infin; as a cost aggregation function can dramatically increase the price of anarchy in multicommodity networks (relative to additive aggregation), but causes no such additional inefficiency in single-commodity networks.&bull; using the l&infin; norms as a cost aggregation function can dramatically increase the price of anarchy, even in single-commodity networks. if attention is restricted to equilibria with additional structure, however---structure that is ensured by distributed shortest-path routing protocols---then using the l&infin; norm does not increase the price of anarchy relative to additive aggregation.
approximate string matching: a simpler faster algorithm. we give two algorithms for finding all approximate matches of a pattern in a text, where the edit distance between the pattern and the matching text substring is at most k. the first algorithm, which is quite simple, runs in time $o(\frac{nk^3}{m}+n+m)$ on all patterns except k-break periodic strings (defined later). the second algorithm runs in time $o(\frac{nk^4}{m}+n+m)$ on k-break periodic patterns. the two classes of patterns are easily distinguished in o(m)time.
dynamic lca queries on trees. we show how to maintain a data structure on trees which allows for the following operations, all in worst-case constant time: insertion of leaves and internal nodes, deletion of leaves, deletion of internal nodes with only one child, determining the least common ancestor of any two nodes. we also generalize the dietz--sleator "cup-filling" scheduling methodology, which may be of independent interest.
a faster implementation of the goemans-williamson clustering algorithm. we give an implementation of the goemans-williamson clustering procedure which is at the core of several approximation algorithms including those for generalized steiner trees, prize collecting travelling salesman, 2-edge connected subgraph etc. on a graph with n nodes and m edge, our implementation gives &ogr; (k(n + m) log2 n) time approximation algorithms for all these problems at the expense of a slight additive degradation of 1/nk in the approximation factor, for any constant k.
multidimensional matching and fast search in suffix trees. we show how to construct a suffix tree of a text string t in linear time, after sorting the characters in the text, so that a search for pattern p take time o(p + log t), independent of the alphabet size, thereby matching the asymptotic performance of suffix arrays. using these suffix trees or suffix arrays we then give linear time algorithms for pattern matching in any fixed dimension.
sampling regular graphs and a peer-to-peer network. we consider a simple markov chain for d-regular graphs on n vertices, and show that the mixing time of this markov chain is bounded above by a polynomial in n and d. a related markov chain for d-regular graphs on a varying number of vertices is introduced, for even degree d. we use this to model a certain peer-to-peer network structure. we prove that the related chain has mixing time which is bounded by a polynomial in n, the expected number of vertices, under reasonable assumptions about the arrival and departure process.
the cover time of sparse random graphs. we study the cover time of a random walk on graphs g &isin; gn, p when p = c log n/n, c < 1. we prove that whpthe cover time is asymptotic to c log (c/c--1) n log n.
the cover time of two classes of random graphs. let g = (v,e) be a connected graph, let |v| = n, and |e| = m. a random walk wu, u &isin; v on the undirected graph g = (v, e) is a markov chain x0 = u, x1,...xt,... &isin; v associated to a particle that moves from vertex to vertex according to the following rule: the probability of a transition from vertex i, of degree di, to vertex j is 1/di if {i,j} &isin; e, and 0 otherwise. for u &isin; v let cu be the expected time taken for wu to visit every vertex of g. the cover time cg of g is defined as cg = maxu&isin;v cu. the cover time of connected graphs has been extensively studied. it is a classic result of aleliunas, karp, lipton, lov&aacute;sz and rackoff [2] that cg &le; 2m(n - 1). it was shown by feige [11], [12], that for any connected graph g[equation]the lower bound is achieved by (for example) the complete graph kn, whose cover time is determined by the coupon collector problem.
a note on random 2-sat with prescribed literal degrees. two classic "phase transitions" in discrete mathematics are the emergence of a giant component in a random graph as the density of edges increases, and the transition of a random 2-sat formula from satisfiable to unsatisfiable as the density of clauses increases. the random-graph result has been extended to the case of prescribed degree sequences, where the almost-sure nonexistence or existence of a giant component is related to a simple property of the degree sequence. we similarly extend the satisfiability result, by relating the almost-sure satisfiability or unsatisfiability of a random 2-sat formula to an analogous property of a prescribed literal sequence.
sparse source-wise and pair-wise distance preservers. we introduce and study the notions of pair-wise and source-wise preservers.given an undirected n-vertex graph g = (v, e) and a subset p of pairs of vertices, let g' = (v, h), h &sube; e, be called a pair-wise preserver of g with respect to p if for every pair {u, w} &isin; p, distg' (u, w) = distg (u, w). for a set s &sube; v of sources, a pair-wise preserver of g with respect to the set of all pairs p = (s/2) of sources is called a source-wise preserver of g with respect to s.we prove that for every undirected possibly weighted n-vertex graph g and every subset p of p = o(n1/2) pairs of vertices of g, there exists a linear-size pair-wise preserver of g with respect to p. consequently, for every subset s &sube; v of s = o(n1/4) sources, there exists a linear-size source-wise preserver of g with respect to s. on the negative side we show that neither of the two exponents (1/2 and 1/4) can be improved even when the attention is restricted to unweighted graphs.our lower bounds involve constructions of dense convexly independent sets of vectors with small euclidean norms. we believe that the link between the areas of discrete geometry and spanners that we establish is of independent interest, and might be useful in the study of other problems in the area of low-distortion embeddings.
ordering by weighted number of wins gives a good ranking for weighted tournaments. we consider the following simple algorithm for feedback arc set problem in weighted tournaments: order the vertices by their weighted indegrees. we show that this algorithm has an approximation guarantee of 5 if the weights satisfy probability constraints (for any pair of vertices u and v, wuv+wvu&equals;1). special cases of the feedback arc set problem in such weighted tournaments include the feedback arc set problem in unweighted tournaments and rank aggregation. to complement the upper bound, for any constant &epsi;>0, we exhibit an infinite family of (unweighted) tournaments for which the aforesaid algorithm (irrespective of how ties are broken) has an approximation ratio of 5-&epsi;.
random max sat, random max cut, and their phase transitions. with random inputs, certain decision problems undergo a &ldquo;phase transition.&rdquo; we prove similar behavior in an optimization context. given a conjunctive normal form (cnf) formula f on n variables and with m k-variable clauses, denote by max f the maximum number of clauses satisfiable by a single assignment of the variables. (thus the decision problem k-sat is to determine if max f is equal to m.) with the formula f chosen at random, the expectation of max f is trivially bounded by (3&#x002f;4)m &les; &eopf; max f &les; m. we prove that for random formulas with m = &lfloor;cn&rfloor; clauses: for constants c < 1, &eopf; max f is &lfloor;cn&rfloor; - &theta;(1&#x002f;n); for large c, it approaches ** equation here ** and in the &ldquo;window&rdquo; c = 1 + &theta;(n-1&#x002f;3), it is cn - &theta;(1). our full results are more detailed, but this already shows that the optimization problem max 2-sat undergoes a phase transition just as the 2-sat decision problem does, and at the same critical value c = 1. most of our results are established without reference to the analogous propositions for decision 2-sat, and can be used to reproduce them. we consider &ldquo;online&rdquo; versions of max 2-sat, and show that for one version the obvious greedy algorithm is optimal; all other natural questions remain open. we can extend only our simplest max 2-sat results to max k-sat, but we conjecture a &ldquo;max k-sat limiting function conjecture&rdquo; analogous to the folklore &ldquo;satisfiability threshold conjecture,&rdquo; but open even for k = 2. neither conjecture immediately implies the other, but it is natural to further conjecture a connection between them. we also prove analogous results for random max cut. &copy; 2004 wiley periodicals, inc. random struct. alg., 2004
the diameter of a long range percolation graph. we consider the following long-range percolation model: an undirected graph with the node set {0, 1, ..., n}d, has edges (x, y) selected with probability ≈ β/||x -y||s if ||x - y|| < 1, and with probability 1 if ||x - y|| = 1, for some parameters β, s < 0. this model was introduced by benjamini and berger [2], who obtained bounds on the diameter of this graph for the one-dimensional case d = 1 and for various values of s, but left cases s = 1, 2 open. we show that, with high probability, the diameter of this graph is θ(log n/log log n) when s = d, and, for some constants 0 >' η1 > η2 > 1, it is at most nη2 when s = 2d, and is at least nη1 when d = 1, s = 2, β > 1 or when s > 2d. we also provide a simple proof that the diameter is at most log o(1) n with high probability, when d > s > 2d, established previously in [2].
an improved data stream algorithm for frequency moments. we present a simple, one-pass, &otilde;(&radic;n)-space data stream algorithm for approximating the third frequency moment. this is the first improvement to the &otilde;(n2/3)-space data stream algorithm of alon, matias, and szegedy [ams99]. the current known lower bound for this problem is &omega;(n1/3) [bjks02a].our algorithm can also be generalized to an &otilde;(n1-1/(k-1))-space data stream algorithm for approximating the k-th frequency moment. besides improving the &otilde;(n1--1/k)-space upper bound [ams99], our algorithm beats the &omega;(n1--1/k)-sampling lower bound [bks01] for this problem.our method suggests a unified perspective of space-efficient data stream algorithms for all frequency moments.
the string edit distance matching problem with moves. the edit distance between two strings s and r is defined to be the minimum number of character inserts, deletes, and changes needed to convert r to s. given a text string t of length n, and a pattern string p of length m, informally, the string edit distance matching problem is to compute the smallest edit distance between p and substrings of t. we relax the problem so that: (a) we allow an additional operation, namely, substring moves; and (b) we allow approximation of this string edit distance. our result is a near-linear time deterministic algorithm to produce a factor of o(log n log&ast; n) approximation to the string edit distance with moves. this is the first known significantly subquadratic algorithm for a string edit distance problem in which the distance involves nontrivial alignments. our results are obtained by embedding strings into l1 vector space using a simplified parsing technique, which we call edit-sensitive parsing (esp).
substring compression problems. we initiate a new class of string matching problems called substring compression problems. given a string s that may be preprocessed, the problem is to quickly find the compressed representation or the compressed size of any query substring of s (substring compression query or scq) or to find the length l substring of s whose compression is the least (least compressible substring or lcs problem).starting from the seminal paper of lempel and ziv over 25 years ago, many different methods have emerged for compressing entire strings. determining substring compressibility is a natural variant that is combinatorially and algorithmically challenging, yet surprisingly has not been studied before. in addition, compressibility of strings is emerging as a tool to compare biological sequences and analyze their information content. however, typically, the compressibility of the entire sequence is not as informative as that of portions of the sequences. thus substring compressibility may be a more suitable basis for sequence analysis.we present the first known, nearly optimal algorithms for substring compression problems---scq, lcs and their generalizations---that are exact or provably approximate. our exact algorithms exploit the structure in strings via suffix trees and our approximate algorithms rely on new relationships we find between lempel-ziv compression and string parsings.
communication complexity of document exchange. we have two users, a and b, who hold documents x and y respectively. neither of the users has any information about the other''s document. they exchange messages so that b computes x; it may be required that a compute y as well. our goal is to design communication protocols with the main objective of minimizing the total number of bits they exchange; other objectives are minimizing the number of rounds and the complexity of internal computations. an important notion which determines the efficiency of the protocols is how one measures the distance between x and y. we consider several metrics for measuring this distance, namely the hamming metric, the levenshtein metric (edit distance), and a new lz metric, which is introduced in this paper. we show how to estimate the distance between x and y using a single message of logarithmic size. for each metric, we present the first communication-efficient protocols, which often match the corresponding lower bounds. a consequence of these are error-correcting codes for these error models which correct up to d errors in n characters using o(d log n) bits. our most interesting methods use a new histogram transformation that we introduce to convert edit distance to l1 distance.
approximation schemes for multidimensional packing. we consider a classic multidimensional generalization of the bin packing problem, namely, packing d-dimensional rectangles into the minimum number of unit cubes. our two results are: an asymptotic polynomial time approximation scheme for packing d-dimensional cubes into the minimum number of unit cubes and a polynomial time algorithm for packing rectangles into at most opt bins whose sides have length (1 + ε), where opt denotes the minimum number of unit bins required to pack the rectangles. both algorithms also achieve the best possible additive constant term. for cubes, this settles the approximability of the problem and represents a significant improvement over the previous best known asymptotic approximation factor of 2 - (2/3)d + ε. for rectangles, this contrasts with the currently best known approximation factor of 1.691....
a sub-quadratic sequence alignment algorithm for unrestricted cost matrices. the classical algorithm for computing the similarity between two sequences [36, 39] uses a dynamic programming matrix, and compares two strings of size n in o(n2) time. we address the challenge of computing the similarity of two strings in sub-quadratic time, for metrics which use a scoring matrix of unrestricted weights. our algorithm applies to both local and global alignment computations.the speed-up is achieved by dividing the dynamic programming matrix into variable sized blocks, as induced by lempel-ziv parsing of both strings, and utilizing the inherent periodic nature of both strings. this leads to an o(n2/log n) algorithm for an input of constant alphabet size. for most texts, the time complexity is actually o(hn2/log n) where h &le; 1 is the entropy of the text.
random walks on the vertices of transportation polytopes with constant number of sources. we consider the problem of uniformly sampling a vertex of a transportation polytope with m sources and n destinations, where m is a constant. we analyse a natural random walk on the edge-vertex graph of the polytope. the analysis makes use of the multicommodity flow technique of sinclair [20] together with ideas developed by morris and sinclair [15, 16] for the knapsack problem, and cryan et al. [2] for contingency tables, to establish that the random walk approaches the uniform distribution in time no(m2).
approximability of dense and sparse instances of minimum 2-connectivity, tsp and path problems. we study the approximability of dense and sparse instances of the following problems: the minimum 2-edge-connected (2-ec) and 2-vertex-connected (2-vc) spanning subgraph, metric tsp with distances 1 and 2 (tsp (1,2)), maximum path packing, and the longest path (cycle) problems. the approximability of dense instances of these problems was left open in arora et al. [3]. we characterize the approximability of all these problems by proving tight upper (approximation algorithms) and lower bounds (inapproximability). we prove that 2-ec, 2-vc and tsp (1,2) are max snp-hard even on 3-regular graphs, and provide explicit hardness constants, under p &ne; np. we also improve the approximation ratio for 2-ec and 2-vc on graphs with maximum degree 3. these are the first explicit hardness results on sparse and dense graphs for these problems. we apply our results to prove bounds on the integrality gaps of lp relaxations for dense and sparse 2-ec and tsp (1,2) problems, related to the famous metric tsp conjecture, due to goemans [17].
better approximation algorithms for bin covering. bin covering takes as input a list of items with sizes in (0, 1) and places them into bins of unit demand so as to maximize the number of bins whose demand is satisfied. this is in a sense a dual problem to the classical one-dimensional bin packing problem, but has for many years lagged behind the latter in terms of the quality of the best approximation algorithms. we design algorithms for this problem that close the gap, both in terms of worst- and average-case results. we present (1) the first asymptotic approximation scheme for the offline version, (2) algorithms that have bounded worst-case behavior for instances with discrete item sizes and expected behavior that is asymptotically optimal for all discrete &ldquo;perfect-packing distributions&rdquo; (ones for which optimal packings have sublinear expected waste), and (3) a learning algorithm that has asymptotically optimal expected behavior for all discrete distributions. the algorithms of (2) and (3) are based on the recently-developed online sum-of-squares algorithm for bin packing. we also present experimental analysis comparing the algorithms of (2) and suggesting that one of them, the sum-of-squares-with-threshold algorithm, performs quite well even for discrete distributions that do not have the perfect-packing property.
chain decompositions and independent trees in 4-connected graphs. this work was motivated by the study of a multitree approach to reliability in distributed networks and by the study of non-separating paths and cycles in highly connected graphs. we first give a result on "non-separating chains" in 4-connected graphs. this result is then used to obtain a "non-separating chain decomposition" of a 4-connected graph g, and an o(&verbar;v(g)&verbar;2&verbar;e(g)&verbar;) algorithm for constructing such a decomposition. as an application of this decomposition, we show how to produce four "independent spanning trees" in a 4-connected graph in o(&verbar;v(g)&verbar;3) time.
sublinear-time approximation of euclidean minimum spanning tree. we consider the problem of finding the weight of a euclidean minimum spanning tree for a set of n points in ℝd. we focus on the situation when the input point set is supported by certain basic (and commonly used) geometric data structures that can provide efficient access to the input in a structured way. we present an algorithm that estimates with high probability the weight of a euclidean minimum spanning tree of a set of points to within 1 + &epsilon; using only &otilde;(&radic; poly(1/&epsilon;)) queries for constant d. the algorithm assumes that the input is supported by a minimal bounding cube enclosing it, by orthogonal range queries, and by cone approximate nearest neighbors queries.
approximation schemes for minimum 2-edge-connected and biconnected subgraphs in planar graphs. given an undirected graph, finding either a minimum 2-edge-connected spanning subgraph or a minimum 2-vertex-connected (biconnected) spanning subgraph is maxsnp-hard. we show that for planar graphs, both problems have a polynomial time approximation scheme (ptas) with running time no(1/ε), where n is the graph size and ε is the relative error allowed.when the planar graph has edge costs, we approximately solve the analogous min-cost subgraph problems in time no(&gamma;/ε), where &gamma; is the ratio of the total edge cost to the optimum solution cost.
soft kinetic data structures. we introduce the framework of soft kinetic data structures (skds). a soft kinetic data structure is an approximate data structure that can be used to answer queries on a set of moving objects with unpredictable motion. we analyze the quality of a soft kinetic data structure by giving a competitive analysis with respect to the dynamics of the system. we illustrate our approach by presenting soft kinetic data structures for maintaining classical data structures: sorted arrays, balanced search trees, heaps, and range trees. we also describe soft kinetic data structures for maintaining the euclidean minimum spanning trees.
tight bounds for worst-case equilibria. we study the problem of traffic routing in noncooperative networks. in such networks, users may follow selfish strategies to optimize their own performance measure and therefore, their behavior does not have to lead to optimal performance of the entire network. in this article we investigate the worst-case coordination ratio, which is a game-theoretic measure aiming to reflect the price of selfish routing. following a line of previous work, we focus on the most basic networks consisting of parallel links with linear latency functions. our main result is that the worst-case coordination ratio on m parallel links of possibly different speeds is &theta;(log m/log log log m). in fact, we are able to give an exact description of the worst-case coordination ratio, depending on the number of links and ratio of speed of the fastest link over the speed of the slowest link. for example, for the special case in which all m parallel links have the same speed, we can prove that the worst-case coordination ratio is &gamma;(&minus;1) (m) &plus; &theta;(1), with &gamma; denoting the gamma (factorial) function. our bounds entirely resolve an open problem posed recently by koutsoupias and papadimitriou [1999].
fast parallel algorithms for the clique separator decomposition. we give an efficient {\it nc} algorithm for finding a clique separator decomposition of an {\it arbitrary} graph, that is, a series of cliques whose removal disconnects the graph. this algorithm allows one to extend a large body of results which were originally formulated for chordal graphs to other classes of graphs. our algorithm is optimal to within a polylogarithmic factor of tarjan''s $o(mn)$ time sequential algorithm. the decomposition can also be used to find {\it nc} algorithms for some optimization problems on special families of graphs, assuming these problems can be solved in {\it nc} for the prime graphs of the decomposition. these optimization problems include: finding a maximum-weight clique, a minimum coloring, a maximum-weight independent set, and a minimum fill-in elimination order. we also give the first parallel algorithms for solving these problems by using the clique separator decomposition. our maximum-weight independent set algorithm applied to chordal graphs yields the most efficient known parallel algorithm for finding a maximum-weight independent set of a chordal graph.
an algorithm for counting maximum weighted independent sets and its applications. we present an o(1.3247n) algorithm for counting the number of independent sets with maximum weight in graphs. we show how this algorithm can be used solving a number of different counting problems: counting exact covers, exact hitting sets, weighted set packing and satisfying assignments in 1-in-k sat.
an exact subexponential-time lattice algorithm for asian options. asian options are path-dependent derivatives. how to price them efficiently and accurately has been a long-standing research and practical problem. asian options can be priced on the lattice. but only exponential-time algorithms are currently known if such options are to be priced on a lattice without approximation. although efficient approximation methods are available, most of them lack accuracy guarantees. this paper proposes a novel lattice for pricing asian options. the resulting exact pricing algorithm runs in subexponential time. this is the first exact lattice algorithm to break the exponential-time barrier. because this lattice converges to the continuous-time stock price process, the proposed algorithm is guaranteed to converge to the desired continuous-time option value.
quantum algorithms for some hidden shift problems. almost all of the most successful quantum algorithms discovered to date exploit the ability of the fourier transform to recover subgroup structures of functions, especially periodicity. the fact that fourier transforms can also be used to capture shift structure has received far less attention in the context of quantum computation. in this paper, we present three examples of &ldquo;unknown shift&rdquo; problems that can be solved efficiently on a quantum computer using the quantum fourier transform. for one of these problems, the shifted legendre symbol problem, we give evidence that the problem is hard to solve classically, by showing a reduction from breaking algebraically homomorphic cryptosystems. we also define the hidden coset problem, which generalizes the hidden shift problem and the hidden subgroup problem. this framework provides a unified way of viewing the ability of the fourier transform to capture subgroup and shift structure.
robbing the bandit: less regret in online geometric optimization against an adaptive adversary. we consider "online bandit geometric optimization," a problem of iterated decision making in a largely unknown and constantly changing environment. the goal is to minimize "regret," defined as the difference between the actual loss of an online decision-making procedure and that of the best single decision in hindsight. "geometric optimization" refers to a generalization of the well-known multi-armed bandit problem, in which the decision space is some bounded subset of rd, the adversary is restricted to linear loss functions, and regret bounds should depend on the dimensionality d, rather than the total number of possible decisions. "bandit" refers to the setting in which the algorithm is only told its loss on each round, rather than the entire loss function.mcmahan and blum [10] presented the best known algorithm in this setting, and proved that its expected additive regret is o(poly(d)t3/4). we simplify and improve their analysis of this algorithm to obtain regret o(poly(d)t2/3).we also prove that, for a large class of full-information online optimization problems, the optimal regret against an adaptive adversary is the same as against a non-adaptive adversary.
maintaining stream statistics over sliding windows (extended abstract). we consider the problem of maintaining aggregates and statistics over data streams, with respect to the last n data elements seen so far. we refer to this model as the sliding window model. we consider the following basic problem: given a stream of bits, maintain a count of the number of 1's in the last n elements seen from the stream. we show that using o(1/e log2n) bits of memory, we can estimate the number of 1's to within a factor of 1 + &epsilon;. we also give a matching lower bound of &omega;(1/e log2 n) memory bits for any deterministic or randomized algorithms. we extend our scheme to maintain the sum of the last n positive integers. we provide matching upper and lower bounds for this more general problem as well. we apply our techniques to obtain efficient algorithms for the lp norms (for p &epsilon; [1, 2]) of vectors under the sliding window model. using the algorithm for the basic counting problem, one can adapt many other techniques to work for the sliding window model, with a multiplicative overhead of o(1/&epsilon;log n) in memory and a 1 + &epsilon; factor loss in accuracy. these include maintaining approximate histograms, hash tables, and statistics or aggregates such as sum and averages.
models of greedy algorithms for graph problems. borodin, nielsen, and rackoff ([5]) gave a model of greedy-like algorithms for scheduling problems and [1] extended their work to facility location and set cover problems. we generalize their notion to include other optimization problems, and apply the generalized framework to graph problems. our goal is to define an abstract model that captures the intrinsic power and limitations of greedy algorithms for various graph optimization problems. we prove bounds on the approximation ratio achievable by such algorithms for basic graph problems such as shortest path, vertex cover, and others. shortest path is an example of a problem where no algorithm in the fixed priority model can achieve any approximation ratio (even one dependent on the graph size), but for which the well-known dijkstra's algorithm shows that an adaptive priority algorithm can be optimal. we also prove that the approximation ratio for vertex cover achievable by adaptive priority algorithms is exactly 2. here, a new lower bound matches the known upper bounds ([8]).
adaptivity and approximation for stochastic packing problems. we study stochastic variants of packing integer programs (pip) --- the problems of finding a maximum-value 0/1 vector x satisfying ax &le; b, with a and b nonnegative. many combinatorial problems belong to this broad class, including the knapsack problem, maximum clique, stable set, matching, hypergraph matching (a.k.a. set packing), b-matching, and others. pip can also be seen as a "multidimensional" knapsack problem where we wish to pack a maximum-value collection of items with vector-valued sizes. in our stochastic setting, the vector-valued sizes of each item is known to us apriori only as a probability distribution, and the size of an item is instantiated once we commit to including the item in our solution.following the framework of [3], we consider both adaptive and non-adaptive policies for solving such problems, adaptive policies having the flexibility of being able to make decisions based on the instantiated sizes of items already included in the solution. we investigate the adaptivity gap for these problems: the maximum ratio between the expected values achieved by optimal adaptive and non-adaptive policies. we show tight bounds on the adaptivity gap for set packing and b-matching, and we also show how to find efficiently non-adaptive policies approximating the adaptive optimum. for instance, we can approximate the adaptive optimum for stochastic set packing to within o(d1/2), which is not only optimal with respect to the adaptivity gap, but it is also the best known approximation factor in the deterministic case. it is known that there is no polynomial-time d1/2-&epsilon; approximation for set packing, unless np = zpp. similarly, for b-matching, we obtain algorithmically a tight bound on the adaptivity gap of o(&lambda;) where &lambda; satisfies &sigma; &lambda;bj+1 = 1.for general stochastic packing, we prove that a simple greedy algorithm provides an o(d)-approximation to the adaptive optimum. for a &isin; [0, 1]dxn, we provide an o(&lambda;) approximation where &sigma; 1/&lambda;bj = 1. (for b = (b, b,..., b), we get &lambda; = d1/b.) we also improve the hardness results for deterministic pip: in the general case, we prove that a polynomial-time d1-&epsilon;-approximation algorithm would imply np = zpp. in the special case when a &isin; [0,1]dxn and b = (b,b,...,b), we show that a d1/b-&isin;-approximation would imply np = zpp. finally, we prove that it is pspace-hard to find the optimal adaptive policy for stochastic packing in any fixed dimension d &ge; 2.
four point conditions and exponential neighborhoods for symmetric tsp. in most of the known polynomially solvable cases of the symmetric travelling salesman problem (tsp) which result from restrictions on the underlying distance matrices, the restrictions have the form of so-called four-point conditions (the inequalities involve four cities). in this paper we treat all possible (symmetric) four-point conditions and investigate whether the corresponding tsp can be solved in polynomial time. as a by-product of our classification we obtain new families of exponential neighborhoods for the tsp which can be searched in polynomial time and for which conditions on the distance matrix can be formulated so that the search for an optimal tsp solution can be restricted to these exponential neighborhoods.
an algorithmic friedman--pippenger theorem on tree embeddings and applications to routing. an (n, d)-expander is a graph g = (v, e) such that for every x &sube; v with |x| &le; 2n &minus; 2 we have |&gamma;g(x)| &ge; (d + 1)|x|. a tree t is small if it has at most n vertices and has maximum degree at most d. friedman and pippenger (1987) proved that any (n, d)-expander contains every small tree. the elegant proof discovered by those authors does not yield an efficient algorithm for obtaining the tree. in this extended abstract, we give an alternative, polynomial formulation for a key concept in their proof, and thus obtain an efficient algorithm for the friedman---pippenger theorem.as an application, we offer a polynomial time algorithm for routing connection requests in wide-sense non-blocking networks of constant depth, following an approach put forward in a seminal paper of feldman, friedman, and pippenger (1988). we thus provide a simple, efficient companion routing scheme for the explicitly described networks of essentially optimal size given by wigderson and zuckerman (1999). the applicability of our methods to deterministically constructible networks is in contrast with some previous work of aggarwal et al. (1996).
subexponential parameterized algorithms on graphs of bounded-genus and -minor-free graphs. we introduce a new framework for designing fixed-parameter algorithms with subexponential running time---2o(&radic;k)no(1). our results apply to a broad family of graph problems, called bidimensional problems, which includes many domination and covering problems such as vertex cover, feedback vertex set, minimum maximal matching, dominating set, edge dominating set, clique-transversal set, and many others restricted to bounded-genus graphs. furthermore, it is fairly straightforward to prove that a problem is bidimensional. in particular, our framework includes as special cases all previously known problems to have such subexponential algorithms. previously, these algorithms applied to planar graphs, single-crossing-minor-free graphs, and map graphs; we extend these results to apply to bounded-genus graphs as well. in a parallel development of combinatorial results, we establish an upper bound on the treewidth (or branchwidth) of a bounded-genus graph that excludes some planar graph h as a minor. this bound depends linearly on the size |v (h)| of the excluded graph h and the genus g(g) of the graph g, and applies and extends the graphminors work of robertson & seymour.building on these results, we develop subexponential fixedparameter algorithms for dominating set, vertex cover, and set cover in any class of graphs excluding a fixed graph h as a minor. in particular, this general category of graphs includes planar graphs, bounded-genus graphs, single-crossing-minor-free graphs, and any class of graphs that is closed under taking minors. specifically, the running time is 2o(&radic;k)nh, where h is a constant depending only on h, which is polynomial for k = o(log2n). we introduce a general approach for developing algorithms on h-minor-free graphs, based on structural results about h-minor-free graphs at the heart of robertson & seymour's graph-minors work. we believe this approach opens the way to further development for problems on h-minor-free graphs.
equivalence of local treewidth and linear local treewidth and its algorithmic applications. we solve an open problem posed by eppstein in 1995 [14, 15] and re-enforced by grohe [16, 17] concerning locally bounded treewidth in minor-closed families of graphs. a graph has bounded local treewidth if the subgraph induced by vertices within distance r of any vertex has treewidth bounded by a function of r (not n). eppstein characterized minor-closed families of graphs with bounded local treewidth as precisely minor-closed families that minor-exclude an apex graph, where an apex graph has one vertex whose removal leaves a planar graph. in particular, eppstein showed that all apex-minor-free graphs have bounded local treewidth, but his bound is doubly exponential in r, leaving open whether a tighter bound could be obtained. we improve this doubly exponential bound to a linear bound, which is optimal. in particular, any minor-closed graph family with bounded local treewidth has linear local treewidth. our bound generalizes previously known linear bounds for special classes of graphs proved by several authors. as a consequence of our result, we obtain substantially faster polynomial-time approximation schemes for a broad class of problems in apex-minor-free graphs, improving the running time from 222o(1/ε) no(1) to 2o(1/ε)no(1).
bidimensionality: new connections between fpt algorithms and ptass. we demonstrate a new connection between fixed-parameter tractability and approximation algorithms for combinatorial optimization problems on planar graphs and their generalizations. specifically, we extend the theory of so-called "bidimensional" problems to show that essentially all such problems have both subexponential fixed-parameter algorithms and ptass. bidimensional problems include e.g. feedback vertex set, vertex cover, minimum maximal matching, face cover, a series of vertex-removal problems, dominating set, edge dominating set, r-dominating set, diameter, connected dominating set, connected edge dominating set, and connected r-dominating set. we obtain ptass for all of these problems in planar graphs and certain generalizations; of particular interest are our results for the two well-known problems of connected dominating set and general feedback vertex set for planar graphs and their generalizations, for which ptass were not known to exist. our techniques generalize and in some sense unify the two main previous approaches for designing ptass in planar graphs, namely, the lipton-tarjan separator approach [focs'77] and the baker layerwise decomposition approach [focs'83]. in particular, we replace the notion of separators with a more powerful tool from the bidimensionality theory, enabling the first approach to apply to a much broader class of minimization problems than previously possible; and through the use of a structural backbone and thickening of layers we demonstrate how the second approach can be applied to problems with a "nonlocal" structure.
graphs excluding a fixed minor have grids as large as treewidth, with combinatorial and algorithmic applications through bidimensionality. we prove that any h-minor-free graph, for a fixed graph h, of treewidth &omega; has an &omega;(&omega;) &times; &omega;(&omega;) grid graph as a minor. thus grid minors suffice to certify that h-minor-free graphs have large treewidth, up to constant factors. this strong relationship was previously known for the special cases of planar graphs and bounded-genus graphs, and is known not to hold for general graphs. the approach of this paper can be viewed more generally as a framework for extending combinatorial results on planar graphs to hold on h-minor-free graphs for any fixed h. our result has many combinatorial con-sequences on bidimensionality theory, parameter-treewidth bounds, separator theorems, and bounded local treewidth; each of these combinatorial results has several algorithmic consequences including subexponential fixed-parameter algorithms and approximation algorithms.
combination can be hard: approximability of the unique coverage problem. we prove semi-logarithmic inapproximability for a maximization problem called unique coverage: given a collection of sets, find a subcollection that maximizes the number of elements covered exactly once. specifically, we prove o(1/ log&sigma;(&epsilon;)n) inapproximability assuming that np &nsube; bptime(2n&epsilon;) for some &epsilon; > 0. we also prove o(1/log1/3-&epsilon; n) inapproximability, for any &epsilon; > 0, assuming that refuting random instances of 3sat is hard on average; and prove o(1/log n) inapproximability under a plausible hypothesis concerning the hardness of another problem, balanced bipartite independent set. we establish matching upper bounds up to exponents, even for a more general (budgeted) setting, giving an &omega;(1/log n)-approximation algorithm as well as an &omega;(1/log b)-approximation algorithm when every set has at most b elements. we also show that our inapproximability results extend to envy-free pricing, an important problem in computational economics. we describe how the (budgeted) unique coverage problem, motivated by real-world applications, has close connections to other theoretical problems including max cut, maximum coverage, and radio broad-casting.
retroactive data structures. we introduce a new data structuring paradigm in which operations can be performed on a data structure not only in the present but also in the past. in this new paradigm, called retroactive data structures, the historical sequence of operations performed on the data structure is not fixed. the data structure allows arbitrary insertion and deletion of operations at arbitrary times, subject only to consistency requirements. we initiate the study of retroactive data structures by formally defining the model and its variants. we prove that, unlike persistence, efficient retroactivity is not always achievable, so we go on to present several specific retroactive data structures.
interpolation search for non-independent data. we define a deterministic metric of "well-behaved data" that enables searching along the lines of interpolation search. specifically, define &delta; to be the ratio of distances between the farthest and nearest pair of adjacent elements. we develop a data structure that stores a dynamic set of n integers subject to insertions, deletions, and predecessor/successor queries in o(lg &delta;) time per operation. this result generalizes interpolation search and interpolation search trees smoothly to nonrandom (in particular, non-independent) input data. in this sense, we capture the amount of "pseudorandomness" required for effective interpolation search.
a linear lower bound on index size for text retrieval. most information-retrieval systems preprocess the data to produce an auxiliary index structure. empirically, it has been observed that there is a tradeoff between query response time and the size of the index. when indexing a large corpus, such as the web, the size of the index is an important consideration. in this case it would be ideal to produce an index that is substantially smaller than the text. in this work we prove a linear worst-case lower bound on the size of any index that reports the location (if any) of a substring in the text in time proportional to the length of the pattern. in other words, an index supporting linear-time substring searches requires about as much space as the original text. here "time" is measured in the number of bit probes to the text; an arbitrary amount of computation may be done on an arbitrary amount of the index. our lower bound applies to inverted word indices as well.
on universally easy classes for np-complete problems. we explore the natural question of whether all np-complete problems have a common restriction under which they are polynomially solvable. more precisely, we study what languages are universally easy in that their intersection with any np-complete problem is in p. in particular, we give a polynomial-time algorithm to determine whether a regular language is universally easy. while our approach is language-theoretic, the results bear directly on finding polynomial-time solutions to very broad and useful classes of problems.
experimental analysis of dynamic all pairs shortest path algorithms. we present the results of an extensive computational study on dynamic algorithms for all pairs shortest path problems. we describe our implementations of the recent dynamic algorithms of king [18] and of demetrescu and italiano [7], and compare them to the dynamic algorithm of ramalingam and reps [25] and to static algorithms on random, real-world and hard instances. our experimental data suggest that some of the dynamic algorithms and their algorithmic techniques can be really of practical value in many situations.
trading off space for passes in graph streaming problems. data stream processing has recently received increasing attention as a computational paradigm for dealing with massive data sets. surprisingly, no algorithm with both sublinear space and passes is known for natural graph problems in classical read-only streaming. motivated by technological factors of modern storage systems, some authors have recently started to investigate the computational power of less restrictive models where writing streams is allowed. in this article, we show that the use of intermediate temporary streams is powerful enough to provide effective space-passes tradeoffs for natural graph problems. in particular, for any space restriction of s bits, we show that single-source shortest paths in directed graphs with small positive integer edge weights can be solved in o((n log3/2 n)/&sqrt;s) passes. the result can be generalized to deal with multiple sources within the same bounds. this is the first known streaming algorithm for shortest paths in directed graphs. for undirected connectivity, we devise an o((n log n)/s) passes algorithm. both problems require &omega;(n/s) passes under the restrictions we consider. we also show that the model where intermediate temporary streams are allowed can be strictly more powerful than classical streaming for some problems, while maintaining all of its hardness for others.
oracles for distances avoiding a link-failure. for a directed graph g we consider queries of the form: "what is the shortest path distance from vertex x to vertex y in g avoiding a failed link (u, v), and what edge leaving x should we use to get on a such a shortest path?" we show that an oracle for such queries can be stored in o(n2 log n) space with a query time of o(log n). no non-trivial solution was known for this problem.
finding nucleolus of flow game. we study the algorithmic issues of finding the nucleolus of a flow game. the flow game is a cooperative game defined on a network d = (v, e; &omega;). the player set is e and the value of a coalition s &sube; e is defined as the value of the maximum flow from source to sink in the subnetwork induced by s. we show that the nucleolus of the flow game defined on a simple network (&omega;(e) = 1 for each e &isin; e) can be computed in polynomial time by a linear program duality approach, settling a twenty-three years old conjecture by kalai and zemel. in contrast, we prove that both computation and recognition of the nucleolus are np-hard for flow games with general capacity.
preemptive scheduling of parallel jobs on multiprocessors. we study the problem of processor scheduling for n parallel jobs applying the method of competitive analysis. we prove that for jobs with a single phase of parallelism, a preemptive scheduling algorithm without information about job execution time can achieve a mean completion time within $2-{2\over n+1}$ times the optimum. in other words, we prove a competitive ratio of $2-{2\over n+1}$. the result is extended to jobs with multiple phases of parallelism (which can be used to model jobs with sublinear speedup) and to interactive jobs (with phases during which the job has no cpu requirements) to derive solutions guaranteed to be within $4-{4\over n+1}$ times the optimum. in comparison with previous work, our assumption that job execution times are unknown prior to their completion is more realistic, our multiphased job model is more general, and our approximation ratio (for jobs with a single phase of parallelism) is tighter and cannot be improved. while this work presents theoretical results obtained using competitive analysis, we believe that the results provide insight into the performance of practical multiprocessor scheduling algorithms that operate in the absence of complete information.
matrix approximation and projective clustering via volume sampling. frieze et al. [17] proved that a small sample of rows of a given matrix a contains a low-rank approximation d that minimizes ||a - d||f to within small additive error, and the sampling can be done efficiently using just two passes over the matrix [12]. in this paper, we generalize this result in two ways. first, we prove that the additive error drops exponentially by iterating the sampling in an adaptive manner. using this result, we give a pass-efficient algorithm for computing low-rank approximation with reduced additive error. our second result is that using a natural distribution on subsets of rows (called volume sampling), there exists a subset of k rows whose span contains a factor (k + 1) relative approximation and a subset of k + k(k + 1)/&epsilon; rows whose span contains a 1+&epsilon; relative approximation. the existence of such a small certificate for multiplicative low-rank approximation leads to a ptas for the following projective clustering problem: given a set of points p in rd, and integers k, j, find a set of j subspaces f1, . . ., fj, each of dimension at most k, that minimize &sigma;p&isin;pmini d(p, fi)2.
perturbations and vertex removal in a 3d delaunay triangulation. though delaunay triangulations are very well known geometric data structures, the problem of the robust removal of a vertex in a three-dimensional delaunay triangulation is still a problem in practice.we propose a simple method that allows to remove any vertex even when the points are in very degenerate configurations. the solution is available in cgal.
delaunay triangulations approximate anchor hulls. recent results establish that a subset of the voronoi diagram of a point set that is sampled from the smooth boundary of a shape approximates the medial axis. the corresponding question for the dual delaunay triangulation is not addressed in the literature. we show that, for two-dimensional shapes, the delaunay triangulation approximates a specific structure which we call anchor hulls. as an application we demonstrate that our approximation result is useful for the problem of shape matching.
shape dimension and approximation from samples. there are many scientific and engineering applications where an automatic detection of shape dimension from sample data is necessary. topological dimensions of shapes constitute an important global feature of them. we present a voronoi based dimension detection algorithm that assigns a dimension to a sample point which is the topological dimension of the manifold it belongs to. based on this dimension detection, we also present an algorithm to approximate shapes of arbitrary dimension from their samples. our empirical results with data sets in three dimensions support our theory.
improved embeddings of graph metrics into random trees. over the past decade, numerous algorithms have been developed using the fact that the distances in any n-point metric (v, d) can be approximated to within o(log n) by distributions d over trees on the point set v [3, 10]. however, when the metric (v, d) is the shortest-path metric of an edge weighted graph g = (v, e), a natural requirement is to obtain such a result where the support of the distribution d is only over subtrees of g. for a long time, the best result satisfying this stronger requirement was a exp {&radic;log n log log n} distortion result of alon et al. [1]. in a recent breakthrough, elkin et al. [9] improved the distortion to o(log2 n log log n). (the best lower bound on the distortion is &omega;(log n), say, for the n-vertex grid [1].)in this paper, we give a construction that improves the distortion to o(log2 n), improving slightly on the eest construction. the main contribution of this paper is in the analysis: we use an algorithm which is similar to one used by eest to give a distortion of o(log3 n), but using a new probabilistic analysis, we eliminate one of the logarithmic factors. the ideas and techniques we use to obtain this logarithmic improvement seem orthogonal to those used earlier in such situations---e.g., seymour's decomposition scheme [4, 9] or the cutting procedures of ckr/frt [5, 10], both which do not seem to give a guarantee of better than o(log2 n log log n) for this problem. we hope that our ideas (perhaps in conjunction with some of these others) will ultimately lead to an o(log n) distortion embedding of graph metrics into distributions over their spanning trees.
certifying and repairing solutions to large lps how good are lp-solvers? state-of-the-art linear programming (lp) solvers give solutions without any warranty. solutions are not guaranteed to be optimal or even close to optimal. of course, it is generally believed that the solvers produce optimal or at least close to optimal solutions.we have implemented a system lpex which allows us to check this belief. more precisely, given an lp and a basis b, it determines whether the basis is primal feasible and/or dual feasible. it can also find the optimum starting from an arbitrary basis (or from scratch). it uses exact arithmetic to guarantee correctness of the results. the system is efficient enough to be applied to medium- to large-scale lps. we present results from the netlib benchmark suite.
tree exploration with little memory. a robot with k-bit memory has to explore a tree whose nodes are unlabeled and edge ports are locally labeled at each node. the robot has no a priori knowledge of the topology of the tree or of its size, and its aim is to traverse all the edges. while o(log δ) bits of memory suffice to explore any tree of maximum degree δ if stopping is not required, we show that bounded memory is not sufficient to explore with stop all trees of bounded degree (indeed ω (log log log n) bits of memory are needed for some such trees of size n). for the more demanding task requiring to stop at the starting node after completing exploration, we show a sharper lower bound ω (log n) on required memory size, and present an algorithm to accomplish this task with o(log2 n)-bit memory, for all n-node trees.
an improved approximation algorithm for combinatorial auctions with submodular bidders. we explore the allocation problem in combinatorial auctions with submodular bidders. we provide an e/e-1 approximation algorithm for this problem. moreover, our algorithm applies to the more general class of xos bidders. by presenting a matching unconditional lower bound in the communication model, we prove that the upper bound is tight for the xos class.our algorithm improves upon the previously known 2-approximation algorithm. in fact, we also exhibit another algorithm which obtains an approximation ratio better than 2 for submodular bidders, even in the value queries model.throughout the paper we highlight interesting connections between combinatorial auctions with xos and submodular bidders and various other combinatorial optimization problems. in particular, we discuss coverage problems and online problems.
lattice approximation and linear discrepency of totally unimodular matrices. this paper shows that the lattice approximation problem for totally unimodular matrices a &isin; rm&times;n can be solved efficiently and optimally via a linear programming approach. the complexity of our algorithm is &ogr;(log m) times the complexity of finding an extremal point of a polytope in rn described by 2(m + n) linear constraints. we also consider the worst-case approximability. this quantity is usually called linear discrepancy lindisc(a). for any totally unimodular m &times; n matrix a we show lindisc(a) &le; min{1 - 1/n+1, 1 - 1/m}. this bound is sharp. it proves spencer's conjecture lindisc(a) &le; (1 - 1/n+1) herdisc(a) for totally unimodular matrices. this seems to be the first time that linear programming is successfully used for a discrepancy problem.
non-independent randomized rounding. we investigate an extension of the randomized rounding technique introduced by raghavan and thompson. whereas their approach only requires that each variable is rounded with probabilities given by its fractional part, we also impose this condition on several sums of variables. thus in particular our roundings are not independent.we show that such non-independent randomized roundings exist if and only if the hypergraph corresponding to these dependencies is totally unimodular.
matrix rounding with low error in small submatrices. we show that any real valued matrix a can be rounded to an integer one b such that the error in all 2 x 2 (geometric) submatrices is less than 1.5, that is, we have |aij - bij| < 1 and |&sigma;i+1k=i &sigma;j+1l=j(akl - bkl| < 1.5 for all i, j. more precisely, an error of less than 1.5 - 3-2mn + 3-d+1 can be achieved in time o(mnd).
neighborhood preserving hashing and approximate queries. let $d \subseteq \sigma^n$ be a dictionary. we look for efficient data structures and algorithms to solve the following approximate query problem: given a query $u \in \sigma^n$ list all words $v \in d$ that are close to u in hamming distance.the problem reduces to the following combinatorial problem: hash the vertices of the n-dimensional hypercube into buckets so that (1) the c-neighborhood of each vertex is mapped into at most k buckets and (2) no bucket is too large.lower and upper bounds are given for the tradeoff between k and the size of the largest bucket. these results are used to derive bounds for the approximate query problem.
selecting the median. improving a long-standing result of schönhage, paterson, and pippenger [ j. comput. system sci., 13 (1976), pp. 184--199] we show that the median of a set containing $n$ elements can always be found using at most $c \cdot n$ comparisons, where c<2.95.
balls and bins models with feedback. we examine generalizations of the classical balls and bins models, where the probability a ball lands in a bin is proportional to the number of balls already in the bin raised to some exponent p. such systems exhibit positive or negative feedback, depending on the exponent p, with a phase transition occurring at p = 1. similar models have proven useful in economics and chemistry; for example, systems with positive feedback (p > 1) tend naturally toward monopoly. we provide several results and useful heuristics for these models, including showing a bound on the time to achieve monopoly with high probability.
sampling algorithms for regression and applications. we present and analyze a sampling algorithm for the basic linear-algebraic problem of l2 regression. the l2 regression (or least-squares fit) problem takes as input a matrix a &isin; rn&times;d (where we assume n &gt; d) and a target vector b &isin; rn, and it returns as output z = minx&isin;rd |b - ax|2. also of interest is xopt = a+b, where a+ is the moore-penrose generalized inverse, which is the minimum-length vector achieving the minimum. our algorithm randomly samples r rows from the matrix a and vector b to construct an induced l2 regression problem with many fewer rows, but with the same number of columns. a crucial feature of the algorithm is the nonuniform sampling probabilities. these probabilities depend in a sophisticated manner on the lengths, i.e., the euclidean norms, of the rows of the left singular vectors of a and the manner in which b lies in the complement of the column space of a. under appropriate assumptions, we show relative error approximations for both z and xopt. applications of this sampling methodology are briefly discussed.
fully persistent lists with catenation. this paper considers the problem of representing stacks with catenation so that any stack, old or new, is available for access or update operations. this problem arises in the implementation of list-based and functional programming languages. a solution is proposed requiring constant time and space for each stack operation except catenation, which requires o(log log k) time and space. here k is the number of stack operations done before the catenation. all the resource bounds are amortized over the sequence of operations.
fast distributed algorithms for (weakly) connected dominating sets and linear-size skeletons. motivated by routing issues in ad hoc networks, we present polylogarithmic-time distributed algorithms for two problems. given a network, we first show how to compute connected and weakly connected dominating sets whose size is at most o(log@d) times the optimum, @d being the maximum degree of the input network. this is best-possible if np@?dtime[n^o^(^l^o^g^l^o^g^n^)] and if the processors are required to run in polynomial-time. we then show how to construct dominating sets that have the above properties, as well as the ''low stretch'' property that any two adjacent nodes in the network have their dominators at a distance of at most o(logn) in the output network. (given a dominating set s, a dominator of a vertex u is any v@?s such that the distance between u and v is at most one.) we also show our time bounds to be essentially optimal.
localizing a robot with minimum travel. we consider the problem of localizing a robot in a known environment modeled by a simple polygon p. we assume that the robot has a map of p but is placed at an unknown location inside p. from its initial location, the robot sees a set of points called the visibility polygon v of its location. in general, sensing at a single point will not suffice to uniquely localize the robot, since the set h of points in p with visibility polygon v may have more than one element. hence, the robot must move around and use range sensing and a compass to determine its position (i.e., localize itself). we seek a strategy that minimizes the distance the robot travels to determine its exact location.we show that the problem of localizing a robot with minimum travel is np-hard. we then give a polynomial time approximation scheme that causes the robot to travel a distance of at most (k - 1)d, where k = |h|, which is no greater than the number of reflex vertices of p, and d is the length of a minimum length tour that would allow the robot to verify its true initial location by sensing. we also show that this bound is the best possible.
on validating planar worlds. we present an optimal linear time algorithm for solving a map validation problem: a robot equipped with one portable marker must determine the correctness of a given map of its graph-like world, modelled as a possibly non-planar embedding of a planar graph.
an approximation algorithm for cutting out convex polygons. we provide an o(logn)-approximation algorithm for the following problem. given a convex n-gon p, drawn on a convex piece of paper, cut p out of the piece of paper in the cheapest possible way. no polynomial-time approximation algorithm was known for this problem posed in 1985.
approximation algorithms for tsp with neighborhoods in the plane. in the euclidean tsp with neighborhoods (tspn), we are given a collection of n regions (neighborhoods) and we seek a shortest tour that visits each region. as a generalization of the classical euclidean tsp, tspn is also np-hard. in this paper, we present new approximation results for the tspn, including (1) a constant-factor approximation algorithm for the case of arbitrary connected neighborhoods having comparable diameters; and (2) a ptas for the important special case of disjoint unit disk neighborhoods (or nearly disjoint, nearly-unit disks). our methods also yield improved approximation ratios for various special classes of neighborhoods, which have previously been studied. further, we give a linear-time o(1)-approximation algorithm for the case of neighborhoods that are (infinite) straight lines.
optimal constrained graph exploration. we address the problem of exploring an unknown graph g = (v, e) from a given start node s with either a tethered robot or a robot with a fuel tank of limited capacity, the former being a tighter constraint. in both variations of the problem, the robot can only move along the edges of the graph, i.e, it cannot jump between non-adjacent vertices. in the tethered robot case, if the tether (rope) has length l, then the robot must remain within distance l from the start node s. in the second variation, a fuel tank of limited capacity forces the robot to return to s after traversing c edges. the efficiency of algorithms for both variations of the problem is measured by the number of edges traversed during the exploration. we present an algorithm for a tethered robot which explores the graph in &ogr;(&brvbar;e&brvbar;) edge traversals. the problem of exploration using a robot with a limited fuel tank capacity can be solved with a simple reduction from the tethered robot case and also yields a &ogr;(&brvbar;e&brvbar;) algorithm. this improves on the previous best known bound of &ogr;(&brvbar;e&brvbar; + &brvbar;v&brvbar;log 2&brvbar;v&brvbar;) in [4]. since the lower bound for the graph exploration problems is &brvbar;e&brvbar;, our algorithm is optimal, thus answering the open problem of awerbuch, betke, rivest, and singh [3].
broadcast scheduling: when fairness is fine. we investigate server scheduling policies to minimize user perceived latency in a client-server system where the server uses broadcast communication. we show that no o(1)-competitive online algorithms exist for this problem. we consider the intuitive algorithm bequi that broadcasts all requested files at a rate proportional to the number of out-standing requests for that file. we show that bequi is an o(1)-speed o(1)-approximation algorithm. we give another algorithm bequi-edf, and show that bequi-edf is also an o(1)-speed o(1)-approximation algorithm. however, bequi-edf has the advantage that it preempts each broadcast on average at most once and will never preempt if the data items have unit size.
a maiden analysis of longest wait first. we consider server scheduling strategies to minimize average flow time in a multicast pull system where data items have uniform size. the algorithm longest wait first (lwf) always services the page where the aggregate waiting times of the outstanding requests for that page is maximized. we provide the first non-trivial analysis of the worst case performance of lwf. on the negative side, we show that lwf is not s-speed o(1)-competitive for s < 1+&radic;5/2. on the positive side, we show that lwf is 6-speed o(1)-competitive.
cake cutting really is not a piece of cake. we consider the well-known cake cutting problem in which a protocol wants to divide a cake among n &ge; 2 players in such a way that each player believes that they got a fair share. the standard robertson-webb model allows the protocol to make two types of queries, evaluation and cut, to the players. a deterministic divide-and-conquer protocol with complexity o(n log n) is known. we provide the first an &omega;(n log n) lower bound on the complexity of any deterministic protocol in the standard model. this improves previous lower bounds, in that the protocol is allowed to assign to a player a piece that is a union of intervals and only guarantee approximate fairness. we accomplish this by lower bounding the complexity to find, for a single player, a piece of cake that is both rich in value, and thin in width. we then introduce a version of cake cutting in which the players are able to cut with only finite precision. in this case, we can extend the &omega;(n log n) lower bound to include randomized protocols.
morphing between polylines. given two non-intersecting simple polylines in the plane, we study the problem of continuously transforming or morphing one polyline into the other. our morphing strategies have the desirable property that every intermediate polyline is also simple. we also guarantee that no portion of the polylines to be morphed is stretched or compressed by more than a user-defined parameter during the entire morphing. our algorithms are based on the morphing width, a new metric we have developed for measuring the similarity between two polylines. we develop an algorithm that computes the morphing width of the two polylines and constructs a corresponding morphing strategy in &ogr;(n2 log2 n) time using &ogr;(n2) space, where n is the total number of vertices in the polylines. we describe another algorithm that computes a factor-2 approximation of the morphing width and a corresponding morphing scheme in &ogr;(n log n) time.
pattern matching for sets of segments. in this paper we present algorithms for a number of problems in geometric pattern matching where the input consist of a collections of segments in the plain. our work consists of two main parts. in the first, we address problems and measures that relate to collections of orthogonal line segments in the plane. such collections arise naturally from problems in mapping buildings and robot exploration. we propose a new measure of segment similarity called a coverage measure, and present efficient algorithms for maximising this measure between sets of axis-parallel segments under translations. our algorithms run in time &ogr;(n3polylogn) in the general case, and run in time &ogr;(n3polylogn) for the case when all segments are horizontal. in addition, we show that when restricted to translations that are only vertical, the hausdorff distance between two sets of horizontal segments can be computed in time roughly &ogr;(n3/2polylog n). these algorithms are significant improvements over the general algorithm of chew et al. that takes time &ogr;(n4 log2 n). in the second part of this paper we address the problem of matching polygonal chains. we study the well known fr&eacute;chet distance, and present the first algorithm for computing the fr&eacute;chet distance under general translations. our methods also yield algorithms for computing a generalization of the fr&eacute;chet distance, and we present a simple approximation algorithm for the fr&eacute;chet distance and its generalization that runs in time &ogr;(n2polylogn).
a combinatorial algorithm for computing a maximum independent set in a t-perfect graph. we present a combinatorial polynomial time algorithm to compute a maximum stable set of a t-perfect graph. the algorithm rests on an &epsilon;-approximation algorithm for general set covering and packing problems and is combinatorial in the sense that it does not use an explicit linear programming algorithm or methods from linear algebra or convex geometry. instead our algorithm is based on basic arithmetic operations and comparisons of rational numbers which are of polynomial binary encoding size in the input.
an improved approximation algorithm for virtual private network design. virtual private network design deals with the reservation of capacities in a network, such that the nodes can share communication. each node in the network has associated upper bounds on the amount of flow that it can send to the network and receive from the network respectively. the problem then is to reserve capacities at minimum cost and to compute paths between every pair of nodes such that all valid traffic-matrices can be routed along the corresponding paths.in this paper we present a simple 4.74-approximation algorithm for virtual private network design. the previous best approximation algorithm for this problem achieves a ratio of 5.55 (gupta, kumar, and roughgarden stoc'03).
0/1 optimization and 0/1 primal separation are equivalent. the 0/1 primal separation problem is: given an extreme point x of a 0/1 polytope p and some point x*, find an inequality which is tight at x, violated by x* and valid for p or assert that no such inequality exists. it is known that this separation variant can be reduced to the standard separation problem for p. we show that 0/1 optimization and 0/1 primal separation are polynomial time equivalent. this implies that the problems 0/1 optimization, 0/1 standard separation, 0/1 augmentation, and 0/1 primal separation are polynomial time equivalent.we apply this result to the perfect matching problem. here, primal separation is easier than its standard version. we present an algorithm for primal separation, which rests only on simple max-flow computations. consequently, we obtain a very simple proof that a maximum weight perfect matching of a graph can be computed in polynomial time. in contrast, the known standard separation method involves padberg and rao's minimum odd cut algorithm, which itself is based on the construction of a gomory-hu tree.
a faster distributed protocol for constructing a minimum spanning tree. this paper studies the problem of constructing a minimum-weight spanning tree (mst) in a distributed network. this is one of the most important problems in the area of distributed computing. there is a long line of gradually improving protocols for this problem, and the state of the art today is a protocol with running time o(&and;(g) + &radic;n log* n) due to kutten and peleg [kp95], where &and;(g) denotes the diameter of the graph g. peleg and rubinovich [pr99] have shown that (&radic;n) time is required for constructing mst even on graphs of small diameter, and claimed that their result "establishes the asymptotic near-optimality" of the protocol of [kp95].in this paper we refine this claim, and devise a protocol that constructs the mst in &otilde;(&mu;(g = w + &radic;n) rounds, where &mu;(g,&mu;) is the mst-radius of the graph. the ratio between the diameter and the mst-radius may be as large as &theta;(n), and, consequently, on some inputs our protocol is faster than the protocol of [kp95] by a factor of (&radic;n). also, on every input, the running time of our protocol is never greater than twice the running time of the protocol of [kp95].as part of our protocol for constructing an mst, we develop a protocol for constructing neighborhood covers with a drastically improved running time. the latter result may be of independent interest.
improved schedule for radio broadcast. we show that for every radio network g = (v, e) and source s &epsilon; v, there exists a radio broadcast schedule for g of length rad(g, s) + o(&radic; rad(g, s). log2 n) = o(rad(g, s) + log4 n), where rad(g, s) is the radius of the radio network g with respect to the source s. this result improves the previously best-known upper bound of o(rad(g, s)+log5 n) due to gaber and mansour [12].for graphs with small genus, particularly for planar graphs, we provide an even better upper bound of rad(g, s) + o(&radic; rad(g, s). log n + log3 n) = o(rad(g, s) + log3 n).
frugality in path auctions. we consider the problem of picking (buying) an inexpensive s -- t path in a graph where edges are owned by independent (selfish) agents, and the cost of an edge is known to its owner only. we study the problem of finding frugal mechanisms for this task, i.e. we investigate the payments the buyer must make in order to buy a path.first, we show that any mechanism with (weakly) dominant strategies (or, equivalently, any truthful mechanism) for the agents can force the buyer to make very large payments. namely, for every such mechanism, the buyer can be forced to pay c(p) + 1/2k(c(q) -- c(p)), where c(p) is the cost of the shortest path, c(q) is the cost of the second-shortest path, and k is the number of edges in p. this extends the previous work of archer and tardos [1], who showed a similar lower bound for a subclass of truthful mechanisms called min-function mechanisms. our lower bounds have no such limitations on the mechanism.motivated by this lower bound, we study mechanisms for this problem providing bayes-nash equilibrium strategies for the agents. in this class, we identify the optimal mechanism with regard to total payment. we then demonstrate a separation in terms of average overpayments between the classical vcg mechanism and the optimal mechanism showing that under various natural distributions of edge costs, the optimal mechanism pays at most logarithmic factor more than the actual cost, whereas vcg pays &radic;k times the actual cost. on the other hand, we also show that the optimal mechanism does incur at least a constant factor overpayment in natural distributions of edge costs. since our mechanism is optimal, this gives a lower bound on all mechanisms with bayes--nash equilibria.
approximating minimum max-stretch spanning trees on unweighted graphs. given a graph g and a spanning tree t of g, we say that t is a tree t-spanner of g if the distance between every pair of vertices in t is at most t times their distance in g. the problem of finding a tree t-spanner minimizing t is referred to as the minimum max-stretch spanning tree (mmst) problem. this paper concerns the mmst problem on unweighted graphs. the problem is known to be np-hard, and the paper presents an o(log n) approximation algorithm for it.
a tight upper bound on the probabilistic embedding of series-parallel graphs. in [6] it is shown that every graph can be probabilistically embedded into a distribution over its spanning trees with expected distortion o(log2 n log log n), narrowing the gap left by [1], where a lower bound of &omega;(log n) is established. this lower bound holds even for the class of series-parallel graphs as proved in [8]. in this paper we close this gap for series-parallel graphs, namely we prove that every n-vertex series-parallel graph can be probabilistically embedded into a distribution over its spanning trees with expected stretch o(log n) for every two vertices. we gain our upper bound by presenting a polynomial time probabilistic algorithm that constructs spanning trees with low expected stretch. this probabilistic algorithm can be derandomized to yield a deterministic polynomial time algorithm for constructing a spanning tree of a given series-parallel graph g, whose communication cost is at most o(log n) times larger than that of g.
derandomized dimensionality reduction with applications. the johnson-lindenstrauss lemma provides a way to map a number of points in high-dimensional space into a low-dimensional space, with only a small distortion of the distances between the points. the proofs of the lemma are non-constructive: they show that a random mapping induces small distortions with high probability, but they do not construct the actual mapping. in this paper, we provide a procedure that constructs such a mapping deterministically in time almost linear in the number of distances to preserve times the dimension of the original space. we then use that result (together with nisan's pseudorandom generator) to obtain an efficient derandomization of several approximation algorithms based on semidefinite programming.
harmonic broadcasting is optimal. harmonic broadcasting was introduced by juhn and tseng as a way to reduce the bandwidth requirements required for video-on-demand broadcasting. in this paper, we note that harmonic broadcasting is actually a special case of the priority encoded transmission scheme introduced by albanese et al. and prove---using an information theoretic argument---that it is impossible to achieve the design goals of harmonic broadcasting using a shorter encoding.
parallel processor scheduling with delay constraints. we consider the problem of scheduling unit-length jobs on identical parallel machines such that the makespan of the resulting schedule is minimized. precedence constraints impose a partial order on the jobs, and both communication and precedence delays impose relative timing constraints on dependent jobs. the combination of these two types of timing constraints naturally models the instruction scheduling problem that occurs during software compilation for state-of-the-art vliw (very long instruction word) processors and multiprocessor parallel machines. we present the first known polynomial-time algorithm for the case where the precedence constraint graph is a forest of in-trees (or a forest of out-trees), the number of machines m is fixed, and the delays (which are a function of both the job pair and the machines on which they run) are bounded by a constant d. our algorithm relies on a new structural theorem for scheduling jobs with arbitrary precedence constraints. given an instance with many independent dags, the theorem shows how to convert, in linear time, a schedule s for only the largest dags into a complete schedule that is either optimal or has the same makespan as s.
improved algorithms for 3-coloring, 3-edge-coloring, and constraint satisfaction. we consider worst case time bounds for np-complete problems including 3-sat, 3-coloring, 3-edge-coloring, and 3-list-coloring. our algorithms are based on a constraint satisfaction (csp) formulation of these problems; 3-sat is equivalent to (2, 3)-csp while the other problems above are special cases of (3, 2)-csp. we give a fast algorithm for (3, 2)-csp and use it to improve the time bounds for solving the other problems listed above. our techniques involve a mixture of davis-putnam-style backtracking with more sophisticated matching and network flow based ideas.
dynamic generators of topologically embedded graphs. we provide a data structure for maintaining an embedding of a graph on a surface (represented combinatorially by a permutation of edges around each vertex) and computing generators of the fundamental group of the surface, in amortized time o(log n + log g(log log g)3) per update on a surface of genus g; we can also test orientability of the surface in the same time, and maintain the minimum and maximum spanning tree of the graph in time o(log n + log4 g) per update. our data structure allows edge insertion and deletion as well as the dual operations; these operations may implicitly change the genus of the embedding surface. we apply similar ideas to improve the constant factor in a separator theorem for low-genus graphs, and to find in linear time a tree-decomposition of low-genus low-diameter graphs.
quasiconvex analysis of backtracking algorithms. we consider a class of multivariate recurrences frequently arising in the worst case analysis of davis-putnam-style exponential time backtracking algorithms for np-hard problems. we describe a technique for proving asymptotic upper bounds on these recurrences, by using a suitable weight function to reduce the problem to that of solving univariate linear recurrences; show how to use quasiconvex programming to determine the weight function yielding the smallest upper bound; and prove that the resulting upper bounds are within a polynomial factor of the true asymptotics of the recurrence. we develop and implement a multiple-gradient descent algorithm for the resulting quasiconvex programs, using a real-number arithmetic package for guaranteed accuracy of the computed worst case time bounds.
testing bipartiteness of geometric intersection graphs. we show how to test the bipartiteness of an intersection graph of n line segments or simple polygons in the plane, or of balls in rd, in time o(n log n). more generally we find subquadratic algorithms for connectivity and bipartiteness testing of intersection graphs of a broad class of geometric objects. for unit balls in rd, connectivity testing has equivalent randomized complexity to construction of euclidean minimum spanning trees, and for line segments in the plane connectivity testing has the same lower bounds as hopcroft's problem; therefore, for these problems, connectivity is unlikely to be solved as efficiently as bipartiteness. for line segments or planar disks, testing k-colorability of intersection graphs for k > 2 is np-complete.
all maximal independent sets and dynamic dominance for sparse graphs. we describe algorithms, based on avis and fukuda's reverse search paradigm, for listing all maximal independent sets in a sparse graph in polynomial time and delay per output. for bounded degree graphs, our algorithms take constant time per set generated; for minor-closed graph families, the time is o(n) per set, and for more general sparse graph families we achieve subquadratic time per set. we also describe new data structures for maintaining a dynamic vertex set s in a sparse or minor-closed graph family, and querying the number of vertices not dominated by s; for minor-closed graph families the time per update is constant, while it is sublinear for any sparse graph family. we can also maintain a dynamic vertex set in an arbitrary m-edge graph and test the independence of the maintained set in time o(&radic;m) per update. we use the domination data structures as part of our enumeration algorithms.
approximating the minimum weight triangulation. in o(n log n) time we compute a triangulation with o(n) new points, and no obtuse triangles, that has length within a constant factor of the minimum possible. we also approximate the minimum weight steiner triangulation using triangulations with no sharp angles. no previous polyonomial time triangulation achieved an approximation factor better than o(log n).
new algorithms for minimum area -gons. given a set p of n points in the plane, we wish to find a set q &sub; p of k points for which the convex hull conv(q> has the minimum area. we solve this, and the related problem of finding a minimum area convex k-gon, in time o(n2 log n) for fixed k, almost matching known bounds for the minimum area triangle problem. our algorithm is based on finding a certain number of nearest vertical neighbors to each line segment determined by two input points. we use a classical result of ramsey theory to prove that these nearest neighbors suffice to determine the minimum convex k-gon.
fast hierarchical clustering and other applications of dynamic closest pairs. we develop data structures for dynamic closest pair problems with arbitrary distance functions, that do not necessarily come from any geometric structure on the objects. based on a technique previously used by the author for euclidean closest pairs, we show how to insert and delete objects from an <i>n</i>-object set, maintaining the closest pair, in <i>o</i>(<i>n</i> log<sup>2</sup> <i>n</i>) time per update and <i>o</i>(<i>n</i>) space. with quadratic space, we can instead use a quadtree-like structure to achieve an optimal time bound, <i>o</i>(<i>n</i>) per update. we apply these data structures to hierarchical clustering, greedy matching, and tsp heuristics, and discuss other potential applications in machine learning, gröbner bases, and local improvement algorithms for partition and placement problems. experiments show our new methods to be faster in practice than previously used heuristics.
internet packet filter management and rectangle geometry. we consider rule sets for internet packet routing and filtering, where each rule consists of a range of source addresses, a range of destination addresses, a priority, and an action. a given packet should be handled by the action from the maximum priority rule that matches its source and destination. we describe new data structures for quickly finding the rule matching an incoming packet, in near-linear space, and a new algorithm for determining whether a rule set contains any conflicts, in time &ogr;(n3/2).
fast approximation of centrality. social studies researchers use graphs to model group activities in social networks. an important property in this context is the centrality of a vertex: the inverse of the average distance to each other vertex. we describe a randomized approximation algorithm for centrality in weighted graphs. for graphs exhibiting the small world phenomenon, our method estimates the centrality of all vertices with high probability within a (1 + &isin;) factor in near-linear time.
optimal online bounded space multidimensional packing. we solve an open problem in the literature by providing an online algorithm for multidimensional bin packing that uses only bounded space. to achieve this, we introduce a new technique for classifying the items to be packed. we show that our algorithm is optimal among bounded space algorithms for any dimension d > 1. its asymptotic performance ratio is (ii&infin;)d, where ii&infin; &asymp; 1:691 is the asymptotic performance ratio of the one-dimensional algorithm harmonic. a modified version of this algorithm for the case where all items are hypercubes is also shown to be optimal. its asymptotic performance ratio is sublinear in d.additionally, for the special case of packing squares in two-dimensional bins, we present a new unbounded space online algorithm with asymptotic performance ratio of at most 2.271. we also present an approximation algorithm for the offline problem with approximation ratio of 16/11.
lower bounds for external algebraic decision trees. we propose a natural extension of algebraic decision trees to the external-memory setting, where the cost of disk operations overwhelms cpu time, and prove a tight lower bound of &omega;(n logm n) on the complexity of both sorting and element uniqueness in this model of computation. we also prove a &omega;(min{n logm n, n}) lower bound for both problems in a less restrictive model, which requires only that the worst-case internal-memory computation time is finite. standard reductions immediately generalize these lower bounds to a large number of fundamental computational geometry problems.
greedy optimal homotopy and homology generators. we describe simple greedy algorithms to construct the shortest set of loops that generates either the fundamental group (with a given basepoint) or the first homology group (over any fixed coefficient field) of any oriented 2-manifold. in particular, we show that the shortest set of loops that generate the fundamental group of any oriented combinatorial 2-manifold, with any given basepoint, can be constructed in o(n log n) time using a straightforward application of dijkstra's shortest path algorithm. this solves an open problem of colin de verdi&egrave;re and lazarus.
np-hardness of broadcast scheduling and inapproximability of single-source unsplittable min-cost flow. we consider the version of broadcast scheduling where a server can transmit w messages of a given set at each time-step, answering previously made requests for these messages. the goal is to minimize the average response time (art) if the amount of requests is known in advance for each time-step and message. we prove that this problem is np-hard, thus answering an open question stated by kalyanasundaram, pruhs and velauthapillai (proceedings of esa 2000, lncs 1879, 2000, pp. 290---301). furthermore, we present an approximation algorithm that is allowed to send several messages at once. using six channels for transmissions, the algorithm achieves an art that is at least as good as the optimal solution using one channel.from the np-hardness of broadcast scheduling we derive a new inapproximability result of (2 ¿ ¿, 1) for the (congestion, cost) bicriteria version of the single source unsplittable min-cost flow problem, for arbitrary ¿ > 0. the result holds even in the often considered case where the maximum demand is less than or equal to the minimum edge capacity (d max ¿ u min), a case for which an algorithm with ratio (3, 1) was presented by skutella.
polynomial-time approximation schemes for geometric graphs. a disk graph is the intersection graph of a set of disks with arbitrary diameters in the plane. for the case that the disk representation is given, we present polynomial-time approximation schemes (ptass) for the maximum weight independent set problem (selecting disjoint disks of maximum total weight) and for the minimum weight vertex cover problem in disk graphs. these are the first known ptass for np-hard optimization problems on disk graphs. they are based on a novel recursive subdivision of the plane that allows applying a shifting strategy on different levels simultaneously, so that a dynamic programming approach becomes feasible. the ptass for disk graphs represent a common generalization of previous results for planar graphs and unit disk graphs. they can be extended to intersection graphs of other &ldquo;disk-like&rdquo; geometric objects (such as squares or regular polygons), also in higher dimensions.
structural and algorithmic aspects of massive social networks. we study the algorithmic and structural properties of very large, realistic social contact networks. we consider the social network for the city of portland, oregon, usa, developed as a part of the transims/episims project at the los alamos national laboratory. the most expressive social contact network is a bipartite graph, with two types of nodes: people and locations; edges represent people visiting locations on a typical day. three types of results are presented. (i) our empirical results show that many basic characteristics of the dataset are well-modeled by a random graph approach suggested by fan chung graham and lincoln lu (the cl-model), with a power-law degree distribution. (ii) we obtain fast approximation algorithms for computing basic structural properties such as clustering coefficients and shortest paths distribution. we also study the dominating set problem for such networks; this problem arose in connection with optimal sensor-placement for disease-detection. we present a fast approximation algorithm for computing near-optimal dominating sets. (iii) given the close approximations provided by the cl-model to our original dataset and the large data-volume, we investigate fast methods for generating such random graphs. we present methods that can generate such a random network in near-linear time, and show that these variants asymptotically share many key features of the cl-model, and also match the portland social network.the structural results have been used to study the impact of policy decisions for controlling large-scale epidemics in urban environments.
restructuring ordered binary trees. we consider the problem of restructuring an ordered binary tree t, preserving the in-order sequence of its nodes, so as to reduce its height to some target value h. such a restructuring necessarily involves the downward displacement of some of the nodes of t. our results, focusing both on the maximum displacement over all nodes and on the maximum displacement over leaves only, provide (i) an explicit tradeoff between the worst-case displacement and the height restriction (including a family of trees that exhibit the worst-case displacements) and (ii) efficient algorithms to achieve height-restricted restructuring while minimizing the maximum node displacement.
optimally scheduling video-on-demand to minimize delay when server and receiver bandwidth may differ. we establish tight bounds on the intrinsic cost (either minimizing delay d for fixed server and receiver bandwidths, or minimizing server bandwidth for fixed delay and receiver bandwidth) of broadcasting a movie of length m over a channel of bandwidth s in such a way that a receiver (with bandwidth r), starting at an arbitrary time t, can download the movie so that it can begin playback after a delay of at most d time units.our bounds are realized by a simple abstract protocol that partitions the movie into a fixed number of segments, partitions the server bandwidth into an equivalent number of equal bandwidth subchannels, and broadcasts each segment repeatedly on its flown subchannel. this protocol can be implemented as a concrete discrete protocol in which movie information is packaged into discrete fixed length packets using only a modest overhead (measured in terms of increased delay or server bandwidth).our primary contribution is a lower bound on the required delay that applies in a very general model of communication. this lower bound matches the behaviour of our abstract protocol in the limit as the number of segments approaches infinity. we are also able to relate its behaviour to arbitrary protocols that have a fixed number of segments.
fast convergence of selfish rerouting. we consider n anonymous selfish users that route their communication through m parallel links. the users are allowed to reroute, concurrently, from overloaded links to underloaded links. the different rerouting decisions are concurrent, randomized and independent. the rerouting process terminates when the system reaches a nash equilibrium, in which no user can improve its state.we study the convergence rate of several migration policies. the first is a very natural policy, which balances the expected load on the links, for the case that all users are identical and apply it, we show that the rerouting terminates in expected o(log log n + log m) stages. later, we consider the nash rerouting policies class, in which every rerouting stage is a nash equilibrium and the users are greedy with respect to the next load they observe. we show a similar termination bounds for this class. we study the structural properties of the nash rerouting policies, and derive both existence result and an efficient algorithm for the case that the number of links is small. we also show that if the users have different weights then there exists a set of weights such that every nash rerouting terminates in &omega;(&radic;n) stages with high probability.
an approximation algorithm for the group steiner problem. the input in the group-steiner problem consists of an undirected connected graph with a cost function p(e) over the edges and a collection of subsets of vertices {gi}. each subset gi is called a group and the vertices in &cup; gi are called terminals. the goal is to find a minimum cost tree that contains at least one terminal from every group.we give the first combinatorial polylogarithmic ratio approximation for the problem on trees. let m denote the number of groups and s denote the number of terminals. the approximation ratio of our algorithm is o(log s &middot; log m/log log s) = o(log2n/log log n). this is an improvement by a &theta;(log log n) factor over the previously best known approximation ratio for the group steiner problem on trees [gkr98].our result carries over to the group steiner problem on general graphs and to the covering steiner problem. garg et al. [gkr98] presented a reduction of the group steiner problem on general graphs to trees. their reduction employs bartal's [b98] approximation of graph metrics by tree metrics. our algorithm on trees implies an approximation algorithm of ratio o(log s &middot; log m &middot; log n &middot; log log n/log log s) = o(log3n) for the group steiner problem on general graphs. the previously best known approximation ratio for this problem on general graphs, as a function of n, is o(log3n &middot; log log n) [gkr98]. our algorithm in conjunction with ideas of [eks01] gives an o(log s &middot; log m &middot; log n &middot; log log n/log log s) = o(log3n)-approximation ratio for the more general covering steiner problem, improving the best known approximation ratio (as a function of n) for the covering steiner problem by a &theta;(log log n) factor.
layout area of the hypercube (extended abstract). in this paper we study the square grid area required for laying out hl, the boolean hypercube of n = 2l vertices. it is shown that this area is 4/9n2 + o(n2). we describe a layout which occupies this much area and prove that no layout of less area exists.
output-sensitive construction of the union of triangles. we present an efficient algorithm for the following problem: given a collection t = {&delta;1.....,&delta;n} of n triangles in the plane, such that there exists a subset s &sub; t (unknown to us), of &cup;&delta; &isin; s &delta; = &cup;&delta;&delta;&isin;t&delta; n triangles, such that &zeta; &laquo; construct efficiently the union of the triangles in t. we show that this problem can be solved in subquadratic time. in our solution, we use the approximate disjoint-cover (dc) algorithm, presented as a heuristics in [9]. we present a detailed implementation of this method, which combines a variety of techniques related to range-searching in two dimensions. we provide a rigorous analysis of its performance in the above setting, showing that it does indeed run in subquadratic time (for a reasonable range of &zeta;).
comparing top k lists. motivated by several applications, we introduce various distance measures between "top k lists." some of these distance measures are metrics, while others are not. for each of these latter distance measures, we show that they are "almost" a metric in the following two seemingly unrelated aspects:(i) they satisfy a relaxed version of the polygonal (hence, triangle) inequality, and(ii) there is a metric with positive constant multiples that bound our measure above and below.this is not a coincidence---we show that these two notions of almost being a metric are the same. based on the second notion, we define two distance measures to be equivalent if they are bounded above and below by constant multiples of each other. we thereby identify a large and robust equivalence class of distance measures.besides the applications to the task of identifying good notions of (dis)similarity between two top k lists, our results imply polynomial-time constant-factor approximation algorithms for the rank aggregation problem with respect to a large class of distance measures.
the k-traveling repairman problem. we consider the k-traveling repairman problem, a generalization of the metric traveling repairman problem, also known as the minimum latency problem, to multiple repairmen. we give an 8.497&alpha;-approximation algorithm for this generalization, where &alpha; denotes the best achievable approximation factor for the problem of finding the least cost rooted tree spanning i vertices (i-mst) problem. this can be compared with the best known approximation algorithm for the case k = 1, which is 3.59&alpha;. we are aware of no previous work on the approximability of the present problem.in addition, we give a simple proof of the 3.59&alpha;approximation result which can be extended to the case of multiple repairmen.
an improved approximation algorithm for the 0-extension problem. given a graph g = (v, e), a set of terminals t &sube; v, and a metric d on t, the 0-extension problem is to assign vertices in v to terminals, so that the sum, over all edges e, of the distance (under d) between the terminals to which the end points of e are assigned, is minimized. this problem was first studied by karzanov. calinescu, karloff and rabani gave an o(logk) approximation algorithm based on a linear programming relaxation for the problem, where k is the number of terminals. we improve on this bound, and give an o(log k/log log k) approximation algorithm for the problem.
on local register allocation. in this paper, we consider the problem of local register allocation (lra): given a sequence of instructions (basic block) and a number of general purpose registers, find the schedule of variables in registers that minimizes the total traffic between cpu and the memory system. local register allocation has been studied for more than thirty years in the theory and compiler communities. it was not known if lra is np-hard, but no subexponential time algorithm was known. furthermore, the most popular heuristics in use in compilers can perform arbitrarily poorly in the worst case. in this paper, we present the following results: we show that the local register allocation problem is np-hard. we show that a variant of the furthest-first heuristic achieves a good approximation ratio. we give a 2-approximation algorithm for lra. we report the experimental performance of a branch-and-bound algorithm and both approximation algorithms on standard benchmarks.
two algorithms for general list matrix partitions. list matrix partitions are restricted binary list constraint satisfaction problems which generalize list homomorphisms and many graph partition problems arising, e.g., in the study of perfect graphs. most of the existing algorithms apply to concrete small matrices, i.e., to partitions into a small number of parts. we focus on two general classes of partition problems, provide algorithms for their solution, and discuss their implications.the first is an o(nr+2)-algorithm for the list m-partition problem where m is any r by r matrix over subsets of {0, 1}, which has the "bisplit property". this algorithm can be applied to recognize so-called k-bisplit graphs in polynomial time, yielding a solution of an open problem from [2].the second is an algorithm running in time (rn)o(log r log n/log log n)no(log2r) for the list m-partition problem where m is any r &times; r matrix over subsets of {0,1,...,q- 1}, with the "incomplete property". this algorithm applies to all non-np-complete list m-partition problems with r = 3, and it improves the running time of the quasi-polynomial algorithm for the "stubborn problem" from [5], and for the "edge-free three-coloring problem" from [12].
finding large cycles in hamiltonian graphs. we show how to find in hamiltonian graphs a cycle of length n^@w^(^1^/^l^o^g^l^o^g^n^)=exp(@w(logn/loglogn)). this is a consequence of a more general result in which we show that if g has a maximum degree d and has a cycle with k vertices (or a 3-cyclable minor h with k vertices), then we can find in o(n^3) time a cycle in g of length k^@w^(^1^/^l^o^g^d^). from this we infer that if g has a cycle of length k, then one can find in o(n^3) time a cycle of length k^@w^(^1^/^(^l^o^g^(^n^/^k^)^+^l^o^g^l^o^g^n^)^), which implies the result for hamiltonian graphs. our results improve, for some values of k and d, a recent result of gabow (2004) [11] showing that if g has a cycle of length k, then one can find in polynomial time a cycle in g of length exp(@w(logk/loglogk)). we finally show that if g has fixed euler genus g and has a cycle with k vertices (or a 3-cyclable minor h with k vertices), then we can find in polynomial time a cycle in g of length f(g)k^@w^(^1^), running in time o(n^2) for planar graphs.
web caching with request reordering. current web caching algorithms process requests in the order of the arrival. while such restriction is inevitable in system paging due to the sequential nature of a program, the http requests are (essentially) independent at a high volume proxy server. this gives a proxy server the flexibility to reorder requests, provided no request is inordinately delayed. the expectation is that reordering requests may lead to better performance. we formulate an online k-reordering problem that captures such phenomenon for unit caches. we give a dynamic programming algorithm to solve the offline case. we give o(1) upper and lower bound on the competitive ratio of the online algorithms. we also generalize this problem to any metric space.
graph distances in the streaming model: the value of space. we investigate the importance of space when solving problems based on graph distance in the streaming model. in this model, the input graph is presented as a stream of edges in an arbitrary order. the main computational restriction of the model is that we have limited space and therefore cannot store all the streamed data; we are forced to make space-efficient summaries of the data as we go along. for a graph of n vertices and m edges, we show that testing many graph properties, including connectivity (ergo any reasonable decision problem about distances) and bipartiteness, requires &omega;(n) bits of space. given this, we then investigate how the power of the model increases as we relax our space restriction. our main result is an efficient randomized algorithm that constructs a (2t + 1)-spanner in one pass. with high probability, it uses o(t .n1+1/t log2n) bits of space and processes each edge in the stream in o(t2&middot;n1/t log n) time. we find approximations to diameter and girth via the constructed spanner. for t = &omega;(log n/log log n), the space requirement of the algorithm is o(n .polylog n), and the per-edge processing time is o(polylog n). we also show a corresponding lower bound of t for the approximation ratio achievable when the space restriction is o(t.n1+1/t log2n).we then consider the scenario in which we are allowed multiple passes over the input stream. here, we investigate whether allowing these extra passes will compensate for a given space restriction. we show that finding vertices at distance d from a particular vertex will always take d passes, for all d &isin; {1,...,t/2}, when the space restriction is o(n1+1/t). for girth, we show the existence of a direct trade-off between space and passes in the form of a lower bound on the product of the space requirement and number of passes. finally, we conclude with two general techniques for speeding up the per-edge computation time of streaming algorithms while increasing the space by at most a log factor.
minimizing the stabbing number of matchings, trees, and triangulations. the (axis-parallel) stabbing number of a given set of line segments is the maximum number of segments that can be intersected by any one (axis-parallel) line. we investigate problems of finding perfect matchings, spanning trees, or triangulations of minimum stabbing number for a given set of points. the complexity of these problems has been a long-standing open problem; in fact, it is one of the original 30 outstanding open problems in computational geometry on the list by demaine, mitchell, and o'rourke.we show that minimum stabbing problems are np-complete. we also show that an iterated rounding technique is applicable for matchings and spanning trees of minimum stabbing number by showing that there is a polynomially solvable lp-relaxation that has fractional solutions with at least one heavy edge. this suggests constant-factor approximations. our approach uses polyhedral methods that are related to another open problem (from a combinatorial optimization list), in combination with geometric properties. we also demonstrate that the resulting techniques are practical for actually solving problems with up to several hundred points optimally or near-optimally.
lp decoding achieves capacity. we give a linear programming (lp) decoder that achieves the capacity (optimal rate) of a wide range of probabilistic binary communication channels. this is the first such result for lp decoding. more generally, as far as the authors are aware this is the first known polynomial-time capacity-achieving decoder with the maximum-likelihood (ml) certificate property---where output codewords come with a proof of optimality. additionally, this result extends the capacity-achieving property of expander codes beyond the binary symmetric channel to a larger family of communication channels.perhaps most importantly, since lp decoding performs well in practice on turbo codes and low-density parity-check (ldpc) codes (comparable to the popular "belief propagation" algorithm), this result exhibits the power of a new, widely applicable "dual witness" technique (feldman, malkin, servedio, stein and wainwright, isit '04) for bounding decoder performance.for expander codes over an adversarial channel, we prove that lp decoding corrects a constant fraction of errors. to show this, we provide a new combinatorial characterization of error events that is of independent interest, and which we expect will lead to further improvements.
hamiltonicity and colorings of arrangement graphs. we study connectivity, hamilton path and hamilton cycle decomposition, 4-edge and 3-vertex coloring for geometric graphs arising from pseudoline (affine or projective) and pseudocircle (spherical) arrangements. while arrangements as geometric objects are well studied in discrete and computational geometry, their graph theoretical properties seem to have received little attention so far. in this paper we show that they provide well-structured examples of families of planar and projective-planar graphs with very interesting properties. most prominently, spherical arrangements admit decompositions into two hamilton cycles; this is a new addition to the relatively few families of 4-regular graphs that are known to have hamiltonian decompositions. other classes of arrangements have interesting properties as well: 4-connectivity, 3-vertex coloring or hamilton paths and cycles. we show a number of negative results as well: there are projective arrangements which cannot be 3-vertex colored. a number of conjectures and open questions accompany our results.
an experimental study of an opportunistic index. the size of electronic data is currently growing at a faster rate than computer memory and disk storage capacities. for this reason compression appears always as an attractive choice, if not mandatory. however space overhead is not the only resource to be optimized when managing large data collections; in fact data turn out to be useful only when properly indexed to support search operations that efficiently extract the user-requested information. approaches to combine compression and indexing techniques are nowadays receiving more and more attention. a first step towards the design of a compressed full-text index achieving guaranteed performance in the worst case has been recently done in [10]. this index combines the compression algorithm proposed by burrows and wheeler [5] with the suffix array data structure [16]. the index is opportunistic in that it takes advantage of the compressibility of the input data by decreasing the space occupancy at no significant asymptotic slowdown in the query performance. in this paper we present an implementation of this index and perform an extensive set of experiments on various text collections. the experiments show that our index is compact (its space occupancy is close to the one achieved by the best known compressors), it is fast in counting the number of pattern occurrences, and the cost of their retrieval is reasonable when they are few (i.e., in case of a selective query). in addition, our experiments show that the fm-index is flexible in that it is possible to trade space occupancy for search time by choosing the amount of auxiliary information stored into it.
compression boosting in optimal linear time using the burrows-wheeler transform. in this paper we provide the first compression booster that turns a zeroth order compressor into a more effiective k-th order compressor without any loss in time efficiency. more precisely, let a be an algorithm that compresses a string s within &lambda;|s|h*0(s)+&mu; bits of storage in o(t (|s|)) time, where h*0(s) is the zeroth order entropy of the string s. our booster improves a by compressing s within &lambda;|s|h*0(s) + log2 |s| + gk bits still using o(t (|s|)) time, where h*k(s) is the k-th order entropy of s.the idea of a "compression booster" has been very recently introduced by giancarlo and sciortino in [7]. they combined the burrows-wheeler transform [3] with dynamic programming and achieved our same compression bound but with running time o(t (|s|)) + &omega;(|s|2). we start from the same premises of [7], but instead of using dynamic programming we design a linear time optimization algorithm based on novel structural properties of the burrows-wheeler transform.
making data structures confluently persistent. we address a longstanding open problem of [j.r. driscoll, n. sarnak, d. sleator, r. tarjan, j. comput. system sci. 38 (1989) 86-124, j. driscoll, d. sleator, r. tarjan, j. acm, 41 (5) (1994) 943-959], and present a general transformation that transforms any pointer based data structure to be confluently persistent. such transformations for fully persistent data structures are given in [j.r. driscoll, n. sarnak, d. sleator, r. tarjan, j. comput. system sci. 38 (1989) 86-124], greatly improving the performance compared to the naive scheme of simply copying the inputs. unlike fully persistent data structures, where both the naive scheme and the fully persistent scheme of [j.r. driscoll, n. sarnak, d. sleator, r. tarjan, j. comput. system sci. 38 (1989) 86-124] are feasible, we show that the naive scheme for confluently persistent data structures is itself infeasible (requires exponential space and time). thus, prior to this paper there was no feasible method for making any data structure confluently persistent at all. our methods give an exponential reduction in space and time compared to the naive method, placing confluently persistent data structures in the realm of possibility.
online conflict-free coloring for intervals. we consider an online version of the conflict-free coloring of a set of points on the line, where each newly inserted point must be assigned a color upon insertion, and at all times the coloring has to be conflict-free, in the sense that in every interval i there is a color that appears exactly once in i. we present several deterministic and randomized algorithms for achieving this goal, and analyze their performance, that is, the maximum number of colors that they need to use, as a function of the number n of inserted points. we first show that a natural and simple (deterministic) approach may perform rather poorly, requiring &omega;(&radic;n) colors in the worst case. we then modify this approach, to obtain an efficient deterministic algorithm that uses a maximum of &theta;(log2 n) colors. next, we present two randomized solutions. the first algorithm requires an expected number of at most o(log2 n) colors, and produces a coloring which is valid with high probability, and the second one, which is a variant of our efficient deterministic algorithm, requires an expected number of at most o(log n log log n) colors but always produces a valid coloring. we also analyze the performance of the simplest proposed algorithm when the points are inserted in a random order, and present an incomplete analysis that indicates that, with high probability, it uses only o(log n) colors. finally, we show that in the extension of this problem to two dimensions, where the relevant ranges are disks, n colors may be required in the worst case. the average-case behavior for disks, and cases involving other planar ranges, are still open.
censorship resistant peer-to-peer content addressable networks. we present a censorship resistant peer-to-peer content addressable network for accessing n data items in a network of n nodes. each search for a data item in the network takes o(log n) time and requires at most o(log2n) messages. our network is censorship resistant in the sense that even after adversarial removal of an arbitrarily large constant fraction of the nodes in the network, all but an arbitrarily small fraction of the remaining nodes can obtain all but an arbitrarily small fraction of the original data items. the network can be created in a fully distributed fashion. it requires only o(log n) memory in each node. we also give a variant of our scheme that has the property that it is highly spam resistant: an adversary can take over complete control of a constant fraction of the nodes in the network and yet will still be unable to generate spam.
the number of bit comparisons used by quicksort: an average-case analysis. the analyses of many algorithms and data structures (such as digital search trees) for searching and sorting are based on the representation of the keys involved as bit strings and so count the number of bit comparisons. on the other hand, the standard analyses of many other algorithms (such as quicksort) are performed in terms of the number of key comparisons. we introduce the prospect of a fair comparison between algorithms of the two types by providing an averagecase analysis of the number of bit comparisons required by quicksort. counting bit comparisons rather than key comparisons introduces an extra logarithmic factor to the asymptotic average total. we also provide a new algorithm, "bitsquick", that reduces this factor to constant order by eliminating needless bit comparisons.
experimental analysis of simple, distributed vertex coloring algorithms. we perform an extensive experimental evaluation of very simple, distributed, randomized algorithms for (&delta; + 1)- and so-called brooks-vizing vertex colorings, i.e., colorings using considerably fewer than &delta; colors. we consider variants of algorithms known from the literature, boosting them with a distributed independent set computation. our study clearly determines the relative performance of the algorithms w.r.t. the number of communication rounds and the number of colors. the results are confirmed by all the experiments and instance families. the empirical evidence shows that some algorithms are extremely fast and very effective, thus being amenable to be used in practice.
testing graphs for colorable properties. let p be a property of graphs. an &egr;-test for p is a randomized algorithm which, given the ability to make queries whether a desired pair of vertices of an input graph g with n vertices are adjacent or not, distinguishes, with high probability, between the case of g satisfying p and the case that it has to be modified by adding and removing more than &egr;( <stack>2n</stack>) edges to make it satisfy p. the property p is called testable if for every &egr; there exists an &egr;-test for p whose total number of queries is independent of the size of the input graph. goldreich, goldwasser, and ron [property testing and its connection to learning and approximation, j acm 45 (1998), 653&ndash;750] showed that certain graph properties, like k-colorability, admit an &egr;-test. in alon, fischer, krivelevich, and szegedy [efficient testing of large graphs, combinatorica 20 (2000), 451&ndash;476] a first step towards a logical characterization of the testable graph properties was made by proving that all first order properties of type &ldquo;&exist;&forall;&rdquo; are testable, while there exist first-order graph properties of type &ldquo;&exist;&forall;&rdquo; that are not testable. for proving the positive part, it was shown that all properties describable by a very general type of coloring problem are testable. while this result is tight from the standpoint of first order expressions, further steps towards the characterization of the testable graph properties can be taken by considering the coloring problem instead. it is proven here that other classes of graph properties, describable by various generalizations of the coloring notion used in alon et al. [combinatorica 20 (2000), 451&ndash;476], are testable, showing that this approach can broaden the understanding of the nature of the testable graph properties. the proof combines some generalizations of the methods used in alon et al. with additional methods. &copy; 2004 wiley periodicals, inc. random struct. alg., 2005an extended abstract of this paper has appeared in the proceedings of the 12th acm-siam soda (2001), 873&ndash;882.
testing graph isomorphism. we deal with the question of how many queries are required to distinguish between the case that two graphs g and h on n vertices are isomorphic, and the case that they are &epsilon;-far, that is they differ in more than &epsilon;(n2) pairs for all possible bijections of their vertices. querying is defined as probing the adjacency matrix of any one of the two graphs, i.e. asking if a pair of vertices forms an edge of the graph or not.we investigate both one-sided error and two-sided error testers under two possible settings: the first setting is where both graphs need to be queried; and the second setting is where one of the graphs is known to the algorithm in advance.we prove that the query complexity of the one-sided error testing problem is &theta;(n3/2) if both graphs need to be queried, and that it is &theta;(n) if one of the graphs is known in advance (where the &theta; notation hides polylogarithmic factors in the upper bounds). for the two-sided error testers we prove that the query complexity is &theta;(&radic;n when one of the graphs is known in advance, and we show that the query complexity lies between &omega;(n) and &otilde;(n5/4) if both g and h need to be queried. all of our algorithms are additionally non-adaptive, while all of our lower bounds apply for adaptive testers as well as non-adaptive ones.
a spectral technique for random satisfiable 3cnf formulas. let i be a random 3cnf formula generated by choosing a truth assignment &phis; for variables x1, xn uniformly at random and including every clause with i literals set true by &phis; with probability pi, independently. we show that for any constants 0 &le; &eta;2,&eta;3 &le; 1 there is a constant dmin so that for all d &ge; dmin a spectral algorithm similar to the graph coloring algorithm of alon and kahale will find a satisfying assignment with high probability for p1 = d-n2, p2 = &eta;2d-n2, and p3 = &eta;3d-n2. appropriately setting the &eta;i's yields natural distributions on satisfiable 3cnfs, not-all-equal-sat 3cnfs, and exactly-one-sat 3cnfs. &copy; 2008 wiley periodicals, inc. random struct. alg., 2008
on the random 2-stage minimum spanning tree. it is known [7] that if the edge costs of the complete graph kn are independent random variables, uniformly distributed between 0 and 1, then the expected cost of the minimum spanning tree is asymptotically equal to &zeta;(3) = &sigma; &infin;i=1 i-3. here we consider the following stochastic two-stage version of this optimization problem. there are two sets of edge costs cm: e &larr; r and ct: e &larr; r, called monday's prices and tuesday's prices, respectively. for each edge e, both costs cm(e) and ct(e) are independent random variables, uniformly distributed in [0, 1]. the monday costs are revealed first. the algorithm has to decide on monday for each edge e whether to buy it at monday's price cm(e), or to wait until its tuesday price ct(e) appears. the set of edges xm bought on monday is then completed by the set of edges xt bought on tuesday to form a spanning tree. if both monday's and tuesday's prices were revealed simultaneously, then the optimal solution would have expected cost &zeta;(3)/2 + o(1). we show that in the case of two-stage optimization, the expected value of the optimal cost exceeds &zeta;(3)/2 by an absolute constant &isin; > 0. we also consider a threshold heuristic, where the algorithm buys on monday only edges of cost less than &alpha; and completes them on tuesday in an optimal way, and show that the optimal choice for &alpha; is &alpha; = 1/n with the expected cost &zeta;(3) - 1/2 + o(1). the threshold heuristic is shown to be sub-optimal. finally we discuss the directed version of the problem, where the task is to construct a spanning out-arborescence rooted at a fixed vertex r, and show, somewhat surprisingly, that in this case a simple variant of the threshold heuristic gives the asymptotically optimal value 1 - 1/e + o(1).
adversarial deletion in a scale free random graph process. we study a dynamically evolving random graph which adds vertices and edges using preferential attachment and is &lsquo;attacked by an adversary&rsquo;. at time $t$, we add a new vertex $x_t$ and $m$ random edges incident with $x_t$, where $m$ is constant. the neighbours of $x_t$ are chosen with probability proportional to degree. after adding the edges, the adversary is allowed to delete vertices. the only constraint on the adversarial deletions is that the total number of vertices deleted by time $n$ must be no larger than $\delta n$, where $\delta$ is a constant. we show that if $\delta$ is sufficiently small and $m$ is sufficiently large then with high probability at time $n$ the generated graph has a component of size at least $n/30$.
online convex optimization in the bandit setting: gradient descent without a gradient. we study a general online convex optimization problem. we have a convex set s and an unknown sequence of cost functions c1, c2,..., and in each period, we choose a feasible point xt in s, and learn the cost ct(xt). if the function ct is also revealed after each period then, as zinkevich shows in [25], gradient descent can be used on these functions to get regret bounds of o(&radic;n). that is, after n rounds, the total cost incurred will be o(&radic;n) more than the cost of the best single feasible decision chosen with the benefit of hindsight, minx &sigma; ct(x).we extend this to the "bandit" setting, where, in each period, only the cost ct(xt) is revealed, and bound the expected regret as o(n3/4).our approach uses a simple approximation of the gradient that is computed from evaluating ct at a single (random) point. we show that this biased estimate is sufficient to approximate gradient descent on the sequence of functions. in other words, it is possible to use gradient descent without seeing anything more than the value of the functions at a single point. the guarantees hold even in the most general case: online against an adaptive adversary.for the online linear optimization problem [15], algorithms with low regrets in the bandit setting have recently been given against oblivious [1] and adaptive adversaries [19]. in contrast to these algorithms, which distinguish between explicit explore and exploit periods, our algorithm can be interpreted as doing a small amount of exploration in each period.
a fast approximation scheme for fractional covering problems with variable upper bounds. we present the first combinatorial approximation scheme for mixed positive packing and covering linear programs that yields a pure approximation guarantee. our algorithm returns solutions that simultaneously satisfy general positive covering constraints and packing constraints that are variable upper bounds. the returned solution has positive linear objective function value at most 1 + ε times the optimal value.our approximation scheme is based on lagrangian-relaxation methods. previous such approximation schemes for mixed packing and covering problems does not simultaneously satisfy packing and covering constraints exactly. we show how to exactly satisfy general positive covering constraints simultaneously with variable upper bounds.a natural set of problems that our work addresses are linear programs for various network design problems: generalized steiner network, vertex connectivity, directed connectivity, capacitated network design, group steiner forest. these are all np-hard problems for which there are approximation algorithms that round the solution to the corresponding linear program. solving the linear program is often the computational bottleneck in these problems, and thus a fast approximation scheme for the lp relaxation means faster approximation algorithms.for the special case of survivable network design, we introduce a new modification of the push-relabel maximum flow algorithm that allows us to perform each iteration in amortized o(m + n log n) time, instead of one maximum flow per iteration that is implied by the straight forward adaptation of our general algorithm. (m is the number of edges and n is the number of vertices in the network.) in conjunction with an observation that reduces the number of iterations to {log n for f0} constraint matrices, the modification allows us to obtain an algorithm that is faster than existing exact or approximate algorithms by a factor of at least o(m) and by a factor of o(m log n) if the number of demand pairs is &omega;(n).
tight approximation algorithms for maximum general assignment problems. a separable assignment problem (sap) is defined by a set of bins and a set of items to pack in each bin; a value, fij, for assigning item j to bin i; and a separate packing constraint for each bin - i.e. for bin i, a family li of subsets of items that fit in bin i. the goal is to pack items into bins to maximize the aggregate value. this class of problems includes the maximum generalized assignment problem (gap)1) and a distributed caching problem (dcp) described in this paper.given a &beta;-approximation algorithm for finding the highest value packing of a single bin, we give1. a polynomial-time lp-rounding based ((1 &minus; 1/e)&beta;)-approximation algorithm.2. a simple polynomial-time local search (&beta;/&beta;+1 - &epsilon;) - approximation algorithm, for any &epsilon; > 0.therefore, for all examples of sap that admit an approximation scheme for the single-bin problem, we obtain an lp-based algorithm with (1 - 1/e - &epsilon;)-approximation and a local search algorithm with (1/2-&epsilon;)-approximation guarantee. furthermore, for cases in which the subproblem admits a fully polynomial approximation scheme (such as for gap), the lp-based algorithm analysis can be strengthened to give a guarantee of 1 - 1/e. the best previously known approximation algorithm for gap is a 1/2-approximation by shmoys and tardos; and chekuri and khanna. our lp algorithm is based on rounding a new linear programming relaxation, with a provably better integrality gap.to complement these results, we show that sap and dcp cannot be approximated within a factor better than 1 -1/e unless np&sube; dtime(no(log log n)), even if there exists a polynomial-time exact algorithm for the single-bin problem.we extend the (1 - 1/e)-approximation algorithm to a nonseparable assignment problem with applications in maximizing revenue for budget-constrained combinatorial auctions and the adwords assignment problem. we generalize the local search algorithm to yield a 1/2-&epsilon; approximation algorithm for the k-median problem with hard capacities. finally, we study naturally defined game-theoretic versions of these problems, and show that they have price of anarchy of 2. we also prove the existence of cycles of best response moves, and exponentially long best-response paths to (pure or sink) equilibria.
approximately optimal control of fluid networks. we give an approximation algorithm for the optimal control problem in fluid networks. such problems arise as fluid relaxations of multiclass queueing networks, and are used to find approximate solutions to complex job shop scheduling problems. in a network with linear flow costs and linear, per-unit-time holding costs, our algorithm finds a drainage of the network, that for given constants &epsilon; > 0 and &delta; > 0 has total cost (1 + &epsilon;)opt + &delta;, where opt is the cost of the minimum cost drainage. the complexity of our algorithm is polynomial in the size of the input network, 1/&epsilon; and log 1/&delta;. the fluid relaxation is a continuous problem. while the problem is known to have a piecewise constant solution, it is not known to have a polynomially-sized solution. we introduce a natural discretization of polynomial size and prove that this discretization produces a solution with low cost. this is the first polynomial time algorithm with a provable approximation guarantee for fluid relaxations.
minimum cost flows over time without intermediate storage. flows over time (also called dynamic flows) generalize standard network flows by introducing an element of time. they naturally model problems where travel and transmission are not instantaneous. solving these problems raises issues that do not arise in standard network flows. one issue is the question of storage of flow at intermediate nodes. in most applications (such as, e.g., traffic routing, evacuation planning, telecommunications etc.), intermediate storage is limited, undesired, or prohibited.the minimum cost flow over time problem is np-hard. in this paper we 1) prove that the minimum cost flow over time never requires storage; 2) provide the first approximation scheme for minimum cost flows over time that does not require storage; 3) provide the first approximation scheme for minimum cost flows over time that meets hard cost constraints, while approximating only makespan.our approach is based on a condensed variant of time- expanded networks. it also yields fast approximation schemes with simple solutions for the quickest multicommodity flow problem.finally, using completely different techniques, we describe a very simple capacity scaling fpas for the minimum cost flow over time problem when costs are proportional to transit times. the algorithm builds upon our observation about the structure of optimal solutions to this problem: they are universally quickest flows. again, the fpas does not use intermediate node storage. in contrast to the preceding algorithms that use a time-expanded network, this fpas runs directly on the original network.
measure and conquer: a simple o(2) independent set algorithm. for more than 30 years davis-putnam-style exponential-time backtracking algorithms have been the most common tools used for finding exact solutions of np-hard problems. despite of that, the way to analyze such recursive algorithms is still far from producing tight worst case running time bounds.the "measure and conquer" approach is one of the recent attempts to step beyond such limitations. the approach is based on the choice of the measure of the subproblems recursively generated by the algorithm considered; this measure is used to lower bound the progress made by the algorithm at each branching step. a good choice of the measure can lead to a significantly better worst case time analysis.in this paper we apply "measure and conquer" to the analysis of a very simple backtracking algorithm solving the well-studied maximum independent set problem. the result of the analysis is striking: the running time of the algorithm is o(20.288n), which is competitive with the current best time bounds obtained with far more complicated algorithms (and naive analysis).our example shows that a good choice of the measure, made in the very first stages of exact algorithms design, can have a tremendous impact on the running time bounds achievable.
dominating sets in planar graphs: branch-width and exponential speed-up. we introduce a new approach to design parameterized algorithms on planar graphs which builds on the seminal results of robertson and seymour on graph minors. graph minors provide a list of powerful theoretical results and tools. however, the widespread opinion in the graph algorithms community about this theory is that it is of mainly theoretical importance. in this paper we show how deep min-max and duality theorems from graph minors can be used to obtain exponential speed-up to many known practical algorithms for different domination problems. our use of branch-width instead of the usual tree-width allows us to obtain much faster algorithms. by using this approach, we show that the k-dominating set problem on planar graphs can be solved in time o(215.13 \sqrt k + n3).
proximity mergesort: optimal in-place sorting in the cache-oblivious model. an algorithm performs its operations in-place if it uses o(1) extra locations of main memory besides those containing the input entries. an algorithm is cache-oblivious if it is not conscious of any parameter of the memory hierarchy (m, the size of cache memory, and b, the size of the minimal contiguous block of information that can be transferred between the cache and the main memory). hence, it cannot directly exploit these parameters to reach the optimality. in the cache-oblivious model the complexity is measured with two criteria: the work complexity, which is the standard complexity in the ram model, and the cache complexity, which is the total number of block transfers (cache misses) incurred during the computation.the contribution of this paper is twofold. we present the first sorting algorithm that is optimal in both work and cache complexity in the cache-oblivious model and that operates in-place. furthermore, we introduce a new approach to the sorting problem in the cache-oblivious model.
implicit dictionaries supporting searches and amortized updates in o(log n log log n) time. we describe a new implicit data structure for maintaining n data values in the first n locations of an array. no information other than n and the data is to be retained, and the only operations which we may perform on the data values (other than reads and writes) are comparisons. our structure supports searches in o(log n log log n) time in the worst case, and insertions and deletions in o(log n log log n) amortized time. the best known bound for these operations in main memory is o(log 2 n/log log n) in the worst case.
implicit dictionaries with (1) modifications per update and fast search. the implicit dictionary problem is that of maintaining a dynamic ordered set, s, under the operations search, insert and delete, so that the elements of s are stored in the first |s| locations of an array. no operations are permitted on the data other than comparisons (&le;) and interchanges. the only auxiliary memory permitted is a constant number of o(log |s|) bit integers. the organization will, then, rely heavily on the permutations of the relative order of the values in which the data is stored. while such a structure can be maintained in o(log |s|) time, the most interesting lower bound on the topic is that of borodin, fich, meyer auf der heide, upfal and wigderson [3]. they proved a tradeoff between search and update time in implicit dictionaries: if the update cost (comparisons and exchanges) is o(1), then the search cost must be &omega;(|s|&epsilon;), for some constant &epsilon; > 0. the authors left open the question of whether such a tradeoff would hold if only the modifications performed during an update were considered. they conjectured that any implicit dictionary performing only o(1) exchanges per update should very quickly become "disorganized", and so require &omega;(|s|&epsilon;) comparisons per search. we answer this long-standing open question by disproving the conjecture.
edge-disjoint paths in expander graphs. given a graph g=(v,e)and a set of $\kappa$ pairs of vertices in v, we are interested in finding, for each pair (ai, bi), a path connecting ai to bi such that the set of $\kappa$ paths so found is edge-disjoint. for arbitrary graphs the problem is ${\cal np}$-complete, although it is in ${\cal p}$ if $\kappa$ is fixed. we present a polynomial time randomized algorithm for finding edge-disjoint paths in an r-regular expander graph g. we show that if g has sufficiently strong expansion properties and r is sufficiently large, then all sets of $\kappa=\omega(n/\log n)$ pairs of vertices can be joined. this is within a constant factor of best possible.
random graphs. we will review some of the major results in random graphs and some of the more challenging open problems. we will cover algorithmic and structural questions. we will touch on newer models, including those related to the www.
the probabilistic relationship between the assignment and asymmetric traveling salesman problems. we consider the gap between the cost of an optimal assignment in a complete bipartite graph with random edge weights, and the cost of an optimal traveling salesman tour in a complete directed graph with the same edge weights. using an improved &ldquo;patching&rdquo; heuristic, we show that with high probability the gap is $o((\ln n)^2/n)$, and that its expectation is $\omega(1/n)$. one of the underpinnings of this result is that the largest edge weight in an optimal assignment has expectation $\theta(\ln n / n)$. a consequence of the small assignment-tsp gap is an $e^{\tilde{o}(\sqrt{n})}$-time algorithm which, with high probability, exactly solves a random asymmetric traveling salesman instance. in addition to the assignment-tsp gap, we also consider the expected gap between the optimal and second-best assignments; it is at least $\omega(1/n^2)$ and at most $o(\ln n/n^2)$.
optimal construction of edge-disjoint paths in random regular graphs. given a graph g = (v, e) and a set of &kappa; pairs of vertices in v, we are interested in finding, for each pair (ai, bi), a path connecting ai to bi such that the set of &kappa; paths so found is edge-disjoint. (for arbitrary graphs the problem is &nscr;&pscr;-complete, although it is in &pscr; if &kappa; is fixed.)we present a polynomial time randomized algorithm for finding edge-disjoint paths in the random regular graph gn,r, for sufficiently large r. (the graph is chosen first, then an adversary chooses the pairs of end-points.) we show that almost every gn,r is such that all sets of &kappa; = &omega;(n&#x002f;log n) pairs of vertices can be joined. this is within a constant factor of the optimum.
controlled perturbation for delaunay triangulations. most geometric algorithms are idealistic in the sense that they are designed for the real-ram model of computation and for inputs in general position. real inputs may be degenerate and floating point arithmetic is only an approximation of real arithmetic. perturbation replaces an input by a nearby input which is (hopefully) in general position and on which the algorithm can be run with floating point arithmetic. controlled perturbation as proposed by halperin et al. calls for more: control over the amount of perturbation needed for a given precision of the floating point system. or conversely, a control over the precision needed for a given amount of perturbation. halperin et al. gave controlled perturbation schemes for arrangements of polyhedral surfaces, spheres, and circles.we extend their work and point out that controlled perturbation is a general scheme for converting idealistic algorithms into algorithms which can be executed with floating point arithmetic. we also show how to use controlled perturbation in the context of randomized geometric algorithms without deteriorating the running time. finally, we give concrete schemes for planar delaunay triangulations and convex hulls and delaunay triangulations in arbitrary dimensions. we analyze the relation between the perturbation amount and the precision of the floating point system. we also report about experiments with a planar delaunay diagram algorithm.
reconstructing a collection of curves with corners and endpoints. we present an algorithm which provably reconstructs a collection of curves with corners and endpoints from a sample set that satisfies a certain sampling condition. the algorithm outputs a polygonal reconstruction that contains the edges in the correct reconstruction of the curves and such that any additional edge between sample points is justified. furthermore, we show that for any such collection of curves, there exists a sample set such that a slightly modified version of our algorithm outputs exactly the correct reconstruction. the algorithm also performs quite well in practice.
smooth-surface reconstruction in near-linear time. a surface reconstruction algorithm takes as input a set of sample points from an unknown closed and smooth surface in 3-d space, and produces a piece-wise linear approximation of the surface that contains the sample points. recently, several algorithms with a correctness guarantee have been proposed. they have unfortunately a worst-case running time that is quadratic in the size of the input because they are based on the construction of 3-d voronoi diagrams or delaunay tetrahedrizations which can have quadratic size. in this paper, we describe a new algorithm that also has a correctness guarantee but whose worst-case running time is o(n log n) where n is the input size. this is actually optimal. as in some of the previous algorithms, the piece-wise linear approximation produced by the new algorithm is a triangulation which is a subset of the 3-d delaunay tetrahedrization.
approximating the minimum degree spanning tree to within one from the optimal degree. we consider the problem of constructing a spanning tree for a graph g = (v,e) with n vertices whose maximal degree is the smallest among all spanning trees of g. this problem is easily shown to be np-hard. we describe an iterative polynomial time approximation algorithm for this problem. this algorithm computes a spanning tree whose maximal degree is at most o(&dgr; + log n), where &dgr; is the degree of some optimal tree. the result is generalized to the case where only some vertices need to be connected (steiner case) and to the case of directed graphs. it is then shown that our algorithm can be refined to produce a spanning tree of degree at most &dgr; + 1. unless p = np, this is the best bound achievable in polynomial time.
dissections and trees, with applications to optimal mesh encoding and to random sampling. we present a bijection between some quadrangular dissections of an hexagon and unrooted binary trees. this correspondence has interesting consequences for enumeration, mesh compression and random graph sampling.it yields a succinct representation for the set p(n) of n-edge 3-connected planar graphs matching the entropy bound 1/n log |p(n)| = 2+o(1) bits per edge. this solves a theoretical problem in mesh compression, as these graphs abstract the combinatorial part of meshes with spherical topology.once the entropy bound is matched, the guaranteed compression rate can only be improved on subclasses: we achieve the optimal parametric rate 1/n log |p(n, i, j)| bits per edge for graphs of p(n) with i vertices and j faces. this effectively reduces the entropy as soon as |i -j| &gt; n1/2, and achieves the optimal rate for triangulations.it also yields an efficient uniform random sampler for labeled 3-connected planar graphs. using it, the amortized complexity of sampling labeled planar graphs is reduced from the best previously known o(n6.5) to o(n3).
an ear decomposition approach to approximating the smallest 3-edge connected spanning subgraph of a multigraph. this paper gives a 3/2 approximation algorithm for the smallest 3-edge connected spanning subgraph of an undirected multigraph. the previous best algorithm of khuller and raghavachari [j. algorithms, 21 (1996), pp. 434--450] has approximation ratio $5/3$. the algorithm of cheriyan and thurimella [siam j. comput., 30 (2000), pp. 528--560] achieves ratio 3/2 for simple graphs. our approach, based on the close relationship between an ear decomposition of a 2-edge connected graph and 3-edge connected components, enables us to achieve running time $o( m \alpha(m,n) )$.
better performance bounds for finding the smallest k-edge connected spanning subgraph of a multigraph. khuller and raghavachari [12] present an approximation algorithm (the kr algorithm) for finding the smallest k-edge connected spanning subgraph (k-ecss) of an undirected multigraph. they prove the kr algorithm has approximation ratio < 1.85. we prove the kr algorithm has approximation ratio &le; 1 + &radic;1/e < 1.61; for odd k this requires a minor modification of the algorithm. this is the bestknown performance bound for the smallest k-ecss problem for arbitrary k. our analysis also gives the best-known performance bound for any fixed value of k &le; 3, e.g., for even k the approximation ratio is &le; 1 + (1 -- 1/k)k/2. our analysis is based on a laminar family of sets (similar to families used in related contexts) which gives a better accounting of edges added in previous iterations of the algorithm. we also present a polynomial time implementation of the kr algorithm on multigraphs, running in the time for o(nm) maximum flow computations, where n (m) is the number of vertices (edges, not counting parallel copies). this complements the implementation of [12] which uses time o((kn)2) and is efficient for small k.
special edges, and approximating the smallest directed -edge connected spanning subgraph. we give two approximation algorithms for finding the smallest k-edge connected spanning subgraph of a digraph. for multidigraphs we achieve performance ratio 2 - 1/3k. this is the first known ratio strictly less than 2. for simple digraphs the best known approximation algorithm is due to cheriyan and thurimella. we improve their analysis of the number of "special edges" of a simple digraph. this improves the performance ratio of their algorithm for simple digraphs from 1 + 4/&radic;k to slightly more than 1 + &radic;2/k, for k &ge; 15. our analysis of the number of special edges is tight for k &ge; 15. for 5 < k < 15 our improved approximation ratio is 1 + 5/k.
upper degree-constrained partial orientations. we wish to orient as many edges as possible in an undirected graph (or multigraph), subject to upper bounds on the indegree and out-degree of each vertex. frank and gy&aacute;rf&aacute;s [2] solve this problem in polynomial time when there are no in-degree bounds, and when every edge can be oriented within the given bounds. however we show that in general the problem is maxsnp-hard. when viewed as a 3-dimensional matching problem the local improvement algorithm of hurkens and schrijver [4] achieves approximation ratio 2/3 -- &epsilon;; we believe is the best previous bound for our problem. we give an lp-rounding algorithm that achieves approximation ratio 3/4.
approximating the smallest -edge connected spanning subgraph by lp-rounding. the smallest k-ecss problem is, given a graph along with an integer k, find a spanning subgraph that is k-edge connected and contains the fewest possible number of edges. we examine a natural approximation algorithm based on rounding an lp solution. a tight bound on the approximation ratio is 1 + 3-k for undirected graphs with k > 1 odd, 1 + 2-k for undirected graphs with k even, and 1 + 2-k for directed graphs with k arbitrary. using iterated rounding improves the first upper bound to 1 + 2-k. on the hardness side we show that for some absolute constant c > 0, for any integer k &ge; 2 (k &ge; 1), a polynomial-time algorithm approximating the smallest k-ecss on undirected (directed) multigraphs to within ratio 1 + c-k would imply p = np. &copy; 2008 wiley periodicals, inc. networks, 2009
how to make a square grid framework with cables rigid. this paper solves the problem of making a bipartite digraph strongly connected by adding the smallest number of new edges that preserve bipartiteness. a result of baglivo and graver shows that this corresponds to making a two-dimensional square grid framework with cables rigid by adding the smallest number of new cables. we prove a min-max formula for the smallest number of new edges in the digraph problem and give a corresponding linear-time algorithm. we generalize these results to the problem of making an arbitrary digraph strongly connected by adding the smallest number of new edges, each of which joins vertices in distinct blocks of a given partition of the vertex set.
finding a long directed cycle. consider a digraph with n vertices. for any fixed value k, we present linear- and almost-linear-time algorithms to find a cycle of length &ge; k, if one exists. we also find a cycle that has length &ge; log n/log log n in polynomial time, if one exists. under an appropriate complexity assumption it is known to be impossible to improve this guarantee by more than a log log n factor. our approach is based on depth-first search.
slow mixing of glauber dynamics for the hard-core model on the hypercube. for &lambda; > 0, let &pi;&lambda; be the probability measure on the independent sets of the hypercube {0,1}d in which i is chosen with probability proportional to &lambda;|i|. we study the glauber dynamics, or single-site-update markov chain, whose stationary distribution is &pi;&lambda;, and show that for values of &lambda; tending to 0 as d grows, the convergence to stationarity is exponentially slow in the volume of the cube. the proof combines a conductance argument with combinatorial enumeration methods.
linear phase transition in random linear constraint satisfaction problems. our model is a generalized linear programming relaxation of a much studied random k-sat problem. specifically, a set of linear constraints c on k variables is fixed. from a pool of n variables, k variables are chosen uniformly at random and a constraint is chosen from c also uniformly at random. this procedure is repeated m times independently. we are interested in whether the resulting linear programming problem is feasible. we prove that the feasibility property experiences a linear phase transition, when n &larr; &infin; and m = cn for a constant c. namely, there exists a critical value c* such that, when c < c*, the problem is feasible or is asymptotically almost feasible, as n &larr; &infin;, but, when c > c*, the "distance" to feasibility is at least a positive constant independent of n. our result is obtained using the combination of a powerful local weak convergence method developed in aldous [ald92], [ald01], aldous and steele [as03], steele [ste02] and martingale techniques. by exploiting a linear programming duality, our theorem implies some results for maximum weight matchings in sparse random graphs g(n, &lfloor;cn&rfloor;) on n nodes with cn edges, where edges are equipped with randomly generated weights.
the expected value of random minimal length spanning tree of a complete graph. we consider the number c(n, m) of connected labeled graphs on n nodes and m edges and the intimately related object, the expected length of the minimal spanning tree of a complete graphs with random edge lengths. we use a very simple recursive procedure for computing the values of c(n, m) for computing the expected length of the minimal spanning tree exactly, under the uniform and the exponential distributions. our computations are recursive, scale very well with the size of the problem, and we provide the values of the expected minimal length spanning trees for complete graphs kn with sizes n &le; 45, extending recent results of steele [ste02], and fill and steele [fs04]. the main proof technique is based on introducing an artificial root to a graph and subsequently using a very simple inductive argument.
expansion of product replacement graphs. we establish a connection between the expansion coefficient of the product replacement graph &#x0393;k(g) and the minimal expansion coefficient of a cayley graph of g with k generators. in particular, we show that the product replacement graphs &#x0393;k(psl(2,p)) form an expander family, under assumption that all cayley graphs of psl(2,p), with at most k generators are expanders. this gives a new explanation of the outstanding performance of the product replacement algorithm and supports the speculation that all product replacement graphs are expanders [42,52].
on contract-and-refine transformations between phylogenetic trees. the inference of evolutionary trees using approaches which attempt to solve the maximum parsimony (mp) and maximum likelihood (ml) optimization problems is a standard part of much of biological data analysis. however, both problems are hard to solve: mp provably np-hard, and ml even harder in practice. consequently, hill-climbing heuristics are used to analyze datasets for phylogeny reconstruction. two primary topological transformations have been used in the most popular heuristics: tbr (tree-bisection-and-reconnection) and ecr (edge-contractions-and-refinements). while most of the popular heuristics exclusively use tbr moves to explore tree space, some recent methods have used ecr in conjunction with tbr and found significant improvements in the speed and accuracy with which they can analyze datasets. in this paper we analyze ecr moves in detail, and provide results on the diameter of the tree space, the neighborhood intersection with tbr, structural analysis of the ecr operation, and an efficient method for sampling uniformly from the 2-ecr neighborhood of a tree. our results should lead to a better understanding of the impact of ecr moves on the performance of heuristic searches.
optimal routing in chord. we propose optimal routing algorithms for chord [1], a popular topology for routing in peer-to-peer networks. chord is an undirected graph on 2b nodes arranged in a circle, with edges connecting pairs of nodes that are 2k positions apart for any k &ge; 0. the standard chord routing algorithm uses edges in only one direction. our algorithms exploit the bidirectionality of edges for optimality. at the heart of the new protocols lie algorithms for writing a positive integer d as the difference of two non-negative integers d&prime; and d&prime; such that the total number of 1-bits in the binary representation of d&prime; and d&prime; is minimized. given that chord is a variant of the hypercube, the optimal routes possess a surprising combinatorial structure.
fair and efficient router congestion control. congestion is a natural phenomenon in any network queuing system, and is unavoidable if the queuing system is operated near capacity. in this paper we study how to set the rules of a queuing system so that all the users have a self-interest in controlling congestion when it happens.routers in the internet respond to local congestion by dropping packets. but if packets are dropped indiscriminately, the effect can be to encourage senders to actually increase their transmission rates, worsening the congestion and destabilizing the system. alternatively, and only slightly more preferably, the effect can be to arbitrarily let a few insistent senders take over most of the router capacity.we approach this problem from first principles: a router packet-dropping protocol is a mechanism that sets up a game between the senders, who are in turn competing for link capacity. our task is to design this mechanism so that the game equilibrium is desirable: high total rate is achieved and is shared widely among all senders. in addition, equilibrium should be reestablished quickly in response to changes in transmission rates. our solution is based upon auction theory: in principle, although not always in practice, we drop packets of the highest-rate sender, in case of congestion. we will prove the game-theoretic merits of our method. we'll also describe a variant of the method with some further advantages that will be supported by network simulations.
analysis of incomplete data and an intrinsic-dimension helly theorem. the analysis of incomplete data is a long-standing challenge in practical statistics. when, as is typical, data objects are represented by points in rd, incomplete data objects correspond to affine subspaces (lines or &delta;-flats). with this motivation we study the problem of finding the minimum intersection radius r(l) of a set of lines or &delta;-flats l: the least r such that there is a ball of radius r intersecting every flat in l. known algorithms for finding the minimum enclosing ball for a point set (or clustering by several balls) do not easily extend to higher-dimensional flats, primarily because "distances" between flats do not satisfy the triangle inequality. in this paper we show how to restore geometry (i.e., a substitute for the triangle inequality) to the problem, through a new analog of helly's theorem. this "intrinsic-dimension" helly theorem states: for any family l of &delta;-dimensional convex sets in a hilbert space, there exist &delta; + 2 sets l' &sube; l such that r(l) &le; 2r(l'). based upon this we present an algorithm that computes a (1 + &epsilon;)-core set l' &sube; l,|l'| = o(&delta;4/&epsilon;2), such that the ball centered at a point c with radius (1 + &epsilon;)r(l') intersects every element of l. the running time of the algorithm is o(n&delta;+1dpoly(1/&epsilon;)). for the case of lines or line segments (&delta; = 1), the (expected) running time of the algorithm can be improved to o(nd poly(1/&epsilon;)). we note that the size of the core set depends only on the dimension of the input objects and is independent of the input size n and the dimension d of the ambient space.
improved approximation for universal facility location. the universal facility location problem (unifl) is a generalized formulation which contains several variants of facility location including capacitated facility location (1-cfl) as its special cases. we present a 6 + &epsilon; approximation for the unifl problem, thus improving the 8 + &isin; approximation given by mahdian and pal. our result bridges the existing gap between the unifl problem and the 1-cfl problem.
linear programming and unique sink orientations. we show that any linear program (lp) in n nonnegative variables and m equality constraints defines in a natural way a unique sink orientation of the n-dimensional cube. from the sink of the cube, we can either read off an optimal solution to the lp, or we obtain certificates for infeasibility or unboundedness.this reduction complements the implicit local neighborhoods induced by the vertex-edge structure of the feasible region with an explicit neighborhood structure that allows random access to all 2n candidate solutions. using the currently best sink-finding algorithm for general unique sink orientations, we obtain the fastest deterministic lp algorithm in the ram model, for the central case n = 2m.
on adaptive deterministic gossiping in ad hoc radio networks. we study deterministic algorithms for gossiping problem in ad hoc radio networks. the gossiping problem is a communication task in which each node of the network possesses a unique single message that is to be communicated to all other nodes in the network. the efficiency of a communication algorithm in radio networks is very often expressed in terms of: max-eccentricity d, max-indegree &delta;, and size (number of nodes) n of underlying graph of connections. the max-eccentricity d of a network is the maximum of the lengths of shortest directed paths from a node u to a node v, taken over all ordered pairs (u, v) of nodes in the network. the max-indegree &delta; of a network is the maximum of indegrees of its nodes.we propose a new method that leads to several improvements in deterministic gossiping. it combines communication techniques designed for both known as well as unknown ad hoc radio networks. first we show how to subsume the o(dn)-time bound yield by the round-robin procedure proposing a new &otilde;(&radic;dn)-time gossiping algorithm. our algorithm is more efficient than the known &otilde;(n3/2)-time gossiping algorithms [3, 6], whenever d = o(n&alpha;) and &alpha; < 1. for large values of max-eccentricity d, we give another gossiping algorithm that works in time o(d&delta;3/2 log3 n) which subsumes the o(d&delta2 log3 n) upper bound presented in [4].
polynomial interpolation from multiples. we are given an unknown polynomial f &isin; ℤ[x] by a black box which on input a &isin; ℤ returns a value rq &middot; f(a) for some unknown nonzero rational numbers ra. if we have appropriate upper bounds on the numerator and denominator of ra and the degree of f, then the coefficients of f can be computed in probabilistic polynomial time.
distance labeling in graphs. we consider the problem of labeling the nodes of a graph in a way that will allow one to compute the distance between any two nodes directly from their labels (without using any additional information). our main interest is in the minimal length of labels needed in different cases. we obtain upper bounds and (most importantly) lower bounds for several interesting families of graphs. in particular, our main results are the following: for general graphs, the length needed is &thgr;(n). for trees, the length needed is &thgr;(log2 n). for planar graphs, we show an upper bound of &ogr;(&radic;n log n) and a lower bound of &ohgr;(n1/3). for bounded degree graphs, we show a lower bound of &ohgr;(&radic;n). the upper bounds for planar graphs and for trees follow by a more general upper bound for graphs with a r(n)- separator. the two lower bounds, however, are obtained by two different arguments that may be interesting in their own right. we also show some lower bounds on the length of the labels, even if it is only required that distances be approximated to a multiplicative factor s. for example, we show that for general graphs the required length is &ohgr;(n). we also consider the problem of the time complexity of the distance function once the labels are computed. we show that there are graphs with optimal labels of length 3 log n, such that if we use any labels with fewer than n bits per label, computing the distance function requires exponential time. a similar result is obtained for planar and bounded degree graphs.
succinct ordinal trees with level-ancestor queries. we consider suc cinct or space-efficient representations of trees that efficiently support a variety of navigation operations. we focus on static ordinal trees, i.e., arbitrary static rooted trees where the children of each node are ordered. the set of operations is essentially the union of the sets of operations supported by previous succinct representations (jacobson, proc. 30th focs, 549--554, 1989; munro and raman, siam j. comput. 31 (2001), 762--776; and benoit et. al proc. 6th wads, lncs 1663, 169--180, 1999), to which we add the level-ancestor operation.our representation takes 2n + o(n) bits to represent an n-node tree, which is within o(n) bits of the information-theoretic minimum, and supports all operations in o(1) time on the ram model. these operations also provide a mapping from the n nodes of the tree onto the integers {1,...,n}. in addition to the existing motivations for studying such data structures, we are motivated by the problem of representing xml documents compactly so that xpath queries can be supported efficiently.
computing strongly connected components in a linear number of symbolic steps. we present an algorithm that computes in a linear number of symbolic steps (o(&verbar;v&verbar;)) the strongly connected components (sccs) of a graph g = &lang;v, e&rang; represented by an ordered binary decision diagram (obdd). this result matches the complexity of the (celebrated) tarjan's algorithm operating on explicit data structures. to date, the best algorithm for the above problem works in &theta;(&verbar;v&verbar;log&verbar;v&verbar;) symbolic steps ([bgs00]).
finding dominators revisited: extended abstract. the problem of finding dominators in a flowgraph arises in many kinds of global code optimization and other settings. in 1979 lengauer and tarjan gave an almost-linear-time algorithm to find dominators. in 1985 harel claimed a linear-time algorithm, but this algorithm was incomplete; alstrup et al. [1999] gave a complete and "simpler" linear-time algorithm on a random-access machine. in 1998, buchsbaum et al. claimed a "new, simpler" linear-time algorithm with implementations both on a random access machine and on a pointer machine. in this paper, we begin by noting that the key lemma of buchsbaum et al. does not in fact apply to their algorithm, and their algorithm does not run in linear time. then we provide a complete, correct, simpler linear-time dominators algorithm. one key result is a linear-time reduction of the dominators problem to a nearest common ancestors problem, implementable on either a random-access machine or a pointer machine.
dominator tree verification and vertex-disjoint paths. we present a linear-time algorithm that given a flowgraph g = (v,a,r) and a tree t, checks whether t is the dominator tree of g. also we prove that there exist two spanning trees of g, t1 and t2, such that for any vertex <u>v</u> the paths from r to <u>v</u> in t1 and t2 intersect only at the vertices that dominate <u>v</u>. the proof is constructive and our algorithm can build the two spanning trees in linear time. simpler versions of our two algorithms run in o(m&alpha;(m, n))-time, where n is the number of vertices and m is the number of arcs in g. the existence of such two spanning trees implies that we can order the calculations of the iterative algorithm for finding dominators, proposed by allen and cocke [2], so that it builds the dominator tree in a single iteration.
design of data structures for mergeable trees. motivated by an application in computational topology, we consider a novel variant of the problem of efficiently maintaining dynamic rooted trees. this variant allows an operation that merges two tree paths. in contrast to the standard problem, in which only one tree arc at a time changes, a single merge operation can change many arcs. in spite of this, we develop a data structure that supports merges and all other standard tree operations in o(log2 n) amortized time on an n-node forest. for the special case that occurs in the motivating application, in which arbitrary arc deletions are not allowed, we give a data structure with an o(log n) amortized time bound per operation, which is asymptotically optimal. the analysis of both algorithms is not straightforward and requires ideas not previously used in the study of dynamic trees. we explore the design space of algorithms for the problem and also consider lower bounds for it.
random planar graphs with nodes and a fixed number of edges. let p(n, m) be the class of simple labelled planar graphs with n nodes and m edges, and let rn,q be a graph drawn uniformly at random from p(n, [qn]). we show properties that hold with high probability (w.h.p.) for rn,q when 1 < q < 3. for example, we show that rn,q contains w.h.p. linearly many nodes of each given degree and linearly many node disjoint copies of each given fixed connected planar graph. additionally, we show that the probability that rn,q is connected is bounded away from one by a non-zero constant. as a tool we show that (|p(n, [qn])|/n!)1/n tends to a limit as n tends to infinity.
the flow complex: a data structure for geometric modeling. we study a special case of the critical point (morse) theory of distance functions namely, the gradient flow associated with the distance function to a finite point set in r^3. the fixed points of this flow are exactly the critical points of the distance function. our main result is a mathematical characterization and algorithms to compute the stable manifolds, i.e., the inflow regions, of the fixed points. it turns out that the stable manifolds form a polyhedral complex that shares many properties with the delaunay triangulation of the same point set. we call the latter complex the flow complex of the point set. the flow complex is suited for geometric modeling tasks like surface reconstruction.
approximation of functions over redundant dictionaries using coherence. one of the central problems of modern mathematical approximation theory is to approximate functions, or signals, concisely, with elements from a large candidate set called a dictionary. formally, we are given a signal a &isin; rn and a dictionary d = {&phi;i}i&isin;i of unit vectors that span rn. a representation r of b terms for input a &isin; rn is a linear combination of dictionary elements, r = &sigma;i&isin;a &alpha;i&phi;i, for &phi;i &isin; d and some a, &verbar;a&verbar; &ge; b. typically, b ⪡ n, so that r is a concise approximation to signal a. the error of the representation indicates by how well it approximates a, and is given by ∥a - r∥2 = &radic;&sigma;t|a[t - r[t]|2. the problem is to find the best b-term representation, i.e., find a r that minimizes ∥a - r∥2. a dictionary may be redundant in the sense that there is more than one possible exact representation for a, i.e., &verbar;d&verbar; > n = dim(rn). redundant dictionaries are used because, both theoretically and in practice, for important classes of signals, as the size of a dictionary increases, the error and the conciseness of the approximations improve.we present the first known efficient algorithm for finding a provably approximate representation for an input signal over redundant dictionaries. we identify and focus on redundant dictionaries with small coherence (ie., vectors are nearly orthogonal). we present an algorithm that preprocesses any such dictionary in time and space polynomial in &verbar;d&verbar;, and obtains an 1 + &epsilon; approximate representation of the given signal in time nearly linear in signal size n and polylogarithmic in &verbar;d&verbar;; by contrast, most algorithms in the literature require &omega;(&verbar;d&verbar;)time, and, yet, provide no provable bounds. the technical crux of our result is our proof that two commonly used local search techniques, when combined appropriately, gives a provably near-optimal signal representation over redundant dictionaries with small coherence. our result immediately applies to several specific redundant dictionaries considered by the domain experts thus far. in addition, we present new redundant dictionaries which have small coherence (and therefore are amenable to our algorithms) and yet have significantly large sizes, thereby adding to the redundant dictionary construction literature.work with redundant dictionaries forms the emerging field of highly nonlinear approximation theory. we have presented algorithmic results for some of the most basic problems in this area, but other mathematical and algorithmic questions remain to be explored.
correlation clustering with a fixed number of clusters. we continue the investigation of problems concerning correlation clustering or clustering with qualitative information, which is a clustering formulation that has been studied recently [5, 7, 8, 3]. the basic setup here is that we are given as input a complete graph on n nodes (which correspond to nodes to be clustered) whose edges are labeled + (for similar pairs of items) and - (for dissimilar pairs of items). thus we have only as input qualitative information on similarity and no quantitative distance measure between items. the quality of a clustering is measured in terms of its number of agreements, which is simply the number of edges it correctly classifies, that is the sum of number of - edges whose endpoints it places in different clusters plus the number of + edges both of whose endpoints it places within the same cluster.in this paper, we study the problem of finding clusterings that maximize the number of agreements, and the complementary minimization version where we seek clusterings that minimize the number of disagreements. we focus on the situation when the number of clusters is stipulated to be a small constant k. our main result is that for every k, there is a polynomial time approximation scheme for both maximizing agreements and minimizing disagreements. (the problems are np-hard for every k &ge; 2.) the main technical work is for the minimization version, as the ptas for maximizing agreements follows along the lines of the property tester for max k-cut from [13].in contrast, when the number of clusters is not specified, the problem of minimizing disagreements was shown to be apx-hard [7], even though the maximization version admits a ptas.
stability of networks and protocols in the adversarial queueing model for packet routing. the adversarial queueing theory model for packet routing was suggested by borodin et al. we give a complete and simple characterization of all networks that are universally stable in this model. we show that a specific greedy protocol, sis (shortest in system), is stable against a large class of stochastic adversaries. new applications such as multicast packet scheduling and job scheduling with precedence constraints xsare suggested for the adversarial model.
simultaneous optimization for concave costs: single sink aggregation or single source buy-at-bulk. we consider the problem of finding efficient trees to send information from k sources to a single sink in a network where information can be aggregated at intermediate nodes in the tree. specifically, we assume that if information from j sources is traveling over a link, the total information that needs to be transmitted is f(j). one natural and important (though not necessarily comprehensive) class of functions is those which are concave, non-decreasing, and satisfy f(0) = 0. our goal is to find a tree which is a good approximation simultaneously to the optimum trees for all such functions. this problem is motivated by aggregation in sensor networks, as well as by buy-at-bulk network design.we present a randomized tree construction algorithm that guarantees e[maxfcf/c*(f)] 1 + log k, where cf is a random variable denoting the cost of the tree for function f and c* (f) is the cost of the optimum tree for function f. to the best of our knowledge, this is the first result regarding simultaneous optimization for concave costs. we also show how to derandomize this result to obtain a deterministic algorithm that guarantees maxf/c*(f) = o(log k). both these results are much stronger than merely obtaining a guarantee on maxfe[cf/c* (f)]. a guarantee on maxfe[cf/c* (f)] can be obtained using existing techniques, but this does not capture simultaneous optimization since no one tree is guaranteed to be a good approximation for all f simultaneously.while our analysis is quite involved, the algorithm itself is very simple and may well find practical use. we also hope that our techniques will prove useful for other problems where one needs simultaneous optimization for concave costs.
online throughput-competitive algorithm for multicast routing and admission control. we present the first polylog-competitive online algorithm for the general multicast problem in the throughput model. the ratio of the number of requests accepted by the optimum offline algorithm to the expected number of requests accepted by our algorithm is polylogarithmic in m and n, where m is the number of multicast groups and n is the number of nodes in the graph. we show that this is close to optimum by presenting an omega(log n log m) lower bound on this ratio for any randomized online algorithm against an oblivious adversary. we also show that it is impossible to be competitive against an adaptive online adversary. as in the previous online routing algorithms, our algorithm uses edge-costs when deciding on which is the best path to use. in contrast to the previous competitive algorithms in the throughput model, our cost is not a direct function of the edge load. the new new cost definition allows us to decouple the effects of routing and admission decisions of different multicast groups.
reductions among high dimensional proximity problems. we present improved running times for a wide range of approximate high dimensional proximity problems. we obtain subquadratic running time for each of these problems. these improved running times are obtained by reduction to nearest neighbour queries. the problems we consider in this paper are approximate diameter, approximate furthest neighbours, approximate discrete center, approximate metric facility location, approximate bottleneck matching, and approximate minimum weight matching.
approximate majorization and fair online load balancing. this article relates the notion of fairness in online routing and load balancing to vector majorization as developed by hardy et al. [1929]. we define &alpha;-supermajorization as an approximate form of vector majorization, and show that this definition generalizes and strengthens the prefix measure proposed by kleinberg et al. [2001] as well as the popular notion of max-min fairness.the article revisits the problem of online load-balancing for unrelated 1-&infin; machines from the viewpoint of fairness. we prove that a greedy approach is o(log n)-supermajorized by all other allocations, where n is the number of jobs. this means the greedy approach is globally o(log n)-fair. this may be contrasted with polynomial lower bounds presented by goel et al. [2001] for fair online routing.we also define a machine-centric view of fairness using the related concept of submajorization. we prove that the greedy online algorithm is globally o(log m)-balanced, where m is the number of machines.
distributed admission control, scheduling, and routing with stale information. we study the problem of distributed online admission control and routing of permanent virtual circuits in a capacitated network. we assume that we have k distinct decision makers, each of which is responsible for gathering its own information about the state of the network. through simulation, we demonstrate that an exponential based routing scheme will perform well in a distributed model provided granularity is sufficiently high. in order to ground these results theoretically, we prove that exponential-based schemes attain best-possible competitive ratios (same as for the centralized case) provided each edge can accommodate at least &ohgr;(k log n) requests. a matching lower-bound shows that no deterministic algorithm can attain best-possible competitive ratios without requiring the same level of granularity. in the randomized case, we present a modified exponential-based approach which obtains best-possible competitive ratios provided the granularity is at least &ohgr;(k + log n). our results may be extended to the case where different requests have different profits, and where requests are allowed to be temporary. they also apply to admission control and scheduling for unrelated machines.
cooperative facility location games. the location of facilities in order to provide service for customers is a well-studied problem in the operations research literature. in the basic model, there is a predefined cost for opening a facility and also for connecting a customer to a facility, the goal being to minimize the total cost. often, both in the case of public facilities (such as libraries, municipal swimming pools, fire stations,....) and private facilities (such as distribution centers, switching stations, ....), we may want to find a 'fair' allocation of the total cost to the customers-this is known as the cost allocation problem. a central question in cooperative game theory is whether the total cost can be allocated to the customers such that no coalition of customers has any incentive to build their own facility or to ask a competitor to service them. we establish strong connections between fair cost allocations and linear programming relaxations for several variants of the facility location problem. in particular, we show that a fair cost allocation exists if and only if there is no integrality gap for a corresponding linear programming relaxation; this was only known for the simplest unconstrained variant of the facility location problem. moreover, we introduce a subtle variant of randomized rounding and derive new proofs for the existence of fair cost allocations for several classes of instances. we also show that it is in general np-complete to decide whether a fair cost allocation exists and whether a given allocation is fair.
covering minimum spanning trees of random subgraphs. we consider the problem of covering the minimum spanning tree (mst) of a random subgraph of g by a sparse set of edges, with high probability. the two random models that we consider are subgraphs induced by a random subset of vertices, each vertex included independently with probability p, and subgraphs generated as a random subset of edges, each edge with probability p.let n be the number of vertices in g. we show that in both cases, there is a covering set q of cardinality o(n logb n) where b = 1/(1 -- p) (and p is possibly a function of n) and this is asymptotically optimal. more generally, we show a similar bound on the covering set in a matroid, which contains the minimum-weight basis of a random subset with high probability. also, we give a randomized algorithm which calls an mst subroutine only a polylogarithmic number of times, and finds the covering set with high probability.
a general approximation technique for constrained forest problems. we present a general approximation technique for a large class of graph problems. our technique mostly applies to problems of covering, at minimum cost, the vertices of a graph with trees, cycles or paths satisfying certain requirements. in particular, many basic combinatorial optimization problems fit in this framework, including the shortest path, minimum spanning tree, minimum-weight perfect matching, traveling salesman and steiner tree problems. our technique produces approximation algorithms that run in o(n2 log n) time and come within a factor of 2 of optimal for most of these problems. for instance, we obtain a 2-approximation algorithm for the minimum-weight perfect matching problem under the triangle inequality. our running time of o(n2 log n) time compares favorably with the best strongly polynomial exact algorithms running in o(n3) time for dense graphs. a similar result is obtained for the 2-matching problem and its variants.we also derive the first approximation algorithms for many np-complete problems, including the non-fixed point-to-point connection problem, the exact path partitioning problem and complex location-design problems. moreover, for the prize-collecting traveling salesman or steiner tree problems, we obtain 2-approximation algorithms, therefore improving the previously best-known performance guarantees of 2.5 and 3, respectively [4].
two-dimensional gantt charts and a scheduling algorithm of lawler. in this note we give an alternate proof that a scheduling algorithm of lawler [e. l. lawler, ann. discrete math., 2 (1978), pp. 75--90, e. l. lawler and j. k. lenstra, in ordered sets, i. rival, ed., d. reidel, 1982, pp. 655--675] finds the optimal solution for the scheduling problem $1 | prec | \sum_j w_j c_j$ when the precedence constraints are series-parallel. we do this by using a linear programming formulation of $1 | prec | \sum_j w_j c_j$ introduced by queyranne and wang. [ math. oper. res., 16 (1991), pp. 1--20]. queyranne and wang proved that their formulation completely describes the scheduling polyhedron in the case of series-parallel constraints; a by-product of our proof of correctness of lawler's algorithm is an alternate proof of this fact. in the course of our proof it is helpful to use what might be called two-dimensional (2d) gantt charts. we think these may find independent use, and to illustrate this we show that some recent work in the area becomes transparent using 2d gantt charts.
scaling algorithms for the shortest paths problem. we describe a new method for designing scaling algorithms for the single-source shortest paths problem and use this method to obtain an $o(\sqrt n m \log n)$ algorithm for the problem. (here $n$ and $m$ is the number of nodes and arcs in the input network and $n$ is essentially the absolute value of the most negative arc length, and arc lengths are assumed to be integral.) this improves previous bounds for the problem. the method extends to related problems.
competitiveness via consensus. we introduce the following consensus estimate problem. several processors hold private and possibly different lower bounds on a value. the processors do not communicate with each other, but can observe a shared source of random numbers. the goal is to come up with a consensus lower bound on the value that is as high as possible. we give a solution to the consensus estimate problem and show how it is useful in the context of mechanism design. the consensus problem is natural and may have other applications. based on our consensus estimate technique, we introduce consensus revenue estimate (core) auctions. this is a class of competitive revenue-maximizing auctions that is interesting for several reasons. one auction from this class achieves a better competitive ratio than any previously known auction. another one uses only two random bits, whereas the previously known competitive auctions on n bidders use n random bits. furthermore, a parameterized core auction performs better than the previous auctions in the context of mass-market goods, such as digital goods.
computing the shortest path: search meets graph theory. we propose shortest path algorithms that use a* search in combination with a new graph-theoretic lower-bounding technique based on landmarks and the triangle inequality. our algorithms compute optimal shortest paths and work on any directed graph. we give experimental results showing that the most efficient of our new algorithms outperforms previous algorithms, in particular a* search with euclidean bounds, by a wide margin on road networks and on some synthetic problem families.
collusion-resistant mechanisms for single-parameter agents. we consider the problem of designing mechanisms with the incentive property that no coalition of agents can engage in a collusive strategy that results in an increase in the combined utility of the coalition. for single parameter agents, we give a characterization that essentially restricts such mechanisms to those that post a "take it or leave it" price to for each agent in advance. we then consider relaxing the incentive property to only hold with high probability. in this relaxed model, we are able to design approximate profit maximizing auctions and approximately efficient auctions. we generalized these results to give a methodology for designing collusion resistant mechanisms for single parameter agents. in addition, we give several results for a weaker incentive property from the literature known as group strategyproofness.
competitive auctions and digital goods. we study a class of single round, sealed bid auctions for items in unlimited supply such as digital goods. we focus on auctions that are truthful and competitive. truthful auctions encourage bidders to bid their utility; competitive auctions yield revenue within a constant factor of the revenue for optimal fixed pricing. we show that for any truthful auction, even a multi-price auction, the expected revenue does not exceed that for optimal fixed pricing. we also give a bound on how far the revenue for optimal fixed pricing can be from the total market utility. we show that several randomized auctions are truthful and competitive under certain assumptions, and that no truthful deterministic auction is competitive. we present simulation results which confirm that our auctions compare favorably to fixed pricing. some of our results extend to bounded supply markets, for which we also get truthful and competitive auctions.
randomly sampling molecules. we give the first polynomial-time algorithm for the following problem: given a degree sequence in which each degree is bounded from above by a constant, select, uniformly at random, an unlabelled connected multigraph with the given degree sequence. we also give the first polynomial-time algorithm for the following related problem: given a molecular formula, select, uniformly at random, a structural isomer having the giver formula.
better approximation guarantees for job-shop scheduling. job-shop scheduling is a classical np-hard problem. shmoys, stein, and wein presented the first polynomial-time approximation algorithm for this problem that has a good (polylogarithmic) approximation guarantee. we improve the approximation guarantee of their work and present further improvements for some important np-hard special cases of this problem (e.g., in the preemptive case where machines can suspend work on operations and later resume). we also present nc algorithms with improved approximation guarantees for some np-hard special cases.
the wake up and report problem is time-equivalent to the firing squad synchronization problem. we consider several problems relating to strongly-connected directed networks of identical finite-state processors that work synchronously in discrete time steps. the conceptually simplest of these problems is the wake up and report problem; this is the problem of having a unique "root" processor send a signal to all other processors in the network and then enter a special "done" state only when all other processors have received the signal. the most difficult of the problems we consider is the classic firing squad synchronization problem; this is the much-studied problem of achieving macro-synchrorization in a network given micro-synchronization. we show via a complex algorithmic application of the "snake" data stucture first introduced in even, litman, and winkler[6] that these two problems in particular are asymptotically time-equivalent up to a constant factor. this result leads immediately to the inclusion of several other related problems into this new asymptotic time-class.
patience is a virtue: the effect of slack on competitiveness for admission control. we consider the online competitiveness for scheduling a single resource non-preemptively in order to maximize its utilization. our work examines this model when parameterizing an instance by a new value which we term the patience. this parameter measures each job's willingness to endure a delay before starting, relative to this same job's processing time. specifically, the slack of a job is defined as the gap between its release time and the last possible time at which it may be started while still meeting its deadline. we say that a problem instance has patience κ, if each job with length ||j|| has a slack of at least κ ċ ||j||.without any restrictions placed on the job characteristics, previous lower bounds show that no algorithm, deterministic or randomized, can guarantee a constant bound on the competitiveness of a resulting schedule. previous researchers have analyzed a problem instance by parameterizing based on the ratio between the longest job's processing time and the shortest job's processing time. our main contribution is to provide a fine-grained analysis of the problem when simultaneously parameterized by patience and the range of job lengths. we are able to give tight or almost tight bounds on the deterministic competitiveness for all parameter combinations.if viewing the analysis of each parameter individually, our evidence suggests that parameterizing solely on patience provides a richer analysis than parameterizing solely on the ratio of the job lengths. for example, in the special case where all jobs have the same length, we generalize a previous bound of 2 for the deterministic competitiveness with arbitrary slacks, showing that the competitiveness for any κ ≥ 0 is exactly 1 + 1/(⌊κ⌋ + 1). without any bound on the job lengths, a simple greedy algorithm is (2+ 1/κ)- competitive for any κ > 0. more generally we will find that for any fixed ratio of job lengths, the competitiveness of the problem tends towards 1 as the patience is increased. the converse is not true, as for any fixed κ > 0 we find that the competitiveness is bounded away from 1, no matter what further restrictions are placed on the ratio of job lengths.
algorithms for infinite huffman-codes. optimal (minimum cost) binary prefix-free codes for infinite sources with geometrically distributed frequencies, e.g., p = {pi(1 - p)}&infin;i=0 0 < p < 1, were first (implicitly) suggested by golomb over thirty years ago in the context of run-length encodings. ten years later gallager and van voorhis exhibited such optimal codes for all values of p: just recently merhav, seroussi and weinberger extended this further to find optimal binary prefix-free codes for two-sided geometric distributions.these codes were derived by cleverly "guessing" optimal codes for finite sources, validating these guesses by using the sibling property of huffman encoding, and then showing that the finite codes converge in a very specific sense to an optimal infinite one.in this paper we describe the first algorithmic approach to constructing optimal prefix-free infinite codes. our approach is to define an infinite weighted graph with the property that the least cost infinite path in the graph corresponds to the optimal code. we then show that even though the graph is infinite, the leastcost infinite path has a repetitive structure and that it is therefore possible to not only find this path but to find it relatively efficiently.this approach will work for even more complicated generalizations of geometric sources where solutions can't be guessed as well as in extensions of huffman-coding for which the huffman algorithm no longer works, e.g., non-uniform cost encoding alphabet characters and/or other restrictions on the codewords. we illustrate our approach by deriving an algorithm for constructing optimal prefix free codes with a geometric source for the telegraph channel. we also implement our algorithm and show what the constructed codes look like in this case.
randomized data structures for the dynamic closest-pair problem. we describe a new randomized data structure, the sparse partition, for solving the dynamic closest-pair problem. using this data structure the closest pair of a set of n points in d-dimensional space, for any fixed d, can be found in constant time. if a frame containing all the points is known in advance, and if the floor function is available at unit cost, then the data structure supports insertions into and deletions from the set in expected o(log n) time and requires expected o(n) space. this method is more efficient than any deterministic algorithm for solving the problem in dimension d > 1. the data structure can be modified to run in o(log2 n) expected time per update in the algebraic computation tree model. even this version is more efficient than the best currently known deterministic algorithm for d > 2. both results assume that the sequence of updates is not determined in any way by the random choices made by the algorithm.
approximating the -multicut problem. we study the k-multicut problem: given an edge-weighted undirected graph, a set of l pairs of vertices, and a target k &le; l, find the minimum cost set of edges whose removal disconnects at least k pairs. this generalizes the well known multicut problem, where k = l. we show that the k-multicut problem on trees can be approximated within a factor of 8/3 + &epsilon;, for any fixed &epsilon; > 0, and within o(log2 n log log n) on general graphs, where n is the number of vertices in the graph.for any fixed &epsilon; > 0, we also obtain a polynomial time algorithm for k-multicut on trees which returns a solution of cost at most (2 + &epsilon;) &middot; opt, that separates at least (1 - &epsilon;) &middot; k pairs, where opt is the cost of the optimal solution separating k pairs.our techniques also give a simple 2-approximation algorithm for the multicut problem on trees using total unimodularity, matching the best known algorithm [8].
approximation algorithms for data placement on parallel disks. we study an optimization problem that arises in the context of data placement in a multimedia storage system. we are given a collection of m multimedia objects (data objects) that need to be assigned to a storage system consisting of n disks d1,d2&hellip;,dn. we are also given sets u1,u2,&hellip;,um such that ui is the set of clients seeking the ith data object. each disk dj is characterized by two parameters, namely, its storage capacity cj which indicates the maximum number of data objects that may be assigned to it, and a load capacity lj which indicates the maximum number of clients that it can serve. the goal is to find a placement of data objects to disks and an assignment of clients to disks so as to maximize the total number of clients served, subject to the capacity constraints of the storage system. we study this data placement problem for two natural classes of storage systems, namely, homogeneous and uniform ratio. we show that an algorithm developed by shachnai and tamir [2000a] for data placement achieves the best possible absolute bound regarding the number of clients that can always be satisfied. we also show how to implement the algorithm so that it has a running time of o((n + m) log(n + m)). in addition, we design a polynomial-time approximation scheme, solving an open problem posed in the same paper.
rank/select operations on large alphabets: a tool for text indexing. we consider a generalization of the problem of supporting rank and select queries on binary strings. given a string of length n from an alphabet of size &sigma;, we give the first representation that supports rank and access operations in o(lg lg &sigma;) time, and select in o(1) time while using the optimal n lg &sigma; + o(n lg &sigma;) bits. the best known previous structure for this problem required o(lg &sigma;) time, for general values of &sigma;. our results immediately improve the search times of a variety of text indexing methods.
an improved approximation algorithm for the partial latin square extension problem. the problem of completing partial latin squares arises in a number of applications, including conflict-free wavelength routing in wide-area optical networks, statistical designs, and error-correcting codes. a partial latin square is an n by n array such that each cell is either empty or contains exactly one of the colors 1, ..., n, and each color occurs at most once in any row or column. in this paper, we consider the problem of finding an extension of a given partial latin square with the maximum number of colored cells. approximation algorithms for this problem were introduced by kumar, russell, and sundaram, who gave a 2-approximation algorithm for this problem that is based on a 3-dimensional assignment formulation. we introduce a packing linear programming relaxation for this problem, and show that a natural randomized rounding algorithm yields an e/(e -- 1)-approximation algorithm.
the on-line -dimensional dictionary problem. we present a new algorithm for the on-line d-dimensional dictionary problem which has many applications including the management of geometrical objects and geometrical searching. the dictionary problem consists of executing on-line any sequence of the following operations: insert(p), delete(p) and membership(p), where p is any point in d-space. we introduce a clean structure based on balanced binary search trees, which we call d-dimensional balanced binary search trees, to represent the set of points. we present algorithms for each of the above operations that take o(d + log n) time, where n is the current number of points in the set, and each insert and delete operation requires no more than a constant number of rotations. our procedures are almost identical to the ones for balanced binary search trees. the main difference is in the way we search for an element. our search strategy is based on the principle &ldquo;assume, verify and conquer&rdquo; (avc). we apply this principle as follows. to avoid multiple verifications we shall assume that some prefixes of strings match. at the end of our search we must determine whether or not these assumptions were valid. this can be done by performing one simple verification step that takes o(d) time. the elimination of multiple verifications is important because in the worst case there are &ohgr;(log n) verifications, and each could take &ohgr;(d) time.
the rainbow skip graph: a fault-tolerant constant-degree distributed data structure. we present a distributed data structure, which we call the rainbow skip graph. to our knowledge, this is the first peer-to-peer data structure that simultaneously achieves high fault-tolerance, constant-sized nodes, and fast update and query times for ordered data. it is a non-trivial adaptation of the skipnet/skip-graph structures of harvey et al. and aspnes and shah, so as to provide fault-tolerance as these structures do, but to do so using constant-sized nodes, as in the family tree structure of zatloukal and harvey. it supports successor queries on a set of n items using o(log n) messages with high probability, an improvement over the expected o(log n) messages of the family tree. our structure achieves these results by using the following new constructs:&bull; rainbow connections: parallel sets of pointers between related components of nodes, so as to achieve good connectivity between "adjacent" components, using constant-sized nodes.&bull; hydra components: highly-connected, highly fault-tolerant components of constant-sized nodes, which will contain relatively large connected subcomponents even under the failure of a constant fraction of the nodes in the component.we further augment the hydra components in the rainbow skip graph by using erasure-resilient codes to ensure that any large subcomponent of nodes in a hydra component is sufficient to reconstruct all the data stored in that component. by carefully maintaining the size of related components and hydra components to be o(log n), we are able to achieve fast times for updates and queries in the rainbow skip graph. in addition, we show how to make the communication complexity for updates and queries be worst case, at the expense of more conceptual complexity and a slight degradation in the node congestion of the data structure.
query-efficient algorithms for polynomial interpolation over composites. the problem of polynomial interpolation is to reconstruct a polynomial based on its valuations on a set of inputs i. we consider the problem over zm when m is composite. we ask the question: given i &sube; zm, how many evaluations of a polynomial at points in i are required to compute its value at every point in i? surprisingly for composite m, this number can vary exponentially between log[i] and [i] in contrast to the prime case where [i] evaluations are necessary. while this minimization problem is np-complete, we give an efficient algorithm of query complexity within a factor t of the optimum where t is the number of prime factors of m. we use our interpolation algorithm to design algorithms for zero-testing and distributional learning of polynomials over zm. in some cases, we get an exponential improvement over known algorithms in query complexity and running time. our main technical contribution is the notion of an interpolating set for i which is a subset s of i such that a polynomial which is 0 over s must be 0 at every point in i. any interpolation algorithm needs to query an interpolating set for i. our query-efficient algorithms are obtained by constructing interpolating sets whose size is close to optimal.
caching with expiration times. caching data together with expiration times beyond which the data is no longer valid is a standard method for promoting information consistency in distributed systems, including the internet and www, large databases, and mobile telecommunications. we use the framework of competitive analysis of online algorithms and study page eviction strategies in the case where data has expiration times. we show that suitable adaptations of lru and its generalizations, namely marking algorithms, are asymptotically optimal and, in the worst case, within a multiplicative factor 2 of the lower bounds. a key technical ingredient of our analysis is a covering invariant that captures some of the subtleties introduced by expiration times. the additional difficulty of dealing with expiration times is also reflected in our analysis of the randomized online marking algorithm, as well as the offline version of the problem for which we obtain a factor 3 approximation. we complement our theoretical findings with experiments on real and synthetic data.
rounds vs queries trade-off in noisy computation. we show that a noisy parallel decision tree making o(n) queries needs &omega;(log* n) rounds to compute or of n bits. this answers a question of newman [21]. we prove more general trade-offs between the number of queries and rounds. we also completely settle a similar question for computing max in the noisy comparison tree model; these results bring out interesting differences among the noise models.
light spanners and approximate tsp in weighted graphs with forbidden minors. given an edge weighted graph g with n vertices and no k&tau;-minor and a small positive constant &epsilon;, we show that a simple greedy algorithm [1] finds a spanning subgraph approximating all shortest-path distances within a factor of 1 + &epsilon;, and with total edge weight at most o((&tau;&radic;log&tau; &middot; logn)/&epsilon;) times the weight of a minimum spanning tree. this result implies a quasi-polynomial time approximation scheme (qptas) for the traveling salesman problem (tsp) in such graphs, with running time no((&tau;4&radic;log&tau;&middot;log n&middot;log log n)/&epsilon;2).our analysis shows that a graph with detour gap number [5] &omega;(&tau;&radic;log&tau; &middot; log n) has a k&tau;-minor. we also show that this dependence on n is nearly tight, by exhibiting graphs with no k6-minor (apex graphs) and detour gap number &omega;((log n)/log log n).as a step towards eliminating the log n factors the first paragraph, we propose a generalized detour gap number, now depending on &epsilon;, and we show that it remains bounded for apex graphs and some similar graph families.
constraint solving via fractional edge covers. many important combinatorial problems can be modelled as constraint satisfaction problems, hence identifying polynomial-time solvable classes of constraint satisfaction problems received a lot of attention. in this paper, we are interested in structural properties that can make the problem tractable. so far, the largest structural class that is known to be polynomial-time solvable is the class of bounded hypertree width instances introduced by gottlob et al. [20]. here we identify a new class of polynomial-time solvable instances: those having bounded fractional edge cover number.combining hypertree width and fractional edge cover number, we then introduce the notion of fractional hypertree width. we prove that constraint satisfaction problems with bounded fractional hypertree width can be solved in polynomial time (provided that a the tree decomposition is given in the input). we also prove that certain parameterized constraint satisfaction, homomorphism, and embedding problems are fixed-parameter tractable on instances having bounded fractional hypertree width.
high-order entropy-compressed text indexes. we present a novel implementation of compressed suffix arrays exhibiting new tradeoffs between search time and space occupancy for a given text (or sequence) of n symbols over an alphabet &sigma;, where each symbol is encoded by lg&verbar;&sigma;&verbar; bits. we show that compressed suffix arrays use just nhh + &sigma; bits, while retaining full text indexing functionalities, such as searching any pattern sequence of length m in o(m lg &verbar;&sigma;&verbar; + polylog(n)) time. the term hh &le; lg &verbar;&sigma;&verbar; denotes the hth-order empirical entropy of the text, which means that our index is nearly optimal in space apart from lower-order terms, achieving asymptotically the empirical entropy of the text (with a multiplicative constant 1). if the text is highly compressible so that hn = o(1) and the alphabet size is small, we obtain a text index with o(m) search time that requires only o(n) bits. further results and tradeoffs are reported in the paper.
when indexing equals compression: experiments with compressing suffix arrays and applications. we report on a new and improved version of high-order entropy-compressed suffix arrays, which has theoretical performance guarantees similar to those in our earlier work [16], yet represents an improvement in practice. our experiments indicate that the resulting text index offers state-of-the-art compression. in particular, we require roughly 20% of the original text size---without requiring a separate instance of the text---and support fast and powerful searches. to our knowledge, this is the best known method in terms of space for fast searching.
approximate distance oracles for geometric graphs. given a geometric t-spanner graph g in ed with n points and m edges, with edge lengths that lie within a polynomial (in n) factor of each other. then, after o(m+n log n) preprocessing, we present an approximation scheme to answer (1+&epsilon;)-approximate shortest path queries in o(1) time. the data structure uses o(n log n) space.
approximation algorithms for wavelet transform coding of data streams. given a set of orthonormal basis functions {&psi;i} and a target function/vector f, the wavelet representation problem is to construct f as a combination of at most b basis vectors to minimize some normed distance between f and f. the problem is well understood if the error is the mean squared error: the largest (ignoring signs) b coefficients of the wavelet expansion should be retained. this strategy follows from the proof of optimality and is not a built-in constraint.the mean squared error, however, is not the optimization criterion in several scenarios. the above easy solution to the wavelet representation problem does not carry over to lp for p &ne; 2, and it turns out that restricting the solution to any subset of coefficients of size b or less is suboptimal compared to the best solution which can choose arbitrary real numbers. further, all the previous literature on non-l2 errors only considered the haar system.in this paper we provide the first approximation schemes for the unrestricted optimization problem. we provide a lower bounding technique based on a system of inequalities. we show that a modified greedy algorithm that retains the coefficients of expansion gives a o(log n) true (factor) approximation algorithm for a wide variety of compact wavelet systems, including haar, daubechies, symmlets, coiflets among others. this vindicates several scaling type algorithms which are used in practice. we subsequently augment the lower bound and give a fptas for the haar system. the same ideas extend to a qptas for the more general class of compact wavelets mentioned above. we also consider adaptive quantization problems, which are generalizations of the b-term representations.
capacitated vertex covering with applications. in this paper we study the capacitated vertex cover problem, a generalization of the well known vertex cover problem. given a graph g = (v, e) with weights on the vertices, the goal is to cover all the edges by picking a cover of minimum weight from the vertices. when we pick a copy of a vertex, we pay the weight of the vertex and cover upto a pre-specified number of edges incident on this vertex (its capacity). the problem is np-hard. we give a primal-dual based 2 approximation and study several generalizations, as well as the problem restricted to trees.
improved algorithms for the data placement problem. we study the data placement problem [1, 3], where the goal is to place certain data objects (with possible replication) in fixed capacity caches in a network to optimize latency of access. the locations of the caches are given and each cache has capacities both on the number of objects it can store and the number of users it can serve. each user has a demand for a specific object.the end objective is to optimize the average user latency of accessing the objects. we present a constant approximation, while blowing up the cache capacities by a constant factor. this improves the previous results, which either ignore the bound on the number of users [1], or which need to blow up the capacities by a logarithmic factor [3]. our solution technique involves writing an integer program for this problem and rounding its linear relaxation.we note that our result is the best possible that can be obtained by lp rounding. the problem is max-snp hard as shown in [1], and the linear program has unbounded integrality gap unless we relax the capacity constraints [5].our basic technique is to separate the rounding into two stages:opening objects: in this stage, we consider each object separately, and open copies in the network. we ignore the interaction of this object with other objects due to the cache capacity constraints. we use the capacitated facility location rounding from [5].packing objects: in this stage, we pack the objects into the cache so that cache capacity constraints are satisfied. we use the gap rounding from [4].
improved algorithms for fault tolerant facility location. we consider a generalization of the classical facility location problem, where we require the solution to be fault-tolerant. every demand point j is served by rj facilities instead of just one. the facilities other than the closest one are &ldquo;backup&rdquo; facilities for that demand, and will be used only if the closer facility (or the link to it) fails. hence, for any demand, we assign non-increasing weights to the routing costs to farther facilities. the cost of assignment for demand j is the weighted linear combination of the assignment costs to its rj closest open facilities. we wish to minimize the sum of the cost of opening the facilities and the assignment cost of each demand j. we obtain a factor 4 approximation to this problem through the application of various rounding techniques to the linear relaxation of an integer program formulation. we further improve this result to 3.16 using randomization and to 2.47 using greedy local-search type techniques.
streaming and sublinear approximation of entropy and information distances. in most algorithmic applications which compare two distributions, information theoretic distances are more natural than standard lp norms. in this paper we design streaming and sublinear time property testing algorithms for entropy and various information theoretic distances.batu et al posed the problem of property testing with respect to the jensen-shannon distance. we present optimal algorithms for estimating bounded, symmetric f-divergences (including the jensen-shannon divergence and the hellinger distance) between distributions in various property testing frameworks. along the way, we close a (log n)/h gap between the upper and lower bounds for estimating entropy h, yielding an optimal algorithm over all values of the entropy. in a data stream setting (sublinear space), we give the first algorithm for estimating the entropy of a distribution. our algorithm runs in polylogarithmic space and yields an asymptotic constant factor approximation scheme. an integral part of the algorithm is an interesting use of an f0 (the number of distinct elements in a set) estimation algorithm; we also provide other results along the space/time/approximation tradeoff curve.our results have interesting structural implications that connect sublinear time and space constrained algorithms. the mediating model is the random order streaming model, which assumes the input is a random permutation of a multiset and was first considered by munro and paterson in 1980. we show that any property testing algorithm in the combined oracle model for calculating a permutation invariant functions can be simulated in the random order model in a single pass. this addresses a question raised by feigenbaum et al regarding the relationship between property testing and stream algorithms. further, we give a polylog-space ptas for estimating the entropy of a one pass random order stream. this bound cannot be achieved in the combined oracle (generalized property testing) model.
the robot localization problem in two dimensions. we consider the following problem: given a simple polygon p and a star-shaped polygon v, find a point (or the set of points) in p from which the portion of p that is visible is congruent to v. the problem arises in the localization of robots using a range-finder&mdash;p is a map of a known environment, v is the portion visible from the robot's position, and the robot must use this information to determine its position in the map. we give a scheme that preprocesses p so that any subsequent query v is answered in optimal time o(m + log n + a), where m and n are the number of vertices in v and p, and a is the number of points in p that are valid answers (the output size). our technique allows us to trade off smoothly between the query time and the preprocessing time or space. we also devise a data structure for output-sensitive determination of the visibility polygon of a query point inside a polygon p. we then consider a variant of the localization problem in which there is a maximum distance to which the robot can &ldquo;see&rdquo;&mdash;this is motivated by practical considerations, and we outline a similar solution for this case. we also show that a single localization query v can be answered in time o(mn) with no preprocessing.
zonotopes as bounding volumes. zonotopes are centrally symmetric polytopes with a very special structure: they are minkowski sums of line segments. in this paper we propose to use zonotopes as bounding volumes for geometry in collision detection and other applications where the spatial relationship between two pieces of geometry is important. we show how to construct optimal, or approximately optimal zonotopes enclosing given set of points or other geometry. we also show how zonotopes can be used for efficient collision testing, based on their representation via their defining line segments --- without ever building their explicit description as polytopes. this implicit representation adds flexibility, power, and economy to the use of zonotopes as bounding volumes.
optimizing markov models with applications to triangular connectivity coding. in this work markov models are constructed to describe the asymptotic stochastical behavior of regular languages, what allows for optimal arithmetic coding of words from the language. a new method is presented for the optimization of markov models such that also constraints are captured that cannot be described within a regular language. the new technique is applied to the encoding of the connectivity graph of triangle meshes of low genus and boundary fraction. the resulting compression rates are up to one percent optimal and the best known upper bound for this class of models.
steiner points in tree metrics don't (really) help. consider an edge-weighted tree t = (v, e, w : e &rarrtl; r+), in which a subset r of the nodes (called the required nodes) are colored red and the remaining nodes in s = v\r are colored black (and called the steiner nodes). the shortest-path distance according to the edge-weights defines a metric dt on the vertex set v. we now ask the following question: is it possible to define another weighted tree t* = (r, e*, w* : e* &rarrtl; r+), this time on just the red vertices so that the shortest-path metric dt* induced by t* on the vertices in r is &ldquo;close&rdquo; to the metric dt restricted to the red vertices? i.e., does there exist a weighted tree t* = (r, e*, c*) and a (small) constant &agr; such that dt(u, v) &le; dt* (u, v) &le; &agr; dt(u, v) for any two red vertices u, v &isin; r? we answer this question in the affirmative, and give a linear time algorithm to obtain a tree t* with &agr; &le; 8. we also give two applications of this result: an upper bound, in which we show that emulating multicasts using unicasts can be almost as good as general multicasts for certain performance measures; and a lower bound, in which we give a simple combinatorial proof of the fact that the metric generated by a graph of girthg must suffer a distortion of at least &ohgr;(g) when approximated by a tree.
improved results for directed multicut. we give a simple algorithm for the minimum directed multicut problem, and show that it gives an o(&radic;n)-approximation. this improves on the previous approximation guarantee of o(&radic;n log k) of cheriyan, karloff and rabani [1], which was obtained by a more sophisticated algorithm.
oblivious network design. consider the following network design problem: given a network g = (v, e), source-sink pairs {si, ti} arrive and desire to send a unit of flow between themselves. the cost of the routing is this: if edge e carries a total of fe flow (from all the terminal pairs), the cost is given by &sigma; el(fe), where l is some concave cost function; the goal is to minimize the total cost incurred. however, we want the routing to be oblivious: when terminal pair {si, ti} makes its routing decisions, it does not know the current flow on the edges of the network, nor the identity of the other pairs in the system. moreover, it does not even know the identity of the function l, merely knowing that l is a concave function of the total flow on the edge. how should it (obliviously) route its one unit of flow? can we get competitive algorithms for this problem?in this paper, we develop a framework to model oblivious network design problems (of which the above problem is a special case), and give algorithms with poly-logarithmic competitive ratio for problems in this framework (and hence for this problem). abstractly, given a problem like the one above, the solution is a multicommodity flow producing a "load" on each edge of le = l(f1(e),f2(e), ..., fk(e)), and the total cost is given by an "aggregation function" agg (le1,...,lem) of the loads of all edges. our goal is to develop oblivious algorithms that approximately minimize the total cost of the routing, knowing the aggregation function agg, but merely knowing that l lies in some class c, and having no other information about the current state of the network. hence we want algorithms that are simultaneously "function-oblivious" as well as "traffic-oblivious".the aggregation functions we consider are the max and &sigma; objective functions, which correspond to the well-known measures of congestion and total cost of a network; in this paper, we prove the following:&bull; if the aggregation function is &sigma;, we give an oblivious algorithm with o(log2 n) competitive ratio whenever the load function l is in the class of monotone sub-additive functions. (recall that our algorithm is also "function-oblivious"; it works whenever each edge has a load function l in the class.)&bull; for the case when the aggregation function is max, we give an oblivious algorithm with o(log2 n log log n) competitive ratio, when the load function l is a norm; we also show that such a competitive ratio is not possible for general sub-additive functions.these are the first such general results about oblivious algorithms for network design problems, and we hope the ideas and techniques will lead to more and improved results in this area.
approximating unique games. the unique games problem is the following: we are given a graph g = (v, e), with each edge e = (u, v) having a weight we and a permutation &pi;uv on [k]. the objective is to find a labeling of each vertex u with a label fu &isin; [k] to minimize the weight of unsatisfied edges---where an edge (u, v) is satisfied if fv = &pi;uv(fu).the unique games conjecture of khot [8] essentially says that for each &epsilon; > 0, there is a k such that it is np-hard to distinguish instances of unique games with (1-&epsilon;) satisfiable edges from those with only &epsilon; satisfiable edges. several hardness results have recently been proved based on this assumption, including optimal ones for max-cut, vertex-cover and other problems, making it an important challenge to prove or refute the conjecture.in this paper, we give an o(log n)-approximation algorithm for the problem of minimizing the number of unsatisfied edges in any unique game. previous results of khot [8] and trevisan [12] imply that if the optimal solution has opt = &epsilon;m unsatisfied edges, semidefinite relaxations of the problem could give labelings with min {k2&epsilon;1/5, (&epsilon; log n)1/2}m unsatisfied edges. in this paper we show how to round a lp relaxation to get an o(log n)-approximation to the problem; i.e., to find a labeling with only o(&epsilon;m log n) = o(opt log n) unsatisfied edges.
counting inversions in lists. in a recent paper, ajtai et al. [1] give a streaming algorithm to count the number of inversions in a stream l&epsilon;[m]n using two passes and o(&epsilon;&minus;1-&radic;n log n(log m + log n)) space. here, we present a simple randomized streaming algorithm for the same problem that uses one pass and o(&epsilon;&minus;3 log2 n log m) space. our algorithm is based on estimating quantiles of the items already seen in the stream, and using that to estimate the number of inversions involving each element.
on profit-maximizing envy-free pricing. we study the problem of pricing items for sale to consumers so as to maximize the seller's revenue. we assume that for each consumer, we know the maximum amount he would be willing to pay for each bundle of items, and want to find pricings of the items with corresponding allocations that maximize seller profit and at the same time are envy-free, which is a natural fairness criterion requiring that consumers are maximally happy with the outcome they receive given the pricing. we study this problem for two important classes of inputs: unit demand consumers, who want to buy at most one item from among a selection they are interested in, and single-minded consumers, who want to buy one particular subset, but only if they can afford it.we show that computing envy-free prices to maximize the seller's revenue is apx-hard in both of these cases, and give a logarithmic approximation algorithm for them. for several interesting special cases, we derive polynomial-time algorithms. furthermore, we investigate some connections with the corresponding mechanism design problem, in which the consumer's preferences are private values: for this case, we give a log-competitive truthful mechanism.
efficiently decodable codes meeting gilbert-varshamov bound for low rates. we demonstrate a probabilistic construction of binary linear codes meeting the gv bound (with overwhelming probability) for rates up to about 10-4 together with polynomial time algorithms to perform encoding and decoding up to half the distance. the only previous result of this type (for rates up to about 0.02) suffered from sub-exponential time decoding [3].
maximum-likelihood decoding of reed-solomon codes is np-hard. maximum-likelihood decoding is one of the central problems in coding theory. it has been known for over 25 years that maximum-likelihood decoding of general linear codes is np-hard. nevertheless, it was so far unknown whether maximum-likelihood decoding remains hard for any specific family of codes with nontrivial algebraic structure. in this paper, we prove that maximum-likelihood decoding is np-hard for the family of reed-solomon codes. we moreover show that maximum-likelihood decoding of reed-solomon codes remains hard even with unlimited preprocessing, thereby strengthening a result of bruck and naor.
parametric optimization of sequence alignment. the optimal alignment or the weighted minimum edit distance between two dna or amino acid sequences for a given set of weights is computed by classical dynamic programming techniques, and is widely used in molecular biology. however, in dna and amino acid sequences there is considerable disagreement about how to weight matches, mismatches, insertions/deletions (indels) and gaps. parametric sequence alignment is the problem of computing the optimal valued alignment between two sequences as a function of variable weights for matches, mismatches, spaces and gaps. the goal is to partition the parameter space into regions (which are necessarily convex) such that in each region one alignment is optimal throughout and such that the regions are maximal for this property. in this paper we are primarily concerned with the structure of this convex decomposition, and secondarily with the complexity of computing the decomposition. the most striking results are the following: for the special case where only matches, mismatches and spaces are counted, and where spaces are counted throughout the alignment, we show that the decomposition is surprisingly simple: all regions are infinite; there are at most n2/3 regions; the lines that bound the regions are all of the form &bgr; = c+(c + 0.5)&agr;; and the entire decomposition can be found in o(knm) time, where k is the actual number of regions and n < m are the lengths of the two strings. these results were found while implementing a large software package to do parametric sequence analysis, and in turn have led to faster algorithms for those tasks.
inserting an edge into a planar graph. computing a crossing minimum drawing of a given planar graph g augmented by an additional edge e in which all crossings involve e, has been a long standing open problem in graph drawing. alternatively, the problem can be stated as finding a planar combinatorial embedding of a planar graph g in which the given edge e can be inserted with the minimum number of crossings. many problems concerned with the optimization over the set of all combinatorial embeddings of a planar graph turned out to be np-hard. surprisingly, we found a conceptually simple linear time algorithm based on spqr trees, which is able to find a crossing minimum solution.
the prize-collecting generalized steiner tree problem via a new approach of primal-dual schema. in this paper we study the prize-collecting version of the generalized steiner tree problem. to the best of our knowledge, there is no general combinatorial technique in approximation algorithms developed to study the prize-collecting versions of various problems. these problems are studied on a case by case basis by bienstock et al. [5] by applying an lp-rounding technique which is not a combinatorial approach. the main contribution of this paper is to introduce a general combinatorial approach towards solving these problems through novel primal-dual schema (without any need to solve an lp). we fuse the primal-dual schema with farkas lemma to obtain a combinatorial 3-approximation algorithm for the prize-collecting generalized steiner tree problem. our work also inspires a combinatorial algorithm [19] for solving a special case of kelly's problem [22] of pricing edges.we also consider the k-forest problem, a generalization of k-mst and k-steiner tree, and we show that in spite of these problems for which there are constant factor approximation algorithms, the k-forest problem is much harder to approximate. in particular, obtaining an approximation factor better than o(n1/6-&epsilon;) for k-forest requires substantially new ideas including improving the approximation factor o(n1/3-&epsilon;) for the notorious densest k-subgraph problem. we note that k-forest and prize-collecting version of generalized steiner tree are closely related to each other, since the latter is the lagrangian relaxation of the former.
improved lower and upper bounds for universal tsp in planar metrics. a universal tsp tour of a metric space is a total ordering of the points of the space such that for any finite subset, the tour which visits these points in the given order is not too much longer than the optimal tour. there is a vast literature on the tsp problem, and universal tsp tours have been studied since the 1980's when bartholdi and platzman [29] introduced the spacefilling curve heuristic for the euclidean tsp problem and conjectured that there exists a constant-competitive universal tsp tour based on this heuristic. here, we settle this conjecture negatively by proving an &omega; (6&radic;log n/log log n) lower bound for universal tsp tours of the n &times; n grid; this is the first known example of a family of finite metrics with no constant-competitive universal tour.generalizing from the n &times; n grid to arbitrary weighted planar graph metrics, and more generally h-minor-free metrics, we improve the best known upper bound for universal tours of such metrics from o(log4 n/ log log n) to o(log2 n).
oblivious routing on node-capacitated and directed graphs. oblivious routing algorithms for general undirected networks were introduced by r&auml;cke [17], and this work has led to many subsequent improvements and applications. comparatively little is known about oblivious routing in general directed networks, or even in undirected networks with node capacities.we present the first non-trivial upper bounds for both these cases, providing algorithms for k-commodity oblivious routing problems with competitive ratio o(&radic;klog(n)) for undirected node-capacitated graphs and o(&radic;kn1/4log(n)) for directed graphs. in the special case that all commodities have a common source or sink, our upper bound becomes o(&radic;nlog(n)) in both cases, matching the lower bound up to a factor of log(n). the lower bound (which first appeared in [6]) is obtained on a graph with very high degree. we show that in fact the degree of a graph is a crucial parameter for node-capacitated oblivious routing in undirected graphs, by providing an o( polylog(n))competitive oblivious routing scheme for graphs of degree. for the directed case, however, we show that the lower bound of &omega;(&radic;n) still holds in low-degree graphs.finally, we settle an open question about routing problems in which all commodities share a common source or sink. we show that even in this simplified scenario there are networks in which no oblivious routing algorithm can achieve a competitive ratio better than &omega;(log n).
new lower bounds for oblivious routing in undirected graphs. oblivious routing algorithms for general undirected networks were introduced by r&auml;cke, and this work has led to many subsequent improvements and applications. r&auml;cke showed that there is an oblivious routing algorithm with polylogarithmic competitive ratio (with respect to edge congestion) for any undirected graph. however, there are directed networks for which the competitive ratio is in &omega;(&radic;n).to cope with this inherent hardness in general directed networks, the concept of oblivious routing with demands chosen randomly from a known demand distribution was introduced recently. under this new model, o(log2 n)-competitiveness with high probability is possible in general directed graphs.however, it remained an open problem whether or not the competitive ratio, under this new model, could also be significantly improved in undirected graphs. in this paper, we rule out this possibility by providing a lower bound of &omega;(log n/log log n) for the multicommodity case and &omega;(&radic;logn) for the single-sink case for oblivious routing in a random demand model.we also introduce a natural candidate model for evaluating the throughput of an oblivious routing scheme which subsumes all suggested models for the throughput of oblivious routing considered so far. in this general model, we first prove a lower bound &omega;(log n/log log n) for the competitive ratio of any oblivious routing scheme. interestingly, the graphs that we consider for the lower bound in this case are expanders, for which we also obtain a lower bound &omega;(log n/log log n) on the competitive ratio of congestion based oblivious routing with adversarial demands.
finding large sticks and potatoes in polygons. we study a class of optimization problems in polygons that seek to compute the "largest" subset of a prescribed type, e.g., a longest line segment ("stick") or a maximum-area triangle or convex body ("potato"). exact polynomial-time algorithms are known for some of these problems, but their time bounds are high (e.g., o(n7) for the largest convex polygon in a simple n-gon). we devise efficient approximation algorithms for these problems. in particular, we give near-linear time algorithms for a (1 - &isin;)-approximation of the biggest stick, an o(1)-approximation of the maximum-area convex body, and a (1 - &isin;)-approximation of the maximum-area fat triangle or rectangle. in addition, we give efficient methods for computing large ellipses inside a polygon (whose vertices are a dense sampling of a closed smooth curve). our algorithms include both deterministic and randomized methods, one of which has been implemented (for computing large area ellipses in a well sampled closed smooth curve).
on algorithms for efficient data migration. the data migration problem is the problem of computing an efficient plan for moving data stored on devices in a network from one configuration to another. load balancing or changing usage patterns could necessitate such a rearrangement of data. in this paper, we consider the case where the objects are fixed-size and the network is complete. the direct migration problem is closely related to edge-coloring. however, because there are space constraints on the devices, the problem is more complex. our main results are polynomial time algorithms for finding a near-optimal migration plan in the presence of space constraints when a certain number of additional nodes is available as temporary storage, and a 3/2-approximation for the case where data must be migrated directly to its destination.
finding subsets maximizing minimum structures. we consider the problem of finding a set of k vertices in a graph that are in some sense remote. stated more formally, given a graph g and an integer k, find a set p of k vertices for which the total weight of a minimum structure on p is maximized. in particular, we are interested in three problems of this type, where the structure to be minimized is a spanning tree ({\sc remote-mst}), steiner tree, or traveling salesperson tour.we study a natural greedy algorithm that simultaneously approximates all three problems on metric graphs. for instance, its performance ratio for {\sc remote-mst} is exactly 4, while this problem is np-hard to approximate within a factor of less than 2. we also give a better approximation for graphs induced by euclidean points in the plane, present an exact algorithm for graphs whose distances correspond to shortest-path distances in a tree, and prove hardness and approximability results for general graphs.
lower bounds for on-line graph coloring. an algorithm for vertex-coloring graphs is said to be online if each vertex is irrevocably assigned a color before any later vertices are considered. we show that such algorithms are inherently ineffective. the performance ratio of any such algorithm can be no better than &ohgr;(n/log2 n), even for randomized algorithms against oblivious adversary. we also show that various means of relaxing the constraints of the on-line model do not reduce these lower bounds. the features include presenting the input in blocks of log2 n vertices, recoloring any fraction of the vertices, presorting vertices according to degree, and disclosing the adversary's previous coloring.
improved approximation algorithms for the vertex cover problem in graphs and hypergraphs. we obtain improved algorithms for finding small vertex covers in bounded degree graphs and hypergraphs. we use semidefinite programming to relax the problems and introduce new} rounding techniques for these relaxations. on graphs with maximum degree at most $\delta$, the algorithm achieves a performance ratio of $2-(1-o(1))\frac{2 \ln \ln \delta}{\ln \delta}$ for large $\delta$, which improves the previously known ratio of $2-\frac{\log \delta + o(1)}{\delta}$ obtained by halld{órsson and radhakrishnan. using similar techniques, we also present improved approximations for the vertex cover problem in hypergraphs. for k-uniform hypergraphs with n vertices, we achieve a ratio of $k-(1-o(1))\frac{k\ln \ln n}{\ln n}$ for large n, and for k-uniform hypergraphs with maximum degree at most $\delta$ the algorithm achieves a ratio of $k-(1-o(1))\frac{k(k-1)\ln \ln \delta}{\ln \delta}$ for large $\delta$. these results considerably improve the previous best ratio of $k(1-c/\delta^\frac{1}{k-1})$ for bounded degree k-uniform hypergraphs, and $k(1-c/n^\frac{k-1}{k})$ for general k-uniform hypergraphs, both obtained by krivelevich. using similar techniques, we also obtain an approximation algorithm for the weighted independent set problem, matching a recent result of halldorsson.
integrality ratio for group steiner trees and directed steiner trees. we present an &omega;(log2k) lower bound on the integrality ratio of the flow-based relaxation for the group steiner tree problem, where k denotes the number of groups; this holds even for input graphs that are hierarchically well-separated trees, introduced by bartal [symp. foundations of computer science, pp. 184--193, 1996], in which case this lower bound is tight. this relaxation appears to be the only one that have been studied for the problem, as well as for its generalization, the directed steiner tree problem. for the latter problem, our results imply an &omega;(log2n/(log logn)2) integrality ratio, where n is the number of vertices in the graph. for both problems, this is the first known lower bound on the integrality ratio that is superlogarithmic in the input size. we also show algorithmically that the integrality ratio for group steiner tree is much better for certain families of instances, which helps pinpoint the types of instances that appear to be most difficult to approximate.
max cut in cubic graphs. we present an improved semidefinite programming based approximation algorithm for the max cut problem in graphs of maximum degree at most 3. the approximation ratio of the new algorithm is at least 0.9326. this improves, and also somewhat simplifies, a result of feige, karpinski and langberg. we also observe that results of hopkins and staton and of bondy and locke yield a simple combinatorial 4/5-approximation algorithm for the problem. finally, we present a combinatorial 22/27-approximation algorithm for the max cut problem for regular cubic graphs.
coloring k-colorable graphs using smaller palettes. we obtain the following new coloring results: a 3-colorable graph on n vertices with maximum degree &dgr; can be colored, in polynomial time, using &ogr;((&dgr; log &dgr;)1/3 &middot;log n) colors. this slightly improves an &ogr;((&dgr;1/3 log&frac12; &dgr;) &middot; log n) bound given by karger, motwani and sudan. more generally, k-colorable graphs with maximum degree &dgr; can be colored, in polynomial time, using &ogr;((&dgr;1-2/k log1/k &dgr;) &middot; log n) colors. a 4-colorable graph on n vertices can be colored, in polynomial time, using &ogr;(n7/19) colors. this improves an &ogr;(n2/5) bound given again by karger, motwani and sudan. more generally, k-colorable graphs on n-vertices can be colored, in polynomial time, using &ogr;(n&agr;k) colors, where &agr;5 = 97/207, &agr;6 = 43/79, &agr;7 = 1391/2315, &agr;8 = 175/271, &hellip; the first result is obtained by a slightly more refined probabilistic analysis of the semidefinite programming based coloring algorithm of karger, motwani and sudan. the second result is obtained by combining the coloring algorithm of karger, motwani and sudan, the combinatorial coloring algorithms of blum and an extension of a technique of alon and kahale (which is based on the karger, motwani and sudan algorithm) for finding relatively large independent sets in graphs that are guaranteed to have very large independent sets. the extension of the alon and kahale result may be of independent interest.
combinatorial approximation algorithms for the maximum directed cut problem. we describe several combinatorial algorithms for the maximum directed cut problem. among our results is a simple linear time 9/20-approximation algorithm for the problem, and a somewhat slower &frac12;-approximation algorithm that uses a bipartite matching routine. no better combinatorial approximation algorithms are known even for the easier maximum cut problem for undirected graphs. our algorithms do not use linear programming, nor semidefinite programming. they are based on the observation that the maximum directed cut problem is equivalent to the problem of finding a maximum independent set in the line graph of the input graph, and that the linear programming relaxation of the problem is equivalent to the problem of finding a maximum fractional independent set of that line graph. the maximum fractional independent set problem can be easily reduced to a bipartite matching problem. as a consequence of this relation, we also get that the maximum directed cut problem for bipartite digraphs can be solved in polynomial time.
computing minimal spanning subgraphs in linear time. let p be a property of undirected graphs. we consider the following problem: given a graph g that has property p, find a minimal spanning subgraph of g with property p. we describe two related algorithms for this problem and prove their correctness under some rather weak assumptions about p. we devise a general technique for analyzing the worst-case behavior of these algorithms. by applying the technique to 2-edge-connectivity and biconnectivity, we obtain an &ohgr;(m + n log n) lower bound on the worst-case running time of the algorithms for these two properties, thus settling open questions posed earlier with regard to these properties. we then describe refinements of the basic algorithms that yield the first linear-time algorithms for finding a minimal 2-edge-connected spanning subgraph and a minimal biconnected spanning subgraph of a graph.
parallel integer sorting is more efficient than parallel comparison sorting on exclusive write prams. we present a significant improvement for parallel integer sorting. on the erew (exclusive read exclusive write) pram our algorithm sorts n integers in the range {0,1, . . . ,m-1 } in time o(log n) with $o(n \sqrt{\frac{\log n}{k}})$ operations using word length $k \log (m+n)$, where $1 \leq k \leq \log n$. in this paper we present the following four variants of our algorithm.\noindent (1) the first variant sorts integers in $\{ 0, 1, \ldots, m-1\}$ in time o(log n) and in linear space with o(n) operations using word length log m log n. (2) the second variant sorts integers in {0, 1, . . , n-1} in time o(log n) and in linear space with $o(n\sqrt{\log n})$ operations using word length log n. (3) the third variant sorts integers in {0, 1, . . . , m-1} in time o(log3/2 n) and in linear space with $o(n\sqrt{\log n})$ operations using word length log (m+n). (4) the fourth variant sorts integers in {0, 1, . . . ,m-1} in time o(log n) and space $o(nm^\epsilon )$ with $o(n\sqrt{\log n})$ operations using word length log (m+n).our algorithms can then be generalized to the situation where the word length is k log (m+n), $1 \leq k \leq \log n$.
on the distributed complexity of computing maximal matchings. we show that maximal matchings can be computed deterministically in o(log4 n) rounds in the synchronous, message-passing model of computation. this is one of the very few cases known of a nontrivial graph structure, and the only "classical" one, which can be computed distributively in polylogarithmic time without recourse to randomization.
a faster algorithm for finding the minimum cut in a graph. we consider the problem of finding the minimum capacity cut in a network g with n nodes. this problem has applications to network reliability and survivability and is useful in subroutines for other network optimization problems. one can use a maximum flow problem to find a minimum cut separating a designated source node s from a designated sink node t, and by varying the sink node one can find a minimum cut in g as a sequence of at most 2n - 2 maximum flow problems. we then show how to reduce the running time of these 2n - 2 maximum flow algorithms to the running time for solving a single maximum flow problem. the resulting running time is o(nm log n2/m) for finding the minimum cut in either a directed or undirected network. the algorithm also determines the arc connectivity of either a directed or undirected network in o(nm) steps.
online point location in planar arrangements and its applications. recently, har-peled [17] presented a new randomized technique for online construction of the zone of a curve in a planar arrangement of arcs. in this paper: we present several applications of this technique, which yield improved solutions to a variety of problems. these applications include: (i) an efficient mechanism for performing online point location queries in an arrangement of arcs; (ii) an efficient algorithm for computing an approximation to the minimum-weight steiner-tree of a set of points, where the weight is the number of intersections between the tree edges and a given collection of arcs; (iii) a subquadratic algorithm for cutting a set of pseudo-parabolas into pseudo-segments; (iv) an algorithm for cutting a set of line segments (`rods') in 3-space so as to eliminate all cycles in the vertical depth order; and (v) a near-optimal algorithm for reporting all bichromatic intersections between a set r of red arcs and a set b of blue arcs, where the unions of the arcs in each set are both connected.
how fast is the k-means method? we present polynomial upper and lower bounds on the number of iterations performed by the k-means method (a.k.a. lloyd's method) for k-means clustering. our upper bounds are polynomial in the number of points, number of clusters, and the spread of the point set. we also present a lower bound, showing that in the worst case the k-means heuristic needs to perform &omega;(n) iterations, for n points on the real line and two centers. surprisingly, the spread of the point set in this construction is polynomial. this is the first construction showing that the k-means heuristic requires more than a polylogarithmic number of iterations. furthermore, we present two alternative algorithms, with guaranteed performance, which are simple variants of the k-means method.
unknotting is in am cup co-am. hass, lagarias, and pippenger analyzed the computational complexity of various decision problems in knot theory. they proved that the problem whether a given knot is unknotting is in np, and conjectured that the problem is contained in np&cap;co-np. agol, hass, and thurston proved that the problem called manifoldgenus, which is a general problem of unknotting, is np-complete. we construct an interactive proof system for knotting, and prove that the problem is contained in ip(2). consequently, unknotting is contained in am &cap; co-am. if unknotting is np-complete, then &sigma;2p = &pi;2p.
an optimal (expected time) algorithm for minimizing lab costs in dna sequencing. the final step for obtaining very accurate dna sequence data is known as "finishing." most steps of dna sequencing are highly automated, but it is only recently that researchers have looked at automating the finishing step. our perspective is to look at automated finishing as an optimization problem, with the goal to minimize lab costs.we give new algorithms for solving this problem. we look at a model of the problem for which previous researchers gave an o(n4) algorithm (where n is the length of the dna measured in reads). we give an algorithm that runs in o(n2⅓) worst case time. we then show that the algorithm runs in o(n) expected time, if we make an assumption, accepted by many molecular biologists, about randomness in the input data.
deterministic network coding by matrix completion. we present a new deterministic algorithm to construct network codes for multicast problems, a particular class of network information ow problems. our algorithm easily generalizes to several variants of multicast problems. our approach is based on a new algorithm for maximum-rank completion of mixed matrices---taking a matrix whose entries are a mixture of numeric values and symbolic variables, and assigning values to the variables so as to maximize the resulting matrix rank. our algorithm is faster than existing deterministic algorithms and can operate over a smaller field.
the complexity of matrix completion. given a matrix whose entries are a mixture of numeric values and symbolic variables, the matrix completion problem is to assign values to the variables so as to maximize the resulting matrix rank. this problem has deep connections to computational complexity and numerous important algorithmic applications. determining the complexity of this problem is a fundamental open question in computational complexity. under different settings of parameters, the problem is variously in p, in rp, or np-hard. we shed new light on this landscape by demonstrating a new region of np-hard scenarios. as a special case, we obtain the first known hardness result for matrices in which each variable appears only twice.another particular scenario that we consider is the simultaneous matrix completion problem, where one must simultaneously maximize the rank for several matrices that share variables. this problem has important applications in the field of network coding. recent work has given a simple, greedy, deterministic algorithm for this problem, assuming that the algorithm works over a sufficiently large field. we show an exact threshold for the field size required to find a simultaneous completion efficiently. this result implies that, surprisingly, the simple greedy algorithm is optimal: finding a simultaneous completion over any smaller field is np-hard.
variable length path coupling. we present a new technique for constructing and analyzing couplings to bound the convergence rate of finite markov chains. our main theorem is a generalization of the path coupling theorem of bubley and dyer, allowing the defining partial couplings to have length determined by a random stopping time. unlike the original path coupling theorem, our version can produce multi-step (non-markovian) couplings. using our variable length path coupling theorem, we improve the upper bound on the mixing time of the glauber dynamics for randomly sampling colorings.
coupling with the stationary distribution and improved sampling for colorings and independent sets. we present an improved coupling technique for analyzing the mixing time of markov chains. using our technique, we simplify and extend previous results for sampling colorings and independent sets. our approach uses properties of the stationary distribution to avoid worst-case configurations which arise in the traditional approach.as an application, we show that for k/&delta; > 1.764, the glauber dynamics on k-colorings of a graph on n vertices with maximum degree &delta; converges in o(n log n) steps, assuming &delta; = &omega;(log n) and that the graph is triangle-free. previously, girth &ge; 5 was needed.as a second application, we give a polynomial-time algorithm for sampling weighted independent sets from the gibbs distribution of the hard-core lattice gas model at fugacity &lambda; < (1 - &epsilon;)e/&delta;, on a regular graph g on n vertices of degree &delta; = &omega;(log n) and girth &ge; 6. the best known algorithm for general graphs currently assumes &lambda; < 2/(&delta; - 2).
network design for information networks. we define a new class of network design problems motivated by designing information networks. in our model, the cost of transporting flow for a set of users (or servicing them by a facility) depends on the amount of information requested by the set of users. we assume that the aggregation cost follows economies of scale, that is, the incremental cost of a new user is less if the set of users already served is larger. naturally, information requested by some sets of users might aggregate better than that of others, so our cost is now a function of the actual set of users. not just their total demand.we provide constant-factor approximation algorithms to two important problems in this general model. in the group facility location problem, each user needs information about a resource. and the cost is a linear function of the number of resources involved (instead of the number of clients served). the dependent maybecast problem extends the karger-minkoff maybecast model to probabilities with limited correlation and also contains the 2-stage stochastic optimization problem as a special case. we also give an o(ln n)-approximation algorithm for the single sink information network design problem.we show that the stochastic steiner tree problem can be approximated by dependent maybecast, and using this we obtain an o(1)-approximation algorithm for the k-stage stochastic steiner tree problem for any fixed k. this is the first approximation algorithm for multi-stage stochastic optimization. our algorithm allows scenarios to have different inflation factors, and works for any distribution provided that we can sample the distribution.
polynomial time recognition of p4-structure. a p4 is a set of four vertices of a graph that induces a chordless path; the p4-structure of a graph is the set of all p4's. va&scaron;ek chv&aacute;tal asked if there is a polynomial time algorithm to determine whether an arbitrary four-uniform hypergraph is the p4-structure of some graph. the answer is yes; we present such an algorithm.
a categorization theorem on suffix arrays with applications to space efficient text indexes. in this paper, we design succinct index structures for a text string t of n binary symbols to support efficient searching of a pattern p of length m. motivated by the fact that the standard representation of suffix arrays uses n lg n bits which is more than the theoretical minimum, we present a theorem that characterizes a permutation as the suffix array of a binary string. based on the theorem, we design a succinct representation of suffix arrays of binary strings that uses n + o(n) bits, which is the theoretical minimum plus a lower order term, and answers existential and cardinality queries in o(m) time without storing the raw text. with 2n+o(n) bits, we can list pattern occurrences in o(m + occ lg n) time in the general case, and for long patterns, when m = &omega;(lg1+&isin; n), we answer such listing queries in o(m + occ) time. we also present another implementation that uses o(n) bits and supports pattern searching in o(m + occ lg&lambda; n) time for any fixed &lambda; such that 0 < &lambda; < 1. more results and trade-offs are reported in the paper.
edge coloring planar graphs with two outerplanar subgraphs. the standard problem of edge coloring a graph with k colors is equivalent to partitioning the edge set of the graph into k matchings. here edge coloring is generalized by replacing matchings with outerplanar graphs. we give a polynomial-time algorithm that edge colors any planar graph with two outerplanar subgraphs. two is clearly minimal for the class of planar graphs. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
scheduling multicasts on unit-capacity trees and meshes. this paper studies the multicast routing and admission control problem on unit-capacity tree and mesh topologies in the throughput model. the problem is a generalization of the edge-disjoint paths problem and is np-hard both on trees and meshes. we study both the offline and the online version of the problem: in the offline setting, we give the first constant-factor approximation algorithm for trees, and an o((log log n)2)-factor approximation algorithm for meshes. in the online setting, we give the first polylogarithmic competitive online algorithm for tree and mesh topologies. no polylogarithmiccompetitive algorithm is possible on general network topologies (lower bounds for on-line graph problems with application to on-line circuits and optical routing, in: proceedings of the 28th acm symposium on theory of computing, 1996, pp. 531-540) and there exists a polylogarithmic lower bound on the competitive ratio of any online algorithm on tree topologies (making commitments in the face of uncertainity: how to pick a winner almost every time, in: proceedings of the 28th annual acm symposium on theory of computing, 1996, pp. 519-530). we prove the same lower bound for meshes.
simplified kinetic connectivity for rectangles and hypercubes. we consider the problem of maintaining connected components in a set of moving objects using the kinetic data structure (kds) framework. we assume that the motion of each object can be specified by a low-degree algebraic trajectory; this trajectory, however, can be modified in an on-line fashion. while the objects move continuously, their connectivity changes at discrete times. a straightforward dynamic graph approach for maintaining connectivity of n objects has three shortcomings: the graph can have &ohgr;(n2) edges, the update bounds are amortized, and the algorithm is very complicated. our first result shows that the connectivity for a set of n moving hypercubes can be maintained using a very simple, easy to determine graph with &ogr;(n) edges. but this graph still requires a general-purpose dynamic graph scheme for connectivity maintenance. our main result is a simplified connectivity data structure for moving rectangles in the plane. for this special but important case, we are able to overcome all three shortcomings mentioned above: our graph has &ogr;(n) edges; our data structure supports updates in &ogr;(log2 n) worst-case time; and the algorithm and data structures are quite a bit simpler than those based on a general dynamic graph scheme.
binary space partitions for 3d subdivisions. we consider the following question: given a subdivision of space into n convex polyhedral cells, what is the worst-case complexity of a binary space partition (bsp) for the subdivision? we show that if the subdivision is rectangular and axis-aligned, then the worstcase complexity of an axis-aligned bsp is &omega;(n4/3) and o(n&alpha; log2 n), where &alpha; = 1 + log2(4/3 ) = 1.4150375 .... by contrast, it is known that the bsp of a collection of n rectangular cells not forming a subdivision has worstcase complexity &theta;(n3/2). we also show that the worstcase complexity of a bsp for a general convex polyhedral subdivision of total complexity o(n) is &omega;(n3/2).
directed graphs requiring large numbers of shortcuts. a conjecture by thorup is that the diameter of a directed graph with n vertices and m edges can be reduced to (log n)o(1) by adding o(m) edges [3]. we give a counterexample to this conjecture. we construct a graph g requiring the addition of &omega;(mn 1/17) edges to reduce its diameter below &theta;(n1/17). by extending the construction to higher dimensions, we construct graphs with n1+&epsilon; edges that require the addition of &omega;(n2--&epsilon;) edges to reduce their diameter. these constructions yield time-space tradeoffs in lower bounds for transitive closure queries in a certain computational model.
a note on the nearest neighbor in growth-restricted metrics. in this paper, we give results relevant to sequential and distributed dynamic data structures for finding nearest neighbors in growth-restricted metrics. our sequential data structure uses linear space, and requires o(log n) queries in expecation and o(log n) queries for lookups with high probability. this improves the results of karger and ruhl [4], whose data structure uses o(n log n) space with comparable expected time bounds. this also improves on the time bound of a load-balanced version of algorithm (for dynamic networks) presented in [3].our algorithm was inspired by the object location data structure developed by plaxton, rajaraman and richa [6], and is similar in structure to the algorithm of krauthgamer and lee [5]. it is significantly different that of karger and ruhl [4].a distributed version of the algorithm presented here is in use as a part of tapestry [3, 8], a peer-to-peer object location system based on [6].
symmetric drawings of triconnected planar graphs. symmetry is one of the most important aesthetic criteria in graph drawing because it reveals structure in the graph. to draw graphs symmetrically, we need two steps. the first step is to find appropriate automorphisms. the second step is to draw the graph to display the automorphisms. our aim in this paper is to construct maximally symmetric straight-line drawings of triconnected planar graphs in linear time. previously known algorithms run in quadratic time. we show that an algorithm of fontet can be used to find an embedding in the plane with the maximum number of symmetries, and present a new algorithm for finding a straight line drawing that achieves that maximum. both algorithms run in linear time.
geometric permutations of high dimensional spheres. we prove the maximum number of geometric permutations, induced by line transversals to a set of n pairwise disjoint congruent spheres in rd with d &gne; 3, is no more than 4 when n is sufficiently large, achieving the best known upper bound for this problem. we also prove the maximum number of geometric permutations of a set of n noncongruent spheres of bounded radius ratio in rd, d &gne; 3, is at most 2[&radic;2m]+1, where m is the ratio or the largest radius and the smallest radius. our result settles a conjecture in combinatorial geometry.
on efficient unsuccessful search. this paper introduces a general technique for speeding up unsuccessful search using very little extra space (2 bits per key). this technique is applicable to many data structures including linear lists, and search trees. for linear lists we get on-line algorithms for processing a sequence of successful and unsuccessful searches which are competitive with strong off-line algorithms. in a virtual memory environment our self-adjusting algorithm for multi-way search trees is competitive with an optimal static multi-way tree and will often outperform the static tree.
optimal planar point location. given a fixed distribution of point location queries among the regions of a triangulation of the plane, a data structure is presented that achieves, within constant multiplicative factors, the entropy bound on the expected point location query time.
alternatives to splay trees with o(log n) worst-case access times. splay trees are a self adjusting form of search tree that supports access operations in &ogr;(log n) amortized time. splay trees also have several amazing distribution sensitive properties, the strongest two of which are the working set theorem and the dynamic finger theorem. however, these two theorems are shown to poorly bound the performance of splay trees on some simple access sequences. the unified conjecture is presented, which subsumes the working set theorem and dynamic finger theorem, and accurately bounds the performance of splay trees over some classes of sequences where the existing theorems' bounds are not tight. while the unified conjecture for splay trees is unproven, a new data structure, the unified structure, is presented where the unified conjecture does hold. this structure also has a worst case of &ogr;(log n) per operation, in contrast to the &ogr;(n) worst case runtime of splay trees. a second data structure, the working set structure, is introduced. the working set structure has the same performance attributed to splay trees through the working set theorem, except the runtime is worst case per operation rather than amortized.
approximating vertex cover on dense graphs. although many problems in max-snp admit a ptas for dense graphs, that is not the case for vertex cover, which is max-snp hard even for dense graphs. this paper presents a randomized approximation algorithm for vertex cover on dense graphs, i.e., graphs whose average degree d is &omega;(n). (i) our algorithm improves the best-known bound for the approximation factor by karpinski and zelikovsky. for example, our bound is 2/1 + d/2&delta; for dense graphs such that |e| &le; &delta;(n - &delta;) where &delta; is the maximum degree. the improvement is especially large when d &ap; &delta;; if d &ge; 2/3&delta; for instance, our bound is at most 1.5 while the previous bound approaches to 2.0 as n/&delta; increases. (ii) it achieves the same factor for a wider range of graphs, i.e., for the graphs whose &delta; is &omega;(n log log n/log n). (iii) it is probably optimal in the sense that if we can achieve a better approximation factor by &delta; > 0 for the above range of graphs, then we can achieve a factor of 2 - &delta; for general graphs.
on the costs and benefits of procrastination: approximation algorithms for stochastic combinatorial optimization problems. combinatorial optimization is often used to "plan ahead," purchasing and allocating resources for demands that are not precisely known at the time of solution. this advance planning may be done because resources become very expensive to purchase or difficult to allocate at the last minute when the demands are known. in this work we study the tradeoffs involved in making some purchase/allocation decisions early to reduce cost while deferring others at greater expense to take advantage of additional, late-arriving information. we consider a number of combinatorial optimization problems in which the problem instance is uncertain---modeled by a probability distribution---and in which solution elements can be purchased cheaply now or at greater expense after the distribution is sampled. we show how to approximately optimize the choice of what to purchase in advance and what to defer.
marriage, honesty, and stability. many centralized two-sided markets form a matching between participants by running a stable marriage algorithm. it is a well-known fact that no matching mechanism based on a stable marriage algorithm can guarantee truthfulness as a dominant strategy for participants. however, as we will show in this paper, in a probabilistic setting where the preference lists of one side of the market are composed of only a constant (independent of the the size of the market) number of entries, each drawn from an arbitrary distribution, the number of participants that have more than one stable partner is vanishingly small. this proves (and generalizes) a conjecture of roth and peranson [23]. as a corollary of this result, we show that, with high probability, the truthful strategy is the best response for a given player when the other players are truthful. we also analyze equilibria of the deferred acceptance stable marriage game. we show that the game with complete information has an equilibrium in which a (1 - o(1)) fraction of the strategies are truthful in expectation. in the more realistic setting of a game of incomplete information, we will show that the set of truthful strategies form a (1 + o(1))-approximate bayesian-nash equilibrium. our results have implications in many practical settings and were inspired by the work of roth and peranson [23] on the national residency matching program.
limitations of cross-monotonic cost sharing schemes. a cost-sharing scheme is a set of rules defining how to share the cost of a service (often computed by solving a combinatorial optimization problem) amongs serviced customers. a cost-sharing scheme is cross-monotonic if it satisfies the property that everyone is better off when the set of people who receive the service expands. in this article, we develop a novel technique for proving upper bounds on the budget-balance factor of cross-monotonic cost-sharing schemes or the worst-case ratio of recovered cost to total cost. we apply this technique to games defined, based on several combinatorial optimization problems, including the problems of edge cover, vertex cover, set cover, and metric facility location and, in each case, derive tight or nearly-tight bounds. in particular, we show that for the facility location game, there is no cross-monotonic cost-sharing scheme that recovers more than a third of the total cost. this result, together with a recent 1/3-budget-balanced cross-monotonic cost-sharing scheme of p&aacute;l and tardos &lsqb;2003&rsqb; closes the gap for the facility location game. for the vertex cover and set cover games, we show that no cross-monotonic cost-sharing scheme can recover more than a o(n&minus;1/3) and o(1/n) fraction of the total cost, respectively. finally, we study the implications of our results on the existence of group-strategyproof mechanisms. we show that every group-strategyproof mechanism corresponds to a cost-sharing scheme that satisfies a condition weaker than cross-monotonicity. using this, we prove that group-strategyproof mechanisms satisfying additional properties give rise to cross-monotonic cost-sharing schemes and therefore our upper bounds hold.
explicit constructions of selectors and related combinatorial structures, with applications. in this paper we present explicit constructions of several combinatorial objects: selectors [cgr00] and selective families [cggpr00], pseudo-random generators for proof systems [abrw00] and fixed waking schedules [gpp00]. as a result, we obtain almost optimal deterministic protocols for broadcasting in unknown directed radio networks [cgr00] and wake-up problem [gpp00]. we also show application of selectors (and its variants) to explicit construction of test sets for coin-weighting problems [dh00]. the parameters of our constructions come close to the best known non-constructive bounds. the constructions are achieved using a common technique, which could be of use for other problems.
better algorithms for high-dimensional proximity problems via asymmetric embeddings. in this paper we give several results based on randomized embeddings of l2 into l&infin;(or "l&infin;-like") spaces. our first result is a (1 + &epsilon;)-distortion asymmetric embedding of n points in l2 into l&infin; with polylog(n) dimension, for any 1 + &epsilon;. this gives the first known o(1)- approximate nearest neighbor algorithm with fast query time and almost polynomial space for a product of euclidean norms, a common generalization of both l2 and l&infin; norms. our embedding also clarifies the relative complexity of approximate nearest neighbor in l2 and l&infin; spaces.our second result in a (1 + &epsilon;)-approximate algorithm for the diameter of n points in ld2, running in time &otilde;(dn1+l/(1+&epsilon;)2); the algorithm is fully dynamic. this improves several previous algorithms for this problem (see table 1 for more information).
approximate nearest neighbor under edit distance via product metrics. we present a data structure for the approximate nearest neighbor problem under edit metric (which is defined as the minimum number of insertions, deletions and character substitutions needed to transform one string into another). for any l &ge; 1 and a set of n strings of length d, the data structure reports a 3l-approximate nearest neighbor for any given query string q in o(d) time. the space requirement of this data structure is roughly o(nd1/(l+1)), i.e., strongly subexponential. to our knowledge, this is the first data structure for this problem with both o(n) query time and storage subexponential in d.
approximate congruence in nearly linear time. the problem of geometric point set matching has been studied extensively in the domain of computational geometry, and has many applications in areas such as computer vision, computational chemistry, and pattern recognition. one of the commonly used metrics is the bottleneck distance, which for two point sets p and q is the minimum over all one-to-one mappings f : p → q of maxp∈pd(p,f(p)), where d is the euclidean distance. much effort has gone into developing efficient algorithms for minimising the bottleneck distance between two point sets under groups of transformations. however, the algorithms that have thus far been developed suffer from running times that are large polynomials in the size of the input, even for approximate formulations of the problem.in this paper we define a point set similarity measure that includes both the bottleneck distance and the hausdorff distance as special cases. this measure relaxes the condition that the mapping must be one-to-one, but guarantees that only a few points are mapped to any point. using a novel application of hall's theorem to reduce the geometric matching problem to a combinatorial matching problem, we present near-linear time approximation schemes for minimising this distance between two point sets in the plane under isometries; we note here that the best known algorithms for congruence under the bottleneck measure run in time õ(n2.5).we also obtain a combinatorial bound on the metric entropy of certain families of geometric objects. this result yields improved algorithms for approximate congruence, and may be of independent interest.
strongly competitive algorithms for paging with locality of reference. what is the best paging algorithm if one has partial information about the possible sequences of page requests? we give a partial answer to this question, by presenting the analysis of strongly competitive paging algorithms in the access graph model. this model restricts page requests so that they conform to a notion of locality of reference, given by an arbitrary access graph. we first consider optimal algorithms for undirected access graphs. borodin et al. [2] define an algorithm, called far, and proved that it is within a logarithmic factor of the optimal. we prove that far is in fact strongly competitive, i.e. within a constant factor of the optimum. for directed access graphs, we present an algorithm that is strongly competitive on all structured program graphs&mdash;graphs modeling the request sequences of structured programs.
probabilistic analysis for scheduling with conflicts. in this paper, we consider scheduling jobs that may be competing for mutually exclusive resources. we model the conflicts between jobs with a conflict graph, so that all concurrently running jobs must form an independent set in the graph. our goal is to bound the maximum response time of any job in the system. we adopt a discrete model of time and assume that each job requires one time unit to be completed once it is started. it has been previously shown [s. irani, v. leung, scheduling with conflicts, and applications to traffic signal control, in: proceedings of the seventh annual acm-siam symposium on discrete algorithms, siam, 1996] that the best competitive ratio achievable by any online algorithm is @w(n), where n is the number of nodes in the graph. as a result, we study scheduling with conflicts under probabilistic assumptions about the input. each node i has a value p"i such that a job arrives at node i in any given time unit with probability p"i. arrivals at different nodes and during different time periods are independent. under reasonable assumptions on the value for the p"i's, we are able to obtain a bounded competitive ratio for an arbitrary conflict graph. in addition, if the conflict graph is a perfect graph, we give an algorithm whose competitive ratio converges to 1.
on-line algorithms for the dynamic traveling repair problem. we consider the dynamic traveling repair problem in which requests with deadlines arrive through time on points in a metric space. servers move from point to point at constant speed. the goal is to plan the motion of servers so that the maximum number of requests are met by their deadline. we consider a restricted version of the problem in which there is a single server and the length of time between the arrival of a request and its deadline is constant. we give upper bounds for the competitive ratio of two very natural algorithms as well as several lower bounds for any deterministic algorithm. most of the results in this paper are expressed as a function of β, the diameter of the metric space. in particular, we prove that the upper bound given for one of the two algorithms is within a constant factor of the best possible competitive ratio.
algorithms for power savings. this paper examines two different mechanisms for saving power in battery-operated embedded systems. the first is that the system can be placed in a sleep state if it is idle. however, a fixed amount of energy is required to bring the system back into an active state in which it can resume work. the second way in which power savings can be achieved is by varying the speed at which jobs are run. we utilize a power consumption curve p(s). which indicates the power consumption level given a particular speed. we assume that p(s) and p(s)/s are convex. the problem is to schedule arriving jobs in a way that minimizes total energy use and so that each job is completed after its arrival time and before its deadline. although each problem has been considered separately, this is the first theoretical analysis of systems which can use both mechanisms. we give an off line algorithm which is within a factor of three of the optimal algorithm. we also give an online algorithm with a constant competitive ratio.
rank-maximal matchings. suppose that each member of a set a of applicants ranks a subset of a set p of posts in an order of preference, possibly involving ties. a matching is a set of (applicant, post) pairs such that each applicant and each post appears in at most one pair. a greedy matching is one in which the maximum possible number of applicants are matched to their first choice post, and subject to that condition, the maximum possible number are matched to their second choice post, and so on. this is a relevant concept in any practical matching situation and it was first studied by irving [8].we define the bipartite graph g = (a u p,ε), where ε consists of all pairs (a, p) such that post p appears in the preference list of applicant a. each edge (a, p) has a rank i, which means that post p is an ith choice for applicant a. the traditional solution of computing a greedy matching in g would be to use the hungarian algorithm to compute a maximum weight matching by assigning a suitably steeply decreasing sequence of weights to the edges. this would result in an algorithm with worst case running time rn(m + n log n) and the space requirement &theta;(rm), where n is the number of vertices, m is the number of edges and r is the largest rank of an edge.here, we describe two algorithms to compute a greedy matching that improve upon this algorithm. we give a combinatorial algorithm with running time o(min(n + c,c&radic;n)m), where c &le; r is the maximal rank of an edge used in a greedy matching. this algorithm works in phases and uses the maximum cardinality matching algorithm. we also give an o(cnm) algorithm that tackles the problem of large edge weights introduced by the hungarian algorithm. this algorithm uses scaling and works in phases. the space requirement of both these algorithms is o(m).
randomized pursuit-evasion with limited visibility. we study the following pursuit-evasion game: one or more hunters are seeking to capture an evading rabbit on a graph. at each round, the rabbit tries to gather information about the l ocation of the hunters but it can see them only if they are located on adjacent nodes. we show that two hunters suffice for catching rabbits with limited visibility with high probability. we distinguish between reactive rabbits who who move only when the hunter is visible and general rabbits can employ more sophisticated strategies. we present polynomial time algorithms that decide whether a graph g is hunter-win, that is, if a single hunter can capture a rabbit of either kind on g.
the phase transition in random horn satisfiability and its algorithmic implications. let c > 0 be a constant, and φ be a random horn formula with n variables and m = c . 2n clauses, chosen uniformly at random (with repetition) from the set of all nonempty horn clauses in the given variables. by analyzing pur, a natural implementation of positive unit resolution, we show that limn→∞ pr(φ is satisfiable) = 1 - f(e-c), where f(x) = (1 - x)(1 - x2)(1 - x4) (1 - x8) .... our method also yields as a byproduct an average-case analysis of this algorithm.
a fully combinatorial algorithm for submodular function minimization. this paper presents a strongly polynomial algorithm for submodular function minimization using only additions, subtractions, comparisons, and oracle calls for function values.
packing steiner trees. the steiner packing problem is to find the maximum number of edge-disjoint subgraphs of a given graph g that connect a given set of required points s. this problem is motivated by practical applications in vlsi- layout and broadcasting, as well as theoretical reasons. in this paper, we study this problem and present an algorithm with an asymptotic approximation factor of &verbar;s&verbar;/4. this gives a sufficient condition for the existence of k edge-disjoint steiner trees in a graph in terms of the edge-connectivity of the graph. we will show that this condition is the best possible if the number of terminals is 3. at the end, we consider the fractional version of this problem, and observe that it can be reduced to the minimum steiner tree problem via the ellipsoid algorithm.
a primal-dual schema based approximation algorithm for the element connectivity problem. the element connectivity problem falls in the category of survivable network design problems-it is intermediate to the versions that ask for edge-disjoint and vertex-disjoint paths. the edge version is by now well understood from the view-point of approximation algorithms [williamson et al., combinatorica 15 (1995) 435-454; goemans et al., in: soda '94, 223-232; jain, combinatorica 21 (2001) 39-60], but very little is known about the vertex version. in our problem, vertices are partitioned into two sets: terminals and nonterminals. only edges and nonterminals can fail--we refer to them as elements--and only pairs of terminals have connectivity requirements, specifying the number of element-disjoint paths required. our algorithm achieves an approximation guarantee of factor 2hk, where k is the largest requirement and hn = 1 + ½ +... + 1/n. besides providing possible insights for solving the vertex-disjoint paths version, the element connectivity problem is of independent interest, since it models a realistic situation.
equilibria for economies with production: constant-returns technologies and production planning constraints. we consider the computation of equilibria in two economic models that generalize the exchange model by including production. in the constant returns model, each producer has a convex, constant-returns-to-scale, technology. in particular, this means that if the technology can output a certain quantity of a good using as input certain quantities of other goods, then scaling all these quantities by a common, non-negative, number also results in a technologically feasible plan. the technology also accomodates the no-free-lunch property, which says that it is not possible to produce something from nothing. at a given price, the producer picks a technologically feasible plan that maximizes her profit. associated with each consumer is an initial endowment of goods and a utility function that describes her preferences between various bundles of goods. at a given price, the consumer sells her initial endowment, thus obtaining a certain income, and demands the bundle of goods maximizing her utility among all bundles that she can afford at the given price with her income.
market equilibria for homothetic, quasi-concave utilities and economies of scale in production. eisenberg and gale (1959) gave a convex program for computing market equilibrium for fisher's model for linear utility functions, and eisenberg (1961) generalized this to concave homogeneous functions of degree one. we further generalize to:1. homothetic, quasi-concave utilities. this also helps extend eisenberg's result to concave homogeneous functions of arbitrary degree.2. we introduce the notion of a trading cone which enables us to compute market equilibrium in the presence of economies of scale in production provided differential pricing is allowed. applications to network pricing are provided.
an asymptotic approximation algorithm for 3d-strip packing. we present an asymptotic (2 + &epsilon;)-approximation algorithm for the 3d-strip packing problem, for any &epsilon; > 0. in the 3d-strip packing problem the input is a set l = {b1, b2,. . ., bn} of 3-dimensional boxes. each box bi has width, length, and height at most 1. the problem is to pack the boxes into a 3-dimensional bin b of width 1, length 1 and minimum height, so that the boxes do not overlap. we consider here only orthogonal packings without rotations; this means that the boxes are packed so that their faces are parallel to the faces of the bin, and rotations are not allowed. this algorithm improves on the previously best algorithm of miyazawa and wakabayashi which has asymptotic performance ratio of 2.64. our algorithm can be easily modified to a (4 + &epsilon;)-approximation algorithm for the 3d-bin packing problem.
on rectangle packing: maximizing benefits. we consider the following rectangle packing problem: given a set of rectangles, each of which is associated with a profit, we are requested to pack a subset of the rectangles into a bigger rectangle to maximize the total profit of rectangles packed. the rectangles may not overlap and may or may not be rotated. this problem is strongly np-hard even for packing squares with identical profits. a simple (3 + ε)-approximation algorithm is presented. we further improve the algorithm by showing a worst-case ratio of at most 5/2 + ε. finally we devise a (2 + ε)-approximation algorithm. a number of restricted cases are also considered.
algorithms for combining rooted triplets into a galled phylogenetic network. this paper considers the problem of determining whether a given set t of rooted triplets can be merged without conflicts into a galled phylogenetic network, and if so, constructing such a network. when the input t is dense, we solve the problem in o(|t|) time, which is optimal since the size of the input is &theta;(|t|). in comparison, the previously fastest algorithm for this problem runs in o(|t|2) time. next, we prove that the problem becomes np-hard if extended to non-dense inputs, even for the special case of simple phylogenetic networks. we also show that for every positive integer n, there exists some set t of rooted triplets on n leaves such that any galled network can be consistent with at most 0.4883&middot;|t| of the rooted triplets in t. on the other hand, we provide a polynomial-time approximation algorithm that always outputs a galled network consistent with at least a factor of 5/12 (>0.4166) of the rooted triplets in t.
performance study of phylogenetic methods: (unweighted) quartet methods and neighbor-joining. we present the results of a large-scale experimental study of quartet-based methods (quartet cleaning and puzzling) for phylogeny reconstruction. our experiments include a broad range of problem sizes and evolutionary rates, and were carefully designed to yield statistically robust results despite the size of the sample space. we measure outcomes in terms of numbers of edges of the true tree correctly inferred by each method (true positives). our results indicate that these quartet-based methods are much less accurate than the simple and efficient method of neighbor-joining, particularly for data composed of short to medium length sequences. we support our experimental findings by theoretical results that suggest that quartet-cleaning methods are unlikely to yield accurate trees with less than exponentially long sequences. we suggest that a proposed reconstruction method should first be compared to the neighbor-joining method and further studied only if it offers a demonstrable practical advantage.
a polynomial time recognition algorithm for probe interval graphs. probe interval graphs were introduced to model a problem arising in a form of dna sequencing. this paper presents an &ogr;(n2) algorithm for recognizing probe interval graphs. this is the first polynomial time recognition algorithm for this class.
a 5/4-approximation algorithm for minimum 2-edge-connectivity. a 5/4-approximation algorithm is presented for the minimum cardinality 2-edge-connected spanning subgraph problem in undirected graphs. this improves the previous best approximation ratio of 4/3. it is shown that our ratio is tight with respect to current lower bounds, and any further improvement is possible only if new lower bounds are discovered.
hiding cliques for cryptographic security. we demonstrate how a well studied combinatorial optimization problem may be used as a new cryptographic primitive. the problem in question is that of finding a "large" clique in a random graph. while the largest clique in a random graph with n vertices and edge probability p is very likely to be of size about 2 \log_{1/p}{n}, it is widely conjectured that no polynomial-time algorithm exists which finds a clique of size \geq (1 + \epsilon)\log_{1/p}n with significant probability for any constant \epsilon > 0. we present a very simple method of exploiting this conjecture by ``hiding'' large cliques in random graphs. in particular, we show that if the conjecture is true, then when a large clique&mdash;of size, say, (1 + 2 \epsilon) \log_{1/p}{n}&mdash;is randomly inserted (``hidden'') in a random graph, finding a clique of size \geq (1 + \epsilon)\log_{1/p}{n} remains hard. our analysis also covers the case of high edge probabilities which allows us to insert cliques of size up to n^{1/4-\epsilon} ( \epsilon>0). our result suggests several cryptographic applications, such as a simple one-way function.
a deterministic subexponential algorithm for solving parity games. the existence of polynomial-time algorithms for the solution of parity games is a major open problem. the fastest known algorithms for the problem are randomized algorithms that run in subexponential time. these algorithms are all ultimately based on the randomized subexponential simplex algorithms of kalai and of matou&scaron;ek, sharir, and welzl. randomness seems to play an essential role in these algorithms. we use a completely different, and elementary, approach to obtain a deterministic subexponential algorithm for the solution of parity games. the new algorithm, like the existing randomized subexponential algorithms, uses only polynomial space, and it is almost as fast as the randomized subexponential algorithms mentioned above.
efficient pattern-matching with don't cares. we present a randomized algorithm for the string matching with don't cares problem. based on the simple fingerprint method of karp and rabin for ordinary string matching [4], our algorithm runs in time o(n log m) for a text of length n and a pattern of length m and is simpler and slightly faster than the previous algorithms [3, 5, 1].
fast approximation algorithm for minimum cost multicommodity flow. minimum-cost multicommodity flow problem is one of the classical optimization problems that arises in a variety of contexts. applications range from finding optimal ways to route information through communication networks to vlsi layout. in this paper, we describe an efficient deterministic approximation algorithm, which given that there exists a multicommodity flow of cost $b$ that satisfies all the demands, produces a flow of cost at most $(1+\delta)b$ that satisfies $(1-\epsilon)$-fraction of each demand. for constant $\delta$ and $\epsilon$, our algorithm runs in $o^*(kmn^2)$ time, which is an improvement over the previously fastest (deterministic) approximation algorithm for this problem due to plotkin, shmoys, and tardos, that runs in $o^*(k^2m^2)$ time.
routing and admission control in general topology networks with poisson arrivals. emerging high speed networks will carry traffic for services such as video-on-demand and video teleconferencing -- that require resource reservation along the path on which the traffic is sent. high bandwidth-delay product of these networks prevents circuit rerouting, i.e. once a circuit is routed on a certain path, the bandwidth taken by this circuit remains unavailable for the duration (holding time) of this circuit. as a result, such networks will need effective routing and admission control strategies. recently developed online routing and admission control strategies have logarithmic competitive ratios with respect to the admission ratio (the fraction of admitted circuits). such guarantees on performance are rather weak in the most interesting case where the rejection ratio of the optimum algorithm is very small or even 0. unfortunately, these guarantees can not be improved in the context of the considered models, making it impossible to use these models to identify algorithms that are going to perform well in practice. in this paper we develop routing and admission control strategies for a more realistic model, where the requests for virtual circuits between any two points arrive according to a poisson process and where the circuit holding times are exponentially distributed. our model is close to the one that was developed to analyse and tune the (currently used) strategies for managing traffic in long-distance telephone networks. we strengthen this model by assuming that the rates of the poisson processes (the ``traffic matrix'''') are unknown to the algorithm and are chosen by the adversary. our strategy is competitive with respect to the expected rejection ratio. more precisely, it achieves expected rejection ratio of at most r+epsilon, where r is the optimum expected rejection ratio. the expectations are taken over the distribution of the request sequences, and epsilon=sqrt(r log n), where r is the maximum fraction of an edge bandwidth that can be requested by a single circuit.
selection with monotone comparison cost. we consider the problem of selecting the rth-smallest element from a list of n elements under a model where the comparisons may have different costs depending on the elements being compared. this model was introduced by [3] and is realistic in the context of comparisons between complex objects. an important special case of this general cost model is one where the comparison costs are monotone in the sizes of the elements being compared. this monotone cost model covers most "natural" cost models that arise and the selection problem turns out to be the most challenging one among the usual problems for comparison-based algorithms. we present an o(log2 n)-competitive algorithm for selection under the monotone cost model. this is in contrast to an &omega;(n) lower bound that is known for arbitrary comparison costs. we also consider selection under a special case of monotone costs --- the min model where the cost of comparing two elements is the minimum of the sizes. we give a randomized o(1)-competitive algorithm for the min model.
computing the local consensus of trees. the inference of consensus from a set of evolutionary trees is a fundamental problem in a number of fields such as biology and historical linguistics, and many models for inferring this consensus have been proposed. in this paper we present a model for deriving what we call a local consensus tree t from a set of trees ${\cal t}$. the model we propose presumes a function f, called a total local consensus function, which determines for every triple a of species, the form that the local consensus tree should take on a. we show that all local consensus trees, when they exist, can be constructed in polynomial time and that many fundamental problems can be solved in linear time. we also consider partial local consensus functions and study optimization problems under this model. we present linear time algorithms for several variations. finally we point out that the local consensus approach ties together many previous approaches to constructing consensus trees.
reducing tile complexity for self-assembly through temperature programming. we consider the tile self-assembly model and how tile complexity can be eliminated by permitting the temperature of the self-assembly system to be adjusted throughout the assembly process. to do this, we propose novel techniques for designing tile sets that permit an arbitrary length m binary number to be encoded into a sequence of o(m) temperature changes such that the tile set uniquely assembles a supertile that precisely encodes the corresponding binary number. as an application, we show how this provides a general tile set of size o(1) that is capable of uniquely assembling essentially any n x n square, where the assembled square is determined by a temperature sequence of length o(log n) that encodes a binary description of n. this yields an important decrease in tile complexity from the required &omega;(log n/log log n) for almost all n when the temperature of the system is fixed. we further show that for almost all n, no tile system can simultaneously achieve both o(log n) temperature complexity and o(log n/log log n) tile complexity, showing that both versions of an optimal square building scheme have been discovered. this work suggests that temperature change can constitute a natural, dynamic method for providing input to self-assembly systems that is potentially superior to the current technique of designing large tile sets with specific inputs hardwired into the tileset.
on-line difference maximization. in this paper we examine problems motivated by on-line financial problems and stochastic games. in particular, we consider a sequence of entirely arbitrary distinct values arriving in random order, and must devise strategies for selecting low values followed by high values in such a way as to maximize the expected gain in rank from low values to high values.first, we consider a scenario in which only one low value and one high value may be selected. we give an optimal on-line algorithm for this scenario, and analyze it to show that, surprisingly, the expected gain is n-o(1), and so differs from the best possible off-line gain by only a constant additive term (which is, in fact, fairly small---at most 15).in a second scenario, we allow multiple nonoverlapping low/high selections, where the total gain for our algorithm is the sum of the individual pair gains. we also give an optimal on-line algorithm for this problem, where the expected gain is $n^2/8-\theta(n\log n)$. an analysis shows that the optimal expected off-line gain is $n^2/6+\theta(1)$, so the performance of our on-line algorithm is within a factor of 3/4 of the best off-line strategy.
a comparison of labeling schemes for ancestor queries. motivated by a recent application in xml search engines we study the problem of labeling the nodes of a tree (xml file) such that given the labels of two nodes one can determine whether one node is an ancestor of the other. we describe several new prefix-based labeling schemes, where an ancestor query roughly amounts to testing whether one label is a prefix of the other. we compare our new schemes to a simple interval-based scheme currently used by search engines, as well as, to schemes with the best theoretical guarantee on the maximum label length. we performed our experimental evaluation on real xml data and on some families of random trees.
randomized incremental constructions of three-dimensional convex hulls and planar voronoi diagrams, and approximate range counting. we present new algorithms for approximate range counting, where, for a specified &epsilon; > 0, we want to count the number of data points in a query range, up to relative error of &epsilon;. we first describe a general framework, adapted from cohen [10], for this task, and then specialize it to two important instances of range counting: halfspaces in r3 and disks in the plane. the technique reduces the approximate range counting problem to that of finding the minimum rank of a data object in the range, with respect to a random permutation of the input.a major technical step in our analysis, which we believe to be of independent interest, is a bound of o(n log n) on the expected complexity of the overlay of all the voronoi faces that are generated during a randomized incremental construction of the voronoi diagram of n points in the plane. the same bound holds for the expected complexity of the overlay of all the faces of the minimization diagram of the lower envelope of n planes in r3, or for the expected complexity of the overlay of all the normal (or gaussian) diagram faces of the convex hull of n points in r3, that are generated during a randomized incremental construction of the lower envelope or of the hull, respectively. all these bounds are tight in the worst case.the first bound leads to an algorithm that, for a query point x &isin; r2, efficiently retrieves the sequence of nearest neighbors of x in p, over the random insertion process. a query takes o(log n) expected time, and the expected storage size is o(n log n). similarly, the other bounds lead to an algorithm that, for a query direction &omega; &isin; s2, efficiently retrieves the sequence of the convex hull vertices that are touched by the planes with outward direction &omega; that support the convex hull during the random insertion process. again, a query takes o(log n) expected time, and the expected storage size is o(n log n). these algorithms are used as the main component in the approximate range counting technique that we present, for ranges that are halfspaces in r3 or disks in the plane.
union-find with deletions. in the classical union-find problem we maintain a partition of a universe of n elements into disjoint sets subject to the operations union and find. the operation union(a, b, c) replaces sets a and b in the partition by their union, given the name c. the operation find(x) returns the name of the set containing the element x. in this paper we revisit the union-find problem in a context where the underlying partitioned universe is not fixed. specifically, we allow a delete(x) operation which removes the element x from the set containing it. we consider both worst-case performance and amortized performance. in both settings the challenge is to dynamically keep the size of the structure representing each set proportional to the number of elements in the set which may now decrease as a result of deletions.for any fixed k, we describe a data structure that supports find and delete in o(logkn) worst-case time and union in o(k) worst-case time. this matches the best possible worst-case bounds for find and union in the classical setting. furthermore, using an incremental global rebuilding technique we obtain a reduction converting any union-find data structure to a union-find with deletions data structure. our reduction is such that the time bounds for find and union change only by a constant factor. the time it takes to delete an element x is the same as the time it takes to find the set containing x plus the time it takes to unite a singleton set with this set.in an amortized setting a classical data structure of tarjan supports a sequence of m finds and at most n unions on a universe of n elements in o(n + m&alpha;(m + n, n, log n)) time where &alpha;(m, n, l) = min{k | ak(&lfloor;m/n&rfloor;) > l} and ai(j) is ackermann's function as described in [6]. we refine the analysis of this data structure and show that in fact the cost of each find is proportional to the size of the corresponding set. specifically, we show that one can pay for a sequence of union and find operations by charging a constant to each participating element and o(&alpha;(m, n, log(l))) for a find of an element in a set of size l. we also show how keep these amortized costs for each find and each participating element while allowing deletions. the amortized cost of deleting an element from a set of l elements is the same as the amortized cost of finding the element; namely, o(&alpha;(m, n, log(l))).
faster kinetic heaps and their use in broadcast scheduling. we describe several implementations of the kinetic heap, a heap (priority queue) in which the key of each item, instead of being fixed, is a linear function of time. the kinetic heap is a simple example of a kinetic data structure of the kind considered by basch, guibas, and hershberger. kinetic heaps have many applications in computational geometry, and previous implementations were designed to address these applications. we describe an additional application, to broadcast scheduling. each of our kinetic heap implementations improves on previous implementations by being simpler or asymptotically faster for some or all applications.
faster approximation schemes for fractional multicommodity flow problems. we present fully polynomial approximation schemes for concurrent multicommodity flow problems that run in time of the minimum possible dependencies on the number of commodities k. we show that by modifying the algorithms by garg and k&ouml;nemann [1998] and fleischer [2000], we can reduce their running time on a graph with n vertices and m edges from &otilde;(&epsiv;&minus;2(m2 &plus; km)) to &otilde;(&epsiv;&minus;2m2) for an implicit representation of the output, or &otilde;(&epsiv;&minus;2(m2 &plus; kn for an explicit representation, where &otilde;(f) denotes a quantity that is o(f logo(1)m). the implicit representation consists of a set of trees rooted at sources (there can be more than one tree per source), and with sinks as their leaves, together with flow values for the flow directed from the source to the sinks in a particular tree. given this implicit representation, the approximate value of the concurrent flow is known, but if we want the explicit flow per commodity per edge, we would have to combine all these trees together, and the cost of doing so may be prohibitive. in case we want to calculate explicitly the solution flow, we modify our schemes so that they run in time polylogarithmic in nk (n is the number of nodes in the network). this is within a polylogarithmic factor of the trivial lower bound of time &omega;(nk) needed to explicitly write down a multicommodity flow of k commodities in a network of n nodes. therefore our schemes are within a polylogarithmic factor of the minimum possible dependencies of the running time on the number of commodities k.
root comparison techniques applied to computing the additively weighted voronoi diagram. this work examines algebraic techniques for comparing quadratic algebraic numbers, thus yielding methods for deciding key predicates in various geometric constructions. our motivation and main application concerns a dynamic algorithm for computing the additively weighted voronoi diagram in the plane. we propose effficient, exact, and complete methods, which are crucial for a fast and robust implementation of these predicates and the overall algorithm. our first contribution is to minimize, on the one hand, the algebraic degree of the computed quantities, thus optimizing precision and, on the other hand, the total number of arithmetic operations. we focus on the hardest predicate, which involves quadratic polynomials, and detail the corresponding algorithms, which are based on polynomial sturm sequences; ancillary tools include geometric invariants, multivariate resultants, and polynomial factorization. our last contribution is a general and efficient implementation, which has been extensively tested in order to demonstrate the practical performance of our methods and the improvements achieved over existing approaches.
static and kinetic geometric spanners with applications. it is well known that the delaunay triangulation is a spanner graph of its vertices. in this paper we show that any bounded aspect ratio triangulation in two and three dimensions is a spanner graph of its vertices as well. we extend the notion of spanner graphs to environments with obstacles and show that both the constrained delaunay triangulation and bounded aspect ratio conforming triangulations are spanners with respect to the corresponding visibility graph. we also show how to kinetize the constrained delaunay triangulation. using such time-varying triangulations we describe how to maintain sets of near neighbors for a set of moving points in both unconstrained and constrained environments. such nearest neighbor maintenance is needed in many virtual environments where nearby agents interact. finally, we show how to use the constrained delaunay triangulation in order to maintain the relative convex hull of a set of points moving inside a simple polygon.
a new constructive root bound for algebraic expressions. computing effective root bounds for constant algebraic expressions is a critical problem in the exact geometric computation approach to robust geometric programs. classical root bounds are often non-constructive. recently, various authors have proposed bounding methods which might be called constructive root bounds. for the important class of radical expressions, burnikel et al (bfms) have provided a constructive root bound which, in the division-free case, is an improvement over previously known bounds and is essentially tight. in the presence of division, their bound requires a quadratic blowup in root bit-bound compared to the division-free case. we present a new constructive root bound that avoids this quadratic blowup and which is applicable to a more general class of algebraic expressions. this leads to dramatically better performance in some computations. we also give an improved version of the degree-measure bound from mignotte and bfms. we describe our implementation in the context of the core library, and report on some experimental results.
learning markov networks: maximum bounded tree-width graphs. markov networks are a common class of graphical models used in machine learning. such models use an undirected graph to capture dependency information among random variables in a joint probability distribution. once one has chosen to use a markov network model, one aims to choose the model that &ldquo;best explains&rdquo; the data that has been observed&mdash;this model can then be used to make predictions about future data. we show that the problem of learning a maximum likelihood markov network given certain observed data can be reduced to the problem of identifying a maximum weight low-treewidth graph under a given input weight function. we give the first constant factor approximation algorithm for this problem. more precisely, for any fixed treewidth objective k, we find a treewidth-k graph with an f(k) fraction of the maximum possible weight of any treewidth-k graph.
two and higher dimensional pattern matching in optimal expected time. algorithms with optimal expected running time are presented for searching the occurrences of a two-dimensional m x m pattern p in a two-dimensional n x n text t over an alphabet of size c. the algorithms are based on placing in the text a static grid of test points, determined only by n, m, and c (not dynamically by earlier test results). using test strings read from the test points the algorithms eliminate as many potential occurrences of p as possible. the remaining potential occurrences are separately checked for actual occurrences. a suitable choice of the test point set leads to algorithms with expected running time o(n2logc m2/m2) using the uniform bernoulli model of randomness. this is shown to be optimal by a generalization of a one-dimensional lower bound result by yao. experimental results show that the algorithms are efficient in practice, too. the method is also generalized for the k mismatches problem. the resulting algorithm has expected running time o(kn2logc m2/m2), provided that $k\leq(m\lfloor m/\lceil\log_c m^2\rceil\rfloor-1)/2$.\ all algorithms need preprocessing of p which takes time and space o(m2). the text processing can be done on-line, using a rather small window. the algorithms easily generalize to d-dimensional matching for any d.
on the convergence time of a path-vector protocol. we study the running time of a particular path-vector protocol for distributively and asynchronously computing shortest paths in a network to a given target node t. we study two cases. in both, the protocol starts with each node possibly knowing some path to t, subject to conditions discussed in the paper. in the first case, the "withdrawal case," all edges incident to the target are cut. we prove that in this case, the protocol always terminates but may need exponential time to do so, if the nodes "fire" (i.e., execute) in an adversarially chosen order, even if the initial paths are shortest. if the graph is a clique, the protocol terminates in polynomial time. if, on the other hand, the nodes fire in random order, and the graph is arbitrary, then the algorithm terminates in polynomial expected time. in the second case, the "announcement case," in which new edges incident to t appear, we prove that the protocol terminates in polynomial time, regardless of the firing order.this protocol is interesting since it models the shortest-path protocol used by bgp, the interdomain routing protocol of the internet, in the absence of policy.
online topological ordering. it is shown that the problem of maintaining the topological order of the nodes of a directed acyclic graph while inserting m edges can be solved in o(min{m3/2 log n m3/3 + n2 log n}) time, an improvement over the best known result of o(mn). in addition, we analyze the complexity of the same algorithm with respect to the treewidth k of the underlying undirected graph. we show that the algorithm runs in time o(mk log2 n) for general k and that it can be implemented to run in o(n log n) time on trees, which is optimal. if the input contains cycles, the algorithm detects this.
labeling schemes for flow and connectivity. this paper studies labeling schemes for flow and connectivity functions. a flow labeling scheme using o(logn?log[^(w)])-bit labels is presented for general n-vertex graphs with maximum (integral) capacity [^(w)]. this is shown to be asymptotically optimal. for edge-connectivity, this yields a tight bound of q(log2 n) bits. a k-vertex connectivity labeling scheme is then given for general n-vertex graphs using at most 3logn bits for k = 2, 5logn bits for k = 3 and 2klogn bits for k < 3. finally, a lower bound of w(klogn) is established for k-vertex connectivity on n-vertex graphs where k is polylogarithmic in n.
max-tolerance graphs as intersection graphs: cliques, cycles, and recognition. max-tolerance graphs can be regarded as generalized interval graphs, where two intervals ii and ij only induce an edge in the corresponding graph iff they overlap for an amount of at least max{ti, tj} where ti is an individual tolerance parameter associated to each interval ii. a new geometric characterization of max-tolerance graphs as intersection graphs of isosceles right triangles, shortly called semi-squares, leverages the solution of various graph-theoretic problems in connection with max-tolerance graphs. first, we solve the maximal and maximum cliques problem. it arises naturally in dna sequence analysis where the maximal cliques might be interpreted as functional domains carrying biologically meaningful information. we prove an upper bound of o(n3) for the number of maximal cliques in max-tolerance graphs and give an efficient o(n3) algorithm for their computation. in the same vein, the semi-square representation yields a simple proof for the fact that this bound is asymptotically tight, i.e., a class of max-tolerance graphs is presented where the instances have &omega;(n3) maximal cliques. additionally, we answer an open question posed in [8] by showing that max-tolerance graphs do not contain complements of cycles cn for n > 9. by exploiting the new representation more deeply, we can go even further and prove that the recognition problem for max-tolerance graphs is np-hard.
on finding minimal 2-connected subgraphs. we present efficient parallel algorithms for the problems of finding a minimal 2-edge-connected spanning subgraph of a 2-edge-connected graph and finding a minimal biconnected spanning subgraph of a biconnected graph. the parallel algorithms for both problems run in polylog time using a linear number of pram processors. we also give sequential algorithms for these problems that run in time o(m+n log n) where n and m denote the number of vertices and edges, respectively, in the input graph.
the hidden subgroup problem and permutation group theory. we employ concepts and tools from the theory of finite permutation groups in order to analyse the hidden subgroup problem via quantum fourier sampling (qfs) for the symmetric group. we show that under very general conditions both the weak and the random-strong form (strong form with random choices of basis) of qfs fail to provide any advantage over classical exhaustive search. in particular we give a complete characterisation of polynomial size subgroups, and of primitive subgroups, that can be distinguished from the identity subgroup with the above methods. furthermore, assuming a plausible group theoretic conjecture for which we give supporting evidence, we show that weak and random-strong qfs for the symmetric group have no advantage whatsoever over classical search.
balanced allocation on graphs. it is well known that if n balls are inserted into n bins, with high probability, the bin with maximum load contains (1 + o(1)) log n/log log n balls. azar, broder, karlin, and upfal [1] showed that instead of choosing one bin, if d &ge; 2 bins are chosen at random and the ball in serted into the least loaded of the d bins, the maximum load reduces drastically to log log n/log d + o(1). in this paper, we study the two choice balls and bins process when balls are not allowed to choose any two random bins, but only bins that are connected by an edge in an underlying graph. we show that for n balls and n bins, if the graph is almost regular with degree n&epsilon;, where &epsilon; is not too small, the previous bounds on the maximum load continue to hold. precisely, the maximum load is log log n + o(1/&epsilon;) + o(1). so even if the graph has degree n&omega;(1/log log n), the maximum load is o(log log n). for general &delta;-regular graphs, we show that the maximum load is log log n + o(log n/log (&delta;/log4 n)) + o(1) and also provide an almost matching lower bound of log log n + log n/log (&delta; log n). further this does not hold for non-regular graphs even if the minimum degree is high.v&ouml;cking [29] showed that the maximum bin size with d choice load balancing can be further improved to o(log log n/d) by breaking ties to the left. this requires d random bin choices. we show that such bounds can be achieved by making only two random accesses and querying d/2 contiguous bins in each access. by grouping a sequence of n bins into 2n/d groups, each of d/2 consecutive bins, if each ball chooses two groups at random and inserts the new ball into the least-loaded bin in the lesser loaded group, then the maximum load is o(log log n/d) with high probability. furthermore, it also turns out that this partitioning into aligned groups of size d/2 is also essential in achieving this bound, that is, instead of choosing two aligned groups, if we simply choose random but possibly unaligned random sets of d/2 consecutive bins, then the maximum load jumps to &omega;(log log n/log d) even if the two sets are always chosen to be disjoint.
loss-bounded analysis for differentiated services. we consider a network providing differentiated services (diffserv) which allow network service providers to offer different levels of quality of service (qos) to different traffic streams. we focus on loss and first show that only trivial bounds could be obtained by means of traditional competitive analysis. then we introduce a new approach for estimating loss of an online policy called loss-bounded analysis. in loss-bounded analysis the loss of an online policy are bounded by the loss of an optimal offline policy plus a constant fraction of the benefit of an optimal offline policy. we derive tight upper and lower bounds for various settings of diffserv parameters using the new loss-bounded model. we believe that loss-bounded analysis is an important technique that may complement traditional competitive analysis and provide new insight and interesting results.
generating all vertices of a polyhedron is hard. we&#x00a0;show that generating all negative cycles of a weighted graph is a hard enumeration problem, in both the directed and undirected cases. more precisely, given a family of negative (directed) cycles, it is an np-complete problem to decide whether this family can be extended or there are no other negative (directed) cycles in the graph, implying that (directed) negative cycles cannot be generated in polynomial output time, unless p=np. as a corollary, we solve in the negative two well-known generating problems from linear programming: (i)&#x00a0;given an infeasible system of linear inequalities, generating all minimal infeasible subsystems is hard. yet, for generating maximal feasible subsystems the complexity remains open. (ii)&#x00a0;given a feasible system of linear inequalities, generating all vertices of the corresponding polyhedron is hard. yet, in the case of bounded polyhedra the complexity remains open. equiva lently, the complexity of generating vertices and extreme rays of polyhedra remains open.
on approximating rectangle tiling and packing. our study of tiling and packing with rectangles in two-dimensional regions is strongly motivated by applications in database mining, histogram-based estimation of query sizes, data partitioning, and motion estimation in video compression by block matching, among others. an example of the problems that we tackle is the following: given an n by n array a of positive numbers, find a tiling using at most p rectangles (that is, no two rectangles must overlap, and each array element must fall within some rectangle) that minimizes the maximum weight of any rectangle; here the "weight" of a rectangle is the sum of the array elements that fall within it. if the array a were one-dimensional, this problem could be easily solved by dynamic programming. we prove that in the two-dimensional case it is np-hard to approximate this problem to within a factor of 1.25. on the other hand, we provide a near-linear time algorithm that returns a solution at most 2.5 times the optimal. other rectangle tiling and packing problems that we study have similar properties: while it is easy to solve them optimally in one dimension, the two-dimensional versions become np-hard. we design efficient approximation algorithms for these problems.
on local search and placement of meters in networks. this work is motivated by the problem of placing pressure-meters in fluid networks. the problem is formally defined in graph-theoretic terms as follows. given a graph, find a cotree (complement of a tree) incident upon the minimum number of vertices. we show that this problem is np-hard and max snp-hard. we design an algorithm with an approximation factor of $2 + \epsilon$ for this problem for any fixed $\epsilon >0$. this approximation bound comes from the analysis of a local search heuristic, a common practical optimization technique that does not often allow formal worst-case analysis. the algorithm is made very efficient by finding restrictive definitions of the local neighborhoods to be searched. we also exhibit a polynomial time approximation scheme for this problem when the input is restricted to planar graphs.
on broadcasting in heterogenous networks. in this paper we study a well known broadcasting heuristic for heterogenous networks of workstations, called fastest node first. we show that this heuristic produces an optimal solution for minimizing the sum of all completion times, and in addition produces a 1.5 approximation for the problem of minimizing the maximum completion time. we extend these results to show that the same bounds can be obtained for the multicast operation on such heterogenous networks. in addition we show that the problem of minimizing the maximum completion time is n p-hard, which settles the complexity of this open problem.
approximating the minimum equivalent diagraph. the meg (minimum equivalent graph) problem is the following: "given a directed graph, find a smallest subset of the edges that maintains all reachability relations between nodes." this problem is np-hard; this paper gives an approximation algorithm achieving a performance guarantee of about 1.64 in polynomial time. the algorithm achieves a performance guarantee of 1.75 in the time required for transitive closure. the heart of the meg problem is the minimum scss (strongly connected spanning subgraph) problem --- the meg problem restricted to strongly connected digraphs. for the minimum scss problem, the paper gives a practical, nearly linear-time implementation achieving a performance guarantee of 1.75. the algorithm and its analysis are based on the simple idea of contracting long cycles. the analysis applies directly to $2$-\exchange, a general "local improvement" algorithm, showing that its performance guarantee is 1.75.
optimal prediction for prefetching in the worst case. response time delays caused by i/o are a major problem in many systems and database applications. prefetching and cache replacement methods are attracting renewed attention because of their success in avoiding costly i/os. prefetching can be looked upon as a type of online sequential prediction, where the predictions must be accurate as well as made in a computationally efficient way. unlike other online problems, prefetching cannot admit a competitive analysis, since the optimal offline prefetcher incurs no cost when it knows the future page requests. previous analytical work on prefetching [. vitter krishnan 1991.] [j. assoc. comput. mach., 143 (1996), pp. 771--793] consisted of modeling the user as a probabilistic markov source. in this paper, we look at the much stronger form of worst-case analysis and derive a randomized algorithm for pure prefetching. we compare our algorithm for every page request sequence with the important class of finite state prefetchers, making no assumptions as to how the sequence of page requests is generated. we prove analytically that the fault rate of our online prefetching algorithm converges almost surely for every page request sequence to the fault rate of the optimal finite state prefetcher for the sequence. this analysis model can be looked upon as a generalization of the competitive framework, in that it compares an online algorithm in a worst-case manner over all sequences with a powerful yet nonclairvoyant opponent. we simultaneously achieve the computational goal of implementing our prefetcher in optimal constant expected time per prefetched page using the optimal dynamic discrete random variate generator of [. matias matias, vitter, and ni [proc. 4th annual siam/acm symposium on discrete algorithms, austin, tx, january 1993].
minimizing migrations in fair multiprocessor scheduling of persistent tasks. suppose that we are given n persistent tasks (jobs) that need to be executed in an equitable way on m processors (machines). each machine is capable of performing one unit of work in each integral time unit and each job may be executed on at most one machine at a time. the schedule needs to specify which job is to be executed on each machine in each time window. the goal is to find a schedule that minimizes job migrations between machines while guaranteeing a fair schedule. we measure the fairness by the drift d defined as the maximum difference between the execution times accumulated by any two jobs. since jobs are persistent we measure the quality of the schedule by the ratio of the number of migrations to time windows. we show a tradeoff between the drift and the number of migrations. let n = qm + r with 0 < r < m (the problem is trivial for n &le; m and for r = 0). for any d &ge; 1, we show a schedule that achieves a migration ratio of r(m - r)/(n(q(d 1) + 1)) + o(1); namely, it asymptotically requires r(m - r) job migrations every n(q(d 1) + 1) time windows. we show how to implement the schedule efficiently. we prove that our algorithm is almost optimal by proving a lower bound of r(m r)/(nqd) on the migration ratio. we also give a more complicated schedule that matches the lower bound for an infinite number of instances. our algorithms can be extended to the dynamic case in which jobs enter and leave the system over time.
hardware-assisted computation of depth contours. given a set of points p in the plane, the location depth of a point u is the minimum number of points of p lying in a closed halfplane defined by a line through u. the set of all points in the plane having location depth at least k is called the depth contour of depth k. in this paper, we present an algorithm that makes extensive use of modern graphics architectures to compute the approximate depth contours of a set of points. the output of our algorithm presents the contours as a coloring of each point with its depth value, as opposed to computing the geometric description of the contour boundary. our algorithm performs significantly better than currently known implementations, outperforming them by at least one order of magnitude and having a strictly better asymptotic growth rate.
on distributions computable by random walks on graphs. we answer a question raised by donald e. knuth and andrew c. yao, concerning the class of polynomials on [0, 1] that can be realized as the distribution function of a random variable, whose binary expansion is the output of a finite state automaton driven by unbiased coin tosses. the polynomial distribution functions which can be obtained in this way are precisely those with rational coefficients, whose derivative has no irrational roots on [0, 1].we also show, strengthening a result of knuth and yao, that all smooth distribution functions which can be obtained by such automata are polynomials.
approximation algorithms for cycle packing problems. the cycle packing number vc(g) of a graph g is the maximum number of pairwise edge-disjoint cycles in g. computing vc(g) is an np-hard problem. we present approximation algorithms for computing vc(g) in both the undirected and directed cases. in the undirected case we analyze the modified greedy algorithm suggested in [4] and show that it has approximation ratio o(&radic;log n) where n = |v(g)|, and this is tight. this improves upon the previous o(log n) upper bound for the approximation ratio of this algorithm. in the directed case we present a &radic;n-approximation algorithm. finally, we give an o(n2/3)-approximation algorithm for the problem of finding a maximum number of edge-disjoint cycles that intersect a specified subset s of vertices. our approximation ratios are the currently best known ones and, in addition, provide bounds on the integrality gap of standard lp-relaxations to these problems.
a faster deterministic maximum flow algorithm. we describe a deterministic version of a 1990 cheriyan, hagerup, and mehlhorn randomized algorithm for computing the maximum flow on a directed graph with n nodes and m edges which runs in time o(mn + n2+&egr;, for any constant &egr;. this improves upon alon's 1989 bound of o(mn + n8/3log n) [a] and gives an o(mn) deterministic algorithm for all m > n1+&egr;. thus it extends the range of m/n for which an o(mn) algorithm is known, and matches the 1988 algorithm of goldberg and tarjan [gt] for smaller values of m/n.
scalable leader election. in the leader election problem, there are n processors of which (1 - b)n are good. the problem is to design a distributed protocol to elect a good leader from the set of all processors. in this paper, we present a scalable leader election protocol. our protocol is scalable in the sense that each good processor sends and processes a number of bits which is only polylogarithmic in n. (we assume no limit on the number of messages sent by bad processors.) for b < 1/3, our protocol elects a good leader with constant probability and ensures that a 1 - o(1) fraction of the good processors know this leader.we assume a point-to-point full information model. this is similar to the full information model, but harder in the sense that in a given round, a bad processor may send different messages to different processors, rather than having to broadcast the same message to every processor.to the best of our knowledge, we present the first leader election protocol that ensures that each good processor sends and processes a sublinear number of bits. having reduced the problem of leader election to one of informing all good processors of a bit held by 1 &minus; o(1) fraction of good processors, we conjecture that the solution to this problem is not possible within polylogarithmic message bounds.our techniques can be used to provide scalable solutions to byzantine agreement and other problems.
solving random satisfiable 3cnf formulas in expected polynomial time. we present an algorithm for solving 3sat instances. several algorithms have been proved to work whp (with high probability) for various sat distributions. however, an algorithm that works whp has a drawback. indeed for typical instances it works well, however for some rare inputs it does not provide a solution at all. alternatively, one could require that the algorithm always produce a correct answer but perform well on average. expected polynomial time formalizes this notion. we prove that for some natural distribution on 3cnf formulas, called planted 3sat, our algorithm has expected polynomial (in fact, almost linear) running time. the planted 3sat distribution is the set of satisfiable 3cnf formulas generated in the following manner. first, a truth assignment is picked uniformly at random. then, each clause satisfied by it is included in the formula with probability p. extending previous work for the planted 3sat distribution, we present, for the first time for a satisfiable sat distribution, an expected polynomial time algorithm. namely, it solves all 3sat instances, and over the planted distribution (with p = d/n2, d > 0 a sufficiently large constant) it runs in expected polynomial time. our results extend to k-sat for any constant k.
on the complexity of distance-based evolutionary tree reconstruction. we give the first tight lower bounds on the complexity of reconstructing k-ary evolutionary trees from additive distance data. we also consider the problem under dna-based distance estimation assumptions, where the accuracy of distance data depends on the length of the sequence and the distance. we give the first o(n2) algorithm to reconstruct trees in this context, and prove a trade-off between the length of the dna sequences and the number of distance queries needed to reconstruct the tree. we introduce new computational models for understanding this problem, which simplify the development of algorithms. we prove lower bounds in these models which apply to the type of techniques currently in use.
the price of being near-sighted. achieving a global goal based on local information is challenging, especially in complex and large-scale networks such as the internet or even the human brain. in this paper, we provide an almost tight classification of the possible trade-off between the amount of local information and the quality of the global solution for general covering and packing problems. specifically, we give a distributed algorithm using only small messages which obtains an (&rho;&delta;)1/k-approximation for general covering and packing problems in time o(k2), where &rho; depends on the lp's coefficients. if message size is unbounded, we present a second algorithm that achieves an o(n1/k) approximation in o(k) rounds. finally, we prove that these algorithms are close to optimal by giving a lower bound on the approximability of packing problems given that each node has to base its decision on information from its k-neighborhood.
deterministic boundary recognition and topology extraction for large sensor networks. we present a new framework for the crucial challenge of self-organization of a large sensor network. the basic scenario can be described as follows: given a large swarm of immobile sensor nodes that have been scattered in a polygonal region, such as a street network. nodes have no knowledge of size or shape of the environment or the position of other nodes. moreover, they have no way of measuring coordinates, geometric distances to other nodes, or their direction. their only way of interacting with other nodes is to send or to receive messages from any node that is within communication range. the objective is to develop algorithms and protocols that allow self-organization of the swarm into large-scale structures that reflect the structure of the street network, setting the stage for global routing, tracking and guiding algorithms.our algorithms work in two stages: boundary recognition and topology extraction. all steps are strictly deterministic, yield fast distributed algorithms, and make no assumption on the distribution of nodes in the environment, other than sufficient density.
upper and lower bounds on constructing alphabetic binary trees. this paper studies the long-standing open question of whether optimal alphabetic binary trees can be constructed in $o(n \lg n)$ time. we show that a class of techniques for finding optimal alphabetic trees which includes all current methods yielding $o(n \lg n)$-time algorithms are at least as hard as sorting in whatever model of computation is used. we also give $o(n)$-time algorithms for the case where all the input weights are within a constant factor of one another and when they are exponentially separated.
how to cut a cake almost fairly. in the cake cutting problem, n &ge; 2 players want to cut a cake into n pieces so that every player gets a "fair" share of the cake by his own measure. we describe a protocol with n - 1 cuts in which each player can enforce to get a share of at least 1/(2n - 2) of the cake. moreover we show that no protocol with n - 1 cuts can guarantee a better fraction.
preprocessing an undirected planar network to enable fast approximate distance queries. we describe a method for preprocessing a weighted planar undirected graph and representing the results of the preprocessing so as to facilitate subsequent approximate distance queries. for any 0 < &epsilon; < 1/10, a representation can be constructed so that computing an &epsilon;-approximate distance from one node to another takes o(&epsilon;-1) time, principally consisting of about 15&epsilon;-1 additions. the representation requires storage of 7.2&epsilon;-1n log2 n distances. by using compressed representation of the distances, the number of bytes required is about .5n&epsilon;-1(9 + 3 log &epsilon;-1)log2 n (at the expense of a small increase in query time).
critical chromatic number and the complexity of perfect packings in graphs. let h be any non-bipartite graph. we determine asymptotically the minimum degree of a graph g which ensures that g has a perfect h-packing. more precisely, we determine the smallest number &tau; having the following property: for every positive constant &gamma; there exists an integer n0 = n0(&gamma;, h) such that every graph g whose order n &ge;n0 is divisible by |h| and whose minimum degree is at least (&tau; + &gamma;) n contains a perfect h-packing. the value of &tau; depends on the relative sizes of the colour classes in the optimal colourings of h. the proof is algorithmic, which shows that the problem of finding a maximum h-packing is polynomially solvable for graphs g whose minimum degree is at least (&tau; + &gamma;)n. on the other hand, given any positive constant &gamma;, we show that for infinitely many (non-bipartite) graphs h the corresponding decision problem becomes np-complete if one considers input graphs g of minimum degree at least (&tau; - &gamma;)n.
multiple-source shortest paths in planar graphs. given an n-node planar graph with nonnegative edge-lengths, our algorithm takes o(n log n) time to construct a data structure that supports queries of the following form in o(log n) time: given a destination node t on the boundary of the infinite face, and given a start node s anywhere, find the s-to-t distance.
end-to-end packet-scheduling in wireless ad-hoc networks. packet-scheduling is a particular challenge in wireless networks due to interference from nearby transmissions. a distance-2 interference model serves as a useful abstraction here, and we study packet routing and scheduling under this model. the main focus of our work is the development of fully-distributed (decentralized) protocols. we present polylogarithmic/constant factor approximation algorithms for various families of disk graphs (which capture the geometric nature of wireless-signal propagation), as well as near-optimal approximation algorithms for general graphs. the packet-scheduling work by l eighton, maggs and rao (combinatorica, 1994) and a basic distributed coloring procedure, originally due to luby (j. computer and system sciences, 1993), underlie many of our algorithms. experimental work of finocchi, panconesi, and silvestri (soda 2002) showed that a natural modification of luby's algorithm leads to improved performance, and a rigorous explanation of this was left as an open question; we prove that the modified algorithm is provably better in the worst-case. finally, using simulations, we study the impact of the routing strategy and the choice of parameters on the performance of our distributed algorithm for unit disk graphs.
shape matching using edit-distance: an implementation. we report on our experience with the implementation of an algorithm for comparing shapes by computing the edit-distance between their medial axes. a shape-comparison method that is robust to various visual transformations has several applications in computer vision, including organizing and querying an image database, and object recognition. there are two components to research on this problem, mathematical formulation of the shape-comparison problem and the computational solution method. we have a clear, well-defined formulation and polynomial-time algorithms for solution. previous research has involved either ill-defined formulations or heuristic methods for solution. our starting-point for the implementation is the edit-distance algorithm of klein et al. [6]. we discuss how we altered that algorithm to handle rotation-invariance while keeping down the time and storage requirements. most important, we define costs for the edit-operations and give an algorithm for computing them. we use a database of shapes to illustrates that our approach performs intuitively in categorization and indexing tasks, and our results are better than previous approaches.
a note on the set systems used for broadcast encryption. an exclusive set system is a family of subsets of a universe with the property that every large subset may be written as the union of subsets from the family. we obtain new upper bounds on the size of such families, showing that in a universe of n elements, there is a system of 48k3 (nk)r/k in subsets with the property that every subset of the universe of size n -- r can be written as the union of k subsets in the system. such sets systems form the combinatorial foundation of many broadcast encryption schemes.
on polynomial approximation to the shortest lattice vector length. we obtain a 2&ogr;(n/&isin;) time algorithm to approximate the length of the shortest vector in an n-dimensional lattice to within a factor of n3+&isin;.
a multiple-choice secretary algorithm with applications to online auctions. in the classical secretary problem, a set s of numbers is presented to an online algorithm in random order. at any time the algorithm may stop and choose the current element, and the goal is to maximize the probability of choosing the largest element in the set. we study a variation in which the algorithm is allowed to choose k elements, and the goal is to maximize their sum. we present an algorithm whose competitive ratio is 1-o(&radic;1/k). to our knowledge, this is the first algorithm whose competitive ratio approaches 1 as k &larr; &infin;. as an application we solve an open problem in the theory of online auction mechanisms.
anytime algorithms for multi-armed bandit problems. how should a decision-maker perform repeated choices so as to optimize the average cost or benefit of those choices in the long run? this question motivates the theory of online learning, which encompasses problems such as the well-known best-expert [13, 9] and multi-armed bandit [10, 1] problems. this paper concerns a new approach to dealing with multi-armed bandit problems in which the decision-maker's strategy set is large (exponential or possibly infinite). recent theoretical progress on the analysis of algorithms for such problems (e.g. [2, 3, 8, 11, 14]) has led to improved online algorithms for problems in areas such as online routing [2], dynamic pricing mechanisms [4, 5, 12], and analysis of reputation systems in e-commerce and peer-to-peer networks [3].
conformance testing in the presence of multiple faults. conformance testing is the problem of determining if a black-box implementation i is equivalent to a specification s, where both are modeled as finite state mealy machines. the problem involves constructing a checking sequence based on the specification, which is a sequence of inputs that detects all faulty machines. traditionally conformance testing algorithms have assumed that the number of states in the implementation does not exceed that in the specification. this is because it is known that, in the absence of this assumption, the length of the checking sequence needs to be at least exponential in the number of extra states in the implementation [41]. however, this has limited the applicability of these techniques in practice where the implementation typically has many more states than the specification.in this paper we relax the constraints on the size of the implementation and investigate the existence of polynomial length checking sequences for implementations with extra states, under the promise that they either have multiple faults or no faults at all. we present randomized algorithms to construct checking sequences that catch faulty implementations with at most &delta; extra states, having at least r faults (where &delta; and r are parameters to the algorithm), and pass all correct implementations. we demonstrate the near optimality of our algorithms by presenting lower bounds for this problem. one of the main technical lemmas used in our proof is an estimate of the probability that a random walk on directed graphs will reach a large target set. we believe that this lemma will be of independent interest in the context of verifying safety properties.
authoritative sources in a hyperlinked environment. the network structure of a hyperlinked environment can be a rich source of information about the content of the environment, provided we have effective means for understanding it. we develop a set of algorithmic tools for extracting information from the link structures of such environments, and report on experiments that demonstrate their effectiveness in a variety of context on the world wide web. the central issue we address within our framework is the distillation of broad search topics, through the discovery of &ldquo;authorative&rdquo; information sources on such topics. we propose and test an algorithmic formulation of the notion of authority, based on the relationship between a set of relevant authoritative pages and the set of &ldquo;hub pages&rdquo; that join them together in the link structure. our formulation has connections to the eigenvectors of certain matrices associated with the link graph; these connections in turn motivate additional heuristrics for link-based analysis.
on binary searching with non-uniform costs. let us consider an ordered vector a[1 : n]. if the cost of testing each position is similar, then the standard binary search is the best strategy to search the vector. this is true in both average and worst case. however, if the costs are non-uniform, then the best strategy is not necessarily the standard binary search. the best algorithm to construct a strategy that minimizes the expected search cost runs in &ogr;(n3) time and requires &ogr;(n2) space. the same complexities hold for the best algorithm to construct a strategy that minimizes the worst case search cost. here, we show how to efficiently construct search strategies that are at most at a constant factor from the optimal one. these constructions take linear time and use only linear space. for the problem of minimizing the expected search cost, we present an algorithm that requires &ogr;(n) space and gives a (2 + &isin; + &ogr;(1))-approximated solution in &ogr;(n) time, for any fixed value of &isin; > 0. on the other hand, for the problem of minimizing the worst case search cost, we describe an algorithm that requires &ogr;(n) space and gives a (2 + &isin; + &ogr;(1))- approximated solution in &ogr;(n) time, for any fixed value of &isin; > 0. these two problems arise when processing a query in a distributed text database indexed by a suffix array.
isomorphism and embedding problems for infinite limits of scale-free graphs. the study of random graphs has traditionally been dominated by the closely-related models g(n, m), in which a graph is sampled from the uniform distribution on graphs with n vertices and m edges, and g(n, p), in which each of the (n/2) edges is sampled independently with probability p. recently, however, there has been considerable interest in alternate random graph models designed to more closely approximate the properties of complex real-world networks such as the web graph, the internet, and large social networks. two of the most well-studied of these are the closely related "preferential attachment" and "copying" models, in which vertices arrive one-by-one in sequence and attach at random in "rich-get-richer" fashion to d earlier vertices.here we study the infinite limits of the preferential attachment process --- namely, the asymptotic behavior of finite graphs produced by preferential attachment (brie y, pa graphs), as well as the infinite graphs obtained by continuing the process indefinitely. we are guided in part by a striking result of erd&ouml;;s and r&eacute;nyi on countable graphs produced by the infinite analogue of the g(n, p) model, showing that any two graphs produced by this model are isomorphic with probability 1; it is natural to ask whether a comparable result holds for the preferential attachment process.we find, somewhat surprisingly, that the answer depends critically on the out-degree d of the model. for d = 1 and d = 2, there exist infinite graphs r&infin;d such that a random graph generated according to the infinite preferential attachment process is isomorphic to r&infin;d with probability 1. for d &ge; 3, on the other hand, two different samples generated from the infinite preferential attachment process are non-isomorphic with positive probability. the main technical ingredients underlying this result have fundamental implications for the structure of finite pa graphs; in particular, we give a characterization of the graphs h for which the expected number of subgraph embeddings of h in an n-node pa graph remains bounded as n goes to infinity.
computation in noisy radio networks. in this paper, we examine noisy radio (broadcast) networks in which every bit transmitted has a certain probability of being flipped. each processor has some initial input bit, and the goal is to compute a function of these input bits. in this model, we show a protocol to compute any threshold function using only a linear number of transmissions.
wavelength conversion in optical networks. in many models of optical routing, we are given a set of communication paths in a network, and we must assign a wavelength to each path so that paths sharing an edge receive different wavelengths. the goal is to assign as few wavelengths as possible, in order to make as efficient use as possible of the optical bandwidth. wilfong and winkler considered the problem of placing wavelength converters in such a network: if a node of the network contains a converter, any path that passes through this node may change its wavelength. having converters at some of the nodes can reduce the number of wavelengths required for routing, down to the following natural {\em congestion bound}: even with converters, we will always need at least as many wavelengths as the maximum number of paths sharing a single edge. thus winkler and wilfong defined a set $s$ of nodes in a network to be {\em sufficient} if, placing converters at the nodes in $s$, every set of paths can be routed with a number of wavelengths equal to its congestion bound. they showed that finding a sufficient set of minimum size is np-complete. in this paper, we provide a polynomial-time algorithm to find a sufficient set for an arbitrary directed network whose size is within a factor of $2$ of minimum. for the special case of planar graphs with bi-directional edges, we obtain a polynomial-time approximation scheme. our techniques establish a connection between the problem of finding a minimum sufficient set and an interesting simultaneous generalization of the vertex cover and feedback vertex set problems in undirected graphs.
network failure detection and graph connectivity. we consider a model for monitoring the connectivity of a network subject to node or edge failures. in particular, we are concerned with detecting (ε, k)-failures: events in which an adversary deletes up to network elements (nodes or edges), after which there are two sets of nodes a and b, each at least an ε fraction of the network, that are disconnected from one another. we say that a set d of nodes is an (ε k)-detection set if, for any (ε k)-failure of the network, some two nodes in d are no longer able to communicate; in this way, d "witnesses" any such failure. recent results show that for any graph g, there is an is (ε k)-detection set of size bounded by a polynomial in k and ε, independent of the size of g.in this paper, we expose some relationships between bounds on detection sets and the edge-connectivity &lambda; and node-connectivity &kappa; of the underlying graph. specifically, we show that detection set bounds can be made considerably stronger when parameterized by these connectivity values. we show that for an adversary that can delete &kappa;&lambda; edges, there is always a detection set of size o((&kappa;/ε) log (1/ε)) which can be found by random sampling. moreover, an (ε, &lambda)-detection set of minimum size (which is at most 1/ε) can be computed in polynomial time. a crucial point is that these bounds are independent not just of the size of g but also of the value of &lambda;.extending these bounds to node failures is much more challenging. the most technically difficult result of this paper is that a random sample of o((&kappa;/ε) log (1/ε)) nodes is a detection set for adversaries that can delete a number of nodes up to &kappa;, the node-connectivity.for the case of edge-failures we use vc-dimension techniques and the cactus representation of all minimum edge-cuts of a graph; for node failures, we develop a novel approach for working with the much more complex set of all minimum node-cuts of a graph.
adaptive heuristics for binary search trees and constant linkage cost. we present lower and upper bounds on adaptive heuristics for maintaining binary search trees using a constant number of link or pointer changes for each operation (constant linkage cost (clc)). we show that no adaptive heuristic with an amortized linkage cost of o(log n) can be competitive. in particular, we show that any heuristic that performs f(n)=o(log n) promotions (rotations) amortized over each access has a competitive ratio of at least $\omega(\log n/f(n))$ against an oblivious adversary, and any heuristic that performs f(n)=o(log n) pointer changes amortized over each access has a competitive ratio of at least $\omega(\frac{\log n}{f(n)\log(\log n/f(n))})$ against an adaptive online adversary.in our investigation of upper bounds we present four adaptive heuristics: a randomized, worst-case-clc heuristic randomized two-promotion (r2p) whose expected search time is within a constant factor of the search time using an optimal tree; that is, it is statically competitive against an oblivious adversary; a randomized, expected-clc heuristic (locally optimized randomized partial splay (lorps)) that has o(log n) expected-amortized update time and is statically competitive against an oblivious adversary; a deterministic, amortized-clc heuristic (locally optimized partial splay (lops)) that has o(log n) amortized update time and is statically competitive against an adaptive adversary; a practical, randomized heuristic (randomized partial splay (rps)) that is not clc but has performance bounds comparable with those of the splay heuristic of sleator and tarjan; it is statically competitive against an adaptive adversary. the randomized heuristics use only constant extra space, whereas the deterministic heuristic uses o(n) extra space.
performance guarentee for online deadline scheduling in the presence of overload. earliest deadline first (edf) is a widely-used online algorithm for scheduling jobs with deadlines in real-time systems. yet, existing results on the performance guarantee of edf are limited to underloaded systems [6,12,14]. this paper initiates the study of edf for overloaded systems, attaining similar performance guarantees as in the underloaded setting. specifically, we show that edf with a simple form of admission control is optimal for scheduling on both uniprocessor and multiprocessors when moderately faster processors are available (our analysis actually admits a tradeoff between speed and extra processors). this is the first result attaining optimality under overload. another contribution of this paper is an improved analysis of the competitiveness for weighted deadline scheduling.
polynomial algorithms for partitioning problems on graphs with fixed clique-width (extended abstract). we consider three graph partitioning problems, both from the vertices and the edges point of view. these problems are dominating set, list-q-coloring with costs (fixed number of colors q) and coloring with non-fixed number of colors. they are all known to be np-hard in general. we show that all these problems (except edge-coloring) can be solved in polynomial time on graphs with clique-width bounded by some constant k, if the k-expression of the input graph is also given. in particular, we present the first polynomial algorithms (on these classes) for chromatic number, edge-dominating set and list-q-coloring with costs (fixed number of colors q, both vertex and edge versions). since these classes of graphs include classes like p4-sparse graphs, distance hereditary graphs and graphs with bounded treewidth, our algorithms also apply to these graphs.
girth restrictions for the 5-flow conjecture. using counting arguments, we show that every smallest counterexample to tutte's 5-flow conjecture (that every bridgeless graph has a nowhere-zero 5-flow) has girth at least nine.
distinguishing string selection problems. this paper presents a collection of string algorithms that are at the core of several biological problems such as discovering potential drug targets, creating diagnostic probes, universal primers or unbiased consensus sequences. all these problems reduce to the task of finding a pattern that, with some error, occurs in one set of strings (closest substring problem) and does not occur in another set (farthest string problem). in this paper, we break down the problem into several subproblems and prove the following results. 1. the following are all np-hard: the farthest string problem, the closest substring problem, and the closest string problem of finding a string that is close to each string in a set. 2. there is a ptas for the farthest string problem based on a linear programming relaxation technique. 3. there is a polynomial-time (4/3 + ε)-approximation algorithm for the closest string problem for any small constant ε > 0. using this algorithm, we also provide an efficient heuristic algorithm for the closest substring problem. 4. the problem of finding a string that is at least hamming distance d from as many strings in a set as possible, cannot be approximated within nε in polynomial time for some fixed constant ε unless np = p, where n is the number of strings in the set. 5. there is a polynomial-time 2-approximation for finding a string that is both the closest substring to one set, and the farthest string from another set.
a near-tight approximation lower bound and algorithm for the kidnapped robot problem. localization is a fundamental problem in robotics. the 'kidnapped robot' possesses a compass and map of its environment; it must determine its location at a minimum cost of travel distance. the problem is np-hard [6] even to minimize within factor c log n[21], where n is the number of vertices. no approximation algorithm has been known. we give a o(log3 n)-factor algorithm. the key idea is to plan travel in a 'majority-rule' map, which eliminates uncertainty and permits a link to the 1/2-group steiner (not group steiner) problem. the approximation factor is not far from optimal: we prove a c log2-&epsilon; n lower bound, assuming np &nsube; ztime(npolylog(n)), for the grid graphs commonly used in practice. we also introduce a new hypothesis equivalence decomposition of the plane, built from pairs of aspect graph duals, in order to extend the algorithm to polygonal maps.
navigating nets: simple algorithms for proximity search. we present a simple deterministic data structure for maintaining a set s of points in a general metric space, while supporting proximity search (nearest neighbor and range queries) and updates to s (insertions and deletions). our data structure consists of a sequence of progressively finer ε-nets of s, with pointers that allow us to navigate easily from one scale to the next.we analyze the worst-case complexity of this data structure in terms of the "abstract dimensionality" of the metric s. our data structure is extremely efficient for metrics of bounded dimension and is essentially optimal in a certain model of distance computation. finally, as a special case, our approach improves over one recently devised by karger and ruhl [kr02].
an optimal algorithm for checking regularity (extended abstract). we present a deterministic algorithm a that, in o(m2) time, verifies whether a given m by m bipartite graph g is regular, in the sense of szemer&eacute;di [18]. in the case in which g is not regular enough, our algorithm outputs a witness to this irregularity. algorithm a may be used as a subroutine in an algorithm that finds an &epsilon;-regular partition of a given n-vertex graph &gamma; in time o(n2). this time complexity is optimal, up to a constant factor, and improves upon the bound o(m(n)), proved by alon, duke, lefmann, r&ouml;dl, and yuster [1, 2], where m(n) = o(n2.376) is the time required to square a 0-1 matrix over the integers.our approach is elementary, except that it makes use of linear-sized expanders to accomplish a suitable form of deterministic sampling.
pattern matching in a digitized image. the continuous pattern matching problem is defined. given are two pictures, each consisting of unicolor regions; one picture is called the scene and the other the pattern. the problem is to find all occurrences of the pattern in the scene. as a step towards efficient algorithmic handling of the continuous pattern matching problem by computers, where discretized representations are involved, we give several algorithms. our strongest algorithmic result is for a one-dimensional version of the problem, where running time which is linear in the length of a digitized representation is achieved. the definitions of our problems are derived from a &ldquo;digitized-based&rdquo; approach to object recognition problems in computer vision, which is different from a common computer vision approach. the digitized based approach may lead towards further research within the discrete algorithms community on computer vision problems.
flows over time with load-dependent transit times. more than forty years ago, ford and fulkerson studied maximum s-t-flows over time (also called "dynamic" flows) in networks with fixed transit times on the arcs and a fixed time horizon. here, flow on arcs may change over time and transit times specify the amount of time it takes for flow to travel through a particular arc. ford and fulkerson proved that there always exists an optimal solution which sends flow on certain s-t-paths at a constant rate as long as there is enough time left for the flow along a path to arrive at the sink; a flow over time featuring this simple structure is called "temporally repeated."although this result does not hold for the more general and also more realistic setting where transit times depend on the current flow situation, we show that there always exists a provably good temporally repeated solution. moreover, such a solution can be determined very efficiently by only one minimum convex cost flow computation. our results rest upon a new model of flow-dependent transit times. it is based on two assumption on the pace of flow on a particular arc. first, the pace of flow on an arc is assumed to be uniform for all flow units on an arc for each point in time. second, this uniform pace is for each moment determined by the actual amount of flow on this arc. finally, we show that the resulting flow-over-time problem is strongly np-hard and cannot be approximated with arbitrary precision in polynomial time, unless p=np.
a new approach to proving upper bounds for max-2-sat. in this paper we present a new approach to proving upper bounds for the maximum 2-satisfiability problem (max-2-sat). we present a new 2k/5.5-time algorithm for max-2-sat, where k is the number of clauses in an input formula. we also obtain a 2n/6 bound, where n is the number of variables in an input formula, for a particular case of max-2-sat, where each variable appears in at most three 2-clauses. this immediately implies a 2n/6 bound, where n is the number of vertices in an input graph, for the independent set problem on 3-regular graphs. the key point of our improvement is a combined complexity measure for estimating the running time of an algorithm. by using a new complexity measure we are able to provide a much simpler proof of new upper bounds for max-2-sat than proofs of previously known bounds.
provably good moving least squares. we analyze a moving least squares (mls) interpolation scheme for reconstructing a surface from point cloud data. the input is a sufficiently dense set of sample points that lie near a closed surface f with approximate surface normals. the output is a reconstructed surface passing near the sample points. for each sample point s in the input, we define a linear point function that represents the local shape of the surface near s. these point functions are combined by a weighted average, yielding a three-dimensional function i. the reconstructed surface is implicitly defined as the zero set of i. we prove that the function i is a good approximation to the signed distance function of the sampled surface f and that the reconstructed surface is geometrically close to and isotopic to f. our sampling requirements are derived from the local feature size function used in delaunay-based surface reconstruction algorithms. our analysis can handle noisy data provided the amount of noise in the input dataset is small compared to the feature size of f.
improved bounds for the unsplittable flow problem. in this paper we consider the unsplittable flow problem (ufp): given a directed or undirected network g=(v,e) with edge capacities and a set of terminal pairs (or requests) with associated demands, find a subset of the pairs of maximum total demand for which a single flow path can be chosen for each pair so that for every edge, the sum of the demands of the paths crossing the edge does not exceed its capacity. we present a collection of new results for the ufp both in the offline (all requests are given from the beginning) and the online (requests arrive at the system one after the other) setting. a fundamental ingredient of our analysis is the introduction of a new graph parameter, the flow number, that aims to capture global communication properties of the network. with the help of the flow number we develop a general method for transforming arbitrary multicommodity flow solutions into solutions that use short paths only. this generalizes a well-known theorem of leighton and rao [j. acm 46 (6) (1999) 787-832] that applies to uniform flows only. both the parameter and the method may therefore be of independent interest.
improved lower bounds for embeddings into . we simplify and improve upon recent lower bounds on the minimum distortion of embedding certain finite metric spaces into l1. in particular, we show that for infinitely many values of n there are n-point metric spaces of negative type that require a distortion of &omega;(log log n) for such an embedding, implying the same lower bound on the integrality gap of a well-known sdp relaxation for sparsest-cut. this result builds upon and improves the recent lower bound of (log log n)1/6---o(1) due to khot and vishnoi [stoc 2005]. we also show that embedding the edit distance on {o, 1}n into l1 requires a distortion of &omega;(log n). this result simplifies and improves a very recent lower bound due to khot and naor [focs 2005].
pianos are not flat: rigid motion planning in three dimensions. consider a robot r that is either a line segment or the minkowski sum of a line segment and a 3-ball, and a set s of polyhedral obstacles with a total of n vertices in r3. we design near-optimal exact algorithms for planning the motion of r among s when r is allowed to translate and rotate. specifically, we can preprocess s in time o(n 4+&epsilon;) for any &epsilon; > 0 into a data structure that given two placements &alpha; and &beta; of r, can decide in time o(log n) whether a collision-free rigid motion of r between &alpha; and &beta; exists and if so, output such a motion in time asymptotically proportional to its complexity. furthermore, we can find in time o(n4+&epsilon;) for any &epsilon; > 0 the largest placement of a similar (translated, rotated and scaled) copy of r that does not intersect s. a number of additional stronger results are provided. our line segment motion planning algorithm improves the result of ke and o'rourke by two orders of magnitude and almost matches their lower bound, thus settling a classical motion planning problem first considered by schwartz and sharir in 1984. this implies a number of natural directions for future work concerning rigid motion planning in three dimensions.
on the overlay of envelopes in four dimensions. we show that the complexity of the overlay of two envelopes of arrangements of n semi-algebraic surfaces or surface patches of constant description complexity in four dimensions is o(n4-1/&lceil;s/2&rceil;+&epsilon;), for any &epsilon; > 0, where s is a constant related to the maximal degree of the surfaces. this is the first non-trivial (sub-quartic) bound for this problem, and for s = 1, 2 it almost matches the near-cubic lower bound. we discuss several applications of this result, including (i) an improved bound for the complexity of the region enclosed between two envelopes in four dimensions, (ii) an improved bound for the complexity of the space of all hyperplane transversals of a collection of simply-shaped convex sets in 4-space, (iii) an improved bound for the complexity of the space of all line transversals of a similar collection of sets in 3-space, and (iv) improved bounds for the complexity of the union of certain families of objects in four dimensions. the analysis technique we introduce is quite general, and has already proved useful in unrelated contexts.
maintaining significant stream statistics over sliding windows. in this paper, we introduce the significant one counting problem. let &epsilon; and &theta; be respectively some user-specified error bound and threshold. the input of the problem is a stream of bits. we need to maintain some data structure that allows us to estimate the number of 1-bits in a sliding window of size n such that whenever there are at least &theta;n 1-bits in the window, the relative error of the estimate is guaranteed to be at most &epsilon;. when &theta; 1/n, our problem becomes the basic counting problem proposed by datar et al. [acm-siam symposium on discrete algorithms (2002), pp. 635--644]. we prove that any data structure for the significant one counting problem must use at least &omega;(1/&epsilon; log2 1/&theta; + log &epsilon; &theta;n) bits of memory. we also design a data structure for the problem that matches this memory bound and supports constant query and update time. note that for fixed &theta; and &epsilon;, our data structure uses o(log n) bits of memory, while any data structure for the basic counting problem needs &omega;(log2 n) bits in the worst case.
online ascending auctions for gradually expiring items. in this paper we consider online auction mechanisms for the allocation of m items that are identical to each other except for the fact that they have different expiration times, and each item must be allocated before it expires. players arrive at different times, and wish to buy one item before their deadline. the main difficulty is that players act "selfishly" and may mis-report their values, deadlines, or arrival times. we begin by showing that the usual notion of truthfulness (where players follow a single dominant strategy) cannot be used in this case, since any (deterministic) truthful auction cannot obtain better than an m-approximation of the social welfare. therefore, instead of designing auctions in which players should follow a single strategy, we design two auctions that perform well under a wide class of selfish, "semi-myopic", strategies. for every combination of such strategies, the auction is associated with a different algorithm, and so we have a family of "semi-myopic" algorithms. we show that any algorithm in this family obtains a 3-approximation, and by this conclude that our auctions will perform well under any choice of such semi-myopic behaviors. we next turn to provide a game-theoretic justification for acting in such a semi-myopic way. we suggest a new notion of "set-nash" equilibrium, where we cannot pin-point a single best-response strategy, but rather only a set of possible best-response strategies. we show that our auctions have a set-nash equilibrium which is all semi-myopic, hence guarantees a 3-approximation. we believe that this notion is of independent interest.
a group-strategyproof mechanism for steiner forests. in this paper we design an approximately budget-balanced and group-strategyproof cost-sharing mechanism for the steiner forest game. an instance of this game consists of an undirected graph g = (v, e), non-negative costs ce for all edges e &isin; e, and a set r &sube; v x v of k terminal pairs. each terminal pair (s, t) &isin; r is associated with an agent that wishes to establish a connection between nodes s and t in the underlying network. a feasible solution is a forest f that contains an s, t-path for each connection request (s, t) &isin; r.previously, jain and vazirani [4] gave a 2-approximate budget-balanced and group-strategyproof cost-sharing mechanism for the steiner tree game --- a special case of the game considered here. such a result for steiner forest games has proved to be elusive so far, in stark contrast to the well known primal-dual (2 -- 1/k)-approximate algorithms [1, 2] for the problem.the cost-sharing method presented in this paper is 2-approximate budget-balanced and this is tight with respect to the budget-balance factor.our algorithm is an original extension of known primal-dual methods for steiner forests [1]. an interesting byproduct of the work in this paper is that our steiner forest algorithm is (2 -- 1/k)-approximate despite the fact that the forest computed by our method is usually costlier than those computed by known primal-dual algorithms. in fact the dual solution computed by our algorithm is infeasible but we can still prove that its total value is at most the cost of a minimum-cost steiner forest for the given instance.
trees and markov convexity. we give combinatorial, geometric, and probabilistic characterizations of the distortion of tree metrics into lp spaces. this requires the development of new embedding techniques, as well as a method for proving distortion lower bounds which is based on the wandering of markov chains in banach spaces, and a new metric invariant we call markov convexity. trees are thus the first non-trivial class of metric spaces for which one can give a simple and complete characterization of their distortion into a hilbert space, up to universal constants. our results also yield an efficient algorithm for constructing such embeddings.
distributions of points in the unit-square and large -gons. we consider a generalization of heilbronn's triangle problem by asking, given any integers n>=k, for the supremum @d"k(n) of the minimum area determined by the convex hull of some k of n points in the unit square [0,1]^2, where the supremum is taken over all distributions of n points in [0,1]^2. improving the lower bound @d"k(n)=@w(1/n^(^k^-^1^)^/^(^k^-^2^)) from [c. bertram-kretzberg, t. hofmeister, h. lefmann, an algorithm for heilbronn's problem, siam journal on computing 30 (2000) 383-390] and from [w.m. schmidt, on a problem of heilbronn, journal of the london mathematical society (2) 4 (1972) 545-550] for k=4, we show that @d"k(n)=@w((logn)^1^/^(^k^-^2^)/n^(^k^-^1^)^/^(^k^-^2^)) for fixed integers k>=3 as asked for in [c. bertram-kretzberg, t. hofmeister, h. lefmann, an algorithm for heilbronn's problem, siam journal on computing 30 (2000) 383-390]. moreover, we provide a deterministic polynomial time algorithm which finds n points in [0,1]^2, which achieve this lower bound on @d"k(n).
complexity classification of network information flow problems. we address the network information flow problem, in which messages available to a set of sources must be passed through a network to a set of sinks with specified demands. this differs from traditional multicommodity flow, because information can be duplicated and encoded. previous work has focused on the special case of multicasting using linear coding. in this paper, we explore the applicability of network coding to a breadth of problems and consider the greater potential of nonlinear coding techniques. our main contribution is a taxonomy of network information flow problems. we establish a three-way partition consisting of problems solvable without resorting to network coding, problems requiring network coding that are polynomial-time solvable, and problems for which obtaining a linear network coding solution is np-hard. we also demonstrate limitations of linear coding: for multicasting, nonlinear codes may employ a smaller alphabet than any linear code and, more generally, there exist solvable information flow problems that do not admit a linear solution.
on approximating the achromatic number. the achromatic number problem is to legally color the vertices of an input graph with the maximum number of colors, denoted &psgr;*, so that every two color classes share at least one edge. this problem is known to be np-hard. for general graphs we give an algorithm that approximates the achromatic number within ratio of &ogr;(n &middot;log log n/ log n). this improves over the previously known approximation ratio of &ogr;(n/&radic;log n), due to chaudhary and vishwanathan [4]. for graphs of girth at least 5 we give an algorithm with approximation ratio &ogr;(min{n1/3, &radic;&psgr;*}). this improves over an approximation ratio &ogr;(&radic;&psgr;*) = &ogr;(n3/8) for the more restricted case of graphs with girth at least 6, due to krista and lorys [13]. we also give the first hardness result for approximating the achromatic number. we show that for every fixed &isin; > 0 there in no 2 - &isin; approximation algorithm, unless p = np.
network coding: does the model need tuning? we consider the general network information flow problem, which was introduced by ahlswede et. al[1]. we show a periodicity effect: for every integer m &ge; 2, there exists an instance of the network information ow problem that admits a solution if and only if the alphabet size is a perfect mth power. building on this result, we construct an instance with o(m) messages and o(m) nodes that admits a solution if and only if the alphabet size is an enormous 2exp(&omega;(m1/3)). in other words, if we regard each message as a length-k bit string, then k must be exponential in the size of the network. for this same instance, we show that if edge capacities are slightly increased, then there is a solution with a modest alphabet size of o(2m). in light of these results, we suggest that a more appropriate model would assume that the network operates at slightly under capacity.
generating low-degree 2-spanners. a k-spanner of a connected graph g = (v,e) is a subgraph g\spr consisting of all the vertices of v and a subset of the edges, with the additional property that the distance between any two vertices in g\spr is larger than that distance in g by no more than a factor of k. this paper concerns the problem of finding a 2-spanner in a given graph, with minimum maximum degree. a randomized approximation algorithm is provided for this problem, with approximation ration of [o\tilde](d1/4).
approximation algorithms for grammar-based compression. several recently-proposed data compression algorithms are based on the idea of representing a string by a context-free grammar. most of these algorithms are known to be asymptotically optimal with respect to a stationary ergodic source and to achieve a low redundancy rate. however, such results do not reveal how effectively these algorithms exploit the grammar-model itself; that is, are the compressed strings produced as small as possible? we address this issue by analyzing the approximation ratio of several algorithms, that is, the maximum ratio between the size of the generated grammar and the smallest possible grammar over all inputs. on the negative side, we show that every polynomial-time grammar-compression algorithm has approximation ratio at least 8569/8568 unless p = np. moreover, achieving an approximation ratio of o(log n/log log n) would require progress on an algebraic problem in a well-studied area. we then upper and lower bound approximation ratios for the following four previously-proposed grammar-based compression algorithms: sequential, bisection, greedy, and lz78, each of which employs a distinct approach to compression. these results seem to indicate that there is much room to improve grammar-based compression algorithms.
complete partitions of graphs. a complete partition of a graph g is a partition of v(g) such that any two classes are connected by an edge. let cp(g) denote the maximum number of classes in a complete partition of g. this measure was defined in 1969 by gupta [18], and is known to be np-hard on several classes of graphs. we obtain the first, and essentially tight, lower and upper bounds on the approximability of this problem. we show that there is a randomized polynomial-time algorithm that given a graph g produces a complete partition of size &omega;(cp(g)/&radic;lg|v(g)|). this algorithm can be derandomized.we show that the upper bound is essentially tight: there is a constant c > 1, such that if there is a randomized polynomial-time algorithm that for all large n, when given a graph g with n vertices produces a complete partition into at least c cp(g)/&radic;lg n classes, then np &sube; rtime(no(lg lg n)). the problem of finding a complete partition of a graph is thus the first natural problem whose approximation threshold has been determined to be of the form &theta;((lg n)c) for some constant c strictly between 0 and 1.
on-line randomized call control revisited. we consider the problem of on-line call admission and routing on trees and meshes. previous work gave randomized on-line algorithms for these problems and proved that they have optimal (up to constant factors) competitive ratios. however, these algorithms can obtain very low profit with high probability. we investigate the question of devising for these problems on-line competitive algorithms that also guarantee a "good" solution with "good" probability.we give a new family of randomized algorithms with asymptotically optimal competitive ratios and "good" probability to get a profit close to the expectation. we complement these results by providing bounds on the probability of any optimally competitive randomized on-line algorithm for the problems we consider to get a profit close to the expectation. to the best of our knowledge, this is the first study of the relationship between the tail distribution and the competitive ratio of randomized on-line benefit algorithms.
analysis of a local search heuristic for facility location problems. in this paper, we study approximation algorithms for several np-hard facility location problems. we prove that a simple local search heuristic yields polynomial-time constant-factor approximation bounds for the metric versions of the uncapacitated k-median problem and the uncapacitated facility location problem. (for the k-median problem, our algorithms require a constant-factor blowup in the parameter k.) this local search heuristic was first proposed several decades ago, and has been shown to exhibit good practical performance in empirical studies. we also extend the above results to obtain constant-factor approximation bounds for the metric versions of capacitated k-median and facility location problems.
placement algorithms for hierarchical cooperative caching. consider a hierarchical network in which each node periodically issues a request for an object drawn from a fixed set of unit-sized objects. suppose further that the following conditions are satisfied: the frequency with which each node accesses each object is known; each node has a cache of known capacity; any cache can be accessed by any node; any request is satisfied by the closest node with a copy of the desired object. in such an environment, it is desirable to fill the available cach space with copies of objects in such a way that the average access cost is minimized. we provide both exact and approximate polynomial-time algorithms for this hierarchical placement problem. our exact algorithm is based on a reduction to min-cost flow, and does not appear to be practical for large problem sizes. thus we are motivated to search for a faster approximation algorithm. our main result is a simple constant-factor approximation algorithm for the hierarchical placement problem that admits an efficient distributed implementation.
property testing of data dimensionality. data dimensionality is a crucial issue in a variety of settings, where it is desirable to determine whether a data set given in a high-dimensional space adheres to a low-dimensional structure. we study this problem in the framework of property testing: given a query access to a data set s, we wish to determine whether s is low-dimensional, or whether it should be modified significantly in order to have the property. allowing a constant probability of error, we aim at algorithms whose complexity does not depend on the size of s.we present algorithms for testing the low-dimensionality of a set of vectors and for testing whether a matrix is of low rank. we then address low-dimensionality in metric spaces. for vectors in the metric space l1, we show that low-dimensionality is not testable. for l2, we show that a data set can be tested for having a low-dimensional structure, but that the property of approximately having such a structure is not testable.
locally satisfiable formulas. a cnf formula &psi; is k-satisfiable if each k clauses of &psi; can be satisfied simultaneously. let &pi;k be the largest real number such that for each k-satisfiable formula with variables xi, there are probabilities pi with the following property: if each variable xi is chosen randomly and independently to be true with the probability pi, then each clause of is satisfied with the probability at least &pi;k.we determine the numbers &pi;k and design a linear-time algorithm which given a formula either outputs that &psi; is not k-satisfiable or finds probabilities pi such that each clause &psi; of is satisfied with the probability at least &pi;k. our approach yields a robust linear-time deterministic algorithm which finds for a k-satisfiable formula a truth assignment satisfying at least the fraction of &pi;k of the clauses.a related parameter is rk which is the largest ratio such that for each k-satisfiable cnf formula with m clauses, there is a truth assignment which satisfies at least rkm clauses. it was known that &pi;k = rk for k = 1, 2, 3. we compute the ratio r4 and show &pi;4 6 = r4. we also design a linear-time algorithm which finds a truth assignment satisfying at least the fraction r4 of the clauses for 4-satisfiable formulas.
a constant approximation algorithm for the one-warehouse multi-retailer problem. deterministic inventory theory provides streamlined optimization models that attempt to capture tradeoffs in managing the flow of goods through a supply chain. we will consider a well-studied inventory model, called the one-warehouse multi-retailer problem (owmr). and give the first approximation algorithm with constant performance guarantee; more specifically, we give a 2.398-approximation algorithm. our results are based on an lp-rounding approach, and hence not only provide good algorithmic results, but show strong integrality gaps for these linear programs. furthermore, we extend this result to obtain a constant performance guarantee for a capacitated variant of this model.
approximating asymmetric maximum tsp. the asymmetric maximum travelling salesman problem, also known as the taxicab ripoff problem, is the problem of finding a maximally weighted tour in a complete asymmetric graph with non-negative weights. interesting in its own right, this problem is also motivated by such problems such as the shortest superstring problem.we propose a polynomial time approximation algorithm for the problem with a 5/8 approximation guarantee. this (1) improves upon the approximation factors of previous results and (2) presents a simpler solution to the previously fairly involved algorithms. our solution uses a simple lp formulation. previous solutions where combinatorial. we make use of the lp in a novel manner and strengthen the path-coloring method originally proposed in [13].
certifying algorithms for recognizing interval graphs and permutation graphs. a certifying algorithm for a problem is an algorithm that provides a certificate with each answer that it produces. the certificate is a piece of evidence that proves that the answer has not been compromised by a bug in the implementation. we give linear-time certifying algorithms for recognition of interval graphs and permutation graphs, and for a few other related problems. previous algorithms fail to provide supporting evidence when they claim that the input graph is not a member of the class. we show that our certificates of nonmembership can be authenticated in o(|v|) time.
the similarity metric. a new class of metrics appropriate for measuring effective similarity relations between sequences, say one type of similarity per metric, is studied. we propose a new "normalized information distance", based on the noncomputable notion of kolmogorov complexity, and show that it minorizes every metric in the class (that is, it is universal in that it discovers all effective similarities). we demonstrate that it too is a metric and takes values in [0, 1]; hence it may be called the similarity metric. this is a theory foundation for a new general practical tool. we give two distinctive applications in widely divergent areas (the experiments by necessity use just computable approximations to the target notions). first, we computationally compare whole mitochondrial genomes and infer their evolutionary history. this results in a first completely automatic computed whole mitochondrial phylogeny tree. secondly, we give fully automatically computed language tree of 52 different language based on translated versions of the "universal declaration of human rights".
between o(nm) and o(n alpha). this paper uses periodic matrix multiplication to improve the time complexities for a number of graph problems. the time for finding a clique cutset in a graph is reduced from o(nm) to o(n2.69), the time for finding an asteroidal triple is reduced to o(n2.82), and the time for finding a star cutset, a two-pair, and a dominating pair is reduced from o(nm) to o(n2.79).it is also shown that each of these problems is at least as hard as one of three basic graph problems for which the best known algorithms run in time o(nm) and o(n&alpha;).
gossip is synteny: incomplete gossip and an exact algorithm for syntenic distance. the syntenic distance between two genomes is given by the minimum number of fusions, fissions, and translocations required to transform one into the other, ignoring the order of genes within chromosomes. the problem of computing this distance is np-complete. in this paper, we give an &ogr;(2&ogr;(n log n)) algorithm to exactly compute the syntenic distance between two genomes that contain at most n chromosomes. our algorithm requires &ogr;(2&ogr;(d log d)) time when this distance is d, improving the &ogr;(2&ogr;(d2)) running time of the beat previous exact algorithm. our result is based upon a tight connection between syntenic distance and a novel generalization of the classical gossip problem. we define the incomplete gossip problem, in which there are n gossipers who each have a unique piece of initial information. they communicate by phone calls in which the participants exchange all their information, and the goal is to minimize the total number of phone calls necessary to inform each gossiper of his set of relevant gossip which he desires to learn.
the diameter of random massive graphs. many massive graphs (such as the www graph and call graphs) share certain universal characteristics which can be described by so-called the &ldquo;power law&rdquo;. here we determine the diameter of random power law graphs up to a constant factor for almost all ranges of parameters. these results show a strong evidence that the diameters of most massive graphs are about logarithm of their sizes up to a constant factor.
superiority and complexity of the spaced seeds. optimal spaced seeds were introduced by the theoretical computer science community to bioinformatics to effectively increase homology search sensitivity. they are now serving thousands of homology search queries daily. while dozens of papers have been published on optimal spaced seeds since their invention, many fundamental questions still remain unanswered. in this paper, we settle several open questions in this area. specifically, we prove that when the length of a non-uniformly spaced seed is bounded by an exponential function of the seed weight, the seed outperforms strictly the traditional consecutive seed in both (i) the average number of non-overlapping hits and (ii) the asymptotic hit probability. then, we study the computation of the hit probability of a spaced seed, solving three more open questions: (iii) hit probability computation in a uniform homologous region is np-hard and (iv) it admits a ptas; (v) the asymptotic hit probability is computable in exponential time in seed length, independent of the homologous region length.
an optimal online algorithm for packet scheduling with agreeable deadlines. an important issue in ip-based qos networks is the effective management of packets at the router level. specifically, if the arriving packets cannot all be stored in a buffer, or if the packets have deadlines by which they must be delivered, the router needs to identify the packets that should be dropped. in recent work, kesselman et al. [6] propose a model, called buffer management with bounded delay, which can be thought of as an online scheduling problem on a single machine: packets arrive at a network switch and are stored in a buffer of size b. each packet has a positive weight and a deadline, with the weight representing the value of transmitting the packet by its deadline. at each integer time step, exactly one packet can be transmitted, and the objective is to maximize the total weight of the transmitted packets. if b = &infin;, this is the online version of the scheduling problem 1| pj = 1, rj, dj |&sigma; wj uj. (we assume that rj and dj are integers.)
randomized online algorithms for minimum metric bipartite matching. we present the first poly-logarithmic competitive online algorithm for minimum metric bipartite matching. via induction and a careful use of potential functions, we show that a simple randomized greedy algorithm is competitive on a hierarchically separated tree. application of recent results on randomized embedding of metrics into trees yield the poly-logarithmic result for general metrics.
on the number of eularian orientations of a graph. we give efficient randomized schemes to sample and approximately count eulerian orientations of any eulerian graph. eulerian orientations are natural flow-like structures, and welsh has pointed out that computing their number (i)corresponds to evaluating the tutte polynomial at the point (0, &ndash;2) [8,19] and (ii) is equivalent to evaluating &ldquo;ice-type partition functions&rdquo; in statistical physics [20]. our algorithms are based on a reduction to sampling and approximately counting perfect matchings for a class of graphs for which the methods of broder [3, 10] and others [4, 6] apply. a crucial step of the reduction is the &ldquo;monotonicity lemma&rdquo; (lemma 3.3) which is of independent combinatorial interest. roughly speaking, the monotonicity lemma establishes the intuitive fact that &ldquo;increasing the number of constraints applied on a flow problem can only decrease the number of solutions&rdquo;. in turn, the proof of the lemma involves a new decomposition technique which decouples problematically overlapping structures (a recurrent obstacle in handling large combinatorial populations) and allows detailed enumeration arguments. as a byproduct, (i) we exhibit a class of graphs for which perfect and near-perfect matchings are polynomially related, and hence the permanent can be approximated, for reasons other than &ldquo;short augmenting paths&rdquo; (previously the only known approach); and (ii) we obtain a further direct sampling scheme for eulerian orientations which is faster than the one suggested by the reduction to perfect matchings. finally, with respect to our approximate counting algorithm, we give the complementary hardness result, namely, that counting exactly eulerian orientations is #p-complete, and provide some connections with eulerian tours.
on parallel complexity of integer linear programming, gcd and the iterated mod function. we study parallel computational methods for integer linear programming problem with two variables. applying several novel techniques, we prove that this problem is nc-equivalent to computing the continued fraction expansion of a rational number, that is, to computing all the intermediate remainders in the euclidean algorithm applied to two integers, plus to computing the output of an iterated modulo function, with the remainder sequence from the euclidean algorithm (that is, with the continued fraction expansion of a rational number) as its input arguments. the best previously known results are special cases of our theorem.
a time efficient delaunay refinement algorithm. in this paper we present a delaunay refinement algorithm for generating good aspect ratio and optimal size triangulations. this is the first algorithm known to have sub-quadratic running time. the algorithm is based on the extremely popular delaunay refinement algorithm of ruppert. we know of no prior refinement algorithm with an analyzed subquadratic time bound. for many natural classes of meshing problems, our time bounds are comparable to know bounds for quadtree methods.
a general approach for incremental approximation and hierarchical clustering. we present a general framework and algorithmic approach for incremental approximation algorithms. the framework handles cardinality constrained minimization problems, such as the k-median and k-mst problems. given some notion of ordering on solutions of different cardinalities k, we give solutions for all values of k such that the solutions respect the ordering and such that for any k, our solution is close in value to the value of an optimal solution of cardinality k. for instance, for the k-median problem, the notion of ordering is set inclusion and our incremental algorithm produces solutions such that any k and k', k < k', our solution of size k is a subset of our solution of size k'. we show that our framework applies to this incremental version of the k-median problem (introduced by mettu and plaxton [30]), and incremental versions of the k-mst problem, k-vertex cover problem, k-set cover problem, as well as the uncapacitated facility location problem (which is not cardinality-constrained). for these problems we either get new incremental algorithms, or improvements over what was previously known. we also show that the framework applies to hierarchical clustering problems. in particular, we give an improved algorithm for a hierarchical version of the k-median problem introduced by plaxton [31].
fast implementation of depth contours using topological sweep. the concept of location depth was introduced in statistics as a way to extend the univariate notion of ranking to a bivariate configuration of data points. it has been used successfully for robust estimation, hypothesis testing, and graphical display. these require the computation of depth regions, which form a collection of nested polygons. the center of the deepest region is called the tukey median. the only available implemented algorithms for the depth contours and the tukey median are slow, which limits their usefulness. in this paper we describe an optimal algorithm which computes all depth contours in &ogr;(n2) time and space, using topological sweep of the dual arrangement of lines. once the contours are known, the location depth of any point is computed in &ogr;(log2 n) time. we provide fast implementations of these algorithms to allow their use in everyday statistical practice.
efficient construction of unit circular-arc models. in a recent paper, dur&aacute;n, gravano, mcconnell, spinrad and tucker described an algorithm of complexity o(n2) for recognizing whether a graph g with n vertices is a unit circular-arc (uca) graph. furthermore the following open questions were posed in the above paper: (i) is it possible to construct a uca model for g in polynomial time? (ii) is it possible to construct a model, whose extremes of the arcs correspond to integers of polynomial size? (iii) if (ii) is true, could such a model be constructed in polynomial time? in the present paper, we describe a characterization of uca graphs which leads to linear time algorithms for recognizing uca graphs and constructing uca models. furthermore, we construct models whose extreme of the arcs correspond to integers of size o(n). the proposed algorithms provide positive answers to the three above questions.
density graphs and separators. we propose a class of graphs that would occur naturally in finite-element problems, and we prove a bound on separators for this class of graphs. for three-dimensional graphs, our separator bound is $o(n^{2/3})$. we also propose a simple randomized algorithm to find this separator in $o(n)$ time. such an algorithm would be used as a preprocessing step for the domain decomposition method of efficiently solving a finite-element problem on a parallel computer. this paper generalizes ``local graphs'''' of vavasis [1990] to the case of graphs with varying densities of nodes. it also generalizes aspects of miller and thurston''s [1990] ``stable graphs.''''
lower bounds on the size of selection and rank indexes. the rank index problem is the following: preprocess and store a bit string x &isin; {0,1}n on a random access machine with word size w so that rank queries "what is &sigma;ji=1 xi?" for arbitrary values of j can afterwards be easily answered. the selection index problem is the following: preprocess and store a bit string x &isin; {0,1}n so that selection queries "what is the index of the j'th 1-bit in x?" for arbitrary values of j can afterwards be easily answered. the data structure representing x should be an index structure, i.e., the n-bit string x is kept verbatim in [n/w] words and the preprocessing phase adds an r-bit index &phi;(x) with additional information contained in [r/w] words. we are interested in tradeoffs between r, the size of the index measured in bits (the redundancy of the scheme), and t, the worst case time for answering a query.
deterministic identity testing for multivariate polynomials. in this paper we present a simple deterministic algorithm for testing whether a multivariate polynomial f(x1, ..., xn) is identically zero, in time polynomial in m, n, log(d + 1) and h. here m is the number of monomials in f, d is the maximum degree of a variable in f and 2h is the least upper bound on the magnitude of the largest coefficient in f. we assume that f has integer coefficients.the main feature of our algorithm is its conceptual simplicity. the proof uses linnik's theorem which is a deep fact about distribution of primes in an arithmetic progression.
computing sequential equilibria for two-player games. koller, megiddo and von stengel showed how to efficiently compute minimax strategies for two-player extensive-form zero-sum games with imperfect information but perfect recall using linear programming and avoiding conversion to normal form. koller and pfeffer pointed out that the strategies obtained by the algorithm are not necessarily sequentially rational and that this deficiency is often problematic for the practical applications. we show how to remove this deficiency by modifying the linear programs constructed by koller, megiddo and von stengel so that pairs of strategies forming a sequential equilibrium are computed. in particular, we show that a sequential equilibrium for a two-player zero-sum game with imperfect information but perfect recall can be found in polynomial time. in addition, the equilibrium we find is normal-form perfect. our technique generalizes to general-sum games, yielding an algorithm for such games which is likely to be prove practical, even though it is not polynomial-time.
fptas for mixed-integer polynomial optimization with a fixed number of variables. we show the existence of an fptas for the problem of maximizing a non-negative polynomial over mixed-integer sets in convex polytopes, when the number of variables is fixed.
sublinear time approximate clustering. clustering is of central importance in a number of disciplines including machine learning, statistics, and data mining. this paper has two foci: (1) it describes how existing algorithms for clustering can benefit from simple sampling techniques arising from work in statistics [pol84]. (2) it motivates and introduces a new model of clustering that is in the spirit of the &ldquo;pac (probably approximately correct)&rdquo; learning model, and gives examples of efficient pac-clustering algorithms.
separation and approximation of polyhedral objects. given a family of disjoint polygons p1, p2,&hellip;, pk in the plane, and an integer parameter m, it is np-complete to decide if the pi's can be separated by a polygonal family consisting of m edges, that is, if there exist polygons r1, r2,&hellip;, rk with pairwise-disjoint boundaries such that pi *** ri and &sgr;|ri| &le; m. in three dimensions, the problem of separating even two nested convex polyhedra by a k-facet polyhedron is np-complete. many other extensions and generalizations of the polyhedral separation problem, either to families of polyhedra or to higher dimensions, are also intractable. in this paper, we present efficient approximation algorithms for constructing separating families of near-optimal size. our main results are as follows. in two dimensions, we give an o(n log n) time algorithm for constructing a separating family whose size is within a constant factor of an optimal separating family; n is the number of edges in the input family of polygons. in three dimensions, we can separate a convex polyhedron from a nonconvex polyhedron with a convex polyhedral surface whose facet-complexity is o(log n, times the optimal, where n = |p|+|q| is the complexity of the input polyhedra. our algorithm runs in o(n4) time, but improves to o (n3) time if the two polyhedra are nested and convex. our algorithm for separating a convex polyhedron from a nonconvex polyhedron extends to higher dimensions. in d dimensions, for d &ge; 4, the facet-complexity of the approximation polyhedron is o(d log n) times the optimal, and the algorithm runs in o(nd+1)time. finally, we also obtain results on separating sets of points, a family of convex polyhedra, and separation by non-polyhedral surfaces, such as spherical patches.
a polynomial algorithm to find an independent set of maximum weight in a fork-free graph. the class of fork-free graphs is an extension of claw-free graphs and their subclass of line graphs. the first polynomial-time solution to the maximum weight independent set problem in the class of line graphs, which is equivalent to the maximum matching problem in general graphs, has been proposed by edmonds in 1965 and then extended to the entire class of claw-free graphs by minty in 1980. recently, alekseev proposed a solution for the larger class of fork-free graphs, but only for the unweighted version of the problem, i.e. finding an independent set of maximum cardinality. in the present paper, we describe the first polynomial-time algorithm to solve the problem for weighted fork-free graphs.
an optimal bloom filter replacement. this paper considers space-efficient data structures for storing an approximation s' to a set s such that s &sube; s' and any element not in s belongs to s' with probability at most &isin;. the bloom filter data structure, solving this problem, has found widespread use. our main result is a new ram data structure that improves bloom filters in several ways:&bull; the time for looking up an element in s' is o(1), independent of &isin;.&bull; the space usage is within a lower order term of the lower bound.&bull; the data structure uses explicit hash function families.&bull; the data structure supports insertions and deletions on s in amortized expected constant time.the main technical ingredient is a succinct representation of dynamic multisets. we also consider three recent generalizations of bloom filters.
linear-time compression of bounded-genus graphs into information-theoretically optimal number of bits. this extended abstract summarizes a new result for the graph compression problem, addressing how to compress a graph g into a binary string z with the requirement that z can be decoded to recover g. graph compression finds important applications in 3d model compression of computer graphics [12, 17-20] and compact routing table of computer networks [7]. for brevity, let a &brvbar;&eth;-graph stand for a graph with property &brvbar;&eth;. the information-theoretically optimal number of bits required to represent an n-node &brvbar;&eth;-graph is &lceil;log2 n&brvbar;&eth;(n)&rceil;, where n&brvbar;&eth;(n) is the number of distinct n-node &brvbar;&eth;-graphs. although determining or approximating the close forms of n&brvbar;&eth;(n) for nontrivial classes of &brvbar;&eth; is challenging, we provide a linear-time methodology for graph compression schemes that are information-theoretically optimal with respect to continuous super-additive functions (abbreviated as optimal for the rest of the extended abstract). specifically, if &brvbar;&eth; satisfies certain properties, then we can compress any n-node m-edge &brvbar;&eth;-graph g into a binary string z such that g and z can be computed from each other in o(m + n) time, and that the bit count of z is at most &brvbar;&acirc;(n) + o(&brvbar;&acirc;(n)) for any continuous super-additive function &brvbar;&acirc;(n) with log2n&brvbar;&eth;(n) &iexcl;&uuml; &brvbar;&acirc;(n) + o(&brvbar;&acirc;(n)). our methodology is applicable to general classes of graphs; this extended abstract focuses on graphs with sublinear genus. for example, if the input n-node &brvbar;&eth;-graph g is equipped with an embedding on its genus surface, which is a reasonable assumption for graphs arising from 3d model compression, then our methodology is applicable to any &brvbar;&eth; satisfying the following statements: f1. the genus of any n-node &brvbar;&eth;-graph is o(n/log2 n); f2. any subgraph of a &brvbar;&eth;-graph remains a &brvbar;&eth;-graph; f3. log n &brvbar;&eth;(n) = &brvbar;&cedil;(n); and f4. there is an integer k = o(1) such that it takes o(n) time to determine whether an o(log(k) n)-node graph satisfies property &brvbar;&eth;. for instance, &brvbar;&eth; can be the property of being a directed 3-colorable simple graph with genus no more than ten. the result is a novel application of planarization algorithm for bounded-genus graphs [5] and separator decomposition tree of planar graphs [9]. rooted trees were the only known nontrivial class of graphs with linear-time optimal coding schemes. he, kao, and lu [11] provided o(n log n)-time compression schemes for planar and plane graphs that are optimal. our results significantly enlarge the classes of graphs that admit efficient optimal compression schemes. more results on various versions of graph compression problems or succinct graph representations can be found in [1-4, 6, 8, 10, 14, 15] and the references therein.
mixing time and long paths in graphs. we prove that regular graphs with large degree and small mixing time contain long paths and some other families of graphs as subgraphs. we present then an efficient algorithm for finding long paths. we apply the results to size ramsey numbers and self-avoiding walks in graphs.
multicoloring unit disk graphs on triangular lattice points. given a pair of non-negative integers m and n, p(m, n) denotes a subset of 2-dimensional triangular lattice points defined by p(m, n) [equation], {(xe1 +ye2 | x &isin; {0, 1,..., m -1}, y &isin; {0, 1,..., n -1}} where e1 [equation] (1,0), e2 [equation] (1/2, &radic;3/2). let tm,n(d) be an undirected graph defined on vertex set p(m, n) satisfying that two vertices are adjacent if and only if the euclidean distance between the pair is less than or equal to d. this paper discusses a necessary and sufficient condition that tm,n(d) is perfect; we show that [&forall;m &isin; z+ tm,n(d) is perfect ] if and only if d &ge; &radic;n2 -3n + 3.given a non-negative vertex weight vector w &isin; zp(m,n)+ a multicoloring of (tm,n(d), &omega;) is an assignment of colors to p(m, n) such that each vertex v &isin; p(m, n) admits w(v) colors and every adjacent pair of two vertices does not share a common color. we also give an efficient algorithm for multicoloring (tm, n (d), w) when p(m, n) is perfect.in general case, our results on the perfectness of p(m, n) implies a polynomial time approximation algorithm for multicoloring (tm, n (d), w). our algorithm finds a multicoloring which uses at most &alpha;(d&omega; + o(d3) colors, where &omega; denotes the weighted clique number. when d = 1, &radic;3, 2, &radic;7, 3, the approximation ratio &alpha;(d) = (4/3), (5/3), (7/4), (5/3), (7/4), respectively. when d > 1, we showed that &alpha;(d) &le; (1 + 2/&radic;3 +2&radic;3-3/d) < 1 + 2/&radic;3 < 2.155.
morphing orthogonal planar graph drawings. we give an algorithm to morph between two planar orthogonal drawings of a graph, preserving planarity and orthogonality. the morph uses a polynomial number of discrete steps. each step is either a linear morph that moves a set of vertices horizontally or vertically; or a "twist" that introduces new bends in the edges incident with one vertex. our morph can be implemented so that inter-vertex distances are well-behaved. this is the first algorithm to provide planarity-preserving morphs with well-behaved complexity for a significant class of graph drawings.
the pure literal rule threshold and cores in random hypergraphs. we describe a technique for determining the thresholds for the appearance of cores in random structures. we use it to determine (i) the threshold for the pure literal rule to find a satisfying assignment for a random instance of r-sat, r &ge; 3, and (ii) the threshold for the appearance of a k-core in a random r-uniform hypergraph for all r, k &ge; 2, r + k > 4.
improved bounds on the average length of longest common subsequences. it has long been known &lsqb;chv&aacute;tal and sankoff 1975&rsqb; that the average length of the longest common subsequence of two random strings of length n over an alphabet of size k is asymptotic to &gamma;kn for some constant &gamma;k depending on k. the value of these constants remains unknown, and a number of papers have proved upper and lower bounds on them. we discuss techniques, involving numerical calculations with recurrences on many variables, for determining lower and upper bounds on these constants. to our knowledge, the previous best-known lower and upper bounds for &gamma;2 were those of dan&ccaron;&iacute;k and paterson, approximately 0.773911 and 0.837623 &lsqb;dan&ccaron;&iacute;k 1994; dan&ccaron;&iacute;k and paterson 1995&rsqb;. we improve these to 0.788071 and 0.826280. this upper bound is less than the &gamma;2 given by steele's old conjecture (see steele &lsqb;1997, page 3&rsqb;) that &gamma;2 &equals; 2/(1 + &sqrt;2)&approx; 0.828427. (as steele points out, experimental evidence had already suggested that this conjectured value was too high.) finally, we show that the upper bound technique described here could be used to produce, for any k, a sequence of upper bounds converging to &gamma;k, though the computation time grows very quickly as better bounds are guaranteed.
tiling groups for wang tiles. we apply tiling groups and height functions to tilings of regions in the plane by wang tiles, which are squares with colored boundaries where the colors of shared edges must match. we define a set of tiles as unambiguous if it contains all tiles equivalent to the identity in its tiling group. for all but one set of unambiguous tiles with two colors, we give efficient algorithms that tell whether a given region with colored boundary is tileable, show how to sample random tilings, and how to calculate the number of local moves or "flips" required to transform one tiling into another. we also analyze the lattice structure of the set of tilings, and study several examples with three and four colors as well.
generic quantum fourier transforms. the quantum fourier transform (qft) is the principal ingredient of most efficient quantum algorithms. we present a generic framework for the construction of efficient quantum circuits for the qft by "quantizing" the highly successful separation of variables technique for the construction of efficient classical fourier transforms. specifically, we use bratteli diagrams, gel'fand-tsetlin bases, and strong generating sets of small adapted diameter to provide efficient quantum circuits for the qft over a wide variety of finite abelian and non-abelian groups, including all group families for which efficient qfts are currently known and many new group families. moreover, our method provides the first subexponential-size quantum circuits for the qft over the linear groups glk(q), slk(q), and the finite groups of lie type, for any fixed prime power q.
the power of basis selection in fourier sampling: hidden subgroup problems in affine groups. many quantum algorithms, including shor's celebrated factoring and discrete log algorithms, proceed by reduction to a hidden subgroup problem, in which a unknown subgroup h of a group g must be determined from a quantum state &psi; over g that is uniformly supported on a left coset of h. these hidden subgroup problems are typically solved by fourier sampling: the quantum fourier transform of &psi; is computed and measured. when the underlying group is nonabelian, two important variants of the fourier sampling paradigm have been identified: the weak standard method, where only representation names are measured, and the strong standard method, where full measurement (i.e., the row and column of the representation as well as its name) occurs. it has remained open whether the strong method is indeed stronger, that is, whether there are hidden subgroups that can be reconstructed via the strong method but not by the weak, or any other known, method.in this article, we settle this question in the affirmative. we show that hidden subgroups of semidirect products of the form ℤq &times; ℤp, where q | (p - 1) and q = p/polylog(p), can be efficiently determined by the strong standard method. furthermore, the weak standard method and the "forgetful" abelian method are insufficient for these groups so that, in fact, it appears that use of the corresponding nonabelian representation theory is crucial. we extend this to an informationtheoretic solution for the hidden subgroup problem over the groups ℤq &times; ℤp where q | (p - 1) and, in particular, the affine groups ap. finally, we prove a simple closure property for the class of groups over which the hidden subgroup problem can be solved efficiently.
load balancing requires omega(log) expected time. in order to obtain very fast parallel algorithms, it is almost always necessary to have some sort of load balancing procedure, so that processors which have finished their required tasks can help processors which have not. if the overloaded processors are not helped, then the expected time of the entire algorithm suffers. in general, we would like to distribute the remaining work as evenly as possible among the processors, or more formally, given at most n independent tasks distributed in an arbitrary way among n processors, we would like to redistribute the tasks so that each processor contains o(1) tasks. we show here that even on the strongest randomized crcw pram model, for a simple random distribution tasks load balancing requires &ohgr;(log* n) expected time. gil, matias, and vishkin [9] give an o(log* n) expected time randomized algorithm which solves the load balancing problem in the worst case, so the lower bound is tight. by reduction we show that both padded sort [12], and linear approximate compaction [13] require &ohgr;(log* n) expected time. we note that our basic technique is one of the few parallel lower bound techniques known which only require 0/1 inputs. we also note that the bounds given in this paper do not place any restriction on the instruction set of the machine, the amount of information which can be stored in a memory cell, or on the number of memory cells.
fully-dynamic two dimensional orthogonal range and line segment intersection reporting in logarithmic time. we consider the two dimensional fully-dynamic orthogonal range reporting problem and the two dimensional fully-dynamic orthogonal line segment intersection reporting problem in the comparison model. we show that if n is the number of stored elements, then these problems can be solved in worst case time &theta;(log n) plus time proportional to the size of the output pr. operation.
trade-offs on the location of the core node in a network. the selection of a core node in a network is a crucial step in the set-up of several multimedia applications such as videoconferences or multi-player games. for a given group of application users, a poorly chosen location can lead to a waste of bandwidth or to long communication delays. since this kind of application usually involves unicast and multicast communications at the same time, we are naturally interested in a core location such that both the sum of the unicast path lengths to the users and the cost of the multicast tree spanning the users and the core are simultaneously small. while optimizing the first criterion is equivalent to finding a 1-median of the users, the second criterion corresponds to the minimum cost steiner tree problem.the goal of this paper is to show that there always exists a core location for which both criteria are close to their optimum. more precisely, we give a continuum of results which proves in particular that both criteria can simultaneously be within 1.37 times their optimum. finally we apply our results to the problem of minimizing a weighted sum of the criteria and we give an easy and fast heuristic with a small approximation ratio.
testing hierarchical systems. we investigate the testing of hierarchical (modular) systems, in which individual modules are modeled by finite state machines. given a hierarchical system, we are interested in finding a small set of tests that exercises all the transitions of the system. we present tight approximation algorithms and hardness results for the problem. our techniques extend to other criteria and metrics.
quantum algorithms for the triangle problem. we present two new quantum algorithms that either find a triangle (a copy of $k_{3}$) in an undirected graph $g$ on $n$ nodes, or reject if $g$ is triangle free. the first algorithm uses combinatorial ideas with grover search and makes $\tilde{o}(n^{10/7})$ queries. the second algorithm uses $\tilde{o}(n^{13/10})$ queries and is based on a design concept of ambainis [in proceedings of the $45$th ieee symposium on foundations of computer science, 2004, pp. 22-31] that incorporates the benefits of quantum walks into grover search [l. grover, in proceedings of the twenty-eighth acm symposium on theory of computing, 1996, pp. 212-219]. the first algorithm uses only $o(\log n)$ qubits in its quantum subroutines, whereas the second one uses $o(n)$ qubits. the triangle problem was first treated in [h. buhrman et al., siam j. comput., 34 (2005), pp. 1324-1330], where an algorithm with $o(n+\sqrt{nm})$ query complexity was presented, where $m$ is the number of edges of $g$.
caching queues in memory buffers. motivated by the need for maintaining multiple, large queues of data in modern high-performance systems, we study the problem of caching queues in memory under the following simple, but widely applicable, model. at each clock-tick, any number of data items may enter the various queues, while data-items are consumed from the heads of the queues. since the number of unconsumed items may exceed memory buffer size, some items in the queues need to be spilled to secondary storage and later moved back into memory for consumption. we provide online queue-caching algorithms under a number of interesting cost models.
i/o-efficient algorithms for graphs of bounded treewidth. we present i/o-efficient algorithms for the single source shortest path problem and np-hard problems on graphs of bounded treewidth. the main step in these algorithms is a method to compute a tree-decomposition for the given graph i/o-efficiently.
a practical approximation algorithm for the lms line estimator. the problem of fitting a straight line to a finite collection of points in the plane is an important problem in statistical estimation. robust estimators are widely used because of their lack of sensitivity to outlying data points. the least median-of-squares (lms) regression line estimator is among the best known robust estimators. given a set of n points in the plane, it is defined to be the line that minimizes the median squared residual or, more generally, the line that minimizes the residual of any given quantile q, where 0=0, and a quantile approximation, which approximates the fraction of points that lie within the strip to within a given error bound @e"q>=0. we present two randomized approximation algorithms for the lms line estimator. the first is a conceptually simple quantile approximation algorithm, which given fixed q and @e"q>0 runs in o(nlogn) time. the second is a practical algorithm, which can solve both types of approximation problems or be used as an exact algorithm. we prove that when used as a quantile approximation, this algorithm's expected running time is o(nlog^2n). we present empirical evidence that the latter algorithm is quite efficient for a wide variety of input distributions, even when used as an exact algorithm.
i/o-optimal algorithms for planar graphs using separators. we present i/o-optimal algorithms for several fundamental problems on planar graphs. our main contribution is an i/o-efficient algorithm for computing a small vertex separator of an unweighted planar graph. this algorithm is superior to all existing external memory algorithms for this problem, as it requires neither a breadth-first search tree nor an embedding of the graph as part of the input. in fact, we derive i/o-optimal algorithms for planar embedding, breadth-first search, depth-first search, single source shortest paths, and computing weighted separators of planar graphs from our unweighted separator algorithm.
colored tutte polynomials and kaufman brackets for graphs of bounded tree width. tutte polynomials are important graph invariants with rich applications in combinatorics, topology, knot theory, coding theory and even physics. the tutte polynomial t(g, x, y) is a polynomial in z[x, y] which depends on a graph g. computing the coefficients of t(g, x, y), and even evaluating t(g, x, y) at specific points (x, y) is #p hard by a result of jaeger et al. (math. proc. cambridge philos. soc. 108 (1989) 35). on the other hand, andrzejak (discrete math. 190 (1998) 39-54) and noble (combin. probab. comput. 7 (1998) 307-321) have shown independently, that, if g is a graph of bounded tree width, computing t(g, x, y) can be done in polynomial time. we extend this result to the signed tutte polynomials introduced in 1989 by kauffman and the colored tutte polynomials introduced in 1999 by bollobas and riordan. this allows us to prove similar results for the jones polynomials and kauffman brackets for knots and links which have a signed graph presentation of bounded tree width. jones polynomials and kauffman polynomials are the most prominent invariants of knot theory. for alternating links, they are easily computable from the tutte polynomials of the signed graph representing the link by a result of thistlethwaite (1988). for general links one has to use the colored tutte polynomial instead. knots and links can be presented as labeled planar graphs. the tree width of a link l is defined as the tree width of its graphical presentation d(l) as crossing diagrams. we show that for (not necessarily alternating) knots and links of tree width at most k, even the kauffman square bracket [l] introduced by bollobas and riordan can be computed in polynomial time. hence, the classical kauffman bracket (l) and the jones polynomial of links of tree width at most k are computable in polynomial time. our proof is based on, but extends considerably previous work by b. courcelle, u. rotics and the author. it also gives a new proof of the result for tutte polynomials and generalizes to a wide class of polynomials defined as generating functions definable in monadic second order logic with order, but invariant under it.
deterministic skip lists. we explore techniques based on the notion of a skip list to guarantee logarithmic search, insert and delete costs. the basic idea is to insist that between any pair of elements above a given height are a small number of elements of precisely that height. the desired behaviour can be achieved by either using some extra space for pointers, or by adding the constraint that the physical sizes of the nodes be exponentially increasing. the first approach leads to simpler code, whereas the second is ideally suited to a buddy system of memory allocation. our techniques are competitive in terms of time and space with balanced tree schemes, and, we feel, inherently simpler when taken from first principles.
a new look at survey propagation and its generalizations. we study the survey propagation algorithm [19, 5, 4], which is an iterative technique that appears to be very effective in solving random k-sat problems even with densities close to threshold. we first describe how any sat formula can be associated with a novel family of markov random fields (mrfs), parameterized by a real number &rho;. we then show that applying belief propagation---a well-known "message-passing technique---to this family of mrfs recovers various algorithms, ranging from pure survey propagation at one extreme (&rho; = 1) to standard belief propagation on the uniform distribution over sat assignments at the other extreme (&rho; = 0). configurations in these mrfs have a natural interpretation as generalized satisfiability assignments, on which a partial order can be defined. we isolate cores as minimal elements in this partial ordering, and prove that any core is a fixed point of survey propagation. we investigate the associated lattice structure, and prove a weight-preserving identity that shows how any mrf with p > 0 can be viewed as a "smoothed" version of the naive factor graph representation of the k-sat problem (p = 0). our experimental results show that message-passing on our family of mrfs is most effective for values of &rho; &ne; 1 (i.e., distinct from survey propagation); moreover, they suggest that random formulas may not typically possess non-trivial cores. finally, we isolate properties of gibbs sampling and message-passing algorithms that are typical for an ensemble of k-sat problems. we prove that the space of cores for random formulas is highly disconnected, and show that for values of p sufficiently close to one, either the associated mrf is highly concentrated around the all-star assignment, or it has exponentially small conductance. similarly, we prove that for p sufficiently close to one, the all-star assignment is attractive for message-passing when analyzed in the density-evolution setting.
representing dynamic binary trees succinctly. we introduce a new updatable representation of binary trees. the structure requires the information theoretic minimum 2n + &ogr;(n) bits and supports basic navigational operations in constant time and subtree size in &ogr;(lg n). in contrast to the linear update costs of previously proposed succinct representations, our representation supports updates in &ogr;(lg2 n) amortized time.
an analysis of the burrows-wheeler transform. the burrows-wheeler transform (also known as block-sorting) is at the base of compression algorithms which are the state of the art in lossless data compression. in this paper we analyze two algorithms which use this technique. the first one is the original algorithm described by burrows and wheeler, which, despite its simplicity, outperforms the gzip compressor. the second one uses an additional run-length encoding step to improve compression. we prove that the compression ratio of both algorithms can be bounded in terms of the k-th order empirical entropy of the input string for any k<0. we make no assumptions on the input and we obtain bounds which hold in the worst case, that is, for every possible input string. all previous results for block-sorting algorithms were concerned with the average compression ratio and have been established assuming that the input comes from a finite-order markov source.
fast distributed graph coloring with o(delta) colors. we consider the problem of deterministic distributed coloring of an n-vertex graph with maximum degree &dgr;, assuming that every vertex knows a priori only its own label and parameters n and &dgr;. the aim is to get a fast algorithm using few colors. linial [17] showed a vertex-coloring algorithm working in time &ogr;(log* n) and using &ogr;(&dgr;2 colors. we improve both the time and the number of colors simultaneously by showing an algorithm working in time &ogr;(log*(n/&dgr;)) and using &ogr;(&dgr;) colors. this is the first known &ogr;(&dgr;)-vertex-coloring distributed algorithm which can work faster than in polylogarithmic time. our method also gives an edge-coloring algorithm with the number of colors and time as above. on the other hand, it follows from linial [17] that our time of &ogr;(&dgr;)-coloring cannot be improved in general. in addition we show how our method gives fast coloring algorithms in communication models weaker than linial's.
fast mixing for independent sets, colorings and other models on trees. we study the mixing time of the glauber dynamics for general spin systems on bounded-degree trees, including the ising model, the hard-core model (independent sets) and the antiferromagnetic potts model at zero temperature (colorings). we generalize a framework, developed in our recent paper [18] in the context of the ising model, for establishing mixing time o(n log n), which ties this property closely to phase transitions in the underlying model. we use this framework to obtain rapid mixing results for several models over a significantly wider range of parameter values than previously known, including situations in which the mixing time is strongly dependent on the boundary condition.
efficient algorithms for document retrieval problems. we are given a collection d of text documents d1,&hellip;,dk, with &sum;i = n, which may be preprocessed. in the document listing problem, we are given an online query comprising of a pattern string p of length m and our goal is to return the set of all documents that contain one or more copies of p. in the closely related occurrence listing problem, we output the set of all positions within the documents where pattern p occurs. in 1973, weiner [24] presented an algorithm with o(n) time and space preprocessing following which the occurrence listing problem can be solved in time o(m + output) where output is the number of positions where p occurs; this algorithm is clearly optimal. in contrast, no optimal algorithm is known for the closely related document listing problem, which is perhaps more natural and certainly well-motivated.we provide the first known optimal algorithm for the document listing problem. more generally, we initiate the study of pattern matching problems that require retrieving documents matched by the patterns; this contrasts with pattern matching problems that have been studied more frequently, namely, those that involve retrieving all occurrences of patterns. we consider document retrieval problems that are motivated by online query processing in databases, information retrieval systems and computational biology. we present very efficient (optimal) algorithms for our document retrieval problems. our approach for solving such problems involve performing "local" encodings whereby they are reduced to range query problems on geometric objects --- points and lines --- that have color. we present improved algorithms for these colored range query problems that arise in our reductions using the structural properties of strings. this approach is quite general and yields simple, efficient, implementable algorithms for all the document retrieval problems in this paper.
adaptive sampling for quickselect. quickselect with median-of-3 is largely used in practice and its behavior is fairly well understood. however, the following natural adaptive variant, which we call proportion-from-3, had not been previously analyzed: choose as pivot the smallest of the sample if the rank of the sought element is small, the largest if the rank is large, and the median if the rank is medium". we first analyze proportion-from-2 and then proportion-from3. we also analyze &nu;-find, a generalization of proportion-from-3 with interval breakpoints at &nu; and 1 -- &nu;. we show that there exists an optimal value of &nu; and we also provide the range of values of &nu; where &nu;-find outperforms median-of-3. our results atrongly suggest that a suitable implementation of this variant could be the method of choice in a practical setting. finally, we also show that proportion-from-s and similar strategies are optimal when s &rarr; &infin;
data streams: algorithms and applications. in the data stream scenario, input arrives very rapidly and there is limited memory to store the input. algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. in the past few years, a new theory has emerged for reasoning about algorithms that work within these constraints on space, time, and number of passes. some of the methods rely on metric embeddings, pseudo-random computations, sparse approximation theory and communication complexity. the applications for this scenario include ip network traffic analysis, mining text message streams and processing massive data sets in general. researchers in theoretical computer science, databases, ip networking and computer systems are working on the data stream challenges. this article is an overview and survey of data stream algorithmics and is an updated version of [1].
percolation theory and computing with faulty arrays of processors. let h be an n x n mesh-connected array of processors. each processor is assumed to fail (independently) with probability p. raghavan [5] gave an algorithm that with high probability routes packets in this mesh with o(log n) dilation and o(log2n) load so long as p &le; 0.29. kklmrrtt [3] improve the load to o(1) for &ldquo;small&rdquo; p while keeping the o(log n) bound for dilation and showing an o(1) bound for congestion. in this paper we show these bounds hold for p as high as *** 0.4. we also consider the problem where links rather than processors fail and shows these same bounds hold for q < 1/2. in both cases these bounds are tight: for greater probabilities of failure the above embedding bounds cannot be achieved. this short cutoff follows from a zero-one result of percolation theory.
the bin-covering technique for thresholding random geometric graph properties. we study the emerging phenomenon of ad hoc, sensor-based communication networks. the communication is modeled by the geometric random graph model g(n, r, &ell;) where n points randomly placed within [0, &ell;]d form the nodes, and any two nodes that correspond to points at most distance r away from each other are connected. we study fundamental properties of g(n, r, &ell;) of interest: connectivity, coverage, and routing-stretch. our main contribution is a simple analysis technique we call bin-covering that we apply uniformly to get first known, (asymptotically) tight thresholds for each of these properties. typically, in the past, geometric random graph analyses involved sophisticated methods from continuum percolation theory; on contrast, our bin-covering approach is discrete and very simple, yet it gives us tight threshold bounds. the technique also yields algorithmic benefits as illustrated by a simple local routing algorithm for finding paths with low stretch. our specific results should also prove interesting to the networking community that has seen a recent increase in the study of geometric random graphs motivated by engineering ad hoc networks.
efficient bundle sorting. many data sets to be sorted consist of a limited number of distinct keys. sorting such data sets can be thought of as bundling together identical keys and having the bundles placed in order; we therefore denote this as bundle sorting. we describe an efficient algorithm for bundle sorting in external memory, which requires at most c(n/b) logm/bk disk accesses, where n is the number of keys, m is the size of internal memory, k is the number of distinct keys, b is the transfer block size, and 2 < c < 4. for moderately sized k, this bound circumvents the theta((n/b) logm/b (n/b)) i/o lower bound known for general sorting. we show that our algorithm is optimal by proving a matching lower bound for bundle sorting. the improved running time of bundle sorting over general sorting can be significant in practice, as demonstrated by experimentation. an important feature of the new algorithm is that it is executed "in-place," requiring no additional disk space.
rangesum histograms. a rangesum query to an array a is a pair (l, r) of range endpoints, which should be answered by &sigma;l&le;ira[i]. to compress a, we consider representing an array a lossily by a histogram, a function that is constant on each of a small number of buckets. we then answer range queries from h instead of from a, i.e., as &sigma;l&le;irh[i]. an optimal rangesum histogram h for this purpose is one whose bucket boundaries and constant heights within buckets are chosen to minimize the expected square error, el, r[(&sigma;l&le;ira[i]--&sigma;l&le;irh[i].)2], assuming each rangesum query is equally likely. rangesum histograms find many applications in database systems.in a degenerate variation, all rangesum queries are over ranges of size one, namely, individual points; histograms optimal for this special case are called pointwise optimal histograms. pointwise optimal histogram is a classical notion in statistics and approximation theory, but rangesum optimal histogram appears to be novel in these areas. while optimal pointwise histograms can be constructed efficiently by simple dynamic progrmming, no efficient (even approximate) general rangesmn histogram construction algorithms were previously known. in practice, all commercial database systems use heuristically built histograms for pointwise and rangesum queries.we present the first general algorithms for approximate rangesum histograms. given parameter b, we denote by (&alpha;, &beta;)-approximation an algorithm to produce a (&alpha;b)-bucket histogram with error at most &beta; times the error of the optimal b-bucket histogram. we give a (2, 1)-approximation with runtime o(n2b), a (2, 1+∊)-approximation with runtime n + (b log(n)/∊)o(1) (1), and a (1, 1 + ∊)-approximation with runtime o(b3n4/∊2). we also consider the problem of dynamic maintenance of rangesum histograms for data updated by additive changes, and we give a (2, 1 + ∊)-approximation that uses space (blog(n)/∊)o(1) and time (blog(n)/∊)o(1) for update and query operations. the bounds are nearly competitive with some of the best known bounds for constructing pointwise optimal histograms modulo small additional number of buckets used; however, rangesum histograms are substantially harder to construct because of the long range dependence between subproblems.
efficient oblivious transfer protocols. 1 introduction oblivious transfer (ot) protocols allow one party, the sender, to transmit part of its inputs to another party, the chooser, in a manner that protects both of them: the sender is assured that the chooser does not receive more information than it is entitled, while the chooser is assured that the sender does not learn which part of the inputs it received. ot is used as a key component in many applications of cryptography. its computational requirements are quite demanding and they are likely to be the bottleneck in many applications that invoke it. 1.1 contributions. this paper presents several significant improvements to oblivious transfer (ot) protocols of strings, and in particular: (i) improving the efficiency of applications which many invocations of oblivious transfer. (ii) providing the first two-round ot protocol whose security analysis does not invoke the random oracle model.
the directed circular arrangement problem. we consider the problem of embedding a directed graph onto evenly-spaced points on a circle while minimizing the total weighted edge length. we present the first poly-logarithmic approximation factor algorithm for this problem which yields an approximation factor of o(log n log log n), thus improving the previous &otilde;(&radic;n) approximation factor. in order to achieve this, we introduce a new problem which we call the directed penalized linear arrangement. this problem generalizes both the directed feedback edge set problem and the directed linear arrangement problem. we present an o(log n log log n) approximation factor algorithm for this newly defined problem. our solution uses two distinct directed metrics ("right" and "left") which together yield a lower bound on the value of an optimal solution. in addition, we define a sequence of new directed spreading metrics that are used for applying the algorithm recursively on smaller subgraphs. the new spreading metrics allow us to define an asymmetric region growing procedure that accounts simultaneously for both incoming and outgoing edges. to the best of our knowledge, this is the first time that a region growing procedure is defined in directed graphs that allows for such an accounting.
a certifying algorithm for the consecutive-ones property. we give a forbidden substructure characterization of set families that have the consecutive-ones property, and a linear time algorithm to find the forbidden substructure if a set family does not have the property. the forbidden substructure has size o(n), where n is the size of the domain. the pq tree is a well-known data structure for representing all consecutive-ones orderings. we show that it is given by a substitution decomposition of arbitrary set families that has not been described previously. this observation gives a generalization of the pq tree to arbitrary set families, and we give a linear-time algorithm to compute it.
construction of probe interval models. an interval graph for a set of intervals on a line consists of one vertex for each interval, and an edge for each pair of intersecting intervals. a probe interval graph is obtained from an interval graph by designating a subset p of vertices as probes, and removing the edges between pairs of vertices in the remaining set n of non-probes. we examine the problem of finding and representing possible layouts of the intervals, given a probe interval graph. we obtain an o(n + m log n) bound, where n is the number of vertices and m is the number of edges. the problem is motivated by an application to molecular biology.
randomized parallel algorithms for matroid union and intersection, with applications to arboresences and edge-disjoint spanning trees. the strong link between matroids and matching is used to extend the ideas that resulted in the design of random nc algorithms for matching to obtain rnc algorithms for the well-known problems of finding an arboresence and a maximum cardinality set of edge-disjoint spanning trees in a graph. the key tools used are linear algebra and randomization.
a new algorithm for protein folding in the hp model. we consider the problem of protein folding in the hp model on the two-dimensional square lattice. this problem is combinatorially equivalent to folding a string of 0's and 1's so that the string forms a self-avoiding walk on the lattice and the number of adjacent pairs of 1's is maximized. we present a linear-time 1/3-approximation algorithm for this problem, improving on the previous best approximation factor of 1/4. the approximation guarantee of this algorithm is based on an upper bound presented by hart and istrail [6] and used in all previous papers that address this problem. we show that this upper bound cannot be used to obtain an approximation factor better than 1/2.
multirate rearrangeable clos networks and a generalized edge coloring problem on bipartite graphs. chung and ross (siam j. comput., 20, 1991) conjectured that the minimum number m(n, r) of middle-state switches for the symmetric 3-stage clos network c(n, m(n, r), r) to be rearrangeable in the multirate enviroment is at most 2n -- 1. this problem is equivalent to a generalized version of the biparite graph edge coloring problem. the best bounds known so far on the function m(n, r) is 11n/9 &le; m(n, r) &le; 41n/16 + o(1), for n, r &ge; 2, derived by du-gao-hwang-kim (siam j. comput., 28, 1999). in this paper, we make several contributions. firstly, we give evidence to show that even a stronger result might hold. in particular, we give a coloring algorithm to show that m(n, r) &le; [(r + 1)n/2], which implies m(n, 2) &le; [3n/2] - stronger than the conjectured value of 2n -- 1. secondly, we derive that m(2, r) = 3 by an elegant argument. lastly, we improve both the best upper and lower bounds given above: [5n/4] &le; m(n, r) &le; 2n -- 1 + [(r -- 1)/2], where the upper bound is an improvement over 41n/16 when r is relatively small compared to n. we also conjecture that m(n, r) &le; [2n (1 -- 1/2(r)].
analyzing and characterizing small-world graphs. we study variants of kleinberg's small-world model where we start with a k-dimensional grid and add a random directed edge from each node. the probability u's random edge is to v is proportional to d(u,v)-r where d(u,v) is the lattice distance and r is a parameter of the model.for a k-dimensional grid, we show that these graphs have poly-log expected diameter when k < r < 2k, but have polynomial expected diameter when r > 2k. this shows an interesting phase-transition between small-world and "large-world" graphs.we also present a general framework to construct classes of small-world graphs with &theta;(log n) expected diameter, which includes several existing settings such as kleinberg's grid-based and tree-based settings [15].we also generalize the idea of 'adding links with probability &alpha; the inverse distance' to design small-world graphs. we use semi-metric and metric functions to abstract distance to create a class of random graphs where almost all pairs of nodes are connected by a path of length o (log n), and using only local information we can find paths of poly-log length.
srpt optimally utilizes faster machines to minimize flow time. we analyze the shortest remaining processing time (srpt) algorithm with respect to the problem of scheduling n jobs with release times on m identical machines to minimize total flow time. it is known that srpt is optimal if m = 1 but that srpt has a worstcase approximation ratio of &theta;(min(log n/m, log &delta;)) for this problem, where &delta; is the ratio of the length of the longest job divided by the length of the shortest job. it has previously been shown that srpt is able to use faster machines to produce a schedule as good as an optimal algorithm using slower machines. we now show that srpt optimally uses these faster machines with respect to the worst-case approximation ratio. that is, if srpt is given machines that are s &ge; 2 - 1/m times as fast as those used by an optimal algorithm, srpt's flow time is at least s times smaller than the flow time incurred by the optimal algorithm. clearly no algorithm can offer a better worst-case guarantee, and we show that existing algorithms with similar performance guarantees to srpt without resource augmentation do not optimally use extra resources.
hole and antihole detection in graphs. in this paper, we study the problems of detecting holes and antiholes in general undirected graphs and present algorithms for them, which, for a graph on n vertices and m edges, run in o(n + m2) time and require o(nm) space; we thus provide a solution to the open problem posed by hayward, spinrad, and sritharan in [12] asking for an o(n4)-time algorithm for finding holes in arbitrary graphs. the key element of the algorithms is a special type of depth-first search traversal which proceeds along p4s (i.e., chordless paths on four vertices) of the input graph. we also describe a different approach which allows us to detect antiholes in graphs that do not contain chordless cycles on 5 vertices in o(n + m2) time requiring o(n + m) space. our algorithms are simple and can be easily used in practice. additionally, we show how our detection algorithms can be augmented so that they return a hole or an antihole whenever such a structure is detected in the input graph; the augmentation takes o(n + m) time and space.
strong concentration for quicksort. let qn be the random number of comparisons made by quicksort in sorting n distinct keys, when we assume that all n! possible orderings are equally likely. known results concerning moments for qn do not show how rare it is for qn to make large deviations from its mean. here we give a good approximation to the probability of such a large deviation, and find that this probability is quite small. as well as the basic quicksort we consider the variant in which the partitioning key is chosen as the median of (2t+1) keys.
approximating connectivity augmentation problems. let g &equals; (v,e) be an undirected graph and let s &sube; v. the s-connectivity &lambda;sg(u,v) of a node pair (u,v) in g is the maximum number of uv-paths that no two of them have an edge or a node in s &minus; {u,v} in common. the corresponding connectivity augmentation (ca) problem is: given a graph g &equals; (v,e), a node subset s &sube; v, and a nonnegative integer requirement function r(u,v) on v &times; v, add a minimum size set f of new edges to g so that &lambda;sg+f(u,v) &ge; r(u,v) for all (u,v) &isin; v &times; v. three extensively studied particular cases are: the edge-ca (s &equals; &empty;), the node-ca (s &equals; v), and the element-ca (r(u,v)&equals; 0 whenever u &isin; s or v &isin; s). a polynomial-time algorithm for edge-ca was developed by frank. in this article we consider the element-ca and the node-ca, that are np-hard even for r(u,v) &isin; {0,2}. the best known ratios for these problems were: 2 for element-ca and o(rmax &sdot; ln n) for node-ca, where rmax &equals; maxu,v &isin; v r(u,v) and n &equals; &verbar;v&verbar;. our main result is a 7/4-approximation algorithm for the element-ca, improving the previously best known 2-approximation. for element-ca with r(u,v) &isin; {0,1,2} we give a 3/2-approximation algorithm. these approximation ratios are based on a new splitting-off theorem, which implies an improved lower bound on the number of edges needed to cover a skew-supermodular set function. for node-ca we establish the following approximation threshold: node-ca with r(u,v) &isin; {0,k} cannot be approximated within o(2log1&minus;&epsis; n) for any fixed &epsis; > 0, unless np &sube; dtime(npolylog(n)).
dag-width: connectivity measure for directed graphs. tree-width is a very useful connectivity measure for undirected graphs. we propose a new definition, called dag-width, for directed graphs which measures how close a graph is to a directed acyclic graph. in addition we define a cops-and-robber game and show that this game characterises exactly the class of graphs of bounded dag-width. a comparison of dag-width with tree-width and directed tree-width follows. finally we show that np-complete problems can be solved in polynomial time on graphs of bounded dag-width.
triangulating vertex colored graphs. this paper examines the class of vertex-colored graphs that can be triangulated without the introduction of edges between vertices of the same color. this is related to a fundamental and long-standing problem for numerical taxonomists, called the perfect phylogeny problem. these problems are known to be polynomially equivalent and np-complete. this paper presents a dynamic programming algorithm that can be used to determine whether a given vertex-colored graph can be so triangulated and that runs in $o((n+m(k-2))^{k+1})$ time, where the graph has $n$ vertices, $m$ edges, and $k$ colors. the corresponding algorithm for the perfect phylogeny problem runs in $o(r^{k+1} k^{k+1} + sk^2 )$ time, where $s$ species are defined by $k$ $r$-state characters.
tail estimates for the space complexity of randomized incremental algorithms. we give tail estimates for the space complexity of randomized incremental algorithms for line segment intersection in the plane. for n the number of segments, m is the number of intersections, and m &ge; n ln n ln(3) n, there is a constant c such that the probability that the total space cost exceeds c times the expected space cost is e-&ohgr;(m/(n ln n)).
approximate local search in combinatorial optimization. local search algorithms for combinatorial optimization problems are in general of pseudopolynomial running time and polynomial-time algorithms are often not known for finding locally optimal solutions for np-hard optimization problems. we introduce the concept of ε-local optimality and show that an ε-local optimum can be identified in time polynomial in the problem size and 1=ε whenever the corresponding neighborhood can be searched in polynomial time, for ε > 0. if the neighborhood can be searched in polynomial time for a &delta;-local optimum, a variation of our main algorithm produces a (&delta; + ε)-local optimum in time polynomial in the problem size and 1/ε. as a consequence, a combinatorial optimization problem has a fully polynomial-time approximation scheme if and only if the problem of determining a better solution---the so-called augmentation problem---has a fully polynomial-time approximation scheme.
certifying large branch-width. branch-width is defined for graphs, matroids, and, more generally, arbitrary symmetric submodular functions. for a finite set v, a function f on the set of subsets 2v of v is submodular if f(x) + f(y) &ge; f(x &cap; y) + f(x &cup; y), and symmetric if f(x) = f(v \ x). we discuss the computational complexity of recognizing that symmetric submodular functions have branch-width at most k for fixed k. an integer-valued symmetric submodular function f on 2v is a connectivity function if f(&theta;) = 0 and f({v}) &le; 1 for all v &isin; v. we show that for each constant k, if a connectivity function f on 2v is presented by an oracle and the branch-width of f is larger than k, then there is a certificate of polynomial size (in |v|) such that a polynomial-time algorithm can verify the claim that branch-width of f is larger than k. in particular it is in conp to recognize matroids represented over a fixed field with branch-width at most k for fixed k.
metric cotype. we introduce the notion of metric cotype, a property of metric spaces related to a property of normed spaces, called rademacher cotype. apart from settling a long standing open problem in metric geometry, this property is used to prove the following dichotomy: a family of metric spaces f is either almost universal (i.e., contains any finite metric space with any distortion > 1), or there exists &alpha; > 0, and arbitrarily large n-point metrics whose distortion when embedded in any member of f is at least &omega;((log n)&alpha;). the same property is also used to prove strong non-embeddability theorems of lq into lp, when q > max{2, p}. finally we use metric cotype to obtain a new type of isoperimetric inequality on the discrete torus.
tight bounds for the partial-sums problem. we close the gaps between known lower and upper bounds for the online partial-sums problem in the ram and group models of computation. if elements are chosen from an abstract group, we prove an &omega;(lg n) lower bound on the number of algebraic operations that must be performed, matching a well-known upper bound. in the ram model with b-bit memory registers, we consider the well-studied case when the elements of the array can be changed additively by &delta;-bit integers. we give a ram algorithm that achieves a running time of &theta;(1 + lg n / lg(b / &delta;)) and prove a matching lower bound in the cell-probe model. our lower bound is for the amortized complexity, and makes minimal assumptions about the relations between n, b, and &delta;. the best previous lower bound was &omega;(lg n = (lg lg n+lg b)), and the best previous upper bound matched only in the special case b = &theta;(lg n) and &delta; = o(lg lg n).
meldable ram priority queues and minimum directed spanning trees. we consider the implementation of meldable priority queues with integer keys in the ram model. we present two new general techniques for transforming non-meldable priority queues into meldable ones. these transformations can be described symbolically as:non-meldable priority queue +union-find &larr; meldable priority queuenon-meldable priority queue +slow meldable priority queue &larr;faster meldable priority queueusing the first transformation to combine a recent non-meldable ram priority queue of thorup with the classical union-find data structure we obtain a meldable ram priority queue with an amortized cost of o(log log n&middot;&alpha;(n)) per operation, where &alpha;(n) = &alpha;(n, n) is the inverse ackermann function. using instead a randomized priority queue of han and thorup we obtain an expected amortized cost of o(&radic;(log log n) &middot; &alpha;(n)) per operation. the second transformation yields slower meldable priority queues, but the obtained queues can support the insert, find-min and decrease-key operations in constant time. in particular, by combining a randomized "atomic-heap" of thorup with, e.g., the classical fibonacci heaps of fredman and tarjan, we obtain, for every fixed ε > 0, a meldable priority queue with an expected amortized cost of o(1) for each insert, find-min and decrease-key operation, and an expected amortized cost of o((log n)1/2+ε) for each delete or meld operation.using the meldable priority queues of the first type, we obtain improved algorithms for finding minimum directed spanning trees in graphs with integer edge weights: a deterministic o(m &middot; log log n &middot; &alpha;(n)) time algorithm and a randomized o(m &middot; &radic;(log log n) &middot; &alpha;(n)) expected time algorithm. these bounds improve, for very sparse graphs, on the o(m + n log n) running time of an algorithm by gabow, galil, spencer and tarjan that works for arbitrary edge weights.
optimal random number generation from a biased coin. we study the optimal generation of random numbers using a biased coin in two cases: first, when the bias is unknown, and second, when the bias is known. in the first case, we characterize the functions that use a discrete random source of unknown distribution to simulate a target discrete random variable with a given rational distribution. we identify the functions that minimize the ratio of source inputs to target outputs. we show that these optimal functions are efficiently computable. in the second case, we prove that it is impossible to construct an optimal tree algorithm recursively, using a model based on the algebraic decision tree. our model of computation is sufficiently general to encompass virtually all previously known algorithms for this problem.
external memory bfs on undirected graphs with bounded degree. we give the first external memory algorithm for breadth-first search (bfs) which achieves &ogr;(n) i/os on arbitrary undirected graphs with n nodes and maximum node degree d. let m and b < d denote the main memory size and block size, respectively. using sort(x) = &thgr;(x&divide;b &middot; log m/b x&divide;b), our algorithm needs &ogr;(n&divide;&ggr;&middot;logdb + sort(n &middot; b&ggr;)) i/os and &ogr;(n &middot; b&ggr;) external space for an arbitrary parameter 0 < &ggr; &lne; &frac12;. the result carries over to bfs, depth-first search (dfs) and single source shortest paths (sssp) on undirected planar graphs with arbitrary node degrees.
single-source shortest-paths on arbitrary directed graphs in linear average-case time. the quest for a linear-time single-source shortest-path (sssp) algorithm on directed graphs with positive edge weights is an ongoing hot research topic. while thorup recently found an &ogr;(n + m) time ram algorithm for undirected graphs with n nodes, m edges and integer edge weights in {0,&hellip;,2w - 1} where w denotes the word length, the currently best time bound for directed sparse graphs on a ram is &ogr;(n + m &middot; log log n). in the present paper we study the average-case complexity of sssp. we give a simple algorithm for arbitrary directed graphs with random edge weights uniformly distributed in [0, 1] and show that it needs linear time &ogr;(n + m) with high probability.
optimal time-space trade-offs for non-comparison-based sorting. we study the problem of sorting n integers of w bits on a unit-cost ram with word size w, and in particular consider the time-space trade-off (product of time and space in bits) for this problem. for comparison-based algorithms, the time-space complexity is known to be &theta;(n2). a result of beame shows that the lower bound also holds for non-comparison-based algorithms, but no algorithm has met this for time below the comparison-based &omega;(nlgn) lower bound.we show that if sorting within some time bound &ttilde; is possible, then time t = o(&ttilde; + nlg* n) can be achieved with high probability using space s = o(n2/t + w), which is optimal. given a deterministic priority queue using amortized time t(n) per operation and space no(1), we provide a deterministic algorithm sorting in time t = o(n(t(n) + lg* n)) with s = o(n2/t + w). both results require that w &le; n1-&omega;(1). using existing priority queues and sorting algorithms, this implies that we can deterministically sort time-space optimally in time &theta;(t) for t &ge; n(lg lg n)2, and with high probability for t &ge; nlg lg n.our results imply that recent space lower bounds for deciding element distinctness in o(nlgn) time are nearly tight.
web caching using access statistics. we consider the problem of caching web pages with the objective of minimizing latency of access. demands for web domains/pages are computed using access statistics; the frequency with which these statistics change is considerably longer than the frequency of page requests. we model caches as being constrained by total size and total number of ports: each cache can handle only a limited request rate and can store only a limited number of domains (eg. modelling bounded update traffic). when the caches have fixed locations, we present a constant factor approximation to the optimum average latency while exceeding capacity constraints by a logarithmic factor. we demonstrate improved results in the special case where no replication of pages is allowed. in the alternate model where we are allowed to place our own caches in the network for a cost, we produce a constant approximation to the weighted sum of cost and average latency. finally, we consider several other variants of the problem which might arise in practice.
can the tpri structure help us to solve the algebraic eigenproblem? we modify the customary approach to solving the algebraic eigenproblem. instead of applying the qr algorithm to a hessenberg matrix, we begin with the recent unitary similarity transform into a triangular plus rank-one matrix. then we show nonunitary transforms of this matrix at a low arithmetic cost into similar arrow-head matrices. the resulting eigenproblem can be effectively solved by the known algorithms. based on some properties of the tpri matrices, we also show that the similarity transforms into both hessenberg and tpri forms tend to decrease the geometric multiplicities of the eigenvalues, and we discuss some relevant research topics.
selfish routing with atomic players. one of the most successful applications of the price of anarchy---the worst-case ratio between the objective function values of noncooperative equilibria and optima---is to "selfish routing", a classical model of how independent network users route traffic in a congested network. however, almost all existing work on this topic (e.g., [2, 5, 7]) assumes a large population of very small network users, so that the actions of a single individual have negligible impact on the cost incurred by others. this assumption---in game theory terminology, that the game is nonatomic---is obviously not justifiable in all applications.
the mathematics of playing golf. we consider a class of non-linear mixed integer programs with n integer variables and k continuous variables. solving instances from this class to optimality is an np-hard problem. we show that for the cases with k &le; 2, every optimal solution is integral. in strong contrast to this, for every k &ge; 3 there exist instances where every optimal solution takes non-integral values.
can entropy characterize performance of online algorithms?. we focus in this work on an aspect of online computation that is not addressed by the standard competitive analysis. namely, identifying request sequences for which non-trivial online algorithms are useful versus request sequences for which all algorithms perform equally bad. the motivation for this work are advanced system and architecture designs which allow the operating system to dynamically allocate resources to online protocols such as prefetching and caching. to utilize these features the operating system needs to identify data streams that can benefit from more resources. our approach in this work is based on the relation between entropy, compression and gambling, extensively studied in information theory. it has been shown that in some settings entropy can either fully or at least partially characterize the expected outcome of an iterative gambling game. viewing online problem with stochastic input as an iterative gambling game, our goal is to study the extent to which the entropy of the input characterizes the expected performance of online algorithms for problems that arise in computer applications. we study bounds based on entropy for three online problems &mdash; list accessing, prefetching and caching. we show that entropy is a good performance characterizer for prefetching, but not so good characterizer for online caching.
efficient hashing with lookups in two memory accesses. the study of hashing is closely related to the analysis of balls and bins. azar et. al. [1] showed that instead of using a single hash function if we randomly hash a ball into two bins and place it in the smaller of the two, then this dramatically lowers the maximum load on bins. this leads to the concept of two-way hashing where the largest bucket contains o(log log n) balls with high probability. the hash look up will now search in both the buckets an item hashes to. since an item may be placed in one of two buckets, we could potentially move an item after it has been initially placed to reduce maximum load. using this fact, we present a simple, practical hashing scheme that maintains a maximum load of 2, with high probability, while achieving high memory utilization. in fact, with n buckets, even if the space for two items are pre-allocated per bucket, as may be desirable in hardware implementations, more than n items can be stored giving a high memory utilization. assuming truly random hash functions, we prove the following properties for our hashing scheme.&bull; each lookup takes two random memory accesses, and reads at most two items per access.&bull; each insert takes o(log n) time and up to log log n+o(1) moves, with high probability, and constant time in expectation.&bull; maintains 83.75% memory utilization, without requiring dynamic allocation during inserts.we also analyze the trade-off between the number of moves performed during inserts and the maximum load on a bucket. by performing at most h moves, we can maintain a maximum load of o(log log n/h log (log log n/h)). so, even by performing one move, we achieve a better bound than by performing no moves at all.
self-testing polynomial functions efficiently and over rational domains. in this paper we give the first self-testers and checkers for polynomials over rational and integer domains. we also show significantly stronger bounds on the efficiency of a simple modification of the algorithm for self-testing polynomials over finite fields given in [8].
entropy based nearest neighbor search in high dimensions. in this paper we study the problem of finding the approximate nearest neighbor of a query point in the high dimensional space, focusing on the euclidean space. the earlier approaches use locality-preserving hash functions (that tend to map nearby points to the same value) to construct several hash tables to ensure that the query point hashes to the same bucket as its nearest neighbor in at least one table. our approach is different - we use one (or a few) hash table and hash several randomly chosen points in the neighborhood of the query point showing that at least one of them will hash to the bucket containing its nearest neighbor. we show that the number of randomly chosen points in the neighborhood of the query point q required depends on the entropy of the hash value h(p) of a random point p at the same distance from q at its nearest neighbor, given q and the locality preserving hash function h chosen randomly from the hash family. precisely, we show that if the entropy i(h(p)|q, h) = m and g is a bound on the probability that two far-off points will hash to the same bucket, then we can find the approximate nearest neighbor in o(np) time and near linear &otilde;(n) space where p = m/log(1/g). alternatively we can build a data structure of size &otilde;(n1/(1-p)) to answer queries in &otilde;(d) time. by applying this analysis to the locality preserving hash functions in [17, 21, 6] and adjusting the parameters we show that the c nearest neighbor can be computed in time &otilde;(np) and near linear space where p &ap; 2.06/c as c becomes large.
game theory, algorithms, and the internet. among the many characteristics of the internet (huge and growing, available and unstructured, dynamic and chaotic), perhaps the most novel, distinguishing, and intellectually challenging one is that, unlike previous computational artifacts and systems, the internet is built, operated, and used by a dazzling diversity of economic interests, in various degrees of collaboration and competition with each other. consequently, it can be argued that the mathematical arsenal necessary for attaining an algorithmic and conceptual understanding of the internet must include some kind of fusion between mathematical economics (especially game theory and its inverse problem, mechanism design) and algorithmic thinking. in this talk i shall survey recent formalisms and results aiming in this general direction, and discuss the research agenda that appears to be emerging.
the vertex-disjoint menger problem in planar graphs. we consider the problem of finding a maximum collection of vertex-disjoint paths in undirected, planar graphs from a vertex $s$ to a vertex $t$. this problem is usually solved using flow techniques, which lead to ${\cal o}(nk)$ and ${\cal o}(n\sqrt{n})$ running times, respectively, where $n$ is the number of vertices and $k$ the maximum number of vertex-disjoint $(s,t)$-paths. the best previously known algorithm is based on a divide-and-conquer approach and has running time ${\cal o}(n\log n)$. the approach presented here is completely different from these methods and yields a linear-time algorithm.
computing equilibria in multi-player games. we initiate the systematic study of algorithmic issues involved in finding equilibria (nash and correlated) in games with a large number of players; such games, in order to be computationally meaningful, must be presented in some succinct, game-specific way. we develop a general framework for obtaining polynomial-time algorithms for optimizing over correlated equilibria in such settings, and show how it can be applied successfully to symmetric games (for which we actually find an exact polytopal characterization), graphical games, and congestion games, among others. we also present complexity results implying that such algorithms are not possible in certain other such games. finally, we present a polynomial-time algorithm, based on quantifier elimination, for finding a nash equilibrium in symmetric games when the number of strategies is relatively small.
multi-dimensional online tracking. we propose and study a new class of online problems, which we call online tracking. suppose an observer, say alice, observes a multi-valued function f: z+ &rarr; zd overtime in an online fashion, i.e., she only sees f(t) for t &le; tnow where tnow is the current time. she would like to keep a tracker, say bob, informed of the current value of f at all times. under this setting, alice could send new values of f to bob from time to time, so that the current value of f is always within a distance of &delta; to the last value received by bob. we give competitive online algorithms whose communication costs are compared with the optimal offline algorithm that knows the entire f in advance. we also consider variations of the problem where alice is allowed to send "predictions" to bob, to further reduce communication for well-behaved functions. these online tracking problems have a variety of application ranging from sensor monitoring, location-based services, to publish/subscribe systems.
the complexity of low-distortion embeddings between point sets. we prove that it is np-hard to approximate by a ratio better than 3 the minimum distortion of a bijection between two given finite three-dimensional sets of points.
a faster and simpler fully dynamic transitive closure. we obtain a new fully dynamic algorithm for maintaining the transitive closure of a directed graph. our algorithm maintains the transitive closure matrix in a total running time of o(mn &plus; (ins &plus; del) &middot; n2), where ins (del) is the number of insert (delete) operations performed. here n is the number of vertices in the graph and m is the initial number of edges in the graph. obviously, reachability queries can be answered in constant time. the algorithm uses only o(n2) time which is essentially optimal for maintaining the transitive closure matrix. our algorithm can also support path queries. if v is reachable from u, the algorithm can produce a path from u to v in time proportional to the length of the path. the best previously known algorithm for the problem is due to demetrescu and italiano [2000]. their algorithm has a total running time of o(n3 &plus; (ins &plus; del) &middot; n2). the query time is also constant. in addition, we also present a simple algorithm for directed acyclic graphs (dags) with a total running time of o(mn &plus; ins &middot; n2 &plus; del). our algorithms are obtained by combining some new ideas with techniques of italiano [1986, 1988], king [1999], king and thorup [2001] and frigioni et al. [2001]. we also note that our algorithms are extremely simple and can be easily implemented.
a new and simple algorithm for quality 2-dimensional mesh generation. we present a simple new algorithm for triangulating polygons and planar straightline graphs. it provides "shape" and "size" guarantees: -all triangles have a bounded aspect ratio. - the number of "steiner points" added is within a constant factor of optimal. such "quality" triangulations are desirable as meshes for the finite element method, in which the running time generally increases with the number of triangles, and where the convergence and stability may be hurt by very skinny triangles. the technique we use--successive refinement of the delaunay triangulation--extends a mesh generation technique of chew by allowing triangles that vary in size. previous algorithms with shape and size bounds have all been based on quadtrees. the delaunay refinement algorithm matches their bounds, but uses a fundamentally different approach. it is much simpler, and hence easier to implement, and it generally produces smaller meshes in practice.
edge dominating and hypomatchable sets. the weighted edge dominating set problem (eds) generalizes both the weighted vertex cover problem and the problem of covering the edges of graph by a minimum cost set of both vertices and edges. although eds was proven np-complete in 1980, not much progress had been made in improving its approximability to match that of weighted vertex cover until 2000. in this paper we develop a 2-approximation for weighted eds by honing the technique of a recent 2 1/10-approximation which exploits the close polyhedral relationship between eds and the edge cover problem. for the sake of completeness we also present a new direct proof of edmonds and johnson's characterization of the edge cover polyhedron. our approximation guarantee is tight in the sense that the existence of a (2-&epsilon;)-approximation for weighted eds for some constant, &epsilon; would imply a (2-&epsilon;)-approximation for weighted vertex cover, constituting a major breakthrough in the field.
succinct representations of lcp information and improvements in the compressed suffix arrays. we introduce two succinct data structures to solve various string problems. one is for storing the information of lcp, the longest common prefix, between suffixes in the suffix array, and the other is an improvement in the compressed suffix array which supports linear time counting queries for any pattern. the former occupies only 2n + o(n) bits for a text of length n for computing lcp between adjacent suffixes in lexicographic order in constant time, and 6n + o(n) bits between any two suffixes. no data structure in the literature attained linear size. the latter has size proportional to the text size and it is applicable to texts on any alphabet &sigma; such that |&sigma;| = logo(1) n. these space-economical data structures are useful in processing huge amounts of text data.
towards a complete characterization of tries. tries and suffix trees are the most popular data structures on words. tries were introduced in 1960 by fredkin as an efficient method for searching and sorting digital data. since then myriad of novel trie applications were found such as dynamic hashing, conflict resolution algorithms, leader election algorithms, ip addresses lookup, coding, polynomial factorization, lempel-ziv compression schemes, and so on. furthermore, various analyses of tries reveal new fundamental properties of strings appearing in those applications. parameters of interest are the (partial) fillup level (the largest full level of the trie), shortest path, height (longest path), typical depth, and path length (sum of depths). all of these parameters are analyzed here in a unifying manner by studying the external and internal profiles. a profile of a tree at level k is the number of nodes (internal or external) at level k. we derive recurrences for both profiles and solve them asymptotically for various ranges of k when the strings stored in the trie are generated by a memoryless source (extension to a markov source is possible). in particular, we present asymptotic results for the average profile, the variance and the limiting distribution. as consequences we find the height, shortest path, fillup level, and the depth. these results are derived here by methods of analytic algorithmics such as generating functions, mellin transform, poissonization and depoissonization, and the saddle point method.
squeezing succinct data structures into entropy bounds. consider a sequence s of n symbols drawn from an alphabet a = {1, 2,. . .,&sigma;}, stored as a binary string of nlog &sigma; bits. a succinct data structure on s supports a given set of primitive operations on s using just f (n) = o(n log &sigma;) extra bits. we present a technique for transforming succinct data structures (which do not change the binary content of s) into compressed data structures using nhk + f(n) + o(n log &sigma; + log log&sigma; n + k)/ log&sigma; n) bits of space, where hk &le; log &sigma; is the kth-order empirical entropy of s. when k + log &sigma; = o(log n), we improve the space complexity of the succinct data structure from n log &sigma; + o(n log &sigma;) to n hk + o(nlog &sigma;) bits by keeping s in compressed format, so that any substring of o(log &sigma; n) symbols in s (i.e. o(log n) bits) can be decoded on the fly in constant time. thus, the time complexity of the supported operations does not change asymptotically. namely, if an operation takes t(n) time in the succinct data structure, it requires o(t(n)) time in the resulting compressed data structure. using this simple approach we improve the space complexity of some of the best known results on succinct data structures we extend our results to handle another definition of entropy.
optimal binary space partitions for orthogonal objects. a binary space partition, or bsp is a scheme for recursively dividing a configuration of objects by hyperplanes until all objects are separated. bsps are widely used in computer graphics as the underlying data structure for computations such as real-time hidden-surface removal, ray tracing, and solid modelling. in these applications, the computational cost is directly related to the size of the bsp, ie the toal number of fragments of the objects generated by the partition. until recently, the question of minimizing the size of bsps for given inputs had been studied only empirically. we concentrate here on ortogonal objects, a case which arises frequently in practice and deserves special attention. we construct bsps of linear size for any set of orthogonal line segments in the plane. in three dimensions, bsps of size o(n^1.5) for any set of n mutually orthogonal line segments or rectangles are constructed. these bounds are optimal and may be contrasted with the omega(n^2) bound for general polygonal objects in r^3.
overhang. how far off the edge of the table can we reach by stacking n identical blocks of length 1? a classical solution achieves an overhang of 1/2hn, where hn = &sigma;ni=1 1/i ~ ln n is the nth harmonic number, by stacking all the blocks one on top of another with the ith block from the top displaced by 1/2i beyond the block below. this solution is widely believed to be optimal. we show that it is exponentially far from optimal by giving explicit constructions with an overhang of &omega;(n1/3). we also prove some upper bounds on the overhang that can be achieved. the stability of a given stack of blocks corresponds to the feasibility of a linear program and so can be efficiently determined.
lower bounds for collusion-secure fingerprinting. collusion-secure fingerprinting codes are an important primitive used by many digital watermarking schemes [1, 10, 9]. boneh and shaw [3] define a model for these types of codes and present an explicit construction. their code has length o(c3 log(l/&epsilon;)) and attains security against coalitions of size c with &epsilon; error. boneh and shaw also present a lower bound of &omega; (c3log(1/c&epsilon;)) on the length of any collusion-secure code.we give new lower bounds on the length of collusion-secure codes by analyzing a weighted coinflipping strategy for the coalition. as an illustration of our methods, we give a simple proof that the boneh-shaw construction cannot be asymptotically improved. next, we prove a general lower bound: no secure code can have length o(c21og(1/c&epsilon;)), which improves the previous known bound by a factor of c. in particular, we show that any secure code will have length &omega;(c2 log(1/c&epsilon;)) as long as log(l/&epsilon;) &ge; k k log c, where k is a constant and k is the number of columns in the code (in some sense, a measure of the code's complexity). finally, we describe a general paradigm for constructing fingerprinting codes which encompasses the construction of [3], and show that no secure code that follows this paradigm can have length o((c3/log c) log(1/c&epsilon;)) follows this (again, by showing a lower bound for large values of ln(1/&epsilon;)). this suggests that any attempts at improvement should be directed toward techniques that lie outside our paradigm.
randomizing combinatorial algorithms for linear programming when the dimension is moderately high. in the last decade researchers in computational geometry have produced a series of algorithms for linear programming, based on a randomized combinatorial approach, which are tuned for linear programs where the number of variables d is small compared to the number n of constraints, although not so small to be considered a constant of the problem. one natural question is how practical are these algorithms for classes of lp instances not necessarily derived from problems in computational geometry. in this paper, building within the randomized combinatorial approach, we propose two algorithms for linear programming and we give evidence of their empirical running times on several classes of randomly generated instances. comparisons with state of the art free software (lp-solve) and state of the art commercial software (cplex) lead to the conclusion that the randomized combinatorial approach for systems with n &ap; d, at the present state of our research, can be competitive for dense systems and for sparse systems where a large fraction of the constraints are equalities. we also consider the case of dense systems where n > > d, which is typical in instances from computational geometry problems, for which we improve upon recent results of g&auml;tner and sch&ouml;nherr [13].
reconciling simplicity and realism in parallel disk models. for the design and analysis of algorithms that process huge data sets, a machine model is needed that handles parallel disks. there seems to be a dilemma between simple and flexible use of such a model and accurate modelling of details of the hardware. this paper explains how many aspects of this problem can be resolved. the programming model implements one large logical disk allowing concurrent access to arbitrary sets of variable size blocks. this model can be implemented efficienctly on multiple independent disks even if zones with different speed, communication bottlenecks and failed disks are allowed. these results not only provide useful algorithmic tools but also imply a theoretical justification for studying external memory algorithms using simple abstract models. the algorithmic approach is random redundant placement of data and optimal scheduling of accesses. the analysis generalizes a previous analysis for simple abstract external memory models in several ways (higher efficiency, variable block sizes, more detailed disk model). as a side effect, an apparently new chernoff bound for sums of weighted 0-1 random variables is derived.
an asymptotic approximation scheme for multigraph edge coloring. the edge coloring problem considers the assignment of colors from a minimum number of colors to edges of a graph such that no two edges with the same color are incident to the same node. we give polynomial time algorithms for approximate edge coloring of multigraphs, that is, parallel edges are allowed. the best previous algorithms achieve a fixed constant approximation factor plus a small additive offset. one of our algorithms achieves solution quality opt &plus; &sqrt;9opt/2 and has execution time polynomial in the number of nodes and the logarithm of the maximum edge multiplicity.
an experimental study of lp-based approximation algorithms for scheduling problems. recently there has been much progress on the design of approximation algorithms for a variety of scheduling problems in which the goal is to minimize the average weighted completion time of the jobs scheduled. many of these approximation algorithms have been inspired by polyhedral formulations of the scheduling problems and their use in computing optimal solutions to small instances. in this paper we demonstrate that the progress in the design and analysis of approximation algorithms for these problems also yields techniques with improved computational efficacy. specifically, we give a comprehensive experimental study of a number of these approximation algorithms for 1|rj|∑wjcj, the problem of scheduling jobs with release dates on one machine so as to minimize the average weighted completion time of the jobs scheduled. we study both the quality of lower bounds given for this problem by different linear-programming relaxations and combinatorial relaxations, and the quality of upper bounds delivered by a number of approximation algorithms based on them. the best algorithms, on almost all instances, come within a few percent of the optimal average weighted completion time. furthermore, we show that this can usually be achieved with o(n log n) computation. in addition we observe that on most kinds of synthetic data used in experimental studies a simple greedy heuristic, used in successful combinatorial branch-and-bound algorithms for the problem, outperforms (on average) all of the lp-based heuristics. we identify, however, other classes of problems on which the lp-based heuristics are superior and report on experiments that give a qualitative sense of the range of dominance of each. we consider the impact of local improvement on the solutions as well. we also consider the performance of the algorithms for the average weighted flow-time criterion, which, although equivalent to average weighted completion time at optimality, is provably much harder to approximate. nonetheless, we demonstrate that for most instances we consider that the algorithms give very good results for this criterion as well. finally, we extend the techniques to a rather different and more complex problem that arises from an actual manufacturing application: resource-constrained project scheduling. in this setting as well, the techniques yield algorithms with improved performance; we give the best-known solutions for a set of instances provided by basf ag, germany.
buffer minimization using max-coloring. given a graph g = (v,e) and positive integral vertex weights w : v &rarr; n, the max-coloring problem seeks to find a proper vertex coloring of g whose color classes c1, c2,...,ck, minimize &sigma;ki = 1 max&nu;&isin;ciw(&nu;). this problem, restricted to interval graphs, arises whenever there is a need to design dedicated memory managers that provide better performance than the general purpose memory management of the operating system. specifically, companies have tried to solve this problem in the design of memory managers for wireless protocol stacks such as gprs or 3g.though this problem seems similar to the wellknown dynamic storage allocation problem, we point out fundamental differences. we make a connection between max-coloring and on-line graph coloring and use this to devise a simple 2-approximation algorithm for max-coloring on interval graphs. we also show that a simple first-fit strategy, that is a natural choice for this problem, yields a 10-approximation algorithm. we show this result by proving that the first-fit algorithm for on-line coloring an interval graph g uses no more than 10.x(g) colors, significantly improving the bound of 26.x(g) by kierstead and qin (discrete math., 144, 1995). we also show that the max-coloring problem is np-hard.
online paging with arbitrary associativity. we tackle the problem of online paging on two level memories with arbitrary associativity (including victim caches, skewed caches etc.). we show that some important classes of paging algorithms are not competitive on a wide class of associativities (even with arbitrary resource augmentation) and that although some algorithms designed for full associativity are actually competitive on any two level memory, the myopic behavior of paging algorithms designed for full associativity will generally result in very poor performance at least for some "associativity topologies". at the same time we present a simple and yet powerful technique that allows us to overcome this shortcoming, generalizing algorithms designed for full associativity into practical algorithms which are efficient on two level memories with arbitrary associativity. we identify a simple topological parameter, pseudo associativity, which characterizes the competitive ratio achievble on any two level memory, giving a lower bound on the competitiveness achievable by any paging algorithm and matching it within a factor 4 with a novel algorithm.
chernoff-hoeffding bounds for applications with limited independence. chernoff-hoeffding (ch) bounds are fundamental tools used in bounding the tail probabilities of the sums of bounded and independent random variables (r.v.'s). we present a simple technique that gives slightly better bounds than these and that more importantly requires only limited independence among the random variables, thereby importing a variety of standard results to the case of limited independence for free. additional methods are also presented, and the aggregate results are sharp and provide a better understanding of the proof techniques behind these bounds. these results also yield improved bounds for various tail probability distributions and enable improved approximation algorithms for jobshop scheduling. the limited independence result implies that a reduced amount and weaker sources of randomness are sufficient for randomized algorithms whose analyses use the ch bounds, e.g., the analysis of randomized algorithms for random sampling and oblivious packet routing.
computing shortest paths with comparisons and additions. we present an undirected all-pairs shortest paths (apsp) algorithm which runs on a pointer machine in time o(mn&alpha;(m,n)) while making o(mnlog &alpha;(m, n)) comparisons and additions, where m and n are the number of edges and vertices, respectively, and &alpha;(m, n) is tarjan's inverse-ackermann function. this improves upon all previous comparison & addition-based apsp algorithms when the graph is sparse, i.e., when m = o(n log n).at the heart of our apsp algorithm is a new single-source shortest paths algorithm which runs in time o(m&alpha;(m, n) + n log log r) on a pointer machine, where r is the ratio of the maximum-to-minimum edge length. so long as r < 2no(1) this algorithm is faster than any implementation of dijkstra's classical algorithm in the comparison-addition model.for directed graphs we give an o(m + n log r)-time comparison & addition-based sssp algorithm on a pointer machine. similar algorithms assuming integer weights or the ram model were given earlier.
minimizing randomness in minimum spanning tree, parallel connectivity, and set maxima algorithms. there are several fundamental problems for which there are optimal randomized algorithms, but whose deterministic complexity remains unresolved. among such problems are the minimum spanning tree problem, the set maxima problem, the problem of computing connected components and (minimum) spanning trees in parallel and the problem of performing sensitivity analysis on shortest path trees and minimum spanning trees. for each of these problems there is an optimal randomized algorithm which uses a linear number of random bits. we propose new algorithms (or adapt old ones) for these problems which preserve optimality while saving an exponential number of random bits. in the case of computing minimum spanning trees and mst/sssp sensitivity analysis, we reduce the dependence on randomness to log* n random bits.we also consider the problem of selection, for which we give two algorithms which make an expected 1.5n + o(n) comparisons; one uses o(log n) random bits and is uniform, the other uses o(log log n) random bits and is non-uniform.
depth optimal sorting networks resistant to k passive faults. we study the problem of constructing a sorting network that is tolerant to faults and whose running time (i.e., depth) is as small as possible. we consider the scenario of worst-case comparator faults and follow the model of passive comparator failure proposed by yao and yao siam j. comput., 14 (1985), pp. 120--128], in which a faulty comparator outputs its inputs directly without comparison. our main result is the first construction of an n-input k-fault-tolerant sorting network with an asymptotically optimal depth $\theta$(log n + k). that improves over the result of leighton and ma [proceedings of the 5th annual acm symposium on parallel algorithms and architectures, velen, germany, 1993, acm, new york, pp. 30--41], whose network is of depth o(log n + klog\frac{log n}{log k})$.actually, we present a fault-tolerant correction network that can be added after any n-input sorting network to correct its output in the presence of at most k faulty comparators. since the depth of the network is o(log n + k) and the constants hidden behind the "o" notation are small, the construction can be of practical use.developing the techniques necessary to show the main result, we construct a fault-tolerant network for the insertion problem. as a by-product, we get an n-input o(log n)-depth insert-network that is tolerant to random faults, thereby answering a question posed by ma in his ph. d. thesis [fault-tolerant sorting network, department of mathematics, massachusetts institute of technology, cambridge, ma, 1994].the results are based on a new notion of constant delay comparator networks, that is, networks in which each register is used (compared) only in a period of time of a constant length. copies of such networks can be pipelined with only a constant increase in the total depth per copy.
new bounds for multi-dimensional packing. new upper and lower bounds are presented for a multi-dimensional generalization of bin packing called box packing.several variants of this problem, including bounded space box packing, square packing, variable sized box packing and resource augmented box packing are also studied. the main results, stated for d = 2, are as follows: a new upper bound of 2.66013 for online box packing, a new 14/9 + &epsilon; polynomial time offline approximation algorithm for square packing, a new upper bound of 2.43828 for online square packing, a new lower bound of 1.62176 for online square packing, a new lower bound of 2.28229 for bounded space online square packing and a new upper bound of 2.32571 for online two-sized box packing.
minimum moment steiner trees. for a rectilinear steiner tree t with a root, define its k-th momentmk(t)= &int;t(dt(u))kduwhere the integration is over all edges of t, dt (u) is the length of the unique path in t from the root to u, and du is the incremental edge length. given a set of points p in the plane, a k-th moment steiner minimum tree (k-smt) is a rectilinear steiner tree that has the minimum k-th moment among all rectilinear steiner trees for p, with the origin as the root. the definition is a natural extension of the traditional steiner minimum tree, and motivated by application in vlsi routing. in this paper properties of the k-smt are studied and approximation algorithms are presented.
undiscretized dynamic programming: faster algorithms for facility location and related problems on trees. in the uncapacitated facility location (ufl) problem, there is a fixed cost for opening a facility, and some distance matrix d that determines the cost of distributing commodities from any facility i to any consumer j. the problem is np-hard in general and when d consists of a distance metric in a graph [7, 12]. however, for the case where the commodity transportation costs are given by path lengths in a tree, an o(n2) dynamic programming algorithm was given by [4, 7]. we improve this dynamic programming algorithm by using the geometry of piecewise linear functions and fast merging of the binary search trees used to store these functions. we achieve the complexity bound of o(n log n) for the tree location problem and some related problems. our approach gives a general method for solving tree dynamic programming problems.
distributed online call control on general networks. we study the problem of online call admission and routing ("call control") on general networks. we give new algorithms that with high probability achieve a poly-logarithmic fraction (in the size of the network) of the optimal solution. the decisions of our algorithms do not depend on the current load of all network links, as in previous algorithms for general network topologies [aap93]. instead, their admission decisions depend only on link loads along a single path between the communicating parties, and they can thus be performed in a distributed hop-by-hop manner through the network. furthemore, our algorithms can handle concurrent requests in the network.
minimizing capacity violations in a transshipment network. the problem of minimizing capacity violation is a variation of the transshipment problem. it is equivalent to the problem of computing maximum mean surplus cuts which arises in the dual approach to the minimum cost network circulation problem. mccormick and ervolina [15] proposed an algorithm which computes a sequence of cuts with increasing mean surpluses, and stops when an optimal one is found. the mean surplus of this cut is equal to the minimum possible maximum capacity violation. mccormick and ervolina proved that the number of iterations in this algorithm is o(m). one iteration, i.e., finding the subsequent cut, amounts to computing maximum flow in an appropriate network. we prove that the number of iterations in this algorithm is &thgr;(n). this gives the best known upper bound o(n2m) for the problem. we also show a tight analysis of this algorithm for the case with integral capacities and demands, and present some improvements.
the interface between computational and combinatorial geometry. we illustrate the rich interface between computational and combinatorial geometry by a series of examples, including k-sets, randomized incremental algorithms, random sampling and partitioning, and analysis of geometric arrangements.
roundtrip spanners and roundtrip routing in directed graphs. we introduce the notion of roundtrip-spanners of weighted directed graphs and describe efficient algorithms for their construction. we show that for every integer k &ge; 1 and any &epsi; > 0, any directed graph on n vertices with edge weights in the range [1, w] has a (2k + &epsi;)-roundtrip-spanner with o(min{(k2/&epsi;) n1 + 1/k (log(nw), (k/&epsi;)2 n1 + 1/k,(log n)2&minus;1/k}) edges. we then extend these constructions and obtain compact roundtrip routing schemes. for every integer k &ge; 1 and every &epsi; > 0, we describe a roundtrip routing scheme that has stretch 4k + &epsi;, and uses at each vertex a routing table of size &otilde;((k2/&epsi;)n1/k log(nw)). we also show that any weighted directed graph with arbitrary/ positive edge weights has a 3-roundtrip-spanner with o(n3/2) edges. this result is optimal. finally, we present a stretch 3 roundtrip routing scheme that uses local routing tables of size &otilde;(n1/2). this routing scheme is essentially optimal. the roundtrip-spanner constructions and the roundtrip routing schemes for directed graphs that we describe are only slightly worse than the best available spanners and routing schemes for undirected graphs. our roundtrip routing schemes substantially improve previous results of cowen and wagner. our results are obtained by combining ideas of cohen, cowen and wagner, thorup and zwick, with some new ideas.
ray shooting amid balls, farthest point from a line, and range emptiness searching. in the range emptiness searching problem, we are given a set p of n points in rd, and wish to preprocess them into a data structure that supports efficient range emptiness queries, in which we specify a range &sigma;, which is a semi-algebraic set in rd of some fixed kind, and wish to determine whether p &cap; &sigma; = &theta;. range emptiness searching arises in many applications, and has been treated by matou&scaron;ek [15] in the special case where the ranges are halfspaces bounded by hyperplanes. in this paper we extend the analysis to the general semi-algebraic case, and show how to adapt matou&scaron;ek's technique to this case, without the need to linearize the ranges into a higher-dimensional space. this yields more efficient solutions to several interesting problems, and we demonstrate the new technique in two applications:(i) an algorithm for ray shooting amid balls in r3, which uses o* (n) storage and preprocessing, and answers a query in o* (n2/3) time, improving the previous bound of o* (n3/47).(ii) an algorithm that preprocesses, in o*(n) time, a set p of n points in r3 into a data structure with o*(n) storage, so that, for any query line l or segment e, the point of p farthest from l or from e can be computed in o* (n1/2) time.our technique is closely related to the notions of nearest- or farthest-neighbor generalized voronoi diagrams, and of the union or intersection of geometric objects, where sharper bounds on the combinatorial complexity of these structures yield faster range emptiness searching algorithms. for example, in the case of ray shooting amid balls, the structure that arises in our algorithm is the euclidean voronoi diagram of lines in 3-space, and the performance of the algorithm depends on the complexity of such diagrams (for which tight bounds are still unknown).
on the number of crossing-free matchings, (cycles, and partitions). we show that a set of $n$ points in the plane has at most $o(10.05^n)$ perfect matchings with crossing-free straight-line embedding. the expected number of perfect crossing-free matchings of a set of $n$ points drawn independently and identically distributed from an arbitrary distribution in the plane is at most $o(9.24^n)$. several related bounds are derived: (a) the number of all (not necessarily perfect) crossing-free matchings is at most $o(10.43^n)$. (b) the number of red-blue perfect crossing-free matchings (where the points are colored red or blue and each edge of the matching must connect a red point with a blue point) is at most $o(7.61^n)$. (c) the number of left-right perfect crossing-free matchings (where the points are designated as left or right endpoints of the matching edges) is at most $o(5.38^n)$. (d) the number of perfect crossing-free matchings across a line (where all the matching edges must cross a fixed halving line of the set) is at most $4^n$. these bounds are employed to infer that a set of $n$ points in the plane has at most $o(86.81^n)$ crossing-free spanning cycles (simple polygonizations) and at most $o(12.24^n)$ crossing-free partitions (these are partitions of the point set so that the convex hulls of the individual parts are pairwise disjoint). we also derive lower bounds for some of these quantities.
robust algorithms for restricted domains. we introduce a new definition of efficient algorithms for restricted domains. under this definition, an algorithm is required to be "robust," i.e., it must produce correct output regardless of whether the input actually belongs to the restricted domain or not. this is to be contrasted with the "promise" version of solving problems on restricted domains, in which there is a guarantee that the input is in the class, and an algorithm to "solve" the problem need not function correctly or even terminate if this guarantee is not met. there exist problems that have a polynomial time promise solution, while being np-hard if required to be robust. we show perhaps the surprising result that robustly finding a maximum independent set in a well-covered graph (i.e., a graph in which every maximal independent set is of the same size) is np-hard. an argument can be made that this hardness result is more meaningful than the trivial polynomial time promise algorithm. we give a polynomial time robust algorithm for the maximum clique problem in unit disk graphs, i.e., given an input graph g in general form, the output is either a maximum clique for g or a certificate that g is not a unit disk graph. the existence of this algorithm is to be reconciled with the apparent contradiction posed by the facts: (1) recognizing whether an input graph given in general form is a unit disk graph is np-hard; in fact, it is not even known to be in np. (2) finding a maximum clique in an input graph given in general form is np-hard.
pursuit-evasion with imprecise target location. we consider a game between two persons where one person tries to chase the other, but the pursuer only knows an approximation of the true position of the fleeing person. the two players have identical constraints on their speed. it turns out that the fugitive can increase his distance from the pursuer beyond any limit. however, when the speed constraints are given by a polyhedral metric, the pursuer can always remain within a constant distance of the other person.we apply this problem to buffer minimization in an online scheduling problem with conflicts.
improved approximation bound for quadratic optimization problems with orthogonality constraints. in this paper we consider the problem of approximating a class of quadratic optimization problems that contain orthogonality constraints, i.e. constraints of the form xtx = i, where x &epsilon; rm x n is the optimization variable. this class of problems, which we denote by (qp--oc), is quite general and captures several well--studied problems in the literature as special cases. in a recent work, nemirovski [17] gave the first non--trivial approximation algorithm for (qp--oc). his algorithm is based on semidefinite programming and has an approximation guarantee of o ((m + n)1/3). we improve upon this result by providing the first logarithmic approximation guarantee for (qp--oc). specifically, we show that (qp--oc) can be approximated to within a factor of o(ln (max{m, n})). the main technical tool used in the analysis is the so--called non--commutative khintchine inequality, which allows us to prove a concentration inequality for the spectral norm of a rademacher sum of matrices. as a by-product, we resolve in the affirmative a conjecture of nemirovski concerning the typical spectral norm of a sum of certain random matrices. the aforementioned concentration inequality also has ramifications in the design of so-called safe tractable approximations of chance constrained optimization problems. in particular, we use it to simplify and improve a recent result of ben--tal and nemirovski [4] concerning certain chance constrained linear matrix inequality systems.
region-fault tolerant geometric spanners. we introduce the concept of region-fault tolerant spanners for planar point sets and prove the existence of region-fault tolerant spanners of small size. for a geometric graph $\mathcal{g}$on a point set p and a region&#x00a0;f, we define $\mathcal{g}\ominus f$to be what remains of $\mathcal{g}$after the vertices and edges of $\mathcal{g}$intersecting&#x00a0;f have been removed. a&#x00a0; $\mathcal{c}$-fault tolerant t-spanner is a geometric graph&#x00a0; $\mathcal{g}$on&#x00a0;p such that for any convex region&#x00a0;f, the graph $\mathcal{g}\ominus f$is a t-spanner for $\mathcal{g}_{c}(p)\ominus f$, where $\mathcal{g}_{c}(p)$is the complete geometric graph on p. we prove that any set&#x00a0;p of n points admits a $\mathcal{c}$-fault tolerant (1+&#x03b5;)-spanner of size $\mathcal{o}(n\log n)$for any constant &#x03b5;>0; if adding steiner points is allowed, then the size of the spanner reduces to&#x00a0; $\mathcal{o}(n)$, and for several special cases, we show how to obtain region-fault tolerant spanners of $\mathcal{o}(n)$size without using steiner points. we also consider fault-tolerant geodesic t -spanners: this is a variant where, for any disk&#x00a0;d, the distance in $\mathcal{g}\ominus d$between any two points u,v&#x2208;p&#x2216;d is at most&#x00a0;t times the geodesic distance between u and v in &#x211d;2&#x2216;d. we prove that for any&#x00a0;p, we can add $\mathcal{o}(n)$steiner points to obtain a fault-tolerant geodesic (1+&#x03b5;)-spanner of size&#x00a0; $\mathcal{o}(n)$.
compressed counting. we propose compressed counting (cc) for approximating the &alpha;th frequency moments (0 < &alpha; &le; 2) of data streams under a relaxed strict-turnstile model, using maximally-skewed stable random projections. estimators based on the geometric mean and the harmonic mean are developed. when &alpha; = 1, a simple counter suffices for counting the first moment (i.e., sum). the geometric mean estimator of cc has asymptotic variance &alpha; &delta; = |&alpha; - 1|, capturing the intuition that the complexity should decrease as &delta; = |&alpha; - 1| &rarr; 0. however, the previous classical algorithms based on symmetric stable random projections[12, 15] required o (1/&epsilon;2) space, in order to approximate the &alpha;th moments within a 1 + &epsilon; factor, for any 0 < &alpha; &le; 2 including &alpha; = 1. we show that using the geometric mean estimator, cc requires o [equation] space, as &delta; &rarr; 0. therefore, in the neighborhood of &alpha; = 1, the complexity of cc is essentially o (1/&epsilon;) instead of o (1/&epsilon;2). cc may be useful for estimating shannon entropy, which can be approximated by certain functions of the &alpha;th moments with &alpha; &rarr; 1. [10, 9] suggested using &alpha; = 1 + &delta; with (e.g.,) &delta; < 0.0001 and &epsilon; < 10&minus;7, to rigorously ensure reasonable approximations. thus, unfortunately, cc is "theoretically impractical" for estimating shannon entropy, despite its empirical success reported in [16].
emulations between qsm, bsp, and logp: a framework for general-purpose parallel algorithm design. we present work-preserving emulations with small slowdown between logp and two other parallel models: bsp and qsm. in conjunction with earlier work-preserving emulations between qsm and bsp, these results establish a close correspondence between these three general-purpose parallel models. our results also correct and improve on results reported earlier on emulations between bsp and logp. in particular we shed new light on the relative power of stalling and non-stalling logp models.the qsm is a shared-memory model with only two parameters--p, the number of processors, and g, a bandwidth parameter. the simplicity of the qsm parameters makes qsm a convenient model for parallel algorithm design, and simple work-preserving emulations of qsm on bsp and qsm on logp show that algorithms designed for the qsm will also map quite well to these other models. the simplicity and generality of qsm present a strong case for the use of qsm as the model of choice for parallel algorithm design.we present qsm algorithms for three basic problems--prefix sums, sample sort and list ranking. we show that these algorithms are optimal in terms of both the total work performed and the number of 'phases' for input sizes of practical interest. for prefix sums, we present a matching lower bound that shows our algorithm to be optimal over the complete range of these parameters. we then examine the predicted and simulated performance of these algorithms. these results suggest that qsm analysis will predict algorithm performance quite accurately for problem sizes that arise in practice.
strictly convex drawings of planar graphs. every three-connected planar graph with n vertices has a drawing on an o(n7/3) &times; o(n7/3) grid in which all faces are strictly convex polygons.
the rectilinear steiner arborescence problem is np-complete. given a set of points in the first quadrant, a rectilinear steiner arborescence (rsa) is a directed tree rooted at the origin, containing all points, and composed solely of horizontal and vertical edges oriented from left to right, or from bottom to top. the complexity of finding an rsa with the minimum total edge length for general planar point sets has been a well-known open problem in algorithm design and vlsi routing. in this paper, we prove the problem is np-complete in the strong sense.
succinct indexable dictionaries with applications to encoding k-ary trees and multisets. we consider the indexable dictionary problem which consists in storing a set s &sube; {0,&hellip;, m - 1} for some integer m, while supporting the operations of rank(x), which returns the number of elements in s that are less than x if x &epsilon; s, and -1 otherwise; and select(i) which returns the i-th smallest element in s.we give a structure that supports both operations in o(1) time on the ram model and requires b(n,m) + o(n) + o(lg lg m) bits to store a set of size n, where b(n,m) = &lceil;lg (nm)&rceil; is the minimum number of bits required to store any n-element subset from a universe of size m. previous dictionaries taking this space only supported (yes/no) membership queries in o(1) time. in the cell probe model we can remove the o(lg lg m) additive term in the space bound, answering a question raised by fich and miltersen, and pagh.we also present two applications of our dictionary structure:&bull; an information-theoretically optimal representation for k-ary cardinal trees (aka k-ary tries). our structure uses c(n,k) + o(n + lg k) bits to store a k-ary tree with n nodes and can support parent, i-th child, child labeled i, and the degree of a node in constant time, where c(n,k) is the minimum number of bits to store any n-node k-ary tree. previous space efficient representations for cardinal k-ary trees required c(n,k) + &omega;(n) bits.&bull; an optimal representation for multisets where (appropriate generalisations of) the select and rank operations can be supported in o(1) time. our structure uses b(n, m + n) + o(n) + o(lg lg m) bits to represent a multiset of size n from an m element set; the first term is the minimum number of bits required to represent such a multiset.
facility location with service installation costs. we consider a generalization of the uncapacitated facility location problem which we call facility location with service installation costs. we are given a set of facilities, f,a set of demands or clients d, and a set of services s. each facility i has a facility opening cost fi, and we have a service installation cost of fli for every facility-service pair (i, l). each client j in d requests a specific service g(j) &isin; s and the cost of assigning a client j to facility i is given by cij. we want to open a set of facilities, install services at the open facilities, and assign each client j to an open facility at which service g(j) is installed, so as to minimize the sum of the facility opening costs, the service installation costs and the client assignment costs.our main result is a primal-dual 6-approximation algorithm under the assumption that there is an ordering on the facilities such that if i comes before i' in this ordering then for every service type l, fli &le; fl i. this includes (as special cases) the settings where the service installation cost fli depends only on the service type l, or depends only on the location i. with arbitrary service installation costs, the problem becomes as hard as the set-cover problem. our algorithm extends the algorithm of jain & vazirani [9] in a novel way. if the service installation cost depends only on the service type and not on the location, we give an lp rounding algorithm that attains an improved approximation ratio of 2.391. the algorithm combines both clustered randomized rounding [6] and the filtering based technique of [10, 14]. we also consider the k-median version of the problem where there is an additional requirement that at most k facilities may be opened. we use our primal-dual algorithm to give a constant-factor approximation for this problem when the service installation cost depends only on the service type.
improved approximation algorithms for shop scheduling problems. in the job shop scheduling problem, there are $m$ machines and $n$ jobs. a job consists of a sequence of operations, each of which must be processed on a specified machine, and the aim is to complete all jobs as quickly as possible. this problem is strongly ${\cal np}$-hard even for very restrictive special cases. the authors give the first randomized and deterministic polynomial-time algorithms that yield polylogarithmic approximations to the optimal length schedule. these algorithms also extend to the more general case where a job is given not by a linear ordering of the machines on which it must be processed but by an arbitrary partial order. comparable bounds can also be obtained when there are $m'$ types of machines, a specified number of machines of each type, and each operation must be processed on one of the machines of a specified type, as well as for the problem of scheduling unrelated parallel machines subject to chain precedence constraints.
slow mixing of glauber dynamics via topological obstructions. many local markov chains based on glauber dynamics are known to undergo a phase transition as a parameter &lambda; of the system is varied. for independent sets on the 2-dimensional cartesian lattice, the gibbs distribution assigns each independent set a weight &lambda;[i], and the markov chain adds or deletes a single vertex at each step, it is believed that there is a critical point &lambda;c &ap; 3.79 such that for &lambda; < &lambda;c, local dynamics converge in polynomial time while for &lambda; > &lambda;c they require exponential time. we introduce a new method for showing slow mixing based on the presence or absence of certain topological obstructions in the independent sets. using elementary arguments, we show that glauber dynamics will be slow for sampling independent sets in 2 dimensions when &lambda; &ge; 8.066, improving on the best known bound by a factor of 10. we also show they are slow on the torus when &lambda; &ge; 6.183.
scheduling precedence-constrained jobs with stochastic processing times on parallel machines. we consider parallel machine scheduling problems where the jobs are subject to precedence constraints, and the processing times of jobs are governed by independent probability distributions. the objective is to minimize the weighted sum of job completion times &sum;, w, c, in expectation, where w, &gne; 0. building upon an lp-relaxation from [3] and an idle time charging scheme from [1], we derive the first approximation algorithms for this model.
distributed approaches to triangulation and embedding. a number of recent papers in the networking community study the distance matrix defined by the node-to-node latencies in the internet and, in particular, provide a number of quite successful distributed approaches that embed this distance into a low-dimensional euclidean space. in such algorithms it is feasible to measure distances among only a linear or near-linear number of node pairs; the rest of the distances are simply not available. moreover, for applications it is desirable to spread the load evenly among the participating nodes. indeed, several recent studies use this 'fully distributed' approach and achieve, empirically, a low distortion for all but a small fraction of node pairs.this is concurrent with the large body of theoretical work on metric embeddings, but there is a fundamental distinction: in the theoretical approaches to metric embeddings, full and centralized access to the distance matrix is assumed and heavily used. in this paper we present the first fully distributed embedding algorithm with provable distortion guarantees for doubling metrics (which have been proposed as a reasonable abstraction of internet latencies), thus providing some insight into the empirical success of the recent vivaldi algorithm [5]. the main ingredient of our embedding algorithm is an improved fully distributed algorithm for a more basic problem of triangulation, where the triangle inequality is used to infer the distances that have not been measured; this problem received a considerable attention in the networking community, and has also been studied theoretically in [19].we use our techniques to extend &isin;-relaxed embeddings and triangulations to infinite metrics and arbitrary measures, and to improve on the approximate distance labeling scheme of talwar [33].
existence theorems, lower bounds and algorithms for scheduling to meet two objectives. we give general results about the existence of schedules which simultaneously minimize two criteria. our results are general in that (i) they apply to any scheduling environment and (ii) they apply to all pairs of metrics in which the first metric is one of maximum flow time, makespan, or maximum lateness and the second metric is one of average flow time, average completion time, average lateness, or number of on-time jobs. for most of the pairs of metrics we consider, we show the existence of near-optimal schedules for both metrics as well as some lower bound results. for some pairs of metrics such as (maximum flow time, average weighted flow time) and (maximum flow time, number of on-time jobs), we prove negative results on the ability to approximate both criteria within a constant factor of optimal. for many other criteria we present lower bounds that match or approach our bicriterion existence results.
approximately covering by cycles in planar graphs. let g = (v(g), e(g)) be a graph and let c be the collection of its cycles. let p: e(g) &rarrtl; z+&ogr;? be a non-negative, integer-valued function on its edge set. the cycle cover problem is the optimization problem of finding a multiset a of cycles of g such that each edge e &isin; e is in at least p(e) of the cycles in a and such that the sum of the lengths of all cycles in a is minimum. we will show how to approximate within a factor of 8 the optimum value of the cycle cover problem for planar graphs in polynomial time.
on the chromatic number of some geometric hypergraphs. a finite family r of simple jordan regions in the plane defines a hypergraph h = h(r) where the vertex set of h is r and the hyperedges are all subsets s &sub; r for which there is a point p such that s = {r &isin; r|p &isin; r. the chromatic number of h(r) is the minimum number of colors needed to color the members of r such that no hyperedge is monochromatic. in this paper we initiate the study of the chromatic number of such hypergraphs. we obtain the following results:(i) any hypergraph that is induced by a family of n simple jordan regions (not necessarily convex) such that the union complexity of any m of them is given by u(m) and u(m)/m is non-decreasing is o(u(n)/n)-colorable. thus, for example we prove that any finite family of pseudodiscs can be colored with a constant number of colors.(ii) any hypergraph induced by a finite family of planar discs is four-colorable. this bound is tight. in fact, we prove that this statement is equivalent to the four-color theorem.(iii) any hypergraph induced by n axis-parallel rectangles is o(log n)-colorable. this bound is asymptotically tight.our proofs are constructive. namely, we provide deterministic polynomial-time algorithms for coloring such hypergraphs with only "few" colors (that is, the number of colors used by these algorithms is upper bounded by the same bounds we obtain on the chromatic number of the given hypergraphs)as an application of (i) and (ii) we obtain simple constructive proofs for the following:(iv) any set of n jordan regions with near linear union complexity admits a conflict-free (cf) coloring with polylogarithmic number of colors.(v) any set of n axis-parallel rectangles admits a cf-coloring with o(log2(n)) colors.
theory of semidefinite programming for sensor network localization. we analyze the semidefinite programming (sdp) based model and method for the position estimation problem in sensor network localization and other euclidean distance geometry applications. we use sdp duality and interior-point algorithm theories to prove that the sdp localizes any network or graph that has unique sensor positions to fit given distance measures. therefore, we show, for the first time, that these networks can be localized in polynomial time. we also give a simple and efficient criterion for checking whether a given instance of the localization problem has a unique realization in $$\mathcal{r}^2$$ using graph rigidity theory. finally, we introduce a notion called strong localizability and show that the sdp model will identify all strongly localizable sub-networks in the input network.
multicommodity facility location. multicommodity facility location refers to the extension of facility location to allow for different clients having demand for different goods, from among a finite set of goods. this leads to several optimization problems, depending on the costs of opening facilities (now a function of the commodities it serves). in this paper, we introduce and study some variants of multicommodity facility location, and provide approximation algorithms and hardness results for them.
a semidefinite programming approach to tensegrity theory and realizability of graphs. recently, connelly and sloughter [14] have introduced the notion of d-realizability of graphs and have, among other things, given a complete characterization of the class of 3-realizable graphs. however, their work has left open the question of finding an algorithm for realizing those graphs. in this paper, we resolve that question by showing that the semidefinite programming (sdp) approach of [11, 32] can be used for realizing 3-realizable graphs. specifically, we use sdp duality theory to show that given a graph g and a set of lengths on its edges, the optimal dual multipliers of a certain sdp give rise to a proper equilibrium stress for some realization of g. using this result and the techniques in [14, 31], we then obtain a polynomial time algorithm for (approximately) realizing 3-realizable graphs. our results also establish a little-explored connection between sdp and tensegrity theories and allow us to derive some interesting properties of tensegrity frameworks.
spanning trees short or small. we study the problem of finding small trees. classical network design problems are considered with the additional constraint that only a specified number $k$ of nodes are required to be connected in the solution. a prototypical example is the $k$mst problem in which we require a tree of minimum weight spanning at least $k$ nodes in an edge-weighted graph. we show that the $k$mst problem is np-hard even for points in the euclidean plane. we provide approximation algorithms with performance ratio $2\sqrt{k}$ for the general edge-weighted case and $o(k^{1/4})$ for the case of points in the plane. polynomial-time exact solutions are also presented for the class of treewidth-bounded graphs, which includes trees, series-parallel graphs, and bounded bandwidth graphs, and for points on the boundary of a convex region in the euclidean plane. we also investigate the problem of finding short trees and, more generally, that of finding networks with minimum diameter. a simple technique is used to provide a polynomial-time solution for finding $k$-trees of minimum diameter. we identify easy and hard problems arising in finding short networks using a framework due to t. c. hu.
allocating vertex pi-guards in simple polygons via pseudo-triangulations. we use the concept of pointed pseudo-triangulations to establish new upper and lower bounds on a well known problem from the area of art galleries: what is the worst case optimal number of vertex &pi;-guards that collectively monitor a simple polygon with n vertices?our results are as follows:1. any simple polygon with n vertices can be mon- itored by at most [n/2] general vertex &pi;-guards. this bound is tight up to an additive constant of 1.2. any simple polygon with n vertices, k of which are convex, can be monitored by at most [(2n -- k)/3] edge-aligned vertex &pi;-guards. this is the first non- trivial upper bound for this problem and it is tight for the worst case families of polygons known so far.
erratum: an approximation algorithm for minimum-cost vertex-connectivity problems. there is an error in our paper "an approximation algorithm for minimum-cost vertex-connectivity problems," which appeared in soda '95 [2] (see also the journal version [3]). below we briefly describe the problem and discuss which of our results can be shown to hold.a complete version of our erratum can be found at www.almaden.ibm.com/cs/people/dpw.
the probabilistic method. the use of randomness is now an accepted tool in theoretical computer science but not everyone is aware of the underpinnings of this methodology in combinatorics - particularly, in what is now called the probabilistic method as developed primarily by paul erdo&huml;s over the past half century. here i will explore a particular set of problems - all dealing with &ldquo;good&rdquo; colorings of an underlying set of points relative to a given family of sets. a central point will be the evolution of these problems from the purely existential proofs of erdo&huml;s to the algorithmic aspects of much interest to this audience.
new approaches to covering and packing problems. covering and packing integer programs model a large family of combinatorial optimization problems. the current-best approximation algorithms for these are an instance of the basic probabilistic method: showing that a certain randomized approach produces a good approximation with positive probability. this approach seems inherently sequential; by employing the method of alteration we present the first rnc and nc approximation algorithms that match the best sequential guarantees. extending our approach, we get the first rnc and nc approximation algorithms for certain multi-criteria versions of these problems. we also present the first nc algorithms for two packing and covering problems that are not subsumed by the above result: finding large independent sets in graphs, and rounding fractional group steiner solutions on trees.
a simple gap-canceling algorithm for the generalized maximum flow problem. we give a simple primal algorithm for the generalized maximum flow problem that repeatedly finds and cancels generalized augmenting paths (gaps). we use ideas of wallacher [26] to find gaps that have a good trade-off between the gain of the gap and the residual capacity of its arcs; our algorithm may be viewed as a special case of wayne's algorithm for the generalized minimum-cost circulation problem [27]. most previous algorithms for the generalized maximum flow problem are dual-based; the few previous primal algorithms (including wayne [27]) require subroutines to test the feasibility of linear programs with two variables per inequality (tvpis). we give an o(mn) time algorithm for finding negative-cost gaps which can be used in place of the tvpi tester. this yields an algorithm with o(m log (mb&epsilon;)) iterations of o(mn) time to compute an &epsilon;-optimal flow, or o(m2 log(mb)) iterations to compute an optimal flow, for an overall running time of o(m3n log(mb)). the fastest known running time for this problem is &otilde;(m2n log b), and is due to radzik [22], building on earlier work of goldfarb, jin, and orlin [14].
how unfair is optimal routing? we are given a network and a rate of traffic between a source node and a destination node, and seek an assignment of traffic to source-destination paths. we assume that each network user controls a negligible fraction of the overall traffic, so that feasible assignments of traffic to paths in the network can be modeled as network flows. we also assume that the time needed to traverse a single link of the network is load-dependent, that is, the common latency suffered by all traffic on the link increases as the link becomes more congested.we consider two types of traffic assignments. in the first, we measure the quality of an assignment by the total latency incurred by network users; an optimal assignment is a feasible assignment that minimizes the total latency. on the other hand, it is often difficult in practice to impose optimal routing strategies on the traffic in a network, leaving network users free to act according to their own interests. we assume that, in the absence of network regulation, users act in a selfish manner. under this assumption, we can expect network traffic to converge to the second type of assignment that we consider, an assignment at nash equilibrium. an assignment is at nash equilibrium if no network user has an incentive to switch paths; this occurs when all traffic travels on minimum-latency paths.the following question motivates our work: is the optimal assignment really a "better" assignment than an assignment at nash equilibrium? while the optimal assignment obviously dominates one at nash equilibrium from the viewpoint of total latency, it may lack desirable fairness properties. for example, consider a network consisting of two nodes, s and t, and two edges, e1 and e2, from s to t. suppose further that one unit of traffic wishes to travel from s to t, that the latency of edge e1 is always 2(1 - &epsilon;) (independent of the edge congestion, where &epsilon; > 0 is a very small number), and that the latency of edge e2 is the same as the edge congestion (i.e., if x units of traffic are on edge e2, then all of this flow incurs x units of latency). in the assignment at nash equilibrium, all traffic is on the second link; in the minimum-latency assignment, 1 - &epsilon; units of traffic use edge e2 while the remaining &epsilon; units of traffic use edge e1. roughly, a small fraction of the traffic is sacrificed to the slower edge because it improves the overall social welfare (by reducing the congestion experienced by the overwhelming majority of network users); needless to say, these martyrs may not appreciate a doubling of their travel time in the name of "the greater good"! indeed, this drawback of routing traffic optimally has inspired practitioners to find traffic assignments that minimize total latency subject to explicit length constraints [1], which require that no network user experiences much more latency than in an assignment at nash equilibrium. the central question of this paper is how much worse off can network users be in an optimal assignment than in one at nash equilibrium? after reviewing some technical preliminaries in the next section (all of which are classical; see [2] for historical references), we provide an exact solution to this problem under weak hypotheses on the class of allowable latency functions.
finding the repeated median regression line. the repeated median regression line is a robust regression estimate, having a maximal 50% breakdown point. this paper presents an o(n(log n)2) algorithm for finding the repeated median regression line through n points in the plane.
correlation clustering: maximizing agreements via semidefinite programming. we consider the correlation clustering problem introduced in [2]. given a graph g = (v,e) where each edge is labeled either "+" (similar) or "-" (different), we want to cluster the nodes so that the + edges lie within the clusters and the -- edges lie between clusters. specifically, we want to maximize agreements --- the number of + edges within clusters and -- edges between clusters. this problem is np-hard [2]. we give a 0.7666-approximation algorithm for maximizing agreements on any graph even when the edges have non-negative weights (along with labels) and we want to maximize the weight of agreements. these were posed as open problems in [2]. previously the only results known were a trivial 0.5-approximation for arbitrary edge weighted graphs, and a ptas with unit edge weights when |e| = &omega;(|v|2). somewhat surprisingly, our algorithm always produces a clustering with at most 6 clusters. as a corollary we get a 0.7666-approximation algorithm for the k-clustering variant of the problem where we may create at most k clusters. a major component of this algorithm is a simple, easy-to-analyze algorithm that by itself achieves an approximation ratio of 0.75, opening at most 4 clusters.
fault-tolerant facility location. we consider a fault-tolerant generalization of the classical uncapacitated facility location problem, where each client j has a requirement that rj distinct facilities serve it, instead of just one. we give a 2.076-approximation algorithm for this problem using lp rounding, which is currently the best-known performance guarantee. our algorithm exploits primal and dual complementary slackness conditions and is based on clustered randomized rounding. a technical difficulty that we overcome is the presence of terms with negative coefficients in the dual objective function, which makes it difficult to bound the cost in terms of dual variables. for the case where all requirements are the same, we give a primal-dual 1.52-approximation algorithm. we also consider a fault-tolerant version of the k-median problem. in the metric k-median problem, we are given n points in a metric space. we must select k of these to be centers, and then assign each input point j to the selected center that is closest to it. in the fault-tolerant version we want j to be assigned to rj distinct centers. the goal is to select the k centers so as to minimize the sum of assignment costs. the primal-dual algorithm for fault-tolerant facility location with uniform requirements also yields a 4-approximation algorithm for the fault-tolerant k-median problem for this case. this the first constant-factor approximation algorithm for the uniform requirements case.
(un)expected behavior of typical suffix trees. suffix tree is a data structure widely used in algorithms on words and data compression. despite this, very little is known about its typical behavior. recently, chang and lawler have designed a sublinear expected time algorithm for approximate string matching using simple estimates of some parameters of suffix trees. it seems that any further advances in such an endover are subject to better understanding of suffix trees behavior. in this paper, we use a novel technique called string ruler approach to provide a characterization of several basic parameters of suffix trees (dependency among symbols are allowed !). these findings are used to :(i) settle in the negative the conjecture of wyner and ziv regarding the typical behavior of the universal data compression scheme of lampel and ziv; (ii) prove an open problem regarding the length of a block in the lampel-ziv parsing algorithm; (iii) provide new insights and generalizations of string matching algorithms, particularly the one by chang and lawler.
self-adjusting top trees. the dynamic trees problem is that of maintaining a forest that changes over time through edge insertions and deletions. we can associate data with vertices or edges, and manipulate this data individually or in bulk, with operations that deal with whole paths or trees. efficient solutions to this problem have numerous applications, particularly in algorithms for network flows and dynamic graphs in general. several data structures capable of logarithmic-time dynamic tree operations have been proposed. the first was sleator and tarjan's st-tree [16, 17], which represents a partition of the tree into paths. although reasonably fast in practice, adapting st-trees to different applications is nontrivial. topology trees [9], top trees [3], and rc-trees [1] are based on tree contractions: they progressively combine vertices or edges to obtain a hierarchical representation of the tree. this approach is more flexible in theory, but all known implementations assume the trees have bounded degree; arbitrary trees are supported only after ternarization. we show how these two approaches can be combined (with very little overhead) to produce a data structure that is as generic as any other, very easy to adapt, and as practical as st-trees.
design of on-line algorithms using hitting times. random walks are well known for playing a crucial role in the design of randomized off-line as well as on-line algorithms. in this work we prove some basic identities for ergodic markov chains (e.g., an interesting characterization of reversibility in markov chains is obtained in terms of first passage times). besides providing new insight into random walks on weighted graphs, we show how these identities give us a way of designing competitive randomized on-line algorithms for certain well-known problems.
quick and good facility location. we consider the facility location problem with shortest path distances in a weighted graph. w.h.p., we get an approximation factor of 1.62 in o(n + m) time with n and m the number of nodes and edges. also, as a kind of warm-up, for a metric with a constant-times distance oracle, we get the factor 1.62 deterministically in o(n2 log n) time.our results build on a recent facility location algorithm of jain, mahdian, and saberi (stoc'02) achieving an approximation factor of 1.61 in o(n3) time.
on ac implementations of fusion trees and atomic heaps. addressing a question of fredman and willard from stoc'90, we show that fusion trees cannot be implemented using the ac0 operations available through a standard programming language such as c. however, they can be implemented using ac0 operations on emerging multimedia processors such as the pentium 4.a fusion node is a linear space representation of an integer set x of size o(&radic;w), where w &ge; log n is the word-length. the fusion node supports searches in x in constant time. here, a search for y in x returns max{x &epsilon; x&verbar;x &le; y}. using fusion nodes in a o(&radic;w)-degree fusion tree gave fredman and willard o(log n/log w) searching for general n, beating the comparison based lower-bound. however, the search routine uses multiplication which is not an ac0 operation.fredman and willard asked if multiplication instructions could be avoided. we show that the answer is "no" unless you have room for a multiplication table. more precisely, restricting ourselves to the ac0 operations available through c, we show that constant time look-ups or searches in sets of any non-constant size require space 2&omega;(w). however, if we have that much space, i.e., 2&epsilon;w for some constant &epsilon; > 0, then we can tabulate multiplication of (&epsilon;w/2)-bit numbers, and then we get constant time multiplication of words using additions and shifts. previous related lowerbounds all disallowed some common ac0 instructions in c such as shifts.we note that even on the weaker "practical ram" the above 2&omega;(w) space lower-bound for constant look-ups was only known for sets of size &omega;(w2) (miltersen, icalp'96). our &omega;(1) set size is best possible since sets of constant size can be searched directly in constant time.contrasting the above result, we show that using the ac0 operations available on intel's new pentium 4, we can implement both fusion trees and fredman and willard's later atomic heaps from focs'90. among the many consequences, we get linear time and space ac0 implementations of minimum spanning tree and undirected single source shortest paths. also, we get optimal &theta;(log n/log log n) implementations of dynamic rank and 1&frac12; dimensional range searching. previous optimal solutions required either multiplication or the use of self-designed ac0 instructions not available on existing processors.
on ram priority queues. priority queues are some of the most fundamental data structures. for example, they are used directly for task scheduling in operating systems. moreover, they are essential to greedy algorithms. we study the complexity of integer priority queue operations on a ram with arbitrary word size, modeling the possibilities in standard imperative programming languages such as c. we present exponential improvements over previous bounds, and we show tight relations to sorting.our first result is a ram priority queue supporting find-min in constant time and insert and delete-min in time o(log log n), where n is the current number of keys in the queue. this is an exponential improvement over the $o(\sqrt{\log n})$ bound of fredman and willard [ proceedings of the 22nd acm symposium on the theory of computing, baltimore, md, pp. 1--7]. plugging this priority queue into dijkstra's algorithm gives an o(mlog log m) algorithm for the single source shortest path problem on a graph with m edges, as compared with the previous $o(m\sqrt{\log m})$ bound based on fredman and willard's priority queue. the above bounds assume $o(n 2^{{\varepsilon} w})$ space, where w is the word length and ${\varepsilon}>0$. they can, however, be achieved in linear space using randomized hashing.our second result is a general equivalence between sorting and priority queues. a priority queue is monotone if the minimum is nondecreasing over time, as in many greedy algorithms. we show that on a ram, the amortized operation cost of a monotone priority queue is equivalent to the per-key cost of sorting. for example, the equivalence implies that the single source shortest paths problem on a graph with m edges is no harder than that of sorting m keys. with the current ram sorting, this gives an o(m log log m) time bound, as above, but the relation holds regardless of the future developments in ram sorting.from the equivalence result, for any fixed ${\varepsilon}>0$, we derive a randomized monotone $o(\sqrt{\log n}^{1+{\varepsilon}})$ priority queue with expected constant time decrease-key. plugging this into dijkstra's algorithm gives an $o(n\sqrt{\log n}^{1+{\varepsilon}}+m)$ algorithm for the single source shortest path problem on a graph with n nodes and m edges, complementing the above o(mlog log m) algorithm if $m\gg n$. this improves the o(nlog n/log log n + m) bound by fredman and willard [proceedings of the 31st ieee symposium on the foundations of computer science, st. louis, mo, 1990, pp. 719--725], based on their o(log n/log log n) priority queue with constant decrease-key.
tabulation based 4-universal hashing with applications to second moment estimation. we show that 4-universal hashing can be implemented efficiently using tabulated 4-universal hashing for characters, gaining a factor of 5 in speed over the fastest existing methods. we also consider generalization to k-universal hashing, and as a prime application, we consider the approximation of the second moment of a data stream.
spanners and emulators with sublinear distance errors. let k &ge; 2 be an integer. we show that any undirected and unweighted graph g = (v, e) on n vertices has a subgraph g' = (v, e') with o(kn1+1/k) edges such that for any two vertices u, v &isin; v, if &delta;g(u, v) = d, then &delta;g'(u, v) = d+o(d1-1/k-1). furthermore, we show that such subgraphs can be constructed in o(mn1/k) time, where m and n are the number of edges and vertices in the original graph. we also show that it is possible to construct a weighted graph g* = (v, e*) with o(kn1+1/(2k-1)) edges such that for every u, v &isin; v, if &delta;g(u, v) = d, then &delta; &le; &delta;g*(u, v) = d + o(d1-1/k-1). these are the first such results with additive error terms of the form o(d), i.e., additive error terms that are sublinear in the distance being approximated.
efficient algorithms for the hitchcock transportation problem. we consider the hitchcock transportation problem on n supply points and k demand points when n is much greater than k. the problem is solved in o(n2k log n + n2 log2 n) time if n > k log k. further, applying a geometric method named splitter finding and randomization, we improve the time complexity for a case in which the ratio c of the least supply and the maximum supply satisfies the inequality log cn < n/k4 log n. indeed, if n < k5 log3 k and c = poly(n), the problem is solved in o(kn) time, which is optimal.
binary space partitions for line segments with a limited number of directions. we show that there is always a binary space partition (bsp) of size o(n log k) and an autopartition of size o(nk) for n disjoint line segments in the plane, assuming that the segments have k distinct orientations. in particular, if k is a constant, these bounds imply that there is a linear-size bsp and autopartition. our proof is constructive and can be turned into algorithms computing such a bsp or autopartition in o(n2) and o(n2k) times.
confronting hardness using a hybrid approach. a hybrid algorithm is a collection of heuristics, paired with a polynomial time selector s that runs on the input to decide which heuristic should be executed to solve the problem. hybrid algorithms are of particular interest in scenarios where the selector must decide between heuristics that are "good" with respect to different complexity measures.we focus on hybrid algorithms with a "hardness-defying" property: for a problem ii, there is a set of complexity measures {mi} whereby ii is known or conjectured to be unsolvable for each mi, but for each heuristic hi of the hybrid algorithm, one can give a complexity guarantee for hi on the instances of ii that s selects for hi that is strictly better than mi. more concretely, we show that for several np-hard problems, a given instance can either be solved exactly with substantially improved runtime (e.g. 2o(n)), or be approximated in polynomial time with an approximation ratio exceeding that of the known or conjectured inapproximability of the problem, assuming p &ne; np.
instability of fifo in the permanent sessions model at arbitrarily small network loads. we show that for any r > 0, there is a network of first-in-first-out servers and a fixed set of sessions such that: &mdash;the network load is r with respect to the permanent sessions model with bounded arrivals. &mdash;the network can be made unstable.
approximation schemes for metric bisection and partitioning. we design polynomial time approximation schemes (ptass) for metric bisection, i.e. dividing a given finite metric space into two halves so as to minimize or maximize the sum of distances across the cut. the method extends to partitioning problems with arbitrary size constraints. our approximation schemes depend on a hybrid placement method and on a new application of linearized quadratic programs.
primal-dual approach for directed vertex connectivity augmentation and generalizations. in their seminal paper, frank and jord&aacute;n &lsqb;1995&rsqb; show that a large class of optimization problems, including certain directed graph augmentation, fall into the class of covering supermodular functions over pairs of sets. they also give an algorithm for such problems, however, it relies on the ellipsoid method. prior to our result, combinatorial algorithms existed only for the 0--1 valued problem. our key result is a combinatorial algorithm for the general problem that includes directed vertex or s&minus;t connectivity augmentation. the algorithm is based on bencz&uacute;r's previous algorithm for the 0--1 valued case &lsqb;bencz&uacute;r 2003&rsqb;. our algorithm uses a primal-dual scheme for finding covers of partially ordered sets that satisfy natural abstract properties as in frank and jord&aacute;n. for an initial (possibly greedy) cover, the algorithm searches for witnesses for the necessity of each element in the cover. if no two (weighted) witnesses have a common cover, the solution is optimal. as long as this is not the case, the witnesses are gradually exchanged for smaller ones. each witness change defines an appropriate change in the solution; these changes are finally unwound in a shortest-path manner to obtain a solution of size one less.
approximating the minimum strongly connected subgraph via a matching lower bound. we present a 3/2-approximation algorithm for the problem of finding a minimum strongly connected spanning subgraph in a given directed graph. as a corollary we obtain a 3/2-approximation algorithm for the more general minimum equivalent digraph problem. the performance of our algorithm is measured against a lower bound obtained from a simple matching problem. the performance guarantee is optimal with respect to the lower bound.
distribution sort with randomizing cycle. parallel independent disks can enhance the performance of external memory (em) algorithms, but the programming task is often difficult. in this paper we develop randomized variants of distribution sort for use with parallel independent disks. we propose a simple variant called randomized cycling distribution sort (rcd) and prove that it has optimal expected i/o complexity. the analysis uses a novel reduction to a model with significantly fewer probabilistic interdependencies. experimental evidence is provided to support its practicality. other simple variants are also examined experimentally and appear to offer similar advantages to rcd. based upon ideas in rcd we propose general techniques that transparently simulate algorithms developed for the unrealistic multihead disk model so that they can be run on the realistic parallel disk model. the simulation is optimal for two important classes of algorithms; the class of multipass algorithms, which make a complete pass through their data before accessing any element a second time, and the algorithms based upon the well-known distribution paradigm of em computation.
predicting the "unpredictable". this is a survey of results about the accuracy of prediction when the predictor has no prior knowledge about the process that s/he must forecast. no prior knowledge means just that; no moments, distributions, periods etc.for example, suppose one is asked to predict successive outcomes of an infinite sequence of 0's and 1's. accuracy will be measured by the fraction of correct guesses. with no information beyond this, how well can one guarantee to do?predicting the actual outcome is demanding and in many cases inappropriate; think for example of the case when the sequence is generated by a stochastic process. in this case it is more natural to ask for a probability forecast. how should one measure the error of a probability forecast? given this measure, are there forecasting algorithms that guarantee a small error no matter what process generates the sequence?
on the rectilinear crossing number of complete graphs. we prove a lower bound of 0.3288(n4) for the rectilinear crossing number cr(kn>) of a complete graph on n vertices, or in other words, for the minimum number of convex quadrilaterals in any set of n points in general position in the euclidean plane. as we see it, the main contribution of this paper is not so much the concrete numerical improvement over earlier bounds, as the novel method of proof, which is not based on bounding cr(kn>) for some small n.
(log log )-competitive dynamic binary search trees. the dynamic optimality conjecture [st85] states that splay trees are competitive (within a constant competitive factor) among the class of all binary search tree (bst) algorithms. despite 20 years of research this conjecture is still unresolved. recently, demaine et al. [dhip04] suggested searching for alternative algorithms which have small but non-constant competitive factors. they proposed tango, a bst algorithm which is nearly dynamically optimal - its competitive ratio is o(log log n) instead of a constant. unfortunately, for many access patterns, such as random and sequential, tango is worse than other bst algorithms by a factor of log log n.in this paper, we introduce the multi-splay tree (mst) data structure, which is the first o(log log n)-competitive bst to simultaneously achieve o(log n) amortized cost and o(log2 n) worst-case cost per query. we also prove the sequential access lemma for msts, which states that sequentially accessing all keys takes linear time. thus, msts are o(log log n)-competitive like tango but, unlike tango, require only o(log n) amortized time per access in an arbitrary sequence and only o(1) amortized time per access during a sequential access sequence.furthermore, we generalize the standard framework for competitive analysis of bst algorithms to include updates (insertions and deletions) in addition to queries. in doing so, we extend the lower bound of wilber [wil89] and demaine et al. [dhip04] to handle these update operations. we show how msts can be modified to support these update operations and be o(log log n)-competitive in the new framework while maintaining the rest of the properties above.
absolute convergence: true trees from short sequences. fast-converging methods for reconstructing phylogenetic trees require that the sequences characterizing the taxa be of only polynomial length, a major asset in practice, since real-life sequences are of bounded length. however, of the half-dozen such methods proposed over the last few years, only two fulfill this condition without requiring knowledge of typically unknown parameters, such as the evolutionary rate(s) used in the model; this additional requirement severely limits the applicability of the methods. we say that methods that need such knowledge demonstrate relative fast convergence, since they rely upon an oracle. we focus on the class of methods that do not require such knowledge and thus demonstrate absolute fast convergence. we give a very general construction scheme that not only turns any relative fast-converging method into an absolute fast-converging one, but also turns any statistically consistent method that converges from sequence of length &ogr;(e&ogr;(diam(t))) into an absolute fast-converging method.
a new property and a faster algorithm for baseball elimination. in the baseball elimination problem, there is a league consisting of n teams. at some point during the season, team i has wi wins and gij games left to play against team j. a team is eliminated if it cannot possibly finish the season in first place or tied for first place. the goal is to determine exactly which teams are eliminated. the problem is not as easy as many sports writers would have you believe, in part because the answer depends not only on the number of games won and left to play but also on the schedule of remaining games. in the 1960's, schwartz showed how to determine whether one particular team is eliminated using a maximum flow computation.this paper indicates that the problem is not as difficult as many mathematicians would have you believe. for each team i, let gi denote the number of games remaining. we prove that there exists a value w* such that team i is eliminated if and only if wi + gi w*. using this surprising fact, we can determine all eliminated teams in time proportional to a single maximum flow computation in a graph with n nodes; this improves upon the previous best known complexity bound by a factor of n.
algorithms for quantified boolean formulas. we present algorithms for solving quantified boolean formulas (qbf, or sometimes qsat) with worst case runtime asymptotically less than o(2n) when the clause-to-variable ratio is smaller or larger than some constant. we solve qbfs in conjunctive normal form (cnf) in o(1.709m) time and space, where m is the number of clauses. extending the technique to a quantified version of constraint satisfaction problems (qcsp), we solve qcsp with domain size d = 3 in o(1.953m) time, and qcsps with d &ge; 4 in o(dm/2+&epsilon;) time and space for &epsilon; < 0, where m is the number of constraints. for 3-cnf qbf, we describe an polynomial space algorithm with time complexity o(1.619n) when the number of 3-cnf clauses is equal to n; the bound approaches 2n as the clause-to-variable ratio approaches 2. for 3-cnf &pi;2-sat (3-cnf qbfs of the form &forall;u1&hellip;uj&exist;xj+1&hellip;xnf), an improved polyspace algorithm has runtime varying from o(1.840m) to o(1.415m), as a particular clause-to-variable ratio increases from 1.
how random is the human genome? now that the human genome is (mostly) sequenced, what do we really know about the statistical properties of that random-looking string of 3 billion a's, c's, g's and t's? the speaker and a group of scientists at rockefeller university (andy dewan, chad hayes, josephine hoh, jurg ott, tony parrado, and richard sackler) have used a little algorithmic theory and some programming to try to get answers.
wavelength assignment and generalized interval graph coloring. in this paper we study wavelength assignment on an optical linesystem without wavelength conversion. consider a set of undirected demands along the line. each demand is carried on a wavelength and any two overlapping demands on the same fiber require distinct wavelengths. suppose &mu; wavelengths are available in the system and each fiber can carry all &mu; wavelengths. we define &ell;(e), the load on link e, to be the smallest integer such that &ell;(e)&mu; is at least the number of demands passing through e. hence, &ell;(e) is the minimum number of fibers required on e in order to support all demands.we present a polynomial-time wavelength assignment algorithm that guarantees each wavelength appears at most &ell;(e) times on each link e. (this generalizes the well-known fact that interval graphs are perfect.) in the presence of moadms (mesh optical add/drop multiplexers), devices that multiplex distinct wavelengths from different fibers into a new fiber, we only need to deploy &ell;(e) fibers per link. on the other hand, if each demand has to stay on a single fiber, as is the case without moadms, we show that some links may require more than &ell;(e) fibers. in fact, we show that it is np-complete to decide if a set of demands can be carried on a given set of fibers, or if there exists a set of fibers with a given total length that can carry all the demands.
assigning chain-like tasks to a chain-like network. we investigate the allocation of a chain-like task system consisting of n tasks to a chain-like network of m computers so as to minimize the bottleneck processing cost. we present an &ogr;(mn) time solution algorithm for this problem. this improves on a sequence of five slower algorithms by bokhari [1988], sheu & chiang [1990], hsu [1993], and young & chan [1993,1994].
asymmetric balanced allocation with simple hash functions. we show that for the asymmetric sequential allocation scheme of v&ouml;cking (2003) one can use very simple hash functions. the hash functions we use are a straightforward extension of the hash functions introduced by dietzfelbinger and woelfel (2003). in order to evaluate a hash function a few arithmetic operations and table lookups suffice. moreover, we show that the scheme has essentially the same behavior if the same balls are allowed to be inserted multiple times (i.e. they may be deleted and reinserted afterwards).
optimal space lower bounds for all frequency moments. we prove that any one-pass streaming algorithm which (ε, &delta;)-approximates the kth frequency moment fk, for any real k &ne; 1 and any ε = &omega;(1/&radic;m), must use &omega;(1/ε&sup2;) bits of space, where m is the size of the universe. this is optimal in terms of ε, resolves the open questions of bar-yossef et al in [3, 4], and extends the &omega;(1/ε&sup2;) lower bound for f0 in [11] to much smaller ε by applying novel techniques. along the way we lower bound the one-way communication complexity of approximating the hamming distance and the number of bipartite graphs with minimum/maximum degree constraints.
a polynomial time approximation scheme for minimum routing cost spanning trees. given an undirected graph with nonnegative costs on the edges, the routing cost of any of its spanning trees is the sum over all pairs of vertices of the cost of the path between the pair in the tree. finding a spanning tree of minimum routing cost is np-hard, even when the costs obey the triangle inequality. we show that the general case is in fact reducible to the metric case and present a polynomial-time approximation scheme valid for both versions of the problem. in particular, we show how to build a spanning tree of an n-vertex weighted graph with routing cost at most $(1+\epsilon)$ of the minimum in time $o(n^{o({\frac{1}{\epsilon}}% )})$. besides the obvious connection to network design, trees with small routing cost also find application in the construction of good multiple sequence alignments in computational biology. the communication cost spanning tree problem is a generalization of the minimum routing cost tree problem where the routing costs of different pairs are weighted by different requirement amounts. we observe that a randomized o(log n log log n)-approximation for this problem follows directly from a recent result of bartal, where n is the number of nodes in a metric graph. this also yields the same approximation for the generalized sum-of-pairs alignment problem in computational biology.
on the approximation of maximum satisfiability. we present a 3/4 polynomial time approximation algorithm for the maximum satisfiability problem: given a set of clauses, find a truth assignment that satisfies the maximum number of clauses. the algorithm applies to the weighted case as well, and involves nontrival application of network flow techniques.
algorithms for subset testing and finding maximal sets. in this paper we consider two related problems: subset testing and finding maximal sets. first, consider a sequence of n operations, where each operation either creates a set, inserts (deletes) an element into (from) a set, queries whether a particular element is in a set, queries whether or not one set is a subset of another, or queries whether or not the intersection of two sets is empty. we show that for any integer k, one can implement subset and intersection testing in time o(n1-(1/k) log n) and all of the other operations in time o(n1/k log n)). it requires o(nk+1)/k) space. when k = 2, this yields a worst case time complexity of o(n1/2 log n) per operation, and uses o(n3/2) space. second, consider a set of sets, where the total size of the input is o(n). we show that one can find those sets that are maximal (a set is maximal if it is not contained in any other set) in time o(mn), where m is the number of maximal sets.
on-line file caching. consider the following file caching problem: in response to a sequence of requests for files, where each file has a specified size and retrieval cost, maintain a cache of files of total size at most some specified k so as to minimize the total retrieval cost. specifically, when a requested file is not in the cache, bring it into the cache, pay the retrieval cost, and choose files to remove from the cache so that the total size of files in the cache is at most k. this problem generalizes previous paging and caching problems by allowing objects of arbitrary size and cost, both important attributes when caching files for world-wide-web browsers, servers, and proxies. we give a simple deterministic on-line algorithm that generalizes many well-known paging and weighted-caching strategies, including least-recently-used, first-in-first-out, flush-when-full, and the balance algorithm. on any request sequence, the total cost incurred by the algorithm is at most k/(k-h+1) times the minimum possible using a cache of size h >= k. for any algorithm satisfying the latter bound, we show it is also the case that for most choices of k, the retrieval cost is either insignificant or the competitive ratio is constant. this helps explain why competitive ratios of many on-line paging algorithms have been typically observed to be constant in practice.
detecting short directed cycles using rectangular matrix multiplication and dynamic programming. we present several new algorithms for detecting short fixed length cycles in digraphs. the new algorithms utilize fast rectangular matrix multiplication algorithms together with a dynamic programming approach similar to the one used in the solution of the classical chain matrix product problem. the new algorithms are instantiations of a generic algorithm that we present for finding a directed ck, i.e., a directed cycle of length k, in a digraph, for any fixed k &ge; 3. this algorithm partitions the prospective ck's in the input digraph g = (v,e) into o(logk v) classes, according to the degrees of their vertices. for each cycle class we determine, in o(eck log v) time, whether g contains a ck from that class, where ck = ck(&omega;) is a constant that depends only on !, the exponent of square matrix multiplication. the search for cycles from a given class is guided by the solution of a small dynamic programming problem. the total running time of the obtained deterministic algorithm is therefore o(eck logk+1 v).for c3, we get c3 = 2&omega;/(&omega; + 1) < 1.41 where &omega; < 2.376 is the exponent of square matrix multiplication. this coincides with an existing algorithm of [ayz97].for c4 we get c4 = (4&omega; - 1)/(2&omega; + 1) < 1.48. we can dispense, in this case, of the polylogarithmic factor and get an o(e(4&omega;-1)/(2&omega;+1)) = o(e1.48) time algorithm. this improves upon an o(e3/2) time algorithm of [ayz97].for c5 we get c5 = 3&omega;/(&omega; + 2) < 1.63. the obtained running time of o(e3&omega;/(&omega;+2) log6 v) = o(e1.63) improves upon an o(e5/3) time algorithm of [ayz97].determining ck for k &ge; 6 is a difficult task. we conjecture that ck = (k + 1)&omega;/(2&omega; + k - 1), for every odd k. the values of ck for even k &ge; 6 seem to exhibit a much more complicated dependence on &omega;.
family trees: an ordered dictionary with optimal congestion, locality, degree, and search time. we consider the problem of storing an ordered dictionary data structure over a distributed set of nodes. in contrast to traditional sequential data structures, distributed data structures should ideally have low congestion. we present a novel randomized data structure, called a family tree, to solve this problem. a family tree has optimal expected congestion, uses only a constant amount of state per node, and supports searches and node insertion/deletion in expected o(log n) time on a system with n nodes. furthermore, a family tree supports keys from any ordered domain. because the keys are not hashed, searches have good locality in the sense that intermediate nodes on the search path have keys that are not far outside of the range between the source and destination.
practical approximation algorithms for zero- and bounded-skew trees. the skew of an edge-weighted rooted tree is the maximum difference between any two root-to-leaf path weights. zero- or bounded-skew trees are needed for achieving synchronization in many applications, including network multicasting [21] and vlsi clock routing [3, 18]. in these applications edge weights represent propagation delays, and a signal generated at the root should be received by multiple recipients located at the leaves (almost) simultaneously. the objective is to find zero- or bounded-skew trees of minimum total weight, since the weight of the tree is directly proportional to the amount of resources that must be allocated to the tree. charikar et al. [9] have recently proposed the first strongly polynomial algorithms with proven constant approximation factors, 2e &ap; 5.44 and 16.86, for finding minimum weight zero- and bounded-skew trees, respectively. in this paper we introduce a new approach to these problems, based on zero-skew &ldquo;stretching&rdquo; of spanning trees, and obtain algorithms with improved approximation factors of 4 and 14. for the case when tree nodes are points in the plane and edge weights are given by the rectilinear metric our algorithms find zero- and bounded-skew trees of length at most 3 and 9 times the optimum. this case is of special interest in vlsi clock routing. an important feature of our algorithms is their practical running time, which is asymptotically the same as the time needed for computing the minimum spanning tree.
approximating the two-level facility location problem via a quasi-greedy approach. we propose a quasi-greedy algorithm for approximating the classical uncapacitated 2-level facility location problem (2-lflp). our algorithm, unlike the standard greedy algorithm, selects a sub-optimal candidate at each step. it also relates the minimization 2-lflp problem, in an interesting way, to the maximization version of the single level facility location problem. another feature of our algorithm is that it combines the technique of randomized rounding with that of dual fitting.this new approach enables us to approximate the metric 2-lflp in polynomial time with a ratio of 1:77, a significant improvement on the previously known approximation ratios. moreover, our approach results in a local improvement procedure for the 2-lflp, which is useful in improving the approximation guarantees for several other multi-level facility location problems.
optimal bounds for matching routing on trees. the permutation routing problem is studied for trees under the matching model. by introducing a novel and useful (so-called) caterpillar tree partition, we prove that any permutation on an n-node tree (and thus graph) can be routed in $\frac{3}{2}n + o(\log n)$ steps. this answers an open problem of alon, chung, and graham [ siam j. discrete math., 7 (1994), pp. 516--530].
shape sensitive geometric permutations. we prove that a set of n unit balls in rd admits at most four distinct geometric permutations, or line transversals, thus settling a long-standing conjecture in combinatorial geometry. the constant bound significantly improves upon the &thgr;(nd-1) bound for the balls of arbitrary radii. intrigued by this large gap between the two bounds, we also investigate how the number of geometric permutations varies as a function of shape, size, and spacing of objects. our results include a tight bound of 2d-1 on the geometric permutations of n disjoint rectangular boxes in rd, and a constant bound on the geometric permutations for disks in the plane when the ratio between the largest to smallest disks is bounded. an important consequence of the former theorem is that if the smallest bounding boxes containing a set of geometric objects in rd are pairwise disjoint, then those objects admit only 2d-1 permutations, which is a significant improvement on the &ogr;(n2d-2) bound known for general convex objects.
on directed steiner trees. the directed steiner tree problem is the following: given a directed graph g = (v, e) with weights on the edges, a set of terminals s &sube; v, and a root vertex r, find a minimum weight out-branching t rooted at r, such that all vertices in s are included in t. this problem is known to be np-hard. recently, non-trivial polynomial time approximation algorithms have been developed for this problem with worst case approximation guarantees of o(k&epsilon;) for any fixed &epsilon; > 0. we consider a natural lp relaxation of this problem. using a dual formulation we construct a simple deterministic (d + 1)-approximation algorithm for a special case when the subgraph induced by v \ s is a tree with depth d (for example, this can be shown to include the group steiner tree problem as a special case, by the loss of poly-log factors in the approximation guarantee). we also show that this lp has an integrality gap of &theta;(&radic;k) for the general problem.
jenga. jenga is a popular block game played by two players. each player in her turn has to remove a block from a stack, without toppling the stack, and then add it the top of the stack. we analyze the game mathematically and describe the optimal strategies of both players. we show that 'physics', that seems to play a dominant role in this game, does not really add much to the complexity of the (idealized) game, and that jenga is, in fact, a nim-like game. in particular, we show that a game that starts with n full layers of blocks is a win for the first player if and only if n = 2, or n &equiv; 1, 2 (mod 3) and n &ge; 4. we also suggest some several natural extensions of the game.
computer assisted proof of optimal approximability results. we obtain computer assisted proofs of several spherical volume inequalities that appear in the analysis of semidefinite programming based approximation algorithms for boolean constraint satisfaction problems. these inequalities imply, in particular, that the performance ratio achieved by the max 3-sat approximation algorithm of karloff and zwick is indeed 7/8, as conjectured by them, and that the performance ratio of the max 3-csp algorithm of the author is indeed 1/2. other results are also implied. the computer assisted proofs are obtained using a system called realsearch, written by the author. this system uses interval arithmetic to produce rigorous proofs that certain collections of constraints in real variables have no real solution.
matroids, secretary problems, and online mechanisms. we study a generalization of the classical secretary problem which we call the "matroid secretary problem". in this problem, the elements of a matroid are presented to an online algorithm in random order. when an element arrives, the algorithm observes its value and must make an irrevocable decision regarding whether or not to accept it. the accepted elements must form an independent set, and the objective is to maximize the combined value of these elements. this paper presents an o(log k)-competitive algorithm for general matroids (where k is the rank of the matroid), and constant-competitive algorithms for several special cases including graphic matroids, truncated partition matroids, and bounded degree transversal matroids. we leave as an open question the existence of constant-competitive algorithms for general matroids. our results have applications in welfare-maximizing online mechanism design for domains in which the sets of simultaneously satisfiable agents form a matroid.
line-of-sight networks. random geometric graphs have been one of the fundamental models for reasoning about wireless networks: one places n points at random in a region of the plane (typically a square or circle), and then connects pairs of points by an edge if they are within a fixed distance of one another. in addition to giving rise to a range of basic theoretical questions, this class of random graphs has been a central analytical tool in the wireless networking community. for many of the primary applications of wireless networks, however, the underlying environment has a large number of obstacles, and communication can only take place among nodes when they are close in space and when they have line-of-sight access to one another – consider, for example, urban settings or large indoor environments. in such domains, the standard model of random geometric graphs is not a good approximation of the true constraints, since it is not designed to capture the line-of-sight restrictions. here we propose a random-graph model incorporating both range limitations and line-of-sight constraints, and we prove asymptotically tight results for k-connectivity. specifically, we consider points placed randomly on a grid (or torus), such that each node can see up to a fixed distance along the row and column it belongs to. (we think of the rows and columns as ‘streets’ and ‘avenues’ among a regularly spaced array of obstructions.) further, we show that when the probability of node placement is a constant factor larger than the threshold for connectivity, near-shortest paths between pairs of nodes can be found, with high probability, by an algorithm using only local information. in addition to analysing connectivity and k-connectivity, we also study the emergence of a giant component, as well an approximation question, in which we seek to connect a set of given nodes in such an environment by adding a small set of additional ‘relay’ nodes.
an unbiased pointing operator for unlabeled structures, with applications to counting and sampling. we introduce a general method to count and randomly sample unlabeled combinatorial structures. the approach is based on pointing unlabeled structures in an "unbiased" way, i.e., in such a way that a structure of size n gives rise to n pointed structures. we develop a specific p&oacute;lya theory for the corresponding pointing operator, and present a sampling framework relying both on the principles of boltzmann sampling and on p&oacute;lya operators. our method is illustrated on several examples: in each case, we provide enumerative results and efficient random samplers. the approach applies to unlabeled families of plane and non-plane unrooted trees, and tree-like structures in general, but also to cactus graphs, outerplanar graphs, rna secondary structures, and classes of planar maps.
on the -simple shortest paths problem in weighted directed graphs. we obtain the first approximation algorithm for finding the k-simple shortest paths connecting a pair of vertices in a weighted directed graph. our algorithm is deterministic and has a running time of o(k(m&radic;n + n3/2 log n)) where m is the number of edges in the graph and n is the number of vertices. let s, t &epsilon; v; the length of the i-th simple path from s to t computed by our algorithm is at most 3/2 times the length of the i-th shortest simple path from s to t. the best algorithms for computing the exact k-simple shortest paths connecting a pair of vertices in a weighted directed graph are due to yen [19] and lawler [13]. the running time of their algorithms, using modern data structures, is o(k(mn + n2 log n)). both algorithms are from the early 70's. although this problem and other variants of the k-shortest path problem drew a lot of attention during the last three and a half decades, the o(k(mn + n2 log n)) bound is still unbeaten.
strong price of anarchy. a strong equilibrium (aumann 1959) is a pure nash equilibrium which is resilient to deviations by coalitions. we define the strong price of anarchy to be the ratio of the worst case strong equilibrium to the social optimum. in contrast to the traditional price of anarchy, which quantifies the loss incurred due to both selfishness and lack of coordination, the strong price of anarchy isolates the loss originated from selfishness from that obtained due to lack of coordination. we study the strong price of anarchy in two settings, one of job scheduling and the other of network creation. in the job scheduling game we show that for unrelated machines the strong price of anarchy can be bounded as a function of the number of machines and the size of the coalition. for the network creation game we show that the strong price of anarchy is at most 2. in both cases we show that a strong equilibrium always exists, except for a well defined subset of network creation games.
efficient contention resolution protocols for selfish agents. we seek to understand behavior of selfish agents accessing a broadcast channel. in particular, we consider the natural agent utility where costs are proportional to delay. access to the channel is modelled as a game in extensive form with simultaneous play. standard protocols such as aloha are vulnerable to manipulation by selfish agents. we show that choosing appropriate transmission probabilities for aloha to achieve equilibrium implies exponentially long delays. we give a very simple protocol for the agents that is in nash equilibrium and is also very efficient --- other than with exponentially negligible probability --- all n agents will successfully transmit within cn time, for some small constant c.
a near linear time constant factor approximation for euclidean bichromatic matching (cost). we give an nlogo(1) n-time randomized o(1)-approximation algorithm for computing the cost of minimum bichromatic matching between two planar point-sets of size n.
embedding metrics into ultrametrics and graphs into spanning trees with constant average distortion. this paper addresses the basic question of how well can a tree approximate distances of a metric space or a graph. given a graph, the problem of constructing a spanning tree in a graph which strongly preserves distances in the graph is a fundamental problem in network design. we present scaling distortion embeddings where the distortion scales as a function of &epsilon;, with the guarantee that for each &epsilon; the distortion of a fraction 1 - &epsilon; of all pairs is bounded accordingly. such a bound implies, in particular, that the average distortion and lq-distortions are small. specifically, our embeddings have constant average distortion and o(&radic;log n) l2-distortion. this follows from the following results: we prove that any metric space embeds into an ultrametric with scaling distortion o(&radic;1/&epsilon;). for the graph setting we prove that any weighted graph contains a spanning tree with scaling distortion o(&radic;1/&epsilon;). these bounds are tight even for embedding in arbitrary trees. for probabilistic embedding into spanning trees we prove a scaling distortion of &otilde;(log2(1/&epsilon;)), which implies constant lq-distortion for every fixed q < &infin;.
dynamic pricing for impatient bidders. we study the following problem related to pricing over time. assume there is a collection of bidders, each of whom is interested in buying a copy of an item of which there is an unlimited supply. every bidder is associated with a time interval over which the bidder will consider buying a copy of the item, and a maximum value the bidder is willing to pay for the item. on every time unit, the seller sets a price for the item. the seller's goal is to set the prices so as to maximize revenue from the sale of copies of items over the time period. in the first model considered, we assume that all bidders are impatient, that is, bidders buy the item at the first time unit within their bid interval that they can afford the price. to the best of our knowledge, this is the first work that considers this model. in the offline setting, we assume that the seller knows the bids of all the bidders in advance. in the online setting we assume that at each time unit the seller only knows the values of the bids that have arrived before or at that time unit. we give a polynomial time offline algorithm and prove upper and lower bounds on the competitiveness of deterministic and randomized online algorithms, compared with the optimal offline solution. the gap between the upper and lower bounds is quadratic. we also consider the envy-free model in which bidders are sold the item at the minimum price during their bid interval, as long as it is not over their limit value. we prove tight bounds on the competitiveness of deterministic online algorithms for this model, and upper and lower bounds on the competitiveness of randomized algorithms with quadratic gap. the lower bounds for the randomized case in both models use a novel general technique.
aggregation of partial rankings, -ratings and top- lists. we study the problem of aggregating partial rankings. this problem is motivated by applications such as meta-searching and information retrieval, search engine spam fighting, e-commerce, learning from experts, analysis of population preference sampling, committee decision making and more. we improve recent constant factor approximation algorithms for aggregation of full rankings and generalize them to partial rankings. our algorithms improve constant factor approximation with respect to a family of metrics recently proposed in the context of comparing partial rankings. we pay special attention to two important types of partial rankings: the well-known top-m lists and the more general p-ratings which we define. we provide first evidence for hardness of aggregating them for constant&#x00a0;m,&#x00a0;p.
pull-based data broadcast with dependencies: be fair to users, not to items. broadcasting is known to be an efficient means of disseminating data in wireless communication environments (such as satellite, mobile phone networks,...). it has been recently observed that the average service time of broadcast systems can be considerably improved by taking into consideration existing correlations between requests. we study a pull-based data broadcast system where users request possibly overlapping sets of items; a request is served when all its requested items are downloaded. we aim at minimizing the average user perceived latency, i.e. the average flow time of the requests. we first show that any algorithm that ignores the dependencies can yield arbitrary bad performances with respect to the optimum even if it is given arbitrary extra resources. we then design a (4 + &epsilon;)-speed o(1 + 1/&epsilon;2)-competitive algorithm for this setting that consists in 1) splitting evenly the bandwidth among each requested set and in 2) broadcasting arbitrarily the items still missing in each set into the bandwidth the set has received. our algorithm presents several interesting features: it is simple to implement, non-clairvoyant, fair to users so that no user may starve for a long period of time, and guarantees good performances in presence of correlations between user requests (without any change in the broadcast protocol). we also present a (4 + &epsilon;)-speed o(1 + 1/&epsilon;3)-competitive algorithm which broad-casts at most one item at any given time and preempts each item broadcast at most once on average. as a side result of our analysis, we design a competitive algorithm for a particular setting of non-clairvoyant job scheduling with dependencies, which might be of independent interest.1
island hopping and path colouring with applications to wdm network design. wavelength division multiplexed (wdm) optical communication offers the advantages of increased capacity and decreased latency for signals (traffic) carried across such networks. the devices used for "switching", however, force additional constraints on the mathematical design of such networks. in this paper we explore two such constaints: (i) optical lightpaths must be assigned individual wavelengths and (ii) sometimes lightpaths must unavoidably go through an optical-electronic-optical (oeo) conversion by means of an expensive piece of equipment called an optical transponder. we term the graph theoretical problems related to these constraints path colouring and island hopping. we present a range of upper and lower bounds for these problems. in particular, we extend the work of winkler and zhang (2003) and anshelevich and zhang (2004).
compacting cuts: a new linear formulation for minimum cut. for a graph (v,e), existing compact linear formulations for the minimum cut problem require &theta;(&verbar;v&verbar;&verbar;e&verbar;) variables and constraints and can be interpreted as a composition of &verbar;v&verbar; &minus; 1 polyhedra for minimum s-t cuts in much the same way as early approaches to finding globally minimum cuts relied on &verbar;v&verbar; &minus; 1 calls to a minimum s-t cut algorithm. we present the first formulation to beat this bound, one that uses o(&verbar;v&verbar;2) variables and o(&verbar;v&verbar;3) constraints. an immediate consequence of our result is a compact linear relaxation with o(&verbar;v&verbar;2) constraints and o(&verbar;v&verbar;3) variables for enforcing global connectivity constraints. this relaxation is as strong as standard cut-based relaxations and has applications in solving traveling salesman problems by integer programming as well as finding approximate solutions for survivable network design problems using jain's iterative rounding method. another application is a polynomial-time verifiable certificate of size n for for the np-complete problem of l1-embeddability of a rational metric on an n-set (as opposed to a certificate of size n2 known previously).
a ptas for tsp with neighborhoods among fat regions in the plane. the euclidean tsp with neighborhoods (tspn) problem seeks a shortest tour that visits a given collection of n regions (neighborhoods). we present the first polynomial-time approximation scheme for tspn for a set of regions given by arbitrary disjoint fat regions in the plane. this improves substantially upon the known approximation algorithms, and is the first ptas for tspn on regions of non-comparable sizes. our result is based on a novel extension of the m-guillotine method. the result applies to regions that are "fat" in a very weak sense: each region pi contains a disk of radius &omega;(diam(pi)), but is otherwise arbitrary. further, the result applies even if the regions intersect arbitrarily, provided that there exists a packing of disjoint disks, of radii &omega;(diam(pi)), contained within their respective regions. finally, the ptas result applies also to the case in which the regions are sets of points or polygons, each each lying within one of a given set of disjoint fat regions.
tree exploration with logarithmic memory. we consider the task of network exploration by a mobile agent (robot) with small memory. the agent has to traverse all nodes and edges of a network (represented as an undirected connected graph), and return to the starting node. nodes of the network are unlabeled and edge ports are locally labeled at each node. the agent has no a priori knowledge of the topology of the network or of its size, and cannot mark nodes in any way. under such weak assumptions, cycles in the network may prevent feasibility of exploration, hence we restrict attention to trees. we present an algorithm to accomplish tree exploration (with return) using o(log n)-bit memory for all n-node trees. this strengthens the result from [15], where o(log2 n)-bit memory was used for tree exploration, and matches the lower bound on memory size proved there.
on the number of tetrahedra with minimum, unit, and distinct volumes in three-space. we formulate and give partial answers to several combinatorial problems on volumes of simplices determined by n points in 3-space, and in general in d dimensions. <label>(i)</label>the number of tetrahedra of minimum (non-zero) volume spanned by n points in <inline-graphic mime-subtype="gif" xlink="s096354830700884x_inline1"><alt-text>$\mathbb{r}$</alt-text></inline-graphic>3 is at most <inline-graphic mime-subtype="gif" xlink="s096354830700884x_inline2"><alt-text>$\frac{2}{3}n^3-o(n^2)$</alt-text></inline-graphic>, and there are point sets for which this number is <inline-graphic mime-subtype="gif" xlink="s096354830700884x_inline3"><alt-text>$\frac{3}{16}n^3-o(n^2)$</alt-text></inline-graphic>. we also present an o(n3) time algorithm for reporting all tetrahedra of minimum non-zero volume, and thereby extend an algorithm of edelsbrunner, o'rourke and seidel. in general, for every <inline-graphic mime-subtype="gif" xlink="s096354830700884x_inline4"><alt-text>$k,d\in \mathbb{n}, 1\leq k \leq d$</alt-text></inline-graphic>, the maximum number of k-dimensional simplices of minimum (non-zero) volume spanned by n points in <inline-graphic mime-subtype="gif" xlink="s096354830700884x_inline1"><alt-text>$\mathbb{r}$</alt-text></inline-graphic>d is θ(nk). <label>(ii)</label>the number of unit volume tetrahedra determined by n points in <inline-graphic mime-subtype="gif" xlink="s096354830700884x_inline1"><alt-text>$\mathbb{r}$</alt-text></inline-graphic>3 is o(n7/2), and there are point sets for which this number is ω(n3 log logn). <label>(iii)</label>for every <inline-graphic mime-subtype="gif" xlink="s096354830700884x_inline5"><alt-text>$d\in \mathbb{n}$</alt-text></inline-graphic>, the minimum number of distinct volumes of all full-dimensional simplices determined by n points in <inline-graphic mime-subtype="gif" xlink="s096354830700884x_inline1"><alt-text>$\mathbb{r}$</alt-text></inline-graphic>d, not all on a hyperplane, is θ(n).
fractional packing in ideal clutters. in this paper we present a polyhedral framework for fractional packing in ideal clutters. consider an ideal clutter with a nonnegative capacity function on its vertices. it follows from ideality that for any nonnegative capacity the total multiplicity of an optimal fractional packing is equal to the minimum capacity of a vertex cover. our framework finds an optimal packing using at most n edges with positive multiplicities, performing at most n times minimizations for the clutter and at most n2 times minimizations for its blocker, where n denotes the cardinality of the vertex set. applied to the clutter of dijoins (directed cut covers), the framework provides the first combinatorial polynomial-time algorithm for fractional packing of dijoins.
zone diagrams: existence, uniqueness and algorithmic challenge. a zone diagram is a new variation of the classical notion of the voronoi diagram. given points (sites) ${\mathbf p}_1,\ldots,{\mathbf p}_n$ in the plane, each ${\mathbf p}_i$ is assigned a region $r_i$, but in contrast to the ordinary voronoi diagrams, the union of the $r_i$ has a nonempty complement, the neutral zone. the defining property is that each $r_i$ consists of all ${\mathbf x}\in{\mathbb{r}}^2$ that lie closer (nonstrictly) to ${\mathbf p}_i$ than to the union of all the other $r_j$, $j\ne i$. thus, the zone diagram is defined implicitly, by a &ldquo;fixed-point property,&rdquo; and neither its existence nor its uniqueness seem obvious. we establish existence using a general fixed-point result (a consequence of schauder's theorem or kakutani's theorem); this proof should generalize easily to related settings, say higher dimensions. then we prove uniqueness of the zone diagram, as well as convergence of a natural iterative algorithm for computing it, by a geometric argument, which also relies on a result for the case of two sites in an earlier paper. many challenging questions remain open.
reconstruction using witness complexes. we present a novel reconstruction algorithm that, given an input point set sampled from an object s, builds a one-parameter family of complexes that approximate s at different scales. at a high level, our method is very similar in spirit to chew's surface meshing algorithm, with one notable difference: the restricted delaunay triangulation is replaced by the witness complex, which makes our algorithm applicable in any metric space. to prove its correctness on curves and surfaces, we highlight the relationship between the witness complex and the restricted delaunay triangulation in 2d and in 3d. specifically, we prove that both complexes are equal in 2d and closely related in 3d, under some mild sampling assumptions.
a rigorous analysis of population stratification with limited data. finding the genetic factors of complex diseases such as cancer, currently a major effort of the international community, will potentially lead to better treatment of these diseases. one of the major difficulties in these studies, is the fact that the genetic components of an individual not only depend on the disease, but also on its ethnicity. therefore, it is crucial to find methods that could reduce the population structure effects on these studies. this can be formalized as a clustering problem, where the individuals are clustered according to their genetic information. mathematically, we consider the problem of clustering bit "feature" vectors, where each vector represents the genetic information of an individual. our model assumes that this bit vector is generated according to a prior probability distribution specified by the individual's membership in a population. we present methods that can cluster the vectors while attempting to optimize the number of features required. the focus of the paper is not on the algorithms, but on showing that optimizing certain objective functions on the data yields the right clustering, under the random generative model. in particular, we prove that some of the previous formulations for clustering are effective. we consider two different clustering approaches. the first approach forms a graph, and then clusters the data using a connected components algorithm, or a max cut algorithm. the second approach tries to estimate simultanously the feature frequencies in each of the populations, and the classification of vectors into populations. we show that using the first approach &theta;(logn/&gamma;2) data (i.e., total number of features times number of vectors) is sufficient to find the correct classification, where n is the number of vectors of each population, and &gamma; is the average l22 distance between the feature probability vectors of the two populations. using the second approach, we show that o(log n/&alpha;4) data is enough, where &alpha; is the average l1 distance between the populations. we also present polynomial time algorithms for the resulting max margin which, for now, needs only slightly more data than stated above. our methods can also be used to give a simple combinatorial algorithm for finding a bisection in a random graph that matches boppana's convex programming approach (and mcsherry's spectral results).
quantum algorithms for simon's problem over general groups. daniel simon's 1994 discovery of an efficient quantum algorithm for solving the hidden subgroup problem (hsp) over zn2 provided one of the first algebraic problems for which quantum computers are exponentially faster than their classical counterparts. in this paper, we study the generalization of simon's problem to arbitrary groups. fixing a finite group g, this is the problem of recovering an involution m = (m1,...,mn) &epsilon; gn from an oracle f with the property that f(x) = f(x &middot; y) ⇔ y &epsilon; {1, m}. in the current parlance, this is the hidden subgroup problem (hsp) over groups of the form gn, where g is a nonabelian group of constant size, and where the hidden subgroup is either trivial or has order two. although groups of the form gn have a simple product structure, they share important representation-theoretic properties with the symmetric groups sn, where a solution to the hsp would yield a quantum algorithm for graph isomorphism. in particular, solving their hsp with the so-called "standard method" requires highly entangled measurements on the tensor product of many coset states. here we give quantum algorithms with time complexity 2o(&radic;n log n) that recover hidden involutions m = (m1,..., mn) &epsilon; gn where, as in simon's problem, each mi is either the identity or the conjugate of a known element m and there is a character x of g for which x(m) = - x(1). our approach combines the general idea behind kuperberg's sieve for dihedral groups with the "missing harmonic" approach of moore and russell. these are the first nontrivial hidden subgroup algorithms for group families that require highly entangled multiregister fourier sampling.
a simple storage scheme for strings achieving entropy bounds. we propose a storage scheme for a string s[1, n], drawn from an alphabet &sigma;, that requires space close to the &kappa;-th order empirical entropy of s, and allows to retrieve any l-long substring of s in optimal o(1+l/log|&sum;|n) time. this matches the best known bounds [14, 7], via the use of binary encodings and tables only. we also apply this storage scheme to prove new time vs space trade-offs for compressed self-indexes [5, 12] and the burrows-wheeler transform [2].
quantum algorithm for a generalized hidden shift problem. consider the following generalized hidden shift problem: given a function f on {0,..., m - 1} x zn promised to be injective for fixed b and satisfying f(b, x) = f(b + 1,x + s) for b = 0, 1,..., m - 2, find the unknown shift s &epsilon; zn. for m = n, this problem is an instance of the abelian hidden subgroup problem, which can be solved efficiently on a quantum computer, whereas for m = 2, it is equivalent to the dihedral hidden subgroup problem, for which no efficient algorithm is known. for any fixed positive &epsilon;, we give an efficient (i.e., poly(log n)) quantum algorithm for this problem provided m &ge; n&epsilon;. the algorithm is based on the "pretty good measurement" and uses h. lenstra's (classical) algorithm for integer programming as a subroutine.
counting colors in boxes. let p be a set of n points in rd, so that each point is colored by one of c given colors. we present algorithms for preprocessing p into a data structure that efficiently supports queries of the form: given an axis-parallel box q, count the number of distinct colors of the points of p &cap; q. we present a general and relatively simple solution that has polylogarithmic query time and worst-case storage about o(nd). it is based on several interesting structural properties of the problem that we derive. we also show that for random inputs, the data structure requires almost linear expected storage. we then present several techniques for achieving space-time tradeoff. in r2, the most efficient solution uses fast matrix multiplication in the preprocessing stage. in higher dimensions we obtain a tradeoff using simpler mechanisms. we give a reduction from matrix multiplication to the offline version of problem, which shows that in r2 our time-space tradeoffs are close to optimal in the sense that improving them substantially would improve the best exponent of matrix multiplication. finally, we present a generalized matrix multiplication problem and show its intimate relation to counting colors in boxes in any dimension.
designing and learning optimal finite support auctions. a classical paper of myerson [18] shows how to construct an optimal (revenue-maximizing) auction in a model where bidders' values are drawn from known continuous distributions. in this paper we show how to adapt this approach to finite support distributions that may be partially unknown. we demonstrate that a myerson-style auction can be constructed in time polynomial in the number of bidders and the size of the support sets. next, we consider the scenario where the mechanism designer knows the support sets, but not the probability of each value. in this situation, we show that the optimal auction may be learned in polynomial time using a weak oracle that, given two candidate auctions, returns one with a higher expected revenue. to study this problem, we introduce a new class of truthful mechanisms which we call order-based auctions. we show that the optimal mechanism is an order-based auction and use the internal structure of this class to prove the correctness of our learning algorithm as well as to bound its running time.
delaunay refinement for piecewise smooth complexes. we present a delaunay refinement algorithm for meshing a piecewise smooth complex in three dimensions. the algorithm protects edges with weighted points to avoid the difficulty posed by small angles between adjacent input elements. these weights are chosen to mimic the local feature size and to satisfy a lipschitz-like property. a delaunay refinement algorithm using the weighted voronoi diagram is shown to terminate with the recovery of the topology of the input. guaranteed bounds on the aspect ratios, normal variation, and dihedral angles are also provided. to this end, we present new concepts and results including a new definition of local feature size and a proof for a generalized topological ball property.
squarepants in a tree: sum of subtree clustering and hyperbolic pants decomposition. we provide efficient constant-factor approximation algorithms for the problems of finding a hierarchical clustering of a point set in any metric space, minimizing the sum of minimimum spanning tree lengths within each cluster, and in the hyperbolic or euclidean planes, minimizing the sum of cluster perimeters. our algorithms for the hyperbolic and euclidean planes can also be used to provide a pants decomposition, that is, a set of disjoint simple closed curves partitioning the plane minus the input points into subsets with exactly three boundary components, with approximately minimum total length. in the euclidean case, these curves are squares; in the hyperbolic case, they combine our euclidean square pants decomposition with our tree clustering method for general metric spaces.
all-pairs bottleneck paths in vertex weighted graphs. let g = (v, e, w) be a directed graph, where w : v &larr; r is an arbitrary weight function defined on its vertices. the bottleneck weight, or the capacity, of a path is the smallest weight of a vertex on the path. for two vertices u, v the bottleneck weight, or the capacity, from u to v, denoted c(u, v), is the maximum bottleneck weight of a path from u to v. in the all-pairs bottleneck paths (apbp) problem we have to find the bottleneck weights for all ordered pairs of vertices. our main result is an o(n2.575) time algorithm for the apbp problem. the exponent is derived from the exponent of fast matrix multiplication. our algorithm is the first sub-cubic algorithm for this problem. unlike the sub-cubic algorithm for the all-pairs shortest paths (apsp) problem, that only applies to bounded (or relatively small) integer edge or vertex weights, the algorithm presented for apbp problem works for arbitrary large vertex weights. the apbp problem has numerous applications, and several interesting problems that have recently attracted attention can be reduced to it, with no asymptotic loss in the running times of the known algorithms for these problems. some examples are a result of vassilevska and williams [stoc 2006] on finding a triangle of maximum weight, a result of bender et al. [soda 2001] on computing least common ancestors in dags and a result of kowaluk and lingas [icalp 2005] on finding maximum witnesses for boolean matrix multiplication. thus, the apbp problem provides a uniform framework for these applications. for some of these problems, we can in fact show that their complexity is equivalent to that of the apbp problem. a slight modification of our algorithm enables us to compute shortest paths of maximum bottleneck weight. let d(u, v) denote the (unweighted) distance from u to v, and let sc(u, v) denote the maximum bottleneck weight of a path from u to v having length d(u, v). the all-pairs bottleneck shortest paths (apbsp) problem is to compute sc(u, v) for all ordered pairs of vertices. we present an algorithm for the apbsp problem whose running time is o(n2.86).
approximating entropy from sublinear samples. we consider the problem of approximating the entropy of a discrete distribution p on a domain of size q, given access to n independent samples from the distribution. it is known that n &ge; q is necessary, in general, for a good additive estimate of the entropy. a problem of multiplicative entropy estimate was recently addressed by batu, dasgupta, kumar, and rubinfeld. they show that n = q&alpha; suffices for a factor-&alpha; approximation, &alpha; > 1. we introduce a new parameter of a distribution--its effective alphabet size qef(p). this is a more intrinsic property of the distribution depending only on its entropy moments. we show qef &le; &otilde;(q). when the distribution p is essentially concentrated on a small part of the domain qef &lt; q. we strengthen the result of batu et al. by showing it holds with qef replacing q. this has several implications. in particular the rate of convergence of the maximum-likelihood entropy estimator (the empirical entropy) for both finite and infinite alphabets is shown to be dictated by the effective alphabet size of the distribution. several new, and some known, facts about this estimator follow easily. our main result is algorithmic. though the effective alphabet size is, in general, an unknown parameter of the distribution, we give an efficient procedure, with access to the alphabet size only, that achieves a factor-&alpha; approximation of the entropy with n = &otilde; (exp {&alpha; 1/4 &middot; log3/4 q &middot; log1/4 qef}). assuming (for instance) log qef &lt; log q this is smaller than any power of q. taking &alpha; &rarr; 1 leads in this case to efficient additive estimates for the entropy as well. in particular, this result shows that for many natural scenarios, a tight estimation of the entorpy may be achieved using a sub-linear sample. several extensions of the results above are discussed.
algorithms and incentives for robust ranking. spam in the form of link spam and click spam has become a major obstacle in the effective functioning of ranking and reputation systems. even in the absence of spam, difficulty in eliciting feedback and self-reinforcing nature of ranking systems are known problems. in this paper, we make a case for sharing with users the revenue generated by such systems as incentive to provide useful feedback and present an incentive based ranking scheme in a realistic model of user behavior which addresses the above problems. we give an explicit ranking algorithm based on user feedback. our incentive structure and ranking algorithm ensure that there is a profitable arbitrage opportunity for the users of the system in correcting the inaccuracies of the ranking. the system is oblivious to the source of inaccuracies (benign or malicious), thus making it robust to spam as well as the problems of eliciting feedback and self-reinforcement.
cheap labor can be expensive. we study markets in which consumers are trying to hire a team of agents to perform a complex task. each agent in the market prices their labor, and based on these prices, consumers hire the cheapest available team capable of doing the job they need done. we define the cheap labor cost in such a market as the ratio of the best nash equilibrium of the original market and the best possible nash equilibrium of any of its submarkets, where "best" is defined with respect to consumers, i.e., we are looking at nash equilibria in which the consumer pays the least. this definition is motivated by a "braess-style" paradox: in certain kinds of marketplaces, competition, in the form of the availability of "cheap labor", can actually cause the prices paid by consumers to go up. we present tight bounds on the cheap labor cost for a variety of markets including s-t path markets, matroid markets and perfect bipartite matching markets. the differences in cheap labor cost across markets demonstrate the complex relationship between the combinatorial structure of the marketplace and the advantages or more precisely, disadvantages to consumers due to competition.
the communication and streaming complexity of computing the longest common and increasing subsequences. we consider the communication complexity of finding the longest increasing subsequence (lis) of a string shared between two parties. we prove tight bounds for the space complexity of randomized one-pass streaming algorithms for this problem. our bounds are parameterized in terms of the lis of the inputs. this resolves an open question in [19]. we also give the first bounds for approximating the lis and its length. next, we consider the communication complexity of finding the longest common subsequece (lcs) of two strings held by different parties, as well as the problem of approximating its length. we improve the existing lower bounds for these problems, even in the most difficult case when both parties have a permutation of n symbols. our results yield tight space bounds for multipass deterministic streaming algorithms. for randomized mutlipass algorithms, our bounds are tight up to a logarithmic factor.
a near-optimal algorithm for computing the entropy of a stream. we describe a simple algorithm for approximating the empirical entropy of a stream of m values in a single pass, using o(&epsilon;-2 log(&delta;-1) log m) words of space. our algorithm is based upon a novel extension of a method introduced by alon, matias, and szegedy [1]. we show a space lower bound of &omega;(&epsilon;-2 / log(&epsilon;-1)), meaning that our algorithm is near-optimal in terms of its dependency on &epsilon;. this improves over previous work on this problem [8, 13, 17, 5]. we show that generalizing to kth order entropy requires close to linear space for all k &ge; 1, and give additive approximations using our algorithm. lastly, we show how to compute a multiplicative approximation to the entropy of a random walk on an undirected graph.
deterministic rendezvous, treasure hunts and strongly universal exploration sequences. we obtain several improved solutions for the deterministic rendezvous problem in general undirected graphs. our solutions answer several problems left open in a recent paper by dessmark et al. we also introduce an interesting variant of the rendezvous problem which we call the deterministic treasure hunt problem. both the rendezvous and the treasure hunt problems motivate the study of universal traversal sequences and universal exploration sequences with some strengthened properties. we call such sequences strongly universal traversal (exploration) sequences. we give an explicit construction of strongly universal exploration sequences. the existence of strongly universal traversal sequences, as well as the solution of the most difficult variant of the deterministic treasure hunt problem, are left as intriguing open problems.
worst case and probabilistic analysis of the 2-opt algorithm for the tsp: extended abstract. 2-opt is probably the most basic and widely used local search heuristic for the tsp. this heuristic achieves amazingly good results on "real world" euclidean instances both with respect to running time and approximation ratio. there are numerous experimental studies on the performance of 2-opt. however, the theoretical knowledge about this heuristic is still very limited. not even its worst case running time on euclidean instances was known so far. in this paper, we clarify this issue by presenting a family of euclidean instances on which 2-opt can take an exponential number of steps. previous probabilistic analyses were restricted to instances in which n points are placed uniformly at random in the unit square [0, 1]2, where it was shown that the expected number of steps is bounded by &otilde;(n10) for euclidean instances. we consider a more advanced model of probabilistic instances in which the points can be placed according to general distributions on [0, 1]2. in particular, we allow different distributions for different points. we study the expected running time in terms of the number n of points and the maximal density &phis; of the probability distributions. we show an upper bound on the expected length of any 2-opt improvement path of &otilde;(n4+1/3 &middot; &phis;8/3). when starting with an initial tour computed by an insertion heuristic, the upper bound on the expected number of steps improves even to &otilde;(n3+5/6 &middot; &phis;8/3). if the distances are measured according to the manhattan metric, then the expected number of steps is bounded by &otilde;(n3+1/2 &middot; &phis;). in addition, we prove an upper bound of o(&radic;&phis;) on the expected approximation factor with respect to both of these metrics. let us remark that our probabilistic analysis covers as special cases the uniform input model with &phis; = 1 and a smoothed analysis with gaussian perturbations of standard deviation &sigma; with &phis; ~ 1/&sigma;2. besides random metric instances, we also consider an alternative random input model in which an adversary specifies a graph and distributions for the edge lengths in this graph. in this model, we achieve even better results on the expected running time of 2-opt.
the quantum schur and clebsch-gordan transforms: i. efficient qudit circuits. we present an efficient family of quantum circuits for a fundamental primitive in quantum information theory, the schur transform. the schur transform on n d-dimensional quantum systems is a transform between a standard computational basis to a labelling related to the representation theory of the symmetric and unitary groups. if we desire to implement the schur transform to an accuracy of &epsilon;-1, then our circuit construction uses a number of gates which is polynomial in n, d and log(&epsilon;-1). the key tool in our construction is a poly(d, log n, log(&epsilon;-1)) algorithm for the ud clebsch-gordan transform. our efficient circuit construction renders numerous protocols in quantum information theory computationally tractable and yields a new possible approach to quantum algorithms which is distinct from the standard paradigm of the quantum fourier transform.
whole genome duplications, multi-break rearrangements, and genome halving problem. the genome halving problem, motivated by the whole genome duplication events in molecular evolution, was solved by el-mabrouk and sankoff. the el-mabrouk-sankoff algorithm is rather complex inspiring a quest for a simpler solution. an alternative approach to genome halving problem based on the notion of the contracted breakpoint graph was recently proposed in [2]. this new technique reveals that while the el-mabrouk-sankoff result is correct in most cases, it does not hold in the case of unichromosomal genomes. this raises a problem of correcting el-mabrouk-sankoff analysis and devising an algorithm that deals adequately with all genomes. in this paper we efficiently classify all genomes into two classes and show that while the el-mabrouk-sankoff theorem holds for the first class, it is incorrect for the second class. the crux of our analysis is a new combinatorial invariant defined on duplicated permutations. using this invariant we were able to come up with a full proof of the genome halving theorem and a polynomial algorithm for genome halving problem (for unichromosomal genomes). we also give the first short proof of the original el-mabrouk-sankoff result for multichromosomal genomes. finally, we discuss a generalization of genome halving problem for a more general set of rearrangement operations (including transpositions) and propose an efficient algorithm for solving this problem.
dynamic weighted ancestors. in the weighted ancestor problem one preprocesses a weighted tree (the weights are on the nodes and increase with tree depth) to support predecessor queries, which are called weighted ancestors queries, on the paths from the query node to the root. since, the weighted ancestor problem appears in numerous applications, the problem has been studied and solutions for static trees are well known. however, it has been an open question whether this can be solved optimally for the dynamic version of the problem, where node insertions are supported. node insertions are leaf insertions or edge splittings. in this paper we present a solution for the dynamic weighted ancestors problem which supports queries and update operations in the same time bounds as those for dynamic predecessor structures.
maximum independent sets in graphs of low degree. we study computational complexity of the maximum independent set problem on graphs of bounded vertex degree. in general, this problem is np-hard. however, under certain restrictions it becomes polynomial-time solvable. we identify three graph properties to which the complexity of the problem is sensible.
the -orientability thresholds for . we prove that, for k &ge; 2, the k-orientability threshold for the random graph gn, p coincides with the threshold at which the (k + 1)-core has average degree 2k. the proof involves the analysis of a heuristic algorithm that attempts to find a k-orientation of the random graph. the k-orientation threshold has several applications including offline balanced allocation with a limit of k on maximum bin-size, perfect hashing with a limit of k on maximum chain-length, and concurrent access to parallel memories through redundancy,
an algebraic algorithm for weighted linear matroid intersection. we present a new algebraic algorithm for the classical problem of weighted matroid intersection. this problem generalizes numerous well-known problems, such as bipartite matching, network flow, etc. our algorithm has running time &otilde;(nr&omega;-1w1+&epsilon;) for linear matroids with n elements and rank r, where &omega; is the matrix multiplication exponent, and w denotes the maximum weight of any element. this algorithm is the fastest known when w is small. our approach builds on the recent work of sankowski (2006) for weighted bipartite matching and harvey (2006) for unweighted linear matroid intersection.
estimating the sortedness of a data stream. the distance to monotonicity of a sequence is the minimum number of edit operations required to transform the sequence into an increasing order; this measure is complementary to the length of the longest increasing subsequence (lis). we address the question of estimating these quantities in the one-pass data stream model and present the first sub-linear space algorithms for both problems. we first present o(&radic;n)-space deterministic algorithms that approximate the distance to monotonicity and the lis to within a factor that is arbitrarily close to 1. we also show a lower bound of &omega;(n) on the space required by any randomized algorithm to compute the lis (or alternatively the distance from monotonicity) exactly, demonstrating that approximation is necessary for sub-linear space computation; this bound improves upon the existing lower bound of &omega;(&radic;n) [lnvz06]. our main result is a randomized algorithm that uses only o(log2 n) space and approximates the distance to monotonicity to within a factor that is arbitrarily close to 4. in contrast, we believe that any significant reduction in the space complexity for approximating the length of the lis is considerably hard. we conjecture that any deterministic (1 + &epsilon;) approximation algorithm for lis requires &omega; (&radic;n) space, and as a step towards this conjecture, prove a space lower bound of &omega;(&radic;n) for a restricted yet natural class of deterministic algorithms.
finding a heaviest triangle is not harder than matrix multiplication. we show that for any &epsilon; > 0, a maximum-weight triangle in an undirected graph with n vertices and real weights assigned to vertices can be found in time o(n&omega; + n2+&epsilon;), where &omega; is the exponent of fastest matrix multiplication algorithm. by the currently best bound on &omega;, the running time of our algorithm is o(n2.376). our algorithm substantially improves the previous time-bounds for this problem recently established by vassilevska et al. (stoc 2006, o(n2.688)) and (icalp 2006, o(n2.575)). its asymptotic time complexity matches that of the fastest known algorithm for finding a triangle (not necessarily a maximum-weight one) in a graph. by applying or extending our algorithm, we can also improve the upper bounds on finding a maximum-weight triangle in a sparse graph and on finding a maximum-weight subgraph isomorphic to a fixed graph established in the papers by vassilevska et al. for example, we can find a maximum-weight triangle in a vertex-weighted graph with m edges in asymptotic time required by the fastest algorithm for finding any triangle in a graph with m edges, i.e., in time o(m1.41).
fast elimination of redundant linear equations and reconstruction of recombination-free mendelian inheritance on a pedigree. computational inference of haplotypes from genotypes has attracted a great deal of attention in the computational biology community recently, partially driven by the international hapmap project. in this paper, we study the question of how to efficiently infer haplotypes from genotypes of individuals related by a pedigree, assuming that the hereditary process was free of mutations (i.e. the mendelian law of inheritance) and recombinants. the problem has recently been formulated as a system of linear equations over the finite field of f(2) and solved in o(m3n3) time by using standard gaussian elimination, where m is the number of loci (or markers) in a genotype and n the number of individuals in the pedigree. we give a much faster algorithm with running time o(mn2 + n3 log2 n log log n). the key ingredients of our construction are (i) a new system of linear equations based on some spanning tree of the pedigree graph and (ii) an efficient method for eliminating redundant equations in a system of o(mn) linear equations over o(n) variables. although such a fast elimination method is not known for general systems of linear equations, we take advantage of the underlying pedigree graph structure and recent progress on low-stretch spanning trees.
minimizing movement. we give approximation algorithms and inapproximability results for a class of movement problems. in general, these problems involve planning the coordinated motion of a large collection of objects (representing anything from a robot swarm or firefighter team to map labels or network messages) to achieve a global property of the network while minimizing the maximum or average movement. in particular, we consider the goals of achieving connectivity (undirected and directed), achieving connectivity between a given pair of vertices, achieving independence (a dispersion problem), and achieving a perfect matching (with applications to multicasting). this general family of movement problems encompasses an intriguing range of graph and geometric algorithms, with several real-world applications and a surprising range of approximability. in some cases, we obtain tight approximation and inapproximability results using direct techniques (without use of pcp), assuming just that p &ne; np.
improved algorithms for path, matching, and packing problems. improved randomized and deterministic algorithms are presented for path, matching, and packing problems. our randomized algorithms are based on the divide-and-conquer technique, and improve previous best algorithms for these problems. for example, for the k-path problem, our randomized algorithm runs in time o(4kk3.42m) and space o(nklogk + m), improving the previous best randomized algorithm for the problem that runs in time o(5.44kkm) and space o(2kkn + m). to achieve improved deterministic algorithms, we study a number of previously proposed de-randomization schemes, and also develop a new derandomization scheme. these studies result in a number of deterministic algorithms: one of time o(4k+o(k)m) for the k-path problem, one of time o(2.803kk nlog2 n) for the 3-d matching problem, and one of time o(43k+o(k)n) for the 3-set packing problem. all these significantly improve previous best algorithms for the problems.
scrambling adversarial errors using few random bits, optimal information reconciliation, and better private codes. communicating over a noisy channel is typically much easier when errors are drawn from a fixed, known distribution than when they are chosen adversarially. this paper looks at how one can use schemes designed for random errors in an adversarial context, at the cost of few additional random bits and without relying on unproven computational assumptions. the basic approach is to permute the positions of a bit string using a permutation drawn from a t-wise independent family, where t = o(n). this leads to several new results: &bull; we show that concatenated codes can correct errors up to the shannon capacity even when the errors are only slightly random --- it is sufficient that they be t-wise independently distributed, for t roughly &omega;(log n). &bull; we construct computationally efficient information reconciliation protocols correcting pn adversarial binary hamming errors with optimal communication complexity and entropy loss n(h(p) + o(1)) bits, where n is the length of the strings and h() is the binary entropy function. information reconciliation protocols allow cooperating parties to correct errors in a shared string. they are important tools in two applications: first, for dealing with noisy secrets in cryptography; second, for synchronizing remote copies of large files. entropy loss measures how much information is leaked to an eavesdropper listening in on the protocol. &bull; we improve the randomness complexity (key length) of efficiently decodable capacity-approaching private codes from &theta;(n log n) to n + o(n). we also present a simplified proof of an existential result on private codes due to langberg (focs '04).
restricted strip covering and the sensor cover problem. suppose we are given a set of objects that cover a region and a duration associated with each object. viewing the objects as jobs, can we schedule their beginning times to maximize the length of time that the original region remains covered? we call this problem the sensor cover problem. it arises in the context of covering a region with sensors. for example, suppose you wish to monitor activity along a fence (interval) by sensors placed at various fixed locations. each sensor has a range (also an interval) and limited battery life. the problem is then to schedule when to turn on the sensors so that the fence is fully monitored for as long as possible. this one-dimensional problem involves intervals on the real line. associating a duration to each yields a set of rectangles in space and time, each specified by a pair of fixed horizontal endpoints and a height. the objective is to assign a bottom position to each rectangle (by moving them up or down) so as to maximize the height at which the spanning interval is fully covered. we call this one-dimensional problem restricted strip covering. if we replace the covering constraint by a packing constraint (rectangles may not overlap, and the goal is to minimize the highest point covered), then the problem becomes identical to dynamic storage allocation, a well-studied scheduling problem, which is in turn a restricted case of the well known problem strip packing. we present a collection of algorithms for restricted strip covering. we show that the problem is np-hard and present an o(log log log n)-approximation algorithm. we also present better approximation or exact algorithms for some special cases, including when all intervals have equal width. for the general sensor cover problem, we distinguish between cases in which elements have uniform or variable durations. the results depend on the structure of the region to be covered: we give a polynomial-time, exact algorithm for the uniform-duration case of restricted strip covering but prove that the uniform-duration case for higher-dimensional regions is np-hard. we give some more specific results for two-dimensional regions. finally, we consider regions that are arbitrary sets, and we present an o(log n)-approximation algorithm for the most general case.
semi-oblivious routing: lower bounds. we initiate the study of semi-oblivious routing, a relaxation of oblivious routing which is first introduced by r&auml;cke and led to many subsequent improvements and applications. in semi-oblivious routing like oblivious routing, the algorithm should select only a polynomial number of paths between the source and the sink of each commodity, but unlike oblivious routing, the flow from each source to its sink is not just a scalar multiple of the single-commodity flow; any amount of flow can be sent along each selected path. semi-oblivious routing has several applications in traffic engineering and vlsi routing. trivially, any competitive ratio &rho; for oblivious routing (includling the polylogarthimic ratio in undirected graphs obtained by r&auml;cke) also implies competitive ratio &rho; for semi-oblivious routing. in this paper, we focus on lower bounds. we rule out the possibility of o(1) competitive ratio for semi-oblivious routing in undirected graphs by providing a lower bound of &omega;(log n/log log n) in grids or even series-parallel graphs. more strongly in directed graphs, we rule out the possibility of sub-polynomial competitive ratio when the number of paths between each source and its sink is in o(n1/5). the proof of our lower bound on the grid uses a non-markovian random walk on the integers with a mixing property which may be of independent interest. last but not least, our lower bounds on the grid can be significantly strengthened to show that with paths of at most b bends, the competitive ratio is in &omega;(n1/2b+1). this answers negatively a long-standing open problem on b-bend routing schemes in grids posed e.g. in [10, 6].
planar graphs are in 1-string. we prove that every planar graph is the intersection graph of strings in the plane, such that any two strings intersect at most once.
approximation algorithms for embedding general metrics into trees. we consider the problem of embedding general metrics into trees. we give the first non-trivial approximation algorithm for minimizing the multiplicative distortion. our algorithm produces an embedding with distortion (c log n)o(&radic;log &delta;), where c is the optimal distortion, and &delta; is the spread of the metric (i.e. the ratio of the diameter over the minimum distance). we give an improved o(1)-approximation algorithm for the case where the input is the shortest path metric over an unweighted graph. moreover, we show that by composing our approximation algorithm for embedding general metrics into trees, with the approximation algorithm of [bcis05] for embedding trees into the line, we obtain an improved approximation algorithm for embedding general metrics into the line. we also provide almost tight bounds for the relation between embedding into trees and embedding into spanning subtrees. we show that for any unweighted graph g, the ratio of the distortion required to embed g into a spanning subtree, over the distortion of an optimal tree embedding of g, is at most o(log n). we complement this bound by exhibiting a family of graphs for which the ratio is &omega;(log n/log log n).
linear programming relaxations of maxcut. it is well-known that the integrality gap of the usual linear programming relaxation for maxcut is 2 - &epsilon;. for general graphs, we prove that for any &epsilon; and any fixed bound k, adding linear constraints of support bounded by k does not reduce the gap below 2 - &epsilon;. we generalize this to prove that for any &epsilon; and any fixed bound k, strengthening the usual linear programming relaxation by doing &kappa; rounds of sherali-adams lift-and-project does not reduce the gap below 2 - &epsilon;. on the other hand, we prove that for dense graphs, this gap drops to 1 + &epsilon; after adding all linear constraints of support bounded by some constant depending on &epsilon;.
matrix scaling by network flow. a given nonnegative n x n matrix a = (aij) is to be scaled, by multiplying its rows and columns by unknown positive multipliers &lambda;i and &mu;j, such that the resulting matrix (aij&lambda;i&mu;j) has specified row and column sums ri and sj. we give an algorithm that achieves the desired row and column sums with a maximum absolute error &epsilon; in o(n4(log n + log h/&epsilon;)) steps, where h is the overall total of the result matrix. our algorithm is a scaling algorithm. it solves a sequence of more and more refined discretizations. the discretizations are minimum-cost network flow problems with convex piecewise linear costs. these discretizations are interesting in their own right because they arise in proportional elections.
buying cheap is expensive: hardness of non-parametric multi-product pricing. we investigate non-parametric unit-demand pricing problems, in which we want to find revenue maximizing prices for products p based on a set of consumer profiles c. a consumer profile consists of a number of non-zero budgets for different products and possibly an additional product ranking. once prices are fixed, each consumer chooses to buy one of the products she can afford based on some predefined selection rule. we distinguish between the min-buying, max-buying, and rank-buying models. for the min-buying model we show that it is not approximable within o(log&epsilon; |c|) for some constant &epsilon; > 0, unless np &sube; dtime(no(loglogn(), thereby closing the gap between the known algorithmic results and previous lower bounds. we also prove inapproximability within o(&ell;&epsilon;), &ell; being an upper bound on the number of non-zero budgets per consumer, and o(|p|epsi;) under slightly stronger assumptions and provide matching upper bounds. surprisingly, these hardness results hold even if a price ladder constraint, i.e., a predefined order on the prices of all products, is given. for the max-buying model a ptas exists if a price ladder is given. we give a matching lower bound by proving strong np-hardness. assuming limited product supply, we analyze a generic local search algorithm and prove that it is 2-approximate. finally, we discuss implications for the rank-buying model.
succinct indexes for strings, binary relations and multi-labeled trees. we define and design succinct indexes for several abstract data types (adts). the concept is to design auxiliary data structures that occupy asymptotically less space than the information-theoretic lower bound on the space required to encode the given data, and support an extended set of operations using the basic operators defined in the adt. as opposed to succinct (integrated data/index) encodings, the main advantage of succinct indexes is that we make assumptions only on the adt through which the main data is accessed, rather than the way in which the data is encoded. this allows more freedom in the encoding of the main data. in this paper, we present succinct indexes for various data types, namely strings, binary relations and multi-labeled trees. given the support for the interface of the adts of these data types, we can support various useful operations efficiently by constructing succinct indexes for them. when the operators in the adts are supported in constant time, our results are comparable to previous results, while allowing more flexibility in the encoding of the given data. using our techniques, we design a succinct encoding that represents a string of length n over an alphabet of size &sigma; using nhk + o(n lg &sigma;) bits1 to support access/rank/select operations in o((lg lg &sigma;)3) time. we also design a succinct text index using nhk + o(n lg &sigma;) bits that supports pattern matching queries in o(m lg lg &sigma; + occ lg1+&epsilon; nlg lg &sigma;) time, for a given pattern of length m. previous results on these two problems either have a lg &sigma; factor instead of lg lg &sigma; in terms of running time, or are not compressible.
a linear work, o(n) time, parallel algorithm for solving planar laplacians. we present a linear work parallel iterative algorithm for solving linear systems involving laplacians of planar graphs. in particular, if ax = b, where a is the laplacian of any planar graph with n nodes, the algorithm produces a vector x such that ||x--x||a &le; &epsilon;, in o(n1/6+clog(1/&epsilon;)) parallel time, doing o(nlog(1/&epsilon;)) work, where c is any positive constant. one of the key ingredients of the solver, is an o(nklog2k) work, o(klogn) time, parallel algorithm for decomposing any embedded planar graph into components of size o(k) that are delimited by o(n/&radic;k) boundary edges. the result also applies to symmetric diagonally dominant matrices of planar structure.
making deterministic signatures quickly. we present a new technique of universe reduction. primary applications are the dictionary problem and the predecessor problem. we give several new results on static dictionaries in different computational models: the word ram, the practical ram, and the cache-oblivious model. all algorithms and data structures are deterministic and use linear space. representative results are: a dictionary with a lookup time of o(log log n) and construction time of o(n) on sorted input on a word ram, and a static predecessor structure for variable- and unbounded length binary strings that in the cache-oblivious model has a query performance of o(&verbar;s&verbar;/b + log &verbar;s&verbar;) i/os, for query argument s.
optimization problems in multiple-interval graphs. multiple-interval graphs are a natural generalization of interval graphs where each vertex may have more then one interval associated with it. we initiate the study of optimization problems in multiple-interval graphs by considering three classical problems: minimum vertex cover, minimum dominating set, and maximum clique. we describe applications for each one of these problems, and then proceed to discuss approximation algorithms for them. our results can be summarized as follows: let t be the number of intervals associated with each vertex in a given multiple-interval graph. for minimum vertex cover, we give a (2&minus;1/t)-approximation algorithm which also works when a t-interval representation of our given graph is absent. following this, we give a t2-approximation algorithm for minimum dominating set which adapts well to more general variants of the problem. we then proceed to prove that maximum clique is np-hard already for 3-interval graphs, and provide a (t2&minus;t+1)/2-approximation algorithm for general values of t &geq; 2, using bounds proven for the so-called transversal number of t-interval families.
approximation algorithms for prize collecting forest problems with submodular penalty functions. in this paper, we study the prize-collecting version of constrained forest problems with an arbitrary 0-1 connectivity requirement function and a submodular penalty function. our framework generalizes the prize collecting generalized steiner tree framework of hajiaghayi and jain [hj06] to incorporate more general connectivity requirements and penalty functions. we generalize their primal-dual algorithm using submodular function minimization to give a 3-approximation algorithm, and devise an lp rounding algorithm with a performance guarantee of 2.54.
combinatorial algorithms for web search engines: three success stories. how much can smart combinatorial algorithms improve web search engines? to address this question we will describe three algorithms that have had a positive impact on web search engines: the pagerank algorithm, algorithms for finding near-duplicate web pages, and algorithms for index server loadbalancing.
distributed algorithms for multicommodity flow problems via approximate steepest descent framework. we consider solutions for distributed multicommodity flow problems, which are solved by multiple agents operating in a cooperative but uncoordinated manner. we show first distributed solutions that allow 1 + &epsilon; approximation and whose convergence time is essentially linear in the maximal path length, and is independent of the number of commodities and the size of the graph. our algorithms use a very natural approximate steepest descent framework, combined with a blocking flow technique to speed up the convergence in distributed and parallel environment. previously known solutions that achieved comparable convergence time and approximation ratio required exponential computational and space overhead per agent.
pagerank and the random surfer model. in recent years there has been considerable interest in analyzing random graph models for the web. we consider two such models - the random surfer model, introduced by blum et al. [7], and the pagerank-based selection model, proposed by pandurangan et al. [18]. it has been observed that search engines influence the growth of the web. the pagerank-based selection model tries to capture the effect that these search engines have on the growth of the web by adding new links according to pagerank. the pagerank algorithm is used in the google search engine [1] for ranking search results. we show the equivalence of the two random graph models and carry out the analysis in the random surfer model, since it is easier to work with. we analyze the expected in-degree of vertices and show that it follows a powerlaw. we also analyze the expected pagerank of vertices and show that it follows the same powerlaw as the expected degree. we show that in both models the expected degree and the pagerank of the first vertex, the root of the graph, follow the same powerlaw. however, the power undergoes a phase-transition as we vary the parameter of the model. this peculiar behavior of the root has not been observed in previous analysis and simulations of the two models.
fully polynomial time approximation schemes for stochastic dynamic programs. we develop a framework for obtaining (deterministic) fully polynomial time approximation schemes (fptass) for stochastic univariate dynamic programs with either convex or monotone single-period cost functions. using our framework, we give the first fptass for several np-hard problems in various fields of research such as knapsack-related problems, logistics, operations management, economics, and mathematical finance.
charity auctions on social networks. charitable giving is influenced by many social, psychological, and economic factors. one common way to encourage individuals to donate to charities is by offering to match their contribution (often by their employer or by the government). conitzer and sandholm introduced the idea of using auctions to allow individuals to offer to match the contribution of others. we explore this idea in a social network setting, where individuals care about the contribution of their neighbors, and are allowed to specify contributions that are conditional on the contribution of their neighbors. we give a mechanism for this setting that raises the largest individually rational contributions given the conditional bids, and analyze the equilibria of this mechanism in the case of linear utilities. we show that if the social network is strongly connected, the mechanism always has an equilibrium that raises the maximum total contribution (which is the contribution computed according to the true utilities); in other words, the price of stability of the game defined by this mechanism is one. interestingly, although the mechanism is not dominant strategy truthful (and in fact, truthful reporting need not even be a nash equilibrium of this game), this result shows that the mechanism always has a full-information equilibrium which achieves the same outcome as in the truthful scenario. of course, there exist cases where the maximum total contribution even with true utilities is zero: we show that the existence of non-zero equilibria can be characterized exactly in terms of the largest eigenvalue of the utility matrix associated with the social network.
cutting cycles of rods in space: hardness and approximation. we study the problem of cutting a set of rods (line segments in ℝ3) into fragments, using a minimum number of cuts, so that the resulting set of fragments admits a depth order. we prove that this problem is np-complete, even when the rods have only three distinct orientations. we also give a polynomial-time approximation algorithm with no restriction on rod orientation that computes a solution of size o(&tau; log &tau; log log &tau;), where &tau; is the size of an optimal solution.
improved algorithms for orienteering and related problems. in this paper we consider the orienteering problem in undirected and directed graphs and obtain improved approximation algorithms. the point to point-orienteering-problem is the following: given an edge-weighted graph g = (v, e) (directed or undirected), two nodes s, t &isin; v and a budget b, find an s-t walk in g of total length at most b that maximizes the number of distinct nodes visited by the walk. this problem is closely related to tour problems such as tsp as well as network design problems such as k-mst. our main results are the following. &bull; a 2 + &epsilon; approximation in undirected graphs, improving upon the 3-approximation from [6]. &bull; an o(log2 opt) approximation in directed graphs. previously, only a quasi-polynomial time algorithm achieved a poly-logarithmic approximation [14] (a ratio of o (log opt)). the above results are based on, or lead to, improved algorithms for several other related problems.
minimizing average latency in oblivious routing. we consider the problem of minimizing average latency cost while obliviously routing traffic in a network with linear latency functions. this is roughly equivalent to minimizing the function &sigma;e(load(e))2, where for a network link e, load(e) denotes the amount of traffic that has to be forwarded by the link. we show that for the case when all routing requests are directed to a single target, there is a routing scheme with competitive ratio o(log n, where n denotes the number of nodes in the network. as a lower bound we show that no oblivious scheme can obtain a competitive ratio of better than &omega;(&radic;log n). this latter result gives a qualitative difference in the performance that can be achieved by oblivious algorithms and by adaptive online algorithms, respectively, since there exist a constant competitive online routing algorithm for the cost-measure of average latency [2]. such a qualitative difference (in general undirected networks) between the performance of online algorithms and oblivious algorithms was not known for other cost measures (e.g. edge-congestion).
the effect of induced subgraphs on quasi-randomness. one of the main questins that arise when studying random and quasi-random structures is which properties p are such that any object that satisfies p "behaves" like a truly random one. in the context of graphs, chung, graham, and wilson [9] call a graph p-quasi-random if it satisfies a long list of the properties that hold in g(n, p) with high probability, like edge distribution, spectral gap, cut size, and more. our main result here is that the following holds for any fixed graph h: if the distribution of induced copies of h in a graph g is close (in a well defined way) to the distribuition we would expect to have in g(n,p), then g is either p-quasi-random or p-quasirandom, where &pmacr; is the unique non-trivial solution of the polynomial equation x&delta; (1 -- x)1-&delta; = p&delta; (1 -- p)1--&delta;, with &delta; being the edge density of h. we thus infer that having the correct distribution of induced copies of any single graph h, is enough to guarantee that a graph has the properties of a random one. the proof techniques we develop here, which combine probabilistic, algebraic and combinatorial tools, may be of independent interest to the study of quasi-random structures.
lower-bounded facility location. we study the lower-bounded facility location problem, which generalizes the classical uncapacitated facility location problem in that it comes with lower bound constraints for the number of clients assigned to a facility in the case that this facility is opened. this problem was introduced independently in the papers by karger and minkoff [12] and by guha, meyerson, and munagala [7], both of which give bicriteria approximation algorithms for it. these bicriteria algorithms come within a constant factor of the optimal solution cost, but they also violate the lower bound constraints by a constant factor. our result in this paper is the first true approximation algorithm for the lower-bounded facility location problem, which respects the lower bound constraints and achieves a constant approximation ratio for the objective function. the main technical idea for the design of the algorithm is a reduction to the capacitated facility location problem, which has known constant-factor approximation algorithms.
adaptive local ratio. local ratio is a well-known paradigm for designing approximation algorithms for combinatorial optimization problems. at a very high level, a local ratio algorithm first decomposes the input weight function w into a positive linear combination of simpler weight functions or models. guided by this process a solution s is constructed such that s is &alpha;-approximate with respect to each model used in the decomposition. as a result, s is &alpha;-approximate under w as well. these models usually have a very simple structure that remains "unchanged" throughout the execution of the algorithm. in this work we show that adaptively choosing a model from a richer spectrum of functions can lead to a better local ratio. indeed, by turning the search for a good model into an optimization problem of its own, we get improved approximations for a data migration problem.
deterministic random walks on regular trees. jim propp's rotor router model is a deterministic analogue of a random walk on a graph. instead of distributing chips randomly, each vertex serves its neighbors in a fixed order. cooper and spencer (comb. probab. comput. (2006)) show a remarkable similarity of both models. if an (almost) arbitrary population of chips is placed on the vertices of a grid zd and does a simultaneous walk in the propp model, then at all times and on each vertex, the number of chips deviates from the expected number the random walk would have gotten there, by at most a constant. this constant is independent of the starting configuration and the order in which each vertex serves its neighbors. this result raises the question if all graphs do have this property. with quite some effort, we are now able to answer this question negatively. for the graph being an infinite k-ary tree (k &ge; 3), we show that for any deviation d there is an initial configuration of chips such that after running the propp model for a certain time there is a vertex with at least d more chips than expected in the random walk model. however, to achieve a deviation of d it is necessary that at least k&theta;(d) vertices contribute by being occupied by a number of chips not divisible by k in a certain time interval.
iterated rounding algorithms for the smallest -edge connected spanning subgraph. we present the best known algorithms for approximating the minimum cardinality undirected k-edge connected spanning subgraph. for simple graphs our approximation ratio is 1 + 1/2k + o(1/k2). the more precise version of our bound requires k &ge; 7, and for all such k it improves the longstanding bound of cheriyan and thurimella, 1 + 2/(k + 1) [2]. the improvement comes in two steps: first we show that for simple k-edge connected graphs, any laminar family of degree k sets is smaller than the general bound (n(1 + 3/k + o(1/k&radic;k)) versus 2n). this immediately implies that iterated rounding improves the bound of [2]. our second step improves iterated rounding by finding good edges for rounding. for multigraphs our approximation ratio is 1 + 21/11k < 1 + 1.91/k. this improves the previous bound 1 + 2/k [6]. it is of interest since it is known that for some constant c > 0, an approximation ratio &le; 1 + c/k implies p = np. our approximation ratio extends to the minimum cardinality steiner network problem, where k denotes the average vertex demand. the algorithm exploits rounding properties of the first two linear programs in iterated rounding.
a local algorithm for finding dense subgraphs. a local graph algorithm is one that searches for an approximation of the best solution near a specified starting vertex, and has a running time independent of the size of the graph. recently, local algorithms have been developed for graph partitioning and clustering. in this paper, we present a local algorithm for finding dense subgraphs of bipartite graphs, according to the measure of density proposed by kannan and vinay. the algorithm takes as input a bipartite graph with a specified starting vertex, and attempts to find a dense subgraph near that vertex. we prove the following local approximation guarantee for the algorithm. for any subgraph s with k vertices and density &theta;, there is a large set of starting vertices within s for which the algorithm produces a subgraph with density &omega;(&theta;/log &delta;), where &delta; is the maximum degree. the running time of the algorithm is o(&delta;k2), independent of the number of vertices in the graph.
optimal universal graphs with deterministic embedding. let h be a finite family of graphs. a graph g is h-universal if it contains a copy of each h &isin; h as a subgraph. let h(k,n) denote the family of graphs on n vertices with maximum degree at most k. for all admissible k and n, we construct an h(k, n)-universal graph g with at most ckn2-2/k edges, where ck is a constant depending only on k. this is optimal, up to the constant factor ck, as it is known that c'kn2-2/k is a lower bound for the number of edges in any such graph. the construction of g is explicit, and there is an efficient deterministic algorithm for finding a copy of any given h &isin; h(k,n) in g.
approximating tsp on metrics with bounded global growth. the traveling salesman problem (tsp) is a canonical np-complete problem which is known to be max-snp hard even on (high-dimensional) euclidean metrics [39]. in order to circumvent this hardness, researchers have been developing approximation schemes for low-dimensional metrics [4, 38] (under different notions of dimension). however, a feature of most current notions of metric dimension is that they are "local": the definitions require every local neighborhood to be well-behaved. in this paper, we consider the case when the metric is less restricted: it has a few "dense" regions, but is "well-behaved on the average"? to this end, we define a global notion of dimension which we call the correlation dimension (denoted by dimc), which generalizes the popular notion of doubling dimension. in fact, the class of metrics with dimc = o(1) not only contains all doubling metrics, but also contains some metrics containing uniform submetrics of size &radic;n. we first show, using a somewhat "local" argument, that one can solve tsp on these metrics in time 2o(&radic;n); we then take advantage of the global nature of tsp (and the global nature of our definition) to give a (1 + &epsilon;)-approximation algorithm that runs in sub-exponential time: i.e., in 2o(n&delta;&epsilon;-4dimc)-time for every constant 0 < &delta; < 1.
geometric and topological guarantees for the wrap reconstruction algorithm. we describe a variant of edelsbrunner's wrap algorithm for surface reconstruction, for which we can prove geometric and topological guarantees within the &epsilon;-sampling model. the wrap algorithm is based on ideas from morse theory applied to the flow map induced by certain distance function. the variant is made possible by a previous result on the "separation" of critical points for a related distance function that directly applies in this case. though the variant is easily proposed, in order to prove the quality guarantees for the output, we need to closely investigate the geometric properties of the flow map.
on bounded leg shortest paths problems. let v be a set of points in a d-dimensional lp-metric space. let s, t &epsilon; v and let l be any real number. an l-bounded leg path from s to t is an ordered set of points which connects s to t such that the leg between any two consecutive points in the set is at most l. the minimal path among all these paths is the l-bounded leg shortest path from s to t. in the s-t bounded leg shortest path (stblsp) problem we are given two points s and t and a real number l, and are required to compute an l-bounded leg shortest path from s to t. in the all-pairs bounded leg shortest path (apblsp) problem we are required to build a data structure that, given any two query points from v and any real number l, outputs the length of the l-bounded leg shortest path (a distance query) or the path itself (a path query). in this paper present first an algorithm for the apblsp problem in any lp-metric which, for any fixed &epsilon; > 0, computes in o(n3 n = log2 n &middot; &epsilon;-d)) time a data structure which approximates any bounded leg shortest path within a multiplicative error of (1 + &epsilon;). it requires o(n2log n) space and distance queries are answered in o (log log n) time. this improves on an algorithm with running time of o(n5) given by bose et al. in [8]. we present also an algorithm for the stblsp problem that, given s, t &isin; v and a real number l, computes in o(n &middot; polylog(n)) the exact l-bounded shortest path from s to t. this algorithm works in l1 and l&infin; metrics. in the euclidean metric we also obtain an exact algorithm but with a running time of o(n4/3+&epsilon;), for any &epsilon; > 0. we end by showing that for any weighted directed graph there is a data structure of size o(n2.5log n) which is capable of answering path queries with a multiplicative error of (1 + &epsilon;) in o (log log n + &ell;) time, where &ell; is the length of the reported path. our results improve upon the results given by bose et al. [8]. our algorithms incorporate several new ideas along with an interesting observation made on geometric spanners, which is of an independent interest.
faster dynamic matchings and vertex connectivity. we present first fully dynamic subquadratic algorithms for: computing maximum matching size, computing maximum bipartite matching weight, computing maximum number of vertex disjoint s, t paths and testing directed vertex k-connectivity of the graph. the presented algorithms are randomized. the algorithms for maximum matching size and disjoint paths support operations in o(n1.495) time. the algorithm for computing the maximum bipartite matching weight maintains the graph with integer edge weights from the set 1,..., w in o(w2.495n1.495) time. the algorithm for testing directed vertex k-connectivity supports updates in o(n1.575 + nk2) time. for all of these problems the presented dynamic algorithms break the input size barrier --- o(n2). as a side result we obtain a dynamic algorithm for the dynamic maintenance of the rank of the matrix that support updates in o(n1.495) time.
yet another algorithm for dense max cut: go greedy. we study dense instances of maxcut and its generalizations. following a long list of existing, diverse and often sophisticated approximation schemes, we propose taking the na&iuml;ve greedy approach; we prove that when the vertices are considered in random order, our algorithms are still approximation schemes. our algorithms may be simple, but the analysis is not. it relies on smoothing the vertices defining the partial cuts and on proving certain martingale properties. we also give a simpler proof of the result from alon, fernandez de la vega, kannan, and karpinski [1] that dense problems have sample complexity &otilde; (1/&epsilon;4). like previous work, our results generalize to dense maximum constraint satisfaction problems.
approximation algorithms for stochastic and risk-averse optimization. we present improved approximation algorithms in stochastic optimization. we prove that the multi-stage stochastic versions of covering integer programs (such as set cover and vertex cover) admit essentially the same approximation algorithms as their standard (non-stochastic) counterparts; this improves upon work of swamy & shmoys that shows an approximability which depends multiplicatively on the number of stages. we also present approximation algorithms for facility location and some of its variants in the 2-stage recourse model, improving on previous approximation guarantees.
the effectiveness of stackelberg strategies and tolls for network congestion games. it is well known that in a network with arbitrary (convex) latency functions that are a function of edge traffic, the worst-case ratio, over all inputs, of the system delay caused due to selfish behavior versus the system delay of the optimal centralized solution may be unbounded even if the system consists of only two parallel links. this ratio is called the price of anarchy (poa). in this paper, we investigate ways by which one can reduce the performance degradation due to selfish behavior. we investigate two primary methods (a) stackelberg routing strategies, where a central authority, e.g., network manager, controls a fixed fraction of the flow, and can route this flow in any desired way so as to influence the flow of selfish users; and (b) network tolls, where tolls are imposed on the edges to modify the latencies of the edges, and thereby influence the induced nash equilibrium. we obtain results demonstrating the effectiveness of both stackelberg strategies and tolls in controlling the price of anarchy. for stackelberg strategies, we obtain the first results for nonatomic routing in graphs more general than parallel-link graphs, and strengthen existing results for parallel-link graphs, (i) in series-parallel graphs, we show that stackelberg routing reduces the poa to a constant (depending on the fraction of flow controlled). (ii) for general graphs, we obtain latency-class specific bounds on the poa with stackelberg routing, which give a continuous trade-off between the fraction of flow controlled and the price of anarchy, (iii) in parallel-link graphs, we show that for any given class l of latency functions, stackelberg routing reduces the poa to at most &alpha; + (1 - &alpha;) &middot; &rho;(l), where &alpha; is the fraction of flow controlled and &rho;(l) is the poa of class l (when &alpha; = 0). for network tolls, motivated by the known strong results for nonatomic games, we consider the more general setting of atomic splittable routing games. we show that tolls inducing an optimal flow always exist, even for general asymmetric games with heterogeneous users, and can be computed efficiently by solving a convex program. furthermore, we give a complete characterization of flows that can be induced via tolls. these are the first results on the effectiveness of tolls for atomic splittable games.
lower bounds on average-case delay for video-on-demand broadcast protocols. video-on-demand broadcast protocols are commonly used to deliver video content to a large uncoordinated set of consumers. since broadcast protocols are not attuned to individual user requests, some delay in service is unavoidable. the worst-case delay, expressed as a function of the available bandwidth, has been well studied; matching upper and lower bounds have been established in a very general setting. in this paper we turn our attention to average-case delay. we establish asymptotically tight lower bounds on average-case delay in the situation where receiver and sender bandwidths are equal. it follows from our results that existing worst-case-optimal broadcast protocols are, to within a small constant factor, optimal in the average case as well.
matrix-vector multiplication in sub-quadratic time: (some preprocessing required). we show that any n x n matrix a over any finite semiring can be preprocessed in o(n2+&epsilon;) time, such that all subsequent vector multiplications with a can be performed in o(n2/(&epsilon;logn)2) time, for all &epsilon; > 0. the approach is combinatorial and can be implemented on a pointer machine or a (logn)-word ram. some applications are described.
maximum matching in graphs with an excluded minor. we present a new randomized algorithm for finding a maximum matching in h-minor free graphs. for every fixed h, our algorithm runs in o(n3&omega;/(&omega;+3)) < o(n1.326) time, where n is the number of vertices of the input graph and &omega; < 2.376 is the exponent of matrix multiplication. this improves upon the previous o(n1.5) time bound obtained by applying the o(mn1/2)-time algorithm of micali and vazirani on this important class of graphs. for graphs with bounded genus, which are special cases of h-minor free graphs, we present a randomized algorithm for finding a maximum matching in o(n&omega;/2) < o(n1.19) time. this extends a previous randomized algorithm of mucha and sankowski, having the same running time, that finds a maximum matching in a planar graphs. we also present a deterministic algorithm with a running time of o(n1+&omega;/2) < o(n2.19) for counting the number of perfect matchings in graphs with bounded genus. this algorithm combines the techniques used by the algorithms above with the counting technique of kasteleyn. using this algorithm we can also count, within the same running time, the number of t-joins in planar graphs. as special cases, we get algorithms for counting eulerian subgraphs (t = &phis;) and odd subgraphs (t = v) of planar graphs.
deterministic pivoting algorithms for constrained ranking and clustering problems. we introduce new problems of finding minimum-cost rankings and clusterings which must be consistent with certain constraints (e.g. an input partial order in the case of ranking problems); we give deterministic approximation algorithms for these problems. randomized approximation algorithms for unconstrained versions of these problems were given by ailon, charikar, and newman [2] and by ailon and charikar [1]. finding deterministic approximation algorithms for these problems answers an open question of ailon et al. [2]. in particular, we give deterministic algorithms for constrained weighted feedback arc set in tournaments, constrained correlation clustering, and constrained hierarchical clustering related to finding good ultrametrics. our algorithms follow the paradigm of ailon et al. [2] of choosing a particular vertex as a pivot and partitioning the graph according to the pivot; unlike their algorithms, we do not choose the pivot randomly but rather use an lp relaxation to choose a good pivot deterministically. additionally, the use of the lp relaxation allows us to impose constraints easily and analyze the results. in several cases we are able to find approximation factors for the constrained problems that improve on the factors they obtained for the unconstrained cases. we also give a combinatorial algorithm for constrained weighted feedback arc set in tournaments with weights satisfying probability constraints. this algorithm improves on the best known factor given by deterministic combinatorial algorithms for the unconstrained case.
stochastic analyses for online combinatorial optimization problems. in this paper, we study online algorithms when the input is not chosen adversarially, but consists of draws from some given probability distribution. while this model has been studied for online problems like paging and k-server, it is not known how to beat the &phi;(log n) bound for online steiner tree if at each time instant, the demand vertex is a uniformly random vertex from the graph. for the online steiner tree problem, we show that if each demand vertex is an independent draw from some probability distribution &pi;: v &rarr; [0, 1], a variant of the natural greedy algorithm achieves e&omega;[a(&omega;)]/e&omega;[opt (&omega;)] = o(1); moreover, this result can be extended to some other subadditive problems. both assumptions that the input sequence consists of independent draws from &pi;, and that &pi; is known to the algorithm are both essential; we show (almost) logarithmic lower bounds if either assumption is violated. moreover, we give preliminary results on extending the steiner tree results above to the related "expected ratio" measure e&omega;[&omega;(&omega;)/opt (&omega;)]. finally, we use these ideas to give an average-case analysis of the universal tsp problem.
analysis of greedy approximations with nonsubmodular potential functions. in this paper, we present two techniques to analyze greedy approximation with nonsubmodular functions restricted submodularity and shifted submodularity. as an application of the restricted submodularity, we present a worst-case analysis of a greedy algorithm for network steiner tree adapted from a heuristic originally proposed by chang in 1972 for euclidean steiner tree. the performance ratio of chang's heuristic is a longstanding open problem due to the nonsubmodularity of its potential function. as an application of the shifted submodularity, we present a worst-case analysis of a greedy algorithm for connected dominating set generalized from a greedy algorithm proposed by ruan et al. such generalized greedy algorithm is shown to have performance ratio at most (1 + &epsilon;)(1 + ln(&delta; - 1)), which matches the well-known lower bound (1-&epsilon;)ln &delta;, where &delta; is the maximum vertex-degree of input graph and &epsilon; is any positive constant.
set connectivity problems in undirected graphs and the directed steiner network problem. in the generalized connectivity problem, we are given an edge-weighted graph g = (v, e) and a collection d = {(s1,t1),&hellip;, (sk,tk)} of distinct demands; each demand (si, ti) is a pair of disjoint vertex subsets. we say that a subgraph f &sube; g connects a demand (si, ti) when it contains a path with one endpoint in si and the other in ti. the goal is to identify a minimum weight subgraph that connects all demands in d. alon et al. (soda '04) introduced this problem to study online network formation settings and showed that it captures some well-studied problems such as steiner forest, non-metric facility location, tree multicast, and group steiner tree. finding a non-trivial approximation ratio for generalized connectivity was left as an open problem. our starting point is the first polylogarithmic approximation for generalized connectivity attaining a performance guarantee of o(log2 n log2 k). here n is the number of vertices in g and k is the number of demands. we also prove that the cut-covering relaxation of this problem has an o(log3 n log2 k) integrality gap. building upon the results for generalized connectivity we obtain improved approximation algorithms for two problems that contain generalized connectivity as a special case. for the directed steiner network problem, we obtain an o(k1/2+&epsilon;) approximation, which improves on the currently best performance guarantee of o(k2/3) due to charikar et al. (soda '98). for the set connector problem, recently introduced by fukunaga and nagamochi (ipco '07), we present a polylogarithmic approximation; this result improves on the previously known ratio which can be &omega;(n) in the worst case.
improved algorithms for fully dynamic geometric spanners and geometric routing. for a set s of points in ℝd, a t-spanner is a sparse graph on the points of s such that between any pair of points there is a path in the spanner whose total length is at most t times the euclidean distance between the points. in this paper, we show how to construct a (1 + &epsilon;)-spanner with o(n/&epsilon;d) edges and maximum degree o(1/&epsilon;d) in time o(n log n). a spanner with similar properties was previously presented in [6, 8]. however, using our new construction (coupled with several other innovations) we obtain new results for two fundamental problems for constant doubling dimension metrics: the first result is an essentially optimal compact routing scheme. in particular, we show how to perform routing with a stretch of 1 + &isin;, where the label size is [log n] and the size of the table stored at each point is only o(log n/&epsilon;d). this routing problem was first considered by peleg and hassin [11], who presented a routing scheme in the plane. later, chan et al. [6] and abraham et al. [1] considered this problem for doubling dimension metric spaces. abraham et al. [1] were the first to present a (1 + &isin;) routing scheme where the label size depends solely on the number of points. in their scheme labels are of size of [log n], and each point stores a table of size o(log2 n/&epsilon;d). in our routing scheme, we achieve routing tables of size o(log n/&epsilon;d), which is essentially the same size as a label (up to the factor of 1/&epsilon;d). the second and main result of this paper is the first fully dynamic geometric spanner with poly-logarithmic update time for both insertions and deletions. we present an algorithm that allows points to be inserted into and deleted from s with an amortized update time of o(log3 n).
an efficient cost-sharing mechanism for the prize-collecting steiner forest problem. in an instance of the prize-collecting steiner forest problem (pcsf) we are given an undirected graph g = (v, e), non-negative edge-costs c(e) for all e &epsilon; e, terminal pairs r = {(si, ti)}1&le;i&le;k, and penalties &pi;1,...,&pi;k. a feasible solution (f, q) consists of a forest f and a subset q of terminal pairs such that for all (si, ti) &epsilon; r either si, ti are connected by f or (si, ti) &epsilon; q. the objective is to compute a feasible solution of minimum cost c(f) + &pi; (q). a game-theoretic version of the above problem has k players, one for each terminal-pair in r. player i's ultimate goal is to connect si and ti, and the player derives a privately held utility ui &ge; 0 from being connected. a service provider can connect the terminals si and ti of player i in two ways: (1) by buying the edges of an si, ti-path in g, or (2) by buying an alternate connection between si and ti (maybe from some other provider) at a cost of &pi;i. in this paper, we present a simple 3-budget-balanced and group-strategyproof mechanism for the above problem. we also show that our mechanism computes client sets whose social cost is at most o(log2 k) times the minimum social cost of any player set. this matches a lower-bound that was recently given by roughgarden and sundararajan (stoc '06).
finding an optimal tree searching strategy in linear time. we address the extension of the binary search technique from sorted arrays and totally ordered sets to trees and tree-like partially ordered sets. as in the sorted array case, the goal is to minimize the number of queries required to find a target element in the worst case. however, while the optimal strategy for searching an array is straightforward (always query the middle element), the optimal strategy for searching a tree is dependent on the tree's structure and is harder to compute. we present an o(n)-time algorithm that finds the optimal strategy for binary searching a tree, improving the previous best o(n3)-time algorithm. the significant improvement is due to a novel approach for computing subproblems, as well as a method for reusing parts of already computed subproblems, and a linear-time transformation from a solution in the form of an edge-weighed tree into a solution in the form of a decision tree.
on properties of random dissections and triangulations. in the past decades the gn,p model of random graphs, introduced by erd&odblac;s and r&eacute;nyi in the 60's, has led to numerous beautiful and deep theorems. a key feature that is used in basically all proofs is that edges in gn,p appear independently. the independence of the edges allows, for example, to obtain extremely tight bounds on the number of edges of gn,p and its degree sequence by straightforward applications of chernoff bounds. this situation changes dramatically if one considers graph classes with structural side constraints. for example, in a random planar graph rn (a graph drawn uniformly at random from the class of all labeled planar graphs on n vertices) the edges are obviously far from being independent. consequently, so far basically all results about properties of random graphs with structural side constraints rely on completely different methods, mostly from analytic combinatorics. in this paper we show that recent progress in the construction of so-called boltzmann samplers by duchon, flajolet, louchard, and schaeffer [3] and fusy [6] can be used to reduce the study of degree sequences and subgraph counts to properties of sequences of independent and identically distributed random variables -- to which we can then again apply chernoff bounds to obtain extremely tight results. we elaborate our ideas by studying random dissections and triangulations of a labeled convex n-gon. for both we obtain the degree sequence and the number of induced copies of given fixed graphs. the degree sequence for triangulations was already obtained previously by gao and wormald [8] using deep methods from analytic combinatorics. we do, however, get better bounds for the tails of the probability distribution.
comparing the strength of query types in property testing: the case of testing -colorability. we study the power of four query models in the context of property testing in general graphs, where our main case study is the problem of testing k-colorability. two query types, which have been studied extensively in the past, are pair queries and neighbor queries. the former corresponds to asking whether there is an edge between any particular pair of vertices, and the latter to asking for the i'th neighbor of a particular vertex. we show that while for pair queries, testing k-colorability requires a number of queries that is a monotone decreasing function in the average degree d, the query complexity in the case of neighbor queries remains roughly the same for every density and for large values of k. we also consider a combined model that allows both types of queries, and we propose a new, stronger, query model, which is related to the field of group testing. we give one-sided error upper and lower bounds for all the models, where the bounds are nearly tight for three of the models. in some of the cases our lower bounds extend to two-sided error algorithms. the problem of testing k-colorability was previously studied in the contexts of dense and sparse graphs, and in our proofs we unify approaches from those cases, and also provide some new tools and techniques which may be of independent interest.
the random graph threshold for -orientiability and a fast algorithm for optimal multiple-choice allocation. we investigate a linear time greedy algorithm for the following load balancing problem: assign m balls to n bins such that the maximum occupancy is minimized. each ball can be placed into one of two randomly choosen bins. this problem is closely related to the problem of orienting the edges of an undirected graph to obtain a directed graph with minimum in-degree. using differential equation methods, we derive thresholds for the solution quality achieved by our algorithm. since these thresholds coincide with lower bounds for the achievable solution quality, this proves the optimality of our algorithm (as n &rarr; &infin;, in a probabilistic sense) and establishes the thresholds for k-orientability of random graphs. this proves an assertion of karp and saks.
auctions for structured procurement. this paper considers a general setting for structured procurement and the problem a buyer faces in designing a procurement mechanism to maximize profit. this brings together two agendas in algorithmic mechanism design, frugality in procurement mechanisms (e.g., for paths and spanning trees) and profit maximization in auctions (e.g., for digital goods). in the standard approach to frugality in procurement, a buyer attempts to purchase a set of elements that satisfy a feasibility requirement as cheaply as possible. for profit maximization in auctions, a seller wishes to sell some number of goods for as much as possible. we unify these objectives by endowing the buyer with a decreasing marginal benefit per feasible set purchased and then considering the problem of designing a mechanism to buy a number of sets which maximize the buyer's profit, i.e., the difference between their benefit for the sets and the cost of procurement. for the case where the feasible sets are bases of a matroid, we follow the approach of reducing the mechanism design optimization problem to a mechanism design decision problem. we give a profit extraction mechanism that solves the decision problem for matroids and show that a reduction based on random sampling approximates the optimal profit. we also consider the problem of non-matroid procurement and show that in this setting the approach does not succeed.
tight lower bounds for selection in randomly ordered streams. we show that any algorithm computing the median of a stream presented in random order, using polylog(n) space, requires an optimal &omega; (log log n) passes, resolving an open question from the seminal paper on streaming by munro and paterson, from focs 1978.
linked decompositions of networks and the power of choice in polya urns. a linked decomposition of a graph with n nodes is a set of subgraphs covering the n nodes such that all pairs of subgraphs intersect; we seek linked decompositions such that all subgraphs have about &radic;n vertices, logarithmic diameter, and each vertex of the graph belongs to either one or two subgraphs. a linked decomposition enables many control and management functions to be implemented locally, such as resource sharing, maintenance of distributed directory structures, deadlock-free routing, failure recovery and load balancing, without requiring any node to maintain information about the state of the network outside the subgraphs to which it belongs. linked decompositions also enable efficient routing, schemes with small routing tables, which we describe in section 5. our main contribution is to show that "internet-like graphs" (e.g. the preferential attachment model proposed by barabasi et al. [10] and other similar models) have linked decompositions with the parameters described above with high probability; moreover, our experiments show that the internet topology itself can be so decomposed. our proof proceeds by analyzing a novel process, which we call polya urns with the power of choice, which may be of great independent interest. in this new process, we start with n nonempty bins containing o(n) balls total, and each arriving ball is placed in the least loaded of m bins, drawn independently at random with probability proportional to load. our analysis shows that in our new process, with high probability the bin loads become roughly balanced some time before o(n2+&epsilon;) further balls have arrived and stay roughly balanced, regardless of how the initial o(n) balls were distributed, where &epsilon; > 0 can be arbitrarily small, provided m is large enough.
sampling algorithms and coresets for &ell; regression. the &ell;p regression problem takes as input a matrix a &isin; ℝn, a vector b &isin; ℝn, and a number p &isin; [1, &infin;), and it returns as output a number z and a vector xopt &isin; ℝd such that z = minx&isin;ℝd ||ax - b||p = ||axopt - b||p. in this paper, we construct coresets and obtain an efficient two-stage sampling-based approximation algorithm for the very overconstrained (n &gt; d) version of this classical problem, for all p &isin; [1, &infin;). the first stage of our algorithm non-uniformly samples &rcirc;1 = o(36pdmax{p/2+1, p}+1) rows of a and the corresponding elements of b, and then it solves the lp regression problem on the sample; we prove this is an 8-approximation. the second stage of our algorithm uses the output of the first stage to resample &rcirc;1/&epsilon;2 constraints, and then it solves the lp regression problem on the new sample; we prove this is a (1 + &epsilon;)-approximation. our algorithm unifies, improves upon, and extends the existing algorithms for special cases of &ell;p regression, namely p = 1,2 [10, 13]. in course of proving our result, we develop two concepts--well-conditioned bases and subspace-preserving sampling--that are of independent interest.
maximum overhang. how far can a stack of n identical blocks be made to hang over the edge of a table? the question dates back to at least the middle of the 19th century and the answer to it was widely believed to be of order log n. however, at soda'06, paterson and zwick constructed n-block stacks with overhangs of order n1/3. here we complete the solution to the overhang problem, and answer paterson and zwick's primary open question, by showing that order n1/3 is best possible. at the heart of the argument is a lemma (possibily of independent interest) showing that order d3 non-adaptive coinflips are needed to propel a discrete random walk on the number line to distance d. we note that our result is not a mainstream algorithmic result, yet it is about the solution to a discrete optimization problem. moreover, it illusrates how methods founded in theoretical computer science can be aplied to a problem that has puzzled some mathematicians and physicists for more than 150 years.
on distance to monotonicity and longest increasing subsequence of a data stream. in this paper we consider problems related to the sortedness of a data stream. first we investigate the problem of estimating the distance to monotonicity; given a sequence of length n, we give a deterministic (2 + &epsilon;)-approximation algorithm for estimating its distance to monotonicity in space o(1/&epsilon;2 log2 (&epsilon;n)). this improves over the randomized (4 + &epsilon;)-approximation, algorithm of [3]. we then consider the problem of approximating the length of the longest increasing subsequence of an input stream of length n. we use techniques from multi-party communication complexity combined with a fooling set approach to prove that any o(1)-pass deterministic streaming algorithm that approximates the length of the longest increasing subsequence within 1 + &epsilon; requires &omega;(&radic;n) space. this proves the conjecture in [3] and matches the current upper bound.
distribution-sensitive point location in convex subdivisions. a data structure is presented for point location in convex planar subdivisions when the distribution of queries is known in advance. the data structure has an expected query time that differs from the optimal one by only lower order terms in the linear comparison tree model.
embedding metric spaces in their intrinsic dimension. a fundamental question of metric embedding is whether the metric dimension of a metric space is related to its intrinsic dimension. that is whether the dimension in which it can be embedded in some real normed space is implied by the intrinsic dimension which is reflected by the inherent geometry of the space. the existence of such an embedding was conjectured by assouad and was later posed as an open problem by others. this question is tightly related to a major goal of many practical application fields: developing tools to represent intrinsically low dimensional metric data sets in a succinct manner. in this paper we give the first algorithmic technique with formal guarantees for finding faithful and low dimensional representations of data lying in high dimensional space. our main theorem states that every finite metric space x embeds into euclidean space with dimension o(dim(x)/&isin;) and distortion o(log 1+&epsilon;n), where dim(x) is the doubling dimension of the space x. moreover, we show that x can be embedded into dimension &otilde;(dim(x)) with constant average distortion and lq-distortion for any q < &infin;. our technique also provides a dimension-distortion tradeoff and an extension of assouad's theorem, providing distance oracles that improve known construction when dim(x) = o(log |x|).
efficient subspace approximation algorithms. confronted with high-dimensional data arising from either word-document count, global climate patterns or any one of the myriad other sources, most scientific approaches extract a good low-dimensional summary. this desire to reduce dimensionality may be seen as a consequence of occam's razor, and the scientific methodologies we have in mind include those from data mining and statistics.
earth mover distance over high-dimensional spaces. the earth mover distance (emd) between two equal-size sets of points in ℝd is defined to be the minimum cost of a bipartite matching between the two pointsets. it is a natural metric for comparing sets of features, and as such, it has received significant interest in computer vision. motivated by recent developments in that area, we address computational problems involving emd over high-dimensional pointsets. a natural approach is to embed the emd metric into l1, and use the algorithms designed for the latter space. however, khot and naor [kn06] show that any embedding of emd over the d-dimensional hamming cube into l1 must incur a distortion &omega;(d), thus practically losing all distance information. we circumvent this roadblock by focusing on sets with cardinalities upper-bounded by a parameter s, and achieve a distortion of only o(log s &middot; log d). since in applications the feature sets have bounded size, the resulting distortion is much smaller than the &omega;(d) lower bound. our approach is quite general and easily extends to emd over ℝd. we then provide a strong lower bound on the multi-round communicatic complexity of estimating emd, which in particular strengthens the known non-embeddability result of [kn06]. our bound exhibits a smooth tradeoff between approximation and communication, and for example implies that every algorithm that estimates emd using constant size sketches can only achieve &omega;(log s) approximation.
computational advertising. computational advertising is an emerging new scientific sub-discipline, at the intersection of large scale search and text analysis, information retrieval, statistical modeling, machine learning, classification, optimization, and microeconomics. the central challenge of computational advertising is to find the "best match" between a given user in a given context and a suitable advertisement. the context could be a user entering a query in a search engine ("sponsored search"), a user reading a web page ("content match" and "display ads"), a user watching a movie on a portable device, and so on. the information about the user can vary from scarily detailed to practically nil. the number of potential advertisements might be in the billions. thus, depending on the definition of "best match" this challenge leads to a variety of massive optimization and search problems, with complicated constraints.
polynomial approximation schemes for smoothed and random instances of multidimensional packing problems. the multidimensional bin packing and vector bin packing problems are known to not have asymptotic polynomial-time approximation schemes (unless p = np). nevertheless, we show that: &bull; any smoothed (randomly perturbed) instance, and any instance from a class of other distributions, does have a polynomial-time probable approximation scheme. namely, for any fixed &epsilon; > 0, we exhibit a linear-time algorithm that finds a (1+ &epsilon;)-approximate packing with probability 1 - 2-&omega;(n) over the space of random inputs. &bull; there exists an oblivious algorithm that does not know from which distribution inputs come, and still asymptotically does almost as well as the previous algorithms. the oblivious algorithm outputs almost surely a (1 + &epsilon;)-approximation for every &epsilon; > 0. &bull; for vector bin packing, for each considered class of random instances, there exists an algorithm that in expected linear time computes a (1 + &epsilon;)-approximation, for any fixed &epsilon; > 0. to achieve these results we develop a multidimensional version of the one-dimensional rounding technique introduced by fernadez de la vega and lueker. our results generalize karp, luby and marchetti-spaccamela's results on approximatibility of random instances of multidimensional bin packing to a much wider class of distributions.
minimum weight convex steiner partitions. new tight bounds are presented on the minimum length of planar straight line graphs connecting n given points in the plane and having convex faces. specifically, we show that the convex steiner partition of n points in the plane is at most o(log n/log log n) times longer than their euclidean minimum spanning tree (emst), and this bound is best possible. without allowing steiner points, the corresponding bound is known to be &theta;(log n), attained for n points lying along a pseudo-triangle. we also show that the convex steiner partition of n points along a pseudo-triangle is at most o(log log n) times longer than the emst, and this bound is also best possible. our methods are constructive and lead to polynomial-time algorithms for computing convex steiner partitions within these bounds in both cases.
nondecreasing paths in a weighted graph or: how to optimally read a train schedule. a travel booking office has timetables giving arrival and departure times for all scheduled trains, including their origins and destinations. a customer presents a starting city and demands a route with perhaps several train connections taking him to his destination as early as possible. the booking office must find the best route for its customers. this problem was first considered in the theory of algorithms by george minty [14], who reduced it to a problem on directed edge-weighted graphs: find a path from a given source to a given target such that the consecutive weights on the path are nondecreasing and the last weight on the path is minimized. minty gave the first algorithm for the single source version of the problem, in which one finds minimum last weight nondecreasing paths from the source to every other vertex. in this paper we give the first linear time algorithm for this problem. we also define an all pairs version for the problem and give a strongly polynomial truly subcubic algorithm for it.
a network formation game for bipartite exchange economies. we introduce a natural new network formation game in which buyers and sellers may purchase edges representing trading opportunities between themselves, and then accrue wealth in the resulting exchange economy. our main result is an exact characterization of the set of bipartite graphs g that are nash equilibria for this game. this characterization provides sharp limits on the amount and structure of wealth variation that can occur, as well as on the allowable equilibrium exchange rates.
finding one tight cycle. a cycle on a combinatorial surface is tight if it as short as possible in its (free) homotopy class. we describe an algorithm to compute a single tight, non-contractible, simple cycle on a given orientable combinatorial surface in o(n log n) time. the only method previously known for this problem was to compute the globally shortest non-contractible or non-separating cycle in o(min{g3, n} n log n) time, where g is the genus of the surface. as a consequence, we can compute the shortest cycle freely homotopic to a chosen boundary cycle in o(n log n) time and a tight octagonal decomposition in o(gn log n) time.
fast load balancing via bounded best response. it is known that the dynamics of best response in an environment of non-cooperative users may converge to a good solution when users play sequentially, but may cycle far away from the global optimum solution when users play concurrently. we introduce the notion of bounded best response where users react with best response subject to rules that are forced locally by the system. we investigate the problem of load balancing tasks on machines in a bipartite graph model and show that the dynamics of concurrent bounded best response converges to a near-optimum solution quickly, i.e., with poly-logarithmic number of rounds. this is in contrast to the concurrent best response dynamics which cycles far away from the optimum and to any sequential dynamics which requires at least a linear number of rounds to get to a reasonable solution.
online make-to-order joint replenishment model: primal dual competitive algorithms. in this paper, we study an online make-to-order variant of the classical joint replenishment problem (jrp) that has been studied extensively over the years and plays a fundamental role in broader planning issues, such as the management of supply chains. in contrast to the traditional approaches of the stochastic inventory theory, we study the problem using competitive analysis against a worst-case adversary. our main result is a 3-competitive deterministic algorithm for the online version of the jrp. we also prove a lower bound of approximately 2.64 on the competitiveness of any deterministic online algorithm for the problem. our algorithm is based on a novel primal-dual approach using a new linear programming relaxation of the offline jrp model. the primal-dual approach that we propose departs from previous primal-dual and online algorithms in rather significant ways. we believe that this approach can extend the range of problems to which online and primal-dual algorithms can be applied and analyzed.
a plant location guide for the unsure. this paper studies an extension of the k-median problem where we are given a metric space (v, d) and not just one but m client sets {si &sube; v}im=1, and the goal is to open k facilities f to minimize: maxi&isin;[m] {&sigma;j&isin;si d(j, f)}, i.e., the worst-case cost over all the client sets. this is a "min-max" or "robust" version of the k-median problem; however, note that in contrast to previous papers on robust/stochastic problems, we have only one stage of decision-making---where should we place the facilities? we present an o(log n + log m) approximation for robust k-median: the algorithm is combinatorial and very simple, and is based on reweighting/lagrangean-relaxation ideas. in fact, we give a general framework for (minimization) facility location problems where there is a bound on the number of open facilities. for robust and stochastic versions of such location problems, we show that if the problem satisfies a certain "projection" property, essentially the same algorithm gives a logarithmic approximation ratio in both versions. we use our framework to give the first approximation algorithms for robust/stochastic versions of k-tree, capacitated k-median, and fault-tolerant k-median.
broadcast scheduling: algorithms and complexity. broadcast scheduling is a popular method for disseminating information in response to client requests. there are n pages of information, and clients request pages at different times. however, multiple clients can have their requests satisfied by a single broadcast of the requested page. in this paper we consider several related broadcast scheduling problems. one central problem we study simply asks to minimize the maximum response time (over all requests). another related problem we consider is the version in which every request has a release time and a deadline, and the goal is to maximize the number of requests that meet their deadlines. while approximation algorithms for both these problems were proposed several years back, it was not known if they were np-complete. one of our main results is that both these problems are np-complete. in addition, we use the same unified approach to give a simple np-completeness proof for minimizing the sum of response times. a very complicated proof was known for this version. furthermore, we give a proof that fifo is a 2-competitive online algorithm for minimizing the maximum response time (this result had been claimed earlier with no proof) and that there is no better deterministic online algorithm (this result was claimed earlier as well, but with an incorrect proof).
the complexity of game dynamics: bgp oscillations, sink equilibria, and beyond. we settle the complexity of a well-known problem in networking by establishing that it is pspace-complete to tell whether a system of path preferences in the bgp protocol [25] can lead to oscillatory behavior; one key insight is that the bgp oscillation question is in fact one about nash dynamics. we also show that the concept of sink equilibria proposed recently in [11] is pspace-complete to analyze and approximate for graphical games. finally, we propose a new equilibrium concept inspired by game dynamics, unit recall equilibria, which we show to be close to universal (exists with high probability in a random game) and algorithmically promising. we also give a relaxation thereof, called componentwise unit recall equilibria, which we show to be both tractable and universal (guaranteed to exist in every game).
greedy drawings of triangulations. greedy routing is a class of routing algorithms in which the packets are forwarded in a manner that reduces the distance to the destination at every step. in an attempt to provide theoretical guarantees for a class of greedy routing algorithms, papadimitriou and ratajczak [19] came up with the following conjecture: any 3-connected planar graph can be drawn in the plane such that for every pair of vertices s and t a distance decreasing path can be found. a path s = v1, v2,&hellip;,vk=t in a drawing is said to be distance decreasing if ||vi - t|| < ||vi-1 -t||, 2 &le; i &le; k where || &hellip; || denotes the euclidean distance. we settle this conjecture in the affirmative for the case of triangulations. a partitioning of the edges of a triangulation g into 3 trees, called the realizer of g, was first developed by walter schnyder who also gave a drawing algorithm based on this. we generalize schnyder's algorithm to obtain a whole class of drawings of any given triangulation g. we show, using the knaster-kuratowski-mazurkiewicz theorem, that some drawing of g belonging to this class is greedy.
a deterministic sub-linear time sparse fourier algorithm via non-adaptive compressed sensing methods. we study the problem of estimating the best b term fourier representation for a given frequency-sparse signal (i.e., vector) a of length n &gt; b. more precisely, we investigate how to deterministically identify b of the largest magnitude frequencies of &acirc;, and estimate their coefficients, in polynomial (b, log n) time. randomized sub-linear time algorithms, which have a small (controllable) probability of failure for each processed signal, exist for solving this problem. however, for failure intolerant applications such as those involving mission-critical hardware designed to process many signals over a long lifetime, deterministic algorithms with no probability of failure are highly desirable. in this paper we build on the deterministic compressed sensing results of cormode and muthukrishnan (cm) [26, 6, 7] in order to develop the first known deterministic sub-linear time sparse fourier transform algorithm suitable for failure intolerant applications. furthermore, in the process of developing our new fourier algorithm, we present a simplified deterministic compressed sensing algorithm which improves on cm's algebraic compressibility results while simultaneously maintaining their results concerning exponential decay.
ultra-low-dimensional embeddings for doubling metrics. we consider the problem of embedding a metric into low-dimensional euclidean space. the classical theorems of bourgain and of johnson and lindenstrauss imply that any metric on n points embeds into an o(log n)-dimensional euclidean space with o(log n) distortion. moreover, a simple "volume" argument shows that this bound is nearly tight: the uniform metric on n points requires &omega;(log n/log log n) dimensions to embed with logarithmic distortion. it is natural to ask whether such a volume restriction is the only hurdle to low-dimensional low-distortion embeddings. do doubling metrics, which do not have large uniform submetrics, embed in low dimensional euclidean spaces with small distortion? in this paper, we answer the question positively and show that any doubling metric embeds into o(log log n) dimensions with o(log n) distortion. in fact, we give a suite of embeddings with a smooth trade-off between distortion and dimension: given an n-point metric (v,d) with doubling dimension dimd, and any target dimension t in the range &omega;(dimd log log n) &le; t &le; o(log n), we embed the metric into euclidean space ℝt with o(log n&radic;dimd/t) distortion.
on allocations that maximize fairness. we consider a problem known as the restricted assignment version of the max-min allocation problem with indivisible goods. there are n items of various nonnegative values and m players. every player is interested only in some of the items and has zero value for the other items. one has to distribute the items among the players in a way that maximizes a certain notion of fairness, namely, maximizes the minimum of the sum of values of items given to any player. bansal and sviridenko [stoc 2006] describe a linear programming relaxation for this problem, and present a rounding technique that recovers an allocation of value at least &omega;(log log log m/log log m) of the optimum. we show that the value of this lp relaxation in fact approximates the optimum value to within a constant factor. our proof is not constructive and does not by itself provide an efficient algorithm for finding an allocation that is within constant factors of optimal.
in-place 2-d nearest neighbor search. we revisit a classic problem in computational geometry: preprocessing a planar n-point set to answer nearest neighbor queries. in socg 2004, br&ouml;nnimann, chan, and chen showed that it is possible to design an efficient data structure that takes no extra space at all other than the input array holding a permutation of the points. the best query time known for such "in-place data structures" is o(log2 n). in this paper, we break the o(log2 n) barrier by providing a method that answers nearest neighbor queries in time {display equation} the new method uses divide-and-conquer (based on planar separators) in a way that is quite unlike traditional point location methods, and extends previous 1-d data structuring techniques (specifically the van emde boas layout). the method has further applications, for example, in answering extreme point queries for a 3-d point set on the boundary of a convex set of constant complexity.
fast edge splitting and edmonds' arborescence construction for unweighted graphs. given an unweighted undirected or directed graph with n vertices, m edges and edge connectivity c, we present a new deterministic algorithm for edge splitting. our algorithm splits-off any specified subset s of vertices satisfying standard conditions (even degree for the undirected case and in-degree &ge; out-degree for the directed case) while maintaining connectivity c for vertices outside s in &otilde;(m+nc2) time for an undirected graph and &otilde;(mc) time for a directed graph. this improves the current best deterministic time bounds due to gabow [8], who splits-off a single vertex in &otilde;(nc2+m) time for an undirected graph and &otilde;(mc) time for a directed graph. further, for appropriate ranges of n, c, |s| it improves the current best randomized bounds due to bencz&uacute;r and karger [2], who split-off a single vertex in an undirected graph in &otilde;(n2) monte carlo time. we give two applications of our edge splitting algorithms. our first application is a sub-quadratic (in n) algorithm to construct edmonds' arborescences. a classical result of edmonds [5] shows that an unweighted directed graph with c edge-disjoint paths from any particular vertex r to every other vertex has exactly c edge-disjoint arborescences rooted at r. for a c edge connected unweighted undirected graph, the same theorem holds on the digraph obtained by replacing each undirected edge by two directed edges, one in each direction. the current fastest construction of these arborescences by gabow [7] takes &otilde;(n2c2) time. our algorithm takes &otilde;(nc3+m) time for the undirected case and &otilde;(nc4+mc) time for the directed case. the second application of our splitting algorithm is a new steiner edge connectivity algorithm for undirected graphs which matches the best known bound of &otilde;(nc2 + m) time due to bhalgat et al [3]. finally, our algorithm can also be viewed as an alternative proof for existential edge splitting theorems due to lov&aacute;sz [9] and mader [11].
metric clustering via consistent labeling. we design approximation algorithms for a number of fundamental optimization problems in metric spaces, namely computing separating and padded decompositions, sparse covers, and metric triangulations. our work is the first to emphasize relative guarantees, that compare the produced solution to the optimal one for the input at hand. by contrast, the extensive previous work on these topics has sought absolute bounds that hold for every possible metric space (or for a family of metrics). while absolute bounds typically translate to relative ones, our algorithms provide significantly better relative guarantees, using a rather different algorithm. our technical approach is to cast a number of metric clustering problems that have been well studied---but almost always as disparate problems---into a common modeling and algorithmic framework, which we call the consistent labeling problem. having identified the common features of all of these problems, we provide a family of linear programming relaxations and simple randomized rounding procedures that achieve provably good approximation guarantees.
on stars and steiner stars. for a set of n points in the plane, a star connects one of the points (the center) to the other n - 1 points by straight line edges, while a steiner star connects an arbitrary point in the plane to all n input points. the center of the minimum steiner star, the weber center, minimizes the sum of distances from the n points. fekete and meijer showed that the minimum star is at most &radic;2 times longer than the minimum steiner star for any finite point configuration in the plane or 3-space. the maximum ratio between the two is conjectured to be 4/&pi; in the plane and 4/3 in three dimensions. here we improve the upper bound to 1.3999 in the plane, and to &radic;2 - 10-4 in 3-space. our results also imply improved bounds on the maximum ratios between the minimum star and the maximum matching in two and three dimensions. our method relies on constructing a suitable discretization for a continuous problem and then using linear programming to optimize over a relatively large set of constraints.
computing excluded minors. by robertson and seymour's graph minor theorem, every minor ideal can be characterised by a finite family of excluded minors. (a minor ideal is a class of graphs closed under taking minors.) we study algorithms for computing excluded minor characterisations of minor ideals. we propose a general method for obtaining such algorithms, which is based on definability in monadic second-order logic and the decidability of the monadic second-order theory of trees. a straightforward application of our method yields algorithms that, for a given k, compute excluded minor characterisations for the minor ideal tk of all graphs of tree width at most k, the minor ideal bk of all graphs of branch width at most k, and the minor ideal gk of all graphs of genus at most k. our main results are concerned with constructions of new minor ideals from given ones. answering a question that goes back to fellows and langston [11], we prove that there is an algorithm that, given excluded minor characterisations of two minor ideals c and d, computes such a characterisation for the ideal c &cup; d. furthermore, we obtain an algorithm for computing an excluded minor characterisation for the class of all apex graphs over a minor ideal c, given an excluded minor characterisation for c. (an apex graph over c is a graph g from which one vertex can be removed to obtain a graph in c.) a corollary of this result is a uniform ftpalgorithm for the "distance k from planarity" problem.
maintaining deforming surface meshes. we present a method to maintain a mesh approximating a deforming surface, which is specified by a dense set of sample points. we identify a reasonable motion model for which a provably good surface mesh can be maintained. our algorithm determines the appropriate times at which the mesh is updated to maintain a good approximation. the updates use simple primitives, and no costly computation such as line-surface intersection is necessary. point insertions and deletions are allowed at the updates. each update takes time linear in the size of the current sample set plus the new sample points inserted. we also construct examples for which, under the same model, no other algorithm makes asymptotically fewer changes to the mesh than our algorithm.
bounded-leg distance and reachability oracles. in a weighted, directed graph an l-bounded leg path is one whose constituent edges have length at most l. for any fixed l, computing l-bounded leg shortest paths is just as easy as the standard shortest path algorithm. in this paper we study approximate distance oracles (and reachability oracles) for bounded leg path problems, where the leg bound l is not known in advance, but forms part of the query. bounded-leg path problems are more complicated than standard shortest path problems because the number of distinct shortest paths between two vertices (over all leg bounds) could be as large as the number of edges in the graph. the bounded leg constraint models situations where there is some limited resource that must be spent when traversing an edge. for example, the size of a fuel tank or the life of a battery places a hard limit on how far a vehicle can travel in one leg before refueling or recharging. someone making a long road trip may place a hard limit on how many hours they are willing to drive in any one day. our main result is a nearly optimal algorithm for preprocessing a directed graph in order to answer approximate bounded leg distance and bounded leg shortest path queries. in particular, we can preprocess any graph in &otilde;(n3) time, producing a data structure with size &otilde;(n2) that answers (1 + &isin;)-approximate bounded leg distance queries in o(log log n) time. if the corresponding (1 + &isin;)-approximate shortest path has l edges it can be returned in o(l log log n) time. these bounds are all within polylog(n) factors of the best standard all-pairs shortest path algorithm and improve substantially the previous best bounded leg shortest path algorithm, whose preprocessing time and space are o(n4) and &otilde;(n2.5). we also consider bounded leg oracles in other situations. in the context of planar directed graphs we give a time-space tradeoff for answering bounded leg reachability queries. for any k &ge; 2 we can build a data structure with size o(kn1+1/k) that answers reachability queries in time &otilde;(nk&minus;1/2k).
coresets, sparse greedy approximation, and the frank-wolfe algorithm. the problem of maximizing a concave function f(x) in a simplex s can be solved approximately by a simple greedy algorithm. for given k, the algorithm can find a point x(k) on a k-dimensional face of s, such that f(x(k)) &ge; f(x*) - o(1/k). here f(x*) is the maximum value of f in s. this algorithm and analysis were known before, and related to problems of statistics and machine learning, such as boosting, regression, and density mixture estimation. in other work, coming from computational geometry, the existence of &epsilon;-coresets was shown for the minimum enclosing ball problem, by means of a simple greedy algorithm. similar greedy algorithms, that are special cases of the frank-wolfe algorithm, were described for other enclosure problems. here these results are tied together, stronger convergence results are reviewed, and several coreset bounds are generalized or strengthened.
a constant factor approximation algorithm for -median clustering with outliers. we consider the k-median clustering with outliers problem: given a finite point set in a metric space and parameters k and m, we want to remove m points (called outliers), such that the cost of the optimal k-median clustering of the remaining points is minimized. we present the first polynomial time constant factor approximation algorithm for this problem.
price based protocols for fair resource allocation: convergence time analysis and extension to leontief utilities. we analyze several distributed, continuous time protocols for a fair allocation of bandwidths to flows in a network (or resources to agents). our protocols converge to an allocation which is a logarithmic approximation, simultaneously, to all canonical social welfare functions (i.e. functions which are symmetric, concave, and non-decreasing). these protocols can be started in an arbitrary state. while a similar protocol was known before, it only applied to the simple bandwidth allocation problem, and its stability and convergence time was not understood. in contrast, our protocols also apply to the more general case of leontief utilities, where each user may place a different requirement on each resource. further, we prove that our protocols converge in polynomial time. the best convergence time we prove is o(n log ncmaxamax/cminamin), where n is the number of agents in the network, cmax and cmin are the maximum and minimum capacity of the links, and amax, amin are the largest and smallest leontief coefficients, respectively. this time is achieved by a simple mimd (multiplicative increase, multiplicative decrease) protocol which had not been studied before in this setting. we also identify combinatorial properties of these protocols that may be useful in proving stronger convergence bounds. the final allocations by our protocols are supported by usage-sensitive dual prices which are fair in the sense that they shield light users of a resource from the impact of heavy users. thus our protocols can also be thought of as efficient distributed schemes for computing fair prices.
approximating connected facility location problems via random facility sampling and core detouring. we present a simple randomized algorithmic framework for connected facility location problems. the basic idea is as follows: we run a black-box approximation algorithm for the unconnected facility location problem, randomly sample the clients, and open the facilities serving sampled clients in the approximate solution. via a novel analytical tool, which we term core detouring, we show that this approach significantly improves over the previously best known approximation ratios for several np-hard network design problems. for example, we reduce the approximation ratio for the connected facility location problem from 8.55 to 4.00 and for the single-sink rent-or-buy problem from 3.55 to 2.92. we show that our connected facility location algorithms can be derandomized at the expense of a slightly worse approximation ratio. the versatility of our framework is demonstrated by devising improved approximation algorithms also for other related problems.
empty-ellipse graphs. we define and study a geometric graph over points in the plane that captures the local behavior of delaunay triangulations of points on smooth surfaces in ir3. two points in a planar point set p are neighbors in the empty-ellipse graph if they lie on an axis-aligned ellipse with no point of p in its interior. the empty-ellipse graph can be a clique in the worst case, but it is usually much less dense. specifically, the empty-ellipse graph of n points has complexity &theta;(&delta;n) in the worst case, where &delta; is the ratio between the largest and smallest pairwise distances. for points generated uniformly at random in a rectangle, the empty-ellipse graph has expected complexity &theta;(n log n). as an application of our proof techniques, we show that the delaunay triangulation of n random points on a circular cylinder has expected complexity &theta;(n log n).
ascending auctions for integral (poly)matroids with concave nondecreasing separable values. consider a seller with a fixed set of resources that can produce a variety of bundles from a set e of indivisible goods. several bidders are interested in purchasing a bundle of such goods. their utility for a bundle is privately known and represented by an additively separable, nondecreasing and concave function. in the case when the set of feasible bundles forms an integral polymatroid (or its basis), we present an ascending auction which in equilibrium returns the efficient outcome. formally, given an integral, monotone, submodular function &rho;: e &rarr; n0 with &rho;(&theta;) = 0 the integral points of the polymatroid p&rho; represent various allocations which the seller can feasibly offer. buyers j &isin; n have privately known valuations vj (xj) for xj &isin; p&rho; with the property that vj (xj) = &sigma;e&isin;evje(xje) where the vje(xje) are nondecreasing and concave. we present an ascending auction running in pseudo-polynomial time in which truthful bidding is an ex post equilibrium and results in the efficient outcome. our auction strictly generalizes the ascending auction of demange, gale, and sotomayor (1986) applied to scheduling matroids (agents want to schedule several jobs; their due and release dates are common knowledge, but the value of completing a job is private information). for a suitable class of uniform matroids, our auction reduces to the ascending auction of ausubel (2004) for the allocation of multiple units of a homogeneous good when agents have decreasing marginal values in quantities. finally, our auction can be applied to the setting of spatially distributed markets considered in babaioff, nisan, and pavlov (2004).
a faster cache-oblivious shortest-path algorithm for undirected graphs with bounded edge lengths. we present a cache-oblivious algorithm for computing single-source shortest paths in undirected graphs with non-negative edge lengths. the algorithm incurs o(&radic;(nm log w)/b+(m/b) log n +mst (n, m)) memory transfers on a graph with n vertices, m edges, and real edge lengths between 1 and w; b denotes the cache block size, and mst(n, m) denotes the number of memory transfers required to compute a minimum spanning tree of a graph with n vertices and m edges. our algorithm is the first cache-oblivious shortest-path algorithm incurring less than one memory transfer per vertex if the graph is sparse (m = o(n)) and w = 2&deg;(b).
an elementary construction of constant-degree expanders. we describe a short and easy-to-analyse construction of constant-degree expanders. the construction relies on the replacement product, applied by reingold, vadhan and wigderson (2002) to give an iterative construction of bounded-degree expanders. here we give a simpler construction, which applies the replacement product (only twice!) to turn the cayley expanders of alon and roichman (1994), whose degree is polylog n, into constant-degree expanders. this enables us to prove the required expansion using a simple new combinatorial analysis of the replacement product (instead of the spectral analysis used by reingold, vadhan and wigderson).
complexity of delaunay triangulation for points on lower-dimensional polyhedra. we show that the delaunay triangulation of a set of points distributed nearly uniformly on a polyhedron (not necessarily convex) of dimension p in d-dimensional space is o(n(d-1)/p). for all 2 &le; p &le; d - 1, this improves on the well-known worst-case bound of o(n&lceil;d/2&rceil;).
improved bounds for the online steiner tree problem in graphs of bounded edge-asymmetry. in this paper we consider the online steiner tree problem in weighted directed graphs of bounded edge-asymmetry &alpha;. the edge-asymmetry of a directed graph is defined as the maximum ratio of the cost (weight) of antiparallel edges in the graph. the problem has applications in multicast routing over a network with non-symmetric links. we improve the previously known upper and lower bounds on the competitive ratio of any deterministic algorithm due to faloutsos et al. [11]. in particular, we show that a better analysis of a simple greedy algorithm yields a competitive ratio of o (min {k, &alpha; log k/log log &alpha;}), where k denotes the number of terminals requested. on the negative side, we show a lower bound of &omega;(min{k1-&epsilon;, &alpha; log k/log log k}) on the competitive ratio of every deterministic algorithm for the problem, for any arbitrarily small constant &epsilon;.
on the separation and equivalence of paging strategies. it has been experimentally observed that lru and variants thereof are the preferred strategies for on-line paging. however, under most proposed performance measures for on-line algorithms the performance of lru is the same as that of many other strategies which are inferior in practice. in this paper we first show that any performance measure which does not include a partition or implied distribution of the input sequences of a given length is unlikely to distinguish between any two lazy paging algorithms as their performance is identical in a very strong sense. this provides a theoretical justification for the use of a more refined measure. building upon the ideas of concave analysis by albers et al. [afg05], we prove strict separation between lru and all other paging strategies. that is, we show that lru is the unique optimum strategy for paging under a deterministic model. this provides full theoretical backing to the empirical observation that lru is preferable in practice.
compressing rectilinear pictures and minimizing access control lists. we consider a geometric model for the problem of minimizing access control lists (acls) in network routers, a model that also has applications to rectilinear picture compression and figure drawing in common graphics software packages. here the goal is to create a colored rectilinear pattern within an initially white rectangular canvas, and the basic operation is to choose a subrectangle and paint it a single color, overwriting all previous colors in the rectangle. rectangle rule list (rrl) minimization is the problem of finding the shortest list of rules needed to create a given pattern. acl minimization is a restricted version of this problem where the set of allowed rectangles must correspond to pairs of ip address prefixes. motivated by the acl application, we study the special cases of rrl and acl minimization in which all rectangles must be strips that extend either the full width or the full height of the canvas (strip-rules). we provide several equivalent characterizations of the patterns achievable using strip-rules and present polynomial-time algorithms for optimally constructing such patterns when, as in the acl application, the only colors are black and white (permit or deny). we also show that rrl minimization is np-hard in general and provide o(min(n1/3, opt1/2))-approximation algorithms for general rrl and acl minimization by exploiting our results about strip-rule patterns.
k-means++: the advantages of careful seeding. the k-means method is a widely used clustering technique that seeks to minimize the average squared distance between points in the same cluster. although it offers no accuracy guarantees, its simplicity and speed are very appealing in practice. by augmenting k-means with a very simple, randomized seeding technique, we obtain an algorithm that is &theta;(logk)-competitive with the optimal clustering. preliminary experiments show that our augmentation improves both the speed and the accuracy of k-means, often quite dramatically.
path-independent load balancing with unreliable machines. we consider algorithms for load balancing on unreliable machines. the objective is to optimize the two criteria of minimizing the makespan and minimizing job reassignments in response to machine failures. we assume that the set of jobs is known in advance but that the pattern of machine failures is unpredictable. motivated by the requirements of bgp routing, we consider path-independent algorithms, with the property that the job assignment is completely determined by the subset of available machines and not the previous history of the assignments. we examine first the question of performance measurement of path-independent load-balancing algorithms, giving the measure of makespan and the normalized measure of reassignments cost. we then describe two classes of algorithms for optimizing these measures against an oblivious adversary for identical machines. the first, based on independent random assignments, gives expected reassignment costs within a factor of 2 of optimal and gives a makespan within a factor of o (log m/log log m) of optimal with high probability, for unknown job sizes. the second, in which jobs are first grouped into bins and at most one bin is assigned to each machine, gives constant-factor ratios on both reassignment cost and makespan, for known job sizes. several open problems are discussed.
sandpile transience on the grid is polynomially bounded. we study the process of adding one grain at a time in the abelian sandpile model (asm) based on the n x n grid (bak et al., 1988, dhar, 1990, dhar et al., 1995). we prove that within a polynomial (in n) number of steps, we necessarily reach a recurrent configuration regardless of the choice of sites where the grains are dropped. this adds credence to the common notion that "recurrence" represents "longterm behavior" of the system.
harmonic algorithm for 3-dimensional strip packing problem. in the three dimensional strip packing problem, we are given a set of three-dimensional rectangular items i = {(xi, yi, zi) : i = 1, ..., n} and a three dimensional box b. the goal is to pack all the items in the box b without any overlap, such that the height of the packing is minimized. we consider the most basic version of the problem, where the items must be packed with their edges parallel to the edges of b and cannot be rotated. building upon caprara's work [4] for the two dimensional bin packing problem we obtain an approximation algorithm with a similar performance guarantee of t&infin; &ap; 1.69 where t&infin; is the well known harmonic number that occurs naturally in the context of bin packing. the previously known approximation algorithms for this problem had worst case performance guarantees of 2 [7], 2.64 [14], 2.67 [15], 2.89 [10] and 3.25 [11]. our second algorithm is an asymptotic ptas for the case in which all items have square bases.
speed scaling for weighted flow time. in addition to the traditional goal of efficiently managing time and space, many computers now need to efficiently manage power usage. for example, intel's speedstep and amd's powernow technologies allow the windows xp operating system to dynamically change the speed of the processor to prolong battery life. in this setting, the operating system must not only have a job selection policy to determine which job to run, but also a speed scaling policy to determine the speed at which the job will be run. these policies must be online since the operating system does not in general have knowledge of the future. in current cmos based processors, the speed satisfies the well known cube-root-rule, that the speed is approximately the cube root of the power [mud01, bbs+00]. thus, in this work, we make the standard generalization that the power is equal to speed to some power &alpha; &ge; 1, where one should think of &alpha; as being approximately 3 [yds95, bkp04]. energy is power integrated over time. the operating system is faced with a dual objective optimization problem as it both wants to conserve energy, and optimize some quality of service (qos) measure of the resulting schedule.
a polynomial-time approximation scheme for steiner tree in planar graphs. we give an o(n log n) approximation scheme for steiner tree in planar graphs.
fast computation of power series solutions of systems of differential equations. we propose algorithms for the computation of the first n terms of a vector (or a full basis) of power series solutions of a linear system of differential equations at an ordinary point, using a number of arithmetic operations that is quasi-linear with respect to n. similar results are also given in the non-linear case. this extends previous results obtained by brent and kung for scalar differential equations of order 1 and 2.
on the bandwidth conjecture for 3-colourable graphs. a conjecture by bollob&aacute;s and koml&oacute;s states that for every &gamma; > 0 and integers r &ge; 2 and &delta;, there exists &beta; > 0 such that for sufficiently large n the following holds: if g is a graph on n vertices with minimum degree at least (r-1/r+&gamma;)n and h is an r-chromatic graph on n vertices with bandwidth at most &beta;n and maximum degree at most &delta;, then g contains a copy of h. this conjecture generalises several results concerning sufficient degree conditions for the containment of spanning subgraphs. we prove the conjecture for the case r = 3. our proof yields a polynomial time algorithm for embedding h into g if h is given together with a 3-colouring and vertex labelling respecting the bandwidth bound.
on extremal subgraphs of random graphs. let &kappa;l denote the complete graph on l vertices. we prove that there is a constant c = c(l) > 0, such that whenever p &ge; n-c, with probability tending to 1 when n goes to infinity, every maximum &kappa;l-free subgraph of the binomial random graph gn, p is (l-1)-partite. this answers a question of babai, simonovits and spencer [3]. the proof is based on a tool of independent interest: we show, for instance, that the maximum cut of almost all graphs with m edges, where m &gt; n, is nearly unique. more precisely, given a maximum cut c of gn, m, we can obtain all maximum cuts by moving at most o (&radic;n3/m) vertices between the parts of c.
single source multiroute flows and cuts on uniform capacity networks. for an integer h &ge; 1, an elementary h-route flow is a flow along h edge disjoint paths between a source and a sink, each path carrying a unit of flow, and a single commodity h-route flow is a non-negative linear combination of elementary h-flows. an instance of a single source multicommodity flow problem for a graph g = (v, e) consists of a source vertex s &epsilon; v and k sinks t1,..., tk &epsilon; v; we denote it i = (s; t1,..., tk). in the single source multicommodity multiroute flow problem, we are given an instance i = (s; t1,..., tk) and an integer h &ge; 1, and the objective is to maximize the total amount of flow that is transferred from the source to the sinks so that the capacity constraints are obeyed and, moreover, the flow of each commodity is an h-route flow. we study the relation between classical and multiroute single source flows on networks with uniform capacities and we provide a tight bound. in particular, we prove the following result. given an instance &ge; = (s; t1,...,tk) such that each s - ti pair is h-connected, the maximum classical flow between s and the ti's is at most 2(1 - 1/h)-times larger than the maximum h-route flow between s and the ti's and this is the best possible bound for h &ge; 2. this, as we show, is in contrast to the situation of general multicommodity multiroute flows that are up to k(1 - 1/h)-times smaller than their classical counterparts. as a corollary, we establish a max-flow min-cut theorem for the single source multicommodity multiroute flow and cut. an h-disconnecting cut for i is a set of edges f &sube; e such that for each i, the maximum h-flow between s - ti is zero. we show that the maximum h-flow is within 2(h-1) of the mininimum h-disconnecting cut, independently of the number of commodities; we also describe a 2(h - 1)-approximation algorithm for the minimum h-disconnecting cut problem.
multiple source shortest paths in a genus g graph. we give an o(g2nlog n) algorithm to represent the shortest path tree from all the vertices on a single specified face f in a genus g graph. from this representation, any query distance from a vertex in f can be obtained in o(log n) time. the algorithm uses a kinetic data structure, where the source of the tree iteratively moves across edges in f. in addition, we give applications using these shortest path trees in order to compute the shortest non-contractible cycle and the shortest non-separating cycle embedded on an orientable 2-manifold in o(g3nlog n) time.
obnoxious centers in graphs. we consider the problem of finding obnoxious centers in graphs. for arbitrary graphs with n vertices and m edges, we give a randomized algorithm with o(n log2 n + m log n) expected time. for planar graphs, we give algorithms with o(n log n) expected time and o(n log3 n) worst-case time. for graphs with bounded treewidth, we give an algorithm taking o(n log n) worst-case time. the algorithms make use of parametric search and several results for computing distances on graphs of bounded treewidth and planar graphs.
declaring independence via the sketching of sketches. we consider the problem of identifying correlations in data streams. surprisingly, our work seems to be the first to consider this natural problem. in the centralized model, we consider a stream of pairs (i,j) &isin; [n]2 whose frequencies define a joint distribution (x,y). in the distributed model, each coordinate of the pair may appear separately in the stream. we present a range of algorithms for approximating to what extent x and y are independent, i.e., how close the joint distribution is to the product of the marginals. we consider various measures of closeness including &ell;1, &ell;2, and the mutual information between x and y. our algorithms are based on "sketching sketches", i.e., composing small-space linear synopses of the distributions. perhaps ironically, the biggest technical challenges that arise relate to ensuring that different components of our estimates are sufficiently independent.
fast asynchronous byzantine agreement and leader election with full information. we resolve two long-standing open problems in distributed computation by describing polylogarithmic protocols for byzantine agreement and leader election in the asynchronous full information model with a non-adaptive malicious adversary. all past protocols for asynchronous byzantine agreement had been exponential, and no protocol for asynchronous leader election had been known. our protocols tolerate up to n/6+&epsilon; faulty processors, for any positive constant &epsilon;. they are monte carlo, succeeding with probability 1 - o(1) for byzantine agreement, and constant probability for leader election. a key technical contribution of our paper is a new approach for emulating feige's lightest bin protocol, even with adversarial message scheduling.
energy efficient online deadline scheduling. this paper extends the study of online algorithms for energy-efficient deadline scheduling to the overloaded setting. specifically, we consider a processor that can vary its speed between 0 and a maximum speed t to minimize its energy usage (of which the rate is roughly a cubic function of the speed). as the speed is upper bounded, the system may be overloaded with jobs and no scheduling algorithms can meet the deadlines of all jobs. an optimal schedule is expected to maximize the throughput, and furthermore, its energy usage should be the smallest among all schedules that achieve the maximum throughput. in designing a scheduling algorithm, one has to face the dilemma of selecting more jobs and being conservative in energy usage. even if we ignore energy usage, the best possible online algorithm is 4-competitive on throughput [12]. on the other hand, existing work on energy-efficient scheduling focuses on minimizing the energy to complete all jobs on a processor with unbounded speed, giving several o(1)-competitive algorithms with respect to the energy usage [2, 20]. this paper presents the first online algorithm for the more realistic setting where processor speed is bounded and the system may be overloaded; the algorithm is o(1)-competitive on both throughput and energy usage. if the maximum speed of the online scheduler is relaxed slightly to (1 + &epsilon;)t for some &epsilon; > 0, we can improve the competitive ratio on throughput to arbitrarily close to one, while maintaining o(1)-competitive on energy usage.
near-optimal algorithms for maximum constraint satisfaction problems. in this article, we present two approximation algorithms for the maximum constraint satisfaction problem with k variables in each constraint (max k-csp). given a (1 &minus; &epsiv;) satisfiable 2csp our first algorithm finds an assignment of variables satisfying a 1 &minus; o(&sqrt;&epsiv;) fraction of all constraints. the best previously known result, due to zwick, was 1 &minus; o(&epsiv;1/3). the second algorithm finds a ck/2k approximation for the max k-csp problem (where c > 0.44 is an absolute constant). this result improves the previously best known algorithm by hast, which had an approximation guarantee of &omega;(k/(2k log k)). both results are optimal assuming the unique games conjecture and are based on rounding natural semidefinite programming relaxations. we also believe that our algorithms and their analysis are simpler than those previously known.
a divide and conquer algorithm for -dimensional arrangement. we give an o(&radic;log n)-approximation algorithm for d-dimensional arrangement - the problem of mapping a graph to a d-dimensional grid (for constant d &ge; 2) to minimize the sum of edge lengths. this improves the previous best o(log n log log n) approximation of even, naor, rao and schieber. the d = 1 case is the well studied minimum linear arrangement problem. the problem is equivalent to the question of mapping a graph to integer points on a line so as to minimize the sum of edge costs, where edge costs are measured by edge lengths raised to the exponent &alpha; = 1/d. we give a simple recursive partitioning algorithm for this variant of linear arrangement for any exponent &alpha; &epsilon; (0, 1). our analysis also applies to a directed version of the problem: given a directed graph, the goal is to map vertices to the line so as to minimize the sum of costs of forward edges. as before, edge costs are edge lengths raised to the exponent &alpha;. the &alpha; = 0 case is the well known minimum feedback arc set problem, and the &alpha; = 1 case is essentially the minimum storage-time product problem. we analyze an extremely simple divide and conquer algorithm that uses a balanced cut subroutine with approximation ratio &beta; to recursively partition the graph. our analysis shows that this approach gives an approximation ratio of o(&beta;) for the minimum linear arrangement problem with exponent &alpha; for any fixed &alpha; &epsilon; (0, 1).
approximation algorithms for node-weighted buy-at-bulk network design. we present algorithms with poly-logarithmic approximation ratios for the buy-at-bulk network design problem in the node-weighted setting. we obtain the following results where h is the number of pairs in the input. &bull; on o(log h) approximation for the single-sink non-uniform buy-at-bulk network design. unless p = np this ratio is tight up to constant factors. &bull; an o(log4 h) approximation for the multi-commodity non-uniform buy-at-bulk network design problem.
approximate shortest paths in anisotropic regions. our goal is to find an approximate shortest path for a point robot moving in a planar subdivision with n vertices. let &rho; &ge; 1 be a real number. distances in each face of this subdivision are measured by a convex distance function whose unit disk is contained in a concentric unit euclidean disk, and contains a concentric euclidean disk with radius 1/&rho;. different convex distance functions may be used for different faces, and obstacles are allowed. these convex distance functions may be asymmetric. for all &epsilon; &isin; (0, 1), and for any two points vs and vd, we give an algorithm that finds a path from vs to vd whose cost is at most (1 + &epsilon;) times the minimum cost. our algorithm runs in o (&rho;2log&rho;/&epsilon;2n3 log (&rho;n/&epsilon;)) time. this bound does not depend on any other parameters; in particular, it does not depend on the minimum angle in the subdivision. we give applications to two special cases that have been considered before: the weighted region problem and motion planning in the presence of uniform flows. for the weighted region problem with weights in [1, &rho;] &cup; {&infin;}, the time bound of our algorithm improves to o (&rho;2log&rho;/&epsilon;n3 log (&rho;n/&epsilon;)).
convergence to approximate nash equilibria in congestion games. we study the ability of decentralized, local dynamics in non-cooperative games to rapidly reach an approximate nash equilibrium. for symmetric congestion games in which the edge delays satisfy a "bounded jump" condition, we show that convergence to an &epsilon;-nash equilibrium occurs within a number of steps that is polynomial in the number of players and &epsilon;-1. this appears to be the first such result for a class of games that includes examples for which finding an exact nash equilibrium is pls-complete, and in which shortest paths to an exact equilibrium are exponentially long. we show moreover that rapid convergence holds even under only the apparently minimal assumption that no player is excluded from moving for arbitrarily many steps. we also prove that, in a generalized setting where players have different "tolerances" &epsilon;i that specify their thresholds in the approximate nash equilibrium, the number of moves made by a player before equilibrium is reached depends only on his associated &epsilon;i, and not on those of the other players. finally, we show that polynomial time convergence still holds even when a bounded number of edges are allowed to have arbitrary delay functions.
a lower bound for scheduling mechanisms. we study the mechanism design problem of scheduling tasks on n unrelated machines in which the machines are the players of the mechanism. the problem was proposed and studied in the seminal paper of nisan and ronen on algorithmic mechanism design, where it was shown that the approximation ratio of mechanisms is between 2 and n. we improve the lower bound to $1+\sqrt{2}$for 3 or more machines.
testing for a theta. in this paper we survey some known results on the question of testing whether a given graph contains certain induced subgraphs. we also present a new algorithm, to test if a graph contains a special kind of an induced subgraph, called a "theta"
on testable properties in bounded degree graphs. we study graph properties which are testable for bounded degree graphs in time independent of the input size. our goal is to distinguish between graphs having a predetermined graph property and graphs that are far from every graph having that property. it is believed that almost all, even very simple graph properties require a large complexity to be tested for arbitrary (bounded degree) graphs. therefore in this paper we focus our attention on testing graph properties for special classes of graphs. we call a graph family non-expanding if every graph in this family is not a weak expander (its expansion is o(1/log2 n), where n is the graph size). a graph family is hereditary if it is closed under vertex removal. similarly, a graph property is hereditary if it is closed under vertex removal. next, we call a graph property &pi; to be testable for a graph family f if for every graph g &epsilon; f, in time independent of the size of g we can distinguish between the case when g satisfies property &pi; and when it is far from every graph satisfying property &pi;. in this paper we prove that in the bounded degree graph model, any hereditary property is testable if the input graph belongs to a hereditary and non-expanding family of graphs. as an application, our result implies that, for example, any hereditary property (e.g., k-colorability, h-freeness, etc.) is testable in the bounded degree graph model for planar graphs, graphs with bounded genus, interval graphs, etc. no such results have been known before and prior to our work, in the bounded degree graph model very few graph properties have been known to be testable for any graph classes.
spectral clustering with limited independence. this paper considers the well-studied problem of clustering a set of objects under a probabilistic model of data in which each object is represented as a vector over the set of features, and there are only k different types of objects. in general, earlier results (mixture models and "planted" problems on graphs) often assumed that all coordinates of all objects are independent random variables. they then appeal to the theory of random matrices in order to infer spectral properties of the feature x object matrix. however, in most practical applications, assuming full independence is not realistic. instead, we only assume that the objects are independent, but the coordinates of each object may not be. we first generalize the required results for random matrices to this case of limited independence using some new techniques developed in functional analysis. surprisingly, we are able to prove results that are quite similar to the fully independent case modulo an extra logarithmic factor. using these bounds, we develop clustering algorithms for the more general mixture models. our clustering algorithms have a substantially different and perhaps simpler "clean-up" phase than known algorithms. we show that our model subsumes not only the planted partition random graph models, but also another set of models under which there is a body of clustering algorithms, namely the gaussian and log-concave mixture models.
probabilistic analysis of linear programming decoding. we initiate the probabilistic analysis of linear programming (lp) decoding of low-density parity-check (ldpc) codes. specifically, we show that for a random ldpc code ensemble, the linear programming decoder of feld-man et al. succeeds in correcting a constant fraction of errors with high probability. the fraction of correctable errors guaranteed by our analysis surpasses all prior non-asymptotic results for ldpc codes, and in particular exceeds the best previous finite-length result on lp decoding by a factor greater than ten. this improvement stems in part from our analysis of probabilistic bit-flipping channels, as opposed to adversarial channels. at the core of our analysis is a novel combinatorial characterization of lp decoding success, based on the notion of a generalized matching. an interesting by-product of our analysis is to establish the existence of "almost expansion" in random bipartite graphs, in which one requires only that almost every (as opposed to every) set of a certain size expands, with expansion coefficients much larger than the classical case.
approximation algorithms via contraction decomposition. we prove that the edges of every graph of bounded (euler) genus can be partitioned into any prescribed number k of pieces such that contracting any piece results in a graph of bounded treewidth (where the bound depends on k). this decomposition result parallels an analogous, simpler result for edge deletions instead of contractions, obtained in [bak94, epp00, ddo+04, dhk05], and it generalizes a similar result for "compression" (a variant of contraction) in planar graphs [kle05]. our decomposition result is a powerful tool for obtaining ptass for contraction-closed problems (whose optimal solution only improves under contraction), a much more general class than minor-closed problems. we prove that any contraction-closed problem satisfying just a few simple conditions has a ptas in bounded-genus graphs. in particular, our framework yields ptass for the weighted traveling salesman problem and for minimum-weight c-edge-connected submultigraph on bounded-genus graphs, improving and generalizing previous algorithms of [gkp95, agk+98, kle05, gri00, cgsz04, bcgz05]. we also highlight the only main difficulty in extending our results to general h-minor-free graphs.
multiple choice tries and distributed hash tables. in this article we consider tries built from n strings such that each string can be chosen from a pool of k strings, each of them generated by a discrete i.i.d. source. three cases are considered: k = 2, k is large but fixed, and k ~ clog n. the goal in each case is to obtain tries as balanced as possible. various parameters such as height and fill-up level are analyzed. it is shown that for two-choice tries a 50% reduction in height is achieved when compared with ordinary tries. in a greedy online construction when the string that minimizes the depth of insertion for every pair is inserted, the height is only reduced by 25&percnt;. to further reduce the height by another 25%, we design a more refined online algorithm. the total computation time of the algorithm is o(nlog n). furthermore, when we choose the best among k &ge; 2 strings, then for large but fixed k the height is asymptotically equal to the typical depth in a trie. finally, we show that further improvement can be achieved if the number of choices for each string is proportional to log n. in this case highly balanced trees can be constructed by a simple greedy algorithm for which the difference between the height and the fill-up level is bounded by a constant with high probability. this, in turn, has implications for distributed hash tables, leading to a randomized id management algorithm in peer-to-peer networks such that, with high probability, the ratio between the maximum and the minimum load of a processor is o(1). &copy; 2008 wiley periodicals, inc. random struct. alg., 2009
equilibria in online games. we initiate the study of scenarios that combine online decision making with interaction between non-cooperative agents. to this end we introduce online games that model such scenarios as non-cooperative games, and lay the foundations for studying this model. roughly speaking, an online game captures systems in which independent agents serve requests in a common environment. the requests arrive in an online fashion and each is designated to be served by a different agent. the cost incurred by serving a request is paid for by the serving agent, and naturally, the agents seek to minimize the total cost they pay. since the agents are independent, it is unlikely that some central authority can enforce a policy or an algorithm (centralized or distributed) on them, and thus, the agents can be viewed as selfish players in a non-cooperative game. in this game, the players have to choose as a strategy an online algorithm according to which requests are served. to further facilitate the game theoretic approach, we suggest the measure of competitive analysis as the players' decision criterion. as the expected result of non-cooperative games is an equilibrium, the question of finding the equilibria of a game is of central importance, and thus, it is the central issue we concentrate on in this paper. we study some natural examples for online games; in order to obtain general insights and develop generic techniques, we present an abstract model for the study of online games generalizing metrical task systems. we suggest a method for constructing equilibria in this model and further devise techniques for implementing it.
considering suppressed packets improves buffer management in qos switches. the following buffer management problem arises in network switches providing differentiated services: at the beginning of each time step, one packet can be sent, and afterwards an arbitrary number of new packets arrive. packets that are not sent can be stored in a buffer. each packet is attributed by a deadline, and a packet is automatically deleted from the buffer if it is still stored in the buffer by the end of its deadline. the differentiated service model is abstracted by attributing each packet with a value according to its service level. a buffer management strategy determines the packet to be sent in each time step. the goal of a buffer management strategy is to maximize the sum of the values of sent packets. we introduce the concept of suppressed packets and present a deterministic strategy that is based on this concept. we show that this strategy achieves a competitive ratio of 2&radic;2--1 &ap; 1.828, which is the best known competitive ratio in the deterministic case. further, we present a memoryless version of this strategy that achieves a competitive ratio of &ap; 1.893. this is the first memoryless strategy that achieves a competitive ratio less than 2, and the competitive ratio of this strategy is even better than the ratios of all previously known deterministic strategies. this demonstrates the potential of the concept of suppressed packets. in addition, we present a simple strategy that achieves the optimal competitive ratio of min{(1 + &alpha;)/&alpha;, 2&alpha;/(&alpha;+1)} &le; &radic;2, if only two packet values 1 and &alpha; > 1 are possible.
graph balancing: a special case of scheduling unrelated parallel machines. we design a 1.75-approximation algorithm for a special case of scheduling parallel machines to minimize the makespan, namely the case where each job can be assigned to at most two machines with the same processing time on either machine. (this is a special case of so-called restricted assignment, where the set of eligible machines can be arbitrary for each job.) we also show that even for this special case it is np-hart to compute better than 1.5 approximation. this is the first improvement of the approximation ratio 2 of lenstra, shmoys, and tardos [approximation algorithms for scheduling unrelated parallel machines, math. program. 46:259--271, 1990], for any special case with unbounded number of machines. our lower bound yields the same ratio as their bound which works for restricted assignment, and which is still the state-of-the-art lower bound even for the most general case.
resilient search trees. we investigate the problem of computing in a reliable fashion in the presence of faults that may arbitrarily corrupt memory locations. in this framework, we focus on the design of resilient data structures, i.e., data structures that, despite the corruption of some memory values during their lifetime, are nevertheless able to operate correctly (at least) on the set of uncorrupted values. in particular, we present resilient search trees which achieve optimal time and space bounds while tolerating up to o(&radic;log n) memory faults, where n is the current number of items in the search tree. in more detail, our resilient search trees are able to insert, delete and search for a key in o(log n + &delta;2) amortized time, where &delta; is an upper bound on the total number of faults. the space required is o(n + &delta;).
analytic combinatorics: a calculus of discrete structures. the efficiency of many discrete algorithms crucially depends on quantifying properties of large structured combinatorial configurations. we survey methods of analytic combinatorics that are simply based on the idea of associating numbers to atomic elements that compose combinatorial structures, then examining the geometry of the resulting functions. in this way, an operational calculus of discrete structures emerges. applications to basic algorithms, data structures, and the theory of random discrete structures are outlined.
network sketching or: "how much geometry hides in connectivity?--part ii". wireless sensor networks typically consist of small, very simple network nodes without any positioning device like gps. after an initialization phase, the nodes know with whom they can talk directly, but have no idea about their relative geographic locations. we examine how much geometry information is nevertheless hidden in the communication graph of the network: assuming that the connectivity is determined by the well-known unit-disk graph model, we show that using a very simple distributed algorithm we can identify a large, provably planar subgraph of the communication graph that faithfully reflects the topology of the network. this planar subgraph can then be embedded using a simple distributed rubber-banding procedure, finally obtaining virtual coordinates for the nodes of the subgraph which can be instrumented for various protocols based on geographic location information. that is, there is enough geometry information hidden in the connectivity structure not only to identify topological features like network holes (as it was also exhibited in the predecessor paper [7]) but even enough information to compute a sketch of the network layout. our simulation results indicate that the algorithm works very well even for very sparse network deployments and produces network sketches that come close to the original layout.
torpid mixing of local markov chains on 3-colorings of the discrete torus. we study local markov chains for sampling 3-colorings of the discrete torus tl, d = {0, ..., l--1}d. we show that there is a constant &rho; &ap; .22 such that for all even l &ge; 4 and d sufficiently large, certain local markov chains require exponential time to converge to equilibrium. more precisely, if m is a markov chain on the set of proper 3-colorings of tl, d that updates the color of at most &rho;ld vertices at each step and whose stationary distribution is uniform, then the convergence to stationarity of m is exponential in ld-1. our proof is based on a conductance argument that builds on sensitive new combinatorial enumeration techniques.
correlation decay and deterministic fptas for counting list-colorings of a graph. we propose a deterministic algorithm for approximately counting the number of list colorings of a graph. under the assumption that the graph is triangle free, the size of every list is at least &alpha;&delta;, where &alpha; is an arbitrary constant bigger than &alpha; = 2.8432 ..., the solution of &alpha;e-1/&alpha; = 2, and &alpha; is the maximum degree of the graph, we obtain the following results. for the case when the size of the each list is a large constant, we show the existence of a deterministic fptas for computing the total number of list colorings. the same deterministic algorithm has complexity 2o(log2 n) without any assumptions on the sizes of the lists, where n is the size of the instance. our results are not based on the most powerful existing counting technique - rapidly mixing markov chain method. rather we build upon concepts from statistical physics, in particular, the decay of correlation phenomena and its implication for the uniqueness of gibbs measures in infinite graphs. this approach was proposed in two recent papers [bg06] and [wei05]. the principle insight of the present work is that the correlation decay property can be established with respect to certain computation tree, as opposed to the conventional correlation decay property which is typically established with respect to graph theoretic neighborhoods of a given node. this allows truncation of computation at a logarithmic depth in order to obtain polynomial accuracy in polynomial time. while the analysis conducted in this paper is limited to the problem of counting list colorings, the proposed algorithm can be extended to an arbitrary constraint satisfaction problem in a straightforward way.
optimal dynamic vertical ray shooting in rectilinear planar subdivisions. we consider the dynamic vertical ray shooting problem against horizontal disjoint segments, that is, the task of maintaining a dynamic set s of n nonintersecting horizontal line segments in the plane under a query that reports the first segment in s intersecting a vertical ray from a query point. we develop a linear-size structure that supports queries, insertions, and deletion in o(log n) worst-case time. our structure works in the comparison model on a random access machine.
model-driven optimization using adaptive probes. in several applications such as databases, planning, and sensor networks, parameters such as selectivity, load, or sensed values are known only with some associated uncertainty. the performance of such a system (as captured by some objective function over the parameters) is significantly improved if some of these parameters can be probed or observed. in a resource constrained situation, deciding which parameters to observe in order to optimize system performance itself becomes an interesting and important optimization problem. this problem is the focus of this paper. unfortunately designing optimal observation schemes is np-hard even for the simplest objective functions, leading to the study of approximation algorithms. in this paper we present general techniques for designing non-adaptive probing algorithms which are at most a constant factor worse than optimal adaptive probing schemes. interestingly, this shows that for several problems of interest, while probing yields significant improvement in the objective function, being adaptive about the probing is not beneficial beyond constant factors.
competitive queue management for latency sensitive packets. we consider the online problem of non-preemptive queue management. an online sequence of packets arrive, each of which has an associated intrinsic value. packets can be accepted to a fifo queue, or discarded. the profit gained by transmitting a packet diminishes over time and is equal to its value minus the delay. this corresponds to the well known and strongly motivated naor's model in operations research. we give a queue management algorithm with a competitive ratio equal to the golden ratio (&phi; &ap; 1.618) in the case that all packets have the same value, along with a matching lower bound. we also derive &theta;(1) upper and lower bounds on the competitive ratio when packets have different intrinsic values (in the case of differentiated services). we can extend our results to deal with more general models for loss of value over time. finally, we re-interpret our online algorithms in the context of selfish agents, producing an online mechanism that approximates the optimal social welfare to within a constant factor.
improved bounds for the symmetric rendezvous value on the line. a notorious open problem in the field of rendezvous search is to decide the rendezvous value of the symmetric rendezvous search problem on the line, when the initial distance between the two players is two. we show that the symmetric rendezvous value is within the interval (4.1520, 4.2574), which considerably improves the previous best-known result (3.9546, 4.3931). to achieve the improved bounds, we call upon results from absorbing markov chain theory and mathematical programming theory---particularly fractional quadratic programming and semidefinite programming. moreover, we also establish some important properties of this problem, which could be of independent interest and useful for resolving this problem completely. finally, we conjecture that the symmetric rendezvous value is asymptotically equal to 4.25 based on our numerical calculations.
efficient algorithms for computing all low edge connectivities and related problems. given an undirected unweighted graph g = (v, e) and an integer k &ge; 1, we consider the problem of computing the edge connectivities of all those (s, t) vertex pairs, whose edge connectivity is at most k. we present an algorithm with expected running time &otilde;(m + nk3) for this problem, where |v| = n and |e| = m. our output is a weighted tree t whose nodes are the sets v1, v2,..., v l of a partition of v, with the property that the edge connectivity in g between any two vertices s &epsilon; vi and t &epsilon; vj, for i &ne; j, is equal to the weight of the lightest edge on the path between vi and vj in t. also, two vertices s and t belong to the same vi for any i if and only if they have an edge connectivity greater than k. currently, the best algorithm for this problem needs to compute all-pairs min-cuts in an o(nk) edge graph; this takes &otilde;(m + n5/2kmin{k1/2, n1/6}) time. our algorithm is much faster for small values of k; in fact, it is faster whenever k is o(n5/6). our algorithm yields the useful corollary that in &otilde;(m + nc3) time, where c is the size of the global min-cut, we can compute the edge connectivities of all those pairs of vertices whose edge connectivity is at most &alpha;c for some constant &alpha;. we also present an &otilde;(m + n) monte carlo algorithm for the approximate version of this problem. this algorithm is applicable to weighted graphs as well. our algorithm, with some modifications, also solves another problem called the minimum t-cut problem. given t &sube; v of even cardinality, we present an &otilde;(m + nk3) algorithm to compute a minimum cut that splits t into two odd cardinality components, where k is the size of this cut.
maximum -flow with crossings in ( log ) time. there is a large body of results on planar graph algorithms that are more efficient than the best known algorithm for general graphs [13]. maximum flow [1] is but one example. more drastically, the maximum cut problem is polynomially solvable for planar instances but np-complete in general [12, 8, 5]. however, little is known about nearly planar graphs. this is unsatisfactory since the nearly planar case is particularly important in practice. think for example of road networks with bridges and tunnels. we present a preflow push algorithm that solves the maximum s-t-flow problem in a network with n vertices and m edges and embedded with k crossings in time o(k3n log n) worst case. to our knowledge there is only one previous result that relates asymptotic running time to a topological parameter of the graph such that the running time is polynomial in this parameter. compared with the currently fastest maximum flow algorithms this reduces the worst case running time by a factor of m/k3 ignoring logarithmic factors. therefore, it is particularly favorable for very sparse or nearly planar graphs.
digraph measures: kelly decompositions, games, and orderings. we consider various well-known, equivalent complexity measures for graphs such as elimination orderings, k-trees and cops and robber games and study their natural translations to digraphs. we show that on digraphs the translations of these measures are also equivalent and induce a natural connectivity measure. we introduce a decomposition for digraphs and an associated width, kelly-width, which is equivalent to the aforementioned measure. we demonstrate its usefulness by exhibiting potential applications including polynomial-time algorithms for np-complete problems on graphs of bounded kelly-width, and complexity analysis of asymmetric matrix factorization. finally, we compare the new width to other known decompositions of digraphs.
a 1.875: approximation algorithm for the stable marriage problem. we consider the problem of finding a stable matching of maximum size when both ties and unacceptable partners are allowed in preference lists. this problem is known to be apx-hard, and the current best known approximation algorithm achieves the approximation ratio 2-c 1/&radic;n, where c is some positive constant. in this paper, we give a 1.875-approximation algorithm, which is the first result on the approximation ratio better than two.
the independent even factor problem. this paper deals with the independent even factor problem, which generalizes both of the matching problem and the matroid intersection problem. for odd-cycle-symmetric digraphs, in which each arc in any odd dicycle has the reverse arc, a min-max formula is established as a common generalization of the tutte-berge formula for matchings and the min-max formula of edmonds (1970) for matroid intersection. we devise a combinatorial efficient algorithm to find a maximum independent even factor in an odd-cycle-symmetric digraph, which commonly extends two of the alternating-path type algorithms, the even factor algorithm of pap (2005) and the matroid intersection algorithms. this algorithm gives a constructive proof of the min-max formula, and contains a new operation on matroids, which corresponds to shrinking factor-critical components in the matching algorithm of edmonds (1965). the running time of the algorithm is o(n4q), where n is the number of vertices and q is the time for an independence test. the algorithm also gives a common generalization of the edmonds-gallai decomposition for matchings and the principal partition for matroid intersection.
ultra-succinct representation of ordered trees. there exist two well-known succinct representations of ordered trees: bp (balanced parenthesis) [munro, raman 2001] and dfuds (depth first unary degree sequence) [benoit et al. 2005]. both have size 2n + o(n) bits for n-node trees, which asymptotically matches the information-theoretic lower bound. many fundamental operations on trees can be done in constant time on word ram, for example finding the parent, the first child, the next sibling, the number of descendants, etc. however there has been no single representation supporting every existing operation in constant time; bp does not support i-th child, while dfuds does not support lca (lowest common ancestor). in this paper, we give the first succinct tree representation supporting every one of the fundamental operations previously proposed for bp or dfuds along with some new operations in constant time. moreover, its size surpasses the information-theoretic lower bound and matches the entropy of the tree based on the distribution of node degrees. we call this an ultra-succinct data structure. as a consequence, a tree in which every internal node has exactly two children can be represented in n + o(n) bits. we also show applications for ultra-succinct compressed suffix trees and labeled trees.
efficient aggregation algorithms for probabilistic data. we study the problem of computing aggregation operators on probabilistic data in an i/o efficient manner. algorithms for aggregation operators such as sum, count, avg, and min/max are crucial to applications on probabilistic databases. we give a generalization of the classical data stream model to handle probabilistic data, called probabilistic streams, in order to analyze the i/o-requirements of our algorithms. whereas the algorithms for sum and count turn out to be simple, the problem is harder for both avg and min/max. although data stream algorithms typically use randomness, all of the algorithms we present are deterministic. for min and max, we obtain efficient one-pass data stream algorithms for estimating each of these quantities with relative accuracy (1 + &epsilon;), using constant update time per element and o(1/&epsilon; lg r) space, where each element has a value between 1 and r. for avg, we present a new data stream algorithm for estimating its value to a relative accuracy (1 + &epsilon;) in o(log n) passes over the data with o(1/&epsilon; log2 n) space and update time o(1/&epsilon; log n) per element. on the other hand, we prove a space lower bound of &omega;(n) for any exact one-pass deterministic data stream algorithm. complementing this result, we also present an o(n log2 n)-time exact deterministic algorithm which uses o(n) space (thus removing the data-streaming restriction), improving dramatically on the previous o(n3)-time algorithm. our algorithms for avg involve a novel technique based on generating functions and numerical integration, which may be of independent interest. finally, we provide an experimental analysis and show that our algorithms, coupled with additional heuristics, have excellent performance over large data sets.
games of fixed rank: a hierarchy of bimatrix games. we propose and investigate bimatrix games, whose (entry-wise) sum of the pay-off matrices of the two players is of rank k, where k is a constant. we will say the rank of such a game is k. for every fixed k, the class of rank k-games strictly generalizes the class of zero-sum games, but is a very special case of general bimatrix games. we show that even for k = 1 the set of nash equilibria of these games can consist of an arbitrarily large number of connected components. while the question of exact polynomial time algorithms to find a nash equilibrium remains open for games of fixed rank, we can provide a deterministic polynomial time algorithm for finding an &epsilon;-approximation (whose running time is polynomial in 1\&epsilon;) as well as a randomized polynomial time approximation algorithm (whose running time is similar), but which offers the possibility of finding an exact solution in polynomial time if a conjecture is valid. the latter algorithm is based on a new application of random sampling methods to quadratic optimization problems of fixed rank.
recognizing partial cubes in quadratic time. we show how to test whether a graph with n vertices and m edges is a partial cube, and if so how to find a distance-preserving embedding of the graph into a hypercube, in the near-optimal time bound o(n2), improving previous o(nm)-time solutions.
noisy binary search and its applications. we study a noisy version of the classic binary search problem of inserting an element into its proper place within an ordered sequence by comparing it with elements of the sequence. in the noisy version we can not compare elements directly. instead we are given a coin corresponding to each element of the sequence, such that as one goes through the ordered sequence the probability of observing heads when tossing the corresponding coin increases. we design online algorithms which adaptively choose a sequence of experiments, each consisting of tossing a single coin, with the goal of identifying the highest-numbered coin in the ordered sequence whose heads probability is less than some specified target value. possible applications of such algorithms include investment planning, sponsored search advertising, admission control in queueing networks, college admissions, and admitting new members into an organization ranked by ability, such as a tennis ladder.
optimal scale-free compact routing schemes in networks of low doubling dimension. we present optimal-stretch scale-free compact routing schemes for networks of low doubling dimension, in both the name-independent and name-dependent models. our name-independent algorithm is the first scale-free name-independent compact routing scheme to achieve asymptotically optimal stretch, closing the gaps left by the work of abraham et al. (icdcs'06) and konjevod et al. (podc'06). our name-dependent algorithm is the first scale-free optimal-stretch name-dependent compact routing scheme that uses optimal [log n]-bit routing labels, in spite of the limited routing label information. we define a simple hierarchical decomposition technique based on ball-packings. our algorithms rely on a novel combination of ball-packings and hierarchical r-nets, which we see as a contribution in its own right.
better online buffer management. as the internet becomes more mature, there is a realization that improving the performance of routers has the potential to substantially improve internet performance in general. currently, most routers forward packets in a first-in-first-out (fifo) order. however, the diversity of applications supported by modern ip-based networks has resulted in unpredictable packet flows, and heterogeneous network traffic. thus, it is becoming more reasonable to consider differentiating between different types of packets, and perhaps to consider allowing packets to specify a deadline by which it must be processed. these issues have made buffer management at routers a critical issue in providing effective quality of service to the various applications that use the network. in this paper, we study an online problem in which each packet is described by its discrete arrival time, non-negative weight and discrete deadline; arriving packets are buffered for delivery and all packets have the same processing time. the packets arrive online, and our objective is to maximize the sum of weights of those packets that are sent by their deadlines. we describe an online deterministic algorithm with a competitive ratio of 1.854, improving the best previous known competitive ratio of 1.939 (bartal et al. stacs 2004). the algorithmic framework we use has several interesting features. first, we do not use a potential function. instead, after each step we modify the adversary's buffer. second, we introduce "dummy packets" to facilitate the decision making.
online vertex colorings of random graphs without monochromatic subgraphs. consider the following generalized notion of graph colorings: a vertex coloring of graph g is valid w.r.t. some fixed nonempty graph f if no color class induces a copy of f in g, i.e., there is no monochromatic copy of f in g. we propose and analyze an algorithm for computing valid colorings of a random graph gn, p on n vertices with edge probability p in an online fashion. for a large family of graphs f including cliques and cycles of arbitrary size, the proposed algorithm is optimal in the following sense: for any integer r &ge; 1, there is a constant &beta; = &beta;(f, r) such that the algorithm a.a.s. (asymptotically almost surely) computes a valid r-coloring of gn, p w.r.t. f online if p &lt; n-&beta;, and any online algorithm will a.a.s. fail to do so if p &gt; n-&beta;. that is, we observe a threshold phenomenon determined by the function n-&beta;.
counting good truth assignments of random -sat formulae. we present a deterministic approximation algorithm to compute logarithm of the number of 'good' truth assignments for a random k-satisfiability (k-sat) formula in polynomial time (by 'good' we mean that violates a small fraction of clauses). the relative error is bounded above by an arbitrarily small constant &epsilon; with high probability1 as long as the clause density (ratio of clauses to variables) &alpha; < &alpha;u(k) = 2k-1logk(1 + o(1)). the algorithm is based on computation of marginal distribution via belief propagation and use of an interpolation procedure. this scheme substitutes the traditional one based on approximation of marginal probabilities via mcmc, in conjunction with self-reduction, which is not easy to extend to the present problem. our results are expected hold for a reasonable non-random setup with locally tree-like sparse k-sat formulas. we derive 2k-1 log k(1+o(1)) as threshold for uniqueness of the gibbs distribution on satisfying assignment of random infinite tree k-sat formulae to establish our results, which is of interest in its own right.
setting lower bounds on truthfulness: extended abstract. we present and discuss general techniques for proving inapproximability results for truthful mechanisms. we make use of these techniques to prove lower bounds on the approximability of several non-utilitarian multi-parameter problems. in particular, we demonstrate the strength of our techniques by exhibiting a lower bound of 2 - 1/m for the scheduling problem with unrelated machines (formulated as a mechanism design problem in the seminal paper of nisan and ronen on algorithmic mechanism design). our lower bound applies to truthful randomized mechanisms (disregarding any computational assumptions on the running time of these mechanisms). moreover, it holds even for the weaker notion of truthfulness for randomized mechanisms - i.e., truthfulness in expectation. this lower bound nearly matches the known 7/4 (randomized) truthful upper bound for the case of two machines (a non-truthful fptas exists). no lower bound for truthful randomized mechanisms in multi-parameter settings was previously known. we show an application of our techniques to the workload-minimization problem in networks. we prove our lower bounds for this problem in the inter-domain routing setting presented by feigenbaum, papadimitriou, sami, and shenker. finally, we discuss several notions of non-utilitarian "fairness" (max-min fairness, min-max fairness, and envy minimization). we show how our techniques can be used to prove lower bounds for these notions.
approximating the spanning star forest problem and its applications to genomic sequence alignment. this paper studies the algorithmic issues of the spanning star forest problem. we prove the following results: (1) there is a polynomial-time approximation scheme for planar unweighted graphs; (2) there is a polynomial-time algorithm with approximation ratio 3/5 for unweighted graphs; (3) it is np-hard to approximate the problem within ratio 545/546 + &epsilon; for unweighted graphs; (4) there is a linear-time algorithm to compute the maximum star forest of a weighted tree; (5) there is a polynomial-time algorithm with approximation ratio 1/2 for weighted graphs. we also show how to apply this spanning star forest model to aligning multiple genomic sequences over a tandem duplication region.
on bregman voronoi diagrams. the voronoi diagram of a point set is a fundamental geometric structure that partitions the space into elementary regions of influence defining a discrete proximity graph and dually a well-shaped delaunay triangulation. in this paper, we investigate a framework for defining and building the voronoi diagrams for a broad class of distortion measures called bregman divergences, that includes not only the traditional (squared) euclidean distance, but also various divergence measures based on entropic functions. as a by-product, bregman voronoi diagrams allow one to define information-theoretic voronoi diagrams in statistical parametric spaces based on the relative entropy of distributions. we show that for a given bregman divergence, one can define several types of voronoi diagrams related to each other by convex duality or embedding. moreover, we can always compute them indirectly as power diagrams in primal or dual spaces, or directly after linearization in an extra-dimensional space as the projection of a euclidean polytope. finally, our paper proposes to generalize bregman divergences to higher-order terms, called &kappa;-jet bregman divergences, and touch upon their voronoi diagrams.
randomization does not help searching predecessors. at stoc'06, we presented a new technique for proving cell-probe lower bounds for static data structures with deterministic queries. this was the first technique which could prove a bound higher than communication complexity, and it gave the first separation between data structures with linear and polynomial space. the new technique was, however, heavily tuned for the deterministic worst-case, demonstrating long query times only for an exponentially small fraction of the input. in this paper, we extend the technique to give lower bounds for randomized query algorithms with constant error probability. our main application is the problem of searching predecessors in a static set of n integers, each contained in a l-bit word. our trade-off lower bounds are tight for any combination of parameters. for small space, i.e. n1+o(1), proving such lower bounds was inherently impossible through known techniques. an interesting new consequence is that for near linear space, the classic van emde boas search time of o(lg l) cannot be improved, even if we allow randomization. this is a separation from polynomial space, since beame and fich [stoc'02] give a predecessor search time of o(lg l/lg lg l) using quadratic space. we also show a tight &omega;(lg lg n) lower bound for 2-dimensional range queries, via a new reduction. this holds even in rank space, where no superconstant lower bound was known, neither randomized nor worst-case. we also slightly improve the best lower bound for the approximate nearest neighbor problem, when small space is available.
ranged hash functions and the price of churn. ranged hash functions generalize hash tables to the setting where hash buckets may come and go over time, a typical case in distributed settings where hash buckets may correspond to unreliable servers or network connections. monotone ranged hash functions are a particular class of ranged hash functions that minimize item reassignments in response to churn: changes in the set of available buckets. the canonical example of a monotone ranged hash function is the ring-based consistent hashing mechanism of karger et al. [13]. these hash functions give a maximum load of &theta; (n/mlogm) when n is the number of items and m is the number of buckets. the question of whether some better bound could be obtained using a more sophisticated hash function has remained open. we resolve this question by showing two lower bounds. first, the maximum load of any randomized monotone ranged hash function is &omega;(&radic;n/mlnm) when n = o(mlogm). this bound covers almost all of the nontrivial case, because when n = &omega;(mlogm) simple random assignment matches the trivial lower bound of &omega;(n/m). we give a matching (though impractical) upper bound that shows that our lower bound is tight over almost all of its range. second, for randomized monotone ranged hash functions derived from metric spaces, there is a further trade-off between the expansion factor of the metric and the load balance, which for the special case of growth-restricted metrics gives a bound of &omega;(n/mlogm), asymptotically equal to that of consistent hashing. these are the first known non-trivial lower bounds for ranged hash functions. they also explain why in ten years no better ranged hash functions have arisen to replace consistent hashing.
why simple hash functions work: exploiting the entropy in a data stream. hashing is fundamental to many algorithms and data structures widely used in practice. for theoretical analysis of hashing, there have been two main approaches. first, one can assume that the hash function is truly random, mapping each data item independently and uniformly to the range. this idealized model is unrealistic because a truly random hash function requires an exponential number of bits to describe. alternatively, one can provide rigorous bounds on performance when explicit families of hash functions are used, such as 2-universal or o(1)-wise independent families. for such families, performance guarantees are often noticeably weaker than for ideal hashing. in practice, however, it is commonly observed that simple hash functions, including 2-universal hash functions, perform as predicted by the idealized analysis for truly random hash functions. in this paper, we try to explain this phenomenon. we demonstrate that the strong performance of universal hash functions in practice can arise naturally from a combination of the randomness of the hash function and the data. specifially, following the large body of literature on random sources and randomness extraction, we model the data as coming from a "block source," whereby each new data item has some "entropy" given the previous ones. as long as the (renyi) entropy per data item is sufficiently large, it turns out that the performance when choosing a hash function from a 2-universal family is essentially the same as for a truly random hash function. we describe results for several sample applications, including linear probing, balanced allocations, and bloom filters.
product growth and mixing in finite groups. we prove the following inequality on the convolution of distributions over a finite group g: {display equation} where x, y are probability distributions over g, the * denotes convolution, u the uniform distribution over g, and || &middot; || the l2-norm; n is the order of g, and m denotes the minimum dimension of nontrivial real representations of g. this inequality can be viewed as a new expansion property of a large class of groups, including all lie-type simple groups of bounded rank, all of which satisfy m > cn&beta; (where c > 0 is an absolute constant and &beta; > 0 depends on the rank bound only). best among them are the groups g = sl2(q) (2 x 2 matrices with determinant 1 over 픽q) where m &sim; n1/3/2. we derive applications of the convolution inequality (0.1) to a variety of areas, ranging from stochastic processes to additive combinatorics to group theory. an immediate consequence is a product growth inequality for subsets of g: if a, b &sube; g then |ab| > n/(1 + &delta;) where &delta; = n2/(m|a||b|). on the one hand, this corollary strengthens a recent result of gowers which served as the inspiration to the present work; on the other hand, it gives a strong (and best possible) affirmative answer to a problem regarding the product growth of subsets of sl2(q) recently posed by venkatesh and green at a conference in the newly flourishing area of "additive combinatorics." another corollary to the main inequality shows that for groups with large m, mixing in the strongest sense (&ell;&infin;-norm) occurs more rapidly than expected; we prove that if x, y, z are distributions over g then {display equation} this generalizes a result of gowers. by easy induction, our main inequality generalizes to the convolution of multiple terms and thereby results in rapid mixing estimates for time-inhomogeneous cayley walks on g. it also gives estimates for the size of the product of several subsets, resulting in diameter estimates for cayley graphs and tying in with the broad subject of "bounded generation" in group theory. an illustration of the connection to diameters: for g = sl2(q) it follows that if a &sube; g and |a| &ge; n2/3+&epsilon; then at = g where t = o(1/&epsilon;); we also show that the elements of g are represented nearly uniformly as words of length t over a. the connection to "bounded generation" is illustrated by one of the main applications of our results: every finite simple group of lie type of characteristic p is the product of 5 sylow p-subgroups. - results of this type are among the ingredients of the recent breakthrough result that all finite simple groups have bounded degree expander cayley graphs [kln]; our results improve and greatly simplify these ingredients. the results and techniques used in this paper were inspired by a link between quasirandomness and group representation theory recently found by gowers [go].
the power of memory in randomized broadcasting. in this paper we analyze the runtime and number of message transmissions generated by simple randomized broadcasting algorithms in random-like networks, and show that an apparently minor change in the ability of the nodes implies an exponential decrease in the average communication overhead produced by these algorithms at an arbitrary node. a natural randomized broadcasting protocol, called random phone call model, has been introduced by karp et al. [20]. in this model it is assumed that in each time step, every node of g calls a neighbor, chosen uniformly at random, and establishes a communication channel with this neighbor. any node u is then allowed to send/receive messages to/from all nodes which have established communication channels with u in the current time step. karp et al. showed that some piece of information r, placed initially on one of the nodes of a complete graph of size n, can be spread with probability 1 - n-&omega;(1) to all nodes of this graph within o(log n) time steps, by using o(n log log n) transmissions related to r. furthermore, they proved that this result is asymptotically optimal among all address-oblivious broadcasting algorithms. in a recent paper [9], we analyzed the random phone call model in traditional random graphs gn,p with p > log2 n/n, and showed that any address-oblivious broadcasting algorithm requires with high probability &omega;(log n) time steps and &omega;(n (log log n + log n/log(pn))) message transmissions to inform all nodes of such a graph. in this paper we consider two simple modifications of the random phone call model, and show that in both cases the number of total message transmissions can be reduced significantly (up to almost a logarithmic factor). in the first case, we allow each node of a random graph gn,p with p > log&delta; n/n, where &lambda; is a properly chosen constant, to call in every time step four different neighbors, chosen uniformly at random, and we prove that the number of message transmissions decreases to o(n log log n). this can be viewed as a "power of multiple choices" type theorem for randomized broadcasting. then we show that if in the random phone call model the nodes are provided with a little memory, i.e., they are able to remember the addresses of the nodes chosen in the most recent three time steps, then the communication overhead decreases substantially, too. finally, we prove the optimality of our results. the algorithms presented in this paper can cope with restricted communication failures, only require rough estimates of the number of nodes, and are robust against slight topological changes. in addition, our results can be extended to the generalized random graph model of [6].
efficient reductions among lattice problems. we give various deterministic polynomial time reductions among approximation problems on point lattices. our reductions are both efficient and robust, in the sense that they preserve the rank of the lattice and approximation factor achieved. our main result shows that for any &gamma; &ge; 1, approximating all the successive minima of a lattice (and, in particular, approximately solving the shortest independent vectors problem, sivp&gamma;) within a factor &gamma; reduces under deterministic polynomial time rank-preserving reductions to approximating the closest vector problem (cvp) within the same factor &gamma;. this solves an open problem posed by bl&ouml;mer in (icalp 2000). as an application, we obtain faster algorithms for the exact solution of sivp that run in time n! &middot; so(1) (where n is the rank of the lattice, and s the size of the input,) improving on the best previously known solution of bl&ouml;mer (icalp 2000) by a factor 3n. we also show that sivp, cvp and many other lattice problems are equivalent in their exact version under deterministic polynomial time rank-preserving reductions.
fast dimension reduction using rademacher series on dual bch codes. the fast johnson-lindenstrauss transform (fjlt) was recently discovered by ailon and chazelle as a novel technique for performing fast dimension reduction with small distortion from &ell;d2 to &ell;d2 in time o(max{d log d,k3}). for k in [&omega;(log d), o(d1/2)] this beats time o(dk) achieved by naive multiplication by random dense matrices, an approach followed by several authors as a variant of the seminal result by johnson and lindenstrauss (jl) from the mid 80's. in this work we show how to significantly improve the running time to o(d log k) for k = o(d1/2&minus;&delta;), for any arbitrary small fixed &delta;. this beats the better of fjlt and jl. our analysis uses a powerful measure concentration bound due to talagrand applied to rademacher series in banach spaces (sums of vectors in banach spaces with random signs). the set of vectors used is a real embedding of dual bch code vectors over gf(2). we also discuss the number of random bits used and reduction to &ell;1 space. the connection between geometry and discrete coding theory discussed here is interesting in its own right and may be useful in other algorithmic applications as well.
delaunay graphs of point sets in the plane with respect to axis-parallel rectangles. given a point set p in the plane, the delaunay graph with respect to axis-parallel rectangles is a graph defined on the vertex set p, whose two points p,q &isin; p are connected by an edge if and only if there is a rectangle parallel to the coordinate axes that contains p and q, but no other elements of p. the following question of even et al. [elrs03] was motivated by a frequency assignment problem in cellular telephone networks. does there exist a constant c > 0 such that the delaunay graph of any set of n points in general position in the plane contains an independent set of size at least cn? we answer this question in the negative, by proving that the largest independent set in a randomly and uniformly selected point set in the unit square is o(n log2 log n/log n), with probability tending to 1. we also show that our bound is not far from optimal, as the delaunay graph of a uniform random set of n points almost surely has an independent set of size at least cn/ log n. we give two further applications of our methods. 1. we construct 2-dimensional n-element partially ordered sets such that the size of the largest independent sets of vertices in their hasse diagrams is o(n). this answers a question of matou&scaron;ek and p&rcaron;&iacute;v&ecaron;tiv&yacute; [map06] and improves a result of k&rcaron;&iacute;&zcaron; and ne&scaron;et&rcaron;il [krn91]. 2. for any positive integers c and d, we prove the existence of a planar point set with the property that no matter how we color its elements by c colors, we find an axis-parallel rectangle containing at least d points, all of which have the same color. this solves an old problem from [brmp05].
the ugc hardness threshold of the &ell; grothendieck problem. for p &ge; 2 we consider the problem of, given an n &times; n matrix a = (aij) whose diagonal entries vanish, approximating in polynomial time the number {display equation} (where optimization is taken over real numbers). when p = 2 this is simply the problem of computing the maximum eigenvalue of a, while for p = &infin; (actually it suffices to take p &ap; log n) it is the grothendieck problem on the complete graph, which was shown to have a o(log n) approximation algorithm in [27, 26, 15], and was used in [15] to design the best known algorithm for the problem of computing the maximum correlation in correlation clustering. thus the problem of approximating optp (a) interpolates between the spectral (p = 2) case and the correlation clustering (p = &infin;) case. from a physics point of view this problem corresponds to computing the ground states of spin glasses in a hard-wall potential well. we design a polynomial time algorithm which, given p &ge; 2 and an n x n matrix a = (aij) with zeros on the diagonal, computes optp (a) up to a factor p/e + 30 log p. on the other hand, assuming the unique games conjecture (ugc) we show that it is np-hard to approximate (1.2) up to a factor smaller than p/e + 1/4. hence as p &rarr; &infin; the ugc-hardness threshold for computing optp (a) is exactly p/e (1 + o(1)).
rapid mixing of gibbs sampling on graphs that are sparse on average. gibbs sampling also known as glauber dynamics is a popular technique for sampling high dimensional distributions defined on graphs. of special interest is the behavior of gibbs sampling on the erd&ouml;s-r&eacute;nyi random graph g(n, d/n), where each edge is chosen independently with probability d/n and d is fixed. while the average degree in g(n, d/n) is d(1 - o(1)), it contains many nodes of degree of order log n/ log log n. the existence of nodes of almost logarithmic degrees implies that for many natural distributions defined on g(n, p) such as uniform coloring (with a constant number of colors) or the ising model at any fixed inverse temperature &beta;, the mixing time of gibbs sampling is at least n1+&omega;(1/log log n). recall that the ising model with inverse temperature &beta; defined on a graph g = (v, e) is the distribution over {&plusmn;}v given by p(&sigma;) = 1/z exp (&beta; &sigma;(v,u)&isin;e &sigma;(v)&sigma;(u)). high degree nodes pose a technical challenge in proving polynomial time mixing of the dynamics for many models including the ising model and coloring. almost all known sufficient conditions in terms of &beta; or number of colors needed for rapid mixing of gibbs samplers are stated in terms of the maximum degree of the underlying graph. in this work we show that for every d < &infin; and the ising model defined on g(n, d/n), there exists a &beta;d > 0, such that for all &beta; < &beta;d with probability going to 1 as n &rarr; &infin;, the mixing time of the dynamics on g(n, d/n) is polynomial in n. our results are the first polynomial time mixing results proven for a natural model on g(n, d/n) for d > 1 where the parameters of the model do not depend on n. they also provide a rare example where one can prove a polynomial time mixing of gibbs sampler in a situation where the actual mixing time is slower than n polylog(n). our proof exploits in novel ways the local treelike structure of erd&odblac;s-r&eacute;nyi random graphs, comparison and block dynamics arguments and a recent result of weitz. our results extend to much more general families of graphs which are sparse in some average sense and to much more general interactions. in particular, they apply to any graph for which every vertex v of the graph has a neighborhood n (v) of radius o (log n) in which the induced subgraph is a tree union at most o(log n) edges and where for each simple path in n(v) the sum of the vertex degrees along the path is o(log n). moreover, our result apply also in the case of arbitrary external fields and provide the first fpras for sampling the ising distribution in this case. we finally present a non markov chain algorithm for sampling the distribution which is effective for a wider range of parameters. in particular, for g(n, d/n) it applies for all external fields and &beta; < &beta;d, where d tanh(&beta;d) = 1 is the critical point for decay of correlation for the ising model on g(n, d/n).
an algorithm for improving graph partitions. we present an algorithm called improve that improves a proposed partition of a graph, taking as input a subset of vertices and returning a new subset of vertices with a smaller quotient cut score. the most powerful previously known method for improving quotient cuts, which is based on parametric flow, returns a partition whose quotient cut score is at least as small as any set contained within the proposed set. for our algorithm, we can prove a stronger guarantee: the quotient score of the set returned is nearly as small as any set in the graph with which the proposed set has a larger-than-expected intersection. the algorithm finds such a set by solving a sequence of polynomially many s -- t minimum cut problems, a sequence that cannot be cast as a single parametric flow problem. we demonstrate empirically that applying improve to the output of various graph partitioning algorithms greatly improves the quality of cuts produced without significantly impacting the running time.
exact and efficient 2d-arrangements of arbitrary algebraic curves. we show how to compute the planar arrangement induced by segments of arbitrary algebraic curves with the bentley-ottmann sweep-line algorithm. the necessary geometric primitives reduce to cylindrical algebraic decompositions of the plane for one or two curves. we compute them by a new and efficient method that combines adaptive-precision root finding (the bitstream descartes method of eigenwillig et al., 2005) with a small number of symbolic computations, and that delivers the exact result in all cases. thus we obtain an algorithm which produces the mathematically true arrangement, undistorted by rounding error, for any set of input segments. our algorithm is implemented in the exacus library alcix. we report on experiments; they indicate the efficiency of our approach.
arc-disjoint in-trees in directed graphs. given a directed graph d = (v, a) and a set of specified vertices s = {s1,&hellip;,sd} &sube; v with |s| = d and a function f: s &rarr; n where n denotes the set of natural numbers, we present a necessary and sufficient condition that there exist &sigma;si &epsilon; arc-disjoint in-trees denoted by ti,1,ti,2,&hellip;,tif (si) for every i = 1,&hellip;,d such that ti,1,&hellip;, ti,f(si) are rooted at si and each ti,j spans vertices from which si is reachable. this generalizes the result of edmonds [2], i.e., the necessary and sufficient condition that for a directed graph d = (v,a) with a specified vertex s &epsilon; v, there are k arc-disjoint in-trees rooted at s each of which spans v. furthermore, we extend another characterization of packing in-trees of edmonds [1] to the one in our case.
on the approximability of influence in social networks. in this paper, we study the spread of influence through a social network, in a model initially studied by kempe, kleinberg and tardos [14, 15]: we are given a graph modeling a social network, where each node v has a (fixed) threshold tv, such that the node will adopt a new product if tv of its neighbors adopt it. our goal is to find a small set s of nodes such that targeting the product to s would lead to adoption of the product by a large number of nodes in the graph. we show strong inapproximability results for several variants of this problem. our main result says that the problem of minimizing the size of s, while ensuring that targeting s would influence the whole network into adopting the product, is hard to approximate within a polylogarithmic factor. this implies similar results if only a fixed fraction of the network is ensured to adopt the product. further, the hardness of approximation result continues to hold when all nodes have majority thresholds, or have constant degree and threshold two. the latter answers a complexity question proposed in [10, 29]. we also give some positive results for more restricted cases, such as when the underlying graph is a tree.
designing networks with good equilibria. in a network with selfish users, designing and deploying a protocol determines the rules of the game by which end users interact with each other and with the network. we study the problem of designing a protocol to optimize the equilibrium behavior of the induced network game. we consider network cost-sharing games, where the set of nash equilibria depends fundamentally on the choice of an edge cost-sharing protocol. previous research focused on the shapley protocol, in which the cost of each edge is shared equally among its users. we systematically study the design of optimal cost-sharing protocols for undirected and directed graphs, single-sink and multicommodity networks, different classes of cost-sharing methods, and different measures of the inefficiency of equilibria. one of our main technical tools is a complete characterization of the uniform cost-sharing protocols---protocols that are designed without foreknowledge of or assumptions on the network in which they will be deployed. we use this characterization result to identify the optimal uniform protocol in several scenarios: for example, the shapley protocol is optimal in directed graphs, while the optimal protocol in undirected graphs, a simple priority scheme, has exponentially smaller worst-case price of anarchy than the shapley protocol. we also provide several matching upper and lower bounds on the best-possible performance of non-uniform cost-sharing protocols.
holographic algorithms with unsymmetric signatures. holographic algorithms were introduced by valiant as a new methodology to derive polynomial time algorithms. here information and computation are represented by exponential sums using the so-called signatures. these signatures express superpositions of perfect matchings, and are used to achieve exponential sized cancellations, and thereby exponential speedups. most holographic algorithms so far used symmetric signatures. in this paper we use unsymmetric signatures to give some new holographic algorithms. we also prove a characterization theorem for a class of realizable un-symmetric signatures, each of which may be used to design new holographic algorithms.
improved distance sensitivity oracles via random sampling. we present improved oracles for the distance sensitivity problem. the goal is to preprocess a graph g = (v,e) with non-negative edge weights to answer queries of the form: what is the length of the shortest path from x to y that does not go through some failed vertex or edge f. there are two state of the art algorithms for this problem. the first produces an oracle of size &otilde;(n2) that has an o(1) query time, and an &otilde;(mn2) construction time. the second oracle has size o(n2.5), but the construction time is only &otilde;(mn1.5). we present two new oracles that substantially improve upon both of these results. both oracles are constructed with randomized, monte carlo algorithms. for directed graphs with non-negative edge weights, we present an oracle of size &otilde;(n2), which has an o(1) query time, and an &otilde;(n2&radic;m) construction time. for unweighted graphs, we achieve a more general construction time of &otilde;(&radic;n3 &middot; apsp + mn), where apsp is the time it takes to compute all pairs shortest paths in an aribtrary subgraph of g.
algorithms for distributed functional monitoring. we study what we call functional monitoring problems. we have k players each tracking their inputs, say player i tracking a multiset ai(t) up until time t, and communicating with a central coordinator. the coordinator's task is to monitor a given function f computed over the union of the inputs &cup;iai(t), continuously at all times t. the goal is to minimize the number of bits communicated between the players and the coordinator. a simple example is when f is the sum, and the coordinator is required to alert when the sum of a distributed set of values exceeds a given threshold &tau;. of interest is the approximate version where the coordinator outputs 1 if f &ge; &tau; and 0 if f &le; (1 - &epsilon;)&tau;. this defines the (k, f, &tau;, &epsilon;) distributed, functional monitoring problem. functional monitoring problems are fundamental in distributed systems, in particular sensor networks, where we must minimize communication; they also connect to problems in communication complexity, communication theory, and signal processing. yet few formal bounds are known for functional monitoring. we give upper and lower bounds for the (k, f, &tau;, &epsilon;) problem for some of the basic f's. in particular, we study frequency moments (f0, f1, f2). for f0 and f1, we obtain continuously monitoring algorithms with costs almost the same as their one-shot computation algorithms. however, for f2 the monitoring problem seems much harder. we give a carefully constructed multi-round algorithm that uses "sketch summaries" at multiple levels of detail and solves the (k, f2, &tau;, &epsilon;) problem with communication &otilde;(k2/&epsilon;+ (&radic;k/&epsilon;)3). since frequency moment estimation is central to other problems, our results have immediate applications to histograms, wavelet computations, and others. our algorithmic techniques are likely to be useful for other functional monitoring problems as well.
distributed broadcast in unknown radio networks. we consider the problem of broadcasting in an unknown radio network modeled as a directed graph g = (v, e), where |v| = n. in unknown networks, every node knows only its own label, while it is unaware of any other parameter of the network, included its neighborhood and even any upper bound on the number of nodes. we show an o(n log n log log n) upper bound on the time complexity of deterministic broadcasting improving upon the time complexity of the currently best known algorithms [6, 12].
concatenated codes can achieve list-decoding capacity. we prove that binary linear concatenated codes with an outer algebraic code (specifically, a folded reed-solomon code) and independently and randomly chosen linear inner codes achieve the list-decoding capacity with high probability. in particular, for any 0 < &rho; < 1/2 and &epsilon; > 0, there exist concatenated codes of rate at least 1 -- h(&rho;) -- &epsilon; that are (combinatorially) list-decodable up to a fraction &rho; of errors. (the best possible rate, aka list-decoding capacity, for such codes is 1 -- h(&rho;), and is achieved by random codes.) a similar result, with better list size guarantees, holds when the outer code is also randomly chosen. our methods and results extend to the case when the alphabet size is any fixed prime power q &ge; 2. our result shows that despite the structural restriction imposed by code concatenation, the family of concatenated codes is rich enough to include capacity achieving list-decodable codes. this provides some encouraging news for tackling the problem of constructing explicit binary list-decodable codes with optimal rate, since code concatenation has been the preeminent method for constructing good codes over small alphabets.
sampling stable marriages: why spouse-swapping won't work. we study the behavior of random walks along the edges of the stable marriage lattice for various restricted families of allowable preference sets. in the "k-attribute model," each man is valued in each of k attributes, and each woman's ranking of the men is determined by a linear function, representing her relative ranking of those attributes; men's rankings of the women are determined similarly. we show that sampling with a random walk on the marriage lattice can take exponential time, even when k = 2. moreover, we show that the marriage lattices arising in the k-attribute model are more restrictive than in the general setting; previously such a restriction had only been shown for the sets of preference lists. the second model we consider is the "k-range model," where each person lies in a position in [i, i + k - 1], for some i, on every preference list of the opposite sex. when k = 1 there is a unique stable marriage. when k = 2 there already can be an exponential number of stable marriages, but we show that a random walk on the stable marriage lattice always converges quickly to equilibrium. however, when k &ge; 5, there are preference sets such that the random walk on the lattice will require exponential time to converge. lastly, we show that in the extreme case where each gender's rankings of the other are restricted to one of just a constant k possible preference lists, there are still instances for which the markov chain mixes exponentially slowly, even when k = 4. this oversimplification of the general model helps elucidate why markov chains based on spouse-swapping are not good approaches to sampling, even in specialized scenarios.
trace reconstruction with constant deletion probability and related results. we provide several new results for the trace reconstruction problem. in this setting, a binary string yields a collection of traces, where each trace is independently obtained by independently deleting each bit with a fixed probability &delta;. each trace therefore consists of a random subsequence of the original sequence. given the traces, we wish to reconstruct the original string with high probability. the questions are how many traces are necessary for reconstruction, and how efficiently can the reconstruction be performed. our primary result is that for some universal constant &gamma; and uniformly chosen strings of length n, for any &delta; < &gamma; reconstruction is possible with poly(n) traces in poly(n) time with high probability. we also obtain algorithms that require a number of traces exponential in &otilde; (&radic;n) for any &delta; < 1 even for worst case strings, and we derive lower bound results for simpler classes of algorithms based on summary statistics from the traces.
geodesic delaunay triangulation and witness complex in the plane. we introduce a novel feature size for bounded planar domains endowed with an intrinsic metric. given a point x in such a domain x, the homotopy feature size of x at x, or hfs(x) for short, measures half the length of the shortest loop through x that is not null-homotopic in x. the resort to an intrinsic metric makes hfs(x) rather insensitive to the local geometry of x, in contrast with its predecessors (local feature size, weak feature size, homology feature size). this leads to a reduced number of samples that still capture the topology of x. under reasonable sampling conditions involving hfs, we show that the geodesic delaunay traingulation dx (l) of a finite sampling l of x is homotopy equivalent to x. moreover, dx (l) is sandwiched between the geodesic witness complex cwx (l) and a relaxed version cwx, v (l), defined by a parameter v. taking advantage of this fact, we prove that the homology of dx (l) (and hence of x) can be retrieved by computing the persistent homology between cwx (l) and cwx, v (l). we propose algorithms for estimating hfs, selecting a landmark set of sufficient density, building its geodesic delaunay triangulation, and computing the homology of x using cwx (l). we also present some simulation results in the context of sensor networks that corroborate our theoretical statements.
dimension augmentation and combinatorial criteria for efficient error-resistant dna self-assembly. dna self-assembly has emerged as a rich and promising primitive for nano-technology. experimental and analytical evidence indicates that such systems are prone to errors, and accordingly, several error-correction mechanisms have been proposed for the tile model of self-assembly. these error-correction mechanisms suffer either from high resolution loss or a large increase in the number of tile-types. in this paper, we propose dimension augmented proof-reading, a technique that uses the third dimension to do error-correction in two dimensional self-assembling systems. this involves no resolution loss in the two dimensions of interest, results in a smaller increase in the number of tile-types than previous techniques, and appears to have the same error-correction properties. error-correcting systems need to be analyzed in the kinetic tile assembly model; such analysis involves complicated markov chains and is cumbersome. in this paper, we also present a set of completely combinatorial criteria that can be used to prove properties of error-correcting self-assembling systems. we illustrate these criteria by applying them to two known proof-reading systems, one of which was not previously known to work. we then use these criteria to prove the correctness of dimension augmented proof-reading applied to a self-assembling system that computes the parity of a string.
robust cost colorings. we consider graph coloring problems where the cost of a coloring is the sum of the costs of the colors, and the cost of a color is a monotone concave function of the total weight of the class. this models resource allocation problems where the cost of a resource depends on the use of the resource. the specific case of interval graphs is of special interest as multi-criteria interval scheduling. we give an algorithm for all perfect graphs that yields a robust coloring: a particular solution that simultaneously approximates all concave functions. for graphs with uniform weights, we show how to modify the solution to approximate any monotone cost function. we complement these results with a number of hardness results and some exact algorithms on restricted classes of graphs.
the hiring problem and lake wobegon strategies. we introduce the hiring problem, in which a growing company continuously interviews and decides whether to hire applicants. this problem is similar in spirit but quite different from the well-studied secretary problem. like the secretary problem, it captures fundamental aspects of decision making under uncertainty and has many possible applications. we analyze natural strategies of hiring above the current average, considering both the mean and the median averages; we call these lake wobegon strategies. like the hiring problem itself, our strategies are intuitive, simple to describe, and amenable to mathematically and economically significant modifications. we demonstrate several intriguing behaviors of the two strategies. specifically, we show dramatic differences between hiring above the mean and above the median. we also show that both strategies are intrinsically connected to the lognormal distribution, leading to only very weak concentration results, and the marked importance of the first few hires on the overall outcome.
online budgeted matching in random input models with applications to adwords. we study an online assignment problem, motivated by adwords allocation, in which queries are to be assigned to bidders with budget constraints. we analyze the performance of the greedy algorithm (which assigns each query to the highest bidder) in a randomized input model with queries arriving in a random permutation. our main result is a tight analysis of greedy in this model showing that it has a competitive ratio of 1 - 1/e for maximizing the value of the assignment. we also consider the more standard i.i.d. model of input, and show that our analysis holds there as well. this is to be contrasted with the worst case analysis of [msvv05] which shows that greedy has a ratio of 1/2, and that the optimal algorithm presented there has a ratio of 1 - 1/e. the analysis of greedy is important in the adwords setting because it is the natural allocation algorithm for an auction-style process. from a theoretical perspective, our result simplifies and generalizes the classic algorithm of karp, vazirani and vazirani for online bipartite matching. our results include a new proof to show that the ranking alforithm of [kvv90] has a ratio of 1 - 1/e in the worst case. it has been recently discovered [kv07] (independent of our results) that one of the crucial lemmas in [kvv90], related to a certain reduction, is incorrect. our proof is direct, in that it does not go via such a reduction, which also enables us to generalize the analysis to our online assignment problem.
spread: an adaptive scheme for redundant and fair storage in dynamic heterogeneous storage systems. in this paper we study the problem of designing an adaptive hash table for redundant data storage in a system of storage devices with arbitrary capacities. ideally, such a hash table should make sure that (a) a storage device with x% of the available capacity should get x% of the data, (b) the copies of each data item are distributed among the storage devices so that no two copies are stored at the same device, and (c) only a near-minimum amount of data replacements is necessary to preserve (a) and (b) under any change in the system. hash tables satisfying (a) and (c) are already known, and it is not difficult to construct hash tables satisfying (a) and (b). however, no hash table is known so far that can satisfy all three properties as long as this is in principle possible. we present a strategy called spread that solves this problem for the first time. as long as (a) and (b) can in principle be satisfied, spread preserves (a) for every storage device within a (1 &plusmn; &epsilon;) factor, with high probability, where &epsilon; > 0 can be made arbitrarily small, guarantees (b) for every data item, and only needs a constant factor more data replacements than minimum possible in order to preserve (a) and (b).
approximating geometric coverage problems. we present the first study on the approximability of geometric versions of the unique coverage problem and the minimum membership set cover problem. in the former problem, one is given a family of sets of elements from some universe and aims to select sets that maximize the number of elements contained in precisely one selected set. unique coverage has important applications in wireless networks and it is thus natural to consider it in a geometric setting. we use the well-known (unit) disk model for wireless networks and show that unique coverage remains np-hard in this case and present a polynomial-time 1/18-approximation algorithm. this algorithm is extended to the budgeted low-coverage problem, where covering can element multiple times yields less profit and we have a fixed budget to 'buy' sets. we give an asymptotic fptas in case the disks have arbitrary size, but bounded ply. for the case that the geometric objects are arbitrary fat objects, we show that these problems are as hard to approximate as in the general case. in the minimum membership set cover problem, the goal is to cover all elements while minimizing the maximum number of sets in which any element is contained. for unit squares and unit disks, we show that the problem remains np-hard and does not admit a polynomial-time approximation algorithm with ratio smaller than 2 unless p=np. for unit squares, we give a 5-approximation algorithm for instances where the optimum objective value is bounded by a constant.
real-time indexing over fixed finite alphabets. the quest for a real-time indexing algorithm is ove three decades old. to date there is no convincing understandable solution to this problem. this paper provides a real-time indexing algorithm over a constant sized alphabet. assuming the text is arriving at a constant rate, the algorithm spends o(1) time on every text symbol. whenever a length m pattern is given, the algorithm decides in time o(m) whether there is an occurrence of the pattern in the text thus far.
on the value of coordination in network design. we study network design games where n self-interested agents have to form a network by purchasing links from a given set of edges. we consider shapley cost sharing mechanisms that split the cost of an edge in a fair manner among the agents using the edge. it is well known that the price of anarchy of these games is as high as n. therefore, recent research has focused on evaluating the price of stability, i.e. the cost of the best nash equilibrium relative to the social optimum. in this paper we investigate to which extent coordination among agents can improve the quality of solutions. we resort to the concept of strong nash equilibria, which were introduced by aumann and are resilient to deviations by coalitions of agents. we analyze the price of anarchy of strong nash equilibria and develop lower and upper bounds for unweighted and weighted games in both directed and undirected graphs. these bounds are tight or nearly tight for many scenarios. it shows that using coordination, the price of anarchy drops from linear to logarithmic bounds. we complement these results by also proving the first super-constant lower bound on the price of stability of standard equilibria (without coordination) in undirected graphs. more specifically, we show a lower bound of &omega;(log w/ log log w) for weighted games, where w is the total weight of all the agents. this almost matches the known upper bound of o(log w). our results imply that, for most settings, the worst-case performance ratios of strong coordinated equilibria are essentially always as good as the performance ratios of the best equilibria achievable without coordination. these settings include unweighted games in directed graphs as well as weighted games in both directed and undirected graphs.
noisy sorting without resampling. in this paper we study noisy sorting without re-sampling. in this problem there is an unknown order {display equation} where &pi; is a permutation on n elements. the input is the status of (n2) queries of the form q(ai, aj), for i < j, where q(ai, aj) = + (-) with probability 1/2 + &gamma; if &pi;(i) > &pi;(j)(&pi;(i) < &pi;(j)) for all pairs i &ne; j, where &gamma; > 0 is a constant. it is assumed that the errors are independent. given the status of the queries the goal is to find the maximum likelihood order. in other words, the goal is find a permutation &sigma; that minimizes the number of pairs &sigma;(i) > &sigma;(j) where q(&sigma;(i), &sigma;(j)) = -. the problem so defined is the feedback arc set problem on distributions of inputs, each of which is a tournament obtained as a noisy perturbation of a linear order. note that when &gamma; < 1/2 and n is large, it is impossible to recover the original order &pi;. it is known that the weighted feedback arc set problem on tournaments is np-hard in general. here we present an algorithm of running time no(&gamma;-4)) and sampling complexity o&gamma; (n log n) that with high probability solves the noisy sorting without re-sampling problem. we also show that if a&sigma;(1), a&sigma;(2), &hellip;, a&sigma;(n) is an optimal solution of the problem then it is "close" to the original order. more formally, with high probability it holds that {display equation}. our results are of interest in applications to ranking, such as ranking in sports, or ranking of search items based on comparisons by experts.
generating random graphs with large girth. we present a simple and efficient algorithm for randomly generating simple graphs without small cycles. these graphs can be used to design high performance low-density parity-check (ldpc) codes. for any constant k, &alpha; &le; 1/2k(k + 3) and m = o(n1+&alpha;), our algorithm generates an asymptotically uniform random graph with n vertices, m edges, and girth larger than k in polynomial time. to the best of our knowledge this is the first polynomial algorithm for the problem. our algorithm generates a graph by sequentially adding m edges to an empty graph with n vertices. recently, this type of sequential process has been very successful for efficiently counting and generating random graphs [35, 18, 11, 7, 5, 6].
fully dynamic algorithm for graph spanners with poly-logarithmic update time. spanner of an undirected graph g = (v, e) is a sub graph which is sparse and yet preserves all-pairs distances approximately. more precisely, a spanner with stretch t &isin; in is a subgraph (v, es), es &sube; e such that the distance between any two vertices in the subgraph is at most t times their distance in g. we present two fully dynamic algorithms for maintaining a sparse t-spanner of an unweighted graph. our first algorithm achieves expected o(7 t/4) time per update independent of the size of the graph. this algorithm is particularly of interest for maintaining small stretch spanners. our second algorithm achieves expected o(polylog |v|) time per update irrespective of the stretch.
quasirandom rumor spreading. we propose and analyse a quasirandom analogue to the classical push model for disseminating information in networks ("randomized rumor spreading"). in the classical model, in each round each informed node chooses a neighbor at random and informs it. results of frieze and grimmett (discrete appl. math. 1985) show that this simple protocol succeeds in spreading a rumor from one node of a complete graph to all others within o(log n) rounds. for the network being a hypercube or a random graph g(n, p) with p &ge; (1 +&epsilon;)(log n)/n, also o(log n) rounds suffice (feige, peleg. raghavan, and upfal, random struct. algorithms 1990). in the quasirandom model, we assume that each node has a (cyclic) list of its neighbors. once informed, it starts at a random position of the list, but from then on informs its neighbors in the order of the list. surprisingly, irrespective of the orders of the lists, the above mentioned bounds still hold. in addition, we also show a o(log n) bound for sparsely connected random graphs g(n, p) with p = (log n + f(n))/n, where f(n) &rarr; &infin; and f(n) = o(log log n). here, the classical model needs &theta;(log2(n)) rounds. hence the quasirandom model achieves similar or better broadcasting times with a greatly reduced use of random bits.
splay trees, davenport-schinzel sequences, and the deque conjecture. we introduce a new technique to bound the asymptotic performance of splay trees. the basic idea is to transcribe, in an indirect fashion, the rotations performed by the splay tree as a davenport-schinzel sequence, none of whose subsequences are isomorphic to a fixed forbidden subsequence. we direct this technique towards tarjan's deque conjecture and prove that n deque operations take only o(n&alpha;*(n)) time, where &alpha;* (n) is the minimum number of applications of the inverse-ackermann function mapping n to a constant. we are optimistic that this approach could be directed towards other open conjectures on splay trees such as the traversal and split conjectures.
fast and reliable reconstruction of phylogenetic trees with very short edges. phylogenetic reconstruction is the problem of reconstructing an evolutionary tree from sequences corresponding to leaves of that tree. a central goal in phylogenetic reconstruction is to be able to reconstruct the tree as accurately as possible from as short as possible input sequences. the sequence length required for correct topological reconstruction depends on certain properties of the tree, such as its depth and minimal edge-weight. fast converging reconstruction algorithms are considered state-of the-art in this sense, as they require asymptotically minimal sequence length in order to guarantee (with high probability) correct topological reconstruction of the entire tree. however, when the original phylogenetic tree contains very short edges, this minimal sequence-length is still too long for practical purposes. short edges are not only very hard to reconstruct; their presence may also prevent the correct reconstruction of long edges. in this paper we present a fast converging reconstruction algorithm which returns a partially resolved topology containing all edges of the original tree whose weight exceeds some (non-trivial) lower bound, which is determined by the input sequence length, as well as some properties of the tree, such as its depth. it does not depend, however, on the minimal edge-weight. this lower bound provides a partial reconstruction guarantee which is strictly stronger than the guarantees given by other fast converging algorithms. our algorithm also has optimal complexity (linear space and quadratic-time) which, together with its partial reconstruction guarantee, makes it appealing for practical use.
algorithms for the coalitional manipulation problem. we investigate the problem of coalitional manipulation in elections, which is known to be hard in a variety of voting rules. we put forward efficient algorithms for the problem in scoring rules, maximum and plurality with runoff, and analyze their windows of error. specifically, given an instance on which an algorithm fails, we bound the additional power the manipulators need in order to succeed. we finally discuss the implications of our results with respect to the popular approach of employing computational hardness to preclude manipulation.
approximating general metric distances between a pattern and a text. let t = t0 &hellip; tn-1 be a text and p = p0 &hellip; pm-1 a pattern taken from some finite alphabet set &sigma;, and let d be a metric on &sigma;. we consider the problem of calculating the sum of distances between the symbols of p and the symbols of substrings of t of length m for all possible offsets. we present an &epsilon;-approximation algorithm for this problem which runs in time o(1/&epsilon;2n &middot; polylog(n, |&sigma;|)). this algorithm is based on a low distortion embedding of metric spaces into normed spaces (especially, into &ell;&infin;), which is done as a preprocessing stage. the algorithm is also based on a technique of sampling.
provably good multicore cache performance for divide-and-conquer algorithms. this paper presents a multicore-cache model that reflects the reality that multicore processors have both per-processor private (l1) caches and a large shared (l2) cache on chip. we consider a broad class of parallel divide-and-conquer algorithms and present a new on-line scheduler, controlled-pdf, that is competitive with the standard sequential scheduler in the following sense. given any dynamically unfolding computation dag from this class of algorithms, the cache complexity on the multicore-cache model under our new scheduler is within a constant factor of the sequential cache complexity for both l1 and l2, while the time complexity is within a constant factor of the sequential time complexity divided by the number of processors p. these are the first such asymptotically-optimal results for any multicore model. finally, we show that a separator-based algorithm for sparse-matrix-dense-vector-multiply achieves provably good cache performance in the multicore-cache model, as well as in the well-studied sequential cache-oblivious model.
better bounds for online load balancing on unrelated machines. we study the problem of scheduling permanent jobs on unrelated machines when the objective is to minimize the lp norm of the machine loads. the problem is known as load balancing under the lp norm. we present an improved upper bound for the greedy algorithm through simple analysis; this bound is also shown to be best possible within the class of deterministic online algorithms for the problem. we also address the question whether randomization helps online load balancing under lp norms on unrelated machines; this is a challenging question which is open for more than a decade even for the l2 norm. we provide a positive answer to this question by presenting the first randomized online algorithms which outperform deterministic ones under any (integral) lp norm for p = 2,&hellip;,137. our algorithms essentially compute in an online manner a fractional solution to the problem and use the fractional values to make random choices. the local optimization criterion used at each step is novel and rather counterintuitive: the values of the fractional variables for each job correspond to flows at an approximate wardrop equilibrium for an appropriately defined non-atomic congestion game. as corollaries of our analysis and by exploiting the relation between the lp norm and the makespan of machine loads, we obtain new competitive algorithms for online makespan minimization, making progress in another longstanding open problem.
approximation algorithms for labeling hierarchical taxonomies. we consider the following taxonomy labeling problem. each node of an n-node tree has to be labeled with the values of k attributes. a partial labeling is given as part of the input. the goal is to complete this labeling, minimizing the maximum variation in labeling along an edge. a special case of this problem (which we call the label extension problem), where every node is either completely labeled or not labeled at all, has been considered previously. we present an o(log2 k)-approximation algorithm based on a natural linear programming relaxation. our results reduce the taxonomy labeling problem to another problem we introduce, called the multicut packing problem (on trees): given k multicommodity flow instances, find a multicut for each instance so as to minimize the maximum number of multicuts that use any single edge. our algorithm yields an o(log2 k)-approximation algorithm for this more general problem. we show that the integrality gap of our relaxation is &omega;(logk), even when applied to the taxonomy labeling problem with 0-1 labels. for the label extension problem, we considerably improve the previous o(log n) approximation guarantee and give the first constant-factor approximation algorithm for this problem. our work relies on relating the label extension problem to questions on lipschitz extensions of functions into banach spaces. in particular, our approximation algorithm builds upon matou&scaron;ek's tree metrics extension theorem. our algorithm also works for other metrics on the label-set, such as edit distance with unit-cost operations, and more generally any shortest path metric induced by an unweighted graph.
incentive compatible regression learning. we initiate the study of incentives in a general machine learning framework. we focus on a game-theoretic regression learning setting where private information is elicited from multiple agents with different, possibly conflicting, views on how to label the points of an input space. this conflict potentially gives rise to untruthfulness on the part of the agents. in the restricted but important case when every agent cares about a single point, and under mild assumptions, we show that agents are motivated to tell the truth. in a more general setting, we study the power and limitations of mechanisms without payments. we finally establish that, in the general setting, the vcg mechanism goes a long way in guaranteeing truthfulness and economic efficiency.
clustering for metric and non-metric distance measures. we study a generalization of the k-median problem with respect to an arbitrary dissimilarity measure d. given a finite set p, our goal is to find a set c of size k such that the sum of errors d(p, c) = &sigma;p&isin;p minc&isin;c{d(p, c)} is minimized. the main result in this paper can be stated as follows: there exists an o(n2k/&epsilon;)o(1)) time (1 + &epsilon;)-approximation algorithm for the k-median problem with respect to d, if the 1-median problem can be approximated within a factor of (1 + &epsilon;) by taking a random sample of constant size and solving the 1-median problem on the sample exactly. using this characterization, we obtain the first linear time (1 + &epsilon;)-approximation algorithms for the k-median problem in an arbitrary metric space with bounded doubling dimension, for the kullback-leibler divergence (relative entropy), for mahalanobis distances, and for some special cases of bregman divergences. moreover, we obtain previously known results for the euclidean k-median problem and the euclidean k-means problem in a simplified manner. our results are based on a new analysis of an algorithm from [20].
strongly polynomial and fully combinatorial algorithms for bisubmodular function minimization. bisubmodular functions are a natural "directed", or "signed", extension of submodular functions with several applications. recently fujishige and iwata showed how to extend the iwata, fleischer, and fujishige (iff) algorithm for submodular function minimization (sfm) to bisubmodular function minimization (bsfm). however, they were able to extend only the weakly polynomial version of iff to bsfm. here we investigate the difficulty that prevented them from also extending the strongly polynomial version of iff to bsfm, and we show a way around the difficulty. this new method gives the first combinatorial strongly polynomial algorithm for bsfm. this further leads to extending iwata's fully combinatorial version of iff to bsfm.
approximate shared-memory counting despite a strong adversary. a new randomized asynchronous shared-memory data structure is given for implementing an approximate counter that can be incremented once by each of n processes in a model that allows up to n&minus;1 crash failures. for any fixed &epsis;, the counter achieves a relative error of &delta; with high probability, at the cost of o(((1/&delta;) log n)o(1/&epsis;)) register operations per increment and o(n4/5+&epsis;((1/&delta;) log n)o(1/&epsis;)) register operations per read. the counter combines randomized sampling for estimating large values with an expander for estimating small values. this is the first counter implementation that is sublinear the number of processes and works despite a strong adversary scheduler that can observe internal states of processes. an application of the improved counter is an improved protocol for solving randomized shared-memory consensus, which reduces the best previously known individual work complexity from o(n log n) to an optimal o(n), resolving one of the last remaining open problems concerning consensus in this model.
two-phase greedy algorithms for some classes of combinatorial linear programs. we present greedy algorithms for some classes of combinatorial packing and cover problems within the general formal framework of hoffman and schwartz' lattice polyhedra. our algorithms compute in a first phase monge solutions for the associated dual cover and packing problems and then proceed to construct greedy solutions for the primal problems in a second phase. we show optimality of the algorithms under certain sub- and supermodular assumptions and monotone constraints. for supermodular lattice polyhedra with submodular constraints, our algorithms offer the farthest reaching generalization of edmonds' polymatroid greedy algorithm currently known.
improved string reconstruction over insertion-deletion channels. consider a binary string x of length n transmitted m times over a memoryless channel that randomly inserts, deletes and flips bits. we consider the problem of reconstructing x from the collection of m binary strings received at the output of the channel. we present an algorithm for this problem and show that, as n tends to infinity, for almost all transmitted strings, the algorithm is guaranteed to reconstruct the transmitted string with probability 1 - o(1), if the channel's flip probability p < 1/2, its insertion and deletion probabilities qi,qd = o(1/log n), and m = &theta;(log n). our algorithm improves on [1] which applies to channels that only delete, and on [2] where qi,qd = o(1/(log n)2). we also show that to reconstruct most strings reliably over any channel with a constant flip probability m = &omega;(log n) transmissions are necessary, and therefore our algorithm is efficient in this sense.
a tight lower bound for parity in noisy communication networks. we show a tight lower bound of &omega;(n log log n) on the number of transmission required to compute the parity of n bits (with constant error) in a network of n randomly placed sensors, communicating using local transmissions, and operating with power near the connectivity threshold. this result settles a question left open by ying, srikant and dullerud (wiopt 06), who showed how the sum of all n bits can be computed using o(n log log n) transmissions. earlier works on lower bounds for communication networks worked with the full broadcast model without using the fact that the communication in real networks is local, determined by the power of the transmitters. in fact, in full broadcast networks parity can be computed using o(n) transmissions. to obtain our lower bound we employ techniques developed by goyal, kindler and saks (focs 05), who showed lower bounds in the full broadcast model by reducing the problem to a model of noisy decision trees. however, in order to capture the limited range of transmissions in real sensor networks, we define and work with a localized version of noisy decision trees. our lower bound is obtained by exploiting special properties of parity computations in such decision trees.
weak &epsilon;-nets and interval chains. we construct weak &epsilon;-nets of almost linear size for certain types of point sets. specifically, for planar point sets in convex position we construct weak 1/r-nets of size o(r&alpha;(r)), where &alpha;(r) denotes the inverse ackermann function. for point sets along the moment curve in ℝd we construct weak 1/r-nets of size r &middot; 2poly(&alpha;(r)), where the degree of the polynomial in the exponent depends (quadratically) on d. our constructions result from a reduction to a new problem, which we call stabbing interval chains with j-tuples. given the range of integers n = [1,n], an interval chain of length k is a sequence of k consecutive, disjoint, nonempty intervals contained in n. a j-tuple &pmacr; is said to stab an interval chain c = i1 &hellip; ik if each pi falls on a different interval of c. the problem is to construct a small-size family z of j-tuples that stabs all k-interval chains in n. let zk(j)(n) denote the minimum size of such a family z. we derive almost-tight upper and lower bounds for zk(j)(n) for every fixed j; our bounds involve functions &alpha;m(n) of the inverse ackermann hierarchy. specifically, we show that for j = 3 we have zk(3)(n) = &theta; for all k &ge; 6. for each j &ge; 4 we construct a pair of functions p'j(m), q'j(m), almost equal asymptotically, such that z(j)p'j(m)(n)=o(n&alpha;m(n)) and z(j)q'j(m)(n)=&omega;(n&alpha;m(n)).
computing large matchings fast. in this paper we present algorithms for computing large matchings in 3-regular graphs, graphs with maximum degree 3, and 3-connected planar graphs. the algorithms give a guarantee on the size of the computed matching and take linear or slightly superlinear time. thus they are faster than the best-known algorithm for computing maximum matchings in general graphs, which runs in o(&radic;nm) time, where n denotes the number of vertices and m the number of edges of the given graph. for the classes of 3-regular graphs and graphs with maximum degree 3 the bounds we achieve are known to be best possible. we also investigate graphs with block trees of bounded degree, where the d-block tree is the adjacency graph of the d-connected components of the given graph. in 3-regular graphs and 3-connected planar graphs with bounded-degree 2- and 4-block trees, respectively, we show how to compute maximum matchings in slightly superlinear time.
parallel monotonicity reconstruction. we investigate the problem of monotonicity reconstruction, as defined in [3], in a parallel setting. we have oracle access to a nonnegative real-valued function f defined on domain [n]d = {1,&hellip;,n}d. we would like to closely approximate f by a monotone function g. this should be done by a procedure (a filter) that given as input a point x &isin; [n]d outputs the value of g(x), and runs in time that is highly sublinear in n. the procedure can (indeed must) be randomized, but we require that all of the randomness be specified in advance by a single short random seed. we construct such an implementation where the the time and space per query is (log n)o(1) and the size of the seed is polynomial in log n and d. furthermore the distance of the approximating function g from f is at most a constant multiple of the minimum distance of any monotone function from f. this implementation allows for parallelization: one can initialize many copies of the filter with the same short random seed, and they can autonomously handle queries, while producing outputs that are consistent with the same approximating function g.
fast approximation of the permanent for very dense problems. approximation of the permanent of a matrix with nonnegative entries is a well studied problem. the most successful approach to date for general matrices uses markov chains to approximately sample from a distribution on weighted permutations, and jerrum, sinclair, and vigoda developed such a method they proved runs in polynomial time in the input. the current bound on the running time of their method is o(n7(log n)4). here we present a very different approach using sequential acceptance/rejection, and show that for a class of dense problems this method has an o(n4 log n) expected running time.
space-efficient dynamic orthogonal point location, segment intersection, and range reporting. we describe an asymptotically optimal data-structure for dynamic point location for horizontal segments. for n line-segments, queries take o(log n) time, updates take o(log n) amortized time and the data structure uses o(n) space. this is the first structure for the problem that is optimal in space and time (modulo the possibility of removing amortization). we also describe dynamic data structures for orthogonal range reporting and orthogonal intersection reporting. in both data structures for n points (segments) updates take o(log n) amortized time, queries take o(log n+k log n/log log n) time, and the structures use o(n) space, where k is the size of the output. the model of computation is the unit cost ram.
dynamic optimality for skip lists and b-trees. sleator and tarjan [39] conjectured that splay trees are dynamically optimal binary search trees (bst). in this context, we study the skip list data structure introduced by pugh [35]. we prove that for a class of skip lists that satisfy a weak balancing property, the working-set bound is a lower bound on the time to access any sequence. furthermore, we develop a deterministic self-adjusting skip list whose running time matches the working-set bound, thereby achieving dynamic optimality in this class. finally, we highlight the implications our bounds for skip lists have on multi-way branching search trees such as b-trees, (a-b)-trees, and other variants as well as their binary tree representations. in particular, we show a self-adjusting b-tree that is dynamically optimal both in internal and external memory.
universality of random graphs. we prove that asymptotically (as n &rarr; &infin;) almost all graphs with n vertices and 10d n2--1/2d log 1/d n edges are universal with respect to the family of all graphs with maximum degree bounded by d. moreover, we provide a polynomial time, deterministic embedding algorithm to find a copy of each bounded degree graph in every graph satisfying some pseudo-random properties. we also prove a counterpart result for random bipartite graphs, where the threshold number of edges is even smaller but the embedding is randomized.
fast algorithms for finding proper strategies in game trees. we show how to find a normal form proper equilibrium in behavior strategies of a given two-player zero-sum extensive form game with imperfect information but perfect recall. our algorithm solves a finite sequence of linear programs and runs in polynomial time. for the case of a perfect information game, we show how to find a normal form proper equilibrium in linear time by a simple backwards induction procedure.
a nearly linear time algorithm for the half integral disjoint paths packing. we consider the following problem, which is called the half integral k disjoint paths packing. input: a graph g, k pair of vertices (s1, t1), (s2, t2),&hellip;, (sk, tk) in g (which are sometimes called terminals). output: paths p1,&hellip;, pk in g such that pi joins si and ti for i = 1,2,&hellip;, k, and in addition, each vertex is on at most two of these paths. we present an o(n log n) time algorithm for this problem for fixed k. this improves a result by kleinberg [21] who gave an o(n3) algorithm for this problem. in fact, we also have algorithms running in o(n(1+&epsilon;)) time for any &epsilon; > 0 for these problems, if k is up to o((log log n)2/5) for general graphs, up to o((log n/(log log n))1/4) for planar graphs, and up to o((log n/g/(log log n/g))1/4) for graphs on the surface, where g is the euler genus. furthermore, if k is fixed, then we have linear time algorithms for the planar case and for the bounded genus case. we also obtain o(n log n) algorithms for several optimization problems related to the bounded unsplittable flow problem when the number of terminal pairs is bounded. these results can all carry over to problems involving edge capacities.
on the bichromatic -set problem. we study a bichromatic version of the well-known k-set problem: given two sets r and b of points of total size n and an integer k, how many subsets of the form (r&cap;h)&cup;(b\ h) can have size exactly k over all halfspaces h? in the dual, the problem is asymptotically equivalent to determining the worst-case combinatorial complexity of the k-level in an arrangement of n halfspaces. disproving an earlier conjecture by linhart (1993), we present the first nontrivial upper bound for all k &lt; n in two dimensions: o(nk1/3 + n5/6--&isin;k2/3+2&isin; + k2) for any fixed &isin; > 0. in three dimensions, we obtain the bound o(nk3/2 +n0.5034k2.4932 + k3). incidentally, this also implies a new upper bound for the original k-set problem in four dimensions: o(n2k3/2+n1.5034k2.4932+nk3), which improves the best previous result for all k &lt; n0.923. extensions to other cases, such as arrangements of disks, are also discussed.
graph algorithms for biological systems analysis. the post-genomic era has witnessed an explosion in the quality, quantity and variety of biological data---sequence, structure, and networks. however, when building computational models on these data, some abstractions recur often. in particular, graph-based computational models are a powerful, flexible and efficient way of modeling many biological systems. graph models are used in systems biology where the goal is to understand relationships among biological entities, and in structural bioinformatics where a graph is used to represent the amino acid (or atom) interaction relationships in a protein or the secondary structure base-pairing relationships in rna. for many of these problems, we can develop algorithms that explore the fact that certain key parameters have complexity dependent on the treewidth of the system, which is typically very small for a variety of biological systems. when treewidth is large, we can still use spectral methods to find biologically sound solutions in an efficient manner.
unconditionally reliable message transmission in directed networks. in the unconditionally reliable message transmission (urmt) problem, two non-faulty players, the sender s and the receiver r are part of a synchronous network modeled as a directed graph. s has a message that he wishes to send to r; the challenge is to design a protocol such that after exchanging messages as per the protocol, the receiver r should correctly obtain s's message with arbitrarily small error probability &delta;, in spite of the influence of a byzantine adversary that may actively corrupt up to t nodes in the network (we denote such a urmt protocol as (t, (1 - &delta;))-reliable). while it is known that (2t + 1) vertex disjoint directed paths from s to r are necessary and sufficient for (t, 1)-reliable urmt (that is with zero error probability), we prove that a strictly weaker condition, which we define and denote as (2t, t)-special-connectivity, together with just (t+1) vertex disjoint directed paths from s to r, is necessary and sufficient for (t, (1' - &delta;))-reliable urmt with arbitrarily small (but non-zero) error probability, &delta;. thus, we demonstrate the power of randomization in the context of reliable message transmission. in fact, for any positive integer k > 0, we show that there always exists a digraph gk such that (k, 1)-reliable urmt is impossible over gk whereas there exists a (2k, (1 - &delta;))-reliable urmt protocol, &delta; > 0 in gk. in a digraph g on which (t, (1 - &delta;))-reliable urmt is possible, an edge is called critical if the deletion of that edge renders (t, (1 - &delta;))-reliable urmt impossible. we give an example of a digraph g on n vertices such that g has &omega;(n2) critical edges. this is quite baffling since no such graph exists for the case of perfect reliable message transmission (or equivalently (t, 1)-reliable urmt) or when the underlying graph is undirected. such is the anomalous behavior of urmt protocols (when "randomness meet directedness") that it makes it extremely hard to design efficient protocols over arbitrary digraphs. however, if urmt is possible between every pair of vertices in the network, then we present efficient protocols for the same.
explicit constructions for compressed sensing of sparse signals. over the recent years, a new approach for obtaining a succinct approximate representation of n-dimensional vectors (or signals) has been discovered. for any signal x, the succinct representation of x is equal to ax, where a is a carefully chosen r x n real matrix, r &lt; n. often, a is chosen at random from some distribution over r x n matrices. the vector ax is often refered to as the measurement vector or a sketch of x. although the dimension of ax is much shorter than of x, it contains plenty of useful information about x.
non-clairvoyant scheduling with precedence constraints. we consider edmonds's model (1999) extended by precedence constraints. in our setting, a scheduler has to schedule non-clairvoyantly jobs consisting in dags of tasks arriving over time, each task going through phases of different degrees of parallelism, unknown to the scheduler. as in the original model without precedence constraints, the scheduler is only informed of the arrival and the completion of each task, at the time of these events, and nothing more. furthermore, it is not aware of the dag structure of each job beforehand neither of the precise characteristics of the phases of the tasks that compose each job. we consider the preemptive strategy equi&cir;equi, that divides the processors evenly among the alive jobs and then divides the processing power alloted to each job evenly among its alive tasks. we show that whatever how complex the precedences are, equi&cir;equi is (2 + &epsilon;)-speed 0(&kappa;/&epsilon;)-competitive for the flowtime metric, where &kappa; is the maximum number of independent tasks in each job. that is to say, the flowtime of the schedule computed by equioequi is at a constant ratio of the optimal flowtime as soon as equi is given slightly more than twice the resources as the optimum it is compared to. interestingly, the extra speed needed to obtain a competitive algorithm, namely (2+&epsilon;), is the same in presence of precedence constraints, as in the original setting without precedences studied by edmonds in 1999. this means that the maximum load that the system can handle without diverging, is the same with or without precedence constraints. furthermore, we propose a simple scheme to analyze a special class of schedulers, namely equi-schedulers, which allows to obtain upper and lower bounds on particular precedences structures, such as independent chains, in-trees, out-trees and serial-parallel dags.
catalan structures and dynamic programming in -minor-free graphs. we give an algorithm that, for a fixed graph h and integer k, decides whether an n-vertex h-minor-free graph g contains a path of length k in 2o(&radic;k). no(1) steps. our approach builds on a combination of demaine-hajiaghayi's bounds on the size of an excluded grid in such graphs with a novel combinatorial result on certain branch decompositions of h-minor-free graphs. this result is used to bound the number of ways vertex disjoint paths can be routed through the separators of such decompositions. the proof is based on several structural theorems from the graph minors series of robertson and seymour. with a slight modification, similar combinatorial and algorithmic results can be derived for many other problems. our approach can be viewed as a general framework for obtaining time 2o(&radic;k). no(1) algorithms on h-minor-free graph classes.
shuffling cards, adding numbers, and symmetric functions. problems of riffle shuffling cards don't seem to have much to do with problems of analyzing "carries" when adding two integers base 10. both subjects seem remote from modern algebraic combinatorics, where things like quasi-symmetric functions are all the rage. in this talk, i will review these three subjects and show that they are intimately related. for shuffling, i will review the "seven shuffles" theorem (with david bayer) and extensions to modern casino shelf-shufflers (work with susan holmes and jason fulman). for carries, i will review the work of knuth and holte on the process of carries when m integers are added base 6. for symmetric functions, i will explain how much of combinatorics has been unified---theories of permutation enumeration, portions, and partially ordered sets are included.
matroid intersection, pointer chasing, and young's seminormal representation of . we consider the number of queries needed to solve the matroid intersection problem, a question raised by welsh (1976). given two matroids of rank r on n elements, it is known that o(nr1.5) independence queries suffice. however, no non-trivial lower bounds are known for this problem. we make the first progress on this question. we describe a family of instances of rank r = n/2 based on a pointer chasing problem, and prove that (log2 3) n-o (n) queries are necessary to solve these instances. this gives a constant factor improvement over the trivial lower bound of n for matroids of this rank. our proof uses methods from communication complexity and group representation theory. we analyze the communication matrix by viewing it as an operator in the group algebra of the symmetric group and explicitly computing its spectrum.
geometric clustering: fixed-parameter tractability and lower bounds with respect to the dimension. we present an algorithm for the 3-center problem in (ℝd, l&infin;), i.e., for finding the smallest side length for 3 cubes that cover a given n-point set in ℝd, that runs in o(n log n) time for any fixed dimension d. this shows that the problem is fixed-parameter tractable when parameterized with d. on the other hand, using tools from parameterized complexity theory, we show that this is unlikely to be the case with the k-center problem in (ℝd, l2), for any k &ge; 2. in particular, we prove that deciding whether a given n-point set in ℝd can be covered by the union of 2 balls of given radius is w[1]-hard with respect to d, and thus not fixed-parameter tractable unless fpt=w[1]. our reduction also shows that even an o(no(d))-time alorithm for the latter does not exist, unless snp &sube; dtime(2o(n)).
(almost) optimal coordination mechanisms for unrelated machine scheduling. we investigate the influence of different algorithmic choices on the approximation ratio in selfish scheduling. our goal is to design local policies that minimize the inefficiency of resulting equilibria. in particular, we design optimal coordination mechanisms for unrelated machine scheduling, and improve the known approximation ratio from &theta;(m) to &theta;(log m), where m is the number of machines. a local policy for each machine orders the set of jobs assigned to it only based on parameters of those jobs. a strongly local policy only uses the processing time of jobs on the the same machine. we prove that the approximation ratio of any set of strongly local ordering policies in equilibria is at least &omega;(m). in particular, it implies that the approximation ratio of a greedy shortest-first algorithm for machine scheduling is at least &omega;(m). this closes the gap between the known lower and upper bounds for this problem, and answers an open question raised by ibarra and kim [16], and davis and jaffe [10]. we then design a local ordering policy with the approximation ratio of &theta;(log m) in equilibria, and prove that this policy is optimal among all local ordering policies. this policy orders the jobs in the non-decreasing order of their inefficiency, i.e, the ratio between the processing time on that machine over the minimum processing time. finally, we show that best responses of players for the inefficiency-based policy may not converge to a pure nash equilibrium, and present a &theta;(log2 m) policy for which we can prove fast convergence of best responses to pure nash equilibria.
a near-linear time algorithm for computing replacement paths in planar directed graphs. let g = (v(g), e(g)) be a weighted directed graph and let p be a shortest path from s to t in g. in the replacement paths problem we are required to compute for every edge e in p, the length of a shortest path from s to t that avoids e. the fastest known algorithm for solving the problem in weighted directed graphs is the trivial one: each edge in p is removed from the graph in its turn and the distance from s to t in the modified graph is computed. the running time of this algorithm is o (mn + n2 log n), where n = |v(g)| and m = |e(g)|. the replacement paths problem is strongly motivated by two different applications. first, the fastest algorithm to compute the k simple shortest paths from s to t in directed graphs [21, 13] repeatedly computes the replacement paths from s to t. its running time is o(kn(m + n log n)). second, the computation of vickrey pricing of edges in distributed networks can be reduced to the replacement paths problem. an open question raised by nisan and ronen [16] asks whether it is possible to compute the vickrey pricing faster than the trivial algorithm described in the previous paragraph. in this paper we present a near-linear time algorithm for computing replacement paths in weighted planar directed graphs. in particular, the algorithm computes the lengths of the replacement paths in o(n log3 n) time. this result immediately improves the running time of the two applications mentioned above by almost a linear factor. our algorithm is obtained by combining several new ideas with a data structure of klein [12] that supports multi-source shortest paths queries in planar directed graphs in logarithmic time. our algorithm can be adapted to address the variant of the problem in which one is interested in the replacement path itself (rather than the length of the path). in that case the algorithm is executed in a preprocessing stage constructing a data structure that supports replacement path queries in time &otilde;(h), where h is the number of hops in the replacement path. in addition, we can handle the variant in which vertices should be avoided instead of edges.
on the connectivity of dynamic random geometric graphs. we provide the first analytical results for the connectivity of dynamic random geometric graphs --- a model of mobile wireless networks in which vertices move in random directions, and an edge exists between two vertices if their euclidean distance is below a given value. we provide precise asymptotic results for the expected length of the connectivity and disconnectivity periods of the network. we believe the formal tools developed in this work could be of use in more concrete settings, in the same manner as the development of connectivity threshold for static random geometric graphs has affected a lot of research done on ad hoc networks. in the process of proving results for the dynamic case we also obtain new asymptotically precise bounds for the probability of the existence of a component of fixed size l, l &ge; 2, for the static case.
a fractional model of the border gateway protocol (bgp). the border gateway protocol (bgp) is the interdomain routing protocol used to exchange routing information between autonomous systems (ases) in the internet today. while intradomain routing protocols such as rip are basically distributed algorithms for solving shortest path problems, the graph theoretic problem that bgp is trying to solve is called the stable paths problem (spp). unfortunately, unlike shortest path problems, it has been shown that instances of spp can fail to have a solution and so bgp can fail to converge. we define a fractional version of spp and show that all such instances of fractional spp have solutions. we also show that while these solutions exist they are not necessarily half-integral.
l(2, 1)-labelling of graphs. an l(2, 1)-labelling of a graph is a function f from the vertex set to the positive integers such that |f(x) - f(y)| &ge; 2 if dist(x, y) = 1 and |f(x) - f(y)| &ge; 1 if dist(x, y) = 2, where dist(x, y) is the distance between the two vertices x and y in the graph g. the span of an l(2, 1)-labelling f is the difference between the largest and the smallest labels used by f plus 1. in 1992, griggs and yeh conjectured that every graph with maximum degree &delta; &ge; 2 has an l(2, 1)-labelling with span at most &delta;2 + 1. by settling this conjecture for &delta; sufficiently large, we prove the existence of a constant c such that the span of any graph of maximum degree &delta; is at most &delta; 2 + c.
succinct approximate convex pareto curves. we study the succinct approximation of convex pareto curves of multiobjective optimization problems. we propose the concept of &epsilon;-convex pareto (&epsilon;-cp) set as the appropriate one for the convex setting, and observe that it can offer arbitrarily more compact representations than &epsilon;-pareto sets in this context. we characterize when an &epsilon;-cp can be constructed in polynomial time in terms of an efficient routine comb for optimizing (exactly or approximately) monotone linear combinations of the objectives. we investigate the problem of computing minimum size &epsilon;-convex pareto sets, both for discrete (combinatorial) and continuous (convex) problems, and present general algorithms using a comb routine. for bi-objective problems, we show that if we have an exact comb optimization routine, then we can compute the minimum &epsilon;-cp for continuous problems (this applies for example to bi-objective linear programming and markov decision processes), and factor 2 approximation to the minimum &epsilon;-cp for discrete problems (this applies for example to bi-objective versions of polynomial-time solvable combinatorial problems such as shortest paths, spanning tree, etc.). if we have an approximate comb routine, then we can compute factor 3 and 6 approximations respectively to the minimum &epsilon;-cp for continuous and discrete bi-objective problems. we consider also the case of three and more objectives and present some upper and lower bounds.
on the hitting times of quantum versus random walks. the hitting time of a classical random walk (markov chain) is the time required to detect the presence of -- or equivalently, to find -- a marked state. the hitting time of a quantum walk is subtler to define; in particular, it is unknown whether the detection and finding problems have the same time complexity. in this paper we define new monte carlo type classical and quantum hitting times, and we prove several relationships among these and the already existing las vegas type definitions. in particular, we show that for some marked state the two types of hitting time are of the same order in both the classical and the quantum case. further, we prove that for any reversible ergodic markov chain p, the quantum hitting time of the quantum analogue of p has the same order as the square root of the classical hitting time of p. we also investigate the (im)possibility of achieving a gap greater than quadratic using an alternative quantum walk. in doing so, we define a notion of reversibility for a broad class of quantum walks and show how to derive from any such quantum walk a classical analogue. for the special case of quantum walks built on reflections, we show that the hitting time of the classical analogue is exactly the square of the quantum walk. finally, we present new quantum algorithms for the detection and finding problems. the complexities of both algorithms are related to the new, potentially smaller, quantum hitting times. the detection algorithm is based on phase estimation and is particularly simple. the finding algorithm combines a similar phase estimation based procedure with ideas of tulsi from his recent theorem [19] for the 2d grid. extending his result, we show that for any state-transitive markov chain with unique marked state, the quantum hitting time is of the same order for both the detection and finding problems.
the unreasonable effectiveness of martingales. 1 three questions. &bull; let g be a d-regular graph on n vertices where 3 &le; d < n. perform bond percolation with p = 1/d-1 and let c1 be the largest open cluster. is e|c1| = o(n2/3)? (this is well known, and sharp, for d = n - 1, the erd&ouml;s-renyi random graph.) &bull; let g be an infinite connected graph with maximal degree d. does simple rw on g always satisfy pt(x, y) &le; c(d)/&radic; t? &bull; simple rw on {0, 1}k, started uniformly, is a stationary, reversible markov chain that for t < k/4, escapes at a positive speed (in the l1 metric) from its starting point. is there a chain with these properties in the l2 metric? and on a tree?
on distributing symmetric streaming computations. a common approach for dealing with large data sets is to stream over the input in one pass, and perform computations using sublinear resources. for truly massive data sets, however, even making a single pass over the data is prohibitive. therefore, streaming computations must be distribued over many machines. in practice, obtaining significant speedups using distributed computations has numerous challenges including synchronization, load balancing, overcoming processor failures, and data distribution. successful systems in practice such as google's mapreduce and apache's hadoop address these problems by only allowing a certain class of highly distributable tasks defined by local computations that can be applied in any order to the input. the fundamental question that arises is: how does the class of computational tasks supported by these systems differ from the class for which streaming solutions exist? we introduce a simple algorithmic model for massive, unordered, distributed (mud) computation, as implemented by these systems. we show that in principle, mud algorithms are equivalent in power to symmetric streaming algorithms. more precisely, we show that any symmetric (order-invariant) function that can be computed by a steraming algorithm can also be computed by a mud algorithym, with comparable space and communication complexity. our simulation uses savitch's theorem and therefore has superpolynomial time complexity. we extend our simulation result to some natural classes of approximate and randomized steraming algorithms. we also give negative results, using communication complexity arguments to prove that extensions to private randomness, promise problems and indeterminate functions are impossible. we also introduce an extension of the mud model to multiple keys and multiple rounds.
loopless generation of multiset permutations using a constant number of variables by prefix shifts. this paper answers the following mathematical question: can multiset permutations be ordered so that each permutation is a prefix shift of the previous permutation? previously, the answer was known for the permutations of any set, and the permutations of any multiset whose corresponding set contains only two elements. this paper also answers the following algorithmic question: can multiset permutations be generated by a loopless algorithm that uses sublinear additional storage? previously, the best loopless algorithm used a linear amount of additional storage. the answers to these questions are both yes.
succinct geometric indexes supporting point location queries. we propose to design data structures called succinct geometric indexes of negligible space (more precisely, o(n) bits) that support geometric queries in optimal time, by taking advantage of the n points in the data set permuted and stored elsewhere as a sequence. our first and main result is a succinct geometric index that can answer point location queries, a fundamental problem in computational geometry, on planar triangulations in o(lg n) time. we also design three variants of this index. the first supports point location using lg n + 2 &radic;lg n + o(lg1/4n) point-line comparisons. the second supports point location in o(lg n) time when the coordinates are integers bounded by u. the last variant can answer point location queries in o(h + 1) expected time, where h is the entropy of the query distribution. these results match the query efficiency of previous point location structures that occupy o(n) words or o(n lg n) bits, while saving drastic amounts of space. we generalize our succinct geometric index to planar subdivisions, and design indexes for other types of queries. finally, we apply our techniques to design the first implicit data structures that support point location in o(lg2 n) time.
on clustering to minimize the sum of radii. given a metric d defined on a set v of points (a metric space), we define the ball b(v, r) centered at u &isin; v and having radius r &ge; 0 to be the set {q &isin; v/d(v, q) &le;r}. in this work, we consider the problem of computing a minimum cost k-cover for a given set p &sube; v of n points, where k > 0 is some given integer which is also part of the input. for k &ge; 0, a k-cover for subset q &sube; p is a set of at most k balls, each centered at a point in p, whose union covers (contains) q. the cost of a set d of balls, denoted cost(d), is the sum of the radii of those balls.
approximating submodular functions everywhere. submodular functions are a key concept in combinatorial optimization. algorithms that involve submodular functions usually assume that they are given by a (value) oracle. many interesting problems involving submodular functions can be solved using only polynomially many queries to the oracle, e.g., exact minimization or approximate maximization. in this paper, we consider the problem of approximating a non-negative, monotone, submodular function f on a ground set of size n everywhere, after only poly(n) oracle queries. our main result is a deterministic algorithm that makes poly(n) oracle queries and derives a function f such that, for every set s, f(s) approximates f(s) within a factor &alpha;(n), where &alpha;(n) = &radic;n+1 for rank functions of matroids and &alpha;(n), = o(&radic;n log n) for general monotone submodular functions. our result is based on approximately finding a maximum volume inscribed ellipsoid in a symmetrized polymatroid, and the analysis involves various properties of submodular functions and polymatroids. our algorithm is tight up to logarithmic factors. indeed, we show that no algorithm can achieve a factor better than &omega;(&radic;n/log n), even for rank functions of a matroid.
parameterized approximation scheme for the multiple knapsack problem. the multiple knapsack problem (mkp) is a well-known generalization of the classical knapsack problem. we are given a set a of n items and set b of m bins (knapsacks) such that each item a &isin; a has a size size(a) and a profit value profit(a), and each bin b &isin; b has a capacity c(b). the goal is to find a subset u &sub; a of maximum total profit such that u can be packed into b without exceeding the capacities. the decision version of mkp is strongly np-complete, since it is a generalization of the classical knapsack and bin packing problem. furthermore, mkp does not admit an fptas even if the number m of bins is two. kellerer gave a ptas for mkp with identical capacities and chekuri and khanna presented a ptas for mkp with general capacities with running time no(log(1/&epsilon;)/&epsilon;8). in this paper we propose an eptas with parameterized running time 2o(log(1/&epsilon;)/&epsilon;5) &middot; poly(n) + o(m) for mkp. this solves also an open question by chekuri and khanna.
the extended -tree algorithm. consider the following problem: given k = 2q random lists of n-bit vectors, l1, ..., lk, each of length m, find x1 &isin; l1, ..., xk &isin; lk such that x1 + ... + xk = 0, where + is the xor operation. this problem has applications in a number of areas, including cryptanalysis, coding theory, finding shortest lattice vectors, and learning theory. the so-called k-tree algorithm, due to wagner, solves this problem in &otilde;(2q+n/(q+1)) expected time provided the length m of the lists is large enough, specifically if m &ge; 2n/(q+1). in many applications, however, it is necessary to work with lists of smaller length, where the above algorithm breaks down. in this paper we generalize the algorithm to work for significantly smaller values of the list length m, all the way down to the threshold value for which a solution exists with reasonable probability. our algorithm exhibits a tradeoff between the value of m and the running time. we also provide the first rigorous bounds on the failure probability of both our algorithm and that of wagner.
improved bounds and new techniques for davenport--schinzel sequences and their generalizations. we present several new results regarding &lambda;s(n), the maximum length of a davenport--schinzel sequence of order s on n distinct symbols. first, we prove that &lambda;s(n) &leq; n &sdot; 2(1/t&excel;)&alpha;(n)t + o(&alpha;(n)t&minus;1) for s &geq; 4 even, and &lambda;s(n) &leq; n &sdot; 2(1/t&excel;)&alpha;(n)t log2 &alpha;(n) + o(&alpha;(n)t) for s&geq; 3 odd, where t &equals; &lfloor;(s&minus;2)/2&rfloor;, and &alpha;(n) denotes the inverse ackermann function. the previous upper bounds, by agarwal et al. &lsqb;1989&rsqb;, had a leading coefficient of 1 instead of 1/t&excel; in the exponent. the bounds for even s are now tight up to lower-order terms in the exponent. these new bounds result from a small improvement on the technique of agarwal et al. more importantly, we also present a new technique for deriving upper bounds for &lambda;s(n). this new technique is very similar to the one we applied to the problem of stabbing interval chains &lsqb;alon et al. 2008&rsqb;. with this new technique we: (1) re-derive the upper bound of &lambda;3(n) &leq; 2n &alpha;(n) + o(n &sqrt;&alpha;(n)) (first shown by klazar &lsqb;1999&rsqb;); (2) re-derive our own new upper bounds for general s and (3) obtain improved upper bounds for the generalized davenport--schinzel sequences considered by adamec et al. &lsqb;1992&rsqb;. regarding lower bounds, we show that &lambda;3(n) &geq; 2n &alpha;(n) &minus; o(n) (the previous lower bound (sharir and agarwal, 1995) had a coefficient of 1/2), so the coefficient 2 is tight. we also present a simpler variant of the construction of agarwal et al. &lsqb;1989&rsqb; that achieves the known lower bounds of &lambda;s(n) &geq; n &sdot; 2(1/t&excel;) &alpha;(n)t &minus; o(&alpha;(n)t&minus;1) for s &geq; 4 even.
stream sampling for variance-optimal estimation of subset sums. from a high volume stream of weighted items, we want to maintain a generic sample of a certain limited size k that we can later use to estimate the total weight of arbitrary subsets. this is the classic context of on-line reservoir sampling, thinking of the generic sample as a reservoir. we present an efficient reservoir sampling scheme, varoptk, that dominates all previous schemes in terms of estimation quality. varoptk provides variance optimal unbiased estimation of subset sums. more precisely, if we have seen n items of the stream, then for any subset size m, our scheme based on k samples minimizes the average variance over all subsets of size m. in fact, the optimality is against any off-line scheme with k samples tailored for the concrete set of items seen. in addition to optimal average variance, our scheme provides tighter worst-case bounds on the variance of particular subsets than previously possible. it is efficient, handling each new item of the stream in o(log k) time, which is optimal even on the word ram. finally, it is particularly well suited for combination of samples from different streams in a distributed setting.
approximate line nearest neighbor in high dimensions. we consider the problem of approximate nearest neighbors in high dimensions, when the queries are lines. in this problem, given n points in rd, we want to construct a data structure to support efficiently the following queries: given a line l, report the point p closest to l. this problem generalizes the more familiar nearest neighbor problem. from a practical perspective, lines, and low-dimensional flats in general, may model data under linear variation, such as physical objects under different lighting. for approximation 1 + &epsilon;, we achieve a query time of d3n0.5+t, for arbitrary small t > 0, with a space of d2no(1/&epsilon;2+1/t2). to the best of our knowledge, this is the first algorithm for this problem with polynomial space and sub-linear query time.
clique-width: on the price of generality. many hard problems can be solved efficiently when the input is restricted to graphs of bounded treewidth. by the celebrated result of courcelle, every decision problem expressible in monadic second order logic is fixed parameter tractable when parameterized by the treewidth of the input graph. moreover, for every fixed k &ge; 0, such problems can be solved in linear time on graphs of treewidth at most k. in particular, this implies that basic problems like dominating set, graph coloring, clique, and hamiltonian cycle are solvable in linear time on graphs of bounded treewidth. a significant amount of research in graph algorithms has been devoted to extending this result to larger classes of graphs. it was shown that some of the algorithmic meta-theorems for treewidth can be carried over to graphs of bounded clique-width. courcelle, makowsky, and rotics proved that the analogue of courcelle's result holds for graphs of bounded clique-width when the logical formulas do not use edge set quantifications. despite of its generality, this does not resolve the parameterized complexity of many basic problems concerning edge subsets (like edge dominating set), vertex partitioning (like graph coloring), or global connectivity (like hamiltonian cycle). there are various algorithms solving some of these problems in polynomial time on graphs of clique-width at most k. however, these are not fixed parameter tractable algorithms and have typical running times o(nf(k)), where n is the input length and f is some function. it was an open problem, explicitly mentioned in several papers, whether any of these problems is fixed parameter tractable when parameterized by the clique-width, i.e. solvable in time o(g(k)&middot;nc), for some function g and a constant c not depending on k. in this paper we resolve this problem by showing that edge dominating set, hamiltonian cycle, and graph coloring are w[1]-hard parameterized by clique-width. this shows that the running time o(nf(k)) of many clique-width based algorithms is essentially the best we can hope for (up to a widely believed assumption from parameterized complexity, namely fpt &ne; w[1])---the price we pay for generality.
hardness of embedding simplicial complexes in . let embedk&rarr;d be the following algorithmic problem: given a finite simplicial complex k of dimension at most k, does there exist a (piecewise linear) embedding of k into rd? known results easily imply polynomiality of embedk&rarr;2 (k = 1, 2; the case k = 1, d = 2 is graph planarity) and of embedk&rarr;2k for all k &ge; 3 (even if k is not considered fixed). we show that the celebrated result of novikov on the algorithmic unsolvability of recognizing the 5-sphere implies that embedd&rarr;d and embed(d-1)&rarr;d are undecidable for each d &ge; 5. our main result is np-hardness of embed2&rarr;4 and, more generally, of embedk&rarr;d for all k, d with d &rarr; 4 and d &rarr; k &rarr; (2d - 2)/3.
on the approximability of the maximum feasible subsystem problem with 0/1-coefficients. given a system of constraints li &le; atix &le; ui, where ai &isin; {0, 1}n, and li, ui &isin; r+, for i = 1,..., m, we consider the problem mrfs of finding the largest subsystem for which there exists a feasible solution x &ge; 0. we present approximation algorithms and inapproximability results for this problem, and study some important special cases. our main contributions are: 1. in the general case, where ai &epsilon; {0, 1}n, a sharp separation in the approximability between the case when l = max{l1, ..., lm} is bounded above by a polynomial in n and m, and the case when it is not. 2. in the case where a is an interval matrix, a sharp separation in approximability between the case where we allow a violation of the upper bounds by at most a (1 + &epsilon;) factor, for any fixed &epsilon; > 0 and the case where no violations are allowed. along the way, we prove that the induced matching problem on bipartite graphs is inapproximable beyond a factor of &omega;(n1/3-&epsilon;), for any &epsilon; > 0 unless np=zpp. finally, we also show applications of mrfs to some recently studied pricing problems.
a near-linear time algorithm for constructing a cactus representation of minimum cuts. we present an &otilde;(m) (near-linear) time monte carlo algorithm for constructing the cactus data structure, a useful representation of all the global minimum edge cuts of an undirected graph. our algorithm represents a fundamental improvement over the best previous (quadratic time) algorithms: because there can be quadratically many min-cuts, our algorithm must avoid looking at all min-cuts during the construction, but nonetheless builds a data structure representing them all. our result closes the gap between the (near-linear) time required to find a single min-cut and that for (implicitly) finding all the min-cuts.
reasoning about online algorithms with weighted automata. we describe an automata-theoretic approach for the competitive analysis of online algorithms. our approach is based on weighted automata, which assign to each input word a cost in r&ge;0. by relating the &ldquo;unbounded look ahead&rdquo; of optimal offline algorithms with nondeterminism, and relating the &ldquo;no look ahead&rdquo; of online algorithms with determinism, we are able to solve problems about the competitive ratio of online algorithms, and the memory they require, by reducing them to questions about determinization and approximated determinization of weighted automata.
decomposition of multiple coverings into more parts. we prove that for every centrally symmetric convex polygon q, there exists a constant &#x03b1; such that any locally finite &#x03b1; k-fold covering of the plane by translates of q can be decomposed into k coverings. this improves on a quadratic upper bound proved by pach and t&#x00f3;th. the question is motivated by a sensor network problem, in which a region has to be monitored by sensors with limited battery life.
overcoming the non-embeddability barrier: algorithms for product metrics. a common approach for solving computational problems over a difficult metric space is to embed the "hard" metric into l1 which admits efficient algorithms and is thus considered an "easy" metric. this approach has proved successful or partially successful for important spaces such as the edit distance, but it also has inherent limitations: it is provably impossible to go below certain approximation for some metrics. we propose a new approach, of embedding the difficult space into richer host spaces, namely iterated products of standard spaces like l1 and l&infin;. we show that this class is rich since it contains useful metric spaces with only a constant distortion, and, at the same time, it is tractable and admits efficient algorithms. using this approach, we obtain for example the first nearest neighbor data structure with o(log log d) approximation for edit distance in non-repetitive strings (the ulam metric). this approximation is exponentially better than the lower bound for embedding into l1. furthermore, we give constant factor approximation for two other computational problems. along the way, we answer positively a question posed in [ajtai, jayram, kumar, and sivakumar, stoc 2002]. one of our algorithms has already found applications for smoothed edit distance over 0--1 strings [andoni and krauthgamer, icalp 2008].
a quadratic kernel for feedback vertex set. we prove that given an undirected graph g on n vertices and an integer k, one can compute in polynomial time in n a graph g' with at most 5k2 + k vertices and an integer k' such that g has a feedback vertex set of size at most k iff g' has a feedback vertex set of size at most k'. this result improves a previous o(k11) kernel of burrage et al. [6], and a more recent cubic kernel of bodlaender [3]. this problem was communicated by fellows in [5].
on risks of using cuckoo hashing with simple universal hash classes. cuckoo hashing, introduced by pagh and rodler [10], is a dynamic dictionary data structure for storing a set s of n keys from a universe u, with constant lookup time and amortized expected constant insertion time. for the analysis, space (2+&epsilon;)n and &omega;(log n)-wise independence of the hash functions is sufficient. in experiments mentioned in [10], several weaker hash classes worked well; however, a certain simple multiplicative hash family worked badly. in this paper, we prove that the failure probability is high when cuckoo hashing is run with the multiplicative class or with the very common class of linear hash functions over a prime field, even if space 4n is provided. the key set s is fully random, but it must be relatively dense in the universe u of all keys (like |s| &ge; |u|11/12). the bad behavior and the fact that this effect depends on the density of s in u can also be observed in experiments. the result transfers to larger universes if the keys are chosen from a suitable smaller domain. viewed from a different perspective, our result illustrates that care must be taken when applying a recent result of mitzenmacher and vadhan ([12], soda 2008) proving good behavior of universal hash classes in combination with key sets that have some entropy. their result is applicable to cuckoo hashing. a technical hypothesis in [12], namely the assumption that either the "collision probability" or the "maximum probability" is small, translates into the condition that |s| is relatively small in comparison to |u|. our result shows that the result from [12] on 2-universal classes ceases to hold if |s|/|u| is not small enough, even for very common 2-universal hash classes and fully random key sets.
computing the nucleolus of weighted voting games. weighted voting games (wvg) are coalitional games in which an agent's contribution to a coalition is given by his weight, and a coalition wins if its total weight meets or exceeds a given quota. these games model decision-making in political bodies as well as collaboration and surplus division in multiagent domains. the computational complexity of various solution concepts for weighted voting games received a lot of attention in recent years. in particular, elkind et al.(2007) studied the complexity of stability-related solution concepts in wvgs, namely, of the core, the least core, and the nucleolus. while they have completely characterized the algorithmic complexity of the core and the least core, for the nucleolus they have only provided an np-hardness result. in this paper, we solve an open problem posed by elkind et al. by showing that the nucleolus of wvgs, and, more generally, k-vector weighted voting games with fixed k, can be computed in pseudopolynomial time, i.e., there exists an algorithm that correctly computes the nucleolus and runs in time polynomial in the number of players n and the maximum weight w. in doing so, we propose a general framework for computing the nucleolus, which may be applicable to a wider of class of games.
sorting by placement and shift. in sorting situations where the final destination of each item is known, it is natural to repeatedly choose items and place them where they belong, allowing the intervening items to shift by one to make room. (in fact, a special case of this algorithm is commonly used to hand-sort files.) however, it is not obvious that this algorithm necessarily terminates. we show that in fact the algorithm terminates after at most 2n-1-1 steps in the worst case (confirming a conjecture of l. larson), and that there are super-exponentially many permutations for which this exact bound can be achieved. the proof involves a curious symmetrical binary representation.
sequential cavity method for computing limits of the log-partition function for lattice models. one of the key computational problems in combinatorics/statistical physics is the problem of computing limits of the log-partition functions for various statistical mechanics models on lattices. in combinatorics this limit corresponds to the exponent of various arrangements on lattices, for example the exponents of the number of independent sets, proper colorings or matchings on a lattice. in statistical physics this limit is called free energy. we propose a new method, sequential cavity, which beats the best known existing methods, such as transfer matrix method, in obtaining sharper bounds on the limits of the log-partition function for two models: independent sets (hard-core) and matchings (monomer-dimer). our method is based on a surprisingly simple representation of the log-partition function limit in terms of a certain marginal probability of a suitably modified lattice, and using recent deterministic approximation counting algorithms for these two models. our method also has a provably better theoretical performance compared with the transfer matrix method.
on the maximum quadratic assignment problem. quadratic assignment is a basic problem in combinatorial optimization that generalizes several other problems such as traveling salesman, linear arrangement, dense k subgraph, and clustering with given sizes. the input to the quadratic assignment problem consists of two n × n symmetric nonnegative matrices <inline-formula><tex-math>$w=(w_{i, j})$</tex-math></inline-formula> and <inline-formula><tex-math>$d=(d_{i, j})$</tex-math></inline-formula>. given matrices w, d, and a permutation <inline-formula><tex-math>$\pi: [n] \rightarrow [n]$</tex-math></inline-formula>, the objective function is <inline-formula><tex-math>$q(\pi):= \sum_{i, j \in [n], i \ne j} w_{i, j} \cdot d_{\pi(i), \pi(j)}$</tex-math></inline-formula>. in this paper, we study the maximum quadratic assignment problem, where the goal is to find a permutation π that maximizes <inline-formula><tex-math>$q(\pi)$</tex-math></inline-formula>. we give an <inline-formula><tex-math>$\tilde{o}(\sqrt{n})$</tex-math></inline-formula>-approximation algorithm, which is the first nontrivial approximation guarantee for this problem. the above guarantee also holds when the matrices w, d are asymmetric. an indication of the hardness of maximum quadratic assignment is that it contains as a special case the dense k subgraph problem, for which the best-known approximation ratio is <inline-formula><tex-math>$\approx n^{1/3}$</tex-math></inline-formula> (feige et al. [feige, u., g. kortsarz, d. peleg. 2001. the dense k-subgraph problem. algorithmica29(3) 410--421]). when one of the matrices w, d satisfies triangle inequality, we obtain a <inline-formula><tex-math>$2e/(e-1) \approx 3.16$</tex-math></inline-formula>-approximation algorithm. this improves over the previously best-known approximation guarantee of four (arkin et al. [arkin, e. m., r. hassin, m. sviridenko. 2001. approximating the maximum quadratic assignment problem. inform. processing lett.77 13--16]) for this special case of maximum quadratic assignment. the performance guarantee for maximum quadratic assignment with triangle inequality can be proved relative to an optimal solution of a natural linear programming relaxation that has been used earlier in branch-and-bound approaches (see, eg., adams and johnson [adams, w. p., t. a. johnson. 1994. improved linear programming-based lower bounds for the quadratic assignment problem. dimacs ser. discrete math. theoret. comput. sci.16 43--77]). it can also be shown that this linear program (lp) has an integrality gap of <inline-formula><tex-math>$\tilde{\omega}(\sqrt{n})$</tex-math></inline-formula> for general maximum quadratic assignment.
column subset selection, matrix factorization, and eigenvalue optimization. given a fixed matrix, the problem of column subset selection requests a column submatrix that has favorable spectral properties. most research from the algorithms and numerical linear algebra communities focuses on a variant called rank-revealing qr, which seeks a well-conditioned collection of columns that spans the (numerical) range of the matrix. the functional analysis literature contains another strand of work on column selection whose algorithmic implications have not been explored. in particular, a celebrated result of bourgain and tzafriri demonstrates that each matrix with normalized columns contains a large column submatrix that is exceptionally well conditioned. unfortunately, standard proofs of this result cannot be regarded as algorithmic. this paper presents a randomized, polynomial-time algorithm that produces the submatrix promised by bourgain and tzafriri. the method involves random sampling of columns, followed by a matrix factorization that exposes the well-conditioned subset of columns. this factorization, which is due to grothendieck, is regarded as a central tool in modern functional analysis. the primary novelty in this work is an algorithm, based on eigenvalue minimization, for constructing the grothendieck factorization. these ideas also result in an approximation algorithm for the (&infin;, 1) norm of a matrix, which is generally np-hard to compute exactly. as an added bonus, this work reveals a surprising connection between matrix factorization and the famous maxcut semidefinite program.
cell probe lower bounds for succinct data structures. in this paper, we consider several static data structure problems in the deterministic cell probe model. we develop a new technique for proving lower bounds for succinct data structures, where the redundancy in the storage can be small compared to the information-theoretic minimum. in fact, we succeed in matching (up to constant factors) the lower order terms of the existing data structures with the lower order terms provided by our lower bound. using this technique, we obtain (i) the first lower bound for the problem of searching and retrieval of a substring in text; (ii) a cell probe lower bound for the problem of representing permutation &pi; with queries &pi;(i) and &pi;&minus;1(i) that matches the lower order term of the existing data structures, and (iii) a lower bound for representing binary matrices that is also matches upper bounds for some set of parameters. the nature of all these problems is that we are to implement two operations that are in a reciprocal relation to each other (search and retrieval, computing forward and inverse element, operations on rows and columns of a matrix). as far as we know, this paper is the first to provide an insight into such problems.
on low dimensional local embeddings. we study the problem of embedding metric spaces into low dimensional lp spaces while faithfully preserving distances from each point to its k nearest neighbors. we show that any metric space can be embedded into [equation] with k-local distortion of o ((log k)/p). we also show that any ultrametric can be embedded into [equation] with k-local distortion 1 + &epsilon;. our embedding results have immediate applications to local distance oracles. we show how to preprocess a graph in polynomial time to obtain a data structure of o(nk1/t log2 k) bits, such that distance queries from any node to its k nearest neighbors can be answered with stretch o(t).
maximizing submodular set functions subject to multiple linear constraints. the concept of submodularity plays a vital role in combinatorial optimization. in particular, many important optimization problems can be cast as submodular maximization problems, including maximum coverage, maximum facility location and max cut in directed/undirected graphs. in this paper we present the first known approximation algorithms for the problem of maximizing a nondecreasing submodular set function subject to multiple linear constraints. given a d-dimensional budget vector [equation], for some d &ge; 1, and an oracle for a non-decreasing submodular set function f over a universe u, where each element e &isin; u is associated with a d-dimensional cost vector, we seek a subset of elements s &sube; u whose total cost is at most [equation], such that f(s) is maximized. we develop a framework for maximizing submodular functions subject to d linear constraints that yields a (1 - &epsilon;)(1 - e&minus;1)-approximation to the optimum for any &epsilon; > 0, where d > 1 is some constant. our study is motivated by a variant of the classical maximum coverage problem that we call maximum coverage with multiple packing constraints. we use our framework to obtain the same approximation ratio for this problem. to the best of our knowledge, this is the first time the theoretical bound of 1 - e&minus;1 is (almost) matched for both of these problems.
inserting a vertex into a planar graph. we consider the problem of computing a crossing minimum drawing of a given planar graph g = (v, e) augmented by a star, i.e., an additional vertex v together with its incident edges ev = {(v, u) | u &isin; v}, in which all crossings involve ev. alternatively, the problem can be stated as finding a planar embedding of g, in which the given star can be inserted requiring the minimum number of crossings. this is a generalization of the crossing minimum edge insertion problem [15], and can help to find improved approximations for the crossing minimization problem. indeed, in practice, the algorithm for the crossing minimum edge insertion problem turned out to be the key for obtaining the currently strongest approximate solutions for the crossing number of general graphs. the generalization considered here can lead to even better solutions for the crossing minimization problem. furthermore, it offers new insight into the crossing number problem for almost-planar and apex graphs. it has been an open problem whether the star insertion problem is polynomially solvable. we give an affirmative answer by describing the first efficient algorithm for this problem. this algorithm uses the spqr-tree data structure to handle the exponential number of possible embeddings, in conjunction with dynamic programming schemes for which we introduce partitioning cost subproblems.
coresets and approximate clustering for bregman divergences. we study the generalized k-median problem with respect to a bregman divergence d&phi;. given a finite set p &sube; rd of size n, our goal is to find a set c of size k such that the sum of errors cost(p, c) = &sigma;p&epsilon;p minc&epsilon;c {d&phi;(p, c)} is minimized. the bregman k-median problem plays an important role in many applications, e.g. information theory, statistics, text classification, and speech processing. we give the first coreset construction for this problem for a large subclass of bregman divergences, including important dissimilarity measures such as the kullback-leibler divergence and the itakura-saito divergence. using these coresets, we give a (1 + &epsilon;)-approximation algorithm for the bregman k-median problem with running time o (dkn + d22(k/c)thetas;(1) logk+2n). this result improves over the previousely fastest known (1 + &epsilon;)-approximation algorithm from [1]. unlike the analysis of most coreset constructions our analysis does not rely on the construction of &epsilon;-nets. instead, we prove our results by purely combinatorial means.
a simpler implementation and analysis of chazelle's soft heaps. chazelle (jacm 47(6), 2000) devised an approximate meldable priority queue data structure, called soft heaps, and used it to obtain the fastest known deterministic comparison-based algorithm for computing minimum spanning trees, as well as some new algorithms for selection and approximate sorting problems. if n elements are inserted into a collection of soft heaps, then up to &epsilon;n of the elements still contained in these heaps, for a given error parameter &epsilon;, may be corrupted, i.e., have their keys artificially increased. in exchange for allowing these corruptions, each soft heap operation is performed in o(log 1/&epsilon;) amortized time. chazelle's soft heaps are derived from the binomial heaps data structure in which each priority queue is composed of a collection of binomial trees. we describe a simpler and more direct implementation of soft heaps in which each priority queue is composed of a collection of standard binary trees. our implementation has the advantage that no clean-up operations similar to the ones used in chazelle's implementation are required. we also present a concise and unified potential-based amortized analysis of the new implementation.
algorithms for finding an induced cycle in planar graphs and bounded genus graphs. in this paper, we consider the problem of finding an induced cycle passing through k given vertices, which we call the induced cycle problem. the significance of finding induced cycles stems from the fact that precise characterization of perfect graphs would require structures of graphs without an odd induced cycle, and its complement. there has been huge progress in the recent years, especially, the strong perfect graph conjecture was solved in [6]. concerning recognition of perfect graphs, there had been a long-standing open problem for detecting an odd hole and its complement, and finally this was solved in [4]. unfortunately, the problem of finding an induced cycle passing through two given vertices is np-complete in a general graph [2]. however, if the input graph is constrained to be planar and k is fixed, then the induced cycle problem can be solved in polynomial time [13, 14, 16]. in particular, an o(n2) time algorithm is given for the case k = 2 by mcdiarmid, reed, schrijver and shepherd [18], where n is the number of vertices of the input graph. our main results in this paper are to improve their result in the following sense. 1. the number of vertices k is allowed to be non-trivially super constant number, up to k = o((log n/log log n)2/3). more precisely, when k = o((log n/log log n)2/3), then the icp in planar graphs can be solved in o(n2+&epsilon;) time for any &epsilon;>0. 2. the time complexity is linear if the given graph is planar and k is fixed. 3. the above results are extended to graphs embedded in a fixed surface. we note that the linear time algorithm (the second result) is independent from the first result. let us point out that we give the first polynomial time algorithm for the problem for the bounded genus case. in fact, our proof gives a short proof of a result announced in [20] (without complete proof) which gives a linear time algorithm for the disjoint paths problem for fixed k for the bounded genus case. we also extend this result to the induced disjoint paths problem. let us observe that if k is as a part of the input, then the problem is still np-complete, and so we need to impose some condition on k.
scalably scheduling processes with arbitrary speedup curves. we give a scalable ((1+&epsilon;)-speed o(1)-competitive) non-clairvoyant algorithm for scheduling jobs with sublinear nondecreasing speed-up curves on multiple processors with the objective of average response time.
on smoothed -cnf formulas and the walksat algorithm. in this paper we study the model of &epsilon;-smoothed k-cnf formulas. starting from an arbitrary instance f with n variables and m = dn clauses, apply the &epsilon;-smoothing operation of flipping the polarity of every literal in every clause independently at random with probability &epsilon;. keeping &epsilon; and k fixed, and letting the density d = m/n grow, it is rather easy to see that for d &ge; &epsilon;-k ln 2, f becomes whp unsatisfiable after smoothing. we show that a lower density that behaves roughly like &epsilon;-k+1 suffices for this purpose. we also show that our bound on d is nearly best possible in the sense that there are k-cnf formulas f of slightly lower density that whp remain satisfiable after smoothing. one consequence of our proof is a new lower bound of &omega;(2k/k2) on the density up to which walksat solves random k-cnfs in polynomial time whp. we are not aware of any previous rigorous analysis showing that walksat is successful at densities that are increasing as a function of k.
finding shortest contractible and shortest separating cycles in embedded graphs. we give a polynomial-time algorithm to find a shortest contractible cycle (i.e., a closed walk without repeated vertices) in a graph embedded in a surface. this answers a question posed by hutchinson. in contrast, we show that finding a shortest contractible cycle through a given vertex is np-hard. we also show that finding a shortest separating cycle in an embedded graph is np-hard. this answers a question posed by mohar and thomassen.
probability, algorithms and complexity. the talk will be a little sightseeing tour through some areas of mathematics and theoretical computer science that i found and find fascinating the tour may touch on the development of a gamblers fortune, the multiplication of numbers and of matrices, probabilistic tests of primality and the complexity of continued fractions.
a new approach to incremental topological ordering. let g = (v, e) be a directed acyclic graph (dag) with n = |v| and m = |e|. we say that a total ordering &pr; on vertices v is a topological ordering if for every edge (u, v) &isin; e, we have u &isin; v. in this paper, we consider the problem of maintaining a topological ordering subject to dynamic changes to the underlying graph. that is, we begin with an empty graph g = (v, &oslash;) consisting of n nodes. the adversary adds m edges to the graph g, one edge at a time. throughout this process, we maintain an online topological ordering of the graph g. in this paper, we present a new algorithm that has a total cost of o(n2logn) for maintaining the topological ordering throughout all the edge additions. at the heart of our algorithm is a new approach for maintaining the ordering. instead of attempting to place the nodes in an ordered list, we assign each node a label that is consistent with the ordering, and yet can be updated efficiently as edges are inserted. when the graph is dense, our algorithm is more efficient than existing algorithms. by way of contrast, the best known prior algorithms achieve only o(min(m1.5, n2.5)) cost.
from coding theory to efficient pattern matching. we consider the classic problem of pattern matching with few mismatches in the presence of promiscuously matching wildcard symbols. given a text t of length n and a pattern p of length m with optional wildcard symbols and a bound k, our algorithm finds all the alignments for which the pattern matches the text with hamming distance at most k and also returns the location and identity of each mismatch. the algorithm we present is deterministic and runs in &otilde;(kn) time, matching the best known randomised time complexity to within logarithmic factors. the solutions we develop borrow from the tool set of algebraic coding theory and provide a new framework in which to tackle approximate pattern matching problems.
collecting weighted items from a dynamic queue. we consider the problem of collecting weighted items from a dynamic queue s. before each step, some items at the front of s can be deleted and some other items can be added to s at any place. an item, once deleted, cannot be re-inserted --- in other words, it "expires". we are allowed to collect one item from s per step. each item can be collected only once. the objective is to maximize the total weight of the collected items. we study the online version of the dynamic queue problem. it is quite easy to see that the greedy algorithm that always collects the maximum-value item is 2-competitive, and that no deterministic online algorithm can be better than 1.618-competitive. we improve both bounds: we give a 1.89-competitive algorithm for general dynamic queues and we show a lower bound of 1.632 on the competitive ratio. we also provide other upper and lower bounds for restricted versions of this problem. the dynamic queue problem is a generalization of the well-studied buffer management problem, and it is an abstraction of the buffer management problem for network links with intermittent access.
dimension detection via slivers. we present a novel approach to estimate the dimension m of an unknown manifold m &sub; rd with positive reach from a set of point samples p &sub; m. it works by analyzing the shape of simplices formed by point samples. suppose that p is drawn from m according to a poisson process with an unknown parameter &lambda;. let k be some fixed positive integer. when &lambda; is large enough, we prove that the dimension can be correctly output in o(kd|p|1+1/k) time with probability greater than 1-2-k. we experimented with a practical variant and showed that its performance is competitive with several previous methods.
approximating fractional hypertree width. fractional hypertree width is a hypergraph measure similar to tree width and hypertree width. its algorithmic importance comes from the fact that, as shown in previous work, constraint satisfaction problems (csp) and various problems in database theory are polynomial-time solvable if the input contains a bounded-width fractional hypertree decomposition of the hypergraph of the constraints. in this article, we show that for every fixed w &ge; 1, there is a polynomial-time algorithm that, given a hypergraph h with fractional hypertree width at most w, computes a fractional hypertree decomposition of width o(w3) for h. this means that polynomial-time algorithms relying on bounded-width fractional hypertree decompositions no longer need to be given a decomposition explicitly in the input, since an appropriate decomposition can be computed in polynomial time. therefore, if h is a class of hypergraphs with bounded fractional hypertree width, then a csp restricted to instances whose structure is in h is polynomial-time solvable. this makes bounded fractional hypertree width the most general known hypergraph property that makes csp, boolean conjunctive queries, and conjunctive query containment polynomial-time solvable.
the ratio index for budgeted learning, with applications. in the budgeted learning problem, we are allowed to experiment on a set of alternatives (given a fixed experimentation budget) with the goal of picking a single alternative with the largest possible expected payoff. constant factor approximation algorithms for this problem were developed by guha and munagala by rounding a linear program that couples the various alternatives together. in this paper we present an index for this problem, which we call the ratio index, which also guarantees a constant factor approximation. index-based policies have the advantage that a single number (i.e. the index) can be computed for each alternative irrespective of all other alternatives, and the alternative with the highest index is experimented upon. this is analogous to the famous gittins index for the discounted multi-armed bandit problem. the ratio index has several interesting structural properties. first, we show that it can be computed in strongly polynomial time. second, we show that with the appropriate discount factor, the gittins index and our ratio index are constant factor approximations of each other, and hence the gittins index also gives a constant factor approximation to the budgeted learning problem. finally, we show that the ratio index can be used to create an index-based policy that achieves an o(1)-approximation for the finite horizon version of the multi-armed bandit problem. moreover, the policy does not require any knowledge of the horizon (whereas we compare its performance against an optimal strategy that is aware of the horizon). this yields the following surprising result: there is an index-based policy that achieves an o(1)-approximation for the multi-armed bandit problem, oblivious to the underlying discount factor.
assignment problem in content distribution networks: unsplittable hard-capacitated facility location. in a content distribution network (cdn), there are m servers storing the data; each of them has a specific bandwidth. all the requests from a particular client should be assigned to one server, because of the routing protocol used. the goal is to minimize the total cost of these assignments ---cost of each is proportional to the distance as well as the request size--- while the load on each server is kept below its bandwidth limit. when each server also has a setup cost, this is an unsplittable hard-capacitated facility location problem. as much attention as facility location problems have received, there has been no nontrivial approximation algorithm when we have hard capacities (i.e., there can only be one copy of each facility whose capacity cannot be violated) and demands are unsplittable (i.e., all the demand from a client has to be assigned to a single facility). we observe it is np-hard to approximate the cost to within any bounded factor. thus, for an arbitrary constant &epsilon; > 0, we relax the capacities to a 1 + &epsilon; factor. for the case where capacities are almost uniform, we give a bicriteria o(log n, 1 + &epsilon;)-approximation algorithm for general metrics and a (1 + &epsilon;, 1 + &epsilon;)-approximation algorithm for tree metrics. a bicriteria (&alpha;, &beta;)-approximation algorithm produces a solution of cost at most &alpha; times the optimum, while violating the capacities by no more than a &beta; factor. we can get the same guarantee for non-uniform capacities if we allow quasipolynomial running time. in our algorithm, some clients guess the facility they are assigned to, and facilities decide the size of clients they serve. a straight-forward approach results in exponential running time. when costs do not satisfy metricity, we show that a 1.5 violation of capacities is necessary to obtain any approximation. it is worth noting that our results generalize bin packing (zero cost matrix and facility costs equal to one), knapsack (single facility with all costs being zero), minimum makespan scheduling for related machines (all costs being zero) and some facility location problems.
the johnson-lindenstrauss lemma almost characterizes hilbert space, but not quite. let x be a normed space that satisfies the johnson-lindenstrauss lemma (j--l lemma, in short) in the sense that for any integer n and any x1,...,xn &epsilon; x there exists a linear mapping l: x &rarr; f, where f &sube; x is a linear subspace of dimension o(log n), such that ||xi - xj|| &le; ||l(xi) - l(xj)|| &le; o(1) &middot; ||xi - xj|| for all i, j &epsilon; {1,..., n). we show that this implies that x is almost euclidean in the following sense: every n-dimensional subspace of x embeds into hilbert space with distortion [equation]. on the other hand, we show that there exists a normed space y which satisfies the j-l lemma, but for every n there exists an n-dimensional subspace en &sube; y whose euclidean distortion is at least 2&omega;(&alpha;(n)), where &alpha; is the inverse ackermann function.
online scheduling to minimize the maximum delay factor. in this paper two scheduling models are addressed. first is the standard model (unicast) where requests (or jobs) are independent. the other is the broadcast model where broadcasting a page can satisfy multiple outstanding requests for that page. we consider online scheduling of requests when they have deadlines. unlike previous models, which mainly consider the objective of maximizing throughput while respecting deadlines, here we focus on scheduling all the given requests with the goal of minimizing the maximum delay factor. the delay factor of a schedule is defined to be the minimum &alpha; &ge; 1 such that each request i is completed by time ai + &alpha;(di - ai) where ai is the arrival time of request i and di is its deadline. delay factor generalizes the previously defined measure of maximum stretch which is based only the processing times of requests [9, 11]. we prove strong lower bounds on the achievable competitive ratios for delay factor scheduling even with unit-time requests. motivated by this, we consider resource augmentation analysis [24] and prove the following positive results. for the unicast model we give algorithms that are (1 + &epsilon;)-speed o(1/&epsilon;)-competitive in both the single machine and multiple machine settings. in the broadcast model we give an algorithm for same-sized pages that is (2 + &epsilon;)-speed o(1/&epsilon;2)-competitive. for arbitrary page sizes we give an algorithm that is (4 + &epsilon;)-speed o(1/&epsilon;2)-competitive.
improved equilibria via public service advertising. many natural games have both high and low cost nash equilibria: their price of anarchy is high and yet their price of stability is low. in such cases, one could hope to move behavior from a high cost equilibrium to a low cost one by a "public service advertising campaign" encouraging players to follow the low-cost equilibrium, and if every player follows the advice then we are done. however, the assumption that everyone follows instructions is unrealistic. a more natural assumption is that some players will follow them, while other players will not. in this paper we consider the question of to what extent can such an advertising campaign cause behavior to switch from a bad equilibrium to a good one even if only a fraction of people actually follow the given advice, and do so only temporarily. unlike the "value of altruism" model, we assume everyone will ultimately act in their own interest. we analyze this question for several important and widely studied classes of games including network design with fair cost sharing, scheduling with unrelated machines, and party affiliation games (which include consensus and cut games). we show that for some of these games (such as fair cost sharing), a random &alpha; fraction of the population following the given advice is sufficient to get a guarantee within an o(1/&alpha;) factor of the price of stability for any &alpha; > 0. for other games (such as party affiliation games), there is a strict threshold (in this case, &alpha; < 1/2 yields almost no benefit, yet &alpha; > 1/2 is enough to reach near-optimal behavior). finally, for some games, such as scheduling, no value &alpha; < 1 is sufficient. we also consider a "viral marketing" model in which certain players are specifically targeted, and analyze the ability of such targeting to influence behavior using a much smaller number of targeted players.
the geometry of binary search trees. we present a novel connection between binary search trees (bsts) and points in the plane satisfying a simple property. using this correspondence, we achieve the following results: 1. a surprisingly clean restatement in geometric terms of many results and conjectures relating to bsts and dynamic optimality. 2. a new lower bound for searching in the bst model, which subsumes the previous two known bounds of wilber [focs'86]. 3. the first proposal for dynamic optimality not based on splay trees. a natural greedy but offline algorithm was presented by lucas [1988], and independently by munro [2000], and was conjectured to be an (additive) approximation of the best binary search tree. we show that there exists an equal-cost online algorithm, transforming the conjecture of lucas and munro into the conjecture that the greedy algorithm is dynamically optimal.
improved approximating algorithms for directed steiner forest. we consider the k-directed steiner forest (k-dsf) problem: given a directed graph g = (v, e) with edge costs, a collection d &isin; v x v of ordered node pairs, and an integer k &le; |d|, find a min-cost subgraph h of g that contains an st-path for (at least) k pairs (s, t) &isin; d. when k = |d|, we get the directed steiner forest (dsf) problem. the best known approximation ratios for these problems are: &otilde;(k2/3) for k-dsf by charikar et al. [2], and o(k1/2+&epsilon;) for dsf by chekuri et al. [3]. for dsf we give an o(n&epsilon;&middot;min {n4/5,m2/3})-approximation scheme using a novel lp-relaxation seeking to connect pairs via "cheap" paths. this is the first sublinear (in terms of n = |v|) approximation ratio for the problem. for k-dsf we give a simple greedy o(k1/2+&epsilon;)-approximation scheme, improving the best known ratio &otilde;(k2/3) by charikar et al. [2], and (almost) matching, in terms of k, the best ratio known for the undirected variant [11]. even when used for the particular case dsf, our algorithm favorably compares to the one of [3], which repeatedly solves linear programs, and uses complex time and space consuming transformations.
efficient algorithms for the 2-gathering problem. pebbles are placed on some vertices of a directed graph. is it possible to move each pebble along at most one edge of the graph so that in the final configuration no pebble is left on its own? we give an o(mn)-time algorithm for solving this problem, which we call the 2-gathering problem, where n is the number of vertices and m is the number of edges of the graph. if such a 2-gathering is not possible, the algorithm finds a solution that minimizes the number of solitary pebbles. the 2-gathering problem forms a nontrivial generalization of the nonbipartite matching problem and it is solved by extending the augmenting paths technique used to solve matching problems.
comparison-based time-space lower bounds for selection. we establish the first nontrivial lower bounds on time-space trade-offs for the selection problem. we prove that any comparison-based randomized algorithm for finding the median requires &omega;(nlog logs n) expected time in the ram model (or more generally in the comparison branching program model), if we have s bits of extra space besides the read-only input array. this bound is tight for all s &gt; log n, and remains true even if the array is given in a random order. our result thus answers a 16-year-old question of munro and raman &lsqb;1996&rsqb;, and also complements recent lower bounds that are restricted to sequential access, as in the multipass streaming model &lsqb;chakrabarti et al. 2008b&rsqb;. we also prove that any comparison-based, deterministic, multipass streaming algorithm for finding the median requires &omega;(nlog&ast;(n/s)+ nlogs n) worst-case time (in scanning plus comparisons), if we have s cells of space. this bound is also tight for all s &gt;log2 n. we get deterministic lower bounds for i/o-efficient algorithms as well. the proofs in this article are self-contained and do not rely on communication complexity techniques.
finding duplicates in a data stream. given a data stream of length n over an alphabet [m] where n > m, we consider the problem of finding a duplicate in a single pass. we give a randomized algorithm for this problem that uses o((log m)3) space. this answers a question of muthukrishnan [mut05] and tarui [tar07], who asked if this problem could be solved using sub-linear space and one pass over the input. our algorithm solves the more general problem of finding a positive frequency element in a stream given by frequency updates where the sum of all frequencies is positive. our main tool is an isolation lemma that reduces this problem to the task of detecting and identifying a dictatorial variable in a boolean halfspace. we present various relaxations of the condition n > m, under which one can find duplicates efficiently.
approximation algorithms for restless bandit problems. in this paper, we consider the restless bandit problem, which is one of the most well-studied generalizations of the celebrated stochastic multi-armed bandit problem in decision theory. in its ultimate generality, the restless bandit problem is known to be pspace-hard to approximate to any non-trivial factor, and little progress has been made on this problem despite its significance in modeling activity allocation under uncertainty. we make progress on this problem by showing that for an interesting and general subclass that we term monotone bandits, a surprisingly simple and intuitive greedy policy yields a factor 2 approximation. such greedy policies are termed index policies, and are popular due to their simplicity and their optimality for the stochastic multi-armed bandit problem. the monotone bandit problem strictly generalizes the stochastic multi-armed bandit problem, and naturally models multi-project scheduling where the state of a project becomes increasingly uncertain when the project is not scheduled. we develop several novel techniques in the design and analysis of the index policy. our algorithm proceeds by introducing a novel "balance" constraint to the dual of a well-known lp relaxation to the restless bandit problem. this is followed by a structural characterization of the optimal solution by using both the exact primal as well as dual complementary slackness conditions. this yields an interpretation of the dual variables as potential functions from which we derive the index policy and the associated analysis.
efficient coordination mechanisms for unrelated machine scheduling. we present three new coordination mechanisms for scheduling n selfish jobs on m unrelated machines. a coordination mechanism aims to mitigate the impact of selfishness of jobs on the efficiency of schedules by defining a local scheduling policy on each machine. the scheduling policies induce a game among the jobs and each job prefers to be scheduled on a machine so that its completion time is minimum given the assignments of the other jobs. we consider the maximum completion time among all jobs as the measure of the efficiency of schedules. the approximation ratio of a coordination mechanism quantifies the efficiency of pure nash equilibria (price of anarchy) of the induced game. our mechanisms are deterministic, local, and preemptive in the sense that the scheduling policy does not necessarily process the jobs in an uninterrupted way and may introduce some idle time. our first coordination mechanism has approximation ratio o(log m) and always guarantees that the induced game has pure nash equilibria to which the system converges in at most n rounds. this result improves a recent bound of o(log2 m) due to azar, jain, and mirrokni and, similarly to their mechanism, our mechanism uses a global ordering of the jobs according to their distinct ids. next we study the intriguing scenario where jobs are anonymous, i.e., they have no ids. in this case, coordination mechanisms can only distinguish between jobs that have different load characteristics. our second mechanism handles anonymous jobs and has approximation ratio o (log m/log log m) although the game induced is not a potential game and, hence, the existence of pure nash equilibria is not guaranteed by potential function arguments. however, it provides evidence that the known lower bounds for non-preemptive coordination mechanisms could be beaten using preemptive scheduling policies. our third coordination mechanism also handles anonymous jobs and has a nice "cost-revealing" potential function. besides in proving the existence of equilibria, we use this potential function in order to upper-bound the price of stability of the induced game by o(log m), the price of anarchy by o(log2 m), and the convergence time to o(log2 m)-approximate assignments by a polynomial number of best-response moves. our third coordination mechanism is the first that handles anonymous jobs and simultaneously guarantees that the induced game is a potential game and has bounded price of anarchy.
a universally fastest algorithm for max 2-sat, max 2-csp, and everything in between. we introduce "hybrid" max 2-csp formulas consisting of "simple clauses", namely conjunctions and disjunctions of pairs of variables, and general 2-variable clauses, which can be any integer-valued functions of pairs of boolean variables. this allows an algorithm to use both efficient reductions specific to and and or clauses, and other powerful reductions that require the general csp setting. parametrizing an instance by the fraction p of nonsimple clauses, we give an exact (exponential-time) algorithm that is the fastest polynomial-space algorithm known for max 2-sat (and other p = 0 formulas, with arbitrary mixtures of and and or clauses); the only efficient algorithm for mixtures of and, or, and general integer-valued clauses; and tied for fastest for general max 2-csp (p = 1). since a pure 2-sat input instance may be transformed to a general csp instance in the course of being solved, the algorithm's efficiency and generality go hand in hand. our novel analysis results in a family of running-time bounds, each optimized for a particular value of p. the algorithm uses new reductions introduced here, as well as recent reductions such as "clause-learning" and "2-reductions" adapted to our setting's mixture of simple and general clauses. each reduction imposes constraints on various parameters, and the running-time bound is an "objective function" of these parameters and p. the optimal running-time bound is obtained by solving a convex nonlinear program, which can be done efficiently and with a certificate of optimality.
(un)expected behavior of digital search tree profile. a digital search tree (dst) -- one of the most fundamental data structures on words -- is a digital tree in which keys (strings, words) are stored directly in (internal) nodes. such trees find myriad of applications from the popular lempel-ziv'78 data compression scheme to distributed hash tables. the profile of a dst measures the number of nodes at the same distance from the root; it is a function of the number of stored strings and the distance from the root. most parameters of dst (e.g., height, fill-up) can be expressed in terms of the profile. however, from the inception of dst, the analysis of the profile has been elusive and it has become a prominent open problem in the area of analysis of algorithms. we make here the first, but decisive, step towards solving this problem. we present a precise analysis of the average profile when stored strings are generated by a biased memoryless source. the main technical difficulty of analyzing the profile lies in solving a sophisticated recurrence equation. we present such a solution for the poissonized version of the problem (i.e., when the number of stored strings is generated by a poisson distribution) in the mellin transform domain. to accomplish it, we introduce a novel functional operator that allows us to express the solution in an explicit form, and then using analytic algorithmics tools to extract the asymptotic behavior of the profile. this analysis is surprisingly demanding but once it is carried out it reveals unusually intriguing and interesting behavior. the average profile undergoes several phase transitions when moving from the root to the longest path. at first, it resembles a full tree until it abruptly starts growing polynomially and it oscillates in this range. our results are derived by methods of analytic algorithmics such as generating functions, mellin transform, poissonization and de-poissonization, the saddle-point method, singularity analysis and uniform asymptotic analysis.
3-bit dictator testing: 1 vs. 5/8. in the conclusion of his monumental paper on optimal inapproximability results, h&aring;stad [13] suggested that fourier analysis of dictator (long code) tests may not be universally applicable in the study of csps. his main open question was to determine if the technique could resolve the approximability of satisfiable 3-bit constraint satisfaction problems. in particular, he asked if the "not two" (ntw) predicate is non-approximable beyond the random assignment threshold of 5/8 on satisfiable instances. around the same time, zwick [30] showed that all satisfiable 3-csps are 5/8-approximable and conjectured that the 5/8 is optimal. in this work we show that fourier analysis techniques can produce a dictator test based on ntw with completeness 1 and soundness 5/8. our test's analysis uses the bonami-gross-beckner hypercontractive inequality. we also show a soundness lower bound of 5/8 for all 3-query dictator tests with perfect completeness. this lower bound for property testing is proved in part via a semidefinite programming algorithm of zwick [30]. our work precisely determines the 3-query "dictatorship testing gap". although this represents progress on zwick's conjecture, current pcp "outer verifier" technology is insufficient to convert our dictator test into an np-hardness-of-approximation result.
on stars and steiner stars: ii. a steiner star for a set p of n points in rd connects an arbitrary center point to all points of p, while a star connects a point p &isin; p to the remaining n -- 1 points of p. all connections are realized by straight line segments. fekete and meijer showed that the minimum star is at most &radic;2 times longer than the minimum steiner star for any finite point configuration in rd. the maximum ratio between them, over all finite point configurations in rd, is called the star steiner ratio in rd. it is conjectured that this ratio is 4/&pi; = 1.2732 ... in the plane and 4/3 = 1.3333 ... in three dimensions. here we give upper bounds of 1.3631 in the plane, and 1.3833 in 3-space, thereby substantially improving recent upper bounds of 1.3999, and &radic;2--10&minus;4, respectively. our results also imply improved bounds on the maximum ratios between the minimum star and the maximum matching in two and three dimensions. our method exploits the connection with the classical problem of estimating the maximum sum of pairwise distances among n points on the unit sphere, first studied by l&aacute;szl&oacute; fejes t&oacute;th. it is quite general and yields the first nontrivial estimates below &radic;2 on the star steiner ratios in arbitrary dimensions. we show, however, that the star steiner ratio in rd tends to &radic;2, the upper bound given by fekete and meijer, as d goes to infinity. our estimates on the star steiner ratios are therefore much closer to the conjectured values in higher dimensions! as it turns out, our estimates as well as the conjectured values of the steiner ratios (in the limit, for n going to infinity) are related to the classical infinite wallis product: [equation]
on the power of two, three and four probes. an adaptive (n, m, s, t)-scheme is a deterministic scheme for encoding a vector x of m bits with at most n ones by a vector y of s bits, so that any bit of x can be determined by t adaptive probes to y. a non-adaptive (n, m, s, t)-scheme is defined analogously. the study of such schemes arises in the investigation of the static membership problem in the bitprobe model. answering a question of buhrman, miltersen, radhakrishnan and venkatesh [sicomp 2002] we present adaptive (n, m, s, 2) schemes with s < m for all n satisfying 4n2 + 4n < m and adaptive (n, m, s, 2) schemes with s = o(m) for all n = o(log m). we further show that there are adaptive (n, m, s, 3)-schemes with s = o(m) for all n = o(m), settling a problem of radhakrishnan, raman and rao [esa 2001], and prove that there are non-adaptive (n, m, s, 4)-schemes with s = o(m) for all n = o(m). therefore, three adaptive probes or four non-adaptive probes already suffice to obtain a significant saving in space compared to the total length of the input vector. lower bounds are discussed as well.
maximum independent set of rectangles. we study the maximum independent set of rectangles (misr) problem: given a collection r of n axis-parallel rectangles, find a maximum-cardinality subset of disjoint rectangles. misr is a special case of the classical maximum independent set problem, where the input is restricted to intersection graphs of axis-parallel rectangles. due to its many applications, ranging from map labeling to data mining, misr has received a significant amount of attention from various research communities. since the problem is np-hard, the main focus has been on the design of approximation algorithms. several groups of researches have independently suggested o(log n)-approximation algorithms for misr, and this remained the best currently known approximation factor for the problem. the main result of our paper is an o(log log n)-approximation algorithm for misr. our algorithm combines existing approaches for solving special cases of the problem, in which the input set of rectangles is restricted to containing specific intersection types, with new insights into the combinatorial structure of sets of intersecting rectangles in the plane. we also consider a generalization of misr to higher dimensions, where rectangles are replaced by d-dimensional hyper-rectangles. our results for misr imply an o((log n)d&minus;2 log log n)-approximation algorithm for this problem, improving upon the best previously known o((log n)d&minus;1)-approximation.
almost all hypergraphs without fano planes are bipartite. the hypergraph of the fano plane is the unique 3-uniform hypergraph with 7 triples on 7 vertices in which every pair of vertices is contained in a unique triple. this hypergraph is not 2-colorable, but becomes so on deleting any hyperedge from it. we show that taking uniformly at random a labeled 3-uniform hypergraph h on n vertices not containing the hypergraph of the fano plane, h turns out to be 2-colorable with probability at least 1 -- 2-&omega;(n2). for the proof of this result we will study structural properties of fano-free hypergraphs.
fast edge orientation for unweighted graphs. we consider an unweighted undirected graph with n vertices, m edges, and edge-connectivity 2k. the weak edge orientation problem requires that the edges of this graph be oriented so the resulting directed graph is at least k edge-connected. nash-williams proved the existence of such orientations and subsequently frank [6], gabow [7], and nagamochi-ibaraki [12] gave algorithmic constructions. all of these algorithms took time at least quadratic in n. we provide the first sub-quadratic (in n) algorithm for this problem. our algorithm takes &otilde;(nk4 + m) time. this improves the previous best bounds of &otilde;(n2k2 + m) by gabow [7] and &otilde;(n2m) by nagamochi-ibaraki [12] when k &le; &radic;n. indeed, many real networks have k &lt; n. our algorithm uses the fast edge splitting paradigm introduced by bhalgat et al. [2]. we seek to split out a large fraction of the vertices, recurse on the resulting graph, and then put back the split-off vertices. the main challenge we face is that only vertices with even degree may be split-off in an undirected graph and there may not be any such vertex in the current graph. the edge orientation algorithms of gabow and nagamochi-ibaraki as well as frank's proof are based on showing the existence of at least two even degree vertices (in fact, vertices with degree 2k) in a 2k minimally connected graph. we generalize this to show that in any edge minimal 2k edge-connected graph, there are at least n/3 even degree vertices. these vertices are then split-off. our next challenge is to drop edges from the given graph so it remains 2k connected and yet has &omega;(n) even degree vertices. we provide an algorithm that discards edges specifically to produce &omega;(n) even degree vertices while maintaining connectivity 2k and takes time &otilde;(nk4 + m). note that this algorithm does not necessarily make the graph edge-minimally 2k edge-connected. we also briefly outline an &otilde;(nk5 + m) time algorithm that achieves edge-minimality which improves the previous best bound of &otilde;(m + n2k2) by gabow [7].
speed scaling with an arbitrary power function. all of the theoretical speed scaling research to date has assumed that the power function, which expresses the power consumption p as a function of the processor speed s, is of the form p = s&alpha;, where &alpha; > 1 is some constant. motivated in part by technological advances, we initiate a study of speed scaling with arbitrary power functions. we consider the problem of minimizing the total flow plus energy. our main result is a (3+&epsilon;)-competitive algorithm for this problem, that holds for essentially any power function. we also give a (2+&epsilon;)-competitive algorithm for the objective of fractional weighted flow plus energy. even for power functions of the form s&alpha;, it was not previously known how to obtain competitiveness independent of &alpha; for these problems. we also introduce a model of allowable speeds that generalizes all known models in the literature.
analysis of scalar fields over point cloud data. given a real-valued function f defined over some metric space x, is it possible to recover some structural information about f from the sole information of its values at a finite set l &sube; x of sample points, whose pairwise distances in x are given? we provide a positive answer to this question. more precisely, taking advantage of recent advances on the front of stability for persistence diagrams, we introduce a novel algebraic construction, based on a pair of nested families of simplicial complexes built on top of the point cloud l, from which the persistence diagram of f can be faithfully approximated. we derive from this construction a series of algorithms for the analysis of scalar fields from point cloud data. these algorithms are simple and easy to implement, have reasonable complexities, and come with theoretical guarantees. to illustrate the generality of the approach, we present some experimental results obtained in various applications, ranging from clustering to sensor networks (see the electronic version of the paper for color pictures).
appointment scheduling with discrete random durations. we consider the problem of determining optimal appointment schedule for a given sequence of jobs (e.g., medical procedures) on a single processor (e.g., operating room, examination facility), to minimize the expected total underage and overage costs when each job has a random processing duration given by a joint discrete probability distribution. simple conditions on the cost rates imply that the objective function is submodular and l-convex. then there exists an optimal appointment schedule which is integer and can be found in polynomial time. our model can handle a given due date for the total processing (e.g., end of day for an operating room) after which overtime is incurred and, no-shows and emergencies.
combinatorial algorithms for nearest neighbors, near-duplicates and small-world design. we study the so called combinatorial framework for algorithmic problems in similarity spaces. namely, the input dataset is represented by a comparison oracle that given three points x, y, y' answers whether y or y' is closer to x. we assume that the similarity order of the dataset satisfies the four variations of the following disorder inequality: if x is the a'th most similar object to y and y is the b'th most similar object to z, then x is among the d(a + b) most similar objects to z, where d is a relatively small disorder constant. though the oracle gives much less information compared to the standard general metric space model where distance values are given, one can still design very efficient algorithms for various fundamental computational tasks. for nearest neighbor search we present deterministic and exact algorithm with almost linear time and space complexity of preprocessing, and near-logarithmic time complexity of search. then, for near-duplicate detection we present the first known deterministic algorithm that requires just near-linear time + time proportional to the size of output. finally, we show that for any dataset satisfying the disorder inequality a visibility graph can be constructed: all outdegrees are near-logarithmic and greedy routing deterministically converges to the nearest neighbor of a target in logarithmic number of steps. the later result is the first known work-around for navarro's impossibility of generalizing delaunay graphs. the technical contribution of the paper consists of handling "false positives" in data structures and an algorithmic technique up-aside-down-filter.
testing halfspaces. this paper addresses the problem of testing whether a boolean-valued function f is a halfspace, i.e. a function of the form f(x) = sgn(w &middot; x - &theta;). we consider halfspaces over the continuous domain rn (endowed with the standard multivariate gaussian distribution) as well as halfspaces over the boolean cube {&minus;1, 1}n (endowed with the uniform distribution). in both cases we give an algorithm that distinguishes halfspaces from functions that are &epsilon;-far from any halfspace using only poly(1/&epsilon;) queries, independent of the dimension n. two simple structural results about halfspaces are at the heart of our approach for the gaussian distribution: the first gives an exact relationship between the expected value of a halfspace f and the sum of the squares of f's degree-1 hermite coefficients, and the second shows that any function that approximately satisfies this relationship is close to a halfspace. we prove analogous results for the boolean cube {&minus;1, 1}n (with fourier coefficients in place of hermite coefficients) for balanced halfspaces in which all degree-1 fourier coefficients are small. dealing with general halfspaces over {&minus;1, 1}n poses significant additional complications and requires other ingredients. these include "cross-consistency" versions of the results mentioned above for pairs of halfspaces with the same weights but different thresholds; new structural results relating the largest degree-1 fourier coefficient and the largest weight in unbalanced halfspaces; and algorithmic techniques from recent work on testing juntas [fkr+02].
packing multiway cuts in capacitated graphs. we consider the following "multiway cut packing" problem in undirected graphs: given a graph g = (v, e) and k commodities, each corresponding to a set of terminals located at different vertices in the graph, our goal is to produce a collection of cuts {e1, ..., ek} such that ei is a multiway cut for commodity i and the maximum load on any edge is minimized. the load on an edge is defined to be the number of cuts in the solution containing the edge. in the capacitated version of the problem the goal is to minimize the maximum relative load on any edge---the ratio of the edge's load to its capacity. multiway cut packing arises in the context of graph labeling problems where we are given a partial labeling of a set of items and a neighborhood structure over them, and the goal, informally stated, is to complete the labeling in the most consistent way. this problem was introduced by rabani, schulman, and swamy (soda'08), who developed an o(log n/log log n) approximation for it in general graphs, as well as an improved o(log2 k) approximation in trees. here n is the number of nodes in the graph. we present the first constant factor approximation for this problem in arbitrary undirected graphs. our lp-rounding-based algorithm guarantees a maximum edge load of at most 8opt + 4 in general graphs. our approach is based on the observation that every instance of the problem admits a laminar solution (that is, no pair of cuts in the solution crosses) that is near-optimal.
a unified approach to distance-two colouring of planar graphs. we introduce the notion of (a, b)-colouring of a graph: for given vertex sets a, b, this is a colouring of the vertices in b so that both adjacent vertices and vertices with a common neighbour in a receive different colours. this concept generalises the notion of colouring the square of graphs and of cyclic colouring of plane graphs. we prove a general result which implies asymptotic versions of wegner's and borodin's conjecture on these two colourings. using a recent approach of havet et al., we reduce the problem to edge-colouring of multigraphs and then use kahn's result that the list chromatic index is close from the fractional chromatic index. our results are based on a strong structural lemma for planar graphs which also implies that the size of a clique in the square of a planar graph of maximum degree &delta; is at most 3/2 &delta; plus a constant.
the uniform hardcore lemma via approximate bregman projections. we give a simple, more efficient and uniform proof of the hard-core lemma, a fundamental result in complexity theory with applications in machine learning and cryptography. our result follows from the connection between boosting algorithms and hard-core set constructions discovered by klivans and servedio [11]. informally stated, our result is the following: suppose we fix a family of boolean functions. assume there is an efficient algorithm which for every input length and every smooth distribution (i.e. one that doesn't assign too much weight to any single input) over the inputs produces a circuit such that the circuit computes the boolean function noticeably better than random. then, there is an efficient algorithm which for every input length produces a circuit that computes the function correctly on almost all inputs. our algorithm significantly simplifies previous proofs of the uniform and the non-uniform hard-core lemma, while matching or improving the previously best known parameters. the algorithm uses a generalized multiplicative update rule combined with a natural notion of approximate bregman projection. bregman projections are widely used in convex optimization and machine learning. we present an algorithm which efficiently approximates the bregman projection onto the set of high density measures when the kullback-leibler divergence is used as a distance function. our algorithm has a logarithmic runtime over any domain from which we can efficiently sample. high density measures correspond to smooth distributions which arise naturally, for instance, in the context of online learning. hence, our technique may be of independent interest.
stepwise randomized combinatorial auctions achieve revenue monotonicity. in combinatorial auctions that use vcg, a seller can sometimes increase revenue by dropping bidders (see e.g. [5]). in our previous work [26], we showed that such failures of "revenue monotonicity" occur under an extremely broad range of deterministic strategyproof combinatorial auction mechanisms, even when bidders have "known single-minded" valuations. in this work we consider the question of whether revenue monotonic, strategyproof mechanisms for such bidders can be found in the broader class of randomized mechanisms. we demonstrate that---surprisingly- such mechanisms do exist, show how they can be constructed, and consider algorithmic techniques for implementing them in polynomial time. more formally, we characterize a class of randomized mechanisms defined for known single-minded bidders that are strategyproof and revenue monotonic, and furthermore satisfy some other desirable properties, namely participation, consumer sovereignty and maximality, representing the mechanism as a solution to a quadratically constrained linear program (qclp). we prove that the qclp is always feasible (i.e., for all bidder valuations) and give its solution analytically. furthermore, we give an algorithm for running such a mechanism in time polynomial in the number of bidders and goods; this is interesting because constructing an instance of such mechanisms from our qclp formulation in a naive way can require exponential time.
a nearly linear time algorithm for the half integral parity disjoint paths packing problem. we consider the following problem, which is called the half integral parity disjoint paths packing problem. input: a graph g, k pair of vertices (s1, t1), (s2, t2), ...,(sk, tk) in g (which are sometimes called terminals), and a parity li for each i with 1 &le; i &le; k, where li = 0 or 1. output: paths p1, ..., pk in g such that pi joins si and ti for i = 1, 2, ..., k and parity of length of the path pi is li, i.e, if li = 0, then length of pi is even, and if li = 1, then length of pi is odd for i = 1, 2, ..., k. in addition, each vertex is on at most two of these paths. we present an o(m&alpha;(m, n) log n) algorithm for fixed k, where n, m are the number of vertices and the number of edges, respectively, and the function &alpha;(m, n) is the inverse of the ackermann function (see by tarjan [43]). this is the first polynomial time algorithm for this problem, and generalizes polynomial time algorithms by kleinberg [23] and kawarabayashi and reed [20], respectively, for the half integral disjoint paths packing problem, i.e., without the parity requirement. as with the robertson-seymour algorithm to solve the k disjoint paths problem, in each iteration, we would like to either use a huge clique minor as a "crossbar", or exploit the structure of graphs in which we cannot find such a minor. here, however, we must maintain the parity of the paths and can only use an "odd clique minor". we must also describe the structure of those graphs in which we cannot find such a minor and discuss how to exploit it. we also have algorithms running in o(m(1 + &epsilon;)) time for any &epsilon; > 0 for this problem, if k is up to o(log log log n) for general graphs, up to o(log log n) for planar graphs, and up to o(log log n/g) for graphs on the surface, where g is euler genus. furthermore, if k is fixed, then we have linear time algorithms for the planar case and for the bounded genus case.
persistent homology for kernels, images, and cokernels. motivated by the measurement of local homology and of functions on noisy domains, we extend the notion of persistent homology to sequences of kernels, images, and cokernels of maps induced by inclusions in a filtration of pairs of spaces. specifically, we note that persistence in this context is well defined, we prove that the persistence diagrams are stable, and we explain how to compute them.
asymptotically optimal frugal colouring. we prove that every graph with maximum degree @d can be properly (@d+1)-coloured so that no colour appears more than o(log@d/loglog@d) times in the neighbourhood of any vertex. this is best possible up to the constant multiple in the o(-) term.
string hashing for linear probing. linear probing is one of the most popular implementations of dynamic hash tables storing all keys in a single array. when we get a key, we first hash it to a location. next we probe consecutive locations until the key or an empty location is found. at stoc'07, pagh et al. presented data sets where the standard implementation of 2-universal hashing leads to an expected number of &omega;(log n) probes. they also showed that with 5-universal hashing, the expected number of probes is constant. unfortunately, we do not have 5-universal hashing for, say, variable length strings. when we want to do such complex hashing from a complex domain, the generic standard solution is that we first do collision free hashing (w.h.p.) into a simpler intermediate domain, and second do the complicated hash function on this intermediate domain. our contribution is that for an expected constant number of linear probes, it is suffices that each key has o(1) expected collisions with the first hash function, as long as the second hash function is 5-universal. this means that the intermediate domain can be n times smaller, and such a smaller intermediate domain typically means that the overall hash function can be made simpler and at least twice as fast. the same doubling of hashing speed for o(1) expected probes follows for most domains bigger than 32-bit integers, e.g., 64-bit integers and fixed length strings. in addition, we study how the overhead from linear probing diminishes as the array gets larger, and what happens if strings are stored directly as intervals of the array. these cases were not considered by pagh et al.
an improved approximation algorithm for the column subset selection problem. we consider the problem of selecting the "best" subset of exactly k columns from an m x n matrix a. in particular, we present and analyze a novel two-stage algorithm that runs in o(min{mn2, m2n}) time and returns as output an m x k matrix c consisting of exactly k columns of a. in the first stage (the randomized stage), the algorithm randomly selects o(k log k) columns according to a judiciously-chosen probability distribution that depends on information in the top-k right singular subspace of a. in the second stage (the deterministic stage), the algorithm applies a deterministic column-selection procedure to select and return exactly k columns from the set of columns selected in the first stage. let c be the m x k matrix containing those k columns, let pc denote the projection matrix onto the span of those columns, and let ak denote the "best" rank-k approximation to the matrix a as computed with the singular value decomposition. then, we prove that [equation] with probability at least 0.7. this spectral norm bound improves upon the best previously-existing result (of gu and eisenstat [21]) for the spectral norm version of this column subset selection problem. we also prove that [equation] with the same probability. this frobenius norm bound is only a factor of &radic;k log k worse than the best previously existing existential result and is roughly o(&radic;k!) better than the best previous algorithmic result (both of deshpande et al. [11]) for the frobenius norm version of this column subset selection problem.
high rate fingerprinting codes and the fingerprinting capacity. including a unique code in each copy of a distributed document is an effective way of fighting intellectual piracy. codes designed for this purpose that are secure against collusion attacks are called fingerprinting codes. in this paper we consider fingerprinting with the marking assumption and design codes that achieve much higher rates than previous constructions. we conjecture that these codes attain the maximum possible rate (the fingerprinting capacity) for any fixed number of pirates. we prove new upper bounds for the fingerprinting capacity that are not far from the rate of our codes. on the downside the accusation algorithm of our codes are much slower than those of earlier codes. we introduce the novel model of weak fingerprinting codes where one pirate should be caught only if the identity of all other pirates are revealed. we construct fingerprinting codes in this model with improved rates but our upper bound on the rate still applies. in fact, these improved codes achieve the fingerprinting capacity of the weak model by a recent upper bound. using analytic techniques we compare the rates of our codes in the standard model and the rates of the optimal codes in the weak model. to our surprise these rates asymptotically agree, that is, their ratio tends to 1 as t goes to infinity. although we cannot prove that each one of our codes in the standard model achieves the fingerprinting capacity, this proves that asymptotically they do.
paging and list update under bijective analysis. it has long been known that for the paging problem in its standard form, competitive analysis cannot adequately distinguish algorithms based on their performance: there exists a vast class of algorithms which achieve the same competitive ratio, ranging from extremely naive and inefficient strategies (such as flush-when-full), to strategies of excellent performance in practice (such as least-recently-used and some of its variants). a similar situation arises in the list update problem: in particular, under the cost formulation studied by mart&iacute;nez and roura [tcs 2000] and munro [esa 2000] every list update algorithm has, asymptotically, the same competitive ratio. several refinements of competitive analysis, as well as alternative performance measures have been introduced in the literature, with varying degrees of success in narrowing this disconnect between theoretical analysis and empirical evaluation. in this paper we study these two fundamental online problems under the framework of bijective analysis [angelopoulos, dorrigiv and l&oacute;pez-ortiz, soda 2007 and latin 2008]. this is an intuitive technique which is based on pairwise comparison of the costs incurred by two algorithms on sets of request sequences of the same size. coupled with a well-established model of locality of reference due to albers, favrholdt and giel [jcss 2005], we show that least-recently-used and move-to-front are the unique optimal algorithms for paging and list update, respectively. prior to this work, only measures based on average-cost analysis have separated lru and mtf from all other algorithms. given that bijective analysis is a fairly stringent measure (and also subsumes average-cost analysis), we prove that in a strong sense lru and mtf stand out as the best algorithms.
robust pca and clustering in noisy mixtures. this paper presents a polynomial algorithm for learning mixtures of logconcave distributions in rn in the presence of malicious noise. that is, each sample is corrupted with some small probability, being replaced by a point about which we can make no assumptions. a key element of the algorithm is robust principle components analysis (pca), which is less susceptible to corruption by noisy points. while noise may cause standard pca to collapse well-separated mixture components so that they are indistinguishable, robust pca preserves the distance between some of the components, making a partition possible. it then recurses on each half of the mixture until every component is isolated. the success of this algorithm requires only a o(log n) factor increase in the required separation between components of the mixture compared to the noiseless case.
optimality of belief propagation for random assignment problem. the assignment problem concerns finding the minimum-cost perfect matching in a complete weighted n x n bipartite graph. any algorithm for this classical question clearly requires &omega;(n2) time, and the best known one (edmonds and karp, 1972) finds solution in o(n3). for decades, it has remained unknown whether optimal computation time is closer to n3 or n2. we provide answer to this question for random instance of assignment problem. specifically, we establish that belief propagation finds solution in o(n2) time when edge-weights are i.i.d. with light tailed distribution.
linear-time algorithms for geometric graphs with sublinearly many crossings. we provide linear-time algorithms for geometric graphs with sublinearly many crossings. that is, we provide algorithms running in o(n) time on connected geometric graphs having n vertices and k crossings, where k is smaller than n by an iterated logarithmic factor. specific problems we study include voronoi diagrams and single-source shortest paths. our algorithms all run in linear time in the standard comparison-based computational model; hence, we make no assumptions about the distribution or bit complexities of edge weights, nor do we utilize unusual bit-level operations on memory words. instead, our algorithms are based on a planarization method that "zeroes in" on edge crossings, together with methods for extending planar separator decompositions to geometric graphs with sublinearly many crossings. incidentally, our planarization algorithm also solves an open computational geometry problem of chazelle for triangulating a self-intersecting polygonal chain having n segments and k crossings in linear time, for the case when k is sublinear in n by an iterated logarithmic factor.
constructing laplace operator from point clouds in . we present an algorithm for approximating the laplace-beltrami operator from an arbitrary point cloud obtained from a k-dimensional manifold embedded in the d-dimensional space. we show that this pcd laplace (point-cloud data laplace) operator converges to the laplace-beltrami operator on the underlying manifold as the point cloud becomes denser. unlike the previous work, we do not assume that the data samples are independent identically distributed from a probability distribution and do not require a global mesh. the resulting algorithm is easy to implement. we present experimental results indicating that even for point sets sampled from a uniform distribution, pcd laplace converges faster than the weighted graph laplacian. we also show that using our pcd laplacian we can directly estimate certain geometric invariants, such as manifold area.
how hard is it to approximate the best nash equilibrium? the quest for a ptas for nash equilibrium in a two-player game seeks to circumvent the ppad-completeness of an (exact) nash equilibrium by finding an approximate equilibrium, and has emerged as a major open question in algorithmic game theory. a closely related problem is that of finding an equilibrium maximizing a certain objective, such as the social welfare. this optimization problem was shown to be np-hard by gilboa and zemel [games and economic behavior 1989]. however, this np-hardness is unlikely to extend to finding an approximate equilibrium, since the latter admits a quasi-polynomial time algorithm, as proved by lipton, markakis and mehta [proc. of 4th ec, 2003]. we show that this optimization problem, namely, finding in a two-player game an approximate equilibrium achieving large social welfare is unlikely to have a polynomial time algorithm. one interpretation of our results is that the quest for a ptas for nash equilibrium should not extend to a ptas for finding the best nash equilibrium, which stands in contrast to certain algorithmic techniques used so far (e.g. sampling and enumeration). technically, our result is a reduction from a notoriously difficult problem in modern combinatorics, of finding a planted (but hidden) clique in a random graph g(n, 1/2). our reduction starts from an instance with planted clique size k = o(log n). for comparison, the currently known algorithms due to alon, krivelevich and sudakov [random struct. & algorithms, 1998], and krauthgamer and feige [random struct. & algorithms, 2000], are effective for a much larger clique size k = &omega;(&radic;n).
monotone minimal perfect hashing: searching a sorted table with (1) accesses. a minimal perfect hash function maps a set s of n keys into the set {0, 1,..., n -- 1} bijectively. classical results state that minimal perfect hashing is possible in constant time using a structure occupying space close to the lower bound of log e bits per element. here we consider the problem of monotone minimal perfect hashing, in which the bijection is required to preserve the lexicographical ordering of the keys. a monotone minimal perfect hash function can be seen as a very weak form of index that provides ranking just on the set s (and answers randomly outside of s). our goal is to minimise the description size of the hash function: we show that, for a set s of n elements out of a universe of 2w elements, o(n log log w) bits are sufficient to hash monotonically with evaluation time o(log w). alternatively, we can get space o(n log w) bits with o(1) query time. both of these data structures improve a straightforward construction with o(n log w) space and o(log w) query time. as a consequence, it is possible to search a sorted table with o(1) accesses to the table (using additional o(n log log w) bits). our results are based on a structure (of independent interest) that represents a trie in a very compact way, but admits errors. as a further application of the same structure, we show how to compute the predecessor (in the sorted order of s) of an arbitrary element, using o(1) accesses in expectation and an index of o(n log w) bits, improving the trivial result of o(n w) bits. this implies an efficient index for searching a blocked memory.
line transversals of convex polyhedra in . we establish a bound of o(n2k1+&epsilon;), for any &epsilon; > 0, on the combinatorial complexity of the set t of line transversals of a collection p of k convex polyhedra in r3 with a total of n facets, and present a randomized algorithm which computes the boundary of t in comparable expected time. thus, when k &lt; n, the new bounds on the complexity (and construction cost) of t improve upon the previously best known bounds, which are nearly cubic in n. to obtain the above result, we study the set tl0 of line transversals which emanate from a fixed line l0, establish an almost tight bound of o(nk1+&epsilon;) on the complexity of tl0, and provide a randomized algorithm which computes tl0 in comparable expected time. slightly improved combinatorial bounds for the complexity of tl0, and comparable improvements in the cost of constructing this set, are established for two special cases, both assuming that the polyhedra of p are pairwise disjoint: the case where l0 is disjoint from the polyhedra of p, and the case where the polyhedra of p are unbounded in a direction parallel to l0.
the complexity of simulating brownian motion. we analyze the complexity of the walk on spheres algorithm for simulating brownian motion in a domain &omega; &sub;rd. the algorithm, which was first proposed in the 1950s, produces samples from the hitting probability distribution of the brownian motion process on &part;&omega; within an error of &epsilon;. the algorithm is used as a building block for solving a variety of differential equations, including the dirichlet problem. the wos algorithm simulates a bm starting at a point x0 = x in a given bounded domain &omega; until it gets &epsilon;-close to the boundary &part;&omega;. at every step, the algorithm measures the distance dk from its current position xk to &part;&omega; and jumps a distance of dk/2 in a uniformly random direction from xk to obtain xk+1. the algorithm terminates when it reaches xn that is &epsilon;-close to &part;&omega;. it is not hard to see that the algorithm requires at least &omega;(log 1/&epsilon;) steps to converge. only partial results with respect to the upper bound existed. in 1959 m. motoo established an o(log 1/&epsilon;) bound on the running time for convex domains. the results were later generalized for a wider, but still very restricted, class of planar and 3-dimensional domains by g. a. mikhailov (1979). in our earlier work (2007), we established an upper bound of o(log2 1/&epsilon;) on the rate of convergence of wos for arbitrary planar domains. in this paper we introduce energy functions using newton potentials to obtain very general upper bounds on the convergence of the algorithm. special instances of the upper bounds yield the following results for bounded domains &omega;. &bull; if &omega; is a planar domain with connected exterior, the wos converges in o(log 1/&epsilon;) steps; &bull; if &omega; is a domain in r3 with connected exterior, the wos converges in o(log2 1/&epsilon;) steps; &bull; for d > 2, if &omega; is a domain in rd, the wos converges in o((1/&epsilon;)2-4/d) steps; &bull; for d > 3, if &omega; is a domain in rd with connected exterior, the wos converges in o((1/&epsilon;)2--4/(d--1)) steps; &bull; for any d, if &omega; is a domain in rd bounded by a smooth surface &part;&omega;, the wos converges in o(log 1/&epsilon;) steps. we also demonstrate that the bounds are tight, i.e. we construct a domain from each class for which the upper bound is exact. our results give the optimal upper bound of o(log 1/&epsilon;) in many cases for which only a bound polynomial in 1/&epsilon; was previously known.
termination criteria for solving concurrent safety and reachability games. we consider concurrent games played on graphs. at every round of a game, each player simultaneously and independently selects a move; the moves jointly determine the transition to a successor state. two basic objectives are the safety objective to stay forever in a given set of states, and its dual, the reachability objective to reach a given set of states. we present in this paper a strategy improvement algorithm for computing the value of a concurrent safety game, that is, the maximal probability with which player 1 can enforce the safety objective. the algorithm yields a sequence of player-1 strategies which ensure probabilities of winning that converge monotonically to the value of the safety game. our result is significant because the strategy improvement algorithm provides, for the first time, a way to approximate the value of a concurrent safety game from below. since a value iteration algorithm, or a strategy improvement algorithm for reachability games, can be used to approximate the same value from above, the combination of both algorithms yields a method for computing a converging sequence of upper and lower bounds for the values of concurrent reachability and safety games. previous methods could approximate the values of these games only from one direction, and as no rates of convergence are known, they did not provide a practical way to solve these games.
on the complexity of nash equilibria of action-graph games. in light of much recent interest in finding a model of multi-player multi-action games that allows for efficient computation of nash equilibria yet remains as expressive as possible, we investigate the computational complexity of nash equilibria in the recently proposed model of action-graph games (aggs). aggs, introduced by bhat and leyton-brown, are succinct representations of games that encapsulate both local dependencies as in graphical games, and partial indifference to other agents' identities as in anonymous games, which occur in many natural settings such as financial markets. this is achieved by specifying a graph on the set of actions, so that the payoff of an agent for selecting a strategy depends only on the number of agents playing each of the neighboring strategies in the action graph. we present a simple fully polynomial time approximation scheme for computing mixed nash equilibria of aggs with constant degree, constant treewidth and a constant number of agent types (but an arbitrary number of strategies), and extend this algorithm to a broader set of instances. however, the main results of this paper are negative, showing that when either of the latter conditions are relaxed the problem becomes intractable. in particular, we show that even if the action graph is a tree but the number of agent-types is unconstrained, it is np- complete to decide the existence of a pure-strategy nash equilibrium and ppad-complete to compute a mixed nash equilibrium (even an approximate one). similarly for aggs with a constant number of agent types but unconstrained treewidth. these hardness results suggest that, in some sense, our fptas is as strong a positive result as one can expect. in the broader context of trying to pin down the boundary where the equilibria of multi-player games can be computed efficiently, these results complement recent hardness results for graphical games and algorithmic results for anonymous games.
combinatorial algorithms for wireless information flow. a long-standing open question in information theory is to characterize the unicast capacity of a wireless relay network. the difficulty arises due to the complex signal interactions induced in the network, since the wireless channel inherently broadcasts the signals and there is interference among transmissions. recently, avestimehr, diggavi and tse proposed a linear binary deterministic model that takes into account the shared nature of wireless channels, focusing on the signal interactions rather than the background noise. they generalized the min-cut max-flow theorem for graphs to networks of deterministic channels and proved that the capacity can be achieved using information theoretical tools. they showed that the value of the minimum cut is in this case the minimum rank of all the binary adjacency matrices describing source-destination cuts. however, since there exists an exponential number of cuts, identifying the capacity through exhaustive search becomes infeasible. in this paper, we develop a polynomial time algorithm that discovers the relay encoding strategy to achieve the min-cut value in binary linear deterministic (wireless) networks, for the case of a unicast connection. our algorithm crucially uses a notion of linear independence between edges to calculate the capacity in polynomial time. moreover, we can achieve the capacity by using very simple onebit processing at the intermediate nodes, thereby constructively yielding finite length strategies that achieve the unicast capacity of the linear deterministic (wireless) relay network.
improved approximation algorithms for scheduling with fixed jobs. we study two closely related problems in non-preemptive scheduling of sequential jobs on identical parallel machines. in these two settings there are either fixed jobs or non-availability intervals during which the machines are not available; in either case, the objective is to minimize the makespan. both formulations have different applications, e.g. in turnaround scheduling or overlay computing. for both problems we contribute approximation algorithms with an improved ratio of 3/2 + &epsilon;, respectively. for scheduling with fixed jobs, a lower bound of 3/2 on the approximation ratio has been obtained by scharbrodt, steger & weisser; for scheduling with non-availability we provide the same lower bound. in total, our approximation ratio for both problems is essentially tight via suitable inapproximability results. we use dual approximation, creation of a gap structure and job configurations, and a ptas for the multiple subset sum problem. however, the main feature of our algorithms is a new technique for the assignment of large jobs via flexible rounding. our new technique is based on an interesting cyclic shifting argument in combination with a network flow model for the assignment of jobs to large gaps.
a generic top-down dynamic-programming approach to prefix-free coding. given a probability distribution over a set of n words to be transmitted, the huffman coding problem is to find a minimal-cost prefix free code for transmitting those words. the basic huffman coding problem can be solved in o(n log n) time but variations are more difficult. one of the standard techniques for solving these variations utilizes a top-down dynamic programming approach. in this paper we show that this approach is amenable to dynamic programming speedup techniques, permitting a speedup of an order of magnitude for many algorithms in the literature for such variations as mixed radix, reserved length and one-ended coding. these speedups are immediate implications of a general structural property that permits batching together the calculation of many dp entries.
on the bit-complexity of lempel-ziv compression. one of the most famous and investigated lossless data-compression schemes is the one introduced by lempel and ziv about 30 years ago [37]. this compression scheme is known as "dictionary-based compressor" and consists of squeezing an input string by replacing some of its substrings with (shorter) codewords which are actually pointers to a dictionary of phrases built as the string is processed. surprisingly enough, although many fundamental results are nowadays known about the speed and effectiveness of this compression process (see e.g. [23, 28] and references therein), "we are not aware of any parsing scheme that achieves optimality when the lz77-dictionary is in use under any constraint on the codewords other than being of equal length" [28, pag. 159]. here optimality means to achieve the minimum number of bits in compressing each individual input string, without any assumption on its generating source. in this paper we investigate three issues pertaining to the bit-complexity of lz-based compressors, and we design algorithms which achieve bit-optimality in the compressed output size by taking efficient/optimal time and optimal space. these theoretical results will be sustained by some experiments that will compare our novel lz-based compressors against the most popular compression tools (like gzip, bzip2) and state-of-the-art compressors (like the booster of [14, 13]).
efficient algorithms on sets of permutations, dominance, and real-weighted apsp. sets of permutations play an important role in the design of some efficient algorithms. in this paper we design two algorithms that manipulate sets of permutations. both algorithms, each solving a different problem, use fast matrix multiplication techniques to achieve a significant improvement in the running time over the naive solutions. for a set of permutations p &sub; sn we say that i k-dominates j if the number of permutations &pi; &isin; p for which &pi;(i) < &pi;(j) is k. the dominance matrix of p is the n x n matrix dp where dp(i, j) = k if and only if i k-dominates j. we give an efficient algorithm for computing dp using fast rectangular matrix multiplication. in particular, when |p| = n our algorithm runs in o(n2.684) time. computing the dominance matrix of permutations is computationally equivalent to the dominance problem in computational geometry. thus, our algorithm slightly improves upon a well-known o(n2.688) time algorithm of matousek for the dominance problem. permutation dominance is used, together with several other ingredients, to obtain a truly sub-cubic algorithm for the all pairs shortest paths (apsp) problem in real-weighted directed graphs, where the number of distinct weights emanating from each vertex is o(n0.338). a special case of this algorithm implies an o(n2.842) time algorithm for real vertex-weighted apsp, which slightly improves a recent result of chan [stoc-07]. a set of permutations p &sub; sn is fully expanding if the product of any two elements of p yields a distinct permutation. stated otherwise, |p2| = |p|2 where p2 &sub; sn is the set of products of two elements of p. we present a randomized algorithm that computes |p2| and hence decides if p is fully expanding. the algorithm also produces a table that, for any &sigma;1, &sigma;2, &sigma;3, &sigma;4 &isin; p, answers the query &sigma;1&sigma;2 = &sigma;3&sigma;4 in &otilde;(1) time. the algorithm uses, among other ingredients, a combination of fast matrix multiplication and polynomial identity testing. in particular, for |p| = n our algorithm runs in o(n&omega;) time where &omega; < 2.376 is the matrix multiplication exponent. we note that the naive deterministic solution for this problem requires &theta;(n3) time.
transitive-closure spanners. we define the notion of a transitive-closure spanner of a directed graph. given a directed graph g = (v, e) and an integer k &ge; 1, a k-transitive-closure-spanner (k-tc-spanner) of g is a directed graph h = (v, eh) that has (1) the same transitive-closure as g and (2) diameter at most k. these spanners were studied implicitly in access control, property testing, and data structures, and properties of these spanners have been rediscovered over the span of 20 years. we bring these areas under the unifying framework of tc-spanners. we abstract the common task implicitly tackled in these diverse applications as the problem of constructing sparse tc-spanners. we study the approximability of the size of the sparsest k-tc-spanner for a given digraph. our technical contributions fall into three categories: algorithms for general digraphs, inapproximability results, and structural bounds for a specific graph family which imply an efficient algorithm with a good approximation ratio for that family. algorithms. we present two efficient deterministic algorithms that find k-tc-spanners of near optimal size. the first algorithm gives an &otilde;(n1-1/k)-approximation for k > 2. our method, based on a combination of convex programming and sampling, yields the first sublinear approximation ratios for (1) directed k-spanner, a well-studied generalization of k-tc-spanner, and (2) its variants client/server directed k-spanner, and the k-diameter spanning subgraph. this resolves the main open question of elkin and peleg (ipco, 2001). the second algorithm, specific to the k-tc-spanner problem, gives an &otilde;(n/k2)-approximation. it shows that for k = &omega;(&radic;n), our problem has a provably better approximation ratio than directed k-spanner and its variants. this algorithm also resolves an open question of hesse (soda, 2003). inapproximability. our main technical contribution is a pair of strong inapproximability results. we resolve the approximability of 2-tc-spanners, showing that it is &theta;(log n) unless p = np. for constant k &ge; 3, we prove that the size of the sparsest k-tc-spanner is hard to approximate within 2log1-&epsilon; n, for any &epsilon; > 0, unless np &sube; dtime (npolylog n). our hardness result helps explain the difficulty in designing general efficient solutions for the applications above, and it cannot be improved without resolving a long-standing open question in complexity theory. it uses an involved application of generalized butterfly and broom graphs, as well as noise-resilient transformations of hard problems, which may be of independent interest. structural bounds. finally, we study the size of the sparsest tc-spanner for h-minor-free digraphs, which include planar, bounded genus, and bounded tree-width graphs, explicitly investigated in applications above. we show that every h-minor-free digraph has an efficiently con-structible k-tc-spanner of size &otilde;(n). this implies an &otilde;(1)-approximation algorithm for this family. furthermore, using our insight that 2-tc-spanners yield property testers, we obtain a monotonicity tester with o(log2 n/&epsilon;) queries for any poset whose transitive reduction is an h-minor free digraph. this improves and generalizes the previous &theta;(&radic;n log n/&epsilon;)-query tester of fischer et al (stoc, 2002).
size complexity of volume meshes vs. surface meshes. typical volume meshes in three dimensions are designed to conform to an underlying two-dimensional surface mesh, with volume mesh element size growing larger away from the surface. the surface mesh may be uniformly spaced or highly graded, and may have fine resolution due to extrinsic mesh size concerns. when we desire that such a volume mesh have good aspect ratio, we require that some space-filling scaffold vertices be inserted off the surface. we analyze the number of scaffold vertices in a setting that encompasses many existing volume meshing algorithms. we show that under simple preconditions, the number of scaffold vertices will be linear in the number of surface vertices.
equilibria of atomic flow games are not unique. in routing games with infinitesimal players, it follows from well-known convexity arguments that equilibria exist and are unique (up to induced delays, and under weak assumptions on delay functions). in routing games with players that control large amounts of flow, uniqueness has been demonstrated only in limited cases: in 2-terminal, nearly-parallel graphs; when all players control exactly the same amount of flow; when latency functions are polynomials of degree at most three. in this work, we answer an open question posed by cominetti, correa, and stier-moses (icalp 2006) and show that there may be multiple equilibria in atomic player routing games. we demonstrate this multiplicity via two specific examples. in addition, we show our examples are topologically minimal by giving a complete characterization of the class of network topologies for which unique equilibria exist. our proofs and examples are based on a novel characterization of these topologies in terms of sets of circulations.
on the approximability of dodgson and young elections. the voting rules proposed by dodgson and young are both designed to find the alternative closest to being a condorcet winner, according to two different notions of proximity; the score of a given alternative is known to be hard to compute under either rule. in this paper, we put forward two algorithms for approximating the dodgson score: an lp-based randomized rounding algorithm and a deterministic greedy algorithm, both of which yield an o(log m) approximation ratio, where m is the number of alternatives; we observe that this result is asymptotically optimal, and further prove that our greedy algorithm is optimal up to a factor of 2, unless problems in np have quasi-polynomial time algorithms. although the greedy algorithm is computationally superior, we argue that the randomized rounding algorithm has an advantage from a social choice point of view. further, we demonstrate that computing any reasonable approximation of the ranking produced by dodgson's rule is np-hard. this result provides a complexity-theoretic explanation of sharp discrepancies that have been observed in the social choice theory literature when comparing dodgson elections with simpler voting rules. finally, we show that the problem of calculating the young score is np-hard to approximate by any factor. this leads to an inapproximability result for the young ranking.
expanders via random spanning trees. motivated by the problem of routing reliably and scalably in a graph, we introduce the notion of a splicer, the union of spanning trees of a graph. we prove that for any bounded-degree n-vertex graph, the union of two random spanning trees approximates the expansion of every cut of the graph to within a factor of o(log n). for the random graph gn, p, for p = &omega;(log n/n), we give a randomized algorithm for constructing two spanning trees whose union is an expander. this is suggested by the case of the complete graph, where we prove that two random spanning trees give an expander. the construction of the splicer is elementary; each spanning tree can be produced independently using an algorithm by aldous and broder: a random walk in the graph with edges leading to previously unvisited vertices included in the tree. splicers also turn out to have applications to graph cut-sparsification where the goal is to approximate every cut using only a small subgraph of the original graph. for random graphs, splicers provide simple algorithms for sparsifiers of size o(n) that approximate every cut to within a factor of o(log n).
perfect matchings via uniform sampling in regular bipartite graphs. in this article we further investigate the well-studied problem of finding a perfect matching in a regular bipartite graph. the first nontrivial algorithm, with running time o(mn), dates back to k&ouml;nig's work in 1916 (here m&equals;nd is the number of edges in the graph, 2n is the number of vertices, and d is the degree of each node). the currently most efficient algorithm takes time o(m), and is due to cole et al. &lsqb;2001&rsqb;. we improve this running time to o(min{m, n2.5ln n/d}); this minimum can never be larger than o(n1.75&sqrt;ln n). we obtain this improvement by proving a uniform sampling theorem: if we sample each edge in a d-regular bipartite graph independently with a probability p &equals; o(n ln n/d2) then the resulting graph has a perfect matching with high probability. the proof involves a decomposition of the graph into pieces which are guaranteed to have many perfect matchings but do not have any small cuts. we then establish a correspondence between potential witnesses to nonexistence of a matching (after sampling) in any piece and cuts of comparable size in that same piece. karger's sampling theorem &lsqb;1994a, 1994b&rsqb; for preserving cuts in a graph can now be adapted to prove our uniform sampling theorem for preserving perfect matchings. using the o(m&sqrt;n) algorithm (due to hopcroft and karp &lsqb;1973&rsqb;) for finding maximum matchings in bipartite graphs on the sampled graph then yields the stated running time. we also provide an infinite family of instances to show that our uniform sampling result is tight up to polylogarithmic factors (in fact, up to ln2 n).
approximate euclidean shortest paths amid convex obstacles. we develop algorithms and data structures for the approximate euclidean shortest path problem amid a set p of k convex obstacles in r2 and r3, with a total of n faces. the running time of our algorithms is linear in n, and the size and query time of our data structure are independent of n. we follow a "core-set" based approach, i.e., we quickly compute a small sketch q of p whose size is independent of n and then compute approximate shortest paths with respect to q.
list-color-critical graphs on a fixed surface. a k-list-assignment for a graph g assigns to each vertex v of g a list l(v) of admissible colors, where |l(v)| &ge; k. a graph is k-list-colorable (or k-choosable) if it can be properly colored from the lists for every k-list-assignment. we prove the following conjecture posed by thomassen in 1994: "there are only finitely many list-color-critical graphs with all lists of cardinality at least 5 on any fixed surface." this generalizes the well-known result of thomassen on the usual graph coloring case. we use this theorem and specific parts of its proof to resolve the complexity status of the following problem about k-list-coloring graphs on a fixed surface s, where k is a fixed positive integer. input: a graph g embedded in the surface s. question: is g k-choosable? if not, provide a certificate (a list-color-critical subgraph and the corresponding k-list-assignment). the cases k = 3, 4 are known to be np-hard (actually even &pi;p2-complete), and the cases k = 1, 2 are easy. our main results imply that the problem is tractable for every k &ge; 5. in fact, together with our recent algorithmic result, we are able to solve it in linear time when k &ge; 5. our proof yields even more: if the input graph is k-list-colorable, then for any k-list-assignment l, we can construct an l-coloring of g in linear time. this generalizes the well-known linear-time algorithms for planar graphs by nishizeki and chiba (for 5-coloring), and thomassen (for 5-list-coloring). we also give a polynomial-time algorithm to resolve the following question: input: a graph g in the surface s, and a k-list-assignment l, where k &ge; 5. question: does g admit an l-coloring? if not, provide a certificate for this. if yes, then return an l-coloring. if the graph g is k-list-colorable, then our first result gives a linear time solution. however, the second problem is more general, since it provides a coloring (or a small obstruction) for an arbitrary graph in s. we also use our main theorem to prove another conjecture that was proposed recently by thomassen: "for every fixed surface s, there exists a positive constant c such that every 5-list-colorable graph with n vertices embedded on s, has at least c &middot; 2n distinct 5-list-colorings for every 5-list-assignment for g." thomassen himself proved that this conjecture holds for usual 5-colorings. in addition to all these results, we also made partial progress towards a conjecture of albertson concerning coloring extensions and a progress on similar questions for triangle-free graphs and graphs of larger girth.
on the relative strength of split, triangle and quadrilateral cuts. integer programs defined by two equations with two free integer variables and nonnegative continuous variables have three types of nontrivial facets: split, triangle or quadrilateral inequalities. in this paper, we compare the strength of these three families of inequalities. in particular we study how well each family approximates the integer hull. we show that, in a well defined sense, triangle inequalities provide a good approximation of the integer hull. the same statement holds for quadrilateral inequalities. on the other hand, the approximation produced by split inequalities may be arbitrarily bad.
discounted deterministic markov decision processes and discounted all-pairs shortest paths. we present algorithms for finding optimal strategies for discounted, infinite-horizon, determinsitc markov decision processes (dmdps). our fastest algorithm has a worst-case running time of o(mn), improving the recent bound of o(mn2) obtained by andersson and vorbyov &lsqb;2006&rsqb;. we also present a randomized o(m1/2n2)-time algorithm for finding discounted all-pairs shortest paths (dapsp), improving an o(mn2)-time algorithm that can be obtained using ideas of papadimitriou and tsitsiklis &lsqb;1987&rsqb;.
online story scheduling in web advertising. we study an online job scheduling problem motivated by storyboarding in web advertising, where an advertiser derives value from uninterrupted sequential access to a user surfing the web. the user ceases to browse with probability 1 -- &beta; at each step, independently. stories (jobs) arrive online; job s has length ls and per-unit value vs. a value vs is obtained for every unit of the job that is scheduled consecutively without interruption, discounted for the time at which it is scheduled. jobs can be preempted, but no further value can be derived from the residual unscheduled units of the job. we seek an online algorithm whose total reward is competitive against that of the offline scheduler that knows all jobs in advance. we consider two models based on the maximum delay that can be allowed between the arrival and scheduling of a job. in the first, a job can be scheduled anytime after its arrival; in the second a job is lost unless scheduled immediately upon arrival, preempting a currently running job if needed. the two settings correspond to two natural models of how long an advertiser retains interest in a relevant user. we show that there is, in fact, a sharp separation between what an online scheduler can achieve in these two settings. in the first setting with no deadlines, we give a natural deterministic algorithm with a constant competitive ratio against the offline scheduler. in contrast, we show that in the sharp deadline setting, no (deterministic or randomized) online algorithm can achieve better than a polylogarithmic ratio.
maximal biconnected subgraphs of random planar graphs. let c be a class of labeled connected graphs, and let cn be a graph drawn uniformly at random from graphs in c that contain exactly n vertices. denote by b(&ell;; cn) the number of blocks (i.e., maximal biconnected subgraphs) of cn that contain exactly &ell; vertices, and let lb(cn) be the number of vertices in a largest block of cn. we show that under certain general assumptions on c, cn belongs with high probability to one of the following categories: (1) lb(cn) &sim; cn, for some explicitly given c &equals; c(c), and the second largest block is of order n&alpha;, where 1 > &alpha; &equals; &alpha;(c), or (2) lb(cn) &equals; o(log n), that is, all blocks contain at most logarithmically many vertices. moreover, in both cases we show that the quantity b(&ell;; cn) is concentrated for all &ell; and we determine its expected value. as a corollary we obtain that the class of planar graphs belongs to category (1). in contrast to that, outerplanar and series-parallel graphs belong to category (2).
optimal halfspace range reporting in three dimensions. we give the first optimal solution to a standard problem in computational geometry: three-dimensional halfspace range reporting. we show that n points in 3-d can be stored in a linear-space data structure so that all k points inside a query halfspace can be reported in o(log n + k) time. the data structure can be built in o(n log n) expected time. the previous methods with optimal query time required superlinear (o(n log log n)) space. we also mention consequences, for example, to higher dimensions and to external-memory data structures. as an aside, we partially answer another open question concerning the crossing number in matou&scaron;ek's shallow partition theorem in the 3-d case (a tool used in many known halfspace range reporting methods).
improved smoothed analysis of the -means method. the k-means method is a widely used clustering algorithm. one of its distinguished features is its speed in practice. its worst-case running-time, however, is exponential, leaving a gap between practical and theoretical performance. arthur and vassilvitskii [3] aimed at closing this gap, and they proved a bound of poly(nk, &sigma;&minus;1) on the smoothed running-time of the k-means method, where n is the number of data points and &sigma; is the standard deviation of the gaussian perturbation. this bound, though better than the worst-case bound, is still much larger than the running-time observed in practice. we improve the smoothed analysis of the k-means method by showing two upper bounds on the expected running-time of k-means. first, we prove that the expected running-time is bounded by a polynomial in n&radic;k and &sigma;&minus;1. second, we prove an upper bound of kkd&middot;poly(n, &sigma;&minus;1), where d is the dimension of the data space. the polynomial is independent of k and d, and we obtain a polynomial bound for the expected running-time for k, d &isin; o(&radic;logn/log logn). finally, we show that k-means runs in smoothed polynomial time for one-dimensional instances.
sorting and selection in posets. classical problems of sorting and searching assume an underlying linear ordering of the objects being compared. in this paper, we study these problems in the context of partially ordered sets, in which some pairs of objects are incomparable. this generalization is interesting from a combinatorial perspective, and it has immediate applications in ranking scenarios where there is no underlying linear ordering, e.g., conference submissions. it also has applications in reconstructing certain types of networks, including biological networks. our results represent significant progress over previous results from two decades ago by faigle and tur&aacute;n. in particular, we present the first algorithm that sorts a width-w poset of size n with optimal query complexity o(n(w + log n)). we also describe a variant of mergesort with query complexity o(wn log n/w) and total complexity o(w2n log n/w); an algorithm with the same query complexity was given by faigle and tur&aacute;n, but no efficient implementation of that algorithm is known. both our sorting algorithms can be applied with negligible overhead to the more general problem of reconstructing transitive relations. we also consider two related problems: finding the minimal elements, and its generalization to finding the bottom k "levels", called the k-selection problem. we give efficient deterministic and randomized algorithms for finding the minimal elements with o(wn) query and total complexity. we provide matching lower bounds for the query complexity up to a factor of 2 and generalize the results to the k-selection problem. finally, we present efficient algorithms for computing a linear extension of a poset and computing the heights of all elements.
better algorithms for benign bandits. the online multi-armed bandit problem and its generalizations are repeated decision making problems, where the goal is to select one of several possible decisions in every round, and incur a cost associated with the decision, in such a way that the total cost incurred over all iterations is close to the cost of the best fixed decision in hindsight. the difference in these costs is known as the regret of the algorithm. the term bandit refers to the setting where one only obtains the cost of the decision used in a given iteration and no other information. perhaps the most general form of this problem is the non-stochastic bandit linear optimization problem, where the set of decisions is a convex set in some euclidean space, and the cost functions are linear. only recently an efficient algorithm attaining &otilde; (&radic;t) regret was discovered in this setting. in this paper we propose a new algorithm for the bandit linear optimization problem which obtains a regret bound of &otilde; (&radic;q), where q is the total variation in the cost functions. this regret bound, previously conjectured to hold in the full information case, shows that it is possible to incur much less regret in a slowly changing environment even in the bandit setting. our algorithm is efficient and applies several new ideas to bandit optimization such as reservoir sampling.
additive approximation algorithms for list-coloring minor-closed class of graphs. it is known that computing the list chromatic number is harder than computing the chromatic number (assuming np &ne; conp). in fact, the problem of deciding whether a given graph is f-list-colorable for a function f: v &rarr; {c -1, c} for c &ge; 3 is &pi;p2-complete. in general, it is believed that approximating list coloring is hard for dense graphs. in this paper, we are interested in sparse graphs. more specifically, we deal with nontrivial minor-closed classes of graphs, i.e., graphs excluding some kk minor. we refine the seminal structure theorem of robertson and seymour, and then give an additive approximation for list-coloring within k - 2 of the list chromatic number. this improves the previous multiplicative o(k)-approximation algorithm [20]. clearly our result also yields an additive approximation algorithm for graph coloring in a minor-closed graph class. this result may give better graph colorings than the previous multiplicative 2-approximation algorithm for graph coloring in a minor-closed graph class [6]. our structure theorem is of independent interest in the sense that it gives rise to a new insight on well-connected h-minor-free graphs. in particular, this class of graphs can be easily decomposed into two parts so that one part has bounded treewidth and the other part is a disjoint union of bounded-genus graphs. moreover, we can control the number of edges between the two parts. the proof method itself tells us how knowledge of a local structure can be used to gain a global structure, which gives new insight on how to decompose a graph with the help of local-structure information.
shortest paths in directed planar graphs with negative lengths: a linear-space ( log )-time algorithm. we give an o(n log2 n)-time, linear-space algorithm that, given a directed planar graph with positive and negative arc-lengths, and given a node s, finds the distances from s to all nodes.
dual-failure distance and connectivity oracles. spontaneous failure is an unavoidable aspect of all networks, particularly those with a physical basis such as communications networks or road networks. whether due to malicious coordinated attacks or other causes, failures temporarily change the topology of the network and, as a consequence, its connectivity and distance metric. in this paper we look at the problem of efficiently answering connectivity, distance, and shortest route queries in the presence of two node or link failures. our data structure uses &otilde;(n2) space and answers queries in &otilde; (1) time, which is within a polylogarithmic factor of optimal and nearly matches the single-failure distance oracles of demestrescu et al. it may yet be possible to find distance/connectivity oracles capable of handling any fixed number of failures. however, the sheer complexity of our algorithm suggests that moving beyond dual-failures will require a fundamentally different approach to the problem.
three-coloring triangle-free planar graphs in linear time. gr&ouml;tzsch's theorem states that every triangle-free planar graph is 3-colorable, and several relatively simple proofs of this fact were provided by thomassen and other authors. it is easy to convert these proofs into quadratic-time algorithms to find a 3-coloring, but it is not clear how to find such a coloring in linear time (kowalik used a nontrivial data structure to construct an o(n log n) algorithm). we design a linear-time algorithm to find a 3-coloring of a given triangle-free planar graph. the algorithm avoids using any complex data structures, which makes it easy to implement. as a by-product we give a yet simpler proof of gr&ouml;tzsch's theorem.
pairing heaps with (log log ) decrease cost. we give a variation of the pairing heaps for which the time bounds for all the operations match the lower bound proved by fredman for a family of similar self-adjusting heaps. namely, our heap structure requires o(1) for insert and findmin, o(log n) for delete-min, and o(log log n) for decrease-key and meld (all the bounds are in the amortized sense except for find-min).
fast algorithms for (max, min)-matrix multiplication and bottleneck shortest paths. given a directed graph with a capacity on each edge, the all-pairs bottleneck paths (apbp) problem is to determine, for all vertices s and t, the maximum flow that can be routed from s to t. for dense graphs this problem is equivalent to that of computing the (max, min)-transitive closure of a real-valued matrix. in this paper, we give a (max, min)-matrix multiplication algorithm running in time o(n(3+&omega;)/2) &le; o(n2.688), where &omega; is the exponent of binary matrix multiplication. our algorithm improves on a recent o(n2+&omega;/3) &le; o(n2.792)- time algorithm of vassilevska, williams, and yuster. although our algorithm is slower than the best apbp algorithm on vertex capacitated graphs, running in o(n2.575) time, it is just as efficient as the best algorithm for computing the dominance product, a problem closely related to (max, min)-matrix multiplication. our techniques can be extended to give subcubic algorithms for related bottleneck problems. the all-pairs bottleneck shortest paths problem (apbsp) asks for the maximum flow that can be routed along a shortest path. we give an apbsp algorithm for edge-capacitated graphs running in o(n(3+&omega;)/2) time and a slightly faster o(n2.657)-time algorithm for vertex-capactitated graphs. the second algorithm significantly improves on an o(n2.859)-time apbsp algorithm of shapira, yuster, and zwick. our apbsp algorithms make use of new hybrid products we call the distance-max-min product and dominance-distance product.
a simple combinatorial algorithm for submodular function minimization. this paper presents a new simple algorithm for minimizing submodular functions. for integer valued submodular functions, the algorithm runs in o(n6eo log nm) time, where n is the cardinality of the ground set, m is the maximum absolute value of the function value, and eo is the time for function evaluation. the algorithm can be improved to run in o ((n4eo+n5)log nm) time. the strongly polynomial version of this faster algorithm runs in o((n5eo + n6) log n) time for real valued general submodular functions. these are comparable to the best known running time bounds for submodular function minimization. the algorithm can also be implemented in strongly polynomial time using only additions, subtractions, comparisons, and the oracle calls for function evaluation. this is the first fully combinatorial submodular function minimization algorithm that does not rely on the scaling method.
biased range trees. a data structure, called a biased range tree, is presented that preprocesses a set s of n points in r2 and a query distribution d for 2-sided orthogonal range counting queries. the expected query time for this data structure, when queries are drawn according to d, matches, to within a constant factor, that of the optimal comparison tree for s and d. the memory and preprocessing requirements of the data structure are o(n log n).
sampling biased lattice configurations using exponential metrics. monotonic surfaces spanning finite regions of zd arise in many contexts, including dna-based self-assembly, card-shuffling and lozenge tilings. we explore how we can sample these surfaces when the distribution is biased to favor higher surfaces. we show that a natural local chain is rapidly mixing with any bias for regions in z2, and for bias &lambda; > d2 in zd, when d > 2. moreover, our bounds on the mixing time are optimal on d-dimensional hyper-cubic regions. the proof uses a geometric distance function and introduces a variant of path coupling in order to handle distances that are exponentially large.
an online mechanism for ad slot reservations with cancellations. many advertisers (bidders) use internet systems to buy display advertisements on publishers' webpages or on traditional media such as radio, tv and newsprint. they seek a simple, online mechanism to reserve ad slots in advance. on the other hand, media publishers (sellers) represent a vast and varying inventory, and they too seek automatic, online mechanisms for pricing and allocating such reservations. we propose and study a simple model for auctioning such ad slot reservations in advance. a seller will display a set of slots at some point t in the future. until t, bidders arrive sequentially and place a bid on the slots they are interested in. the seller must decide immediately whether or not to grant a reservation. our model allows the seller to cancel at any time any reservation made earlier, in which case the holder of the reservation incurs a utility loss amounting to a fraction of her value for the reservation and may also receive a cancellation fee from the seller. our main result is an online mechanism for allocation and pricing in this model with many desirable game-theoretic properties. it is individually rational. winners have an incentive to be honest and bidding one's true value dominates any lower bid. further, it bounds the earnings of speculators who are in the game to obtain the cancellation fees. the mechanism in addition has optimization guarantees. its revenue is within a constant fraction of the a posteriori revenue of the vickrey-clarke-groves (vcg) mechanism which is known to be truthful (in the offline case). our mechanism's efficiency is within a constant fraction of the a posteriori optimally efficient solution. if efficiency also takes into account the utility losses of bidders whose reservation was canceled, we show that our mechanism matches (for appropriate values of the parameters) an upper bound on the competitive ratio of any deterministic online algorithm. our mechanism's technical core is a variant of the online weighted bipartite matching problem where unlike prior variants in which one randomizes edge arrivals or bounds edge weights, we may revoke previously committed edges. our results make no assumptions about bidders' arrival order or value distribution. they still hold if we replace items with elements of a matroid and matchings with independent sets, or if all bidders have additive value for a set of items.
a logarithmic approximation for unsplittable flow on line graphs. we consider the unsplittable flow problem on a line. in this problem, we are given a set of n tasks, each specified by a start time si, an end time ti, a demand di > 0, and a profit pi > 0. a task, if accepted, requires di units of "bandwidth" from time si to ti and accrues a profit of pi. for every time t, we are also specified the available bandwidth ct, and the goal is to find a subset of tasks with maximum profit subject to the bandwidth constraints. in this paper, we present the first polynomial-time o(log n)-approximation algorithm for this problem. no polynomial-time o(n)-approximation was known prior to this work. previous results for this problem were known only in more restrictive settings, in particular, either if the given instance satisfies the so-called "no-bottleneck" assumption: maxi di &le; mint ct, or else if the ratio of the maximum to the minimum demands and ratio of the maximum to the minimum capacities are polynomially (or quasi-polynomially) bounded in n. our result, on the other hand, does not require any of these assumptions. our algorithm is based on a combination of dynamic programming and rounding a natural linear programming relaxation for the problem. while there is an &omega;(n) integrality gap known for this lp relaxation, our key idea is to exploit certain structural properties of the problem to show that instances that are bad for the lp can in fact be handled using dynamic programming.
towards computing the grothendieck constant. the grothendieck constant kg is the smallest constant such that for every d &isin; n and every matrix a = (aij), [equation] where b(d) is the unit ball in rd. despite several efforts [15, 23], the value of the constant kg remains unknown. the grothendieck constant kg is precisely the integrality gap of a natural sdp relaxation for the km, n-quadratic programming problem. the input to this problem is a matrix a = (aij) and the objective is to maximize the quadratic form &sigma;ij aijxiyj over xiyj &isin; [&minus;1, 1]. in this work, we apply techniques from [22] to the km, n-quadratic programming problem. using some standard but non-trivial modifications, the reduction in [22] yields the following hardness result: assuming the unique games conjecture [9], it is np-hard to approximate the km, n-quadratic programming problem to any factor better than the grothendieck constant kg. by adapting a "bootstrapping" argument used in a proof of grothendieck inequality [5], we are able to perform a tighter analysis than [22]. through this careful analysis, we obtain the following new results: &bull; an approximation algorithm for km, n-quadratic programming that is guaranteed to achieve an approximation ratio arbitrarily close to the grothendieck constant kg (optimal approximation ratio assuming the unique games conjecture). &bull; we show that the grothendieck constant kg can be computed within an error &eta;, in time depending only on &eta;. specifically, for each &eta;, we formulate an explicit finite linear program, whose optimum is &eta;-close to the grothendieck constant. we also exhibit a simple family of operators on the gaussian hilbert space that is guaranteed to contain tight examples for the grothendieck inequality.
weighted flow time does not admit o(1)-competitive algorithms. we consider the classic online scheduling problem of minimizing the total weighted flow time on a single machine with preemptions. here, each job j has an arbitrary arrival time rj, weight wj and size pj, and given a schedule its flow time is defined as the duration of time since its arrival until it completes its service requirement. the first non-trivial algorithms with poly-logarithmic competitive ratio for this problem were obtained relatively recently, and it was widely believed that the problem admits a constant factor competitive algorithm. in this paper, we show an &omega;(1) lower bound on the competitive ratio of any deterministic online algorithm. our result is based on a gap amplification technique for online algorithms. starting with a trivial lower bound of 1, we give a procedure to improve the lower bound sequentially, while ensuring at each step that the size of the instance increases relatively modestly.
hypergraph regularity and quasi-randomness. thomason and chung, graham, and wilson were the first to systematically study quasi-random graphs and hypergraphs, and proved that several properties of random graphs imply each other in a deterministic sense. their concepts of quasi-randomness match the notion of &epsilon;-regularity from the earlier szemer&eacute;di regularity lemma. in contrast, there exists no "natural" hypergraph regularity lemma matching the notions of quasi-random hypergraphs considered by those authors. we study several notions of quasi-randomness for 3-uniform hypergraphs which correspond to the regularity lemmas of frankl and r&ouml;dl, gowers and haxell, nagle and r&ouml;dl. we establish an equivalence among the three notions of regularity of these lemmas. since the regularity lemma of haxell et al. is algorithmic, we obtain algorithmic versions of the lemmas of frankl-r&ouml;dl (a special case thereof) and gowers as corollaries. as a further corollary, we obtain that the special case of the frankl-r&ouml;dl lemma (which we can make algorithmic) admits a corresponding counting lemma. (this corollary follows by the equivalences and that the regularity lemma of gowers or that of haxell et al. admits a counting lemma.)
the cover time of random geometric graphs. we study the cover time of random geometric graphs. let i(d) = [0, 1]d denote the unit torus in d dimensions. let d(x, r) denote the ball (disc) of radius r. let &upsih;d be the volume of the unit ball d(0, 1) in d dimensions. a random geometric graph g = g(d, r, n) in d dimensions is defined as follows: sample n points v independently and uniformly at random from i(d). for each point x draw a ball d(x, r) of radius r about x. the vertex set v(g) = v and the edge set e(g) = {{v, w}: w &ne; v, w &isin; d(v, r)}. let g(d, r, n), d &ge; 3 be a random geometric graph. let c > 1 be constant, and let r = (c log n/(&upsih;dn))1/d. then whp cg ~ clog(c/c-1)nlogn.
partitioning graphs into balanced components. we consider the k-balanced partitioning problem, where the goal is to partition the vertices of an input graph g into k equally sized components, while minimizing the total weight of the edges connecting different components. we allow k to be part of the input and denote the cardinality of the vertex set by n. this problem is a natural and important generalization of well-known graph partitioning problems, including minimum bisection and minimum balanced cut. we present a (bi-criteria) approximation algorithm achieving an approximation of o(&radic;log n log k), which matches or improves over previous algorithms for all relevant values of k. our algorithm uses a semidefinite relaxation which combines l22 metrics with spreading metrics. surprisingly, we show that the integrality gap of the semidefinite relaxation is &omega;(log k) even for large values of k (e.g., k = n&omega;(1), implying that the dependence on k of the approximation factor is necessary. this is in contrast to previous approximation algorithms for k-balanced partitioning, which are based on linear programming relaxations and their approximation factor is independent of k.
approximate clustering without the approximation. approximation algorithms for clustering points in metric spaces is a flourishing area of research, with much research effort spent on getting a better understanding of the approximation guarantees possible for many objective functions such as k-median, k-means, and min-sum clustering. this quest for better approximation algorithms is further fueled by the implicit hope that these better approximations also yield more accurate clusterings. e.g., for many problems such as clustering proteins by function, or clustering images by subject, there is some unknown correct "target" clustering and the implicit hope is that approximately optimizing these objective functions will in fact produce a clustering that is close pointwise to the truth. in this paper, we show that if we make this implicit assumption explicit---that is, if we assume that any c-approximation to the given clustering objective &phi; is &epsilon;-close to the target---then we can produce clusterings that are o(&epsilon;)-close to the target, even for values c for which obtaining a c-approximation is np-hard. in particular, for k-median and k-means objectives, we show that we can achieve this guarantee for any constant c > 1, and for the min-sum objective we can do this for any constant c > 2. our results also highlight a surprising conceptual difference between assuming that the optimal solution to, say, the k-median objective is &epsilon;-close to the target, and assuming that any approximately optimal solution is &epsilon;-close to the target, even for approximation factor say c = 1.01. in the former case, the problem of finding a solution that is o(&epsilon;)-close to the target remains computationally hard, and yet for the latter we have an efficient algorithm.
self-overlapping curves revisited. let s be a surface embedded in space in such a way that each point has a neighborhood within which the surface is a terrain. then s projects to an immersed surface in the plane, the boundary of which is a (possibly self-intersecting) curve. under what circumstances can we reverse these mappings algorithmically? shor and van wyk considered one such problem, determining whether a curve is the boundary of an immersed disk; they showed that the self-overlapping curves defined in this way can be recognized in polynomial time. we show that several related problems are more difficult: it is np-complete to determine whether an immersed disk is the projection of a disk embedded in space, or whether a curve is the boundary of an immersed surface in the plane that is not constrained to be a disk. however, when a casing is supplied with a self-intersecting curve, describing which component of the curve lies above and which below at each crossing, we may determine in time linear in the number of crossings whether the cased curve forms the projected boundary of a surface in space. as a related result, we show that an immersed surface with a single boundary curve that crosses itself n times has at most 2n/2 combinatorially distinct spatial embeddings, and we discuss the existence of fixed-parameter tractable algorithms for related problems.
an almost (log )-approximation for -connected subgraphs. we consider two cases of the survivable network design (snd) problem: given a complete graph gn = (v, en) with costs on the edges and connectivity requirements {r(u, v): u, v &isin; v}, find a minimum cost subgraph g of gn that contains r(u, v) internally disjoint uv-paths for all u, v &isin; v. our main result is an o (log k &middot; log n/n--k)-approximation algorithm for the k-connected subgraph problem (the case r(u, v) = k for all u, v &isin; v.), for both directed and undirected graphs, where n = |v|. our ratio is o(log k), unless k = n - o(n). previously, the best known approximation guarantees for this problem were o(log2 k) for directed/undirected graphs [kortsarz and nutov stoc 2004, fakcharoenphol and laekhanukit stoc 2008], and o(log k) for undirected graphs with k &le; &radic;n/2 [cheriyan, vempala, and vetta stoc 2002]. as in previous work, we consider the k-connectivity augmentation problem of increasing at minimum cost the connectivity of a given graph j from k - 1 to k; a &rho;-approximation for it is used to derive an o(&rho; &middot; log k)-approximation for k-connected subgraph. fakcharoenphol and laekhanukit showed that k-connectivity augmentation admits an o(log v)-approximation algorithm, where v is the number of minimal "violated" sets in j. however, we may have v = &theta;(n), so this gives only an o(log n)-approximation. we design a novel primal-dual algorithm that adds an edge set of cost &le; opt to get v &le; 2n/n - k. combined with the algorithm of fakcharoenphol and laekhanukit, this gives the ratio o (log n/n - k) for k-connectivity augmentation, which is o(1), unless k = n - o(n). our additional result is for the (undirected) rooted snd, where for a "root" s &isin; v, the connectivity requirements are {r(s, t) = r(t): t &isin; t &sube; v}, and the solution graph should contain r(t) internally disjoint st-paths for all t &isin; t. for large values of k = maxt&isin;t r(t) rooted snd is at least as hard to approximate as directed steiner tree [lando and nutov approx 2008]. for rooted snd [chakraborty, chuzhoy, khanna stoc 08] gave recently a ko(k2) log4 n-approximation algorithm. slightly later [chuzhoy and khanna focs 08] improved the ratio to o(k2 log n), and also gave an o(k8 log2 n)-approximation algorithm for the case of node-costs. independently, we obtained a simple approximation algorithm with ratios o(k2 log n) for edge-costs, and o(k4 log2 n) for node-costs.
combinatorial stochastic processes and nonparametric bayesian modeling. computer science has historically been strong on data structures and weak on inference from data, whereas statistics has historically been weak on data structures and strong on inference from data. one way to draw on the strengths of both disciplines is to develop "inferential methods for data structures"; i.e., methods that update probability distributions on recursively-defined objects such as trees, graphs, grammars and function calls. this is the world of "nonparametric bayes," where prior and posterior distributions are allowed to be general stochastic processes. both statistical and computational considerations lead one to certain classes of stochastic processes, and these tend to have interesting connections to combinatorics. i will give some examples of how this blend of ideas leads to useful models in some applied problem domains, including natural language parsing, computational vision, statistical genetics and protein structural modeling.
secretary problems: weights and discounts. the classical secretary problem studies the problem of selecting online an element (a "secretary") with maximum value in a randomly ordered sequence. the difficulty lies in the fact that an element must be either selected or discarded upon its arrival, and this decision is irrevocable. constant-competitive algorithms are known for the classical secretary problems (see, e.g., the survey of freeman [7]) and several variants. we study the following two extensions of the secretary problem: &bull; in the discounted secretary problem, there is a time-dependent "discount" factor d(t), and the benefit derived from selecting an element/secretary e at time t is d(t) &middot; v(e). for this problem with arbitrary (not necessarily decreasing) functions d(t), we show a constant-competitive algorithm when the expected optimum is known in advance. with no prior knowledge, we exhibit a lower bound of &omega;(log n/log log n), and give a nearly-matching o(log n)-competitive algorithm. &bull; in the weighted secretary problem, up to k secretaries can be selected; when a secretary is selected (s)he must be irrevocably assigned to one of k positions, with position k having weight w(k), and assigning object/secretary e to position k has benefit w(k) &middot; v(e). the goal is to select secretaries and assign them to positions to maximize &sigma;e, k w(k) &middot; v(e) &middot; xek where xek is an indicator variable that secretary e is assigned position k. we give constant-competitive algorithms for this problem. most of these results can also be extended to the matroid secretary case (babaioff et al. [2]) for a large family of matroids with a constant-factor loss, and an o(log rank) loss for general matroids. these results are based on a reduction from various matroids to partition matroids which present a unified approach to many of the upper bounds of babaioff et al. these problems have connections to online mechanism design (see, e.g., hajiaghayi et al. [9]). all our algorithms are monotone, and hence lead to truthful mechanisms for the corresponding online auction problems.
natural algorithms. we provide further evidence that the study of complex self-organizing systems can benefit from an algorithmic perspective. the subject has been traditionally viewed through the lens of physics and control theory. using tools typically associated with theoretical computer science, we settle an old question in theoretical ecology: bounding the convergence of bird flocks. we bound the time to reach steady state by a tower-of-twos of height linear in the number of birds. we prove that, surprisingly, the tower-of-twos growth is intrinsic to the model. this unexpected result demonstrates the merits of approaching biological dynamical systems as "natural algorithms" and applying algorithmic techniques to them.
an efficient sparse regularity concept. let a be a 0/1 matrix of size m x n, and let p be the density of a (i.e., the number of ones divided by m &middot; n). we show that a can be approximated in the cut norm within &epsilon; &middot; mnp by a sum of cut matrices (of rank 1), where the number of summands is independent of the size m &middot; n of a, provided that a satisfies a certain boundedness condition. the decomposition can be computed in polynomial time. this result extends the work of frieze and kannan (combinatorica 1999) to sparse matrices. as an application, we obtain efficient 1 - &epsilon; approximation algorithms for "bounded" instances of max csp problems.
a sense of self for unix processes. a method for anomaly detection is introduced in which ``normal'' is defined by short-range correlations in a process' system calls. initial experiments suggest that the definition is stable during normal behavior for standard unix programs. further, it is able to detect several common intrusions involving sendmail and lpr. this work is part of a research program aimed at building computer security systems that incorporate the mechanisms and algorithms used by natural immune systems.
lomac: low water-mark integrity protection for cots environments. we hypothesize that a form of kernel-resident access-control-based integrity protection can gain widespread acceptance in commercial off-the-shelf (cots) environments if it couples some useful protection with a high degree of compatibility with existing software, configurations, and practices. to test this hypothesis, we have developed a highly compatible free open-source prototype called lomac, and released it on the internet. lomac is a dynamically loadable extension for cots linux kernels that provide integrity protection based on low water-mark access control. we present a classification of existing access control models with regard to compatibility, concluding that models similar to low water-mark are especially well suited to high-compatibility solutions. we also describe our practical strategies for dealing with the pathological cases in the low water-mark model's behavior, which include a small extension of the model, and an unusual application of its concepts.
on confidentiality and algorithms. abstract: recent interest in methods for certifying programs for secure information flow (noninterference) have failed to raise a key question: can efficient algorithms be written so as to satisfy the requirements of secure information flow? in this paper we discuss how algorithms for searching and sorting can be adapted to work on collections of secret data without leaking any confidential information, either directly, indirectly, or through timing behaviour. we pay particular attention to the issue of timing channels caused by cache behaviour, and argue that it is necessary to disable the effect of the cache in order to construct algorithms manipulating pointers to objects in such a way that they satisfy the conditions of noninterference. we also discuss how randomisation can be used to implement secure algorithms, and discuss how randomised hash tables might be made practically secure.
improving computer security using extended static checking. we describe a method for finding security flaws in source code by wayof static analysis.the method is notable because it allows a user tospecify a wide range of security properties while also leveraging aset of predefined common flaws.it works by using an automatedtheorem prover to analyze verification conditions generated from csource code and a set of specifications that define securityproperties.we demonstrate that the method can be used to identifyreal vulnerabilities in real programs.
probabilistic treatment of mixes to hamper traffic analysis. the goal of anonymity providing techniques is to preservethe privacy of users, who has communicated withwhom, for how long, and from which location, by hidingtraffic information. this is accomplished by organizing additionaltraffic to conceal particular communication relationshipsand by embedding the sender and receiver of amessage in their respective anonymity sets. if the number ofoverall participants is greater than the size of the anonymityset and if the anonymity set changes with time due to unsynchronizedparticipants, then the anonymity technique becomesprone to traffic analysis attacks. in this paper, we areinterested in the statistical properties of the disclosure attack,a newly suggested traffic analysis attack on the mixes.our goal is to provide analytical estimates of the number ofobservations required by the disclosure attack and to identifyfundamental (but avoidable) weak operational modes'of the mixes and thus to protect users against a traffic analysisby the disclosure attack.
analyzing consistency of security policies. abstract: we discuss the development of a methodology for reasoning about properties of security policies. we view a security policy as a special case of regulation which specifies what actions some agents are permitted, obliged or forbidden to perform and we formalize a policy by a set of deontic formulae. we first address the problem of checking policy consistency and describe a method for solving it. the second point we are interested in is how to query a policy to know the actual norms which apply to a given situation. in order to provide the user with consistent answers, the normative conflicts which may appear in the policy must be solved. for doing so, we suggest using the notion of roles and define priorities between roles.
using conservation of flow as a security mechanism in network protocols. the law of conservation of flow, which states that an input must either be absorbed or sent on as an output (possibly with modification), is an attractive tool with which to analyze network protocols for security properties. one of its uses is to detect disruptive network elements that launch denial of service attacks by absorbing or discarding packets. its use requires several assumptions about the protocols being analyzed. in this paper, we examine the watchers algorithm to detect misbehaving routers. we show that it uses conservation of flow without sufficient verification of its assumptions, and can consequently be defeated. we suggest improvements to make the use of conservation of flow valid.
cryptographic security for mobile code. abstract: this paper addresses the protection of mobile code against cheating and potentially malicious hosts. we point out that the recent approach based on computing with "encrypted functions" is limited to the case where only the code originator learns the result of the computation and the host running the code must not notice anything at all. we argue that if the host is to receive some output of the computation, then securing mobile code requires minimal trust in a third party. tamper-proof hardware installed on each host has been proposed for this purpose. in this paper we introduce a new approach for securely executing (fragments of) mobile code that relies on a minimally trusted third party. this party is a generic independent entity, called the secure computation service, which performs some operations on behalf of the mobile application, but does not learn anything about the encrypted computation. because it is universal, the secure computation service needs to be only minimally trusted and can serve many different applications. we present a protocol based on tools from theoretical cryptography that is quite practical for computing small functions.
semantics-aware malware detection. a malware detector is a system that attempts to determine whether a program has malicious intent. in order to evade detection, malware writers (hackers) frequently use obfuscation to morph malware. malware detectors that use a pattern-matching approach (such as commercial virus scanners) are susceptible to obfuscations used by hackers. the fundamental deficiency in the pattern-matching approach to malware detection is that it is purely syntactic and ignores the semantics of instructions. in this paper, we present a malware-detection algorithm that addresses this deficiency by incorporating instruction semantics to detect malicious program traits. experimental evaluation demonstrates that our malware-detection algorithm can detect variants of malware with a relatively low run-time overhead. moreover, our semantics-aware malware detection algorithm is resilient to common obfuscations used by hackers.
searching for a solution: engineering tradeoffs and the evolution of provably secure protocols. tradeoffs are an important part of engineering security. protocol security is important. so are efficiency and cost. this paper provides an early framework for handling such aspects in a uniform way based on combinatorial optimization techniques. ban logic is viewed as both a specification and proof system and as a `protocol programming language'. the paper shows how evolutionary search in the form of genetic algorithms can be utilized to `grow' correct and efficient ban protocols and shows how goals and assumptions can co-evolve, effectively engaging in `specification synthesis'.
surviving information warfare attacks on databases. abstract: we consider the problem of surviving information warfare attacks on databases. we adopt a fault tolerance approach to the different phases of an attack. to maintain precise information about the attack, we mark data to reflect the severity of detected damage as well as the degree to which the damaged data has been repaired. in the case of partially repaired data, integrity constraints might be violated, but data is nonetheless available to support mission objectives. we define a notion of consistency suitable for databases in which some information is known to be damaged, and other information is known to be only partially repaired. we present a protocol for normal transactions with respect to the damage markings and show that consistency preserving normal transactions maintain database consistency in the presence of damage. we present an algorithm for taking consistent snapshots of databases under attack. the snapshot algorithm has the virtue of not interfering with countermeasure transactions.
towards constant bandwidth overhead integrity checking of untrusted data. we present an adaptive tree-log scheme to improve the performance of checking the integrity of arbitrarily-large untrusted data, when using only a small fixed-sized trusted state. currently, hash trees are used to check the data. in many systems that use hash trees, programsperform many data operations before performing a critical operation that exports a resultoutside of the program's execution environment. the adaptive tree-log scheme we present uses this observation to harness the power of the constant runtime bandwidth overhead of a log-based scheme. for all programs, the adaptive tree-log scheme's bandwidth overhead is guaranteed to never be worse than a parameterizable worst case bound. furthermore, for all programs, as the average number of times the program accesses data between critical operations increases, the adaptive tree-log scheme's bandwidth overhead moves from a logarithmic to a constant bandwidth overhead.
ensuring atomicity of multilevel transactions. ensuring atomicity is a major outstanding problem with present methods of handling multilevel transactions. the chief difficulty is that a high section of a transaction may be unable to complete due to violations of the integrity constraints, and a rollback of sections can be exploited to implement a covert channel. we define a notion of semantic atomicity which guarantees that either all or none of the sections of a transaction are present in any history. the notion of correct executions in our model is based on semantic correctness -- that is, maintenance of integrity constraints -- rather than serializability. we give a method whereby the application developer can statically analyze the set of transactions in the application and determine if the set ensures semantic atomicity and other desirable properties.
using views in a multilevel secure database management system. the use of database views in databasemanagement systems that enforce user level discretionaryand nondiscretionary access controlpolicies is discussed. this discussion involvesseveral issues such as how should views beclassified?, what types of mechanisms should beused to define views?, etc. mapping betweenviews, view updating, and aggregation andinference problems are also discussed.
sd3: a trust management system with certified evaluation. abstract: we introduce sd3, a trust management system consisting of a high-level policy language, a local policy evaluator, and a certificate retrieval system. a unique feature of sd3 is its certified evaluator: as the evaluator computes the answer to a query, it also computes a proof that the answer follows from the security policy. before the answer is returned, the proof is passed through a simple checker, and incorrect proofs are reported as errors. the certified evaluator reduces the trusted computing base and greatly increases our confidence that the answers produced by the evaluator follow from the specification, despite complex optimizations. to illustrate sd3's capabilities, we show how to implement a secure name service, similar to dnssec, entirely in sd3.
privacy technology lessons from healthcare. the probability that information will be abused depends both on its value and on the number of people who have access. the modern trend to ever-larger databases increases both of these risk factors at the same time. compartmented security polices can solve many of the technical issues, and there are applications - such as healthcare - where they have been developed in some detail. however, the big problem is not technical; it is legal and regulatory. insurers, employers and governments will not adopt compartmented systems, or will allow them to be adopted only in places such as hospitals, which are not where the real threats lie.
a more efficient use of delta-crls. delta-certificate revocation lists (delta-crls) were designed to provide a more efficient way to distribute certificate status information. however, as this paper shows, in some environments the benefits of using delta-crls will be minimal if delta-crls are used as was originally intended. this paper provides an analysis of delta-crls that demonstrates the problems associated with issuing delta-crls in the ¿traditional¿ manner. a new, more efficient technique for issuing delta-crls, sliding window delta-crls, is presented.
an approach to indentification of minimum tcb requirements for various threat/risk environments. a gross identification of threats andrisks based on a data classificationenvironment and the minimum clearancelevel of individuals using a system isrelated to the levels identified in thedodcsc trusted computer evaluationcriteria. a proposed set of minimum tcblevels for given threat risk environmentsis identified.
a logic for constraint-based security protocol analysis. we propose ps-ltl, a pure-past security linear temporal logic that allows the specification of a variety of authentication, secrecy and data freshness properties. furthermore, we present a sound and complete decision procedure to establish the validity of security properties for symbolic execution traces, and show the integration with constraintbased analysis techniques.
a security policy model for clinical information systems. abstract: the protection of personal health information has become a live issue in a number of countries, including the usa, canada, britain and germany. the debate has shown that there is widespread confusion about what should be protected, and why. designers of military and banking systems can refer to bell & lapadula (1973) and clark & wilson (1987) respectively, but there is no comparable security policy model that spells out clear and concise access rules for clinical information systems. in this article, we present just such a model. it was commissioned by doctors and is driven by medical ethics; it is informed by the actual threats to privacy, and reflects current best clinical practice. its effect is to restrict both the number of users who can access any record and the maximum number of records accessed by any user. this entails controlling information flows across rather than down and enforcing a strong notification property. we discuss its relationship with existing security policy models, and its possible use in other applications where information exposure must be localised; these range from private banking to the management of intelligence data.
a basis for secure communication in large distributed systems. large distributed systems have properties that, from the point of view of security distinguish them from lan-based systems. we describe these differences and show the security mechanisms found in current distributed systems are not well-suited to large system. we propose a secure communication architecture for large systems that puts security below the transport level. we argue that this is preferable to putting it at higher levels, and that in fact it can simplify and improve the performance of transport protocols.
a safety-oriented platform for web applications. the web browser has become the dominant interface to a broad range of applications, including online banking, web-based email, digital media delivery, gaming, and ecommerce services. early web browsers provided simple access to static hypertext documents. in contrast, modern browsers serve as de facto operating systems that must manage dynamic and potentially malicious applications. unfortunately, browsers have not properly adapted to their new role. as a consequence, they fail to provide adequate isolation across applications, exposing both users and web services to attack.
formal treatment of certificate revocation under communal access control. abstract: the conventional approach to distributed access-control (ac) tends to be server-centric. under this approach, each server establishes its own policy regarding the use of its resources and services by its clients. the choice of this policy, and its implementation, are generally considered the prerogative of each individual server. this approach to access-control may be appropriate for many current client-server applications, where the server is an autonomous agent, in complete charge of its resources. but it is not suitable for the growing class of applications where a group of servers, and sometimes their clients, belong to a single enterprise, and are subject to the enterprise-wide policy governing them all. one may not be able to entrust such an enterprise-wide policy to the individual servers, for two reasons: first, it is hard to ensure that an heterogeneous set of servers implement exactly the same policy. second, as we will demonstrate, an ac policy can have aspects that cannot, in principle, be implemented by servers alone. as argued in a previous paper [11], what is needed in this situation is a concept of communal policy that governs the interaction between the members of a distributed community of agents involved in some common activity, along with a mechanism that provides for the explicit formulation of such policies, and for their scalable enforcement. this paper focuses on the communal treatment of expiration and revocation of the digital certificates used for the authentication of the identity and roles of members of the community.
a secure and reliable bootstrap architecture. abstract: in a computer system, the integrity of lower layers is typically treated as axiomatic by higher layers. under the presumption that the hardware comprising the machine (the lowest layer) is valid, the integrity of a layer can be guaranteed if and only if: (1) the integrity of the lower layers is checked and (2) transitions to higher layers occur only after integrity checks on them are complete. the resulting integrity "chain" inductively guarantees system integrity. when these conditions are not met, as they typically are not in the bootstrapping (initialization) of a computer system, no integrity guarantees can be made, yet these guarantees are increasingly important to diverse applications such as internet commerce, security systems and "active networks". in this paper, we describe the aegis architecture for initializing a computer system. it validates integrity at each layer transition in the bootstrap process. aegis also includes a recovery process for integrity check failures, and we show how this results in robust systems.
using programmer-written compiler extensions to catch security holes. this paper shows how system-specific static analysis can find securityerrors that violate rules such as ``integers from untrusted sourcesmust be sanitized before use'' and ``do not dereference user-suppliedpointers.''in our approach, programmers write system-specificextensions that are linked into the compiler and check their code forerrors.we demonstrate the approach's effectiveness by using it tofind over 100 security errors in linux and openbsd, over 50 of whichhave led to kernel patches.an unusual feature of our approach is theuse of methods to automatically detect when we miss code actions thatshould be checked.
alert correlation in a cooperative intrusion detection framework. this paper presents the work we have done within the mirador project to design crim, a cooperative module for intrusion detection systems (ids). this module implements functions to manage, cluster, merge and correlate alerts. the clustering and merging functions recognize alerts that correspond to the same occurrence of an attack and create a new alert that merge data contained in these various alerts. experiments show that these functions significantly reduce the number of alerts. however, we also observe that alerts we obtain are still too elementary to be managed by a security administrator. the purpose of the correlation function is thus to generate global and synthetic alerts. this paper focuses on the approach we suggest to design this function.
mixminion: design of a type iii anonymous remailer protocol. we present mixminion, a message-based anonymous remailerprotocol with secure single-use reply blocks. mixnodes cannot distinguish mixminion forward messages fromreply messages, so forward and reply messages share thesame anonymity set. we add directory servers that allowusers to learn public keys and performance statistics of participatingremailers, and we describe nymservers that providelong-term pseudonyms using single-use reply blocksas a primitive. our design integrates link encryption betweenremailers to provide forward anonymity. mixminionworks in a real-world internet environment, requires littlesynchronization or coordination between nodes, and protectsagainst known anonymity-breaking attacks as well asor better than other systems with similar design parameters.
intransitive non-interference for cryptographic purpose. information flow and non-interference have recentlybecome very popular concepts for expressing both integrityand privacy properties. because of the enormouspotential of transmitting information using probabilisticmethods of cryptography, interest arose in capturingprobabilistic non-interference. we investigate the notionof intransitive probabilistic non-interference in reactivesystems, i.e., downgrading of probabilistic informationand detection of probabilistic information flowby one or more involved third parties. based on concreteexamples, we derive several definitions that comprisecryptography-related details like error probabilities andcomputational restrictions. this makes the definitionsapplicable to systems involving real cryptography. detectionof probabilistic information flow is significantlymore complicated to define if several third parties areinvolved because of the possibilities of secret sharing.we solve this problem by graph-theoretic techniques.
relating symbolic and cryptographic secrecy. we investigate the relation between symbolic and cryptographic secrecy properties for cryptographic protocols. symbolic secrecy of payload messages or exchanged keys is arguably the most important notion of secrecy shown with automated proof tools. it means that an adversary restricted to symbolic operations on terms can never get the entire considered object into its knowledge set. cryptographic secrecy essentially means computational indistinguishability between the real object and a random one, given the view of a much more general adversary. in spite of recent advances in linking symbolic and computational models of cryptography, no relation for secrecy under active attacks is known yet. for exchanged keys, we show that a certain strict symbolic secrecy definition over a specific dolev-yao-style cryptographic library implies cryptographic key secrecy for a real implementation of this cryptographic library. for payload messages, we present the first general cryptographic secrecy definition for a reactive scenario. the main challenge is to separate secrecy violations by the protocol under consideration from secrecy violations by the protocol users in a general way. for this definition we show a general secrecy preservation theorem under reactive simulatability, the cryptographic notion of secure implementation. this theorem is of independent cryptographic interest. we then show that symbolic secrecy implies cryptographic payload secrecy for the same cryptographic library as used in key secrecy. our results thus enable existing formal proof techniques to establish cryptographically sound proofs of secrecy for payload messages and exchanged keys.
binder, a logic-based security language. we introduce the concept of a security language, used to expresssecurity statements in a distributed system. most existing securitylanguages encode security statements as schematized data structures,such as acls and x.509 certificates. in contrast, binder is an openlogic-based security language that encodes security statements ascomponents of communicating distributed logic programs. binder programscan be more expressive than statements in standard security languages,and the meanings of standard security constructs and operations such ascertificates and delegation are simplified and clarified by theirformulation in binder. translation into binder has been used to explorethe design of other new and existing security languages.
a security infrastructure for distributed java applications. we describe the design and implementation of a security infrastructure for a distributed java application. this work is inspired by sdsi/spki, but has a few twists of its own. we define logic for access control, such that access is granted if a proof that it should be granted is derivable in the logic. our logic supports linked local name spaces, privilege delegation across administrative domains, and attribute certificates. we use ssl to establish secure channels through which principals can ¿speak¿, and have implemented our access control system in java. while we implemented our infrastructure for the placeless documents system, our design is applicable to other applications as well. we discuss general issues related to building secure, distributed java applications that we discovered.
joint encryption and error-correction coding. this paper considers the problem of joint encryptionand error-correction coding and proposesa solution using d-sequences, which are decimal'expansions of fractions. the encryption operationconsidered is equivalent to exponentiation whichforms the basis of several public-key schemes.several new results on d-sequences are also presented which make the applications to encryptionand error coding possible.
secret handshakes from pairing-based key agreements. consider a cia agent who wants to authenticate herselfto a server, but does not want to reveal her cia credentialsunless the server is a genuine cia outlet. consider also thatthe cia server does not want to reveal its cia credentialsto anyone but cia agents - not even to other cia servers.in this paper we first show how pairing-based cryptographycan be used to implement such secret handshakes.we then propose a formal definition for secure secret handshakes,and prove that our pairing-based schemes are secureunder the bilinear diffie-hellman assumption. ourprotocols support role-based group membership authentication,traceability, indistinguishability to eavesdroppers,unbounded collusion resistance, and forward repudiability.our secret-handshake scheme can be implemented as atls cipher suite. we report on the performance of our preliminaryjava implementation.
constrained delegation. sometimes it is useful to be able to separate between the management of a set of resources, and the access to the resources themselves.current accounts of delegation do not allow such distinctions to be easily made, however.we introduce a new model for delegation to address this issue. the approach is based on the idea of controlling the possible shapes of delegation chains.we use constraints to restrict the capabilities at each step of delegation.constraints may re?ect e.g.group memberships, timing constraints, or dependencies on external data.regular expressions are used to describe chained constraints.we present a number of example delegation structures, based on a scenario of collaborating organisations.
the many-time pad: theme and variations. the man-time pad is a method of subverting thesecurity controls of a system to obtain data that is notdirectly accessible(e.g., because the data is confidential,classified, or otherwise deemed sensitive). it is theantithesis of the one-time pad, the only theoreticallyunbreakable cipher, in two respects: 1) whereas theone-time pad is a method of protection,the many-timepad is a method of attack; and 2) whereas the one-timepad is used just once, the many-time pad is reusable.a1so, whereas the interpretation of "pad" m the one-timepad comes from a "pad of paper", its interpretation in the many-time pad comes from "stuffing".what makes the many-time pad attack interesting isthat it arises in three different contexts: cryptographicsystems, where digital signatures can be forged ormessages decrypted; statistical databases, wheretrackers can be used to obtain confidential data; andprogramming systems, where trojan horses can beplanted in programs to leak sensitive input data, weshall first describe the basic structure of the attack andcountermeasures for foiling it. we shall then show howthese three seemingly unrelated security threats arevariations of a common theme.
an intrusion-detection model. a model of a real-time intrusion-detection expert system capable of detecting break-ins, penetrations, and other forms of computer abuse is described. the model is based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns of system usage. the model includes profiles for representing the behavior of subjects with respect to objects in terms of metrics and statistical models, and rules for acquiring knowledge about this behavior from audit records and for detecting anomalous behavior. the model is independent of any particular system, application environment, system vulnerability, or type of intrusion, thereby providing a framework for a general-purpose intrusion-detection expert system.
firmato: a novel firewall management toolkit. in recent years packet-filtering firewalls have seen some impressive technological advances (e.g., stateful inspection, transparency, performance, etc.) and wide-spread deployment. in contrast, firewall and security <i>management</i> technology is lacking. in this paper we present <i>firmato</i>, a firewall management toolkit, with the following distinguishing properties and components: (1) an entity-relationship model containing, in a unified form, global knowledge of the security policy and of the network topology; (2) a model definition language, which we use as an interface to define an instance of the entity-relationship model; (3) a model compiler, translating the global knowledge of the model into firewall-specific configuration files; and (4) a graphical firewall rule illustrator. we implemented a prototype of our toolkit to work with several commercially available firewall products. this prototype was used to control an operational firewall for several months. we believe that our approach is an important step toward streamlining the process of configuring and managing firewalls, especially in complex, multi-firewall installations.
privacy and contextual integrity: framework and applications. contextual integrity is a conceptual framework for understanding privacy expectations and their implications developed in the literature on law, public policy, and political philosophy. we formalize some aspects of contextual integrity in a logical framework for expressing and reasoning about norms of transmission of personal information. in comparison with access control and privacy policy frameworks such as rbac, epal, and p3p, these norms focus on who personal information is about, how it is transmitted, and past and future actions by both the subject and the users of the information. norms can be positive or negative depending on whether they refer to actions that are allowed or disallowed. our model is expressive enough to capture naturally many notions of privacy found in legislation, including those found in hipaa, coppa, and glba. a number of important problems regarding compliance with privacy norms, future requirements associated with specific actions, and relations between policies and legal standards reduce to standard decision procedures for temporal logic.
deriving an information flow checker and certifying compiler for java. language-based security provides a means to enforce endto- end confidentiality and integrity policies inmobile code scenarios, and is increasingly being contemplated by the smartcard and mobile phone industry as a solution to enforce information flow and resource control policies. two threads of work have emerged in research on languagebased security: work that focuses on enforcing security policies for source code, which is tailored towards developers that want to increase confidence in their applications, and work that focuses on efficiently verifying similar policies for bytecode, which is tailored to code consumers that want to protect themselves against hostile applications. these lines of work serve different purposes - and thus have been developed independently but connecting them is a key step towards the deployment of language-based security in practical applications. this paper introduces a systematic technique to connect source code and bytecode security type systems. the technique is applied to an information flow type system for a fragment of java with exceptions, thus confronting challenges in both control and data flow tracking.
distributed proving in access-control systems. we present a distributed algorithm for assembling a proof that a request satisfies an access-control policy expressed in a formal logic, in the tradition of lampson et al. we show analytically that our distributed proof-generation algorithm succeeds in assembling a proof whenever a centralized prover utilizing remote certificate retrieval would do so. in addition, we show empirically that our algorithm outperforms centralized approaches in various measures of performance and usability, notably the number of remote requests and the number of user interruptions. we show that when combined with additional optimizations including caching and automatic tactic generation, which we introduce here, our algorithm retains its advantage, while achieving practical performance. finally, we briefly describe the utilization of these algorithms as the basis for an access-control framework being deployed for use at our institution.
secure computer systems: a retrospective. eight years after the completion of the "securecomputer systems" series, basic questions about thatwork are being raised. is the model useful? is itoverly restrictive? are further modeling effortsnecessary to address current problems? this paperaddresses those questions in a personal view of thedevelopment and the utility of the "secure computersystems" security model. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
an immunological approach to change detection: algorithms, analysis and implications. we present new results on a distributable change-detection method inspired by the natural immune system. a weakness in the original algorithm was the exponential cost of generating detectors. two detector-generating algorithms are introduced which run in linear time. the algorithms are analyzed, heuristics are given for setting parameters based on the analysis, and the presence of holes in detector space is examined. the analysis provides a basis for assessing the practicality of the algorithms in specific settings, and some of the implications are discussed.
supporting multiple access control policies in database systems. elisa bertino, sushil jajodia, and pierangela samarati although there are several choices of policies for protection of information, access control models have been developed for a fixed set pre-defined access control policies that are then built into the corresponding access control mechanisms. this becomes a problem, however, if the access control requirements of an application are different from the policies built into a mechanism. in most cases, the only solution is to enforce the requirements as part of the application code, but this makes verification, modification, and adequate enforcement of these policies impossible. in this paper, we propose a flexible authorization mechanism that can support different security policies. the mechanism enforces a general authorization model onto which multiple access control policies can be mapped. the model permits negative and positive authorizations, authorizations that must be strongly obeyed and authorizations that allow for exceptions, and enforces ownership together with delegation of administrative privileges.
random key predistribution schemes for sensor networks. key establishment in sensor networks is a challengingproblem because asymmetric key cryptosystems are unsuitablefor use in resource constrained sensor nodes, and alsobecause the nodes could be physically compromised by anadversary. we present three new mechanisms for key establishmentusing the framework of pre-distributing a randomset of keys to each node. first, in the q-compositekeys scheme, we trade off the unlikeliness of a large-scalenetwork attack in order to significantly strengthen randomkey predistribution's strength against smaller-scale attacks.second, in the multipath-reinforcement scheme, we showhow to strengthen the security between any two nodes byleveraging the security of other links. finally, we presentthe random-pairwise keys scheme, which perfectly preservesthe secrecy of the rest of the network when any nodeis captured, and also enables node-to-node authenticationand quorum-based revocation.
logic induction of valid behavior specifications for intrusion detection. this paper introduces an automated technique for constructing valid behavior specifications of programs (at the system call level) that are independent of system vulnerabilities and are highly effective in identifying intrusions. the technique employs a machine learning method, inductive logic programming (ilp), for synthesizing first order logic formulas that describe the valid operations of a program from the normal runs of the program. ilp, backed by theories and techniques extended from computational logic, allows the use of complex domain-specific background knowledge in the learning process to produce sound and consistent knowledge. a specification induction engine has been developed by extending an existing ilp tool and has been used to construct specifications for several (>10) privileged programs in unix. coupling with rich background knowledge in systems and security, the prototype induction engine generates human understandable and analyzable specifications that are as good as those specified by a human. preliminary experiments with existing attacks show that the generated specifications are highly effective in detecting attacks that subvert privileged programs to gain unauthorized accesses to resources.
new constructions and practical applications for private stream searching (extended abstract). a system for private stream searching allows a client to retrieve documents matching some search criteria from a remote server while the server evaluating the request remains provably oblivious to the search criteria. in this extended abstract, we give a high level outline of a new scheme for this problem and an experimental analysis of its scalability. the new scheme is highly efficient in practice. we demonstrate the practical applicability of the scheme by considering its performance in the demanding scenario of providing a privacy preserving version of the google news alerts service.
dataflow anomaly detection. beginning with the work of forrest et al, several researchers have developed intrusion detection techniques based on modeling program behaviors in terms of system calls. a weakness of these techniques is that they focus on control flows involving system calls, but not their arguments. this weakness makes them susceptible to several classes of attacks, including attacks on security-critical data, race-condition and symbolic link attacks, and mimicry attacks. to address this weakness, we develop a new approach for learning dataflow behaviors of programs. the novelty in our approach, as compared to previous system-call argument learning techniques, is that it learns temporal properties involving the arguments of different system calls, thus capturing the flow of security-sensitive data through the program. an interesting aspect of our technique is that it can be uniformly layered on top of most existing control-flow models, and can leverage control-flow contexts to significantly increase the precision of dataflows captured by the model. this contrasts with previous system-call argument learning techniques that did not leverage control-flow information, and moreover, were focused on learning statistical properties of individual system call arguments. through experiments, we show that temporal properties enable detection of many attacks that aren't detected by previous approaches. moreover, they support formal reasoning about security assurances that can be provided when a program follows its dataflow behavior model, e.g., tar would read only files located within a directory specified as a command-line argument.
an mbone proxy for an application gateway firewall. the internet's multicast backbone (mbone) holds great potential for many organizations because it supports low-cost audio and video conferencing and carries live broadcasts of an increasing number of public interest events. mbone conferences are transmitted via unauthenticated multicast datagrams, which unfortunately convey significant security vulnerabilities to any system that receives them. for this reason, most application gateway firewalls block mbone datagrams sent from the internet and prevent them from reaching hosts on internal networks.this paper describes the design and rationale for a new set of facilities for the tis internet firewall toolkit (fwtk). these facilities, which are fully implemented, significantly reduce the security risks of observing or participating in mbone conferences. they impose no functional constraints on mbone applications and are transparent to users. configuration options that support tradeoffs among security, performance, and ease of use are discussed.
the final nail in wep's coffin. the 802.11 encryption standard wired equivalent privacy (wep) is still widely used today despite the numerous discussions on its insecurity. in this paper, we present a novel vulnerability which allows an attacker to send arbitrary data on a wep network after having eavesdropped a single data packet. furthermore, we present techniques for real-time decryption of data packets, which may be used under common circumstances. vendor produced mitigation techniques which cause frequent wep re-keying prevent traditional attacks, whereas our attack remains effective even in such scenarios. we implemented a fully automatic version of this attack which demonstrates its practicality and feasibility in real networks. as even rapidly re-keyed networks can be quickly compromised, we believe wep must now be abandoned rather than patched yet again.
intrusion-tolerant enclaves. despite our best efforts, any sufficiently complex computer system hasvulnerabilities. it is safe to assume that such vulnerabilities can beexploited by attackers who will be able to penetrate the system.intrusion tolerance attempts to maintain acceptable service despitesuch intrusions. this paper presents an application ofintrusion-tolerance concepts to enclaves, a software infrastructurefor supporting secure group applications. intrusion tolerance isachieved via a combination of byzantine fault-tolerant protocols andsecret sharing techniques.
some weaknesses of the tcb model. this paper summarizes the affirmative argument supporting the proposition that "the concept of the trusted computing base (tcb) as a basis for constructing systems to meet security requirements is fundamentally flawed and should no longer be used to justify system security architectures".
irm enforcement of java stack inspection. two implementations are given for java''s stack-inspection access-control policy. each implementation is obtained by generating an inlined reference monitor (irm) for a different formulation of the policy. performance of the implementations is evaluated, and one is found to be competitive with java''s less-flexible, jvm-resident implementation. the exercise illustrates the power of the irm approach for enforcing security policies.
a computationally sound mechanized prover for security protocols. we present a new mechanized prover for secrecy properties of cryptographic protocols. in contrast to most previous provers, our tool does not rely on the dolev-yao model, but on the computational model. it produces proofs presented as sequences of games; these games are formalized in a probabilistic polynomial-time process calculus. our tool provides a generic method for specifying security properties of the cryptographic primitives, which can handle sharedand public-key encryption, signatures, message authentication codes, and hash functions. our tool produces proofs valid for a number of sessions polynomial in the security parameter, in the presence of an active adversary. we have implemented our tool and tested it on a number of examples of protocols from the literature.
decentralized trust management. we identify the "trust management problem" as a distinct and important component of security in network services. aspects of the trust management problem include formulating security policies and security credentials, determining whether particular sets of credentials satisfy the relevant policies, and deferring trust to third parties. existing systems that support security in networked applications, including x.509 and pgp, address only narrow subsets of the overall trust management problem and often do so in a manner that is appropriate to only one application. we present a comprehensive approach to trust management, based on a simple language for specifying trusted actions and trust relationships. we also describe a prototype implementation of a "trust management system," called policymaker, that can facilitate the development of security features in a wide range of network services. this paper was presented at the ieee symposium on security and privacy, oakland ca, may 1996.
siren: catching evasive malware (short paper). with the growing popularity of anomaly detection systems, which is due partly to the rise in zero-day attacks, a new class of threats have evolved where the attacker mimics legitimate activity to blend in and avoid detection. we propose a new system called siren that injects crafted human input alongside legitimate user activity to thwart these mimicry attacks. the crafted input is specially designed to trigger a known sequence of network requests, which siren compares to the actual traffic. it then flags unexpected messages as malicious. using this method, we were able to detect ten spyware programs that we tested, many of which attempt to blend in with user activity. this paper presents the design, implementation, and evaluation of the siren activity injection system, as well as a discussion of its potential limitations.
the channel assignment problem. an optimization problem exists in the context oflocal area network security. the network provides anumber of physical or logical "channels", each carrying aset of levels or compartments of information. a channelis accessible to users cleared for all the levels it carries.the problem is to assign the set of levels to be carried byeach channel so as to minimize the total number ofchannels, under the constraint that each pair of userswith a level in common can communicate over somechannel. this problem was found to be equivalent to aknown np-complete problem, the set basis problem.themain result is an approximatealgorithm that runs inpolynomial time and finds one solution. it has succeededin finding an optimal solution in all of the test casessmall enough to confirm the optimality independently.
anomaly detection using call stack information. the call stack of a program execution can be a very goodinformation source for intrusion detection. there is no priorwork on dynamically extracting information from call stackand effectively using it to detect exploits. in this paper, wepropose a new method to do anomaly detection using callstack information. the basic idea is to extract return addressesfrom the call stack, and generate abstract executionpath between two program execution points. experimentsshow that our method can detect some attacks thatcannot be detected by other approaches, while its convergenceand false positive performance is comparable to orbetter than the other approaches. we compare our methodwith other approaches by analyzing their underlying principlesand thus achieve a better characterization of theirperformance, in particular, on what and why attacks will bemissed by the various approaches.
a trend analysis of exploitations. abstract: we have conducted an empirical study of a number of computer security exploits and determined that the rates at which incidents involving the exploit are reported to the cert can be modeled using a common mathematical framework. data associated with three significant exploits involving vulnerabilities in phf, imap, and bind can all be modeled using the formula c = i + s x vm where c is the cumulative count of reported incidents, m is the time since the start of the exploit cycle, and i and s are the regression coefficients determined by analysis of the incident report data. further analysis of two additional exploits involving vulnerabilities in mountd and statd confirm the model. we believe that the models will aid in predicting the severity of subsequent vulnerability exploitations, based on the rate of early incident reports.
providing flexibility in information flow control for object oriented systems. abstract: this paper presents an approach to control information flow in object-oriented systems that takes into account, besides authorizations on objects, also how the information has been obtained and/or transmitted. these aspects are considered by allowing exceptions to the restrictions stated by the authorizations. exceptions are specified by means of waivers associated with methods. two kinds of waivers are supported: invoke-waivers, specifying exceptions applicable during a method's execution, and reply-waivers, specifying exceptions applicable to the information returned by a method. information flowing from one object into another object is subject to the different waivers of the methods enforcing the transmission. we formally characterize information transmission and flow in a transaction taking into consideration different interaction modes among objects. we then define security specifications, meaning authorizations and waivers, and characterize safe information flows. we formally define conditions whose satisfaction ensures absence of unsafe flows and present an algorithm enforcing these conditions.
towards automatic generation of vulnerability-based signatures. in this paper we explore the problem of creating vulnerability signatures. a vulnerability signature matches all exploits of a given vulnerability, even polymorphic or metamorphic variants. our work departs from previous approaches by focusing on the semantics of the program and vulnerability exercised by a sample exploit instead of the semantics or syntax of the exploit itself. we show the semantics of a vulnerability define a language which contains all and only those inputs that exploit the vulnerability. a vulnerability signature is a representation (e.g., a regular expression) of the vulnerability language. unlike exploitbased signatures whose error rate can only be empirically measured for known test cases, the quality of a vulnerability signature can be formally quantified for all possible inputs.
computer security training and education: a needs analysis. abstract: this paper examines, from an employer's perspective, the kind of education and training that today's computer security practitioners need. it suggests answers to three important questions: (1) what are we educating people to do? (2) what should be included in education and training programs? (3) what can industry do to help?.
defining noninterference in the temporal logic of actions. abstract: covert channels are a critical concern for multilevel secure (mls) systems. due to their subtlety, it is desirable to use formal methods to analyze mls systems for the presence of covert channels. this paper describes an approach for using abadi & lamport's (1993) temporal logic of actions (tla) to specify noninterference properties. in addition to providing a more intuitive definition of noninterference than previous attempts, this approach also supports the analysis of systems that do contain covert channels to demonstrate limitations on their exploitations. in relating the definition of noninterference given in this paper to prior definitions of noninterference, this paper discusses ways in which other definitions of noninterference can be formalized in tla, too. finally, this paper discusses how prior work on specification refinement and composition might be applied to the noninterference problem within the framework provided by tla.
integrity (i) codes: message integrity protection and authentication over insecure channels. inspired by unidirectional error detecting codes that are used in situations where only one kind of bit errors are possible (e.g., it is possible to change a bit "0" into a bit "1", but not the contrary), we propose integrity codes (i-codes) for a radio communication channel, which enable integrity protection of messages exchanged between entities that do not hold any mutual authentication material (i.e. public keys or shared secret keys). the construction of i-codes enables a sender to encode any message such that if its integrity is violated in transmission over a radio channel, the receiver is able to detect it. in order to achieve this, we rely on the physical properties of the radio channel. we analyze in detail the use of i-codes on a radio communication channel and we present their implementation on a mica2 wireless sensor platform as a "proof of concept". we finally introduce a novel concept called "authentication through presence" that can be used for several applications, including for key establishment and for broadcast authentication over an insecure radio channel. we perform a detailed analysis of the security of our coding scheme and we show that it is secure with respect to a realistic attacker model.
collaborative filtering with privacy. server-based collaborative ?ltering systems have been very successful in e-commerce and in direct recommendation applications. in future, they have many potential applications in ubiquitous computing settings. but today's schemes have problems such as loss of privacy, favoring retail monopolies, and with hampering diffusion of innovations. we propose an alternative model in which users control all of their log data. we describe an algorithm whereby a community of users can compute a public "aggregate " of their data that does not expose individual users' data. the aggregate allows personalized recommendations to be computed by members of the community, or by outsiders. the numerical algorithm is fast, robust and accurate. our method reduces the collaborative ?ltering task to an iterative calculation of the aggregate requiring only addition of vectors of user data. then we use homomorphic encryption to allow sums of encrypted vectors o be computed and decrypted without exposing individual data. we give veri?cation schemes for all parties in the computation. our system can be implemented with untrusted servers, or with additional infrastructure, as a fully peer-to-peer (p2p)system.
a framework for the evaluation of intrusion detection systems. classification accuracy in intrusion detection systems (idss) deals with such fundamental problems as how to compare two or more idss, how to evaluate the performance of an ids, and how to determine the best configuration of the ids. in an effort to analyze and solve these related problems, evaluation metrics such as the bayesian detection rate, the expected cost, the sensitivity and the intrusion detection capability have been introduced. in this paper, we study the advantages and disadvantages of each of these performance metrics and analyze them in a unified framework. additionally, we introduce the intrusion detection operating characteristic (idoc) curves as a new ids performance tradeoff which combines in an intuitive way the variables that are more relevant to the intrusion detection evaluation problem. we also introduce a formal framework for reasoning about the performance of an ids and the proposed metrics against adaptive adversaries. we provide simulations and experimental results to illustrate the benefits of the proposed framework.
a security model of dynamic labeling providing a tiered approach to verification. in the proposed mandatory access control model, arbitrary label changing policies can be expressed. the relatively simple model can capture a wide variety of security policies, including high-water marks, downgrading, separation of duties, and chinese walls. the model forms the basis for a tiered approach to the formal development of secure systems, whereby security verification can be spread across what makes up the reference monitor and the security requirement specification. the advantage of this approach is that once a trusted computing base (tcb) is in place, reconfiguring it for different security requirements requires verification of just the new requirements. we illustrate the approach with a number of examples, including one policy that permits high-level subjects to make relabeling requests on low-level objects; the policy is multilevel secure.
evaluation of intrusion detectors: a decision theory approach. abstract: this paper presents a method of analysis for evaluating intrusion detection systems. the method can be used to compare the performance of intrusion detectors, to evaluate performance goals for intrusion detectors, and to determine the best configuration of an intrusion detector for a given environment. the method uses a decision analysis that integrates and extends roc (receiver operating characteristics) and cost analysis methods to provide an expected cost metric. we provide general results and illustrate the method in several numerical examples that cover a range of detectors operating that meet a performance goal and two actual detectors operating in a realistic environment. we demonstrate that, contrary to common advice, the value of an intrusion detection system and the optimal operation of that system depend not only on the system's roc curve, but also on cost metrics and the hostility of the operating environment as summarized by the probability of intrusion. extensions of the method are outlined, and conclusions are drawn.
retrofitting legacy code for authorization policy enforcement. researchers have argued that the best way to construct a secure system is to proactively integrate security into the design of the system. however, this tenet is rarely followed because of economic and practical considerations. instead, security mechanisms are added as the need arises, by retrofitting legacy code. existing techniques to do so are manual and ad hoc, and often result in security holes. we present program analysis techniques to assist the process of retrofitting legacy code for authorization policy enforcement. these techniques can be used to retrofit legacy servers, such as x window, web, proxy, and cache servers. because such servers manage multiple clients simultaneously, and offer shared resources to clients, they must have the ability to enforce authorization policies. a developer can use our techniques to identify security-sensitive locations in legacy servers, and place reference monitor calls to mediate these locations. we demonstrate our techniques by retrofitting the x11 server to enforce authorization policies on its x clients.
deterring voluntary trace disclosure in re-encryption mix networks. an all too real threat to the privacy offered by a mix network is that individual mix administrators may volunteer partial tracing information to a coercer. while this threat can never be eliminated - coerced mix servers could simply be forced to reveal all their secret data - we can deter administrators from succumbing to coercive attacks by raising the stakes. we introduce the notion of a trace-deterring mix permutation to guarantee privacy, and show how it ensures that a collateral key (used for an arbitrary purpose) be automatically revealed given any end-to-end trace from input to output elements. however, no keying material is revealed to a party who simply knows what input element corresponds to what output element. our techniques are sufficiently efficient to be deployed in large-scale elections, thereby providing a sort of publicly verifiable privacy guarantee. their impact on the size of the anonymity set - while quantifiable - are not of practical concern.
what do we mean by entity authentication? abstract: the design of authentication protocols has proven to be surprisingly error-prone. we suggest that this is partly due to a language problem. the objectives of entity authentication are usually given in terms of human encounters while we actually implement message passing protocols. we propose various translations of the high-level objectives into a language appropriate for communication protocols. in addition, protocols are often specified at too low a level of abstraction. we argue that encryption should not be used as a general primitive as it does not capture the specific purpose for using a cryptographic function in aparticular protocol.
leap-frog packet linking and diverse key distributions for improved integrity in network broadcasts. we present two new approaches to improving the integrity of network broadcasts and multicasts with low storage and computation overhead. the first approach is a leapfrog linking protocol for securing the integrity of packets as they traverse a network during a broadcast, such as in the setup phase for link-state routing. this technique allows each router to gain confidence about the integrity of a packet before passing it on to the next router; hence, allows many integrity violations to be stopped immediately in their tracks. the second approach is a novel key predistribution scheme that we use in conjunction with a small number of hashed message authentication codes (hmacs), which allows end-to-end integrity checking as well as improved hop-by-hop integrity checking. our schemes are suited to environments, such as in ad hoc and overlay networks, where routers can share only a small number of symmetric keys. moreover, our protocols do not use encryption (which, of course, can be added as an optional security enhancement). instead, security is based strictly on the use of one-way hash functions; hence, our algorithms are considerably faster than those based on traditional public-key signature schemes. this improvement in speed comes with only modest reductions in the security for broadcasting, as our schemes can tolerate small numbers of malicious routers, provided they donýt form significant cooperating coalitions.
efficient intrusion detection using automaton inlining. host-based intrusion detection systems attempt to identify attacks by discovering program behaviors that deviate from expected patterns. while the idea of performing behavior validation on-the-fly and terminating errant tasks as soon as a violation is detected is appealing, existing systems exhibit serious shortcomings in terms of accuracy and/or efficiency. to gain acceptance, a numberof technical advances are needed. in this paper we focus on automated, conservative, intrusion detection techniques, i.e. techniques which do not require human intervention and do not suffer from false positives. we present a static analysis algorithm for constructing a flow- and context-sensitive model of a program that allows for efficient online validation. context-sensitivity is essential to reduce the number of impossible control-flow paths accepted by the intrusion detection system because such paths provide opportunities for attackers to evade detection. an important consideration for on-the-fly intrusion detection is to reduce the performance overhead caused by monitoring. compared to the existing approaches, our inlined automaton model (iam) presents a good tradeoff between accuracy and performance. on a 32k line program, the monitoring overhead is negligible. while the space requirements of a naive iam implementation can be quite high, compaction techniques can be employed to substantially reduce that footprint.
using memory errors to attack a virtual machine. we present an experimental study showing that softmemory errors can lead to serious security vulnerabilitiesin java and .net virtual machines, or in any system thatrelies on type-checking of untrusted programs as a protectionmechanism. our attack works by sending to the jvma java program that is designed so that almost any memoryerror in its address space will allow it to take controlof the jvm. all conventional java and .net virtual machinesare vulnerable to this attack. the technique of theattack is broadly applicable against other language-basedsecurity schemes such as proof-carrying code.we measured the attack on two commercial java virtualmachines: sun's and ibm's. we show that a single-biterror in the java program's data space can be exploitedto execute arbitrary code with a probability ofabout 70%, and multiple-bit errors with a lower probability.our attack is particularly relevant against smart cardsor tamper-resistant computers, where the user has physicalaccess (to the outside of the computer) and can usevarious means to induce faults; we have successfully usedheat. fortunately, there are some straightforward defensesagainst this attack.
analysis of the linux random number generator. linux is the most popular open source project. the linux random number generator is part of the kernel of all linux distributions and is based on generating randomness from entropy of operating system events. the output of this generator is used for almost every security protocol, including tls/ssl key generation, choosing tcp sequence numbers, and file system and email encryption. although the generator is part of an open source project, its source code (about 2500 lines of code) is poorly documented, and patched with hundreds of code patches. we used dynamic and static reverse engineering to learn the operation of this generator. this paper presents a description of the underlying algorithms and exposes several security vulnerabilities. in particular, we show an attack on the forward security of the generator which enables an adversary who exposes the state of the generator to compute previous states and outputs. in addition we present a few cryptographic flaws in the design of the generator, as well as measurements of the actual entropy collected by it, and a critical analysis of the use of the generator in linux distributions on diskless devices.
filtering postures: local enforcement for global policies. a abstract: when packet filtering is used as a security mechanism, different routers may need to cooperate to enforce the desired security policy. it is difficult to ensure that they will do so correctly. we introduce a simple language for expressing global network access control policies of a kind that filtering routers are capable of enforcing. we then introduce an algorithm that, given the network topology, will compute a set of filters for the individual routers; these filters are guaranteed to enforce the policy correctly. since these filters may not provide optimal service, a human must sometimes alter them. a second algorithm compares a resulting set of filters to the global network access control policy to determine all policy violations, or to report that none exist. a prototype implementation demonstrates that the algorithms are efficient enough to give quick answers to questions of realistic scale.
authentication tests. suppose a principal in a cryptographic protocol creates and transmits a message containing a new value v, which it later receives back in cryptographically altered form. it can conclude that some principal possessing the relevant key has transformed the message containing v. in some circumstances, this must be a regular participant of the protocol, not the penetrator. an inference of this kind is an authentication test. we introduce two main kinds of authentication test. an outgoing test is one in which the new value v is transmitted in encrypted form, and only a regular participant can extract it from that form. an incoming test is one in which v is received back in encrypted form, and only a regular participant can put it in that form. we combine these two tests with a supplementary idea, the unsolicited test, and a related method for checking that certain values remain secret. together, they determine what authentication properties are achieved by a wide range of cryptographic protocols. in this paper, we introduce authentication tests and illustrate their power, giving new and straightforward proofs of security goals for several protocols. we also illustrate how to use the authentication tests as a heuristic for finding attacks against incorrect protocols. finally, we suggest a protocol design process. we express these ideas in the strand space formalism [21], and prove them correct elsewhere [8].
an experience using two covert channel analysis techniques on a real system design. this paper examines the application of two covert channel analysis techniques to a high level design for a real system, the honeywell secure ada® target (sat). the techniques used were a version of the noninterference model of multilevel security due to goguen and meseguer and the shared resource matrix method of kemmerer. both techniques were applied to the gypsy abstract model of the sat. the paper discusses the application of the techniques and the nature of the covert channels discovered. the relative strengths and weaknesses of the two methods are discussed and criteria for an ideal covert channel tool are developed.
catalytic inference analysis: detecting inference threats due to knowledge discovery. knowledge discovery in databases can be enhanced by introducing "catalytic relations" conveying external knowledge. the new information catalyzes database inference, manifesting latent channels. catalytic inference is imprecise in nature, but the granularity of inference may be fine enough to create security compromises. catalytic inference is computationally intensive. however, it can be automated by advanced search engines that gather and assemble knowledge from information repositories. the relentless information gathering potential of such search engines makes them formidable security threats.this paper presents a formalism for modeling and analyzing catalytic inference in "mixed'' databases containing various precise, imprecise and fuzzy relations. the inference formalism is flexible and robust, and well-suited to implementation.
muse : a computer assisted verification system. muse is a verification system which extends the collection of tools developed by sri international for their hierarchical development methodology (hdm). it enhances the sri system by providing a capability for proving invariants and constraints for the state machine described by a specification written in special (the specification language of hdm). in particular, it enables one to use the hdm system to meet the requirements for formal verification in a national computer security center a1 evaluation of a secure operating system. in addition to the tools provided by sri, muse has a parser, a facility to handle multiple modules, a formula generator, and a theorem prover. the theorem prover has a number of interesting features designed to facilitate human direction of the proving process. in concept, it is open-ended. we introduce the notion of a theorem prover kernel as a device for ensuring the logical soundness of the prover in the face of continual improvements to its functionality.
practical attacks on proximity identification systems (short paper). the number of rfid devices used in everyday life has increased, along with concerns about their security and user privacy. this paper describes our initial findings on practical attacks that we implemented against 'proximity' (iso 14443 a) type rfid tokens. focusing mainly on the rf communication interface we discuss the results and implementation of eavesdropping, unauthorized scanning and relay attacks. although most of these attack scenarios are regularly mentioned in literature little technical details have been published previously. we also present a short overview of mechanisms currently available to prevent these attacks.
performance of public-key-enabled kerberos authentication in large networks. abstract: several proposals have been made to public-key-enable various stages of the secret-key-based kerberos network authentication protocol. the computational requirements of public key cryptography are much higher than those of secret key cryptography, and the substitution of public key encryption algorithms for secret key algorithms impacts performance. this paper uses closed, class-switching queuing models to demonstrate the quantitative performance differences between pkcross and pktapp-two proposals for public-key-enabling kerberos. our analysis shows that, while pktapp is more efficient for authenticating to a single server, pkcross outperforms the simpler protocol if there are two or more remote servers per remote realm. this heuristic can be used to guide a high-level protocol that combines both methods of authentication to improve performance.
sdc secure release terminal project. the sdc secure release terminal srt) project provides a useful view of the process involved in constructing software whose code is intended to be formally verified to satisfy desired security properties.the purpose of the srt is to move appropriately classified data from a processing environment at one security level to a processing environmentat another level in machine readable form. this paper discusses the design process for the srt which was carried out using the sdc formal development methodology(fdm).the srt project is the first application of the fdm code level verification capabilities.however, since the code level verification has not yet been performed this paper concentrates on the design problems inherent in targeting a system for code level verification.
simulatable security and polynomially bounded concurrent composability. simulatable security is a security notion for multi-party protocols that implies strong composability features. the main definitional flavours of simulatable security are standard simulatability, universal simulatability, and black-box simulatability. all three come in "computational," "statistical" and "perfect" subflavours indicating the considered adversarial power. universal and black-box simulatability, in all of their subflavours, are already known to guarantee that the concurrent composition even of a polynomial number of secure protocols stays secure. we show that computational standard simulatability does not allow for secure concurrent composition of polynomially many protocols, but we also show that statistical standard simulatability does. the first result assumes the existence of an interesting cryptographic tool (namely time-lock puzzles), and its proof employs a cryptographic multi-party computation in an interesting and unconventional way.
hamsa: fast signature generation for zero-day polymorphicworms with provable attack resilience. zero-day polymorphic worms pose a serious threat to the security of internet infrastructures. given their rapid propagation, it is crucial to detect them at edge networks and automatically generate signatures in the early stages of infection. most existing approaches for automatic signature generation need host information and are thus not applicable for deployment on high-speed network links. in this paper, we propose hamsa, a network-based automated signature generation system for polymorphic worms which is fast, noise-tolerant and attack-resilient. essentially, we propose a realistic model to analyze the invariant content of polymorphic worms which allows us to make analytical attack-resilience guarantees for the signature generation algorithm. evaluation based on a range of polymorphic worms and polymorphic engines demonstrates that hamsa significantly outperforms polygraph [16] in terms of efficiency, accuracy, and attack resilience.
specifying and verifying hardware for tamper-resistant software. we specify a hardware architecture that supportstamper-resistant software by identifying an "idealized"model, which gives the abstracted actions available to asingle user program. this idealized model is compared toa concrete "actual" model that includes actions of an adversarialoperating system. the architecture is verified byusing a finite-state enumeration tool (a model checker) tocompare executions of the idealized and actual models. inthis approach, software tampering occurs if the system canenter a state where one model is inconsistent with the other.in performing the verification, we detected an replay attackscenario and were able to verify the security of our solutionto the problem. our methods were also able to verifythat all actions in the architecture are required, as well ascome up with a set of constraints on the operating system toguarantee liveness for users.
is electronic privacy achievable? &ldquo;you have zero privacy anyway. get over it.&rdquo; scott mcnealy, sun microsystemswhile secrecy and integrity policies are most often crafted for protection of corporate (e.g., commercial, educational and government) information, we understand privacy policies to be targeted toward the protection of information for and about individuals. the purpose of this panel is to focus on how new technologies are affecting privacy.
beyond proof-of-compliance: safety and availability analysis in trust management. trust management is a form of distributed access controlusing distributed policy statements. since one party maydelegate partial control to another party, it is natural toask what permissions may be granted as the result of policychanges by other parties. we study security propertiessuch as safety and availability for a family of trust managementlanguages, devising algorithms for deciding the possibleconsequences of certain changes in policy. while trustmanagement is more powerful in certain ways than mechanismsin the access matrix model, and the security propertiesconsidered are more than simple safety, we find that incontrast to the classical hru undecidability of safety properties,our primary security properties are decidable. inparticular, most properties we studied are decidable in polynomialtime. containment, the most complicated securityproperty we studied, is decidable in polynomial time for thesimplest tm language in the family. the problem becomesconp-hard when intersection or linked roles are added tothe language.
how to systematically classify computer security intrusions. this paper presents a classification of intrusions with respect to technique as well as to result. the taxonomy is intended to be a step on the road to an established taxonomy of intrusions for use in incident reporting, statistics, warning bulletins, intrusion detection systems etc. unlike previous schemes, it takes the viewpoint of the system owner and should therefore be suitable to a wider community than that of system developers and vendors only. it is based on data from a realistic intrusion experiment, a fact that supports the practical applicability of the scheme. the paper also discusses general aspects of classification, and introduces a concept called dimension. after having made a broad survey of previous work in the field, we decided to base our classification of intrusion techniques on a scheme proposed by neumann and parker in 1989 and to further refine relevant parts of their scheme. our classification of intrusion results is derived from the traditional three aspects of computer security: confidentiality, availability and integrity.
security and source code access: issues and realities. this position paper addresses some of the benefits and drawbacks for security of open access to source code. after a discussion of alternative models for open access to source code, the paper reviews the positive and negative implications of each for system security. the paper concludes that source code review can have real benefits for security, but that those benefits are not realized automatically, and that some source code access models introduce significant drawbacks.
a logical language for expressing authorizations. a major drawback of existing access control systems is that they have all been developed with a specific access control policy in mind. this means that all protection requirements (i.e., accesses to be allowed or denied) must be specified in terms of the policy enforced by the system. while this may be trivial for some requirements, specification of other requirements may become quite complex or even impossible. the reason for this is that a single policy simply cannot capture different protection requirements users may need to enforce on different data.in this paper we take a first step towards a model able to support different access control policies.we propose a logical language for the specification of authorizations on which such a model can be based.the language allows users to specify, together with the authorizations, the policy according to which access control decisions are to be made.policies are expressed by means of rules which enforce derivation of authorizations, conflict resolution, access control, and integrity constraint checking.
pixy: a static analysis tool for detecting web application vulnerabilities (short paper). the number and the importance of web applications have increased rapidly over the last years. at the same time, the quantity and impact of security vulnerabilities in such applications have grown as well. since manual code reviews are time-consuming, error-prone and costly, the need for automated solutions has become evident. in this paper, we address the problem of vulnerable web applications by means of static source code analysis. more precisely, we use flow-sensitive, interprocedural and context-sensitive data flow analysis to discover vulnerable points in a program. in addition, alias and literal analysis are employed to improve the correctness and precision of the results. the presented concepts are targeted at the general class of taint-style vulnerabilities and can be applied to the detection of vulnerability types such as sql injection, cross-site scripting, or command injection. pixy, the open source prototype implementation of our concepts, is targeted at detecting cross-site scripting vulnerabilities in php scripts. using our tool, we discovered and reported 15 previously unknown vulnerabilities in three web applications, and reconstructed 36 known vulnerabilities in three other web applications. the observed false positive rate is at around 50% (i.e., one false positive for each vulnerability) and therefore, low enough to permit effective security audits.
cache cookies for browser authentication (extended abstract). like conventional cookies, cache cookies are data objects that servers store in web browsers. cache cookies, however, are unintentional byproducts of protocol design for browser caches. they do not enjoy any explicit interface support or security policies. in this paper, we show that despite limitations, cache cookies can play a useful role in the identification and authentication of users. many users today block conventional cookies in their browsers as a privacy measure. the cache-cookie tools we propose can help restore lost usability and convenience to such users while maintaining good privacy. as we show, our techniques can also help combat online security threats such as phishing and pharming that ordinary cookies cannot. the ideas we introduce for cache-cookie management can strengthen ordinary cookies as well. the full version of this paper may be referenced at www.ravenwhite.com.
message authentication with manipulation detection code. in many applications of cryptography, assuring theauthenticity of communications is as important asprotecting their secrecy. a well known and securemethod of providing message authentication is tocompute a message authentication code (mac) byencrypting the message. if only one key is used toboth encrypt and authenticate a message, however,the system is subject to several forms ofcryptographic attack. techniques have also beensought for combining secrecy and authentication inonly one encryption pass, using a manipulationdetection code generated by noncryptographicmeans. previous investigations have shown that aproposed mdc technique involving block-by-blockexclusive-oring is not secure when used with thecipher block chaining (cbc) mode of operation of thedata encryption standard (des]. it is shown herethat the cipher feedback (cfei) mode of operationexhibits similar weaknesses. a linear addition modulo264 mdc is analyzed, including discussion of severalnovel attack scenarios. a quadratic congruentialmanipulation detection code is proposed to avoid theproblems of previous schemes.
networked cryptographic devices resilient to capture. abstract: we present a simple technique by which a device that performs private key operations (signatures or decryptions) in networked applications, and whose local private key is activated with a password or pin, can be immunized to off-line dictionary attacks in case the device is captured. our techniques do not assume tamper resistance of the device, but rather exploit the networked nature of the device, in that the device's private key operations are performed using a simple interaction with a remote server. this server, however, is untrusted--its compromise does not reduce the security of the device's private key unless the device is also captured--and need not have a prior relationship with the device. we further extend this approach with support for key disabling, by which the rightful owner of a stolen device can disable the device's private key even if the attacker already knows the user's password.
on access checking in capability-based systems. public descriptions of capability-based system designs often do not clarify the necessary details concerning the propagation of access rights within the systems. a casual reader may assume that it is adequate for capabilities to be passed in accordance with the rules for data copying. a system using such a rule cannot enforce either the military security policy or the bell and lapadula rules. the paper shows why this problem arises and provides a taxonomy of capability-based designs. within the space of design options defined by the taxonomy we identify a class of designs that cannot enforce the bell-lapadula rules and two designs that do allow their enforcement.
new key generation algorithms for multilevel security. this paper addresses one aspect ofthe problem of access control in a hierarchy.a general scheme is describedwhich allows a user to generate from hisown key the keys of users below him inthe hierarchy. two implementations ofthis scheme are then proposed andcompared in terms of security andefficiency to an existing one.
preserving information flow properties under refinement. abstract: in a stepwise development process, it is essential that system properties that have been already investigated in some phase need not be re-investigated in later phases. in formal developments, this corresponds to the requirement that properties are preserved under refinement. while safety and liveness properties are indeed preserved under most standard forms of refinement, it is well known that this is, in general, not true for information flow properties, a large and useful class of security properties. in this article, we propose a collection of refinement operators as a solution to this problem. we prove that these operators preserve information flow as well as other system properties. thus, information flow properties become compatible with step-wise development. moreover, we show that our operators are an optimal solution.
on the composition of secure systems. when complex systems are constructed from simpler components it isimportant to know how properties of the components behave undercomposition. in this article, we present various compositionalityresults for security properties. in particular, we introduce a novelsecurity property and show that this property is, in general,composable although it is weaker than forward correctability.moreover, we demonstrate that certain nontrivial security propertiesemerge under composition and illustrate how this fact can beexploited.all compositionality results that we present areverified with the help of a single, quite powerful lemma. basing onthis lemma, we also re-prove several already known compositionalityresults with the objective to unify these results. as a side effect,we obtain a classification of known compositionality results forsecurity properties.
on two proposals for on-line bankcard payments using open networks: problems and solutions. recently, two major bankcard payment instrument operators visa and mastercard published specifications for securing bankcard payment transactions on open networks for open scrutiny. (visa: secure transaction technology, stt; mastercard: secure electronic payment protocol, sepp.) based on their success in operating the existing on-line payment systems, both proposals use advanced cryptographic technologies to supply some security services that are well-understood to be inadequate in open networks, and otherwise specify systems similar to today's private-network versions. in this paper we reason that when an open network is used for underlying electronic commerce some subtle vulnerabilities will emerge and the two specifications are seen not in anticipation of them. a number of weaknesses are found as a result of missing and misuse of security services. missing and misused services include: authentication, non-repudiation, integrity, and timeliness. we identify problems and devise solutions while trying to keep the current successful working style of financial institutions being respected.
fang: a firewall analysis engine. today, even a moderately sized corporate intranet contains multiple firewalls and routers, which are all used to enforce various aspects of the global corporate security policy. configuring these devices to work in unison is difficult, especially if different vendors make them. even testing or reverse-engineering an existing configuration (say, when a new security administrator takes over) is hard. firewall configuration files are written in low-level formalisms, whose readability is comparable to assembly code, and the global policy is spread over all the firewalls that are involved.to alleviate some of these difficulties, we designed and implemented a novel firewall analysis tool. our software allows the administrator to easily discover and test the global firewall policy (either a deployed policy or a planned one). our tool uses a minimal description of the network topology, and directly parses the various vendor-specific low-level configuration files. it interacts with the user through a query-and-answer session, which is conducted at a much higher level of abstraction. a typical question our tool can answer is ¿from which machines can our dmz be reached, and with which services?¿ thus, our tool complements existing vulnerability analysis tools, as it can be used before a policy is actually deployed, it operates on a more understandable level of abstraction, and it deals with all the firewalls at once.
seeing-is-believing: using camera phones for human-verifiable authentication. current mechanisms for authenticating communication between devices that share no prior context are inconvenient for ordinary users, without the assistance of a trusted authority. we present and analyse seeing-is-believing (sib), a system that utilises 2d barcodes and camera-phones to implement a visual channel for authentication and demonstrative identification of devices. we apply this visual channel to several problems in computer security, including authenticated key exchange between devices that share no prior context, establishment of the identity of a tcg-compliant computing platform, and secure device configuration in the context of a smart home.
detection of denial-of-message attacks on sensor network broadcasts. so far, sensor network broadcast protocols assume a trustworthy environment. however, in safety and mission-critical sensor networks this assumption may not be valid and some sensor nodes might be adversarial. in these environments, malicious sensor nodes can deprive other nodes from receiving a broadcast message. we call this attack a denial-of-message attack (dom). in this paper, we model and analyze this attack, and present countermeasures. we present sis, a secure implicit sampling scheme that permits a broadcasting base station to probabilistically detect the failure of nodes to receive its broadcast, even if these failures result from an attacker motivated to induce these failures undetectably. sis works by eliciting authenticated acknowledgments from a subset of nodes per broadcast, where the subset is unpredictable to the attacker and tunable so as to mitigate acknowledgment implosion on the base station. we use a game-theoretic approach to evaluate this scheme in the face of an optimal attacker that attempts to maximize the number of nodes it denies the broadcast while remaining undetected by the base station, and show that sis significantly constrains such an attacker even in sensor networks exhibiting high intrinsic loss rates. we also discuss extensions that permit more targeted detection capabilities.
methods and limitations of security policy reconciliation. a security policy is a means by which participant session requirements are specified. however, existing frameworks provide limited facilities for the automatereconciliation of participant policies. this paper considers the limits and methods of reconciliation in a general-purpose policy model. we identify an algorithm for efficient two-policy reconciliation, and show that, in the worst-case, reconciliation of three or more policies is intractable. further, we suggest efficient heuristics for the detection and resolution of intractable reconciliation. based upon the policy model, we describe the design and implementation of the ismene policy language. the expressiveness of ismene, and indirectly of our model, is demonstrated through the representation and exposition of policies supported by existing policy languages. we conclude with brief notes on the integration and enforcement of ismene policy within the antigone communication system.
will openish source really improve security. will openish source really improve security? no.
fundamental limits on the anonymity provided by the mix technique. the mix technique forms the basis of many popular services that offer anonymity of communication in open and shared networks such as the internet. in this paper, fundamental limits on the anonymity provided by the mix technique are found by considering two different settings. first, we consider an information theoretic setting to determine the extent of information inherent in observations of the traffic passing through the mix.we show that if the size of sender anonymity sets is less than the total user population, the information contained in traffic observations is sufficient to deduce all communication relationships between senders and receivers using the mix. more importantly, we show that even if every user sends a message in each communication round, it is possible to compromise the anonymity significantly. we precisely characterize the extent of compromised anonymity in each case. in the second setting, we assume that the attacker has unlimited computational resources and is free to choose any attack algorithm. we derive tight upper and lower bounds on the minimum number of observations required to deduce all recipient peer-partners of a targeted user. the analysis done in these two settings reveals many discrete mathematical structures inherent in anonymity sets, and the intuition gained from these structures can be used when designing or using a mix based anonymity technique.
subvirt: implementing malware with virtual machines. attackers and defenders of computer systems both strive to gain complete control over the system. to maximize their control, both attackers and defenders have migrated to low-level, operating system code. in this paper, we assume the perspective of the attacker, who is trying to run malicious software and avoid detection. by assuming this perspective, we hope to help defenders understand and defend against the threat posed by a new class of rootkits. we evaluate a new type of malicious software that gains qualitatively more control over a system. this new type of malware, which we call a virtual-machine based rootkit (vmbr), installs a virtual-machine monitor underneath an existing operating system and hoists the original operating system into a virtual machine. virtual-machine based rootkits are hard to detect and remove because their state cannot be accessed by software running in the target system. further, vmbrs support general-purpose malicious services by allowing such services to run in a separate operating system that is protected from the target system. we evaluate this new threat by implementing two proof-of-concept vmbrs. we use our proof-of-concept vmbrs to subvert windows xp and linux target systems, and we implement four example malicious services using the vmbr platform. last, we use what we learn from our proof-of-concept vmbrs to explore ways to defend against this new threat. we discuss possible ways to detect and prevent vmbrs, and we implement a defense strategy suitable for protecting systems against this threat.
noninterference and intrusion detection. this paper presents an intrusion detection methodology based on the concept of noninterference for detecting race-condition attacks. in general, this type of attack occurs when an unprivilege process causes a privilege process to perform illegal operations by executing strategic operations in the appropriate timing window. we apply the non-interference model in a novel way that allows us to formally represent valid interleaving between privilege and unprivilege processes. instead of proving a system satis?es noninterference assertions, we derive an algorithm for checking the assertions at run-time based on the developed theory and a formal model of unix system calls. our methodology can detect unknown race-condition attacks. in addition, this work provides an example of the application of formal speci?cation and reasoning in intrusion detection.
execution monitoring of security-critical programs in distributed systems: a specification-based approach. abstract: we describe a specification-based approach to detect exploitations of vulnerabilities in security-critical programs. the approach utilizes security specifications that describe the intended behavior of programs and scans audit trails for operations that are in violation of the specifications. we developed a formal framework for specifying the security-relevant behavior of programs, on which we based the design and implementation of a real-time intrusion detection system for a distributed system. also, we wrote security specifications for 15 unix setuid root programs. our system detects attacks caused by monitored programs, including security violations caused by improper synchronization in distributed programs. our approach encompasses attacks that exploit previously unknown vulnerabilities in security-critical programs.
a practical revocation scheme for broadcast encryption using smart cards. we present an anti-pirate revocation scheme for broadcastencryption systems (e.g., pay tv), in which the data isencrypted to ensure payment by users. in the systems weconsider, decryption of keys is done on smartcards, and keymanagement is done in-band. our starting point is a recentscheme of naor and pinkas. the basic scheme uses secretsharing to remove up to t parties, is information theoreticsecure against coalitions of size t, and is capable of creatinga new group key. however, with current smartcard technology,this scheme is only feasible for small system parameters,allowing up to about 100 pirates to be revoked beforeall the smartcards need to be replaced.we first present a novel implementation method of theirbasic scheme that distributes the work in novel ways amongthe smartcard, set-top terminal, and center. based on this,we construct several improved schemes for many statefulrevocation rounds that scale to realistic system sizes. weallow up to about 10000 pirates to be revoked using currentsmartcard technology before re-carding is needed. thetransmission lengths of our constructions are on par withthose of the best tree-based schemes. however, our constructionshave much lower smartcard cpu complexity:only o (1) smartcard operations per revocation round, asopposed to a poly-logarithmic complexity of the best tree-basedschemes.we evaluate the system behavior via an exhaustive simulationstudy. our simulations show that with mild assumptionson the piracy discovery rate, our constructions canperform effective pirate revocation for realistic broadcastencryption scenarios.
remote physical device fingerprinting. we introduce the area of remote physical device fingerprinting, or fingerprinting a physical device, as opposed to an operating system or class of devices, remotely, and without the fingerprinted device's known cooperation. we accomplish this goal by exploiting small, microscopic deviations in device hardware: clock skews. our techniques do not require any modification to the fingerprinted devices. our techniques report consistent measurements when the measurer is thousands of miles, multiple hops, and tens of milliseconds away from the fingerprinted device, and when the fingerprinted device is connected to the internet from different locations and via different access technologies. further, one can apply our passive and semi-passive techniques when the fingerprinted device is behind a nat or firewall, and also when the device's system time is maintained via ntp or sntp. one can use our techniques to obtain information about whether two devices on the internet, possibly shifted in time or ip addresses, are actually the same physical device. example applications include: computer forensics; tracking, with some probability, a physical device as it connects to the internet from different public access points; counting the number of devices behind a nat even when the devices use constant or random ip ids; remotely probing a block of addresses to determine if the addresses correspond to virtual hosts, e.g., as part of a virtual honeynet; and unanonymizing anonymized network traces.
stateful intrusion detection for high-speed networks. as networks become faster there is an emerging need for security analysistechniques that can keep up with the increased network throughput. existingnetwork-based intrusion detection sensors can barely keep up withbandwidthsof a few hundred mbps. analysis tools that can deal with higher throughputareunable to maintain state between different steps of an attack or they arelimited to the analysis of packet headers. we propose a partitioningapproachto network security analysis that supports in-depth, stateful intrusiondetection on high-speed links. the approach is centered around a "slicing"mechanism that divides the overall network traffic into subsets ofmanageablesize. the traffic partitioning is done so that a single slice contains alltheevidence necessary to detect a specific attack, making sensor-to-sensorinteractions unnecessary. this paper describes the approach and presents afirst experimental evaluation of its effectiveness.
optical time-domain eavesdropping risks of crt displays. a new eavesdropping technique can be used to read cathode-ray tube(crt) displays at a distance. the intensity of the light emitted by araster-scan screen as a function of time corresponds to the videosignal convolved with the impulse response of the phosphors.experiments with a typical personal computer color monitor show thatenough high-frequency content remains in the emitted light to permitthe reconstruction of readable text by deconvolving the signalreceived with a fast photosensor. these optical compromisingemanations can be received even after diffuse reflection from a wall.shot noise from background light is the critical performance factor.in a sufficiently dark environment and with a large enough sensoraperture, practically significant reception distances are possible.this information security risk should be considered in applicationswith high confidentiality requirements, especially in those thatalready require "tempest"-shielded equipment designed to minimizeradio-frequency emission-security concerns.
information-theoretic measures for anomaly detection. abstract: anomaly detection is an essential component of the protection mechanisms against novel attacks. in this paper, we propose to use several information-theoretic measures, namely, entropy, conditional entropy, relative conditional entropy, information gain, and information cost for anomaly detection. these measures can be used to describe the characteristics of an audit data set, suggest the appropriate anomaly detection model(s) to be built, and explain the performance of the model(s). we use case studies on unix system call data, bsm data, and network tcpdump data to illustrate the utilities of these measures.
an efficient, dynamic and trust preserving public key infrastructure. nested certification is a methodology for efficient certificate path verification. nested certificates can be used together with classical certificates in the public key infrastructures (pkis). such a pki, which is called nested certificate based pki (npki), is proposed in this paper as alternative to classical pki. the npki formation model is a transition from an existing pki by issuing nested certificates. thus, we can extract efficiently verifiable nested certificate paths instead of classical certificate paths. npki is a dynamic system and involves several authorities in order to add a new user to the system. this uses the authorities idle time to the benefit of the verifiers. in this paper, we analyze the trade-off between the nested certification overhead and the time improvement on the certificate path verification. this trade-off is acceptable in order to generate quickly verifiable certificate paths. moreover, pki-to-npki transition preserves the existing hierarchy and trust relationships in the pki, so that it can be used for strictly hierarchical pkis.
protocol-independent secrecy. inductive proofs of secrecy invariants for cryptographic protocols can be facilitated by separating the protocol-dependent part from the protocol-independent part. our secrecy theorem encapsulates the use of induction so that the discharge of protocol-specific proof obligations is reduced to first-order reasoning. in addition, the verification conditions are modularly associated with the protocol messages. secrecy proofs for otway-rees and the corrected needham-schroeder protocol are given.
a practically implementable and tractable delegation logic. we address the goal of making delegation logic (dl) into a practically implementable and tractable trust-management system. dl is a logic-based knowledge representation (i.e., language) for authorization in large-scale, open, distributed systems.as introduced in [li, feigenbaum, and grosof 1999], dl inferencing is computationally intractable and highly impractical to implement. we introduce a new version of delegation logic that remedies these difficulties. to achieve this, we impose a syntactic restriction and redefine the semantics somewhat. we show that, for this revised version of dl, inferencing is computationally tractable under the same commonly met restrictions for which ordinary logic programs (olp) inferencing is tractable (e.g., datalog and bounded number of logical variables per rule).we give implementation architecture for this version of dl; it uses a delegation compiler from dl to olp and can modularly exploit a variety of existing olp inference engines. as proof of concept, we have implemented a large expressive subset of this version of dl, using this architecture.
graph-based authentication of digital streams. abstract: we consider the authentication of digital streams over a lossy network. the overall approach taken is graph-based, as this yields simple methods for controlling overhead, delay, and the ability to authenticate, while serving to unify many previously known hash- and mac-based techniques. the loss pattern of the network is defined probabilistically, allowing both bursty and random packet loss to be modeled. our authentication schemes are customizable by the sender of the stream; that is, within reasonable constraints on the input parameters, we provide schemes that achieve the desired authentication probability while meeting the input upper bound on the overhead per packet. in addition, we demonstrate that some of the shortcomings of previously known schemes correspond to easily identifiable properties of a graph, and hence, may be more easily avoided by taking a graph-based approach to designing authentication schemes.
practical inference control for data cubes (extended abstract). the fundamental problem for inference control in data cubes is how to efficiently calculate the lower and upper bounds for each cell value given the aggregations of cell values over multiple dimensions. in this paper, we provide the first practical solution for estimating exact bounds in two-dimensional irregular data cubes (i.e., data cubes in which certain cell values are known to a snooper). our results imply that the exact bounds cannot be obtained by a direct application of the fréchet bounds in some cases. we then propose a new approach to improve the classic fréchet bounds for any high-dimensional data cube in the most general case. the proposed approach improves upon the fréchet bounds in the sense that it gives bounds that are at least as tight as those computed by fréchet, yet is simpler in terms of time complexity. based on our solutions to the fundamental problem, we discuss two security applications, privacy protection of released data and fine-grained access control and auditing.
design of a role-based trust-management framework. we introduce the rt framework, a family of role-based trust-managementlanguages for representing policies and credentials in distributedauthorization. rt combines the strengths of role-based access controland trust-management systems and is especially suitable forattribute-based access control. using a few simple credential forms, rtprovides localized authority over roles, delegation in role definition,linked roles, and parameterized roles. rt also introduces manifoldroles, which can be used to express threshold and separation-of-dutypolicies, and delegation of role activations. we formally define thesemantics of credentials in the rt framework by presenting a translationfrom credentials to datalog rules.this translation also shows thatthis semantics is algorithmically tractable.
tamper-evident, history-independent, subliminal-free data structures on prom storage-or-how to store ballots on a voting machine (extended abstract). we enumerate requirements and give constructions for the vote storage unit of an electronic voting machine. in this application, the record of votes must survive even an unexpected failure of the machine; hence the data structure should be durable. at the same time, the order in which votes are cast must be hidden to protect the privacy of voters, so the data structure should be history-independent. adversaries may try to surreptitiously add or delete votes from the storage unit after the election has concluded, so the storage should be tamper-evident. finally, we must guard against an adversarial voting machine's attempts to mark ballots through the representation of the data structure, so we desire a subliminal-free representation. we leverage the properties of programmable read only memory (prom), a special kind of write-once storage medium, to meet these requirements. we give constructions for data structures on prom storage that simultaneously satisfy all our desired properties. our techniques can significantly reduce the need to verify code running on a voting machine.
on safety in discretionary access control. an apparently prevailing myth is that safety is undecidable in discretionary access control (dac); therefore, one needs to invent new dac schemes in which safety analysis is decidable. in this paper, we dispel this myth. we argue that dac should not be equated with the harrison-ruzzo-ullman access matrix scheme, in which safety is undecidable. we present an efficient (running time cubic in its input size) algorithm for deciding safety in the graham-denning dac scheme, which subsumes the dac schemes used in the literature on comparing dac with other access control models. we also counter several claims made in recent work by solworth and sloan, in which the authors present a new access control scheme based on labels and relabelling and assert that it can implement the full range of dac models. we present a precise characterization of their access control scheme and show that it does not adequately capture a relatively simple dac scheme.
cryptographic key generation from voice. abstract: we propose a technique to reliably generate a crypto-graphic key from a user's voice while speaking a password. the key resists cryptanalysis even against an attacker who captures all system information related to generating or verifying the cryptographic key. moreover, the technique is sufficiently robust to enable the user to reliably regenerate the key by uttering her password again. we describe an empirical evaluation of this technique using 250 utterances recorded from 50 users.
secure software architectures. abstract: the computer industry is increasingly dependent on open architectural standards for their competitive success. this paper describes a new approach to secure system design in which the various representations of the architecture of a software system are described formally and the desired security properties of the system are proven to hold at the architectural level. the main ideas are illustrated by means of the x/open distributed transaction processing reference architecture, which is formalized and extended for secure access control as defined by the bell-lapadula model. the extension allows vendors to develop individual components independently and with minimal concern about security. two important observations were gleaned on the implications of incorporating security into software architectures.
low-cost traffic analysis of tor. tor is the second generation onion router, supporting the anonymous transport of tcp streams over the internet. its low latency makes it very suitable for common tasks, such as web browsing, but insecure against traffic-analysis attacks by a global passive adversary. we present new traffic-analysis techniques that allow adversaries with only a partial view of the network to infer which nodes are being used to relay the anonymous streams and therefore greatly reduce the anonymity provided by tor. furthermore, we show that otherwise unrelated streams can be linked back to the same initiator. our attack is feasible for the adversary anticipated by the tor designers. our theoretical attacks are backed up by experiments performed on the deployed, albeit experimental, tor network. our techniques should also be applicable to any low latency anonymous network. these attacks highlight the relationship between the field of traffic-analysis and more traditional computer security issues, such as covert channel analysis. our research also highlights that the inability to directly observe network links does not prevent an attacker from performing traffic-analysis: the adversary can use the anonymising network as an oracle to infer the traffic load on remote nodes in order to perform traffic-analysis.
factors affecting distributed system security. recent work examining distributed system security requirements. is critiqued. a notion of trust based on distributed system topology and distributed system node evaluation levels proposed in that work is shown to be deficient. the notion fails to make allowances for the distributed system physical security environment, security factors related to the management of distributed systems by more than one jurisdictive authority, and the interactions that can occur between nodes supporting different mandatory and discretionary security mechanisms.
robust nonproprietary software. our ultimate goal here is to be able to develop robust systems and applications that are capable of satisfying serious requirements, not merely for security but also for reliability, fault tolerance, human safety, and survivability in the face of a wide range of realistic adversities - including hardware malfunctions, software glitches, inadvertent human actions, massive coordinated attacks, and acts of god. also relevant are additional operational requirements such as interoperability, evolvability and maintainability, as well as discipline in the software development process.
polygraph: automatically generating signatures for polymorphic worms. it is widely believed that content-signature-based intrusion detection systems (idses) are easily evaded by polymorphic worms, which vary their payload on every infection attempt. in this paper, we present polygraph, a signature generation system that successfully produces signatures that match polymorphic worms. polygraph generates signatures that consist of multiple disjoint content substrings. in doing so, polygraph leverages our insight that for a real-world exploit to function properly, multiple invariant substrings must often be present in all variants of a payload; these substrings typically correspond to protocol framing, return addresses, and in some cases, poorly obfuscated code. we contribute a definition of the polymorphic signature generation problem; propose classes of signature suited for matching polymorphic worm payloads; and present algorithms for automatic generation of signatures in these classes. our evaluation of these algorithms on a range of polymorphic worms demonstrates that polygraph produces signatures for polymorphic worms that exhibit low false negatives and false positives.
an authorization scheme for distributed object systems. this paper addresses the problem of distributed object system protection. a new authorization scheme is presented and described. it is based on the collaboration between a central authorization server and security kernels located on each site of the system. a novel approach to access rights management for such an architecture is detailed: it is based on a new kind of access rights and a new scheme of privilege delegation. this authorization scheme can be adapted to various security policies, including multilevel policies such as bell-lapadula. an extension of the bell-lapadula model to distributed object systems is presented and its implementation using the authorization scheme is described.
modified architecture for the sub-keys model. a secure implementation for subkeydatabase encryption is presented. bothvertical and horizontal accessto thecontrolencrypted date are defined anddescribed. communication protocolsbetween user and system are alsoprovided.
locating hidden servers. hidden services were deployed on the tor anonymous communication network in 2004. announced properties include server resistance to distributed dos. both the eff and reporters without borders have issued guides that describe using hidden services via tor to protect the safety of dissidents as well as to resist censorship. we present fast and cheap attacks that reveal the location of a hidden server. using a single hostile tor node we have located deployed hidden servers in a matter of minutes. although we examine hidden services over tor, our results apply to any client using a variety of anonymity networks. in fact, these are the first actual intersection attacks on any deployed public network: thus confirming general expectations from prior theory and simulation. we recommend changes to route selection design and implementation for tor. these changes require no operational increase in network overhead and are simple to make; but they prevent the attacks we have demonstrated. they have been implemented.
efficient multicast packet authentication using signature amortization. we describe a novel method for authenticating multicast packetsthat is robust against packet loss. our main focus is to minimize the sizeof the communication overhead required to authenticate the packets. ourapproach is to encode the hash values and the signatures with rabin'sinformation dispersal algorithm (ida) to construct an authenticationscheme that amortizes a single signature operation over multiple packets.this strategy is especially efficient in terms of space overhead, becausejust the essential elements needed for authentication (i.e., one hash perpacket and one signature per group of packets) are used in conjunctionwith an erasure code that is space optimal. to evaluate the performance ofour scheme, we compare our technique with four other previously proposedschemes using analytical and empirical results. two different bursty lossmodels are considered in the analyses.
distributed detection of node replication attacks in sensor networks. the low-cost, off-the-shelf hardware components in unshielded sensor-network nodes leave them vulnerable to compromise. with little effort, an adversary may capture nodes, analyze and replicate them, and surreptitiously insert these replicas at strategic locations within the network. such attacks may have severe consequences; they may allow the adversary to corrupt network data or even disconnect significant parts of the network. previous node replication detection schemes depend primarily on centralized mechanisms with single points of failure, or on neighborhood voting protocols that fail to detect distributed replications. to address these fundamental limitations, we propose two new algorithms based on emergent properties, i.e., properties that arise only through the collective action of multiple nodes. randomized multicast distributes node location information to randomly-selected witnesses, exploiting the birthday paradox to detect replicated nodes, while line-selected multicast uses the topology of the network to detect replication. both algorithms provide globally-aware, distributed node-replica detection, and line-selected multicast displays particularly strong performance characteristics. we show that emergent algorithms represent a promising new approach to sensor network security; moreover, our results naturally extend to other classes of networks in which nodes can be captured, replicated and re-inserted by an adversary.
number theoretic attacks on secure password schemes. abstract: encrypted key exchange (eke) (s. bellovin and m. merritt, 1992; 1993) allows two parties sharing a password to exchange authenticated information over an insecure network by using a combination of public and secret key cryptography. eke promises security against active attacks and dictionary attacks. other secure protocols have been proposed based on the use of randomized confounders (l. gong et al., 1993). we use some basic results from number theory to present password guessing attacks on all versions of eke discussed in the paper (s. bellovin and m. merritt, 1992) and we also offer countermeasures to the attacks. however for the rsa version of eke, we show that simple modifications are not enough to rescue the protocol. attacks are also presented on half encrypted versions of eke. we also show how randomized confounders cannot protect direct authentication protocol and secret public key protocol versions of a secure password scheme from attacks. we discuss why these attacks are possible against seemingly secure protocols and what is necessary to make secure protocols.
on the secrecy of timing-based active watermarking trace-back techniques. timing-based active watermarking schemes are developed to trace back attackers through stepping stone connections or anonymizing networks. by slightly changing packet timing, these schemes achieve robust correlation for encrypted network connections under timing perturbation. however, the manipulation on packet timing makes the schemes themselves a potential target of intelligent attackers. in this paper, we analyze the secrecy of the timingbased active watermarking techniques for tracing through stepping stones, and propose an attack scheme based on analyzing the packet delays between adjacent stepping stones. we develop attack techniques to infer important watermark parameters, and to recover and duplicate embedded watermarks. the resulting techniques enable an attacker to defeat the tracing systems in certain cases by removing watermarks from the stepping stone connections, or replicating watermarks in non-stepping stone connections. we also develop techniques to determine in real-time whether a stepping stone connection is being watermarked for trace-back purposes. we have performed substantial experiments using real-world data to evaluate these techniques. the experimental results demonstrate that for the watermark scheme being attacked (1) embedded watermarks can be successfully recovered and duplicated when the watermark parameters are not chosen carefully, and (2) the existence of watermarks in a network flow can always be quickly detected.
limitations on design principles for public key protocols. recent papers have taken a new look at cryptographic protocols from the perspective of proposing design principles. for years the main approach to cryptographic protocols has been logical, and a number of papers have examined the limitations of those logics. this paper takes a similar cautionary look at the design principal approach. limitations and exceptions are offered on some of the previously given basic design principals. the focus is primarily on public key protocols, especially on the order of signature and encryption. but, other principles are discussed as well. apparently secure protocols that fail to meet principles are presented. also presented are new attacks on protocols as well as previously claimed attacks which are not.
anonymous connections and onion routing. onion routing provides anonymous connections that are strongly resistant to both eavesdropping and traffic analysis. unmodified internet applications can use these anonymous connections by means of proxies. the proxies may also make communication anonymous by removing identifying information from the data stream. onion routing has been implemented on sun solaris 2.x with proxies for web browsing, remote logins, and e-mail. this paper's contribution is a detailed specification of the implemented onion routing system, a vulnerability analysis based on this specification, and performance results.
elk, a new protocol for efficient large-group key distribution. abstract: secure media broadcast over the internet poses unique security challenges. one problem access control to a large number of subscribers in a public broadcast. a common solution is to encrypt the broadcast data and to disclose the decryption key to legitimate receivers only. however, how do we securely and efficiently establish a shared secret among the legitimate receivers? and most importantly, how can we efficiently update the group key securely if receivers join or leave? how can we provide reliability for key update messages in a way that scales up to large groups? recent research makes substantial progress to address these challenges. current schemes feature efficient key update mechanisms assuming that the key updates are communicated reliably to the receivers. in practice, however, the principal impediment to achieve a scalable system is to distribute the key updates reliably to all receivers. we have designed and implemented elk, a novel key distribution protocol, to address these challenges with the following features:elk features perfectly reliable, super-efficient member joins.elk uses smaller key update messages than previous protocols.elk features a mechanism that allows short hint messages to be used for key recovery allowing a tradeoff of communication overhead with member computation.elk proposes to append a small amount of key update information to data packets, such that the majority of receivers can recover from lost key update messages.elk allows to trade off security with communication overhead.
hardening functions for large scale distributed computations. the past few years have seen the development of distributedcomputing platforms designed to utilize the spareprocessor cycles of a large number of personal computersattached to the internet in an effort to generate levelsof computing power normally achieved only with expensivesupercomputers. such large scale distributed computationsrunning in untrusted environments raise a numberof security concerns, including the potential for intentionalor unintentional corruption of computations, and for participantsto claim credit for computing that has not beencompleted. this paper presents two strategies for hardeningselected applications that utilize such distributed computations.specifically, we show that carefully seeding certaintasks with precomputed data can significantly increaseresistance to cheating (claiming credit for work not computed)and incorrect results. similar results are obtainedfor sequential tasks through a strategy of sharing the computationof n tasks among k > n nodes. in each case, theassociated cost is significantly less than the cost of assigningtasks redundantly.
the design and implementation of a multilevel secure log manager. abstract: this paper discusses the security issues involved in log management for a multilevel secure database system and presents a design and implementation of a prototype multilevel secure log manager. the main goal of a log manager is to provide high bandwidth and low flush latency. we examine the performance of our design, by observing the flush latency and log bandwidth. we also informally evaluate the security of our approach.
"why 6?" defining the operational limits of stide, an anomaly-based intrusion detector. anomaly-detection techniques have considerable promise for twodifficult and critical problems in information security and intrusiondetection: detecting novel attacks, and detecting masqueraders.oneof the best-known anomaly detectors used in intrusion detection isstide.developed at the university of new mexico, stide aims todetect attacks that exploit processes that run with root privileges.the original work on stide presented empirical results indicatingthat data sequences of length six and above were required foreffective intrusion detection.this observation has given rise tothe long-standing question, "why six?" accompanied by relatedquestions regarding the conditions under which six may or may not beappropriate.this paper addresses the "why six" issue by presenting anevaluation framework that maps out stide's effective operating space,and identifies the conditions that contribute to detectioncapability, particularly detection blindness.a theoreticaljustification explains the effectiveness of sequence lengths of sixand above, as well as the consequences of using other values.inaddition, results of an investigation are presented, comparingstide's anomaly-detection capabilities with those of a competingdetector.
a model for asynchronous reactive systems and its application to secure message transmission. abstract: we present a rigorous model for secure reactive systems in asynchronous networks with a sound cryptographic semantics, supporting abstract specifications and the composition of secure systems. this enables modular proofs of security, which is essential in bridging the gap between the rigorous proof techniques of cryptography and tool-supported formal proof techniques. the model follows the general simulatability approach of modern cryptography. a variety of network structures and trust models can be described, such as static and adaptive adversaries; some examples of this are given. as an example of our specification methodology we provide an abstract and complete specification for secure message transmission, improving on recent results by lynch, and verify one concrete implementation. our proof is based on a general theorem on the security of encryption in a reactive multi-user setting, generalizing a recent result by bellare et.al.
garbage collector memory accounting in language-based systems. language run-time systems are often called upon tosafely execute mutually distrustful tasks within the sameruntime, protecting them from other tasks' bugs or otherwisehostile behavior. well-studied access controls exist insystems such as java to prevent unauthorized reading orwriting of data, but techniques to measure and control resourceusage are less prevalent. in particular, most languagerun-time systems include no facility to account forand regulate heap memory usage on a per-task basis. thisoversight can be exploited by a misbehaving task, whichmight allocate and hold live enough memory to cause adenial-of-service attack, crashing or slowing down othertasks. in addition, tasks can legitimately share referencesto the same objects, and traditional approaches that chargememory to its allocator fail to properly account for thissharing. we present a method for modifying the garbagecollector, already present in most modern language run-timesystems, to measure the amount of live memory reachablefrom each task as it performs its regular duties. oursystem naturally distinguishes memory shared across tasksfrom memory reachable from only a single task without requiringincompatible changes to the semantics of the programminglanguage. our prototype implementation imposesnegligible performance overheads in a variety ofbenchmarks, yet provides enough information for the expressionof rich policies to express the limits on a task'smemory usage.
view-based access control with high assurance. view-based access control enables content-based and context-based security, as opposed to container-based security provided in operating systems. however, view-based access control in multilevel secure (mls) databases suffers from two problems: safety and assurance. we investigate view-based access control in mls relational databases for a large class of views expressible as project-select-join queries. we develop a polynomial-time label compilation algorithm that transforms view-level labeling to tuple-level labeling in such a way that guarantees safety and high assurance. we identify two problems related to optimal label compilation, and show that they are both np-complete even for totally ordered security lattices of size two.
run-time principals in information-flow type systems. information-flow type systems are a promising approach for enforcing strong end-to-end confidentiality and integrity policies. such policies, however, are usually specified in terms of static information&mdash;data is labeled high or low security at compile time. in practice, the confidentiality of data may depend on information available only while the system is running. this article studies language support for run-time principals, a mechanism for specifying security policies that depend on which principals interact with the system. we establish the basic property of noninterference for programs written in such language, and use run-time principals for specifying run-time authority in downgrading mechanisms such as declassification. in addition to allowing more expressive security policies, run-time principals enable the integration of language-based security mechanisms with other existing approaches such as java stack inspection and public key infrastructures. we sketch an implementation of run-time principals via public keys such that principal delegation is verified by certificate chains.
partitioning attacks: or how to rapidly clone some gsm cards. in this paper, we introduce a new class of side--channel attackscalled partitioning attacks. we have successfully launched a versionof the attack on several implementations of comp128, the popular gsmauthentication algorithm that has been deployed by different serviceproviders in several types of sim cards, to retrieve the 128 bit keyusing as few as 8 chosen plaintexts. we show how partitioning attackscan be used effectively to attack implementations that have beenequipped with ad hoc and inadequate countermeasures againstside--channel attacks. such ad hoc countermeasures are systemic inimplementations of cryptographic algorithms, such as comp128, whichrequire the use of large tables since there has been a mistaken beliefthat sound countermeasures require more resources than areavailable. to address this problem, we describe a newresource--efficient countermeasure for protecting table lookups incryptographic implementations and justify its correctness rigorously.
practical data-swapping: the first steps. the problem of statistical database confidentiality in releasing microdata is addressed through the use of approximate data-swapping. here, a portion of the microdata is replaced with a database that has been selected with approximately the same statistics. the result guarantees the confidentiality of the original data, while providing microdata with accurate statistics. methods for achieving such transformations are considered and analyzed through simulation.
toward acceptable metrics of authentication. abstract: authentication using a path of trusted intermediaries, each able to authenticate the next one in the path, is a well-known technique for authenticating entities in a large-scale system. recent work has extended this technique to include multiple paths in an effort to bolster authentication, but the success of this approach may be unclear in the face of intersecting paths, ambiguities in the meaning of certificates, and interdependencies in the use of different keys. several authors have thus proposed metrics to evaluate the confidence afforded by a set of paths. in this paper, we develop a set of guiding principles for the design of such metrics. we motivate our principles by showing how previous approaches fail with respect to them and what the consequences to authentication might be. we then propose a direction for constructing metrics that come closer to meeting our principles and thus, we believe, to being satisfactory metrics for authentication.
cobra: fine-grained malware analysis using stealth localized-executions. fine-grained code analysis in the context of malware is a complex and challenging task that provides insight into malware code-layers (polymorphic/metamorphic), its data encryption/ decryption engine, its memory layout etc., important pieces of information that can be used to detect and counter the malware and its variants. current research in fine-grained code analysis can be categorized into static and dynamic approaches. static approaches have been tailored towards malware and allow exhaustive fine-grained malicious code analysis, but lack support for self-modifying code, have limitations related to code-obfuscations and face the undecidability problem. given that most if not all malware employ self-modifying code and code-obfuscations, poses the need to analyze them at runtime using dynamic approaches. however, current dynamic approaches for fine-grained code analysis are not tailored specifically towards malware and lack support for multithreading, self-modifying/self-checking code and are easily detected and countered by ever-evolving anti-analysis tricks employed by malware. to address this problem we propose a powerful dynamic fine-grained malicious code analysis framework, codenamed cobra, to combat malware that are becoming increasingly hard to analyze. our goal is to provide a stealth, efficient, portable and easy-to-use framework supporting multithreading, self-modifying/self-checking code and any form of code obfuscation in both user- and kernel-mode on commodity operating systems. cobra cannot be detected or countered and can be dynamically and selectively deployed on malware specific code-streams while allowing other code-streams to execute as is. we also illustrate the framework utility by describing our experience with a tool employing cobra to analyze a real-world malware.
fingerprinting. this paper presents a generaldiscussion of the use of fingerprints, especiallyfingerprinted data, fingerprinting is classifiedin four orthogonal ways, and some illustrativeexamples are given. the basis for a statisticalanalysis of altered fingerprints is presented,along with an example simulation. the possibilityof more subtle fingerprints is discussed.
using model checking to analyze network vulnerabilities. even well administered networks are vulnerable to attacks due to the security ramifications of offering a variety of combined services. that is, services that are secure when offered in isolation nonetheless provide an attacker with a vulnerability to exploit when offered simultaneously. many current tools address vulnerabilities in the context of a single host. in this paper, we address vulnerabilities due to the configuration of various hosts in a network. in a different line of research, formal methods are often useful for generating test cases, and model checkers are particularly adept at this task due to their ability to generate counterexamples. in this paper, we address the network vulnerability problem with test cases, which amount to attack scenarios, generated by a model checker. we encode the vulnerabilities in a state machine description suitable for a model checker and then assert that an attacker cannot acquire a given privilege on a given host. the model checker either offers assurance that the assertion is true on the actual network or provides a counterexample detailing each step of a successful attack.
a communication agreement framework for access/action control. we introduce a framework for access/action control which shifts the emphasis from the participants to their relationships. the framework is based on a communication model in which participants negotiate the mutually agreed-upon boundary conditions of their relationships, and create social reference points by encapsulating them in compact "communication pacts," called "commpacts." commpacts are designed to provide a language enabling a social mechanism of coordinated expectation. we argue that in networked environments characterized by multiple authorities and "trusted proxies," this model can deal with the complexities of general (user- and content-dependent) distributed access/action control and provides a clear user-conceptual metaphor. the frame work embeds naturally into the existing legal and institutional infrastructure; it generalizes work in electronic contracting. commpacts can be seen as a third fundamental type next to access-control lists (acls) and capabilities.
intrusion detection via static analysis. abstract: one of the primary challenges in intrusion detection is modelling typical application behavior, so that we can recognize attacks by their atypical effects without raising too many false alarms. we show how static analysis may be used to automatically derive a model of application behavior. the result is a host-based intrusion detection system with three advantages: a high degree of automation, protection against a broad class of attacks based on corrupted code, and the elimination of false alarms. we report on our experience with a prototype implementation of this technique.
language-based generation and evaluation of nids signatures. we present a methodology to automatically construct robust signatures whose accuracy is based on formal reasoning so it can be systematically evaluated. our methodology is based on two formal languages that describe different properties of a given attack. the first language, called a session signature, describes temporal relations between the attack events. the second, called an attack invariant, describes semantic properties that hold in any instance of the attack. for example, an invariant may state that a given ftp attack must include a successful ftp login and can be launched only after the ftp representation mode has been set to ascii. we iteratively eliminate false positives and negatives from an initial session signature by comparing the signature language to the language of the invariant. we developed gard, a tool for session-signature construction, and used it to construct session signatures for multi-step attacks. we show that a session signature is more accurate than existing signatures.
a distributed secure system. we describe the design of a distributed general-purposecomputing system that enforces a multilevel security policy.the system is composed of standard unix systems and smalltrustworthy security mechanisms linked together in such a wayas to provide a total system which, is not only demonstrablysecure, but also highly efficient and cost effective. despite theheterogeneity of its components, the system as a whole appearsto be a single multilevel secure unix system, since the fact thatit is actually a distributed system is completely hidden from itsusers and their programs.this is achieved through the use ofthe "newcastle connection", a software subsystem that linkstogether multiple unix or unix-look-alike systems, withoutrequiring any changes to the source code of either the operatingsystem or any user programs. construction of a prototypeimplementation is in progress.
defending against denial-of-service attacks with puzzle auction. although client puzzles represent a promising approach to defend against certain classes of denial-of-service attacks, several questions stand in the way oftheir deployment in practice: e.g., how to set the puzzledifficulty in the presence of an adversary with unknowncomputing power, and how to integrate the approachwith existing mechanisms. in this paper, we attempt toaddress these questions with a new puzzle mechanismcalled the puzzle auction. our mechanism enables eachclient to "bid" for resources by tuning the difficulty ofthe puzzles it solves, and to adapt its bidding strategyin response to apparent attacks. we analyze the effectiveness of our auction mechanism and further demonstrate it using an implementation within the tcp protocol stack of the linux kernel. our implementationhas several appealing properties. it effectively defendsagainst syn ooding attacks, is fully compatible withtcp, and even provides a degree of interoperabilitywith clients with unmodified kernels: even without apuzzle-solving kernel, a client still can connect to a puzzle auction server under attack (albeit less effectivelythan those with puzzle-solving kernels, and at the costof additional server expense).
secure device pairing based on a visual channel (short paper). recently several researchers and practitioners have begun to address the problem of how to set up secure communication between two devices without the assistance of a trusted third party. mccune, et al. [4] proposed that one device displays the hash of its public key in the form of a barcode, and the other device reads it using a camera. mutual authentication requires switching the roles of the devices and repeating the above process in the reverse direction. in this paper, we show how strong mutual authentication can be achieved even with a unidirectional visual channel, without having to switch device roles. by adopting recently proposed improved pairing protocols, we propose how visual channel authentication can be used even on devices that have very limited displaying capabilities.
understanding trust management systems. abstract: this paper presents a mathematical framework for expressing trust management systems. the framework makes it easier to understand existing systems and to compare them to one another, as well as to design new systems. the framework defines the semantics of a trust management engine via a least fixpoint in a lattice, which, in some situations, leads to an efficient implementation. to demonstrate its flexibility, we present keynote and spki as instantiations of the framework.
statistical identification of encrypted web browsing traffic. encryption is often proposed as a tool for protecting the privacy ofworld wide web browsing.however, encryption--particularly astypically implemented in, or in concert with popular webbrowsers--does not hide all information aboutthe encryptedplaintext.specifically, http object count and sizes are oftenrevealed (or at least incompletely concealed). we investigate theidentifiability of world wide web traffic based on this unconcealedinformation in a large sample of web pages, and show that it sufficesto identify a significant fraction of them quite reliably.we alsosuggest some possible countermeasures against the exposure of thiskind of information and experimentally evaluate their effectiveness.
ensuring assurance in mobile computing. abstract: this paper introduces a panel discussion on establishing assurance evidence that mobile code applications perform as expected by the user, without the side effects that have been demonstrated as possible in constructed examples of malicious or "rogue" applets. the paper's principal authors, schaefer and pinsky, have been engaged in cooperative research with the javasoft community to gain understanding of the complexities of assurance for mobile code applications. the paper discusses part of this on-going research. the panel adds the voices and experience of a continuing researcher, dean, and of active practitioners from the principal vendors of mobile-code-enabled (and enabling) products. the panel actively debates the issues of providing compelling assurance evidence relating to the control of such code.
cognitive authentication schemes safe against spyware (short paper). can we secure user authentication against eavesdropping adversaries, relying on human cognitive functions alone, unassisted by any external computational device? to accomplish this goal, we propose challenge response protocols that rely on a shared secret set of pictures. under the considered brute-force attack the protocols are safe against eavesdropping, in that a modestly powered adversary who fully records a series of successful interactions cannot compute the user's secret. moreover, the protocols can be tuned to any desired level of security against random guessing, where security can be traded-off with authentication time. the proposed protocols have two drawbacks: first, training is required to familiarize the user with the secret set of pictures. second, depending on the level of security required, entry time can be significantly longer than with alternative methods. we describe user studies showing that people can use these protocols successfully, and quantify the time it takes for training and for successful authentication. we show evidence that the secret can be maintained for a long time (up to a year) with relatively low loss.
evaluating security properties of computer systems. the department of defense hasrecently published trusted computer systemevaluation criteria that provide the basisfor evaluating the effectiveness ofsecurity controls built into computersystems. this paper summarizes basicsecurity requirements and the technicalcriteria that are used to classify systemsinto eight hierarchical classes ofenhanced security protection. thesecriteria are used in specifying securityrequirements during acquisition, guidingthe design and development of trustedsystems and evaluating systems used toprocess sensitive information.
open source in security: visiting the bizarre. although open-source software development has virtues, there is reason to believe that the approach would not have a significant effect on the security of today's systems. the lion's share of vulnerabilities caused by software bugs is easily dealt with by means other than source code inspections. in addition, the tenets of open-source development are inhospitable to business models whose success depends on promoting secure systems.
security properties and csp. security properties such as confidentiality and authenticity may be considered in terms of the flow of messages within a network. to the extent that this characterization is justified, the use of a process algebra such as communicating sequential processes (csp) seems appropriate to describe and analyze them. this paper explores ways in which security properties may be described as csp specifications, how security mechanisms may be captured, and how particular protocols designed to provide these properties may be analyzed within the csp framework. the paper is concerned with the theoretical basis for such analysis. a sketch verification of a simple example is carried out as an illustration.
analysis of a denial of service attack on tcp. this paper analyzes a network-based denial of service attack for ip (internet protocol) based networks. it is popularly called syn flooding. it works by an attacker sending many tcp (transmission control protocol) connection requests with spoofed source addresses to a victim's machine. each request causes the targeted host to instantiate data structures out of a limited pool of resources. once the target host's resources are exhausted, no more incoming tcp connections can be established, thus denying further legitimate access.the paper contributes a detailed analysis of the syn flooding attack and a discussion of existing and proposed countermeasures. furthermore, we introduce a new solution approach, explain its design, and evaluate its performance. our approach offers protection against syn flooding for all hosts connected to the same local area network, independent of their operating system or networking stack implementation. it is highly portable, configurable, extensible, and requires neither special hardware, nor modifications in routers or protected end systems.
data mining methods for detection of new malicious executables. abstract: a serious security threat today is malicious executables, especially new, unseen malicious executables often arriving as email attachments. these new malicious executables are created at the rate of thousands every year and pose a serious security threat. current anti-virus systems attempt to detect these new malicious programs with heuristics generated by hand. this approach is costly and oftentimes ineffective. in this paper, we present a data-mining framework that detects new, previously unseen malicious executables accurately and automatically. the data-mining framework automatically found patterns in our data set and used these patterns to detect a set of new malicious binaries. comparing our detection methods with a traditional signature-based method, our method more than doubles the current detection rates for new malicious executables.
a fast automaton-based method for detecting anomalous program behaviors. abstract: forrest et al. introduced a new intrusion detection approach that identifies anomalous sequences of system calls executed by programs. since their work, anomaly detection on system call sequences has become perhaps the most successful approach for detecting novel intrusions. a natural way for learning sequences is to use a finite-state automaton (fsa). however, previous research seemed to indicate that fsa-learning is computationally expensive, that it cannot be completely automated, or that the space usage of the fsa may be excessive. we present a new approach in this paper that overcomes these difficulties. our approach builds a compact fsa in a fully automatic and efficient manner, without requiring access to source code for programs. the space requirements for the fsa is low--of the order of a few kilobytes for typical programs. the fsa uses only a constant time per system call during the learning as well as detection period. this factor leads to low overheads for intrusion detection. unlike many of the previous techniques, our fsa-technique can capture both short term and long term temporal relationships among system calls, and thus perform more accurate detection. for instance, the fsa can capture common program structures such as branches, joins, loops etc. this enables our approach to generalize and predict future behaviors from past behaviors. for instance, if a program executed a loop once in an execution, the fsa approach can generalize and predict that the same loop may be executed zero or more times in subsequent executions. as a result, the training periods needed for our fsa based approach are shorter. moreover, false positives are reduced without increasing the likelihood of missing attacks. this paper describes our fsa based technique and presents a comprehensive experimental evaluation of the technique.
extending ina jo with temporal logic. the authors give both informal and formal descriptions of both the current ina jo specification language and ina jo enhanced with temporal logic. they include details of a simple example to demonstrate the use of the proof system and details of an extended example to demonstrate the expressiveness of the enhanced language. the authors discuss their language design goals, decisions, and their implications.
run-time security evaluation (rtse) for distributed applications. formal security specifications for a distributed application can be checked for compliance at run-time using executable security assertions. we propose the run-time security evaluation (rtse) method which makes use of histories/traces of events, assertions and operational evaluation in the distributed environment to ensure the security specifications for the application are fulfilled at run-time. a model problem is used to aid in developing the security requirements formally.
safety in automated trust negotiation. exchange of attribute credentials is a means to establish mutual trust between strangers wishing to share resources or conduct business transactions. automated trust negotiation (atn) is an approach to regulate the exchange of sensitive information during this process. it treats credentials as potentially sensitive resources, access to which is under policy control. negotiations that correctly enforce policies have been called &ldquo;safe&rdquo; in the literature. prior work on atn lacks an adequate definition of this safety notion. in large part, this is because fundamental questions such as &ldquo;what needs to be protected in atn?&rdquo; and &ldquo;what are the security requirements?&rdquo; are not adequately answered. as a result, many prior methods of atn have serious security holes. we introduce a formal framework for atn in which we give precise, usable, and intuitive definitions of correct enforcement of policies in atn. we argue that our chief safety notion captures intuitive security goals. we give precise comparisons of this notion with two alternative safety notions that may seem intuitive, but that are seen to be inadequate under closer inspection. we prove that an approach to atn from the literature meets the requirements set forth in the preferred safety definition, thus validating the safety of that approach, as well as the usability of the definition.
kronos: a scalable group re-keying approach for secure multicast. in this paper, we describe a novel approach to scalable group re-keying for secure multicast. our approach, which we call kronos, is based upon the idea of periodic group re-keying. we first motivate our approach by showing that if a group is re-keyed on each membership change, as the size of the group increases and/or the rate at which members leave and join the group increases, the frequency of re-keying becomes the primary bottleneck for scalable group re-keying. in contrast, kronos can scale to handle large and dynamic groups because the frequency of re-keying is independent of the size and membership dynamics of the group. next, we describe how kronos can be used in conjunction with distributed key management frameworks such as igkmp, that use a single group-wide session key for encrypting communications between members of the group. using a detailed simulation, we compare the performance tradeoffs between kronos and other key management protocols.
active mapping: resisting nids evasion without altering traffic. a critical problem faced by a network intrusion detectionsystem (nids) is that of ambiguity.thenidscannot always determine what traffic reaches a givenhost nor how that host will interpret the traffic, and attackersmay exploit this ambiguity to avoid detection orcause misleading alarms. we present a lightweight solution,active mapping, which eliminates tcp/ip-basedambiguity in a nids' analysis with minimal runtimecost. active mapping efficiently builds profiles of thenetwork topology and the tcp/ip policies of hosts onthe network; a nids may then use the host profiles todisambiguate the interpretation of the network traffic ona per-host basis. active mapping avoids the semanticand performance problems of traffic normalization,inwhich traffic streams are modified to remove ambiguities.we have developed a prototype implementation ofactive mapping and modified a nids to use the activemapping-generated profile database in our tests. wefound wide variation across operating systems' tcp/ipstack policies in real-world tests (about 6,700 hosts), underscoringthe need for this sort of disambiguation.
vulnerabilities in synchronous ipc designs. recent advances in interprocess communication (ipc)performance have been exclusively based on thread-migratingipc designs. thread-migrating designs assumethat ipc interactions are synchronous, and that user-levelexecution will usually resume with the invoked process(modulo preemption). this ipc design approach offersshorter instruction path lengths, requires fewer locks, hassmaller instruction and data cache footprints, dramaticallyreduces tlb overheads, and consequently offershigher performance and lower timing variance than previousipc designs. with care, it can be performed as anatomic unit of operation.while the performance of thread-migrating ipc hasbeen examined in detail, the vulnerabilities implicit insynchronous ipc designs have not been examined indepth in the archival literature, and their implications foripc design have been actively misunderstood in at leastone recent publication. in addition to performance, asound ipc design must address concerns of asymmetrictrust and reproducibility and provide support for dynamicpayload lengths. previous ipc designs, including thoseof eros, mach, l4, flask, and pebble, satisfy only two ofthese three requirements.in this paper, we show how these three design objectivescan be met simultaneously. we identify the conflictof requirements and illustrate how their collision arisesin two well-documented ipc architectures: l4 and eros.we then show how all three design objectives are simultaneouslymet in the next generation eros ipc system.
security enhancement through product evaluation. this paper describes a major goal ofthe dod computer security center, which isto encouraqe the easy availability ofcomputer products with enhanced securityfeatures. the mechanisms by which this isto be accomplished are described. thereare detailed explanations of thepreliminary and final product evaluationprocesses. the paper then takes apragmatic view, from three perspectives,of how the process is actually working.finally, an update is included, whichdescribes the present status of theevaluation efforts underway. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
verifying the eros confinement mechanism. capability systems can be used to implement higher-level security policies including the property if a mechanism exists to ensure confinement. the implementation can be efficient if the ¿weak¿ access restriction described in this paper is introduced. in the course of developing eros, a pure capability system, it became clear that verifying the correctness of the confinement mechanism was necessary in establishing the security of the operating system. this paper presents a verification of the eros confinement mechanism with respect to a broad class of capability architectures (including eros). we give a formal statement of the requirements, construct a model of the architecture's security policy and operational semantics, and show that architectures covered by this model enforce the confinement requirements if a small number of initial static checks on the confined subsystem are satisfied. the method used generalizes to any capability system.
p5: a protocol for scalable anonymous communication. we present a protocol for anonymous communication over the internet. our protocol, called p5 (peer-to-peer personal privacy protocol) provides sender-, receiver-, and sender-receiver anonymity. p5 is designed to be implemented over the current internet protocols, and does not require any special infrastructure support. a novel feature of p5 is that it allows individual participants to trade-off degree of anonymity for communication efficiency, and hence can be used to scalably implement large anonymous groups. we present a description of p5 an analysis of its anonymity and communication efficiency, and evaluate its performance using detailed packet-level simulations.
automated generation and analysis of attack graphs. an integral part of modeling the global view of network security isconstructing attack graphs.in practice, attack graphs areproduced manually by red teams.construction by hand, however, istedious, error-prone, and impractical for attack graphs larger than ahundred nodes.in this paper we present an automated technique forgenerating and analyzing attack graphs.we base our technique onsymbolic model checking algorithms,letting us construct attack graphs automatically and efficiently.wealso describe two analyses to help decide which attacks would be mostcost-effective to guard against.we implemented our technique in atool suite and tested it on a small network example, which includesmodels of a firewall and an intrusion detection system.
defending anonymous communications against passive logging attack. we study the threat that passive logging attacks poseto anonymous communications. previous work analyzedthese attacks under limiting assumptions. we first describea possible defense that comes from breaking the assumptionof uniformly random path selection. our analysisshows that the defense improves anonymity in the staticmodel, where nodes stay in the system, but fails in a dynamicmodel, in which nodes leave and join. additionally,we use the dynamic model to show that the intersectionattack creates a vulnerability in certain peer-to-peer systemsfor anonymous communciations. we present simulationresults that show that attack times are significantlylower in practice than the upper bounds given by previouswork. to determine whether users' web traffic has communicationpatterns required by the attacks, we collectedand analyzed the web requests of users. we found that,for our study, frequent and repeated communication to thesame web site is common.
bind: a fine-grained attestation service for secure distributed systems. in this paper, we propose bind (binding instructions and data), a fine-grained attestation service for securing distributed systems. code attestation has recently received considerable attention in trusted computing. however, current code attestation technology is relatively immature. first, due to the great variability in software versions and configurations, verification of the hash is difficult. second, the time-of-use and time-of-attestation discrepancy remains to be addressed, since the code may be correct at the time of the attestation, but it may be compromised by the time of use. the goal of bind is to address these issues and make code attestation more usable in securing distributed systems. bind offers the following properties: 1) bind performs fine-grained attestation. instead of attesting to the entire memory content, bind attests only to the piece of code we are concerned about. this greatly simplifies verification. 2) bind narrowsthe gap between time-of-attestation and time-of-use. bind measures a piece of code immediately before it is executed and uses a sand-boxing mechanism to protect the execution of the attested code. 3) bind ties the code attestation with the data that the code produces, such that we can pinpoint what code has been run to generate that data. in addition, by incorporating the verification of input data integrity into the attestation, bind offers transitive integrity verification, i.e., through one signature, we can vouch for the entire chain of processes that have performed transformations over a piece of data. bind offers a general solution toward establishing a trusted environment for distributed system designers.
recent advances in the design and implementation of large integer factorization algorithms. the latest and possibly fastest of the generalfactoring methods for large composite numbers is thequadratic sieve of carl pomerance. a variation ofthe algorithm is described and an implementation issuggested which combines the forces of a fast pipelinecomputer such as the cray i, and a high speedhighly parallel array processor such as the goodyearmpp. a running time analysis, which is based onempirical data rather than asymptotic estimates,suggests that this method could be capable offactoring a 60 digit number in as little as 10minutes and a 100 digit number is as little as 60days of continuous computer time.
a generic attack on checksumming-based software tamper resistance. self-checking software tamper resistance mechanisms employing checksums, including advanced systems as recently proposed by chang and atallah (2002) and horne et al. (2002), have been promoted as an alternative to other software integrity verification techniques. appealing aspects include the promise of being able to verify the integrity of software independent of the external support environment, as well as the ability to automatically integrate checksumming code during program compilation or linking. in this paper, we show that the rich functionality of many modern processors, including ultrasparc and x86-compatible processors, facilitates automated attacks which defeat such checksumming by self-checking programs.
extended abstract: forward-secure sequential aggregate authentication. wireless sensors are employed in a wide range of applications. one common feature of many sensor settings is the need to communicate sensed data to some collection point or sink. this communication can be direct (to a mobile collector) or indirect - via other sensors towards a remote sink. in either case, a sensor might not be able to communicate to a sink at will. instead it might collect data and wait (for a potentially long time) for a signal to upload accumulated data directly. in a hostile setting, a sensor may be compromised and its post-compromise data can be manipulated. one important issue is forward security - how to ensure that precompromise data cannot be manipulated? since a typical sensor is limited in storage and communication facilities, another issue is how to minimize resource consumption by accumulated data. it turns out that current techniques are insufficient to address both challenges. to this end, we explore the notion of forward-secure sequential aggregate (fssagg) authentication schemes. we consider fssagg authentication schemes in the contexts of both conventional and public key cryptography and construct a fssagg mac scheme and a fssagg signature scheme, each suitable under different assumptions. this work represents the initial investigation of forward-secure aggregation and, although the proposed schemes are not optimal, we believe it opens a new direction for follow-on research.
accurate real-time identification of ip prefix hijacking. we present novel and practical techniques to accurately detect ip prefix hijacking attacks in real time to facilitate mitigation. attacks may hijack victim's address space to disrupt network services or perpetrate malicious activities such as spamming and dos attacks without disclosing identity. we propose novel ways to significantly improve the detection accuracy by combining analysis of passively collected bgp routing updates with data plane ingerprints of suspicious prefixes. the key insight is to use data plane information in the form of edge network ingerprinting to disambiguate suspect ip hijacking incidences based on routing anomaly detection. conflicts in data plane ingerprints provide much more definitive evidence of successful ip pre- fix hijacking. utilizing multiple real-time bgp feeds, we demonstrate the ability of our system to distinguish between legitimate routing changes and actual attacks. strong correlation with addresses that originate spam emails from a spam honeypot confirms the accuracy of our techniques.
verification of treaty compliance revisited. in a series of papers, the author has documentedthe evolution at the sandia national laboratoriesof a solution to the problem of how two mutuallydeceitful and distrusting parties -- the hostand the monitor -- can both trust a data acquisitionsystem whose function is to inform the monitor,and perhaps third parties, whether the hosthas or has not violated the terms of a treaty. thenational interests of the various participants,host, monitor and third parties, at first appear tobe mutually irreconcilable, however the conclusionof this paper will be that it is possible to simultaneouslysatisfy the interests of all parties. thetechnical device on which this fourth, and hopefullyfinal, iteration of treaty verification systemsis based is the concatenation of two or moretwo key cryptographic systems. in the resultingsystem no part of the rneasage need be kept secretfrom any participant at anytime; no party, nor collusionof fewer than all of the parties can utteran undetectable forgery;no unilateral action onthe part of any party can lessen the confidence ofthe others as to the authenticity of the data andfinally third parties can be logically persuadedof the authenticity of messages. thus, finallyafter a decade of development a complete technicalsolution is in hand for the problem of the verificationof treaty compliance.
modeling security-relevant data semantics. the use of an extended data model which represents both integrity and secrecy aspects of data is demonstrated. this semantic data model for security (sdms) provides a technique that assists domain experts, security officers, and database designers in first understanding their security requirements, and then translating them into a good database design. identifying security requirements at this semantic level provides the basis for analyzing the security requirements and the database design for inference and signaling vulnerabilities. another contribution is a comprehensive taxonomy of security-relevant data semantics that must be captured and understood to implement a multilevel secure automated information system.
worm origin identification using random moonwalks. we propose a novel technique that can determine both the host responsible for originating a propagating worm attack and the set of attack flows that make up the initial stages of the attack tree via which the worm infected successive generations of victims. we argue that knowledge of both is important for combating worms: knowledge of the origin supports law enforcement, and knowledge of the causal flows that advance the attack supports diagnosis of how network defenses were breached. our technique exploits the "wide tree" shape of a worm propagation emanating from the source by performing random "moonwalks" backward in time along paths of flows. correlating the repeated walks reveals the initial causal flows, thereby aiding in identifying the source. using analysis, simulation, and experiments with real world traces, we show how the technique works against both todayýs fast propagating worms and stealthy worms that attempt to hide their attack flows among background traffic.
pi: a path identification mechanism to defend against ddos attack. distributed denial of service (ddos) attacks continueto plague the internet. defense against these attacksis complicated by spoofed source ip addresses,which make it difficult to determine a packet's true origin.we propose pi (short for path identifier), a newpacket marking approach in which a path fingerprint isembedded in each packet, enabling a victim to identifypackets traversing the same paths through the interneton a per packet basis, regardless of source ip addressspoofing.pi features many unique properties. it is a per-packetdeterministic mechanism: each packet traveling alongthe same path carries the same identifier. this allowsthe victim to take a proactive role in defending againsta ddos attack by using the pi mark to filter out packetsmatching the attackers' identifiers on a per packet basis.the pi scheme performs well under large-scale ddosattacks consisting of thousands of attackers, and is effectiveeven when only half the routers in the internetparticipate in packet marking. pi marking and filteringare both extremely light-weight and require negligiblestate.we use traceroute maps of real internet topologies(e.g. caida's skitter [5] and burch and cheswick's internetmap [3, 14]) to simulate ddos attacks and validateour design.
expander graphs for digital stream authentication and robust overlay networks. we use expander graphs to provide efficient new constructions for two security applications: authentication of long digital streams over lossy networks and building scalable,robust overlay networks. here is a summaryof our contributions: (1) to authenticate long digital streams over lossy networks,we provide a construction with a provable lower bound on the ability to authenticate a packet and that lower bound is independent of the size of the graph.to achieve this,we present an authentication expander graph with constant degree.(previous work,such as [ms01],used authentication graphs but requir ed graphs with degree linear in the number of vertices. ) (2) to build efficient,robust,and scalable overlay networks,we provide a construction using undirected expander graphs with a provable lower bound on the ability of a broadcast message to successfully reach any receiver.this also gives us a new,more efficient solution to the decentralized certicate revocation problem [wlm00].
practical techniques for searches on encrypted data. it is desirable to store data on data storage servers such as mail servers and file servers in encrypted form to reduce security and privacy risks. however, this usually implies that one has to sacrifice functionality for security. for example, if a client wishes to retrieve only documents containing certain words, it was not previously known how to let the data storage server perform the search and answer the query without loss of data confidentiality.in this paper, we describe our cryptographic schemes for the problem of searching on encrypted data and provide proofs of security for the resulting crypto systems. our techniques have a number of crucial advantages. they are provably secure: they provide provable secrecy for encryption, in the sense that the untrusted server cannot learn anything about the plain text when only given the ciphertext; they provide query isolation for searches, meaning that the untrusted server cannot learn anything more about the plaintext than the search result; they provide controlled searching, so that the untrusted server cannot search for an arbitrary word without the user's authorization; they also support hidden queries, so that the user may ask the untrusted server to search for a secret word without revealing the word to the server. the algorithms we present are simple, fast (for a document of length $n$, the encryption and search algorithms only need o(n) stream cipher and block cipher operations), and introduce almost no space and communication overhead, and hence are practical to use today.
automatically generating malicious disks using symbolic execution. many current systems allow data produced by potentially malicious sources to be mounted as a file system. file system code must check this data for dangerous values or invariant violations before using it. because file system code typically runs inside the operating system kernel, even a single unchecked value can crash the machine or lead to an exploit. unfortunately, validating file system images is complex: they form dags with complex dependency relationships across massive amounts of data bound together with intricate, undocumented assumptions. this paper shows how to automatically find bugs in such code using symbolic execution. rather than running the code on manually-constructed concrete input, we instead run it on symbolic input that is initially allowed to be "anything." as the code runs, it observes (tests) this input and thus constrains its possible values. we generate test cases by solving these constraints for concrete values. the approach works well in practice: we checked the disk mounting code of three widely-used linux file systems: ext2, ext3, and jfs and found bugs in all of them where malicious data could either cause a kernel panic or form the basis of a buffer overflow attack.
escort: securing scout paths. abstract: scout is a communication oriented operating system that can be specialized for different information appliances. it uses paths as an explicit first class object to describe the flow of information through the system. escort is the security architecture for scout. it uses the explicit knowledge provided by a path abstraction to secure information flow in a flexible manner.
self-healing key distribution with revocation. we address the problem of establishing a group key amongst a dynamicgroup of users over an unreliable, or lossy, network.we term ourkey distribution mechanisms self-healing because users arecapable of recovering lost group keys on their own, withoutrequesting additional transmissions from the group manager, thuscutting back on network traffic, decreasing the load on the groupmanager, and reducing the risk of user exposure through trafficanalysis. a user must be a member both before and after the sessionin which a particular key is sent in order to be able to recover thekey through self-healing. binding the ability to recover keys tomembership status enables the group manager to use short broadcaststo establish group keys, independent of the group size.inaddition, the self-healing approach to key distribution isstateless, meaning that a group member who has been off-line forsome time is able to recover new session keys immediately aftercoming back on-line.
fireman: a toolkit for firewall modeling and analysis. security concerns are becoming increasingly critical in networked systems. firewalls provide important defense for network security. however, misconfigurations in firewalls are very common and significantly weaken the desired security. this paper introduces fireman, a static analysis toolkit for firewall modeling and analysis. by treating firewall configurations as specialized programs, fireman applies static analysis techniques to check misconfigurations, such as policy violations, inconsistencies, and inefficiencies, in individual firewalls as well as among distributed firewalls. fireman performs symbolic model checking of the firewall configurations for all possible ip packets and along all possible data paths. it is both sound and complete because of the finite state nature of firewall configurations. fireman is implemented by modeling firewall rules using binary decision diagrams (bdds), which have been used successfully in hardware verification and model checking. we have experimented with fireman and used it to uncover several real misconfigurations in enterprise networks, some of which have been subsequently confirmed and corrected by the administrators of these networks.
a unified scheme for resource protection in automated trust negotiation. automated trust negotiation is an approach to establishingtrust between strangers through iterative disclosure ofdigital credentials. in automated trust negotiation, accesscontrol policies play a key role in protecting resources fromunauthorized access. unlike in traditional trust managementsystems, the access control policy for a resource isusually unknown to the party requesting access to the resource,when trust negotiation starts. the negotiating partiescan rely on policy disclosures to learn each other's accesscontrol requirements. however, a policy itself may alsocontain sensitive information. disclosing policies' contentsunconditionally may leak valuable business information orjeopardize individuals' privacy. in this paper, we proposeunipro, a unified scheme to model protection of resources,including policies, in trust negotiation. unipro improves onprevious work by modeling policies as first-class resources,protecting them in the same way as other resources, providingfine-grained control over policy disclosure, and clearlydistinguishing between policy disclosure and policy satisfaction,which gives users more flexibility in expressing theirauthorization requirements. we also show that unipro canbe used with practical negotiation strategies without jeopardizingautonomy in the choice of strategy, and present criteriaunder which negotiations using unipro are guaranteedto succeed in establishing trust.
cryptovirology: extortion-based security threats and countermeasures. traditionally, cryptography and its applications are defensive in nature, and provide privacy, authentication, and security to users. in this paper we present the idea of ``cryptovirology'' which employs a twist on cryptography, showing that it can also be used offensively. by being offensive we mean that it can be used to mount extortion based attacks that cause loss of access to information, loss of confidentiality, and information leakage, tasks which cryptography typically prevents. in this paper we analyze potential threats and attacks that rogue use of cryptography can cause when combined with rogue software (viruses, trojan horses), and demonstrate them experimentally by presenting an implementation of a ``cryptovirus'' that we have tested (we took careful precautions in the process to insure that the virus remained contained). public-key cryptography is essential to the attacks that we demonstrate (which we call "cryptovirological attacks''). we also suggest countermeasures and mechanisms to cope with and prevent such attacks. these attacks have implications on how the use of cryptographic tools should be managed and audited in general purpose computing environments, and imply that access to cryptographic tools should be well controlled. the experimental virus demonstrates how cryptographic packages can be condensed into a small space, which may have independent applications (e.g., cryptographic module design in small mobile devices).
deniable password snatching: on the possibility of evasive electronic espionage. abstract: cryptovirology has recently been introduced as a means of mounting active viral attacks using public key cryptography. it has been shown to be a tool for extortion attacks and "electronic warfare", where attacks are mounted against information resources. the natural question to ask is whether cryptovirology is also useful in the area of spying via malware. we demonstrate that cryptovirology does help in "electronic espionage" and allows the spy to conceal his or her identity (as well as past collected information). specifically, we present an attack that can be mounted by a cryptotrojan that allows the attacker to gather information (passwords) from a system in such a way that the attacker cannot be proven guilty beyond reasonable doubt. that is, even if the attacker is under surveillance on the local machine from when he first attacks the target machine, to when he obtains the passwords, and even if the leaked information is made available to the attacker exclusively, he still cannot be caught. the threat is made possible by the combination of public key cryptography, probabilistic encryption, and the use of public information (i/o or communication) channels which together form a "secure receiver-anonymous channel". the machine can be standalone or networked. what we learn from the attack is extracted as general tools and basic principles for "espionage attacks".
a general theory of security properties. abstract: we present a general theory of possibilistic security properties. we show that we can express a security property as a predicate that is true of every set containing all the traces with the same low level event sequence. given this security predicate, we show how to construct a partial ordering of security properties. we also discuss information flow and present the weakest property such that no information can flow from high level users to low level users. finally, we present a comparison of our framework and mclean's (1994) selective interleaving functions framework.
using replication and partitioning to build secure distributed systems. a challenging unsolved security problem is how to specifyand enforce system-wide security policies; this problemis even more acute in distributed systems with mutual distrust.this paper describes a way to enforce policies fordata confidentiality and integrity in such an environment.programs annotated with security specifications are staticallychecked and then transformed by the compiler to runsecurely on a distributed system with untrusted hosts. thecode and data of the computation are partitioned acrossthe available hosts in accordance with the security specification.the key contribution is automatic replication ofcode and data to increase assurance of integrity-withoutharming confidentiality, and without placing undue trustin any host. the compiler automatically generates securerun-time protocols for communication among the replicatedcode partitions. results are given from a prototype implementationapplied to various distributed programs.
a fair non-repudiation protocol. abstract: a fair non-repudiation protocol should not give the sender of a message an advantage over the receiver, or vice versa. we present a fair non-repudiation protocol that requires a trusted third party but attempts to minimize its involvement in the execution of the protocol. we draw particular attention to the nonstandard use of encryption in our protocol and discuss some aspects of its formal verification.
casting out demons: sanitizing training data for anomaly sensors. the efficacy of anomaly detection (ad) sensors depends heavily on the quality of the data used to train them. artificial or contrived training data may not provide a realistic view of the deployment environment. most realistic data sets are dirty; that is, they contain a number of attacks or anomalous events. the size of these high-quality training data sets makes manual removal or labeling of attack data infeasible. as a result, sensors trained on this data can miss attacks and their variations. we propose extending the training phase of ad sensors (in a manner agnostic to the underlying ad algorithm) to include a sanitization phase. this phase generates multiple models conditioned on small slices of the training data. we use these “micro-models” to produce provisional labels for each training input, and we combine the micro-models in a voting scheme to determine which parts of the training data may represent attacks. our results suggest that this phase automatically and significantly improves the quality of unlabeled training data by making it as “attack-free” and “regular” as possible in the absence of absolute ground truth. we also show how a collaborative approach that combines models from different networks or domains can further refine the sanitization process to thwart targeted training or mimicry attacks against a single site.
robust de-anonymization of large sparse datasets. we present a new class of statistical de-anonymization attacks against high-dimensional micro-data, such as individual preferences, recommendations, transaction records and so on. our techniques are robust to perturbation in the data and tolerate some mistakes in the adversary's background knowledge. we apply our de-anonymization methodology to the netflix prize dataset, which contains anonymous movie ratings of 500,000 subscribers of netflix,the world's largest online movie rental service. we demonstrate that an adversary who knows only a little bit about an individual subscriber can easily identify this subscriber's record in the dataset. using the internet movie database as the source of background knowledge, we successfully identified the netflix records of known users, uncovering their apparent political preferences and other potentially sensitive information.
jamming-resistant key establishment using uncoordinated frequency hopping. we consider the following problem: how can two devices that do not share any secrets establish a shared secret key over a wireless radio channel in the presence of a communication jammer? an inherent challenge in solving this problem is that known anti-jamming techniques (e.g.,frequency hopping or direct-sequence spread spectrum) which should support device communication during the key establishment require that the devices share a secret spreading key (or code) prior to the start of their communication. this requirement creates a circular dependency between anti-jamming spread-spectrum communication and key establishment, which has so far not been addressed. in this work, we propose an uncoordinated frequency hopping (ufh) scheme that breaks this dependencyand enables key establishment in the presence of a communication jammer. we perform a detailed analysis of our ufh scheme and show its feasibility, both in terms of execution time and resource requirements.
efficient and robust tcp stream normalization. network intrusion detection and prevention systems are vulnerable to evasion by attackers who craft ambiguous traffic to breach the defense of such systems. a normalizer is an inline network element that thwarts evasion attempts by removing ambiguities in network traffic. a particularly challenging step in normalization is the sound detection of inconsistent tcp retransmissions, wherein an attacker sends tcp segments with different payloads for the same sequence number space to present a network monitor with ambiguous analysis. normalizers that buffer all unacknowledged data to verify the consistency of subsequent retransmissions consume inordinate amounts of memory on high-speed links. on the other hand, normalizers that buffer only the hashes of unacknowledged segments cannot verify the consistency of 20-30% of retransmissions that, according to our traces, do not align with the original transmissions. this paper presents the design of robonorm, a normalizer that buffers only the hashes of unacknowledged segments, and yet can detect all inconsistent retransmissions in any tcp byte stream. robonorm consumes 1-2 orders of magnitude less memory than normalizers that buffers all unacknowledged data, and is amenable to a high-speed implementation. robonorm is also robust to attacks that attempt to compromise its operation or exhaust its resources.
towards practical privacy for genomic computation. many basic tasks in computational biology involve operations on individual dna and protein sequences. these sequences, even when anonymized, are vulnerable to re-identification attacks and may reveal highly sensitive information about individuals. we present a relatively efficient, privacy-preserving implementation of fundamental genomic computations such as calculating the edit distance and smith-waterman similarity scores between two sequences. our techniques are cryptographically secure and significantly more practical than previous solutions. we evaluate our prototype implementation on sequences from the pfam database of protein families, and demonstrate that its performance is adequate for solving real-world sequence-alignment and related problems in a privacy-preserving manner. furthermore, our techniques have applications beyond computational biology. they can be used to obtain efficient, privacy-preserving implementations for many dynamic programming algorithms over distributed datasets.
preventing memory error exploits with wit. attacks often exploit memory errors to gain control over the execution of vulnerable programs. these attacks remain a serious problem despite previous research on techniques to prevent them. we present write integrity testing (wit), a new technique that provides practical protection from these attacks. wit uses points-to analysis at compile time to compute the control-flow graph and the set of objects that can be written by each instruction in the program. then it generates code instrumented to prevent instructions from modifying objects that are not in the set computed by the static analysis, and to ensure that indirect control transfers are allowed by the control-flow graph. to improve coverage where the analysis is not precise enough, wit inserts small guards between the original program objects. we describe an efficient implementation with optimizations to reduce space and time overhead. this implementation can be used in practice because it compiles c and c++ programs without modifications, it has high coverage with no false positives, and it has low overhead. wit's average runtime overhead is only 7% across a set of cpu intensive benchmarks and it is negligible when io is the bottleneck.
pacemakers and implantable cardiac defibrillators: software radio attacks and zero-power defenses. our study analyzes the security and privacy properties of an implantable cardioverter defibrillator (icd). introduced to the u.s. market in 2003, this model of icd includes pacemaker technologyand is designed to communicate wirelessly with a nearby external programmer in the 175 khz frequency range. after partially reverse-engineering the icd's communications protocol with an oscilloscope and a software radio, we implemented several software radio-based attacks that could compromise patient safety and patient privacy. motivated by our desire to improve patient safety, and mindful of conventional trade-offs between security and power consumption for resource-constrained devices, we introduce three new zero-power defenses based on rf power harvesting. two of these defenses are human-centric, bringing patients into the loop with respect to the security and privacy of their implantable medical devices (imds). our contributions provide a scientific baseline for understanding the potential security and privacy risks of current and future imds, and introduce human-perceptible and zero-power mitigation techniques that address those risks. to the best of our knowledge, this paper is the first in our community to use general-purpose software radios to analyze and attack previously unknown radio communications protocols.
automated formal analysis of a protocol for secure file sharing on untrusted storage. we study formal security properties of a state-of-the-art protocol for secure file sharing on untrusted storage, in the automatic protocol verifier proverif. as far as we know, this is the first automated formal analysis of a secure storage protocol. the protocol, designed as the basis for the file system plutus, features a number of interesting schemes like lazy revocation and key rotation. these schemes improve the protocol's performance, but complicate its security properties. our analysis clarifies several ambiguities in the design and reveals some unknown attacks on the protocol. we propose corrections, and prove precise security guarantees for the corrected protocol.
expressive declassification policies and modular static enforcement. this paper provides a way to specify expressive declassification policies, in particular, when, what, and where policies that include conditions under which downgrading is allowed. secondly, an end-to-end semantic property is introduced, based on a model that allows observations of intermediate low states as well as termination. an attacker's knowledge only increases at explicit declassification steps, and within limits set by policy. thirdly, static enforcement is provided by combining type-checking with program verification techniques applied to the small subprograms that carry out declassifications. enforcement is proved sound for a simple programming language and the extension to object-oriented programs is described.
cloaker: hardware supported rootkit concealment. rootkits are used by malicious attackers who desire to run software on a compromised machine without being detected. they have become stealthier over the years as a consequence of the ongoing struggle between attackers and system defenders. in order to explore the next step in rootkit evolution and to build strong defenses, we look at this issue from the point of view of an attacker. we construct cloaker, a proof-of-concept rootkit for the arm platform that is non-persistent and only relies on hardware state modifications for concealment and operation. a primary goal in the design of cloaker is to not alter any part of the host operating system (os) code or data, thereby achieving immunity to all existing rootkit detection techniques which perform integrity, behavior and signature checks of the host os. cloaker also demonstrates that a self-contained execution environment for malicious code can be provided without relying on the host os for any services. integrity checks of hardware state in each of the machine's devices are required in order to detect rootkits such as cloaker. we present a framework for the linux kernel that incorporates integrity checks of hardware state performed by device drivers in order to counter the threat posed by rootkits such as cloaker.
stack and queue integrity on hostile platforms. when computationally intensive tasks have to be carried out on trusted, but limited, platforms such as smart cards, it becomes necessary to compensate for the limited resources (memory, cpu speed) by off-loading implementations of data structures on to an available (but insecure, untrusted) fast coprocessor. however, data structures, such as stacks, queues, rams, and hash tables, can be corrupted (and made to behave incorrectly) by a potentially hostile implementation platform or by an adversary knowing or choosing data structure operations. this paper examines approaches that can detect violations of datastructure invariants, while placing limited demands on the resources of the secure computing platform.
trojan detection using ic fingerprinting. hardware manufacturers are increasingly outsourcing their ic fabrication work overseas due to their much lower cost structure. this poses a significant security risk for ics used for critical military and business applications. attackers can exploit this loss of control to substitute trojan ics for genuine ones or insert a trojan circuit into the design or mask used for fabrication. we show that a technique borrowed from side-channel cryptanalysis can be used to mitigate this problem. our approach uses noise modeling to construct a set of fingerprints for an ic family utilizing sidechannel information such as power, temperature, and electromagnetic (em) profiles. the set of fingerprints can be developed using a few ics from a batch and only these ics would have to be invasively tested to ensure that they were all authentic. the remaining ics are verified using statistical tests against the fingerprints. we describe the theoretical framework and present preliminary experimental results to show that this approach is viable by presenting results obtained by using power simulations performed on representative circuits with several different trojan circuitry. these results show that trojans that are 3-4 orders of magnitude smaller than the main circuit can be detected by signal processing techniques. while scaling our technique to detect even smaller trojans in complex ics with tens or hundreds of millions of transistors would require certain modifications to the ic design process, our results provide a starting point to address this important problem.
gradual release: unifying declassification, encryption and key release policies. information security has a challenge to address: enabling information-flow controls with expressive information release (or declassification) policies. existing approaches tend to address some aspects of information release, exposing the other aspects for possible attacks. it is striking that these approaches fall into two mostly separate categories: revelation-based (as in information purchase, aggregate computation, moves in a game, etc.) and encryption-based declassification (as in sending encrypted secrets over an untrusted network, storing passwords, etc.). this paper introduces gradual release, a policy that unifies declassification, encryption, and key release policies. we model an attacker's knowledge by the sets of possible secret inputs as functions of publicly observable outputs. the essence of gradual release is that this knowledge must remain constant between releases. gradual release turns out to be a powerful foundation for release policies, which we demonstrate by formally connecting revelation-based and encryption-based declassification. furthermore, we show that gradual release can be provably enforced by security types and effects.
information flow in the peer-reviewing process. we investigate a new type of information flow in the electronic publishing process. we show that the use of postscript in this process introduces serious confidentiality issues. in particular, we explain how the reviewer's anonymity in the peer-reviewing process can be compromised by maliciously prepared postscript documents. a demonstration of this attack is available. we briefly discuss how this attack can be extended to other document formats as well.
lurking in the shadows: identifying systemic threats to kernel data. the integrity of kernel code and data is fundamental to the integrity of the computer system. tampering with the kernel data is an attractive venue for rootkit writers since malicious modifications in the kernel are harder to identify compared to their user-level counterparts. so far however, the pattern followed for tampering is limited to hiding malicious objects in user-space. this involves manipulating a subset of kernel data structures that are related to intercepting user requests or affecting the user's view of the system. hence, defense techniques are built around detecting such hiding behavior. the contribution of this paper is to demonstrate a new class of stealthy attacks that only exist in kernel space and do not employ any hiding techniques traditionally used by rootkits. these attacks are stealthy because the damage done to the system is not apparent to the user or intrusion detection systems installed on the system and are symbolic of a more systemic problem present throughout the kernel. our goal in building these attack prototypes was to show that such attacks are not only realistic, but worse; they cannot be detected by the current generation of kernel integrity monitors, without prior knowledge of the attack signature.
ciphertext-policy attribute-based encryption. in several distributed systems a user should only be able to access data if a user posses a certain set of credentials or attributes. currently, the only method for enforcing such policies is to employ a trusted server to store the data and mediate access control. however, if any server storing the data is compromised, then the confidentiality of the data will be compromised. in this paper we present a system for realizing complex access control on encrypted data that we call ciphertext-policy attribute-based encryption. by using our techniques encrypted data can be kept confidential even if the storage server is untrusted; moreover, our methods are secure against collusion attacks. previous attribute- based encryption systems used attributes to describe the encrypted data and built policies into user's keys; while in our system attributes are used to describe a user's credentials, and a party encrypting data determines a policy for who can decrypt. thus, our methods are conceptually closer to traditional access control methods such as role-based access control (rbac). in addition, we provide an implementation of our system and give performance measurements.
extended abstract: provable-security analysis of authenticated encryption in kerberos. kerberos is a widely-deployed network authentication protocol that is being considered for standardization. many works have analyzed its security, identifying flaws and often suggesting fixes, thus helping the protocol's evolution. several recent results present successful formal-methodsbased verification of a significant portion of the current version 5, and some even imply security in the computational setting. for these results to hold, encryption in kerberos should satisfy strong cryptographic security notions. however, neither currently deployed as part of kerberos encryption schemes nor their proposed revisions are known to provably satisfy such notions. we take a close look at kerberos' encryption and confirm that most of the options in the current version provably provide privacy and authenticity, some with slight modification that we suggest. our results complement the formal-methods-based analysis of kerberos that justifies its current design.
endorsed e-cash. an electronic cash (e-cash) scheme lets a user withdraw money from a bank and then spend it anonymously. e-cash can be used only if it can be securely and fairly exchanged for electronic goods or services. in this paper, we introduce and realize endorsed e-cash. an endorsed e-coin consists of a lightweight endorsement x and the rest of the coin which is meaningless without x. we reduce the problem of exchanging e-cash to that of exchanging endorsements. we demonstrate the usefulness of endorsed e-cash by exhibiting simple and efficient solutions to two important problems: (1) optimistic and unlinkable fair exchange of e-cash for digital goods and services; and (2) onion routing with incentives and accountability for the routers. finally, we show how to represent a set of n endorsements using just one endorsement; this means that the complexity of the fair exchange protocol for n coins is the same as for one coin, making e-cash all the more scalable and suitable for applications. our fair exchange of multiple e-coins protocol can be applied to fair exchanges of (almost) any secrets.
fuzzy multi-level security: an experiment on quantified risk-adaptive access control. this paper presents a new model for, or rather a new way of thinking about adaptive, risk-based access control. our basic premise is that there is always inherent uncertainty and risk in access control decisions that is best addressed in an explicit way. we illustrate this concept by showing how the rationale of the well-known, bell-lapadula model based, multi-level security (mls) access control model could be used to develop a risk-adaptive access control model. this new model is more like a fuzzy logic control system [9] than a traditional access control system and hence the name "fuzzy mls". the long version of this paper is published as an ibm research report [3].
shieldgen: automatic data patch generation for unknown vulnerabilities with informed probing. in this paper, we present shieldgen, a system for automatically generating a data patch or a vulnerability signature for an unknown vulnerability, given a zero-day attack instance. the key novelty in our work is that we leverage knowledge of the data format to generate new potential attack instances, which we call probes, and use a zero-day detector as an oracle to determine if an instance can still exploit the vulnerability; the feedback of the oracle guides our search for the vulnerability signature. we have implemented a shieldgen prototype and experimented with three known vulnerabilities. the generated signatures have no false positives and a low rate of false negatives due to imperfect data format specifications and the sampling technique used in our probe generation. overall, they are significantly more precise than the signatures generated by existing schemes. we have also conducted a detailed study of 25 vulnerabilities for which microsoft has issued security bulletins between 2003 and 2006. we estimate that shieldgen can produce high quality signatures for a large portion of those vulnerabilities and that the signatures are superior to the signatures generated by existing schemes.
attacking the ipsec standards in encryption-only configurations. we describe new attacks which break any rfccompliant implementation of ipsec making use of encryption-only esp in tunnel mode. the new attacks are both efficient and realistic: they are ciphertext-only and need only the capability to eavesdrop on esp-encrypted traffic and to inject traffic into the network. we report on our experiences in applying the attacks to a variety of implementations of ipsec.
improving the robustness of private information retrieval. since 1995, much work has been done creating protocols for private information retrieval (pir). many variants of the basic pir model have been proposed, including such modifications as computational vs. information-theoretic privacy protection, correctness in the face of servers that fail to respond or that respond incorrectly, and protection of sensitive data against the database servers themselves. in this paper, we improve on the robustness of pir in a number of ways. first, we present a byzantine-robust pir protocol which provides information-theoretic privacy protection against coalitions of up to all but one of the responding servers, improving the previous result by a factor of 3. in addition, our protocol allows for more of the responding servers to return incorrect information while still enabling the user to compute the correct result. we then extend our protocol so that queries have information-theoretic protection if a limited number of servers collude, as before, but still retain computational protection if they all collude. we also extend the protocol to provide information-theoretic protection to the contents of the database against collusions of limited numbers of the database servers, at no additional communication cost or increase in the number of servers. all of our protocols retrieve a block of data with communication cost only o(.) times the size of the block, where . is the number of servers.
cryptanalysis of a cognitive authentication scheme (extended abstract). we present attacks against two cognitive authentication schemes [9] proposed at the 2006 ieee symposium on security and privacy. these authentication schemes are designed to be secure against eavesdropping attacks while relying only on human cognitive skills. they achieve authentication via challenge response protocols based on a shared secret set of pictures. our attacks use a sat solver to recover a user's secret key in a few seconds, after observing only a small number of successful logins. these attacks demonstrate that the authentication schemes of [9] are not secure against an eavesdropping adversary.
usable mandatory integrity protection for operating systems. existing mandatory access control systems for operating systems are difficult to use. we identify several principles for designing usable access control systems and introduce the usable mandatory integrity protection (umip) model that adds usable mandatory access control to operating systems. the umip model is designed to preserve system integrity in the face of network-based attacks. the usability goals for umip are twofold. first, configuring a umip system should not be more difficult than installing and configuring an operating system. second, existing applications and common usage practices can still be used under umip. umip has several novel features to achieve these goals. for example, it introduces several concepts for expressing partial trust in programs. furthermore, it leverages information in the existing discretionary access control mechanism to derive file labels for mandatory integrity protection. we also discuss our implementation of the umip model for linux using the linux security modules framework, and show that it is simple to configure, has low overhead, and effectively defends against a number of network-based attacks.
minimal tcb code execution. we propose an architecture that allows code to execute in complete isolation from other software while trusting only a tiny software base that is orders of magnitude smaller than even minimalist virtual machine monitors. our technique also enables more meaningful attestation than previous proposals, since only measurements of the security-sensitive portions of an application need to be included. we achieve these guarantees by leveraging hardware support provided by commodity processors from amd and intel that are shipping today.
a systematic approach to uncover security flaws in gui logic. to achieve end-to-end security, traditional machine-to-machine security measures are insufficient if the integrity of the human-computer interface is compromised. gui logic flaws are a category of software vulnerabilities that result from logic bugs in gui design/implementation. visual spoofing attacks that exploit these flaws can lure even securityconscious users to perform unintended actions. the focus of this paper is to formulate the problem of gui logic flaws and to develop a methodology for uncovering them in software implementations. specifically, based on an in-depth study of key subsets of internet explorer (ie) browser source code, we have developed a formal model for the browser gui logic and have applied formal reasoning to uncover new spoofing scenarios, including nine for status bar spoofing and four for address bar spoofing. the ie development team has confirmed all these scenarios and has fixed most of them in their latest build. through this work, we demonstrate that a crucial subset of visual spoofing vulnerabilities originate from gui logic flaws, which have a well-defined mathematical meaning allowing a systematic analysis.
beyond stack inspection: a unified access-control and information-flow security model. modern component-based systems, such as java and microsoft .net common language runtime (clr), have adopted stack-based access control (sbac). its purpose is to use stack inspection to verify that all the code responsible for a security-sensitive action is sufficiently authorized to perform that action. previous literature has shown that the security model enforced by sbac is flawed in that stack inspection may allow unauthorized code no longer on the stack to influence the execution of security-sensitive code. a different approach, history-based access control (hbac), is safe but may prevent authorized code from executing a security-sensitive operation if less trusted code was previously executed. in this paper, we formally introduce information-based access control (ibac), a novel security model that verifies that all and only the code responsible for a security-sensitive operation is sufficiently authorized. given an access-control policy á, we present a mechanism to extract from it an implicit integrity policy é, and we prove that ibac enforces é. furthermore, we discuss large-scale application code scenarios to which ibac can be successfully applied.
the emperor's new security indicators. we evaluate website authentication measures that are designed to protect users from man-in-the-middle, "phishing', and other site forgery attacks. we asked 67 bank customers to conduct common online banking tasks. each time they logged in, we presented increasingly alarming clues that their connection was insecure. first, we removed https indicators. next, we removed the participant's site-authentication image-the customer-selected image that many websites now expect their users to verify before entering their passwords. finally, we replaced the bank's password-entry page with a warning page. after each clue, we determined whether participants entered their passwords or withheld them. we also investigate how a study's design affects participant behavior: we asked some participants to play a role and others to use their own accounts and passwords. we also presented some participants with security-focused instructions. we confirm prior findings that users ignore https indicators: no participants withheld their passwords when these indicators were removed. we present the first empirical investigation of site-authentication images, and we find them to be ineffective: even when we removed them, 23 of the 25 (92%) participants who used their own accounts entered their passwords. we also contribute the first empirical evidence that role playing affects participants' security behavior: role-playing participants behaved significantly less securely than those using their own passwords.
multi-dimensional range query over encrypted data. we design an encryption scheme called multi-dimensional range query over encrypted data (mrqed), to address the privacy concerns related to the sharing of network audit logs and various other applications. our scheme allows a network gateway to encrypt summaries of network flows before submitting them to an untrusted repository. when network intrusions are suspected, an authority can release a key to an auditor, allowing the auditor to decrypt flows whose attributes (e.g., source and destination addresses, port numbers, etc.) fall within specific ranges. however, the privacy of all irrelevant flows are still preserved. we formally define the security for mrqed and prove the security of our construction under the decision bilinear diffie-hellman and decision linear assumptions in certain bilinear groups. we study the practical performance of our construction in the context of network audit logs. apart from network audit logs, our scheme also has interesting applications for financial audit logs, medical privacy, untrusted remote storage, etc. in particular, we show that mrqed implies a solution to its dual problem, which enables investors to trade stocks through a broker in a privacypreserving manner.
using rescue points to navigate software recovery. we present a new technique that enables software recovery in legacy applications by retrofitting exception-handling capabilities, error virtualization using rescue points. we introduce the idea of "rescue points" as program locations to which an application can recover its execution in the presence of failures. the use of rescue points reduces the chance of unanticipated execution paths thereby making recovery more robust by mimicking system behavior under controlled error conditions. these controlled error conditions can be thought of as a set erroneous inputs, like the ones used by most quality-assurance teams during software development, designed to stress-test an application. to discover rescue points applications are profiled and monitored during tests that bombard the program with bad/random inputs. the intuition is that by monitoring application behavior during these runs, we gain insight into how programmer-tested program points are used to propagate faults gracefully.
on the optimal communication complexity of multiphase protocols for perfect communication. in the perfectly secure message transmission (psmt) problem, two synchronized non-faulty players (or processors), the sender s and the receiver r are connected by n wires (each of which facilitates 2-way communication); s has a message, represented by a sequence of - elements from a finite field, that he wishes to send to r; after exchanging messages in phases r should correctly obtain s's message, while an adversary listening on and actively controlling any set of t (or less) wires should have no information about s's message. similarly, in the problem of perfect reliable message transmission (prmt), the receiver r should correctly obtain s's message, in spite of the adversary actively controlling any set of t (or less) wires.
a cryptographic decentralized label model. information-flow security policies are an appealing way of specifying confidentiality and integrity policies in information systems. most previous work on language-based security has assumed that programs run in a closed, managed environment and that they use potentially unsafe constructs, such as declassification, to interface to external communication channels, perhaps after encrypting data to preserve its confidentiality. this situation is unsatisfactory for systems that need to communicate over untrusted channels or use untrusted persistent storage, since the connection between the cryptographic mechanisms used in the untrusted environment and the abstract security labels used in the trusted language environment is ad hoc and unclear. this paper addresses this problem in three ways: first, it presents a simple, security-typed language with a novel mechanism called packages that provides an abstract means for creating opaque objects and associating them with security labels; well-typed programs in this language enforce noninterference. second, it shows how to implement these packages using public-key cryptography. this implementation strategy uses a variant of myers and liskov's decentralized label model, which supports a rich label structure in which mutually distrusting data owners can specify independent confidentiality and integrity requirements. third, it demonstrates that this implementation of packages is sound with respect to dolev-yao style attackers such an attacker cannot determine the contents of a package without possessing the appropriate keys, as determined by the security label on the package.
network flow watermarking attack on low-latency anonymous communication systems. many proposed low-latency anonymous communication systems have used various flow transformations such as traffic padding, adding cover traffic (or bogus packets), packet dropping, flow mixing, flow splitting, and flow merging to achieve anonymity. it has long been believed that these flow transformations would effectively disguise network flows, thus achieve good anonymity. in this paper, we investigate the fundamental limitations of flow transformations in achieving anonymity, and we show that flow transformations do not necessarily provide the level of anonymity people have expected or believed. by injecting unique watermark into the inter-packet timing domain of a packet flow, we are able to make any sufficiently long flow uniquely identifiable even if 1) it is disguised by substantial amount of cover traffic, 2) it is mixed or merged with a number of other flows, 3) it is split into a number subflows, 4) there is a substantial portion of packets dropped, and 5) it is perturbed in timing due to either natural network delay jitter or deliberate timing perturbation. in addition to demonstrating the theoretical limitations of low-latency anonymous communications systems, we develop the first practical attack on the leading commercial low-latency anonymous communication system. our real-time experiments show that our flow watermarking attack only needs about 10 minutes activeweb browsing traffic to "penetrate" the total net shield service provided by www.anonymizer.com. our analytical and empirical results demonstrate that achieving anonymity in low-latency communication systems is much harder than we have realized, and current flow transformation based low-latency anonymous communication systems need to be revisited.
dsss-based flow marking technique for invisible traceback. law enforcement agencies need the ability to conduct electronic surveillance to combat crime, terrorism, or other malicious activities exploiting the internet. however, the proliferation of anonymous communication systems on the internet has posed significant challenges to providing such traceback capability. in this paper, we develop a new class of flow marking technique for invisible traceback based on direct sequence spread spectrum (dsss), utilizing a pseudo-noise (pn) code. by interfering with a sender's traffic and marginally varying its rate, an investigator can embed a secret spread spectrum signal into the sender's traffic. the embedded signal is carried along with the traffic from the sender to the receiver, so the investigator can recognize the corresponding communication relationship, tracing the messages despite the use of anonymous networks. the secret pn code makes it difficult for others to detect the presence of such embedded signals, so the traceback, while available to investigators is, effectively invisible. we demonstrate a practical flow marking system which requires no training, and can achieve both high detection and low false positive rates. using a combination of analytical modeling, simulations, and experiments on tor (a popular internet anonymous communication system), we demonstrate the effectiveness of the dsss-based flow marking technique.
on the safety and efficiency of firewall policy deployment. firewall policy management is challenging and error-prone. while ample research has led to tools for policy specification, correctness analysis, and optimization, few researchers have paid attention to firewall policy deployment: the process where a management tool edits a firewall's configuration to make it run the policies specified in the tool. in this paper, we provide the first formal definition and theoretical analysis of safety in firewall policy deployment. we show that naive deployment approaches can easily create a temporary security hole by permitting illegal traffic, or interrupt service by rejecting legal traffic during the deployment. we define safe and most-efficient deployments, and introduce the shuffling theorem as a formal basis for constructing deployment algorithms and proving their safety. we present efficient algorithms for constructing most-efficient deployments in popular policy editing languages. we show that in certain widelyinstalled policy editing languages, a safe deployment is not always possible. we also show how to leverage existing diff algorithms to guarantee a safe, mostefficient, and monotonic deployment in other editing languages.
exploring multiple execution paths for malware analysis. malicious code (or malware) is defined as software that fulfills the deliberately harmful intent of an attacker. malware analysis is the process of determining the behavior and purpose of a given malware sample (such as a virus, worm, or trojan horse). this process is a necessary step to be able to develop effective detection techniques and removal tools. currently, malware analysis is mostly a manual process that is tedious and time-intensive. to mitigate this problem, a number of analysis tools have been proposed that automatically extract the behavior of an unknown program by executing it in a restricted environment and recording the operating system calls that are invoked. the problem of dynamic analysis tools is that only a single program execution is observed. unfortunately, however, it is possible that certain malicious actions are only triggered under specific circumstances (e.g., on a particular day, when a certain file is present, or when a certain command is received). in this paper, we propose a system that allows us to explore multiple execution paths and identify malicious actions that are executed only when certain conditions are met. this enables us to automatically extract a more complete view of the program under analysis and identify under which circumstances suspicious actions are carried out. our experimental results demonstrate that many malware samples show different behavior depending on input read from the environment. thus, by exploring multiple execution paths, we can obtain a more complete picture of their actions.
moats and drawbridges: an isolation primitive for reconfigurable hardware based systems. blurring the line between software and hardware, reconfigurable devices strike a balance between the raw high speed of custom silicon and the post-fabrication flexibility of general-purpose processors. while this flexibility is a boon for embedded system developers, who can now rapidly prototype and deploy solutions with performance approaching custom designs, this results in a system development methodology where functionality is stitched together from a variety of "soft ip cores," often provided by multiple vendors with different levels of trust. unlike traditional software where resources are managed by an operating system, soft ip cores necessarily have very fine grain control over the underlying hardware. to address this problem, the embedded systems community requires novel security primitives which address the realities of modern reconfigurable hardware. we propose an isolation primitive, moats and drawbridges, that are built around four design properties: logical isolation, interconnect traceability, secure reconfigurable broadcast, and configuration scrubbing. each of these is a fundamental operation with easily understood formal properties, yet maps cleanly and efficiently to a wide variety of reconfigurable devices. we carefully quantify the required overheads on real fpgas and demonstrate the utility of our methods by applying them to the practical problem of memory protection.
sybillimit: a near-optimal social network defense against sybil attacks. decentralized distributed systems such as peer-to-peer systems are particularly vulnerable to sybil attacks, where a malicious user pretends to have multiple identities (called sybil nodes). without a trusted central authority, defending against sybil attacks is quite challenging. among the small number of decentralized approaches, our recent sybilguard protocol [42] leverages a key insight on social networks to bound the number of sybil nodes accepted. although its direction is promising, sybilguard can allow a large number of sybil nodes to be accepted. furthermore, sybilguard assumes that social networks are fast mixing, which has never been confirmed in the real world. this paper presents the novel sybillimit protocol that leverages the same insight as sybilguard but offers dramatically improved and near-optimal guarantees. the number of sybil nodes accepted is reduced by a factor of theta(sqrt(n)), or around 200 times in our experiments for a million-node system. we further prove that sybillimit’s guarantee is atmost a log n factor away from optimal, when considering approaches based on fast-mixing social networks. finally, based on three large-scale real-world social networks, we provide the first evidence that real-world social networks are indeed fast mixing. this validates the fundamental assumption behind sybillimit’s and sybilguard’s approach.
verifying the safety of user pointer dereferences. operating systems divide virtual memory addresses into kernel space and user space. the interface of a modern operating system consists of a set of system call procedures that may take pointer arguments called user pointers. it is safe to dereference a user pointer if and only if it points into user space. if the operating system dereferences a user pointer that does not point into user space, then a malicious user application could gain control of the operating system, reveal sensitive data from kernel space, or crash the machine. because the operating system cannot trust user processes, the operating system must check that the user pointer points to user space before dereferencing it. in this paper, we present a scalable and precise static analysis capable of verifying the absence of unchecked user pointer dereferences. we evaluate an implementation of our analysis on the entire linux operating system with over 6.2 million lines of code with false alarms reported on only 0.05% of dereference sites.
secure web browsing with the op web browser. current web browsers are plagued with vulnerabilities, providing hackers with easy access to computer systems via browser-based attacks. browser security efforts that retrofit existing browsers have had limited success because the design of modern browsers is fundamentally flawed. to enable more secure web browsing, we design and implement a new browser, called the op web browser, that attempts to improve the state-of-the-art in browser security. our overall design approach is to combine operating system design principles with formal methods to design a more secure web browser by drawing on the expertise of both communities. our overall design philosophy is to partition the browser into smaller subsystems and make all communication between subsystems simple and explicit. at the core of our design is a small browser kernel that manages the browser subsystems and interposes on all communications between them to enforce our new browser security features. to show the utility of our browser architecture, we design and implement three novel security features. first, we develop novel and flexible security policies that allows us to include plugins within our security framework. our policy removes the burden of security from plugin writers, and gives plugins the flexibility to use innovative network architectures to deliver content while still maintaining the confidentiality and integrity of our browser, even if attackers compromise the plugin. second, we use formal methods to prove that the address bar displayed within our browser user interface always shows the correct address for the current web page. third, we design and implement a browser-level information-flow tracking system to enable post-mortem analysis of browser-based attacks. if an attacker is able to compromise our browser, we highlight the subset of total activity that is causally related to the attack, thus allowing users and system administrator to determine easily which web site lead to the compromise and to assess the damage of a successful attack. to evaluate our design, we implemented op and tested both performance and file system impact. to test performance, we measure latency to verify op's performance penalty from security features will be minimal from a users perspective. our experiments show that on average the speed of the op browser is comparable to firefox and the audit log footprint for the same pages average around 80kb.
saner: composing static and dynamic analysis to validate sanitization in web applications. web applications are ubiquitous, perform mission-critical tasks, and handle sensitive user data. unfortunately, web applications are often implemented by developers with limited security skills, and, as a result, they contain vulnerabilities. most of these vulnerabilities stem from the lack of input validation. that is, web applications use malicious input as part of a sensitive operation, without having properly checked or sanitized the input values prior to their use.past research on vulnerability analysis has mostly focused on identifying cases in which a web application directly uses external input in critical operations. however, little research has been performed to analyze the correctness of the sanitization process. thus, whenever a web application applies some sanitization routine to potentially malicious input, the vulnerability analysis assumes that the result is innocuous. unfortunately, this might not be the case, as the sanitization process itself could be incorrect or incomplete.in this paper, we present a novel approach to the analysis of the sanitization process. more precisely, we combine static and dynamic analysis techniques to identify faultysanitization procedures that can be bypassed by an attacker. we implemented our approach in a tool, called saner, and we applied it to a number of real-world applications. our results demonstrate that we were able to identify several novel vulnerabilities that stem from erroneous sanitization procedures.
clearshot: eavesdropping on keyboard input from video. eavesdropping on electronic communication is usually prevented by using cryptography-based mechanisms. however, these mechanisms do not prevent one from obtaining private information through side channels, such as the electromagnetic emissions of monitors or the sound produced by keyboards. while extracting the same information by watching somebody typing on a keyboard might seem to be an easy task, it becomes extremely challenging if it has to be automated. however, an automated tool is needed in the case of long-lasting surveillance procedures or long user activity, as a human being is able to reconstruct only a few characters per minute. this paper presents a novel approach to automatically recovering the text being typed on a keyboard, based solely on a video of the user typing. as part of the approach, we developed a number of novel techniques for motion tracking, sentence reconstruction, and error correction. the approach has been implemented in a tool, called clearshot, which has been tested in a number of realistic settings where it was able to reconstruct a substantial part of the typed information.
predictable design of network-based covert communication systems. this paper presents a predictable and quantifiable approach to designing a covert communication system capable of effectively exploiting covert channels found in the various layers of network protocols. two metrics are developed that characterize the overall system. a measure of probability of detection is derived using statistical inference techniques. a measure of reliability is developed as the bit error rate of the combined noisy channel and an appropriate error-correcting code. to support reliable communication, a family of error-correcting codes are developed that handle the high symbol insertion rates found in these covert channels. the system metrics are each shown to be a function of the covert channel signal-to-noise ratio, and as such the two can be used to perform system level design trade-offs. validation of the system design methodology is provided by means of an experiment using real network traffic data.
preserving caller anonymity in voice-over-ip networks. applications such as voip need to provide anonymity to clients while maintaining low latency to satisfy quality of service (qos) requirements. existing solutions for providing anonymity such as mix networks are not well suited to applications like voip, ssh, and gaming which require low communication latency. this paper investigates the problem of on-demand construction of qos sensitive routes on anonymizing networks using the voip application. we first describe triangulation based timing analysis attacks on shortest path route set up protocols. we show that even when a small fraction (sim1) of the network is malicious, the adversary can infer the source (caller) with reasonably high probability. second, we describe random walk based route set up protocols that significantly improve anonymity while satisfying latency-based qos guarantees. we describe a prototype implementation of our proposal and show that our protocols can significantly reduce the probability of inferring the caller. we present a detailed experimental evaluation to demonstrate our attacks and quantify the performance and scalability of our guards.
practical proactive integrity preservation: a basis for malware defense. unlike today's reactive approaches, information flow based approaches can provide positive assurances about overall system integrity, and hence can defend against sophisticated malware. however, there hasn't been much success in applying information flow based techniques to desktop systems running modern cots operating systems. this is, in part, due to the fact that a strict application of information flow policy can break existing applications and os services. another important factor is the difficulty of policy development, which requires us to specify integrity labels for hundreds of thousands of objects on the system. this paper develops a new approach for proactive integrity protection that overcomes these challenges by decoupling integrity labels from access policies. we then develop an analysis that can largely automate the generation of integrity labels and policies that preserve the usability of applications in most cases. evaluation of our prototype implementation on a linux desktop distribution shows that it does not break or inconvenience the use of most applications, while stopping a variety of sophisticated malware attacks.
thinking inside the box: system-level failures of tamper proofing. pin entry devices (peds) are critical security components in emv smartcard payment systems as they receive a customer's card and pin. their approval is subject to an extensive suite of evaluation and certification procedures. in this paper, we demonstrate that the tamper proofing of peds is unsatisfactory, as is the certification process. we have implemented practical low-cost attackson two certified, widely-deployed peds -- the ingenico i3300 and the dionextreme. by tapping inadequately protected smartcard communications, an attacker with basic technical skills can expose card details and pins, leaving cardholders open to fraud. we analyze the anti-tampering mechanisms of the two peds and show that, while the specific protection measures mostly work as intended, critical vulnerabilities arise because of the poor integration of cryptographic, physical and procedural protection. as these vulnerabilities illustrate a systematic failure in the design process, we propose a methodology for doing it better in the future. these failures also demonstrate a serious problem with the common criteria. so we discuss the incentive structures of the certification process, and show how they can lead to problems of the kind we identified. finally, we recommend changes to the common criteria framework in light of the lessons learned.
spot me if you can: uncovering spoken phrases in encrypted voip conversations. despite the rapid adoption of voice over ip (voip), its security implications are not yet fully understood. since voip calls may traverse untrusted networks, packets should be encrypted to ensure confidentiality. however, we show that when the audio is encoded using variable bit rate codecs, the lengths of encrypted voip packets can be used to identify the phrases spoken within a call. our results indicate that a passive observer can identify phrases from a standard speech corpus within encrypted calls with an average accuracy of 50%, and with accuracy greater than 90% for some phrases. clearly, such an attack calls into question the efficacy of current voip encryption standards. in addition, we examine the impact of various features of the underlying audio on our performance and discuss methods for mitigation.
compromising reflections-or-how to read lcd monitors around the corner. we present a novel eavesdropping technique for spying at a distance on data that is displayed on an arbitrary computer screen, including the currently prevalent lcd monitors. our technique exploits reflections of the screen's optical emanations in various objects that one commonly finds in close proximity to the screen and uses those reflections to recover the original screen content. such objects include eyeglasses, tea pots, spoons, plastic bottles, and even the eye of the user. we have demonstrated that this attack can be successfully mounted to spy on even small fonts using inexpensive, off-the-shelf equipment (less than 1500 dollars) from a distance of up to 10 meters. relying on more expensive equipment allowed us to conduct this attack from over 30 meters away, demonstrating that similar attacks are feasible from the other side of the street or from a close-by building. we additionally establish theoretical limitations of the attack; these limitations may help to estimate the risk that this attack can be successfully mounted in a given environment.
zero-knowledge in the applied pi-calculus and automated verification of the direct anonymous attestation protocol. we devise an abstraction of zero-knowledge protocols that is accessible to a fully mechanized analysis. the abstraction is formalized within the applied pi-calculus using a novel equational theory that abstractly characterizes the cryptographic semantics of zero-knowledge proofs. we present an encoding from the equational theory into a convergent rewriting system that is suitable for the automated protocol verifier proverif. the encoding is sound and fully automated. we successfully used proverif to obtain the first mechanized analysis of (a simplified variant of) the direct anonymous attestation (daa) protocol. this required us to devise novel abstractions of sophisticated cryptographic security definitions based on interactive games. the analysis reported a novel attack on daa that was overlooked in its existing cryptographic security proof. we propose a revised variant of daa that we successfully prove secure using proverif.
xfa: faster signature matching with extended automata. automata-based representations and related algorithms have been applied to address several problems in information security, and often the automata had to be augmented with additional information. for example, extended finite-state automata (efsa) augment finite-state automata (fsa) with variables to track dependencies between arguments of system calls. in this paper, we introduce extended finite automata (xfas) which augment fsas with finite scratch memory and instructions to manipulate this memory. our primary motivation for introducing xfas is signature matching innetwork intrusion detection systems (nids). representing nids signatures as deterministic finite-state automata (dfas) results in very fast signature matching but for several classes of signatures dfas can blowup in space. using nondeterministic finite-state automata (nfa) to represent nids signatures results in a succinct representation but at the expense of higher time complexity for signature matching. in other words, dfas are time-efficient but space-inefficient, and nfas are space-efficient but time-inefficient. in our experiments we have noticed that for a large class of nids signatures xfas have time complexity similar to dfas and space complexity similar to nfas. for our test set, xfas use 10 timesless memory than a dfa-based solution, yet achieve 20 times higher matching speeds.
fable: a language for enforcing user-defined security policies. this paper presents fable, a core formalism for a programming language in which programmers may specify security policies and reason that these policies are properly enforced. in fable, security policies can be expressed by associating security labels with the data or actions they protect. programmers define the semantics of labels in a separate part of the program called the enforcement policy. fable prevents a policy from being circumvented by allowing labeled terms to be manipulated only within the enforcement policy; application code must treat labeled values abstractly. together, these features facilitate straightforward proofs that programs implementing a particular policy achieve their high-level security goals. fable is flexible enough to implement a wide variety of security policies, including access control, information flow, provenance, and security automata. we have implemented fable as part of the links web programming language; we call the resulting language selinks. we report on our experience using selinks to build two substantial applications, a wiki and an on-line store, equipped with a combination of access control and provenance policies. to our knowledge, no existing framework enables the enforcement of such a wide variety of security policies with an equally high level of assurance.
anonymous networking with minimum latency in multihop networks. the problem of security against timing based traffic analysis in multihop networks is considered in this work. in particular, the relationship between the level of anonymity provided and the quality of service, as measured by network latency, is analyzed theoretically. using an information theoretic measure of anonymity of routes in eavesdropped networks is considered, and packet scheduling strategies are designed to guarantee any desired level of anonymity. in particular, for individual relays, scheduling strategies based on mixing are designed so that the incoming and outgoing transmission epochs do not reveal any information. the proposed strategies utilize a limited fraction of dummy transmissions, and a significant reduction in packet latency at individual relays is demonstrated analytically for poisson distributed arrivals. to minimize overall network latency, a randomized selection strategy is considered to choose the set of relays that use the designed scheduling strategies. the random selection is optimized for the desired level of anonymity using a well known distortion rate optimization in information theory. the tradeoff between overall network latency and anonymity in the network is characterized for centralized and decentralized scheduling strategies.
civitas: toward a secure voting system. civitas is the first electronic voting system that is coercion-resistant, universally and voter verifiable, and suitable for remote voting. this paper describes the design and implementation of civitas. assurance is established in the design through security proofs, and in the implementation through information-flow security analysis. experimental results give a quantitative evaluation of the tradeoffs between time, cost, and security.
lares: an architecture for secure active monitoring using virtualization. host-based security tools such as anti-virus and intrusion detection systems are not adequately protected on today's computers. malware is often designed to immediately disable any security tools upon installation, rendering them useless. while current research has focused on moving these vulnerable security tools into an isolated virtual machine, this approach cripples security tools by preventing them from doing active monitoring. this paper describes an architecture that takes a hybrid approach, giving security tools the ability to do active monitoring while still benefiting from the increased security of an isolated virtual machine. we discuss the architecture and a prototype implementation that can process hooks from a virtual machine running windows xp on xen. we conclude with a security analysis and show the performance of a single hook to be 28 microseconds in the best case.
automatic patch-based exploit generation is possible: techniques and implications. the automatic patch-based exploit generation problem is: given a program p and a patched version of the program p, automatically generate an exploit for the potentially unknown vulnerability present in p but fixed in p. in this paper, we propose techniques for automatic patch-based exploit generation, and show that our techniques can automatically generate exploits for 5 microsoft programs based upon patches provided via windows update. although our techniques may not work in all cases, a fundamental tenant of security is to conservatively estimate the capabilities of attackers. thus, our results indicate that automatic patch-based exploit generation should be considered practical. one important security implication of our results is that current patch distribution schemes which stagger patch distribution over long time periods, such as windows update, may allow attackers who receive the patch first to compromise the significant fraction of vulnerable hosts who have not yet received the patch.
partial security policies to support timeliness in secure real-time databases. conflicts in database systems with both real-time and security requirements can be unresolvable. we address this issue by allowing a database system to provide partial security in order to improve real-time performance when necessary. systems that are partially secure allow potential security violations such as covert channel use at certain situations. we present the idea of requirement specification that enables the system designer to specify important properties of the database at an appropriate level. to help the designer, a tool can process the database specification to find unresolvable conflicts, and to allow the designer to specify the rules to follow during execution when those conflicts arise. we discuss several partial security policies and compare their performance in terms of timeliness and potential security violations.
a new quantum lower bound method, : with applications to direct product theorems and time-space tradeoffs. we give a new version of the adversary method for proving lower bounds on quantum query algorithms. the new method is based on analyzing the eigenspace structure of the problem at hand. we use it to prove a new and optimal strong direct product theorem for 2-sided error quantum algorithms computing k independent instances of a symmetric boolean function: if the algorithm uses significantly less than k times the number of queries needed for one instance of the function, then its success probability is exponentially small in k. we also use the polynomial method to prove a direct product theorem for 1-sided error algorithms for k threshold functions with a stronger bound on the success probability. finally, we present a quantum algorithm for evaluating solutions to systems of linear inequalities, and use our direct product theorems to show that the time-space tradeoff of this algorithm is close to optimal.
constant factor approximation of vertex-cuts in planar graphs. we devise the first constant factor approximation algorithm for minimum quotient vertex-cuts in planar graphs. our algorithm achieves approximation ratio 1+4/3(1+ε) with running time o(w• n3+2/ε), where w is the total weight of the vertices. the approximation ratio improves to 4/3(1+ε+o(1)) if there is an optimal quotient vertex-cut (a*,b*,c*) where the weight of c* is of low order compared to those of a* and b*; this holds, for example, when the input graph has uniform weights and costs. the ratio further improves to 1+ε+o(1) if, in addition, min[w(a*),w(b*)] ≤ 1/3 w.we use our algorithm for quotient vertex-cuts to achieve the first constant-factor pseudo-approximation for vertex separators in planar graphs.our technical contribution is two-fold. first, we prove a structural theorem for planar graphs, showing the existence of a near-optimal quotient vertex-cut whose high-level structure is that of a bounded-depth tree. second, we develop an algorithm that optimizes over such complex structures in running time that depends (exponentially) not on the size of the structure, but rather only on its depth. these techniques may be applicable in other problems.
a unifying framework for the theory of iterative arrays of machines a mathematical framework is defined in which many questions concerning uniform arrays of finite-state machines can be formulated and studied. an outline is then presented that informally describes some research areas that have been under investigation. some of the results uncovered to date are described and many open problems are stated.
the care and feeding of lr(k) grammars we consider methods of modifying lr(k) parsers [1] while preserving the ability of that parsing method to detect errors at the earliest possible point on the input. two transformations are developed, and the methods of korenjak [2] and deremer [3] are expressed in terms of these transformations. the relation between these two methods is exposed. proofs are for the most part omitted, but can be found in [4].
quantum lower bound for the collision problem. (math) the collision problem is to decide whether a function x: { 1,&ldots;,n} &rarr; { 1, &ldots;,n} is one-to-one or two-to-one, given that one of these is the case. we show a lower bound of &omega;(n1/5) on the number of queries needed by a quantum computer to solve this problem with bounded error probability. the best known upper bound is o(n1/3), but obtaining any lower bound better than &omega;(1) was an open problem since 1997. our proof uses the polynomial method augmented by some new ideas. we also give a lower bound of &omega;(n1/7) for the problem of deciding whether two sets are equal or disjoint on a constant fraction of elements. finally we give implications of these results for quantum complexity theory.
a technique for speeding up lr(k) parsers we present a new transformation that reduces the size and increases the speed of lr(k) parsers. this transformation can be applied to all lr(k) parsers including those produced by knuth's and deremer's techniques. the transformation causes the parser to avoid reductions by productions of the form a &ran; b where a and b are non-terminals.
multilinear formulas and skepticism of quantum computing. several researchers, including leonid levin, gerard 't hooft, and stephen wolfram, have argued that quantum mechanics will break down before the factoring of large numbers becomes possible. if this is true, then there should be a natural set of quantum states that can account for all quantum computing experiments performed to date, but not for shor's factoring algorithm. we investigate as a candidate the set of states expressible by a polynomial number of additions and tensor products. using a recent lower bound on multilinear formula size due to raz, we then show that states arising in quantum error-correction require nω(log n) additions and tensor products even to approximate, which incidentally yields the first superpolynomial gap between general and multilinear formula size of functions. more broadly, we introduce a complexity classification of pure quantum states, and prove many basic facts about this classification. our goal is to refine vague ideas about a breakdown of quantum mechanics into specific hypotheses that might be experimentally testable in the near future.
node listings for reducible flow graphs in [1], kennedy conjectures that for every n node reducible flow graph, there is a sequence of nodes (with repetitions) of length o(nlogn) such that all acyclic paths are subsequences thereof. such a sequence would, if it could be found easily, enable one to do various kinds of global data flow analyses quickly. we show that for all reducible flow graphs such a sequence does exist, even if the number of edges is much larger than n. if the number of edges is o(n), the node listing can be found in o(nlogn) time.
lower bounds for local search by quantum arguments. the problem of finding a local minimum of a black-box function is central for understanding local search as well as quantum adiabatic algorithms. for functions on the boolean hypercube $\left\{0,1\right\}^n$, we show a lower bound of $\omega\left(2^{n/4}/n\right)$ on the number of queries needed by a quantum computer to solve this problem. more surprisingly, our approach, based on ambainis's quantum adversary method, also yields a lower bound of $\omega\left(2^{n/2}/n^2\right)$ on the problem's classical randomized query complexity. this improves and simplifies a 1983 result of aldous. finally, in both the randomized and quantum cases, we give the first nontrivial lower bounds for finding local minima on grids of constant dimension $d\geq3$.
representing hard lattices with o(n log n) bits. we present a variant of the ajtai-dwork public-key cryptosystem where the size of the public-key is only o(nlog n) bits and the encrypted text/clear text ratio is also o(nlog n). this is true with the assumption that all of the participants in the cryptosystem share o(n2log n) random bits which has to be picked only once and the users of the cryptosystem get them e.g. together with the software implementing the protocol. the public key is a random lattice with an nc-unique nonzero shortest vector, where the constant c>1‾2 can be picked arbitrarily close to 1‾2, and we pick the lattice according to a distribution described in the paper. we do not prove a worst-case average-case equivalence but the security of the system follows from the hardness of a randomized diophantine approximation problem related to a well-known theorem of dirichlet.
the complexity of agreement. a celebrated 1976 theorem of aumann asserts that bayesian agents with common priors can never "agree to disagree": if their opinions about any topic are common knowledge, then those opinions must be equal. but two key questions went unaddressed: first, can the agents reach agreement after a conversation of reasonable length? second, can the computations needed for that conversation be performed efficiently? this paper answers both questions in the affirmative, thereby strengthening aumann's original conclusion.we show that for two agents with a common prior to agree within ε about the expectation of a [0,1] variable with high probability over their prior, it suffices for them to exchange o(1/ε2) bits. this bound is completely independent of the number of bits n of relevant knowledge that the agents have. we also extend the bound to three or more agents; and we give an example where the "standard protocol" (which consists of repeatedly announcing one's current expectation) nearly saturates the bound, while a new "attenuated protocol" does better. finally, we give a protocol that would cause two bayesians to agree within ε after exchanging o(1/ε2) messages, and that can be simulated by agents with limited computational resources. by this we mean that, after examining the agents' knowledge and a transcript of their conversation, no one would be able to distinguish the agents from perfect bayesians. the time used by the simulation procedure is exponential in 1/ε6 but not in n.
advances in metric embedding theory. metric embedding plays an important role in a vast range of application areas such as computer vision, computational biology, machine learning, networking, statistics, and mathematical psychology, to name a few.the theory of metric embedding received much attention in recent years by mathematicians as well as computer scientists and has been applied in many algorithmic applications.a cornerstone of the field is a celebrated theorem of bourgain which states that every finite metric space on n points embeds in euclidean space with o(log n) distortion.bourgain's result is best possible when considering the worst case distortion over all pairs of points in the metric space. yet, it is possible that an embedding can do much better in terms of the average distortion.indeed, in most practical applications of metric embedding the main criteria for the quality of an embedding is its average distortion over all pairs.in this paper we provide an embedding with constant average distortion for arbitrary metric spaces, while maintaining the same worst case bound provided by bourgain's theorem.in fact, our embedding possesses a much stronger property. we define the lq-distortion of a uniformly distributed pair of points. our embedding achieves the best possible lq-distortion for all 1 ≤ q ≤ ∞ simultaneously.these results have several algorithmic implications, e.g. an o(1) approximation for the unweighted uncapacitated quadratic assignment problem.the results are based on novel embedding methods which improve on previous methods in another important aspect: the dimension.the dimension of an embedding is of very high importance in particular in applications and much effort has been invested in analyzing it. however, no previous result improved the bound on the dimension which can be derived from bourgain's embedding.we prove that any metric space on n points embeds into lp with distortion o(log n) in dimension o(log n). this provides an optimal bound on the dimension of the embedding.somewhat surprisingly, we show that a further small improvement is possible at a small price in the distortion, obtaining an embedding with distortion o(log1+θ n) in optimal dimension o(θ-1 log n/log log n), for any θ > 0. it is worth noting that with the small loss in the distortion this improves upon the best known embedding of arbitrary spaces into euclidean space, where dimension reduction is used.our techniques also allow to obtain the optimal distortion for embedding into lp with nearly tight dimension. for any 1 ≤ p ≤ ⊂ and any 1 ≤ k ≤ p, we give an embedding into lp with distortion o(⌈ log n/k ⌉) in dimension 2o(k)log n.underlying our results is a novel embedding method. probabilistic metric decomposition techniques have played a central role in the field of finite metric embedding in recent years. here we introduce a novel notion of probabilistic metric decompositions which comes particularly natural in the context of embedding. our new methodology provides a unified approach to all known results on embedding of arbitrary metric spaces. moreover, as described above, with some additional ideas they allow to get far stronger results. these metric decompositions seem of independent interest.
optimal code generation for expression trees we discuss the problem of generating code for a wide class of machines, restricting ourselves to the computation of expression trees. after defining a broad class of machines and discussing the properties of optimal programs on these machines, we derive a necessary and sufficient condition which can be used to prove the optimality of any code generation algorithm for expression trees on this class. we then present a dynamic programming algorithm which produces optimal code for any machine in the class; this algorithm runs in time which is linearly proportional to the number of vertices in an expression tree.
a sharp threshold in proof complexity. we give the first example of a sharp threshold in proof complexity. more precisely, we show that for any sufficiently small &egr;>0 and &dgr;>2.28, random formulas consisting of (1-&egr;)n 2-clauses and &dgr n 3-clauses, which are known to be unsatisfiable almost certainly, almost certainly require resolution and davis-putnam proofs of unsatisfiability of exponential size, whereas it is easily seen that random formulas with (1+&egr;)n 2-clauses (and &dgr; n 3 clauses) have linear size proofs of unsatisfiability almost certainly.a consequence of our result also yields the first proof that typical random 3-cnf formulas at ratios below the generally accepted range of the satisfiability threshold (and thus expected to be satisfiable almost certainly) cause natural davis-putnam algorithms to take exponential time to find satisfying assignments.
a conjecture about polynomial time computable lattice-lattice functions. we formulate a conjecture which describes all of the polynomial time computable (p. t. c. ) functions f with domain(f)=lattice n, range(f) ⊆ lattice m, m ≤ nc, where latticen is the set of lattices in rn with determinant 1. a former conjecture, the 0-1-conjecture, of the author states that all 0,1-valued functions defined on latticen are constant almost everywhere. since the n-dimensional lattices as abelian groups are pairwise isomorphic we can say that, according to this conjecture, the value of a p. t. c. 0,1-function may depend only on the algebraic structure of the lattice and not on the metric defined on it. the new conjecture generalizes this statement for functions where the value is also a lattice. as a typical example we can think of the function f(l)=l′, where l′ is the dual of l. when both the domain and the range of the functions are n-dimensional lattices with determinants 1 then, according to the conjecture, every p. c. t. functions are either constant or identical almost everywhere to f(l)=al, or f(l)=al′, where a is a suitably chosen linear transformation with determinant one.there is a striking analogy between the new conjecture and theorems describing the uniquely definable functions which assign for each n-dimensional vectorspace an m-dimensional vectorspace. these theorems are closely related to questions about the axiom of choice. in this analogy polynomial time computation corresponds to definability (in set theory) and lattices to finite dimensional vectorspaces.
parallel computation over hyperbolic groups hyperbolic groups are a rich class of groups frequently encountered in mathematical research, particularly in topology. it has been the focus of intense study by many combinatorial group theorists and topologists recently. we present some computational results for infinite groups, especially for hyperbolic groups. it is shown that the word problem for hyperbolic groups is solvable in nc2. this is the first nc algorithm for a class of groups in combinatorial group theory. we also consider the isomorphism problem of randomly generated groups using a novel technique: the alexander polynomial from knot theory. these randomly generated groups are almost always hyperbolic groups.
on the bias of traceroute sampling: or, power-law degree distributions in regular graphs. understanding the graph structure of the internet is a crucial step for building accurate network models and designing efficient algorithms for internet applications. yet, obtaining this graph structure can be a surprisingly difficult task, as edges cannot be explicitly queried. for instance, empirical studies of the network of internet protocol (ip) addresses typically rely on indirect methods like traceroute to build what are approximately single-source, all-destinations, shortest-path trees. these trees only sample a fraction of the network's edges, and a paper by lakhina et al. [2003] found empirically that the resulting sample is intrinsically biased. further, in simulations, they observed that the degree distribution under traceroute sampling exhibits a power law even when the underlying degree distribution is poisson. in this article, we study the bias of traceroute sampling mathematically and, for a very general class of underlying degree distributions, explicitly calculate the distribution that will be observed. as example applications of our machinery, we prove that traceroute sampling finds power-law degree distributions in both &delta;-regular and poisson-distributed random graphs. thus, our work puts the observations of lakhina et al. on a rigorous footing, and extends them to nearly arbitrary degree distributions.
almost all graphs with average degree 4 are 3-colorable. we analyze a randomized version of the brelaz heuristic on sparse random graphs. we prove that almost all graphs with average degree d ≤ 4.03, i.e., g(n,p = d/n), are 3-colorable and that a constant fraction of all 4-regular graphs are 3-colorable.
the two possible values of the chromatic number of a random graph. for every d > 0, let kd be the smallest integer k such that d < 2k log k. we prove that the chromatic number of a random graph g(n,d/n) is either kd or kd+1 almost surely. if d ∈ (2k log k - log k, 2k log k) we further prove that the chromatic number almost surely equals k+1.
approximate counting of inversions in a data stream. (math) inversions are used as a fundamental quantity to measure the sortedness of data, to evaluate different ranking methods for databases, and in the context of rank aggregation. considering the volume of the data sets in these applications, the data stream model {14, 2] is a natural setting to design efficient algorithms.we obtain a suite of space-efficient streaming algorithms for approximating the number of inversions in a permutation. the best space bound we achieve is $o(\log n \log \log n)$ through a deterministic algorithm. in contrast, we derive an $\omega(n)$ lower bound for randomized exact computation for this problem; thus approximation is essential.(math) we also consider two generalizations of this problem: (1) approximating the number of inversions between two permutations, for which we obtain a randomized $o(\sqrt{n} \log n)$-space algorithm, and (2) approximating the number of inversions in a general list, for which we obtain a randomized $o(\sqrt{n} \log^2 n)$-space two-pass algorithm. in contrast, we derive $\omega(n)$-space lower bounds for deterministic approximate computation for these problems; thus both randomization and approximation are essential.all our algorithms use only o(log n) time per data item.
the threshold for random k-sat is 2 (ln 2 - o(k)). let fk(n,m) be a random k-sat formula on n variables formed by selecting uniformly and independently m out of all possible k-clauses. it is well-known that for r ≥ 2k ln 2, fk(n,rn) is unsatisfiable with probability 1-o(1). we prove that there exists a sequence tk = o(k) such that for r ≥ 2k ln 2 - tk, fk(n,rn) is satisfiable with probability 1-o(1).our technique yields an explicit lower bound for every k which for k > 3 improves upon all previously known bounds. for example, when k=10 our lower bound is 704.94 while the upper bound is 708.94.
a sieve algorithm for the shortest lattice vector problem. we present a randomized 2^{o(n)} time algorithm to compute a shortest non-zero vector in an n-dimensional rational lattice. the best known time upper bound for this problem was 2^{o(n\log n)} first given by kannan [7] in 1983. we obtain several consequences of this algorithm for related problems on lattices and codes, including an improvement for polynomial time approximations to the shortest vector problem. in this improvement we gain a factor of log log n in the exponent of the approximating factor.
on the solution-space geometry of random constraint satisfaction problems. for a number of random constraint satisfaction problems, such as random k-sat and random graph/hypergraph coloring, there are very good estimates of the largest constraint density for which solutions exist. yet, all known polynomial-time algorithms for these problems fail to find solutions even at much lower densities. to understand the origin of this gap we study how the structure of the space of solutions evolves in such problems as constraints are added. in particular, we prove that much before solutions disappear, they organize into an exponential number of clusters, each of which is relatively small and far apart from all other clusters. moreover, inside each cluster most variables are frozen, i.e., take only one value. the existence of such frozen variables gives a satisfying intuitive explanation for the failure of the polynomial-time algorithms analyzed so far. at the same time, our results establish rigorously one of the two main hypotheses underlying survey propagation, a heuristic introduced by physicists in recent years that appears to perform extraordinarily well on random constraint satisfaction problems.
low level complexity for combinatorial games there have been numerous attempts to discuss the time complexity of problems and classify them into hierarchical classes such as p, np, pspace, exp, etc. a great number of familiar problems have been reported which are complete in np (nondeterministic polynomial time). even and tarjan considered generalized hex and showed that the problem to determine who wins the game if each player plays perfectly is complete in polynomial space. shaefer derived some two-person game from np complete problems which are complete in polynomial space. a rough discussion such as to determine whether or not a given problem belongs to np is independent of the machine model and the way of defining the size of problems, since any of the commonly used machine models can be simulated by any other with a polynomial loss in running time and by no matter what criteria the size is defined, they differ from each other by polynomial order. however, in precise discussion, for example, in the discussion whether the computation of a problem requires o(n k) time or o(nk+l) time, the complexity heavily depends on machine models and the definition of size of problems. from these points, we introduce somewhat stronger notion of the reducibility.
deterministic simulation in logspace in this paper we show that a wide class of probabilistic algorithms can be simulated by deterministic algorithms. namely if there is a test in logspace so that a random sequence of length (log n)2 / log log n passes the test with probability at least 1/n then a deterministic sequence can be constructed in logspace which also passes the test. it is important that the machine performing the test gets each bit of the sequence only once. the theorem remains valid if both the test and the machine constructing the satisfying sequence have access to the same oracle of polynomial size. the sequence that we construct does not really depend on the test, in the sense that a polynomial family of sequences is constructed so that at least one of them passes any test. this family is the same even if the test is allowed to use an oracle of polynomial size, and it can be constructed in logspace (without using an oracle).
a deterministic poly(log log n)-time n-processor algorithm for linear programming in fixed dimension it is shown that for any fixed number of variables, the linear programming problems with n linear inequalities can be solved deterministically by n parallel processors in sub-logarithmic time. the parallel time bound is o((log log n)d) where d is the number of variables. in the one-dimensional case this bound is optimal.
running time and program size for self-assembled squares. recently rothemund and winfree [6] have considered the program size complexity of constructing squares by self-assembly. here, we consider the time complexity of such constructions using a natural generalization of the tile assembly model defined in [6]. in the generalized model, the rothemund-winfree construction of n \times n squares requires time &thgr;(n log n) and program size &thgr;(log n). we present a new construction for assembling n \times n squares which uses optimal time &thgr;(n) and program size &thgr;(\frac{log n}{log log n}). this program size is also optimal since it matches the bound dictated by kolmogorov complexity. our improved time is achieved by demonstrating a set of tiles for parallel self-assembly of binary counters. our improved program size is achieved by demonstrating that self-assembling systems can compute changes in the base representation of numbers. self-assembly is emerging as a useful paradigm for computation. in addition the development of a computational theory of self-assembly promises to provide a new conduit by which results and methods of theoretical computer science might be applied to problems of interest in biology and the physical sciences.
translations on a context free grammar two schemes for the specification of translations on a context-free grammar are proposed. the first scheme, called a generalized syntax directed translation (gsdt), consists of a context free grammar with a set of semantic rules associated with each production of the grammar. in a gsdt an input word is parsed according to the underlying context free grammar, and at each node of the tree, a finite number of translation strings are computed in terms of the translation strings defined at the descendants of that node. the functional relationship between the length of input and length of output for translations defined by gsdt's is investigated. the second method for the specification of translations is in terms of tree automata - finite automata with output, operating on derivation trees of a context free grammar. it is shown that tree automata provide an exact characterization for those gsdt's with a linear relationship between input and output length.
combinatorial optimization problems in self-assembly. self-assembly is the ubiquitous process by which simple objects autonomously assemble into intricate complexes. it has been suggested that intricate self-assembly processes will ultimately be used in circuit fabrication, nano-robotics, dna computation, and amorphous computing. in this paper, we study two combinatorial optimization problems related to efficient self-assembly of shapes in the tile assembly model of self-assembly proposed by rothemund and winfree [18]. the first is the minimum tile set problem, where the goal is to find the smallest tile system that uniquely produces a given shape. the second is the tile concentrations problem, where the goal is to decide on the relative concentrations of different types of tiles so that a tile system assembles as quickly as possible. the first problem is akin to finding optimum program size, and the second to finding optimum running time for a "program" to assemble the shape.self-assembly is the ubiquitous process by which simple objects autonomously assemble into intricate complexes. it has been suggested that intricate self-assembly processes will ultimately be used in circuit fabrication, nano-robotics, dna computation, and amorphous computing. in this paper, we study two combinatorial optimization problems related to efficient self-assembly of shapes in the tile assembly model of self-assembly proposed by rothemund and winfree [18]. the first is the minimum tile set problem, where the goal is to find the smallest tile system that uniquely produces a given shape. the second is the tile concentrations problem, where the goal is to decide on the relative concentrations of different types of tiles so that a tile system assembles as quickly as possible. the first problem is akin to finding optimum program size, and the second to finding optimum running time for a "program" to assemble the shape.we prove that the first problem is np-complete in general, and polynomial time solvable on trees and squares. in order to prove that the problem is in np, we present a polynomial time algorithm to verify whether a given tile system uniquely produces a given shape. this algorithm is analogous to a program verifier for traditional computational systems, and may well be of independent interest. for the second problem, we present a polynomial time $o(\log n)$-approximation algorithm that works for a large class of tile systems that we call partial order systems.
on basing one-way functions on np-hardness. we consider the possibility of basing one-way functions on np-hardness; that is, we study possible reductions from a worst-case decision problem to the task of average-case inverting a polynomial-time computable function f. our main findings are the following two negative results:if given y one can efficiently compute |f-1(y)| then the existence of a (randomized) reduction of np to the task of inverting f implies that conp ⊆ am. thus, it follows that such reductions cannot exist unless conp ⊆ am. for any function f, the existence of a (randomized) non-adaptive reduction of np to the task of average-case inverting f implies that conp ⊆ am.our work builds upon and improves on the previous works of feigenbaum and fortnow (siam journal on computing, 1993) and bogdanov and trevisan (44th focs, 2003), while capitalizing on the additional "computational structure" of the search problem associated with the task of inverting polynomial-time computable functions. we believe that our results illustrate the gain of directly studying the context of one-way functions rather than inferring results for it from a the general study of worst-case to average-case reductions.
recognizing primes in random polynomial time this paper is the first in a sequence of papers which will prove the existence of a random polynomial time algorithm for the set of primes. the techniques used are from arithmetic algebraic geometry and to a lesser extent algebraic and analytic number theory. the result complements the well known result of strassen and soloway that there exists a random polynomial time algorithm for the set of composites.
on randomized online scheduling. (math) we study one of the most basic problems in online scheduling. a sequence of jobs has to be scheduled on $m$ identical parallel machines so as to minimize the makespan. whenever a new job arrives, its processing time is known in advance. the job has to be scheduled immediately on one of the machines without knowledge of any future jobs. in the sixties graham presented the famous list scheduling algorithm which is $(2-{1\over m})$-competitive. in the last ten years deterministic online algorithms with an improved competitiveness have been developed. the first algorithm with a performance guarantee asymptotically smaller than 2 was 1.986- competitive. the competitive ratio was first improved to 1.945 and then to 1.923 and 1.9201. randomized competitive algorithms that are better than (known) deterministic algorithms were proposed for specific values of $m$, i.e. for $m\in\{2,\ldots,7\}$.(math) in this paper we present the first randomized online algorithm that performs better than known deterministic algorithms for general $m$. the algorithm is a combination of two deterministic scheduling strategies $a_1$ and $a_2$. initially, when starting the scheduling process, a scheduler chooses $a_i$, $i\in\{1,2\}$, with probability ${1\over 2}$ and then serves the entire job sequence using the chosen algorithm. the new randomized algorithm is 1.916-competitive. we prove that this performance cannot be achieved by a deterministic algorithm based on analysis techniques that have been used in the literature so far: using know techniques (or generalizations) it is impossible to prove a competitiveness smaller than 1.919 for any deterministic online algorithm. our results strictly limit the performance that can be achieved with existing techniques.
better bounds for online scheduling. we study a classical problem in online scheduling. a sequence of jobs must be scheduled on m identical parallel machines. as each job arrives, its processing time is known. the goal is to minimize the makespan. bartal et al. [ j. comput. system sci., 51 (1995), pp. 359--366] gave a deterministic online algorithm that is 1.986-competitive. karger, phillips, and torng [ j. algorithms, 20 (1996), pp. 400--430] generalized the algorithm and proved an upper bound of 1.945. the best lower bound currently known on the competitive ratio that can be achieved by deterministic online algorithms is equal to 1.837. in this paper we present an improved deterministic online scheduling algorithm that is 1.923-competitive; for all $m\geq 2$. the algorithm is based on a new scheduling strategy, i.e., it is not a generalization of the approach by bartal et al. also, the algorithm has a simple structure. furthermore, we develop a better lower bound. we prove that, for general m, no deterministic online scheduling algorithm can be better than 1.852-competitive.
on paging with locality of reference. motivated by the fact that competitive analysis yields too pessimistic results when applied to the paging problem, there has been considerable research interest in refining competitive analysis and in developing alternative models for studying online paging. in this paper, we propose a new, simple model for studying paging with locality of reference. the model is closely related to denning's working set concept and directly reflects the amount of locality that request sequences exhibit. we use the page fault rate to evaluate the quality of paging algorithms, which is the performance measure used in practice. we develop tight or nearly tight bounds on the fault rates achieved by popular paging algorithms such as lru, fifo, deterministic marking strategies and lfd. these bounds show that lru is an optimal online algorithm, whereas fifo and marking strategies are not optimal in general. we present an experimental study comparing the page fault rates proven in our analyses to the page fault rates observed in practice.
reducibility, randomness, and intractability (abstract) the method of showing a problem np-complete by polynomial reduction is one of the most elegant and productive in our theory ([ 1 ], [ 3 ]). it is a means of providing compelling evidence that a problem in np is not in p. in this paper we will demonstrate new methods for showing this. our methods, based on a new notion of reducibility (gamma-reducibility) are apparently of more general applicability than that of polynomial reduction and are intended to be of practical value to researchers in the field. we use our methods to &ldquo;demonstrate&rdquo; (i.e., give compelling evidence) that some natural problems in np which are not known to be np-complete are, nonetheless, not in p.
minimizing stall time in single and parallel disk systems. we study integrated prefetching and caching problems following the work of cao et al. [1995] and kimbrel and karlin [1996]. cao et al. and kimbrel and karlin gave approximation algorithms for minimizing the total elapsed time in single and parallel disk settings. the total elapsed time is the sum of the processor stall times and the length of the request sequence to be served.we show that an optimum prefetching/caching schedule for a single disk problem can be computed in polynomial time, thereby settling an open question by kimbrel and karlin. for the parallel disk problem, we give an approximation algorithm for minimizing stall time. the solution uses a few extra memory blocks in cache. stall time is an important and harder to approximate measure for this problem. all of our algorithms are based on a new approach which involves formulating the prefetching/caching problems as linear programs.
tradeoffs in probabilistic packet marking for ip traceback. there has been considerable recent interest in probabilistic packet marking schemes for the problem of tracing a sequence of network packets back to an anonymous source. an important consideration for such schemes is the number of packet header bits that need to be allocated to the marking protocol. let b denote this value. all previous schemes belong to a class of protocols for which b must be at least log n, where n is the number of bits used to represent the path of the packets. in this paper, we introduce a new marking technique for tracing a sequence of packets sent along the same path. this new technique is effective even when b=1. in other words, the sequence of packets can be traced back to their source using only a single bit in the packet header. with this scheme, the number of packets required to reconstruct the path is o(22n), but we also show that &omega;(2n) packets are required for any protocol where b=1. we also study the tradeoff between b and the number of packets required. we provide a protocol and a lower bound that together demonstrate that for the optimal protocol, the number of packets required (roughly) increases exponentially with n, but decreases doubly exponentially with b. the protocol we introduce is simple enough to be useful in practice. we also study the case where the packets are sent along k different paths. for this case, we demonstrate that any protocol must use at least log(2k&mdash;1) header bits. we also provide a protocol that requires &lceil;log(2k+1)&rceil; header bits in some restricted scenarios. this protocol introduces a new coding technique that may be of independent interest.
exploring unknown environments. we consider exploration problems where a robot has to construct a complete map of an unknown environment. we assume that the environment is modeled by a directed, strongly connected graph. the robot's task is to visit all nodes and edges of the graph using the minimum number r of edge traversals. deng and papadimitriou [ proceedings of the 31st symposium on the foundations of computer science, 1990, pp. 356--361] showed an upper bound for r of do(d) m and koutsoupias (reported by deng and papadimitriou) gave a lower bound of $\omega(d^2 m)$, where m is the number of edges in the graph and d is the minimum number of edges that have to be added to make the graph eulerian. we give the first subexponential algorithm for this exploration problem, which achieves an upper bound of do(log d) m. we also show a matching lower bound of $d^{\omega(\log d)}m$ for our algorithm. additionally, we give lower bounds of $2^{\omega(d)}m$, respectively, $d^{\omega(\log d)}m$ for various other natural exploration algorithms.
polynomial algorithms for linear programming over the algebraic numbers we derive an algorithm based on the ellipsoid method that solves linear programs whose coefficients are real algebraic numbers. by defining the encoding size of an algebraic number to be the bit size of the coefficients of its minimal polynomial, we prove the algorithm runs in time polynomial in the dimension of the problem, the encoding size of the input coefficients, and the degree of any algebraic extension which contains the input coefficients. this bound holds even if all input and arithmetic is performed symbolically, using rational numbers only.
on the performance of greedy algorithms in packet buffering. we study a basic buffer management problem that arises in network switches. consider $m$ input ports, each of which is equipped with a buffer (queue) of limited capacity. data packets arrive online and can be stored in the buffers if space permits; otherwise packet loss occurs. in each time step the switch can transmit one packet from one of the buffers to the output port. the goal is to maximize the number of transmitted packets. simple arguments show that any work-conserving algorithm, which serves any nonempty buffer, is 2-competitive. azar and richter recently presented a randomized online algorithm and gave lower bounds for deterministic and randomized strategies. in practice, greedy algorithms are very important because they are fast, use little extra memory, and reduce packet loss by always serving a longest queue. in this paper we first settle the competitive performance of the entire family of greedy strategies. we prove that greedy algorithms are not better than 2-competitive no matter how ties are broken. our lower bound proof uses a new recursive construction for building adversarial buffer configurations that may be of independent interest. we also give improved lower bounds for deterministic and randomized online algorithms.in this paper we present the first deterministic online algorithm that is better than 2-competitive. we develop a modified greedy algorithm, called semigreedy, and prove that it achieves a competitive ratio of $17/9 \approx 1.89$. the new algorithm is simple, fast, and uses little extra memory. only when the risk of packet loss is low does it not serve the longest queue. additionally we study scenarios when an online algorithm is granted additional resources. we consider resource augmentation with respect to memory and speed; i.e., an online algorithm may be given larger buffers or higher transmission rates. we analyze greedy and other online strategies.
lower bounds for k-dnf resolution on random 3-cnfs. we prove exponential lower bounds for the refutation of a random 3-cnf with linear number of clauses by k-dnf resolution for k ≤ √ log n ⁄ log log n. for this we design a specially tailored random restrictions that preserve the structure of the input random 3-cnf while mapping every k-dnf with large covering number to 1 with high probability. next we make use of the switching lemma for small restrictions by segerlind, buss and impagliazzo to prove the lower bound.this work improves the previously known lower bound for res(2) system on random 3-cnfs by atserias, bonet and esteban and the result of segerlind, buss, impagliazzo stating that random o(k2)-cnf do not possess short res(k) refutations.
towards asymptotic optimality in probabilistic packet marking. there has been considerable recent interest in probabilistic packet marking schemes for sending information from nodes (routers) along one or more paths traveled by a stream of packets to the end-host receiving that stream. a central consideration for such schemes is the tradeoff between the number b of possible states of the marking bits in a packet, the number of bits n of information being sent by the nodes, and the expected number of packets t required to reconstruct this information. for the case where the packets all travel along the same path, we prove a lower bound of t ≥ ω(b22n/(b-1)), roughly the square of an earlier lower bound of adler.for an upper bound, we consider a model where each of m nodes along a single path must send one of s possible messages (thus n = m log2 s total bits are sent). we prove that t ≤ o(m • 22m(log2 s)/(b-1)) suffices (the implicit constant depends on b and s); this almost matches the lower bound, and is roughly the square root of an earlier upper bound of adler. the new bound holds for all b and s in two slightly relaxed models, while under the strictest requirements we prove it only for some special values of b and s. this is related to a challenging geometric problem: the existence of an s-reptile (b-1)-dimensional simplex, i.e. a simplex s that can be tiled by s congruent simplices similar to s.we also consider the case where the packets travel along multiple paths to the same destination. in this case, we present a new protocol and analysis technique that together allow us to significantly generalize over previous work the scenarios where the protocol is effective.
towards strong nonapproximability results in the lovasz-schrijver hierarchy. lovász and schrijver described a generic method of tightening the lp and sdp relaxation for any 0-1 optimization problem. these tightened relaxations were the basis of several celebrated approximation algorithms (such as for max-cu , max-3sat, and sparsest cut).we prove strong inapproximability results in this model for well-known problems such as max-3sat, hypergraph vertex cover and set cover. we show that the relaxations produced by as many as ω(n) rounds of the ls+ procedure do not allow nontrivial approximation, thus ruling out the possibility that the ls+ approach gives even slightly subexponential approximation algorithms for these problems.we also point out why our results are somewhat incomparable to known inapproximability results proved using pcps, and formalize several interesting open questions.
a stochastic process on the hypercube with applications to peer-to-peer networks. consider the following stochastic process executed on a graph g=(v,e) whose nodes are initially uncovered. in each step, pick a node at random and if it is uncovered, cover it. otherwise, if it has an uncovered neighbor, cover a random uncovered neighbor. else, do nothing. this can be viewed as a structured coupon collector process. we show that for a large family of graphs, o(n) steps suffice to cover all nodes of the graph with high probability, where n is the number of vertices. among these graphs are d-regular graphs with d =ω(log n log log n), random d-regular graphs with d =ω(log n) and the k-dimensional hypercube where n=2k.this process arises naturally in answering a question on load balancing in peer-to-peer networks. we consider a distributed hash table in which keys are partitioned across a set of processors, and we assume that the number of processors grows dynamically, starting with a single processor. if at some stage there are n processors, the number of queries required to find a key is log2 n+o(1), the number of pointers maintained by each processor is log2 n+o(1), and moreover the worst ratio between the loads of processors is o(1), with high probability. to the best of our knowledge, this is the first analysis of a distributed hash table that achieves asymptotically optimal load balance, while still requiring only o(log n) pointers per processor and o(log n) queries for locating a key; previous methods required ω(log2 n) pointers per processor and ω(log n) queries for locating a key.
space complexity in propositional calculus. we study space complexity in the framework of propositional proofs. we consider a natural model analogous to turing machines with a read-only input tape and such popular propositional proof systems as resolution, polynomial calculus, and frege systems. we propose two different space measures, corresponding to the maximal number of bits, and clauses/monomials that need to be kept in the memory simultaneously. we prove a number of lower and upper bounds in these models, as well as some structural results concerning the clause space for resolution and frege systems.
an exponential separation between regular and general resolution. two distinct proofs of an exponential separation between regular resolution and unrestricted resolution are given. the previous best known separation between these systems was quasi-polynomial.
a simplex algorithm whose average number of steps is bounded between two quadratic functions of the smaller dimension it has been a challenge for mathematicians to confirm theoretically the extremely good performance of simplex-type algorithms for linear programming. in this paper the average number of steps performed by a simplex algorithm, the so-called self-dual method, is analyzed. the algorithm is not started at the traditional point (1, &hellip; , l)t, but points of the form (1, &egr;, &egr;2, &hellip;)t, with &egr; sufficiently small, are used. the result is better, in two respects, than those of the previous analyses. first, it is shown that the expected number of steps is bounded between two quadratic functions c1(min(m, n))2 and c2(min(m, n))2 of the smaller dimension of the problem. this should be compared with the previous two major results in the field. borgwardt proves an upper bound of o(n4m1/(n-1)) under a model that implies that the zero vector satisfies all the constraints, and also the algorithm under his consideration solves only problems from that particular subclass. smale analyzes the self-dual algorithm starting at (1, &hellip; , 1)t. he shows that for any fixed m there is a constant c(m) such the expected number of steps is less than c(m)(ln n)m(m+1); megiddo has shown that, under smale's model, an upper bound c(m) exists. thus, for the first time, a polynomial upper bound with no restrictions (except for nondegeneracy) on the problem is proved, and, for the first time, a nontrivial lower bound of precisely the same order of magnitude is established. both borgwardt and smale require the input vectors to be drawn from spherically symmetric distributions. in the model in this paper, invariance is required only under certain
quantitative solution of omega-regular games. we consider two-player games played for an infinite number of rounds, with ω-regular winning conditions. the games may be concurrent, in that the players choose their moves simultaneously and independently, and probabilistic, in that the moves determine a probability distribution for the successor state. we introduce quantitative game µ-calculus, and we show that the maximal probability of winning such games can be expressed as the fixpoint formulas in this calculus. we develop the arguments both for deterministic and for probabilistic concurrent games; as a special case, we solve probabilistic turn-based games with ω-regular winning conditions, which was also open. we also characterize the optimality, and the memory requirements, of the winning strategies. in particular, we show that while memoryless strategies suffice for winning games with safety and reachability conditions, büchi conditions require the use of strategies with infinite memory. the existence of optimal strategies, as opposed to ε-optimal, is only guaranteed in games with safety winning conditions.
some consequences of the existence of pseudorandom generators if secure pseudorandom generators exist, then probabilistic computation does not uniformly speed up deterministic computation. if sets in p must contain infinitely many noncomplex strings, then nondeterministic computation does not uniformly speed up deterministic computation. connections are drawn between pseudorandom generation, generalized kolmogorov complexity, and immunity properties of complexity classes.
expanders, sorting in rounds and superconcentrators of limited depth expanding graphs and superconcentrators are relevant to theoretical computer science in several ways. here we use finite geometries to construct explicitly highly expanding graphs with essentially the smallest possible number of edges. our graphs enable us to improve significantly previous results on a parallel sorting problem, by describing an explicit algorithm to sort n elements in k time units using &ogr;(n&agr;k) processors, where, e.g., &agr;2 = 7/4. using our graphs we can also construct efficient n-superconcentrators of limited depth. for example, we construct an n superconcentrator of depth 3 with &ogr;(n4/3) edges; better than the previous known results.
the online set cover problem. let $x=\{1,2,\ldots,n\}$ be a ground set of $n$ elements, and let ${\cal s}$ be a family of subsets of $x$, $|{\cal s}|=m$, with a positive cost $c_s$ associated with each $s\in{\cal s}$. consider the following online version of the set cover problem, described as a game between an algorithm and an adversary. an adversary gives elements to the algorithm from $x$ one by one. once a new element is given, the algorithm has to cover it by some set of ${\cal s}$ containing it. we assume that the elements of $x$ and the members of ${\cal s}$ are known in advance to the algorithm; however, the set $x'\subseteq x$ of elements given by the adversary is not known in advance to the algorithm. (in general, $x'$ may be a strict subset of $x$.) the objective is to minimize the total cost of the sets chosen by the algorithm. let ${\cal c}$ denote the family of sets in ${\cal s}$ that the algorithm chooses. at the end of the game the adversary also produces (offline) a family of sets ${\cal c}_{opt}$ that covers $x'$. the performance of the algorithm is the ratio between the cost of ${\cal c}$ and the cost of ${\cal c}_{opt}$. the maximum ratio, taken over all input sequences, is the competitive ratio of the algorithm. we present an $o(\log m\log n)$ competitive deterministic algorithm for the problem and establish a nearly matching $\omega\bigl(\frac{\log n\log m}{\log\log m+\log\log n}\bigr)$ lower bound for all interesting values of $m$ and $n$. the techniques used are motivated by similar techniques developed in computational learning theory for online prediction (e.g., the winnow algorithm) together with a novel way of converting a fractional solution into a deterministic online algorithm.
a random nc algorithm for depth first search in this paper we present a fast parallel algorithm for constructing a depth first search tree for an undirected graph. the algorithm is an rnc algorithm, meaning that it is a probabilistic algorithm that runs in polylog time using a polynomial number of processors on a p-ram. the run time of the algorithm is &ogr;(tmm(n)log3n), and the number of processors used is pmm(n) where tmm(n) and pmm(n) are the time and number of processors needed to find a minimum weight perfect matching on an n vertex graph with maximum edge weight n.
routing permutations on graphs via matchings. a class of routing problems on connected graphs $g$ is considered. initially, each vertex $v$ of $g$ is occupied by a ``pebble'' that has a unique destination $\pi (v)$ in $g$ (so that $\pi$ is a permutation of the vertices of $g$). it is required that all the pebbles be routed to their respective destinations by performing a sequence of moves of the following type: a disjoint set of edges is selected, and the pebbles at each edge's endpoints are interchanged. the problem of interest is to minimize the number of steps required for any possible permutation $\pi$. this paper investigates this routing problem for a variety of graphs $g$, including trees, complete graphs, hypercubes, cartesian products of graphs, expander graphs, and cayley graphs. in addition, this routing problem is related to certain network flow problems, and to several graph invariants including diameter, eigenvalues, and expansion coefficients.
a model for hierarchical memory in this paper we introduce the hierarchical memory model (hmm) of computation. it is intended to model computers with multiple levels in the memory hierarchy. access to memory location x is assumed to take time &lceil; log x &rceil;. tight lower and upper bounds are given in this model for the time complexity of searching, sorting, matrix multiplication and fft. efficient algorithms in this model utilize locality of reference by bringing data into fast memory and using them several times before returning them to slower memory. it is shown that the circuit simulation problem has inherently poor locality of reference. the results are extended to hmm's where memory access time is given by an arbitrary (nondecreasing) function. tight upper and lower bounds are obtained for hmm's with polynomial memory access time; the algorithms for searching, fft and matrix multiplication are shown to be optimal for arbitrary memory access time. on-line memory management algorithms for the hmm model are also considered. an algorithm that uses lru policy at the successive &ldquo;levels&rdquo; of the memory hierarchy is shown to be optimal.
quadratic forms on graphs. we introduce a new graph parameter, called the grothendieck constant of a graph g=(v,e), which is defined as the least constant k such that for every a:e→r,supf:v→s|v|-1 σ(u,v) ∈ e a(u,v) · ‹f(u),f(v)› ≤ k supf:v→(-1,+1) σ(u,v)∈ e a(u,v) · f(u)f(v).the classical grothendieck inequality corresponds to the case of bipartite graphs, but the case of general graphs is shown to have various algorithmic applications. indeed, our work is motivated by the algorithmic problem of maximizing the quadratic form ∑u,v∈ea(u,v)f(vover all f: v →-1,1, which arises in the study of correlation clustering and in the investigation of the spin glass model. we give upper and lower estimates for the integrality gap of this program. we show that the integrality gap is o(log θḡ)) where θ(ḡ) is the lovász theta function of the complement of g, which is always smaller than the chromatic number of g. this yields an efficient constant factor approximation algorithm for the above maximization problem for a wide range of graphs g. we also show that the maximum possible integrality gap is always at least ω(log ω(g)), where ω(g) is the clique number of g. in particular it follows that the maximum possible integrality gap for the complete graph on n θ vertices with no loops is ⏷(log n ). more generally, the maximum possible integrality gap for any perfect graph with chromatic number n is ⏷(log n). the lower bound for the complete graph improves a result of kashin and szarek on gram matrices of uniformly bounded functions, and settles a problem of megretski and of charikar and wirth.
transformations on straight line programs-preliminary version we consider a program schema that models straight line intermediate level code. a complete set of equivalence preserving transformations on programs is found for the case in which programs are equivalent if and only if their output functions are identical. this result is extended to the case in which programs are deemed equivalent if their output functions can be shown equivalent under a fixed set of algebraic laws. it is also shown that in the no algebra case and in cases where certain types of algebraic identities are allowed the problem of finding optimal code under a reasonable cost function can be reduced to finding a desired sequence of topological and algebraic transformations on programs.
a characterization of span program size and improved lower bounds for monotone span programs. we give a characterization of span program size by a combinatorial-algebraic measure. the measure we consider is a generalization of a measure on covers which has been used to prove lower bounds on formula size and has also been studied with respect to communication complexity.in the monotone case our new methods yield nω(log n) lower bounds for the monotone span program complexity of explicit boolean functions in n variables over arbitrary fields, improving the previous lower bounds on monotone span program size. our characterization of span program size implies that any matrix with superpolynomial separation between its rank and cover number can be used to obtain superpolynomial lower bounds on monotone span program size. we also identify a property of bipartite graphs that is sufficient for constructing boolean functions with large monotone span program complexity.
derandomization of auctions. we study the problem of designing seller-optimal auctions, i.e. auctions where the objective is to maximize revenue. prior to this work, the only auctions known to be approximately optimal in the worst case employed randomization. our main result is the existence of deterministic auctions that approximately match the performance guarantees of these randomized auctions. we give a fairly general derandomization technique for turning any randomized mechanism into an asymmetric deterministic one with approximately the same revenue. in doing so, we bypass the impossibility result for symmetric deterministic auctions and show that asymmetry is nearly as powerful as randomization for solving optimal mechanism design problems. our general construction involves solving an exponential-sized flow problem and thus is not polynomial-time computable. to complete the picture, we give an explicit polynomial-time construction for derandomizing a specific auction with good worst-case revenue. our results are based on toy problems that have a flavor similar to the hat problem from [3].
a linear time algorithm for computing the voronoi diagram of a convex polygon we present an algorithm for computing certain kinds of three-dimensional convex hulls in linear time. using this algorithm, we show that the voronoi diagram of n points in the plane can be computed in &thgr;(n) time when these points form the vertices of a convex polygon in, say, counterclockwise order. this settles an outstanding open problem in computational geometry. our techniques can also be used to obtain linear time algorithms for computing the farthest-point voronoi diagram and the medial axis of a convex polygon and for deleting a vertex from a general planar voronoi diagram.
approximating the cut-norm via grothendieck's inequality. the cut-norm $||a||_c$ of a real matrix $a=(a_{ij})_{i\in r,j\in s}$ is the maximum, over all $i \subset r$, $j \subset s$, of the quantity $|\sum_{i \in i, j\in j} a_{ij}|$. this concept plays a major role in the design of efficient approximation algorithms for dense graph and matrix problems. here we show that the problem of approximating the cut-norm of a given real matrix is max snp hard, and we provide an efficient approximation algorithm. this algorithm finds, for a given matrix $a=(a_{ij})_{i\in r,j\in s}$, two subsets $i \subset r$ and $j \subset s$, such that $|\sum_{i \in i, j\in j} a_{ij}| \geq \rho ||a||_c$, where $\rho>0$ is an absolute constant satisfying $\rho >0.56$. the algorithm combines semidefinite programming with a rounding technique based on grothendieck's inequality. we present three known proofs of grothendieck's inequality, with the necessary modifications which emphasize their algorithmic aspects. these proofs contain rounding techniques which go beyond the random hyperplane rounding of goemans and williamson [j. acm, 42 (1995), pp. 1115-1145], allowing us to transfer various algorithms for dense graph and matrix problems to the sparse case.
testing subgraphs in directed graphs. let h be a fixed directed graph on h vertices, let g be a directed graph on n vertices and suppose that at least εn2 edges have to be deleted from it to make it h-free. we show that in this case g contains at least f(ε, h)nh copies of h. this is proved by establishing a directed version of szemerédi's regularity lemma, and implies that for every h there is a one-sided error property tester whose query complexity is bounded by a function of ε only for testing the property ph of being h-free.as is common with applications of the undirected regularity lemma, here too the function 1/f(ε,h) is an extremely fast growing function in ε. we therefore further prove a precise characterization of all the digraphs h, for which f(ε,h) has a polynomial dependency on ε. this implies a characterization of all the digraphs h, for which the property of being h-free has a one-sided error property tester whose query complexity is polynomial in 1/ε. we further show that the same characterization also applies to two-sided error property testers as well. a special case of this result settles an open problem raised by the first author in (alon, proceedings of the 42nd ieee focs, ieee, new york, 2001, pp. 434-441). interestingly, it turns out that if ph has a polynomial query complexity, then there is a two-sided ε-tester for ph that samples only o(1/ε) vertices, whereas any one-sided tester for ph makes at least (1/ε)d/2 queries, where d is the average degree of h. we also show that the complexity of deciding if for a given directed graph h, ph has a polynomial query complexity, is np-complete, marking an interesting distinction from the case of undirected graphs.for some special cases of directed graphs h, we describe very efficient one-sided error property-testers for testing ph. as a consequence we conclude that when h is an undirected bipartite graph, we can give a one-sided error property tester with query complexity o((1/ε)h/2), improving the previously known upper bound o((1/ε)h2). the proofs combine combinatorial, graph theoretic and probabilistic arguments with results from additive number theory.
node-disjoint paths on the mesh and a new trade-off in vlsi layout. a number of basic models for vlsi layout are based on the construction of node-disjoint paths between terminals on a multilayer grid. in this setting, one is interested in minimizing both the number of layers required and the area of the underlying grid. building on work of cutler and shiloach [ networks, 8 (1978), pp. 253--278], aggarwal et al. [ proc. 26th ieee symposium on foundations of computer science , portland, or, 1985; algorithmica, 6 (1991), pp. 241--255], and aggarwal, klawe, and shor [ algorithmica}, 6 (1991), pp. 129--151], we prove an upper-bound trade-off between these two quantities in a general multilayer grid model. as a special case of our main result, we obtain significantly improved bounds for the problem of routing a full permutation on the mesh using node-disjoint paths; our new bound here is within polylogarithmic factors of the bisection bound. our algorithms involve some new techniques for analyzing the structure of node-disjoint paths in planar graphs and indicate some respects in which this problem, at least in the planar case, is fundamentally different from its edge-disjoint counterpart.
every monotone graph property is testable. a graph property is called monotone if it is closed under taking (not necessarily induced) subgraphs (or, equivalently, if it is closed under removal of edges and vertices). many monotone graph properties are some of the most well-studied properties in graph theory, and the abstract family of all monotone graph properties was also extensively studied. our main result in this paper is that any monotone graph property can be tested with one-sided error, and with query complexity depending only on ε. this result unifies several previous results in the area of property testing, and also implies the testability of well-studied graph properties that were previously not known to be testable. at the heart of the proof is an application of a variant of szemerédi's regularity lemma. the main ideas behind this application may be useful in characterizing all testable graph properties, and in generally studying graph property testing.as a byproduct of our techniques we also obtain additional results in graph theory and property testing, which are of independent interest. one of these results is that the query complexity of testing testable graph properties with one-sided error may be arbitrarily large. another result, which significantly extends previous results in extremal graph-theory, is that for any monotone graph property p, any graph that is ε -far from satisfying p, contains a subgraph of size depending on ε only, which does not satisfy p. finally, we prove the following compactness statement: if a graph g is ε-far from satisfying a (possibly infinite) set of graph properties p, then it is at least δ p ε-far from satisfying one of the properties.
random sampling and approximation of max-csp problems. we present a new efficient sampling method for approximating r-dimensional maximum constraint satisfaction problems, max-rcsp, on n variables up to an additive error &egr;nr. we prove a newgeneral paradigm in that it suffices, for a given set of constraints, to pick a small uniformly random subset of its variables, and the optimum value of the subsystem induced on these variables gives (after a direct normalization and with high probability) an approximation to the optimum of the whole system up to an additive error of &egr;nr. our method gives for the first time a polynomial in &egr;&mdash;1 bound on the sample size necessary to carry out the above approximation. moreover, this bound is independent in the exponent on the dimension r. the above method gives a completely uniform sampling technique for all the max-rcsp problems, and improves the best known sample bounds for the low dimensional problems, like max-cut. the method of solution depends on a new result on t he cut norm of random subarrays, and a new sampling technique for high dimensional linear programs. this method could be also of independent interest.
when trees collide: an approximation algorithm for the generalized steiner problem on networks we give the first approximation algorithm for the {\em generalized network steiner tree problem}, a problem in network design. an instance consists of a network with link-costs and, for each pair ${i,j}$ of nodes, an edge-connectivity requirement. the goal is to find a minimum-cost network using the available links and satisfying the requirements. our algorithm outputs a solution whose cost is within $ 2 \log r $ of optimal, where $r$ is the highest requirement value. in the course of proving the performance guarantee, we prove a combinatorial min-max approximate equality relating minimum-cost networks to maximum packings of certain kinds of cuts. as a consequence of the proof of this theorem, we obtain an approximation algorithm for optimally packing these cuts; we show that this algorithm has application to estimating the reliability of a probabilistic network.
dual integer linear programs and the relationship between their optima we consider dual pairs of packing and covering integer linear programs. best possible bounds are found between their optimal values. tight inequalities are obtained relating the integral optima and the optimal rational solutions.
optimal static range reporting in one dimension. we consider static one dimensional range searching problems. these problems are to build static data structures for an integer set s \subseteq u, where u = \{0,1,\dots,2^w-1\}, which support various queries for integer intervals of u. for the query of reporting all integers in s contained within a query interval, we present an optimal data structure with linear space cost and with query time linear in the number of integers reported. this result holds in the unit cost ram model with word size w and a standard instruction set. we also present a linear space data structure for approximate range counting. a range counting query for an interval returns the number of integers in s contained within the interval. for any constant &egr;>0, our range counting data structure returns in constant time an approximate answer which is within a factor of at most 1+&egr; of the correct answer.
a polynomial quantum algorithm for approximating the jones polynomial. the jones polynomial, discovered in 1984 [18], is an important knot invariant in topology. among its many connections to various mathematical and physical areas, it is known (due to witten [32]) to be intimately connected to topological quantum field theory (tqft). the works of freedman, kitaev, larsen and wang [13, 14] provide an efficient simulation of tqft by a quantum computer, and vice versa. these results implicitly imply the existence of an efficient quantum algorithm that provides a certain additive approximation of the jones polynomial at the fifth root of unity, e2π i/5, and moreover, that this problem is bqp-complete. unfortunately, this important algorithm was never explicitly formulated. moreover, the results in [13, 14] are heavily based on tqft, which makes the algorithm essentially inaccessible to computer scientists.we provide an explicit and simple polynomial quantum algorithm to approximate the jones polynomial of an n strands braid with m crossings at any primitive root of unity e2π i/k, where the running time of the algorithm is polynomial in m,n and k. our algorithm is based, rather than on tqft, on well known mathematical results (specifically, the path model representation of the braid group and the uniqueness of the markov trace for the temperly lieb algebra). by the results of [14], our algorithm solves a bqp complete problem.the algorithm we provide exhibits a structure which we hope is generalizable to other quantum algorithmic problems. candidates of particular interest are the approximations of other downwards self-reducible p-hard problems, most notably, the potts model.
deterministic sorting in o(nlog log n) time and linear space. we present a fast deterministic algorithm for integer sorting in linear space. our algorithm sorts n integers in the range {0, 1, 2, &1dots;, m&mdash;1} in linear space in o(n log log n) time. this improves our previous result [8] which sorts in o(n log log n log log log n) time and linear space. this also improves previous best deterministic sorting algorithm [3, 11] which sorts in o(nlog log n) time but uses o(m&egr;) space. our results can also be compared with thorup's previous result [16] which sorts in o(nlog log n) time and linear space but uses randomization.
time-adaptive algorithms for synchronization. we consider concurrent systems in which there is an unknown upper bound on memory access time. such a model is inherently different from the asynchronous model, where no such bound exists, and also from timing-based models, where such a bound exists and is known a priori. the appeal of our model lies in the fact that while it abstracts from implementation details, it is a better approximation of real concurrent systems than the asynchronous model. furthermore, it is stronger than the asynchronous model, enabling us to design algorithms for problems that are unsolvable in the asynchronous model.two basic synchronization problems, consensus and mutual exclusion, are investigated in a shared-memory environment that supports atomic read/write registers. we show that $\theta(\delta\frac{\log \delta}{\log\log \delta})$ is an upper and lower bound on the time complexity of consensus, where $\delta$ is the (unknown) upper bound on memory access time. for the mutual exclusion problem, we design an efficient algorithm that takes advantage of the fact that some upper bound on memory access time exists. the solutions for both problems are even more efficient in the absence of contention, in which case their time complexity is a constant.
adiabatic quantum state generation and statistical zero knowledge. the design of new quantum algorithms has proven to be an extremely difficult task. this paper considers a different approach to the problem, by studying the problem of 'quantum state generation'.we first show that any problem in statistical zero knowledge (including eg. discrete log, quadratic residuosity and gap closest vector in a lattice) can be reduced to an instance of the quantum state generation problem. having shown the generality of the state generation problem, we set the foundations for a new paradigm for quantum state generation. we define 'adiabatic state generation' (asg), which is based on hamiltonians instead of unitary gates. we develop tools for asg including a very general method for implementing hamiltonians (the sparse hamiltonian lemma), and ways to guarantee non negligible spectral gaps (the jagged adiabatic path lemma). we also prove that asg is equivalent in power to state generation in the standard quantum model. after setting the foundations for asg, we show how to apply our techniques to generate interesting superpositions related to markov chains.the asg approach to quantum algorithms provides intriguing links between quantum computation and many different areas: the analysis of spectral gaps and groundstates of hamiltonians in physics, rapidly mixing markov chains, statistical zero knowledge, and quantum random walks. we hope that these links will bring new insights and methods into quantum algorithms.
covert two-party computation. we introduce covert two-party computation, a stronger notion of security than standard secure two-party computation. like standard secure two-party computation, covert two-party computation allows alice and bob, with secret inputs xa and xb respectively, to compute a function f(xa,xb) without leaking any additional information about their inputs. in addition, covert two-party computation guarantees that even the existence of a computation is hidden from all protocol participants unless the value of the function mandates otherwise. this allows the construction of protocols that return f(xa,xb) only when it equals a certain value of interest (such as "yes, we are romantically interested in each other") but for which neither party can determine whether the other even ran the protocol whenever f(xa,xb) is not a value of interest. since existing techniques for secure function evaluation always reveal that both parties participate in the computation, covert computation requires the introduction of new techniques based on provably secure steganography. we introduce security definitions for covert two-party computation and show that this surprising notion can be achieved by a protocol given the decisional diffie-hellman assumption in the "honest but curious" model. using this protocol as a subroutine, we present another protocol which is fair and secure against malicious adversaries in the random oracle model --- unlike most other protocols against malicious adversaries, this protocol does not rely on zero-knowledge proofs (or similar cut-and-choose techniques), because they inherently reveal that a computation took place. we remark that all our protocols are of comparable efficiency to protocols for standard secure two-party computation.
visibly pushdown languages. we propose the class of visibly pushdown languages as embeddings of context-free languages that is rich enough to model program analysis questions and yet is tractable and robust like the class of regular languages. in our definition, the input symbol determines when the pushdown automaton can push or pop, and thus the stack depth at every position. we show that the resulting class vpl of languages is closed under union, intersection, complementation, renaming, concatenation, and kleene-*, and problems such as inclusion that are undecidable for context-free languages are exptime-complete for visibly pushdown automata. our framework explains, unifies, and generalizes many of the decision procedures in the program analysis literature, and allows algorithmic verification of recursive programs with respect to many context-free properties including access control properties via stack inspection and correctness of procedures with respect to pre and post conditions. we demonstrate that the class vpl is robust by giving two alternative characterizations: a logical characterization using the monadic second order (mso) theory over words augmented with a binary matching predicate, and a correspondence to regular tree languages. we also consider visibly pushdown languages of infinite words and show that the closure properties, mso-characterization and the characterization in terms of regular trees carry over. the main difference with respect to the case of finite words turns out to be determinizability: nondeterministic büchi visibly pushdown automata are strictly more expressive than deterministic muller visibly pushdown automata.
on finding lowest common ancestors in trees trees in an n node forest are to be merged according to instructions in a given sequence, while other instructions in the sequence ask for the lowest common ancestor of pairs of nodes. we show that any sequence of o(n) instructions can be processed &ldquo;on line&rdquo; in o(n log n) steps on a random access computer. if we can accept our answer &ldquo;off-line&rdquo;, that is, no answers need to be produced until the entire sequence of instructions has been seen seen, then we may perform the task in o(n g(n)) steps, where g(n) is the number of times we must apply log2 to n to obtain a number less than or equal to zero. a third algorithm solves a problem of intermediate complexity. we require the answers on line, but we suppose that all tree merging instructions precede the information requests. this algorithm requires o(n log log n) time. we apply the first on line algorithm to a problem in code optimization, that of computing immediate dominators in a reducible flow graph. we show how this computation can be performed in o(n log n) steps.
on notions of information transfer in vlsi circuits several papers have recently dealt with techniques for proving area-time lower bounds for vlsi computation by &ldquo;crossing sequence&rdquo; methods. a number of natural questions are raised by these definitions. 1.is the fooling set approach the most powerful way to get information-transfer-based lower bounds? we shall show it is not, and offer a candidate for the title &ldquo;most powerful.&rdquo; of course, without a precise definition of &ldquo;information transfer argument,&rdquo; there could be other contenders. 2.are the notions of the three papers cited equivalent? we shall exhibit certain inequivalences among the three notions, although open questions remain. however, we can resolve an open question of papadimitriou and sipser [ps] concerning the relationship between nondeterministic and deterministic communication complexity.
quantum lower bounds by quantum arguments. we propose a new method for proving lower bounds on quantum query algorithms. instead of a classical adversary that runs the algorithm with on input and then modifies the input, we use a quantum adversary that runs the algorithm with a superposition of inputs. if the algorithm works correctly, its state becomes entangled with the superposition over inputs. we bound the number of queries needed to achieve a sufficient entanglement and this implies a lower bound on the number of queries for the computation. using this method, we prove two new ω(√n) lower bounds on computing and of ors and inverting a permutation and also provide more uniform proofs for several known lower bounds which have been previously proven via a variety of different techniques.
a new protocol and lower bounds for quantum coin flipping. we present a new protocol and two lower bounds for quantum coin flipping. in our protocol, no dishonest party can achieve one outcome with probability more than 0.75. then we show that out protocol is optimal among 3-round protocols of a certain form.for arbitrary quantum protocols, we show that if a protocol achieves a bias of at most ε, it must use at least ω(log log 1ε) rounds of communication. this implies that the parallel repetition fails for quantum coin flipping. (the bias of a protocol cannot be arbitrarily decreased by running several copies of it in parallel.)
quantum algorithms a decade after shor. in 1994, peter shor discovered a polynomial time quantum algorithm for factoring and discrete logarithm. two years later, in 1996, lov grover discovered a search algorithm which is quadratically better than conventional search. by now, each of the two algorithms has developed into a line of research which goes well beyond the original algorithm. shor's algorithm has inspired the study of quantum fourier sampling which has resulted in more quantum algorithms for number-theoretic and group-theoretic problems. grover's algorithm has developed into the area of quantum query algorithms.i will survey the developments in quantum query algorithms. the topics will include: applications of grover's algorithm to element distinctness and other problems, lower bounds on quantum algorithms and the use of quantum random walks to design better search algorithm. i will also describe how some of techniques in this area can be used as "quantum black boxes" in an otherwise classical algorithm.
lower bounds for linear degeneracy testing. in the late nineties, erickson proved a remarkable lower bound on the decision tree complexity of one of the central problems of computational geometry: given n numbers, do any r of them add up to 0? his lower bound of &omega;(n&lceil;r/2&rceil;), for any fixed r, is optimal if the polynomials at the nodes are linear and at most r-variate. we generalize his bound to s-variate polynomials for s > r. erickson's bound decays quickly as r grows and never reaches above pseudo-polynomial: we provide an exponential improvement. our arguments are based on three ideas: (i) a geometrization of erickson's proof technique; (ii) the use of error-correcting codes; and (iii) a tensor product construction for permutation matrices.
one-dimensional quantum walks. we define and analyze quantum computational variants of random walks on one-dimensional lattices. in particular, we analyze a quantum analog of the symmetric random walk, which we call the hadamard walk. several striking differences between the quantum and classical cases are observed. for example, when unrestricted in either direction, the hadamard walk has position that is nearly uniformly distributed in the range [-t/\sqrt 2, t/\sqrt 2] after t steps, which is in sharp contrast to the classical random walk, which has distance o(\sqrt t) from the origin with high probability. with an absorbing boundary immediately to the left of the starting position, the probability that the walk exits to the left is 2/&pgr, and with an additional absorbing boundary at location n, the probability that the walk exits to the left actually increases, approaching 1/\sqrt 2 in the limit. in the classical case both values are 1.
approximate nearest neighbors and the fast johnson-lindenstrauss transform. we introduce a new low-distortion embedding of l2d into lpo(log n) (p=1,2), called the fast-johnson-linden-strauss-transform. the fjlt is faster than standard random projections and just as easy to implement. it is based upon the preconditioning of a sparse projection matrix with a randomized fourier transform. sparse random projections are unsuitable for low-distortion embeddings. we overcome this handicap by exploiting the "heisenberg principle" of the fourier transform, ie, its local-global duality. the fjlt can be used to speed up search algorithms based on low-distortion embeddings in l1 and l2. we consider the case of approximate nearest neighbors in l2d. we provide a faster algorithm using classical projections, which we then further speed up by plugging in the fjlt. we also give a faster algorithm for searching over the hypercube.
quantum walks on graphs. we set the ground for a theory of quantum walks on graphs-the generalization of random walks on finite graphs to the quantum world. such quantum walks do not converge to any stationary distribution, as they are unitary and reversible. however, by suitably relaxing the definition, we can obtain a measure of how fast the quantum walk spreads or how confined the quantum walk stays in a small neighborhood. we give definitions of mixing time, filling time, dispersion time. we show that in all these measures, the quantum walk on the cycle is almost quadratically faster then its classical correspondent. on the other hand, we give a lower bound on the possible speed up by quantum walks for general graphs, showing that quantum walks can be at most polynomially faster than their classical counterparts.
aggregating inconsistent information: ranking and clustering. we address optimization problems in which we are given contradictory pieces of input information and the goal is to find a globally consistent solution that minimizes the number of disagreements with the respective inputs. specifically, the problems we address are rank aggregation, the feedback arc set problem on tournaments, and correlation and consensus clustering. we show that for all these problems (and various weighted versions of them), we can obtain improved approximation factors using essentially the same remarkably simple algorithm. additionally, we almost settle a long-standing conjecture of bang-jensen and thomassen and show that unless np⊆bpp, there is no polynomial time algorithm for the problem of minimum feedback arc set in tournaments.
the invasiveness of off-line memory checking. memory checking is the task of checking the correctness of a sequence of "store" and "retrieve" operations. the operations are performed in a large unreliable memory. a checker using a much smaller but completely reliable memory tries to decide whether they were executed correctly. m. blum, w. evans, p. gemmel, s. kannan and m. naor, has shown in 1991 that the off-line checking of a sequence of memory operations concerning a ram consisting of n registers can be done, in a probabilistic sense, by a checker using only o(log n) reliable memory and a constant number of ram operation per each "store" and "retrieve" operations (with log n word length), moreover no unproven cryptographic assumptions are needed in the proof. the probability of error will be polynomially small in n. the solution however requires the checker to store some extra information in the unreliable memory, that is, the checking protocol is invasive. (in this solution the time of each "store" operation must be stored together with the data and must be supplied to the checker at the time of the corresponding retrieve operation.) in this paper we prove that off-line memory checking, in the sense described above, is necessarily invasive, even if we make the problem somewhat easier for the checker to exclude trivial counter-examples. we show that even if the checker is allowed to read a constant number of registers from the large memory after each "store" or "retrieve" instruction, off-line non-invasive memory checking is not possible. moreover for the case when the invasiveness consists of storing some extra information together with each piece of data and retrieving it together with the data we give a quantitative lower bound on the amount of extra "invasive" information stored in the memory. namely, if the checker has o(log n) memory and the probability of error is polynomially small than the "invasiveness" of the mentioned method of [5] is optimal upto a constant factor. with other words the total number of extra bits that must be written in the memory is at least &egr;t log t, where t is the number of store and retrieve operations. in the lower bounds we do not restrict the computational power of the checker at all, in fact we only assume that the checker is an n-way branching program with o(log n) bits of memory.
the worst-case behavior of schnorr's algorithm approximating the shortest nonzero vector in a lattice. schnorr's algorithm for finding an approximation for the shortest nonzero vector in an n dimensional lattice depends on a parameter k. he proved that for a fixed k ≤ n his algorithm (block 2k-reduction) provides a lattice vector whose length is greater than the length of a shortest nonzero vector in the lattice by at most a factor of (4k2) n/k. (the time required by the algorithm depends on k.) we show that if k=o(n), this bound on the performance of schnorr's algorithm cannot be improved (apart from a constant factor in the exponent), namely there is a lattice and a basis so that if they are given as an input to the algorithm then the resulting approximating factor of the output is at least k ε n/k. (for larger integers k if schnorr's algorithm runs in polynomial time then we have already a polynomial time algorithm for finding the shortest nonzero vector.) we also solve an open problem formulated by schnorr about the the korkine-zolotareff lattice constants αk. we show that his upper bound αk ≤ k1 + ln k is the best possible apart from a constant factor in the exponent. we prove a similar result about his upper bound βk≤ 4k2, where βk is another lattice constant with an important role in schnorr's analysis of his algorithm.
hierarchies based on computational complexity and irregularities of class determining measured sets (preliminary report) we consider here the problem of building transfinite hierarchies of computable functions on the basis of their difficulty of computation. previous hierarchies of functions through the constructive ordinals have had two major problems, each apparently caused by not having techniques to restrict the classes considered at limit ordinals. these problems are, first that every function occurs at some name for &ohgr;, or some other small ordinal, and second that two names for the same constructive ordinal have two different classes of functions associated with them. the axioms of computational complexity introduced by blum[1] and several theorems by blum[1],and by mccreight and meyer[9], particularly the union theorem, lead to a very natural method of hierarchy building that partially avoids the first of these problems. the other problem is not overcome, however. in attempting to understand the problem of obtaining unique, or nearly unique classes of functions we have encountered difficulties because the class determining measured sets of mccreight and meyer[9] lack several properties that might reasonably be desired.
computing the betti numbers of arrangements. (math) in this paper, we consider the problem of computing the betti numbers of an arrangement of $n$ compact semi-algebraic sets, $s_1,\ldots,s_n \subset \r^k$, where each $s_i$ is described using a constant number of polynomials with degrees bounded by a constant. such arrangements are ubiquitous in computational geometry. we give an algorithm for computing $\ell$-th betti number, $\beta_\ell(\cup_i s_i), 0 \leq \ell \leq k-1$, using $o(n^{\ell+2})$ algebraic operations. additionally, one has to perform linear algebra on matrices of size bounded by $o(n^{\ell+1})$. all previous algorithms for computing the betti numbers of arrangements, triangulated the arrangement giving rise to a complex of size $o(n^{2^k})$ in the worst case. to our knowledge this is the first algorithm for computing $\beta_\ell(\cup_i s_i)$ that does not rely on such a global triangulation, and has a graded complexity which depends on $\ell$.
hardness of the undirected edge-disjoint paths problem. we show that there is no log 1 over 3-ε m approximation for the undirected edge-disjoint paths problem unless np ⊆ zptime(npolylog(n), where m is the size of the graph and ε is any positive constant. this hardness result also applies to the undirected all-or-nothing multicommodity flow problem and the undirected node-disjoint paths problem.
hardness of the undirected congestion minimization problem. we show that there is no $\gamma\log\log m/\log\log\log m$-approximation for the undirected congestion minimization problem unless $np \subseteq zptime(n^{{\rm polylog} n})$, where $m$ is the size of the graph and &ggr; is some positive constant.
logarithmic hardness of the directed congestion minimization problem. we show that for any constant ε > 0, there is no ω(log1-εm)-approximation algorithm for the directed congestion minimization problem on networks of size m unless np ⊆ zptime(npolylog n). this bound is almost tight given the o(log m/ log log m)-approximation via randomized rounding due to raghavan and thompson.
finding patterns common to a set of strings (extended abstract) we motivate, formalize, and study a computational problem in concrete inductive inference. a &ldquo;pattern&rdquo; is defined to be a concatenation of constants and variables, and the language of a pattern is defined to be the set of strings obtained by substituting constant strings for the variables. the problem we consider is, given a set of strings, find a minimal pattern language containing this set. this problem is shown to be effectively solvable in the general case and to lead to correct inference in the limit of the pattern languages. there exists a polynomial time algorithm for it in the restricted case of one-variable patterns. inference from positive data is re-examined, and a characterization given of when it is possible for a family of recursive languages. various collateral results about patterns and pattern languages are obtained. section 1 is an introduction explaining the context of this work and informally describing the problem formulation. section 2 is definitions. section 3 is results concerning patterns and pattern languages. section 4 concerns the abstract question of inference from positive data. section 5 gives a polynomial time algorithm for finding minimal one-variable pattern languages compatible with a given set of strings. section 6 contains remarks.
local and global properties in networks of processors (extended abstract) this paper attempts to get at some of the fundamental properties of distributed computing by means of the following question: &ldquo;how much does each processor in a network of processors need to know about its own identity, the identities of other processors, and the underlying connection network in order for the network to be able to carry out useful functions?&rdquo; the approach we take is to require that the processors be designed without any knowledge (or only very broad knowledge) of the networks they are to be used in, and furthermore, that all processors with the same number of communication ports be identical. given a particular network function, e.g., setting up a spanning tree, we ask whether processors may be designed so that when they are embedded in any connected network and started in some initial configuration, they are guaranteed to accomplish the desired function.
learning a circuit by injecting values. we propose a new model for exact learning of acyclic circuits using experiments in which chosen values may be assigned to an arbitrary subset of wires internal to the circuit, but only the value of the circuit's single output wire may be observed. we give polynomial time algorithms to learn (1) arbitrary circuits with logarithmic depth and constant fan-in and (2) boolean circuits of constant depth and unbounded fan-in over and, or, and not gates. thus, both ac0 and nc1 circuits are learnable in polynomial time in this model. negative results show that some restrictions on depth, fan-in and gate types are necessary: exponentially many experiments are required to learn and/or circuits of unbounded depth and fan-in; it is np-hard to learn and/or circuits of unbounded depth and fan-in 2; and it is np-hard to learn circuits of bounded depth and unbounded fan-in over and, or, and threshold gates, even when the target circuit is known to contain at most one threshold gate and that threshold gate has threshold 2. we also consider the effect of adding an oracle for behavioral equivalence. in this case there are polynomial-time algorithms to learn arbitrary circuits of constant fan-in and unbounded depth and to learn boolean circuits with arbitrary fan-in and unbounded depth over and, or, and not gates. a corollary is that these two classes are pac-learnable if experiments are available.
fast probabilistic algorithms for hamiltonian circuits and matchings the main purpose of this paper is to give techniques for analysing the probabilistic performance of certain kinds of algorithms, and hence to suggest some fast algorithms with provably desirable probabilistic behaviour. the particular problems we consider are: finding hamiltonian circuits in directed graphs (dhc), finding hamiltonian circuits in undirected graphs (uhc), and finding perfect matchings in undirected graphs (pm). we show that for each problem there is an algorithm that is extremely fast (0(n(log n)2) for dhc and uhc, and 0(nlog n) for pm), and which with probability tending to one finds a solution in randomly chosen graphs of sufficient density. these results contrast with the known np-completeness of the first two problems [2,12] and the best worst-case upper bound known of 0(n2.5) for the last [9].
near-optimal network design with selfish agents. we introduce a simple network design game that models how independent selfish agents can build or maintain a large network. in our game every agent has a specific connectivity requirement, i.e. each agent has a set of terminals and wants to build a network in which his terminals are connected. possible edges in the network have costs and each agent's goal is to pay as little as possible. determining whether or not a nash equilibrium exists in this game is np-complete. however, when the goal of each player is to connect a terminal to a common source, we prove that there is a nash equilibrium as cheap as the optimal network, and give a polynomial time algorithm to find a (1+ε)-approximate nash equilibrium that does not cost much more. for the general connection game we prove that there is a 3-approximate nash equilibrium that is as cheap as the optimal network, and give an algorithm to find a (4.65+ε)-approximate nash equilibrium that does not cost much more.
stability of load balancing algorithms in dynamic adversarial systems. in the dynamic load balancing problem, we seek to keep the job load roughly evenly distributed among the processors of a given network. the arrival and departure of jobs is modeled by an adversary restricted in its power. muthukrishnan and rajaraman [an adversarial model for distributed dynamic load balancing, in proceedings of the 10th acm symposium on parallel algorithms and architectures, acm, new york, 1998] gave a clean characterization of a restriction on the adversary that can be considered the natural analogue of a cut condition. they proved that a simple local balancing algorithm proposed by aiello et al. [approximate load balancing on dynamic and asynchronous networks, in proceedings of the 25th acm symposium on theory of computing, acm, new york, 1993] is stable against such an adversary if the insertion rate is restricted to a $(1-\varepsilon)$ fraction of the cut size. they left as an open question whether the algorithm is stable at rate 1. in this paper, we resolve this question positively, by proving stability of the local algorithm at rate 1. our proof techniques are very different from the ones used by muthukrishnan and rajaraman and yield a simpler proof and tighter bounds on the difference in loads. in addition, we introduce a multicommodity version of this load balancing model and show how to extend the result to the case of balancing two different kinds of loads at once (obtaining as a corollary a new proof of the 2-commodity max-flow min-cut theorem). we also show how to apply the proof techniques to the problem of routing packets in adversarial systems. awerbuch et al. [simple routing strategies for adversarial systems, in proceedings of the 42nd ieee symposium on foundations of computer science, ieee computer society, los alamitos, ca, 2001] showed that the same load balancing algorithm is stable against an adversary, inserting packets at rate 1 with a single destination in dynamically changing networks. our techniques give a much simpler proof for a different model of adversarially changing networks.
fast leader-election protocols with bounded cheaters' edge. we study the leader election problem on n players in the asynchronous full-information model. our main contention is that the most commonly used performance measure for leader-election protocols, called resilience, is unable to discern whether a small number of players can exercise disproportionate influence on the outcome of a protocol, or not. as a remedy we propose a new quantity, named cheaters' edge, which roughly describes by what multiplicative factor malicious players may increase, through cheating, their probability of getting elected. arguably, a good protocol must have bounded cheaters' edge.we present polynomial-time constructions of new leader-election protocols that are fast, in terms of the rounds required (5, 5 log n, and log n rounds, respectively), but moreover exhibit bounded cheaters' edge under progressively looser restrictions on the number t of malicious players: t < θn / log n, t < θn / √log n log log n, and, eventually, no restriction at all---without relying on any a priori knowledge of t. the latter of these three protocols constitutes the first constructive solution to a problem posed by alon and naor more than a decade ago.
the complexity of analytic tableaux. the method of analytic tableaux is employed in many introductory texts and has also been used quite extensively as a basis for automated theorem proving. in this paper, we discuss the complexity of the system as a method for refuting contradictory sets of clauses, and resolve several open questions. we discuss the three forms of analytic tableaux: clausal tableaux, generalized clausal tableaux, and binary tableaux. we resolve the relative complexity of these three forms of tableaux proofs and also resolve the relative complexity of analytic tableaux versus resolution. we show that there is a quasi-polynomial simulation of tree resolution by analytic tableaux; this simulation cannot be improved, since we give a matching lower bound that is tight to within a polynomial.
cache-oblivious priority queue and graph algorithm applications. (math) in this paper we develop an optimal cache-oblivious priority queue data structure, supporting insertion, deletion, and deletemin operations in o(1 \over b logm/bn \over b) amortized memory transfers, where m and b are the memory and block transfer sizes of any two consecutive levels of a multilevel memory hierarchy. in a cache-oblivious data structure, m and b are not used in the description of the structure. the bounds match the bounds of several previously developed external-memory (cache-aware) priority queue data structures, which all rely crucially on knowledge about m and b. priority queues are a critical component in many of the best known external- memory graph algorithms, and using our cache-oblivious priority queue we develop several cache- oblivious graph algorithms.
a difference in efficiency between synchronous and asynchronous systems a system of parallel processes is said to be synchronous if all processes run using the same clock, and it is asynchronous if each process has its own independent clock. for any s, n, a particular distributed problem is defined involving system behavior at n &ldquo;ports&rdquo;. this problem can be solved in time s by a synchronous system but requires time at least (s-1) log n on any asynchronous system.
cutting triangular cycles of lines in space. we show that n lines in 3-space can be cut into o(n2-1/69log16/69n) pieces, such that all depth cycles defined by triples of lines are eliminated. this partially resolves a long-standing open problem in computational geometry, motivated by hidden-surface removal in computer graphics.
distinct distances in three and higher dimensions. improving an old result of clarkson, edelsbrunner, guibas, sharir and welzl, we show that the number of distinct distances determined by a set $p$ of $n$ points in three-dimensional space is $\omega(n^{77/141-\varepsilon})=\omega(n^{0.546})$, for any $\varepsilon>0$. moreover, there always exists a point $p\in p$ from which there are at least so many distinct distances to the remaining elements of $p$. the same result holds for points on the three-dimensional sphere. as a consequence, we obtain analogous results in higher dimensions.
new approximation guarantee for chromatic number. we describe how to color every 3-colorable graph with o(n0.2111) colors, thus improving an algorithm of blum and karger from almost a decade ago. our analysis uses new geometric ideas inspired by the recent work of arora, rao, and vazirani on sparsest cut, and these ideas show promise of leading to further improvements.
fitting algebraic curves to noisy data. we introduce the following problem which is motivated by applications in vision and pattern detection: we are given pairs of datapoints (x1,y1), (x2,y2),...,(xm, ym) ∈ [- 1, 1] × [- 1, 1], a noise parameter δ > 0, a degree bound d, and a threshold ρ > 0. we desire an algorithm that enlists every degree d polynomial h such that |h(xi) - yi| ≤ δ for at least δ fraction of the indices i. if δ = 0, this is just the list decoding problem that has been popular in complexity theory and for which sudan gave a poly(m,d) time algorithm. however, for δ > 0, the problem as stated becomes ill-posed and one needs a careful reformulation (see the introduction). we prove a few basic results about this (reformulated) problem. we show that the problem has no polynomial-time algorithm (our counterexample works for ρ = 0.5). this is shown by exhibiting an instance of the problem where the number of solutions is as large as exp(d0.5-ε) and every pair of solutions is far from each other in ℓ∞ norm. on the algorithmic side, we give a rigorous analysis of a brute force algorithm that runs in exponential time. also, in surprising contrast to our lowerbound, we give a polynomial-time algorithm for learning the polynomials assuming the data is generated using a mixture model in which the mixing weights are "nondegenerate."
approximation schemes for minimum latency problems. the minimum latency problem, also known as the traveling repairman problem, is a variant of the traveling salesman problem in which the starting node of the tour is given and the goal is to minimize the sum of the arrival times at the other nodes. we present a quasi-polynomial time approximation scheme (qptas) for this problem when the instance is a weighted tree, when the nodes lie in $\mathbb{r}^d$ for some fixed d, and for planar graphs. we also present a polynomial time constant factor approximation algorithm for the general metric case. the currently best polynomial time approximation algorithm for general metrics, due to goemans and kleinberg, computes a 3.59-approximation.
euclidean distortion and the sparsest cut. we prove that every n-point metric space of negative type (in particular, every n-point subset of l1) embeds into a euclidean space with distortion o(√log n log log n), a result which is tight up to the o(log log n) factor. as a consequence, we obtain the best known polynomial-time approximation algorithm for the sparsest cut problem with general demands. if the demand is supported on a subset of size k, we achieve an approximation ratio of o(√log k log log k).
expander flows, geometric embeddings and graph partitioning. we give a o(&sqrt;log n)-approximation algorithm for the sparsest cut, edge expansion, balanced separator, and graph conductance problems. this improves the o(log n)-approximation of leighton and rao (1988). we use a well-known semidefinite relaxation with triangle inequality constraints. central to our analysis is a geometric theorem about projections of point sets in rd, whose proof makes essential use of a phenomenon called measure concentration. we also describe an interesting and natural &ldquo;approximate certificate&rdquo; for a graph's expansion, which involves embedding an n-node expander in it with appropriate dilation and congestion. we call this an expander flow.
local search heuristic for k-median and facility location problems. we analyze local search heuristics for the metric k-median and facility location problems. we define the locality gap of a local search procedure for a minimization problem as the maximum ratio of a locally optimum solution (obtained using this procedure) to the global optimum. for k-median, we show that local search with swaps has a locality gap of 5. furthermore, if we permit up to p facilities to be swapped simultaneously, then the locality gap is 3+2/p. this is the first analysis of a local search for k-median that provides a bounded performance guarantee with only k medians. this also improves the previous known 4 approximation for this problem. for uncapacitated facility location, we show that local search, which permits adding, dropping, and swapping a facility, has a locality gap of 3. this improves the bound of 5 given by m. korupolu, c. plaxton, and r. rajaraman [analysis of a local search heuristic for facility location problems, technical report 98-30, dimacs, 1998]. we also consider a capacitated facility location problem where each facility has a capacity and we are allowed to open multiple copies of a facility. for this problem we introduce a new local search operation which opens one or more copies of a facility and drops zero or more facilities. we prove that this local search has a locality gap between 3 and 4.
space-efficient approximate voronoi diagrams. (math) given a set $s$ of $n$ points in $\ir^d$, a {\em $(t,\epsilon)$-approximate voronoi diagram (avd)} is a partition of space into constant complexity cells, where each cell $c$ is associated with $t$ representative points of $s$, such that for any point in $c$, one of the associated representatives approximates the nearest neighbor to within a factor of $(1+\epsilon)$. like the voronoi diagram, this structure defines a spatial subdivision. it also has the desirable properties of being easy to construct and providing a simple and practical data structure for answering approximate nearest neighbor queries. the goal is to minimize the number and complexity of the cells in the avd.(math) we assume that the dimension $d$ is fixed. given a real parameter $\gamma$, where $2 \le \gamma \le 1/\epsilon$, we show that it is possible to construct a $(t,\epsilon)$-avd consisting of \[o(n \epsilon^{\frac{d-1}{2}} \gamma^{\frac{3(d-1)}{2}} \log \gamma) \] cells for $t = o(1/(\epsilon \gamma)^{(d-1)/2})$. this yields a data structure of $o(n \gamma^{d-1} \log \gamma)$ space (including the space for representatives) that can answer $\epsilon$-nn queries in time $o(\log(n \gamma) + 1/(\epsilon \gamma)^{(d-1)/2})$. (hidden constants may depend exponentially on $d$, but do not depend on $\epsilon$ or $\gamma$).(math) in the case $\gamma = 1/\epsilon$, we show that the additional $\log \gamma$ factor in space can be avoided, and so we have a data structure that answers $\epsilon$-approximate nearest neighbor queries in time $o(\log (n/\epsilon))$ with space $o(n/\epsilon^{d-1})$, improving upon the best known space bounds for this query time. in the case $\gamma = 2$, we have a data structure that can answer approximate nearest neighbor queries in $o(\log n + 1/\epsilon^{(d-1)/2})$ time using optimal $o(n)$ space. this dramatically improves the previous best space bound for this query time by a factor of $o(1/\epsilon^{(d-1)/2})$.(math) we also provide lower bounds on the worst-case number of cells assuming that cells are axis-aligned rectangles of bounded aspect ratio. in the important extreme cases $\gamma \in \{2, 1/\epsilon\}$, our lower bounds match our upper bounds asymptotically. for intermediate values of $\gamma$ we show that our upper bounds are within a factor of $o((1/\epsilon)^{(d-1)/2}\log \gamma)$ of the lower bound.
on the importance of idempotence. range searching is among the most fundamental problems in computational geometry. an n-element point set in rd is given along with an assignment of weights to these points from some commutative semigroup. subject to a fixed space of possible range shapes, the problem is to preprocess the points so that the total semigroup sum of the points lying within a given query range η can be determined quickly. in the approximate version of the problem we assume that η is bounded, and we are given an approximation parameter ε > 0. we are to determine the semigroup sum of all the points contained within η and may additionally include any of the points lying within distance ε • diam(η) of η's boundar.in this paper we contrast the complexity of range searching based on semigroup properties. a semigroup (s,+) is idempotent if x + x = x for all x ∈ s, and it is integral if for all k ≥ 2, the k-fold sum x + ... + x is not equal to x. for example, (r, min) and (0,1, ∨) are both idempotent, and (n, +) is integral. to date, all upper and lower bounds hold irrespective of the semigroup. we show that semigroup properties do indeed make a difference for both exact and approximate range searching, and in the case of approximate range searching the differences are dramatic.first, we consider exact halfspace range searching. the assumption that the semigroup is integral allows us to improve the best lower bounds in the semigroup arithmetic model. for example, assuming o(n) storage in the plane and ignoring polylog factors, we provide an ω*(n2/5) lower bound for integral semigroups, improving upon the best lower bound of ω*(n1/3), thus closing the gap with the o(n1/2) upper bound.we also consider approximate range searching for euclidean ball ranges. we present lower bounds and nearly matching upper bounds for idempotent semigroups. we also present lower bounds for range searching for integral semigroups, which nearly match existing upper bounds. these bounds show that the advantages afforded by idempotency can result in major improvements. in particular, assuming roughly linear space, the exponent in the ε-dependencies is smaller by a factor of nearly 1/2. all our results are presented in terms of space-time tradeoffs, and our lower and upper bounds match closely throughout the entire spectrum.to our knowledge, our results provide the first proof that semigroup properties affect the computational complexity of range searching in the semigroup arithmetic model. these are the first lower bound results for any approximate geometric retrieval problems. the existence of nearly matching upper bounds, throughout the range of space-time tradeoffs, suggests that we are close to resolving the computational complexity of both idempotent and integral approximate spherical range searching in the semigroup arithmetic model.
edge-deletion and edge-contraction problems for a property -&-pgr; on graphs, the corresponding edge-deletion problem ped(-&-pgr;) (edge-contraction problem pec(-&-pgr;), resp.) is defined as follows: given a graph g, find a set of edges of minimum cardinality whose deletion (contraction, resp.) results in a graph satisfying property -&-pgr;. in this paper we show that the edge-deletion problem ped (-&-pgr;) (edge-contraction problem pec (-&-pgr;), resp.) is np-hard if -&-pgr; is hereditary on subgraphs (contractions, resp.) and is determined by the 3-connected components.
the distance trisector curve. given points p and q in the plane, we are interested in separating them by two curves c1 and c2 such that every point of c1 has equal distance to p and to c2, and every point of c2 has equal distance to c1 and to q. we show by elementary geometric means that such c1 and c2 exist and are unique. moreover, for p = (0,1) and q = (0,-1), c1 is the graph of a function ƒ: r → r, c2 is the graph of -f, and f is convex and analytic (i.e., given by a convergent power series at a neighborhood of every point). we conjecture that f is not expressible by elementary functions and, in particular, not algebraic. we provide an algorithm that, given x ∈ r and ε > 0, computes an approximation to f(x) with error at most ε in time polynomial in log 1+|x|/ε.the separation of two points by two "trisector" curves considered here is a special (two-point) case of a new kind of voronoi diagram, which we call the voronoi diagram with neutral zone and which we investigate in a companion paper.
lower bounds for distributed coin-flipping and randomized consensus. we examine a class of collective coin-flipping games that arises from randomized distributed algorithms with halting failures. in these games, a sequence of local coin flips is generated, which must be combined to form a single global coin flip. an adversary monitors the game and may attempt to bias its outcome by hiding the result of up to t local coin flips. we show that to guarantee at most constant bias, &ohgr;(t2) local coins are needed, even if (a) the local coins can have arbitrary distributions and ranges, (b) the adversary is required to decide immediately wheter to hide or reveal each local coin, and (c) the game can detect which local coins have been hidden. if the adversary is permitted to control the outcome of the coin except for cases whose probability is polynomial in t, &ohgr;(t2/log2t) local coins are needed. combining this fact with an extended version of the well-known fischer-lynch-paterson impossibility proof of deterministic consensus, we show that given an adaptive adversary, any t-resilient asynchronous consensus protocol requires &ohgr;(t2/log2t) local coin flips in any model that can be simulated deterministically using atomic registers. this gives the first nontrivial lower bound on the total work required by wait-free consensus and is tight to within logarithmic factors.
wait-free consensus with infinite arrivals. a randomized algorithm is given that solves the wait-free consensus problem for a shared-memory model with infinitely many processes. the algorithm is based on a weak shared coin algorithm that uses weighted voting to achieve a majority outcome with at least constant probability that cannot be disguised even if a strong adversary is allowed to destroy infinitely many votes. the number of operations performed by process i is a polynomial function of i. additional algorithms are given for solving consensus more efficiently in models with an unknown upper bound b on concurrency or an unknown upper bound n on the number of active processes; under either of these restrictions, it is also shown that the problem can be solved even with infinitely many anonymous processes by prefixing each instance of the shared coin with a naming algorithm that breaks symmetry with high probability. for many of these algorithms, matching lower bounds are proved that show that their per-process work is nearly optimal as a function of i, b, or n. the case of n active processes gives an algorithm for anonymous, adaptive consensus that requires only o(n log2 n) per-process work, which is within a constant factor of the best previously known non-adaptive algorithm for a strong adversary. finally, it is shown that standard universal constructions based on consensus continue to work with infinitely many processes with only slight modifications. this shows that in infinite distributed systems, as in finite ones, with randomness all things are possible.
graph problems on a mesh-connected processor array (preliminary version) we give o(n) step algorithms for solving a number of graph problems on an n-&-times;n array of processors. the problems considered include: marking the bridges of an undirected graph, marking the articulation points of such a graph, finding the length of a shortest cycle, finding a minimum spanning tree, and a number of other problems.
a correctness condition for high-performance multiprocessors (extended abstract) hybrid consistency, a new consistency condition for shared memory multiprocessors, attempts to capture the guarantees provided by contemporary high-performance architectures. it combines the expressiveness of strong consistency conditions(e.g., sequential consistency, linearizability) and the efficiency of weak consistency conditions (e.g., pipelined ram, causal memory). memory access operations are classified either strong or weak. a global ordering of strong operations at different processes is guaranteed, but there is very little guarantee on the ordering of weak operations at different processes, except for what is implied by their interleaving with the strong operations. a formal and precise definition of this condition is given. an efficient implementation of hybrid consistency on distributed memory machines is presented. in this implementation, weak opearations are executed instantaneously, while the response time for strong operations is linear in the network delay. (it is proven that this is within a constant factor of the optimal time bounds.) to motivate hybrid consistency it is shown that weakly consistent memories do not support non-cooperative (in particular, non-centralized) algorithms for mutual exclusion.
computing with faulty arrays we present and o(1) slowdown emulation of a fault-free n x n two dimensional mesh with a slack of o(log n log log n) by a faulty mesh of the same size and slack. all components of the faulty mesh, including the memory modules, are assumed to be subject to failure. the faults may occur at any time during the emulation and the system readjusts dynamically.
on bounds on the number of steps to compute functions let f be a partial recursive function defined in terms of other functions g1,...,gn such that f converges if and only if some well defined assertions about the convergency of g1,...,gn hold: then we can find a total function (depending on the number of steps required to compute g1,...,gn) that bounds the step counting function of f almost everywhere f is defined. it is also shown that, in that case, to compute the bound to the step counting function is not much harder than computing the step counting function itself.
on the problem of computational time and complexity of arithmetic functions the time and incremental complexity required to perform two-operand addition using logical circuitry are compared for nonredundant and minimally redundant encodings of the operands. the comparison is extended to multi-operand addition and two-operand multiplication.
improved approximation guarantees for minimum-weight -trees and prize-collecting salesmen. consider a salesperson that must sell some quota of brushes in order to win a trip to hawaii. this salesperson has a map (a weighted graph) in which each city has an attached demand specifying the number of brushes that can be sold in that city. what is the best route to take to sell the quota while traveling the least distance possible? notice that unlike the standard traveling salesman problem, not only do we need to figure out the order in which to visit the cities, but we must decide the more fundamental question: which cities do we want to visit? in this paper we give the first approximation algorithms with poly-logarithmic performance guarantees for this problem, as well as for the slightly more general pctsp problem of balas, and a variation we call the "bank-robber problem" (also called the "orienteering problem" by golden, levi, and vohra). we do this by providing an o(log^2 k) approximation to the k-mst problem which is defined as follows. given an undirected graph on n nodes with non-negative edge weights and an integer k > n, find the tree of least weight that spans k vertices. (if desired, one may specify in the problem a "root vertex" that must be in the tree as well.) our result improves on the previous best bound of o(k^0.5) of ravi et al. and comes quite close to the bound of o(log k) of garg and hochbaum for the special case of points in 2-dimensional euclidean space.
large the price of routing unsplittable flow. the essence of the routing problem in real networks is that the traffic demand from a source to destination must be satisfied by choosing a single path between source and destination. the splittable version of this problem is when demand can be satisfied by many paths, namely a flow from source to destination. the unsplittable, or discrete version of the problem is more realistic yet is more complex from the algorithmic point of view; in some settings optimizing such unsplittable traffic flow is computationally intractable.in this paper, we assume this more realistic unsplittable model, and investigate the "price of anarchy", or deterioration of network performance measured in total traffic latency under the selfish user behavior. we show that for linear edge latency functions the price of anarchy is exactly $2.618 for weighted demand and exactly $2.5 for unweighted demand. these results are easily extended to (weighted or unweighted) atomic "congestion games", where paths are replaced by general subsets. we also show that for polynomials of degree d edge latency functions the price of anarchy is dδ(d). our results hold also for mixed strategies.previous results of roughgarden and tardos showed that for linear edge latency functions the price of anarchy is exactly 4/3 under the assumption that each user controls only a negligible fraction of the overall traffic (this result also holds for the splittable case). note that under the assumption of negligible traffic pure and mixed strategies are equivalent and also splittable and unsplittable models are equivalent.
minimizing the flow time without migration. we consider the classical problem of scheduling jobs in a multiprocessor setting in order to minimize the flow time (total time in the system). the performance of the algorithm, both in offline and online settings, can be significantly improved if we allow preemption, i.e., interrupt a job and later continue its execution, perhaps migrating it to a different machine. preemption is inherent to make a scheduling algorithm efficient. while in the case of a single processor most operating systems can easily handle preemptions, migrating a job to a different machine results in a huge overhead. thus, it is not commonly used in most multiprocessor operating systems. the natural question is whether migration is an inherent component for an efficient scheduling algorithm in either the online or offline setting.leonardi and raz [proceedings of the twenty-ninth annual acm symposium on theory of computing, el paso, tx, 1997, pp. 110--119] showed that the well-known algorithm, shortest remaining processing time (srpt), performs within a logarithmic factor of the optimal offline algorithm. note that srpt must use both preemption and migration to schedule the jobs. it is not known if better approximation factors can be reached and thus srpt, although it is an online algorithm, becomes the best known algorithm in the offline setting. in fact, in the online setting, leonardi and raz showed that no algorithm can achieve a better bound.without migration, no (offline or online) approximations are known. this paper introduces a new algorithm that does not use migration, works online, and is just as effective (in terms of approximation ratio) as the best known offline algorithm that uses migration.
reducing truth-telling online mechanisms to online optimization. we describe a general technique for converting an online algorithm β to a truthtelling mechanism. we require that the original online competitive algorithm has certain "niceness" properties in that actions on future requests are independent of the actual value of requests which were accepted (though these actions will of course depend upon the set of accepted requests). under these conditions, we are able to give an online truthtelling mechanism (where the values of requests are given by bids which may not accurately represent the valuation of the requesters) such that our total profit is within o(ρ + log μ) of the optimum offline profit obtained by an omniscient algorithm (one which knows the true valuations of the users). here ρ is the competitive ratio of β for the optimization version of the problem, and μ is the ratio of the maximum to minimum valuation for a request. in general there is an ω(log μ) lower bound on the ratio of worst-case profit for a truthtelling mechanism when compared to the profit obtained by an omniscient algorithm, so this result is in some sense best possible. in addition, we prove that our construction is resilient against many forms of "cheating" attempts, such as forming coalitions.we demonstrate applications of this result to several problems. we develop online truthtelling mechanisms for online routing and admission control of path or multicast requests, assuming large network capacities. assuming the existance of an algorithm β for the optimization version of the problem, our techniques provide truthtelling mechanisms for general combinatorial auctions. however, designing optimization algorithms may be difficult in general because of online or approximation lower bounds. for the cases described above, we are able to design optimization algorithms β by amortizing the lost benefit from online computation (and from approximation hardness in the case of multicast) against the benefit obtained from accepted requests.we comment that our upper bounds on profit competitiveness imply, as an obvious corollary, similar bound on global efficiency, namely overall well-being of all the users. this contrasts with most other work on truthtelling mechanisms for general online resource allocation, where only efficiency is maximized, and competitiveness can be arbitrarily poor.
competitive distributed file allocation. this paper deals with the file allocation problem [6] concerning the dynamic optimization of communication costs to access data in a distributed environment. we develop a dynamic file re-allocation strategy that adapts on-line to a sequence of read and write requests whose location and relative frequencies are completely unpredictable. this is achieved by replicating the file in response to read requests and migrating the file in response to write requests while paying the associated communications costs, so as to be closer to processors that access it frequently. we develop first explicit deterministic on-line strategy assuming existence of global information about the state of the network; previous (deterministic) solutions were complicated and more expensive. our solution has (optimal) logarithmic competitive ratio. the paper also contains the first explicit deterministic data migration [7] algorithm achieving the best known competitive ratio for this problem. using somewhat different technique, we also develop the first deterministic distributed file allocation algorithm (using only local information) with poly-logarithmic competitive ratio against a globally optimized optimal prescient strategy.
finding euler circuits in logarithmic parallel time a parallel algorithm for finding euler circuits in graphs is presented. its depth is log |e| and it employs |e| processors. the computational model considered is the pram (the shared memory model). this algorithm is a nice example of utilizing another parallel algorithm that does not seem to be closely related to our problem, namely the algorithm for finding the connected components and a spanning forest of an undirected graph.
adaptive routing with end-to-end feedback: distributed learning and geometric approaches. minimal delay routing is a fundamental task in networks. since delays depend on the (potentially unpredictable) traffic distribution, online delay optimization can be quite challenging. while uncertainty about the current network delays may make the current routing choices sub-optimal, the algorithm can nevertheless try to learn the traffic patterns and keep adapting its choice of routing paths so as to perform nearly as well as the best static path. this online shortest path problem is a special case of online linear optimization, a problem in which an online algorithm must choose, in each round, a strategy from some compact set s ⊆ rd so as to try to minimize a linear cost function which is only revealed at the end of the round. kalai and vempala[4] gave an algorithm for such problems in the transparent feedback model, where the entire cost function is revealed at the end of the round. here we present an algorithm for online linear optimization in the more challenging opaque feedback model, in which only the cost of the chosen strategy is revealed at the end of the round. in the special case of shortest paths, opaque feedback corresponds to the notion that in each round the algorithm learns only the end-to-end cost of the chosen path, not the cost of every edge in the network.we also present a second algorithm for online shortest paths, which solves the shortest-path problem using a chain of online decision oracles, one at each node of the graph. this has several advantages over the online linear optimization approach. first, it is effective against an adaptive adversary, whereas our linear optimization algorithm assumes an oblivious adversary. second, even in the case of an oblivious adversary, the second algorithm performs better than the first, as measured by their additive regret.
competitive distributed job scheduling (extended abstract) this paper examines the problem of balancing the job load in a network of processors, and introduces an online algorithm for scheduling a sequence of jobs in a competitive manner. the algorithm is shown to be polylog (n)-competitive according to a strict definition that forces the online algorithm to be competitive even when considering any bounded area of the network and bounded period of time. we also analyze the common greedy feedback-based approach, and provide matching lower and upper bounds (up to a polylogarithmic factor) for the tradeoff between the costs of searches and updates under this approach.
adapting to asynchronous dynamic networks (extended abstract) the computational power of different communication models is a fundamental question in the theory of distributed computation. for example, in the synchronous model messages are assumed to be delivered within one time unit, whereas in the asynchronous model message delays may be arbitrary. another important parameter of the model is the assumptions about the topology. in the dynamic topology model, links are assumed to crash and recover dynamically, but their status is known to the incident node processors. a meaningful computation can be carried out if the topology stabilizes for a sufficiently long period. in this paper we show that the model of asynchronous, dynamic-topology network is equivalent, up to polylogarithmic factors, to the synchronous, static protocols that can withstand arbitrary link delays and changing topology at the expense of only polylogarithmic blowup in the running time, the number of messages, and the space requirement. previous methods entailed a linear blowup in at least one of these resources. the generality of our method is demonstrated by a series of improvements for important applications, including breadth first search, computing compact efficient routing tables, and packet routing on asynchronous networks.
biased random walks how much can an imperfect source of randomness affect an algorithm? we examine several simple questions of this type concerning the long-term behavior of a random walk on a finite graph. in our setup, each step of the random walk a &ldquo;controller&rdquo; can, with a certain small probability, fix the next step, thus introducing a bias. we analyze the extent to which the bias can affect the limit behavior of the walk. the controller is assumed to associate a real, nonnegative, &ldquo;benefit&rdquo; with each state, and to strive to maximize the long-term expected benefit. we derive tight bounds on the maximum of this objective function over all controller's strategies, and present polynomial time algorithms for computing the optimal controller strategy.
balanced allocations (extended abstract). suppose that we sequentially place n balls into n boxes by putting each ball into a randomly chosen box. it is well known that when we are done, the fullest box has with high probability lnn/lnlnn(1 + o(1)) balls in it. suppose instead, that for each ball we choose two boxes at random and place the ball into the one which is less full at the time of placement. we show that with high probability, the fullest box contains only lnlnn/ln2 + o(1) balls - exponentially less than before. furthermore, we show that a similar gap exists in the infinite process, where at each step one ball, chosen uniformly at random, is deleted, and one ball is added in the manner above. we discuss consequences of this and related theorems for dynamic resource allocation, hashing, and on-line load balancing.
optimal oblivious routing in polynomial time. a recent seminal result of räcke is that for any undirected network there is an oblivious routing algorithm with a polylogarithmic competitive ratio with respect to congestion. unfortunately, räcke's construction is not polynomial time. we give a polynomial time construction that guarantees räcke's bounds, and more generally gives the true optimal ratio for any (undirected or directed) network.
convex programming for scheduling unrelated parallel machines. we consider the classical problem of scheduling parallel unrelated machines. each job is to be processed by exactly one machine. processing job j on machine i requires time pij. the goal is to find a schedule that minimizes the lp norm. previous work showed a 2-approximation algorithm for the problem with respect to the l∞ norm. for any fixed lp norm the previously known approximation algorithm has a performance of θ(p). we provide a 2-approximation algorithm for any fixed lp norm (p>1). this algorithm uses convex programming relaxation. we also give a √ 2-approximation algorithm for the l2 norm. this algorithm relies on convex quadratic programming relaxation. to the best of our knowledge, this is the first time that general convex programming techniques (apart from sdps and cqps) are used in the area of scheduling. we show for any given lp norm a ptas for any fixed number of machines. we also consider the multidimensional generalization of the problem in which the jobs are d-dimensional. here the goal is to minimize the lp norm of the generalized load vector, which is a matrix where the rows represent the machines and the columns represent the jobs dimension. for this problem we give a (d+1)-approximation algorithm for any fixed lp norm (p>1).
spectral analysis of data. experimental evidence suggests that spectral techniques are valuable for a wide range of applications. a partial list of such applications include (i) semantic analysis of documents used to cluster documents into areas of interest, (ii) collaborative filtering --- the reconstruction of missing data items, and (iii) determining the relative importance of documents based on citation/link structure. intuitive arguments can explain some of the phenomena that has been observed but little theoretical study has been done. in this paper we present a model for framing data mining tasks and a unified approach to solving the resulting data mining problems using spectral analysis. these results give strong justification to the use of spectral techniques for latent semantic indexing, collaborative filtering, and web site ranking.
management of multi-queue switches in qos networks. the concept of quality of service (qos) networks has gained growing attention recently, as the traffic volume in the internet constantly increases, and qos guarantees are essential to ensure proper operation of most communication based applications. a qos switch serves m incoming queues by transmitting packets arriving at these queues through one output port, one packet per time unit. each packet is marked with a value indicating its guaranteed quality of service. since the queues have bounded capacity and the rate of arriving packets can be much higher than the transmission rate, packets can be lost due to insufficient queue space. the goal is to maximize the total value of transmitted packets. this problem encapsulates two dependent questions: admission control, namely which packets to discard in case of queue overflow, and scheduling, i.e. which queue to use for transmission in each time unit. we use competitive analysis to study online switch performance in qos based networks. specifically, we provide a novel generic technique that decouples the admission control and scheduling problems. our technique transforms any single queue admission control strategy (preemptive or nonpreemptive) to a scheduling and admission control algorithm for our general m queues model, whose competitive ratio is at most twice the competitive ratio of the given admission control strategy. we use our technique to derive concrete algorithms for the general preemptive and nonpreemptive cases, as well as for the interesting special cases of the 2-value model and the unit value model. to the best of our knowledge this is the first result combining both scheduling and admission control decisions for arbitrary packets sequences in multi-queue switches. we also provide a 1.58-competitive randomized algorithm for the unit value case. this case is interesting by itself since most current networks (e.g. ip networks) only support a best-effort service in which all packets streams are treated equally.
the zero-one principle for switching networks. recently, approximation analysis has been extensively used to study algorithms for routing weighted packets in various network settings. although different techniques were applied in the analysis of diverse models, one common property was evident: the analysis of input sequences composed solely of two different values is always substantially easier, and many results are known only for restricted value sequences. motivated by this, we introduce our zero-one principle for switching networks which characterizes a wide range of algorithms for which achieving c-approximation (as well as c-competitiveness) with respect to sequences composed of 0's and 1's implies achieving c-approximation. the zero-one principle proves to be very efficient in the design of switching algorithms, and substantially facilitates their analysis. we present three applications. first, we consider the multi-queue qos switching model and design a 3-competitive algorithm, improving the result from [6]. second, we study the weighted dynamic routing problem on a line topology of length k and present a (k+1)-competitive algorithm, which improves and generalizes the results from [1,12]. as a third application, we consider the work of [11], that compares the performance of local algorithms to the global optimum in various network topologies, and generalize their results from 2-value sequences to arbitrary value sequences.
trading group theory for randomness in a previous paper [bs] we proved, using the elements of the theory of nilpotent groups, that some of the fundamental computational problems in matriz groups belong to np. these problems were also shown to belong to conp, assuming an unproven hypothesis concerning finite simple groups. the aim of this paper is to replace most of the (proven and unproven) group theory of [bs] by elementary combinatorial arguments. the result we prove is that relative to a random oracle b, the mentioned matrix group problems belong to (np&cap;conp)b. the problems we consider are membership in and order of a matrix group given by a list of generators. these problems can be viewed as multidimensional versions of a close relative of the discrete logarithm problem. hence np&cap;conp might be the lowest natural complexity class they may fit in. we remark that the results remain valid for black box groups where group operations are performed by an oracle. the tools we introduce seem interesting in their own right. we define a new hierarchy of complexity classes am(k) &ldquo;just above np&rdquo;, introducing arthur vs. merlin games, the bounded-away version of papdimitriou's games against nature. we prove that in spite of their analogy with the polynomial time hierarchy, the finite levels of this hierarchy collapse to am=am(2). using a combinatorial lemma on finite groups [be], we construct a game by which the nondeterministic player (merlin) is able to convince the random player (arthur) about the relation [g]=n provided arthur trusts conclusions based on statistical evidence (such as a slowly-strassen type &ldquo;proof&rdquo; of primality). one can prove that am consists precisely of those languages which belong to npb for almost every oracle b. our hierarchy has an interesting, still unclarified relation to another hierarchy, obtained by removing the central ingredient from the user vs. expert games of goldwasser, micali and rackoff.
isomorphism of graphs with bounded eigenvalue multiplicity we investigate the connection between the spectrum of a graph, i.e. the eigenvalues of the adjacency matrix, and the complexity of testing isomorphism. in particular we describe two polynomial time algorithms which test isomorphism of undirected graphs whose eigenvalues have bounded multiplicity. if x and y are graphs of eigenvalue multiplicity m, then the isomorphism of x and y can be tested by an o(n4m+c) deterministic and by an o(n2m+c) las vegas algorithm, where n is the number of vertices of x and y.
canonical labeling of graphs we announce an algebraic approach to the problem of assigning canonical forms to graphs. we compute canonical forms and the associated canonical labelings (or renumberings) in polynomial time for graphs of bounded valence, in moderately exponential, exp(n&frac12; + &ogr;(1)),time for general graphs, in subexponential, nlog n, time for tournaments and for 2-(&ngr;,&kgr;,&lgr;) block designs with &kgr;,&lgr; bounded and nlog log n time for &lgr;-planes (symmetric designs) with &lgr; bounded. we prove some related problems np-hard and indicate some open problems.
permutation groups in nc we show that the basic problems of permutation group manipulation admit efficient parallel solutions. given a permutation group g by a list of generators, we find a set of nc-efficient strong generators in nc. using this, we show, that the following problems are in nc: membership in g; determining the order of g; finding the center of g; finding a composition series of g along with permutation representations of each composition factor. moreover, given g, we are able to find the pointwise stabilizer of a set in nc. one consequence is that isomorphism of graphs with bounded multiplicity of eigenvalues is in nc. the analysis of the algorithms depends, in several ways, on consequences of the classification of finite simple groups.
fast algorithms under the extended riemann hypothesis: a concrete estimate several results in theoretical computer science use the following theorem: for a positive integer q, let z-&-bull;q denote the multiplicative group of all integers x, 0-&-lt;x-&-lt;q, that are relatively prime to q. let g be a proper subgroup of z-&-bull;q. then, assuming the extended riemann hypothesis, there is a constant c such that if q is sufficiently large, z-&-bull;q-&-minus;g contains a positive integer n-&-le;c (logeq)2. we show that for q-&-ge;106, one may take c-&-equil;60. as an application, we discuss a deterministic polynomial-time primality test. miller proved that such algorithms must exist if the erh is true, but we are unable to specify one without the concrete information given above. we eliminate this difficulty, and show how to implement a fast primality test.
how to generate random integers with known factorization recent work in public-key cryptography has led to the need to generate large random numbers with known factorization. this paper describes a probabilistic algorithm that produces a random k-bit integer in factored form. each such number is equally likely to appear. the expected running time is, up to a constant factor, that required for k prime tests on k-bit integers. thus, under reasonable assumptions about the speed of primality testing, it is a polynomial time process.
realistic analysis of some randomized algorithms many problems such as primality testing can be solved efficiently using a source of independent, identically distributed random numbers. it is therefore customary in the theory of algorithms to assume the availability of such a source. however, probabilistic algorithms often work well in practice with pseudo-random numbers; the point of this paper is to offer a justification for this fact. the results below apply to sequences generated by iteratively applying functions of the form &fnof; (&khgr;) = &agr;&khgr; + &bgr; (mod p) to a randomly chosen seed x, and estimate the probability that a predetermined number of trials of an algorithm will fail. in particular, the following bounds hold: for finding square roots modulo a prime p, a failure probability of &ogr; (log p/&radic;p). for testing p for primality, a failure probability of &ogr; (p-1/4+&egr;), for any &egr;>0. (in both cases, the number of trials is about 1/2 log p.) the analysis uses results of andr&eacute; weil concerning the number of points on algebraic varieties over finite fields.
average case analysis for batched disk scheduling and increasing subsequences. (math) we consider the problem of estimating the tour length and finding approximation algorithms for the asymmetric traveling salesman problem arising from the disk scheduling problem. given n requests, we show that if the seek function has positive derivative at 0 the tour length is concentrated in probability around the value cf,pn1/2 for an explicit constant cf,p dependent on the seek function and the distribution of requests. for linear seek function we provide even tighter bounds and provide an o(nlog(n)) time algorithm for finding the optimal tour. the proof uses several results on the size and location of maximal increasing subsequences. to handle more general seek functions we introduce a more general concept of increasing subsequences. we provide order of magnitude estimates on the tour length for a wide class of seek functions with vanishing derivative at 0. for general seek functions we use some geometric information on the location of maximal generalized increasing subsequences obtained via talagrand's isoperimetric inequalities to produce a probabilistic 1+&egr; approximation algorithm. these results complement the results on guaranteed approximation algorithms for this problem presented in [2].
low-distortion embeddings of general metrics into the line. a low-distortion embedding between two metric spaces is a mapping which preserves the distances between each pair of points, up to a small factor called distortion. low-distortion embeddings have recently found numerous applications in computer science.most of the known embedding results are "absolute",that is, of the form: any metric y from a given class of metrics c can be embedded into a metric x with low distortion c. this is beneficial if one can guarantee low distortion for all metrics y in c. however, in any situations, the worst-case distortion is too large to be meaningful. for example, if x is a line metric, then even very simple metrics (an n - point star or an n -point cycle) are embeddable into x only with distortion linear in n. nevertheless, embeddings into the line (or into low-dimensional spaces) are important for many applications.a solution to this issue is to consider "relative" (or "approximation") embedding problems, where the goal is to design an (a-approxiation) algorithm which, given any metric x from c as an input, finds an embedding of x into y which has distortion a *cy (x), where cy (x)is the best possible distortion of an embedding of x into y.in this paper we show algorithms and hardness results for relative embedding problems.in particular we give: •an algorith that, given a general metric m, finds an embedding with distortion o (δ3⁄4 poly(c line (m))), where δ is the spread of m•an algorithm that,given a weighted tree etric m, finds an embedding with distortion poly(c line (m)) •a hardness result, showing that computing minimum line distortion is hard to approximate up to a factor polynomial in n,even for weighted tree metrics with spread δ=n o (1).
approximate clustering via core-sets. in this paper, we show that for several clustering problems one can extract a small set of points, so that using those core-sets enable us to perform approximate clustering efficiently. the surprising property of those core-sets is that their size is independent of the dimension.using those, we present a (1+ &egr;)-approximation algorithms for the k-center clustering and k-median clustering problems in euclidean space. the running time of the new algorithms has linear or near linear dependency on the number of points and the dimension, and exponential dependency on 1/&egr; and k. as such, our results are a substantial improvement over what was previously known.we also present some other clustering results including (1+ &egr;)-approximate 1-cylinder clustering, and k-center clustering with outliers.
tree transductions and families of tree languges interest in the study of sets of trees, tree languages, has led to the definition of finite automata which accept trees [2,11] and transducers which map trees into other trees [7,9,10]. these generalized machines may read treesfinite automata which accept trees [2,11] and of transducers which map trees into other trees [7,9,10]. these generalized machines may read trees either &ldquo;top-down&rdquo; (from the root toward the leaves) or &ldquo;bottom-up&rdquo; (from the leaves toward the root). here it is shown that both the class of top-down transductions and the class of bottom-up transductions can be characterized in terms of two restricted classes of tree transductions. from these ductions and the class of bottom-up transductions can be characterized in terms of two restricted classes of tree transductions. from these characterizations, it is shown that the composition of any n bottom-up transductions can be realized by the composition of n+1 top-down transductions, and similarly, the composition of any n top-down transductions can be realized by the composition of n+1 bottom-up transductions. next, we study the families of tree languages which can be obtained from the recognizable sets (sets accepted by finite tree automata) by the composition of n top-down or bottom-up transductions, n>0. the yield operation, which concatenates the leaves of a tree from left to right to form a of string, languages from the hierarchy of families of tree languages. it is shown that each family of string languages in this hierarchy is properly contained in the family of context-sensitive languages.
stable prehension with three fingers we study grasps by a robot hand in the absence of friction. in two dimensions, a hand with three spring-loaded fingers and five degrees of freedom can achieve an equilibrium grasp on any object described by a polygon. furthermore, the grasp is stable, that is, at a local minimum of the potential energy function defined by the springs of the fingers. in three dimensions, the hand can grasp any cylinder. in contrast, if the degrees of freedom of the hand are restricted to correspond to a hand built by hanafusa and asada, stable grips on a polygon cannot in general be achieved.
approximation algorithms for deadline-tsp and vehicle routing with time-windows. given a metric space g on n nodes, with a start node r and deadlines d(v) for each vertex v, we consider the deadline-tsp problem of finding a path starting at r that visits as many nodes as possible by their deadlines. we also consider the more general vehicle routing with time-windows problem, in which each node v also has a release-time r(v) and the goal is to visit as many nodes as possible within their "time-windows" [r(v),d(v)]. no good approximations were known previously for these problems on general metric spaces. we give an o(logn) approximation algorithm for deadline-tsp, and extend this algorithm to an o(log2n) approximation for the time-window problem. we also give a bicriteria approximation algorithm for both problems: given an ε>0, our algorithm produces a (1/ε) approximation, while exceeding the deadlines by a factor of 1+ε. we use as a subroutine for these results a constant-factor approximation that we develop for a generalization of the orienteering problem in which both the start and the end nodes of the path are fixed. in the process, we give a 3-approximation to the orienteering problem, improving on the previously best known 4-approximation of [6].
a quasi-ptas for unsplittable flow on line graphs. we study the unsplittable flow problem (ufp) on line graphs and cycles, focusing on the long-standing open question of whether the problem is apx-hard. we describe a deterministic quasi-polynomial time approximation scheme for ufp on line graphs, thereby ruling out an apx-hardness result, unless np ⊆ dtime(2polylog(n)). our result requires a quasi-polynomial bound on all edge capacities and demands in the input instance. we extend this result to undirected cycle graphs.earlier results on this problem included a polynomial time (2+ε)-approximation under the assumption that no demand exceeds any edge capacity (the "no-bottleneck assumption") and a super-constant integrality gap if this assumption did not hold. unlike most earlier work on ufp, our results do not require a no-bottleneck assumption.
server scheduling in the l norm: a rising tide lifts all boat. often server systems do not implement the best known algorithms for optimizing average quality of service (qos) out of concern of that these algorithms may be insufficiently fair to individual jobs. the standard method for balancing average qos and fairness is optimize the lp metric, 1 < p < ∞. thus we consider server scheduling strategies to optimize the lp norms of the standard qos measures, flow and stretch. we first show that there is no no(1)-competitive online algorithm for the lp norms of either flow or stretch. we then show that the standard clairvoyant algorithms for optimizing average qos, sjf and srpt, are o(1+ε)-speed o(1/ε)-competitive for the lp norms of flow and stretch. and that the standard nonclairvoyant algorithm for optimizing average qos, setf, is o(1+ε)-speed o(1/ε(2+2/p))-competitive for the lp norms of flow. these results argue that these standard algorithms will not starve jobs until the system is near peak capacity. in contrast, we show that the round robin, or processor sharing algorithm, which is sometimes adopted because of its seeming fairness properties, is not o(1+ε)-speed no(1)-competitive for sufficiently small ε.
the santa claus problem. we consider the following problem: the santa claus has n presents that he wants to distribute among m kids. each kid has an arbitrary value for each present. let pij be the value that kid i has for present j. the santa's goal is to distribute presents in such a way that the least lucky kid is as happy as possible, i.e he tries to maximize mini=1,...,m sumj ∈ si pij where si is a set of presents received by the i-th kid.our main result is an o(log log m/log log log m) approximation algorithm for the restricted assignment case of the problem when pij ∈ pj,0 (i.e. when present j has either value pj or 0 for each kid). our algorithm is based on rounding a certain natural exponentially large linear programming relaxation usually referred to as the configuration lp. we also show that the configuration lp has an integrality gap of ω(m1/2) in the general case, when pij can be arbitrary.
a unified approach to approximating resource allocation and scheduling. we present a general framework for solving resource allocation and scheduling problems. given a resource of fixed size, we present algorithms that approximate the maximum throughput or the minimum loss by a constant factor. our approximation factors apply to many problems, among which are: (i) real-time scheduling of jobs on parallel machines, (ii) bandwidth allocation for sessions between two endpoints, (iii) general caching, (iv) dynamic storage allocation, and (v) bandwidth allocation on optical line and ring topologies. for some of these problems we provide the first constant factor approximation algorithm. our algorithms are simple and efficient and are based on the local-ratio technique. we note that they can equivalently be interpreted within the primal-dual schema.
bandwidth allocation with preemption. bandwidth allocation is a fundamental problem in the design of networks where bandwidth has to be reserved for connections in advance. the problem is intensified when the requested bandwidth exceeds the capacity and not all requests can be served. furthermore, acceptance/rejection decisions regarding connections have to be made on-line, without knowledge of future requests. we show that the ability to preempt (i.e., abort) connections while in service in order to be able to schedule ``more valuable'''' connections substantially improves the overall throughput of some networks. we present bandwidth allocation strategies that use preemption and show that they achieve constant competiveness with respect to the throughput, given that any single call occupies only a constant fraction of the bandwidth. our results should be contrasted with recent works showing that nonpreemptive strategies have at most logarithmic competitiveness.
on approximating a vertex cover for planar graphs the approximation problem for vertex cover of n-vertex planar graphs is treated. two results are presented: (1) a linear time approximation algorithm for which the (error) performance bound is 2/3. (2) an o(n log n) time approximation scheme.
sampling lower bounds via information theory. we present a novel technique, based on the jensen-shannon divergence from information theory, to prove lower bounds on the query complexity of sampling algorithms that approximate functions over arbitrary domain and range. unlike previous methods, our technique does not use a reduction from a decision promise problem. as a result, it gives stronger bounds for functions that possess a large set of inputs, each two of which exhibit a gap in the function value.we demonstrate the technique with new query complexity lower bounds for three fundamental problems: (1) the "election problem", for which we obtain a quadratic improvement over previous bounds, (2) low rank matrix approximation, for which we prove the first lower bounds, showing that the algorithms given for this problem are almost optimal, and (3) matrix reconstruction.in addition, we introduce a new method for proving lower bounds on the expected query complexity of functions, using the kullback-leibler divergence. we demonstrate its use by a simple query complexity lower bound for the mean.
exponential separation of quantum and classical one-way communication complexity. we give the first exponential separation between quantum and bounded-error randomized one-way communication complexity. specifically, we define the hidden matching problem hmn: alice gets as input a string x ∈ (0, 1)n and bob gets a perfect matching m on the n coordinates. bob's goal is to output a tuple [i,j,b] such that the edge (i,j) belongs to the matching m and b = xi ⊕ xj. we prove that the quantum one-way communication complexity of hmn is o(log n), yet any randomized one-way protocol with bounded error must use ω(√n) bits of communication. no asymptotic gap for one-way communication was previously known. our bounds also hold in the model of simultaneous messages (sm) and hence we provide the first exponential separation between quantum sm and randomized sm with public coins.for a boolean decision version of hmn, we show that the quantum one-way communication complexity remains o(log n) and that the 0-error randomized one-way communication complexity is ω(n). we prove that any randomized linear one-way protocol with bounded error for this problem requires ω(√[3] n log n) bits of communication.
sampling algorithms: lower bounds and applications. we develop a framework to study probabilistic sampling algorithms that approximate general functions of the form \genfunc, where \domain and \range are arbitrary sets. our goal is to obtain lower bounds on the query complexity of functions, namely the number of input variables x_i that any sampling algorithm needs to query to approximate f(x_1,\ldots,x_n).we define two quantitative properties of functions --- the it block sensitivity and the minimum hellinger distance --- that give us techniques to prove lower bounds on the query complexity. these techniques are quite general, easy to use, yet powerful enough to yield tight results. our applications include the mean and higher statistical moments, the median and other selection functions, and the frequency moments, where we obtain lower bounds that are close to the corresponding upper bounds.we also point out some connections between sampling and streaming algorithms and lossy compression schemes.
simulating independence: new constructions of condensers, ramsey graphs, dispersers, and extractors. a distribution x over binary strings of length n has min-entropy k if every string has probability at most 2-k in x. we say that x is a δ-source if its rate k⁄n is at least δ.we give the following new explicit instructions (namely, poly(n)- time computable functions) of deterministicextractors, dispersers and related objects. all work for any fixed rate δ>0. no previous explicit construction was known for either of these, for any δ‹1⁄2. the first two constitute major progress to very long-standing open problems. bipartite ramsey f1: (0,1)n)2 →0,1, such that for any two independent δ-sources x1, x2 we have f1(x1,x2) = 0,1 this implies a new explicit construction of 2n-vertex bipartite graphs where no induced nδ by nδ subgraph is complete or empty. multiple source extraction f2: (0,1n)3→0,1 such that for any three independent δ-sources x1,x2,x3 we have that f2(x1,x2,x3) is (o(1)-close to being) an unbiased random bit. constant seed condenser2 f3: n →(0,1m)c, such that for any δ-source x, one of the c output distributions f3(x)i, is a 0.9-source over 0,1m. here c is a constant depending only on δ.subspace ramsey f4: 0,1n→0,1 such that for any affine-δ-source3 x we have f4(x)= 0,1.the constructions are quite involved and use as building blocks other new and known gadgets. but we can point out two important themes which recur in these constructions. one is that gadgets which were designed to work with independent inputs, sometimes perform well enough with correlated, high entropy inputs. the second is using the input to (introspectively) find high entropy regions within itself.
strict polynomial-time in simulation and extraction. the notion of efficient computation is usually identified in cryptography and complexity with (strict) probabilistic polynomial-time. however, until recently, in order to obtain \emph{constant-round} zero-knowledge proofs and proofs of knowledge, one had to allow simulators and knowledge extractors to run in time that is only polynomial on the average (i.e., expected polynomial-time). recently barak gave the first constant-round zero-knowledge argument with a strict (in contrast to expected) polynomial-time simulator. the simulator in his protocol is a nonblack-box simulator (i.e., it makes inherent use of the description of the code of the verifier).in this paper, we further address the question of strict polynomial-time in constant-round zero-knowledge proofs and arguments of knowledge. first, we show that there exists a constant-round zero-knowledge argument of knowledge with a strict polynomial-time knowledge extractor. as in the simulator of barak's zero-knowledge protocol, the extractor for our argument of knowledge is not black-box and makes inherent use of the code of the prover. on the negative side, we show that nonblack-box techniques are essential for both strict polynomial-time simulation and extraction. that is, we show that no (nontrivial) constant-round zero-knowledge proof or argument can have a strict polynomial-time black-box simulator. similarly, we show that no (nontrivial) constant-round zero-knowledge proof or argument of knowledge can have a strict polynomial-time black-box knowledge extractor.
2-source dispersers for sub-polynomial entropy and ramsey graphs beating the frankl-wilson construction. the main result of this paper is an explicit disperser for two independent sources on n bits, each of entropy k=no(1). put differently, setting n=2n and k=2k, we construct explicit n x n boolean matrices for which no k x k submatrix is monochromatic. viewed as adjacency matrices of bipartite graphs, this gives an explicit construction of k-ramsey bipartite graphs of size n.this greatly improves the previous bound of k=o(n) of barak, kindler, shaltiel, sudakov and wigderson [4]. it also significantly improves the 25-year record of k = õ (√n) on the special case of ramsey graphs, due to frankl and wilson [9].the construction uses (besides "classical" extractor ideas) almost all of the machinery developed in the last couple of years for extraction from independent sources, including:bourgain's extractor for 2 independent sources of some entropy rate < 1/2 [5]raz's extractor for 2 independent sources, one of which has any entropy rate > 1/2 [18]rao's extractor for 2 independent block-sources of entropy nω (1) [17]the "challenge-response" mechanism for detecting "entropy concentration" of [4].the main novelty comes in a bootstrap procedure which allows the challenge-response mechanism of [4] to be used with sources of less and less entropy, using recursive calls to itself. subtleties arise since the success of this mechanism depends on restricting the given sources, and so recursion constantly changes the original sources. these are resolved via a new construct, in between a disperser and an extractor, which behaves like an extractor on sufficiently large subsources of the given ones.this version is only an extended abstract, please see the full version, available on the authors' homepages, for more details.
short random walks on graphs. the short-term behavior of random walks on graphs is studied, in particular, the rate at which a random walk discovers new vertices and edges. a conjecture by linial that the expected time to find $\cal n$ distinct vertices is $o({\cal n}^{3})$ is proved. in addition, upper bounds of $o({\cal m}^{2})$ on the expected time to traverse $\cal m$ edges and of $o(\cal m \cal n)$ on the expected time to either visit $\cal n$ vertices or traverse $\cal m$ edges (whichever comes first) are proved.
now you may compose temporal logic specifications a compositional temporal logic proof system for the specification and verification of concurrent programs is presented. versions of the system are developed for shared variables and communication based programming languages that include procedures.
finite monoids and the fine structure of nc¹ recently a new connection was discovered between the parallel complexity class nc1 and the theory of finite automata in the work of barrington on bounded width branching programs. there (nonuniform) nc1 was characterized as those languages recognized by a certain nonuniform version of a dfa. here we extend this characterization to show that the internal structures of nc1 and the class of automata are closely related. in particular, using th&eacute;rien's classification of finite monoids, we give new characterizations of the classes ac0, depth-k ac0, and acc, the last being the ac0 closure of the mod q functions for all constant q. we settle some of the open questions in [3], give a new proof that the dot-depth hierarchy of algebraic automata theory is infinite [8], and offer a new framework for understanding the internal structure of nc1.
approximating min-sum -clustering in metric spaces. the min-sum k-clustering problem in a metric space is to find a partition of the space into k clusters as to minimize the total sum of distances between pairs of points assigned to the same cluster. we give the first polynomial time non-trivial approximation algorithm for this problem. the algorithm provides an $\ratio$ approximation to the min-sum k-clustering problem in general metric spaces, with running time $\runtime$. the result is based on embedding of metric spaces into hierarchically separated trees. we also provide a bicriteria approximation result that provides a constant approximation factor solution with only a constant factor increase in the number of clusters. this result is obtained by modifying and drawing ideas from recently developed primal dual approximation algorithms for facility location.
new algorithms for an ancient scheduling problem we consider the on-line version of the original m-machine scheduling problem: given m machines and n positive real jobs, schedule the n jobs on the m machines so as to minimize the makespan, the completion time of the last job. in the on-line version, as soon as job j arrrives, it must be assigned immediately to one of the m machines. we present two main results. the first is a (2&ndash;&egr;)-competitive deterministic algorithm for all m. the competitive ratio of all previous algorithms approaches 2 as m&rarr; &infin; . indeed, the problem of improving the competitive ratio for large m had been open since 1966, when the first algorithm for this problem appeared. the second result is an optimal randomized algorithm for the case m = 2. to the best of our knowledge, our 4/3-competitive algorithm is the first specifically randomized algorithm for the original, m-machine, on-line scheduling problem.
lower bounds for on-line graph problems with application to on-line circuit and optical routing. we present lower bounds on the competitive ratio of randomized algorithms for a wide class of on-line graph optimization problems, and we apply such results to on-line virtual circuit and optical routing problems. lund and yannakakis [the approximation of maximum subgraph problems, in proceedings of the 20th international colloquium on automata, languages and programming, 1993, pp. 40-51] give inapproximability results for the problem of finding the largest vertex induced subgraph satisfying any nontrivial, hereditary property pi--e.g., independent set, planar, acyclic, bipartite. we consider the on-line version of this family of problems, where some graph g is fixed and some subgraph h of g is presented on-line, vertex by vertex. the on-line algorithm must choose a subset of the vertices of h, choosing or rejecting a vertex when it is presented, whose vertex induced subgraph satisfies property pi. furthermore, we study the on-line version of graph coloring whose off-line version has also been shown to be inapproximable [c. lund and m. yannakakis, on the hardness of approximating minimization problems, in proceedings of the 25th acm symposium on theory of computing, 1993], on-line max edge-disjoint paths, and on-line path coloring problems. irrespective of the time complexity, we show an omega(nepsilon) lower bound on the competitive ratio of randomized on-line algorithms for any of these problems. as a consequence, we obtain an omega(nepsilon) lower bound on the competitive ratio of randomized on-line algorithms for virtual circuit routing on general networks, in contrast to the known results for some specific networks. similar lower bounds are obtained for on-line optical routing as well.
competitive algorithms for distributed data management (extended abstract) we deal with the competitive analysis of algorithms for managing data in a distributed environment. we deal with the file allocation problem ([c], [df], [ml]), where copies of a file may be stored in the local storage of some subset of processors, copies may be replicated and discarded over time so as to optimize communication costs, but multiple copies must be kept consistent and at least one copy must be stored somewhere in the network at all times. we deal with competitive algorithms for minimizing communication costs, over arbitrary sequences of reads and writes, and arbitrary network topologies. we define the constrained file allocation problem to be the solution of many individual file allocation problems simultaneously, subject to the constraints of local memory size. we give competitive algorithms for this prblem on uniform networks. we then introduce distributed competitive algorithms for on-line data tracking (a generalization of mobile user tracking [ap1, ap3] to transform our competitive distributed data management algorithms into distributed algorithms themselves.
on metric ramsey-type phenomena. this paper deals with ramsey-type theorems for metric spaces. such a theorem states that every n point metric space contains a large subspace which can be embedded with some fixed distortion in a metric space from some special class.our main theorem states that for any ε>0, every n point metric space contains a subspace of size at least n1-ε which is embeddable in an ultrametric with o(log(1/ε)/ε distortion. this in particular provides a bound for embedding in euclidean spaces. the bound on the distortion is tight up to the log(1/ε) factor even for embedding in arbitrary euclidean spaces. this result can be viewed as a non-linear analog of dvoretzky's theorem, a cornerstone of modern banach space theory and convex geometry.our main ramsey-type theorem and techniques naturally extend to give theorems for classes of hierarchically well-separated trees which have algorithmic implications, and can be viewed as the solution of a natural clustering problem.we further include a comprehensive study of various other aspects of the metric ramsey problem.
feasibility testing for systems of real quadratic equations we consider the problem of deciding whether a given system of quadratic homogeneous equations over the reals has non-trivial solution. we design an approximative algorithm whose complexity is polynomial in the number of variables and exponential in the number of equations. some applications to general systems of polynomial equations and inequalities over the reals are discussed.
a sublinear algorithm for weakly approximating edit distance. we show how to determine whether the edit distance between two given strings is small in sublinear time. specifically, we present a test which, given two n-character strings a and b, runs in time o(n) and with high probability returns "close" if their edit distance is o(nα), and "far" if their edit distance is ω(n), where α is a fixed parameter less than 1. our algorithm for testing the edit distance works by recursively subdividing the strings a and b into smaller substrings and looking for pairs of substrings in a, b with small edit distance. to do this, we query both strings at random places using a special technique for economizing on the samples which does not pick the samples independently and provides better query and overall complexity. as a result, our test runs in time õ(nmax(α/2, 2α - 1\)) for any fixed α < 1. our algorithm thus provides a trade-off between accuracy and efficiency that is particularly useful when the input data is very large.we also show a lower bound of ω(nα/2) on the query complexity of every algorithm that distinguishes pairs of strings with edit distance at most nα from those with edit distance at least n/6.
polynomial time algorithm for computing the top betti numbers of semi-algebraic sets defined by quadratic inequalities. for any fixed l > 0, we present an algorithm which takes as input a semi-algebraic set, s, defined by p1 ≥ 0,...,ps ≥ 0, where each pi ∈ r[x1,...,xk] has degree ≤ 2, and computes the top l betti numbers of s, bk-1(s), ..., bk-l(s), in polynomial time. the complexity of the algorithm, stated more precisely, is σi=0l+2 (si k2o((l,s)). for fixed l, the complexity of the algorithm can be expressed as sl+2 k2o(l), which is polynomial in the input parameters s and k. to our knowledge this is the first polynomial time algorithm for computing non-trivial topological invariants of semi-algebraic sets in rk defined by polynomial inequalities, where the number of inequalities is not fixed and the polynomials are allowed to have degree greater than one. for fixed s, we obtain by letting l = k, an algorithm for computing all the betti numbers of s whose complexity is k2o(s)
sublinear algorithms for testing monotone and unimodal distributions. the complexity of testing properties of monotone and unimodal distributions, when given access only to samples of the distribution, is investigated. two kinds of sublinear-time algorithms---those for testing monotonicity and those that take advantage of monotonicity---are provided. the first algorithm tests if a given distribution on [n] is monotone or far away from any monotone distribution in l1-norm; this algorithm uses o(√n) samples and is shown to be nearly optimal. the next algorithm, given a joint distribution on [n] x [n], tests if it is monotone or is far away from any monotone distribution in l1-norm; this algorithm uses o(n3/2) samples. the problems of testing if two monotone distributions are close in l1-norm and if two random variables with a monotone joint distribution are close to being independent in l1-norm are also considered. algorithms for these problems that use only poly(log n) samples are presented. the closeness and independence testing algorithms for monotone distributions are significantly more efficient than the corresponding algorithms as well as the lower bounds for arbitrary distributions. some of the above results are also extended to unimodal distributions.
on classes of computable functions the complexity closure of a computable function is defined by a set of axioms. the axioms are satisfied by complexity classes that are computation time closed and also by other complexity classes which do not have this property. it is then shown that there exist honest recursive functions whose complexity closure are setwise incomparable. further that there exist chains of honest recursive functions whose complexity closures are densely ordered under set inclusion.
an analysis of the full alpha-beta pruning algorithm an analysis of the alpha-beta pruning algorithm is presented which takes into account both shallow and deep cut-offs. a formula is first developed to measure the average number of terminal nodes examined by the algorithm in a uniform free of degree n and depth d when ties are allowed among the bottom positions: specifically, all bottom values are assumed to be independent identically distributed random variables drawn from a discrete probability distribution. a worst case analysis over all possible probability distributions is then presented by considering the limiting case when the discrete probability distribution tends to a continuous probability distribution. the branching factor of the alpha-beta pruning algorithm is shown to grow with n as &thgr;(n/in n), therefore confirming a claim by knuth and moore that deep cut-offs only have a second order effect on the behavior of the algorithm.
computing the first betti number and the connected components of semi-algebraic sets. in this paper we describe the first singly exponential algorithm for computing the first betti number of a given semi-algebraic set. we also describe algorithms for obtaining semi-algebraic descriptions of the semi-algebraically connected components of any given real algebraic or semi-algebraic set. singly exponential algorithms for computing the zero-th betti number, and the euler-poincaré characteristic, were known before. no singly exponential algorithm was known for computing any of the individual betti numbers other than the zero-th one.
improved decremental algorithms for maintaining transitive closure and all-pairs shortest paths. this paper presents improved algorithms for the following problem: given an unweighted directed graph g(v,e) and a sequence of on-line shortest-path/reachability queries interspersed with edge-deletions, develop a data-structure that can answer each query in optimal time, and can be updated efficiently after each edge-deletion. the central idea underlying our algorithms is a scheme for implicitly storing all-pairs reachability/shortest-path information, and an efficient way to maintain this information. our algorithms are randomized and have one-sided inverse polynomial error for query.
angles of planar triangular graphs. we give a characterization of all the planar drawings of a triangular graph through a system of equations and inequalities relating its angles; we also discuss minimality properties of the characterization. the characterization can be used: (1) to decide in linear time whether a given distribution of angles between the edges of a planar triangular graph can result in a planar drawing; (2) to reduce the problem of maximizing the minimum angle in a planar straight-line drawing of a planar triangular graph to a nonlinear optimization problem purely on a space of angles; (3) to give a characterization of the planar drawings of a triconnected graph through a system of equations and inequalities relating its angles; (4) to give a characterization of delaunay triangulations through a system of equations and inequalities relating its angles; (5) to give a characterization of all the planar drawings of a triangular graph through a system of equations and inequalities relating the lengths of its edges; in turn, this result allows us to give a new characterization of the disc-packing representations of planar triangular graphs.
a general sequential time-space tradeoff for finding unique elements an optimal &ohgr;(n2) lower bound is shown for the time-space product of any r-way branching program that determines those values which occur exactly once in a list of n integers in the range [1, r] where r &ge; n. this &ohgr;(n2) tradeoff also applies to the sorting problem and thus improves the previous time-space tradeoffs for sorting. because the r-way branching program is a such a powerful model these time-space product tradeoffs also apply to all models of sequential computation that have a fair measure of space such as off-line multi-tape turing machines and off-line log-cost rams.
the complexity of approximating entropy. (math) we consider the problem of approximating the entropy of a discrete distribution under several models. if the distribution is given explicitly as an array where the i-th location is the probability of the i-th element, then linear time is both necessary and sufficient for approximating the entropy.we consider a model in which the algorithm is given access only to independent samples from the distribution. here, we show that a &lgr;-multiplicative approximation to the entropy can be obtained in o(n(1+&eta;)/&lgr;2 < poly(log n)) time for distributions with entropy &omega;(&lgr; &eta;), where n is the size of the domain of the distribution and &eta; is an arbitrarily small positive constant. we show that one cannot get a multiplicative approximation to the entropy in general in this model. even for the class of distributions to which our upper bound applies, we obtain a lower bound of &omega;(nmax(1/(2&lgr;2), 2/(5&lgr;2&mdash;2)).we next consider a hybrid model in which both the explicit distribution as well as independent samples are available. here, significantly more efficient algorithms can be achieved: a &lgr;-multiplicative approximation to the entropy can be obtained in o(&lgr;2.finally, we consider two special families of distributions: those for which the probability of an element decreases monotonically in the label of the element, and those that are uniform over a subset of the domain. in each case, we give more efficient algorithms for approximating the entropy.
optimal bounds for decision problems on the crcw pram optimal &ohgr;(log n/log log n) lower bounds on the time for crcw prams with polynomially bounded numbers of processors or memory cells to compute parity and a number of related problems are proven. a strict time hierarchy of explicit boolean functions of n bits on such machines that holds up to &ogr;(log n/log log n) time is also exhibited. that is, for every time bound t within this range a function is exhibited that can be easily computed using polynomial resources in time t but requires more than polynomial resources to be computed in time t - 1. finally, it is shown that almost all boolean functions of n bits require log n - log log n + &ohgr;(1) time when the number of processors is at most polynomial in n. the bounds do not place restrictions on the uniformity of the algorithms nor on the instruction sets of the machines.
randomized versus nondeterministic communication complexity our main result is the demonstration of a boolean function f with nondeterministic and co-nondeterministic complexities o(log n) and &egr;-error randomized complexity &ohgr;(log2 n), for 0 &le; &egr; < 1/2. this is the first separation of this kind for a decision problem.
time-space tradeoffs, multiparty communication complexity, and nearest-neighbor problems. recently, the first non-trivial time-space tradeoff lower bounds have been shown for decision problems in p, using notions derived from the study of two-party communication complexity. these results are proven directly for branching programs, natural generalizations of decision trees to directed graphs that provide elegant models of both non-uniform time t and space s simultaneously.we develop a new lower bound criterion, based on extending two-party communication complexity ideas to multiparty communication complexity. applying this criterion to an explicit boolean function based on a multilinear form overgf(2^s) for suitable s, we show lower bounds that yield t=\omega(n\log^2 n) whens\le n^{1-\epsilon}\log |d| for large input domain d. this improves the previous best lower bounds for general branching programs of t=\omega(n\log (n/s)).using these ideas, we also give a conceptually simple proof of the relationship between multiparty communication complexity and time-space tradeoffs for oblivious branching programs (previously shown by babai et al.). this relationship yields time-space tradeoff lower bounds of the form t=\omega(n\log^2(n/s)) for 1gap on oblivious branching programs. since 1gap has a trivial general branching program of time n and space o(\log n), this provides the first separation between general and oblivious branching program computation.finally, we develop lower bounds for nearest-neighbor problems involving n data points in a variety of d-dimensional metric spaces. in yao's general cell-probe model, borodin et al. showed that time \omega(d/\log n) is required for nearest-neighbor queries over \{0,1\}^d. we consider slightly more restricted data structure algorithms that are charged for access to individual components of the query.in this model, for certain d-dimensional metric spaces, we prove query time lower bounds \omega(d\log d) or \omega(d\sqrt{\log d/\log\log d}), depending on the metric. these follow using a general relationship, suggested by miltersen et al., between data structure bounds and time-space tradeoff bounds for branching programs. the above bounds use coordinates of size polynomial in d. over \{0,1\}^d, we prove query time lower bounds of \omega(d) in general and \omega(d\log d) when the data structure corresponds to an oblivious branching program.
non-clairvoyant scheduling to minimize the average flow time on single and parallel machines. scheduling a sequence of jobs released over time when the processing time of a job is only known at its completion is a classical problem in cpu scheduling in time sharing operating systems. a widely used measure for the responsiveness of the system is the average flow time of the jobs, i.e. the average time spent by jobs in the system between release and completion.the windows nt and the unix operating system scheduling policies are based on the multi-level feedback algorithm [12, 1]. in this paper we prove that a randomized version of the multi-level feedback algorithm is competitive for single and parallel machine systems, in our opinion providing one theoretical validation of the goodness of an idea that has been very effective in practice along the last two decades.the randomized multi-level feedback algorithm (rmlf) was first proposed by kalyanasundaram and pruhs [7] for a single machine achieving an o(\log n \log\log n) competitive ratio to minimize the average flow time against the on-line adaptive adversary, where n is the number of jobs that are released. we present a version of rmlf working for any numberm of parallel machines. we show for rmlf a first o(\log n\log \frac{n}{m}) competitiveness result against the oblivious adversary on parallel machines. we also show that the same rmlf algorithm surprisingly achieves a tight o(\log n) competitive ratio against the oblivious adversary on a single machine, therefore matching the lower bound of [10].
properties of acyclic database schemes there is a class of database descriptions, involving one &ldquo;acyclic&rdquo; join dependency and a collection of functional dependencies, and nothing else, that appears powerful enough to describe most any real-world body of data in relational database terms. further, this class has many desirable properties. some properties make operations like updates and the selection of joins to implement a query over a universal relation especially easy. other properties of interest were studied by other researchers who described the same class in radically different terms, and found desirable properties in their own contexts. it is the purpose of this paper to define the class formally, to give its important properties and the equivalences with the other classes mentioned, and to explain the importance of each property. this paper is intended to summarize the results that will appear in more detail in [fmu] and [bfmy].
equivalence of relational database schemes we investigate the question of when two database schemes embody the same information. we argue that this question reduces to the equivalence of the sets of fixed points of the project-join mappings associated with the two database schemes in question. when data dependencies are given, we need only consider those fixed points that satisfy the dependencies. a polynomial algorithm to test the equivalence of database schemes, when there are no dependencies, is given. we also provide an exponential algorithm to handle the case where there are functional and/or multivalued dependencies. furthermore, we give a polynomial time test to determine whether a project-join mapping preserves a set of functional dependencies, and a polynomial time algorithm for equivalence of database schemes whose project-join mappings do preserve the given set of functional dependencies. lastly, we introduce the &ldquo;update sets&rdquo; approach to database design as an application of these results.
random knapsack in expected polynomial time. we present the first average-case analysis proving a polynomial upper bound on the expected running time of an exact algorithm for the 0/1 knapsack problem. in particular, we prove for various input distributions, that the number of pareto-optimal knapsack fillings is polynomially bounded in the number of available items. an algorithm by nemhauser and ullmann can enumerate these solutions very efficiently so that a polynomial upper bound on the number of pareto-optimal solutions implies an algorithm with expected polynomial running time.the random input model underlying our analysis is quite general and not restricted to a particular input distribution. we assume adversarial weights and randomly drawn profits (or vice versa). our analysis covers general probability distributions with finite mean and, in its most general form, can even handle different probability distributions for the profits of different items. this feature enables us to study the effects of correlations between profits and weights. our analysis confirms and explains practical studies showing that so-called strongly correlated instances are harder to solve than weakly correlated ones.
typical properties of winners and losers in discrete optimization. we present a probabilistic analysis for a large class of combinatorial optimization problems containing, e. g., all binary optimization problems defined by linear constraints and a linear objective function over (0,1)n. by parameterizing which constraints are of stochastic and which are of adversarial nature, we obtain a semi-random input model that enables us to do a general average-case analysis for a large class of optimization problems while at the same time taking care for the combinatorial structure of individual problems. our analysis covers various probability distributions for the choice of the stochastic numbers and includes smoothed analysis with gaussian and other kinds of perturbation models as a special case. in fact, we can exactly characterize the smoothed complexity of optimization problems in terms of their random worst-case complexity.a binary optimization problem has a polynomial smoothed complexity if and only if it has a pseudopolynomial complexity. our analysis is centered around structural properties of binary optimization problems, called winner, loser, and feasibility gaps. we show, when the coefficients of the objective function and/or some of the constraints are stochastic, then there usually exist a polynomial n-ω(1) gap between the best and the second best solution as well as a polynomial slack to the boundary of the constraints. similar to the condition number for linear programming, these gaps describe the sensitivity of the optimal solution to slight perturbations of the input and can be used to bound the necessary accuracy as well as the complexity for solving an instance. we exploit the gaps in form of an adaptive rounding scheme increasing the accuracy of calculation until the optimal solution is found. the strength of our techniques is illustrated by applications to various np-hard optimization problems from mathematical programming, network design, and scheduling for which we obtain the the first algorithms with polynomial average-case/smoothed complexity.
np might not be as easy as detecting unique solutions. we construct an oracle a such that p^a = parityp^a and np^a=exp^a. this relativized world has several amazing properties: - the oracle a gives the first relativized world where one can solve satisfiability on formulae with at most one assignment yet p is not equal to np. - the oracle a is the first where p^a = up^a >< np^a = conp^a. - the construction gives a much simpler proof than fenner, fortnow and kurtz of a relativized world where all np-complete sets are polynomial-time isomorphic. it is the first such computable oracle. - relative to $a$ we have a collapse of parityexp^a is in zpp^a in p^a/poly. we also create a different relativized world where there exists a set l in np that is np-complete under reductions that make one query to l but not under traditional many-one reductions. this contrasts with the result of buhrman, spaan and torenvliet showing that these two completeness notions for nexp coincide.
private approximation of search problems. many approximation algorithms have been presented in the last decades for ${\cal np}$-hard search problems. the focus of this paper is on cryptographic applications, where it is desirable to design algorithms which do not leak unnecessary information. specifically, we are interested in private approximation algorithms&mdash;efficient approximation algorithms whose output does not leak information not implied by the optimal solutions to the search problems. privacy requirements add constraints on the approximation algorithms; in particular, known approximation algorithms usually leak a lot of information. for functions, feigenbaum et al. [acm trans. algorithms, 2 (2006), pp. 435-472] presented a natural requirement that a private algorithm should not leak information not implied by the original function. generalizing this requirement to relations is not straightforward as an input may have many different outputs. we present a new definition that captures a minimal privacy requirement from such algorithms; applied to an input instance, it should not leak any information that is not implied by its collection of exact solutions. we argue that our privacy requirement is natural and quite minimal. we show that, even under this minimal definition of privacy, for well-studied problems such as vertex cover and max exact 3sat, private approximation algorithms are unlikely to exist even for poor approximation ratios. similarly to halevi et al. [in proceedings of the 33rd acm symposium on theory of computing, acm, new york, 2001, pp. 550-559], we define a relaxed notion of approximation algorithms that leak (a little) information, and demonstrate the applicability of this notion by showing near optimal approximation algorithms for max exact 3sat that leak a little information.
a new recursion-theoretic characterization of the polytime functions (extended abstract) we give a recursion-theoretic characterization of fp which describes polynomial time computation independently of any externally imposed resource bounds. in particular, this syntactic characterization avoids the explicit size bounds on recursion (and the initial function 2|x|.|y|) of cobham.
backing up in singly linked lists. we show how to reduce the time overhead for implementing two-way movement on a singly linked list to o(n&epsi;) per operation without modifying the list and without making use of storage other than a finite number of pointers into the list. we also prove a matching lower bound.these results add precision to the intuitive feeling that doubly linked lists are more efficient than singly linked lists, and quantify the efficiency gap in a read-only situation. we further analyze the number of points of access into the list (pointers) necessary for obtaining a desired value of &epsi;. we obtain tight tradeoffs which also separate the amortized and worst-case settings.our upper bound implies that read-only programs with singly-linked input can do string matching much faster than previously expected.
can finite samples detect singularities of real-valued functions? consider the following type of problem: there is an unknown function, f : rn &rarr; rm, there is also a black-box that on query x (&egr; rn) returns f(x). is there an algorithm that, using probes to the black-box, can figure out analytic information about f? (for an example: &ldquo;is f a polynomial?&rdquo;, &ldquo;is f a second order differentiable at x = (0,0,&hellip;,0)?&rdquo; etc.). clearly, for examples as these, if we bound the number of probes an algorithm has to settle for, no algorithm can carry the task. on the other hand, if one allows an infinite iteration of a &ldquo;probe compute and guess&rdquo; process, then, (quite surprisingly) for many such questions, there are algorithms that are guaranteed to be correct in all but finitely many of their guesses. we call such questions decidable in the limit, (dil). we analyze the class of dil problems and provide a necessary and sufficient condition for the membership of a decision problem in this class. we offer an algorithm for any dil problem, and apply it to several types of learning tasks. furthermore, if an a-priori probability distribution p, according to which f is being chosen, is available to the algorithm, then it can be strengthened into a finite algorithm. more precisely, for many distributions p, there exists a polynomial function, l, such that for every 0<&dgr;<1, there is an algorithm using at most l(log(&dgr;)) many probes that succeeds on more than (1&ndash;&dgr;) of the f's (as measured by p). we believe that the new approach presented here will be found useful for many further applications.
towards a theory of semantics and compilers for programming languages the concept of imbedding a programming language l into a formal system is introduced and used as the basis of defining the semantics &fgr; of the language. &fgr; is an operator which maps a program p in l onto a function. the pair (l, &fgr;) is called a programming system. if (l, &fgr;) and (l,' &fgr;') are two programming systems, a mapping &ggr; from l into l' is called a compiler. a compiler is said to be correct if &fgr;'(&ggr;(p)) &equil; &fgr;(p) for p in l. these ideas are illustrated in terms of two programming systems, one for recursive functions and the other for turing machines.
on the cryptographic security of single rsa bits the ability to &ldquo;hide&rdquo; one bit in trapdoor functions has recently gained much interest in cryptography research, and is of great importance in many transactions protocols. in this paper we study the cryptographic security of rsa bits. in particular, we show that unless the cryptanalyst can completely break the rsa encryption, any heuristic he uses to determine the least significant bit of the cleartext must have an error probability greater than 1&edivide;4&mdash;&egr; a similar result is shown for rabin's encryption scheme.
multi-prover interactive proofs: how to remove intractability assumptions quite complex cryptographic machinery has been developed based on the assumption that one-way functions exist, yet we know of only a few possible such candidates. it is important at this time to find alternative foundations to the design of secure cryptography. we introduce a new model of generalized interactive proofs as a step in this direction. we prove that all np languages have perfect zero-knowledge proof-systems in this model, without making any intractability assumptions. the generalized interactive-proof model consists of two computationally unbounded and untrusted provers, rather than one, who jointly agree on a strategy to convince the verifier of the truth of an assertion and then engage in a polynomial number of message exchanges with the verifier in their attempt to do so. to believe the validity of the assertion, the verifier must make sure that the two provers can not communicate with each other during the course of the proof process. thus, the complexity assumptions made in previous work, have been traded for a physical separation between the two provers. we call this new model the multi-prover interactive-proof model, and examine its properties and applicability to cryptography.
linear time bounds for median computations new upper and lower bounds are presented for the maximum number of comparisons, f(i,n), required to select the i-th largest of n numbers. an upper bound is found, by an analysis of a new selection algorithm, to be a linear function of n: f(i,n) &le; 103n/18 < 5.73n, for 1 &le; i &le; n. a lower bound is shown deductively to be: f(i,n) &ge; n+min(i,n&minus;i+l) + [log2(n)] &minus; 4, for 2 &le; i &le; n&minus;1, or, for the case of computing medians: f([n/2],n) &ge; 3n/2 &minus; 3
linear approximation of shortest superstrings we consider the following problem: given a collection of strings s1,&hellip;, sm, find the shortest string s such that each si appears as a substring (a consecutive block) of s. although this problem is known to be np-hard, a simple greedy procedure appears to do quite well and is routinely used in dna sequencing and data compression practice, namely: repeatedly merge the pair of (distinct) strings with maximum overlap until only one string remains. let n denote the length of the optimal superstring. a common conjecture states that the above greedy procedure produces a superstring of length o(n) (in fact, 2n), yet the only previous nontrivial bound known for any polynomial-time algorithm is a recent o(n log n) result. we show that the greedy algorithm does in fact achieve a constant factor approximation, proving an upper bound of 4n. furthermore, we present a simple modified version of the greedy algorithm that we show produces a superstring of length at most 3n. we also show the superstring problem to be maxsnp-hard, which implies that a polynomial-time approximation scheme for this problem is unlikely.
fast quantum byzantine agreement. we present a fast quantum byzantine agreement protocol that can reach agreement in o(1) expected communication rounds against a strong full information, dynamic adversary, tolerating up to the optimal t‹n3 faulty players in the synchronous setting, and up to t‹n4 faulty players for asynchronous systems. this should be contrasted with the known classical synchronous lower bound of ω(√ nlog n) [3] when t=(n).
designing programs that check their work a program correctness checker is an algorithm for checking the output of a computation. this paper defines the concept of a program checker. it designs program checkers for a few specific and carefully chosen problems in the class p of problems solvable in polynomial time. it also applies methods of modern cryptography, especially the idea of a probabilistic interactive proof, to the design of program checkers for group theoretic computations. finally it characterizes the problems that can be checked.
byzantine agreement in the full-information model in o(log n) rounds. we present a randomized byzantine agreement (ba) protocol with an expected running time of o(log n) rounds, in a synchronous full-information network of n players. for any constant ε > 0, the constructed protocol tolerates t non-adaptive byzantine faults, as long as n ≥ (4 + ε)t. in the full-information model, no restrictions are placed on the computational power of the faulty players or the information available to them. in particular, the faulty players may be infinitely powerful, and they can observe all communication among the honest players.this constitutes significant progress over the best known randomized ba protocol in the same setting which has a round-complexity of θ(t/log n) rounds [9], and answers an open problem posed by chor and dwork [10].
noise-tolerant learning, the parity problem, and the statistical query model. we describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptographic and coding problems. our algorithm runs in polynomial time for the case of parity functions that depend on only the first o(log n log log n) bits of input, which provides the first known instance of an efficient noise-tolerant algorithm for a concept class that is not learnable in the statistical query model of kearns [1998]. thus, we demonstrate that the set of problems learnable in the statistical query model is a strict subset of those problems learnable in the presence of noise in the pac model.in coding-theory terms, what we give is a poly(n)-time algorithm for decoding linear k &times; n codes in the presence of random noise for the case of k = c log n log log n for some c > 0. (the case of k = o(log n) is trivial since one can just individually check each of the 2k possible messages and choose the one that yields the closest codeword.)a natural extension of the statistical query model is to allow queries about statistical properties that involve t-tuples of examples, as opposed to just single examples. the second result of this article is to show that any class of functions learnable (strongly or weakly) with t-wise queries for t = o(log n) is also weakly learnable with standard unary queries. hence, this natural extension to the statistical query model does not increase the set of weakly learnable functions.
size space tradeoffs for resolution. we investigate tradeoffs of various basic complexity measures such as size, space, and width. we show examples of formulas that have optimal proofs with respect to any one of these parameters, but optimizing one parameter must cost an increase in the other. these results have implications to the efficiency (or rather, inefficiency) of some commonly used sat solving heuristics. our proof relies on a novel connection of the variable space of a proof to the black-white pebbling measure of an underlying graph.
fast learning of k-term dnf formulas with queries this paper presents an algorithm that uses equivalence and membership queries to learn the class of k-term dnf formulas in time o(n&bull;2o(k)), where n is the number of input variables. this improves upon previous o(nk) bounds and allows one to learn dnf of o(log n) terms in polynomial time. we present the algorithm in its most natural form as a randomized algorithm, and then show how recent derandomization techniques can be used to make it deterministic. the algorithm is an exact learning algorithm, but one where the equivalance query hypotheses and the final output are general (not necessarily k-term) dnf formulas. for the special case of 2-term dnf formulas, we give a simpler version of our algorithm that uses at most 4n + 2 total membership and equivalence queries.
on effective procedures for speeding up algorithms this paper is concerned with the nature of speedups. let f be any recursive function. we show that there is no effective procedure for going from an algorithm for f to a significantly faster algorithm for f. on the other hand, there is an effective procedure for going from any algorithm to a faster algorithm, provided one has a bound on the size of the algorithm that does the computation faster for all inputs. if no bound on the size of the faster algorithm is known in advance, one can still obtain a pseudo speedup: this is a very fast algorithm which computes a variant of the function, one which differs from the original function on a finite number of inputs.
robust pcps of proximity, shorter pcps and applications to coding. we continue the study of the trade-off between the length of probabilistically checkable proofs (pcps) and their query complexity, establishing the following main results (which refer to proofs of satisfiability of circuits of size $n$): 1. we present pcps of length $\exp(o(\log\log n)^2)\cdot n$ that can be verified by making $o(\log\log n)$ boolean queries. 2. for every \epsilon>0, we present pcps of length $\exp(\log^\epsilon n)\cdot n$ that can be verified by making a constant number of boolean queries. in both cases, false assertions are rejected with constant probability (which may be set to be arbitrarily close to 1). the multiplicative overhead on the length of the proof, introduced by transforming a proof into a probabilistically checkable one, is just quasi polylogarithmic in the first case (of query complexity $o(\log\log n)$), and is $2^{(\log n)^\epsilon}$, for any $\epsilon > 0$, in the second case (of constant query complexity). our techniques include the introduction of a new variant of pcps that we call &ldquo;robust pcps of proximity.&rdquo; these new pcps facilitate proof composition, which is a central ingredient in the construction of pcp systems. (a related notion and its composition properties were discovered independently by dinur and reingold.) our main technical contribution is a construction of a &ldquo;length-efficient&rdquo; robust pcp of proximity. while the new construction uses many of the standard techniques used in pcp constructions, it does differ from previous constructions in fundamental ways, and in particular does not use the &ldquo;parallelization&rdquo; step of arora et al. [j. acm, 45 (1998), pp. 501-555]. the alternative approach may be of independent interest. we also obtain analogous quantitative results for locally testable codes. in addition, we introduce a relaxed notion of locally decodable codes and present such codes mapping $k$ information bits to codewords of length $k^{1+\epsilon}$ for any $\epsilon>0$.
some 3cnf properties are hard to test. for a boolean formula $\phi$ on n variables, the associated property $p_\phi$ is the collection of n-bit strings that satisfy $\phi$. we study the query complexity of tests that distinguish (with high probability) between strings in $p_\phi$ and strings that are far from $p_\phi$ in hamming distance. we prove that there are 3cnf formulae (with o(n) clauses) such that testing for the associated property requires $\omega(n)$ queries, even with adaptive tests. this contrasts with 2cnf formulae, whose associated properties are always testable with $o(\sqrt{n})$ queries [e. fischer et al., monotonicity testing over general poset domains, in proceedings of the 34th annual acm symposium on theory of computing, acm, new york, 2002, pp. 474--483]. notice that for every negative instance (i.e., an assignment that does not satisfy $\phi$) there are three bit queries that witness this fact. nevertheless, finding such a short witness requires reading a constant fraction of the input, even when the input is very far from satisfying the formula that is associated with the property.a property is linear if its elements form a linear space. we provide sufficient conditions for linear properties to be hard to test, and in the course of the proof include the following observations which are of independent interest: in the context of testing for linear properties, adaptive two-sided error tests have no more power than nonadaptive one-sided error tests. moreover, without loss of generality, any test for a linear property is a linear test. a linear test verifies that a portion of the input satisfies a set of linear constraints, which define the property, and rejects if and only if it finds a falsified constraint. a linear test is by definition nonadaptive and, when applied to linear properties, has a one-sided error. random low density parity check codes (which are known to have linear distance and constant rate) are not locally testable. in fact, testing such a code of length n requires $\omega(n)$ queries.
simple pcps with poly-log rate and query complexity. we give constructions of probabilistically checkable proofs (pcps) of length n . poly(log n) (to prove satisfiability of circuits of size n) that can verified by querying poly(log n) bits of the proof. we also give constructions of locally testable codes (ltcs) with similar parameters.previous constructions of short pcps (from [5]to [9]) relied extensively on properties of low degree multi-variate polynomials. in contrast, our constructions rely on new problems and techniques revolving around the properties of codes based on high degree polynomials in one variable (also known as reed-solomon codes). we show how to convert the problem of verifying the satisfaction of a circuit by a given assignment to the task of verifying that a given function is close to being a reed-solomon codeword, i.e., a univariate polynomial of specified degree. this reduction is simpler than the corresponding steps in previous reductions, and gives a new alternative to using the popular "sum-check protocol". we then give a new pcp for the special task of proving that a function is close to being a reed-solomon codeword. this step of the construction is by a self-contained recursion, and the only ingredient needed in the analysis is the bi-variate low-degree test of polischuk and spielman[27].note that our constructions yield ltcs first, which are then converted to pcps. in contrast, most recent constructions go in the opposite (and less natural) direction of getting ltcs from pcps.
new lower bounds for parallel computation lower bounds are proven on the parallel-time complexity of several basic functions on the most powerful concurrent-read concurrent-write pram with unlimited shared memory and unlimited power of individual processors (denoted by priority(&infin;)): it is proved that with a number of processors polynomial in n, &ohgr; (log n) time is needed for addition, multiplication or bitwise or of n numbers, when each number has n' bits. hence even the bit complexity (i.e., the time complexity as a function of the total number of bits in the input) is logarithmic in this case. this improves a beautiful result of meyer auf der heide and wigderson [22]. they proved a log n lower bound using ramsey-type techniques. using ramsey theory, it is possible to get an upper bound on the number of bits in the inputs used. however, for the case of polynomially many processors, this upper bound is more than a polynomial in n. an &ohgr; (log n) lower bound is given for priority(&infin;) with no(1) processors on a function with inputs from {0, 1}, namely for the function &fnof;(x1, &hellip; , xn,) = &sgr; nl- 1 xlai where a is fixed and xi &egr; {0, 1}. finally, by a new efficient simulation of priority(&infin;) by unbounded fan-in circuits, that with less than exponential number of processors, it is proven a priority(&infin;) cannot compute parity in constant time, and with no(1) processors &ohgr;(@@@@log n) time is needed. the simulation technique is of independent interest since it can serve as a general tool to translate circuit lower bounds into pram lower bounds. further, the lower bounds in (1) and (2) remain valid for probabilistic or nondeterministic concurrent-read concurrent-write prams.
randomness-efficient low degree tests and short pcps via epsilon-biased sets. we present the first explicit construction of probabilistically checkable proofs (pcps) and locally testable codes (ltcs) of fixed constant query complexity which have almost-linear (= n * 2õ(√log n)) size. such objects were recently shown to exist (nonconstructively) by goldreich and sudan[17]. previous explicit constructions required size n1 + ω(ε) with 1/ε queries. the key to these constructions is a nearly optimal randomness-efficient version of the low degree test[32]. in a similar way we give a randomness-efficient version of the blr linearity test[13] (which is used, for instance, in locally testing the hadamard code). the derandomizations are obtained through ε-biased sets for vector spaces over finite fields. the analysis of the derandomized tests rely on alternative views of ε-biased sets --- as generating sets of cayley expander graphs for the low degree test, and as defining linear error-correcting codes for the linearity test.
short proofs are narrow - resolution made simple. the width of a resolution proof is defined to be the maximal number of literals in any clause of the proof. in this paper we relate proof width to proof size, in both general resolution, and its tree-like variant. specifically, the main observation of this paper is a relation between these two fundamental resources
building a complete inverted file for a set of text files in linear time given a finite set of texts s &equil; {&ohgr;1, ..., &ohgr;k} over some fixed finite alphabet &sgr;, a complete inverted file for s is an abstract data type that provides the functions find(&ohgr;), which returns the longest prefix of &ohgr; which occurs in s; freq(&ohgr;), which returns the number of times &ohgr; occurs in s; and locations(&ohgr;) which returns the set of positions at which &ohgr; occurs. we give a data structure to implement a complete inverted file for s which occupies linear space and can be built in linear time, using the uniform cost ram model. using this data structure, the time for each of the above query functions is optimal. to accomplish this, we use techniques from the theory of finite automata to build a deterministic finite automaton which recognizes the set of all sub words of the set s. this automaton is then annotated with additional information and compacted to facilitate the desired query functions.
space-efficient scheduling of multithreaded computations. this paper considers the problem of scheduling dynamic parallel computations to achieve linear speedup without using significantly more space per processor than that required for a single-processor execution. utilizing a new graph-theoretic model of multithreaded computation, execution efficiency is quantified by three important measures: t1 is the time required for executing the computation on a 1 processor, $t_\infty$ is the time required by an infinite number of processors, and s1 is the space required to execute the computation on a 1 processor. a computation executed on p processors is time-efficient if the time is $o(t_1/p + t_\infty)$, that is, it achieves linear speedup when $p=o(t_1/t_\infty)$, and it is space-efficient if it uses o(s1p) total space, that is, the space per processor is within a constant factor of that required for a 1-processor execution.the first result derived from this model shows that there exist multithreaded computations such that no execution schedule can simultaneously achieve efficient time and efficient space. but by restricting attention to "strict" computations---those in which all arguments to a procedure must be available before the procedure can be invoked---much more positive results are obtainable. specifically, for any strict multithreaded computation, a simple online algorithm can compute a schedule that is both time-efficient and space-efficient. unfortunately, because the algorithm uses a global queue, the overhead of computing the schedule can be substantial. this problem is overcome by a decentralized algorithm that can compute and execute a p-processor schedule online in expected time $o(t_1/p + t_\infty\lg p)$ and worst-case space $o(s_1p\lg p)$, including overhead costs.
the power of a pebble: exploring and mapping directed graphs. exploring and mapping an unknown environment is a fundamental problem that is studied in a variety of contexts. many results have focused on finding efficient solutions to restricted versions of the problem. in this paper, we consider a model that makes very limited assumptions about the environment and solve the mapping problem in this general setting. we model the environment by an unknown directed graph g, and consider the problem of a robot exploring and mapping g. the edges emanating from each vertex are numbered from '1' to 'd', but we do not assume that the vertices of g are labeled. since the robot has no way of distinguishing between vertices, it has no hope of succeeding unless it is given some means of distinguishing between vertices. for this reason we provide the robot with a "pebble'--a device that it can place on a vertex and use to identify the vertex later. in this paper we show: (1) if the robot knows an upper bound on the number of vertices then it can learn the graph efficiently with only one pebble. (2) if the robot does not know an upper bound on the number of vertices n, then θ(log log n) pebbles are both necessary and sufficient. in both cases our algorithms are deterministic.
balanced boolean functions that can be evaluated so that every input bit is unlikely to be read. a boolean function of n bits is balanced if it takes the value 1 with probability 1⁄2. we exhibit a balanced boolean function with a randomized evaluation procedure (with probability 0 of making a mistake) so that on uniformly random inputs, no input bit is read with probability more than θ(n-1/2√ log n). we construct a balanced monotone boolean function and a randomized algorithm computing it for which each bit is read with probability θ(n-1⁄3 log n). we then show that for any randomized algorithm for evaluating a balanced boolean function, when the input bits are uniformly random, there is some input bit that is read with probability at least θ(n-1䊪). for balanced monotone boolean functions, there is some input bit that is read with probability at least θ(n-1䊫).
an iteration theorem for one-counter languages we give a definition of one-counter languages. we show that the smallest full afl containing this family is principal with full generator d'@@@@ @@@@, the semi-dyck language on two letters. we then give without the proof, which shall be published elsewhere, our main result: an iteration theorem for one-counter languages that yields several corollaries.
modified log-sobolev inequalities, mixing and hypercontractivity. motivated by (the rate of information loss or) the rate at which the entropy of an ergodic markov chain relative to its stationary distribution decays to zero, we study modified versions of the standard logarithmic sobolev inequality in the discrete setting of finite markov chains and graphs. these inequalities turn out to be weaker than the standard log-sobolev inequality, but stronger than the poincare' (spectral gap) inequality. we also derive a hypercontractivity formulation equivalent to our main modified log-sobolev inequality which might be of independent interest. finally we show that, in contrast with the spectral gap, for bounded degree expander graphs various log-sobolev-type constants go to zero with the size of the graph.
a linear time algorithm for finding tree-decompositions of small treewidth. in this paper, we give for constant $k$ a linear-time algorithm that, given a graph $g=(v,e)$, determines whether the treewidth of $g$ is at most $k$ and, if so, finds a tree-decomposition of $g$ with treewidth at most $k$. a consequence is that every minor-closed class of graphs that does not contain all planar graphs has a linear-time recognition algorithm. another consequence is that a similar result holds when we look instead for path-decompositions with pathwidth at most some constant $k$.
some unexpected expected behavior results for bin packing we study the asymptotic expected behavior of the first fit and first fit decreasing bin packing algorithms applied to items chosen uniformly from the interval (0,u], u &le; 1. our results indicate that the algorithms perform even better than previously expected.
pseudorandom generators for low degree polynomials. we investigate constructions of pseudorandom generators that fool polynomial tests of degree d in m variables over finite fields f. our main construction gives a generator with seed length o(d4 log m (1 + log(d ⁄ ε) ⁄ log log m) + log |f|) bits that achieves arbitrarily small bias ε and works whenever |f| is at least polynomial in d, log m, and 1⁄ε. we also present an alternate construction that uses a seed that can be described by o(c2d8m6⁄(c-2) log(d⁄ε) + log |f|) bits (more precisely, o(c2d8m6⁄(c-2)) field elements, each chosen from a set of size poly(cd⁄ε), plus two field elements ranging over all of f), works whenever |f| is at least polynomial in c, d, and 1⁄ε, and has the property that every element of the output is a function of at most c field elements in the input. both generators are computable by small arithmetic circuits. the main tool used in the construction is a reduction that allows us to transform any "dense" hitting set generator for polynomials into a pseudorandom generator.
divide-and-conquer in multidimensional space we investigate a divide-and-conquer technique in multidimensional space which decomposes a geometric problem on n points in k dimensions into two problems on n/2 points in k dimensions plus a single problem on n points in k&minus;1 dimension. special structure of the subproblems is exploited to obtain an algorithm for finding the two closest of n points in 0(n log n) time in any dimension. related results are discussed, along with some conjectures and unsolved geometric problems.
an area-maximum edge length tradeoff for vlsi layout we construct an n-node graph g which has (i) a layout with area o(n) and maximum edge length o(n1/2), (ii) a layout with area o(n5/4) and maximum edge length o(n1/4). we prove for 1 &le; f(n) &le; o(n1/8) that any layout for g with area nf(n) has an edge of length &ohgr;(n1/2/f (n) &bull;log n). hence g has no layout which is optimal with respect to both measures.
balanced allocations: the heavily loaded case. we investigate balls-into-bins processes allocating $m$ balls into $n$ bins based on the multiple-choice paradigm. in the classical single-choice variant each ball is placed into a bin selected uniformly at random. in a multiple-choice process each ball can be placed into one out of $d \ge 2$ randomly selected bins. it is known that in many scenarios having more than one choice for each ball can improve the load balance significantly. formal analyses of this phenomenon prior to this work considered mostly the lightly loaded case, that is, when $m \approx n$. in this paper we present the first tight analysis in the heavily loaded case, that is, when $m \gg n$ rather than $m \approx n$.the best previously known results for the multiple-choice processes in the heavily loaded case were obtained using majorization by the single-choice process. this yields an upper bound of the maximum load of bins of $m/n + {\mbox{$\cal o$}}(\sqrt{m \ln n \,/\, n})$ with high probability. we show, however, that the multiple-choice processes are fundamentally different from the single-choice variant in that they have "short memory." the great consequence of this property is that the deviation of the multiple-choice processes from the optimal allocation (that is, the allocation in which each bin has either $\lfloor m/n \rfloor$ or $\lceil m/n \rceil$ balls) does not increase with the number of balls as in the case of the single-choice process. in particular, we investigate the allocation obtained by two different multiple-choice allocation schemes, the greedy scheme due to azar et al. and the always-go-left scheme due to vöcking. we show that these schemes result in a maximum load of only $m/n + {\mbox{$\cal o$}}(\ln \ln n)$ with high probability. all our detailed bounds on the maximum load are tight up to an additive constant.furthermore, we investigate the two multiple-choice algorithms in a comparative study. we present a majorization result showing that the always-go-left scheme obtains a better load balancing than the greedy scheme for any choice of $n$, $m$, and $d$.
isotopic implicit surface meshing. this paper addresses the problem of piecewise linear approximation of implicit surfaces. we first give a criterion ensuring that the zero-set of a smooth function and the one of a piecewise linear approximation of it are isotopic. then, we deduce from this criterion an implicit surface meshing algorithm certifying that the output mesh is isotopic to the actual implicit surface. this is the first algorithm achieving this goal in a provably correct way.
tree-walking automata do not recognize all regular languages. tree-walking automata are a natural sequential model for recognizing tree languages. every tree language recognized by a tree-walking automaton is regular. in this paper, we present a tree language which is regular but not recognized by any (nondeterministic) tree-walking automaton. this settles a conjecture of engelfriet, hoogeboom and van best. moreover, the separating tree language is definable already in first-order logic over a signature containing the left-son, right-son and ancestor relations.
reconstructing a three-dimensional model with arbitrary errors. a number of current technologies allow for the determination of interatomic distance information in structures such as proteins and rna. thus, the reconstruction of a three-dimensional set of points using information about its interpoint distances has become a task of basic importance in determining molecular structure. the distance measurements one obtains from techniques such as nmr are typically sparse and error-prone, greatly complicating the reconstruction task. many of these errors result in distance measurements that can be safely assumed to lie within certain fixed tolerances. but a number of sources of systematic error in these experiments lead to inaccuracies in the data that are very hard to quantify; in effect, one must treat certain entries of the measured distance matrix as being arbitrarily &ldquo;corrupted.&rdquo;the existence of arbitrary errors leads to an interesting sort of error-correction problem&mdash;how many corrupted entries in a distance matrix can be efficiently corrected to produce a consistent three-dimensional structure? for the case of an n &times; n matrix in which every entry is specified, we provide a randomized algorithm running in time o(n log n) that enumerates all structures consistent with at most (1/2-&egr;)n errors per row, with high probability. in the case of randomly located errors, we can correct errors of the same density in a sparse matrix-one in which only a &bgr; fraction of the entries in each row are given, for any constant &bgr;gt;0.
on the expected behaviour of disjoint set union algorithms we show that the expected time of the weighted quickfind (qfw) disjoint set union and find algorithm to perform (n - 1) randomly chosen unions is cn + o(n/log n), where c = 2.0847 &hellip;. this implies, through an observation of tarjan and van leeuwen, linear expected time bounds to perform o(n) unions and finds for a class of other union -find algorithms. we also prove that the expected time of the unweighted quickfind (qf) algorithm is n2/8 + o(n(log n)2), and set the several related open questions of knuth and sch&ouml;nhage.
finding smooth integers in short intervals using crt decoding. we present a new algorithm for crt list decoding. an instance of the, crt list decoding problem consists of integers b, 〈p1, ..., pn〉 and 〈r1, ..., rn〉, where p1 < p2 < ... < pn is a sequence of relatively prime integers. the crt list decoding problem is to find all positive integers x < b such that x = ri mod pi for all but e values of i ∈ {1, ..., n}. suppose b = πi=1r pi for some integer k. goldreich, ron, and sudan (in "proc. of stoc'99", pp. 225-234, 1999) recently gave several applications for this problem and presented the first efficient algorithm that works whenever e (approximately) satisfies e < n - √2kn log pn/log p1. our new algorithm achieves the stronger bound e < n - √kn log pn/log p1 (approximately). the improvement is significant when k is relatively close to n, e.g. k > n/3. the bounds we obtain are similar to the bounds obtained by guruswami and sudan for reed-solomon list decoding. hence, our algorithm reduces the gap between crt list decoding and list decoding of reed-solomon codes. in addition, we give a new application for crt list decoding: finding smooth integers in short intervals. problems of this type come up in several algorithms for factoring large integers. we define and solve a generalized crt list decoding problem and discuss how it might be used within the quadratic sieve factoring method.
a completeness technique for d-axiomatizable semantics in this paper, we show that by dropping the restrictions on interpretations of arbitrary programs and requiring only that very natural deductive systems are sound, we get classes of semantics which give good representations of program behavior and are more well-suited for applications involving an axiomatic approach (for example program verification). in addition, by tying the restrictions on the behavior of arbitrary programs or specified axiom schema, we get both a powerful formal tool and properties more widely used specifications lack such as compactness and completeness. completeness is a very desirable property. it is fairly straightforward to show given any reasonable deductive system d for a class of models a that pr(d) @@@@ th(a) . but given an application such as program verification, if it is not true that th(a) @@@@ pr(d) , we may be able to find correct programs which we cannot verify. in this paper we show that by using the &ldquo;axiomatizability&rdquo; of programming constructs, we can obtain a technique for showing completeness results for some of the more widely used variations of pdl. we begin with some definitions.
constructing evolutionary trees in the presence of polymorphic characters. most phylogenetics literature and construction methods based upon characters presume monomorphism (one state per character per species), yet polymorphism (multiple states per character per species) is well documented in both biology and historical linguistics. in this paper we consider the problem of inferring evolutionary trees for polymorphic characters. we show efficient algorithms for the construction of perfect phylogenies from polymorphic data. these methods have been used to help construct the evolutionary tree proposed by warnow, ringe, and taylor for the indo-european family of languages and presented by invitation at the national academy of sciences in november 1995.
quasi-realtime languages-extended abstract quasi-realtime languages are the languages accepted by nondeterministic multitape turing machines in real time. the family of quasi-realtime languages forms an abstract family of languages closed under intersection, linear erasing, and reversal. it is identical with the family of languages accepted by nondeterministic multitape turing machines in linear time. every quasi-realtime language can be accepted in real time by a non-deterministic one stack, one pushdown store machine, and can be expressed as the length-preserving homomorphic image of the intersection of three context-free languages.
tape- and time-bounded turing acceptors and afls: extended abstract complexity classes of formal languages defined by time- and tape-bounded turing acceptors are studied with the aim of showing sufficient conditions for these classes to be afls and to be principal afls.
intersections of linear context-free languages and reversal-bounded multipushdown machines (extended abstract) the purpose of this paper is to establish the following result. theorem 3.1. let l be a language. the following are equivalent: (i) l is accepted by a nondeterministic multipushdown acceptor which operates in such a way that in every accepting computation each pushdown store makes at most a bounded number of reversals and which runs in linear time; (ii) l is accepted by a nondeterministic multipushdown acceptor which operates in such a way that in every accepting computation each pushdown store makes at most one reversal and which runs in real time; (iii) l is the length-preservlng homomorphie image of the intersection of some finite number of linear context-free languages; (iv) l is accepted by a nondeterministlc acceptro with three pushdown stores which operates in such a way that in every computation each pushdown store makes at most one reversal and which rmls in real time; (v) l is the length-preservlng homomorphic image of the intersection of three linear context-free languages.
linear algorithms to recognize interval graphs and test for the consecutive ones property a matrix of zeroes and ones is said to have the consecutive ones property if there is a permutation of its rows such that the ones in each column appear consecutively. this paper develops a data structure which may be used to test a matrix for the consecutive ones property, and produce the desired permutation of the rows, in linear time. one application of the consecutive ones property is in recognizing interval graphs. a graph is an interval graph if there exists a 1-1 correspondence between its vertices and a set of intervals on the real line such that two vertices are adjacent if and only if the corresponding intervals have a nonempty intersection. fulkerson and gross have characterized interval graphs as those for which the clique versus vertex incidence matrix has the consecutive ones property. in testing this particular matrix for the consecutive ones property we may process the columns in a special order to simplify the algorithm. this yields the interval graph recognition algorithm which is presented in section 2; section 3 indicates how this algorithm may be extended to the general consecutive ones problem.
threshold functions and bounded depth monotone circuits we prove an exponential lower bound for the majority function on constant depth monotone circuits, solving an open problem of a. yao's.. in particular, we prove that computing majority on depth d monotone circuits requires exp&ohgr;(n1/(d-1)) size. using this result we also get exponential lower bounds for other problems, such as connectivity and cliques.
optimal separations between concurrent-write parallel machines we obtain tight bounds on the relative powers of the priority and common models of parallel random-access machines (prams). specifically we prove that: the element distinctness function of n integers, though solvable in constant time on a priority pram with n processors, requires &ohgr;(a(n,p)) time to solve on a common pram with p &ge; n processors, where a(n,p) = n log n/p log (n/p log n + 1). one step of a priority pram with n processors can be simulated on a common pram with p processors in &ogr;(a(n,p)) steps. as an example, the results show that the time separation between priority and common prams each with n processors is &thgr;(log n/log log n).
quantum complexity theory. in this paper we study quantum computation from a complexity theoretic viewpoint. our first result is the existence of an efficient universal quantum turing machine in deutsch's model of a quantum turing machine (qtm) [proc. roy. soc. london ser. a, 400 (1985), pp. 97--117]. this construction is substantially more complicated than the corresponding construction for classical turing machines (tms); in fact, even simple primitives such as looping, branching, and composition are not straightforward in the context of quantum turing machines. we establish how these familiar primitives can be implemented and introduce some new, purely quantum mechanical primitives, such as changing the computational basis and carrying out an arbitrary unitary transformation of polynomially bounded dimension.we also consider the precision to which the transition amplitudes of a quantum turing machine need to be specified. we prove that $o(\log t)$ bits of precision suffice to support a $t$ step computation. this justifies the claim that the quantum turing machine model should be regarded as a discrete model of computation and not an analog one. we give the first formal evidence that quantum turing machines violate the modern (complexity theoretic) formulation of the church--turing thesis. we show the existence of a problem, relative to an oracle, that can be solved in polynomial time on a quantum turing machine, but requires superpolynomial time on a bounded-error probabilistic turing machine, and thus not in the class $\bpp$. the class $\bqp$ of languages that are efficiently decidable (with small error-probability) on a quantum turing machine satisfies $\bpp \subseteq \bqp \subseteq \ptime^{\sp}$. therefore, there is no possibility of giving a mathematical proof that quantum turing machines are more powerful than classical probabilistic turing machines (in the unrelativized setting) unless there is a major breakthrough in complexity theory.
the k-steiner ratio in graphs. a steiner minimum tree (smt) is the shortest-length tree in a metric space interconnecting a set of points, called the regular points, possibly using additional vertices. a k-size steiner minimum tree (ksmt) is one that can be split into components where all regular points are leaves and all components have at most k leaves. the k-steiner ratio, $\rho_{k}$, is the infimum of the ratios smt/ksmt over all finite sets of regular points in all possible metric spaces, where the distances are given by a complete graph. previously, only $\rho_{2}$ and $\rho_{3}$ were known exactly in graphs, and some bounds were known for other values of k. in this paper, we determine $\rho_{k}$ exactly for all k. from this we prove a better approximation ratio for the steiner tree problem in graphs.
a characterization of the class of functions computable in polynomial time on random access machines enumeration problems constitute a major part of combinatorial mathematics. combinatorial mathematics expresses the solution of enumeration problems by means of solving formulas, generally based on the usual arithmetic operations [7]. these solving formulas can be formally represented as programs for a random access machine (ram) with arithmetical primitives, for which the natural complexity measure is the arithmetical complexity [1].
graph limits and parameter testing. we define a distance of two graphs that reflects the closeness of both local and global properties. we also define convergence of a sequence of graphs, and show that a graph sequence is convergent if and only if it is cauchy in this distance. every convergent graph sequence has a limit in the form of a symmetric measurable function in two variables. we use these notions of distance and graph limits to give a general theory for parameter testing. as examples, we provide short proofs of the testability of maxcut and the recent result of alon and shapira about the testability of hereditary graph properties.
solving convex programs by random walks. minimizing a convex function over a convex set in n-dimensional space is a basic, general problem with many interesting special cases. here, we present a simple new algorithm for convex optimization based on sampling by a random walk. it extends naturally to minimizing quasi-convex functions and to other generalizations.
sharp threshold and scaling window for the integer partitioning problem. we consider the problem of partitioning n integers chosen randomly between 1 and 2^m into two subsets such that the discrepancy, the absolute value of the difference of their sums, is minimized. a partition is called perfect if the optimum discrepancy is 0 when the sum of all n integers in the original set is even, or 1 when the sum is odd. parameterizing the random problem in terms of &kgr; = m/n, we prove that the problem has a sharp threshold at &kgr; = 1, in the sense that for &kgr; , there are many perfect partitions with probability tending to 1 as n \to \infty, while for 1, there are no perfect partitions with probability tending to 1. moreover, we show that the derivative of the so-called entropy is discontinuous at &kgr;=1.we also determine the scaling window about the transition point: &kgr;_n = 1 - (2n)^{-1}\log_2 n + &lgr;_n / n, by showing that the probability of a perfect partition tends to 0, 1, or some explicitly computable p(&lgr;) \in (0,1), depending on whether &lgr;_n tends to -\infty$, $\infty$, or $&lgr; \in (-\infty, \infty), respectively. for &lgr;_n \to -\infty fast enough, we show that the number of perfect partitions is gaussian in the limit. for &lgr;_n \to \infty, we prove that with high probability the optimum partition is unique, and that the optimum discrepancy is &thgr;(&lgr;_n). within the window, i.e., if |&lgr;_n| is bounded, we prove that the optimum discrepancy is bounded. both for &lgr;_n \to \infty and within the window, the limiting distribution of the (scaled) discrepancy
how to assemble tree machines (extended abstract) many researchers have proposed that ensembles of processing elements be organized as trees. this paper explores how large tree machines may be assembled efficiently from smaller components. a principal constraint that we consider is the limited number of external connections from an integrated circuit chip. we also explore the emerging capability of restructurable vlsi which allows a chip to be customized after fabrication. we give a linear-area chip of m processors and only four off-chip connections which can be used as the sole building block to construct an arbitrarily large complete binary tree. we also present a restructurable linear-area layout of m processors with o(lg m) pins that can realize an arbitrary binary tree. this layout is based on a solution to the graph-theoretic problem: given a tree in which each vertex is either black or white, determine how many edges need be cut in order to bisect the tree into equal-size components, each containing exactly half the black and half the white vertices.
solving fractional packing problems in (1/?) iterations. we adapt a method proposed by nesterov [16] to design an algorithm that computes ε-optimal solutions to fractional packing problems by solving o*(ε-1 √kn) separable convex quadratic programs, where k is the maximum number of non-zeros per row and n is the number of variables. we also show that the quadratic program can be approximated to any degree of accuracy by an appropriately defined piecewise-linear program. for the special case of the maximum concurrent flow problem on a graph g =(v,e) with rational capacities and demands we obtain an algorithm that computes an ε-optimal flow by solving o*(ε-1 k3/2|e| √|v| (log 1/ε+ lu + ld)) shortest path problems, where k is the number of commodities, and lu, ld are, respectively, the number of bits needed to store the capacities and demands. we also show that the complexity of computing a maximum multicommodity flow is o*(1/εlog2(1/ε)). in contrast, previous algorithms required ω(ε-2) iterations.
on the number of additions to compute specific polynomials (preliminary version) it is well known from the work of motzkin [55], belaga [58] and pan [66], that &ldquo;most&rdquo; nth degree polynomials p &egr; r[x] require about n/2 &times;, &divide; ops and n &plusmn; ops and that these bounds can always be achieved within the framework of preconditioned evaluation (1). more precisely, if p can be computed using less than [equation] &times;, &divide; or less than n &plusmn; ops, then the coefficients of p are algebraically dependent. the situation when counting &plusmn; ops with the potential of unlimited * ops, is not as clear. while the arguments based on algebraic dependence provide us with our best lower bounds thus far, a different approach of independent interest is taken in section iv. namely, we are able to show that the number of &plusmn; ops required to compute any p &egr; r[x] is bounded below by a function of the number of distinct real zeros of p. the potential (e.g., for producing non linear lower bounds) and limitations of this approach will be discussed.
a time-space tradeoff for sorting on a general sequential model of computation in a general sequential model of computation, no restrictions are placed on the way in which the computation may proceed, except parallel operations are not allowed. we show that in such an unrestricted environment time&bull;space&equil;&ohgr;(n2/log n) in order to sort n elements, each in the range [1,n2].
bounds for width two branching programs branching programs for the computation of boolean functions were first studied in the master's thesis of masek.7 in a rather straightforward manner they generalize the concept of a decision tree to a decision graph. let p be a branching program with edges labelled by the boolean variables, x1,...,xn and their complements. given an input a&equil;(a1,...,an) &egr; {0,1}n, program p computes a function value fp(a) in the following way. the nodes of p play the role of states or configurations. in particular, sinks play the role of final states or stopping configurations. the length of program p is the length of the longest path in p. following cobham,2capacity of the program is defined to be the logarithm to the base 2 of the number of nodes in p. length and capacity are lower bounds on time and space requirements for any reasonable model of sequential computation. clearly, any n-variable boolean function can be computed by a branching program of length n if the capacity is not constrained. since space lower bounds in excess of log n remain a fundamental challenge, we consider restricted branching programs in the hope of gaining insight into this problem and the closely related problem of time-space trade-offs.
size-time complexity of boolean networks for prefix computations the prefix problem consists of computing all the products x0x1 &hellip; xj (j = 0, &hellip; , n - 1), given a sequence x = (x0, x1, &hellip; , xn-1) of elements in a semigroup. in this paper we completely characterize the size-time complexity of computing prefixes with boolean networks, which are synchronized interconnections of boolean gates and one-bit storage devices. this complexity crucially depends upon two properties of the underlying semigroup, which we call cycle-freedom (no cycle of length greater than one in the cayley graph of the semigroup), and memory-induciveness (arbitrarily long products of semigroup elements are true functions of all their factors). a nontrivial characterization is given of non-memory-inducive semigroups as those whose recurrent subsemigroup (formed by the elements with self-loops in the cayley graph) is the direct product of a left-zero semigroup and a right-zero semigroup. denoting by s and t size and computation time, respectively, we have s = &thgr;((n/t)log(n/t)) for memory-inducive non-cycle-free semigroups, and s = &thgr;(n/t) for all other semigroups. we have t &egr; [&ohgr;(log n), &ogr;(n)] for all semigroups, with the exception of those whose recurrent subsemigroup is a right-zero semigroup, for which t &egr; [&ohgr;(1), &ogr;(n)]. the preceding results are also extended to the vlsi model of computation. area-time optimal circuits are obtained for both boundary and nonboundary i/o protocols.
proof of a conjecture of r. kannan r. kannan conjectured that every non-deterministic two-way finite automaton can be positionally simulated by a deterministic two-way finite automaton. the conjecture is proved here by reduction to a similar problem about finite semigroups. the method and the result are then generalized to alternating two-way finite automata.
adversarial queueing theory. we consider packet routing when packets are injected continuously into a network. we develop an adversarial theory of queuing aimed at addressing some of the restrictions inherent in probabilistic analysis and queuing theory based on time-invariant stochastic generation. we examine the stability of queuing networks and policies when the arrival process is adversarial, and provide some preliminary results in this direction. our approach sheds light on various queuing policies in simple networks, and paves the way for a systematic study of queuing with few or no probabilistic assumptions.
an optimal online algorithm for metrical task systems in practice, almost all dynamic systems require decisions to be made online, without full knowledge of their future impact on the system. we introduce a general model for the processing of sequences of tasks and develop a general online decision algorithm. we show that, for an important class of special cases, this algorithm is optimal among all online algorithms. specifically, a task system (s, d) for processing sequences of tasks consists of a set s of states and a cost matrix d where d(i, j) is the cost of changing from state i to state j (we assume that d satisfies the triangle inequality and all diagonal entries are o.) the cost of processing a given task depends on the state of the system. a schedule for a sequence t1, t2 &hellip; tk of tasks is a sequence s1, s2 &hellip; sk of states where si is the state in which ti is processed; the cost of a schedule is the sum of all task processing costs and state transition costs incurred. an online scheduling algorithm is one that chooses si only knowing t1 t2 &hellip; ti. such an algorithm operates within waste factor w if, on any input task sequence, its costs is within an additive constant of w times the optimal offline schedule cost. the online waste factor w(s, d) is the infirm waste factor of any online scheduling algorithm for (s, d). we show that w(s, d) = 2|s| - 1 for every task system in which d symmetric, and w(s, d) = &ogr;(|s|2) for every task system.
subquadratic approximation algorithms for clustering problems in high dimensional spaces. one of the central problems in information retrieval, data mining, computational biology, statistical analysis, computer vision, geographic analysis, pattern recognition, distributed protocols is the question of classification of data according to some clustering rule. often the data is noisy and even approximate classification is of extreme importance. the difficulty of such classification stems from the fact that usually the data has many incomparable attributes, and often results in the question of clustering problems in high dimensional spaces. since they require measuring distance between every pair of data points, standard algorithms for computing the exact clustering solutions use quadratic or &ldquo;nearly quadratic&rdquo; running time&semi; i.e., o(dn2&minus;&alpha;(d)) time where n is the number of data points, d is the dimension of the space and &alpha;(d) approaches 0 as d grows. in this paper, we show (for three fairly natural clustering rules) that computing an approximate solution can be done much more efficiently. more specifically, for agglomerative clustering (used, for example, in the alta vista&trade; search engine), for the clustering defined by sparse partitions, and for a clustering based on minimum spanning trees we derive randomized (1 + &epsi;) approximation algorithms with running times &otilde;(d2 n2&minus;&gamma;) where &gamma; > 0 depends only on the approximation parameter &epsi; and is independent of the dimension d.
how much can hardware help routing? we study the extent to which complex hardware can speed up routing. specifically, we consider the following questions. how much does adaptive routing improve over oblivious routing? how much does randomness help? how does it help if each node can have a large number of neighbors? what benefit is available if a node can send packets to several neighbors within a single time step? some of these features require complex networking hardware, and thus it is important to investigate whether the performance justifies the investment. by varying these hardware parameters, we obtain a hierarchy of time bounds for worst-case permutation routing. we develop a nearly complete taxonomy of the complexity of routing.
finding extremal polygons given n points in the plane, we present algorithms for finding maximum perimeter or area convex k-gons with vertices k of the given n points. our algorithms work in linear space and time o(knlg n + n lg 2n). for the special case k -&-equil; 3 we give o (nlgn) algorithms for these problems. several related issues are discussed.
the chip complexity of binary arithmetic the chip complexity of a computation is concerned with the chip area, a, and the time, t, required to perform the computation when implemented on a chip. an area-time product at&agr;,for &agr; &ge; 0, is used as a complexity measure. a particular value of &agr;, which is chosen by the user, reflects the relative importance between a and t. this paper derives lower and upper bounds on the area-time complexity for chips that implement binary arithmetic, assuming a model of computation which is intended to approximate, current and anticipated lsi or vlsi technology.
approximation techniques for utilitarian mechanism design. this paper deals with the design of efficiently computable incentive compatible, or truthful, mechanisms for combinatorial optimization problems with multi-parameter agents. we focus on approximation algorithms for np-hard mechanism design problems. these algorithms need to satisfy certain monotonicity properties to ensure truthfulness. since most of the known approximation techniques do not fulfill these properties, we study alternative techniques.our first contribution is a quite general method to transform a pseudopolynomial algorithm into a monotone fptas. this can be applied to various problems like, e.g., knapsack, constrained shortest path, or job scheduling with deadlines. for example, the monotone fptas for the knapsack problem gives a very efficient, truthful mechanism for single-minded multi-unit auctions. the best previous result for such auctions was a 2-approximation. in addition, we present a monotone ptas for the generalized assignment problem with any bounded number of parameters per agent.the most efficient way to solve packing integer programs (pips) is lp-based randomized rounding, which also is in general not monotone. we show that primal-dual greedy algorithms achieve almost the same approximation ratios for pips as randomized rounding. the advantage is that these algorithms are inherently monotone. this way, we can significantly improve the approximation ratios of truthful mechanisms for various fundamental mechanism design problems like single-minded combinatorial auctions (cas), unsplittable flow routing and multicast routing. our approximation algorithms can also be used for the winner determination in cas with general bidders specifying their bids through an oracle.
target shooting with programmed random variables letx1,...,xn be pairwise independent random variables of known (but not necessarily identical) distribution; we wish to select a subset of these whose sum will be as close as possible to some known target value t. conditions described below force the selections to be made by a primitive distributed system (similar to one considered by papadimitriou and yannakakis [2] in podc '91); here we are able to obtain a surprising amount of information about optimal solutions. the conditions are that each variable must be &ldquo;programmed&rdquo; in advance, joining the selected set according to its own value. thus, for example, one variable might be programmed to join just if its value lies between &agr; and &bgr;, while another is told to join regardless of its value. our object is to find a strategy, that is, a collection of programs, which minimizes the mean square error in approximating t. typical applications involve producing a steady flow of some commodity when supply is controlled at a multiplicity of random sources. it turns out that there is always an optimal strategy in which each xi is programmed to join if its value is between 0 and &thgr;i, for appropriate choice of thresholds &thgr;i. when the variables are identically distributed, we examine conditions under which the &thgr;i's must be equal. the case of uniform distributions on [0,1], for which the above conditions are not satisfied, is analyzed in detail, showing the rather bizarre behavior of the &thgr;i's which may take place in general as the target value is gradually changed. next, we analyze the problem in which the variables are permitted to contribute any part of themselves to the sum; here it turns out that in an optimal strategy each program will be of the form &ldquo;contribute the minimum of xi and &eegr;i&rdquo; with all the &eegr;i's equal in the i.i.d. case. finally, we show how the original target shooting problem can be generalized to a kind of load balancing, where variables are assigned to different buckets, each with its own target, and the penalty is a weighted sum of squared errors. the surprising result here is that when the weights are equal, an optimal solution assigns variables only according to their signs.
on the optimal evaluation of a set of bilinear forms although general theories are beginning to emerge in the area of automata based complexity theory, there are very few general methods or even general problem formulations in the area of arithmetic complexity. in this paper we propose and defend a general model for studying bilinear multiplication in order to provide a common framework for discussing a wide class of problems. at the heart of a number of problems in minimizing the number of multiplications required to perform a calculation is a problem in matrix algebra relating to the expansion of a given set of matrices as linear combinations of rank one matrices. in this paper we make a systematic attack on this problem and derive some general results which unify and extend numerous known results. among the new results given here to illustrate the strength of this approach is a new lower bound on the number of multiplications required for n by n matrix multiplication of 3n2-3n+1 which is independent of the subset of the reals with respect to which multiplication is regarded as free. an even sharper bound is obtained if this set is restricted to the integers.
on the limits of cache-obliviousness. in this paper, we present lower bounds for permuting and sorting in the cache-oblivious model. we prove that (1) i/o optimal cache-oblivious comparison based sorting is not possible without a tall cache assumption, and (2) there does not exist an i/o optimal cache-oblivious algorithm for permuting, not even in the presence of a tall cache assumption.our results for sorting show the existence of an inherent trade-off in the cache-oblivious model between the strength of the tall cache assumption and the overhead for the case m » b, and show that funnelsort and recursive binary mergesort are optimal algorithms in the sense that they attain this trade-off.
optimal finger search trees in the pointer machine. we develop a new finger search tree with worst-case constant update time in the pointer machine (pm) model of computation. this was a major problem in the field of data structures and was tantalizingly open for over 20 years, while many attempts by researchers were made to solve it. the result comes as a consequence of the innovative mechanism that guides the rebalancing operations, combined with incremental multiple splitting and fusion techniques over nodes.
trading space for time in undirected s-t connectivity aleliunas et al. [1] posed the following question: &ldquo;the reachability problem for undirected graphs can be solved in logspace and o(mn) time [m is the number of edges and n is the number of vertices] by a probabilistic algorithm that simulates a random walk, or in linear time and space by a conventional deterministic graph traversal algorithm. is there a spectrum of time-space trade-offs between these extremes?&rdquo; we answer this question in the affirmative for linear-sized graphs by presenting an algorithm which is faster than the random walk by a factor essentially proportional to the size of its workspace. for denser graphs, the algorithm is faster than the random walk but the speed-up factor is smaller.
the complexity of priority queue maintenance a notion of priority queue efficiency is defined, based on comparison counting. a good lower bound on the average and worst case number of comparisons is derived; several priority queue algorithms are exhibited which nearly attain the bound. it is shown that one of these algorithms, using binomial queues, can be characterized in a simple way based on the number and type of comparisons that it requires. the proof of this result involves an interesting problem on trees for which huffman's construction gives a solution.
kraft storage and access for list implementations (extended abstract) this paper is part of an investigation into efficient ways of implementing variable-length lists (see brown [1]). storage and access optimality are discussed from an information-theoretic viewpoint; in particular, we develop the notions of kraft storage and kraft access (see elias [4]). our attention here is restricted to the implementation of questions of the form: &ldquo;what is the ith element in the list?&rdquo; we derive consequences of achieving kraft storage and/or kraft access and then examine some common implementation schemes. in this abstract we shall give only an informal discussion of some basic concepts and results.
a representation for linear lists with movable fingers this paper describes a data structure which is useful for representing linear lists when the pattern of accesses to a list exhibits a (perhaps time-varying) locality of reference. the structure has many of the properties of the representation proposed by guibas, mccreight, plass, and roberts [4], but is substantially simpler and may be practical for lists of moderate size. the analysis of our structure includes a general treatment of the worst-case node splitting caused by consecutive insertions into a 2-3 tree.
on time-space classes and their relation to the theory of real addition a new lower bound on the computational complexity of the theory of real addition and several related theories is established: any decision procedure for these theories requires either space 2&egr;n or nondeterministic time 2&egr;n2 for some constant &egr; > o and infinitely many n. the proof is based on the families of languages tisp(t(n),s(n)) which can be recognized simultaneously in time t(n) and space s(n) and the conditions under which they form a hierarchy.
on the extended direct sum conjecture we consider the quadratic complexity of certain sets of quadratic forms. we study a classes of direct sums of quadratic forms. for these classes of problems we show that the complexity of one direct sum is the sum of the complexity of the summands and that every minimal quadratic algorithm for computing the direct sums is a direct-sum algorithm.
noise-tolerant distribution-free learning of general geometric concepts. we present an efficient algorithm for pac-learning a very general class of geometric concepts over r d for fixed d. more specifically, let t be any set of s halfspaces. let x =(x1, &hellip;, xd) be an arbitrary point in r d. with each t&isin;t we associate a boolean indicator function it(x) which is 1 if and only if x is in the halfspace t. the concept class, cds , that we study consists of all concepts formed by any boolean function over it1, &hellip;, its for ti &isin;t . this class is much more general than any geometric concept class known to be pac-learnable. our results can be extended easily to learn efficiently any boolean combination of a polynomial number of concepts selected from any concept class c over r given that the vc-dimension of c has dependence only on d and there is a polynomial time algorithm to determine if there is a concept from c consistent with a given set of labeled examples. we also present a statistical query version of our algorithm that can tolerate random classification noise. finally we present a generalization of the standard &egr;-net result of haussler and welzl [1987] and apply it to give an alternative noise-tolerant algorithm for d = 2 based on geometric subdivisions.
learning arithmetic read-once formulas a formula is read-once if each variable appears at most once in it. an arithmetic read-once formula is one in which the operators are addition, subtraction, multiplication, and division. we present polynomial time algorithm for exactly learning (or interpolating) arithmetic read-once formulas computing functions over a field. we present an algorithm that uses randomized membership queries (or substitutions) to identify such formulas over large finite fields and infinite fields. we also present a deterministic algorithm that uses equivalence queries as well as membership queries to identify arithmetic read-once formulas over small finite fields. we then non-constructively show the existence of deterministic membership query (interpolation) algorithms for arbitrary formulas over fields of characteristic 0 and for division-free formulas over large or infinite fields. our algorithms assume we are able to efficiently perform arithmetic operations on field elements and compute square roots in the field. it is shown that the ability to compute square roots is necessary, in the sense that the problem of computing n &ndash; 1 square roots in a field can be reduced to the problem of identifying an arithmetic formula over n variables in that field. our equivalence queries are of a slightly non-standard form, in which counterexamples are required to not be inputs on which the formula evaluates to 0/0. this assumption is shown to be necessary for fields of size o(n/log n), for which it is shown that there is no polynomial time identification algorithm that uses just membership and standard equivalence queries.
opt versus load in dynamic storage allocation. dynamic storage allocation is the problem of packing given axis-aligned rectangles into a horizontal strip of minimum height by sliding the rectangles vertically but not horizontally. where l= is the maximum sum of heights of rectangles that intersect any vertical line and opt is the minimum height of the enclosing strip, it is obvious that $\ensuremath{\text{\it opt}}\ge \ensuremath{\text{\it load}}$; previous work showed that $\ensuremath{\text{\it opt}}\le 3\cdot load. we continue the study of the relationship between opt and load, proving that opt=l+o((hmax/l)1/7)l, where hmax is the maximum job height. conversely, we prove that for any $\epsilon>0$, there exists a c>0 such that for all sufficiently large integers $h_{\max}$, there is a dynamic storage allocation instance with maximum job height $h_{\max}$, maximum load at most l, and $\ensuremath{\text{\it opt}}\geq l+c(h_{\max}/l)^{1/2+\epsilon}l$, for infinitely many integers l. en route, we construct several new polynomial-time approximation algorithms for dynamic storage allocation, including a $(2+\epsilon)$-approximation algorithm for the general case and polynomial-time approximation schemes for several natural special cases.
are bitvectors optimal? we study the it static membership problem: given a set s of at most n keys drawn from a universe u of size m, store it so that queries of the form "is u in s?" can be answered by making few accesses to the memory. we study schemes for this problem that use space close to the information theoretic lower bound of $\omega(n\log(\frac{m}{n}))$ bits and yet answer queries by reading a small number of bits of the memory.we show that, for $\epsilon > 0$, there is a scheme that stores $o(\frac{n}{\epsilon^2}\log m)$ bits and answers membership queries using a randomized algorithm that reads just one bit of memory and errs with probability at most $\epsilon$. we consider schemes that make no error for queries in s but are allowed to err with probability at most $\epsilon$ for queries not in s. we show that there exist such schemes that store $o((\frac{n}{\epsilon})^2 \log m)$ bits and answer queries using just one bitprobe. if multiple probes are allowed, then the number of bits stored can be reduced to $o(n^{1+\delta}\log m)$ for any $\delta > 0$. the schemes mentioned above are based on probabilistic constructions of set systems with small intersections.we show lower bounds that come close to our upper bounds (for a large range of n and $\epsilon$): schemes that answer queries with just one bitprobe and error probability $\epsilon$ must use $\omega(\frac{n}{\epsilon\log(1/\epsilon)} \log m)$ bits of storage; if the error is restricted to queries not in s, then the scheme must use $\omega(\frac{n^2}{\epsilon^2 \log (n/\epsilon)}\log m)$ bits of storage. we also consider deterministic schemes for the static membership problem and show tradeoffs between space and the number of probes.
the complexity of maximal constraint languages. many combinatorial search problems can be expressed as &ldquo;constraint satisfaction problems&rdquo; using an appropriate &ldquo;constraint language&rdquo;, that is, a set of relations over some fixed finite set of values. it is well-known that there is a trade-off between the expressive power of a constraint language and the complexity of the problems it can express. in the present paper we systematically study the complexity of all maximal constraint languages, that is, languages whose expressive power is just weaker than that of the language of all constraints. using the algebraic invariance properties of constraints, we exhibit a strong necessary condition for tractability of such a constraint language. moreover, we show that, at least for small sets of values, this condition is also sufficient.
counting complexity classes for numeric computations ii: algebraic and semialgebraic sets. we define counting classes #pr and #pc in the blum-shub-smale setting of computations over the real or complex numbers, respectively. the problems of counting the number of solutions of systems of polynomial inequalities over r, or of systems of polynomial equalities over c, respectively, turn out to be natural complete problems in these classes. we investigate to what extent the new counting classes capture the complexity of computing basic topological invariants of semialgebraic sets (over r) and algebraic sets (over c). we prove that the problem of computing the euler-yao characteristic of semialgebraic sets is fpr#pr-complete, and that the problem of computing the geometric degree of complex algebraic sets is fpc#pc-complete. we also define new counting complexity classes in the classical turing model via taking boolean parts of the classes above, and show that the problems to compute the euler characteristic and the geometric degree of (semi)algebraic sets given by integer polynomials are complete in these classes. we complement the results in the turing model by proving, for all k ∈ n, the fpspace-hardness of the problem of computing the kth betti number of the set of real zeros of a given integer polynomial. this holds with respect to the singular homology as well as for the borel-moore homology.
complexity problems in real time computation the study of computational complexity is continued under the additional requirement that the turing machines operate in real time. the work reported here is motivated by that of rabin [r] which asks implicitly about the computational power of n tape vs n+1 tape real time turing machines and that of hartmanis [h] who attempts a complexity measure for turing machines in terms of reversals. the first result concerns itself with n tape real time turing machines operating in a reversal bounded mode. a doubly infinite hierarchy (tapes-reversals) of classes of real time computable functions is shown to exist. the second result deals with n deterministic real time pushdown automata operating independently in parallel. it is shown that an increase in the number of pushdown automata operating in this manner always yields an increase in the computational power of the configuration.
on generalized finite automata and unrestricted generative grammars the notion of the graphical representation of a &ldquo;canonical derivation&rdquo; is extended to semi-thue systems; the graphs are called &ldquo;derivation structures.&rdquo; derivation structures are distinguished from phrase structures and generative grammars are distinguished from phrase structure grammars. the distinctions disappear only in the context free case. this paper considers generative grammars and derivation structures. (a subsequent paper will consider phrase-structure grammars and phrase structures.) the notion of generalized finite automaton (tree automaton) is extended to systems which process arbitrary labeled directed ordered acyclic graphs. we study a restriction of these automata which process derivation structures. analogous to the hierarchy of generative grammars, it is shown that there is a hierarchy of generalized finite automata which recognize the same languages. their structure-defining relationship is a generalization of the context free case, i.e., the structures recognized by the automata are projections of the structures defined by the grammars. the proofs give algorithms for constructing the automata from the grammars and the grammars from the automata.
a decomposition of multi-dimensional point-sets with applications to k-nearest-neighbors and n-body potential fields (preliminary version) we define the notion of a well-separated pair decomposition of points in d-dimensional space. we develop efficient sequential and parallel algorithms for computing such a decomposition. we apply the resulting decomposition to the efficient computation of k-nearest neighbors and n-body potential fields.
adaptively secure multi-party computation. a fundamental problem in designing secure multi-party protocols is how to deal with adaptive adversaries (i.e., adversaries that may choose the corrupted parties during the course of the computation), in a setting where the channels are insecure and secure communication is achieved by cryptographic primitives based on computational limitations of the adversary. it turns out that the power of an adaptive adversary is greatly affected by the amount of information gathered upon the corruption of the party. this amount of information models the extent to which uncorrupted parties are trusted to carry out instructions that cannot be externally verified, such as erasing records of past configurations. it has been shown that if the parties are trusted to erase such records, then adaptivity secure computation can be carried out using known primitives. however, this total trust in parties may be unrealistic in many scenarios. an important question, open since 1986, is whether adaptively secure multi-party computation can be carried out in the "insecure channel" setting, even if no party is thoroughly trusted. our main result is an affirmative resolution of this question for the case where even uncorrupted parties may deviate from the protocol by keeping record of all past configurations. we first propose a novel property of encryption protocols and show that if an encryption protocol enjoying this property is used, instead of a standard encryption scheme, then known constructions become adaptively secure. next we constructed, based on standard rsa assumption, an encryption protocol that enjoys this property. we also consider parties that, even when corrupted, may internally deviate from their protocols in arbitrary ways, as long as no external test can detect faulty behavior. we show that in this case no non-trivial protocol can be proven adaptively secure using black-box simulation. this holds even if the communication channels are totally secure.
bounding the power of preemption in randomized scheduling. we study on-line scheduling in overloaded systems. requests for jobs arrive one by one as time proceeds; the serving agents have limited capacity and not all requests can be served. still, we want to serve the "best" set of requests according to some criterion. in this situation, the ability to preempt (i.e., abort) jobs in service in order to make room for better jobs that would otherwise be rejected has proven to be of great help in some scenarios. we show that, surprisingly, in many other scenarios this is not the case. in a simple, generic model, we prove a polylogarithmic lower bound on the competitiveness of randomized and preemptive on-line scheduling algorithms. our bound applies to several recently studied problems. in fact, in certain scenarios our bound is quite close to the competitiveness achieved by known deterministic, nonpreemptive algorithms.
universally composable two-party and multi-party secure computation. we show how to securely realize any multi-party functionality in a universally composable way, regardless of the number of corrupted participants. that is, we consider a multi-party network with open communication and an adversary that can adaptively corrupt as many parties as it wishes. in this setting, our protocols allow any subset of the parties (with pairs of parties being a special case) to securely realize any desired functionality of their local inputs, and be guaranteed that security is preserved regardless of the activity in the rest of the network. this implies that security is preserved under concurrent composition of an unbounded number of protocol executions, it implies non-malleability with respect to arbitrary protocols, and more. our constructions are in the common reference string model and make general intractability assumptions.
some algebraic and geometric computations in pspace we give a pspace algorithm for determining the signs of multivariate polynomials at the common zeros of a system of polynomial equations. one of the consequences of this result is that the &ldquo;generalized movers' problem&rdquo; in robotics drops from exptime into pspace, and is therefore pspace-complete by a previous hardness result [rei]. we also show that the existential theory of the real numbers can be decided in pspace. other geometric problems that also drop into pspace include the 3-d euclidean shortest path problem, and the &ldquo;2-d asteroid avoidance problem&rdquo; described in [rs]. our method combines the theorem of the primitive element from classical algebra with a symbolic polynomial evaluation lemma from [bkr]. a decision problem involving several algebraic numbers is reduced to a problem involving a single algebraic number or primitive element, which rationally generates all the given algebraic numbers.
randomness conductors and constant-degree lossless expanders. the main concrete result of this paper is the first explicit construction of constant degree "lossless" expanders. in these graphs, the expansion factor is almost as large as possible: (1-eps)d, where d is the degree and eps is an arbitrarily small constant. such graphs are known to have many applications, e.g. in constructing networks that can implement fast distributed, routing algorithms, expander-based linear codes, various storage schemes, and hard tautologies for various proof systems. the best previous explicit constructions gave expansion factor d/2, which is too weak for many applications. the d/2 bound was obtained via the eigenvalue method, and is known that that method cannot give better bounds.the main abstract contribution of this paper is the introduction and initial study of "randomness conductors," a notion which generalizes extractors, expanders, condensers and other similar objects. in all these functions, certain guarantee on the input "entropy" is converted to a guarantee on the output "entropy". for historical reasons, specific objects used specific guarantees of different flavors (e.g., in expanders entropy means "support size", and their property is satisfied whenever input entropy is small. in contrast, in extractors, entropy means "min-entropy" and their property is satisfied whenever input entropy is large). we show that the flexibility afforded by the conductor definition leads to interesting combinations of these objects, and to better constructions such as those above.the main technical tool in these constructions is a natural generalization to conductors of the zig-zag graph product, previously defined for expanders and extractors.
exponential space complete problems for petri nets and commutative semigroups: preliminary report the uniform word problem for commutative semigroups (uwcs) is the problem of determining from any given finite set of defining relations and any pair of words, whether the words describe the same element in the commutative semigroup defined by the relations. the effective decidability of this classical algebraic problem was first explicitly noted by malcev [1958] and emilichev [1958], though in retrospect this result can be seen to be contained in the earlier work of k&ouml;nig [1903] and hermann [1926] on polynomial ideals.
graph pebbling with many free pebbles can be difficult the pebble game on directed acyclic graphs can be used to model the space-time tradeoff behavior of a straight-line algorithm (sla). in this game, the maximum number of pebbles used at any one time corresponds to the number of temporary registers available and is called space. the number of moves made to reach the outputs of the graph, or the time, corresponds to the number of operations required by the sla. in this paper, it is shown that there exist infinite families of constructible graphs on n nodes which possess an extreme time-space tradeoff. for a particular set of graphs, if space is restricted to fall in the range of &thgr;(log n) to &thgr;((@@@@n/log n)), then the pebbling time necessary is superpolynomial in n. this result is obtained by deriving a lower bound on time when extra space is restricted, and then diagonalizing over the amount of this space. an extension of this argument shows that the minimum space requirement for such constructible graph families can grow as any slowly increasing function of n.
uniformly erasable afl the purpose of this paper is to show that a number of well-known families have property (*). in particular, we prove that the family of context-free languages does indeed have this property. in addition, we show that several familiar subfamilies of the context-free languages, such as the one-counter languages, have property (*). finally, we show that there are families satisfying (*) which are not subfamilies of the context-free languages, for we prove that any family generated from one-letter languages has property (*), thereby extending a result of [17].
the theory of signature testing for vlsi several methods for testing vlsi chips can be classified as signature methods. both conventional and signature testing methods apply a number of test patterns to the inputs of the circuit. the difference is that a conventional method examines each output, while a signature method first accumulates the outputs in some data compression device, then examines the signature - the final contents of the accumulator - to see if it agrees with the signature produced by a good chip. signature testing methods have several advantages, but they run the risk that masking may occur. masking is said to occur if a faulty chip and a good chip behave differently on the test patterns, but the signatures are identical. when masking occurs, the signature testing method will incorrectly conclude that the chip is good, whereas a conventional method would discover that the chip is defective. this paper gives theoretical justification to the use of several signature testing techniques. we show that for these methods, the probability that masking will occur is small. an important difference between this and other work is that our results require very few assumptions about the behavior of faulty chips. they hold even in the presence of so-called correlated errors or even if the circuit were subject to sabatoge. when we speak of the probability of masking, we use the probabilistic approach of gill, rabin and others. that is, we introduce randomness into the testing method in a way which can be controlled by the designer. thus, one theorem assumes that the order of the input patterns - or the patterns themselves - is random; another assumes that the connections between the chip and the signature accumulator are made randomly, and a third assumes that the signature accumulator itself incorporates a random choice. most of the results of this paper use a particularly simple and practical signature accumulator based on a linear feedback shift register.
exact and approximate membership testers in this paper we consider the question of how much space is needed to represent a set. given a finite universe u and some subset v (called the vocabulary), an exact membership tester is a procedure that for each element s in u determines if s is in v. an approximate membership tester is allowed to make mistakes: we require that the membership tester correctly accepts every element of v, but we allow it to also accept a small fraction of the elements of u - v.
how to use expert advice. we analyze algorithms that predict a binary value by combining the predictions of several prediction strategies, called `experts''. our analysis is for worst-case situations, i.e., we make no assumptions about the way the sequence of bits to be predicted is generated. we measure the performance of the algorithm by the difference between the expected number of mistakes it makes on the bit sequence and the expected number of mistakes made by the best expert on this sequence, where the expectation is taken with respect to the randomization in the predictions. we show that the minimum achievable difference is on the order of the square root of the number of mistakes of the best expert, and we give efficient algorithms that achieve this. our upper and lower bounds have matching leading constants in most cases. we then show how this leads to certain kinds of pattern recognition/learning algorithms with performance bounds that improve on the best results currently known in this context. we also extend our analysis to the case in which log loss is used instead of the expected number of mistakes.
dynamic subgraph connectivity with geometric applications. inspired by dynamic connectivity applications in computational geometry, we consider a problem we call dynamic subgraph connectivity: design a data structure for an undirected graph $g=(v,e)$ and a subset of vertices $s \subseteq v$ to support insertions/deletions in $s$ and connectivity queries (are two vertices connected?) in the subgraph induced by $s$. we develop the first sublinear, fully dynamic method for this problem for general sparse graphs, using a combination of several simple ideas. our method requires $\widetilde o(|e|^{4\omega/(3\omega+3)})=o(|e|^{0.94})$ amortized update time, and $\widetilde o(|e|^{1/3})$ query time, after $\widetilde o(|e|^{(5\omega+1)/(3\omega+3)})$ preprocessing time, where &ohgr; is the matrix multiplication exponent and $\widetilde o$ hides polylogarithmic factors.
reversal complexity of counter machines it has long been known that deterministic 1-way counter machines recognize exactly all r.e. sets. here we investigate counter machines with general recursive bounds on counter reversals. our main result is that for bounds which are at least linear, counter reversal is polynomially related to turing machine time, for both 1-way and 2-way counter machines and in both the deterministic and the nondeterministic cases. this leads to natural characterizations of the classes p and np, and hence of the p &equil;? np question, on the counter machine model. we also establish reversal complexity hierarchies for counter machines, using a variety of techniques which include translation of turing machine time hierarchies, padding arguments as well as more ad hoc counting arguments.
a unified analysis of hot video schedulers. in this paper we consider the notion of relative competitive analysis, which is a simple generalization of the conventional competitive analysis and extra-resource analysis for on-line algorithms. we apply this analysis to study on-line schedulers for stream merging in two different video-on-demand (vod) systems, which are based on two common approaches, namely, piggybacking and skimming. our new analysis, in its simplest form, reveals a 3-competitive algorithm for stream merging based on skimming as well as piggybacking. this improves all previous results [4, 8]. we also show how to obtain guarantee on the performance improvement based on adding extra resources, and more interestingly, we provide a unified methodology to compare piggybacking and skimming. we believe that our result gives a clue to system designers for choosing desirable configurations.
abstract families of deterministic languages abstract families of (one-way) deterministic acceptors are formalized and shown to be characterized by families of languages closed under marked union, marked *, and inverse marked gsm mapping. the independence of these closure operations is also proved.
degrees of translatability and canonical forms in program schemas: part i we define a measure of the generality of the control structure of a program schema. this imposes a partial ordering on program schemas, and leads to a concept of the &ldquo;difficulty&rdquo; of a programming problem. in this sense there exists a &ldquo;hardest&rdquo; flowchart program, recursive program etc. some earlier proofs can also be simplified and/or clarified by this approach.
unbounded fan-in circuits and associative functions we consider the computation of finite semigroups using unbounded fan-in circuits. there are constant-depth, polynomial size circuits for semigroup product iff the semigroup does not contain a nontrivial group as a subset. in the case that the semigroup in fact does not contain a group, then for any primitive recursive function f, circuits of size o(nf&minus;1(n)) and constant depth exist for the semigroup product of n elements. the depth depends upon the choice of the primitive recursive function f. the circuits not only compute the semigroup product, but every prefix of the semigroup product. a consequence is that the same bounds apply for circuits computing the sum of two n-bit numbers.
multi-party protocols many different types of inter-process communication have been examined from a complexity point of view [sp, y]. we study a new model, in which a collection of processes p0, ..., pk&minus;1 that share information about a set of integers {a0, ...,ak&minus;1}, communicate to determine a 0-1 predicate of the numbers. in this new model, tremendous sharing of information is allowed, while no single party is given enough information to determine the predicate on its own. formally, each pi has access to every aj except for ai. for simplicity, we only allow the parties to communicate as follows.
computable queries for relational data bases (preliminary report) the concept of a &ldquo;reasonable&rdquo; query in a relational data base is investigated. we provide an abstract characterization of the class of queries which are computable, and define the completeness of a query language as the property of being precisely powerful enough to express the queries in this class. our main result is the completeness of a simple programming language which can be thought of as consisting of the relational algebra augmented with the power of iteration.
equations between regular terms and an application to process logic regular terms with the kleene operations &ugr;,;, and * can be thought of as operators on languages, generating other languages. an equation r1 &equil; r2 between two such terms is said to be satisfiable just in case languages exist which make this equation true. we show that the satisfiability problem even for *-free regular terms is undecidable. similar techniques are used to show that a very natural extension of the process logic of harel, kozen and parikh is undecidable.
embedded implicational dependencies and their inference problem it is shown that the general inference problem for embedded implicational dependencies (eids) is undecidable. for the more important case of finite inference (i.e., inference for finite data bases), the problem is not even recursively enumerable (r.e.); rather, it is complete in co-r.e. these results hold even for typed eids without equality, as well as for (untyped) template dependencies. the case for typed template dependencies remains open. the complexity of the inference problem for full dependencies has also been characterized - it is complete in exponential time for full implicational dependencies, and even for full typed template dependencies.
program schemas with equality we discuss the class of program schemas augmented with equality tests, that is, tests of equality between terms. in the first part of the paper we discuss and illustrate the &ldquo;power&rdquo; of equality tests. it turns out that the class of program schemas with equality is more powerful than the &ldquo;maximal&rdquo; classes of schemas suggested by other investigators. in the second part of the paper we discuss the decision problems of program schemas with equality. it is shown for example that while the decision problems normally considered for schemas (such as halting, divergence, equivalence, isomorphism and freedom) are solvable for ianov schemas, they all become unsolvable if general equality tests are added. we suggest, however, limited equality tests which can be added to certain subclasses of program schemas while preserving their solvable properties.
optimal implementation of conjunctive queries in relational data bases we define the class of conjunctive queries in relational data bases, and the generalized join operator on relations. the generalized join plays an important part in answering conjunctive queries, and it can be implemented using matrix multiplication. it is shown that while answering conjunctive queries is np complete (general queries are pspace complete), one can find an implementation that is within a constant of optimal. the main lemma used to show this is that each conjunctive query has a unique minimal equivalent query (much like minimal finite automata).
the analysis of two-dimensional patterns using picture processing grammars a method for the description of the hierarchical structure of two-dimensional pictures is proposed. the model is called picture-processing grammar. it can be regarded as an extension of phrase-structure grammars to the two-dimensional case. a picture analysis program is described. it accepts picture-processing grammar in tabular form and processes pictures using that grammar. experiments have been performed to analyze handwritten numerals, mathematical expressions and line drawings. some practical applications are discussed.
on the parallel computation of local operations the problem of parallel computation of local operations using five differently organized parallel processing machines (the sasd, sapd, pasd, pamd, and papd computers) is investigated. it is shown that for a special class of local operations, called window operations, there is a trade-off between computation time and machine complexity. it is also shown that for the pamd computer, the computation time increases as the degree of disorderliness of the local operation increases. in conclusion, in the designing of special-purpose parallel processing machines, we must take into consideration the degree of disorderliness of the operations to be performed.
similarity estimation techniques from rounding algorithms. (math) a locality sensitive hashing scheme is a distribution on a family $\f$ of hash functions operating on a collection of objects, such that for two objects x,y, prh&egr;f[h(x) = h(y)] = sim(x,y), where sim(x,y) &egr; [0,1] is some similarity function defined on the collection of objects. such a scheme leads to a compact representation of objects so that similarity of objects can be estimated from their compact sketches, and also leads to efficient algorithms for approximate nearest neighbor search and clustering. min-wise independent permutations provide an elegant construction of such a locality sensitive hashing scheme for a collection of subsets with the set similarity measure sim(a,b) = \frac{|a &pgr; b|}{|a &pgr b|}.(math) we show that rounding algorithms for lps and sdps used in the context of approximation algorithms can be viewed as locality sensitive hashing schemes for several interesting collections of objects. based on this insight, we construct new locality sensitive hashing schemes for:<ol>a collection of vectors with the distance between &rarr; \over u and &rarr; \over v measured by &oslash;(&rarr; \over u, &rarr; \over v)/&pgr;, where &oslash;(&rarr; \over u, &rarr; \over v) is the angle between &rarr; \over u) and &rarr; \over v). this yields a sketching scheme for estimating the cosine similarity measure between two vectors, as well as a simple alternative to minwise independent permutations for estimating set similarity.a collection of distributions on n points in a metric space, with distance between distributions measured by the earth mover distance (emd), (a popular distance measure in graphics and vision). our hash functions map distributions to points in the metric space such that, for distributions p and q, emd(p,q) &xie; eh&egr;\f [d(h(p),h(q))] &xie; o(log n log log n). emd(p, q).</ol>.
incremental clustering and dynamic information retrieval. motivated by applications such as document and image classification in information retrieval, we consider the problem of clustering dynamic point sets in a metric space. we propose a model called incremental clustering which is based on a careful analysis of the requirements of the information retrieval application, and which should also be useful in other applications. the goal is to efficiently maintain clusters of small diameter as new points are inserted. we analyze several natural greedy algorithms and demonstrate that they perform poorly. we propose new deterministic and randomized incremental clustering algorithms which have a provably good performance, and which we believe should also perform well in practice. we complement our positive results with lower bounds on the performance of incremental algorithms. finally, we consider the dual clustering problem where the clusters are of fixed diameter, and the goal is to minimize the number of clusters.
on non-uniform multicommodity buy-at-bulk network design. we study the multicommodity buy-at-bulk network design problem in which we seek to design a network that satisfies the demands between terminals from a given set of source-sink pairs. the key characteristic of this problem is the fact that the cost functions associated with the edges of the graph are sub-additive monotone and hence experience economies of scale. in the non-uniform case, each edge has its own cost function -- possibly different from other edges. special cases of this problem have been studied extensively: there are approximation algorithms when the edge cost functions are identical or when all source-sink pairs share the same source. we present the first non-trivial approximation algorithm for the general case. our algorithm is an extremely simple randomized greedy algorithm and has an approximation guarantee of exp(o√ln n ln ln n)) when the instance has at most n source-sink pairs with unit demands. in the case of general demands, this yields an approximation factor of exp(o √ln n ln ln n)), where n is the sum of all demands.
algorithms for capacitated vehicle routing. given n identical objects (pegs), placed at arbitrary initial locations, we consider the problem of transporting them efficiently to n target locations (slots) with a vehicle that can carry at most k pegs at a time. this problem is referred to as k-delivery tsp, and it is a generalization of the traveling salesman problem. we give a 5-approximation algorithm for the problem of minimizing the total distance traveled by the vehicle.there are two kinds of transportations possible---one that could drop pegs at intermediate locations and pick them up later in the route for delivery (preemptive) and one that transports pegs to their targets directly (nonpreemptive). in the former case, by exploiting the freedom to drop, one may be able to find a shorter delivery route. we construct a nonpreemptive tour that is within a factor 5 of the optimal preemptive tour. in addition we show that the ratio of the distances traveled by an optimal nonpreemptive tour versus a preemptive tour is bounded by 4.
approximating the smallest grammar: kolmogorov complexity in natural models. we consider the problem of finding the smallest context-free grammar that generates exactly one given string of length n. the size of this grammar is of theoretical interest as an efficiently computable variant of kolmogorov complexity. the problem is of practical importance in areas such as data compression and pattern extraction.the smallest grammar is known to be hard to approximate to within a constant factor, and an o(logn/log logn) approximation would require progress on a long-standing algebraic problem [10]. previously, the best proved approximation ratio was o(n1/2) for the bisection algorithm [8]. our main result is an exponential improvement of this ratio; we give an o(log (n/g*)) approximation algorithm, where g* is the size of the smallest grammar.we then consider other computable variants of kolomogorov complexity. in particular we give an o(log2 n) approximation for the smallest non-deterministic finite automaton with advice that produces a given string. we also apply our techniques to "advice-grammars" and "edit-grammars", two other natural models of string complexity.
near-optimal algorithms for unique games. unique games are constraint satisfaction problems that can be viewed as a generalization of max-cut to a larger domain size. the unique games conjecture states that it is hard to distinguish between instances of unique games where almost all constraints are satisfiable and those where almost none are satisfiable. it has been shown to imply a number of inapproximability results for fundamental problems that seem difficult to obtain by more standard complexity assumptions. thus, proving or refuting this conjecture is an important goal. we present significantly improved approximation algorithms for unique games. for instances with domain size k where the optimal solution satisfies 1-ε fraction of all constraints, our algorithms satisfy roughly k-ε/(2-ε) and 1- o(√εlog k) fraction of all constraints. our algorithms are based on rounding a natural semidefinite programming relaxation for the problem and their performance almost matches the integrality gap of this relaxation. our results are near optimal if the unique games conjecture is true, i.e. any improvement (beyond low order terms) would refute the conjecture.
better streaming algorithms for clustering problems. we study clustering problems in the streaming model, where the goal is to cluster a set of points by making one pass (or a few passes) over the data using a small amount of storage space. our main result is a randomized algorithm for the k--median problem which produces a constant factor approximation in one pass using storage space o(k poly log n). this is a significant improvement of the previous best algorithm which yielded a 2o(1/ε) approximation using o(nε) space. next we give a streaming algorithm for the k--median problem with an arbitrary distance function. we also study algorithms for clustering problems with outliers in the streaming model. here, we give bicriterion guarantees, producing constant factor approximations by increasing the allowed fraction of outliers slightly.
clustering to minimize the sum of cluster diameters. we study the problem of clustering points in a metric space so as to minimize the sum of cluster diameters or the sum of cluster radii. significantly improving on previous results, we present a primal-dual based constant factor approximation algorithm for this problem. we present a simple greedy algorithm that achieves a logarithmic approximation. this also applies when the distance function is asymmetric and the objective is to minimize the sum of cluster radii. the previous best-known result obtained a logarithmic approximation with a constant factor blowup in the number of clusters. we also obtain an incremental clustering algorithm that maintains a solution whose cost is at most a constant factor times that of optimal with a constant factor blowup in the number of clusters.
convex decompositions of polyhedra an important direction of research in computational geometry has been to find methods for decomposing complex structures into simpler components. in this paper, we examine the problem of decomposing a three-dimensional polyhedron p into a minimal number of convex pieces. letting n be the number of vertices in p and n the number of edges which exhibit a reflex angle (i.e. the notches of p), our main result is an o(nn3) time algorithm for computing a convex decomposition of p. the algorithm produces o(n2) convex parts, which is optimal in the worst case. in most situations where the problem arises (e.g. graphics, tool design, pattern recognition), the number of notches n seems greatly dominated by the number of vertices n; the algorithm is therefore viable in practice.
intersecting is easier than sorting this paper settles a long-standing open question of computational geometry: is it possible to compute all k intersections between n arbitrary line segments in time linear in k? we answer this question affirmatively by presenting the first algorithm with a running time of the form o(k + f(n)), where f is a subquadratic function of n. the function f we achieve is actually quasi-linear in n, which makes our algorithm the most efficient to date for each value of k. to obtain this result we must turn away from traditional, sweep-line-based schemes. instead, we introduce a new hierarchical strategy for dealing with segments without ever reducing the dimensionality of the problem. this framework is used to solve other related problems. in particular, we are able to present the first subquadratic algorithm for counting intersections (as opposed to reporting each of them explicitly), and we give the first optimal algorithm for computing the intersections of a line arrangement with a query segment. using duality arguments we also present an improved algorithm for a point enclosure problem.
decomposing a polygon into its convex parts a common operation in geometric computing is the decomposition of complex structures into more basic structures. since it is easier to apply most algorithms to triangles or arbitrary convex polygons, there is considerable interest in finding fast algorithms for such decompositions. we consider the problem of decomposing a simple (non-convex) polygon into the union of a minimal number of convex polygons. although the structure of the problem led to the conjecture that it was np-complete, we have been able to reach polynomial time bounded algorithms for exact solution as well as low degree polynomial time bounded algorithm/or approximation methods.
detection is easier than computation (extended abstract) perhaps the most important application of computer geometry involves determining whether a pair of convex objects intersect. this problem is well understood in a model of computation where the objects are given as input and their intersection is returned as output. however, for many applications, we may assume that the objects already exist within the computer and that the only output desired is a single piece of data giving a common point if the objects intersect or reporting no intersection if they are disjoint. for this problem, none of the previous lower bounds are valid and we propose algorithms requiring sublinear time for their solution in 2 and 3 dimensions.
the complexity of cutting convex polytopes throughout this paper, we use the term subdivision as a shorthand for &ldquo;a subdivision of e2 into convex regions&rdquo;. a subdivision is said to be of size n if it is made of n convex (open) regions, and it is of degree d if every region is adjacent to at most d other regions. we define the line span of a subdivision as the maximum number of regions which can be intersected by a single line (section 3).
lines in space-combinatorics, algorithms and applications we study combinatorial and algorithmic problems involving arrangements of n lines in 3-dimensional space, and then present applications of our results to a variety of problems on polyhedral terrains. our main results include: a tight &thgr;(n2) bound on the complexity of the space of all lines passing above all the n given lines (their &ldquo;upper envelope&rdquo;) and satisfying a certain orientation consistency constraint. a preprocessing procedure using near-quadratic time and storage that builds a structure supporting &ogr;(log n) time queries for testing if a line lies above all the given lines. an &ogr;(n4/3+&egr;) randomized expected time algorithm, for any fixed &egr; > 0, that tests the &ldquo;towering property&rdquo;: do n given red lines lie all above n given blue lines? a preprocessing procedure for a polyhedral terrain &sgr; with n edges, that uses near-quadratic time and storage and builds a structure supporting &ogr;(log2 n) time rayshooting queries for computing the first intersection of an arbitrary query ray with &sgr;. finding the smallest vertical distance between two disjoint polyhedral terrains with a total of n edges, in time &ogr;(n4/3+&egr;), for any &egr; > 0. computing the upper envelope (pointwise maximum) of two polyhedral terrains with a total of n edges, in time &ogr;(n1.5+&egr; + klog2 n), for any &egr; > 0, where &kgr; is the size of the output envelope. the tools used to obtain these results include pl&uuml;cker coordinates for lines in space, random sampling in geometric problems, and a new variant of segment trees.
lower bounds for intersection searching and fractional cascading in higher dimension. given an n-edge convex subdivision of the plane, is it possible to report its k intersections with a query line segment in o(k + polylog(n)) time, using subquadratic storage? if the query is a plane and the input is a polytope with n vertices, can one achieve o(k + polylog(n)) time with subcubic storage? does any convex polytope have a boundary dominant dobkin-kirkpatrick hierarchy? can fractional cascading be generalized to planar maps instead of linear lists? we prove that the answer to all of these questions is no, and we derive near-optimal solutions to these classical problems.
sublinear geometric algorithms. we initiate an investigation of sublinear algorithms for geometric problems in two and three dimensions. we give optimal algorithms for intersection detection of convex polygons and polyhedra, point location in two-dimensional delaunay triangulations and voronoi diagrams, and ray shooting in convex polyhedra, all of which run in time o(√n), where n is the size of the input. we also provide sublinear solutions for the approximate evaluation of the volume of a convex polytope and the length of the shortest path between two points on the boundary.
a model of computation for vlsi with related complexity results a new model of computation for vlsi, based on the assumption that time for propagating information is at least linear in the distance, is proposed. while accommodating for basic laws of physics, the model is designed to be general and technology independent. thus, from a complexity viewpoint, it is especially suited for deriving lower bounds and trade-offs. new results for a number of problems, including fan-in, transitive functions, matrix multiplication, and sorting are presented. as regards upper bounds, it must be noted that, because of communication costs, the model clearly favors regular and pipelined architectures (e.g., systolic arrays).
approximation schemes for preemptive weighted flow time. (math) we present the first approximation schemes for minimizing weighted flow time on a single machine with preemption. our first result is an algorithm that computes a (1+&egr;)-approximate solution for any instance of weighted flow time in o(no(ln w ln p/&egr;3)) time; here p is the ratio of maximum job processing time to minimum job processing time, and w is the ratio of maximum job weight to minimum job weight. this result directly gives a quasi-ptas for weighted flow time when p and w are poly-bounded, and a ptas when they are both o(1). we strengthen the former result to show that in order to get a quasi- ptas it suffices to have just one of p and w to be poly-bounded. our result provides strong evidence to the hypothesis that the weighted flow time problem has a ptas. we note that the problem is strongly np-hard even when p and w are o(1). we next consider two important special cases of weighted flow time, namely, when p is o(1) and w is arbitrary, and when the weight of a job is inverse of its processing time referred to as the stretch metric. for both of the above special cases we obtain a (1+&egr;)-approximation for any &egr; &rho; 0 by using a randomized partitioning scheme to reduce an arbitrary instance to several instances all of which have p and w bounded by a constant that depends only on &egr;.
the all-or-nothing multicommodity flow problem. we consider the all-or-nothing multicommodity flow problem in general graphs. we are given a capacitated undirected graph g=(v,e,u) and set of k pairs s1 t1, s2t2, …, sktk. each pair has a unit demand. the objective is to find a largest subset s of 1,2,…,k such that for every i in s we can send a flow of one unit between si and ti. note that this differs from the edge-disjoint path problem (edp) in that we do not insist on integral flows for the pairs. this problem is np-hard, and apx-hard, even on trees. for trees, a 2--approximation is known for the cardinality case and a 4--approximation for the weighted case. in this paper we build on a recent result of räcke on low congestion oblivious routing in undirected graphs to obtain a poly-logarithmic approximation for the all-or-nothing problem in general undirected graphs. the best previous known approximation for all-or-nothing flow problem was o(min(n<2/3, √m)), the same as that for edp. our algorithm extends to the case where each pair siti has a demand di associated with it and we need to completely route di to get credit for pair i. we also consider the online admission control version where pairs arrive online and the algorithm has to decide immediately on its arrival whether to accept it or not. we obtain a randomized algorithm with a competitive ratio that is similar to the approximation ratio for the offline algorithm.
multicommodity flow, well-linked terminals, and routing problems. we study multicommodity routing problems in both edge and node capacitated undirected graphs. the input to each problem is a capacitated graph g=(v,e) and a set τ of node pairs. in the simplest setting, the goal is to route a unit of flow for as many pairs as possible subject to the edge (node) capacity constraints. if the flow for a routed pair is required to be along a single path, it is the well-studied disjoint paths problem. if we allow fractional routings of the flow, it is known as the all-or-nothing flow problem. the nodes in τ are referred to as terminals.in recent work [8,9], the authors obtained the first poly-logarithmic approximation algorithms for some edge routing problems. a key idea in these algorithms is to decompose an instance into a collection of instances in which the terminals are well-linked. informally speaking, a set of nodes is well-linked in a graph if it does not have small separators. a decomposition into well-linked instances was previously achieved in [8] via räcke's hierarchical graph decomposition for oblivious routing [32]. in this paper, we design a simple new decomposition algorithm that is based on computing sparse cuts in a graph. our new algorithm improves the earlier results for edge routing problems. another important advantage of the algorithm is that it also applies to node-capacitated problems. we note that for oblivious routing with node capacities, an ω√n) lower bound is known on the congestion [18], and hence the oblivious routing approach cannot yield poly-logarithmic bounds for well-linked decompositions. using the new decomposition, we obtain a poly-logarithmic approximation for the node capacitated all-or-nothing flow problem in general graphs and node-disjoint path problem in planar graphs with o(1) congestion. we also show that the flow-cut gap for product multicommodity flows in node capacitated planar graphs is o(1), improving upon the o(log n) bound from [28].
edge-disjoint paths in planar graphs with constant congestion. we study the maximum edge-disjoint paths problem in undirected planar graphs: given a graph $g$ and node pairs (demands) $s_1t_1$, $s_2t_2$, $\dots$, $s_kt_k$, the goal is to maximize the number of demands that can be connected (routed) by edge-disjoint paths. the natural multicommodity flow relaxation has an $\omega(\sqrt{n})$ integrality gap, where $n$ is the number of nodes in $g$. motivated by this, we consider solutions with small constant congestion $c>1$, that is, solutions in which up to $c$ paths are allowed to use an edge (alternatively, each edge has a capacity of $c$). in previous work we obtained an $o(\log n)$ approximation with congestion 2 via the flow relaxation. this was based on a method of decomposing into well-linked subproblems. in this paper we obtain an $o(1)$ approximation with congestion 4. to obtain this improvement we develop an alternative decomposition that is specific to planar graphs. the decomposition produces instances that we call okamura-seymour (os) instances. these have the property that all terminals lie on a single face. another ingredient we develop is a constant factor approximation for the all-or-nothing flow problem on os instances via the flow relaxation.
algorithms for minimizing weighted flow time. we study the problem of minimizing weighted flow time on a single machine in the preemptive setting. we present an o(\log^2 p)-competitive semi-online algorithm where p is the ratio of the maximum and minimum processing times of jobs in the system. in the offline setting we show that a (2+\eps)-approximation is achievable in quasi-polynomial time. these are the first non-trivial results for the weighted versions of minimizing flow time. for multiple machines we show that no competitive randomized online algorithm exists for weighted flow time. we also present an improved online algorithm for minimizing total stretch (a special case of weighted flow time) on multiple machines.
on algorithms for discrete and approximate brouwer fixed points. we study the algorithmic complexity of the discrete fixed point problem and develop an asymptotic matching bound for a cube in any constantly bounded finite dimension. to obtain our upper bound, we derive a new fixed point theorem, based on a novel characterization of boundary conditions for the existence of fixed points.in addition, exploring a linkage with the approximation problem of the continuous fixed point problem, we obtain asymptotic matching bounds for complexity of the approximate brouwer fixed point problem in the continuous case for lipschitz functions that close a previous exponential gap. it settles a fifteen years old open problem of hirsch, papadimitriou and vavasis by improving both the upper and lower bounds.our new characterization for existence of a fixed point is also applicable to functions defined on non-convex domain and makes it a potentially useful tool for design and analysis of algorithms for fixed points in general domain.
linear fpt reductions and computational lower bounds. we develop new techniques for deriving very strong computational lower bounds for a class of well-known np-hard problems, including weighted satisfiability, dominating set, hitting set, set cover, clique, and independent set. for example, although a trivial enumeration can easily test in time o(nk) if a given graph of n vertices has a clique of size k, we prove that unless an unlikely collapse occurs in parameterized complexity theory, the problem is not solvable in time f(k) no(k) for any function f, even if we restrict the parameter value k to be bounded by an arbitrarily small function of n. under the same assumption, we prove that even if we restrict the parameter values k to be θ(μ(n)) for any reasonable function μ, no algorithm of running time no(k) can test if a graph of n vertices has a clique of size k. similar strong lower bounds are also derived for other problems in the above class. our techniques can be extended to derive computational lower bounds on approximation algorithms for np-hard optimization problems. for example, we prove that the np-hard distinguishing substring selection problem, for which a polynomial time approximation scheme has been recently developed, has no polynomial time approximation schemes of running time f(1/ε)no(1/ε) for any function f unless an unlikely collapse occurs in parameterized complexity theory.
reducing randomness via irrational numbers. we propose a general methodology for testing whether a given polynomial with integer coefficients is identically zero. the methodology evaluates the polynomial at efficiently computable approximations of suitable irrational points. in contrast to the classical technique of demillo, lipton, schwartz, and zippel, this methodology can decrease the error probability by increasing the precision of the approximations instead of using more random bits. consequently, randomized algorithms that use the classical technique can generally be improved using the new methodology. to demonstrate the methodology, we discuss two nontrivial applications. the first is to decide whether a graph has a perfect matching in parallel. our new nc algorithm uses fewer random bits while doing less work than the previously best nc algorithm by chari, rohatgi, and srinivasan. the second application is to test the equality of two multisets of integers. our new algorithm improves upon the previously best algorithms by blum and kannan and can speed up their checking algorithm for sorting programs on a large range of inputs.
(almost) tight bounds and existence theorems for confluent flows. a flow is said to be confluent if at any node all the flow leaves along a single edge. given a directed graph g with k sinks and non-negative demands on all the nodes of g, we consider the problem of determining a confluent flow that routes every node demand to some sink such that the maximum congestion at a sink is minimized. confluent flows arise in a variety of application areas, most notably in networking; in fact, most flows in the internet are confluent since internet routing is destination based.we present near-tight approximation algorithms, hardness results, and existence theorems for confluent flows. the main result of this paper is a polynomial-time algorithm for determining a confluent flow with congestion at most 1 + ln(k) in g, if g admits a splittable flow with congestion at most 1. we complement this result in two directions. first, we present a graph g that admits a splittable flow with congestion at most 1, yet no confluent flow with congestion smaller than hk, thus establishing tight upper and lower bounds to within an additive constant less than 1. second, we show that it is np-hard to approximate the congestion of an optimal confluent flow to within a factor of (lg k)/2, thus resolving the polynomial-time approximability to within a multiplicative constant. we also consider a demand maximization version of the problem. we show that if g admits a splittable flow of congestion at most 1, then a variant of the congestion minimization algorithm yields a confluent flow in g with congestion at most 1 that satisfies 1/3 fraction of total demand.we show that the gap between confluent flows and splittable flows is much smaller, if the underlying graph were k connected. in particular, we prove that k-connected graphs with k sinks admit confluent flows of congestion less than c + dmax, where c is the congestion of the best splittable flow, and dmax is the maximum demand of any node in g. the proof of this existence theorem is non-constructive and relies on topological techniques introduced in [16].
optimal buy-and-hold strategies for financial markets with bounded daily returns. in the context of investment analysis, we formulate an abstract online computing problem called a planning game and develop general tools for solving such a game. we then use the tools to investigate a practical buy-and-hold trading problem faced by long-term investors in stocks. we obtain the unique optimal static online algorithm for the problem and determine its exact competitive ratio. we also compare this algorithm with the popular dollar averaging strategy using actual market data.
meet and merge: approximation algorithms for confluent flows. in this paper, we investigate the problem of determining confluent flows with minimum congestion. a flow of a given commodity is said to be confluent if at any node all the flow of the commodity departs along a single edge. confluent flows appear in a variety of application areas ranging from wireless communications to evacuations; in fact, most flows in the internet are confluent since internet routing is destination based. we consider the single-commodity confluent flow problem, in which we are given an n-node directed network g, a sink t and supplies at each node, and the goal is to find a confluent flow that routes all the supplies to the sink while minimizing the maximum edge congestion. our main result is an approximation algorithm, based on randomized rounding, for the special case when all the supplies are uniform; the algorithm finds a confluent flow with edge (and node) congestion o(c^2log^3n), where c is the node congestion of a splittable flow with minimum node congestion; here the node congestion of a flow is the maximum, over all nodes other than t, of the congestion at a node. this implies an o@?(n) approximation algorithm for the problem with uniform supplies. our result relies on the analysis of a natural probabilistic process defined on directed acyclic graphs, that may be of independent interest. for tree networks, we present an optimal polynomial-time algorithm for a multi-sink generalization of the above confluent flow problem. we show that it is np-hard to approximate the congestion of the optimal confluent flow for general networks to within a factor of 32. we also establish a lower bound on the gap between confluent and splittable flows, and consider multi-commodity and fractional versions of confluent flow problems.
approximation algorithms for network design with metric costs. we study undirected networks with edge costs that satisfy the triangle inequality. let $n$ denote the number of nodes. we present an $o(1)$-approximation algorithm for a generalization of the metric-cost subset $k$-node-connectivity problem. our approximation guarantee is proved via lower bounds that apply to the simple edge-connectivity version of the problem, where the requirements are for edge-disjoint paths rather than for openly node-disjoint paths. a corollary is that, for metric costs and for each $k=1,2,\dots,n-1$, there exists a $k$-node connected graph whose cost is within a factor of ${ 22\/}$ of the cost of any simple $k$-edge connected graph. based on our $o(1)$-approximation algorithm, we present an $o(\log r_{\max})$-approximation algorithm for the metric-cost node-connectivity survivable network design problem, where $r_{\max}$ denotes the maximum requirement over all pairs of nodes. our results contrast with the case of edge costs of 0 or 1, where kortsarz, krauthgamer, and lee. [siam j. comput., 33 (2004), pp. 704-720] recently proved, assuming np$\nsubseteq\;$dtime($n^{polylog(n)}$), a hardness-of-approximation lower bound of $2^{\log^{1-\epsilon}n}$ for the subset $k$-node-connectivity problem, where $\epsilon$ denotes a small positive number.
approximation algorithms for minimum-cost k-vertex connected subgraphs. (math) we present two new algorithms for the problem of finding a minimum-cost k-vertex connected spanning subgraph. the first algorithm works on undirected graphs with at least 6k2 vertices and achieves an approximation factor of 6 times the kth harmonic number, which is $o(\log k)$. the second algorithm works on directed and undirected graphs. it gives an $o(\sqrt{ n /\keps})$-approximation algorithm for any $\keps > 0$ and $k \le (1-\keps)n$. the latter algorithm also extends to other problems in network design with vertex connectivity requirements. our main tools are setpair relaxations, a theorem of mader's (in the undirected case) and iterative rounding (general case).
unique normal forms in term rewriting systems with repeated variables a term rewriting system is a finite set of axiom schemata of the form a@@@@b where a and b are terms that contain variables. an important question for such systems is whether normal forms are unique (i.e. each term has at most one normal form). for schemata without repeated variables (i.e. no variable is repeated on the left side of an axiom schema), o'donnell [o'd] has given sufficient conditions for the confluence property (church-rosser property), a stronger property than unique normal forms. klop [klo] has shown that the confluence property does not necessarily hold in these systems when repeated variables are allowed. this paper shows that normal forms are unique in such systems despite the lack of the confluence property.
clifford algebras and approximating the permanent. we study approximation algorithms for the permanent of an n × n (0,1) matrix a based on the following simple idea: obtain a random matrix b by replacing each 1-entry of a independently by ±e, where e is a random basis element of a suitable algebra; then output |det(b)|2. this estimator is always unbiased, but it may have exponentially large variance. in our first main result we show that, if we take the algebra to be a clifford algebra of dimension polynomial in n, then we get an estimator with small variance. hence, only a constant number of trials suffices to estimate the permanent to good accuracy. the idea of using clifford algebras is a natural extension of earlier work by godsil and gutman, karmarkar et al., and barvinok, who used the real numbers, complex numbers and quaternions, respectively. the above result implies that, in principle, this approach gives a fully-polynomial randomized approximation scheme for the permanent, provided |det(b)|2 can be efficiently computed in the clifford algebras. since these algebras are noncommutative it is not clear how to do this. however, our second main result shows how to compute in polynomial time an estimator with the same mean and variance over the 4-dimensional algebra (which is the quaternions, and is non-commutative); in addition to providing some hope that the computations can be performed in higher dimensions, this quaternion algorithm provides an exponential improvement in the variance over that of the 2-dimensional complex version studied by karmarkar et al.
exponential algorithmic speedup by a quantum walk. we construct a black box graph traversal problem that can be solved exponentially faster on a quantum computer than on a classical computer. the quantum algorithm is based on a continuous time quantum walk, and thus employs a different technique from previous quantum algorithms based on quantum fourier transforms. we show how to implement the quantum walk efficiently in our black box setting. we then show how this quantum walk solves our problem by rapidly traversing a graph. finally, we prove that no classical algorithm can solve the problem in subexponential time.
cooperative asynchronous update of shared memory. the write-all problem for an asynchronous shared-memory system has the objective for the processes to update the contents of a set of shared registers, while minimizing the total number of read and write operations. first abstracted by kanellakis and shvartsman [12], write-all is among the standard problems in distributed computing. the model consists of $n$ asynchronous processes and n registers, where every process can read and write to any register. processes may fail by crashing. the most efficient previously known deterministic algorithm performs o(n1+ε) reads and writes, for an arbitrary fixed constant ε>0, and is due to anderson and woll [4]. this paper presents a new deterministic algorithm that performs o(n polylog n) read/write operations, thus improving the best previously known upper bound from polynomial to polylogarithmic in the average number of read/write operations per process. using an approach to store and retrieve information about progress made in auxiliary registers, the novelty of the new algorithm is in using a family of multi-partite graphs with expansion properties to structure a set of registers as a graph and then have each asynchronous process explore a part of the graph according to its pattern of traversals. an explicit instantiation of our write-all algorithm, based on best-known polynomial-time constructions of lossless expanders and a-expanding graphs, performs n • 2o(log3 log n) reads and writes. in this explicit solution to write-all, the processes perform asymptotically less read/write operations than the most efficient non-explicit solution known before.
collective asynchronous reading with polylogarithmic worst-case overhead. the collect problem for an asynchronous shared-memory system has the objective for the processors to learn all values of a collection of shared registers, while minimizing the total number of read and write operations. first abstracted by saks, shavit, and woll [37], collect is among the standard problems in distributed computing, the model consists of $n$ asynchronous processes, each with a single-writer multi-reader register of a polynomial capacity. the best previously known deterministic solution performs o(n3/2log n) reads and writes, and it is due to ajtai, aspnes, dwork, and waarts [3]. this paper presents a new deterministic algorithm that performs o(n log7 n) read/write operations, thus substantially improving the best previous upper bound. using an approach based on epidemic rumor-spreading, the novelty of the new algorithm is in using a family of expander graphs and ensuring that each of the successive groups of processes collect and propagate sufficiently many rumors to the next group. the algorithm is adapted to the repeatable collect problem, which is an on-line version. the competitive latency of the new algorithm is o(log7 n) vs. the much higher competitive latency o(√nlog n) given in [3]. a result of independent interest in this paper abstracts a gossiping game that is played on a graph and that gives its payoff in terms of expansion.
pricing for fairness: distributed resource allocation for multiple objectives. in this paper, we present a simple distributed algorithm for resource allocation which simultaneously approximates the optimum value for a large class of objective functions. in particular, we consider the class of canonical utility functions&#x00a0;u that are symmetric, non-decreasing, concave, and satisfy&#x00a0;u(0) = 0. our distributed algorithm is based on primal-dual updates. we prove that this algorithm is an&#x00a0;o(log&#x2009;&#x03c1;)-approximation for all canonical utility functions simultaneously, i.e. without any knowledge of &#x00a0;u. the algorithm needs at most&#x00a0;o(log&#x2009;2 &#x03c1;) iterations where &#x00a0;&#x03c1; is the biggest one among the number of flows, the number of edges, and the ratio between the maximum capacity and the minimum capacity of the edges in the network. this result is refined for multi-path routing problem, and also extended to a natural pricing mechanism that results in a simple and practical protocol for bandwidth allocation in a network.
efficient fault tolerant algorithms for resource allocation in distributed systems solutions to resource allocation problems in distributed systems are examined with respect to the measures of response time, message complexity, and failure locality. response time measures the time it takes for an algorithm to respond to the requests of a process, message complexity measures the number of messages sent and received by a process, and failure locality characterizes the size of the network that is affected by the failure of a single process. an algorithm that achieves a constant failure locality of four along with a quadratic response time and a quadratic message complexity is presented.
the price of anarchy of finite congestion games. we consider the price of anarchy of pure nash equilibria in congestion games with linear latency functions. for asymmetric games, the price of anarchy of maximum social cost is θ(√n), where n is the number of players. for all other cases of symmetric or asymmetric games and for both maximum and average social cost, the price of anarchy is 5/2. we extend the results to latency functions that are polynomials of bounded degree. we also extend some of the results to mixed nash equilibria.
self-organizing sequential search and hilbert's inequalities in this paper we describe a general technique which can be used to solve an old problem in analyzing self-organizing sequential search. we prove that the average time required for the move-to-front heuristic is no more than &pgr;/2 times that of the optimal order and this bound is best possible. hilbert's inequalities will be used to derive large classes of inequalities some of which can be applied to obtain tight worst-case bounds for several self-organizing heuristics.
asymmetric k-center is log -hard to approximate. in the asymmetric k-center problem, the input is an integer k and a complete digraph over n points together with a distance function obeying the directed triangle inequality. the goal is to choose a set of k points to serve as centers and to assign all the points to the centers, so that the maximum distance of any point to its center is as small as possible. we show that the asymmetric k-center problem is hard to approximate up to a factor of log* n - θ(1) unless np ⊆ dtime(nlog log n). since an o(log* n)-approximation algorithm is known for this problem, this essentially resolves the approximability of this problem. this is the first natural problem whose approximability threshold does not polynomially relate to the known approximation classes. we also resolve the approximability threshold of the metric k-center problem with costs.
hardness of cut problems in directed graphs. we study the approximability of the multicut and the (non-bipartite) sparsest cut problems in directed graphs. in the multicut problem, we are a given a graph g along with k source-sink pairs, and the goal is to find a smallest subset of edges whose deletion separates all source-sink pairs. the sparsest cut problem has the same input, but the goal is to find a subset of edges to delete so as to minimize the ratio of deleted edges to the number of source-sink pairs that are separated by this deletion. study of algorithms for cut problems is intimately connected to the dual notion of flows in networks, and many approximation algorithms for cut problems use a flow solution as a starting point. the best known approximation algorithm for directed multicut is based on this approach and gives an o(√n)-approximation. on the other hand, the gap between the maximum multicommodity flow and the minimum multicut is known to be ω(min(k , log n)). while this flow-cut gap may be interpreted as an evidence of inherent difficulty in designing good approximation algorithms for directed multicut, the strongest hardness result known is an apx-hardness. even assuming the unique games conjecture, only an ω(1)-hardness is known. similar bounds hold for the directed sparsest cut problem.our main result is that directed multicut is ω(log n / log log n)-hard to approximate unless np ⊆ dtime (npolylog n). we show that this hardness result holds even when we allow a bicriteria relaxation, where the approximate solution is required to separate only a constant fraction of the pairs. this bicriteria hardness allows us to infer an ω(log n / log log n)-hardness for the directed (non-bipartite) sparsest cut problem.
new hardness results for congestion minimization and machine scheduling. we study the approximability of two natural np-hard problems. the first problem is congestion minimization in directed networks. we are given a directed capacitated graph and a set of source-sink pairs. the goal is to route all pairs with minimum congestion on the network edges. a special well-studied case of this problem is the edge-disjoint paths problem, where all edges have unit capacities. the second problem is discrete machine scheduling, where we are given a set of jobs, and for each job a list of intervals in which it can be scheduled. the goal is to find the smallest number of machines on which all jobs can be scheduled, such that no two jobs assigned to the same machine overlap. both problems are known to be o(log n/log log n)-approximable via the randomized rounding technique of raghavan and thompson. however, until recently, only a max snp hardness was known for each problem. we make some progress in closing this gap by showing that both problem are ω(log log n)-hard to approximate unless np ⊆ dtime(no(log log log n)). our hardness proof for congestion minimization holds even for the special case of the edge-disjoint paths problem.
a new strategy for querying priced information. this paper focuses on competitive function evaluation in the context of computing with priced information. a function f is given together with a cost cx for each variable x of f. the cost cx has to be paid to read the value of x. the problem is to design algorithms that query the values of the variables sequentially in order to compute the function while trying to minimize the total cost incurred. competitive analysis is employed to evaluate the performance of the algorithms. we describe a novel approach for devising efficient algorithms in this setting. we apply our approach to several classes of functions which have been studied in the literature of computing with priced information. in all cases considered, our approach provides algorithms that achieve better bounds than the best known algorithm for the same class of functions.more precisely, for the class of monotone boolean functions, we give a polynomial time algorithm with extremal competitiveness (k+l - √ min(k,l)) where k (l) denotes the minimum number of variables that one must read, in the worst case, in order to prove that the function under consideration evaluates to 1 (0). this dramatically improves upon the best known result which is an exponential time 2 max(k, l)-competitive algorithm. for the subclass of monotone boolean functions known as threshold trees we further improve our bounds and give a polynomial time algorithm with extremal competitive ratio 1.618 max(k, l).we then apply our methodology to classes of non-boolean functions. we consider the case of the so called game trees. we improve upon previously published results for this class of functions providing a polynomial time algorithm with extremal competitive ratio 1.5 γ(f), where γ(f) is a lower bound on the extremal competitive ratio of any deterministic algorithm.finally, we consider the case when f is the function min (minimum). in this case, we are able to determine the optimal competitiveness for the problem. in fact we provide an algorithm with an (n-2)-competitive ratio, which matches the known lower bound.
a probabilistic algorithm for the post office problem the post office problem is the following: points in d-dimensional space, so that given an arbitrary point p, the closest points in s to p can be found quickly. we consider the case of this problem where the euclidean norm is the measure of distance. the previous best algorithm for this problem for d>2 requires &ogr;(n2d+1) preprocessing time to build a data structure allowing an &ogr;(log n query time. we will show that a data structure can be built in expected &ogr;(n(d-1)(1+k)) time, for any fixed k;>&ogr;, so that closest-point queries can be answered in &ogr;(log n) worstcase time. (the constant factors depend on d and k.) the algorithm employs random sampling, so the expected time holds for any set of points. a variant of this algorithm (for the variant problem where only one closest point of s to the query point is desired) requires &ogr;(n&lceil;d/2&rceil;) &ogr;(n&lceil;d/2&rceil;) preprocessing time for &ogr;(nt) worst-case query time, for any fixed &egr;>0. these results approach the &ohgr;(n&lceil;d/2&rceil;) preprocessing time required for any algorithm constructing the voronoi diagram of the input points. implementation of these algorithms requires not too much more than a random sampling procedure and a procedure for constructing the voronoi diagram of that random sample.
market equilibrium via the excess demand function. we consider the problem of computing market equilibria and show three results. (i) for exchange economies satisfying weak gross substitutability we analyze a simple discrete version of tâtonnement, and prove that it converges to an approximate equilibrium in polynomial time. this is the first polynomial-time approximation scheme based on a simple atonnement process. it was only recently shown, using vastly more sophisticated techniques, that an approximate equilibrium for this class of economies is computable in polynomial time. (ii) for fisher's model, we extend the frontier of tractability by developing a polynomial-time algorithm that applies well beyond the homothetic case and the gross substitutes case. (iii) for production economies, we obtain the first polynomial-time algorithms for computing an approximate equilibrium when the consumers' side of the economy satisfies weak gross substitutability and the producers' side is restricted to positive production.
polylog-time and near-linear work approximation scheme for undirected shortest paths. shortest paths computations constitute one of the most fundamental network problems. nonetheless, known parallel shortest-paths algorithms are generally inefficient: they perform significantly more work (product of time and processors) than their sequential counterparts. this gap, known in the literature as the &ldquo;transitive closure bottleneck,&rdquo; poses a long-standing open problem. our main result is an omne0+s m+n1+e0 work polylog-time randomized algorithm that computes paths within (1 + o(1/polylog n) of shortest from s source nodes to all other nodes in weighted undirected networks with n nodes and m edges (for any fixed &egr;0>0). this work bound nearly matches the o&d5;sm sequential time. in contrast, previous polylog-time algorithms required nearly mino&d5; n3,o&d5; m2 work (even when s=1), and previous near-linear work algorithms required near-o(n) time. we also present faster sequential algorithms that provide good approximate distances only between &ldquo;distant&rdquo; vertices: we obtain an om+snne 0 time algorithm that computes paths of weight (1+o(1/polylog n) dist + o(wmax polylog n), where dist is the corresponding distance and wmax is the maximum edge weight. our chief instrument, which is of independent interest, are efficient constructions of sparse hop sets. a (d,&egr;)-hop set of a network g=(v,e) is a set e* of new weighted edges such that mimimum-weight d-edge paths in v,e&cup;e* have weight within (1+&egr;) of the respective distances in g. we construct hop sets of size on1+e0 where &egr;=o(1/polylog n) and d=o(polylog n).
pushdown store machines and real-time computation a comparison is made of the computing capabilities of pushdown store machines and real-time iterative arrays of finite-state machines with the following results. every pushdown store computation can be performed by some iterative array in real time. the latter are strictly more powerful, since they can recognize the set of palindromes in real time, which is impossible for pushdown-store machines even without a real-time constraint. versions of pushdown store machines, the tabulator machines and the n-dimensional pushdown store machines, are introduced during the development. by imposing a real-time constraint and letting the number of tabs and the number of dimensions vary, these form infinite hierarchies whose unions are equivalent to the pushdown store machine.
pricing network edges for heterogeneous selfish users. we study the negative consequences of selfish behavior in a congested network and economic means of influencing such behavior. we consider a model of selfish routing in which the latency experienced by network traffic on an edge of the network is a function of the edge congestion, and network users are assumed to selfishly route traffic on minimum-latency paths. the quality of a routing of traffic is measured by the sum of travel times (the total latency).it is well known that the outcome of selfish routing (a nash equilibrium) does not minimize the total latency. an ancient strategy for improving the selfish solution is the principle of marginal cost pricing, which asserts that on each edge of the network, each network user on the edge should pay a tax offsetting the congestion effects caused by its presence. by pricing network edges according to this principle, the inefficiency of selfish routing can always be eradicated.this result, while fundamental, assumes a very strong homogeneity property: all network users are assumed to trade off time and money in an identical way. the guarantee also ignores both the algorithmic aspects of edge pricing and the unfortunate possibility that an efficient routing of traffic might only be achieved with exorbitant taxes. motivated by these shortcomings, we extend this classical work on edge pricing in several different directions and prove the following results.we prove that the edges of a single-commodity network can always be priced so that an optimal routing of traffic arises as a nash equilibrium, even for very general heterogeneous populations of network users.when there are only finitely many different types of network users and all edge latency functions are convex, we show how to compute such edge prices efficiently.we prove that an easy-to-check mathematical condition on the population of heterogeneous network users is both necessary and sufficient for the existence of edge prices that induce an optimal routing while requiring only moderate taxes.
searching dynamic point sets in spaces with bounded doubling dimension. we present a new data structure that facilitates approximate nearest neighbor searches on a dynamic set of points in a metric space that has a bounded doubling dimension. our data structure has linear size and supports insertions and deletions in o(log n) time, and finds a (1+ε)-approximate nearest neighbor in time o(log n) + (1/ε)o(1). the search and update times hide multiplicative factors that depend on the doubling dimension; the space does not. these performance times are independent of the aspect ratio (or spread) of the points.
dictionary matching and indexing with errors and don't cares. this paper considers various flavors of the following online problem: preprocess a text or collection of strings, so that given a query string p, all matches of p with the text can be reported quickly. in this paper we consider matches in which a bounded number of mismatches are allowed, or in which a bounded number of "don't care" characters are allowed. the specific problems we look at are: indexing, in which there is a single text t, and we seek locations where p matches a substring of t; dictionary queries, in which a collection of strings is given upfront, and we seek those strings which match p in their entirety; and dictionary matching, in which a collection of strings is given upfront, and we seek those substrings of a (long) p which match an original string in its entirety. these are all instances of an all-to-all matching problem, for which we provide a single solution.the performance bounds all have a similar character. for example, for the indexing problem with n=|t| and m=|p|, the query time for k substitutions is o(m + (c1 log n)k⁄k! + # matches), with a data structure of size o(n (c2 log n)k⁄k!) and a preprocessing time of o(n (c2 log n)k⁄k!), where c1,c2 > 1 are constants. the deterministic preprocessing assumes a weakly nonuniform ram model; this assumption is not needed if randomization is used in the preprocessing.
faster suffix tree construction with missing suffix links. we consider suffix tree construction for situations with missing suffix links. two examples of such situations are suffix trees for parameterized strings and suffix trees for two-dimensional arrays. these trees also have the property that the node degrees may be large. we add a new back-propagation component to mccreight's algorithm and also give a high probability hashing scheme for large degrees. we show that these two features enable construction of suffix trees for general situations with missing suffix links in o(n) time, with high probability. this gives the first randomized linear time algorithm for constructing suffix trees for parameterized strings.
verifying candidate matches in sparse and wildcard matching. (math) this paper obtains the following results on pattern matching problems in which the text has length n and the pattern has length man o(nlog m) time deterministic algorithm for the string matching with wildcards problems, even when the alphabet is large.an o(klog2 m) time las vegas algorithm for the sparse string matching with wildcards problem, where k&laquo;n is the number of non-zeros in the text. we also give las vegas algorithms for the higher dimensional version of this problem.as an application of the above, an o(nlog2 m) time las vegas algorithm for the subset matching and tree pattern matching problems, and a las vegas algorithm for the geometric pattern matching problem.finally, an o(nlog2 m) time deterministic algorithm for subset matching and tree pattern matching..the crucial new idea underlying the first three results above is that of confirming matches by convolving vectors obtained by coding characters in the alphabet with non-boolean (i.e., rational or even complex) entries; in contrast, almost all previous pattern matching algorithms consider only boolean codes for the alphabet. the crucial new idea underlying the fourth result is a simpler method of shifting characters which ensures that each character occurs as a singleton in some shift.
a fast algorithm for computing steiner edge connectivity. given an undirected graph or an eulerian directed graph g and a subset s of its vertices, we show how to determine the edge connectivity c of the vertices in s in time o(c3 n log n+m). this algorithm is based on an efficient construction of tree packings which generalizes edmonds' theorem. these packings also yield a characterization of all minimal steiner cuts of size c from which an efficient data structure for maintaining edge connectivity between vertices in s under edge insertion can be obtained. this data structure enables the efficient construction of a cactus tree for representing significant c-cuts among these vertices, called c-separations, in the same time bound. in turn, we use the cactus tree to give a fast implementation of an approximation algorithm for the survivable network design problem due to williamson, goemans, mihail and vazirani.
on k-hulls and related problems for any set x of points (in any dimension) and any k &equil; 1,2, ..., we introduce the concept of the k-hull of x. this unifies the well-known notion of 'convex hulls' with the notion of 'centers' recently introduced by f.f. yao. the concept is intimately related to some other concepts (k-belts, k-sets) studied by edelsbrunner, welzl, lov&aacute;sz, erd&ouml;s and others. several computational problems related to k-hulls are studied here. some of our algorithms are of interest in themselves because of the techniques employed; in particular, the 'parametric' searching technique of megiddo is used in a nontrivial way. we will also extend megiddo's technique to las vegas algorithms. our results have applications to a variety of problems in computational geometry: efficient computation of the 'cut' guaranteed by the classical 'ham sandwich theorem', faster preprocessing time for polygon retrieval, and theoretical improvements to a problem of intersecting lines and points posed by hopcroft.
on the size of programs in subrecursive formalisms this paper gives an overview of subrecursive hierarchy theory as it relates to computational complexity and applies some of the concepts to questions about the size of programs in subrecursive programming languages. the purpose is three-fold, to reveal in simple terms the workings of subrecursive hierarchies, to indicate new results in the area, and to point out ways that the fundamental ideas in hierarchy theory can lead to interesting questions about programming languages. a specific application yields new information about blum's results on the size of programs and about the relationship between size and efficiency.
loop schemata we define a class of program schemata arising from the subrecursive programming language loop. in this preliminary report on loop schemata we show how to assign functional expressions to these schemata (as one aspect of the problem of assigning meaning to these programs), and we outline a solution to the schemata equivalence problem. schemata equivalence is reduced to questions about formal expressions. certain subcases of the problem are easily shown solvable, and although we claim that the general problem is solvable, we do not present the complete solution here because of its complexity.
type two computational complexity a programming language for the partial computable functionals is used as the basis for a definition of the computational complexity of functionals (type2 functions). an axiomatic account in the spirit of blum is then provided. the novel features of this approach are justified by applying it to problems in abstract complexity, specifically operator speed-up, and by using it to define the illusive notion of the polynomial degree of an arbitrary function. new results are obtained for these degrees.
on the theory of programming logics a new logic for reasoning about programs is proposed here, and its metamathematics is investigated. no new primitive notions are needed for the logic beyond those used in elementary programming and mathematics, yet the combination of these notions is remarkably powerful. the logic includes a programming language, designed with michael o'donnell, for program verification. it forms the core of the pl/cv verifier at cornell. this study belongs to the discipline of algorithmic logic as conceived by engeler. the logic is related to park's mu-calculus based on functions instead of relations. the monadic quantifier free subset is developed in the style of the system in j.w. debakker's recursive procedures. but this logic is substantially different from either of these. it is intended to be a practical programming logic in the spirit of e. dijkstra's calculus. this paper proves the completeness and decidability of the monadic (iterative) programming logic. it discusses the polyadic logic and the programming language briefly, and considers general models for the iterative programming logic. the polyadic logic is shown to be incomplete with respect to standard models, but complete with respect to general models.
complexity of formal translations and speed-up results the purpose of this paper is to give a model for the study of quantitative problems about formal translations from one programming language into another, as well as derive some initial results about the speed of programs produced by translations. the paper also contains a new speed-up result which shows that in any computational complexity measure there exist functions which have arbitrarily large speed-ups but that the size of the speed-up programs must grow non-computably fast.
subrecursive program schemata i & ii: i. undecidable equivalence problems; ii. decidable equivalence problems the study of program schemata and the study of subrecursive programming languages are both concerned with limiting program structure in order to permit a more complete analysis of algorithms while retaining sufficiently rich computing power to allow interesting algorithms. in this paper we combine these approaches by defining classes of subrecursive program schemata and investigating their equivalence problems. since the languages are all subrecursive, any scheme written in any one of them must halt (as long as we assume the basic functions and predicates are all total). hence equivalence of schemes is the first question of interest we can ask about these languages. we consider schematic versions of various subrecursive programming languages similar to the loop language. we distinguish between pre-loop and post-loop languages on the basis of whether the exit condition in an iteration loop is tested before iteration, as in algol (pre-), or after iteration, as in fortran (post-). we show that at the program level all these languages have the same computing power (the primitive recursive functions) and all have unsolvable equivalence problems (of arithmetic degree &pgr;01). but at the level of schemes, pre-loop has an unsolvable equivalence problem, while at least one formulation of post-loop has a solvable equivalence problem.
variations on pushdown machines (detailed abstract) a class of machines called auxiliary pushdown machines is introduced. several types of pushdown automata, including stack automata, are characterized in terms of these machines. the computing power of each class of machines in question is characterized in terms of time bounded turing machines, and corollaries are derived which answer some open questions in the field.
path systems and language recognition our main result, theorem 2, gives a bound on the storage required for a turing machine to simulate certain time-bounded pushdown machines. the theorem is a generalization of the result appearing in [3] stating that any context-free language can be recognized by a deterministic turing machine within storage (log n)2. we introduce a combinatorial object, called a path system, develop its theory briefly, and use the theory to prove both the result on pushdown machines and the result on context free languages, as well as a third result. the third result is the theorem of savitch [5] stating that a non-deterministic l(n) - storage bounded turing machine can be simulated by a deterministic (l(n))2 - storage bounded turing machine.
the complexity of theorem-proving procedures it is shown that any recognition problem solved by a polynomial time-bounded nondeterministic turing machine can be &ldquo;reduced&rdquo; to the problem of determining whether a given propositional formula is a tautology. here &ldquo;reduced&rdquo; means, roughly speaking, that the first problem can be solved deterministically in polynomial time provided an oracle is available for solving the second. from this notion of reducible, polynomial degrees of difficulty are defined, and it is shown that the problem of determining tautologyhood has the same polynomial degree as the problem of determining whether the first of two given graphs is isomorphic to a subgraph of the second. other examples are discussed. a method of measuring the complexity of proof procedures for the predicate calculus is introduced and discussed.
a hierarchy for nondeterministic time complexity the purpose of this paper is to prove the following result: theorem 1 for any real numbers r1, r2, 1 &le; r1 < r2, there is a set a of strings which has nondeterministic time complexity nr2 but not nondeterministic time complexity nr1 the computing devices are non-deterministic multitape turing machines.
an observation on time-storage trade off recently there have been several attempts to prove that every set of strings in @@@@ (i.e., recognizable in deterministic polynomial time) can be recognized in deterministic storage (log n)2. the methods used in the attempts were based on that of [1], in which it is shown that every context free language can be accepted in storage (log n)2 our thesis in the present paper is that these attempts must fail. we define a specific set sp of strings which is clearly in @@@@, but in a certain well-defined sense cannot be recognized in storage (log n)2 using the techniques in [1]. we conjecture that no turing machine recognizes sp within storage (log n)2, and show that if this conjecture is false, then in fact every member of @@@@ can be recognized within storage (log n)2.
feasibly constructive proofs and the propositional calculus (preliminary version) the motivation for this work comes from two general sources. the first source is the basic open question in complexity theory of whether p equals np (see [1] and [2]). our approach is to try to show they are not equal, by trying to show that the set of tautologies is not in np (of course its complement is in np). this is equivalent to showing that no proof system (in the general sense defined in [3]) for the tautologies is &ldquo;super&rdquo; in the sense that there is a short proof for every tautology. extended resolution is an example of a powerful proof system for tautologies that can simulate most standard proof systems (see [3]). the main theorem (5.5) in this paper describes the power of extended resolution in a way that may provide a handle for showing it is not super. the second motivation comes from constructive mathematics. a constructive proof of, say, a statement @@@@&times;a must provide an effective means of finding a proof of a for each value of x, but nothing is said about how long this proof is as a function of x. if the function is exponential or super exponential, then for short values of x the length of the proof of the instance of a may exceed the number of electrons in the universe. in section 2, i introduce the system pv for number theory, and it is this system which i suggest properly formalizes the notion of a feasibly constructive proof.
deterministic cfl's are accepted simultaneously in polynomial time and log squared space we propose to prove the theorem in the title. let ploss be the class of sets recognizable on a deterministic turing machine simultaneously in polynomial time and log squared space. using the notation of bruss and meyer [1], ploss &equil; &ugr;k tisp(nk,k log2n).
bounds on the time for parallel ram's to compute simple functions we prove that a parallel ram with no write conflicts allowed requires -&-ohgr;(log n) steps to compute the boolean or of n bits stored in the first n global memory cells. we first argue that this result is subtler than it appears, and in fact the -&-ldquo;obvious-&-rdquo; lower bound of log2n steps can be beaten.
time-bounded random access machines in this paper we introduce a formal model for random access computers and argue that the model is a good one to use in the theory of computational complexity. results are proved which compare run times for recognizing sets using this model (which has a fixed program) with a stored program model and with turing machines. the main result, theorem 3, shows the existence of a time complexity hierarchy which is finer than that of any standard abstract computer model. an algol-like programming language is introduced which facilitates proofs of the theorems.
on the lengths of proofs in the propositional calculus (preliminary version) one of the most important open questions in the field of computational complexity is the question of whether there is a polynomial time decision procedure for the classical propositional calculus. the purpose of the present paper is to study a question related to the complexity of decision procedures for the propositional calculus; namely, the complexity of proof systems for the propositional calculus. the fundamental issue here is whether there exists any proof system, and a polynomial p(n) such that every valid formula has a proof of length not exceeding p(n), where n is the length of the formula. theorem 1 below helps establish the importance of this question. for the purposes of this theorem, we give the following definitions.
storage requirements for deterministic polynomial time recognizable languages a striking example of practical tradeoffs between storage space and execution time is provided by the ibm 1401 fortran compiler. on another level, there is an interesting relation between the time and storage required to recognize context free languages. the recognition algorithm in [y] requires time no more than 0(n3), but requires at least linear storage, whereas the algorithm in [li requires recognition space no more than 0((log n)2) and requires more than polynomial time. an intriguing question is whether (log n)2 space is enough to recognize all languages recognizable in deterministic polynomial time. the above question has been narrowed down in [c] to the storage required to recognize a particular language called sp. this paper presents further evidence in support of the conjecture that sp cannot be recognized using storage (log n)k for any k. in section 2 we consider a game on directed acyclic graphs (dags) and show that at least 0(n1/4) markers are needed to play the game on some n node dags. the 0(n1/4) bound is used in section 3 to show that a fairly general machine to recognize sp also requires 0(n1/4) storage.
reconstructing curves in three (and higher) dimensional space from noisy data. we consider the task of reconstructing a curve in constant dimensional space from noisy data. we consider curves of the form c = [(x,y1,•••,yc) | yj = pj(x)], where the pj's are polynomials of low degree. given n points in (c+1)-dimensional space, such that t of these lie on some such unknown curve c while the other n-t are chosen randomly and independently, we give an efficient algorithm to recover the curve c and the identity of the good points. the success of our algorithm depends on the relation between n, t, c and the degree of the curve c, requiring t = ω (n deg(c)) 1/(c+1). this generalizes, in the restricted setting of random errors, the work of sudan (j. complexity, 1997) and of guruswami and sudan (ieee trans. inf. th. 1999) that considered the case c=1.
matrix multiplication via arithmetic progressions we present a new method for accelerating matrix multiplication asymptotically. thiswork builds on recent ideas of volker strassen, by using a basic trilinear form which is not a matrix product. we make novel use of the salem-spencer theorem, which gives a fairly dense set of integers with no three-term arithmetic progression. our resulting matrix exponent is 2.376.
equational theories and database constraints we present a novel way to formulate database dependencies as sentences of first-order logic, using equational statements instead of horn clauses. dependency implication is directly reduced to equational implication. our approach is powerful enough to express functional and inclusion dependencies, which are the most common database constraints. we present a new proof procedure for these dependencies. we use our equational formulation to derive new upper and lower bounds for the complexity of their implication problems.
semantics and axiomatics of a simple recursive language in this paper, we provide a simple recursive programming language with a semantics and a formal proof system, along the lines of [5], [17] and [23]. we show that the semantics used is the &ldquo;best&rdquo; possible if one admits the validity of algol's copy rule, and that the proof system is complete with respect to the semantics. the definitions and methods used are meant to provide a basis for a broader theory of program schemas, which models parallel as well as sequential programs.
secure multi-party quantum computation. secure multi-party computing, also called secure function evaluation, has been extensively studied in classical cryptography. we consider the extension of this task to computation with quantum inputs and circuits. our protocols are information-theoretically secure, i.e. no assumptions are made on the computational power of the adversary. for the weaker task of verifiable quantum secret sharing, we give a protocol which tolerates any t &xi; n/4 cheating parties (out of n). this is shown to be optimal. we use this new tool to show how to perform any multi-party quantum computation as long as the number of dishonest players is less than n/6.
a polynomial-time algorithm to approximately count contingency tables when the number of rows is constant. we consider the problem of counting the number of contingency tables with given row and column sums. this problem is known to be #p-complete, even when there are only two rows (random structures algorithms 10(4) (1997) 487). in this paper we present the first fully polynomial randomized approximation scheme for counting contingency tables when the number of rows is constant. a novel feature of our algorithm is that it is a hybrid of an exact counting technique with an approximation algorithm, giving two distinct phases. in the first, the columns are partitioned into "small" and "large". we show that the number of contingency tables can be expressed as the weighted sum of a polynomial number of new instances of the problem, where each instance consists of some new row sums and the original large column sums. in the second phase, we show how to approximately count contingency tables when all the column sums are large. in this case, we show that the solution lies in approximating the volume of a single convex body, a problem which is known to be solvable in polynomial time (j. acm 38 (1) (1991) 1).
approximately counting integral flows and cell-bounded contingency tables. we consider the problem of approximately counting integral flows in a network. we show that there is an fpras based on volume estimation if all capacities are sufficiently large, generalising a result of dyer, kannan and mount (1997). we apply this to approximating the number of contingency tables with prescribed cell bounds when the number of rows is constant, but the row sums, column sums and cell bounds may be arbitrary. we provide an fpras for this problem via a combination of dynamic programming and volume estimation. this generalises an algorithm of cryan and dyer (2002) for standard contingency tables, but the analysis here is considerably more intricate.
on the sum-of-squares algorithm for bin packing. in this article we present a theoretical analysis of the online sum-of-squares algorithm (ss) for bin packing along with several new variants. ss is applicable to any instance of bin packing in which the bin capacity b and item sizes s(a) are integral (or can be scaled to be so), and runs in time o(nb). it performs remarkably well from an average case point of view: for any discrete distribution in which the optimal expected waste is sublinear, ss also has sublinear expected waste. for any discrete distribution where the optimal expected waste is bounded, ss has expected waste at most o(log n). we also discuss several interesting variants on ss, including a randomized o(nb log b)-time online algorithm ss&ast; whose expected behavior is essentially optimal for all discrete distributions. algorithm ss&ast; depends on a new linear-programming-based pseudopolynomial-time algorithm for solving the np-hard problem of determining, given a discrete distribution f, just what is the growth rate for the optimal expected waste.
the degree hierarchy of undecidable problems of formal grammars after a brief discussion of historical matters in &sect;1, twenty-seven predicates of formal grammers are introduced in &sect;2. the next two sections discuss recursively enumerable predicates and nonrecursively enumerable predicates, respectively. these results show that the degree of unsolvability of a predicate is determined by its domain of definition. the paper concludes with a degree diagram and suggestions for further development. from a more comprehensive point of view these results complement the computational complexity classification of solvable problems and extend that classification to unsolvable problems based on their degree of unsolvability.
the effect of updates in binary search trees if a binary search tree is created by inserting n keys in random order using the usual insertion algorithm, then it is well known that the average search path is about 1.4lgn. however, if deletions, using the frequently recommended hibbard's algorithm, are interspersed with the insertions, then virtually nothing has been proven except for knuth and jonassen's very difficult, but complete, analysis of the case n = 3. in this paper it is shown that after a sufficient number of updates the average search path is &thgr;(n1/2). an improved algorithm given by knuth is shown to have the same asymptotic behavior.
the omega-sequence equivalence problem for dol systems is decidable the following problem is shown to be decidable. given are homomorphisms h1 and h2 from &sgr;* to &sgr;* and strings &sgr;1 and &sgr;2 over &sgr; such that hni(&sgr;i) is a proper prefix of hn+1i (&sgr;i) for i &equil; 1, 2 and all n &ge; 0, i.e. for i &equil; 1, 2, hi generates from &sgr;i an infinite string &agr;i with prefixes hni(&sgr;i) for all n &ge; 0. test whether &agr;1 &equil; &agr;2. from this result easily follows the decidability of limit language equivalence (&ohgr;-equivalence) for dol systems.
average case selection it is shown that n + k - o(1) comparisons are necessary, on average, to find the kth smallest of n numbers (k &lne; n/2). this lower bound matches the behavior of the technique of floyd and rivest to within a lower-order term. 7n/4 &plusmn; o(n) comparisons, on average, are shown to be necessary and sufficient to find the maximum and median of a set. an upper bound of 9n/4 &plusmn; o(n) and a lower bound of 2n - o(n) are shown for the max-min-median problem.
an approach to the k paths problem the k paths problem asks whether it is possible to find k edge-disjoint paths joining k given pairs of vertices in a graph. we show that this problem can be solved in polynomial time for k&le;5 if the input graph is k+2 -connected. it follows from this result that under the same restriction, the subgraph homeomorphism problem is polynomial for any pattern graph with five or fewer edges.
selfish traffic allocation for server farms. we investigate the price of selfish routing in non-cooperative networks in terms of the coordination and bicriteria ratios in the recently introduced game theoretic network model of koutsoupias and papadimitriou. we present the first thorough study of this model for general, monotone families of cost functions and for cost functionsm from queueing theory. our main results can be summarized as follows.we give a precise characterization of cost functions having a bounded/unbounded coordination ratio. for example, cost functions that describe the expected delay in queueing systems have an unbounded coordination ratio.we show that an unbounded coordination ratio implies additionally an extremely high performance degradation under bicriteria measures. we demonstrate that the price of selfish routing can be as high as a bandwidth degradation by a factor that is linear in the network size.we separate the game theoretic (integral) allocation model from the (fractional) flow model by demonstrating that even a very small, in fact negligible, amount of integrality can lead to a dramatic performance degradation.we unify recent results on selfish routing under different objectives by showing that an unbounded coordination ratio under the min-max objective implies an unbounded coordination ratio under the average-cost (or total-latency) objective and vice versa..our special focus lies on cost functions describing the behavior of web servers that can open only a limited number of tcp connections. in particular, we compare the performance of queueing systems that serve all incoming requests with servers that reject requests in case of overload.from the result presented in this paper we conclude that queuing systems without rejection cannot give any reasonable guarantee on the expected delay of requests under selfish routing even when the injected load is far away from the capacity of the system. in contrast, web server farms that are allowed to reject requests can guarantee a high quality of service for every individual request stream even under relatively high injection rates.
estimating the weight of metric minimum spanning trees in sublinear-time. in this paper we present a sublinear-time $(1+\varepsilon)$-approximation randomized algorithm to estimate the weight of the minimum spanning tree of an $n$-point metric space. the running time of the algorithm is $\widetilde{\mathcal{o}}(n/\varepsilon^{\mathcal{o}(1)})$. since the full description of an $n$-point metric space is of size $\theta(n^2)$, the complexity of our algorithm is sublinear with respect to the input size. our algorithm is almost optimal as it is not possible to approximate in $o(n)$ time the weight of the minimum spanning tree to within any factor. we also show that no deterministic algorithm can achieve a $b$-approximation in $o(n^2/b^3)$ time. furthermore, it has been previously shown that no $o(n^2)$ algorithm exists that returns a spanning tree whose weight is within a constant times the optimum.
the complexity of multiway cuts (extended abstract) in the multiway cut problem we are given an edge-weighted graph and a subset of the vertices called terminals, and asked for a minimum weight set of edges that separates each terminal from all the others. when the number k of terminals is two, this is simply the min-cut, max-flow problem, and can be solved in polynomial time. we show that the problem becomes np-hard as soon as k = 3, but can be solved in polynomial time for planar graphs for any fixed k. the planar problem is np-hard, however, if k is not fixed. we also describe a simple approximation algorithm for arbitrary graphs that is guaranteed to come within a factor of 2&ndash;2/k of the optimal cut weight.
self-testing of universal and fault-tolerant sets of quantum gates. we consider the design of self-testers for quantum gates. a self-tester for the gates $\boldsymbol{f}_1,\ldots, \boldsymbol{f}_m$ is a procedure that, given any gates $\boldsymbol{g}_1, \ldots, \boldsymbol{g}_m$, decides with high probability if each $\boldsymbol{g}_i$ is close to $\boldsymbol{f}_i$. this decision has to rely only on measuring in the computational basis the effect of iterating the gates on the classical states. it turns out that, instead of individual gates, we can design only procedures for families of gates. to achieve our goal we borrow some elegant ideas of the theory of program testing: we characterize the gate families by specific properties, develop a theory of robustness for them, and show that they lead to self-testers. in particular we prove that the universal and fault-tolerant set of gates consisting of a hadamard gate, a $\mathrm{c\text{-}not}$ gate, and a phase rotation gate of angle $\pi/4$ is self-testable.
adaptive versus nonadaptive attribute-efficient learning. we study the complexity of learning arbitrary boolean functions of n variables by membership queries, if at most r variables are relevant. problems of this type have important applications in fault searching, e.g. logical circuit testing and generalized group testing. previous literature concentrates on special classes of such boolean functions and considers only adaptive strategies. first we give a straightforward adaptive algorithm using o(r2r log n) queries, but actually, most queries are asked nonadaptively. this leads to the problem of purely nonadaptive learning. we give a graph-theoretic characterization of nonadaptive learning families, called r-wise bipartite connected families. by the probabilistic method we show the existence of such families of size o(r2r log n + r22r). this implies that nonadaptive attribute-efficient learning is not essentially more expensive than adaptive learning. we also sketch an explicit pseudopolynomial construction, though with a slightly worse bound. it uses the common derandomization technique of small-biased k-independent sample spaces. for the special case r &equals; 2, we get roughly 2.275 log n adaptive queries, which is fairly close to the obvious lower bound of 2 log n. for the class of monotone functions, we prove that the optimal query number o(2r + r log n) can be already achieved in o(r) stages. on the other hand, &omega;(2r log n) is a lower bound on nonadaptive queries.
non-interactive and reusable non-malleable commitment schemes. we consider non-malleable (nm) and universally composable (uc) commitment schemes in the common reference string (crs) model. we show how to construct non-interactive nm commitments that remain non-malleable even if the adversary has access to an arbitrary number of commitments from honest players - rather than one, as in several previous schemes. we show this is a strictly stronger security notion. our construction is the first non-interactive scheme achieving this that can be based on the minimal assumption of existence of one-way functions. but it can also be instantiated in a very efficient version based on the strong rsa assumption. for uc commitments, we show that existence of a uc commitment scheme in the crs model (interactive or not) implies key exchange and - for a uniform reference string - even implies oblivious transfer. this indicates that uc commitment is a strictly stronger primitive than nm. finally, we show that our strong rsa based construction can be used to improve the most efficient known uc commitment scheme so it can work with a crs of size independent of the number of players, without loss of efficiency.
the complexity of computing a nash equilibrium. in 1951, john f. nash proved that every game has a nash equilibrium [ann. of math. (2), 54 (1951), pp. 286-295]. his proof is nonconstructive, relying on brouwer's fixed point theorem, thus leaving open the questions, is there a polynomial-time algorithm for computing nash equilibria? and is this reliance on brouwer inherent? many algorithms have since been proposed for finding nash equilibria, but none known to run in polynomial time. in 1991 the complexity class ppad (polynomial parity arguments on directed graphs), for which brouwer's problem is complete, was introduced [c. papadimitriou, j. comput. system sci., 48 (1994), pp. 489-532], motivated largely by the classification problem for nash equilibria; but whether the nash problem is complete for this class remained open. in this paper we resolve these questions: we show that finding a nash equilibrium in three-player games is indeed ppad-complete; and we do so by a reduction from brouwer's problem, thus establishing that the two problems are computationally equivalent. our reduction simulates a (stylized) brouwer function by a graphical game [m. kearns, m. littman, and s. singh, graphical model for game theory, in 17th conference in uncertainty in artificial intelligence (uai), 2001], relying on &ldquo;gadgets,&rdquo; graphical games performing various arithmetic and logical operations. we then show how to simulate this graphical game by a three-player game, where each of the three players is essentially a color class in a coloring of the underlying graph. subsequent work [x. chen and x. deng, setting the complexity of 2-player nash-equilibrium, in 47th annual ieee symposium on foundations of computer science (focs), 2006] established, by improving our construction, that even two-player games are ppad-complete; here we show that this result follows easily from our proof.
optimal phylogenetic reconstruction. one of the major tasks of evolutionary biology is the reconstruction of phylogenetic trees from molecular data. the evolutionary model is given by a markov chain on the true evolutionary tree. given samples from this markov chain at the leaves of the tree, the goal is to reconstruct the evolutionary tree.it is well known that in order to reconstruct a tree on n leaves, sequences of length ω(log n) are needed. it was conjectured by m. steel that for the cfn evolutionary model, if the mutation probability on all edges of the tree is less than p* = (√2-1)/23/2, then the tree can be recovered from sequences of length o(log n). this was proven by the second author in the special case where the tree is "balanced". the second author also proved that if all edges have mutation probability larger than p* then the length needed is nω(1). this "phase-transition" in the number of samples needed is closely related to the phase transition for the reconstruction problem (or extremality of free measure) studied extensively in statistical physics, probability and computer science.here we complete the proof of steel's conjecture and give a reconstruction algorithm using optimal (up to a multiplicative constant) sequence length. our results further extend to obtain an optimal reconstruction algorithm for the jukes-cantor model with short edges. all reconstruction algorithms run in polynomial time.
denotational semantics of concurrency a general framework for the denotational treatment of concurrency is introduced. the key idea is the notion of process which is element of a domain obtained as solution of a domain equation in the style as considered previously by plotkin. we use tools from metric topology as advocated by nivat to solve this equation, show how operations upon processes can be defined conveniently, and illustrate the approach with the definition of a variety of concepts as encountered in the study of concurrency. only few proofs of the supporting mathematical theory are given; full proofs will appear in the final version of the paper.
online trading algorithms and robust option pricing. in this work we show how to use efficient online trading algorithms to price the current value of financial instruments, such as an option. we derive both upper and lower bounds for pricing an option, using online trading algorithms.our bounds depend on very minimal assumptions and are mainly derived assuming that there are no arbitrage opportunities.
some connections between mathematical logic and complexity theory however difficult the fundamental problems of theoretical computer science may seem, there is very little to suggest that they are anything more than knotty combinatorial problems. so, when we look for reasons for our inability to resolve p &equil; np and related questions, we most likely find them dealing with a lack of understanding of particular computational problems and their lower bounds. this is the sense of hopcroft's prediction: &ldquo;...within the next five years, nobody will prove that any of these problems takes more than let's say n2 time. i think that's a reasonably safe conjecture and it also illustrates how little we know about lower bounds.&rdquo; [mt]. hopcroft's guess is uncanny in its accuracy&mdash;after six years and considerable effort by many researchers, his conjecture remains unchallenged. the results in this paper offer a possible explanation for our failure to resolve these problems. roughly, the main result of the sequel links lower bounds and a branch of mathematical logic known as model theory. in particular, we prove that the existence of nonpolynomial lower bounds is equivalent to the existence of nonstandard models of a sizable fragment of arithmetic. since these are deep logical issues and there are very few techniques for handling them, and since the nonstandard models in question are non-effective, it seems plausible that this linking of complexity theory and logic explains our failure to obtain nontrivial lower bounds. one of the aims of mathematical logic is to clarify the relation between mathematical theories and their interpretations&mdash;or models.
the consistency of ``p = np'' and related problems with fragments of number theory the main results of this paper demonstrate the consistency of &ldquo;p &equil; np&rdquo; and a variant of &ldquo;np @@@@ conp&rdquo; with certain natural fragments of number theory to be defined precisely in the sequel.@@@@ consistency results represent an approach to the lower bound problems of complexity theory which points to a number of interesting lines of inquiry. our ultimate goal is to make precise the difficulty of proving certain nontrivial lower bounds. among the possibilities which follow from this approach are: (1) that logical techniques may help us resolve the p &equil; np question, (2) that showing why certain arguments must fail may lead to mathematical tools capable of resolving the problems, and (3) that the special character of model theoretic methods in complexity theory may lead to new results which are of purely logical interest. we will address these possibilities below.
cryptographic protocols a cryptographic transformation is a mapping f from a set of cleartext messages, m, to a set of ciphertext messages. since for m e m, f(m) should hide the contents of m from an enemy, f-1 should, in a certain technical sense, be difficult to infer from f(m) and public knowledge about f. a cryptosystem is a model of computation and communication which permits the manipulation of messages by cryptographic transformations.
liveness properties as convergence in metric spaces four liveness properties of concurrent programs are characterized by the fact that their computations, represented as sequences of partial orderings of events, are convergent in suitable metric spaces. the corresponding topological completions do not therefore contain the infinite computations without the desired properties. the properties are: vitality (i.e. every running process will eventually produce an observable event), global and local fairness, and deadlock freedom. this approach proves fruitful since a universal scheduler is defined, which, when supplied with a particular metric, generates all and only convergent computations. thus, this scheduler can be used to generate all and only vital, fair or deadlock free computations.
a new approach to dynamic all pairs shortest paths. we study novel combinatorial properties of graphs that allow us to devise a completely new approach to dynamic all pairs shortest paths problems. our approach yields a fully dynamic algorithm for general directed graphs with non-negative real-valued edge weights that supports any sequence of operations in o(n2log3n) amortized time per update and unit worst-case time per distance query, where n is the number of vertices. we can also report shortest paths in optimal worst-case time. these bounds improve substantially over previous results and solve a long-standing open problem. our algorithm is deterministic, uses simple data structures, and appears to be very fast in practice.
on the complexity of equilibria. we prove complexity, approximability, and inapproximability results for the problem of finding an exchange equilibrium in markets with indivisible (integer) goods, most notably a polynomial-time algorithm that approximates the market equilibrium arbitrarily closely when the number of goods is bounded and the utilities are linear. we also show a communication complexity lower bound, implying that the ideal informational economy of a market with unique individual optima is unattainable in general.
the spending constraint model for market equilibrium: algorithmic, existence and uniqueness results. the traditional model of market equilibrium supports impressive existence results, including the celebrated arrow-debreu theorem. however, in this model, polynomial time algorithms for computing (or approximating) equilibria are known only for linear utility functions. we present a new, and natural, model of market equilibrium that not only admits existence and uniqueness results paralleling those for the traditional model but is also amenable to efficient algorithms.
integrality gaps for sparsest cut and minimum linear arrangement problems. arora, rao and vazirani [2] showed that the standard semi-definite programming (sdp) relaxation of the sparsest cut problem with the triangle inequality constraints has an integrality gap of o(√log n). they conjectured that the gap is bounded from above by a constant. in this paper, we disprove this conjecture (referred to as the arv-conjecture) by constructing an ω(log log n) integrality gap instance. khot and vishnoi [16] had earlier disproved the non-uniform version of the arv-conjecture.a simple "stretching" of the integrality gap instance for the sparsest cut problem serves as an ω(log log n) integrality gap instance for the sdp relaxation of the minimum linear arrangement problem. this sdp relaxation was considered in [6, 11], where it was shown that its integrality gap is bounded from above by o(√log n log log n).
alpha-shapes and flow shapes are homotopy equivalent. in this paper we establish a topological similarity between two apparently different shape constructors from a set of points. shape constructors are geometric structures that transform finite point sets into continuous shapes. due to their immense practical importance in geometric modeling various shape constructors have been proposed recently. understanding the relations among them often leads to new insights that are potentially helpful in applications. here we discover a topological equivalence among two such geometric structures, namely α shapes and flow shapes. both shapes found applications in surface reconstruction and molecular modelin.
maintaining order in a linked list we present a new representation for linked lists. this representation allows one to efficiently insert objects into the list and to quickly determine the order of list elements. the basic data structure, called an indexed 2-3 tree, allows one to do n inserts in o(nlogn) steps and to determine order in constant time. we speed up the algorithm by dividing the data structure up into log*n layers. the improved algorithm does n insertions and comparisons in o(nlog*n) steps. the paper concludes with two applications: determining ancestor relationships in a growing tree and maintaining a tree structured environment (context tree).
two algorithms for maintaining order in a list the order maintenance problem is that of maintaining a list under a sequence of insert and delete operations, while answering order queries (determine which of two elements comes first in the list). we give two new algorithms for this problem. the first algorithm matches the o(1) amortized time per operation of the best previously known algorithm, and is much simpler. the second algorithm permits all operations to be performed in o(1) worst-case time.
almost random graphs with simple hash functions. we describe a simple randomized construction for generating pairs of hash functions h1,h2 from a universe u to ranges v = [m] = (0,1,...,m-1) and w = [m] so that for every key set s ⊆ u with n = |s| ≤ m/(1 + ε) the (random) bipartite (multi)graph with node set v ∪ w and edge set (h1(x),h2(x))| x ∈ s exhibits a structure that is essentially random. the construction combines d-wise independent classes for d a relatively small constant with the well-known technique of random offsets. while keeping the space needed to store the description of h1 and h2 at o(nζ), for ζ < 1 fixed arbitrarily, we obtain a much smaller (constant) evaluation time than previous constructions of this kind, which involved siegel's high-performance hash classes. the main new technique is the combined analysis of the graph structure and the inner structure of the hash functions, as well as a new way of looking at the cycle structure of random (multi)graphs. the construction may be applied to improve on pagh and rodler's "cuckoo hashing" (2001), to obtain a simpler and faster alternative to a recent construction of ostlin and pagh (2002/03) for simulating uniform hashing on a key set s, and to the simulation of shared memory on distributed memory machines. we also describe a novel way of implementing (approximate) d-wise independent hashing without using polynomials.
the pcp theorem by gap amplification. the pcp theorem [arora and safra 1998; arora et. al. 1998] says that every language in np has a witness format that can be checked probabilistically by reading only a constant number of bits from the proof. the celebrated equivalence of this theorem and inapproximability of certain optimization problems, due to feige et al. [1996], has placed the pcp theorem at the heart of the area of inapproximability. in this work, we present a new proof of the pcp theorem that draws on this equivalence. we give a combinatorial proof for the np-hardness of approximating a certain constraint satisfaction problem, which can then be reinterpreted to yield the pcp theorem. our approach is to consider the unsat value of a constraint system, which is the smallest fraction of unsatisfied constraints, ranging over all possible assignments for the underlying variables. we describe a new combinatorial amplification transformation that doubles the unsat-value of a constraint-system, with only a linear blowup in the size of the system. the amplification step causes an increase in alphabet-size that is corrected by a (standard) pcp composition step. iterative application of these two steps yields a proof for the pcp theorem. the amplification lemma relies on a new notion of &ldquo;graph powering&rdquo; that can be applied to systems of binary constraints. this powering amplifies the unsat-value of a constraint system provided that the underlying graph structure is an expander. we also extend our amplification lemma towards construction of assignment testers (alternatively, pcps of proximity) which are slightly stronger objects than pcps. we then construct pcps and locally-testable codes whose length is linear up to a polylog factor, and whose correctness can be probabilistically verified by making a constant number of queries. namely, we prove sat &isin; pcp 1/2,1[log2(n&sdot;poly log n), o(1)].
on the fourier tails of bounded functions over the discrete cube. a theorem of bourgain [4] on fourier tails states that if f :(-1, 1)n → (-1, 1) is a boolean-valued function on the discrete cube such that for any k > 0, [σ|s| > k f(s)2 < k-1/2 + o(1), ] then essentially, f depends on only 2o(k) coordinates. this and related theorems such as friedgut's theorem [12], kkl [16], the fkn theorem [14], and the majority is stablest theorem [27] have proven useful for numerous results in theoretical computer science [3, 5, 9, 6, 7, 10, 11, 18, 19, 20, 24, 17, 25, 23, 22, 28, 29, 31].in this paper we prove an analogue to bourgain's theorem for bounded functions on the discrete cube, f : (n ⋺ [-1,1]); such functions arise naturally in hardness-of-approximation problems, as averages of boolean functions. specifically, we show that for every k > 0, if [σ|s| > k f(s)2 < exp(-o(k2 log k))] then essentially, f depends on only 2o(k) coordinates. we also show, perhaps surprisingly, that this result is sharp up to the log k factor in the exponent.our proof uses fourier analysis, as well as some extremal properties of the chebyshev polynomials.
a new multilayered pcp and the hardness of hypergraph vertex cover. given a k-uniform hypergraph, the ek-vertex-cover problem is to find the smallest subset of vertices that intersects every hyperedge. we present a new multilayered probabilistically checkable proof (pcp) construction that extends the raz verifier. this enables us to prove that ek-vertex-cover is np-hard to approximate within a factor of $(k-1-\epsilon)$ for arbitrary constants $\epsilon>0$ and $k\ge 3$. the result is nearly tight as this problem can be easily approximated within factor k. our construction makes use of the biased long-code and is analyzed using combinatorial properties of s-wise t-intersecting families of subsets.we also give a different proof that shows an inapproximability factor of $\lfloor \frac{k}{2} \rfloor -\eps$. in addition to being simpler, this proof also works for superconstant values of k up to (log n)1/c, where c > 1 is a fixed constant and n is the number of hyperedges.
conditional hardness for approximate coloring. we study the aprxcoloring$(q,q)$ problem: given a graph $g$, decide whether $\chi(g)\le q$ or $\chi(g)\ge q$. we present hardness results for this problem for any constants $3\le q<q$. for $q\ge4$, our result is based on khot's 2-to-1 label cover, which is conjectured to be np-hard [s. khot, proceedings of the 34th annual acm symposium on theory of computing, 2002, pp. 767-775]. for $q=3$, we base our hardness result on a certain &ldquo;${\rhd\hskip-0.5em<}$-shaped&rdquo; variant of his conjecture. previously no hardness result was known for $q=3$ and $q\ge6$. at the heart of our proof are tight bounds on generalized noise-stability quantities, which extend the recent work of mossel, o'donnell, and oleszkiewicz [&ldquo;noise stability of functions with low influences: invariance and optimality,&rdquo; ann. of math. (2), to appear] and should have wider applicability.
the importance of being biased. (math) we show that the minimum vertex cover problem is np-hard to approximate to within any factor smaller than $10\sqrt{5}-21 \approx 1.36067$, improving on the previously known hardness result for a $\frac{7}{6}$ factor.
on some generalizations of binary search classic binary search is extended to multidimensional search problems. these new search methods can efficiently solve several important problems of computer science. applications of these results to an open problem in the theory of computation are discussed yielding new insight into the lba problem.
approximation algorithms for combinatorial auctions with complement-free bidders. we exhibit three approximation algorithms for the allocation problem in combinatorial auctions with complement free bidders. the running time of these algorithms is polynomial in the number of items $m$ and in the number of bidders n, even though the "input size" is exponential in m. the first algorithm provides an o(log m) approximation. the second algorithm provides an o(√ m) approximation in the weaker model of value oracles. this algorithm is also incentive compatible. the third algorithm provides an improved 2-approximation for the more restricted case of "xos bidders", a class which strictly contains submodular bidders. we also prove lower bounds on the possible approximations achievable for these classes of bidders. these bounds are not tight and we leave the gaps as open problems.
truthful randomized mechanisms for combinatorial auctions. we design two computationally-efficient incentive-compatible mechanisms for combinatorial auctions with general bidder preferences. both mechanisms are randomized, and are incentive-compatible in the universal sense. this is in contrast to recent previous work that only addresses the weaker notion of incentive compatibility in expectation. the first mechanism obtains an o(√m)-approximation of the optimal social welfare for arbitrary bidder valuations -- this is the best approximation possible in polynomial time. the second one obtains an o(log2 m)-approximation for a subclass of bidder valuations that includes all submodular bidders. this improves over the best previously obtained incentive-compatible mechanism for this class which only provides an o(√ m)-approximation.
correcting errors without leaking partial information. this paper explores what kinds of information two parties must communicate in order to correct errors which occur in a shared secret string w. any bits they communicate must leak a significant amount of information about w --- that is, from the adversary's point of view, the entropy of w will drop significantly. nevertheless, we construct schemes with which alice and bob can prevent an adversary from learning any useful information about w. specifically, if the entropy of w is sufficiently high, then there is no function f(w) which the adversary can learn from the error-correction information with significant probability.this leads to several new results: (a) the design of noise-tolerant "perfectly one-way" hash functions in the sense of canetti et al. [7], which in turn leads to obfuscation of proximity queries for high entropy secrets w; (b) private fuzzy extractors [11], which allow one to extract uniformly random bits from noisy and nonuniform data w, while also insuring that no sensitive information about w is leaked; and (c) noise tolerance and stateless key re-use in the bounded storage model, resolving the main open problem of ding [10].the heart of our constructions is the design of strong randomness extractors with the property that the source w can be recovered from the extracted randomness and any string w' which is close to w.
on abstractions of parallel programs we discuss a parallel program model that allows a very general synchronization mechanism with a scheduler to control the progress of processes &ldquo;undergoing synchronization.&rdquo; we how to &ldquo;abstract&rdquo; the program, i.e. remove the scheduler, resulting in a simpler program. we then show that, for a large class of schedulers, a process can become deadlocked in the original program iff it can become deadlocked in the abstracted program.
on the possibility and impossibility of achieving clock synchronization it is known that clock synchronization can be achieved in the presence of faulty clocks numbering more than one-third of the total number of participating clocks provided that some authentication technique is used. without authentication the number of faults that can be tolerated has been an open question. here we show that if we restrict logical clocks to running within some linear function of real time, then clock synchronization is impossible, without authentication, when one-third or more of the processors are faulty. however, if there is a bound on the rate at which a processor can generate messages, then we show that clock synchronization is achievable, without authentication, as long as the faults do not disconnect the network. finally, we provide a lower bound on the closeness to which simultaneity can be achieved in the network as a function of the transmission and processing delay properties of the network.
a new look at fault tolerant network routing consider a communication network g in which a limited number of link and/or node faults f might occur. a routing &rgr; for the network (a fixed path between each pair of nodes) must be chosen without any knowledge of which components might become faulty. choosing a good routing corresponds to bounding the diameter of the surviving route graph r(g,&rgr;)/f, where two nonfaulty nodes are joined by an edge if there are no faults on the route between them. we prove a number of results concerning the diameter of surviving route graphs. we show that if &rgr; is a minimal length routing, then the diameter of r(g,&rgr;)/f can be on the order of the number of nodes of g, even if f consists of only a single node. however, if g is the n-dimensional cube, the diameter of r(g,&rgr;)/f&le;3 for any minimal length routing &rgr; and any set of faults f with |f|<n. we also show that if f consists only of edges and does not disconnect g, then the diameter of r(g,&rgr;)/f is &le; 3|f|+1, while if f consists only of nodes and does not disconnect g, then the diameter of r(g,&rgr;)/f is &le; the sum of the degrees of the nodes in f, where in both cases &rgr; is an arbitrary minimal length routing. we conclude with one of the most important contributions of this paper: a list of interesting and apparently difficult open problems.
optimal wiring between rectangles we consider the problem of wiring together two parallel rows of points under a variety of conditions. the options include whether we allow the rows to slide relative to one another, whether we use only rectilinear wires or arbitrary wires, and whether we can use wires in one layer or several layers. in almost all of these combinations of conditions, we can provide a polynomial-time algorithm to minimize the distance between the parallel rows of points. we also compare two fundamentally different wiring approaches, where one and two layers are used. we show that although the theoretical model implies that there can be great gains for the two-layer strategy, even in cases where no crossovers are required, when we consider typical design rules for laying out vlsi circuits there is no substantial advantage to the two-layer approach over the one-layer approach.
polynomial algorithms for multiple processor agreement reaching agreement in a distributed system while handling malfunctioning behavior is a central issue for reliable computer systems. all previous algorithms for reaching the agreement required an exponential number of messages to be sent, with or without authentication. we give polynomial algorithms for reaching (byzantine) agreement, both with and without the use of authentication protocols. we also prove that no matter what kind of information is exchanged, there is no way to reach agreement with fewer than t+1 rounds of exchange, where t is the upper bound on the number of faults.
bounded concurrent time-stamp systems are constructible concurrent time stamping is at the heart of solutions to some of the most fundamental problems in distributed computing. based on concurrent-time-stamp-systems, elegant and simple solutions to core problems such as &fnof;c&fnof;s-mutual-exclusion, construction of a multi-reader-multi-writer atomic register, probabilistic consensus,&hellip; were developed. unfortunately, the only known implementation of a concurrent time stamp system has been theoretically unsatisfying, since it requires unbounded size time-stamps, in other words, unbounded memory. not knowing if bounded concurrent-time-stamp-systems are at all constructible, researchers were led to constructing complicated problem-specific solutions to replace the simple unbounded ones. in this work, for the first time, a bounded implementation of a concurrent-time-stamp-system is presented. it provides a modular unbounded-to-bounded transformation of the simple unbounded solutions to problems such as above. it allows solutions to two formerly open problems, the bounded-probabilistic-consensus problem of abrahamson [a88] and the &fnof;i&fnof;o-@@@@-exclusion problem of [flbb85], and a more efficient construction of mrmw atomic registers.
graph decomposition is npc-a complete proof of holyer's conjecture an h-decomposition of a graph g = (v,e) is a partition of e into subgraphs isomorphic to h. given a fixed graph h, the h-decomposition problem is to determine whether an input graph g admits an h-decomposition. i. holyer (1980) conjectured that h-decomposition is np-complete whenever h is connected and has at least 3 edges. some partial results have been obtained during the last decade. a complete proof for holyer's conjecture is the content of this paper.
propositional representation of arithmetic proofs (preliminary version) equations f@@@@ &equil; g@@@@ between polynomial time computable functions can be represented by sets of propositional formulas. if f@@@@ &equil; g@@@@ is provable in certain arithmetic systems, then polynomial length proofs of the representing formulas exist in certain propositional systems. two cases of this phenomenon and a general theory are given.
competitive recommendation systems. a recommendation system tracks past purchases of a group of users to make product recommendations to individual members of the group. in this paper we present a notion of competitive recommendation systems, building on recent theoretical work on this subject. we reduce the problem of achieving competitiveness to a problem in matrix reconstruction. we then present a matrix reconstruction scheme that is competitive: it requires a small overhead in the number of users and products to be sampled, delivering in the process a net utility that closely approximates the best possible with full knowledge of all user-product preferences.
on the diameter of permutation groups we show that any group represented by generators that are cycles of bounded degree has o(n2) diameter, i.e., that the longest product of generators required to reach any permutation in the group is o(n2). we also show how such &ldquo;short&rdquo; products can be found in polynomial time. the techniques presented are applicable to generalizations of many permutation-group puzzles such as alexander's star and the hungarian rings.
touring a sequence of polygons. given a sequence of k polygons in the plane, a start point s, and a target point, t, we seek a shortest path that starts at s, visits in order each of the polygons, and ends at t. if the polygons are disjoint and convex, we give an algorithm running in time o(kn log (n/k)), where n is the total number of vertices specifying the polygons. we also extend our results to a case in which the convex polygons are arbitrarily intersecting and the subpath between any two consecutive polygons is constrained to lie within a simply connected region; the algorithm uses o(nk2 log n) time. our methods are simple and allow shortest path queries from s to a query point t to be answered in time o(k log n + m), where m is the combinatorial path length. we show that for nonconvex polygons this "touring polygons" problem is np-hard.the touring polygons problem is a strict generalization of some classic problems in computational geometry, including the safari problem, the zoo-keeper problem, and the watchman route problem in a simple polygon. our new results give an order of magnitude improvement in the running times of the safari problem and the watchman route problem: we solve the safari problem in o(n2 log n) time and the watchman route problem (through a fixed point s) in time o(n3 log n), compared with the previous time bounds of o(n3) and o(n4), respectively.
on the randomness complexity of efficient sampling. we consider the following question: can every efficiently samplable distribution be efficiently sampled, up to a small statistical distance, using roughly as much randomness as the length of its output? towards a study of this question we generalize the current theory of pseudorandomness and consider pseudorandom generators that fool non-boolean distinguishers (nb-prgs). we show a link between nb-prgs and a notion of function compression, introduced by harnik and naor [16]. (a compression algorithm for f should efficiently compress an input x in a way that will preserve the information needed to compute f(x).) by constructing nb-prgs, we answer the above question affirmatively under the following types of assumptions:cryptographic incompressibility assumptions (that are implied by, and seem weaker than, "exponential" cryptographic assumptions).nisan-wigderson style (average-case) incompressibility assumptions for polynomial-time computable functions.no assumptions are needed for answering our question affirmatively in the case of constant depth samplers.to complement the above, we extend an idea from [16] and establish the following win-win situation. if the answer to our main question is "no", then it is possible to construct a (weak variant of) collision-resistant hash function from any one-way permutation. the latter would be considered a surprising result, as a black-box construction of this type was ruled out by simon [35].finally, we present an application of nb-prgs to information theoretic cryptography. specifically, under any of the above assumptions, efficient protocols for information-theoretic secure multiparty computation never need to use (much) more randomness than communication.
optimal outlier removal in high-dimensional. we study the problem of finding an outlier-free subset of a set of points (or a probability distribution) in n-dimensional euclidean space. a point x is defined to be a &bgr;-outlier if there exists some direction w in which its squared distance from the mean along w is greater than &bgr; times the average squared distance from the mean along w [1]. our main theorem is that for any &egr;>0, there exists a (1-&egr;) fraction of the original distribution that has no o(\frac{n}{&egr;}(b+log \frac{n}{&egr;))-outliers, improving on the previous bound of o(n^7b/&egr;). this bound is shown to be nearly the best possible. the theorem is constructive, and results in a \frac{1}{1-&egr;} approximation to the following optimization problem: given a distribution &mgr; (i.e. the ability to sample from it), and a parameter &egr;>0, find the minimum &bgr; for which there exists a subset of probability at least (1-&egr;) with no &bgr;-outliers.
a simple polynomial-time rescaling algorithm for solving linear programs. the perceptron algorithm, developed mainly in the machine learning literature, is a simple greedy method for finding a feasible solution to a linear program (alternatively, for learning a threshold function). in spite of its exponential worst-case complexity, it is often quite useful, in part due to its noise-tolerance and also its overall simplicity. in this paper, we show that a randomized version of the perceptron algorithm along with periodic rescaling runs in polynomial-time. the resulting algorithm for linear programming has an elementary description and analysis.
complex tilings. we study the minimal complexity of tilings of a plane with a given tile set. we note that any tile set admits either no tiling or some tiling with \ooo(n) kolmogorov complexity of its (n\times n)-squares. we construct tile sets for which this bound is nearly tight: all tilings have complexity >n/r(n), given any unbounded computable monotone r. this adds a quantitative angle to classical results on non-recursivity of tilings -- that we also develop in terms of turing degrees of unsolvability.
fooling a two-way automaton or one pushdown store is better than one counter for two way machines (preliminary version) we define a language l and show that is cannot be recognized by any two way deterministic counter machine. it is done by fooling any given such machine; i.e. showing that if it accepts l' @@@@ l, then l'-l @@@@ &fgr;. for this purpose, an argument stronger than the well known crossing sequence argument needs to be introduced. since l is accepted by a two-way deterministic pushdown automaton, we consequently show that one pushdown stack is more powerful than one counter for deterministic two-way machines.
two tapes are better than one for nondeterministic machines it is known that k tapes are no better than two tapes for nondeterministic machines. we show here that two tapes are better than one. in fact, we show that two pushdown stores are better than one tape. also, k tapes are no better than two for nondeterministic reversal-bounded machines. we show here that two tapes are better than one for such machines. in fact, we show that two reversal-bounded pushdown stores are better than one reversal-bounded tape. we also show that for one-tape nondeterministic machines, unrestricted machines are better than reversal-bounded machines.
lower bounds on communication complexity we prove the following four results on communication complexity: 1) for every k &ge; 2, the language lk of encodings of directed graphs of out degree one that contain a path of length k+1 from the first vertex to the last vertex and can be recognized by exchanging o(k log n) bits using a simple k-round protocol requires exchanging &ohgr;(n1/2/k4log3n) bits if any (k&minus;1)- round protocol is used. 2) for every k &ge; 1 and for infinitely many n &ge; 1, there exists a collection of sets lnk @@@@ {0,1}2n that can be recognized by exchanging o(k log n) bits using a k-round protocol, and any (k&minus;1)-round protocol recognizing lnk requires exchanging &ohgr;(n/k) bits. 3) given a set l @@@@ {0,1}2n, there is a set l@@@@{0,1}8n such that any (k-round) protocol recognizing l@@@@ can be transformed to a (k-round) fixed partition protocol recognizing l with the same communication complexity, and vice versa. 4) for every integer function f, 1 &le;f(n) &le; n, there are languages recognized by a one round deterministic protocol exchanging f(n) bits, but not by any nondeterministic protocol exchanging f(n)&minus;1 bits. the first two results show in an incomparable way an exponential gap between (k&minus;1)-round and k-round protocols, settling a conjecture by papadimitriou and sipser. the third result shows that as long as we are interested in existence proofs, a fixed partition of the input is not a restriction. the fourth result extends a result by papadimitriou and sipser who showed that for every integer function f, 1 &le; f(n) &le; n, there is a language accepted by a deterministic protocol exchanging f(n) bits but not by any deterministic protocol exchanging f(n) &minus; 1 bits.
locally decodable codes with 2 queries and polynomial identity testing for depth 3 circuits. in this work we study two, seemingly unrelated, notions. locally decodable codes (ldcs) are codes that allow the recovery of each message bit from a constant number of entries of the codeword. polynomial identity testing (pit) is one of the fundamental problems of algebraic complexity: we are given a circuit computing a multivariate polynomial and we have to determine whether the polynomial is identically zero. we improve known results on locally decodable codes and on polynomial identity testing and show a relation between the two notions. in particular we obtain the following results:we show that if e: fn → fm is a linear ldc with 2 queries then m = exp(ω(n)). previously this was only known for fields of size << 2n [18].we show that from every depth 3 arithmetic circuit (σπς circuit), c, with a bounded (constant) top fan-in that computes the zero polynomial, one can construct a locally decodeable code. more formally: assume that c is minimal (no subset of the multiplication gates sums to zero) and simple (no linear function appears in all the multiplication gates). denote by d the degree of the polynomial computed by c and by r the rank of the linear functions appearing in c. then we can construct a linear ldc with 2 queries, that encodes messages of length r/polylog(d) by codewords of length o(d).we prove a structural theorem for σπς circuits, with a bounded top fan-in, that compute the zero polynomial. in particular we show that if such a circuit is simple and minimal and of polynomial size then its rank, r, is only polylogarithmic in the number of variables (a priory it could have been linear).we give new pit algorithms for σπς circuits with a bounded top fan-in:a deterministic algorithm that runs in quasi polynomial time.a randomized algorithm that runs in polynomial time and uses only polylogarithmic number of random bits..moreover, when the circuit is multilinear our deterministic algorithm runs in polynomial time. previously, deterministic subexponential time algorithms for pit in bounded depth circuits were known only for depth 2 circuits (in the black box model)[22, 9, 28]. in particular, for the special case of depth 3 circuits with 3 multiplication gates our result resolves an open question asked by klivans and spielman [28].
contention in shared memory algorithms. most complexity measures for concurrent algorithms for asynchronous shared-memory architectures focus on process steps and memory consumption. in practice, however, performance of multiprocessor algorithms is heavily influenced by contention, the extent to which processess access the same location at the same time. nevertheless, even though contention is one of the principal considerations affecting the performance of real algorithms on real multiprocessors, there are no formal tools for analyzing the contention of asynchronous shared-memory algorithms.this paper introduces the first formal complexity model for contention in shared-memory multiprocessors. we focus on the standard multiprocessor architecture in which n asynchronous processes communicate by applying read, write, and read-modify-write operations to a shared memory. to illustrate the utility of our model, we use it to derive two kinds of results: (1) lower bounds on contention for well-known basic problems such as agreement and mutual exclusion, and (2) trade-offs between the length of the critical path (maximal number of accesses to shared variables performed by a single process in executing the algorithm) and contention for these algorithms. furthermore, we give the first formal contention analysis of a variety of counting networks, a class of concurrent data structures inplementing shared counters. experiments indicate that certain counting networks outperform conventional single-variable counters at high levels of contention. our analysis provides the first formal model explaining this phenomenon.
concurrent zero-knowledge. concurrent executions of a zero-knowledge protocol by a single prover (with one or more verifiers) may leak information and may not be zero-knowledge in toto. in this article, we study the problem of maintaining zero-knowledge.we introduce the notion of an (&alpha;, &beta;) timing constraint: for any two processors p1 and p2, if p1 measures &alpha; elapsed time on its local clock and p2 measures &beta; elapsed time on its local clock, and p2 starts after p1 does, then p2 will finish after p1 does. we show that if the adversary is constrained by an (&alpha;, &beta;) assumption then there exist four-round almost concurrent zero-knowledge interactive proofs and perfect concurrent zero-knowledge arguments for every language in np. we also address the more specific problem of deniable authentication, for which we propose several particularly efficient solutions. deniable authentication is of independent interest, even in the sequential case; our concurrent solutions yield sequential solutions without recourse to timing, that is, in the standard model.
2-round zero knowledge and proof auditors. we construct 2-round (ie, 2-message), public-coin, black-box (concurrent) zero-knowledge proof systems and arguments for any language in np under the assumption that the prover is resource-bounded during the execution of the protocol.
approximate counting by dynamic programming. we give efficient algorithms to sample uniformly, and count approximately, the solutions to a zero-one knapsack problem. the algorithm is based on using dynamic programming to provide a deterministic relative approximation. then "dart throwing" techniques are used to give arbitrary approximation ratios. we also indicate how further improvements can be obtained using randomized rounding. we extend the approach to several related problems: the m-constraint zero-one knapsack, the general integer knapsack (including its m-constraint version) and contingency tables with constantly many rows.
a random polynomial time algorithm for approximating the volume of convex bodies a randomized polynomial-time algorithm for approximating the volume of a convex body k in n-dimensional euclidean space is presented. the proof of correctness of the algorithm relies on recent theory of rapidly mixing markov chains and isoperimetric inequalities to show that a certain random walk can be used to sample nearly uniformly from within k.
speedups of deterministic machines by synchronous parallel machines this paper presents the new speedups dtime(t) @@@@ atime(t/log t) and dtime(t) @@@@ pram-time(@@@@t). these improve the results of hopcroft, paul, and valiant that dtime(t) @@@@ dspace(t/log t), and of paul and reischuk that dtime(t) @@@@ atime(t log log t/log t). the new approach unifies not only these two previous results, but also the result of paterson and valiant that size(t) @@@@ depth(o(t/log t)).
tight security proofs for the bounded-storage model. (math) in the bounded-storage model for information-theoretically secure encryption and key-agreement one can prove the security of a cipher based on the sole assumption that the adversary's storage capacity is bounded, say by s bits, even if her computational power is unlimited. assume that a random t-bit string r is either publicly available (e.g. the signal of a deep space radio source) or broadcast by one of the legitimate parties. if s$xi;t, the adversary can store only partial information about r. the legitimate sender alice and receiver bob, sharing a short secret key k initially, can therefore potentially generate a very long n-bit one-time pad x with n&raquo;|k| about which the adversary has essentially no information, thus at first glance apparently contradicting shannon's bound on the key size of a perfect cipher.all previous results in the bounded-storage model were partial or far from optimal, for one of the following reasons: either the secret key k had in fact to be longer than the derived one-time pad, or t had to be extremely large (t&rho;ns), or the adversary was assumed to be able to store only actual bits of r rather than arbitrary s bits of information about r, or the adversary could obtain a non-negligible amount of information about x.in this paper we prove the first non-restricted security result in the bounded-storage model, exploiting the full potential of the model: k is short, x is very long (e.g. gigabytes), t needs to be only moderately larger than s, and the security proof is optimally strong. in fact, we prove that s/t can be arbitrarily close to 1 and hence the storage bound is essentially optimal.
computability concepts for programming language semantics this paper is about mathematical problems in programming language semantics and their influence on recursive function theory. we define a notion of computability on continuous higher types (for all types) and show its equivalence to effective operators. this result shows that our computable operators can model mathematically (i.e. extensionally) everything that can be done in an operational semantics. these new recursion theoretic concepts which are appropriate to semantics also allow us to construct scott models for the &lgr;-calculus which contain all and only computable elements. depending on the choice of the initial cpo, our general theory yields a theory for either strictly determinate or else arbitrary non-deterministic objects (parallelism). the formal theory is developed in part ii of this paper. part i gives motivation and comparison with related work.
on (un)predictability of formal languages (extended abstract) formal language theory deals with a variety of classes of languages. some of these are abstracting features of languages used for communication (as e.g., natural languages, programming languages or languages used in logic), some of them are abstracting features of languages used for description of processes (as e.g. basic classes of l languages) and still others are considered for mathematical reasons. can we have a criterion for deciding whether a language can serve as a &ldquo;communication language&rdquo; (e.g. for man-to-man or man-to-machine communication) ? our main result (the basic unpredictability inequality) displays a connection between the &ldquo;rate of unpredictability&rdquo; and the relative number of subpatterns occurring in a language. after establishing this result we investigate (as samples) two classes of languages: regular languages and dol languages
complexity of implementations on the level of algebraic specifications the aim of this paper is to study implementations of abstract data types and their complexity within the framework of algebraic specifications. an implementation of an abstract data type adto by an abstract data type adt1 is defined on a syntactical and on a semantical level where data and operations of adto are simulated by those of adt1. in order to investigate complexity of implemented operations and to compair different implementations we axiomatically introduce complexity measures for the operations in adto with respect to a given implementation of adto by adt1. a most natural interesting class of complexity measures which satisfy our axioms is compatible with time complexity of turing machines. this is shown by specification and implementation of timebounded turing machines within our algebraic framework and the simulation of a general nondeterministic interpreter for algebraic implementations by a nondeterministic turing machine. this relationship allows to show the existence of solutions and of upper and lower bounds for the complexity of a broad class of implementation problems in our sense. a corollary shows that there are algebraic specifications for all those recursive functions which are bounded in time by algebraically specifyable functions. since the complexity measure for adto-operations in a given implementation impl1 of adto by adt1 in general depends on the complexity of the adt1-operations it is possible to substitute the complexity of the adt1-operations which may be obtained from an implementation impl2 of adt1 by adt2. on the other hand the composite implementation impl3 of adto by adt2 can be constructed and it is shown that the composite complexity of impl3 is less or equal to the substituted complexity considered above provided that some natural consistency conditions are satisfied.
classes of semigroups and classes of sets let a be a subset of &sgr;+, the free semigroup generated by a finite set &sgr;. in &sgr;+ we consider congruences satisfying the condition x&ntilde;y & x&egr;a@@@@y&egr; a among all such congruences there is a largest one, and the quotient monoid by this congruence is denoted by sa and is called the syntactic semigroup of a. this semigroup is finite if and only if the set a is recognizable (by a finite automaton). the semigroup sa can then easily be described using the minimal automaton of a. it is reasonable to expect that reasonable properties of the recognizable set a will be reflected by reasonable properties of the finite semigroups sa and vice-versa. in trying to establish such a dialog, one is handicapped by the fact that there are finite semigroups which are not syntactic monoids of any set. the objective of this note is to state a theorem showing that the above inconvenience disappears if one considers classes of sets (rather than individual sets) and classes of semigroups.
new results on monotone dualization and generating hypergraph transversals. we consider the problem of dualizing a monotone cnf (equivalently, computing all minimal transversals of a hypergraph) whose associated decision problem is a prominent open problem in np-completeness. we present a number of new polynomial time, respectively, output-polynomial time results for significant cases, which largely advance the tractability frontier and improve on previous results. furthermore, we show that duality of two monotone cnfs can be disproved with limited nondeterminism. more precisely, this is feasible in polynomial time with o(log2 n/\log log n) suitably guessed bits. this result sheds new light on the complexity of this important problem.
excellent codes from modular curves. we introduce a new construction of error-correcting codes from algebraic curves over finite fields. modular curves of genus g\ra\infty over a field of size q_0^2 yield nonlinear codes more efficient than the linear goppa codes obtained from the same curves. these new codes now have the highest asymptotic transmission rates known for certain ranges of alphabet size and error rate. both the theory and possible practical use of these new record codes require the development of new tools. on the theoretical side, establishing the transmission rate depends on an error estimate for a theorem of schanuel applied to the function field of an asymptotically optimal curve. on the computational side, actual use of the codes will hinge on the solution of new problems in the computational algebraic geometry of curves.
unconditional lower bounds on the time-approximation tradeoffs for the distributed minimum spanning tree problem. the design of distributed approximation protocols is a relatively new rapidly developing area of research. however, so far little progress was done in the study of the hardness of distributed approximation. in this paper we initiate the systematic study of this subject, and show strong unconditional lower bounds on the time-approximation tradeoff of the distributed minimum spanning tree problem, and some of its variants.
lower-stretch spanning trees. we show that every weighted connected graph g contains as a subgraph a spanning tree into which the edges of g can be embedded with average stretch o (log2 n log log n). moreover, we show that this tree can be constructed in time o (m log2n) in general, and in time o (mlog n) if the input graph is unweighted. the main ingredient in our construction is a novel graph decomposition technique.our new algorithm can be immediately used to improve the running time of the recent solver for symmetric diagonally dominant linear systems of spielman and teng from m2(o√lognlog log n) to m log o(1)n and to o (n log2n log log n) when the system is planar. our result can also be used to improve several earlier approximation algorithms that use low-stretch spanning trees.
combinatorial logarithmic approximation algorithm for directed telephone broadcast problem. (math) consider a synchronous network of processors, modeled by directed or undirected graph g = (v,e), in which on each round every processor is allowed to choose one of its neighbors and to send him a message. given a processor s &egr; v, and a subset t &sube; v of processors, the telephone multicast problem requires to compute the shortest schedule (in terms of the number of rounds) that delivers a message from s to all the processors of t. the particular case t = v is called telephone broadcast problem.these problems have multiple applications in distributed computing. several approximation algorithms with polylogarithmic ratio, including one with logarithmic ratio, for the undirected variants of these problems are known. however, all these algorithms involve solving large linear programs. devising a polylogarithmic approximation algorithm for the directed variants of these problems is anopen problem, posed in [15].we devise a combinatorial logarithmic approximation algorithm for these problems, that applies also for the directed broadcast problem. our algorithm has significantly smaller running time, and seems to reveal more information about the combinatorial structure of the solution, than the previous algorithms, that are based on linear programming.(math) we also improve the lower bounds on the approximation threshold of these problems. both problems are known to be 3/2-inapproximable. for the undirected (resp., directed) broadcast problem we show that it is np-hard (resp., impossible unless $np &supe; dtime(no(log n))) to approximate it within a ratio of 3 &mdash;&egr; for any &egr; &rho; 0 (resp., &omega;(\sqrt log n)).finally, we study the radio broadcast problem. its setting is similar to the telephone broadcast problem, but in every round every processor may either send a message to all its neighbors or may not send it at all. a processor is informed in a certain round if and only if it receives a message from precisely one neighbor.(math) this problem was known to admit o(log2 n)-approximation algorithm, but no hardness of approximation was known. in this paper we show that the problem is &omega;(log n)-inapproximable unless np &sube; bptime(nlog log n}).
(1+epsilon, beta)-spanner constructions for general graphs. an {\em $(\alpha,\beta)$-spanner} of a graph g is a subgraph h such that $\mathit{dist}_h(u,w)\le \alpha\cdot \mathit{dist}t_g(u,w)+\beta$ for every pair of vertices u,w, where distg'(u,w) denotes the distance between two vertices u and v in g'. it is known that every graph g has a polynomially constructible $(2\kappa-1,0)$-spanner (also known as multiplicative $(2\kappa-1)$-spanner) of size $o(n^{1+1/\kappa})$ for every integer $\kappa\ge 1$, and a polynomially constructible (1,2)-spanner (also known as additive 2-spanner) of size ${\tilde o}(n^{3/2})$. this paper explores hybrid spanner constructions (involving both multiplicative and additive factors) for general graphs and shows that the multiplicative factor can be made arbitrarily close to 1 while keeping the spanner size arbitrarily close to o(n), at the cost of allowing the additive term to be a sufficiently large constant. more formally, we show that for any constant $\epsilon, \lambda > 0$ there exists a constant $\beta = \beta(\epsilon, \lambda)$ such that for every $n$-vertex graph g there is an efficiently constructible $(1+ \epsilon, \beta)$-spanner of size $o(n^{1 + \lambda})$.
probabilistic tree automata the purpose of this paper is meant to be three-fold. first it will introduce the reader to the concepts of probabilistic languages and probabilistic grammars. second, it indicates that previous definitions of probabilistic finite automaton have always been restricted to 1 of 8 classes of automaton and shows that other classes are useful. third, the probabilistic concept is extended from finite automata to higher level automata (such as probabilistic pdas and probabilistic turing automata). a specific application of this theory is given in the development of probabilistic tree automata. theorems concerning these automata and operations on them are presented. it is indicated that this type of automaton is relevant because it characterizes probabilistic context free languages. the results are taken from the author's phd thesis.4
decision procedures and expressiveness in the temporal logic of branching time in this paper we consider the computation tree logic (ctl) proposed in [ce] which extends the unified branching time logic (ub) of [bmp] by adding an until operator. we establish that ctl has the small property by showing that any satisfiable ctl formulae is satisfiable in a small finite model obtained from a small -&-ldquo;pseudo-model-&-rdquo; resulting from the fischer ladner quotient construction. we then give an exponential time algorithm for deciding satisfiability in ctl, and extend the axiomatization of ub given in [bmp] to a complete axiomatization for ctl. lastly, we study the relative expressive power of a family of temporal logics obtained by extending or restricting the syntax of ub and ctl.
deciding branching time logic in this paper we study the full branching time logic (ctl*) in which a path quantifier, either a (&ldquo;for all paths-&-rdquo;) or e (-&-ldquo;for some path&rdquo;), prefixes an assertion composed of arbitrary combinations of the usual linear time operators f (&ldquo;sometime&rdquo;), g (&ldquo;always&rdquo;), x (&ldquo;nexttime&rdquo;), and u (&ldquo;until&rdquo;). we show that the problem of determining if a ctl* formula is satisfiable in structure generated by a binary relation is decidable in triple exponential time. the decision procedure exploits the special structure of the finite state &ohgr;-automata for linear temporal formulae which allows them to be determinized with only a single exponential blowup in size. we also compare the expressive power of tree automata with ctl* augmented by quantified auxillary propositions.
iterated pushdown automata and complexity classes an iterated pushdown is a pushdown of pushdowns of ... of pushdowns. an iterated exponential function is 2 to the 2 to the ... to the 2 to some polynomial. the main result is that nondeterministic 2-way and multi-head iterated pushdown automata characterize deterministic iterated exponential time complexity classes. this is proved by investigating both nondeterministic and alternating auxiliary iterated pushdown automata, for which similar characterization results are given. in particular it is shown that alternation corresponds to one more iteration of pushdowns. these results are applied to the 1-way iterated pushdown automata: (1) they form a proper hierarchy with respect to the number of iterations, (2) their emptiness problem is complete in deterministic iterated exponential time.
tree transducers, l systems and two-way machines (extended abstract) this extended abstract is a condensed version of the results presented in two technical reports ([16] and [13]). in [16] a systematic treatment of the relationships between parallel rewriting systems (top-down tree transducer, etol system) and two-way machines (2-way gsm, tree-walking automaton, checking stack automaton) is given. particular attention is paid to the effect of restricting the copying power of these devices. in [13] the results of [16] are employed to show that the iteration of nondeterministic top-down tree transducers, of nondeterministic 2-way gsm's and of control on etol systems each gives rise to a proper hierarchy.
testing multivariate linear functions: overcoming the generator bottleneck. the problem of testing program correctness has received considerable attention in computer science. one approach to this problem is the notion of self-testing programs \cite{blumlubyrubinfeld}. self-testing usually becomes more costly in the case of testing multivariate functions. in this paper we present efficient methods for self-testing multivariate linear functions. we then apply these methods to several multivariate linear problems to construct efficient self-testers.
biased dictionaries with fast insert/deletes. a dictionary data structure supports efficient search, insert, and delete operations on n keys from a totally ordered universe. red-black trees, 2-3 trees, avl trees, skip lists and other classic data structures facilitate o(logn) time search, insert and deletes, matching the information theoretic lower bound when access probabilities are uniform i.i.d. if access probabilities are non-uniform but still i.i.d., there are other weighted data structures such as d-trees, biased search trees, splay trees and treaps which can achieve optimality.in many applications, however, the source of nonuniformity in access probabilities is locality of reference: examples include memory, cache, disk and buffer management and emerging applications in internetwork traffic management. in such applications, the access probability of any given key is not i.i.d., but decreases with idle time since the last access to the key.it is possible to adjust the weighted dictionaries to achieve optimal search time even under time dependent distributions; however insert/delete times will be suboptimal at o(logn). in this paper, we present a lazy updating scheme which can be applied to weighted dictionaries to improve their amortized insert/delete performance when access probabilities decrease with time; optimality of search time is preserved. more speci%cally, let r(k) be the number of distinct keys accessed since the last access to key k- that is r(k) is the move-to-front rank of k. let rmax(k) be the maximum rank of k during its lifetime. then our lazy update scheme enables the abovementioned data structures to perform search in o(log r(k)) time and insert/delete in o(log rmax(k)) time. we illustrate our lazy update scheme in the context of a new biased skip list data structure and show that our bounds are optimal.
lower bounds for noisy boolean decision trees. we present a new method for deriving lower bounds to the expected number of queries made by noisy decision trees computing boolean functions. the new method has the feature that expectations are taken with respect to a uniformly distributed random input, as well as with respect to the random noise, thus yielding stronger lower bounds. it also applies to many more functions than do previous results. the method yields a simple proof of the result (previously established by reischuk and schmeltz) that almost all boolean functions of n arguments require omega(n log n) queries, and strengthens this bound from the worst-case over inputs to the average over inputs. the method also yields bounds for specific boolean functions in terms of their spectra (their fourier transforms). the simplest instance of this spectral bound yields the result (previously established by feige, peleg, raghavan and upfal) that the parity function of n arguments requires omega(n log n) queries, and again strengthens this bound from the worst-case over inputs to the average over inputs. in its full generality, the spectral bound applies to the "highly resilient" functions introduced by chor, friedman, goldreich, hastad, rudich and smolensky, and it yields non-linear lower bounds whenever the resiliency is asymptotic to the number of arguments.
approximations of general independent distributions we describe efficient constructions of small probability spaces that approximate the independent distribution for general random variables. previous work on efficient constructions concentrate on approximations of the independent distribution for the special case of uniform boolean-valued random variables. our results yield efficient constructions of small sets with low discrepancy in high dimensional space and have applications to derandomizing randomized algorithms.
a combinatorial problem which is complete in polynomial space we consider a generalization, which we call the shannon switching game on vertices, of a familiar board game called hex. we show that determining who wins such a game if each player plays perfectly is very hard; in fact, it is as hard as carrying out any polynomial-space-bounded computation. this result suggests that the theory of combinatorial games is difficult.
the complexity of pure nash equilibria. we investigate from the computational viewpoint multi-player games that are guaranteed to have pure nash equilibria. we focus on congestion games, and show that a pure nash equilibrium can be computed in polynomial time in the symmetric network case, while the problem is pls-complete in general. we discuss implications to non-atomic congestion games, and we explore the scope of the potential function method for proving existence of pure nash equilibria.
horn clauses and database dependencies (extended abstract) in the last year or so, a number of generalizations of these dependencies have appeared: nicolas's mutual dependencies [ni], which say that a relation is the join of three of its projections; rissanen's and aho, beeri, and ullman's join dependencies ([ri], [abu]), which generalize further to an arbitrary number of projections; paradaens' transitive dependencies [pa], which generalize both fds and mvds; sagiv and walecka's subset dependencies [sw] which generalize embedded mvds; and sadri and ullman's template dependencies [su], which generalize embedded join dependencies. the purpose of this paper is to help bring order to the chaos by presenting certain mathematical properties shared by all of these dependencies. in section 2, we introduce the concept of &ldquo;faithfulness&rdquo; (with respect to direct product), and show that ids and eids are faithful, whereas slight variations are not necessarily faithful. in section 3, we discuss &ldquo;armstrong relations&rdquo;, which were known to exist in certain special cases (such as when the only sentences of interest were functional, multivalued, and join dependencies).in section 4, we discuss finite armstrong relations.in section 5, we present some more counterexamples about the existence of armstrong relations. in section 6, we discuss projections of classes of relations. although zaiddan [za] showed that projections of fd classes are not necessarily fd classes, it turns out that projections of fd classes (and, even more, of id classes) are id classes. in section 7, we discuss certain extensions of our results.
a tight bound on approximating arbitrary metrics by tree metrics. in this paper, we show that any n point metric space can be embedded into a distribution over dominating tree metrics such that the expected stretch of any edge is o(log n). this improves upon the result of bartal who gave a bound of o(log n log log n). moreover, our result is existentially tight; there exist metric spaces where any tree embedding must have distortion ω(log n)-distortion. this problem lies at the heart of numerous approximation and online algorithms including ones for group steiner tree, metric labeling, buy-at-bulk network design and metrical task system. our result improves the performance guarantees for all of these problems.
efficient algorithms for inverting evolution. evolution can be mathematically modelled by a stochastic process that operates on the dna of species. such models are based on the established theory that the dna sequences, or genomes, of all extant species have been derived from the genome of the common ancestor of all species by a process of random mutation and natural selection.a stochastic model of evolution can be used to construct phylogenies, or evolutionary trees, for a set of species. maximum likelihood estimation (mle) methods seek the evolutionary tree which is most likely to have produced the dna under consideration. while these methods are intellectually satisfying, they have not been widely accepted because of their computational intractability.in this paper, we address the intractability of mle methods as follows: we introduce a metric on stochastic process models of evolution. we show that this metric is meaningful by proving that in order for any algorithm to distinguish between two stochastic models that are close according to this metric, it needs to be given many observations. we complement this result with a simple and efficient algorithm for inverting the stochastic process of evolution, that is, for building a tree from observations on two-state characters. (we will use the same techniques in a subsequent paper to solve the problem for multistate characters, and hence for building a tree from dna sequence data.) the tree we build is provably close, in our metric, to the tree generating the data and gets closer as more observations become available.though there have been many heuristics suggested for the problem of finding good approximations to the most likely tree, our algorithm is the first one with a guaranteed convergence rate, and further, this rate is within a polynomial of the lower-bound rate we establish. ours is also the first polynomial-time algorithm that is proven to converge at all to the correct tree.
a tight time lower bound for space-optimal implementations of multi-writer snapshots. a snapshot object consists of a collection of m > 1 components, each capable of storing a value, shared by n processes in an asynchronous shared-memory distributed system. it supports two operations: a process can update any individual component or atomically scan the entire collection to obtain the values of all the components. it is possible to implement a snapshot object using m registers so that each operation takes o(mn) time.in a previous paper, we proved that m registers are necessary to implement a snapshot object with m < n-1 components. here we prove that, for any such space-optimal implementation, ω(mn) steps are required to perform a scan operation in the worst case, matching the upper bound. we also extend our space and time lower bounds to implementations that use single-writer registers in addition to the multi-writer registers. specifically, we prove that at least m multi-writer registers are still needed, provided the scans do not read a large fraction of the single-writer registers. we also prove that any implementation that uses single-writer registers in addition to $m$ multi-writer registers uses ω(√mn) steps in the worst case. our proof yields insight into the structure of any implementation that uses only m multi-writer registers, showing that processes must access the multi-writer registers in a very constrained way.
time-space tradeoffs for implementations of snapshots. a snapshot object is an abstraction of the fundamental problem of obtaining a consistent view of the contents of the shared memory in a distributed system while other processes may concurrently update those contents. a snapshot object stores an array of m components and can be accessed by two operations: an update that changes the value of an individual component and a powerful scan that returns the contents of the entire array.this paper proves time-space tradeoffs for fault-tolerant implementations of a snapshot object from registers that support only read and write operations. for anonymous implementations (where all processes are programmed identically), we prove that a scan requires ω(n/r) time, where n is the number of processes in the system and r is the number of registers used by the implementation. for the general non-anonymous case, we prove that, for any fixed r, the time required to do a scan grows without bound as n increases. these tradeoffs hold even in the case where the snapshot object has just two components.this is the first time a lower bound on the tradeoff between time complexity and the number of registers has been proved for any problem in asynchronous shared-memory systems. we introduce a new tool for proving distributed lower bounds: the notion of a shrinkable execution, from which an adversary can remove portions as necessary.
optimal algorithms for approximate clustering in a clustering problem, the aim is to partition a given set of n points in d-dimensional space into k groups, called clusters, so that points within each cluster are near each other. two objective functions frequently used to measure the performance of a clustering algorithm are, for any l4 metric, (a) the maximum distance between pairs of points in the same cluster, and (b) the maximum distance between points in each cluster and a chosen cluster center; we refer to either measure as the cluster size. we show that one cannot approximate the optimal cluster size for a fixed number of clusters within a factor close to 2 in polynomial time, for two or more dimensions, unless p=np. we also present an algorithm that achieves this factor of 2 in time &ogr;(n log k), and show that this running time is optimal in the algebraic decision tree model. for a fixed cluster size, on the other hand, we give a polynomial time approximation scheme that estimates the optimal number of clusters under the second measure of cluster size within factors arbitrarily close to 1. our approach is extended to provide approximation algorithms for the restricted centers, suppliers, and weighted suppliers problems that run in optimal &ogr;(n log k) time and achieve optimal or nearly optimal approximation bounds.
computing the median with uncertainty. we consider a new model for computing with uncertainty. it is desired to compute a function f(x1,. . .,xn), where x1, . . ., xn are unknown but guaranteed to lie in specified intervals i1, . . ., in. it is possible to query the precise value of any xj at a cost cj. the goal is to pin down the value of f to within a precision $\delta$ at a minimum possible cost. we focus on the selection function f which returns the value of the kth smallest argument. we present optimal offline and online algorithms for this problem.
relations between average case complexity and approximation complexity. we investigate relations between average case complexity and the complexity of approximation. under the assumption that refuting 3sat is hard on average on a natural distribution, we derive new hardness of approximation results.
on sums of independent random variables with unbounded variance, and estimating the average degree in a graph. we prove the following inequality: for every positive integer $n$ and every collection $x_1, \ldots, x_n$ of nonnegative independent random variables, each with expectation 1, the probability that their sum remains below $n+1$ is at least $\alpha > 0$. our proof produces a value of $\alpha = 1/13 \simeq 0.077$, but we conjecture that the inequality also holds with $\alpha = 1/e \simeq 0.368$.as an example for the use of the new inequality, we consider the problem of estimating the average degree of a graph by querying the degrees of some of its vertices. we show the following threshold behavior: approximation factors above 2 require far fewer queries than approximation factors below 2. the new inequality is used in order to get tight (up to multiplicative constant factors) relations between the number of queries and the quality of the approximation. we show how the degree approximation algorithm can be used in order to quickly find those edges in a network that belong to many shortest paths.
on maximizing welfare when utility functions are subadditive. we consider the problem of maximizing welfare when allocating $m$ items to $n$ players with subadditive utility functions. our main result is a way of rounding any fractional solution to a linear programming relaxation to this problem so as to give a feasible solution of welfare at least $1/2$ that of the value of the fractional solution. this approximation ratio of $1/2$ is an improvement over an $\omega(1/\log m)$ ratio of dobzinski, nisan, and schapira [proceedings of the 37th annual acm symposium on theory of computing (baltimore, md), acm, new york, 2005, pp. 610-618]. we also show an approximation ratio of $1-1/e$ when utility functions are fractionally subadditive. a result similar to this last result was previously obtained by dobzinski and schapira [proceedings of the 17th annual acm-siam symposium on discrete algorithms (miami, fl), siam, philadelphia, 2006, pp. 1064-1073], but via a different rounding technique that requires the use of a so-called &ldquo;xos oracle.&rdquo; the randomized rounding techniques that we use are oblivious in the sense that they only use the primal solution to the linear program relaxation, but have no access to the actual utility functions of the players.
zero knowledge proofs of identity in this paper we extend the notion of zero knowledge proofs of membership (which reveal one bit of information) to zero knowledge proofs of knowledge (which reveal no information whatsoever). after formally defining this notion, we show its relevance to identification schemes, in which parties prove their identity by demonstrating their knowledge rather than by proving the validity of assertions. we describe a novel scheme which is provably secure if factoring is difficult and whose practical implementations are about two orders of magnitude faster than rsa-based identification schemes. in the last part of the paper we consider the question of sequential versus parallel executions of zero knowledge protocols, define a new notion of &ldquo;transferable information&rdquo;, and prove that the parallel version of our identification scheme (which is not known to be zero knowledge) is secure since it reveals no transferable information.
improved approximation algorithms for minimum-weight vertex separators. we develop the algorithmic theory of vertex separators, and its relation to the embeddings of certain metric spaces. unlike in the edge case, we show that embeddings into l1 (and even euclidean embeddings) are insufficient, but that the additional structure provided by many embedding theorems does suffice for our purposes.we obtain an o(√log n) approximation for min-ratio vertex cuts in general graphs, based on a new semidefinite relaxation of the problem, and a tight analysis of the integrality gap which is shown to be θ(√log n). we also prove various approximate max-flow/min-vertex-cut theorems, which in particular give a constant-factor approximation for min-ratio vertex cuts in any excluded-minor family of graphs. previously, this was known only for planar graphs, and for general excluded-minor families the best-known ratio was o(log n).these results have a number of applications. we exhibit an o(√log n) pseudo-approximation for finding balanced vertex separators in general graphs. in fact, we achieve an approximation ratio of o(√log opt) where opt is the size of an optimal separator, improving over the previous best bound of o(log opt). likewise, we obtain improved approximation ratios for treewidth: in any graph of treewidth k, we show how to find a tree decomposition of width at most o(k √log k), whereas previous algorithms yielded o(k log k). for graphs excluding a fixed graph as a minor (which includes, e.g., bounded genus graphs), we give a constant-factor approximation for the treewidth; this can be used to obtain the first polynomial-time approximation schemes for problems like minimum feedback vertex set and minimum connected dominating set in such graphs.
two prover protocols: low error at affordable rates. we introduce the miss-match form for two-prover one-round proof systems. any two-prover one-round proof system can be easily modified so as to be in miss-match form. proof systems in miss-match form have the "projection" property that is important for deriving hardness of approximation results for np-hard combinatorial optimization problems.our main result is an upper bound on the number of parallel repetitions that suffice in order to reduce the error of miss-match proof systems from p to $\epsilon$. this upper bound depends only on p and on $\epsilon$ (polynomial in 1/(1-p) and in $1/\epsilon$). based on previous work, it follows that for any $\epsilon >0,$ np has two-prover one-round proof systems with logarithmic-sized questions, constant-sized answers, and error at most $\epsilon$.as part of our proof we prove upper bounds on the influence of random variables on multivariate functions, which may be of independent interest.
on the hardness of computing the permanent of random matrices (extended abstract) we study the complexity of computing the permanent on random inputs. we consider matrices drawn randomly from the space of n by n matrices with integer values between 0 and p&ndash;1, for any large enough prime p. we show that any polynomial time algorithm which computes the permanent correctly on even an exponentially small fraction of these matrices, implies the collapse of the polynomial-time hierarchy to its second level. we also show that it is hard to get partial information about the value of the permanent modulo p. we show that any balanced polynomial-time 0/1 predicate (e.g., the least significant bit, the parity of all the bits, the quadratic residuosity character) cannot be guessed with probability significantly greater than 1/2 (unless the polynomial hierarchy collapses). this result can be extended to showing simultaneous hardness for linear size groups of bits.
two-prover one-round proof systems: their power and their problems (extended abstract) we characterize the power of two-prover one-round (mip(2,1)) proof systems, showing that mip(2,1)=nexptime. however, the following intriguing question remains open: does parallel repetition decrease the error probability of mip(2,1) proof systems?. we use techniques based on quadratic programming to study this problem, and prove the parallel repetition conjecture in some special cases. interestingly, our work leads to a general polynomial time heuristic for any np-problem. we prove the effectiveness of this heuristic for several problems, such as computing the chromatic number of perfect graphs.
finding small balanced separators. let g be an n-vertex graph that has a vertex separator of size k that partitions the graph into connected components of size smaller than α n, for some fixed 2/3 ≤ α < 1. such a separator is called an α-separator. finding an α-separator of size at most k is np-hard. moreover, under reasonable complexity theoretic assumptions, it is shown that this problem is not polynomially solvable even when k=o(log n). in this paper, we give a randomized algorithm that finds an α-separator of size k in the given graph, unless the graph contains an (α+ε)-separator of size strictly less than k, in which case our algorithm finds one such separator. for fixed ε, the running time of our algorithm is no(1)2o(k), which is polynomial for k = o(log n). for bounded degree graphs (as well as for the case of finding balanced edge separators), we present a deterministic algorithm with similar running time.our algorithm involves (among other things) a new concept that we call (ε,k)-samples. this is related to the notion of detection sets for network failures, introduced by kleinberg [focs 2000]. our proofs adapt and simplify techniques that were introduced by kleinberg. as a by-product, our proof improves the known bounds on the size of detection sets. we also show applications of (ε,k)-samples to problems in approximation algorithms and rigorous analysis of heuristics.
on the integrality ratio of semidefinite relaxations of max cut. max cut is the problem of partitioning the vertices of a graph into two sets, maximizing the number of edges joining these sets. this problem is np-hard. goemans and williamson proposed an algorithm that first uses a semidefinite programming relaxation of max cut to embed the vertices of the graph on the surface of an n dimensional sphere, and then uses a random hyperplane to cut the sphere in two, giving a cut of the graph. they show that the expected number of edges in the random cut is at least &agr; \cdot sdp, where &agr; \simeq 0.87856 and sdp is the value of the semidefinite program.this manuscript shows the following results:1. the integrality ratio of the semidefinite program is &agr;. the previously known bound on the integrality ratio was roughly 0.8845.2. in the presence of the so called &ldquo;triangle constraints&rdquo;, the integrality ratio is no better than roughly 0.891. the previously known bound was above 0.95.
hardness of approximate two-level logic minimization and pac learning with membership queries. producing a small dnf expression consistent with given data is a classical problem in computer science that occurs in a number of forms and has numerous applications. we consider two standard variants of this problem. the first one is two-level logic minimization or finding a minimal dnf formula consistent with a given complete truth table (tt-mindnf. this problem was formulated by quine in 1952 and has been since one of the key problems in logic design. it was proved np-complete by masek in 1979. the best known polynomial approximation algorithm is based on a reduction to the set-cover problem and produces a dnf formula of size o(d ∙ opt), where d is the number of variables. we prove that tt-mindnf is np-hard to approximate within dγ for some constant γ > 0, establishing the first inapproximability result for the problem.the other dnf minimization problem we consider is pac learning of dnf expressions when the learning algorithm must output a dnf expression as its hypothesis (referred to as proper learning). we prove that dnf expressions are np-hard to pac learn properly even when the learner has access to membership queries, thereby answering a long-standing open question due to valiant [40]. finally, we show that inapproximability of tt-mindnf implies hardness results for restricted proper learning of dnf expressions with membership queries even when learning with respect to the uniform distribution only.
a decidable propositional probabilistic dynamic logic a propositional version of feldman and harel's pr (dl) is defined, and shown to be decidable. the logic allows propositional-level formulas involving probabilistic programs, and contains full real-number theory for dealing with probabilities. the decidability proof introduces model schemes, which seem to be the most basic structures relating programs and probabilities.
fault tolerance of minimal path routings in a network we prove the conjectured 2t-1 pound on the diameter of a surviving quote graph from which t edges are removed, under the assumption that a minimal path routing is used we also prove the related conjecture for node failure, and combine the results into a more general theorem.
a probabilistic dynamic logic a logic, pr(dl), is presented, which enables reasoning about probabilistic programs or, alternatively, reasoning probabilistically about conventional programs. the syntax of pr(dl) derives from pratt's first-order dynamic logic and the semantics extends kozen's semantics of probabilistic programs. an axiom system for pr(dl) is presented and shown to be complete relative to an extension of first-order analysis. for discrete probabilities it is shown that first-order analysis actually suffices. examples are presented, both of the expressive power of pr(dl), and of a proof in the axiom system.
optimal algorithms for byzantine agreement we exhibit randomized byzantine agreement (ba) algorithms achieving optimal running time and fault tolerance against all types of adversaries ever considered in the literature. our ba algorithms do not require trusted parties, preprocessing, or non-constructive arguments. given private communication lines, we show that n processors can reach ba in expected constant time in a syncronous network if any < n/3 faults occur in an asynchronous network if any < n/4 faults occur for both synchronous and asynchronous networks whose lines do not guarantee private communication, we may use cryptography to obtain algorithms optimal both in fault tolerance and running time against computationally bounded adversaries. (thus, in this setting, we tolerate up to n/3 faults even in an asynchronous network.)
optimal online scheduling of parallel jobs with dependencies. we study the following general online scheduling problem. parallel jobs arrive dynamically according to the dependencies between them. each job requests a certain number of processors with a specific communication configuration, but its running time is not known until it is completed. we present optimal online algorithms for prams, hypercubes and one-dimensional meshes, and obtain optimal tradeoffs between the competitive ratio and the largest number of processors requested by any job. our work shows that for efficient online scheduling it is necessary to use virtualization, i.e., to schedule parallel jobs on fewer processors than requested while preserving the work. assume that the largest number of processors requested by a job is lambda(n), where 0 > lambda > 1 and n is the number of processors of - a machine. with virtualization, our algorithm for prams has a competitive __________ ratio of 2 + /4lamba + 1 - 1 . our lower bound shows that this ratio _______________ 2lambda is optimal. as lambda goes from 0 to 1, the ratio changes from 2 to 2 + phi, where phi ~ 0.168 is the golden ratio. for hypercubes and ~ one-dimensional meshes we present theta (log n ) -competitive algorithms ______ (log log n) as well as matching lower bounds. without virtualization, no online scheduling algorithm can achieve a competitive ratio smaller than n for lambda = 1. for lambda > 1, the lower bound is 1 + 1 and our _____ 1 - y algorithm for prams achieves this competitive ratio. we prove that tree constraints are complete for the scheduling problem, i.e., any algorithm that solves the scheduling problem if the dependency graph is a tree can be converted to solve the general problem equally efficiently. this shows that the structure of a dependency graph is not as important for online scheduling as it is for offline scheduling, although even simple dependencies make the problem much harder than scheduling independent jobs.
clique-width minimization is np-hard. clique-width is a graph parameter that measures in a certain sense the complexity of a graph. hard graph problems (e.g., problems expressible in monadic second order logic with second-order quantification on vertex sets, that includes np-hard problems) can be solved efficiently for graphs of small clique-width. it is widely believed that determining the clique-width of a graph is np-hard; in spite of considerable efforts, no np-hardness proof has been found so far. we give the first hardness proof. we show that the clique-width of a given graph cannot be absolutely approximated in polynomial time unless p=np. we also show that, given a graph g and an integer k, deciding whether the clique-width of g is at most k is nphy complete. this solves a problem that has been open since the introduction of clique-width in the early 1990s.
maximum k-chains in planar point sets: combinatorial structure and algorithms. a chain of a set p of n points in the plane is a chain of the dominance order on p. a k-chain is a subset c of p that can be covered by k chains. a k-chain c is a maximum k-chain if no other k-chain contains more elements than c. this paper deals with the problem of finding a maximum k-chain of p in the cardinality and in the weighted case.using the skeleton s(p) of a point set p introduced by viennot we describe a fairly simple algorithm that computes maximum k-chains in time o(kn log n) and linear space. the basic idea is that the canonical chain partition of a maximum (k-1)-chain in the skeleton s(p) provides k regions in the plane such that a maximum k-chain for p can be obtained as the union of a maximal chain from each of these regions.by the symmetry between chains and antichains in the dominance order we may use the algorithm for maximum k-chains to compute maximum k-antichains for planar points in time o(kn log n). however, for large k one can do better. we describe an algorithm computing maximum k-antichains (and, by symmetry, k-chains) in time o((n2 k) log n) and linear space. consequently, a maximum k-chain can be computed in time o(n3/2 log n) for arbitrary k.the background for the algorithms is a geometric approach to the greene--kleitman theory for permutations. we include a skeleton-based exposition of this theory and give some hints on connections with the theory of young tableaux.the concept of the skeleton of a planar point set is extended to the case of a weighted point set. this extension allows to compute maximum weighted k-chains with an algorithm that is similar to the algorithm for the cardinality case. the time and space requirements of the algorithm for weighted k-chains are o(2kn log(2kn)) and o(2kn), respectively.
competitive generalized auctions. we describe mechanisms for auctions that are simultaneously truthful (alternately known as strategy-proof or incentive compatible) and guarantee high "net" profit. we make use of appropriate variants of competitive analysis of algorithms in designing and analyzing our mechanisms. thus, we do not require any probabilistic assumptions on bids.we present two new concepts regarding auctions, that of a cancellable auction and that of a generalized auction. we use cancellable auctions in the design of generalized auctions, but they are of independent interest as well. cancellable auctions have the property that if the revenue collected does not meet certain predetermined criteria, then the auction can be cancelled and the resulting auction is still truthful. the trivial approach (run a truthful auction and cancel if needed) yields an auction that is not necessarily truthfu.generalized auctions can be used to model many problems previously considered in the literature, as well as numerous new problems. in particular, we give the first truthful profit-maximizing auctions for problems such as conditional financing and multicast.
better algorithms for unfair metrical task systems and applications. unfair metrical task systems are a generalization of online metrical task systems. in this paper we introduce new techniques to combine algorithms for unfair metrical task systems and apply these techniques to obtain improved randomized online algorithms for metrical task systems on arbitrary metric spaces.
implicit o(1) probe search given a set of n elements from the domain 1, &hellip;, m, we investigate how to arrange them in a table of size n, so that searching for an element in the table can be done in constant time. yao has shown that this cannot be done when the domain is sufficiently large as a function of n ([yao]). [fnss] have shown that this can be done when the domain is linear in the number of elements. we give a constructive solution when the domain m is polynomial in the number of elements n, and give a nonconstructive proof for m no larger than exponential in poly(n). we improve upon [yao] and give better bounds on the maximum m for which implicit o(1) probe search can be done. we achieve our results by showing the tight relationship between hashing and certain encoding problems.
rigorous time/space tradeoffs for inverting functions we provide rigorous time-space tradeoffs for inverting any function. given a function f, we give a time space tradeoff of ts2 = n3q(f), where q(f) is the probability that two random elements are mapped to the same image under f. we also give a more general tradeoff, ts3 = n3, that can invert any function at any point.
lower bounds for the cycle detection problem given a function f over a domain and an element x in the domain, the cycle detection problem is to find a repetition in the sequence of values x, f(x), f(f(x)), f3(x),. . . , if one exists. this paper investigates lower bounds on the number of function evaluations needed when there is a bound on the amount of memory available. for certain restricted classes of algorithms which use two memory locations optimality is achieved. a summary of the major results appears in the final section.
new bounds for parallel prefix circuits in this paper, new upper and lower bounds are obtained for the number of gates in parallel prefix circuits with minimum depth when the number of inputs is a power of two. in addition, structural information concerning these circuits is described. parallel prefix circuits with bounds imposed on the fan-out of the gates are also considered. in both cases, the upper and lower bounds obtained differ by small constant factors.
the parallel complexity of exponentiating polynomials over finite fields modular integer exponentiation (given a, e, and m, compute ae mod m) is a fundamental problem in algebraic complexity for which no efficient parallel algorithm is known. two closely related problems are modular polynomial exponentiation (given a(x), e, and m(x), compute (a(x))e mod m(x)) and polynomial exponentiation (given a(x), e. and t, compute the coefficient of xt in (a(x))e). it is shown that these latter two problems are in nc2 when a(x) and m(x) are polynomials over a finite field whose characteristic is polynomial in the input size.
fast matrix multiplication this paper deals with three aspects of algebraic complexity. the first section is concerned with lower bounds on the number of operations required to compute several functions. several theorems are presented and their proofs sketched. the second section deals with relationships among the complexities of several sets of functions. in the third section, several matrices of general interest are examined and upper bounds on the number of operations required to multiply by them are constructively derived.
polynomial evaluation via the division algorithm: the fast fourier transform revisited a polynomial p(x) can be evaluated at several points x1,...,xm by first constructing a polynomial d(x) which has x1,...,xm as roots, then dividing p(x) by d(x), and finally evaluating the remainder r(x) at x1,...,xm. this method is useful if the coefficient sequence of d(x) can be chosen to be sparse, thus simplifying the construction of r(x). the case m&equil;1 and d(x) &equil; x&minus;x1 is horner's rule, while the case d(x) &equil; xm&minus;1 yields the fast fourier transform algorithm.
an efficient algorithm for determining whether a cubic graph is toroidal the algorithm of the title is presented. it runs in time bounded by a polynomial in the number of the edges of the graph.
sorting and searching in the presence of memory faults (without redundancy). we investigate the design of algorithms resilient to memory faults, i. e., algorithms that, despite the corruption of some memory values during their execution, are able to produce a correct output on the set of uncorrupted values. in this framework, we consider two fundamental problems: sorting and searching. in particular, we prove that any o(nlog n) comparison-based sorting algorithm can tolerate at most o((nlog n)1/2) memory faults. furthermore, we present one comparison-based sorting algorithm with optimal space and running time that is resilient to o((nlog n)1/3) faults. we also prove polylogarithmic lower and upper bounds on fault-tolerant searching.
the difficulty of testing for isomorphism against a graph that is given in advance. motivated by a question from [e. fischer, g. kindler, d. ron, s. safra, and a. samorodnitsky, j. comput. system sci., 68 (2004), pp. 753--787], we investigate the number of queries required for testing that an input graph g is isomorphic to a fixed graph h that is given in advance. we correlate this number with a measure of the "complexity" of h that we define here, by proving both an upper bound and a lower bound on the number of queries that depends on this new measure. as far as we know this is the first characterization of this type for graphs.
some properties of precedence languages the classes of languages definable by operator precedence grammars1 and by wirth-weber precedence grammars2 are studied. a grammar is backwards-deterministic3 if no two productions have the same right part. operator precedence grammars have no more generative power than backwards deterministic operator precedence grammars, but wirth-weber precedence grammars (i.e., grammars having unique wirth-weber precedence relations) are more powerful than backwards-deterministic wirth-weber precedence grammars; indeed they can generate any context-free language. an algorithm is developed for finding a wirth-weber precedence grammar equivalent to a given operator precedence grammar, a result of possible practical significance. the operator precedence languages are shown to be a proper subclass of the backwards-deterministic wirth-weber precedence languages which in turn are a proper subclass of the deterministic context-free languages.
monotonicity testing over general poset domains. the field of property testing studies algorithms that distinguish, using a small number of queries, between inputs which satisfy a given property, and those that are `far' from satisfying the property. testing properties that are defined in terms of monotonicity has been extensively investigated, primarily in the context of the monotonicity of a sequence of integers, or the monotonicity of a function over the n-dimensional hypercube {1,&ldots;,m}n. these works resulted in monotonicity testers whose query complexity is at most polylogarithmic in the size of the domain.we show that in its most general setting, testing that boolean functions are close to monotone is equivalent, with respect to the number of required queries, to several other testing problems in logic and graph theory. these problems include: testing that a boolean assignment of variables is close to an assignment that satisfies a specific 2-cnf formula, testing that a set of vertices is close to one that is a vertex cover of a specific graph, and testing that a set of vertices is close to a clique.we then investigate the query complexity of monotonicity testing of both boolean and integer functions over general partial orders. we give algorithms and lower bounds for the general problem, as well as for some interesting special cases. in proving a general lower bound, we construct graphs with combinatorial properties that may be of independent interest.
lower bounds on the size of boolean formulas: preliminary report let c(n)k be the boolean function of n variables that equals one iff the number of arguments equal to one is a multiple of k. it is shown that every boolean expression for c(n)k, allowing all of the 16 binary connectives, has size exceeding &egr;n log n/log log n, &egr;> 0. this result follows from a general criterion relating the minimum size expression for a boolean function to the kinds of subfunctions obtainable through restriction. lower bounds on formula size for several other functions are obtained. in some cases, the lower bounds are nearly achievable by known constructions.
testing of matrix properties. combinatorial property testing deals with the following relaxation of decision problems: given a fixed property p and an input f, distinguish between the case that f satisfies p, and the case that no input that differs from f in less than some fixed fraction of the places satisfies p. an (&egr;,q)-test for p is a randomized algorithm that queries at most q places of an input x and distinguishes with probability 2/3 between the case that f has the property and the case that at least an &egr;-fraction of the places of f need to be changed in order for it to have the property.here we concentrate on labeled, d-dimensional grids, where the grid is viewed as a partially ordered set (poset) in the standard way (i.e as a product order of total orders). the main result here is an (&egr,poly(1/&egr))-test for every property of 0/1 labeled, d-dimensional grids that is characterized by a finite collection of forbidden induced posets. such properties include the `monotonicity' property and many other properties. a (less efficient) test for such properties with larger fixed size alphabets is also presented. another result is a more efficient test than was previously known for a collection of bipartite graph properties.both collections above are variants of properties that are defined by certain first order formulae with no quantifier alternation over the syntax containing the grid order relations (and some additional relations for the bipartite graph properties). we also show that with one quantifier alternation, a certain property can be defined, for which no test with query complexity of o(n^{1/10}) exists. the above results identify new classes of efficiently
testing versus estimation of graph properties. tolerant testing is an emerging topic in the field of property testing, which was defined in [m. parnas, d. ron, and r. rubinfeld, j. comput. system sci., 72 (2006), pp. 1012-1042] and has recently become a very active topic of research. in the general setting, there exist properties that are testable but are not tolerantly testable [e. fischer and l. fortnow, proceedings of the $20$th ieee conference on computational complexity, 2005, pp. 135-140]. on the other hand, we show here that in the setting of the dense graph model, all testable properties are not only tolerantly testable (which was already implicitly proved in [n. alon, e. fischer, m. krivelevich, and m. szegedy, combinatorica, 20 (2000), pp. 451-476] and [o. goldreich and l. trevisan, random structures algorithms, 23 (2003), pp. 23-57]), but also admit a constant query size algorithm that estimates the distance from the property up to any fixed additive constant. in the course of the proof we develop a framework for extending szemer&eacute;di's regularity lemma, both as a prerequisite for formulating what kind of information about the input graph will provide us with the correct estimation, and as the means for efficiently gathering this information. in particular, we construct a probabilistic algorithm that finds the parameters of a regular partition of an input graph using a constant number of queries, and an algorithm to find a regular partition of a graph using a $\mathrm{tc}_0$ circuit. this, in some ways, strengthens the results of [n. alon, r. a. duke, h. lefmann, v. r&ouml;dl, and r. yuster, j. algorithms, 16 (1994), pp. 80-109].
optimal tree layout (preliminary version) we consider the problem of finding a minimal cost layout of a tree in euclidian d-space. a tree is an acyclic undirected edge-weighted graph, and a layout is an assignment of a point in d-dimensional euclidian space to each of the nodes of the tree. the &ldquo;length&rdquo; of an edge in the layout is the &ldquo;distance&rdquo; between its endpoints as measured by some norm. the cost of an edge is its length times its weight, and the cost of the whole layout is the sum of the costs of all the edges. we assume the positions of certain nodes are fixed in advance, and we wish to place the remaining nodes so as to minimize the cost of the layout.
fast convergence to wardrop equilibria by adaptive sampling methods. we study rerouting policies in a dynamic round-based variant of a well known game theoretic traffic model due to wardrop. previous analyses (mostly in the context of selfish routing) based on wardrop's model focus mostly on the static analysis of equilibria. in this paper, we ask the question whether the population of agents responsible for routing the traffic can jointly compute or better learn a wardrop equilibrium efficiently. the rerouting policies that we study are of the following kind. in each round, each agent samples an alternative routing path and compares the latency on this path with its current latency. if the agent observes that it can improve its latency then it switches with some probability depending on the possible improvement to the better path.we can show various positive results based on a rerouting policy using an adaptive sampling rule that implicitly amplifies paths that carry a large amount of traffic in the wardrop equilibrium. for general asymmetric games, we show that a simple replication protocol in which agents adopt strategies of more successful agents reaches a certain kind of bicriteria equilibrium within a time bound that is independent of the size and the structure of the network but only depends on a parameter of the latency functions, that we call the relative slope. for symmetric games, this result has an intuitive interpretation: replication approximately satisfies almost everyone very quickly.in order to achieve convergence to a wardrop equilibrium besides replication one also needs an exploration component discovering possibly unused strategies. we present a sampling based replication-exploration protocol and analyze its convergence time for symmetric games. for example, if the latency functions are defined by positive polynomials in coefficient representation, the convergence time is polynomial in the representation length of the latency functions. to the best of our knowledge, all previous results on the speed of convergence towards wardrop equilibria, even when restricted to linear latency functions, were pseudopolynomial.in addition to the upper bounds on the speed of convergence, we can also present a lower bound demonstrating the necessity of adaptive sampling by showing that static sampling methods result in a slowdown that is exponential in the size of the network. a further lower bound illustrates that the relative slope is, in fact, the relevant parameter that determines the speed of convergence.
fast on-line integer multiplication a turing machine multiplies on-line if it receives its inputs low order digits first and it produces the k-th output digit before reading in the (k+1)-st inputs. we present a general method for converting any off-line multiplication algorithm which forms the product of two n-bit binary numbers in time f(n) into an on-line method, and the new algorithm requires time only 0(f(n) log n). applying this technique to the fast multiplication algorithm of sch&ouml;nhage and strassen gives an upper bound of 0(n (log n)2 log log n) for on-line multiplication of integers. other applications are to the on-line problems of products of polynomials over a finite ring, recognition of palindromes, and multiplication by a constant.
computing integrated costs of sequences of operations with application to dictionaries we introduce a notion of integrated cost of a dictionary, as average cost of sequences of search, insert and delete operations. we express generating functions of these sequences in terms of continued fractions; from this we derive an explicit integral expression of integrated costs for three common representations of dictionaries.
on the average case performance of some greedy approximation algorithms for the uncapacitated facility location problem. in combinatorial optimization, a popular approach tonp-hard problems is the design of approximation algorithms. these algorithms typically run in polynomial time and are guaranteed to produce a solution which is within a known multiplicative factor of optimal. unfortunately, the known factor is often known to be large in pathological instances. conventional wisdom holds that, in practice, approximation algorithms will produce solutions closer to optimal than their proven guarantees. in this paper, we use the rigorous-analysis-of-heuristics framework to investigate this conventional wisdom.we analyze the performance of 3 related approximation algorithms for the uncapacitated facility location problem (from [jain, mahdian, markakis, saberi, vazirani, 2003] and [mahdian, ye, zhang, 2002]) when each is applied to an instances created by placing n points uniformly at random in the unit square. we find that, with high probability, these 3 algorithms do not find asymptotically optimal solutions, and, also with high probability, a simple plane partitioning heuristic does find an asymptotically optimal solution.
simple cost sharing schemes for multicommodity rent-or-buy and stochastic steiner tree. in the multi-commodity rent-or-buy network design problem (mrob) we are given a network together with a set of k terminal pairs r = (s_1, t_1), ..., (s_k, t_k). the goal is to install capacities on the edges of the network so that a prescribed amount of flow fi can be routed between all terminal pairs si and ti simultaneously. we can either rent capacity on an edge at some cost per unit flow or buy infinite capacity on an edge at some larger fixed cost. the overall objective is to install capacities at a minimum total cost.the version of the stochastic steiner tree problem (sst) considered here is the steiner tree problem in the model of two-stage stochastic optimization with recourse. in stage one, there is a known probability distribution on subsets of vertices and we can choose to buy a subset of edges at a given cost. in stage two, a subset of vertices t from the prior known distribution is realized, and additional edges can be bought at a possibly higher cost. the objective is to buy a set of edges in stages one and two so that all vertices in t are connected, and the expected cost is minimized.gupta et al. (focs '03) give a randomized scheme for the mrob problem that was both used subsequently to improve the approximation ratio for this problem, and extended to yield the best approximation algorithm for sst. one building block of this scheme is a good approximation algorithm for steiner forests.we present a surprisingly simple 5-approximation algorithm for mrob and 6-approximation for sst, improving on the best previous guarantees of 6.828 and 12.6, and show that no approximation ratio better than 4.67 can be achieved using the above mentioned randomized scheme in combination with the currently best known steiner forest approximation algorithms. a key component of our approach are cost shares that are 3-strict for the unmodified primal-dual steiner forest algorithm.
finding the depth of a flow graph the depth of a flow graph is the maximum number of back edges in a cycle free path, where a back edge is defined by some depth-first spanning tree for the flow graph. in the case of a reducible graph, the depth is independent of the dfst chosen. we show that the computation of the depth of a reducible flow graph may be done in polynomial time. our algorithm is 0(ne) on a flow graph of n nodes and e edges. since e&le;2n for normal flow graphs, our algorithm is really 0(n2). while even an 0(n2) algorithm is not likely to be acceptable, it is suggestive of the possibility of a more efficient algorithm. finally, we show that the general problem of computing the depth of an arbitrary flow graph with respect to an arbitrary dfst is np-complete.
beyond np: the work and legacy of larry stockmeyer. shortly after steve cook and richard karp showed the ex-istence of many natural np-complete languages, researchers started to realize the great importance of the p versus np problem and the difficulty of settling it. one graduate student at the massachusetts institute of technology started to look beyond np, asking what problems have a higher complexity and how do we classify them. larry stockmeyer discovered an amazing structure of complexity classes that continues to direct the research in complexity to this day. stockmeyer passed away on july 31, 2004 at the age of 55 and in this paper we review some of his research and the legacy he has left on the community.
probabilistic computation and linear time in this paper, we give an oracle under which bpp is equal to probabilistic linear time, an unusual collapse of a complexity time hierarchy. in addition, we also give oracles where &dgr;p2 is contained in probabilistic linear time and where bpp has linear sized circuits, as well as oracles for the negation of these questions. this indicates that these questions will not be solved by techniques that relativize. finally, we note that probabilistic linear time can not contain both np and bpp, implying that there are languages solvable by interactive proof systems that can not be solved in probabilistic linear time.
hierarchies for semantic classes. we show that for any constant a, zpp/b(n) strictly contains zptime(na)/b(n) for some b(n) = o(log n log log n). our techniques are very general and give the same hierarchy for all common semantic time classes including rtime, ntime ∩ contime, utime, matime, amtime and bqtime.we show a stronger hierarchy for rtime: for every constant c, rp/1 is not contained in rtime(nc)/(log n)1/2c. to prove this result we first prove a similar statement for np by building on zák's proof of the nondeterministic time hierarchy.
parallelism in random access machines a model of computation based on random access machines operating in parallel and sharing a common memory is presented. the computational power of this model is related to that of traditional models. in particular, deterministic parallel ram's can accept in polynomial time exactly the sets accepted by polynomial tape bounded turing machines; nondeterministic ram's can accept in polynomial time exactly the sets accepted by nondeterministic exponential time bounded turing machines. similar results hold for other classes. the effect of limiting the size of the common memory is also considered.
coresets in dynamic geometric data streams. a dynamic geometric data stream consists of a sequence of m insert/delete operations of points from the discrete space 1,…,δd [26]. we develop streaming (1 + ε)-approximation algorithms for k-median, k-means, maxcut, maximum weighted matching (maxwm), maximum travelling salesperson (maxtsp), maximum spanning tree (maxst), and average distance over dynamic geometric data streams. our algorithms maintain a small weighted set of points(a coreset) that approximates with probability 2/3 the current point set with respect to the considered problem during the m insert/delete operations of the data stream. they use poly (ε-1, log m, log δ) space and update time per insert/delete operation for constant k and dimension dhaving a coreset one only needs a fast approximation algorithm for the weighted problem to compute a solution quickly. in fact, even an exponential algorithm is sometimes feasible as its running time may still be polynomial in n. for example one can compute in poly(log n, exp(o((1+log (1⁄ε)⁄ε)d-1))) time a solution to k-median and k-means [21] where n is the size of the current point set and k and d are constants. finding an implicit solution to maxcut can be done in poly(log n, exp((1⁄ε)o(1))) time. for maxst and average distance we require poly(log n, ε-1) time and for maxwm we require o(n3) time to do this.
communication complexity of secure computation (extended abstract) a secret-ballot vote for a single proposition is an example of a secure distributed computation. the goal is for m participants to jointly compute the output of some n-ary function (in this case, the sum of the votes), while protecting their individual inputs against some form of misbehavior. in this paper, we initiate the investigation of the communication complexity of unconditionally secure multi-party computation, and its relation with various fault-tolerance models. we present upper and lower bounds on communication, as well as tradeoffs among resources. first, we consider the &ldquo;direct sum problem&rdquo; for communications complexity of perfectly secure protocols: can the communication complexity of securely computing a single function f : fn &rarr; f at k sets of inputs be smaller if all are computed simultaneously than if each is computed individually? we show that the answer depends on the failure model. a factor of o(n/log n) can be gained in the privacy model (where processors are curious but correct); specifically, when f is n-ary addition (mod 2), we show a lower bound of &ohgr;(n2 log n) for computing f o(n) times simultaneously. no gain is possible in a slightly stronger fault model (fail-stop mode); specifically, when f is n-ary addition over gf(q), we show an exact bound of &thgr;(kn2 log q) for computing f at k sets of inputs simultaneously (for any k &ge; 1). however, if one is willing to pay an additive cost in fault tolerance (from t to t-k+1), then a variety of known non-cryptographic protocols (including &ldquo;provably unparallelizable&rdquo; protocols from above!) can be systematically compiled to compute one function at k sets of inputs with no increase in communication complexity. our compilation technique is based on a new compression idea of polynomial-based multi-secret sharing. lastly, we show how to compile private protocols into error-detecting protocols at a big savings of a factor of o(n3) (up to a log factor) over the best known error-correcting protocols. this is a new notion of fault-tolerant protocols, and is especially useful when malicious behavior is infrequent, since error-detection implies error-correction in this case.
an algorithm for constructing regions with rectangles: independence and minimum generating sets for collections of intervals we provide an algorithm which solves the following problem: given a polygon with edges parallel to the x and y axes, which is convex in the y direction, find a minimum size collection of rectangles, which cover the polygon and are contained within it. the algorithm is quadratic in the number of vertices of the polygon. our method also yields a new proof of a recent duality theorem equating minimum size rectangle covers to maximum size sets of independent points in the polygon.
small sets supporting fáry embeddings of planar graphs answering a question of rosenstiehl and tarjan, we show that every plane graph with n vertices has a f&aacute;ry embedding (i.e., straight-line embedding) on the 2n - 4 by n - 2 grid and provide an &ogr;(n) space, &ogr;(n log n) time algorithm to effect this embedding. the grid size is asymptotically optimal and it had been previously unknown whether one can always find a polynomial sized grid to support such an embedding. on the other hand we show that any set f, which can support a f&aacute;ry embedding of every planar graph of size n, has cardinality at least n + (1 - &ogr;(1)) &radic;n which settles a problem of mohar.
generalized selection and ranking (preliminary version) selection in a set requires time linear in the size of the set when there are no a priori constraints on the total orders possible for the set. constraints often come for free, however, with sets which arise in applications. linear time selection [bl] can be suboptimal for such problems. we therefore generalize the well known selection problem to admit constraints on the input sets, with a view toward settling the complexity issues which arise. the generalization also applies to the other quantile problems of ranking a given element in the input set and verification of the claim that a given element has a specified rank.
the impact of synchronous communication on the problem of electing a leader in a ring we consider the problem of electing a leader in a synchronous ring of n processors. we obtain both positive and negative results. on the one hand, we show that if processor id's are chosen from some countable set, then there is an algorithm which uses only o(n) messages in the worst case. on the other hand, we obtain two lower bound results: if the algorithm is restricted to use only comparisons of id's, then we obtain an &ohgr;(n log n) lower bound for the number of messages required in the worst case. alternatively, there is a (very fast-growing) function f with the following property. if the number of rounds is required to be bounded by some t in the worst case, and id's are chosen from any set having at least f(n,t) elements, then any algorithm requires &ohgr; (n log n) messages in the worst case.
two applications of a probabilistic search technique: sorting x + y and building balanced search trees let x &equil; {x1,...,xn} and y &equil; {y1,...,yn} be sets of n real numbers. we denote by x + y the multiset {xi + yj; 1 &le; i, j &le; n} of size n2. berklekamp has posed the problem of sorting x + y. harper, payne, savage and strauss [1] show that n21og2n comparisons suffice to sort x + y, thereby saving a factor of 2 over sorting without exploiting the structure of x + y. (given u in x + y, we assume that we know the i,j indices such that u &equil; xi + yj.) furthermore, they show that this bound is tight for a restricted class of comparison algorithms. however, without their restriction the order of magnitude comparison complexity of this problem has remained an open question. in this paper we show that x + y can be sorted with o(n2) comparisons. our proof is unusual for this type of problem in that we do not explicitly exhibit an algorithm. instead, it is a particular application of a more general search technique whose behavior is easily related to information theoretic lower bounds. in the context of sorting, this search method translates into an insertion sort, where the insertions are not performed by means of the usual binary search, but rather as off-centered searches designed so that each comparison, roughly speaking, equally divides the space of remaining possibilities. we draw attention to this search technique because it might find application to other problems, and we illustrate this possibility with a second application. our second application concerns the construction of probabilistically balanced binary search trees.
a near optimal data structure for a type of range query problem let g denote the set of elements of a commutative group whose addition operations is denoted by +, let n be a positive integer, and let a(1) ,..., a(n) denote an array with values in g. we will be concerned with designing data structures for representing the array a, which facilitate efficient implementation of the following two on-line tasks: (1) update(j,x); replace a(j) by a(j) +x. (j and x are inputs, 1&le;j&le;n and x&egr;g) (2) retrieve(j); returns the value of a(1) +...+ a(j). (j is an input, 1&le;j&le;n) as a motivating example, let g be the group of integers with + denoting the usual addition operation. imagine a standardized examination given to large numbers of individuals over an indefinite period of time. assume that each examinee will attain an integer score in the interval [1,n]. if an individual gets j points, this fact is recorded by executing update(j,1). so that a(j) represents the number of individuals to date having scored j points. in order to compute the percentile currently associated with a particular score k, we need the cumulative sum provided by executing retrieve(k).
the cell probe complexity of dynamic data structures dynamic data structure problems involve the representation of data in memory in such a way as to permit certain types of modifications of the data (updates) and certain types of questions about the data (queries). this paradigm encompasses many fundamental problems in computer science. the purpose of this paper is to prove new lower and upper bounds on the time per operation to implement solutions to some familiar dynamic data structure problems including list representation, subset ranking, partial sums, and the set union problem. the main features of our lower bounds are: they hold in the cell probe model of computation (a. yao [18]) in which the time complexity of a sequential computation is defined to be the number of words of memory that are accessed. (the number of bits b in a single word of memory is a parameter of the model). all other computations are free. this model is at least as powerful as a random access machine and allows for unusual representation of data, indirect addressing etc. this contrasts with most previous lower bounds which are proved in models (e.g., algebraic, comparison, pointer manipulation) which require restrictions on the way data is represented and manipulated. the lower bound method presented here can be used to derive amortized complexities, worst case per operation complexities, and randomized complexities. the results occasionally provide (nearly tight) tradeoffs between the number r of words of memory that are read per operation, the number w of memory words rewritten per operation and the size b of each word. for the problems considered here there is a parameter n that represents the size of the data set being manipulated and for these problems b = logn is a natural register size to consider. by letting b vary, our results illustrate the effect of register size on time complexity. for instance, one consequence of the results is that for some of the problems considered here, increasing the register size from logn to polylog(n) only reduces the time complexity by a constant factor. on the other hand, decreasing the register size from logn to 1 increases time complexity by a logn factor for one of the problems we consider and only a loglogn factor for some other problems. the first two specific data structure problems for which we obtain bounds are: list representation. this problem concerns the representation of an ordered list of at most n (not necessarily distinct) elements from the universe u = {1, 2,&hellip;, n}. the operations to be supported are report(k), which returns the kth element of the list, insert(k, u) which inserts element u into the list between the elements in positions k - 1 and k, delete(k), which deletes the kth item. subset rank. this problem concerns the representation of a subset s of u = {1, 2,&hellip;, n}. the operations that must be supported are the updates &ldquo;insert item j into the set&rdquo; and &ldquo;delete item j from the set&rdquo; and the queries rank(j), which returns the number of elements in s that are less than or equal to j. the natural word size for these problems is b = logn, which allows an item of u or an index into the list to be stored in one register. one simple solution to the list representation problem is to maintain a vector v, whose kth entry contains the kth item of the list. the report operation can be done in constant time, but the insert and delete operations may take time linear in the length of the list. alternatively, one could store the items of the list with each element having a pointer to its predecessor and successor in the list. this allows for constant time updates (given a pointer to the appropriate location), but requires linear cost for queries. this problem can be solved must more efficiently by use of balanced trees (such as avl trees). when b = logn, the worst case cost per operation using avl trees is o(logn). if instead b = 1, so that each bit access costs 1, then the avl three solution requires o(log2n) per operation. it is not hard to find similar upper bounds for the subset rank problem (the algorithms for this problem are actually simpler than avl trees). the question is: are these upper bounds bet possible? our results show that the upper bounds for the case of logn bit registers are within a loglogn factor of optimal. on the other hand, somewhat surprisingly, for the case of single bit registers there are implementations for both of these problems that run in time significantly faster than o(log2n) per operation. let cprobe(b) denote the cell probe computational model with register size b. theorem 1. if b &le; (logn)t for some t, then any cprobe(b) implementation of either list representation or the subset rank requires &ohgr;(logn/loglogn) amortized time per operation. theorem 2. subset rank and list representation have cprobe(1) implementations with respective complexities o((logn)(loglogn)) and o((logn)(loglogn)2) per operation. paul dietz (personal communication) has found an implementation of list representation with logn bit registers that requires only o(logn/loglogn) time per operation, and thus the result of theorem 1 is best possible. the lower bounds of theorem 1 are derived from lower bounds for a third problem: partial sum mode k. an array a[1],&hellip;, a[n] of integers mod k is to be represented. updates are add(i, &dgr;) which implements a[i] &larr; a[i] + &dgr;; and queries are sum(j) which returns &sgr;i&le;ja[i] (mod k). this problem is demoted ps(n, k). our main lower bound theorems provide tradeoffs between the number of register rewrites and register reads as a function of n, k, and b. two corollaries of these results are: theorem 3. any cprobe(b) implementation of ps(n, 2) (partial sums mod 2) requires &ohgr;(logn/(loglogn + logb)) amortized time per operation, and for b &ge; logn, there is an implementation that achieves this. in particular, if b = &thgr;((logn)c) for some constant c, then the optimal time complexity of ps(n, 2) is &thgr;(logn/loglogn). theorem 4. any cprobe(1) implementation of ps(n, n) with single bit registers requires &ohgr;((logn/loglogn)2) amortized time per operation, and there is an implementation that achieves o(log2n) time per operation. it can be shown that a lower bound of ps(n, 2) is also a lower bound for both list representation and subset rank (the details, which are not difficult, are omitted from this report), and thus theorem 1 follows from theorem 3. the results of theorem 4 make an interesting contrast with those of theorem 2. for the three problems, list representation, subset rank and ps(n, k), there are standard algorithms that can be implemented on a cprobe(logn) that use time o(logn per operation, and their implementations on cprobe(1) require o(log2n) time. theorem 4 says that for the problem ps(n, n) this algorithm is essentially best possible, while theorem 2 says that for list representation and rank, the algorithm can be significantly improved. in fact, the rank problem an be viewed as a special case of ps(n, n) where the variables take on values on {0, 1}, and apparently this specialization is enough to reduce the complexity on a cprobe(1) by a factor of logn/loglogn, even though on a cprobe(logn) the complexities of the two problems differ by no more than a loglogn factor. the third problem we consider is the set union problem. this problem concerns the design of a data structure for the on-line manipulation of sets in the following setting. initially, there are n singleton sets {1}, {2},&hellip;, {n} with i chosen as the name of the set {i}. our data structure is required to implement two operations, find(j), and union(a, b, c). the operation find(j) returns the name of the set containing j. the operation union(a, b, c) combines the sets with names a and b. the names of the existing sets at any moment must be unique and chosen to be integers in the range from 1 to 2n. the sets existing at any time are disjoint and define a partition of the elements into equivalence classes. a well known data structure for the set union problem represents the sets as trees and stores the name of a set in the root of its corresponding tree. a union operation is performed by attaching the root of the smaller set as a child of the root of the larger set (weight rule). a find operation is implemented by following the path from the appropriate node to the root of the tree containing it, and then redirecting to the root the parent pointers of the nodes encountered along this path (path compression). from now on we consider sequences of union and find operations consisting of n-1 union operations and m find operations with m &ge; n. tarjan [14] demonstrated that the above algorithm requires time &thgr;(m&agr;(m, n)), where &agr;(m, n) is an inverse to ackermann's function, to execute n-1 union and m find operations. in particular, if m = &thgr;(n), then the running time is almost, but not quite, linear. tarjan conjectured [14] that no linear time algorithm exists for the set union problem, and provided significant evidence in favor of this conjecture (which we discuss in the following section). we affirm tarjan's conjecture in the cprobe(logn) model. theorem 5. any cprobe(logn) implementation of the set union problem requires &ohgr;(m&agr;(m, n)) time to execute m find's and n-1 union's, beginning with n singleton sets. n. blum [2] has given a logn/loglogn algorithm (worst case time per operation) for the set union problem. this algorithm is also optimal in the cprobe(polylogn) model. the following section provides further discussion of these results, section 3 outlines our lower bound method, and section 4 contains some proofs.
hidden translation and orbit coset in quantum computing. we give efficient quantum algorithms for the problems of hidden translation and hidden subgroup in a large class of non-abelian groups including solvable groups of constant exponent and of constant length derived series. our algorithms are recursive. for the base case, we solve efficiently hidden translation in z pn, whenever p is a fixed prime. for the induction step, we introduce the problem orbit coset generalizing both hidden translation and hidden subgroup, and prove a powerful self-reducibility result: orbit coset in a finite group g is reducible to orbit coset in g/n and subgroups of n, for any solvable normal subgroup n of g.
efficient testing of groups. we construct an efficient probabilistic algorithm that, given a finite set with a binary operation, tests if it is an abelian group. the distance used is an analogue of the edit distance for strings. the query complexity of the tester is polylogarithmic in the size of the set. previous testers used hamming type distances and had superlinear query complexity. a building block for our construction is a constant query complexity homomorphism tester for functions mapping an given finite group into an arbitrary set equipped with a binary operation.
a proof of alon's second eigenvalue conjecture. a d-regular graph has largest or first (adjacency matrix) eigenvalue λ1 = d. in this paper we show the following conjecture of alon. fix an integer d > 2 and a real ε > 0. then for sufficiently large n we have that "most" d-regular graphs on n vertices have all their eigenvalues except λ1 = d bounded above by 2√d-1 + ε. our methods, being trace methods, also bound those eigenvalues below by -2√d-1 - ε.
the tight deterministic time hierarchy let k be a constant -&-ge; 2, and let us consider only deterministic k-tape turing machines. we assume t2(n) -&-gt; n and t2 is computable in time t2. then there is a language which is accepted in time t2, but not accepted in any time t1 with t1(n) -&-equil; o(t2(n)). furthermore, we obtain a strong hierarchy (isomorphic to the rationals q) for languages accepted in fixed space and variable time.
normal forms for trivalent graphs and graphs of bounded valence a function f is defined, mapping graphs with n vertices onto graphs with vertex set {1,...,n} . f(x) is isomorphic to x and x is isomorphic to y iff f(x) &equil; f(y). for each d, the restriction of f to graphs of valence d is computable in time o(n&tgr;(d)) for a suitable integer &tgr;(d). for d > 3, the proof uses a recent result of l. babai, p.j. cameron and p.p. p&aacute;lfy on the order of primitive groups with bounded composition factors; for the trivalent case a more elementary proof is presented.
finding paths and cycles of superpolylogarithmic length. let $\ell$ be the number of edges in a longest cycle containing a given vertex $v$ in an undirected graph. we show how to find a cycle through $v$ of length $\exp(\omega(\sqrt {\log \ell/\log\log \ell}))$ in polynomial time. this implies the same bound for the longest cycle, longest $vw$-path, and longest path. the previous best bound for longest path is length $\omega( (\log \ell )^2/\, \log\log \ell)$ due to bjo&uml;rklund and husfeldt. our approach, which builds on bjo&uml;rklund and husfeldt&rsquo;s, uses cycles to enlarge cycles. this self-reducibility allows the approximation method to be iterated.
an efficient reduction technique for degree-constrained subgraph and bidirected network flow problems efficient algorithms are given for the bidirected network flow problem and the degree-constrained subgraph problem. four versions of each are solved, depending on whether edge capacities/multiplicities are one or arbitrary, and whether maximum value/maximum cardinality or minimum cost/maximum weight is the objective. a version of the shortest path problem is also efficiently solved. the algorithms use a reduction technique that solves one problem instance by reducing to a number of problems.
scaling and related techniques for geometry problems three techniques in computational geometry are explored: scaling solves a problem by viewing it at increasing levels of numerical precision; activation is a restricted type of update operation, useful in sweep algorithms; the cartesian tree is a data structure for problems involving maximums and minimums. these techniques solve the minimum spanning tree problem in rk1 and rk@@@@ in o(n(lg n)rlg lg n) time and o(n) space, where for rk@@@@ and k &ge; 3, r &equil; k&minus;2; for rk1, r &equil; 1, 2, 4 for k &equil; 3, 4, 5 and r &equil; k for k > 5. other problems solved include rk1and rk all nearest neighbors, post office and maximum spanning tree; rk maxima, rk rectangle searching problems, and zkp all nearest neighbors (1 &le; p &le; @@@@).
algorithms for edge coloring bipartite graphs a minimum edge coloring of a bipartite graph is a partition of the edges into &dgr; matchings, where &dgr; is the maximum degree in the graph. coloring algorithms are presented that use time o(min(&brvbar;e&brvbar; &dgr; log n, &brvbar;e&brvbar; @@@@n log n, n2log &dgr;)) and space o(n&dgr;). this compares favorably to the previous o(&brvbar;e&brvbar; [equation] log &dgr;) time bound. the coloring algorithms also find maximum matchings on regular (or semi-regular) bipartite graphs. the time bounds compare favorably to the o(&brvbar;e&brvbar @@@@n) matching algorithm, expect when [equation] &le; &dgr; &le; @@@@n log n.
a linear-time algorithm for a special case of disjoint set union this paper presents a linear-time algorithm for the special case of the disjoint set union problem in which the structure of the unions (defined by a &ldquo;union tree&rdquo;) is known in advance. the algorithm executes an intermixed sequence of m union and find operations on n elements in 0(m+n) time and 0(n) space. this is a slight but theoretically significant improvement over the fastest known algorithm for the general problem, which runs in 0(m&agr;(m+n, n)+n) time and 0(n) space, where &agr; is a functional inverse of ackermann's function. used as a subroutine, the algorithm gives similar improvements in the efficiency of algorithms for solving a number of other problems, including two-processor scheduling, the off-line min problem, matching on convex graphs, finding nearest common ancestors off-line, testing a flow graph for reducibility, and finding two disjoint directed spanning trees. the algorithm obtains its efficiency by combining a fast algorithm for the general problem with table look-up on small sets, and requires a random access machine for its implementation. the algorithm extends to the case in which single-node additions to the union tree are allowed. the extended algorithm is useful in finding maximum cardinality matchings on nonbipartite graphs.
almost-optimum speed-ups of algorithms for bipartite matching and related problems we present algorithms for matching and related problems that run on an erew pram with p processors. given is a bipartite graph g with n vertices, m edges, and integral edge costs at most n in magnitude. we give an algorithm for the assignment problem (minimum cost perfect bipartite matching) that runs in &ogr;(&radic;nm log (nn)(log(2p))/p) time and &ogr;(m) space, for p &le; m/(&radic;nlog2n). for p = 1 this improves the best known sequential algorithm, and is within a factor of log (nn) of the best known bound for the problem without costs (maximum cardinality matching). for p > 1 the time is within a factor of log p of optimum speed-up. extensions include an algorithm for maximum cardinality bipartite matching with slightly better processor bounds, and similar results for bipartite degree-constrained subgraph problems (with and without costs). our ideas also extend to general graph matching problems.
forests, frames and games: algorithms for matroid sums and applications this paper presents improved algorithms for matroid partitioning problems, such as finding a maximum cardinality set of edges of a graph that can be partitioned into k forests. the notion of a clamp in a matroid sum is introduced. efficient algorithms for problems involving clumps are presented. applications of these algorithms to problems arising in the study of structural rigidity of graphs, the shannon switching game and others are given.
compatible sequences and a slow winkler percolation. two infinite 0-1 sequences are called compatible when it is possible to cast out 0's from both in such a way that they become complementary to each other. answering a question of peter winkler, we show that if the two 0-1-sequences are random i.i.d. and independent from each other, with probability p of 1's, then if p is sufficiently small they are compatible with positive probability. the question is equivalent to a certain dependent percolation with a power-law behavior: the probability that the origin is blocked at distance n but not closer decreases only polynomially fast and not, as usual, exponentially.
clairvoyant scheduling of random walks. two infinite walks on the same finite graph are called compatible if it is possible to introduce delays into them in such a way that they never collide. about 10 years ago, peter winkler asked the question: for which graphs are two independent walks compatible with positive probability. up to now, no such graphs were found. we show in this paper that large complete graphs have this property. the question is equivalent to a certain dependent percolation with a power-law behavior: the probability that the origin is blocked at distance n but not closer decreases only polynomially fast and not, as usual, exponentially.
reliable computation with cellular automata we construct a one-dimensional array of cellular automata on which arbitrarily large computations can be implemented reliably, even though each automaton at each step makes an error with some constant probability. to compute reliably with unreliable components, von neumann proposed boolean circuits whose intricate interconnection pattern (arising from the error-correcting organization) he had to assume to be immune to errors. in a uniform cellular medium, the error-correcting organization exists only in &ldquo;software&rdquo;, therefore errors threaten to disable it. the real technical novelty of the paper is therefore the construction of a self-repairing organization.
from a static impossibility to an adaptive lower bound: the complexity of early deciding set agreement. set agreement, where processors decisions constitute a set of outputs, is notoriously harder to analyze than consensus where the decisions are restricted to a single output. this is because the topological questions that underly set agreement are not about simple connectivity as in consensus. analyzing set agreement inspired the discovery of the relation between topology and distributed algorithms, and consequently the impossibility of asynchronous set agreement.yet, the application of topological reasoning has been to the static case, that of asynchronous and synchronous tasks. it is not known yet for example, how to characterize starvation-free solvability of non-terminating tasks. non-terminating tasks are dynamic entities with no defined end. in a similar vain, early deciding synchronous set agreement, in which the number of rounds it takes a processor to decide adapts to the actual number of failures, falls in this category of dynamic entities.this paper develops a simulation technique that brings to bear topological results to deal with the dynamic situation that arises with early decisions. the novelty of the new simulation is the ability of simulators to look back at the transcript of past rounds of the simulation to influence their current behavior.using our new technique, we not only re-derive past results, but we propose and prove a lower bound to synchronous early stopping set agreement. we then provide an algorithm to match the lower bound. our technique uses the bg simulation, in the most creative way it was used to-date, to obtain a rather simple reduction from a static asynchronous impossibility. this reduction is a simple alternative to yet unknown topological argument, and in fact may suggest the way of finding such an argument.
computing nash equilibria for scheduling on restricted parallel links. we consider the problem of routing n users on m parallel links, under the restriction that each user may only be routed on a link from a certain set of allowed links for the user. thus, the problem is equivalent to the correspondingly restricted problem of assigning n jobs to m parallel machines. in a pure nash equilibrium, no user may improve its own individual cost (delay) by unilaterally switching to another link from its set of allowed links. as our main result, we introduce a polynomial time algorithm to compute from any given assignment a pure nash equilibrium with non-increased makespan. the algorithm gradually changes a given assignment by pushing unsplittable user traffics through a network that is defined by the users and the links. here, we use ideas from blocking flows. furthermore, we use similar techniques as in the generic preflow-push algorithm to approximate a schedule with minimum makespan, gaining an improved approximation factor of 2 - 1/w1 for identical links, where w1 is the largest user traffic. we extend this result to related links, gaining an approximation factor of 2. our approximation algorithms run in polynomial time. we close with tight upper bounds on the coordination ratio for pure nash equilibria.
lower bounds on the amount of randomness in private computation. we consider the amount of randomness necessary in information-theoretic private protocols. we prove that at least ω(log n) random bits are necessary for the t-private computation of the function xor by n players, for any t ≥ 2. in view of the upper bound of o(t2log(n/t))[19], this bound is tight, up to constant factors, for any fixed t. for a class of protocols obeying certain restrictions, we give stronger lower bounds of ω(t log (n/t)). we note that all known randomness efficient private protocols designed specifically for xor belong to this class. all our lower bounds hold for the "trusted dealer" model as well, and the ω(t log (n/t)) lower bound for restricted protocols is tight, up to constant factors, for any t ≥ 2 in this model.in comparison, the previous lower bounds on the amount of randomness required by t-private computation of explicit functions did not grow with n for constant values of t, and our results improve the previous lower bounds for xor for any 2 ≤ t = o(log n). our results also show that already for t = 2, ω(log n) random bits are necessary, while it is known that for the case of t = 1 a single random bit is sufficient for privately computing xor for any number of players.our proofs use novel techniques by which we extract random variables from a t-private protocol, and then use the t-privacy property of the protocol to prove properties of these random variables. these properties in turn imply that the number of random bits used by the players is large.
a theorem on sensitivity and applications in private computation. in this paper we prove a theorem that gives an (almost) tight upper bound on the sensitivity of a multiple-output boolean function in terms of the sensitivity of its coordinates and the size of the range of the function. we apply this theorem to get improved lower bounds on the time (number of rounds) to compute boolean functions by private protocols. these bounds are given in terms of the sensitivity of the function being computed and the amount of randomness used by the private protocol. these lower bounds are tight (up to constant factors) for the case of the xor function and together with the results in [e. kushilevitz and a. rosén, siam j. discrete math., 11 (1998), pp. 61--80.] establish a tight (up to constant factors) tradeoff between randomness and time in private computation.
on the validity and complexity of bounded resolution several procedures based on (not necessarily regular) resolution for checking whether a formula in cn3 is contradictory are considered. the procedures use various methods of bounding the size of the clauses which are generated. the following results are obtained: 1) all of the proposed procedures which are forced to run in polynomial time do not always work&mdash;i.e., they do not identify all contradictory formulas. 2) those which always work must run in exponential time. the exponential lower bounds for these procedures do not follow from tseitin's lower bound for regular resolution since these procedures also allow nonregular resolution trees.
real-time algorithms for string-matching and palindrome recognition we give a sufficient condition when an on-line algorithm can be transformed into a real-time algorithm. we use this condition to construct real-time algorithms for string-matching and palindrome recognition problems by random access machines and by turing machines.
optimal parallel algorithms for string matching let wram [pram] be a parallel computer with p processors (ram's) which share a common memory and are allowed simultaneous reads and writes [only simultaneous reads]. the only type of simultaneous writes allowed is a simultaneous and: several processors may write o simultaneously into the same memory cell. let t be the time bound of the computer. we design below families of parallel algorithms that solve the string matching problem with inputs of size n (n is the sum of lengths of the pattern and the text) and have the following performance in terms of p, t and n: 1. for wram: pt &equil; o(n) for for p &le; n/log n. 2. for pram: pt &equil; o(n) for p &le; n/log2n. 3. for wram: t &equil; constant for p &equil; nl+&egr; and any &egr; > o. 4. for wram: t &equil; o(log n/log log n) for p &equil; n. similar families are also obtained for the problem of finding all initial palindromes of a given string.
a constant-time optimal parallel string-matching algorithm given a pattern string, we describe a way to preprocess it. we design a constant-time optimal parallel algorithm for finding all occurences of the (preprocessed) pattern in any given text.
network flow and generalized path compression an o(evlog2v) algorithm for finding the maximal flow in networks is described. it is asymptotically better than the other known algorithms if e &equil; o(v2&minus;&egr;) for some &egr;>0. the analysis of the running time exploits the discovery of a phenomenon similar to (but more general than) path compression, although the union find algorithm is not used. the time bound is shown to be tight in terms of v and e by exhibiting a family of networks that require &ohgr;(evlog2v) time.++
an efficient general purpose parallel computer in this paper we investigate the question of what is a good way to interconnect a large number of processors. our main result is the construction of a universal parallel machine that can simulate every reasonable parallel machine with only a small loss of time and with essentially the same number of processors.
well-separated pair decomposition for the unit-disk graph metric and its applications. we extend the classic notion of well-separated pair decomposition [p. b. callahan and s. r. kosaraju, j. acm, 42 (1975), pp. 67--90] to the unit-disk graph metric: the shortest path distance metric induced by the intersection graph of unit disks. we show that for the unit-disk graph metric of n points in the plane and for any constant $c\geq 1$, there exists a c-well-separated pair decomposition with o(n log n) pairs, and the decomposition can be computed in o(n log n) time. we also show that for the unit-ball graph metric in k dimensions where $k\geq 3$, there exists a c-well-separated pair decomposition with o(n2-2/k) pairs, and the bound is tight in the worst case. we present the application of the well-separated pair decomposition in obtaining efficient algorithms for approximating the diameter, closest pair, nearest neighbor, center, median, and stretch factor, all under the unit-disk graph metric.
some np-complete geometric problems we show that the steiner tree problem and traveling salesman problem for points in the plane are np-complete when distances are measured either by the rectilinear (manhattan) metric or by a natural discretized version of the euclidean metric. our proofs also indicate that the problems are np-hard if the distance measure is the (unmodified) euclidean metric. however, for reasons we discuss, there is some question as to whether these problems, or even the well-solved minimum spanning tree problem, are in np when the distance measure is the euclidean metric.
worst-case analysis of memory allocation algorithms various memory allocation problems can be modeled by the following abstract problem. given a list a &equil; (&agr;1,&agr;2,...&agr;n,) of real numbers in the range (0, 1], place these in a minimum number of &ldquo;bins&rdquo; so that no bin holds numbers summing to more than 1. we let a* be the smallest number of bins into which the numbers of list a may be placed. since a general placement algorithm for attaining a* appears to be impractical, it is important to determine good heuristic methods for assigning numbers of bins. we consider four such simple methods and analyze the worst-case performance of each, closely bounding the maximum of the ratio of the number of bins used by each method applied to list a to the optimal quantity a*.
some simplified np-complete problems it is widely believed that showing a problem to be np-complete is tantamount to proving its computational intractability. in this paper we show that a number of np-complete problems remain np-complete even when their domains are substantially restricted. first we show the completeness of simple max cut (max cut with edge weights restricted to value 1), and, as a corollary, the completeness of the optimal linear arrangement problem. we then show that even if the domains of the node cover and directed hamiltonian path problems are restricted to planar graphs, the two problems remain np-complete, and that these and other graph problems remain np-complete even when their domains are restricted to graphs with low node degrees. for graph 3-colorability, node cover, and undirected hamiltonian circuit, we determine essentially the lowest possible upper bounds on node degree for which the problems remain np-complete.
saving an epsilon: a 2-approximation for the k-mst problem in graphs. we present a polynomial time 2-approximation algorithm for the problem of finding the minimum tree that spans at least k vertices. our result also leads to a 2-approximation algorithm for finding the minimum tour that visits k vertices and to a 3-approximation algorithm for the problem of finding the maximum number of vertices that can be spanned by a tree of length at most a given bound.
auction algorithms for market equilibrium. in this paper we study algorithms for computing market equilibrium in markets with linear utility functions. the buyers in the market have an initial endowment given by a portfolio of goods. the market equilibrium problem is to compute a price vector that ensures market clearing, i.e., the demand of a positively priced good equals its supply, and given the prices, each buyer maximizes its utility. the problem is of considerable interest in economics. this paper presents a formulation of the market equilibrium problem as a parameterized linear program. we construct a family of duals corrresponding to these parameterized linear programs and show that finding the market equilibrium is the same as finding a linear program from this family of linear programs. the market-clearing conditions arise naturally from complementary slackness conditions. we then define an auction mechanism that computes prices such that approximate market clearing is achieved. the algorithm we obtain outperforms previously known methods.
minimizing average flow time on related machines. we give the first on-line poly-logarithmic competitve algorithm for minimizing average flow time with preemption on related machines, i.e., when machines can have different speeds. this also yields the first poly-logarithmic polynomial time approximation algorithm for this problem.more specifically, we give an o(log2 p • log s)-competitive algorithm, where p is the ratio of the biggest and the smallest processing time of a job, and s is the ratio of the highest and the smallest speed of a machine. our algorithm also has the nice property that it is non-migratory. the scheduling algorithm is based on the concept of making jobs wait for a long enough time before scheduling them on slow machines.
approximate max-flow min-(multi)cut theorems and their applications. consider the multicommodity flow problem in which the object is to maximize the sum of commodities routed. we prove the following approximate max-flow min-multicut theorem: $$ \dst \frac{\mbox{\rm min multicut}}{o(\log k)} \leq \mbox{ \rm max flow } \leq \mbox{ \rm min multicut}, $$ \noindent where $k$ is the number of commodities. our proof is constructive; it enables us to find a multicut within $o(\log k)$ of the max flow (and hence also the optimal multicut). in addition, the proof technique provides a unified framework in which one can also analyse the case of flows with specified demands of leighton and rao and klein et al. and thereby obtain an improved bound for the latter problem.
on the equivalence of schemes one objective of the study of schemes for computation is that of finding general methods for checking or verifying a given program against its specifications. if one views the program and its specification as presenting two supposedly equivalent schemes for a computation, then the objective reduces to one of finding general methods for determining whether, in fact, the two schemes are equivalent. unfortunately, for many classes of schemes which are sufficiently powerful, this &ldquo;equivalence problem&rdquo; is not decidable, i.e. there are no general methods capable of determining, in all cases, whether two schemes in the class are equivalent. in this report we investigate the question of which classes of schemes have decidable equivalence problems, or, in otherwords the question of for which classes of schemes there exist general methods capable of determining equivalence.
parallel algorithms for algebraic problems in borodin-von zur gathen-hopcroft[82] the following program is laid out: obtain a &ldquo;theory package for parallel algebraic computations&rdquo;, i.e. fast parallel computations for the widely used problems of symbolic manipulation in an algebraic context. in that paper, two basic problems were considered: solving systems of linear equations and computing the gcd of two polynomials, both over arbitrary ground fields. the present paper continues this program, and fast parallel solutions to the following algebraic problems are given: computing all entries of the extended euclidean scheme of two polynomials over an arbitrary field, gcd and lcm of many polynomials, factoring polynomials over finite fields, and the squarefree decomposition of polynomials over fields of characteristic zero and over finite fields.
bounded-error quantum state identification and exponential separations in communication complexity. we consider the following problem of bounded-error quantum state identification: given either state $\alpha_0$ or state $\alpha_1$, we are required to output &ldquo;0&rdquo;, &ldquo;1&rdquo;, or &ldquo;?&rdquo; (&ldquo;don't know"), such that conditioned on outputting &ldquo;0&rdquo; or &ldquo;1&rdquo;, our guess is correct with high probability. the goal is to maximize the probability of not outputting &ldquo;?&rdquo;. we prove the following direct product theorem: if we are given two such problems, with optimal probabilities $a$ and $b$, respectively, and the states in the first problem are pure, then the optimal probability for the joint bounded-error state identification problem is $o(ab)$. our proof is based on semidefinite programming duality. using this result, we present two exponential separations in the simultaneous message passing model of communication complexity. first, we describe a relation that can be computed with $o(\log n)$ classical bits of communication in the presence of shared randomness, but needs $\omega(n^{1/3})$ communication if the parties don't share randomness, even if communication is quantum. this shows the optimality of yao's recent exponential simulation of shared-randomness protocols by quantum protocols without shared randomness. combined with an earlier separation in the other direction due to bar-yossef, jayram, and kerenidis, this shows that the quantum simultaneous message passing (smp) model is incomparable with the classical shared-randomness smp model. second, we describe a relation that can be computed with $o(\log n)$ classical bits of communication in the presence of shared entanglement, but needs $\omega((n/\log n)^{1/3})$ communication if the parties share randomness but no entanglement, even if communication is quantum. this is the first example in communication complexity of a situation where entanglement buys much more than quantum communication.
lower bounds on the efficiency of encryption and digital signature schemes. a central focus of modern cryptography is to investigate the weakest possible assumptions under which various cryptographic algorithms exist. typically, a proof that a "weak" primitive (e.g., a one-way function) implies the existence of a "strong" algorithm (e.g., a private-key encryption scheme) proceeds by giving an explicit construction of the latter from the former. in addition to showing the existence of such a construction, an equally important research direction is to explore the efficiency of such constructions.among the most fundamental cryptographic algorithms are digital signature schemes and schemes for public- or private-key encryption. here, we show the first lower bounds on the efficiency of any encryption or signature construction based on black-box access to one-way or trapdoor one-way permutations. if s is the assumed security of the permutation π (i.e., no adversary of size s can invert π on a fraction larger than 1/s of its inputs), our results show that:any public-key encryption scheme for m-bit messages must query π at least ω(m log s) times.any private-key encryption scheme for m-bit messages (with k-bit keys) must query π at least ω(m-k/log s) times.any signature verification algorithm for m-bit messages must query π at least ω(m log s) times.our bounds match known upper bounds for the case of encryption.we prove our results in an extension of the impagliazzo-rudich model. that is, we show that any black-box construction beating our lower bounds would imply the unconditional existence of a one-way function.
the round complexity of verifiable secret sharing and secure multicast. the round complexity of interactive protocols is one of their most important complexity measures. in this work we study the exact round complexity of two basic secure computation tasks: verifiable secret sharing (vss) and secure multicast.vss allows a dealer to share a secret among several players in a way that would later allow a unique reconstruction of the secret. it is a well-studied primitive, which is used as a building block in virtually every general protocol for secure multi-party computation. secure multicast is perhaps the simplest non-trivial instance of a secure computation. it allows a dealer to securely distribute an identical message to all players in a prescribed subset m. both types of protocols are parameterized by the number of players, n, and a security threshold, t, which bounds the total number of malicious players (possibly including the dealer).we focus on a standard setting of perfect information-theoretic security, where all players have access to secure point-to-point channels and a common broadcast medium. for both types of primitives we prove, using related techniques, tight tradeoffs between the round complexity and the achievable security threshold. specifically, for the vss problem we show:2-round vss is possible iff n>4t, where the ``if'' direction is realized by an efficient protocol.3-round vss is possible iff n>3t, where the ``if'' direction is realized by an inefficient protocol.4-round efficient vss is possible if n>3t.for the secure multicast problem we show:2-round secure multicast is (efficiently) possible iff
analysis of algorithms, a case study: determinants of polynomials we consider the problem of computing the determinant of a matrix of polynomials; we compare two algorithms (expansion by minors and gaussian elimination), examining each under two models for polynomial computation (dense univariate and totally sparse). the results, while interesting in themselves, also serve to display two points: 1. asymptotic results are sometimes misleading for noninfinite (e.g., practical) problems. 2. models of computation are by definition simplifications of reality: algorithmic analysis should be carried out under several distinct computational models, and should be supported by empirical data.
work-competitive scheduling for cooperative computing with dynamic groups. the problem of cooperatively performing a set of t tasks in a decentralized computing environment subject to failures is one of the fundamental problems in distributed computing. the setting with partitionable networks is especially challenging, as algorithmic solutions must accommodate the possibility that groups of processors become disconnected (and, perhaps, reconnected) during the computation. the efficiency of task-performing algorithms is often assessed in terms of work: the total number of tasks, counting multiplicities, performed by all of the processors during the computation. in general, the scenario where the processors are partitioned into g disconnected components causes any task-performing algorithm to have work $\omega(t\cdot g)$ even if each group of processors performs no more than the optimal number of $\theta(t)$ tasks. given that such pessimistic lower bounds apply to any scheduling algorithm, we pursue a competitive analysis. specifically, this paper studies a simple randomized scheduling algorithm for p asynchronous processors, connected by a dynamically changing communication medium, to complete t known tasks. the performance of this algorithm is compared against that of an omniscient off-line algorithm with full knowledge of the future changes in the communication medium. the paper describes a notion of computation width, which associates a natural number with a history of changes in the communication medium, and shows both upper and lower bounds on work-competitiveness in terms of this quantity. specifically, it is shown that the simple randomized algorithm obtains the competitive ratio $(1+\mathbf{cw}/e)$, where $\mathbf{cw}$ is the computation width and $e$ is the base of the natural logarithm ($e=2.7182\ldots$); this competitive ratio is then shown to be tight.
transition logic: how to reason about temporal properties in a compositional way this paper addresses the problem of obtaining formal proof systems that support reasoning about temporal properties of parallel programs in a way that is compositional or 'syntax directed' - the distinctive feature of e.g. hoare style proof systems. now, temporal properties of programs express properties about execution traces of these programs. in the presence of concurrency, compositionality is obtained by concentrating exclusively on the execution traces associated with the atomic actions of programs - the so-called transitions of those programs. to reason about such transitions in a compositional way, 'transition logic' is proposed, expressing properties of the form &ldquo;every transition of a program, say &agr;, that starts in a state satisfying assertion p, must end in a state validating &rdquo;: [p]&agr;[q]. essential is that these assertions can express properties of control locations of programs, too. for this logic, a compositional proof system is obtained which is proved to be sound and relatively complete. an interesting feature of the proof system is the axiomatization of the flow-of-control of programs. the relevance of this logic is supported by the fact that the temporal behaviour of a program is ultimately provable in terms of properties of its transitions, as shown by the work of z. manna and a. pnueli [16].
tight analyses of two local load balancing algorithms. this paper presents an analysis of the following load balancing algorithm. at each step, each node in a network examines the number of tokens at each of its neighbors and sends a token to each neighbor with at least 2d+1 fewer tokens, where d is the maximum degree of any node in the network. we show that within $o(\delta / \alpha)$ steps, the algorithm reduces the maximum difference in tokens between any two nodes to at most $o((d^2 \log n)/\alpha)$, where $\delta$ is the global imbalance in tokens (i.e., the maximum difference between the number of tokens at any node initially and the average number of tokens), n is the number of nodes in the network, and $\alpha$ is the edge expansion of the network. the time bound is tight in the sense that for any graph with edge expansion $\alpha$, and for any value $\delta$, there exists an initial distribution of tokens with imbalance $\delta$ for which the time to reduce the imbalance to even $\delta/2$ is at least $\omega(\delta/\alpha)$. the bound on the final imbalance is tight in the sense that there exists a class of networks that can be locally balanced everywhere (i.e., the maximum difference in tokens between any two neighbors is at most 2d), while the global imbalance remains $\omega((d^2 \log n) / \alpha)$. furthermore, we show that upon reaching a state with a global imbalance of $o((d^2 \log n)/\alpha)$, the time for this algorithm to locally balance the network can be as large as $\omega(n^{1/2})$. we extend our analysis to a variant of this algorithm for dynamic and asynchronous networks. we also present tight bounds for a randomized algorithm in which each node sends at most one token in each step.
fast, small-space algorithms for approximate histogram maintenance. (math) a vector a of length n is defined implicitly, via a stream of updates of the form "add 5 to a3." we give a sketching algorithm, that constructs a small sketch from the stream of updates, and a reconstruction algorithm, that produces a b-bucket piecewise-constant representation (histogram) h for a from the sketch, such that ||a&mdash;h||&xie;(1+&egr;)||a&mdash;hopt|&#124, where the error ||a&mdash;h|| is either $\ell_1$ (absolute) or $\ell_2$ (root-mean-square) error. the time to process a single update, time to reconstruct the histogram, and size of the sketch are each bounded by poly(b,log(n),log||a,1/&egr;. our result is obtained in two steps. first we obtain what we call a robust histogram approximation for a, a histogram such that adding a small number of buckets does not help improve the representation quality significantly. from the robust histogram, we cull a histogram of desired accruacy and b buckets in the second step. this technique also provides similar results for haar wavelet representations, under $\ell_2$ error. our results have applications in summarizing data distributions fast and succinctly even in distributed settings.
near-optimal sparse fourier representations via sampling. (math) we give an algorithm for finding a fourier representation r of b terms for a given discrete signal signal a of length n, such that $\|\signal-\repn\|_2^2$ is within the factor (1 +&egr;) of best possible $\|\signal-\repn_\opt\|_2^2$. our algorithm can access a by reading its values on a sample set t &sube;[0,n), chosen randomly from a (non-product) distribution of our choice, independent of a. that is, we sample non-adaptively. the total time cost of the algorithm is polynomial in b log(n)log(m)&egr; (where m is the ratio of largest to smallest numerical quantity encountered), which implies a similar bound for the number of samples.
on the fractal behavior of tcp. we propose a natural, mathematically tractable model of tcp which captures both its additive-increase, multiplicative-decrease behavior and its feedback mechanism. neither a fluid nor a mean-field model, our model does not explicitly model the loss process; the losses are entirely determined by the rates of the sources at the time of buffer overflow. the system involves two sources competing to send packets into one recipient buffer of size b, from which bytes are drained at the rate of d per step. we prove that for many choices of the pairs (b,d), the long term behavior of the system is fractal. we conjecture that this fact continues to hold for all b > d and d > 2.
the pebbling problem is complete in polynomial space we examine a pebbling problem which has been used to study the storage requirements of various models of computation. sethi has shown this problem to be np-hard and lingas has shown a generalization to be p-space complete. we prove the original problem p-space complete by employing a modification of lingas's proof. the pebbling problem is one of the few examples of a p-space complete problem not exhibiting any obvious quantifier alternation.
computational complexity of probabilistic turing machines probabilistic turing machines are turing machines with the ability to flip coins in order to make random decisions. we allow probabilistic turing machines small but nonzero error probability in computing number-theoretic functions. an example is given of a function computable more quickly by probabilistic turing machines than by deterministic turing machines. it is shown how probabilistic linear-bounded automata can simulate nondeterministic linear-bounded automata.
intersection-closed full afl and the recursively enumerable languages a study is made of conditions on a language l which ensure that the smallest intersection-closed full afl containing l (written @@@@ @@@@(l)) does or does not contain all recursively enumerable languages. for example, it is shown that if l &euil; {ani/i @@@@ 0}and [equation]inf ni+1/ni>1, then [equation](l) contains all recursively enumerable languages. on the other hand, it is shown that if l @@@@ a* and the ratio of the number of words in l of length less than n to n goes to 1 as [equation], then [equation] does not contain all recursively enumerable languages.
comparative complexity of grammar forms the definition of &ldquo;grammar form&rdquo; introduced in [cg] makes it possible to state and prove results about various types of grammars in a uniform way. among questions naturally formalizable in this framework are many about the complexity or efficiency of grammars of different kinds. grammar forms provide a reasonable way of considering the totality of other forms we might use, and so answering the question with both upper and lower bound results. the general question considered in this paper is the following: which grammar forms are more efficient than other grammar forms for the expression of classes of languages, and how much gain in efficiency is possible? our results deal solely with context-free grammars, and use both derivation complexity and size of grammars as complexity measures.
scheduling data transfers in a network and the set scheduling problem. in this paper we consider the online ftp problem. the goal is to service a sequence of file transfer requests given bandwidth constraints of the underlying communication network. the main result of the paper is a technique that leads to algorithms that optimize several natural metrics, such as max-stretch, total flow time, max flow time, and total completion time. in particular, we show how to achieve optimum total flow time and optimum max-stretch if we increase the capacity of the underlying network by a logarithmic factor. we show that the resource augmentation is necessary by proving polynomial lower bounds on the max-stretch and total flow time for the case where online and offline algorithms are using same-capacity edges. moreover, we also give polylogarithmic lower bounds on the resource augmentation factor necessary in order to keep the total flow time and max-stretch within a constant factor of optimum.
sharp thresholds for monotone properties in random geometric graphs. random geometric graphs result from taking n uniformly distributed points in the unit cube, [0,1]d, and connecting two points if their euclidean distance is at most r, for some prescribed r. we show that monotone properties for this class of graphs have sharp thresholds by reducing the problem to bounding the bottleneck matching on two sets of $n$ points distributed uniformly in [0,1]d. we present upper bounds on the threshold width, and show that our bound is sharp for d = 1 and at most a sublogarithmic factor away for d ≥ 2. interestingly, the threshold width is much sharper for random geometric graphs than for bernoulli random graphs. further, a random geometric graph is shown to be a subgraph, with high probability, of another independently drawn random geometric graph with a slightly larger radius; this property is shown to have no analogue for bernoulli random graphs.
approximation algorithms for max-3-cut and other problems via complex semidefinite programming. a number of recent papers on approximation algorithms have used the square roots of unity, - 1 and 1, to represent binary decision variables for problems in combinatorial optimization, and have relaxed these to unit vectors in real space using semidefinite programming in order to obtain near optimum solutions to these problems. in this paper, we consider using the cube roots of unity, 1, ei2π/3, and ei4π/3, to represent ternary decision variables for problems in combinatorial optimization. here the natural relaxation is that of unit vectors in complex space. we use an extension of semidefinite programming to complex space to solve the natural relaxation, and use a natural extension of the random hyperplane technique introduced by the authors in goemans and williamson (j. acm 42 (1995) 1115-1145) to obtain near-optimum solutions to the problems. in particular, we consider the problem of maximizing the total weight of satisfied equations xu - xv ≡ c (mod 3) and inequations xu - xv ≢ c (mod 3), where xu ∈ {0, 1, 2} for all u. this problem can be used to model the max-3-cut problem and a directed variant we call max-3-dicut. for the general problem, we obtain a 0.793733-approximation algorithm. if the instance contains only inequations (as it does for max-3-cut), we obtain a performance guarantee of 7/12 + 3/4π2 arccos2(-1/4) - ε > 0.836008. this compares with proven performance guarantees of 0.800217 for max-3-cut (by frieze and jerrum (algorithmica 18 (1997) 67-81) and 1/3 + 10-8 for the general problem (by andersson et al. (j. algorithms 39 (2001) 162-204)). it matches the guarantee of 0.836008 for max-3-cut found independently by de klerk et al. (on approximate graph colouring and max-k-cut algorithms based on the ℓ-function, manuscript, october 2000). we show that all these algorithms are in fact equivalent in the case of max-3- cut, and that our algorithm is the same as that of anderson et al. in the general case.
the complexity of choosing an h-colouring (nearly) uniformly at random. cooper, dyer, and frieze [j. algorithms, 39 (2001), pp. 117--134] studied the problem of sampling h-colorings (nearly) uniformly at random. special cases of this problem include sampling colorings and independent sets and sampling from statistical physics models such as the widom--rowlinson model, the beach model, the potts model and the hard-core lattice gas model. cooper et al. considered the family of "cautious" ergodic markov chains with uniform stationary distribution and showed that, for every fixed connected "nontrivial " graph h, every such chain mixes slowly. in this paper, we give a complexity result for the problem. namely, we show that for any fixed graph h with no trivial components, there is unlikely to be any polynomial almost uniform sampler (paus) for h-colorings. we show that if there were a paus for the h-coloring problem, there would also be a paus for sampling independent sets in bipartite graphs, and, by the self-reducibility of the latter problem, there would be a fully polynomial randomized approximation scheme (fpras) for #bis---the problem of counting independent sets in bipartite graphs. dyer, goldberg, greenhill, and jerrum have shown that #bis is complete in a certain logically defined complexity class. thus, a paus for sampling h-colorings would give an fpras for the entire complexity class. in order to achieve our result we introduce the new notion of sampling-preserving reduction which seems to be more useful in certain settings than approximation-preserving reduction.
on finding the exact solution of a zero-one knapsack problem given a 0-1 knapsack problem with input drawn from a certain probability distribution, we show that for every &egr; > 0, there is a self-checking polynomial-time algorithm that finds an optimal solution with probability at least 1 -&egr;. we also prove some upper and lower bounds on random variables related to the problem.
reducibility among equilibrium problems. we address the fundamental question of whether the nash equilibria of a game can be computed in polynomial time. we describe certain efficient reductions between this problem for normal form games with a fixed number of players and graphical games with fixed degree. our main result is that the problem of solving a game for any constant number of players, is reducible to solving a 4-player game.
parallel symmetry-breaking in sparse graphs we describe efficient deterministic techniques for breaking symmetry in parallel. the techniques work well on rooted trees and graphs of constant degree or genus. our primary technique allows us to 3-color a rooted tree in &ogr;(lg*n) time on an erew pram using a linear number of processors. we apply these techniques to construct fast linear processor algorithms for several problems, including (&dgr; + 1)-coloring constant-degree graphs, 5-coloring planar graphs, and finding depth-first-search trees in planar graphs. we also prove lower bounds for 2-coloring directed lists and for finding maximal independent sets in arbitrary graphs.
compression and ranking a complexity-theoretic approach to the classical data compression problem is to define a notion of language compression by a machine in a certain complexity class, and to study language classes compressible under the above definition. languages that can be compressed efficiently (e.g. by a probabilistic polynomial time machine) are of special interest. we define the notion of language compressibility, and show that sufficiently sparse &ldquo;easy&rdquo; languages (e.g. polynomial time) can be compressed efficiently. we also define a notion of ranking (which is an optimal compression) and show that some &ldquo;very easy&rdquo; languages (e.g. unambiguous context-free languages) can be ranked efficiently. we exhibit languages which cannot be compressed or ranked efficiently. the notion of compressibility is closely related to kolmogorov complexity and randomness. we discuss this relationship and the complexity-theoretic implications of our results.
a new approach to the maximum flow problem all previously known efficient maximum-flow algorithms work by finding augmenting paths, either one path at a time (as in the original ford and fulkerson algorithm) or all shortest-length augmenting paths at once (using the layered network approach of dinic). an alternative method based on the preflow concept of karzanov is introduced. a preflow is like a flow, except that the total amount flowing into a vertex is allowed to exceed the total amount flowing out. the method maintains a preflow in the original network and pushes local flow excess toward the sink along what are estimated to be shortest paths. the algorithm and its analysis are simple and intuitive, yet the algorithm runs as fast as any other known method on dense graphs, achieving an o(n3) time bound on an n-vertex graph. by incorporating the dynamic tree data structure of sleator and tarjan, we obtain a version of the algorithm running in o(nm log(n2/m)) time on an n-vertex, m-edge graph. this is as fast as any known method for any graph density and faster on graphs of moderate density. the algorithm also admits efficient distributed and parallel implementations. a parallel implementation running in o(n2log n) time using n processors and o(m) space is obtained. this time bound matches that of the shiloach-vishkin algorithm, which also uses n processors but requires o(n2) space.
solving minimum-cost flow problems by successive approximation we introduce a framework for solving minimum-cost flow problems. our approach measures the quality of a solution by the amount that the complementary slackness conditions are violated. we show how to extend techniques developed for the maximum flow problem to improve the quality of a solution. this framework allows us to achieve &ogr;(min(n3, n5/3 m2/3, nm log n) log (nc)) running time.
finding minimum-cost circulations by canceling negative cycles a classical algorithm for finding a minimum-cost circulation consists of repeatedly finding a residual cycle of negative cost and canceling it by pushing enough flow around the cycle to saturate an arc. we show that a judicious choice of cycles for canceling leads to a polynomial bound on the number of iterations in this algorithm. this gives a very simple strongly polynomial algorithm that uses no scaling. a variant of the algorithm that uses dynamic trees runs in o(nm(log n) min{log(nc), mlog n}) time on a network of n vertices, m arcs, and arc costs of maximum absolute value c. this bound is comparable to those of the fastest previously known algorithms.
simulating threshold circuits by majority circuits. we prove that a single threshold gate with arbitrary weights can be simulated by an explicit polynomial-size, depth-2 majority circuit. in general we show that a polynomial-size, depth-d threshold circuit can be simulated uniformly by a polynomial-size majority circuit of depth d + 1. goldmann, håstad, and razborov showed in [comput. complexity, 2 (1992), pp. 277--300] that a nonuniform simulation exists. our construction answers two open questions posed by them: we give an explicit construction, whereas they use a randomized existence argument, and we show that such a simulation is possible even if the depth d grows with the number of variables n (their simulation gives polynomial-size circuits only when d is constant).
concurrent zero-knowledge with timing, revisited. following dwork, naor, and sahai (30th stoc, 1998), we consider concurrent execution of protocols in a semi-synchronized network. specifically, we assume that each party holds a local clock such that a constant bound on the relative rates of these clocks is a-priori known, and consider protocols that employ time-driven operations (i.e., time-out in-coming messages and delay out-going messages).we show that the constant-round zero-knowledge proof for np of goldreich and kahan (jour. of crypto., 1996) preserves its security when polynomially-many independent copies are executed concurrently under the above timing model.we stress that our main result establishes zero-knowledge of interactive proofs, whereas the results of dwork et al are either for zero-knowledge arguments or for a weak notion of zero-knowledge (called &egr;-knowledge) proofs.our analysis identifies two extreme schedulings of concurrent executions under the above timing model: the first is the case of parallel execution of polynomially-many copies, and the second is of concurrent execution of polynomially-many copies such the number of copies that are simultaneously active at any time is bounded by a constant (i.e., bounded simultaneity). dealing with each of these extreme cases is of independent interest, and the general result (regarding concurrent executions under the timing model) is obtained by combining the two treatments.
towards a theory of software protection and simulation by oblivious rams software protection is one of the most important issues concerning computer practice. there exist many heuristics and ad-hoc methods for protection, but the problem as a whole has not received the theoretical treatment it deserves. in this paper, we make the first steps towards a theoretic treatment of software protection: first, we distill and formulate the key problem of learning about a program from its execution. second, assuming the existence of one-way permutations, we present an efficient way of executing programs such that it is infeasible to learn anything about the program by monitoring its executions. how can one efficiently execute programs without allowing an adversary, monitoring the execution, to learn anything about the program? traditional cryptographic techniques can be applied to keep the contents of the memory unknown throughout the execution, but are not applicable to the problem of hiding the access pattern. the problem of hiding the access pattern efficiently corresponds to efficient simulation of random access machines (ram) on an oblivious ram. we define an oblivious ram to be a (probabilistic) ram for which (the distribution of) the memory access pattern is independent of the input. we present an (on-line) simulation of t steps of an arbitrary ram with m memory cells, by less than t&middot;m&egr; steps of an oblivious ram with 2m memory cells, where &egr;>0 is an arbitrary constant.
a hard-core predicate for all one-way functions a central tool in constructing pseudorandom generators, secure encryption functions, and in other areas are &ldquo;hard-core&rdquo; predicates b of functions (permutations) &fnof;, discovered in [blum micali 82]. such b(x) cannot be efficiently guessed (substantially better than 50-50) given only &fnof;(x). both b, &fnof; are computable in polynomial time. [yao 82] transforms any one-way function &fnof; into a more complicated one, &fnof;*, which has a hard-core predicate. the construction applies the original &fnof; to many small pieces of the input to &fnof;* just to get one &ldquo;hard-core&rdquo; bit. the security of this bit may be smaller than any constant positive power of the security of &fnof;. in fact, for inputs (to &fnof;*) of practical size, the pieces effected by &fnof; are so small that &fnof; can be inverted (and the &ldquo;hard-core&rdquo; bit computed) by exhaustive search. in this paper we show that every one-way function, padded to the form &fnof;(p, x) = (p, g(x)), &verbar;&verbar;p&verbar;&verbar; = &verbar;x&verbar;, has by itself a hard-core predicate of the same (within a polynomial) security. namely, we prove a conjecture of [levin 87, sec. 5.6.2] that the scalar product of boolean vectors p, x is a hard-core of every one-way function &fnof;(p, x) = (p, g(x)). the result extends to multiple (up to the logarithm of security) such bits and to any distribution on the x's for which &fnof; is hard to invert.
a unified approach to models of synchronous parallel machines a number of different models of synchronous, unbounded parallel computers have appeared in recent literature. without exception, running time on these models has been shown to be polynomially related to the classical space complexity measure. the general applicability of this relationship is called &ldquo;the parallel computation thesis&rdquo; and strong evidence of its truth is given in this paper by introducing the notion of &ldquo;conglomerates&rdquo; - a very large class of parallel machines, including all those which could feasibly be built. basic parallel machine models are also investigated, in an attempt to pin down the notion of parallel time to within a constant factor. to this end, a universal conglomerate structure is developed with can simulate any other basic model within linear time. this approach also leads to fair estimates of instruction execution times for various parallel models.
strong signature schemes the notion of digital signature based on trapdoor functions has been introduced by diffie and hellman[3]. rivest, shamir and adleman[8] gave the first number theoretic implementation of a signature scheme based on a trapdoor function. if f is a trapdoor function and m a message, f&minus;1(m) is the signature of m. the signature can be verified by computing f(f&minus;1(m)) &equil; m. this approach presents the following problems even when f is hard to invert: 1) there may be special message spaces (or subsets of them) that are easy to sign without knowing the trapdoor information 2) it is possible to forge the signature of random numbers; this violates the requirements of many protocols 3) given a polynomial number of signed messages, it may be possible to sign a new one without knowing the trapdoor information. we solve the above problems by exhibiting two signature schemes for which any strategy of an adversary, who has seen all previously signed messages, that has a moderate success in forging even a single additional signature, is transformable to a fast algorithm for factoring or inverting the rsa function. this provably holds for all message spaces with all possible probability distributions. thus, in particular, given the signature of m, forging the signature of m+1 or 2m or 2sm is as hard as factoring. the two signature schemes
huffman coding with unequal letter costs. (math) in the standard huffman coding problem, one is given a set of words and for each word a positive frequency. the goal is to encode each word w as a codeword c(w) over a given alphabet. the encoding must be prefix free (no codeword is a prefix of any other) and should minimize the weighted average codeword size &sgr;w freq w, &124;c(w)&124;. the problem has a well-known polynomial-time algorithm due to huffman [15].here we consider the generalization in which the letters of the encoding alphabet may have non-uniform lengths. the goal is to minimize the weighted average codeword length &sgr;w freq (w) cost(c(w)), where cost s is the sum of the (possibly non-uniform) lengths of the letters in s. despite much previous work, the problem is not known to be np-hard, nor was it previously known to have a polynomial-time approximation algorithm. here we describe a polynomial-time approximation scheme (ptas) for the problem.
edge partition of planar sraphs into two outerplanar graphs. an outerplanar graph is a planar graph that can be embedded in the plane without crossing edges, in such a way that all the vertices are on the outer boundary. in this paper, we prove a conjecture of chartrand, geller, and hedetniemi that any planar graph g=(v,e) has a bipartition of its edge set e = a ∪ b such that the graphs induced by these subsets, g[a] and g[b], are outerplanar.
a linear probing sort and its analysis (preliminary draft) we present a variant of the distribution sort approach which makes use of extra storage to sort a list of n elements in an average of about (2+@@@@2)n &equil; 3.412...n probes into a table. an accurate analysis of this technique is made by introducing a transform from a poisson approximation to the exact (finite) distribution. this analysis also leads to the solution of an interesting parking problem.
on the stability of the ethernet we consider the stochastic behavior of binary exponential backoff, a probabilistic algorithm for regulating transmissions on a multiple access channel. ethernet, a local area network, is built upon this algorithm. the fundamental theoretical issue is stability: does the backlog of packets awaiting transmission remain bounded in time, provided the rates of new packet arrivals are small enough? we present a realistic model of n &ge; 2 stations communicating over the channel. our main result is to establish that the algorithm is stable if the sum of the arrival rates is sufficiently small. we report detailed results on which rates lead to stability when n = 2 stations share the channel. in passing we derive several other results bearing on the efficiency of the conflict resolution process. lastly, we report results from a simulation study, which, in particular, indicate alternative retransmission strategies can significantly improve performance.
coordinate representation of order types requires exponential storage we give doubly exponential upper and lower bounds on the size of the smallest grid on which we can embed every planar configuration of n points in general position up to order type. the lower bound is achieved by the construction of a widely dispersed &ldquo;rigid&rdquo; configuration which is then modified to one in general position by recent techniques of sturmfels and white, while the upper bound uses recent results of grigor'ev and vorobjou on the solution of simultaneous inequalities. this provides a sharp answer to a question first posed by chazelle.
on line context free language recognition in less than cubic time (extended abstract) a new on-line context free language recognition algorithm is presented which is derived from earley's algorithm and has several advantages over the original. first, the new algorithm not only is conceptually simpler than earley's, but also allows significant speed improvements. second, our algorithm serves to explain the connections between earley's algorithm and the cocke-kasami-younger algorithm. third, our algorithm allows an implementation which uses only 0(n2/log n) operations on bit vectors of length n, or 0(n3/log n) operations on a ram. this makes it the fastest known on-line context free language recognition algorithm.
on the time complexity of broadcast communication schemes (preliminary version) in this paper, we investigate the power of such broadcast in solving a paradigmatic problem in distributed computing. imagine a network in which each node machine ni (1-&-le;i-&-le;n) keeps a boolean value vi in local memory. the vi 's determine a set s-&-equil;{i: vi-&-equil;1}. the non-emptiness problem on n nodes is to find some i in s, or else find that s is empty. in practice, a problem of this type arises in two ways: 1. consensus testing: has any node voted -&-ldquo;no-&-rdquo;, where vi-&-equil;1 means node i votes -&-ldquo;no-&-rdquo;, and vi-&-equil;o means node i votes -&-ldquo;yes-&-rdquo;? 2. establishing a distinguished node: s specifies a set of candidates, and solving non-emptiness selects one. for example, the nodes may be bidding for a job or a resource. in section 2, we introduce an idealistic broadcast communication scheme which abstracts certain features of the csma technology.
some restrictions on w-grammars the effect of some restrictions on w-grammars (the formalization of the syntax of algol 68) are explored. two incomparable families examined at length are wrb (languages generated by normal regular-based w-grammars) and ws (languages generated by simple w-grammars). both properly contain the context-free languages and are properly contained in the family of quasirealtime languages. in addition, wrb is closed under nested iterated substitution (but is not an afl) and is properly contained in the family of indexed languages.
quantum mechanical algorithms for the nonabelian hidden subgroup problem. we provide positive and negative results concerning the &ldquo;standard method&rdquo; of identifying a hidden subgroup of a nonabelian group using a quantum computer.
a lower bound for randomized algebraic decision trees. we extend the lower bounds on the depth of algebraic decision trees to the case of randomized algebraic decision trees (with two-sided error) for languages being finite unions of hyperplanes and the intersections of halfspaces. as an application, among other things, we derive, for the first time, $\omega(n^2)$ randomized lower bound for the {\em knapsack problem} (which was previously only known for deterministic algebraic decision trees).
computing crossing numbers in quadratic time. we show that for every fixed k ≥ 0 there is a quadratic time algorithm that decides whether a given graph has crossing number at most k and, if this is the case, computes a drawing of the graph into the plane with at most k crossings.
when is the evaluation of conjunctive queries tractable? the evaluation of conjunctive queries is hard both with respect to its combined complexity (np-complete) and its parameterized complexity (w[1]-complete). it becomes tractable (ptime for combined complexity, fpt for parameterized complexity), when the underlying graphs of the conjunctive queries have bounded tree-width [2]. we show that, in some sense, this is optimal both with respect to combined and parameterized complexity: for every class c of graphs, the evaluation of all conjunctive queries whose underlying graph is in c is tractable if, and only if, c has bounded tree-width.a technical result of independent interest is that the colored grid homomorphism problem is np-complete and, if parameterized by the grid size, w[1]-complete.
asymptotic conditional probabilities for first-order logic motivated by problems that arise in computing degrees of belief, we consider the problem of computing asymptotic conditional probabilities for first-order formulas. that is, given first-order formulas &fgr; and &thgr;, we consider the number of structures with domain {1,&hellip;,n} that satisfy &thgr;, and compute the fraction of them in which &fgr; is true. we then consider what happens to this probability of first-order formulas, except that now we are considering asymptotic conditional probabilities. although work has been done on special cases of asymptotic conditional probabilities, no general theory has been developed. this is probably due in part to the fact that it has been known that, if there is a binary predicate symbol in the vocabulary, asymptotic conditional probabilities do not always exist. we show that in this general case, almost all the questions one might want to ask (such as deciding whether the asymptotic probability exists) are highly undecidable. on the other hand, we show that the situation with unary predicates only is much better. if the vocabulary consists only of unary predicate and constant symbols, it is decidable whether the limit exists, and if it does, there is an effective algorithm for computing it. the complexity depends on two parameters: whether there is a fixed finite vocabulary or an infinite one, and whether there is a bound on the depth of quantifier nesting.
data-streams and histograms. histograms have been used widely to capture data distribution, to represent the data by a small number of step functions. dynamic programming algorithms which provide optimal construction of these histograms exist, albeit running in quadratic time and linear space. in this paper we provide linear time construction of 1 + &egr; approximation of optimal histograms, running in polylogarithmic space.our results extend to the context of data-streams, and in fact generalize to give 1 + &egr; approximation of several problems in data-streams which require partitioning the index set into intervals. the only assumptions required are that the cost of an interval is monotonic under inclusion (larger interval has larger cost) and that the cost can be computed or approximated in small space. this exhibits a nice class of problems for which we can have near optimal data-stream algorithms.
a constant factor approximation for the single sink edge installation problems. we present the first constant approximation to the single sink buy-at-bulk network design problem, where we have to design a network by buying pipes of different costs and capacities per unit length to route demands at a set of sources to a single sink. the distances in the underlying network form a metric. this result improves the previous bound of $o(\log|r|)$, where $r$ is the set of sources. we also present a better constant approximation to the related access network design problem. our algorithms are randomized and combinatorial. as a subroutine in our algorithm, we use an interesting variant of facility location with lower bounds on the amount of demand an open facility needs to serve. we call this variant load balanced facility location and present a constant factor approximation for it, while relaxing the lower bounds by a constant factor.
a new representation for linear lists we present a new data structure for maintaining a set of records in a linear list according to their key values. this data structure has the property that we can keep a number of fingers at points of interest in the key space (e.g., the beginning or the end of the list), so that access and modification in the neighborhood of a finger is very efficient. in the section 2 we discuss the general structure of our b-tree. since we propose to search the tree from a leaf upwards, additional links need to be introduced. in section 3 we show how to obtain our result for the case of one finger. a key idea is the construction of a number representation behaving as described above, which we can use to model the propagation of modifications in the b-tree along the finger path. in section 4 we generalize the structure so that several fingers in the key space can be maintained, with the advantage that access is cheap in the neighborhood of each finger. finally in section 5 we present some implementation notes and applications, mostly to sorting.
the analysis of double hashing (extended abstract) in this paper we analyze the performance of a well known algorithm known as double hashing [knuth]. in this method we probe the hash table along arithmetic progressions, where both the initial element and the increment of the progression are chosen randomly and independently depending only on the key k of the search. we prove that double hashing is asymptotically equivalent to uniform probing, an idealized hashing technique that exhibits no clustering and is known to be optimal in a certain sense. between steps of the extension process we can show that the effect of clustering is negligible, and that we therefore never depart too far from the truly random situation.
primitives for the manipulation of general subdivisions and the computation of voronoi diagrams we discuss the following problem: given n points in the plane (the &ldquo;sites&rdquo;), and an arbitrary query point q, find the site that is closest to q. this problem can be solved by constructing the voronoi diagram of the given sites, and then locating the query point in one of its regions. we give two algorithms, one that constructs the voronoi diagram in o(n lg n) time, and another that inserts a new site in o(n) time. both are based on the use of the voronoi dual, the delaunay triangulation, and are simple enough to be of practical value. the simplicity of both algorithms can be attributed to the separation of the geometrical and topological aspects of the problem, and to the use of two simple but powerful primitives, a geometric predicate and an operator for manipulating the topology of the diagram. the topology is represented by a new data structure for generalized diagrams, that is embeddings of graphs in two-dimensional manifolds. this structure represents simultaneously an embedding, its dual, and its mirror-image. furthermore, just two operators are sufficient for building and modifying arbitrary diagrams.
on translating a set of rectangles given a collection of disjoint objects in the plane, we are interested in translating them by a common vector. if we have a primitive for translating one object at a time, then the order in which the objects can individually be translated is often geometrically constrained. in this paper we study the nature of these constraints and exhibit optimal algorithms for finding valid motion ordering for several different classes of objects. these algorithms find use in computer display applications.
provisioning a virtual private network: a network design problem for multicommodity flow. consider a setting in which a group of nodes, situated in a large underlying network, wishes to reserve bandwidth on which to support communication. virtual private networks (vpns) are services that support such a construct; rather than building a new physical network on the group of nodes that must be connected, bandwidth in the underlying network is reserved for communication within the group, forming a virtual &ldquo;sub-network.&rdquo;provisioning a virtual private network over a set off terminals gives rise to the following general network design problem. we have bounds on the cumulative amount of traffic each terminal can send and receive; we must choose a path for each pair of terminals, and a bandwidth allocation for each edge of the network, so that any traffic matrix consistent with the given upper bounds can be feasibly routed. thus, we are seeking to design a network that can support a continuum of possible traffic scenarios.we provide optimal and approximate algorithms for several variants of this problem, depending on whether the traffic matrix is required to be symmetric, and on whether the designed network is required to be a tree (a natural constraint in a number of basic applications). we also establish a relation between this collection of network design problems and a variant of the facility location problem introduced by karger and minkoff; we extend their results by providing a stronger approximation algorithm for this latter problem.
simpler and better approximation algorithms for network design. we give simple and easy-to-analyze randomized approximation algorithms for several well-studied np-hard network design problems. our algorithms improve over the previously best known approximation ratios. our main results are the following.we give a randomized 3.55-approximation algorithm for the connected facility location problem. the algorithm requires three lines to state, one page to analyze, and improves the best-known performance guarantee for the problem.we give a 5.55-approximation algorithm for virtual private network design. previously, constant-factor approximation algorithms were known only for special cases of this problem.we give a simple constant-factor approximation algorithm for the single-sink buy-at-bulk network design problem. our performance guarantee improves over what was previously known, and is an order of magnitude improvement over previous combinatorial approximation algorithms for the problem.
boosted sampling: approximation algorithms for stochastic optimization. several combinatorial optimization problems choose elements to minimize the total cost of constructing a feasible solution that satisfies requirements of clients. in the steiner tree problem, for example, edges must be chosen to connect terminals (clients); in vertex cover, vertices must be chosen to cover edges (clients); in facility location, facilities must be chosen and demand vertices (clients) connected to these chosen facilities. we consider a stochastic version of such a problem where the solution is constructed in two stages: before the actual requirements materialize, we can choose elements in a first stage. the actual requirements are then revealed, drawn from a pre-specified probability distribution π thereupon, some more elements may be chosen to obtain a feasible solution for the actual requirements. however, in this second (recourse) stage, choosing an element is costlier by a factor of σ> 1. the goal is to minimize the first stage cost plus the expected second stage cost.we give a general yet simple technique to adapt approximation algorithms for several deterministic problems to their stochastic versions via the following method. first stage: draw σ independent sets of clients from the distribution π and apply the approximation algorithm to construct a feasible solution for the union of these sets. second stage: since the actual requirements have now been revealed, augment the first-stage solution to be feasible for these requirements. we use this framework to derive constant factor approximations for stochastic versions of vertex cover, steiner tree and uncapacitated facility location for arbitrary distributions π in one fell swoop. for special (product) distributions, we obtain additional and improved results. our techniques adapt and use the notion of strict cost-shares introduced in [5].
an np-complete number-theoretic problem systems of nonlinear equations of the form d: a&ymarc; &equil; &sgr;marc;.(x), where a is an m&times;n matrix of rational constants and &ymarc; &equil; (y1,...,yn), &sgr;(x) &equil; (&sgr;1(x),..., &sgr;m (x)) are column vectors are considered. each &sgr;i(x) is of the form ri(x) or @@@@ri(x)@@@@, where ri(x) is a rational function of x with rational coefficients. it is shown that the problem of determining for a given system d whether there exists a nonnegative integral solution (y1,...,yn,x) satisfying d is decidable. in fact, the problem is np-complete when restricted to systems d in which the maximum degree of the polynomials defining the &sgr;i(x)'s is bounded by some fixed polynomial in the length of the representation of d. some recent results connecting diophantine equations and counter machines are briefly mentioned.
the complexity of the equivalence problem for counter machines, semilinear sets, and simple programs it is shown that the class of relations (functions) definable by presburger formulas is exactly the class of relations (functions) computable by finite-reversal multicounter machines. an upper bound of 2c(n/logn)4 on the deterministic time complexity of the equivalence problem for such machines is established. in fact, it is proved that the inequivalence problem is np-complete. these results are used to derive some upper bounds on the complexity of the equivalence problem for semilinear sets and simple programs. for example, it is shown that the equivalence problem for semilinear sets (these sets are exactly the presburger relations) is decidable in deterministic time 22cn2. a class of programs which realize exactly the relations (functions) definable by presburger formulas is shown to have an np-complete inequivalence problem. hence, its equivalence problem is decidable in deterministic time 2p(n). this bound is a four-level exponential improvement over a previously known result.
trees, automata, and games in 1969 rabin introduced tree automata and proved one of the deepest decidability results. if you worked on decision problems you did most probably use rabin's result. but did you make your way through rabin's cumbersome proof with its induction on countable ordinals? building on ideas of our predecessors-&-mdash;and especially those of b-&-uuml;chi-&-mdash;we give here an alternative and transparent proof of rabin's result. generalizations and further results will be published elsewhere.
limits to list decodability of linear codes. we consider the problem of the best possible relation between the list decodability of a binary linear code and its minimum distance. we prove, under a widely-believed number-theoretic conjecture, that the classical "johnson bound" gives, in general, the best possible relation between the list decoding radius of a code and its minimum distance. the analogous result is known to hold by a folklore random coding argument for the case of non-linear codes, but the linear case is more subtle and has remained open.we prove our result by exhibiting an infinite family of binary linear codes of "large" minimum distance with a super-polynomial number (in blocklength) of codewords all within a hamming ball of radius close to the johnson bound. even the existence of codes with a super-polynomial number of codewords in a ball of radius bounded away from the minimum distance (let alone radius close to the johnson bound) was open prior to our work. we also unconditionally prove the "tightness" of the johnson bound for decoding with list size that is an arbitrarily large constant.
better extractors for better codes? we present an explicit construction of codes that can be list decoded from a fraction (1-ε) of errors in sub-exponential time and which have rate ε/logo(1)(1/ε). this comes close to the optimal rate of ω(ε), and is the first sub-exponential complexity construction to beat the rate of ε2 achieved by reed-solomon or algebraic-geometric codes. our construction is based on recent extractor constructions with very good seed length [17]. while the "standard" way of viewing extractors as codes (as in [16]) cannot beat the o(ε2) rate barrier due to the 2 log (1/ε) lower bound on seed length for extractors, we use such extractor codes as a component in a well-known expander-based construction scheme to get our result. the o(ε2) rate barrier also arises if one argues about list decoding using the minimum distance (via the so-called johnson bound) --- so this also gives the first explicit construction that "beats the johnson bound" for list decoding from errors.the main message from our work is perhaps conceptual, namely that good strong extractors for low min-entropies will yield near-optimal list decodable codes. given all the progress that has been made on extractors, we view this as an optimistic avenue to look for better list decodable codes, both by looking for better explicit extractor constructions, as well as by importing non-trivial techniques from the extractor world in reasoning about and constructing codes.
near-optimal linear-time codes for unique decoding and new list-decodable codes over smaller alphabets. we present an explicit construction of linear-time encodable and decodable codes of rate r which can correct a fraction (1&mdash:r&egr;)/2 of errors over an alphabet of constant size depending only on &egr;, for every 0 < r < 1 and arbitrarily small &egr;> 0. the error-correction performance of these codes is optimal as seen by the singleton bound (these are "near-mds" codes). such near-mds linear-time codes were known for the decoding from erasures [2]; our construction generalizes this to handle errors as well. concatenating these codes with good, constant-sized binary codes gives a construction of linear-time binary codes which meet the so-called "zyablov bound". in a nutshell, our results match the performance of the previously known explicit constructions of codes that had polynomial time encoding and decoding, but in addition have linear time encoding and decoding algorithms.we also obtain some results for list decoding targeted at the situation when the fraction of errors is very large, namely (1&mdash;&egr;) for an arbitrarily small constant &egr; > 0. the previously known constructions of such codes of good rate over constant-sized alphabets either used algebraic-geometric codes and thus suffered from complicated constructions and slow decoding, or as in the recent work of the authors [9], had fast encoding/decoding, but suffered from an alphabet size that was exponential in 1/&egr;. we present two constructions of such codes with rate close to &ohgr;(&egr;2) over an alphabet of size quasi-polynomial in 1/&egr;. one of the constructions, at the expense of a slight worsening of the rate, can achieve an alphabet size which is polynomial in 1/&egr;. it also yields constructions of codes for list decoding from erasures which achieve new trade-offs. in particular, we construct codes of rate close to the optimal &ohgr;(&egr;) rate which can be efficiently list decoded from a fraction (1&mdash;&egr;) of erasures.
linear time encodable and list decodable codes. we present the first construction of error-correcting codes which can be (list) decoded from a noise fraction arbitrarily close to 1 in linear time. specifically, we present an explicit construction of codes which can be encoded in linear time as well as list decoded in linear time from a fraction (1-ε) of errors for arbitrary ε > 0. the rate and alphabet size of the construction are constants that depend only on ε. our construction involves devising a new combinatorial approach to list decoding, in contrast to all previous approaches which relied on the power of decoding algorithms for algebraic codes like reed-solomon codes.our result implies that it is possible to have, and in fact explicitly specifies, a coding scheme for arbitrarily large noise thresholds with only constant redundancy in the encoding and constant amount of work (at both the sending and receiving ends) for each bit of information to be communicated. such a result was known for certain probabilistic error models, and here we show that this is possible under the stronger adversarial noise model as well.
near-optimal hardness results and approximation algorithms for edge-disjoint paths and related problems. we study the approximability of edge-disjoint paths and related problems. in the edge-disjoint paths (edp) problem, we are given a network g with source-sink pairs (si, ti), 1 ≤i≤k, and the goal is to find a largest subset of source-sink pairs that can be simultaneously connected in an edge-disjoint manner. we show that in directed networks, for any ε>0, edp is np-hard to approximate within m1/2-ε. we also design simple approximation algorithms that achieve essentially matching approximation guarantees for some generalizations of edp. another related class of routing problems that we study concerns edp with the additional constraint that the routing paths be of bounded length. we show that, for any ε > 0, bounded length edp is hard to approximate within m1/2-ε even in undirected networks, and give an o(√m)-approximation algorithm for it. for directed networks, we show that even the single source-sink pair case (i.e. find the maximum number of paths of bounded length between a given source-sink pair) is hard to approximate within m1/2-ε, for any ε > 0.
limits to list decoding reed-solomon codes. in this paper, we prove the following two results that expose some combinatorial limitations to list decoding reed-solomon codes.given n distinct elements α1,...,αn from a field f, and n subsets s1,...,sn of f each of size at most l, the list decoding algorithm of guruswami and sudan [7] can in polynomial time output all polynomials p of degree at most k which satisfy p(αi) ∈ si for every i, as long as l < ⌈ n/k ⌉. we show that the performance of this algorithm is the best possible in a strong sense; specifically, we show that when l = ⌈ n/k ⌉, the list of output polynomials can be super-polynomially large in n. one way to interpret our result is the following. the algorithm in [7] can, when given as input $n'$ distinct pairs (βi,∈i) ∈ f2 (the βi's need not be distinct), find and output all degree k polynomials p such that p(βi) = γi for at least $t$ values of i, provided t > √k n'. by our result, an improvement to the reed-solomon list decoder of [7] that works with slightly smaller agreement, say t > √kn' - k/2, can only be obtained by exploiting some property of the βi's (for example, their (near) distinctness).for reed-solomon codes of block length $n$ and dimension k where k = nδ for small enough δ, we exhibit an explicit received word r with a super-polynomial number of reed-solomon codewords that agree with it on $(2 - ε) k locations, for any desired ε > 0 (we note agreement of k is trivial to achieve). such a bound was known earlier only for a non-explicit center. we remark that finding explicit bad list decoding configurations is of significant interest --- for example the best known rate vs. distance trade-off is based on a bad list decoding configuration for algebraic-geometric codes [14] which is unfortunately not explicitly known.
explicit capacity-achieving list-decodable codes. for every 0 < r < 1 and ε > 0, we present an explicit construction of error-correcting codes of rate r that can be list decoded in polynomial time up to a fraction (1-r-ε) of errors. these codes achieve the "capacity" for decoding from adversarial errors, i.e., achieve the optimal trade-off between rate and error-correction radius. at least theoretically, this meets one of the central challenges in coding theory.prior to this work, explicit codes achieving capacity were not known for any rate r. in fact, our codes are the first to beat the error-correction radius of 1-√r, that was achieved for reed-solomon (rs) codes in [9], for all rates r. (for rates r < 1/16, parvaresh and vardy [12] had recently improved upon the 1-√r bound; for r → 0, their algorithm can decode a fraction 1-o(r log(1/r)) of errors.)our codes are simple to describe --- they are certain folded reed-solomon codes, which are in fact exactly rs codes, but viewed as a code over a larger alphabet by careful bundling of codeword symbols. given the ubiquity of rs codes, this is an appealing feature of our result, since the codes we propose are not too far from the ones in actual use.the main insight in our work is that some carefully chosen folded rs codes are "compressed" versions of a related family of parvaresh-vardy codes. further, the decoding of the folded rs codes can be reduced to list decoding the related parvaresh-vardy codes. the alphabet size of these folded rs codes is polynomial in the block length. this can be reduced to a constant that depends on the distance ε to capacity using ideas concerning "list recovering" and expander-based codes from [7, 8]. concatenating the folded rs codes with suitable inner codes also gives us polytime constructible binary codes that can be efficiently list decoded up to the zyablov bound.
classical deterministic complexity of edmonds' problem and quantum entanglement. generalizing a decision problem for bipartite perfect matching, j. edmonds introduced in [14] the problem (now known as the edmonds problem) of deciding if a given linear subspace of m(n) contains a nonsingular matrix, where m(n) stands for the linear space of complex nxn matrices. this problem led to many fundamental developments in matroid theory etc.classical matching theory can be defined in terms of matrices with nonnegative entries. the notion of positive operator, central in quantum theory, is a natural generalization of matrices with nonnegative entries. (here operator refers to maps from matrices to matrices.) first, we reformulate the edmonds problem in terms of of completely positive operators, or equivalently, in terms of bipartite density matrices. it turns out that one of the most important cases when edmonds' problem can be solved in polynomial deterministic time, i.e. an intersection of two geometric matroids, corresponds to unentangled (aka separable) bipartite density matrices. we introduce a very general class (or promise) of linear subspaces of m(n) on which there exists a polynomial deterministic time algorithm to solve edmonds' problem. the algorithm is a thoroughgoing generalization of algorithms in [23], [26], and its analysis benefits from an operator analog of permanents, so called quantum permanents. finally, we prove that the weak membership problem for the convex set of separable normalized bipartite density matrices is np-hard.
hyperbolic polynomials approach to van der waerden/schrijver-valiant like conjectures: sharper bounds, simpler proofs and algorithmic applications. let p(x1,...,xn) = p(x) , x ∈ rn be a homogeneous polynomial of degree n in n real variables, e = (1,1,..,1) ∈ rn be a vector of all ones . such a polynomial p is called e-hyperbolic if for all real vectors x ∈ rn the univariate polynomial equation p(te - x) = 0 has all real roots λ1(x) ≥ ... ≥ λn(x). the number of nonzero roots |i :λi(x) ≠ 0 | is called rankp(x). an e-hyperbolic polynomial p is called pos-hyperbolic if roots of vectors x ∈ rn+ with nonnegative coordinates are also nonnegative (the orthant rn+ belongs to the hyperbolic cone) and p(e) > 0. below e1,...,en stands for the canonical orthogonal basis in rn. the main results of this paper states that if p(x1,x2,...,xn) is a pos-hyperbolic (homogeneous) polynomial of degree n, rankp (ei) = ri and p(x1,x2,...,xn) ≥ ∏1 ≤ i ≤ n xi ; xi > 0, 1 ≤ i ≤ n, then the following inequality holds ∂n/∂ x1...∂ xn p(0,...,0) ≥ ∏1 ≤ i ≤ n (gi-1/gi)gi-1, where gi = min(ri , n+1-i) . this inequality is a vast (and unifying) generalization of the van der waerden conjecture on the permanents of doubly stochastic matrices as well as the schrijver-valiant conjecture on the number of perfect matchings in k-regular bipartite graphs. these two famous results correspond to the pos-hyperbolic polynomials which are products of linear forms with nonnegative coefficients.our proof is relatively simple and "noncomputational"; it actually slightly improves schrijver's lower bound, and uses very basic (more or less centered around rolle's theorem) properties of hyperbolic polynomials. we present some important algorithmic applications of the result, including a polynomial time deterministic algorithm approximating the permanent of n x n entry-wise non-negative matrices within a multiplicative factor en/nm for any fixed positive m; and a deterministic poly-time algorithm approximating the permanent of n x n matrix a having at most k nonzero entries in each column to within a multiplicative factor (k-1/k)(k-1)n.this paper introduces a new powerful "polynomial" technique , which allows us to simplify and unify hard and key known results as well as to prove new important theorems and get new algorithms.
oblivious routing in directed graphs with random demands. oblivious routing algorithms for general undirected networks were introduced by räcke, and this work has led to many subsequent improvements and applications. more precisely, räcke showed that there is an oblivious routing algorithm with polylogarithmic competitive ratio (w.r.t. edge congestion) for any undirected graph. comparatively little positive results are known about oblivious routing in general directed networks. using a novel approach, we present the first oblivious routing algorithm which is o(log2 n) competitive with high probability in directed graphs given that the demands are chosen randomly from a known demand-distribution. on the other hand, we show that no oblivious routing algorithm can be o(logn/log log n) competitive even with constant probability in general directed graphs.our routing algorithms are not oblivious in the traditional definition, but we add the concept of demand-dependence, i.e., the path chosen for an s-t pair may depend on the demand between s and t. this concept that still preserves that routing decisions are only based on local information proves very powerful in our randomized demand model.finally, we show that our approach for designing competitive oblivious routing algorithms is quite general and has applications in other contexts like stochastic scheduling.
on the communication complexity of graph properties we prove &thgr;(n log n) bounds for the deterministic 2-way communication complexity of the graph properties connectivity, s-t-connectivity and bipartiteness (for arbitrary partitions of the variables into two sets of equal size). the proofs are based on combinatorial results of dowling-wilson and lov&aacute;sz-saks about partition matrices using the m&ouml;bius function, and the regularity lemma of szemer&eacute;di. the bounds imply improved lower bounds for the vlsi complexity of these decision problems and sharp bounds for a generalized decision tree model which is related to the notion of evasiveness.
private approximation of np-hard functions. the notion of private approximation was introduced recently by feigenbaum, fong, strauss and wright. informally, a private approximation of a function f is another function f that approximates f in the usual sense, but does not yield any information on x other than what can be deduced from f(x). as such, f(x) is useful for private computation of f(x) (assuming that f can be computed more efficiently than f.in this work we examine the properties and limitations of this new notion. specifically, we show that for many np-hard problems, the privacy requirement precludes non-trivial approximation. this is the case even for problems that otherwise admit very good approximation (e.g., problems with ptas). on the other hand, we show that slightly relaxing the privacy requirement, by means of leaking &ldquo;just a few bits of informationrdquo; about x, again permits good approximation.
polynomial-time quantum algorithms for pell's equation and the principal ideal problem. we give polynomial-time quantum algorithms for three problems from computational algebraic number theory. the first is pell's equation. given a positive nonsquare integer d, pell's equation is x2 &minus; dy2 &equals; 1 and the goal is to find its integer solutions. factoring integers reduces to finding integer solutions of pell's equation, but a reduction in the other direction is not known and appears more difficult. the second problem we solve is the principal ideal problem in real quadratic number fields. this problem, which is at least as hard as solving pell's equation, is the one-way function underlying the buchmann--williams key exchange system, which is therefore broken by our quantum algorithm. finally, assuming the generalized riemann hypothesis, this algorithm can be used to compute the class group of a real quadratic number field.
fast quantum algorithms for computing the unit group and class group of a number field. computing the unit group and class group of a number field are two of the main tasks in computational algebraic number theory. factoring integers reduces to solving pell's equation, which is a special case of computing the unit group, but a reduction in the other direction is not known and appears more difficult. we give polynomial-time quantum algorithms for computing the unit group and class group when the number field has constant degree.
limitations of quantum coset states for graph isomorphism. it has been known for some time that graph isomorphism reduces to the hidden subgroup problem (hsp). what is more, most exponential speedups in quantum computation are obtained by solving instances of the hsp. a common feature of the resulting algorithms is the use of quantum coset states, which encode the hidden subgroup. an open question has been how hard it is to use these states to solve graph isomorphism. it was recently shown by moore, russell, and schulman [30] that only an exponentially small amount of information is available from one, or a pair of coset states. a potential source of power to exploit are entangled quantum measurements that act jointly on many states at once. we show that entangled quantum measurements on at least ω(n log n) coset states are necessary to get useful information for the case of graph isomorphism, matching an information theoretic upper bound. this may be viewed as a negative result because highly entangled measurements seem hard to implement in general. our main theorem is very general and also rules out using joint measurements on few coset states for some other groups, such as gl(n,fpm) and gn where g is finite and satisfies a suitable property.
polylogarithmic inapproximability. we provide the first hardness result of a polylogarithmic approximation ratio for a natural np-hard optimization problem. we show that for every fixed ε>0, the group-steiner-tree problem admits no efficient log2-ε k approximation, where k denotes the number of groups (or, alternatively, the input size), unless np has quasi polynomial las-vegas algorithms. this hardness result holds even for input graphs which are hierarchically well-separated trees, introduced by bartal [focs, 1996]. for these trees (and also for general trees), our bound is nearly tight with the log-squared approximation currently known. our results imply that for every fixed ε>0, the directed-steiner tree problem admits no log2-ε n--approximation, where n is the number of vertices in the graph, under the same complexity assumption.
a logic to reason about likelihood we present a logic ll which uses a modal operator l to help capture the notion of likely. despite the fact that no use is made of numbers, ll can capture many of the properties of likelihood in an intuitively appealing way. using standard techniques of modal logic, we give a complete axiomatization for ll and show that satisfiability of ll formulas can be decided in exponential time. we discuss how the logic might be used in areas where decision making is crucial, such as management and medical diagnosis, and conclude by using ll to give a formal proof of correctness of a protocol for exchanging secrets.
rational secret sharing and multiparty computation: extended abstract. we consider the problems of secret sharing and multiparty computation, assuming that agents prefer to get the secret (resp., function value) to not getting it, and secondarily, prefer that as few as possible of the other agents get it. we show that, under these assumptions, neither secret sharing nor multiparty function computation is possible using a mechanism that has a fixed running time. however, we show that both are possible using randomized mechanisms with constant expected running time.
a patent problem for abstract programming languages: machine-independent computations a programming language may be viewed as an acceptable numbering of the partial recursive functions, with &ldquo;semantics&rdquo; the mapping from programs onto the functions computed [1]. (in this view, syntax receives little attention, although it is best to consider it as a characteristic function of a recursive set of indices instead of allowing all natural numbers. such a view is natural for the usual arithmetizations, and eliminates some possible confusions, for example in interpreting the recursion theorem for pairs of numberings.) the virtue of functional semantics is that the semantic range is a machine-independent class. the abstract view in which details of the semantic mapping are ignored, in which the function assigned to a program is &ldquo;the one it computes,&rdquo; with the enumeration and s-m-n theorems assumed to compensate for the lost detail, has found only a restricted application to programning-language problems. computational complexity, in the successful abstraction by blum [2], is an attempt to provide more semantic structure without introducing a tenacious machine-dependence. the blum measures are not themselves suitable as a semantic range. two programs may have the same measure function, yet compute wildly different functions in widly different ways; other programs, intuitively very similar, may have wildly different measure functions [3]. a composite semantics of a function computed and a measure function is much like the approach suggested here: using formal computation functions as the semantic range.
a new grammatical transformation into ll(k) form (extended abstract) for some time, it has been recognized that left-to-right deterministic top-down parsing has a number of features to recommend it. the logic of such a parser is easily expressed as a one-state pushdown machine, and very flexible translations can readily be performed in conjunction with top-down processing. the major difficulty with this style of parsing is that there are relatively few grammars which satisfy the rather restrictive requirements to admit of top-down parsing (the ll(k) grammars), in comparsion with grammars that can be parsed deterministically bottom-up (the lr(k) grammars). there has been some research along the lines of trying to apply transformations to non-ll(k) grammars in order to convert them into equivalent ll(k) form [1,2,3]; the most successful approach has been that of rosenkrantz and lewis [4]. they define class of grammars, the lc(k) grammars, which can be parsed in a mixed hybrid of top-down bottom-up techniques; this class strictly includes the ll(k) grammars, as well as many interesting but non-ll(k) grammars. they then provide a deterministic algorithm for converting any lc(k) grammar into an equivalent ll(k) grammar. this work is a generalization of, and in the same spirit as, the lewis and rosenkrantz program. we investigate a new hybrid parsing method, basically bottom-up in character, but which contains a minimal infusion of top-down ideas. we consider the class of grammars which can be parsed by this method, and observe that it strictly includes the class of lc(k) grammars. then we exhibit an algorithm for deriving from any such grammar an equivalent ll(k) grammar; this derived grammar is also as &ldquo;useful&rdquo; as the original one in directing compilation activities, for it can support translations equivalent to those supportable by the original grammar.
transforming cabbage into turnip: polynomial algorithm for sorting signed permutations by reversals. genomes frequently evolve by reversals &rgr;(i,j) that transform a gene order &pgr;1 &hellip; &pgr;i&pgr;i+1 &hellip; &pgr;j-1&pgr;j &hellip; &pgr;n into &pgr;1 &hellip; &pgr;i&pgr;j-1 &hellip; &pgr;i+1&pgr;j &hellip; &pgr;n. reversal distance between permutations &pgr; and &sgr;is the minimum number of reversals to transform &pgr; into &agr;. analysis of genome rearrangements in molecular biology started in the late 1930's, when dobzhansky and sturtevant published a milestone paper presenting a rearrangement scenario with 17 inversions between the species of drosophilia. analysis of genomes evolving by inversions leads to a combinatorial problem of sorting by reversals studied in detail recently. we study sorting of signed permutations by reversals, a problem that adequately models rearrangements in a small genomes like chloroplast or mitochondrial dna. the previously suggested approximation algorithms for sorting signed permutations by reversals compute the reversal distance between permutations with an astonishing accuracy for both simulated and biological data. we prove a duality theorem explaining this intriguing performance and show that there exists a &ldquo;hidden&rdquo; parameter that allows one to compute the reversal distance between signed permutations in polynomial time.
on coresets for k-means and k-median clustering. in this paper, we show the existence of small coresets for the problems of computing k-median and k-means clustering for points in low dimension. in other words, we show that given a point set p in rd, one can compute a weighted set s ⊆ p, of size o(k ε-d log n), such that one can compute the k-median/means clustering on s instead of on p, and get an (1+ε)-approximation. as a result, we improve the fastest known algorithms for (1+ε)-approximate k-means and k-median. our algorithms have linear running time for a fixed k and ε. in addition, we can maintain the (1+ε)-approximate k-median or k-means clustering of a stream when points are being only inserted, using polylogarithmic space and update time.
computability and completeness in logics of programs (preliminary report) dynamic logic is a generalization of first order logic in which quantifiers of the form &ldquo;for all &khgr;...&rdquo; are replaced by phrases of the form &ldquo;after executing program &agr;...&rdquo;. this logic subsumes most existing first-order logics of programs that manipulate their environment, including floyd's and hoare's logics of partial correctness and manna and waldinger's logic of total correctness, yet is more closely related to classical first-order logic than any other proposed logic of programs. we consider two issues: how hard is the validity problem for the formulae of dynamic logic, and how might one axiomatize dynamic logic? we give bounds on the validity problem for some special cases, including a &pgr;02-completeness result for the partial correctness theories of uninterpreted flowchart programs. we also demonstrate the completeness of an axiomatization of dynamic logic relative to arithmetic.
a complete axiomatic system for proving deductions about recursive programs denoting a version of hoare's system for proving partial correctness of recursive programs by h, we present an extension d which may be thought of as h &ugr; {@@@@,@@@@,@@@@,@@@@} &ugr; h-1, including the rules of h, four special purpose rules and inverse rules to those of hoare. d is shown to be a complete system (in cook's sense) for proving deductions of the form &sgr;1,....&sgr;n @@@@ &sgr; over a language, the wff's of which are assertions in some assertion language l and partial correctness specifications of the form p(&agr;)q. all valid formulae of l are taken as axioms of d. it is shown that d is sufficient for proving partial correctness, total correctness and program equivalence as well as other important properties of programs, the proofs of which are impossible in h. the entire presentation is worked out in the framework of nondeterministic programs employing iteration and mutually recursive procedures.
completeness in two-party secure computation: a computational view. a secure function evaluation (sfe) of a two-variable function f(·,·) is a protocol that allows two parties with inputs x and y to evaluate f(x,y) in a manner where neither party learns "more than is necessary". a rich body of work deals with the study of completeness for secure two-party computation. a function f is complete for sfe if a protocol for securely evaluating f allows the secure evaluation of all (efficiently computable) functions. the questions investigated are which functions are complete for sfe, which functions have sfe protocols unconditionally and whether there are functions that are neither complete nor have efficient sfe protocols.the previous study of these questions was mainly conducted from an information theoretic point of view and provided strong answers in the form of combinatorial properties. however, we show that there are major differences between the information theoretic and computational settings. in particular, we show functions that are considered as having sfe unconditionally by the combinatorial criteria but are actually complete in the computational setting. we initiate the fully computational study of these fundamental questions. somewhat surprisingly, we manage to provide an almost full characterization of the complete functions in this model as well. more precisely, we present a computational criterion (called computational row non-transitivity) for a function f to be complete for the asymmetric case. furthermore, we show a matching criterion called computational row transitivity for f to have a simple sfe (based on no additional assumptions). this criterion is close to the negation of the computational row non-transitivity and thus we essentially characterize all "nice" functions as either complete or having sfe unconditionally.
probabilistic temporal logics for finite and bounded models we present two (closely-related) propositional probabilistic temporal logics based on temporal logics of branching time as introduced by ben-ari, pnueli and manna and by clarke and emerson. the first logic, ptlf, is interpreted over finite models, while the second logic, ptlb, which is an extension of the first one, is interpreted over infinite models with transition probabilities bounded away from 0. the logic ptlf allows us to reason about finite-state sequential probabilistic programs, and the logic ptlb allows us to reason about (finite-state) concurrent probabilistic programs, without any explicit reference to the actual values of their state-transition probabilities. a generalization of the tableau method yields exponential-time decision procedures for our logics, and complete axiomatizations of them are given. several meta-results, including the absence of a finite-model property for ptlb, and the connection between satisfiable formulae of ptlb and finite state concurrent probabilistic programs, are also discussed.
on isomorphisms and density of np and other complete sets if all np complete sets are isomorphic under deterministic polynomial time mappings (p-isomorphic) then p @@@@ np and if all ptape complete sets are p-isomorphic then p @@@@ ptape. we show that all np complete sets known (in the literature) are indeed p-isomorphic and so are the known ptape complete sets. thus showing that, inspite of the radically different origins and attempted simplification of these sets, all the known np complete sets are identical but for polynomially time bounded permutations. furthermore, if all np complete sets are p-isomorphic then they all must have similar densities and, for example, no language over a single letter alphabet can be np complete, nor can any sparse language over an arbitrary alphabet be np complete. we show that complete sets in exptime and exptape cannot be sparse and therefore they cannot be over a single letter alphabet. similarly, we show that the hardest context-sensitive languages cannot be sparse. we also relate the existence of sparse complete sets to the existence of simple combinatorial circuits for the corresponding truncated recognition problem of these languages.
sparse sets in np-p: exptime versus nexptime this paper investigates the structural properties of sets in np-p and shows that the computational difficulty of lower density sets in np depends explicitly on the relations between higher deterministic and nondeterministic time-bounded complexity classes. the paper exploits the recently discovered upward separation method, which shows for example that there exist sparse sets in np-pif and only if exptime @@@@ nexptime. in addition, the paper uses relativization techniques to determine logical possibilities, limitations of these proof techniques, and, for the first time, to exhibit structural differences between relativized np and conp.
every 2-csp allows nontrivial approximation. we use semidefinite programming to prove that any constraint satisfaction problem in two variables over any domain allows an efficient approximation algorithm that does provably better than picking a random assignment. to be more precise assume that each variable can take values in [d] and that each constraint rejects t out of the d2 possible input pairs. then, for some universal constant c, we can, in probabilistic polynomial time, find an assignment whose objective value is, on expectation, within a factor (1- t/d2(1- c/d2 log d)) of optimal.
some optimal inapproximability results. we prove optimal, up to an arbitrary &epsilon; > 0, inapproximability results for max-e k-sat for k &ge; 3, maximizing the number of satisfied linear equations in an over-determined system of linear equations modulo a prime p and set splitting. as a consequence of these results we get improved lower bounds for the efficient approximability of many optimization problems studied previously. in particular, for max-e2-sat, max-cut, max-di-cut, and vertex cover.
the cryptographic security of truncated linearly related variables in this paper we describe a polynomial time algorithm for computing the values of variables x1, &hellip; xk when some of their bits and some linear relationships between them are known. the algorithm is essentially optimal in its use of information in the sense that it can be applied as soon as the values of the xi become uniquely determined by the constraints. its cryptanalytic significance is demonstrated by two applications: breaking linear congruential generators whose outputs are truncated, and breaking blum's protocol for exchanging secrets.
on the advantage over a random assignment. we initiate the study of a new measure of approximation. this measure compares the performance of an approximation algorithm to the random assignment algorithm. this is a useful measure for optimization problems where the random assignment algorithm is known to give essentially the best possible polynomial time approximation. in this paper, we focus on this measure for the optimization problems max-lin-2 in which we need to maximize the number of satisfied linear equations in a system of linear equations modulo 2, and max-k-lin-2, a special case of the above problem in which each equation has at most k variables. the main techniques we use, in our approximation algorithms and inapproximability results for this measure, are from fourier analysis and derandomization.
classes of functions for computing on binary trees (extended abstract) this paper constitutes part of a general investigation into abstract computability on finitely generated free algebras (term algebras). the general idea is to determine an abstract computational process appropriate for computing on term algebras, the effectiveness of which should be apparent from the inductive structure of that domain, without reference to computability on the natural numbers (say, via coding).
randomly coloring graphs of girth at least five. we improve rapid mixing results for the simple glauber dynamics designed to generate a random k-coloring of a bounded-degree graph.let g be a graph with maximum degree δ = ω(log n), and girth ≥ 5. we prove that if k > α δ, where α ≈ 1.763 then glauber dynamics has mixing time o(n log n). if girth(g) ≥ 6 and k > β δ, where β ≈ 1.489 then glauber dynamics has mixing time o(n log n). this improves a recent result of molloy, who proved the same conclusion under the stronger assumptions that δ=ω(log n) and girth ω(log δ). our work suggests that rapid mixing results for high girth and degree graphs may extend to general graphs.analogous results hold for random graphs of average degree up to n¼, compared with polylog(n), which was the best previously known.some of our proofs rely on a new chernoff-hoeffding type bound, which only requires the random variables to be well-behaved with high probability. this tail inequality may be of independent interest.
the effect of collusion in congestion games. in this paper we initiate the study of how collusion alters the quality of solutions obtained in competitive games. the price of anarchy aims to measure the cost of the lack of coordination by comparing the quality of a nash equilibrium to that of a centrally designed optimal solution. this notion assumes that players act not only selfishly, but also independently. we propose a framework for modeling groups of colluding players, in which members of a coalition cooperate so as to selfishly maximize their collective welfare. clearly, such coalitions can improve the social welfare of the participants, but they can also harm the welfare of those outside the coalition. one might hope that the improvement for the coalition participants outweighs the negative effects on the others. this would imply that increased cooperation can only improved the overall solution quality of stable outcomes. however, increases in coordination can actually lead to significant decreases in total social welfare. in light of this, we propose the price of collusion as a measure of the possible negative effect of collusion, specifying the factor by which solution quality can deteriorate in the presence of coalitions. we give examples to show that the price of collusion can be arbitrarily high even in convex games. our main results show that in the context of load-balancing games, the price of collusion depends upon the disparity in market power among the game participants. we show that in some symmetric nonatomic games (where all users have access to the same set of strategies) increased cooperation always improves the solution quality, and in the discrete analogs of such games, the price of collusion is bounded by two.
using nondeterminism to amplify hardness. we revisit the problem of hardness amplification in $\mathcal{np}$, as recently studied by o'donnell [j. comput. system sci., 69 (2004), pp. 68-94]. we prove that if $\mathcal{np}$ has a balanced function $f$ such that any circuit of size $s(n)$ fails to compute $f$ on a $1/\poly(n)$ fraction of inputs, then $\mathcal{np}$ has a function $f'$ such that any circuit of size $s'(n)=s(\sqrt{n})^{\omega(1)}$ fails to compute $f'$ on a $1/2 - 1/s'(n)$ fraction of inputs. in particular, \begin{enumerate} \item if $s(n)=n^{\omega(1)}$, we amplify to hardness $1/2-1/n^{\omega(1)}$; \item if $s(n)=2^{n^{\omega(1)}}$, we amplify to hardness $1/2-1/2^{n^{\omega(1)}}$; \item if $s(n)=2^{\omega(n)}$, we amplify to hardness $1/2-1/2^{\omega(\sqrt{n})}$. \end{enumerate}our results improve those of of o'donnell, which amplify to $1/2-1/\sqrt{n}$. o'donnell also proved that no construction of a certain general form could amplify beyond $1/2-1/n$. we bypass this barrier by using both derandomization and nondeterminism in the construction of $f'$.we also prove impossibility results demonstrating that both our use of nondeterminism and the hypothesis that $f$ is balanced are necessary for "black-box" hardness amplification procedures (such as ours).
the pagenumber of genus g graphs is o(g) in 1979, bernhart and kainen conjectured that graphs of fixed genus g &ge; 1 have unbounded pagenumber. in this paper, it is proven that genus g graphs can be embedded in o(g) pages, thus disproving the conjecture. an &ohgr;(g1/2) lower bound is also derived. the first algorithm in the literature for embedding an arbitrary graph in a book with a non-trivial upper bound on the number of pages is presented. first, the algorithm computes the genus g of a graph using the algorithm of filotti, miller, reif (1979), which is polynomial-time for fixed genus. second, it applies an optimal-time algorithm for obtaining an o(g)-page book embedding. separate book embedding algorithms are given for the cases of graphs embedded in orientable and nonorientable surfaces. an important aspect of the construction is a new decomposition theorem, of independent interest, for a graph embedded on a surface. book embedding has application in several areas, two of which are directly related to the results obtained: fault-tolerant vlsi and complexity theory.
flow graph reducibility the structure of programs can often be described by a technique called &ldquo;interval analysis&rdquo; on their flow graphs. here, we characterize the set of flow graphs that can be analyzed in this way in terms of two very simple transformation on graphs. we then give a necessary and sufficient condition for analyzability and apply it to &ldquo;goto-less programs,&rdquo; showing that they all meet the criterion.
a polynomial linear search algorithm for the n-dimensional knapsack problem we present a linear search algorithm which decides the n-dimensional knapsack problem in n4log(n) + 0.(n3) steps. this algorithm works for inputs consisting of n numbers for some arbitrary but fixed integer n. this result solves an open problem posed for example in [6] and [7] by dobkin / lipton and a.c.c. yao, resp.. it destroys the hope of proving large lower bounds for this np-complete problem in the model of linear search algorithms.
fast algorithms for n-dimensional restrictions of hard problems let m be a parallel ram with p processors and arithmetic operations addition and subtraction recognizing l &sub; nn in t steps. (inputs for m are given integer by integer, not bit by bit.) then l can be recognized by a (sequential) linear search algorithm (lsa) in o(n4(log(n) + t + log(p))) steps. thus many n-dimensional restrictions of np-complete problems (binary programming, traveling salesman problem, etc.) and even that of the uniquely optimum traveling salesman problem, which is &dgr;p2-complete, can be solved in polynomial time by an lsa. this result generalizes the construction of a polynomial lsa for the n-dimensional restriction of the knapsack problem previously shown by the author, and destroys the hope of proving nonpolynomial lower bounds on lsas for any problem that can be recognized by a pram as above with 2poly(n) processors in poly(n) time.
testing polynomials which are easy to compute (extended abstract) we exploit the fact that the set of all polynomials p&egr;@@@@[x1,..,xn] of degree &le;d which can be evaluated with &le;v nonscalar steps can be embedded into a zariski-closed affine set w(d,n,v),dim w(d,n,v)&le;(v+1 +n)2 and deg w(d,n,v)&le;(2vd)(v+1+n)2. as a consequence we prove that for u:&equil; 2v(d+1)2 and s:&equil; 6(v+1+n)2 there exist &abarbelow;1,..,&abarbelow;s&egr; [u]n &equil; {1,2,..,u}n such that for all polynomials p&egr;w(d,n,v):p(&abarbelow;1) &equil; p(&abarbelow;2) &equil;...&equil; p(&abarbelow;s) &equil; o implies p&xgr;o. this means that &abarbelow;1,...,&abarbelow;s is a correct test sequence for a zero test on all polynomials in w(d,n,v). moreover, &ldquo;almost every&rdquo; sequence &abarbelow;1,..,&abarbelow;s&egr;[u]n is such a correct test sequence for w(d,n,v). the existence of correct test sequences &abarbelow;1,..,&abarbelow;s&egr; [u]n is established by a counting argument without constructing a correct test sequence. we even show that it is beyond the known methods to establish (i.e. to construct and to prove correctness) of such a short correct test sequence for w(d,n,v). we prove that given such a short, correct test sequence for w(d,n,v) we can efficiently construct a multivariate polynomial p&egr;@@@@[x1,..,xn] with deg(p) &equil; d and small integer coefficients such that p@@@@ w(d,n,v). for v>n log d lower bounds of this type are beyond our present methods in algebraic complexity theory.
how many queries are needed to learn? we investigate the query complexity of exact learning in the membership and (proper) equivalence query model. we give a complete characterization of concept classes that are learnable with a polynomial number of polynomial sized queries in this model. we give applications of this characterization, including results on learning a natural subclass of dnf formulas, and on learning with membership queries alone. query complexity has previously been used to prove lower bounds on the time complexity of exact learning. we show a new relationship between query complexity and time complexity in exact learning: if any &ldquo;honest&rdquo; class is exactly and properly learnable with polynomial query complexity, but not learnable in polynomial time, then p = np. in particular, we show that an honest class is exactly polynomial-query learnable if and only if it is learnable using an oracle for &ggr;p4.
exact learning of dnf formulas using dnf hypotheses. we show the following: (a) for any @e>0, log^(^3^+^@e^)n-term dnf cannot be polynomial-query learned with membership and strongly proper equivalence queries. (b) for sufficiently large t, t-term dnf formulas cannot be polynomial-query learned with membership and equivalence queries that use t^1^+^@e-term dnf formulas as hypotheses, for some @e
the strong exponential hierarchy collapses the polynomial hierarchy, composed of the levels p, np, pnp, npnp, etc., plays a central role in classifying the complexity of feasible computations. it is not known whether the polynomial hierarchy collapses. we resolve the question of collapse for an exponential-time analogue of the polynomial-time hierarchy. composed of the levels e (i.e., &cup;c dtime[2cn]), ne, pne, npne, etc., the strong exponential hierarchy collapses to its &dgr;2 level. e &ne; pne = npne &cup; npnpne &cup; &middot;&middot;&middot; our proof stresses the use of partial census information and the exploitation of nondeterminism. extending our techniques, we also derive new quantitative relativization results. we show that if the (weak) exponential hierarchy's &dgr;j+1 and &sgr;j+1 levels, respectively e&sgr;pj and ne&sgr;pj, do separate, this is due to the large number of queries ne makes to its &sgr;pj database.1 our technique provide a successful method of proving the collapse of certain complexity classes.
parameter-passing mechanisms and nondeterminism the problem of defining an adequate semantics for recursive definitions which allow various types of parameter-passing mechanisms has generated a considerable amount of interest in the literature. (see [b1], [m4], [r3], [v2]) consider for example the well-known recursive definition f <x, y> <&equil; if x&equil;0 then 0 else f<x&minus;1,f<x, y>>. interpreted as a fixpoint equation over the flat cpo of non-negative integers it has as its least solution f(x, y) = 0 if x&equil;m for any non-negative integer m &equil; @@@@ otherwise (&ldquo;@@@@&rdquo; means undefined) this also happens to coincide with the computed function if a call-by-name (or outside-in) evaluation mechanism is used. however if a call-by-value (or inside-out) evaluation mechanism is used the computed function is fv (x, y) &equil; 0 if x&equil;0 &equil; @@@@ otherwise in [vl] the conclusion is drawn that the call-by-value evaluation mechanism is incorrect and should not be considered.
what's decidable about hybrid automata? hybrid automata model systems with both digital and analog components, such as embedded control programs. many verification tasks for such programs can be expressed as reachability problems for hybrid automata. by improving on previous decidability and undecidability results, we identify the precise boundary between decidability and undecidability of the reachability problem for hybrid automata. on the positive side, we give an (optimal) pspace reachability algorithm for the case of initialized rectangular automata, where all analog variables follow trajectories within piecewise-linear envelopes and are reinitialized whenever the envelope changes. our algorithm is based on the construction of a timed automaton that contains all reachability information about a given initialized rectangular automaton. the translation has practical significance for verification, because it guarantees the termination of symbolic procedures for the reachability analysis of initialized rectangular automata. the translation also preserves the $\omega$-languages of initialized rectangular automata with bounded nondeterminism. on the negative side, we show that several slight generalizations of initialized rectangular automata lead to an undecidable reachability problem. in particular, we prove that the reachability problem is undecidable for timed automata augmented with a single stopwatch.
computability over arbitrary fields in most attempts to make precise the concept of a computable function, or decidable predicate, over a field f, it is considered necessary that the elements of f should be in some sense effectively describable, and hence that f itself should be countable. this is the attitude taken in the study of computable fields (see rabin1). our proposed definition of computability over arbitrary fields is based on the shepherdson - sturgis2 concept of an unlimited register machine.
matrix searching with the shortest path metric. we present an o(n) time algorithm for computing row-wise maxima or minima of an implicit, totally monotone $n \times n$ matrix whose entries represent shortest-path distances between pairs of vertices in a simple polygon. we apply this result to derive improved algorithms for several well-known problems in computational geometry. most prominently, we obtain linear-time algorithms for computing the geodesic diameter, all farthest neighbors, and external farthest neighbors of a simple polygon, improving the previous best result by a factor of o(log n) in each case.
parallel algorithms for the transitive closure and the connected component problems parallel programs are presented that determine the transitive closure of a matrix using n3 processors and connected components of an undirected graph using n2 processors. in both cases, the desired results are obtained in time 0(log2n). it is assumed that the processors have access to common memory. simultaneous access to the same location is permitted for fetch, but not store, instructions. the problem of determining the connected components of a graph using a parallel computer has recently appeared in the literature [1,2]. the result in [1] is based on finding the transitive closure of a matrix in time 0(log2n) which can be done using 0(n3) processors. we show that n2 processors are sufficient to solve the connected component problem in time 0(log2n). we present algorithm closure that will find the transitive closure of boolean matrix m [n by n] using n3 processors [numbered p(0,0,0) through p(n&minus;1 ,n&minus;1, n&minus;1)] each of which has local memory and each of which can access common array a [n by n].
powers of graphs: a powerful approximation technique for bottleneck problems in this paper we investigate a powerful, and yet simple, technique for devising approximation algorithms for a wide variety of np-complete problems in routing, location, and communication network design. each of the algorithms presented here delivers an approximate solution guaranteed to be within a constant factor of the optimal solution. in addition, for several of these problems we can show that unless p&eqil;np, there does not exist a polynomial-time algorithm that has a better performance guarantee.
the logical complexity of geometric properties in the plane this paper studies the logical complexity of geometric properties in the plane. these properties are characterized according to the length of formulas necessary to express them. in this study a portion of the plane x will be considered as a collection of squares {x1, ..., xn} arranged into a fine grid. a pattern p is a subset of x and the grid is assumed to be fine enough so that approximations to geometrical figures can be obtained. p can be defined by mapping m: x &ran;{0,1} where for x &egr; x, m(x) &equil; 1 iff x &egr; p. a set of patterns or a geometrical property &rgr; can be expressed as a boolean function f on the n variables x1, ..., xn such that the value of f is 1 under the assignment m iff p &egr; &rgr.
testing isomorphism on cone graphs (extended abstract) we give algorithms to decide graph isomorphism in a subclass of graphs which we call cone graphs. a cone graph is an undirected graph for which there exists a vertex r which uniquely determines a breadth-first search (bfs) tree. equivalently, all shortest paths from r to any other graph vertex are unique. our algorithms may be used either nondeterministically or probabilistically. used as probabilistic algorithms, they return always a correct answer, but with an expected running time only.
key agreement from weak bit agreement. assume that alice and bob, given an authentic channel, have a protocol where they end up with a bit sa and sb, respectively, such that with probability 1+ε/2 these bits are equal. further assume that conditioned on the event sa =n sb no polynomial time bounded algorithm can predict the bit better than with probability 1-δ/2. is it possible to obtain key agreement from such a primitive? we show that for constant δ and ε the answer is yes if and only if δ > 1-ε/1+ε, both for uniform and non-uniform adversaries.the main computational technique used in this paper is a strengthening of impagliazzo's hard-core lemma to the uniform case and to a set size parameter which is tight (i.e., twice the original size). this may be of independent interest.
poly-logarithmic deterministic fully-dynamic algorithms for connectivity, minimum spanning tree, 2-edge, and biconnectivity. deterministic fully dynamic graph algorithms are presented for connectivity, minimum spanning tree, 2-edge connectivity, and biconnectivity. assuming that we start with no edges in a graph with n vertices, the amortized operation costs are o(log2 n) for connectivity, o(log4 n) for minimum spanning forest, 2-edge connectivity, and o(log5 n) biconnectivity.
a new pcp outer verifier with applications to homogeneous linear equations and max-bisection. we show an optimal hardness result for the following problem: given a system of homogeneous linear equations over gf(2) with 3 variables per equation, find a balanced assignment that satisfies maximum number of equations. for arbitrarily small constant ζ > 0, we show that it is hard to determine (in polynomial time) whether such a system has a balanced assignment that satisfies 1-ζ fraction of equations or there is no balanced assignment that satisfies more than ½+ζ fraction of equations. as a corollary, we show that it is hard to approximate (in polynomial time) the max-bisection problem within factor 16⁄15-ζ. these hardness results hold under the assumption np ⊈ ∩ε > 0 dtime(2nε).our results are obtained via a construction of a new pcp outer verifier that has a mixing property and a smoothness property. these properties are crucial in the analysis of the inner verifier. no previous outer verifier can achieve both these properties simultaneously. an outer verifier is essentially a 2-query pcp over a large alphabet. loosely speaking, the mixing property says that the locations of the two queries read by the verifier are uncorrelated. the smoothness property says that the verifier's acceptance predicate is close to being a bijective predicate. our construction relies on the algebraic techniques used to prove the pcp theorem. this is in contrast with all earlier constructions that use the pcp theorem as a black-box. the progress in inapproximability theory seems to require new ideas for building outer verifiers and our construction takes a first step in that direction.
notes on merging networks (preliminary version) several new results which contribute to the understanding of parallel merging networks are presented. first, a simple new explanation of the operation of batcher's merging networks is offered. this view leads to the derivation of a modified version of batcher's odd-even (m, n) network which has delay time [log(m+n)]. this is the same delay time as batcher's bitonic (m, n) network, but it is achieved with substantially fewer comparators. second, a correspondence is demonstrated between the number of comparators (and the delay time) for such networks and certain properties of binary number systems which have recently been extensively studied. third, the [log(m + n)] delay time is shown to be optimal for a non-degenerate range of values of m and n.
duality applied to the complexity of matrix multiplications and other bilinear forms the paper considers the complexity of bilinear forms in a noncommutative ring. the dual of a computation is defined and applied to matrix multiplication and other bilinear forms. it is shown that the dual of an optimal computation gives an optimal computation for a dual problem. an nxm by mxp matrix product is shown to be the dual of an nxp by pxm or an mxn by nxp matrix product implying that each of the matrix products requires the same number of multiplications to compute. finally an algorithm for computing a single bilinear form over a noncommutative ring with a minimum number of multiplications is derived by considering a dual problem.
linear time algorithm for isomorphism of planar graphs (preliminary report) the isomorphism problem for graphs g1 and g2 is to determine if there exists a one-to-one mapping of the vertices of g1 onto the vertices of g2 such that two vertices of g1 are adjacent if and only if their images in g2 are adjacent. in addition to determining the existence of such an isomorphism, it is useful to be able to produce an isomorphism-inducing mapping in the case where one exists. the isomorphism problem for triconnected planar graphs is particularly simple since a triconnected planar graph has a unique embedding on a sphere [6]. weinberg [5] exploited this fact in developing an algorithm for testing isomorphism of triconnected planar graphs in o(|v|2) time where v is the set consisting of the vertices of both graphs. the result has been extended to arbitrary planar graphs and improved to o(|v|log|v|) steps by hopcroft and tarjan [2,3]. in this paper, the time bound for planar graph isomorphism is improved to o(|v|). in addition to determining the isomorphism of two planar graphs, the algorithm can be easily extended to partition a set of planar graphs into equivalence classes of isomorphic graphs in time linear in the total number of vertices in all graphs in the set. a random access model of computation (see cook [1]) is assumed. although the proposed algorithm has a linear asymptotic growth rate, at the present stage of development it appears to be inefficient on account of a rather large constant. this paper is intended only to establish the existence of a linear algorithm which subsequent work might make truly efficient.
algorithms for rational function arithmetic operations despite recent advances in speeding up many arithmetic and algebraic algorithms plus a general increase in algorithm analyses, no computing time study has ever been done for algorithms which perform the rational function arithmetic operations. mathematical symbol manipulation systems which provide for operations on rational functions use algorithms which were initially given by p. henrici in 1956. in this paper, these algorithms are precisely specified and their computing times analyzed. then, new algorithms based on the use of modular arithmetic are developed and analyzed. it is shown that the computing time for adding and taking the derivative of rational functions is 2 orders of magnitude faster using the modular algorithms. also, the computing time for rational function multiplication will be one order of magnitude faster using the modular algorithm.
efficient stable sorting with minimal extra space in his chapter on sorting, knuth [1]@@@@ describes the open problem of stable sorting with no more than 0(log2n) bits of extra space and less than 0(n2) computation time. in this paper we define the concept of a contiguent and show that a contiguent forming algorithm may be used as the basis for a stable sort. a class of such contiguent forming algorithm may be used as the basis for a stable sort. a class of such contiguent forming algorithms is described, the most naive of which requires 0(log n) bits of extra space and 0(n log2n) computation time. we also describe a stable merging algorithm which requires 0(n) time and 0(log n) bits of extra space, but which is not applicable to all cases. it is shown, however, that this merge may be combined with a contiguent compilation algorithm to yield a generally applicable stable sorting algorithm. one such combination provides the basis for a stable sorting algorithm which requires 0(n.logn.g(n)) time and 0(log n) bits of extra space. another such combination provides the basis for a stable sorting algorithm which requires 0(n log n) time and 0(log2n) bits of extra space.
nondeterministic communication with a limited number of advice bits. we present a new technique for differentiating deterministic from nondeterministic communication complexity. as a consequence we give almost tight lower bounds for the nondeterministic communication complexity with a restricted number of advice bits. in particular, for any function $t : \mathbb{n} \rightarrow \mathbb{n}$ with $t(n) \leq n/2$ we construct a family $(l_{n,t(n)} : n \in \mathbb{n})$ of languages such that $l_{n,t(n)} \subseteq \{0,1\}^{2n}$, ${\rm nc}(l_{n,t(n)}) = o(t(n) \cdot \log_2 \frac{n}{t(n)})$ and ${\rm nc}(\overline{l_{n,t(n)}}) = o\bigl(\frac{n}{t(n) \cdot \log_2 \frac{n}{t(n)}} + \log_2 t(n)\bigr)$, but ${\rm nc}_{o(t(n))}(l_{n,t(n)}) = \omega\bigl(\frac{n}{\log_2 \frac{n}{t(n)}}\bigr)$. here ${\rm nc}_r(l)$ is the nondeterministic communication complexity of l, assuming that at most r advice bits are utilized. thus, in contrast to probabilistic communication complexity, a small reduction in the number of advice bits results in almost maximal communication. as a special case we obtain a family $l_n \subseteq \{0,1\}^{2n}$ of languages with {\rm nc}_{o(\sqrt{n}/\log_2 n)}(l_n) &=& \omega\biggl(\frac{n}{\log_2 n}\biggr),\\ {\rm nc}(l_n) + {\rm nc}(\overline{l_n}) &=& o(\sqrt{n}), and hence nondeterministic communication with slightly restricted access to advice bits is almost quadratically weaker than nondeterminism that always gives correct answers (from the set {yes, no, ?}). as a consequence we obtain an almost optimal separation between monte-carlo communication and "correct" nondeterminism and answer a question of beame and lawry.
factorization of polynomials over finite fields and factorization of primes in algebraic number fields based on kummer theorem, we study the deterministic complexity of two factorization problems: polynomial factorization over finite fields and prime factorization in algebraic number fields. we show that factoring polynomials of degree n in fp[x], with p prime, is polynimially equivalent to factoring p in algebraic number field of extension degree n over q, where p is &ldquo;regular&rdquo; with respect to the generating polynomials of the number fields. part of the proof also yields an efficient polynomial time algorithm for computing the factorization pattern. number theoretical methods are then developed to solve two important kinds of polynomials:&fgr;n(x) mod p where &fgr;n is the n-th cyclotomic polynomial, and xn. - &agr; mod p where &agr; &egr; n. we show that when extended riemann hypothesis is assumed, all the roots of both kinds of polynomials in fp can be found efficiently in time polynomial in n and logp. as &agr; consequence, when p &xgr; 1(n), factorization of p in the n-th cyclotomic field can be computed in polynomial time. the result on finding all roots of xn &xgr; &agr;(p) extends &agr; result of adleman, menders, and miller, which states that the least root of xn &xgr; &agr;(p) can be found in polynomial time, when extended riemann hypothesis is assumed.
riemann hypothesis and finding roots over finite fields it is shown that assuming generalized riemann hypothesis, the roots of &fnof;(x) = o mod p, where p is a prime and f(x) is an integral abilene polynomial can be found in deterministic polynomial time. the method developed for solving this problem is also applied to prime decomposition in abelian number fields, and the following result is obtained: assuming generalized riemann hypotheses, for abelian number fields k of finite extension degree over the rational number field q, the decomposition pattern of a prime p in k, i.e. the ramification index and the residue class degree, can be computed in deterministic polynomial time, providing p does not divide the extension degree of k over q. it is also shown, as a theorem fundamental to our algorithm, that for q, p prime and m the order of p mod q, there is a q-th nonresidue in the finite field fpm that can be written as ao + a1w + &hellip; + am-1wm-1, where |a1| &le; cq2 log2(pq), c is an absolute effectively computable constant, and 1, w, &hellip;, wm-1 form a basis of fpm over fp. more explicitly, w is a root of the q-th cyclotomic polynomial over fp. this result partially generalizes, to finite field extensions over fp, a classical result in number theory stating that assuming generalized riemann hypothesis, the least q-th nonresidue mod p for p,q prime and q dividing p - t is bounded by c log2p, where c is an absolute, effectively computable constant.
on the time and tape complexity of languages i we investigate the following: (1) the relationship between the classes of languages accepted by deterministic and nondeterministic polynomial time bounded turing machines; (2) the time and tape complexity of many predicates on the regular sets; (3) the relationship between the classes of languages accepted by deterministic or nondeterministic polynomial time bounded turing machines and the class of languages accepted by polynomial tape bounded turing machines; and (4) the complexity of many predicates about stack automata. we find several problems with nonpolynomial lower complexity bounds.
computational parallels between the regular and context-free languages this paper presents a complexity theory of formal languages. the main technique used is that of embedding &ldquo;&equil;{0,1}*&rdquo;, &ldquo;&equil;0*&rdquo;, and &ldquo;&equil;&fgr;&rdquo; into other linguistic predicates. in section 2, the undecidability of &ldquo;&equil;{0,1}*&rdquo; for cfl's is exploited to provide sufficient conditions for the undecidability of predicates on the cfl's. in section 3, the same techniques are applied to regular sets. predicates satisfying conditions similar to those of section 2 are shown to be hard, where how hard depends on the descriptors used to enumerate the regular sets. section 4 concentrates on the equivalence and containment problems for cfl's. for cfl's, regular sets, and linear cfl's, the complexity of determining equivalence to a fixed language is linked to whether the fixed language is finite, infinite but bounded, or unbounded. in section 5, the ability of cfg's to generate finite languages whose strings are exponential in the size of the grammar is used to obtain exponential lower bounds on several decidable problems for cfg's generating finite sets. in section 6, all nontrivial predicates for certain specific classes of languages are shown to be hard. in section 7, we show that a dpda can always be converted in polynomial time into an equivalent dpda that always halts. therefore the predicate &ldquo;&equil;{0,1}*&rdquo; is in p for dpda's, and embedding this problem into other predicates on the dpda's will not yield nonpolynomial lower bounds. in section 8, some of the preceding results are generalized to other families of languages.
on the complexity of grammar and related problems in [1] and [2] a complexity theory for formal languages and automata was developed. this theory implies most of the previously known results and yields many new results as well. here we develop an analogous theory for several classes of more practically motivated problems. two such classes, both closely related to formal language and automata theory, suggest themselves - grammar problems and program scheme problems. here, our primary emphasis is on grammar problems of interest in parsing and compiling. other problems considered include - (1) possible techniques for proving non-trivial lower complexity bounds for problems in p; (2) the relationship of the complexity of tree automaton equivalence, structural equivalence, and grammatical covering; and (3) the complexity of the equivalence problem for schemes. in each case we relate the computational complexity of a problem to its underlying combinatorial structure. the remainder of the paper is divided into four sections.
dichotomization, reachability, and the forbidden subgraph problem (extended abstract) we present several techniques for proving lower bounds that can be applied to problems about grammars, formal languages, program schemes, simple programming languages, and automata. these techniques include dichotomization, extensions of dichotomization to certain classes of relational problems, recursive analogues of the post correspondence problem, and the reachability problem. these techniques provide many new lower bounds and provide a unified framework for viewing much of the work on the complexity of problems about grammars, languages, schemes, and automata. we show how to prove the undecidability of a problem by efficiently reducing the membership problem for tms that always halt to it. we also introduce the forbidden subgraph problem.
the complexity of the equivalence problem for commutative semigroups and symmetric vector addition systems this paper shows that the equivalence problems for commutative semigroups and symmetric vector addition systems are decidable in space cnlogn for some fixed constant c, solving an open question by cardoza, lipton, mayr, and meyer. from the exponential-space completeness of the word problems, it follows that our upper bound is nearly optimal.
on the parallel evaluation of multivariate polynomials we prove that any multivariate polynomial p of degree d that can be computed with c(p) multiplications-divisions can be computed in o(log d.log c(p)) parallel steps and o(log d) parallel multiplicative steps.
the complexity of parallel evaluation of linear recurrence the concept of computers such as c.mmp and illiac iv is to achieve computational speed-up by performing several operations simultaneously with parallel processors. this type of computer organization is referred to as a parallel computer. in this paper, we prove upper bounds on speed-ups achievable by parallel computers for a particular problem, the solution of first order linear recurrences. we consider this problem because it is important in practice and also because it is simply stated so that we might obtain some insight into the nature of parallel computation by studying it.
an efficient algorithm for computing optimal desk merge patterns (extended abstract) in this paper, we present an algorithm which computes the optimal pattern for merging n equal size sorted sequences stored on a disk, in time o(log n) and constant space. the best previously known algorithm for solving this problem (knuth [4], schlumberger-vuillemin [5]) takes time o(n2) and space o(n).
a useful device for showing the solvability of some decision problems we look at a restricted model of a multihead pushdown automaton and use some of its properties to show the existence of algorithms for some decision problems concerning code sets and vector addition systems.
the complexity of the equivalence problem for straight-line programs we look at several classes of straight-line programs and show that the equivalence problem is either undecidable or computationally intractable for all but the trivial classes. for example, there is no algorithm to determine if an arbitrary program (with positive, negative, or zero integer inputs) using only constructs x &larr; 1, x &larr; x + y, x &larr; x/y (integer division) outputs 0 for all inputs. the result holds even if we consider only programs which compute total 0/1 - functions. for programs using constructs x &larr; 0, x &larr; c, x &larr; cx, x &larr; x/c, x &larr; x + y, x &larr; x &minus; y, skip l, if p(x) then skip l, and halt,1 the equivalence problem is decidable in [equation] time (&lgr; is a fixed positive constant and n is the maximum of the sizes of the programs). the bound cannot be reduced to a polynomial in n unless p &equil; np. in fact, we prove the following rather surprising result: the equivalence problem for programs with one input/output variable and one intermediate variable using only constructs x &larr; x + y and x &larr; x/2 is np-hard. we also show the decidability of the equivalence problem for a certain class of programs and use this result to prove the following: let in be the set of natural numbers and f be any total one-to-one function from in onto in &times; in. (f is called a pair generator. such functions are useful in recursive function and computability theory.) then f cannot be computed by any program using only constructs x &larr; 0, x &larr; c, x &larr; x + y, x &larr; x &minus; y, x &larr; x * y, x &larr; x/y, skip l, if p(x) then skip l, and halt.
quantifier elimination in the theory of an algebraically-closed field in this paper we develop a fast parallel procedure for deciding when a set of multivariate polynomials with coefficients in an arbitrary field k have a common algebraic solution. moreover, since the proposed algorithm is algebraic, it easily yields a procedure for quantifier elimination in the theory of an arbitrary algebraically closed field. more precisely, we show how to decide whether m polynomials in n variables, each of degree at most d, with coefficients in an arbitrary field k have a common zero in the algebraic closure of k, using sequential time (mn)&ogr;(n)d&ogr;(n)2), or parallel time &ogr;(n3 log3 d log m) with (mn)&ogr;(n)d&ogr;(n)2) processors, in the operations of the coefficient field k. using randomization, this may be improved to (mn)&ogr;(1)d&ogr;(n) time. in addition, the construction is used give a direct expspace algorithm for quantifier elimination in the theory of an algebraically-closed field, which runs in pspace or parallel polynomial time when restricted to formulas with a fixed number of alternations of quantifiers.
relational queries computable in polynomial time (extended abstract) query languages for relational databases have received considerable attention. in 1972 codd [cod72] showed that two natural mathematical languages for queries-&-mdash;one algebraic and the other a version of first order predicate calculus-&-mdash;had identical powers of expressibility. query languages which are as expressive as codd's relational calculus are sometimes called complete. this term is misleading, however, because many interesting queries are not expressible in -&-ldquo;complete-&-rdquo; languages. in this paper we show: theorem 2: the fixpoint hierarchy collapses at the first fixpoint level. that is, any query expressible with several applications of least fixpoint can already be expressed with one. we also show: theorem 1: let l be a query language consisting of relational calculus plus the least fixpoint operator. suppose that l contains a relation symbol for a total ordering relation on the domain (e.g. lexicographic ordering). then the queries expressible in l are exactly the queries computable in polynomial time. theorem 1 was discovered independantly by m. vardi [var82]. it gives a simple syntactic categorization of those queries which can be answered in polynomial time. of course queries requiring polynomial time in the size of the database are usually prohibitatively expensive. we also consider weaker languages for expressing less complex queries.
can every randomized algorithm be derandomized? among the most important modern algorithmic techniques is the use of random decisions. starting in the 1970's, many of the most significant results were randomized algorithms solving basic compuatational problems that had (to that time) resisted efficient deterministic computation. (ber72, ss79, rab80, sch80, zip79, akllr). in contrast, many of the most exciting recent work has been on derandomizing these same algorithms, coming up with efficient deterministic versions, e.g., (aks02, rein05). this raises the question, can such results be obtained for all randomized algorithms? will the remaining classical randomized algorithms be derandomized by similar techniques?clear but complicated answers to these questions have emerged from complexity-theoretic studies of randomized complexity classes (e.g., rp and bpp) and pseudo-random generators. these questions are inextricably linked to another basic problem in complexity: which functions require large circuits to compute?in this talk, we'll survey some results from the theory of derandomization. i'll stress connections to other questions, especially circuit complexity, explicit extractors, hardness amplification, and error-correcting codes. much of the talk is based on joint work with valentine kabanets and avi wigderson, but it will also include results by many other researchers.a priori, possibilities concerning the power of randomized algorithms include:randomization always helps speed up intractable problems, i.e., exp=bpp.the extent to which randomization helps is problem-specific. depending on the problem, it can reduce complexity by any amount from not at all to exponentially.true randomness is never needed, and random choices can always be simulated deterministically, i.e., p=bpp..either of the last two possibilities seem plausible, but most consider the first wildly implausible. however, while a strong version of the middle possibility has been ruled out, the implausible first one is still open. recent results indicate both that the last, p=bpp, is both very likely to be the case and very difficult to prove.more precisely: either no problem in e has strictly exponential circuit complexity or p=bpp. this seems to be strong evidence that, in fact, p=bpp, since otherwise circuits can always shortcut computation time for hard problems. (nw, bfnw, iw97, stv01, su01, uma02).either bpp=exp, or any problem in bpp has a deterministic sub-exponential time algorithm that works on almost all instances. in other words, either randomness solves every hard problem, or it does not help exponentially, except on rare instances. this rules out strong problem-dependence, since if randomization helps exponentially for many instances of some problem, we can conclude that it helps exponentially for all intractible problems. (iw98). if rp=p , then either the permanent problem requires super-polynomial algebraic circuits or there is a problem in nexp that has no polynomial-size boolean circuit. (ikw01, ki). that is, proving the last possibility requires one to prove a new circuit lower bound, and so is likely to be difficult. (moreover, we do not need the full hypothesis that p=rp to obtain the same conclusion: it actually suffices that the schwartz-zippel identity testing algorithm be derandomizable. thus, we will not be able to derandomize even the "classic" algorithms without proving circuit lower bounds.)all of these results use the hardness-vs-randomness paradigm introduced by yao (yao82, see also bm, levin): use a hard computational problem to define a small set of "pseudo-random" strings, that no limited adversary can distinguish from random. use these "pseudo-random" strings to replace the random choices in a probabilistic algorithm. the algorithm will not have enough time to distinguish the pseudo-random sequences from truly random ones, and so will behave the same as it would given random sequences.
limits on the provable consequences of one-way permutations we present strong evidence that the implication, &ldquo;if one-way permutations exist, then secure secret key agreement is possible&rdquo;, is not provable by standard techniques. since both sides of this implication are widely believed true in real life, to show that the implication is false requires a new model. we consider a world where all parties have access to a black box for a randomly selected permutation. being totally random, this permutation will be strongly one-way in a provable, information-theoretic way. we show that, if p = n p, no protocol for secret key agreement is secure in such a setting. thus, to prove that a secret key agreement protocol which uses a one-way permutation as a black box is secure is as hard as proving p &ne; n p. we also obtain, as a corollary, that there is an oracle relative to which the implication is false, i.e., there is a one-way permutation, yet secret-exchange is impossible. thus, no technique which relativizes can prove that secret exchange can be based on any one-way permutation. our results present a general framework for proving statements of the form, &ldquo;cryptographic application x is not likely possible based solely on complexity assumption y.&rdquo;
optimal approximations of the frequency moments of data streams. we give a 1-pass õ(m1-2⁄k)-space algorithm for computing the k-th frequency moment of a data stream for any real k > 2. together with the lower bounds of [1, 2, 4], this resolves the main problem left open by alon et al in 1996 [1]. our algorithm also works for streams with deletions and thus gives an õ(m 1-2⁄p) space algorithm for the lp difference problem for any p > 2. this essentially matches the known ω(m1-2⁄p-o(1)) lower bound of [12, 2]. finally the update time of our algorithms is õ(1).
two-dimensional alternating turing machines this paper introduces a two-dimensional alternating turing machine (2-atm) which is an extension of an alternating turing machine to two-dimensions. this paper also introduces a three-way two-dimensional alternating turing machine (tr2-atm) which is an alternating version of a three-way two-dimensional turing machine. we first investigate a relationship between the accepting powers of space-bounded 2-atm's (or tr2-atm's) and ordinary space-bounded two-dimensional turing machines (or three-way two-dimensional turing machines). we then introduce a simple, natural complexity measure for 2-atm's (or tr2-atm's), called -&-ldquo;leaf-size-&-rdquo;, and provides a spectrum of complexity classes based on leaf-size bounded computations. we finally investigate the recognizability of connected patterns by 2-atm's (or tr2-atm's).
black-box constructions for secure computation. it is well known that the secure computation of non-trivial functionalities in the setting of no honest majority requires computational assumptions. we study the way such computational assumptions are used. specifically, we ask whether the secure protocol can use the underlying primitive (e.g., one-way trapdoor permutation) in a black-box way, or must it be nonblack-box (by referring to the code that computes this primitive)? despite the fact that many general constructions of cryptographic schemes (e.g., cpa-secure encryption) refer to the underlying primitive in a black-box way only, there are some constructions that are inherently nonblack-box. indeed, all known constructions of protocols for general secure computation that are secure in the presence of a malicious adversary and without an honest majority use the underlying primitive in a nonblack-box way (requiring to prove in zero-knowledge statements that relate to the primitive).in this paper, we study whether such nonblack-box use is essential. we present protocols that use only black-box access to a family of (enhanced) trapdoor permutations or to a homomorphic public-key encryption scheme. the result is a protocol whose communication complexity is independent of the computational complexity of the underlying primitive (e.g., a trapdoor permutation) and whose computational complexity grows only linearly with that of the underlying primitive. this is the first protocol to exhibit these properties.
batch codes and their applications. a batch code encodes a string x into an m-tuple of strings, called buckets, such that each batch of k bits from x can be decoded by reading at most one (more generally, t) bits from each bucket. batch codes can be viewed as relaxing several combinatorial objects, including expanders and locally decodable codes. we initiate the study of these codes by presenting some constructions, connections with other problems, and lower bounds. we also demonstrate the usefulness of batch codes by presenting two types of applications: trading maximal load for storage in certain load-balancing scenarios, and amortizing the computational cost of private information retrieval (pir) and related cryptographic protocols.
on the sample size of k-restricted min-wise independent permutations and other k-wise distributions. an explicit study of min-wise independent permutation families, together with their variants --- k-restricted, approximate, etc. --- was initiated by broder, et al[4]. in this paper, we give a lower bound for the size of k-restricted min-wise independent permutation family. a family f of permutations on [0,n-1]=(0,1,...,n-1) is said to be k-restricted min-wise independent if for any subset x ⊆ [0,n-1] with |x| ≤ k and any x ∈ x, pr[min(π(x))=π(x)] = 1/|x|, when π is randomly chosen from f according to a probability distribution d on the family f. for the minimum size of a family of k-restricted min-wise independent permutations, upper bounds of o(nk) for any fixed k have been shown for uniform and biased probability distributions on f. we show that if a family f of permutations on [0,n-1] is k-restricted min-wise independent, then |f| ≥ m(n-1,k-1), where m(n,d) = ∑i=0d/2(ni) if d is even; m(n,d)= ∑i=0(d-1)/2(ni) + (n-1(d-1)/2) otherwise. the lower bound for the size of f still holds when we allow an arbitrary probability distribution on f. our proof technique is based on linear algebra methods, and can be regarded as a generalization of the result by alon, babai, and itai[1], i.e., if random variables x1,x2,...,xn: ω → (0,1) are k-wise independent and pr[xi=1] = pi is neither 0 nor 1, then |ω| ≥ m(n,k). by applying our proof technique, we also derive lower bounds for the sample size of the related notions, e.g., k-wise symmetrically independent distributions, k-rankwise independent permutation families, etc.
unique decomposability of shuffled strings: a formal treatment of asynchronous time-multiplexed communication a string x is said to be decomposed into strings yl,y2,...,yn if x is in y1 @@@@ y2 @@@@ ... @@@@ yn where @@@@ is the shuffle operator. we consider the problem of decomposing x into yl,y2,...,yn such that yl,y2,...,yn belong to predetermined languages l1,l2,...,ln, respectively. conditions under which such a decomposition is unique are presented as well as uniquely decomposable l1,l2,...,ln which are of practical significance from the viewpoint of time-multiplexed communication.
optimal evaluation of pairs of bilinear forms a large class of multiplication problems in arithmetic complexity can be viewed as the simultaneous evaluation of a set of bilinear forms. this class includes the multiplication of matrices, polynomials, quaternions, cayley and complex numbers. considering bilinear algorithms, the optimal number of non-scalar multiplications can be described as the rank of a three-tensor or as the smallest number of rank one matrices necessary to include a given set of matrices in their span. in this paper, we attack a rather large subclass of three-tensors, namely that of (p, q, 2) tensors, for arbitrary p and q, and solve it completely. the complexity of a general pair of bilinear forms is determined explicitly in terms of parameters related to kronecker's theory of pencils and to the theory of invariant polynomials. this reveals unexpected results and shows explicitly the dependence on the algebraic structure of the constants; we display, for example, a pair of n x n bilinear forms whose complexity is n + 1 over infinite fields and which, however, requires exactly n+[(n-1) &brvbar;k] multiplications over a finite field with cardinality k. another consequence of our results is that any set of m, p x q, bilinear forms require at most m/2(min(p+q/2, q+p/2)) multiplications over any field.
on the complexity of bilinear forms with commutativity we consider the problem of computing a set of bilinear forms in the case when the indeterminates commute. we develop lower bound techniques which seem to be more powerful than those already known in the literature for the commutative case. an unexpected result is the fact that duality theory does not hold in the commutative case; we prove that the multiplication of 2 &times; n by n &times; 2 matrices requires at least [27n/8] multiplications while it is possible to multiply 2 &times; 2 by 2 &times; n matrices using only 3n + 2 multiplications. we also settle the question of whether commutativity can reduce the number of multiplications by 1/2 by showing that this can never happen. on the other hand, we show that, over algebraically closed fields, the complexity of computing a pair of bilinear forms is the same whether or not commutativity is allowed. we feel that, in general, commutativity will have little effect whenever the constant set is an algebraically closed field.
time-space tradeoffs for some algebraic problems we study the time-space relationship of several algebraic problems such as matrix multiplication and matrix inversion. several results relating the algebraic properties of a set of functions to the structure of the graph of any straight-line program, that computes this set, are shown. some of our results are the following. multiplying m &times; n by n &times; p matrices with space s requires at least time t &ge; &ohgr;(mnp/s). inverting an n &times; n matrix with space s requires at least time t &ge; &ohgr;(n4/s).
a new greedy approach for facility location problems. we present a simple and natural greedy algorithm for the metric uncapacitated facility location problem achieving an approximation guarantee of 1.61. we use this algorithm to find better approximation algorithms for the capacitated facility location problem with soft capacities and for a common generalization of the k-median and facility location problems. we also prove a lower bound of 1+2/e on the approximability of the k-median problem. at the end, we present a discussion about the techniques we have used in the analysis of our algorithm, including a computer-aided method for proving bounds on the approximation factor.
equitable cost allocations via primal-dual-type algorithms. perhaps the strongest notion of truth-revealing in a cost sharing method is group strategyproofness. however, matters are not so clear-cut on fairness, and many different, sometimes even conflicting, notions of fairness have been proposed which have relevance in different situations. we present a large class of group strategyproof cost sharing methods, for submodular cost functions, satisfying a wide range of fairness criteria, thereby allowing the service provider to choose a method that best satisfies the notion of fairness that is most relevant to her application. our class includes the dutta-ray egalitarian method as a special case. it also includes a new cost sharing method, which we call the opportunity egalitarian method.
improved approximation schemes for scheduling unrelated parallel machines. we consider the problem of schedulingn independent jobs onm unrelated parallel machines where each job has to be processed by exactly one machine, processing jobj on machinei requiresp ijtime units, and the objective is to minimize the makespan, i.e., the maximum job completion time. focusing on the case whenm is fixed, we present for both preemptive and nonpreemptive variants of the problem fully polynomial approximation schemes whose running times depend only linearly onn. we also study an extension of the problem where processing jobj on machinei incurs a cost ofc ij , and thus there are two optimization criteria: makespan and cost. we show that, for any fixedm, there is a fully polynomial approximation scheme that, given valuest andc, computes for any fixed e &gt; 0 a schedule in0( n) time with makespan at most (1 + e) t and cost at most (1 + e) c, if there exists a schedule of makespant and costc.
on strip packing with rotations. we present an asymptotic fully polynomial time approximation scheme for two-dimensional strip packing with rotations. in this problem, a set of rectangles need to be packed into a rectangle (strip) of fixed width and minimum height, and these rectangles can be rotated by 90°. additionally, we present a simple asymptotic polynomial time approximation scheme, and give an improved algorithm for two-dimensional bin packing with rotations.
an optimal multi-writer snapshot algorithm. an m-component, n-process snapshot object is an abstraction of shared memory that consists of m words and allows up to n processes to concurrently execute the following two types of operations: write(i,v), which writes v into the ith word, and scan(), which returns the current values of all m locations [1, 3]. the snapshot problem is to design algorithms for the write and scan operations that meet two challenging requirements: (1) operations appear to be atomic, and (2) operations are wait-freefor any (m-component, n-process) snapshot algorithm, which runs on hardware that supports only word-sized objects, ω(1) and ω(m) are trivial lower bounds on the time complexity of write(i,v) and scan(), respectively. but, are these bounds tight?for a restricted version of the snapshot problem, known in the literature as the single-writer snapshot problem, riany, shavit and touitou [18] showed that the answer is yes: they designed an algorithm with o(1) and o(m) running times for the write(i,v) and scan() operations, respectively. (the single-writer snapshot problem assumes that (i) the number m of words of the snapshot object is equal to the number n of processes, and (ii) only the ith process may write into the ith snapshot word.this paper shows that the same (optimal) running times of o(1) for write(i,v) and o(m) for scan() are achievable for the general problem, known in the literature as the multiwriter snapshot problem. our algorithm requires hardware support for the cas (compare&swap) operation (in comparison, riany, shavit and touitou's algorithm requires hardware support for cas, fetch&inc, and fetch&dec operations).
cell-probe lower bounds for the partial match problem. given a database of n points in {0, 1)d, the partial match problem is: in response to a query x in {0,1,*}d, is there a database point y such that for every i whenever xi ≠ *, we have xi = yi. in this paper we show randomized lower bounds in the cell-probe model for this well-studied problem (analysis of associative retrieval algorithms, ph.d. thesis, stanford university, 1974; the art of computer programming; sorting and searching, addison-wesley, reading, ma, 1973; siam j. comput. 5(1) (1976) 19; j. comput. system sci. 57(1) (1998) 37; proceedings of the 31st annual acm symposium on theory of computing, 1999; proceedings of the 29th international colloquium on algorithms, logic, and programming, 1999).our lower bounds follow from a near-optimal asymmetric communication complexity lower bound for this problem. specifically, we show that either alice has to send ω(d/log n) bits or bob has to send ω(n1-o(1)) bits. when applied to the cell-probe model, it means that if the number of cells is restricted to be poly(n,d) where each cell is of size poly(log n,d), then ω(d/log2 n) probes are needed. this is an exponential improvement over the previously known lower bounds for this problem obtained by miltersen et al. (1998) and borodin et al. (1999).our lower bound also leads to new and improved lower bounds for related problems including a lower bound for the l∞ c-nearest neighbor problem for c < 3 and an improved communication complexity lower bound for the exact nearest neighbor problem.
online server allocation in a server farm via benefit task systems. a web content hosting service provider needs to dynamically allocate servers in a server farm to its customers' web sites. ideally, the allocation to a site should always suffice to handle its load. however, due to a limited number of servers and the overhead incurred in changing the allocation of a server from one site to another, the system may become overloaded. the problem faced by the web hosting service provider is how to allocate the available servers in the most profitable way. adding to the complexity of this problem is the fact that future loads of the sites are either unknown or known only for the very near future.in this paper we model this server allocation problem, and consider both its offline and online versions. we give a polynomial time algorithm for computing the optimal offline allocation. in the online setting, we show almost optimal algorithms (both deterministic and randomized) for any positive lookahead. the quality of the solution improves as the lookahead increases. we also consider several special cases of practical interest. finally, we present some experimental results using actual trace data that show that one of our online algorithm performs very close to optimal.interestingly, the online server allocation problem can be cast as a more general benefit task system that we define. our results extend to this task system, which captures also the benefit maximization variants of the k-server problem and the metrical task system problem. it follows that the benefit maximization variants of these problems are more tractable than their cost minimization variants.
two applications of information complexity. we show the following new lower bounds in two concrete complexity models:<ol>(1) in the two-party communication complexity model, we show that the tribes function on n inputs[6] has two-sided error randomized complexity ω(n), while its nondeterminstic complexity and co-nondeterministic complexity are both θ(√n). this separation between randomized and nondeterministic complexity is the best possible and it settles an open problem in kushilevitz and nisan[17], which was also posed by beame and lawry[5].(2) in the boolean decision tree model, we show that the recursive majority-of-three function on 3h inputs has randomized complexity ω((7/3)h). the deterministic complexity of this function is θ(3h), and the nondeterministic complexity is θ(2h). our lower bound on the randomized complexity is a substantial improvement over any lower bound for this problem that can be obtained via the techniques of saks and wigderson [23], heiman and wigderson[14], and heiman, newman, and wigderson[13]. recursive majority is an important function for which a class of natural algorithms known as directional algorithms does not achieve the best randomized decision tree upper bound.</ol.these lower bounds are obtained using generalizations of information complexity, which quantifies the minimum amount of information that will have to be revealed about the inputs by every correct algorithm in a given model of computation.
a polynomial-time approximation algorithm for the permanent of a matrix with non-negative entries. we present a fully-polynomial randomized approximation scheme for computing the permanent of an arbitrary matrix with non-negative entries.
universal approximations for tsp, steiner tree, and set cover. we introduce a notion of universality in the context of optimization problems with partial information. universality is a framework for dealing with uncertainty by guaranteeing a certain quality of goodness for all possible completions of the partial information set. universal variants of optimization problems can be defined that are both natural and well-motivated. we consider universal versions of three classical problems: tsp, steiner tree and set cover.we present a polynomial-time algorithm to find a universal tour on a given metric space over n vertices such that for any subset of the vertices, the sub-tour induced by the subset is within o(log4n/log log n) of an optimal tour for the subset. similarly, we show that given a metric space over n vertices and a root vertex, we can find a universal spanning tree such that for any subset of vertices containing the root, the sub-tree induced by the subset is within o(log4n/log log n) of an optimal steiner tree for the subset. our algorithms rely on a new notion of sparse partitions, that may be of independent interest. for the special case of doubling metrics, which includes both constant-dimensional euclidean and growth-restricted metrics, our algorithms achieve an o(log n) upper bound. we complement our results for the universal steiner tree problem with a lower bound of ω(log n/log log n) that holds even for n vertices on the plane. we also show that a slight generalization of the universal steiner tree problem is conp-hard and present nearly tight upper and lower bounds for a universal version of set cover.
two heads are better than two tapes. we show that a turing machine with two single-head one-dimensional tapes cannot recognize the set.
free groups and regular expressions group events are defined as regular events recognized by partial group automata. canonical forms are introduced for the class of regular expressions denoting group events. algorithms are presented to find a canonical form from a recognizing automaton, to find a recognizing automaton from a canonical form, and to find a canonical form from a regular expression denoting a simple group event. furthermore an algorithm is presented that decides whether or not two canonical forms denote the same event.
approximation algorithms for combinatorial problems simple, polynomial-time, heuristic algorithms for finding approximate solutions to various polynomial complete optimization problems are analyzed with respect to their worst case behavior, measured by the ratio of the worst solution value that can be chosen by the algorithm to the optimal value. for certain problems, such as a simple form of the knapsack problem and an optimization problem based on satisfiability testing, there are algorithms for which this ratio is bounded by a constant, independent of the problem size. for a number of set covering problems, simple algorithms yield worst case ratios which can grow with the log of the problem size. and for the problem of finding the maximum clique in a graph, no algorithm has been found for which the ratio does not grow at least as fast as 0(n&egr;), where n is the problem size and &egr;> 0 depends on the algorithm.
complete problems for deterministic polynomial time the results of cook and karp ([k], [c]) aroused considerable interest for at least two reasons. first, the answer to a long-standing open question which had seemed peculiar to automata theory&mdash;whether deterministic and nondeterministic polynomial-time-bounded turing machines are equivalent in power&mdash;was seen to be exactly equivalent to determining whether any of several familiar combinatorial problems can be solved by polynomial-time algorithms. second, the existence of complete problems for np1 made it possible to replace an entire class of questions by a question about a single representative.thus all of these combinatorial and automata-theoretic problems were essentially restatements of a single problem, such as: can satisfiability of a propositional formula be decided in polynomial time. the main purpose of this paper is to introduce several problems which are complete for p, the class of languages recognizable in deterministic polynomial time. any such language has the property that if it is recognizable in space logk(&bull;), then every language in p is so recognizable. thus a problem complete for p will serve to differentiate those sets in p which are not recognizable in logarithmic space from those which are, providing such differentiation is possible. a problem of this type was first presented by cook in [c2], concerning solvable path systems.
turing machines and the spectra of first-order formulas with equality in this paper we show that these similarities are not accidental - that spectra and context sensitive languages are closely related, and that their open questions are merely special cases of a family of open questions which relate to the difference (if any) between deterministic and non-deterministic time-or space-bounded turing machines.
independence results in computer science? (preliminary version) although there has been considerable additional work discussing limitations of formal proof techniques for computer science ([yo-73&77], [har-76], [har&ho-77], [haj-77&79], [go-79]), these papers show only very general consequences of incompleteness: the stated results hold for all sufficiently powerful formal systems for computer science. only the work of o'donnell and of lipton directly addresses the question of just how powerful formal axioms for computer science should be, and these two authors make rather radically different suggestions. we investigate this latter question: how powerful should a set of axioms be if it is to be adequate for computer science? in particular, in this paper we investigate the adequacy of the system of [li-78] as a formal system for computer science.
fast programs for initial segments and polynomial time computation in weak models of arithmetic (preliminary abstract) in this paper we study two alternative approaches for investigating whether np complete sets have fast algorithms. one is to ask whether there are long initial segments on which such sets are easily decidable by relatively short programs. the other approach is to ask whether there are weak fragments of arithmetic for which it is consistent to believe that p &equil; np. we show, perhaps surprisingly, that the two questions are equivalent: it is consistent to believe that p &equil; np in certain models of weak arithmetic theories iff it is true (in the standard model of computation) that there are infinitely many initial segments on which satisfiability is polynomially decidable by programs that are much shorter than the length of the initial segment.
derandomizing polynomial identity tests means proving circuit lower bounds. we show that derandomizing polynomial identity testing is essentially equivalent to proving arithmetic circuit lower bounds for nexp. more precisely, we prove that if one can test in polynomial time (or even nondeterministic subexponential time, infinitely often) whether a given arithmetic circuit over integers computes an identically zero polynomial, then either (i) nexp ⊄ p/poly or (ii) permanent is not computable by polynomial-size arithmetic circuits. we also prove a (partial) converse: if permanent requires superpolynomial-size arithmetic circuits, then one can test in subexponential time whether a given arithmetic circuit of polynomially bounded degree computes an identically zero polynomial.since polynomial identity testing is a corp problem, we obtain the following corollary: if rp = p (or even corp ⊆ ∩ε > 0 ntime(2nε), infinitely often), then nexp is not computable by polynomial-size arithmetic circuits. thus establishing that rp = corp or bpp = p would require proving superpolynomial lower bounds for boolean or arithmetic circuits. we also show that any derandomization of rnc would yield new circuit lower bounds for a language in nexp.we also prove unconditionally that nexprp does not have polynomial-size boolean or arithmetic circuits. finally, we show that nexp ⊄ p/poly if both bpp = p and low-degree testing is in p; here low-degree testing is the problem of checking whether a given boolean circuit computes a function that is close to some low-degree polynomial over a finite field.
entropy and sorting we reconsider the old problem of sorting under partial information, and give polynomial time algorithms for the following tasks. (1) given a partial order p, find (adaptively) a sequence of comparisons (questions of the form, &ldquo;is x < y?&rdquo;) which sorts (i.e. finds an unknown linear extension of) p using o(log(e(p))) comparisons in worst case (where e(p) is the number of linear extensions of p). (2) compute (on line) answers to any comparison algorithm for sorting a partial order p which force the algorithm to use &ohgr;(log(e(p))) comparisons. (3) given a partial order p of size n, estimate e(p) to within a factor exponential in n. (we give upper and lower bounds which differ by the factor nn/n!.) our approach, based on entropy of the comparability graph of p and convex minimization via the ellipsoid method, is completely different from earlier attempts to deal with these questions.
every poset has a good comparison we show that any finite partially ordered set p contains a pair of elements x and y such that the proportion of linear extensions of p in which x lies below y is between 3/11 and 8/11. a consequence is that the information-theoretic lower bound for sorting under partial information is tight up to a multiplicative constant. precisely: if x is a totally ordered set about which we are given some partial information, and if e(x) is the number of total orderings of x compatible with this partial information, then it is possible to sort x using no more than c log2e(x) comparisons (c@@@@2.17).
concurrent general composition of secure protocols in the timing model. in the setting of secure multiparty computation, a set of mutually distrustful parties wish to jointly compute some function of their input (i.e., they wish to securely carry out some distributed task). %the joint computation should be such that even in the stand-alone case, it has been shown that every efficient function can be securely computed. however, in the setting of concurrent composition, broad impossibility results have been proven for the case where there is no honest majority (or trusted setup).in this paper, we investigate the feasibility of obtaining secure multiparty protocols in a network where certain time bounds are assumed. specifically, the security of our protocols rely on the very reasonable assumption that local clocks do not "drift" too much (i.e., it is assumed that they proceed at approximately the same rate). we show that under this mild timing assumption, it is possible to securely compute any functionality under concurrent general composition (as long as messages from the arbitrary other protocols are delayed for a specified amount of time).
boosting in the presence of noise. boosting algorithms are procedures that ''boost'' low-accuracy weak learning algorithms to achieve arbitrarily high accuracy. over the past decade boosting has been widely used in practice and has become a major research topic in computational learning theory. in this paper we study boosting in the presence of random classification noise, giving both positive and negative results. we show that a modified version of a boosting algorithm due to mansour and mcallester (j. comput. system sci. 64(1) (2002) 103) can achieve accuracy arbitrarily close to the noise rate. we also give a matching lower bound by showing that no efficient black-box boosting algorithm can boost accuracy beyond the noise rate (assuming that one-way functions exist). finally, we consider a variant of the standard scenario for boosting in which the ''weak learner'' satisfies a slightly stronger condition than the usual weak learning guarantee. we give an efficient algorithm in this framework which can boost to arbitrarily high accuracy in the presence of classification noise.
a polynomial reduction from multivariate to bivariate integral polynomial factorization given an arbitrary but fixed integer r -&-ge; 3. we show that testing r-variate polynomials with integer coefficients for irreducibility is m-reducible in polynomial time of the total degree and the largest coefficient length to testing bivariate polynomials for irreducibility. factoring r-variate polynomials into irreducibles is polynomial time turing-reducible to completely factoring bivariate polynomials.
computing with polynomials given by straight-line programs i: greatest common divisors we develop algorithms on multivariate polynomials represented by straight-line programs for the greatest common divisor problem and conversion to sparse representation. our algorithms are in random polynomial-time for the usual coefficient fields and output with controllably high probability the correct result which for the gcd problem is a straight-line program determining the gcd of the inputs and for the conversion algorithm is the sparse representation of the input. the algorithms only require an a priori bound for the total degrees of the inputs. over rational numbers the conversion algorithm also needs a bound on the size of the polynomial coefficients. as specializations we get, e.g., random polynomial-time algorithms for computing the sparse gcd of polynomial determinants or for computing the sparse solution of a linear system whose coefficients are given by formulas.
single-factor hensel lifting and its application to the straight-line complexity of certain polynomials three theorems are presented that establish polynomial straight-line complexity for certain operations on polynomials given by straight-line programs of unbounded input degree. the first theorem shows how to compute a higher order partial derivative in a single variable. the other two theorems impose the degree of the output polynomial as a parameter of the length of the output program. first it is shown that if a straight-line program computes an arbitrary power of a multivariate polynomial, that polynomial also admits a polynomial bounded straight-line computation. second, any factor of a multivariate polynomial given by a division-free straight-line program with relatively prime co-factor also admits a straight-line computation of length polynomial in the input length and the degree of the factor. this result is based on a new hensel lifting process, one where only one factor image is lifted back to the original factor. as an application we get that the greatest common divisor of polynomials given by a division-free straight-line program has polynomial straight-line complexity in terms of the input length and its own degree.
fault-tolerant scheduling. we study fault-tolerant multiprocessor scheduling under the realistic assumption that the occurrence of faults cannot be predicted. the goal in these problems is to minimize the delay incurred by the jobs. since this is an online problem we use competitive analysis to evaluate possible algorithms. for the problems of minimizing the makespan and minimizing the average completion time (for static release times), we give nonclairvoyant algorithms (both deterministic and randomized) that have provably asymptotically optimal competitive ratios. the main tool used by these algorithms to combat faults is redundancy. we also show that randomization has the same effect as redundancy.
deterministic extractors for small-space sources. we give polynomial-time, deterministic randomness extractors for sources generated in small space, where we model space s sources on (0,1)n as sources generated by width 2s branching programs: for every constant δ>0, we can extract .99 δ n bits that are exponentially close to uniform (in variation distance) from space s sources of min-entropy δ n, where s=ω(n). in addition, assuming an efficient deterministic algorithm for finding large primes, there is a constant η > 0 such that for any δ>n-η, we can extract m=(δ-δ)n bits that are exponentially close to uniform from space s sources with min-entropy δ n, where s=ω(β3 n). previously, nothing was known for δ ≤ 1/2, even for space 0.our results are obtained by a reduction to a new class of sources that we call independent-symbol sources, which generalize both the well-studied models of independent sources and symbol-fixing sources. these sources consist of a string of n independent symbols over a d symbol alphabet with min-entropy k. we give deterministic extractors for such sources when k is as small as polylog(n), for small enough d.
improved algorithms for integer programming and related lattice problems the integer programming problem is: given m&times;n and m&times;l matrices a and b respectively of integers, find whether, there exists an all integer n&times;l vector x satisfying the m inequalities a&times;&le;b. in settling an important open problem, lenstra (1981) showed in an elegant way that when n, the number of dimensions is fixed, there is a polynomial-time algorithm to solve this problem. his algorithm achieves a running-time of 0(cn3&bull;p(length of data)) where p is some polynomial and c a constant independent of n. since such an algorithm has several important applications - cryptography (shamir (1982)), diophantine approximations (lagarias (1982)), coding theory (conway and sloane (1982), etc. it is important to improve the running time. we present an algorithm here that has a running time of 0(n9nl log l) where l is the length of the input. whereas lenstra's algorithm in the worst case reduces an n-dimensional problem to cn2&minus;(n&minus;) dimensional problems, our algorithm effectively reduces an n-dimensional problem to at most polynomially many (n&minus;1) dimensional problems, thus achieving our time bound. the algorithm we propose, first finds a &ldquo;more orthogonal&rdquo; basis for a lattice (see the next section for the definition of a lattice) than those of lenstra (1981) and lenstra, lenstra and lovasz (1982), but in time 0(ndn poly (length of input)). it then uses an enumeration technique to solve integer programming and related problems. while this paper presents mainly the theoretical improvements that can be made in the algorithms, we discuss in section 6 why in practice our estimates of running time may be overly pessimistic. the last part of the paper discusses some complexity issues. it is an interesting open problem as to whether finding the euclidean shortest non-zero vector of a given lattice is np-hard. (see lenstra (1981), van emde boas (1981) and lagarias (1982)).
alternation and the power of nondeterminism while nondeterminism is widely beleived to be more powerful than determinism in various contexts (the most famous being the conjecture that np strictly contains p), no proof of the added power of nondeterminism is available for any significant issue. the weaker conjecture (than np strictly contains p) that there is a language accepted by a nondeterministic linear time bounded multitape turing machine that cannot be accepted by a deterministic linear time bounded multi-tape tm still seems quite hard (paul 1982). the aim of this paper is to show how the existance of the polynomial-time hierarchy of meyer and stockmeyer(1972) and the related concept of alternation (chandra, kozen and stockmeyer(1981)) can be exploited to prove the power of nondeterminism over determinism in some contexts. it is hoped that this approach may be useful in proving stronger results.
the orbit problem is decidable the &ldquo;accessibility problem&rdquo; for linear sequential machines (harrison [7]) is the problem of deciding whether there is an input x that sends such a machine from a given state q1 to a given state q2. harrison [7] showed that this problem is reducible to the &ldquo;orbit problem:&rdquo; given a&egr;qn&times;n does there exist i&egr;n such that aix &equil;y.* we will call this the &ldquo;orbit problem&rdquo; because the question can be rephrased as: does y belong to the orbit of x under a where the &ldquo;orbit of x under a&rdquo; is the set {aix: i &equil; 0,1,2,...}. (a0 is the identity matrix i.) in harrison's original problem the elements of a,x, and y were members of an arbitrary &ldquo;computable&rdquo; field. in view of the lack of structure of such fields, we study only the rationals. shank [13] proves that the orbit problem is decidable for the rational case when n&equil;2. the current paper establishes that for the general rational case, the problem is decidable - and in fact polynomial-time decidable. we wish to give a brief idea of our approach to the problem.
implicit representation of graphs how to represent a graph in memory is a fundamental data structuring question. in the usual representations of an n-node graph, the names of the nodes (i.e. integers from 1 to n) betray nothing about the graph itself. indeed, the names (or labels) on the n nodes are just logn bit place holders to allow data on the edges to code for the structure of the graph. in our scenario, there is no such waste. by assigning &ogr;(logn) bit labels to the nodes, we completely code for the structure of the graph, so that given the labels of two nodes we can test if they are adjacent in time linear in the size of the labels. furthermore, given an arbitrary original labeling of the nodes, we can find structure coding labels (as above) that are no more than a small constant factor larger than the original labels. these notions are intimately related to vertex induced universal graphs of polynomial size. for example, we can label planar graphs with structure coding labels of size < 4logn. this implies the existence of a graph with n4 nodes that contains all n-node planar graphs as vertex induced subgraphs (it was not previously known that this class had polynomial sized universal graphs). the theorems on finite graphs extend to a theorem about the constrained labeling of infinite graphs.
learning with attribute costs. we study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for different attributes). our model assumes that the correct classification is given by some target function f from a class of functions cal f; most of our results discuss the ability to learn a clause (an or function of a subset of the variables) in various settings:offline: we are given both the function f and the distribution d that is used to generate an input x. the goal is to design a strategy to decide what attribute of x to observe next so as to minimize the expected evaluation cost of f(x). (in this setting there is no "learning" to be done but only an optimization problem to be solved; this problem to be np-hard and hence approximation algorithms are presented.)distributional online: we study two types of "learning" problems; one where the target function f is known to the learner but the distribution d is unknown (and the goal is to minimize the expected cost including the cost that stems from "learning" d), and the other where f is unknown (except that f∈cal f) but d is known (and the goal is to minimize the expected cost while limiting the prediction error involved in "learning" f).adversarial online: we are given f, however the inputs are selected adversarially. the goal is to compare the learner's cost to that of the best fixed evaluation order (i.e., we analyze the learner's performance by a competitive analysis).
dynamic rectangular intersection with priorities. we present efficient data structures to maintain dynamic set of rectangles, each with priority assigned to it, such that we can efficiently find the rectangle of maximum priority containing a query point. our data structures support insertions and deletions of rectangles. in one dimension, when rectangles are intervals, our most efficient data structure supports queries and insertions in o(log n) time, deletions in o(log n loglog n) time and requires linear space. when intervals are guaranteed to be nonoverlapping (but one can be nested within the other) we obtain a simpler data structure that supports all operations in o(log n) time.
meldable heaps and boolean union-find. in the classical meldable heap data type we maintain an item-disjoint collection of heaps under the operations find-min, insert, delete, decrease-key, and meld. in the usual definition decrease-key and delete get the item and the heap containing it as parameters. we consider the modified problem where decrease-key and delete get only the item but not the heap containing it. we show that for this problem one of the operations find-min, decrease-key, or meld must take non-constant time. this is in contrast with the original data type in which data structures supporting all these three operations in constant time are known (both in an amortized and a worst-case setting).to establish our results for meldable heaps we consider a weaker version of the union-find problem that is of independent interest, which we call boolean union-find. in the boolean union-find problem the find operation is a binary predicate that gets an item x and a set a and answers positively if and only if &khgr; &egr; a. we prove that the lower bounds which hold for union-find in the cell probe model hold for boolean union-find as well.we also suggest new heap data structures implementing the modified meldable heap data type that are based on redundant binary counters. our data structures have good worst-case bounds. the best of our data structures matches the worst-case lower bounds which we establish for the problem. the simplest of our data structures is an interesting generalization of binomial queues.
purely functional representations of catenable sorted lists. the power of purely functional programming in the construction of data structures has received much attention, not only because functional languages have many desirable properties, but because structures built purely functionally are automatically {\em fully persistent}: any and all versions of a structure can coexist indefinitely. recent results illustrate the surprising power of pure functionality. one such result was the development of a representation of double-ended queues with catenation that supports all operations, including catenation, in worst-case constant time~\cite{katar}. this paper is a continuation of our study of pure functionality, especially as it relates to persistence. for one purposes, a purely functional data structure is one built only with the lisp functions car, cons, cdr. we explore purely functional representations of sorted lists, implemented as finger search trees. we describe three implementations. the most efficient of these achieves logarithmic access, insertion, and deletion time, and double-logarithmic catenation time. it uses one level of structural bootstrapping to obtain its efficiency. the bounds for find, insert, and delete are the same as the best known bounds for an ephemeral implementation of these operations using finger search trees. the representations we present are the first that address the issues of persistence and pure functionality, and the first for which fast implementations of catenation and split are presented. they are simple to implement and could be efficient in practice, especially for applications that require worst-case time bounds or persistence.
monotone circuits for connectivity require super-logarithmic depth we prove that every monotone circuit which tests st-connectivity of an undirected graph on n nodes has depth &ohgr;(log2n). this implies a superpolynomial (n&ohgr;(log n)) lower bound on the size of any monotone formula for st-connectivity. the proof draws intuition from a new characterization of circuit depth in terms of communication complexity. it uses counting arguments and extremal set theory. within the same framework, we also give a very simple and intuitive proof of a depth analogue of a theorem of krapchenko concerning formula size lower bounds.
a randomized fully polynomial time approximation scheme for the all terminal network reliability problem. the classic all-terminal network reliability problem posits a graph, each of whose edges fails independently with some given probability. the goal is to determine the probability that the network becomes disconnected due to edge failures. this problem has obvious applications in the design of communication networks. since the problem is ${\sharp {\cal p}}$-complete and thus believed hard to solve exactly, a great deal of research has been devoted to estimating the failure probability. in this paper, we give a fully polynomial randomized approximation scheme that, given any n-vertex graph with specified failure probabilities, computes in time polynomial in n and $1/\epsilon$ an estimate for the failure probability that is accurate to within a relative error of $1\pm\epsilon$ with high probability. we also give a deterministic polynomial approximation scheme for the case of small failure probabilities. some extensions to evaluating probabilities of $k$-connectivity, strong connectivity in directed eulerian graphs and $r$-way disconnection, and to evaluating the tutte polynomial are also described. this version of the paper corrects several errata that appeared in the previous journal publication [d. r. karger, siam j. comput., 29 (1999), pp. 492--514].
minimum cuts in near-linear time. we significantly improve known time bounds for solving the minimum cut problem on undirected graphs. we use a "semiduality" between minimum cuts and maximum spanning tree packings combined with our previously developed random sampling techniques. we give a randomized (monte carlo) algorithm that finds a minimum cut in an m-edge, n-vertex graph with high probability in o(m log3 n) time. we also give a simpler randomized algorithm that finds all minimum cuts with high probability in o(m log3 n) time. this variant has an optimal rnc parallelization. both variants improve on the previous best time bound of o(n2 log3 n). other applications of the tree-packing approach are new, nearly tight bounds on the number of near-minimum cuts a graph may have and a new data structure for representing them in a space-efficient manner.
rounding algorithms for a geometric embedding of minimum multiway cut. given an undirected graph with edge costs and a subset ofk=3 nodes calledterminals, a multiway, ork-way, cut is a subset of the edges whose removal disconnects each terminal from the others. the multiway cut problem is to find a minimum-cost multiway cut. this problem is max-snp hard. recently, calinescu et al. (calinescu, g., h. karloff, y. rabani. 2000. an improved approximation algorithm for multiway cut.j. comput. system sci.60(3) 564--574) gave a novel geometric relaxation of the problem and a rounding scheme that produced a (3/2-1/ k)-approximation algorithm.in this paper, we study their geometric relaxation. in particular, we study the worst-case ratio between the value of the relaxation and the value of the minimum multicut (the so-called integrality gap of the relaxation). fork=3, we show the integrality gap is 12/11, giving tight upper and lower bounds. that is, we exhibit a family of graphs with integrality gaps arbitrarily close to 12/11 and give an algorithm that finds a cut of value 12/11 times the relaxation value. our lower bound shows that this is the best possible performance guarantee for any algorithm based purely on the value of the relaxation. our upper bound meets the lower bound and improves the factor of 7/6 shown by calinescu et al.for allk, we show that there exists a rounding scheme with performance ratio equal to the integrality gap, and we give explicit constructions of polynomial-time rounding schemes that lead to improved upper bounds. fork=4 and 5, our best upper bounds are based on computer-constructed rounding schemes (with computer proofs of correctness). for generalk we give an algorithm with performance ratio 1.3438-e k .our results were discovered with the help of computational experiments that we also describe here.
random sampling in residual graphs. consider an n-vertex, m-edge, undirected graph with maximum flow value v. we give a new &otilde;(m+nv)-time maximum flow algorithm based on finding augmenting paths in random samples of the edges of residual graphs. after assigning certain special sampling probabilities to edges in &otilde;(m) time, our algorithm is very simple: repeatedly find an augmenting path in a random sample of edges from the residual graph.
finding nearest neighbors in growth-restricted metrics. most research on nearest neighbor algorithms in the literature has been focused on the euclidean case. in many practical search problems however, the underlying metric is non-euclidean. nearest neighbor algorithms for general metric spaces are quite weak, which motivates a search for other classes of metric spaces that can be tractably searched.in this paper, we develop an efficient dynamic data structure for nearest neighbor queries in growth-constrained metrics. these metrics satisfy the property that for any point q and number r the ratio between numbers of points in balls of radius 2r and r is bounded by a constant. spaces of this kind may occur in networking applications, such as the internet or peer-to-peer networks, and vector quantization applications, where feature vectors fall into low-dimensional manifolds within high-dimensional vector spaces.
dynamic tcp acknowledgement and other stories about e/(e-1). we present the first optimal randomized online algorithms for the tcp acknowledgment problem [5] and the bahncard problem [7]. these problems are well-known to be generalizations of the classical online ski rental problem, however, they appeared to be harder. in this paper, we demonstrate that a number of online algorithms which have optimal competitive ratios of e/(e-1), including these, are fundamentally no more complex than ski rental. our results also suggest a clear paradigm for solving ski rental-like problems.
how good is the goemans-williamson max cut algorithm? the celebrated semidefinite programming algorithm for max cut introduced by goemans and williamson was known to have a performance ratio of at least $\alpha=\frac 2 {\pi} \min_{0
on earthmover distance, metric labeling, and 0-extension. we study the fundamental classification problems 0-extension and metric labeling. a generalization of multiway cut, 0-extension is closely related to partitioning problems in graph theory and to lipschitz extensions in banach spaces; its generalization metric labeling is motivated by applications in computer vision. researchers had proposed using earthmover metrics to get polynomial-time-solvable relaxations for these problems. a conjecture that has attracted much attention recently is that the integrality ratio for these relaxations is constant. we prove (1) that the integrality ratio of the earthmover relaxation for metric labeling is $\omega(\log k)$ (which is asymptotically tight), $k$ being the number of labels, whereas the best previous lower bound on the integrality ratio was only constant; (2) that the integrality ratio of the earthmover relaxation for 0-extension is $\omega(\sqrt{\log k})$, $k$ being the number of terminals (it was known to be $o((\log k)/\log\log k)$), whereas the best previous lower bound was only constant; (3) that for no $\epsilon>0$ is there a polynomial-time $o((\log n)^{1/4-\epsilon})$-approximation algorithm for 0-extension, $n$ being the number of vertices, unless np$\subseteq$dtime$(n^{\mathrm{poly}(\log n)})$, whereas the strongest inapproximability result known before was only max snp-hardness; and (4) that there is a polynomial-time approximation algorithm for 0-extension with performance ratio $o(\sqrt{\mathrm{diam}(d)})$, where $\mathrm{diam}(d)$ is the ratio of the largest to smallest nonzero distances in the terminal metric.
randomized algorithms and pseudorandom numbers randomized algorithms are analyzed as if unlimited amounts of perfect randomness were available, while pseudorandom number generation is usually studied from the perspective of cryptographic security. bach recently proposed studying the interaction between pseudorandom number generators and randomized algorithms. we follow bach's lead; we assume that a (small) random seed is available to start up a simple pseudorandom number generator which is then used for the randomized algorithm. we study randomized algorithms for (1) sorting; (2) selection; and (3) oblivious routing in networks.
a new polynomial-time algorithm for linear programming we present a new polynomial-time algorithm for linear programming. the running-time of this algorithm is o(n3-5l2), as compared to o(n6l2) for the ellipsoid algorithm. we prove that given a polytope p and a strictly interior point a &egr; p, there is a projective transformation of the space that maps p, a to p', a' having the following property. the ratio of the radius of the smallest sphere with center a', containing p' to the radius of the largest sphere with center a' contained in p' is o (n). the algorithm consists of repeated application of such projective transformations each followed by optimization over an inscribed sphere to create a sequence of points which converges to the optimal solution in polynomial-time.
some connections between nonuniform and uniform complexity classes it is well known that every set in p has small circuits [13]. adleman [1] has recently proved the stronger result that every set accepted in polynomial time by a randomized turing machine has small circuits. both these results are typical of the known relationships between uniform and nonuniform complexity bounds. they obtain a nonuniform upper bound as a consequence of a uniform upper bound. the central theme here is an attempt to explore the converse direction. that is, we wish to understand when nonuniform upper bounds can be used to obtain uniform upper bounds. in this section we will define our basic notion of nonuniform complexity. then we will show how to relate it to more common notions.
efficient pram simulation on a distributed memory machine we present a randomized simulation of a nlog log (n) log (n)-processor shared memory machine (dmm) with optimal expected delay o(log log (n)) per step of simulation. the time bound for the delay is guaranteed with overwhelming probability. the algorithm is based on hashing and uses a novel simulation scheme. the best previous simulations use a simpler scheme based on hashing and have much larger expected delay: &thgr;(log(n)/log log (n)) for the simulation of an n-processor pram on an n processor dmm, and &thgr;(log(n)) in the case where the simulation preserves the processor-time product.
a probabilistic analysis of multidimensional bin packing problems this paper gives probabilistic analyses of two kinds of multidimensional bin packing problems: vector packing and rectangle packing. in the vector packing problem each of the d dimensions can be interpreted as a resource. a given object i consumes aij units of the jth resource, and the objects packed in any given bin may not collectively consume more than one unit of any resource. subject to this constraint, the objects are to be packed into a minimum number of bins. the rectangle packing problem is more geometric in character. the ith object is a d-dimensional box whose jth side is of length aij, and the goal is to pack the objects into a minimum number of cubical boxes of side 1. we study these problems on the assumption that the aij are drawn independently from the uniform distribution over [0,1]. we study a vector packing heuristic called vpack that tries to place two objects in each bin and a rectangle packing heuristic called rpack that tries to pack one object into each of the 2d corners of each bin. we show that each of these heuristics tends to produce packings in which very little of the capacity of the bins is wasted. in the case of rectangle packing, we show that the results can be extended to a wide class of distributions of the piece sizes.
rapid identification of repeated patterns in strings, trees and arrays in this paper we look at a number of matching problems and devise general techniques for attacking such problems. in particular, we describe a strategy for constructing efficient algorithms for solving two types of matching problems. we use this strategy to develop explicit algorithms for these two problems applied to strings (where the patterns are substrings) and arrays (where the patterns are subarrays or blocks). we also develop algorithms for these and related problems for trees, where the patterns are subtrees. certain special cases of these algorithms are also discussed. although we do not claim that these algorithms are optimal, we analyze each algorithm to estimate its computational cost. this provides some basis for choosing which algorithm is most desirable in any given situation.
linear expected-time algorithms for connectivity problems (extended abstract) researchers in recent years have developed many graph algorithms that are fast in the worst case, but little work has been done on graph algorithms that are fast on the average. (exceptions include the work of angluin and valiant [1], karp [7], and schnorr [9].) in this paper we analyze the expected running time of four algorithms for solving graph connectivity problems. our goal is to exhibit algorithms whose expected time is within a constant factor of optimum and to shed light on the properties of random graphs. in section 2 we develop and analyze a simple algorithm that finds the connected components of an undirected graph with n vertices in o(n) expected time. in sections 3 and 4 we describe algorithms for finding the strong components of a directed graph and the blocks of an undirected graph in o(n) expected time. the time required for these three problems is &ohgr;(m) in the worst case, where m is the number of edges in the graph, since all edges must be examined; but our results show that only o(n) edges must be examined on the average.*@@@@ in section 5 we present an algorithm for finding a minimum weight spanning forest in an undirected graph with edge weights in o(m) expected time.
constructing a perfect matching is in random nc we show that the problem of constructing a perfect matching in a graph is in the complexity class random nc: i.e., the problem is solvable in polylog time by a randomized parallel algorithm using a polynomial-bounded number of processors. we also show that several related problems lie in random nc. these include: (i) constructing a perfect matching of maximum weight in a graph whose edge weights are given in unary notation; (ii) constructing a maximum-cardinality matching; (iii) constructing a matching covering a set of vertices of maximum weight in a graph whose vertex weights are given in binary; (iv) constructing a maximum s-t flow in a directed graph whose edge weights are given in unary.
are search and decision problems computationally equivalent? from the point of view of sequential polynomial time computation, the answer to the question in the title is 'yes'. the process of self-reducibility is a linear time turing (oracle) reduction from a given combinatorial search problem to an appropriately defined decision problem. however, from the point of view of fast parallel computation, the answer is not so clear. many of the sequential algorithms that were 'marked off' as being &ldquo;inherently sequential&rdquo; embed within them the self-reducibility process. can this inherently sequential process be parallelized? to study this problem, we define an abstract setting (namely that of an independence system) in which one, universal search problem captures all combinatorial search problems. we consider several natural decision and function oracles to which this search problem may be reduced. on the positive side, we give efficient probabilistic parallel reductions to these oracles. these reductions constitute a scheme for parallelizing search problems in case the oracles for these problems are themselves efficiently computable in parallel. we give examples of problems that did not yield to parallelism before, but can be parallelized using this scheme. on the negative side, we prove lower bounds on any determininistic parallel reductions to the same oracles. if p processors are used, the sequential (linear) running time cannot be enhanced by more than a factor of &ogr;(log p) and hence for any polynomial number of processors the problem remains inherently sequential. this proves that randomization can be exponentially more powerful than determinism in our model, and suggests that nc &ne; random nc. finally, we state some intriguing conjectures and suggest new directions of research in complexity theory that arise from this work.
a fast parallel algorithm for the maximal independent set problem a parallel algorithm is presented that accepts as input a graph g and produces a maximal independent set of vertices in g. on a p-ram without the concurrent write or concurrent read features, the algorithm executes in o((log n)4) time and uses o((n/(log n))3) processors, where n is the number of vertices in g. the algorithm has several novel features that may find other applications. these include the use of balanced incomplete block designs to replace random sampling by deterministic sampling, and the use of a &ldquo;dynamic pigeonhole principle&rdquo; that generalizes the conventional pigeonhole principle.
a randomized parallel branch-and-bound procedure we present a universal randomized method called local best-first search for parallelizing sequential branch-and-bound algorithms. the method executes on a message-passing multiprocessor system, and requires no global data structures or complex communication protocols. we show that, uniformly on all instances, the execution time of the method is unlikely to exceed a certain inherent lower bound by more than a constant factor.
polynomial bounds for vc dimension of sigmoidal neural networks. we introduce a new method for proving explicit upper bounds on the vc dimension of general functional basis networks, and prove as an application, for the first time, the vc dimension of analog neural networks with the sigmoid activation function $\sigma(y)=1/1+e^{-y}$ to be bounded by a quadratic polynomial in the number of programmable parameters.
a new solution to the critical section problem a classical problem in concurrent program control is to provide a mechanism whereby several processes running concurrently can gain exclusive control of a resource. for each process, the section of its program in which it accesses the resource is called its critical section, and the problem is called the critical section problem. a solution to the critical section problem guarantees that no more than one process can be in its critical section at any time. the solution presented here improves on previous solutions by allowing processes to enter their critical sections on a first-come first-served basis.
approximating the list-chromatic number and the chromatic number in minor-closed and odd-minor-closed classes of graphs. it is well-known (feige and kilian [24], håstad [39]) that approximating the chromatic number within a factor of n1-ε cannot be done in polynomial time for ε>0, unless corp = np. computing the list-chromatic number is much harder than determining the chromatic number. it is known that the problem of deciding if the list-chromatic number is k, where k ≥ 3, is π2p-complete [37].in this paper, we focus on minor-closed and odd-minor-closed families of graphs. in doing that, we may as well consider only graphs without kk-minors and graphs without odd kk-minors for a fixed value of k, respectively. our main results are that there is a polynomial time approximation algorithm for the list-chromatic number of graphs without kk-minors and there is a polynomial time approximation algorithm for the chromatic number of graphs without odd-kk-minors. their time complexity is o(n3) and o(n4), respectively. the algorithms have multiplicative error o(√log k) and additive error o(k), and the multiplicative error occurs only for graphs whose list-chromatic number and chromatic number are θ(k), respectively.let us recall that h has an odd complete minor of order l if there are l vertex disjoint trees in h such that every two of them are joined by an edge, and in addition, all the vertices of trees are two-colored in such a way that the edges within the trees are bichromatic, but the edges between trees are monochromatic. let us observe that the complete bipartite graph kn/2,n/2 contains a kk-minor for k ≤ n/2, but on the other hand, it does not contain an odd kk-minor for any k ≥ 3. odd k5-minor-free graphs are closely related to one field of discrete optimization which is finding conditions under which a given polyhedron has integer vertices, so that integer optimization problems can be solved as linear programs. see [33, 34, 64]. also, the odd version of the well-known hadwiger's conjecture has been considered, see [28].our main idea involves precoloring extension. this idea is used in many results; one example is thomassen's proof on his celebrated theorem on planar graphs [69].the best previously known approximation for the first result is a simple o(k √log k)-approximation following algorithm that guarantees a list-coloring with o(k √log k) colors for kk-minor-free graphs. this follows from results of kostochka [54, 53] and thomason [67, 68].the best previous approximation for the second result comes from the recent result of geelen et al. [28] who gave an o(k √log k)-approximation algorithm.we also relate our algorithm to the well-known conjecture of hadwiger [38] and its odd version. in fact, we give an o(n3) algorithm to decide whether or not a weaker version of hadwiger's conjecture is true. here, by a weaker version of hadwiger's conjecture, we mean a conjecture which says that any 27k-chromatic graph contains a kk-minor. also, we shall give an o(n2500k) algorithm for deciding whether or not any 2500k-chromatic graph contains an odd-kk-minor.let us mention that this presentation consists of two papers which are merged into this one. the first one consists of results concerning minor-closed classes of graphs by two current authors, and the other consists of results concerning odd-minor-closed classes of graphs by the first author.
efficient noise-tolerant learning from statistical queries. in this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of valiant and its variants. in order to identify the class of &ldquo;robust&rdquo; learning algorithms in the most general way, we formalize a new but related model of learning from statistical queries. intuitively, in this model a learning algorithm is forbidden to examine individual examples of the unknown target function, but is given acess to an oracle providing estimates of probabilities over the sample space of random examples.one of our main results shows that any class of functions learnable from statistical queries is in fact learnable with classification noise in valiant's model, with a noise rate approaching the information-theoretic barrier of 1/2. we then demonstrate the generality of the statistical query model, showing that practically every class learnable in valiant's model and its variants can also be learned in the new model (and thus can be learned in the presence of noise). a notable exception to this statement is the class of parity functions, which we prove is not learnable from statistical queries, and for which no noise-tolerant algorithm is known.
combining dimensionality and rate of growth arguments for establishing lower bounds on the number of multiplications in this paper we describe a new method for establishing lower bounds for the number of multiplications and divisions required to compute rational functions. we shall start by reminding the reader of some standard notations.
efficient program transformations for resilient parallel computation via randomization (preliminary version) in this paper, we address the problem of automatically transforming arbitrary programs written for an ideal parallel machine to run on a completely asynchronous machine. we present a transformation which can be applied to an ideal program such that the resulting program's execution on an asynchronous machine is work and space efficient, relative to the ideal program from which it is derived. above all, the transformation will guarantee that the ideal program will execute in a continually progressive manner on the asynchronous machine; these instructions are not universal. furthermore, the individual processors can get delayed for arbitrary amounts of time while executing any instruction. in contrast, previous work relied either on the asynchronous machine having universal read-modify-write instructions as primitives, or on limited asynchrony by restricting the relative speeds of the processors.
approximability and nonapproximability results for minimizing total flow time on a single machine. we consider the problem of scheduling n jobs that are released over time on a single machine in order to minimize the total flow time. this problem is well known to be np-complete, and the best polynomial-time approximation algorithms constructed so far had (more or less trivial) worst-case performance guarantees of o(n). in this paper, we present one positive and one negative result on polynomial-time approximations for the minimum total flow time problem: the positive result is the first approximation algorithm with a sublinear worst-case performance guarantee of $o(\sqrt{n})$. this algorithm is based on resolving the preemptions of the corresponding optimum preemptive schedule. the performance guarantee of our approximation algorithm is not far from best possible, as our second, negative result demonstrates: unless p=np, no polynomial-time approximation algorithm for minimum total flow time can have a worst-case performance guarantee of $o(n^{1/2-\eps})$ for any $\eps>0$.
spectral partitioning, eigenvalue bounds, and circle packings for graphs of bounded genus. in this paper, we address two long-standing questions about finding good separators in graphs of bounded genus and degree: 1. it is a classical result of gilbert, hutchinson, and tarjan [j. algorithms, 5 (1984), pp. 391-407] that one can find asymptotically optimal separators on these graphs if given both the graph and an embedding of it onto a low genus surface. does there exist a simple, efficient algorithm to find these separators, given only the graph and not the embedding? 2. in practice, spectral partitioning heuristics work extremely well on these graphs. is there a theoretical reason why this should be the case? we resolve these two questions by showing that a simple spectral algorithm finds separators of cut ratio $o(\sqrt{\smash[b]{g/n}})$ and vertex bisectors of size $o(\sqrt{gn})$ in these graphs, both of which are optimal. as our main technical lemma, we prove an $o(g/n)$ bound on the second smallest eigenvalue of the laplacian of such graphs and show that this is tight, thereby resolving a conjecture of spielman and teng. while this lemma is essentially combinatorial in nature, its proof comes from continuous mathematics, drawing on the theory of circle packings and the geometry of compact riemann surfaces.
a randomized polynomial-time simplex algorithm for linear programming. we present the first randomized polynomial-time simplex algorithm for linear programming. like the other known polynomial-time algorithms for linear programming, its running time depends polynomially on the number of bits used to represent its input.we begin by reducing the input linear program to a special form in which we merely need to certify boundedness. as boundedness does not depend upon the right-hand-side vector, we run the shadow-vertex simplex method with a random right-hand-side vector. thus, we do not need to bound the diameter of the original polytope.our analysis rests on a geometric statement of independent interest: given a polytope a x ≤ b in isotropic position, if one makes a polynomially small perturbation to b then the number of edges of the projection of the perturbed polytope onto a random 2-dimensional subspace is expected to be polynomial.
on the parallel complexity of computing a maximal independent set in a hypergraph a maximal independent set in a hypergraph is a subset of vertices that is maximal with respect to the property of not containing any edge of the hypergraph. we show that an algorithm proposed by beame and luby is in randomized nc for hypergraphs in which the maximum edge size is bounded by a constant. to prove this, we bound the upper tail of sums of dependent random variables defined on the edges of a hypergraph. these bounds may be viewed as extensions of bounds on the tail of the binomial distribution. we derandomize this algorithm to obtain the first sublinear time deterministic algorithm for hypergraphs with edges of size o(1). the algorithm exhibits the following time-processor tradeoff: it can be made to run in time o(n&egr;) with no(1/&egr;) processors for a hypergraph on n vertices, for any &egr; &ge; 2d+1&bull; (log log n)/(log n); here d = o(1) denotes the maximum size of an edge in h. in particular, for any constant &egr; > o, we have an algorithm running in time o(n&egr;) on a polynomial number of processors, and we have an algorithm running in time (log n)o(1) on no(log n/log log n) processors.
spatial gossip and resource location protocols. the dynamic behavior of a network in which information is changing continuously over time requires robust and efficient mechanisms for keeping nodes updated about new information. gossip protocols are mechanisms for this task in which nodes communicate with one another according to some underlying deterministic or randomized algorithm, exchanging information in each communication step. in a variety of contexts, the use of randomization to propagate information has been found to provide better reliability and scalability than more regimented deterministic approaches.in many settings --- consider a network of sensors, or a cluster of distributed computing hosts --- new information is generated at individual nodes, and is most &ldquo;interesting&rdquo; to nodes that are nearby. thus, we propose distance-based propagation bounds as a performance measure for gossip algorithms: a node at distance d from the origin of a new piece of information should be able to learn about this information with a delay that grows slowly with d, and is independent of the size of the network.for nodes arranged with uniform density in euclidean space, we present natural gossip algorithms that satisfy such a guarantee: new information is spread to nodes at distance \dist, with high probability, in o(\log^{1 + \ve} \dist) time steps. such a bound combines the desirable qualitative features of uniform gossip, in which information is spread with a delay that is logarithmic in the full network size, and deterministic flooding, in which information is spread with a delay that is linear in the distance and independent of the network size. our algorithms and their analysis resolve a conjecture of demers et al. we show an application of our gossip algorithms to a basic resource location problem, in which nodes seek to rapidly
connectivity and inference problems for temporal networks. many network problems are based on fundamental relationships involving time. consider, for example, the problems of modeling the flow of information through a distributed network, studying the spread of a disease through a population, or analyzing the reachability properties of an airline timetable. in such settings, a natural model is that of a graph in which each edge is annotated with a time label specifying the time at which its endpoints "communicated." we will call such a graph a temporal network. to model the notion that information in such a network "flows" only on paths whose labels respect the ordering of time, we call a path time-respecting if the time labels on its edges are non-decreasing. the central motivation for our work is the following question: how do the basic combinatorial and algorithmic properties of graphs change when we impose this additional temporal condition? the notion of a path is intrinsic to many of the most fundamental algorithmic problems on graphs; spanning trees, connectivity, flows, and cuts are some examples. when we focus on time-respecting paths in place of arbitrary paths, many of these problems acquire a character that is different from the traditional setting, but very rich in its own right. we provide results on two types of problems for temporal networks. first, we consider connectivity problems, in which we seek disjoint time-respecting paths between pairs of nodes. the natural analogue of menger's theorem for node-disjoint paths fails in general for time-respecting paths; we give a non-trivial characterization of those graphs for which the theorem does hold in terms of an excluded subdivision theorem, and provide a polynomial-time algorithm for connectivity on this class of graphs. (the problem on general graphs is np-complete.) we then define and study the class of inference problems, in which we seek to reconstruct a partially specified time labeling of a network in a manner consistent with an observed history of information flow.
a decentralized algorithm for spectral analysis. in many large network settings, such as computer networks, social networks, or hyperlinked text documents, much information can be obtained from the network's spectral properties. however, traditional centralized approaches for computing eigenvectors struggle with at least two obstacles: the data may be difficult to obtain (both due to technical reasons and because of privacy concerns), and the sheer size of the networks makes the computation expensive. a decentralized, distributed algorithm addresses both of these obstacles: it utilizes the computational power of all nodes in the network and their ability to communicate, thus speeding up the computation with the network size. and as each node knows its incident edges, the data collection problem is avoided as well.our main result is a simple decentralized algorithm for computing the top k eigenvectors of a symmetric weighted adjacency matrix, and a proof that it converges essentially in o(τmixlog2 n) rounds of communication and computation, where τmix is the mixing time of a random walk on the network. an additional contribution of our work is a decentralized way of actually detecting convergence, and diagnosing the current error. our protocol scales well, in that the amount of computation performed at any node in any one round, and the sizes of messages sent, depend polynomially on k, but not on the (typically much larger) number n of nodes.
verifying partial orders we present a randomized algorithm which uses o(n(log n)1/3) expected comparisons to verify that a given partial order holds on n elements from an unknown total order.
low distortion maps between point sets. we initiate the study of the minimum distortion problem: given as input two n-point metric spaces, find a bijection between them with minimum distortion. this is an abstraction of certain geometric problems in shape and image matching, and is also a natural variation and extension of the fundamental problems of graph isomorphism and bandwidth. our focus is on algorithms that find an optimal (or near-optimal) bijection when the distortion is fairly small. we present a polynomial time algorithm that finds an optimal bijection between two line metrics, provided the distortion is less than 3+2√2. we also give a parameterized polynomial time algorithm that finds an optimal bijection between an arbitrary unweighted graph metric and a bounded-degree tree metric.
exponential lower bound for 2-query locally decodable codes via a quantum argument. a locally decodable code (ldc) encodes n-bit strings x in m-bit codewords c(x) in such a way that one can recover any bit xi from a corrupted codeword by querying only a few bits of that word. we use a quantum argument to prove that ldcs with 2 classical queries require exponential length: m = 2ω(n). previously, this was known only for linear codes (goldreich et al., in: proceedings of 17th ieee conference on computation complexity, 2002, pp. 175-183). the proof proceeds by showing that a 2-query ldc can be decoded with a single quantum query, when defined in an appropriate sense. it goes on to establish an exponential lower bound on any 'l-query locally quantum-decodable code'. we extend our lower bounds to non-binary alphabets and also somewhat improve the polynomial lower bounds by katz and trevisan for ldcs with more than 2 queries. furthermore, we show that q quantum queries allow more succinct ldcs than the best known ldcs with q classical queries. finally, we give new classical lower bounds and quantum upper bounds for the setting of private information retrieval. in particular, we exhibit a quantum 2-server private information retrieval (pir) scheme with o(n3/10) qubits of communication, beating the o(n1/3) bits of communication of the best known classical 2-server pir.
buffer overflow management in qos switches. we consider two types of buffering policies that are used in network switches supporting quality of service (qos). in the fifo type, packets must be transmitted in the order in which they arrive; the constraint in this case is the limited buffer space. in the bounded-delay type, each packet has a maximum delay time by which it must be transmitted, or otherwise it is lost. we study the case of overloads resulting in packet loss. in our model, each packet has an intrinsic value, and the goal is to maximize the total value of transmitted packets.our main contribution is a thorough investigation of some natural greedy algorithms in various models. for the fifo model we prove tight bounds on the competitive ratio of the greedy algorithm that discards packets with the lowest value when an overflow occurs. we also prove that the greedy algorithm that drops the earliest packets among all low-value packets is the best greedy algorithm. this algorithm can be as much as 1.5 times better than the tail-drop greedy policy, which drops the latest lowest-value packets.in the bounded-delay model we show that the competitive ratio of any on-line algorithm for a uniform bounded-delay buffer is bounded away from 1, independent of the delay size. we analyze the greedy algorithm in the general case and in three special cases: delay bound 2, link bandwidth 1, and only two possible packet values.finally, we consider the off-line scenario. we give efficient optimal algorithms and study the relation between the bounded-delay and fifo models in this case.
graph partitioning using single commodity flows. we show that the sparsest cut in graphs with n vertices and m edges can be approximated within o(log2 n) factor in &otilde;(m + n3/2) time using polylogarithmic single commodity max-flow computations. previous algorithms are based on multicommodity flows that take time &otilde;(m + n2). our algorithm iteratively employs max-flow computations to embed an expander flow, thus providing a certificate of expansion. our technique can also be extended to yield an o(log2 n)-(pseudo-) approximation algorithm for the edge-separator problem with a similar running time.
on broadcast disk paging. broadcast disks are an emerging paradigm for massive data dissemination. in a broadcast disk, data is divided into n equal-sized pages, and pages are broadcast in a round-robin fashion by a server. broadcast disks are effective because many clients can simultaneously retrieve any transmitted data. paging is used by the clients to improve performance, much as in virtual memory systems. however, paging on broadcast disks differs from virtual memory paging in at least two fundamental aspects: a page fault in the broadcast disk model has a variable cost that depends on the requested page as well as the current state of the broadcast. prefetching is both natural and a provably essential mechanism for achieving significantly better competitive ratios in broadcast disk paging. in this paper, we design a deterministic algorithm that uses prefetching to achieve an o(n log k) competitive ratio for the broadcast disk paging problem, where k denotes the size of the client's cache. we also show a matching lower bound of $\omega(n\log k)$ that applies even when the adversary is not allowed to use prefetching. in contrast, we show that when prefetching is not allowed, no deterministic online algorithm can achieve a competitive ratio better than $\omega(nk)$. moreover, we show a lower bound of $\omega(n \log k)$ on the competitive ratio achievable by any nonprefetching randomized algorithm against an oblivious adversary. these lower bounds are trivially matched from above by known results about deterministic and randomized marking algorithms for paging. an interpretation of our results is that in the broadcast disk paging, prefetching is a perfect substitute for randomization.
hardness results for approximate hypergraph coloring. (math) guruswami et al [6] show the hardness of coloring 2-colorable 4-uniform hypergraphs on n vertices with &omega;(log log n \over log log log n}) colors assuming np $\not\subseteq$ dtime(no log log n)). we obtain a stronger hardness result for approximate coloring of p-colorable 4-uniform hypergraphs for any fixed integer p &rhoe; 7. we prove that there exists an absolute constant c &rho; 0 such that for every fixed integer p &rhoe; 7, it is hard to color a p-colorable 4-uniform hypergraph with (log n)cp colors assuming np $\not \subseteq$ dtime(2(log n)o(1)).this work builds on the idea of "covering complexity" of probabilistically checkable proof systems (pcps) developed in [6] and we introduce some new techniques as well. firstly, we define a new code which we call the split code. this is a variation of the long code, but much shorter in length and it reduces the proof size significantly. split codes enable us to exploit the special structure of the "outer pcp verifier" constructed via raz's parallel repetition theorem [18]. secondly, we make a novel use of the split codes over the domain gf(p) for a prime p. working over non-boolean domain in fact makes our proof technically simpler than the proof of guruswami at al [6].
on the power of unique 2-prover 1-round games. a 2-prover game is called unique if the answer of one prover uniquely determines the answer of the second prover and vice versa (we implicitly assume games to be one round games). the value of a 2-prover game is the maximum acceptance probability of the verifier over all the prover strategies. we make the following conjecture regarding the power of unique 2-prover games, which we call the unique games conjecture: the unique games conjecture: for arbitrarily small constants \zeta, \delta > 0, there exists a constant k = k(\zeta,\delta) such that it is np-hard to determine whether a unique 2-prover game with answers from a domain of size k has value at least 1-\zeta or at most \delta.we show that a positive resolution of this conjecture would imply the following hardness results: (1) for any 1/2 0, it is np-hard to distinguish between the instances of the problem 2-linear-equations mod 2 where either there exists an assignment that satisfies 1-\epsilon fraction of equations or no assignment can satisfy more than 1-\epsilon^t fraction of equations. as a corollary of this result, it is np-hard to approximate the min-2cnf-deletion problem within any constant factor. (2) for the constraint satisfaction problem where every constraint is the predicate not-all-equal(a,b,c) with a,b,c being ternary variables, it is np-hard to distinguish between the instances where either there exists an assignment that satisfies 1-\epsilon fraction of the constraints or no assignment satisfies more than 8/9 + \epsilon fraction of the constraints for an arbitrarily small constant \epsilon > 0. this problem is relavant for showing hardness of coloring 3-colorable 3-uniform hypergraphs. we also show that a variation of the unique games conjecture implies that for arbitrarily small constant \delta > 0, it is hard to find an independent set of size (\delta n) in a graph that is guaranteed to have an independent set of size \omega(n).the main idea in all the above results is to use the 2-prover game given by the unique games conjecture as an "outer verifier" and build new probabilistically checkable proof systems (pcps) on top of it. the uniqueness property plays a crucial role in the analysis of these pcps.in light of such interesting consequences, we think it is an important open problem to prove (or disprove) the unique games conjecture. we also present a semi-definite programming based algorithm for finding reasonable prover strategies for a unique 2-prover game. given a unique 2-prover game with value 1-\zeta and answers from a domain of size k, this algorithm finds prover strategies that make the verifier accept with probability 1-o(k^2 \zeta^{1/5} \sqrt{\log(1/\zeta)}). this result shows that the domain size k = k(\zeta, \delta) must be sufficiently large if the unique games conjecture is true.
low degree spanning trees of small weight. given $n$ points in the plane, the degree-$k$ spanning-tree problem asks for a spanning tree of minimum weight in which the degree of each vertex is at most $k$. this paper addresses the problem of computing low-weight degree-$k$ spanning trees for $k>2$. it is shown that for an arbitrary collection of $n$ points in the plane, there exists a spanning tree of degree 3 whose weight is at most 1.5 times the weight of a minimum spanning tree. it is shown that there exists a spanning tree of degree 4 whose weight is at most 1.25 times the weight of a minimum spanning tree. these results solve open problems posed by papadimitriou and vazirani. moreover, if a minimum spanning tree is given as part of the input, the trees can be computed in $o(n)$ time. the results are generalized to points in higher dimensions. it is shown that for any $d \ge 3$, an arbitrary collection of points in $\re^d$ contains a spanning tree of degree 3 whose weight is at most 5/3 times the weight of a minimum spanning tree. this is the first paper that achieves factors better than 2 for these problems.
biconnectivity approximations and graph carvings a spanning tree in a graph is the smallest connected spanning subgraph. given a graph, how does one find the smallest (i.e., least number of edges) 2-connected spanning subgraph (connectivity refers to both edge and vertex connectivity, if not specified)? unfortunately, the problem is known to be np-hard. we consider the problem of finding an approximation to the smallest 2-connected subgraph, by an efficient algorithm. for 2-edge connectivity our algorithm guarantees a solution that is no more than 3/2 times the optimal. for 2-vertex connectivity our algorithm guarantees a solution that is no more than 5/3 times the optimal. the previous best approximation factor is 2 for each of these problems. the new algorithms (and their analyses) depend upon a structure called a carving of a graph, which is of independent interest. we show that approximating the optimal solution to within an additive constant is np-hard as well. we also consider the case where the graph has edge weights. we show that an approximation factor of 2 is possible in polynomial time for finding a k-edge connected spanning subgraph. this improves an approximation factor of 3 for k=2 due to [fj81], and extends it for any k (with an increased running time though).
founding cryptography on oblivious transfer suppose your netmail is being erratically censored by captain yossarian. whenever you send a message, he censors each bit of the message with probability 1/2, replacing each censored bit by some reserved character. well versed in such concepts as redundancy, this is no real problem to you. the question is, can it actually be turned around and used to your advantage? we answer this question strongly in the affirmative. we show that this protocol, more commonly known as oblivious transfer, can be used to simulate a more sophisticated protocol, known as oblivious circuit evaluation([y]). we also show that with such a communication channel, one can have completely noninteractive zero-knowledge proofs of statements in np. these results do not use any complexity-theoretic assumptions. we can show that they have applications to a variety of models in which oblivious transfer can be done.
a note on efficient zero-knowledge proofs and arguments (extended abstract) in this note, we present new zero-knowledge interactive proofs and arguments for languages in np. to show that x &egr; l, with an error probability of at most 2-k, our zero-knowledge proof system requires o(|x|c1)+o(lgc2|x|)k ideal bit commitments, where c1 and c2 depend only on l. this construction is the first in the ideal bit commitment model that achieves large values of k more efficiently than by running k independent iterations of the base interactive proof system. under suitable complexity assumptions, we exhibit zero knowledge arguments that require o(lgc|x|kl bits of communication, where c depends only on l, and l is the security parameter for the prover. this is the first construction in which the total amount of communication can be less than that needed to transmit the np witness. our protocols are based on efficiently checkable proofs for np[4].
concurrent and resettable zero-knowledge in poly-loalgorithm rounds. a proof is concurrent zero-knowledge if it remains zero-knowledge when many copies of the proof are run in an asynchronous environment, such as the internet. richardson and kilian have shown that there exists a concurrent zero-knowledge proof for any language in np, but with round complexity polynomial in the maximum number of concurrent proofs. in this paper, we present a concurrent zero-knowledge proof for all languages in np with a poly-logarithmic round complexity: specifically, &ohgr;(log^2 k) rounds given at most k concurrent proofs. finally, we show that a simple modification of our proof is a resettable zero-knowledge proof for np, with &ohgr;(log^2 k) rounds; previously known protocols required a polynomial number of rounds.
probabilistically checkable proofs with zero knowledge. we construct pcps with strong zero-knowledge properties. first, we construct polynomially bounded (in size) pcp''s for {\sf np} which can be checked using poly-logarithmic queries, with polynomially low error, yet are statistical zero-knowledge against an adversary that makes $u$ arbitrary queries, where $u$ can be set to any polynomial. second, we construct pcps for {\sf{nexptime}} that can be checked using polynomially many queries, yet are statistically zero-knowledge against any polynomially bounded adversary. these pcps are exponential in size and have exponentially low error. previously, it was only known how to construct zero-knowledge pcps with a constant error probability. \par in the course of constructing these pcp''s we abstract a tool we call {\em locking systems}. we provide the definition and also a locking system with very efficient parameters. this mechanism may be useful in other settings as well.
digital disks and a digital compactness measure an o(n2) time algorithm is presented that determines whether or not a given convex digital region is a digital disk. a new compactness measure for digital regions is introduced, and an algorithm to evaluate the compactness measure of convex digital regions is also presented.
digital straightness and convexity (extended abstract) we define straightness and convexity of regions in a digital picture. then it is shown that a few important properties satisfied by convex (euclidean) regions are also satisfied by convex digital regions. we extend the definition of digital convexity of regions to digital solids. efficient algorithms are presented that determine whether or not a digital region is convex, a digital arc is a digital straight line segment and a digital solid is convex.
generating random regular graphs. random regular graphs play a central role in combinatorics and theoretical computer science. in this paper, we analyze a simple algorithm introduced by steger and wormald [10] and prove that it produces an asymptotically uniform random regular graph in a polynomial time. precisely, for fixed d and n with d = o(n1/3&#x2212;&#x03b5;), it is shown that the algorithm generates an asymptotically uniform random d-regular graph on n vertices in time o(nd2). this confirms a conjecture of wormald. the key ingredient in the proof is a recently developed concentration inequality by the second author. the algorithm works for relatively large d in practical (quadratic) time and can be used to derive many properties of uniform random regular graphs.
an algebraic system for process structuring and interprocess communication an extension of regular expressions is introduced to represent the activities of synchronizing concurrent processes. a communication link is defined as an automaton (infinite) with one-to-one partial transformations, and communication protocol as an assignment of events to actions of a communication link. a synchronization problem is defined as a problem of concurrent decomposition of a process into a deadlock-free family of processes sharing a communication protocol. it is shown that it is decidable whether a finite family of sequential processes, communicating through a finite link, is deadlock-free or not.
measures of parallelism in alternating computation trees (extended abstract) we examine three ways of restricting the size (and shape) of the accepting computation trees of alternating turing machines. we continue study by examining bounds on the number of leaves in the tree (section 3), the 'width' of the tree (section 4), and the number of nodes at any level of the tree (section 5). each of these measures can be interpreted as a limit on the amount of parallelism permitted the computation.
lower bounds on the complexity of graph properties in this simple model, a decision tree algorithm must determine whether an unknown digraph on nodes {1, 2, &hellip;, n} has a given property by asking questions of the form &ldquo;is edge <i,j> in the graph?&rdquo;. the complexity of a property is the number of questions which must be asked in the worst case. aanderaa and rosenberg conjectured that any monotone, nontrivial, (isomorphism-invariant) n-node digraph property has complexity &ohgr;(n2). this bound was proved by rivest and vuillemin and subsequently improved to n2/4+&ogr;(n2). in part i, we give a bound of n2/2+&ogr;(n2). whether these properties are evasive remains open. in part ii, we investigate the power of randomness in recognizing these properties by considering randomized decision tree algorithms in which coins may be flipped to determine the next edge to be queried. yao's lower bound on the randomized complexity of any monotone nontrivial graph property is improved from &ohgr;(nlog1/12n) to &ohgr;(n5/4), and improved bounds for the complexity of monotone, nontrivial bipartite graph properties are shown.
an interpretation oriented theorem prover over integers a special purpose theorem prover for establishing the validity of expressions over integer variables was developed as part of a program verifier. it is built around a powerful system for manipulating and simplifying integer expressions.
a fully dynamic algorithm for maintaining the transitive closure. this paper presents an efficient fully dynamic graph algorithm for maintaining the transitive closure of a directed graph. the algorithm updates the adjacency matrix of the transitive closure with each update to the graph; hence, each reachability query of the form "is there a directed path from i to j?" can be answered in o(1) time. the algorithm is randomized and has a one-sided error; it is correct when answering yes, but has o(1/nc) probability of error when answering no, for any constant c. in acyclic graphs, worst case update time is o(n2). in general graphs, the update time is o(n2.26). the space complexity of the algorithm is o(n2).
computations with a restricted number of nondeterministic steps (extended abstract) nondeterminism is one of the most elusive concepts in computing. in this paper we direct our efforts towards viewing nondeterminism as an additional resource at the disposal of time or space bounded turing machine computations and study the classes of languages acceptable by these machines with restricted amounts of nondeterminism. one motivation for this study comes from the observation that for many of the well-known np-complete problems, if n' is the length of the input, an algorithm exists requiring a total number of moves which is polynomial in n, but the number of nondeterministic moves is only linear in n.
on the additions necessary to compute certain functions we introduce a theoretical notion, strongly related to algebraic independence, which can be applied to the terms of any computable expression to derive a lower bound on the number of additions and subtractions required to compute that expression.
determining graph properties from matrix representations an open problem, posed by a. rosenberg [r], motivates the consideration of representations of graphs and the effect of these representations on the efficiency of algorithms which determine properties of unlabelled graphs. in this paper we investigate three matrix representations of graphs; the (vertex) adjacency matrix, the edge-adjacency matrix, and the incidence matrix. with the exception of one instance of the edge-adjacency matrix, these structures determine an unlabelled graph up to isomorphism and are, as a result, natural candidates for computer representations of graphs.
on the completeness of a generalized matching problem a perfect matching in a graph h may be viewed as a collection of subgraphs of h, each of which is isomorphic to k2, whose vertex sets partition the vertex set of h. this is naturally generalized by replacing k2 by an arbitrary graph g. we show that if g contains a component with at least three vertices then this generalized matching problem is np-complete. these generalized matchings have numerous applications including the minimization of second-order conflicts in examination scheduling.
measuring energy consumption in vlsi circuits: a foundation energy conservation is a key question in today' s society and the proliferation of vlsi circuits encourages an energy conscious approach to their design. although a single chip at current densities may consume less than one watt of power, assembling larger and larger systems with these chips results in significant energy costs [me 80]. moreover, energy consumed by a circuit is dissipated, typically by convection, as heat. the heat dissipated is proportional to the energy consumed. increased densities in planar technologies and the possibility of 3-dimensional technologies, therefore, increase the need to reduce the amount of heal. produced. the intent of this paper is to lay the ground work for measuring the switching energy consumed in vlsi circuits. intuitively, switching energy measures the area -&-ldquo;used-&-rdquo; to effect a computation. a wire or gate consumes switching energy when it changes staie from 0 to 1 or from 1 to 0. some technologies consume more than switching energy. for example, nmos dissipates dc power [mc 80]. cmos, however, consumes only switching energy [mc 80]. switching energy is thus a lower bound on total energy, and is alternately termed -&-ldquo;energy-&-rdquo; throughout this paper. in this paper, two energy models are developed, model 1, the uniswitch model (usm), assumes that a wire or gate in an acyclic circuit can switch at most once. in particular, wire delays are neglected, the affects of different path lengths are neglected (ie. circuits are synchronous [sa 76]), and all inputs are assumed to arrive together. model 2, the multiswitch model (msm), is more sensitive to timing issues that can cause wires and gates in an acyclic circuit to switch more than once. the rest of this paper is organized as follows. section 2 defines the energy models. in section 3, a class of restricted acyclic circuits is defined. lower and upper bounds for worst case energy are obtained for these circuits. an -&-ohgr;(area) lower bound is obtained for acyclic monotone circuits. in section 4, average energy bounds are obtained for the restricted circuits.
quantum time-space tradeoffs for sorting. we investigate the complexity of sorting in the model of sequential quantum circuits. while it is known that in general a quantum algorithm based on comparisons alone cannot outperform classical sorting algorithms by more than a constant factor in time complexity, this is wrong in a space bounded setting. we observe that for all storage bounds n/log ≥ s ≥ log3n, one can devise a quantum algorithm that sorts n numbers (using comparisons only) in time t=o(n3/2 log3/2 n/√s). we then show the following lower bound on the time-space tradeoff for sorting n numbers from a polynomial size range in a general sorting algorithm (not necessarily based on comparisons): ts=ω(n3/2). hence for small values of s the upper bound is almost tight. classically the time-space tradeoff for sorting is ts=θ(n2).
interaction in quantum communication and the complexity of set disjointness. one of the most intriguing facts about communication using quantum states is that these states cannot be used to transmit more classical bits than the number of qubits used, yet in some scenarios there are ways of conveying information with exponentially fewer qubits than possible classically [3, 26]. moreover, these methods have a very simple structure---they involve only few message exchanges between the communicating parties.we consider the question as to whether every classical protocol may be transformed to a &ldquo;simpler&rdquo; quantum protocol---one that has similar efficiency, but uses fewer message exchanges. we show that for any constant k, there is a problem such that its k+1 message classical communication complexity is exponentially smaller than its k message quantum communication complexity, thus answering the above question in the negative. this in particular proves a round hierarchy theorem for quantum communication complexity, and implies via a simple reduction, an \omega(n^{1/k}) lower bound for k message protocols for set disjointness for constant~k.our result builds on two primitives, local transitions in bi-partite states (based on previous work) and average encoding which may be of significance in other contexts as well.
a subset spanner for planar graphs, : with application to subset tsp. let ε>0 be a constant. for any edge-weighted planar graph g and a subset s of nodes of g, there is a subgraph h of g of weight a constant times that of the minimum steiner tree for s such that distances in h between nodes in s are at most 1+ε times the corresponding distances in g. as a consequence, there is an o(n log n)-time approximation scheme for finding a tsp among a given subset of nodes of a planar graph. this is the first ptas for the problem.
efficient approximation algorithms for semidefinite programs arising from max cut and coloring. the best known approximation algorithm for graph max cut, due to goemans and williamson, first finds the optimal solution a semidefinite program and then derives a graph cut from that solution. building on this result, karger, motwani, and sudan gave an approximation algorithm for graph coloring that also involves solving a semidefinite program. solving these semidefinite programs using known methods (ellipsoid, interior-point), though polynomial-time, is quite expensive. we show how they can be approximately solved in $\tilde o(nm)$ time for graphs with $n$ nodes and $m$ edges.
faster shortest-path algorithms for planar graphs. we give a linear-time algorithm for single-source shortest paths in planar graphs with nonnegative edge-lengths. our algorithm also yields a linear-time algorithm for maximum flow in a planar graph with the source and sink on the same face. the previous best algorithms for these problems required $\omega(n \sqrt{\log n})$ time where $n$ is the number of nodes in the input graph. for the case where negative edge-lengths are allowed, we give an algorithm requiring $o(n^{4/3} \log nl)$ time, where $l$ is the absolute value of the most negative length. previous algorithms for shortest paths with negative edge-lengths required $\omega(n^{3/2})$ time. our shortest-path algorithm yields an $o(n^{4/3} \log n)$-time algorithm for finding a perfect matching in a planar bipartite graph. a similar improvement is obtained for maximum flow in a directed planar graph.
a parallel randomized approximation scheme for shortest paths we give a randomized parallel algorithm for approximate shortest path computation in an undirected weighted graph. the algorithm is based on a technique used by ullman and yannakakis in a parallel algorithm for breadth-first search. it has application, e.g., in approximate solution of multicommodity flow problems with unit capacities. we also show how to adapt the algorithm to perform better for planar graphs.
a randomized linear-time algorithm for finding minimum spanning trees. we present a randomized linear-time algorithm for finding a minimum spanning tree in a connected graph with edge weights. the algorithm is a modification of one proposed by karger and uses random sampling in combination with a recently discovered linear-time algorithm for verifying a minimum spanning tree. our computational model is a unit-cost random-access machine with the restriction that the only operations allowed on edge weights are binary comparisons.
the small-world phenomenon: an algorithm perspective. long a matter of folklore, the ``small-world phenomenon'''' --the principle that we are all linked by short chains of acquaintances --was inaugurated as an area of experimental study in the social sciences through the pioneering work of stanley milgram in the 1960''s. this work was among the first to make the phenomenon quantitative, allowing people to speak of the ``six degrees of separation'''' between any two people in the united states. since then, a number of network models have been proposed as frameworks in which to study the problem analytically. one of the most refined of these models was formulated in recent work of watts and strogatz; their framework provided compelling evidence that the small-world phenomenon is pervasive in a range of networks arising in nature and technology, and a fundamental ingredient in the evolution of the world wide web. but existing models are insufficient to explain the striking algorithmic component of milgram''s original findings: that individuals using local information are collectively very effective at actually constructing short paths between two points in a social network. although recently proposed network models are rich in short paths, we prove that no decentralized algorithm, operating with local information only, can construct short paths in these networks with non-negligible probability. we then define an infinite family of network models that naturally generalizes the watts-strogatz model, and show that for one of these models, there is a decentralized algorithm capable of finding short paths with high probability. more generally, we provide a strong characterization of this family of network models, showing that there is in fact a unique model within the family for which decentralized algorithms are effective.
segmentation problems. we study a novel genre of optimization problems, which we call segmentation problems, motivated in part by certain aspects of clustering and data mining. for any classical optimization problem, the corresponding segmentation problem seeks to partition a set of cost vectors into several segments, so that the overall cost is optimized. we focus on two natural and interesting (but maxsnp-complete) problems in this class, the hypercube segmentation problem and the catalog segmentation problem, and present approximation algorithms for them. we also present a general greedy scheme, which can be specialized to approximate any segmentation problem.
allocating bandwidth for bursty connections. in this paper, we undertake the first study of statistical multiplexing from the perspective of approximation algorithms. the basic issue underlying statistical multiplexing is the following: in high-speed networks, individual connections (i.e., communication sessions) are very bursty, with transmission rates that vary greatly over time. as such, the problem of packing multiple connections together on a link becomes more subtle than in the case when each connection is assumed to have a fixed demand.we consider one of the most commonly studied models in this domain: that of two communicating nodes connected by a set of parallel edges, where the rate of each connection between them is a random variable. we consider three related problems: (1) stochastic load balancing, (2) stochastic bin-packing, and (3) stochastic knapsack. in the first problem the number of links is given and we want to minimize the expected value of the maximum load. in the other two problems the link capacity and an allowed overflow probability p are given, and the objective is to assign connections to links, so that the probability that the load of a link exceeds the link capacity is at most $p$. in bin-packing we need to assign each connection to a link using as few links as possible. in the knapsack problem each connection has a value, and we have only one link. the problem is to accept as many connections as possible.for the stochastic load balancing problem we give an o(1)-approximation algorithm for arbitrary random variables. for the other two problems we have algorithms restricted to on-off sources (the most common special case studied in the statistical multiplexing literature), with a somewhat weaker range of performance guarantees.a standard approach that has emerged for dealing with probabilistic resource requirements is the notion of effective bandwidth---this is a means of associating a fixed demand with a bursty connection that "represents" its distribution as closely as possible. our approximation algorithms make use of the standard definition of effective bandwidth and also a new one that we introduce; the performance guarantees are based on new results showing that a combination of these measures can be used to provide bounds on the optimal solution.
using mixture models for collaborative filtering. a collaborative filtering system at an e-commerce site or similar service uses data about aggregate user behavior to make recommendations tailored to specific user interests. we develop recommendation algorithms with provable performance guarantees in a probabilistic mixture model for collaborative filtering proposed by hoffman and puzicha. we identify certain novel parameters of mixture models that are closely connected with the best achievable performance of a recommendation algorithm; we show that for any system in which these parameters are bounded, it is possible to give recommendations whose quality converges to optimal as the amount of data grows.all our bounds depend on a new measure of independence that can be viewed as an l1-analogue of the smallest singular value of a matrix. using this, we introduce a technique based on generalized pseudoinverse matrices and linear programming for handling sets of high-dimensional vectors. we also show that standard approaches based on l2-spectral methods are not strong enough to yield comparable results, thereby suggesting some inherent limitations of spectral analysis.
new layouts for the shuffle-exchange graph (extended abstract) in this extended abstract, we present several new layouts for the shuffle-exchange graph, including one which requires only 0(n2/log2n) area. the optimal layout is described and analyzed in section 3. the analysis is heavily dependent on several combinatorial results which we state in section 2 and prove in the appendix. the other layouts are described in section 4. although these layouts are not asymptotically optimal (most require 0(n2/log3/2n) area), the theory behind their development is interesting and may eventually lead to good practical layouts as well as other asymptotically optimal layouts.
graph nonisomorphism has subexponential size proofs unless the polynomial-time hierarchy collapses. traditional hardness versus randomness results focus on time-efficient randomized decision procedures. we generalize these trade-offs to a much wider class of randomized processes. we work out various applications, most notably to derandomizing arthur-merlin games. we show that every language with a bounded round arthur-merlin game has subexponential size membership proofs for infinitely many input lengths unless exponential time coincides with the third level of the polynomial-time hierarchy (and hence the polynomial-time hierarchy collapses). since the graph nonisomorphism problem has a bounded round arthur-merlin game, this provides the first strong evidence that graph nonisomorphism has subexponential size proofs. we also establish hardness versus randomness trade-offs for space bounded computation.
randomness efficient identity testing of multivariate polynomials. we present a randomized polynomial time algorithm to determine if a multivariate polynomial is zero using o(\log mn&dgr;) random bits where n is the number of variables, m is the number of monomials, and &dgr; is the total degree of the unknown polynomial. all other known randomized identity tests (see for example [7, 12, 1]) use &ohgr;(n) random bits even when the polynomial is sparse and has low total degree. in such cases our algorithm has an exponential savings in randomness. in addition, we obtain the first polynomial time algorithm for interpolating sparse polynomials over finite fields of large characteristic. our approach uses an error correcting code combined with the randomness optimal isolation lemma of [8] and yields a generalized isolation lemma which works with respect to a set of linear forms over a base set.
learning dnf in time 2. using techniques from learning theory, we show that any s-term dnf over n variables can be computed by a polynomial threshold function of degree o(n1/3 log s). this upper bound matches, up to a logarithmic factor, the longstanding lower bound given by minsky and papert in their 1968 book perceptrons. as a consequence of this upper bound we obtain the fastest known algorithm for learning polynomial size dnf, one of the central problems in computational learning theory.
on structuring flowcharts (preliminary version) cooper's syntactic transformations for structuring flowcharts are studied. after exhibiting major problems with these transformations, a modified set of transformations are proposed. it is proved that a flowchart g is transformable into a d-chart if and only if for every 3 connected circuits c1, c2 and c3 in g, there exists a vertex v on c1+c2+c3 such that for every i, ci passes through v or every path from ci to the out of the flowchart passes through v.
on a multidimensional search problem (preliminary version) the problem of searching for a given k-vector among a sorted list of n k-vectors is considered. the binary search is known to be optimal when k is 1. here an almost optimal algorithm is presented for the 2-dimensional case. interesting upper and lower bounds are derived for the general problem.
the decision problem for the probabilities of higher-order properties the probability of a property on the class of all finite relational structures is the limit as n &rarr; &infin; of the fraction of structures with n elements satisfying the property, provided the limit exists. it is known that 0-1 laws hold for any property expressible in first-order logic or in fixpoint logic, i.e. the probability of any such property exists and is either 0 or 1. it is also known that the associated decision problem for the probabilities is pspace-complete and exptime-complete for first-order logic and fixpoint logic respectively. the 0-1 law fails, however, in general for second-order properties and the decision problem becomes unsolvable. we investigate here logics which on the one hand go beyond fixpoint in terms of expressive power and on the other possess the 0-1 law. we consider first iterative logic which is obtained from first order logic by adding while looping as a construct. we show that the 0-1 law holds for this logic and determine the complexity of the associated decision problem. after this we study a fragment of second order logic called strict &sgr;11. this class of properties is obtained by restricting appropriately the first-order part of existential second-order sentences. every strict &sgr;11 property is np-computable and there are strict &sgr;11 properties that are np-complete, such as 3-colorability. we show that the 0-1 law holds for strict &sgr;11 properties and establish that the associated decision problem is nexptime-complete. the proofs of the decidability and complexity results require certain combinatorial machinery, namely generalizations of ramsey's theorem.
fast parallel processing array algorithms for some graph problems (preliminary version) the parallel processing array consists of an n&times;n array of processors to which a cn2 node directed graph can be input by placing c nodes at every point of the array. it is shown that every one of the following properties of the graph can be computed in order of n steps: (1) to test whether the graph is strongly connected, (2) to mark a node in every strongly connected component, (3) to mark a strong connected component that contains a given node, (4) to mark a simple directed path between a given pair of nodes, and (5) to compute the interconnectivity of the c nodes within every point. as a consequence, several open problems can be solved. for example, any language recognized by a 2-dimensional finite state automaton with 1 pebble can be recognized in order of n steps by a parallel processing array. (it was not even known whether the languages recognized by 2-dimensional finite state automata without pebbles can be recognized in order of n steps by a parallel processing array). note that a 1 pebble automaton can run for order of n4 steps before accepting an input.
constructing small sample spaces satisfying given constraints. the subject of this paper is finding small sample spaces for joint distributions of n discrete random variables. such distributions are often only required to obey a certain limited set of constraints of the form pr (event) = $\pi$. it is shown that the problem of deciding whether there exists any distribution satisfying a given set of constraints is np-hard. however, if the constraints are consistent, then there exists a distribution satisfying them, which is supported by a "small" sample space (one whose cardinality is equal to the number of constraints). for the important case of independence constraints, where the constraints have a certain form and are consistent with a joint distribution of independent random variables, a small sample space can be constructed in polynomial time. this last result can be used to derandomize algorithms; this is demonstrated by an application to the problem of finding large independent sets in sparse hypergraphs.
real-time simulation of concatenable double-ended queues by double-ended queues (preliminary version) it is shown that concatenable double-ended queues can be simulated in real-time by double-ended queues without concatenation. consequently, every multihead turing machine with head-to-head jumps can be simulated in real-time by multitape turing machines.
localized search in sorted lists it is well known that every one of the set operations insert, delete and member can be performed in o(log n) steps, where n is the number of elements currently in the set. here we implement these operations and a move operation for a sorted list with f fingers (points of reference) established on the list. it is shown that these operations can be performed in o(log d) steps, where d is the distance between the corresponding finger and the key involved.
a matter of degree: improved approximation algorithms for degree-bounded minimum spanning trees. in this paper, we present a new bicriteria approximation algorithm for the degree-bounded minimum spanning tree problem. in this problem, we are given an undirected graph, a nonnegative cost function on the edges, and a positive integer b*, and the goal is to find a minimum-cost spanning tree t with maximum degree at most b*. in an n-node graph, our algorithm finds a spanning tree with maximum degree o(b*+logn) and cost o(optb*), where optb* is the minimum cost of any spanning tree whose maximum degree is at most b*. our algorithm uses ideas from lagrangean duality. we show how a set of optimum lagrangean multipliers yields bounds on both the degree and the cost of the computed solution.
decidability of reachability in vector addition systems (preliminary version) a convincing proof of the decidability of reachability in vector addition systems is presented. no drastically new ideas beyond those in sacerdote and tenney, and mayr are made use of. the complicated tree constructions in the earlier proofs are completely eliminated.
primal-dual meets local search: approximating mst's with nonuniform degree bounds. we present a new bicriteria approximation algorithm for the degree-bounded minimum-cost spanning tree problem: given an undirected graph with nonnegative edge weights and degree bounds bv > 1 for all vertices v, find a spanning tree t of minimum total edge-cost such that the maximum degree of each node v in t is at most bv. our algorithm finds a tree in which the degree of each node v is o(bv + log n) and the total edge-cost is at most a constant times the cost of any tree that obeys all degree constraints.our previous algorithm[9] with similar guarantees worked only in the case of uniform degree bounds (i.e. bv=b for all vertices v). while the new algorithm is based on ideas from lagrangean relaxation as is our previous work, it does not rely on computing a solution to a linear program. instead it uses a repeated application of kruskal's mst algorithm interleaved with a combinatorial update of approximate lagrangean node-multipliers maintained by the algorithm. these updates cause subsequent repetitions of the spanning tree algorithm to run for longer and longer times, leading to overall progress and a proof of the performance guarantee.
lower bounds & competitive algorithms for online scheduling of unit-size tasks to related machines. in this paper we study the problem of assigning unit-size tasks to related machines when only limited online information is provided to each task. this is a general framework whose special cases are the classical multiple-choice games for the assignment of unit-size tasks to identical machines. the latter case was the subject of intensive research for the last decade. the problem is intriguing in the sense that the natural extensions of the greedy oblivious schedulers, which are known to achieve near-optimal performance in the case of identical machines, are proved to perform quite poorly in the case of the related machines.(math) in this work we present a rather surprising lower bound stating that any oblivious scheduler that assigns an arbitrary number of tasks to $n$ related machines would need $\omega\left(\frac{\log n}{\l2 n}\right)$ polls of machine loads per task, in order to achieve a constant competitive ratio versus the optimum offline assignment of the same input sequence to these machines. on the other hand, we prove that the missing information for an oblivious scheduler to perform almost optimally, is the amount of tasks to be inserted into the system. in particular, we provide an oblivious scheduler that only uses $\o(\l2 n)$ polls, along with the additional information of the size of the input sequence, in order to achieve a constant competitive ratio vs. the optimum offline assignment. the philosophy of this scheduler is based on an interesting exploitation of the slowfit concept ([1, 5, 3]; for a survey see [6, 9, 16]) for the assignment of the tasks to the related machines despite the restrictions on the provided online information, in combination with a layered induction argument for bounding the tails of the number of tasks passing from slower to faster machines. we finally use this oblivious scheduler as the core of an adaptive scheduler that does not demand the knowledge of the input sequence and yet achieves almost the same performance.
efficient lr(1) processor construction strings from lr(k) grammars can be recognized and parsed in linear time by a processor that is directed by a pre-computed parsing table. this paper deals with two questions of practical importance: the effort required to generate an lr(k)parsing table for a grammar and the size of the table generated. knuth has described an algorithm for checking an arbitrary context-free grammar for the lr(k) condition and producing a parsing table, if possible. the time-complexity of this algorithm and the size of the table it produces are each exponential functions of the grammar size. thus, for very large grammars &mdash; such as those defining the syntax of a programming language &mdash; it is not feasible to use this algorithm directly. this paper presents a practical method of checking large cfgs for the lr(1) condition and generating the corresponding parsing table. it significantly decreases both the computation required to produce the parsing table and the size of the resulting table. it operates as follows. the given grammar g is partitioned into a number of parts. each part is checked for lr(1)-ness and individual parsing tables are generated, using the knuth algorithm. certain conditional modifications to these tables are then made; if the conditions are satisfied, the grammar g is lr(1) and the modified tables can be combined into a single parsing table for g. because of the exponential nature of the knuth algorithm, this process of partitioning, computing and combining can greatly improve the efficiency of the table generation procedure. using this method lr(1) parsers for a number of programming languages, including algol, have been constructed. the empirical evidence obtained has verified the efficacy of this method: in one programming language example, table construction time was reduced by a factor of nine and the table size was reduced by a factor of three.
approximation algorithm for k-node connected subgraphs via critical graphs. we present two new approximation algorithms for the problem of finding a k-node connected spanning subgraph (directed or undirected) of minimum cost. the best known approximation guarantees for this problem were o(min (k,n/√n-k)) for both directed and undirected graphs, and o(ln k) for undirected graphs with n ≥ 6k2, where n is the number of nodes in the input graph. our first algorithm has approximation ratio o(k/n-kln 2 k, which is o(ln2 k) except for very large values of k, namely, k=n-o(n). this algorithm is based on a new result on l-connected p-critical graphs, which is of independent interest in the context of graph theory. our second algorithm uses the primal-dual method and has approximation ratio o(√n ln k) for all values of n,k. combining these two gives an algorithm with approximation ratio o(ln k • min (√k, k/n-k ln k)), which asymptotically improves the best known approximation guarantee for directed graphs for all values of n,k, and for undirected graphs for k> √n⁄6. moreover, this is the first algorithm that has an approximation guarantee better than θ(k) for all values of n,k. our approximation ratio also provides an upper bound on the integrality gap of the standard lp-relaxation to the problem.as a byproduct, we also get the following result which is of independent interest. to get a faster implementation of our algorithms, we consider the problem of adding a minimum-cost edge set to increase the outconnectivity of a directed graph by δ a graph is said to be l-outconnected from its node r if it contains l internally disjoint paths from r to any other node. the best known time complexity for the later problem is o(m3). for the particular case of δ=1, we give a primal-dual algorithm with running time o(m2).
euler paths in series parallel graphs. given a series-parallel graph, we consider the problem of drawing its layout in the plane (and the planar dual of the layout) such that the euler count of the layout is minimized. this problem is of considerable importance to the design of cmos circuits. even though it was believed that there cannot exist a polynomial time algorithm for this problem, we have been able to design a polynomial time algorithm. the degree of the polynomial is unrealistically large. the main interest is in the existence of a polynomial time algorithm for the problem. we are not aware of any natural problem for which a natural dynamic programming based algorithm has such a large degree.
analysis of structured programs we investigate various control structures to understand their computational complexity and limitations. it is generally felt that goto-less programs constructed from the classical primitives are very restrictive; structured programming languages like bliss, however, incorporating repeat-exit constructs appear to ease this sense of restrictiveness. in this paper we analyze this construct. we answer a conjecture of knuth and floyd as a special case of the general theory. we also investigate a general top-down programming construct, which we call the tdn-construct. we structurally characterize the class of goto-less programs. we also generalize such an analysis and solve an open problem of b&ouml;hm and jacopini.
computational complexity of computing polynomials over the fields of real and complex numbers fast computation of polynomials of 1 variable in the fields r and c of real and complex numbers is considered. the optimal schemes of computation with preconditioning (that is, the schemes involving the minimal number of arithmetic operations without counting preliminary treatment of coefficients) for evaluation in c are presented. the schemes which are close to optimal ones are presented for evaluation in r. the difference between the complexity of computation in r and in c is established. a new generalization of the problem is presented.
bounded-depth circuits: separating wires from gates. we develop a new method to analyze the flow of communication in constant-depth circuits. this point of view allows usto prove new lower bounds on the number of wires required to recognize certain languages. we are able to provide explicit languages that can be recognized by ac0 circuits with o(n) gates but not with o(n) wires, and similarly for acc0 circuits. we are also able to characterize exactly the regular languages that can be recognized with o(n) wires, both in ac0 and acc0 framework.
short path queries in planar graphs in constant time. we present a new algorithm for answering short path queries in planar graphs. for any fixed constant k and a given unweighted planar graph g=(v,e) one can build in o(|v|) time a data structure, which allows to check in o(1) time whether two given vertices are distant by at most k in g and if so a shortest path between them is returned. this significantly improves the previous result of d. eppstein [5] where after a linear preprocessing the queries are answered in o(log |v|) time. our approach can be applied to compute the girth of a planar graph and a corresponding shortest cycle in o(|v|) time provided that the constant bound on the girth is known.our results can be easily generalized to other wide classes of graphs~--~for instance we can take graphs embeddable in a surface of bounded genus or graphs of bounded tree-width.
complexity of finitely presented algebras an algebra a is finitely presented if there is a finite set g of generator symbols, a finite set o of operator symbols, and a finite set &ggr; of defining relations x&xgr;y where x and y are well-formed terms over g and o, such that a is isomorphic to the free algebra on g and o modulo the congruence induced by &ggr;. the uniform word problem, the finiteness problem, the triviality problem (whether a is the one element algebra), and the subalgebra membership problem (whether a given element of a is contained in a finitely generated subalgebra of a) for finitely presented algebras are shown to be &le;mlog-complete for p. the schema satisfiability problem and schema validity problem are shown to be &le;mlog-complete for np and co-np, respectively. finally, the problem of isomorphism of finitely presented algebras is shown to be polynomial time many-one equivalent to the problem of graph isomorphism.
indexing of subrecursive classes a theory of subrecursive indexings is developed, with emphasis on relationships between reducibilities, uniform simulation, and diagonalization.
a probabilistic pdl in this paper we give a probabilistic analog ppdl of propositional dynamic logic. we prove a small model property and give a polynomial space decision procedure for formulas involving well-structured programs. we also give a deductive calculus and illustrate its use by calculating the expected running time of a simple random walk program.
pebblings, edgings, and equational logic a lower bound of &ohgr;(n/logn) space is shown for two natural proof systems for equational logic. the method introduces an edging game, a generalization of the pebble game [p].
the intrinsic dimensionality of graphs. we resolve the following conjecture raised by levin together with linial, london, and rabinovich [combinatorica, 1995]. for a graph g, let dim(g) be the smallest d such that g occurs as a (not necessarily induced) subgraph of &#x2124;&#x221e; d , the infinite graph with vertex set &#x2124; d and an edge (u, v) whenever &#x2225;u &#x2212; v&#x2225;&#x221e; = 1. the growth rate of g, denoted &#x03c1; g , is the minimum &#x03c1; such that every ball of radius r > 1 in g contains at most r &#x03c1; vertices. by simple volume arguments, dim(g) = &#x03a9;(&#x03c1; g ). levin conjectured that this lower bound is tight, i.e., that dim(g) = o(&#x03c1; g ) for every graph g. previously, it was unknown whether dim(g) could be bounded above by any function of &#x03c1; g . we show that a weaker form of levin&#x2019;s conjecture holds by proving that dim(g) = o(&#x03c1; g log &#x03c1; g ) for any graph g. we disprove, however, the specific bound of the conjecture and show that our upper bound is tight by exhibiting graphs for which dim(g) = &#x03a9;(&#x03c1; g log &#x03c1; g ). for several special families of graphs (e.g., planar graphs), we salvage the strong form, showing that dim(g) = o(&#x03c1; g ). our results extend to a variant of the conjecture for finite-dimensional euclidean spaces posed by linial and independently by benjamini and schramm.
examples of hard tautologies in the propositional calculus we present examples of hard tautologies in propositional calculus by encoding instances of the assertions made by ramsey's theorem. we provide evidence that these tautologies are indeed hard by 1. showing that there are no short proofs for these tautologies in certain restricted classes of proof systems; 2. relating a proof of these tautologies to the problem of determining the diagonal ramsey numbers for graphs.
covering rectilinear polygons with axis-parallel rectangles. we give an $o(\sqrt{\log n})$ factor approximation algorithm for covering a rectilinear polygon with holes using axis-parallel rectangles. this is the first polynomial time approximation algorithm for this problem with an $o(\log n)$ approximation factor.
a bound on the multiplication efficiency of iteration for a convergent sequence {xi} generated by xi+1 &equil; @@@@(xi,x1,...,xi&minus;d+1), define the multiplication efficiency measure e to be p&frac1m;, where p is the order of convergence, and m is the number of multiplications or divisions (except by 2) needed to compute @@@@. then, if @@@@ is any multivariate rational function, e &le; 2. since e &equil; 2 for the sequence {xi} generated by xi+1 &equil; &frac12;(xi +&fracax; i)with the limit @@@@a, the bound on e is sharp.
the computational complexity of algebraic numbers let {xi} be a sequence approximating an algebraic number &agr; of degree r, and let [equation], for some rational function @@@@ with integral coefficients. let m denote the number of multiplications or divisions needed to compute @@@@ and let &mmarc; denote the number of multiplications or divisions, except by constants, needed to compute @@@@. define the multiplication efficiency measure of {xi} as [equation] or as [equation], where p is the order of convergence of {xi}. kung [1] showed that &emarc;({xi}) &le; 1 or equivalently, [equation]. in this paper we show that (i) [equation]; (ii) if e({xi}) &equil; 1 then &agr; is a rational number; (iii) if &emarc;({xi}) &equil; 1 then &agr; is a rational or quadratic irrational number. this settles the question of when the multiplication efficiency e({xi}) or &emarc;({xi}) achieves its optimal value of unity.
new algorithms and lower bounds for the parallel evaluation of certain rational expressions this paper presents new algorithms for the parallel evaluation of certain polynomial expression. in particular, for the parallel evaluation of xn,we introduce an algorithm which takes two steps of parallel division and [log2n] steps of parallel addition, while the usual algorithm takes [log2n] steps of parallel multiplication. hence our algorithm is faster than the usual algorithms when multiplication takes more time than addition. similar algorithm for the evaluation of other polynomial expressions are also introduced. lower bounds on the time needed for the parallel evaluation of rational expressions are given. all the algorithms presented in the paper are shown to be asymptotically optimal. moreover, we prove that by using parallelism the evaluation of any first order rational recurrence, e.g., [equation], and any non-linear polynomial recurrence can be sped up at most by a constant factor, no matter how many processors are used.
on the random oracle hypothesis we give two counterexamples to the random oracle hypothesis as formalized by bennett and gill[2]. we then discuss the future of the random oracle hypothesis in light of these examples we believe that these examples will severely test any new candidate for a formal random oracle hypothesis.
information-theoretically secure protocols and security under composition. we investigate the question of whether security of protocols in the information-theoretic setting (where the adversary is computationally unbounded) implies security under concurrent composition. this question is motivated by the folklore that all known protocols that are secure in the information-theoretic setting are indeed secure under concurrent composition. we provide answers to this question for a number of different settings (i.e., considering perfect versus statistical security, and concurrent composition with adaptive versus fixed inputs). our results enhance the understanding of what is necessary for obtaining security under composition, as well as providing tools (i.e., composition theorems) that can be used for proving the security of protocols under composition while considering only the standard stand-alone definitions of security.
lower bounds for randomized mutual exclusion. we establish, for the first time, lower bounds for randomized mutual exclusion algorithms (with a read-modify-write operation). our main result is that a constant-size shared variable cannot guarantee strong fairness, even if randomization is allowed. in fact, we prove a lower bound of $\omega (\log\log n)$ bits on the size of the shared variable, which is also tight.we investigate weaker fairness conditions and derive tight (upper and lower) bounds for them as well. surprisingly, it turns out that slightly weakening the fairness condition results in an exponential reduction in the size of the required shared variable. our lower bounds rely on an analysis of markov chains that may be of interest on its own and may have applications elsewhere.
log-space polynomial end-to-end communication. communication between processors is the essence of distributed computing: clearly, without communication, distributed computation is impossible. however, as networks become larger and larger, the frequency of link failures increases. the end-to-end communication problem asks how to efficiently carry out fault-free communication between two processors over a network, in spite of such frequent link failures. the sole minimum assumption is that the two processors that are trying to communicate are not permanently disconnected (i.e., the communication should proceed even when there does not (ever) simultaneously exist an operational path between the two processors that are trying to communicate).we present a protocol to solve the end-to-end problem with logarithmic-space and polynomial communication at the same time. this is an exponential memory improvement to all previous polynomial communication solutions. that is, all previous polynomial communication solutions needed at least linear (in n, the size of the network) amount of memory per link.our protocol transfers packets over the network, maintains a simple-to-compute o(log n)-bits potential function at each link in order to perform routing, and uses a novel technique of packet canceling which allows us to keep only one packet per link. the computations of both our potential function and our packet-canceling policy are totally local in nature.
efficient search for approximate nearest neighbor in high dimensional spaces. we address the problem of designing data structures that allow efficient search for approximate nearest neighbors. more specifically, given a database consisting of a set of vectors in some high dimensional euclidean space, we want to construct a space-efficient data structure that would allow us to search, given a query vector, for the closest or nearly closest vector in the database. we also address this problem when distances are measured by the l1 norm and in the hamming cube. significantly improving and extending recent results of kleinberg, we construct data structures whose size is polynomial in the size of the database and search algorithms that run in time nearly linear or nearly quadratic in the dimension. (depending on the case, the extra factors are polylogarithmic in the size of the database.)
explicit lower bound of for boolena circuits. we prove a lower bound of 4.5n - o(n) for the circuit complexity of an explicit boolean function (that is, a function constructible in deterministic polynomial time), over the basis u_2. that is, we obtain a lower bound of 4.5n - o(n) for the number of {and,or} gates needed to compute a certain boolean function, over the basis {and,or,not} (where the not gates are not counted). our proof is based on a new combinatorial property of boolean functions, called strongly-two-dependence, a notion that may be interesting in its own right. our lower bound applies to any strongly-two-dependent boolean function.
polynomial time reducibility several of the results that appear in [4] are stated to be true of polynominal time reducibility (&le;p) but are not proved explicitly. we shall prove several of these results with the hope of shedding some light on the &ldquo;determinism vs. nondeterminism&rdquo; problem. the ideas behind these proofs already exist in [4] but appear here in a different setting. we shall spend most of our time on two theorems: (i) if &fgr; <p &bgr; then there exists an &agr; such that &fgr; <p &agr; <p &bgr; and (ii) there exist &agr; and &bgr; neither of which is polynominal time computable but such that if c &le;p &agr; and c &le;p &bgr; then c is polynominal time computable. we show how the techniques used in the proofs of these theorems may be extended to prove other results.
the complexity of problems in systems of communicating sequential processes (extended abstract) there is a wide-spread belief among computer scientists that systems of communicating sequential processes are harder to analyze than purely sequential processes. the belief is largely based on the observation that the parallelism in such systems leads to a large number of possible interleavings of the actions of the different processes. we will show that other evidence supporting this belief is that the properties we are trying to analyze about these systems are themselves intrinsically complex. they are properties that make no sense when they are applied to purely sequential processes, or even parallel systems of sequential processes that have no ability to communicate with each other.
comparisons of polynomial-time reducibilities comparison of the polynomial-time-bounded reducibilities introduced by cook [1] and karp [4] leads naturally to the definition of several intermediate truth-table reducibilities. we give definitions and comparisons for these reducibilities; we note, in particular, that all reducibilities of this type which do not have obvious implication relationships are in fact distinct in a strong sense. proofs are by simultaneous diagonalization and encoding constructions. work of meyer and stockmeyer [7] and gill [2] then leads us to define nondeterministic versions of all of our reducibilities. although many of the definitions degenerate, comparison of the remaining nondeterministic reducibilities among themselves and with the corresponding deterministic reducibilities yields some interesting relationships.
tradeoffs between communication and space this paper initiates the study of communication complexity when the processors have limited work space. the following tradeoffs between number c of communications steps and space s are proved: for multiplying two n &times; n matrices in the arithmetic model with two-way communication, cs = &thgr;(n2). for convolution of two degree n polynomials in the arithmetic model with two-way communication, cs = &thgr;(n2). for multiplying an n &times; n matrix by an n-vector in the boolean model with one-way communication, cs = &thgr;(n2). in contrast, the discrete fourier transform and sorting can be accomplished in &ogr;(n) communication steps and &ogr;(log n) space simultaneously, and the search problems of karchmer and wigderson associated with any language in nck can be solved in &ogr;(logk n) communication steps and &ogr;(logk n) space simultaneously.
solvability by radicals is in polynomial time every high school student knows how to express the roots of a quadratic equation in terms of radicals; what is less well-known is that this solution was found by the babylonians a millenia and a half before christ [ne]. three thousand years elapsed before european mathematicians determined how to express the roots of cubic and quartic equations in terms of radicals, and there they stopped, for their techniques did not extend. lagrange published a treatise which discussed why the methods that worked for polynomials of degree less than five did not work for quintic polynomials [lag], they require double exponential time. through the years other mathematicians developed alternate algorithms all of which, however, remained exponential. a major impasse was the problem of factoring polynomials, for until the recent breakthrough of lenstra, lenstra, and lov&aacute;sz [l3], all earlier algorithms had exponential running time. their algorithm, which factors polynomials over the rationals in polynomial time, gave rise to a hope that some of the classical questions of galois theory might have polynomial time solutions. galois transformed the question of solvability by radicals from a problem concerning fields to a problem about groups. what we do is to change the inquiry into several problems concerning the solvability of certain primitive groups.
recursive properties of abstract complexity classes (preliminary version) it is proven that complexity classes of abstract measures of complexity need not be recursively enumerable. however, the complement of each class is r.e. properties of effective enumerations of complexity classes are studied. for any measure there is another measure with 'almost' the same complexity classes such that almost every class admits an effective enumeration in terms of speedy devices. finally complexity classes are shown to not be closed under intersection.
the subgraph homeomorphism problem we investigate the problem of finding a homeomorphic image of a &ldquo;pattern&rdquo; graph h in a larger input graph g. we view this problem as finding specified sets of edge disjoint or node disjoint paths in g. our main result is a linear time algorithm to determine if there exists a simple cycle containing three given nodes in g; here h is a triangle. no polynomial time algorithm for this problem was previously known. we also discuss a variety of reductions between related versions of this problem and a number of open problems.
location of a point in a planar subdivision and its applications given a subdivision of the plane induced by a planar graph with n vertices, in this paper we consider the problem of identifying which region of the subdivision contains a given test point. we present a search algorithm, called point-location algorithm, which operates on a suitably preprocessed data structure. the search runs in time at most 0((log n)2), while the preprocessing task runs in time at most 0(n log n) and requires 0(n) storage. the methods are quite general, since an arbitrary subdivision can be transformed in time at most 0(n log n) into one to which the preprocessing procedure is applicable. this solution of the point-location problem yields interesting and efficient solutions of other geometric problems, such as spatial convex inclusion and inclusion in an arbitrary polygon.
online minimization of transition systems (extended abstract) we are given a transition system implicitly through a compact representation and wish to perform simultaneously reachability analysis and minimization without constructing first the whole system graph. we present an algorithm for this problem that applies to general systems, provided we have appropriate primitive operations for manipulating blocks of states and we can determine termination; the number of operations needed to construct the minimal reachable graph is quadratic in the size of this graph. we specialize the method to obtain efficient algorithms for extended finite state machines that apply separable affine transformations on the variables.
a partial solution to the reachability-problem for vector-addition systems with geometrical techniques we hope to bring new insight into the reachability problem for vector-addition systems, which is pertaining in many areas in computer science theory but unsolved ever since it was proposed by karp and miller. we show that the reachability-problem is decidable in dim. &le; 3 and give a partial solution for the general problem covering a wide instance of it. in both cases a semi-linear characterization is obtained for the complete set of solutions. contrary to common belief the complete solution in dim. 3 does not immediately generalize, and our analysis gives evidence why. a few generalizations and application to long-standing classificational problems in language theory are discussed.
a layout strategy for vlsi which is provably good (extended abstract) in this paper, we introduce a new framework within which to study vlsi layout problems. the framework is based on a straightforward generalization of the lipton-tarjan notion of a planar separator and, unlike previous approaches, leads to universally close upper and lower bounds on the layout area and crossing number of an arbitrary network. in addition, the framework permits simple proofs of results previously thought to be difficult and is suitable for use with good bisection width heurisitcs.
fast approximation algorithms for multicommodity flow problems in this paper, we describe the first polynomial-time combinatorial algorithms for approximately solving the multicommodity flow problem. our algorithms are significantly faster than the best previously known algorithms, that were based on linear programming. for a k-commodity multicommodity flow problem, the running time of our randomized algorithm is (up to log factors) the same as the time needed to solve k single-commodity flow problems, thus giving the surprising result that approximately computing a k-commodity maximum-flow is not much harder than computing about k single-commodity maximum-flows in isolation. given any multicommodity flow problem as input, our algorithm is guaranteed to provide a feasible solution to a modified flow problem in which all capacities are increased by a (1 + epsilon)-factor, or to provide a proof that there is no feasible solution to the original problem. we also describe faster approximation algorithms for multicommodity flow problems with a special structure, such as those that arise in the "sparsest cut" problems and the uniform concurrent flow problems if k >= the square root of m.
algorithms for routing and testing routability of planar vlsi layouts this paper studies the problem of routing wires in a grid among features on one layer of a vlsi chip, when a sketch of the layer is given. a sketch specifies the positions of features and the topology of the interconnecting wires. we give polynomial-time algorithms that (1) determine the routability of a sketch, and (2) produce a routing of a sketch that optimizes both individual and total wire length. these algorithms subsume most of the polynomial-time algorithms in the literature for planar routing and routability testing in the rectilinear grid model. we also provide an explicit construction of a database, called the rubber-band equivalent, to support computation involving the layout topology.
upper and lower bounds on time-space tradeoffs this paper derives asymptotically tight bounds on the time-space tradeoffs for pebbling three different classes of directed acyclic graphs. let n be the size of the graph, s the number of available pebbles, and t the time necessary for pebbling the graph. (a) a time space tradeoff of the form st &equil; &thgr;(n2) is proved for a special class of permutation graphs which implement the bit reversal permutation. (b) a time-space tradeoff of the form t &equil; s &thgr;(n/s)&thgr;(n/s) is proved for a class of graphs constructed by stacking superconcentrators in series. (c) a time-space tradeoff of the form t &equil; s.22&thgr;(n/s)is proved for pebbling general directed acyclic graphs.
approximating total flow time on parallel machines. we consider the problem of optimizing the total flow time of a stream of jobs that are released over time in a multiprocessor setting. this problem is np-hard even when there are only two machines and preemption is allowed. although the total (or average) flow time is widely accepted as a good measurement of the overall quality of service, no approximation algorithms were known for this basic scheduling problem. this paper contains two main results. we first prove that when preemption is allowed, shortest remaining processing time (srpt) is an o(log(min{nm,p})) approximation algorithm for the total flow time, where n is the number of jobs, m is the number of machines, and p is the ratio between the maximum and the minimum processing time of a job. we also provide an @w(log(nm+p)) lower bound on the (worst case) competitive ratio of any randomized algorithm for the on-line problem in which jobs are known at their release times. thus, we show that up to a constant factor srpt is an optimal on-line algorithm. our second main result addresses the non-preemptive case. we present a general technique that allows to transform any preemptive solution into a non-preemptive solution at the expense of an o(nm) factor in the approximation ratio of the total flow time. combining this technique with our previous result yields an o(nmlognm) approximation algorithm for this case. we also show an @w(n^1^3^-^@e) lower bound on the approximability of this problem (assuming p
new real-time simulations of multihead tape units just as the church-turing thesis has simplified proofs of computability [8], efficient simulations of one computer model by another have simplified proofs of complexity upper bounds. a good example of this is fischer, meyer, and rosenberg's real-time simulation of multihead turing machines by multitape turing machines [5]. without this result, for example, even slisenko [11] may have found it hopeless to show that a multitape turing machine can recognize palindromes in real time. in this paper we give a comparatively simple proof of the fischer-meyer-rosenberg result, dramatically reduce the number of single-head tapes required for the simulation, and generalize the result to multidimensional tapes. in the case of slisenko's palindrome-recognizer, for example, our best simulation brings the number of tapes for a multitape turing machine implementation down from 41 to 20.
collusion-free protocols. secure protocols attempt to minimize the injuries to privacy and correctness inflicted by malicious participants who collude during run-time. they do not, however, prevent malicious parties from colluding and coordinating their actions in the first place!eliminating such collusion of malicious parties during the execution of a protocol is an important and exciting direction for research in cryptography. we contribute the first general result in this direction: (1) we provide a rigorous definition of what a collusion-free protocol is; and (2) we prove that, under standard physical and computational assumptions ---i.e., plain envelopes and trapdoor permutations---collusion-free protocols exist for all finite protocol tasks with publicly observable actions. (note that such tasks are allowed to have secret global state, and thus include poker, bridge, and other such games.our solution is tight in the sense that, for a collusion-free protocol to exist, each of (a) the finiteness of the game of interest, (b) the public observability of its actions, and (c) the use of some type of physically private channel is provably essential.
primal-dual algorithms for deterministic inventory problems. we consider several classical models in deterministic inventory theory: the single-item lot-sizing problem, the joint replenishment problem, and the multistage assembly problem. these inventory models have been studied extensively, and play a fundamental role in broader planning issues, such as the management of supply chains. for each of these problems, we wish to balance the cost of maintaining surplus inventory for future demand against the cost of replenishing inventory more frequently. for example, in the joint replenishment problem, demand for several commodities is specified over a discrete finite planning horizon, the cost of maintaining inventory is linear in the number of units held, but the cost incurred for ordering a commodity is independent of the size of the order; furthermore, there is an additional fixed cost incurred each time a nonempty subset of commodities is ordered. the goal is to find a policy that satisfies all demands on time and minimizes the overall holding and ordering cost. we shall give a novel primal-dual framework for designing algorithms for these models that significantly improve known results in several ways: the performance guarantees for the quality of the solutions improve on or match previously known results; the performance guarantees hold under much more general assumptions about the structure of the costs, and the algorithms and their analysis are significantly simpler than previous known results. finally, our primal-dual framework departs from the structure of previously studied primal-dual approximation algorithms in significant ways, and we believe that our approach may find applications in other settings. more specifically, we provide 2-approximation algorithms for the joint replenishment problem and for the assembly problem, and solve the single-item lot-sizing problem to optimality. the results for the joint replenishment and the lot-sizing problems also hold for their generalizations with back orders allowed. as a byproduct of our work, we prove known and new upper bounds on the integrality gap of some linear-programming (lp) relaxations of the abovementioned problems.
provably near-optimal sampling-based algorithms for stochastic inventory control models. we consider two fundamental stochastic optimization problems that arise in the context of supply-chain models, the single-period newsvendor problem and its multiperiod extension with independent demands. these problems are among the most well-studied stochastic optimization problems in the operations research literature. most commonly, these problems are studied from the perspective that the input probability distributions are given in terms of specific probability distribution functions that are computationally tractable; under this assumption, both problems can be solved efficiently. unfortunately, this information is unlikely to be available in practice, and hence we make the more realistic assumption that the probability distribution is given by a "black box" from which independent samples can be drawn. we give the first fully polynomial randomized approximation schemes for these two problems in this sampling-based model.our work provides new insights into the power of two of the most often-used approaches to solving stochastic optimization problems, the sample average approximation (saa) and stochastic dynamic programming. for the newsvendor problem, we show that by taking a polynomial number of samples and then solving the newsvendor problem with respect to the resulting approximation to the true distribution, we obtain provably near-optimal solution. this significantly extends the class of problems for which the saa is known to yield a scheme. finally, we show how to adapt the framework of stochastic dynamic programming to yield an approximation scheme for the multiperiod newsvendor problem with independent demands. we believe that this is an interesting first step towards the goal of providing a mechanism for deriving efficient approximate stochastic dynamic programming methods for a wide range of multistage stochastic optimization problems.
one-way functions and pseudorandom generators one-way are those functions which are easy to compute, but hard to invert on a non-negligible fraction of instances. the existence of such functions with some additional assumptions was shown to be sufficient for generating perfect pseudorandom strings |blum, micali 82|, |yao 82|, |goldreich, goldwasser, micali 84|. below, among a few other observations, a weaker assumption about one-way functions is suggested, which is not only sufficient, but also necessary for the existence of pseudorandom generators. the main theorem can be understood without reading the sections 3-6.
some results in tree automata in this paper, we will essentially present three results in tree automata. two of these are concerned with certain open problems posed by rounds [1] and martin and vere [3], and the third one is related to the result of peters and ritchie [4]. first we will briefly state the results and then describe them in some detail in sections 2, 3, and 4.
unsolvability considerations in computational complexity the study of computational complexity began with the investigation of turing machine computations with limits on the amounts of tape or time which could be used. latter a set of general axioms for measures of resource limiting was presented and this instigated much study of the properties of these general measures. many interesting results were shown, but the general axioms allowed measures with undesirable properties and many attempts have been made to tighten up the axioms so that only desirable measures will be defined. in this paper several undecidability aspects of complexity classes and several sets associated with them will be examined. these sets will be classified by their degree of unsolvability and restrictions will be placed on measures so that these degrees are identical. this gives rise to a new criterion for the &ldquo;naturalness&rdquo; of measures and to suggestions for strengthening the measures of complexity.
closure of families of languages under substitution operators this paper treats the closure of families of formal languages under operators which may be viewed as substitution into a particular language. a language l over alphabet {a1,...,an} induces an n-place operator on languages by substitution of the n arguments li for the symbols ai. for example, if l is regular, it induces an operator under which any full afl is closed. in section two we find a large class of full afl's which are closed under no other such operators than those induced by regular languages. also, for any full afl @@@@', let @@@@ be the class of languages which @@@@' is closed under substitution into. then @@@@ is itself a full afl and is closed under substitution. finally we show that any substitution-closed full afl @@@@ is obtained in this manner from some non-substitution-closed full afl @@@@ (except when @@@@ is the universal family). the study is based on the concept of a full afl, and in section one considerable effort is devoted to a novel approach to the subject. a full afl is taken to be a family of languages closed under finite-state transducer mappings and substitution into regular sets. by replacing the family of regular sets with more general families we obtain some broad results about canonical forms for derivations of languages from other languages using transducers and substitution. these forms yield several known forms as special cases, and provide tools needed for the study of full afl's in section two.
on the complexity of the maximum subgraph problem for a fixed graph property, the maximum subgraph recognition problem for the property is: given a graph g and integer k, does g have a subgraph induced by k vertices which satisfies the property. this paper studies the complexity of this problem for various properties. the principal result is that if the property is any one of a wide class of monotone properties, the maximum subgraph problem is np-hard. this suggests a promising direction of inquiry into the p &equil; ?np question.
attributed translations attributed translation grammars are introduced as a means of specifying a translation from strings of input symbols to strings of output symbols. each of these symbols can have a finite set of attributes, each of which can take on a value from a possibly infinite set. attributed translation grammars can be applied in depth to practical compiling problems. certain augmented pushdown machines are defined and characterizations are given of the attributed translations they can perform both deterministically and non-deterministically. classes of attributed translation grammars are defined whose translation can be performed deterministically while parsing top down or bottom up.
finding similar regions in many strings. algorithms for finding similar, or highly conserved, regions in a group of sequences are at the core of many molecular biology problems. assume that we are given n dna sequences s1, ...., sn. the consensus patterns problem, which has been widely studied in bioinformatics research, in its simplest form, asks for a region of length l in each si, and a median string s of length l so that the total hamming distance from s to these regions is minimized. we show that the problem is np-hard and give a polynomial time approximation scheme (ptas) for it. we then present an efficient approximation algorithm for the consensus pattern problem under the original relative entropy measure. as an interesting application of our analysis, we further obtain a ptas for a restricted (but still np-hard) version of the important consensus alignment problem allowing at most constant number of gaps, each of arbitrary length, in each sequence.
isomorphism for graphs embeddable on the projective plane there are no known polynomial time algorithms for graph isomorphism. for certain classes of graphs, however, efficient algorithms have been found. in particular, there is a polynomial time algorithm for isomorphism of planar graphs [4,5]. this paper presents a generalization of the third theorem to the projective plane, allowing a straightforward adaptation of the planar algorithm to the projective plane. gary miller has subsequently generalized my result to surfaces of arbitrary genus, so that there is now a graph isomorphism algorithm which is polynomial for any fixed genus.
imperfect random sources and discrete controlled processes we consider a simple model for a class of discrete control processes, motivated in part by recent work about the behavior of imperfect random sources in computer algorithms. the process produces a string of characters from {0, 1} of length n and is a &ldquo;success&rdquo; or &ldquo;failure&rdquo; depending on whether the string produced belongs to a prespecified set l. in an uninfluenced process each character is chosen by a fair coin toss, and hence the probability of success is |l|/2n. we are interested in the effect on the probability of success in the presence of a player (controller) who can intervene in the process by specifying the value of certain characters in the string. we answer the following questions in both worst and average case: (1) how much can the player increase the probability of success given a fixed number of interventions? (2) in terms of |l| what is the expected number of interventions needed to guarantee success? in particular our results imply that if |l|/2n = 1/w(n) where w(n) tends to infinity with n (so the probability of success with no interventions is o(1)) then with &ogr;(&radic;nlogw(n)) interventions the probability of success is 1-o(1). our main results and the proof techniques are related to a well-known theorem of kruskal, katona, and harper in extremal set theory.
epsilon-approximations with minimum packing constraint violation (extended abstract) we present efficient new randomized and deterministic methods for transforming optimal solutions for a type of relaxed integer linear program into provably good solutions for the corresponding np-hard discrete optimization problem. without any constraint violation, the &egr;-approximation problem for many problems of this type is itself np-hard. our methods provide polynomial-time &egr;-approximations while attempting to minimize the packing constraint violation. our methods lead to the first known approximation algorithms with provable performance guarantees for the s-median problem, the tree prunning problem, and the generalized assignment problem. these important problems have numerous applications to data compression, vector quantization, memory-based learning, computer graphics, image processing, clustering, regression, network location, scheduling, and communication. we provide evidence via reductions that our approximation algorithms are nearly optimal in terms of the packing constraint violation. we also discuss some recent applications of our techniques to scheduling problems.
bounded-concurrent secure two-party computation without setup assumptions. in this paper we study the feasibility of obtaining protocols for general two-party computation that remain secure under concurrent composition. (a general protocol can be used for obtaining secure computation of any functionality.) we consider a scenario where no trusted setup is assumed (and so, for example, there is no common reference string available to the parties); we call this the "plain model". we present both negative and positive results for this model. specifically, we show that a general two-party protocol that remains secure for m concurrent executions and can be proven via black-box simulation, must have more than m rounds of communication. an important corollary of this result is that there do not exist protocols for black-box secure general two-party computation for the case of unbounded concurrency (where any polynomial number of concurrent executions may be run). on the positive side, we show that under general cryptographic assumptions, there exist secure protocols for general two-party computation in the model of bounded concurrent composition (in this model the number of concurrent executions is fixed and the protocol design may depend on this number). our protocol has o(m) rounds of communication, where m is the bound on the number of concurrent executions, and uses both black-box and non black-box techniques. we note that this protocol constitutes the first feasibility result for general two-party computation without setup assumptions for any model of concurrency.
a logspace algorithm for tree canonization (extended abstract) we present a solution to the problem of assigning to each directed tree t of size n a unique isomorphism invariant name for t, using only work space o(log n). hence, tree isomorphism is computable in logspace. as another consequence, we obtain the corollary that the set of logspace computable queries (lspace) on trees is recursively enumerable. our results extend easily to undirected trees and even forests.
on the composition of authenticated byzantine agreement. a fundamental problem of distributed computing is that of simulating a secure broadcast channel, within the setting of a point-to-point network. this problem is known as byzantine agreement (or generals) and has been the focus of much research. lamport et al. [1982] showed that in order to achieve byzantine agreement in the plain model, more than two thirds of the participating parties must be honest. they further showed that by augmenting the network with a public-key infrastructure for digital signatures, it is possible to obtain protocols that are secure for any number of corrupted parties. the problem in this augmented model is called &ldquo;authenticated byzantine agreement&rdquo;.in this article, we consider the question of concurrent, parallel and sequential composition of authenticated byzantine agreement protocols with a single common setup. we present surprising impossibility results showing that:(1) authenticated byzantine agreement protocols that remain secure under parallel or concurrent composition (even for just two executions) and tolerate a third or more corrupted parties, do not exist.(2) deterministic authenticated byzantine agreement protocols that run for r rounds and tolerate a third or more corrupted parties, can remain secure for at most 2r &minus; 1 sequential executions.in contrast, we present randomized protocols for authenticated byzantine agreement that remain secure under sequential composition, for any polynomial number of executions. we exhibit two such protocols. in the first protocol, an honest majority is required. in the second protocol, any number of parties may be corrupted; however, the complexity of the protocol is in the order of 2n &middot; n&excl; for n parties. in order to have this polynomial in the security parameter k (used for the signature scheme in the protocol), this requires the overall number of parties to be limited to o(log k/log log k). the above results are achieved due to a new protocol for authenticated byzantine generals for three parties that can tolerate any number of faulty parties and composes sequentially.finally, we show that when the model is further augmented so that in each session, all the participating parties receive a common session identifier that is unique to that session, then any polynomial number of authenticated byzantine agreement protocols can be concurrently executed, while tolerating any number of corrupted parties.
developmental systems and languages developmental systems were introduced (lindenmayer, 1968, 1971) in order to model morphogenetic (pattern-generating) processes in growing, multicellular, filamentous organisms. these systems were originally conceived as linear arrays of interconnected finite automata, each automaton corresponding to a living cell, with the possibility that new automata can be added to the array (cells divide) or be deleted from the array (cells die). each cell in the array is supposed to have the same state-transition and output functions. as required by biological considerations these functions must be applied to all cells in the array simultaneously at each time step. thus one obtains infinite sequences of arrays once the functions and the initial arrays are specified. simplified constructs are defined (and used in this paper) by considering the states and outputs to be identical and thus omitting the output functions. such filamentous developmental systems have been called &ldquo;lindenmayer models&rdquo; herman, 1969, 1970) or &ldquo;l-systems&rdquo; (van dalen, 1971).
the design of parsers for incremental language processors an incremental language processor is one that accepts as input a sequence of substrings of the source language and maps them independently onto fragments in some object code. the ordered sequence of these object code fragments are then either compiled, in which case we have an incremental compiler, or interpreted. in the first case the advantage resulting is that subsequent changes in the source program entail only reprocessing the source fragments affected and recompiling the updated collection of object code fragments. in an environment where small changes are made frequently to large programs, e.g. debugging, the curtailment of reprocessing is attractive. in the second case the object code fragments are the actual run-time program representation, and hence inter-fragment relations are transiently evaluated as needed in the process of execution, with no long-term preservation of these relationships beyond the scope of their immediate need in execution time. this permits the possibility of program recomposition in the midst of execution, one of the principal characteristics of conversational computing. many conversational language processors execute a program representation functionally analogous to parse trees, i.e. the syntax analysis of a fragment, insofar as it is possible, is done at fragment load time. this representation choice is popular because many of the expensive aspects of interpretation, including character string scanning, symbol table lookup, and parsing, are performed once only and do not contribute to the execution overhead. this paper is devoted to examining the question of the construction of such a parser in a general manner for an arbitrary source language.
girth and euclidean distortion. (math) in this paper we partially prove a conjecture that was raised by linial, london and rabinovich in \cite{llr}. let $g$ be a $k$-regular graph, $k \ge 3$, with girth $g$. we show that every embedding $f : g \to \ell_2$ has distortion $\omega (\sqrt{g})$. the original conjecture which remains open is that the euclidean distortion is bounded below by $\omega(g)$. two proofs are given, one based on semi-definite programming, and the other on markov type, a concept that considers random walks on metrics.
limitations of synchronization primitives with conditional branching and global variables a formal model of the process concept is presented. this model can represent sets of processes that use the synchronization primitive pv or one of the many generalizations of pv. the study of synchronization problems is then reduced to the study of relations between sets of processes. for one relation&mdash; &ldquo;simulate&rdquo;&mdash;it is possible to show that there are differences between several synchronization primitives. these differences show that the relative &ldquo;power&rdquo; of these synchronization primitives is not the same.
complexity measures and hierarchies for the evaluation of integers, polynomials, and n-linear forms the difficulty of evaluating integers and polynomials has been studied in various frameworks ranging from the addition-chain approach [5] to integer evaluation to recent efforts aimed at generating polynomials that are hard to evaluate [2,8,10]. here we consider the classes of integers and polynomials that can be evaluated within given complexity bounds and prove the existence of proper hierarchies of complexity classes. the framework in which our problems are cast is general enough to allow any finite set of binary operations rather than just addition, subtraction, multiplication, and division. the motivation for studying complexity classes rather than specific integers or polynomials is analogous to why complexity classes are studied in automata-based complexity: (i) the immense difficulty associated with computing the complexity of a specific integer or polynomial; (ii) the important insight obtained from discovering the structure of the complexity classes.
the complexity of control structures and data structures the running time or computational complexity of a sequential process is usually determined by summing weights attached to the basic operations from which the process is derived. in practice, however, the complexity is often limited by how efficiently it can access its data structures and how efficiently it can control program flow. furthermore, it has been extensively argued [4] that certain limitations on the process sequencing mechanisms available to the programmer result in more &ldquo;efficient&rdquo; representations for the underlying processes. in this paper we will examine these issues in an attempt to assess the &ldquo;power&rdquo; of various data and control structures.
evaluation of polynomials with super-preconditioning in an effort to understand the complexity of arithmetic computation, a number of researchers [1,5,7,8,9,11] have studied the following question: given a polynomial f(x), find a minimal cost straightline program that computes f(x).@@@@ in this paper this question is generalized to the following question: given a polynomial f(x) and an operator &dgr; that maps polynomials to sets of polynomials, find a minimal cost straightline program that computes some h(x) &egr; &dgr;(f(x)).
lower bounds for vlsi increased use of very large scale integration (vlsi) for the fabrication of digital circuits has led to increased interest in complexity results on the inherent vlsi difficulty of various problems. lower bounds have been obtained for problems such as integer multiplication [1,2], matrix multiplication [7], sorting [8], and discrete fourier transform [9], all within vlsi models similar to one originally developed by thompson [8,9]. the lower bound results all pertain to a space-time trade-off measure that arises naturally within this model. in this paper, we extend the model and the class of functions for which non-trivial bounds can be proved. in section 2, we give a more general model than has been proposed previously. in section 3 we show how to reduce the derivation of lower bounds within the model to a problem in distributed computing in section 4, we consider lower bounds for a number of predicates: n-input, l-output functions (as contrasted with the n-input, n-output functions which have been studied previously). in section 5, we show that previous lower bound results (for n-input, n-output functions) also apply even when the model is extended to allow nondeterminism, randomness, and multiple arrivials. finally, the full details of the results presented here will appear in the final version of this paper.
on-line learning of linear functions we present an algorithm for the on-line learning of linear functions which is optimal to within a constant factor with respect to bounds on the sum of squared errors for a worst case sequence of trials. the bounds are logarithmic in the number of variables. furthermore, the algorithm is shown to be optimally robust with respect to noise in the data (again to within a constant factor). we also discuss an application of our methods to the iterative solution of sparse systems of linear equations.
critical path scheduling of task systems with resource and processor constraints (extended abstract) minimum execution time scheduling of unit execution time (uet) task systems with resources has been the subject of several papers over the past few years. because such scheduling problems are, in general, np-hard, a variety of heuristic methods for producing schedules have been studied, among them, critical path scheduling. the strongest results to date have been for systems where there is no processor constraint. these results may be utilized for systems with a processor constraint by treating the processors as an additional resource. unfortunately, in those cases where the number of processors is close to the number of resources, this results in an upper bound which is somewhat misleading. in this paper we investigate the performance of critical path scheduling for uet task systems with resources and a fixed number of processors. an upper bound for the worst case performance of critical path scheduling is given. this bound depends both on the number of processors and on the number of different resources. moreover, we show that this is the best possible (asymptotic) upper bound.
on gamma-reducibility versus polynomial time many-one reducibility (extended abstract) we prove that a class of functions (denoted by npcpt), whose graphs can be accepted in non-deterministic polynomial time, can be evaluated in deterministic polynomial time if and only if &ggr;-reducibility is equivalent to polynomial time many-one reducibility. we also modify the proof technique used to obtain part of this result to obtain the stronger result that if every &ggr;-reduction can be replaced by a polynomial time turing reduction then every function in npcpt can be evaluated in deterministic polynomial time.
how discreet is the discrete log? blum and micali [4] showed how to hide one bit using the discrete logarithm function. in this paper we show how to hide c&bull;loglog p bits for any constant c, where p is the modulus.
hit-and-run from a corner. we show that the hit-and-run random walk mixes rapidly starting from any interior point of a convex body. this is the first random walk known to have this property. in contrast, the ball walk can take exponentially many steps from some starting points. the proof extends to sampling an exponential density over a convex body.
on minimal-program complexity measures brief consideration is given to some properties of three measures of complexity based on the length of minimal descriptive programs. although the measures explicitly deal with finite sequences, the complexity of an infinite sequence can be regarded as a function mapping each positive integer n to the complexity of the initial segment of length n. some properties of a complexity hierarchy of infinite sequences with respect to one of the measures is considered.
extractors: optimal up to constant factors. this paper provides the first explicit construction of extractors which are simultaneously optimal up to constant factors in both seed length and output length. more precisely, for every n,k, our extractor uses a random seed of length o(log n) to transform any random source on n bits with (min-)entropy k, into a distribution on (1-α)k bits that is ε-close to uniform. here α and ε can be taken to be any positive constants. (in fact, ε can be almost polynomially small.our improvements are obtained via three new techniques, each of which may be of independent interest. the first is a general construction of mergers [22] from locally decodable error-correcting codes. the second introduces new condensers that have constant seed length (and retain a constant fraction of the min-entropy in the random source). the third is a way to augment the "win-win repeated condensing" paradigm of [17] with error reduction techniques like [15] so that the our constant seed-length condensers can be used without error accumulation.
doubly lexical orderings of matrices a doubly lexical ordering of the rows and columns of any real-valued matrix is defined. this notion extends to graphs. these orderings are used to prove and unify results on several classes of matrices and graphs, including totally balanced matrices and chordal graphs. an almost-linear time doubly lexical ordering algorithm is given.
a simple parallel algorithm for the maximal independent set problem simple parallel algorithms for the maximal independent set (mis) problem are presented. the first algorithm is a monte carlo algorithm with a very local property. the local property of this algorithm may make it a useful protocol design tool in distributed computing environments and artificial intelligence. one of the main contributions of this paper is the development of powerful and general techniques for converting monte carlo algorithms into deterministic algorithms. these techniques are used to convert the monte carlo algorithm for the mis problem into a simple deterministic algorithm with the same parallel running time.
maximization problems on graphs with edge weights chosen from a normal distribution (extended abstract) we consider optimization problems on complete graphs with edge weights chosen from identical but independent normal distributions. we show some very general techniques for obtaining upper and lower bounds on the asymptotic behavior of these problems. often, but not always, these bounds are equal, enabling us to state the asymptotic behavior of the maximum. problems in which the bounds are tight include finding the optimum traveling salesman tour, finding a minimum cost spanning tree, and finding a heaviest clique on k vertices. we then discuss some greedy heuristic algorithms for these problems.
more analysis of double hashing in [gs78] a deep and elegant analysis showed that double hashing was equivalent to the ideal uniform hashing up to a load factor of about 0.319. in this paper we give an analysis which extends this to load factors arbitrarily close to 1. we understand from [ko86, gu87] that ajtai, guibas, koml&oacute;s, and szemer&eacute;di obtained this result in the first part of 1986; the analysis in this paper is of interest nonetheless because we demonstrate how a resampling technique can be used to obtain a remarkably simple proof.
straight-line program length as a parameter for complexity measures this paper represents a continuation of work in [lbi] and [lb2] directed toward the development of a unified, relative model for complexity theory. the earlier papers establish a simple, natural and fairly general model, and demonstrated its attractiveness by using it to state and prove a variety of technical results. the present paper uses the same model but deals more specifically with the problems involved in stating complexity bounds in a usable closed form for arbitrary operations on arbitrary data types. work currently in progress is directed toward similar unified treatment of complexity of data structures.
fast allocation of nearby resources in a distributed system dijkstra's informally-stated dining philosophers problem [d] involves a number n of philosophers sitting in a circle, a single fork between each pair of adjacent philosophers. the problem is to program the philosophers in ways which guarantee certain conditions of fairness and absence of deadlock. in this paper, the problem is generalized to a distributed system resource allocation problem which is local in two senses. first, although the system and number of users can be very large, there is a limit to the overlap in resource demands of different users. the second condition can be thought of as a property of the geography of the network - the resources are (or can be) located in the network in such a way that communication between a user and any of its required resources is fast.
efficient reducibility between programming systems: preliminary report much of the research on semantic theories has concentrated on qualitative properties such as definability (of such programming concepts as recursive procedures), equivalence (of different language constructs), and verifiability (of the correctness, or consistency, of one expression relative to another). current qualitative theories are in a tentative state and much remains to be done. however, there is also a quantitative side to semantics. indeed, many of the questions which any semantic theory must answer are at once qualitative and quantitative. we would like to draw upon complexity-theoretic techniques to answer such questions. we are currently working on the development of new algebraic constructs to provide a mathematical framework for both qualitative and quantitative analysis of semantic problems.
sets that don't help this paper contains several results yielding pairs of problems which don't help each other's solution, and therefore which may be said to be complex for &ldquo;different reasons.&rdquo; statements are formalized and results proved within blum complexity theory, generalized to relative algorithms. the approach is fairly intuitive; all details appear in [1] and [2].
bounds for the computational power and learning complexity of analog neural nets. it is shown that high-order feedforward neural nets of constant depth with piecewise-polynomial activation functions and arbitrary real weights can be simulated for boolean inputs and outputs by neural nets of a somewhat larger size and depth with heaviside gates and weights from {-1, 0, 1}. this provides the first known upper bound for the computational power of the former type of neural nets. it is also shown that in the case of first-order nets with piecewise-linear activation functions one can replace arbitrary real weights by rational numbers with polynomially many bits without changing the boolean function that is computed by the neural net. in order to prove these results, we introduce two new methods for reducing nonlinear problems about weights in multilayer neural nets to linear problems for a transformed set of parameters. these transformed parameters can be interpreted as weights in a somewhat larger neural net.as another application of our new proof technique we show that neural nets with piecewise-polynomial activation functions and a constant number of analog inputs are probably approximately correct (pac) learnable (in valiant's model for pac learning [comm. assoc. comput. mach., 27 (1984), pp. 1134--1142]).
two tapes are better than one for off-line turing machines we prove the first superlinear lower bound for a concrete decision problem in p on a turing machine with one work tape and a two-way input tape (also called: off-line 1-tape turing machine). in particular we show for off-line turing machines that 2 tapes are better than 1 and that 3 pushdown stores are better than 2 (both in the deterministic and in the nondeterministic case).
on contention resolution protocols and associated probabilistic phenomena. consider an on-line scheduling problem in which a set of abstract processes are competing for the use of a number of resources. further assume that it is either prohibitively expensive or impossible for any two of the processes to directly communicate with one another. if several processes simultaneously attempt to allocate a particular resource (as may be expected to occur, since the processes cannot easily coordinate their allocations), then none succeed. in such a framework, it is a challenge to design efficient contention resolution protocols.two recently-proposed approaches to the problem of pram emulation give rise to scheduling problems of the above kind. in one approach, the resources (in this case, the shared memory cells) are duplicated and distributed randomly. we analyze a simple and efficient deterministic algorithm for accessing some subset of the duplicated resources. in the other approach, we analyze how quickly we can access the given (nonduplicated) resource using a simple randomized strategy. we obtain precise bounds on the performance of both strategies. we anticipate that our results with find other applications.
classification of computable functions by primitive recursive classes a classification of all the computable functions is given in terms of subrecursive programming languages. these classes are those which also arise from the relation &ldquo;primitive recursive in.&rdquo; by distinguishing between honest and dishonest classes the classification is related to the computational complexity of the functions classified, and the classification has a wide degree of measure invariance. the structure of the honest and dishonest classes under inclusion is explored. it is shown that any countable partial ordering can be embedded in the honest or in the dishonest classes. the honest classes are dense in themselves, and the dishonest classes are dense in the honest classes. every honest class is minimal over some dishonest class, but there is a dishonest class with no honest class minimal over it. every honest class is the intersection (g.l.b.) of two incomparable honest classes, but there are incomparable pairs of honest classes with no g.l.b. it follows that the upper semi-lattice of the recursive degrees of primitive recursiveness is not a lattice. finally, no r.e. increasing sequence of honest classes has a l.u.b.
a new proof of the weak pigeonhole principle. the exact complexity of the weak pigeonhole principle is an old and fundamental problem in proof complexity. using a diagonalization argument, j. b. paris et al. (j. symbolic logic 53 (1988), 1235-1244) showed how to prove the weak pigeonhole principle with bounded-depth, quasipolynomialsize proofs. their argument was further refined by j. krajícek (j. symbolic logic 59 (1994), 73-86). in this paper, we present a new proof: we show that the weak pigeonhole principle has quasipolynomial-size lk proofs where every formula consists of a single and/or of polylog fan-in. our proof is conceptually simpler than previous arguments, and is optimal with respect to depth.
minimum covers in the relational database model (extended abstract) numerous algorithms concerning relational databases use a cover for a set of functional dependencies as all or part of their input. examples are bernstein and beeri's synthesis algorithm [bb] and the tableau modification algorithm of aho, beeri, and ullman [abu]. the performance of these algorithms may depend both on the number of functional dependencies in the cover and the total size of the cover. starting with a smaller cover will make such algorithms run faster. after bernstein [be75], many researchers believe the problem of finding a minimum cover is np-complete. we show that minimum covers can be found in polynomial time, using the notion of direct determination. the proof details the structure of minimum covers, refining the structure bernstein and beeri show for non-redundant covers [bb]. the kernel algorithm of lewis, sekino, and ting [lst] is improved using these results.
on the angular resolution of planar graphs it is a well-known fact that every planar graph admits a planar straight-line drawing. the angular resolution of such a drawing is the minimum angle subtended by any pair of incident edges. the angular resolution of the graph is the supremum angular resolution over all planar straight-line drawings of the graph. in a recent paper by formann et al. [proc. 31st ieee sympos. on found. of comput. sci., 1990, pp. 86-95], the following question is posed: does there exist a constant $r(d) > 0$ such that every planar graph of maximum degree $d$ has angular resolution $\geq r(d)$ radians? the present authors show that the answer is yes and that it follows easily from results in the literature on disk-packings. the conclusion is that every planar graph of maximum degree $d$ has angular resolution at least $\alpha^d$ radians, $0
byzantine quorum systems. quorum systems are well-known tools for ensuring the consistency and availability of replicated data despite the benign failure of data repositories. in this paper we consider the arbitrary (byzantine) failure of data repositories and present the first study of quorum system requirements and constructions that ensure data availability and consistency despite these failures. we also consider the load associated with our quorum systems, i.e., the minimal access probability of the busiest server. for services subject to arbitrary failures, we demonstrate quorum systems over <i>n</i> servers with a load of <i>o</i>(1/√<i>n</i>), thus meeting the lower bound on load for benignly fault-tolerant quorum systems. we explore several variations of our quorum systems and extend our constructions to cope with arbitrary client failures.
competitive algorithms for on-line problems an on-line problem is one in which an algorithm must handle a sequence of requests, satisfying each request without knowledge of the future requests. examples of on-line problems include scheduling the motion of elevators, finding routes in networks, allocating cache memory, and maintaining dynamic data structures. a competitive algorithm for an on-line problem has the property that its performance on any sequence of requests is within a constant factor of the performance of any other algorithm on the same sequence. this paper presents several general results concerning competitive algorithms, as well as results on specific on-line problems.
np-complete decision problems for quadratic polynomials in this article we show the np-completeness of some simple number-theoretic problems. natural simplifications of these problems invariably are known to be in p. our research was motivated by the question whether one could study non-deterministic computation without loss of generality on a restricted, number theoretically significant class of nondeterministic turing machines, the nondeterministic diophantine machines defined below [1,2]. the results suggest this is true. because of the relative difficulty of the reduction of the satisfiability problem used in the proof, and the distinctly number-theoretic character of the problems shown to be np-complete, we hope that the np-completeness of these problems will play a role in showing the np-completeness of further problems of a numerical nature, much as the satisfiability problem has in showing the np-completeness of combinatorial problems ([3],[5]). the results illustrate an intimate connection between problems in computational theory, such as &ldquo;p&equil;np?&rdquo;, and problems in number theory, e.g. about quadratic congruences in one unknown, which are just beyond the range in which efficient algorithms exist. thus our work exposes an interface between the state-of-the-art in number theory and in the theory of computation. also, our results can be seen as the solution to a natural and important revision of hilbert's 10thproblem: give a feasible algorithmic procedure to decide whether an arbitrary diophantine equation has solutions. unless p&equil;np this is impossible, even for a class of quadratic diophantine equations in two unknowns for which a decision procedure in the original sense is in fact available. certainly, these results present a striking rigorous demonstration that number theorists' intuitions about where problems about diophantine equations and quadratic congruences start to be truly difficult are justified.
know thy neighbor's neighbor: the power of lookahead in randomized p2p networks. several peer-to-peer networks are based upon randomized graph topologies that permit efficient greedy routing, e. g., randomized hypercubes, randomized chord, skip-graphs and constructions based upon small-world percolation networks. in each of these networks, a node has out-degree θ(log n), where n denotes the total number of nodes, and greedy routing is known to take o(log n) hops on average. we establish lower-bounds for greedy routing for these networks, and analyze neighbor-of-neighbor (non)-greedy routing. the idea behind non, as the name suggests, is to take a neighbor's neighbors into account for making better routing decisions.the following picture emerges: deterministic routing networks like hypercubes and chord have diameter θ(log n) and greedy routing is optimal. randomized routing networks like randomized hypercubes, randomized chord, and constructions based on small-world percolation networks, have diameter θ(log n / log log n) with high probability. the expected diameter of skip graphs is also θ(log n / log log n). in all of these networks, greedy routing fails to find short routes, requiring ω(log n) hops with high probability. surprisingly, the non-greedy routing algorithm is able to diminish route-lengths to θ(log n / log log n) hops, which is asymptotically optimal.
second-order mathematical theory of computation in this work we show that it is possible to formalize all properties regularly observed in (deterministic and non-deterministic) algorithms in second-order predicate calculus. moreover, we show that for any given algorithm it suffices to know how to formalize its 'partial correctness' by a second-order formula in order to formalize all other properties by second-order formulas. this result is of special interest since 'partial correctness' has already been formalized in second-order predicate calculus for many classes of algorithms.
formalization of properties of recursively defined functions this paper is concerned with the relationship between the convergence, correctness and equivalence of recursively defined functions and the satisfiability (or unsatisfiability) of certain first-order formulas.
the optimal fixedpoint of recursive programs in this paper a new fixedpoint approach towards the semantics of recursive programs is presented. the fixedpoint defined by a recursive program under this semantics contains, in some sense, the maximal amount of &ldquo;interesting&rdquo; information which can be extracted from the program. this optimal fixedpoint (which always uniquely exists) may be strictly more defined than the program's least fixedpoint. we consider both the theoretical and the computational aspects of the approach, as well as some techniques for proving properties of the optimal fixedpoint of a given recursive program.
on syntax-directed transduction and tree transducers several topics of theoretical and practical importance to the field of translator writing systems are presented in this paper. these are (1). implementation of generalized syntax-directed transduction (gsdt) on a finite-state tree transducer; (2). implementation of gsdt on a tree-walking pushdown store transducer; (3). transformation of the context-free grammar underlying a gsdt and the resulting transformation of the transduction elements of that gsdt; (4). tree transduction of parse trees between equivalent context-free grammars.
the price of selfish routing. we study the problem of routing traffic through a congested network. we focus on the simplest case of a network consisting of m parallel links. we assume a collection of n network users, each employing a mixed strategy which is a probability distribution over links, to control the shipping of its own assigned traffic. given a capacity for each link specifying the rate at which the link processes traffic, the objective is to route traffic so that the maximum expected latency over all links is minimized. we consider both uniform and non-uniform link capacities.how much decrease in global performace is necessary due to the absence of some central authority to regulate network traffic and implement an optimal assignment of traffic to links? we investigate this fundamental question in the context of nash equilibria for such a system, where each network user selfishly routes its traffic only on those links available to it that minimize its expected latency cost, given the network congestion caused by the other users. we use the coordination ratio, defined by koutsoupias and papadimitriou [25] as the ratio of the maximum (over all links) expected latency in the worst possible nash equlibrium, over the least possible maximum latency had global regulation been available, as a measure of the cost of lack of coordination among the network users.
self-stabilizing symmetry breaking in constant-space (extended abstract) we investigate the problem of self-stabilizing round-robin token management scheme on an anonymous bidirectional ring of identical processors, where each processor is an asynchronous probabilistic (coin-flipping) finite state machine which sends and receives messages. we show that the solution to this problem is equivalent to symmetry breaking (i.e., leader election). requiring only constant-size messages and message-passing model has practical implications: our solution can be implemented in high-speed networks using a universal fast hardware switches (i.e., finite state machines) of size independent of the size of the network.
an algorithm for the general petri net reachability problem an algorithm is presented for the general petri net reachability problem based on a generalization of the basic reachability construction which is symmetric with respect to the initial and final marking. sets of transition sequences described by finite automata are used for approximations to firing sequences, and the approximation error is assessed by uniformly constructable presburger expressions. the approximation algorithm is iterated until a sufficient criterion for reachability can be given, not-withstanding the remaining uncertainty.
classes of computable functions defined by bounds on computation: preliminary report the structure of the functions computable in time or space bounded by t is investigated for recursive functions t. the t-computable classes are shown to be closed under increasing recursively enumerable unions; as a corollary the primitive recursive functions are shown to equal the t-computable functions for a certain recursive t. any countable partial order can be isomorphically embedded in the family of t-computable classes partially ordered by set inclusion. for any recursive t, there is a recursive t' which is (approximately) equal to an actual running time such that the t-computable functions equal the t'-computable functions.
the correctness of a modified secd machine landin's secd machine does not completely compute certain expressions of the &lgr;-calculus and so is modified by the addition of an output component and a unique name counter. this modified machine is proven to correctly implement the &lgr;-calculus.
a decision procedure for generalized sequential mapability-onto of regular sets in [1] various problems are solved about the possibility of mapping regular sets into or onto other regular sets by means of a complete sequential machine or a generalized sequential machine under various restraints. one problem in this class has remained open. that problem, as restated on pp. 129-130 of [2], is whether it is &ldquo;recursively solvable to determine for arbitrary regular sets l1 and l2 whether there exists a generalized sequential machine s such that s(l1) &equil; l2.&rdquo; the claim is hereby made on the affirmative solution to this problem. [3] contains an interesting solution to a certain nontrivial subproblem, namely where l1 and l2 are restricted to regular sets with the prefix property.
combinatorial optimization with rational objective functions let a be the problem of minimizing c1x1+...+cnxn subject to certain constraints on x&equil;(x1,...,xn), and let b be the problem of minimizing (a0+a1x1+...+anxn)/(b0+b1x1+...+bnxn) subject to the same constraints, assuming the denominator is always positive. it is shown that if a is solvable within o[p(n)] comparisons and o[q(n)] additions, then b is solvable in time o[p(n)(q(n)+p(n))]. this applies to most of the &ldquo;network&rdquo; algorithms. consequently, minimum ratio cycles, minimum ratio spanning trees, minimum ratio (simple) paths, maximum ratio weighted matchings, etc., can be computed within polynomial-time in the number of variables. this improves a result of e. l. lawler, namely, that a minimum ratio cycle can be computed within a time bound which is polynomial in the number of bits required to specify an instance of the problem. a recent result on minimum ratio spanning trees by r. chandrasekaran is also improved by the general arguments presented in this paper. algorithms of time-complexity o(&brvbar;e&brvbar; &bull; &brvbar;v&brvbar;2&bull;log&brvbar;v&brvbar;) for a minimum ratio cycle and o(&brvbar;e&brvbar; &bull; log2&brvbar;v&brvbar; &bull; log log &brvbar;v&brvbar;) for a minimum ratio spanning tree are developed.
polynomial and abstract subrecursive classes we define polynomial time computable operator. our definition generalizes cook's definition to arbitrary function inputs. polynomial classes are defined in terms of these operators; the properties of these classes are investigated. honest polynomial classes are generated by running time. they posses a modified ritchie-cobham property. a polynomial class is a complexity class iff it is honest. starting from the observation that many results about subrecursive classes hold for all reducibility relations (e.g. primitive recursive in, elementary recursive in), which were studied so far, we define abstract subrecursive reducibility relation. many results hold for all abstract subrecursive reducibilities.
las vegas is better than determinism in vlsi and distributed computing (extended abstract) in this paper we describe a new method for proving lower bounds on the complexity of vlsi - computations and more generally distributed computations. lipton and sedgewick observed that the crossing sequence arguments used to prove lower bounds in vlsi (or tm or distributed computing) apply to (accepting) nondeterministic computations as well as to deterministic computations. hence whenever a boolean function f is such that f and -&-fmarc; (the complement of f, -&-fmarc; -&-equil; 1 -&-minus; f) have efficient nondeterministic chips then the known techniques are of no help for proving lower bounds on the complexity of deterministic chips. in this paper we describe a lower bound technique (thm 1) which only applies to deterministic computations
program size and economy of descriptions: preliminary report restricted programming languages, for example primitive recursive definition schemes, are very often not nearly as succinct in describing primitive recursive functions as a general programming language [1]. we show that as one increases the power of programming languages, one can obtain economies in program size by any recursive amount for even very simple functions. this parallels a situation in the arithmetic hierarchy, where it is possible to get a recursively enumerable set whose smallest recursively enumerable index is much larger than the smallest index for the same set considered, say, as a set recursively enumerable in &oslash;'. these phenomena follow from the fact that the ability to write programs which refer to the universal functions of an enumeration enables one to decrease significantly the size of programs. the notation, when not defined is that of [4].
definability in dynamic logic we study the expressive power of various versions of dynamic logic and compare them with each other as well as with standard languages in the logical literature. one version of dynamic logic is equivalent to the infinitary logic lck&ohgr;1&ohgr;, but regular dynamic logic is strictly less expressive. in particular, the ordinals &ohgr;&ohgr; and &ohgr; &ohgr;.2 are indistinguishable by formulas of regular dynamic logic.
on the expressive power of dynamic logic (preliminary report) we show that &ldquo;looping&rdquo; of while-programs can be expressed in regular first-order dynamic logic, disproving a conjecture made in [harel-pratt 1978]. in addition we show that the expressive power of quantifier-free dynamic logic increases when nondeterminism is introduced in the programs that are part of formulae of dynamic logic. allowing assignments of random values to variables increases the expressive power even further.
linear representation of tree structure: a mathematical theory of parenthesis-free notations in this paper we present a substantially general theory of parenthesis-free notations for finite plane trees. we obtain stronger one-to-oneness results, including a characterization of one-to-oneness for a large class of notations, and a quite general sufficient condition for one-to-oneness that involves the recursive structure of plane trees in what appears to be a minimal way. we then study various properties of notations that promise to be of practical interest. the two most important of these&mdash;single scan bottom-up readability, and single scan top-down readability&mdash;both turn out to be particular cases of our general sufficient condition for one-to-oneness. we formulate simple descriptions of all notations that have one or the other of these properties, and find a simple transformation of notations that establishes a one-to-one correspondence between them. the unique fixed point of this transformation turns out to be the only notation single scan readable in both directions.
profit-earning facility location. we consider opening facilities in order to gain a profit. we are given a set of demand points, and we must open some set of facilities such that every demand may be satisfied from a local facility and the total profit gained in this process is maximized. this contrasts with previous work on facility location and k-center problems, where opening a facility incurred a cost. the profit gained by opening a facility is a function of the amount of demand the facility satisfies. we model the dependence of profit on demand by creating many different possible facilities at each location, each of which provides a certain profit if opened and requires at least a certain amount of demand in order to open. our model captures problem instances where profits may be positive or negative, and also instances where it is not necessary to satisfy every demand. our algorithms provide the optimum total profit, while stretching the definition of locality by a constant and violating the required demands by a constant. we prove that without this stretch, the problem becomes np-hard to approximate.
local zero knowledge. we put forward the notion of local zero knowledge and provide its first implementations in a variety of settings under standard complexity assumptions.whereas the classical notion of zero knowledge guarantees the secrecy only of information that is hard to compute, the new one meaningfully guarantees the secrecy of any information (in case of perfect zero-knowledge, and asymptotically in all other cases). consequently, local zero knowledge remains very meaningful even if dp = np.
improved cryptographic hash functions with worst-case/average-case connection. we define a new family of collision resistant hash functions whose security is based on the worst case hardness of approximating the covering radius of a lattice within a factor o(t n^2 log n), where t is a value between 1 and sqrt(n) that depends on the solution of the closest vector problem in certain "almost perfect" lattices. using standard transference theorems from the geometry of numbers, our result immediately gives a connection between the worst-case and average-case complexity of the shortest vector problem with connection factor o(t n^3 log n).
construction with parallel derivatives of the closure of a parallel program schema the parallel derivative of a set of strings is introduced. given a serial, repetition-free parallel program schema, its closure is constructed by taking parallel derivatives of its set of computations. the construction resembles the construction of a state diagram from a regular expression by means of derivatives.
toward mechanical verification of properties of roundoff error propagation in this paper we will be concerned with portions of roundoff analysis which can be automated. conditions are given under which proofs of numerical stability can be performed completely automatically and very economically (in particular, in polynomial time). we also discuss the use of &ldquo;numerical heuristics&rdquo; which apply &ldquo;hill-climbing&rdquo; methods to functionals measuring contamination from roundoff. in section 2 we will relate this work to the extensive literature on roundoff error. two properties of error propagation in straight-line programs are defined in section 3, and their relationship demonstrated in theorem 1. the properties are guaranteed to be effectively decidable since they can be formulated in the first-order theory of real-closed fields. in section 4 we present sufficient conditions for the properties to hold; conditions which can be checked in time bounded by a polynomial in the size of the given straight-line program.
computational complexity and numerical stability limiting consideration to algorithms satisfying various numerical stability requirements may change lower bounds for computational complexity and/or make lower bounds easier to prove. we will show that, under a sufficiently strong restriction upon numerical stability, any algorithm for multiplying two n&times;n matrices using only +, &minus; and &times; requires at least n3 multiplications. we conclude with a survey of results concerning the numerical stability of several algorithms which have been considered by complexity theorists.
riemann's hypothesis and tests for primality the purpose of this paper is to present new upper bounds on the complexity of algorithms for testing the primality of a number. the first upper bound is 0(n&frac17;); it improves the previously best known bound of 0(n&frac14;) due to pollard [11]. the second upper bound is dependent on the extended riemann hypothesis (erh): assuming erh, we produce an algorithm which tests primality and runs in time 0((log n)4) steps. thus we show that primality is testable in time a polynomial in the length of the binary representation of a number. finally, we give a partial solution to the relationship between the complexity of computing the prime factorization of a number, computing the euler phi function, and computing other related functions.
graph isomorphism, general remarks an open question is the computational complexity of recognizing when two graphs are isomorphic. in an attempt to answer this question we shall analyze the relative computational complexity of generalizations and restrictions of the graph isomorphism problem. in the first section we show graph isomorphism of regular undirected graphs is complete over isomorphism of explicitly given structures (say tarski models from logic). then we show that valence seems to be important. finally we analyze symmetric cubic graphs.
isomorphism testing for graphs of bounded genus we present an algorithm which determines isomorphism of graphs in vo(g)steps where v is the number of vertices and g is the genus of the graphs. in [fmr 79] an algorithm was presented for embedding graph on surfaces of genus g in vo(g) steps. here we show how to extend this algorithm to isomorphism testing for graphs of small genus. this result is noteworthy for at least two reasons. first, this extends the polynomial time isomorphism results for the plane [ht 72] and also the projective plane [l 80] to arbitrary surfaces. second, this gives one of the few known natural decompositions of the isomorphism problem into an infinite hierarchy of problems po,p1,... such that isomorphism testing of problems in p1 is decidable in time vo(i).
finding small simple cycle separators for 2-connected planar graphs we show that every 2-connected triangulated planar graph with n vertices has a simple cycle c of length at most 4@@@@n which separates the interior vertices a from the exterior vertices b such that neither a nor b contains more than 2/3n vertices. the method also gives a linear time algorithm for finding the simple cycle. in general, if the maximum face size is d then we exhibit a cycle c as above of size at most 2@@@@2d&bull;n.
a new graph triconnectivity algorithm and its parallelization we present a new algorithm for finding the tri-connected components of an undirected graph. the algorithm is based on ear decomposition and has linear sequential running time. it also has a parallel implementation on a crcw pram with o(log2n) parallel time using a linear number of processors, where n is the number of vertices in the graph. this is the first efficient parallel algorithm for graph tri-connectivity.
dynamic parallel complexity of computational circuits the dynamic parallel complexity of general computational circuits (defined in introduction) is discussed. we exhibit some relationships between parallel circuit evaluation and some uniform closure properties of a certain class of unary functions and present a systematic method for the design of processor efficient parallel algorithms for circuit evaluation. using this method: (1) we improve the algorithm for parallel boolean circuit evaluation; (2) we give a nontrivial upper bound for parallel min-max-plus circuit evaluation; (3) we partially answer the first open question raised in [mirk85] by showing that all circuits over finite noncommutative semi-ring and circuits over infinite non-commutative semi-ring which has finite dimension over a commutative semi-ring can be evaluated in polylogarithmic time in its size and degree using m(n) processors. moreover, we develop a theory for determining closure properties of certain classes of unary functions.
on formulating simultaneity for studying parallelism and synchronization when studying parallel computation and synchronization one is faced with the problem of modeling the simultaneous execution of processes. although there has been a multitude of formal means for representing such problems [2, 6, 9, 10, 13, 14, 15], invariably, when all the other complexities of the models have been stripped away, the parallelism or synchronization is studied via sequences of events. in all of these studies simultaneity of events is not studied directly. rather, it is represented by the interleaving of the separate events into sequences, and by studying properties of the set of all such sequences.
lower bounds for union-split-find related problems on random access machines. we prove =(clog logn ) lower bounds on the random access machine complexity of several dynamic, partially dynamic and static data structure problems, including the union-split-find problem, dynamic prefix problems and one-dimensional range query problems. the proof techniques include a general technique using perfect hashing for reducing static data structure problems (with a restriction of the size of the structure) into partially dynamic data structure problems (with no such restriction), thus providing a way to transfer lower bounds. we use a generalization of a method due to ajtai for proving the lower bounds on the static problems, but describe the proof in terms of communication complexity, revealing a striking similarity to the proof used by karchmer and wigderson for proving lower bounds on the monotone circuit depth of connectivity.
complete axiomatization of algorithmic properties of program schemes with bounded nondeterministic interpretations propositional algorithmic logic pal is a propositional counterpart of algorithmic logics. it investigates properties of program connectives: begin...end, while...do, if..then..else, or .... pal supplies tools for reasoning about programs constructed from program variables by means of program connectives and about their algorithmic properties. sound rules of inference and tautologies of pal are as important in analysis of programs (e.g. verification) as tautologies of classical propositional calculus. on the other hand propositional algorithmic theories are of highest interest, since they can capture properties of data structures and also algorithmic properties of behaviours of concurrent systems. we proved that the semantical and the syntactical consequence operations coincide (completeness property) and that the model existence theorem holds.
fast computation of gcds an integer greatest common divisor (gcd) algorithm due to sch&ouml;nhage is generalized to hold in all euclidean domains which possess a fast multiplication algorithm. it is shown that if two n precision elements can be multiplied in o(n loga n), then their gcd can be computed in o(n loga+1 n). as a consequence, a new faster algorithm for multivariate polynomial gcd's can be derived and with that new bounds for rational function manipulation.
the glauber dynamics on colourings of a graph with high girth and maximum degree. we prove that the glauber dynamics on the c-colorings of a graph g on n vertices with girth g and maximum degree $\delta$ mixes rapidly if (i) $c=q\delta$ and $q>q^*$, where $q^*=1.4890\ldots$ is the root of $(1-{\rm e}^{-1/q})^2+q{\rm e}^{-1/q}=1$; and (ii) $\delta\geq d\log n$ and $g\geq d\log\delta$ for some constant d=d(q). this improves the bound of roughly $1.763\delta$ obtained by dyer and frieze [ proceedings of the 32nd annual symposium on foundations of computer science, 2001] for the same class of graphs. our bound on this class of graphs is lower than the bound of $11\delta/6\approx1.833\delta$ obtained by vigoda [j. math. phys., 41 (2000), pp. 1555--1569] for general graphs.
models and thresholds for random constraint satisfaction problems. we introduce a class of models for random constraint satisfaction problems. this class includes and generalizes many previously studied models. we characterize those models from our class which exhibit thresholds for satisfiability in the sense that the limiting probability of satisfiability changes significantly as the number of constraints increases. we also discuss models which exhibit sharp thresholds in the sense that the limiting probability jumps from 0 to 1 suddenly.
colouring graphs when the number of colours is nearly the maximum degree. we consider for graphs of maximum degree &dgr;, the problem of determining whether &khgr;g) > &dgr;-k for various values of k. we obtain sharp theorems characterizing when the barrier to &dgr;-k colourability must be a local condition, i.e. a small subgraph, and when it can be global. we also show that for large fixed &dgr;, this problem is either np-complete or can be solved in linear time, and we determine precisely which values of k correspond to each case prove that hitting set with sets of size b is hard to approximate to within a factor $b^{1/19}$. the problem can be approximated to within a factor b [19], and it is the vertex cover problem for b=2. the relationship between hardness of approximation and set size seems to have not been explored before.
bandwidth constrained np-complete problems bandwidth restrictions are considered on several np-complete problems, including the following problems: (1) 3-satisfiability, (2) independent set and vertex cover, (3) simple max cut (4) partition into triangles, (5) 3-dimensional matching, (6) exact cover by 3 sets, (7) dominating set, (8) graph grundy numbering (for graphs of finite degree), (9) 3-colorability, (10) directed and undirected hamiltonian circuit, (11) bandwidth minimization, and (12) feedback vertex set and feedback arc set. it is shown that each of the problems (1)-(12) when restricted to graphs (formulas, triples, or sets) of bandwidth bounded by a function f is log space hard for the complexity class ntisp (poly,f(n)). (ntisp(poly,f(n)) denotes the family of problems solvable nondeterministically in polynomial time and simultaneous f(n) space, e.g., ntisp(poly,poly) &equil; np and ntisp(poly, log n) &equil; nspace(log n).). in fact, (1)-(9) are log space complete for ntisp(poly,f(n)) when the bandwidth is bounded by the function f. this means, for example, that (1)-(9) provide several new examples of problems complete for nspace(log n), and hence solvable in polynomial time deterministically, when restricted to bandwidth log2n. in general, for a function f, if any of the problems (1)-(12), when restricted to bandwidth f(n), could be solved deterministically in polynomial time, then ntisp(poly, f(n)) @@@@ p. (this does not seem particularly likely even when f(n) &equil; log2n.) this indicates that several np-complete problems become easier with diminishing bandwidth. however, they remain intractable unless the bandwidth is restricted to c-log2n, for some c>0.
edge isoperimetry and rapid mixing on matroids and geometric markov chains. we show how to bound the mixing time and log-sobolev constants of markov chains by bounding the edge-isoperimetry of their underlying graphs. to do this we use two recent techniques, one involving average conductance and the other log-sobolev constants. we show a sort of strong conductance bound on a family of geometric markov chains, give improved bounds for the mixing time of a markov chain on balanced matroids, and in both cases find lower bounds on the log-sobolev constants of these chains.
the mixing time of the thorp shuffle. the thorp shuffle is defined as follows. cut the deck into two equal piles. drop the first card from the left pile or the right pile according to the outcome of a fair coin flip; then drop from the other pile. continue this way until both piles are empty. we show that the mixing time for the thorp shuffle with 2d cards is polynomial in d.
a result on the relationship between simple precedence languages and reducing transition languages two of the more recently published systems for the efficient parsing of subclasses of deterministic, context-free languages are the backwards-deterministic, (or unambiguous, as they were originally called) simple precedence languages due to wirth and weber, and the reducing transition languages due to eickel, paul, bauer, and samelson. the main result demonstrated in this paper is that the backwards-deterministic, simple precedence languages are a proper subclass of the reducing transition languages. the reducing transition languages are certainly a subclass of the deterministic, context-free (lr(1)) languages but it is not known if this inclusion is proper. the major complaint against the reducing transition languages is the large amount of memory required when this technique is utilized with large grammars, such as the algol 60 grammar. with memory costs and physical memory sizes decreasing at a rapid rate, it is very possible that this disadvantage will not exist in the not-too-distant future. when this becomes true, the advantage of reducing transition languages, i.e., the relatively small amount of time required for their parsing, may result in their significance being substantially increased. thus it is of some import that we study their relationship to other languages. the main result is based on two theorems: (1) if g is a backwards-deterministic simple precedence grammar, then g is a reducing transition grammar; and (2) the language l1 &equil; {a0n1n2m&brvbar;m,n &ge; 1} &ugr; {b0n1m2n&brvbar;m,n &ge; 1} is a reducing transition language but is not a backwards-deterministic simple precedence language.
recursion schemes with lists scheme translation is used to compare the abilities of languages obtained by augmenting recursion schemes with lists, markers, and functional values. it is shown that the first two additions make orthogonal contributions to the language's power. theorems 4 and 5 appear to be new results.
evolving sets and mixin. we show that a new probabilistic technique, recently introduced by the first author, yields the sharpest bounds obtained to date on mixing times in terms of isoperimetric properties of the state space (also known as conductance bounds or cheeger inequalities). we prove that the bounds for mixing time in total variation obtained by lovasz and kannan, can be refined to apply to the maximum relative deviation |pn(x,y)/π(y)-1| of the distribution at time n from the stationary distribution π. our approach also yields a direct link between isoperimetric inequalities and heat kernel bounds; previously, this link rested on analytic estimates known as nash inequalities.
on dynamic range reporting in one dimension. we consider the problem of maintaining a dynamic set of integers and answering queries of the form: report a point (equivalently, all points) in a given interval. range searching is a natural and fundamental variant of integer search, and can be solved using predecessor search. however, for a ram with w-bit words, we show how to perform updates in o(lg w) time and answer queries in o(lg lg w) time. the update time is identical to the van emde boas structure, but the query time is exponentially faster. existing lower bounds show that achieving our query time for predecessor search requires doubly-exponentially slower updates. we present some arguments supporting the conjecture that our solution is optimal.our solution is based on a new and interesting recursion idea which is "more extreme" that the van emde boas recursion. whereas van emde boas uses a simple recursion (repeated halving) on each path in a trie, we use a nontrivial, van emde boas-like recursion on every such path. despite this, our algorithm is quite clean when seen from the right angle. to achieve linear space for our data structure, we solve a problem which is of independent interest. we develop the first scheme for dynamic perfect hashing requiring sublinear space. this gives a dynamic bloomier filter (a storage scheme for sparse vectors) which uses low space. we strengthen previous lower bounds to show that these results are optimal.
sub-constant error low degree test of almost-linear size. given a function f:fm→f over a finite field f, a low degree tester tests its agreement with an m-variate polynomial of total degree at most d over f. the tester is usually given access to an oracle a providing the supposed restrictions of f to affine subspaces of constant dimension (e.g., lines, planes, etc.). the tester makes very few (probabilistic) queries to f and to a (say, one query to f and one query to a), and decides whether to accept or reject based on the replies.we wish to minimize two parameters of a tester: its error and its size. the error bounds the probability that the tester accepts although the function is far from a low degree polynomial. the size is the number of bits required to write the oracle replies on all possible tester's queries.low degree testing is a central ingredient in most constructions of probabilistically checkable proofs (pcps) and locally testable codes (ltcs). the error of the low degree tester is related to the soundness of the pcp and its size is related to the size of the pcp (or the length of the ltc).we design and analyze new low degree testers that have both sub-constant error o(1) and almost-linear size n1+o(1) (where n=|f|m). previous constructions of sub-constant error testers had polynomial size [13, 16]. these testers enabled the construction of pcps with sub-constant soundness, but polynomial size [13, 16, 9]. previous constructions of almost-linear size testers obtained only constant error [13, 7]. these testers were used to construct almost-linear size ltcs and almost-linear size pcps with constant soundness [13, 7, 5, 6, 8].
approximation algorithms for constrained for constrained node weighted steiner tree problems. we consider a class of optimization problems, where the input is an undirected graph with two weight functions defined for each node, namely the node's profit and its cost. the goal is to find a connected set of nodes of low cost and high profit. we present approximation algorithms for three natural optimization criteria that arise in this context, all of which are np-hard. the budget problem asks for maximizing the profit of the set subject to a budget constraint on its cost. the quota problem requires minimizing the cost of the set subject to a quota constraint on its profit. finally, the prize collecting problem calls for minimizing the cost of the set plus the profit (here interpreted as a penalty) of the complement set. for all three problems, our algorithms give an approximation guarantee of o(\log n), where n is the number of nodes. to the best of our knowledge, these are the first approximation results for the quota problem and for the prize collecting problem, both of which are at least as hard to approximate as set cover. for the budget problem, our results improve on a previous o(\log^2 n) result of guha, moss, naor, and schieber. our methods involve new theorems relating tree packings to (node) cut conditions. we also show similar theorems (with better bounds) using edge cut conditions. these imply bounds for the analogous budget and quota problems with edge costs which are comparable to known (constant factor) bounds.
learning juntas. we consider a fundamental problem in computational learning theory: learning an arbitrary boolean function which depends on an unknown set of k out of n boolean variables. we give an algorithm for learning such functions from uniform random examples which runs in time roughly (nk)ω/(ω + 1), where ω < 2.376 is the matrix multiplication exponent. we thus obtain the first polynomial factor improvement on the naive nk time bound which can be achieved via exhaustive search. our algorithm and analysis exploit new structural properties of boolean functions.
learning nonsingular phylogenies and hidden markov models. in this paper, we study the problem of learning phylogenies and hidden markov models. we call a markov model nonsingular if all transition matrices have determinants bounded away from 0 (and 1). we highlight the role of the nonsingularity condition for the learning problem. learning hidden markov models without the nonsingularity condition is at least as hard as learning parity with noise. on the other hand, we give a polynomial-time algorithm for learning nonsingular phylogenies and hidden markov models.
conditions on input vectors for consensus solvability in asynchronous distributed systems. this article introduces and explores the condition-based approach to solve the consensus problem in asynchronous systems. the approach studies conditions that identify sets of input vectors for which it is possible to solve consensus despite the occurrence of up to f process crashes. the first main result defines acceptable conditions and shows that these are exactly the conditions for which a consensus protocol exists. two examples of realistic acceptable conditions are presented, and proved to be maximal, in the sense that they cannot be extended and remain acceptable. the second main result is a generic consensus shared-memory protocol for any acceptable condition. the protocol always guarantees agreement and validity, and terminates (at least) when the inputs satisfy the condition with which the protocol has been instantiated, or when there are no crashes. an efficient version of the protocol is then designed for the message passing model that works when f < n/2, and it is shown that no such protocol exists when f &ge; n/2. it is also shown how the protocol's safety can be traded for its liveness.
expanding graphs and the average-case analysis of algorithms for matchings and related problems hall's theorem states that a bipartite graph has a perfect matching if and only if every set of vertices has an equal number of neighbours. equivalently, it states that every non-maximum matching has an augmenting path if the graph is an expander with expansion 1. we use this insight to demonstrate that if a graph is an expander with expansion more than one than every non-maximum matching has a short augmenting path and, therefore, the bipartite matching algorithm performs much better on such graphs than in the worst case. we then apply this idea to the average case analysis of various augmenting path algorithms and to the approximation of the permanent. in particular, we demonstrate that the following algorithms perform much better on the average than in the worst case. in fact, they will rarely exhibit their worst-case running times. hopcroft-karp's algorithm for bipartite matchings. micali-vazirani's and even-kariv's algorithms for non-bipartite matchings. gabow-tarjan's parallel algorithm for bipartite matchings. dinic's algorithm for k-factors and 0-1 network flows. jerrum-sinclair's approximation scheme for the permanent. it seems rather surprising that the algorithms which are the fastest known for worst-case inputs also do exceedingly on almost every graph.
on optimal slicing of parallel programs. optimal program slicing determines for a statement s in a program &pgr; whether or not s affects a specified set of statements, given that all conditionals in &pgr; are interpreted as non-deterministic choices.only recently, it has been shown that reachability of program points and hence also optimal slicing is undecidable for multi-threaded programs with (parameterless) procedures and synchronization [23]. here, we sharpen this result by proving that slicing remains undecidable if synchronization is abandoned---although reachability becomes polynomial. moreover, we show for multi-threaded programs without synchronization, that slicing stays pspace-hard when procedure calls are forbidden, and becomes np-hard for loop-free programs. since the latter two problems can be solved in pspace and np, respectively, even in presence of synchronization, our new lower bounds are tight.finally, we show that the above decidability and lower bound properties equally apply to other simple program analysis problems like copy constant propagation and true liveness of variables. this should be contrasted to the problems of strong copy constant propagation and (ordinary) liveness of variables for which polynomial algorithms have been designed [15, 14, 24].
pushdown automata, graphs, ends, second-order logic, and reachability problems we have discovered a very strong connection between certain areas of theoretical computer science&mdash;the theory of context-free languages and pushdown automata, tiling problems, cellular automata, and vector addition systems&mdash;and certain concepts from group theory, topology, and second-order logic. we use these concepts to investigate a rather wide class of graphs which we call context-free graphs. using the results obtained and rabin's theorem that the monadic second-order theory of the infinite binary tree is decidable, we are able to show that the monadic second-order theory of any context-free graph is decidable. cellular automata and vector addition systems are usually considered as involving the grid of integer lattice points in n-dimensional space. we show that such systems make sense on a very general class of graphs and, in contrast to the classical case, all the relevant algorithmic problems concerning such systems are solvable on context-free graphs.
searching a two key table under a single key we present a method for arranging an arbitrary 2-key table as an n by 2 array such that a search can be performed under either key in o(lg2n lglg n) time. this is in sharp contrast with an &ohgr;(&radic;n) lower bound for the problem under a model in which all comparisons must involve the value being searched for.
implicit data structures (preliminary draft) we consider representations of data structures in which the relative ordering of the values stored is implicit in the pattern in which the elements are retained, rather than explicit in pointers. several implicit schemes for storing data are introduced to permit efficient implementation of the instructions insert, delete and find. &thgr;(@@@@n) basic operations are shown to be necessary and sufficient, in the worst case, to perform these instructions provided that the data elements are kept in some fixed partial order. we demonstrate, however, that further improvements can be made if an arrangement other than a fixed partial order is used. a structure, based on a fixed partial order, is introduced to facilitate multiple key searches. this structure, together with the retrieval scheme based upon it, is shown to be within a constant factor of the optimal one based on a partial order.
communication preserving protocols for secure function evaluation. a secure function evaluation protocol allows two parties to jointly compute a function f(x,y) of their inputs in a manner not leaking more information than necessary. a major result in this field is: &ldquo;any function f that can be computed using polynomial resources can be computed securely using polynomial resources&rdquo; (where &ldquo;resources&rdquo; refers to communication and computation). this result follows by a general transformation from any circuit for f to a secure protocol that evaluates f. although the resources used by protocols resulting from this transformation are polynomial in the circuit size, they are much higher (in general) than those required for an insecure computation of f.we propose a new methodology for designing secure protocols, utilizing the communication complexity tree (or branching program) representation of f. we start with an efficient (insecure) protocol for f and transform it into a secure protocol. in other words, ``any function f that can be computed using communication complexity c can be can be computed securely using communication complexity that is polynomial in c and a security parameter''. we show several simple applications of this new methodology resulting in protocols efficient either in communication or in computation. in particular, we exemplify a protocol for the millionaires problem, where two participants want to compare their values but reveal no other information. our protocol is more efficient than previously known ones in either communication or computation.
balanced metric labeling. we define the balanced metric labeling problem, a generalization of the metric labeling problem, in which each label has a capacity, i.e., at most l vertices can be assigned to it. the balanced metric labeling problem is a generalization of fundamental problems in the area of approximation algorithms, e.g., arrangements and balanced partitions of graphs. it is also motivated by resource limitations in certain practical scenarios. we focus on the case where the given metric is uniform and note that this case alone encompasses various well-known graph partitioning problems. we present the first (pseudo) approximation algorithm for this problem, achieving for any ε, 0 < ε < 1, an approximation factor of o((ln n)/ε), while assigning at most min {o(ln k)/1 - ε, l + 1| ( 1 + ε) l vertices to each label (k is the number of labels). our approximation algorithm is based on a novel randomized rounding of a linear programming formulation that combines an embedding of the graph in a simplex together with spreading metrics and additional constraints that strengthen the formulation. our randomized rounding technique uses both a randomized metric decomposition technique and a randomized label assignment technique. at the heart of our approach is the fact that only limited dependency is created between the labels assigned to different vertices, allowing us to bound the expected cost of the solution and the number of vertices assigned to each label, simultaneously. we note that the number of vertices assigned to each label is bounded via a new inequality of janson[15] for tail bounds of (partly) dependent random variables.
what can be computed locally? the purpose of this paper is a study of computation that can be done locally in a distributed network, where "locally" means within time (or distance) independent of the size of the network. locally checkable labeling (lcl) problems are considered, where the legality of a labeling can be checked locally (e.g., coloring). the results include the following: there are nontrivial lcl problems that have local algorithms. there is a variant of the dining philosophers problem that can be solved locally. randomization cannot make an lcl problem local; i.e., if a problem has a local randomized algorithm then it has a local deterministic algorithm. it is undecidable, in general, whether a given lcl has a local algorithm. however, it is decidable whether a given lcl has an algorithm that operates in a given time $t$. any lcl problem that has a local algorithm has one that is order-invariant (the algorithm depends only on the order of the processor ids).
anti-presistence: history independent data structures. many data structures give away much more information than they were intended to. whenever privacy is important, we need to be concerned that it might be possible to infer information from the memory representation of a data structure that is not available through its &ldquo;legitimate&rdquo; interface. word processors that quietly maintain old versions of a document are merely the most egregious example of a general problem.we deal with data structures whose current memory representation does not reveal their history. we focus on dictionaries, where this means revealing nothing about the order of insertions or deletions. our first algorithm is a hash table based on open addressing, allowing o(1) insertion and search. we also present a history independent dynamic perfect hash table that uses space linear in the number of elements inserted and has expected amortized insertion and deletion time o(1). to solve the dynamic perfect hashing problem we devise a general scheme for history independent memory allocation. for fixed-size records this is quite efficient, with insertion and deletion both linear in the size of the record. our variable-size record scheme is efficient enough for dynamic perfect hashing but not for general use. the main open problem we leave is whether it is possible to implement a variable-size record scheme with low overhead.
universal one-way hash functions and their cryptographic applications we define a universal one-way hash function family, a new primitive which enables the compression of elements in the function domain. the main property of this primitive is that given an element x. we prove constructively that universal one-way hash functions exist if any 1-1 one-way functions exist. among the various applications of the primitive is a one-way based secure digital signature scheme, a system which is based on the existence of any 1-1 one-way functions and is secure against the most general attack known. previously, all provably secure signature schemes were based on the stronger mathematical assumption that trapdoor one-way functions exist.
a polynomial approximation algorithm for the minimum fill-in problem. in the minimum fill-in problem, one wishes to find a set of edges of smallest size, whose addition to a given graph will make it chordal. the problem has important applications in numerical algebra and has been studied intensively since the 1970s. we give the first polynomial approximation algorithm for the problem. our algorithm constructs a triangulation whose size is at most eight times the optimum size squared. the algorithm builds on the recent parameterized algorithm of kaplan, shamir, and tarjan for the same problem.for bounded degree graphs we give a polynomial approximation algorithm with a polylogarithmic approximation ratio. we also improve the parameterized algorithm.
on learning boolean functions this paper deals with the learnability of boolean functions. an intuitively appealing notion of dimensionality is developed and used to identify the most general class of boolean function families that are learnable from polynomially many positive examples with one-sided error. it is then argued that although bounded dnf expressions lie outside this class, they must have efficient learning algorithms as they are well suited for expressing many human concepts. a framework that permits efficient learning of bounded dnf functions is identified.
on communication over an entanglement-assisted quantum channel. shared entanglement is a resource available to parties communicating over a quantum channel, much akin to public coins in classical communication protocols: the two parties may be given some number of quantum bits jointly prepared in a fixed superposition, prior to communicating with each other. the quantum channel is then said to be "entanglement-assisted."shared randomness does not help in the transmission of information from one party to another. moreover, it does not significantly reduce the classical complexity of computing functions vis-a-vis private-coin protocols. on the other hand, prior entanglement leads to startling phenomena such as "quantum teleportation" and "superdense coding." the problem of characterising the power of prior entanglement has baffled many researchers, especially in the setting of bounded-error protocols. it is open whether it leads to more than a factor of two savings (using superdense coding) or more than an additive~o(\log n) savings (when used to create shared randomness). few lower bounds are known for communication problems in this setting, and are all derived using sophisticated information-theoretic techniques.in this paper, we focus on the most basic problem in the setting of communication over an entanglement-assisted quantum channel, that of communicating classical bits from one party to another. we derive optimal bounds on the number of quantum bits required for this task, for any given probability of error.
linear time low tree-width partitions and algorithmic consequences. classes of graphs with bounded expansion have been introduced in [15], [12]. they generalize both proper minor closed classes and classes with bounded degree.for any class with bounded expansion c and any integer p there exists a constant n(c,p) so that the vertex set of any graph g ∈ c may be partitioned into at most n(c,p) parts, any i ≤ p parts of them induce a subgraph of tree-width at most (i-1) [12] (actually, of tree-depth [16] at most i, what is sensibly stronger). such partitions are central to the resolution of homomorphism problems like restricted homomorphism dualities [14].we give here a simple algorithm to compute such partitions and prove that if we restrict the input graph to some fixed class c with bounded expansion, the running time of the algorithm is bounded by a linear function of the order of the graph (for fixed c and p).this result is applied to get a linear time algorithm for the subgraph isomorphism problem with fixed pattern and input graphs in a fixed class with bounded expansion.more generally, let φ be a first order logic sentence. we prove that any fixed graph property of type "∃x: (|x| ≤ p) ⇿(g[x]=φ)" may be decided in linear time for input graphs in a fixed class with bounded expansion.
zero knowledge with efficient provers. we prove that every problem in np that has a zero-knowledge proof also has a zero-knowledge proof where the prover can be implemented in probabilistic polynomial time given an np witness. moreover, if the original proof system is statistical zero knowledge, so is the resulting efficient-prover proof system. an equivalence of zero knowledge and efficient-prover zero knowledge was previously known only under the assumption that one-way functions exist (whereas our result is unconditional), and no such equivalence was known for statistical zero knowledge. our results allow us to translate the many general results and characterizations known for zero knowledge with inefficient provers to zero knowledge with efficient provers.
binary search trees of bounded balance a new class of binary search trees, called trees of bounded balance, is introduced. these trees are easy to maintain in their form despite insertions and deletions of nodes, and the search time is only moderately longer than in completely balanced trees. trees of bounded balance differ from other classes of binary search trees in that they contain a parameter which can be varied so the compromise between short search time and infrequent restructuring can be chosen arbitrarily.
crew prams and decision trees this paper gives a full characterization of the time needed to compute a boolean function on a crew pram with an unlimited number of processors. the characterization is given in terms of a new complexity measure of boolean functions: the &ldquo;block sensitivity&rdquo;. this measure is a generalization of the well know &ldquo;critical sensitivity&rdquo; measure (see [w], [cdr], [si]). the block sensitivity is also shown to relate to the boolean decision tree complexity, and the implication is that the decision tree complexity also fully characterizes the crew pram complexity. this solves an open problem of [w]. our results imply that changes in the instruction set of the processors or in the capacity of the shared memory cells do not change by more than a constant factor the time required by a crew pram to compute any boolean function. moreover, we even show that a seemingly weaker version of a crew pram, the crow pram ([dr]), can compute functions as quickly as a general crew pram. this solves an open problem of [dr]. finally, our results have implications regarding the power of randomization in the boolean decision tree model. we show that in this model, randomization may only achieve a polynomial speedup over deterministic computation. this was known for las-vegas randomized computation; we prove it also for 1-sided error computation (a quadratic bound) and 2-sided error (a cubic bound).
on the degree of boolean functions as real polynomials every boolean function may be represented as a real polynomial. in this paper we characterize the degree of this polynomial in terms of certain combinatorial properties of the boolean function. our first result is a tight lower bound of &ohgr;(log n) on the degree needed to represent any boolean function that depends on n variables. our second result states that for every boolean function f the following measures are all polynomially related:(1) the decision tree complexity of f. (2) the degree of the polynomial representing f. (3) the smallest degree of a polynomial approximating f in the lmax norm.
symmetric logspace is closed under complement. we present a logspace, many-one reduction from the undirected s-t connectivity problem to its complement. this shows that sl=cosl.
on some families of languages related to the dyck language we recall that the dyck language on the alphabet of 2n letters x &equil; {x1,...,xn,&xmarc;1,...,&xmarc;n} is the equivalence class of the empty word 1 &egr; x@@@@ modulo the thue congruence generated on x@@@@ by the 2n relations xi&xmarc;i &equil; &xmarc;ixi &equil; 1 i &egr; {1,...,n}. indeed for all n &egr; x@@@@ the equivalence class of n modulo this congruence is a non ambiguous algebraic (ie. context-free) language, the complement of which is also a non ambiguous algebraic language. the same situation is true for the congruence generated on x@@@@ by the n relations xi&xmarc;i &equil; 1 i &egr; {1,...,n}. the author convinced himself that many other congruences have the same property [ni 1], and undertook the task of finding them systematically. here is presented a part of the results of this undertaking. an important family of congruences is brought to light which have interesting decidability properties: in the constructions leading to these decidability properties we used as a guide line the nice paper of mac naughton [mcn]. sufficient conditions are given in order that the equivalence classes (and their complements) of such a congruence be an algebraic language. we do not study in this paper the properties of these languages, this will be done elsewhere [ni 2].
ensembles reconnaissables de mots biinfinis the purpose of automata theory is to study and classify those properties of words that may be defined by a finite structure, say a finite automaton or a finite monoid. it seems natural to consider the same problem for infinite words. this amounts to studying the asymptotic behaviour of finite automata. as is well-known, this breaks the equivalence between determinism and non-determinism of finite automata. the study of the infinite behaviour of finite automata is based on a deep theorem due to b-&-uuml;chi and mc naughton: the recognizable sets of infinite words are the finite boolean combinations of deterministic ones (i.e. recognized by deterministic automata). the aim of this paper is to build an analogous theorem for two-sided infinite sequences. we define a biinfinite word as the equivalence class under the shift of a two-sided infinite sequence. the recognizable sets of biinfinite words are defined in a natural way and one is led to a two-sided notion of determinism. this notion seems to be new and justifies the consideration of biinfinite words. the main result of this paper is the extension to biinfinite words of the theorem of b-&-uuml;chi and mc naughton: the recognizable sets of biinfinite words are the finite boolean combinations of deterministic ones (theorem 3.1). there exist three available proofs of b-&-uuml;chi-mc naughton's theorem. the original one by mc naughton [4] is hard to read. the proof given by eilenberg in his book [2] has been constructed by sch-&-uuml;tzenberger and eilenberg from mc naughton's proof; it is similar to that of rabin [5]. finally, sch-&-uuml;tzenberger gave a further proof in [6], which makes the argument more direct by using the methods of the theory of finite monoids. the proof of our main result follows closely sch-&-uuml;tzenberger's method. this method allows to reduce the two-sided case to the one-sided case, although this seems very difficult to obtain directly. in the first section, we briefly recall the theory of the one-sided infinite behaviour of finite automata. in particular, we give sch-&-uuml;tzenberger's proof of b-&-uuml;chi-mc naughton's theorem. the elements of this proof are used in the proof of our main result. in the second section we define the notions of biinfinite word, biautomaton and deterministic biautomaton. the last section contains the proof of our main result.
narrow proofs may be spacious: separating space and width in resolution. the width of a resolution proof is the maximal number of literals in any clause of the proof. the space of a proof is the maximal number of clauses kept in memory simultaneously if the proof is only allowed to infer new clauses from clauses currently in memory. both of these measures have previously been studied and related to the resolution refutation size of unsatisfiable conjunctive normal form (cnf) formulas. also, the minimum refutation space of a formula has been proven to be at least as large as the minimum refutation width, but it has been open whether space can be separated from width or the two measures coincide asymptotically. we prove that there is a family of $k$-cnf formulas for which the refutation width in resolution is constant but the refutation space is nonconstant, thus solving a problem mentioned in several previous papers.
subtree replacement systems: a unifying theory for recursive equations, lisp, lucid and combinatory logic recent work on computation of functions defined by sets of recursive equations by cadiou [ca72], vuillemin [vu74] and downey and sethi [ds76] depends on semantic interpretations of such equations. a purely syntactic, combinatory approach yields similar results for a much wider class of sets of equations, including sets of defining equations for lisp, lucid and the combinator calculus. the application to lisp proves several conjectures of henderson and morris [hm76].
a programming language theorem which is independent of peano arithmetic strongly typed programming languages contain a natural subrecursive part consisting of programs with no loops and no explicitly recursive (circular) function definitions. for languages with polymorphic type structure, such as model, the termination of all loop-free nonrecursive programs is independent of peano arithmetic. an attempt to apply the same techniques to prove independence of the p@@@@np problem can succeed only if np complete problems have almost polynomial complexity.
new degree bounds for polynomial threshold functions. we give new upper and lower bounds on the degree of real multivariate polynomials which sign-represent boolean functions. our upper bounds for boolean formulas yield the first known subexponential time learning algorithms for formulas of superconstant depth. our lower bounds for constant-depth circuits and intersections of halfspaces are the first new degree lower bounds since 1968, improving results of minsky and papert. the lower bounds are proved constructively; we give explicit dual solutions to the necessary linear programs.
approximate max-integral-flow/min-multicut theorems. we establish several approximate max-integral-flow / min-multicut theorems. while in general this ratio can be very large, we prove strong approximation ratios in the case where the min-multicut is a constant fraction ε of the total capacity of the graph. this setting is motivated by several combinatorial and algorithmic applications. prior to this work, a general max-integral-flow / min-multicut bound was known only for the special case where the graph is a tree. we prove that, for arbitrary graphs, the max-integral-flow / min-multicut ratio is o(ε-1 log k), where k is the number of commodites; for graphs excluding a fixed subgraph as a minor (for instance, planar graphs), o(1 / ε); and, for dense graphs, o(1√ε). our proofs are constructive in the sense that we give efficient algorithms which compute either an integral flow achieving the claimed approximation ratios, or a witness that the precondition is violated.
intercalation theorems for stack languages this paper develops necessary conditions for languages to be stack generable, stack decidable, and non-erasing stack generable. the result for stack generable languages shows that the languages {an3&brvbar;n&ge; 0} and {an bn2 cn &brvbar;n&ge;0) are not stack generable. it also shows that the language {am bm2 cn &brvbar;m, n&ge1} &ugr;{am bn2 cn &brvbar;m, n&ge;1} is inherently ambiguous as a stack language. in addition, it shows that the infiniteness problem for stack generable languages is solvable. the necessary conditions for stack decidable and non-erasing stack generable languages show that {an bn2 &brvbar;n&ge;1} &ugr;{an b2n2 c&brvbar;n&ge;1} is not stack decidable and that {an bn2 &brvbar;n&ge;0}is not non-erasing stack generable. these examples show that these two families of languages are not closed under reversal. two unsolvability results are also obtained. the question of whether a stack generable language is inherently ambiguous as a stack language is undecidable. the question of whether the reversal of a non-erasing stack generable language is also non-erasing stack generable is undecidable.
compositions of n tree transducers top-down tree transductions, introduced as models of syntax-directed translations and transformational grammars in [12] and [11], are not closed under relational composition. however, closure under relational composition is not always needed; for example, in establishing closure properties of surface sets.(surface sets are tree-languages obtained as ranges of transductions.) one such closure property, whether the image of a surface set under a transduction is a surface set, remained open. in this paper, we show that transductions need not preserve surface sets. in fact, we exhibit a hierarchy of tree languages obtained by successive transductions. we do not have a good proof that the hierarchy inclusions are proper, but there are strong reasons for so suspecting. as is customary in tree automata papers, we spend some effort on notation. this time, we present a list of first-order axioms for plane (ordered) trees. the gorn-brainerd-doner representation of trees as prefix-closed sets of sequences ([5],[2],[3]) really is a representation in the sense that any (well-founded) abstract tree satisfying our axioms is isomorphic to a prefix-closed set. we then adopt rosen's notation [10] for trees in subsequent definitions. in our opinion, however, a universally acceptable notation remains to be discovered.
the pl hierarchy collapses. it is shown that the pl hierarchy plh = pl ,\bigcup\limits\, plpl ,\bigcup\limits\, plplpl ,\bigcup\limits\, \cdots$, defined in terms of the ruzzo--simon--tompa relativization, collapses to pl.
a characterization of hoare's logic for programs with pascal-like procedures this paper presents a new characterization of applicability and limitations of hoare's logic. we consider a programming language lpas consisting of nondeterministic programs with a pascal-like procedure concept and prove as our main theorem: admissible sublanguages l of lpas have a sound and relatively complete hoare logic if and only if all programs in l have regular formal call trees. moreover, we present an explicit hoare calculus for l whenever such a hoare logic exists. our theorem generalizes clarke's results on completeness and incompleteness for languages with procedures [cl 79] and improves lipton's characterization of hoare's logic which cannot deal with nondeterminism and does not provide explicit calculi [li 77].
an efficient signature scheme based on quadratic equations electronic messages, documents and checks must be authenticated by digital signatures which are not forgeable even by their recipients. the rsa system can generate and verify such signatures, but each message requires hundreds of high precision modular multiplications which can be implemented efficiently only on special purpose hardware. in this paper we propose a new signature scheme which can be easily implemented in software on microprocessors: signature generation requires one modular multiplication and one modular division, signature verification requires three modular multiplications, and the key size is comparable to that of the rsa system. the new scheme is based on the quadratic equation m &equil; s21 + ks22 (mod n), where m is the message, s1 and s2 are the signature, and k and n are the publicly known key. while we cannot prove that the security of the scheme is equivalent to factoring, all the known methods for solving this quadratic equation for arbitrary k require the extraction of square roots modulo n or the solution of similar problems which are at least as hard as factoring. a novel property of the new scheme is that legitimate users can choose k in such a way that they can sign messages even without knowing the factorization of n, and thus everyone can use the same modulus if no one knows its factorization.
elementary bounds for presburger arithmetic we consider the first-order theory whose language has as nonlogical symbols the constant symbols 0 and 1, the binary relation symbols &equil; and <, the unary function symbol &minus; and the binary function symbol + this theory of integers under addition is commonly called the 'presburger arithmetic' and is known to be decidable for truth [presburger (1929), hilbert and bernays (1968)]. we prove here that there exists a decision procedure for this theory, involving quantifier elimination, for which there is a superexponential upper bound on the size of formula produced when all variables have been eliminated.
proving assertions about programs that manipulate data structures in this paper we wish to consider the problem of proving assertions about programs that construct and alter data structures. our method will be to define a suitable assertion language l for data structures, to define a simple programming language l' for constructing and altering data structures, to give axioms and rules of inference (in the style of [hoare 1969]) which specify the effect of program segments on data structures (described by formulas in l) and finally to prove that these axioms are correct (relative to a formal definition of the semantics of l') and, in a reasonable sense, complete. thus our intention is to provide a complete theoretical framework for describing arbitrary data structures and proving assertions about programs that manipulate them.
the complexity of dynamic languages and dynamic optimization problems in this paper we offer a unifying framework for dynamic problems in terms of &ldquo;dynamic languages&rdquo;, and we discuss the complexity of these languages. in particular, many dynamic languages derived from np-complete languages can be shown to be polynomial space (p-space) complete. among these are the following: the dynamic 3-satisfiability problem, and dynamic 3-dimensional matching problem, the dynamic partition problem, the dynamic hamiltonian circuit problem, and the dynamic independent set problem. we provide a general technique for showing how to prove the p-space completeness of dynamic problems derived from np-complete problems.
a faster strongly polynominal minimum cost flow algorithm we present a new strongly polynomial algorithm for the minimum cost flow problem, based on a refinement of the edmonds-karp scaling technique. our algorithm solves the uncapacitated minimum cost flow problem as a sequence of &ogr;(n log n) shortest path problems on networks with n nodes and m arcs and runs in &ogr;(n log n(m + n log n)) steps. using a standard transformation, this approach yields an &ogr;(m log n (m + n log n)) algorithm for the capacitated minimum cost flow problem. this algorithm improves the best previous strongly polynomial algorithm due to galil and tardos, by a factor of m/n. our algorithm is even more efficient if the number of arcs with finite upper bounds, say m', is much less than m. in this case, the number of shortest path problems solved is &ogr;((m + n) log n).
communication with secrecy constraints let x, y, z be finite sets, x,y random variables uniformly distributed over x&times;y, f a function from x&times;y to z and 0&le;&egr;&le1. a person px knows x and a person py knows y and they want to exchange x and y. an eavesdropper who knows their protocol listens to their communication in order to obtain information about f(x, y). px and py want to ensure that for every value (x,y) of (x,y) the eavesdropper's a priori and a posteriori probabilities of {f(x,y)&equil;j} are &egr;-close for all j. therefore, they encrypt some of the transmitted bits. the problem is to find a protocol that minimizes the number of bits encrypted in the worst case. two kinds of protocols are considered: deterministic and randomized. for deterministic protocols it is shown that for all x,y, boolean f (|z|&equil;2) and &egr;>0, there exists a protocol that requires no more than 2&bull; log(1/&egr;) + 16 bits. an example where log(1/&egr;) &minus; 1 bits must be encrypted is given. for k valued functions (|z|&equil;k) it is shown that at most ck(&egr;) bits must be encrypted (independent of x, y and f ). the results are extended to n persons communicating over a broadcast channel. the proofs rely on results concerning partitions of k valued matrices. for randomized protocols it is shown that for all x,y boolean f, and all possible joint distributions of x,y (not only uniform), total secrecy (&egr;&equil;0) can be achieved using only two secret bits.
uniform hashing in constant time and linear space. many algorithms and data structures employing hashing have been analyzed under the uniform hashing assumption, i.e., the assumption that hash functions behave like truly random functions. starting with the discovery of universal hash functions, many researchers have studied to what extent this theoretical ideal can be realized by hash functions that do not take up too much space and can be evaluated quickly. in this paper we present an almost ideal solution to this problem: a hash function that, on any set of n inputs, behaves like a truly random function with high probability, can be evaluated in constant time on a ram, and can be stored in o(n) words, which is optimal. for many hashing schemes this is the first hash function that makes their uniform hashing analysis come true, with high probability, without incurring overhead in time or space.
low distortion embeddings for edit distance. we show that 0,1d endowed with edit distance embeds into l1 with distortion 2o(√log dlog log d). we further show efficient implementations of the embedding that yield solutions to various computational problems involving edit distance. these include sketching, communication complexity, nearest neighbor search. for all these problems, we improve upon previous bounds.
simple and efficient leader election in the full information model. in this paper, we study the leader election problem in the full information model. we show two results in this context. first, we exhibit a constructive $o(\log n)$ round protocol that is resilient against linear size coalitions. that is, our protocol is resilient against any coalition of size less then $\beta n$ for some constant (but small) value of $\beta$. second, we provide an easy, non-constructive probabilistic argument that shows the existence of $o(\log n)$ round protocol in which $\beta$ can be made as large as $\half - \epsilon$ for any positive $\epsilon$. our protocols are extremely simple.
dynamically maintaining configurations in the plane (detailed abstract) for a number of common configurations of points (lines) in the plane, we develop datastructures in which insertions and deletions of points (or lines, respectively) can be processed rapidly without sacrificing much of the efficiency of query answering of known static structures for these configurations. as a main result we establish a fully dynamic maintenance algorithm for convex hulls that can process insertions and deletions of single points in only o(log3n) steps or less per transaction, where n is the number of points currently in the set. the algorithm has several intriguing applications, including that one can &ldquo;peel&rdquo; a set of n points in only o(log3n) steps and that one can maintain two sets at a costs of only o(log3n) or less per insertion and deletion such that it never takes more than o(log2n) steps to determine whether the two sets are separable by a straight line. also efficient algorithms are obtained for dynamically maintaining the common intersection of a set of half-spaces and for dynamically maintaining the maximal elements of a set of plane points. the results are all derived by means of one master technique, which is applied repeatedly and which seems to capture an appropriate notion of &ldquo;decomposability&rdquo; for configurations.
a consistent and complete deductive system for the verification of parallel programs the semantics of a simple parallel programming language is presented in two ways: deductively, by a set of hoare-like axioms and inference rules, and operationally, by means of an interpreter. it is shown that the deductive system is consistent with the interpreter. it would be desirable to show that the deductive system is also complete with respect to the interpreter, but this is impossible since the programming language contains the natural numbers. instead it is proved that the deductive system is complete relative to a complete proof system for the natural numbers; this result is similar to cook's relative completeness for sequential programs. the deductive semantics given here is an extension of an incomplete deductive system proposed by hoare. the key difference is an additional inference rule which provides for the introduction of auxiliary variables in a program to be verified.
the lane tracing algorithm for constructing lr(k) parsers the paper presents, as far as the author is aware, the first practical general method for constructing lr(k) parsers. it has been used, without computational difficulty, to produce lr(1), lr(2) and lr(3) parsers for grammars of the size of algol.
on the cell probe complexity of membership and perfect hashing. we study two fundamental static data structure problems, membership and perfect hashing, in yao's cell probe model. the first space and bit probe optimal worst case upper bound is given for the membership problem. we also give a new efficient membership scheme where the query algorithm makes just one adaptive choice, and probes a total of three words. a lower bound shows that two word probes generally do not suffice. for minimal perfect hashing we show a tight bit probe lower bound, and give a simple scheme achieving this performance, making just one adaptive choice. linear range perfect hashing is shown to be implementable with the same number of bit probes, of which just one is adaptive. in contrast, we establish that for sufficiently sparse sets, non-adaptive perfect hashing needs exponentially more bit probes. this is the first such separation of adaptivity and non-adaptivity.
new and improved constructions of non-malleable cryptographic protocols. we present a new constant round protocol for non-malleable zero-knowledge. using this protocol as a subroutine, we obtain a new constant-round protocol for non-malleable commitments. our constructions rely on the existence of (standard) collision resistant hash functions. previous constructions either relied on the existence of trapdoor permutations and hash functions that are collision resistant against sub-exponential sized circuits, or required a super-constant number of rounds.additional results are the first construction of a non-malleable commitment scheme that is statistically hiding (with respect to opening), and the first non-malleable protocols that satisfy a strict polynomial-time simulation requirement. the latter are constructed by additionally assuming the existence of trapdoor permutations.our approach differs from the approaches taken in previous works in that we view non-malleable zero-knowledge as a building-block rather than an end goal. this gives rise to a modular construction of non-malleable commitments and results in a somewhat simpler analysis.the techniques that we use to construct our zero-knowl-edge protocol are non black-box, but are different than the non black-box techniques previously used in the context of non-malleable coin-tossing.
efficient parallel solution of linear systems the most efficient known parallel algorithms for inversion of a nonsingular n &times; n matrix a or solving a linear system ax = b over the rationals require &ogr;(log n)2 time and m(n)n0.5 processors (where m(n) is the number of processors required in order to multiply two n &times; n rational matrices in time &ogr;(log n).) furthermore, all known polylog time algorithms for those problems are unstable: they require the calculation to be done with perfect precision; otherwise they give no results at all. this paper describes parallel algorithms that have good numerical stability and remain efficient as n grows large. in particular, we describe a quadratically convergent iterative method that gives the inverse (within the relative precision 2-no(1)) of an n &times; n rational matrix a with condition &le; n0(1) in &ogr;(log n)2 time using m(n) processors. this is the optimum processor bound and the factor n0.5 improvement of known processor bounds for polylog time matrix inversion. it is the first known polylog time algorithm that is numerically stable. the algorithm relies on our method of computing an approximate inverse of a that involves &ogr;(log n) parallel steps and n2 processors. also, we give a parallel algorithm for solution of a linear system ax = b with a sparse n &times; n symmetric positive definite matrix a. if the graph g(a) (which has n vertices and has an edge for each nonzero entry of a) is s(n)-separable, then our algorithm requires only &ogr;((log n)(log s(n))2) time and |e| + m(s(n)) processors. the algorithm computes a recursive factorization of a so that the solution of any other linear system ax = b&prime; with the same matrix a requires only &ogr;(log n log s(n)) time and |e| + s(n)2 processors.
on adequate performance measures for paging. memory management is a fundamental problem in computer architecture and operating systems. we consider a two-level memory system with fast, but small cache and slow, but large main memory. the underlying theoretical problem is known as the paging problem. a sequence of requests to pages has to be served by making each requested page available in the cache. a paging strategy replaces pages in the cache with requested ones. the aim is to minimize the number of page faults that occur whenever a requested page is not in the cache.experience shows that the paging strategy least-recently-used (lru) usually achieves a factor around 2 to 3 compared to the optimum number of faults. this contrasts the theoretical worst case, in which this factor can be as large as the cache size k.one difficulty in analyzing the paging problem was the lack of an appropriate lower bound for the minimum number of page faults. we address this issue and propose a general lower bound which provides insight into the global structure of a given request sequence. in addition, we derive a characterization for the number of faults incurred by lru.we give a theoretical explanation why lru performs well in practice. we classify the set of all request sequences according to certain parameters and prove a bound on the competitive ratio of lru, which depends on them. this bound varies between 2 and k, i.e., it includes the worst-case, but explains for which sequences lru achieves constant competitive ratio. the classification is motivated from the structure of request sequences of practical applications: locality of reference and characteristic data access patterns. we argue that this structure yields values around 2 for our bound. indeed, it is between 2 and 5 in extensive practical experiments.furthermore, we study the paging problem with variable cache size, which was already considered previously. we show that this approach is not appropriate to explain the usual good performance of lru. we measure the performance of lru with the expected competitive ratio e[alg]/e[opt] and the expected performance ratio e[alg]/e[opt] in a diffuse adversary model and compare both measures. our analysis yields that the expected competitive ratio gives a misleading answer.
linear unification a unification algorithm is described which tests a set of expressions for unifiability and which requires time and space which are only linear in the size of the input.
shallow multiplication circuits and wise financial investments paterson, pippenger and zwick have recently obtained a general theory that describes the optimal way in which given carry-save adders can be combined into carry-save networks. their work produces, in particular, multiplication circuits of depth 3.71 log* n (these circuits put out two numbers whose sum is the result of the multiplication). in this work an extension of the above general theory is obtained. we now consider carry-save adders that may receive inputs and produce outputs using several different representation methods. we describe the optimal way of utilising any such collection of carry-save adders. the optimality proof uses the min-max theorem of game theory. by using several different representation standards, the depth of multiplication circuits can be surprisingly reduced to 3.48 log* n (again two output numbers are produced). we introduce bit level redundancy by using a novel coding scheme in which each bit is distributed over four wires. interestingly, the information on these four wires is usually not transmitted simultaneously. finally, an analogy is made between the optimisation problem faced by the circuit designer and the optimisation problem faced by an investor, offered a collection of financial investment plans, each involving perhaps several different currencies. this analogy is used to obtain intuitive explanations of the results obtained.
the joy of theory. this talk is meant to be a celebration of theoreticians, thier achievements, and thier unique style, drawing to a large extent on examples from this volume.theoretical computer science has largely succeeded in its core mission, that is, improving a rigorous and productive foundational understanding of the power and limitations of the von neumann computer and its software. and in the past few years it has strived to extend its reach to the internet and the worldwide web, the central computational artifact of our times.but theoreticians have achieved much more than this. our community has identified p vs. np, arguably the deepest and most important mathematical question of our time -- and it is leading the assault on it. in addition we are developing "algorithmic mirrors" through which other sciences (notably physics and biology, with economics and other social sciences soon to join) rediscover, fruitfully, themselves. and we have furthered and influenced crucially combinatorics and logic, the important mathematical fields from which we have drawn methodologically. the newfound respectability and prestige of our parent field, computer science, owes much to these achievements.theoreticians comprise a microcosm with wonderful characteristics: great scientific, social, and intellectual openness; responsibility and mutual respect, but also healthy doses of irreverence, mistrust of the establishment, willingness to experiment, and self-critical spirit; and a strong sense of an international community that is remarkably cohesive and tightly knit while celebrating the diversity of its people, of their backgrounds, and of their scientific interests and approaches.we have also developed a fascinating, complex esthetic of our work based on mathematical elegance and depth, relevance and fashion, timeliness and competition -- but also on playfulness and humor. our esthetic has served us well: some of our most important results were derived by long chains of contributions, each seemingly guided to a large extent by such esthetic considerations. in fact, this esthetic extends delightfully to the exposition of our work, as evidenced by the unique genre of scientific prose known as "focs/stoc abstract".
computing correlated equilibria in multi-player games. we develop a polynomial-time algorithm for finding correlated equilibria (a well-studied notion of rationality due to aumann that generalizes the nash equilibrium) in a broad class of succinctly representable multiplayer games, encompassing essentially all known kinds, including all graphical games, polymatrix games, congestion games, scheduling games, local effect games, as well as several generalizations. our algorithm is based on a variant of the existence proof due to hart and schmeidler [11], and employs linear programming duality, the ellipsoid algorithm, markov chain steady state computations, as well as application-specific methods for computing multivariate expectations.
on the faithful regular extensions of iterative algebras in ([6]), tiuryn proved the existence of extensions of algebras with the unique fixed point property (iterative algebras) to ordered algebras with the least fixed point property (regular algebras), extensions preserving the fixed point solutions. the aim of this paper is to prove that whenever the extension is &ldquo;faithful&rdquo;, i.e. obtained without collapsing elements of the carrier, the new regular algebra is again iterative. in section 1 we fix some notations and definitions and state tiuryn's result. section 2 contains the formulation of the problem and a sketch of the proof. section 3 deals with the main construction.
some complexity results for the traveling salesman problem it is shown that, unless p&equil;np, local search algorithms for the traveling salesman problem having polynomial time complexity per iteration will generate solutions arbitrarily far from the optimal. the traveling salesman problem is also shown to be np-complete even if its instances are restricted to be realizable by a set of points on the euclidean plane.
communication complexity in this paper we prove several results concerning this complexity measure. first we establish (in a non-constructive manner) that there exist languages which cannot be recognized with less than n communication (obviously, communication n is always enough for recognizing any language). in fact, we show that for any functionf(n)-&-lt; n, there are languages recognizable with communicationf(n) but not with communicationf (n)-&-minus;1. in other words, this complexity measure possesses a very dense hierarchy or complexity classes, as miniscule increments in communication add to the languages that can be recognized.
on the complexity of matrix product. our main result is a lower bound of $\omega(m^2 \log m)$ for the size of any arithmetic circuit for the product of two matrices, over the real or complex numbers, as long as the circuit does not use products with field elements of absolute value larger than 1 (where m &times; m is the size of each matrix). that is, our lower bound is superlinear in the number of inputs and is applied for circuits that use addition gates, product gates, and products with field elements of absolute value up to 1. we also prove size-depth tradeoffs for such circuits: we show that if a circuit, as above, is of depth d, then its size is $\omega(m^{2+ 1/o(d)})$.
testing metric properties. finite metric spaces, and in particular tree metrics play an important role in various disciplines such as evolutionary biology and statistics. a natural family of problems concerning metrics is deciding, given a matrix m, whether or not it is a distance metric of a certain predetermined type. here we consider the following relaxed version of such decision problems: for any given matrix m and parameter ε, we are interested in determining, by probing m, whether m has a particular metric property p, or whether it is ε-far from having the property. in ε-far we mean that at least an ε-fraction of the entries of m must be modified so that it obtains the property. the algorithm may query the matrix on entries m[i,j] of its choice, and is allowed a constant probability of error.we describe algorithms for testing euclidean metrics, tree metrics and ultrametrics. furthermore, we present an algorithm that tests whether a matrix m is an approximate ultrametric. in all cases the query complexity and running time are polynomial in 1/ε and independent of the size of the matrix. finally, our algorithms can be used to solve relaxed versions of the corresponding search problems in time that is sub-linear in the size of the matrix.
multi-linear formulas for permanent and determinant are of super-polynomial size. an arithmetic formula is multilinear if the polynomial computed by each of its subformulas is multilinear. we prove that any multilinear arithmetic formula for the permanent or the determinant of an n &times; n matrix is of size super-polynomial in n. previously, super-polynomial lower bounds were not known (for any explicit function) even for the special case of multilinear formulas of constant depth.
bounded-concurrent secure multi-party computation with a dishonest majority. we show how to securely realize any multi-party functionality in a way that preserves security under an a-priori bounded number of concurrent executions, regardless of the number of corrupted parties. previous protocols for the above task either rely on set-up assumptions such as a common reference string, or require an honest majority. our constructions are in the plain model and rely on standard intractability assumptions (enhanced trapdoor permutations and collision resistant hash functions). even though our main focus is on feasibility of concurrent multi-party computation we actually obtain a protocol using only a constant number of communication rounds. as a consequence our protocol yields the first construction of constant-round phstand-alone secure multi-party computation with a dishonest majority, proven secure under standard (polynomial-time) hardness assumptions; previous solutions to this task either require logarithmic round-complexity, or subexponential hardness assumptions. the core of our protocol is a novel construction of (concurrently) simulation-sound zero-knowledge protocols, which might be of independent interest. finally, we extend the framework constructed to give a protocol for secure multi-party (and thus two-party) computation for any number of corrupted parties, which remains secure even when arbitrary subsets of parties concurrently execute the protocol, possibly with interchangeable roles. as far as we know, for the case of two-party or multi-party protocols with a dishonest majority, this is the first positive result for any non-trivial functionality which achieves this property in the plain model.
extractors with weak random seeds. we show how to extract random bits from two or more independent weak random sources in cases where only one source is of linear min-entropy and all other sources are of logarithmic min-entropy. our main results are as follows: a long line of research, starting by nisan and zuckerman[14], gives explicit constructions of seeded-extractors, that is, extractors that use a short seed of truly random bits to extract randomness from a weak random source. for every such extractor e, with seed of length d, we construct an extractor e′, with seed of length d′=o(d), that achieves the same parameters as e but only requires the seed to be of min-entropy larger than (1⁄2+δ) •d′ (rather than fully random), where δ is an arbitrary small constant. fundamental results of chor and goldreich and vazirani [6,21] show how to extract ω(n) random bits from two (independent) sources of length n and min-entropy larger than (1⁄2δ) • n, where δ is an arbitrary small constant. we show how to extract ω(n) random bits (with optimal probability of error) when only one source is of min-entropy (1⁄2+δ) •n and the other source is of logarithmic min entropy.3 a recent breakthrough of barak, impagliazzo and wigderson[4] shows how to extract ω(n) random bits from a constant number of (independent) sources of length n and min-entropy larger than δ n, where δ is an arbitrary small constant. we show how to extract ω (n) random bits (with optimal probability of error) when only one source is of min-entropy δ n and all other (constant number of) sources are of logarithmic min-entropy.a very recent result of barak, kindler, shaltiel, sudakov and wigderson[5] shows how to extract a constant number of random bits from three (independent) sources of length n and min-entropy larger than δn, where δ is an arbitrary small constant. we show how to extract ω(n)/ random bits, with sub-constant probability of error, from one source of min-entropy δ n and two sources of logarithmic min-entropy.in the same paper, barak, kindler, shaltiel, sudakov and wigderson[5] give an explicit coloring of the complete bipartite graph of size 2n x 2n with two colors, such that there is no monochromatic subgraph of size larger than 2δn x 2 2δn, where δ is an arbitrary small constant. we give an explicit coloring of the complete bipartite graph of size 2n x 2n with a constant number of colors, such that there is no monochromatic subgraph of size larger than 2δn x n5.we also give improved constructions of mergers and condensers. in particular, we show that using a constant number of truly random bits, one can condense a source of length n and min-entropy rate δ into a source of length ω (n) and min-entropy rate 1-δ, where δ is an arbitrary small constant.we show that using a constant number of truly random bits, one can merge a constant number of sources of length n, such that at least one of them is of min-entropy rate 1-δ, into one source of length ω(n) and min-entropy rate slightly less than 1-δ, where δ is any small constant.
the complexity of facets (and some facets of complexity) many important combinatorial optimization problems, including the traveling salesman problem (tsp), the clique problem and many others, call for the optimization of a linear functional over some discrete set of vectors.
extractors for a constant number of polynomially small min-entropy independent sources. we consider the problem of randomness extraction from independent sources. we construct an extractor that can extract from a constant number of independent sources of length $n$, each of which have min-entropy $n^\gamma$, for an arbitrarily small constant $\gamma>0$. our extractor is obtained by composing seeded extractors in simple ways. we introduce a new technique to condense independent somewhere-random sources which looks like a useful way to manipulate independent sources. our techniques are different from those used in recent work [b. barak, r. impagliazzo, and a. wigderson, siam j. comput., 36 (2006), pp. 1095-1118; b. barak, g. kindler, r. shaltiel, b. sudakov, and a. wigderson, simulating independence: new constructions of condensers, ramsey graphs, dispersers, and extractors, in proceedings of the 37th annual acm symposium on theory of computing, acm, new york, 2005, pp. 1-10; r. raz, extractors with weak random seeds, in proceedings of the 37th annual acm symposium on theory of computing, acm, new york, 2005, pp. 11-20; j. bourgain, int. j. number theory, 1 (2005), pp. 1-32] for this problem in the sense that they do not rely on any results from arithmetic combinatorics. using an extractor of bourgain's [int. j. number theory, 1 (2005), pp. 1-32] as a black box, we obtain a new extractor for two independent block sources with few blocks, even when the min-entropy is as small as $\operatorname{polylog}(n)$. we also show how to modify the 2 source disperser for linear min-entropy of barak et al. [simulating independence: new constructions of condensers, ramsey graphs, dispersers, and extractors, in proceedings of the 37th annual acm symposium on theory of computing, acm, new york, 2005, pp. 1-10] and the three source extractor of raz [extractors with weak random seeds, in proceedings of the 37th annual acm symposium on theory of computing, acm, new york, 2005, pp. 11-20] to get dispersers/extractors with exponentially small error and linear output length where previously both were constant.
lower bounds for dynamic connectivity. we prove an ω(lg erik n) cell-probe lower bound on maintaining connectivity in dynamic graphs, as well as a more general trade-off between updates and queries. our bound holds even if the graph is formed by disjoint paths, and thus also applies to trees and plane graphs. the bound is known to be tight for these restricted cases, proving optimality of these data structures (e. g., sleator and tarjan's dynamic trees). our trade-off is known to be tight for trees, and the best two data structures for dynamic connectivity in general graphs are points on our trade-off curve. in this sense these two data structures are optimal, and this tightness serves as strong evidence that our lower bounds are the best possible. from a more theoretical perspective, our result is the first logarithmic cell-probe lower bound for any problem in the natural class of dynamic language membership problems, breaking the long standing record of ω(lg n / lg lg n). in this sense, our result is the first data-structure lower bound that is "truly" logarithmic, i. e., logarithmic in the problem size counted in bits. obtaining such a bound is listed as one of three major challenges for future research by miltersen [13] (the other two challenges remain unsolved). our techniques form a general framework for proving cell-probe lower bounds on dynamic data structures. we show how our framework also applies to the partial-sums problem to obtain a nearly complete understanding of the problem in cell-probe and algebraic models, solving several previously posed open problems.
time-space trade-offs for predecessor search. we develop a new technique for proving cell-probe lower bounds for static data structures. previous lower bounds used a reduction to communication games, which was known not to be tight by counting arguments. we give the first lower bound for an explicit problem which breaks this communication complexity barrier. in addition, our bounds give the first separation between polynomial and near linear space. such a separation is inherently impossible by communication complexity.using our lower bound technique and new upper bound constructions, we obtain tight bounds for searching predecessors among a static set of integers. given a set y of n integers of l bits each, the goal is to efficiently find predecessor (x) = max (y ∈ y | y ≤ x). for this purpose, we represent y on a ram with word length b using s ≥ nl bits of space. defining a = lg s/n, we show that the optimal search time is, up to constant factors: min(logbn, lgl-lg n / n, lg(l/a) / lg(a/lg n * lg l/a), lg (l/a) / lg (lg (l/a) / lg (lg n / a)).in external memory (b > l), it follows that the optimal strategy is to use either standard b-trees, or a ram algorithm ignoring the larger block size. in the important case of b = l = γ lg n, for γ > 1 (i.e. polynomial universes), and near linear space (such as s = n • lgo(1) n), the optimal search time is θ(lg l). thus, our lower bound implies the surprising conclusion that van emde boas' classic data structure from [focs'75] is optimal in this case. note that for space n1+ε, a running time of o(lg l / lg lg l) was given by beame and fich [stoc'99].
on the degree of polynomials that approximate symmetric boolean functions (preliminary version) in this paper, we provide matching (up to a constant factor) upper and lower bounds on the degree of polynomials that represent symmetric boolean functions with an error 1/3. let &ggr;(f)=min{|2k&ndash;n+1|:fk &ne; fk+ 1 and 0 &le; k &le; n &ndash; 1} where fi is the value of f on inputs with exactly i 1's. we prove that the minimum degree over all the approximating polynomials of f is &thgr;((n(n-&ggr;(f))).5). we apply the techniques and tools from approximation theory to derive this result.
a 2.5 n-lower bound on the combinatorial complexity of boolean functions consider the combinational complexity l(f) of boolean functions over the basis &ohgr; &equil; {f&brvbar; f:{0,1}2 &rarr; {0,1}}. a new method for proving linear lower bounds of size 2n is presented. combining it with methods presented in [12] and [15], we establish for a special sequence of functions fn:{0,1}n &rarr; {0,1}: 2.5n &le; l(f) &le 6n. also a trade-off result between circuit complexity and formula size is derived.
on time hierarchies for fixed k &ge; 2 we tighten the time hierarchy for k-tape turing machines. also for fixed k &ge; 2 we exhibit infinite hierarchies of languages recognizable by k-tape machines with increasing amount of time on the same amount of space.
an information-theoretic approach to time bounds for on-line computation (preliminary version) static, descriptional complexity (program size) [16, 9] can be used to obtain lower bounds on dynamic, computational complexity (such as running time). we describe and discuss this &ldquo;information-theoretic approach&rdquo; in the following section. paul introduced it in [13], to obtain restricted lower bounds on the time complexity of sorting. we use the approach here to obtain lower time bounds for on-line simulation of one abstract storage unit by another. a major goal of our work is to promote the approach.
space bounds for a game of graphs we study a one-person game played by placing pebbles, according to certain rules, on the vertices of a directed graph. in [3] it was shown that for each graph with n vertices and maximum in-degree d , there is a pebbling strategy which requires at most c(d) n/log n pebbles. here we show that this bound is tight to within a constant factor. we also analyze a variety of pebbling algorithms, including one which achieves the 0(n/log n) bound.
on point location and motion planning among simplices. let $\ss$ be a set of $n$ possibly intersecting $(d-1)$-simplices in $d$-space for $d \geq 2$, and let ${\cal a}(\ss)$ be the arrangement of $\ss$. let $k = |{\cal a}(\ss)|$ be the number of faces of any dimension in the arrangement of $\ss$. a data structure is described that uses storage $o(n^{d-1+\eps} +k)$ and is built {\em deterministically} in time $o(n^{d-1+\eps} +k\log n)$, where $\eps >0$ is an arbitrarily small constant, such that the face of ${\cal a}(\ss)$ containing a query point is located in time $o(\log^3 n)$. if two query points are in the same cell of ${\cal a}(\ss)$, a collision-free path connecting them is produced. this result is obtained by exploiting powerful and so far overlooked properties of sparse nets introduced by chazelle [{\em discrete comput. geom.}, 9 (1993), pp. 145--158]. if the $(d-1)$-simplices in $\ss$ have pairwise-disjoint interiors and $d \geq 3$, improved bounds are obtained. a data structure is described that uses $o(n^{d-1})$ storage and is built deterministically in time $o(n^{d-1})$ such that point-location queries are solved in time $o(\log n)$. also, as a by-product, this method gives the first optimal worst-case algorithm for triangulating a nonsimple polyhedron in 3-space.
intercalation theorems for tree transducer languages we develop intercalation lemmas for the computations of the top-down tree transducers defined by rounds [15] and thatcher [17]. these lemmas are used to prove necessary conditions for languages all of whose strings are of exponential length to be tree transducer languages. the language {ww:w&egr;{a,b}*, &brvbar;w&brvbar;&equil;2n,n&ge;0}, which is generable by the composition of two transducers, is shown not to be generable by one. the proof technique applies to bottom-up transducers as well. the results are related to some subclasses of woods' augmented transition networks [18] characterized elsewhere in terms of tree transducer languages [14].
on the relationship between finite automata, finite monoids, and prefix codes it is the aim of the present study to establish links between the structure of a given (finite) prefixcode and that of its syntactic monoid, using automata theory as a tool.
time-space trade-offs for asynchronous parallel models: reducibilities and equivalences the question of relative efficiencies is studied in the context of a simple model of communicating aynchronous processes. the fundamental problem is whether a simple distributed system, with arbitrary size variables, is any more powerful than a system where only binary valued variables are permitted. the answer was (surprisingly) found to be negative, with an intuitive definition of the power of systems. the development of these notions required formalization of concepts such as equivalence of models, and the reduction of systems between models. it was discovered that requiring a strong definition of equivalence which decreased time apparently results in an increase in space. the trade-offs involved are seen to be tight in one approach to the problem.
economical solutions for the critical section problem in a distributed system (extended abstract) a solution to the critical section problem, first posed by dijkstra [1], is a fundamental requirement for concurrent program control. the problem is to ensure that no two processes are in a specified area of their programs (the critical section) at the same time. improvements to dijkstra's solution were made by knuth [2], debruijn [3], and eisenberg and mcguire [4]. the situation, for a distributed system was considered by lamport [5]. rivest and pratt [6] presented a solution for a distributed system where processes may repeatedly fail. the algorithms to be presented will be further improvements, where the comparisons will be made according to three measures: message size&mdash;the number of values the variable for interprocess communication can take on; fairness&mdash;the sequence in which waiting processes enter their critical sections; and time&mdash;the amount of time a process spends attempting to enter its critical section.
two infinite sets of primes with fast primality tests infinite sets p and q of primes are described, p &sub; q. for any natural number n it can be decided if n &isin; p in (deterministic) time &ogr;((log n)9). this answers affirmatively the question of whether there exists an infinite set of primes whose membership can be tested in polynomial time, and is the main result of the paper. also, for every n &isin; q, we show how to produce at random, in expected time &ogr;((log n)3), a certificate of length &ogr;(log n) which can be verified in (deterministic) time &ogr;((log n)3); this is less than the time needed for two exponentiations and is much faster than existing methods. finally it is important that p is relatively dense (at least cn2/3/log n elements less than n). elements of q in a given range may be generated quickly, but it would be costly for an adversary to search q in this range; this could be useful in cryptography.
the realization of monotone boolean functions (preliminary version) in this paper we study the complexity of realizing a monotone but otherwise arbitrary boolean function. we consider realizations by means of networks and formulae. in both cases the possibility exists that although a monotone function can always be realized in terms of monotone basis functions, a more economical realization may be possible if basis functions that are not themselves monotone are used. thus, we have four cases, namely: 1. the cost of realizing a monotone function with a network over a universal basis. 2. the cost of realizing a monotone function with a network over a monotone basis. 3. the cost of realizing a monotone function with a formula over a universal basis. 4. the cost of realizing a monotone function with a formula over a monotone basis. for the first case, we obtain a complete solution to the problem. for the other three cases, we obtain improvements over previous results and come within a logarithmic factor or two of a complete solution.
comparative schematology and pebbling with auxiliary pushdowns (preliminary version) this paper has three claims to interest. first, it combines comparative schematology with complexity theory. this combination is capable of distinguishing among strong's &ldquo;languages of maximal power,&rdquo; a distinction not possible when comparative schematology is based on computability considerations alone, and it is capable of establishing exponential disparities in running times, a capability not currently possessed by complexity theory alone. secondly, this paper inaugurates the study of pebbling with auxiliary pushdowns, which bears to plain pebbling the same relationship as cook's study of space-bounded machines with auxiliary pushdowns bears to plain space-bounded machines. this extension of pebbling serves as the key to the problems of comparative schematology mentioned above. finally, this paper advantageously displays the virtues of recent work by gabber and galil giving explicit constructions for certain graphs, for the availability of such explicit constructions is essential to the results of this paper.
probabilistic simulations (preliminary version) the results of this paper concern the question of how fast machines with one type of storage media can simulate machines with a different type of storage media. most work on this question has focused on the question of how fast one deterministic machine can simulate another. in this paper we shall look at the question of how fast a probabilistic machine can simulate another. this approach should be of interest in its own right, in view of the great attention that probabilistic algorithms have recently attracted.
self-routing superconcentrators. superconcentrators are switching systems that solve the generic problem of interconnecting clients and servers during sessions, in situations where either the clients or the servers are interchangable (so that it does not matter which client is connected to which server). previous constructions of superconcentrators have required an external agent to find the interconnections appropriate in each instance. we remedy this shortcoming by constructing superconcentrators that are ``self-routing'''', in the sense that they compute for themselves the required interconnections. specifically, we show how to construct, for each n, a system s_n with the following properties. (1) the system s_n has n inputs, n outputs, and o(n) components, each of which is of one of a fixed finite number of finite automata, and is connected to a fixed finite number of other components through cables, each of which carries signals from a fixed finite alphabet. (2) when some of the inputs, and an equal number of outputs, are ``marked'''' (by the presentation of a certain signal), then after o(log n) steps (a time proportional to the ``diameter'''' of the network) the system will establish a set of disjoint paths from the marked inputs to the marked outputs.
regular resolution lower bounds for the weak pigeonhole principle. we prove that any regular resolution proof for the weak pigeon hole principle, with n holes and any number of pigeons, is of length &ohgr;(2^{n^{&egr;}}), (for some global constant &egr; > 0$).
the minimum consistent dfa problem cannot be approximated within any polynomial the minimum consistent dfa problem is that of finding a dfa with as few states as possible that is consistent with a given sample (a finite collection of words, each labeled as to whether the dfa found should accept or reject). assuming that p &ne; np, it is shown that for any constant k, no polynomial time algorithm can be guaranteed to find a consistent dfa of size optk, where opt is the size of a smallest dfa consistent with the sample. this result holds even if the alphabet is of constant size two, and if the algorithm is allowed to produce an nfa, a regular grammar, or a regular expression that is consistent with the sample. similar hardness results are described for the problem of funding small consistent linear grammars.
flowchart schemata with counters the translation of a specific flowchart schema with one counter into an equivalent flowchart schema without counters is described. this result leads easily to the general translation method from one-counter flowchart schemata to zero-counter flowchart schemata. some generalizations are then presented.
on the distribution of independent formulae of number theory it follows by g&ouml;del's incompleteness theorem [6] that any effective sound system of logic for elementary arithmetic must be incomplete. we show that in any effective sound system of logic for elementary arithmetic, there exist valid unprovable formulae that are quite small relative to the complexity of the logical system. also, such formulae are quite dense. in fact, the situation is about as bad as it could possibly be. that is , no infinite axiom system for elementary arithmetic can be much more compact than a listing of all the valid formulae. the unprovable formulae we construct express predicates in the classes &sgr2 and &pgr; 2 of the kleene arithmetic hierarchy [12]. the construction yields a set of short formulae, at least one of which must be valid and unprovable, but the construction does not tell us which one is valid and unprovable. we also construct small valid unprovable formulae expressing a relation in the class &pgr; 1 of the kleene arithmetic hierarchy. these latter formulae are not as small. we do not know how small the independent formulae corresponding to the class &pgr; 1 are. the constructions are based on the concept of a restricted oracle, first introduced in [10] and further developed in [11]. the proofs make use of the recent result of matijasevic [9] concerning the relationship between recursively enumerable sets and diophantine equations.
an efficient algorithm for solving word equations. we present the first dexptime algorithm which solves word equations i.e. finds a finite representation of all solutions of an equation in a free semigroup. we show how to use our approach to solve two new problems in pspace which deal with properties of the solution set of a word equation:deciding finiteness of the solution set,deciding boundness of the set of maximal exponents of periodicity of solutions. the approach can be generalized to solve in pspace three problems for expressible relations, namely the emptiness of the relation, finiteness of the relation and boundness of the set of maximal exponents of periodicity of elements of the relation.
approximation algorithms for hierarchical location problems. we formulate and (approximately) solve hierarchical versions of two prototypical problems in discrete location theory, namely, the metric uncapacitated k-median and facility location problems. our work yields new insights into hierarchical clustering, a widely used technique in data analysis. for example, we show that every metric space admits a hierarchical clustering that is within a constant factor of optimal at every level of granularity with respect to the average (squared) distance objective. a key building block of our hierarchical facility location algorithm is a constant-factor approximation algorithm for an ''incremental'' variant of the facility location problem; the latter algorithm may be of independent interest.
a hypercubic sorting network with nearly logarithmic depth a natural class of &ldquo;hypercubic&rdquo; sorting networks is defined. the regular structure of these sorting networks allows for elegant and efficient implementations on any of the so-called hypercubic networks (e.g., the hypercube, shuffle-exchange, butterfly, and cube-connected cycles). this class of sorting networks contains batcher's o(lg2 n)-depth bitonic sort, but not the o(lg n)-depth sorting network of ajtai, komlo&acute;s, and szemere&acute;di. in fact, no o(lg2 n)-depth compare-interchange sort was previously known for any of the hypercubic networks. in this paper, we prove the existence of a family of 2o((lg lg n)1/2) lg n-depth hypercubic sorting networks. note that this depth is o(lg1+&egr; n) for any constant &egr; > 0.
on the extremely fair treatment of probabilistic algorithms a proof system based on linear temporal logic for the qualitative verification of concurrent probabilistic programs is proposed. the concept of extreme fairness is introduced as an approximation to the notion of probabilistic executions. the proof system proposed is shown to be relatively complete with respect to validity over all extremely fair computations. the proof methodology is demonstrated by proving correctness of a new probabilistic algorithm for solving the mutual exclusion problem ([clp]).
a lower bound for integer multiplication with read-once branching programs. we prove that read-once branching programs computing integer multiplication require size $2^{\omega(\sqrt{n})}$. this is the first nontrivial lower bound for multiplication on branching programs that are not oblivious. by the appropriate problem reductions, we obtain the same lower bound for other arithmetic functions.
the communication complexity of pointer chasing: applications of entropy and sampling. we study the k-round two-party communication complexity of pointer chasing problem for fixed k. damm, jukna and sgall showed an upper bound of o(n \log ^{(k-1)} n) for this problem. we prove a matching lower bound; this improves the lower bound of \omega(n) shown by nisan and wigderson. this yields a corresponding improvement in the hierarchy results for bounded-depth monotone circuits.we consider the bit version of this problem, and show upper and lower bounds. this implies that there is an abrupt jump in complexity, from linear to superlinear, when the number of rounds is reduced below k/2. we also consider the s-paths version originally studied by klauck and obtain upper and lower bounds.the lower bounds are based on arguments using entropy. one of the main contributions of this work is a transfer lemma for distributions with high entropy; this should be of independent interest.
minimum spanning ellipsoids the notion of a minimum spanning ellipsoid in any dimension is explained. basic definitions and theorems provide the ideas for an algorithm to find the minimum spanning ellipsoid of a set of points, i.e., the ellipsoid of minimum volume containing the set. the run-time of the algorithm o (n2) independent of dimension, where n is the number of points.
new notions of security: achieving universal composability without trusted setup. we propose a modification to the framework of universally composable (uc) security [3]. our new notion involves comparing the real protocol execution with an ideal execution involving ideal functionalities (just as in uc-security), but allowing the environment and adversary access to some super-polynomial computational power. we argue the meaningfulness of the new notion, which in particular subsumes many of the traditional notions of security. we generalize the universal composition theorem of [3] to the new setting. then under new computational assumptions, we realize secure multi-party computation (for static adversaries) without a common reference string or any other set-up assumptions, in the new framework. this is known to be impossible under the uc framework.
a comparison of instruction sets for stack machines suppose you are approached by a computer designer who wants to select a machine architecture and instruction set that is desirable from a compiler writers standpoint. what would you recommend, and why? we give a limited answer to the above question. we focus on the computation of arithmetic expressions like a&minus;b+c. when computing a&minus;b we need different instructions depending on where a and b are to be found. on a programmable calculator for example, a or b may be on the stack, or stored in some memory register. we also need instructions that copy values from one place to another. algorithms that generate code for arithmetic expressions tend to treat general purpose registers as a stack. moreover, results about machines that perform all arithmetic in a hardware stack are directly applicable to machines with general purpose registers. we therefore start our study of instruction sets by looking at stack machines. we compare machines based on the number of instructions needed to compute a given expression. we then turn to algorithms that generate optimal programs for computing expressions on the various machines.
computing permutations with double-ended queues, parallel stacks and parallel queues a memory may be regarded as a computer with input, output and storage facilities, but with no explicit functional capability. the only possible outputs are permutations of a multiset of its inputs. thus the natural question to ask of a class of memories is, what permutations can its members compute? we are particularly interested here in switchyard networks studied by knuth [1968], even and itai [1971], and tarjan [1972], where the permutations are of the set of inputs, rather than of a multiset of them.
the power of negative thinking in multiplying boolean matrices we are interested in combinational circuits synthesized from and-gates and or-gates. we first show that n3 distinct and-gate inputs are needed to form the product of two boolean matrices, and hence o(n3) two-input and-gates are needed to compute the transitive closure of a boolean matrix. while this result has the flavor of kerr's (achievable)lower bound [kerr 1970] of n3+-gates for computing the min/+ product of integer-valued matrices using only min-gates and +-gates, the problem turns out on closer inspection to be considerably more subtle, and in fact we have been able to come only to within a factor of two of the best known upper bound of n3and-gates. secondly we use this result to study the effect on combinational circuts of not using not-gates inverters).
a practical decision method for propositional dynamic logic: preliminary report we give a new characterization of the set of satisfiable formulae of propositional dynamic logic (pdl) based on the method of tableaux. from it we derive a heuristically efficient goal-directed proof procedure and a complete axiom system for pdl. the proof procedure illustrates a striking connection between natural deduction and symbolic execution. the completeness proof for the axiom system incorporates a method for the automatic synthesis of invariants. we also augment dl with new modalities throughout, during, and preserves, supply a new semantic foundation for dl programs, and show how to extend the satisfiability characterizations for pdl to throughout.
dynamic algebras and the nature of induction dynamic algebras constitute the variety (equationally defined class) of models of the segerberg axioms for propositional dynamic logic. we obtain the following results (to within inseparability). (i) in any dynamic algebra * is reflexive transitive closure. (ii) every free dynamic algebra can be factored into finite dynamic algebras. (iii) every finite dynamic algebra is isomorphic to a kripke structure. (ii) and (iii) imply parikh's completeness theorem for the segerberg axioms. we also present an approach to treating the inductive aspect of recursion within dynamic algebras.
a characterization of the power of vector machines random access machines (rams) are usually defined to have registers that hold integers. while this captures in part the structure of a commercial computer, it overlooks an implementation-dependent feature of most binary oriented machines, namely their ability to operate bit by bit on the bit vectors used to represent integers. typical operations are bit-wise boolean operations (and, or, not, etc.) and shifts by an amount specified in some register. these operations are ideal for certain problems, such as dealing with sets represented as bit vectors, some parsing algorithms [4], propositional calculus theorem proving, and analysis of sorting networks. a ram so implemented we shall call a vector machine.
on average distortion of embedding metrics into the line and into l1. we introduce and study the notion of the average distortion of a nonexpanding embedding of one metric space into another. less sensitive than the multiplicative metric distortion, the average distortion captures well the global picture, and, overall, is a quite interesting new measure of metric proximity, related to the concentration of measure phenomenon. we establish close mutual relations between the mincut- maxflow gap in a uniform-demand multicommodity flow, and the average distortion of embedding the suitable (dual) metric into l1. these relations are exploited to show that the shortest-path metrics of special (e.g., planar, bounded treewidth, etc.) graphs embed into l1 with constant average distortion. the main result of the paper claims that this remains true even if l1 is replaced with the line. this result is further sharpened for graphs of a bounded treewidth.
relativized questions involving probabilistic algorithms let r @@@@ np be the collection of languages l such that for some polynomial time computable predicate p(x,y) and constant k, l &equil; {x|@@@@y, |y|&equil;|x|k,p(x,y)} &equil; {x|@@@@ at least 2|x|k&minus;1 values of y, |y|&equil;|x|k,p(x,y)}. let u @@@@ np be the collection of languages l such that for some polynomial time computable predicate p(x,y) and constant k, l &equil; {x|@@@@y,|y|&equil;|x|k,p(x,y)}&equil; {x|@@@@ unique y, |y|&equil;|x|k,p(x,y)}. let ra,ua, pa,npa,co-npa be the relativization of these classes with respect to an oracle a as in [ 5 ]. then for some oracle e (npe @@@@ co-npe) &equil; ue &equil; re &equil; pe @@@@ npe while for some other oracle d co-npd &equil; npd &equil; ud &equil; rd @@@@ pd.
the changing face of web search: algorithms, auctions and advertising. web search has come to dominate our consciousness as a convenience we take for granted, as a medium for connecting advertisers and buyers, and as a fast-growing revenue source for the companies that provide this service. following a brief overview of the state of the art and how we got there, this talk covers a spectrum of technical challenges arising in web search.this lecture will begin with an overview of the social, economic and historical challenges underlying web search. understanding the basic background is a useful prerequisite for deep technical work in this area. following this, we will cover three vignettes, whose goal is to expose significant research areas rather than to present definitive results.the first deals with an emerging area variously referred to as human computation, social computation or social media. the idea is to solve difficult problems in artificial intelligence (such as image recognition) not through direct computation, but by exploiting the wisdom of crowds on the web. in the simplest form, an incentive mechanism is devised whereby many web users label images descriptively. these labels are then used for image retrieval. this immediately raises several foundational questions. what incentive mechanisms lead to high-quality labels? given the inevitability of misleading labels (spam), how does one filter out good labels? since the participants in such a system are likely to be connected in various social networks, how does one propagate trust and reputation in these networks to obtain reliable judges and thereby judgments.the second vignette centers around optimization and marketplace design for advertisements on the internet. we first outline how the presentation of brand advertisement on the internet leads to stochastic programming problems - in turn leading to novel issues in the design of futures contracts. we then turn to a problem more heavily studied in the theoretical computer science literature: the auction design and pricing of advertisement on keyword search results. beginning with the classic vickrey auction, known to be a truthful mechanism for single-item, sealed-bid auctions, we point out how sponsored search advertisements depart from this simple setting. we review the current state of the art here and mention several problems that remain open.the final vignette is based on the paper with kleinberg. we formulate a model for query incentive networks, motivated by users seeking information or services that pose queries, together with incentives for answering them. this type of information-seeking process can be formulated as a game among the nodes in the network, and this game has a natural nash equilibrium. how much incentive is needed in order to achieve a reasonable probability of obtaining an answer to a query? we study the size of query incentives as a function both of the rarity of the answer and the structure of the underlying network. this leads to natural questions related to strategic behavior in branching processes. whereas the classically studied criticality of branching processes is centered around the region where the branching parameter is 1, we show in contrast that strategic interaction in incentive propagation exhibits critical behavior when the branching parameter is 2.
provably good routing in graphs: regular arrays we examine the problem of routing wires on a vlsi chip where the nodes to be connected are arranged in a two-dimensional array. we develop provably good algorithms that find a solution close to the optimal one with high probability. our approximation algorithms solve the relevant 0-1 integer optimization problems by solving their relaxed versions and then rounding by an interesting probabilistic technique. one of our algorithms, using multicommodity flow, has applications to routing in circuit switching networks.
efficient routing in all-optical networks. communication in all-optical networks requires novel routing paradigms. the high bandwidth of the optic fiber is utilized through wavelength-division multiplexing : a single physical optical link can carry several logical signals, provided that they are transmitted on different wavelengths. we study the problem of routing a set of requests (each of which is a pair of nodes to be connected by a path) on sparse networks using a limited number of wavelengths, ensuring that different paths using the same wavelength never use the same physical link.
stochastic contention resolution with short delays. we study contention resolution protocols under a stochastic model of continuous request generation from a set of contenders. the performance of such a protocol is characterized by two parameters: the maximum arrival rate for which the protocol is stable and the expected delay of a request from arrival to service. known solutions are either unstable for any constant injection rate, or have polynomial (in the number of contenders) expected delay. our main contribution is a protocol that is stable for a constant injection rate, while achieving logarithmic expected delay. we extend our results to the case of multiple servers, with each request being targeted for a specific server. this is related to the optically connected parallel computer (or ocpc ) model. finally, we prove a lower bound showing that long delays are inevitable in a class of protocols including backoff-style protocols, if the arrival rate is large enough (but still smaller than 1).
absolutely parallel grammars and two-way deterministic finite-state transducers absolutely parallel grammars are defined and it is shown that the family of languages generated is equal to the family of languages generated by two-way deterministic finite-state transducers. furthermore it is shown that this family forms a full afl [4], is properly contained in the family of languages generated by two-way nondeterministic finite-state transducers (which is equal to the family of checking automata languages [8]) and properly contains the family of nonexpansive context-free languages [7].
operational and semantic equivalence between recursive programs in this paper, we show that two widely different notions of program equivalence coincide for the language of recursive definitions with simplification rules. the first one is the now classical equivalence for fixed-point semantics. the other one is purely operational in nature and is much closer to a programmer's intuition of program equivalence.
a fully dynamic reachability algorithm for directed graphs with an almost linear update time. we obtain a new fully dynamic algorithm for the reachability problem in directed graphs. our algorithm has an amortized update time of o(m+n log n) and a worst-case query time of o(n), where m is the current number of edges in the graph, and n is the number of vertices in the graph. each update operation either inserts a set of edges that touch the same vertex, or deletes an arbitrary set of edges. the algorithm is deterministic and uses fairly simple data structures. this is the first algorithm that breaks the o(n2) update barrier for all graphs with o(n2) edges.one of the ingredients used by this new algorithm may be interesting in its own right. it is a new dynamic algorithm for strong connectivity in directed graphs with an interesting persistency property. each insert operation creates a new version of the graph. a delete operation deletes edges from emphall versions. strong connectivity queries can be made on each version of the graph. the algorithm handles each update in o(mα(m,n)) amortized time, and each query in o(1) time, where α(m,n) is a functional inverse of ackermann's function appearing in the analysis of the union-find data structure. note that the update time of o(mα(m,n)), in case of a delete operation, is the time needed for updating all versions of the graph.
improved data structures for fully dynamic biconnectivity. we present fully dynamic algorithms for maintaining the biconnected components in general and plane graphs. a fully dynamic algorithm maintains a graph during a sequence of insertions and and deletions of edges or isolated vertices. let $m$ be the number of edges and $n$ be the number of vertices in a graph. the time per operation of the best known algorithms are $o(\sqrt{n})$ in general graphs and $o(\log n)$ in plane graphs for fully dynamic connectivity and $o(\min\{m^{2/3}, n\})$ in general graphs and $o(\sqrt{n})$ in plane graphs for fully dynamic biconnectivity. we improve the later running times to $(\min\{\sqrt{m}\log n, n \})$ in general graphs and $o(\log^{2}n)$ in plane graphs. our algorithm for general graphs can also find the biconnected components of all vertices in time $o(n)$. the update times in general graphs are amortized. this shows that the biconnected components of a graph can be dynamically maintained almost as efficiently as the connected components.
simple algebras are difficult let f be a finite field or an algebraic number field. in previous work we have shown how to find the basic building blocks (the radical and the simple components) of a finite dimensional algebra over f in polynomial time (deterministically in characteristic zero and las vegas in the finite case). here we address the more general problem of finding zero divisors in a. this problem is equivalent to finding a nontrivial common invariant subspace of a set of linear operators and includes, as a subcase, the problem of factoring polynomials over the field in question. in [fr] the problem of zero divisors has been reduced, in polynomial time (las vegas in the finite case), to the case of simple algebras. we show that, while zero divisors can be found in las vegas polynomial time if f is finite, the problem over the rationals might be substantially more difficult. we link the problem to hard number theoretic problems such as quadratic residuosity modulo a composite number. we show that assuming the generalized riemann hypothesis, there exists a randomized polynomial time reduction from quadratic residuosity to determining whether or not a given 4-dimensional algebra over q has zero divisors. it will follow that finding a pair of zero divisors is at least as hard as factoring squarefree integers. as for the finite case, we give a polynomial time las vegas method to construct explicit isomorphisms of matrix algebras. applications include an algorithm to solve the problem of finding common invariant subspaces for a set of linear operators. another application answers a question of w. m. kantor on permutation groups. finally, as another application of the grh, we mention a partial result on deterministic factoring over finite fields.
many birds with one stone: multi-objective approximation algorithms. we study network-design problems with multiple design objectives. in particular, we look at two cost measures to be minimized simultaneously: the total cost of the network and the maximum degree of any node in the network. our main result can be roughly stated as follows: given an integer $b$, we present approximation algorithms for a variety of network-design problems on an $n$-node graph in which the degree of the output network is $o(b \log (\frac{n}{b}))$ and the cost of this network is $o(\log n)$ times that of the minimum-cost degree-$b$-bounded network. these algorithms can handle costs on nodes as well as edges. moreover, we can construct such networks so as to satisfy a variety of connectivity specifications including spanning trees, steiner trees and generalized steiner forests. the performance guarantee on the cost of the output network is nearly best-possible unless $np = \tilde{p}$. we also address the special case in which the costs obey the triangle inequality. in this case, we obtain a polynomial-time approximation algorithm with a stronger performance guarantee. given a bound $b$ on the degree, the algorithm finds a degree-$b$-bounded network of cost at most a constant time optimum. there is no algorithm that does as well in the absence of triangle inequality unless $p = np$. we also show that in the case of spanning networks, we can simultaneously approximate within a constant factor yet another objective: the maximum cost of any edge in the network, also called the bottleneck cost of the network. we extend our algorithms to find tsp tours and $k$-connected spanning networks for any fixed $k$ that simultaneously approximate all these three cost measures.
abstract families of processors a &ldquo;processor&rdquo; is a turing-like automaton with auxiliary storage. an &ldquo;abstract family&rdquo; of processors (afp) consists of all processors that use the storage in the same way. properties common to all afp are derived. for a family of operations to be the output functions of some afp, it is necessary and sufficient that certain word-sets representing its members form a full afl (in the sense of ginsburg and greibach) closed under intersection and iterated finite substitution.2 for a family of word-sets to be the accepted languages of some afp, it is necessary and sufficient that it be a full afl closed under intersection and iterated finite substitution. the smallest full afl of this kind is the family of all recursively enumerable sets.
resolution lower bounds for the weak pigeonhole principle. we prove that any resolution proof for the weak pigeon hole principle, with n holes and any number of pigeons, is of length \omega(2^{n^{\epsilon}}), (for some constant \epsilon > 0). one corollary is that a certain propositional formulation of the statement np \not \subset p/poly does not have short resolution proofs.
a parallel repetition theorem. we show that a parallel repetition of any two-prover one-round proof system (mip(2,1)) decreases the probability of error at an exponential rate. no constructive bound was previously known. the constant in the exponent (in our analysis) depends only on the original probability of error and on the total number of possible answers of the two provers. the dependency on the total number of possible answers is logarithmic, which was recently proved to be almost the best possible [u. feige and o. verbitsky, proc.11th annual ieee conference on computational complexity, ieee computer society press, los alamitos, ca, 1996, pp. 70--76].
algorithmic aspects of vertex elimination we consider a graph-theoretic elimination process which is related to performing gaussian elimination on sparse symmetric and unsymmetric systems of linear equations. we discuss good algorithms for finding elimination orderings, showing that a generalization of breadth-first search, called lexicographic search, can be used to find perfect orderings in 0(n+e) time and minimal orderings in 0(ne) time, if the problem graph is undirected and has n vertices and e edges. we also give efficient (though slower) algorithms for generating such orderings on directed graphs. we claim that the minimum ordering problem for directed graphs is np-complete, and conjecture that it is also np-complete for undirected graphs. we include a brief discussion of the relation of elimination to transitive closure and discuss some unresolved, more general, issues.
tree-manipulating systems and church-rosser theorems we define a general class of tree-manipulating systems that includes many of the special cases from logic, linguistics, and automata theory. systems possessing what we call the &ldquo;church-rosser property&rdquo; are appropriate for evaluation or translation processes: the end result of a complete sequence of applications of the rules does not depend on the order in which the rules were applied. we sketch the theoretical and practical advantages of such flexibility. we derive general sufficient conditions for the church-rosser property and apply them to some important tree-manipulating systems. applications include tree transducers, the mccarthy formalism for recursive computation, and the classical church-rosser theorem for the full lambda-calculus.
extracting all the randomness and reducing the error in trevisan's extractors. we give explicit constructions of extractors which work for a source of any min-entropy on strings of length n. these extractors can extract any constant fraction of the min-entropy using o(log2 n) additional random bits, and can extract all the min-entropy using o(log3 n) additional random bits. both of these constructions use fewer truly random bits than any previous construction which works for all min-entropies and extracts a constant fraction of the min-entropy. we then improve our second construction and show that we can reduce the entropy loss to 2log(1/ε)+o(1) bits, while still using o(log3n) truly random bits (where entropy loss is defined as [(source min-entropy)+(# truly random bits used)-(# output bits)], and ε is the statistical difference from uniform achieved). this entropy loss is optimal up to a constant additive term. our extractors are obtained by observing that a weaker notion of "combinatorial design" suffices for the nisan-wigderson pseudorandom generator, which underlies the recent extractor of trevisan. we give near-optimal constructions of such "weak designs" which achieve much better parameters than possible with the notion of designs used by nisan-wigderson and trevisan. we also show how to improve our constructions (and trevisan's construction) when the required statistical difference ε from the uniform distribution is relatively small. this improvement is obtained by using multilinear error-correcting codes over finite fields, rather than the arbitrary error-correcting codes used by trevisan.
data graphs and addressing schemes: extended abstract a data graph is obtained from a data structure by masking out the specific data items at the nodes of the structure and concentrating only on the linkages in the structure. structural uniformities in data graphs can often be exploited to facilitate and systematize the accessing of nodes in the graph and the implementation of the graph in a computer. this paper presents a model for data graphs which can be used to study such uniformities. the main results reported characterize, in terms of structural uniformities, those classes of data graphs which can be implemented by &ldquo;relative addressing&rdquo; and by &ldquo;relocatable relative addressing&rdquo;.
lower bounds for matrix product, in bounded depth circuits with arbitrary gates. we prove super-linear lower bounds for the number of edges in constant depth circuits with n inputs and up to n outputs. our lower bounds are proved for all types of constant depth circuits, e.g., constant depth arithmetic circuits and constant depth boolean circuits with arbitrary gates. the bounds apply for several explicit functions, and, most importantly, for matrix product. in particular, we obtain the following results:we show that the number of edges in any constant depth arithmetic circuit for matrix product (over any field is super-linear in m^2 (where m \times m is the size of each matrix). that is, the lower bound is super-linear in the number of input variables. moreover, if the circuit is bilinear the result applies also for the case where the circuit gets for free any product of two linear functions.we show that the number of edges in any constant depth arithmetic circuit for the trace of the product of 3 matrices (over fields with characteristic~0) is super-linear in m^2. (note that the trace is a single-output function).we give explicit examples for n boolean functions f_1,\dots,f_ , such that any constant depth for f_1,...,f_n has a super-linear number of edges. the lower bound is proved also for circuits with arbitrary gates over any finite field. the bound applies for matrix product over finite fields as well as for several other explicit functions.
addressable data graphs: extended abstract this paper continues the study of the classes of data graphs which are implementable in a random access memory using &ldquo;relative addressing&rdquo; and &ldquo;relocatable realization&rdquo;, which was initiated in [1]. a new characterization of the class of rooted (&equil;relative addressable) data graphs yields simple and natural proofs of the preservation of rootedness under broad families of operations for composing data graphs. these positive results somewhat diminish the impact of the general unsolvability of detecting rootedness and free-rootedness (&equil;relocatability) in data graphs.
monotone circuits for matching require linear depth it is proven that monotone circuits computing the perfect matching function on n-vertex graphs require &ohgr;(n) depth. this implies an exponential gap between the depth of monotone and nonmonotone circuits.
hashing schemes for extendible arrays (extended arrays) the use of hashing schemes for storing extendible arrays is investigated. it is shown that extendible hashing schemes whose worst-case access behavior is close to optimal must utilize storage inefficiently; conversely, hashing schemes that utilize storage too conservatively are inevitably poor in expected access time. if requirements on the utilization of storage are relaxed slightly, then one can find rather efficient extendible hashing schemes. specifically, for any dimensionality of arrays, one can find extendible hashing schemes which at once utilize storage well [fewer than 2p storage locations need be set aside for storing arrays having p or fewer positions] and enjoy good access characteristics [expected access time is 0(1), and worst-case access time is 0(log log p) for p- or fewer-position arrays]. moreover, at the cost of only an additive increase in access time, storage demands can be decreased to (l+&egr;)p locations for arbitrary &egr;>0. in fact, if one will abide a more drastic degradation of access efficiency, one can lower storage demands to p+o(p) locations.
storage representations for tree-like data structures we review the motivation underlying the study of data encodings and the formal framework of the study. we then present a series of results whose main message is that (complete) trees are materially less congenial storage representations for tree-like data structures than they have been shown to be for array-like data structures. in response to these results, we propose a new data structure, called a dree, which we show to share the advantages of trees, but not to suffer their disadvantages, when used as a storage structure.
properties of deterministic top down grammars the class of context free grammars that can be deterministically parsed in a top down manner with a fixed amount of look-ahead is investigated. these grammars, called ll(k) grammars where k is the amount of look-ahead are first defined and a procedure is given for determining if a context free grammar is ll(k) for a given value of k. it is shown that &egr;-rules can be eliminated from an ll(k) grammar, at the cost of increasing the value of k by one, and a description is given of a canonical pushdown machine for recognizing ll(k) languages. it is shown that for each value of k there are ll(k+l) languages that are not ll(k) languages. it is shown that the equivalence problem is decidable for ll(k) grammars. additional properties are also given.
read-once branching programs, rectangular proofs of the pigeonhole principle and the transversal calculus. we investigate read-once branching programs for the following search problem: given a boolean m &#x00d7; n matrix with m > n, &#xfb01;nd either an all-zero row, or two 1&#x2019;s in some column. our primary motivation is that this models regular resolution proofs of the pigeonhole principle $$php^{m}_{n}$$, and that for m > n2 no lower bounds are known for the length of such proofs. we prove exponential lower bounds (for arbitrarily large m!) if we further restrict this model by requiring the branching program either to finish one row of queries before asking queries about another row (the row model) or put the dual column restriction (the column model).then we investigate a special class of resolution proofs for $$php^{m}_{n}$$ that operate with positive clauses of rectangular shape; we call this fragment the rectangular calculus. we show that all known upper bounds on the size of resolution proofs of $$php^{m}_{n}$$ actually give rise to proofs in this calculus and, inspired by this fact, also give a remarkably simple &#x201c;rectangular&#x201d; reformulation of the haken&#x2013;buss&#x2013;tur&#x00e1;n lower bound for the case m &#x226a; n2. finally we show that the rectangular calculus is equivalent to the column model on the one hand, and to transversal calculus on the other hand, where the latter is a natural proof system for estimating from below the transversal size of set families. in particular, our exponential lower bound for the column model translates both to the rectangular and transversal calculi.
nonserial dynamic programming is optimal we show that nonserial dynamic programming is optimal among one class of algorithms for an important class of discrete optimization problems. we consider discrete, multivariate, optimization problems in which the objective function is given as a sum of terms. each term is a function of only a subset of the variables. we first consider a class of optimization algorithms which eliminate suboptimal solutions by comparing the objective function on &ldquo;comparable&rdquo; partial solutions. a large, natural subclass of comparison algorithms in which the subproblems considered are either nested or nonadjacent (i.e., noninteracting) is then defined. it is shown that a variable-elimination procedure, nonserial dynamic programming, is optimal in an extremely strong sense among all algorithms in the subclass. the results' strong implications for choosing deterministic, adaptive, and nondeterministic algorithms for the optimization problem, for defining a complexity measure for a pattern of interactions, and for describing general classes of decomposition procedures are discussed. several possible extensions and unsolved problems are mentioned.
presburger arithmetic with bounded quantifier alternation this paper concerns both the complexity aspects of pa and the pragmatics of improving algorithms for dealing with restricted subcases of pa for uses such as program verification. we improve the cooper-presburger decision procedure and show that the improved version permits us to obtain time and space upper bounds for pa classes restricted to a bounded number of alternations of quantifiers. the improvement is one exponent less than the upper bounds for the decision problem for full pa. the pragmatists not interested in complexity bounds can read the results as substantiation of the intuitive feeling that the improvement to the cooper-presburger algorithm is a real, rather than ineffectual, improvement. (it can be easily shown that the bounds obtained here are not achievable using the cooper-presburger procedure).
uniform definability on finite structures with successor we study inductive and second-order definability on finite structures with successor and relate these notions to complexity theory. we introduce the dimension d of an inductive definition, directly related to the time complexity, representing the number of variables necessary to carry an induction. we will prove the following: connectivity is not uniformly unary &sgr;11 definable on graphs with successor, generalizing a similar result of fagin on graphs without successor. we will mention that similarly, hamiltonicity is neither unary-&sgr;11 nor unary-&pgr;11 on graphs with successor. these results show that disconnectivity is not inductive of dimension 1 although it is inductive of dimension 2, and that hamiltonicity is neither inductive nor co-inductive of dimension 1 on graphs with successor.
finding approximate separators and computing tree width quickly we show that for any fixed k, there is a linear-time algorithm which given a graph g either: (i) finds a cutset x of g with |x| &le; k such that no component of g&ndash;x contains more than 3/4|g&ndash;x| vertices, or (ii) determines that for any set x of vertices of g with |x| &le; k, there is a component of g&ndash;x which contains more than 2/3|g&ndash;x| vertices. this approximate separator algorithm can be used to develop and o(n log n algorithm for determining if g has a tree decomposition of width at most k (for fixed k) and finding such a tree decomposition if it exists.
stackelberg scheduling strategies. we study the problem of optimizing the performance of a system shared by selfish, noncooperative users. we consider the concrete setting of scheduling small jobs on a set of shared machines possessing latency functions that specify the amount of time needed to complete a job, given the machine load. we measure system performance by the total latency of the system. assigning jobs according to the selfish interests of individual users, who wish to minimize only the latency that their own jobs experience, typically results in suboptimal system performance. however, in many systems of this type there is a mixture of "selfishly controlled" and "centrally controlled" jobs. the congestion due to centrally controlled jobs will influence the actions of selfish users, and we thus aspire to contain the degradation in system performance due to selfish behavior by scheduling the centrally controlled jobs in the best possible way.we formulate this goal as an optimization problem via stackelberg games, games in which one player acts a leader (here, the centralized authority interested in optimizing system performance) and the rest as followers (the selfish users). the problem is then to compute a strategy for the leader (a stackelberg strategy) that induces the followers to react in a way that (approximately) minimizes the total latency in the system.in this paper, we prove that it is np-hard to compute an optimal stackelberg strategy and present simple strategies with provably good performance guarantees. more precisely, we give a simple algorithm that computes a strategy inducing a job assignment with total latency no more than a constant times that of the optimal assignment of all of the jobs; in the absence of centrally controlled jobs and a stackelberg strategy, no result of this type is possible. we also prove stronger performance guarantees in the special case where every machine latency function is linear in the machine load.
new lattice based cryptographic constructions. we introduce the use of fourier analysis on lattices as an integral part of a lattice-based construction. the tools we develop provide an elegant description of certain gaussian distributions around lattice points. our results include two cryptographic constructions that are based on the worst-case hardness of the unique shortest vector problem. the main result is a new public key cryptosystem whose security guarantee is considerably stronger than previous results (o(n1.5) instead of o(n7)). this provides the first alternative to ajtai and dwork's original 1996 cryptosystem. our second result is a family of collision resistant hash functions with an improved security guarantee in terms of the unique shortest vector problem. surprisingly, both results are derived from one theorem that presents two indistinguishable distributions on the segment [0, 1). it seems that this theorem can have further applications; as an example, we use it to solve an open problem in quantum computation related to the dihedral hidden subgroup problem.
the price of anarchy is independent of the network topology. we study the degradation in network performance caused by the selfish behavior of noncooperative network users. we consider a model of selfish routing in which the latency experienced by network traffic on an edge of the network is a function of the edge congestion, and network users are assumed to selfishly route traffic on minimum-latency paths. the quality of a routing of traffic is measured by the sum of travel times, also called the total latency. the outcome of selfish routing--a nash equilibrium--does not in general minimize the total latency; hence, selfish behavior carries the cost of decreased network performance. we quantify this degradation in network performance via the price of anarchy, the worst-possible ratio between the total latency of a nash equilibrium and of an optimal routing of the traffic. in this paper, we show that the price of anarchy is determined only by the simplest of networks. specifically, we prove that under weak hypotheses on the class of allowable edge latency functions, the worst-case ratio between the total latency of a nash equilibrium and of a minimum-latency routing for any multicommodity flow network is achieved by a single-commodity instance in a network of parallel links. in the special case where the class of allowable latency functions includes all of the constant functions, we prove that a network with only two parallel links suffices to achieve the worst-possible ratio. our guarantee that simple networks always furnish worst-possible examples provides a powerful method for computing the price of anarchy with respect to an arbitrary class of latency functions. we apply this method to function classes that have been well studied in the literature, including degree-bounded polynomials and queuing delay functions. these are the first tight analyses of the price of anarchy for significant classes of latency functions outside the class of linear functions.
on lattices, learning with errors, random linear codes, and cryptography. our main result is a reduction from worst-case lattice problems such as svp and sivp to a certain learning problem. this learning problem is a natural extension of the 'learning from parity with error' problem to higher moduli. it can also be viewed as the problem of decoding from a random linear code. this, we believe, gives a strong indication that these problems are hard. our reduction, however, is quantum. hence, an efficient solution to the learning problem implies a quantum algorithm for svp and sivp. a main open question is whether this reduction can be made classical.using the main result, we obtain a public-key cryptosystem whose hardness is based on the worst-case quantum hardness of svp and sivp. previous lattice-based public-key cryptosystems such as the one by ajtai and dwork were only based on unique-svp, a special case of svp. the new cryptosystem is much more efficient than previous cryptosystems: the public key is of size õ(n2) and encrypting a message increases its size by õ(n)(in previous cryptosystems these values are õ(n4) and õ(n2), respectively). in fact, under the assumption that all parties share a random bit string of length õ(n2), the size of the public key can be reduced to õ(n).
new trade-offs in cost-sharing mechanisms. a cost-sharing mechanism is a protocol that collects bids from a set of players, selects a subset of the players to receive a service (incurring a subset-dependent cost), and determines a price to charge each of these players. three standard requirements for cost-sharing mechanisms are incentive compatibility, which states that players are motivated to bid their true valuation for the service; budget-balance, meaning that the prices charged should recover the cost incurred; and efficiency, which states that the cost incurred and the valuations of the players served should be traded off in an optimal way. these three goals have been known to be mutually incompatible for thirty years. as a result, nearly all work on cost-sharing mechanisms in the economics and theoretical computer science literatures has focused on achieving two of these goals while completely ignoring the third.we show that incentive-compatibility, budget-balance, and approximate efficiency are simultaneously achievable for a wide range of cost functions, where efficiency is measured using the social cost---the sum of the incurred service cost and the excluded valuations. in particular, we prove such guarantees for well-known mechanisms for all submodular cost functions and for the steiner tree cost function. we also prove a generic, quantifiable trade-off between the objectives of efficiency and budget-balance in groupstrategyproof cost-sharing mechanisms.
lattice problems and norm embeddings. we present reductions from lattice problems in the l2 norm to the corresponding problems in other norms such as l1, l∞ (and in fact in any other lp norm where 1 ≤ p ≤ ∞). we consider lattice problems such as the shortest vector problem, shortest independent vector problem, closest vector problem and the closest vector problem with preprocessing. most reductions are simple and follow from known constructions of embeddings of normed spaces.among other things, our reductions imply that the shortest vector problem in the l1 norm and the closest vector problem with preprocessing in the l∞ norm are hard to approximate to within any constant (and beyond). previously, the former problem was known to be hard to approximate to within 2-ε, while no hardness result was known for the latter problem.
context-free grammars on trees in this paper we discuss still another version of indexed grammars 1 and macro grammars3,gaining some geometric intuition about the structure of these systems. an ordinary context-free grammar is a rewriting system for strings; we find that a macro grammar is a rewriting system for trees. cf grammars on strings form a special case since strings can be thought of as trees without branching nodes. we consider the special case of finite-state grammars in this report. we define the tree analogue of a non deterministic generalized sequential machine and obtain results about the domain and range of such a mapping. we relate these results to the theory of generalized finite automata6.
the quantum adiabatic optimization algorithm and local minima. the quantum adiabatic optimization algorithm uses the adiabatic theorem from quantum physics to minimize a function by interpolation between two hamiltonians. the quantum wave function can sometimes tunnel through significant obstacles. however it can also sometimes get stuck in local minima, even for fairly simple problems. an initial hamiltonian which insufficiently mixes computational basis states is analogous to a poorly mixing markov transition rule. we study a physical system -- the ising quantum chain with alternating sector interaction defects, but constant transverse field -- which is equivalent to applying the quantum adiabatic algorithm to a particular sat problem. we prove that for a constant range of values for the transverse field, the spectral gap is exponentially small in the sector length. indeed, we prove that there are exponentially many eigenvalues all exponentially close to the ground state energy. applying the adiabatic theorem therefore takes exponential time, even for this simple problem.
tree-oriented proofs of some theorems on context-free and indexed languages in this paper we study some applications and generalizations of the yield theorem: the yield of a recognizable set of trees (dendrolanguage) is an indexed language [1]. standard results on context-free languages can be obtained quickly using this theorem. we consider here the peters-ritchie theorem [4]: the language analyzable by a finite set of cs rules is cf. an extension of the yield theorem reads: the yield of a cf set of trees is an indexed language. we prove some closure properties of cf sets of trees. applying the yield theorem, we obtain properties of indexed languages. as a special result, we can solve the infiniteness problem for such languages.
universal games of incomplete information we consider two-person games of incomplete information in which certain portions of positions are private to each player and cannot be viewed by the opponent. we present various games of incomplete information which are universal for all reasonable games. the problem of determining the outcome of these universal games from a given initial position is shown to be complete in doubly-exponential time. we also define &ldquo;private alternating turing machines&rdquo; which are alternating turing machines with certain tapes and portions of states private to universal states. the time and space complexity of these machines is characterized in terms of the time complexity of deterministic turing machines, with single and double exponential jumps. we also consider blindfold games, which are restricted games in which the second player is not allowed to modify the common position. we show various blindfold games to have exponential space complete outcome problems and to be universal for reasonable blindfold games. we define &ldquo;blind alternating turing machines&rdquo; which are private alternating turing machines with the restriction that the universal states cannot modify the public tapes and public portion of states. a single exponential jump characterizes the relation between the space complexity of deterministic turing machines.
a new family of cayley expanders (?). we assume that for some fixed large enough integer d, the symmetric group sd can be generated as an expander using d1/30 generators. under this assumption, we explicitly construct an infinite family of groups gn, and explicit sets of generators yn ⊂ gn, such that all generating sets have bounded size (at most d1/7), and the associated cayley graphs are all expanders. the groups gn above are very simple, and completely different from previous known examples of expanding groups. indeed, gn is (essentially) all symmetries of the d-regular tree of depth n. the proof is completely elementary, using only simple combinatorics and linear algebra. the recursive structure of the groups gn (iterated wreath products of the alternating group ad) allows for an inductive proof of expansion, using the group theoretic analogue [4] of the zig-zag graph product of [38]. the explicit construction of the generating sets yn uses an efficient algorithm for solving certain equations over these groups, which relies on the work of [33] on the commutator width of perfect groups.we stress that our assumption above on weak expansion in the symmetric group is an open problem. we conjecture that it holds for all d. we discuss known results related to its likelihood in the paper.
logics for probabilistic programming (extended abstract) this paper introduces a logic for probabilistic programming+ prob-dl (for probabilistic dynamic logic; see section 2 for a formal definition). this logic has &ldquo;dynamic&rdquo; modal operators in which programs appear, as in pratt's [1976] dynamic logic dl. however the programs of prob-dl contain constructs for probabilistic branching and looping whereas dl is restricted to nondeterministic programs. the formula {a}&sgr;p of prob-dl denotes &ldquo;with measure &ge;&sgr;, formula p holds after executing program a.&rdquo; in section 3, we show that prob-dl has a complete and consistent axiomatization, (using techniques derived from parikh's [1978] completeness proof for the propositional dynamic logic). section 4 presents a probabilistic quantified boolean logic (prob-qbf) which also has applications to probabilistic programming.
testing monotone high-dimensional distributions. a monotone distribution p over a (partially) ordered domain has p(y) ≥ p(x) if y ≥ x in the order. we study several natural problems of testing properties of monotone distributions over the n-dimensional boolean cube, given access to random draws from the distribution being tested. we give a poly(n)-time algorithm for testing whether a monotone distribution is equivalent to or ε-far (in the l1 norm) from the uniform distribution. a key ingredient of the algorithm is a generalization of a known isoperimetric inequality for the boolean cube. we also introduce a method for proving lower bounds on testing monotone distributions over the n-dimensional boolean cube, based on a new decomposition technique for monotone distributions. we use this method to show that our uniformity testing algorithm is optimal up to polylog(n) factors, and also to give exponential lower bounds on the complexity of several other problems (testing whether a monotone distribution is identical to or ε-far from a fixed known monotone product distribution and approximating the entropy of an unknown monotone distribution).
symmetric complementation this paper introduces a class of 1 player games of perfect information, which we call complementing games;; the player is allowed moves which complement the value of successive plays. a complementing game is symmetric if all noncomplement moves are reversible (i.e., form a symmetric relation). these games are naturally related to a class of machines we call symmetric complementing machines. symmetric nondeterministic machines were studied in [lewis and papadimitriou, 80]; they are identical to our symmetric complementing machines with complement moves allowed only on termination. (a companion paper to appear describes the computational complexity of symmetric complementing and alternating machines.) of particular interest is the complexity class -&-sgr;(@@@@) csymlog, which contains the outcome problem of symmetric complementing games with constant complement bound with game positions encoded in log space, and next move relations computable in log space. we show that the decision problem for a restricted quantified boolean logic -&-sgr;(@@@@) qbf@@@@ is complete in -&-sgr;(@@@@) csymlog.
lower bounds for leader election and collective coin-flipping in the perfect information model. collective coin-flipping is the problem of producing common random bits in a distributed computing environment with adversarial faults. we consider the perfect information model: all communication is by broadcast and corrupt players are computationally unbounded. protocols in this model may involve many asynchronous rounds. we assume that honest players communicate only uniformly random bits. we demonstrate that any n-player coin-flipping protocol that is resilient against corrupt coalitions of linear size must use either at least [1/2 - o(1)]log* n communication rounds or at least [log(2k-1) n]1-o(1) communication bits in the kth round, where log(j) denotes the logarithm iterated j times. in particular, protocols using one bit per round require [1/2 - o(1)]log* n rounds. these bounds also apply to the leader election problem. the primary component of this result is a new bound on the influence of random sets of variables on boolean functions. finally, in the one-round case, using other methods we prove a new bound on the influence of sets of variables of size $\beta n$ for $\beta > 1/3$.
approximate complex polynomial evaluation in near constant work per point. given the n complex coefficients of a degree n-1 complex polynomial, we wish to evaluate the polynomial at a large number $m \ge n$ of points on the complex plane. this problem is required by many algebraic computations and so is considered in most basic algorithm texts (e.g., [a. v. aho, j. e. hopcroft, and j. d. ullman, the design and analysis of computer algorithms, addison-wesley, 1974]). we assume an arithmetic model of computation, where on each step we can execute an arithmetic operation, which is computed exactly. all previous exact algorithms [c. m. fiduccia, proceeding} 4th annual acm symposium on theory of computing, 1972, pp. 88--93; h. t. kung, fast evaluation and interpolation, carnegie-mellon, 1973; a. b. borodin and i. munro, the computational complexity of algebraic and numerical problems, american elsevier, 1975; v. pan, a. sadikou, e. landowne, and o. tiga, comput. math. appl., 25 (1993), pp. 25--30] cost at least work $\omega(\log^2 n)$ per point, and previously, there were no known approximation algorithms for complex polynomial evaluation within the unit circle with work bounds better than the fastest known exact algorithms. there are known approximation algorithms [v. rokhlin, j. complexity, 4 (1988), pp. 12--32; v. y. pan, j. h. reif, and s. r. tate, in proceedings 32nd annual ieee symposium on foundations of computer science, 1992, pp. 703--713] for polynomial evaluation at real points, but these do not extend to evaluation at general points on the complex plane.we provide approximation algorithms for complex polynomial evaluation that cost, in many cases, near constant amortized work per point. let $k = \log(|p|/\epsilon)$, where |p| is the sum of the moduli of the coefficients of the input polynomial p(z). let {\it ${\tilde{p}}(z_j)$ be an $\epsilon$-approx of $p(z)$} if $\epsilon$ upper bounds the modulus of the error of the approximation ${\tilde{p}}(z_j)$ at each evaluation point zj, that is, $|p(z_j)-{\tilde{p}}(z_j)| \le \epsilon;$ note that $\epsilon$ is an absolute error bound rather than a relative error bound. in many applications (particularly in signal processing) the evaluation points zj are fixed and require only polylogarithmic $k = \log(|p|/\epsilon) = o(\log^{o(1)} n)$; for these cases we get a surprising reduction in work by use of approximation algorithms, as compared to the fastest known exact algorithms. we $\epsilon$-approx complex degree n-1 polynomial evaluation at $m \ge n\log n/\log^2 k $ fixed points on or within the unit disk in the complex plane in amortized work o(log2 k) per point, which is o(log2 log n) for polylogarithmic k. if the m points are not fixed, then we have increased amortized work o(log2 k + log m) per point, which is o(log m) for polylogarithmic k and $m \ge n\log n/\log k,$ and is still substantially below the previous bound of $\omega(\log^2 m)$ for known exact algorithms. we further reduce our amortized bounds for special sets of evaluation points widely used in signal processing applications. the chirp transform is equivalent to evaluating a complex degree n-1 polynomial at the chirp points, which are $\zeta^j, j = 0,\dots,m-1$, for some fixed complex number $\zeta.$ we $\epsilon$-approx complex degree $n-1$ polynomial evaluation at these $m$ chirp points, where $m \ge n \log n/\log^2 k$ and $|\zeta| \le 1$ % or (ii) $m \ge n$ and $|\zeta| \le $ a function that limits to $1$ %for %$k = o(n)$ and large $n$) in amortized work o(log k) per point, whereas the previous best bounds for exact evaluation (via the chirp transform) were $\omega(\log m)$ per point [a. v. aho, k. steiglitz, and j. d. ullman, siam j. comput., 4 (1975), pp. 533--539]. using instead a reduction to approximate real polynomial evaluation (by interpolation at the chebyshev points), in total work o(n log k), we $\epsilon$-approx the evaluation of a degree n polynomial at the first n powers of the n'th root of unity, where $n' \ge \omega(n^2/k), $ and $\epsilon$-approx the n-point dft for certain inputs with descending coefficient magnitude. all of our results require polylogarithmic (that is, logo(1)n)depth with the same work bounds.we also provide a lower bound for a wide class of schemes for approximate evaluation of a degree n-1 polynomial on the unit circle; namely, we prove that if a scheme uses an approximation polynomial of degree k-1, then it can be convergent only over a small fraction o(k/n) of the unit circle. we believe this is the first lower bound of this sort proved, and the proof uses an interesting reduction to the approximation of a matrix product by a matrix of reduced rank.
space-bounded hierarchies and probabilistic computations this paper studies two aspects of the power of space-bounded probabilistic turing machines. section 2 presents a simple alternative proof of simon's recent result [13] that space-bounded probabilistic complexity classes are closed under complement. section 3 demonstrates that any language in the log n space hierarchy can be recognized by an log n space-bounded probabilistic turing machine with small error; this is a generalization of gill's result that any language in nspace(log n) can be recognized by such a machine the second result raises interesting questions about space hierarchies, which are considered in section 4. the usual definition is in terms of space-bounded alternating turing machines with a constant number of alternations [4].
random matroids we introduce a new random structure generalizing matroids. these random matroids allow us to develop general techniques for solving hard combinatorial optimization problems with random inputs.
distributed algorithms for synchronizing interprocess communication within real time this paper considers a fixed (possibly infinite) set &pgr; of distributed asynchronous processes which at various times are willing to communicate with each other. we describe probabilistic algorithms for synchronizing this communication with boolean &ldquo;flag&rdquo; variables, each of which can be written by only one process and read by at most one other process. with very few assumptions (the speeds of processes may vary in time within fixed arbitrary bounds, and the processes may be willing to communicate with a time varying set of processes (but bounded in number), and no probability assumptions about system behavior) we show our synchronization algorithms have real time response: if a pair of processes are mutually willing to communicate within a constant time interval, they establish communication in that interval, with high likelihood (for the worst case behavior of the system). our communication model and synchronization algorithms are quite robust. they are applied to solve a large class of real time resource synchronization problems, as well as real time implementation of the synchronization primitives of hoare's multiprocessing language csp.
polling: a new randomized sampling technique for computational geometry we introduce a new randomized sampling technique, called polling which has applications to deriving efficient parallel algorithms. as an example of its use in computational geometry, we present an optimal parallel randomized algorithm for intersection of half-spaces in three dimensions. because of well-known reductions, our methods also yield equally efficient algorithms for fundamental problems like the convex hull in three dimensions, voronoi diagram of point sites on a plane and euclidean minimal spanning tree. our algorithms run in time t = o(logn) for worst-case inputs and uses p = o(n) processors in a crew pram model where n is the input size. they are randomized in the sense that they use a total of only o(log2 n) random bits and terminate in the claimed time bound with probability 1 - n-&agr; for any &agr; > 0. they are also optimal in p . t product since the sequential time bound for all these problems is &ohgr;(nlogn). the best known determistic parallel algorithms for 2-d voronoi-diagram and 3-d convex hull run in o(log2 n) and o(log2 nlog * n) time respectively while using o(n) processors.
a logarithmic time sort for linear size networks a randomized algorithm that sorts on an n node network with constant valence in o(log n) time is given. more particularly, the algorithm sorts n items on an n-node cube-connected cycles graph, and, for some constant k, for all large enough &agr;, it terminates within k&agr; log n time with probability at least 1 - n-&agr;.
undirected st-connectivity in log-space. we present a deterministic, log-space algorithm that solves st-connectivity in undirected graphs. the previous bound on the space complexity of undirected st-connectivity was log4/3 obtained by armoni, ta-shma, wigderson and zhou [9]. as undirected st-connectivity is complete for the class of problems solvable by symmetric, non-deterministic, log-space computations (the class sl), this algorithm implies that sl = l (where l is the class of problems solvable by deterministic log-space computations). independent of our work (and using different techniques), trifonov [45] has presented an o(log n log log n)-space, deterministic algorithm for undirected st-connectivity.our algorithm also implies a way to construct in log-space a fixed sequence of directions that guides a deterministic walk through all of the vertices of any connected graph. specifically, we give log-space constructible universal-traversal sequences for graphs with restricted labelling and log-space constructible universal-exploration sequences for general graphs.
pseudorandom walks on regular digraphs and the rl vs. l problem. we revisit the general rl vs. l question, obtaining the following results. generalizing reingold's techniques to directed graphs, we present a deterministic, log-space algorithm that given a regular directed graph g (or, more generally, a digraph with eulerian connected components) and two vertices s and t, finds a path between s and t if one exists.if we restrict ourselves to directed graphs that are regular and consistently labelled, then we are able to produce pseudorandom walks for such graphs in logarithmic space (this result already found an independent application).we prove that if (2) could be generalized to all regular directed graphs (including ones that are not consistently labelled) then l=rl. we do so by exhibiting a new complete promise problem for rl, and showing that such a problem can be solved in deterministic logarithmic space given a log-space pseudorandom walk generator for regular directed graphs.
the predicate elimination strategy in theorem proving the predicate elimination strategy is a complete resolution proof strategy for multi-predicate formulas. essentially, the procedure focuses on one of the predicate symbols p, and attempts to deduce clauses independent of p by means of resolution in which only predicates in p are &ldquo;resolved away&rdquo; from parent clauses. the completeness theorem states that one can in this way, deduce an unsatisfiable p-independent set of clauses, provided the given set is unsatisfiable. the strategy is then extended to a suitable form of semantic resolution. this leads to the following strategy: in the attempt to deduce an unsatisfiable p-independent set of clauses, apply elementary resolution to &ldquo;resolve away&rdquo; predicates in p only from parent clauses, one of which has all of its predicates in p positive (negative).
a quasi-polynomial time approximation scheme for minimum weight triangulation. the minimum weight triangulation problem is to find a triangulation t&ast; of minimum length for a given set of points p in the euclidean plane. it was one of the few longstanding open problems from the famous list of twelve problems with unknown complexity status, published by garey and johnson [1979]. very recently, the problem was shown to be np-hard by mulzer and rote [2006]. in this article, we present a quasi-polynomial time approximation scheme for minimum weight triangulation.
the computational complexity of some julia sets. although numerous computer programs have been written to compute sets of points which claim to approximate julia sets, no reliable high precision pictures of non-trivial julia sets are currently known. usually, no error estimates are added and even those algorithms which work reliably in theory, become unreliable in practice due to rounding errors and the use of fixed length floating point numbers.in this paper we prove the existence of polynomial time algorithms to approximate the julia sets of complex functions f(z)=z2+c for |c|<1/4. we will give a strict computable error estimation w.r.t. the hausdorff metric dh which means that the set is recursive [10]. although these and many more julia sets j are proven to be recursive [12] and furthermore recursive compact subsets of the euclidean plane are known to have a computable turing machine time complexity [10], hardly anything is known about the computational complexity of non-trivial examples. the algorithms given in this paper compute the julia sets locally in time o(k2• m(k)) (where m(k) is a time bound for multiplication of two k-bit integers). roughly speaking, the local time complexity is the number of turing machine steps to decide for a single point whether it belongs to a grid kk⊆ (2-k• z)2 such that dh(kk,j)≤ 2-k.
how to reuse a ``write-once'' memory (preliminary version) storage media such as digital optical disks, proms, or paper tape consist of a number of -&-ldquo;write-once-&-rdquo; bit positions (wits); each wit initially contains a -&-ldquo;0-&-rdquo; that may later be irreversibly overwritten with a -&-ldquo;i-&-rdquo;. we demonstrate that such -&-ldquo;write-once memories-&-rdquo; (woms) can be -&-ldquo;rewritten-&-rdquo; to a surprising degree. for example, only 3 wits suffice to represent any 2-bit value in a way that can later be updated to represent any other 2-bit value. for large k, 1.29... k wits suffice to represent a k-bit value in a way that can be similarly updated. most surprising, allowing t writes of a k-bit value requires only t + o(t) wits, for any fixed k. for fixed t, approximately k.t/log(t) wits are required as k -&-rarr; @@@@. an n-wit wom is shown to have a -&-ldquo;capacity-&-rdquo; (i.e. k.t when writing a k-bit value t times) of up to n.log(n) bits.
a generalization and proof of the aanderaa-rosenberg conjecture we investigate the maximum number c(p) of arguments of p that must be tested in order to compute p, a boolean function of d boolean arguments. we present evidence for the general conjecture that c(p)&equil;d whenever p(0d) @@@@ p(1d) and p is left invariant by a transitive permutation group acting on the arguments. a non-constructive argument (not based on the construction of an &ldquo;oracle&rdquo;) proves the generalized conjecture for d a prime power. we use this result to prove the aanderaa-rosenberg conjecture by showing that at least v2/9 entries of the adjacency matrix of a v-vertex undirected graph g must be examined in the worst case to determine if g has any given non-trivial monotone graph property.
complexity classes of partial recursive functions (preliminary version) this paper studies possible extensions of the concept of complexity class of recursive functions to partial recursive functions. many of the well-known results for total complexity classes are shown to have corresponding, though not exactly identical, statements for partial classes. in particular, with two important exceptions, all results on the presentation and decision problems of membership for the two most reasonable definitions of partial classes are the same as for total classes. the exceptions concern presentations of the complements and maximum difficulty for decision problems of the more restricted form of partial classes. the last section of this paper shows that it is not possible to have an &ldquo;intersection theorem&rdquo;, corresponding to the union theorem of mccreight and meyer, either for complexity classes or complexity index sets.
structure of complexity in the weak monadic second-order theories of the natural numbers the complexity of decision procedures for the weak monadic second-order theories of the natural numbers are considered. if only successor is allowed as a primitive, then every alternation of second-order quantifiers causes an exponential increase in the complexity of deciding the validity of a formula. thus a heirarchy similar in form to kleene's arithmetic heirarchy may be shown to correspond to the ritchie functions. on the other hand, if first-order less-than is allowed as a primitive, one existential quantifier suffices for arbitrarily complex (in the ritchie heirarchy) decision problems. this leads to a normal form, in which every sentence in the theory is equivalent in polynomial time to a sentence with less-than but only one existential second-order quantifier.
the decidability of the reachability problem for vector addition systems (preliminary version) let v be a finite set of integral vectors in euclidian n-space, and let &abarbelow; be an integral point in the first orthant of n-space. the reachability set r(&abarbelow;,v) is the set of integral points &bbarbelow; in the first orthant such that there is a polygonal path &ggr; from &abarbelow; to &bbarbelow; satisfying (i) all of &ggr; lies in the first orthant, and (ii) the edges of &ggr; are translates of the vectors in v. the reachability problem for the vector addition system (&abarbelow;,v) asks for an algorithm to decide which integral points &bbarbelow; are in r(&abarbelow;,v). in this paper we give an algorithm to solve this problem.
a complete axiomatization for a large class of dependencies in relational databases relational database theory has discovered complete axiomatizations for functional and multivalued dependencies. however, a database design system that makes use of dependencies declared by the user must deal with some more general kinds of dependencies than these&mdash; at least with embedded multivalued dependencies. yet no axiomatization for embedded multivalued dependencies is known. in this paper, we define a more general class of dependencies, called &ldquo;template dependencies&rdquo; and give a complete axiomatization for these. we then discuss the interaction between functional dependencies and template dependencies.
algorithmic derandomization via complexity theory. we point out how the methods of nisan (1990, 1992), originally developed for derandomizing space-bounded computations, may be applied to obtain polynomial-time and nc derandomizations of several probabilistic algorithms. our list includes the randomized rounding steps of linear and semi-definite programming relaxations of optimization problems, parallel derandomization of discrepancy-type problems, and the johnson--lindenstrauss lemma, to name a few.a fascinating aspect of this style of derandomization is the fact that we often carry out the derandomizations directly from the statements about the correctness of probabilistic algorithms, rather than carefully mimicking their proofs.
exponential determinization for omega-automata with strong-fairness acceptance condition (extended abstract) in [saf88] an exponential determination procedure for bu&uml;chi automata was shown, yielding tight bounds for decision procedures of some logics ([ej88, saf88, sv89, kt89]). in [sv89] the complexity of determinization and complementation of &ohgr;-automata was further investigated, leaving as an open question the complexity of the determinization of a single class of &ohgr;-automata. for this class of &ohgr;-automata with strong fairness as acceptance condition (street automata), [sv89] managed to show an exponential complementation procedure, but showed that the blow-up of the translation of these automata to any of the classes known to admit exponential determinization is inherently exponential. this might suggest that the blow-up of the determinization of street automata is inherently doubly exponential. surprisingly, we show an exponential determinization construction for any streett automaton. in fact, the complexity of our construction is roughly the same as the complexity achieved in [saf88] for bu&uml;chi automata. moreover, a simple observation extends this upper bound to the complexity of the complementation problem. since any &ohgr;-automaton that admits exponential determinization can be easily converted into a streett automaton, we get one procedure that can be used for all of these conversions. this construction is optimal (up to a constant factor in the exponent) for all of these conversions. our results imply that streett automata (with strong fairness as acceptance condition) can be used instead of bu&uml;chi automata (with the weaker acceptance condition) without any loss of efficiency.
on decomposing languages defined by parallel devices in this paper we give a method for decomposing subclasses of different families of languages, into other possibly smaller families. this method can be used to produce languages not in a family by using known examples of languages not belonging to other families.
a data structure for dynamic trees we propose a data structure to maintain a collection of vertex-disjoint trees under a sequence of two kinds of operations: a link operation that combines two trees into one by adding an edge, and a cut operation that divides one tree into two by deleting an edge. our data structure requires o(log n) time per operation when the time is amortized over a sequence of operations. using our data structure, we obtain new fast algorithms for the following problems: (1) computing deepest common ancestors. (2) solving various network flow problems including finding maximum flows, blocking flows, and acyclic flows. (3) computing certain kinds of constrained minimum spanning trees. (4) implementing the network simplex algorithm for the transshipment problem. our most significant application is (2); we obtain an o(mn log n)-time algorithm to find a maximum flow in a network of n vertices and m edges, beating by a factor of log n the fastest algorithm previously known for sparse graphs.
space lower bounds for distance approximation in the data stream model. (math) we consider the problem of approximating the distance of two d-dimensional vectors x and y in the data stream model. in this model, the 2d coordinates are presented as a "stream" of data in some arbitrary order, where each data item includes the index and value of some coordinate and a bit that identifies the vector (x or y) to which it belongs. the goal is to minimize the amount of memory needed to approximate the distance. for the case of lp-distance with p &egr; [1,2], there are good approximation algorithms that run in polylogarithmic space in d (here we assume that each coordinate is an integer with o(log d) bits). here we prove that they do not exist for p&rho;2. in particular, we prove an optimal approximation-space tradeoff of approximating l&infty; distance of two vectors. we show that any randomized algorithm that approximates l&infty; distance of two length d vectors within factor of d&dgr; requires &omega;(d1&mdash;4&dgr;) space. as a consequence we show that for p&rho;2/(1&mdash;4&dgr;), any randomized algorithm that approximate lp distance of two length d vectors within a factor d&dgr; requires &omega;(d 1&mdash; 2< \over p&mdash;4&dgr;) space.the lower bound follows from a lower bound on the two-party one-round communication complexity of this problem. this lower bound is proved using a combination of information theory and fourier analysis.
self-adjusting binary trees we use the idea of self-adjusting trees to create new, simple data structures for priority queues (which we call heaps) and search trees. unlike other efficient implementations of these data structures, self-adjusting trees have no balance condition. instead, whenever the tree is accessed, certain adjustments take place. (in the case of heaps, the adjustment is a sequence of exchanges of children, in the case of search trees the adjustment is a sequence of rotations.) self-adjusting trees are efficient in an amortized sense: any particular operation may be slow but any sequence of operations must be fast. self-adjusting trees have two advantages over the corresponding balanced trees in both applications. first, they are simpler to implement because there are fewer cases in the algorithms. second, they are more storage-efficient because no balance information needs to be stored. furthermore, a self-adjusting search tree has the remarkable property that its running time (for any sufficiently long sequence of search operations) is within a constant factor of the running time for the same set of searches on any fixed binary tree. it follows that a self-adjusting tree is (up to a constant factor) as fast as the optimal fixed tree for a particular probability distribution of search requests, even though the distribution is unknown.
wait-free k-set agreement is impossible: the topology of public knowledge. in the classical consensus problem, each of n processors receives a private input value and produces a decision value which is one of the original input values, with the requirement that all processors decide the same value. a central result in distributed computing is that, in several standard models including the asynchronous shared-memory model, this problem has no deterministic solution. the k-set agreement problem is a generalization of the classical consensus proposed by chaudhuri [ inform. and comput., 105 (1993), pp. 132--158], where the agreement condition is weakened so that the decision values produced may be different, as long as the number of distinct values is at most k. for $n>k\geq 2$ it was not known whether this problem is solvable deterministically in the asynchronous shared memory model. in this paper, we resolve this question by showing that for any k < n, there is no deterministic wait-free protocol for n processors that solves the k-set agreement problem. the proof technique is new: it is based on the development of a topological structure on the set of possible processor schedules of a protocol. this topological structure has a natural interpretation in terms of the knowledge of the processors of the state of the system. this structure reveals a close analogy between the impossibility of wait-free k-set agreement and the brouwer fixed point theorem for the k-dimensional ball.
correct and optimal implementations of recursion in a simple programming language the object of this paper is to study the mechanism of recursion in a simple, lisp-like programming language, where the only mean of iteration is through recursion. the theory of computation developped in scott [4] provides the framework of our study. we show how the implementations of recursion which deserve to be called &ldquo;correct&rdquo; can be characterized semantically, and demonstrate a general criterion for the correctness of an implementation. we then describe an implementation of recursion which is both correct and optimal in a general class of sequential languages, and therefore constitutes an attractive alternative to both &ldquo;call-by-name&rdquo; and &ldquo;call-by-value&rdquo;.
spectral norm of random matrices. in this paper, we present a new upper bound for the spectral norm of symmetric random matrices with independent (but not necessarily identical) entries. our results improve an earlier result of f&#x00fc;redi and koml&#x00f3;s.
a complexity theoretic approach to randomness we study a time bounded variant of kolmogorov complexity. this notion, together with universal hashing, can be used to show that problems solvable probabilistically in polynomial time are all within the second level of the polynomial time hierarchy. we also discuss applications to the theory of probabilistic constructions.
on obfuscating point functions. we investigate the possibility of obfuscating point functions in the framework of barak et al. from crypto '01. a point function is a boolean function that assumes the value 1 at exactly one point. our main results are as follows:we provide a simple construction of efficient obfuscators for point functions for a slightly relaxed notion of obfuscation, for which obfuscating general circuits is nonetheless impossible. our construction relies on the existence of a very strong one-way permutation, and yields the first non-trivial obfuscator under general assumptions in the standard model. we also obtain obfuscators for point functions with multi-bit output and for prefix matching.our assumption is that there is a one-way permutation wherein any polynomial-sized circuit inverts the permutation on at most a polynomial number of inputs. we show that a similar assumption is in fact necessary, and that our assumption holds relative to a random permutation oracle.finally, we establish two impossibility results which indicate that the limitations on our construction, namely simulating only adversaries with single-bit output and using nonuniform advice in our simulator, are in some sense inherent.previous work gave negative results for the general class of circuits (barak et al., crypto '01) and positive results in the random oracle model (lynn et al., eurocrypt '04) or under non-standard number-theoretic assumptions (canetti, crypto '97). this work represents the first effort to bridge the gap between the two for a natural class of functionalities.
gowers uniformity, influence of variables, and pcps. we study the relation of query complexity and soundness in probabilistically checkable proofs (pcps). we present a pcp verifier for languages that are unique-games-hard and such that the verifier makes $q$ queries, has almost perfect completeness, and has soundness error at most $2q/2^q+\varepsilon$ for arbitrarily small $\varepsilon>0$. for values of $q$ of the form $2^t-1$, the soundness error is $(q+1)/2^q+\varepsilon$. charikar, makarychev, and makarychev show that there is a constant $\beta$ such that every language that has a verifier of query complexity $q$ and a ratio of soundness error to completeness smaller than $\beta q/2^q$ is decidable in polynomial time. up to the value of the multiplicative constant and to the validity of the unique games conjecture, our result is therefore tight. as a corollary, we show that approximating the maximum independent set problem in graphs of degree $\delta$ within a factor better than $\delta/(\log\delta)^\alpha$ is unique-games-hard for a certain constant $\alpha>0$. our main technical results are (i) a connection between the gowers uniformity of a boolean function and the influence of its variables and (ii) the proof that &ldquo;gowers uniform&rdquo; functions pass the &ldquo;hypergraph linearity test&rdquo; approximately with the same probability of a random function. the connection between gowers uniformity and influence might have other applications.
the round complexity of two-party random selection. we study the round complexity of two-party protocols for generating a random n-bit string such that the output is guaranteed to have bounded bias (according to some measure) even if one of the two parties deviates from the protocol (even using unlimited computational resources). specifically, we require that the output's statistical difference from the uniform distribution on zon is bounded by a constant less than 1.we present a protocol for the above problem that has 2 log*n+o(1) rounds, improving a 2n-round protocol that follows from the work of goldreich, goldwasser, and linial (focs'91). like the ggl protocol, our protocol actually provides a stronger guarantee, ensuring that the output lands in any set t⊆zon of density μ with probability at most o(√μ+δ), where δ is an arbitarily small constant.we then prove a matching lower bound, showing that any protocol guaranteeing bounded statistical difference requires at least log*n - log* log*n-o(1) rounds. as far as we know, this is the first nontrivial lower bound on the round complexity of random selection protocols (of any type) that does not impose additional constraints (e.g. on communication or "simulatability").we also state several results for the case when the output's bias is measured by the maximum multiplicative factor by which a party can increase the probability of a set t ⊆ zon.
on tape versus core; an application of space efficient perfect hash functions to the invariance of space in complexity theory the use of informal estimates can be justified by appealing to the invariance thesis which states that all standard models of computing devices are sufficiently equivalent. this thesis would require, among others, that a ram can be simulated by a turingmachine with constant factor overhead in space. such a simulation is hard to obtain if the traditional spacemeasure for ram-space is used. the simulation uses a new method for condensing space, based on perfect hashing.
algebraic methods in the theory of lower bounds for boolean circuit complexity we use algebraic methods to get lower bounds for complexity of different functions based on constant depth unbounded fan-in circuits with the given set of basic operations. in particular, we prove that depth k circuits with gates not, or and modp where p is a prime require exp(&ogr;(n1/2k)) gates to calculate modr functions for any r &ne; pm. this statement contains as special cases yao's parity result [ ya 85 ] and razborov's new majority result [ra 86] (modm gate is an oracle which outputs zero, if the number of ones is divisible by m).
quantum and classical query complexities of local search are polynomially related. let f be an integer valued function on a finite set v. we call an undirected graph g(v,e) a neighborhood structure for f. the problem of finding a local minimum for f can be phrased as: for a fixed neighborhood structure g(v,e) find a vertex x ∈ v such that f(x) is not bigger than any value that f takes on some neighbor of x. the complexity of the algorithm is measured by the number of questions of the form "what is the value of f on x?" we show that the deterministic, randomized and quantum query complexities of the problem are polynomially related. this generalizes earlier results of aldous[4] ald and aaronson [1] aar and solves the main open problem in aar.
reimer's inequality and tardos' conjecture. (math) let f: {0,1}n &rarr; {0,1} be a boolean function. for &egr;&roe; 0 de(f) be the minimum depth of a decision tree for f that makes an error for &xie;&egr; fraction of the inputs &khar; &egr; {0,1}n. we also make an appropriate definition of the approximate certificate complexity of f, c&egr;(f). in particular, d0(f) and c0(f) are the ordinary decision and certificate complexities of f. it is known that $d_0(f) \leq (c_0(f))^2$. answering a question of tardos from 1989, we show that for all $\ge > 0$ there exists a $\gd' > 0$ such that for all $0 \leq \gd < \gd'$, we have $d_\ge(f) \leq k (c_\gd(f))^2$ where $k = k(\ge,\gd) > 0$ is a constant independent of f. the algorithm used in the proof is modeled after those developed by r. impagliazzo and s. rudich for use in other problems.
algebraic structure theory of stochastic machines in the present paper, an algebraic structure theory of stochastic machines is developed which contains both bacon's theory [1] and hartmanis' theory for deterministic machines [5] as special cases. although the present theory is patterned after both theories, it exhibits many interesting features which are here-to-fore unknown. among other things, it is shown that the basic concepts involved, e.g., partitions with substitution property, partition pairs, state-behavior realizations, are all equivalent to well-known concepts in linear algebra. section ii introduces the model of stochastic machines to be used in subsequent developments. in section iii, various types of realizations and assignments are introduced. the concepts of partitions with substitution property, partition pairs, etc. are introduced in section iii. the last section gives a formulation of a network of concurrently operating qsms.
time-space tradeoff lower bounds for integer multiplication and graphs of arithmetic functions. we prove exponential size lower bounds for nondeterministic and randomized read-k bps as well as a time-space tradeoff lower bound for unrestricted, deterministic multi-way bps computing the middle bit of integer multiplication. the lower bound for randomized read-k bps is superpolynomial as long as the error probability is superpolynomially small. for polynomially small error, we have a polynomial upper bound on the size of approximating read once bps for this function. the lower bounds follow from a more general result for the graphs of universal hash classes that is applicable to the graphs of arithmetic functions such as integer multiplication, convolution, and finite field multiplication.
smoothed analysis of algorithms: why the simplex algorithm usually takes polynomial time. we introduce the smoothed analysis of algorithms, which continuously interpolates between the worst-case and average-case analyses of algorithms. in smoothed analysis, we measure the maximum over inputs of the expected performance of an algorithm under small random perturbations of that input. we measure this performance in terms of both the input size and the magnitude of the perturbations. we show that the simplex algorithm has smoothed complexity polynomial in the input size and the standard deviation of gaussian perturbations.
deterministic simulation of non-deterministic turing machines (detailed abstract) computations of non-deterministic turing machines are shown to correspond to &ldquo;solving&rdquo; certain mazes. the storage needed to &ldquo;solve&rdquo; mazes is related to the storage needed to deterministically simulate non-deterministic turing machines. in particular, it is shown that a non-deterministic l(n)-tape bounded turing machine can be simulated by an (l(n))2-tape bounded turing machine, provided l(n)&ge;log2n.
nearly-linear time algorithms for graph partitioning, graph sparsification, and solving linear systems. we present algorithms for solving symmetric, diagonally-dominant linear systems to accuracy ε in time linear in their number of non-zeros and log (κf (a) ε), where κf (a) is the condition number of the matrix defining the linear system. our algorithm applies the preconditioned chebyshev iteration with preconditioners designed using nearly-linear time algorithms for graph sparsification and graph partitioning.
maze recognizing automata (extended abstract) in [2], computations of nondeterministic machines are shown to correspond to threadings of certain mazes. we briefly summarize these results and then obtain some new extentions of them. a new device called a maze-recognizing automaton is introduced. this is a type of finite-state device that crawls through mazes. the following statements are proven equivalent. (i) there is a maze-recognizing automaton which recognizes the threadable mazes. (ii) every nondeterministic l(n) tape-bounded turing machine is equivalent to some deterministic l(n) tape-bounded turing machine, provided l(n) &ge; log2n.
complexity of decision problems based on finite two-person perfect-information games we present a number of simply-structured combinatorial games for which the problem of determining the outcome of optimal play is complete in polynomial space&mdash;a condition which gives very strong assurance that these problems are hard. in addition to proving this completeness property for some particular games, we introduce a general technique for deriving games complete in polynomial space from np-complete problems.
the complexity of satisfiability problems the problem of deciding whether a given propositional formula in conjunctive normal form is satisfiable has been widely studied. i t is known that, when restricted to formulas having only two literals per clause, this problem has an efficient (polynomial-time) solution. but the same problem on formulas having three literals per clause is np-complete, and hence probably does not have any efficient solution. in this paper, we consider an infinite class of satisfiability problems which contains these two particular problems as special cases, and show that every member of this class is either polynomial-time decidable or np-complete. the infinite collection of new np-complete problems so obtained may prove very useful in finding other new np-complete problems. the classification of the polynomial-time decidable cases yields new problems that are complete in polynomial time and in nondeterministic log space. we also consider an analogous class of problems, involving quantified formulas, which has the property that every member is either polynomial time decidable or complete in polynomial space.
graph ramsey theory and the polynomial hierarchy. in the ramsey theory of graphs f arrows (g,h) means that for every way of coloring the edges of f red and blue f will contain either a red g or a blue h. the problem arrowing of deciding whether f arrows (g,h) lies in conp^np and it was shown to be conp-hard by burr in 1990. we prove that arrowing is actually conp^np-complete, simultaneously settling a conjecture of burr and providing a rare natural example of a problem complete for a higher level of the polynomial hierarchy. we also show that strong arrowing, the version for induced subgraphs, is complete for conp^np under turing-reductions.
decidability of string graphs. we show that string graphs can be recognized in nondeterministic exponential time by giving an exponential upper bound on the number of intersections for a drawing realizing the string graph in the plane. this upper bound confirms a conjecture by kratochv\'{\i}l and matou\v{s}ek~\cite{km91} and settles the long-standing open problem of the decidability of string graph recognition (sinden~\cite{s66}, graham~\cite{g76}). finally we show how to apply the result to solve another old open problem: deciding the existence of euler diagrams, a central problem of topological inference (grigni, papadias, papadimitriou~\cite{gpp95}).
optimal rate-based scheduling on multiprocessors. the pd2 pfair/erfair scheduling algorithm is the most efficient known algorithm for optimally scheduling periodic tasks on multiprocessors. in this paper, we prove that pd2 is also optimal for scheduling "rate-based" tasks whose processing steps may be highly jittered. the rate-based task model we consider generalizes the widely-studied sporadic task model.
recognizing string graphs in np. a string graph is the intersection graph of a set of curves in the plane. each curve is represented by a vertex, and an edge between two vertices means that the corresponding curves intersect. we show that string graphs can be recognized in np. the recognition problem was not known to be decidable until very recently, when two independent papers established exponential upper bounds on the number of intersections needed to realize a string graph (mutzel (ed.), graph drawing 2001, lecture notes in computer science, springer, berlin; proceedings of the 33rd annual acm symposium on theory of computing (stoc-2001)). these results implied that the recognition problem lies in nexp. in the present paper we improve this by showing that the recognition problem for string graphs is in np, and therefore np-complete, since kratochvíl showed that the recognition problem is np-hard (j. combin theory, ser. b 52). the result has consequences for the computational complexity of problems in graph drawing, and topological inference. we also show that the string graph problem is decidable for surfaces of arbitrary genus.
a constant-factor approximation algorithm for packet routing, and balancing local vs. global criteria. we present the first constant-factor approximation algorithm for a fundamental problem: the store-and-forward packet routing problem on arbitrary networks. furthermore, the queue sizes required at the edges are bounded by an absolute constant. thus, this algorithm balances a global criterion (routing time) with a local criterion (maximum queue size) and shows how to get simultaneous good bounds for both. for this particular problem, approximating the routing time well, even without considering the queue sizes, was open. we then consider a class of such local vs. global problems in the context of covering integer programs and show how to improve the local criterion by a logarithmic factor by losing a constant factor in the global criterion.
on the power of quantum fingerprinting. in the simultaneous message model, two parties holding n-bit integers x,y send messages to a third party, the referee, enabling him to compute a boolean function f(x,y). buhrman et al [3] proved the remarkable result that, when f is the equality function, the referee can solve this problem by comparing short "quantum fingerprints" sent by the two parties, i.e., there exists a quantum protocol using only o(log n) bits. this is in contrast to the well-known classical case for which ω(n1/2) bits are provably necessary for the same problem even with randomization. in this paper we show that short quantum fingerprints can be used to solve the problem for a much larger class of functions. let r<??par line>,pub(f) denote the number of bits needed in the classical case, assuming in addition a common sequence of random bits is known to all parties (the public coin model). we prove that, if r<??par line>,pub(f)=o(1), then there exists a quantum protocol for f using only o(log n) bits. as an application we show that o(log n) quantum bits suffice for the bounded hamming distance function, defined by f(x,y)=1 if and only if x and y have a constant hamming distance d or less.
a new average case analysis for completion time scheduling. we present a new average case analysis for the problem of scheduling n jobs on m machines so that the sum of job completion times is minimized. our goal is to use the concept of competitive ratio---which is a typical worst case notion---also within an average case analysis. we show that the classic sept scheduling strategy with &omega;(n) worst-case competitive ratio achieves an average of o(1) under several natural distributions, among them the exponential distribution. our analysis technique allows to also roughly estimate the probability distribution of the competitive ratio. thus, our result bridges the gap between worst case and average case performance guarantee.
formal languages and power series section 1 of this paper presents the basic mathematical definitions for our work. section 2 defines the notion of a weighted phrase-structure grammar over either a semiring or zero monoid coefficient structure. the notion of canonical derivations (from griffiths [1968]) and top-down derivations is defined in section 3, along with some of their basic properties. equivalence relations over weighted phrase-structure grammars are defined in section 4 as well as power series representations of the associated languages. section 5 shows that every weighted type 0 grammar is equivalent to a grammar in standard form. section 6 describes the equations associated with a grammar in standard form and describes a process of iteratively obtaining approximations to the language.
how to spread adversarial nodes?: rotate! in this paper we study the problem of how to keep a dynamic system of nodes well-mixed even under adversarial behavior. this problem is very important in the context of distributed systems.more specifically, we consider the following game: there are n white pebbles and ε n black pebbles for some fixed constant ε < 1. initially, all of the white pebbles are laid down in a ring, and the adversary has all of the black pebbles in its bag. in each round, the adversary can look at the entire ring and can select to add a black pebble to the ring (if its bag is not empty) or to take any black pebble from the ring and put it back into its bag (i.e. we consider adaptive adversaries). however, the adversary cannot place a black pebble into any position it likes. this is handled by a join strategy to be specified by the system. the goal is to find an oblivious join strategy, i.e. a strategy that cannot distinguish between the white and black pebbles in the ring, that integrates the black pebbles into this ring and may do some further rearrangements so that for a polynomial number of rounds the adversary will not manage to include its black pebbles into the ring so that there is a sequence of s=θ(log n) consecutive pebbles in which at least half of the pebbles are black. if this is achieved by the join strategy, it wins. otherwise, the adversary wins.of course, the brute-force strategy of rearranging all of the pebbles in the ring at random after each insertion of a black pebble will achieve the stated goal, with high probability, but this would be a very expensive strategy. the challenge is to find a join strategy that needs as little randomness and as few rearrangements as possible in order to win with high probability. in this paper, we present and analyze a very simple strategy called k-rotation that chooses k-1 existing positions uniformly at random in the ring, creates a new position uniformly at random in the ring, and then rotates the new pebble and the k-1 old pebbles along these positions. interestingly, even if the adversary has just $s$ pebbles, it can still win for k=2. but the k-rotation rule wins with high probability for k=3 as long as ε<2/3, demonstrating that there is a sharp threshold for keeping pebbles in a sufficiently perturbed state.
from static to dynamic routing: efficient transformations of store-and-forward protocols. we investigate how static store-and-forward routing algorithms can be transformed into efficient dynamic algorithms, that is, how algorithms that have been designed for the case that all packets are injected at the same time can be adapted to more realistic scenarios in which packets are continuously injected into the network. besides describing specific transformations for well-known static routing algorithms, we present a black box transformation scheme applicable to every static, oblivious routing algorithm. we analyze the performance of our protocols under a stochastic and an adversarial model of packet injections.one result of our specific transformations is the first dynamic routing algorithm for leveled networks that is stable for arbitrary admissible injection rates and that works with packet buffers of size depending solely on the injection rate and the node degree, but not on the size of the network. furthermore, we prove strong delay bounds for the packets. our results imply, for example, that a throughput of 99% can be achieved on an n-input butterfly network with buffers of constant size while each packet is delivered in time o(log n), with high probability.our black box transformation ensures that if the static algorithm is pure (i.e., no extra packets apart from the original packets are routed), its dynamic variant is stable up to a maximum possible injection rate. furthermore, in the stochastic model, the routing time of a packet depends on local parameters such as the length of its routing path, rather than on the maximum possible path length, even if the static algorithm chosen for the transformation does not provide this locality feature and is not pure. in the adversarial model, the delay bound of the packets is closely related to the time bound given for the static algorithm.
word problems requiring exponential time: preliminary report the equivalence problem for kleene's regular expressions has several effective solutions, all of which are computationally inefficient. in [1], we showed that this inefficiency is an inherent property of the problem by showing that the problem of membership in any arbitrary context-sensitive language was easily reducible to the equivalence problem for regular expressions. we also showed that with a squaring abbreviation ( writing (e)2 for e&times;e) the equivalence problem for expressions required computing space exponential in the size of the expressions. in this paper we consider a number of similar decidable word problems from automata theory and logic whose inherent computational complexity can be precisely characterized in terms of time or space requirements on deterministic or nondeterministic turing machines. the definitions of the word problems and a table summarizing their complexity appears in the next section. more detailed comments and an outline of some of the proofs follows in the remaining sections. complete proofs will appear in the forthcoming papers [9, 10, 13]. in the final section we describe some open problems.
the node cost measure for embedding graphs on the planar grid (extended abstract) the two major cost measures used in the past for grid embeddings are area (or the area of the smallest square or rectangle that contains the embedding) and total edge length. this paper is primarily concerned with a third measure, total number of nodes. to embed a graph on the planar grid, it may be necessary to &ldquo;bend&rdquo; edges. this can be modeled by allowing the insertion of nodes along edges of the graph and then insisting that the embedding may not bend edges.
the macro model for data compression (extended abstract) a general model for data compression is presented which includes most data compression systems in the literature as special cases. all macro schemes are based on the principle of finding redundant strings or patterns and replacing them by pointers to a common copy. different varieties of macro schemes may be defined by varying the interpretation of pointers, for instance, a pointer may indicate a substring of the compressed string, a substring of the original string, or a substring of some other string such as an external dictionary. other varieties of macros schemes may be defined by restricting the type of overlapping or recursion that may be used. trade-offs between different varieties of macro schemes, exact lower bounds on the amount of compression obtainable, and the complexity of encoding and decoding are discussed as well as how the work of other authors (such as lempel-ziv) relates to this model.
polynomial time quantum algorithm for the computation of the unit group of a number field. we present a quantum algorithm for the computation of the irrational period lattice of a function on zn which is periodic in a relaxed sense. this algorithm is applied to compute the unit group of finite extensions of q. execution time for fixed field degree over q is polynomial in the discriminant of the field. our algorithms generalize and improve upon hallgren's work [9] for the one-dimensional case corresponding to real-quadratic fields.
topological matching there is a lot of practical and theoretical interest in designing algorithms to process digital pictures. of particular interest are problems arising when one starts with an nxn array of pixels and stores it, one pixel per processor, in some sort of array-like parallel computer. in this paper we give an optimal &thgr;(n) time solution, based on a simpler &thgr;(n) time solution for a more powerful computer called a mesh computer. beyer suggested that this problem was a prime candidate for a non-linear recognition problem, but our result shows that this is not true.
the process complexity and effective random tests we propose a variant of the kolmogorov concept of complexity which yields a common theory of finite and infinite random sequences. the process complexity does not oscillate. we establish some concepts of effective tests which are proved to be equivalent.
propositional dynamic logic of looping and converse propositional dynamic logic can be extended to include both an infinitary iteration construct delta and a backtracking construct converse. the resulting logic does not satisfy the finite model property, but is nevertheless elementarily decidable. in order to establish this decidability result, deterministic two-way automata on infinite trees are defined and shown to be reducible to nondeterministic one-way automata on infinite trees. the decision procedure suggests a nonstandard semantics for the extended logic for which the finite model property does hold.
translating recursion equations into flow charts this paper proposes the foundations for a systematic study of the translation of recursive function definitions into flow charts (often called the removal of recursions). several notions of translation are presented. emphasis is placed on translation which could be performed mechanically, operating only on the syntactical structure of the recursion equations. systems of recursion equations are classified by structure and by the dynamics of their implicit computations. theorems on the limitations of translation are based on these classifications. an effective first approximation to a syntactic characterization of one notion of translatability is presented. finally, open problems are discussed. space limitations prevent the inclusion of proofs or lengthy definitions.
vector execution of flow graphs (extended abstract) given a vector of tasks intended to execute the same program simultaneously on a machine which can execute only one instruction at a time, but can execute that instruction for any specified subset of the vector, the object is to schedule the execution to take maximal advantage of parallelism. such a scheduling is called a vector execution scheme. a class of &ldquo;perfect&rdquo; programs is characterized for which such scheduling is easy and on which many vector execution schemes are optimal. this characterization shows that scheduling difficulties arise from unrestricted use of gotos producing irreducible programs, from branches in loops, and from nested loops. once the path through the program is known for each task, it is a finite problem to find an optimal schedule; so there is an optimal vector execution scheme, even over imperfect programs. however, there is no implementable vector execution scheme which does not make use of knowledge of the future and which is optimal with respect to length of execution sequences. some implementable vector execution schemes based on priority ordering and node sequence approaches are studied and compared as to worst case behavior on imperfect programs.
sample spaces uniform on neighborhoods let a universe of m elements be given, along with a family of subsets of the universe (neighborhoods), each of size at most k. we describe methods for assigning the m elements to points in a small-dimensional vector space (over gf(2)), in such a way that the elements in each neighborhood are assigned to an independent set of vectors. such constructions lead, through a standard correspondence between linear and statistical independence, to the construction of small sample spaces which restrict to the uniform distribution in each neighborhood. (the sample space is a uniformly-weighted family of binary m-vectors). the size of such a small space will be a function of the number of neighborhoods; and for sparse families, will be substantially smaller than any space which restricts to the uniform distribution in all k-sets. previous work on small spaces with limited independence focused on providing independence or near-independence in every k-set of the universe. we show how to construct the sample spaces efficiently both sequentially and in parallel. in case there are polynomially many (in m) neighborhoods, each of size o(log m), the parallel construction is in nc. these spaces provide a new derandomization technique for algorithms; particularly, algorithms related to the lova&acute;sz local lemma. we also describe applications to the exhaustive testing of vlsi circuits, and to coding for burst errors on noisy channels.
on deterministic context-free languages, multihead automata, and the power of an auxiliary pushdown store a deterministic context-free language l0 is described which is log(n)-complete for the family of languages recognized by deterministic log(n)- tape bounded auxiliary pushdown automata in polynomial time. it follows that l0 is a &ldquo;hardest&rdquo; deterministic context-free language (dcfl), since all dcfl's are recognized in polynomial time by deterministic pushdown automata. l0 is, moreover, a simple precedence language and a simple ll(1) language. thus the tape complexities of these proper subfamilies are essentially the same as the tape complexity of all dcfl's. we show that an auxiliary pushdown store does, in fact, add some power to some restricted families of log(n)-tape bounded turing machines. the basic result is that every two-way 2k-head nondeterministic finite automation can be replaced by an equivalent two-way k-head nondeterministic pushdown automation. this indicates, also, that every 2k-head nondeterministic finite automation language can be recognized in 0(n3k) steps. other results relate multihead automata classes with other multihead automata classes, with families recognized by log(n)-tape bounded turing machines with restricted tape alphabets, and with time-bounded complexity classes.
separating tape bounded auxiliary pushdown automata classes previous results in the literature which describe separation theorems for time bounded complexity classes serve also to separate classes defined by tape bounded auxiliary pushdown automata. results described here refine these basic relationships between classes defined by tape bounded auxpda. it is shown that, for auxiliary pda fully constructable functions s0 and s1 satisfying s1 (n+1) &egr; o,(s0 (n)), s0 tape bounded auxpda are more powerful than s1 tape bounded auxpda. further results refine the resulting separation by the number of worktape symbols and the number of worktape heads. results are also described for separating classes defined by tape bounded auxpda with one pushdown store symbol, i.e. auxiliary counter automata (auxca). refinements of the known equivalence of nondeterministic l(n)-tape bounded auxpda and deterministic l(n)-tape bounded auxpda are also described. one corollary is that every two-way nondeterministic pda can be simulated by a two-way deterministic pda with four input tape heads and that every context-free language can be recognized by a deterministic two-way pda with three heads. another corollary of these results shows that there are languages over a single letter alphabet which are recognized by (k+1)-head two-way pda but cannot be recognized by any k-head two-way pda. it is shown also that auxpda and auxca can fully construct very slow growing functions so that even small amounts of worktape space (e.g. that bounded by log*n) increase their computational power.
unique binary search tree representations and equality-testing of sets and sequences this paper studies the problem of representing sets over an ordered universe by unique binary search trees, so that dictionary operations can be performed efficiently on any set. although efficient randomized solutions to the problem are known, its deterministic complexity has been open. the paper exhibits representations that permit the execution of dictionary operations in optimal deterministic time when the dictionary is sufficiently sparse or sufficiently dense. the results demonstrate an exponential separation between the deterministic and randomized complexities of the problem. unique representations are applied to obtain efficient data structures for maintaining a dynamic collection of sets/sequences under queries that test the equality of a pair of objects. the data structure for set equality testing tests equality of sets in constant time and processes set updates in $o(\log m)$ amortized time and $o(\log m)$ space, where $m$ denotes the total number of updates performed. it is based on an efficient implementation of cascades of c{\vipt ons} operations on uniquely stored s-expressions. the data structure for sequence equality testing tests equality of sequences in constant time and processes updates in $o(\sqrt{n \log m}\, + \log m)$ amortized time and $o(\sqrt{n})$ amortized space where $n$ denotes the length of the sequence that is updated and $m$ denotes the total number of updates performed.
heuristics for weighted perfect matching the problem of finding near optimal perfect matchings of an even number n of vertices is considered. when the distances between the vertices satisfy the triangle inequality it is possible to get within a constant multiplicative factor of the optimal matching in time o(n2 log k) where k is the ratio of the longest to the shortest distance between vertices. other heuristics are analyzed as well, including one that gets within a logarithmic factor of the optimal matching in time o(n2 log n). finding an optimal weighted matching requires &thgr;(n3) time by the fastest known algorithm, so these heuristics are quite useful. when the n vertices lie in the unit (euclidean) square, no heuristic can be guaranteed to produce a matching of cost less than [equation] in the worst case. we analyze various heuristics for this case, including one that always produces a matching costing at most [equation]. in addition, this heuristic also finds a traveling salesman tour of the n vertices costing at most [equation]. a different one of the heuristics analyzed produces asymptotically optimal results. it is also shown that asymptotically optimal traveling salesman tours can be found in o(n log n) time in the unit square.
computability theory in admissible domains denotational semantics was introduced by strachey as a means of defining semantics of programming languages. it's mathematical foundation was justified by scott [14] in 1969 when he introduced continuous lattices to model data types and showed how to solve reflexive domain equations. it is not the case that any solution of a given reflexive domain equation is a suitable model for studying denotational semantics. in programming languages, the constructs that we deal with can all be realizable by some machines, hence their meanings, considered as mathematical objects in a lattice, should be computable. in other words, we need a solution where we can formalize the notion of computability. of course, this means that many continuous lattices are irrelevant to the study of denotational semantics of programming languages. it is the purpose of this paper to isolate those lattices which are relevant.
multicommodity flows in planar undirected graphs and shortest paths this paper deals with the multicommodity flow problems for two classes of planar undirected graphs. the first class c12 consists of graphs in which each source-sink pair is located on one of two specified face boundaries. the second class c01 consists of graphs in which some of the source-sink pairs are located on a specified face boundary and all the other pairs share a common sink located on the boundary. we show that the multicommodity flow problem for a graph in c12 (resp. c01) can be reduced to the shortest path problem for an undirected (resp. a directed) graph obtained from the dual of the original undirected graph.
the complexity of finding periods given a function f over a finite domain d and an arbitrary starting point x, the sequence x,f(x),f(f(x)),... is ultimately periodic. such sequences typically are used for constructing random number generators. the cycle problem is to determine the first repeated element fn(x) in the sequence. previous algorithms for this problem have required 3n operations. in this paper we present an algorithm which only requires n(1+o(1/(@@@@)m)) steps, if m memory cells are available to store values of the function. by increasing m, this running time can be made arbitrarily close to the information-theoretic lower bound on the running time of any algorithm for the cycle problem. our treatment is novel in that we explicitly consider the performance of the algorithm as a function of the amount of memory available as well as the relative cost of evaluating f and comparing sequence elements for equality.
the computation of finite functions this paper discusses the computation of finite functions with the aim of investigating ways of judging the relative worth of the different methods for computing a given finite function. any finite function may, of course, be computed in a number of ways, including a &ldquo;brute-force&rdquo; method of table look-up and methods which exploit some pattern which may exist in the function. how &ldquo;good&rdquo; we judge each of the several methods to be will depend on which criteria we wish to apply, and here we will be considering two: size of program and cost of computation, first of all separately, and then together. the latter case gives rise to the notion of a &ldquo;reasonable&rdquo; way of computing a finite function, and certain considerations with respect to this notion suggest a modified notion of &ldquo;relatively reasonable&rdquo;. some properties of these concepts, in particular some of the differences between them, are developed. the spirit of the paper is machine-independent except for the last paragraph which suggests a need for some idea of &ldquo;program structure&rdquo; to be introduced into the formulation.
the dlt priority sampling is essentially optimal. the priority sampling procedure of n. duffield, c. lund and m. thorup is not only an exciting new approach to sampling weighted data streams, but it has also proven to be highly successful in a variety of practical applications. we resolve the two major issues related to its performance. first we solve the main conjecture of n. alon, n. duffield, c. lund and m. thorup in [1], which states that the standard deviation for the subset sum estimator obtained from k priority samples is upper bounded by w/√k-1, where w denotes the actual subset sum that the estimator estimates. although alon et al. give an o(w/√k-1) upper bound on the standard deviation of the estimator, their formula cannot be used as a performance guarantee in an applied setting, because the constants coming up in their proof are very large. our constant cannot be improved. we also resolve the conjecture of duffield, c. lund and m. thorup which states that the variance of the priority sampling procedure is not larger than the variance of the threshold sampling procedure with sample size only one smaller. this is the main conjecture in [7]. the conjecture's significance is that the latter procedure is provably optimal within a very general class of sampling algorithms, but unlike priority sampling, it is not practical. our result therefore certifies that priority sampling offers the unlikely feat of uniting mathematical elegance, (essential) optimality and applicability. our proof is based on a new integral formula and on very finely tuned telescopic sums.
observations on nondeterministic multidimensional iterative arrays let nia(d) be the family of languages accepted within linear time by nondeterministic d-dimensional iterative arrays. (on-line deterministic multidimensional iterative arrays have been studied by cole [2].) it has been observed [8] that every language accepted by a one-dimensional single-head turing machine simultaneously within time n2 and space n is in nia(2). our main result (theorem 2) generalizes this observation to ntime(nd) @@@@ nia(d), where ntime(t(n)) is the family of languages accepted within time t(n) by nondeterministic one-dimensional multihead turing machines. conversely, we show that nia(d) @@@@ ntime(nd+l) (theorem 3). the two facts together show [equation]nia(d) = [equation]ntime(nd), which is the same as karp's class np [6]. we also use both facts in a proof that nia(d) @@@@ nia(d+2). let ntm(d) be the family of languages accepted within linear time by nondeterministic d-dimensional multihead turing machines. a real-time simulation of turing machines by iterative arrays gives ntm(d) @@@@ nia(d) (theorem 1), but a less direct simulation (using theorem 2) gives the stronger result [equation] ntm(d) @@@@ nia(2). thus, in the nondeterministic case, two-dimensional iterative arrays outperform all multi-dimensional multihead turing machines. finally, in section 7, we examine related deterministic questions and summarize.
validating register allocations for straight line programs straight line programs are essentially sequences of assignment statements. a general program consists of straight line segments with flow of control between these segments. the interfaces between a straight line segment and the rest of the program place constraints on register allocations for the segment. these constraints may render a register allocation for a straight line program unrealizable. an algorithm is given to determine if a register allocation for a straight line program is realizable. it is shown that the algorithm takes 0(n3) steps, where n is the number of statements in the program. an unrealizable assignment may be made realizable by introducing stores into memory at appropriate points. it is shown how the minimum number of such stores may be found.
loss-less condensers, unbalanced expanders, and extractors. an extractor is a procedure which extracts randomness from a detective random source using a few additional random bits. explicit extractor constructions have numerous applications and obtaining such constructions is an important derandomization goal. trevisan recently introduced an elegant extractor construction, but the number of truly random bits required is suboptimal when the input source has low-min-entropy. significant progress toward overcoming this bottleneck has been made, but so far has required complicated recursive techniques that lose the simplicity of trevisan's construction. we give a clean method for overcoming this bottleneck by constructing {\em loss-less condensers}. which compress the n-bit input source without losing any min-entropy, using o(\log n) additional random bits. our condensers are built using a simple modification of trevisan's construction, and yield the best extractor constructions to date. loss-less condensers also produce unbalanced bipartite expander graphs with small (polylogarithmic) degree d and very strong expansion of (1-\epilon)d. we give other applications of our construction, including dispersers with entropy loss o(\log n), depth two super-concentrators whose size is within a polylog of optimal, and an improved hardness of approximation result.
complete register allocation problems the search for efficient algorithms for register allocation dates back to the time of the first fortran compiler for the ibm 704. since then, many variants of the problem have been considered; depending on two factors: (1) the particular model for registers, and (2) the definition of the term &ldquo;computation of a program&rdquo; e.g. whether values may be computed more than once. we will show that several variants of the register allocation problem for straight line programs are polynomial complete. in particular we consider, (1) the case when each value is computed exactly once, and (2) the case when values may be recomputed as necessary. the completeness of the third problem considered is surprising. a straight line program starts with a set of initial values, and computes intermediate and final values. suppose, for each value, the register that value must be computed into is preassigned. then, (3) the problem of determining if there is a computation of the straight line program, that computes values into the assigned registers, is polynomial complete.
extractor codes. we define new error correcting codes based on extractors. we show that for certain choices of parameters these codes have better list decoding properties than are known for other codes, and are provably better than reed-solomon codes. we further show that codes with strong list decoding properties are equivalent to slice extractors, a variant of extractors. we give an application of extractor codes to extracting many hardcore bits from a one-way function, using few auxiliary random bits. finally, we show that explicit slice extractors for certain other parameters would yield optimal bipartite ramsey graphs.
on the cryptocomplexity of knapsack systems a recent trend in cryptographic systems is to base their encryption/decryption functions on np-complete problems, and in particular on the knapsack problem. to analyze the security of these systems, we need a complexity theory which is less worst-case oriented and which takes into account the extra conditions imposed on the problems to make them cryptographically useful. in this paper we consider the two classes of one-to-one and onto knapsack systems, analyze the complexity of recognizing them and of solving their instances, introduce a new complexity measure (median complexity), and show that this complexity is inversely proportional to the density of the knapsack system. the tradeoff result is based on a fast probabilistic knapsack solving algorithm which is applicable only to one-to-one systems, and it indicates that knapsack-based cryptographic systems in which one can both encrypt and sign messages are relatively insecure. we end the paper with new results about the security of some specific knapsack systems.
bypassing the embedding: algorithms for low dimensional metrics. the doubling dimension of a metric is the smallest k such that any ball of radius 2r can be covered using 2k balls of radius r. this concept for abstract metrics has been proposed as a natural analog to the dimension of a euclidean space. if we could embed metrics with low doubling dimension into low dimensional euclidean spaces, they would inherit several algorithmic and structural properties of the euclidean spaces. unfortunately however, such a restriction on dimension does not suffice to guarantee embeddibility in a normed space.in this paper we explore the option of bypassing the embedding. in particular we show the following for low dimensional metrics: quasi-polynomial time (1+ε)-approximation algorithm for various optimization problems such as tsp, k-median and facility location. (1+ε)-approximate distance labeling scheme with optimal label length. (1+ε)-stretch polylogarithmic storage routing scheme.
geometric complexity the complexity of a number of fundamental problems in computational geometry is examined and a number of new fast algorithms are presented and analyzed. general methods for obtaining results in geometric complexity are given and upper and lower bounds are obtained for problems involving sets of points, lines, and polygons in the plane. an effort is made to recast classical theorems into a useful computational form and analogies are developed between constructibility questions in euclidean geometry and computability questions in modern computational complexity.
on random pm 1 matrices: singularity and determinant. we proved several results concerning the determinant of a random pm 1 matrix. in particular, we show that with high probability, the determinant has absolute value very close to √n!.
a combinatorial characterization of the testable graph properties: it's all about regularity. a common thread in all of the recent results concerning the testing of dense graphs is the use of szemer&eacute;di's regularity lemma. in this paper we show that in some sense this is not a coincidence. our first result is that the property defined by having any given szemer&eacute;di-partition is testable with a constant number of queries. our second and main result is a purely combinatorial characterization of the graph properties that are testable with a constant number of queries. this characterization (roughly) says that a graph property ${\cal p}$ can be tested with a constant number of queries if and only if testing ${\cal p}$ can be reduced to testing the property of satisfying one of finitely many szemer&eacute;di-partitions. this means that in some sense, testing for szemer&eacute;di-partitions is as hard as testing any testable graph property. we thus resolve one of the main open problems in the area of property-testing, which was first raised by goldreich, goldwasser, and ron [j. acm, 45 (1998), pp. 653-750] in the paper that initiated the study of graph property-testing. this characterization also gives an intuitive explanation as to what makes a graph property testable.
optimal probabilistic fingerprint codes. we construct binary codes for fingerprinting digital documents. our codes for n users that are &epsi;-secure against c pirates have length o(c2log(n/&epsi;)). this improves the codes proposed by boneh and shaw &lsqb;1998&rsqb; whose length is approximately the square of this length. the improvement carries over to works using the boneh--shaw code as a primitive, for example, to the dynamic traitor tracing scheme of tassa &lsqb;2005&rsqb;. by proving matching lower bounds we establish that the length of our codes is best within a constant factor for reasonable error probabilities. this lower bound generalizes the bound found independently by peikert et al. &lsqb;2003&rsqb; that applies to a limited class of codes. our results also imply that randomized fingerprint codes over a binary alphabet are as powerful as over an arbitrary alphabet and the equal strength of two distinct models for fingerprinting.
on shortest paths in polyhedral spaces we consider the problem of computing the shortest path between two points in two- or three-dimensional space bounded by polyhedral surfaces. in the 2-d case the problem is easily solved in time o(n2 log n).in the general 3-d case the problem is quite hard to solve, and is not even discrete; we present a doubly-exponential procedure for solving the discrete subproblem of determining the sequence of boundary edges through which the shortest path passes. the main result of this paper involves a favorable special case of the 3-d shortest path problem, namely that of finding the shortest path between two points along the surface of a convex polyhedron. we analyze this problem and solve it in time o(n3 log n).
testing flow graph reducibility many problems in program optimization have been solved by applying a technique called interval analysis to the flow graph of the program. a flow graph which is susceptible to this type of analysis is called reducible. this paper describes an algorithm for testing whether a flow graph is reducible. the algorithm uses depth-first search to reveal the structure of the flow graph and a good method for computing disjoint set unions to determine reducibility from the search information. when the algorithm is implemented on a random access computer, it requires o(e log* e) time to analyze a graph with e edges, where log* x &equil; min{i/logix&le;1}. the time bound compares favorably with the o(e log e) bound of a previously known algorithm.
threshold spectra for random graphs let g = g(n, p) be the random graph with n vertices and edge probability p and &fnof;(n, p, a) be the probability that g has a, where a is a first order property of graphs. the evolution of the random graph is discussed in terms of a spectrum of p = p(n) where &fnof;(n, p, a) changes. a partial characterization of possible spectra is given. when p = n-a, a irrational, and a is any first order statement, it is shown that lim &fnof;(n, p, a) = 0 or 1.
testing graph connectivity an algorithm proposed by dinic for finding maximum flows in networks and by hopcroft and karp for finding maximum bipartite matchings is applied to graph connectivity problems. it is shown that the algorithm requires 0(v1/2e) time to find a maximum set of node-disjoint paths in a graph, and 0(v2/3e) time to find a maximum set of edge disjoint paths. these bounds are tight. thus the node connectivity of a graph may be tested in 0(v5/2e) time, and the edge connectivity of a graph may be tested in 0(v5/3e) time.
languages in general algebras this paper presents the results of recent investigations into the question of when the context-free (cf) languages of an algebra are all recognizable. first, it is shown (theorem 2.1.3) that phrase structure (ps) languages are the same as the cf languages in any (finitely generated) generic algebra. mezei & wright (mw) previously generalized the equality of cf and recognizable languages in generic monadic algebras to arbitrary generic algebras. thus it now follows that the ps, cf and recognizable languages are the same in any generic algebra. this result has the following consequence: let &rgr; be a congruence on a generic algebra a with the property that there exists a ps grammar g on a such that the language generated by g from any element x of a is the &rgr; congruence class of x. then in a/&rgr;, the cf languages (which are precisely the homomorphic images of the cf languages in a) are the same as the recognizable languages (which are precisely the inverse homomorphic images of subsets of finite algebras). any algebra with this latter property is called regular. the following is a more powerful sufficient condition for the regularity of an algebra: suppose a and b are regular algebras and that f1 and f2 are homomorphisms from a to b. let r be a recognizable language in a and define &rgr; b &times; b by &rgr; &equil; {(x,y) &brvbar; ( @@@@ z &egr; r) (f1 (z) &equil; x &lgr; f2 (z) &equil; y }. then if &rgr; is a congruence on b, b/&rgr; is regular. any relation &rgr; (not necessarily a congruence) defined in the above way is called an algebraic transduction. it is shown that the notion of algebraic transduction generalizes the notion of binary transduction as presented for generic monadic algebras by elgot and mezei (em). some proofs have been omitted below, especially when they are standard or straightforward. details can be found in [s].
space efficient dynamic stabbing with fast queries. in dynamic stabbing, we operate on a dynamic set of intervals. a stabbing query asks for an interval containing a given point. this basic problem encodes problems such as method look-up in object oriented programming languages and classification in ip firewalls. for such application, very fast, say constant, query time is extremely important, small space is very important, and fast updates are good but the least important. previous solutions traded space and update time for fast queries. we show here that space needs not be sacrificed. we get the same trade-off between update time and query time but using only the space necessary for locating a query point among the interval end-points. all our bounds are optimal or near-optimal.
tensor norms and the classical communication complexity of nonlocal quantum measurement. nonlocality is at the heart of quantum information processing. in this paper we investigate the minimum amount of classical communication required to simulate a nonlocal quantum measurement. we derive general upper bounds, which in turn translate to systematic classical simulations of quantum communication protocols.as a concrete application, we prove that any quantum communication protocol with shared entanglement for computing a boolean function can be simulated by a classical protocol whose cost does not depend on the amount of the shared entanglement. this implies that if the cost of communication is a constant, quantum and classical protocols, with shared entanglement and shared coins, respectively, compute the same class of functions.furthermore, we describe a new class of efficient quantum communication protocols based on fast quantum algorithms. while some of them have efficient classical simulations by our method, others appear to be good candidates for separating quantum v.s. classical protocols, and quantum protocols with v.s. without shared entanglement.yet another application is in the context of simulating quantum correlations using local hidden variable models augmented with classical communications. we give a constant cost, approximate simulation of quantum correlations when the number of correlated variables is a constant, while the dimension of the entanglement and the number of possible measurements can be arbitrary.our upper bounds are expressed in terms of some tensor norms on the measurement operator. those norms capture the nonlocality of bipartite operators in their own way and may be of independent interest and further applications.
reference machines require non-linear time to maintain disjoint sets this paper describes a machine model intended to be useful in deriving realistic complexity bounds for tasks requiring list processing. as an example of the use of the model, the paper shows that any such machine requires non-linear time in the worst case to compute unions of disjoint sets on-line. all set union algorithms known to the author are instances of the model and are thus subject to the derived bound. one of the known algorithms achieves the bound to within a constant factor.
the complexity of propositional linear temporal logics the complexity of satisfiability and determination of truth in a particular finite structure are considered for different propositional linear temporal logics. it is shown that these problems are np-complete for the logic with f and are pspace-complete for the logics with f, x, with u, with u, s, x operators and for the extended logic with regular operators given by wolper.
context-free error analysis by evaluation of algebraic power series optimal error analysis with respect to a context-free language may be viewed as the evaluation of an algebraic power series. by generalization of the nodal span context-free recognition algorithm, any algebraic power series is computable in o(n3) steps. the closure of algebraic power series under sequential transduction yields a generous class of reasonable error measures for which optimal analysis is o(n3). included is minimizing the number of symbol insertions, deletions and/or replacements needed for correction, a special case which has been studied separately.
sparse polynomial approximation in finite fields. we consider a polynomial analogue of the hidden number problem which has recently been introduced by boneh and venkatesan. namely we consider the sparse polynomial approximation problem of recovering an unknown polynomial f(x) \in \f_p[x] with at most $m$ non-zero terms from approximate values of f(t) at polynomially many points t \in \f_p selected uniformly at random. the case of a polynomial f(x) = &agr; x corresponds to the hidden number problem. the above problem is related to the noisy polynomial interpolation problem and to the sparse polynomial interpolation problem which have recently been considered in the literature. our results are based on a combination of some number theory tools such as bounds of exponential sums and the number of solutions of congruences with the lattice reduction technique.
an algorithm generating the decision table of a deterministic bottom up parser for a subset of context free grammars an algorithm is described, whose input is a context-free grammar g and whose output is, if g fulfils a set of conditions, a decision table for a deterministic bottom up parser yielding the syntactic structure of the terminal sentences that belong to l (g). the complexity of the decision table depends on the stringency of the conditions satisfied by g and corresponds to some subsets of context free grammars which are compared with previously defined subsets such as ll(k), brc (m,k)-i.e bounded right context -, lr(k).
derandomizing homomorphism testing in general groups. the main result of this paper is a near-optimal derandomization of the affine homomorphism test of blum, luby, and rubinfeld [j. comput. system sci., 47 (1993), pp. 549-595]. we show that for any groups g and &ggr;, and any expanding generating set s of g, the natural deramdomized version of the blr test in which we pick an element x randomly from g and y randomly from s and test whether $f(x)\cdot f(y)=f(x\cdot y)$, performs nearly as well (depending of course on the expansion) as the original test. moreover, we show that the underlying homomorphism can be found by the natural local &ldquo;belief propagation decoding.&rdquo; we note that the original blr test uses $2\log_2 |g|$ random bits, whereas the derandomized test uses only $(1+o(1))\log_2 |g|$ random bits. this factor of 2 savings in the randomness complexity translates to a near quadratic savings in the length of the tables in the related locally testable codes (and possibly probabilistically checkable proofs which may use them). our result is a significant generalization of recent results that either refer to the special case of the groups $g=z_p^m$ and $&ggr; =z_p$ or are nonconstructive. we use simple combinatorial arguments and the transitivity of cayley graphs (and this analysis gives optimal results up to constant factors). previous techniques used the fourier transform, a method which seems unextendable to general groups (and furthermore gives suboptimal bounds). finally, we provide a polynomial time (in $|g|$) construction of a (somewhat) small ($|g|^{\epsilon}$) set of expanding generators for every group $g$, which yield efficient testers of randomness $(1+\epsilon) \log |g|$ for $g$. this result follows from a simple derandomization of a known probabilistic construction.
transformations and translations from the point of view of generalized finite automata theory the objective of this work is to expand the study of generalized finite automata theory by introducing generalized finite state mappings (finite state mappings of trees). in the process, we hope to provide an algebraic framework in which to study formalizations of transformations (in the sense that linguists use the term) and translations of natural and artificial languages. the concepts, &ldquo;syntax directed translation&rdquo; [2,18,19, 22, 29] and &ldquo;transformation&rdquo; [11, 25] can be formulated quite neatly within this framework. sections 2 and 3 present basic concepts of generalized finite automata theory and its relationship to context-free languages. we provide some general notation for transformations in section 4 and in the following four sections, two basic kinds of transformations will be introduced and certain fundamental properties proved. in section 9, these definitions will be related to others in the literature and several areas for further investigation will be indicated.
data type specification: parameterization and the power of specification techniques this paper extends our earlier work on abstract data types by providing an algebraic treatment of parametrized data types (e.g., sets-of-(), stacks-of-(), etc.), as well as answering a number of questions on the power and limitations of algebraic specification techniques. in brief: we investigate the &ldquo;hidden function&rdquo; problem (the need to include operations in specifications which we want to be hidden from the user); we prove that conditional specifications are inherently more powerful than equational specifications; we show that parameterized specifications must contain &ldquo;side conditions&rdquo; (e.g., that finite-sets-of-d requires an equality predicate on d), and we compare the power of the algebraic approach taken here with the more categorical approach of lehman and smyth.
on feasible numbers (preliminary version) we study complexity problems associated with generation and manipulation of integers. we show that many such questions may be formulated as problems about random access machines (rams), and recent results about rams with special instructions sets can be used to give estimates about the complexity of the manipulations. finally we settle an open problem about rams (which becomes more interesting in this setting), namely the power of unrestricted vector machines, studied in [5] [6] [2]. we prove that allowing arbitrary shifts (instead of bounded shifts) gives at most a polynomial reduction in the time necessary to recognize languages by vector machines, thus solving the main problem left unanswered by the papers of pratt and stockmeyer [5], [6] and hartmanis and simon [2], [3]. equivalently, it is possible to compare two integers, each obtained by a sequence of at most n operations of shift, sum, and boolean vector operations, within tape polynomial in n.
space-bounded probabilistic turing machine complexity classes are closed under complement (preliminary version) for tape constructible functions s(n)&ge;log n, if a language l is accepted by an s(n) tape bounded probabilistic turing machine, then there is an s(n) tape bounded probabilistic turing machine that accepts &lmarc;, the complement of l.
area-time complexity for vlsi the complexity of the discrete fourier transform (dft) is studied with respect to a new model of computation appropriate to vlsi technology. this model focuses on two key parameters, the amount of silicon area and time required to implement a dft on a single chip. lower bounds on area (a) and time (t) are related to the number of points (n) in the dft: at2&ge; n2/16. this inequality holds for any chip design based on any algorithm, and is nearly tight when t &equil; &thgr;(n1/2) or t &equil; &thgr;(log n). a more general lower bound is also derived: atx &equil; &ohgr;(n1+x/2), for 0&le;&times;&le;2.
polynomial reducibilities and upward diagonalizations an open question of [lls] is whether polynomial time many-one reducibility &le;mp and polynomial time turing reducibility &le;tp differ on np. an affirmative answer to this question would yield p @@@@ np as a corollary, but it is possible that p @@@@ np even if the answer is negative. ladner, lynch, and selman [lls] conjecture that if p @@@@ np then &le;mp and &le;tp differ on np. one method that might prove helpful in settling this conjecture is to exhibit an efficient construction that builds from any nonpolynomial set a a set b such that a &le;tp b but a @@@@mp b. if such a construction were sufficiently efficient, then when applied to a set a in np - p it would yield a set b in np/
sorting on a mesh-connected parallel computer two algorithms for sorting n2 elements on an n&times;n mesh-connected processor array that require 0(n) routing and comparison steps are presented. the best previous algorithms take time 0(n log n). our algorithms are shown to be optimal in time within small constant factors.
on the complexity of ram with various operation sets we prove that polynomial time bounded rams with the instruction set [shift, +, x, boolean ] accept exactly the languages in pspace. this generalizes previous results: [5] showed the same for the instruction set that does not include multiplication, [5] and [7] proved the weaker theorems, that rams (and even prams) with this instruction set could be simulated in exptape. the pram result is a simple corollary to our theorems. we also introduce other powerful string-manipulating instructions for rams, show a nontrivial simulation of turing machines by these rams, and show that in a sense such simulations are optimal.
lower bounds on the size of sweeping automata establishing good lower bounds on the complexity of languages is an important area of current research in the theory of computation. however, despite much effort, fundamental questions such as p &equil;? np and l &equil;? nl remain open. to resolve these questions it may be necessary to develop a deep combinatorial understanding of polynomial time or log space computations, possibly a formidable task. one avenue for approaching these problems is to study weaker models of computation for which the analogous problems may be easier to settle, perhaps yielding insight into the original problems. sakoda and sipser [3] raise the following question about finite automata: is there a polynomial p, such that every n-state 2nfa (two-way nondeterministic finite automaton) has an equivalent p(n)-state 2dfa? they conjecture a negative answer to this. in this paper we take a step toward proving this conjecture by showing that 2nfa are exponentially more succinct than 2dfa of a certain restricted form.
fully-dynamic min-cut. we show that we can maintain up to polylogarithmic edge connectivity for a fully-dynamic graph in $$\ifmmode\expandafter\tilde\else\expandafter\~\fi{o}{\left( {{\sqrt n }} \right)}$$ worst-case time per edge insertion or deletion. within logarithmic factors, this matches the best time bound for 1-edge connectivity. previously, no o(n) bound was known for edge connectivity above 3, and even for 3-edge connectivity, the best update time was o(n2/3), dating back to focs'92. our algorithm maintains a concrete min-cut in terms of a pointer to a tree spanning one side of the cut plus ability to list the cut edges in o(log n) time per edge. by dealing with polylogarithmic edge connectivity, we immediately get a sampling based expected factor (1+o(1)) approximation to general edge connectivity in $$\ifmmode\expandafter\tilde\else\expandafter\~\fi{o}{\left( {{\sqrt n }} \right)}$$ time per edge insertion or deletion. this algorithm also maintains a pointer to one side of a near-minimal cut, but if we want to list the cut edges in o(log n) time per edge, the update time increases to $$\ifmmode\expandafter\tilde\else\expandafter\~\fi{o}{\left( {{\sqrt m }} \right)}$$.
borel sets and circuit complexity it is shown that for every k, polynomial-size, depth-k boolean circuits are more powerful than polynomial-size, depth-(k&minus;1) boolean circuits. connections with a problem about borel sets and other questions are discussed.
integer priority queues with decrease key in constant time and the single source shortest paths problem. we consider fibonacci heap style integer priority queues supporting find-rain, insert, and decrease key operations in constant time. we present a deterministic linear space solution that with n integer keys supports delete in o(log log n) time. if the integers are in the range [0,n), we can also support delete in o(log log n) time.even for the special case of monotone priority queues, where the minimum has to be non-decreasing, the best previous bounds on delete were o((log n)1/(3-ε)) and o((log n)1/(4-ε)). these previous bounds used both randomization and amortization. our new bounds are deterministic, worst-case, with no restriction to monotonicity, and exponentially faster.as a classical application, for a directed graph with n nodes and m edges with non-negative integer weights, we get single source shortest paths in o(m + n log log n) time, or o(m + n log log c) if c is the maximal edge weight. the latter solves an open problem of ahuja, mehlhorn, orlin, and tarjan from 1990.
worst-case update times for fully-dynamic all-pairs shortest paths. we present here the first solution to the fully-dynamic all pairs shortest path problem where every update is faster than a recomputation from scratch in ω(n3log ⁄n) time. this is for a directed graph with arbitrary non-negative edge weights. an update inserts or deletes a vertex with all incident edges. after each such vertex update, we update a complete distance matrix in õ(n2.75) time.
approximate distance oracles. let g=(v,e) be an undirected weighted graph with |v|=n and |e|=m. let k\ge 1 be an integer. we show that g=(v,e) can be preprocessed in o(kmn^{1/k}) expected time, constructing a data structure of size o(kn^{1+1/k}), such that any subsequent distance query can be answered, approximately, in o(k) time. the approximate distance returned is of stretch at most 2k-1, i.e., the quotient obtained by dividing the estimated distance by the actual distance lies between 1 and 2k-1. we show that a 1963 girth conjecture of erd{\h{o}}s, implies that &ohgr(n^{1+1/k}) space is needed in the worst case for any real stretch strictly smaller than 2k+1. the space requirement of our algorithm is, therefore, essentially optimal. the most impressive feature of our data structure is its constant query time, hence the name ``oracle''. previously, data structures that used only o(n^{1+1/k}) space had a query time of &ohgr(n^{1/k}) and a slightly larger, non-optimal, stretch. our algorithms are extremely simple and easy to implement efficiently. they also provide faster constructions of sparse spanners of weighted graphs, and improved tree covers and distance labelings of weighted or unweighted graphs.}
minimax parametric optimization problems and multi-dimensional parametric searching. the parametric minimax problem, which finds the parameter value minimizing the weight of a solution of a combinatorial maximization problem, is a fundamental problem in sensitivity analysis. moreover, several problems in computational geometry can be formulated as parametric minimax problems. the parametric search paradigm gives an efficient sequential algorithm for a convex parametric minimax problem with one parameter if the original non-parametric problem has an efficient parallel algorithm. we consider the parametric minimax problem with d parameters for a constant d, and solve it by using multidimensional version of the parametric search paradigm. as a new feature, we give a feasible region in the parameter space in which the parameter vector must be located.typical results obtained as applications are: (1) efficient solutions for some geometric problems, including theoretically efficient solutions for the minimum diameter bridging problem in d-dimensional space between convex polytopes. (2) parametric polymatroid optimization, for example, o(n log n) time algorithm to compute the parameter vector minimizing k-largest linear parametric elements with d dimensions.
time-space tradeoffs for computing functions, using connectivity properties of their circuits recent research has investigated time-space tradeoffs for register allocation strategies of certain fixed sets of expressions. this paper is concerned with the time-space tradeoff for register allocation strategies of any set of expressions which compute given functions. time-space tradeoffs for pebbling superconcentrators and grates are developed. corollaries which follow include tradeoffs for any straight-line program which computes polynomial multiplication, polynomial convolution, the discrete fourier transform, oblivious merging, and most sets of linear forms.
an optimal solution to a wire-routing problem (preliminary version) a wire-routing problem which arises commonly in the layout of circuits for very large scale integration (vlsi) is discussed. given the coordinates of terminals u1, u2, ..., un of one component and v1, v2, ..., vn of another, the problem is to lay out n wires so that the ith wire connects ui to vi, and adjacent wires are separated at least by some fixed distance. the solution with minimum wire length is characterized, and an optimal algorithm which constructs it is presented.
two familiar transitive closure algorithms which admit no polynomial time, sublinear space implementations any boolean straight-line program which computes the transitive closure of an nxn boolean matrix by successive squaring requires time exceeding any polynomial in n if the space used is o(n). this is the first demonstration of a &ldquo;natural&rdquo; algorithm which (1) has a polynomial time implementation and (2) has a small (e.g., o(log2n)) space implementation, but (3) has no implementation running in polynomial time and small space simultaneously. it is also shown that any implementation of warshall's transitive closure algorithm requires &ohgr;(n) space.
deadlock- and livelock-free packet switching networks a controller for a packet switching network is an algorithm to control the flow of packets through the network. a local controller is a controller executed independently by each node in the network, using only local information available to these nodes. a controller is deadlock- and livelock-free if it guarantees that every packet in the network reaches its destination within a finite amount of time. we present a local controller which is proved to be deadlock- and livelock-free.
deadlock-free packet switching networks deadlock is one of the most serious system failures that can occur in a computer system or a network. deadlock states have been observed in existing computer networks emphasizing the need for carefully designed flow control procedures (controllers) to avoid deadlocks. such a deadlock-free controller is readily found if we allow it global information about the overall network state. generally, this assumption is not realistic, and we must resort to deadlock free local controllers using only packet and node information. we present here several types of such controllers, we study their relationship and give a proof of their optimality with respect to deadlock free controllers using the same set of local parameters.
non-approximability results for optimization problems on bounded degree instances. par>we prove some non-approximability results for restrictions of basic combinatorial optimization problems to instances of bounded &ldquo;degree&r dquo;or bounded &ldquo;width.&rdquo; specifically:we prove that the max 3sat problem on instances where each variable occurs in at most b clauses, is hard to approximate to within a factor $7/8 + o(1/\sqrt{b})$, unless $rp = np$. h\aa stad [18] proved that the problem is approximable to within a factor $7/8 + 1/64b$ in polynomial time, and that is hard to approximate to within a factor $7/8 +1/(\log b)^{&ohgr;(1)}$. our result uses a new randomized reduction from general instances of max 3sat to bounded-occurrences instances. the randomized reduction applies to other max snp problems as well.we observe that the set cover problem on instances where each set has size at most b is hard to approximate to within a factor $\ln b - o(\ln\ln b)$ unless $p=np$. the result follows from an appropriate setting of parameters in feige's reduction [11]. this is essentially tight in light of the existence of $(1+\ln b)$-approximate algorithms [20, 23, 9]we present a new pcp construction, based on applying parallel repetition to the ``inner verifier,'' and we provide a tight analysis for it. using the new construction, and some modifications to known reductions from pcp to hitting set, we prove that hitting set with sets of size b is hard to approximate to within a factor $b^{1/19}$. the problem can be approximated to within a factor b [19], and it is the vertex cover problem for b=2. the relationship between hardness of approximation and set size seems to have not been explored before. we observe that the independent set problem on graphs having degree at most b is hard to approximate to within a factor $b/2^{o(sqrt{\log b})}$, unless p = np. this follows from a comination of results by clementi and trevisan [28] and reingold, vadhan and wigderson [27]. it had been observed that the problem is hard to approximate to within a factor $b^{&ohgr; (1)}$ unless p=np [1]. an algorithm achieving factor $o (b)$ is also known [21, 2, 30, 16}.
on uniform amplification of hardness in np. we continue the study of amplification of average-case complexity within np, and we focus on the uniform case.we prove that if every problem in np admits an efficient uniform algorithm that (averaged over random inputs and over the internal coin tosses of the algorithm) succeeds with probability at least 1 ⁄ 2 +1 (log n )α, then for every problem in np there is an efficient uniform algorithm that succeeds with probability at least 1 - 1 poly(n). above, α > 0 is an absolute constant.previously, trevisan (focs'03) presented a similar redution between success 3⁄4 + 1 (log n) and 1 - 1 (log n)α stronger reductions, due to o'donnell (stoc'02) and healy, vadhan and viola (focs'04) are known in the non-uniform case.
an o(log n log log n) space algorithm for undirected st-connectivity. we present a deterministic o(log n log log n) space algorithm for undirected st-connectivity. it is based on the deterministic erew algorithm of chong and lam [6] and uses the universal exploration sequences for trees constructed by koucký [13]. our result improves the o(log4/3 n) bound of armoni et al.\ [2] and is a big step towards the optimal o(log n). independently of our result and using a different set of techniques, the optimal bound was achieved by reingold [18].
probabilistic analysis of bandwidth minimization algorithms we study the probabilistic performance of heuristic algorithms for the np-complete bandwidth minimization problem. let (equation) be a graph with (equation). define the bandwidth of g by (equation) where &tgr; ranges over all permutations on v. let a be a bandwidth minimization algorithm and let a (g) denote the bandwidth of the layout produced by a on the graph g. we say that a is a level algorithm if for all graphs (equation) the layout &tgr; produced by a on g satisfies (equation) the level algorithms were first introduced by cuthill and mckee [1] and have proved quite successful in practice. however, it is easy to construct examples that cause the level algorithms to perform poorly. consequently worst-case analysis provides no insight to their practical success. in this paper we use probabilistic analysis in order to gain an understanding of these algorithms and to help us design better algorithms. let (equation) be the graph defined by (equation) and let g be a random spanning subgraph of bn&darr; in which the vertices have been randomly re-labelled. we show that if a, is a level algorithm and (equation) then (equation) almost always holds, where &egr; is any positive constant. we also introduce a class of algorithms called the modified level algorithms and show that if a ' is a modified level algorithm and (equation) then (equation) almost always holds. a particular modified level algorithm mla1 is analyzed and we show that when (equation). we also study several other properties of random subgraphs of bn&darr;.
a decision method for the equivalence of some non-real-time deterministic pushdown automata a generalization of the alternate stacking procedure of valiant for deciding the equivalence of some deterministic pushdown automata (dpda) is introduced. to analyze the power of the generalized procedure we define a subclass of dpda's, called the proper dpda's. this class properly contains the non-singular dpda's and the real time strict dpda's, and the corresponding class of languages properly contains the real time strict deterministic languages. the equivalence problem for proper automata is reducible to the problem of deciding whether or not an automaton is proper. the main result of the paper is that the generalized procedure yields an equivalence test for proper dpda's, at least one of which is also a finite-turn machine.
lalr(k) testing is pspace-complete the problem of testing whether or not an arbitrary context-free grammar is lalr(k) for a fixed integer k &ge; 1 (i.e. only the subject grammar is a problem parameter) is shown to be pspace-complete. the result is in contrast with testing the membership in several other easily parsed classes of grammars, such as lr(k), slr(k), lc(k) and ll(k) grammars, for which deterministic polynomial time membership tests are known. the pspace-hardness of the problem is proved using a transformation from the finite state automaton non-universality problem. a nondeterministic algorithm for constructing sets of lr(k) items leads to a polynomially space bounded algorithm for lalr(k) testing.
the inherent ambiguity partial algorithm problem for context free languages it is shown that there is no &ldquo;partial algorithm&rdquo; (effective procedure that may fail to terminate) by which, given a context free grammar, one can always find an unambiguous context free grammar generating the same language if such an unambiguous grammar exists. the argument turns on the degree of unsolvability of the inherent ambiguity problem for context free languages.
three theorems on abstract families of languages (1) if every set in @@@@ is a subset of a* and the empty word belongs to one of them, then 7(@@@@)&equil;&7circ; (@@@@). one consequence is that &7circ;(l) is always principal for l &le; a*. (2) on the other hand, there is a language l &le; a*b* such that &7circ;(l) is not principal. (3) there are subsets j and k of a* such that 7(j) @@@@ 7(k) is not principal.
pseudo-random generators for all hardnesses. we construct the first pseudo-random generators with logarithmic seed length that convert s bits of hardness into s^{\omega(1)} bits of 2-sided pseudo-randomness, for any s. this improves [isw00] and gives a direct proof of the optimal hardness vs. randomness tradeoff in [su01]. a key element in our construction is an augmentation of the standard low-degree extension encoding that exploits the field structure of the underlying space in a new way.
parallel scheduling of programs in a restricted model of computation the purpose of this paper is to present the basis of an automata-theoretic model which treats the concept of &ldquo;schedule&rdquo; for programs which admit a (predefined) degree of parallelism. after a brief review of notational conventions (section 2), the class of representing automata will be introduced as a device for treating a program's control structure. in section 4, since the definition of schedules is non-constructive in the sense that no procedure is given for passing from a representing automaton to a schedule, a particular kind of schedule with such an effective presentation is given and shown to be optimal in the natural sense of optimality defined in section 6. section 5 presents one of the many possible interpretation schemes for our model; this scheme is used to justify some of the claims we have made in this section. finally, we examine some elementary conditions, on a program's control structure which affect the existence of optimal schedules which have finite, explicit presentation.
the recognition of series parallel digraphs we present an algorithm that recognizes the class of general series parallel digraphs and runs in time proportional to the size of its input. to perform this recognition task it is necessary to compute the transitive reduction and transitive closure of any general series parallel digraph. our analysis is based on the relationship between general series parallel digraphs and a class of well known models of electrical networks.
quantum computers that can be simulated classically in polynomial time. a model of quantum computation based on unitary matrix operations was introduced by feynman and deutsch. it has been asked whether the power of this model exceeds that of classical turing machines. we show here that a significant class of these quantum computations can be simulated classically in polynomial time. in particular we show that two-bit operations characterized by 4 \times 4 matrices in which the sixteen entries obey a set of five polynomial relations can be composed according to certain rules to yield a class of circuits that can be simulated classically in polynomial time. this contrasts with the known universality of two-bit operations, and demonstrates that efficient quantum computation of restricted classes is reconcilable with the polynomial time turing hypothesis. in other words it is possible that quantum phenomena can be used in a scalable fashion to make computers but that they do not have superpolynomial speedups compared to turing machines for any problem. the techniques introduced bring the quantum computational model within the realm of algebraic complexity theory. in a manner consistent will one view of quantum physics, the wave function is simulated deterministically, and randomization arises only in the course of making measurements. the results generalize the quantum model in that they do not require the matrices to be unitary. in a different direction these techniques also yield deterministic polynomial time algorithms for the decision and parity problems for certain classes of read-twice boolean formulae. all our results are based on the use of gates that are defined in terms of their graph matching properties.
the decidability of equivalence for deterministic finite-turn pushdown automata a deterministic pushdown automaton (dpda) is described as finite-turn if there is a bound on the number of times the direction of the stack movement can change in the set of all derivations from the starting configuration. the purpose of this paper is to show that there exists a procedure for deciding whether two such finite-turn machines recognize the same language. by virtue of a direct correspondence between a restricted class of one-turn dpda and deterministic two-tape acceptors (valiant (1973)), our proof also provides a solution to the equivalence problem for the latter, alternative to that of bird (1973). since some of the ideas we introduce are not related exclusively to the finite-turn property, or even pushdown machines, it is hoped that our methods can be adapted for constructing equivalence tests for other classes of deterministic automata. our main technique can be regarded as a generalization in several directions of one introduced by rosenkrantz and stearns (1970). they consider a class of pushdown automata for which a natural valuation can be placed on each stack segment, and deduce that for any input word, two equivalent machines in that class must have closely related stack movements. they show how, under such circumstances, for any two machines a single pushdown automaton can be constructed to simulate them both, and used to decide their equivalence. what we shall show is that even for a class with no such stack valuation known, and in which two equivalent machines can have totally dissimilar stack movements, pushdown automata, now nondeterministic, can be found to perform the required simulations.
on non-linear lower bounds in computational complexity the purpose of this paper is to explore the possibility that purely graph-theoretic reasons may account for the superlinear complexity of wide classes of computational problems. the results are therefore of two kinds: reductions to graph theoretic conjectures on the one hand, and graph theoretic results on the other. we show that the graph of any algorithm for any one of a number of arithmetic problems (e.g. polynomial multiplication, discrete fourier transforms, matrix multiplication) must have properties closely related to concentration networks.
universal circuits (preliminary report) we show that there is a combinational (acyclic) boolean circuit of complexity 0(slog s), that can be made to compute any boolean function of complexity s by setting its specially designated set of control inputs to appropriate fixed values. we investigate the construction of such &ldquo;universal circuits&rdquo; further so as to exhibit directions in which refinements of the asymptotic multiplicative constant factor in the complexity bound can be found. in this pursuit useful detailed guidance is provided by available lower bound arguments. in the final section we discuss some other problems in computational complexity that can be related directly to the graph-theoretic ideas behind our constructions. for motivation we start by illustrating some of the applications of universal circuits themselves.
negation can be exponentially powerful among the most remarkable algorithms in algebra are strassen's algorithm for the multiplication of matrices and the fast fourier transform method for the convolution of vectors. for both of these problems the definition suggests an obvious algorithm that uses just the monotone operations + and &times;. schnorr [18] has shown that these algorithms, which use &thgr;(n3) and &thgr;(n2) operations respectively, are essentially optimal among algorithms that use only these monotone operations. by using subtraction as an additional operation and exploiting cancellations of computed terms in a very intricate way strassen showed that a faster algorithm requiring only o(n2.81) operations is possible. the fft method for convolution achieves o(nlog n) complexity in a similar fashion. the question arises as to whether we can expect even greater gains in computational efficiency by such judicious use of cancellations. in this paper we give a positive answer to this, by exhibiting a problem for which an exponential speedup can be attained using {+,&minus;,&times;} rather than just {+,&times;} as operations. the problem in question is the multivariate polynomial associated with perfect matchings in planar graphs. for this a fast algorithm is implicit in the pfaffian technique of fisher and kasteleyn [6,8]. the main result we provide here is the exponential lower bound in the monotone case.
completeness classes in algebra in the theory of recursive functions and computational complexity it has been demonstrated repeatedly that the natural problems tend to cluster together in &ldquo;completeness classes&rdquo;. these are families of problems that (a) are computationally interreducible and (b) are the hardest members of some computationally defined class. the aim of this paper is to demonstrate that for both algebraic and combinatorial problems this phenomenon exists in a form that is purely algebraic in both of the respects (a) and (b). such computational consequences as np-completeness are particular manifestations of something more fundamental. the core of the paper is self-contained, consisting as it does essentially of the two notions of &ldquo;p-definability&rdquo; and the five algebraic relations that are proved as theorems. in the remainder our aim is to elucidate the computational consequences of these basic results. hence in the auxiliary propositions and discussion for convenience we do assume familiarity with algebraic and boolean complexity theory.
exponential lower bounds for restricted monotone circuits in this paper we consider monotone boolean circuits with three alternations, in the order &ldquo;or&rdquo;, &ldquo;and&rdquo;, &ldquo;or.&rdquo; whenever the number of alternations is limited to a fixed constant the formula and circuit size measures are polynomially related to each other. we shall therefore refer to this measure interchangeably as &sgr;&pgr;&sgr;-formula size or &sgr;&pgr;&sgr;-circuit size. we shall prove that any such circuit or formula for detecting the existence of cliques in an n-node graph has at least 2&ohgr;(n&egr;) gates for some &egr; > 0 independent of n.
a theory of the learnable humans appear to be able to learn new concepts without needing to be programmed explicitly in any conventional sense. in this paper we regard learning as the phenomenon of knowledge acquisition in the absence of explicit programming. we give a precise methodology for studying this phenomenon from a computational viewpoint. it consists of choosing an appropriate information gathering mechanism, the learning protocol, and exploring the class of concepts that can be learnt using it in a reasonable (polynomial) number of steps. we find that inherent algorithmic complexity appears to set serious limits to the range of concepts that can be so learnt. the methodology and results suggest concrete principles for designing realistic learning systems.
universal schemes for parallel communication in this paper we isolate a combinatorial problem that, we believe, lies at the heart of this question and provide some encouragingly positive solutions to it. we show that there exists an n-processor realistic computer that can simulate arbitrary idealistic n-processor parallel computations with only a factor of o(log n) loss of runtime efficiency. the main innovation is an o(log n) time randomized routing algorithm. previous approaches were based on sorting or permutation networks, and implied loss factors of order at least (log n)2.
np is as easy as detecting unique solutions for all known np-complete problems the number of solutions in instances having solutions may vary over an exponentially large range. furthermore, most of the well-known ones, such as satisfiability, are parsimoniously interreducible, and these can have any number of solutions between zero and an exponentially large number. it is natural to ask whether the inherent intractability of np-complete problems is caused by this wide variation. in this paper we give a negative answer to this using randomized reductions. we show that the problems of distinguishing between instances of sat having zero or one solution, or finding solutions to instances of sat having unique solutions, are as hard as sat itself. several corollaries about the difficulty of specific problems follow. for example if the parity of the number of solutions of sat can be computed in rp then np = rp. some further problems can be shown to be hard for np or dp via randomized reductions.
provably fast integer factoring with quasi-uniform small quadratic residues finding small quadratic residues modulo n, when n is a large composite number of unknown factorisation is almost certainly a computationally hard problem. this problem arises in a natural way when factoring n by the use of congruences of squares. we construct here a polynomial-time algorithm based on the use of lattices, which finds in a near uniform way quadratic residues mod n that are smaller than o(n2/3). in this way, we derive a class of integer factorisation algorithms, the fastest of which provides the best rigorously established probabilistic complexity bound for integer factorisation algorithms.
the complexity of relational query languages (extended abstract) two complexity measures for query languages are proposed. data complexity is the complexity of evaluating a query in the language as a function of the size of the database, and expression complexity is the complexity of evaluating a query in the language as a function of the size of the expression defining the query. we study the data and expression complexity of logical languages - relational calculus and its extensions by transitive closure, fixpoint and second order existential quantification - and algebraic languages - relational algebra and its extensions by bounded and unbounded looping. the pattern which will be shown is that the expression complexity of the investigated languages is one exponential higher then their data complexity, and for both types of complexity we show completeness in some complexity class.
automata theoretic techniques for modal logics of programs (extended abstract) we present a new technique for obtaining decision procedures for modal logics of programs. the technique centers around a new class of finite automata on infinite trees for which the emptiness problem can be solved in polynomial time. the decision procedures then consist of constructing an automaton af for a given formula f, such that af accepts some tree if and only if f is satisfiable. we illustrate our technique by giving an exponential decision procedure for deterministic propositional dynamic logic and a variant of the &mgr-calculus of kozen.
distribution functions of probabilistic automata. each probabilistic automaton m over an alphabet $\cal a$ defines a probability measure $\prob_m$ on the set of all finite and infinite words over $\cal a$. we can identify a k letter alphabet $\cal a$ with the set {0,1,&hellip;,k-1}, and, hence, we can consider every finite or infinite word w over $\cal a$ as a radix k expansion of a real number x(w) in the interval [0,1]. this makes x(w) a random variable and the distribution function of m is defined as usual: f(x):=\prob_m{w : x(w)}. utilizing the fixed--point semantics (denotational semantics), extended to probabilistic computations, we investigate the distribution functions of probabilistic automata in detail. automata with continuous distribution functions are characterized. by a new, and much more easier method, it is shown that the distribution function f(x) is an analytic function if it is a polynomial. finally, answering a question posed by d. knuth and a. yao, we show that a polynomial distribution function f(x) on [0,1] can be generated by a probabilistic automaton iff all the roots of f'(x)=0 in this interval, if any, are rational numbers. for this, we define two dynamical systems on the set of polynomial distributions and study attracting fixed points of random composition of these two systems.
the two-processor scheduling problem is in r-nc the two-processor scheduling problem is perhaps the most basic problem in scheduling theory, and several efficient algorithms have been discovered for it. however, these algorithms are inherently sequential in nature. we give a fast parallel (r-nc) algorithm for this problem. interestingly enough, our algorithm for this purely combinatoric-looking problem draws on some powerful algebraic methods.
approximation schemes for clustering problems. let k be a fixed integer. we consider the problem of partitioning an input set of points endowed with a distance function into k clusters. we give polynomial time approximation schemes for the following three clustering problems: metric k-clustering, l 22 k-clustering, and l22 k-median. in the k-clustering problem, the objective is to minimize the sum of all intra-cluster distances. in the k-median problem, the goal is to minimize the sum of distances from points in a cluster to the (best choice of) cluster center. in metric instances, the input distance function is a metric. in l 22 instances, the points are in r d and the distance between two points x,y is measured by x&minus;y 22 (notice that (r d, &sdot; 22 is not a metric space). for the first two problems, our results are the first polynomial time approximation schemes. for the third problem, the running time of our algorithms is a vast improvement over previous work.
tensor decomposition and approximation schemes for constraint satisfaction problems. the only general class of max-rcsp problems for which polynomial time approximation schemes (ptas) are known are the dense problems. in this paper, we give ptas's for a much larger class of weighted max-rcsp problems which includes as special cases the dense problems and, for r = 2, all metric instances (where the weights satisfy the triangle inequality) and quasimetric instances; for r > 2, our class includes a generalization of metrics. our algorithms are based on low-rank approximations with two novel features: (1) a method of approximating a tensor by the sum of a small number of "rank-1" tensors, akin to the traditional singular value decomposition (this might be of independent interest) and (2) a simple way of scaling the weights. besides max-rcsp problems, we also give ptas's for problems with a constant number of global constraints such as maximum weighted graph bisection and some generalizations.
random instances of a graph coloring problem are hard np-complete problems should be hard on some (may be extremely rare) instances. but on generic instances many such problems (especially related to random graphs) have been proven easy. we show the intractability of random instances of a graph coloring problem by modifying the np-completeness theorem.
properties that characterize logcfl two properties, called semi-unboundedness, and polynomial proof-size, are identified as key properties shared by the definitions of logcfl on several models of computations. the semi-unboundedness property leads to the definition of new models of computation based on unbounded fan-in circuits. these are circuits obtained from unbounded fan-in circuits by restricting the fan-in of gates of one type. a new characterization of logcfl is obtained on such a model in which the fan-in of the and gates are bounded by a constant. this property also suggests new characterizations of logcfl on the following models: alternating turing machines [cks81], nondeterministic auxiliary pushdown automata [co71], and bounded fan-in boolean circuits [co85].
randomized speed-ups in parallel computation the following problem is considered: given a linked list of length n, compute the distance of each element of the linked list from the end of the list. the problem has two standard deterministic algorithms: a linear time serial algorithm, and an o((nlog n)/p + log n) time parallel algorithm using p processors. a known conjecture states that it is impossible to design an o(log n) time deterministic parallel algorithm that uses only n/log n processors. we present three randomized parallel algorithms for the problem. one of these algorithms runs almost-surely in time of o(n/p + log nlog*n) using p processors on an exclusive-read exclusive-write parallel ram.
almost optimal permutation routing on hypercubes. this paper deals with permutation routing on hypercube networks in the store-and-forward model. we introduce the first (on-line and off-line) algorithms routing any permutation on the d-dimensional hypercube in d+o(d) steps. the best previously known results were 2d+o(d) (oblivious on-line) and 2d-3 (off-line). in particular, we presenta randomized, oblivious on-line algorithm with routing time d + o(d/log d),a matching lower bound of d + &ohgr;(d/log d) for (randomized) oblivious on-line routing, anda deterministic, off-line algorithm with routing time d+o(\sqrt{d\log d}).previous algorithms lose a factor of two mainly because packets are first sent to intermediate destinations in order to resolve congestion. as a consequence, the maximum path length becomes 2d - o(d). our algorithms use intermediate destinations as well, but we introduce a simple, elegant trick ensuring that the routing paths are not stretched too much. in fact, we achieve small congestion using paths of length at most d.the main focus of our work, however, lies on the scheduling aspect. on one hand, we investigate well-known and practical scheduling policies for on-line routing, namely farthest-to-go and nearest-to-origin. on the other hand, we present a new off-line scheduling scheme that is based on frugal colorings of multigraphs. this scheme might be of interest for other sparse scheduling problems, too.
some structural properties of polynomial reducibilities and sets in np in this abstract and discussion of forthcoming papers, we will be concerned with variations on a common theme: without assuming a solution to p vs np, what can one say of a general nature that relates structural properties of general classes of sets in np to reducibilities among these sets? by &ldquo;structural&rdquo; we mean, in ways that will become clearer as we proceed, properties which arise from general definitions rather than properties which may arise from a perhaps more &ldquo;natural&rdquo; computational point of view. although quite a bit is known about such questions relative to oracles or relative to the assumption that p @@@@ np, in so far as possible we wish to obtain absolute results; that is results which are about sets in np (not relativized) and which can be obtained without assuming a solution to p vs np. in a final section summarizing our results we will make some general comments about the historical antecedents and possible future significance of this approach.
speed-ups by changing the order in which sets are enumerated (preliminary version) in a suitably general context, the following analogue of the blum speed-up theorem is proven: there are some infinite sets which are so difficult to enumerate that, given any order for enumerating the set, there is some other order, and some one method of enumerating the set in this second order which is much faster than any method of enumerating the set in the first ordering. it may be possible to interpret this result as a statement about the relative merits of &ldquo;hardware&rdquo; vs. &ldquo;programming&rdquo; speed-ups. the proof itself is one of the first nontrivial applications of priority methods to questions of computational complexity. as such, it perhaps represents an advance in bringing the results and techniques of contemporary &ldquo;pure&rdquo; recursion theory to bear on questions of computational complexity. in this paper we shall prove, in a suitably general context, the following analogue of the blum speed-up theorem, [b1]: there are some infinite sets which are so difficult to enumerate that, given any order for enumerating the set, there is some other order, and some one method of enumerating the set in this second order which is much faster than any method of enumerating the set in the first ordering.
an algebraic theory of recursive definitions and recursive languages this is the introductory paper in a series devoted to a general algebraic theory of &ldquo;recursive definitions&rdquo; and &ldquo;recursive languages&rdquo;. in this paper we present the fundamental concepts and theorems concerning the basic structure (basic syntax), the semantics and the combination and manipulation of &ldquo;recursive definitions&rdquo; and the closure properties of &ldquo;recursive languages&rdquo;. the development is carried out within the framework of category theory and lattice theory. to illustrate the generality of the approach and our results we show how they apply directly to the specific examples of &ldquo;recursive languages&rdquo; of (generalized) context-free grammars, turing machines, and flowcharts.
formal models for some features of programming languages in this paper we attempt to tighten the connections between classical mathematics, automata theory, and the theory of programming languages. formal linguistic objects corresponding to programs are defined via sets of functional equations; two interpretations of such an object are given, one in classical mathematics, and one in terms of an abstract machine that executes the program. within this framework we examine flow charts, recursion, parameterization, and declaration.
from algebras to programming languages this paper gives an informal presentation of constructions which, when combined, enable one to construct high level programming languages from algebras or, equivalently, from collections of primitive operations on some set (e.g. from the arithmetic, vector and logical operations on the set of integers, integer vectors, and truth values). using this approach one can construct languages with block structure, procedures, procedure calls by both name and value, plus essentially simpler concepts such as assignment statements and conditional transfers. the constructions are algebraic in the sense that they are constructions on algebras which yield new algebras. however, for the sake of comprehensibility, we present them in this paper in a more informal manner as constructions on &ldquo;black boxes&rdquo;. this paper is a continuation of work presented earlier in [3] and [4] and owes much to the joint work to be reported in [5].
new upper and lower bounds for randomized and quantum local search. local search problem, which finds a local minimum of a black-box function on a given graph, is of both practical and theoretical importance to combinatorial optimization, complexity theory and many other areas in theoretical computer science. in this paper, we study the problem in the randomized and quantum query models and give new lower and upper bound techniques in both models.the lower bound technique works for any graph that contains a product graph as a subgraph. applying it to the boolean hypercube (0, 1)n and the constant dimensional grids [n]d, two particular product graphs that recently drew much attention, we get the following tight results: rls((0, 1)n) = θ(2n/2n1/2), qls((0, 1)n) = θ(2n/3n1/6); rls([n]d) = θ(nd/2), ∀ d ≥ 4, qls([n]d) = θ(nd/3), ∀ d ≥ 6. here rls(g) and qls(g) are the randomized and quantum query complexities of local search on g, respectively. these improve the previous results by aaronson [2], ambainis (unpublished) and santha and szegedy [20].our new algorithms work well when the underlying graph expands slowly. as an application to [n]2, a new quantum algorithm using o(☂n(log log n)1.5) queries is given. this improves the previous best known upper bound of o(n2/3) (aaronson, [2]), and implies that local search on grids exhibits different properties in low dimensions.
on the complexity of the extended string-to-string correction problem the extended string-to-string correction problem [esscp] is defined as the problem of determining, for given strings a and b over alphabet v, a minimum-cost sequence s of edit operations such that s(a) &equil; b. the sequence s may make use of the operations: change, insert, delete and swaps, each of constant cost wc, wi, wd, and ws respectively. swap permits any pair of adjacent characters to be interchanged. the principal results of this paper are: (1) a brief presentation of an algorithm (the cellar algorithm) which solves esscp in time &oslash;(&brvbar;a&brvbar;* &brvbar;b&brvbar;* &brvbar;v&brvbar;s*s), where s &equil; min(4wc, wi+wd)/ws + 1; (2) presentation of polynomial time algorithms for the cases (a) ws &equil; 0, (b) ws > 0, wc&equil; wi&equil; wd&equil; @@@@; (3) proof that esscp, with wi < wc &equil; wd &equil; @@@@, 0 < ws < @@@@, suitably encoded, is np-complete. (the remaining case, ws&equil; @@@@, reduces esscp to the string-to-string correction problem of [1], where an &oslash;( &brvbar;a&brvbar;* &brvbar;b&brvbar;) algorithm is given.) thus, &ldquo;almost all&rdquo; esscp's can be solved in deterministic polynomial time, but the general problem is np-complete.
linear degree extractors and the inapproximability of max clique and chromatic number. a randomness extractor is an algorithm which extracts randomness from a low-quality random source, using some additional truly random bits. we construct new extractors which require only log n + o(1) additional random bits for sources with constant entropy rate. we further construct dispersers, which are similar to one-sided extractors, which use an arbitrarily small constant times log n additional random bits for sources with constant entropy rate. our extractors and dispersers output 1-α fraction of the randomness, for any α>0.we use our dispersers to derandomize results of hastad [23] and feige-kilian [19] and show that for all ε>0, approximating max clique and chromatic number to within n1-ε are np-hard. we also derandomize the results of khot [29] and show that for some γ > 0, no quasi-polynomial time algorithm approximates max clique or chromatic number to within n/2(log n)1-γ, unless np = p.our constructions rely on recent results in additive number theory and extractors by bourgain-katz-tao [11], barak-impagliazzo-wigderson [5], barak-kindler-shaltiel-sudakov-wigderson [6], and raz [36]. we also simplify and slightly strengthen key theorems in the second and third of these papers, and strengthen a related theorem by bourgain [10].
characterization of flowchartable recursions (short version) in this paper we give new characterizations for the flowchartability of recursive functionals. the general question of flowchartability is recursively undecidable. we present here an effective map from recursions to representatives for which the question is decidable. the decision provides a good approximation to a characterization for general flowchartability in the following senses: (1) if a representative is flowchartable then the recursions it represents are, and (2) there is a straightforward method of flowcharting, depending only on recursion structure, such that a recursion is flowchartable by this method if and only if its representative is flowchartable. the main results of the paper are (1) that such a representative is flowchartable if, and only if, it is simple or linear, and (2) that, when the context is restricted so that only invertible operations are considered, such a representative is flowchartable if, and only if, it is nested. the terms &ldquo;simple&rdquo; and &ldquo;linear&rdquo; have been defined in previous papers in the area, although they are extended slightly in this one. the term nested is introduced here. simple, linear, and nested recursions are very easy to identify by inspection.
an unusual application of program-proving an inductive proof in mathematics may often be expressed as an algorithm and a proof that the algorithm is correct. especially when the proof proceeds by cases, a recursive pattern-matching language, such as hewitt's matchless, is a felicitous language for writing the algorithm. we use this idea to prove a new mathematical result, which itself is of interest in computer science. we define objects called k-models. our main theorem is a necessary and sufficient condition for a k-model to be the restriction of a k+1-model.
a new incompleteness result for hoare's system a structure a is presented for which hoare's formal system for partial correctness is incomplete, even if the entire first-order theory of a is included among the axioms. it follows that the language of first-order logic is insufficient to express all loop invariants. the implications of this result for program-proving are discussed.
estimating true evolutionary distances between genomes. evolution operates on whole genomes by operations that change the order and strandedness of genes within the genomes. this type of data presents new opportunities for discoveries about deep evolutionary rearrangement events, provided that sufficiently accurate methods can be developed to reconstruct evolutionary trees in these models [3, 6, 7, 15, 17]. a necessary component of any such method is the ability to accurately estimate true evolutionary distances between two genomes, which is the number of rearrangement events that took place in the evolutionary history between them. we present a new technique called iebp, for estimating the true evolutionary distance between two genomes, whether signed or unsigned, circular or linear, and for any relative probabilities of rearrangement event classes. the method is highly accurate, as our simulation study shows. this simulation study also shows that the distance estimation technique improves the accuracy of the phylogenetic trees reconstructed by the popular distance-based method, neighbor joining [1, 20].
predecessor machines and regressing functions a predecessor machine is a random-access machine with a predecessor operation (i.e., an instruction which subtracts 1 from the contents of a memory cell), but with no operation which can increase the contents of a cell. a regressing function is a total function which never yields an output larger than the maximum of its inputs and a constant. unlike the situation for random-access machines with a successor operation, it does not matter whether or not predecessor machines with loop control also have conditional transfer instructions. furthermore, the class of functions computable by predecessor loop machines consists of exactly those regressing functions which are computable by a deterministic linear-bounded automaton. some generalized predecessor machines are also considered.
lower bounds for 2-dimensional range counting. proving lower bounds for range queries has been an active topic of research since the late 70s, but so far nearly all results have been limited to the (rather restrictive) semigroup model. we consider one of the most basic range problem, orthogonal range counting in two dimensions, and show almost optimal bounds in the group model and the (holy grail) cell-probe model. specifically, we show the following bounds, which were known in the semigroup model, but are major improvements in the more general models:* in the group and cell-probe models, a static data structure of size n lgo(1) n requires omega(lg n lglg n) time per query. this is an exponential improvement over previous bounds, and matches known upper bounds.* in the group model, a dynamic data structure takes time omega((lg n lglg n)2) per operation. this is close to the o(lg2 n) upper bound, where as the previous lower bound was omega(lg n). proving such (static and dynamic) bounds in the group model has been regarded as an important challenge at least since [fredman, jacm 1982] and [chazelle, focs 1986].
quantum algorithms for solvable groups. in this paper we give a polynomial-time quantum algorithm for computing orders of solvable groups. several other problems, such as testing membership in solvable groups, testing equality of subgroups in a given solvable group, and testing normality of a subgroup in a given solvable group, reduce to computing orders of solvable groups and therefore admit polynomial-time quantum algorithms as well. our algorithm works in the setting of black-box groups, wherein none of these problems have polynomial-time classical algorithms. as an important byproduct, our algorithm is able to produce a pure quantum state that is uniform over the elements in any chosen subgroup of a solvable group, which yields a natural way to apply existing quantum algorithms to factor groups of solvable groups.
some new results on node-capacitated packing of a-paths. in this paper we propose a (semi-strongly) polynomial time algorithm to find a maximum packing subject to node-capacities, and thus we obtain a generalization of keijsper, pendavingh and stougie algorithm concerning edge-capacities. our method is based on gerards' strongly polynomial time algorithm to find a maximum b-matching in a graph, which is based on a so-called proximity lemma. our node-capacitated a-path packing algorithm first constructs a maximum fractional packing by using an ellipsoid method subroutine, then takes its integer part to obtain a near-optimal integral packing, and finally we construct a maximum integer packing by a short sequence of augmentations. this short sequence of augmentations is constructed by applying the version of gerards' proximity lemma, specially formulated for the node-capacitated a-path packing problem. in addition, we also state some related results on the fractional packing problem. we prove the primal- and dual integrality of the corresponding linear program. we mention that the fractional packing problem reduces to the matroid fractional matching problem.
zero-knowledge against quantum attacks. this paper proves that several interactive proof systems are zero-knowledge against general quantum attacks. this includes the well-known goldreich-micali-wigderson classical zero-knowledge protocols for graph isomorphism and graph 3-coloring (assuming the existence of quantum computationally concealing commitment schemes in the second case). also included is a quantum interactive proof system for a complete problem for the complexity class of problems having honest verifier quantum statistical zero-knowledge proofs, which therefore establishes that honest verifier and general quantum statistical zero-knowledge are equal: $\mathrm{qszk}= \mathrm{qszk}_{\mathrm{hv}}$. previously no nontrivial interactive proof systems were known to be zero-knowledge against quantum attacks, except in restricted settings such as the honest verifier and common reference string models. this paper therefore establishes for the first time that true zero-knowledge is indeed possible in the presence of quantum information and computation.
smooth sensitivity and sampling in private data analysis. we introduce a new, generic framework for private data analysis.the goal of private data analysis is to release aggregate information about a data set while protecting the privacy of the individuals whose information the data set contains.our framework allows one to release functions f of the data withinstance-based additive noise. that is, the noise magnitude is determined not only by the function we want to release, but also bythe database itself. one of the challenges is to ensure that the noise magnitude does not leak information about the database. to address that, we calibrate the noise magnitude to the smoothsensitivity of f on the database x --- a measure of variabilityof f in the neighborhood of the instance x. the new frameworkgreatly expands the applicability of output perturbation, a technique for protecting individuals' privacy by adding a smallamount of random noise to the released statistics. to our knowledge, this is the first formal analysis of the effect of instance-basednoise in the context of data privacy. our framework raises many interesting algorithmic questions. namely,to apply the framework one must compute or approximate the smoothsensitivity of f on x. we show how to do this efficiently for several different functions, including the median and the cost ofthe minimum spanning tree. we also give a generic procedure based on sampling that allows one to release f(x) accurately on manydatabases x. this procedure is applicable even when no efficient algorithm for approximating smooth sensitivity of f is known orwhen f is given as a black box. we illustrate the procedure by applying it to k-sed (k-means) clustering and learning mixtures of gaussians.
a polynomial combinatorial algorithm for generalized minimum cost flow. we propose the first combinatorial solution to the generalized minimum cost flow problem (flow with losses and gains). despite a rich history dating back to kantorovich and dantzig, until now, the only known way to solve the problem in polynomial-time was via general-purpose linear programming techniques. polynomial combinatorial algorithms were previously known only for the version of our problem without costs. we design the first such algorithms for the version with costs. our algorithms also find provably good solutions faster than optimal ones, providing the first strongly polynomial approximation schemes for the problem.our techniques extend to optimize linear programs with two variables per inequality. polynomial combinatorial algorithms were previously developed for testing the feasibility of such linear programs. we propose the first such methods for the optimization version.
survivable network design with degree or order constraints. we present algorithmic and hardness results for network design problems with degree or order constraints. the first problem we consider is the survivable network design problem with degree constraints on vertices. the objective is to find a minimum cost subgraph which satisfies connectivity requirements between vertices and also degree upper bounds $b_v$ on the vertices. this includes the well-studied minimum bounded degree spanning tree problem as a special case. our main result is a $(2,2b_v+3)$-approximation algorithm for the edge-connectivity survivable network design problem with degree constraints, where the cost of the returned solution is at most twice the cost of an optimum solution (satisfying the degree bounds) and the degree of each vertex $v$ is at most $2b_v+3$. this implies the first constant factor (bicriteria) approximation algorithms for many degree constrained network design problems, including the minimum bounded degree steiner forest problem. our results also extend to directed graphs and provide the first constant factor (bicriteria) approximation algorithms for the minimum bounded degree arborescence problem and the minimum bounded degree strongly $k$-edge-connected subgraph problem. in contrast, we show that the vertex-connectivity survivable network design problem with degree constraints is hard to approximate, even when the cost of every edge is zero. a striking aspect of our algorithmic result is its simplicity. it is based on the iterative relaxation method, which is an extension of jain's iterative rounding method. this provides an elegant and unifying algorithmic framework for a broad range of network design problems. we also study the problem of finding a minimum cost $\lambda$-edge-connected subgraph with at least $k$ vertices, which we call the $(k,\lambda)$-subgraph problem. this generalizes some well-studied classical problems such as the $k$-mst and the minimum cost $\lambda$-edge-connected subgraph problems. we give a polylogarithmic approximation for the $(k,2)$-subgraph problem. however, by relating it to the densest $k$-subgraph problem, we provide evidence that the $(k,\lambda)$-subgraph problem might be hard to approximate for arbitrary $\lambda$.
lattices that admit logarithmic worst-case to average-case connection factors. we exhibit an average-case problem that is as hard as finding γ(n)-approximate shortest nonzero vectors in certain n-dimensional lattices in the worst case, for γ(n) = o(√log n). the previously best known factor for any non-trivial class of lattices was γ(n) = õ(n). our results apply to families of lattices having special algebraic structure. specifically, we consider lattices that correspond to ideals in the ring of integers of an algebraic number field. the worst-case problem we rely on is to find approximate shortest vectors in these lattices, under an appropriate form of preprocessing of the number field. for the connection factors γ(n) we achieve, the corresponding decision problems on ideal lattices are not known to be np-hard; in fact, they are in p. however, the search approximation problems still appear to be very hard. indeed, ideal lattices are well-studied objects in computational number theory, and the best known algorithms for them seem to perform no better than the best known algorithms for general lattices. to obtain the best possible connection factor, we instantiate our constructions with infinite families of number fields having constant root discriminant. such families are known to exist and are computable, though no efficient construction is yet known. our work motivates the search for such constructions. even constructions of number fields having root discriminant up to o(n2/3-ε) would yield connection factors better than õ(n). as an additional contribution, we give reductions between various worst-case problems on ideal lattices, showing for example that the shortest vector problem is no harder than the closest vector problem. these results are analogous to previously-known reductions for general lattices.
neighborhood search algorithms for finding optimal traveling salesman tours must be inefficient search in this paper, we explore the use of neighborhood search techniques for finding optimal solutions to the symmetric traveling salesman problem. these techniques have been dramatically successful in obtaining near-optimal solutions to this problem for a reasonable expenditure of effort (1,2,3,4,5,6,9,10,12). extensions of these techniques can be used to obtain the globally optimum solution, but the effort involved is at least an exponential function of the number of cities, n. indeed, as this paper demonstrates, all local search algorithms that are capable of finding the optimal solution to an arbitrary n-city problem must grow at least as fast as equation !. thus for large problems, these algorithms are computationally inefficient. in following section we show that any exact neighborhood search algorithm for the traveling salesman problem must inspect a prohibitively large number of feasible solutions. we begin with a brief discussion of the traveling salesman problem (tsp) and neighborhood search techniques in section ii. in section iii we develop a necessary condition for neighborhood search to converge to an optimal solution. we use this result in sections iv and v to obtain a lower bound on the effectiveness of neighborhood search as applied to the tsp.
computing crossing number in linear time. we show that for every fixed k, there is a linear time algorithm that decides whether or not a given graph has crossing number at most k, and if this is the case, computes a drawing of the graph in the plane with at most k crossings. this answers the question posed by grohe (stoc'01 and jcss 2004). our algorithm can be viewed as a generalization of the seminal result by hopcroft and tarjan lin1, which determines if a given graph is planar in linear time. our algorithm can also be compared to the algorithms by mohar (stoc'96 and siam j. discrete math 2001), for testing the embeddability of an input graph in a fixed surface. for each surface s, mohar describes an algorithm which yields either an embedding of g in s or a minor of g which is not embeddable in s and is minimal with this property. the same approach allows us to obtain linear time algorithms for the same question for a variety of other crossing numbers. we can also determine in linear time if an input graph can be made planar by the deletion of k edges (for fixed k).
counting independent sets up to the tree threshold. consider the problem of approximately counting weighted independent sets of a graph g with activity λ, i.e., where the weight of an independent set i is λ|i|. we present a novel analysis yielding a deterministic approximation scheme which runs in polynomial time for any graph of maximum degree δ and λ< λc=(δ-1)δ-1/(δ-2)δ. this improves on the previously known general bound of λ ≤ (2 ‾ δ-2). the new regime includes the interesting case of λ=1 (uniform weights) and δ ≤ 5. the previous bound required δ ≤ 4 for uniform approximate counting and there is evidence that for δ ≥ 6 the problem is hard. note that λc is the critical activity for uniqueness of the gibbs measure on the regular tree of degree δ, i.e., for λ ≤ λc the probability that the root is in the independent set is asymptotically independent of the configuration on the leaves far below. indeed, our analysis is focused on establishing decay of correlations with distance in the above weighted distribution. we show that on any graph of maximum degree δ correlations decay with distance at least as fast as they do on the regular tree of the same degree. this resolves an open conjecture in statistical physics. our comparison of a general graph with the tree uses an algorithmic argument yielding the approximation scheme mentioned above. also, by existing arguments, establishing decay of correlations for all graphs and λ<λc gives that the glauber dynamics is rapidly mixing in this regime. however, the implication from decay of correlations to rapid mixing of the dynamics is only known to hold for graphs of subexponential growth, and hence, our result regarding the glauber dynamics is limited to this class of graphs.
the condition number of a randomly perturbed matrix. let m be an arbitrary n by n matrix. we study the conditionnumber a random perturbation m+nn of m, where nn is arandom matrix. it is shown that, under very general conditions on m and mn, the condition number of m+nn is polynomial in nwith very high probability. the main novelty here is that we allow nn to have discrete distribution.
proportional response dynamics leads to market equilibrium. one of the main reasons of the recent success of peer to peer (p2p)file sharing systems such as bittorrent is their built-in tit-for-tat mechanism. in this paper, we model the bandwidth allocation in a p2p system as an exchange economy and study a tit-for-tat dynamics, namely the proportional response dynamics, in this economy. in aproportional response dynamics each player distributes its good to its neighbors proportional to the utility it received from them in thelast period. we show that this dynamics not only converges but converges to a market equilibrium, a standard economic characterization of efficient exchanges in a competitive market. in addition, for some classes of utility functions we consider, it converges much faster than the classical tat process and any existingalgorithms for computing market equilibria. as a part of our proof we study the double normalization of a matrix, an operation that linearly scales the rows of a matrix sothat each row sums to a prescribed positive number, followed by a similar scaling of the columns. we show that the iterative double normalization process of any non-negative matrix always converges. this complements the previous studies in matrix scaling that has focused on the convergence condition of the process when the row and column normalizations are considered as separate steps.
depth through breadth, or why should we attend talks in other areas? given that the two other invited lectures in this conference are on such remote areas as "quantum computation" and "algorithmic game theory," and given the diversity of other topics represented in the program, it makes sense to ask if the stoc/focs community is still one.indeed, the program chair has asked me to respond to this question.in the talk i'll try to illustrate, with a few (of many) examples, how the presence of such diversity in our community and conferences was actually responsible for important progress in specific areas of research, why i find these a natural and expected phenomena, and why i expect this trend to continue.
simple deterministic approximation algorithms for counting matchings. we construct a deterministic fully polynomial time approximationscheme (fptas) for computing the total number of matchings in abounded degree graph. additionally, for an arbitrary graph, weconstruct a deterministic algorithm for computing approximately thenumber of matchings within running time exp(o(√n log2n)),where n is the number of vertices. our approach is based on the correlation decay technique originating in statistical physics. previously thisapproach was successfully used for approximately counting thenumber of independent sets and colorings in some classes of graphs [1, 24, 6].thus we add another problem to the small, but growing, class of p-complete problems for whichthere is now a deterministic fptas.
a new approximate graph coloring algorithm let a be a graph coloring algorithm. denote by -&-agrave; (g) the ratio between the maximum number of colors a will use to color the graph g, and the chromatic number of g,x(g). for most existing polynomial coloring algorithms, -&-agrave;(g) can be as bad as o(n), where n is the number of vertices in g. the best currently known algorithm guarantees -&-agrave; (g)-&-equil;o(n/logn). in this paper we present a simple and efficient coloring algorithm which guarantees -&-agrave;(g)-&-le;x(g)n (equation), a considerable improvem-&-edot;nt over the current bounds.
uncertainty principles, extractors, and explicit embeddings of l2 into l1. we give an explicit construction of a constant distortion embedding f of l2n into l1m, with m=n1+o(1).as a bonus, our embedding also has good computational properties: for any input x, fx can be computed in n1+o(1) time.the previously known mappings required ω(n2) evaluation time.
balanced allocations: the weighted case. we investigate balls-and-bins processes where m weighted balls areplaced into n bins using the "power of two choices" paradigm,whereby a ball is inserted into the less loaded of two randomly chosen bins. the case where each of the m balls has unit weight had been studied extensively. in a seminal paper azar et.al. showed that when m=n the most loaded bin has θ(log log n) balls with high probability. surprisingly, thegap in load between the heaviest bin and the average bin does not increase with m and was shown by berenbrink etal tobe θ(log log n) with high probability for arbitrarily large m. we generalize this result to the weighted case where balls have weights drawn from an arbitrary weight distribution. we show that aslong as the weight distribution has finite second moment andsatisfies a mild technical condition, the gap between the weight of the heaviest bin and the weight of the average bin is independent ofthe number balls thrown. this is especially striking whenconsidering heavy tailed distributions such as power-law andlog-normal distributions. in these cases, as more balls are thrown,heavier and heavier weights are encountered. nevertheless with high probability, the imbalance in the load distribution does notincrease. furthermore, if the fourth moment of the weight distribution is finite, the expected value of the gap is shown to beindependent of the number of balls.
local embeddings of metric spaces. in many application areas, complex data sets are often representedby some metric space and metric embedding is used to provide a more structured representation of the data. in many of these applications much greater emphasis is put on the preserving the local structure of the original space than on maintaining its complete structure. this is also the case in some networking applications where "small world" phenomena in communication patterns has been observed. practical study of embedding has indeed involved with finding embeddings with this property. in this paper we initiate thestudy of local embeddings of metric spaces and provide embeddings with distortion depending solely on the local structureof the space.
white pebbles help a family of directed acyclic graphs of vertex indegree 2 is constructed for which there are strategies of the black-white pebble game that use asymptotically fewer pebbles than the best strategies of the black pebble game. this shows that there are straight-line programs that can be evaluated nondeterministically with asymptotically less space than is required by any deterministic evaluation.
maintaining dense sequential files in a dynamic environment (extended abstract) in this article, we study an alternate approach that shifts the records among adjacent pages rather than using overflow pointers when space is needed for inserting a record in a sequential file. we show how to use this method to achieve a worst-case record insertion-deletion complexity of o[(log2n)/(d-d)] page-accesses, in (d-d)-dense files.
more algorithms for all-pairs shortest paths in weighted graphs. in the first part of the paper, we reexamine the all-pairsshortest paths (apsp) problem and present a newalgorithm with running time approaching o(n3/log2n), which improves all known algorithms for general real-weighted dense graphs andis perhaps close to the best result possible without using fast matrix multiplication, modulo a few log log n factors. in the second part of the paper, we use fast matrix multiplication to obtain truly subcubic apsp algorithms for a large class of "geometrically weighted" graphs, where the weight of an edge is a function of the coordinates of its vertices. for example, for graphs embedded in euclidean space of a constant dimension d, we obtain a time bound near o(n3-(3-ω)/(2d+4)), where ω < 2.376 ; in two dimensions, this is o(n2.922). our framework greatly extends the previously considered case of small-integer-weighted graphs, and incidentally also yields the first truly subcubic result (near o(n3-(3-ω)/4)=o(n2.844) time) forapsp in real-vertex-weighted graphs, as well as an improved result (near o(n(3+ω)/2)=o(n2.688) time) for the all-pairs lightest shortest path problem for small-integer-weighted graphs.
exponential separations for one-way quantum communication complexity, with applications to cryptography. we give an exponential separation between one-way quantum and classical communication protocols for a partial boolean function (a variant of the boolean hidden matching problem of bar-yossef et al.). previously, such an exponential separation was known only for a relational problem. the communication problem corresponds to a strong extractor that fails against a small amount of quantum information about its random source. our proof uses the fourier coefficients inequality of kahn, kalai, and linial. we also give a number of applications of this separation. in particular, we show that there are privacy amplification schemes that are secure against classical adversaries but not against quantum adversaries; and we give the first example of a key-expansion scheme in the model of bounded-storage cryptography that is secure against classical memory-bounded adversaries but not against quantum ones.
combinatorial complexity in o-minimal geometry. in this paper we prove tight bounds on the combinatorial and topological complexity of sets dened in terms of n denable sets belonging to some fixed denable family of sets in an o-minimal structure. this generalizes the combinatorial parts of similar bounds known in the case of semi-algebraic and semi-pfaffian sets, and as a result vastly increases the applicability of results on combinatorial and topological complexity of arrangements studied in discrete and computational geometry. as a sample application, we extend a ramsey-type theorem due to alon et al. [3], originally proved for semi-algebraic sets of fixed description complexity to this more general setting.
domolki's algorithm applied to generalized overlap resolvable grammars recently hext and roberts have attempted to refine domolki's parsing algorithm to include limited context checking. this paper links their effort to lynch's overlap resolvable grammars, which are here extended to include &egr;-rules. both lynch's and hext and roberts' versions of the algorithm are modified, the former with a considerable time improvement and the latter using the full power of overlap resolvability. results are also proposed on removing 1-productions from overlap resolvable grammars for such parsers, answering a question of lynch. both new formulations of the algorithm can be efficiently implemented: the former being particularly suited for fixed word length machines, and the latter for newer array processing systems. an extension of these algorithms to parse deremer's slr(1) class of grammars is demonstrated.
statistically-hiding commitment from any one-way function. we give a construction of statistically-hiding commitment schemes (ones where the hiding propertyholds information theoretically), based on the minimal cryptographic assumption that one-way functions exist. our construction employs two-phase commitment schemes, recently constructed by nguyen, ong and vadhan (focs '06), and universal one-way hash functions introduced and constructedby naor and yung (stoc '89) and rompel (stoc '90).
degree-languages, polynomial time recognition, and the lba problem the so-called chomsky hierarchy [5], consisting of regular, context-free, context-sensitive, and recursively enumerable languages, does not account for many &ldquo;real world&rdquo; classes of languages, e.g., programming languages and natural languages [4]. this is one of the reasons why many attempts have been made to &ldquo;refine&rdquo; the original chomsky classification. the main goal has been to describe languages which, for instance, are not context-free but are still context-sensitive, without using the powerful and complex concept of context-sensitive grammars.
on the convergence of newton's method for monotone systems of polynomial equations. monotone systems of polynomial equations (mspes) are systems of fixed-point equations x1 = f1(x1, ..., xn), ..., xn = fn(x1, ..., xn) where each fi is a polynomial with positive real coefficients. the question of computing the least non-negative solution of a given mspe x = f(x) arises naturally in the analysis of stochastic context-free grammars, recursive markov chains, and probabilistic pushdown automata. while the kleene sequence f(0), f(f(0)), ... always converges to the least solution mu.f, if it exists, the number of iterations needed to compute the first i bits of mu.f may grow exponentially in i.etessami and yannakakis have recently adapted newton's iterative method to mspes and proved that the newton sequence converges at least as fast as the kleene sequence and exponentially faster in many cases.they conjecture that, given an mspe of size m, the number of newton iterations needed to obtain i accurate bits of mu.f grows polynomially in i and m. in this paper we show that the number of iterations grows linearly in i for strongly connected mspes and may grow exponentially in m for general mspes.
zero-knowledge from secure multiparty computation. we present a general construction of a zero-knowledge proof for an np relation r(x,w) which only makes a black-box use of a secure protocol for a related multi-partyfunctionality f. the latter protocol is only required to be secure against a small number of "honest but curious" players. as an application, we can translate previous results on the efficiency of secure multiparty computation to the domain of zero-knowledge, improving over previous constructions of efficient zero-knowledge proofs. in particular, if verifying r on a witness of length m can be done by a circuit c of size s, and assuming one-way functions exist, we get the following types of zero-knowledge proof protocols. approaching the witness length. if c has constant depth over ∧,∨,⊕, - gates of unbounded fan-in, we get a zero-knowledge protocol with communication complexity m·poly(k)·polylog(s), where k is a security parameter. such a protocol can be implemented in either the standard interactive model or, following a trusted setup, in a non-interactive model. "constant-rate" zero-knowledge. for an arbitrary circuit c of size s and a bounded fan-in, we geta zero-knowledge protocol with communication complexity o(s)+poly(k). thus, for large circuits, the ratio between the communication complexity and the circuit size approaches a constant. this improves over the o(ks) complexity of the best previous protocols.
node- and edge-deletion np-complete problems if &pgr; is a graph property, the general node(edge) deletion problem can be stated as follows: find the minimum number of nodes(edges), whose deletion results in a subgraph satisfying property &pgr;. in this paper we show that if &pgr; belongs to a rather broad class of properties (the class of properties that are hereditary on induced subgraphs) then the node-deletion problem is np-complete, and the same is true for several restrictions of it. for the same class of properties, requiring the remaining graph to be connected does not change the np-complete status of the problem; moreover for a certain subclass, finding any "reasonable" approximation is also np-complete. edge-deletion problems seem to be less amenable to such generalizations. we show however that for several common properties (e.g. planar, outer-planar, line-graph, transitive digraph) the edge-deletion problem is np-complete.
randomly coloring planar graphs with fewer colors than the maximum degree. we study markov chains for randomly sampling k-colorings of a graph with maximum degree δ. our main result is a polynomial upper bound on the mixing time of the single-site update chain knownas the glauber dynamics for planar graphs when k=ω(δ/logδ). our results can be partially extended to the more general case where the maximum eigenvalue of the adjacency matrix of the graphis at most δ1-ε, for fixed ε > 0. the main challenge when k ≤ δ + 1 is the possibility of "frozen" vertices, that is, vertices for which only one coloris possible, conditioned on the colors of its neighbors. indeed, when δ = o(1), even a typical coloring canhave a constant fraction of the vertices frozen.our proofs rely on recent advances in techniquesfor bounding mixing time using "local uniformity" properties.
issues of correctness in database concurrency control by locking our aim in this paper is to show that there is a mathematically inherent reason why existing systems enforce d-serializability (rather than just because of its simplicity): it is because they are based on locking. our main result is a characterization of the power of locking which states that if a locking policy is safe then it must allow only d-serializable schedules. furthermore any such schedule can be produced by some safe locking policy. the rest of the paper is organized as follows. in section 2 we formalize our concepts and describe the model. in section 3 we characterize d-serializability in semantic terms. in section 4 we examine when a set of transactions can be let to run safely by themselves without locking or any intervention from the scheduler. section 5 is concerned with locking policies and in section 6 we discuss some implications of our results.
an approximation algorithm for max-min fair allocation of indivisible goods. in this paper we give the first approximation algorithm for the problem of max-min fair allocation of indivisible goods. the approximation ratio of our algorithm is ω1√k log3 k. as a part of our algorithm, we design an iterative method for rounding a fractional matching on a tree which might be of independent interest.
circuit lower bounds for merlin-arthur classes. we show that for each $k>0$, $\mathsf{ma}/1$ ($\mathsf{ma}$ with 1 bit of advice) does not have circuits of size $n^k$. this implies the first superlinear circuit lower bounds for the promise versions of the classes $\mathsf{ma}$, $\mathsf{am}$, and $\mathsf{zpp}_{\parallel}^{\mathsf{np}}$. we extend our main result in several ways. for each $k$, we give an explicit language in $(\mathsf{ma}\cap\mathsf{coma})/1$ which does not have circuits of size $n^k$. we also adapt our lower bound to the average-case setting; i.e., we show that $\mathsf{ma}/1$ cannot be solved on more than $1/2+1/n^k$ fraction of inputs of length $n$ by circuits of size $n^k$. furthermore, we prove that $\mathsf{ma}$ does not have arithmetic circuits of size $n^k$ for any $k$. as a corollary to our main result, we obtain that derandomization of $\mathsf{ma}/o(1)$ implies the existence of pseudorandom generators computable using $o(1)$ bits of advice.
tensor-based hardness of the shortest vector problem to within almost polynomial factors. we show that unless np ⊆ rtime (2poly(log n)), for any ε > 0 there is no polynomial-time algorithm approximating the shortest vector problem (svp) on n-dimensional lattices inthe lp norm (1 ≤q p<∞) to within a factor of 2(log n)1-ε. this improves the previous best factor of 2(logn)1/2-ε under the same complexity assumption due to khot. under the stronger assumption np ࣰ rsubexp, we obtain a hardness factor of nc/log log n for some c > 0. our proof starts with khot's svp instances from that are hard to approximate to within some constant. to boost the hardness factor we simply apply the standard tensor product oflattices. the main novel part is in the analysis, where we show that khot's lattices behave nicely under tensorization. at the heart of the analysis is a certain matrix inequality which was first used in the context of lattices by de shalit and parzanchevski.
on the impossibility of a quantum sieve algorithm for graph isomorphism. it is known that any quantum algorithm for graph isomorphism thatworks within the framework of the hidden subgroup problem (hsp) must performhighly entangled measurements across ω(n log n) coset states. one ofthe only known models for how such a measurement could be carried outefficiently is kuperberg's algorithm for the hsp in the dihedral group, in whichquantum states are adaptively combined and measured according to thedecomposition of tensor products into irreducible representations. this "quantum sieve" starts with coset states, and works its way down towardsrepresentations whose probabilities differ depending on, for example, whetherthe hidden subgroup is trivial or nontrivial. in this paper we show that no such approach can produce a polynomial-time quantum algorithm for graph isomorphism. specifically, we consider the natural reduction of graph isomorphism to the hsp over the the wreath product sn ࣀ z2. using a recently proved bound on the irreducible characters of sn, we show that no algorithm in this family can solve graph isomorphism in less than eω(√n) time, no matter what adaptive rule it uses to select and combine quantum states. in particular, algorithms of this type can offer essentially no improvement over the best known classical algorithms, which run in time eo(√(n log n)).
graph entropy and quantum sorting problems. let p = (x, < p) be a partial order on a set of n elements x = x1, x2,..., xn. define the quantum sorting problem qsortp as: given n distinct numbers x1, x2,..., xn consistent with p, sort them by a quantum decision tree using comparisons of the form "xi: xj". let qε(p) be the minimum number of queries used by any quantum decision tree for solving qsortp with error less than ε (where 0 < ε < 1/10 is fixed). it was proved by hoyer, neerbek and shi (algorithmica 34 (2002), 429--448) that, when p0 is the empty partial order, qε(p0) ≥ ω (n log n), i. e., the classical information lower bound holds for quantum decision trees when the input permutations are unrestricted.in this paper we show that the classical information lower bound holds, up to an additive linear term, for quantum decision trees for any partial order p. precisely, we prove qε(p) ≥ c log2 e(p)-c'n where c,c' > 0 are constants and e(p) is the number of linear orderings consistent with p. our proof builds on an interesting connection between sorting and korner's graph entropy that was first noted and developed by kahn and kim (jcss 51(1995), 390--399).
eisenberg-gale markets: algorithms and structural properties. we define a new class of markets, the eisenberg-gale markets. this class contains fisher's linear market, markets from the resource allocation framework of kelly kelly, as well as numerous interesting new markets.we obtain combinatorial, strongly polynomial algorithms for severalmarkets in this class. our algorithms have a simple description as ascending price auctions. our algorithms lead to insights into the efficiency, fairness, rationality of solutions, and competition monotonicity of these markets. a classification of eisenberg-gale markets w.r.t. these properties reveals a surprisingly rich set of possibilities.
on computing the minima of quadratic forms (preliminary report) the following problem was recently raised by c. william gear [1]: let f(x1,x2,...,xn) &equil; &sgr;i&le;j a'ijxixj + &sgr;i bixi +c be a quadratic form in n variables. we wish to compute the point x&rarr;(0) &equil; (x1(0),...,xn(0)), at which f achieves its minimum, by a series of adaptive functional evaluations. it is clear that, by evaluating f(x&rarr;) at 1/2(n+1)(n+2)+1 points, we can determine the coefficients a'ij,bi,c and thereby find the point x&rarr;(0). gear's question is, &ldquo;how many evaluations are necessary?&rdquo; in this paper, we shall prove that o(n2) evaluations are necessary in the worst case for any such algorithm.
on the submodularity of influence in social networks. we prove and extend a conjecture of kempe, kleinberg, and tardos (kkt) on the spread of influence in social networks. a social network can be represented by a directed graph where the nodes are individuals and the edges indicate a form of social relationship. a simple way to model the diffusion of ideas, innovative behavior, or "word-of-mouth" effects on such a graph is to consider an increasing process of "infected" (or active) nodes: each node becomes infected once an activation function of the set of its infected neighbors crosses a certain threshold value. such a model was introduced by kkt in [7,8] where the authors also impose several natural assumptions: the threshold values are (uniformly) random to account for our lack of knowledge of the true values; and the activation functions are monotone and submodular, i.e. have "diminishing returns." the monotonicity condition indicates that a node is more likely to become active if more of its neighbors are active, while the submodularity condition, indicates that the marginal effect of each neighbor is decreasing when the set of active neighbors increases. for an initial set of active nodes s, let σ(s) denote the expected number of active nodes at termination. here we prove a conjecture of kkt: we show that the function σ(s) is submodular under the assumptions above. we prove the same result for the expected value of any monotone, submodular function of the set of active nodes at termination. in other words, our results demonstrate that "local" submodularity is preserved "globally" under diffusion processes. this is of natural computational interest, as many optimization problems have good approximation algorithms for submodular functions. in particular, our results coupled with an argument in [7] imply that a greedy algorithm gives an (1-1/e-ε)-approximation algorithm for maximizing σ(s) among all sets s of a given size. this result has important practical implications for many social network analysis problems, notably viral marketing.
on the average behavior of set merging algorithms (extended abstract) in this paper we study the expected running time of a variety of algorithms that perform set merging. the set merging problem (for example, see ahu [1]) is concerned with using suitable data structures to represent partition of a set s &equil; { 1,2, .... ,n} so that a sequence of instructions of the form &ldquo;x &xgr; y&rdquo;, meaning &ldquo;find the subset containing x; find the subset containing y; merge the two subsets if they are different.&rdquo; may be carried out efficiently. several alternative data structures for solving this problem are known, and their worse-case complexity fairly well understood [3], [4], [5], [8]. in contrast, the average behavior of even the most basic of these schemes remains an open problem [6]. it is the purpose of the present paper to determine the average behavior for several of the set merging algorithms commonly known.
a 3-query pcp over integers. a classic result due to haastad~hastad established that for every constant ε > 0, given an overdetermined system of linear equations over a finite field fq where each equation depends on exactly 3 variables and at least a fraction (1-ε) of the equations can be satisfied, it is np-hard to satisfy even a fraction (1/q+ε) of the equations. in this work, we prove the analog of håstad's result for equations over the integers (as well as the reals). formally, we prove that for every ε,δ > 0, given a system of linear equations with integer coefficients where each equation is on 3 variables, it is np-hard to distinguish between the following two cases: (i) there is an assignment of integer values to the variables that satisfies at least a fraction (1-ε) of the equations, and (ii) no assignmenteven of real values to the variables satisfies more than a fraction δ of the equations.
some complexity questions related to distributive computing (preliminary report) let m &equil; {0, 1, 2, ..., m&mdash;1} , n &equil; {0, 1, 2,..., n&mdash;1} , and f:m &times; n &rarr; {0, 1} a boolean-valued function. we will be interested in the following problem and its related questions. let i &egr; m, j &egr; n be integers known only to two persons p1 and p2, respectively. for p1 and p2 to determine cooperatively the value f(i, j), they send information to each other alternately, one bit at a time, according to some algorithm. the quantity of interest, which measures the information exchange necessary for computing f, is the minimum number of bits exchanged in any algorithm. for example, if f(i, j) &equil; (i + j) mod 2. then 1 bit of information (conveying whether i is odd) sent from p1 to p2 will enable p2 to determine f(i, j), and this is clearly the best possible. the above problem is a variation of a model of abelson [1] concerning information transfer in distributive computions.
degree-constrained network flows. a d-furcated flow is a network flow whose support graph has maximum out degree d. take a single-sink multi-commodity flow problem on any network and with any set of routing demands. then we show that the existence of feasible fractional flow with node congestion one implies the existence of a d-furcated flow with congestion at most 1+1/(d-1), for d ≥ 2. this result is tight, and sothe congestion gap for d-furcated flows is bounded andexactly equal to 1+ 1/(d-1). for the case d=1 (confluent flows), it is known that the congestion gap is unbounded, namely θ(log n). thus, allowing single-sink multicommodity network flows to increase their maximum out degree from one to two virtually eliminates this previously observed congestion gap. as a corollary we obtain a factor 1 + 1/(d-1)-approximation algorithm for the problem of finding a minimum congestion d-furcated flow; we also prove that this problem is max snp-hard. using known techniques these results also extend to degree-constrained unsplittable routing,where each individual demand must be routed along a unique path.
efficient dynamic programming using quadrangle inequalities dynamic programming is one of several widely used problem-solving techniques in computer science and operation research. in applying this technique, one always seeks to find speed-up by taking advantage of special properties of the problem at hand. however, in the current state of art, ad hoc approaches for speeding up seem to be characteristic; few general criteria are known. in this paper we give a quadrangle inequality condition for rendering speed-up. this condition is easily checked, and can be applied to several apparently different problems. for example, it follows immediately from our general condition that the construction of optimal binary search trees may be speeded up from o(n3) steps to o(n2), a result that was first obtained by knuth using a different and rather complicated argument.
vertex cuts, random walks, and dimension reduction in series-parallel graphs. we consider questions about vertex cuts in graphs, random walks in metric spaces, and dimension reduction in l1 and l2; these topics are intimately connected because they can each be reduced to the existence ofvarious families of real-valued lipschitz maps on certain metric spaces. we view these issues through the lens of shortest-path metricson series-parallel graphs, and we discussthe implications for a variety of well-known open problems. our main results follow. every n-point series-parallel metric embeds into l1dom with o(√ log n) distortion, matchinga lower bound of newman and rabinovich. our embeddings yield an o(√log n) approximation algorithm for vertex sparsestcut in such graphs, as well as an o(√log k) approximate max-flow/min-vertex-cut theorem for series-parallel instances withk terminals, improving over the o(log n) and o(log k) boundsfor general graphs. every n-point series-parallel metric embeds withdistortion d into l1d with d = n1/ω(d2),matching the dimension reduction lower bound of brinkman andcharikar. there exists a constant c > 0 such that if (x,d) is aseries-parallel metric then for every stationary, reversible markovchain ztt=0∞ on x, we have for all t ≥ 0, e[d(zt,z0)2] ≤ ct ·, e[d(z0,z1)2]. more generally, we show thatseries-parallel metrics have markov type 2. this generalizesa result of naor, peres, schramm, and sheffield for trees.
on the parallel computation for the knapsack problem we are interested in the complexity of solving the knapsack problem with n input real numbers on a parallel computer with real arithmetic and branching operations. a processor-time tradeoff constraint is derived; in particular, it is shown that an exponential number of processors have to be used if the problem is to be solved in time t &le; @@@@n/2.
interval completion with few edges. we present an algorithm with runtime o(k(2k)n3 * m) for the following np-complete problem: given an arbitrary graph g on n vertices and m edges, can we obtain an interval graph by adding at most k new edges to g? this resolves the long-standing open question, first posed by kaplan, shamir and tarjan, of whether this problem could be solved in time f(k) * n(o(1)).the problem has applications in physical mapping of dna and in profile minimization for sparse matrix computations. for the first application, our results show tractability for the case of a small number k of false negative errors, and for the second, a small number k of zero elements in the envelope. our algorithm performs bounded search among possible ways of adding edges to a graph to obtain an interval graph, and combines this with a greedy algorithm when graphs of a certain structure are reached by the search. the presented result is surprising, as it was not believed that a bounded search tree algorithm would suffice to answer the open question affirmatively.
the entropic limitations on vlsi computations (extended abstract) in this paper we will explore the limitations imposed by entropic constraints, both in generality and for specific problems. we list below the main questions that we will address. (1) in the binary number system, addition is easy while multiplication is hard for vlsi. is there an &ldquo;ideal&rdquo; number representation, in which all arithmetic operations have efficient vlsi implementations? (2) can one build multipliers for binary numbers, which achieve both small area and fast average computation time? (3) thompson's technique applies only to multiple output functions. how can one prove area-time bounds for single output functions? (4) what other ways are there for deriving entropic constraints from consideration of data movement? answers to these questions will be discussed in the ensuing sections.
tight bounds for asynchronous randomized consensus. a distributed consensus algorithm allows n processes to reach acommon decision value starting from individual inputs. wait-free consensus, in which a process always terminates within a finite number of its own steps, is impossible in anasynchronous shared-memory system. however, consensus becomes solvable using randomization when a process only has to terminatewith probability 1. randomized consensus algorithms are typically evaluated by their total step complexity, which is the expected total number of steps taken by all processes. this work proves that the total step complexity of randomized consensus is θ(n2) in an asynchronous shared memory systemusing multi-writer multi-reader registers. the bound is achieved by improving both the lower and the upper bounds for this problem. in addition to improving upon the best previously known result bya factor of log2 n, the lower bound features agreatly streamlined proof. both goals are achieved through restricting attention to a set of layered executions andusing an isoperimetric inequality for analyzing their behavior. the matching algorithm decreases the expected total step complexity by a log n factor, by leveraging themulti-writing capability of the shared registers. its correctness proof is facilitated by viewing each execution of the algorithmas a stochastic process and applying kolmogorov's inequality.
space-time tradeoff for answering range queries (extended abstract) in this paper, we raise and investigate the question of (storage) space- (retrieval) time tradeoff for a static database, in the general framework of fredman's. as will be seen, such tradeoff results also lead to lower bounds on the complexity of processing a sequence of m insert and query instructions. the latter results are incomparable to fredman's, since the presence of delete instructions was crucial for his proof technique. we will present our results in detail in the next few sections. here we will only mention three main conclusions. firstly, circular query is shown to be intrinsically hard in the sense that, for some static database with n records, there is a space-time tradeoff ts -&-gt; n1 + -&-egr; where -&-egr;-&-gt;0; in contrast, orthogonal query can always be implemented with space s-&-equil;0(n(log n)k) and time t-&-equil;0((log n)k) for fixed k. furthermore, any algorithm for processing 0(n) insert and query instructions must use time -&-ohgr;(n1+-&-egr;) in the worst case. secondly, for the -&-ldquo;interval-&-rdquo; query, we have determined the space-time tradeoff quite precisely to be t @@@@ -&-agr;(s,n), where -&-agr; is the inverse to an ackermann's function first defined by tarjan [9]. this is a rare case where the function -&-agr; arises outside the context of path compression, and is obtained through a totally independent derivation. thirdly, we prove that, for the interval query, any algorithm to process a sequence of 0(n) insert and query must take time -&-ohgr;((n log n)/(log log n)) in the worst case. this means that one cannot hope to maintain the most efficient static data structure (with retrieval time -&-agr;(s,n)) in the dynamic case.
limitations of vcg-based mechanisms. we consider computationally-efficient incentive-compatiblemechanisms that use the vcg payment scheme, and study how well theycan approximate the social welfare in auction settings. we present anovel technique for setting lower bounds on the approximation ratioof this type of mechanisms. specifically, for combinatorial auctionsamong submodular (and thus also subadditive) bidders we prove an ω(m1/6) lower bound, which is close to the knownupper bound of o(m1/2), and qualitatively higher than theconstant factor approximation possible from a purely computationalpoint of view.
one sketch for all: fast algorithms for compressed sensing. compressed sensing is a new paradigm for acquiring the compressible signals that arise in many applications. these signals can be approximated using an amount of information much smaller than the nominal dimension of the signal. traditional approaches acquire the entire signal and process it to extract the information. the new approach acquires a small number of nonadaptive linear measurements of the signal and uses sophisticated algorithms to determine its information content. emerging technologies can compute these general linear measurements of a signal at unit cost per measurement. this paper exhibits a randomized measurement ensemble and a signal reconstruction algorithm that satisfy four requirements: 1. the measurement ensemble succeeds for all signals, with high probability over the random choices in its construction. 2. the number of measurements of the signal is optimal, except for a factor polylogarithmic in the signal length. 3. the running time of the algorithm is polynomial in the amount of information in the signal and polylogarithmic in the signal length. 4. the recovery algorithm offers the strongest possible type of error guarantee. moreover, it is a fully polynomial approximation scheme with respect to this type of error bound. emerging applications demand this level of performance. yet no otheralgorithm in the literature simultaneously achieves all four of these desiderata.
circuits and local computation this paper contains two parts. in part i, we show that polynomial-size monotone threshold circuits of depth k form a proper hierarchy in parameter k. this implies in particular that monotone tc0 is properly contained in nc1. in part ii, we introduce a new concept, called local function, which tries to characterize when a function can be efficiently computed using only localized processing elements. it serves as a unifying framework for viewing related and sometimes apparently unrelated results. in particular, it will be demonstrated that the recent results on lower bounds for monotone circuits by razborov [ra1] and karchmer and wigderson [kw], as well as a main theorem in part i of this paper, can be regarded as proving certain functions to be nonlocal. we will also suggest an approach based on locality for attacking the conjecture that (nonmonotone) tc0 is properly contained in nc1.
approximating minimum bounded degree spanning trees to within one of optimal. in the minimum bounded degree spanning tree problem, we aregiven an undirected graph with a degree upper bound bv on eachvertex v, and the task is to find a spanning tree of minimumcost which satisfies all the degree bounds. let opt be the costof an optimal solution to this problem. in this paper, we presenta polynomial time algorithm which returns a spanning tree t ofcost at most opt and dt(v) ≤ bv+1 for all v, where dt(v) denotes the degree of v in t. this generalizes aresult of furer and raghavachari [8] to weighted graphs, andsettles a 15-year-old conjecture of goemans [10] affirmatively. the algorithm generalizes when each vertex v hasa degree lower bound av and a degree upper bound bv, andreturns a spanning tree with cost at most opt and av - 1 ≤dt(v) ≤ bv + 1 for all v. this is essentially the bestpossible. the main technique used is an extension of the iterativerounding method introduced by jain [12] for the design ofapproximation algorithms.
parallel repetition: simplifications and the no-signaling case. consider a game where a refereed chooses (x,y) according to a publiclyknown distribution pxy, sends x to alice, and y to bob. withoutcommunicating with each other, alice responds with a value "a" and bobresponds with a value "b". alice and bob jointly win if a publiclyknown predicate q(x,y,a,b) holds. let such a game be given and assume that the maximum probabilitythat alice and bob can win is v<1. raz (siam j. comput. 27, 1998)shows that if the game is repeated n times in parallel, then the probability that alice and bob win all games simultaneously is at most v'(n/log(s)), where s is the maximal number of possible responses from alice and bob in the initial game, and v' is a constant depending only on v. in this work, we simplify raz's proof in various ways and thus shorten it significantly. further we study the case where alice and bob are not restricted to local computations and can use any strategy which does not imply communication among them.
hardness of routing with congestion in directed graphs. given as input a directed graph on n vertices and a set ofsource-destination pairs, we study the problem of routing themaximum possible number of source-destination pairs on paths, suchthat at most c(n) paths go through any edge. we show that theproblem is hard to approximate within an nω(1/c(n)) factoreven when we compare to the optimal solution that routes pairs onedge-disjoint paths, assuming np doesn't have no(log logn)-time randomized algorithms. here the congestion c(n) can beany function in the range 1 ≤ c(n) ≤ α log n/log log n for some absolute constant α > 0. the hardness result is in the right ballpark since a factor no(1/c(n)) approximation algorithm is known for this problem, viarounding a natural multicommodity-flow relaxation. we also give asimple integrality gap construction that shows that themulticommodity-flow relaxation has an integrality gap of nω(1/c) for c ranging from 1 to θ((log n)/(log log n)). a solution to the routing problem involves selecting which pairs tobe routed and what paths to assign to each routed pair. two naturalrestrictions can be placed on input instances to eliminate one ofthese aspects of the problem complexity. the first restriction is toconsider instances with perfect completeness; an optimalsolution is able to route all pairs with congestion 1 in suchinstances. the second restriction to consider is the uniquepaths property where each source-destination pair has a unique pathconnecting it in the instance. an important aspect of our result isthat it holds on instances with any one of these tworestrictions. our hardness construction with the perfectcompleteness restriction allows us to conclude that the directedcongestion minimization problem, where the goal is to route allpairs with minimum congestion, is hard to approximate to within afactor of ω(log n/log log n). on the other hand, thehardness construction with unique paths property allows us toconclude an nω(1/c) inapproximability bound also for theall-or-nothing flow problem. this is in a sharp contrast to theundirected setting where the all-or-nothing flow problem is known tobe approximable to within a poly-logarithmic factor.
inapproximability of the tutte polynomial. the tutte polynomial of a graph g is a two-variable polynomial t(g;x,y) that encodes many interesting properties of the graph. we study the complexity of the following problem, for rationals x and y: take as input a graph g, and output a value which is a good approximation to t(g;x,y). jaeger et al. have completely mapped the complexity of exactly computing the tutte polynomial. they have shown that this is #p-hard, except along the hyperbola (x-1)(y-1)=1 and at four special points. we are interested in determining for which points (x,y) there is a fully polynomial randomised approximation scheme (fpras) for t(g;x,y). under the assumption rpnp, there is no fpras at the point (x,y)=(0,1-@l) when @l>2 is a positive integer. thus, there is no fpras for counting nowhere-zero @l flows for @l>2. this is an interesting consequence of our work since the corresponding decision problem is in p for example for @l=6. although our main concern is to distinguish regions of the tutte plane that admit an fpras from those that do not, we also note that the latter regions exhibit different levels of intractability. at certain points (x,y), for example the integer points on the x-axis, or any point in the positive quadrant, there is a randomised approximation scheme for t(g;x,y) that runs in polynomial time using an oracle for an np predicate. on the other hand, we identify a region of points (x,y) at which even approximating t(g;x,y) is as hard as #p.
the communication complexity of uncoupled nash equilibrium procedures. we study the question of how long it takes players to reach a nashequilibrium in uncoupled setups, where each player initially knowsonly his own payoff function. we derive lower bounds on the communication complexity of reaching a nash equilibrium, i.e., on thenumber of bits that need to be transmitted, and thus also on the requirednumber of steps. specifically, we show lower bounds that are exponential inthe number of players in each one of the following cases: (1) reaching apure nash equilibrium; (2) reaching a pure nash equilibrium in a bayesiansetting; and (3) reaching a mixed nash equilibrium. we then show that, incontrast, the communication complexity of reaching a correlated equilibriumis polynomial in the number of players.
space-time tradeoffs and first order problems in a model of programs we introduce a model of programs for comparison-based problems. this model gives a measure of space usage and is &ldquo;uniform&rdquo;. we first obtain upper and lower bounds on the selection problems which demonstrate the tradeoffs between time and space. we next introduce the class of first order problems and characterize them semantically. a surprisingly simple classification of first order problems into three complexity classes is shown. finally we extend the first order problems to the weak second order problems and show that these can be solved in polynomial time by programs in our model augmented with push-down stores.
testing k-wise and almost k-wise independence. in this work, we consider the problems of testing whether adistribution over (0,1n) is k-wise (resp. (ε,k)-wise) independentusing samples drawn from that distribution. for the problem of distinguishing k-wise independent distributions from those that are δ-far from k-wise independence in statistical distance, we upper bound the number ofrequired samples by õ(nk/δ2) and lower bound it by ω(nk-1/2/δ) (these bounds hold for constantk, and essentially the same bounds hold for general k). toachieve these bounds, we use fourier analysis to relate adistribution's distance from k-wise independence to its biases, a measure of the parity imbalance it induces on a setof variables. the relationships we derive are tighter than previouslyknown, and may be of independent interest. to distinguish (ε,k)-wise independent distributions from thosethat are δ-far from (ε,k)-wise independence in statistical distance, we upper bound thenumber of required samples by o(k log n / δ2ε2) and lower bound it by ω(√ k log n / 2k(ε+δ)√ log 1/2k(ε+δ)). although these bounds are anexponential improvement (in terms of n and k) over thecorresponding bounds for testing k-wise independence, we give evidence thatthe time complexity of testing (ε,k)-wise independence isunlikely to be poly(n,1/ε,1/δ) for k=θ(log n),since this would disprove a plausible conjecture concerning the hardness offinding hidden cliques in random graphs. under the conjecture, ourresult implies that for, say, k = log n and ε = 1 / n0.99,there is a set of (ε,k)-wise independent distributions, and a set of distributions at distance δ=1/n0.51 from (ε,k)-wiseindependence, which are indistinguishable by polynomial time algorithms.
all-pairs bottleneck paths for general graphs in truly sub-cubic time. in the all-pairs bottleneck paths (apbp) problem (a.k.a. all-pairs maximum capacity paths), one is given a directed graph with real non-negative capacities on its edges and is asked to determine, for all pairs of vertices s and t, the capacity of a single path for which a maximum amount of flow can be routed from s to t. the apbp problem was first studied in operations research, shortly after the introduction of maximum flows and all-pairs shortest paths. we present the first truly sub-cubic algorithm for apbp in general dense graphs. in particular, we give a procedure for computing the (max, min)-product of two arbitrary matrices over r ∪ (∞,-∞) in o(n2+ω/3) ≤ o(n2.792) time, where n is the number of vertices and ω is the exponent for matrix multiplication over rings. using this procedure, an explicit maximum bottleneck path for any pair of nodes can be extracted in time linear in the length of the path.
towards 3-query locally decodable codes of subexponential length. a q-query locally decodable code (ldc) encodes an n-bit message x as an n-bit codeword c(x), such that one can probabilistically recover any bit xi of the message by querying only q bits of the codeword c(x), even after some constant fraction of codeword bits has been corrupted. we give new constructions of three query ldcs of vastly shorter length than that of previous constructions. specifically, given any mersenne prime p &equals; 2t &minus; 1, we design three query ldcs of length n &equals; exp(o(n1/t)), for every n. based on the largest known mersenne prime, this translates to a length of less than exp(o(n10 &minus; 7)) compared to exp(o(n1/2)) in the previous constructions. it has often been conjectured that there are infinitely many mersenne primes. under this conjecture, our constructions yield three query locally decodable codes of length n &equals; exp(no(1/log log n)) for infinitely many n. we also obtain analogous improvements for private information retrieval (pir) schemes. we give 3-server pir schemes with communication complexity of o(n10 &minus; 7) to access an n-bit database, compared to the previous best scheme with complexity o(n1/5.25). assuming again that there are infinitely many mersenne primes, we get 3-server pir schemes of communication complexity no(1/log logn)) for infinitely many n. previous families of ldcs and pir schemes were based on the properties of low-degree multivariate polynomials over finite fields. our constructions are completely different and are obtained by constructing a large number of vectors in a small dimensional vector space whose inner products are restricted to lie in an algebraically nice set.
hardness-randomness tradeoffs for bounded depth arithmetic circuits. in this paper we show that lower bounds for bounded depth arithmetic circuits imply derandomization of polynomial identity testing for bounded depth arithmetic circuits. more formally, if there exists an explicit polynomial f(x1,...,xm) that cannot be computed by a depth d arithmetic circuit of small size then there exists an efficient deterministic algorithm to test whether a given depth d-8 circuit is identically zero or not (assuming the individual degrees of the tested circuit are not too high). in particular, if we are guaranteed that the circuit computes a multilinear polynomial then we can perform the identity test efficiently. to the best of our knowledge this is the first hardness-randomness tradeoff for bounded depth arithmetic circuits. the above results are obtained using the arithmetic nisan-wigderson generator of impagliazzo and kabanets together with a new theorem on bounded depth circuits, which is the main technical contribution of our work. this theorem deals with polynomial equations of the form p(x1,...,xn,y) ≡ 0 and shows that if p has a circuit of depth d and size s and if the polynomial f(x1,...,xn) satisfies p(x1,...,xn,f(x1,...,xn))≡ 0 then f has a circuit of depth d+3 and size o(s • r + mr), where m is the degree of f and r is the highest degree of the variable y appearing in p. in the other direction we observe that the methods of impagliazzo and kabanets imply that if we can derandomize polynomial identity testing for bounded depth circuits then nexp does not have bounded depth arithmetic circuits. that is, either nexp ⊄ p/poly or the permanent is not computable by polynomial size bounded depth arithmetic circuits.
graph sparsification by effective resistances. we present a nearly-linear time algorithm that produces high-quality sparsifiers of weighted graphs. given as input a weighted graph g=(v,e,w) and a parameter ε>0, we produce a weighted subgraph h=(v,~e,~w) of g such that |~e|=o(n log n/ε2) and for all vectors x in rv. (1-ε) ∑uv ∈ e (x(u)-x(v))2wuv≤ ∑uv in ~e(x(u)-x(v))2~wuv ≤ (1+ε)∑uv ∈ e(x(u)-x(v))2wuv. this improves upon the sparsifiers constructed by spielman and teng, which had o(n logc n) edges for some large constant c, and upon those of benczur and karger, which only satisfied (1) for x in {0,1}v. we conjecture the existence of sparsifiers with o(n) edges, noting that these would generalize the notion of expander graphs, which are constant-degree sparsifiers for the complete graph. a key ingredient in our algorithm is a subroutine of independent interest: a nearly-linear time algorithm that builds a data structure from which we can query the approximate effective resistance between any two vertices in a graph in o(log n) time.
sampling-based dimension reduction for subspace approximation. we give a randomized bi-criteria algorithm for the problem of finding a k-dimensional subspace that minimizesthe lp-error for given points, i.e., p-th root of the sum of p-th powers of distances to given points,for any p ≥ 1. our algorithm runs in time õ (mn · pk3 (k/ε)2p) andproduces a subset of size õ (pk2 (k/ε)2p) from the given points such that, withhigh probability, the span of these points gives a (1+ε)-approximation to the optimal k-dimensionalsubspace. we also show a dimension reduction type of result for this problem where we can efficiently find asubset of size õ (pk2(p+1) + (k/ε)p+2) such that, with high probability, theirspan contains a k-dimensional subspace that gives (1+ε)-approximation to the optimum. we prove similarresults for the corresponding projective clustering problem where we need to find multiple k-dimensional subspaces.
faster approximate lossy generalized flow via interior point algorithms. we present asymptotically faster approximation algorithms for the generalized flow problems in which multipliers on edges are at most 1. for this lossy version of the maximum generalized flow problem, we obtain an additive ε approximation of the maximum flow in time o{m3/2 log (u/ε)2}, where m is the number of edges in the graph, all capacities are integers in the range {1, ... , u}, and all loss multipliers are ratios of integers in this range. for minimum cost lossy generalized flow with costs in the range {1,... ,u}, we obtain a flow that has value within an additive ε of the maximum value and cost at most the optimal cost. in many parameter ranges, these algorithms improve over the previously fastest algorithms for the generalized maximum flow problem by a factor of m1/2 and for the minimum cost generalized flow problem by a factor of approximately m1/2/ ε2. the algorithms work by accelerating traditional interior point algorithms by quickly solving the system of linear equations that arises in each step. the contributions of this paper are twofold. first, we analyze the performance of interior point algorithms with approximate linear system solvers. this analysis alone provides an algorithm for the standard minimum cost flow problem that runs in time om3/2 log u}--an improvement of roughly o{n / m1/2} over previous algorithms. second, we examine the linear equations that arise when using an interior point algorithm to solve generalized flow problems. we observe that these belong to the family of symmetric m-matrices, and we then develop om-time algorithms for solving linear systems in these matrices. these algorithms reduce the problem of solving a linear system in a symmetric m-matrix to that of solving o{log n} linear systems in symmetric diagonally-dominant matrices, which we can do in time om using the algorithm of spielman and teng. all of our algorithms operate on numbers of bit length at most o{log n u / ε}.
a combinatorial construction of almost-ramanujan graphs using the zig-zag product. reingold, vadhan and wigderson [21] introduced the graph zig-zag product. this product combines a large graph and a small graph into one graph, such that the resulting graph inherits its size from the large graph, its degree from the small graph and its spectral gap from both. using this product they gave the first fully-explicit combinatorial construction of expander graphs. they showed how to construct d-regular graphs having spectral gap 1-o(d-1/3). in the same paper, they posed the open problem of whether a similar graph product could be used to achieve the almost-optimal spectral gap 1-o(d-1/2). in this paper we propose a generalization of the zig-zag product that combines a large graph and several small graphs. the new product gives a better relation between the degree and the spectral gap of the resulting graph. we use the new product to give a fully-explicit combinatorial construction of d-regular graphs having spectral gap 1-d-1/2 + o(1).
universal semantic communication i. is it possible for two intelligent beings to communicate meaningfully, without any common language or background? this question has interest on its own, but is especially relevant in the context of modern computational infrastructures where an increase in the diversity of computers is making the task of inter-computer interaction increasingly burdensome. computers spend a substantial amount of time updating their software to increase their knowledge of other computing devices. in turn, for any pair of communicating devices, one has to design software that enables the two to talk to each other. is it possible instead to let the two computing entities use their intelligence (universality as computers) to learn each others' behavior and attain a common understanding? what is 'common understanding?' we explore this question in this paper. to formalize this problem, we suggest that one should study the 'goal of communication:' why are the two entities interacting with each other, and what do they hope to gain by it? we propose that by considering this question explicitly, one can make progress on the question of universal communication. we start by considering a computational setting for the problem where the goal of one of the interacting players is to gain some computational wisdom from the other player. we show that if the second player is "sufficiently" helpful and powerful, then the first player can gain significant computational power (deciding pspace complete languages). our work highlights some of the definitional issues underlying the task of formalizing universal communication, but also suggests some interesting phenomena and highlights potential tools that may be used for such communication.
additive guarantees for degree bounded directed network design. we present polynomial-time approximation algorithms for some degree-bounded directed network design problems. our main result is for intersecting supermodular connectivity with degree bounds: given a directed graph g=(v,e) with non-negative edge-costs, a connectivity requirement specified by an intersecting supermodular function f, and upper bounds av, bvv∈ v on in-degrees and out-degrees of vertices, find a minimum-cost f-connected subgraph of g that satisfies the degree bounds. we give a bicriteria approximation algorithm that for any 0 ≤ ε ≤ 1/2, computes an f-connected subgraph with in-degrees at most ⌈ av/1-ε ⌉ + 4, out-degrees at most ⌈ bv/1-ε ⌉ + 4, and cost at most 1/ε times the optimum. this includes, as a special case, the minimum-cost degree-bounded arborescence problem. we also obtain similar results for the (more general) class of crossing supermodular requirements. our result extends and improves the (3av+4, 3bv+4, 3)-approximation of lau et al. setting ε=0, our result gives the first purely additive guarantee for the unweighted versions of these problems. our algorithm is based on rounding an lp relaxation for the problem. we also prove that the above cost-degree trade-off (even for the degree-bounded arborescence problem) is optimal relative to the natural lp relaxation. for every 0v/1-ε + o(1) has cost at least 1-o(1)/ε times the optimal lp value. for the special case of finding a minimum degree arborescence (without costs), we give a stronger +2 additive approximation. this improves on a result of lau et al. [13] that gives a 2δ*+2 guarantee, and klein et al. [11] that gives a (1+ε)δ*+o(log1+ε n) bound, where δ* is the degree of the optimal arborescence. as a corollary of our result, we (almost) settle a conjecture of bang-jensen et al. [1] on low-degree arborescences. our algorithms use the iterative rounding technique of jain, which was used by lau et al. and singh and lau in the context of degree-bounded network design. it is however non-trivial to extend these techniques to the directed setting without incurring a multiplicative violation in the degree bounds. this is due to the fact that known polyhedral characterization of arborescences has the cut-constraints which, along with degree-constraints, are unsuitable for arguing the existence of integral variables in a basic feasible solution. we overcome this difficulty by enhancing the iterative rounding steps and by means of stronger counting arguments. our counting technique is quite general, and it also simplifies the proofs of many previous results. we also apply the technique to undirected graphs. we consider the minimum crossing spanning tree problem: given an undirected edge-weighted graph g, edge-subsets eii=1k, and non-negative integers bii=1k, find a minimum-cost spanning tree (if it exists) in g that contains at most bi edges from each set ei. we obtain a +(r-1) additive approximation for this problem, when each edge lies in at most r sets; this considerably improves the result of bilo et al. a special case of this problem is degree-bounded minimum spanning tree, and our result gives a substantially easier proof of the recent +1 approximation of singh and lau.
on the constant-depth complexity of k-clique. we prove a lower bound of ω(nk/4) on the size of constant-depth circuits solving the k-clique problem on n-vertex graphs (for every constant k). this improves a lower bound of ω(nk/89d2) due to beame where d is the circuit depth. our lower bound has the advantage that it does not depend on the constant d in the exponent of n, thus breaking the mold of the traditional size-depth tradeoff. our k-clique lower bound derives from a stronger result of independent interest. suppose fn :0,1n/2 → {0,1} is a sequence of functions computed by constant-depth circuits of size o(nt). let g be an erdos-renyi random graph with vertex set {1,...,n} and independent edge probabilities n-α where α ≤ 1/2t-1. let a be a uniform random k-element subset of {1,...,n} (where k is any constant independent of n) and let ka denote the clique supported on a. we prove that fn(g) = fn(g ∪ ka) asymptotically almost surely. these results resolve a long-standing open question in finite model theory (going back at least to immerman in 1982). the m-variable fragment of first-order logic, denoted by fom, consists of the first-order sentences which involve at most m variables. our results imply that the bounded variable hierarchy fo1 ⊂ fo2 ⊂ ... ⊂ fom ⊂ ... is strict in terms of expressive power on finite ordered graphs. it was previously unknown that fo3 is less expressive than full first-order logic on finite ordered graphs.
hardness amplification proofs require majority. hardness amplification is the fundamental task of converting a δ-hard function f : (0, 1)n -> (0, 1) into a (1/2-ε)-hard function amp(f), where f is γ-hard if small circuits fail to compute f on at least a γ fraction of the inputs. typically, ε,δ are small (and δ=2-k captures the case where f is worst-case hard). achieving ε = 1/nω(1) is a prerequisite for cryptography and most pseudorandom-generator constructions. in this paper we study the complexity of black-box proofs of hardness amplification. a class of circuits cal d proves a hardness amplification result if for any function h that agrees with amp(f) on a 1/2+e fraction of the inputs there exists an oracle circuit d ∈ d such that dh agrees with f on a 1-δ fraction of the inputs. we focus on the case where every d ∈ d makes non-adaptive queries to h. this setting captures most hardness amplification techniques. we prove two main results: the circuits in d "can be used" to compute the majority function on 1e bits. in particular, these circuits have large depth when ε ≤ 1/ poly log n. the circuits in d must make ω log(1/δ)/e2 oracle queries. both our bounds on the depth and on the number of queries are tight up to constant factors. our results explain why hardness amplification techniques have failed to transform known lower bounds against constant-depth circuit classes into strong average-case lower bounds. when coupled with the celebrated "natural proofs" result by razborov and rudich (j. css '97) and the pseudorandom functions by naor and reingold (j. acm '04), our results show that standard techniques for hardness amplification can only be applied to those circuit classes for which standard techniques cannot prove circuit lower bounds. our results reveal a contrast between yao's xor lemma (amp(f) := f(x1) ⊕ ... ⊕ f(xt) ∈ zo) and the direct-product lemma (amp(f) := f(x1) o ... o f(xt) ∈ zot; here amp(f) is non-boolean). our results (1) and (2) apply to yao's xor lemma, whereas known proofs of the direct-product lemma violate both (1) and (2). one of our contributions is a new technique to handle "non-uniform" reductions, i.e. the case when d contains many circuits.
robust lower bounds for communication and stream computation. we study the communication complexity of evaluating functions when the input data is randomly allocated (according to some known distribution) amongst two or more players, possibly with information overlap. this naturally extends previously studied variable partition models such as the best-case and worst-case partition models [32,29]. we aim to understand whether the hardness of a communication problem holds for almost every allocation of the input, as opposed to holding for perhaps just a few atypical partitions. a key application is to the heavily studied data stream model. there is a strong connection between our communication lower bounds and lower bounds in the data stream model that are "robust" to the ordering of the data. that is, we prove lower bounds for when the order of the items in the stream is chosen not adversarially but rather uniformly (or near-uniformly) from the set of all permuations. this random-order data stream model has attracted recent interest, since lower bounds here give stronger evidence for the inherent hardness of streaming problems. our results include the first random-partition communication lower bounds for problems including multi-party set disjointness and gap-hamming-distance. both are tight. we also extend and improve previous results [19,7] for a form of pointer jumping that is relevant to the problem of selection (in particular, median finding). collectively, these results yield lower bounds for a variety of problems in the random-order data stream model, including estimating the number of distinct elements, approximating frequency moments, and quantile estimation.
unconditional pseudorandom generators for low degree polynomials. we give an explicit construction of pseudorandom generators against low degree polynomials over finite fields. we show that the sum of 2d small-biased generators with error ε2o(d) is a pseudorandom generator against degree d polynomials with error ε. this gives a generator with seed length 2o(d) log(n/ε). our construction follows the recent breakthrough result of bogadnov and viola. their work shows that the sum of d small-biased generators is a pseudo-random generator against degree d polynomials, assuming the inverse gowers conjecture. however, this conjecture is only proven for d=2,3. the main advantage of our work is that it does not rely on any unproven conjectures.
fast polynomial factorization and modular composition in small characteristic. we obtain randomized algorithms for factoring degree n univariate polynomials over f_q that use o(n1.5 + o(1) + n1 + o(1)log q) field operations, when the characteristic is at most no(1). when log q the improvements come from a new algorithm for modular composition of degree n univariate polynomials, which is the asymptotic bottleneck in fast algorithms for factoring polynomials over finite fields. the best previous algorithms for modular composition use o(n(omega + 1)/2) field operations, where omega is the exponent of matrix multiplication (brent & kung (1978)), with a slight improvement in the exponent achieved by employing fast rectangular matrix multiplication (huang & pan (1997)). we show that modular composition and multipoint evaluation of multivariate polynomials are essentially equivalent in the sense that an algorithm for one achieving exponent α implies an algorithm for the other with exponent α + o(1), and vice versa. we then give a new algorithm that requires o(n1 + o(1)) field operations when the characteristic is at most no(1), which is optimal up to lower order terms. our algorithms do not rely on fast matrix multiplication, in contrast to all previous subquadratic algorithms for these problems. the main operations are fast univariate polynomial arithmetic, multipoint evaluation, and interpolation, and consequently the algorithms could be feasible in practice.
pricing combinatorial markets for tournaments. in a prediction market, agents trade assets whose value is tied to a future event, for example the outcome of the next presidential election. asset prices determine a probability distribution over the set of possible outcomes. typically, the outcome space is small, allowing agents to directly trade in each outcome, and allowing a market maker to explicitly update asset prices. combinatorial markets, in contrast, work to estimate a full joint distribution of dependent observations, in which case the outcome space grows exponentially. in this paper, we consider the problem of pricing combinatorial markets for single-elimination tournaments. with $n$ competing teams, the outcome space is of size 2n-1. we show that the general pricing problem for tournaments is p-hard. we derive a polynomial-time algorithm for a restricted betting language based on a bayesian network representation of the probability distribution. the language is fairly natural in the context of tournaments, allowing for example bets of the form "team i wins game k". we believe that our betting language is the first for combinatorial market makers that is both useful and tractable. we briefly discuss a heuristic approximation technique for the general case.
sketching in adversarial environments. we formalize a realistic model for computations over massive data sets. the model, referred to as the {\em adversarial sketch model}, unifies the well-studied sketch and data stream models together with a cryptographic flavor that considers the execution of protocols in "hostile environments", and provides a framework for studying the complexity of many tasks involving massive data sets. the adversarial sketch model consists of several participating parties: honest parties, whose goal is to compute a pre-determined function of their inputs, and an adversarial party. computation in this model proceeds in two phases. in the first phase, the adversarial party chooses the inputs of the honest parties. these inputs are sets of elements taken from a large universe, and provided to the honest parties in an on-line manner in the form of a sequence of insert and delete operations. once an operation from the sequence has been processed it is discarded and cannot be retrieved unless explicitly stored. during this phase the honest parties are not allowed to communicate. moreover, they do not share any secret information and any public information they share is known to the adversary in advance. in the second phase, the honest parties engage in a protocol in order to compute a pre-determined function of their inputs. in this paper we settle the complexity (up to logarithmic factors) of two fundamental problems in this model: testing whether two massive data sets are equal, and approximating the size of their symmetric difference. we construct explicit and efficient protocols with sublinear sketches of essentially optimal size, poly-logarithmic update time during the first phase, and poly-logarithmic communication and computation during the second phase. our main technical contribution is an explicit and deterministic encoding scheme that enjoys two seemingly conflicting properties: incrementality and high distance, which may be of independent interest.
graph and map isomorphism and all polyhedral embeddings in linear time. for every surface s (orientable or non-orientable), we give a linear time algorithm to test the graph isomorphism of two graphs, one of which admits an embedding of face-width at least 3 into s. this improves a previously known algorithm whose time complexity is no(g), where g is the genus of s. this is the first algorithm for which the degree of polynomial in the time complexity does not depend on g. the above result is based on two linear time algorithms, each of which solves a problem that is of independent interest. the first of these problems is the following one. let s be a fixed surface. given a graph g and an integer k ≥ 3, we want to find an embedding of g in s of face-width at least k, or conclude that such an embedding does not exist. it is known that this problem is np-hard when the surface is not fixed. moreover, if there is an embedding, the algorithm can give all embeddings of face-width at least k, up to whitney equivalence. here, the face-width of an embedded graph g is the minimum number of points of g in which some non-contractible closed curve in the surface intersects the graph. in the proof of the above algorithm, we give a simpler proof and a better bound for the theorem by mohar and robertson concerning the number of polyhedral embeddings of 3-connected graphs. the second ingredient is a linear time algorithm for map isomorphism and whitney equivalence. this part generalizes the seminal result of hopcroft and wong that graph isomorphism can be decided in linear time for planar graphs.
interdomain routing and games. we present a game-theoretic model that captures many of the intricacies of interdomain routing in today's internet. in this model, the strategic agents are source nodes located on a network, who aim to send traffic to a unique destination node. the interaction between the agents is dynamic and complex -- asynchronous, sequential, and based on partial information. best-reply dynamics in this model capture crucial aspects of the interdomain routing protocol de facto, namely the border gateway protocol (bgp). we study complexity and incentive-related issues in this model. our main results are showing that in realistic and well-studied settings, bgp is incentive-compatible. i.e., not only does myopic behaviour of all players converge to a "stable" routing outcome, but no player has motivation to unilaterally deviate from the protocol. moreover, we show that even coalitions of players of any size cannot improve their routing outcomes by collaborating. unlike the vast majority of works in mechanism design, our results do not require any monetary transfers (to or by the agents).
optimal approximation for the submodular welfare problem in the value oracle model. in the submodular welfare problem, m items are to be distributed among n players with utility functions wi: 2[m] → r+. the utility functions are assumed to be monotone and submodular. assuming that player i receives a set of items si, we wish to maximize the total utility ∑i=1n wi(si). in this paper, we work in the value oracle model where the only access to the utility functions is through a black box returning wi(s) for a given set s. submodular welfare is in fact a special case of the more general problem of submodular maximization subject to a matroid constraint: max{f(s): s ∈ i}, where f is monotone submodular and i is the collection of independent sets in some matroid. for both problems, a greedy algorithm is known to yield a 1/2-approximation [21, 16]. in special cases where the matroid is uniform (i = s: |s| ≤ k) [20] or the submodular function is of a special type [4, 2], a (1-1/e)-approximation has been achieved and this is optimal for these problems in the value oracle model [22, 6, 15]. a (1-1/e)-approximation for the general submodular welfare problem has been known only in a stronger demand oracle model [4], where in fact 1-1/e can be improved [9]. in this paper, we develop a randomized continuous greedy algorithm which achieves a (1-1/e)-approximation for the submodular welfare problem in the value oracle model. we also show that the special case of n equal players is approximation resistant, in the sense that the optimal (1-1/e)-approximation is achieved by a uniformly random solution. using the pipage rounding technique [1, 2], we obtain a (1-1/e)-approximation for submodular maximization subject to any matroid constraint. the continuous greedy algorithm has a potential of wider applicability, which we demonstrate on the examples of the generalized assignment problem and the adwords assignment problem.
delegating computation: interactive proofs for muggles. in this work we study interactive proofs for tractable languages. the (honest) prover should be efficient and run in polynomial time, or in other words a "muggle". the verifier should be super-efficient and run in nearly-linear time. these proof systems can be used for delegating computation: a server can run a computation for a client and interactively prove the correctness of the result. the client can verify the result's correctness in nearly-linear time (instead of running the entire computation itself). previously, related questions were considered in the holographic proof setting by babai, fortnow, levin and szegedy, in the argument setting under computational assumptions by kilian, and in the random oracle model by micali. our focus, however, is on the original interactive proof model where no assumptions are made on the computational power or adaptiveness of dishonest provers. our main technical theorem gives a public coin interactive proof for any language computable by a log-space uniform boolean circuit with depth d and input length n. the verifier runs in time (n+d) • polylog(n) and space o(log(n)), the communication complexity is d • polylog(n), and the prover runs in time poly(n). in particular, for languages computable by log-space uniform nc (circuits of polylog(n) depth), the prover is efficient, the verifier runs in time n • polylog(n) and space o(log(n)), and the communication complexity is polylog(n). using this theorem we make progress on several questions: we show how to construct short (polylog size) computationally sound non-interactive certificates of correctness for any log-space uniform nc computation, in the public-key model. the certificates can be verified in quasi-linear time and are for a designated verifier: each certificate is tailored to the verifier's public key. this result uses a recent transformation of kalai and raz from public-coin interactive proofs to one-round arguments. the soundness of the certificates is based on the existence of a pir scheme with polylog communication. interactive proofs with public-coin, log-space, poly-time verifiers for all of p. this settles an open question regarding the expressive power of proof systems with such verifiers. zero-knowledge interactive proofs with communication complexity that is quasi-linear in the witness, length for any np language verifiable in nc, based on the existence of one-way functions. probabilistically checkable arguments (a model due to kalai and raz) of size polynomial in the witness length (rather than the instance length) for any np language verifiable in nc, under computational assumptions.
fast integer multiplication using modular arithmetic. we give an o(n • log n • 2o(log*n)) algorithm for multiplying two n-bit integers that improves the o(n • log n • log log n) algorithm by schönhage-strassen. both these algorithms use modular arithmetic. recently, fürer gave an o(n • log n • 2o(log*n)) algorithm which however uses arithmetic over complex numbers as opposed to modular arithmetic. in this paper, we use multivariate polynomial multiplication along with ideas from fürer's algorithm to achieve this improvement in the modular setting. our algorithm can also be viewed as a p-adic version of fürer's algorithm. thus, we show that the two seemingly different approaches to integer multiplication, modular and complex arithmetic, are similar.
algebrization: a new barrier in complexity theory. any proof of p!=np will have to overcome two barriers: relativization and natural proofs. yet over the last decade, we have seen circuit lower bounds (for example, that pp does not have linear-size circuits) that overcome both barriers simultaneously. so the question arises of whether there is a third barrier to progress on the central questions in complexity theory. in this paper we present such a barrier, which we call algebraic relativization or algebrization. the idea is that, when we relativize some complexity class inclusion, we should give the simulating machine access not only to an oracle a, but also to a low-degree extension of a over a finite field or ring. we systematically go through basic results and open problems in complexity theory to delineate the power of the new algebrization barrier. first, we show that all known non-relativizing results based on arithmetization -- both inclusions such as ip=pspace and mip=nexp, and separations such as maexp not in p/poly -- do indeed algebrize. second, we show that almost all of the major open problems -- including p versus np, p versus rp, and nexp versus p/poly -- will require non-algebrizing techniques. in some cases algebrization seems to explain exactly why progress stopped where it did: for example, why we have superlinear circuit lower bounds for promisema but not for np. our second set of results follows from lower bounds in a new model of algebraic query complexity, which we introduce in this paper and which is interesting in its own right. some of our lower bounds use direct combinatorial and algebraic arguments, while others stem from a surprising connection between our model and communication complexity. using this connection, we are also able to give an ma-protocol for the inner product function with o(sqrt(n) log n) communication (essentially matching a lower bound of klauck).
computing how we became human. with our ability to sequence entire genomes, we have for the first time the opportunity to compare the genomes of present day species, and deduce the trajectories by which they diversified from a common ancestral genome. for example, starting with a small shrew-like ancestor in the cretaceous period about 100 million years ago, the different species of placental mammals radiated outward, creating a stunning diversity of forms from whales to armadillos to humans. from the genomes of present-day species, it is possible to computationally reconstruct what most of the dna bases in the genome of the common ancestor of placental mammals must have looked like, and deduce most of the changes that lead to humans. in so doing, we discover how darwinian evolution has shaped us at the molecular level. because most random mutations to functionally important regions of dna reduce fitness, these changes usually disappear over time, in a process known as negative selection. from its unusually high conservation between species, it is immediately evident that at least 5% of the human genome has been under negative selection during most of mammalian evolution, and is hence likely to be functionally important. protein-coding genes and structural rna genes stand out among the negatively selected regions because of their distinctive pattern of restricted dna base substitutions, insertions and deletions. however, most of the dna under negative selection in mammalian genomes, and indeed in vertebrate genomes in general, does not appear to be part of protein-coding or structural rna genes, and shares no sequence similarity with any dna in the genomes of invertebrates. experimental evidence suggests that many of these unclassified vertebrate-conserved dna elements serve to regulate genes involved in embryonic development. a significant amount of this material appears to have been put into place by the movement of transposons, mobile dna elements that are derived from ancient viruses, the remnants of which constitute at least half of our genome. this provides new evidence for older theories of mcclintock and later britten and davidson that mobile dna elements played a significant role in the evolution of plant and animal gene regulatory networks. overlaid on the background of negative selection, we occasionally see a short segment of dna that has changed rapidly in a particular lineage, suggesting possible positive selection for a modified function in that lineage. the most dramatic example of this in the last 5 million years of human evolution occurs in a previously unstudied rna gene expressed in the developing cerebral cortex, known as human accelerated region 1 (har1). this gene is turned on only in a select set of neurons, during the time in fetal development when these neurons orchestrate the formation of the substantially larger cortex of the human brain. it will be many years before the biology of such examples is fully understood, but right now we relish the opportunity to get a first peek at the molecular tinkering that transmuted our animal ancestors into humans.
graphs, polymorphisms and the complexity of homomorphism problems. we use a connection between polymorphisms and the structure of smooth digraphs to prove the conjecture of bang-jensen and hell from 1990 and, as a consequence, a conjecture of bang-jensen, hell and macgillivray from 1995. the conjectured characterization of computationally complex coloring problems for smooth digraphs is proved using tools of universal algebra. we cite further graph results obtained using this new approach. the proofs are based in an universal algebraic framework developed for the constraint satisfaction problem and the csp dichotomy conjecture of feder and vardi in particular.
span-program-based quantum algorithm for evaluating formulas. we give a quantum algorithm for evaluating formulas over an extended gate set, including all two- and three-bit binary gates (e.g., nand, 3-majority). the algorithm is optimal on read-once formulas for which each gate's inputs are balanced in a certain sense. the main new tool is a correspondence between a classical linear-algebraic model of computation, "span programs," and weighted bipartite graphs. a span program's evaluation corresponds to an eigenvalue-zero eigenvector of the associated graph. a quantum computer can therefore evaluate the span program by applying spectral estimation to the graph. for example, the classical complexity of evaluating the balanced ternary majority formula is unknown, and the natural generalization of randomized alpha-beta pruning is known to be suboptimal. in contrast, our algorithm generalizes the optimal quantum and-or formula evaluation algorithm and is optimal for evaluating the balanced ternary majority formula.
optimal query complexity bounds for finding graphs. we consider the problem of finding an unknown graph by using two types of queries with an additive property. given a graph, an additive query asks the number of edges in a set of vertices while a cross-additive query asks the number of edges crossing between two disjoint sets of vertices. the queries ask sum of weights for the weighted graphs. these types of queries were partially motivated in dna shotgun sequencing and linkage discovery problem of artificial intelligence. for a given unknown weighted graph g with n vertices, m edges, and a certain mild condition on weights, we prove that there exists a non-adaptive algorithm to find the edges of g using o(m log n / log m) queries of both types provided that m ≥ nε for any constant ε > 0. for an unweighted graph, it is shown that the same bound holds for all range of m. this settles a conjecture of grebinski [23] for finding an unweighted graph using additive queries. we also consider the problem of finding the fourier coefficients of a certain class of pseudo-boolean functions. a similar coin weighing problem is also considered.
some topics in analysis of boolean functions. this article accompanies a tutorial talk given at the 40th acm stoc conference. in it, we give a brief introduction to fourier analysis of boolean functions and then discuss some applications: arrow's theorem and other ideas from the theory of social choice; the bonami-beckner inequality as an extension of chernoff/hoeffding bounds to higher-degree polynomials; and, hardness for approximation algorithms.
list-decoding reed-muller codes over small fields. we present the first local list-decoding algorithm for the rth order reed-muller code rm(2,m) over f for r ≥ 2. given an oracle for a received word r: fm --r - ε) from r for any ε r,ε-r). the list size could be exponential in m at radius 2-r, so our bound is optimal in the local setting. since rm(2,m) has relative distance 2-r, our algorithm beats the johnson bound for r ≥ 2. in the setting where we are allowed running-time polynomial in the block-length, we show that list-decoding is possible up to even larger radii, beyond the minimum distance. we give a deterministic list-decoder that works at error rate below j(21-r), where j(δ) denotes the johnson radius for minimum distance δ. this shows that rm(2,m) codes are list-decodable up to radius η for any constant η q, we present list-decoding algorithms in both the global and local settings that work up to the list-decoding radius. we conjecture that the list-decoding radius approaches the minimum distance (like over f), and prove this holds true when the degree is divisible by q-1.
combinatorial construction of locally testable codes. an error correcting code is said to be locally testable if there is a test that checks whether a given string is a codeword, or rather far from the code, by reading only a constant number of symbols of the string. locally testable codes (ltcs) were first systematically studied by goldreich and sudan (j. acm 53(4)) and since then several constructions of ltcs have been suggested. while the best known construction of ltcs by ben-sasson and sudan (stoc 2005) and dinur (j. acm 54(3)) achieves very efficient parameters, it relies heavily on algebraic tools and on pcp machinery. in this work we present a new and arguably simpler construction of ltcs that is purely combinatorial, does not rely on pcp machinery and matches the parameters of the best known construction. however, unlike the latter construction, our construction is not entirely explicit.
algorithms for subset selection in linear regression. we study the problem of selecting a subset of k random variables to observe that will yield the best linear prediction of another variable of interest, given the pairwise correlations between the observation variables and the predictor variable. under approximation preserving reductions, this problem is equivalent to the "sparse approximation" problem of approximating signals concisely. the subset selection problem is np-hard in general; in this paper, we propose and analyze exact and approximation algorithms for several special cases of practical interest. specifically, we give an fptas when the covariance matrix has constant bandwidth, and exact algorithms when the associated covariance graph, consisting of edges for pairs of variables with non-zero correlation, forms a tree or has a large (known) independent set. furthermore, we give an exact algorithm when the variables can be embedded into a line such that the covariance decreases exponentially in the distance, and a constant-factor approximation when the variables have no "conditional suppressor variables". much of our reasoning is based on perturbation results for the r2 multiple correlation measure, which is frequently used as a natural measure for "goodness-of-fit statistics". it lies at the core of our fptas, and also allows us to extend our exact algorithms to approximation algorithms when the matrix "nearly" falls into one of the above classes. we also use our perturbation analysis to prove approximation guarantees for the widely used "forward regression" heuristic under the assumption that the observation variables are nearly independent.
elusive functions and lower bounds for arithmetic circuits. a basic fact in linear algebra is that the image of the curve f(x)=(x1,x2,x3,...,xm), say over c, is not contained in any m-1 dimensional affine subspace of cm. in other words, the image of f is not contained in the image of any polynomial-mapping γ:cm-1 → cm of degree~1 (that is, an affine mapping). can one give an explicit example for a polynomial curve f:c → cm, such that, the image of f is not contained in the image of any polynomial-mapping γ:cm-1 → cm of degree 2? in this paper, we show that problems of this type are closely related to proving lower bounds for the size of general arithmetic circuits. for example, any explicit f as above (with the right notion of explicitness implies super-polynomial lower bounds for computing the permanent over~c. more generally, we say that a polynomial-mapping f:fn → fm is (s,r)-elusive, if for every polynomial-mapping γ:fs → fm of degree r, im(f) ⊄ im(γ). we show that for many settings of the parameters n,m,s,r, explicit constructions of elusive polynomial-mappings imply strong (up to exponential) lower bounds for general arithmetic circuits. finally, for every r n → fn2, of degree o(r), that is (s,r)-elusive for s = n1+ω(1/r). we use this to construct for any r, an explicit example for an n-variate polynomial of total-degree o(r), with coefficients in {0,1,}such that, any depth r arithmetic circuit for this polynomial (over any field) is of size ≥ n1+ω(1/r). in particular, for any constant r, this gives a constant degree polynomial, such that, any depth r arithmetic circuit for this polynomial is of size ≥ n1+ω(1). previously, only lower bounds of the type ω(n • λr (n)), where λr (n) are extremely slowly growing functions (e.g., λ5(n) = log n, and λ7(n) = log* log*n), were known for constant-depth arithmetic circuits for polynomials of constant degree.
testing symmetric properties of distributions. we introduce the notion of a canonical tester for a class of properties on distributions, that is, a tester strong and general enough that "a distribution property in the class is testable if and only if the canonical tester tests it". we construct a canonical tester for the class of symmetric properties of one or two distributions, satisfying a certain weak continuity condition. analyzing the performance of the canonical tester on specific properties resolves several open problems, establishing lower bounds that match known upper bounds: we show that distinguishing between entropy α/β- o(1) samples, and distinguishing whether a pair of distributions has statistical distance 1-o(1) samples. our techniques also resolve a conjecture about a property that our canonical tester does not apply to: distinguishing identical distributions from those with statistical distance >β requires ω(n2/3) samples.
additive approximation for bounded degree survivable network design. we study a general network design problem with additional degree constraints. given connectivity requirements ruv for all pairs of vertices, a steiner network is a graph in which there are at least ruv edge-disjoint paths between u and v for all pairs of vertices u,v. in the minimum bounded-degree steiner network problem, we are given an undirected graph g with an edge cost for each edge, a connectivity requirement ruv for each pair of vertices u and v, and a degree upper bound for each vertex v. the task is to find a minimum cost steiner network which satisfies all the degree upper bounds. the aim of this paper is to design approximation algorithms that minimize the total cost and the degree violation simultaneously. our main results are the following: there is a polynomial time algorithm which returns a steiner forest of cost at most 2 opt and the degree violation at each vertex is at most 3 ,where opt is the cost of an optimal solution which satisfies all the degree bounds. there is a polynomial time algorithm which returns a steiner network of cost at most 2 opt and the degree violation at each vertex is at most 6r max +3 ,where opt is the cost of an optimal solution which satisfies all the degree bounds, and r max := max u,v {r uv}. these results achieve the best known guarantees for both the total cost and the degree violation simultaneously. as corollaries, these results provide the first additive approximation algorithms for finding low degree subgraphs including steiner forests, k -edge-connected subgraphs, and steiner networks. the algorithms develop on the iterative relaxation method applied to a natural linear programming relaxation as in [10, 16, 22]. the new algorithms avoid paying a multiplicative factor of two on the degree bounds even though the algorithm can only pick edges with fractional value 1/2 . this is based on a stronger characterization of the basic so-algorithm is nearly tight.
regret minimization and the price of total anarchy. we propose weakening the assumption made when studying the price of anarchy: rather than assume that self-interested players will play according to a nash equilibrium (which may even be computationally hard to find), we assume only that selfish players play so as to minimize their own regret. regret minimization can be done via simple, efficient algorithms even in many settings where the number of action choices for each player is exponential in the natural parameters of the problem. we prove that despite our weakened assumptions, in several broad classes of games, this "price of total anarchy" matches the nash price of anarchy, even though play may never converge to nash equilibrium. in contrast to the price of anarchy and the recently introduced price of sinking, which require all players to behave in a prescribed manner, we show that the price of total anarchy is in many cases resilient to the presence of byzantine players, about whom we make no assumptions. finally, because the price of total anarchy is an upper bound on the price of anarchy even in mixed strategies, for some games our results yield as corollaries previously unknown bounds on the price of anarchy in mixed strategies.
on hardness of learning intersection of two halfspaces. we show that unless np = rp, it is hard to (even) weakly pac-learn intersection of two halfspaces in rn using a hypothesis which is a function of up to l linear threshold functions for any integer l. specifically, we show that for every integer l and an arbitrarily small constant ε > 0, unless np = rp, no polynomial time algorithm can distinguish whether there is an intersection of two halfspaces that correctly classifies a given set of labeled points in rn, or whether any function of l linear threshold functions can correctly classify at most 1/2+ε fraction of the points.
direct product theorems for classical communication complexity via subdistribution bounds: extended abstract. a basic question in complexity theory is whether the computational resources required for solving k independent instances of the same problem scale as k times the resources required for one instance. we investigate this question in various models of classical communication complexity. we introduce a new measure, the subdistribution bound , which is a relaxation of the well-studied rectangle or corruption bound in communication complexity. we nonetheless show that for the communication complexity of boolean functions with constant error, the subdistribution bound is the same as the latter measure, up to a constant factor. we prove that the one-way version of this bound tightly captures the one-way public-coin randomized communication complexity of any relation, and the two-way version bounds the two-way public-coin randomized communication complexity from below. more importantly, we show that the bound satisfies the strong direct product property under product distributions for both one- and two-way protocols, and the weak direct product property under arbitrary distributions for two-way protocols. these results subsume and strengthen, in a unified manner, several recent results on the direct product question. the simplicity and broad applicability of our technique is perhaps an indication of its potential to solve yet more challenging questions regarding the direct product problem.
games for exchanging information. we consider the rational versions of two of the classical problems in foundations of cryptography: secret sharing and multiparty computation, suggested by halpern and teague (stoc 2004). our goal is to design games and fair strategies that encourage rational participants to exchange information about their inputs for their mutual benefit, when the only mean of communication is a broadcast channel. we show that protocols for the above information exchanging tasks, where players' values come from a bounded domain, cannot satisfy some of the most desirable properties. in contrast, we provide a rational secret sharing scheme with simultaneous broadcast channel in which shares are taken from an unbounded domain, but have finite (and polynomial sized) expectation. previous schemes (mostly cryptographic) have required computational assumptions, making them inexact and susceptible to backward induction, or used stronger communication channels. our scheme is non-cryptographic, immune to backward induction, and satisfies a stronger rationality concept (strict nash equilibrium). we show that our solution can also be used to construct an ε-nash equilibrium secret sharing scheme for the case of a non-simultaneous broadcast channel.
an o(log k)-approximation algorithm for the k-vertex connected spanning subgraph problem. we present an o(log n• log k)-approximation algorithm for the problem of finding k-vertex connected spanning subgraph of minimum cost, where n is the number of vertices in the input graph, and k is the connectivity requirement. our algorithm works for both directed and undirected graphs. the best known approximation guarantees for these problems are o(ln k• min{√k,n/n-k ln k}) by kortsarz and nutov, and o(ln{k}) in the case of undirected graphs where n≥ 6k2 by cheriyan, vempala, and vetta. our algorithm is the first that has a polylogarithmic guarantee for all values of k. combining our algorithm with the algorithm of kortsarz and nutov in case of small k, e.g., k2 k)-approximation algorithm. as in previous work, we use the frank-tardos algorithm for finding k-outconnected subgraphs as a subroutine. however, with a structural lemmas that we proved, we are able to show that we need only partial solutions returned by the frank-tardos algorithm; thus, we can avoid paying the whole cost of the optimal solution every time the algorithm is applied.
randomized competitive algorithms for generalized caching. we consider online algorithms for the generalized caching problem. here we are given a cache of size k and pages with arbitrary sizes and fetching costs. given a request sequence of pages, the goal is to minimize the total cost of fetching the pages into the cache. we give an online algorithm with competitive ratio o(log2k), which is the first algorithm for the problem with competitive ratio sublinear in k. we also give improved o(log k)-competitive algorithms for the special cases of the bit model and fault model. in the bit model, the fetching cost is proportional to the size of the page and in the fault model all fetching costs are uniform. previously, an o(log2 k)-competitive algorithm due to irani [14] was known for both of these models. our algorithms are based on an extension of the primal-dual framework for online algorithms which was developed by buchbinder and naor [7]. we first generate an o(log k)-competitive fractional algorithm for the problem. this is done by using a strengthened lp formulation with knapsack-cover constraints, where exponentially many constraints are added upon arrival of a new request. second, we round online the fractional solution and obtain a randomized online algorithm. our techniques provide a unified framework for caching algorithms and are substantially simpler than those previously used.
improved approximation for directed cut problems. we present improved approximation algorithms for directed multicutand directed sparsest cut. the current best known approximationratio for these problems is o(n1/2). we obtain an õ(n11/23)-approximation. our algorithm works with thenatural lp relaxation used in prior work. we use a randomized roundingalgorithm with a more sophisticated charging scheme and analysis toobtain our improvement. this also implies a õ(n11/23) upper bound on the ratio between the maximum multicommodity flowand minimum multicut in directed graphs.
on agnostic boosting and parity learning. the motivating problem is agnostically learning parity functions, i.e., parity with arbitrary or adversarial noise. specifically, given random labeled examples from an *arbitrary* distribution, we would like to produce an hypothesis whose accuracy nearly matches the accuracy of the best parity function. our algorithm runs in time 2o(n/log n), which matches the best known for the easier cases of learning parities with random classification noise (blum et al, 2003) and for agnostically learning parities over the uniform distribution on inputs (feldman et al, 2006). our approach is as follows. we give an agnostic boosting theorem that is capable of nearly achieving optimal accuracy, improving upon earlier studies (starting with ben david et al, 2001). to achieve this, we circumvent previous lower bounds by altering the boosting model. we then show that the (random noise) parity learning algorithm of blum et al (2000) fits our new model of agnostic weak learner. our agnostic boosting framework is completely general and may be applied to other agnostic learning problems. hence, it also sheds light on the actual difficulty of agnostic learning by showing that full agnostic boosting is indeed possible.
multi-armed bandits in metric spaces. in a multi-armed bandit problem, an online algorithm chooses from a set of strategies in a sequence of $n$ trials so as to maximize the total payoff of the chosen strategies. while the performance of bandit algorithms with a small finite strategy set is quite well understood, bandit problems with large strategy sets are still a topic of very active investigation, motivated by practical applications such as online auctions and web advertisement. the goal of such research is to identify broad and natural classes of strategy sets and payoff functions which enable the design of efficient solutions. in this work we study a very general setting for the multi-armed bandit problem in which the strategies form a metric space, and the payoff function satisfies a lipschitz condition with respect to the metric. we refer to this problem as the "lipschitz mab problem". we present a complete solution for the multi-armed problem in this setting. that is, for every metric space (l,x) we define an isometry invariant max min cov(x) which bounds from below the performance of lipschitz mab algorithms for $x$, and we present an algorithm which comes arbitrarily close to meeting this bound. furthermore, our technique gives even better results for benign payoff functions.
terminal backup, 3d matching, and covering cubic graphs. we define a problem called simplex matching, and show that it is solvable in polynomial time. while simplex matching is interesting in its own right as a nontrivial extension of non-bipartite min-cost matching, its main value lies in many(seemingly very different) problems that can be solved using ouralgorithm. for example, suppose that we are given a graph with terminal nodes, non-terminal nodes, and edge costs. then, the terminal backup problem, which consists of finding the cheapest forest connecting every terminal to at least one other terminal, is reducible to simplex matching. simplex matching is also useful for various tasks that involve forming groups of at least two members, such as project assignment and variants of facility location. in an instance of simplex matching, we are given a hypergraphh with edge costs, and edge size at most 3. we show how to find the min-cost perfect matching of h efficiently, if the edge costs obey a simple and realistic inequality that we call the simplexcondition. the algorithm we provide is relatively simple to understand and implement, but difficult to prove correct. in the process of this proof we show some powerful new results about covering cubic graphs with simple combinatorial objects.
a learning theory approach to non-interactive database privacy. we demonstrate that, ignoring computational constraints, it is possible to release privacy-preserving databases that are useful for all queries over a discretized domain from any given concept class with polynomial vc-dimension. we show a new lower bound for releasing databases that are useful for halfspace queries over a continuous domain. despite this, we give a privacy-preserving polynomial time algorithm that releases information useful for all halfspace queries, for a slightly relaxed definition of usefulness. inspired by learning theory, we introduce a new notion of data privacy, which we call distributional privacy, and show that it is strictly stronger than the prevailing privacy notion, differential privacy.
a combinatorial, primal-dual approach to semidefinite programs. semidefinite programs (sdp) have been used in many recentapproximation algorithms. we develop a general primal-dualapproach to solve sdps using a generalization ofthe well-known multiplicative weights update rule to symmetricmatrices. for a number of problems, such as sparsest cut and balanced separator in undirected and directed weighted graphs, and the min uncut problem, this yields combinatorial approximationalgorithms that are significantly more efficient than interiorpoint methods. the design of our primal-dual algorithms is guidedby a robust analysis of rounding algorithms used to obtain integersolutions from fractional ones.
tight rmr lower bounds for mutual exclusion and other problems. we investigate the remote memory references (rmrs) complexity of deterministic processes that communicate by reading and writing shared memory in asynchronous cache-coherent and distributed shared-memory multiprocessors. we define a class of algorithms that we call order encoding. by applying information-theoretic arguments, we prove that every order encoding algorithm, shared by n processes, has an execution that incurs ω(n log n) rmrs. from this we derive the same lower bound for the mutual exclusion, bounded counter and store/collect synchronization problems. the bounds we obtain for these problems are tight. it follows from the results of [10] that our lower bounds hold also for algorithms that can use comparison primitives and load-linked/store-conditional in addition to reads and writes. our mutual exclusion lower bound proves a longstanding conjecture of anderson and kim.
balanced max 2-sat might not be the hardest. we show that, assuming the unique games conjecture, it is np-hard to approximate max2sat within αllz-+ε, where 0.9401 < αllz- < 0.9402 is the believed approximation ratio of the algorithm of lewin, livnat and zwick [28]. this result is surprising considering the fact that balanced instances of max2sat, i.e., instances where each variable occurs positively and negatively equally often, can be approximated within 0.9439. in particular, instances in which roughly 68% of the literals are unnegated variables and 32% are negated appear less amenable to approximation than instances where the ratio is 50% - 50%.
a quadratic lower bound for the permanent and determinant problem over any characteristic != 2. in valiant's theory of arithmetic complexity, the classes vp and vnp are analogs of p and np. a fundamental problem concerning these classes is the permanent and determinant problem: given a field f of characteristic ≠2, and an integer n, what is the minimum m such that the permanent of an n x n matrix x=(xij) can be expressed as a determinant of an m x m matrix, where the entries of the determinant matrix are affine linear functions of xij's, and the equality is in f [x]. mignon and ressayre (2004) [11] proved a quadratic lower bound m=ω(n2) for fields of characteristic 0. we extend the mignon-ressayre quadratic lower bound to all fields of characteristic ≠2.
lower bounds for randomized read/write stream algorithms. motivated by the capabilities of modern storage architectures, we consider the following generalization of the data stream model where the algorithm has sequential access to multiple streams. unlike the data stream model, where the stream is read only, in this new model (introduced in [8,9]) the algorithms can also write onto streams. there is no limit on the size of the streams but the number of passes made on the streams is restricted. on the other hand, the amount of internal memory used by the algorithm is scarce, similar to data stream model. we resolve the main open problem in [7] of proving lower bounds in this model for algorithms that are allowed to have 2-sided error. previously, such lower bounds were shown only for deterministic and 1-sided error randomized algorithms [9,7]. we consider the classical set disjointness problemthat has proved to be invaluable for deriving lower bounds for many other problems involving data streams and other randomized models of computation. for this problem, we show a near-linear lower bound on the size of the internal memory used by a randomized algorithm with 2-sided error that is allowed to have o(log n/log log n) passes over the streams. this bound is almost optimal sincethere is a simple algorithm that can solve this problem using logarithmic memory if the number of passes over the streams. applications include near-linear lower bounds onthe internal memory for well-known problems in the literature:(1) approximately counting the number of distinct elements in the input (f0);(2) approximating the frequency of the mod of an input sequence(f*∞);(3) computing the join of two relations; and (4) deciding if some node of an xml document matches an xquery (or xpath) query. our techniques involve a novel direct-sum type of argument that yields lower bounds for many other problems. our results asymptotically improve previously known bounds for any problem even in deterministic and 1-sided error models of computation.
optimal hierarchical decompositions for congestion minimization in networks. hierarchical graph decompositions play an important role in the design of approximation and online algorithms for graph problems. this is mainly due to the fact that the results concerning the approximation of metric spaces by tree metrics (e.g. [10,11,14,16]) depend on hierarchical graph decompositions. in this line of work a probability distribution over tree graphs is constructed from a given input graph, in such a way that the tree distances closely resemble the distances in the original graph. this allows it, to solve many problems with a distance-based cost function on trees, and then transfer the tree solution to general undirected graphs with only a logarithmic loss in the performance guarantee. the results about oblivious routing [30,22] in general undirected graphs are based on hierarchical decompositions of a different type in the sense that they are aiming to approximate the bottlenecks in the network (instead of the point-to-point distances). we call such decompositions cut-based decompositions. it has been shown that they also can be used to design approximation and online algorithms for a wide variety of different problems, but at the current state of the art the performance guarantee goes down by an o(log2n log log n)-factor when making the transition from tree networks to general graphs. in this paper we show how to construct cut-based decompositions that only result in a logarithmic loss in performance, which is asymptotically optimal. remarkably, one major ingredient of our proof is a distance-based decomposition scheme due to fakcharoenphol, rao and talwar [16]. this shows an interesting relationship between these seemingly different decomposition techniques. the main applications of the new decomposition are an optimal o(log n)-competitive algorithm for oblivious routing in general undirected graphs, and an o(log n)-approximation for minimum bisection, which improves the o(log1.5n) approximation by feige and krauthgamer [17].
read-once polynomial identity testing. in this paper we study the problems of polynomial identity testing (pit) and reconstruction of read-once formulas. the following are some deterministic algorithms that we obtain. an no(k2) algorithm for checking whether given k rofs sum to zero or not. an no(d+k2) time algorithm for checking whether a black box holding the sum of k depth d rofs computes the zero polynomial. in other words, we provide a hitting set of size no(d+k2) for the sum of k depth d rofs. this implies an no(d) deterministic algorithm for the reconstruction of depth d rofs. a hitting set of size exp(~o(√n+k2)) for the sum of k rofs (without depth restrictions). this implies a sub-exponential time deterministic algorithm for black-box identity testing and reconstructing of rofs. to the best of our knowledge our results give the first polynomial time (non black-box) and sub-exponential time (black-box) identity testing algorithms for the sum of (a constant number of) rofs. in addition, we introduce and study the read-once testing problem (rot for short): given an arithmetic circuit computing a polynomial p(x), decide whether there is a rof computing p(x). if there is such a formula then output it. otherwise output "no". we show that most previous algorithms for polynomial identity testing can be strengthen to yield algorithms for the rot problem. in particular we give rot algorithms for: depth-2 circuits (circuits computing sparse polynomials), depth-3 circuits with bounded top fan-in (both in the black-box and non black-box settings, where the running time depends on the model), non-commutative formulas and sum of k rofs. the running time of the rot algorithm is essentially the same running time as the corresponding pit algorithm for the class. the main tool in most of our results is a new connection between polynomial identity testing and reconstruction of read-once formulas. namely, we show that in any model that is closed under partial derivatives (that is, a partial derivative of a polynomial computed by a circuit in the model, can also be computed by a circuit in the model) and that has an efficient deterministic polynomial identity testing algorithm, we can also answer the read-once testing problem.
constructing non-computable julia sets. while most polynomial julia sets are computable, it has been recently shown [12] that there exist non-computable julia sets. the proof was non-constructive, and indeed there were doubts as to whether specific examples of parameters with non-computable julia sets could be constructed. it was also unknown whether the non-computability proof can be extended to the filled julia sets. in this paper we give an answer to both of these questions, which were the main open problems concerning the computability of polynomial julia sets. we show how to construct a specific polynomial with a non-computable julia set. in fact, in the case of julia sets of quadratic polynomials we give a precise characterization of juliasets with computable parameters. moreover, assuming a widely believed conjecture in complex dynamics, we give a poly-time algorithm forcomputing a number c such that the julia set jz2+c z is non-computable. in contrast with these results, we show that the filled julia set of a polynomial is always computable.
the complexity of temporal constraint satisfaction problems. a temporal constraint language is a set of relations that has a first-order definition in (b q,
holographic algorithms: from art to science. we develop the theory of holographic algorithms. we definea basis manifold and give characterizations of algebraic varieties of realizable symmetric generators and recognizers on this manifold. we present a polynomial time decision algorithm for the simultaneous realizability problem. using the general machinery we are able to giveunexpected holographic algorithms for some counting problems, modulo certain mersenne type integers. these counting problems are p-complete without the moduli. going beyond symmetric signatures, we define d-admissibility and d-realizability for general signatures, and give a characterizationof 2-admissibility.
randomized k-server on hierarchical binary trees. we design a randomized online algorithm for k-server on binary trees with hierarchical edge lengths, with expected competitive ratio o(log delta), where delta is the diameter of the metric. this is one of the first k-server algorithms with competitive ratio poly-logarithmic in the natural problem parameters, and represents substantial progress on the randomized k-server conjecture. extending the algorithm to trees of higher degree would give a competitive ratio of o(log2 delta log n) for the k-server problem on general metrics with n points and diameter delta.
a fixed-parameter algorithm for the directed feedback vertex set problem. the (parameterized) feedback vertex set problem on directed graphs, which we refer to as the dfvs problem, is defined as follows: given a directed graph g and a parameter k, either construct a feedback vertex set of at most k vertices in g or report that no such set exists. whether or not the dfvs problem is fixed-parameter tractable has been a well-known open problem in parameterized computation and complexity, i.e., whether the problem can be solved in time f(k)no(1) for some function f. in this paper we develop new algorithmic techniques that result in an algorithm with running time 4k k! no(1) for the dfvs problem, thus showing that this problem is fixed-parameter tractable.
polynomial flow-cut gaps and hardness of directed cut problems. we study the multicut and the sparsest cut problems in directed graphs. in the multicut problem, we are a given an n-vertex graph g along with k source-sink pairs, and the goal is to find the minimum cardinality subset of edges whose removal separates all source-sink pairs. the sparsest cut problem has the same input, but the goal is to find a subset of edges to delete so as to minimize the ratio of the number of deleted edges to the number of source-sink pairs that are separated by this deletion. the natural linear programming relaxation for multicut corresponds, by lp-duality, to the well-studied maximum (fractional) multicommodity flow problem, while the standard lp-relaxation for sparsest cut corresponds to maximum concurrent flow. therefore, the integrality gap of the linear programming relaxation for multicut/sparsest cut is also the flow-cut gap: the largest gap, achievable for any graph, between the maximum flow value and the minimum cost solution for the corresponding cut problem. our first result is that the flow-cut gap between maximum multicommodity flow and minimum multicut is &omega;&tilde;(n1/7) in directed graphs. we show a similar result for the gap between maximum concurrent flow and sparsest cut in directed graphs. these results improve upon a long-standing lower bound of &omega;(log n) for both types of flow-cut gaps. we notice that these polynomially large flow-cut gaps are in a sharp contrast to the undirected setting where both these flow-cut gaps are known to be &theta;(log n). our second result is that both directed multicut and sparsest cut are hard to approximate to within a factor of 2&omega;(log1&minus;&epsis; n) for any constant &epsis; > 0, unless np &sube; zpp. this improves upon the recent &omega;(log n/log log n)-hardness result for these problems. we also show that existence of pcp's for np with perfect completeness, polynomially small soundness, and constant number of queries would imply a polynomial factor hardness of approximation for both these problems. all our results hold for directed acyclic graphs.
stability of the max-weight routing and scheduling protocol in dynamic networks and at critical loads. we study the stability of the max-weight protocol for combined routingand scheduling in communication networks. previous work has shownthat this protocol is stable for adversarial multicommodity trafficin subcritically loaded static networks and for single-commoditytraffic in critically loaded dynamic networks. we show: the max-weight protocol is stable for adversarial multicommodity traffic in adversarial dynamic networks whenever the network is subcriticallyloaded. the max-weight protocol is stable for fixed multicommodity trafficin fixed networks even if the network is critically loaded. the latter result has implications for the running time of themax-weight protocol when it is used to solve multicommodity flowproblems. in particular, for a fixed problem instance we show thatif the value of the optimum solution is known, the max-weight protocolfinds a flow that is within a (1-ε)-factor of optimal in time o(1/ε) (improving the previous bound of o(1/ε2)). if thevalue of the optimum solution is not known, we show how to apply themax-weight algorithm in a binary search procedure that runs in o(1/ε) time.
random projection trees and low dimensional manifolds. we present a simple variant of the k-d tree which automatically adapts to intrinsic low dimensional structure in data without having to explicitly learn this structure.
minimum k-way cuts via deterministic greedy tree packing. we present a simple and fast deterministic algorithm for the minimum k-way cut problem in a capacitated graph, that is, finding a set of edges with minimum total capacity whose removal splits the graph into at least k components. the algorithm packs o(mk3 log n) trees. each new tree is a minimal spanning tree with respect to the edge utilizations, and the utilization of an edge is the number of times it has been used in previous spanning trees divided by its capacity. we prove that each minimum k-way cut is crossed at most 2k-2 times by one of the trees. we can enumerate all such cuts in ~o(n2k) time, which is hence the running time of our algorithm producing all minimum k-way cuts. the previous fastest deterministic algorithm of kamidoi et al. [sicomp'06] took o(n(4+o(1))k) time, so this is a near-quadratic improvement. moreover, we essentially match the o(n(2-o(1))k) running time of the monto carlo (no correctness guarantee) randomized algorithm of karger and stein [jacm'96].
classical interaction cannot replace a quantum message. we demonstrate a two-player communication problem that can be solved in the one-way quantum model by a 0-error protocol of cost o(log n) but requires exponentially more communication in the classical interactive (bounded error) model.
iteratively constructing preconditioners via the conjugate gradient method. we consider the problem of solving a symmetric, positive definite system of linear equations.the most well-known and widely-used method for solving such systemsis the preconditioned conjugate gradient method.the performance of this method depends crucially on knowing a good preconditioner matrix.we show that the conjugate gradient method itself canproduce good preconditioners as a by-product. these preconditioners allow us to derive new asymptotic bounds on the timeto solve multiple related linear systems.
the price of privacy and the limits of lp decoding. this work is at theintersection of two lines of research. one line, initiated by dinurand nissim, investigates the price, in accuracy, of protecting privacy in a statistical database. the second, growing from an extensive literature on compressed sensing (see in particular the work of donoho and collaborators [4,7,13,11])and explicitly connected to error-correcting codes by candès and tao ([4]; see also [5,3]), is in the use of linearprogramming for error correction. our principal result is the discovery of a sharp threshhold ρ*∠ 0.239, so that if ρ < ρ* and a is a random m x n encoding matrix of independently chosen standardgaussians, where m = o(n), then with overwhelming probability overchoice of a, for all x ∈ rn, lp decoding corrects ⌊ ρ m⌋ arbitrary errors in the encoding ax, while decoding can be made to fail if the error rate exceeds ρ*. our boundresolves an open question of candès, rudelson, tao, and vershyin [3] and (oddly, but explicably) refutesempirical conclusions of donoho [11] and candès et al [3]. by scaling and rounding we can easilytransform these results to obtain polynomial-time decodable random linear codes with polynomial-sized alphabets tolerating any ρ < ρ* ∠ 0.239 fraction of arbitrary errors. in the context of privacy-preserving datamining our results say thatany privacy mechanism, interactive or non-interactive, providingreasonably accurate answers to a 0.761 fraction of randomly generated weighted subset sum queries, and arbitrary answers on the remaining 0.239 fraction, is blatantly non-private.
reordering buffers for general metric spaces. in the reordering buffer problem, we are given an input sequence of requests for service each of which corresponds to a point in a metric space. the cost of serving the requests heavily depends on the processing order. serving a request induces cost corresponding to the distance between itself and the previously served request, measured in the underlying metric space. a reordering buffer with storage capacity k can be used to reorder the input sequence in a restricted fashion so as to construct an output sequence with lower service cost. this simple and universal framework is useful for many applications in computer science and economics, e.g., disk scheduling, rendering in computer graphics, or painting shops in car plants. in this paper, we design online algorithms for the reordering buffer problem. our main result is a strategy with a polylogarithmic competitive ratio for general metric spaces. previous work on the reordering buffer problem only considered very restricted metric spaces. we obtain our result by first developing a deterministic algorithm for arbitrary weighted trees with a competitive ratio of o(d · log k), where d denotes the unweighted diameter of the tree, i.e., the maximum number of edges on a path connecting two nodes. then we show how to improve this competitive ratio to o(log2 k) for metric spaces that are derived from hsts. combining this result with the results on probabilistically approximating arbitrary metrics by tree metrics, we obtain a randomized strategy for general metric spaces that achieves a competitive ratio of o(log2 k · log n) in expectation against an oblivious adversary. here n denotes the number of distinct points in the metric space. note that the length of the input sequence can be much larger than n.
optimal suffix selection. given a string s[1·s n], the suffix selection problemis to find the kth lexicographically smallest amongst the n suffixes s[i·s n], for i=1,...,n. in particular, the fundamental question is if selection can be performed more efficiently than sorting all the suffixes. if one considered n numbers, they can be sorted using θ(n log n) comparisonsand the classical result from 70's is that selection can be done using o(n) comparisons. thus selection is provably more efficient than sorting, for n numbers. suffix sorting can be done using θ(n log n) comparisons, but does suffix selection need suffix sorting? we settle this fundamental problem by presenting an optimal, deterministic algorithm for suffix selection using o(n) comparisons.
faster integer multiplication. for more than 35 years, the fastest known method for integer multiplication has been the sch&ouml;nhage-strassen algorithm running in time $o(n\log n\log\log n)$. under certain restrictive conditions, there is a corresponding $\omega(n\log n)$ lower bound. all this time, the prevailing conjecture has been that the complexity of an optimal integer multiplication algorithm is $\theta(n\log n)$. we take a major step towards closing the gap between the upper bound and the conjectured lower bound by presenting an algorithm running in time $n\log n\,2^{o(\log^*n)}$. the running time bound holds for multitape turing machines. the same bound is valid for the size of boolean circuits.
verifying and decoding in constant depth. we develop a general approach for improving the efficiency of a computationally bounded receiver interacting with a powerful and possibly malicious sender. the key idea we use is that of delegating some of the receiver's computation to the (potentially malicious) sender. this idea was recently introduced by goldwasser et al. [14] in the area of program checking. a classic example of such a sender-receiver setting is interactive proof systems. by taking the sender to be a (potentially malicious) prover and the receiver to be a verifier, we show that (p-prover) interactive proofs with k rounds of interaction are equivalent to (p-prover) interactive proofs with k+o(1) rounds, where the verifier is in nc0. that is, each round of the verifier's computation can be implemented in constant parallel time. as a corollary, we obtain interactive proof systems, with (optimally) constant soundness, for languages in am and nexp, where the verifier runs in constant parallel-time. another, less immediate sender-receiver setting arises in considering error correcting codes. by taking the sender to be a (potentially corrupted) codeword and the receiver to be a decoder, we obtain explicit families of codes that are locally (list-)decodable by constant-depth circuits of size polylogarithmic in the length of the codeword. using the tight connection between locally list-decodable codes and average-case complexity, we obtain a new, more efficient, worst-case to average-case reduction for languages in exp.
approximation algorithms for budgeted learning problems. we present the first approximation algorithms for a large class of budgeted learning problems. one classicexample of the above is the budgeted multi-armed bandit problem. in this problem each arm of the bandithas an unknown reward distribution on which a prior isspecified as input. the knowledge about the underlying distribution can be refined in the exploration phase by playing the arm and observing the rewards. however, there is a budget on the total number of plays allowed during exploration. after this exploration phase,the arm with the highest (posterior) expected reward is hosen for exploitation. the goal is to design the adaptive exploration phase subject to a budget constraint on the number of plays, in order to maximize the expected reward of the arm chosen for exploitation. while this problem is reasonably well understood in the infinite horizon discounted reward setting, the budgeted version of the problem is np-hard. for this problem and several generalizations, we provide approximate policies that achieve a reward within constant factor of the reward optimal policy. our algorithms use a novel linear program rounding technique based on stochastic packing.
toward a general theory of quantum games. we study properties of quantum strategies, which are complete specifications of a given party's actions in any multiple-round interaction involving the exchange of quantum information with one or more other parties. in particular, we focus on a representation of quantum strategies that generalizes the choi-jamiolkowski representation of quantum , with respect to which each strategy is described by a single operations. this new representation associates with each strategy a positive semidefinite operator acting only on the tensor product of its input and output spaces. various facts about such representations are established, and two applications are discussed: the first is a new and conceptually simple proof of kitaev's lower bound for strong coin-flipping, and the second is a proof of the exact characterization qrg = exp of the class of problems having quantum refereed games.
negative weights make adversaries stronger. the quantum adversary method is one of the most successful techniques for proving lower bounds on quantum query complexity. it gives optimal lower bounds for many problems, has application to classical complexity in formula size lower bounds, and is versatile with equivalent formulations interms of weight schemes, eigen values, and kolmogorov complexity. all these formulations rely on the principlethat if an algorithm successfully computes a function then, in particular, itis able to distinguish between inputs which map to different values. we present a stronger version of the adversary method which goes beyond this principle to make explicit use of the stronger condition that the algorithm actually computes the function. this new method, which we call adv+-, has all the advantages ofthe old: it is a lower bound on bounded-error quantum query complexity, its square is a lower bound on formula size, and it behaves well with respect tofunction composition. moreover adv+- is always at least as large as the adversary method adv, and we show an example of a monotone function forwhich adv+-(f)=omega(adv(f)1.098). we also give examples showing that adv+- does not face limitations of adv like the certificate complexity barrier and the property testing barrier.
playing games with approximation algorithms. in an online linear optimization problem, on each period $t$, an online algorithm chooses $s_t\in\mathcal{s}$ from a fixed (possibly infinite) set $\mathcal{s}$ of feasible decisions. nature (who may be adversarial) chooses a weight vector $w_t\in\mathbb{r}^n$, and the algorithm incurs cost $c(s_t,w_t)$, where $c$ is a fixed cost function that is linear in the weight vector. in the full-information setting, the vector $w_t$ is then revealed to the algorithm, and in the bandit setting, only the cost experienced, $c(s_t,w_t)$, is revealed. the goal of the online algorithm is to perform nearly as well as the best fixed $s\in\mathcal{s}$ in hindsight. many repeated decision-making problems with weights fit naturally into this framework, such as online shortest-path, online traveling salesman problem (tsp), online clustering, and online weighted set cover. previously, it was shown how to convert any efficient exact offline optimization algorithm for such a problem into an efficient online algorithm in both the full-information and the bandit settings, with average cost nearly as good as that of the best fixed $s\in\mathcal{s}$ in hindsight. however, in the case where the offline algorithm is an approximation algorithm with ratio $\alpha >1$, the previous approach worked only for special types of approximation algorithms. we show how to convert any offline approximation algorithm for a linear optimization problem into a corresponding online approximation algorithm, with a polynomial blowup in runtime. if the offline algorithm has an $\alpha$-approximation guarantee, then the expected cost of the online algorithm on any sequence is not much larger than $\alpha$ times that of the best $s\in\mathcal{s}$, where the best is chosen with the benefit of hindsight. our main innovation is combining zinkevich's algorithm for convex optimization with a geometric transformation that can be applied to any approximation algorithm. standard techniques generalize the above result to the bandit setting, except that a &ldquo;barycentric spanner&rdquo; for the problem is also (provably) necessary as input. our algorithm can also be viewed as a method for playing large repeated games, where one can compute only approximate best responses, rather than best responses.
on achieving the "best of both worlds" in secure multiparty computation. two settings are typically considered for secure multipartycomputation, depending on whether or not a majority of the partiesare assumed to be honest. protocols designed under this assumptionprovide "full security" (and, in particular, guarantee outputdelivery and fairness) when this assumption is correct; however, if half or more of the parties are dishonest then security iscompletely compromised. on the other hand, protocols toleratingarbitrarily-many faults do not provide fairness or guaranteed output delivery even if only a single party is dishonest. it isnatural to wonder whether it is possible to achieve the "best ofboth worlds" : namely, a single protocol that simultaneouslyachieves the best possible security in both the above settings. ishai, et al. (crypto 2006) recently addressed this question, andruled out constant-round protocols of this type. as our main result, we completely settle the question by ruling outprotocols using any (expected) polynomial number of rounds. given this stark negative result, we then ask what can be achieved if we are willing to assume simultaneous message transmission (or, equivalently, a non-rushing adversary). in this setting, we show that impossibility still holdsfor logarithmic-round protocols. we also show, for any polynomialp, a protocol (whose round complexity depends on p) that can be simulated to within closeness o(1/p).
how to rank with few errors. we present a polynomial time approximation scheme (ptas) for the minimum feedback arc set problem on tournaments. a simple weighted generalization gives a ptas for kemeny-young rank aggregation.
lower bounds in communication complexity based on factorization norms. we introduce a new method to derive lower bounds on randomized and quantum communication complexity. our method is based on factorization norms, a notion from banach space theory. this approach gives us access to several powerful tools from this area such as normed spaces duality and grothendiek's inequality. this extends the arsenal of methods for deriving lower bounds in communication complexity. as we show, our method subsumes most of the previously known general approaches to lower bounds on communication complexity. moreover, we extend all (but one) of these lower bounds to the realm of quantum communication complexity with entanglement. our results also shed some light on the question how much communication can be saved by using entanglement. it is known that entanglement can save one of every two qubits, and examples for which this is tight are also known. it follows from our results that this bound on the saving in communication is tight almost always. &copy; 2008 wiley periodicals, inc. random struct. alg., 2009
search via quantum walk. we propose a new method for designing quantum search algorithms forfinding a "marked" element in the state space of a classical markovchain. the algorithm is based on a quantum walk à la szegedy [25] that is defined in terms of the markov chain. the main new idea is to apply quantum phase estimation to the quantumwalk in order to implement an approximate reflection operator. thisoperatoris then used in an amplitude amplification scheme. as a result weconsiderably expand the scope of the previous approaches ofambainis [6] and szegedy [25]. our algorithm combines the benefits of these approaches in terms of beingable to find marked elements, incurring the smaller cost of the two,and being applicable to a larger class of markov chain. in addition,it is conceptually simple, avoids several technical difficulties in the previous analyses, and leads to improvements in various aspects of several algorithms based on quantum walk.
linear probing with constant independence. hashing with linear probing dates back to the 1950s and is among the most widely studied algorithms. in recent years, it has become one of the most important hash table organizations because it uses the cache of modern computers very well. unfortunately, previous analyses relied either on complicated and space-consuming hash functions, or on the unrealistic assumption of free access to a hash function with random and independent function values. carter and wegman, in their seminal paper on universal hashing, have already raised the question of extending their analysis to linear probing. however, we show in this paper that linear probing using a pairwise independent family may have expected logarithmic cost per operation. on the positive side, we show that 5-wise independence is enough to ensure constant expected time per operation. this resolves the question of finding a space- and time-efficient hash function that provably ensures good performance for linear probing.
an efficient parallel repetition theorem for arthur-merlin games. we show a parallel-repetition theorem for constant-round arthur-merlin games, using an efficient reduction. as a consequence, we show that parallel repetition reduces the soundness-error at an optimal rate (up to a negligible factor) in constant-round public-coin argument systems, and constant-round public-coinproofs of knowledge. the former of these results resolves an open questionposed by bellare, impagliazzo and naor (focs '97).
property testing in hypergraphs and the removal lemma. property testers are efficient, randomized algorithms which recognize if an input graph (or other combinatorial structure) satisfies a given property or if it is "far" from exhibiting it.generalizing several earlier results, alon and shapira showed thathereditary graph properties are testable (with one-sided error). in this paper we prove the analogous result for hypergraphs.this result is an immediate consequence of a (hyper)graph theoretic statement, which is an extension of the so-called removal lemma. the proof of this generalization relies on the regularity method for hypergraphs.
low-degree tests at large distances. we define tests of boolean functions which distinguish between linear (or quadratic) polynomials, and functions which are very far, in an appropriate sense, from these polynomials. the tests have optimal or nearly optimal trade-offs between soundness and the number of queries. a central step in our analysis of quadraticity tests is the proof of aninverse theorem for the third gowers uniformity norm of boolean functions. the last result implies that it ispossible to estimate efficiently the distance from the second-order reed-muller code on inputs lying far beyond its list-decoding radius. our main technical tools are fourier analysis on z2n and methods from additive number theory. we observe that these methods can be used to give a tight analysis of the abelian homomorphism testing problemfor some families of groups, including powers of zp.
tight integrality gaps for lovasz-schrijver lp relaxations of vertex cover and max cut. we study linear programming relaxations of vertex cover and max cutarising from repeated applications of the "lift-and-project" method of lovasz and schrijver starting from the standard linear programming relaxation. for vertex cover, arora, bollobas, lovasz and tourlakis prove thatthe integrality gap remains at least 2-ε after ωε(log n) rounds, where n is the number ofvertices, and tourlakis proves that integrality gap remains at least 1.5-ε after ω((log n)2) rounds. fernandez de lavega and kenyon prove that the integrality gap of max cut is at most 12 + ε after any constant number of rounds. (theirresult also applies to the more powerful sherali-adams method. we prove that the integrality gap of vertex cover remains at least 2-ε after ωε (n) rounds, and that theintegrality gap of max cut remains at most 1/2 +ε after ωε(n) rounds.
low-end uniform hardness vs. randomness tradeoffs for am. impagliazzo and wigderson [proceedings of the 39th annual ieee symposium on foundations of computer science, ieee computer society, washington, dc, 1998, pp. 734-743] proved a hardness versus randomness tradeoff for bpp in the uniform setting, which was subsequently extended to give optimal tradeoffs for the full range of possible hardness assumptions (in slightly weaker settings). gutfreund, shaltiel, and ta-shma [comput. complexity, 12 (2003), pp. 85-130] proved a uniform hardness versus randomness tradeoff for am, but that result worked only on the &ldquo;high end&rdquo; of possible hardness assumptions. in this work, we give uniform hardness versus randomness tradeoffs for am that are near-optimal for the full range of possible hardness assumptions. following gutfreund, shaltiel, and ta-shma, we do this by constructing a hitting-set-generator (hsg) for am with &ldquo;resilient reconstruction.&rdquo; our construction is a recursive variant of the miltersen-vinodchandran hsg [comput. complexity, 14 (2005), pp. 256-279], the only known hsg construction with this required property. the main new idea is to have the reconstruction procedure operate implicitly and locally on superpolynomially large objects, using tools from pcps (low-degree testing, self-correction) together with a novel use of extractors that are built from reed-muller codes for a sort of locally computable error-reduction. as a consequence we obtain gap theorems for am (and am $\cap$ coam) that state, roughly, that either am (or am $\cap$ coam) protocols running in time $t(n)$ can simulate all of exp (&ldquo;arthur-merlin games are powerful&rdquo;) or else all of am (or am $\cap$ coam) can be simulated in nondeterministic time $s(n)$ (&ldquo;arthur-merlin games can be derandomized&rdquo;) for a near-optimal relationship between $t(n)$ and $s(n)$. as in gutfreund, shatiel, and ta-shma, the case of am $\cap$ coam yields a particularly clean theorem that is of special interest due to the wide array of cryptographic and other problems that lie in this class.
separating ac from depth-2 majority circuits. we prove that ac0 cannot be efficiently simulated by majºmaj circuits. namely, we construct an ac0 circuit of depth 3 that requires majºmaj circuits of size 2ω(n1/5). this matches allender's classic result that ac0 can be simulated by majºmajºmaj circuits of quasipolynomial size. our proof is based on communication complexity. to obtain the above result, we develop a novel technique for communication lower bounds, the degree/discrepancy theorem. this technique is a separate contribution of our paper. it translates lower bounds on the threshold degree of a boolean function into upper bounds on the discrepancy of a related function. upper bounds on the discrepancy, in turn, immediately imply communication lower bounds as well as lower bounds against threshold circuits. as part of our proof, we use the degree/discrepancy theorem to obtain an explicit ac0 circuit of depth 3 that has discrepancy 2-ω(n1/5), under an explicit distribution. this yields the first known ac0 function with exponentially small discrepancy. finally, we apply our work to learning theory, showing that polynomial-size dnf and cnf formulas have margin complexity 2ω(n1/5).
interpolation of depth-3 arithmetic circuits with two multiplication gates. in this paper we consider the problem of constructing a small arithmetic circuit for a polynomial for which we have oracle access. our focus is on $n$-variate polynomials, over a finite field $\mathbb{f}$, that have depth-3 arithmetic circuits (with an addition gate at the top) with two multiplication gates of degree at most $d$. we obtain the following results: 1. multilinear case. when the circuit is multilinear (multiplication gates compute multilinear polynomials) we give an algorithm that outputs, with probability $1-o(1)$, all the depth-3 circuits with two multiplication gates computing the polynomial. the running time of the algorithm is $\operatorname{poly}(n,|\mathbb{f}|)$. 2. general case. when the circuit is not multilinear we give a quasi-polynomial (in $n,d,|\mathbb{f}|$) time algorithm that outputs, with probability $1-o(1)$, a succinct representation of the polynomial. in particular, if the depth-3 circuit for the polynomial is not of small depth-3 rank (namely, after removing the g.c.d. (greatest common divisor) of the two multiplication gates, the remaining linear functions span a not too small linear space), then we output the depth-3 circuit itself. in the case that the rank is small we output a depth-3 circuit with a quasi-polynomial number of multiplication gates. $\diamond$ prior to our work there have been several interpolation algorithms for restricted models. however, all the techniques used there completely fail when dealing with depth-3 circuits with even just two multiplication gates. our proof technique is new and relies on the factorization algorithm for multivariate black-box polynomials, on lower bounds on the length of linear locally decodable codes with two queries, and on a theorem regarding the structure of identically zero depth-3 circuits with four multiplication gates.
first to market is not everything: an analysis of preferential attachment with fitness. the design of algorithms on complex networks, such as routing, ranking or recommendation algorithms, requires a detailed understanding of the growth characteristics of the networks of interest, such as the internet,the web graph, social networks or online communities. to this end, preferential attachment, in which the popularity (or relevance) of a node is determined by its degree, is a well-known and appealing random graph model, whose predictions are in accordance with experiments on the web graph and several social networks. however, its central assumption, that the popularity of the nodes dependsonly on their degree, is not a realistic one, since every node has potentially some intrinsic quality which can differentiate its attractiveness from other nodes with similar degrees. in this paper, we provide a rigorous analysis of preferential attachment with fitness, suggested by bianconi and barabási and studied by motwani and xu, in which the degree of a vertex is scaled by its quality to determine its attractiveness. including quality considerations in the classical preferential attachment model provides a much more realistic description of many complex networks, such as the web graph, and allows toobserve a much richer behavior in the growth dynamics of these networks. specifically, depending on the shape of the distributionfrom which the qualities of the vertices are drawn, we observe three distinct phases, namely a first-mover-advantage phase, afit-get-richer phase and an innovation-pays-offphase. we precisely characterize the properties of the quality distribution that result in each of these phases and we computethe exact growth dynamics for each phase. the dynamics provide rich information about the quality of the vertices, which can bevery useful in many practical contexts, including ranking algorithms for the web, recommendation algorithms, as well as thestudy of social networks.
network design for vertex connectivity. we study the survivable network design problem (sndp) for vertex connectivity. given a graph g(v,e) with costs on edges, the goal of sndp is to find a minimum cost subset of edges that ensures a given set of pairwise vertex connectivity requirements. when all connectivity requirements are between a special vertex, called the source, and vertices in a subset t ⊆ v, called terminals, the problem is called the single-source sndp. our main result is a randomized ko(k2) log4n-approximation algorithm for single-source sndp where k denotes the largest connectivity requirement for any source-terminal pair. in particular, we get a poly-logarithmic approximation for any constant k. prior to our work, no non-trivial approximation guarantees were known for this problem for any k ≥ 3. we also show that sndp is kω(1)-hard to approximate and provide an elementary construction that shows that the well-studied set-pair linear programming relaxation for this problem has an ω(k1/3) integrality gap.
a discriminative framework for clustering via similarity functions. problems of clustering data from pairwise similarity information are ubiquitous in computer science. theoretical treatments typically view the similarity information as ground-truth and then design algorithms to (approximately) optimize various graph-based objective functions. however, in most applications, this similarity information is merely based on some heuristic; the ground truth is really the unknown correct clustering of the data points and the real goal is to achieve low error on the data. in this work, we develop a theoretical approach to clustering from this perspective. in particular, motivated by recent work in learning theory that asks "what natural properties of a similarity (or kernel) function are sufficient to be able to learn well?" we ask "what natural properties of a similarity function are sufficient to be able to cluster well?" to study this question we develop a theoretical framework that can be viewed as an analog of the pac learning model for clustering, where the object of study, rather than being a concept class, is a class of (concept, similarity function) pairs, or equivalently, a property the similarity function should satisfy with respect to the ground truth clustering. we then analyze both algorithmic and information theoretic issues in our model. while quite strong properties are needed if the goal is to produce a single approximately-correct clustering, we find that a number of reasonable properties are sufficient under two natural relaxations: (a) list clustering: analogous to the notion of list-decoding, the algorithm can produce a small list of clusterings (which a user can select from) and (b) hierarchical clustering: the algorithm's goal is to produce a hierarchy such that desired clustering is some pruning of this tree (which a user could navigate). we develop a notion of the clustering complexity of a given property (analogous to notions of capacity in learning theory), that characterizes its information-theoretic usefulness for clustering. we analyze this quantity for several natural game-theoretic and learning-theoretic properties, as well as design new efficient algorithms that are able to take advantage of them. our algorithms for hierarchical clustering combine recent learning-theoretic approaches with linkage-style methods. we also show how our algorithms can be extended to the inductive case, i.e., by using just a constant-sized sample, as in property testing. the analysis here uses regularity-type results of [fk] and [afkk].
evolvability from learning algorithms. valiant has recently introduced a framework for analyzing the capabilities and the limitations of the evolutionary process of random change guided by selection. in his framework the process of acquiring a complex functionality is viewed as a substantially restricted form of pac learning of an unknown function from a certain set of functions. valiant showed that classes of functions evolvable in his model are also learnable in the statistical query (sq) model of kearns and asked whether the converse is true. we show that evolvability is equivalent to learnability by a restricted form of statistical queries. based on this equivalence we prove that for any fixed distribution d over the instance space, every class of functions learnable by sqs over d is evolvable over d. previously, only the evolvability of monotone conjunctions of boolean variables over the uniform distribution was known. on the other hand, we prove that the answer to valiant's question is negative when distribution-independent evolvability is considered. to demonstrate this, we develop a technique for proving lower bounds on evolvability and use it to show that decision lists and linear threshold functions are not evolvable in a distribution-independent way. this is in contrast to distribution-independent learnability of decision lists and linear threshold functions in the statistical query model.
optimal algorithms and inapproximability results for every csp? semidefinite programming(sdp) is one of the strongest algorithmic techniques used in the design of approximation algorithms. in recent years, unique games conjecture(ugc) has proved to be intimately connected to the limitations of semidefinite programming. making this connection precise, we show the following result : if ugc is true, then for every constraint satisfaction problem(csp) the best approximation ratio is given by a certain simple sdp. specifically, we show a generic conversion from sdp integrality gaps to ugc hardness results for every csp. this result holds both for maximization and minimization problems over arbitrary finite domains. using this connection between integrality gaps and hardness results we obtain a generic polynomial-time algorithm for all csps. assuming the unique games conjecture, this algorithm achieves the optimal approximation ratio for every csp. unconditionally, for all 2-csps the algorithm achieves an approximation ratio equal to the integrality gap of a natural sdp used in literature. further the algorithm achieves at least as good an approximation ratio as the best known algorithms for several problems like maxcut, max2sat, maxdicut and unique games.
parallel repetition in projection games and a concentration bound. in a two player game, a referee asks two cooperating players (who are not allowed to communicate) questions sampled from some distribution and decides whether they win or not based on some predicate of the questions and their answers. the parallel repetition of the game is the game in which the referee samples n independent pairs of questions and sends corresponding questions to the players simultaneously. the players may now answer each question in a way that depends on the other questions they are asked. if the players cannot win the original game with probability better than (1-ε), what's the best they can do in the repeated game? we improve earlier results of raz and holenstein, which showed that the players cannot win all copies in the repeated game with probability better than (1-ε3)ω(n/c) (here c is the length of the answers in the game), in the following ways: we prove the bound (1-ε2)ω(n) as long as the game is a "projection game", the type of game most commonly used in hardness of approximation results. our bound is independent of the answer length and has a better dependence on ε. by the recent work of raz, this bound is essentially tight. a consequence of this bound is to the unique games conjecture of khot. many tight or almost tight hardness of approximation results have been proved using the unique games conjecture, so it would be very interesting to prove this conjecture. we make progress towards this goal by showing that it suffices to prove the following easier statement: {unique games conjecture} for every δ,ε> 0, there exists an alphabet size m(ε) such that it is np-hard to distinguish a unique game with alphabet size m for which a 1-ε2 fraction of the constraints can be satisfied from one in which a 1-ε1-δ fraction of the constraints can be satisfied. we also prove a concentration bound for parallel repetition (of general games) showing that for any constant 04 n/c)). an application of this is in testing bell inequalities. our result implies that the parallel repetition of the chsh game can be used to get an experiment that has a very large classical versus quantum gap.
an optimal sdp algorithm for max-cut, and equally optimal long code tests. let g be an undirected graph for which the standard max-cut sdp relaxation achieves at least a c fraction of the total edge weight, 1/2 2' algorithm. thus we have given an efficient, optimal sdp-rounding algorithm for max-cut. the fact that it is rpr2 confirms a conjecture of feige and langberg [17]. we also describe and analyze the tight connection between sdp gaps and long code tests (and the constructions of [25, 3, 4]). using this connection, we give optimal long code tests for max-cut. combining these with results implicit in [27, 29] and ideas from [19], we derive the following conclusions: - the max-cut sdp gap curve subject to triangle inequalities is also given by s(c). - no rpr2 algorithm can be guaranteed to find cuts of value larger than s(c) in graphs where the optimal cut is c. (contrast this with the fact that in the graphs exhibiting the c vs. s(c) sdp gap, our rpr2 algorithm actually finds the optimal cut.) - further, no polynomial-time algorithm of any kind can have such a guarantee, assuming p ≠ np and the unique games conjecture.
every minor-closed property of sparse graphs is testable. testing a property p of graphs in the bounded degree model deals with the following problem: given a graph g of bounded degree d we should distinguish (with probability 0.9, say) between the case that g satisfies p and the case that one should add/remove at least ε d n edges of g to make it satisfy p. in sharp contrast to property testing of dense graphs, which is relatively well understood, very few properties are known to be testable in bounded degree graphs with a constant number of queries. in this paper we identify for the first time a large (and natural) family of properties that can be efficiently tested in bounded degree graphs, by showing that every minor-closed graph property can be tested with a constant number of queries. as a special case, we infer that many well studied graph properties, like being planar, outer-planar, series-parallel, bounded genus, bounded tree-width and several others, are testable with a constant number of queries. none of these properties was previously known to be testable even with o(n) queries. the proof combines results from the theory of graph minors with results on convergent sequences of sparse graphs, which rely on martingale arguments.
uniform direct product theorems: simplified, optimized, and derandomized. the classical direct-product theorem for circuits says that if a boolean function f: {0,1}n -> {0,1} is somewhat hard to compute on average by small circuits, then the corresponding k-wise direct product function fk(x1,...,xk)=(f(x1),...,f(xk)) (where each xi -> {0,1}n) is significantly harder to compute on average by slightly smaller circuits. we prove a fully uniform version of the direct-product theorem with information-theoretically optimal parameters, up to constant factors. namely, we show that for given k and ε, there is an efficient randomized algorithm a with the following property. given a circuit c that computes fk on at least ε fraction of inputs, the algorithm a outputs with probability at least 3/4 a list of o(1/ε) circuits such that at least one of the circuits on the list computes f on more than 1-δ fraction of inputs, for δ = o((log 1/ε)/k). moreover, each output circuit is an ac0 circuit (of size poly(n,k,log 1/δ,1/ε)), with oracle access to the circuit c. using the goldreich-levin decoding algorithm [5], we also get a fully uniform version of yao's xor lemma [18] with optimal parameters, up to constant factors. our results simplify and improve those in [10]. our main result may be viewed as an efficient approximate, local, list-decoding algorithm for direct-product codes (encoding a function by its values on all k-tuples) with optimal parameters. we generalize it to a family of "derandomized" direct-product codes, which we call intersection codes, where the encoding provides values of the function only on a subfamily of k-tuples. the quality of the decoding algorithm is then determined by sampling properties of the sets in this family and their intersections. as a direct consequence of this generalization we obtain the first derandomized direct product result in the uniform setting, allowing hardness amplification with only constant (as opposed to a factor of k) increase in the input length. finally, this general setting naturally allows the decoding of concatenated codes, which further yields nearly optimal derandomized amplification.
inapproximability of pure nash equilibria. the complexity of computing pure nash equilibria in congestion games was recently shown to be pls-complete. in this paper, we therefore study the complexity of computing approximate equilibria in congestion games. an alpha-approximate equilibrium, for α > 1, is a state of the game in which none of the players can make an α-greedy step, i.e., an unilateral strategy change that decreases the player's cost by a factor of at least α. our main result shows that finding an α-approximate equilibrium of a given congestion game is sc pls-complete, for any polynomial-time computable α > 1. our analysis is based on a gap introducing pls-reduction from flip, i.e., the problem of finding a local optimum of a function encoded by an arbitrary circuit. as this reduction is tight it additionally implies that computing an α-approximate equilibrium reachable from a given initial state by a sequence of α-greedy steps is pspace-complete. our results are in sharp contrast to a recent result showing that every local search problem in pls admits a fully polynomial time approximation scheme. in addition, we show that there exist congestion games with states such that any sequence of α-greedy steps leading from one of these states to an α-approximate nash equilibrium has exponential length, even if the delay functions satisfy a bounded-jump condition. this result shows that a recent result about polynomial time convergence for α-greedy steps in congestion games satisfying the bounded-jump condition is restricted to symmetric games only.
optimal mechanism design and money burning. mechanism design is now a standard tool in computer science for aligning the incentives of self-interested agents with the objectives of a system designer. there is, however, a fundamental disconnect between the traditional application domains of mechanism design (such as auctions) and those arising in computer science (such as networks): while monetary "transfers" (i.e., payments) are essential for most of the known positive results in mechanism design, they are undesirable or even technologically infeasible in many computer systems. classical impossibility results imply that the reach of mechanisms without transfers is severely limited. computer systems typically do have the ability to reduce service quality--routing systems can drop or delay traffic, scheduling protocols can delay the release of jobs, and computational payment schemes can require computational payments from users (e.g., in spam-fighting systems). service degradation is tantamount to requiring that users "burn money", and such "payments" can be used to influence the preferences of the agents at a cost of degrading the social surplus. we develop a framework for the design and analysis of "money-burning mechanisms" to maximize the residual surplus-the total value of the chosen outcome minus the payments required. our primary contributions are the following. * we define a general template for prior-free optimal mechanism design that explicitly connects bayesian optimal mechanism design, the dominant paradigm in economics, with worst-case analysis. in particular, we establish a general and principled way to identify appropriate performance benchmarks in prior-free mechanism design. * for general single-parameter agent settings, we characterize the bayesian optimal money-burning mechanism. * for multi-unit auctions, we design a near-optimal prior-free money-burning mechanism: for every valuation profile, its expected residual surplus is within a constant factor of our benchmark, the residual surplus of the best bayesian optimal mechanism for this profile. * for multi-unit auctions, we quantify the benefit of general transfers over money-burning: optimal money-burning mechanisms always obtain a logarithmic fraction of the full social surplus, and this bound is tight.
cryptography with constant computational overhead. current constructions of cryptographic primitives typically involve a large multiplicative computational overhead that grows with the desired level of security. we explore the possibility of implementing basic cryptographic primitives, such as encryption, authentication, signatures, and secure two-party computation, while incurring only a constant computational overhead compared to insecure implementations of the same tasks. here we make the usual security requirement that the advantage of any polynomial-time attacker must be negligible in the input length. we obtain affirmative answers to this question for most central cryptographic primitives under plausible, albeit sometimes nonstandard, intractability assumptions. we start by showing that pairwise-independent hash functions can be computed by linear-size circuits, disproving a conjecture of mansour, nisan, and tiwari (stoc 1990). this construction does not rely on any unproven assumptions and is of independent interest. our hash functions can be used to construct message authentication schemes with constant overhead from any one-way function. under an intractability assumption that generalizes a previous assumption of alekhnovich (focs 2003), we get (public and private key) encryption schemes with constant overhead. using an exponentially strong version of the previous assumption, we get signature schemes of similar complexity. assuming the existence of pseudorandom generators in nc z with polynomial stretch together with the existence of an (arbitrary) oblivious transfer protocol, we get similar results for the seemingly very complex task of secure two-party computation. more concretely, we get general protocols for secure two-party computation in the semi-honest model in which the two parties can be implemented by circuits whose size is a constant multiple of the size s of the circuit to be evaluated. in the malicious model, we get protocols whose communication complexity is a constant multiple of s and whose computational complexity is slightly super-linear in s. for natural relaxations of security in the malicious model that are still meaningful in practice, we can also keep the computational complexity linear in s. these results extend to the case of a constant number of parties, where an arbitrary subset of the parties can be corrupted. our protocols rely on non-black-box techniques, and suggest the intriguing possibility that the ultimate efficiency in this area of cryptography can be obtained via such techniques.
on partitioning graphs via single commodity flows. in this paper we obtain improved upper and lower bounds for the best approximation factor for sparsest cut achievable in the cut-matching game framework proposed in khandekar et al. [9]. we show that this simple framework can be used to design combinatorial algorithms that achieve o(log n) approximation factor and whose running time is dominated by a poly-logarithmic number of single-commodity max-flow computations. this matches the performance of the algorithm of arora and kale [2]. moreover, we also show that it is impossible to get an approximation factor of better than ω(√log n) in the cut-matching game framework. these results suggest that the simple and concrete abstraction of the cut-matching game may be powerful enough to capture the essential features of the complexity of sparsest cut.
the pattern matrix method for lower bounds on quantum communication. in a breakthrough result, razborov (2003) gave optimal lower bounds on the communication complexity of every function f of the form f(x,y)=d(|x and y|) for some d:{0,1,...,n}->{0,1}, in the bounded-error quantum model with and without prior entanglement. this was proved by the multidimensional discrepancy method. we give an entirely different proof of razborov's result, using the original, one-dimensional discrepancy method. this refutes the commonly held intuition (razborov 2003) that the original discrepancy method fails for functions such as disjointness. more importantly, our communication lower bounds hold for a much broader class of functions for which no methods were available. namely, fix an arbitrary function f:{0,1}n/4->{0,1} and let a be the boolean matrix whose columns are each an application of f to some subset of the variables x1,x2,...,xn. we prove that the communication complexity of a in the bounded-error quantum model with and without prior entanglement is omega(d), where d is the approximate degree of f. from this result, razborov's lower bounds follow easily. our result also establishes a large new class of total boolean functions whose quantum communication complexity (regardless of prior entanglement) is at best polynomially smaller than their classical complexity. our proof method is a novel combination of two ingredients. the first is a certain equivalence of approximation and orthogonality in euclidean n-space, which follows by linear-programming duality. the second is a new construction of suitably structured matrices with low spectral norm, the pattern matrices, which we realize using matrix analysis and the fourier transform over (z2)n. the method of this paper has recently inspired important progress in multiparty communication complexity.
the vpn conjecture is true. we consider the following network design problem. we are given an undirected graph g=(v,e) with edges costs c(e) and a set of terminal nodes w. a hose demand matrix for w is any symmetric matrix [dij] such that for each i, ∑ j ≠ i dij ≤ 1. we must compute the minimum cost edge capacities that are able to support the oblivious routing of every hose matrix in the network. an oblivious routing template, in this context, is a simple path pij for each pair i,j ∈ w. given such a template, if we are to route a demand matrix d, then for each i,j we send dij units of flow along each pij. fingerhut et al. and gupta et al. obtained a 2-approximation for this problem, using a solution template in the form of a tree. it has been widely asked and subsequently conjectured [italiano 2006] that this solution actually results in the optimal capacity for the single path vpn design problem; this has become known as the vpn conjecture. the conjecture has previously been proven for some restricted classes of graphs [hurkens 2005, grandoni 2007, fiorini 2007]. our main theorem establishes that this conjecture is true in general graphs. this also gives the first polynomial time algorithm for the single path vpn problem. we also show that the multipath version of the conjecture is false.
sdp gaps and ugc hardness for multiway cut, 0-extension, and metric labeling. the connection between integrality gaps and computational hardness of discrete optimization problems is an intriguing question. in recent years, this connection has prominently figured in several tight ugc-based hardness results. we show in this paper a direct way of turning integrality gaps into hardness results for several fundamental classification problems. specifically, we convert linear programming integrality gaps for the multiway cut, 0-extension, and and metric labeling problems into ugc-based hardness results. qualitatively, our result suggests that if the unique games conjecture is true then a linear relaxation of the latter problems studied in several papers (so-called earthmover linear program) yields the best possible approximation. taking this a step further, we also obtain integrality gaps for a semi-definite programming relaxation matching the integrality gaps of the earthmover linear program. prior to this work, there was an intriguing possibility of obtaining better approximation factors for labeling problems via semi-definite programming.
stateless distributed gradient descent for positive linear programs. we develop a framework of distributed and stateless solutions for packing and covering linear programs, which are solved by multiple agents operating in a cooperative but uncoordinated manner. our model has a separate "agent" controlling each variable and an agent is allowed to read-off the current values only of those constraints in which it has non-zero coefficients. this is a natural model for many distributed applications like flow control, maximum bipartite matching, and dominating sets. the most appealing feature of our algorithms is their simplicity and polylogarithmic convergence. for the packing lp max{cx | ax i = exp[1ε * (aix/bi -1)] for each constraint i and each agent j iteratively increases (resp. decreases) xj multiplicatively if ajt y is too small (resp. large) as compared to cj. our algorithm starting from a feasible solution, always maintains feasibility, and computes a (1+epsilon) approximation in poly((ln (mn a_max))ε) rounds. here m and n are number of rows and columns of a and a_max, also known as the "width" of the lp, is the ratio of maximum and minimum non-zero entries aij/(bicj). similar algorithm works for the covering lp min{by | at y >= c, y >= 0} as well. while exponential dual variables are used in several packing/ covering lp algorithms before [25, 9, 13, 12, 26, 16], this is the first algorithm which is both stateless and has polylogarithmic convergence. our algorithms can be thought of as applying distributed gradient descent/ascent on a carefully chosen potential. our analysis differs from those of previous multiplicative update based algorithms and argues that while the current solution is far away from optimality, the potential function decreases/increases by a significant factor.
lossy trapdoor functions and their applications. we propose a new general primitive called lossy trapdoor functions (lossy tdfs), and realize it under a variety of different number theoretic assumptions, including hardness of the decisional diffie-hellman (ddh) problem and the worst-case hardness of lattice problems. using lossy tdfs, we develop a new approach for constructing several important cryptographic primitives, including (injective) trapdoor functions, collision-resistant hash functions, oblivious transfer, and chosen ciphertext-secure cryptosystems. all of the constructions are simple, efficient, and black-box. these results resolve some long-standing open problems in cryptography. they give the first known injective trapdoor functions based on problems not directly related to integer factorization, and provide the first known cca-secure cryptosystem based solely on the worst-case complexity of lattice problems.
fast-converging tatonnement algorithms for one-time and ongoing market problems. why might markets tend toward and remain near equilibrium prices? in an effort to shed light on this question from an algorithmic perspective, this paper formalizes the setting of ongoing markets, by contrast with the classic market scenario, which we term one-time markets. the ongoing market allows trade at non-equilibrium prices, and, as its name suggests, continues over time. as such, it appears to be a more plausible model of actual markets. for both market settings, this paper defines and analyzes variants of a simple tatonnement algorithm that differs from previous algorithms that have been subject to asymptotic analysis in three significant respects: the price update for a good depends only on the price, demand, and supply for that good, and on no other information; the price update for each good occurs distributively and asynchronously; the algorithms work (and the analyses hold) from an arbitrary starting point. our algorithm introduces a new and natural update rule. we show that this update rule leads to fast convergence toward equilibrium prices in a broad class of markets that satisfy the weak gross substitutes property. these are the first analyses for computationally and informationally distributed algorithms that demonstrate polynomial convergence. our analysis identifies three parameters characterizing the markets, which govern the rate of convergence of our protocols. these parameters are, broadly speaking: 1. a bound on the fractional rate of change of demand for each good with respect to fractional changes in its price. 2. a bound on the fractional rate of change of demand for each good with respect to fractional changes in wealth. 3. the closeness of the market to a fisher market (a market with buyers starting with money alone). we give two types of protocols. the first type assumes global knowledge of only (an upper bound on) the first parameter. for this protocol, we also provide a matching lower bound in terms of these parameters for the one-time market. our second protocol, which is analyzed for the one-time market alone, assumes no global knowledge whatsoever.
decodability of group homomorphisms beyond the johnson bound. given a pair of finite groups g and h, the set of homomorphisms from g to h form an error-correcting code where codewords differ in at least 1/2 the coordinates. we show that for every pair of abelian groups g and h, the resulting code is (locally) list-decodable from a fraction of errors arbitrarily close to its distance. at the heart of this result is the following combinatorial result: there is a fixed polynomial p(•) such that for every pair of abelian groups g and h, if the maximum fraction of agreement between two distinct homomorphisms from g to h is λ, then for every ε> 0 and every function f:g -> h, the number of homomorphisms that have agreement λ + ε with f is at most p(1/ε). we thus give a broad class of codes whose list-decoding radius exceeds the "johnson bound". examples of such codes are rare in the literature, and for the ones that do exist, "combinatorial" techniques to analyze their list-decodability are limited. our work is an attempt to add to the body of such techniques. we use the fact that abelian groups decompose into simpler ones and thus codes derived from homomorphisms over abelian groups may be viewed as certain "compositions" of simpler codes. we give techniques to lift list-decoding bounds for the component codes to bounds for the composed code. we believe these techniques may be of general interest.
towards an optimal separation of space and length in resolution. most state-of-the-art satisfiability algorithms today are variants of the dpll procedure augmented with clause learning. the main bottleneck for such algorithms, other than the obvious one of time, is the amount of memory used. in the field of proof complexity, the resources of time and memory correspond to the length and space of resolution proofs. there has been a long line of research trying to understand these proof complexity measures, as well as relating them to the width of proofs, i.e., the size of the largest clause in the proof, which has been shown to be intimately connected with both length and space. while strong results have been proven for length and width, our understanding of space is still quite poor. for instance, it has remained open whether the fact that a formula is provable in short length implies that it is also provable in small space (which is the case for length versus width), or whether on the contrary these measures are completely unrelated in the sense that short proofs can be arbitrarily complex with respect to space. in this paper, we present some evidence that the true answer should be that the latter case holds and provide a possible roadmap for how such an optimal separation result could be obtained. we do this by proving a tight bound of theta(√(n)) on the space needed for so-called pebbling contradictions over pyramid graphs of size n. also, continuing the line of research initiated by (ben-sasson 2002) into trade-offs between different proof complexity measures, we present a simplified proof of the recent length-space trade-off result in (hertel and pitassi 2007), and show how our ideas can be used to prove a couple of other exponential trade-offs in resolution.
an effective ergodic theorem and some applications. this work is a synthesis of recent advances in computable analysis with the theory of algorithmic randomness. in this theory, we try to strengthen probabilistic laws, i.e., laws which hold with probability 1, to laws which hold in their pointwise effective form - i.e., laws which hold for every individual constructively random point. in a tour-de-force, v'yugin proved an effective version of the ergodic theorem which holds when the probability space, the transformation and the random variable are computable. however, v'yugin's theorem cannot be directly applied to many examples, because all computable functions are continuous, and many applications use discontinuous functions. we prove a stronger effective ergodic theorem to include a restriction of braverman's "graph-computable functions". we then use this to give effective ergodic proofs of the effective versions of levy-kuzmin and khinchin theorems relating to continued fractions.
inverse conjecture for the gowers norm is false. let p be a fixed prime number and n be a large integer. the "inverse conjecture for the gowers norm" states that if the "d-th gowers norm" of a function f:fnp to fp is non-negligible, that is larger than a constant independent of n, then f has a non-trivial correlation with a degree d-1 polynomial. the conjecture is known to hold for d=2,3 and for any prime p. in this paper we show the conjecture to be false for p=2 and for d=4, by presenting an explicit function whose 4-th gowers norm is non-negligible, but whose correlation with any polynomial of degree 3 is exponentially small. essentially the same result, with different bounds for correlation, was independently obtained by green and tao. their analysis uses a modification of a ramsey-type argument of alon and beigel to show inapproximability of certain functions by low-degree polynomials. we observe that a combination of our results with the argument of alon and beigel implies the inverse conjecture to be false for any prime p, for d = p2.
logconcave random graphs. we propose the following model of a random graph on n vertices. let f be a distribution in r+n(n-1)/2 with a coordinate for every pair ij with 1 ≤ i,j ≤ n. then gf,p is the distribution on graphs with n vertices obtained by picking a random point x from f and defining a graph on n vertices whose edges are pairs ij for which xij ≤ p. the standard erdos-renyi model is the special case when f is uniform on the 0-1 unit cube. we determine basic properties such as the connectivity threshold for quite general distributions. we also consider cases where the xij are the edge weights in some random instance of a combinatorial optimization problem. by choosing suitable distributions, we can capture random graphs with interesting properties such as triangle-free random graphs and weighted random graphs with bounded total weight.
communication in the presence of replication. we consider the following problem. suppose that a big amount of data is distributed among several parties, so that each party misses only few pieces of data. the parties wish to perform some global computation on the data while minimizing the communication between them. this situation is common in many real-life scenarios. a naive solution to this problem is to first perform a synchronization step, letting one party learn all pieces of data, and then let this party perform the required computation locally. we study the question of obtaining better solutions to the problem, focusing mainly on the case of computing low-degree polynomials via non-interactive protocols. we present interesting connections between this problem and the well studied cryptographic problem of secret sharing. we use this connection to obtain nontrivial upper bounds and lower bounds using results and techniques from the domain of secret sharing. the relation with open problems from the area of secret sharing also provides evidence for the difficulty of resolving some of the questions we leave open.
algebraic property testing: the role of invariance. we argue that the symmetries of a property being tested play a central role in property testing. we support this assertion in the context of algebraic functions, by examining properties of functions mapping a vector space kn over a field k to a subfield f. we consider (f-)linear properties that are invariant under linear transformations of the domain and prove that an o(1)-local "characterization" is a necessary and sufficient condition for o(1)-local testability. when |k| = o(1). (a local characterization of a property is a definition of a property in terms of local constraints satisfied by functions exhibiting a property.) for the subclass of properties that are invariant under affine transformations of the domain, we prove that the existence of a single o(1)-local constraint implies o(1)-local testability. these results generalize and extend the class of algebraic properties, most notably linearity and low-degree-ness, that were previously known to be testable. in particular, the extensions include properties satisfied by functions of degree linear in n that turn out to be o(1)-locally testable. our results are proved by introducing a new notion that we term "formal characterizations". roughly this corresponds to characterizations that are given by a single local constraint and its permutations under linear transformations of the domain. our main testing result shows that local formal characterizations essentially imply local testability. we then investigate properties that are linear-invariant and attempt to understand their local formal characterizability. our results here give coarse upper and lower bounds on the locality of constraints and characterizations for linear-invariant properties in terms of some structural parameters of the property we introduce. the lower bounds rule out any characterization, while the upper bounds give formal characterizations. combining the two gives a test for all linear-invariant properties with local characterizations. we believe that invariance of properties is a very interesting notion to study in the context of property testing in general and merits a systematic study. in particular, the class of linear-invariant and affine-invariant properties exhibits a rich variety among algebraic properties and offer better intuition about algebraic properties than the more limited class of low-degree functions.
unique games on expanding constraint graphs are easy: extended abstract. we present an efficient algorithm to find a good solution to the unique games problem when the constraint graph is an expander. we introduce a new analysis of the standard sdp in this case that involves correlations among distant vertices. it also leads to a parallel repetition theorem for unique games when the graph is an expander.
the chow parameters problem. in the 2nd annual focs (1961), c. k. chow proved that every boolean threshold function is uniquely determined by its degree-0 and degree-1 fourier coefficients. these numbers became known as the chow parameters. providing an algorithmic version of chow's theorem --- i.e., efficiently constructing a representation of a threshold function given its chow parameters --- has remained open ever since. this problem has received significant study in the fields of circuit complexity, game theory and the design of voting systems, and learning theory. in this paper we effectively solve the problem, giving a randomized ptas with the following behavior: theorem: given the chow parameters of a boolean threshold function f over n bits and any constant ε > 0, the algorithm runs in time o(n2 log2 n) and with high probability outputs a representation of a threshold function f' which is ε-close to f. along the way we prove several new results of independent interest about boolean threshold functions. in addition to various structural results, these include the following new algorithmic results in learning theory (where threshold functions are usually called "halfspaces"): an ~o(n2)-time uniform distribution algorithm for learning halfspaces to constant accuracy in the "restricted focus of attention" (rfa) model of ben-david et al. [3]. this answers the main open question of [6]. an o(n2)-time agnostic-type learning algorithm for halfspaces under the uniform distribution. this contrasts with recent results of guruswami and raghavendra [21] who show that the learning problem we solve is np-hard under general distributions. as a special case of the latter result we obtain the fastest known algorithm for learning halfspaces to constant accuracy in the uniform distribution pac learning model. for constant ε our algorithm runs in time ~o(n2), which substantially improves on previous bounds and nearly matches the ω(n2) bits of training data that any successful learning algorithm must use.
a (de)constructive approach to program checking. program checking, program self-correcting and program self-testing were pioneered by [blum and kannan] and [blum, luby and rubinfeld] in the mid eighties as a new way to gain confidence in software, by considering program correctness on an input by input basis rather than full program verification. work in the field of program checking focused on designing, for specific functions, checkers, testers and correctors which are more efficient than the best program known for the function. these were designed utilizing specific algebraic, combinatorial or completeness properties of the function at hand. in this work we introduce a novel composition methodology for improving the efficiency of program checkers. we use this approach to design a variety of program checkers that are provably more efficient, in terms of circuit depth, than the optimal program for computing the function being checked. extensions of this methodology for the cases of program testers and correctors are also presented. in particular, we show: for all i ≥ 1, every language in rnci (that is nco-hard under ncz-reductions) has a program checker in rnci-1. in addition, for all i ≥ 1, every language in rnci (that is nco-hard under acz-reductions) has a program corrector, tester and checker in raci-1. this is the first time checkers are designed for a wide class of functions characterized only by its complexity, rather than by algebraic or combinatorial properties. this characterization immediately yields new and efficient checkers for languages such as graph connectivity, perfect matching and bounded-degree graph isomorphism. constant-depth checkers, testers and correctors for matrix multiplication, inversion, determinant and rank. all previous program checkers, testers and correctors for these problems run in nearly logarithmic depth. moreover, except for matrix multiplication, they all require the use of the library notion of [blum-luby-rubinfeld], in which checkers have access to a library of programs for various matrix functions, rather than only having access to a program for the function being checked. furthermore, we provide conditions under which program libraries can be eliminated. important ingredients in these results are new and very efficient checkers for complete languages in low complexity classes (e.g. nco). these constructions are based on techniques that were developed in the field of cryptography.
trapdoors for hard lattices and new cryptographic constructions. we show how to construct a variety of "trapdoor" cryptographic tools assuming the worst-case hardness of standard lattice problems (such as approximating the length of the shortest nonzero vector to within certain polynomial factors). our contributions include a new notion of trapdoor function with preimage sampling, simple and efficient "hash-and-sign" digital signature schemes, and identity-based encryption. a core technical component of our constructions is an efficient algorithm that, given a basis of an arbitrary lattice, samples lattice points from a discrete gaussian probability distribution whose standard deviation is essentially the length of the longest gram-schmidt vector of the basis. a crucial security property is that the output distribution of the algorithm is oblivious to the particular geometry of the given basis.
infeasibility of instance compression and succinct pcps for np. the or-sat problem asks, given boolean formulae φ1,...,φm each of size at most n, whether at least one of the φi's is satisfiable. we show that there is no reduction from or-sat to any set a where the length of the output is bounded by a polynomial in n, unless np ⊆ conp/poly, and the polynomial-time hierarchy collapses. this result settles an open problem proposed by bodlaender et. al. [4] and harnik and naor [15] and has a number of implications. a number of parametric $\np$ problems, including satisfiability, clique, dominating set and integer programming, are not instance compressible or polynomially kernelizable unless np ⊆ conp/poly. satisfiability does not have pcps of size polynomial in the number of variables unless np ⊆ conp/poly. an approach of harnik and naor to constructing collision-resistant hash functions from one-way functions is unlikely to be viable in its present form. (buhrman-hitchcock) there are no subexponential-size hard sets for np unless np is in co-np/poly. we also study probabilistic variants of compression, and show various results about and connections between these variants. to this end, we introduce a new strong derandomization hypothesis, the oracle derandomization hypothesis, and discuss how it relates to traditional derandomization assumptions.
the myth of the folk theorem. a well-known result in game theory known as "the folk theorem" suggests that finding nash equilibria in repeated games should be easier than in one-shot games. in contrast, we show that the problem of finding any (approximate) nash equilibrium for a three-player infinitely-repeated game is computationally intractable (even when all payoffs are in {-1,0,1}), unless all of ppad can be solved in randomized polynomial time. this is done by showing that finding nash equilibria of (k+1)-player infinitely-repeated games is as hard as finding nash equilibria of k-player one-shot games, for which ppad-hardness is known (daskalakis, goldberg and papadimitriou, 2006; chen, deng and teng, 2006; chen, teng and valiant, 2007). this also explains why no computationally-efficient learning dynamics, such as the "no regret" algorithms, can be "rational" (in general games with three or more players) in the sense that, when one's opponents use such a strategy, it is not in general a best reply to follow suit.
finding short lattice vectors within mordell's inequality. the celebrated lenstra-lenstra-lovász lattice basis reduction algorithm (lll) can naturally be viewed as an algorithmic version of hermite's inequality on hermite's constant. we present a polynomial-time blockwise reduction algorithm based on duality which can similarly be viewed as an algorithmic version of mordell's inequality on hermite's constant. this achieves a better and more natural approximation factor for the shortest vector problem than schnorr's algorithm and its transference variant by gama, howgrave-graham, koy and nguyen. furthermore, we show that this approximation factor is essentially tight in the worst case.
rethinking internet routing. internet routing introduces many interesting challenges, far beyond the basic problem of computing paths on a graph. this talk presents an overview of several open research questions in internet routing, with the broader goal of placing the design of future routing architectures on a stronger theoretical foundation.
agnostically learning decision trees. we give a query algorithm for agnostically learning decision trees with respect to the uniform distribution on inputs. given black-box access to an *arbitrary* binary function f on the n-dimensional hypercube, our algorithm finds a function that agrees with f on almost (within an epsilon fraction) as many inputs as the best size-t decision tree, in time poly(n,t,1ε). this is the first polynomial-time algorithm for learning decision trees in a harsh noise model. we also give a *proper* agnostic learning algorithm for juntas, a sub-class of decision trees, again using membership queries. conceptually, the present paper parallels recent work towards agnostic learning of halfspaces (kalai et al, 2005); algorithmically, it is more challenging. the core of our learning algorithm is a procedure to implicitly solve a convex optimization problem over the l1 ball in 2n dimensions using an approximate gradient projection method.
achieving higher magnification in context. the difficulty of accessing information details while preserving context has generated many different focus-in-context techniques. a common limitation of focus-in-context techniques is their ability to work well at high magnification. we present a set of improvements that will make high magnification in context more feasible. we demonstrate new distortion functions that effectively integrate high magnification within its context. finally, we show how lenses can be used on top of other lenses, effectively multiplying their magnification power in the same manner that a magnifying glass applied on top of another causes multiplicative magnification. the combined effect is to change feasible detail-in-context magnification factors from less than 8 to more than 40.
sketchread: a multi-domain sketch recognition engine. we present sketchread, a multi-domain sketch recognition engine capable of recognizing freely hand-drawn diagrammatic sketches. current computer sketch recognition systems are difficult to construct, and either are fragile or accomplish robustness by severely limiting the designer's drawing freedom. our system can be applied to a variety of domains by providing structural descriptions of the shapes in that domain; no training data or programming is necessary. robustness to the ambiguity and uncertainty inherent in complex, freely-drawn sketches is achieved through the use of context. the system uses context to guide the search for possible interpretations and uses a novel form of dynamically constructed bayesian networks to evaluate these interpretations. this process allows the system to recover from low-level recognition errors (e.g., a line misclassified as an arc) that would otherwise result in domain level recognition errors. we evaluated sketch-read on real sketches in two domains--family trees and circuit diagrams--and found that in both domains the use of context to reclassify low-level shapes significantly reduced recognition error over a baseline system that did not reinterpret low-level classifications. we also discuss the system's potential role in sketch based user interfaces.
a framework for unifying presentation space. making effective use of the available display space has long been a fundamental issue in user interface design. we live in a time of rapid advances in available cpu power and memory. however, the common sizes of our computational display spaces have only minimally increased or in some cases, such as hand held devices, actually decreased. in addition, the size and scope of the information spaces we wish to explore are also expanding. representing vast amounts of information on our relatively small screens has become increasingly problematic and has been associated with problems in navigation, interpretation and recognition. user interface research has proposed several differing presentation approaches to address these problems. these methods create displays that vary considerably, visually and algorithmically. we present a unified framework that provides a way of relating seemingly distinct methods, facilitating the inclusion of more than one presentation method in a single interface. furthermore, it supports extrapolation between the presentation methods it describes. of particular interest are the presentation possibilities that exist in the ranges between various distortion presentations, magnified insets and detail-in-context presentations, and between detail-in-context presentations and a full-zooming environment. this unified framework offers a geometric presentation library in which presentation variations are available independently of the mode of graphic representation. the intention is to promote the ease of exploration and experimentation into the use of varied presentation combinations.
tools for expressive text-to-speech markup. this paper describes handicapped accessible text-to-speech markup software developed for poetry and performance. most text-to-speech software allows the user to select a voice, but provides no control over performance parameters such as rate, volume, and pitch. for users with vocal disabilities, the default "computer voice" is often dreaded since it provides no personalization. evolving standards exist for text-to-speech markup (sable, java speech markup language, spoken text markup language), but few tools exist for non-experts to modify documents using these prosody options [1, 5]. furthermore, we could find fewer tools allowing for straightforward live performance using a synthesized voice [3]. thus we created an easy to learn text-to-speech markup tool that requires little training to use.
crossy: a crossing-based drawing application. we introduce crossy, a simple drawing application developed as a benchmark to demonstrate the feasibility of goal-crossing as the basis for a graphical user interface. while crossing was previously identified as a potential substitute for the classic point-and-click interaction, this work is the first to report on the practical aspects of implementing an interface solely based on goal-crossing.
metisse is not a 3d desktop! twenty years after the general adoption of overlapping windows and the desktop metaphor, modern window systems differ mainly in minor details such as window decorations or mouse and keyboard bindings. while a number of innovative window management techniques have been proposed, few of them have been evaluated and fewer have made their way into real systems. we believe that one reason for this is that most of the proposed techniques have been designed using a low fidelity approach and were never made properly available. in this paper, we present metisse, a fully functional window system specifically created to facilitate the design, the implementation and the evaluation of innovative window management techniques. we describe the architecture of the system, some of its implementation details and present several examples that illustrate its potential.
revisiting visual interface programming: creating gui tools for designers and programmers. involving graphic designers in the large-scale development of user interfaces requires tools that provide more graphical flexibility and support efficient software processes. these requirements were analysed and used in the design of the tkz-inc graphical library and the intuikit interface design environment. more flexibility is obtained through a wider palette of visual techniques and support for iterative construction of images, composition and parametric displays. more efficient processes are obtained with the use of the svg standard to import graphics, support for linking graphics and behaviour, and a unifying model-driven architecture. we describe the corresponding features of our tools, and show their use in the development of an application for airports. benefits include a wider access to high quality visual interfaces for specialised applications, and shorter prototyping and development cycles for multidisciplinary teams.
"killer app" of wearable computing: wireless force sensing body protectors for martial arts. ubiquitous and wearable computing both have the goal of pushing the computer into the background, supporting all kinds of human activities. application areas include areas such as everyday environments (e.g. clothing, home, office), promoting new forms of creative learning via physical/virtual objects, and new tools for interactive design. in this paper, we thrust ubiquitous computing into the extremely hostile environment of the sparring ring of a martial art competition. our system uses piezoelectric force sensors that transmit signals wirelessly to enable the detection of when a significant impact has been delivered to a competitor's body. the objective is to support the judges in scoring the sparring matches accurately, while preserving the goal of merging and blending into the background of the activity. the system therefore must take into account of the rules of the game, be responsive in real-time asynchronously, and often cope with untrained operators of the system. we present a pilot study of the finished prototype and detail our experience.
predictive interaction using the delphian desktop. this paper details the design and evaluation of the delphian desktop, a mechanism for online spatial prediction of cursor movements in a windows-icons-menus-pointers (wimp) environment. interaction with wimp-based interfaces often becomes a spatially challenging task when the physical interaction mediators are the common mouse and a high resolution, physically large display screen. these spatial challenges are especially evident in overly crowded windows desktops. the delphian desktop integrates simple yet effective predictive spatial tracking and selection paradigms into ordinary wimp environments in order to simplify and ease pointing tasks. predictions are calculated by tracking cursor movements and estimating spatial intentions using a computationally inexpensive online algorithm based on estimating the movement direction and peak velocity. in testing the delphian desktop effectively shortened pointing time to faraway icons, and reduced the overall physical distance the mouse (and user hand) had to mechanically traverse.
guided gesture support in the paper pda. ordinary paper offers properties of readability, fluidity, flexibility, cost, and portability that current electronic devices are often hard pressed to match. in fact, a lofty goal for many interactive systems is to be "as easy to use as pencil and paper". however, the static nature of paper does not support a number of capabilities, such as search and hyperlinking that an electronic device can provide. the paper pda project explores ways in which hybrid paper electronic interfaces can bring some of the capabilities of the electronic medium to interactions occurring on real paper. key to this effort is the invention of on-paper interaction techniques which retain the flexibility and fluidity of normal pen and paper, but which are structured enough to allow robust interpretation and processing in the digital world. this paper considers the design of a class of simple printed templates that allow users to make common marks in a fluid fashion, and allow additional gestures to be invented by the users to meet their needs, but at the same time encourages marks that are quite easy to recognize.
supporting interaction in augmented reality in the presence of uncertain spatial knowledge. a significant problem encountered when building augmented reality (ar) systems is that all spatial knowledge about the world has uncertainty associated with it. this uncertainty manifests itself as registration errors between the graphics and the physical world, and ambiguity in user interaction. in this paper, we show how estimates of the registration error can be leveraged to support predictable selection in the presence of uncertain 3d knowledge. these ideas are demonstrated in osgar, an extension to openscenegraph with explicit support for uncertainty in the 3d transformations. the osgar runtime propagates this uncertainty throughout the scene graph to compute robust estimates of the probable location of all entities in the system from the user's viewpoint, in real-time. we discuss the implementation of selection in osgar, and the issues that must be addressed when creating interaction techniques in such a system.
tangible nurbs-curve manipulation techniques using graspable handles on a large display. this paper presents tangible interaction techniques for fine-tuning one-to-one scale nurbs curves on a large display for automotive design. we developed a new graspable handle with a transparent groove that allows designers to manipulate virtual curves on a display screen directly. the use of the proposed handle leads naturally to a rich vocabulary of terms describing interaction techniques that reflect existing shape styling methods. a user test raised various issues related to the graspable user interface, two-handed input, and large-display interaction.
low-cost multi-touch sensing through frustrated total internal reflection. this paper describes a simple, inexpensive, and scalable technique for enabling high-resolution multi-touch sensing on rear-projected interactive surfaces based on frustrated total internal reflection. we review previous applications of this phenomenon to sensing, provide implementation details, discuss results from our initial prototype, and outline future directions.
automation and customization of rendered web pages. on the desktop, an application can expect to control its user interface down to the last pixel, but on the world wide web, a content provider has no control over how the client will view the page, once delivered to the browser. this creates an opportunity for end-users who want to automate and customize their web experiences, but the growing complexity of web pages and standards prevents most users from realizing this opportunity. we describe chickenfoot, a programming system embedded in the firefox web browser, which enables end-users to automate, customize, and integrate web applications without examining their source code. one way chickenfoot addresses this goal is a novel technique for identifying page components by keyword pattern matching. we motivate this technique by studying how users name web page components, and present a heuristic keyword matching algorithm that identifies the desired component from the user's name.
citrus: a language and toolkit for simplifying the creation of structured editors for code and data. direct-manipulation editors for structured data are increasingly common. while such editors can greatly simplify the creation of structured data, there are few tools to simplify the creation of the editors themselves. this paper presents citrus, a new programming language and user interface toolkit designed for this purpose. citrus offers language-level support for constraints, restrictions and change notifications on primitive and aggregate data, mechanisms for automatically creating, removing, and reusing views as data changes, a library of widgets, layouts and behaviors for defining interactive views, and two comprehensive interactive editors as an interface to the language and toolkit itself. together, these features support the creation of editors for a large class of data and code.
bridging the gap from theory to practice: the path toward innovation in human-computer interaction. how do we break away from existing tools and techniques in hci and truly innovate in a way that benefits the next generation of computer users? today, too many of our technological designs and inventions are "one off" point designs, not building on or contributing to a theoretical foundation of understanding around human perception, cognition, social behavior and physical movement. of course, these point designs can be successful in and of themselves, so why bother with theory and models? in order to mature as a field in a way that benefits users, it can be argued that we need to work more closely together and with an awareness of multiple disciplines, including not just the computer science and engineering arenas, but also psychology, sociology, and any field of human behavior. of course, this could be a daunting task-how do we know that important improvements in user interface design can be obtained? i will present a series of examples of what i consider to be significant contributions to the field of hci, each based on a multidisciplinarian, theory-driven approach. i hope to challenge the audience to creatively consider ways that their own work could be more theoretically motivated, and what it might take for more of us to move forward in that direction.
cursive: a novel interaction technique for controlling expressive avatar gesture. we are developing an interaction technique for rich nonverbal communication through an avatar. by writing a single letter on a pen tablet device, a user can express their ideas or intentions, non-verbally, using their avatar body. our system solves the difficult problem of controlling the movements of a highly articulated, 3d avatar model using a common input device within the context of an office environment. we believe that writing is a richly expressive and natural means for controlling expressive avatar gesture.
distributed mediation of ambiguous context in aware environments. many context-aware services make the assumption that the context they use is completely accurate. however, in reality, both sensed and interpreted context is often ambiguous. a challenge facing the development of realistic and deployable context-aware services, therefore, is the ability to handle ambiguous context. in this paper, we describe an architecture that supports the building of context-aware services that assume context is ambiguous and allows for mediation of ambiguity by mobile users in aware environments. we illustrate the use of our architecture and evaluate it through three example context-aware services, a word predictor system, an in/out board, and a reminder tool.
focus plus context screens: combining display technology with visualization techniques. computer users working with large visual documents, such as large layouts, blueprints, or maps perform tasks that require them to simultaneously access overview information while working on details. to avoid the need for zooming, users currently have to choose between using a sufficiently large screen or applying appropriate visualization techniques. currently available hi-res "wall-size" screens, however, are cost-intensive, space-intensive, or both. visualization techniques allow the user to more efficiently use the given screen space, but in exchange they either require the user to switch between multiple views or they introduce distortion.in this paper, we present a novel approach to simultaneously display focus and context information. focus plus context screens consist of a hi-res display and a larger low-res display. image content is displayed such that the scaling of the display content is preserved, while its resolution may vary according to which display region it is displayed in. focus plus context screens are applicable to practically all tasks that currently use overviews or fisheye views, but unlike these visualization techniques, focus plus context screens provide a single, non-distorted view. we present a prototype that seamlessly integrates an lcd with a projection screen and demonstrate four applications that we have adapted so far.
the ahi: an audio and haptic interface for contact interactions. we have implemented a computer interface that renders synchronized auditory and haptic stimuli with very low (0.5ms) latency. the audio and haptic interface (ahi) includes a pantograph haptic device that reads position input from a user and renders force output based on this input. we synthesize audio by convolving the force profile generated by user interaction with the impulse response of the virtual surface. auditory and haptic modes are tightly coupled because we produce both stimuli from the same force profile. we have conducted a user study with the ahi to verify that the 0.5ms system latency lies below the perceptual threshold for detecting separation between auditory and haptic contact events. we discuss future applications of the ahi for further perceptual studies and for synthesizing continuous contact interactions in virtual environments.
collapse-to-zoom: viewing web pages on small screen devices by interactively removing irrelevant content. overview visualizations for small-screen web browsers were designed to provide users with visual context and to allow them to rapidly zoom in on tiles of relevant content. given that content in the overview is reduced, however, users are often unable to tell which tiles hold the relevant material, which can force them to adopt a time-consuming hunt-and-peck strategy. collapse-to-zoom addresses this issue by offering an alternative exploration strategy. in addition to allowing users to zoom into relevant areas, collapse-to-zoom allows users to collapse areas deemed irrelevant, such as columns containing menus, archive material, or advertising. collapsing content causes all remaining content to expand in size causing it to reveal more detail, which increases the user's chance of identifying relevant content. collapse-to-zoom navigation is based on a hybrid between a marquee selection tool and a marking menu, called marquee menu. it offers four commands for collapsing content areas at different granularities and to switch to a full-size reading view of what is left of the page.
informal prototyping of continuous graphical interactions by demonstration. informal prototyping tools have shown great potential in facilitating the early stage design of user interfaces. how-ever, continuous interactions, an important constituent of highly interactive interfaces, have not been well supported by previous tools. these interactions give continuous visual feedback, such as geometric changes of a graphical object, in response to continuous user input, such as the movement of a mouse. we built monet, a sketch-based tool for proto-typing continuous interactions by demonstration. in monet, designers can prototype continuous widgets and their states of interest using examples. they can also demonstrate com-pound behaviors involving multiple widgets by direct ma-nipulation. monet allows continuous interactions to be eas-ily integrated with event-based, discrete interactions. con-tinuous widgets can be embedded into storyboards and their states can condition or trigger storyboard transitions. monet achieves these features by employing continuous function approximation and statistical classification techniques, without using any domain specific knowledge or assuming any application semantics. informal feedback showed that monet is a promising approach to enabling more complete tool support for early stage ui design.
novel interaction techniques for overlapping windows. this note presents several techniques to improve window management with overlapping windows: tabbed windows, turning and peeling back windows, and snapping and zipping windows.
stylecam: interactive stylized 3d navigation using integrated spatial & temporal controls. this paper describes stylecam, an approach for authoring 3d viewing experiences that incorporate stylistic elements that are not available in typical 3d viewers. a key aspect of stylecam is that it allows the author to significantly tailor what the user sees and when they see it. the resulting viewing experience can approach the visual richness and pacing of highly authored visual content such as television commercials or feature films. at the same time, stylecam allows for a satisfying level of interactivity while avoiding the problems inherent in using unconstrained camera models. the main components of stylecam are camera surfaces which spatially constrain the viewing camera; animation clips that allow for visually appealing transitions between different camera surfaces; and a simple, unified, interaction technique that permits the user to seamlessly and continuously move between spatial-control of the camera and temporal-control of the animated transitions. further, the user's focus of attention is always kept on the content, and not on extraneous interface widgets. in addition to describing the conceptual model of stylecam, its current implementation, and an example authored experience, we also present the results of an evaluation involving real users.
multi-finger and whole hand gestural interaction techniques for multi-user tabletop displays. recent advances in sensing technology have enabled a new generation of tabletop displays that can sense multiple points of input from several users simultaneously. however, apart from a few demonstration techniques [17], current user interfaces do not take advantage of this increased input bandwidth. we present a variety of multifinger and whole hand gestural interaction techniques for these displays that leverage and extend the types of actions that people perform when interacting on real physical tabletops. apart from gestural input techniques, we also explore interaction and visualization techniques for supporting shared spaces, awareness, and privacy. these techniques are demonstrated within a prototype room furniture layout application, called roomplanner.
mediating photo collage authoring. the medium of collage supports the visualization of meaningful event summaries using photographs. it can however be rather tedious to author a collage from a large collection of photographs. in this work we present an approach that supports efficient construction of a collage by assisting the user with an automatic layout procedure that can be controlled at a high level. our layout method utilizes a pre-designed template which consists of cells for photos and annotations applied to these cells. the layout is then filled by matching the metadata of photos to the annotations in the cells using an optimization algorithm. the user exercises flexibility in the authoring process by (a) maintaining high-level control through the types of constraints applied and (b) leveraging visual emphases supported by the layout algorithm. the user can of course provide fine-grained control of the final collage through direct manipulation. off-loading the tedium of collage construction to a user controlled yet automated process clears the way for rapidly generating different views of the same album and could also support the increased sharing of digital photos in the form of compact collages.
eyelook: using attention to facilitate mobile media consumption. one of the problems with mobile media devices is that they may distract users during critical everyday tasks, such as navigating the streets of a busy city. we addressed this issue in the design of eyelook: a platform for attention sensitive mobile computing. eyelook appliances use embedded low cost eyecontact sensors (ecs) to detect when the user looks at the display. we discuss two eyelook applications, seetv and seetxt, that facilitate courteous media consumption in mobile contexts by using the ecs to respond to user attention. seetv is an attentive mobile video player that automatically pauses content when the user is not looking. seetxt is an attentive speed reading application that flashes words on the display, advancing text only when the user is looking. by making mobile media devices sensitive to actual user attention, eyelook allows applications to gracefully transition users between consuming media, and managing life.
photomesa: a zoomable image browser using quantum treemaps and bubblemaps. photomesa is a zoomable image browser that uses a novel treemap algorithm to present large numbers of images grouped by directory, or other available metadata. it uses a new interaction technique for zoomable user interfaces designed for novices and family use that makes it straightforward to navigate through the space of images, and impossible to get lost.photomesa groups images using one of two new algorithms that lay out groups of objects in a 2d space-filling manner. quantum treemaps are designed for laying out images or other objects of indivisible (quantum) size. they are a variation on existing treemap algorithms in that they guarantee that every generated rectangle will have a width and height that are an integral multiple of an input object size. bubblemaps also fill space with groups of quantum-sized objects, but generate non-rectangular blobs, and utilize space more efficiently.
dt controls: adding identity to physical interfaces. in this paper, we show how traditional physical interface components such as switches, levers, knobs and touch screens can be easily modified to identify who is activating each control. this allows us to change the function per-formed by the control, and the sensory feedback provided by the control itself, dependent upon the user. an auditing function is also available that logs each user's actions. we describe a number of example usage scenarios for our tech-nique, and present two sample implementations.
diamondtouch: a multi-user touch technology. a technique for creating a touch-sensitive input device is proposed which allows multiple, simultaneous users to interact in an intuitive fashion. touch location information is determined independently for each user, allowing each touch on a common surface to be associated with a particular user. the surface generates location dependent, modulated electric fields which are capacitively coupled through the users to receivers installed in the work environment. we describe the design of these systems and their applications. finally, we present results we have obtained with a small prototype device.
real-time audio buffering for telephone applications. a system that uses an ear proximity sensor to actively manage periods of distraction during telephone conversations is described. we detect when the phone is removed from the ear, record any incoming audio, and play it back when the phone is returned to the ear. by dropping silent intervals and speeding up playback with a pitch-preserving algorithm, we quickly return to real-time without the loss of information. this real-time audio buffering technique also allows us to create a user-activated, lossless instant replay function.
rhythm modeling, visualizations and applications. people use their awareness of others' temporal patterns to plan work activities and communication. this paper presents algorithms for programatically detecting and modeling temporal patterns from a record of online presence data. we describe analytic and end-user visualizations of rhythmic patterns and the tradeoffs between them. we conducted a design study that explored the accuracy of the derived rhythm models compared to user perceptions, user preference among the visualization alternatives, and users' privacy preferences. we also present a prototype application based on the rhythm model that detects when a person is "away" for an extended period and predicts their return. we discuss the implications of this technology on the design of computer-mediated communication.
combining crossing-based and paper-based interaction paradigms for dragging and dropping between overlapping windows. despite novel interaction techniques proposed for virtual desktops, common yet challenging tasks remain to be investigated. dragging and dropping between overlapping windows is one of them. the fold-and-drop technique presented here offers a natural and efficient way of performing those tasks. we show how this technique successfully builds upon several interaction paradigms previously described, while shedding new light on them.
artistic resizing: a technique for rich scale-sensitive vector graphics. when involved in the visual design of graphical user interfaces, graphic designers can do more than providing static graphics for programmers to incorporate into applications. we describe a technique that allows them to provide examples of graphical objects at various key sizes using their usual drawing tool, then let the system interpolate their resizing behavior. we relate this technique to current practices of graphic designers, provide examples of its use and describe the underlying inference algorithm. we show how the mathematical properties of the algorithm allows the system to be predictable and explain how it can be combined with more traditional layout mechanisms.
view management for virtual and augmented reality. we describe a view-management component for interactive 3d user interfaces. by view management, we mean maintaining visual constraints on the projections of objects on the view plane, such as locating related objects near each other, or preventing objects from occluding each other. our view-management component accomplishes this by modifying selected object properties, including position, size, and transparency, which are tagged to indicate their constraints. for example, some objects may have geometric properties that are determined entirely by a physical simulation and which cannot be modified, while other objects may be annotations whose position and size are flexible.we introduce algorithms that use upright rectangular extents to represent on the view plane a dynamic and efficient approximation of the occupied space containing the projections of visible portions of 3d objects, as well as the unoccupied space in which objects can be placed to avoid occlusion. layout decisions from previous frames are taken into account to reduce visual discontinuities. we present augmented reality and virtual reality examples to which we have applied our approach, including a dynamically labeled and annotated environment.
an annotated situation-awareness aid for augmented reality. we present a situation-awareness aid for augmented reality systems based on an annotated "world in miniature." our aid is designed to provide users with an overview of their environment that allows them to select and inquire about the objects that it contains. two key capabilities are discussed that are intended to address the needs of mobile users. the aid's position, scale, and orientation are controlled by a novel approach that allows the user to inspect the aid without the need for manual interaction. as the user alternates their attention between the physical world and virtual aid, popup annotations associated with selected objects can move freely between the objects' representations in the two models.
visionwand: interaction techniques for large displays using a passive wand tracked in 3d. a passive wand tracked in 3d using computer vision techniques is explored as a new input mechanism for interacting with large displays. we demonstrate a variety of interaction techniques that exploit the affordances of the wand, resulting in an effective interface for large scale interaction. the lack of any buttons or other electronics on the wand presents a challenge that we address by developing a set of postures and gestures to track state and enable command input. we also describe the use of multiple wands, and posit designs for more complex wands in the future.
flannel: adding computation to electronic mail during transmission. in this paper, we describe flannel, an architecture for adding computational capabilities to email. flannel allows email to be modified by an application while in transit between sender and receiver. this modification is done without modification to the endpoints---mail clients---at either end. this paper also describes interaction techniques that we have developed to allow senders of email to quickly and easily select computations to be performed by flannel. through, our experience, we explain the properties that applications must have in order to be successful in the context of flannel.
docwizards: a system for authoring follow-me documentation wizards. traditional documentation for computer-based procedures is difficult to use: readers have trouble navigating long complex instructions, have trouble mapping from the text to display widgets, and waste time performing repetitive procedures. we propose a new class of improved documentation that we call follow-me documentation wizards. follow-me documentation wizards step a user through a script representation of a procedure by highlighting portions of the text, as well application ui elements. this paper presents algorithms for automatically capturing follow-me documentation wizards by demonstration, through observing experts performing the procedure. we also present our docwizards implementation on the eclipse platform. we evaluate our system with an initial user study that showing that most users have a marked preference for this form of guidance over traditional documentation.
role-based control of shared application views. collaboration often relies on all group members having a shared view of a single-user application. a common situation is a single active presenter sharing a live view of her workstation screen with a passive audience, using simple hardware-based video signal projection onto a large screen or simple bitmap-based sharing protocols. this offers simplicity and some advantages over more sophisticated software-based replication solutions, but everyone has the exact same view of the application. this conflicts with the presenter's need to keep some information and interaction details private. it also fails to recognize the needs of the passive audience, who may struggle to follow the presentation because of verbosity, display clutter or insufficient familiarity with the application.views that cater to the different roles of the presenter and the audience can be provided by custom solutions, but these tend to be bound to a particular application. in this paper we describe a general technique and implementation details of a prototype system that allows standardized role-specific views of existing single-user applications and permits additional customization that is application-specific with no change to the application source code. role-based policies control manipulation and display of shared windows and image buffers produced by the application, providing semi-automated privacy protection and relaxed verbosity to meet both presenter and audience needs.
the "mighty mouse" multi-screen collaboration tool. many computer operating systems provide seamless support for multiple display screens, but there are few cross-platform tools for collaborative use of multiple computers in a shared display environment. mighty mouse is a novel groupware tool built on the public domain vnc protocol. it is tailored specifically for face-to-face collaboration where multiple heterogeneous computers (usually laptops) are viewed simultaneously (usually via projectors) by people working together on a variety of applications under various operating systems. mighty mouse uses only the remote input capability of vnc, but enhances this with various features to support flexible movement between the various platforms, "floor control" to facilitate smooth collaboration, and customization features to accommodate different user, platform, and application preferences in a relatively seamless manner. the design rationale arises from specific observations about how people collaborate in meetings, which allows certain simplifying assumptions to be made in the implementation.
conducting a realistic electronic orchestra. personal orchestra is the first system to let users conduct an actual audio and video recording of an orchestra, using an infrared baton to control tempo, volume, and instrument sections. a gesture recognition algorithm interprets user input, and a novel high-fidelity playback algorithm renders audio and video data at variable speed without time-stretching artifacts. the system is installed as a public exhibit in the house of music vienna.
tracking menus. we describe a new type of graphical user interface widget, known as a "tracking menu." a tracking menu consists of a cluster of graphical buttons, and as with traditional menus, the cursor can be moved within the menu to select and interact with items. however, unlike traditional menus, when the cursor hits the edge of the menu, the menu moves to continue tracking the cursor. thus, the menu always stays under the cursor and close at hand.in this paper we define the behavior of tracking menus, show unique affordances of the widget, present a variety of examples, and discuss design characteristics. we examine one tracking menu design in detail, reporting on usability studies and our experience integrating the technique into a commercial application for the tablet pc. while user interface issues on the tablet pc, such as preventing round trips to tool palettes with the pen, inspired tracking menus, the design also works well with a standard mouse and keyboard configuration.
aesthetic information collages: generating decorative displays that contain information. normally, the primary purpose of an information display is to convey information. if information displays can be aesthetically interesting, that might be an added bonus. this paper considers an experiment in reversing this imperative. it describes the kandinsky system which is designed to create displays which are first aesthetically interesting, and then as an added bonus, able to convey information. the kandinsky system works on the basis of aesthetic properties specified by an artist (in a visual form). it then explores a space of collages composed from information bearing images, using an optimization technique to find compositions which best maintain the properties of the artist's aesthetic expression.
specifying behavior and semantic meaning in an unmodified layered drawing package. in order to create and use rich custom appearances, designers are often forced to introduce an unnatural gap into the design process. for example, a designer creating a skin for a music player must separately specify the appearance of the elements in the music player skin and the mapping between these visual elements and the functionality provided by the music player. this gap between appearance and semantic meaning creates a number of problems. we present a set of techniques that allows designers to use their preferred drawing tool to specify both appearance and semantic meaning. we demonstrate our techniques in an unmodified version of adobe photoshop&reg;, but our techniques are general and adaptable to nearly any layered drawing package.
gadget: a toolkit for optimization-based approaches to interface and display generation. recent work is beginning to reveal the potential of numerical optimization as an approach to generating interfaces and displays. optimization-based approaches can often allow a mix of independent goals and constraints to be blended in ways that would be difficult to describe algorithmically. while optimization-based techniques appear to offer several potential advantages, further research in this area is hampered by the lack of appropriate tools. this paper presents gadget, an experimental toolkit to support optimization for interface and display generation. gadget provides convenient abstractions of many optimization concepts. gadget also provides mechanisms to help programmers quickly create optimizations, including an efficient lazy evaluation framework, a powerful and configurable optimization structure, and a library of reusable components. together these facilities provide an appropriate tool to enable exploration of a new class of interface and display generation techniques.
zoom-and-pick: facilitating visual zooming and precision pointing with interactive handheld projectors. designing interfaces for interactive handheld projectors is an exiting new area of research that is currently limited by two problems: hand jitter resulting in poor input control, and possible reduction of image resolution due to the needs of image stabilization and warping algorithms. we present the design and evaluation of a new interaction technique, called zoom-and-pick, that addresses both problems by allowing the user to fluidly zoom in on areas of interest and make accurate target selections. subtle design features of zoom-and-pick enable pixel-accurate pointing, which is not possible in most freehand interaction techniques. our evaluation results indicate that zoom-and-pick is significantly more accurate than the standard pointing technique described in our previous work.
a widget framework for augmented interaction in scape. we have previously developed a collaborative infrastructure called scape - an acronym for stereoscopic collaboration in augmented and projective environments - that integrates the traditionally separate paradigms of virtual and augmented reality. in this paper, we extend scape by formalizing its underlying mathematical framework and detailing three augmented widgets constructed via this framework: cocylinder, magnifier, and cocube. these devices promote intuitive ways of selecting, examining, and sharing synthetic objects, and retrieving associated documentary text. finally we present a testbed application to showcase scape's capabilities for interaction in large, augmented virtual environments.
dtlens: multi-user tabletop spatial data exploration. supporting groups of individuals exploring large maps and design diagrams on interactive tabletops is still an open research problem. today's geospatial, mechanical engineering and cad design applications are mostly single-user, keyboard and mouse-based desktop applications. in this paper, we present the design of and experience with dtlens, a new zoom-in-context, multi-user, two-handed, multi-lens interaction technique that enables group exploration of spatial data with multiple individual lenses on the same direct-touch interactive tabletop. dtlens provides a set of consistent interactions on lens operations, thus minimizes tool switching by users during spatial data exploration.
clip, connect, clone: combining application elements to build custom interfaces for information access. many applications provide a form-like interface for requesting information: the user fills in some fields, submits the form, and the application presents corresponding results. such a procedure becomes burdensome if (1) the user must submit many different requests, for example in pursuing a trial-and-error search, (2) results from one application are to be used as inputs for another, requiring the user to transfer them by hand, or (3) the user wants to compare results, but only the results from one request can be seen at a time. we describe how users can reduce this burden by creating custom interfaces using three mechanisms: clipping of input and result elements from existing applications to form cells on a spreadsheet; connecting these cells using formulas, thus enabling result transfer between applications; and cloning cells so that multiple requests can be handled side by side. we demonstrate a prototype of these mechanisms, initially specialised for handling web applications, and show how it lets users build new interfaces to suit their individual needs.
preference elicitation for interface optimization. decision-theoretic optimization is becoming a popular tool in the user interface community, but creating accurate cost (or utility) functions has become a bottleneck --- in most cases the numerous parameters of these functions are chosen manually, which is a tedious and error-prone process. this paper describes arnauld, a general interactive tool for eliciting user preferences concerning concrete outcomes and using this feedback to automatically learn a factored cost function. we empirically evaluate our machine learning algorithm and two automatic query generation approaches and report on an informal user study.
classroom bridge: using collaborative public and desktop timelines to support activity awareness. classroom bridge supports activity awareness by facilitating planning and goal revision in collaborative, project-based middle school science. it integrates large-screen and desktop views of project times to support incidental creation of awareness information through routine document transactions, integrated presentation of awareness information as part of workspace views, and public access to subgroup activity. it demonstrates and develops an object replication approach to integrating synchronous and asynchronous distributed work for a platform incorporating both desktop and large-screen devices. this paper describes an implementation of these concepts with preliminary evaluation data, using timeline-based user interfaces.
moving markup: repositioning freeform annotations. freeform digital ink annotation allows readers to interact with documents in an intuitive and familiar manner. such marks are easy to manage on static documents, and provide a familiar annotation experience. in this paper, we describe an implementation of a freeform annotation system that accommodates dynamic document layout. the algorithm preserves the correct position of annotations when documents are viewed with different fonts or font sizes, with different aspect ratios, or on different devices. we explore a range of heuristics and algorithms required to handle common types of annotation, and conclude with a discussion of possible extensions to handle special kinds of annotations and changes to documents.
smartmusickiosk: music listening station with chorus-search function. this paper describes a new music-playback interface for trial listening, smartmusickiosk. in music stores, short trial listening of cd music is not usually a passive experience -- customers often search out the chorus or "hook" of a song using the fast-forward button. listening of this type, however, has not been traditionally supported. this research achieves a function for jumping to the chorus section and other key parts of a song plus a function for visualizing song structure. these functions make it easier for a listener to find desired parts of a song and thereby facilitate an active listening experience. the proposed functions are achieved by an automatic chorus-section detecting method, and the results of implementing them as a listening station have demonstrated their usefulness.
physical user interfaces: what they are and how to build them. physical user interfaces are special purpose devices that can be situated in a real-world setting. unlike general purpose computers, they are typically designed for particular contexts and uses. in this survey, i present an introductory tour of this new interface genre. first, i will summarize what they are by describing several design niches for these devices: ubiquitous computing, tangible media, foreground and ambient devices, collaborative devices, roomware, and physical controls. examples will be plentiful, and will range from the playful, to the artistic, and to the serious. second, i will introduce technologies that are suitable for software professionals who wish to prototype these physical user interfaces. the commercially available phidgets (www.phidgets.com) are used as a case study of what is available and what can be done with them.
customizable physical interfaces for interacting with conventional applications. when using today's productivity applications, people rely heavily on graphical controls (gui widgets) as the way to invoke application functions and to obtain feedback. yet we all know that certain controls can be difficult or tedious to find and use. as an alternative, a customizable physical interface lets an end-user easily bind a modest number of physical controls to similar graphical counterparts. the user can then use the physical control to invoke the corresponding graphical control's function, or to display its graphical state in a physical form. to show how customizable physical interfaces work, we present examples that illustrate how our combined phidgets&reg; and widget tap packages are used to link existing application widgets to physical controls. while promising, our implementation prompts a number of issues relevant to others pursuing interface customization.
phidgets: easy development of physical interfaces through physical widgets. physical widgets or phidgets are to physical user interfaces what widgets are to graphical user interfaces. similar to widgets, phidgets abstract and package input and output devices: they hide implementation and construction details, they expose functionality through a well-defined api, and they have an (optional) on-screen interactive interface for displaying and controlling device state. unlike widgets, phidgets also require: a connection manager to track how devices appear on-line; a way to link a software phidget with its physical counterpart; and a simulation mode to allow the programmer to develop, debug and test a physical interface even when no physical device is present. our evaluation shows that everyday programmers using phidgets can rapidly develop physical interfaces.
multi-finger gestural interaction with 3d volumetric displays. volumetric displays provide interesting opportunities and challenges for 3d interaction and visualization, particularly when used in a highly interactive manner. we explore this area through the design and implementation of techniques for interactive direct manipulation of objects with a 3d volumetric display. motion tracking of the user's fingers provides for direct gestural interaction with the virtual objects, through manipulations on and around the display's hemispheric enclosure. our techniques leverage the unique features of volumetric displays, including a 360&deg; viewing volume that enables manipulation from any viewpoint around the display, as well as natural and accurate perception of true depth information in the displayed 3d scene. we demonstrate our techniques within a prototype 3d geometric model building application.
paper augmented digital documents. paper augmented digital documents (padds) are digital documents that can be manipulated either on a computer screen or on paper. padds, and the infrastructure supporting them, can be seen as a bridge between the digital and the paper worlds. as digital documents, padds are easy to edit, distribute and archive; as paper documents, padds are easy to navigate, annotate and well accepted in social settings. the chimeric nature of padds make them well suited for many tasks such as proofreading, editing, and annotation of large format document like blueprints.we are presenting an architecture which supports the seamless manipulation of padds using today's technologies and reports on the lessons we learned while implementing the first padd system.
fluid interaction with high-resolution wall-size displays. this paper describes new interaction techniques for direct pen-based interaction on the interactive mural, a large (6&prime;x3.5&prime;) high resolution (64 dpi) display. they have been tested in a digital brainstorming tool that has been used by groups of professional product designers. our "interactive wall" metaphor for interaction has been guided by several goals: to support both free-hand sketching and high-resolution materials, such as images, 3d models and gui application windows; to present a visual appearance that does not clutter the content with control devices; and to support fluid interaction, which minimizes the amount of attention demanded and interruption due to the mechanics of the interface. we have adapted and extended techniques that were developed for electronic whiteboards and generalized the use of the flowmenu to execute a wide variety of actions in a single pen stroke, while these techniques were designed for a brainstorming tool, they are very general and can be used in a wide variety of application domains using interactive surfaces.
synchronous gestures for multiple persons and computers. this research explores distributed sensing techniques for mobile devices using synchronous gestures. these are patterns of activity, contributed by multiple users (or one user with multiple devices), which take on a new meaning when they occur together in time, or in a specific sequence in time. to explore this new area of inquiry, this work uses tablet computers augmented with touch sensors and two-axis linear accelerometers (tilt sensors). the devices are connected via an 802.11 wireless network and synchronize their time-stamped sensor data. this paper describes a few practical examples of interaction techniques using synchronous gestures such as dynamically tiling together displays by physically bumping them together, discusses implementation issues, and speculates on further possibilities for synchronous gestures.
toward more sensitive mobile phones. although cell phones are extremely useful, they can be annoying and distracting to owners and others nearby. we describe sensing techniques intended to help make mobile phones more polite and less distracting. for example, our phone's ringing quiets as soon as the user responds to an incoming call, and the ring mutes if the user glances at the caller id and decides not to answer. we also eliminate the need to press a talk button to answer an incoming call by recognizing if the user picks up the phone and listens to it.
satin: a toolkit for informal ink-based applications. software support for making effective pen-based applications is currently rudimentary. to facilitate the creation of such applications, we have developed satin, a java-based toolkit designed to support the creation of applications that leverage the informal nature of pens. this support includes a scenegraph for manipulating and rendering objects; support for zooming and rotating objects, switching between multiple views of an object, integration of pen input with interpreters, libraries for manipulating ink strokes, widgets optimized for pens, and compatibility with java's swing toolkit. satin includes a generalized architecture for handling pen input, consisting of recognizers, interpreters, and multi-interpreters. in this paper, we describe the functionality and architecture of satin, using two applications built with satin as examples.
a modular geometric constraint solver for user interface applications. constraints have been playing an important role in the user interface field since its infancy. a prime use of constraints in this field is to automatically maintain geometric layouts of graphical objects. to facilitate the construction of constraint-based user interface applications, researchers have proposed various constraint satisfaction methods and constraint solvers. most previous research has focused on either local propagation or linear constraints, excluding more general nonlinear ones. however, nonlinear geometric constraints are practically useful to various user interfaces, e.g., drawing editors and information visualization systems. in this paper, we propose a novel constraint solver called chorus, which realizes various powerful nonlinear geometric constraints such as euclidean geometric, non-overlapping, and graph layout constraints. a key feature of chorus is its module mechanism that allows users to define new kinds of geometric constraints. also, chorus supports "soft" constraints with hierarchical strengths or preferences (i.e., constraint hierarchies). we describe its framework, algorithm, implementation, and experimental results.
using light emitting diode arrays as touch-sensitive input and output devices. light emitting diodes (leds) offer long life, low cost, efficiency, brightness, and a full range of colors. because of these properties, they are widely used for simple displays in electronic devices. a previously characterized, but little known property of leds allows them to be used as photo sensors. in this paper, we show how this capability can be used to turn unmodified, off the shelf, led arrays into touch sensitive input devices (while still remaining capable of producing output). the technique is simple and requires little or no extra hardware - in some cases operating with the same micro-controller based circuitry normally used to produce output, requiring only software changes. we will describe a simple hybrid input/output device prototype implemented with this technique, and discuss the design opportunities that this type of device opens up.
the magglite post-wimp toolkit: draw it, connect it and run it. this article presents magglite, a toolkit and sketch-based interface builder allowing fast and interactive design of post-wimp user interfaces. magglite improves design of advanced uis thanks to its novel <i>mixed-graph</i> architecture that dynamically combines scene-graphs with interaction-graphs. <i>scene-graphs</i> provide mechanisms to describe and produce rich graphical effects, whereas <i>interaction-graphs</i> allow expressive and fine-grained description of advanced interaction techniques and behaviors such as multiple pointers management, toolglasses, bimanual interaction, gesture, and speech recognition. both graphs can be built interactively by sketching the ui and specifying the interaction using a dataflow visual language. communication between the two graphs is managed at runtime by components we call <i>interaction access points</i>. while developers can extend the toolkit by refining built-in generic mechanisms, ui designers can quickly and interactively design, prototype and test advanced user interfaces by applying the magglite principle: "draw it, connect it and run it".
dynamic approximation of complex graphical constraints by linear constraints. current constraint solving techniques for interactive graphical applications cannot satisfactorily handle constraints such as non-overlap, or containment within non-convex shapes or shapes with smooth edges. we present a generic new technique for efficiently handling such kinds of constraints based on trust regions and linear arithmetic constraint solving. our approach is to model these more complex constraints by a dynamically changing conjunction of linear constraints. at each stage, these give a local approximation to the complex constraints. during direct manipulation, linear constraints in the current local approximation can become active indicating that the current solution is on the boundary of the trust region for the approximation. the associated complex constraint is notified and it may choose to modify the current linear approximation. empirical evaluation demonstrates that it is possible to (re-)solve systems of linear constraints that are dynamically approximating complex constraints such as non-overlap sufficiently quickly to support direct manipulation in interactive graphical applications.
voice as sound: using non-verbal voice input for interactive control. we describe the use of non-verbal features in voice for direct control of interactive applications. traditional speech recognition interfaces are based on an indirect, conversational model. first the user gives a direction and then the system performs certain operation. our goal is to achieve more direct, immediate interaction like using a button or joystick by using lower-level features of voice such as pitch and volume. we are developing several prototype interaction techniques based on this idea, such as "control by continuous voice", "rate-based parameter control by pitch," and "discrete parameter control by tonguing." we have implemented several prototype systems, and they suggest that voice-as-sound techniques can enhance traditional voice recognition approach.
a suggestive interface for 3d drawing. this paper introduces a new type of interface for 3d drawings that improves the usability of gestural interfaces and augments typical command-based modeling systems. in our suggestive interface, the user gives hints about a disired operation to the system by highlighting related geometric components in the scene. the system then infers possible operations based on the hints and presents the results of these operations as small thumbnails. the user complets the editing operation simply by clicking on the disired thumbnail. the hinting mechanism lets the user specify geometric relations among graphical components in the scene, and the multiple thumbnail suggestions make it possible to define many operations with relatively few distinct hint patterns. the suggestive interface system is implemented as a set o suggestion engines working in parallel, and is easily extended by adding customized engines. our prototype 3d drawing system, chateau, shows that a suggestive interface can effectively support construction of various 3d drawings.
clothing manipulation. this paper presents interaction techniques (and the underlying implementations) for putting clothes on a 3d character and manipulating them. the user paints freeform marks on the clothes and corresponding marks on the 3d character; the system then puts the clothes around the body so that corresponding marks match. internally, the system grows the clothes on the body surface around the marks while maintaining basic cloth constraints via simple relaxation steps. the entire computation takes a few seconds. after that, the user can adjust the placement of the clothes by an enhanced dragging operation. unlike standard dragging where the user moves a set of vertices in a single direction in 3d space, our dragging operation moves the cloth along the body surface to make possible more flexible operations. the user can apply pushpins to fix certain cloth points during dragging. the techniques are ideal for specifying an initial cloth configuration before applying a more sophisticated cloth simulation.
interacting with hidden content using content-aware free-space transparency. we present <i>content-aware free-space transparency</i>, an approach to viewing and manipulating the otherwise hidden content of obscured windows through unimportant regions of overlapping windows. traditional approaches to interacting with otherwise obscured content in a window system render an entire window uniformly transparent. in contrast, content-aware free-space transparency uses opaque-to-transparent gradients and image-processing filters to minimize the interference from overlapping material, based on properties of that material. by increasing the amount of simultaneously visible content and allowing basic interaction with otherwise obscured content, without modifying window geometry, we believe that free-space transparency has the potential to improve user productivity.
dynamo: a public interactive surface supporting the cooperative sharing and exchange of media. in this paper we propose a novel way of supporting occasional meetings that take place in unfamiliar public places, which promotes lightweight, visible and fluid collaboration. our central idea is that the sharing and exchange of information occurs across public surfaces that users can easily access and interact with. to this end, we designed and implemented dynamo, a communal multi-user interactive surface. the surface supports the cooperative sharing and exchange of a wide range of media that can be brought to the surface by users that are remote from their familiar organizational settings.
pointright: experience with flexible input redirection in interactive workspaces. we describe the design of and experience with pointright, a peer-to-peer pointer and keyboard redirection system that operates in multi-machine, multi-user environments. pointright employs a geometric model for redirecting input across screens driven by multiple independent machines and operating systems. it was created for interactive workspaces that include large, shared displays and individual laptops, but is a general tool that supports many different configurations and modes of use. although previous systems have provided for re-routing pointer and keyboard control, in this paper we present a more general and flexible system, along with an analysis of the types of re-binding that must be handled by any pointer redirection system this paper describes the system, the ways in which it has been used, and the lessons that have been learned from its use over the last two years.
a1: end-user programming for web-based system administration. system administrators work with many different tools to manage and fix complex hardware and software infrastructure in a rapidly paced work environment. through extensive field studies, we observed that they often build and share custom tools for specific tasks that are not supported by vendor tools. recent trends toward web-based management consoles offer many advantages but put an extra burden on system administrators, as customization requires web programming, which is beyond the skills of many system administrators. to meet their needs, we developed a1, a spreadsheet-based environment with a task-specific system-administration language for quickly creating small tools or migrating existing scripts to run as web portlets. using a1, system administrators can build spreadsheets to access remote and heterogeneous systems, gather and integrate status data, and orchestrate control of disparate systems in a uniform way. a preliminary user study showed that in just a few hours, system administrators can learn to use a1 to build relatively complex tools from scratch.
hierarchical parsing and recognition of hand-sketched diagrams. a long standing challenge in pen-based computer interaction is the ability to make sense of informal sketches. a main difficulty lies in reliably extracting and recognizing the intended set of visual objects from a continuous stream of pen strokes. existing pen-based systems either avoid these issues altogether, thus resulting in the equivalent of a drawing program, or rely on algorithms that place unnatural constraints on the way the user draws. as one step toward alleviating these difficulties, we present an integrated sketch parsing and recognition approach designed to enable natural, fluid, sketch-based computer interaction. the techniques presented in this paper are oriented toward the domain of network diagrams. in the first step of our approach, the stream of pen strokes is examined to identify the arrows in the sketch. the identified arrows then anchor a spatial analysis which groups the uninterpreted strokes into distinct clusters, each representing a single object. finally, a trainable shape recognizer, which is informed by the spatial analysis, is used to find the best interpretations of the clusters. based on these concepts, we have built simusketch, a sketch-based interface for matlab's simulink software package. an evaluation of simusketch has indicated that even novice users can effectively utilize our system to solve real engineering problems without having to know much about the underlying recognition techniques.
olfactory display. the last twenty years have seen enormous leaps forward in computers' abilities to generate sound and video. what happens when computers can produce scents on demand? in this talk, i present three approaches to this question. i first look at human olfactory processing: what is our olfactory bandwidth, and what are the limitations of our sense of smell? i then explore the use of scent to accompany other media, from historical examples like sense-o-rama and aromarama, to more recent work including firefighter training systems, augmented gaming, and food and beverage applications. finally, i look at the possibilities of olfactory output as an ambient display medium. i conclude with an overview of current computer-controlled olfactory output devices: off the shelf solutions for incorporating scent into user interface applications.
a remote control interface for large displays. we describe a new widget and interaction technique, known as a "frisbee," for interacting with areas of a large display that are difficult or impossible to access directly. a frisbee is simply a portal to another part of the display. it consists of a local "telescope" and a remote "target". the remote data surrounded by the target is drawn in the telescope and interactions performed within it are applied on the remote data. in this paper we define the behavior of frisbees, show unique affordances of the widget, and discuss design characteristics. we have implemented a test application and report on an experiment that shows the benefit of using the frisbee on a large display. our results suggest that the frisbee is preferred over walking back and forth to the local and remote spaces at a distance of 4.5 feet.
video-based document tracking: unifying your physical and electronic desktops. this paper presents an approach for tracking paper documents on the desk over time and automatically linking them to the corresponding electronic documents using an overhead video camera. we demonstrate our system in the context of two scenarios, <i>paper tracking</i> and <i>photo sorting</i>. in the paper tracking scenario, the system tracks changes in the stacks of printed documents and books on the desk and builds a complete representation of the spatial structure of the desktop. when users want to find a printed document buried in the stacks, they can query the system based on appearance, keywords, or access time. the system also provides a <i>remote desktop</i> interface for directly browsing the physical desktop from a remote location. in the photo sorting scenario, users sort printed photographs into physical stacks on the desk. the systemautomatically recognizes the photographs and organizes the corresponding digital photographs into separate folders according to the physical arrangement. our framework provides a way to unify the physical and electronic desktops without the need for a specialized physical infrastructure except for a video camera.
the designers' outpost: a tangible interface for collaborative web site. in our previous studies into web design, we found that pens, paper, walls, and tables were often used for explaining, developing, and communicating ideas during the early phases of design. these wall-scale paper-based design practices inspired the designers' outpost, a tangible user interface that combines the affordances of paper and large physical workspaces with the advantages of electronic media to support information design. with outpost, users collaboratively author web site information architectures on an electronic whiteboard using physical media (post-it notes and images), structuring and annotating that information with electronic pens. this interaction is enabled by a touch-sensitive smart board augmented with a robust computer vision system, employing a rear-mounted video camera for capturing movement and a front-mounted high-resolution camera for capturing ink. we conducted a participatory design study with fifteen professional web designers. the study validated that outpost supports information architecture work practice, and led to our adding support for fluid transitions to other tools.
considering the direction of cursor movement for efficient traversal of cascading menus. cascading menus are commonly seen in most gui systems. however, people sometimes choose the wrong items by mistake, or become frustrated when submenus pop up unnecessarily. this paper proposes two methods for improving the usability of cascading menus. the first uses the direction of cursor movement to change the menu behavior: horizontal motion opens/closes submenus, while vertical motion changes the highlight within the current menu. this feature can reduce cursor movement errors. the second causes a submenu to pop up at the position where horizontal motion occurs. this is expected to reduce the length of the movement path for menu traversal. a user study showed that our methods reduce menu selection times, shorten search path lengths, and prevent unexpected submenu appearance and disappearance.
sensing and visualizing spatial relations of mobile devices. location information can be used to enhance interaction with mobile devices. while many location systems require instrumentation of the environment, we present a system that allows devices to measure their spatial relations in a true peer-to-peer fashion. the system is based on custom sensor hardware implemented as usb dongle, and computes spatial relations in real-time. in extension of this system we propose a set of spatialized widgets for incorporation of spatial relations in the user interface. the use of these widgets is illustrated in a number of applications, showing how spatial relations can be employed to support and streamline interaction with mobile devices.
simplicial families of drawings. in this paper we present a method for helping artists make artwork more accessible to casual users. we focus on the specific case of drawings, showing how a small number of drawings can be transformed into a richer object containing an entire family of similar drawings. this object is represented as a simplicial complex approximating a set of valid interpolations in configuration space. the artist does not interact directly with the simplicial complex. instead, she guides its construction by answering a specially chosen set of yes/no questions. by combining the flexibility of a simplicial complex with direct human guidance, we are able to represent very general constraints on membership in a family. the constructed simplicial complex supports a variety of algorithms useful to an end user, including random sampling of the space of drawings, constrained interpolation between drawings, projection of another drawing into the family, and interactive exploration of the family.
shark: a large vocabulary shorthand writing system for pen-based computers. zhai and kristensson (2003) presented a method of speed-writing for pen-based computing which utilizes gesturing on a stylus keyboard for familiar words and tapping for others. in shark<sup>2</sup>:, we eliminated the necessity to alternate between the two modes of writing, allowing any word in a large vocabulary (e.g. 10,000-20,000 words) to be entered as a shorthand gesture. this new paradigm supports a gradual and seamless transition from visually guided tracing to recall-based gesturing. based on the use characteristics and human performance observations, we designed and implemented the architecture, algorithms and interfaces of a high-capacity multi-channel pen-gesture recognition system. the system's key components and performance are also reported.
tsi (teething ring sound instrument): a design of the sound instrument for the baby. in this paper, we will describe the tsi (teething ring sound instrument), a new sound instrument given to babies, which consists of a teething ring, a knob, an i-cubex digitizer [1] and a computer which processes midi messages. the tsi is designed to bring music experience to baby with the movement of the babies reflex sucking motion. we provided the tsi to a baby and observed her action to the tsi and her reaction to the generated sound. this experiment showed the high potential of the tsi.
talkback: a conversational answering machine. current asynchronous voice messaging interfaces, like voicemail, fail to take advantage of our conversational skills. talkback restores conversational turn-taking to voicemail retrieval by dividing voice messages into smaller sections based on the most significant silent and filled pauses and pausing after each to record a response. the responses are composed into a reply, alternating with snippets of the original message for context. talkback is built into a digital picture frame; the recipient touches a picture of the caller to hear each segment of the message in turn. the minimal interface models synchronous interaction and facilitates asynchronous voice messaging. talkback can also present a voice-annotated slide show which it receives over the internet.
bimanual and unimanual image alignment: an evaluation of mouse-based techniques. we present an evaluation of three mouse-based techniques for aligning digital images. we investigate the physical image alignment task and discuss the implications for interacting with virtual images. in a formal evaluation we show that a symmetric bimanual technique outperforms an asymmetric bimanual technique which in turn outperforms a unimanual technique. we show that even after mode switching times are removed, the symmetric technique outperforms the single mouse technique. subjects also exhibited more parallel interaction using the symmetric technique than when using the asymmetric technique.
a molecular architecture for creating advanced guis. this paper presents a new gui architecture for creating advanced interfaces. this model is based on a limited set of general principles that improve flexibility and provide capabilities for implementing information visualization techniques such as magic lenses, transparent tools or semantic zooming. this architecture also makes it possible to create multiple views and application-sharing systems (by sharing views on multiple computer screens) in a simple and uniform way and to handle bimanual interaction and multiple pointers. an experimental toolkit called ubit was implemented to test the feasibility of this approach. it is based on a pseudo-declarative c++ api that tries to simplify gui programming by providing a higher level of abstraction.
haptic pen: a tactile feedback stylus for touch screens. in this paper we present a system for providing tactile feedback for stylus-based touch-screen displays. the haptic pen is a simple low-cost device that provides individualized tactile feedback for multiple simultaneous users and can operate on large touch screens as well as ordinary surfaces. a pressure-sensitive stylus is combined with a small solenoid to generate a wide range of tactile sensations. the physical sensations generated by the haptic pen can be used to enhance our existing interaction with graphical user interfaces as well as to help make modern computing systems more accessible to those with visual or motor impairments.
automatic projector calibration with embedded light sensors. projection technology typically places several constraints on the geometric relationship between the projector and the projection surface to obtain an undistorted, properly sized image. in this paper we describe a simple, robust, fast, and low-cost method for automatic projector calibration that eliminates many of these constraints. we embed light sensors in the target surface, project gray-coded binary patterns to discover the sensor locations, and then prewarp the image to accurately fit the physical features of the projection surface. this technique can be expanded to automatically stitch multiple projectors, calibrate onto non-planar surfaces for object decoration, and provide a method for simple geometry acquisition.
the kinetic typography engine: an extensible system for animating expressive text. kinetic typography --- text that uses movement or other temporal change --- has recently emerged as a new form of communication. as we hope to illustrate in this paper, kinetic typography can be seen as bringing some of the expressive power of film --- such as its ability to convey emotion, portray compelling characters, and visually direct attention --- to the strong communicative properties of text. although kinetic typography offers substantial promise for expressive communications, it has not been widely exploited outside a few limited application areas (most notably in tv advertising). one of the reasons for this has been the lack of tools directly supporting it, and the accompanying difficulty in creating dynamic text. this paper presents a first step in remedying this situation --- an extensible and robust system for animating text in a wide variety of forms. by supporting an appropriate set of carefully factored abstractions, this engine provides a relatively small set of components that can be plugged together to create a wide range of different expressions. it provides new techniques for automating effects used in traditional cartoon animation, and provides specific support for typographic manipulations.
moveable interactive projected displays using projector based tracking. video projectors have typically been used to display images on surfaces whose geometric relationship to the projector remains constant, such as walls or pre-calibrated surfaces. in this paper, we present a technique for projecting content onto moveable surfaces that adapts to the motion and location of the surface to simulate an active display. this is accomplished using a projector based location tracking techinque. we use light sensors embedded into the moveable surface and project low-perceptibility gray-coded patterns to first discover the sensor locations, and then incrementally track them at interactive rates. we describe how to reduce the perceptibility of tracking patterns, achieve interactive tracking rates, use motion modeling to improve tracking performance, and respond to sensor occlusions. a group of tracked sensors can define quadrangles for simulating moveable displays while single sensors can be used as control inputs. by unifying the tracking and display technology into a single mechanism, we can substantially reduce the cost and complexity of implementing applications that combine motion tracking and projected imagery.
visual tracking of bare fingers for interactive surfaces. visual tracking of bare fingers allows more direct manipulation of digital objects, multiple simultaneous users interacting with their two hands, and permits the interaction on large surfaces, using only commodity hardware. after presenting related work, we detail our implementation. its design is based on our modeling of two classes of algorithms that are key to the tracker: image differencing segmentation (ids) and fast rejection filters (frf). we introduce a new chromatic distance for ids and a frf that is independent to finger rotation. the system runs at full frame rate (25 hz) with an average total system latency of 80 ms, independently of the number of tracked fingers. when used in a controlled environment such as a meeting room, its robustness is satisfying for everyday use.
topiary: a tool for prototyping location-enhanced applications. location-enhanced applications use the location of people, places, and things to augment or streamline interaction. location-enhanced applications are just starting to emerge in several different domains, and many people believe that this type of application will experience tremendous growth in the near future. however, it currently requires a high level of technical expertise to build location-enhanced applications, making it hard to iterate on designs. to address this problem we introduce topiary, a tool for rapidly prototyping location-enhanced applications. topiary lets designers create a map that models the location of people, places, and things; use this active map to demonstrate scenarios depicting location contexts; use these scenarios in creating storyboards that describe interaction sequences; and then run these storyboards on mobile devices, with a wizard updating the location of people and things on a separate device. we performed an informal evaluation with seven researchers and interface designers and found that they reacted positively to the concept.
papiercraft: a command system for interactive paper. knowledge workers use paper extensively for document reviewing and note-taking due to its versatility and simplicity of use. as users annotate printed documents and gather notes, they create a rich web of annotations and cross references. unfortunately, as paper is a static media, this web often gets trapped in the physical world. while several digital solutions such as xlibris [15] and digital desk [18] have been proposed, they suffer from a small display size or onerous hardware requirements.to address these limitations, we propose papiercraft, a gesture-based interface that allows users to manipulate digital documents directly using their printouts as proxies. using a digital pen, users can annotate a printout or draw command gestures to indicate operations such as copying a document area, pasting an area previously copied, or creating a link. upon pen synchronization, our infrastructure executes these commands and presents the result in a customized viewer. in this paper we describe the design and implementation of the papiercraft command system, and report on early user feedback.
automatic image retargeting with fisheye-view warping. image retargeting is the problem of adapting images for display on devices different than originally intended. this paper presents a method for adapting large images, such as those taken with a digital camera, for a small display, such as a cellular telephone. the method uses a non-linear fisheye-view warp that emphasizes parts of an image while shrinking others. like previous methods, fisheye-view warping uses image information, such as low-level salience and high-level object recognition to find important regions of the source image. however, unlike prior approaches, a non-linear image warping function emphasizes the important aspects of the image while retaining the surrounding context. the method has advantages in preserving information content, alerting the viewer to missing information and providing robustness.
augmenting conversations using dual-purpose speech. in this paper, we explore the concept of dual-purpose speech: speech that is socially appropriate in the context of a human-to-human conversation which also provides meaningful input to a computer. we motivate the use of dual-purpose speech and explore issues of privacy and technological challenges related to mobile speech recognition. we present three applications that utilize dual-purpose speech to assist a user in conversational tasks: the calendar navigator agent, dialogtabs, and speech courier. the calendar navigator agent navigates a user's calendar based on socially appropriate speech used while scheduling appointments. dialogtabs allows a user to postpone cognitive processing of conversational material by proving short-term capture of transient information. finally, speech courier allows asynchronous delivery of relevant conversational information to a third party.
dart: a toolkit for rapid design exploration of augmented reality experiences. in this paper [macintyre et al 2004]. we describe the designer's augmented reality toolkit (dart). dart is built on top of macromedia director, a widely used multimedia development environment. we summarize the most significant problems faced by designers working with ar in the real world, and discuss how dart addresses them. most of dart is implemented in an interpreted scripting language, and can be modified by designers to suit their needs. our work focuses on supporting early design activities, especially a rapid transition from storyboards to working experience, so that the experiential part of a design can be tested early and often. dart allows designers to specify complex relationships between the physical and virtual worlds, and supports 3d animatic actors (informal, sketch-based content) in addition to more polished content. designers can capture and replay synchronized video and sensor data, allowing them to work off-site and to test specific parts of their experience more effectively.
support for multitasking and background awareness using interactive peripheral displays. in this paper, we describe kimura, an augmented office environment to support common multitasking practices. previous systems, such as rooms, limit users by constraining the interaction to the desktop monitor. in kimura, we leverage interactive projected peripheral displays to support the perusal, manipulation and awareness of background activities. furthermore, each activity is represented by a montage comprised of images from current and past interaction on the desktop. these montages help remind the user of past actions, and serve as a springboard for ambient context-aware reminders and notifications.
letterwise: prefix-based disambiguation for mobile text input. a new technique to enter text using a mobile phone keypad is described. for text input, the traditional touchtone phone keypad is ambiguous because each key encodes three or four letters. instead of using a stored dictionary to guess the intended word, our technique uses probabilities of letter sequences --- "prefixes" --- to guess the intended letter. compared to dictionary-based methods, this technique, called letterwise, takes significantly less memory and allows entry of non-dictionary words without switching to a special input mode. we conducted a longitudinal study to compare letterwise to multitap, the conventional text entry method for mobile phones. the experiment included 20 participants (10 letterwise, 10 multitap), and each entered phrases of text for 20 sessions of about 30 minutes each. error rates were similar between the techniques; however, by the end of the experiment the mean entry speed was 36% faster with letterwise than with multitap.
the missing link: augmenting biology laboratory notebooks. using a participatory design process, we created three prototype augmented laboratory notebooks that provide the missing link between paper, physical artifacts and on-line data. the final a-book combines a graphics tablet and a pda. the tablet captures writing on the paper notebook and the pda acts as an "interaction lens" or window between physical and electronic documents. our approach is document-centered, with a software architecture based on layers of physical and electronic information.
interacting with large displays from a distance with vision-tracked multi-finger gestural input. we explore the idea of using vision-based hand tracking over a constrained tabletop surface area to perform multi-finger and whole-hand gestural interactions with large displays from a distance. we develop bimanual techniques to support a variety of asymmetric and symmetric interactions, including fast targeting and navigation to all parts of a large display from the comfort of a desk and chair, as well as techniques that exploit the ability of the vision-based hand tracking system to provide multi-finger identification and full 2d hand segmentation. we also posit a design that allows for handling multiple concurrent users.
supporting interspecies social awareness: using peripheral displays for distributed pack awareness. in interspecies households, it is common for the non homo sapien members to be isolated and ignored for many hours each day when humans are out of the house or working. for pack animals, such as canines, information about a pack member's extended pack interactions (outside of the nuclear household) could help to mitigate this social isolation. we have developed a pack activity watch system: allowing broad interspecies love in telecommunication with internet-enabled sociability (pawsabilities) for helping to support remote awareness of social activities. our work focuses on canine companions, and includes, pawticipatory design, labradory tests, and canid camera monitoring.
interaction techniques for ambiguity resolution in recognition-based interfaces. because of its promise of natural interaction, recognition is coming into its own as a mainstream technology for use with computers. both commercial and research applications are beginning to use it extensively. however the errors made by recognizers can be quite costly, and this is increasingly becoming a focus for researchers. we present a survey of existing error correction techniques in the user interface. these mediation techniques most commonly fall into one of two strategies, repetition and choice. based on the needs uncovered by this survey, we have developed oops, a toolkit that supports resolution of input ambiguity through mediation. this paper describes four new interaction techniques built using oops, and the toolkit mechanisms required to build them. these interaction techniques each address problems not directly handled by standard approaches to mediation, and can all be re-used in a variety of settings.
physical embodiments for mobile communication agents. this paper describes a physically embodied and animated user interface to an interactive call handling agent, consisting of a small wireless animatronic device in the form of a squirrel, bunny, or parrot. a software tool creates movement primitives, composes these primitives into complex behaviors, and triggers these behaviors dynamically at state changes in the conversational agent's finite state machine. gaze and gestural cues from the animatronics alert both the user and co-located third parties of incoming phone calls, and data suggests that such alerting is less intrusive than conventional telephones.
a toolkit for managing user attention in peripheral displays. traditionally, computer interfaces have been confined to conventional displays and focused activities. however, as displays become embedded throughout our environment and daily lives, increasing numbers of them must operate on the periphery of our attention. <i>peripheral displays</i> can allow a person to be aware of information while she is attending to some other primary task or activity. we present the peripheral displays toolkit (ptk), a toolkit that provides structured support for managing user attention in the development of peripheral displays. our goal is to enable designers to explore different approaches to managing user attention. the ptk supports three issues specific to conveying information on the periphery of human attention. these issues are <i>abstraction</i> of raw input, rules for assigning <i>notification levels</i> to input, and <i>transitions</i> for updating a display when input arrives. our contribution is the investigation of issues specific to attention in peripheral display design and a toolkit that encapsulates support for these issues. we describe our toolkit architecture and present five sample peripheral displays demonstrating our toolkit's capabilities.
outlier finding: focusing user attention on possible errors. when users handle large amounts of data, errors are hard to notice. outlier finding is a new way to reduce errors by directing the user's attention to inconsistent data which may indicate errors. we have implemented an outlier finder for text, which can detect both unusual matches and unusual mismatches to a text pattern. when integrated into the user interface of a pbd text editor and tested in a user study, outlier finding substantially reduced errors.
c-blink: a hue-difference-based light signal marker for large screen interaction via any mobile terminal. to enable common mobile terminals to interact with contents shown on large screens, we propose "c-blink", a new light signal marker method that uses the color liquid-crystal display of a mobile terminal as a visible light source. we overcome the performance limitations of such displays by developing a hue-difference-blink technique. in combination with a screen-side sensor, we describe a system that detects and receives light signal markers sent by cell phone displays. evaluations of a prototype system confirm that c-blink performs well under common indoor lighting. the c-blink program can be installed in any mobile terminal that has a color display, and the installation costs are small. c-blink is a very useful way of enabling ubiquitous large screens to become interfaces for mobile terminals.
navigating documents with the virtual scroll ring. we present a technique for scrolling through documents that is simple to implement and requires no special hardware. this is accomplished by simulating a hardware scroll ring--a device that maps circular finger motion into vertical scrolling. the technique performs at least as well as a mouse wheel for medium and long distances, and is preferred by users. it can be particularly useful in portable devices where screen-space and space for peripherals is at a premium.
user interfaces when and where they are needed: an infrastructure for recombinant computing. users in ubiquitous computing environments need to be able to make serendipitous use of resources that they did not anticipate and of which they have no prior knowledge. the speakeasy recombinant computing framework is designed to support such ad hoc use of resources on a network. in addition to other facilities, the framework provides an infrastructure through which device and service user interfaces can be made available to users on multiple platforms. the framework enables uis to be provided for connections involving multiple entities, allows these uis to be delivered asynchronously, and allows them to be injected by any party participating in a connection.
generating remote control interfaces for complex appliances. the personal universal controller (puc) is an approach for improving the interfaces to complex appliances by introducing an intermediary graphical or speech interface. a puc engages in two-way communication with everyday appliances, first downloading a specification of the appliance's functions, and then automatically creating an interface for controlling that appliance. the specification of each appliance includes a high-level description of every function, a hierarchical grouping of those functions, and dependency information, which relates the availability of each function to the appliance's state. dependency information makes it easier for designers to create specifications and helps the automatic interface generators produce a higher quality result. we describe the architecture that supports the puc, and the interface generators that use our specification language to build high-quality graphical and speech interfaces.
join and capture: a model for nomadic interaction. the xweb architecture delivers interfaces to a wide variety of interactive platforms. xweb's subscribe mechanism allows multiple interactive clients to synchronize with each other. we define the concept of join as the mechanism for acquiring access to a service's interface. join also allows the formation of spontaneous collaborations with other people. we define the concept of capture as the means for users to assemble suites of interactive resources to apply to a particular problem. these mechanisms allow users to access devices that they encounter in their environment rather than carrying all their devices with them. we describe two prototype implementations of join and capture. one uses a java ring to carry a user's identification and to make connections. the other uses a set of cameras to watch where users are and what they touch. lastly we present algorithms for resolving conflicts generated when independent interactive clients manipulate the same information.
screencrayons: annotating anything. screencrayons is a system for collecting annotations on any type of document or visual information from any application. the basis for the system is a screen capture upon which the user can highlight the relevant portions of the image. the user can define any number of topics for organizing notes. each topic is associated with a highlighting "crayon." in addition the user can supply annotations in digital ink or text. algorithms are described that summarize captured images based on the highlight strokes so as to provide overviews of many annotations as well as being able to "zoom in" on particular information about a given note and the context of that note.
query-by-critique: spoken language access to large lists. spoken language interfaces provide highly mobile, small form-factor, hands-free, eyes-free interaction with information. uniform access to large lists of information using spoken interfaces is highly desirable, but problematic due to inherent limitations of speech. a speech widget for lists of attributed objects is described that provides for approximate queries to retrieve desired items. user tests demonstrate that this is an effective technique for accessing information using speech.
the actuated workbench: computer-controlled actuation in tabletop tangible interfaces. the actuated workbench is a device that uses magnetic forces to move objects on a table in two dimensions. it is intended for use with existing tabletop tangible interfaces, providing an additional feedback loop for computer output, and helping to resolve inconsistencies that otherwise arise from the computer's inability to move objects on the table. we describe the actuated workbench in detail as an enabling technology, and then propose several applications in which this technology could be useful.
tilttype: accelerometer-supported text entry for very small devices. tilttype is a novel text entry technique for mobile devices. to enter a character, the user tilts the device and presses one or more buttons. the character chosen depends on the button pressed, the direction of tilt, and the angle of tilt. tilttype consumes minimal power and requires little board space, making it appropriate for wristwatch-sized devices. but because controlled tilting of one's forearm is fatiguing, a wristwatch using this technique must be easily removable from its wriststrap. applications include two-way paging, text entry for watch computers, web browsing, numeric entry for calculator watches, and existing applications for pdas.
empirical measurements of intrabody communication performance under varied physical configurations. intrabody communication (ibc) is a wireless communications technology that uses a person's body as the transmission medium for imperceptible electrical signals. because communication is limited to the vicinity of a person's body, ambiguities arising from communication between personal devices and environmental devices when multiple people are present can, in theory, be solved simply. intrabody communication also potentially allows data to be transferred when a person touches an ibc-enabled device. we have designed and constructed an intrabody communication system, modeled after zimmerman's original design, and extended it to operate up to 38.4kbps and to calculate signal strength. in this paper, we present quantitative measurements of data error rates and signal strength while varying hand distance to transceiver plate, electrode location on the body, touch plate size and shape, and several other factors. we find that plate size and shape have only minor effects, but that the distance to plate and the coupling mechanism significantly effect signal strength. we also find that portable devices, with poor ground coupling, suffer more significant signal attenuation. our goal is to promote design guidelines for this technology and identify the best contexts for its effective deployment.
a gesture-based authentication scheme for untrusted public terminals. powerful mobile devices with minimal i/o capabilities increase the likelihood that we will want to annex these devices to i/o resources we encounter in the local environment. this opportunistic annexing will require authentication. we present a sensor-based authentication mechanism for mobile devices that relies on physical possession instead of knowledge to setup the initial connection to a public terminal. our solution provides a simple mechanism for shaking a device to authenticate with the public infrastructure, making few assumptions about the surrounding infrastructure while also maintaining a reasonable level of security.
that one there! pointing to establish device identity. computing devices within current work and play environments are relatively static. as the number of 'networked' devices grows, and as people and their devices become more dynamic, situations will commonly arise where users will wish to use 'that device there' instead of navigating through traditional user interface widgets such as lists. this paper describes a process for identifying devices through a pointing gesture using custom tags and a custom stylus called the gesturepen. implementation details for this system are provided along with qualitative and quantitative results from a formal user study. as ubiquitous computing environments become more pervasive, people will rapidly switch their focus between many computing devices. the results of our work demonstrate that our gesturepen method can improve the user experience in ubiquitous environments by facilitating significantly faster interactions between computing devices.
connectables: dynamic coupling of displays for the flexible creation of shared workspaces. we present the connectable, a new mobile, networked and context-aware information appliance that provides affordances for pen-based individual and cooperative work as well as for the seamless transition between the two. in order to dynamically enlarge an interaction area for the purpose of shared use, a flexible coupling of displays has been realized that overcomes the restrictions of display sizes and borders. two connectable displays dynamically form a homogeneous display area when moved close to each other. the appropriate triggering signal comes from built-in sensors allowing users to temporally combine their individual displays to a larger shared one by a simple physical movement in space. connected connectables allow their users to work in parallel on an ad-hoc created shared workspace as well as exchanging information by simply shuffling objects from one display to the other. we discuss the user interface and related issues as well as the software architecture. we also present the physical realization of the connectables.
tactile interfaces for small touch screens. we present the design, implementation, and informal evaluation of tactile interfaces for small touch screens used in mobile devices. we embedded a tactile apparatus in a sony pda touch screen and enhanced its basic gui elements with tactile feedback. instead of observing the response of interface controls, users can feel it with their fingers as they press the screen. in informal evaluations, tactile feedback was greeted with enthusiasm. we believe that tactile feedback will become the next step in touch screen interface design and a standard feature of future mobile devices.
ambient touch: designing tactile interfaces for handheld devices. this paper investigates the sense of touch as a channel for communicating with miniature handheld devices. we embedded a pda with a touchenginetm --- a thin, miniature lower-power tactile actuator that we have designed specifically to use in mobile interfaces (figure 1). unlike previous tactile actuators, the touchengine is a universal tactile display that can produce a wide variety of tactile feelings from simple clicks to complex vibrotactile patterns. using the touchengine, we began exploring the design space of interactive tactile feedback for handheld computers. here, we investigated only a subset of this space: using touch as the ambient, background channel of interaction. we proposed a general approach to design such tactile interfaces and described several implemented prototypes. finally, our user studies demonstrated 22% faster task completion when we enhanced handheld tilting interfaces with tactile feedback.
user interface continuations. dialog boxes that collect parameters for commands often create ephemeral, unnatural interruptions of a program's normal execution flow, encouraging the user to complete the dialog box as quickly as possible in order for the program to process that command. in this paper we examine the idea of turning the act of collecting parameters from a user into a first class object called a user interface continuation. programs can create user interface continuations by specifying what information is to be collected from the user and supplying a callback (i.e., a continuation) to be notified with the collected information. a partially completed user interface continuation can be saved as a new command, much as currying and partially evaluating a function with a set of parameters produces a new function. furthermore, user interface continuations, like other continuation-passing paradigms, can be used to allow program execution to continue uninterrupted while the user determines a command's parameters at his or her leisure.
fluid interaction techniques for the control and annotation of digital video. we explore a variety of interaction and visualization techniques for fluid navigation, segmentation, linking, and annotation of digital videos. these techniques are developed within a concept prototype called lean that is designed for use with pressure-sensitive digitizer tablets. these techniques include a transient position+velocity widget that allows users not only to move around a point of interest on a video, but also to rewind or fast forward at a controlled variable speed. we also present a new variation of fish-eye views called twist-lens, and incorporate this into a position control slider designed for the effective navigation and viewing of large sequences of video frames. we also explore a new style of widgets that exploit the use of the pen's pressure-sensing capability, increasing the input vocabulary available to the user. finally, we elaborate on how annotations referring to objects that are temporal in nature, such as video, may be thought of as links, and fluidly constructed, visualized and navigated.
side views: persistent, on-demand previews for open-ended tasks. we introduce side views, a user interface mechanism that provides on-demand, persistent, and dynamic previews of commands. side views are designed to explicitly support the practices and needs of expert users engaged in openended tasks. in this paper, we summarize results from field studies of expert users that motivated this work, then discuss the design of side views in detail. we show how side views' design affords their use as tools for clarifying, comparing, and contrasting commands; generating alternative visualizations; experimenting without modifying the original data (i.e., "what-if" tools); and as tools that support the serendipitous discovery of viable alternatives. we then convey lessons learned from implementing side views in two sample applications, a rich text editor and an image manipulation application. these contributions include a discussion of how to implement side views for commands with parameters, for commands that require direct user input (such as mouse strokes for a paint program), and for computationally-intensive commands.
zliding: fluid zooming and sliding for high precision parameter manipulation. high precision parameter manipulation tasks typically require adjustment of the scale of manipulation in addition to the parameter itself. this paper introduces the notion of zoom sliding, or zliding, for fluid integrated manipulation of scale (zooming) via pressure input while parameter manipulation within that scale is achieved via x-y cursor movement (sliding). we also present the zlider (figure 1), a widget that instantiates the zliding concept. we experimentally evaluate three different input techniques for use with the zlider in conjunction with a stylus for x-y cursor positioning, in a high accuracy zoom and select task. our results marginally favor the stylus with integrated isometric pressure sensing tip over bimanual techniques which separate zooming and sliding controls over the two hands. we discuss the implications of our results and present further designs that make use of zliding.
from desktop to phonetop: a ui for web interaction on very small devices. while it is generally accepted that new internet terminals should leverage the installed base of web content and services, the differences between desktop computers and very small devices makes this challenging. indeed, the browser interaction model has evolved on desktop computers having a unique combination of user interface (large display, keyboard, pointing device), hardware, and networking capabilities. in contrast, internet enabled cell phones, typically with 3-10 lines of text, sacrifice usability as web terminals in favor of portability and other functions. based on our earlier experiences building and using a web browser for small devices we propose a new ui that splits apart the integrated activities of link following and reading into separate modes: navigating to; and acting on web content. this interaction technique for very small devices is both simpler for navigating and allows users to do more than just read. the m-links system incorporates modal browsing interaction and addresses a number of associated problems. we have built our system with an emphasis on simplicity and user extensibility and describe the design, implementation and evolution of the user interface.
boom chameleon: simultaneous capture of 3d viewpoint, voice and gesture annotations on a spatially-aware display. we introduce the boom chameleon, a novel input/output device consisting of a flat-panel display mounted on a tracked mechanical boom. the display acts as a physical window into 3d virtual environments, through which a one-to-one mapping between real and virtual space is preserved. the boom chameleon is further augmented with a touch-screen and a microphone/speaker combination. we present a 3d annotation application that exploits this unique configuration in order to simultaneously capture viewpoint, voice and gesture information. design issues are discussed and results of an informal user study on the device and annotation software are presented. the results show that the boom chameleon annotation facilities have the potential to be an effective, easy to learn and operate 3d design review system.
augmenting shared personal calendars. in this paper, we describe augur, a groupware calendar system to support personal calendaring practices, informal workplace communication, and the socio-technical evolution of the calendar system within a workgroup. successful design and deployment of groupware calendar systems have been shown to depend on several converging, interacting perspectives. we describe calendar-based work practices as viewed from these perspectives, and present the augur system in support of them. augur allows users to retain the flexibility of personal calendars by anticipating and compensating for inaccurate calendar entries and idiosyncratic event names. we employ predictive user models of event attendance, intelligent processing of calendar text, and discovery of shared events to drive novel calendar visualizations that facilitate interpersonal communication. in addition, we visualize calendar access to support privacy management and long-term evolution of the calendar system.
presense: interaction techniques for finger sensing input devices. although graphical user interfaces started as imitations of the physical world, many interaction techniques have since been invented that are not available in the real world. this paper focuses on one of these "previewing", and how a sensory enhanced input device called "presense keypad" can provide a preview for users before they actually execute the commands. preview important in the real world because it is often not possible to undo an action. this previewable feature helps users to see what will occur next. it is also helpful when the command assignment of the keypad dynamically changes, such as for universal commanders. we present several interaction techniques based on this input device, including menu and map browsing systems and a text input system. we also discuss finger gesture recognition for the presense keypad.
interactive public ambient displays: transitioning from implicit to explicit, public to personal, interaction with multiple users. we develop design principles and an interaction framework for sharable, interactive public ambient displays that support the transition from implicit to explicit interaction with both public and personal information. a prototype system implementation that embodies these design principles is described. we use novel display and interaction techniques such as simple hand gestures and touch screen input for explicit interaction and contextual body orientation and position cues for implicit interaction. techniques are presented for subtle notification, self-revealing help, privacy controls, and shared use by multiple people each in their own context. initial user feedback is also presented, and future directions discussed.
distant freehand pointing and clicking on very large, high resolution displays. we explore the design space of freehand pointing and clicking interaction with very large high resolution displays from a distance. three techniques for gestural pointing and two for clicking are developed and evaluated. in addition, we present subtle auditory and visual feedback techniques to compensate for the lack of kinesthetic feedback in freehand interaction, and to promote learning and use of appropriate postures.
: using tilt for text input to mobile phones. tilttext, a new technique for entering text into a mobile phone is described. the standard 12-button text entry keypad of a mobile phone forces ambiguity when the 26- letter roman alphabet is mapped in the traditional manner onto keys 2-9. the tilttext technique uses the orientation of the phone to resolve this ambiguity, by tilting the phone in one of four directions to choose which character on a particular key to enter. we first discuss implementation strategies, and then present the results of a controlled experiment comparing tilttext to multitap, the most common text entry technique. the experiment included 10 participants who each entered a total of 640 phrases of text chosen from a standard corpus, over a period of about five hours. the results show that text entry speed including correction for errors using tilttext was 23% faster than multitap by the end of the experiment, despite a higher error rate for tilttext. tilttext is thus amongst the fastest known language-independent techniques for entering text into mobile phones.
playanywhere: a compact interactive tabletop projection-vision system. we introduce playanywhere, a front-projected computer vision-based interactive table system which uses a new commercially available projection technology to obtain a compact, self-contained form factor. playanywhere's configuration addresses installation, calibration, and portability issues that are typical of most vision-based table systems, and thereby is particularly motivated in consumer applications. playanywhere also makes a number of contributions related to image processing techniques for front-projected vision-based table systems, including a shadow-based touch detection algorithm, a fast, simple visual bar code scheme tailored to projection-vision table systems, the ability to continuously track sheets of paper, and an optical flow-based algorithm for the manipulation of onscreen objects that does not rely on fragile tracking algorithms.
rapid serial visual presentation techniques for consumer digital video devices. in this paper we propose a new model for a class of rapid serial visual presentation (rsvp) interfaces [16] in the context of consumer video devices. the basic spatial layout "explodes" a sequence of image frames into a 3d trail in order to provide more context for a spatial/temporal presentation. as the user plays forward or back, the trail advances or recedes while the image in the foreground focus position is replaced. the design is able to incorporate a variety of methods for analyzing or highlighting images in the trail. our hypotheses are that users can navigate more quickly and precisely to points of interest when compared to conventional consumer-based browsing, channel flipping, or fast-forwarding techniques. we report on an experiment testing our hypotheses in which we found that subjects were more accurate but not faster in browsing to a target of interest in recorded television content with a tv remote.
parallel bargrams for consumer-based information exploration and choice. in this paper we introduce multidimensional visualization and interaction techniques that are an extension to related work in parallel histograms and dynamic querying. bargrams are, in effect, histograms whose bars have been tipped over and lined up end-to-end. we discuss affordances of parallel bargrams in the context of systems that support consumer-based information exploration and choice based on the attributes of the items in the choice set. our tool called ezchooser has enabled a number of prototypes in such domains as internet shopping, investment decisions, college choice, and so on, and a limited version has been deployed for car shopping. evaluations of the techniques include an experiment indicating that trained users prefer ezchooser over static tables for choice tasks among sets of 50 items with 7-9 attributes.
webthumb: interaction techniques for small-screen browsers. the proliferation of wireless handheld devices is placing the world wide web in the palms of users, but this convenience comes at a high interactive cost. the web that came of age on the desktop is ill-suited for use on the small displays of handhelds. today, handheld browsing often feels like browsing on a pc with a shrunken desktop. overreliance on scrolling is a big problem in current handheld browsing. users confined to viewing a small portion of each page often lack a sense of the overall context --- they may feel lost in a large page and be forced to remember the locations of items as those items scroll out of view. in this paper, we present a synthesis of interaction techniques to address these problems. we implemented these techniques in a prototype, webthumb, that can browse the live web.
edgewrite: a stylus-based text entry method designed for high accuracy and stability of motion. edgewrite is a new unistroke text entry method for handheld devices designed to provide high accuracy and stability of motion for people with motor impairments. it is also effective for able-bodied people. an edgewrite user enters text by traversing the edges and diagonals of a square hole imposed over the usual text input area. gesture recognition is accomplished not through pattern recognition but through the sequence of corners that are hit. this means that the full stroke path is unimportant and recognition is highly deterministic, enabling better accuracy than other gestural alphabets such as graffiti. a study of able-bodied users showed subjects with no prior experience were 18% more accurate during text entry with edge write than with graffiti (p>.05), with no significant difference in speed. a study of 4 subjects with motor impairments revealed that some of them were unable to do graffiti, but all of them could do edge write. those who could do both methods had dramatically better accuracy with edge write.
perceptually-supported image editing of text and graphics. this paper presents a novel image editing program emphasizing easy selection and manipulation of material found in informal, casual documents such as sketches, handwritten notes, whiteboard images, screen snapshots, and scanned documents. the program, called scanscribe, offers four significant advances. first, it presents a new, intuitive model for maintaining image objects and groups, along with underlying logic for updating these in the course of an editing session. second, scanscribe takes advantage of newly developed image processing algorithms to separate foreground markings from a white or light background, and thus can automatically render the background transparent so that image material can be rearranged without occlusion by background pixels. third, scanscribe introduces new interface techniques for selecting image objects with a pointing device without resorting to a palette of tool modes. fourth, scanscribe presents a platform for exploiting image analysis and recognition methods to make perceptually significant structure readily available to the user. as a research prototype, scanscribe has proven useful in the work of members of our laboratory, and has been released on a limited basis for user testing and evaluation.
stylus input and editing without prior selection of mode. this paper offers a solution to the mode problem in computer sketch/notetaking programs. conventionally, the user must specify the intended "draw" or "command" mode prior to performing a stroke. this necessity has proven to be a barrier to the usability of pen/stylus systems. we offer a novel inferred-mode interaction protocol that avoids the mode hassles of conventional sketch systems. the system infers the user's intent, if possible, from the properties of the pen trajectory and the context of the trajectory. if the intent is ambiguous, the user is offered a choice mediator in the form of a pop-up button. to maximize the fluidity of drawing, the user is entitled to ignore the mediator and continue drawing. we present decision logic for the inferred mode protocol, and discuss subtleties learned in the course of its development. we also present results of initial user trials validating the usability of this interaction design.
who cares?: reflecting who is reading what on distributed community bulletin boards. in this paper, we describe the yeti information sharing system that has been designed to foster community building through informal digital content sharing. the yeti system is a general information parsing, hosting and distribution infrastructure, with interfaces designed for individual and public content reading. in this paper we describe the yeti public display interface, with a particular focus on tools we have designed to provide lightweight awareness of others' interactions with posted content. our tools augment content with metadata that reflect people's reading of content - captured video clips of who's reading and interacting with content, tools to allow people to leave explicit freehand annotations about content, and a visualization of the content access history to show when content is interacted with. results from an initial evaluation are presented and discussed.
dial and see: tackling the voice menu navigation problem with cross-device user experience integration. ivr (interactive voice response) menu navigation has long been recognized as a frustrating interaction experience. we propose an im-based system that sends a coordinated visual ivr menu to the caller's computer screen. the visual menu is updated in real time in response to the caller's actions. with this automatically opened supplementary channel, callers can take advantages of different modalities over different devices and interact with the ivr system with the ease of graphical menu selection. our approach of utilizing existing network infrastructure to pinpoint the caller's virtual location and coordinating multiple devices and multiple channels based on users' id registration can also be more generally applied to create integrated user experiences across a group of devices.
mediated voice communication via mobile ip. impromptu is a mobile audio device which uses wireless internet protocol (ip) to access novel computer-mediated voice communication channels. these channels show the richness of ip-based communication as compared to conventional mobile telephony, adding audio processing and storage in the network, and flexible, user-centered call control protocols. these channels may be synchronous, asynchronous, or event-triggered, or even change modes as a function of other user activity. the demands of these modes plus the need to navigate with an entirely non-visual user interface are met with a number of audio-oriented user interaction techniques.
an explanation-based, visual debugger for one-way constraints. this paper describes a domain-specific debugger for one-way constraint solvers. the debugger makes use of several new techniques. first, the debugger displays only a portion of the dataflow graph, called a <i>constraint slice</i>, that is directly related to an incorrect variable. this technique helps the debugger scale to a system containing thousands of constraints. second, the debugger presents a visual representation of the solver's data structures and uses color encodings to highlight changes to the data structures. finally, the debugger allows the user to point to a variable that has an unexpected value and ask the debugger to suggest reasons for the unexpected value. the debugger makes use of information gathered during the constraint satisfaction process to generate plausible suggestions. informal testing has shown that the explanatory capability and the color coding of the constraint solver's data structures are particularly useful in locating bugs in constraint code.
pop through mouse button interactions. we present a range of novel interactions enabled by a simple modification in the design of a computer mouse. by converting each mouse button to pop through tactile push-buttons, similar to the focus/shutter-release buttons used in many cameras, users can feel, and the computer can sense, two distinct "clicks" corresponding to pressing lightly and pressing firmly to pop through. despite the prototypical status of our hardware and software implementations, our current pop through mouse interactions are compelling and warrant further investigation. in particular, we demonstrate that pop through buttons not only yield an additional button activation state that is composable with, or even preferable to, techniques such as double-clicking, but also can endow a qualitatively novel user experience when meaningfully and consistently applied. we propose a number of software guidelines that may provide a consistent, systemic benefit; for example, light pressure may invoke default interaction (short menu), and firm pressure may supply more detail (long menu).
the ibar: a perspective-based camera widget. we present a new screen space widget, the ibar, for effective camera control in 3d graphics environments. the ibar provides a compelling interface for controlling scene perspective based on the artistic concept of vanishing points. various handles on the widget manipulate multiple camera parameters simultaneously to create a single perceived projection change. for example, changing just the perspective distortion is accomplished by simultaneously decreasing the camera's distance to the scene while increasing focal length. we demonstrate that the ibar is easier to learn for novice users and improves their understanding of camera perspective.
simple vs. compound mark hierarchical marking menus. we present a variant of hierarchical marking menus where items are selected using a series of inflection-free simple marks, rather than the single "zig-zag" compound mark used in the traditional design. theoretical analysis indicates that this simple mark approach has the potential to significantly increase the number of items in a marking menu that can be selected efficiently and accurately. a user experiment is presented that compares the simple and compound mark techniques. results show that the simple mark technique allows for significantly more accurate and faster menu selections overall, but most importantly also in menus with a large number of items where performance of the compound mark technique is particularly poor. the simple mark technique also requires significantly less physical input space to perform the selections, making it particularly suitable for small footprint pen-based input devices. visual design alternatives are also discussed.
an optimization-based approach to dynamic data content selection in intelligent multimedia interfaces. we are building a multimedia conversation system to facilitate information seeking in large and complex data spaces. to provide tailored responses to diverse user queries introduced during a conversation, we automate the generation of a system response. here we focus on the problem of determining the data content of a response. specifically, we develop an optimization-based approach to content selection. compared to existing rule-based or plan-based approaches, our work offers three unique contributions. first, our approach provides a general framework that effectively addresses content selection for various interaction situations by balancing a comprehensive set of constraints (e.g., content quality and quantity constraints). second, our method is easily extensible, since it uses feature-based metrics to systematically model selection constraints. third, our method improves selection results by incorporating content organization and media allocation effects, which otherwise are treated separately. preliminary studies show that our method can handle most of the user situations identified in a wizard-of-oz study, and achieves results similar to those produced by human designers.
reflective physical prototyping through integrated design, test, and analysis. prototyping is the pivotal activity that structures innovation, collaboration, and creativity in design. prototypes embody design hypotheses and enable designers to test them. framin design as a thinking-by-doing activity foregrounds iteration as a central concern. this paper presents d.tools, a toolkit that embodies an iterative-design-centered approach to prototyping information appliances. this work offers contributions in three areas. first, d.tools introduces a statechart-based visual design tool that provides a low threshold for early-stage prototyping, extensible through code for higher-fidelity prototypes. second, our research introduces three important types of hardware extensibility - at the hardware-to-pc interface, the intra-hardware communication level, and the circuit level. third, d.tools integrates design, test, and analysis of information appliances. we have evaluated d.tools through three studies: a laboratory study with thirteen participants; rebuilding prototypes of existing and emerging devices; and by observing seven student teams who built prototypes with d.tools.
the radial scroll tool: scrolling support for stylus- or touch-based document navigation. we present radial scroll, an interface widget to support scrolling particularly on either small or large scale touch displays. instead of dragging a elevator in a scroll bar, or using repetitive key presses to page up or down, users gesture anywhere on the document surface such that clockwise gestures advance the document; counter clockwise gestures reverse the document. we describe our prototype implementation and discuss the results of an initial user study.
quiet interfaces that help students think. as technical as we have become, modern computing has not permeated many important areas of our lives, including mathematics education which still involves pencil and paper. in the present study, twenty high school geometry students varying in ability from low to high participated in a comparative assessment of math problem solving using existing pencil and paper work practice (pp), and three different interfaces: an anoto-based digital stylus and paper interface (dp), pen tablet interface (pt), and graphical tablet interface (gt). cognitive load theory correctly predicted that as interfaces departed more from familiar work practice (gt > pt > dp), students would experience greater cognitive load such that performance would deteriorate in speed, attentional focus, meta-cognitive control, correctness of problem solutions, and memory. in addition, low-performing students experienced elevated cognitive load, with the more challenging interfaces (gt, pt) disrupting their performance disproportionately more than higher performers. the present results indicate that cognitive load theory provides a coherent and powerful basis for predicting the rank ordering of users' performance by type of interface. in the future, new interfaces for areas like education and mobile computing could benefit from designs that minimize users' load so performance is more adequately supported.
recipesheet: creating, combining and controlling information processors. many tasks require users to extract information from diverse sources, to edit or process this information locally, and to explore how the end results are affected by changes in the information or in its processing. we present the recipesheet, a general-purpose tool for assisting users in such tasks. the recipesheet lets users create information processors, called recipes, which may take input in a variety of forms such as text, web pages, or xml, and produce results in a similar variety of forms. the processing carried out by a recipe may be specified using a macro or query language, of which we currently support rexx, smalltalk and xquery, or by capturing the behaviour of a web application or web service. in the recipesheet's spreadsheet-inspired user interface, information appears in cells, with inter-cell dependencies defined by recipes rather than formulas. users can also intervene manually to control which information flows through the dependency connections. through a series of examples we illustrate how tasks that would be challenging in existing environments are supported by the recipesheet.
viewpointer: lightweight calibration-free eye tracking for ubiquitous handsfree deixis. we introduce viewpointer, a wearable eye contact sensor that detects deixis towards ubiquitous computers embedded in real world objects. viewpointer consists of a small wearable camera no more obtrusive than a common bluetooth headset. viewpointer allows any real-world object to be augmented with eye contact sensing capabilities, simply by embedding a small infrared (ir) tag. the headset camera detects when a user is looking at an infrared tag by determining whether the reflection of the tag on the cornea of the user's eye appears sufficiently central to the pupil. viewpointer not only allows any object to become an eye contact sensing appliance, it also allows identification of users and transmission of data to the user through the object. we present a novel encoding scheme used to uniquely identify viewpointer tags, as well as a method for transmitting urls over tags. we present a number of scenarios of application as well as an analysis of design principles. we conclude eye contact sensing input is best utilized to provide context to action.
haptic techniques for media control. we introduce a set of techniques for haptically manipulating digital media such as video, audio, voicemail and computer graphics, utilizing virtual mediating dynamic models based on intuitive physical metaphors. for example, a video sequence can be modeled by linking its motion to a heavy spinning virtual wheel: the user browses by grasping a physical force-feedback knob and engaging the virtual wheel through a simulated clutch to spin or brake it, while feeling the passage of individual frames. these systems were implemented on a collection of single axis actuated displays (knobs and sliders), equipped with orthogonal force sensing to enhance their expressive potential. we demonstrate how continuous interaction through a haptically actuated device rather than discrete button and key presses can produce simple yet powerful tools that leverage physical intuition.
robust computer vision-based detection of pinching for one and two-handed gesture input. we present a computer vision technique to detect when the user brings their thumb and forefinger together (a pinch gesture) for close-range and relatively controlled viewing circumstances. the technique avoids complex and fragile hand tracking algorithms by detecting the hole formed when the thumb and forefinger are touching; this hole is found by simple analysis of the connected components of the background segmented against the hand. our thumb and fore-finger interface (taffi) demonstrates the technique for cursor control as well as map navigation using one and two-handed interactions.
circle & identify: interactivity-augmented object recognition for handheld devices. the first requirement of a "spatial mouse" is the ability to identify the object that it is aiming at. among many possible technologies that can be employed for this purpose, possibly the best solution would be object recognition by machine vision. the problem, however, is that object recognition algorithms are not yet reliable enough or light enough for hand-held devices. this paper demonstrates that a simple object recognition algorithm can become a practical solution when augmented by interactivity. the user draw a circle around a target using a spatial mouse, and the mouse captures a series of camera frames. the frames can be easily stitched together to give a target image separated from the background, with which we need only additional steps of feature extraction and object classification. we present here results from two experiments with a few household objects.
personalizing routes. navigation services (e.g., in-car navigation systems and online mapping sites) compute routes between two locations to help users navigate. however, these routes may direct users along an unfamiliar path when a familiar path exists, or, conversely, may include redundant information that the user already knows. these overly complicated directions increase the cognitive load of the user, which may lead to a dangerous driving environment. since the level of detail is user specific and depends on their familiarity with a region, routes need to be personalized. we have developed a system, called myroute, that reduces route complexity by creating user specific routes based on a priori knowledge of familiar routes and landmarks. myroute works by compressing well known steps into a single contextualized step and rerouting users along familiar routes.
projector-guided painting. this paper presents a novel interactive system for guiding artists to paint using traditional media and tools. the enabling technology is a multi-projector display capable of controlling the appearance of an artist's canvas. this display-on-canvas guides the artist to construct the painting as a series of layers. our process model for painting is based on classical techniques and was designed to address three main issues which are challenging to novices: (1) positioning and sizing elements on the canvas, (2) executing the brushstrokes to achieve a desired texture and (3) mixing pigments to make a target color. these challenges are addressed through a set of interaction modes. preview and color selection modes enable the artist to focus on the current target layer by highlighting the areas of the canvas to be painted. orientation mode displays brushstroke guidelines for the creation of desired brush texture. color mixing mode guides the artist through the color mixing process with a user interface similar to a color wheel. these interaction modes allow a novice artist to focus on a series of manageable subtasks in executing a complex painting. our system covers the gamut of the painting process from overall composition down to detailed brushwork. we present the results from a user study which quantify the benefit that our system can provide to a novice painter.
personal computing in the 21st century. ever since the dawn of the digital computer, invention, innovation, and creativity have been a hallmark of the industry. the mainframe computer seemed for a while to be the real player with experts or at least highly trained professionals operating these large and expensive machines. most users were allowed to see them through glass windows but "hands on" was a rare opportunity. in 1972, the xerox palo alto research center (parc), built a remarkable personal computer named the alto. except for the visionaries at parc and a few others, most people considered the personal computer a mere curiosity in this early period. today, the personal computer has become a tool that very few imagined. what might be yet to come.while prognosticating about the future is a risky endeavor at best, perhaps we can obtain a look ahead with a straightforward review of the current status of personal computing. we will look at operating systems, application software and peripherals, however, the real goal of this talk is to see what the user interface, tools and interactions with this future computing environment might be or perhaps even should be. will we still be using continuing variations of doug englebart's mouse in 2020 or might something new and much more advanced emerge? how might users seamlessly deal with terabytes of storage? how might multi-user environments be used and could multi-os machines be an economic and generally available personal computing environment? are there user experience issues that are critical in multi-os environments? how might the user's display be different from today? will tomorrow's displays be larger, have a significantly higher pixel density, be much more paper-like, etc.? might electronic printers and their requisite paper output still be with us by 2025, for example? will home and neighborhood network resources finally be a powerful ally of the computing environment? many exciting opportunities and questions beg for answers and industry insight.this talk will attempt to peer into the near future to see what we might expect of the personal computing environment based on what we can extrapolate from current experience and technology directions. while the exactitude of such projections may be limited, taken as a whole, there is perhaps much that can be learned from such an exercise. why do this? charles kettering, the great automotive inventor was asked why he spent so much time planning and thinking about the future. he wisely replied, "because i am going to spend the rest of my life there." thirty years ago, very few could have imagined all the wonderful things that personal computing has enabled. perhaps we have just begun our exciting journey. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
cuetip: a mixed-initiative interface for correcting handwriting errors. with advances in pen-based computing devices, handwriting has become an increasingly popular input modality. researchers have put considerable effort into building intelligent recognition systems that can translate handwriting to text with increasing accuracy. however, handwritten input is inherently ambiguous, and these systems will always make errors. unfortunately, work on error recovery mechanisms has mainly focused on interface innovations that allow users to manually transform the erroneous recognition result into the intended one. in our work, we propose a mixed-initiative approach to error correction. we describe cuetip, a novel correction interface that takes advantage of the recognizer to continually evolve its results using the additional information from user corrections. this significantly reduces the number of actions required to reach the intended result. we present a user study showing that cuetip is more efficient and better preferred for correcting handwriting recognition errors. grounded in the discussion of cuetip, we also present design principles that may be applied to mixed-initiative correction interfaces in other domains.
rapid construction of functioning physical interfaces from cardboard, thumbtacks, tin foil and masking tape. rapid, early, but rough system prototypes are becoming a standard and valued part of the user interface design process. pen, paper, and tools like flash™ and director™ are well suited to creating such prototypes. however, in the case of physical forms with embedded technology, there is a lack of tools for developing rapid, early prototypes. instead, the process tends to be fragmented into prototypes exploring forms that look like the intended product or explorations of functioning interactions that work like the intended product - bringing these aspects together into full design concepts only later in the design process. to help alleviate this problem, we present a simple tool for very rapidly creating functioning, rough physical prototypes early in the design process - supporting what amounts to interactive physical sketching. our tool allows a designer to combine exploration of form and interactive function, using objects constructed from materials such as thumbtacks, foil, cardboard and masking tape, enhanced with a small electronic sensor board. by means of a simple and fluid tool for delivering events to "screen clippings," these physical sketches can then be easily connected to any existing (or new) program running on a pc to provide real or wizard of oz supported functionality.
under the table interaction. we explore the design space of a two-sided interactive touch table, designed to receive touch input from both the top and bottom surfaces of the table. by combining two registered touch surfaces, we are able to offer a new dimension of input for co-located collaborative groupware. this design accomplishes the goal of increasing the relative size of the input area of a touch table while maintaining its direct-touch input paradigm. we describe the interaction properties of this two-sided touch table, report the results of a controlled experiment examining the precision of user touches to the underside of the table, and a series of application scenarios we developed for use on inverted and two-sided tables. finally, we present a list of design recommendations based on our experiences and observations with inverted and two-sided tables.
citrine: providing intelligent copy-and-paste. we present citrine, a system that extends the widespread copy-and-paste interaction technique with intelligent transformations, making it useful in more situations. citrine uses text parsing to find the structure in copied text and allows users to paste the structured information, which might have many pieces, in a single paste operation. for example, using citrine, a user can copy the text of a meeting request and add it to the outlook calendar with a single paste. in applications such as excel, users can teach citrine by example how to copy and paste data by showing it which fields go into which columns, and can use this to copy or paste many items at a time in a user-defined manner. citrine can be used with a wide variety of applications and types of data and can be easily extended to work with more. it currently includes parsers that recognize contact information, calendar appointments and bibliographic citations. it works with internet explorer, outlook, excel, palm desktop, endnote and other applications. citrine is available to download on the internet.
content-aware scrolling. scrolling is used to navigate large information spaces on small screens, but is often too restrictive or cumbersome to use for particular types of content, such as multi-page, multi-column documents. to address this problem, we introduce content-aware scrolling (cas), an approach that takes into account various characteristics of document content to determine scrolling direction, speed, and zoom. we also present the cas widget, which supports scrolling through a content-aware path using traditional scrolling methods, demonstrating the advantages of making a traditional technique content-aware.
summarizing personal web browsing sessions. we describe a system, implemented as a browser extension, that enables users to quickly and easily collect, view, and share personal web content. our system employs a novel interaction model, which allows a user to specify webpage extraction patterns by interactively selecting webpage elements and applying these patterns to automatically collect similar content. further, we present a technique for creating visual summaries of the collected information by combining user labeling with predefined layout templates. these summaries are interactive in nature: depending on the behaviors encoded in their templates, they may respond to mouse events, in addition to providing a visual summary. finally, the summaries can be saved or sent to others to continue the research at another place or time. informal evaluation shows that our approach works well for popular websites, and that users can quickly learn this interaction model for collecting content from the web.
windowscape: a task oriented window manager. we propose windowscape, a window manager that uses a photograph metaphor for lightweight, post hoc task management. this is the first task management windowing model to provide intuitive accessibility while allowing windows to exist simultaneously in multiple tasks. windowscape exploits users' spatial and visual memories by providing a stable thumbnail layout in which to search for windows. a function is provided to let users search the window space while maintaining a largely consistent screen image to minimize distractions. a novel keyboard interaction technique is also presented.
multi-user, multi-display interaction with a single-user, single-display geospatial application. in this paper, we discuss our adaptation of a single-display, single-user commercial application for use in a multi-device, multi-user environment. we wrap google earth, a popular geospatial application, in a manner that allows for synchronized coordinated views among multiple instances running on different machines in the same co-located environment. the environment includes a touch-sensitive tabletop display, three vertical wall displays, and a tabletpc. a set of interaction techniques that allow a group to manage and exploit this collection of devices is presented.
automatic thumbnail cropping and its effectiveness. thumbnail images provide users of image retrieval and browsing systems with a method for quickly scanning large numbers of images. recognizing the objects in an image is important in many retrieval tasks, but thumbnails generated by shrinking the original image often render objects illegible. we study the ability of computer vision systems to detect key components of images so that automated cropping, prior to shrinking, can render objects more recognizable. we evaluate automatic cropping techniques 1) based on a general method that detects salient portions of images, and 2) based on automatic face detection. our user study shows that these methods result in small thumbnails that are substantially more recognizable and easier to find in the context of visual search.
in-stroke word completion. we present the design and implementation of a word-level stroking system called fisch, which is intended to improve the speed of character-level unistrokes. importantly, fisch does not alter the way in which character-level unistrokes are made, but allows users to gradually ramp up to word-level unistrokes by extending their letters in minimal ways. fisch relies on in-stroke word completion, a flexible design for fluidly turning unistroke letters into whole words. fisch can be memorized at the motor level since word completions always appear at the same positions relative to the strokes being made. our design for fisch is suitable for use with any unistroke alphabet. we have implemented fisch for multiple versions of edgewrite, and results show that fisch reduces the number of strokes during entry by 43.9% while increasing the rate of entry. an informal test of "record speed" with the stylus version resulted in 50-60 wpm with no uncorrected errors.
swingstates: adding state machines to the swing toolkit. this article describes swingstates, a library that adds state machines to the java swing user interface toolkit. unlike traditional approaches, which use callbacks or listeners to define interaction, state machines provide a powerful control structure and localize all of the interaction code in one place. swingstates takes advantage of java's inner classes, providing programmers with a natural syntax and making it easier to follow and debug the resulting code. swingstates tightly integrates state machines, the java language and the swing toolkit. it reduces the potential for an explosion of states by allowing multiple state machines to work together. we show how to use swingstates to add new interaction techniques to existing swing widgets, to program a powerful new canvas widget and to control high-level dialogues.
pen-top feedback for paper-based interfaces. current paper-based interfaces such as papiercraft, provide very little feedback and this limits the scope of possible interactions. so far, there has been little systematic exploration of the structure, constraints, and contingencies of feedback-mechanisms in paper-based interaction systems for paper-only environments. we identify three levels of feedback: discovery feedback (e.g., to aid with menu learning), status-indication feedback (e.g., for error detection), and task feedback (e.g., to aid in a search task). using three modalities (visual, tactile, and auditory) which can be easily implemented on a pen-sized computer, we introduce a conceptual matrix to guide systematic research on pen-top feedback for paper-based interfaces. using this matrix, we implemented a multimodal pen prototype demonstrating the potential of our approach. we conducted an experiment that confirmed the efficacy of our design in helping users discover a new interface and identify and correct their errors.
assieme: finding and leveraging implicit references in a web search interface for programmers. programmers regularly use search as part of the development process, attempting to identify an appropriate api for a problem, seeking more information about an api, and seeking samples that show how to use an api. however, neither general-purpose search engines nor existing code search engines currently fit their needs, in large part because the information programmers need is distributed across many pages. we present assieme, a web search interface that effectively supports common programming search tasks by combining information from web-accessible java archive (jar) files, api documentation, and pages that include explanatory text and sample code. assieme uses a novel approach to finding and resolving implicit references to java packages, types, and members within sample code on the web. in a study of programmers performing searches related to common programming tasks, we show that programmers obtain better solutions, using fewer queries, in the same amount of time spent using a general web search interface.
smart bookmarks: automatic retroactive macro recording on the web. we present a new web automation system that allows users to create a smart bookmark, consisting of a starting url plus a script of commands that returns to a particular web page or state of a web application. a smart bookmark can be requested for any page, and the necessary commands are automatically extracted from the user's interaction history. unlike other web macro recorders, which require the user to start recording before navigating to the desired page, smart bookmarks are generated retroactively, after the user has already reached a page, and the starting point of the macro is found automatically. smart bookmarks have a rich graphical visualization that combines textual commands, web page screenshots, and animations to explain what the bookmark does. a bookmark's script consists of keyword commands, interpreted without strict reliance on syntax, allowing bookmarks to be easily edited and shared.
gui --- phooey!: the case for text input. information cannot be found if it is not recorded. existing rich graphical application approaches interfere with user input in many ways, forcing complex interactions to enter simple information, requiring complex cognition to decide where the data should be stored, and limiting the kind of information that can be entered to what can fit into specific applications' data models. freeform text entry suffers from none of these limitations but produces data that is hard to retrieve or visualize. we describe the design and implementation of jourknow, a system that aims to bridge these two modalities, supporting lightweight text entry and weightless context capture that produces enough structure to support rich interactive presentation and retrieval of the arbitrary information entered.
gaze-enhanced scrolling techniques. scrolling is an essential part of our everyday computing experience. contemporary scrolling techniques rely on the explicit initiation of scrolling by the user. the act of scrolling is tightly coupled with the user?s ability to absorb information via the visual channel. the use of eye gaze information is therefore a natural choice for enhancing scrolling techniques. we present several gaze-enhanced scrolling techniques for manual and automatic scrolling which use gaze information as a primary input or as an augmented input. we also introduce the use off-screen gaze-actuated buttons for document navigation and control.
two-finger input with a standard touch screen. most current implementations of multi-touch screens are still too expensive or too bulky for widespread adoption. to improve this situation, this work describes the electronics and software needed to collect more data than one pair of coordinates from a standard 4-wire touch screen. with this system, one can measure the pressure of a single touch and approximately sense the coordinates of two touches occurring simultaneously. naturally, the system cannot offer the accuracy and versatility of full multi-touch screens. nonetheless, several example applications ranging from painting to zooming demonstrate a broad spectrum of use.
searchtogether: an interface for collaborative web search. studies of search habits reveal that people engage in many search tasks involving collaboration with others, such as travel planning, organizing social events, or working on a homework assignment. however, current web search tools are designed for a single user, working alone. we introduce searchtogether, a prototype that enables groups of remote users to synchronously or asynchronously collaborate when searching the web. we describe an example usage scenario, and discuss the ways searchtogether facilitates collaboration by supporting awareness, division of labor, and persistence. we then discuss the findings of our evaluation of searchtogether, analyzing which aspects of its design enabled successful collaboration among study participants.
e-conic: a perspective-aware interface for multi-display environments. multi-display environments compose displays that can be at different locations from and different angles to the user; as a result, it can become very difficult to manage windows, read text, and manipulate objects. we investigate the idea of perspective as a way to solve these problems in multi-display environments. we first identify basic display and control factors that are affected by perspective, such as visibility, fracture, and sharing. we then present the design and implementation of e-conic, a multi-display multi-user environment that uses location data about displays and users to dynamically correct perspective. we carried out a controlled experiment to test the benefits of perspective correction in basic interaction tasks like targeting, steering, aligning, pattern-matching and reading. our results show that perspective correction significantly and substantially improves user performance in all these tasks.
evaluating user interface systems research. the development of user interface systems has languished with the stability of desktop computing. future systems, however, that are off-the-desktop, nomadic or physical in nature will involve new devices and new software systems for creating interactive applications. simple usability testing is not adequate for evaluating complex systems. the problems with evaluating systems work are explored and a set of criteria for evaluating new ui systems work is presented.
shadow reaching: a new perspective on interaction for large displays. we introduce shadow reaching, an interaction technique that makes use of a perspective projection applied to a shadow representation of a user. the technique was designed to facilitate manipulation over large distances and enhance understanding in collaborative settings. we describe three prototype implementations that illustrate the technique, examining the advantages of using shadows as an interaction metaphor to support single users and groups of collaborating users. using these prototypes as a design probe, we discuss how the three components of the technique (sensing, modeling, and rendering) can be accomplished with real (physical) or computed (virtual) shadows, and the benefits and drawbacks of each approach.
specifying label layout style by example. creating high-quality label layouts in a particular visual style is a time-consuming process. although automated labeling algorithms can aid the layout process, expert design knowledge is required to tune these algorithms so that they produce layouts which meet the designer's expectations. we propose a system which can learn a labellayout style from a single example layout and then apply this style to new labeling problems. because designers find it much easier to create example layouts than tune algorithmic parameters, our system provides a more natural workflow for graphic designers. we demonstrate that our system is capable of learning a variety of label layout styles from examples.
lucid touch: a see-through mobile device. touch is a compelling input modality for interactive devices; however, touch input on the small screen of a mobile device is problematic because a user's fingers occlude the graphical elements he wishes to work with. in this paper, we present lucidtouch, a mobile device that addresses this limitation by allowing the user to control the application by touching the back of the device. the key to making this usable is what we call pseudo-transparency: by overlaying an image of the user's hands onto the screen, we create the illusion of the mobile device itself being semi-transparent. this pseudo-transparency allows users to accurately acquire targets while not occluding the screen with their fingers and hand. lucid touch also supports multi-touch input, allowing users to operate the device simultaneously with all 10 fingers. we present initial study results that indicate that many users found touching on the back to be preferable to touching on the front, due to reduced occlusion, higher precision, and the ability to make multi-finger input.
capturing the user's attention: insights from the study of human vision. an effective user interface is a cooperative interaction between humans and their technology. for that interaction to work, it needs to recognize the limitations and exploit the strengths of both parties. in this talk, i will concentrate on the human side of the equation. what do we know about human visual perceptual abilities that might have an impact on the design of user interfaces? the world presents us with more information than we can process. just try to read this abstract and the next piece of prose at the same time. we cope with this problem by using attentional mechanisms to select a subset of the input for further processing. an inter-face might be designed to .capture. attention, in order to induce a human to interact with it. once the human is using an interface, that interface should .guide. the user.s atten-tion in an intelligent manner. in recent decades, many of the rules of attentional capture and guidance have been worked out in the laboratory. i will illustrate some of the basic principles. for example: do some colors grab attention better than others? are faces special? when and why do people fail to .see. things that are right in front of their eyes.
sidesight: multi-"touch" interaction around small devices. interacting with mobile devices using touch can lead to fingers occluding valuable screen real estate. for the smallest devices, the idea of using a touch-enabled display is almost wholly impractical. in this paper we investigate sensing user touch around small screens like these. we describe a prototype device with infra-red (ir) proximity sensors embedded along each side and capable of detecting the presence and position of fingers in the adjacent regions. when this device is rested on a flat surface, such as a table or desk, the user can carry out single and multi-touch gestures using the space around the device. this gives a larger input space than would otherwise be possible which may be used in conjunction with or instead of on-display touch input. following a detailed description of our prototype, we discuss some of the interactions it affords.
an application-independent system for visualizing user operation history. a history-of-user-operations function helps make applications easier to use. for example, users may have access to an operation history list in an application to undo or redo a past operation. to provide an overview of a long operation history and help users find target interactions or application states quickly, visual representations of operation history have been proposed. however, most previous systems are tightly integrated with target applications and difficult to apply to new applications. we propose an application-independent method that can visualize the operation history of arbitrary gui applications by monitoring the input and output gui events from outside of the target application. we implemented a prototype system that visualizes operation sequences of generic java awt/swing applications using an annotated comic strip metaphor. we tested the system with various applications and present results from a user study.
cinch: a cooperatively designed marking interface for 3d pathway selection. to disentangle and analyze neural pathways estimated from magnetic resonance imaging data, scientists need an interface to select 3d pathways. broad adoption of such an interface requires the use of commodity input devices such as mice and pens, but these devices offer only two degrees of freedom. cinch solves this problem by providing a marking interface for 3d pathway selection. cinch interprets pen strokes as pathway selections in 3d using a marking language designed together with scientists. its bimanual interface employs a pen and a trackball (see figure 1), allowing alternating selections and scene rotations without changes of mode. cinch was evaluated by observing four scientists using the tool over a period of three weeks as part of their normal work activity. event logs and interviews revealed dramatic improvements in both the speed and quality of scientists' everyday work, and a set of principles that should inform the design of future 3d marking interfaces. more broadly, cinch demonstrates the value of the iterative, participatory design process that catalyzed its evolution.
the prod framework for proactive displays. a proactive display is an application that selects content to display based on the set of users who have been detected nearby. for example, the ticket2talk [17] proactive display application presented content for users so that other people would know something about them. it is our view that promising patterns for proactive display applications have been discovered, and now we face the need for frameworks to support the range of applications that are possible in this design space. in this paper, we present the proactive display (prod) framework, which allows for the easy construction of proactive display applications. it allows a range of proactive display applications, including ones already in the literature. prod also enlarges the design space of proactive display systems by allowing a variety of new applications that incorporate different views of social life and community.
from information visualization to direct manipulation: extending a generic visualization framework for the interactive editing of large datasets. today's generic data management applications such as accounting, crm or logging and tracking software, rely on form and menu based interfaces. these applications take only marginal advantage of current graphical user interfaces. this is because the data they handle does not have intrinsic visual representations upon which direct manipulation principles can be used. this article presents how we have extended an information visualization framework with generic data manipulation functions. these new data editing capabilities are tuned to take advantage of the characteristics of each view. they enable us to generalize the direct manipulation mechanisms to address many abstract data manipulation needs. in this article we present five uses of the features we have implemented and deduce a general workflow applicable to a variety of contexts. the workflow comprises three steps and five editing actions. the steps are: adjust view, select, and edit. the editing actions are: edit a value or group of values, clone objects, remove objects, add attributes, and remove attributes. the workflow provides complete editing access to table and hierarchical data structures using particularly terse interaction methods. it defines a general data editing model that enables powerful data manipulation tasks without requiring end-user programming or scripting.
design as exploration: creating interface alternatives through parallel authoring and runtime tuning. creating multiple prototypes facilitates comparative reasoning, grounds team discussion, and enables situated exploration. however, current interface design tools focus on creating single artifacts. this paper introduces the juxtapose code editor and runtime environment for designing multiple alternatives of both application logic and interface parameters. for rapidly comparing code alternatives, juxtapose introduces selectively parallel source editing and execution. to explore parameter variations, juxtapose automatically creates control interfaces for "tuning" application variables at runtime. this paper describes techniques to support design exploration for desktop, mobile, and physical interfaces, and situates this work in a larger design space of tools for explorative programming. a summative study of juxtapose with 18 participants demonstrated that parallel editing and execution are accessible to interaction designers and that designers can leverage these techniques to survey more options, faster.
soap: a pointing device that works in mid-air. soap is a pointing device based on hardware found in a mouse, yet works in mid-air. soap consists of an optical sensor device moving freely inside a hull made of fabric. as the user applies pressure from the outside, the optical sensor moves independent from the hull. the optical sensor perceives this relative motion and reports it as position input. soap offers many of the benefits of optical mice, such as high-accuracy sensing. we describe the design of a soap prototype and report our experiences with four application scenarios, including a wall display, windows media center, slide presentation, and interactive video games.
browsing large html tables on small screens. we propose new interaction techniques that support better browsing of large html tables on small screen devices, such as mobile phones. we propose three modes for browsing tables: normal mode, record mode, and cell mode. normal mode renders tables in the ordinary way, but provides various useful functions for browsing large tables, such as hiding unnecessary rows and columns. record mode regards each row (or column) as the basic information unit and displays it in a record-like format with column (or row) headers, while cell mode regards each cell as the basic unit and displays each cell together with its corresponding row and column headers. for these table presentations, we need to identify row and column headers that explain the meaning of rows and columns. to provide users with both row and column headers even when the tables have attributes for only one of them, we introduce the concept of keys and develop a method of automatically discovering attributes and keys in tables. another issue in these presentations is how to handle composite cells spanning multiple rows or columns. we determine the semantics of such composite cells and render them in appropriate ways in accordance with their semantics.
phosphor: explaining transitions in the user interface using afterglow effects. sometimes users fail to notice a change that just took place on their display. for example, the user may have accidentally deleted an icon or a remote collaborator may have changed settings in a control panel. animated transitions can help, but they force users to wait for the animation to complete. this can be cumbersome, especially in situations where users did not need an explanation. we propose a different approach. phosphor objects show the outcome of their transition instantly; at the same time they explain their change in retrospect. manipulating a phosphor slider, for example, leaves an afterglow that illustrates how the knob moved. the parallelism of instant outcome and explanation supports both types of users. users who already understood the transition can continue interacting without delay, while those who are inexperienced or may have been distracted can take time to view the effects at their own pace. we present a framework of transition designs for widgets, icons, and objects in drawing programs. we evaluate phosphor objects in two user studies and report significant performance benefits for phosphor objects.
an exploration of pen rolling for pen-based interaction. current pen input mainly utilizes the position of the pen tip, and occasionally, a button press. other possible device parameters, such as rolling the pen around its longitudinal axis, are rarely used. we explore pen rolling as a supporting input modality for pen-based interaction. through two studies, we are able to determine 1) the parameters that separate intentional pen rolling for the purpose of interaction from incidental pen rolling caused by regular writing and drawing, and 2) the parameter range within which accurate and timely intentional pen rolling interactions can occur. building on our experimental results, we present an exploration of the design space of rolling-based interaction techniques, which showcase three scenarios where pen rolling interactions can be useful: enhanced stimulus-response compatibility in rotation tasks [7], multi-parameter input, and simplified mode selection.
mnemonic rendering: an image-based approach for exposing hidden changes in dynamic displays. managing large amounts of dynamic visual information involves understanding changes happening out of the user's sight. in this paper, we show how current software does not adequately support users in this task, and motivate the need for a more general approach. we propose an image-based storage, visualization, and implicit interaction paradigm called mnemonic rendering that provides better support for handling visual changes. once implemented on a system, mnemonic rendering techniques can benefit all applications. we explore its rich design space and discuss its expected benefits as well as limitations based on feedback from users of a small-screen and a wall-size prototype.
towards more paper-like input: flexible input devices for foldable interaction styles. this paper presents foldable user interfaces (fui), a combination of a 3d gui with windows imbued with the physics of paper, and foldable input devices (fids). fids are sheets of paper that allow realistic transformations of graphical sheets in the fui. foldable input devices are made out of construction paper augmented with ir reflectors, and tracked by computer vision. window sheets can be picked up and flexed with simple movements and deformations of the fid. fids allow a diverse lexicon of one-handed and two-handed interaction techniques, including folding, bending, flipping and stacking. we show how these can be used to ease the creation of simple 3d models, but also for tasks such as page navigation.
interacting with dynamically defined information spaces using a handheld projector and a pen. the recent trend towards miniaturization of projection technology indicates that handheld devices will soon have the ability to project information onto any surface, thus enabling interfaces that are not possible with current handhelds. we explore the design space of dynamically defining and interacting with multiple virtual information spaces embedded in a physical environment using a handheld projector and a passive pen tracked in 3d. we develop techniques for defining and interacting with these spaces, and explore usage scenarios.
interactive viscosity. when the macintosh first made graphical user interfaces popular the notion of each person having their own computer was novel. today's technology landscape is characterized by multiple computers per person many with far more capacity than that original mac. the world of input devices, display devices and interactive techniques is far richer than those macintosh days. despite all of this diversity in possible interactions very few of these integrate well with each other. the monolithic isolated user interface architecture that characterized the macintosh still dominates a great deal of today's personal computing. this talk will explore how possible ways to change that architecture so that information, interaction and communication flows more smoothly among our devices and those of our associates.
an infrastructure for extending applications' user experiences across multiple personal devices. users increasingly interact with a heterogeneous collection of computing devices. the applications that users employ on those devices, however, still largely provide user experiences that assume the use of a single computer. this failure is due in part to the difficulty of creating user experiences that span multiple devices, particularly the need to manage identifying, connecting to, and communicating with other devices. in this paper we present an infrastructure based on instant messaging that simplifies adding that additional functionality to applications. our infrastructure elevates device ownership to a first class property, allowing developers to provide functionality that spans personal devices without writing code to manage users' devices or establish connections among them. it also provides simple mechanisms for applications to send information, events, or commands between a user's devices. we demonstrate the effectiveness of our infrastructure by presenting a set of sample applications built with it and a user study demonstrating that developers new to the infrastructure can implement all of the cross-device functionality for three applications in, on average, less than two and a half hours.
videotater: an approach for pen-based digital video segmentation and tagging. the continuous growth of media databases necessitates development of novel visualization and interaction techniques to support management of these collections. we present videotater, an experimental tool for a tablet pc that supports the efficient and intuitive navigation, selection, segmentation, and tagging of video. our veridical representation immediately signals to the user where appropriate segment boundaries should be placed and allows for rapid review and refinement of manually or automatically generated segments. finally, we explore a distribution of modalities in the interface by using multiple timeline representations, pressure sensing, and a tag painting/erasing metaphor with the pen.
living better with robots. the emerging field of human-robot interaction is undergoing rapid growth, motivated by important societal challenges and new applications for personal robotic technologies for the general public. in this talk, i highlight several projects from my research group to illustrate recent research trends to develop socially interactive robots that work and learn with people as partners. an important goal of this work is to use interactive robots as a scientific tool to understand human behavior, to explore the role of physical embodiment in interactive technology, and to use these insights to design robotic technologies that can enhance human performance and quality of life. throughout the talk i will highlight synergies with hci and connect hri research goals to specific applications in healthcare, education, and communication.
comparing and managing multiple versions of slide presentations. despite the ubiquity of slide presentations, managing multiple presentations remains a challenge. understanding how multiple versions of a presentation are related to one another, assembling new presentations from existing presentations, and collaborating to create and edit presentations are difficult tasks. in this paper, we explore techniques for comparing and managing multiple slide presentations. we propose a general comparison framework for computing similarities and differences between slides. based on this framework we develop an interactive tool for visually comparing multiple presentations. the interactive visualization facilitates understanding how presentations have evolved over time. we show how the interactive tool can be used to assemble new presentations from a collection of older ones and to merge changes from multiple presentation authors.
sphere: multi-touch interactions on a spherical display. sphere is a multi-user, multi-touch-sensitive spherical display in which an infrared camera used for touch sensing shares the same optical path with the projector used for the display. this novel configuration permits: (1) the enclosure of both the projection and the sensing mechanism in the base of the device, and (2) easy 360-degree access for multiple users, with a high degree of interactivity without shadowing or occlusion. in addition to the hardware and software solution, we present a set of multi-touch interaction techniques and interface concepts that facilitate collaborative interactions around sphere. we designed four spherical application concepts and report on several important observations of collaborative activity from our initial sphere installation in three high-traffic locations.
sensing from the basement: a feasibility study of unobtrusive and low-cost home activity recognition. the home deployment of sensor-based systems offers many opportunities, particularly in the area of using sensor-based systems to support aging in place by monitoring an elder's activities of daily living. but existing approaches to home activity recognition are typically expensive, difficult to install, or intrude into the living space. this paper considers the feasibility of a new approach that "reaches into the home" via the existing infrastructure. specifically, we deploy a small number of low-cost sensors at critical locations in a home's water distribution infrastructure. based on water usage patterns, we can then infer activities in the home. to examine the feasibility of this approach, we deployed real sensors into a real home for six weeks. among other findings, we show that a model built on microphone-based sensors that are placed away from systematic noise sources can identify 100% of clothes washer usage, 95% of dishwasher usage, 94% of showers, 88% of toilet flushes, 73% of bathroom sink activity lasting ten seconds or longer, and 81% of kitchen sink activity lasting ten seconds or longer. while there are clear limits to what activities can be detected when analyzing water usage, our new approach represents a sweet spot in the tradeoff between what information is collected at what cost.
hybridpointing: fluid switching between absolute and relative pointing with a direct input device. we present hybridpointing, a technique that lets users easily switch between absolute and relative pointing with a direct input device such as a pen. our design includes a new graphical element, the trailing widget, which remains "close at hand" but does not interfere with normal cursor operation. the use of visual feedback to aid the user's understanding of input state is discussed, and several novel visual aids are presented. an experiment conducted on a large, wall-sized display validates the benefits of hybridpointing under certain conditions. we also discuss other situations in which hybridpointing may be useful. finally, we present an extension to our technique that allows for switching between absolute and relative input in the middle of a single drag-operation.
creating map-based storyboards for browsing tour videos. watching a long unedited video is usually a boring experience. in this paper we examine a particular subset of videos, tour videos, in which the video is captured by walking about with a running camera with the goal of conveying the essence of some place. we present a system that makes the process of sharing and watching a long tour video easier, less boring, and more informative. to achieve this, we augment the tour video with a map-based storyboard, where the tour path is reconstructed, and coherent shots at different locations are directly visualized on the map. this allows the viewer to navigate the video in the joint location-time space. to create such a storyboard we employ an automatic pre-processing component to parse the video into coherent shots, and an authoring tool to enable the user to tie the shots with landmarks on the map. the browser-based viewing tool allows users to navigate the video in a variety of creative modes with a rich set of controls, giving each viewer a unique, personal viewing experience. informal evaluation shows that our approach works well for tour videos compared with conventional media players.
a direct texture placement and editing interface. the creation of most models used in computer animation and computer games requires the assignment of texture coordinates, texture painting, and texture editing. we present a novel approach for texture placement and editing based on direct manipulation of textures on the surface. compared to conventional tools for surface texturing, our system combines uv-coordinate specification and texture editing into one seamless process, reducing the need for careful initial design of parameterization and providing a natural interface for working with textures directly on 3d surfaces.a combination of efficient techniques for interactive constrained parameterization and advanced input devices makes it possible to realize a set of natural interaction paradigms. the texture is regarded as a piece of stretchable material, which the user can position and deform on the surface, selecting arbitrary sets of constraints and mapping texture points to the surface; in addition, the multi-touch input makes it possible to specify natural handles for texture manipulation using point constraints associated with different fingers. pressure can be used as a direct interface for texture combination operations. the 3d position of the object and its texture can be manipulated simultaneously using two-hand input.
foldable interactive displays. modern computer displays tend to be in fixed size, rigid, and rectilinear rendering them insensitive to the visual area demands of an application or the desires of the user. foldable displays offer the ability to reshape and resize the interactive surface at our convenience and even permit us to carry a very large display surface in a small volume. in this paper, we implement four interactive foldable display designs using image projection with low-cost tracking and explore display behaviors using orientation sensitivity.
the design and evaluation of selection techniques for 3d volumetric displays. volumetric displays, which display imagery in true 3d space, are a promising platform for the display and manipulation of 3d data. to fully leverage their capabilities, appropriate user interfaces and interaction techniques must be designed. in this paper, we explore 3d selection techniques for volumetric displays. in a first experiment, we find a ray cursor to be superior to a 3d point cursor in a single target environment. to address the difficulties associated with dense target environments we design four new ray cursor techniques which provide disambiguation mechanisms for multiple intersected targets. our techniques showed varied success in a second, dense target experiment. one of the new techniques, the depth ray, performed particularly well, significantly reducing movement time, error rate, and input device footprint in comparison to the 3d point cursor.
attribute gates. attribute gates are a new user interface element designed to address the problem of concurrently setting attributes and moving objects between territories on a digital tabletop. motivated by the notion of task levels in activity theory, and crossing interfaces, attribute gates allow users to operationalize multiple subtasks in one smooth movement. we present two configurations of attribute gates; (1) grid gates which spatially distribute attribute values in a regular grid, and require users to draw trajectories through the attributes; (2) polar gates which distribute attribute values on segments of concentric rings, and require users to align segments when setting attribute combinations. the layout of both configurations was optimised based on targeting and steering laws derived from fitts' law. a study compared the use of attribute gates with traditional contextual menus. users of attribute gates demonstrated both increased performance and higher mutual awareness.
viz: a visual analysis suite for explaining local search behavior. np-hard combinatorial optimization problems are common in real life. due to their intractability, local search algorithms are often used to solve such problems. since these algorithms are heuristic-based, it is hard to understand how to improve or tune them. we propose an interactive visualization tool, viz, meant for understanding the behavior of local search. viz uses animation of abstract search trajectories with other visualizations which are also animated in a vcr-like fashion to graphically playback the algorithm behavior. it combines generic visualizations applicable on arbitrary algorithms with algorithm and problem specific visualizations. we use a variety of techniques such as alpha blending to reduce visual clutter and to smooth animation, highlights and shading, automatically generated index points for playback, and visual comparison of two algorithms. the use of multiple viewpoints can be an effective way of understanding search behavior and highlight algorithm behavior which might otherwise be hidden.
kinematic templates: end-user tools for content-relative cursor manipulations. this paper introduces kinematic templates, an end-user tool for defining content-specific motor space manipulations in the context of editing 2d visual compositions. as an example, a user can choose the "sandpaper" template to define areas within a drawing where cursor movement should slow down. our current implementation provides templates that amplify or dampen the cursor's speed, attenuate jitter in a user's movement, guide movement along paths, and add forces to the cursor. multiple kinematic templates can be defined within a document, with overlapping templates resulting in a form of function composition. a template's strength can also be varied, enabling one to improve one's strokes without losing the human element. since kinematic templates guide movements, rather than strictly prescribe them, they constitute a visual composition aid that lies between unaided freehand drawing and rigid drawing aids such as snapping guides, masks, and perfect geometric primitives.
enabling web browsers to augment web sites' filtering and sorting functionalities. existing augmentations of web pages are mostly small cosmetic changes (e.g., removing ads) and minor addition of third-party content (e.g., product prices from competing sites). none leverages the structured data presented in web pages. this paper describes sifter, a web browser extension that can augment a well-structured web site with advanced filtering and sorting functionality. these added features work inside the site's own pages, preserving the site's presentational style and the user's context. sifter contains an algorithm that scrapes structured data out of well-structured web pages while usually requiring no user intervention. we tested sifter on real web sites and real users and found that people could use sifter to perform sophisticated queries and high-level analyses on sizable data collections on the web. we propose that web sites can be similarly augmented with other sophisticated data-centric functionality, giving users new benefits over the existing web.
lineogrammer: creating diagrams by drawing. we present the design of lineogrammer, a diagram-drawing system motivated by the immediacy and fluidity of pencil-drawing. we attempted for lineogrammer to feel like a modeless diagramming "medium" in which stylus input is immediately interpreted as a command, text label or a drawing element, and drawing elements snap to or sculpt from existing elements. an inferred dual representation allows geometric diagram elements, no matter how they were entered, to be manipulated at granularities ranging from vertices to lines to shapes. we also integrate lightweight tools, based on rulers and construction lines, for controlling higher-level diagram attributes, such as symmetry and alignment. we include preliminary usability observations to help identify areas of strength and weakness with this approach.
using a low-cost electroencephalograph for task classification in hci research. modern brain sensing technologies provide a variety of methods for detecting specific forms of brain activity. in this paper, we present an initial step in exploring how these technologies may be used to perform task classification and applied in a relevant manner to hci research. we describe two experiments showing successful classification between tasks using a low-cost off-the-shelf electroencephalograph (eeg) system. in the first study, we achieved a mean classification accuracy of 84.0% in subjects performing one of three cognitive tasks - rest, mental arithmetic, and mental rotation - while sitting in a controlled posture. in the second study, conducted in more ecologically valid setting for hci research, we attained a mean classification accuracy of 92.4% using three tasks that included non-cognitive features: a relaxation task, playing a pc based game without opponents, and engaging opponents within the game. throughout the paper, we provide lessons learned and discuss how hci researchers may utilize these technologies in their work.
ilovesketch: as-natural-as-possible sketching system for creating 3d curve models. we present ilovesketch, a 3d curve sketching system that captures some of the affordances of pen and paper for professional designers, allowing them to iterate directly on concept 3d curve models. the system coherently integrates existing techniques of sketch-based interaction with a number of novel and enhanced features. novel contributions of the system include automatic view rotation to improve curve sketchability, an axis widget for sketch surface selection, and implicitly inferred changes between sketching techniques. we also improve on a number of existing ideas such as a virtual sketchbook, simplified 2d and 3d view navigation, multi-stroke nurbs curve creation, and a cohesive gesture vocabulary. an evaluation by a professional designer shows the potential of our system for deployment within a real design process.
translating keyword commands into executable code. modern applications provide interfaces for scripting, but many users do not know how to write script commands. however, many users are familiar with the idea of entering keywords into a web search engine. hence, if a user is familiar with the vocabulary of an application domain, we anticipate that they could write a set of keywords expressing a command in that domain. for instance, in the web browsing domain, a user might enter <b>click search button</b>. we call expressions of this form keyword commands, and we present a novel approach for translating keyword commands directly into executable code. our prototype of this system in the web browsing domain translates <b>click search button</b> into the chickenfoot code <b>click(findbutton("search"))</b>. this code is then executed in the context of a web browser to carry out the effect. we also present an implementation of this system in the domain of microsoft word. a user study revealed that subjects could use keyword commands to successfully complete 90% of the web browsing tasks in our study without instructions or training. conversely, we would expect users to complete close to 0% of the tasks if they had to guess the underlying javascript commands with no instructions or training.
is the sky pure today? awkchecker: an assistive tool for detecting and correcting collocation errors. collocation preferences represent the commonly used expressions, idioms, and word pairings of a language. because collocation preferences arise from consensus usage, rather than a set of well-defined rules, they must be learned on a case-by-case basis, making them particularly challenging for non-native speakers of a language. to assist non-native speakers with these parts of a language, we developed awkchecker, the first end-user tool geared toward helping non-native speakers detect and correct collocation errors in their writing. as a user writes, awkchecker automatically flags collocation errors and suggests replacement expressions that correspond more closely to consensus usage. these suggestions include example usage to help users choose the best candidate. we describe awkchecker's interface, its novel methods for detecting collocation errors and suggesting alternatives, and an early study of its use by non-native english speakers at our institution. collectively, these contributions advance the state of the art in writing aids for non-native speakers.
brain-computer interaction. the promise of brain-computer interfaces (bci) technology is to augment human capabilities by enabling people to interact with a computer through a conscious and spontaneous modulation of their brainwaves after a short training period. indeed, by analyzing brain electrical activity online, several groups have designed brain-actuated systems that provide alternative channels for communication, entertainment and control. thus, a person can write messages using a virtual keyboard on a computer screen and also browse the internet. alternatively, subjects can operate simple computer games, or brain games, and interact with educational software. researchers have also been able to train monkeys to move a computer cursor to desired targets and also to control a robot arm. work with humans has shown that it is possible for them to move a cursor and even to drive a mobile robot between rooms in a house model. in this talk i will review the field of bci, with a focus on non-invasive systems based on electroencephalogram (eeg) signals. i will also describe three brain-actuated applications we have developed: a virtual keyboard, a brain game, and a mobile robot (emulating a motorized wheelchair). finally, we discuss current research directions we are pursuing in order to improve the performance and robustness of our bci system, especially for real-time control of brain-actuated robots.
scratch input: creating large, inexpensive, unpowered and mobile finger input surfaces. we present scratch input, an acoustic-based input technique that relies on the unique sound produced when a fingernail is dragged over the surface of a textured material, such as wood, fabric, or wall paint. we employ a simple sensor that can be easily coupled with existing surfaces, such as walls and tables, turning them into large, unpowered and ad hoc finger input surfaces. our sensor is sufficiently small that it could be incorporated into a mobile device, allowing any suitable surface on which it rests to be appropriated as a gestural input surface. several example applications were developed to demonstrate possible interactions. we conclude with a study that shows users can perform six scratch input gestures at about 90% accuracy with less than five minutes of training and on wide variety of surfaces.
huddle: automatically generating interfaces for systems of multiple connected appliances. systems of connected appliances, such as home theaters and presentation rooms, are becoming commonplace in our homes and workplaces. these systems are often difficult to use, in part because users must determine how to split the tasks they wish to perform into sub-tasks for each appliance and then find the particular functions of each appliance to complete their sub-tasks. this paper describes huddle, a new system that automatically generates task-based interfaces for a system of multiple appliances based on models of the content flow within the multi-appliance system.
taskposé: exploring fluid boundaries in an associative window visualization. window management research has aimed to leverage users' tasks to organize the growing number of open windows in a useful manner. this research has largely assumed task classifications to be binary -- either a window is in a task, or not -- and context-independent. we suggest that the continual evolution of tasks can invalidate this approach and instead propose a fuzzy association model in which windows are related to one another by varying degrees. task groupings are an emergent property of our approach. to support the association model, we introduce the windowrank algorithm and its use in determining window association. we then describe taskposé, a prototype window switch visualization embodying these ideas, and report on a week-long user study of the system.
procedural haptic texture. we present the haptic shading framework (hsf), a framework for procedurally defining haptic texture. hsf haptic texture shaders are short procedures allowing an application-programmer to easily define interesting haptic surface interaction and the parameters that control the surface properties. these shaders provide the illusion of surface characteristics by altering previously calculated forces from object collision in the haptic pipeline.hsf can be used in an existing haptic application with few modifications. the framework consists of user-programmable modules that are dynamically loaded. this framework and all user-defined procedures are written in c++, with a provided library of useful math and geometry functions. these functions are meant to mimic renderman functionality, creating a familiar shading environment. as we demonstrate, many procedural shading methods and algorithms can be directly adopted for haptic shading.
bringing physics to the surface. this paper explores the intersection of emerging surface technologies, capable of sensing multiple contacts and of-ten shape information, and advanced games physics engines. we define a technique for modeling the data sensed from such surfaces as input within a physics simulation. this affords the user the ability to interact with digital objects in ways analogous to manipulation of real objects. our technique is capable of modeling both multiple contact points and more sophisticated shape information, such as the entire hand or other physical objects, and of mapping this user input to contact forces due to friction and collisions within the physics simulation. this enables a variety of fine-grained and casual interactions, supporting finger-based, whole-hand, and tangible input. we demonstrate how our technique can be used to add real-world dynamics to interactive surfaces such as a vision-based tabletop, creating a fluid and natural experience. our approach hides from application developers many of the complexities inherent in using physics engines, allowing the creation of applications without preprogrammed interaction behavior or gesture recognition.
mobile interaction using paperweight metaphor. conventional scrolling methods for small sized display in pdas or mobile phones are difficult to use when frequent switching of scrolling and editing operations are required, for example, browsing and operating large sized www pages.in this paper, we have proposed a new user-interface method to provide seamless switching of scrolling / zooming mode and editing mode, based on a "paperweight metaphor". a sheet of paper that has been placed on a slippery table is difficult to draw on. therefore, in order to write or draw something on the sheet of paper, a person must secure the paper with his/her palm to avoid the paper from moving. this will be a good metaphor to design switching operation of scroll and editing modes.we have made a prototype system by placing a touch sensor under a pda screen where user's palm will be hit. we also have developed an application program to switch scrolling / editing mode by the sensor output and assessed our method.
inky: a sloppy command line for the web with rich visual feedback. we present inky, a command line for shortcut access to common web tasks. inky aims to capture the efficiency benefits of typed commands while mitigating their usability problems. inky commands have little or no new syntax to learn, and the system displays rich visual feedback while the user is typing, including missing parameters and contextual information automatically clipped from the target web site. inky is an example of a new kind of hybrid between a command line and a gui interface. we describe the design and implementation of two prototypes of this idea, and report the results of a preliminary user study.
modelcraft: capturing freehand annotations and edits on physical 3d models. with the availability of affordable new desktop fabrication techniques such as 3d printing and laser cutting, physical models are used increasingly often during the architectural and industrial design cycle. models can easily be annotated to capture comments, edits and other forms of feedback. unfortunately, these annotations remain in the physical world and cannot be easily transferred back to the digital world. here we present a simple solution to this problem based on a tracking pattern printed on the surface of each model. our solution is inexpensive, requires no tracking infrastructure or per object calibration, and can be used in the field without a computer nearby. it lets users not only capture annotations, but also edit the model using a simple yet versatile command system. once captured, annotations and edits are merged into the original cad models. there they can be easily edited or further refined. we present the design of a solidworks plug-in implementing this concept, and report initial feedback from potential users using our prototype. we also present how this prototype could be extended seamlessly to a fully functional system using current 3d printing technology.
hybrid infrared and visible light projection for location tracking. a number of projects within the computer graphics, computer vision, and human-computer interaction communities have recognized the value of using projected structured light patterns for the purposes of doing range finding, location dependent data delivery, projector adaptation, or object discovery and tracking. however, most of the work exploring these concepts has relied on visible structured light patterns resulting in a caustic visual experience. in this work, we present the first design and implementation of a high-resolution, scalable, general purpose invisible near-infrared projector that can be manufactured in a practical manner. this approach is compatible with simultaneous visible light projection and integrates well with future digital light processing (dlp) projector designs -- the most common type of projectors today. by unifying both the visible and non-visible pattern projection into a single device, we can greatly simply the implementation and execution of interactive projection systems. additionally, we can inherently provide location discovery and tracking capabilities that are unattainable using other approaches.
iterative design and evaluation of an event architecture for pen-and-paper interfaces. this paper explores architectural support for interfaces combining pen, paper, and pc. we show how the event-based approach common to guis can apply to augmented paper, and describe additions to address paper's distinguishing characteristics. to understand the developer experience of this architecture, we deployed the toolkit to 17 student teams for six weeks. analysis of the developers' code provided insight into the appropriateness of events for paper uis. the usage patterns we distilled informed a second iteration of the toolkit, which introduces techniques for integrating interactive and batched input handling, coordinating interactions across devices, and debugging paper applications. the study also revealed that programmers created gesture handlers by composing simple ink measurements. this desire for informal interactions inspired us to include abstractions for recognition. this work has implications beyond paper - designers of graphical tools can examine api usage to inform iterative toolkit development.
octopocus: a dynamic guide for learning gesture-based command sets. we describe octopocus, an example of a dynamic guide that combines on-screen feedforward and feedback to help users learn, execute and remember gesture sets. octopocus can be applied to a wide range of single-stroke gestures and recognition algorithms and helps users progress smoothly from novice to expert performance. we provide an analysis of the design space and describe the results of two experi-ments that show that octopocus is significantly faster and improves learning of arbitrary gestures, compared to con-ventional help menus. it can also be adapted to a mark-based gesture set, significantly improving input time compared to a two-level, four-item hierarchical marking menu.
multi-layer interaction for digital tables. interaction on digital tables has been restricted to a single layer on the table's active work-surface. we extend the design space of digital tables to include multiple layers of interaction. we leverage 3d position information of a pointing device to support interaction in the space above the active work-surface by creating multiple layers with drift-correction in which the user can interact with an application. we also illustrate through a point-design that designers can use multiple-layers to create a rich and clutter free application. a subjective evaluation showed that users liked the interaction techniques and found that, because of the drift correction we use, they could control the pointer when working in any layer.
edge-respecting brushes. digital paint is one of the more successful interactive applications of computing. brushes that apply various effects to an image have been central to this success. current painting techniques ignore the underlying image. by considering that image we can help the user paint more effectively. there are algorithms that assist in selecting regions to paint including flood fill, intelligent scissors and graph cut. selected regions and the algorithms to create them introduce conceptual layers between the user and the painting task. we propose a series of "edge-respecting brushes" that spread paint or other effects according to the edges and texture of the image being modified. this restores the simple painting metaphor while providing assistance in working with the shapes already in the image. our most successful fill brush algorithm uses competing least-cost-paths to identify what should be selected and what should not.
camera phone based motion sensing: interaction techniques, applications and performance study. this paper presents tinymotion, a pure software approach for detecting a mobile phone user's hand movement in real time by analyzing image sequences captured by the built-in camera. we present the design and implementation of tinymotion and several interactive applications based on tinymotion. through both an informal evaluation and a formal 17-participant user study, we found that 1. tinymotion can detect camera movement reliably under most background and illumination conditions. 2. target acquisition tasks based on tinymotion follow fitts' law and fitts law parameters can be used for tinymotion based pointing performance measurement. 3. the users can use vision tilttext, a tinymotion enabled input method, to enter sentences faster than multitap with a few minutes of practicing. 4. using camera phone as a handwriting capture device and performing large vocabulary, multilingual real time handwriting recognition on the cell phone are feasible. 5. tinymotion based gaming is enjoyable and immediately available for the current generation camera phones. we also report user experiences and problems with tinymotion based interaction as resources for future design and development of mobile interfaces.
backward highlighting: enhancing faceted search. directional faceted browsers, such as the popular column browser itunes, let a person pick an instance from any column-facet to start their search for music. the expected effect is that any columns to the right are filtered. in keeping with this directional filtering from left to right, however, the unexpected effect is that the columns to the left of the click provide no information about the possible associations to the selected item. in itunes, this means that any selection in the album column on the right returns no information about either the artists (immediate left) or genres (leftmost) associated with the chosen album. backward highlighting (bh) is our solution to this problem, which allows users to see and utilize, during search, associations in columns to the left of a selection in a directional column browser like itunes. unlike other possible solutions, this technique allows such browsers to keep direction in their filtering, and so provides users with the best of both directional and non-directional styles. as well as describing bh in detail, this paper presents the results of a formative user study, showing benefits for both information discovery and subsequent retention in memory.
highlight: a system for creating and deploying mobile web applications. we present a new server-side architecture that enables rapid prototyping and deployment of mobile web applications created from existing web sites. key to this architecture is a remote control metaphor in which the mobile device controls a fully functional browser that is embedded within a proxy server. content is clipped from the proxy browser, transformed if necessary, and then sent to the mobile device as a typical web page. users' interactions with that content on the mobile device control the next steps of the proxy browser. we have found this approach to work well for creating mobile sites from a variety of existing sites, including those that use dynamic html and ajax technologies. we have conducted a small user study to evaluate our model and api with experienced web programmers.
interactive environment-aware display bubbles. we present a novel display metaphor which extends traditional tabletop projections in collaborative environments by introducing freeform, environment-aware display representations and a matching set of interaction schemes. for that purpose, we map personalized widgets or ordinary computer applications that have been designed for a conventional, rectangular layout into space-efficient bubbles whose warping is performed with a potential-based physics approach. with a set of interaction operators based on laser pointer tracking, these freeform displays can be transformed and elastically deformed using focus and context visualization techniques. we also provide operations for intuitive instantiation of bubbles, cloning, cut & pasting, deletion and grouping in an interactive way, and we allow for user-drawn annotations and text entry using a projected keyboard. additionally, an optional environment-aware adaptivity of the displays is achieved by imperceptible, realtime scanning of the projection geometry. subsequently, collision-responses of the bubbles with non-optimal surface parts are computed in a rigid body simulation. the extraction of the projection surface properties runs concurrently with the main application of the system. our approach is entirely based on off the-shelf, low-cost hardware including dlp-projectors and firewire cameras.
going beyond the display: a surface technology with an electronically switchable diffuser. we introduce a new type of interactive surface technology based on a switchable projection screen which can be made diffuse or clear under electronic control. the screen can be continuously switched between these two states so quickly that the change is imperceptible to the human eye. it is then possible to rear-project what is perceived as a stable image onto the display surface, when the screen is in fact transparent for half the time. the clear periods may be used to project a second, different image through the display onto objects held above the surface. at the same time, a camera mounted behind the screen can see out into the environment. we explore some of the possibilities this type of screen technology affords, allowing surface computing interactions to extend 'beyond the display'. we present a single self-contained system that combines these off-screen interactions with more typical multi-touch and tangible surface interactions. we describe the technical challenges in realizing our system, with the aim of allowing others to experiment with these new forms of interactive surfaces.
qume: a mechanism to support expertise finding in online help-seeking communities. help-seeking communities have been playing an increasingly critical role in the way people seek and share information. however, traditional help-seeking mechanisms of these online communities have some limitations. in this paper, we describe an expertise-finding mechanism that attempts to alleviate the limitations caused by not knowing users' expertise levels. as a result of using social network data from the online community, this mechanism can automatically infer expertise level. this allows, for example, a question list to be personalized to the user's expertise level as well as to keyword similarity. we believe this expertise location mechanism will facilitate the development of next generation help-seeking communities.
enabling efficient orienteering behavior in webmail clients. webmail clients provide millions of end users with convenient and ubiquitous access to electronic mail - the most successful collaboration tool ever. web email clients are also the platform of choice for recent innovations on electronic mail and for integration of related information services into email. in the enterprise, however, webmail applications have been relegated to being a supplemental tool for mail access from home or while on the road. in this paper, we draw on recent research in the area of electronic mail to understand usage models and performance requirements for enterprise email applications. we then present an innovative architecture for a webmail client. by leveraging recent advances in web browser technology, we show that webmail clients can offer performance and responsiveness that rivals a desktop application while still retaining all the advantages of a browser based client.
zoetrope: interacting with the ephemeral web. the web is ephemeral. pages change frequently, and it is nearly impossible to find data or follow a link after the underlying page evolves. we present zoetrope, a system that enables interaction with the historicalweb (pages, links, and embedded data) that would otherwise be lost to time. using a number of novel interactions, the temporal web can be manipulated, queried, and analyzed from the context of familar pages. zoetrope is based on a set of operators for manipulating content streams. we describe these primitives and the associated indexing strategies for handling temporal web data. they form the basis of zoetrope and enable our construction of new temporal interactions and visualizations.
measuring how design changes cognition at work. the various fields associated with interactive software systems engage in design activities to enable people who would use the resulting systems to meet goals, coordinate with others, find meaning, and express themselves in myriad ways. yet many development projects fail, and we all have contact with clumsy software-based systems that force work-arounds and impose substantial attentional, knowledge and workload burdens. on the other hand, field observations reveal people re-shaping the artifacts they encounter and interact with as resources to cope with the demands of the situations they face as they seek to meet their goals. in this process some new devices are quickly seized upon and exploited in ways that transform the nature of human activity, connections, and expression. the software intensive interactive systems and devices under development around us are valuable to the degree that they expand what people in various roles and organizations can achieve. how can we measure this value provided to others? are current measures of usability adequate? does creeping complexity wipe out incremental gains as products evolve? do designers and developers mis-project the impact when systems-to-be-realized are fielded? which technology changes will trigger waves of expansive adaptations that transform what people do and even why they do it. sponsors of projects to develop new interactive software systems are asking developers for tangible evidence of the value to be delivered to those people responsible for activities and goals in the world. traditional measures of usability and human performance seem inadequate. cycles of inflation in the claims development organizations make (and the legacy of disappointment and surprise) have left sponsors numb and eroded trust. thus, we need to provide new forms of evidence about the potential of new interactive systems and devices to enhance human capability. luckily, this need has been accompanied by a period of innovation in ways to measure the impact of new designs on: growth of expertise in roles,synchronizing activities over wider scopes and ranges,expanding adaptive capacities.. this talk reviews a few of the new measures being tested in each of these categories, points to some of the underlying science, and uses these examples to trigger discussion about how design of future interactive software provides will provide value to stakeholders.
search vox: leveraging multimodal refinement and partial knowledge for mobile voice search. internet usage on mobile devices continues to grow as users seek anytime, anywhere access to information. because users frequently search for businesses, directory assistance has been the focus of many voice search applications utilizing speech as the primary input modality. unfortunately, mobile settings often contain noise which degrades performance. as such, we present search vox, a mobile search interface that not only facilitates touch and text refinement whenever speech fails, but also allows users to assist the recognizer via text hints. search vox can also take advantage of any partial knowledge users may have about the business listing by letting them express their uncertainty in an intuitive way using verbal wildcards. in simulation experiments conducted on real voice search data, leveraging multimodal refinement resulted in a 28% relative reduction in error rate. providing text hints along with the spoken utterance resulted in even greater relative reduction, with dramatic gains in recovery for each additional character.
tapping and rubbing: exploring new dimensions of tactile feedback with voice coil motors. tactile feedback allows devices to communicate with users when visual and auditory feedback are inappropriate. unfortunately, current vibrotactile feedback is abstract and not related to the content of the message. this often clash-es with the nature of the message, for example, when sending a comforting message. we propose addressing this by extending the repertoire of haptic notifications. by moving an actuator perpendicular to the user's skin, our prototype device can tap the user. moving the actuator parallel to the user's skin induces rub-bing. unlike traditional vibrotactile feedback, tapping and rubbing convey a distinct emotional message, similar to those induced by human-human touch. to enable these techniques we built a device we call soundtouch. it translates audio wave files into lateral motion using a voice coil motor found in computer hard drives. soundtouch can produce motion from below 1hz to above 10khz with high precision and fidelity. we present the results of two exploratory studies. we found that participants were able to distinguish a range of taps and rubs. our findings also indicate that tapping and rubbing are perceived as being similar to touch interactions exchanged by humans.
socially augmenting employee profiles with people-tagging. employee directories play a valuable role in helping people find others to collaborate with, solve a problem, or provide needed expertise. serving this role successfully requires accurate and up-to-date user profiles, yet few users take the time to maintain them. in this paper, we present a system that enables users to tag other users with key words that are displayed on their profiles. we discuss how people-tagging is a form of social bookmarking that enables people to organize their contacts into groups, annotate them with terms supporting future recall, and search for people by topic area. in addition, we show that people-tagging has a valuable side benefit: it enables the community to collectively maintain each others' interest and expertise profiles. our user studies suggest that people tag other people as a form of contact management and that the tags they have been given are accurate descriptions of their interests and expertise. moreover, none of the people interviewed reported offensive or inappropriate tags. based on our results, we believe that peopletagging will become an important tool for relationship management in an organization.
a unidraw-based user interface builder. ibuild is a user interface builder that lets a user manipulate simulations of toolkit objects rather than actual toolkit objects. ibuild is built with unidraw, a framework for building graphical editors that is part of the interviews toolkit. unidraw makes the simulation-based approach attractive. simulating toolkit objects in unidraw makes it easier to support editing facilities that are common in other kinds of graphical editors, and it keeps the builder insulated from a particular toolkit implementation. ibuild supports direct manipulation analogs of interviews'' composition mechanisms, which simplify the specification of an interface''s layout and resize semantics. ibuild also leverages the c++ inheritance mechanism to decouple builder-generated code from the rest of the application. and while current user interface builders stop at the widget level, ibuild incorporates unidraw abstractions to simplify the implementation of graphical editors.
the picasso applications framework. picasso is a graphical user interface development system that includes an interface toollkit and an application framework. the application framework provides high-level abstractions including modal dialog boxes and non-modal frames and panels similar to conventional programming language procedures and co-routines. these abstractions can be used to define objects that have local variables and that can be called with parameters. picasso also has a constraint system that is used to bind program variables to widgets, to implement triggered behaviors, and to implement multiple views of data. the system is implemented in common lisp using the common lisp object system and the clx interface to the x window system. keywords: graphical user interface development environment, application framework, user interface toolkit, user interfaces.
extending 2d object arrangement with pressure-sensitive layering cues. we demonstrate a pressure-sensitive depth sorting technique that extends standard two-dimensional (2d) manipulation techniques, particularly those used with multi-touch or multi-point controls. we combine this layering operation with a page-folding metaphor for more fluid interaction in applications requiring 2d sorting and layout.
lightweight material detection for placement-aware mobile computing. numerous methods have been proposed that allow mobile devices to determine where they are located (e.g., home or office) and in some cases, predict what activity the user is currently engaged in (e.g., walking, sitting, or driving). while useful, this sensing currently only tells part of a much richer story. to allow devices to act most appropriately to the situation they are in, it would also be very helpful to know about their placement - for example whether they are sitting on a desk, hidden in a drawer, placed in a pocket, or held in one's hand - as different device behaviors may be called for in each of these situations. in this paper, we describe a simple, small, and inexpensive multispectral optical sensor for identifying materials in proximity to a device. this information can be used in concert with e.g., location information, to estimate, for example, that the device is "sitting on the desk at home", or "in the pocket at work". this paper discusses several potential uses of this technology, as well as results from a two-part study, which indicates that this technique can detect placement at 94.4% accuracy with real-world placement sets.
annotating gigapixel images. panning and zooming interfaces for exploring very large images containing billions of pixels (gigapixel images) have recently appeared on the internet. this paper addresses issues that arise when creating and rendering auditory and textual annotations for such images. in particular, we define a distance metric between each annotation and any view resulting from panning and zooming on the image. the distance then informs the rendering of audio annotations and text labels. we demonstrate the annotation system on a number of panoramic images.
continuum: designing timelines for hierarchies, relationships and scale. temporal events, while often discrete, also have interesting relationships within and across times: larger events are often collections of smaller more discrete events (battles within wars; artists' works within a form); events at one point also have correlations with events at other points (a play written in one period is related to its performance over a period of time). most temporal visualisations, however, only represent discrete data points or single data types along a single timeline: this event started here and ended there; this work was published at this time; this tag was popular for this period. in order to represent richer, faceted attributes of temporal events, we present continuum. continuum enables hierarchical relationships in temporal data to be represented and explored; it enables relationships between events across periods to be expressed, and in particular it enables user-determined control over the level of detail of any facet of interest so that the person using the system can determine a focus point, no matter the level of zoom over the temporal space. we present the factors motivating our approach, our evaluation and implementation of this new visualisation which makes it easy for anyone to apply this interface to rich, large-scale datasets with temporal data.
opa browser: a web browser for cellular phone users. cellular phones are widely used to access the www. however, most available web pages are designed for desktop pcs. cellular phones only have small screens and poor interfaces, and thus, it is inconvenient to browse such large sized pages. in addition, cellular phone users browse web pages in various situations, so that appropriate presentation styles for web pages depend on users' situations. in this paper, we propose a novel web browsing system for cellular phones that allocates various functions for web browsing on each numerical key of a cellular phone. users can browse web pages comfortably, selecting appropriate functions according to their situations by pushing a single button.
multi-user interaction using handheld projectors. recent research on handheld projector interaction has expanded the display and interaction space of handheld devices by projecting information onto the physical environment around the user, but has mainly focused on single-user scenarios. we extend this prior single-user research to co-located multi-user interaction using multiple handheld projectors. we present a set of interaction techniques for supporting co-located collaboration with multiple handheld projectors, and discuss application scenarios enabled by them.
rubberedge: reducing clutching by combining position and rate control with elastic feedback. position control devices enable precise selection, but significant clutching degrades performance. clutching can be reduced with high control-display gain or pointer acceleration, but there are human and device limits. elastic rate control eliminates clutching completely, but can make precise selection difficult. we show that hybrid position-rate control can outperform position control by 20% when there is significant clutching, even when using pointer acceleration. unlike previous work, our rubberedge technique eliminates trajectory and velocity discontinuities. we derive predictive models for position control with clutching and hybrid control, and present a prototype rubberedge position-rate control device including initial user feedback.
sketchwizard: wizard of oz prototyping of pen-based user interfaces. sketchwizard allows designers to create wizard of oz prototypes of pen-based user interfaces in the early stages of design. in the past, designers have been inhibited from participating in the design of pen-based interfaces because of the inadequacy of paper prototypes and the difficulty of developing functional prototypes. in sketchwizard, designers and end users share a drawing canvas between two computers, allowing the designer to simulate the behavior of recognition or other technologies. special editing features are provided to help designers respond quickly to end-user input. this paper describes the sketchwizard system and presents two evaluations of our approach. the first is an early feasibility study in which wizard of oz was used to prototype a pen-based user interface. the second is a laboratory study in which designers used sketchwizard to simulate existing pen-based interfaces. both showed that end users gave valuable feedback in spite of delays between end-user actions and wizard updates.
relations, cards, and search templates: user-guided web data integration and layout. we present three new interaction techniques for aiding users in collecting and organizing web content. first, we demonstrate an interface for creating associations between websites, which facilitate the automatic retrieval of related content. second, we present an authoring interface that allows users to quickly merge content from many different websites into a uniform and personalized representation, which we call a card. finally, we introduce a novel search paradigm that leverages the relationships in a card to direct search queries to extract relevant content from multiple web sources and fill a new series of cards instead of just returning a list of webpage urls. preliminary feedback from users is positive andvalidates our design.
automatically generating user interfaces adapted to users' motor and vision capabilities. most of today's guis are designed for the typical, able-bodied user; atypical users are, for the most part, left to adapt as best they can, perhaps using specialized assistive technologies as an aid. in this paper, we present an alternative approach: supple++ automatically generates interfaces which are tailored to an individual's motor capabilities and can be easily adjusted to accommodate varying vision capabilities. supple++ models users. motor capabilities based on a onetime motor performance test and uses this model in an optimization process, generating a personalized interface. a preliminary study indicates that while there is still room for improvement, supple++ allowed one user to complete tasks that she could not perform using a standard interface, while for the remaining users it resulted in an average time savings of 20%, ranging from an slowdown of 3% to a speedup of 43%.
rethinking the progress bar. progress bars are prevalent in modern user interfaces. typically, a linear function is employed such that the progress of the bar is directly proportional to how much work has been completed. however, numerous factors cause progress bars to proceed at non-linear rates. additionally, humans perceive time in a non-linear way. this paper explores the impact of various progress bar behaviors on user perception of process duration. the results are used to suggest several design considerations that can make progress bars appear faster and ultimately improve users' computing experience.
programming by a sample: rapidly creating web applications with d.mix. source-code examples of apis enable developers to quickly gain a gestalt understanding of a library's functionality, and they support organically creating applications by incrementally modifying a functional starting point. as an increasing number of web sites provide apis, significantlatent value lies in connecting the complementary representations between site and service - in essence, enabling sites themselves to be the example corpus. we introduce d.mix, a tool for creating web mashups that leverages this site-to-service correspondence. with d.mix, users browse annotated web sites and select elements to sample. d.mix's sampling mechanism generates the underlying service calls that yield those elements. this code can be edited, executed, and shared in d.mix's wiki-based hosting environment. this sampling approach leverages pre-existing web sites as example sets and supports fluid composition and modification of examples. an initial study with eight participants found d.mix to enable rapid experimentation, and suggested avenues for improving its annotation mechanism.
thinsight: versatile multi-touch sensing for thin form-factor displays. thinsight is a novel optical sensing system, fully integrated into a thin form factor display, capable of detecting multi-ple fingers placed on or near the display surface. we describe this new hardware in detail, and demonstrate how it can be embedded behind a regular lcd, allowing sensing without degradation of display capability. with our approach, fingertips and hands are clearly identifiable through the display. the approach of optical sensing also opens up the exciting possibility for detecting other physical objects and visual markers through the display, and some initial experiments are described. we also discuss other novel capabilities of our system: interaction at a distance using ir pointing devices, and ir-based communication with other electronic devices through the display. a major advantage of thinsight over existing camera and projector based optical systems is its compact, thin form-factor making such systems even more deployable. we therefore envisage using thinsight to capture rich sensor data through the display which can be processed using computer vision techniques to enable both multi-touch and tangible interaction.
graphstract: minimal graphical help for computers. we explore the use of abstracted screenshots as part of a new help interface. graphstract, an implementation of a graphical help system, extends the ideas of textually oriented minimal manuals to the use of screenshots, allowing multiple small graphical elements to be shown in a limited space. this allows a user to get an overview of a complex sequential task as a whole. the ideas have been developed by three iterations of prototyping and evaluation. a user study shows that graphstract helps users perform tasks faster on some but not all tasks. due to their graphical nature, it is possible to construct graphstracts automatically from pre-recorded interactions. a second study shows that automated capture and replay is a low-cost method for authoring graphstracts, and the resultant help is as understandable as manually constructed help.
dirty desktops: using a patina of magnetic mouse dust to make common interactor targets easier to select. a common task in graphical user interfaces is controlling onscreen elements using a pointer. current adaptive pointing techniques require applications to be built using accessibility libraries that reveal information about interactive targets, and most do not handle path/menu navigation. we present a pseudo-haptic technique that is os and application independent, and can handle both dragging and clicking. we do this by associating a small force with each past click or drag. when a user frequently clicks in the same general area (e.g., on a button), the patina of past clicks naturally creates a pseudo-haptic magnetic field with an effect similar to that ofsnapping or sticky icons. our contribution is a bottom-up approach to make targets easier to select without requiring prior knowledge of them.
boomerang: suspendable drag-and-drop interactions based on a throw-and-catch metaphor. we present the boomerang technique, which makes it possible to suspend and resume drag-and-drop operations. a throwing gesture while dragging an object suspends the operation, anytime and anywhere. a drag-and-drop interaction, enhanced with our technique, allows users to switch windows, invoke commands, and even drag other objects during a drag-and-drop operation without using the keyboard or menus. we explain how a throwing gesture can suspend drag-and-drop operations, and describe other features of our technique, including grouping, copying, and deleting dragged objects. we conclude by presenting prototype implementations and initial feedback on the proposed technique.
eyepatch: prototyping camera-based interaction through examples. cameras are a useful source of input for many interactive applications, but computer vision programming is difficult and requires specialized knowledge that is out of reach for many hci practitioners. in an effort to learn what makes a useful computer vision design tool, we created eyepatch, a tool for designing camera-based interactions, and evaluated the eyepatch prototype through deployment to students in an hci course. this paper describes the lessons we learned about making computer vision more accessible, while retaining enough power and flexibility to be useful in a wide variety of interaction scenarios.
robust, low-cost, non-intrusive sensing and recognition of seated postures. in this paper, we present a methodology for recognizing seated postures using data from pressure sensors installed on a chair. information about seated postures could be used to help avoid adverse effects of sitting for long periods of time or to predict seated activities for a human-computer interface. our system design displays accurate near-real-time classification performance on data from subjects on which the posture recognition system was not trained by using a set of carefully designed, subject-invariant signal features. by using a near-optimal sensor placement strategy, we keep the number of required sensors low thereby reducing cost and computational complexity. we evaluated the performance of our technology using a series of empirical methods including (1) cross-validation (classification accuracy of 87% for ten postures using data from 31 sensors), and (2) a physical deployment of our system (78% classification accuracy using data from 19 sensors).
blui: low-cost localized blowable user interfaces. we describe a unique form of hands-free interaction that can be implemented on most commodity computing platforms. our approach supports blowing at a laptop or computer screen to directly control certain interactive applications. localization estimates are produced in real-time to determine where on the screen the person is blowing. our approach relies solely on a single microphone, such as those already embedded in a standard laptop or one placed near a computer monitor, which makes our approach very cost-effective and easy-to-deploy. we show example interaction techniques that leverage this approach.
the re: search engine: simultaneous support for finding and re-finding. re-finding, a common web task, is difficult when previously viewed information is modified, moved, or removed. for example, if a person finds a good result using the query "breast cancer treatments", she expects to be able to use the same query to locate the same result again. while re-finding could be supported by caching the original list, caching precludes the discovery of new information, such as, in this case, new treatment options. people often use search engines to simultaneously find and re-find information. the re:search engine is designed to support both behaviors in dynamic environments like the web by preserving only the memorable aspects of a result list. a study of result list memory shows that people forget a lot. the re:search engine takes advantage of these memory lapses to include new results where old results have been forgotten.
bubble clusters: an interface for manipulating spatial aggregation of graphical objects. spatial layout is frequently used for managing loosely organized information, such as desktop icons and digital ink. to help users organize this type of information efficiently, we propose an interface for manipulating spatial aggregations of objects. the aggregated objects are automatically recognized as a group, and the group structure is visualized as a two-dimensional bubble surface that surrounds the objects. users can drag, copy, or delete a group by operating on the bubble. furthermore, to help pick out individual objects in a dense aggregation, the system spreads the objects to avoid overlapping when requested. this paper describes the design of this interface and its implementation. we tested our technique in icon grouping and ink relocation tasks and observed improvements in user performance.
gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes. although mobile, tablet, large display, and tabletop computers increasingly present opportunities for using pen, finger, and wand gestures in user interfaces, implementing gesture recognition largely has been the privilege of pattern matching experts, not user interface prototypers. although some user interface libraries and toolkits offer gesture recognizers, such infrastructure is often unavailable in design-oriented environments like flash, scripting environments like javascript, or brand new off-desktop prototyping environments. to enable novice programmers to incorporate gestures into their ui prototypes, we present a "$1 recognizer" that is easy, cheap, and usable almost anywhere in about 100 lines of code. in a study comparing our $1 recognizer, dynamic time warping, and the rubine classifier on user-supplied gestures, we found that $1 obtains over 97% accuracy with only 1 loaded template and 99% accuracy with 3+ loaded templates. these results were nearly identical to dtw and superior to rubine. in addition, we found that medium-speed gestures, in which users balanced speed and accuracy, were recognized better than slow or fast gestures for all three recognizers. we also discuss the effect that the number of templates or training examples has on recognition, the score falloff along recognizers' n-best lists, and results for individual gestures. we include detailed pseudocode of the $1 recognizer to aid development, inspection, extension, and testing.
a model for input and output of multilingual text in a windowing environment. the layered multilingual input/output(i/o) sytems we designed, based on typological studies of major-language writing conventions, unifies common features of such conventions to enable international and local utilization. the internationalization layer input module converts keystroke sequences to phonograms and ideograms. the corresponding output module displays position-independent and dependent characters. the localization layer positions language-specific functions outside the structure, integrating them as tables used by finite automaton interpreters and servers to add new languages and code sets without recompilation. the i/o system generates and displays stateful and stateless code sets, enabling interactive language switching. going beyond posix locale model bounds, the system generates iso 2022, iso/dis 10646 (1990), and compound text, defined for the interchange encoding format in x11 protocols, for basic polyglot text communication and processing. able to generate multilingual code sets, the i/o system clearly demonstrates that code sets should be selected by applications which have purposes beyond selecting one element from a localization set. functionality and functions related to text manipulation in an operating sytem (os) must also be determined by such applications. a subset of this i/o system was implemented in the x window system as a basic use of x11r5 i/o by supplying basic code set generation and string manipulation to eliminate os interference. to ensure polyglot string manipulation, the i/o system must clearly be implemented separately from an os and its limitations.
re-framing the desktop interface around the activities of knowledge work. the venerable desktop metaphor is beginning to show signs of strain in supporting modern knowledge work. in this paper, we examine how the desktop metaphor can be re-framed, shifting the focus away from a low-level (and increasingly obsolete) focus on documents and applications to an interface based upon the creation of and interaction with manually declared, semantically meaningful activities. we begin by unpacking some of the foundational assumptions of desktop interface design, describe an activity-based model for organizing the desktop interface based on theories of cognition and observations of real-world practice, and identify a series of high-level system requirements for interfaces that use activity as their primary organizing principle. based on these requirements, we present the novel interface design of the giornata system, a prototype activity-based desktop interface, and share initial findings from a longitudinal deployment of the giornata system in a real-world setting.
video object annotation, navigation, and composition. we explore the use of tracked 2d object motion to enable novel approaches to interacting with video. these include moving annotations, video navigation by direct manipulation of objects, and creating an image composite from multiple video frames. features in the video are automatically tracked and grouped in an off-line preprocess that enables later interactive manipulation. examples of annotations include speech and thought balloons, video graffiti, path arrows, video hyperlinks, and schematic storyboards. we also demonstrate a direct-manipulation interface for random frame access using spatial constraints, and a drag-and-drop interface for assembling still images from videos. taken together, our tools can be employed in a variety of applications including film and video editing, visual tagging, and authoring rich media such as hyperlinked video.
the uvm virtual memory system. we introduce uvm, a new virtual memory system for the bsd kernel that has an improved design that increases system performance over the old mach-based 4.4bsd vm system. in this paper we present an overview of both uvm and the bsd vm system. we focus our discussion on the design decisions made when creating uvm and contrast the uvm design with the less efficient bsd vm design. topics covered include mapping, memory object management, anonymous memory and copy-on-write mechanisms, and pager design. we also present an overview of virtual memory based data movement mechanisms that have been introduced in bsd by uvm. we believe that the lessons we learned from designing and implementing uvm can be applied to other kernels and large software systems. implemented in the netbsd operating system, uvm will completely replace bsd vmin netbsd 1.4.
opening the source repository with anonymous cvs. anonymous cvs is an advanced source file distribution mechanism we created to allow open source software projects to distribute source code and information about code to internet users. built on top of the concurrent versions system (cvs) revision control system, anonymous cvs safely allows anonymous read-only access to a cvs source repository. prior to the introduction of anonymous cvs, access to a cvs repository had to be restricted to a select group of privileged software developers. the advantage of open source software is that it promotes reliability and quality by allowing independent peer review and rapid evolution of source code. by introducing anonymous cvs, we have extended the concept of open source software projects to open source repository projects. having an open source repository allows users to take a more active role in the debugging and development of open source projects. in this paper we will examine and compare the mechanisms used by open source projects to distribute source code. we will present the design and implementation of the first anonymous cvs server (used to distribute the openbsd operating system). we will explain some of our concerns (e.g., security) and some of the problems we faced when trying to adapt cvs for anonymous use. we also will present other more recent source file distribution mechanisms that make use of an open cvs repository. anonymous cvs is currently bring used by a number of projects including openbsd, freebsd, mozilla, ecgs, gnome, python, and gnustep.
profiling and tracing dynamic library usage via interposition. run-time resolution of library functions provides a rich and powerful opportunity to collect workload profiles and function/parameter trace information without source, special compilation, or special linking. this can be accomplished by having the linker resolve library functions to special wrapper functions that collect statistics before and after calling the real library function, leaving both the application and real library unaltered. the set of dynamic libraries is quite large including interesting libraries like libc (the c library and operating system interface), graphics, database, network interface, and many more. coupling this with the ability to simultaneously trace multiple processes on multiple processors covering both client and server processes yields tremendous feedback. we have found the amount of detailed information that can be gathered has been useful in many stages of the project life-cycle including the design, development, tuning, and sustaining of hardware, libraries, and applications. this paper first contrasts our extended view of interposition to other profiling, tracing, and interposing techniques. this is followed by a description and sample output of tools developed around this view; a discussion of obstacles encountered developing the tools; and finally, a discussion of anticipated and unanticipated ways those tools have been applied.
linking programs in a single address space. linking and loading are the final steps in preparing a program for execution. this paper assesses issues concerning dynamic and static linking in traditional as well as single-address-space operating systems (sasos). related loading issues are also addressed. we present the dynamic linking model implemented in the mungi sasos and discuss its strengths and limitations. benchmarking shows that dynamic linking in a sasos carries significantly less overhead than dynamic linking in sgi's irix operating system. the same performance advantages could be achieved in unix systems, if they reserved a portion of the address space for dynamically linked libraries, and ensured that each library is always mapped at the same address.
a network positioning system for the internet. network positioning has recently been demonstrated to be a viable concept to represent the network distance relationships among internet end hosts. several subsequent studies have examined the potential benefits of using network position in applications, and proposed alternative network positioning algorithms. in this paper, we study the problem of designing and building a network positioning system (nps). we identify several key system-building issues such as the consistency, adaptivity and stability of host network positions over time. we propose a hierarchical network positioning architecture that maintains consistency while enabling decentralization, a set of adaptive decentralized algorithms to compute and maintain accurate, stable network positions, and finally present a prototype system deployed on planetlab nodes that can be used by a variety of applications. we believe our system is a viable first step to provide a network positioning capability in the internet.
the region trap library: handling traps on application-defined regions of memory. user-level virtual memory (vm) primitives are used in many different application domains including distributed shared memory, persistent objects, garbage collection, and checkpointing. unfortunately, vm primitives only allow traps to be handled at the granularity of fixed-sized pages defined by the operating system and architecture. in many cases, this results in a size mismatch between pages and application-defined objects that can lead to a significant loss in performance. in this paper we describe the design and implementation of a library that provides, at the granularity of application-defined regions, the same set of services that are commonly available at a page-granularity using vm primitives. applications that employ the interface of this library, called the region trap library (rtl), can create and use multiple objects with different levels of protection (i.e., invalid, read-only, or read-write) that reside on the same virtual memory page and trap only on read/write references to objects in an invalid state or write references to objects in a read-only state. all other references to these objects proceed at hardware speeds. benchmarks of an implementation on five different os/architecture combinations are presented along with a case study using region trapping within a distributed shared memory (dsm) system, to implement a region-based version of the lazy release consistency (lrc) coherence protocol. together, the benchmark results and the dsm case study suggest that region trapping mechanisms provide a feasible region-granularity alternative for application domains that commonly rely on page-based virtual memory primitives.
the old man and the c. "you can't teach an old dog new tricks" goes the old proverb. this is a story about a pack of old dogs (c programmers) and their odyssey of trying to learn new tricks (c++ programming). c++ is a large, complex language which can easily be abused, but also includes many features to help programmers more quickly write higher quality code. the teamware group consciously decided which c++ features to use and, just as importantly, which features not to use. we also incrementally adopted those features we chose to use. this resulted in a successful c++ experience.
towards availability benchmarks: a case study of software raid systems. benchmarks have historically played a key role in guiding the progress of computer science systems research and development, but have traditionally neglected the areas of availability, maintainability, and evolutionary growth, areas that have recently become critically important in high-end system design. as a first step in addressing this deficiency, we introduce a general methodology for benchmarking the availability of computer systems. our methodology uses fault injection to provoke situations where availability may be compromised, leverages existing performance benchmarks for workload generation and data collection, and can produce results in both detail-rich graphical presentations or in distilled numerical summaries. we apply the methodology to measure the availability of the software raid systems shipped with linux, solaris 7 server, and windows 2000 server, and find that the methodology is powerful enough not only to quantify the impact of various failure conditions on the availability of these systems, but also to unearth their design philosophies with respect to transient errors and recovery policy.
undo for operators: building an undoable e-mail store. system operators play a critical role in maintaining server dependability yet lack powerful tools to help them do so. to help address this unfulfilled need, we describe operator undo, a tool that provides a forgiving operations environment by allowing operators to recover from their own mistakes, from unanticipated software problems, and from intentional or accidental data corruption. operator undo starts by intercepting and logging user interactions with a network service before they enter the system, creating a record of user intent. during an undo cycle, all system hard state is physically rewound, allowing the operator to perform arbitrary repairs; after repairs are complete, lost user data is reintegrated into the repaired system by replaying the logged user interactions while tracking and compensating for any resulting externally-visible inconsistencies. we describe the design and implementation of an application-neutral framework for operator undo, and detail the process by which we instantiated the framework in the form of an undo-capable e-mail store supporting smtp mail delivery and imap mail retrieval. our proof-of-concept e-mail implementation imposes only a small performance overhead, and can store days or weeks of recovery log on a single disk.
retrofitting quality of service into a time-sharing operating system. theoretical aspects of proportional share schedulers have received considerable attention recently. we contribute practical considerations on how to retrofit such schedulers into mainstream time-sharing systems. in particular, we propose /reserv, a uniform api for hierarchical proportional resource sharing. the central idea in /reserv is associating resource reservations with references to shared objects (and not with the objects themselves). we discuss in detail the implementation of /reserv and several proportional share schedulers on freebsd; the modified system is called eclipse/bsd. our experiments demonstrate that the proposed modifications allow selected applications to isolate their (or their clients') performance from cpu, disk, or network overloads caused by other applications. this capability is increasingly important for soft real-time, multimedia, web, and distributed client-server applications.
multihoming performance benefits: an experimental evaluation of practical enterprise strategies. multihoming is increasingly being employed by large enterprises and data centers as a mechanism to extract good performance from their provider connections. today, multihomed end-networks can employ a variety of commercial route control products to optimize performance over multiple isp links. however, little is known about the mechanisms employed by such products and their relative trade-offs. in this paper, we propose and evaluate a wide range practical schemes that could go into the design of a route control device and analyze their trade-offs. we implement the proposed schemes on a linux-based web proxy and perform a trace-based emulation of their relative performance benefits. we show that both passive and active monitoring based techniques are equally effective and could improve web performance by about 25% when compared to using a single provider. another key observation is that the conventional practice of employing historical measurement samples to monitor and predict isp performance could, in fact, result in sub-optimal performance.
signaled receiver processing. protocol processing of received packets in bsd unix is interrupt-driven and may cause scheduling anomalies that are unacceptable in systems that provide quality of service (qos) guarantees. we propose an alternative mechanism, signaled receiver processing (srp), that generates a signal to the receiving process when a packet arrives. the default action of this signal is to perform protocol processing asynchronously. however, a receiving process may catch, block, or ignore the signal and defer protocol processing until a subsequent receive call. in any case, protocol processing occurs in the context of the receiving process and is correctly charged. therefore, srp allows the system to enforce and honor qos guarantees. srp offers several advantages over lazy receiver processing (lrp), a previous solution to bsd's scheduling anomalies: srp is easily portable to systems that support neither kernel threads nor resource containers (e.g., freebsd); gives applications control over the scheduling of protocol processing; uses a demultiplexing strategy that is appropriate for both hosts and gateways; and easily enables real-time or proportional-share scheduling.
adaptive block rearrangement under unix. an adaptive unix disk device driver is described. the driver copies frequently-referenced blocks from their original locations to reserved space near the center of the disk to reduce seek times. reference frequencies need not be known in advance. instead, they are estimated by monitoring the stream of arriving requests. measurements show that the adaptive driver reduces seek times by more than half, and improves response times significantly.
an efficient kernel-based implementation of posix threads. this paper describes the kernel-based implementation of posix threads (pthreads) in the dg/uxtm operating system. the implementation achieves time efficiency by using a general-purpose trap mechanism, known as a kernel function call (kfc), that carries an order of magnitude less overhead than a traditional system call. on a 50 mhz motorola mc88110, the implementation can create and exit a thread (with the associated context switch) in 8.1 microseconds and yield to another thread in 4.0 microseconds. the implementation also achieves space efficiency by paging and decoupling bulky data structures. the advantages of a kernel-based implementation include design simplicity, less code redundancy, optimization of global (interprocess) operations, avoidance of inopportune preemption, and global semantic flexibility. the disadvantage is a monolithic design that lacks user-level flexibility.
exploiting multiple i/o streams to provide high data-rates. we present an i/o architecture, called swift, that addresses the problem of data-rate mismatches between the requirements of an application, the maximum data-rate of the storage devices, and the 6ata-rate of the interconnection medium. the goal of swift is to support integrated continuous multimedia in general purpose distributed systems. in installations with a high-speed interconnection medium, swift will provide high data-rate transfers by using multiple slower storage devices in parallel. the data-rates obtained with this approach scale well when using multiple storage devices and multiple interconnections. swift has the flexibility to use any appropriate storage technology, including disk arrays. the ability to adapt to technological advances will allow swift to provide for ever increasing i/o demands. to address the problem of partial failures, swift stores data redundantly. using the unix operating system, we have constructed a simplified prototype of the swift architecture. using a single ethernet-based local-area network and three servers, the prototype provides data-rates that are almost three times as fast as access to the local scsi disk in the case of writes. when compared to nfs, the swift prototype provides double the data-rate for reads and eight times the data-rate for writes. the data-rate of our prototype scales almost linearly in the number of servers and the number of network segments. its performance is shown to be limited by the speed of the ethernet-based local-area network. we also constructed a simulation model to show how the swift architecture can exploit storage, communication, and processor advances, and to locate the components that will limit i/o performance. in a simulated gigabit/second token ring local-area network the data-rates are seen to scale proportionally to the size of the transfer unit and to the number of storage agents.
dynamic function placement for data-intensive cluster computing. optimally partitioning application and filesystem functionality within a cluster of clients and servers is a difficult problem due to dynamic variations in application behavior, resource availability, and workload mixes. this paper presents abacus, a run-time system that monitors and dynamically changes function placement for applications that manipulate large data sets. several examples of data-intensive workloads are used to show the importance of proper function placement and its dependence on dynamic run-time characteristics, with performance differences frequently reaching 2-10x. we evaluate how well the abacus prototype adapts to run-time system behavior, including both long-term variation (e.g., filter selectivity) and short-term variation (e.g., multi-phase applications and interapplication resource contention). our experiments with abacus indicate that it is possible to adapt in all of these situations and that the adaptation converges most quickly in those cases where the performance impact is most significant.
flipc: a low latency messaging system for distributed real time environments. flipc is a new messaging system intended to support distributed real time applications on high performance communication hardware. application messaging systems designed for high performance computing environments are not well suited to other environments because they lack support for the complex application structures involving multiple processes, threads, and classes of message traffic found in environments such as distributed real time. these messaging systems also have not been optimized for medium size messages found in important classes of real time applications. flipc includes additional features to support applications outside the high performance computing domain. for medium size messages, our system significantly outperforms other messaging systems on the intel paragon. an explicit design focus on programmable communication hardware and the resulting use of wait-free synchronization was a key factor in achieving this level of performance. the implementation of flipc was accelerated by our use of pc clusters connected by ethernet or by a scsi bus as development platforms to reduce the need for paragon time.
an application-aware data storage model. we describe a new application-controlled file persistence model in which applications select the desired stability from a range of persistence guarantees. this new abstraction extends conventional abstractions by allowing applications to specify a file's volatility and methods for automatic reconstruction in case of loss. the model allows applications, particularly ones with weak persistence requirements, to leverage the memory space of other machines to improve their performance. an automated (filename-matching) interface permits legacy applications to take advantage of the variable persistence guarantees without being modified. our prototype implementation shows significant speed-ups, in some cases more than an order of magnitude over conventional network file systems such as nfs version 3.
the autofs automounter. prior to the introduction of the automounter in 1987, nfs mounts were administered separately on each workstation. the automounter has provided administrators with a tool to construct a filesystem namespace that can be shared across an organization. while the automounter is widely used, its success has been tempered by problems inherent in its implementation. this paper describes a new implementation of the automounter based on a new filesystem. this new automounter not only fixes the problems, but provides some interesting opportunities for future development.
high performance x servers in the kdrive architecture. the common usage patterns of 2d drivers for the x window system have changed over time. new extensions such as render and composite are creating new demands for 2d rendering which do not match those for previous architectures tailored to the core protocol. this paper describes changes made to the kdrive x server implementation to implement new 2d acceleration, improve management of offscreen memory, implement opengl, and implement xvideo in a manner compatible with the composite extension. with these changes, kdrive is far better suited as a desktop x server than before and may serve as an example for desktop x server implementations. simple benchmarks are presented.
cut-and-paste file-systems: integrating simulators and file-systems. we have implemented an integrated and configurable file system called the pegasus fie-systems (pfs) and a trace-driven file-system simulator called patsy. patsy is used for off-line analysis of file-system algorithms, pfs is used for on-line file-system data storage. algorithms are first analyzed in patsy and when we are satisfied with the performance results, migrated into pfs for on-line usage. since patsy and pfs are derived from a common cut-and-paste filesystem framework, this migration proceeds smoothly. we have found this integration quite useful: algorithm bottlenecks have been found through patsy that could have led to performance degradations in pfs. off-line simulators are simpler to analyze compared to on-line file-systems because a work load can repeatedly be replayed on the same off-line simulator. this is almost impossible in on-line filesystems since it is hard to provide similar conditions for each experiment run. since simulator and file-system are integrated (hence, use the same code), experiment results from the simulator have relevance in the real system. this paper describes the cut-and-paste framework, the instantiation of the framework to pfs and patsy and finally, some of the experiments we conducted in patsy.
human computation. tasks like image recognition are trivial for humans, but continue to challenge even the most sophisticated computer programs. this talk discusses a paradigm for utilizing human processing power to solve problems that computers cannot yet solve. traditional approaches to solving such problems focus on improving software. i advocate a novel approach: constructively channel human brainpower using computer games. for example, the esp game, described in this talk, is an enjoyable online game - many people play over 40 hours a week - and when people play, they help label images on the web with descriptive keywords. these keywords can be used to significantly improve the accuracy of image search. people play the game not because they want to help, but because they enjoy it.
webmin: a web-based system administration tool for unix. this paper describes the design and implementation of the unix administration tool webmin, available from http://www.webmin.com/webmin/. webmin allows moderately experienced users to manage their unix system through a web browser interface, instead of editing configuration files directly. the most recent version supports apache, squid, bind, samba and many other servers and services. it supports multiple operating systems and distributions, different languages, multiple users each with different levels of access, and ssl encryption. the first part of the paper explains why webmin was developed and the initial design goals, and compares the design to other similar tools such as linuxconf. subsequent sections cover the design and implementation of the detailed multi-user security model, the implementation of webmin itself, how support for multiple operating systems is handled and how internationalization works. finally, two webmin modules are discussed in more detail and various problems explained before the conclusion.
dynamic instrumentation of production systems. this paper presents dtrace, a new facility for dynamic instrumentation of production systems. dtrace features the ability to dynamically instrument both user-level and kernel-level software in a unified and absolutely safe fashion. when not explicitly enabled, dtrace has zero. probe effect--the system operates exactly as if dtrace were not present at all. dtrace allows for many tens of thousands of instrumentation points, with even the smallest of systems offering on the order of 30,000 such points in the kernel alone. we have developed a c-like high-level control language to describe the predicates and actions at a given point of instrumentation. the language features user-defined variables, including thread-local variables and associative arrays. to eliminate the need for most postprocessing, the facility features a scalable mechanism for aggregating data and a mechanism for speculative tracing. dtrace has been integrated into the solaris operating system and has been used to find serious systemic performance problems on production systems-problems that could not be found using pre-existing facilities.
dp: a library for building portable, reliable distributed applications. dp is a library of process management and communication tools for writing portable, reliable distributed applications. it provides support for a flexible set of message operations as well as process creation and management. it has been successfully used in developing distributed monte carlo, disjunctive programming and integer goal programming codes.it differs from pvm and similar libraries in its support for lightweight, unreliable messages, as well as asynchronous delivery of interrupt-generating messages. in addition, dp supports the development of long-running distributed applications tolerant to the failure or loss of a subset of its processors.
application-controlled file caching policies. we consider how to improve the performance of file caching by allowing user-level control over file cache replacement decisions. we use two-level cache management: the kernel allocates physical pages to individual applications (allocation), and each application is responsible for deciding how to use its physical pages (replacement). previous work on two-level memory management has focused on replacement, largely ignoring allocation. the main contribution of this paper is our solution to the allocation problem. our solution allows processes to manage their own cache blocks, while at the same time maintains the dynamic allocation of cache blocks among processes. our solution makes sure that good user-level policies can improve the file cache hit ratios of the entire system over the existing replacement approach. we evaluate our scheme by trace-based simulation, demonstrating that it leads to significant improvements in hit ratios for a variety of applications.
efficient support for p-http in cluster-based web servers. this paper studies mechanisms and policies for supporting http/1.1 persistent connections in cluster-based web servers that employ content-based request distribution. we present two mechanisms for the efficient, content-based distribution of http/1.1 requests among the back-end nodes of a cluster server. a trace-driven simulation shows that these mechanisms, combined with an extension of the locality-aware request distribution (lard) policy, are effective in yielding scalable performance for http/1.1 requests. we implemented the simpler of these two mechanisms, back-end forwarding. measurements of this mechanism in connection with extended lard on a prototype cluster, driven with traces from actual web servers, confirm the simulation results. the throughput of the prototype is up to four times better than that achieved by conventional weighted round-robin request distribution. in addition, throughput with persistent connections is up to 26% better than without.
scalable content-aware request distribution in cluster-based network servers. we present a scalable architecture for content-aware request distribution in web server clusters. in this architecture, a level-4 switch acts as the point of contact for the server on the inernet and distributes the incoming requests to a number of back-end nodes. the switch does not perform any contect-based distribution. this function is performed by each of the back-end nodes, which may forward the incoming request to another back-end based on the requested contect. in terms of scalability, this architecture compares favorably to existing approaches where a front-end node performs contect-based distribution. in our architecture, the expensive operations of tcp connection estabilishment and handoff are distributes among the back-ends, rather than being centralized in the front-end node. only a minimal additional latency penatly is paid for much improved scalability. we have implemented this new architecture, and we demonstrate its superior scalability by comparing it to a system that performs contect-aware distribution in the front-end, both under synthetic and trace-drive workloads.
u-p2p: a peer-to-peer framework for universal resource sharing and discovery. we present u-p2p, an open source framework for developing, deploying and discovering file-sharing communities. we address the problem of search in peer-to-peer file sharing by allowing the end user to add meta-data to shared documents. each file-sharing community allows the sharing of a particular structured document type. communities are themselves modeled as structured documents, thus enabling their sharing and discovery just like any other document. the creator of a particular community specifies, among other properties, the document type that it shares and the deployment model. u-p2p's extensible architecture allows developers to create new properties or extend existing ones. for example, developers can provide new deployment models or custom privacy and authentication features. u-p2p makes use of other open source projects such as jakarta tomcat and exist, an xml database system.
jemacs-the java/scheme-based emacs. jemacs is a re-implementation of the emacs programmable text editor. it is written in java, and uses the swing gui toolkit. emacs is based on the extension language emacs lisp (elisp), which is a dynamically-scoped member of the lisp family. jemacs supports elisp, as well as the use of scheme, a more modern statically-scoped lisp dialect. both languages get compiled to java bytecodes, either in advance or on-the-fly, using the kawa compilation framework.
implementation of ipv6 in 4.4 bsd. the widespread availability of the tcp/ip protocols in early versions of bsd unix fostered the currently widespread use of those protocols in commercial products. rapid depletion of the ipv4 address space has caused the internet engineering task force to design version 6 of the internet protocol (ipv6). ipv6 has some similiarities with ipv4, but it also has many differences, most notably in address size. this paper describes our experience creating a freely distributable implementation of ipv6 inside 4.4 bsd, with focus on the areas that have changed between the ipv4 and ipv6 implementations.
concert/c: a language for distributed programming. concert/c is a new language for distributed c programming that extends ansi c to support distribution and process dynamics. concert/c provides the ability to create and terminate processes, connect them together, and communicate among them. it supports transparent remote function calls (rpc) and asynchronous messages. interprocess communications interfaces are typed in concert/c, and type correctness is checked at compile time wherever possible, otherwise at runtime. all c data types, including complex data structures containing pointers and aliases, can be transmitted in rpcs. concert/c programs run on a heterogeneous set of machine architectures and operating systems and communicate over multiple rpc and messaging protocols. the current concert/c implementation runs on aix 3.2, sunos 4.1, solaris 2.2 and os/2 2.1, and communicates over sun rpc, osf/dce and udp multicast. several groups inside and outside ibm are actively using concert/c, and it is available via anonymous ftp from software.watson.ibm.com:/pub/concert.
techniques for the design of java operating systems. language-based extensible systems, such as java virtual machines and spin, use type safety to provide memory safety in a single address space. by using software to provide safety, they can support more efficient ipc. memory safety alone, however, is not sufficient to protect different applications from each other. such systems need to support a process model that enables the control and management of computational resources. in particular, language-based extensible systems should support resource control mechanisms analogous to those in standard operating systems. they need to support the separation of processes and limit their use of resources, but still support safe and efficient ipc. we demonstrate how this challenge is being addressed in several java-based systems. first, we lay out the design choices when implementing a process model in java. second, we compare the solutions that have been explored in several projects: alta, k0, and the j-kernel. alta closely models the fluke operating system; k0 is similar to a traditional monolithic kernel; and the j-kernel resembles a microkernel-based system. we compare how these systems support resource control, and explore the tradeoffs between the various designs.
c-jdbc: flexible database clustering middleware. large web or e-commerce sites are frequently hosted on clusters. successful open-source tools exist for clustering the front tiers of such sites (web servers and application servers). no comparable success has been achieved for scaling the backend databases. an expensive smp machine is required if the database tier becomes the bottleneck. the few tools that exist for clustering databases are often database-specific and/or proprietary. clustered jdbc (c-jdbc) addresses this problem. it is a freely available, open-source, flexible and efficient middleware for database clustering. c-jdbc presents a single virtual database to the application through the jdbc interface. it does not require any modification to jdbc-based applications. it furthermore works with any database engine that provides a jdbc driver, without modification to the database engine. the flexible architecture of c-jdbc supports large and complex database cluster architectures offering various performance, fault tolerance and availability tradeoffs. we present the design and the implementation of c-jdbc, as well as some uses of the system in various scenarios. finally, performance measurements using a clustered implementation of the tpc-w benchmark show the efficiency and scalability of c-jdbc.
improving application performance through swap compression. the performance of large applications tends to be poor due to the high overhead added by the swapping mechanism. the same problem may be found in highly-loaded multi-programmed systems where many of the running applications have to use the swap space in order to be able to execute at the same time. furthermore, those large applications might not be able to run on laptop or home computers as their resources are usually smaller than the ones found in an office system. in this paper, we present a solution to both problems that we have implemented in the linux kernel. the idea consists of compressing the swapped pages and keeping them in a swap cache whenever possible. we have tested this new mechanism with a set of real applications obtaining a significant performance improvement.
supporting mobility in mosquitonet. the goal of the mosquitonet project is to provide continuous internet connectivity to mobile hosts. mobile hosts must be able to take advantage of the best network connectivity available in any location, whether wired or wireless. we have implemented a mobile ip system that supports seamless switching between different networks and communication devices. in contrast to previous approaches to mobile ip, we believe mobile hosts should not assume any explicit mobility support from the networks they visit, aside from basic internet connectivity. this decision places extra responsibilities on the mobile hosts themselves. in this paper, we describe the design and implications of such a system. measurements of our implementation show that the inherent overhead to switch networks (below 10ms) is insignificant compared to the time required to bring up a new communication device.
porting the coda file system to windows. we first describe how the coda distributed filesystem was ported to windows 95 and 98. coda consists of user level cache managers and servers and kernel level code for filesystem support. severe reentrancy difficulties in the win32 environment on this platform were overcome by extending the djgpp dos c compiler package with kernel level support for sockets and more flexible memory management. with this support library and kernel modules for windows 9x filesystems in place, the coda file system client could be ported with very little patching and will likely soon run as well on windows 9x as on linux. we ported coda file servers to windows nt. for fileservers the cygwin32 kit was used. we will not report here on the port of the coda client to windows nt, which is in an early stage. in both cases cross compilation from a linux environment was most helpful to get a good development environment.
the globe distribution network. the goal of the globe project is to design and build a middleware platform that facilitates the development of large-scale distributed applications, such as those found on the internet. to demonstrate the feasibility of our design and to test our ideas, we are currently building a new internet application: the globe distribution network. the globe distribution network, or gdn, is an application for the efficient, worldwide distribution of free software and other free data. the gdn can be seen as an improvement to anonymous ftp and the world wide web due to its flexibility and extensive support for replication. this paper describes the design of the gdn. we start by explaining how the replication facilities of the globe middleware are used to make the gdn efficient, and how these facilities are implemented. next, we present the architecture of the gdn and discuss how the domain name system can be used as a first approach towards a worldwide service for naming software packages and other entities. this is followed by an analysis of the security requirements for the gdn and measures taken to satisfy these requirements. we hope to make globe and gdn itself available for free under the bsd license by 2001.
a hierarchical internet object cache. this paper discusses the design and performance of a hierarchical proxy-cache designed to make internet information systems scale better. the design was motivated by our earlier trace-driven simulation study of internet traffic. we challenge the conventional wisdom that the benefits of hierarchical file caching do not merit the costs, and believe the issue merits reconsideration in the internet environment. the cache implementation supports a highly concurrent stream of requests. we present performance measurements that show that our cache outperforms other popular internet cache implementations by an order of magnitude under concurrent load. these measurements indicate that hierarchy does not measurably increase access latency. our software can also be configured as a web-server accelerator; we present data that our httpd-accelerator is ten times faster than netscape's netsite and ncsa 1.4 servers. finally, we relate our experience fitting the cache into the increasingly complex and operational world of internet information systems, including issues related to security, transparency to cache-unaware clients, and the role of file systems in support of ubiquitous wide-area information systems.
auto-diagnosis of field problems in an appliance operating system. the use of network appliances, i.e., computer systems specialized to perform a single function, is becoming increasingly widespread. network appliances have many advantages over traditional general-purpose systems such as higher performance/cost metrics, easier configuration and lower costs of management. unfortunately, while the complexity of configuration and management of network appliances in normal usage is much lower than that of general-purpose systems, this is not always true in problem situations. the debugging of configuration and performance problems with appliance computers is a task similar to the debugging of such problems with general-purpose systems, and requires substantial expertise. this paper examines the issues of appliance-like management and performance debugging. we present a number of techniques that enable appliance-like problem diagnosis. these include continuous monitoring for abnormal conditions, diagnosis of configuration problems of network protocols via protocol augmentation, path-based problem isolation via cross-layer analysis, and automatic configuration change tracking. we also describe the use of these techniques in a problem autodiagnosis subsystem that we have built for the data ontap operating system. our experience with this system indicates a significant reduction in the cost of problem debugging and a much simpler user experience.
a scalable and explicit event delivery mechanism for unix. unix applications not wishing to block when doing i/o often use the select() system call, to wait for events on multiple file descriptors. the select() mechanism works well for small-scale applications, but scales poorly as the number of file descriptors increases. many modern applications, such as internet servers, use hundreds or thousands of file descriptors, and suffer greatly from the poor scalability of select(). previous work has shown that while the traditional implementation of select() can be improved, the poor scalability is inherent in the design. we present a new event-delivery mechanism, which allows the application to register interest in one or more sources of events, and to efficiently dequeue new events. we show that this mechanism, which requires only minor changes to applications, performs independently of the number of file descriptors.
transparent run-time defense against stack-smashing attacks. the exploitation of buffer overflow vulnerabilities in process stacks constitutes a significant portion of security attacks. we present two new methods to detect and handle such attacks. in contrast to previous work, the new methods work with any existing pre-compiled executable and can be used transparently per-process as well as on a system-wide basis. the first method intercepts all calls to library functions known to be vulnerable. a substitute version of the corresponding function implements the original functionality, but in a manner that ensures that any buffer overflows are contained within the current stack frame. the second method uses binary modification of the process memory to force verification of critical elements of stacks before use. we have implemented both methods on linux as dynamically loadable libraries and shown that both libraries detect several known attacks. the performance overhead of these libraries range from negligible to 15%.
monkey see, monkey do: a tool for tcp tracing and replaying. the performance of popular internet web services is governed by a complex combination of server behavior, network characteristics and client workload-all interacting through the actions of the underlying transport control protocol (tcp). consequently, even small changes to tcp or to the network infrastructure can have significant impact on end-to-end performance, yet at the same time it is challenging for service administrators to predict what that impact will be. in this paper we describe the implementation of a tool called monkey that is designed to help address such questions. monkey collects live tcp trace data near a server, distills key aspects of each connection (e.g., network delay, bottleneck bandwidth, server delays, etc.) and then is able to faithfully replay the client workload in a new setting. using monkey, one can easily evaluate the effects of different network implementations or protocol optimizations in a controlled fashion, without the limitations of synthetic workloads or the lack of reproducibility of live user traffic. using realistic network traces from the google search site, we show that monkey is able to replay traces with a high degree of accuracy and can be used to predict the impact of changes to the tcp stack.
creating a portable programming language using open source software. on a first glance, the field of compiler construction and programming language design may not seem to have experienced major innovations over the last decade. by now, it is almost common knowledge how a lexer works, how parsing is done, but not many have yet realized how open source software-and in particular the gnu compiler collection-have silently offered language implementors new and better ways to do their job. therefore, this paper describes the novel advantages open source software provides and, furthermore, it illustrates these with practical examples showing how the presented concepts can be put into practice. another important contribution of this paper is to give an overview over the existing limitations and the technical problems that can occur when creating an open source based programming language implementation.
limitations of the kerberos authentication system. the kerberos authentication system, a part of mit's project athena, has been adopted by other organizations. despite kerberos's many strengths, it has a number of limitations and some weaknesses. some are due to specifics of the mit environment; others represent deficiencies in the protocol design. we discuss a number of such problems, and present solutions to some of them. we also demonstrate how special-purpose cryptographic hardware may be needed in some cases.
mapping and visualizing the internet. we have been collecting and recording routing paths from a test host to each of over 90,000 registered networks on the internet since august 1998. the resulting database contains intersting routing and reachability information, and is available to the public for research purpose. the daily scans cover approximately a tenth of the networks on the internet, with a full scan run roughly once a month. we have also been collecting lucent's intranet data, and applied these tools to understanding its size and connectivity. we have also detected the sloss of power to routers in yugoslavia as the result of nato bombing. a simulated spring-force algorithm lays out the graphs thgat results from these database. this algorithm is well known, but has never been applied to such a large problem. the internet graph, with around 88,000 nodes and 100,000 edges, is larger than those previsouly considered tractable by the data visualization community. the resulting internet layouts are pleasent, though rather cluttered. on smaller networks, like lucent's intranet, the layouts present the data in a useful way. for the internet data, we have also tried plotting a minimum distance spanning tree; by throwing away edges, the remaining graph can be made more accessible. once a layout is chosen, it can be colored in various ways to show network-relevant data, such as ip address, domain information, location, isps, and result of scan (completed, filtered, loop, etc). this paper expands and updates the description of the project given in an ieee computer article [1].
managing traffic with altq. altq is a package for traffic management. altq includes a queueing framework and several advanced queueing disciplines such as cbq, red, wfq and rio. altq also supports rsvp and diffserv. altq can be configured in a variety of ways for both research and operation. however, it requires understanding of the technologies to set up things correctly. in this paper, i summarize the design trade-offs, the available technologies and their limitations, and how they can be applied to typical network settings.
tron: process-specific file protection for the unix operating system. the file protection mechanism provided in unix is insufficient for current computing environments. while the unix file protection system attempts to protect users from attacks by other users, it does not directly address the agents of destruction-executing processes. as computing environments become more interconnected and interdependent, there is increasing pressure and opportunity for users to acquire and test non-secure, and possibly malicious, software. we introduce tron, a process-level discretionary access control system for unix. tron allows users to specify capabilities for a process' access to individual files, directories, and directory trees. these capabilities are enforced by system call wrappers compiled into the operating system kernel. no privileged system calls, special files, system administrator intervention, or changes to the file system are required. existing unix programs can be run without recompilation under tron-enhanced unix. thus, tron improves unix security while maintaining current standards of flexibility and openness.
traffic data repository at the wide project. it becomes increasingly important for both network researchers and operators to know the trend of network traffic and to find anomaly in their network traffic. this paper describes an on-going effort within the wide project to collect a set of free tools to build a traffic data repository containing detailed information of our backbone traffic. traffic traces are collected by tcpdump and, after removing privacy information, the traces are made open to the public. we review the issues on user privacy, and then, the tools used to build the wide traffic repository. we will report the current status and findings in the early stage of our ipv6 deployment.
an implementation study of a detection-based adaptive block replacement scheme. in this paper, we propose a new adaptive buffer management scheme called dear (detection based adaptive replacement) that automatically detects the block reference patterns of applications and applies different replacement policies to different applications based on the detected reference pattern. the proposed dear scheme uses a periodic process. detection is made by associating block attribute values such as backward distance and frequency gathered at the (i - 1)-th invocation with forward distances of blocks referenced between the (i - 1)-th and i-th invocations. we implemented the dear scheme in freebsd 2.2.5 and measured its performance using several real applications. the results show that compared with the lru buffer management scheme, the proposed scheme reduces the number of disk i/os by up to 51% (with an average of 23%) and the response time by up to 35% (with an average of 12%) in the case of single application executions. for multiple applications, the proposed scheme reduces the number of disk i/os by up to 20% (with an average of 12%) and the over-all response time by up to 18% (with an average of 8%).
the nachos instructional operating system. in teaching operating systems at an undergraduate level, we belive that it is important to provide a project that is realistic enought to show how real operating systems work, yet is simple enough that the students can understand and modify it in significant ways. a number of these instructional saystems have been created over the last two decades, but recent advances in hardware and software design, along with the increasing power of available computational resources, have changed the basis for many of the tradeoffs made by these systems. we have implemented an instructional operating system, called nachos, and designed a series of assignments to go with it. our system includes cpu and device simulatiors, and it runs as a regulat unix process. nachos illustrates and takes advantage of modern operating systems technology, such as threads and remote procedure calls, recent harware advances, such as risc's and the prevalence of memory hierarchies, and modern software design techniques, such as protocol layering and object-oriented programming. nachos has been used to teach undergraduate operating systems classes at several universities with positive results.
secure short-cut routing for mobile ip. this paper describes the architecture and implementation of a mobile ip system. it allows mobile hosts to roam between cells implemented with 2-mbps radio base stations, while maintaining internet connectivity. the system is being developed as part of a course on wireless networks at harvard and has been operational since march 1994. the architecture scales well, both geographically and in the number of mobile hosts supported. it supports secure short-cut routing to mobile hosts using the existing internet routing system without change. the implementation demonstrates a robust, low complexity realization of the architecture, and provides trade-off opportunities between efficiency and cost. measured performance of the mobile system is generally excellent. the system can handle a high rate of location updates, and routes packets almost as efficiently for mobile hosts as the internet does for stationary hosts. we observe reasonable tcp behavior during hand-offs.
zero-copy tcp in solaris. this paper describes a new feature in solaris that uses virtual memory remapping combined with checksumming support from the networking hardware, to eliminate data-touching overhead from the tcp/ip protocol stack. by implementing page remapping operations at the right level of the operating system, and caching mmu mappings to take advantage of locality of reference, significant performance gain is attained on certain hardware platforms. nevertheless, the performance improvement over cpu copying varies, depending on the host memory cache architecture, mmu design, and application behavior. we begin by comparing different zero-copy schemes, and explain our preference for page remapping and copy-on-write (cow) techniques. we then describe our implementation, and present its performance characteristics under a number of different parameters. we conclude with ideas for future improvements.
virtual machine memory access tracing with hypervisor exclusive cache. virtual machine (vm) memory allocation and vm consolidation can benefit from the prediction of vm page miss rate at each candidate memory size. such prediction is challenging for the hypervisor (or vm monitor) due to a lack of knowledge on vm memory access pattern. this paper explores the approach that the hypervisor takes over the management for part of the vm memory and thus all accesses that miss the remaining vm memory can be transparently traced by the hypervisor. for online memory access tracing, its overhead should be small compared to the case that all allocated memory is directly managed by the vm. to save memory space, the hypervisor manages its memory portion as an exclusive cache (i.e., containing only data that is not in the remaining vm memory). to minimize i/o overhead, evicted data from a vm enters its cache directly from vm memory (as opposed to entering from the secondary storage). we guarantee the cache correctness by only caching memory pages whose current contents provably match those of corresponding storage locations. based on our design, we show that when the vm evicts pages in the lru order, the employment of the hypervisor cache does not introduce any additional i/o overhead in the system. we implemented the proposed scheme on the xen para-virtualization platform. our experiments with microbenchmarks and four real data-intensive services (specweb99, index searching, tpc-c, and tpc-h) illustrate the overhead of our hypervisor cache and the accuracy of cache-driven vm page miss rate prediction. we also present the results on adaptive vm memory allocation with performance assurance.
heuristic cleaning algorithms in log-structured file systems. research results show that while log-structured file systems (lfs) offer the potential for dramatically improved file system performance, the cleaner can seriously degrade performance, by as much as 40% in transaction processing workloads [9]. our goal is to examine trace data from live file systems and use those to derive simple heuristics that will permit the cleaner to run without interfering with normal file access. our results show that trivial heuristics perform very well, allowing 97% of all cleaning on the most heavily loaded system we studied to be done in the background.
early experience with an internet broadcast system based on overlay multicast. in this paper, we report on experience in building and deploying an operational internet broadcast system based on overlay multicast. in over a year, the system has been providing a cost-effective alternative for internet broadcast, used by over 4000 users spread across multiple continents in home, academic and commercial environments. technical conferences and special interest groups are the early adopters. our experience confirms that overlay multicast can be easily deployed and can provide reasonably good application performance. the experience has led us to identify first-order issues that are guiding our future efforts and are of importance to any overlay multicast protocol or system. our key contributions are (i) enabling a real overlay multicast application and strengthening the case for overlays as a viable architecture for enabling group communication applications on the internet, (ii) the details in engineering and operating a fully functional streaming system, addressing a wide range of real-world issues that are not typically considered in protocol design studies, and (iii) the data, analysis methodology, and experience that we are able to report given our unique standpoint.
xen and the art of repeated research. xen is an x86 virtual machine monitor produced by the university of cambridge computer laboratory and released under the gnu general public license. performance results comparing xenolinux (linux running in a xen virtual machine) to native linux as well as to other virtualization tools such as user mode linux (uml) were recently published in the paper "xen and the art of virtualization" at the symposium on operating systems principles (october 2003). in this study, we repeat this performance analysis of xen. we also extend the analysis in several ways, including comparing xenolinux on x86 to an ibm zserver. we use this study as an example of repeated research. we argue that this model of research, which is enabled by open source software, is an important step in transferring the results of computer science research into production environments.
key management in an encrypting file system. as distributed computing systems grow in size, complexity and variety of application, the problem of protecting sensitive data from unauthorized disclosure and tampering becomes increasingly important. cryptographic techniques can play an important role in protecting communication links and file data, since access to data can be limited to those who hold the proper key. in the case of file data, however, the routine use of encryption facilities often places the organizational requirements of information security in opposition to those of information management. since strong encryption implies that only the holders of the cryptographic key have access to the cleartext data, an organization may be denied the use of its own critical business records if the key used to encrypt these records becomes unavailable (e.g., through the accidental death of the key holder). this paper describes a system, based on cryptographic "smartcards," for the temporary "escrow" of file encryption keys for critical files in a cryptographic file system. unlike conventional escrow schemes, this system is bilaterally auditable, in that the holder of an escrowed key can verify that, in fact, he or she holds the key to a particular directory and the owner of the key can verify, when the escrow period is ended, that the escrow agent has neither used the key nor can use it in the future. we describe a new algorithm, based on the des cipher, for the on-line encryption of file data in a secure and efficient manner that is suitable for use in a smartcard.
probing tcp implementations. in this paper, we demonstrate a technique called active probing used to study tcp implementations. active probing treats a tcp implementation as a black box, and uses a set of procedures to probe the black box. by studying the way tcp responds to the probes, one can deduce several characteristics of the implementation. the technique is particularly useful if tcp source code is unavailable. to demonstrate the technique, the paper shows example probe procedures that examine three aspects of tcp. the results are informative: they reveal implementation flaws, protocol violations, and the details of design decisions in five vendor-supported tcp implementations. the results of our experiment suggest that active probing can be used to test tcp implementations.
the slab allocator: an object-caching kernel memory allocator. this paper presents a comprehensive design overview of the sunos 5.4 kernel memory allocator. this allocator is based on a set of object-caching primitives that reduce the cost of allocating complex objects by retaining their state between uses. these same primitives prove equally effective for managing stateless memory (e.g. data pages and temporary buffers) because they are space-efficient and fast. the allocator's object caches respond dynamically to global memory pressure, and employ an object-coloring scheme that improves the system's overall cache utilization and bus balance. the allocator also has several statistical and debugging features that can detect a wide range of problems throughout the system.
oodce: a c++ framework for the osf distributed computing environment. this paper presents a method for developing object-oriented distributed applications using the c++ and dce technologies. the core of this package is a dce idl-to-c++ compiler and a set of c++ classes providing easy access to dce functionality. using this approach we were able to develop more object-oriented distributed applications, and saw a significant decrease in application code size. this contributed to an increase in developer productivity and code maintainability.
why use a fishing line when you have a net? an adaptive multicast data distribution protocol. the design and implementation of a system to provide reliable and efficient distribution of large quantities of data to many hosts on a local area network or internetwork is described. by exploiting the one-to-many transmission capabilities of multicast and broadcast, it is possible to transmit data to multiple hosts simultaneously, using less bandwidth and thus obtaining greater efficiency than repeated unicasting. although performance measurements indicate the superiority of multicast, we dynamically select from available transmission modes so as to maximize efficiency and throughput while providing reliable delivery of data to all hosts. our results demonstrate that file-distribution programs based on our protocol can benefit from a substantial speed-up over tcp-based programs such as rdist. for example, our system has been used to distribute a 133 kbyte password file to 68 hosts in 20 seconds, whereas the equivalent rdist took 251 seconds.
a multi-user virtual machine. recent efforts aimed at improving the scalability of the javatm platform have focused primarily on the safe collocation of multiple applications in the virtual machine. this is often beneficial for various performance metrics, but ultimately leads to a single-user multitasking environment. the lack of multi-user capabilities forms a barrier to the scalability of multitasking virtual machines, as it requires one per user. in this paper we demonstrate how to enhance a multitasking virtual machine with multi-user support. in particular, users can securely manipulate their private files, load their own native libraries without endangering other computations, and use all standard apis. auxiliary processes are needed to provide multiple operating system resource and user contexts, but no modifications are needed to the operating system itself.
evaluation of design alternatives for a cluster file system. based on implementation experience and measurements, this paper presents an evaluation of design alternatives to a cluster file system. the file system is targeted for ibm cluster systems, scalable powerparallel and aix hacmp/600. we considered a shared disk approach where serialized, multiple instances of a single-system file system directly access file data as disk blocks, and a shared file system approach which is the conventional method of distributing file system function between a client and a server. we conclude that the shared disk approach suffers form the difficulties of metadata serialization, pooor write-sharing performance, and read throughput.
tracking and viewing changes on the web. we describe a set of tools that detect when world-wide-web pages have been modified and present the modifications visually to the user through marked-up html. the tools consist of three components: w3newer, which detects changes to pages; snapshot, which permits a user to store a copy of an arbitrary web page and to compare any subsequent version of a page with the saved version; and htmldiff, which marks up html text to indicate how it has changed from a previous version. we refer to the tools collectively as the att internet difference engine (aide). this paper discusses several aspects of aide, with an emphasis on systems issues such as scalability, security, and error conditions.
adaptive modem connection lifetimes. internet service providers sometimes go to great lengths to minimize dial-up connection times, in order to make the best use of limited resources. typically they disconnect users after a fixed period of complete inactivity, such as 10-15 minutes. we propose adaptive time-out policies that take past history into account, and we evaluate some of these policies using a trace from a production environment. we find that adaptive policies can reduce cumulative connection times and average simultaneous usage by about 10-20% compared to a conservative fixed threshold, in exchange for a moderate increase in the number of disconnections that inconvenience the user.
thwarting the power-hungry disk. minimizing power consumption is important for mobile computers, and disks consume a significant portion of system-wide power. there is a large difference in power consumption between a disk that is spinning and one that is not, so systems try to keep the disk spinning only when it must. the system must trade off between the power that can be saved by spinning the disk down quickly after each access and the impact on response time from spinning it up again too often. we use trace-driven simulation to examine these trade-offs, and compare a number of different algorithms for controlling disk spin-down. we simulate disk accesses from a mobile computer (a macintosh powerbook duo 230) and also from a desktop workstation (a hewlett-packard 9000/845 personal workstation running hp-ux), running on two disks used on mobile computers, the hewlett-packard kittyhawk c3014a and the quantum go•drive 120. we show that the "perfect" off-line algorithm--one that consumes minimum power without increasing response time relative to a disk that never spins down--can reduce disk power consumption by 35--50%, compared to the fixed threshold suggested by manufacturers. an on-line algorithm with a threshold of 10 seconds, running on the powerbook trace and go•drive disk, reduces energy consumption by about 40% compared to the 5-minute threshold recommended by manufacturers of comparable disks; however, over a 4-hour trace period it results in 140 additional delays due to disk spin-ups.
optimistic lookup of whole nfs paths in a single operation. vfs lookup code examines and translates path names one component at a time, checking for special cases such as mount points and symlinks. vfs calls the nfs lookup operation as necessary. nfs employs caching to reduce the number of lookup operations that go to the server. however, when part or all of a path is not cached, nfs lookup operations go back to the server. although nfs's caching is effective, component-by-component translation of an uncached path is inefficient, enough so that lookup is typically the operation most commonly processed by servers. we study the effect of augmenting the vfs lookup algorithm and the nfs protocol so that a client can ask a server to translate an entire path in a single operation. the preconditions for a successful request are usually but not always satisfied, so the algorithm is optimistic. this small change can deliver substantial improvements in client latency and server load.
extending internet services via ldap. this project report examines the use of an ldap (lightweight directory access protocol) v2 server to provide an easily accessible data storage facility. the main purpose of the ldap database is to store related information based on a common thread such as a person's name, an organization's name, or the description of a service offered, in a simple yet hierarchical structure. the use of ldap enables new fields to be added to existing user information to 1) enable end-users to store pertinent user information to be used by a mainframe-to-pc intermediary file server using samba, 2) enable new groupings of electronic mail distributions to be created with little or no change to sendmail, and 3) enhance the granularity of internetworknews (usenet) article submission acceptance capabilities. some additional benefits of these facilities included using a single, non-proprietary database which required very little new coding to make use of. the data used for the various facilities were easily associated with database objects defined for enterprise personnel. the administration load for each service was reduced since service related data, such as userids or mailboxes, were not maintained directly as a part of the specific service. the internet directory service, as provided by the ldap server, is accessible by several methods, rather than just one specialized or proprietary interface.
fault interpretation: fine-grain monitoring of page accesses. this paper presents a technique for obtaining fine-grain information about page accesses from standard virtual memory hardware and unix operating system software. this can be used to monitor all user-mode accesses to specified regions of the address space of a process. application code can intervene before and/or after an access occurs, permitting a wide variety of semantics to be associated with memory pages. the technique facilitates implementing complex replication or consistency protocols on transparent distributed shared memory and persistent memory. the technique can also improve the efficiency of certain generational and incremental garbage collection algorithms. this paper presents our implementation and suggest several others. efficiency measurements show faults to be about three orders of magnitude more expensive than normal memory accesses, but two orders of magnitude less expensive than page faults. information about how to obtain the code via anonymous ftp appears at the end of the paper.
nfs tricks and benchmarking traps. we describe two modifications to the freebsd 4.6 nfs server to increase read throughput by improving the read-ahead heuristic to deal with reordered requests and stride access patterns. we show that for some stride access patterns, our new heuristics improve end-to-end nfs throughput by nearly a factor of two. we also show that benchmarking and experimenting with changes to an nfs server can be a subtle and challenging task, and that it is often difficult to distinguish the impact of a new algorithm or heuristic from the quirks of the underlying software and hardware with which they interact. we discuss these quirks and their potential effects.
lazy asynchronous i/o for event-driven servers. we introduce lazy asynchronous i/o (laio), a new asynchronous i/o interface that is well suited to event-driven programming. laio is general in the sense that it applies to all blocking i/o operations. furthermore, it is lazy in the sense that it creates a continuation only when an operation actually blocks, and it notifies the application only when a blocked operation completes in its entirety. these features make programming high-performance, event-driven servers using laio considerably easier than with previous interfaces. we describe a user-level implementation of laio, relying only on kernel support for scheduler activations, a facility present in many unix-like systems. we compare the performance of web servers implemented using laio to the performance obtained with previous interfaces. for workloads with an appreciable amount of disk i/o, laio performs substantially better than the alternatives, because it avoids blocking entirely. in one such case, the peak throughput with laio is 24% higher than the next best alternative. for in-memory workloads it performs comparably.
portable multithreading-the signal stack trick for user-space thread creation. this paper describes a pragmatic but portable fallback approach for creating and dispatching between the machine contexts of multiple threads of execution on unix systems that lack a dedicated user-space context switching facility. such a fallback approach for implementing machine contexts is a vital part of a user-space multithreading environment, if it has to achieve maximum portability across a wide range of unix flavors. the approach is entirely based on standard unix system facilities and ansi-c language features and especially does not require any assembly code or platform specific tricks at all. the most interesting issue is the technique of creating the machine context for threads, which this paper explains in detail. the described approach closely follows the algorithm as implemented by the author for the popular user-space multithreading library gnu portable threads (gnu pth, [25]) which this way quickly gained the status of one of the most portable user-space multithreading libraries.
atom: a flexible interface for building high performance program analysis tools. code instrumentation is a powerful mechanism for understanding program behavior. unfortunately, code instrumentation is extremely difficult, and therefore has been mostly relegated to building special purpose tools for use on standard industry benchmark suites. atom (analysis tools with om) provides a very flexible and efficient code instrumentation interface that allows powerful, high performance program analysis tools to be built with very little effort. this paper illustrates this flexibility by building five complete tools that span the interests of application programmers, computer architects, and compiler writers. this flexibility does not come at the expense of performance. because atom uses procedure calls as the interface between the application and the analysis routines, the performance of each tool is similar to or greatly exceeds the best known hand-crafted implementations.
design and implementation of a transaction-based filesystem on freebsd. transactional database management systems (dbms's) have special data integrity requirements that standard filesystems such as the berkeley fast filesystem do not address. this paper briefly describes the requirements a transactional dbms makes of a transaction-based filesystem, then goes on to describe the design and implementation of such a filesystem, referred to as a block repository, which is part of the sqrl dbms project. the implementation of sqrl's block repository is different than most traditional filesystems in that it is purposely implemented in user-land using raw devices and threads. its performance is more tunable to the needs of transaction processing than would be the case if it were integrated into the kernel.
new tricks for an old terminal driver. users expect more out of command lines than they did fifteen years ago, but the terminal interface has not evolved to keep up with their expectations. with a few modifications, though, the terminal driver can provide every program with support for the arrow keys and several common emacs commands.
distributed computing: moving from cgi to corba. in this paper, we document the evolution of a banner and delivery system from a simple cgi script written in perl running on a single host into a distributed computing application using corba. while corba has an established history in the enterprise-computing world, it is only recently that the open-source ® community has begun to embrace it. starting without any rpc programming experience, it took targetnet a little less than half a year to integrate corba into the apache web server and convert all their cgi programs into corba servers. performance of the system increased from 50 transactions per second to over 400 per second. thanks to the cross-platform capabilities of corba, future components can be developed on virtually any operating system and programming language. by adding inexpensive servers, the capacity of the system scales in a near-linear fashion. most importantly, the switch to corba didn't require a change of operating system or development environment - everything runs on a free operating system using opensource components.
an extensible protocol architecture for application-specific networking. plexus is a networking architecture that allows applications to achieve high performance with customized protocols. application-specific protocols are written in a typesafe language and installed dynamically into the operating system kernel. because these protocols execute within the kernel, they can access the network interface and other operating system services with low overhead. protocols implemented with plexus outperform equivalent protocols implemented on conventional monolithic systems. plexus runs in the context of the spin extensible operating system.
evolving mach 3.0 to a migrating thread model. we have modified mach 3.0 to treat cross-domain remote procedure call (rpc) as a single entity, instead of a sequence of message passing operations. with rpc thus elevated, we improved the transfer of control during rpc by changing the thread model. like most operating systems, mach views threads as statically associated with a single task, with two threads involved in an rpc. an alternate model is that of migrating threads, in which, during rpc, a single thread abstraction moves between tasks with the logical flow of control, and "server" code is passively executed. we have compatibly replaced mach's static threads with migrating threads, in an attempt to isolate this aspect of operating system design and implementation. the key element of our design is a decoupling of the thread abstraction into the execution context and the schedulable thread of control, consisting of a chain of contexts. a key element of our implementation is that threads are now "based" in the kernel, and temporarily make excursions into tasks via upcalls. the new system provides more precisely defined semantics for thread manipulation and additional control operations, allows scheduling and accounting attributes to follow threads, simplifies kernel code, and improves rpc performance. we have retained the old thread and ipc interfaces for backwards compatibility, with no changes required to existing client programs and only a minimal change to servers, as demonstrated by a functional unix single server and clients. the logical complexity along the critical rpc path has been reduced by a factor of nine. local rpc, doing normal marshaling, has sped up by factors of 1.7-3.4. we conclude that a migrating-thread model is superior to a static model, that kernel-visible rpc is a prerequisite for this improvement, and that it is feasible to improve existing operating systems in this manner.
the shell as a service. this paper explores the design history of the nmake shell coprocess. originally a special purpose uniprocessor executor, the coshell has evolved into a general purpose service that automatically executes shell actions on lightly loaded hosts in a local network. a major thrust of this work has been ease of use. the only privilege required for installation, administration or use is rsh access to the local hosts. nmake and gnu-make users can take advantage of network execution with no makefile modifications. shell level access is similar to but more efficient than rsh and allows host expression matching to replace the explicit host name argument. also provided is a c programming library interface with five primitive operations that follow the fork-exec-wait process model. beside the speedups attained by parallelizing computations in a homogeneous network, coshell also supports heterogeneous configurations. this presents novel solutions to traditional cross-compilation problems. it also allows the user to view a new network host as a compute engine rather than yet another architecture on which to port the home environment and tools. coshell runs on most s5r4 and bsd unix* operating system variants.
migrating an mvs mainframe application to a pc. due to advances in computer architecture, performance of the pc now exceeds that of the typical mainframe. however, computing cost on a mainframe continues to greatly exceed that on a pc. thus, migrating mainframe applications to pc can result in substantial savings. the major stumbling block in doing this is the cost of software migration itself. this paper discusses an experiment in using a software tool approach to migrate a large billing application from mvs running on a mainframe to unix running on a pc. we developed tools to port the application from mainframe to pc with minimal code rewriting and enable transferring data cheaply so that processing can be done without interrupting other ongoing mainframe operations. we were able to transfer data from the mvs mainframe to a linux pc and complete its processing in less total time than if done entirely on the original mainframe.
extended data formatting using sfio. the ansi-c standard defines stdio as the i/o library for c programs. despite its ubiquitous use, stdio has well-documented deficiencies in various areas including data formatting. the sfio library provides an alternative to stdio with improved functionality, robustness and performance. in particular, sfio extends the data formatting functions so that applications can deal with arbitrary scalar objects, avoid unsafe operations and even define their own conversion patterns. this paper discusses these formatting enhancements
the pebble component-based operating system. pebble is a new operating system designed with the goals of flexibility, safety, and performance. its architecture combines a set of features heretofore not found in a single system, including (a) a minimal privileged mode nucleus, responsible for switching between protection domains, (b) implementation of all system services by replaceable user-level components with minimal privileges (including the scheduler and all device drivers) that run in separate protection domains enforced by hardware memory protection, and (c) generation of code specialized for each possible cross-domain transfer. the combination of these techniques results in a system with extremely inexpensive cross-domain calls that makes it well-suited for both efficiently specializing the operating system on a per-application basis and supporting modern component-based applications.
trapeze/ip: tcp/ip at near-gigabit speeds. this paper presents experiences with high-speed tcp/ip networking on a gigabit-per-second myrinet network, using a myrinet messaging system called trapeze. we explore the effects of common optimizations above and below the tcp/ip protocol stack, including zero-copy sockets, large packets with scatter/gather i/o, checksum offloading, message pipelining, and interrupt suppression. our experiments use extended freebsd 4.0 kernels on a range of intel and compaq alpha platforms. these experiments give a snapshot of the freebsd tcp/ip implementation running at bandwidths as high as 956 mb/s. we also report some results using gigabit ethernet products from alteon networks, which yielded a tcp bandwidth of 988 mb/s using zero-copy sockets on a 500 mhz compaq alpha 21264 workstation.
embedded inodes and explicit grouping: exploiting disk bandwidth for small files. small file performance in most file systems is limited by slowly improving disk access times, even though current file systems improve on-disk locality by allocating related data objects in the same general region. the key insight for why current file systems perform poorly is that locality is insufficient -- exploiting disk bandwidth for small data objects requires that they be placed adjacently. we describe c-ffs (co-locating fast file system), which introduces two techniques, embedded inodes and explicit grouping, for exploiting what disks do well (bulk data movement) to avoid what they do poorly (reposition to new locations). with embedded inodes, the inodes for most files are stored in the directory with the corresponding name, removing a physical level of indirection without sacrificing the logical level of indirection. with explicit grouping, the data blocks of multiple small files named by a given directory are allocated adjacently and moved to and from the disk as a unit in most cases. measurements of our c-ffs implementation show that embedded inodes and explicit grouping have the potential to increase small file throughput (for both reads and writes) by a factor of 5-7 compared to the same file system without these techniques. the improvement comes directly from reducing the number of disk accesses required by an order of magnitude. preliminary experience with software-development applications shows performance improvements ranging from 10-300 percent.
emstar: a software environment for developing and deploying wireless sensor networks. many wireless sensor network (wsn) applications are composed of a mixture of deployed devices with varying capabilities, from extremely constrained 8-bit "motes" to less resource-constrained 32-bit "microservers". emstar is a software environment for developing and deploying complex wsn applications on networks of 32-bit embedded microserver platforms, and integrating with networks of motes. emstar consists of libraries that implement message-passing ipc primitives, tools that support simulation, emulation, and visualization of live systems, both real and simulated, and services that support networking, sensing, and time synchronization. while emstar's design has favored ease of use and modularity over efficiency, the resulting increase in overhead has not been an impediment to any of our current projects.
linux device driver emulation in mach. we describe the design and performance of code added to the mach microkernel (mach 4.0, version uk02p21) that permits one to build a mach kernel that includes unmodified linux device drivers. we have written emulation code to support all linux 1.3.35 network and scsi drivers for the isa and pci i/o buses. emulation increases latency, but very little. the degree depends on both device and operation, and varies from 2 microseconds for receiving small (60 byte) network packets up to 197 microseconds for writing 16kb to an isa scsi device.
multi-resident afs: an adventure in mass storage. the pittsburgh supercomputing center has been working to integrate distributed file system technology with hierarchical mass storage. we produced a system utilizing the andrew file system that can be interfaced to many mass storage systems. we retained the semantics of afs and compatibility with standard clients and servers. the architecture has a logical separation between the facility that provides the user interface and access semantics and the management of the storage systems that contain user data. support for file level replication is provided for high availability to data in a fashion that is transparent to users. this system is called multi-resident afs.
idleness is not sloth. many people have observed that computer systems spend much of their time idle, and various schemes have been proposed to use this idle time productively. the commonest approach is to off-load activity from busy periods to less-busy ones in order to improve system responsiveness. in addition, speculative work can be performed in idle periods in the hopes that it will be needed later at times of higher utilization, or non-renewable resource like battery power can be conserved by disabling unused resources. we found opportunities to exploit idle time in our work on storage systems, and after a few attempts to tackle specific instances of it in ad hoc ways, began to investigate general mechanisms that could be applied to this problem. our results include a taxonomy of idle-time detection algorithms, metrics for evaluating them, and an evaluation of a number of idleness predictors that we generated from our taxonomy.
the refdbms distributed bibliographic database system. refdbms is a database system for sharing bibliographic references among many users at sites on a wide-area network such as the internet. this paper describes our experiences in building and using refdbms for the last two years. it summarizes the collection of facilities that refdbms provides, and gives detailed information on how well refdbms functions as a collaborative, wide-area, distributed information system.
a 3-tier raid storage system with raid1, raid5, and compressed raid5 for linux. this paper presents the design and implementation of a host-based driver (a "volume manager") for a 3-tier raid storage system, currently with 3 tiers: a small raid1 tier and larger raid5 and compressed raid5 (craid5) tiers. based on access patterns ("temperature"), the driver automatically migrates frequently accessed data to raid1 while demoting not so frequently accessed data to raid5/craid5. the prototype system, called "temperature sensitive storage" (tss), provides reliable persistence semantics for data migration between the tiers using ordered updates or logging. mechanisms are separated from policies through an api so that any desired policy can be implemented in trusted user processes. we also discuss the problems faced while moving from the original implementation on the solaris platform to linux. finally, we present comparison of the performance of our design with comparable systems using striping or raid5.
adaptable binary programs. to accurately and comprehensively monitor a program's behavior, many performance measurement tools transform the program's executable representation or binary. by instrumenting binary programs to monitor program events, tools can precisely analyze compiler optimization effectiveness, memory system performance, pipeline interlocking, and other dynamic program characteristics that are fully exposed only at this level. binary transformation has also been used to support software-enforced fault isolation, debugging, machine re-targeting, and machine-dependent optimization. at present, binary transformation applications face a difficult trade-off. previous approaches to implementing robust transformations result in significant disk space and run-time overhead. to improve efficiency, some current systems sacrifice robustness, relying on heuristic assumptions about the program and recognition of compiler-dependent code generation idioms. in this paper we begin by investigating the run-time and disk space overhead of transformation strategies that do not require assumptions about the program's control flow or register usage. we then detail simple information about the binary program that can significantly reduce this overhead. for each type of information, we show how it enables a corresponding type of binary transformation. we call binary programs that contain such enabling information adaptable binaries. because adaptable binary information is simple, any compiler can generate it. despite its simplicity, adaptable binary information has the necessary and sufficient expressive power to support a rich set of binary transformations.
the multispace: an evolutionary platform for infrastructural services. this paper presents the architecture for a base, a clustered environment for building and executing highly available, scalable, but flexible and adaptable infrastructure services. our architecture has three organizing principles: addressing all of the difficult service fault-tolerance, availability, and consistency problems in a carefully controlled environment, building that environment out of a collection of execution environments that are receptive to mobile code, and using dynamically generated code to introduce run-time-generated levels of indirection separating clients from services. we present a prototype java implementation of a base called the multispace, and talk about two applications written on this prototype: the ninja jukebox (a cluster based music warehouse), and keiretsu (an instant messaging service that supports heterogeneous clients). we show that the multispace implementation successfully reduces the complexity of implementing services, and that the platform is conducive to rapid service evolution.
reducing file system latency using a predictive approach. despite impressive advances in file system through put resulting from technologies such as high-bandwidth networks and disk arrays, file system latency has not improved and in many cases has become worse. consequently, file system i/o remains one of the major bottlenecks to operating system performance [10]. this paper investigates an automated predictive approach towards reducing file latency. automatic prefetching uses past file accesses to predict future file systemrequests. the objective is to provide data in advance of the request for the data, effectively masking access latencies. we have designed and implement a system to measure the performance benefits of automatic prefetching. our current results, obtained from a trace-driven simulation, show that prefetching results in as much as a 280% improvement over lru especially for smaller caches. alternatively, prefetching can reduce cache size by up to 50%.
newscache - a high-performance cache implementation for usenet news. usenet news is reaching its limits as current traffic strains the available infrastructure. news data volume increases steadily and competition with other internet services has intensified. consequently bandwidth requirements are often beyond that provided by typical links and the processing power needed exceeds a single system's capabilities. a rapidly growing number of users, especially attracted by www, overloads communication links and makes bandwidth a scarce resource. while an elaborate caching infrastructure was adopted for the www, usenet news still uses most of its originally defined infrastructure. caching techniques have not yet been adopted on a large scale. we believe that this is due to the lack of efficient cache implementations. in this paper we present a high performance cache server for usenet news that helps to conserve network bandwidth, computing power, and disk storage and is compatible with the current infrastructure and standards. after a thorough comparison of existing news database formats and replacement strategies we designed and implemented newscache to remedy usenet news bottlenecks. we present an empirical comparison of different cache replacement strategies as well as an evaluation of the use of newscache as a news server.
cse - a c++ servlet environment for high-performance web applications. current environments for web application development focus on java or scripting languages. developers that want to or have to use c or c++ are left behind with little options. we have developed a c/c++ servlet environment (cse) that provides a high performance servlet engine for c and c++. one of the biggest challenges we have faced while developing this environment was to come up with an architecture that provides high performance while not allowing a single servlet to crash the whole servlet environment, a serious risk with c and c++ application development. in this paper we explain our architecture, the challenges and trade-offs we have faced, and compare the performance of our environment to that of top servlet environments available today.
world wide web cache consistency. the bandwidth demands of the world wide web continue to grow at a hyper-exponential rate. given this rocketing growth, caching of web objects as a means to reduce network bandwidth consumption is likely to be a necessity in the very near future. unfortunately, many web caches do not satisfactorily maintain cache consistency. this paper presents a survey of contemporary cache consistency mechanisms in use on the internet today and examines recent research in web cache consistency. using trace-driven simulation, we show that a weak cache consistency protocol (the one used in the alex ftp cache) reduces network bandwidth consumption and server load more than either time-to-live fields or an invalidation protocol and can be tuned to return stale data less than 5% of the time.
a new object-oriented programming language: sh. many have frittered away their time on c++, while overlooking the new, posix.2-required, object-oriented language: sh. as will be clear from the enclosed code, the name may allude to the fact that the author would be embarrassed to have anyone find out about it. this paper introduces a tiny, object-oriented programming system written entirely in posix-conforming shell scripts.
workstation support for real-time multimedia communication. we show how multimedia applications with real-time requirements can be supported in a distributed system. a unix system has been modified to give soft real-time support. the modifications include deadline-based scheduling, preemption points and prioritized interrupt processing. in addition, a system call interface for real-time application programming has been designed. we justify the modifications by experiments with a simple distributed multimedia delivery system. the experiments are made on an atm network, where resources are reserved by means of the st-2 internetworking protocol.
call path profiling of monotonic program resources in unix. practical performance improvement of a complex program must be guided by empirical measurements of its resource usage. essentially, the programmer wants to know where in the source code the program is inefficient and why this is so. the process interface of unix system v (proc(4)) provides access to the raw data (e.g. time, faults, traps, and system calls) necessary to answering the why question, but gives no guidance in answering the where question. this paper describes a novel approach to the latter, call path profiling, which is both more informative and more closely tied to the process of program optimization than either trace-based or prof/gprof-like approaches. in addition, by viewing consumption of a resource as the ticking of a clock, we generalize the interval-based sampling approach of time profilers to arbitrary monotonic resources. the approach is embodied in several prototypes, including cpprof which operates under system v.
implementing internet key exchange (ike). a key component of the ip security architecture is the internet key exchange protocol. ike is invoked to establish session keys (and associated cryptographic and networking configuration) between two hosts across the network. ike needs to authenticate and authorize the parties involved in an exchange, negotiate parameters to be used for the communication, and interact with the local ipsec stack. the number of tasks, along with the flexibility built into the protocol, as well as the need to allow future additions and modifications to the protocol, need to be taken into consideration when designing and implementing ike. another complicating factor is the need for security policy management. although ike can establish security associations with remote hosts, some method for determining what kinds of traffic can and should be exchanged with a remote host is necessary. as there is no standard specification yet, we are using a trust-management based approach using the keynote system as a basis for specifying policy. this paper discusses the design, architecture, and implementation details of the openbsd ike daemon, with separate mention of the security policy mechanism.
modular construction of dte policies. this paper describes a tool which composes a policy for a fine-grained mandatory access control system (dte) from a set of mostly independent policy modules. for a large system with many services, a dte policy becomes unwieldy. however, many system services and security extensions can be considered to be largely standalone. by providing for explicit grouping, namespaces, and globbing by namespaces, inter-module access rules can be made generic enough to permit modules to be mixed and matched as needed. as a result, it becomes easier to extend a policy, debug a policy, and to distribute meaningful policy modules with new software.
the spring nucleus: a microkemel for objects. copyright 1993 usenix. reprinted with permission. the spring system is a distributed operating system that supports a distributed, object-oriented application framework. each individual spring system is based around a microkernel known as the nucleus, which is structured to support fast cross-address-space object invocations. this paper discusses the design rationale for the nucleus's ipc facilities and how they fit into the overall spring programming model. we then describe how the internal structure of the nucleus is organized to support fast cross-address-space calls, including some specific details and performance information on the current implementation.
location-aware scheduling with minimal infrastructure. mobile computers often benefit from software which adapts to their location. for example, a computer might be backed up when at the office, or the default printer might always be a nearby one. in many existing systems, location-triggered actions are only possible for specific applications or with special infrastructure. this paper describes lcron, a system which supports user-configurable actions triggered on change in location or other events common to mobile computers. key features of lcron are its use of existing clues for location information and mapping low-level location information into user-sensible terms. lcron uses a number of existing sources of location such as network connection and base station id, allowing it to work without special hardware or gps receivers. we map sources of low-level information such as ip address and latitude/longitude into user-meaningful logical locations. we describe the design, implementation and our experiences with this system.
calliope: a distributed, scalable multimedia server. calliope is a distributed multimedia server constructed from personal computers. preliminary performance measurements indicate that calliope can be scaled from a single pc producing about 22 mpeg-1 video streams to hundreds of pcs producing thousands of streams. the system can store both variable-and constant-rate video and audio encodings and can deliver them over any network supported by the underlying operating system. calliope is cost-effective because it requires only commodity hardware and portable because it runs under unix.
file system design for an nfs file server appliance. network appliance corporation recently began shipping a new kind of network server called an nfs file server appliance, which is a dedicated server whose sole function is to provide nfs file service. the file system requirements for an nfs appliance are different from those for a general-purpose unix system, both because an nfs appliance must be optimized for network file access and because an appliance must be easy to use. this paper describes wafl (write anywhere file layout), which is a file system designed specifically to work in an nfs appliance. the primary focus is on the algorithms and data structures that wafl uses to implement snapshotst, which are read-only clones of the active file system. wafl uses a copy-on-write technique to minimize the disk space that snapshots consume. this paper also describes how wafl uses snapshots to eliminate the need for file system consistency checking after an unclean shutdown.
optimizing the performance of dynamically-linked programs. dynamically-linked programs in general do not perform as well as statically-linked programs. this paper identifies three main areas that account for the performance loss. first, symbols are referenced indirectly and thus extra instructions are required. second, the overhead in run-time symbol resolution is significant. third, poor locality of functions in shared libraries and data structures maintained by the run-time linker may result in poor memory utilization. this paper presents new optimization techniques we developed that address these three areas and significantly improve the performance of dynamically-linked programs. also, we provide measurements of the performance improvement achieved. most importantly, we show that all desirable features of shared libraries can be achieved without sacrificing performance.
computer system performance problem detection using time series model. computer systems require monitoring to detect performance anomalies such as runaway processes, but problem detection and diagnosis is a complex task requiring skilled attention. although human attention was never ideal for this task, as networks of computers grow larger and their interactions more complex, it falls far short. existing computer-aided management systems require the administrator manually to specify fixed "trouble" thresholds. in this paper we report on an expert system that automatically sets thresholds, and detects and diagnoses performance problems on a network of unix computers. key to the success and scalability of this system are the time series models we developed to model the variations in workload on each host. analysis of the load average records of 50 machines yielded models which show, for workstations with simulated problem injection, false positive and negative rates of less than 1%. the server machines most difficult to model still gave average false positive/negative rates of only 6%/32%. observed values exceeding the expected range for a particular host cause the expert system to focus on that machine. there it applies tools with finer resolution and more discrimination, including per-command profiles gleaned from process accounting records. it makes one of 18 specific diagnoses and notifies the administrator, and optionally the user [a].
design and implementation of power-aware virtual memory. despite constant improvements in fabrication technology, hardware components are consuming more power than ever. with the ever-increasing demand for higher performance in highly-integrated systems, and as battery technology falls further behind, managing energy is becoming critically important to various embedded and mobile systems. in this paper, we propose and implement power-aware virtual memory to reduce the energy consumed by the memory in response to workloads becoming increasingly data-centric. we can use the power management features in current memory technology to put individual memory devices into low power modes dynamically under software control to reduce the power dissipation. however, it is imperative that any techniques employed weigh memory energy savings against any potential energy increases in other system components due to performance degradation of the memory. using a novel power-aware virtual memory implementation, we estimate a significant reduction in memory power dissipation, from 4.1 w to 0.5-2.7 w, based on rambus memory specifications, while running various real-world applications in a working linux system. unfortunately, due to a hardware bug in the chipset, direct power measurement is currently not possible. applying more advanced techniques, we can reduce power dissipation further to 0.2-1.7 w, depending on the actual workload, with negligible effects on performance. we also show this work is applicable to other memory architectures, and is orthogonal to previously-proposed hardware-controlled power-management techniques, so it can be applied simultaneously to further enhance energy conservation in a variety of platforms.
gecko: tracking a very large billing system. there is a growing need for very large databases which are not practical to implement with conventional relational database technology. these databases are characterised by huge size and frequent large updates; they do not require traditional database transactions, instead the atomicity of bulk updates can be guaranteed outside of the database. given the i/o and cpu resources available on modern computer systems, it is possible to build these huge databases using simple flat files and simply scanning all the data when doing queries. this paper describes gecko, a system for tracking the state of every call in a very large billing system, which uses sorted flat files to implement a database of about 60g records occupying 2.6tb. this paper describes gecko's architecture, both data and process, and how we handle interfacing with the existing legacy mvs systems. we focus on the performance issues, particularly with regard to job management, i/o management and data distribution, and on the tools we built. we finish with the important lessons we learned along the way, some tools we developed that would be useful in dealing with legacy systems, a benchmark comparing some alternative system architectures, and an assessment of the scalability of the system.
integrating handwriting recognition into unix. many new portable computers are substituting an electronic stylus, or pen, for the mouse. while the pen can serve as a simple replacement for the mouse, it also provides an enhanced drawing capability. this capability opens up the potential for new modes of user interaction, one of which is text input through handwriting instead of keyboard entry. in this paper, the integration of handwriting recognition into the unix operation system is discussed. we begin with an examination of the current state of the art in recognition algorithms and how handwriting recognition can enhance a user interface. a standard application program interface for handwriting recognition engines (hre api) is then presented. the hre api is distinguished from existing pc operating system api's in that it is specifically designed for multiple handwriting recognition engines of differing technologies, rather than a single, vendor-specific engine, and it shares a relatively narrow surface area with the window system. the latter characteristic allows it to be used with existing window systems, such as x, but does not hinder migration to other window systems should they become available. the api has been implemented with a public domain recognition engine and is currently being circulated among vendors of handwriting recognition engines for comment. finally, the paper concludes with a discussion of where handwriting recognition belongs in the current x window system architecture, and what would be needed to make handwriting an equal partner with typed keyboard input for text entry.
treadmarks: distributed shared memory on standard workstations and operating systems. treadmarks is a distributed shared memory (dsm) system for standard unix systems such as sunos and ultrix. this paper presents a performance evaluation of treadmarks running on ultrix using decstation-5000/240's that are connected by a 100-mbps switch-based atm lan and a 10-mbps ethernet. our objective is to determine the efficiency of a user-level dsm implementation on commercially available workstations and operating systems. we achieved good speedups on the 8-processor atm network for jacobi (7.4), tsp (7.2), quicksort (6.3), and ilink (5.7). for a slightly modified version of water from the splash benchmark suite, we achieved only moderate speedups (4.0) due to the high communication and synchronization rate. speedups decline on the 10-mbps ethernet (5.5 for jacobi, 6.5 for tsp, 4.2 for quicksort, 5.1 for ilink, and 2.1 for water), reflecting the bandwidth limitations of the ethernet. these results support the contention that, with suitable networking technology, dsm is a viable technique for parallel computation on clusters of workstations. to achieve these speedups, treadmarks goes to great lengths to reduce the amount of communication performed to maintain memory consistency. it uses a lazy implementation of release consistency, and it allows multiple concurrent writers to modify a page, reducing the impact of false sharing. great care was taken to minimize communication overhead. in particular, on the atm network, we used a standard low-level protocol, aal3/4, bypassing the tcp/ip protocol stack. unix communication overhead, however, remains the main obstacle in the way of better performance for programs like water. compared to the unix communication overhead, memory management cost (both kernel and user level) is small and wire time is negligible. this research was supported in part by the national science foundation under grants ccr-9116343, ccr-9211004, cda-9222911, and cda-9310073, by the texas advanced technology program under grant 003604014, and by a nasa graduate fellowship.
transparent network security policy enforcement. recent work in the area of network security, such as ipsec, provides mechanisms for securing the traffic between any two interconnected hosts. however, it is not always possible, economical, or even practical from an administration and operational point of view to upgrade the software and configuration of all the nodes in a network to support such security protocols. one apparent solution to this problem is the use of security gateways that apply the relevant security protocols on behalf of the protected nodes, under the assumption that the "last hop" between the security gateway and the end node is safe without cryptography. such a gateway can be set to enforce specific security policies for different types of traffic. while this solution is appealing in static scenarios (such as building so-called "intranets"), the use of layer-3 (network) routers as security gateways presents some transparency and configuration problems with regards to peer authentication in the automated key management protocol. this paper describes the architecture and implementation of a layer-2 (link layer) bridge with extensions for offering layer-3 security services. we extend the openbsd ethernet bridge to perform simple ip packet filtering and ipsec processing for incoming and outgoing packets on behalf of a protected node, completely transparently to both the protected and the remote communication endpoint. the same mechanism may be used to construct "virtual local area networks," by establishing ipsec tunnels between openbsd bridges connected geographically separated lans. as our system operates in the link layer, there is no need for software or configuration changes in the protected nodes.
dynamic vnodes - design and implementation. dynamic vnodes make the unix kernel responsive to a varying demand for vnodes, without a need to rebuild the kernel. it also optimizes the usage of memory by deallocating excess vnodes. this paper describes the design and implementation of dynamic vnodes in dec osf/1 v3.0. the focus is on the vnode deallocation logic in a symmetric multi-processing environment. deallocation of vnodes differs from the familiar concept of dynamically allocated data structures in the following ways: the legacy name-cache design implicitly assumes that vnodes are never deallocated, and the vnode free-list needs to cache unused vnodes effectively.
solaris mc: a multi computer os. solaris mc is a prototype distributed operating system for multi-computers (i.e. clusters of nodes) that provides a single-system image: a cluster appears to the user and applications as a single computer running the solaris®, operating system. solaris mc is built as a set of extensions to the base solaris unix®, system and provides the same abi/api as solaris, running unmodified applications. the components of solaris mc are implemented in c++ through a corba-compliant object oriented system with all new services defined by the idl definition language. objects communicate through a runtime system that borrows from solaris doors and spring subcontracts. solaris mc is designed for high availability: if a node fails, the remaining nodes remain operational. solaris mc has a distributed caching file system with unix consistency semantics, based on the spring virtual memory and file system architecture. process operations are extended across the cluster, including remote process execution and a global /proc file system. the external networks is transparently accessible from any node in the cluster. the prototype is fairly complete--we regularly exercise the system by running multiple copies of an off-the-shelf commercial database system.
operating system support for virtual machines. a virtual-machine monitor (vmm) is a useful technique for adding functionality below existing operating system and application software. one class of vmms (called type ii vmms) builds on the abstractions provided by a host operating system. type ii vmms are elegant and convenient, but their performance is currently an order of magnitude slower than that achieved when running outside a virtual machine (a standalone system). in this paper, we examine the reasons for this large overhead for type ii vmms. we find that a few simple extensions to a host operating system can make it a much faster platform for running a vmm. taking advantage of these extensions reduces virtualization overhead for a type ii vmm to 14-35% overhead, even for workloads that exercise the virtual machine intensively.
a network file system over http: remote access and modification of files and . the goal of the present httpfs project is to enable access to remote files, directories, and other containers through an http pipe. httpfs system permits retrieval, creation and modification of these resources as if they were regular files and directories on a local filesystem. the remote host can be any unix or win9x/winnt box that is capable of running a perl cgi script and accessible either directly or via a web proxy or a gateway. httpfs runs entirely in user space. the current implementation fully supports reading as well as creating, writing, appending, and truncating of files on a remote http host. httpfs provides an isolation level for concurrent file access stronger than the one mandated by posix file system semantics, closer to that of afs. both a programmatic interface with familiar open(), read(), write(), close(), etc. calls, and an interactive interface, via the popular midnight commander file browser, are provided.
improving the write performance of an nfs server. the network file system (nfs) utilizes a stateless protocol between clients and servers; the major advantage of this statelessness is that nfs crash recovery is very easy. however, the protocol requires that data modification operations such as write be fully committed to stable storage before replying to the client. the cost of this is significant in terms of response latency and server cpu and i/o loading. this paper describes a write gathering technique that exploits the fact that there are often several write requests for the same file presented to the server at about the same time. with this technique the data portions of these writes are combined and a single metadata update is done that applies to them all. no replies are sent to the client until after this metadata update has been fully committed, thus the nfs crash recovery design is not violated. this technique can be used in most nfs server implementations and requires no client modifications.
rex: secure, extensible remote execution. the ubiquitous ssh package has demonstrated the importance of secure remote login and execution. as remote execution tools grow in popularity, users require new features and extensions, which are difficult to add to existing systems. rex is a remote execution utility with a novel architecture specifically designed for extensibility as well as security and transparent connection persistence in the face of network complexities such as nat and dynamic ip addresses. to achieve extensibility, rex bases much of its functionality on a single new abstraction--emulated file descriptor passing across machines. this abstraction is powerful enough for users to extend rex's functionality in many ways without changing the core software or protocol. rex addresses security in two ways. first, the implementation internally leverages file descriptor passing to split the server into several smaller programs, reducing both privileged and remotely exploitable code. second, rex selectively delegates authority to processes running on remote machines that need to access other resources. the delegation mechanism lets users incrementally construct trust policies for remote machines. finally, rex provides mechanisms for accessing servers without globally routable ip addresses, and for resuming sessions when a tcp connection aborts or an endpoint's ip address changes. measurements of the system demonstrate that rex's architecture does not come at the cost of performance.
the ferret document browser. the ferret document browser is a vehicle for exploring the design and use of document storage and retrieval systems. its distributed, modular structure allows independent information providers to control their data, yet make use of a common access and billing control facility. document images are distributed via a nationwide at&t corporate internet which consists mainly of ethernet networks interconnected by leased data circuits. the relatively low bandwidth of this networks is dealt with by compressing the documents for transmission, and by decompressing pages as requested on the workstation. a page image can be decompressed and displayed in less that a half second. a broadband version of the system makes use of the bbfs broadband file server, the hpc interconnect, the luckynet broadband network and the liaison network multimedia workstation. this system allows document browsing at rates up to 15 page images per second.
a flash-memory based file system. a flash memory device driver that supports a conventional unix file system transparently was designed. to avoid the limitations due to flash memory's restricted number of write cycles and its inability to be overwritten, this driver writes data to the flash memory system sequentially as a log-structured file system (lfs) does and uses a cleaner to collect valid data blocks and reclaim invalid ones by erasing the corresponding flash memory regions. measurements showed that the overhead of the cleaner has little effect on the performance of the prototype when utilization is low but that the effect becomes critical as the utilization gets higher, reducing the random write throughput from 222 kbytes/s at 30% utilization to 40 kbytes/s at 90% utilization. the performance of the prototype in the andrew benchmark test is roughly equivalent to that of the 4.4bsd pageable memory based file system (mfs).
a cooperative internet backup scheme. we present a novel peer-to-peer backup technique that allows computers connected to the internet to back up their data cooperatively: each computer has a set of partner computers, which collectively hold its backup data. in return, it holds a part of each partner's backup data. by adding redundancy and distributing the backup data across many partners, a highly-reliable backup can be obtained in spite of the low reliability of the average internet machine. because our scheme requires cooperation, it is potentially vulnerable to several novel attacks involving free riding (e.g., holding a partner's data is costly, which tempts cheating) or disruption. we defend against these attacks using a number of new methods, including the use of periodic random challenges to ensure partners continue to hold data and the use of disk-space wasting to make cheating unprofitable. results from an initial prototype show that our technique is feasible and very inexpensive: it appears to be one to two orders of magnitude cheaper than existing internet backup services.
building secure high-performance web services with okws. okws is a toolkit for building fast and secure web services. it provides web developers with a small set of tools that has proved powerful enough to build complex systems with limited effort. despite its emphasis on security, okws shows performance improvements compared to popular systems: when servicing fully dynamic, non-disk-bound database workloads, okws's throughput and responsiveness exceed that of apache 2 [3], flash [23] and haboob [44]. experience with okws in a commercial deployment suggests it can reduce hardware and system management costs, while providing security guarantees absent in current systems.
an analysis of trace data for predictive file caching in mobile computing. one way to provide mobile computers with access to the resources of a network, even in the absence of communication, is to predict which information will be used during disconnection and cache the appropriate data while still connected. to determine the feasibility of this approach, traces of file-access activity for three diverse application domains were collected for periods of over two months. analysis of these traces using traditional and new measures reveals that user working sets tend to be small compared to modern disk sizes, that users tend to reference the same files for several days or even weeks at a time, and that different users do not tend to write to the same file except in highly constrained circumstances. these factors encourage the conclusion that an automated caching system can be built for a wide variety of environments.
redundancy elimination within large collections of files. ongoing advancements in technology lead to ever-increasing storage capacities. in spite of this, optimizing storage usage can still provide rich dividends. several techniques based on delta-encoding and duplicate block suppression have been shown to reduce storage overheads, with varying requirements for resources such as computation and memory. we propose a new scheme for storage reduction that reduces data sizes with an effectiveness comparable to the more expensive techniques, but at a cost comparable to the faster but less effective ones. the scheme, called redundancy elimination at the block level (rebl), leverages the benefits of compression, duplicate block suppression, and delta-encoding to eliminate a broad spectrum of redundant data in a scalable and efficient manner. rebl generally encodes more compactly than compression (up to a factor of 14) and a combination of compression and duplicate suppression (up to a factor of 6.7). rebl also encodes similarly to a technique based on delta-encoding, reducing overall space significantly in one case. furthermore, rebl uses super-fingerprints, a technique that reduces the data needed to identify similar blocks while dramatically reducing the computational requirements of matching the blocks: it turns o(n2) comparisons into hash table lookups. as a result, using super-fingerprints to avoid enumerating matching data objects decreases computation in the resemblance detection phase of rebl by up to a couple orders of magnitude.
flexible and safe resolution of file conflicts. in this paper we describe the support provided by the coda file system for transparent resolution of conflicts arising from concurrent updates to a file in different network partitions. such partitions often occur in mobile computing environments. coda provides a framework for invoking customized pieces of code called application-specific resolvers (asrs) that encapsulate the knowledge needed for file resolution. if resolution succeeds, the user notices nothing more than a slight performance delay. only if resolution fails does the user have to resort to manual repair. our design combines a rule-based approach to asr selection with transactional encapsulation of asr execution. this paper shows how such an approach leads to flexible and efficient file resolution without loss of security or robustness.
a performance comparison of unix operating systems on the pentium. this paper evaluates the performance of three popular versions of the unix operating system on the x86 architecture: linux, freebsd, and solaris. we evaluate the systems using freely available micro- and application benchmarks to characterize the behavior of their operating system services. we evaluate the currently available major releases of the systems "asis," without any performance tuning. our results show that the x86 operating systems and system libraries we tested fail to deliver the pentium's full memory write performance to applications. on small-file workloads, linux is an order of magnitude faster than the other systems. on networking software, freebsd provides two to three times higher bandwidth than linux. in general, solaris performance usually lies between that of the other two systems. although each operating system out-performs the others in some area, we conclude that no one system offers clearly better overall performance. other factors, such as extra features, ease of installation, or freely available source code, are more convincing reasons for choosing a particular system.
design and implementation of a multimedia protocol suite in a bsd unix kernel. development of distributed multimedia applications requires support for coordination and temporal/causal synchronization of traffic over related streams. our current research involves investigation of appropriate os and communication abstractions to support such applications. towards this goal, we have designed and implemented mcp, a suite of transport and session layer protocols, in the framework of a standard bsd unix networking platform. mcp contains two new abstractions. first, mcp contains a token-based mechanism for coordination of traffic over a multipoint connection. second, mcp includes an abstraction called a multi-flow conversation that enforces both temporal and causal synchronization among related data streams. this paper discusses unix kernel implementation of mcp and describes our experience in using mcp.
mgtk: an sml binding of gtk+. we describe mgtk, a standard ml language binding for the gtk+ toolkit. gtk+ is a graphical toolkit for the x window system, and provides an object-oriented c language api. since standard ml is a mostly-functional language without object types, constructing a binding to gtk+ is not a trivial task. in mgtk, a single-inheritance class hierarchy is encoded using sml's type system. most of the mgtk binding is machine generated, to best utilize the limited manpower of the project. the goal of the mgtk project is "just" to present a type-safe interface to gtk+ for sml programmers. this contrasts with gui libraries for functional languages, which concentrate on producing good user interfaces: there are several sml graphical user interface libraries available for this task. with mgtk, sml applications have access to the mature, complete and familiar gtk+ user interface.
operation-based update propagation in a mobile file system. in this paper we describe a technique called operation-based update propagation for efficiently transmitting updates to large files that have been modified on a weakly connected client of a distributed file system. in this technique, modifications are captured above the file-system layer at the client, shipped to a surrogate client that is strongly connected to a server, re-executed at the surrogate, and the resulting files transmitted from the surrogate to the server. if re-execution fails to produce a file identical to the original, the system falls back to shipping the file from the client over the slow network. we have implemented a prototype of this mechanism in the coda file system on linux, and demonstrated performance improvements ranging from 40 percents to nearly three orders of magnitude in reduced network traffic and elapsed time. we also found a novel use of forward error correction in this context.
network programming for the rest of us. twisted is a high-level networking framework that is built around event-driven asynchronous i/o. it supports tcp, ssl, udp and other network transports. twisted supports a wide variety of network protocols (including imap, ssh, http, dns). it is designed in a way that makes it easy to use with other event-driven toolkits such as gtk+, qt, tk, wxpython and win32. implemented mostly in python, twisted makes it possible to create network applications without having to worry about low-level platform specific details. however, unlike many other network toolkits, twisted still allows developers to access platform specific features if necessary. twisted has been used to develop a wide variety of applications, including messaging clients, distributed hash tables, web applications and both open source projects and commercial applications.
the vinum volume manager. the vinum volume manager is a block device driver which implements virtual disk drives. it isolates disk hardware from the block device interface and maps data in ways which result in an increase in flexibility, performance and reliability compared to the traditional slice view of disk storage. vinum implements the raid-0, raid-1 and raid-5 models, both individually and in combination.
malloc() performance in a multithreaded linux environment. network servers make special demands that other types of applications may not make on memory allocators. we describe a simple malloc() microbenchmark suite that tests the ability of malloc() to divide its work efficiently among multiple threads and processors. the purpose of this suite is to determine the suitability of an operating system's heap allocator for use with network servers running in an smp environment.
the design of the dents dns server. dents is a server implementation of the internet's domain name system. dents main features are a modular driver architecture, a corba-based control facility, a replaceable tree system, a clean design and good karma. dents is free software, licensed under version 2 of the gpl. in this paper, i describe the design of dents, concentrating on the innovations and evolutions it embodies, and including the future directions in which we hope to take the server. i describe some of the problems we've had. finally, i summarize some lessons about server design which dents reflects.
a quantitative analysis of disk drive power management in portable computers. with the advent and subsequent popularity of portable computers, power management of system components has become an important issue. current portable computers implement a number of power reduction techniques to achieve a longer battery life. included among these is spinning down a disk during long periods of inactivity. in this paper, we perform a quantitative analysis of the potential costs and benefits of spinning down the disk drive as a power reduction technique. our conclusion is that almost all the energy consumed by a disk drive can be eliminated with little loss in performance. although on current hardware, reliability can be impacted by our policies, the next generation of disk drives will use technology (such as dynamic head loading) which is virtually unaffected by repeated spinups. we found that the optimal spindown delay time, the amount of time the disk idles before it is spun down, is 2 seconds. this differs significantly from the 3-5 minutes in current practice by industry. we will show in this paper the effect of varying the spindown delay on power consumption; one conclusion is that a 3-5 minute delay results in only half of the potential benefit of spinning down a disk.
drinking from the firehose: multicast usenet news. news transport and spooling systems of the last several years have concentrated on decreasing the resource load on news servers. one beneficial side effect has been the average decrease in time that a news system spends on a given article. this paper describes a novel usenet news transport protocol, which we call muse. the two major motivations behind muse are to reduce the average propagation delays of articles on usenet and to further reduce the resource load on a centralized news server. muse runs on top of the experimental internet multicast backbone, commonly referred to as the mbone. major design and implementation issues are discussed. security concerns of multicast news are discussed and our solution is examined. the problems of scaling news distribution to thousands of hosts are also addressed.
implementation of a modern web search engine cluster. yuntis is a fully-functional prototype of a complete web search engine with features comparable to those available in commercial-grade search engines. in particular, yuntis supports page quality scoring based on global web linkage graph, extensively exploits text associated with links, computes pages' keywords and lists of similar pages of good quality, and provides a very flexible query language. this paper reports our experiences in the three-year development process of yuntis, by presenting its design issues, software architecture, implementation details, and performance measurements.
eliminating receive livelock in an interrupt-driven kernel. most operating systems use interface interrupts to schedule network tasks. interrupt-driven systems can provide low overhead and good latency at low offered load, but degrade significantly at higher arrival rates unless care is taken to prevent several pathologies. these are various forms ofreceive livelock, in which the system spends all of its time processing interrupts, to the exclusion of other necessary tasks. under extreme conditions, no packets are delivered to the user application or the output of the system. to avoid livelock and related problems, an operating system must schedule network interrupt handling as carefully as it schedules process execution. we modified an interrupt-driven networking implementation to do so; this modification eliminates receive livelock without degrading other aspects of system performance. our modifications include the use of polling when the system is heavily loaded, while retaining the use of interrupts ur.jer lighter load. we present measurements demonstrating the success of our approach.
the restore-o-mounter: the file motel revisited. we present a scheme for referencing and accessing saved ((footnote 1: we use the word "save" to denote the super set of "backup" and "archive"; save is also easier to conjugate than backup.)) files in a manner that is transparent to unix" applications. the scheme requires no kernel modifications. instead, it uses a "mounted" process that allows users to change directories to the past and browse their saved files with their favorite utilities. the mounted process acts as a protocol gateway between nfs and a commercially available network backup product. time travel is supported; users may change directories to any moment in the past. any saved version (not just the most recent version) of any file can be viewed or recovered, even if the file has since been deleted. using this transparent method of retrieving saved files by naming their location in the past, a poor man's file migration scheme can be implemented by substituting a symbolic link to a saved location for a file. once a file is referenced, the symbolic link can be replaced with its original file. this migration scheme requires no kernel modifications yet remains transparent to unix applications and users.
performance implications of multiple pointer sizes. many users need 64-bit architectures: 32-bit systems cannot support the largest applications, and 64-bit systems perform better for some applications. however, performance on some other applications can suffer from the use of large pointers; large pointers can also constrain feasible problem size. such applications are best served by a 64-bit machine that supports the use of both 32-bit and 64-bit pointer variables. this paper analyzes several programs and programming techniques to understand the performance implications of different pointer sizes. many (but not all) programs show small but definite performance consequences, primarily due to cache and paging effects.
porting the sgi xfs file system to linux. the limitations of traditional linux file systems are becoming evident as new application demands for linux file systems arise. sgi has ported the xfs file system to the linux operating system to address these constraints. this paper describes the major technical areas that were addressed in this port, specifically regarding the file system interface to the operating system, buffer caching in xfs, and volume management layers. in addition, this paper describes some of the legal issues surrounding the porting of the xfs file system, and the encumbrance review process that sgi performed.
operating system support for distributed multimedia. multimedia applications place new demands upon processors, networks and operating systems. while some network designers, through atm for example, have considered revolutionary approaches to supporting multimedia, the same cannot be said for operating systems designers. most work is evolutionary in nature, attempting to identify additional features that can be added to existing systems to support multimedia. here we describe the pegasus project's attempt to build an integrated hardware and operating system environment from the ground up specifically targeted towards multimedia.
not quite nfs, soft cache consistency for nfs. there are some constraints inherent in the nfstm∈ protocol that result in performance limitations for high performance workstation environments. this paper discusses an nfs-like protocol named not quite nfs (nqnfs), designed to address some of these limitations. this protocol provides full cache consistency during normal operation, while permitting more effective client-side caching in an effort to improve performance. there are also a variety of minor protocol changes, in order to resolve various nfs issues. the emphasis is on observed performance of a preliminary implementation of the protocol, in order to show how well this design works and to suggest possible areas for further improvement.
peer-to-peer communication across network address translators. network address translation (nat) causes well-known difficulties for peer-to-peer (p2p) communication, since the peers involved may not be reachable at any globally valid ip address. several nat traversal techniques are known, but their documentation is slim, and data about their robustness or relative merits is slimmer. this paper documents and analyzes one of the simplest but most robust and practical nat traversal techniques, commonly known as hole punching. hole punching is moderately well-understood for udp communication, but we show how it can be reliably used to set up peer-to-peer tcp streams as well. after gathering data on the reliability of this technique on a wide variety of deployed nats, we nd that about 82% of the nats tested support hole punching for udp, and about 64% support hole punching for tcp streams. as nat vendors become increasingly conscious of the needs of important p2p applications such as voice over ip and online gaming protocols, support for hole punching is likely to increase in the future.
large granularity cache coherence for intermittent connectivity. to function in mobile computing environments, distributed file systems must cope with networks that are slow, intermittent, or both. intermittence vitiates the effectiveness of callback-based cache coherence schemes in reducing client-server communication, because clients must validate files when connections are reestablished. in this paper we show how maintaining cache coherence at a large granularity alleviates this problem. we report on the implementation and performance of large granularity cache coherence for the coda file system. our measurements confirm the value of this technique. at 9.6 kbps, this technique takes only 4-20% of the time required by two other strategies to validate the cache for a sample of coda users. even at this speed, the network is effectively eliminated as the bottleneck for cache validation.
swarm: a log-structured storage system for linux. swarm [3] is a storage system for linux that provides scalable, reliable, and cost-effective data storage. at its lowest level, swarm implements a log-structured interface to a cluster of storage devices. above the log, swarm provides an infrastructure that allows high-level abstractions and functionality to be implemented easily and efficiently. this paper describes the design and implementation of swarm, paying particular attention to the swarm infrastructure and how it has been used to construct two storage systems: sting, a log-structured file system for linux, and ext2fs/swarm, a swarm-based version of the linux ext2 file system that runs unmodified above ablock device compatibility layer. the paper concludes with a discussion of our experiences using linux as a platform for research.
an overview of the netware operating system. the netware operating system is designed specifically to provide service to clients over a computer network. this design has resulted in a system that differs in several respects from more general-purpose operating systems. in addition to highlighting the design decisions that have led to these differences, this paper provides an overview of the netware operating system, with a detailed description of its kernel and its software-based approach to fault tolerance.
reducing the disk i/o of web proxy server caches. the dramatic increase of http traffic on the internet has resulted in wide-spread use of large caching proxy servers as critical internet infrastructure components. with continued growth the demand for larger caches and higher performance proxies grows as well. the common bottleneck of large caching proxy servers is disk i/o. in this paper we evaluate ways to reduce the amount of required disk i/o. first we compare the file system interactions of two existing web proxy servers, cern and squid. then we show how design adjustments to the current squid cache architecture can dramatically reduce disk i/o. our findings suggest two that strategies can significantly reduce disk i/o: (1) preserve locality of the http reference stream while translating these references into cache references, and (2) use virtual memory instead of the file system for objects smaller than the system page size. the evaluated techniques reduced disk i/o by 50% to 70%.
an analysis of process and memory models to support high-speed networking in a unix environment. in order to reap the benefits of high-speed networks, the performance of the host operating system must at least match that of the underlying network. a barrier to achieving high throughput is the cost of copying data within current host architectures. we present a performance comparison of three styles of network device driver designed for a conventional monolithic unix kernel. each driver performs a different number of copies. the zero-copy driver works by allowing the memory on the network adapter to be mapped directly into user address space. this maximises performance at the cost of: 1) breaking the semantics of existing network apis such as bsd sockets and svr4 tli; 2) pushing responsibility for network buffer management up from the kernel into the application layer. the single-copy driver works by copying data directly between user space and adapter memory obviating the need for an intermediate copy into kernel buffers in main memory. this approach can be made transparent to existing application code but, like the zero-copy case, relies on an adapter with a generous quantity of on-board memory for buffering network data. the two-copy driver is a conventional streams driver. the two-copy approach sacrifices performance for generality. we observe that the streams overhead for small packets is significant. we report on the benefit of the hardware cache in ameliorating the effect of the second copy, although we note that streaming network data through the cache reduces the level of cache residency seen by the rest of the system. a barrier to achieving low jitter is the non-deterministic nature of many operating system schedulers. we describe the implementation and report on the performance of a kernel streaming driver that allows data to be copied between a network adapter and another i/o device without involving the process scheduler. this provides performance benefits in terms of increased throughput, increased cpu availability and reduced jitter.
finding similar files in a large file system. we present a tool, called sif, for finding all similar files in a large file system. files are considered similar if they have significant number of common pieces, even if they are very different otherwise. for example, one file may be contained, possibly with some changes, in another file, or a file may be a reorganization of another file. the running time for finding all groups of similar files, even for as little as 25% similarity, is on the order of 500mb to 1gb an hour. the amount of similarity and several other customized parameters can be determined by the user at a post-processing stage, which is very fast. sif can also be used to very quickly identify all similar files to a query file using a preprocessed index. application of sif can be found in file management, information collecting (to remove duplicates), program reuse, file synchronization, data compression, and maybe even plagiarism detection.
glimpse: a tool to search through entire file systems. glimpse, which stands for global implicit search, provides indexing and query schemes for file systems. the novelty of glimpse is that it uses a very small index - in most cases 2-4% of the size of the text - and still allows very flexible full-text retrieval including boolean queries, approximate matching (i.e., allowing misspelling), and even searching for regular expressions. in a sense, glimpse extends agrep to entire file systems, while preserving most of its functionality and simplicity. query times are typically slower than with inverted indexes, but they are still fast enough for many applications. for example, it took 5 seconds of cpu time to find all 19 occurrences of usenix and winter in a file system containing 69mb of text spanning 4300 files. glimpse is particularly designed for personal information, such as one's own file system. the main characteristic of personal information is that it is non-uniform and includes many types of documents. an information retrieval system for personal information should support many types of queries, flexible interaction, low overhead, and customization, all these are important features of glimpse.
high performance dynamic linking through caching. the spring operating system provides high performance dynamic linking of program images. spring uses caching of both fixed-up program images and partially fixed-up shared libraries to make dynamic linking of program images efficient, to reduce the need for pic (position-independent code), and to improve page sharing between different program images running the same libraries. the result is that with program image caching, dynamically-linked programs have a start-up cost similar to statically-linked programs regardless of the number of unresolved symbols in dynamically-linked program images and shared libraries. in addition, with library and program image caching, we have reduced the need for pic and have increased page sharing.
a uniform name service for spring's unix environment. the spring operating system provides a uniform name service that can be used to associate any name with any object independent of the type of object, and allows arbitrary name spaces to be created and used as first-class objects. we have used this name service to unify the many unix® name spaces. objects that on unix systems are typically stored in separate name spaces are all accessible via a single uniform name service in spring. in addition, it is easy to add new spring objects that are not currently available in unix systems without modifying the underlying name service.
implementation of a reliable remote memory pager. traditional operating systems use magnetic disks as paging devices, even though the cost of a disk transfer measured in processor cycles continues to increase. in this paper we explore the use of remote main memory for paging. we describe the design, implementation and evaluation of a pager that uses main memory of remote workstations as a faster-than-disk paging device and provides reliability in case of single workstation failures. our pager has been implemented as a block device driver linked to the dec osf/1 operating system, without any modifications to the kernel code. using several test applications we measure the performance of remote memory paging over an ethernet interconnection network and find it to be faster than traditional disk paging. we evaluate the performance of various reliability policies and prove their feasibility even over low bandwidth networks, like ethernet. we conclude that the benefits of reliable remote memory paging in workstation clusters are significant today and will probably increase in the near future.
learning spam: simple techniques for freely-available software. the problem of automatically filtering out spam email using a classifier based on machine learning methods is of great recent interest. this paper gives an introduction to machine learning methods for spam filtering, reviewing some of the relevant ideas and work in the open source community. an overview of several feature detection and machine learning techniques for spam filtering is given. the authors' freely-available implementations of these techniques are discussed. the techniques' performance on several different corpora are evaluated. finally, some conclusions are drawn about the state of the art and about fruitful directions for spam filtering for freely-available unix software practitioners.
the design and implementation of a dcd device driver for unix. recent research results [1, 2] using simulation have demonstrated that disk caching disk (dcd), a new disk i/o architecture, has the potential for drastically improving disk write performance besides its higher reliability than traditional disk systems. to validate whether dcd can live up to its promise in the real world environment, we have designed and implemented a dcd device driver for the sun's solaris operating system. measured performance results are very promising. for metadata intensive benchmarks, our dcd driver outperforms the traditional system by a factor of 2-6 in terms of program execution speeds. the driver also guarantees file system integrity in the events of system crashes or failures. moreover, unlike other approaches such as log-structured file systems or soft updates, the dcd driver is completely transparent to the os. it does not require any changes to the os or the on-disk data layout. as a result, it can be used as a "drop-in" replacement for the traditional disk device driver in an existing system to obtain immediate performance improvement. our multi-layered device-driver approach significantly reduces the implementation overhead and improves portability.
an operating system in java for the lego mindstorms rcx microcontroller. the lego mindstorms is a lego bricks based robotics toy series produced by the lego group, based on the ideas developed at the massachusetts institute of technology in the programmable brick project. the heart of a lego robot, the rcx microcontroller, hosts a hitachi h8 microcontroller with 28 kilobytes of memory available for downloadable firmware and applications. in addition to the gui based programming environment provided by lego, a number of alternative programming environments have been developed for the rcx. however, these alternative programming environments are written in c, tightly bound to the hardware, and provide only relatively low level services. the strong hardware dependency makes it hard to debug programs; in practice, a hardware simulator is needed, and such a simulator does not yet exist in an open source form. in this paper we present a new type of operating system and new programming environments for the lego rcx brick. the operating system is written almost completely in java, and currently provides runtime support for java, c and c++ programs. in the case of java applications, simulation and debugging is relatively simple as it can be performed on a standard java virtual machine with just a small hardware simulation package.
the bsd packet filter: a new architecture for user-level packet capture. many versions of unix provide facilities for user-level packet capture, making possible the use of general purpose workstations for network monitoring. because network monitors run as user-level processes, packets must be copied across the kernel/user-space protection boundary. this copying can be minimized by deploying a kernel agent called a packet filter, which discards unwanted packets as early as possible. the original unix packet filter was designed around a stack-based filter evaluator that performs sub-optimally on current risc cpus. the bsd packet filter (bpf) uses a new, register-based filter evaluator that is up to 20 times faster than the original design. bpf alson uses a straighforward buffering strategy that makes its overall performance up to 100 times faster than sun's nit running on the same hardware.
glitz: hardware accelerated image compositing using opengl. in recent years 2d graphics applications and window systems tend to use more demanding graphics features such as alpha blending, image transformations and anti-aliasing. these features contribute to the user interfaces by making it possible to add more visual effects as well as new usable functionalities. all together it makes the graphical interface a more hospitable, as well as efficient, environment for the user. even with today's powerful computers these tasks constitute a heavy burden on the cpu. this is why many proprietary window systems have developed powerful 2d graphics engines to carry out these tasks by utilizing the acceleration capabilities in modern graphics hard-ware. we present glitz, an open source implementation of such a graphics engine, a portable 2d graphics library that can be used to render hardware accelerated graphics. glitz is layered on top of opengl and is designed to act as an additional backend for cairo, providing it with hardware accelerated output. furthermore, an effort has been made to investigate if the level of hardware acceleration provided by the x window system can be improved by using glitz to carry out its fundamental drawing operations.
mosix: how linux clusters solve real-world problems. as the complexity of software increases, the size of the software tends to increase as well, which incurs longer compilation and build cycles. in this paper, the authors present one example of how clusters of linux systems, using the mosix extensions for load monitoring and remote execution, were used to eliminate a performance bottleneck and to reduce the cost of building software. we present a discussion of our original software development cluster, an analysis of the performance issues in that cluster, and the development and modifications done to mosix and linux in order to produce a solution to our problem. we finish by presenting future developments that will enhance our cluster.
process labeled kernel profiling: a new facility to profile system activities. profiling tools that empirically measure the resource usage of a program have been widely used in program development. these tools have traditionally focused on the behavior of the target program. the target program, however, actually performs its job in collaboration with other programs, such as servers and an operating system kernel, in a modern system environment. process-labeled kernel profiling is a novel facility that measures and attributes the kernel resource consumption of programs benefiting from it. this facility, in conjunction with a conventional profiler, enables a programmer to grasp the resource consumption of programs from an overall system point of view. using this information, the programmer is better able to reduce overall resource consumption.
soft updates: a technique for eliminating most synchronous writes in the fast filesystem. traditionally, filesystem consistency has been maintained across system failures either by using synchronous writes to sequence dependent metadata updates or by using write-ahead logging to atomically group them. soft updates, an alternative to these approaches, is an implementation mechanism that tracks and enforces metadata update dependencies to ensure that the disk image is always kept consistent. the use of soft updates obviates the need for a separate log or for most synchronous writes. indeed, the ability of soft updates to aggregate many operations previously done individually and synchronously reduces the number of disk writes by 40 to 70% for file-intensive environments (e.g., program development, mail servers, etc.). in addition to performance enhancement, soft updates can also maintain better disk consistency. by ensuring that the only inconsistencies are unclaimed blocks or inodes, soft updates can eliminate the need to run a filesystem check program after every system crash. instead, the system is brought up immediately. when it is convenient, a background task can be run on the active filesystem to reclaim any lost blocks and inodes. this paper describes an implementation of soft updates and its incorporation into the 4.4bsd fast filesystem. it details the changes that were needed, both to the original research prototype and to the bsd system, to create a production-quality system. it also discusses the experiences, difficulties, and lessons learned in moving soft updates from research to reality; as is often the case, non-focal operations (e.g., fsck and "fsync") required rethinking and additional code. experiences with the resulting system validate the earlier research: soft updates integrates well with existing filesystems and enforces metadata dependencies with performance that is within a few percent of optimal.
lmbench: portable tools for performance analysis. lmbench is a micro-benchmark suite designed to focus attention on the basic building blocks of many common system applications, such as databases, simulations, software development, and networking. in almost all cases, the individual tests are the result of analysis and isolation of a customer's actual performance problem. these tools can be, and currently are, used to compare different system implementations from different vendors. in several cases, the benchmarks have uncovered previously unknown bugs and design flaws. the results have shown a strong correlation between memory system performance and overall performance. lmbench includes an extensible database of results from systems current as of late 1995.
the gnome canvas: a generic engine for structured graphics. the gnome canvas is a generic engine for structured graphics that offers a rich imaging model, high performance rendering, and a powerful high-level api. application programmers can use the canvas to create interactive graphics displays easily. many gnome applications use the canvas as their main display engine, some of them using the basic functionality provided by the canvas, and others by extending it for their particular needs. this paper describes the architecture of the canvas in detail and examines the way it is used in several gnome applications.
berkeley db. berkeley db is an open source embedded database system with a number of key advantages over comparable systems. it is simple to use, supports concurrent access by multiple users, and provides industrial-strength transaction support, including surviving system and disk crashes. this paper describes the design and technical features of berkeley db, the distribution, and its license.
protocol independence using the sockets api. the bsd sockets api provides abstractions and other features that help applications be protocol-independent. unfortunately, not all of the api is abstract and generic, and many programs do not use the apis in a protocol-independent way. this means that most network programs, in practice, only work with one layered set of communications protocols - usually tcp over ip. this hinders compatibility with older protocols and deployment of new ones, and is making ip a victim of its own success. during the course of next-generation ip development, implementors worked to convert protocol-dependent applications into protocol-independent applications. along the way, they defined new interfaces to fix some problems and they found a number of usage problems that lead to protocol dependencies. this paper explains many of the problems encountered, using examples from freely available software, and how to solve them. it also explains many of the new protocol-independent interfaces.
safety checking of kernel extensions. there are many places in operating systems today where extending the running kernel with small and fast extensions is an interesting thing to do. for example, the berkeley packet filter (bpf) allows code for a virtual machine to be uploaded intoa running kernel and executed at packet reception, allowing fairly arbitrary filtering of packets before they cross the expensive kernel to user interface. whatever mechanism is used needs to provide some reasonable guarantees about the safety of the resulting code, which makes this problem complex. this paper describes a simple x86 bytecode verifier that is intended to be used to verify that a small program that is to be loaded obeys a reasonable safety policy. for program constructs that it is able to reason about, it can verify that code does not execute privileged instructions, only accesses known memory locations, and terminates. it cannot reason about arbitrary programs, but can reason about simple programs and developers that know the prover's limitations can write their code to be recognizable by the verifier. the contribution of this work is to show that a very limited prover can operate on native machine code and can efficiently reason about a small but still interesting set of programs.
porting kernel code to four bsds and linux. the u.s. naval research laboratory develops and maintains a freely available ipv6 and ip security distribution. all of the software builds and runs on bsd/os, freebsd, netbsd, and openbsd, and a growing portion of the software builds and runs on linux. each of the four bsds has evolved significantly from their original 4.4bsd-lite ancestor, and increasingly more of that evolution is along divergent paths. linux shares no significant ancestry with the bsds, but is still a posix system, which means that many of the same high-level facilities are available even though their implementation might be completely different. this paper discusses many of the differences and many of the similarities we encountered in the internals of these systems. it also discusses the techniques and glue software that we developed for isolating and abstracting the differences so that we could build a significant base of system code that is portable between all five systems.
tcl: an embeddable command language. tel is an interpreter for a tool command language. it consists of a library package that is embedded in tools (such as editors, debuggers, etc.) as the basic command interpreter. tel provides (a) a parser for a simple textual command language, (b) a collection of built-in utility commands, and a c interface that tools use to augment the built-in commands with tool-specific commands. tel is particularly attractive when integrated with the widget library of a window system; it increases the programmability of the widgets by providing mechanisms for variables, procedures, expressions, etc, it allows users to program both the appearance and the actions of widgets; and it offers a simple but powerful communication mechanism between interactive programs.
managing volunteer activity in free software projects. during the last few years, thousands of volunteers have created a large body of free software. even though this accomplishment shows that the free software development model works, there are some drawbacks associated with this model. due to the volunteer nature of most free software projects, it is impossible to fully rely on participants. volunteers may become busy and neglect their duties. this may lead to a steady decrease of quality as work is not being carried out. the problem of inactive volunteers is intensified by the fact that most free software projects are distributed, which makes it hard to quickly identify volunteers who neglect their duties. this paper shows debian's approach to inactive volunteers. insights presented here can be applied to other free software projects in order to implement effective quality assurance strategies.
efficiently scheduling x clients. the x server is charged with providing window system services to many applications simultaneously, and needs a scheduling mechanism to distribute it's limited resources among these applications. the original scheduling mechanism was simplistic and caused graphics-intensive applications to starve interactive applications. a new scheduling mechanism has been designed which fairly distributes time among the requesting applications while at the same time increasing performance by a small amount. descriptions of the original and new scheduling mechanism and empirical measurements demonstrating the effects of scheduling within the x server are included along with a discussion on how the design was arrived at.
an analysis of file migration in a unix supercomputing environment. the supercomputer center at the national center for atmospheric research (ncar) migrates large numbers of files to and from its mass storage system (mss) because there is insufficient space to store them on the cray supercomputer''s local disks. this paper presents an analysis of file migration data collected over two years. the analysis shows that requests to the mss are periodic, with one day and one week periods. read requests to the mss account for the majority of the periodicity; as write requests are relatively constant over the course of a week. additionally, reads show a far greater fluctuation than writes over a day and week since reads are driven by human users while writes are machine-driven.
a new rendering model for x. x version 11 [sg92] was originally designed and implemented in 1987. in the intervening 13 years, there have been advancements in both applications and hardware, but the core of the x window system has remained largely unchanged. the last major x server architecture changes were included in x11r4. the last wide-spread functional enhancement exported by the x server might well be the shape extension [pac89], designed (in the hot tub) at the 1989 winter usenix in san diego. the rise of inexpensive unix desktop systems in the last couple of years has led to the development of new user-interface libraries, which are not well served by the existing x rendering model. a new 2d rendering model is being developed to serve this new community of applications. the problem space and proposed solutions are discussed.
rama: easy access to a high-bandwidth massively parallel file system. massively parallel file systems must provide high bandwidth file access to programs running on their machines. most accomplish this goal by striping files across arrays of disks attached to a few specialized i/o nodes in the massively parallel processor (mpp). this arrangement requires programmers to give the file system many hints on how their data is to be laid out on disk if they want to achieve good performance. additionally, the custom interface makes massively parallel file systems hard for programmers to use and difficult to seamlessly integrate into an environment with workstations and tertiary storage. the rama file system addresses these problems by providing a massively parallel file system that does not need user hints to provide good performance. rama takes advantage of the recent decrease in physical disk size by assuming that each processor in an mpp has one or more disks attached to it. hashing is then used to pseudo-randomly distribute data to all of these disks, insuring high bandwidth regardless of access pattern. since mpp programs often have many nodes accessing a single file in parallel, the file system must allow access to different parts of the file without relying on a particular node. in rama, a file request involves only two nodes -- the node making the request and the node on whose disk the data is stored. thus, rama scales well to hundreds of processors. since rama needs no layout hints from applications, it fits well into systems where users cannot (or will not) provide such hints. fortunately, this flexibility does not cause a large loss of performance. rama's simulated performance is within 10-15% of the optimum performance of a similarly-sized striped file system, and is a factor of 4 or more better than a striped file system with poorly laid out data.
integrating a command shell into a web browser. the transition from command-line interfaces to graphical interfaces has resulted in programs that are easier to learn and use, but harder to automate and reuse. another transition is now underway, to html interfaces hosted by a web browser. to help users automate html interfaces, we propose the browser-shell, a web browser that integrates a command interpreter into the browser's location box. the browser-shell's command language is designed for extracting and manipulating html and text, and commands can also invoke local programs. command input is drawn from the current browser page, and command output is displayed as a new page. the browser-shell brings to web browsing many advantages of the unix shell, including scripting web services and creating pipelines of web services and local programs. a browser-shell also allows legacy command-line programs to be wrapped with an html/cgi interface that is graphical but still scriptable, and offers a new shell interaction model, different from the conventional typescript model, which may improve usability in some respects.
lightweight structured text processing. text is a popular storage and distribution format for information, partly due to generic text-processing tools like unix grep and sort. unfortunately, existing generic tools make assumptions about text format (e.g., each line is a record) that limit their applicability. custom-built tools are one alternative, but they require substantial time investment and programming expertise. we describe a new approach, lightweight structured text processing, which overcomes these difficulties by enabling users to define text structure interactively and manipulate the structure with generic tools. our prototype system, lapis, is a web browser that can highlight, filter, and sort text regions described by the user. lapis has several advantages over other systems: (1) the ability to define custom structure with a simple, intuitive pattern language; (2) interactive specification, showing pattern matches in context and letting users choose the most convenient combination of manual selection and pattern matching; and (3) external parsers for standard text formats. the pattern language in lapis, text constraints, describes text structure in high-level terms, with region relationships like before, after, in, and contains. we describe an implementation of text constraints using a novel, compact representation of region sets as collections of rectangles, or region intervals. we also illustrate some examples of applying lapis to web pages, text files, and source code.
ask: active spam killer. we present active spam killer (ask), a program that attempts to validate unknown senders before allowing delivery of their message. validation occurs by means of a challenge reply sent to senders who are not yet known to the system. messages are kept in a queue pending confirmation until the sender replies to the challenge. further messages coming from confirmed senders are delivered immediately. in a sample of 1000 spam mails, ask was 99.7% effective at blocking spam, resulting in only 3 spam messages being delivered. other programs' best ratios were 97.8% or as many as 22 spam messages delivered.
strlcpy and strlcat - consistent, safe, string copy and concatenation. as the prevalence of buffer overflow attacks has increased, more and more programmers are using size or length-bounded string functions such as strncpy() and strncat(). while this is certainly an encouraging trend, the standard c string functions generally used were not really designed for the task. this paper describes an alternate, intuitive, and consistent api designed with safe string copies in mind. there are several problems encountered when strncpy() and strncat() are used as safe versions of strcpy() and strcat(). both functions deal with nul-termination and the length parameter in different and non-intuitive ways that confuse even experienced programmers. they also provide no easy way to detect when truncation occurs. finally, strncpy() zero-fills the remainder of the destination string, incurring a performance penalty. of all these issues, the confusion caused by the length parameters and the related issue of nul-termination are most important. when we audited the openbsd source tree for potential security holes we found rampant misuse of strncpy() and strncat(). while not all of these resulted in exploitable security holes, they made it clear that the rules for using strncpy() and strncat() in safe string operations are widely misunderstood. the proposed replacement functions, strlcpy() and strlcat(), address these problems by presenting an api designed for safe string copies (see figure 1 for function prototypes). both functions guarantee nul-termination, take as a length parameter the size of the string in bytes, and provide an easy way to detect truncation. neither function zero-fills unused bytes in the destination.
flash: an efficient and portable web server. this paper presents the design of a new web server architecture called the asymmetric multi-process event-driven (amped) architecture, and evaluates the performance of an implementation of this architecture, the flash web server. the flash web server combines the high performance of single-process event-driven servers on cached workloads with the performance of multiprocess and multi-threaded servers on disk-bound workloads. furthermore, the flash web server is easily portable since it achieves these results using facilities available in all modern operating systems. the performance of different web server architectures is evaluated in the context of a single implementation in order to quantify the impact of a server's concurrency architecture on its performance. furthermore, the performance of flash is compared with two widely-used web servers, apache and zeus. results indicate that flash can match or exceed the performance of existing web servers by up to 50% across a wide range of real workloads. we also present results that show the contribution of various optimizations embedded in flash.
a better update policy. some file systems can delay writing modified data to disk, in order to reduce disk traffic and overhead. prudence dictates that such delays be bounded, in case the system crashes. we refer to an algorithm used to decide when to write delayed data back to disk as an update policy. traditional unix® systems use a periodic update policy, writing back all delayed-write data once every 30 seconds. periodic update is easy to implement but performs quite badly in some cases. this paper describes an approximate implementation of an interval periodic update policy, in which each individual delayed-write block is written when its age reaches a threshold. interval periodic update adds little code to the kernel and can perform much better than periodic update. in particular, interval periodic update can avoid the huge variances in read response time caused by using periodic update with a large buffer cache.
pandora: a flexible network monitoring platform. this paper presents pandora, a network monitoring platform that captures packets using purely passive techniques. pandora addresses current needs for improving internet middleware and infrastructure by providing both in-depth understanding of network usage and metrics to compare existing protocols. pandora is flexible and easy to use and deploy. the elementary monitoring tasks are encapsulated as independent entities we call monitoring components. the actual packet analysis is performed by stacking the appropriate components. pandora also preserves user privacy by allowing control of the "anonymization" policy. finally, the evaluation we conducted shows that overheads due to pandora's flexibility do not significantly affect performance. pandora is fully functional and has already been used to collect web traffic traces at inria rocquencourt.
union mounts in 4.4bsd-lite. this paper describes the design and rationale behind union mounts, a new filesystem-namespace management tool available in 4.4bsd-lite. unlike a traditional mount that hides the contents of the directory on which it is placed, a union mount presents a view of a merger of the two directories. although only the filesystem at the top of the union stack can be modified, the union filesystem gives the appearance of allowing anything to be deleted or modified. files in the lower layer may be deleted with whiteout in the top layer. files to be modified are automatically copied to the top layer. this new functionality makes possible several new applications including the ability to apply patches to a cd-rom and eliminate symbolic links generated by an automounter. also possible is the provision of per-user views of the filesystem, allowing private views of a shared work area, or local builds from a centrally shared read-only source tree.
implementing lottery scheduling: matching the specializations in traditional schedulers. we describe extensions to lottery scheduling, a proportional-share resource management algorithm, to provide the performance assurances present in traditional non-real time process schedulers. lottery scheduling enables flexible control over relative process execution rates with a ticket abstraction and provides load insulation among groups of processes using currencies. we first show that a straightforward implementation of lottery scheduling does not provide the responsiveness for a mixed interactive and cpu-bound workload offered by the decay usage priority scheduler of the freebsd operating system. moreover, standard lottery scheduling ignores kernel priorities used in the freebsd scheduler to reduce kernel lock contention. in this paper, we show how to use dynamic ticket adjustments to incorporate into a lottery scheduler the specializations present in the freebsd scheduler to improve interactive response time and reduce kernel lock contention. we achieve this while maintaining lottery scheduling's flexible control over relative execution rates and load insulation. in spite of added scheduling overhead, the throughput of cpu-bound workloads under our scheduler is within one percent of the freebsd scheduler for all but one test. we describe our design, evaluate our implementation, and relate our experience in deploying our hybrid lottery scheduler on production machines.
lexical file names in plan 9, or, getting dot-dot right. symbolic links make the unix file system non-hierarchical, resulting in multiple valid path names for a given file. this ambiguity is a source of confusion, especially since some shells work overtime to present a consistent view from programs such as pwd, while other programs and the kernel itself do nothing about the problem. plan 9 has no symbolic links but it does have other mechanisms that produce the same difficulty. moreover, plan 9 is founded on the ability to control a program's environment by manipulating its name space. ambiguous names muddle the result of operations such as copying a name space across the network. to address these problems, the plan 9 kernel has been modified to maintain an accurate path name for every active file (open file, working directory, mount table entry) in the system. the definition of 'accurate' is that the path name for a file is guaranteed to be the rooted, absolute name the program used to acquire it. these names are maintained by an efficient method that combines lexical processing--such as evaluating .. by just removing the last path name element of a directory--with local operations within the file system to maintain a consistently, easily understood view of the name system. ambiguous situations are resolved by examining the lexically maintained names themselves. a new kernel call, fd2path, returns the file name associated with an open file, permitting the use of reliable names to improve system services ranging from pwd to debugging. although this work was done in plan 9, unix systems could also benefit from the addition of a method to recover the accurate name of an open file or the current directory.
plumbing and other utilities. plumbing is a new mechanism for interprocess communication in plan 9, specifically the passing of messages between interactive programs as part of the user interface. although plumbing shares some properties with familiar notions such as cut and paste, it offers a more general data exchange mechanism without imposing a particular user interface. the core of the plumbing system is a program called the plumber, which handles all messages and dispatches and reformats them according to configuration rules written in a special-purpose language. this approach allows the contents and context of a piece of data to define how it is handled. unlike with drag and drop or cut and paste, the user doesn't need to deliver the data; the contents of a plumbing message, as interpreted by the plumbing rules, determine its destination. the plumber has an unusual architecture: it is a language-driven file server. this design has distinct advantages. it makes plumbing easy to add to an existing, unix-like command environment; it guarantees uniform handling of inter-application messages; it offloads from those applications most of the work of extracting and dispatching messages; and it works transparently across a network.
acme: a user interface for programmers. a hybrid of window system, shell, and editor, acme gives text-oriented applications a clean, expressive, and consistent style of interaction. traditional window systems support interactive client programs and offer libraries of pre-defined operations such as pop-up menus and buttons to promote a consistent user interface among the clients. acme instead provides its clients with a fixed user interface and simple conventions to encourage its uniform use. clients access the facilities of acme through a file system interface; acme is in part a file server that exports device-like files that may be manipulated to access and control the contents of its windows. written in a concurrent programming language, acme is structured as a set of communicating processes that neatly subdivide the various aspects of its tasks: display management, input, file server, and so on. acme attaches distinct functions to the three mouse buttons: the left selects text; the middle executes textual commands; and the right combines context search and file opening functions to integrate the various applications and files in the system. acme works well enough to have developed a community that uses it exclusively. although acme discourages the traditional style of interaction based on typescript windows-- teletypes--its users find acme's other services render typescripts obsolete.
libckpt: transparent checkpointing under unix. checkpointing is a simple technique for rollback recovery: the state of an executing program is periodically saved to a disk file from which it can be recovered after a failure. while recent research has developed a collection of powerful techniques for minimizing the overhead of writing checkpoint files, checkpointing remains unavailable to most application developers. in this paper we describe libckpt, a portable checkpointing tool for unix that implements all applicable performance optimizations which are reported in the literature. while libckpt can be used in a mode which is almost totally transparent to the programmer, it also supports the incorporation of user directives into the creation of checkpoints. this user-directed checkpointing is an innovation which is unique to our work.
alternatives for detecting redundancy in storage systems data. storage systems frequently maintain identical copies of data. identifying such data can assist in the design of solutions in which data storage, transmission, and management are optimised. in this paper we evaluate three methods used to discover identical portions of data: whole file content hashing, fixed size blocking, and a chunking strategy that uses rabin fingerprints to delimit content-defined data chunks. we assess how effective each of these strategies is in finding identical sections of data. in our experiments, we analysed diverse data sets from a variety of different types of storage systems including a mirrored section of sunsite.org.uk, different data profiles in the file system infrastructure of the cambridge university computer laboratory, source code distribution trees, compressed data, and packed files. we report our experimental results and present a comparative analysis of these techniques. this study also shows how levels of similarity differ between data sets and file types. finally, we discuss the advantages and disadvantages in the application of these methods in the light of our experimental results.
open information pools. on the www it is not possible to supplement existing web pages of other people with new information or a link to that information, because the www does not have a standard method for write access. with write access, information can be added in the right context, which eases searching. we therefore define open information pools: a collection of www based databases with public write access. by using databases we add structure to the information. each database deals with a specific topic. we developed an architecture to support open information pools. important elements in the architecture are the rating and moderation tools. with these tools the user group is able to maintain and update the database and also to prevent errors and abuse. we conducted measurements on operational rating and moderation tools to show the validity of our idea. the study of slashdot.org's rating and moderation tools shows that insightful information is recognised after only 37 minutes. we implemented a prototype of a true open information pool containing music information. this database contains biographies, audio cd descriptions, audio cd cover pictures, lyrics of the songs with timing information, and midi files. we developed several tools to create, insert and search this database.
scalable network i/o in linux. recent highly publicized benchmarks have suggested that linux systems do not scale as well as other systems, such as windows nt, when used as network servers. windows nt contains features such as i/o completion ports that help boost network server performance and scalability. in this paper we focus on improving the linux implementation of poll() to reduce the expense of managing large numbers of network connections. we also explore the newer posix rt signal api that will help network servers scale into the next decade. a comparison between the two interfaces shows that a server using our /dev/poll interface scales better than a server using rt signals.
a future-adaptable password scheme. many authentication schemes depend on secret passwords. unfortunately, the length and randomness of user-chosen passwords remain fixed over time. in contrast, hardware improvements constantly give attackers increasing computational power. as a result, password schemes such as the traditional unix user-authentication system are failing with time. this paper discusses ways of building systems in which password security keeps up with hardware speeds. we formalize the properties desirable in a good password system, and show that the computational cost of any secure password scheme must increase as hardware improves. we present two algorithms with adaptable cost--eksblowfish, a block cipher with a purposefully expensive key schedule, and bcrypt, a related hash function. failing a major breakthrough in complexity theory, these algorithms should allow password-based systems to adapt to hardware improvements and remain secure well into the future.
a text retrieval package for the unix operating system. this paper describes lq-text, an inverted index text retrieval package written by the author. inverted index text retrieval provides a fast and effective way of searching large amounts of text. this is implemented by making an index to all of the natural-language words that occur in the text. the actual text remains unaltered in place, or, if desired, can be compressed or archived; the index allows rapid searching even if the data files have been altogether removed. the design and implementation of lq-text are discussed, and performance measurements are given for comparison with other text searching programs such as grep and agrep. the functionality provided is compared briefly with other packages such as glimpse and zbrowser. the lq-text package is available in source form, has been successfully integrated into a number of other systems and products, and is in use at over 100 sites.
cryptography in openbsd: an overview. cryptographic mechanisms are an important security component of an operating system in securing the system itself and its communication paths. indeed, in many situations, cryptography is the only tool that can solve a particular problem, e.g., network-level security. while cryptography by itself does not guarantee security, when applied correctly, it can significantly improve overall security. since one of the main foci of the openbsd system is security, various cryptographic mechanisms are employed in a number of different roles. this paper gives an overview of the cryptography employed in openbsd. we discuss the various components (ipsec, ssl libraries, stronger password encryption, kerberos iv, random number generators, etc.), their role in system security, and their interactions with the rest of the system (and, where applicable, the network).
trusted path execution for the linux 2.6 kernel as a linux security module. the prevention of damage caused to a system via malicious executables is a significant issue in the current state of security on linux operating systems. several approaches are available to solve such a problem at the application level of a system but very few are actually implemented into the kernel. the linux security module project was aimed at applying security to the linux kernel without imposing on the system. it performs this task by creating modules that could be loaded and unloaded onto the system on the fly and according to how the administrator would like to lock down their system. the trusted path execution (tpe) project was ported to the linux kernel as a linux security module (lsm) to create a barrier against such security issues from occurring. this paper will attempt to explain how trusted path execution is implemented in the linux kernel as an lsm. it will also describe how tpe can prevent the running of malicious code on a linux system via a strategically placed hook in the kernel. the usage of a pseudo-filesystem approach to creating an access control list for users on the system will also be discussed. the paper will further explain how tpe is designed and implemented in the kernel. this paper will show how the access control list is utilized by the module to place checks on the execution of code on the system along with a check of the path the code is being run in. further, the origins of the "trusted path" concept and its origination in the openbsd operating system will be discussed along with how tpe was introduced to the linux security community. the paper will conclude with a synopsis of the contents and future paths and goals of the project.
the new jersey machine-code toolkit. the new jersey machine-code toolkit helps programmers write applications that process machine code. applications that use the toolkit are written at an assembly-language level of abstraction, but they recognize and emit binary. guided by a short instruction-set specification, the toolkit generates all the bit-manipulating code. the toolkit's specification language uses four concepts: fields and tokens describe parts of instructions, patterns describe binary encodings of instructions or groups of instructions, and constructors map between the assembly-language and binary levels. these concepts are suitable for describing both cisc and risc machines; we have written specifications for the mips r3000, sparc, and intel 486 instruction sets. we have used the toolkit to help write two applications: a debugger and a linker. the toolkit generates efficient code; for example, the linker emits binary up to 15% faster than it emits assembly language, making it 1.7-2 times faster to produce an a.out directly than by using the assembler.
in-place rsync: file synchronization for mobile and wireless devices. the open-source rsync utility reduces the time and bandwidth required to update a file across a network. rsync uses an interactive protocol that detects changes in a file and sends only the changed data [18, 19]. we have modified rsync so that it operates on space constrained devices. files on the target host are updated in the same storage the current version of the file occupies. space-constrained devices cannot use traditional rsync because it requires memory or storage for both the old and new version of the file. examples include synchronizing files on cellular phones and handheld pcs, which have small memories. the in-place rsync algorithm encodes the compressed representation of a file in a graph, which is then topologically sorted to achieve the in-place property. we compare the performance of in-place rsync to rsync and conclude that in-place rsync degrades performance minimally.
resolving file conflicts in the ficus file system. ficus is a flexible replication facility with optimistic concurrency control designed to span a wide range of scales and network environments. optimistic concurrency control provides rapid local access and high availability of files for update in the face of disconnection, at the cost of occasional conflicts that are only discovered when the system is reconnected. ficus reliably detects all possible conflicts. many conflicts can be automatically resolved by recognizing the file type and understanding the file's semantics. this paper describes experiences with conflicts and automatic conflict resolution in ficus. it presents data on the frequency and character of conflicts in our environment. this paper also describes how semantically knowledgeable resolvers are designed and implemented, and discusses our experiences with their strengths and limitations. we conclude from our experience that optimistic concurrency works well in at least one realistic environment, conflicts are rare, and a large proportion of those conflicts that do occur can be automatically solved without human intervention.
virtual services: a new abstraction for server consolidation. modern server operating systems (os's) do not address the issue of interference between competing applications. this deficiency is a major road-block for internet and application service providers who want to multiplex server resources among their business clients. to insulate applications from each other, we introduce virtual services (vss). besides providing per-service resource budgets, vss drastically reduce cross-service interference in the presence of shared backend services, such as databases and name services. vss provide dynamic per-service resource partitioning and management in a manner completely transparent to applications. to accomplish this goal, we introduce a kernel-based work classification mechanism called gates. gates track work that propagates from one service to another and are configured by the system administrator via simple rules. they automate the binding of processes and sockets to vss, and ensure that any work done on behalf of a vs, even if it is done by shared services, is charged to the resource budget of the vs that requested it. using our experimental linux 2.0.36-based implementation we applied them effectively to co-hosted web servers. thus, nearly eliminating performance interference between the co-hosted sites.
a comparison of file system workloads. in this paper, we describe the collection and analysis of file system traces from a variety of different environments, including both unix and nt systems, clients and servers, and instructional and production systems. our goal is to understand how modern workloads affect the ability of file systems to provide high performance to users. because of the increasing gap between processor speed and disk latency, file system performance is largely determined by its disk behavior. therefore we primarily focus on the disk i/o aspects of the traces. we find that more processes access files via the memory-map interface than through the read interface. however, because many processes memory-map a small set of files, these files are likely to be cached. we also find that file access has a bimodal distribution pattern: some files are written repeatedly without being read; other files are almost exclusively read. we develop a new metric for measuring file lifetime that accounts for files that are never deleted. using this metric, we find that the average block lifetime for some workloads is significantly longer than the 30-second write delay used by many file systems. however, all workloads show lifetime locality: the same files tend to be overwritten multiple times.
permanent web publishing. lockss (lots of copies keep stuff safe) is a prototype of a system to preserve access to scientific journals published on the web. it is a majority-voting fault-tolerant system that, unlike normal systems, has far more replicas than would be required just to survive the anticipated failures. we are exploring techniques that exploit the surplus of replicas to permit a much looser form of coordination between them than conventional fault-tolerant technology would require.
making the "box" transparent: system call performance as a first-class result. for operating system intensive applications, the ability of designers to understand system call performance behavior is essential to achieving high performance. conventional performance tools, such as monitoring tools and profilers, collect and present their information off-line or via out-of-band channels. we believe that making this information first-class and exposing it to applications via in-band channels on a per-call basis presents opportunities for performance analysis and tuning not available via other mechanisms. furthermore, our approach provides direct feedback to applications on time spent in the kernel, resource contention, and time spent blocked, allowing them to immediately observe how their actions affect kernel behavior. not only does this approach provide greater transparency into the workings of the kernel, but it also allows applications to control how performance information is collected, filtered, and correlated with application-level events. to demonstrate the power of this approach, we show that our implementation, debox, obtains precise information about os behavior at low cost, and that it can be used in debugging and tuning application performance on complex workloads. in particular, we focus on the industry-standard specweb99 benchmark running on the flash web server. using debox, we are able to diagnose a series of problematic interactions between the server and the os. addressing these issues as well as other optimization opportunities generates an overall factor of four improvement in our specweb99 score, throughput gains on other benchmarks, and latency reductions ranging from a factor of 4 to 47.
design and implementation of a simulation library using lightweight processes. the \si/ lightweight-process based system for simulating process interactions is an enhancement to the c programming language in the form of library primitives with sets of predefined data structures. the \si/ system encapsulates an existing lightweight-process library to provide a discrete-event simulation environment supporting the process view. it was developed as a research testbed for investigating methods which support simulations efficiently. easy extensions and modifications to the \si/ system are a major design objective, accomplished through modularity and layering. this paper describes the system, our experiences with its implementation, and its applicability to simulation modeling. we report on performance measurements of different implementations of the simulation scheduler, and of different algorithms for simulating service disciplines.
afraid - a frequently redundant array of independent disks. disk arrays are commonly designed to ensure that stored data will always be able to withstand a disk failure, but meeting this goal comes at a significant cost in performance. we show that this is unnecessary. by trading away a fraction of the enormous reliability provided by disk arrays, it is possible to achieve performance that is almost as good as a non-parity-protected set of disks. in particular, our afraid design eliminates the small-update penalty that plagues traditional raid 5 disk arrays. it does this by applying the data update immediately, but delaying the parity update to the next quiet period between bursts of client activity. that is, afraid makes sure that the array is frequently redundant, even if it isn't always so. by regulating the parity update policy, afraid allows a smooth trade-off between performance and availability. under real-life workloads, the afraid design can provide close to the full performance of an array of unprotected disks, and data availability comparable to a traditional raid 5. our results show that afraid offers 42% better performance for only 10% less availability, 97% better for 23% less, and as much as a factor of 4.1 times better performance for giving up less than half raid 5's availability. we explore here the detailed availability and performance implications of the afraid approach.
transparent fault tolerance for parallel applications on networks of workstations. this paper describes a new method for providing transparent fault tolerance for parallel applications on a network of workstations. we have designed our method in the context of shared object system called sam, a portable run-time system which provides a global name space and automatic caching of shared data. sam incorporates a novel design intended to address the problem of the high communication overheads in distributed memory environments and is implemented on a variety of distributed memory platforms. our fundamental approach to providing fault tolerance is to ensure the replication of all data on more than one workstation using the dynamic caching already providedby sam. the replicated data is accessible to the local processor like other cached data, making access to shared data faster and potentially offsetting some of the fault tolerance overhead. in addition, our method uses information available in sam applications on how processes access shared data to enable several optimizations which reduce the fault-tolerance overhead. we have built an implementation of our fault-tolerance method in sam for heterogeneous networks of workstations running pvm3. in this paper, we present our fault-tolerance method and describe its implementation in detail. we give performance results and overhead numbers for several large sam applications running on a cluster of alpha workstations connected by an atm network. our method is successful in providing transparent fault tolerance for parallel applications running on a network of workstations and is unique in requiring no global synchronizations and no disk operations to a reliable file server.
lap: a little language for os emulation. lap, the linux application platform, is a linux emulation package for bsd/os which uses a "little language" [salu98] to describe transformations from linux data types and values to bsd/os data types and values, and vice versa. the little language simplifies and regularizes the specification of transformations, making the emulation easier to maintain. this paper describes the language and its place in the framework of lap.
an implementation of a log-structured file system for unix. research results [rose91] suggest that a log-structured file system (lfs) offers the potential for dramatically improved write performance, faster recovery time, and faster file creation and deletion than traditional unix file systems. this paper presents a redesign and implementation of the sprite [rose91] log-structured file system that is more robust and integrated into the vnode interface [klei86]. measurements show its performance to be superior to the 4bsd fast file system (ffs) in a variety of benchmarks and not significantly less than ffs in any test. unfortunately, an enhanced version of ffs (with read and write clustering) [mcvo91] provides comparable and sometimes superior performance to our lfs. however, lfs can be extended to provide additional functionality such as embedded transactions and versioning, not easily implemented in traditional file systems.
journaling versus soft updates: asynchronous meta-data protection in file systems. the unix fast file system (ffs) is probably the most widely-used file system for performance comparisons. however, such comparisons frequently overlook many of the performance enhancements that have been added over the past decade. in this paper, we explore the two most commonly used approaches for improving the performance of meta-data operations and recovery: journaling and soft updates. journaling systems use an auxiliary log to record meta-data operations and soft updates uses ordered writes to ensure metadata consistency. the commercial sector has moved en masse to journaling file systems, as evidenced by their presence on nearly every server platform available today: solaris, aix, digital unix, hp-ux, irix, and windows nt. on all but solaris, the default file system uses journaling. in the meantime, soft updates holds the promise of providing stronger reliability guarantees than journaling, with faster recovery and superior performance in certain boundary cases. in this paper, we explore the benefits of soft updates and journaling, comparing their behavior on both microbenchmarks and workload-based macrobenchmarks. we find that journaling alone is not sufficient to "solve" the meta-data update problem. if synchronous semantics are required (i.e., meta-data operations are durable once the system call returns), then the journaling systems cannot realize their full potential. only when this synchronicity requirement is relaxed can journaling systems approach the performance of systems like soft updates (which also relaxes this requirement). our asynchronous journaling and soft updates systems perform comparably in most cases. while soft updates excels in some meta-data intensive microbenchmarks, the macrobenchmark results are more ambiguous. in three cases soft updates and journaling are comparable. in a file intensive news workload, journaling prevails, and in a small isp workload, soft updates prevails.
file system logging versus clustering: a performance comparison. the log-structured file system (lfs), introduced in 1991 [8], has received much attention for its potential order-of-magnitude improvement in file system performance. early research results [9] showed that small file performance could scale with processor speed and that cleaning costs could be kept low, allowing lfs to write at an effective bandwidth of 62 to 83% of the maximum. later work showed that the presence of synchronous disk operations could degrade performance by as much as 62% and that cleaning overhead could become prohibitive in transaction processing workloads, reducing performance by as much as 40% [10]. the same work showed that the addition of clustered reads and writes in the berkeley fast file system [6] (ffs) made it competitive with lfs in large-file handling and software development environments as approximated by the andrew benchmark [4]. these seemingly inconsistent results have caused confusion in the file system research community. this paper presents a detailed performance comparison of the 4.4bsd log-structured file system and the 4.4bsd fast file system. ignoring cleaner overhead, our results show that the order-of-magnitude improvement in performance claimed for lfs applies only to meta-data intensive activities, specifically the creation of files one-kilobyte or less and deletion of files 64 kilobytes or less. for small files, both systems provide comparable read performance, but lfs offers superior performance on writes. for large files (one megabyte and larger), the performance of the two file systems is comparable. when ffs is tuned for writing, its large-file write performance is approximately 15% better than lfs, but its read performance is 25% worse. when ffs is optimized for reading, its large-file read and write performance is comparable to lfs. both lfs and ffs can suffer performance degradation, due to cleaning and disk fragmentation respectively. we find that active ffs file systems function at approximately 85-95% of their maximum performance after two to three years. we examine lfs cleaner performance in a transaction processing environment and find that cleaner overhead reduces lfs performance by more than 33% when the disk is 50% full.
ditools: application-level support for dynamic extension and flexible composition. today, operating systems set-up process images from executable files using fixed rules. programs are restricted to run in essentially the same environment at every execution. however, we believe that this behavior is not always convenient, and that many times it is interesting to make variations to the execution environment, either to introduce new functionality or to specialize critical services, even when their source code is not available. this problem can be mitigated through application-level extensibility and flexible composition of binary modules. in this paper, we describe ditools an application-level tool that supports dynamic interposition on dynamically-linked procedure-call boundaries. this tool enables both global and per-module dynamic interposition. we also present a detailed use of ditools and various short examples of extensions.
sendmail evolution: 8.10 and beyond. sendmailtm has been the de facto mail transfer agent implementation since the dawn of the internet. today, sendmail development is still driven by a continually changing set of network requirements and user demands. lately, two new driving forces have also contributed to sendmail development. first, as more open source mail transfer agents, such as exim and postfix, become available, a new friendly competition has developed in which the authors of the various mtas share their ideas via open source and help to advance open standards as opposed to advancing their own particular implementation. second, a new "hybrid" company, sendmail, inc., has been created to offer commercial versions of the open source software while continuing to fuel open source development. this paper will briefly discuss the evolution of sendmail; the influences which drive sendmail development; and how the creation of sendmail, inc. has contributed to the open source version. the paper will also describe the new features appearing in the next "functionality release" of open source sendmail. in particular, changes in queueing and new protocol support are discussed. finally, the authors will speculate on future directions for sendmail.
how xlib is implemented (and what we're doing about it). the x window system is the de facto standard graphical environment for linux and unix hosts, and is usable on nearly any class of computer one could find today. its success is partially due to its flexible, extensible design. unfortunately, as research proceeds on cutting-edge window system functionality, the brittleness of the underlying software is a critical impediment to progress. xlib, the client-side implementation of the network protocol that underlies x, is one source of these issues. many developers working on new features in the x protocol are discovering that xlib requires changes to support these features, but xlib makes those changes difficult. for more than 15 years, new features have been added to xlib by accretion, rather than with careful design. we discuss the implementation of xlib and analyze some specific difficulties in it that cause problems in understanding and maintaining this code base. we also present our current work on migrating the x window system to a more maintainable, carefully designed architecture.
sawmill: a high-bandwidth logging file system. this paper describes the implementation of sawmill, a network file system using the raid-ii storage system. sawmill takes advantage of the direct data path in raid-ii between the disks and the network, which bypasses the file server cpu. the key ideas in the implementation of sawmill are combining logging (lfs) with raid to obtain fast small writes, using new log layout techniques to improve bandwidth, and pipelining through the controller memory to reduce latency. the file system can currently read data at 21 mb/s and write data at 15 mb/s, close to the raw disk array bandwidth, while running on a relatively slow sun-4. performance measurements show that lfs improved performance of a stream of small writes by over a order of magnitude compared to writing directly to the raid, and this improvement would be even larger with a faster cpu. sawmill demonstrates that by using a storage system with a direct data path, a file system can provide data at bandwidths much higher than the file server itself could handle. however, processor speed is still an important factor, especially when handling many small requests in parallel.
why does file system prefetching work? most file systems attempt to predict which disk blocks will be needed in the near future and prefetch them into memory; this technique can improve application throughput as much as 50%. but why? the reasons include that the disk cache comes into play, the device driver amortizes the fixed cost of an i/o operation over a larger amount of data, total disk seek time can be decreased, and that programs can overlap computation and i/o. however, intuition does not tell us the relative benefit of each of these causes, or techniques for increasing the effectiveness of prefetching. to answer these questions, we constructed an analytic performance model for file system reads. the model is based on a 4.4bsd-derived file system, and parameterized by the access patterns of the files, layout of files on disk, and the design characteristics of the file system and of the underlying disk. we then validated the model against several simple workloads; the predictions of our model were typically within 4% of measured values, and differed at most by 9% from measured values. using the model and experiments, we explain why and when prefetching works, and make proposals for how to tune file system and disk parameters to improve overall system throughput.
deceit: a flexible distributed file system. deceit, a distributed file system being developed at cornell, focuses on flexible file semantics in relation to efficiency, scalability, and reliability. deceit servers are interchangeable and collectively provide the illusion of a single, large server machine to any clients of the deceit service. non-volatile replicas of each file are stored on a subset of the file servers. the user is able to set parameters on a file to achieve different levels of availability, performance, and one-copy serializability. deceit also supports a file version control mechanism. in contrast with many recent dfs efforts, deceit can behave like a plain sun network file system server and can be used by any nfs client without modifying any client software. the current deceit prototype uses the isis distributed programming environment for all communication and process group management, an approach that reduces system complexity and increases system robustness.
ubc: an efficient unified i/o and memory caching subsystem for netbsd. this paper introduces ubc ("unified buffer cache"), a design for unifying the filesystem and virtual memory caches of file data, thereby providing increased system performance. in this paper we discuss both the traditional bsd caching interfaces and new ubc interfaces, concentrating on the design decisions that were made as the design progressed. we also discuss the designs used by other operating systems to solve the same problems that ubc solves, with emphasis on the practical implications of the differences between these designs. this project is still in progress, and once completed will be part of a future release of netbsd.
network subsystems reloaded: a high-performance, defensible network subsystem. traditionally, operating systems have used monolithic network stack implementations: implementations where the whole network stack executes in the kernel or (in microkernels) in a single, trusted, user level server. code maintenance issues, ease of debugging, need for simultaneous existence of multiple protocols, and security benefit have argued for removing the networking implementation from kernel and dividing it into multiple user level protection domains. previous attempts to do so have failed to deliver adequate performance. given the advances made in both hardware (cpu, memory, nic) and micro-kernel design over the last decade, it is now appropriate to re-evaluate how these re-factored implementations perform, and to examine the reasons for earlier failures in greater detail. building on the primitives of the eros microkernel, we have implemented two network subsystems: one a conventional, user mode, monolithic design and the other a domain-factored user level networking stack that restructures the network subsystem into several protection domains. we show that the restructuring maintains performance very close to that of the monolithic design, and that both designs compare favorably to a conventional in-kernel implementation. we discuss the issues faced in engineering the domain-factored implementation to achieve high performance, and present the quantitative evaluation of the resulting network subsystems.
a comparison of os extension technologies. the current trend in operating systems research is to allow applications to dynamically extend the kernel to improve application performance or extend functionality, but the most effective approach to extensibility remains unclear. some systems use safe languages to permit code to be downloaded directly into the kernel; other systems provide in-kernel interpreters to execute extension code; still others use software techniques to ensure the safety of kernel extensions. the key characteristics that distinguish these systems are the philosophy behind extensibility and the technology used to implement extensibility. this paper presents a taxonomy of the types of extensions that might be desirable in an extensible operating system, evaluates the performance cost of various extension technologies currently being employed, and compares the cost of adding a kernel extension to the benefit of having the extension in the kernel. our results show that compiled technologies (e.g. modula-3 and software fault isolation) are good candidates for implementing general-purpose kernel extensions, but that the overhead of interpreted languages is sufficiently high that they are inappropriate for this use.
performing replacement in modem pools. we examine a policy for managing modem pools that disconnects users only if not enough modems are available for other users to connect. managing the modem pool then becomes a replacement problem, similar to buffer cache management (e.g., in virtual memory systems). when a new connection request is received, the system needs to find a user to "replace". in this paper we examine such demand-disconnect schemes using extensive activity data from actual isps. we discuss various replacement policies and propose cirg: a novel replacement algorithm that is well suited for modem pools. in general, the choice of algorithm is significant. a naive algorithm (e.g., one that randomly replaces any user who has been inactive for a while) incurs many tens of percent more "faults" (i.e., disconnections of users who are likely to want to be active again soon) than the lru algorithm, which, in turn, incurs 10% more faults than cirg. for good replacement algorithms, the impact can be significant in terms of resource requirements. we show that the same standards of service as a system that does not disconnect idle users can be achieved with up to 13% fewer modems.
a comparison of ffs disk allocation policies. the 4.4bsd file system includes a new algorithm for allocating disk blocks to files. the goal of this algorithm is to improve file clustering, increasing the amount of sequential i/o when reading or writing files, thereby improving file system performance. in this paper we study the effectiveness of this algorithm at reducing file system fragmentation. we have created a program that artificially ages a file system by replaying a workload similar to that experienced by a real file system. we used this program to evaluate the effectiveness of the new disk allocation algorithm by replaying ten months of activity on two file systems that differed only in the disk allocation algorithms that they used. at the end of the ten month simulation, the file system using the new allocation algorithm had approximately half the fragmentation of a similarly aged file system that used the traditional disk allocation algorithm. measuring the performance difference between the two file systems by reading and writing the same set of files on the two systems showed that this decrease in fragmentation improved file write throughput by 20% and read throughput by 32%. in certain test cases, the new allocation algorithm provided a performance improvement of greater than 50%.
a usage profile and evaluation of a wide-area distributed file system. the evolution of the andrew file system (afs) into a wide-area distributed file system has encouraged collaboration and information dissemination on a much broader scale than ever before. in this paper, we examine afs as a provider of wide-area file services to over 80 organizations around the world. we discuss usage characteristics of afs derived from empirical measurements of the system, and from user responses to a questionnaire. our observations indicate that afs provides robust and efficient data access in its current configuration, thus confirming its viability as a design point for wide-area distributed file systems.
outwit: unix tool-based programming meets the windows world. the ubiquity of windows-based desktop environments has not been matched by a corresponding emergence of tools supporting the unix tool composition paradigm. outwit is a suite of tools based on the unix tool design principles allowing the processing of windows application data with sophisticated data manipulation pipelines. the outwit tools offer access to the windows clipboard, the registry, relational databases, document properties, and shell links. we demonstrate a number of applications of the outwit tools used in conjuction with existing unix commands, and discuss future directions of our work.
wux: unix tools under windows. wux is a port of unix tools to the microsoft windows environment. it is based on a library providing a unix-compatible set of system calls on top of windows. unix-derived tools run in parallel, communicating using the unix pipe abstraction. all processes are run within an application template that gives them basic windows compatibility such as input and output windows and an icon. the performance of the system is comparable to that of unix ports to the pc architecture.
flashback: a lightweight extension for rollback and deterministic replay for software debugging. software robustness has significant impact on system availability. unfortunately, finding software bugs is a very challenging task because many bugs are hard to reproduce. while debugging a program, it would be very useful to rollback a crashed program to a previous execution point and deterministically re-execute the "buggy" code region. however, most previous work on rollback and replay support was designed to survive hardware or operating system failures, and is therefore too heavyweight for the fine-grained rollback and replay needed for software debugging. this paper presents flashback, a lightweight os extension that provides fine-grained rollback and replay to help debug software. flashback uses shadow processes to efficiently roll back in-memory state of a process, and logs a process' interactions with the system to support deterministic replay. both shadow processes and logging of system calls are implemented in a lightweight fashion specifically designed for the purpose of software debugging. we have implemented a prototype of flashback in the linux operating system. our experimental results with micro-benchmarks and real applications show that flashback adds little overhead and can quickly roll back a debugged program to a previous execution point and deterministically replay from that point.
sbox: put cgi scripts in a box. sbox is a cgi wrapper script that allows web sites to safely grant cgi authoring privileges to untrusted or naive authors. the script increases security in several ways. it changes the process privileges of cgi scripts to match their owners, preventing one script from interfering with another's data files or operations. it establishes configurable ceilings on script resource usage, avoiding intentional or unintentional denial of service attacks. most importantly, sbox can also be used to run untrusted cgi scripts within a chroot()-ed directory, thereby preventing cgi scripts from accessing sensitive portions of the file system. sbox can be used and redistributed freely. the complete package is available for download at http://stein.cshl.org/www/software/sbox/
splicing unix into a genome mapping laboratory. the whitehead institute/mit center for genome research is responsible for a number of large genome mapping efforts, the scale of which create problems of data and workflow management that dictate reliance on computer support. two years ago, when we started to design the informatics support for the laboratory, we realized that the fluid and ever-changing nature of the experimental protocols precluded any effort to create a single monolithic piece of software. instead we designed a system that relied on multiple distributed data analysis and processing tools knit together by a centralized database. the obvious choice of operating systems was unix. in order to make this choice palatable to the laboratory biologists--who rightly consider it their job to do experiments rather than to interact with computers, and who have come to expect all software to be as intuitive and responsive as the apple macintoshes on their desks--we designed a system that runs automatically and essentially invisibly. whenever it is necessary for the informatics system to interact with a member of the laboratory we have carefully chosen a user interface paradigm that best balances the user's expectations against the system's capabilities. when possible we have chosen to adapt familiar software to our user interface needs rather than to write user interfaces from scratch. we've managed to hide the power of unix behind the innocuous personal computer-based front ends our users know and love, using techniques that should be applicable in other environments as well.
portals in 4.4bsd. portals were added to 4.4bsd as an experimental feature and are in the publicly available 4.4bsd-lite distribution. portals provide access to alternate file types or devices using names in the normal filesystem that a process just opens. for example, an open of /p/tcp/foo.com/smtp returns a tcp socket descriptor to the calling process that is connected to the smtp server on the specified host. by providing access through the normal filesystem, the calling process need not be aware of the special functions necessary to create a tcp socket and establish a tcp connection. this makes tcp connections, for example, available to programs such as awk, tcl, and shell scripts. this paper describes the implementation of portals in 4.4bsd as another type of filesystem and provides some examples.
mach-us: unix on generic os object servers. this paper examines the mach-us operating system, its unique architecture, and the lessons demonstrated through its implementation. mach-us is an object-oriented multi-server os which runs on the mach3.0 kernel. mach-us has a set of separate servers supplying orthogonal os services and a library which is loaded into each user process. this library uses the services to generate the semantics of the mach2.5/4.3bsd application programmers interface (api). this architecture makes mach-us a flexible research platform and a powerful tool for developing and examining various os service options. we will briefly describe mach-us, the motivations for its design choices, and its demonstrated strengths and weaknesses. we will then discuss the insights that we've acquired in the areas of multi-server architecture, os remote method invocation, object oriented technology for os implementation, api independent os services, unix api re-implementation, and smart user-space api emulation libraries.
dmfs-a data migration file system for netbsd. i have recently developed dmfs, a data migration file system, for netbsd[1]. this file system provides kernel support for the data migration system being developed by my research group at nasa/ames. the file system utilizes an underlying file store to provide the file backing, and coordinates user and system access to the files. it stores its internal metadata in a flat file, which resides on a separate file system. this paper will first describe our data migration system to provide a context for dmfs, then it will describe dmfs. i also will describe the changes to netbsd needed to make dmfs work. then i will give an overview of the file archival and restoration procedures, and describe how some typical user actions are modified by dmfs. lastly, i will present simple performance measurements which indicate that there is little performance loss due to the use of the dmfs layer.
isolation with flexibility: a resource management framework for central servers. proportional-share resource management is becoming increasingly important in today's computing environments. in particular, the growing use of the computational resources of central service providers argues for a proportional-share approach that allows resource principals to obtain allocations that reflect their relative importance. in such environments, resource principals must be isolated from one another to prevent the activities of one principal from impinging on the resource rights of others. however, such isolation limits the flexibility with which resource allocations can be modified to reflect the actual needs of applications. we present extensions to the lottery-scheduling resource management framework that increase its flexibility while preserving its ability to provide secure isolation. to demonstrate how this extended framework safely overcomes the limits imposed by existing proportional-share schemes, we have implemented a prototype system that uses the framework to manage cpu time, physical memory, and disk bandwidth. we present the results of experiments that evaluate the prototype, and we show that our framework has the potential to enable server applications to achieve significant gains in performance.
scalability in the xfs file system. in this paper we describe the architecture and design of a new file system, xfs, for silicon graphics' irix operating system. it is a general purpose file system for use on both workstations and servers. the focus of the paper is on the mechanisms used by xfs to scale capacity and performance in supporting very large file systems. the large file system support includes mechanisms for managing large files, large numbers of files, large directories, and very high performance i/o. in discussing the mechanisms used for scalability we include both descriptions of the xfs on-disk data structures and analyses of why they were chosen. we discuss in detail our use of b+ trees in place of many of the more traditional linear file system structures. xfs has been shipping to customers since december of 1994 in a version of irix 5.3, and we are continuing to improve its performance and add features in upcoming releases. we include performance results from running on the latest version of xfs to demonstrate the viability of our design.
turning the aix operating system into an mp-capable os. this paper describes those mp features that bull and ibm together introduced into the aix operating system to support the symmetric multiprocessor machine marketed by bull under the escala name and by ibm under the rs/6000 models g30, j30 and r30 names. the powerpc architecture and the aix operating system present some specific challenges. we present the major problems encountered and how they were solved.
time-based fairness improves performance in multi-rate wlans. the performance seen by individual clients on a wireless local area network (wlan) is heavily influenced by the manner in which wireless channel capacity is allocated. the popular mac protocol dcf (distributed coordination function) used in 802.11 networks provides equal long-term transmission opportunities to competing nodes when all nodes experience similar channel conditions. when similar-sized packets are also used, dcf leads to equal achieved throughputs (throughput-based fairness) among contending nodes. because of varying indoor channel conditions, the 802.11 standard supports multiple data transmission rates to exploit the trade-off between data rate and bit error rate. this leads to considerable rate diversity, particularly when the network is congested. under such conditions, throughput-based fairness can lead to drastically reduced aggregate throughput. in this paper, we argue the advantages of time-based fairness, in which each competing node receives an equal share of the wireless channel occupancy time. we demonstrate that this notion of fairness can lead to significant improvements in aggregate performance while still guaranteeing that no node receives worse channel access than it would in a single-rate wlan. we also describe our algorithm, tbr (time-based regulator), which runs on the ap and works with any mac protocol to provide time-based fairness by regulating packets. through experiments, we show that our practical and backward compatible implementation of tbr in conjunction with an existing implementation of dcf achieves time-based fairness.
role classification of hosts within enterprise networks based on connection patterns. role classification involves grouping hosts into related roles. it exposes the logical structure of a network, simplifies network management tasks such as policy checking and network segmentation, and can be used to improve the accuracy of network monitoring and analysis algorithms such as intrusion detection. this paper defines the role classification problem and introduces two practical algorithms that group hosts based on observed connection patterns while dealing with changes in these patterns over time. the algorithms have been implemented in a commercial network monitoring and analysis product for enterprise networks. results from grouping two enterprise networks show that the number of groups identified by our algorithms can be two orders of magnitude smaller than the number of hosts and that the way our algorithms group hosts highly reflect the logical structure of the networks.
simple continuous media storage server on real-time mach. this paper presents the design and implementation of a simple continuous media storage server: cras on real-time mach. cras is a specially optimized storage system for retrieving multiple continuous media streams such as audio and video from a disk at constant rates for small scale distributed multimedia systems. many previous continuous media storage servers have focussed on high throughput for supporting as many video sessions as possible. however, these servers are too big and complicated for playback applications that retrieve continuous media data from the local disks of personal computers. also, there are many continuous media systems requiring small continuous media storage servers that can be shared by a small number of applications. to reduce hardware costs, the servers should run on less powerful computers. this means that the previous big and complicated servers are not appropriate for such small scale environments. we show that our simple continuous media server for small scale systems can guarantee the retrieval of continuous media data at a constant rate, and provide high throughput even though it is compact and simple.
x through the firewall, and other application relay. organizations often impose an administrative security policy when they connect to other organizations on a public network such as the internet. many applications have their own notions of security, or they simply rely on the security of the underlying protocols. using the x window system as a case study, we describe some techniques for building application-specific relays that allow the use of applications across organizational boundaries. in particular, we focus on analyzing administrative and application-specific security policies to construct solutions that satisfy the security requirements while providing the necessary functions of the applications.
email prioritization: reducing delays on legitimate mail caused by junk mail. in recent years the volume of junk email (spam, virus etc.) has increased dramatically. these unwanted messages clutter up users' mailboxes, consume server resources, and cause delays to the delivery of mail. this paper presents an approach that ensures that nonjunk mail is delivered without excessive delay, at the expense of delaying junk mail. using data from two internet-facing mail servers, we show how it is possible to simply and accurately predict whether the next message sent from a particular server will be good or junk, by monitoring the types of messages previously sent. the prediction can be used to delay acceptance of junk mail, and prioritize good mail through the mail server, ensuring that loading is reduced and delays are low, even if the server is overloaded. the paper includes a review of server-based anti-spam techniques, and an evaluation of these against the data. we develop and calibrate a model of mail server performance, and use it to predict the performance of the prioritization scheme. we also describe an implementation on a standard mail server.
phonestation, moving the telephone onto the virtual desktop. phonestation is a system that provides a sun microsystems sparcstation with complete control over an ordinary telephone line. it consists of a telephone line interface unit with loop control and touch tone detection, a suite of supporting software libraries that include digital signal processing for call progress monitoring, text-to-speech conversion, telephone line control, and phonescript, a high level procedural language that uses tcl for building interactive based application.
metadata logging in an nfs server. over the last few years, there have been several efforts to use logging to improve performance, reliability, and recovery times of file systems. the two major techniques are metadata logging, where the log records metadata changes and is a supplement to the on-disk file system, and log-structured file systems, whose log is their only on-disk representation. when the file system is mainly or wholly accessed through the network file system (nfs) protocol, it adds new considerations to the suitability of the logging technique. nfs requires that all operations be updated to stable storage before returning. as a result, file system implementations that were effective for local access may perform poorly on an nfs server. this paper analyzes the issues regarding the use of logging on an nfs server, and describes an implementation of a bsd fast file system (ffs) with metadata logging that performs effectively for a dedicated nfs server.
web++: a system for fast and reliable web service. we describe the design of a system for a fast and reliable http service termed web++. web++ achieves high reliability by dynamically replicating web data among multiple web servers. web++ selects a server which is available and that is expected to provide the fastest response time. furthermore, web++ guarantees data delivery, provided that at least one server containing the requested data is available. after detecting a server failure, web++ client requests are satisfied transparently to the client by another server. web++ is built on top of the standard http protocol and does not require any changes either in existing web browsers, or the installation of any software on the client side. we implement a web++ prototype; performance experiments indicate that web++ improves the client response time on average by 36.6%, and in many cases by as much as 59%, when compared with the current web performance.
implementing real time packet forwarding policies using streams. this paper describes an implementation of the class based queueing (cbq) mechanisms proposed by sally floyd and van jacobson to provide real time policies for packet forwarding. cbq allows the traffic flows sharing a data link to be guaranteed a share of the bandwidth when the link is congested, yet allows flexible sharing of the unused bandwidth when the link is unloaded. in addition, cbq provides mechanisms which give flows requiring low delay priority over other flows. in this way, links can be shared by multiple flows yet still meet the policy and quality of service (qos) requirements of the flows. we present a brief description of the implementation and some preliminary preformance measurements. the problems of packet classification are addressed in a flexible and extensible, yet efficient manner, and whilst the streams implementation cannot cope with very high speed interfaces, it can cope with the serial link speeds that are likely to be loaded.
events in an rpc based distributed system. we show how to build a distributed system allowing objects to register interest in and receive notifications of events in other objects. the system is built on top of a pair of interfaces that are interesting only in their extreme simplicity. we then present a simple and efficient implementation of these interfaces. we then show how more complex functionality can be introduced to the system by adding third-party services. these services can be added without changing the simple interfaces, and without changing the objects in the system that do not need the functionality of those services. finally, we note a number of open issues that remain, and attempt to draw some conclusions based on the work.
reliability and security in the codeen content distribution network. with the advent of large-scale, wide-area networking testbeds, researchers can deploy long-running distributed services that interact with other resources on the web. the codeen content distribution network, deployed on planetlab, uses a network of caching web proxy servers to intelligently distribute and cache requests from a potentially large client population. we have been running this system nearly continuously since june 2003, allowing open access from any client in the world. in that time, it has become the most heavily-used long-running service on planetlab, handling over four million accesses per day. in this paper, we discuss the design of our system, focusing on the reliability and security mechanisms that have kept the service in operation. our reliability mechanisms assess node health, preventing failing nodes from disrupting the operation of the overall system. our security mechanisms protect nodes from being exploited and from being implicated in malicious activities, problems that commonly plague other open proxies. we believe that future services, especially peer-to-peer systems, will require similar mechanisms as more services are deployed on non-dedicated distributed systems, and as their interaction with existing protocols and systems increases. our experiences with codeen and our data on its availability should serve as an important starting point for designers of future systems.
gnu mailman, internationalized. gnu mailman is a mailing list management system that has been in production use since 1998. in december 2002, a version 2.1 was released containing many new features. this paper will describe one of the most important - mailman 2.1's internationalization support. presented here are the tools that were built and the approaches mailman took to marking and translating text, as well a review of some of the benefits and pitfalls of mailman's solution. also presented will be some future directions for internationalized mailman, as well as other complex python applications such as zope.
the case for compressed caching in virtual memory systems. compressed caching uses part of the available ram to hold pages in compressed form, effectively adding a new level to the virtual memory hierarchy. this level attempts to bridge the huge performance gap between normal (uncompressed) ram and disk. unfortunately, previous studies did not show a consistent benefit from the use of compressed virtual memory. in this study, we show that technology trends favor compressed virtual memory--it is attractive now, offering reduction of paging costs of several tens of percent, and it will be increasingly attractive as cpu speeds increase faster than disk speeds. two of the elements of our approach are innovative. first, we introduce novel compression algorithms suited to compressing in-memory data representations. these algorithms are competitive with more mature ziv-lempel compressors, and complement them. second, we adaptively determine how much memory (if at all) should be compressed by keeping track of recent program behavior. this solves the problem of different programs, or phases within the same program, performing best for different amounts of compressed memory.
laddis: the next generation in nfs file server benchmarking. the ability to compare the performance of various nfs(1) file server configurations from several vendors is critically important to a computing facility when selecting an nfs file server. to date, nhfsstone(2) has been a popular means of characterizing nfs file server performance. however, several deficiencies have been found in nhfsstone. the laddis nfs file server benchmark has been developed to resolve nhfsstone's shortcomings and provide new functionality. the standard performance evaluation corporation (spec(3)) released the system file server (sfs) release 1.0 benchmark suite, which contains 097.laddis, as an industry-standard nfs file server benchmark in april 1993. this paper describes the major technical issues involved in developing the benchmark and the rationale used to establish default 097.laddis workload parameter values. where appropriate, areas for further research are identified and encouraged.
latency analysis of tcp on an atm network. in this paper we characterize the latency of the bsd 4.4 alpha implementation of tcp on an atm network. latency reduction is a difficult task, and careful analysis is the first step towards reduction. we investigate the impact of both the network controller and the protocol implementation on latency. we find that a low latency network controller has a significant impact on the overall latency of tcp. we also characterize the impact on latency of some widely discussed improvements to tcp, such as header prediction and the combination of the checksum calculation with data copying.
operating system support for multi-user, remote, graphical interaction. the emergence of thin client computing and multi-user, remote, graphical interaction revives a range of operating system research issues long dormant, and introduces new directions as well. this paper investigates the effect of operating system design and implementation on the performance of thin client service and interactive applications. we contend that the key performance metric for this type of system and its applications is user-perceived latency and we give a structured approach for investigating operating system design with this criterion in mind. in particular, we apply our approach to a quantitative comparison and analysis of windows nt, terminal server edition (tse), and linux with the x windows system, two popular implementations of thin client service. we find that the processor and memory scheduling algorithms in both operating systems are not tuned for thin client service. under heavy cpu and memory load, we observed user-perceived latencies up to 100 times beyond the threshold of human perception. even in the idle state, these systems induce unnecessary latency. tse performs particularly poorly despite scheduler modifications to improve interactive responsiveness. we also show that tse's network protocol outperforms x by up to six times, and also makes use of a bitmap cache which is essential for handling dynamic elements of modern user interfaces and can reduce network load in these cases by up to 2000%.
snp: an interface for secure network programming. snp provides a high-level abstraction for secure end-to-end network communications. it supports both stream and datagram semantics with security guarantees (e.g., data origin authenticity, data integrity and data confidentiality). it is designed to resemble the berkeley sockets interface so that security can be easily retrofitted into existing socket programs with only minor modifications. snp is built on top of gss-api, thus making it relatively portable across different authentication mechanisms conforming to gss-api. snp hides the details of gss-api (e.g., credentials and contexts management), the communication sublayer as well as the cryptographic sublayer from the application programmers. it also encapsulates security sensitive information, thus preventing accidental or intentional disclosure by an application program.
measuring and characterizing system behavior using kernel-level event logging. analyzing the dynamic behavior and performance of complex software systems is diffcult. currently available systems either analyze each process in isolation, only provide system level cumulative statistics, or provide a fixed and limited number of process group related statistics. the linux trace toolkit (ltt) introduced here provides a novel, modular, and extensible way of recording and analyzing complete system behavior. because all significant system events are recorded, it is possible to analyze any desired subset of the running processes, and for instance distinguish between the time spent waiting for some relevant event (data from disk or another process) versus time spent waiting for some unrelated process to use up its time slice. despite the extensive information gathered, experimental results show that the ltt time and memory overhead is minimal (< 2:5% when observing core kernel events). moreover, due to the ltt and linux kernel modularity and open source code availability, the system is easily extended both in terms of system events gathered, and of later post-processing and graphical presentation.
sift - a tool for wide-area information dissemination. the dissemination model is becoming increasingly important in wide-area information system. in this model, the user subscribes to an information dissemination service by submitting profiles that describe his interests. he then passively receives new, filtered information. the stanford information filtering tool (sift) is a tool to help provide such service. it supports full-text filtering using well-known information retrieval models. the sift filtering engine implements novel indexing techniques, capable of processing large volumes of information against a large number of profiles. it runs on several major unix platforms and is freely available to the public. in this paper we present sift's approach to user interest modeling and user-server communication. we demonstrate the processing capability of sift by describing a running server that disseminates usenet news. we present an empirical study of sift's performance, examining its main memory requirement and ability to scale with information volume and user population.
clue tables: a distributed, dynamic-binding naming mechanism. this paper presents a distributed, dynamic naming mechanism called clue tables for building highly scalable, highly available distributed file systems. the clue tables naming mechanism is distinctive in three aspects. first, it is designed to cope well with the hierarchical structure of the modern large-scale computer networks. second, it implicitlycarries out load balancing among servers to improve systemscalability. third, it supports file replication and dynamically designates a primary copy to resolve possible data inconsistency. this paper also reports a performance evaluation of the clue tables mechanism when compared with nfs, a popular distributed file system.
anonymous rpc: low-latency protection in a 64-bit address space. in this paper, we propose a method of reducing the latency of cross-domain remote procedure call (rpc). traditional systems use separate address spaces to provide memory protection between separate processes, but even with a highly optimized rpc system, the cost of switching between address spaces can make cross-domain rpc prohibitively expensive. our approach is to use anonymity instead of hardware page tables for protection. logically independent memory segments are placed at random locations in the same address space and protection domain. with 64-bit virtual addresses, it is unlikely that a process will be able to locate any other segment by accidental or malicious memory probes; it is impossible to corrupt a segment without knowing its location. the benefit is that a cross-domain rpc need not involve a hardware context switch. measurements of our prototype implementation show that a round-trip null rpc takes only 7.7us on an intel 486-33.
efficient packet demultiplexing for multiple endpoints and large messages. this paper describes a new packet filter mechanism that efficiently dispatches incoming network packets to one of multiple endpoints, for example address spaces. earlier packet filter systems iteratively applied each installed filter against every incoming packet, resulting in high processing overhead whenever multiple filters existed. our new packet filter provides an associative match function that enables similar but not identical filters to be combined together into a single filter. the filter mechanism, which we call the mach packet filter (mpf), has been implemented for the mach 3.0 operating system and is being used to support endpoint-based protocol processing, whereby each address space implements its own suite of network protocols. with large numbers of registered endpoints, mpf outperforms the earlier bsd packet filter (bpf) by over a factor of four. mpf also allows a filter program to dispatch fragmented packets, which was quite difficult with previous filter mechanisms.
extending file systems using stackable templates. extending file system functionality is not a new idea, but a desirable one nonetheless[6, 14, 18]. in the several years since stackable file systems were first proposed, only a handful are in use[12, 19]. impediments to writing new file systems include the complexity of operating systems, the difficulty of writing kernel-based code, the lack of a true stackable vnode interface[14], and the challenges of porting one file system to another operating system. we advocate writing new stackable file systems as kernel modules. as a starting point, we propose a portable, stackable template file system we call wrapfs (wrapper file system). wrapfs is a canonical, minimal stackable file system that can be used as a pattern across a wide range of operating systems and file systems. given wrapfs, developers can add or modify only that which is necessary to achieve the desired functionality. wrapfs takes care of the rest, and frees developers from the details of operating systems. wrapfs templates exist for several common operating systems (solaris, linux, and freebsd), thus alleviating portability concerns. wrapfs can be ported to any operating system with a vnode interface that provides a private data pointer for each data structure used in the interface. the overhead imposed by wrapfs is only 5-7%. this paper describes the design and implementation of wrapfs, explores portability issues, and shows how the implementation was achieved without changing client file systems or operating systems. we discuss several examples of file systems written using wrapfs.
discovery and hot replacement of replicated read-only file systems, with application to mobile computing. we describe a mechanism for replacing files, including open files, of a read-only file system while the file system remains mounted; the act of replacement is transparent to the user. such a "hot replacement" mechanism can improve fault-tolerance, performance, or both. our mechanism monitors, from the client side, the latency of operations directed at each file system. when latency degrades, the client automatically seeks a replacement file system that is equivalent to but hopefully faster than the current file system. the files in the replacement file system then take the place of those in the current file system. this work has particular relevance to mobile computers, which in some cases might move over a wide area. wide area movement can be expected to lead to highly variable response time, and give rise to three sorts of problems: increased latency, increased failures, and decreased scalability. if a mobile client moves through regions having partial replicas of common file systems, then the mobile client can depend on our mechanism to provide increased fault tolerance and more uniform performance.
fist: a language for stackable file systems. traditional file system development is difficult. stackable file systems promise to ease the development of file systems by offering a mechanism for incremental development. unfortunately, existing methods often require writing complex low-level kernel code that is specific to a single operating system platform and also difficult to port. we propose a new language, fist, to describe stackable file systems. fist uses operations common to file system interfaces. from a single description, fist's compiler produces file system modules for multiple platforms. the generated code handles many kernel details, freeing developers to concentrate on the main issues of their file systems. this paper describes the design, implementation, and evaluation of fist. we extended file system functionality in a portable way without changing existing kernels. we built several file systems using fist on solaris, freebsd, and linux. our experiences with these examples shows the following benefits of fist: average code size over other stackable file systems is reduced ten × average development time is reduced seven × performance overhead of stacking is 1-2%.
a new approach to distributed memory management in the mach microkernel. in this paper we describe a new approach towards extending mach virtual memory semantics across the node boundaries of a multicomputer system. at its core, the advanced shared virtual memory (asvm) system employs algorithms from the realm of shared virtual memory that were adapted and extended to create a system that is efficient and scalable and supports full vm semantics, paging between node memories and efficient execution of svm applications. our performance measurements demonstrate asvm's superior efficiency and scalability compared to its predecessor, the extended memory manager (xmm) that is part of the mach kernel's norma distribution.
currentcy: a unifying abstraction for expressing energy management policies. the global nature of energy creates challenges and opportunities for developing operating system policies to effectively manage energy consumption in battery-powered mobile/wireless devices. the proposed currentcy model creates the framework for the operating system to manage energy as a first-class resource. furthermore, currentcy provides a powerful mechanism to formulate energy goals and to unify resource management policies across diverse competing applications and spanning device components with very different power characteristics. this paper explores the ability of the currentcy model to capture more complex interactions and to express more mature energy goals than previously considered. we carry out this exploration in ecosystem, an "energy-centric" linux-based operating system. we extend ecosystem to address four new goals: 1) reducing residual battery capacity at the end of the targeted battery lifetime when it is no longer required (e.g., recharging is available), 2) dynamic tracking of the energy needs of competing applications for more effective energy sharing, 3) reducing response time variation caused by limited energy availability, and 4) energy efficient disk management. our results show that the currentcy model can express complex energy-related goals and behaviors, leading to more effective, unified management policies than those that develop from per-device approaches.
a transport layer approach for improving end-to-end performance and robustness using redundant paths. recent work on internet measurement and overlay networks has shown that redundant paths are common between pairs of hosts and that one can often achieve better end-to-end performance by adaptively choosing an alternate path [8, 28]. in this paper, we propose an end-to-end transport layer protocol, mtcp, which can aggregate the available bandwidth of those redundant paths in parallel. by striping one flow's packets across multiple paths, mtcp can not only obtain higher end-to-end throughput but also become more robust under path failures. when some paths fail, mtcp can continue sending packets on other living paths and the recovery process normally takes only a few seconds. because mtcp could obtain an unfair share of bandwidth under shared congestion, we integrate a shared congestion detection mechanism into our system. it allows us to dynamically detect and suppress paths with shared congestion so as to alleviate the aggressiveness problem. mtcp can also passively monitor the performance of several paths in parallel and discover better paths than the path provided by the underlying routing infrastructure. we also propose a heuristic to find disjoint paths between pairs of nodes using traceroute. we have implemented our system on top of overlay networks and evaluated it in both planet-lab and emulab.
hyper-threading aware process scheduling heuristics. intel corporation's "hyper-threading technology" is the first commercial implementation of simultaneous multithreading. hyper-threading allows a single physical processor to execute two heavyweight threads (processes) at the same time, dynamically sharing processor resources. this dynamic sharing of resources, particularly caches, causes a wide variety of inter-thread behaviour. threads competing for the same resource can experience a low combined throughput. hyper-threads are abstracted by the hardware as logical processors. current generation operating systems are aware of the logical-physical processor hierarchy and are able to perform simple load-balancing. however, the particular resource requirements of the individual threads are not taken into account and sub-optimal schedules can arise and remain undetected. we present a method to incorporate knowledge of per-thread hyper-threading performance into a commodity scheduler through the use of hardware performance counters and the modification of dynamic priority.
implementing transparent shared memory on clusters using virtual machines. shared memory systems, such as smp and ccnuma topologies, simplify programming and administration. on the other hand, clusters of individual workstations are commonly used due to cost and scalability considerations. we have developed a virtual-machine-based solution, dubbed vnuma, that seeks to provide a numa-like environment on a commodity cluster, with a single operating system instance and transparent shared memory. in this paper we present the design of vnuma and some preliminary evaluation.
slinky: static linking reloaded. static linking has many advantages over dynamic linking. it is simple to understand, implement, and use. it ensures that an executable is self-contained and does not depend on a particular set of libraries during execution. as a consequence, the user executes exactly the same executable image as was tested by the developer, diminishing the risk that the user's environment will affect correct behavior. the major disadvantages of static linking are increases in the memory required to run an executable, network bandwidth to transfer it, and disk space to store it. in this paper we describe the slinky system that uses digest-based sharing to combine the simplicity of static linking with the space savings of dynamic linking: although slinky executables are completely self-contained, minimal performance and disk-space penalties are incurred if two executables use the same library. we have developed a slinky prototype that consists of tools for adding digests to executables, a slight modification of the linux kernel to use those digests to share code pages, and tools for transferring files between machines based on digests of their contents. results show that our prototype has no measurable performance decrease relative to dynamic linking, a comparable memory footprint, a 20% storage space increase, and a 34% increase in the network bandwidth required to transfer the packages. we believe that slinky obviates many of the justifications for dynamic linking, making static linking a superior technology for software organization and distribution.
a portable kernel abstraction for low-overhead ephemeral mapping management. modern operating systems create ephemeral virtual-to-physical mappings for a variety of purposes, ranging from the implementation of inter-process communication to the implementation of process tracing and debugging. with succeeding generations of processors the cost of creating ephemeral mappings is increasing, particularly when an ephemeral mapping is shared by multiple processors. to reduce the cost of ephemeral mapping management within an operating system kernel, we introduce the sf_buf ephemeral mapping interface. we demonstrate how in several kernel subsystems -- including pipes, memory disks, sockets, execve(), ptrace(), and the vnode pager -- the current implementation can be replaced by calls to the sf_buf interface. we describe the implementation of the sf_buf interface on the 32-bit i386 architecture and the 64-bit amd64 architecture. this implementation reduces the cost of ephemeral mapping management by reusing wherever possible existing virtual-to-physical address mappings. we evaluate the sf_buf interface for the pipe, memory disk and networking subsystems. our results show that these subsystems perform significantly better when using the sf_buf interface. on a multiprocessor platform interprocessor interrupts are greatly reduced in number or eliminated altogether.
a transactional flash file system for microcontrollers. we present a transactional file system for flash memory devices. the file system is designed for embedded microcontrollers that use an on-chip or on-board nor flash device as a persistent file store. the file system provides atomicity to arbitrary sequences of file system operations, including reads, writes, file creation and deletion, and so on. the file system supports multiple concurrent transactions. thanks to a sophisticated data structure, the file system is efficient in terms of read/write-operation counts, flash-storage overhead, and ram usage. in fact, the file system typically uses several hundreds bytes of ram (often less than 200) and a bounded stack (or no stack), allowing it to be used on many 16-bit microcontrollers. flash devices wear out; each block can only be erased a certain number of times. the file system manages the wear of blocks to avoid early wearing out of frequently-used blocks.
adaptive main memory compression. applications that use large data sets frequently exhibit poor performance because the size of their working set exceeds the real memory, causing excess page faults, and ultimately exhibit thrashing behavior. this paper describes a memory compression solution to this problem that adapts the allocation of real memory between uncompressed and compressed pages and also manages fragmentation without user involvement. the system manages its resources dynamically on the basis of the varying demands of each application and also on the situational requirements that are data dependent. the technique used to localize page fragments in the compressed area allows the system to reclaim or add space easily if it is advisable to shrink or grow the size of the compressed area. the design is implemented in linux, runs on both 32- bit and 64-bit architectures, and has been demonstrated to work in practice under complex workload conditions and memory pressure. the benefits from our approach depend on the relationship between the size of the compressed area, the application's compression ratio, and the access pattern of the application. for a range of benchmarks and applications, the system shows an increase in performance by a factor of 1.3 to 55.
thresher: an efficient storage manager for copy-on-write snapshots. a new generation of storage systems exploit decreasing storage costs to allow applications to take snapshots of past states and retain them for long durations. over time, current snapshot techniques can produce large volumes of snapshots. indiscriminately keeping all snapshots accessible is impractical, even if raw disk storage is cheap, because administering such large-volume storage is expensive over a long duration. moreover, not all snapshots are equally valuable. thresher is a new snapshot storage management system, based on novel copy-on-write snapshot techniques, that is the first to provide applications the ability to discriminate among snapshots efficiently. valuable snapshots can remain accessible or stored with faster access while less valuable snapshots are discarded or moved off-line. measurements of the thresher prototype indicate that the new techniques are efficient and scalable, imposing minimal (4%) performance penalty on expected common workloads.
privacy analysis for data sharing in *nix systems. linux and its various flavors (together called *nix) are growing in mainstream popularity and many enterprise infrastructures now are based on *nix platforms. an important component of these systems is the ingrained multi-user support that lets users share data with each other. in this paper, we analyze *nix systems and identify an urgent need for better privacy support in their data sharing mechanisms. in one of our studies it was possible to access over 84 gb of private data at one organization of 836 users, including over 300,000 emails and 579 passwords to financial and other private services websites. the most surprising aspect was the extremely low level of sophistication of the attack. the attack uses no technical vulnerabilities, rather inadequacies of *nix access control combined with user/application's privacy-indifferent behavior.
system- and application-level support for runtime hardware reconfiguration on soc platforms. this paper discusses the design and implementation of a system-level mechanism and corresponding application-level support that enables programs running on a reconfigurable soc to modify the underlying fpga at runtime. applications may request the addition and/or removal of softcore devices at any point in time. requests are handled in a coordinated way via a separate user-level process that fetches the configuration bistream from an exernal server. system reconfiguration is implemented via a fast suspend-resume mechanism with support for dynamic softcore device address management to achieve flexible device placement on the reconfigurable fabric. even though our approach does not rely on advanced (and expensive) hardware that supports dynamic partial reconfiguration, the obtained functionality is sufficient for a wide range of application scenarios.
reval: a tool for real-time evaluation of ddos mitigation strategies. there is a growing number of ddos attacks on the internet, resulting in significant impact on users. network operators today have little access to scientific means to effectively deal with these attacks in real time. the need of the hour is a tool to accurately assess the impact of attacks and more importantly identify feasible mitigation responses enabling real-time decision making. we designed and implemented reval, a tool that reports ddos attack impact in real time, scaling to large networks. this is achieved by modeling resource constraints of network elements and incorporating routing information. we demonstrate the usefulness of the tool on two real network topologies using empirical traffic data and examining real attack scenarios. using data from a tier-1 isp network (core, access and customer router network) of size in excess of 60000 nodes, reval models network conditions with close to 0.4 million traffic flows in about 11 seconds, and evaluates a given mitigation deployment chosen from a sample set in about 35 seconds. besides real-time decision support, we show how the simulator can also be used in longer term network planning to identify where and how to upgrade the network to improve network resilience. the tool is applicable for networks of any size and can be used to analyze other network anomalies like flash crowds.
interactive performance measurement with vncplay. today many system benchmarks use throughput as a measure of performance. while throughput is appropriate for benchmarking server environments, response time is a better metric for evaluating desktop performance. currently, there is a lack of good tools to measure interactive performance; although several commercial gui testing tools exist, they are not designed for performance measurement. this paper presents vncplay, a cross-platform tool for measuring interactive performance of gui-based systems. vncplay records a user's interactive session with a system and replays it multiple times under different system configurations; interactive response time is evaluated by comparing the times at which similar screen updates occur in each of the replayed sessions. using vncplay we studied the effect of processor speed and disk load on interactive performance of microsoft windows and linux. these experiments show that the same user session can have widely varying interactive response times in different environments while maintaining the same total running time, illustrating that response time is a better measure of interactive performance than throughput. the experimental results make a case for a response time measurement tool like vncplay.
smonitor: a non-intrusive client-perceived end-to-end performance monitor of secured internet services. end-to-end performance measurement is fundamental to building high-performance internet services. while many internet services often operate using http over ssl/tls, current monitors are limited to plaintext http services. this paper presents smonitor, a non-intrusive server-side end-to-end performance monitor that can monitor https services. the monitor passively collects live packet traces from a server site. it then uses a size-based analysis method on http requests to infer characteristics of client accesses and measures client-perceived pageview response time in real time. we designed and implemented a prototype of smonitor. preliminary evaluations show measurement error of less than 5%.
an evaluation of network stack parallelization strategies in modern operating systems. as technology trends push future microprocessors toward chip multiprocessor designs, operating system network stacks must be parallelized in order to keep pace with improvements in network bandwidth. there are two competing strategies for stack parallelization. message-parallel network stacks use concurrent threads to carry out network operations on independent messages (usually packets), whereas connection-parallel stacks map operations to groups of connections and permit concurrent processing on independent connection groups. connection-parallel stacks can use either locks or threads to serialize access to connection groups. this paper evaluates these parallel stack organizations using a modern operating system and chip multiprocessor hardware. compared to uniprocessor kernels, all parallel stack organizations incur additional locking overhead, cache inefficiencies, and scheduling overhead. however, the organizations balance these limitations differently, leading to variations in peak performance and connection scalability. lock-serialized connection-parallel organizations reduce the locking overhead of message-parallel organizations by using many connection groups and eliminate the expensive thread handoff mechanism of thread-serialized connection-parallel organizations. the resultant organization outperforms the others, delivering 5.4 gb/s of tcp throughput for most connection loads and providing a 126% throughput improvement versus a uniprocessor for the] heaviest connection loads.
how dns misnaming distorts internet topology mapping. network researchers commonly use reverse dns lookups of router names to provide geographic or topological information that would otherwise be difficult to obtain. by systematically examining a large isp, we find that some of these names are incorrect. we develop techniques to automatically identify these misnamings, and determine the actual locations, which we validate against the configuration of the isp's routers. while the actual number of misnamings is small, these errors induce a large number of false links in the inferred connectivity graph. we also measure the effects on path inflation, and find that the misnamings make path inflation and routing problems appear much worse than they actually are.
trickle: a userland bandwidth shaper for unix-like systems. as with any finite resource, it is often necessary to apply policies to the shared usage of network resources. existing solutions typically implement this by employing traffic management in edge routers. however, users of smaller networks regularly find themselves in need of nothing more than ad-hoc rate limiting. such networks are typically unmanaged, with no network administrator(s) to manage complicated traffic management schemes. trickle bridges this gap by providing a simple and portable solution to rate limit the tcp connections of a given process or group of processes. trickle takes advantage of the unix dynamic loader's preloading functionality to interposition itself in front of the bsd socket api provided by the system's libc. running entirely in user space, shapes network traffic by delaying and truncating socket i/os without requiring administrator privileges. instances of trickle can cooperate, even across networks allowing for the specification of global rate limiting policies. due to the prevalence of bsd sockets and dynamic loaders, trickle enjoys the benefit of portability accross a multitude of unix-like platforms.
a parts-of-file file system. the parts-of-file file system (poffs) allows read-write accesses to different views of a given file or set of files in order to help the user separate and manipulate different concerns. the set of files is considered as a mount point from which views can be selected as read-write files via directories. paths are formulas mentioning properties of a desired view. each directory contain a file (the view) which contains the parts of the mounted files that satisfy the properties. this service is offered generically at the file system level, and a plug-in interface permits that file formats, or application-specific details are handled by user-defined operators. special plug-ins called transducers can be defined for automatically attaching properties to parts of files. performances are encouraging; files of 100 000 lines are handled efficiently.
freevga: architecture independent video graphics initialization for linuxbios. linuxbios is fast becoming a widely accepted alternative to the traditional pc bios for cluster computing applications. however, in the process it is gaining attention from developers of internet appliance, desktop and visualization applications, who also wish to take advantage of the features provided by linuxbios, such as minimizing user interaction, increasing system reliability, and faster boot times. unlike cluster computing, these applications tend to rely heavily on graphical user interfaces, so it is important that the vga hardware is correctly initialized early in the boot process in additional to the hardware initialization currently performed by linuxbios. unfortunately, the open-source nature of linuxbios means that many graphic card vendors are reluctant to expose code relating to the initialization of their hardware in the fear that this might allow competitors access to proprietary chipset information. as a consequence, in many cases the only way to initialize the vga hardware is to use the vendor provided, proprietary, vga bios. to achieve this it is necessary to provide a compatibility layer that operates between the vga bios and linuxbios in order to simulate the environment that the vga bios assumes is available. in this paper we present our preliminary results on freevga, an x86 emulator based on x86emu that can be used as such a compatibility layer. we will show how we have successfully used freevga to initialize vga cards from both ati and nvidia on a tyan s2885 platform.
building a reactive immune system for software services. we propose a reactive approach for handling a wide variety of software failures, ranging from remotely exploitable vulnerabilities to more mundane bugs that cause abnormal program termination (e.g., illegal memory dereference) or other recognizable bad behavior (e.g., computational denial of service). our emphasis is in creating "self-healing" software that can protect itself against a recurring fault until a more comprehensive fix is applied. briefly, our system monitors an application during its execution using a variety of external software probes, trying to localize (in terms of code regions) observed faults. in future runs of the application, the "faulty" region of code will be executed by an instruction-level emulator. the emulator will check for recurrences of previously seen faults before each instruction is executed. when a fault is detected, we recover program execution to a safe control flow. using the emulator for small pieces of code, as directed by the observed failure, allows us to minimize the performance impact on the immunized application. we discuss the overall system architecture and a prototype implementation for the x86 platform. we show the effectiveness of our approach against a range of attacks and other software failures in real applications such as apache, sshd, and bind. our preliminary performance evaluation shows that although full emulation can be prohibitively expensive, selective emulation can incur as little as 30% performance overhead relative to an uninstrumented (but failure-prone) instance of apache. although this overhead is significant, we believe our work is a promising first step in developing self-healing software.
amp: program context specific buffer caching. we present adaptive multi-policy disk caching (amp), which uses multiple caching policies within one application, and adapts both which policies to use and their relative fraction of the cache, based on program-context specific information. amp differentiate disk requests based on the program contexts, or code locations, that issue them. compared to recent work, amp is unique in that it employs a new robust scheme for detecting looping patterns in access streams, as well as a low-overhead randomized way of managing many cache partitions. we show that amp outperforms non-detection-based caching algorithms on a variety of workloads by up to 50% in miss rate reduction. compared to other detection-based schemes, we show that amp detects access patterns more accurately for a series of synthesized workloads, and incurs up to 15% fewer misses for one application trace.
netstate: a network version tracking system. network administrators and security analysts often do not know what network services are being run in every corner of their networks. if they do have a vague grasp of the services running on their networks, they often do not know what specific versions of those services are running. actively scanning for services and versions does not always yield complete results, and patch and service management, therefore, suffer. we present net-state, a system for monitoring, storing, and reporting application and operating system version information for a network. netstate gives security and network administrators the ability to know what is running on their networks while allowing for user-managed machines and complex host configurations. our architecture uses distributed modules to collect network information and a centralized server that stores and issues reports on that collected version information. we discuss some of the challenges to building and operating netstate as well as the legal issues surrounding the promiscuous capture of network data. we conclude that this tool can solve some key problems in network management and has a wide range of possibilities for future uses.
comparison-based file server verification. comparison-based server verification involves testing a server by comparing its responses to those of a reference server. an intermediary, called a "server tee," interposes between clients and the reference server, synchronizes the system-under-test (sut) to match the reference server's state, duplicates each request for the sut, and compares each pair of responses to identify any discrepancies. the result is a detailed view into any differences in how the sut satisfies the client-server protocol specification, which can be invaluable in debugging servers, achieving bug compatibility, and isolating performance differences. this paper introduces, develops, and illustrates the use of comparison-based server verification. as a concrete example, it describes a nfsv3 tee and reports on its use in identifying interesting differences in several production nfs servers and in debugging a prototype nfs server. these experiences confirm that comparison-based server verification can be a useful tool for server implementors.
ourmon and network monitoring performance. ourmon is an open-source network management and anomaly detection system that has been developed over a period of several years at portland state university. ourmon monitors a target network both to highlight abnormal network traffic and measure normal traffic loads. in this paper, we describe the features and performance characteristics of ourmon. ourmon features include a novel mechanism for running multiple concurrent berkeley packet filter (bpf) expressions bound to a single rrdtool-style graph, as well as various types of top talker (top-n) filters aimed at conventional network flow measurements and anomaly detection. these features permit a variety of useful and easily-understood measurements. one problem that sniffer-based network monitor systems face is network-intensive attacks that can overwhelm monitoring and analysis resources. lab experiments with an ixia high-speed packet generator, as well as experiences with ourmon in a real network environment, demonstrate this problem. some recent modifications to ourmon have greatly improved its performance. however, minimum-size packets in a high-speed network can still easily make a host lose packets even at relatively slow rates and low monitor workloads. we contend that small packet performance is a general network security problem faced by current monitoring systems including both open source systems such as ourmon and snort, and commercial systems.
sarc: sequential prefetching in adaptive replacement cache. sequentiality of reference is an ubiquitous access pattern dating back at least to multics. sequential workloads lend themselves to highly accurate prediction and prefetching. in spite of the simplicity of the workload, design and analysis of a good sequential prefetching algorithm and associated cache replacement policy turns out to be surprisingly intricate. as first contribution, we uncover and remedy an anomaly (akin to famous belady's anomaly) that plagues sequential prefetching when integrated with caching. typical workloads contain a mix of sequential and random streams. as second contribution, we design a self-tuning, low overhead, simple to implement, locally adaptive, novel cache management policy sarc that dynamically and adaptively partitions the cache space amongst sequential and random streams so as to reduce the read misses. as third contribution, we implemented sarc along with two popular state-of-the-art lru variants on hardware for ibm's flagship storage controller shark. on shark hardware with 8 gb cache and 16 raid-5 arrays that is serving a workload akin to storage performance council's widely adopted spc-1 benchmark, sarc consistently and dramatically outperforms the two lru variants shifting the throughput-response time curve to the right and thus fundamentally increasing the capacity of the system. as anecdotal evidence, at the peak throughput, sarc has average response time of 5.18ms as compared to 33.35ms and 8.92ms for the two lru variants.
clock-pro: an effective improvement of the clock replacement. with the ever-growing performance gap between memory systems and disks, and rapidly improving cpu performance, virtual memory (vm) management becomes increasingly important for overall system performance. however, one of its critical components, the page replacement policy, is still dominated by clock, a replacement policy developed almost 40 years ago. while pure lru has an unaffordable cost in vm, clock simulates the lru replacement algorithm with a low cost acceptable in vm management. over the last three decades, the inability of lru as well as clock to handle weak locality accesses has become increasingly serious, and an effective fix becomes increasingly desirable. inspired by our i/o buffer cache replacement algorithm, lirs [13], we propose an improved clock replacement policy, called clock-pro. by additionally keeping track of a limited number of replaced pages, clock-pro works in a similar fashion as clock with a vm-affordable cost. furthermore, it brings all the much-needed performance advantages from lirs into clock. measurements from an implementation of clock-pro in linux kernel 2.4.21 show that the execution times of some commonly used programs can be reduced by up to 47%.
chameleon: a self-evolving, fully-adaptive resource arbitrator for storage systems. enterprise applications typically depend on guaranteed performance from the storage subsystem, lest they fail. however, unregulated competition is unlikely to result in a fair, predictable apportioning of resources. given that widespread access protocols and scheduling policies are largely best-effort, the problem of providing performance guarantees on a shared system is a very difficult one. clients typically lack accurate information on the storage system's capabilities and on the access patterns of the workloads using it, thereby compounding the problem. chameleon is an adaptive arbitrator for shared storage resources; it relies on a combination of self-refining models and constrained optimization to provide performance guarantees to clients. this process depends on minimal information from clients, and is fully adaptive; decisions are based on device and workload models automatically inferred, and continuously refined, at run-time. corrective actions taken by chameleon are only as radical as warranted by the current degree of knowledge about the system's behavior. in our experiments on a real storage system chameleon identified, analyzed, and corrected performance violations in 3-14 minutes--which compares very favorably with the time a human administrator would have needed. our learning-based paradigm is a most promising way of deploying large-scale storage systems that service variable workloads on an ever-changing mix of device types.
build buddy for fun and profit. we present a build and packaging system called build buddy. the system is comprised of a set of tools for building and maintaining software packages on multiple operating systems and architectures.
running virtualized native drivers in user mode linux. a simulation infrastructure for wireless network emulation based on user mode linux and on the virtualisation of the hostap driver is proposed. the interconnection of these components is first described and the architecture of the resulting network emulator is explained. two practical applications are then detailed : the testing of an implementation of the aodv routing protocol in a highly realistic environment and the study of the interactions between the hostap driver and the card it drives.
opencsg: a library for image-based csg rendering. we present the design and implementation of a real-time 3d graphics library for image-based constructive solid geometry (csg). this major approach of 3d modeling has not been supported by real-time computer graphics until recently. we explain two essential image-based csg rendering algorithms, and we introduce an api that provides a compact access to their complex functionality and implementation. as an important feature, the csg library seam lessly integrates application-defined 3d shapes as primitives of csg operations to ensure high adaptability and openness. we also outline optimization techniques to improve the performance in the case of complex csg models. a number of use cases demonstrate potential applications of the library.
maintaining high-bandwidth under dynamic network conditions. the need to distribute large files across multiple wide-area sites is becoming increasingly common, for instance, in support of scientific computing, configuring distributed systems, distributing software updates such as open source isos or windows patches, or disseminating multimedia content. recently a number of techniques have been proposed for simultaneously retrieving portions of a file from multiple remote sites with the twin goals of filling the client's pipe and overcoming any performance bottlenecks between the client and any individual server. while there are a number of interesting tradeoffs in locating appropriate download sites in the face of dynamically changing network conditions, to date there has been no systematic evaluation of the merits of different protocols. this paper explores the design space of file distribution protocols and conducts a detailed performance evaluation of a number of competing systems running in both controlled emulation environments and live across the internet. based on our experience with these systems under a variety of conditions, we propose, implement and evaluate bullet' (bullet prime), a mesh based high bandwidth data dissemination system that outperforms previous techniques under both static and dynamic conditions.
automatic synthesis of filters to discard buffer overflow attacks: a step towards realizing self-healing systems. buffer overflows have become the most common target for network-based attacks. they are also the primary propagation mechanism used by worms. although many techniques (such as stackguard) have been developed to protect servers from being compromised by buffer overflow attacks, these techniques cause the server to crash. in the face of automated, repetitive attacks such as those due to worms, these protection mechanisms lead to repeated restarts of the victim application, rendering its service unavailable. in contrast, we present a promising new approach that learns the characteristics of inputs associated with attacks, and filters them out in the future. it can be implemented without changing the server code, or even having access to its source. since attack-bearing inputs are dropped before they corrupt the victim process, there is no need to restart the victim; as a result, recovery from attacks can be very fast. we tested our approach on 8 buffer overflow attacks reported in the past few years on securityfocus.com and were available with working exploit code, and found that it generated accurate filters for 7 out of these 8 attacks.
using valgrind to detect undefined value errors with bit-precision. we present memcheck, a tool that has been implemented with the dynamic binary instrumentation framework valgrind. memcheck detects a wide range of memory errors in programs as they run. this paper focuses on one kind of error that memcheck detects: undefined value errors. such errors are common, and often cause bugs that are hard to find in programs written in languages such as c, c++ and fortran. memcheck's definedness checking improves on that of previous tools by being accurate to the level of individual bits. this accuracy gives memcheck a low false positive and false negative rate. the definedness checking involves shadowing every bit of data in registers and memory with a second bit that indicates if the bit has a defined value. every value-creating operation is instrumented with a shadow operation that propagates shadow bits appropriately. memcheck uses these shadow bits to detect uses of undefined values that could adversely affect a program's behaviour. under memcheck, programs typically run 20-30 times slower than normal. this is fast enough to use with large programs. memcheck finds many errors in real programs, and has been used during the past two years by thousands of programmers on a wide range of systems, including openoffice, mozilla, opera, kde, gnome, mysql, perl, samba, the gimp, and unreal tournament.
the ethernet speaker system. if we wish to distribute audio in a large room, building, or even a campus, we need multiple speakers. these speakers must be jointly managed and synchronized. the ethernet speaker (es) system presented in this paper can be thought of as a distributed audio amplifier and speakers, it does not "play" any particular format, but rather relies on off-the-shelf audio applications (e.g., mpg123 player, real audio player) to act as the audio source. the ethernet speaker, consists of three elements: (a) a system that converts the audio output of the unmodified audio application to a network stream containing configuration and timing information (rebroad-caster), (b) the devices that generate sound from the audio stream (ethernet speakers), and (c) the protocol that ensures that all the speakers in a lan play the same sounds. this paper covers all three elements, discussing design considerations, experiences from the prototype implementations, and our plans for extending the system to provide additional features such as automatic volume control, local user interfaces, and security.
linux physical memory analysis. we present a tool suite for analysis of physical memory usage within the linux kernel environment. this tool suite can be used to collect and analyze how the physical memory within a linux environment is being used.
transparent checkpoint-restart of multiple processes on commodity operating systems. the ability to checkpoint a running application and restart it later can provide many useful benefits including fault recovery, advanced resources sharing, dynamic load balancing and improved service availability. however, applications often involve multiple processes which have dependencies through the operating system. we present a transparent mechanism for commodity operating systems that can checkpoint multiple processes in a consistent state so that they can be restarted correctly at a later time. we introduce an efficient algorithm for recording process relationships and correctly saving and restoring shared state in a manner that leverages existing operating system kernel functionality. we have implemented our system as a loadable kernel module and user-space utilities in linux. we demonstrate its ability on real-world applications to provide transparent checkpoint-restart functionality without modifying, recompiling, or relinking applications, libraries, or the operating system kernel. our results show checkpoint and restart times 3 to 55 times faster than openvz and 5 to 1100 times faster than xen.
qemu, a fast and portable dynamic translator. we present the internals of qemu, a fast machine emulator using an original portable dynamic translator. it emulates several cpus (x86, powerpc, arm and sparc) on several hosts (x86, powerpc, arm, sparc, alpha and mips). qemu supports full system emulation in which a complete and unmodified operating system is run in a virtual machine and linux user mode emulation where a linux process compiled for one target cpu can be run on another cpu.
active internet traffic filtering: real-time response to denial-of-service attacks. this paper describes active internet traffic filtering (aitf), a mechanism for blocking highly distributed denial-of-service (ddos) attacks. these attacks are an acute contemporary problem, with few practical solutions available today; we describe in this paper the reasons why no effective ddos filtering mechanism has been deployed yet. we show that the current internet's routers have sufficient filtering resources to thwart such attacks, with the condition that attack traffic be blocked close to its sources; aitf leverages this observation. our results demonstrate that aitf can block a million-flow attack within seconds, while it requires only tens of thousands of wire-speed filters per participating router -- an amount easily accommodated by today's routers. aitf can be deployed incrementally and yields benefits even to the very first adopters.
brooery: a graphical environment for analysis of security-relevant network activity. we present the design and implementation of the brooery, a system for graphical analysis of network activity reported by instances of the bro intrusion detection system. it supports multiple input streams and provides a web-based graphical user interface to allow the user to analyze the reported activity. the brooery understands activity at different abstraction levels, allows for quick drill-down searches by focusing on contextuality when moving through the history of events, and provides user-friendly and semantically strong hierarchical filtering to reduce the amount of information presented.
measuring cpu overhead for i/o processing in the xen virtual machine monitor. virtual machine monitors (vmms) are gaining popularity in enterprise environments as a software-based solution for building shared hardware infrastructures via virtualization. in this work, using the xen vmm, we present a light weight monitoring system for measuring the cpu usage of different virtual machines including the cpu overhead in the device driver domain caused by i/o processing on behalf of a particular virtual machine. our performance study attempts to quantify and analyze this overhead for a set of i/o intensive workloads.
binder: an extrusion-based break-in detector for personal computers. compromised computers have been a menace to both personal and business computing. in this paper, we tackle the problem of automated detection of break-ins of new unknown threats such as worms, spyware and adware on personal computers. we propose break-in detector (binder), a host-based break-in detection system. our key observation is that many break-ins make extrusions, stealthy malicious outgoing network connections. binder exploits a unique characteristic of personal computers, that most network activities are directly or indirectly triggered by user input. since threats tend to run as background precesses and thus do not receive any user input, the intuition behind binder is that only threats generate connections without user input. by correlating outgoing network connections and processing information with user activities, binder can capture extrusions and thus break-ins.
performance of multithreaded chip multiprocessors and implications for operating system design. we investigated how operating system design should be adapted for multithreaded chip multiprocessors (cmt) - a new generation of processors that exploit thread-level parallelism to mask the memory latency in modern workloads. we determined that the l2 cache is a critical shared resource on cmt and that an insufficient amount of l2 cache can undermine the ability to hide memory latency on these processors. to use the l2 cache as efficiently as possible, we propose an l2-conscious scheduling algorithm and quantify its performance potential. using this algorithm it is possible to reduce miss ratios in the l2 cache by 25-37% and improve processor throughput by 27-45%.
a tool for automated iptables firewall analysis. we describe itval, a tool that enables the efficient analysis of an iptables-based firewall. the underlying basis of itval is a library for the efficient manipulation of multi-way decision diagrams. we represent iptables rule sets and queries about the firewall defined by those rule sets as multi-way decision diagrams, and determine answers for the queries by manipulating the diagrams. in addition to discussing the design and implementation of itval, we describe how it can be used to detect and correct common firewall errors.
pulse: a dynamic deadlock detection mechanism using speculative execution. deadlock can occur wherever multiple processes interact. most existing static and dynamic deadlock detection tools focus on simple types of deadlock, such as those caused by incorrect ordering of lock acquisitions. in this paper, we propose pulse, a novel operating system mechanism that dynamically detects various types of deadlock in application programs. pulse runs as a system daemon. periodically, it scans the system for processes that have been blocked for a long time (e.g., waiting on i/o events). to determine if these processes are deadlocked, pulse speculatively executes them ahead to discover their dependences. based on this information, it constructs a general resource graph and detects deadlock by checking if the graph contains cycles. the ability to look into the future allows pulse to detect deadlocks involving consumable resources, such as synchronization semaphores and pipes, which no existing tools can detect. we evaluate pulse by showing that it can detect deadlocks in the classical dining-philosophers and smokers problems. furthermore, we show that pulse can detect a well-known deadlock scenario, which is widely referred to as a denial-of-service vulnerability, in the apache web server. our results show that pulse can detect all these deadlocks within three seconds, and it introduces little performance overhead to normal applications that do not deadlock.
scmbug: policy-based integration of software configuration management with bug-tracking. software configuration management(scm) and bug-tracking are key components of a successful software engineering project. existing systems integrating the two have failed to meet the needs of the asu scalable computing lab, powered by open-source software. an improved solution to the integration problem, designed to accomodate both free and commercial systems alike, is presented. scmbug offers a policy-based mechanism of capturing and handling integration of scm events, such as committing software change-sets and labeling software releases, with a bug-tracking system. synchronous verification checks and the flexibilty to match multiple development models separate this approach from related work. we address design limitations of existing integration efforts, suggest improvements in scm and bug-tracking systems required to achieve a scalable solution, and document our early integration experiences.
loose synchronization for large-scale networked systems. traditionally, synchronization barriers ensure that no cooperating process advances beyond a specified point until all processes have reached that point. in heterogeneous large-scale distributed computing environments, with unreliable network links and machines that may become overloaded and unresponsive, traditional barrier semantics are too strict to be effective for a range of emerging applications. in this paper, we explore several relaxations, and introduce a partial barrier, a synchronization primitive designed to enhance liveness in loosely coupled networked systems. partial barriers are robust to variable network conditions; rather than attempting to hide the asynchrony inherent to wide-area settings, they enable appropriate application-level responses. we evaluate the improved performance of partial barriers by integrating them into three publicly available distributed applications running across planetlab. further, we show how partial barriers simplify a re-implementation of mapreduce that targets wide-area environments.
stealth probing: efficient data-plane security for ip routing. ip routing is notoriously vulnerable to accidental misconfiguration and malicious attack. although secure routing protocols are an important defense, the data plane must be part of any complete solution. existing proposals for secure (link-level) forwarding are heavy-weight, requiring cryptographic operations at each hop in a path. instead, we propose a light-weight data-plane mechanism (called stealth probing) that monitors the availability of paths in a secure fashion, while enabling the management plane to home in on the location of adversaries by combining the results of probes from different vantage points (called byzantine tomography). we illustrate how stealth probing and byzantine tomography can be applied in today's routing architecture, without requiring support from end hosts or internal routers.
ip only server. present day servers must support a variety of legacy i/o devices and protocols that are rarely used in the day to day server operation, at a significant cost in board layout complexity, reliability, power consumption, heat dissipation, and ease of management. we present a design of an ip only server, which has a single, unified i/o interface: ip network. all of the server's i/o is emulated and redirected over ip/ethernet to a remote management station, except for the hard disks which are accessed via iscsi. the emulation is done in hardware, and is available from power-on to shutdown, including the pre-os and post-os (crash) stages, unlike alternative solutions such as vnc that can only function when the os is operational. the server's software stack -- the bios, the os, and applications -- will run without any modifications. we have developed a prototype ip only server, based on a cots fpga running our embedded i/o emulation firmware. the remote station is a commodity pc running a vnc client for video, keyboard and mouse. initial performance evaluations with unmodified bios and windows and linux operating systems indicate negligible network overhead and acceptable user experience. this prototype is the first attempt to create a diskless and headless x86 server that runs unmodified industry standard software (bios, os, and applications).
compare-by-hash: a reasoned analysis. compare-by-hash is the now-common practice used by systems designers who assume that when the digest of a cryptographic hash function is equal on two distinct files, then those files are identical. this approach has been used in both real projects and in research efforts (for example rysnc [16] and lbfs [12]). a recent paper by henson criticized this practice [8]. the present paper revisits the topic from an advocate's standpoint: we claim that compare-by-hash is completely reasonable, and we offer various arguments in support of this viewpoint in addition to addressing concerns raised by henson.
flux: a language for programming high-performance servers. programming high-performance server applications is challenging: it is both complicated and error-prone to write the concurrent code required to deliver high performance and scalability. server performance bottlenecks are difficult to identify and correct. finally, it is difficult to predict server performance prior to deployment. this paper presents flux, a language that dramatically simplifies the construction of scalable high-performance server applications. flux lets programmers compose off-the-shelf, sequential c or c++ functions into concurrent servers. flux programs are type-checked and guaranteed to be deadlock-free. we have built a number of servers in flux, including a web server with php support, an image-rendering server, a bittorrent peer, and a game server. these flux servers match or exceed the performance of their counterparts written entirely in c. by tracking hot paths through a running server, flux simplifies the identification of performance bottlenecks. the flux compiler also automatically generates discrete event simulators that accurately predict actual server performance under load and with different hardware resources.
transparent contribution of memory. a multitude of research and commercial projects have proposed contributory systems that utilize wasted cpu cycles, idle memory and free disk space found on end-user machines. these applications include distributed computation such as signal processing and protein folding, peer-to-peer backup, and large-scale distributed storage. while users are generally willing to give up unused cpu cycles, the use of memory by contributory applications deters participation in such systems. contributory applications pollute the machine's memory, forcing user pages to be evicted to disk. this paging can disrupt user activity for seconds or even minutes. in this paper, we describe the design and implementation of an operating system mechanism to support transparent contribution of memory. a transparent memory manager (tmm) controls memory usage by contributory applications, ensuring that users will not notice an increase in the miss rate of their applications. tmm is able to protect user pages such that page miss overhead is limited to 1.7%, while donating hundreds of megabytes of memory.
proper: privileged operations in a virtualised system environment. virtualised systems have experienced a resurgence in popularity in recent years, particularly in supporting a large number of independent services on a single host. this paper describes our work designing and implementing proper, a service running on the planetlab system, that allows other services to perform privileged operations in a safe, controlled manner. we describe how implementing such a system in a traditional unix environment is non-trivial, and discuss the practical use of proper.
integrated scientific workflow management for the emulab network testbed. the main forces that shaped current network testbeds were the needs for realism and scale. now that several testbeds support large and complex experiments, management of experimentation processes and results has become more difficult and a barrier to high-quality systems research. the popularity of network testbeds means that new tools for managing experiment workflows, addressing the ready-made base of testbed users, can have important and significant impacts. we are now evolving emulab, our large and popular network testbed, to support experiments that are organized around scientific workflows. this paper summarizes the opportunities in this area, the new approaches we are taking, our implementation in progress, and the challenges in adapting scientific workflow concepts for testbed-based research. with our system, we expect to demonstrate that a network testbed with integrated scientific workflow management can be an important tool to aid research in networking and distributed systems.
cutting through the confusion: a measurement study of homograph attacks. web homograph attacks have existed for some time, and the recent adoption of international domain names (idns) support by browsers and dns registrars has exacerbated the problem [gabr02]. many international letters have similar glyphs, such as the cyrillic letter p (lower case 'er,' unicode 0x0440) and the latin letter p. because of the large potential for misuse of idns, browser vendors, policy advocates, and researchers have been exploring techniques for mitigating homograph attacks [=mozi05, appl05, oper05, mark05]. there has been plenty of attention on the problem recently, but we are not aware of any data that quantifies the degree to which web homograph attacks are currently taking place. in this paper, we use a combination of passive network tracing and active dns probing to measure several aspects of web homographs. our main findings are four-fold. first, many authoritative web sites that users visit have several confusable domain names registered. popular web sites are much more likely to have such confusable domains registered. second, registered confusable domain names tend to consist of single character substitutions from their authoritative domains, though we saw instances of five-character substitutions. most confusables currently use latin character homographs, but we did find a non-trivial number of idn homographs. third, web sites associated with non-authoritative confusable domains most commonly show users advertisements. less common functions include redirecting victims to competitor sites and spoofing the content of authoritative site. fourth, during our nine-day trace, none of the 828 web clients we observed visited a non-authoritative confusable web site. overall, our measurement results suggest that homograph attacks currently are rare and not severe in nature. however, given the recent increases in phishing incidents, homograph attacks seem like an attractive future method for attackers to lure users to spoofed sites.
efficient query subscription processing for prospective search engines. current web search engines are retrospective in that they limit users to searches against already existing pages. prospective search engines, on the other hand, allow users to upload queries that will be applied to newly discovered pages in the future. we study and compare algorithms for efficiently matching large numbers of simple keyword queries against a stream of newly discovered pages.
sharing networked resources with brokered leases. this paper presents the design and implementation of shirako, a system for on-demand leasing of shared networked resources. shirako is a prototype of a service-oriented architecture for resource providers and consumers to negotiate access to resources over time, arbitrated by brokers. it is based on a general lease abstraction: a lease represents a contract for some quantity of a typed resource over an interval of time. resource types have attributes that define their performance behavior and degree of isolation. shirako decouples fundamental leasing mechanisms from resource allocation policies and the details of managing a specific resource or service. it offers an extensible interface for custom resource management policies and new resource types. we show how shirako enables applications to lease groups of resources across multiple autonomous sites, adapt to the dynamics of resource competition and changing load, and guide configuration and deployment. experiments with the prototype quantify the costs and scalability of the leasing mechanisms, and the impact of lease terms on fidelity and adaptation.
implementation and evaluation of moderate parallelism in the bind9 dns server. suboptimal performance of the isc bind9 dns server with multiple threads is a well known problem. this paper explores practical approaches addressing this long-standing issue. first, intensive profiling identifies major bottlenecks occurring due to overheads for thread synchronization. these bottlenecks are then eliminated by giving separate work areas with a large memory pool to threads, introducing faster operations on reference counters, and implementing efficient reader-writer locks. whereas some of the solutions developed depend on atomic operations specific to hardware architecture, which are less portable, the resulting implementation still supports the same platforms as before through abstract apis. the improved implementation scales well with up to four processors whether it is operating as an authoritative-only dns server, with or without dynamic updates, or as a caching dns server. it also reduces the memory footprint for large dns databases. acceptance of this new sever will also have a positive side effect in that bind9, and its new features such as dnssec, should get wider acceptance. the direct result has other ramifications: first, the better performance at the application level reveals a kernel bottleneck in freebsd; also, while the results described here are based on our experience with bind9, the techniques should be applicable to other thread-based applications.
antfarm: tracking processes in a virtual machine environment. in a virtualized environment, the vmm is the system's primary resource manager. some services usually implemented at the os layer, like i/o scheduling or certain kinds of security monitoring, are therefore more naturally implemented inside the vmm. implementing such services at the vmm layer can be complicated by the lack of os and application-level knowledge within a vmm. this paper describes techniques that can be used by a vmm to independently overcome part of the "semantic gap" separating it from the guest operating systems it supports. these techniques enable the vmm to track the existence and activities of operating system processes. antfarm is an implementation of these techniques that works without detailed knowledge of a guest's internal architecture or implementation. an evaluation of antfarm for two virtualization environments and two operating systems shows that it can accurately infer process events while incurring only a small 2.5% runtime overhead in the worst case. to demonstrate the practical benefits of process information in a vmm we implement an anticipatory disk scheduler at the vmm level. this case study shows that significant disk throughput improvements are possible in a virtualized environment by exploiting process information within a vmm.
towards a resilient operating system for wireless sensor networks. active research has recently been conducted on large scale wireless sensor networks, especially network management and maintenance, but the technique for managing application errors on mmu-less sensor node devices has not been seriously considered. this paper presents a resilient operating system mechanism for wireless sensor networks. the proposed mechanism separates the kernel from the user execution area via dual mode operation, and the access violation of applications is controlled by static/dynamic code checking. the experiment results on a common sensor node show that the proposed mechanisms effectively protect the system from errant applications.
resilient connections for ssh and tls. disconnection of an ssh shell or a secure application session due to network outages or travel is a familiar problem to many internet users today. in this paper, we extend the ssh and tls protocols to support resilient connections that can span several sequential tcp connections. the extensions allow sessions to survive both changes in ip addresses and long periods of disconnection. our design emphasizes deployability in real-world environments, and addresses many of the challenges identified in previous work, including assumptions made about network middleboxes such as firewalls and nats. we have also implemented the extensions in the openssh and puretls software packages and tested them in practice.
high performance vmm-bypass i/o in virtual machines. currently, i/o device virtualization models in virtual machine (vm) environments require involvement of a virtual machine monitor (vmm) and/or a privileged vm for each i/o operation, which may turn out to be a performance bottleneck for systems with high i/o demands, especially those equipped with modern high speed interconnects such as infiniband. in this paper, we propose a new device virtualization model called vmm-bypass i/o, which extends the idea of os-bypass originated from user-level communication. essentially, vmm-bypass allows time-critical i/o operations to be carried out directly in guest vms without involvement of the vmm and/or a privileged vm. by exploiting the intelligence found in modern high speed network interfaces, vmm-bypass can significantly improve i/o and communication performance for vms without sacrificing safety or isolation. to demonstrate the idea of vmm-bypass, we have developed a prototype called xen-ib, which offers infiniband virtualization support in the xen 3.0 vm environment. xen-ib runs with current infiniband hardware and does not require modifications to existing user-level applications or kernel-level drivers that use infiniband. our performance measurements show that xen-ib is able to achieve nearly the same raw performance as the original infiniband driver running in a non-virtualized environment.
bump in the ether: a framework for securing sensitive user input. we present bump in the ether (bite), an approach for preventing user-space malware from accessing sensitive user input and providing the user with additional confidence that her input is being delivered to the expected application. rather than preventing malware from running or detecting already-running malware, we facilitate user input that bypasses common avenues of attack. user input traverses a trusted tunnel from the input device to the application. this trusted tunnel is implemented using a trusted mobile device working in tandem with a host platform capable of attesting to its current software state. based on a received attestation, the mobile device verifies the integrity of the host platform and application, provides a trusted display through which the user selects the application to which her inputs should be directed, and encrypts those inputs so that only the expected application can decrypt them. we describe the design and implementation of bite, with emphasis on both usability and security issues.
provenance-aware storage systems. a provenance-aware storage system (pass) is a storage system that automatically collects and maintains provenance or lineage, the complete history or ancestry of an item. we discuss the advantages of treating provenance as meta-data collected and maintained by the storage system, rather than as manual annotations stored in a separately administered database. we describe a pass implementation, discussing the challenges it presents, performance cost it incurs, and the new functionality it enables. we show that with reasonable overhead, we can provide useful functionality not available in today's file systems or provenance management systems.
design tradeoffs in applying content addressable storage to enterprise-scale systems based on virtual machines. this paper analyzes the usage data from a live deployment of an enterprise client management system based on virtual machine (vm) technology. over a period of seven months, twenty-three volunteers used vm-based computing environments hosted by the system and created over 800 checkpoints of vm state, where each checkpoint included the virtual memory and disk states. using this data, we study the design tradeoffs in applying content addressable storage (cas) to such vm-based systems. in particular, we explore the impact on storage requirements and network load of different privacy properties and data granularities in the design of the underlying cas system. the study clearly demonstrates that relaxing privacy can reduce the resource requirements of the system, and identifies designs that provide reasonable compromises between privacy and resource demands.
understanding and validating database system administration. a large number of enterprises need their commodity database systems to remain available at all times. although administrator mistakes are a significant source of unavailability and cost in these systems, no study to date has sought to quantify the frequency of mistakes in the field, understand the context in which they occur, or develop system support to deal with them explicitly. in this paper, we first characterize the typical administrator tasks, testing environments, and mistakes using results from an extensive survey we have conducted of 51 experienced administrators. given the results of this survey, we next propose system support to validate administrator actions before they are made visible to users. our prototype implementation creates a validation environment that is an extension of a replicated database system, where administrator actions can be validated using real workloads. the prototype implements three forms of validation, including a novel form in which the behavior of a database replica can be validated even without an example of correct behavior for comparison. our results show that the prototype can detect the major classes of administrator mistakes.
service placement in a shared wide-area platform. emerging federated computing environments offer attractive platforms to test and deploy global-scale distributed applications. when nodes in these platforms are timeshared among competing applications, available resources vary across nodes and over time. thus, one open architectural question in such systems is how to map applications to available nodes--that is, how to discover and select resources. using a six-month trace of planetlab resource utilization data and of resource demands from three long-running planetlab services, we quantitatively characterize resource availability and application usage behavior across nodes and over time, and investigate the potential to mitigate the application impact of resource variability through intelligent service placement and migration. we find that usage of cpu and network resources is heavy and highly variable. we argue that this variability calls for intelligently mapping applications to available nodes. further, we find that node placement decisions can become ill-suited after about 30 minutes, suggesting that some applications can benefit from migration at that timescale, and that placement and migration decisions can be safely based on data collected at roughly that timescale. we find that inter-node latency is stable and is a good predictor of available bandwidth; this observation argues for collecting latency data at relatively coarse timescales and bandwidth data at even coarser timescales, using the former to predict the latter between measurements. finally, we find that although the utilization of a particular resource on a particular node is a good predictor of that node's utilization of that resource in the near future, there do not exist correlations to support predicting one resource's availability based on availability of other resources on the same node at the same time, on availability of the same resource on other nodes at the same site, or on time-series forecasts that assume a daily or weekly regression to the mean.
securing web service by automatic robot detection. web sites are routinely visited by automated agents known as web robots, that perform acts ranging from the beneficial, such as indexing for search engines, to the malicious, such as searching for vulnerabilities, attempting to crack passwords, or spamming bulletin boards. previous work to identify malicious robots has relied on ad-hoc signature matching and has been performed on a per-site basis. as web robots evolve and diversify, these techniques have not been scaling. we approach the problem as a special form of the turing test and defend the system by inferring if the traffic source is human or robot. by extracting the implicit patterns of human web browsing, we develop simple yet effective algorithms to detect human users. our experiments with the codeen content distribution network show that 95% of human users are detected within the first 57 requests, and 80% can be identified in only 20 requests, with a maximum false positive rate of 2.4%. in the time that this system has been deployed on codeen, robot-related abuse complaints have dropped by a factor of 10.
structured and unstructured overlays under the microscope: a measurement-based view of two p2p systems that people use. existing peer-to-peer systems rely on overlay network protocols for object storage and retrieval and message routing. these overlay protocols can be broadly classified as structured and unstructured - structured overlays impose constraints on the network topology for efficient object discovery, while unstructured overlays organize nodes in a random graph topology that is arguably more resilient to peer population transiency. there is an ongoing discussion on the pros and cons of both approaches. this paper contributes to the discussion a multiple-site, measurement-based study of two operational and widely-deployed file-sharing systems. the two protocols are evaluated in terms of resilience, message overhead, and query performance. we validate our findings and further extend our conclusions through detailed analysis and simulation experiments.
disk drive level workload characterization. in this paper, we present a characterization of disk drive workloads measured in systems representing the enterprise, desktop, and consumer electronics environments. we observe that the common characteristics across all traces are disk drive idleness and workload burstiness. our analysis shows that the majority of characteristics, including request disk arrival rate, response time, service time, write performance, and request size, are environment dependent. however, characteristics such as read/write ratio and access pattern are application dependent.
understanding and addressing blocking-induced network server latency. we investigate the origin and components of network server latency under various loads and find that filesystem-related kernel queues exhibit head-of-line blocking, which leads to bursty behavior in event delivery and process scheduling. in turn, these problems degrade the existing fairness and scheduling policies in the operating system, causing requests that could have been served in memory, with low latency, to unnecessarily wait on disk-bound requests. while this batching behavior only mildly affects throughput, it severely degrades latency. this problem manifests itself in fairness and service quality degradation, a phenomenon we call service inversion. we show a portable solution that avoids these problems without kernel or filesystem modifications, we modify two different web servers to use this approach, and demonstrate a qualitatively different change in their latency profiles, generating more than an order of magnitude reduction in latency. the resulting systems are able to serve most requests without being tied to disk performance, and they scale better with improvements in processor speed. these results are not dependent on server software architecture, and can be profitably applied to experimental and production servers.
lads: large-scale automated ddos detection system. many denial of service attacks use brute-force bandwidth flooding of intended victims. such volume-based attacks aggregate at a target's access router, suggesting that (i) detection and mitigation are best done by providers in their networks; and (ii) attacks are most readily detectable at access routers, where their impact is strongest. in-network detection presents a tension between scalability and accuracy. specifically, accuracy of detection dictates fine grained traffic monitoring, but performing such monitoring for the tens or hundreds of thousands of access interfaces in a large provider network presents serious scalability issues. we investigate the design space for in-network ddos detection and propose a triggered, multi-stage approach that addresses both scalability and accuracy. our contribution is the design and implementation of lads (large-scale automated ddos detection system). the attractiveness of this system lies in the fact that it makes use of data that is readily available to an isp, namely, snmp and netflow feeds from routers, without dependence on proprietary hardware solutions. we report our experiences using lads to detect ddos attacks in a tier-1 isp.
smart: an integrated multi-action advisor for storage systems. the designers of clustered file systems, storage resource management software and storage virtualization devices are trying to provide the necessary planning functionality in their products to facilitate the invocation of the appropriate corrective actions in order to satisfy user specified service level objectives (slos). however, most existing approaches only perform planning for a single type of action such as workload throttling, or data migration, or addition of new resources. as will be shown in this paper, single action based plans are not always cost effective. in this paper we present a framework smart that considers multiple types of corrective actions in an integrated manner and generates a combined corrective action schedule. furthermore, often times, the best cost-effective schedule for a one-week lookahead could be different from the best cost-effective schedule for a one-year lookahead. an advantage of the smart framework is that it considers this lookahead time window in coming up with its corrective action schedules. finally, another key advantage of this framework is that it has a built-in mechanism to handle unexpected surges in workloads. we have implemented our framework and algorithm as part of a clustered file system and performed various experiments to show the benefits of our approach.
fast transparent migration for virtual machines. this paper describes the design and implementation of a system that uses virtual machine technology [1] to provide fast, transparent application migration. this is the first system that can migrate unmodified applications on unmodified mainstream intel x86-based operating system, including microsoft windows, linux, novell netware and others. neither the application nor any clients communicating with the application can tell that the application has been migrated. experimental measurements show that for a variety of workloads, application downtime caused by migration is less than a second.
analysis and evolution of journaling file systems. we develop and apply two new methods for analyzing file system behavior and evaluating file system changes. first, semantic block-level analysis (sba) combines knowledge of on-disk data structures with a trace of disk traffic to infer file system behavior; in contrast to standard benchmarking approaches, sba enables users to understand why the file system behaves as it does. second, semantic trace playback (stp) enables traces of disk traffic to be easily modified to represent changes in the file system implementation; in contrast to directly modifying the file system, stp enables users to rapidly gauge the benefits of new policies. we use sba to analyze linux ext3, reiserfs, jfs, and windows ntfs; in the process, we uncover many strengths and weaknesses of these journaling file systems. we also apply stp to evaluate several modifications to ext3, demonstrating the benefits of various optimizations without incurring the costs of a real implementation.
reclaiming network-wide visibility using ubiquitous endsystem monitors. network-centric tools like netflow and security systems like idses provide essential data about the availability, reliability, and security of network devices and applications. however, the increased use of encryption and tunnelling has reduced the visibility of monitoring applications into packet headers and payloads (e.g. 93% of traffic on our enterprise network is ipsec encapsulated). the result is the inability to collect the required information using network-only measurements. to regain the lost visibility we propose that measurement systems must themselves apply the end-to-end principle: only endsystems can correctly attach semantics to traffic they send and receive. we present such an end-to-end monitoring platform that ubiquitously records per-flow data and then we show that this approach is feasible and practical using data from our enterprise network.
making scheduling "cool": temperature-aware workload placement in data centers. trends towards consolidation and higher-density computing configurations make the problem of heat management one of the critical challenges in emerging data centers. conventional approaches to addressing this problem have focused at the facilities level to develop new cooling technologies or optimize the delivery of cooling. in contrast to these approaches, our paper explores an alternate dimension to address this problem, namely a systems-level solution to control the heat generation through temperature-aware workload placement. we first examine a theoretic thermodynamic formulation that uses information about steady state hot spots and cold spots in the data center and develop real-world scheduling algorithms. based on the insights from these results, we develop an alternate approach. our new approach leverages the non-intuitive observation that the source of cooling inefficiencies can often be in locations spatially uncorrelated with its manifested consequences; this enables additional energy savings. overall, our results demonstrate up to a factor of two reduction in annual data center cooling costs over location-agnostic workload distribution, purely through software optimizations without the need for any costly capital investment.
drive-thru: fast, accurate evaluation of storage power management. running traces of realistic user activity is an important step in evaluating storage power management. unfortunately, existing methodologies that replay traces as fast as possible on a live system cannot be used to evaluate timeout-based power management policies. other methodologies that slow down replay to preserve the recorded delays between operations are too time-consuming. we propose a hybrid approach, called drive-thru, that provides both accuracy and speed of evaluation by separating time-dependent and time-independent activity. we first synchronously replay file system activity on the target platform to create a base trace that captures the semantic relationship between file system activity and storage accesses. we then use the base trace as input to a simulator that can evaluate different disk, network, file cache, and file system power management policies. we use drive-thru to study the benefit of several recent proposals to reduce file system energy usage.
grave robbers from outer space: using 9p2000 under linux. this paper describes the implementation and use of the plan 9 distributed resource protocol 9p under the linux 2.6 operating system. the use of the 9p protocol along with the recent addition of private name spaces to the 2.6 kernel creates a foundation for seamless distributed computing using linux. we review the design principles and benefits of plan 9 distributed systems, go over the basics of the 9p protocol, describe 9p extensions to better support unix® file systems, and show some example linux distributed applications using 9p to provide system and application services. we conclude by providing a performance analysis of the protocol versus nfs for sharing a static file system.
addressing email loss with suremail: measurement, design, and evaluation. we consider the problem of silent email loss in the internet, where neither the sender nor the intended recipient is notified of the loss. our detailed measurement study over several months shows a silent email loss rate of 0.71% to 1.02%. the silent loss of an important email can impose a high cost on users. we further show that spam filtering can be the significant cause of silent email loss, but not the sole cause. suremail augments the existing smtp-based email infrastructure with a notification system to make intended recipients aware of email they are missing. a notification is a short, fixed-format fingerprint of an email, constructed so as to preserve sender and recipient privacy, and prevent spoofing by spammers. suremail is designed to be usable immediately by users without requiring the cooperation of their email providers, so it leaves the existing email infrastructure (including anti-spam infrastructure) untouched and does not require a pki for email users. it places minimal demands on users, by automating the tasks of generating, retrieving, and verifying notifications. it alerts users only when there is actual email loss. our prototype implementation demonstrates the effectiveness of suremail in notifying recipients upon email loss.
providing dynamic update in an operating system. dynamic update is a mechanism that allows software updates and patches to be applied to a running system without loss of service or down-time. operating systems would benefit from dynamic update, but place unique demands on any implementation of such features. these demands stem from the event-driven nature of operating systems, from their restricted run-time execution environment, and from their role in simultaneously servicing multiple clients. we have implemented a dynamic update mechanism in the k42 research operating system, and tested it using previous modifications of the system by kernel developers. our system supports updates changing both kernel code and data structures. in this paper we identify requirements needed to provide a dynamically updatable operating system, describe our implementation, and present our experiences in designing and using the dynamic update mechanism. we also discuss its applicability to other operating systems.
group ratio round-robin: o(1) proportional share scheduling for uniprocessor and multiprocessor systems. we present group ratio round-robin (gr3), the first proportional share scheduler that combines accurate proportional fairness scheduling behavior with o(1) scheduling overhead on both uniprocessor and multiprocessor systems. gr3 uses a simple grouping strategy to organize clients into groups of similar processor allocations which can be more easily scheduled. using this strategy, gr3 combines the benefits of low overhead round-robin execution with a novel ratio-based scheduling algorithm. gr3 introduces a novel frontlog mechanism and weight readjustment algorithm to operate effectively on multiprocessors. gr3 provides fairness within a constant factor of the ideal generalized processor sharing model for client weights with a fixed upper bound and preserves its fairness properties on multiprocessor systems. we have implemented gr3 in linux and measured its performance. our experimental results show that gr3 provides much lower scheduling overhead and much better scheduling accuracy than other schedulers commonly used in research and practice.
server network scalability and tcp offload. server network performance is increasingly dominated by poorly scaling operations such as i/o bus crossings, cache misses and interrupts. their overhead prevents performance from scaling even with increased cpu, link or i/o bus bandwidths. these operations can be reduced by redesigning the host/adapter interface to exploit additional processing on the adapter. offloading processing to the adapter is bene cial not only because it allows more cycles to be applied but also of the changes it enables in the host/adapter interface. as opposed to other approaches such as rdma, tcp offload provides benets without requiring changes to either the transport protocol or api. we have designed a new host/adapter interface that exploits offloaded processing to reduce poorly scaling operations. we have implemented a prototype of the design including both host and adapter software components. experimental evaluation with simple network benchmarks indicates our design significantly reduces i/o bus crossings and holds promise to reduce other poorly scaling operations as well.
attrition defenses for a peer-to-peer digital preservation system. in peer-to-peer systems, attrition attacks include both traditional, network-level denial of service attacks as well as application-level attacks in which malign peers conspire to waste loyal peers' resources. we describe several defenses for the lockss peer-to-peer digital preservation system that help ensure that application-level attrition attacks even from powerful adversaries are less effective than simple network-level attacks, and that network-level attacks must be intense, widespread, and prolonged to impair the system.
surviving internet catastrophes. in this paper, we propose a new approach for designing distributed systems to survive internet catastrophes called informed replication, and demonstrate this approach with the design and evaluation of a cooperative backup system called the phoenix recovery service. informed replication uses a model of correlated failures to exploit software diversity. the key observation that makes our approach both feasible and practical is that internet catastrophes result from shared vulnerabilities. by replicating a system service on hosts that do not have the same vulnerabilities, an internet pathogen that exploits a vulnerability is unlikely to cause all replicas to fail. to characterize software diversity in an internet setting, we measure the software diversity of host operating systems and network services in a large organization. we then use insights from our measurement study to develop and evaluate heuristics for computing replica sets that have a number of attractive features. our heuristics provide excellent reliability guarantees, result in low degree of replication, limit the storage burden on each host in the system, and lend themselves to a fully distributed implementation. we then present the design and prototype implementation of phoenix, and evaluate it on the planetlab testbed.
auto-pilot: a platform for system software benchmarking. when developing software, it is essential to evaluate its performance and stability, making benchmarking an essential and significant part of the software development cycle. benchmarking is also used to show that a system is useful or provide insight into how systems behave. however, benchmarking is a tedious task that few enjoy, but every programmer or systems researcher must do. developers need an easy-to-use system for collecting and analyzing benchmark results. we introduce auto-pilot, a tool for producing accurate and informative benchmark results. auto-pilot provides an infrastructure for running tests, sample test scripts, and analysis tools. auto-pilot is not just another metric or benchmark: it is a system for automating the repetitive tasks of running, measuring, and analyzing the results of arbitrary programs. auto-pilot can run a given test until results stabilize, automatically highlight outlying results, and automatically detect memory leaks. we have used autopilot for over three years on eighteen distinct projects and have found it to be an invaluable tool that saved us significant effort.
sprockets: safe extensions for distributed file systems. sprockets are a lightweight method for extending the functionality of distributed file systems. they specifically target file systems implemented at user level and small extensions that can be expressed with up to several hundred lines of code. each sprocket is akin to a procedure call that runs inside a transaction that is always rolled back on completion, even if sprocket execution succeeds. sprockets therefore make no persistent changes to file system state; instead, they communicate their result back to the core file system through a restricted format using a shared memory buffer. the file system validates the result and makes any necessary changes if the validations pass. sprockets use binary instrumentation to ensure that a sprocket can safely execute file system code without making changes to persistent state. we have implemented sprockets that perform type-specific handling within file systems such as querying application metadata, application-specific conflict resolution, and handling custom devices such as digital cameras. our evaluation shows that sprockets can be up to an order of magnitude faster to execute than extensions that utilize operating system services such as fork. we also show that sprockets allow fine-grained isolation and, thus, can catch some bugs that a fork-based implementation cannot.
a dollar from 15 cents: cross-platform management for internet services. as internet services become ubiquitous, the selection and management of diverse server platforms now affects the bottom line of almost every firm in every industry. ideally, such cross-platform management would yield high performance at low cost, but in practice, the performance consequences of such decisions are often hard to predict. in this paper, we present an approach to guide cross-platform management for real-world internet services. our approach is driven by a novel performance model that predicts application-level performance across changes in platform parameters, such as processor cache sizes, processor speeds, etc., and can be calibrated with data commonly available in today's production environments. our model is structured as a composition of several empirically observed, parsimonious sub-models. these sub-models have few free parameters and can be calibrated with lightweight passive observations on a current production platform. we demonstrate the usefulness of our cross-platform model in two management problems. first, our model provides accurate performance predictions when selecting the next generation of processors to enter a server farm. second, our model can guide platform-aware load balancing across heterogeneous server farms.
bridging the gap between software and hardware techniques for i/o virtualization. the paravirtualized i/o driver domain model, used in xen, provides severl advantages including device driver isolation in a safe execution environment, support for guest vm transparent services including live migration, and hardware independence for guests. however, these advantages currently come at the cost of high cpu overhead which can lead to low throughput for high bandwidth links such as 10 gigabit ethernet. direct i/o has been proposed as the solution to this performance problem but at the cost of removing the benefits of the driver domain model. in this paper we show how to significantly narrow the performance gap by improving the performance of the driver domain model. in particular, we reduce execution costs for conventional nics by 56% on the receive path, and we achieve close to direct i/o performance for network devices supporting multiple hardware receive queues. these results make the xen driver domain model an attractive solution for i/o virtualization for a wider range of scenarios.
cutting corners: workbench automation for server benchmarking. a common approach to benchmarking a server is to measure its behavior under load from a workload generator. often a set of such experiments is required-- perhaps with different server configurations or workload parameters--to obtain a statistically sound result for a given benchmarking objective. this paper explores a framework and policies to conduct such benchmarking activities automatically and efficiently. the workbench automation framework is designed to be independent of the underlying benchmark harness, including the server implementation, configuration tools, and workload generator. rather, we take those mechanisms as given and focus on automation policies within the framework. as a motivating example we focus on rating the peak load of an nfs file server for a given set of workload parameters, a common and costly activity in the storage server industry. experimental results show how an automated workbench controller can plan and coordinate the benchmark runs to obtain a result with a target threshold of confidence and accuracy at lower cost than scripted approaches that are commonly practiced. in more complex benchmarking scenarios, the controller can consider various factors including accuracy vs. cost tradeoffs, availability of hardware resources, deadlines, and the results of previous experiments.
a compacting real-time memory management system. we propose a real real-time memory management system called compact-fit that offers both time and space predictability. compact-fit is a compacting memory management system for allocating, deallocating, and accessing memory in real time. the system provides predictable memory fragmentation and response times that are constant or linear in the size of the request, independently of the global memory state. we present two compact-fit implementations and compare them to established memory management systems, which all fail to provide predictable memory fragmentation. the experiments confirm our theoretical complexity bounds and demonstrate competitive performance. in addition, we can control the performance versus fragmentation trade-off via our concept of partial compaction. the system can be parameterized with the needed level of compaction, improving the performance while keeping memory fragmentation predictable.
using causality to diagnose configuration bugs. we present a novel method for diagnosing configuration management errors. our proposed approach deduces the state of a buggy computer by running predicates that test system correctness and comparing the resulting execution to that generated by running the same predicates on a reference computer. our approach generates signatures that represent the execution path of a predicate by recording the causal dependencies of its execution. our results show that comparisons based on dependency sets significantly outperform comparisons based on predicate success or failure, uniquely identifying the correct bug 86-100% of the time. in the remaining cases, the dependency set method identifies the correct bug as one of two equally likely bugs.
free factories: unified infrastructure for data intensive web services. we introduce the free factory, a platform for deploying data-intensive web services using small clusters of commodity hardware and free software. independently administered virtual machines called freegols give application developers the flexibility of a general purpose web server, along with access to distributed batch processing, cache and storage services. each cluster exploits idle ram and disk space for cache, and reserves disks in each node for high bandwidth storage. the batch processing service uses a variation of the mapreduce model. virtualization allows every cpu in the cluster to participate in batch jobs. each 48-node cluster can achieve 4-8 gigabytes per second of disk i/o. our intent is to use multiple clusters to process hundreds of simultaneous requests on multi-hundred terabyte data sets. currently, our applications achieve 1 gigabyte per second of i/o with 123 disks by scheduling batch jobs on two clusters, one of which is located in a remote data center.
fast, inexpensive content-addressed storage in foundation. foundation is a preservation system for users' personal, digital artifacts. foundation preserves all of a user's data and its dependencies--fonts, programs, plugins, kernel, and configuration state--by archiving nightly snapshots of the user's entire hard disk. users can browse through these images to view old data or recover accidentally deleted files. to access data that a user's current environment can no longer interpret, foundation boots the disk image in which that data resides under an emulator, allowing the user to view and modify the data with the same programs with which the user originally accessed it. this paper describes foundation's archival storage layer, which uses content-addressed storage (cas) to retain nightly snapshots of users' disks indefinitely. current state-of-the-art cas systems, such as venti [34], require multiple high-speed disks or other expensive hardware to achieve high performance. foundation's archival storage layer, in contrast, matches the storage efficiency of venti using only a single usb hard drive. foundation archives disk snapshots at an average throughput of 21 mb/s and restores them at an average of 14 mb/s, more than an order of magnitude improvement over venti running on the same hardware. unlike venti, foundation does not rely on the assumption that sha-1 is collision-free.
power-aware remote replication for enterprise-level disaster recovery systems. electric energy consumed in data centers is rapidly growing. power-aware it, recently called 'green it', is widely recognized as a significant challenge. disk storage is a non-negligible energy consumer. rather, in light of recent data-intensive systems where a number of disk drives are incorporated, the disk storage may be what we must consider primarily. yet, all of the disk drives are not used for primary datasets, but rather larger portion of them are utilized for storing a variety of copies such as backups and snapshots. saving the energy of such storage resources that manage copies is a promising approach. the paper presents a power-aware disaster recovery system, in which the reflection of transferred updated information can be deferred through eager compaction technique. great energy saving of storage systems is expected in the remote secondary site. our experiments using a commercial database system show that 80-85% energy of the secondary-site disk storage can be saved with small penalties of possible service breakdown time.
diverse replication for single-machine byzantine-fault tolerance. new single-machine environments are emerging from abundant computation available through multiple cores and secure virtualization. in this paper, we describe the research challenges and opportunities around diversified replication as a method to increase the byzantine-fault tolerance (bft) of single-machine servers to software attacks or errors. we then discuss the design space of bft protocols enabled by these new environments.
handling flash crowds from your garage. the garage innovator creates new web applications which may rocket to popular success - or sink when the flash crowd that arrives melts the web server. in the web context, utility computing provides a path by which the innovator can, with minimal capital, prepare for overwhelming popularity. many components required for web computing have recently become available as utilities. we analyze the design space of building a load-balanced system in the context of garage innovation. we present six experiments that inform this analysis by highlighting limitations of each approach. we report our experience with three services we deployed in "garage" style, and with the flash crowds that each drew.
idle read after write - iraw. despite a low occurrence rate, silent data corruption represents a growing concern for storage systems designers. throughout the storage hierarchy, from the file system down to the disk drives, various solutions exist to avoid, detect, and correct silent data corruption. undetected errors during the completion of writes may cause silent data corruption. a portion of the write errors may be detected and corrected successfully by verifying the data written on the disk with the data in the disk cache. write verification traditionally is scheduled immediately after a write completion (read after write - raw) which is unattractive, because it degrades user performance. to reduce the performance penalty associated with raw, we propose to retain the written content in the disk cache and verify it once the disk drive becomes idle. although attractive, this approach (called iraw - idle read after write) contends for resources, i.e., cache and idle time, with user traffic and other background activities. in this paper, we present a trace-driven evaluation of iraw and show its feasibility. our analysis indicates that idleness is present in disk drives and can be utilized for write verification with minimal effect on user performance. iraw benefits significantly if some amount of cache, i.e., 1 or 2 mb, is dedicated to retain the unverified writes. if the cache is shared with the user requests then a cache retention policy that places both reads and writes upon completion at the most recently used cache segment, yields best iraw performance without effecting user reads cache hit ratio and overall user performance.
vx32: lightweight user-level sandboxing on the x86. code sandboxing is useful for many purposes, but most sandboxing techniques require kernel modifications, do not completely isolate guest code, or incur substantial performance costs. vx32 is a multipurpose user-level sandbox that enables any application to load and safely execute one or more guest plug-ins, confining each guest to a system call api controlled by the host application and to a restricted memory region within the host's address space. vx32 runs guest code efficiently on several widespread operating systems without kernel extensions or special privileges; it protects the host program from both reads and writes by its guests; and it allows the host to restrict the instruction set available to guests. the key to vx32's combination of portability, flexibility, and efficiency is its use of x86 segmentation hardware to sandbox the guest's data accesses, along with a lightweight instruction translator to sandbox guest instructions. we evaluate vx32 using microbenchmarks and whole system benchmarks, and we examine four applications based on vx32: an archival storage system, an extensible public-key infrastructure, an experimental user-level operating system running atop another host os, and a linux system call jail. the first three applications export custom apis independent of the host os to their guests, making their plug-ins binary-portable across host systems. compute-intensive workloads for the first two applications exhibit between a 30% slowdown and a 30% speedup on vx32 relative to native execution; speedups result from vx32's instruction translator improving the cache locality of guest code. the experimental user-level operating system allows the use of the guest os's applications alongside the host's native applications and runs faster than whole-system virtual machine monitors such as vmware and qemu. the linux system call jail incurs up to 80% overhead but requires no kernel modifications and is delegation-based, avoiding concurrency vulnerabilities present in other interposition mechanisms.
improving ssh-style host authentication with multi-path probing. the popularity of "trust-on-first-use" (tofu) authentication, used by ssh and https with self-signed certificates, demonstrates significant demand for host authentication that is low-cost and simple to deploy. while tofu-based applications are a clear improvement over completely insecure protocols, they can leave users vulnerable to even simple network attacks. our system, perspectives, thwarts many of these attacks by using a collection of "notary" hosts that observes a server's public key via multiple network vantage points (detecting localized attacks) and keeps a record of the server's key over time (recognizing short-lived attacks). clients can download these records on-demand and compare them against an unauthenticated key, detecting many common attacks. perspectives explores a promising part of the host authentication design space: trust-on-first-use applications gain significant attack robustness without sacrificing their ease-of-use. we also analyze the security provided by perspectives and describe our experience building and deploying a publicly available implementation.
confidns: leveraging scale and history to detect compromise. while cooperative dns resolver systems, such as co-dns, have demonstrated improved reliability and performance over standard approaches, their security has been weaker, since any corruption or misbehavior of a single resolver can easily propagate throughout the system. we address this weakness in a new system called confi-dns, which augments the cooperative lookup process with configurable policies that utilize multi-site agreement and per-site lookup histories. not only does confi-dns provide better security than cooperative approaches, but for up to 99.8% of unique lookups, confidns exceeds the security of standard dns resolvers. confidns provides these benefits while retaining the other benefits of codns, such as incremental deployability, higher reliability, and improved performance, in some cases faster than codns.
a tcp-layer name service for tcp ports. this paper presents a simple name service for tcp ports, allowing services to be reached by name instead of number. names are arbitrary byte arrays that are bound to listening ports. name resolutions take place during the tcp three-way handshake, not requiring extra message exchanges. the new tcp handshake conforms with the standard and is fully compatible with existing tcp implementations. a prototype implementation was developed in linux, paying special attention to backward compatibility with legacy systems (kernels and applications). among the many opportunities created by the name service, it allows services with unusual names, known only by small communities, to remain undetected by port scanners (though not by network sniffers).
adaptive file transfers for diverse environments. this paper presents dsync, a file transfer system that can dynamically adapt to a wide variety of environments. while many transfer systems work well in their specialized ontext, their performance comes at the cost of generality, and they perform poorly when used elsewhere. in contrast, dsync adapts to its environment by intelligently determining which of its available resources is the best to use at any given time. the resources dsync can draw from include the sender, the local disk, and network peers. while combining these resources may appear easy, in practice it is difficult because these resources may have widely different performance or contend with each other. in particular, the paper presents a novel mechanism that enables dsync to aggressively search the receiver's local disk for useful data without interfering with concurrent network transfers. our evaluation on several workloads in various network environments shows that dsync outperforms existing systems by a factor of 1.4 to 5 in one-to-one and one-to-many transfers.
a linux implementation validation of track-aligned extents and track-aligned raids. through clean-slate implementation of two storage optimizations--track-aligned extents and track-aligned raids--this paper shows the values of independent validations. the experience revealed many unanticipated disk and storage data path behaviors as potential roadblocks for wide deployment of these optimizations, and also identified implementation issues to retrofit these concepts to legacy data paths.
load shedding in network monitoring applications. monitoring and mining real-time network data streams is crucial for managing and operating data networks. the information that network operators desire to extract from the network traffic is of different size, granularity and accuracy depending on the measurement task (e.g., relevant data for capacity planning and intrusion detection are very different). to satisfy these different demands, a new class of monitoring systems is emerging to handle multiple arbitrary and continuous traffic queries. such systems must cope with the effects of overload situations due to the large volumes, high data rates and bursty nature of the network traffic. in this paper, we present the design and evaluation of a system that can shed excess load in the presence of extreme traffic conditions, while maintaining the accuracy of the traffic queries within acceptable levels. the main novelty of our approach is that it is able to operate without explicit knowledge of the traffic queries. instead, it extracts a set of features from the traffic streams to build an on-line predictionmodel of the query resource requirements. this way the monitoring system preserves a high degree of flexibility, increasing the range of applications and network scenarios where it can be used. we implemented our scheme in an existing network monitoring system and deployed it in a research isp network. our results show that the system predicts the resources required to run each traffic query with errors below 5%, and that it can efficiently handle extreme load situations, preventing uncontrolled packet losses, with minimum impact on the accuracy of the queries' results.
cool job allocation: measuring the power savings of placing jobs at cooling-efficient locations in the data center. data center costs for computer power and cooling are staggering. because certain physical locations inside the data center are more efficient to cool than others, this suggests that allocating heavy computational workloads onto those servers that are in more efficient places might bring substantial savings. this simple idea raises two critical research questions that we address: (1) how should one measure and rank the cooling efficiency of different places in a data center? (2) how substantial is the savings? we performed a set of experiments in a thermally isolated portion of a real data center, and validated that the potential savings is substantial and therefore warrants further work in this area to exploit the savings opportunity.
reboots are for hardware: challenges and solutions to updating an operating system on the fly. patches to modern operating systems, including bug fixes and security updates, and the reboots and downtime they require, cause tremendous problems for system users and administrators. dynamic update allows an operating system to be patched without the need for a reboot or other service interruption. we have taken the approach of building dynamic update functionality directly into an existing operating system, k42. to determine the applicability of our update system, and to investigate the changes that are made to os code, we analysed k42's revision history. the analysis showed that our original system could only support half of the desired changes to k42. the main problem preventing more changes from being converted to dynamic updates was our system's inability to update interfaces. other studies, as well as our own investigations, have shown that change to interfaces is also prevalent in systems such as linux. thus, it is apparent that a dynamic update mechanism needs to handle interface changes to be widely applicable. in this paper, we describe how to support interface changes in a modular dynamic update system. with this improvement, approximately 79% of past performance and bug fix changes to k42 could be converted to dynamic updates, and we expect the proportion would be even higher if the fixes were being developed for dynamic update. measurements of our system show that the runtime overhead is very low, and the time to apply updates is acceptable. this paper makes the following contributions. we present a mechanism to handle interface changes for dynamic updates to an operating system. for performance-sensitive updates, we show how to apply changes lazily. we discuss lessons learned, including how an operating system can be structured to better support dynamic update. we also describe how our approach extends to other systems such as linux, that although structured modularly, are not strictly object-oriented like k42.
exploring recovery from operating system lockups. operating system lockup errors can render a computer unusable by preventing the execution other programs. watchdog timers can be used to recover from a lockup by resetting the processor and rebooting the system when a lockup is detected. this results in a loss of unsaved data in running programs. based on the observation that volatile memory is not affected when a processor a reset occurs, we present an approach to recover from a watchdog reset with minimal or zero loss of application state. we study the resolution of lockup conditions using thread termination and using exception dispatch. thread termination can still result in a usable system and is already used as a recovery strategy for other errors in linux. using exceptions allows developers to write code to handle a lockup within the erroneous thread and attempt application transparent recovery. fault injection experiments show that a significant percentage of lockups can be recovered by thread termination. exception handling further improves the recoverability of the operating system.
hyperion: high volume stream archival for retrospective querying. network monitoring systems that support data archiving and after-the-fact (retrospective) queries are useful for a multitude of purposes, such as anomaly detection and network and security forensics. data archiving for such systems, however, is complicated by (a) data arrival rates, which may be hundreds of thousands of packets per second on a single link, and (b) the need for online indexing of this data to support retrospective queries. at these data rates, both common database index structures and general-purpose file systems perform poorly. this paper describes hyperion, a system for archiving, indexing, and on-line retrieval of high-volume data streams. we employ a write-optimized stream file system for high-speed storage of simultaneous data streams, and a novel use of signature file indexes in a distributed multi-level index. we implement hyperion on commodity hardware and conduct a detailed evaluation using synthetic data and real network traces. our streaming file system, streamfs, is shown to be fast enough to archive traces at over a million packets per second. the index allows queries over hours of data to complete in as little as 10-20 seconds, and the entire system is able to index and archive over 200,000 packets/sec while processing simultaneous on-line queries.
configuration management at massive scale: system design and experience. the development and maintenance of network device configurations is one of the central challenges faced by large network providers. current network management systems fail to meet this challenge primarily because of their inability to adapt to rapidly evolving customer and provider-network needs, and because of mismatches between the conceptual models of the tools and the services they must support. in this paper, we present the presto configuration management system that attempts to address these failings in a comprehensive and flexible way. developed for and deployed over the last 4 years within a large isp network, presto constructs device-native configurations based on the composition of configlets representing different services or service options. configlets are compiled by extracting and manipulating data from external systems as directed by the presto configuration scripting and template language. we outline the configuration management needs of large-scale network providers, introduce the presto system and configuration language, and demonstrate the use, workflows, and ultimately the platform's flexibility via an example of vpn service. we conclude by considering future work and reflect on the operators' experiences with presto.
implementation and performance evaluation of fuzzy file block matching. the fuzzy file block matching technique (fuzzy matching for short), was first proposed for opportunistic use of content addressable storage. fuzzy matching aims to increase the hit ratio in the content-addressable storage providers, and thus can improve the performance of underlying distributed file storage systems by potentially saving significant network bandwidth and reducing file transmission costs. fuzzy matching employs shingling to represent the fuzzy hashing of file blocks for similarity detection, and error-correcting information to reconstruct the canonical content of a file block from some similar blocks. in this paper, we present the implementation details of fuzzy matching and a very basic evaluation of its performance. in particular, we show that fuzzy matching can recover new versions of gnu emacs source from older versions.
from trusted to secure: building and executing applications that enforce system security. commercial operating systems have recently introduced mandatory access controls (mac) that can be used to ensure system-wide data confidentiality and integrity. these protections rely on restricting the flow of information between processes based on security levels. the problem is, there are many applications that defy simple classification by security level, some of them essential for system operation. surprisingly, the common practice among these operating systems is simply to mark these applications as "trusted", and thus allow them to bypass label protections. this compromise is not a limitation of mac or the operating system services that enforce it, but simply a fundamental inability of any operating system to reason about how applications treat sensitive data internally--and thus the os must either restrict the data that they receive or trust them to handle it correctly. these practices were developed prior to the advent security-typed languages. these languages provide a means of reasoning about how the os's sensitive data is handled within applications. thus, applications can be shown to enforce system security by guaranteeing, in advance of execution, that they will adhere to the os's mac policy. in this paper, we provide an architecture for an operating system service, that integrate security-typed language with operating system mac services. we have built an implementation of this service, called siesta, which handles applications developed in the security-typed language, jif, running on the selinux operating system. we also provide some sample applications to demonstrate the security, flexibility and efficiency of our approach.
safestore: a durable and practical storage system. this paper presents safestore, a distributed storage system designed to maintain long-term data durability despite conventional hardware and software faults, environmental disruptions, and administrative failures caused by human error or malice. the architecture of safestore is based on fault isolation, which safe-store applies aggressively along administrative, physical, and temporal dimensions by spreading data across autonomous storage service providers (ssps). however, current storage interfaces provided by ssps are not designed for high end-to-end durability. in this paper, we propose a new storage system architecture that (1) spreads data efficiently across autonomous ssps using informed hierarchical erasure coding that, for a given replication cost, provides several additional 9's of durability over what can be achieved with existing black-box ssp interfaces, (2) performs an efficient end-to-end audit of ssps to detect data loss that, for a 20% cost increase, improves data durability by two 9's by reducing mttr, and (3) offers durable storage with cost, performance, and availability competitive with traditional storage systems. we instantiate and evaluate these ideas by building a safestore-based file system with an nfs-like interface.
events can make sense. tame is a new event-based system for managing concurrency in network applications. code written with tame abstractions does not suffer from the "stack-ripping" problem associated with other event libraries. like threaded code, tamed code uses standard control flow, automatically-managed local variables, and modular interfaces between callers and callees. tame's implementation consists of c++ libraries and a source-to-source translator; no platform-specific support or compiler modifications are required, and tame induces little runtime overhead. experience with tame in real-world systems, including a popular commercial web site, suggests it is easy to adopt and deploy.
a memory soft error measurement on production systems. memory state can be corrupted by the impact of particles causing single-event upsets (seus). understanding and dealing with these soft (or transient) errors is important for system reliability. several earlier studies have provided field test measurement results on memory soft error rate, but no results were available for recent production computer systems. we believe the measurement results on real production systems are uniquely valuable due to various environmental effects. this paper presents methodologies for memory soft error measurement on production systems where performance impact on existing running applications must be negligible and the system administrative control might or might not be available. we conducted measurements in three distinct system environments: a rack-mounted server farm for a popular internet service (ask.com search engine), a set of office desktop computers (univ. of rochester), and a geographically distributed network testbed (planetlab). our preliminary measurement on over 300 machines for varying multi-month periods finds 2 suspected soft errors. in particular, our result on the internet servers indicates that, with high probability, the soft error rate is at least two orders of magnitude lower than those reported previously. we provide discussions that attribute the low error rate to several factors in today's production system environments. as a contrast, our measurement unintentionally discovers permanent (or hard) memory faults on 9 out of 212 ask.com machines, suggesting the relative commonness of hard memory faults.
mapjax: data structure abstractions for asynchronous web applications. the current approach to developing rich, interactive web applications relies on asynchronous rpcs (remote procedure calls) to fetch new data to be displayed by the client. we argue that for the majority of web applications, this rpc-based model is not the correct abstraction: it forces programmers to use an awkward continuation-passing style of programming and to expend too much effort manually transferring data. we propose a new programming model, mapjax, to remedy these problems. mapjax provides the abstraction of data structures shared between the browser and the server, based on the familiar primitives of objects, locks, and threads. mapjax also provides additional features (parallel for loops and prefetching) that help developers minimize response times in their applications. map-jax thus allows developers to focus on what they do best-writing compelling applications-rather than worrying about systems issues of data transfer and callback management. we describe the design and implementation of the mapjax framework and show its use in three prototypical web applications: a mapping application, an email client, and a search-autocomplete application. we evaluate the performance of these applications under realistic internet latency and bandwidth constraints and find that the unoptimized mapjax versions perform comparably to the standard ajax versions, while mapjax performance optimizations can dramatically improve performance, by close to a factor of 2 relative to non-mapjax code in some cases.
supporting practical content-addressable caching with czip compression. content-based naming (cbn) enables content sharing across similar files by breaking files into position-independent chunks and naming these chunks using hashes of their contents. while a number of research systems have recently used custom cbn approaches internally to good effect, there has not yet been any mechanism to use cbn in a general-purposeway. in this paper, we demonstrate a practical approach to applying cbn without requiring disruptive changes to end systems. we develop czip, a cbn compression scheme which reduces data sizes by eliminating redundant chunks, compresses chunks using existing schemes, and facilitates sharing within files, across files, and across machines by explicitly exposing cbn chunk hashes. czip-aware caching systems can exploit the cbn information to reduce storage space, reduce bandwidth consumption, and increase performance, while content providers and middleboxes can selectively encode their most suitable content. we show that czip compares well to stand-alone compression schemes, that a cbn cache for czip is easily implemented, and that a czip-aware cdn produces significant benefits.
evaluating block-level optimization through the io path. this paper focuses on evaluation of the effectiveness of optimization at various layers of the io path, such as the file system, the device driver scheduler, and the disk drive itself. io performance is enhanced via effective block allocation at the file system, request merging and reordering at the device driver, and additional complex request reordering at the disk drive. our measurements show that effective combination of these optimization forms yields superior performance under specific workloads. in particular, the impact on io performance of technological advances in modern disk drives (i.e., reduction on head positioning times and deployment of complex request scheduling) is shown. for example, if the outstanding requests in the io subsystem can all be accommodated by the disk queue buffer then disk level request scheduling is as effective as to close any gaps in the performance between io request schedulers at the device driver level. even more, for disk drives with write through caches, large queue depths improve overall io throughput and when combined with the best performing disk scheduling algorithm at the device driver level, perform comparably with an io subsystem where disks have write-back caches.
dandelion: cooperative content distribution with robust incentives. content distribution via the internet is becoming increasingly popular. to be cost-effective, commercial content providers are considering the use of peer-to-peer (p2p) protocols such as bittorrent to save on bandwidth costs and to handle peak demands. however, when an online content provider uses a p2p protocol, it faces a crucial issue: how to incentivize its clients to upload to their peers. this paper presents dandelion, a system designed to address this issue in the case of paid content distribution. unlike previous solutions, most notably bittorrent, dandelion provides robust (provably non-manipulable) incentives for clients to upload to others. in addition, unlike systems with tit-for-tat-based incentives, a client is motivated to upload to its peers even if the peers do not have content that interests the client. a client that honestly uploads to its peers is rewarded with credit, which can be redeemed for various types of rewards, such as discounts on paid content. in designing dandelion, we trade scalability for the ability to provide robust incentives. the evaluation of our prototype system on planetlab demonstrates the viability of our approach. a dandelion server that runs on commodity hardware with a moderate access link is capable of supporting up to a few thousand clients. these clients can download content at rates comparable to those of bittorrent clients.
energy management for hypervisor-based virtual machines. current approaches to power management are based on operating systems with full knowledge of and full control over the underlying hardware; the distributed nature of multi-layered virtual machine environments renders such approaches insufficient. in this paper, we present a novel framework for energy management in modular, multi-layered operating system structures. the framework provides a unified model to partition and distribute energy, and mechanisms for energy-aware resource accounting and allocation. as a key property, the framework explicitly takes the recursive energy consumption into account, which is spent, e.g., in the virtualization layer or subsequent driver components. our prototypical implementation targets hypervisor-based virtual machine systems and comprises two components: a host-level subsystem, which controls machine-wide energy constraints and enforces them among all guest oses and service components, and, complementary, an energy-aware guest operating system, capable of fine-grained application-specific energy management. guest level energy management thereby relies on effective virtualization of physical energy effects provided by the virtual machine monitor. experiments with cpu and disk devices and an external data acquisition system demonstrate that our framework accurately controls and stipulates the power consumption of individual hardware devices, both for energy-aware and energyunaware guest operating systems.
potshards: secure long-term storage without encryption. users are storing ever-increasing amounts of information digitally, driven by many factors including government regulations and the public's desire to digitally record their personal histories. unfortunately, many of the security mechanisms that modern systems rely upon, such as encryption, are poorly suited for storing data for indefinitely long periods of time--it is very difficult to manage keys and update cryptosystems to provide secrecy through encryption over periods of decades. worse, an adversary who can compromise an archive need only wait for cryptanalysis techniques to catch up to the encryption algorithm used at the time of the compromise in order to obtain "secure" data. to address these concerns, we have developed potshards, an archival storage system that provides long-term security for data with very long lifetimes without using encryption. secrecy is achieved by using provably secure secret splitting and spreading the resulting shares across separately-managed archives. providing availability and data recovery in such a system can be difficult; thus, we use a new technique, approximate pointers, in conjunction with secure distributed raid techniques to provide availability and reliability across independent archives. to validate our design, we developed a prototype potshards implementation, which has demonstrated "normal" storage and retrieval of user data using indexes, the recovery of user data using only the pieces a user has stored across the archives and the reconstruction of an entire failed archive.
passwords for everyone: secure mnemonic-based accessible authentication. in many environments, a computer system is severely constrained to the extent that the practical input mechanisms are merely binary switches. requiring the user to remember a long random bit string and to authenticate by entering each bit in the available binary input mechanism, is completely impractical. this paper deals with the question of authentication in such environments where the inputs are constrained to be yes/no responses to statements displayed on the user's screen. we present passwit, a mnemonic-based system for such environments that combines good usability with high security, and has many additional features such as (to mention a few) resistance to phishing, keystroke-logging, and compatibility with currently deployed systems and password file formats (hence it can co-exist with existing login mechanisms).
wresting control from bgp: scalable fine-grained route control. today's internet users and applications are placing increased demands on internet service providers (isps) to deliver fine-grained, flexible route control. to assist network operators in addressing this challenge, we present the intelligent route service control point (irscp), a route control architecture that allows a network operator to flexibly control routing between the traffic ingresses and egresses within an isp's network, without modifying the isp's existing routers. in essence, irscp subsumes the control plane of an isp's network by replacing the distributed bgp decision process of each router in the network with a more flexible, logically centralized, appliction-controlled route computation. irscp supplements the traditional bgp decision process with an explicitly ranked decision process that allows route control applications to provide a per-destination, per-router explicit ranking of traffic egresses. we describe our implementation of irscp as well as a straightforward set of correctness requirements that prevents routing anomalies. to illustrate the potential of application-controlled route selection, we use our irscp prototype to implement a simple form of dynamic customer-traffic load balancing, and demonstrate through emulation that our implementation is scalable.
a comparison of structured and unstructured p2p approaches to heterogeneous random peer selection. random peer selection is used by numerous p2p applications; examples include application-level multicast, unstructured file sharing, and network location mapping. in most of these applications, support for a heterogeneous capacity distribution among nodes is desirable: in other words, nodes with higher capacity should be selected proportionally more often. random peer selection can be performed over both structured and unstructured graphs. this paper compares these two basic approaches using a candidate example from each approach. for unstructured heterogeneous random peer selection, we use swaplinks, from our previous work. for the structured approach, we use the bamboo dht adapted to heterogeneous selection using our extensions to the item-balancing technique by karger and ruhl. testing the two approaches over graphs of 1000 nodes and a range of network churn levels and heterogeneity distributions, we show that swaplinks is the superior random selection approach: (i) swaplinks enables more accurate random selection than does the structured approach in the presence of churn, and (ii) the structured approach is sensitive to a number of hard-to-set tuning knobs that affect performance, whereas swaplinks is essentially free of such knobs.
virtually shared displays and user input devices. this paper proposes making displays and input devices as first-class citizens in a networked system environment for collaborative applications. the paper describes a virtually shared model that enables users to use remote displays as extensions of their local displays and to allow multiple users to use multiple cursors and keyboards to input and control shared applications and their windows simultaneously. we have implemented a prototype system and deployed it to three doe fusion control rooms. the implementation performs well on today's hardware and our user feedbacks show that such a paradigm can substantially improve information sharing.
using provenance to aid in personal file search. as the scope of personal data grows, it becomes increasingly difficult to find what we need when we need it. desktop search tools provide a potential answer, but most existing tools are incomplete solutions: they index content, but fail to capture dynamic relationships from the user's context. one emerging solution to this is context-enhanced search, a technique that reorders and extends the results of content-only search using contextual information. within this framework, we propose using strict causality, rather than temporal locality, the current state of the art, to direct contextual searches. causality more accurately identifies data flow between files, reducing the false-positives created by context-switching and background noise. further, unlike previous work, we conduct an online user study with a fully-functioning implementation to evaluate user-perceived search quality directly. search results generated by our causality mechanism are rated a statistically-significant 17% higher on average over all queries than by using content-only search or context-enhanced search with temporal locality.
from stem to sead: speculative execution for automated defense. most computer defense systems crash the process that they protect as part of their response to an attack. although recent research explores the feasibility of self-healing to automatically recover from an attack, self-healing faces some obstacles before it can protect legacy applications and cots (commercial off-the-shelf) software. besides the practical issue of not modifying source code, self-healing must know both when to engage and how to guide a repair. previous work on a self-healing system, stem, left these challenges as future work. this paper improves stem's capabilities along three lines to provide practical speculative execution for automated defense (sead). first, stem is now applicable to cots software: it does not require source code, and it imposes a roughly 73% performance penalty on apache's normal operation. second, we introduce repair policy to assist the healing process and improve the semantic correctness of the repair. finally, stem can create behavior profiles based on aspects of data and control flow.
diskseen: exploiting disk layout and access history to enhance i/o prefetch. current disk prefetch policies in major operating systems track access patterns at the level of the file abstraction. while this is useful for exploiting application-level access patterns, file-level prefetching cannot realize the full performance improvements achievable by prefetching. there are two reasons for this. first, certain prefetch opportunities can only be detected by knowing the data layout on disk, such as the contiguous layout of file metadata or data from multiple files. second, nonsequential access of disk data (requiring disk head movement) is much slower than sequential access, and the penalty for mis-prefetching a 'random' block, relative to that of a sequential block, is correspondingly more costly. to overcome the inherent limitations of prefetching at the logical file level, we propose to perform prefetching directly at the level of disk layout, and in a portable way. our technique, called diskseen, is intended to be supplementary to, and to work synergistically with, file-level prefetch policies, if present. diskseen tracks the locations and access times of disk blocks, and based on analysis of their temporal and spatial relationships, seeks to improve the sequentiality of disk accesses and overall prefetching performance. our implementation of the diskseen scheme in the linux 2.6 kernel shows that it can significantly improve the effectiveness of prefetching, reducing execution times by 20%-53% for micro-benchmarks and real applications such as grep, cvs, and tpc-h.
supporting multiple oses with os switching. people increasingly put more than one oses into their computers and devices like mobile phones. multiboot and virtualization are two common technologies for this purpose. in this paper we promote a new approach called os switching. with os switching, multiple oses timeshare the same computer cooperatively. a typical implementation can reuse an os's suspend/resume functionality with little modification. the os switching approach promises fast native execution speed with shorter switching time than traditional multi-boot approach. we describe the design of os switching as well as our implementation with linux and wince, and evaluate its performance.
dynamic spyware analysis. spyware is a class of malicious code that is surreptitiously installed on victims' machines. once active, it silently monitors the behavior of users, records their web surfing habits, and steals their passwords. current anti-spyware tools operate in a way similar to traditional virus scanners. that is, they check unknown programs against signatures associated with known spyware instances. unfortunately, these techniques cannot identify novel spyware, require frequent updates to signature databases, and are easy to evade by code obfuscation. in this paper, we present a novel dynamic analysis approach that precisely tracks the flow of sensitive information as it is processed by the web browser and any loaded browser helper objects. using the results of our analysis, we can identify unknown components as spyware and provide comprehensive reports on their behavior. the techniques presented in this paper address limitations of our previouswork on spyware detection and significantly improve the quality and richness of our analysis. in particular, our approach allows a human analyst to observe the actual flows of sensitive data in the system. based on this information, it is possible to precisely determine which sensitive data is accessed and where this data is sent to. to demonstrate the effectiveness of the detection and the comprehensiveness of the generated reports, we evaluated our system on a substantial body of spyware and benign samples.
flexvol: flexible, efficient file volume virtualization in wafl. virtualization is a well-known method of abstracting physical resources and of separating the manipulation and use of logical resources from their underlying implementation. we have used this technique to virtualize file volumes in the wafl® file system, adding a level of indirection between client-visible volumes and the underlying physical storage. the resulting virtual file volumes, or flexvol® volumes, are managed independent of lower storage layers. multiple volumes can be dynamically created, deleted, resized, and reconfigured within the same physical storage container. we also exploit this new virtualization layer to provide several powerful new capabilities. we have enhanced snapmirror®, a tool for replicating volumes between storage systems, to remap storage allocation during transfer, thus optimizing disk layout for the destination storage system. flexclone® volumes provide writable snapshot® copies, using a flexvol volume backed by a snapshot copy of a different volume. flexvol volumes also support thin provisioning; a flexvol volume can have a logical size that exceeds the available physical storage. flexclone volumes and thin provisioning are a powerful combination, as they allow the creation of light-weight copies of live data sets while consuming minimal storage resources. we present the basic architecture of flexvol volumes, including performance optimizations that decrease the overhead of our new virtualization layer. we also describe the new features enabled by this architecture. our evaluation of flexvol performance shows that it incurs only a minor performance degradation compared with traditional, nonvirtualized wafl volumes. on the industry-standard spec sfs benchmark, flexvol volumes exhibit less than 4% performance overhead, while providing all the benefits of virtualization.
design tradeoffs for ssd performance. solid-state disks (ssds) have the potential to revolutionize the storage system landscape. however, there is little published work about their internal organization or the design choices that ssd manufacturers face in pursuit of optimal performance. this paper presents a taxonomy of such design choices and analyzes the likely performance of various configurations using a trace-driven simulator and workload traces extracted from real systems. we find that ssd performance and lifetime is highly workload-sensitive, and that complex systems problems that normally appear higher in the storage stack, or even in distributed systems, are relevant to device firmware.
prefetching with adaptive cache culling for striped disk arrays. conventional prefetching schemes regard prediction accuracy as important because useless data prefetched by a faulty prediction may pollute the cache. if prefetching requires considerably low read cost but the prediction is not accurate, it may or may not be beneficial depending on the situation. however, the problem of low prediction accuracy can be dramatically reduced if we efficiently manage prefetched data by considering the total hit rate for both prefetched data and cached data. to achieve this goal, we propose an adaptive strip prefetching (asp) scheme, which provides low prefetching cost and evicts prefetched data at the proper time by using differential feedback that maximizes the hit rate of both prefetched data and cached data in a given cache management scheme. additionally, asp controls prefetching by using an online disk simulation that investigates whether prefetching is beneficial for the current workloads and stops prefetching if it is not. finally, asp provides methods that resolve both independency loss and parallelism loss that may arise in striped disk arrays. we implemented a kernel module in linux version 2.6.18 as a raid-5 driver with our scheme, which significantly outperforms the sequential prefetching of linux from several times to an order of magnitude in a variety of realistic workloads.
protection strategies for direct access to virtualized i/o devices. commodity virtual machine monitors forbid direct access to i/o devices by untrusted guest operating systems in order to provide protection and sharing. however, both i/o memory management units (iommus) and recently proposed software-based methods can be used to reduce the overhead of i/o virtualization by providing untrusted guest operating systems with safe, direct access to i/o devices. this paper explores the performance and safety tradeoffs of strategies for using these mechanisms. the protection strategies presented in this paper provide equivalent inter-guest protection among operating system instances. however, they provide varying levels of intra-guest protection from driver software and incur varying levels of overhead. a simple direct-map strategy incurs the least overhead, providing native-level performance but offering no enhanced protection from misbehaving device drivers within the guest operating system. additional protection against guest drivers can be achieved by limiting iommu page-table mappings to memory buffers that are actually used in i/o transfers. furthermore, the cost incurred by this limitation can be minimized by aggressively reusing these mappings. surprisingly, a software-only strategy that does not use an iommu at all performs competitively, and sometimes better than, hardware-based strategies while maintaining strict inter-guest isolation.
wide-scale data stream management. this paper describes mortar, a distributed stream processing platform for building very large queries across federated systems (enterprises, grids, datacenters, testbeds). nodes in such systems can be queried for distributed debugging, application control and provisioning, anomaly detection, and measurement. we address the primary challenges of managing continuous queries that have thousands of wide-area sources that may periodically be down, disconnected, or overloaded, e.g., multiple data centers filled with cheap pcs, internet testbeds such as planetlab, or country-wide sensor installations. mortar presents a clean-slate design for best-effort in-network processing. for each query, it builds multiple, static overlays and leverages the union of overlay paths to provide resilient query installation and data routing. further, a unique data management scheme mitigates the impact of clock skew on distributed stream processing, reducing result latency by a factor of 8, and allows users to specify custom in-network operators that transparently benefit from multipath routing. when compared to a contemporary distributed snapshot querying substrate, mortar uses a fifth of the bandwidth while providing increased query resolution, responsiveness, and accuracy during failures.
evaluating distributed systems: does background traffic matter? evaluating novel networked protocols and services requires subjecting the target system to realistic internet conditions. however, there is no common understanding of what is required to capture such realism. conventional wisdom suggests that competing background traffic will influence service and protocol behavior. once again however, there is no understanding of what aspects of background traffic are important and the extent to which services are sensitive to these characteristics. earlier work shows that internet traffic demonstrates significant burstiness at a range of time scales. unfortunately, existing systems evaluations either do not consider background traffic or employ simple synthetic models, e.g., based on poisson arrivals, that do not capture these burstiness properties. in this paper, we show that realistic background traffic, has qualitatively different impact on application and protocol behavior than simple traffic models. one conclusion from our work is that applications should be evaluated under a range of background traffic characteristics to determine the relative merits of applications and to understand behavior in corner cases of live deployment.
context-aware mechanisms for reducing interactive delays of energy management in disks. aggressive energy conserving mechanisms can maximize energy efficiency, but often have the negative trade-off of simultaneously reducing system responsiveness due to the switching of component power modes. this side-effect is especially prominent in hard disk drives, where the time required to switch power modes is dictated by the latency of the mechanical elements of the drive. existing disk activity prediction schemes provide solutions for eliminating transition delays in the presence of non-interactive applications and processes, but perform poorly on systems dominated by interactive applications. the key idea in eliminating transition delays exposed to users in interactive applications is that the users are responsible for placing energy and performance demand on the systems through interactions with applications. therefore, monitoring user interactions with applications provides an opportunity for predicting upcoming power mode transitions and, as a result, eliminating the delays associated with these transitions. in this paper, we propose a set of user behavior monitoring and prediction mechanisms that significantly reduce delays in interactive applications while minimizing energy consumption.
large-scale virtualization in the emulab network testbed. network emulation is valuable largely because of its ability to study applications running on real hosts and "somewhat real" networks. however, conservatively allocating a physical host or network link for each corresponding virtual entity is costly and limits scale. we present a system that can faithfully emulate, on low-end pcs, virtual topologies over an order of magnitude larger than the physical hardware, when running typical classes of distributed applications that have modest resource requirements. this version of emulab virtualizes hosts, routers, and networks, while retaining near-total application transparency, good performance fidelity, responsiveness suitable for interactive use, high system throughput, and efficient use of resources. our key design techniques are to use the minimum degree of virtualization that provides transparency to applications, to exploit the hierarchy found in real computer networks, to perform optimistic automated resource allocation, and to use feed-back to adaptively allocate resources. the entire system is highly automated, making it easy to use even when scaling to more than a thousand virtual nodes. this paper identifies the many problems posed in building a practical system, and describes the system's motivation, design, and preliminary evaluation.
remote profiling of resource constraints of web servers using mini-flash crowds. unexpected surges in web request traffic can exercise server-side resources (e.g., access bandwidth, processing, storage etc.) in undesirable ways. administrators today do not have requisite tools to understand the impact of such "flash crowds" on their servers. most web servers either rely on over-provisioning and admission control, or use potentially expensive solutions like cdns, to ensure high availability in the face of flash crowds. a more fine-grained understanding of the performance of individual server resources under emulated but realistic and controlled flash crowd-like conditions can aid administrators to make more efficient resource management decisions. in this paper, we present miniflash crowds (mfc) - a light-weight profiling service that reveals resource bottlenecks in a web server infrastructure. mfc uses a set of controlled probes where an increasing number of distributed clients make synchronized requests that exercise specific resources or portions of a remote web server. we carried out controlled lab-based tests and experiments in collaboration with operators of production servers. we show that our approach can faithfully track the impact of request loads on different server resources and provide useful insights to server operators on the constraints of different components of their infrastructure. we also present results from a measurement study of the provisioning of several hundred popular web servers, a few hundred web servers of startup companies, and about hundred phishing servers.
context-aware prefetching at the storage server . in many of today's applications, access to storage constitutes the major cost of processing a user request. data prefetching has been used to alleviate the storage access latency. under current prefetching techniques, the storage system prefetches a batch of blocks upon detecting an access pattern. however, the high level of concurrency in today's applications typically leads to interleaved block accesses, which makes detecting an access pattern a very challenging problem. towards this, we propose and evaluate quickmine, a novel, lightweight and minimally intrusive method for contextaware prefetching. under quickmine, we capture application contexts, such as a transaction or query, and leverage them for context-aware prediction and improved prefetching effectiveness in the storage cache. we implement a prototype of our context-aware prefetching algorithm in a storage-area network (san) built using network block device (nbd). our prototype shows that context-aware prefetching clearly out-performs existing context-oblivious prefetching algorithms, resulting in factors of up to 2 improvements in application latency for two e-commerce workloads with repeatable access patterns, tpc-w and rubis.
optimizing tcp receive performance. the performance of receive side tcp processing has traditionally been dominated by the cost of the 'per-byte' operations, such as data copying and checksumming. we show that architectural trends in modern processors, in particular aggressive prefetching, have resulted in a fundamental shift in the relative overheads of per-byte and per-packet operations in tcp receive processing, making per-packet operations the dominant source of overhead. motivated by this architectural trend, we present two optimizations, receive aggregation and acknowledgment offload, that improve the receive side tcp performance by reducing the number of packets that need to be processed by the tcp/ip stack. our optimizations are similar in spirit to the use of tcp segment offload (tso) for improving transmit side performance, but without need for hardware support. with these optimizations, we demonstrate performance improvements of 45-67% for receive processing in native linux, and of 86% for receive processing in a linux guest operating system running on xen.
experiences with client-based speculative remote display. we propose an approach to remote display systems in which the client predicts the screen update events that the server will send and applies them to the screen immediately, thus eliminating the network round-trip time and making the system more responsive in a wide-area or high loss environment. incorrectly predicted events are undone when the actual events arrive from the server. the approach requires no server or protocol changes, and thus can work with existing systems. since it is core to the feasibility of such a speculative remote display system, we study the predictability of the events that occur under typical workloads in two extant systems, windows remote desktop and vnc. we find that simple, state-limited markov models are often able to correctly predict the next event. based on these results, we design, implement, and evaluate a speculative remote display extension to the vnc client. in our implementation, the end user can trade off between the responsiveness of the display and the level of temporarily displayed incorrect predictions. we evaluate vnc/srd with two user studies. we conclude by describing design alternatives.
automatic optimization of parallel dataflow programs. large-scale parallel dataflow systems, e.g., dryad and map-reduce, have attracted significant attention recently. high-level dataflow languages such as pig latin and sawzall are being layered on top of these systems, to enable faster program development and more maintainable code. these languages engender greater transparency in program structure, and open up opportunities for automatic optimization. this paper proposes a set of optimization strategies for this context, drawing on and extending techniques from the database community.
measurement and analysis of large-scale network file system workloads. in this paper we present the analysis of two large-scale network file system workloads. we measured cifs traffic for two enterprise-class file servers deployed in the netapp data center for a three month period. one file server was used by marketing, sales, and finance departments and the other by the engineering department. together these systems represent over 22tb of storage used by over 1500 employees, making this the first ever large-scale study of the cifs protocol. we analyzed how our network file system workloads compared to those of previous file system trace studies and took an in-depth look at access, usage, and sharing patterns. we found that our workloads were quite different from those previously studied; for example, our analysis found increased read-write file access patterns, decreased read-write ratios, more randomfile access, and longer file lifetimes. in addition, we found a number of interesting properties regarding file sharing, file re-use, and the access patterns of file types and users, showing that modern file system workload has changed in the past 5-10 years. this change in workload characteristics has implications on the future design of network file systems, which we describe in the paper.
conflict-aware scheduling for dynamic content applications. we present a new lazy replication technique, suitable for scaling the back-end database of a dynamic content site using a cluster of commodity computers. our technique, called conflict-aware scheduling, provides both throughput scaling and 1-copy serializability. it has generally been believed that this combination is hard to achieve through replication because of the growth of the number of conflicts. we take advantage of the presence in a database cluster of a scheduler through which all incoming requests pass. we require that transactions specify the tables that they access at the beginning of the transaction. using that information, a conflictaware scheduler relies on a sequence-numbering scheme to implement 1-copy serializability, and directs incoming queries in such a way that the number of conflicts is reduced. we evaluate conflict-aware scheduling using the tpcw e-commerce benchmark. for small clusters of up to eight database replicas, our evaluation is performed through measurements of a web site implementing the tpc-w specification. we use simulation to extend our measurement results to larger clusters, faster database engines, and lower conflict rates. our results show that conflict-awareness brings considerable benefits compared to both eager and conflict-oblivious lazy replication for a large range of cluster sizes, database speeds, and conflict rates. conflict-aware scheduling provides near-linear throughput scaling up to a large number of database replicas for the browsing and shopping workloads of tpc-w. for the write-heavy ordering workload, throughput scales, but only to a smaller number of replicas.
using fault injection and modeling to evaluate the performability of cluster-based services. we propose a two-phase methodology for quantifying the performability (performance and availability) of cluster-based internet services. in the first phase, evaluators use a fault-injection infrastructure to measure the impact of faults on the server's performance. in the second phase, evaluators use an analytical model to combine an expected fault load with measurements from the first phase to assess the server's performability. using this model, evaluators can study the server's sensitivity to different design decisions, fault rates, and environmental factors. to demonstrate our methodology, we study the performability of 4 versions of the press web server against 5 classes of faults, quantifying the effects of different design decisions on performance and availability. finally, to further show the utility of our model, we also quantify the impact of two hypothetical changes, reduced human operator response time and the use of raids.
mining longest repeating subsequences to predict world wide web surfing. modeling and predicting user surfing paths involves tradeoffs between model complexity and predictive accuracy. in this paper we explore predictive modeling techniques that attempt to reduce model complexity while retaining predictive accuracy. we show that compared to various markov models, longest repeating subsequence models are able to significantly reduce model size while retaining the ability to make accurate predictions. in addition, sharp increases in the overall predictive capabilities of these models are achievable by modest increases to the number of predictions made.
mayday: distributed filtering for internet services. mayday is an architecture that combines overlay networks with lightweight packet filtering to defend against denial of service attacks. the overlay nodes perform client authentication and protocol verification, and then relay the requests to a protected server. the server is protected from outside attack by simple packet filtering rules that can be efficiently deployed even in backbone routers. mayday generalizes earlier work on secure overlay services. mayday improves upon this prior work by separating the overlay routing and the filtering, and providing a more powerful set of choices for each. through this generalization, mayday supports several different schemes that provide different balances of security and performance, continuum, and supports mechanisms that achieve better security or better performance than earlier systems. to evaluate both mayday and previous work, we also present several practical attacks, two of them novel, that are effective against filtering-based systems.
active names: flexible location and transport of wide-area resources. in this paper, we explore flexible name resolution as a way of supporting extensibility for wide-area distributed services. our approach, called active names, maps names to a chain of mobile programs that can customize how a service is located and how its results are transformed and transported back to the client. to illustrate the properties of our system, we implement prototypes of server selection based on end-to-end performance measurements, location-independent data transformation, and caching of composable active objects and demonstrate up to a five-fold performance improvement to end users. we show how these new services are developed, composed, and secured in our framework. finally, we develop a set of algorithms to control how mobile active name programs are mapped onto available wide-area resources to optimize performance and availability.
a user's and programmer's view of the new javascript security model. in this paper we introduce a new security model for javascript in mozilla, as well as its programming interface. we present important concepts via examples from electronic commerce applications. we also describe our experience of implementing the model in the publicly available mozilla source code. this model is likely to be integrated into navigator 5.0, which, as of this writing, is scheduled to be released in late fall, 1999.
secure public internet access handler (spinach). this paper describes a system that controls access to computer networks through publicly accessible lans, enabling network administrators to authorize users either on a permanent or occasional basis. the system has been designed with minimal assumptions about the software and hardware required of users, and requires very little specialized equipment within the network infrastructure. we enumerate the requirements for such a system, describe the design and implementation of the system, and note tradeoffs between security and efficiency.
using full reference history for efficient document replacement in web caches. with the increase in popularity of the world wide web, the research community has recently seen a proliferation of web caching algorithms. this paper presents a new such algorithm, that is efficient and robust, called least unified-value (luv). luv evaluates a web document based on its cost normalized by the likelihood of it being re-referenced. this results in a normalized assessment of the contribution to the value of a document, leading to a fair replacement policy. luv can conform to arbitrary cost functions of web documents, so it can optimize any particular performance measure of interest, such as the hit rate, the byte hit rate, or the delay-savings ratio. unlike most existing algorithms, luv exploits complete reference history of documents, in terms of reference frequency and recency, to estimate the likelihood of being re-referenced. nevertheless, luv allows for an efficient implementation in both space and time complexities. the space needed to maintain the reference history of a document is only a few bytes and furthermore, the time complexity of the algorithm is o(log2n), where n is the number of documents in the cache. trace-driven simulations show that the luv algorithm outperforms existing algorithms for various performance measures for a wide range of cache configurations.
sase: implementation of a compressed text search engine. keyword based search engines are the basic building block of text retrieval systems. higher level systems like content sensitive search engines and knowledge-based systems still rely on keyword search as the underlying text retrieval mechanism. with the explosive growth in content, internet and intranet information repositories require efficient mechanisms to store as well as index data. in this paper we discuss the implementation of the shrink and search engine (sase) framework which unites text compression and indexing to maximize keyword search performance while reducing storage cost. sase features the novel capability of being able to directly search through compressed text without explicit decompression. the implementation includes a search server architecture, which can be accessed from a java front-end to perform keyword search on the internet. the performance results show that the compression efficiency of sase is within 7-17% of gzip one of the best lossless compression schemes. the sum of the compressed file size and the inverted indices is only between 55-76% of the original database while the search performance is comparable to a fully inverted index. the framework allows a flexible trade-off between search performance and storage requirements for the search indices.
measuring the capacity of a web server. the widespread use of the world wide web and related applications places interesting performance demands on network servers. the ability to measure the effect of these demands is important for tuning and optimizing the various software components that make up a web server. to measure these effects, it is necessary to generate realistic http client requests. unfortunately, accurate generation of such traffic in a testbed of limited scope is not trivial. in particular, the commonly used approach is unable to generate client request-rates that exceed the capacity of the server being tested even for short periods of time. this paper examines pitfalls that one encounters when measuring web server capacity using a synthetic workload. we propose and evaluate a new method for web traffic generation that can generate bursty traffic, with peak loads that exceed the capacity of the server. finally, we use the proposed method to measure the performance of a web server.
adaptive overload control for busy internet servers. as internet services become more popular and pervasive, a critical problem that arises is managing the performance of services under extreme overload. this paper presents a set of techniques for managing overload in complex, dynamic internet services. these techniques are based on an adaptive admission control mechanism that attempts to bound the 90th-percentile response time of requests flowing through the service. this is accomplished by internally monitoring the performance of the service, which is decomposed into a set of event-driven stages connected with request queues. by controlling the rate at which each stage admits requests, the service can perform focused overload management, for example, by filtering only those requests that lead to resource bottlenecks. we present two extensions of this basic controller that provide class-based service differentiation as well as application-specific service degradation. we evaluate these mechanisms using a complex web-based e-mail service that is subjected to a realistic user load, as well as a simpler web server benchmark.
providing dynamic and customizable caching policies. web caching has emerged as one solution for improving client latency on the web. cache effectiveness depends on the policies used to route requests to other caches and servers, to maintain up-to-date web objects and to remove objects from the cache. traditional caches apply one set of policies, which determines the efficiency as well as the effectiveness of the caches. this set of policies often does not exploit the diversity inherent in different web objects, caches and clients. policies that do exploit this diversity result in convoluted caching policies that attempt to combine multiple policies and guess at the unknown characteristics of web objects, caches and clients. in this paper, we present an extensible caching infrastructure in which cache administrators, servers, and end users can customize how web objects are cached, replaced, and kept consistent. the infrastructure includes a domain-specific language, cachel, for defining customizable caching policies that can be changed dynamically. analysis of our prototype, polisquid, shows the benefits of the infrastructure for variable coherency policies, localized removal policies, and early removal of objects from servers.
organization-based analysis of web-object sharing and caching. performance-enhancing mechanisms in the world wide web primarily exploit repeated requests to web documents by multiple clients. however, little is known about patterns of shared document access, particularly from diverse client populations. the principal goal of this paper is to examine the sharing of web documents from an organizational point of view. an organizational analysis of sharing is important, because caching is often performed on an organizational basis; i.e., proxies are typically placed in front of large and small companies, universities, departments, and so on. unfortunately, simultaneous multi-organizational traces do not currently exist and are difficult to obtain in practice. the goal of this paper is to explore the extent of document sharing (1) among clients within single organizations, and (2) among clients across different organizations. to perform the study, we use a large university as a model of a diverse collection of organizations. within our university, we have traced all external web requests and responses, anonymizing the data but preserving organizational membership information. this permits us to analyze both inter-and intra-organization document sharing and to test whether organization membership is significant. as well, we characterize a number of parameters of our data, including basic object characteristics, object cacheability, and server distributions.
cost-aware www proxy caching algorithms. web caches can not only reduce network traffic and downloading latency, but can also affect the distribution of web traffic over the network through cost-aware caching. this paper introduces greedydual-size, which incorporates locality with cost and size concerns in a simple and non-parameterized fashion for high performance. trace-driven simulations show that with the appropriate cost definition, greedydual-size outperforms existing web cache replacement algorithms in many aspects, including hit ratios, latency reduction and network cost reduction. in addition, greedydual-size can potentially improve the performance of main-memory caching of web documents.
efficient support for content-based routing in web server clusters. clustered server architectures have been employed for many years on the internet as a way to increase performance, reliability and scalability in the presence of the internet's explosive growth. a routing mechanism for mapping requests to individual servers within cluster is at the heart of any server clustering techniques. in this paper, we first analyze the deficiencies of existing request-routing approaches. based on these observations, we argue that the request routing mechanism in a cluster-based server should factor in the content of a request in making decisions. thus, we designed and implemented a new mechanism to efficiently support content-aware routing in web server clusters. with this mechanism, we also built in a number of sophisticated content-aware intelligence for making routing decision. performance evaluation on a prototype implementation demonstrates substantial performance improvements over contemporary routing schemes. the proposed mechanism can also enable many new capabilities in cluster-based servers, such as sophisticated load balancing, differentiated service, special content deployment, session integrity, etc.
hierarchical cache consistency in a wan. this paper explores ways to provide improved consistency for internet applications that scale to millions of clients. we make four contributions. first, we identify how workloads affect the scalability of cache consistency algorithms. second, we define two primitive mechanisms, split and join, for growing and shrinking consistency hierarchies, and we present a simple mechanism for implementing them. third, we describe and evaluate policies for using split and join to address the fault tolerance and performance challenges of consistency hierarchies. fourth, using synthetic workload and trace-based simulation, we compare various algorithms for maintaining strong consistency in a range of hierarchy configurations. our results indicate that a promising configuration for providing strong consistency in a wan is a two-level consistency hierarchy where servers and proxies work to maintain consistency for data cached at clients. specifically, by adapting to clients' access patterns, two-level hierarchies reduce the read latency for demanding workloads without introducing excessive overhead for nondemanding workloads. also, they can improve scalability by orders of magnitude. furthermore, this configuration is easy to deploy by augmenting proxies, and it allows invalidation messages to traverse firewalls.
jpeg compression metric as a quality-aware image transcoding. transcoding is becoming a preferred technique to tailor multimedia objects for delivery across variable network bandwidth and for storage and display on the destination device. this paper presents techniques to quantify the quality-versus-size tradeoff characteristics for transcoding jpeg images. we analyze the characteristics of images available in typical web sites and explore how we can perform informed transcoding using the jpeg compression metric. we present the effects of this transcoding on the image storage size and image information quality. we also present ways of predicting the computational cost as well as potential space benefits achieved by the transcoding. these results are useful in any system that uses transcoding to reduce access latencies, increase effective storage space as well as reduce access costs.
anypoint: extensible transport switching on the edge. anypoint is a new model for one-to-many communication with ensemble sites-aggregations of end nodes that appear to the external internet as a unified site. policies for routing any-point traffic are defined by application-layer plugins residing in extensible routers at the ensemble edge. anypoint's switching functions operate at the transport layer at the granularity of transport frames. communication over an anypoint connection preserves end-to-end transport rate control, partial ordering, and reliable delivery. experimental results from a host-based anypoint prototype and an nfs storage router application show that anypoint is a powerful technique for virtualizing and extending cluster services, and is amenable to implementation in high-speed switches. the anypoint prototype improves storage router throughput by 29% relative to a tcp proxy.
cha-cha: a system for organizing intranet search results. although search over world wide web pages has recently received much academic and commercial attention, surprisingly little research has been done on how to search the web pages within large, diverse intranets. intranets contain the information associated with the internal workings of an organization. a standard search engine retrieves web pages that fall within a widely diverse range of information contexts, but presents these results uniformly, in a ranked list. as an alternative, the cha-cha system organizes web search results in such a way as to reflect the underlying structure of the intranet. in our approach, an "outline" or "table of contents" is created by first recording the shortest paths in hyperlinks from root pages to every page within the web intranet. after the user issues a query, these shortest paths are dynamically combined to form a hierarchical outline of the context in which the search results occur. the system is designed to be helpful for users with a wide range of computer skills. preliminary user study and survey results suggest that some users find the resulting structure more helpful than the standard retrieval results display for intranet search.
fastreplica: efficient large file distribution within content delivery networks. in this work, we consider a large-scale distributed network of servers and a problem of content distribution across it. we propose a novel algorithm, called fastreplica, for an efficient and reliable replication of large files in the internet environment. there are a few basic ideas exploited in fastreplica. in order to replicate a large file among n nodes (n is in the range of 10-30 nodes), the original file is partitioned into n subfiles of equal size and each subfile is transferred to a different node in the group. after that, each node propagates its subfile to the remaining nodes in the group. thus instead of the typical replication of an entire file to n nodes by using n internet paths, connecting the original node to the replication group, fastreplica exploits n × n internet paths within the replication group where each path is used for transferring 1/n -th of the file. we design a scalable and reliable fastreplica algorithm which can be used for replication of large files to a large group of nodes. the new method is simple and inexpensive. it does not require any changes or modifications to the existing internet infrastructure, and at the same time, it significantly reduces the file replication time as we demonstrate through experiments on a prototype implementation of fastreplica in a wide-area testbed.
compression proxy server: design and implementation. automatic data compression in the web proxy server is an important mechanism that can potentially reduce network bandwidth consumption and web access latency significantly. however, unlike traditional data compression, web protocols and data have unique characteristics that make compression challenging. these include data block streaming, wide range of data object sizes and types, and real-time response. in this paper, we focus on automatic web data compression in the http proxy server. a new classification of web data compression based on system complexity and http requirements is proposed: stream, block and file compression. then, the concept of hybrid web data compression is introduced. to understand the potentials of web data compression better, an implementation of the proposed hybrid compression in the squid proxy server is described. the result is very promising, as about 30% of the bandwidth can be saved easily. furthermore, even with a low end pentium 266 mhz pc as the proxy machine, the compression overhead is less than 1% of the transfer time.
why do internet services fail, and what can be done about it? in 1986 jim gray published his landmark study of the causes of failures of tandem systems and the techniques tandem used to prevent such failures [6]. seventeen years later, internet services have replaced fault-tolerant servers as the new kid on the 24×7-availability block. using data from three large-scale internet services, we analyzed the causes of their failures and the (potential) effectiveness of various techniques for preventing and mitigating service failure. we find that (1) operator error is the largest cause of failures in two of the three services, (2) operator errors is the largest contributor to time to repair in two of the three services, (3) configuration errors are the largest category of operator errors, (4) failures in custom-written front-end software are significant, and (5) more extensive online testing and more thoroughly exposing and detecting component failures would reduce failure rates in at least one service. qualitatively we find that improvement in the maintenance tools and systems used by service operations staff would decrease time to diagnose and repair problems.
a highly scalable electronic mail service using open systems. email is one of the most important of the internet services. as a very large, fast growing, internet service provider, earthlink requires a robust and powerful email architecture that will support rapid expansion. this paper describes such an architecture, its motivations, its future, and the difficulties in implementing a service on this scale.
on the performance of tcp splicing for url-aware redirection. this paper describes the design, implementation and performance of a layer-7 switch which supports url-aware redirection of http traffic. currently, there are several vendors who are beginning to announce the availability of such switches in the market, but little or no implementation and performance information is available. we discuss design issues pertaining to such switches through a prototype implementation of a url-aware switch in the linux kernel, and analyze the performance of our implementation. we investigate the use of tcp splicing as a mechanism for improving the performance of the switch; we explore whether tcp splicing will benefit url-aware redirection even though http connections, on average, are short-lived and transfer small amounts of data. results from our implementation show that tcp splicing does improve the performance of url-aware switches that handle short-lived http connections. our results also re-affirm earlier findings that tcp splicing substantially improves the performance of any application-layer proxy when large amounts of data are transferred through the splice.
connection scheduling in web servers. under high loads, a web server may be servicing many hundreds of connections concurrently. in traditional web servers, the question of the order in which concurrent connections are serviced has been left to the operating system. in this paper we ask whether servers might provide better service by using non-traditional service ordering. in particular, for the case when a web server is serving static files, we examine the costs and benefits of a policy that gives preferential service to short connections. we start by assessing the scheduling behavior of a commonly used server (apache running on linux) with respect to connection size and show that it does not appear to provide preferential service to short connections. we then examine the potential performance improvements of a policy that does favor short connections (shortest-connection-first). we show that mean response time can be improved by factors of four or five under shortest-connection-first, as compared to an (apache-like) size-independent policy. finally we assess the costs of shortest-connection-first scheduling in terms of unfairness (i.e., the degree to which long connections suffer). we show that under shortest-connection-first scheduling, long connections pay very little penalty. this surprising result can be understood as a consequence of heavy-tailed web server workloads, in which most connections are small, but most server load is due to the few large connections. we support this explanation using analysis.
using the structure of html documents to improve retrieval. the world wide web (www) is a gigantic information resource, which is growing daily. as more and more data are added to the www, it is becoming increasingly difficult to effectively locate useful information from this environment. in this paper, we propose a method for making use of the structures and hyperlinks of html documents to improve the effectiveness of retrieving html documents. our study assigns the occurrences of terms in a document collection into six classes according to the tags in which a particular term appears (such as title, h1-h6, and anchor). based on the assignment, we extend the weighting schemes in traditional information retrieval by incorporating different importance factors to terms in different classes. the rationale is that terms appearing in different places of a document may have different significance in identifying the document. for this research we have built a web based search tool, webor, created a testbed, and conducted extensive experiments to determine an optimal class importance factor combination. our study indicates that substantial improvement of retrieval effectiveness can be achieved using this technique.
rate of change and other metrics: a live study of the world wide web. caching in the world wide web is based on two critical assumptions: that a significant fraction of requests reaccess resources that have already been retrieved; and that those resources do not change between accesses. we tested the validity of these assumptions, and their dependence on characteristics of web resources, including access rate, age at time of reference, content type, resource size, and internet top-level domain. we also measured the rate at which resources change, and the prevalence of duplicate copies in the web. we quantified the potential benefit of a shared proxy-caching server in a large environment by using traces that were collected at the internet connection points for two large corporations, representing significant numbers of references. only 22% of the resources referenced in the traces we analyzed were accessed more than once, but about half of the references were to those multiply-referenced resources. of this half, 13% were to a resource that had been modified since the previous traced reference to it. we found that the content type and rate of access have a strong influence on these metrics, the domain has a moderate influence, and size has little effect. in addition, we studied other aspects of the rate of change, including semantic differences such as the insertion or deletion of anchors, phone numbers, and email addresses.
hpp: html macro-preprocessing to support dynamic document caching. a number of techniques are available for reducing latency and bandwidth requirements for resources on the world wide web, including caching, compression, and delta-encoding [12]. these approaches are limited: much data on the web is dynamic, for which traditional caching is of limited use, and delta-encoding requires both a common version base against which to apply a delta and the complete generation of the resource prior to encoding it. in contrast to these approaches, we take an application-specific view, in which we separate the static and dynamic portions of a resource. the static portions (called the template) can then be cached, with (presumably small) dynamic portions obtained on each access. our html extension, which we refer to as hpp (for html pre-processing) supports resources that contain variable number of static and dynamic elements, such as query responses. results with macro-encoding of query response resources from local cgi scripts and two popular search engines indicate that our approach promises a substantial reduction of network traffic, server load, and access latency for dynamic documents. the size of network transfers using hpp are comparable to delta-encoding (factors of 2-8 smaller than the original resource), while the data generated by content providers is simpler, and the load on the end-servers is slightly lower.
model-based resource provisioning in a web service utility. internet service utilities host multiple server applications on a shared server cluster. a key challenge for these systems is to provision shared resources on demand to meet service quality targets at least cost. this paper presents a new approach to utility resource management focusing on coordinated provisioning of memory and storage resources. our approach is model-based: it incorporates internal models of service behavior to predict the value of candidate resource allotments under changing load. the model-based approach enables the system to achieve important resource management goals, including differentiated service quality, performance isolation, storage-aware caching, and proactive allocation of surplus resources to meet performance goals. experimental results with a prototype demonstrate model-based dynamic provisioning under web workloads with static content.
prefetching hyperlinks. this paper develops a new method for prefetching web pages into the client cache. clients send reference information to web servers, which aggregate the reference information in near-real-time and then disperse the aggregated information to all clients, piggybacked on get responses. the information indicates how often hyperlink urls embedded in pages have been previously accessed relative to the embedding page. based on knowledge about which hyperlinks are generally popular, clients initiate prefetching of the hyperlinks and their embedded images according to any algorithm they prefer. both client and server may cap the prefetching mechanism's space overhead and waste of network resources due to speculation. the result of these differences is improved prefetching: lower client latency (by 52.3%) and less wasted network bandwidth (24.0%).
the measured access characteristics of world-wide-web client proxy caches. the growing popularity of the world wide web is placing tremendous demands on the internet. a key strategy for scaling the internet to meet these increasing demands is to cache data near clients and thus improve access latency and reduce network and server load. unfortunately, research in this area has been hampered by a poor understanding of the locality and sharing characteristics of web-client accesses. the recent popularity of web proxy servers provides a unique opportunity to improve this understanding, because a small number of proxy servers see accesses from thousands of clients. this paper presents an analysis of access traces collected from seven proxy servers deployed in various locations throughout the internet. the traces record a total of 47.4 million requests made by 23,700 clients over a twenty-one day period. we use a combination of static analysis and trace-driven cache simulation to characterize the locality and sharing properties of these accesses. our analysis shows that a 2- to 10-gb second-level cache yields hit rates between 24% and 45% with 85% of these hits due to sharing among different clients. caches with more clients exhibit more sharing and thus higher hit rates. between 2% and 7% of accesses are consistency misses to unmodified objects, using the squid and cern proxy cache coherence protocols. sharing is bimodal. requests for shared objects are divided evenly between objects that are narrowly shared and those that are shared by many clients; widely shared objects also tend to be shared by clients from unrelated traces.
energy conservation policies for web servers. energy management for servers is now necessary for technical, financial, and environmental reasons. this paper describes three policies designed to reduce energy consumption in web servers. the policies employ two power management mechanisms: dynamic voltage scaling (dvs), an existing mechanism, and request batching, a new mechanism introduced in this paper. the first policy uses dvs in isolation, except that we extend recently introduced task-based dvs policies for use in server environments with many concurrent tasks. the second policy uses request batching to conserve energy during periods of low workload intensity. the third policy uses both dvs and request batching mechanisms to reduce processor energy usage over a wide range of workload intensities. all the policies trade off system responsiveness to save energy. however, the policies employ the mechanisms in a feedback-driven control framework in order to conserve energy while maintaining a given quality of service level, as defined by a percentile-level response time. we evaluate the policies using salsa, a web server simulator that has been extensively validated for both energy and response time against measurements from a commodity web server. three daylong static web workloads from real web server systems are used to quantify the energy savings: the nagano olympics98 web server, a financial services company web site, and a disk intensive web workload. our results show that when required to maintain a 90th-percentile response time of 50ms, the dvs and request batching policies save from 8.7% to 38% and from 3.1% to 27% respectively of the cpu energy used by the base system. the two polices provide these savings for complementary workload intensities. the combined policy is effective for all three workloads across a broad range of intensities, saving from 17% to 42% of the cpu energy.
the ninja jukebox. we present the design and implementation of the "ninja jukebox", an infrastructural service that allows a community of users to build a distributed, collaborative music repository that delivers digital music to internet clients, and that performs simple collaborative filtering based on users' song preferences inferred by the service. the jukebox, implemented in java, was designed to allow rapid service evolution and reconfiguration, simplicity in participation, and extensibility. we demonstrate that our careful use of a distributed component architecture enabled rapid prototyping of the service, and that our use of carefully designed, strongly typed interfaces enabled the smooth evolution of the service from a simple prototype to a more complex, mature system.
going beyond the sandbox: an overview of the new security architecture in the java development kit 1.2. this paper describes the new security architecture that has been implemented aspart of jdk1.2, the forthcoming javatm development kit. in going beyond the sandbox security model in the original release of java, jdk1.2 provides fine-grained access control via an easily configurable security policy. moreover, jdk1.2 introduces the concept of protection domain and a few related security primitives that help to make the underlying protection mechanism more robust.
system design issues for internet middleware services: deductions from a large client trace. in this paper, we present the analysis of a large client-side web trace gathered from the home ip service at the university of california at berkeley. specifically, we demonstrate the heterogeneity of web clients, the existence of a strong and very predictable diurnal cycle in the clients' web activity, the burstiness of clients' requests at small time scales (but not large time scales, implying a lack of self-similarity), the presence of locality of reference in the clients' requests that is a strong function of the client population size, and the high latency that services encounter when delivering data to clients, implying that services will need to maintain a very large number of simultaneously active requests. we then present system design issues for internet middleware services that were drawn both from our trace analysis and our implementation experience of the transend transformation proxy.
skipnet: a scalable overlay network with practical locality properties. scalable overlay networks such as chord, can, pastry, and tapestry have recently emerged as flexible infrastructure for building large peer-to-peer systems. in practice, such systems have two disadvantages: they provide no control over where data is stored and no guarantee that routing paths remain within an administrative domain whenever possible. skipnet is a scalable overlay network that provides controlled data placement and guaranteed routing locality by organizing data primarily by string names. skipnet allows for both fine-grained and coarse-grained control over data placement: content can be placed either on a pre-determined node or distributed uniformly across the nodes of a hierarchical naming sub-tree. an additional useful consequence of skipnet's locality properties is that partition failures, in which an entire organization disconnects from the rest of the system, can result in two disjoint, but well-connected overlay networks.
a document-based framework for internet application control. this paper motivates and details a document-based framework for manipulating the components that comprise distributed internet applications. in the framework, xml documents are used to describe both server-side functionality and the mapping between a client's applications and the servers it accesses. our system model contrasts with explicitly context-aware application designs, where location information must be explicitly manipulated by the application to affect change; instead, a middleware layer is interposed between client applications and services so that invocations between the two can be transparently remapped. this approach is useful for a subset of application domains, including our example domain of "remote control" of local resources (e.g., lights, stereo components, etc.). we illustrate how the framework allows for 1) remapping of a portion of an existing user interface to a new service, 2) viewing of arbitrary subsets and combinations of the available functionality, and 3) mixing dynamically-generated user interfaces with existing user interfaces. the use of a document-based framework in addition to a conventional object-oriented programming language provides a number of key features. one of the most useful is that it exposes the mappings between programs/uis and the objects to which they refer, thereby providing a standard location for manipulation of this indirection.
network-sensitive service discovery. we consider the problem of network-sensitive service selection (nsss): finding services that match a particular set of functional and network properties. current solutions handle this problem using a two-step process. first, a user obtains a list of candidates through service discovery. then, the user applies a network-sensitive server selection technique to find the best service. such approaches are complex and expensive since each user has to solve the nsss problem independently. in this paper, we present a simple alternative: network-sensitive service discovery (nssd). by integrating network-sensitivity into the service discovery process, nssd allows users who are looking for services to specify both the desired functional and network properties at the same time. users benefit since they only have to solve a restricted version of the server selection problem. moreover, nssd can solve the nsss problem more efficiently by amortizing the overhead over many users. we present the design of nssd, a prototype implementation, and experimental results that illustrate how nssd can be utilized for different applications.
improving web server performance by caching dynamic data. dynamic web pages can seriously reduce the performance of web servers. one technique for improving performance is to cache dynamic web pages. we have developed the dynamic web cache which is particularly well-suited for dynamic pages. our cache has improved performance significantly at several commercial web sites. this paper analyzes the design and performance of the dynamicweb cache. it also presents a model for analyzing overall system performance in the presence of caching. our cache can satisfy several hundred requests per second. on systems which invoke server programs via cgi, the dynamicweb cache results in near-optimal performance, where optimal performance is that which would be achieved by a hypothetical cache which consumed no cpu cycles. on a system we tested which invoked server programs via icapi which has significantly less overhead than cgi, the dynamicweb cache resulted in near-optimal performance for many cases and 58% of optimal performance in the worst case. the dynamicweb cache achieved a hit rate of around 80% when it was deployed to support the official internet web site for the 1996 atlanta olympic games.
a study of the performance potential of dht-based overlays. we use simulation to study whether overlays based on the recent distributed hash tables (dhts) have the potential to deliver performance comparable to that of overlays based on measurements. our work is motivated by the use of dhts for services such as multicast, which is already targeted by measurement-based overlays; there is currently little understanding of how the two approaches compare at scales where both are viable. we compare three dht-based overlays (can, chord and pastry) with two measurement-based overlays (narada and nice), as well as power-law random graphs (plrgs) that represent gnutella. to enable comparisons, we configure the overlays with the same average out-degree and focus on moderate scale. to gauge potential, we look at current and idealized dht algorithms. we find that basic versions of dhts have a latency stretch that is at least twice that of nice and narada, but similar performance in terms of bandwidth hotspots. however, dht performance can be improved considerably with routing heuristics and topology-aware overlay construction, which have the potential to bring dht performance at par with nice. we also report on performance of overlays with power-law structure and the impact of hierarchy on performance.
nps: a non-interfering deployable web prefetching system. we present nps, a novel non-intrusive web prefetching system that (1) utilizes only spare resources to avoid interference between prefetch and demand requests at the server as well as in the network , and (2) is deployable without any modifications to servers, browsers, network or the http protocol. nps's self-tuning architecture eliminates the need for traditional "thresholds" or magic numbers typically used to limit interference caused by prefetching, thereby allowing applications to improve benefits and reduce the risk of aggressive prefetching. nps avoids interference with demand requests by monitoring the responsiveness of the server and accordingly throttling the prefetch aggressiveness, and by using tcp-nice, a congestion control protocol suitable for low priority transfers. nps avoids the need to modify existing infrastructure by modifying html pages to include javascripttm code that issues prefetch requests and by wrapping the server infrastructure with several simple external modules that require no knowledge of or no modifications to the internals of existing servers. our measurements of the prototype under a web trace indicate that nps is both non-interfering and efficient under different network load and server load conditions. for example, in our experiments with a loaded server with little spare capacity, we observe that a threshold-based prefetching scheme causes response times to increase by a factor of 2 due to interference, whereas prefetching using nps decreases response times by 25%.
using random subsets to build scalable network services. in this paper, we argue that a broad range of large-scale network services would benefit from a scalable mechanism for delivering state about a random subset of global participants. key to this approach is ensuring that membership in the subset changes periodically and with uniform representation over all participants. random subsets could help overcome inherent scaling limitations to services that maintain global state and perform global network probing. it could further improve the routing performance of peer-to-peer distributed hash tables by locating topologically-close nodes. this paper presents the design, implementation, and evaluation of ransub, a scalable protocol for delivering such state. as a first demonstration of the ransub utility, we construct saro, a scalable and adaptive application-layer overlay tree. saro uses ransub state information to locate appropriate peers for meeting application-specific delay and bandwidth targets and to dynamically adapt to changing network conditions. a large-scale evaluation of 1000 overlay nodes participating in an emulated 20,000- node wide-area network topology demonstrate both the adaptivity and scalability (in terms of per-node state and network overhead) of both ransub and saro. finally, we use an existing streaming media server to distribute content through saro running on top of the planetlab internet testbed.
a flexible and efficient application programming interface (api) for a customizable proxy cache. this paper describes the design, implementation, and performance of a simple yet powerful application programming interface (api) for providing extended services in a proxy cache. this api facilitates the development of customized content adaptation, content management, and specialized administration features. we have developed several modules that exploit this api to perform various tasks within the proxy, including a module to support the internet content adaptation protocol (icap) without any changes to the proxy core. the api design parallels those of high-performance servers, enabling its implementation to have minimal overhead on a high-performance cache. at the same time, it provides the infrastructure required to process http requests and responses at a high level, shielding developers from low-level http and socket details and enabling modules that perform interesting tasks without significant amounts of code. we have implemented this api in the portable and high-performance imimic datareactortm proxy cache1. we show that implementing the api imposes negligible performance overhead and that realistic content-adaptation services achieve high performance levels without substantially hindering a background benchmark load running at a high throughput level.
rainman: a workflow system for the internet. as individuals and enterprises get interconnected via global networks, workflows that scale beyond traditional organizational boundaries and execute seamlessly across these networks will become relevant. we address the problem of designing a scalable workflow infrastructure for the internet that supports both flexibility in workflow participation and interoperability between heterogeneous workflow system components. rainman is a distributed workflow system developed in java that lives naturally on the internet. rainman is a loosely-coupled collection of independent services that cooperate with each other rather than a monolithic system. some of the useful features of rainman are browser-based workflow specification, participation, and management, and dynamic workflow modification. the rainman system is based on rainmaker, our generic workflow framework that defines a core set of well-defined interfaces for workflow components.
study of piggyback cache validation for proxy caches in the world wide web. this paper presents work on piggyback cache validation (pcv), which addresses the problem of maintaining cache coherency for proxy caches. the novel aspect of our approach is to capitalize on requests sent from the proxy cache to the server to improve coherency. in the simplest case, whenever a proxy cache has a reason to communicate with a server it piggybacks a list of cached, but potentially stale, resources from that server for validation. trace-driven simulation of this mechanism on two large, independent data sets shows that pcv both provides stronger cache coherency and reduces the request traffic in comparison to the time-to-live (ttl) based techniques currently used. specifically, in comparison to the best ttl-based policy, the best pcv-based policy reduces the number of request messages from a proxy cache to a server by 16-17% and the average cost (considering response latency, request messages and bandwidth) by 6-8%. moreover, the best pcv policy reduces the staleness ratio by 57-65% in comparison to the best ttl-based policy. additionally, the pcv policies can easily be implemented within the http 1.1 protocol.
exploring the bounds of web latency reduction from caching and prefetching. prefetching and caching are techniques commonly used in i/o systems to reduce latency. many researchers have advocated the use of caching and prefetching to reduce latency in the web. we derive several bounds on the performance improvements seen from these techniques, and then use traces of web proxy activity taken at digital equipment corporation to quantify these bounds. we found that for these traces, local proxy caching could reduce latency by at best 26%, prefetching could reduce latency by at best 57%, and a combined caching and prefetching proxy could provide at best a 60% latency reduction. furthermore, we found that how far in advance a prefetching algorithmwas able to prefetch an object was a significant factor in its ability to reduce latency. we note that the latency reduction from caching is significantly limited by the rapid changes of objects in the web. we conclude that for the workload studied caching offers moderate assistance in reducing latency. prefetching can offer more than twice the improvement of caching but is still limited in its ability to reduce latency.
rapid reverse dns lookups for web servers. when a web server wants to learn the domain name of one of its clients, it must perform a lookup in the domain name system's "reverse domain", inaddr.arpa. these lookups can take time and may have an adverse impact on the web server's response to its clients. rapid dns is an intermediate client/server system that operates between a web server and a dns server. it provides caching of the results and, more importantly, limits web server lookups to the data contained in the cache. this provides a significant improvement in response time for situations in which knowledge of the hostname is not critical to the web server's operation. the rapid dns system was implemented for use in the web farm that serves the collection of cable news network (cnn) sites. its design is presented, along with measurements of its performance in the cnn environment.
bit: a tool for instrumenting java bytecodes. bit (bytecode instrumenting tool) is a collection of java classes that allow one to build customized tools to instrument java virtual machine (jvm) bytecodes. because understanding program behavior is an essential part of developing effective optimization algorithms, researchers and software developers have built numerous tools that carry out program analysis. although there are existing tools that analyze and modify executables on a variety of operating systems and machine architectures, there currently is no framework for carrying out the same task for jvm bytecodes. in this paper, we describe bit, which allows the user to insert calls to analysis methods anywhere in the bytecode, so that information can be extracted from the user program while it is being executed. in this paper, we describe several simple tools built using bit and also report on bit's performance. we found that the overhead for the execution speed and size were between 23% to 150%.
scalable web caching of frequently updated objects using reliable multicast. frequently updated web objects reduce the benefit of caching, increase the problem of cache inconsistency, and aggravate the inefficiency of the conventional "repeated unicast" delivery model. in this paper, we investigate multicast invalidation and delivery of popular, frequently updated objects to web cache proxies. our protocol, mmo, groups objects into volumes, each of which maps to one ip multicast group. we show that, by forming volumes of the appropriate size and/or object correlation, the benefit from reliable multicast outweighs the cost of delivering extraneous data as well as the overhead of multicast reliability. moreover, trace-driven simulations show that the bandwidth saving over conventional approaches increases significantly as the audience size grows. we conclude that mmo provides efficient bandwidth utilization and service scalability, and makes strong web cache consistency for dynamic objects practical.
alleviating the latency and bandwidth problems in www browsing. this work addresses three problems that are associated with web browsing: (a) low bandwidth available to the end user who is connected via slow modems or outdoor wireless networks, (b) long and variable latencies in document access, and (c) temporary disconnections of mobile users. three techniques are used with a variety of heuristics in order to overcome these problems: (a) profiling user and group access patterns and using these profiles in order to pre-fetch documents, (b) filtering http requests and responses in order to reduce data transmission over bottleneck links, and (c) hoarding documents based on user profiles in order to support limited web browsing even during disconnection. in this paper, we describe the design and implementation of a www proxy-based system that incorporates the above techniques. we describe our experiences with the proxy system, and present performance results that show an improvement in the experience of web browsing using this system.
salamander: a push-based distribution substrate for internet applications. the salamander distribution system is a wide-area network data dissemination substrate that has been used daily for over a year by several groupware and webcasting internet applications. specifically, salamander is designed to support push-based applications and provides a variety of delivery semantics. these semantics range from basic data delivery, used by the internet performance measurement and analysis (ipma) project, to collaborative group communication used by the upper atmospheric research collaboratory (uarc) project. the salamander substrate is designed to accommodate the large variation in internet connectivity and client resources through the use of application-specific plug-in modules. these modules provide a means for placing application code throughout the distribution network, thereby allowing the application to respond to network and processor resource constraints near their bottlenecks. the delivery substrate can be tailored by an application for use with a heterogeneous set of clients. for example the ipma and uarc projects send and receive data from: java applets and applications; perl, c and c++ applications; and unix and windows 95/nt clients. this paper illustrates the architecture and design of the salamander system driven by the needs of its set of current applications. the main architectural features described include: the data distribution mechanism, persistent data queries, negotiated push-technology, resource announcement and discovery, and support for application-level quality of service policies.
creating a personal web notebook. this paper introduces a tool, called nabbit, to go from the world-wide web to your own web. nabbit uses a copy-and-paste paradigm, adapted to the way the web is used, to provide a convenient personal notebook. while browsing, users can select, with the mouse, any part of an html page they are looking at, and nabbit will copy that part with the original format -- images, forms, links and all -- to their own pages. the source, date, and even personal comments are copied as well. collection of information becomes as simple as "here's what i want -- click -- i got it." nabbit can be used to write reports interleaved with web content, maintain extended hot lists (with your own comments and even parts of pages), collect selected hits from search results, and much more.
the search broker. the current search facilities on the web are amazingly powerful, but they are still lacking. taking the whole universe as one flat data space and searching it with keywords has inherent limitations of scale. the challenge is to provide users with ways to focus their search better without making it too difficult or too inefficient. we introduce a method of conducting search on the web that is based on a two-level search idea. it strikes a balance between flat global search and specialized databases, and gives users convenient access to vast amounts of information.
symphony: distributed hashing in a small world. we present symphony, a novel protocol for maintaining distributed hash tables in a wide area network. the key idea is to arrange all participants along a ring and equip them with long distance contacts drawn from a family of harmonic distributions. through simulation, we demonstrate that our construction is scalable, flexible, stable in the presence of frequent updates and offers small average latency with only a handful of long distance links per node. the cost of updates when hosts join and leave is small.
web facts and fantasy. there is a great deal of research about improving web server performance and building better, faster servers, but little research in characterizing servers and the load imposed upon them. while some tremendously popular and busy sites, such as netscape.com, playboy.com, and altavista.com, receive several million hits per day, most servers are never subjected to loads of this magnitude. this paper presents the analysis of internet web server logs for a variety of different types of sites. we present a taxonomy of the different types of web sites and characterize their access patterns and, more importantly, their growth. we then use our server logs to address some common perceptions about the web. we show that, on a variety of sites, contrary to popular belief, the use of cgi does not appear to be increasing and that long latencies are not necessarily due to server loading. we then show that, as expected, persistent connections are generally useful, but that dynamic time-out intervals may be unnecessarily complex and that allowing multiple persistent connections per client may actually hinder resource utilization compared to allowing only a single persistent connection.
secondary storage management for web proxies. world-wide web proxies are being increasingly used to provide internet access to users behind a firewall and to reduce wide-area network traffic. recent results suggest that disk i/o is increasingly becoming the limiting factor for the performance of web proxies. in this paper we study the overheads associated with disk i/o for web proxies, and propose secondary storage management alternatives that improve performance. we use a combination of experimental evaluation and simulation based on traces from busy web proxies. we show that web proxies experience significant overheads due to disk i/o. we propose several file management methods that reduce the disk i/o overhead overhead by a factor of 25 overall, resulting in a single-disk service rate that exceeds 500 (url-get) operations per second.
lightweight security primitives for e-commerce. emerging applications in electronic commerce often involve very low-cost transactions, which execute in the context of ongoing, extended client-server relationships. for example, consider a website (server) which offers repeated authenticated personalized stock quotes to each of its subscribers (clients). the value of a single transaction (e.g., delivery of a web-page with a customized set of quotes) does not warrant the cost of executing a handshake and key distribution protocol. also, a client might not always use the same machine during such an extended relationship (e.g., a pc at home, a laptop on a trip). typical transport/session-layer security mechanisms such as ssl and s-http either require handshake/key distribution for each transaction or do not support client mobility. we propose a new security framework for extended relationships between clients and servers, based on persistent shared keys. we argue that this is a preferred model for inexpensive transactions executing within extended relationships. our main contribution is the design and implementation of a set of lightweight application-layer primitives, for (1) generating and maintaining persistent shared keys without requiring a client to store any information between transactions and (2) securing a wide range of web-transactions (e.g., subscription, authenticated and/or private delivery of information, receipts) with adequate computational cost. our protocols require public key infrastructure only for servers/vendors, and its usage only once per client (upon first interaction).
moving edge-side includes to the real edge - the clients. edge-side includes (esi) is an open mark-up language that allows content providers to break their pages into fragments with individual caching characteristics. a page is reassembled from esi fragments by a content delivery network (cdn) at an edge server, which selectively downloads from the origin content server only those fragments that are necessary (as opposed to the entire page). this is expected to reduce the load and bandwidth requirements of the content server. this paper proposes an esi-compliant approach in which page reconstruction occurs at the browser rather than the cdn. unlike page assembly at the network edge, csi optimizes content delivery over the last mile, which is where the true bottleneck often is. we call the client-based approach client-side includes, or csi.
scriptroute: a public internet measurement facility. we present scriptroute, a system that allows ordinary internet users to conduct network measurements from remote vantage points. we seek to combine the flexibility found in dedicated measurement testbeds such as nimi with the general accessibility and popularity of web-based public traceroute servers. to use scriptroute, clients use dns to discover measurement servers and then submit a measurement script for execution in a sandboxed, resource-limited environment. the servers ensure that the script does not expose the network to attack by applying source- and destination-specific filters and security checks, and by rate-limiting traffic. scriptroute code is publicly available and has been deployed on the planetlab testbed of 42 sites. as proof-of-concept, we have used it both to create rpt, a tool for measuring routing trees toward a destination, and to repeat the experiment used to evaluate gnp, a recently proposed internet distance estimation technique. we find that our system is flexible enough to implement a variety of measurement tools despite its security restrictions, that access to many remote vantage points makes the system valuable, and that scripting is an apt choice for expressing and combining measurement tasks.
person-level routing in the mobile people architecture. ubiquitous network connectivity for devices does not automatically imply continuous reachability for people. people move from place to place and switch from one network device to another. as a result, phones ring in empty offices, email cannot reach most cell phones, and spam clogs expensive, low-bandwidth links to laptops. whereas existing mechanisms have addressed host mobility or the mobility of people within one network, few have allowed people, the ultimate and most important endpoints of communication, to roam freely, without being constrained to one location, one application, one device, or one network. we have designed the mobile people architecture (mpa) to maintain person-to-person reachability. the central component of mpa is a person-level router called the personal proxy. it tracks a mobile person's location, accepts communications on his behalf, converts them into different application formats according to his preferences, and forwards the resulting communications to him. in contrast to similar systems, the personal proxy protects the user's privacy, is easily extensible to new network devices and applications, and has been deployed with no modifications to the existing network and telecommunications infrastructure. in this paper, we describe the design, implementation, and preliminary evaluation of our prototype personal proxy, a service that integrates internet and telephone communication and addresses the need for person-to-person reachability.
sting: a tcp-based network measurement tool. understanding wide-area network characteristics is critical for evaluating the performance of internet applications. unfortunately, measuring the end-to-end network behavior between two hosts can be problematic. traditional icmp-based tools, such as ping, are easy to use and work universally, but produce results that are limited and inaccurate. measurement infrastructures, such as nimi, can produce highly detailed and accurate results, but require specialized software to be deployed at both the sender and the receiver. in this paper we explore using the tcp protocol to provide more accurate network measurements than traditional tools, while still preserving their near-universal applicability. our first prototype, a tool called sting, is able to accurately measure the packet loss rate on both the forward and reverse paths between a pair of hosts. we describe the techniques used to accomplish this, how they were validated, and present our preliminary experience measuring the packet loss rates to and from a variety of web servers.
spand: shared passive network performance discovery. in the internet today, users and applications must often make decisions based on the performance they expect to receive from other internet hosts. for example, users can often view many web pages in low-bandwidth or high-bandwidth versions, while other pages present users with long lists of mirror sites to chose from. current techniques to perform these decisions are often ad hoc or poorly designed. the most common solution used today is to require the user to manually make decisions based on their own experience and whatever information is provided by the application. previous efforts to automate this decision-making process have relied on isolated, active network probes from a host. unfortunately, this method of making measurements has several problems. active probing introduces unnecessary network traffic that can quickly become a significant part of the total traffic handled by busy web servers. probing from a single host results in less accurate information and more redundant network probes than a system that shares information with nearby hosts. in this paper, we propose a system called spand (shared passive network performance discovery) that determines network characteristics by making shared, passive measurements from a collection of hosts. in this paper, we show why using passive measurements from a collection of hosts has advantages over using active measurements from a single host. we also show that sharing measurements can significantly increase the accuracy and timeliness of predictions. in addition, we present a initial prototype design of spand, the current implementation status of our system, and initial performance results that show the potential benefits of spand.
exploiting result equivalence in caching dynamic web content. caching is currently the primary mechanism for reducing the latency as well as bandwidth requirements for delivering web content. numerous techniques and tools have been proposed, evaluated and successfully used for caching static content. recent studies show that requests for dynamic web content also contain substantial locality for identical requests. in this paper, we classify locality in dynamic web content into three kinds: identical requests, equivalent requests, and partially equivalent requests. equivalent requests are not identical to previous requests but result in generation of identical dynamic content. the documents generated for partially equivalent requests are not identical but can be used as temporary place holders for each other while the real document is being generated. we present a new protocol, which we refer to as dynamic content caching protocol (dccp), to allow individual content generating applications to exploit query semantics and specify how their results should be cached and/or delivered. we illustrate the usefulness of dccp for several applications and evaluate its effectiveness using traces from the alexandria digital library and nasa kennedy center as case studies.
tied, libsafeplus: tools for runtime buffer overflow protection. buffer overflow exploits make use of the treatment of strings in c as character arrays rather than as first-class objects. manipulation of arrays as pointers and primitive pointer arithmetic make it possible for a program to access memory locations which it is not supposed to access. there have been many efforts in the past to overcome this vulnerability by performing array bounds checking in c. most of these solutions are either inadequate, inefficient or incompatible with legacy code. in this paper, we present an efficient and transparent runtime approach for protection against all known forms of buffer overflow attacks. our solution consists of two tools: tied (type information extractor and depositor) and libsafeplus. tied extracts size information of all global and automatic buffers defined in the program from the debugging information produced by the compiler and inserts it back in the program binary as a data structure available at runtime. libsafeplus is a dynamic library which provides wrapper functions for unsafe c library functions such as strcpy. these wrapper functions check the source and target buffer sizes using the information made available by tied and perform the requested operation only when it is safe to do so. for dynamically allocated buffers, the sizes and starting addresses are recorded at runtime. with our simple design we are able to protect most applications with a performance overhead of less than 10%.
network-in-a-box: how to set up a secure wireless network in under a minute. combining effective security and usability is often considered impossible. for example, deploying effective security for wireless networks is a difficult task, even for skilled systems administrators - a fact that is impeding the deployment of many mobile systems. in this paper we describe a system that lets typical users easily build a highly secure wireless network. our main contribution is to show how gesture-based user interfaces can be applied to provide a complete solution for securing wireless networks. this allows users to intuitively manage the network security of their mobile devices, even those with limited user interfaces. we demonstrate through user studies that our secure implementation is considerably easier to use than typical commercially available options, even those that provide lower security. our gesture-based approach is quite general, and can be used to design a wide variety of systems that are simultaneously secure and easy to administer.
privtrans: automatically partitioning programs for privilege separation. privilege separation partitions a single program into two parts: a privileged program called the monitor and an unprivileged program called the slave. all trust and privileges are relegated to the monitor, which results in a smaller and more easily secured trust base. previously the privilege separation procedure, i.e., partitioning one program into the monitor and slave, was done by hand [18, 28]. we design techniques and develop a tool called privtrans that allows us to automatically integrate privilege separation into source code, provided a few programmer annotations. for instance, our approach can automatically integrate the privilege separation previously done by hand in openssh, while enjoying similar security benefits. additionally, we propose optimization techniques that augment static analysis with dynamic information. our optimization techniques reduce the number of expensive calls made by the slave to the monitor. we show privtrans is effective by integrating privilege separation into several open-source applications.
on user choice in graphical password schemes. graphical password schemes have been proposed as an alternative to text passwords in applications that support graphics and mouse or stylus entry. in this paper we detail what is, to our knowledge, the largest published empirical evaluation of the effects of user choice on the security of graphical password schemes. we show that permitting user selection of passwords in two graphical password schemes, one based directly on an existing commercial product, can yield passwords with entropy far below the theoretical optimum and, in some cases, that are highly correlated with the race or gender of the user. for one scheme, this effect is so dramatic so as to render the scheme insecure. a conclusion of our work is that graphical password schemes of the type we study may generally require a different posture toward password selection than text passwords, where selection by the user remains the norm today.
fixing races for fun and profit: how to use access(2). it is well known that it is insecure to use the access(2) system call in a setuid program to test for the ability of the program's executor to access a file before opening said file. although the access(2) call appears to have been designed exactly for this use, such use is vulnerable to a race condition. this race condition is a classic example of a time-of-check-to-time-of-use (tocttou) problem. we prove the "folk theorem" that no portable, deterministic solution exists without changes to the system call interface, we present a probabilistic solution, and we examine the effect of increasing cpu speeds on the exploitability of the attack.
panalyst: privacy-aware remote error analysis on commodity software . remote error analysis aims at timely detection and remedy of software vulnerabilities through analyzing run-time errors that occur on the client. this objective can only be achieved by offering users effective protection of their private information and minimizing the performance impact of the analysis on their systems without undermining the amount of information the server can access for understanding errors. to this end, we propose in the paper a new technique for privacy-aware remote analysis, called panalyst. panalyst includes a client component and a server component. once a runtime exception happens to an application, panalyst client sends the server an initial error report that includes only public information regarding the error, such as the length of the packet that triggers the exception. using an input built from the report, panalyst server performs a taint analysis and symbolic execution on the application, and adjusts the input by querying the client about the information upon which the execution of the application depends. the client agrees to answer only when the reply does not give away too much user information. in this way, an input that reproduces the error can be gradually built on the server under the client's consent. our experimental study of this technique demonstrates that it exposes a very small amount of user information, introduces negligible overheads to the client and enables the server to effectively analyze an error.
tor: the second-generation onion router. we present tor, a circuit-based low-latency anonymous communication service. this second-generation onion routing system addresses limitations in the original design by adding perfect forward secrecy, congestion control, directory servers, integrity checking, configurable exit policies, and a practical design for location-hidden services via rendezvous points. tor works on the real-world internet, requires no special privileges or kernel modifications, requires little synchronization or coordination between nodes, and provides a reasonable tradeoff between anonymity, usability, and efficiency. we briefly describe our experiences with an international network of more than 30 nodes. we close with a list of open problems in anonymous communication.
to catch a predator: a natural language approach for eliciting malicious payloads. we present an automated, scalable, method for crafting dynamic responses to real-time network requests. specifically, we provide a flexible technique based on natural language processing and string alignment techniques for intelligently interacting with protocols trained directly from raw network traffic. we demonstrate the utility of our approach by creating a low-interaction web-based honeypot capable of luring attacks from search worms targeting hundreds of different web applications. in just over two months, we witnessed over 368, 000 attacks from more than 5, 600 botnets targeting several hundred distinct webapps. the observed attacks included several exploits detected the same day the vulnerabilities were publicly disclosed. our analysis of the payloads of these attacks reveals the state of the art in search-worm based botnets, packed with surprisingly modular and diverse functionality.
on gray-box program tracking for anomaly detection. many host-based anomaly detection systems monitor a process ostensibly running a known program by observing the system calls the process makes. numerous improvements to the precision of this approach have been proposed, such as tracking system call sequences, and various "gray-box" extensions such as examining the program counter or return addresses on the stack when system calls are made. in this paper, we perform the first systematic study of a wide spectrum of such methods. we show that prior approaches can be organized along three axes, revealing new possibilities for system-call-based program tracking. through an empirical analysis of this design space, we shed light on the benefits and costs of various points in the space and identify new regions that appear to outperform prior approaches. in separate contributions, we demonstrate novel mimicry attacks on a recent proposal using return addresses for system-call-based program tracking, and then suggest randomization techniques to make such attacks more difficult.
collapsar: a vm-based architecture for network attack detention center. the honeypot has emerged as an effective tool to provide insights into new attacks and current exploitation trends. though effective, a single honeypot or multiple independently operated honeypots only provide a limited local view of network attacks. deploying and managing a large number of coordinating honeypots in different network domains will not only provide a broader and more diverse view, but also create potentials in global network status inference, early network anomaly detection, and attack correlation in large scale. however, coordinated honeypot deployment and operation require close and consistent collaboration across participating network domains, in order to mitigate potential security risks associated with each honeypot and the non-uniform level of security expertise in different network domains. it is challenging, yet desirable, to provide the two conflicting features of decentralized presence and uniform management in honeypot deployment and operation. to address these challenges, this paper presents collapsar, a virtual-machine-based architecture for network attack detention. a collapsar center hosts and manages a large number of high-interaction virtual honeypots in a local dedicated network. these honeypots appear, to potential intruders, as typical systems in their respective production networks. decentralized logical presence of honeypots provides a wide diverse view of network attacks, while the centralized operation enables dedicated administration and convenient event correlation, eliminating the need for honeypot experts in each production network domain. we present the design, implementation, and evaluation of a collapsar testbed. our experiments with several real-world attack incidences demonstrate the effectiveness and practicality of collapsar.
finding user/kernel pointer bugs with type inference. today's operating systems struggle with vulnerabilities from careless handling of user space pointers. user/kernel pointer bugs have serious consequences for security: a malicious user could exploit a user/kernel pointer bug to gain elevated privileges, read sensitive data, or crash the system. we show how to detect user/kernel pointer bugs using type-qualifier inference, and we apply this method to the linux kernel using cqual, a type-qualifier inference tool. we extend the basic type-inference capabilities of cqual to support context-sensitivity and greater precision when analyzing structures so that cqual requires fewer annotations and generates fewer false positives. with these enhancements, we were able to use cqual to find 17 exploitable user/kernel pointer bugs in the linux kernel. several of the bugs we found were missed by careful hand audits, other program analysis tools, or both.
autograph: toward automated, distributed worm signature detection. today's internet intrusion detection systems (idses) monitor edge networks' dmzs to identify and/or filter malicious flows. while an ids helps protect the hosts on its local edge network from compromise and denial of service, it cannot alone effectively intervene to halt and reverse the spreading of novel internet worms. generation of the worm signatures required by an ids--the byte patterns sought in monitored traffic to identify worms--today entails non-trivial human labor, and thus significant delay: as network operators detect anomalous behavior, they communicate with one another and manually study packet traces to produce a worm signature. yet intervention must occur early in an epidemic to halt a worm's spread. in this paper, we describe autograph, a system that automatically generates signatures for novel internet worms that propagate using tcp transport. autograph generates signatures by analyzing the prevalence of portions of flow payloads, and thus uses no knowledge of protocol semantics above the tcp level. it is designed to produce signatures that exhibit high sensitivity (high true positives) and high specificity (low false positives); our evaluation of the system on real dmz traces validates that it achieves these goals. we extend autograph to share port scan reports among distributed monitor instances, and using trace-driven simulation, demonstrate the value of this technique in speeding the generation of signatures for novel worms. our results elucidate the fundamental trade-off between early generation of signatures for novel worms and the specificity of these generated signatures.
static disassembly of obfuscated binaries. disassembly is the process of recovering a symbolic representation of a program's machine code instructions from its binary representation. recently, a number of techniques have been proposed that attempt to foil the disassembly process. these techniques are very effective against state-of-the-art disassemblers, preventing a substantial fraction of a binary program from being disassembled correctly. this could allow an attacker to hide malicious code from static analysis tools that depend on correct disassembler output (such as virus scanners). the paper presents novel binary analysis techniques that substantially improve the success of the disassembly process when confronted with obfuscated binaries. based on control flow graph information and statistical methods, a large fraction of the program's instructions can be correctly identified. an evaluation of the accuracy and the performance of our tool is provided, along with a comparison to several state-of-the-art disassemblers.
privacy-preserving sharing and correlation of security alerts. we present a practical scheme for internet-scale collaborative analysis of information security threats which provides strong privacy guarantees to contributors of alerts. wide-area analysis centers are proving a valuable early warning service against worms, viruses, and other malicious activities. at the same time, protecting individual and organizational privacy is no longer optional in today's business climate. we propose a set of data sanitization techniques and correlation, while maintaining privacy for alert contributors. our approach is practical, scalable, does not rely on trusted third parties or secure multiparty computation schemes, and does not require sophisticated schemes, and does not require sophisticated key management.
avfs: an on-access anti-virus file system. viruses and other malicious programs are an ever-increasing threat to current computer systems. they can cause serious damage and consume countless hours of system administrators' time to combat. most current virus scanners perform scanning only when a file is opened, closed, or executed. such scanners are inefficient because they scan more data than is needed. worse, scanning on close may detect a virus after it had already been written to stable storage, opening a window for the virus to spread before detection. we developed avfs, a true on-access anti-virus file system that incrementally scans files and prevents infected data from being committed to disk. avfs is a stackable file system and therefore can add virus detection to any other file system: ext3, nfs, etc. avfs supports forensic modes that can prevent a virus from reaching the disk or automatically create versions of potentially infected files to allow safe recovery. avfs can also quarantine infected files on disk and isolate them from user processes. avfs is based on the open-source clamav scan engine, which we significantly enhanced for efficiency and scalability. whereas clamav's performance degrades linearly with the number of signatures, our modified clamav scales logarithmically. our linux prototype demonstrates an overhead of less than 15% for normal user-like workloads.
copilot - a coprocessor-based kernel runtime integrity monitor. copilot is a coprocessor-based kernel integrity monitor for commodity systems. copilot is designed to detect malicious modifications to a host's kernel and has correctly detected the presence of 12 real-world rootkits, each within 30 seconds of their installation with less than a 1% penalty to the host's performance. copilot requires no modifications to the protected host's software and can be expected to operate correctly even when the host kernel is thoroughly compromised - an advantage over traditional monitors designed to run on the host itself.
a virtual honeypot framework. a honeypot is a closely monitored network decoy serving several purposes: it can distract adversaries from more valuable machines on a network, provide early warning about new attack and exploitation trends, or allow in-depth examination of adversaries during and after exploitation of a honeypot. deploying a physical honeypot is often time intensive and expensive as different operating systems require specialized hardware and every honeypot requires its own physical system. this paper presents honeyd, a framework for virtual honeypots that simulates virtual computer systems at the network level. the simulated computer systems appear to run on unallocated network addresses. to deceive network fingerprinting tools, honeyd simulates the networking stack of different operating systems and can provide arbitrary routing topologies and services for an arbitrary number of virtual systems. this paper discusses honeyd's design and shows how the honeyd framework helps in many areas of system security, e.g. detecting and disabling worms, distracting adversaries, or preventing the spread of spam email.
design and implementation of a tcg-based integrity measurement architecture. we present the design and implementation of a secure integrity measurement system for linux. all executable content that is loaded onto the linux system is measured before execution and these measurements are protected by the trusted platform module (tpm) that is part of the trusted computing group (tcg) standards. our system is the first to extend the tcg trust measurement concepts to dynamic executable content from the bios all the way up into the application layer. in effect, we show that many of the microsoft ngscb guarantees can be obtained on today's hardware and today's software and that these guarantees do not require a new cpu mode or operating system but merely depend on the availability of an independent trusted entity, a tpm for example. we apply our trust measurement architecture to a web server application where we show how our system can detect undesirable invocations, such as rootkit programs, and that our measurement architecture is practical in terms of the number of measurements taken and the performance impact of making them.
side effects are not sufficient to authenticate software. kennell and jamieson [kj03] recently introduced the genuinity system for authenticating trusted software on a remote machine without using trusted hardware. genuinity relies on machine-specific computations, incorporating side effects that cannot be simulated quickly. the system is vulnerable to a novel attack, which we call a substitution attack. we implement a successful attack on genuinity, and further argue this class of schemes are not only impractical but unlikely to succeed without trusted hardware.
design of the eros trusted window system. window systems are the primary mediator of user input and output in modern computing systems. they are also a commonly used interprocess communication mechanism. as a result, they play a key role in the enforcement of security policies and the protection of sensitive information. a user typing a password or passphrase must be assured that it is disclosed exclusively to the intended program. in highly secure systems, global policies concerning information flow restrictions must be honored. most window systems today, including x11 and microsoft windows, have carried forward the presumptive trust assumptions of the xerox alto from which they were conceptually derived. these assumptions are inappropriate for modern computing environments. in this paper, we present the design of a new trusted window system for the eros capability-based operating system. the eros window system (ews) provides robust traceability of user volition and is capable (with extension) of enforcing mandatory access controls. the entire implementation of ews is less than 4,500 lines, which is a factor of ten smaller than previous trusted window systems such as trusted x, and well within the range of what can feasibly be evaluated for high assurance.
graphical dictionaries and the memorable space of graphical passwords. in commonplace textual password schemes, users choose passwords that are easy to recall. since memorable passwords typically exhibit patterns, they are exploitable by brute-force password crackers using attack dictionaries. this leads us to ask what classes of graphical passwords users find memorable. we postulate one such class supported by a collection of cognitive studies on visual recall, which can be characterized as mirror symmetric (reflective) passwords. we assume that an attacker would put this class in an attack dictionary for graphical passwords and propose how an attacker might order such a dictionary. we extend the existing analysis of graphical passwords by analyzing the size of the mirror symmetric password space relative to the full password space of the graphical password scheme of jermyn et al. (1999), and show it to be exponentially smaller (assuming appropriate axes of reflection). this reduction in size can be compensated for by longer passwords: the size of the space of mirror symmetric passwords of length about l + 5 exceeds that of the full password space for corresponding length l ≤ 14 on a 5 × 5 grid. this work could be used to help in formulating password rules for graphical password users and in creating proactive graphical password checkers.
very fast containment of scanning worms. computer worms - malicious, self-propagating programs - represent a significant threat to large networks. one possible defense, containment, seeks to limit a worm's spread by isolating it in a small subsection of the network. in this work we develop containment algorithms suitable for deployment in high-speed, low-cost network hardware. we show that these techniques can stop a scanning host after fewer than 10 scans with a very low false-positive rate. we also augment this approach by devising mechanisms for cooperation that enable multiple containment devices to more effectively detect and respond to an emerging infection. finally, we discuss ways that a worm can attempt to bypass containment techniques in general, and ours in particular.
securing frame communication in browsers. many web sites embed third-party content in frames, relying on the browser's security policy to protect against malicious content. however, frames provide insufficient isolation in browsers that let framed content navigate other frames. we evaluate existing frame navigation policies and advocate a stricter policy, which we deploy in the open-source browsers. in addition to preventing undesirable interactions, the browser's strict isolation policy also affects communication between cooperating frames. we therefore analyze two techniques for interframe communication between isolated frames. the first method, fragment identifier messaging, initially provides confidentiality without authentication, which we repair using concepts from a well-known network protocol. the second method, <code>postmessage</code>, initially provides authentication, but we discover an attack that breaches confidentiality. we propose improvements in the <code>postmessage</code> api to provide confidentiality; our proposal has been standardized and adopted in browser implementations.
votebox: a tamper-evident, verifiable electronic voting system. commercial electronic voting systems have experienced many high-profile software, hardware, and usability failures in real elections. while it is tempting to abandon electronic voting altogether, we show how a careful application of distributed systems and cryptographic techniques can yield voting systems that surpass current systems and their analog forebears in trustworthiness and usability. we have developed the votebox, a complete electronic voting system that combines several recent e-voting research results into a coherent whole that can provide strong end-to-end security guarantees to voters. votebox machines are locally networked and all critical election events are broadcast and recorded by every machine on the network. votebox network data, including encrypted votes, can be safely relayed to the outside world in real time, allowing independent observers with personal computers to validate the system as it is running. we also allow any voter to challenge a votebox, while the election is ongoing, to produce proof that ballots are cast as intended. the votebox design offers a number of pragmatic benefits that can help reduce the frequency and impact of poll worker or voter errors.
lest we remember: cold boot attacks on encryption keys. contrary to widespread assumption, dynamic ram (dram), the main memory in most modern computers, retains its contents for several seconds after power is lost, even at room temperature and even if removed from a motherboard. although dram becomes less reliable when it is not refreshed, it is not immediately erased, and its contents persist sufficiently for malicious (or forensic) acquisition of usable full-system memory images. we show that this phenomenon limits the ability of an operating system to protect cryptographic key material from an attacker with physical access to a machine. it poses a particular threat to laptop users who rely on disk encryption: we demonstrate that it could be used to compromise several popular disk encryption products without the need for any special devices or materials. we experimentally characterize the extent and predictability of memory retention and report that remanence times can be increased dramatically with simple cooling techniques. we offer new algorithms for finding cryptographic keys in memory images and for correcting errors caused by bit decay. though we discuss several strategies for mitigating these risks, we know of no simple remedy that would eliminate them.
reverse-engineering a cryptographic rfid tag. the security of embedded devices often relies on the secrecy of proprietary cryptographic algorithms. these algorithms and their weaknesses are frequently disclosed through reverse-engineering software, but it is commonly thought to be too expensive to reconstruct designs from a hardware implementation alone. this paper challenges that belief by presenting an approach to reverse-engineering a cipher from a silicon implementation. using this mostly automated approach, we reveal a cipher from an rfid tag that is not known to have a software or micro-code implementation. we reconstruct the cipher from the widely used mifare classic rfid tag by using a combination of image analysis of circuits and protocol analysis. our analysis reveals that the security of the tag is even below the level that its 48-bit key length suggests due to a number of design flaws. weak random numbers and a weakness in the authentication protocol allow for pre-computed rainbow tables to be used to find any key in a matter of seconds. our approach of deducing functionality from circuit images is mostly automated, hence it is also feasible for large chips. the assumption that algorithms can be kept secret should therefore to be avoided for any type of silicon chip.
highly predictive blacklisting. the notion of blacklisting communication sources has been a well-established defensive measure since the origins of the internet community. in particular, the practice of compiling and sharing lists of the worst offenders of unwanted traffic is a blacklisting strategy that has remained virtually unquestioned over many years. but do the individuals who incorporate such blacklists into their perimeter defenses benefit from the blacklisting contents as much as they could from other list-generation strategies? in this paper, we will argue that there exist better alternative blacklist generation strategies that can produce higher-quality results for an individual network. in particular, we introduce a blacklisting system based on a relevance ranking scheme borrowed from the link-analysis community. the system produces customized blacklists for individuals who choose to contribute data to a centralized log-sharing infrastructure. the ranking scheme measures how closely related an attack source is to a contributor, using that attacker's history and the contributor's recent log production patterns. the blacklisting system also integrates substantive log prefiltering and a severity metric that captures the degree to which an attacker's alert patterns match those of common malware-propagation behavior. our intent is to yield individualized blacklists that not only produce significantly higher hit rates, but that also incorporate source addresses that pose the greatest potential threat. we tested our scheme on a corpus of over 700 million log entries produced from the dshield data center and the result shows that our blacklists not only enhance hit counts but also can proactively incorporate attacker addresses in a timely fashion. an early form of our system have been fielded to dshield contributors over the last year.
botminer: clustering analysis of network traffic for protocol- and structure-independent botnet detection. botnets are now the key platform for many internet attacks, such as spam, distributed denial-of-service (ddos), identity theft, and phishing. most of the current botnet detection approaches work only on specific botnet command and control (c&c) protocols (e.g., irc) and structures (e.g., centralized), and can become ineffective as botnets change their c&c techniques. in this paper, we present a general detection framework that is independent of botnet c&c protocol and structure, and requires no a priori knowledge of botnets (such as captured bot binaries and hence the botnet signatures, and c&c server names/addresses). we start from the definition and essential properties of botnets. we define a botnet as a coordinated group of malware instances that are controlled via c&c communication channels. the essential properties of a botnet are that the bots communicate with some c&c servers/peers, perform malicious activities, and do so in a similar or correlated way. accordingly, our detection framework clusters similar communication traffic and similar malicious traffic, and performs cross cluster correlation to identify the hosts that share both similar communication patterns and similar malicious activity patterns. these hosts are thus bots in the monitored network. we have implemented our botminer prototype system and evaluated it using many real network traces. the results show that it can detect real-world botnets (irc-based, http-based, and p2p botnets including nugache and storm worm), and has a very low false positive rate.
automatic generation of xss and sql injection attacks with goal-directed model checking. cross-site scripting (xss) and sql injection errors are two prominent examples of taint-based vulnerabilities that have been responsible for a large number of security breaches in recent years. this paper presents qed, a goal-directed model-checking system that automatically generates attacks exploiting taint-based vulnerabilities in large java web applications. this is the first time where model checking has been used successfully on real-life java programs to create attack sequences that consist of multiple http requests. qed accepts any java web application that is written to the standard servlet specification. the analyst specifies the vulnerability of interest in a specification that looks like a java code fragment, along with a range of values for form parameters. qed then generates a goal-directed analysis from the specification to perform session-aware tests, optimizes to eliminate inputs that are not of interest, and feeds the remainder to a model checker. the checker will systematically explore the remaining state space and report example attacks if the vulnerability specification is matched. qed provides better results than traditional analyses because it does not generate any false positive warnings. it proves the existence of errors by providing an example attack and a program trace showing how the code is compromised. past experience suggests this is important because it makes it easy for the application maintainer to recognize the errors and to make the necessary fixes. in addition, for a class of applications, qed can guarantee that it has found all the potential bugs in the program. we have run qed over 3 java web applications totaling 130,000 lines of code. we found 10 sql injections and 13 cross-site scripting errors.
selective versioning in a secure disk system. making vital disk data recoverable even in the event of os compromises has become a necessity, in view of the increased prevalence of os vulnerability exploits over the recent years. we present the design and implementation of a secure disk system, svsds, that performs selective, flexible, and transparent versioning of stored data, at the disk-level. in addition to versioning, svsds actively enforces constraints to protect executables and system log files. most existing versioning solutions that operate at the disk-level are unaware of the higher-level abstractions of data, and hence are not customizable. we evolve a hybrid solution that combines the advantages of disk-level and file-system--level versioning systems thereby ensuring security, while at the same time allowing flexible policies. we implemented and evaluated a software-level prototype of svsds in the linux kernel and it shows that the space and performance overheads associated with selective versioning at the disk level are minimal.
practical symmetric key cryptography on modern graphics hardware. graphics processors are continuing their trend of vastly outperforming cpus while becoming more general purpose. the latest generation of graphics processors have introduced the ability handle integers natively. this has increased the gpu's applicability to many fields, especially cryptography. this paper presents an application oriented approach to block cipher processing on gpus. a new block based conventional implementation of aes on an nvidia g80 is shown with 4-10x speed improvements over cpu implementations and 2-4x speed increase over the previous fastest aes gpu implementation. we outline a general purpose data structure for representing cryptographic client requests which is suitable for execution on a gpu. we explore the issues related to the mapping of this general structure to the gpu. finally we present the first analysis of the main encryption modes of operation on a gpu, showing the performance and behavioural implications of executing these modes under the outlined general purpose data model. our aes implementation is used as the underlying block cipher to show the overhead of moving from an optimised hard-coded approach to a generalised one.
an improved clock-skew measurement technique for revealing hidden services. the tor anonymisation network allows services, such as web servers, to be operated under a pseudonym. in previous work murdoch described a novel attack to reveal such hidden services by correlating clock skew changes with times of increased load, and hence temperature. clock skew measurement suffers from two main sources of noise: network jitter and timestamp quantisation error. depending on the target's clock frequency the quantisation noise can be orders of magnitude larger than the noise caused by typical network jitter. quantisation noise limits the previous attacks to situations where a high frequency clock is available. it has been hypothesised that by synchronising measurements to the clock ticks, quantisation noise can be reduced. we show how such synchronisation can be achieved and maintained, despite network jitter. our experiments show that synchronised sampling significantly reduces the quantisation error and the remaining noise only depends on the network jitter (but not clock frequency). our improved skew estimates are up to two magnitudes more accurate for low-resolution timestamps and up to one magnitude more accurate for high-resolution timestamps, when compared to previous random sampling techniques. the improved accuracy not only allows previous attacks to be executed faster and with less network traffic but also opens the door to previously infeasible attacks on low-resolution clocks, including measuring skew of a http server over the anonymous channel.
measurement and classification of humans and bots in internet chat. the abuse of chat services by automated programs, known as chat bots, poses a serious threat to internet users. chat bots target popular chat networks to distribute spam and malware. in this paper, we first conduct a series of measurements on a large commercial chat network. our measurements capture a total of 14 different types of chat bots ranging from simple to advanced. moreover, we observe that human behavior is more complex than bot behavior. based on the measurement study, we propose a classification system to accurately distinguish chat bots from human users. the proposed classification system consists of two components: (1) an entropy-based classifier and (2) a machine-learning-based classifier. the two classifiers complement each other in chat bot detection. the entropy-based classifier is more accurate to detect unknown chat bots, whereas the machine-learning-based classifier is faster to detect known chat bots. our experimental evaluation shows that the proposed classification system is highly effective in differentiating bots from humans.
an empirical security study of the native code in the jdk. it is well known that the use of native methods in java defeats java's guarantees of safety and security, which is why the default policy of java applets, for example, does not allow loading non-local native code. however, there is already a large amount of trusted native c/c++ code that comprises a significant portion of the java development kit (jdk). we have carried out an empirical security study on a portion of the native code in sun's jdk 1.6. by applying static analysis tools and manual inspection, we have identified in this security-critical code previously undiscovered bugs. based on our study, we describe a taxonomy to classify bugs. our taxonomy provides guidance to construction of automated and accurate bug-finding tools. we also suggest systematic remedies that can mediate the threats posed by the native code.
cloudav: n-version antivirus in the network cloud. antivirus software is one of the most widely used tools for detecting and stopping malicious and unwanted files. however, the long term effectiveness of traditional host-based antivirus is questionable. antivirus software fails to detect many modern threats and its increasing complexity has resulted in vulnerabilities that are being exploited by malware. this paper advocates a new model for malware detection on end hosts based on providing antivirus as an in-cloud network service. this model enables identification of malicious and unwanted software by multiple, heterogeneous detection engines in parallel, a technique we term 'n-version protection'. this approach provides several important benefits including better detection of malicious software, enhanced forensics capabilities, retrospective detection, and improved deployability and management. to explore this idea we construct and deploy a production quality in-cloud antivirus system called cloudav. cloudav includes a lightweight, cross-platform host agent and a network service with ten antivirus engines and two behavioral detection engines. we evaluate the performance, scalability, and efficacy of the system using data from a real-world deployment lasting more than six months and a database of 7220 malware samples covering a one year period. using this dataset we find that cloudav provides 35% better detection coverage against recent threats compared to a single antivirus engine and a 98% detection rate across the full dataset. we show that the average length of time to detect new threats by an antivirus engine is 48 days and that retrospective detection can greatly minimize the impact of this delay. finally, we relate two case studies demonstrating how the forensics capabilities of cloudav were used by operators during the deployment.
proactive surge protection: a defense mechanism for bandwidth-based attacks. large-scale bandwidth-based distributed denial-of-service (ddos) attacks can quickly knock out substantial parts of a network before reactive defenses can respond. even traffic that is not under direct attack can suffer significant collateral damage if the traffic passes through links that are common to attack routes. this paper presents a proactive surge protection (psp) mechanism that aims to provide a broad first line of defense against ddos attacks. the approach aims to minimize collateral damage by providing bandwidth isolation between traffic flows. the proposed solution is readily deployable using existing router mechanisms and does not rely on any unauthenticated packet header information. our extensive evaluation across two large commercial backbone networks, using both distributed and targeted attacks, shows that up to 95.5% of the network could suffer collateral damage, but our solution was able to significantly reduce the amount of collateral damage by up to 97.58% in terms of the number of packets dropped and 90.36% in terms of the number of flows with packet loss. further, we show that psp can maintain low packet loss rates even when the intensity of attacks is increased significantly.
the practical subtleties of biometric key generation. the inability of humans to generate and remember strong secrets makes it difficult for people to manage cryptographic keys. to address this problem, numerous proposals have been suggested to enable a human to repeatably generate a cryptographic key from her biometrics, where the strength of the key rests on the assumption that the measured biometrics have high entropy across the population. in this paper we show that, despite the fact that several researchers have examined the security of bkgs, the common techniques used to argue the security of practical systems are lacking. to address this issue we reexamine two well known, yet sometimes misunderstood, security requirements. we also present another that we believe has not received adequate attention in the literature, but is essential for practical biometric key generators. to demonstrate that each requirement has significant importance, we analyze three published schemes, and point out deficiencies in each. for example, in one case we show that failing to meet a requirement results in a construction where an attacker has a 22% chance of finding ostensibly 43-bit keys on her first guess. in another we show how an attacker who compromises a user's cryptographic key can then infer that user's biometric, thus revealing any other key generated using that biometric. we hope that by examining the pitfalls that occur continuously in the literature, we enable researchers and practitioners to more accurately analyze proposed constructions.
hypervisor support for identifying covertly executing binaries. hypervisors have been proposed as a security tool to defend against malware that subverts the os kernel. however, hypervisors must deal with the semantic gap between the low-level information available to them and the high-level os abstractions they need for analysis. to bridge this gap, systems have proposed making assumptions derived from the kernel source code or symbol information. unfortunately, this information is nonbinding - rootkits are not bound to uphold these assumptions and can escape detection by breaking them. in this paper, we introduce patagonix, a hypervisor-based system that detects and identifies covertly executing binaries without making assumptions about the os kernel. instead, patagonix depends only on the processor hardware to detect code execution and on the binary format specifications of executables to identify code and verify code modifications. with this, patagonix can provide trustworthy information about the binaries running on a system, as well as detect when a rootkit is hiding or tampering with executing code. we have implemented a patagonix prototype on the xen 3.0.3 hypervisor. because patagonix makes no assumptions about the os kernel, it can identify code from application and kernel binaries on both linux and windows xp. patagonix introduces less than 3% overhead on most applications.
autoises: automatically inferring security specification and detecting violations. the importance of software security cannot be overstated. in the past, researchers have applied program analysis techniques to automatically detect security vulnerabilities and verify security properties. however, such techniques have limited success in reality because they require manually provided code-level security specifications. manually writing and generating these code-level security specifications are tedious and error-prone. additionally, they seldom exist in production software. in this paper, we propose a novel method and tool, called autoises, which automatically infers security specifications by statically analyzing source code, and then directly use these specifications to automatically detect security violations. our experiments with the linux kernel and xen demonstrated the effectiveness of this approach - autoises automatically generated 84 security specifications and detected 8 vulnerabilities in the linux kernel and xen, 7 of which have already been confirmed by the corresponding developers.
helios: web-based open-audit voting. voting with cryptographic auditing, sometimes called open-audit voting, has remained, for the most part, a theoretical endeavor. in spite of dozens of fascinating protocols and recent ground-breaking advances in the field, there exist only a handful of specialized implementations that few people have experienced directly. as a result, the benefits of cryptographically audited elections have remained elusive. we present helios, the first web-based, open-audit voting system. helios is publicly accessible today: anyone can create and run an election, and any willing observer can audit the entire process. helios is ideal for on-line software communities, local clubs, student government, and other environments where trustworthy, secret-ballot elections are required but coercion is not a serious concern. with helios, we hope to expose many to the power of open-audit elections.
unidirectional key distribution across time and space with applications to rfid security. we explore the problem of secret-key distribution in unidirectional channels, those in which a sender transmits information blindly to a receiver. we consider two approaches: (1) key sharing across space, i.e., via simultaneously emitted values that may follow different data paths and (2) key sharing across time, i.e., in temporally staggered emissions. our constructions are of general interest, treating, for instance, the basic problem of constructing highly compact secret shares. our main motivating problem, however, is practical key management in rfid (radio-frequency identification) systems. we describe the application of our techniques to rfid-enabled supply chains and a prototype privacy-enhancing system.
all your iframes point to us. as the web continues to play an ever increasing role in information exchange, so too is it becoming the prevailing platform for infecting vulnerable hosts. in this paper, we provide a detailed study of the pervasiveness of so-called drive-by downloads on the internet. drive-by downloads are caused by urls that attempt to exploit their visitors and cause malware to be installed and run automatically. over a period of 10 months we processed billions of urls, and our results shows that a non-trivial amount, of over 3 million malicious urls, initiate drive-by downloads. an even more troubling finding is that approximately 1.3% of the incoming search queries to google's search engine returned at least one url labeled as malicious in the results page. we also explore several aspects of the drive-by downloads problem. specifically, we study the relationship between the user browsing habits and exposure to malware, the techniques used to lure the user into the malware distribution networks, and the different properties of these networks.
privacy-preserving location tracking of lost or stolen devices: cryptographic techniques and replacing trusted third parties with dhts. we tackle the problem of building privacy-preserving device-tracking systems--or private methods to assist in the recovery of lost or stolen internet-connected mobile devices. the main goals of such systems are seemingly contradictory: to hide the device's legitimately-visited locations from third-party services and other parties (location privacy) while simultaneously using those same services to help recover the device's location(s) after it goes missing (device-tracking). we propose a system, named adeona, that nevertheless meets both goals. it provides strong guarantees of location privacy while preserving the ability to efficiently track missing devices. we build a version of adeona that uses opendht as the third party service, resulting in an immediately deployable system that does not rely on any single trusted third party. we describe numerous extensions for the basic design that increase adeona's suitability for particular deployment environments.
multi-flow attacks against network flow watermarking schemes. we analyze several recent schemes for watermarking network flows based on splitting the flow into intervals. we show that this approach creates time dependent correlations that enable an attack that combines multiple watermarked flows. such an attack can easily be mounted in nearly all applications of network flow watermarking, both in anonymous communication and stepping stone detection. the attack can be used to detect the presence of a watermark, recover the secret parameters, and remove the watermark from a flow. the attack can be effective even if different the watermarks in different flows carry different messages. we analyze the efficacy of our attack using a probabilistic model and a markov-modulated poisson process (mmpp) model of interactive traffic. we also implement our attack and test it using both synthetic and real-world traces, showing that our attack is effective with as few as 10 watermarked flows. finally, we propose a countermeasure that defeats the attack by using multiple watermark positions.
netauth: supporting user-based network services. in user-based network services (ubns), the process servicing requests from user u runs under u's id. this enables (operating system) access controls to tailor service authorization to u. like privilege separation, ubns partitions applications into processes in such a way that each process' permission is minimized. however, because ubns fundamentally affects the structure of an application, it is best performed early in the design process. ubns depends on other security mechanisms, most notably authentication and cryptographic protections. these seemingly straightforward needs add considerable complexity to application programming. to avoid this complexity, programmers regularly ignore security issues at the start of program construction. however, after the application is constructed, ubns is difficult to apply since it would require significant structural changes to the application code. this paper describes easy-to-use security mechanisms supporting ubns, and thus significantly reducing the complexity of building ubns applications. this simplification enables much earlier (and hence more effective) use of ubns. it focuses the application developer's attention on the key security task in application development, partitioning applications so that least privilege can be effectively applied. it removes vulnerabilities due to poor application implementation or selection of security mechanisms. finally, it enables significant control to be externally exerted on the application, increasing the ability of system administrators to control, understand, and secure such services.
verifying compliance of trusted programs. in this paper, we present an approach for verifying that trusted programs correctly enforce system security goals when deployed. a trusted program is trusted to only perform safe operations despite have the authority to perform unsafe operations; for example, initialization programs, administrative programs, root network daemons, etc. currently, these programs are trusted without concrete justification. the emergence of tools for building programs that guarantee policy enforcement, such as security-typed languages (stls), and mandatory access control systems, such as user-level policy servers, finally offers a basis for justifying trust in such programs: we can determine whether these programs can be deployed in compliance with the reference monitor concept. since program and system policies are defined independently, often using different access control models, compliance for all program deployments may be difficult to achieve in practice, however. we observe that the integrity of trusted programs must dominate the integrity of system data, and use this insight, which we call the pidsi approach, to infer the relationship between program and system policies, enabling automated compliance verification. we find that the pidsi approach is consistent with the selinux reference policy for its trusted programs. as a result, trusted program policies can be designed independently of their target systems, yet still be deployed in a manner that ensures enforcement of system security goals.
multi-robot simultaneous localization and mapping using particle filters. this paper describes an on-line algorithm for multi-robot simultaneous localization and mapping (slam). the starting point is the single-robot rao-blackwellized particle filter described by hähnel et al., and three key generalizations are made. first, the particle filter is extended to handle multi-robot slam problems in which the initial pose of the robots is known (such as occurs when all robots start from the same location). second, an approximation is introduced to solve the more general problem in which the initial pose of robots is not known a priori (such as occurs when the robots start from widely separated locations). in this latter case, it is assumed that pairs of robots will eventually encounter one another, thereby determining their relative pose. this relative attitude is used to initialize the filter, and subsequent observations from both robots are combined into a common map. third and finally, a method is introduced to integrate observations collected prior to the first robot encounter, using the notion of a virtual robot travelling backwards in time. this novel approach allows one to integrate all data from all robots into a single common map.
a filtered retrieval technique for structural information. we present a filtered retrieval technique for structural information on internet-scale knowledge such as large-scale xml data in the web. the technique evaluates xml standard queries on heterogeneous xml documents using information retrieval technique based on the relational tables in relational database management systems. the xml standard queries, xpath queries, in their general form are partial match queries, and these queries are particularly useful for searching documents of heterogeneous schemas. thus, our technique is geared for partial match queries expressed as the queries. this indexes the elements in label paths, which are sequences of node labels, like keywords in texts, and finds the label paths matching a given query.
intelligent embedded real-time software architecture for dynamic skill selection and identification in multi-shaped robots. this paper presents an intelligent embedded, modular software and hardware architecture for multi-shaped robots using real-time dynamic skill identification and selection. it is a layered architecture with reusable and reconfigurable modules, which can embed in an expert system as both hardware and software modules and demonstrated with snake robot and physically reconfigured four-legged robot as examples. the intelligent dynamic selection and synchronization of selected behaviors enable the mobile robot to perform many tasks in complex situations. the architecture proposed is applicable to multi-shaped robots, for dynamic selection of behaviors during reconfiguration, where the hardware and software modules can be reused during reconfiguration. related videos of these robots can be viewed at: http://rtlab.knu.ac.kr/robots.htm
efficient rfid authentication protocol for minimizing rfid tag computation. rfid systems have become vital technology for realizing ubiquitous computing environments. however, features of rfid systems present potential security and privacy problems. in an effort to resolve these problems, many kinds of security and privacy enhancement technologies have been researched. however, solutions produced to date still have flaws and are not sufficiently effective for real rfid systems such as the epcglobal network™. therefore, in this paper, to make rfid systems more secure and efficient, improved technology based on password, is proposed. the proposed technology combines an encryption algorithm with a password-derived key, and can be applied to low-cost rfid systems for enhancing the security and privacy of these systems.
approximate life cycle assessment of product concepts using a hybrid genetic algorithm and neural network approach. environmental impact assessment of products has been a key area of research and development for sustainable product development. many companies copy these trends and they consider environmental criteria into the product design process. life cycle assessment (lca) is used to support the decision-making for product design and the best alternative can be selected by its estimated environmental impacts and benefits. the need for analytical lca has resulted in the development of approximate lca. this paper presents an optimization strategy for approximate lca using a hybrid approach which incorporate genetic algorithms (gas) and neural networks (nns). in this study, gas are employed to select feature subsets to eliminate irrelevant factors and determine the number of hidden nodes and processing elements. in addition, gas will optimize the connection weights between layers of nn simultaneously. experimental results show that a hybrid ga and nn approach outperforms the conventional backpropagation neural network and verify the effectiveness of the proposed approach.
investigative data mining for counterterrorism. after the tragic events of 9/11, the concern about national security has increased significantly. however, law enforcement agencies, particularly in view of current emphasis on terrorism, increasingly face the challenge of information overload and lack of advanced, automated techniques for the effective analysis of criminal and terrorism activities. data mining applied in the context of law enforcement and intelligence analysis, called investigative data mining (idm), holds the promise of alleviating such problems. an important problem targeted by idm is the identification of terror/crime networks, based on available intelligence and other information. in this paper, we present an understanding to show how idm works and the importance of this approach in the context of terrorist network investigations and give particular emphasis on how to destabilize them by knowing the information about leaders and subgroups through hierarchical structure.
optimally pricing european options with real distributions. most option pricing methods use mathematical distributions to approximate underlying asset behavior. however, it is difficult to approximate the real distribution using pure mathematical distribution approaches. this study first introduces an innovative computational method of pricing european options based on the real distributions of the underlying asset. this computational approach can also be applied to expected value related applications that require real distributions rather than mathematical distributions. the contributions of this study include the following: a) it solves the risk neutral issue related to price options with real distributions, b) it proposes a simple method adjusting the standard deviation according to the practical need to apply short term volatility to real world applications and c) it demonstrates that modern databases are capable of handling large amounts of sample data to provide efficient execution speeds.
ubiquitous healthcare system using context information based on the dogf. this paper proposed the ubiquitous healthcare system using context information for the personalized healthcare services in a home network environment. the context information is generated by location, health, and home environment information collected from sensors/devices equipped in home. this system is designed on the distributed object group framework (dogf) supporting the functions which manage context information, applications and devices as one or more logical units in healthcare home environment. especially, the system provides the continuous healthcare multimedia service by generating the context information based on resident's location through the mobile proxy and the context provider as components of the dogf. for verifying the execution of our system, we implemented the seamless multimedia service, the prescription/advice service and the schedule notification/alarm service according to a healthcare scenario in home. finally, we showed the execution results of healthcare home services by using service devices existed in the residential space.
moving cast shadow elimination algorithm using principal component analysis in vehicle surveillance video. moving cast shadows on object distort figures which causes serious detection deficiency and analysis problems in its related applications. thus, shadow removal plays an important role for robust object extraction from surveillance videos. in this paper, we propose an algorithm to eliminate moving cast shadow that uses features of color information about foreground and background figures. the significant information among the features of shadow, background and object is extracted by pca transformation and tilting coordinates system. by appropriate analyses of the information, we found distributive characteristics of colors from the tilted pca space. with this new color space, we can detect moving cast shadow and remove them effectively.
real-time travel time estimation using automatic vehicle identification data in hong kong. this paper proposes a real-time traveler information system (rtis) for estimating current travel times using automatic vehicle identification (avi) data in hong kong. the current travel times, in rtis, are estimated by real-time avi data, the off-line travel time estimates and the related variance-covariance relationships between road links. the real-time avi data adopted for rtis are autotoll tag data in hong kong; whereas the off-line link travel time estimates and their variance-covariance matrices are obtained from a traffic flow simulator. on the basis of integration of these real-time and off-line traffic data, the current traffic conditions on hong kong major roads can be estimated at five-minute intervals. a case study is carried out in kowloon central urban area to collect observed data for validation of the results of the proposed rtis.
a frequency adaptive packet wavelet coder for still images using cnn. we present the packet wavelet coder implemented with cellular neural network architecture as an example of the applications of cellular neural networks. this paper also demonstrates how the cellular neural universal machine (cnnum) architecture can be extended to image compression. the packet wavelet coder performs the operation of image compression, aided by cnn architecture. it uses the highly parallel nature of the cnn structure and its speed outperforms traditional digital computers. in packet wavelet coder, an image signal can be analyzed by passing it through an analysis filter banks followed by a decimation process, according to the rules of packet wavelets. the simulation results indicate that the quality of the reconstructed image is improvised by using packet wavelet coding scheme.
design and implementation of a performance analysis and visualization toolkit for cluster environments. the low cost and wide availability of pc-based clusters have made them excellent alternatives to supercomputing. however, while network of workstations are readily available, there is an increasing need for performance tools that support these computing platforms in order to achieve even higher performance. strategies that may be considered toward such performance achievement we may list are: performance data analysis, algorithm design, parallel program restructuring, among others. introduced in this paper is a toolkit that generates performance data and graphical charts of pure mpi, pure openmp, as well as hybrid mpi/openmp parallel applications, reflecting to its sequence of execution over time and cache behavior, with the use of dp*graph representation, a parallel version of timing graph. that is, parallel applications have their execution sequence in a cluster system platform shown through graphical charts composed by sequential codes, parallel threads, dependencies and communication structures, symbols defined in dp*graph. it is discussed the implementation of this toolkit, as also some of its features, together with experimental use of the toolkit on parallel applications such as matrix multiplication (parallel implementation using mpi) and spice3 (parallel implementation using openmp).
load balancing using dynamic replication scheme for the distributed object group. corba is the most widely used middleware for implementing distributed application. currently, object implementations facilitate object group model to organize the object services. in addition to the complexity of designing the object groups, researchers also seek to improve the quality of service (qos) by various means such as implementing load balancing to the system. this paper deals with the proposed load balancing service of distributed object groups. the proposed load balancing service uses the dynamic replication scheme which is mechanized by flow balance assumption (fba) that derives from the arrival and service rate to execute request forwarding to new objects. the proposed on-demand replication scheme adjusts the number of replicated objects based on the arrival rate to minimize the waiting time of clients. it consists of procedures such as intercepting the request and executing on-demand activation of objects. the result of the simulation shows the improvement of the total mean client request completion time of the system as compared to other load balancing schemes.
a user-oriented gis search service using ontology in location-based services. geographical information systems (gis) technology plays an increasingly important role in location-based services (lbs), which include applications such as car navigation, tour guide information, route-guide information, and tracking systems. most gis applications focus on showing the stored information on a map, not providing user-orientedmap services to register user's preferred information. we propose an ontology-based approach to register and to search personal information on maps. we also implement a gis search prototype considering user preferences using favorite food information and having a connection function to web sites on the map using our digital map format. our contribution is to provide a personalized service by connecting lbs/gis services and ontology technology.
the situation dependent application areas of epc sensor network in u-healthcare. electronic product code (epc) sensor network is a collection of objects for sensing data. it is crucial to ubiquitous society. it can provide an application service based on situation dependency with its properties. the situation dependency is an emerging concept which can collect location-based and personalized information. with the situation dependency, many industries can serve ubiquitous service for independent users. u-healthcare is one of ubiquitous service to provide seamless medical treatment. the concept of situation dependency is applied in u-healthcare with epc sensor network technology. due to specialized four properties of epc sensor network which are driven from this paper, the situation dependency is well-established in u-healthcare service. in this paper, we defined value and architecture of u-healthcare service and we analyzed application areas of u-healthcare.
repetition coding aided time-domain cancellation for inter-carrier interference reduction in ofdm systems. in this paper, an enhanced time-domain cancellation method is proposed for inter-carrier interference (ici) reduction in ofdm systems. the conventional time-domain cancellation neglects the effect of channel variation in cyclic prefix during the time-domain cancellation and does not work well in deep fades. in order to supplement the conventional method, the simple repetition (de-)coding and the modulation order increasing are employed in the time-domain cancellation. the repetition coding provides reliable symbols in the regeneration operation, and the modulation order increasing maintains or increases the spectral efficiency. simulation results indicate that the proposed method using 16qam significantly improves the ber performance compared to the conventional method using qpsk, while maintains the spectral efficiency. moreover, the proposed method using 64qam concurrently improves both the ber performance and the spectral efficiency.
optimization and routing discovery for ad hoc wireless networks: a cross layer approach. wireless communication links are time-varying in nature, causing degradation of network's performance; this however, could be alleviated by allowing cross layer interaction in the protocol stack. hence, optimization problems formulated in this paper considered parameters from the physical, mac, and network layers where an optimal transmission power vector that minimizes the overall transmission power of the network, satisfying the sinr, required data rate, and maximum transmission power constraints was formulated to exist. distributed algorithms for the joint scheduling, power control and routing were also derived and an energy-aware routing algorithm which maximizes network lifetime was proposed. the energy consumed by each node in the routing path and delays associated on each transmission were considered as link cost such that a route with minimum link cost is utilized. basically, the routing algorithm searched an energy-efficient route, satisfying the energy constraint of each node in a routing path at a tolerable delay.
agent-based intelligent decision support for the home healthcare environment. this paper brings together the multi-agent platform and artificial neural network to create an intelligent decision support system for a group of medical specialists collaborating in the pervasive management of healthcare for chronic patients. artificial intelligence is employed to support the management of chronic illness through the early identification of adverse trends in the patient's physiological data. a framework based on software agents that proxy for participants in a home healthcare environment is presented. the proposed approach enables the agent-based home healthcare system to identify the emergent chronic conditions from the patterns of symptoms and allows the appropriate remediation to be initiated and managed transparently.
automatic marker-driven three dimensional watershed transform for tumor volume measurement. molecular imaging can detect abnormal functions of living tissue. functional abnormality in gene expression or metabolism can be represented as altered volume or probe intensity. accurate measurement of volume and probe intensity in tissue mainly relies on image segmentation techniques. thus, segmentation is a critical technique in quantitative analysis. we developed an automatic object marker-driven three dimensional(3d) watershed transform for quantitative analysis of functional images. to reduce the discretization error in volume measurement less than 5%, the size criteria for digital spheres were investigated to provide the minimum volume. when applied to spect images, our segmentation technique produced 89% or higher accuracy in the volume and intensity of tumors and also showed high correlation with the ground truth segmentation (ρ > 0.93). the developed 3d method did not require interactive object marking and offered higher accuracy than a 2d watershed approach. furthermore, it computed faster than the segmentation technique based on the marker-driven gradient modification.
a mom-based home automation platform. while there have been many home networking technologies such as upnp and insteon, appliances supporting different home networking technologies cannot collaborate to finish home automation (ha). although many studies of interoperability among home networking technologies have been done, researches on further ha in heterogeneous environments are still lacking. this paper proposes the mom-based home automation platform (mhap), which accomplishes event-driven ha in incompatible home networks.mhapis independent of any home networking technology and integrates home networking technologies in the home gateway. for users, mhap provides the easy-to-use and standardized way to configure complex ha scenarios by rules. through introducing message oriented middleware (mom) and open service gateway initiative (osgi), mhap offers reliable automatic operations, fault tolerant and re-configurable ha, high extensibility and large scalable collaboration among appliances, other mhap gateways and internet services.
applying stated preference methods to investigate effects of traffic information on route choice. this research is exploring the extent to which providing traffic information on vms affects driversroute choice behaviour. the information include extra delay and charges. three different charging regimes were tested. stated preference(sp) surveys were conducted and route choice logit models were estimated. the results show that drivers' route choice is affected by length of delay and by road user charges on vms. the fixed charges may be most likely to induce drivers to change their behaviour. drivers value delay time more highly and they become increasingly sensitive to delay time as it increases.
analysis of the characteristics of rain attenuation in the 12.25ghz band for wireless networking. quantitative analysis and prediction of radio attenuation is required in order to improve reliability of satellite-earth communication links and for economically efficient design. for this reason, many countries have made efforts to develop their own rain attenuation prediction models which are fit for their rain environment. in this study the slant path length adjustment factor and rain height proposed in korea and japan was applied to itu-r model (p.618-5, p.618-8), which is most widely used in the world. their results were compared to measured data of rain attenuation and their effectiveness and validity were examined through evaluating the pearson correlation coefficient.
a novel buffer cache scheme using java card object with high locality for efficient java card applications. java card technology enables smart cards and other devices with very limited memory to run small applications. it provides users with a secure and interoperable execution platform that can store and update multiple applications on a single device. however, a major difficulty with java card is its low execution speed caused by hardware limitations. in this paper, we propose a novel scheme about how to improve the execution speed of java card. the key idea of our approach is a buffer cache scheme that uses ram instead of eeprom to improve the execution speed of java card. the proposed scheme reduces i/o count, especially eeprom writing. our scheme is based on the high locality of java card objects and the use of ram that is several magnitude faster than eeprom.
data generalization algorithm for the extraction of road horizontal alignment design elements using the gps/ins data. this paper provides the methodologies to extract the road horizontal alignment design elements using the acquisition data from the global positioning system (gps) and inertial navigation system (ins). for this study, highly accurate gps/ins data from the rossav (road safety survey and analysis vehicle) were collected, and also extraction algorithm of road horizontal alignment design elements was proposed according to the statistical inference.
mobile pharmacology. in mobile usage scenarios, patient care involving point of care considerations build upon increasingly complex information and information structures. furthermore, communication of information must be enabled regardless of space and time. decision support and guidelines are expected to communicate with other subsystems, such as those provided by information sources and hardware devices. as also these subsystems may build upon intelligence and involve their own usage scenarios, this implies further complications also the knowledge representation and software engineering tasks. in these developments, public health problems provide case studies with potentially rather huge impacts. examples are provided e.g. by guidelines involving pharmacological treatment. knowledge and reasoning need to interact with information management, and often involves utility of various devices. well organized databases for pharmacological information are necessary for successful engineering of mobile extensions in these case studies. the public is now also one of the driving forces in these developments. as electronic prescriptions and generic substitutes are appreciated by the public, we experience how knowledge in its various forms provide success stories in this field.
mmorpg map evaluation using pedestrian agents. massive multiplayer online role-playing games (mmorpg) increasingly become places of social engagement, by providing spaces for social interaction and relationship beyond home and workplace. the center of this is the virtual environment, in which players interact. today's savvy players are demanding progressive, more playable and navigable game environments. traditional methods of the game map evaluation, though reliable, do not offer a quantitative measure of players discomfort and efficiency. this paper introduces a complementary method of the mmorpg map evaluation by utilizing pedestrian agents. the agents employ calculable measures of walking efficiency and discomfort, providing objective criteria, against which the game maps are evaluated. thus, they promote social interaction by improving the space wherein the players interact.
design of wlan secure system against weaknesses of the ieee 802.1x. the ieee 802.1x framework, what was known to have adjusted the ieee 802.11b's weakness in client authentication is a port-based control mechanism that introduces the logical port idea and performs authentication through the ap or the bridge system. unfortunately, there are two problems in existing access authentication scheme for wireless lan, the ieee 802.1x. one of the problems is that it is possible for a malicious user to disguise as a right authenticator because he/she does not take into account the authentication of authenticators. the other problem is that a malicious user can force an authentication server to waste computational resource by continuously accessing requests. in this paper, we propose a wireless lan secure system that offers secure encrypted communication and user authentications. the purpose of the wlan secure system that this study suggests is to improve the weakness in security of ieee 802.1x and to guarantee a secure encrypted communication.
image resize application of novel stochastic methods of function recovery. a novel family of stochastic methods developed for function recovery tasks is presented and its properties are discussed in some detail. a new image resize facility based on these new methods is applied to an image and this compares favorably in quality to the application to this image of an equivalent facility from a popular commercial graphics package.
on scheduling transmissions for hidden terminal problems in dynamic rfid systems. the problem of scheduling transmissions of dynamic radio frequency identification (rfid) systems has been recently studied.one of the common problems, reader collision avoidance has instigated researchers to propose different heuristic algorithms. in this paper, we present a prime based first come higher priority (fchp) transmission scheduling method for reader collision problems that caused by hidden terminal. fchp is a simple mechanism for coordinating simultaneous transmissions among multiple readers. a significant improvement of this approach is that fchp prevents reader collisions by giving contention free scheduling. the second advantage of the proposed technique is that fchp is adaptive in both static and dynamic rfid environments. the simulation results show that the proposed technique provides superior performance in both static and dynamic instances. the fchp is shown to be effective in terms of system throughput, system efficiency and easy to implement.
particle swarm optimization for a multi-ucav cooperative task scheduling. task scheduling is one of the core steps to effectively exploit the capabilities of cooperative control of multiple uninhabited combat aerial vehicles(ucavs) team. the main function of multi-ucav cooperative task scheduling is to allocate tasks which should be implemented by vehicles, and arrange the sequence of these tasks to be carried out for each vehicle simultaneously, while optimizing the team objective and satisfying various constrains of vehicles and tasks. by analyzing the characters of tasks and ucavs, we presented a general mathematical model based on a combinatorial optimization. by defining a suitable particle structure, the particle swarm optimization (pso) algorithm was applied to solve this problem. adaptive weight values and stochastic turbulence strategies were added to the algorithm. simulation results indicate that the pso algorithm proposed in this paper is a feasible and efficient approach for task scheduling in multi-ucav cooperative control.
expert system using fuzzy petri nets in computer forensics. in the past, computer forensics was only used by means of investigation. however, nowadays, due to the sharp increase of awareness of computer security, computer forensics becomes very significant even to the nonprofessionals, and it needs inference as well as the integrity and reliability of the procedure. in this paper, we describe the inference rules using fuzzy petri nets and adapt the collected data in a compromised system to a proposition for inference of the intrusion information. the inferred results are expressed as formalized 5w1h format. the comfex(computer forensic expert system) is inferable, even if the data is damaged in certain section, and the inference function of uncertainty is improved. this is useful to a system administrator who has weak analyzing ability of hacking, and it has improved capacity of managing the system security.
integration of artificial market simulation and text mining for market analysis. it is important to understand and to provide a rationale for the actions of users in financial markets. simulations of artificial financial markets are one means by which to address these needs, and this paper describes how to integrate the technique of text mining with a simulation of an artificial financial market to enhance the value and usefulness of the simulation. the procedure that is proposed consists of extracting the economic trends from the text data that is circulating in the real world and to input these economic trends into the market simulation. we show how this was experimentally tested as a decision support system for an exchange rate policy and how it suggested that the applied combination of interest rate and intervention operations was effective for stabilization of the yen-dollar rate in 1994 and 1995.
an alternative measure of public transport accessibility based on space syntax. the local governments of major cities in korea are giving focus on public transportation to reduce congestion and improve accessibility in city areas. in this regards, the proper measurement of accessibility is now a key policy requirement for reorganizing the public transport network. however, public transport routing problems are considered to be highly complicated since a multi-mode travel generates different combinations of accessibility. while most of the previous research efforts on measuring transport accessibility are found at zone-levels, an alternative approach at a finer scale such as bus links and stops is presented in this study. we propose a method to compute the optimal route choice of origin-destination pairs and measure the accessibility of the chosen mode combination based on topological configuration. the genetic algorithm is used for the computation of the journey paths, whereas the space syntax theory is used for the accessibility. the resulting accessibilities of bus stops are calibrated by o-d survey data and the proposed process is tested on a cbd of seoul using the city gis network data.
wireless control system for pet dogs in a residential environment. this paper concerns a wireless control system (wcs) for pet dogs using wireless sensor networks (wsns) in a residential environment. the developed wcs is composed of a central control system, a wireless auto-feeder, a small-sized guidance robot, and wireless sensing devices. the developed system uses luminance, temperature, and sound data from a pet dog and the surrounding environment. the presented design method provides an efficient way to control and monitor the pet dog usingwsns. the implemented system can be used as a design framework of portable devices for pet dog control within a residential network.
a study on determining the priorities of its services using analytic hierarchy and network processes. daegu metropolitan city is currently in the process of implementing an intelligent transportation systems (its) basic plan in order to establish these systems and the foundation of basic services, in addition to setting establishment goals based on the national basic plan of its. some criteria have proven to be very effective at determining the priorities of its services, measuring their contribution to solving transportation problems, identifying the services preferred by users, and evaluating its systems and related technologies. in this study, the authors prioritize six its services using the analytic network process (anp), which considers mutual dependence between the evaluation items and alternatives. the analytic hierarchy process (ahp), meanwhile, is a one-way process that does not consider the independence of feedback from the services. according to the results of the super decisions ratings, the regional traffic information center system was chosen to be the top priority project followed by the urban arterial incident management system and the bus information system.
an aware-environment enhanced group home: awarerium. we have constructed "awarerium", an enhanced group home with ubiquitous technology to establish person-centered care. the group home is a facility that provides care for alzheimer's and dementia patients. the group home is effective in curbing the progress of alzheimer's dementia. a small number of elderly persons with no relations in need of care, support, or supervision, such as alzheimer's and dementia patients, can live together in the group home. in this paper, we describe the design concept of awarerium and the sensing and projection devices installed therein. we present two support systems for position awareness using these devices in awarerium: a system for finding lost objects and a system for identifying and noticing dangers in order to prevent dangers in the group home.
adaptive routing algorithm using evolution program for multiple shortest paths in drgs. there are several search algorithms for the shortest path problem: the dijkstra algorithm and bellman-ford algorithm, to name a few. these algorithms are not effective for dynamic traffic network involving rapidly changing travel time. the evolution program is useful for practical purposes to obtain approximate solutions for dynamic route guidance systems (drgs). the objective of this paper is to propose an adaptive routing algorithm using evolution program (araep) that is to find the multiple shortest paths within limited time when the complexity of traffic network including turn-restrictions, u-turns, and p-turns exceeds a predefined threshold.
personalized e-learning process using effective assessment and feedback. the amount and quality of feedback provided to the learner has an impact on the learning process. personalized feedback is particularly important to the effective delivery of e-learning courses. e-learning delivery methods such as web-based instruction are required to overcome the barriers to traditional-type classroom feedback. thereby, the feed-back for a learner should consist not only of adaptive information about his errors and performance, but also of adaptive hints for the improvement of his solution. furthermore, the tutoring component is required to individually motivate the learners. in this paper, an adaptive assessment and feedback process model for personalized e-learning is proposed and developed for the purpose of maximizing the effects of learning.
a solution for bi-level network design problem through nash genetic algorithm. this paper presents a nash genetic algorithm (nash ga) as a solution for a network design problem, formulated as a bi-level programming model and designs a backbone topology in a hierarchical link-state (ls) routing domain. given that the sound backbone topology structure has a great impact on the overall routing performance in a hierarchical ls domain, the importance of this research is evident. the proposed decision model will find an optimal configuration that consists of backbone router for backbone provider (bp), router for internet service provider (isp), and connection link properly meeting two-pronged engineering goals: i.e., average message delay and connection costs. it is also presumed that there are decision makers for bp and the decision makers for isp join in the decision making process in order to optimize the own objective function. the experiment results clearly indicates that it is essential to the effective operations of hierarchical ls routing domain to consider not only the engineering aspects but also specific benefits from systematical layout of backbone network, which presents the validity of the decision model and nash ga.
an introduction of indicator variables and their application to the characteristics of congested traffic flow at the merge area. research on the merge area has mainly dealt with free flow traffic and research on the congested traffic at the merge area is rare. this study investigates the relationship between mainline traffic and on-ramp traffic at three different segments of the merge area. for this purpose, new indicators based on traffic variables such as flow, speed, and density are used. the results show that a negative relationship exists between mainline and on-ramp flow. it is also found that the speed and the density of the right two lanes in the mainline traffic are significantly affected by the on-ramp flow. based on the correlation analysis of the indicators, it is confirmed that the right two lanes of the freeway mainline are influenced by the ramp flow. the revealed relationships between mainline and on-ramp traffic may help to analyze the capacity of the downstream freeway segment of the merge area in congested traffic.
header compression of rtp/udp/ip packets for real time high-speed ip networks. in this paper, a new header compression scheme considering bcb (basic compression bits) or ncb (negotiation compression bits). the header compression scheme can be used for reducing the header size by eliminated repeated fields in the packet header. here, the efficiency of the compression of the dynamic field in rtp/udp/ip packets is very important in real-time high-speed ip networks. our new compression method with sn and ts fields can be applicable to iphc (internet protocol header compression), rohc (robust header compression protocol), and other header compression schemes. the performance of the proposed scheme is discussed via simulation results.
an error sharing agent for multimedia collaboration environment running on pervasive networks. this paper presents the design of an error sharing agent for multimedia collaboration environment which is running on rcsm. rcsm means reconfigurable context-sensitive middleware. rcsm provides an object-based framework for supporting context-sensitive applications. it has other services in optional components. a good example of other services in rcsm is a distance education system for multimedia collaboration environment. we propose an adaptive error hooking agent based on a hybrid software architecture carv(centralized abstraction and replicated view). this system can be automatically enforced according to different situations such as wired or wireless network environment.
a context-aware elevator scheduling system for smart apartment buildings. ubiquitous computing technologies are becoming increasingly a part of our daily lives. for example, in the ubiquitous home environments, plenty of context information can be obtained from various home sensors, and this information can be exploited for smart home activities. this paper presents a new elevator scheduling system for smart apartment buildings that exploits the ubiquitous sensor technologies. in the proposed elevator scheduling system, floor sensors are located at each floor of the apartment building and detect the candidate elevator passengers' behavior before they come to the elevator door and push the elevator call button. the detected information is then delivered to the elevator scheduling system through the building network and the elevator scheduling system utilizes this information in the efficient control of the elevator. through extensive simulations with various passengers' traffic conditions, we show that the proposed system performs better than the conventional elevator scheduling system in terms of the passengers' average waiting time, the maximum waiting time, and the energy consumption of the elevator significantly.
how to overcome main obstacles to building a virtual telematics center. this paper describes the limiting factors for building a virtual telematics center which integrates its (intelligent transportation systems) information collected by the system of each of the three government agencies. it also provides some details into how some of the obstacles and barriers can be solved such as data standardization, system mechanisms and regulations. there are very few papers and case studies regarding real problems and solutions for integrating systems of different organizations in general, and telematics, in particular. the processes and outcomes of implementing systems in this study can be useful to develop other its and telematics systems.
efficient fixed codebook search method for acelp speech codecs. there are several sub-optimal search techniques for fast algebraic codebook search of acelp speech codecs. focused search method, depth-first tree search method and pulse replacement methods are used to reduce computational complexity of algebraic codebook search. in previous pulse replacement methods, the computational load is increased as the pulse replacement procedure is repeated. in this paper, we propose a fast algebraic codebook search method based on iteration-free pulse replacement. the proposed method is composed of two stages. at the first stage, an initial codevector is determined by the backward filtered target vector or the pulse-position likelihood-estimate vector. at the second stage, after computing pulse contributions for every track the pulse replacement is performed to maximize the search criterion qk over all combination replacing the pulses of the initial codevector with the most important pulses for every track. the performance of the proposed algebraic codebook search method is measured in terms of the segmental signal to noise ratio (snrseg) and pesq (perceptual evaluation of speech quality) using various speech data. experimental results show that the proposed method is very efficient in computational complexity and speech quality comparing to previous pulse replacement methods.
conventional beamformer using post-filter for speech enhancement. this paper presents a combined handsfree speech enhancement method based on a spatialpost-filter. the scheme uses a linear microphone array to capture a speech signal that has been corrupted by babble noise, car noise, and interference signals. simulation results for real environment show that the proposed structure achieves a maximum interference suppression of 12 db, an improvement of 6 db over the delay and sum beamformer. furthermore, the system is robust in the presence of distortion as opposed to the generalized sidelobe canceller. the subjective evaluation has shown that the combined system of delay and sum with the minimum mean square error estimator using a noncausal signal to noise ratio (snr) estimator obtained 3.8 points on a fivepoint.
improvement of adaptive modulation system with optimal turbo coded v-blast technique. in this paper, we propose and analyze the adaptive modulation system with optimal turbo coded v-blast (vertical-bell-lab layered space-time) technique that adopts the extrinsic information from map (maximum a posteriori) decoder with iterative decoding as a priori probability in two decoding procedures of a v-blast scheme; the ordering and the slicing. also, comparing with the adaptive modulation system using conventional turbo coded v-blast technique that is simply combined a v-blast scheme with a turbo coding scheme, we observe how much throughput performance can be improved. as a result of a simulation, it has been proved that the proposed system achieves a higher throughput performance than the conventional system in the whole snr (signal to noise ratio) range. specifically, the result shows that the maximum throughput improvement is about 350 kbps.
automatic face analysis system based on face recognition and facial physiognomy. an automatic face analysis system is proposed which uses face recognition and facial physiognomy. it first detects human's face, extracts its features, and classifies the shape of facial features. it will analyze the person's facial physiognomy and then automatically make an avatar drawing using the facial features. the face analysis method of the proposed algorithm can recognize face at real-time and analyze facial physiognomy which is composed of inherent physiological characteristics of humans, orientalism, and fortunes with regard to human's life. the proposed algorithm can draw the person's avatar automatically based on face recognition. we conform that the proposed algorithm could contribute to the scientific and quantitative on-line face analysis fields as well as the biometrics.
a study on the medical image transmission service based on ieee 802.15.4a. in this paper, the transmission service for medical image is proposed via ieee 802.15.4a on wpan environment. also, transmission and receiving performance of medical image using th uwb-ir system is evaluated on indoor multi-path fading environment. on the results, the proposed scheme can solve the problem of interference from the medical equipment in same frequency band, and minimize the loss due to the indoor multi-path fading environment. therefore, the transmission with low power usage is possible.
design and implementation of the decompiler for virtual machine code of the c++ compiler in the ubiquitous game platform. the ubiquitous game platform implemented by our team is composed of a c++ compiler, a java translator, and a virtual machine. the evm (embedded virtual machine) is a stack-based solution that supports object-oriented languages such as c++ and java. it uses the sil (standard intermediate language) as an intermediate language, which consists of an operation code set for procedural and object-oriented languages. the existing c++ compilers are used to execute programs after translating them into a target machine code. the downside of this method is its low practicality, along with its platform-dependency. to resolve this matter, we developed a c++ compiler that generates virtual machine codes based on platform-independent stacks that are not target machine codes. this paper presents a decompiler system that converts a c++ compiler generated intermediate language, namely sil, to a representation of a c++ program. this method optimizes the simulation needed for the generation of exacted sil code, and a solution that can verify the sil code generation through a c++ program represented in the decompiler. furthermore, the ease of extracting the meaning of a program, as opposed to assembly-structured sil codes, allows much more convenience in changing the software structure and correcting it to improve performance.
bandwidth extension of a narrowband speech coder for music delivery over ip. in this paper, we propose a bandwidth extension (bwe) algorithm of a narrowband speech coder for music delivery services over ip networks. the proposed bwe algorithm is based on an embedded structure of using a baseline coder followed by an enhancement layer. to minimize the bit-rate increase by the enhancement layer, the proposed algorithm shares spectral envelope and excitation parameters between the baseline coder and the enhancement layer. in this paper, we choose the ilbc as the baseline coder and mel-frequency cepstral coefficients (mfccs) are used to reconstruct higher frequency components at the enhancement layer. by doing this, the bit-rate of the proposed bwe coder is 15.45 kbit/s which is just 0.25 kbit/s higher than the ilbc. we compare the quality of the proposed bwe coder with that of the ilbc, and it is shown from an informal listening test that the proposed bwe coder provides significantly better quality than the ilbc for all four different kinds of music genres such as pop, classical, jazz and rock.
a sophisticated base station centralized simple clustering protocol for sensor networks. in wireless sensor networks, energy efficiency has been a key factor. so far, many energy-efficient routing protocols have been proposed and much attention has been paid to cluster-based routing protocols due to their advantages. however, some cluster-based sensor network routing protocols need location information of the sensor nodes in the network to construct clusters efficiently. owing to the cost, it is not feasible to know the locations of all sensor nodes in the sensor network. in this paper, we propose a sophisticated base station centralized simple clustering protocol (sbcsp). the proposed protocol utilizes the remaining energy of each sensor node, standard deviation of their energy consumed and the number of cluster heads changed depending on the number of sensor nodes alive in the sensor network. throughout the performance experiments, we show that sbcsp has better performance than low-energy adaptive clustering hierarchy (leach).
enterprise application framework for constructing secure rfid application. in the ubiquitous environment, anyone could easilyaccess all shared informations which means it also has many serious drawbacks, such as security problems. therefore the ubiquitous environment should provide a security service. this paper suggests an enterprise application framework(eaf) which includes a security module as well as a business process module for constructing secure rfid application. the security module includes user authentication mechanism, key sharing mechanism, and authorization mechanism. thus, this framework is expected to provide more secure management in the ubiquitous environments such as rfid applications.
reduced rbf centers based multi-user detection in ds-cdma systems. the major goal of this paper is to develop a practically implemental radial basis function neural network based multi-user detector for direct sequence code division in multiple access systems. this work is expected to provide an efficient solution by quickly setting up the proper number of radial basis function centers and their locations required in training. the basic idea in this research is to select all the possible radial basis function centers by using supervised k-means clustering technique, select the only centers which locate near seemingly decision boundary, and reduce them further by grouping some of the centers adjacent to each other. therefore, it reduces the computational burden for finding the proper number of radial basis function centers and their locations in the existing radial basis function based multi-user detector, and ultimately, make its implementation practical.
detecting image based spam email. image based spam email can easily circumvent widely used text based spam email filters. more and more spammers are adapting the technology. being able to detect the nature of email from its image content is urgently needed. we propose to use ocr (optical character recognition) technology to extract the embedded text from the images and then assess the nature of the email by the extracted text using the same text based engine. this approach avoids maintaining an extra image based detection engine and also takes the benefit of the strong and reasonably mature text based engine. the success of this approach relies on the accuracy of the ocr. however, regardless of how good an ocr is, misrecognition is unavoidable. therefore, a markov model which has the ability to tolerate misspells is also proposed. the solution proposed in this paper can be integrated smoothly into existing spam email filters.
reduction based symbolic value partition. theory of rough sets provides good foundations for the attribute reduction processes in data mining. for numeric attributes, it is enriched with appropriately designed discretization methods. however, not much has been done for symbolic attributes with large numbers of values. the paper presents a framework for the symbolic value partition problem, which is more general than the attribute reduction, and more complicated than the discretization problems.we demonstrate that such problem can be converted into a series of the attribute reduction phases. we propose an algorithm searching for a (sub)optimal attribute reduct coupled with attribute value domains partitions. experimental results show that the algorithm can help in computing smaller rule sets with better coverage, comparing to the standard attribute reduction approaches.
the accurate performance evaluation of time hopping uwb systems with pulse based polarity. the bit rate performance of the time hopping impulse radio uwb system with the pulse based polarity is analyzed. it is well known that the pulse polarity helps reduce the spectral spike appearing in the conventional impulse radio system. this paper provides the method for accurately modeling the multiple access interference(mai) in the system with the pulse polarity. the characteristic function is used to consider the mai. we also show the mai can be simplified as gaussian random variable when the number of pulses representing an information symbol or the pulse rate becomes large. it is obtained directly from approximating the characteristic function of the mai in case of the large number of pulses. some results have been shown to prove validity for our method. the results also show with the total processing gain fixed, increasing the pulse rates proves the system performance. but the system without the pulse polarity does not.
plus-tree: a routing protocol for wireless sensor networks. we study tree-based routing protocols for wireless sensor networks. the existing tree-based algorithm has a few shortcomings; (1) it may take a long path since sensor node must transmit packets via either its parent or its children nodes and (2) it is vulnerable to a link failure since the tree has to be reconstructed in case of a single link failure. we propose plus-tree, a routing protocol, which overcomes the shortcomings and improves the performance of the existing protocol. a node in plus-tree may have neighbor links other than tree links that can be used for alternative path. simulation results show that plus-tree performs better than the existing tree-based protocol with respect to hop counts.
a gdb-based real-time tracing tool for remote debugging of soc programs. since embedded systems based on system-on-a-chip(soc) have limited resources, debugging programs in such systems requires a remote debugging system that has enough resources. however, existing jtag based remote debugging system that uses gdb in linux environment does not provide tracing function, so it is hard to monitor the executions of soc program in real time. this paper adds a tracing facility to existing gdb remote debugging system to provide a real time monitoring tool. to demonstrate a real time tracing of synthetic program, intel a xscale pxa series processor based target system is used.
a hybrid intelligent multimedia service framework in next generation home network environment. in next generation home network environment (nghe), multimedia service will be a key concept of advanced intelligent and secure services which are different from the existing ones. in this paper, we propose a hybrid intelligent multimedia service framework (himsf) which is mixed with application technologies like intelligent home infrastructure or multimedia protection management through the ubiquitous sensor network based technology to provide a proper multimedia service suitable for nghe. the proposed framework provides an interoperability among heterogeneous equipments regarding home network appliances like wireless devices, electronic appliances, pc. in addition, it provides adaptive application services.
an analysis of a lymphoma/leukaemia dataset using rough sets and neural networks. in this paper, we describe a rough sets approach to classification and attribute extraction of a lymphoma cancer dataset. we verify the classification accuracy of the results obtained from rough sets with a two artificial neural network based classifiers (anns). our primary goal was to produce a classifier and a set of rules that could be used in a predictive manner. the dataset consisted of a number of relevant clinical variables obtained from patients that were suspected of having some form of blood based cancer (lymphoma or leukaemia). of the 18 attributes that were collected for this patient cohort, seven were useful with respect to outcome prediction. in addition, this study was able to predict with a high degree of accuracy whether or not the disease would undergo metastases.
the analysis of game playing experiences: focusing on massively multiplayer online role-playing game. the purpose of this study is to (1) develop an analytic framework to systematically code the players' cognitive process during massively multiplayer online role-playing game (mmorpg) gameplay, and (2) to empirically explore the players' cognitive process. to construct the analytical framework of mmorpg gameplay, previous studies regarding gameplay and problem solving theory are reviewed. the specific gameplay actions and contents are derived by using a concurrent protocol analysis method. consequently, gameplay actions are categorized into kinematics, perception, function, representation, methodology, and simulation. a new framework suitable for mmorpg gameplay is built. in order to study the players' cognitive process, the empirical experiment is executed during mmorpg gameplay. as a result of this study, we find a new problem space in the methodological scheme of gameplay. this study concludes with a number of key implications for game design in order to improve the quality of future gaming products.
information retrieval oriented word segmentation based on character association strength ranking. this paper presents a novel, ranking-style word segmentation approach, called rsvm-seg, which is well tailored to chinese information retrieval(cir). this strategy makes segmentation decision based on the ranking of the internal associative strength between each pair of adjacent characters of the sentence. on the training corpus composed of query items, a ranking model is learned by a widely-used tool ranking svm, with some useful statistical features, such as mutual information, difference of t-test, frequency and dictionary information. experimental results show that, this method is able to eliminate overlapping ambiguity much more effectively, compared to the current word segmentation methods. furthermore, as this strategy naturally generates segmentation results with different granularity, the performance of cir systems is improved and achieves the state of the art.
a casual conversation system using modality and word associations retrieved from the web. in this paper we present a textual dialogue system that uses word associations retrieved from the web to create propositions. we also show experiment results for the role of modality generation. the proposed system automatically extracts sets of words related to a conversation topic set freely by a user. after the extraction process, it generates an utterance, adds a modality and verifies the semantic reliability of the proposed sentence. we evaluate word associations extracted form the web, and the results of adding modality. over 80% of the extracted word associations were evaluated as correct. adding modality improved the system significantly for all evaluation criteria. we also show how our system can be used as a simple and expandable platform for almost any kind of experiment with human-computer textual conversation in japanese. two examples with affect analysis and humor generation are given.
automatic prediction of parser accuracy. statistical parsers have become increasingly accurate, to the point where they are useful in many natural language applications. however, estimating parsing accuracy on a wide variety of domains and genres is still a challenge in the absence of gold-standard parse trees. in this paper, we propose a technique that automatically takes into account certain characteristics of the domains of interest, and accurately predicts parser performance on data from these new domains. as a result, we have a cheap (no annotation involved) and effective recipe for measuring the performance of a statistical parser on any given domain.
lattice minimum bayes-risk decoding for statistical machine translation. we present minimum bayes-risk (mbr) decoding over translation lattices that compactly encode a huge number of translation hypotheses. we describe conditions on the loss function that will enable efficient implementation of mbr decoders on lattices. we introduce an approximation to the bleu score (papineni et al., 2001) that satisfies these conditions. the mbr decoding under this approximate bleu is realized using weighted finite state automata. our experiments show that the lattice mbr decoder yields moderate, consistent gains in translation performance over n-best mbr decoding on arabic-to-english, chinese-to-english and english-to-chinese translation tasks. we conduct a range of experiments to understand why lattice mbr improves upon n-best mbr and study the impact of various parameters on mbr performance.
scaling textual inference to the web. most web-based q/a systems work by finding pages that contain an explicit answer to a question. these systems are helpless if the answer has to be inferred from multiple sentences, possibly on different pages. to solve this problem, we introduce the holmes system, which utilizes textual inference (ti) over tuples extracted from text. whereas previous work on ti (e.g., the literature on textual entailment) has been applied to paragraph-sized texts, holmes utilizes knowledge-based model construction to scale ti to a corpus of 117 million web pages. given only a few minutes, holmes doubles recall for example queries in three disparate domains (geography, business, and nutrition). importantly, holmes's runtime is linear in the size of its input corpus due to a surprising property of many textual relations in the web corpus---they are "approximately" functional in a well-defined sense.
online acquisition of japanese unknown morphemes using morphological constraints. we propose a novel lexicon acquirer that works in concert with the morphological analyzer and has the ability to run in online mode. every time a sentence is analyzed, it detects unknown morphemes, enumerates candidates and selects the best candidates by comparing multiple examples kept in the storage. when a morpheme is unambiguously selected, the lexicon acquirer updates the dictionary of the analyzer, and it will be used in subsequent analysis. we use the constraints of japanese morphology and effectively reduce the number of examples required to acquire a morpheme. experiments show that unknown morphemes were acquired with high accuracy and improved the quality of morphological analysis.
hotspots: visualizing edits to a text. compared to the telephone, email based customer care is increasingly becoming the preferred channel of communication for corporations and customers. most email-based customer care management systems provide a method to include template texts in order to reduce the handling time for a customer's email. the text in a template is suitably modified into a response by a customer care agent. in this paper, we present two techniques to improve the effectiveness of a template by providing tools for the template authors. first, we present a tool to track and visualize the edits made by agents to a template which serves as a vital feedback to the template authors. second, we present a novel method that automatically extracts potential templates from responses authored by agents. these methods are investigated in the context of an email customer care analysis tool that handles over a million emails a year.
learning with compositional semantics as structural inference for subsentential sentiment analysis. determining the polarity of a sentiment-bearing expression requires more than a simple bag-of-words approach. in particular, words or constituents within the expression can interact with each other to yield a particular overall polarity. in this paper, we view such subsentential interactions in light of compositional semantics, and present a novel learning-based approach that incorporates structural inference motivated by compositional semantics into the learning procedure. our experiments show that (1) simple heuristics based on compositional semantics can perform better than learning-based methods that do not incorporate compositional semantics (accuracy of 89.7% vs. 89.1%), but (2) a method that integrates compositional semantics into learning performs better than all other alternatives (90.7%). we also find that "content-word negators", not widely employed in previous work, play an important role in determining expression-level polarity. finally, in contrast to conventional wisdom, we find that expression-level classification accuracy uniformly decreases as additional, potentially disambiguating, context is considered.
part-of-speech tagging for english-spanish code-switched text. code-switching is an interesting linguistic phenomenon commonly observed in highly bilingual communities. it consists of mixing languages in the same conversational event. this paper presents results on part-of-speech tagging spanish-english code-switched discourse. we explore different approaches to exploit existing resources for both languages that range from simple heuristics, to language identification, to machine learning. the best results are achieved by training a machine learning algorithm with features that combine the output of an english and a spanish part-of-speech tagger.
sampling alignment structure under a bayesian translation model. we describe the first tractable gibbs sampling procedure for estimating phrase pair frequencies under a probabilistic model of phrase alignment. we propose and evaluate two nonparametric priors that successfully avoid the degenerate behavior noted in previous work, where overly large phrases memorize the training data. phrase table weights learned under our model yield an increase in bleu score over the word-alignment based heuristic estimates used regularly in phrase-based translation systems.
sparse multi-scale grammars for discriminative latent variable parsing. we present a discriminative, latent variable approach to syntactic parsing in which rules exist at multiple scales of refinement. the model is formally a latent variable crf grammar over trees, learned by iteratively splitting grammar productions (not categories). different regions of the grammar are refined to different degrees, yielding grammars which are three orders of magnitude smaller than the single-scale baseline and 20 times smaller than the split-and-merge grammars of petrov et al. (2006). in addition, our discriminative approach integrally admits features beyond local tree configurations. we present a multiscale training method along with an efficient cky-style dynamic program. on a variety of domains and languages, this method produces the best published parsing accuracies with the smallest reported grammars.
revisiting readability: a unified framework for predicting text quality. we combine lexical, syntactic, and discourse features to produce a highly predictive model of human readers' judgments of text readability. this is the first study to take into account such a variety of linguistic factors and the first to empirically demonstrate that discourse relations are strongly associated with the perceived quality of text. we show that various surface metrics generally expected to be related to readability are not very good predictors of readability judgments in our wall street journal corpus. we also establish that readability predictors behave differently depending on the task: predicting text readability or ranking the readability. our experiments indicate that discourse relations are the one class of features that exhibits robustness across these two tasks.
cross-task knowledge-constrained self training. we present an algorithmic framework for learning multiple related tasks. our framework exploits a form of prior knowledge that relates the output spaces of these tasks. we present pac learning results that analyze the conditions under which such learning is possible. we present results on learning a shallow parser and named-entity recognition system that exploits our framework, showing consistent improvements over baseline methods.
who is who and what is what: experiments in cross-document co-reference. this paper describes a language-independent, scalable system for both challenges of cross-document co-reference: name variation and entity disambiguation. we provide system results from the ace 2008 evaluation in both english and arabic. our english system's accuracy is 8.4% relative better than an exact match baseline (and 14.2% relative better over entities mentioned in more than one document). unlike previous evaluations, ace 2008 evaluated both name variation and entity disambiguation over naturally occurring named mentions. an information extraction engine finds document entities in text. we describe how our architecture designed for the 10k document ace task is scalable to an even larger corpus. our cross-document approach uses the names of entities to find an initial set of document entities that could refer to the same real world entity and then uses an agglomerative clustering algorithm to disambiguate the potentially co-referent document entities. we analyze how different aspects of our system affect performance using ablation studies over the english evaluation set. in addition to evaluating cross-document co-reference performance, we used the results of the cross-document system to improve the accuracy of within-document extraction, and measured the impact in the ace 2008 within-document evaluation.
learning the scope of negation in biomedical texts. in this paper we present a machine learning system that finds the scope of negation in biomedical texts. the system consists of two memory-based engines, one that decides if the tokens in a sentence are negation signals, and another that finds the full scope of these negation signals. our approach to negation detection differs in two main aspects from existing research on negation. first, we focus on finding the scope of negation signals, instead of determining whether a term is negated or not. second, we apply supervised machine learning techniques, whereas most existing systems apply rule-based algorithms. as far as we know, this way of approaching the negation scope finding task is novel.
the linguistic structure of english web-search queries. web-search queries are known to be short, but little else is known about their structure. in this paper we investigate the applicability of part-of-speech tagging to typical english-language web search-engine queries and the potential value of these tags for improving search results. we begin by identifying a set of part-of-speech tags suitable for search queries and quantifying their occurrence. we find that proper-nouns constitute 40% of query terms, and proper nouns and nouns together constitute over 70% of query terms. we also show that the majority of queries are noun-phrases, not unstructured collections of terms. we then use a set of queries manually labeled with these tags to train a brill tagger and evaluate its performance. in addition, we investigate classification of search queries into grammatical classes based on the syntax of part-of-speech tag sequences. we also conduct preliminary investigative experiments into the practical applicability of leveraging query-trained part-of-speech taggers for information-retrieval tasks. in particular, we show that part-of-speech information can be a significant feature in machine-learned search-result relevance. these experiments also include the potential use of the tagger in selecting words for omission or substitution in query reformulation, actions which can improve recall. we conclude that training a part-of-speech tagger on labeled corpora of queries significantly outperforms taggers based on traditional corpora, and leveraging the unique linguistic structure of web-search queries can improve search experience.
a structured vector space model for word meaning in context. we address the task of computing vector space representations for the meaning of word occurrences, which can vary widely according to context. this task is a crucial step towards a robust, vector-based compositional account of sentence meaning. we argue that existing models for this task do not take syntactic structure sufficiently into account. we present a novel structured vector space model that addresses these issues by incorporating the selectional preferences for words' argument positions. this makes it possible to integrate syntax into the computation of word meaning in context. in addition, the model performs at and above the state of the art for modeling the contextual adequacy of paraphrases.
a japanese predicate argument structure analysis using decision lists. this paper describes a new automatic method for japanese predicate argument structure analysis. the method learns relevant features to assign case roles to the argument of the target predicate using the features of the words located closest to the target predicate under various constraints such as dependency types, words, semantic categories, parts of speech, functional words and predicate voices. we constructed decision lists in which these features were sorted by their learned weights. using our method, we integrated the tasks of semantic role labeling and zero-pronoun identification, and achieved a 17% improvement compared with a baseline method in a sentence level performance analysis.
jointly combining implicit constraints improves temporal ordering. previous work on ordering events in text has typically focused on local pairwise decisions, ignoring globally inconsistent labels. however, temporal ordering is the type of domain in which global constraints should be relatively easy to represent and reason over. this paper presents a framework that informs local decisions with two types of implicit global constraints: transitivity (a before b and b before c implies a before c) and time expression normalization (e.g. last month is before yesterday). we show how these constraints can be used to create a more densely-connected network of events, and how global consistency can be enforced by incorporating these constraints into an integer linear programming framework. we present results on two event ordering tasks, showing a 3.6% absolute increase in the accuracy of before/after classification over a pairwise model.
incorporating temporal and semantic information with eye gaze for automatic word acquisition in multimodal conversational systems. one major bottleneck in conversational systems is their incapability in interpreting unexpected user language inputs such as out-of-vocabulary words. to overcome this problem, conversational systems must be able to learn new words automatically during human machine conversation. motivated by psycholinguistic findings on eye gaze and human language processing, we are developing techniques to incorporate human eye gaze for automatic word acquisition in multimodal conversational systems. this paper investigates the use of temporal alignment between speech and eye gaze and the use of domain knowledge in word acquisition. our experiment results indicate that eye gaze provides a potential channel for automatically acquiring new words. the use of extra temporal and domain knowledge can significantly improve acquisition performance.
sentence fusion via dependency graph compression. we present a novel unsupervised sentence fusion method which we apply to a corpus of biographies in german. given a group of related sentences, we align their dependency trees and build a dependency graph. using integer linear programming we compress this graph to a new tree, which we then linearize. we use germanet and wikipedia for checking semantic compatibility of co-arguments. in an evaluation with human judges our method outperforms the fusion approach of barzilay & mckeown (2005) with respect to readability.
weakly-supervised acquisition of labeled class instances using graph random walks. we present a graph-based semi-supervised label propagation algorithm for acquiring open-domain labeled classes and their instances from a combination of unstructured and structured text sources. this acquisition method significantly improves coverage compared to a previous set of labeled classes and instances derived from free text, while achieving comparable precision.
forest-based translation rule extraction. translation rule extraction is a fundamental problem in machine translation, especially for linguistically syntax-based systems that need parse trees from either or both sides of the bi-text. the current dominant practice only uses 1-best trees, which adversely affects the rule set quality due to parsing errors. so we propose a novel approach which extracts rules from a packed forest that compactly encodes exponentially many parses. experiments show that this method improves translation quality by over 1 bleu point on a state-of-the-art tree-to-string system, and is 0.5 points better than (and twice as fast as) extracting on 30-best parses. when combined with our previous work on forest-based decoding, it achieves a 2.5 bleu points improvement over the base-line, and even outperforms the hierarchical system of hiero by 0.7 points.
attacking decipherment problems optimally with low-order n-gram models. we introduce a method for solving substitution ciphers using low-order letter n-gram models. this method enforces global constraints using integer programming, and it guarantees that no decipherment key is overlooked. we carry out extensive empirical experiments showing how decipherment accuracy varies as a function of cipher length and n-gram order. we also make an empirical investigation of shannon's (1949) theory of uncertainty in decipherment.
online large-margin training of syntactic and structural translation features. minimum-error-rate training (mert) is a bottleneck for current development in statistical machine translation because it is limited in the number of weights it can reliably optimize. building on the work of watanabe et al., we explore the use of the mira algorithm of crammer et al. as an alternative to mert. we first show that by parallel processing and exploiting more of the parse forest, we can obtain results using mira that match or surpass mert in terms of both translation quality and computational cost. we then test the method on two classes of features that address deficiencies in the hiero hierarchical phrase-based model: first, we simultaneously train a large number of marton and resnik's soft syntactic constraints, and, second, we introduce a novel structural distortion model. in both cases we obtain significant improvements in translation performance. optimizing them in combination, for a total of 56 feature weights, we improve performance by 2.6 bleu on a subset of the nist 2006 arabic-english evaluation data.
integrating multi-level linguistic knowledge with a unified framework for mandarin speech recognition. to improve the mandarin large vocabulary continuous speech recognition (lvcsr), a unified framework based approach is introduced to exploit multi-level linguistic knowledge. in this framework, each knowledge source is represented by a weighted finite state transducer (wfst), and then they are combined to obtain a so-called analyzer for integrating multi-level knowledge sources. due to the uniform transducer representation, any knowledge source can be easily integrated into the analyzer, as long as it can be encoded into wfsts. moreover, as the knowledge in each level is modeled independently and the combination is processed in the model level, the information inherently in each knowledge source has a chance to be thoroughly exploited. by simulations, the effectiveness of the analyzer is investigated, and then a lvcsr system embedding the presented analyzer is evaluated. experimental results reveal that this unified framework is an effective approach which significantly improves the performance of speech recognition with a 9.9% relative reduction of character error rate on the hub-4 test set, a widely used mandarin speech recognition task.
online methods for multi-domain learning and adaptation. nlp tasks are often domain specific, yet systems can learn behaviors across multiple domains. we develop a new multi-domain online learning framework based on parameter combination from multiple classifiers. our algorithms draw from multi-task learning and domain adaptation to adapt multiple source domain classifiers to a new target domain, learn across multiple similar domains, and learn across a large number of disparate domains. we evaluate our algorithms on two popular nlp domain adaptation tasks: sentiment classification and spam filtering.
a graph-theoretic model of lexical syntactic acquisition. this paper presents a graph-theoretic model of the acquisition of lexical syntactic representations. the representations the model learns are non-categorical or graded. we propose a new evaluation methodology of syntactic acquisition in the framework of exemplar theory. when applied to the childes corpus, the evaluation shows that the model's graded syntactic representations perform better than previously proposed categorical representations.
generalizing local and non-local word-reordering patterns for syntax-based machine translation. syntactic word reordering is essential for translations across different grammar structures between syntactically distant language-pairs. in this paper, we propose to embed local and non-local word reordering decisions in a synchronous context free grammar, and leverages the grammar in a chart-based decoder. local word-reordering is effectively encoded in hiero-like rules; whereas non-local word-reordering, which allows for long-range movements of syntactic chunks, is represented in tree-based reordering rules, which contain variables correspond to source-side syntactic constituents. we demonstrate how these rules are learned from parallel corpora. our proposed shallow tree-to-string rules show significant improvements in translation quality across different test sets.
automatic set expansion for list question answering. this paper explores the use of set expansion (se) to improve question answering (qa) when the expected answer is a list of entities belonging to a certain class. given a small set of seeds, se algorithms mine textual resources to produce an extended list including additional members of the class represented by the seeds. we explore the hypothesis that a noise-resistant se algorithm can be used to extend candidate answers produced by a qa system and generate a new list of answers that is better than the original list produced by the qa system. we further introduce a hybrid approach which combines the original answers from the qa system with the output from the se algorithm. experimental results for several state-of-the-art qa systems show that the hybrid system performs better than the qa systems alone when tested on list question data from past trec evaluations.
latent-variable modeling of string transductions with finite-state methods. string-to-string transduction is a central problem in computational linguistics and natural language processing. it occurs in tasks as diverse as name transliteration, spelling correction, pronunciation modeling and inflectional morphology. we present a conditional loglinear model for string-to-string transduction, which employs overlapping features over latent alignment sequences, and which learns latent classes and latent string pair regions from incomplete training data. we evaluate our approach on morphological tasks and demonstrate that latent variables can dramatically improve results, even when trained on small data sets. on the task of generating morphological forms, we outperform a baseline method reducing the error rate by up to 48%. on a lemmatization task, we reduce the error rates in wicentowski (2002) by 38--92%.
automatic induction of framenet lexical units. most attempts to integrate framenet in nlp systems have so far failed because of its limited coverage. in this paper, we investigate the applicability of distributional and wordnet-based models on the task of lexical unit induction, i.e. the expansion of framenet with new lexical units. experimental results show that our distributional and wordnet-based models achieve good level of accuracy and coverage, especially when combined.
unsupervised models for coreference resolution. we present a generative model for unsupervised coreference resolution that views coreference as an em clustering process. for comparison purposes, we revisit haghighi and klein's (2007) fully-generative bayesian model for unsupervised coreference resolution, discuss its potential weaknesses and consequently propose three modifications to their model. experimental results on the ace data sets show that our model outperforms their original model by a large margin and compares favorably to the modified model.
learning graph walk based similarity measures for parsed text. we consider a parsed text corpus as an instance of a labelled directed graph, where nodes represent words and weighted directed edges represent the syntactic relations between them. we show that graph walks, combined with existing techniques of supervised learning, can be used to derive a task-specific word similarity measure in this graph. we also propose a new path-constrained graph walk method, in which the graph walk process is guided by high-level knowledge about meaningful edge sequences (paths). empirical evaluation on the task of named entity coordinate term extraction shows that this framework is preferable to vector-based models for small-sized corpora. it is also shown that the path-constrained graph walk algorithm yields both performance and scalability gains.
online word games for semantic data collection. obtaining labeled data is a significant obstacle for many nlp tasks. recently, online games have been proposed as a new way of obtaining labeled data; games attract users by being fun to play. in this paper, we consider the application of this idea to collecting semantic relations between words, such as hypernym/hyponym relationships. we built three online games, inspired by the real-life games of scattergories&trade; and taboo&trade;. as of june 2008, players have entered nearly 800,000 data instances, in two categories. the first type of data consists of category/answer pairs ("types of vehicle","car"), while the second is essentially free association data ("submarine","underwater"). we analyze both types of data in detail and discuss potential uses of the data. we show that we can extract from our data set a significant number of new hypernym/hyponym pairs not already found in wordnet.
word sense disambiguation using ontonotes: an empirical study. the accuracy of current word sense disambiguation (wsd) systems is affected by the fine-grained sense inventory of wordnet as well as a lack of training examples. using the wsd examples provided through ontonotes, we conduct the first large-scale wsd evaluation involving hundreds of word types and tens of thousands of sense-tagged examples, while adopting a coarse-grained sense inventory. we show that though wsd systems trained with a large number of examples can obtain a high level of accuracy, they nevertheless suffer a substantial drop in accuracy when applied to a different domain. to address this issue, we propose combining a domain adaptation technique using feature augmentation with active learning. our results show that this approach is effective in reducing the annotation effort required to adapt a wsd system to a new domain. finally, we propose that one can maximize the dual benefits of reducing the annotation effort while ensuring an increase in wsd accuracy, by only performing active learning on the set of most frequently occurring word types.
modeling annotators: a generative approach to learning from annotator rationales. a human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (zaidan et al., 2007). how can one exploit this side information to better learn the desired parameters &theta;? we present a generative model of how a given annotator, knowing the true &theta;, stochastically chooses rationales. thus, observing the rationales helps us infer the true &theta;. we collect substring rationales for a sentiment classification task (pang and lee, 2004) and use them to obtain significant accuracy improvements for each annotator. our new generative approach exploits the rationales more effectively than our previous "masking svm" approach. it is also more principled, and could be adapted to help learn other kinds of probabilistic classifiers for quite different tasks.
mining and modeling relations between formal and informal chinese phrases from web corpora. we present a novel method for discovering and modeling the relationship between informal chinese expressions (including colloquialisms and instant-messaging slang) and their formal equivalents. specifically, we proposed a bootstrapping procedure to identify a list of candidate informal phrases in web corpora. given an informal phrase, we retrieve contextual instances from the web using a search engine, generate hypotheses of formal equivalents via this data, and rank the hypotheses using a conditional log-linear model. in the log-linear model, we incorporate as feature functions both rule-based intuitions and data co-occurrence phenomena (either as an explicit or indirect definition, or through formal/informal usages occurring in free variation in a discourse). we test our system on manually collected test examples, and find that the (formal-informal) relationship discovery and extraction process using our method achieves an average 1-best precision of 62%. given the ubiquity of informal conversational style on the internet, this work has clear applications for text normalization in text-processing systems including machine translation aspiring to broad coverage.
discriminative learning of selectional preference from unlabeled text. we present a discriminative method for learning selectional preferences from unlabeled text. positive examples are taken from observed predicate-argument pairs, while negatives are constructed from unobserved combinations. we train a support vector machine classifier to distinguish the positive from the negative instances. we show how to partition the examples for efficient training with 57 thousand features and 6.5 million training instances. the model outperforms other recent approaches, achieving excellent correlation with human plausibility judgments. compared to mutual information, it identifies 66% more verb-object pairs in unseen text, and resolves 37% more pronouns correctly in a pronoun resolution experiment.
predicting success in machine translation. the performance of machine translation systems varies greatly depending on the source and target languages involved. determining the contribution of different characteristics of language pairs on system performance is key to knowing what aspects of machine translation to improve and which are irrelevant. this paper investigates the effect of different explanatory variables on the performance of a phrase-based system for 110 european language pairs. we show that three factors are strong predictors of performance in isolation: the amount of reordering, the morphological complexity of the target language and the historical relatedness of the two languages. together, these factors contribute 75% to the variability of the performance of the system.
syntactic constraints on paraphrases extracted from parallel corpora. we improve the quality of paraphrases extracted from parallel corpora by requiring that phrases and their paraphrases be the same syntactic type. this is achieved by parsing the english side of a parallel corpus and altering the phrase extraction algorithm to extract phrase labels alongside bilingual phrase pairs. in order to retain broad coverage of non-constituent phrases, complex syntactic labels are introduced. a manual evaluation indicates a 19% absolute improvement in paraphrase quality over the baseline method.
a comparison of bayesian estimators for unsupervised hidden markov model pos taggers. there is growing interest in applying bayesian techniques to nlp problems. there are a number of different estimators for bayesian models, and it is useful to know what kinds of tasks each does well on. this paper compares a variety of different bayesian estimators for hidden markov model pos taggers with various numbers of hidden states on data sets of different sizes. recent papers have given contradictory results when comparing bayesian estimators to expectation maximization (em) for unsupervised hmm pos tagging, and we show that the difference in reported results is largely due to differences in the size of the training data and the number of states in the hmm. we invesigate a variety of samplers for hmms, including some that these earlier papers did not study. we find that all of gibbs samplers do well with small data sets and few states, and that variational bayes does well on large data sets and is competitive with the gibbs samplers. in terms of times of convergence, we find that variational bayes was the fastest of all the estimators, especially on large data sets, and that explicit gibbs sampler (both pointwise and sentence-blocked) were generally faster than their collapsed counterparts on large data sets.
adding redundant features for crfs-based sentence sentiment classification. in this paper, we present a novel method based on crf's in response to the two special characteristics of "contextual dependency" and "label redundancy" in sentence sentiment classification. we try to capture the contextual constraints on sentence sentiment using crfs. through introducing redundant labels into the original sentimental label set and organizing all labels into a hierarchy, our method can add redundant features into training for capturing the label redundancy. the experimental results prove that our method outperforms the traditional methods like nb, svm, maxent and standard chain crfs. in comparison with the cascaded model, our method can effectively alleviate the error propagation among different layers and obtain better performance in each layer.
lattice-based minimum error rate training for statistical machine translation. minimum error rate training (mert) is an effective means to estimate the feature function weights of a linear model such that an automated evaluation criterion for measuring system performance can directly be optimized in training. to accomplish this, the training procedure determines for each feature function its exact error surface on a given set of candidate translations. the feature function weights are then adjusted by traversing the error surface combined over all sentences and picking those values for which the resulting error count reaches a minimum. typically, candidates in mert are represented as n-best lists which contain the n most probable translation hypotheses produced by a decoder. in this paper, we present a novel algorithm that allows for efficiently constructing and representing the exact error surface of all translations that are encoded in a phrase lattice. compared to n-best mert, the number of candidate translations thus taken into account increases by several orders of magnitudes. the proposed method is used to train the feature function weights of a phrase-based statistical machine translation system. experiments conducted on the nist 2008 translation tasks show significant runtime improvements and moderate bleu score gains over n-best mert.
dependency-based semantic role labeling of propbank. we present a propbank semantic role labeling system for english that is integrated with a dependency parser. to tackle the problem of joint syntactic--semantic analysis, the system relies on a syntactic and a semantic subcomponent. the syntactic model is a projective parser using pseudo-projective transformations, and the semantic model uses global inference mechanisms on top of a pipeline of classifiers. the complete syntactic-semantic output is selected from a candidate pool generated by the subsystems. we evaluate the system on the conll-2005 test sets using segment-based and dependency-based metrics. using the segment-based conll-2005 metric, our system achieves a near state-of-the-art f1 figure of 77.97 on the wsj+brown test set, or 78.84 if punctuation is treated consistently. using a dependency-based metric, the f1 figure of our system is 84.29 on the test set from conll-2008. our system is the first dependency-based semantic role labeler for propbank that rivals constituent-based systems in terms of performance.
one-class clustering in the text domain. having seen a news title "alba denies wedding reports", how do we infer that it is primarily about jessica alba, rather than about weddings or reports? we probably realize that, in a randomly driven sentence, the word "alba" is less anticipated than "wedding" or "reports", which adds value to the word "alba" if used. such anticipation can be modeled as a ratio between an empirical probability of the word (in a given corpus) and its estimated probability in general english. aggregated over all words in a document, this ratio may be used as a measure of the document's topicality. assuming that the corpus consists of on-topic and off-topic documents (we call them the core and the noise), our goal is to determine which documents belong to the core. we propose two unsupervised methods for doing this. first, we assume that words are sampled i.i.d., and propose an information-theoretic framework for determining the core. second, we relax the independence assumption and use a simple graphical model to rank documents according to their likelihood of belonging to the core. we discuss theoretical guarantees of the proposed methods and show their usefulness for web mining and topic detection and tracking (tdt).
graph-based analysis of semantic drift in espresso-like bootstrapping algorithms. bootstrapping has a tendency, called semantic drift, to select instances unrelated to the seed instances as the iteration proceeds. we demonstrate the semantic drift of bootstrapping has the same root as the topic drift of kleinberg's hits, using a simplified graph-based reformulation of bootstrapping. we confirm that two graph-based algorithms, the von neumann kernels and the regularized laplacian, can reduce semantic drift in the task of word sense disambiguation (wsd) on senseval-3 english lexical sample task. proposed algorithms achieve superior performance to espresso and previous graph-based wsd methods, even though the proposed algorithms have less parameters and are easy to calibrate.
joint unsupervised coreference resolution with markov logic. machine learning approaches to coreference resolution are typically supervised, and require expensive labeled data. some unsupervised approaches have been proposed (e.g., haghighi and klein (2007)), but they are less accurate. in this paper, we present the first unsupervised approach that is competitive with supervised ones. this is made possible by performing joint inference across mentions, in contrast to the pairwise classification typically used in supervised methods, and by using markov logic as a representation language, which enables us to easily express relations like apposition and predicate nominals. on muc and ace datasets, our model outperforms haghigi and klein's one using only a fraction of the training data, and often matches or exceeds the accuracy of state-of-the-art supervised models.
when harry met harri: cross-lingual name spelling normalization. foreign name translations typically include multiple spelling variants. these variants cause data sparseness problems, increase out-of-vocabulary (oov) rate, and present challenges for machine translation, information extraction and other nlp tasks. this paper aims to identify name spelling variants in the target language using the source name as an anchor. based on word-to-word translation and transliteration probabilities, as well as the string edit distance metric, target name translations with similar spellings are clustered. with this approach tens of thousands of high precision name translation spelling variants are extracted from sentence-aligned bilingual corpora. when these name spelling variants are applied to machine translation and information extraction tasks, improvements over strong baseline systems are observed in both cases.
regular expression learning for information extraction. regular expressions have served as the dominant workhorse of practical information extraction for several years. however, there has been little work on reducing the manual effort involved in building high-quality, complex regular expressions for information extraction tasks. in this paper, we propose relie, a novel transformation-based algorithm for learning such complex regular expressions. we evaluate the performance of our algorithm on multiple datasets and compare it against the crf algorithm. we show that relie, in addition to being an order of magnitude faster, outperforms crf under conditions of limited training data and cross-domain data. finally, we show how the accuracy of crf can be improved by using features extracted by relie.
soft-supervised learning for text classification. we propose a new graph-based semi-supervised learning (ssl) algorithm and demonstrate its application to document categorization. each document is represented by a vertex within a weighted undirected graph and our proposed framework minimizes the weighted kullback-leibler divergence between distributions that encode the class membership probabilities of each vertex. the proposed objective is convex with guaranteed convergence using an alternating minimization procedure. further, it generalizes in a straightforward manner to multi-class problems. we present results on two standard tasks, namely reuters-21578 and webkb, showing that the proposed algorithm significantly outperforms the state-of-the-art.
dependency parsing by belief propagation. we formulate dependency parsing as a graphical model with the novel ingredient of global constraints. we show how to apply loopy belief propagation (bp), a simple and effective tool for approximate learning and inference. as a parsing algorithm, bp is both asymptotically and empirically efficient. even with second-order features or latent variables, which would make exact parsing considerably slower or np-hard, bp needs only o(n3) time with a small constant factor. furthermore, such features significantly improve parse accuracy over exact first-order methods. incorporating additional features would increase the runtime additively rather than multiplicatively.
arabic named entity recognition using optimized feature sets. the named entity recognition (ner) task has been garnering significant attention in nlp as it helps improve the performance of many natural language processing applications. in this paper, we investigate the impact of using different sets of features in two discriminative machine learning frameworks, namely, support vector machines and conditional random fields using arabic data. we explore lexical, contextual and morphological features on eight standardized data-sets of different genres. we measure the impact of the different features in isolation, rank them according to their impact for each named entity class and incrementally combine them in order to infer the optimal machine learning approach and feature set. our system yields a performance of f&beta;=1-measure=83.5 on ace 2003 broadcast news data.
understanding the value of features for coreference resolution. in recent years there has been substantial work on the important problem of coreference resolution, most of which has concentrated on the development of new models and algorithmic techniques. these works often show that complex models improve over a weak pairwise baseline. however, less attention has been given to the importance of selecting strong features to support learning a coreference model. this paper describes a rather simple pairwise classification model for coreference resolution, developed with a well-designed set of features. we show that this produces a state-of-the-art system that outperforms systems built with complex models. we suggest that our system can be used as a baseline for the development of more complex models -- which may have less impact when a more robust set of features is used. the paper also presents an ablation study and discusses the relative contributions of various features.
mention detection crossing the language barrier. while significant effort has been put into annotating linguistic resources for several languages, there are still many left that have only small amounts of such resources. this paper investigates a method of propagating information (specifically mention detection information) into such low resource languages from richer ones. experiments run on three language pairs (arabic-english, chinese-english, and spanish-english) show that one can achieve relatively decent performance by propagating information from a language with richer resources such as english into a foreign language alone (no resources or models in the foreign language). furthermore, while examining the performance using various degrees of linguistic information in a statistical framework, results show that propagated features from english help improve the source-language system performance even when used in conjunction with all feature types built from the source language. the experiments also show that using propagated features in conjunction with lexically-derived features only (as can be obtained directly from a mention annotated corpus) yields similar performance to using feature types derived from many linguistic resources.
improved sentence alignment on parallel web pages using a stochastic tree alignment model. parallel web pages are important source of training data for statistical machine translation. in this paper, we present a new approach to sentence alignment on parallel web pages. parallel web pages tend to have parallel structures, and the structural correspondence can be indicative information for identifying parallel sentences. in our approach, the web page is represented as a tree, and a stochastic tree alignment model is used to exploit the structural correspondence for sentence alignment. experiments show that this method significantly enhances alignment accuracy and robustness for parallel web pages which are much more diverse and noisy than standard parallel corpora such as "hansard". with improved sentence alignment performance, web mining systems are able to acquire parallel sentences of higher quality from the web.
topic-driven multi-document summarization with encyclopedic knowledge and spreading activation. information of interest to users is often distributed over a set of documents. users can specify their request for information as a query/topic -- a set of one or more sentences or questions. producing a good summary of the relevant information relies on understanding the query and linking it with the associated set of documents. to "understand" the query we expand it using encyclopedic knowledge in wikipedia. the expanded query is linked with its associated documents through spreading activation in a graph that represents words and their grammatical connections in these documents. the topic expanded words and activated nodes in the graph are used to produce an extractive summary. the method proposed is tested on the duc summarization data. the system implemented ranks high compared to the participating systems in the duc competitions, confirming our hypothesis that encyclopedic knowledge is a useful addition to a summarization system.
a discriminative candidate generator for string transformations. string transformation, which maps a source string s into its desirable form t*, is related to various applications including stemming, lemmatization, and spelling correction. the essential and important step for string transformation is to generate candidates to which the given string s is likely to be transformed. this paper presents a discriminative approach for generating candidate strings. we use substring substitution rules as features and score them using an l1-regularized logistic regression model. we also propose a procedure to generate negative instances that affect the decision boundary of the model. the advantage of this approach is that candidate strings can be enumerated by an efficient algorithm because the processes of string transformation are tractable in the model. we demonstrate the remarkable performance of the proposed method in normalizing inflected words and spelling variations.
complexity of finding the bleu-optimal hypothesis in a confusion network. confusion networks are a simple representation of multiple speech recognition or translation hypotheses in a machine translation system. a typical operation on a confusion network is to find the path which minimizes or maximizes a certain evaluation metric. in this article, we show that this problem is generally np-hard for the popular bleu metric, as well as for smaller variants of bleu. this also holds for more complex representations like generic word graphs. in addition, we give an efficient polynomial-time algorithm to calculate unigram bleu on confusion networks, but show that even small generalizations of this data structure render the problem to be np-hard again. since finding the optimal solution is thus not always feasible, we introduce an approximating algorithm based on a multi-stack decoder, which finds a (not necessarily optimal) solution for n-gram bleu in polynomial time.
coarse-to-fine syntactic machine translation using language projections. the intersection of tree transducer-based translation models with n-gram language models results in huge dynamic programs for machine translation decoding. we propose a multipass, coarse-to-fine approach in which the language model complexity is incrementally introduced. in contrast to previous order-based bigram-to-trigram approaches, we focus on encoding-based methods, which use a clustered encoding of the target language. across various encoding schemes, and for multiple language pairs, we show speed-ups of up to 50 times over single-pass decoding while improving bleu score. moreover, our entire decoding cascade for trigram language models is faster than the corresponding bigram pass alone of a bigram-to-trigram decoder.
cocqa: co-training over questions and answers with an application to predicting question subjectivity orientation. an increasingly popular method for finding information online is via the community question answering (cqa) portals such as yahoo! answers, naver, and baidu knows. searching the cqa archives, and ranking, filtering, and evaluating the submitted answers requires intelligent processing of the questions and answers posed by the users. one important task is automatically detecting the question's subjectivity orientation: namely, whether a user is searching for subjective or objective information. unfortunately, real user questions are often vague, ill-posed, poorly stated. furthermore, there has been little labeled training data available for real user questions. to address these problems, we present cocqa, a co-training system that exploits the association between the questions and contributed answers for question analysis tasks. the co-training approach allows cocqa to use the effectively unlimited amounts of unlabeled data readily available in cqa archives. in this paper we study the effectiveness of cocqa for the question subjectivity classification task by experimenting over thousands of real users' questions.
a phrase-based alignment model for natural language inference. the alignment problem---establishing links between corresponding phrases in two related sentences---is as important in natural language inference (nli) as it is in machine translation (mt). but the tools and techniques of mt alignment do not readily transfer to nli, where one cannot assume semantic equivalence, and for which large volumes of bitext are lacking. we present a new nli aligner, the manli system, designed to address these challenges. it uses a phrase-based alignment representation, exploits external lexical resources, and capitalizes on a new set of supervised training data. we compare the performance of manli to existing nli and mt aligners on an nli alignment task over the well-known recognizing textual entailment data. we show that manli significantly outperforms existing aligners, achieving gains of 6.2% in f1 over a representative nli aligner and 10.5% over giza++.
indirect-hmm-based hypothesis alignment for combining outputs from machine translation systems. this paper presents a new hypothesis alignment method for combining outputs of multiple machine translation (mt) systems. an indirect hidden markov model (ihmm) is proposed to address the synonym matching and word ordering issues in hypothesis alignment. unlike traditional hmms whose parameters are trained via maximum likelihood estimation (mle), the parameters of the ihmm are estimated indirectly from a variety of sources including word semantic similarity, word surface similarity, and a distance-based distortion penalty. the ihmm-based method significantly outperforms the state-of-the-art ter-based alignment model in our experiments on nist benchmark datasets. our combined smt system using the proposed method achieved the best chinese-to-english translation result in the constrained training track of the 2008 nist open mt evaluation.
multimodal subjectivity analysis of multiparty conversation. we investigate the combination of several sources of information for the purpose of subjectivity recognition and polarity classification in meetings. we focus on features from two modalities, transcribed words and acoustics, and we compare the performance of three different textual representations: words, characters, and phonemes. our experiments show that character-level features outperform wordlevel features for these tasks, and that a careful fusion of all features yields the best performance.1
cheap and fast - but is it good? evaluating non-expert annotations for natural language tasks. human linguistic annotation is crucial for many natural language processing tasks but can be expensive and time-consuming. we explore the use of amazon's mechanical turk system, a significantly cheaper and faster method for collecting annotations from a broad base of paid non-expert contributors over the web. we investigate five tasks: affect recognition, word similarity, recognizing textual entailment, event temporal ordering, and word sense disambiguation. for all five, we show high agreement between mechanical turk non-expert annotations and existing gold standard labels provided by expert labelers. for the task of affect recognition, we also show that using non-expert labels for training machine learning algorithms can be as effective as using gold standard annotations from experts. we propose a technique for bias correction that significantly improves annotation quality on two tasks. we conclude that many large labeling tasks can be effectively designed and carried out in this method at a fraction of the usual expense.
refining generative language models using discriminative learning. we propose a new approach to language modeling which utilizes discriminative learning methods. our approach is an iterative one: starting with an initial language model, in each iteration we generate 'false' sentences from the current model, and then train a classifier to discriminate between them and sentences from the training corpus. to the extent that this succeeds, the classifier is incorporated into the model by lowering the probability of sentences classified as false, and the process is repeated. we demonstrate the effectiveness of this approach on a natural language corpus and show it provides an 11.4% improvement in perplexity over a modified kneser-ney smoothed trigram.
two languages are better than one (for syntactic parsing). we show that jointly parsing a bitext can substantially improve parse quality on both sides. in a maximum entropy bitext parsing model, we define a distribution over source trees, target trees, and node-to-node alignments between them. features include monolingual parse scores and various measures of syntactic divergence. using the translated portion of the chinese treebank, our model is trained iteratively to maximize the marginal likelihood of training tree pairs, with alignments treated as latent variables. the resulting bitext parser outperforms state-of-the-art monolingual parser baselines by 2.5 f1 at predicting english side trees and 1.8 f1 at predicting chinese side trees (the highest published numbers on these corpora). moreover, these improved trees yield a 2.4 bleu increase when used in a downstream mt evaluation.
n-gram weighting: reducing training data mismatch in cross-domain language model estimation. in domains with insufficient matched training data, language models are often constructed by interpolating component models trained from partially matched corpora. since the n-grams from such corpora may not be of equal relevance to the target domain, we propose an n-gram weighting technique to adjust the component n-gram probabilities based on features derived from readily available segmentation and metadata information for each corpus. using a log-linear combination of such features, the resulting model achieves up to a 1.2% absolute word error rate reduction over a linearly interpolated baseline language model on a lecture transcription task.
maximum entropy based rule selection model for syntax-based statistical machine translation. this paper proposes a novel maximum entropy based rule selection (mers) model for syntax-based statistical machine translation (smt). the mers model combines local contextual information around rules and information of sub-trees covered by variables in rules. therefore, our model allows the decoder to perform context-dependent rule selection during decoding. we incorporate the mers model into a state-of-the-art linguistically syntax-based smt model, the tree-to-string alignment template model. experiments show that our approach achieves significant improvements over the baseline system.
learning to predict code-switching points. predicting possible code-switching points can help develop more accurate methods for automatically processing mixed-language text, such as multilingual language models for speech recognition systems and syntactic analyzers. we present in this paper exploratory results on learning to predict potential code-switching points in spanish-english. we trained different learning algorithms using a transcription of code-switched discourse. to evaluate the performance of the classifiers, we used two different criteria: 1) measuring precision, recall, and f-measure of the predictions against the reference in the transcription, and 2) rating the naturalness of artificially generated code-switched sentences. average scores for the code-switched sentences generated by our machine learning approach were close to the scores of those generated by humans.
construction of an idiom corpus and its application to idiom identification based on wsd incorporating idiom-specific features. some phrases can be interpreted either idiomatically (figuratively) or literally in context, and the precise identification of idioms is indispensable for full-fledged natural language processing (nlp). to this end, we have constructed an idiom corpus for japanese. this paper reports on the corpus and the results of an idiom identification experiment using the corpus. the corpus targets 146 ambiguous idioms, and consists of 102, 846 sentences, each of which is annotated with a literal/idiom label. for idiom identification, we targeted 90 out of the 146 idioms and adopted a word sense disambiguation (wsd) method using both common wsd features and idiom-specific features. the corpus and the experiment are the largest of their kind, as far as we know. as a result, we found that a standard supervised wsd method works well for the idiom identification and achieved an accuracy of 89.25% and 88.86% with/without idiom-specific features and that the most effective idiom-specific feature is the one involving the adjacency of idiom constituents.
better binarization for the cky parsing. we present a study on how grammar binarization empirically affects the efficiency of the cky parsing. we argue that binarizations affect parsing efficiency primarily by affecting the number of incomplete constituents generated, and the effectiveness of binarization also depends on the nature of the input. we propose a novel binarization method utilizing rich information learnt from training corpus. experimental results not only show that different binarizations have great impacts on parsing efficiency, but also confirm that our learnt binarization outperforms other existing methods. furthermore we show that it is feasible to combine existing parsing speed-up techniques with our binarization to achieve even better performance.
scalable language processing algorithms for the masses: a case study in computing word co-occurrence matrices with mapreduce. this paper explores the challenge of scaling up language processing algorithms to increasingly large datasets. while cluster computing has been available in commercial environments for several years, academic researchers have fallen behind in their ability to work on large datasets. i discuss two barriers contributing to this problem: lack of a suitable programming model for managing concurrency and difficulty in obtaining access to hardware. hadoop, an open-source implementation of google's mapreduce framework, provides a compelling solution to both issues. its simple programming model hides system-level details from the developer, and its ability to run on commodity hardware puts cluster computing within the reach of many academic research groups. this paper illustrates these points with a case study in building word cooccurrence matrices from large corpora. i conclude with an analysis of an alternative computing model based on renting instead of buying computer clusters.
improving interactive machine translation via mouse actions. although machine translation (mt) is a very active research field which is receiving an increasing amount of attention from the research community, the results that current mt systems are capable of producing are still quite far away from perfection. because of this, and in order to build systems that yield correct translations, human knowledge must be integrated into the translation process, which will be carried out in our case in an interactive-predictive (ip) framework. in this paper, we show that considering mouse actions as a significant information source for the underlying system improves the productivity of the human translator involved. in addition, we also show that the initial translations that the mt system provides can be quickly improved by an expert by only performing additional mouse actions. in this work, we will be using word graphs as an efficient interface between a phrase-based mt system and the ip engine.
bayesian unsupervised topic segmentation. this paper describes a novel bayesian approach to unsupervised topic segmentation. unsupervised systems for this task are driven by lexical cohesion: the tendency of well-formed segments to induce a compact and consistent lexical distribution. we show that lexical cohesion can be placed in a bayesian context by modeling the words in each topic segment as draws from a multinomial language model associated with the segment; maximizing the observation likelihood in such a model yields a lexically-cohesive segmentation. this contrasts with previous approaches, which relied on hand-crafted cohesion metrics. the bayesian framework provides a principled way to incorporate additional features such as cue phrases, a powerful indicator of discourse structure that has not been previously used in unsupervised segmentation systems. our model yields consistent improvements over an array of state-of-the-art systems on both text and speech datasets. we also show that both an entropy-based analysis and a well-known previous technique can be derived as special cases of the bayesian framework.
phrase translation probabilities with itg priors and smoothing as learning objective. the conditional phrase translation probabilities constitute the principal components of phrase-based machine translation systems. these probabilities are estimated using a heuristic method that does not seem to optimize any reasonable objective function of the word-aligned, parallel training corpus. earlier efforts on devising a better understood estimator either do not scale to reasonably sized training data, or lead to deteriorating performance. in this paper we explore a new approach based on three ingredients (1) a generative model with a prior over latent segmentations derived from inversion transduction grammar (itg), (2) a phrase table containing all phrase pairs without length limit, and (3) smoothing as learning objective using a novel maximum-a-posteriori version of deleted estimation working with expectation-maximization. where others conclude that latent segmentations lead to overfitting and deteriorating performance, we show here that these three ingredients give performance equivalent to the heuristic method on reasonably sized training data.
acquiring domain-specific dialog information from task-oriented human-human interaction through an unsupervised learning. we describe an approach for acquiring the domain-specific dialog knowledge required to configure a task-oriented dialog system that uses human-human interaction data. the key aspects of this problem are the design of a dialog information representation and a learning approach that supports capture of domain information from in-domain dialogs. to represent a dialog for a learning purpose, we based our representation, the form-based dialog structure representation, on an observable structure. we show that this representation is sufficient for modeling phenomena that occur regularly in several dissimilar task-oriented domains, including information-access and problem-solving. with the goal of ultimately reducing human annotation effort, we examine the use of unsupervised learning techniques in acquiring the components of the form-based representation (i.e. task, subtask, and concept). these techniques include statistical word clustering based on mutual information and kullback-liebler distance, texttiling, hmm-based segmentation, and bisecting k-mean document clustering. with some modifications to make these algorithms more suitable for inferring the structure of a spoken dialog, the unsupervised learning algorithms show promise.
revealing the structure of medical dictations with conditional random fields. automatic processing of medical dictations poses a significant challenge. we approach the problem by introducing a statistical framework capable of identifying types and boundaries of sections, lists and other structures occurring in a dictation, thereby gaining explicit knowledge about the function of such elements. training data is created semi-automatically by aligning a parallel corpus of corrected medical reports and corresponding transcripts generated via automatic speech recognition. we highlight the properties of our statistical framework, which is based on conditional random fields (crfs) and implemented as an efficient, publicly available toolkit. finally, we show that our approach is effective both under ideal conditions and for real-life dictation involving speech recognition errors and speech-related phenomena such as hesitation and repetitions.
stacking dependency parsers. we explore a stacked framework for learning to predict dependency structures for natural language sentences. a typical approach in graph-based dependency parsing has been to assume a factorized model, where local features are used but a global function is optimized (mcdonald et al., 2005b). recently nivre and mcdonald (2008) used the output of one dependency parser to provide features for another. we show that this is an example of stacked learning, in which a second predictor is trained to improve the performance of the first. further, we argue that this technique is a novel way of approximating rich non-local features in the second parser, without sacrificing efficient, model-optimal prediction. experiments on twelve languages show that stacking transition-based and graph-based parsers improves performance over existing state-of-the-art dependency parsers.
improving chinese semantic role classification with hierarchical feature selection strategy. in recent years, with the development of chinese semantically annotated corpus, such as chinese proposition bank and normalization bank, the chinese semantic role labeling (srl) task has been boosted. similar to english, the chinese srl can be divided into two tasks: semantic role identification (sri) and classification (src). many features were introduced into these tasks and promising results were achieved. in this paper, we mainly focus on the second task: src. after exploiting the linguistic discrepancy between numbered arguments and argms, we built a semantic role classifier based on a hierarchical feature selection strategy. different from the previous src systems, we divided src into three sub tasks in sequence and trained models for each sub task. under the hierarchical architecture, each argument should first be determined whether it is a numbered argument or an argm, and then be classified into fine-gained categories. finally, we integrated the idea of exploiting argument interdependence into our system and further improved the performance. with the novel method, the classification precision of our system is 94.68%, which outperforms the strong baseline significantly. it is also the state-of-the-art on chinese src.
seeded discovery of base relations in large corpora. relationship discovery is the task of identifying salient relationships between named entities in text. we propose novel approaches for two sub-tasks of the problem: identifying the entities of interest, and partitioning and describing the relations based on their semantics. in particular, we show that term frequency patterns can be used effectively instead of supervised ner, and that the p-median clustering objective function naturally uncovers relation exemplars appropriate for describing the partitioning. furthermore, we introduce a novel application of relationship discovery: the unsupervised identification of protein-protein interaction phrases.
multilingual subjectivity analysis using machine translation. although research in other languages is increasing, much of the work in subjectivity analysis has been applied to english data, mainly due to the large body of electronic resources and tools that are available for this language. in this paper, we propose and evaluate methods that can be employed to transfer a repository of subjectivity resources across languages. specifically, we attempt to leverage on the resources available for english and, by employing machine translation, generate resources for subjectivity analysis in other languages. through comparative evaluations on two different languages (romanian and spanish), we show that automatic translation is a viable alternative for the construction of resources and tools for subjectivity analysis in a new target language.
transliteration as constrained optimization. this paper introduces a new method for identifying named-entity (ne) transliterations in bilingual corpora. recent works have shown the advantage of discriminative approaches to transliteration: given two strings (ws, wt) in the source and target language, a classifier is trained to determine if wt is the transliteration of ws. this paper shows that the transliteration problem can be formulated as a constrained optimization problem and thus take into account contextual dependencies and constraints among character bi-grams in the two strings. we further explore several methods for learning the objective function of the optimization problem and show the advantage of learning it discriminately. our experiments show that the new framework results in over 50% improvement in translating english nes to hebrew.
question classification using head words and their hypernyms. question classification plays an important role in question answering. features are the key to obtain an accurate question classifier. in contrast to li and roth (2002)'s approach which makes use of very rich feature space, we propose a compact yet effective feature set. in particular, we propose head word feature and present two approaches to augment semantic features of such head words using wordnet. in addition, lesk's word sense disambiguation (wsd) algorithm is adapted and the depth of hypernym feature is optimized. with further augment of other standard features such as unigrams, our linear svm and maximum entropy (me) models reach the accuracy of 89.2% and 89.0% respectively over a standard benchmark dataset, which outperform the best previously reported accuracy of 86.2%.
ltag dependency parsing with bidirectional incremental construction. in this paper, we first introduce a new architecture for parsing, bidirectional incremental parsing. we propose a novel algorithm for incremental construction, which can be applied to many structure learning problems in nlp. we apply this algorithm to ltag dependency parsing, and achieve significant improvement on accuracy over the previous best result on the same data set.
a simple and effective hierarchical phrase reordering model. while phrase-based statistical machine translation systems currently deliver state-of-the-art performance, they remain weak on word order changes. current phrase reordering models can properly handle swaps between adjacent phrases, but they typically lack the ability to perform the kind of long-distance re-orderings possible with syntax-based systems. in this paper, we present a novel hierarchical phrase reordering model aimed at improving non-local reorderings, which seamlessly integrates with a standard phrase-based system with little loss of computational efficiency. we show that this model can successfully handle the key examples often used to motivate syntax-based systems, such as the rotation of a prepositional phrase around a noun phrase. we contrast our model with reordering models commonly used in phrase-based systems, and show that our approach provides statistically significant bleu point gains for two language pairs: chinese-english (+0.53 on mt05 and +0.71 on mt08) and arabic-english (+0.55 on mt05).
unsupervised multilingual learning for pos tagging. we demonstrate the effectiveness of multilingual learning for unsupervised part-of-speech tagging. the key hypothesis of multilingual learning is that by combining cues from multiple languages, the structure of each becomes more apparent. we formulate a hierarchical bayesian model for jointly predicting bilingual streams of part-of-speech tags. the model learns language-specific features while capturing cross-lingual patterns in tag distribution for aligned words. once the parameters of our model have been learned on bilingual parallel data, we evaluate its performance on a held-out monolingual test set. our evaluation on six pairs of languages shows consistent and significant performance gains over a state-of-the-art monolingual baseline. for one language pair, we observe a relative reduction in error of 53%.
using bilingual knowledge and ensemble techniques for unsupervised chinese sentiment analysis. it is a challenging task to identify sentiment polarity of chinese reviews because the resources for chinese sentiment analysis are limited. instead of leveraging only monolingual chinese knowledge, this study proposes a novel approach to leverage reliable english resources to improve chinese sentiment analysis. rather than simply projecting english resources onto chinese resources, our approach first translates chinese reviews into english reviews by machine translation services, and then identifies the sentiment polarity of english reviews by directly leveraging english resources. furthermore, our approach performs sentiment analysis for both chinese reviews and english reviews, and then uses ensemble methods to combine the individual analysis results. experimental results on a dataset of 886 chinese product reviews demonstrate the effectiveness of the proposed approach. the individual analysis of the translated english reviews outperforms the individual analysis of the original chinese reviews, and the combination of the individual analysis results further improves the performance.
relative rank statistics for dialog analysis. we introduce the relative rank differential statistic which is a non-parametric approach to document and dialog analysis based on word frequency rank-statistics. we also present a simple method to establish semantic saliency in dialog, documents, and dialog segments using these word frequency rank statistics. applications of our technique include the dynamic tracking of topic and semantic evolution in a dialog, topic detection, automatic generation of document tags, and new story or event detection in conversational speech and text. our approach benefits from the robustness, simplicity and efficiency of non-parametric and rank based approaches and consistently outperformed term-frequency and tf-idf cosine distance approaches in several experiments conducted.
computing word-pair antonymy. knowing the degree of antonymy between words has widespread applications in natural language processing. manually-created lexicons have limited coverage and do not include most semantically contrasting word pairs. we present a new automatic and empirical measure of antonymy that combines corpus statistics with the structure of a published thesaurus. the approach is evaluated on a set of closest-opposite questions, obtaining a precision of over 80%. along the way, we discuss what humans consider antonymous and how antonymy manifests itself in utterances.
automatic inference of the temporal location of situations in chinese text. chinese is a language that does not have morphological tense markers that provide explicit grammaticalization of the temporal location of situations (events or states). however, in many nlp applications such as machine translation, information extraction and question answering, it is desirable to make the temporal location of the situations explicit. we describe a machine learning framework where different sources of information can be combined to predict the temporal location of situations in chinese text. our experiments show that this approach significantly outperforms the most frequent tense baseline. more importantly, the high training accuracy shows promise that this challenging problem is solvable to a level where it can be used in practical nlp applications with more training data, better modeling techniques and more informative and generalizable features.
adapting a lexicalized-grammar parser to contrasting domains. most state-of-the-art wide-coverage parsers are trained on newspaper text and suffer a loss of accuracy in other domains, making parser adaptation a pressing issue. in this paper we demonstrate that a ccg parser can be adapted to two new domains, biomedical text and questions for a qa system, by using manually-annotated training data at the pos and lexical category levels only. this approach achieves parser accuracy comparable to that on newspaper data without the need for annotated parse trees in the new domain. we find that retraining at the lexical category level yields a larger performance increase for questions than for biomedical text and analyze the two datasets to investigate why different domains might behave differently for parser adaptation.
htm: a topic model for hypertexts. previously topic models such as plsi (probabilistic latent semantic indexing) and lda (latent dirichlet allocation) were developed for modeling the contents of plain texts. recently, topic models for processing hypertexts such as web pages were also proposed. the proposed hypertext models are generative models giving rise to both words and hyperlinks. this paper points out that to better represent the contents of hypertexts it is more essential to assume that the hyperlinks are fixed and to define the topic model as that of generating words only. the paper then proposes a new topic model for hypertext processing, referred to as hypertext topic model (htm). htm defines the distribution of words in a document (i.e., the content of the document) as a mixture over latent topics in the document itself and latent topics in the documents which the document cites. the topics are further characterized as distributions of words, as in the conventional topic models. this paper further proposes a method for learning the htm model. experimental results show that htm outperforms the baselines on topic discovery and document classification in three datasets.
a generative model for parsing natural language to meaning representations. in this paper, we present an algorithm for learning a generative model of natural language sentences together with their formal meaning representations with hierarchical structures. the model is applied to the task of mapping sentences to hierarchical representations of their underlying meaning. we introduce dynamic programming techniques for efficient training and decoding. in experiments, we demonstrate that the model, when coupled with a discriminative reranking technique, achieves state-of-the-art performance when tested on two publicly available corpora. the generative model degrades robustly when presented with instances that are different from those seen in training. this allows a notable improvement in recall compared to previous models.
ranking reader emotions using pairwise loss minimization and emotional distribution regression. this paper presents two approaches to ranking reader emotions of documents. past studies assign a document to a single emotion category, so their methods cannot be applied directly to the emotion ranking problem. furthermore, whereas previous research analyzes emotions from the writer's perspective, this work examines readers' emotional states. the first approach proposed in this paper minimizes pairwise ranking errors. in the second approach, regression is used to model emotional distributions. experiment results show that the regression method is more effective at identifying the most popular emotion, but the pairwise loss minimization method produces ranked lists of emotions that have better correlations with the correct lists.
an exploration of document impact on graph-based multi-document summarization. the graph-based ranking algorithm has been recently exploited for multi-document summarization by making only use of the sentence-to-sentence relationships in the documents, under the assumption that all the sentences are indistinguishable. however, given a document set to be summarized, different documents are usually not equally important, and moreover, different sentences in a specific document are usually differently important. this paper aims to explore document impact on summarization performance. we propose a document-based graph model to incorporate the document-level information and the sentence-to-document relationship into the graph-based ranking process. various methods are employed to evaluate the two factors. experimental results on the duc2001 and duc2002 datasets demonstrate that the good effectiveness of the proposed model. moreover, the results show the robustness of the proposed model.
selecting sentences for answering complex questions. complex questions that require inferencing and synthesizing information from multiple documents can be seen as a kind of topic-oriented, informative multi-document summarization. in this paper, we have experimented with one empirical and two unsupervised statistical machine learning techniques: k-means and expectation maximization (em), for computing relative importance of the sentences. however, the performance of these approaches depends entirely on the feature set used and the weighting of these features. we extracted different kinds of features (i.e. lexical, lexical semantic, cosine similarity, basic element, tree kernel based syntactic and shallow-semantic) for each of the document sentences in order to measure its importance and relevancy to the user query. we used a local search technique to learn the weights of the features. for all our methods of generating summaries, we have shown the effects of syntactic and shallow-semantic features over the bag of words (bow) features.
probabilistic inference for machine translation. we advance the state-of-the-art for discriminatively trained machine translation systems by presenting novel probabilistic inference and search methods for synchronous grammars. by approximating the intractable space of all candidate translations produced by intersecting an ngram language model with a synchronous grammar, we are able to train and decode models incorporating millions of sparse, heterogeneous features. further, we demonstrate the power of the discriminative training paradigm by extracting structured syntactic features, and achieving increases in translation performance.
summarizing spoken and written conversations. in this paper we describe research on summarizing conversations in the meetings and emails domains. we introduce a conversation summarization system that works in multiple domains utilizing general conversational features, and compare our results with domain-dependent systems for meeting and email data. we find that by treating meetings and emails as conversations with general conversational features in common, we can achieve competitive results with state-of-the-art systems that rely on more domain-specific features.
decomposability of translation metrics for improved evaluation and efficient algorithms. bleu is the de facto standard for evaluation and development of statistical machine translation systems. we describe three real-world situations involving comparisons between different versions of the same systems where one can obtain improvements in bleu scores that are questionable or even absurd. these situations arise because bleu lacks the property of decomposability, a property which is also computationally convenient for various applications. we propose a very conservative modification to bleu and a cross between bleu and word error rate that address these issues while improving correlation with human judgments.
specialized models and ranking for coreference resolution. this paper investigates two strategies for improving coreference resolution: (1) training separate models that specialize in particular types of mentions (e.g., pronouns versus proper nouns) and (2) using a ranking loss function rather than a classification function. in addition to being conceptually simple, these modifications of the standard single-model, classification-based approach also deliver significant performance improvements. specifically, we show that on the ace corpus both strategies produce f-score gains of more than 3% across the three coreference evaluation metrics (muc, b3, and ceaf).
seed and grow: augmenting statistically generated summary sentences using schematic word patterns. we examine the problem of content selection in statistical novel sentence generation. our approach models the processes performed by professional editors when incorporating material from additional sentences to support some initially chosen key summary sentence, a process we refer to as sentence augmentation. we propose and evaluate a method called "seed and grow" for selecting such auxiliary information. additionally, we argue that this can be performed using schemata, as represented by word-pair co-occurrences, and demonstrate its use in statistical summary sentence generation. evaluation results are supportive, indicating that a schemata model significantly improves over the baseline.
an analysis of active learning strategies for sequence labeling tasks. active learning is well-suited to many problems in natural language processing, where unlabeled data may be abundant but annotation is slow and expensive. this paper aims to shed light on the best active learning approaches for sequence labeling tasks such as information extraction and document segmentation. we survey previously used query selection strategies for sequence models, and propose several novel algorithms to address their shortcomings. we also conduct a large-scale empirical comparison using multiple corpora, which demonstrates that our proposed methods advance the state of the art.
language and translation model adaptation using comparable corpora. traditionally, statistical machine translation systems have relied on parallel bi-lingual data to train a translation model. while bi-lingual parallel data are expensive to generate, monolingual data are relatively common. yet monolingual data have been under-utilized, having been used primarily for training a language model in the target language. this paper describes a novel method for utilizing monolingual target data to improve the performance of a statistical machine translation system on news stories. the method exploits the existence of comparable text---multiple texts in the target language that discuss the same or similar stories as found in the source language document. for every source document that is to be translated, a large monolingual data set in the target language is searched for documents that might be comparable to the source documents. these documents are then used to adapt the mt system to increase the probability of generating texts that resemble the comparable document. experimental results obtained by adapting both the language and translation models show substantial gains over the baseline system.
studying the history of ideas using topic models. how can the development of ideas in a scientific field be studied over time? we apply unsupervised topic modeling to the acl anthology to analyze historical trends in the field of computational linguistics from 1978 to 2006. we induce topic clusters using latent dirichlet allocation, and examine the strength of each topic over time. our methods find trends in the field including the rise of probabilistic methods starting in 1988, a steady increase in applications, and a sharp decline of research in semantics and understanding between 1978 and 2001, possibly rising again after 2001. we also introduce a model of the diversity of ideas, topic entropy, using it to show that coling is a more diverse conference than acl, but that both conferences as well as emnlp are becoming broader over time. finally, we apply jensen-shannon divergence of topic distributions to show that all three conferences are converging in the topics they cover.
learning with probabilistic features for improved pipeline models. we present a novel learning framework for pipeline models aimed at improving the communication between consecutive stages in a pipeline. our method exploits the confidence scores associated with outputs at any given stage in a pipeline in order to compute probabilistic features used at other stages downstream. we describe a simple method of integrating probabilistic features into the linear scoring functions used by state of the art machine learning algorithms. experimental evaluation on dependency parsing and named entity recognition demonstrate the superiority of our approach over the baseline pipeline models, especially when upstream stages in the pipeline exhibit low accuracy.
triplet lexicon models for statistical machine translation. this paper describes a lexical trigger model for statistical machine translation. we present various methods using triplets incorporating long-distance dependencies that can go beyond the local context of phrases or n-gram based language models. we evaluate the presented methods on two translation tasks in a reranking framework and compare it to the related ibm model 1. we show slightly improved translation quality in terms of bleu and ter and address various constraints to speed up the training based on expectation-maximization and to lower the overall number of triplets without loss in translation performance.
a dependency-based word subsequence kernel. this paper introduces a new kernel which computes similarity between two natural language sentences as the number of paths shared by their dependency trees. the paper gives a very efficient algorithm to compute it. this kernel is also an improvement over the word subsequence kernel because it only counts linguistically meaningful word subsequences which are based on word dependencies. it overcomes some of the difficulties encountered by syntactic tree kernels as well. experimental results demonstrate the advantage of this kernel over word subsequence and syntactic tree kernels.
preface. for a long time, i have wanted to make a short film with this song.
a sensory controlled gripper system. in this paper, a gripper system, provided with tactile sensors, is described. various ways of using tactile information have been explored. the work contains two parts. one is concerned with servo control aspects, where the tactile sensors were used as force sensors, together with a position transducer, to implement position and force hybrid control. the other part deals with tactile image processing, where slip detection, object localization and object recognition are discussed and implemented.
robotics: where has it been? where is it going? the history of robotics stretches far into the past, with numerous tales of attempts to create artificial life. the start-up and rapid growth eras, from 1950 till 1985, were dominated by applications in spot welding and spray painting. the current era of disillusionment has occurred because the tasks of assembly and mobility are technologically more difficult than most people had anticipated. the future has many promising applications, from undersea to outerspace. what the future brings will depend on how much of our wealth we invest in it.
a prototype for intelligent computer integrated wood truss fabrication. this paper describes research efforts in which an expert process planning system, based on the semi-intelligent process selector (sips) expert system shell, is linked with an industrial robot arm to perform fixed plant cutting and assembly operations (wood truss fabrication). the operational protocol of this system involves providing truss design input to the process planner via a file of truss feature parameter frames. this planner, which is resident on a ti explorer workstation, generates the fabrication sequence and transfers this sequence to a robot control program which is resident on a separate microcomputer. this control program creates the required robot commands to produce robot movement. this paper provides a general discussion of knowledge-based expert systems and computer-aided process planning followed by the specifics of the development and operation of a sips based automated truss manufacturing system. this latter section includes an overview of the process planning shell utilized in this effort, and the structure of the knowledge bases developed. the makeup and function of the interpreter software package and the specifics of the major system hardware components are also discussed.
economic effects of robotization in japan. in this paper several questions related to robotics are dealt with in the context of the japanese economy. these include the economic distinction of robots and the problems that can be solved by them, as well as the explanation for the rapid spread of robotics in japan.
autonomous single arm oru changeout - strategies, control issues, and implementation. a preliminary strategy for autonomous single arm orbital replacement unit (oru) changeout, the associated compliance and force control issues, and implementation results are described. the changeout operation is separated into subtasks, e.g. bolt-turn, compliant-grasp, and dual-pin-insertion/removal. compliance and force control are done in cartesian space and the selection of appropriate locations for the cartesian control frame is discussed. the dual-pin-insertion/removal subtask requires a decision based strategy in conjunction with compliant control to prevent jamming. actual implementation was done with a puma 560 6 degree of freedom manipulator although the control strategies could be implemented on any manipulator with at least 6 degrees of freedom.
design of a snake-like manipulator. over the past decade, investigations have been made into issues which are specific to the design and control of highly-flexible manipulators - arias which are composed of a large number of small, rigid links. of particular importance to these researchers is the means of joint actuation, since most manipulators in this category are too small to have drive motors placed directly at the joints. this paper also deals with joint actuation, but attacks the problem in a unique fashion. the result is a manipulator in which all of the joints are driven by a single prime mover and whose snake-like motion ensures obstacle avoidance.
constructive recognizability for task-directed robot programming. the primary goal of our research is task-level planning. we approach this goal by utilizing a blend of theory, implementation, and experimentation. we investigate task-level planning for autonomous agents, such as mobile robots, that function in an uncertain environment. these robots typically have very approximate, inaccurate, or minimal models of the environment. for example, although the geometry of its environment is crucial to determining its performance, [footnote:i.e., what the geometry is will have a key role in determining the robot''s actions or behavior.] a mobile robot might only have a partial, or local ``map'''' of the world. similarly, the expected effects of a robot''s actuators critically influence its selection of actions to accomplish a goal, but a robot may have only a very approximate, or local predictive ability with regard to forward-simulation of a control strategy. while mobile robots are typically equipped with sensors in order to gain information about the world, and to compensate for errors in actuation and prediction, these sensors are noisy, and in turn provide inaccurate information. we investigate an approach whereby the robot attempts to acquire the necessary information about the world by planning a series of experiments [footnote: the robot (not the researchers!) performs the experiments, to gain information about the world.] using the robot''s sensors and actuators, and building data-structures based on the robot''s observations of these experiments. a key feature of this approach is that the experiments the robot performs should be driven by the information demands of the task. that is, in performing some task, the robot may enter a state in which making progress towards a goal requires more information about the world (or its own state). in this case, the robot should plan experiments which can disambiguate the situation. when this process is driven by the information demands of the task, we believe it is an important algorithmic technique to effect task-directed sensing. this introductory survey article discusses: 1. a theory of sensor interpretation and task-directed planning using perceptual equivalence classes, intended to be applicable in highly uncertain or unmodelled environments, such as for a mobile robot. 2. algorithmic techniques for modelling geometric constraints on recognizability, and the building of internal representations (such as maps) using these constraints. 3. explicit encoding of the information requirements of a task using a lattice (information hierarchy) of recognizable sets, which allows the robot to perform experiments to recognize a situation or a landmark. 4. the synthesis of robust mobot programs using the geometric constraints, constructive recognizability experiments, and uncertainty models imposed by the task. we discuss how to extend our theory and the geometric theory of planning to overcome challenges of the autonomous mobile robot domain. one of our most important goals is to s
dynamic motion vision. motion vision deals with the analysis of image sequences acquired by a camera moving relative to an environment. the goal is to recover the motion of the camera as well as the structure of the environment. we model the changing structure of the scene perceived in the camera as a dynamical system. the state of this system is the depth, the distance of a scene point from the camera, the measurement is the optical flow, a vector field of image velocities which can be computed from the image brightness arrays acquired by the camera. we use the dynamical systems model in the construction of a kalman filter which optimally estimates the depth of a point in the image incrementally over the sequence of frames. by using one kalman filter per image pixel we are able to recover a dense depth map of the environment, i.e. the scene structure. in every filter iteration we estimate the motion parameters of the camera from the optical flow field using the filter's current depth estimate in a least-squares fashion. the resulting algorithm recovers both the camera motion and the scene structure in an systematic way which could not be accomplished previously. we have implemented this algorithm and tested it on real and synthetic images.
automation in construction. robots are being used in increasing numbers in manufacturing throughout the world. the expanded use of industrial robots in manufacturing and the increased projections of greater numbers in the future has resulted in a greater interest by the construction industry. this paper describes five prototype robots developed by shimizu corporation for applications in construction industry.
intelligent control of an autonomous mobile robot in a hazardous material spill accident - a blackboard structure approach. this paper describes the use of the blackboard architecture for the high level programming and control of autonomous mobile robots in a hazardous material spill emergency situation. the purpose of the robot is to perform some of the tasks which are dangerous for the emergency response personnels. the proposed blackboard system provides a unifying framework for the integration of information from various sensor-based and knowledge-based sub-systems.
off-line programming by cad-systems for welding robots. information theory constitutes more and more an essential element for robots control. it gives a primary role to programming systems which make it possible to take full advantage of the flexibility possibilities of robots. the informatic structure on which these systems rest is more often than not organized around the concept of a programming language specific to robotics [1]. this article sets out the development of a system for automatic production of programs for welding robots control, from cad specification till welding parameters.
nonlinear formation control of unicycle-type mobile robots. we investigate formation control of a group of unicycle-type mobile robots at the dynamics level with a little amount of inter-robot communication. a combination of the virtual structure and path-tracking approaches is used to derive the formation architecture. each individual robot has only position and orientation available for feedback. for each robot, a coordinate transformation is first derived to cancel the velocity quadratic terms. an observer is then designed to globally exponentially/asymptotically estimate the unmeasured velocities. an output feedback controller is designed for each robot. the controller is designed in such a way that the path derivative is left as a free input to synchronize the robots' motion. simulations illustrate the soundness of the proposed controller.
an automated shear stud welding system. stud welding is highly repetitive and stressful on the worker; thus it is a prime candidate for automation. a robotic device, called the ''studmaster'', has been developed at mit which automates stud welding during construction of industrial buildings and can easily be adapted for use on bridge decks. the machine is controlled by a microcomputer, and utilizes a loading and welding mechanism which is actuated by three pneumatic cylinders and one mechanical relay. this mechanism is mounted on a small tracked vehicle which is manually indexed to each weld site by a human operator. expected payback time for an industrially hardened version is estimated to be on the order of 1-2 years.
an effective trajectory generation method for bipedal walking. this paper presents the virtual height inverted pendulum mode (vhipm), which is a simple and effective trajectory generation method for the stable walking of biped robots. vhipm, which is based on the inverted pendulum mode (ipm), can significantly reduce the zero moment point (zmp) error by adjusting the height in the inverted pendulum. we show the relationship between vhipm and other popular trajectory generation methods, and compare the zmp errors in walking when trajectories are generated by various methods including vhipm. we also investigate the sensitivity of the zmp error in vhipm to the step length, walking period and mass distribution of a robot. the simulation results show that vhipm significantly reduces the zmp errors compared to other methods under various circumstances.
the nonholonomic redundancy of second-order nonholonomic mechanical systems. the nonholonomic redundancy of second-order nonholonomic mechanical systems is investigated. it has been verified that the self-motion can be implemented demonstrably by some nonholonomic mechanical systems such as the underactuated redundant manipulators. an exponentially stabilization control method is proposed for a class of underactuated manipulators, of which the number of actuated joints is no less than that of the passive joints. it has been shown that this class of underactuated manipulators are completely controllable when the dynamic coupling of the underactuated manipulators is non-degenerated and the up-boundary of the inputs is large enough. by the proposed control method, we exhibit this class manipulators with zero weight can realize the ''self-motion'' as a full-actuated redundant one. as a typical application, the problem of path tracking with suppressing vibration is investigated for the underactuated redundant manipulators. it is revealed that the vibration of the underactuated redundant manipulator can be converted into an internal resonance that is compatible with the ''self-motion'', while it leads to no vibration at the end-effector of the manipulator. some numerical simulations by a planar four-dof underactuated manipulator with two actuated joints and two passive joints show the effectiveness of the accurate trajectory control method and the value of the self-motion compatible internal resonance.
motion design and learning of autonomous robots based on primitives and heuristic cost-to-go. the task of trajectory design of autonomous vehicles is typically two-fold. first, it needs to take into account the intrinsic dynamics of the vehicle, which are sometimes termed local constraints. second, on a higher level, the designed trajectories must allow the vehicle to achieve some application-specific task. the specification of the task results in the so-called global constraints. both of these two components of trajectory design are generally nontrivial problems, and very often, they are pursued as two parallel areas. when the results drawn from the two areas are applied in conjunction, the synthesis is usually somewhat arbitrary. in this paper, we assume that some optimal control laws are available as a set of motion primitives to address the vehicle dynamics. the trajectories that achieve the task are determined solely through the primitives and do not reference the vehicle dynamics directly. for the higher level, we translate the task into a very special type of cost-to-go function, which is partially specified artificially and partially determined by an admissibility condition imposed by the set of primitives. the optimality feature of the primitives is formally extended to the final trajectory design. we illustrate this result with the example of a mobile robot retrieving an object, which is an interesting problem of its own right. both a direct design approach and a learning approach are presented.
unified controller for both trajectory tracking and point regulation of second-order nonholonomic chained systems. in this article, a unified controller is developed for both trajectory tracking and point regulation of nonholonomic second-order chained systems. the controller design relies on converting the error model of second-order chained systems to the form of perturbed first-order nonholonomic integrator, followed by a dynamic state feedback control law steering the tracking error to origin exponentially. the proposed control law is universal for both trajectory tracking and point regulation, as the reference trajectories can be any one produced by bounded reference inputs. the control design approach is illustrated by application to a planar manipulator with two translational actuated joints and one revolute unactuated joint. simulation results show the effectiveness of the proposed approach.
output-feedback formation tracking control of unicycle-type mobile robots with limited sensing ranges. this paper presents a constructive method to design output-feedback cooperative controllers that force a group of n unicycle-type mobile robots with limited sensing ranges to perform desired formation tracking, and guarantee no collisions between the robots. the robot velocities are not required for control implementation. for each robot an interlaced observer, which is a reduced order observer plus an interlaced term, is designed to estimate the robot unmeasured velocities. the observer design is based on a coordinate transformation that transforms the robot dynamics to a new dynamics, which does not contain velocity quadratic terms. the interlaced term is determined after the formation control design is completed to void difficulties due to observer errors and consideration of collision avoidance. smooth and p times differentiable jump functions are introduced and incorporated into novel potential functions to design a formation tracking control system. despite the robot limited sensing ranges, no switchings are needed to solve the collision avoidance problem. simulations illustrate the results.
a programming and simulation environment for the karlsruhe dextrous hand. in this paper the development of a programming and simulation environment is described, which was especially tailored for programming of multifinger hands. the research has concerned with the programming of the karlsruhe dextrous hand, a non-anthropomorphic three finger gripper with 9 degrees of freedom, which is being developed at our institute. the work presents the results of a task-oriented approach to the object manipulation problem and contains two main parts: a system programming module and an application programming module. this realization supports the interactive generation and evaluation of a hand program using graphical simulation.
automatic visual guidance of a forklift engaging a pallet. this paper presents the development of a prototype vision-guided forklift system for the automatic engagement of pallets. the system is controlled using the visual guidance method of mobile camera-space manipulation, which is capable of achieving a high level of precision in positioning and orienting mobile manipulator robots without relying on camera calibration. the paper contains development of the method, the development of a prototype forklift as well as experimental results in actual pallet engagement tasks. the technology could be added to agv systems enabling them to engage arbitrarily located pallets. it also could be added to standard forklifts as an operator assist capability.
automated modeling of modular robotic configurations. this research presents an automated method to build kinematic and dynamic models for assembling modular components of modular robotic systems. by comparison with other approaches, the proposed method is applicable to any robotic configuration with serial, parallel, or hybrid structures. in addition, it is object oriented so that each modular component is an element with a submodel and the overall model can be assembled from submodels subject to the connection constraints.
reinforcement learning for quasi-passive dynamic walking of an unstable biped robot. a class of biped locomotion called passive dynamic walking (pdw) has been recognized to be efficient in energy consumption and a key to understand human walking. although pdw is sensitive to the initial condition and disturbances, studies of quasi-pdw which incorporates supplemental actuators have been reported to overcome this sensitivity. in this article, we propose a reinforcement learning method designed particularly for quasi-pdw of a biped robot whose possession of knees makes the system unstable. simulations show that the learning is quickly accomplished after 1000 episodes, and the obtained controller is robust against variations in the slope gradient and sudden perturbations.
distributed multi-robot coordination in area exploration. this paper proposes a reliable and efficient multi-robot coordination algorithm to accomplish an area exploration task given that the communication range of each robot is limited. this algorithm is based on a distributed bidding model to coordinate the movement of multiple robots. two measures are developed to accommodate the limited-range communications. first, the distances between robots are considered in the bidding algorithm so that the robots tend to stay close to each other. second, a map synchronization mechanism, based on a novel sequence number-based map representation and an effective robot map update tracking, is proposed to reduce the exchanged data volume when robot subnetworks merge. simulation results show the effectiveness of the use of nearness measure, as well as the map synchronization mechanism. by handling the limited communication range we can make the coordination algorithms more realistic in multi-robot applications.
an integrated approach to the conceptual design and development of an intelligent autonomous mobile robot. this paper proposes a new approach to the design and development of an intelligent mobile robot and discusses the complex functional structure of such systems, providing solutions to some typical design problems. the proposed design approach provides a clearer view of the design problems from a function-oriented interdisciplinary point of view. the approach proves to be a useful tool in allowing the designer to cross the boundaries of technical disciplines and optimise the interdisciplinary system's components, thereby improving the overall system performance. the paper also presents a case study where it takes the design problem from the most abstract level up to the final stage, in which the developed autonomous mobile robot's specifications are verified and validated. the issues addressed in this paper include the design, development, systems integration, and experimental testing of the intelligent mobile robot.
low level controller for a pomdp based on wifi observations. this paper shows the results of a low level controller that has been applied to an autonomous robotic system using a wifi-based partially observable markov decision process (pomdp). these observations provide a clue for global robot localization from the first iteration of the pomdp algorithm. due to the noise channel of wifi measures, it becomes necessary to make observations at a well known location within the environment. therefore, a robust local navigator is needed in order to place the robot in an optimal position for making the observation. the system has been tested with two pioneer 2at robots in the premises of the department of electronics at the university of alcala.
a sensor for dynamic tactile information with applications in human-robot interaction and object exploration. we present a novel tactile sensor, which is applied for dextrous grasping with a simple robot gripper. the hardware novelty consists of an array of capacitive sensors, which couple to the object by means of little brushes of fibers. these sensor elements are very sensitive (with a threshold of about 5 mn) but robust enough not to be damaged during grasping. they yield two types of dynamical tactile information corresponding roughly to two types of tactile sensor in the human skin. the complete sensor consists of a foil-based static force sensor, which yields the total force and the center of the two-dimensional force distribution and is surrounded by an array of the dynamical sensor elements. one such sensor has been mounted on each of the two gripper jaws of our humanoid robot and equipped with the necessary read-out electronics and a can bus interface. we describe applications to guiding a robot arm on a desired trajectory with negligible force, reflective grip improvement, and tactile exploration of objects to create a shape representation and find stable grips, which are applied autonomously on the basis of visual recognition.
a 3-level autonomous mobile robot navigation system designed by using reasoning/search approaches. this paper describes how soft computing methodologies such as fuzzy logic, genetic algorithms and the dempster-shafer theory of evidence can be applied in a mobile robot navigation system. the navigation system that is considered has three navigation subsystems. the lower-level subsystem deals with the control of linear and angular volocities using a multivariable pi controller described with a full matrix. the position control of the mobile robot is at a medium level and is nonlinear. the nonlinear control design is implemented by a backstepping algorithm whose parameters are adjusted by a genetic algorithm. we propose a new extension of the controller mentioned, in order to rapidly decrease the control torques needed to achieve the desired position and orientation of the mobile robot. the high-level subsystem uses fuzzy logic and the dempster-shafer evidence theory to design a fusion of sensor data, map building, and path planning tasks. the fuzzy/evidence navigation based on the building of a local map, represented as an occupancy grid, with the time update is proven to be suitable for real-time applications. the path planning algorithm is based on a modified potential field method. in this algorithm, the fuzzy rules for selecting the relevant obstacles for robot motion are introduced. also, suitable steps are taken to pull the robot out of the local minima. particular attention is paid to detection of the robot's trapped state and its avoidance. one of the main issues in this paper is to reduce the complexity of planning algorithms and minimize the cost of the search. the performance of the proposed system is investigated using a dynamic model of a mobile robot. simulation results show a good quality of position tracking capabilities and obstacle avoidance behavior of the mobile robot.
a sonar approach to obstacle detection for a vision-based autonomous wheelchair. an advanced prototype computer controlled power wheelchair navigation system or ccpwns has been developed to provide autonomy for highly disabled users, whose mix of disabilities makes it difficult or impossible to control their own power chairs in their homes. the working paradigm is ''teach and repeat'' a mode of control for typical industrial holonomic robots. ultrasound sensors, which during subsequent autonomous tracking will be used to detect obstacles, also are active during teaching. based upon post-processed data collected during this teaching event, elaborate trajectories-which may involve multiple direction changes, pivoting and so on, depending upon the requirements of the typically restricted spaces within which the chair must operate-will later be called upon by the disabled rider. an off-line postprocessor assigns an ultrasound profile to the sequence of poses of any taught trajectory. use of this profile during tracking obviates most of the inherent problems of using ultrasound to avoid obstacles while retaining the ability to near solid objects, such as when passing through a narrow doorway, where required by the environment and trajectory objectives. the work in this article describes a procedure to obtain consistent maps of sonar boundaries during the teaching process, and a preliminary approach to use this information during the tracking phase. the approach is illustrated by results obtained by using the ccpwns prototype.
prediction of geometric errors of robot manipulators with particle swarm optimisation method. this paper reports on the prediction of the expected positioning errors of robot manipulators due to the errors in their geometric parameters. a swarm intelligence (si) based algorithm, which is known as particle swarm optimization (pso), has been used to generate error estimation functions. the experimental system used is a motoman sk120 manipulator. the error estimation functions are based on the robot position data provided by a high precision laser measurement system. the functions have been verified for three test trajectories, which contain various configurations of the manipulator. the experimental results demonstrate that the positioning errors of robot manipulators can be effectively predicted using some constant coefficient polynomials whose coefficients are determined by employing the pso algorithm. it must be emphasized that once the estimation functions are obtained, there may be no need of any further experimental data in order to determine the expected positioning errors for a subsequent use in the error correction process.
cognitive maps for mobile robots - an object based approach. robots are rapidly evolving from factory work-horses to robot-companions. the future of robots, as our companions, is highly dependent on their abilities to understand, interpret and represent the environment in an efficient and consistent fashion, in a way that is comprehensible to humans. the work presented here is oriented in this direction. it suggests a hierarchical probabilistic representation of space that is based on objects. a global topological representation of places with object graphs serving as local maps is proposed. the work also details the first efforts towards conceptualizing space on the basis of the human compatible representation so formed. such a representation and the resulting conceptualization would be useful for enabling robots to be cognizant of their surroundings. experiments on place classification and place recognition are reported in order to demonstrate the applicability of such a representation towards understanding space and thereby performing spatial cognition. further, relevant results from user studies validating the proposed representation are also reported. thus, the theme of the work is - representation for spatial cognition.
biomimetic whiskers for shape recognition. rodents demonstrate an outstanding capability of tactile perception with their whiskers. mechanoreceptors surrounding the whisker shaft in their follicle structure measure deflection of the whisker. we designed biomimetic whiskers following the basic design of the follicle. in experiments with the artificial whiskers, we have explored tactile perception based on active whisking where the deflection angle or velocity provides the localization information which is the basis of shape recognition. measuring contact distances at varying protraction angles allows discrimination of round objects with a varying curvature, or objects with different lateral shapes, such as square and round objects. we show the capabilities and limitations of a single whisker for shape recognition as well as the usefulness of multiple whiskers. in addition, measuring both vertical and horizontal deflection of a single whisker allows detection of the vertical shape for objects with a smooth surface. two or more whiskers stacked vertically can recognize the vertical shape by observing the difference of their deflection amplitudes or the time shift of deflection velocity peak. the results provide a clue on how autonomous robots could improve their sensory capabilities with mechanical probes.
self-calibration of environmental camera for mobile robot navigation. an environmental camera is a camera embedded in a working environment to provide vision guidance to a mobile robot. in the setup of such robot systems, the relative position and orientation between the mobile robot and the environmental camera are parameters that must unavoidably be calibrated. traditionally, because the configuration of the robot system is task-driven, these kinds of external parameters of the camera are measured separately and should be measured each time a task is to be performed. in this paper, a method is proposed for the robot system in which calibration of the environmental camera is rendered by the robot system itself on the spot after a system is set up. specific kinds of motion patterns of the mobile robot, which are called test motions, have been explored for calibration. the calibration approach is based upon executing certain selected test motions on the mobile robot and then using the camera to observe the robot. according to a comparison of odometry and sensing data, the external parameters of the camera can be calibrated. furthermore, an evaluation index (virtual sensing error) has been developed for the selection and optimization of test motions to obtain good calibration performance. all the test motion patterns are computed offline in advance and saved in a database, which greatly shorten the calibration time. simulations and experiments verified the effectiveness of the proposed method.
fast and accurate slam with rao-blackwellized particle filters. rao-blackwellized particle filters have become a popular tool to solve the simultaneous localization and mapping problem. this technique applies a particle filter in which each particle carries an individual map of the environment. accordingly, a key issue is to reduce the number of particles and/or to make use of compact map representations. this paper presents an approximative but highly efficient approach to mapping with rao-blackwellized particle filters. moreover, it provides a compact map model. a key advantage is that the individual particles can share large parts of the model of the environment. furthermore, they are able to reuse an already computed proposal distribution. both techniques substantially speed up the overall filtering process and reduce the memory requirements. experimental results obtained with mobile robots in large-scale indoor environments and based on published standard datasets illustrate the advantages of our methods over previous mapping approaches using rao-blackwellized particle filters.
using covariance intersection for slam. one of the greatest obstacles to the use of simultaneous localization and mapping (slam) in a real-world environment is the need to maintain the full correlation structure between the vehicle and all of the landmark estimates. this structure is computationally expensive to maintain and is not robust to linearization errors. in this tutorial we describe slam algorithms that attempt to circumvent these difficulties through the use of covariance intersection (ci). ci is the optimal algorithm for fusing estimates when the correlations among them are unknown. a feature of ci relative to techniques which exploit full correlation information is that it provides provable consistency with much less computational overhead. in practice, however, a tradeoff typically needs to be made between estimation accuracy and computational cost. we describe a number of techniques that span the range of tradeoffs from maximum computational efficiency with straight ci to maximum estimation efficiency with the maintenance of all correlation information. we present a set of examples illustrating benefits of ci-based slam.
active estimation of distance in a robotic system that replicates human eye movement. in a moving agent, the different apparent motion of objects located at various distances provides an important source of depth information. while motion parallax is evident for large translations of the agent, a small parallax also occurs in most head/eye systems during rotations of the cameras. a similar parallax is also present in the human eye, so that a redirection of gaze shifts the projection of an object on the retina by an amount that depends not only on the amplitude of the rotation, but also on the distance of the object with respect to the observer. this study examines the accuracy of distance estimation on the basis of the parallax produced by camera rotations. sequences of human eye movements were used to control the motion of a pan/tilt system specifically designed to reproduce the oculomotor parallax present in the human eye. we show that the oculomotor strategies by which humans scan visual scenes produce parallaxes that provide accurate estimation of distance. this information simplifies challenging visual tasks such as image segmentation and figure/ground segregation.
occupancy grids building by sonar and mobile robot. in this paper, a modified method for occupancy grid map building by a moving mobile robot and a scanning ultrasonic range-finder is proposed. the map building process consists of two phases: (1) gleaning of information from environment, and (2) sonar data processing. for sonar data processing the proposed modified method combines: (1) statistical approach for probability sonar model building; and (2) application of fuzzy logic theory for sonar data fusion. it is experimentally shown that, in some applications, the proposed modified method has advantages over other well-known methods.
bilateral teleoperation through the internet. this paper proposes a stable control structure for the bilateral teleoperation of robots through internet. the problem is motivated by the increasing use of the internet as a communication channel. internet has a time-varying delay which depends on factors such as congestion, bandwidth and distance. in this work, we propose a control structure for the teleoperation of a manipulator robot with force feedback. such a control structure includes state controllers (placed on the local and remote sites) and a time-delay compensation, which modifies the delayed position command generated by the human operator using the force that he feels in such a delayed moment and the current force between the slave and the remote environment. in addition, the proposed control scheme is designed considering a model of the communication channel. finally, experiments of bilateral teleoperation of robots through intranet and internet are shown to test the performance and stability of the designed teleoperation system.
recursive scan-matching slam. this paper presents scan-slam, a new generalization of simultaneous localization and mapping (slam). slam implementations based on extended kalman filter (ekf) data fusion have traditionally relied on simple geometric models for defining landmarks. this limits ekf-slam to environments suited to such models and tends to discard much potentially useful data. the approach presented in this paper is a marriage of ekf-slam and scan correlation. landmarks are no longer defined by analytical models; instead they are defined by templates composed of raw sensed data. these templates can be augmented as more data become available so that the landmark definition improves with time. a new generic observation model is derived that is generated by scan correlation, and this permits stochastic location estimation for landmarks with arbitrary shape within the kalman filter framework. the statistical advantages of an ekf representation are augmented with the general applicability of scan matching. scan matching also serves to enhance data association reliability by providing a shape metric for landmark disambiguation. experimental results in an outdoor environment are presented which validate the algorithm.
robust localization and tracking of simultaneous moving sound sources using beamforming and particle filtering. mobile robots in real-life settings would benefit from being able to localize and track sound sources. such a capability can help localizing a person or an interesting event in the environment, and also provides enhanced processing for other capabilities such as speech recognition. to give this capability to a robot, the challenge is not only to localize simultaneous sound sources, but to track them over time. in this paper we propose a robust sound source localization and tracking method using an array of eight microphones. the method is based on a frequency-domain implementation of a steered beamformer along with a particle filter-based tracking algorithm. results show that a mobile robot can localize and track in real-time multiple moving sources of different types over a range of 7 m. these new capabilities allow a mobile robot to interact using more natural means with people in real-life settings.
multi-robot mobility enhanced hop-count based localization in ad hoc networks. the localization problem is important in mobile robots and wireless sensor network and has been studied for many years. among many localization methods, the hop-count based approach is simple and scalable; however, the localization accuracy is not satisfactory if the node density is low. to solve this problem, in this paper a multi-robot approach is proposed to utilize the cooperation and mobility of the robots to improve the node distribution (density), thus enhancing the hop-count based localization. by an auction-based task allocation scheme, the robots can negotiate with the static sensor nodes and then select the most suitable robots to move to the area of sparse node density, thus increasing the localization accuracy for the static sensor nodes. on the other hand, the robots also can localize themselves with the help of the static sensor nodes. the efficacy of this approach is shown by simulation.
design and dock analysis for the interactive module of a lattice-based self-reconfigurable robot. in this paper, a novel, lattice-based self-reconfigurable modular robot is presented. each module is composed of a cubic part and six rotary sides. there are two holes and two extension pegs on each side. rotary motion is generated by a motor with a reducer by using cone-shaped gears, clutches and so on. its quick disconnect/connect mechanism is analyzed. a face-face incidence matrix (ffim) is proposed to describe the relationship between modules in detail. the states of docking and constraint between modules are analyzed with the geometric method and the contact force of docking is described. lastly, a self-reconfigurable robot consisting of five similar modules designed to pass the groove in simulation with the proposed motion rules and its ffim is presented. the results verify that the above analysis is effective.
on point-to-point motion planning for underactuated space manipulator systems. in free-floating mode, space manipulator systems have their actuators turned off, and exhibit nonholonomic behavior due to angular momentum conservation. the system is underactuated and a challenging problem is to control both the location of the end effector and the attitude of the base, using manipulator actuators only. here a path planning methodology satisfying this requirement is developed. the method uses high order polynomials, as arguments in cosine functions, to specify the desired path directly in joint-space. in this way, the accessibility of final configurations is extended drastically, and the free parameters are determined by optimization techniques. it was found that this approach leads always to a path, provided that the desired change in configuration lies between physically permissible limits. physical limitations, imposed by system's dynamic parameters, are examined. lower and upper bounds for base rotation, due to manipulator motions, are estimated and shown in the implementation section. the presented method avoids the need for many small cyclical motions, and uses smooth functions in the planning scheme, leading to smooth configuration changes in finite and prescribed time.
evolution of fuzzy behaviors for multi-robotic system. in a multi-robotic system, robots interact with each other in a dynamically changing environment. the robots need to be intelligent both at the individual and group levels. in this paper, the evolution of a fuzzy behavior-based architecture is discussed. the behavior-based architecture decomposes the complicated interactions of multiple robots into modular behaviors at different complexity levels. the fuzzy logic approach brings in human-like reasoning to the behavior construction, selection and coordination. various behaviors in the fuzzy behavior-based architecture are evolved by genetic algorithm (ga). at the lowest level of the architecture hierarchy, the evolved fuzzy controllers enhanced the smoothness and accuracy of the primitive robot actions. at a higher level, the individual robot behaviors have become more skillful after the evolution. at the topmost level, the evolved group behaviors have resulted in aggressive competition strategy. the simulation and real-world experimentation on a robot-soccer system justify the effectiveness of the approach.
on the use of bayesian networks to develop behaviours for mobile robots. bayesian networks are models which capture uncertainties in terms of probabilities that can be used to perform reasoning under uncertainty. this paper presents an attempt to use bayesian networks as a learning technique to manage task execution in mobile robotics. to learn the bayesian network structure from data, the k2 structural learning algorithm is used, combined with three different net evaluation metrics. the experiment led to a new hybrid multiclassifying system resulting from the combination of 1-nn with the bayesian network, that allows one to use the power of the bayesian network while avoiding the computational burden of the reasoning mechanism - the so-called evidence propagation process. as an application example we present an approach of the presented paradigm to implement a door-crossing behaviour in a mobile robot using only sonar readings, in an environment with smooth walls and doors. both the performance of the learning mechanism and the experiments run in the real robot-environment system show that bayesian networks are valuable learning mechanisms, able to deal with the uncertainty and variability inherent to such systems.
a relative map approach to slam based on shift and rotation invariants. this paper presents a solution to the simultaneous localization and mapping (slam) problem in the stochastic map framework based on the concept of the relative map. the idea consists in introducing a map state, which only contains relative quantities among the features invariant under shift and rotation. the estimation of this relative state is carried out through an extended kalman filter. the shift and rotation invariance of the state allows us to significantly reduce the computational burden. in particular, the computational requirement is independent of the number of features. furthermore, since the estimation process is local, it is not affected by the linearization introduced by the ekf. the cases of point features and corner features are considered. furthermore, in the case of corners, it is considered a realistic case of an indoor environment containing structures consisting of several corners. finally, since a relative map contains dependent elements, the information coming from all the constraints which express the elements dependency, is exploited. for this, an approximated solution with low computational requirement is proposed. its limitation arises at the loop closure since it cannot exploit the information in this case. this is discussed in depth for the case of point features. experimental results carried out on a real platform in our laboratory and by using the victoria park dataset show the performance of the approach.
real-time motion planning of an autonomous mobile manipulator using a fuzzy adaptive kalman filter. this paper presents the real-time motion planning i.e., map building and path planning of an autonomous mobile manipulator capable of scanning natural terrain using a detector e.g., a landmine detector. map building generates a terrain map using the measurements of laser and ultrasonic rangefinders, and path planning uses the map to define an obstacle-free path for the detector. map building involves sensor fusion to tackle the uncertainties associated with range measurement. fusion takes place in a hierarchical filtering process that updates the map in real time and also optimizes the scanning process based on the terrain type. the filtering process includes a proposed fuzzy adaptive kalman filter in which the gain of the filter is adapted using a fuzzy model that characterizes the terrain. the efficiency of the proposed map building and path planning methods has been verified by experiments on a prototype mine detector robot.
including probabilistic target detection attributes into map representations. range measuring sensors can play an extremely important role in robot navigation. all range measuring devices rely on a 'detection criterion' made in the presence of noise, to determine when the transmitted signal is considered detected and hence a range reading is obtained. in commonly used sensors, such as laser range finders and polaroid sonars, the criterion under which successful detection is assumed, is kept hidden from the user. however, 'detection decisions' on the presence of noise still take place within the sensor. this paper integrates signal detection probabilities into the map building process which provides the most accurate interpretation of such sensor data. to facilitate range detection analysis, map building with a frequency modulated continuous wave millimetre wave radar (fmcw mmwr), which is able to provide complete received power-range spectra for multiple targets down range is considered. this allows user intervention in the detection process and although not directly applicable to the commonly used 'black-box' type range sensors, provides insight as to how not only range values, but received signal strength values should be incorporated into the map building process. this paper presents two separate methods of map building with sensors which return both range and received signal power information. the first is an algorithm which uses received signal-to-noise power to make an estimates of the range to multiple targets down range, without any signal distribution assumptions. we refer to this as feature detection based on target presence probability (tpp). in contrast to the first method, the second method does use assumptions on the statistics of the signal in target presence and absence scenarios to formulate a probabilistic likelihood detector. this allows for an increased rate of convergence to ground truth. evidence theory is then introduced to model and update successive observations in a recursive fashion. both methods are then compared using real mmwr data sets from indoor and outdoor experiments.
real-time implementation of airborne inertial-slam. this paper addresses some challenges to the real-time implementation of simultaneous localisation and mapping (slam) on a uav platform. when compared to the implementation of slam in 2d environments, airborne implementation imposes several difficulties in terms of computational complexity and loop closure, with high nonlinearity in both vehicle dynamics and observations. an implementation of airborne slam is formulated to relieve this computational complexity in both direct and indirect ways. our implementation is based on an extended kalman filter (ekf), which fuses data from an inertial measurement unit (imu) with data from a passive vision system. real-time results from flight trials are provided.
a decomposition approach to multi-vehicle cooperative control. we use a decomposition approach to generate cooperative strategies for a class of multi-vehicle control problems. by introducing a set of tasks to be completed by the team of vehicles and a task execution method for each vehicle, we decompose the problem into a combinatorial component and a continuous component. the continuous component of the problem is captured by task execution, and the combinatorial component is captured by task assignment. in this paper, we present a solver for task assignment that generates near-optimal assignments quickly and can be used in real-time applications. to motivate our methods, we apply them to an adversarial game between two teams of vehicles. one team is governed by simple rules and the other by our algorithms. in our study of this game we found phase transitions, showing that the task assignment problem is most difficult to solve when the capabilities of the adversaries are comparable. finally, we utilize our algorithms in a hierarchical model predictive control architecture with a variable replanning rate at each level to provide feedback in dynamically changing and uncertain environments.
robocentric map joining: improving the consistency of ekf-slam. in this paper we study the extended kalman filter approach to simultaneous localization and mapping (ekf-slam), describing its known properties and limitations, and concentrate on the filter consistency issue. we show that linearization of the inherent nonlinearities of both the vehicle motion and the sensor models frequently drives the solution of the ekf-slam out of consistency, specially in those situations where uncertainty surpasses a certain threshold. we propose a mapping algorithm, robocentric map joining, which improves consistency of the ekf-slam algorithm by limiting the level of uncertainty in the continuous evolution of the stochastic map: (1) by building a sequence of independent local maps, and (2) by using a robot centered representation of each local map. simulations and a large-scale indoor/outdoor experiment validate the proposed approach.
oats: oxford aerial tracking system. small robot helicopters are becoming a popular research platform due to the availability of off-the-shelf components and their suitability for useful applications. we describe the oxford aerial tracking system (oats) that we are commissioning, which takes a commercial airframe and low-level flight controller, and adapts these for use in applications requiring the visual tracking of ground targets. this uses a camera on a two-axis gimbal feeding images into an on-board processing system, which communicates summary information to a ground station. so far we have tested the system off the aircraft using laboratory targets and canned image sequences; we have also developed in simulation a variety of high-level algorithms for the platform, including those for target area scanning, geo-localisation, 3-d path planning, and target trajectory prediction; this paper focuses on the hardware, system software, and object tracking sub-systems. testing on the airframe is now underway.
visual task identification and characterization using polynomial models. developing robust and reliable control code for autonomous mobile robots is difficult, because the interaction between a physical robot and the environment is highly complex, subject to noise and variation, and therefore partly unpredictable. this means that to date it is not possible to predict robot behaviour based on theoretical models. instead, current methods to develop robot control code still require a substantial trial-and-error component to the software design process. this paper proposes a method of dealing with these issues by (a) establishing task-achieving sensor-motor couplings through robot training, and (b) representing these couplings through transparent mathematical functions that can be used to form hypotheses and theoretical analyses of robot behaviour. we demonstrate the viability of this approach by teaching a mobile robot to track a moving football and subsequently modelling this task using the narmax system identification technique.
realtime motion path generation using subtargets in a rapidly changing environment. in this work an algorithm is proposed for path planning in a rapidly changing environment. the algorithm is computationally cheap and generates a sub-optimal smooth path with bounds on the allowed velocity, acceleration, and jerk. the algorithm is designed for holonomic omniwheel platforms. it outperforms potential field algorithms regarding both convergence and optimality. furthermore, it is able to adapt fast in a rapidly changing environment due to the low computational cost in the order of ms for a single update, in contrast with computationally more expensive methods such as wavefront algorithms and global optimization methods, where the computational cost is mostly on the order of seconds. the algorithm will be tested via simulations and experiments.
fault-tolerant robot manipulators based on output-feedback h controllers. this paper develops two fault-tolerant control strategies for robot manipulators. the first is based on linear parameter-varying systems and the second on markovian jump linear systems. firstly, it is shown that with the lpv approach post-fault stability is guaranteed only if the robot stops completely after a fault detection. then, with an underactuated configuration, the manipulator can be controlled appropriately. secondly, it is shown that with the fault-tolerant system based on markovian jump linear systems, stability is guaranteed after a fault is detected even with the robot still moving. this approach incorporates all manipulator configurations in a unified model. both strategies have been implemented based on output-feedback controllers, which are the main focus of this paper. experimental results illustrate the performance of each controller.
learning spatial concepts from ratslam representations. ratslam is a biologically-inspired visual slam and navigation system that has been shown to be effective indoors and outdoors on real robots. the spatial representation at the core of ratslam, the experience map, forms in a distributed fashion as the robot learns the environment. the activity in ratslam's experience map possesses some geometric properties, but still does not represent the world in a human readable form. a new system, dubbed ratchat, has been introduced to enable meaningful communication with the robot. the intention is to use the ''language games'' paradigm to build spatial concepts that can be used as the basis for communication. this paper describes the first step in the language game experiments, showing the potential for meaningful categorization of the spatial representations in ratslam.
autonomous and fast robot learning through motivation. research on robot techniques that are fast, user-friendly, and require little application-specific knowledge by the user, is more and more encouraged in a society where the demand of home-care or domestic-service robots is increasing continuously. in this context we propose a methodology which combines reinforcement learning and genetic algorithms to teach a robot how to perform a task when only the specification of the main restrictions of the desired behaviour is provided. through this combination, both paradigms must be merged in such a way that they influence each other to achieve a fast convergence towards a good robot-control policy, and reduce the random explorations the robot needs to carry out in order to find a solution. another advantage of our proposal is that it is able to easily incorporate any kind of domain-dependent knowledge about the task. this is very useful for improving a robot controller, for applying a robot-controller to move a different robot-platform, or when we have certain ''feelings'' about how the task should be solved. the performance of our proposal is shown through its application to solve a common problem in mobile robotics.
instantaneous robot self-localization and motion estimation with omnidirectional vision. this paper presents two related methods for autonomous visual guidance of robots: localization by trilateration, and interframe motion estimation. both methods use coaxial omnidirectional stereopsis (omnistereo), which returns the range r to objects or guiding points detected in the images. the trilateration method achieves self-localization using r from the three nearest objects at known positions. the interframe motion estimation is more general, being able to use any features in an unknown environment. the guiding points are detected automatically on the basis of their perceptual significance and thus they need not have either special markings or be placed at known locations. the interframe motion estimation does not require previous motion history, making it well suited for detecting acceleration (in 20th of a second) and thus supporting dynamic models of robot's motion which will gain in importance when autonomous robots achieve useful speeds. an initial estimate of the robot's rotation &omega; (the visual compass) is obtained from the angular optic flow in an omnidirectional image. a new noniterative optic flow method has been developed for this purpose. adding &omega; to all observed (robot relative) bearings &theta; gives true bearings towards objects (relative to a fixed coordinate frame). the rotation &omega; and the r,&theta; coordinates obtained at two frames for a single fixed point at unknown location are sufficient to estimate the translation of the robot. however, a large number of guiding points are typically detected and matched in most real images. each such point provides a solution for the robot's translation. the solutions are combined by a robust clustering algorithm clumat that reduces rotation and translation errors. simulator experiments are included for all the presented methods. real images obtained from scitosg5 autonomously moving robot were used to test the interframe rotation and to show that the presented vision methods are applicable to real images in real robotics scenarios.
space-variant motion detection for active visual target tracking. a biologically inspired approach to active visual target tracking is presented. the approach makes use of three strategies found in biological systems: space-variant sensing, a spatio-temporal-frequency-based model of motion detection and the alignment of sensory-motor maps. space-variant imaging is used to create a 1d array of elementary motion detectors (emds) that are tuned in such a way as to make it possible to detect motion over a wide range of velocities while still being able to detect motion precisely. the array is incorporated into an active visual tracking system. a method of analysis and design for such a tracking system is proposed. it makes use of a sensory-motor map which consists of a phase-plane plot of the continuous-time dynamics of the tracking system overlaid onto a map of the detection capabilities of the array of emds. this sensory-motor map is used to design a simple 1d tracking system and several simulations show how the method can be used to control tracking performance using such metrics as overshoot and settling time. a complete 1d active vision system is implemented and a set of simple target tracking experiments are performed to demonstrate the effectiveness of the approach.
a tactile luminous floor for an interactive autonomous space. this paper describes the interactive tactile luminous floor that was constructed and used as the skin of the playful interactive space ada, which ran as a public exhibit for five months in 2002 and had over 550,000 visitors. ada's floor was custom-built to provide a means for individual and collective user interaction. it consists of 360 hexagonal 66 cm tiles covering a total area of 136 m^2, each with analogue tactile load sensors based on force-sensitive resistors and dimmable neon red, green and blue (rgb) lamps. the tiles are constructed from extruded aluminum with glass tops. an interbus factory automation bus senses and controls the tiles. software is described for rendering fluid, dynamic visual effects on the floor, for signal processing of the load information, for real-time visitor tracking and for a variety of behavioural modes, games and interactions. data from single tiles and from tracking are shown. this floor offers new modalities of human-computer interaction and human-robot interaction for autonomous robotic spaces.
neural network models of haptic shape perception. three different models of tactile shape perception inspired by the human haptic system were tested using an 8 d.o.f. robot hand with 45 tactile sensors. one model is based on the tensor product of different proprioceptive and tactile signals and a self-organizing map (som). the two other models replace the tensor product operation with a novel self-organizing neural network, the tensor-multiple peak self-organizing map (t-mpsom). the two t-mpsom models differ in the procedure employed to calculate the neural activation. the computational models were trained and tested with a set of objects consisting of hard spheres, blocks and cylinders. all the models learned to map different shapes to different areas of the som, and the tensor product model as well as one of the t-mpsom models also learned to discriminate individual test objects.
application of sonql for real-time learning of robot behaviors. this paper describes the semi-online neural-q-learning (sonql) algorithm designed for real-time learning of reactive robot behaviors. the q-function is generalized by a multilayer neural network allowing the use of continuous states. the algorithm uses a database of the most recent learning samples to accelerate and improve the convergence. each sonql algorithm represents an independent, reactive and adaptive state-action mapping, which implements the function of a robot behavior for one degree of freedom (dof). the generalization capability of the sonql algorithm was demonstrated by computer simulation with the ''mountain-car'' benchmark. the sonql was also investigated by experiment on a mobile robot for a target-following task. experimental results show that the sonql is promising for online robot learning.
intelligent decision making in multi-agent robot soccer system through compounded artificial neural networks. this paper proposes a two-stage approach using artificial neural networks for the intelligent decision-making by the robots in a mirosot small league. the first stage involves the use of an evolutionary algorithm for getting a rough estimate of the neural network weight matrices. the proposed approach is then generalized to the case of quick, intelligent and accurate decision-making in the case of a robot soccer system with robots utilizing the concept of compounded artificial neural networks. in the proposed approach a soccer field is divided into three zones so that the decision of the robots depends on the zone of the ball at any instant. the concept of a forward robot is also introduced in this paper to enhance the accuracy of the decision-making with the global strategy of advancing towards the goal area of the opponent for scoring a goal. simulation results indicate that the proposed techniques are very effective in taking intelligent decision-making in a multi-agent robot soccer system in mirosot small league as well as middle league.
self-localization in non-stationary environments using omni-directional vision. this paper presents an image-based approach for localization in non-static environments using local feature descriptors, and its experimental evaluation in a large, dynamic, populated environment where the time interval between the collected data sets is up to two months. by using local features together with panoramic images, robustness and invariance to large changes in the environment can be handled. results from global place recognition with no evidence accumulation and a monte carlo localization method are shown. to test the approach even further, experiments were conducted with up to 90% virtual occlusion in addition to the dynamic changes in the environment.
compensation of velocity and/or acceleration joint saturation applied to redundant manipulator. the article describes a new method for velocity/acceleration redistribution in order to compensate joint velocity and/or acceleration saturation. the method is designed for redundant manipulators. when some of the joint velocities/accelerations are in saturation other joints compensate for the lack of the velocity and the velocity in the task space remains unchanged. without the compensation the task space error would appear. using the compensation method we can achieve maximal velocity/acceleration in the task space while preserving joint velocity/acceleration within limits. the method is also appropriate to compensate a torque saturation. additionally, we have introduced a condition that shows if the compensation is kinematically and mathematically possible or not.
a biologically inspired method for vision-based docking of wheeled mobile robots. we present a new control law for the problem of docking a wheeled robot to a target at a certain location with a desired heading. recent research into insect navigation has inspired a solution which uses only one video camera. the control law is of the ''behavioral'' type in that all control actions are based on immediate visual information. docking success under certain conditions is proved mathematically and simulation studies show the control law to be robust to camera intrinsic parameter errors. experiments were performed for verification of the control law.
a variational method for the recovery of dense 3d structure from motion. the purpose of this study is to investigate a variational formulation of the problem of three-dimensional (3d) interpretation of temporal image sequences based on the 3d brightness constraint and anisotropic regularization. the method allows movement of both the viewing system and objects and does not require the computation of image motion prior to 3d interpretation. interpretation follows the minimization of a functional with two terms: a term of conformity of the 3d interpretation to the image sequence first-order spatio-temporal variations, and a term of regularization based on anisotropic diffusion to preserve the boundaries of interpretation. the euler-lagrange partial differential equations corresponding to the functional are solved efficiently via the half-quadratic algorithm. results of several experiments on synthetic and real image sequences are given to demonstrate the validity of the method and its implementation.
amirolos an active marker internet-based robot localization system. sauron (surveillance autonomous robots over network) is a research project focused on the use of autonomous patrolling robots for surveillance purposes. this paper presents the structure of sauron localization module amirolos (active marker internet-based robot localization system). it provides on demand the robot position in indoor and outdoor environments using active markers and commercial off-the-shelf web-cams. the system has a client-server architecture, and is now part of a message-oriented middleware that is under development at the university of brescia. the functionality of the localization module has been demonstrated with real-world experiments.
dynamic object manipulation by an array of 1-dof manipulators: kinematic modeling and planning. dynamic manipulation of polygonal objects by an array of one degree of freedom arms is studied from kinematics and planning points of view. in the studied manipulation method, an object is manipulated to its goal configuration by a sequence of juggles. a kinematic model of an object throwing task is driven and a method for object manipulation by a sequence of throws is proposed. the method, called backward throws method (btm), is based on throwing an object backward towards the arm pivot. based on the developed model, a planning algorithm is proposed for btm. in addition, the only existing similar method to btm, which is based on forward throws-named ftm in this paper-is reformulated for implementation by a series of arms and compared with the proposed method. analytical investigations, simulation results, and experimental outcomes show that btm meets the desired requirements. moreover, in comparison to ftm, btm requires fewer number of throws and lower release velocity. in addition, the object's maximum height of flight is much lower in btm which results in lower catching impact. according to the experimental results, although the proposed method has no feedback from object position, accumulated position error is very small. this fact is directly related to the attained decrease in catching impact which causes small object slippage and rebound on catching. furthermore, there is no restriction on the arm geometry in btm while in ftm an arm with negative offset is needed.
reachability-based analysis for probabilistic roadmap planners. in the last fifteen years, sampling-based planners like the probabilistic roadmap method (prm) have proved to be successful in solving complex motion planning problems. while theoretically, the complexity of the motion planning problem is exponential in the number of degrees of freedom, sampling-based planners can successfully handle this curse of dimensionality in practice. we give a reachability-based analysis for these planners which leads to a better understanding of the success of the approach. this analysis compares the techniques based on coverage and connectivity of the free configuration space. the experiments show, contrary to general belief, that the main challenge is not getting the free space covered but getting the nodes connected, especially when the problems get more complicated, e.g. when a narrow passage is present. by using this knowledge, we can tackle the narrow passage problem by incorporating a refined neighbor selection strategy, a hybrid sampling strategy, and a more powerful local planner, leading to a considerable speed-up.
observer-based sliding mode impedance control of bilateral teleoperation under constant unknown time delay. sliding mode control has been used extensively in robotics to cope with parametric uncertainty and hard nonlinearities, in particular for time-delay teleoperators, which have gained gradual acceptance due to technological advancements. however, since the slave teleoperator is in contact with a rigid environment, the slave controller requires a free of chattering control strategy, thus making first order sliding mode teleoperation control unsuitable. as an alternative, chatter free, higher-order sliding mode teleoperator control is proposed in this paper to guarantee robust tracking under unknown constant time delay. moreover, complete order observers are proposed to avoid measurement of velocity and acceleration, along with a formal closed-loop stability proof of the observer-based controller. experimental results are presented and discussed, which reveals the effectiveness of the proposed teleoperation scheme.
vision-based interception of a moving target with a nonholonomic mobile robot. a novel vision-based scheme is presented for driving a nonholonomic mobile robot to intercept a moving target. the proposed method has a two-level structure. on the lower level, the pan-tilt platform carrying the on-board camera is controlled so as to keep the target as close as possible to the center of the image plane. on the higher level, the relative position of the target is retrieved from its image coordinates and the camera pan-tilt angles through simple geometry, and used to compute a control law which drives the robot to the target. various possible choices are discussed for the high-level robot controller, and the associated stability properties are rigorously analysed. the proposed visual interception method is validated through simulations as well as experiments on the mobile robot magellanpro.
adaptive task assignment for multiple mobile robots via swarm intelligence approach. this paper describes an adaptive task assignment method for a team of fully distributed mobile robots with initially identical functionalities in unknown task environments. a hierarchical assignment architecture is established for each individual robot. in the higher hierarchy, we employ a simple self-reinforcement learning model inspired by the behavior of social insects to differentiate the initially identical robots into ''specialists'' of different task types, resulting in stable and flexible division of labor; on the other hand, in dealing with the cooperation problem of the robots engaged in the same type of task, ant system algorithm is adopted to organize low-level task assignment. to avoid using a centralized component, a ''local blackboard'' communication mechanism is utilized for knowledge sharing. the proposed method allows the robot team members to adapt themselves to the unknown dynamic environments, respond flexibly to the environmental perturbations and robustly to the modifications in the team arising from mechanical failure. the effectiveness of the presented method is validated in two different task domains: a cooperative concurrent foraging task and a cooperative collection task.
classifying still faces with ultrasonic sensing. the echo of a chirp of ultrasonic energy from an object contains information about the geometry of that object: the relative depth of its surfaces and the approximate area of those surfaces. a human face has complex geometry that produces a distinctive echo. in this paper, we report the initial research into whether there is sufficient information in the echo to recognize a still face. potential features for classification are identified using a facial model. the classification results for 10 faces encourage future research with a larger number of faces and with moving faces.
short and long-range visual navigation using warped panoramic images. in this paper, we present a method that uses panoramic images to perform long-range navigation as a succession of short-range homing steps along a route specified by appearances of the environment of the robot along the route. our method is different from others in that it does not extract any features from the images and only performs simple image processing operations. the method does only make weak assumptions about the surroundings of the robot, assumptions that are discussed. furthermore, the method uses a technique borrowed from computer graphics to simulate the effect in the images of short translations of the robot to compute local motion parameters. finally, the proposed method shows that it is possible to perform navigation without explicitly knowing where the destination is nor where the robot currently is. results in our lab are presented that show the performance of the proposed system.
force position control for a robot finger with a soft tip and kinematic uncertainties. we consider the problem of force and position regulation for a robot finger with a soft tip in contact with a surface with unknown geometrical characteristics. an adaptive controller is proposed, and the asymptotic convergence of the applied force error and the estimated position error of the tip to zero is shown for the spatial case. simulation results demonstrate the controller performance.
real-time hierarchical pomdps for autonomous robot navigation. this paper proposes a new hierarchical formulation of pomdps for autonomous robot navigation that can be solved in real-time, and is memory efficient. it will be referred to in this paper as the robot navigation-hierarchical pomdp (rn-hpomdp). the rn-hpomdp is utilized as a unified framework for autonomous robot navigation in dynamic environments. as such, it is used for localization, planning and local obstacle avoidance. hence, the rn-hpomdp decides at each time step the actions the robot should execute, without the intervention of any other external module for obstacle avoidance or localization. our approach employs state space and action space hierarchy, and can effectively model large environments at a fine resolution. finally, the notion of the reference pomdp is introduced. the latter holds all the information regarding motion and sensor uncertainty, which makes the proposed hierarchical structure memory efficient and enables fast learning. the rn-hpomdp has been experimentally validated in real dynamic environments.
a fast evaluation criterion for the recognition of occluded shapes. a robust and fast object recognition method is crucial in many robotic applications, especially (but not restricted to) in manufacturing. this paper introduces a novel algorithm that satisfies both of these criteria and is capable of recognising a set of model shapes in a complicated scene given as input. the shapes are described using the turning angle representation. shape matching is carried out by finding the correspondence between the model shape and the input (i.e. corresponding points), and calculating the geometrical transformation of the model that minimises the least square distance between the corresponding points. a new geometric feature is proposed, called ''generalised angle'', which facilitates fast elimination of infeasible matches. the generalised angle (ga) is invariant to rotation, translation and scaling and does not result in a considerable computational cost to the system. moreover, an evaluation function is used, which takes several criteria into account and renders the method capable of recognising shapes under occlusion effectively.
image-based robot navigation from an image memory. this paper addresses the problem of vision-based navigation and proposes an original control law to perform such navigation. the overall approach is based on an appearance-based representation of the environment, where the scene is directly defined in the sensor space by a database of images acquired during a learning phase. within this context, a path to follow is described by a set of images, or image path extracted from the database. this image path is designed so as to provide enough information to control the robotic system. the central contribution of this paper is the closed-loop control law that drives the robot to its desired position using this image path. this control does not require either a global 3d reconstruction or a temporal planning step. furthermore, the robot is not constrained to converge directly upon each image of the path, but chooses its trajectory automatically. we propose a process of qualitative visual servoing, enabling us to enlarge the convergence space towards positioning in a range within a confidence interval. we propose and use specific visual features which ensure that the robot navigates within the visibility path. experimental simulations are given to show the effectiveness of this method for controlling the motion of a camera in three-dimensional environments (free-flying camera, or camera moving on a plane). in addition, experiments realized with a robotic arm observing a planar scene are also presented.
visual novelty detection with automatic scale selection. this paper presents experiments with an autonomous inspection robot, whose task was to highlight novel features in its environment from camera images. the experiments used two different attention mechanisms-saliency map and multi-scale harris detector-and two different novelty detection mechanisms - the grow-when-required (gwr) neural network and an incremental principal component analysis (pca). for all mechanisms we compared fixed-scale image encoding with automatically scaled image patches. results show that automatic scale selection provides a more efficient representation of the visual input space, but that performance is generally better using a fixed-scale image encoding.
mobile robot localization using active sensing based on bayesian network inference. in this paper we propose a novel method of sensor planning for a mobile robot localization problem. we represent the conditional dependence relation between local sensing results, actions, and belief of the global localization using a bayesian network. initially, the structure of the bayesian network is learned from the complete data of the environment using the k2 algorithm combined with a genetic algorithm (ga). in the execution phase, when the robot is kidnapped to some place, it plans an optimal sensing action by taking into account the trade-off between the sensing cost and the global localization belief, which is obtained by inference in the bayesian network. we have validated the learning and planning algorithm by simulation experiments in an office environment.
path planning with general end-effector constraints. in this paper, we address the path planning problem with general end-effector constraints (ppgec) for robot manipulators. two approaches are proposed. the first approach is the adapted-rgd method, which is adapted from an existing randomized gradient descent (rgd) method for closed-chain robots. the second approach is radically different. we call it atace, alternate task-space and configuration-space exploration. unlike the first approach which searches purely in c-space, atace works in both task space and c-space. it explores the task space for end-effector paths satisfying given constraints, and utilizes trajectory tracking technique(s) as a local planner(s) to track these paths in the configuration space. we have implemented both approaches and compared their relative performances in different scenarios. atace outperforms adapted-rgd in the majority (but not all) of the scenarios. we outline intuitive explanations for the relative performances of these two approaches.
a constrained slam approach to robust and accurate localisation of autonomous ground vehicles. for driving assistance systems, intelligent vehicles and autonomous robots to be viable in complex environments, it is necessary to have a reliable and robust localisation function. due to the large variability and uncertainty of such complex environments, which include theme parks, university campuses, suburbs, industrial estates and the like, it is difficult to rely on a specific method or set of sensor data to correctly and robustly estimate the robot path/pose. the key to solving the localisation problem is to optimally use and fuse all useful sources of information available to the mobile platform. for the envisaged environment, it is not unusual to have approximate digital maps of the road network. in this paper, in addition to the typical sensory information provided by extereoceptive and proprioceptive sensors, it is shown how a priori approximate knowledge available in the form of a road map can be systematically fused within a simultaneous localisation and map building (slam) framework to obtain more accurate and robust localisation results. this reformulation of slam through the introduction of constraints in the form of a priori map information not only makes the problem theoretically more correct in the sense of observability but also makes the system viable and effective, yielding more accurate results. the results obtained in an actual environment are presented to validate the claims.
high resolution relative localisation using two cameras. wheel odometry is a common method for high resolution relative localisation. however, wheel odometry relies on the integrity and accuracy of a kinematic model. in this paper, a new method for relative localisation, 'visiodometry', which does not rely on a kinematic model, is proposed. the system consists of two ground-facing cameras mounted on either side of the robot. from the sequence of images acquired, the relative change in pose of the robot is estimated using a phase correlation based method. results on a plain coloured carpeted surface, show that the method provides a truly odometric type sensor data input similar in modality and resolution to wheel odometry. a method to calibrate the visiodometry system using a 1d object is also presented.
multi-method learning and assimilation. considering the wide range of possible behaviours to be acquired for domestic robots, applying a single learning method is clearly insufficient. in this paper, we propose a new strategy for behaviour acquisition for domestic robots where the behaviours are acquired using multiple differing learning methods that are subsequently incorporated into a common behaviour selection system, enabling them to be performed in appropriate situations. an example of the implementation of this strategy applied to the entertainment humanoid robot qrio is introduced and the results are discussed.
maccepa, the mechanically adjustable compliance and controllable equilibrium position actuator: design and implementation in a biped robot. in this paper a rotational actuator with a novel adaptable compliance (inverse of stiffness) is presented. first, a number of comparable designs are given with their possible drawbacks. the maccepa concept and design is then described in detail. the equation to calculate the generated torque is derived. depending on the design parameters, it is shown that the torque is a quasi linear function with respect to the angle between the equilibrium position and the actual position. also, the change of the pre-tension has a quasi linear effect on the torque. another advantage is that the actuator can be built with standard components, e.g. electrical servo motors. experiments show independent control of the equilibrium position and compliance. the use of the maccepa in the controlled passive walking biped veronica is described. controlled passive walking is an approach that combines the advantages of actively controlled robots and passive walkers. by adapting the compliance of the joints, natural motions can be chosen in order to obtain a controllable and energy efficient walking motion. to test the concept, the biped veronica is built, actuated by six maccepas.
supervised semantic labeling of places using information extracted from sensor data. indoor environments can typically be divided into places with different functionalities like corridors, rooms or doorways. the ability to learn such semantic categories from sensor data enables a mobile robot to extend the representation of the environment facilitating interaction with humans. as an example, natural language terms like ''corridor'' or ''room'' can be used to communicate the position of the robot in a map in a more intuitive way. in this work, we first propose an approach based on supervised learning to classify the pose of a mobile robot into semantic classes. our method uses adaboost to boost simple features extracted from sensor range data into a strong classifier. we present two main applications of this approach. firstly, we show how our approach can be utilized by a moving robot for an online classification of the poses traversed along its path using a hidden markov model. in this case we additionally use as features objects extracted from images. secondly, we introduce an approach to learn topological maps from geometric maps by applying our semantic classification procedure in combination with a probabilistic relaxation method. alternatively, we apply associative markov networks to classify geometric maps and compare the results with a relaxation approach. experimental results obtained in simulation and with real robots demonstrate the effectiveness of our approach in various indoor environments.
hybrid deliberative/reactive control of a scanning system for landmine detection. antipersonnel mines infest fields all over the world. according to recent estimates, landmines are killing and maiming more than 2000 innocent civilians per month. the problem of landmine detection and removal requires the cooperation of a number of engineering fields, which in turn poses a need for new technologies, such as improved sensors, efficient manipulators and mobile robots. this paper describes the configuration and control architecture of a scanning manipulator for detecting antipersonnel landmines. the scanning system is part of a demining system based on a walking robot that acts as the carrier for the scanning manipulator. broadly speaking, the scanning system consists of a sensor head that can detect certain kinds of landmines and, to move the sensor head over large areas, a manipulator that has been appropriately sensorized to scan irregular terrains in the presence of obstacles. the proposed control architecture is of the hybrid deliberative/reactive type: a deliberative controller defines a sweep trajectory that furnishes complete coverage of the infested area, while two reactive controllers are involved in on-line adaptation to the environment. experiments show good performance of the whole system.
programmable springs: developing actuators with programmable compliance for autonomous robots. developing real robots that can exploit dynamic interactions with the environment requires the use of actuators whose behaviour can vary from high stiffness to complete compliance or zero impedance. we will outline our design for an electric actuator, called a programmable spring, which can easily be configured using a high-level programming interface to emulate complex multimodal spring damping systems. the types of behaviour that our actuator can exhibit are explored, including antagonistic actuation, cyclic behaviour and hysteresis. this system is intended as the basis for a cost-effective 'off-the-shelf' component for robotics research and development.
developmental learning for autonomous robots. developmental robotics is concerned with the design of algorithms that promote robot adaptation and learning through qualitative growth of behaviour and increasing levels of competence. this paper uses ideas and inspiration from early infant psychology (up to three months of age) to examine how robot systems could discover the structure of their local sensory-motor spaces and learn how to coordinate these for the control of action. an experimental learning model is described and results from robotic experiments using the model are presented and discussed.
sensor-based path planning for nonholonomic mobile robots subject to dynamic constraints. it is generally not easy to achieve smooth path planning in an unknown environment for nonholonomic mobile robots, which are subject to various robot constraints. in this paper, a hybrid approach is proposed for smooth path planning with global convergence for differential drive nonholonomic robots. we first investigate the use of a polar polynomial curve (ppc) to produce a path changing continuously in curvature and satisfying dynamic constraints. in order to achieve path generation in real-time, a computationally effective method is proposed for collision test of the complex curve. then, a hybrid path planning approach is presented to guide the robot to move forward along the boundary of an obstacle of arbitrary shape, by generating a proper ''instant goal'' (and a series of deliberate motions through ppc curve based path generation) and planning reactively when needed using a fuzzy controller for wall following. the choice of an instant goal is limited to the set of candidates that are practically reachable by the robot and that enable the robot to continue following the obstacle. the effectiveness of the proposed approach is verified by simulation experiments.
task identification and characterisation in mobile robotics through non-linear modelling. the lack of a theory-based design methodology for mobile robot control programs means that control programs have to be developed through an empirical trial-and-error process. this can be costly, time consuming and error prone. in this paper we show how to develop a theory of robot-environment interaction, which would overcome the above problem. we show how we can model a mobile robot's task (so-called ''task identification'') using non-linear polynomial models (narmax), which can subsequently be formally analysed using established mathematical methods. this provides an understanding of the underlying phenomena governing the robot's behaviour. apart from the paper's main objective of formally analysing robot-environment interaction, the task identification process has further benefits, such as the fast and convenient cross-platform transfer of robot control programs (''robot java''), parsimonious task representations (memory issues) and very fast control code execution times.
decentralized cooperative control of heterogeneous vehicle groups. we coordinate in discrete time the interaction of two heterogeneous groups of mobile agents: a group of ground vehicles (ugvs) and a group of aerial vehicles (uavs). the ground agents interact with each other through time-invariant, nearest-neighbour rules. they synchronize their velocities through a specific communication protocol, and maintain cohesion and separation behaviour by means of interagent potential forces. ground vehicles estimate their formation's centroid using only locally available delayed information. that same information is transmitted to the aerial group, which orbits above the ground formation's centroid, while avoiding midair collisions. stability of the ground group motion is established in a lyapunov framework. a lyapunov analysis is also used to ensure that uavs track the ground group's centroid.
the reverse monte carlo localization algorithm. global localization is a very fundamental and challenging problem in robotic soccer. here, the main aim is to find the best method which is very robust and fast and requires less computational resources and memory compared to similar approaches and is precise enough for robot soccer games and technical challenges. in this work, the reverse monte carlo localization (r-mcl) method is introduced. the algorithm is designed for fast, precise and robust global localization of autonomous robots in the robotic soccer domain, to overcome the uncertainties in the sensors, environment and the motion model. r-mcl is a hybrid method based on markov localization (ml) and monte carlo localization (mcl), where the ml based module finds the region where the robot should be and the mcl based part predicts the geometrical location with high precision by selecting samples in this region. it is called reverse since the mcl routine is applied in a reverse manner in this algorithm. in this work, this method is tested on a challenging data set that is used by many other researchers and compared in terms of error rate against different levels of noise, and sparsity. additionally, the time required to recover from kidnapping and the processing time of the methods are tested and compared. according to the test results r-mcl is a considerable method against high sparsity and noise. it is preferable when its recovery from kidnapping and processing times are considered. it gives robust and fast but relatively coarse position estimations against imprecise and inadequate perceptions, and coarse action data, including regular misplacements, and false perceptions.
from images to rooms. in this paper we start from a set of images obtained by the robot that is moving around in an environment. we present a method to automatically group the images into groups that correspond to convex subspaces in the environment which are related to the human concept of rooms. pairwise similarities between the images are computed using local features extracted from the images and geometric constraints. the images with the proposed similarity measure can be seen as a graph or in a way as a base level dense topological map. from this low level representation the images are grouped using a graph-clustering technique which effectively finds convex spaces in the environment. the method is tested and evaluated on challenging data sets acquired in real home environments. the resulting higher level maps are compared with the maps humans made based on the same data.
automatic surface roughing with 3d machine vision and cooperative robot control. this paper presents an innovative and practical strategy for automated leather surface roughing, using structured light 3d machine vision for object profile perception, and nurbs interpolation for accurate and smooth trajectory generation. as high pressure grit blasting is used for roughing, considering the spacial constraints in the blasting chamber, an additional degree of freedom is introduced using a rotary table, which supports the workpiece. cooperative control is implemented between a 6-dof robot and the rotary table to minimize robot movements, while satisfying the requirements of variable velocity control, accurate trajectory tracking and orientation control. experimental results of consistent roughing performance have shown the efficiency of the proposed method.
robot team coordination for target tracking using fuzzy logic controller in game theoretic framework. this paper involves a collision free target tracking problem of multi-agent robot system. target tracking requires team coordination to maintain a desired formation and to keep team-mates and target together. every team-mate makes decisions on their moving direction that may spoil the tactical position of others and makes the global coordination task nontrivial. the contribution of the paper is twofold. first, the convergence of target tracking is improved by a new game theoretic concept using a semi-cooperative stackelberg equilibrium point and a new formation component in the individual cost functions. to enhance the robustness, a pd like fuzzy controller tunes the cost function weights directly for the game theoretic solution and helps to achieve a prescribed value of cost function components. simulation result for target tracking by a three-member robot team is presented.
uncalibrated visual servoing using the fundamental matrix. this paper describes a new algorithm for visual control of an uncalibrated 3 dof joint system, using two weakly calibrated fixed cameras. the algorithm estimates on-line the image jacobian, a matrix which linearly relates joint velocity and image feature velocity. in our experiments we prove that by using the fundamental matrix, robustness of the estimation in the presence of noise is significantly increased with respect to already existing algorithms in specialized literature.
adaptive visual gesture recognition for human-robot interaction using a knowledge-based software platform. in human-human communication we can adapt or learn new gestures or new users using intelligence and contextual information. achieving natural gesture-based interaction between humans and robots, the system should be adaptable to new users, gestures and robot behaviors. this paper presents an adaptive visual gesture recognition method for human-robot interaction using a knowledge-based software platform. the system is capable of recognizing users, static gestures comprised of the face and hand poses, and dynamic gestures of face in motion. the system learns new users, poses using multi-cluster approach, and combines computer vision and knowledge-based approaches in order to adapt to new users, gestures and robot behaviors. in the proposed method, a frame-based knowledge model is defined for the person-centric gesture interpretation and human-robot interaction. it is implemented using the frame-based software platform for agent and knowledge management (spak). the effectiveness of this method has been demonstrated by an experimental human-robot interaction system using a humanoid robot 'robovie'.
formation optimization for a fleet of wheeled mobile robots - a geometric approach. tight formation-based operations are critical in several emerging applications for robot collectives - ranging from cooperative payload transport to synchronized distributed data-collection. in this paper, we investigate the optimal relative layout for members of a team of differentially-driven wheeled mobile robots (dd-wmrs) moving in formation for ultimate deployment in cooperative payload transport tasks. our particular focus is on modeling such formations, developing the motion plans and determining the ''best formation'' in a differential-geometric setting. specifically, a preferred team-fixed frame serves as a virtual leader inducing motion plans for the individual dd-wmrs which form the vertices of a virtual structure. the resulting motion plans for the dd-wmrs as well as overall team-performance depend both on the specifiedteam-frame motions as well as their relative-layout within the formation. emphasis is placed on developing suitable invariant (yet quantitative) measures of formation quality and a systematic optimization-based selection of the formation-layout. the use of relative formation-parameterization with respect to a team-frame serves to decouple the team-level optimal layout selection process. the optimal location of each dd-wmr can now be found with respect to the team-frame individually and the feasibility of distributed implementation facilitates scaling to larger-sized formations. analytical and numerical results, from case studies of formation optimization of three dd-wmrs maneuvering along certain desired planar paths, are presented to highlight the salient features and benefits.
velocity planning for a mobile robot to track a moving target - a potential field approach. potential field method has been widely used for mobile robot path planning, but mostly in a static environment where the target and the obstacles are stationary. the path planning result is normally the direction of the robot motion. in this paper, the potential field method is applied for both path and speed planning, or the velocity planning, for a mobile robot in a dynamic environment where the target and the obstacles are moving. the robot's planned velocity is determined by relative velocities as well as relative positions among robot, obstacles and targets. the implementation factors such as maximum linear and angular speed of the robot are also considered. the proposed approach guarantees that the robot tracks the moving target while avoiding moving obstacles. simulation studies are provided to verify the effectiveness of the proposed approach.
from omnidirectional images to hierarchical localization. we propose a new vision-based method for global robot localization using an omnidirectional camera. topological and metric localization information are combined in an efficient, hierarchical process, with each step being more complex and accurate than the previous one but evaluating fewer images. this allows us to work with large reference image sets in a reasonable amount of time. simultaneously, thanks to the use of 1d three-view geometry, accurate metric localization can be achieved based on just a small number of nearby reference images. owing to the wide baseline features used, the method deals well with illumination changes and occlusions, while keeping the computational load small. the simplicity of the radial line features used speeds up the process without affecting the accuracy too much. we show experiments with two omnidirectional image data sets to evaluate the performance of the method and compare the results using the proposed radial lines with results from state-of-the-art wide-baseline matching techniques.
development of intelligent multisensor surveillance systems with agents. intelligent multisensor surveillance systems consist of several types of sensors, which are installed on fixed and mobile devices. these components provide a huge quantity of information that has to be contrasted, correlated and integrated in order to recognize and react on special situations. these systems work in highly dynamic environments, with severe security and robustness requirements. all these characteristics imply the need for distributed solutions. in these solutions, scattered components can decide and act with some degree of autonomy (for instance, if they become isolated), or cooperate and coordinate for a complete tracking of special situations. in order to cope with these requirements and to better structure the solution, we have decided to design surveillance system control as a multiagent system. this is done by applying an agent-orientated methodology, which is assessed with concrete scenarios.
a multi-agent architecture with cooperative fuzzy control for a mobile robot. the challenges of robotics have led the researchers to develop control architectures composed of distributed, independent and asynchronous behaviors. one way to approach decentralization is through cooperative control, since it allows the development of complex behavior based on several controllers combined to achieve the desired result. robots, however, require high-level cognitive capacities, and multi-agent architectures provide the appropriate level of abstraction to define them. this article describes a multi-agent architecture combined with cooperative control developed within the agent. the experiments were carried out on an activmedia pioneer 2dx mobile robot.
the centre of area method as a basic mechanism for representation and navigation. potential methods and all their gradient-based derivations are extensively used in autonomous robotics, primarily in association with reactive navigational strategies. in this article we introduce the fundamentals, formalisation and application of a brand-new method based on first-order moments called the ''centre of area method''. we also comment on its validity, at an individual level and in combination with other methods, in order to build a situated representation of the environment.
symbol grounding through robotic manipulation in cognitive systems. though proposals have been put forth to solve the classical symbol grounding problem through robotic sensorimotor interactions, only little progress has been made in this direction with actual working systems, and symbol grounding through physical interaction has been rarely dealt with. we address this problem in the context of robotic manipulation for cognitive systems, and claim that there are symbols which do not refer simply to physical objects but rather to the embodied interactions between the robot and the objects in its environment. through the description of two manipulation experiments we offer a proposal on which to build a theory of symbolic representations for physical interactions. some important neuroscience studies that support our view are also briefly described.
localization of legged robots combining a fuzzy-markov method and a population of extended kalman filters. this paper presents a new approach to robot vision-based self-localization in dynamic and noisy environments for legged robots when efficiency is a strong requirement. the major contribution of this paper is the improvement of a markovian method based on a fuzzy occupancy grid (fmk). our proposal combines fmk with a population of extended kalman filters, making the complete algorithm both robust and accurate while keeping its computational cost bounded. two different strategies have been designed to combine both the methods. they have been tested in the robocup environment and quantitatively compared with other approaches in several experiments with the real robot.
from bio-inspired vs. psycho-inspired to etho-inspired robots. artificial intelligence has been roughly divided into two schools of thought since its beginnings, the symbolic (also known as gofai, neat, classical, etc.) and the subsymbolic one (connectionist, scruffy, etc.). these two approaches have also had strong influence on the robotics field. in this paper we want to present a less known one, based on ethology, and its application to the generation of autonomous behavior in mobile robots. in this way, we present the foundations of jde (jerarquia dinamica de esquemas), an etho-inspired architecture where behavior is organized as a dynamic hierarchy of independent schemas, as well as some examples of its applications, and a discussion about its properties.
globally consistent 3d mapping with scan matching. a globally consistent solution to the simultaneous localization and mapping (slam) problem in 2d with three degrees of freedom (dof) poses was presented by lu and milios [f. lu, e. milios, globally consistent range scan alignment for environment mapping, autonomous robots 4 (april) (1997) 333-349]. to create maps suitable for natural environments it is however necessary to consider the 6dof pose case, namely the three cartesian coordinates and the roll, pitch and yaw angles. this article describes the extension of the proposed algorithm to deal with these additional dofs and the resulting non-linearities. simplifications using taylor expansion and cholesky decomposition yield a fast application that handles the massive amount of 3d data and the computational requirements due to the 6dof. our experiments demonstrate the functionality of estimating the exact poses and their covariances in all 6dof, leading to a globally consistent map. the correspondences between scans are found automatically by use of a simple distance heuristic.
researching and developing a real-time infrastructure for intelligent systems - evolution of an integrated approach. in this paper, we describe the principles and the methodologies that we have researched for the creation of a software infrastructure for bridging the gap from brain-like systems design to standard software technology. looking at the brain, we constantly take inspiration and choose the relevant principles that our computer-base model should/could be based on. this ranges from the evolution of the brain (phylogenetically and ontogenetically), the inherent autonomy of the currently identified areas, the intrinsic synchronization through the most basic control mechanisms that regulates interaction, communication, and modulation. with these principles in mind, we started to make a subdivision of our system into instance, functional and computing architecture, modeling each sub-system with processes and tools in order to create a basic infrastructure that supports the research and creation of intelligent systems. the basic elements of our infrastructure are the bbcm (brain bytes component model) and bbdm (brain bytes data model), created to enable the modularization and reuse of our systems. based on those, we have developed dtbos (design tool for brain operating system), the design environment for supporting graphical design, rtbos (real-time brain operating system), the middleware that supports real-time execution of our modular systems, and cmbos (control-monitor brain operating system) to enable the monitoring of running modules. we will show the feasibility of the established environment by shortly describing some of the experimental systems in the area of cognitive robotics that we have created. this will serve to give a more concrete understanding of the dimensions and the type of systems that we have been able to create.
appearance-based localization for mobile robots using digital zoom and visual compass. this paper describes a localization system for mobile robots moving in dynamic indoor environments, which uses probabilistic integration of visual appearance and odometry information. the approach is based on a novel image matching algorithm for appearance-based place recognition that integrates digital zooming, to extend the area of application, and a visual compass. ambiguous information used for recognizing places is resolved with multiple hypothesis tracking and a selection procedure inspired by markov localization. this enables the system to deal with perceptual aliasing or absence of reliable sensor data. it has been implemented on a robot operating in an office scenario and the robustness of the approach is demonstrated experimentally.
toward humanoid manipulation in human-centred environments. in order for humanoid robots to enter human-centred environments, it is indispensable to equip them with manipulative, perceptive and communicative skills necessary for real-time interaction with the environment and humans. the goal of our work is to provide reliable and highly integrated humanoid platforms which on the one hand allow the implementation and tests of various research activities and on the other hand the realization of service tasks in a household scenario. in this paper, we present a new humanoid robot currently being developed for applications in human-centred environments. in addition, we present an integrated grasping and manipulation system consisting of a motion planner for the generation of collision-free paths and a vision system for the recognition and localization of a subset of household objects as well as a grasp analysis component which provides the most feasible grasp configurations for each object.
biped robot design powered by antagonistic pneumatic actuators for multi-modal locomotion. an antagonistic muscle mechanism that regulates joint compliance contributes enormously to human dynamic locomotion. antagonism is considered to be the key for realizing more than one locomotion mode. in this paper, we demonstrate how antagonistic pneumatic actuators can be utilized to achieve three dynamic locomotion modes (walking, jumping, and running) in a biped robot. firstly, we discuss the contribution of joint compliance to dynamic locomotion, which highlights the importance of tunable compliance. secondly, we introduce the design of a biped robot powered by antagonistic pneumatic actuators. lastly, we apply simple feedforward controllers for realizing walking, jumping, and running and confirm the contribution of joint compliance to such multimodal dynamic locomotion. based on the results, we can conclude that the antagonistic pneumatic actuators are superior candidates for constructing a human-like dynamic locomotor.
towards long-lived robot genes. robot projects are often evolutionary dead ends, with the software and hardware they produce disappearing without trace afterwards. in humanoid robotics, a small field with an avid appetite for novel devices, we experience a great deal of ''churn'' of this nature. in this paper, we explore how best to make our projects stable and long-lasting, without compromising our ability to constantly change our sensors, actuators, processors and networks. we also look at how to encourage the propagation and evolution of hardware designs, so that we can start to build up a ''gene-pool'' of material to draw upon for new projects. we advance on two fronts, software and hardware. for some time, we have been developing and using the yarp robot software architecture [giorgio metta, paul fitzpatrick, lorenzo natale, yarp: yet another robot platform, international journal on advanced robotics systems 3 (2006) 43-48], which helps organize communication between sensors, processors, and actuators so that loose coupling is encouraged, making gradual system evolution much easier. yarp includes a model of communication that is transport-neutral, so that data flow is decoupled from the details of the underlying networks and protocols in use. importantly for the long term, yarp is designed to play well with other architectures. device drivers written for yarp can be ripped out and used without any ''middleware''. on the network, basic interoperation is possible with a few lines of code in any language with a socket library, and maximally efficient interoperation can be achieved by following documented protocols. these features are not normally the first things that end-users look for when starting a project, but they are crucial for longevity. we emphasize the strategic utility of the free software social contract [b. perens, the open source definition, in: chris dibona, sam ockman, mark stone (eds.), open sources: voices from the open source revolution, o'reilly and associates, cambridge, ma, 1999] to software development for small communities with idiosyncratic requirements. we also work to expand our community by releasing the design of our icub humanoid [n.g. tsagarakis, g. metta, g. sandini, d. vernon, r. beira, f. becchi, l. righetti, j. santos-victor, a.j. ijspeert, m.c. carrozza, d.g. caldwell, icub - the design and realization of an open humanoid platform for cognitive and neuroscience research, journal of advanced robotics 21 (10) (2007) 1151-1175] under a free and open licence, and funding development using this platform.
from schemas to neural networks: a multi-level modelling approach to biologically-inspired autonomous robotic systems. biology has been an important source of inspiration in building adaptive autonomous robotic systems. due to the inherent complexity of these models, most biologically-inspired robotic systems tend to be ethological without linkage to underlying neural circuitry. yet, neural mechanisms are crucial in modelling adaptation and learning. the work presented in this paper describes a schema and neural network multi-level modelling approach to biologically inspired autonomous robotic systems. a prey acquisition model with detour behaviour in frogs is presented to exemplify the modelling approach. the model is tested with simulated and physical robots using the asl/nsl and miro robotic system.
sensor fusion-based visual target tracking for autonomous vehicles with the out-of-sequence measurements solution. in this paper, a novel algorithm is proposed for the visual target tracking by autonomous guide vehicles (agv). this paper proposes a sensor data fusion system to estimate the dynamics of the target. optical flow vectors, colour features, stereo pair disparities are used as the visual features while the vehicle's inertial measurements are used to estimate the stereo cameras' motion. the algorithm estimates the velocity and position of the target which is then used by the vehicle to track the target. in this sensor data fusion-based tracking system, the measurements from the same target can arrive out of sequence. this is called the ''out-of-sequence'' measurements (oosm) problem. thus the resulting problem - how to update the current state estimate with an ''older'' measurement - needs to be solved. in this paper the 1-step-lag oosm solution from bar-shalom is applied for the extended kalman filter-based target-state estimation. the performance of the proposed tracking algorithm with the oosm solution is demonstrated through extensive experimental results.
recognition of in-hand manipulation using contact state transition for multifingered robot hand control. this paper proposes a method for recognizing in-hand manipulation of the operator by observing a contact state transition between an object and the human hand. an instrumented object with a pressure distribution sensor and a position/orientation sensor has been developed. by processing information from the sensors, the contact regions on the operator's palm surface are detected. a contact state transition diagram is created by taking practical contact states into account. a recognition algorithm based on dynamic programming (dp) is proposed to recognize the type of in-hand manipulation by comparing the similarity of the contact state transition between an input sequence and template manipulation primitives. the validity of the proposed method is confirmed by experiments.
a combined stochastic and greedy hybrid estimation capability for concurrent hybrid models with autonomous mode transitions. probabilistic hybrid discrete/continuous models, such as concurrent probabilistic hybrid automata (cpha) are convenient tools for modeling complex robotic systems. in this paper, we present a novel method for estimating the hybrid state of cpha that achieves robustness by balancing greedy and stochastic search. to accomplish this, we (1) develop an efficient stochastic sampling approach for cpha based on rao-blackwellised particle filtering, (2) perform an empirical comparison of the greedy and stochastic approaches to hybrid estimation and (3) propose a strategy for mixing stochastic and greedy search. the resulting method handles nonlinear dynamics, concurrently operating components and autonomous mode transitions. we demonstrate the robustness of the mixed method empirically.
hardware design of high performance miniature anthropomorphic robots. technical issues in designing reliable high-performance miniature humanoid robots are discussed. although the light-weight and small-size body of such a humanoid robot facilitates safer and smoother experiments of agile motions involving large accelerations and impacts, building a complex humanoid system in a small body is still a challenging problem. simultaneous requirements for wider motion ranges, higher rigidity, less fragile electric devices and circuits, and less sensitive electric wiring should be satisfied in a limited space. in order to meet them by overcoming the difficulties, we propose to mechanically modularize joint structures, and to equip a centralized electric control unit involving pc boards, sensing devices, signal-processors, communication boards, and power amplifiers. the developments of the mechanical modules and the centralized unit are made for two miniature humanoid robots.
control hardware integration of a biped humanoid robot with an android head. the kaist hubo team and the hanson robotics team jointly developed an android-type humanoid robot termed albert hubo, which may be the world's first robot that incorporates an expressive human face on a walking biped robot. albert hubo adopts the techniques of the hubo design for the body of albert hubo and uses technology from hanson robotics for the head. the head and the body are two independent systems that use different computers to control each system. the head uses rc servo motors for facial expressions. it is controlled using a pc that utilizes rs232 communication. the head pc also processes vocal and visual information. the body (including the arms, fingers, legs, and torso) pc controls walking and body movements. it is connected via can communication to body servo controllers. the pcs are connected by rs232, which is able to transfer command data to each system. the height and weight of albert hubo are 137 cm and 57 kg, respectively. the robot has 66 dofs (31 for the head motions and 35 for the body motions). the head part uses a material known as 'frubber', which serves as a smooth human-like skin. in the head, 28 servo motors for facial movements and three servo motors for neck movements are used to generate a full range of facial expressions; thus, the robot is able to laugh, act surprised, and express sadness or anger. the body is modified from hubo (khr-3), which was introduced in 2004, and is joined with the head of albert hubo with 35 dc motors that are embedded for the purpose of imitating various human-like body motions. the biped humanoid robot with a human-like android head was realized by integrating two independent systems as a self-contained robotic system. the integration of the two systems is in the topic of this paper.
when hard realtime matters: software for complex mechatronic systems. a still growing number of software concepts and frameworks have been proposed to meet the challenges in the development of more and more complex robotic systems, like humanoids or networked robotics. the issue of hard realtime, however, has not been the main focus of such concepts, but is essential for building and controlling mechatronic systems. here we discuss the specific demands of complex mechatronic systems and present a software concept, the ''agile robot development'' (ard) concept, which we developed at our institute to pragmatically address these demands. we show that the performance of current computing and communication hardware allows for a flexible component-based concept with distributed execution, even in hard realtime with rates in the khz range.
theoretical foundations for rendezvous of glowworm-inspired agent swarms at multiple locations. we present theoretical foundations for a variation of the multi-agent rendezvous problem involving design of local control strategies that enable agent swarms, with hard-limited sensing ranges, to split into disjoint subgroups, exhibit simultaneous taxis behavior toward, and eventually rendezvous at, multiple unknown locations of interest. the algorithm used to solve the above problem is based on a glowworm swarm optimization (gso) technique, developed earlier, that finds multiple optima of multi-modal objective functions. we characterize the various phases of the algorithm that help us to develop a theoretical framework required for analysis. in particular, we show through simulations that the implementation of the gso algorithm at the individual agent level gives rise to two major phases at the group level-splitting of the agent-swarm into subgroups and local convergence of agents in each subgroup to the peak locations. we provide local convergence results under certain restricted set of assumptions, leading to a simplified model of the algorithm, making it amenable to analysis, while still reflecting most of the features of the original algorithm. in particular, we find an upper bound on the time taken by the agents to converge to an isolated leader and on the time taken by the agents to converge to one of the leaders with non-isolated and non-overlapping neighborhoods. finally, we show that agents under the influence of multiple leaders with overlapping neighborhoods asymptotically converge to one of the leaders. we present some illustrative simulations to support the theoretical findings of the paper.
conflict-free container routing in mesh yard layouts. container terminals play an important role in global cargo transportation and they have become an essential intermodal interface between the sea and the land. in the container terminal, the service area is often arranged into rectangular blocks, which leads to a mesh-like path topology. we present a mathematical model for general container routing in mesh yard layouts. based on this model, a simple container routing algorithm guaranteeing freedom of conflicts is then presented. the algorithm works by carefully choosing suitable containers' speeds such that the containers using the same junction will arrive at different points in time, and hence incur no conflicts; meanwhile, high routing performance can be achieved. the task completion time and the requirements on timing control during the container routing are also presented. numerical results verify that our routing scheme has good performance and is free of conflicts.
a dialogue approach to learning object descriptions and semantic categories. acquiring new knowledge through interactive learning mechanisms is a key ability for humanoid robots in a natural environment. such learning mechanisms need to be performed autonomously, and through interaction with the environment or with other agents/humans. in this paper, we describe a dialogue approach and a dynamic object model for learning semantic categories, object descriptions, and new words acquisition for object learning and integration with visual perception for grounding objects in the real world. the presented system has been implemented and evaluated on the humanoid robot armar iii.
bio-mimetic impedance control of robotic manipulator for dynamic contact tasks. a human performs a variety of skillful movements by adjusting dynamic characteristics of his or her musculoskeletal system according to a task involved. such characteristics of human movements can be described by mechanical impedance parameters. if the regulation mechanism of human impedance properties during the task can be clarified and modeled, there is a possibility that human skillful strategies can be integrated into robot motion control. this paper investigates human hand impedance in preparation for task operations, the so-called ''task-readiness impedance'', in a virtual ball-catching task. it further discusses a bio-mimetic impedance control of robotic manipulators for contact tasks via computer simulations using measured task-readiness impedance.
what can be done with an embedded stereo-rig in urban environments? the development of the autonomous guided vehicles (agvs) with urban applications are now possible due to the recent solutions (darpa grand challenge) developed to solve the simultaneous localization and mapping (slam) problem: perception, path planning and control. for the last decade, the introduction of gps systems and vision have been allowed the transposition of slam methods dedicated to indoor environments to outdoor ones. when the gps data are unavailable, the current position of the mobile robot can be estimated by the fusion of data from odometer and/or inertial navigation system (ins). we detail in this article what can be done with an uncalibrated stereo-rig, when it is embedded in a vehicle which is going through urban roads. the methodology is based on features extracted on planes: we mainly assume the road at the foreground as the plane common to all the urban scenes but other planes like vertical frontages of buildings can be used if the features extracted on the road are not enough relevant. the relative motions of the coplanar features tracked with both cameras allow us to estimate the vehicle ego-motion with a high precision. futhermore, the features which don't check the relative motion of the considered plane can be assumed as obstacles.
towards semantic maps for mobile robots. intelligent autonomous action in ordinary environments calls for maps. 3d geometry is generally required for avoiding collision with complex obstacles and to self-localize in six degrees of freedom (6 dof) (x, y, z positions, roll, yaw, and pitch angles). meaning, in addition to geometry, becomes inevitable if the robot is supposed to interact with its environment in a goal-directed way. a semantic stance enables the robot to reason about objects; it helps disambiguate or round off sensor data; and the robot knowledge becomes reviewable and communicable. the paper describes an approach and an integrated robot system for semantic mapping. the prime sensor is a 3d laser scanner. individual scans are registered into a coherent 3d geometry map by 6d slam. coarse scene features (e.g., walls, floors in a building) are determined by semantic labeling. more delicate objects are then detected by a trained classifier and localized. in the end, the semantic maps can be visualized for human inspection. we sketch the overall architecture of the approach, explain the respective steps and their underlying algorithms, give examples based on a working robot implementation, and discuss the findings.
solving the potential field local minimum problem using internal agent states. we propose a new, extended artificial potential field method, which uses dynamic internal agent states. the internal states are modeled as a dynamical system of coupled first order differential equations that manipulate the potential field in which the agent is situated. the internal state dynamics are forced by the interaction of the agent with the external environment. local equilibria in the potential field are then manipulated by the internal states and transformed from stable equilibria to unstable equilibria, allowing escape from local minima in the potential field. this new methodology successfully solves reactive path planning problems, such as a complex maze with multiple local minima, which cannot be solved using conventional static potential fields.
combining declarative, procedural, and predictive knowledge to generate, execute, and optimize robot plans. one of the main challenges in motor control is expressing high-level goals in terms of low-level actions. to do so effectively, motor control systems must reason about actions at different levels of abstraction. grounding high-level plans in low-level actions is essential semantic knowledge for plan-based control of real robots. we present a robot control system that uses declarative, procedural and predictive knowledge to generate, execute and optimize plans. declarative knowledge is represented in pddl, durative actions constitute procedural knowledge, and predictive knowledge is learned by observing action executions. we demonstrate how learned predictive knowledge enables robots to autonomously optimize plan execution with respect to execution duration and robustness in real-time. the approach is evaluated in two different robotic domains.
path planning for laser scanning with an industrial robot. reverse engineering is concerned with the problem of creating cad models of real objects by measuring point data from their surfaces. current solutions either require manual interaction or expect the nature of the objects to be known. we believe that in order to create a fully automatic system for re of unknown objects the software that creates the cad-model should be able to control the operation of the measuring system. this paper is based on a real implementation of a measuring system controlled by cad software, capable of measuring along curved paths. some details of the system have been described in earlier publications. this paper is concerned with the problem of automatic path planning for a system that can move along curved paths.
motion intention recognition in robot assisted applications. acquiring, representing and modelling human skills is one of the key research areas in teleoperation, programming-by-demonstration and human-machine collaborative settings. the problems are challenging mainly because of the lack of a general mathematical model to describe human skills. one of the common approaches is to divide the task that the operator is executing into several subtasks or low-level subsystems in order to provide manageable modelling. in this paper we consider the use of a layered hidden markov model (lhmm) to model human skills. we evaluate a gesteme classifier that classifies motions into basic action-primitives, or gestemes. the gesteme classifiers are then used in a lhmm to model a teleoperated task. the proposed methodology uses three different hmm models at the gesteme level: one-dimensional hmm, multi-dimensional hmm and multi-dimensional hmm with fourier transform. the online and off-line classification performance of these three models is evaluated with respect to the number of gestemes, the influence of the number of training samples, the effect of noise and the effect of the number of observation symbols. we also apply the lhmm to data recorded during the execution of a trajectory tracking task in 2d and 3d with a mobile manipulator in order to provide qualitative as well as quantitative results for the proposed approach. the results indicate that the lhmm is suitable for modelling teleoperative trajectory-tracking tasks and that the difference in classification performance between one and multidimensional hmms for gesteme classification is small. it can also be seen that the lhmm is robust with respect to misclassifications in the underlying gesteme classifiers.
a visual 3d-tracking and positioning technique for stereotaxy with ct scanners. in this paper, we present a 3d-tracking technique inspired by visual servoing, specifically designed for computed tomography (ct). this work has been developed within the framework of robot- and computer-assisted interventional radiology, using stereotactic external fiducials made of radiopaque rods. these fiducials produce a set of image feature points that are used in a pose estimation algorithm, with only one slice. the patient's movements can then be tracked with the proposed algorithm by means of a motion field approach, so as to update the 2d/3d registration. therefore, the proposed method solves a fundamental safety issue associated to the robotic assistance of ct-guided interventions. the contributions of the paper are threefold. first, the stereotactic visual feedback is modelled using the plucker representation for 3d straight lines, while the ct plane slice provides corresponding image points. it is shown that the number of features needed to compute the pose is minimal compared to the known previous techniques. second, the jacobian matrix which relates the image points displacements to the velocity screw of the stereotactic frame is computed, providing the ct motion field. third, the update of the jacobian matrix is investigated. it requires the on-line stereotactic registration. as with the ct imaging modality, the 2d/3d registration is highly inaccurate when the fiducials are being moving, this paper provides a ct visual 3d tracking method inspired by the image-based visual servoing, which may alleviate the jacobian matrix updates. to validate this technique, we first present simulations of the ct visual tracking. finally, the proposed method is applied to real images obtained with stereotactic markers mounted on a robotic platform and placed in a ct scanner.
integration of planning and execution in force controlled compliant motion. this paper presents the compliant task generator, a new approach for the automatic conversion of a geometrical contact path into a force-based task specification. a contact path planner generates a sequence of six-dimensional poses and corresponding contact formations, while a hybrid robot controller expects a desired wrench, twist and the local wrench and twist subspaces. our approach automatically converts a geometrical path description into a force based tasks specification for the hybrid controller, based on a user specified input of the magnitudes and the norms of the desired contact force and execution speed. the approach applies to all contact motions between known polyhedral objects, and is verified in real world experiments.
two-phase discontinuous gaits for quadruped walking machines with a failed leg. a fault-tolerant gait of multi-legged robots with static walking is a gait which can maintain gait stability and continue its walking against an occurrence of a leg failure. this paper proposes two-phase discontinuous gaits as a new fault-tolerant gait for quadruped robots suffering from a locked joint failure, which prevents a joint of a leg from moving and makes it locked in a known place. by comparing with previously developed one-phase discontinuous gaits, it is shown that the proposed gait has great advantages in gait performance such as the stride length and terrain adaptability. as an application of the proposed gait, the gait algorithm for ditch crossing and avoidance of quadruped robots with a failed leg is presented and illustrated by simulated figures.
logic-based robot control in highly dynamic domains. in this paper, we present the robot programming and planning language readylog, a golog dialect, which was developed to support the decision making of robots acting in dynamic real-time domains, such as robotic soccer. the formal framework of readylog, which is based on the situation calculus, features imperative control structures such as loops and procedures, allows for decision-theoretic planning, and accounts for a continuously changing world. we developed high-level controllers in readylog for our soccer robots in robocup's middle-size league, but also for service robots and for autonomous agents in interactive computer games. for a successful deployment of readylog on a real robot it is also important to account for the control problem as a whole, integrating the low-level control of the robot (such as localization, navigation, and object recognition) with the logic-based high-level control. in doing so, our approach can be seen as a step towards bridging the gap between the fields of robotics and knowledge representation.
an interactive tool for mobile robot motion planning. this paper presents an interactive tool aimed at facilitating the understanding of several well-known algorithms and techniques involved in solving mobile robot motion problems. these range from those modelling the mechanics of mobility to those used in navigation. the tool focuses on describing these problems in a simple manner in order to be useful for education purposes among different disciplines. by highlighting interactivity, the tool provides a novel means to study robot motion planning ideas in a manner that enhances full understanding. furthermore, the paper discuses how the tool can be used in an introductory course of mobile robotics.
action evaluation for mobile robot global localization in cooperative environments. this work is about solving the global localization issue for mobile robots, operating in large and cooperative environments. it tackles the problem of estimating the pose of a robot, or team of robots in a map reference frame, given the map, the real-time data from the robot onboard sensors, and the real-time data coming from other robots or sensors in the environment. after a first step of position hypotheses generation, an efficient probabilistic active strategy selects an action, for a single lost robot case, or two joint actions when two lost robots are in a line of sight, so that the hypotheses set is best disambiguated. the action set is adapted to the multi-hypothesis situation, and action evaluation takes into account remote observations available in robot network systems. this paper presents the theoretical formulation for both non-cooperative, and cooperative cases. an implementation of the proposed strategy is discussed, and simulation results presented.
location of legged robots in outdoor environments. knowledge of a robot's position with an accuracy of within a few centimeters is required for potential applications for legged robots, such as humanitarian de-mining tasks. individual sensors are unable to provide such accuracy. thus information from various sources must be used to accomplish the tasks. following this trend, this paper describes the method developed for estimating the position of legged robots in outdoor environments. the proposed method factors in the specific features of legged robots and combines dead-reckoning estimation with data provided by a differential global positioning system through an extended kalman filter algorithm. this localization system permits accurate trajectory tracking of legged robots during critical activities such as humanitarian de-mining tasks. preliminary experiments carried out with the silo4 system have shown adequate performance using this localization system.
free gait generation with reinforcement learning for a six-legged robot. in this paper the problem of free gait generation and adaptability with reinforcement learning are addressed for a six-legged robot. using the developed free gait generation algorithm the robot maintains to generate stable gaits according to the commanded velocity. the reinforcement learning scheme incorporated into the free gait generation makes the robot choose more stable states and develop a continuous walking pattern with a larger average stability margin. while walking in normal conditions with no external effects causing unstability, the robot is guaranteed to have stable walk, and the reinforcement learning only improves the stability. the adaptability of the learning scheme is tested also for the abnormal case of deficiency in one of the rear-legs. the robot gets a negative reinforcement when it falls, and a positive reinforcement when a stable transition is achieved. in this way the robot learns to achieve a continuous pattern of stable walk with five legs. the developed free gait generation with reinforcement learning is applied in real-time on the actual robot both for normal walking with different speeds and learning of five-legged walking in the abnormal case.
a sensor fusion framework for online sensor and algorithm selection. this paper presents a sensor fusion framework for selecting online the most reliable logical sensors and the most suitable algorithm for fusing sensor data in a robot platform. the framework is rule-based, employing the concept of using the simplest sensor fusion algorithm with the most reliable sensors. the framework is realized by implementing measures that were developed to quantify online sensor performance. statistical, histogram, time series and graphical analyses demonstrate the advantages of this new framework.
constructing dependable certainty grids from unreliable sensor data. measurements from sensors as they are used for robotic grid map applications typically show behavior like degradation or discalibration over time, which affects the quality of the generated maps. this paper presents two novel algorithms for the generation of certainty grids dealing with this behavior. the first algorithm named fault-tolerant certainty grid (ftcg) performs voting over multiple sensor readings. this approach removes up to (n-1)/2 faulty measurements for grid cells that are updated by n independent sensors, however it requires that each grid cell is covered by at least three different independent sensors. the second algorithm named robust certainty grid (rcg) uses a sensor validation method that detects abnormal sensor measurements and adjusts a confidence value for each sensor. this method also supports reintegration of recovered sensors from transient faults and sensor maintenance by providing a measurement for the operability of a sensor. the rcg algorithm works with at least three sensors with a partially overlapping sensing range and needs fewer sensor inputs and less memory than the ftcg approach. results from simulation and an experimental evaluation on an autonomous mobile robot show that under the presence of unreliable sensor data, both algorithms perform better than the bayesian approach typically used for certainty grids.
omni-directional mobile robot controller based on trajectory linearization. in this paper, a nonlinear controller design for an omni-directional mobile robot is presented. the robot controller consists of an outer-loop (kinematics) controller and an inner-loop (dynamics) controller, which are both designed using the trajectory linearization control (tlc) method based on a nonlinear robot dynamic model. the tlc controller design combines a nonlinear dynamic inversion and a linear time-varying regulator in a novel way, thereby achieving robust stability and performance along the trajectory without interpolating controller gains. a sensor fusion method, which combines the onboard sensor and the vision system data, is employed to provide accurate and reliable robot position and orientation measurements, thereby reducing the wheel slippage induced tracking error. a time-varying command filter is employed to reshape an abrupt command trajectory for control saturation avoidance. the real-time hardware-in-the-loop (hil) test results show that with a set of fixed controller design parameters, the tlc robot controller is able to follow a large class of 3-degrees-of-freedom (3dof) trajectory commands accurately.
network robot systems. this article introduces the definition of network robot systems (nrs) as is understood in europe, usa and japan. moreover, it describes some of the nrs projects in europe and japan and presents a summary of the papers of this special issue.
development of a 3dof mobile exoskeleton robot for human upper-limb motion assist. in order to assist physically disabled, injured, and/or elderly persons, we have been developing exoskeleton robots for assisting upper-limb motion, since upper-limb motion is involved in a lot of activities of everyday life. this paper proposes a mechanism and control method of a mobile exoskeleton robot for 3dof upper-limb motion assist (shoulder vertical and horizontal flexion/extension, and elbow flexion/extension motion assist). the exoskeleton robot is mainly controlled by the skin surface electromyogram (emg) signals, since emg signals of muscles directly reflect how the user intends to move. the force vector at the end-effector is taken into account to generate the natural and smooth hand trajectory of the user in the proposed control method. an obstacle avoidance algorithm is applied to prevent accidental collision between the user's upper-limb and the robot frame. the experiment was performed to evaluate the effectiveness of the proposed exoskeleton robot.
autonomous sailboat navigation for short course racing. the paper presents a compact method to calculate a suitable route for a sailboat in order to reach any specified target. the calculation is based on the optimisation of the time derivative of the distance between boat and target and features a hysteresis condition, which is of particular importance for beating to windward. the algorithm provides an answer to the perennial question when to tack on upwind courses. further, it immediately adapts to varying wind conditions. the resulting routes for different conditions are analysed on the basis of a simulation featuring a mathematical boat model. experiments have been carried out using an unmanned and autonomously controlled sailboat. the navigated route agrees well with the simulation results.
monitoring the execution of robot plans using semantic knowledge. even the best laid plans can fail, and robot plans executed in real world domains tend to do so often. the ability of a robot to reliably monitor the execution of plans and detect failures is essential to its performance and its autonomy. in this paper, we propose a technique to increase the reliability of monitoring symbolic robot plans. we use semantic domain knowledge to derive implicit expectations of the execution of actions in the plan, and then match these expectations against observations. we present two realizations of this approach: a crisp one, which assumes deterministic actions and reliable sensing, and uses a standard knowledge representation system (loom); and a probabilistic one, which takes into account uncertainty in action effects, in sensing, and in world states. we perform an extensive validation of these realizations through experiments performed both in simulation and on real robots.
robots in the kitchen: exploiting ubiquitous sensing and actuation. our goal is to develop intelligent service robots that operate in standard human environments, automating common tasks. in pursuit of this goal, we follow the ubiquitous robotics paradigm, in which intelligent perception and control, are combined with ubiquitous computing. by exploiting sensors and effectors in its environment, a robot can perform more complex tasks without becoming overly complex itself. following this insight, we have developed a service robot that operates autonomously in a sensor-equipped kitchen. the robot learns from demonstration, and performs sophisticated tasks, in concert with the network of devices in its environment. we report on the design, implementation, and usage of this system, which is freely available for use, and improvement by others, in the research community.
real-time tour construction for a mobile robot in a dynamic environment. mobile robots are increasingly used in many areas. an optimum trajectory increases the effectiveness of a mobile robot. however, the environment may change dynamically which may require a real-time tour construction for the mobile robot. in this study, a heuristic-based tsp approach is applied to real-time dynamic tour construction problem for a mobile robot. savings algorithm together with dijsktra's algorithm is used to determine a feasible tour for the mobile robot. the proposed method is applicable when the network is complete or sparse, directed or undirected. experiments are conducted to show the effectiveness of the proposed algorithm.
automated design of distributed control rules for the self-assembly of prespecified artificial structures. the self-assembly problem involves the design of agent-level control rules that will cause the agents to form some desired, target structure, subject to environmental constraints. this paper describes a fully automated rule generation procedure that allows structures to successfully self-assemble in a simulated environment with constrained, continuous motion. this environment implicitly imposes ordering constraints on the self-assembly process, where certain parts of the target structure must be assembled before others, and where it may be necessary to assemble (and subsequently disassemble) temporary structures such as staircases. a provably correct methodology is presented for computing a partial order on the self-assembly process, and for generating rules that enforce this order at runtime. the assembly and disassembly of structures is achieved by generating another set of rules, which are inspired by construction behavior among certain species of social insects. computational experiments verify the effectiveness of the approach on a diverse set of target structures.
bayesian space conceptualization and place classification for semantic maps in mobile robotics. the future of robots, as our companions is dependent on their ability to understand, interpret and represent the environment in a human compatible manner. towards this aim, this work attempts to create a hierarchical probabilistic concept-oriented representation of space, based on objects. specifically, it details efforts taken towards learning and generating concepts and attempts to classify places using the concepts gleaned. several algorithms, from naive ones using only object category presence to more sophisticated ones using both objects and relationships, are proposed. both learning and inference use the information encoded in the underlying representation-objects and relative spatial information between them. the approaches are based on learning from exemplars, clustering and the use of bayesian network classifiers. the approaches are generative. further, even though they are based on learning from exemplars, they are not ontology specific; i.e. they do not assume the use of any particular ontology. the presented algorithms rely on a robots inherent high-level feature extraction capability (object recognition and structural element extraction) capability to actually form concept models and infer them. thus, this report presents methods that could enable a robot to to link sensory information to increasingly abstract concepts (spatial constructs). such a conceptualization and the representation that results thereof would enable robots to be more cognizant of their surroundings and yet, compatible to us. experiments on conceptualization and place classification are reported. thus, the theme of this work is-conceptualization and classification for representation and spatial cognition.
rose - a framework for multicast communication via unreliable networks in multi-robot systems. multi-robot systems obtain their performance advantages from close collaboration of the participating robot systems. as the demand for such cooperation increases, the aspect of wireless communication is getting more and more important. to cope with the challenges of the wireless communication we propose an easy to use communication framework for a multi-robot system. this framework is designed for wireless networks, therefore it expects unreliable communication and can even cope with complete network separations. using multicast as the default communication scheme, the framework can directly benefit from the broadcast nature of the wireless medium if such an optimisation is supported by the lower network protocols. we therefore introduce our multicast capable wireless routing protocol, which supports this optimisation. the software is implemented and frequently used in our experimental multi-robot system.
fuzzy logic-based real-time robot navigation in unknown environment with dead ends. the proposed approach in this paper involves a new grid-based map model called ''memory grid'' and a new behavior-based navigation method called ''minimum risk method''. the memory grid map records not only the environmental information, but also the robot experience. the minimum risk method is just one of the applications of the memory grid technique, which addresses the local minimum problem faced by a goal-oriented robot navigating in unknown indoor environments. the minimum risk implies that the robot is able to choose the safest region that can avoid colliding with obstacles and prevent the robot from iterating previous trajectory. this method is demonstrated to work in long wall, large concave, recursive u-shaped, unstructured, cluttered, maze-like, and dynamic indoor environments. it adopts a strategy of multi-behavior coordination in which a novel path-searching behavior is developed to recommend the region offering the minimum risk. fuzzy logic is used to implement the behavior design and coordination. the proposed approach is verified with simulation and real-world tests.
depth control of remotely operated underwater vehicles using an adaptive fuzzy sliding mode controller. sliding mode control, due to its robustness against modelling imprecisions and external disturbances, has been successfully employed to the dynamic positioning of remotely operated underwater vehicles. in order to improve the performance of the complete system, the discontinuity in the control law must be smoothed out to avoid the undesirable chattering effects. the adoption of a properly designed thin boundary layer has proven effective in completely eliminating chattering, however, leading to an inferior tracking performance. this paper describes the development of a depth control system for remotely operated underwater vehicles. the adopted approach is based on the sliding mode control strategy and enhanced by an adaptive fuzzy algorithm for uncertainty/disturbance compensation. the stability and convergence properties of the closed-loop system are analytically proved using lyapunov stability theory and barbalat's lemma. numerical results are presented in order to demonstrate the control system performance.
conceptual spatial representations for indoor mobile robots. we present an approach for creating conceptual representations of human-made indoor environments using mobile robots. the concepts refer to spatial and functional properties of typical indoor environments. following different findings in spatial cognition, our model is composed of layers representing maps at different levels of abstraction. the complete system is integrated in a mobile robot endowed with laser and vision sensors for place and object recognition. the system also incorporates a linguistic framework that actively supports the map acquisition process, and which is used for situated dialogue. finally, we discuss the capabilities of the integrated system.
kinematic analysis of two novel 3upu i and 3upu ii pkms. two novel 3upu i and 3upu ii pkms (parallel kinematic machines) with two rotations and one translation are proposed, and their kinematics are studied systematically. first, the kinematic characteristics of the 3upu i and 3upu ii pkms are analyzed and the geometric constrained equations are derived. second, some analytic formulae are derived for solving inverse displacement, inverse/forward velocity and acceleration of the two pkms. third, the reachable workspaces of the two pkms are solved and analyzed. the analytic results are verified by their simulation mechanism.
curious george: an attentive semantic robot. state-of-the-art methods have recently achieved impressive performance for recognising the objects present in large databases of pre-collected images. there has been much less focus on building embodied systems that recognise objects present in the real world. this paper describes an intelligent system that attempts to perform robust object recognition in a realistic scenario, where a mobile robot moving through an environment must use the images collected from its camera directly to recognise objects. to perform successful recognition in this scenario, we have chosen a combination of techniques including a peripheral-foveal vision system, an attention system combining bottom-up visual saliency with structure from stereo, and a localisation and mapping technique. the result is a highly capable object recognition system that can be easily trained to locate the objects of interest in an environment, and subsequently build a spatial-semantic map of the region. this capability has been demonstrated during the semantic robot vision challenge, and is further illustrated with a demonstration of semantic mapping. we also empirically verify that the attention system outperforms an undirected approach even with a significantly lower number of foveations.
the initial development of object knowledge by a learning robot. we describe how a robot can develop knowledge of the objects in its environment directly from unsupervised sensorimotor experience. the object knowledge consists of multiple integrated representations: trackers that form spatio-temporal clusters of sensory experience, percepts that represent properties for the tracked objects, classes that support efficient generalization from past experience, and actions that reliably change object percepts. we evaluate how well this intrinsically acquired object knowledge can be used to solve externally specified tasks, including object recognition and achieving goals that require both planning and continuous control.
virtual sensors for human concepts - building detection by an outdoor mobile robot. in human-robot communication it is often important to relate robot sensor readings to concepts used by humans. we suggest the use of a virtual sensor (one or several physical sensors with a dedicated signal processing unit for the recognition of real world concepts) and a method with which the virtual sensor can learn from a set of generic features. the virtual sensor robustly establishes the link between sensor data and a particular human concept. in this work, we present a virtual sensor for building detection that uses vision and machine learning to classify the image content in a particular direction as representing buildings or non-buildings. the virtual sensor is trained on a diverse set of image data, using features extracted from grey level images. the features are based on edge orientation, the configurations of these edges, and on grey level clustering. to combine these features, the adaboost algorithm is applied. our experiments with an outdoor mobile robot show that the method is able to separate buildings from nature with a high classification rate, and to extrapolate well to images collected under different conditions. finally, the virtual sensor is applied on the mobile robot, combining its classifications of sub-images from a panoramic view with spatial information (in the form of location and orientation of the robot) in order to communicate the likely locations of buildings to a remote human operator.
sensor-driven neural control for omnidirectional locomotion and versatile reactive behaviors of walking machines. this article describes modular neural control structures for different walking machines utilizing discrete-time neurodynamics. a simple neural oscillator network serves as a central pattern generator producing the basic rhythmic leg movements. other modules, like the velocity regulating and the phase switching networks, enable the machines to perform omnidirectional walking as well as reactive behaviors, like obstacle avoidance and different types of tropisms. these behaviors are generated in a sensori-motor loop with respect to appropriate sensor inputs, to which a neural preprocessing is applied. the neuromodules presented are small so that their structure-function relationship can be analysed. the complete controller is general in the sense that it can be easily adapted to different types of even-legged walking machines without changing its internal structure and parameters.
reinforcement learning for problems with symmetrical restricted states. a reinforcement learning method is proposed that can utilize parts of states and their partial symmetries to solve a problem efficiently. in most cases the action selection does not need considering all the states but only needs looking at parts of states or restricted state of corresponding action. moreover, restricted states of different actions are symmetrical, and thus the action value function based on restricted states can be shared which further reduces the reinforcement learning problem size. the method is compared, in terms of simulation results and other aspects, with other standard reinforcement learning methods.
robot task planning using semantic maps. task planning for mobile robots usually relies solely on spatial information and on shallow domain knowledge, such as labels attached to objects and places. although spatial information is necessary for performing basic robot operations (navigation and localization), the use of deeper domain knowledge is pivotal to endow a robot with higher degrees of autonomy and intelligence. in this paper, we focus on semantic knowledge, and show how this type of knowledge can be profitably used for robot task planning. we start by defining a specific type of semantic maps, which integrates hierarchical spatial information and semantic knowledge. we then proceed to describe how these semantic maps can improve task planning in two ways: extending the capabilities of the planner by reasoning about semantic information, and improving the planning efficiency in large domains. we show several experiments that demonstrate the effectiveness of our solutions in a domain involving robot navigation in a domestic environment.
distributed coordination architecture for multi-robot formation control. in the exploration and implementation of formation control strategies, communication range and bandwidth limitations form a barrier to large scale formation control applications. the limitations of current formation control strategies involving a leader-follower approach and a consensus-based approach with fully available group trajectory information are explored. a unified, distributed formation control architecture that accommodates an arbitrary number of group leaders and arbitrary information flow among vehicles is proposed. the architecture requires only local neighbor-to-neighbor information exchange. in particular, an extended consensus algorithm is applied on the group level to estimate the time-varying group trajectory information in a distributed manner. based on the estimated group trajectory information, a consensus-based distributed formation control strategy is then applied for vehicle level control. the proposed architecture is experimentally implemented and validated on a multi-robot platform under local neighbor-to-neighbor information exchange with a single or multiple leaders involved.
robot navigation in very cluttered environments by preference-based fuzzy behaviors. one of the key challenges in application of autonomous ground vehicles (agvs) is navigation in environments that are densely cluttered with obstacles. the control task becomes more complex when the configuration of obstacles is not known a priori. the most popular control methods for such systems are based on reactive local navigation schemes that tightly couple the robot actions to the sensor information. because of the environmental uncertainties, fuzzy behavior systems have been proposed. the most difficult problem in applying fuzzy-reactive-behavior-based navigation control systems is that of arbitrating or fusing the reactions of the individual behaviors, which is addressed here by the use of preference logic. this paper presents the design of a preference-based fuzzy behavior system for navigation control of robotic vehicles using the multivalued logic framework. as shown in simulation and experimental results, the proposed method allows the robot to smoothly and effectively navigate through cluttered environments such as dense forests. experimental comparisons with the vector field histogram method (vfh) show that the proposed method usually produces smoother albeit longer paths to the goal.
on multi-rate fusion for non-linear sampled-data systems: application to a 6d tracking system. egomotion estimation, e.g. for robot navigation or augmented reality applications, requires the fusion of non-linear sampled-data system with different sensors. an example is to fuse the complimentary characteristics of visual and inertial sensors. existing approaches either use kalman filters in conventionally sampled systems or use particle filters to accommodate the uncertainty of motion models. this paper introduces an approach that models multi-rate non-linear systems to exploit the characteristics of both sensors, assuming synchronicity and periodicity of measurements. the final contribution of this paper is an in-depth analysis and performance comparison of the extended kalman filter, the unscented kalman filter and three particle filters (bootstrap, extended and unscented). while there is large debate over the pros and cons of these two approaches, this work shows the following results for fusing visual and inertial data in 6 dof (position and orientation) in a tracking application: the bootstrap particle filter gives higher estimation error than extended and unscented particle filters, which give very similar results than extended and unscented kalman filters, but with considerable higher computational burden.
objective locomotion parameters based inverted pendulum trajectory generator. this paper describes a new trajectory generator for lucy, a bipedal walking robot actuated by pleated pneumatic artificial muscles. the strategy is based on the inverted pendulum approximation, which models the robot as a single point mass. the trajectory generator allows the step length, intermediate foot lift and velocity to be chosen for each step while keeping the zero moment point (zmp) in the ankle point during the single support phase and it provides a smooth transition of the zmp from the rear ankle point to the front ankle point during the double support phase. the path of the zmp is discussed for a complete multibody model instead of a single point mass. the proposed trajectory generator has been tested in the robot and the results are presented and discussed.
closed loop motion planning of cooperating mobile robots using graph connectivity. in this paper we address the problem of planning the motion of a team of cooperating mobile robots subject to constraints on relative configuration imposed by the nature of the task they are executing. we model constraints between robots using a graph where each edge is associated with the interaction between two robots and describes a constraint on relative configurations. we develop a decentralized motion control system that leads each robot to their individual goals while maintaining the constraints specified on the graph. we present experimental results with groups of holonomic and non-holonomic mobile robots.
theory and implementation of path planning by negotiation for decentralized agents. this paper presents a cooperative decentralized path-planning algorithm for a group of autonomous agents that provides guaranteed collision-free trajectories in real-time. the algorithm is robust with respect to arbitrary delays in the wireless traffic, possible sources being transmission time and error correction. agents move on reserved areas which are guaranteed not to intersect, therefore ensuring safety. a handshaking procedure guarantees recent information states for the agents. conflicts between agents are resolved by a cost-based negotiation process. the basic algorithm is augmented by the introduction of waypoints, which increase performance at the cost of additional wireless traffic. an implementation of the algorithm is tested in simulation and successfully applied to a real system of autonomous robots. the results are presented and discussed.
context-based design of robotic systems. the need for improving the robustness, as well as the ability to adapt to different operational conditions, is a key requirement for a wider deployment of robots in many application domains. in this paper, we present an approach to the design of robotic systems, that is based on the explicit representation of knowledge about context. the goal of the approach is to improve the system's performance, by dynamically tailoring the functionalities of the robot to the specific features of the situation at hand. while the idea of using contextual knowledge is not new, the proposed approach generalizes previous work, and its advantages are discussed through a case study including several experiments. in particular, we identify many attempts to use contextual knowledge in several basic functionalities of a mobile robot such as: behavior, navigation, exploration, localization, mapping and perception. we then show how re-designing our mobile platform with a common representation of contextual knowledge, leads to interesting improvements in many of the above mentioned components, thus achieving greater flexibility and robustness in the face of different situations. moreover, a clear separation of contextual knowledge leads to a design methodology, which supports the design of small specialized system components instead of complex self-contained subsystems.
the virtual wall approach to limit cycle avoidance for unmanned ground vehicles. robot navigation in unknown and very cluttered environments constitutes one of the key challenges in unmanned ground vehicle (ugv) applications. navigational limit cycles can occur when navigating (ugvs) using behavior-based or other reactive algorithms. limit cycles occur when the robot is navigating towards the goal but enters an enclosure that has its opening in a direction opposite to the goal. the robot then becomes effectively trapped in the enclosure. this paper presents a solution named the virtual wall approach (vwa) to the limit cycle problem for robot navigation in very cluttered environments. this algorithm is composed of three stages: detection, retraction, and avoidance. the detection stage uses spatial memory to identify the limit cycle. once the limit cycle has been identified, a labeling operator is applied to a local map of the obstacle field to identify the obstacle or group of obstacles that are causing the deadlock enclosure. the retraction stage defines a waypoint for the robot outside the deadlock area. when the robot crosses the boundary of the deadlock enclosure, a virtual wall is placed near the endpoints of the enclosure to designate this area as off-limits. finally, the robot activates a virtual sensor so that it can proceed to its original goal, avoiding the virtual wall and obstacles found on its way. simulations, experiments, and analysis of the vwa implemented on top of a preference-based fuzzy behavior system demonstrate the effectiveness of the proposed method.
towards 3d point cloud based object maps for household environments. this article investigates the problem of acquiring 3d object maps of indoor household environments, in particular kitchens. the objects modeled in these maps include cupboards, tables, drawers and shelves, which are of particular importance for a household robotic assistant. our mapping approach is based on pcd (point cloud data) representations. sophisticated interpretation methods operating on these representations eliminate noise and resample the data without deleting the important details, and interpret the improved point clouds in terms of rectangular planes and 3d geometric shapes. we detail the steps of our mapping approach and explain the key techniques that make it work. the novel techniques include statistical analysis, persistent histogram features estimation that allows for a consistent registration, resampling with additional robust fitting techniques, and segmentation of the environment into meaningful regions.
learning and generalising semantic knowledge from object scenes. the robot described in this paper learns words that relate to objects and their attributes, and also learns concepts, which may be recursive, that involve relationships between several objects. once the system is explicitly taught some words by a human teacher it finds new objects that might help to refine its concepts. once it has found a new object, it tries to generalise its concepts to include the new object and asks the teacher for feedback. the robot learns further properties of objects by interacting with them, by touching them or walking around them to gain a new perspective. the system learns semantic knowledge from spoken interactions, using speech recognition and generation, motion segmentation, feature extraction from images using ripple down rules and generalisation using inductive logic programming.
end-to-end congestion control protocols for remote programming of robots, using heterogeneous networks: a comparative analysis. there are many interesting aspects of internet telerobotics within the network robotics context, such as variable bandwidth and time-delays. some of these aspects have been treated in the literature from the control point of view. moreover, only a little work is related to the way internet protocols can help to minimize the effect of delay and bandwidth fluctuation on network robotics. in this paper, we present the capabilities of tcp, udp, tcp las vegas, tear, and trinomial protocols, when performing a remote experiment within a network robotics application, the uji industrial telelaboratory. comparative analysis is presented through simulations within the ns2 platform. results show how these protocols perform in two significant situations within the network robotics context, using heterogeneous wired networks: (1) an asymmetric network when controlling the system through a adsl connection, and (2) a symmetric network using the system on campus. conclusions show a set of characteristics the authors of this paper consider very important when designing an end-to-end congestion control transport protocol for internet telerobotics.
visual door detection integrating appearance and shape cues. an important component of human-robot interaction is the capability to associate semantic concepts with encountered locations and objects. this functionality is essential for visually guided navigation as well as location and object recognition. in this paper we focus on the problem of door detection using visual information only. doors are frequently encountered in structured man-made environments and function as transitions between different places. we adopt a probabilistic approach for door detection, by defining the likelihood of various features for generated door hypotheses. differing from previous approaches, the proposed model captures both the shape and appearance of the door. this is learned from a few training examples, exploiting additional assumptions about the structure of indoor environments. after the learning stage, we describe a hypothesis generation process and several approaches to evaluate the likelihood of the generated hypotheses. the approach is tested on numerous examples of indoor environment. it shows a good performance provided that the door extent in the images is sufficiently large and well supported by low level feature measurements.
human behavior recognition using unconscious cameras and a visible robot in a network robot system. we developed a network robot system integrating various types of robots via ubiquitous networks that introduce an interactive robot into areas in which people are located. in this paper, we present a human behavior recognition method necessary for providing guidance in a public space, which uses a tangible network robot system composed of a mobile robot and vision sensors embedded in an environment. we define some basic features that a person typically exhibits when in need of guidance. various human behaviors were successfully interpreted by first recognizing the basic features and then forming their different combinations.
a dynamic object manipulation approach to dynamic biped locomotion. in this paper, we aim at an integrated approach to dynamic biped walking (dbw) and dynamic object manipulation (dom) at an abstract level. to this end, we offer a unified and abstract concept with a dual interpretation as a dom and as a dbw system. we validate the proposed approach by using a set of simulations on an illustrative case study and show how it can be used in modeling as well as design of planning and control algorithms for dom and dbw systems. in the case study, we describe the proposed approach and show its dual interpretation by identifying the relations between 2d dynamic object manipulation of a disc using two planar manipulators and 2d dynamic object locomotion of lower part of a biped robot. more specifically, having obtained the equations of dom, we change the boundary conditions of the problem in such a way that both radius and mass of the disc tend to infinity. simultaneously, both size and mass of the manipulators' base, i.e. the planet earth, tend to some values in the order of human body mass and dimension. regarding these changes, we can transform dom into dbw and vice versa. to test the proposed approach, a simple control strategy is introduced to handle impact between the manipulators (legs) and the object (the earth). in addition, a motion planning system is designed in such a way that the manipulators (legs) catch and throw the manipulated object (the earth) in appropriate configurations.
switching visual control based on epipoles for mobile robots. in this paper, we present a visual control approach consisting in a switching control scheme based on the epipolar geometry. the method facilitates a classical teach-by-showing approach where a reference image is used to control the robot to the desired pose (position and orientation). as a result of our proposal a mobile robot carries out a smooth trajectory towards the target and the epipolar geometry model is used through the whole motion. the control scheme developed considers the motion constraints of the mobile platform in a framework based on the epipolar geometry that does not rely on artificial markers or specific models of the environment. the proposed method is designed in order to cope with the degenerate estimation case of the epipolar geometry with short baseline. experimental evaluation has been performed in realistic indoor and outdoor settings.
exploration of a cluttered environment using voronoi transform and fast marching. the extended voronoi transform and the fast marching method combination provide potential maps for robot navigation in previously unexplored dynamic environments. the extended voronoi transform of a binary image of the environment gives a grey scale that is darker near the obstacles and walls and lighter far from them. the logarithm of the extended voronoi transform imitates the repulsive electric potential from walls and obstacles. the method proposed, called voronoi fast marching method, uses a fast marching technique on the extended voronoi transform of the environment's image, provided by sensors, to determine a motion plan. the computational efficiency of the method lets the planner operate at high rate sensor frequencies. this avoids the need for collision avoidance algorithms. the robot is directed towards the most unexplored and free zones of the environment so as to be able to explore all the workspace. this method is very fast and reliable and the trajectories are similar to the human trajectories: smooth and not very close to obstacles and walls. in this article we propose its application to the task of exploring unknown environments.
on redundancy, efficiency, and robustness in coverage for multiple robots. motivated by potential efficiency and robustness gains, there is growing interest in the use of multiple robots for coverage. in coverage, robots visit every point in a target area, at least once. previous investigations of multi-robot coverage focus on completeness of the coverage, and on eliminating redundancy, but do not formally address robustness. moreover, a common assumption is that elimination of redundancy leads to improved efficiency (coverage time). we address robustness and efficiency in a novel family of multi-robot coverage algorithms, based on spanning-tree coverage of approximate cell decomposition of the work-area. we analytically show that the algorithms are robust, in that as long as a single robot is able to move, the coverage will be completed. we also show that non-redundant (non-backtracking) versions of the algorithms have a worst-case coverage time virtually identical to that of a single robot-thus no performance gain is guaranteed in non-redundant coverage. surprisingly, however, redundant coverage algorithms lead to guaranteed performance which halves the coverage time even in the worst case. we present a polynomial-time redundant coverage algorithm, whose coverage time is optimal, and which is able to address robots heterogeneous in speed and fuel. we compare the performance of all algorithms empirically and show that the use of the optimal algorithm leads to significant improvements in coverage time.
framework and service allocation for network robot platform and execution of interdependent services. this research introduces a framework for network robot platform (nwr-pf) and a service allocation method for heterogeneous distributed robots; they cooperate to perform services that include interdependent tasks. the proposed framework is composed of three layers: connection units, the area management gateway, and the robot-user interaction database. the area management gateway and robot-user interaction database treat the information of the users, robots, services, and service history in a uniform manner, because the connection units hide the differences, such as format and protocol, among the heterogeneous robots. the 4w1h matching method is also proposed for service allocation. the method selects the most suitable robots by comparing the elements of user, robot, and service information. moreover, it generates robot commands in a common format, by combining the service scenario, and service history. a feature of the method is that both robotic functions to execute service and functions that robots possess are described as independent parameters. after the service trigger is received, both the robot and scenario needed to execute the service are decided by matching these parameters. experiments show that robots controlled by nwr-pf can perform interdependent services by referring to the service history.
robust and accurate global vision system for real time tracking of multiple mobile robots. this paper presents a new global vision system for tracking of multiple mobile robots. to the best knowledge of the authors it outperforms all existing global vision systems with respect to measurement precision and accuracy, high speed and real time operation and reliable tracking of large (theoretically unlimited) number of robots under light intensity changes. the originality of the proposed system lies mainly in specially designed robot marks and robots' poses measuring directly in bayer format image delivered by the camera. these two measures enable robust pose estimation of the robots with subpixel precision, while the significant simplification of the image processing algorithms ensures tracking of many robots with very high framerates. with algorithms running on a 3 ghz athlon 64 processor 65 robots can be tracked at 80 fps. moreover, in order to perform a thorough analysis of the system performances related to defined requirements, we propose a new experimental procedure that can serve as a benchmark for evaluation of other systems for the same purpose.
facial behaviour mapping - from video footage to a robot head. as autonomous robotic systems advance, they will be required and designed for interaction with humans in order to exchange information, which is essential for fulfilling their tasks. it is well established that human-machine interactions are more believable and memorable when a physical entity is present, provided that the machine behaves in a realistic manner. it is desirable to adopt face-to-face communication, because it is the most natural and efficient way of exchanging information, and does not require users to alter their habits. in this context, this paper describes a process for animating a robot head, based on video input of a human head. we map from the 2d coordinates of feature points into the robot's servo space, using partial least squares (pls). learning is done using a small set of keyframes manually created by an animator. the method is efficient, robust to tracking errors and independent of the scale of the face being tracked.
accurate robot simulation through system identification. robot simulators are useful tools for developing robot behaviour. they provide a fast and efficient means for testing robot control code at the convenience of the office desk. in all but the simplest cases though, due to complexities of physical systems modelled in the simulator, there are considerable differences between the behaviour of the robot in the simulator and that in the real world environment. in this paper we present a novel method to create a robot simulator using real sensor data. logged sensor data are used to construct a mathematically explicit model (in the form of a narmax polynomial) of the robot's environment. the advantage of such a transparent model -in contrast to opaque modelling methods such as artificial neural networks -is that it can be analysed to characterise the modelled system, using established mathematical methods. in this paper we compare the behaviour of the robot running a particular task in both the simulator and the real-world using qualitative and quantitative measures including statistical methods to investigate the faithfulness of the simulator.
fusion of aerial images and sensor data from a ground vehicle for improved semantic mapping. this work investigates the use of semantic information to link ground level occupancy maps and aerial images. a ground level semantic map, which shows open ground and indicates the probability of cells being occupied by walls of buildings, is obtained by a mobile robot equipped with an omni-directional camera, gps and a laser range finder. this semantic information is used for local and global segmentation of an aerial image. the result is a map where the semantic information has been extended beyond the range of the robot sensors and predicts where the mobile robot can find buildings and potentially driveable ground.
robot training using system identification. this paper focuses on developing a formal, theory-based design methodology to generate transparent robot control programs using mathematical functions. the research finds its theoretical roots in robot training and system identification techniques such as armax (auto-regressive moving average models with exogenous inputs) and narmax (non-linear armax). these techniques produce linear and non-linear polynomial functions that model the relationship between a robot's sensor perception and motor response. the main benefits of the proposed design methodology, compared to the traditional robot programming techniques are: (i) it is a fast and efficient way of generating robot control code, (ii) the generated robot control programs are transparent mathematical functions that can be used to form hypotheses and theoretical analyses of robot behaviour, and (iii) it requires very little explicit knowledge of robot programming, therefore end-users/programmers who do not have any specialized robot programming skills can nevertheless generate task-achieving sensor-motor couplings. the nature of this research is concerned with obtaining sensor-motor couplings, be it through human demonstration via the robot, direct human demonstration, or other means. the viability of our methodology has been demonstrated by teaching various mobile robots different sensor-motor tasks such as wall following, corridor passing, door traversal and route learning.
unsupervised identification of useful visual landmarks using multiple segmentations and top-down feedback. in this paper, we tackle the problem of unsupervised selection and posterior recognition of visual landmarks in image sequences acquired by an indoor mobile robot. this is a highly valuable perceptual capability for a wide variety of robotic applications, in particular autonomous navigation. our method combines a bottom-up data driven approach with top-down feedback provided by high level semantic representations. the bottom-up approach is based on three main mechanisms: visual attention, area segmentation, and landmark characterization. as there is no segmentation method that works properly in every situation, we integrate multiple segmentation algorithms in order to increase robustness of the approach. in terms of top-down feedback, this is provided by two information sources: (i) an estimation of the robot position that reduces the searching scope for potential matches with previously selected landmarks, (ii) a set of weights that, according to the results of previous recognitions, controls the influence of each segmentation algorithm in the recognition of each landmark. we test our approach with encouraging results in three datasets corresponding to real-world scenarios.
autonomous functional configuration of a network robot system. we consider distributed systems of networked robots in which: (1) each robot includes sensing, acting and/or processing modular functionalities; and (2) robots can help each other by offering those functionalities. a functional configuration is any way to allocate and connect functionalities among the robots. an interesting feature of a system of this type is the possibility to use different functional configurations to make the same set of robots perform different tasks, or to perform the same task under different conditions. in this paper, we propose an approach to automatically generate at run time a functional configuration of a network robot system to perform a given task in a given environment, and to dynamically change this configuration in response to failures. our approach is based on artificial intelligence planning techniques, and it is provably sound, complete and optimal. moreover, our configuration planner can be combined with an action planner to deal with tasks that require sequences of configurations. we illustrate our approach on a specific type of network robot system, called peis-ecology, and show experiments in which a sequence of configurations is automatically generated and executed on real robots. these experiments demonstrate that our self-configuration approach can help the system to achieve greater autonomy, flexibility and robustness.
a probabilistic framework for entire wsn localization using a mobile robot. this paper presents a new method for the localization of a wireless sensor network (wsn) by means of collaboration with a robot within a network robot system (nrs). the method employs the signal strength as input, and has two steps: an initial estimation of the position of the nodes is obtained centrally by one robot and is based on particle filtering. it does not require any prior information about the position of the nodes. in the second stage, the nodes refine their position estimates employing a decentralized information filter. the paper shows how the method is able to recover the 3d position of the nodes, and is very suitable for wsn outdoor applications. the paper includes several implementation aspects and experimental results.
online generation of cyclic leg trajectories synchronized with sensor measurement. the generation of trajectories for a biped robot is a problem which has been largely studied for several years, and many satisfying offline solutions exist for steady-state walking in absence of disturbances. the question is a little more complex when the generation of the desired trajectories of joints or links has to be achieved or adapted online, i.e. in real time, for example when it is wished to strongly synchronize these trajectories with an external motion. this is precisely the problem addressed in this paper. indeed, we consider the case where the ''master'' motion is measured by a position sensor embedded on a human leg. we propose a method to synchronize the motion of a robot or of other device with respect to the output signal of the sensor. the main goal is to estimate as accurately as possible the current phase along the gait cycle. we use for that purpose a model based on a nonlinear oscillator, which we associate an observer. introducing the sensor output in the observer allows us to compute the oscillator phase and to generate a synchronized multilinks trajectory, at a very low computational cost. the paper also presents evaluation results in terms of robustness against parameter estimation errors and velocity changes in the input.
model identification and model analysis in robot training. robot training is a fast and efficient method of obtaining robot control code. many current machine learning paradigms used for this purpose, however, result in opaque models that are difficult, if not impossible to analyse, which is an impediment in safety-critical applications or application scenarios where humans and robots occupy the same workspace. in experiments with a magellan pro mobile robot we demonstrate that it is possible to obtain transparent models of sensor-motor couplings that are amenable to subsequent analysis, and how such analysis can be used to refine and tune the models post hoc.
local visual homing by warping of two-dimensional images. local visual homing methods can be used in the context of topological maps to travel between neighboring locations. these methods take two images as input and produce a home vector that points from the vantage point of one image to that of the other. ''warping'' [m.o. franz, b. scholkopf, h.a. mallot, h.h. bulthoff, where did i take that snapshot? scene-based homing by image matching, biological cybernetics 79 (3) (1998) 191-202] is an attractive homing method since it does not require an external compass. here we describe how the performance of warping can be substantially improved by extending the method from one- to two-dimensional images, with only a moderate increase in the computational effort. experiments on several image databases confirm the improved performance.
ivvi: intelligent vehicle based on visual information. human errors are the cause of most traffic accidents, with drivers' inattention and wrong driving decisions being the two main sources. these errors can be reduced, but not completely eliminated. that is why advanced driver assistance systems (adas) can reduce the number, danger and severity of traffic accidents. several adas, which nowadays are being researched for intelligent vehicles, are based on artificial intelligence and robotics technologies. in this article a research platform for the implementation of systems based on computer vision is presented, and different visual perception modules useful for some adas such as line keeping system, adaptive cruise control, pedestrian protector, or speed supervisor, are described.
online generation of scene descriptions in urban environments. the ability to extract a rich set of semantic workspace labels from sensor data gathered in complex environments is a fundamental prerequisite to any form of semantic reasoning in mobile robotics. in this paper, we present an online system for the augmentation of maps of outdoor urban environments with such higher-order, semantic labels. the system employs a shallow supervised classification hierarchy to classify scene attributes, consisting of a mixture of 2d/3d geometric and visual scene information, into a range of different workspace classes. the union of classifier responses yields a rich, composite description of the local workspace. we present extensive experimental results, using two large urban data sets collected by our research platform.
subjective local maps for hybrid metric-topological slam. hybrid maps where local metric submaps are kept in the nodes of a graph-based topological structure are gaining relevance as the focus of robot simultaneous localization and mapping (slam) shifts towards spatial scalability and long-term operation. in this paper we examine the applicability of spectral graph partitioning techniques to the automatic generation of metric submaps by establishing groups in the sequence of observations gathered by the robot. one of the main aims of this work is to provide a probabilistically grounded interpretation of such a partitioning technique in the context of generating local maps. we also discuss how to apply it to different kinds of sensory data (landmarks extracted from stereo images and laser range scans) and how to consider them simultaneously. an important feature of our approach is that the partitioning takes into account the intrinsic characteristics of the sensors, such as the sensor field of view, instead of applying heuristics supplied by a human as in other works. thus the robot builds ''subjective'' local maps whose size will be determined by the nature of the sensors. the ideas presented here are supported by experimental results from a real mobile robot as well as simulations for statistical analysis. we discuss the effects of considering different combinations of sensors in the resulting clustering of the environment.
a new autonomous celestial navigation method for the lunar rover. a secure and autonomous navigation system is needed for the lunar rover in future lunar missions in case of emergencies. celestial navigation is a very attractive solution for long distance navigation on the moon without the need of ground navigation aids. it only uses star altitudes, which are measured by a high accuracy star sensor and inertial measurement unit (imu) to estimate the position of the rover. the navigational accuracy of this method depends largely on the accuracy of measurements, so the measurement errors have a great impact on the navigational performance. a new autonomous celestial navigation method for the lunar rover is presented in this paper, which uses the augmented state unscented particle filter (asupf) to deal with the systematic error and random error in the measurements. the validity and feasibility of this new method is tested and examined by the hardware-in-loop test. a position estimation error within 60 m is obtained. compared to the conventional method, this method shows better navigation performance and higher adaptability to these measurement errors.
a bezier curve based path planning in a multi-agent robot soccer system without violating the acceleration limits. this paper proposes an efficient, bezier curve based approach for the path planning of a mobile robot in a multi-agent robot soccer system. the boundary conditions required for defining the bezier curve are compatible with the estimated initial state of the robot and the ball. the velocity of the robot along the path is varied continuously to its maximum allowable levels by keeping its acceleration within the safe limits. an obstacle avoidance scheme is incorporated for dealing with the stationary and moving obstacles. when the robot is approaching a moving obstacle in the field, it is decelerated and deviated to another bezier path leading to the estimated target position. the radius of curvature of the path at its end points is determined from the known terminal velocity constraint of the robot.
kdd-2004 workshop report link analysis and group detection (linkkdd-2004). in this paper we provide a summary of the workshop on link analysis and group detection (linkkdd-2004) held in conjunction with acm sigkdd 2004, on august 22, seattle, washington, usa. we report in details about the research issues addressed in the talks and the workshop.
kdd-2002 workshop report fractals and self-similarity in data mining: issues and approaches. in this report we provide a summary of the first workshop on application of self-similarity and fractals in data mining: issues and approaches held in conjunction with acm sigkdd 2002, july 23 at edmonton, alberta, canada.
feature engineering for a gene regulation prediction task. this paper describes an approach that won honorable mention for the gene regulation prediction task of the 2002 kdd cup competition [1]. our methodology used extensive cross-validation to direct the search for an appropriate problem representation and the selection of an 'off-the-shelf' induction algorithm. a prominent trait of the dataset is the presence of three hierarchical attributes, for each of which we generated a novel predictive feature: the percentage of positives hierarchically aggregated at the node specified by the instance.
kdd-2005 workshop report: link discovery: issues, approaches and application (linkkdd-2005). in this paper we provide a summary of the workshop on link discovery: issues, approaches and applications (linkkdd-2005) held in conjunction with acm sigkdd 2005, on august 21st in chicago, illinois, usa. we report in detail about the research issues addressed in the talks at the workshop.
towards long pattern generation in dense databases. this paper discusses the problem of long pattern generation in dense databases. in recent years, there has been an increase of interest in techniques for maximal pattern generation. we present a survey of this class of methods for long pattern generation which differ considerably from the level-wise approach of traditional methods. many of these techniques are rooted in combinatorial tricks which can be applied only when the generation of frequent patterns is not forced to be level wise. we present an overview of the different kinds of methods which can be used in order to improve the counting and search space exploration methods for long patterns.
overview of the 2003 kdd cup. this paper surveys the 2003 kdd cup, a competition held in conjunction with the ninth acm sigkdd international conference on knowledge discovery and data mining (kdd) in august 2003. the competition focused on mining the complex real-life social network inherent in the e-print arxiv (arxiv.org). we describe the four kdd cup tasks: citation prediction, download prediction, data cleaning, and an open task.
towards effective and interpretable data mining by visual interaction. the primary aim of most data mining algorithms is to facilitate the discovery of concise and interpretable information from large amounts of data. however, many of the current formalizations of data mining algorithms have not quite reached this goal. one of the reasons for this is that the focus on using purely automated techniques has imposed several constraints on data mining algorithms. for example, any data mining problem such as clustering or association rules requires the specification of particular problem formulations, objective functions, and parameters. such systems fail to take the user's needs into account very effectively. this makes it necessary to keep the user in the loop in a way which is both efficient and interpretable. one unique way of achieving this is by leveraging human visual perceptions on intermediate data mining results. such a system combines the computational power of a computer and the intuitive abilities of a human to provide solutions which cannot be achieved by either. this paper will discuss a number of recent approaches to several data mining algorithms along these lines.
kdd'99 competition: knowledge discovery contest. in this paper, we expand on the 1998 kdd cup competition findings: exploratory data analysis reveals unusual data anomalies; a two-stage prediction model yields superior results those obtained in the 1998 competition; we use a decision tree better understand the model (the decision boundary); and we apply a confidence interval to establish a range upon which we can reasonably judge model performance.
a note on "beyond market baskets: generalizing association rules to correlations". in their paper [1], s. brin, r. matwani and c. silverstien discussed measuring significance of (generalized) association rules via the support and the chi-squared test for correlation. they provided some illustrative examples and pointed that the chi-squared test needs to be agumented by a measure of interest that they also suggested.this paper presents a further elaboration and extension of their discussion. as suggested by brin et al, the chi-squared test succeeds in measuring the cell dependencies in a 2x2 contingency table. however, it can be misleading in cases of bigger contingency tables. we will give some illustrative examples based on those presented in [1]. we will also propose a more appropriate reliability measure of association rules.
link mining: a new data mining challenge. a key challenge for data mining is tackling the problem of mining richly structured datasets, where the objects are linked in some way. links among the objects may demonstrate certain patterns, which can be helpful for many data mining tasks and are usually hard to capture with traditional statistical models. recently there has been a surge of interest in this area, fueled largely by interest in web and hypertext mining, but also by interest in mining social networks, security and law enforcement data, bibliographic citations and epidemiological records.
sampling algorithms for pure network topologies: a study on the stability and the separability of metric embeddings. in a time of information glut, observations about complex systems and phenomena of interest are available in several applications areas, such as biology and text. as a consequence, scientists have started searching for patterns that involve interactions among the objects of analysis, to the effect that research on models and algorithms for network analysis has become a central theme for knowledge discovery and data mining (kdd). the intuitions behind the plethora of approaches rely upon few basic types of networks, identified by specific local and global topological properties, which we term "pure" topology types.in this paper, (1) we survey pure topology types along with existing sampling algorithms that generate them, (2) we introduce novel algorithms that enhance the diversity of samples, and address the case of cellular topologies, (3) we perform statistical studies of the stability of the properties of pure types to alternative generative algorithms, and a joint study of the separability of pure types, in terms of their embedding in a space of metrics for network analysis, widely adopted in the social and physical sciences.we conclude with a word of caution to the practitioners, who sample pure topology types to assess the "statistical significance" of their findings, e.g., the p-value of the clustering coefficient is sensitive to the sampling algorithm used. we find that different pure types share similar topological properties. further, real world networks hardly present the variability profile of a single pure type. we suggest the assumption of "mixtures of types" as an alternative starting point for developing models and algorithms for network analysis.
introduction to the special issue on link mining. an emerging challenge for data mining is the problem of mining richly structured datasets, where the objects are linked in some way. many real-world datasets describe a variety of entity types linked via multiple types of relations. these links provide additional context that can be helpful for many data mining tasks. yet multi-relational data violates the traditional assumption of independent, identically distributed data instances that provides the basis for many statistical machine learning algorithms. therefore, new approaches are needed that can exploit the dependencies across the attribute and link structure.
link mining: a survey. many datasets of interest today are best described as a linked collection of interrelated objects. these may represent homogeneous networks, in which there is a single-object type and link type, or richer, heterogeneous networks, in which there may be multiple object and link types (and possibly other semantic information). examples of homogeneous networks include single mode social networks, such as people connected by friendship links, or the www, a collection of linked web pages. examples of heterogeneous networks include those in medical domains describing patients, diseases, treatments and contacts, or in bibliographic domains describing publications, authors, and venues. link mining refers to data mining techniques that explicitly consider these links when building predictive or descriptive models of the linked data. commonly addressed link mining tasks include object ranking, group detection, collective classification, link prediction and subgraph discovery. while network analysis has been studied in depth in particular areas such as social network analysis, hypertext mining, and web analysis, only recently has there been a cross-fertilization of ideas among these different communities. this is an exciting, rapidly expanding area. in this article, we review some of the common emerging themes.
: using constrained models for guaranteed-error semantic compression. while a variety of lossy compression schemes have been developed for certain forms of digital data (e.g., images, audio, video), the area of lossy compression techniques for arbitrary data tables has been left relatively unexplored. nevertheless, such techniques are clearly motivated by the ever-increasing data collection rates of modern enterprises and the need for effective, guaranteed-quality approximate answers to queries over massive relational data sets.in this paper, we propose spartan, a system that takes advantage of attribute semantics and data-mining models to perform lossy compression of massive data tables. spartan is based on the novel idea of exploiting predictive data correlations and prescribed error-tolerance constraints for individual attributes to construct concise and accurate classification and regression tree (cart) models for entire columns of a table. more precisely, spartan selects a certain subset of attributes (referred to as predicted attributes) for which no values are explicitly stored in the compressed table; instead, concise error-constrained carts that predict these values (within the prescribed error tolerances) are maintained. to restrict the huge search space of possible cart predictors, spartan uses a bayesian network structure to guide the selection of cart models that minimize the overall storage requirement, based on the prediction and materialization costs for each attribute. spartan's cart-building algorithms employ novel integrated pruning strategies that take advantage of the given error constraints on individual attributes to minimize the computational effort involved. our experimentation with several real-life data sets offers convincing evidence of the effectiveness of spartan's model-based approach --- spartan is able to consistently yield substantially better compression ratios than existing semantic or syntactic compression tools (e.g., gzip) while utilizing only small samples of the data for model inference.
automatic scientific text classification using local patterns: kdd cup 2002 (task 1). in this paper, we describe our approach for addressing task 1 in the kdd cup 2002 competition. the approach is based on developing and using an improved automatic feature selection method in conjunction with traditional classifiers. the feature selection method used is based on capturing frequently occurring keyword combinations (or motifs) within short segments of the text of a document and has proved to produce more accurate classification results than approaches relying solely on using keyword-based features.
machine learning methods applied to dna microarray data can improve the diagnosis of cancer. the morbidity rate of cancer victims varies greatly for similar patients who receive similar treatments. it is hypothesized that this variation can be explained by the genetic heterogeneity of the disease. dna microarrays, which can simultaneously measure the expression level of thousands of different genes, have been successfully used to identify such genetic differences. however, microarray data typically has a large number of features and relatively few observations, meaning that conventional machine learning tools can fail when applied to such data. we describe a novel procedure called "nearest shrunken centroids" that has successfully detected clinically relevant genetic differences in cancer patients. this procedure has the potential to become a powerful tool for diagnosing and treating cancer.
meta-clustering of gene expression data and literature-based information. the current tendency in the life sciences to spawn ever growing amounts of high-throughput assays has led to a situation where the interpretation of data and the formulation of hypotheses lag the pace at which information is produced. although the first generation of statistical algorithms scrutinizing single, large-scale data sets found their way into the biological community, the great challenge to connect their results to existing knowledge still remains. despite the fairly large number of biological databases that is currently available, a lot of relevant information is found in free-text format (such as textual annotations, scientific abstracts and full publications). in this paper we explore how an integrated analysis of expression data and literature-extracted information can reveal biologically meaningful clusters not identified when using microarray information alone. the joint analysis is validated in terms of transcriptional regulation.
requirements for clustering data streams. scientific and industrial examples of data streams abound in astronomy, telecommunication operations, banking and stock-market applications, e-commerce and other fields. a challenge imposed by continuously arriving data streams is to analyze them and to modify the models that explain them as new data arrives. in this paper, we analyze the requirements needed for clustering data streams. we review some of the latest algorithms in the literature and assess if they meet these requirements.
instance filtering for entity recognition. in this paper we propose instance filtering as preprocessing step for supervised classification-based learning systems for entity recognition. the goal of instance filtering is to reduce both the skewed class distribution and the data set size by eliminating negative instances, while preserving positive ones as much as possible. this process is performed on both the training and test set, with the effect of reducing the learning and classification time, while maintaining or improving the prediction accuracy. we performed a comparative study on a class of instance filtering techniques, called stop word filters, that simply remove all the tokens belonging to a list of stop words. we evaluated our approach on three different entity recognition tasks (i.e. named entity, bio-entity and temporal expression recognition) in english and dutch, showing that both the skewness and the data set size are drastically reduced. consequently, we reported an impressive reduction of the computation time required for training and classification, while maintaining (and sometimes improving) the prediction accuracy.
a survey of data mining and knowledge discovery software tools. knowledge discovery in databases is a rapidly growing field, whose development is driven by strong research interests as well as urgent practical, social, and economical needs. while the last few years knowledge discovery tools have been used mainly in research environments, sophisticated software products are now rapidly emerging. in this paper, we provide an overview of common knowledge discovery tasks and approaches to solve these tasks. we propose a feature classification scheme that can be used to study knowledge and data mining software. this scheme is based on the software's general characteristics, database connectivity, and data mining characteristics. we then apply our feature classification scheme to investigate 43 software products, which are either research prototypes or commercially available. finally, we specify features that we consider important for knowledge discovery software to possess in order to accommodate its users effectively, as well as issues that are either not addressed or insufficiently solved yet.
a study of the behavior of several methods for balancing machine learning training data. there are several aspects that might influence the performance achieved by existing learning systems. it has been reported that one of these aspects is related to class imbalance in which examples in training data belonging to one class heavily outnumber the examples in the other class. in this situation, which is found in real world data describing an infrequent but important event, the learning system may have difficulties to learn the concept related to the minority class. in this work we perform a broad experimental evaluation involving ten methods, three of them proposed by the authors, to deal with the class imbalance problem in thirteen uci data sets. our experiments provide evidence that class imbalance does not systematically hinder the performance of learning systems. in fact, the problem seems to be related to learning with too few minority class examples in the presence of other complicating factors, such as class overlapping. two of our proposed methods deal with these conditions directly, allying a known over-sampling method with data cleaning methods in order to produce better-defined class clusters. our comparative experiments show that, in general, over-sampling methods provide more accurate results than under-sampling methods considering the area under the roc curve (auc). this result seems to contradict results previously published in the literature. two of our proposed methods, smote + tomek and smote + enn, presented very good results for data sets with a small number of positive examples. moreover, random over-sampling, a very simple over-sampling method, is very competitive to more complex over-sampling methods. since the over-sampling methods provided very good performance results, we also measured the syntactic complexity of the decision trees induced from over-sampled data. our results show that these trees are usually more complex then the ones induced from original data. random over-sampling usually produced the smallest increase in the mean number of induced rules and smote + enn the smallest increase in the mean number of conditions per rule, when compared among the investigated over-sampling methods.
open source data mining: workshop report. over the past decade tremendous progress has been made in data mining methods like clustering, classification, frequent pattern mining, and so on. unfortunately, however, the advanced implementations are often not made publicly available, and thus the results cannot be independently verified. we believe that this hampers the rapid advances in the field. with this workshop we intended to promote open source data mining (osdm) by creating a first meeting place to discuss open source data mining methods.
interface '99: a data mining overview. this personal overview of interface '99 is intended to communicate its meaning and relevance to sigkdd, as well as provide valuable information on trends within the interface for data miners seeking to learn more about statistics. in addition, it is the newest link in a bridge between the interface and kdd begun by references 2-4 and the sessions on kdd at interface '98 and interface '99.
multi-relational data mining 2005: workshop report. in this report we briefly review the 4th workshop on multi-relational data mining (mrdm-2005), which was organized by the authors and held in chicago, il, on august 21, as part of the workshop program of the eleventh acm sigkdd international conference on knowledge discovery and data mining. the goal of the workshop was to bring together researchers and practitioners of data mining interested in methods and applications of finding patterns in expressive languages from multi-relational, complex, and/or structured data.
kdd-2003 workshop on data mining standards, services and platforms (dm-ssp 03). at kdd 2003 a half day workshop was held on data mining standards and data mining services based on them. a theme of the workshop was that data mining standards have matured sufficiently that standards-based services and applications can now be deployed easily.
scalability and efficiency in multi-relational data mining. efficiency and scalability have always been important concerns in the field of data mining, and are even more so in the multi-relational context, which is inherently more complex. the issue has been receiving an increasing amount of attention during the last few years, and quite a number of theoretical results, algorithms and implementations have been presented that explicitly aim at improving the efficiency and scalability of multi-relational data mining approaches. with this article we attempt to present a structured overview.
data mining standards, services, and platforms 2004 (dm-ssp 2004). this is a summary of the workshop on data mining standards, services and platforms, which was held at kdd 2004. the workshop contained talks on the predictive model markup language (pmml) and the java standard for data mining jsr-73. it also contained talks on emerging service-based architectures for data mining. finally, infrastructures for privacy preserving data mining were also discussed.
mining sales data using a neural network model of market response. modeling aggregate market response is a core issue in marketing research. in this research, we extend previous forecasting comparative research by comparing the forecasting accuracy of feed-forward neural network models to the premier market modeling technique, multiplicative competitive interaction (mci) models. forecasts are compared in two separate studies: (1) the information resources inc. (iri) coffee dataset from marion, in and (2) the a. c. nielsen catsup dataset from sioux falls, sd. our results suggest neural networks are a useful substitute for mci models when there are too few observations available to estimate a fully-extended mci model. implications are discussed.
the 6th international workshop on multimedia data mining (mdm/kdd2005). in this report, we provide a summary of the issues and research directions on multimedia data mining and the outcomes of the mdm/kdd'05 workshop that was held in conjunction with the 11th acm sigkdd international conference on knowledge discovery and data mining (kdd 2005), august 21--24 in chicago il.
information diffusion through blogspace. we study the dynamics of information propagation in environments of low-overhead personal publishing, using a large collection of weblogs over time as our example domain. we characterize and model this collection at two levels. first, we present a macroscopic characterization of topic propagation through our corpus, formalizing the notion of long-running "chatter" topics consisting recursively of "spike" topics generated by outside world events, or more rarely, by resonances within the community. second, we present a microscopic characterization of propagation from individual to individual, drawing on the theory of infectious diseases to model the flow. we propose, validate, and employ an algorithm to induce the underlying propagation network from a sequence of posts, and report on the results.
learning from imbalanced data sets with boosting and data generation: the databoost-im approach. learning from imbalanced data sets, where the number of examples of one (majority) class is much higher than the others, presents an important challenge to the machine learning community. traditional machine learning algorithms may be biased towards the majority class, thus producing poor predictive accuracy over the minority class. in this paper, we describe a new approach that combines boosting, an ensemble-based learning algorithm, with data generation to improve the predictive power of classifiers against imbalanced data sets consisting of two classes. in the databoost-im method, hard examples from both the majority and minority classes are identified during execution of the boosting algorithm. subsequently, the hard examples are used to separately generate synthetic examples for the majority and minority classes. the synthetic data are then added to the original training set, and the class distribution and the total weights of the different classes in the new training set are rebalanced. the databoost-im method was evaluated, in terms of the f-measures, g-mean and overall accuracy, against seventeen highly and moderately imbalanced data sets using decision trees as base classifiers. our results are promising and show that the databoost-im method compares well in comparison with a base classifier, a standard benchmarking boosting algorithm and three advanced boosting-based algorithms for imbalanced data set. results indicate that our approach does not sacrifice one class in favor of the other, but produces high predictions against both minority and majority classes.
the download estimation task on kdd cup 2003. this paper describes our work on the download estimation task for kdd cup 2003. the task requires us to estimate how many times a paper has been downloaded in the first 60 days after it has been published on arxiv.org, a preprint server for papers on physics and related areas. the training data consists of approximately 29000 papers, the citation graph, and information about the downloads of a subset of these papers. our approach is based on an extension of the bag-of-words model, with linear svm regression as the learning algorithm. we describe our experiments with various kinds of features. we focus particularly on issues of feature construction and weighting, which turns out to be quite important for this task.
improving classification of microarray data using prototype-based feature selection. this paper addresses the problem of improving accuracy in the machine-learning task of classification from microarray data. one of the known issues specifically related to microarray data is the large number of inputs (genes) versus the small number of available samples (conditions). a promising direction of research to decrease the generalization error of classification algorithms is to perform gene selection so as to identify those genes which are potentially most relevant for the classification. classical feature selection methods are based on direct statistical methods. we present a reduction algorithm based on the notion of prototypegene. each prototype represents a set of similar gene according to a given clustering method. we present experimental evidence of the usefulness of combining prototype-based feature selection with statistical gene selection methods for the task of classifying adenocarcinoma from gene expressions.
genetic subtyping using cluster analysis. in this paper we (1) describe state-of-the-art methods to identify clusters in dna sequence data for taxonomic analysis; (2) describe a new method with better scaling properties based on model-based clustering, and (3) present examples using the nucleoprotein and hemagglutin regions of influenza and the env and gag regions of human immunodeficiency virus (hiv).
the true lift model - a novel data mining approach to response modeling in database marketing. in database marketing, data mining has been used extensively to find the optimal customer targets so as to maximize return on investment. in particular, using marketing campaign data, models are typically developed to identify characteristics of customers who are most likely to respond. while these models are helpful in identifying the likely responders, they may be targeting customers who have decided to take the desirable action or not regardless of whether they receive the campaign contact (e.g. mail, call). based on many years of business experience, we identify the appropriate business objective and its associated mathematical objective function. we point out that the current approach is not directly designed to solve the appropriate business objective. we then propose a new methodology to identify the customers whose decisions will be positively influenced by campaigns. the proposed methodology is easy to implement and can be used in conjunction with most commonly used supervised learning algorithms. an example using simulated data is used to illustrate the proposed methodology. this paper may provide the database marketing industry with a simple but significant methodological improvement and open a new area for further research and development.
statistics and data mining: intersecting disciplines. statistics and data mining have much in common, but they also have differences. the nature of the two disciplines is examined, with emphasis on their similarities and differences.
a data cleaning solution by perl scripts for the kdd cup 2003 task 2. in this paper, we present our solution for the kdd cup 2003 task 2 competition. our approach is based on a data cleaning methodology using perl scripts. these scripts contain regular expression for automatically extracting relevant information from the 35472 latex texts. these expressions were optimized by statistical investigations on the texts. our solution has permitted us to obtain 144,087 associations.
the 1st workshop on roc analysis in artificial intelligence (rocai-2004). this short report includes a summary of the presentations and discussions held during the rocai-2004 workshop, as well as the workshop conclusions and the future agenda. rocai-2004 was held in valencia, on august the 22nd, as part of the 16th european conference on artificial intelligence, ecai-2004, in valencia, spain.
resource description framework: metadata and its applications. universality, the property of the web that makes it the largest data and information source in the world, is also the property behind the lack of a uniform organization scheme that would allow easy access to data and information. a semantic web, wherein different applications and web sites can exchange information and hence exploit web data and information to their full potential, requires the information about web resources to be represented in a detailed and structured manner. resource description framework (rdf), an effort in this direction supported by the world wide web consortium, provides a means for the description of metadata which is a necessity for the next generation of interoperable web applications. the success of rdf and the semantic web will depend on (1) the development of applications that prove the applicability of the concept, (2) the availability of application interfaces which enable the development of such applications, and (3) databases and inference systems that exploit rdf to identify and locate most relevant web resources. in addition, many practical issues, such as security, ease of use, and compatibility, will be crucial in the success of rdf. this survey aims at providing a glimpse at the past, present, and future of this upcoming technology and highlights why we believe that the next generation of the web will be more organized, informative, searchable, accessible, and, most importantly, useful. it is expected that knowledge discovery and data mining can benefit from rdf and the semantic web.
artificial neural networks - a science in trouble . this article points out some very serious misconceptions about the brain in connectionism and artificial neural networks. some of the connectionist ideas have been shown to have logical flaws, while others are inconsistent with some commonly observed human learning processes and behavior. for example, the connectionist ideas have absolutely no provision for learning from stored information, something that humans do all the time. the article also argues that there is definitely a need for some new ideas about the internal mechanisms of the brain. it points out that a very convincing argument can be made for a "control theoretic" approach to understanding the brain. a "control theoretic" approach is actually used in all connectionist and neural network algorithms and it can also be justified from recent neurobiological evidence. a control theoretic approach proposes that there are subsystems within the brain that control other subsystems. hence a similar approach can be taken in constructing learning algorithms and other intelligent systems.
model builder for predictive analytics & fair isaac's approach to kdd cup 2003. fair isaac tackled the third task of kdd cup 2003 using a predictive modeling approach that leveraged citation graphs, text mining, custom variable creation and linear regression. the core tools we used were embedded in our model builder for predictive analytics (mbpa) product that makes commercially available a broad set of previously proprietary methodologies used by fair isaac for predictive scoring systems such as credit risk and credit card fraud. this short paper reviews the kdd cup problem our approach, and the toolset. we analyze the predictive variables in the model, the main sources of prediction errors, and the steps that could be taken to alleviate such errors in future work.
the myth of the double-blind review?: author identification using only citations. prior studies have questioned the degree of anonymity of the double-blind review process for scholarly research articles. for example, one study based on a survey of reviewers concluded that authors often could be identified by reviewers using a combination of the author's reference list and the referee's personal background knowledge. for the kdd cup 2003 competition's "open task," we examined how well various automatic matching techniques could identify authors within the competition's very large archive of research papers. this paper describes the issues surrounding author identification, how these issues motivated our study, and the results we obtained. the best method, based on discriminative self-citations, identified authors correctly 40--45% of the time. one main motivation for double-blind review is to eliminate bias in favor of well-known authors. however, identification accuracy for authors with substantial publication history is even better (60% accuracy for the top-10% most prolific authors, 85% for authors with 100 or more prior papers).
kdd-cup 2004: results and analysis. this paper summarizes and analyzes the results of the 2004 kdd-cup. the competition consisted of two tasks from the areas of particle physics and protein homology detection. it focused on the problem of optimizing supervised learning to different performance measures (accuracy, cross-entropy, roc area, slac-q, squared error, average precision, top 1, and rank of last). a total of 102 groups participated in the competition, 6 of which received awards or honorable mentions. their approaches are described in other papers in this issue of sigkdd explorations. in this paper we do not analyze any particular approach, but give insight into the performance of the field of competitors as a whole. we study what fraction of the participants found good solutions, how well participants were able to optimize to different performance measures, how homogeneous their submitted predictions are, and if the best submissions represent the maximal performances that could reasonably be achieved. we are keeping the kdd-cup 2004 www site open and have added an automatic scoring system for new submissions in order to encourage further research in this area.
is pushing constraints deeply into the mining algorithms really what we want?: an alternative approach for association rule mining. the common approach to exploit mining constraints is to push them deeply into the mining algorithms. in our paper we argue that this approach is based on an understanding of kdd that is no longer up-to-date. in fact, today kdd is seen as a human centered, highly interactive and iterative process. blindly enforcing constraints already during the mining runs neglects the process character of kdd and therefore is no longer state of the art. constraints can make a single algorithm run faster but in fact we are still far from response times that would allow true interactivity in kdd. in addition we pay the price of repeated mining runs and moreover risk reducing data mining to some kind of hypothesis testing. taking all the above into consideration we propose to do exactly the contrary of constrained mining: we accept an initial (nearly) unconstrained and costly mining run. but instead of a sequence of subsequent and still expensive constrained mining runs we answer all further mining queries from this initial result set. whereas this is straight forward for constraints that can be implemented as filters on the result set, things get more complicated when we restrict the underlying mining data. actually in practice such constraints are very important, e.g. the generation of rules for certain days of the week, for families, singles, male or female customers etc. we show how to postpone such row-restriction constraints on the transactions from rule generation to rule retrieval from the initial result set.
a multistrategy approach for digital text categorization from imbalanced documents. the goal of the research described here is to develop a multistrategy classifier system that can be used for document categorization. the system automatically discovers classification patterns by applying several empirical learning methods to different representations for preclassified documents belonging to an imbalanced sample. the learners work in a parallel manner, where each learner carries out its own feature selection based on evolutionary techniques and then obtains a classification model. in classifying documents, the system combines the predictions of the learners by applying evolutionary techniques as well. the system relies on a modular, flexible architecture that makes no assumptions about the design of learners or the number of learners available and guarantees the independence of the thematic domain.
data mining for hypertext: a tutorial survey. with over 800 million pages covering most areas of human endeavor, the world-wide web is a fertile ground for data mining research to make a difference to the effectiveness of information search. today, web surfers access the web through two dominant interfaces: clicking on hyperlinks and searching via keyword queries. this process is often tentative and unsatisfactory. better support is needed for expressing one's information need and dealing with a search result in more structured ways than available now. data mining and machine learning have significant roles to play towards this end.in this paper we will survey recent advances in learning and mining problems related to hypertext in general and the web in particular. we will review the continuum of supervised to semi-supervised to unsupervised learning problems, highlight the specific challenges which distinguish data mining in the hypertext domain from data mining in the context of data warehouses, and summarize the key areas of recent and ongoing research.
mining semantics for large scale integration on the web: evidences, insights, and challenges. the web has been rapidly "deepened" -- with myriad searchable databases online, where data are hidden behind query interfaces. toward large scale integration over this "deep web," we are facing a new challenge- with its dynamic and ad-hoc nature, such large scale integration mandates dynamic semantics discovery. that is, we must on-the-fly cope with "semantics" of dynamically discovered sources without pre-configured source-specific knowledge. to tackle this challenge, our initial works hinge on the insight that the large scale is itself also a unique opportunity: we observe that the desired "semantics" often connects to surface presentation characteristics, through some hidden regularities over many sources. such regularities can be essentially leveraged in enabling semantics discovery. in particular, we report our evidences in three initial tasks for integrating the deep web: interface extraction, schema matching, and query translation. generalizing these specific evidences, we thus propose our "unified insight" of "mining" semantics for large scale integration by exploiting hidden regularities across holistic sources. further, to fulfill the promise of such holistic mining, we discuss challenges toward its realization for dynamic semantics discovery. as our initial works as well as several related efforts have witnessed, we believe our unified insight, holistic mining for semantics discovery, is a promising methodology toward enabling large scale integration.
graph-based relational learning: current and future directions. graph-based relational learning (gbrl) differs from logic-based relational learning, as addressed by inductive logic programming techniques, and differs from frequent subgraph discovery, as addressed by many graph-based data mining techniques. learning from graphs, rather than logic, presents representational issues both in input data preparation and output pattern language. while a form of graph-based data mining, gbrl focuses on identifying novel, not necessarily most frequent, patterns in a graph-theoretic representation of data. this approach to graph-based data mining provides both simplifications and challenges over frequency-based approaches. in this paper we discuss these issues and future directions of graph-based relational learning.
kdd-99: the fifth acm sigkdd international conference on knowledge discovery and data mining. kdd-99 was the fifth conference in the kdd series attracting over 200 high quality submissions and almost 600 attendees. here we describe some of the highlights of the technical program.
a workshop report: mining for and from the semantic web at kdd 2004. the international workshop on mining for and from the semantic web (msw) at the kdd 2004 successfully brought together people from the communities semantic web and knowledge discovery. the goal of the workshop was to strengthen the communication and interaction between these communities as there is currently an agreement that both can benefit largely from each other. overall the contributions and discussions showed that today mining for the semantic web is the primarily targeted research area. however, with a growing amount of available semantic web data also mining from the semantic web will be more prominent.
data snooping, dredging and fishing: the dark side of data mining, a sigkdd99 panel report. this article briefly describes a panel discussion at sigkdd99.
kdd cup 2001 report. this paper presents results and lessons from kdd cup 2001. kdd cup 2001 focused on mining biological databases. it involved three cutting-edge tasks related to drug design and genomics.
towards interactive exploration of gene expression patterns. analyzing coherent gene expression patterns is an important task in bioinformatics research and biomedical applications. recently, various clustering methods have been adapted or proposed to identify clusters of co-expressed genes and recognize coherent expression patterns as the centroids of the clusters. however, the interpretation of co-expressed genes and coherent patterns mainly depends on the domain knowledge, which presents several challenges for coherent pattern mining and cannot be solved by most existing clustering approaches.in this paper, we introduce an interactive exploration system genex (gene explorer) for mining coherent expression patterns. we develop a novel coherent pattern index graph to provide highly confident indications of the existence of coherent patterns. typical exploration operations are supported based on the index graph. we also provide a bunch of graphical views as the user interface to visualize the data set and facilitate the interactive operations. to help users to interpret and validate the mining results, we design the gene annotation panel that connects the genes with some public annotation databases. the experimental results show that our approach is more effective than the state-of-the-art methods in mining real gene expression data sets.
learning by googling. the goal of giving a well-defined meaning to information is currently shared by endeavors such as the semantic web as well as by current trends within knowledge management. they all depend on the large-scale formalization of knowledge and on the availability of formal metadata about information resources. however, the question how to provide the necessary formal metadata in an effective and efficient way is still not solved to a satisfactory extent. certainly, the most effective way to provide such metadata as well as formalized knowledge is to let humans encode them directly into the system, but this is neither efficient nor feasible. furthermore, as current social studies show, individual knowledge is often less powerful than the collective knowledge of a certain community.as a potential way out of the knowledge acquisition bottleneck, we present a novel methodology that acquires collective knowledge from the world wide web using the googletm api. in particular, we present pankow, a concrete instantiation of this methodology which is evaluated in two experiments: one with the aim of classifying novel instances with regard to an existing ontology and one with the aim of learning sub-/superconcept relations.
class imbalances versus small disjuncts. it is often assumed that class imbalances are responsible for significant losses of performance in standard classifiers. the purpose of this paper is to the question whether class imbalances are truly responsible for this degradation or whether it can be explained in some other way. our experiments suggest that the problem is not directly caused by class imbalances, but rather, that class imbalances may yield small disjuncts which, in turn, will cause degradation. we argue that, in order to improve classifier performance, it may, then, be more useful to focus on the small disjuncts problem than it is to focus on the class imbalance problem. we experiment with a method that takes the small disjunct problem into consideration, and show that, indeed, it yields a performance superior to the performance obtained using standard or advanced solutions to the class imbalance problem.
learning missing values from summary constraints. real-world data sets often contain errors and inconsistency. even though this is a very important problem it has received relatively little attention in the research community. in this paper we examine the problem of learning missing values when some summary information is available. we use linear algebra and constraint programming techniques to learn the missing values using apriori-known summary information and that derived from the raw data. we reconstruct the missing values by different methods in three scenarios: ideal-constrained, under-constrained, and over-constrained. furthermore, for a range query involving missing values, we also give the lower bound and upper bound for the values using constraint programming techniques. we believe that theory of linear algebra and constraint programming constitutes a sound basis for learning missing values when summary information is available.
behind-the-scenes data mining: a report on the kdd-98 panel. successful technology becomes invisible. few people think much about internal combustion engines while they drive to work in three-thousand-pound hunks of metal powered by them, or electricity while it enables countless parts of their modern lives. data mining has a long way to go before it succeeds in this way -- or does it? at kdd-98, the behind-the-scenes data mining panel presented five views on this aspect of the success of data mining. george h. john, data mining guru at e.piphany, moderated the panel which included usama fayyad, senior researcher at microsoft; elliot fishman, director of product management at doubleclick; gerald fahner, project analyst at fair isaac & co.; and paul dubose, cto of analytika. the story below is a fictional amalgam of their presentations, seen from the viewpoint of an average citizen -- a day in the life of john q. record.
the genomics of a signaling pathway: a kdd cup challenge task. this article describes task 2 of the kdd cup 2002 datamining competition. the task involved predicting whether deletions of individual genes in a yeast genome would affect a particular signaling pathway in the cell. with its rich data sources and abundance of missing information, the task is representative of data mining problems in genomics and proved to be quite challenging.
statistical methods for joint data mining of gene expression and dna sequence database. one of the purposes of microarray gene expression experiments is to identify genes regulated under specific cellular conditions. with the availability of putative transcription factor binding motifs, it is now possible to relate gene expression pattern to the pattern of transcription factor binding sites (tfbs), as well as study how tfbs interact with each other to control gene expression. the objectives of this study are to develop a systematic approach for combining data from microarray gene expression experiments and the corresponding regulatory motif patterns in order to delineate gene regulation mechanisms. a secondary goal is to develop a predictive model for finding similarly regulated genes. three consecutive procedures are proposed for such data mining activities. first, a linear mixed-effect model is fit to data from microarray gene expression experiments and potential regulated (positive) genes are identified based on a specific biological hypothesis. putative tfbs are then retrieved for the identified positive genes and randomly selected controls. second, a cluster analysis is conducted to reduce collinearity among the binding sites. in the third step, logistic regression is applied to choose the best model to predict gene type (positive, control) based on the numerous tfbs predictors. the above approach was applied to an internal example and a model was developed to predict up-regulated genes in activated t-helper (th) cells. using a leave-one-out cross- validation scheme, the model has an 18.9% false positive rate and a 41.7% false negative rate.
report on kdd conference 2004 panel discussion can natural language processing help text mining? with large amounts of text data now available on-line, both on the internet and in corporate repositories, text mining is an area of growing interest. historically, data mining researchers have come out of the statistics, database and machine learning communities. despite a few exceptions, it has by and large had little interaction with the computational linguistics and natural language processing (nlp) community. given that the subject matter of text mining is free text, one might naturally assume techniques developed over the last few decades in computational linguistics and nlp, should make big contributions towards the younger field of text mining. however, other than in the area of information extraction, empirical evidence has not borne this out.
text mining and natural language processing: introduction for the special issue. this paper provides an introduction to this special issue of sigkdd explorations devoted to natural language processing and text mining.
when and how to subsample: report on the kdd-2001 panel. databases in the terabyte range are now common. in many domains, mining all the data available in reasonable time is already beyond the reach of current systems. yet the size of databases continues to grow rapidly. is subsampling unavoidable? or should it be avoided at all costs? if we subsample, what is the best way to do it? what issues must be taken into account? the kdd-2001 panel on when and how to subsample addressed these and related questions, with the twin goals of developing practical guidelines and identifying key research issues. it was chaired by pedro domingos (university of washington), and the participants were surajit chaudhuri (microsoft research), david jensen (university of massachusetts at amherst), ronny kohavi (blue martini), and foster provost (new york university). below is each panelist's summary of his position.
the ferrety algorithm for the kdd cup 2005 problem. in this paper, we present a general solution for the kdd cup 2005 problem. it uses the internet as source of knowledge and extends it to categorize very short (less than 5 words) documents with reasonable accuracy. our approach consists of three main parts: i.) a central knowledge filter ii.) an on-demand web crawler and iii.) a very efficient categorizer system. our solution obtained creativity and precision runner-up awards at the competition. the main idea of ferrety algorithm can be generalized for mapping one taxonomy to another if training documents are available.
prospects and challenges for multi-relational data mining. this short paper argues that multi-relational data mining has a key role to play in the growth of kdd, and briefly surveys some of the main drivers, research problems, and opportunities in this emerging field.
mining structures for semantics. online data is available in two avors: unstructured data that resides as free text in html pages, and structured data that resides in databases and knowledge bases. unstructured data is easily accessed as human-readable text on a browser, while structured data is hidden behind web query interfaces (web forms), web services, and custom database apis. access to this data, popularly referred to as the hidden web, entails submitting correctly completed web forms or writing code to access web services using protocols such as soap.
mobimine: monitoring the stock market from a pda. this paper describes an experimental mobile data mining system that allows intelligent monitoring of time-critical financial data from a hand-held pda. it presents the overall system architecture and the philosophy behind the design. it explores one particular aspect of the system---automated construction of personalized focus area that calls for user's attention. this module works using data mining techniques. the paper describes the data mining component of the system that employs a novel fourier analysis-based approach to efficiently represent, visualize, and communicate decision trees over limited bandwidth wireless networks. the paper also discusses a quadratic programming-based personalization module that runs on the pdas and the multi-media based user-interfaces. it reports experimental results using an ad hoc peer-to-peer ieee 802.11 wireless network.
loss-based estimation with cross-validation: applications to microarray data analysis. current statistical inference problems in genomic data analysis involve parameter estimation for high-dimensional multivariate distributions, with typically unknown and intricate correlation patterns among variables. addressing these inference questions satisfactorily requires: (i) an intensive and thorough search of the parameter space to generate good candidate estimators; (ii) an approach for selecting an optimal estimator among these candidates; and (iii) a method for reliably assessing the performance of the resulting estimator. we propose a unified loss-based methodology for estimator construction, selection, and performance assessment with cross-validation. in this approach, the parameter of interest is defined as the risk minimizer for a suitable loss function and candidate estimators are generated using this (or possibly another) loss function. cross-validation is applied to select an optimal estimator among the candidates and to assess the overall performance of the resulting estimator. this general estimation framework encompasses a number of problems which have traditionally been treated separately in the statistical literature, including multivariate outcome prediction and density estimation based on either uncensored or censored data. this article provides an overview of the methodology and describes its application to the prediction of biological and clinical outcomes (possibly censored) using microarray gene expression measures.
a machine learning approach for the curation of biomedical literature - kdd cup 2002 (task 1). in this paper, we present an automated text classification system for the classification of biomedical papers. this classification is based on whether there is experimental evidence for the expression of molecular gene products for specified genes within a given paper. the system performs pre-processing and data cleaning, followed by feature extraction from the raw text. it subsequently classifies the paper using the extracted features with a na&iuml;ve bayes classifier. our approach has made it possible to classify (and curate) biomedical papers automatically, thus potentially saving considerable time and resources.
interactive mining and knowledge reuse for the closed-itemset incremental-mining problem. using concept lattices as a theoretical background for finding association rules [11] has led to designing algorithms like charm [10], close [7] or closet [8]. while they are considered as extremely appropriate when finding concepts for association rules, due to the smaller amount of results, they do not cover a certain area of significant results, namely the pseudo-intents that form the base for global implications. we have proposed an approach that, besides finding all proper partial implications, also finds the pseudo-intents. the way our algorithm is devised, it allows certain important operations on concept lattices, like adding or extracting items, meaning we can reuse previously found results. it is a well-known fact that mining association rules may lead to a large amount of results. since, the mining results are meant to be understood by the user, we have come to the conclusion that he will benefit more from starting small, with some of the items in the data base, understand a small amount of results, and then add items receiving only the extra-results. this way the number of human interventions during the "full" mining process is increased and the process becomes user-driven.
multi-relational data mining: an introduction. data mining algorithms look for patterns in data. while most existing data mining approaches look for patterns in a single data table, multi-relational data mining (mrdm) approaches look for patterns that involve multiple tables (relations) from a relational database. in recent years, the most common types of patterns and approaches considered in data mining have been extended to the multi-relational case and mrdm now encompasses multi-relational (mr) association rule discovery, mr decision trees and mr distance-based methods, among others. mrdm approaches have been successfully applied to a number of problems in a variety of areas, most notably in the area of bioinformatics. this article provides a brief introduction to mrdm, while the remainder of this special issue treats in detail advanced research topics at the frontiers of mrdm.
comparison of graph-based and logic-based multi-relational data mining. we perform an experimental comparison of the graph-based multi-relational data mining system, subdue, and the inductive logic programming system, cprogol, on the mutagenesis dataset and various artificially generated bongard problems. experimental results indicate that subdue can significantly outperform cprogol while discovering structurally large multi-relational concepts. it is also observed that cprogol is better at learning semantically complicated concepts and it tends to use background knowledge more effectively than subdue. an analysis of the results indicates that the differences in the performance of the systems are a result of the difference in the expressiveness of the logic-based and the graph-based representations. the ability of graph-based systems to learn structurally large concepts comes from the use of a weaker representation whose expressiveness is intermediate between propositional and first-order logic. the use of this weaker representation is advantageous while learning structurally large concepts but it limits the learning of semantically complicated concepts and the utilization background knowledge.
multi-relational data mining 2004: workshop report. in this report we briefly review the 3rd workshop on multi-relational data mining (mrdm-2004), which was organized by the authors and held in seattle, wa, on august 22, as part of the workshop program of the tenth acm sigkdd international conference on knowledge discovery and data mining. the goal of the workshop was to bring together researchers and practitioners of data mining and interested in methods and applications of finding patterns in expressive languages from multi-relational, complex, and/or structured data.
the 5th international workshop on multimedia data mining (mdm/kdd2004). in this short report we summarize the presentations, conclusions and directions of future work that were discussed during mdm/kdd2004 workshop, held in conjunction with the 11th acm sigkdd international conference on knowledge discovery and data mining, august 22, 2004 at seattle, washington, usa.
multi-relational data mining: a workshop report. in this report, we briefly review the multi-relational data mining workshop, which was held in edmonton, canada on july, 23, 2002 as part of the workshop program of the 8th acm sigkdd international conference on knowledge discovery and data mining (kdd-02).
kdd-2006 workshop report: theory and practice of temporal data mining. in this paper we provide a summary of the workshop on theory and practice of temporal data mining held in conjunction with acm sigkdd 2006, on august 20st in philadelphia, pennsylvania, usa. we report in detail about the research issues addressed in the talks at the workshop.
multirelational data mining 2003: workshop report. in this report, we briefly review the second international workshop on multi-relational data mining (mrdm-03), which was organized by the authors and held in washington, d.c. on august 27th, 2003 as part of the workshop program of the ninth acm sigkdd international conference on knowledge discovery and data mining (kdd-03). the goal of the workshop was to bring together researchers and practitioners of data mining and interested in methods and applications of finding patterns in expressive languages from multi-relational, complex and/or structured data.
one class svm for yeast regulation prediction. in this paper, we outline the main steps leading to the development of the winning solution for task 2 of kdd cup 2002 (yeast gene regulation prediction). our unusual solution was a pair of linear classifiers in high dimensional space (&sim;14,000), developed with just 38 and 84 training examples, respectively, all belonging to the target class only. the classifiers were built using the support vector machine approach outlined in the paper.
combining data and text mining techniques for yeast gene regulation prediction: a case study. in order to solve task 2 of the kdd cup 2002, we exploited various available information sources. in particular, use of relational information describing the interactions among genes and information automatically extracted from scientific abstracts improves the accuracy of our predictions.
service quality improvement through business process management based on data mining. to improve the quality of service, internal business processes should be managed like the intermediate products are controlled for quality of final products in the manufacturing industry. the business process management (bpm) aims to improve processes and requires both analysis and evaluation of practices. in this paper, we introduce the voice of call center customers (voc) as a data source for bpm in the service industry. we adopt a voc management framework that acquires data about business processes performance and quality of services. we develop a web-based system for analyzing the voc of a life insurance company, which helps decision makers understand customer needs better and helps them make consistent decisions regarding customer support. it uses conventional statistical and data mining techniques to identify customer voice patterns. we gather actual customer complaints from the service operation of the target company. using this data, the system pinpoints problematic areas where complaints happened, the relationship among problems, and the root cause of problems.
why so many clustering algorithms: a position paper. we argue that there are many clustering algorithms, because the notion of "cluster" cannot be precisely defined. clustering is in the eye of the beholder, and as such, researchers have proposed many induction principles and models whose corresponding optimization problem can only be approximately solved by an even larger number of algorithms. therefore, comparing clustering algorithms, must take into account a careful understanding of the inductive principles involved.
quick and dirty quantum predictions with firmplus. in this paper, we describe our approach to the quantum physics classification problem posed in kdd cup 2004. we used our firmplus recursive partitioning random tree approach to classify the two particle types. we spent almost no time tuning parameters, which made our 3rd place finish somewhat surprising.
randomization in privacy-preserving data mining. suppose there are many clients, each having some personal information, and one server, which is interested only in aggregate, statistically significant, properties of this information. the clients can protect privacy of their data by perturbing it with a randomization algorithm and then submitting the randomized version. the randomization algorithm is chosen so that aggregate properties of the data can be recovered with sufficient precision, while individual entries are significantly distorted. how much distortion is needed to protect privacy can be determined using a privacy measure. several possible privacy measures are known; finding the best measure is an open question. this paper presents some methods and results in randomization for numerical and categorical data, and discusses the issue of measuring privacy.
generalized naive bayes classifiers. this paper presents a generalization of the naive bayes classifier. the method is specifically designed for binary classification problems commonly found in credit scoring and marketing applications. the generalized naive bayes classifier turns out to be a powerful tool for both exploratory and predictive analysis. it can generate accurate predictions through a flexible, non-parametric fitting procedure, while being able to uncover hidden patterns in the data. in this paper, the generalized naive bayes classifier and the original bayes classifier will be demonstrated. also, important ties to logistic regression, the generalized additive model (gam), and weight of evidence will be discussed.
the inference problem: a survey. access control models protect sensitive data from unauthorized disclosure via direct accesses, however, they fail to prevent indirect accesses. indirect data disclosure via inference channels occurs when sensitive information can be inferred from non-sensitive data and metadata. inference channels are often low-bandwidth and complex; nevertheless, detection and removal of inference channels is necessary to guarantee data security. this paper presents a survey of the current and emerging research in data inference control and emphasizes the importance of targeting this so often overlooked problem during database security design.
applying data mining to intrusion detection: the quest for automation, efficiency, and credibility. intrusion detection is an essential component of the layered computer security mechanisms. it requires accurate and efficient models for analyzing a large amount of system and network audit data. this paper is an overview of our research in applying data mining techniques to build intrusion detection models. we describe a framework for mining patterns from system and network audit data, and constructing features according to analysis of intrusion patterns. we discuss approaches for improving the run-time efficiency as well as the credibility of detection models. we report the ideas, algorithms, and prototype systems we have developed, and discuss open research problems.
introduction to the special issue on data mining for health informatics. one of the holy grails of medical research in the next decade is what is often called "personalized" medicine. the goal is to individualize therapy and treatment options, and even prevention strategies. this movement is fueled by the rapid advances made in high-throughput biotechnologies. prime examples include snp (single nucleotide polymorphisms) chips and cgh (comparative genomic hybridization) arrays for dna profiling, oligonucleotide arrays for mrna expression, and advanced mass spectrometry for peptide/protein and metabolite quantitation.
exploiting succinct constraints using fp-trees. since its introduction, frequent-set mining has been generalized to many forms, which include constrained data mining. the use of constraints permits user focus and guidance, enables user exploration and control, and leads to effective pruning of the search space and efficient mining of frequent itemsets. in this paper, we focus on the use of succinct constraints. in particular, we propose a novel algorithm called fps to mine frequent itemsets satisfying succinct constraints. the fps algorithm avoids the generate-and-test paradigm by exploiting succinctness properties of the constraints in a fp-tree based framework. in terms of functionality, our algorithm is capable of handling not just the succinct aggregate constraint, but any succinct constraint in general. moreover, it handles multiple succinct constraints. in terms of performance, our algorithm is more efficient and effective than existing fp-tree based constrained frequent-set mining algorithms.
"in vivo" spam filtering: a challenge problem for kdd. spam, also known as unsolicited commercial email (uce), is the bane of email communication. many data mining researchers have addressed the problem of detecting spam, generally by treating it as a static text classification problem. true in vivo spam filtering has characteristics that make it a rich and challenging domain for data mining. indeed, real-world datasets with these characteristics are typically difficult to acquire and to share. this paper demonstrates some of these characteristics and argues that researchers should pursue in vivo spam filtering as an accessible domain for investigating them.
kdd-99 classifier learning contest: llsoft's results overview. kernel miner is a new data-mining tool based on building the optimal decision forest. the tool won second place in the kdd99 classifier learning contest, august 1999. we describe the kernel miner's approach and method used for solving the contest task. the received results are analyzed and explained.
kdd-cup 2004: protein homology task. in this paper we describe the winning model for the performance measure "lowest ranked homologous sequence" (rkl). this was a subtask of the protein homology prediction task of the kdd cup 2004. the goal was to predict protein homology for different performance metrics. the given data was organized in blocks, each of which corresponds to a specific native sequence. the two metrics average precision (apr) and rkl explicitly make use of this block structure. our solution consists of two parts. the first one is a global classification svm not aware of the block structure. the second part is a k-nearestneighbor scheme for block similarity, used to train ranking svms on the fly. furthermore, we sketch our approach to optimize the root-mean-squared-error and report some alternative solutions that turned out to be suboptimal.
a survey on wavelet applications in data mining. recently there has been significant development in the use of wavelet methods in various data mining processes. however, there has been written no comprehensive survey available on the topic. the goal of this is paper to fill the void. first, the paper presents a high-level data-mining framework that reduces the overall process into smaller components. then applications of wavelets for each component are reviewd. the paper concludes by discussing the impact of wavelets on data mining research and outlining potential future research directions and applications.
distributed higher order association rule mining using information extracted from textual data. the burgconing amount of textual data in distributed sources combined with the obstacles involved in creating and maintaining central repositories motivates the need for effective distributed information extraction and mining techniques. recently, as the need to mine patterns across distributed databases has grown, distributed association rule mining (d-arm) algorithms have been developed. these algorithms, however, assume that the databases are either horizontally or vertically distributed. in the special case of databases populated from information extracted from textual data, existing d-arm algorithms cannot discover rules based on higher-order associations between items in distributed textual documents that are neither vertically nor horizontally distributed, but rather a hybrid of the two. in this article we present d-hotm, a framework for distributed higher order text mining. d-hotm is a hybrid approach that combines information extraction and distributed data mining. we employ a novel information extraction technique to extract meaningful entities from unstructured text in a distributed environment. the information extracted is stored in local databases and a mapping function is applied to identify globally unique keys. based on the extracted information, a novel distributed association rule mining algorithm is applied to discover higher-order associations between items (i.e., entities) in records fragmented across the distributed databases using the keys. unlike existing algorithms, d-hotm requires neither knowledge of a global schema nor that the distribution of data be horizontal or vertical. evaluation methods are proposed to incorporate the performance of the mapping function into the traditional support metric used in arm evaluation. an example application of the algorithm on distributed law enforcement data demonstrates the relevance of d-hotm in the fight against terrorism.
a critical review of multi-objective optimization in data mining: a position paper. this paper addresses the problem of how to evaluate the quality of a model built from the data in a multi-objective optimization scenario, where two or more quality criteria must be simultaneously optimized. a typical example is a scenario where one wants to maximize both the accuracy and the simplicity of a classification model or a candidate attribute subset in attribute selection. one reviews three very different approaches to cope with this problem, namely: (a) transforming the original multi-objective problem into a single-objective problem by using a weighted formula; (b) the lexicographical approach, where the objectives are ranked in order of priority; and (c) the pareto approach, which consists of finding as many non-dominated solutions as possible and returning the set of non-dominated solutions to the user. one also presents a critical review of the case for and against each of these approaches. the general conclusions are that the weighted formula approach -- which is by far the most used in the data mining literature -- is to a large extent an ad-hoc approach for multi-objective optimization, whereas the lexicographic and the pareto approach are more principled approaches, and therefore deserve more attention from the data mining community.
chinese named entity recognition using lexicalized hmms. this paper presents a lexicalized hmm-based approach to chinese named entity recognition (ner). to tackle the problem of unknown words, we unify unknown word identification and ner as a single tagging task on a sequence of known words. to do this, we first employ a known-word bigram-based model to segment a sentence into a sequence of known words, and then apply the uniformly lexicalized hmms to assign each known word a proper hybrid tag that indicates its pattern in forming an entity and the category of the formed entity. our system is able to integrate both the internal formation patterns and the surrounding contextual clues for ner under the framework of hmms. as a result, the performance of the system can be improved without losing its efficiency in training and tagging. we have tested our system using different public corpora. the results show that lexicalized hmms can substantially improve ner performance over standard hmms. the results also indicate that character-based tagging (viz. the tagging based on pure single-character words) is comparable to and can even outperform the relevant known-word based tagging when a lexicalization technique is applied.
kdd cup-2005 report: facing a great challenge. the kdd-cup 2005 competition was held in conjunction with the eleventh acm sigkdd international conference on knowledge discovery and data mining. the task of the kdd-cup 2005 competition was to classify 800,000 internet user search queries into 67 predefined categories. this task is easy to understand, but the lack of straightforward training set, subjective user intents of queries, poor information in short queries, and high noise level make the task very challenge.in this paper, we summarize the competition task, the evaluation method, and the results of the competition. here we only highlight some key techniques used in submitted solutions. the technical details of the solutions from the three award winning teams are available in their papers separately in this issue of sigkdd explorations. at the end, we also share the results of a survey conducted with this year's cup participants. to facilitate research in this area, the task description, data, answer set, and related information of this kdd-cup are published at the kdd-cup 2005 web site: http://www.acm.org/sigs/sigkdd/kdd2005/kddcup.html.
a block-based support vector machine approach to the protein homology prediction task in kdd cup 2004. this paper describes our solution for the protein homology prediction task in kdd cup 2004 competition. this task is modeled as a supervised learning problem with multiple performance metrics. several key characteristics make the problem both novel and challenging, including the concept of data blocks and the presence of large-scale and imbalanced training data. these features make a naive application of the traditional classification algorithms infeasible. our approach focuses on making full use of the abundant information within the blocks, and developing a new technique for reducing and balancing training data to make the support vector machine applicable to this kind of large-scale and imbalanced learning tasks.
extracting statistical data frames from text. we present a framework that bridges the gap between natural language processing (nlp) and text mining. central to this is a new approach to text parameterization that captures many interesting attributes of text usually ignored by standard indices, like the term-document matrix. by storing nlp tags, the new index supports a higher degree of knowledge discovery and pattern finding from text. the index is relatively compact, enabling dynamic search of arbitrary relationships and events in large document collections. we can export search results in formats and data structures that are transparent to statistical analysis tools like s-plusid&reg;. in a number of experiments, we demonstrate how this framework can turn mountains of unstructured information into informative statistical graphs.
classification of heterogeneous gene expression data. recent advanced technologies in dna microarray analysis are intensively applied in disease classification, especially for cancer classification. most recent proposed gene expression classifiers can successfully classify testing samples obtained from the same microarray experiment as training samples with the assumption that the symmetric errors are constant among training and testing samples. however, the classification performance is degraded with heterogeneous testing samples obtained from different microarray experiments. in this paper, we propose the "impact factors" (ifs) to measure the variations between individual classes in training samples and heterogeneous testing samples, and integrate the ifs to classifiers for classification of heterogeneous samples. two publicly available lung adenocarcinomas gene expression data sets are used in our experiments to demonstrate the effectiveness of the ifs. it shows that, with the integration of the ifs to the golub and slonim (gs) and k-nearest neighbors (knn) classifiers, the classifiers can be further improved on the classification accuracy of heterogeneous samples. even more, the classification accuracy of the integrated gs classifier is around 90%.
using unsupervised link discovery methods to find interesting facts and connections in a bibliography dataset. this paper describes a submission to the open task of the 2003 kdd cup. for this task contestants were asked to devise their own questions about the hep-th bibliography dataset, and the most interesting result would be selected as the winner. instead of taking a more traditional approach such as starting with a inspection of the data, formulating questions or hypotheses interesting to us and then devising an analysis and approach to answer these questions, we tried to go a different route: can we develop a program that automatically finds interesting facts and connections in the data?to do this we developed a set of unsupervised link discovery methods that compute interestingness based on a notion of "rarity" and "abnormality". the experiments performed on the hep-th dataset show that our approaches are able to automatically uncover interesting hidden connections (e.g. significant relationships between people) and unexpected facts (e.g. citation loops) without the support of any prerequisite knowledge or training examples. the interestingness of some of our results is self-evident. for others we were able to verify them by looking for supporting evidence on the world-wide-web, which shows that our methods can find connections between entities that actually are interestingly connected in the real world in an unsupervised way.
subspace clustering for high dimensional categorical data. data clustering has been discussed extensively, but almost all known conventional clustering algorithms tend to break down in high dimensional spaces because of the inherent sparsity of the data points. existing subspace clustering algorithms for handling high-dimensional data focus on numerical dimensions. in this paper, we designed an iterative algorithm called subcad for clustering high dimensional categorical data sets, based on the minimization of an objective function for clustering. we deduced some cluster memberships changing rules using the objective function. we also designed an objective function to determine the subspace associated with each cluster. we proved various properties of this objective function that are essential for us to design a fast algorithm to find the subspace associated with each cluster. finally, we carried out some experiments to show the effectiveness of the proposed method and the algorithm.
editorial: special issue on web content mining. with the phenomenal growth of the web, there is an everincreasing volume of data and information published in numerous web pages. the research in web mining aims to develop new techniques to effectively extract and mine useful knowledge or information from these web pages [8]. due to the heterogeneity and lack of structure of web data, automated discovery of targeted or unexpected knowledge/information is a challenging task. it calls for novel methods that draw from a wide range of fields spanning data mining, machine learning, natural language processing, statistics, databases, and information retrieval. in the past few years, there was a rapid expansion of activities in the web mining field, which consists of web usage mining, web structure mining, and web content mining. web usage mining refers to the discovery of user access patterns from web usage logs. web structure mining tries to discover useful knowledge from the structure of hyperlinks. web content mining aims to extract/mine useful information or knowledge from web page contents. for this special issue, we focus on web content mining.
mining data streams under block evolution. in this paper we survey recent work on incremental data mining model maintenance and change detection under block evolution. in block evolution, a dataset is updated periodically through insertions and deletions of blocks of records at a time. we describe two techniques: (1) we describe a generic algorithm for model maintenance that takes any traditional incremental data mining model maintenance algorithm and transforms it into an algorithm that allows restrictions on a temporal subset of the database. (2) we also describe a generic framework for change detection, that quantifies the difference between two datasets in terms of the data mining models they induce.
a survey of kernels for structured data. kernel methods in general and support vector machines in particular have been successful in various learning tasks on data represented in a single table. much 'real-world' data, however, is structured - it has no natural representation in a single table. usually, to apply kernel methods to 'real-world' data, extensive pre-processing is performed to embed the data into areal vector space and thus in a single table. this survey describes several approaches of defining positive definite kernels on structured instances directly.
support vector machines classification with a very large-scale taxonomy. very large-scale classification taxonomies typically have hundreds of thousands of categories, deep hierarchies, and skewed category distribution over documents. however, it is still an open question whether the state-of-the-art technologies in automated text categorization can scale to (and perform well on) such large taxonomies. in this paper, we report the first evaluation of support vector machines (svms) in web-page classification over the full taxonomy of the yahoo! categories. our accomplishments include: 1) a data analysis on the yahoo! taxonomy; 2) the development of a scalable system for large-scale text categorization; 3) theoretical analysis and experimental evaluation of svms in hierarchical and non-hierarchical settings for classification; 4) an investigation of threshold tuning algorithms with respect to time complexity and their effect on the classification accuracy of svms. we found that, in terms of scalability, the hierarchical use of svms is efficient enough for very large-scale classification; however, in terms of effectiveness, the performance of svms over the yahoo! directory is still far from satisfactory, which indicates that more substantial investigation is needed.
mining biologically active patterns in metabolic pathways using microarray expression profiles. we present a new probabilistic framework for analyzing a metabolic pathway with microarray expression profiles. our purpose is to find biologically significant paths and patterns in a given metabolic pathway. our approach first builds a markov model using a graph structure of a known metabolic pathway, and then estimates parameters of a mixture of the markov models using microarray data, based on an em algorithm. in our experiments, we used a main pathway of glycolysis to evaluate the effectiveness of our method. we first measured the performance of our method comparing with that of another method, in a supervised learning manner, and found that our method significantly outperformed another method, which was trained by microarray data only. we further analyzed the trained models and obtained a number of new biological findings on frequent patterns (paths) and long-range correlations in a metabolic pathway.
5th international workshop on knowledge discovery in inductive databases (kdid'06): workshop report. this report presents a review of the 5th international workshop on knowledge discovery in inductive databases (kdid'06), which was organized by the authors and held in berlin, germany, on september 18, 2006, in conjunction with ecml/pkdd'06, the 17th european conference on machine learning and the 10th european conference on principles and practice of knowledge discovery in databases. the goal of the workshop was to bring together the researchers that are interested in the area of inductive databases, inductive queries, constraint-based data mining, and data mining query languages.
data mining methods for anomaly detection kdd-2005 workshop report. for many applications, data mining systems are required to detect anomalous (abnormal, unmodeled, or unexpected) observations. this has so far proven to be a difficult challenge because anomalies are usually considered to be "non-normal" observations, where "normality" is typically defined by very complex concepts. because of these and other reasons, there are no standard and principled approaches for anomaly detection, yet, and the data mining processes that have led to successful solutions include most of the times ad-hoc (algorithmic, design, and implementation) decisions that incorporate prior or commonsense knowledge about the tasks that are addressed.consequently, we considered that it would be beneficial for both researchers and practitioners interested in anomaly detection and data mining, to organize workshop that would bring together people interested in this topic. we considered that the international conference on knowledge discovery and data mining would be a good venue for such a workshop because of the diversity of interests, backgrounds, and problems that motivate people to attend the conference.this paper describes the workshop on "data mining methods for anomaly detection" - a one day event held in conjunction with kdd-2005 in chicago, on august 21, 2005.
webkdd-99: workshop on web usage analysis and user profiling. the webkdd'99 workshop on "web usage analysis and user profiling" took place at aug. 15, 1999 under the auspices of the sigkdd international conference on knowledge discovery and data mining (kdd'99). we report on the topics addressed in the workshop, the contributions and the discussions that took place in its framework.
webkdd 2002 - web mining for usage patterns & profiles. in this paper, we provide a summary of the webkdd 2002 workshop, whose theme was 'web mining for usage patterns and profiles'. this workshop was held in conjunction with the acm sigkdd international conference on knowledge discovery and data mining (kdd-2002).
phenomenal data mining: from data to phenomena. phenomenal data mining finds relations between the data and the phenomena that give rise to data rather than just relations among the data.for example, suppose supermarket cash register data does not identify cash customers. nevertheless, there really are customers, and these customers are characterized by sex, age, ethnicity, tastes, income distribution, and sensitivity to price changes. a data mining program might be able to identify which baskets of purchases are likely to have been made by the same customers. in this example, the receipts are the data, and the customers are phenomena not directly represented in the data. once the "baskets" of purchases are grouped by customer, the way is open to infer further phenomena about the customers, e.g. their sex, age, etc.this article concerns what can be inferred by programs about phenomena from data and what facts are relevant to doing this. we work mainly with the supermarket example, but the idea is general.in order to infer phenomena from data, facts about their relations must be supplied. sometimes these facts can be implicit in the programs that look for the phenomena, but more generality is achieved if the facts are represented as sentences of logic in a knowledge base used by the programs. the result of phenomenal data-mining might include an extended database with additional fields on existing relations and new relations. thus the relations describing supermarket baskets might be extended with a customer field, and new relations about customers and their properties might be introduced.
exploiting relational structure to understand publication patterns in high-energy physics. we analyze publication patterns in theoretical high-energy physics using a relational learning approach. we focus on four related areas: understanding and identifying patterns of citations, examining publication patterns at the author level, predicting whether a paper will be accepted by specific journals, and identifying research communities from the citation patterns and paper text. each of these analyses contributes to an overall understanding of theoretical high-energy physics.
a preprocessing scheme for high-cardinality categorical attributes in classification and prediction problems. categorical data fields characterized by a large number of distinct values represent a serious challenge for many classification and regression algorithms that require numerical inputs. on the other hand, these types of data fields are quite common in real-world data mining applications and often contain potentially relevant information that is difficult to represent for modeling purposes.this paper presents a simple preprocessing scheme for high-cardinality categorical data that allows this class of attributes to be used in predictive models such as neural networks, linear and logistic regression. the proposed method is based on a well-established statistical method (empirical bayes) that is straightforward to implement as an in-database procedure. furthermore, for categorical attributes with an inherent hierarchical structure, like zip codes, the preprocessing scheme can directly leverage the hierarchy by blending statistics at the various levels of aggregation.while the statistical methods discussed in this paper were first introduced in the mid 1950's, the use of these methods as a preprocessing step for complex models, like neural networks, has not been previously discussed in any literature.
discovering geographic knowledge in data rich environments: a report on a specialist meeting. on 18--20 march 1999, a specialist meeting on "discovering geographic knowledge in data-rich environments" was convened under the auspices of the varenius project of the national center for geographic information and analysis (ncgia). this, workshop brought together a diverse group of researchers and practitioners with interests in developing and applying new techniques for exploring large and diverse geographic datasets. the interaction prior to, during and after the three-day workshop resulted in the identification of research priorities and directions for continued development of "geographic knowledge discovery" (gkd) theory techniques.
mining knowledge from text using information extraction. an important approach to text mining involves the use of natural-language information extraction. information extraction (ie) distills structured data or knowledge from unstructured text by identifying references to named entities as well as stated relationships between such entities. ie systems can be used to directly extricate abstract knowledge from a text corpus, or to extract concrete data from a set of documents which can then be further analyzed with traditional data-mining techniques to discover more general patterns. we discuss methods and implemented systems for both of these approaches and summarize results on mining real text corpora of biomedical abstracts, job announcements, and product descriptions. we also discuss challenges that arise when employing current information extraction technology to discover knowledge in text.
gene ranking using bootstrapped p-values. recent research has shown that it is possible to find genes involved in the pathogenesis of a particular condition on the basis of microarray experiments. genes which are differentially expressed, for example between healthy and diseased tissues, are likely to be relevant to the disease under study. some of the properties of microarray datasets make the task of finding these genes a challenging one. this paper proposes a gene-ranking algorithm whose main novelty is the use of bootstrapped p-values. we present an analysis of the algorithm, showing how it takes account of small-sample variability in observed values of the test statistic, in a way conventional statistical tests cannot. experimental results show that our algorithm outperforms the widely-used two-sample t-test on challenging artificial data. gene ranking is then performed on two well-known microarray datasets, with encouraging results. for example, a number of genes from one of the datasets, whose differential expression was subsequently confirmed by a more reliable biochemical analysis, are found to be ranked higher by the bootstrapped algorithm than by the conventional t-test, suggesting that the proposed algorithm may be better able to exploit the limited data available to infer biologically useful information.
a baseline feature set for learning rhetorical zones using full articles in the biomedical domain. at a time when experimental throughput in the field of molecular biology is increasing, it is necessary for biologists and people working in related fields to have access to sophisticated tools to enable them to efficiently process large amounts of information in order to stay abreast of current research.rhetorical zone analysis is an application of natural language processing in which areas of text in scientific papers are classified in terms of argumentation and intellectual contribution in order to pinpoint and distinguish certain types of information. such analysis can be employed to assist in information extraction, helping to assess and integrate data generated by experiments into the scientific community's store of knowledge.we present results for several experiments in automatic zone identification on the zaisa-1 dataset, a new dataset composed of full biomedical research papers hand-annotated for rhetorical zones. we concentrate on general purpose and linguistically motivated features, and report results for a variety of sets of features. it is our intention to provide a baseline feature set for modeling, which can be extended in future work using combinations of heuristics and more sophisticated and task-specific modeling techniques.
a novel approach to determine normal variation in gene expression data. animal models for human diseases are of crucial importance for studying gene expression and regulation. in the last decade the development of mouse models for cancer, diabetes, neuro-degenerative and many other diseases has been on steady rise. microarray analysis of patterns of gene expression in mouse models of various pathological types and the study of molecular level changes as a result of interventions, holds lot of promise to the understanding of biological processes involved. the genes which show normal variance across genetically identical mice are of particular interest because they could serve as a databank for possible false positives in gene expression studies in similar kind of mice. also they could provide useful insights into the biological processes behind the differential expression patterns in otherwise similar mice. our approach systematically removes variance due to experimental noise in each of the mice and then mines for normal variance among the identical mice. this analysis carried over six tissues sampled from mice, resulted in several genes which showed variations among identical mice, thus enabling a comprehensive database of normal variations in gene expression for mouse models. a large number of these genes are known to be related to stress response, hypertension and heat shock. also principal component analysis was done to visualize similarity among the mice models and within the replicates. these studies help in the design of gene expression studies in mouse models and help in validation of the results.
webkdd 2004: web mining and web usage analysis post-workshop report. in this report, we summarize the contents and outcomes of the recent webkdd 2004 workshop that was held in conjunction with the 10th acm sigkdd international conference on knowledge discovery and data mining (kdd 2004), august 22-25, 2004, in seattle, washington. we also reflect on the trend in participation levels in the webkdd series of workshops over the last six years, and indicate new directions in web mining research as reflected in the latest workshop.
webkdd 2005: web mining and web usage analysis post-workshop report. in this report, we summarize the contents and outcomes of the recent webkdd 2005 workshop on web mining and web usage analysis that was held in conjunction with the 11th acm sigkdd international conference on knowledge discovery and data mining (kdd 2005), august 21-24, 2005, in chicago, illinois. the theme of this workshop was "taming evolving, expanding and multi-faceted web clickstreams". we also reflect on possible new directions in web mining research as reflected by the discussions and the talks during the workshop.
differential expression, class discovery and class prediction using s-plus and s+arrayanalyzer. microarrays are a powerful experimental platform, allowing simultaneous studies of gene expression for thousands of genes under different experimental conditions. however there is much biological variability induced throughout the experimental process that can obscure the biological signals of interest. as such, the need for experimental design, replication and statistical rigor are now widely recognized. statistical hypothesis testing has become the accepted differential expression analysis approach and many classification and prediction methods used in class discovery and class prediction now incorporate stochastic modeling components.this paper provides a review of statistical analysis approaches to the analysis of data from microarray experiments. this includes discussion of experimental design, data management, preprocessing, differential expression, clustering and class prediction, reporting and annotation. the review is illustrated with the analysis of an experiment with 3 experimental conditions using the affymetrix murine chip mgu 74av2; and with descriptions of available functionality in the statistical analysis software s-plus and its associated module for microarray analysis, s+arrayanalyzer.
prediction and ranking algorithms for event-based network data. event-based network data consists of sets of events over time, each of which may involve multiple entities. examples include email traffic, telephone calls, and research publications (interpreted as co-authorship events). traditional network analysis techniques, such as social network models, often aggregate the relational information from each event into a single static network. in contrast, in this paper we focus on the temporal nature of such data. in particular, we look at the problems of temporal link prediction and node ranking, and describe new methods that illustrate opportunities for data mining and machine learning techniques in this context. experimental results are discussed for a large set of co-authorship events measured over multiple years, and a large corporate email data set spanning 21 months.
biological applications of multi-relational data mining. biological databases contain a wide variety of data types, often with rich relational structure. consequently multi-relational data mining techniques frequently are applied to biological data. this paper presents several applications of multi-relational data mining to biological data, taking care to cover a broad range of multi-relational data mining techniques.
association against dissociation: some pragmatic considerations for frequent itemset generation under fixed and variable thresholds. traditionally, support is considered to be the standard measure for frequent itemset generation in association rule mining. this paper provides a new measure called togetherness where dissociation among items is also considered as a parameter in the frequent itemset generation process. results of performance analysis show that association against dissociation is a more pragmatic approach and discovers truly associated candidate itemsets. second part of the paper extends this togetherness measure to the domain of variable threshold. here, like variable minimum support, a variable minimum togetherness has been proposed where this minimum value decreases as the itemset size increases. a simple and pragmatic process has been described, which can be easily implemented. it also provides ample control facilities in the hand of the users. necessary change and extension of the existing algorithms have been made to establish the concepts. here as well, results of performance analysis justify the approach.
subspace clustering for high dimensional data: a review. subspace clustering is an extension of traditional clustering that seeks to find clusters in different subspaces within a dataset. often in high dimensional data, many dimensions are irrelevant and can mask existing clusters in noisy data. feature selection removes irrelevant and redundant dimensions by analyzing the entire dataset. subspace clustering algorithms localize the search for relevant dimensions allowing them to find clusters that exist in multiple, possibly overlapping subspaces. there are two major branches of subspace clustering based on their search strategy. top-down algorithms find an initial clustering in the full set of dimensions and evaluate the subspaces of each cluster, iteratively improving the results. bottom-up approaches find dense regions in low dimensional spaces and combine them to form clusters. this paper presents a survey of the various subspace clustering algorithms along with a hierarchy organizing the algorithms by their defining characteristics. we then compare the two main approaches to subspace clustering using empirical scalability and accuracy tests and discuss some potential applications where subspace clustering could be particularly useful.
biokdd 2005 workshop report. bioinformatics is the science of managing, mining, and interpreting information from biological entities. genome sequencing projects have contributed to an exponential growth in complete and partial sequence databases. the structural genomics initiative aims to catalog the structure-function information for proteins. advances in technology such as microarrays have launched the subfield of genomics and proteomics to study the genes, proteins, and the regulatory gene expression circuitry inside the cell. what characterizes the state of the field is the flood of data that exists today or that is anticipated in the future; data that needs to be mined to help unlock the secrets of the cell. knowledge extracted from such analysis can be used effectively to better design new drugs, offer better medical care via diagnostic tests that combine information from multiple sources, and improve scientific and clinical practice.
data mining standards, services and platforms 2005 workshop report. this report is a summary of the workshop on data mining standards, services and platform, which was held at the kdd 2005 in chicago on august 21, 2005. the workshop included several presentations on the application of data mining standards in various systems and platforms, as well as presentations on recent changes to the pmml standard, an opening panel discussion and a concluding round-table forum.
constrained frequent pattern mining: a pattern-growth view. it has been well recognized that frequent pattern mining plays an essential role in many important data mining tasks. however, frequent pattern mining often generates a very large number of patterns and rules, which reduces not only the efficiency but also the effectiveness of mining. recent work has highlighted the importance of the constraint-based mining paradigm in the context of mining frequent itemsets, associations, correlations, sequential patterns, and many other interesting patterns in large databases.recently, we developed efficient pattern-growth methods for frequent pattern mining. interestingly, pattern-growth methods are not only efficient but also effective in mining with various constraints. many tough constraints which cannot be handled by previous methods can be pushed deep into the pattern-growth mining process. in this paper, we overview the principles of pattern-growth methods for constrained frequent pattern mining and sequential pattern mining. moreover, we explore the power of pattern-growth methods towards mining with tough constraints and highlight some interesting open problems.
mining logs files for data-driven system management. with advancement in science and technology, computing systems are becoming increasingly more complex with an increasing variety of heterogeneous software and hardware components. they are thus becoming increasingly more difficult to monitor, manage and maintain. traditional approaches to system management have been largely based on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. this has been well known and experienced as a cumber-some, labor intensive, and error prone process. in addition, this process is difficult to keep up with the rapidly changing environments. there is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing systems.a popular approach to system management is based on analyzing system log files. however, some new aspects of the log files have been less emphasized in existing methods from data mining and machine learning community. the various formats and relatively short text messages of log files, and temporal characteristics in data representation pose new challenges. in this paper, we will describe our research efforts on mining system log files for automatic management. in particular, we apply text mining techniques to categorize messages in log files into common situations, improve categorization accuracy by considering the temporal characteristics of log messages, and utilize visualization tools to evaluate and validate the interesting temporal patterns for system management.
p-tree classification of yeast gene deletion data. genomics data has many properties that make it different from "typical" relational data. the presence of multi-valued attributes as well as the large number of null values led us to a p-tree-based bit-vector representation in which matching 1-values were counted to evaluate similarity between genes. quantitative information such as the number of interactions was also included in the classifier. interaction information allowed us to extend the known properties of one protein with information on its interacting neighbors. different feature attributes were weighted independently. relevance of different attributes was systematically evaluated through optimization of weights using a genetic algorithm. the aroc value for the classified list was used as the fitness function for the genetic algorithm.
discovery in multi-attribute data with user-defined constraints. there has been a growing interest in mining frequent itemsets in relational data with multiple attributes. a key step in this approach is to select a set of attributes that group data into transactions and a separate set of attributes that labels data into items. unsupervised and unrestricted mining, however, is stymied by the combinatorial complexity and the quantity of patterns as the number of attributes grows. in this paper, we focus on leveraging the semantics of the underlying data for mining frequent itemsets. for instance, there are usually taxonomies in the data schema and functional dependencies among the attributes. domain knowledge and user preferences often have the potential to significantly reduce the exponentially growing mining space. these observations motivate the design of a user-directed data mining framework that allows such domain knowledge to guide the mining process and control the mining strategy. we show examples of tremendous reduction in computation by using domain knowledge in mining relational data with multiple attributes.
the 4th international workshop on multimedia data mining (mdm/kdd2003). in this short report we provide a summary of the presentations, conclusions and directions of future work that were discussed during mdm/kdd2003 workshop, held in conjunction with the 9th acm sigkdd international conference on knowledge discovery and data mining, august 27, 2003 at washington, dc, usa.
winning the kdd99 classification cup: bagged boosting. we briefly describe our approach for the kdd99 classification cup. the solution is essentially a mixture of bagging and boosting. additionally, asymmetric error costs are taken into account by minimizing the so-called conditional risk. furthermore, the standard sampling with replacement methodology of bagging was modified to put a specific focus on the smaller but expensive-if-predicted-wrongly classes.
the weka solution to the 2004 kdd cup. this short communication describes the weka solution for the 2004 kdd cup problems, mostly focusing on the bioinformatics problem, where this approach performed best among all submissions. differences were not significant for the best three submissions, though. the identical setup trained for the physics problem achieved rank nineteen, which is still reasonable.
minority report in fraud detection: classification of skewed data. this paper proposes an innovative fraud detection method, built upon existing fraud detection research and minority report, to deal with the data mining problem of skewed data distributions. this method uses backpropagation (bp), together with naive bayesian (nb) and c4.5 algorithms, on data partitions derived from minority oversampling with replacement. its originality lies in the use of a single meta-classifier (stacking) to choose the best base classifiers, and then combine these base classifiers' predictions (bagging) to improve cost savings (stacking-bagging). results from a publicly available automobile insurance fraud detection data set demonstrate that stacking-bagging performs slightly better than the best performing bagged algorithm, c4.5, and its best classifier, c4.5 (2), in terms of cost savings. stacking-bagging also outperforms the common technique used in industry (bp without both sampling and partitioning). subsequently, this paper compares the new fraud detection method (meta-learning approach) against c4.5 trained using undersampling, oversampling, and smoteing without partitioning (sampling approach). results show that, given a fixed decision threshold and cost matrix, the partitioning and multiple algorithms approach achieves marginally higher cost savings than varying the entire training data set with different class distributions. the most interesting find is confirming that the combination of classifiers to produce the best cost savings has its contributions from all three algorithms.
kdnuggets interview with usama fayyad. kdnuggets newsletter has a new section of interviews with leaders in the field. this article presents the interview with usama fayyad, president and ceo of digimine.
kdnuggets interview with jesus mena. the kdnuggets newsletter has a new section of interviews with leaders in the field. this article presents the interview with jesus mena, ceo of webminer.
cryptographic techniques for privacy-preserving data mining. research in secure distributed computation, which was done as part of a larger body of research in the theory of cryptography, has achieved remarkable results. it was shown that non-trusting parties can jointly compute functions of their different inputs while ensuring that no party learns anything but the defined output of the function. these results were shown using generic constructions that can be applied to any function that has an efficient representation as a circuit. we describe these results, discuss their efficiency, and demonstrate their relevance to privacy preserving computation of data mining algorithms. we also show examples of secure computation of data mining algorithms that use these generic constructions.
using text mining and natural language processing for health care claims processing. a health care claims processing application is introduced which processes both structured and unstructured information associated with medical insurance claims. the application makes use of a natural language processing (nlp) engine, together with application-specific knowledge, written in a concept specification language. using nlp techniques, the entities and relationships that act as indicators of recoverable claims are mined from management notes, call centre logs and patient records to identify medical claims that require further investigation. text mining techniques can then be applied to find dependencies between different entities, and to combine indicators to provide scores to individual claims. claims are scored to determine whether they involve potential fraud or abuse, or to determine whether claims should be paid by or in conjunction with other insurers or organizations. dependencies between claims and other records can then be combined to create cases. issues related to the design of the application are discussed, specifically the use of rule-based techniques which provide a capability for deeper analysis than traditionally found in statistical techniques.
classification trees for problems with monotonicity constraints. for classification problems with ordinal attributes very often the class attribute should increase with each or some of the explaining attributes. these are called classification problems with monotonicity constraints. classical decision tree algorithms such as cart or c4.5 generally do not produce monotone trees, even if the dataset is completely monotone. this paper surveys the methods that have so far been proposed for generating decision trees that satisfy monotonicity constraints. a distinction is made between methods that work only for monotone datasets and methods that work for monotone and non-monotone datasets alike.
a perspective on inductive databases. inductive databases tightly integrate databases with data mining. the key ideas are that data and patterns (or models) are handled in the same way and that an inductive query language allows the user to query and manipulate the patterns (or models) of interest.this paper proposes a simple and abstract model for inductive databases. we describe the basic formalism, a simple but fairly powerful inductive query language, some basics of reasoning for query optimization, and discuss some memory organization and implementation issues.
probabilistic logic learning. the past few years have witnessed an significant interest in probabilistic logic learning, i.e. in research lying at the intersection of probabilistic reasoning, logical representations, and machine learning. a rich variety of different formalisms and learning techniques have been developed. this paper provides an introductory survey and overview of the state-of-the-art in probabilistic logic learning through the identification of a number of important probabilistic, logical and learning concepts.
discovering informative connection subgraphs in multi-relational graphs. discovering patterns in graphs has long been an area of interest. in most approaches to such pattern discovery either quantitative anomalies, frequency of substructure or maximum flow is used to measure the interestingness of a pattern. in this paper we introduce heuristics that guide a subgraph discovery algorithm away from banal paths towards more "informative" ones. given an rdf graph a user might pose a question of the form: "what are the most relevant ways in which entity x is related to entity y?" the response to which is a subgraph connecting x to y. we use our heuristics to discover informative subgraphs within rdf graphs. our heuristics are based on weighting mechanisms derived from edge semantics suggested by the rdf schema. we present an analysis of the quality of the subgraphs generated with respect to path ranking metrics. we then conclude presenting intuitions about which of our weighting schemes and heuristics produce higher quality subgraphs.
extreme re-balancing for svms: a case study. there are many practical applications where learning from single class examples is either, the only possible solution, or has a distinct performance advantage. the first case occurs when obtaining examples of a second class is difficult, e.g., classifying sites of "interest" based on web accesses. the second situation is exemplified by the gene knock-out experiments for understanding aryl hydrocarbon receptor signalling pathway that provided the data for the second task of the kdd 2002 cup, where minority one-class svms significantly outperform models learnt using examples from both classes.this paper explores the limits of supervised learning of a two class discrimination from data with heavily unbalanced class proportions. we focus on the case of supervised learning with support vector machines. we consider the impact of both sampling and weighting imbalance compensation techniques and then extend the balancing to extreme situations when one of the classes is ignored completely and the learning is accomplished using examples from a single class.our investigation with the data for kdd 2002 cup as well as text benchmarks such as reuters newswire shows that there is a consistent pattern of performance differences between one and two-class learning for all svms investigated, and these patterns persist even with aggressive dimensionality reduction through automated feature selection. using insight gained from the above analysis, we generate synthetic data showing similar pattern of performance.
the case for anomalous link discovery. in this paper, we describe the challenges inherent to the link prediction (lp) problem in multirelational data mining, and explore the reasons why many lp models have performed poorly. we present the alternate (and complimentary) task of anomalous link discovery (ald) and qualitatively demonstrate the effectiveness of simple lp models for the ald task.
exploratory medical knowledge discovery: experiences and issues. the application of data mining and knowledge discovery techniques to medical and health datasets is a rewarding but highly challenging area. not only are the datasets large, complex, heterogeneous, hierarchical, time-varying and of varying quality but there exists asubstantial medical knowledge base which demands a robust collaboration between the data miner and the health professional(s) if useful information is to be extracted.this paper presents the experiences of the authors and others in applying exploratory data mining techniques to medical, health and clinical data. in so doing, it elicits a number of general issues and provides pointers to possible areas of future research in data mining and knowledge discovery more broadly.
what's interesting about cricket? - on thresholds and anticipation in discovered rules. despite significant progress, determining the interestingness of a rule remains a difficult problem. this short paper investigates the lessons that may be learned from analysing the (largely manual) selection of interesting statistics for cricket (or any other data rich sport) by experts. in particular, the effect of thresholds on the interestingness of rules describing events in the sporting arena is discussed. the concept of anticipation is shown also to be critical in this selection and to vary the level of interest in events that may contribute to the achievement of a threshold value during a match, thus adding a temporal dimension to interestingness. this temporal aspect can be best modelled on the single-past-branching-future model of time. as a result of this investigation, a few new general ideas are discussed that add to the research in this area. significantly, some of the new criteria are implicitly temporal in that they rely on a model of behaviour over time. the applicability of threshold values for detecting uncharacteristically poor performances are canvassed as areas of interest yet to be explored.
a bibliography of temporal, spatial and spatio-temporal data mining research. with the growth in the size of datasets, data mining has recently become an important research topic and is receiving substantial interest from both academia and industry. at the same time, a greater recognition of the value of temporal and spatial data has been evident and the first papers looking at the confluence of these two areas are starting to emerge. this short paper provides a few comments on this research and provides a bibliography of relevant research papers investigating temporal, spatial and spatio-temporal data mining.
extracting relational data from html repositories. there is a vast amount of valuable information in html documents, widely distributed across the world wide web and across corporate intranets. unfortunately, html is mainly presentation oriented and hard to query. in this paper, we develop a system to extract desired information (records) from thousands of html documents, starting from a small set of examples. duplicates in the result are automatically detected and eliminated. we propose a novel method to estimate the current coverage of results by the system, based on capture-recapture models with unequal capture probabilities. we also propose techniques for estimating the error rate of the extracted information and an interactive the technique for enhancing information quality. to evaluate the method and ideas proposed in this paper, we conducted an extensive set of experiments. our experimental results validate the effectiveness and utility of our system, and demonstrate interesting tradeoffs between running time of information extraction and coverage of results.
machine learning in low-level microarray analysis. machine learning and data mining have found a multitude of successful applications in microarray analysis, with gene clustering and classification of tissue samples being widely cited examples. low-level microarray analysis -- often associated with the pre-processing stage within the microarray life-cycle -- has increasingly become an area of active research, traditionally involving techniques from classical statistics. this paper explores opportunities for the application of machine learning and data mining methods to several important low-level microarray analysis problems: monitoring gene expression, transcript discovery, genotyping and resequencing. relevant methods and ideas from the machine learning community include semi-supervised learning, learning from heterogeneous data, and incremental learning.
data-driven modeling and prediction of acute toxicity of pesticide residues. this paper outlines and implements a concept for developing alternative tools for toxicity modeling and prediction of chemical compounds to be used for evaluation and authorization purposes of public regulatory bodies to help minimizing animal tests, costs, and time associated with registration and risk assessment processes. starting from a general problem description we address and introduce concepts of multileveled self-organization for high-dimensional modeling, model validation, model combining, and decision support within the frame of a knowledge discovery from noisy data.
learning to extract information from large domain-specific websites using sequential models. in this article we describe a novel information extraction task on the web and show how it can be solved effectively using the emerging conditional exponential models. the task involves learning to find specific goal pages on large domain-specific websites. an example of such a task is to find computer science publications starting from university root pages. we encode this as a sequential labeling problem solved using conditional random fields (crfs). these models enable us to exploit a wide variety of features including keywords and patterns extracted from and around hyperlinks and html pages, dependency among labels of adjacent pages, and existing databases of named entities in a unified probabilistic framework. this is an important advantage over previous rule-based or generative models for tackling the challenges of diversity on web data.
voting with a parameterized veto strategy: solving the kdd cup 2006 problem by means of a classifier committee. this paper presents our winner solution for the kdd cup 2006 problem. it is based on the results of three different supervised learning techniques which are then combined in a classifier committee, and finally a single solution is obtained with a voting procedure. the voting procedure assigns weights to each member of the committee according to their average performance on a ten-fold cross-validation test and it also takes into account the confidence values returned by the three algorithms. the final decision of the committee is determined by means of a parameterized veto strategy, which takes into consideration the maximal allowed error rate beside the confidence values of the committee members. the solution presented here won task 2 and became runner-up at task 1 in the competition.
resolving citations in a paper repository. in this paper, we describe our process of creating a citation graph from a given repository of physics publications in latex format. the task involved a series of information extraction, data cleaning, matching and ranking steps. this paper describes the challenges we faced along the way and the issues involved in resolving them.
modifying boosted trees to improve performance on task 1 of the 2006 kdd challenge cup. task 1 of the 2006 kdd challenge cup required classification of pulmonary embolisms (pes) using variables derived from computed tomography angiography. we present our approach to the challenge and justification for our choices. we used boosted trees to perform the main classification task, but modified the algorithm to address idiosyncrasies of the scoring criteria. the two main modifications were: 1) changing the dependent variable in the training set to account for multiple pes per patient, and 2) incorporating neighborhood information through augmentation of the set of predictor variables. both of these resulted in measurable predictive improvement. in addition, we discuss a statistically based method for setting the classification threshold.
dynamic social network analysis using latent space models. this paper explores two aspects of social network modeling. first, we generalize a successful static model of relationships into a dynamic model that accounts for friendships drifting over time. second, we show how to make it tractable to learn such models from data, even as the number of entities n gets large. the generalized model associates each entity with a point in p-dimensional euclidean latent space. the points can move as time progresses but large moves in latent space are improbable. observed links between entities are more likely if the entities are close in latent space. we show how to make such a model tractable (sub-quadratic in the number of entities) by the use of appropriate kernel functions for similarity in latent space; the use of low dimensional kd-trees; a new efficient dynamic adaptation of multidimensional scaling for a first pass of approximate projection of entities into latent space; and an efficient conjugate gradient update rule for non-linear local optimization in which amortized time per entity during an update is o(log n). we use both synthetic and real-world data on up to 11,000 entities which indicate near-linear scaling in computation time and improved performance over four alternative approaches. we also illustrate the system operating on twelve years of nips co-authorship data.
feature selection for text categorization on imbalanced data. a number of feature selection metrics have been explored in text categorization, among which information gain (ig), chi-square (chi), correlation coefficient (cc) and odds ratios (or) are considered most effective. cc and or are one-sided metrics while ig and chi are two-sided. feature selection using one-sided metrics selects the features most indicative of membership only, while feature selection using two-sided metrics implicitly combines the features most indicative of membership (e.g. positive features) and non-membership (e.g. negative features) by ignoring the signs of features. the former never consider the negative features, which are quite valuable, while the latter cannot ensure the optimal combination of the two kinds of features especially on imbalanced data. in this work, we investigate the usefulness of explicit control of that combination within a proposed feature selection framework. using multinomial na&iuml;ve bayes and regularized logistic regression as classifiers, our experiments show both great potential and actual merits of explicitly combining positive and negative features in a nearly optimal fashion according to the imbalanced data.
profiling your customers using bayesian networks. this report describes a complete knowledge discovery session using bayesware discoverer, a program for the induction of bayesian networks from incomplete data. we build two causal models to help an american charitable organization understand the characteristics of respondents to direct mail fund raising campaigns. the first model is a bayesian network induced from the database of 96,376 lapsed donors to the june '97 renewal mailing. the network describes the dependency of the probability of response to the renewal mail on a subset of the variables in the database. the second model is a bayesian network representing the dependency of the dollar amount of the gift on the variables in the same reduced database. this model is induced from the 5% of cases in the database corresponding to the respondents to the renewal campaign. the two models are used for both predicting the expected gift of a donor and understanding the characteristics of donors. these two uses can help the charitable organization to maximize the profit.
text mining for product attribute extraction. we describe our work on extracting attribute and value pairs from textual product descriptions. the goal is to augment databases of products by representing each product as a set of attribute-value pairs. such a representation is beneficial for tasks where treating the product as a set of attribute-value pairs is more useful than as an atomic entity. examples of such applications include demand forecasting, assortment optimization, product recommendations, and assortment comparison across retailers and manufacturers. we deal with both implicit and explicit attributes and formulate both kinds of extractions as classification problems. using single-view and multi-view semi-supervised learning algorithms, we are able to exploit large amounts of unlabeled data present in this domain while reducing the need for initial labeled data that is expensive to obtain. we present promising results on apparel and sporting goods products and show that our system can accurately extract attribute-value pairs from product descriptions. we describe a variety of application that are built on top of the results obtained by the attribute extraction system.
link mining applications: progress and challenges. this article reviews a decade of progress in the area of link mining, focusing on application requirements and how they have and have not yet been addressed, especially in the area of complex event detection. it discusses some ongoing challenges and suggests ideas that could be opportunities for solutions. the most important conclusion of this article is that while there are many link mining techniques that work well for individual link mining tasks, there is not yet a comprehensive framework that can support a combination of link mining tasks as needed for many real applications.
data mining for improved cardiac care. cardiovascular disease (cvd) is the single largest killer in the world. although, several cvd treatment guidelines have been developed to improve quality of care and reduce healthcare costs, for a number of reasons, adherence to these guidelines remains poor. further, due to the extremely poor quality of data in medical patient records, most of today's healthcare it systems cannot provide significant support to improve the quality of cvd care (particularly in chronic cvd situations which contribute to the majority of costs).we present remind, a probabilistic framework for reliable extraction and meaningful inference from nonstructured data. remind integrates the structured and unstructured clinical data in patient records to automatically create high-quality structured clinical data. there are two principal factors that enable remind to overcome the barriers associated with inference from medical records. first, patient data is highly redundant -- exploiting this redundancy allows us to deal with the inherent errors in the data. second, remind performs inference based on external medical domain knowledge to combine data from multiple sources and to enforce consistency between different medical conclusions drawn from the data -- via a probabilistic reasoning framework that overcomes the incomplete, inconsistent, and incorrect nature of data in medical patient records.this high-quality structuring allows existing patient records to be mined to support guideline compliance and to improve patient care. however, once remind is configured for an institution's data repository, many other important clinical applications are also enabled, including: quality assurance; therapy selection for individual patients; automated patient identification for clinical trials; data extraction for research studies; and to relate financial and clinical factors. remind provides value across the continuum of healthcare, ranging from small physician practice databases to the most complex hospital it systems, from acute cardiac care to chronic cvd management, and to experimental research studies. remind is currently deployed across multiple disease areas over a total of 5,000,000 patients across the us.
qc@ust: our winning solution to query classification in kddcup 2005. in this paper, we describe our ensemble-search based approach, q2c@ust (http://webprojectl.cs.ust.hk/q2c/), for the query classification task for the kddcup 2005. there are two aspects to the key difficulties of this problem: one is that the meaning of the queries and the semantics of the predefined categories are hard to determine. the other is that there are no training data for this classification problem. we apply a two-phase framework to tackle the above difficulties. phase i corresponds to the training phase of machine learning research and phase ii corresponds to testing phase. in phase i, two kinds of classifiers are developed as the base classifiers. one is synonym-based and the other is statistics based. phase ii consists of two stages. in the first stage, the queries are enriched such that for each query, its related web pages together with their category information are collected through the use of search engines. in the second stage, the enriched queries are classified through the base classifiers trained in phase i. based on the classification results obtained by the base classifiers, two ensemble classifiers based on two different strategies are proposed. the experimental results on the validation dataset help confirm our conjectures on the performance of the q2c@ust system. in addition, the evaluation results given by the kddcup 2005 organizer confirm the effectiveness of our proposed approaches. the best f1 value of our two solutions is 9.6% higher than the best of all other participants' solutions. the average f1 value of our two submitted solutions is 94.4% higher than the average f1 value from all other submitted solutions.
introduction to the special issue on successful real-world data mining applications. since its inception, the field of data mining and knowledge discovery from databases has been driven by the need to solve practical problems [4]. from scaling to large databases and handling noisy and high-dimensional data to finding associational patterns in grocery store transaction data, data mining is a research area rich in application [1]. despite its practical roots few case studies of data mining applications have been published. the industrial track of the annual sigkdd conference has provided one such forum, but rarely do these papers present complete descriptions of deployed systems [2]. this special issue attempts to address the gap by showcasing the choices, strategies, and lessons learned from building a real-world data mining application. in a sense this collection is a follow-up to the first workshop on data mining case studies held during icdm-2006 [3]. this issue however introduces several new papers. of the 29 papers reviewed 10 papers were accepted. the papers come from a broad range of application areas including customer relationship management, medicine, taxation, and software development.
spatial data mining to support pandemic preparedness. effective detection of and response to pandemic disease outbreaks require significant advances in data mining. contributions to the recently held siam dm 2006 workshop on spatial data mining highlighted key challenges, directions, and progress in this context. we summarize here the main themes presented at the workshop as well as promising research directions for the data mining community.
vdm@ecml/pkdd2001: the international workshop on visual data mining at ecml/pkdd 2001. this brief report presents an overview of the international workshop on visual data mining, conducted on 4 september 2001 in conjunction with the 12th european conference on machine learning (ecml'01) and 5th european conference on principles and practice of knowledge discovery in databases (pkdd'01). it includes summary of the presentations and discussions, and provides pointers to relevant resources in the area.
network reconstruction from dynamic data. over the past decade, many powerful data mining techniques have been developed to analyze temporal and sequential data. the time is now fertile for addressing problems of larger scope under the purview of temporal data mining. the fourth sigkdd workshop on temporal data mining focused on the question: what can we infer about the structure of a complex dynamical system from observed temporal data? the goals of the workshop were to critically evaluate the need in this area by bringing together leading researchers from industry and academia, and to identify promising technologies and methodologies for doing the same. we provide a brief summary of the workshop proceedings and ideas arising out of the discussions.
mining source code elements for comprehending object-oriented systems and evaluating their maintainability. data mining and its capacity to deal with large volumes of data and to uncover hidden patterns has been proposed as a means to support industrial scale software maintenance and comprehension. this paper presents a methodology for knowledge acquisition from source code in order to comprehend an object-oriented system and evaluate its maintainability. we employ clustering in order to support semi-automated software maintenance and comprehension.a model and an associated process are provided, in order to extract elements from source code; k-means clustering is then applied on these data, in order to produce system overviews and deductions. the methodology is evaluated on jboss, a very large open source application server; results are discussed and conclusions are presented together with directions for future work.
championing of an ltv model at ltc. in this paper we report on the successful implementation of a lifetime value (ltv) forecasting system at a large telecommunications company (ltc). while some research results have been reported elsewhere on the technical challenges of modeling customer value, our experience suggests that a data mining system implementation can expect to encounter several organizational challenges that can impinge on its success. we provide a background on the application, and then analyze several success factors.
supervised analysis when the number of candidate features (p) greatly exceeds the number of cases (n). new genomic and proteomic technologies provide measurements of thousands of features for each case. this provides a context for enhanced discovery and false discovery. most statistical and machine learning procedures were not developed for the p>>n setting and the literature of dna microarray studies contains many examples of mis-use of analytic and computatinal methods such a cross-validation. this paper highlights some of key aspects of p>>n problems for identifying informative features and developing accurate classifiers.
utility-based anonymization for privacy preservation with less information loss. privacy becomes a more and more serious concern in applications involving microdata. recently, efficient anonymization has attracted much research work. most of the previous methods use global recoding, which maps the domains of the quasi-identifier attributes to generalized or changed values. however, global recoding may not always achieve effective anonymization in terms of discernability and query answering accuracy using the anonymized data. moreover, anonymized data is often used for analysis. as well accepted in many analytical applications, different attributes in a data set may have different utility in the analysis. the utility of attributes has not been considered in the previous methods. in this paper, we study the problem of utility-based anonymization. first, we propose a simple framework to specify utility of attributes. the framework covers both numeric and categorical data. second, we develop two simple yet efficient heuristic local recoding methods for utility-based anonymization. our extensive performance study using both real data sets and synthetic data sets shows that our methods outperform the state-of-the-art multidimensional global recoding methods in both discernability and query answering accuracy. furthermore, our utility-based method can boost the quality of analysis using the anonymized data.
client-side web mining for community formation in peer-to-peer environments. in this paper we present a framework for forming interests-based peer-to-peer communities using client-side web browsing history. at the heart of this framework is the use of an order statistics-based approach to build communities with hierarchical structure. we have also carefully considered privacy concerns of the peers and adopted cryptographic protocols to measure similarity between them without disclosing their personal profiles. we evaluated our framework on a distributed data mining platform we have developed. the experimental results show that our framework could effectively build interests-based communities.
learning important models for web page blocks based on layout and content analysis. previous work shows that a web page can be partitioned into multiple segments or blocks, and often the importance of those blocks in a page is not equivalent. it has also been proven that differentiating noisy and unimportant blocks from pages can facilitate web mining, search and accessibility. however, no uniform approach and model has been presented to measure the importance of different blocks in a web page. through a user study, we found that people do have a consistent view about the importance of blocks in a web page. thus, we investigate how to find a model to automatically assign importance values to blocks in a web page. we formulate the block importance estimation as a learning problem. first, we use a vision-based page segmentation technique to partition a web page into semantic blocks with a hierarchical structure. then spatial features (such as position and size) and content features (such as the number of images and links) are extracted to construct a feature vector for each block. then, learning algorithms are used to train a model to assign importance to each block in the web page. in our experiments, the best model can achieve the performance with micro-f1 80.2% and micro-accuracy 86.8%.
blocking objectionable web content by leveraging multiple information sources. the world wide web has now become a humongous archive of various contents. the inordinate amount of information found on the web presents a challenge to deliver right information to the right users. on one hand, the abundant information is freely accessible to all web denizens; on the other hand, much of such information may be irrelevant or even deleterious to some users. for example, some control and filtering mechanisms are desired to prevent inappropriate or offensive materials such as pornographic websites from reaching children. ways of accessing websites are termed as access scenarios. an access scenario can include using search engines (e.g., image search that has very little textual content), url redirection to some websites, or directly typing (porn) website urls. in this paper we propose a framework to analyze a website from several different aspects or information sources, and generate a classification model aiming to accurately classify such content irrespective of access scenarios. extensive experiments are performed to evaluate the resulting system, which illustrates the promise of the proposed approach.
overview of the acm sigkdd 2004 workshops. following a tradition of several years, kdd conferences host a number of workshops on challenging topics that emerge and demand concerted research activities and intensive sharing of experiences. this short paper an one-glance overview of the 8 workshops that took place at august 22, 2004 before the official opening of kdd 2004 in seattle. the individual workshop reports follow in the next pages. complete information on the workshops including links to the individual sites can be found from the kdd 2004 web site http://www.acm.org/sigs/sigkdd/kdd2004.
closing the gap: automated screening of tax returns to identify egregious tax shelters. according to the most recent strategic plan for the united states internal revenue service (irs), high-income individuals are a primary contributor to the "tax gap," the difference between the amount of tax that should be collected and the amount of tax that actually is collected [1]. this case study addresses the use of machine learning and statistical analysis for the purpose of helping the irs target high-income individuals engaging in abusive tax shelters. kernel-based analysis of known abuse allows targeting individual taxpayers, while associative analysis allows targeting groups of taxpayers who appear to be participating in a tax shelter being promoted by a common financial advisor. unlike many kdd applications that focus on classification or density estimation, this analysis task requires estimating risk, a weighted combination of both the likelihood of abuse and the potential revenue losses.
what are the grand challenges for data mining?: kdd-2006 panel report. we discuss what makes exciting and motivating grand challenge problems for data mining, and propose criteria for a good grand challenge. we then consider possible gc problems from multimedia mining, link mining, large-scale modeling, text mining, and proteomics. this report is the result of a panel held at kdd-2006 conference.
web usage mining: discovery and applications of usage patterns from web data. web usage mining is the application of data mining techniques to discover usage patterns from web data, in order to understand and better serve the needs of web-based applications. web usage mining consists of three phases, namely preprocessing, pattern discovery, and pattern analysis. this paper describes each of these phases in detail. given its application potential, web usage mining has seen a rapid increase in interest, from both the research and practice communities. this paper provides a detailed taxonomy of the work in this area, including research efforts as well as commercial offerings. an up-to-date survey of the existing work is also provided. finally, a brief overview of the websift system as an example of a prototypical web usage mining system is given.
maximizing classifier utility when training data is costly. classification is a well-studied problem in machine learning and data mining. classifier performance was originally gauged almost exclusively using predictive accuracy. however, as work in the field progressed, more sophisticated measures of classifier utility that better represented the value of the induced knowledge were introduced. nonetheless, most work still ignored the cost of acquiring training examples, even though this affects the overall utility of a classifier. in this paper we consider the costs of acquiring the training examples in the data mining process; we analyze the impact of the cost of training data on learning, identify the optimal training set size for a given data set, and analyze the performance of several progressive sampling schemes, which, given the cost of the training data, will generate classifiers that come close to maximizing the overall utility.
biokdd06: data mining in bioinformatics. data mining is the process of automatic discovery of novel and understandable models and patterns from large amounts of data. bioinformatics is the science of storing, analyzing, and utilizing information from biological data such as sequences, molecules, gene expressions, and pathways. development of novel data mining methods will play a fundamental role in understanding these rapidly expanding sources of biological data. the extensive databases of biological information create both challenges and opportunities for developing novel data mining methods.
relevance search and anomaly detection in bipartite graphs. many real applications can be modeled using bipartite graphs, such as users vs. files in a p2p system, traders vs. stocks in a financial trading system, conferences vs. authors in a scientific publication network, and so on. we introduce two operations on bipartite graphs: 1) identifying similar nodes (relevance search), and 2) finding nodes connecting irrelevant nodes (anomaly detection). and we propose algorithms to compute the relevance score for each node using random walk with restarts and graph partitioning; we also propose algorithms to identify anomalies, using relevance scores. we evaluate the quality of relevance search based on semantics of the datasets, and we also measure the performance of the anomaly detection algorithm with manually injected anomalies. both effectiveness and efficiency of the methods are confirmed by experiments on several real datasets.
on the medical frontier: the 2006 kdd cup competition and results. the 2006 kdd cup competition featured three data mining tasks drawn from a medical imaging domain. at the core, all of these tasks were concerned with identifying pulmonary embolisms (pes) from pre-processed computed tomography (ct) images of human lungs. however, these tasks were complicated by features such as multi-instance learning, stringent performance standards, hard-threshold evaluation functions, spatial correlations, and small training sets. this paper gives an overview of the data and medical imaging tasks, the competition and evaluation, and the competition victors.
privacy-enhanced linking. while computer scientists are uniquely situated to incorporate privacy protections in the link analysis algorithms they construct, most computer scientists are unaware of this opportunity and of ways to think about achieving needed protections. the work presented in this writing introduces a new way for computer scientists to think about providing privacy protection within link analysis and introduces the notion of "privacy-enhanced linking" as algorithms that perform link analysis with guarantees of privacy protection modeled after the fair information practices. in this approach, privacy protection is realized by assessing the validity and interpretation of link analysis results such that inappropriate harm to individuals is provably minimized.
data mining for business applications: kdd-2006 workshop. even though data mining has been successful in becoming a major component of various business processes as well as in transferring innovations from academic research into the business world, the gap between the problems that the research community works on and real-world ones is still significant. we believe that it is essential for the business and the academic research communities to interact frequently. the goal of the kdd-2006 workshop on data mining for business applications was to gather both researchers and business practitioners and talk about their different perspectives and to share their latest problems and idea. we wanted to not only bring them together at kdd but also to create relationships that would continue and grow after the event as well.
data mining, national security, privacy and civil liberties. in this paper, we describe the threats to privacy that can occur through data mining and then view the privacy problem as a variation of the inference problem in databases.
ubdm 2006: utility-based data mining 2006 workshop report. in this report we provide a summary of the second international workshop on utility-based data mining (ubdm-06) held in conjunction with the 12th acm sigkdd international conference on knowledge discovery and data mining. the workshop was held on august 20, 2006 in philadelphia, pa, usa. as was the case for the first ubdm workshop, this workshop brought together researchers who currently investigate how to incorporate economic utility aspects into the data mining process and practitioners who have real-world experience with how these factors influence data mining applications.
frequent closed itemset based algorithms: a thorough structural and analytical survey. as a side effect of the digitalization of unprecedented amount of data, traditional retrieval tools proved to be unable to extract hidden and valuable knowledge. data mining, with a clear promise to provide adequate tools and/or techniques to do so, is the discovery of hidden information that can be retrieved from datasets. in this paper, we present a structural and analytical survey of <u>f</u>requent <u>c</u>losed <u>i</u>temset (fci) based algorithms for mining association rules. indeed, we provide a structural classification, in four categories, and a comparison of these algorithms based on criteria that we introduce. we also present an analytical comparison of fci-based algorithms using benchmark dense and sparse datasets as well as "worst case" datasets. aiming to stand beyond classical performance analysis, we intend to provide a focal point on performance analysis based on memory consumption and advantages and/or limitations of optimization strategies, used in the fci-based algorithms.
the third sigkdd workshop on mining temporal and sequential data (kdd/tdm 2004). in this short report, we provide a summary of the results, issues, and research directions on mining temporal and sequential data, discussed in tdm-2004, held in conjunction with the 10-th acm sigkdd international conference on knowledge discovery and data mining (kdd-2004) on august 22, 2004 in seattle, washington, u.s.a.
parameter optimized, vertical, nearest-neighbor-vote and boundary-based classification. in this paper, we describe a reliable high performance classification system that includes a nearest neighbor vote based classification and a local decision boundary based classification combined with an evolutionary algorithm for parameter optimization and a vertical data structure (predicate tree or p-tree1 for processing efficiency.
predicting the effects of gene deletion. in this paper, we describe techniques that can be used to predict the effects of gene deletion. we will focus mainly on the creation of predictive variables, and then briefly discuss different modeling techniques that have been used successfully on this data.
webkdd 2006: web mining and web usage analysis post-workshop report. in this report, we summarize the contents and outcomes of the recent webkdd 2006 workshop on web mining and web usage analysis that was held in conjunction with the 12th acm sigkdd international conference on knowledge discovery and data mining (kdd 2006), august 20-23, 2006, in philadelphia, pennsylvania. in 2006, webkdd was organized for the eighth time. it solicited papers on the broad overview subject "knowledge discovery on the web" and on new directions for web mining research. we reflect on the results of the workshop, as captured in presentations and plenary discussions.
unsupervised pattern mining from symbolic temporal data. we present a unifying view of temporal concepts and data models in order to categorize existing approaches for unsupervised pattern mining from symbolic temporal data. in particular we distinguish time point-based methods and interval-based methods as well as univariate and multivariate methods. the mining paradigms and the robustness of many proposed approaches are compared to aid the selection of the appropriate method for a given problem. for time points, sequential pattern mining algorithms can be used to express equality and order of time points with gaps in multivariate data. for univariate data and limited gaps suffix tree methods are more efficient. recently, efficient algorithms have been proposed to mine the more general concept of partial order from time points. for time interval data with precise start and end points the relations of allen can be used to formulate patterns. the recently proposed time series knowledge representation is more robust on noisy data and offers an alternative semantic that avoids ambiguity and is more expressive. for both pattern languages efficient mining algorithms have been proposed.
interview with simon funk. interview with simon funk -- a netflix prize leader, an outstanding hacker, and an original thinker.
anti-matter detection: particle physics model for kdd cup 2004. what is the difference between matter and anti-matter? a. i. insight's winning solution on the particle physics task for the 2004 kdd cup demonstrates how an accurate predictive model can be formulated without knowledge of the content of the data. information on the data was not available for the modeling, including a description on the outcome to be predicted. in other words, an 80 x 150,000 grid of numbers with the header "particle physics" was all that was given to the 500+ registrants of this competition. key steps in creating the winning model were interactive analysis of the variables, detection of interactions, a powerful self-organizing neural network, and customization of the 4 different error criteria.
the problem of disguised missing data. missing data is a well-recognized problem in large datasets, widely discussed in the statistics and data analysis literature. many programming environments provide explicit codes for missing data, but these are not standardized and are not always used. this lack of standardization is one of the leading causes of the subtle problem of disguised missing data, in which unknown, inapplicable, or otherwise nonspecified responses are encoded as valid data values. following a brief overview of the problem of explicitly coded missing data, this paper discusses sources, consequences, and detection of disguised missing data, including two real-world examples. as the first of these examples illustrates, the consequences of disguised missing data can be quite serious. the key to its detection lies in first, recognizing disguised missing data as a possibility and second, finding a sufficiently informative view of the data to reveal its presence.
protein matching with custom neural network objective functions. this 2004 kdd cup presents a perfect case where the usual neural network objective functions do not apply. while the contest problem consisted of 4 different entries with 4 different objective functions, this paper will focus on the solution optimizing grmse (grouped root mean squared error). it will be shown that the more typical objective functions (including rmse) cannot be as effective at meeting this criteria. while this objective function may be specific to this problem, and the reader may never see this exact function again in his/her lifetime, the idea behind this paper is applicable in many situations. too often neural networks are used to minimize sse (sum of the squares of the errors) or cross entropy, when the true measure of success for the model may require a small coding change to the neural network objective function. it is shown in this paper that a few small coding changes can make a big difference on a model's performance.
kdd/mdm 2006: the 7 kdd multimedia data mining workshop report. this is a report of the 7th acm kdd/mdm workshop on multimedia data mining held in philadelphia, pa, usa, on 20 august 2006. this report outlines the motivations to hold the workshop, the response we have received in terms of paper submissions and participations, as well as the post-workshop events. the central theme of this year's mdm workshop is to merge multimedia and data mining research together to exploit the synergy between the two areas to advance and promote the research and development in multimedia data mining. the workshop was extremely successful. the feedback we have received during and after the workshop was overwhelmingly positive, which indicates the emerging interest and enthusiasm on the topic of multimedia data mining in the related research communities. due to this fact, we plan to continue this series next year.
can exclusive clustering on streaming data be achieved? clustering on streaming data aims at partitioning a list of data points into k groups of "similar" objects by scanning the data once. most current one-scan clustering algorithms do not keep original data in the resulting clusters. the output of the algorithms is therefore not the clustered data points but the approximations of data properties according to the predefined similarity function, such that k centers and radiuses reflect the up-to-date data grouping. in this paper, we raise a critical question: can the partition-based clustering, or exclusive clustering, be achieved on streaming data by those currently available algorithms? after identifying the differences between traditional clustering and clustering on data streams, we discuss the basic requirements for the clusters that can be discovered from streaming data. we evaluate the recent work that is based on a subcluster maintenance approach. by using a few straightforward examples we illustrate that the subcluster maintenance approach may fail to resolve the exclusive clustering on data streams. based on our observations, we also present the challenges on any heuristic method that claims solving the clustering problem on data streams in general.
kdd physics task: discussion of modeling approaches. in this paper, we present the methodology followed by inductis in developing the predictive models for quantum physics task in kdd cup 2004. we discuss many challenges that we faced in approaching the task and how we overcame them. we explored the solution space with various classification approaches and finally used stochastic gradient boosting offered on the treenet platform. a set of treenet models was fit varying various parameters and its performance was measured.
revenue recovering with insolvency prevention on a brazilian telecom operator. this paper deals with a real application on a brazilian telephone company. data mining analysis, based on neural networks, was performed on the customer base in order to understand and to prevent bad debt events. this paper describes the knowledge discovering process and focuses on two main products: the cluster analysis of the customer base and a bad debt event classification model. the segmentation of the customer base has provided a better understanding of several groups of customers' behavior. distinct actions are taken, depending on the segment a given client was put in, according to strategic directions of the company. the classification of insolvent customers is used as a tool to help the company to take preventing actions in order to avoid main losses and taxes leakage. the results of the project's implantation show that investment on information technology infra-structure for data mining is highly profitable.
state of the art of graph-based data mining. the need for mining structured data has increased in the past few years. one of the best studied data structures in computer science and discrete mathematics are graphs. it can therefore be no surprise that graph based data mining has become quite popular in the last few years.this article introduces the theoretical basis of graph based data mining and surveys the state of the art of graph-based data mining. brief descriptions of some representative approaches are provided as well.
classifying search engine queries using the web as background knowledge. the performance of search engines crucially depends on their ability to capture the meaning of a query most likely intended by the user. we study the problem of mapping a search engine query to those nodes of a given subject taxonomy that characterize its most likely meanings. we describe the architecture of a classification system that uses a web directory to identify the subject context that the query terms are frequently used in. based on its performance on the classification of 800,000 example queries recorded from msn search, the system received the runner-up award for query categorization performance of the kdd cup 2005.
mining with rarity: a unifying framework. rare objects are often of great interest and great value. until recently, however, rarity has not received much attention in the context of data mining. now, as increasingly complex real-world problems are addressed, rarity, and the related problem of imbalanced data, are taking center stage. this article discusses the role that rare classes and rare cases play in data mining. the problems that can result from these two forms of rarity are described in detail, as are methods for addressing these problems. these descriptions utilize examples from existing research. so that this article provides a good survey of the literature on rarity in data mining. this article also demonstrates that rare classes and rare cases are very similar phenomena---both forms of rarity are shown to cause similar problems during data mining and benefit from the same remediation methods.
kdd workshop on data mining standards, services & platforms (dm-ssp) 2006. dm-ssp '06 was the fourth year there has been a conference on data mining standards, services and platforms and the sixth year that there has been a conference on the predictive model markup language (pmml) and related areas. the workshop consisted of five talks and two panels.
report on ubdm-05: workshop on utility-based data mining. in this report we provide a summary of the first international workshop on utility-based data mining (ubdm-05) held in conjunction with the 11th acm sigkdd international conference on knowledge discovery and data mining. the workshop was held on august 21, 2005 in chicago, il, usa. this workshop was geared toward researchers with an interest in how economic utility factors affect data mining (e.g., researchers in cost-sensitive learning and active learning) and practitioners who have real-world experience with how these factors influence data mining applications.
automatic microscopy video mining for leukocytes. biological videos are very different from conventional videos. automatic spatiotemporal mining of moving cells from in vivo microscopy videos is extremely difficult because of the severe noises, camera/subject movements, deformations, and strong dependencies on microscopy operators. in this paper, we present an automatic spatiotemporal mining system of rolling and adherent leukocytes for intravital videos. the magnitude of leukocyte adhesion and decrease in rolling velocity are common interests in inflammation response studies. currently, there is no existing system which is perfect for such purposes. several approaches have been proposed for tracking leukocytes. however, these approaches can either only track leukocytes that roll along the centerline of the blood vessel, or can only handle leukocytes with fixed morphologies. in addition, the camera/subject movement is a severe problem which occurs frequently while analyzing in vivo microscopy videos. in this paper, we proposed a new method for automatic recognition of non-adherent and adherent leukocytes. the proposed method includes three steps: (1) camera/subject movement alignment; (2) moving leukocytes detection; (3) adherent leukocytes detection. the experimental results demonstrate the effectiveness of the proposed method.
graphical modeling based gene interaction analysis for microarray data. dna microarray provides a powerful basis for analysis of gene expression. data mining methods such as clustering have been widely applied to microarray data to link genes that show similar expression patterns. however, this approach usually fails to unveil gene-gene interactions in the same cluster. in this paper, we propose to use graphical modeling based interaction analysis for this purpose. we apply graphical gaussian model to discover pairwise gene interactions and use loglinear model to discover multi-gene interactions. we have constructed a prototype system that permits rapid interactive exploration of gene relationships; results can be validated by experts or known information, or suggest new experiments. we have tested our methodology using the yeast microarray data. our results reveal some previously unknown interactions that have solid biological explanations.
citation prediction using time series approach kdd cup 2003 (task 1). in this article we describe our experiences in building the winning system for kdd cup, 2003, task 1. this year's competition was based on a very large archive of research papers that provides an unusually comprehensive snapshot of a particular social network in action; in addition to the full text of research papers, it includes both explicit citation structure and partial data on the downloading of papers by users. it provides a framework for testing general network and usage mining techniques, which can be explored via four varied and interesting tasks. each task is a separate competition with its own specific goal. in task 1 the goal is to predict the change in number of citations to each paper in the archive over time.the contest was very challenging because the given data was not in a format suitable for conventional data mining techniques. so we had to do a considerable amount of data processing. also there were different sources of data like tex files, citation graph, slac-data database. so we had to make a decision about which sources to use and how much to use.
background and overview for kdd cup 2002 task 1: information extraction from biomedical articles. this paper presents a background and overview for task 1 (of 2 tasks) of the kdd challenge cup 2002, a competition held in conjunction with the acm sigkdd international conference on knowledge discovery and data mining (kdd), july 23--26, 2002. task 1 dealt with detecting which papers, in a set of fruitfly genetics papers (texts), contained experimental results about gene products (transcripts and proteins), and also within each paper, which genes had experimental results about their products mentioned.
drug exposure side effects from mining pregnancy data. this paper presents an interdisciplinary collaborative research project between the epidemiology department and the computer science department for using data mining technique to analyze data from pregnant women. specifically, the authors use association rule mining approach to derive possible side effects due to exposure to multiple drugs at different duration of the pregnancy. the derived temporal sequential rules discover new information that would not be detected by the traditional analysis method that is currently used in pharmaco-epidemiology.
mdm/kdd: multimedia data mining for the second time. this is brief report summarizes the presentations, conclusions and directions for future work that were discussed during the second edition of the international workshop on multimedia data mining. the report includes references to resources where one can find more information about the workshop format, the proceedings and the workshop participants.
enabling more sophisticated gene expression analysis for understanding diseases and optimizing treatments. we survey the progress in the analysis of gene expression data for the purposes of disease subtype diagnosis, new subtype discovery, and understanding of diseases and treatment responses. we find existing works fall short on several issues: these works provide little information on the interplay between selected genes; the collection of pathways that can be used, evaluated, and ranked against the observed expression data is limited; and a comprehensive set of rules for reasoning about relevant molecular events has not been compiled and formalized. we thus envision an advanced integrated framework, and are developing a system based on it, to provide biologically inspired solutions. it comprises: (i) automated analysis and extraction of information from biomedical texts; (ii) targeted construction of known pathways; and (iii) direct hypothesis generation based on logical reasoning on, and tests for, consistencies and inconsistencies of observed data against known pathways.
novel approaches for small biomolecule classification and structural similarity search. structural similarity search among small molecules is a standard tool used in molecular classification and in-silico drug discovery. the effectiveness of this general approach depends on how well the following problems are addressed. the notion of similarity should be chosen for providing the highest level of discrimination of compounds with respect to the bioactivity of interest. the data structure for performing search should be very efficient as the molecular databases of interest include several millions of compounds. in this paper we summarize the recent applications of k-nearest-neighbor search method for small molecule classification. the k-nn classification of small molecules is based on selecting the most relevant set of chemical descriptors which are then compared under standard minkowski distance lp. here we describe how to computationally design the optimal weighted minkowski distance wlp for maximizing the discrimination between active and inactive compounds wrt bioactivities of interest. k-nn classification requires fast similarity search for predicting bioactivity of a new molecule. we then focus on construction of pruning based k-nn search data structures for any wlp distance that minimizes similarity search time. the accuracy achieved by k-nn classifier is better than the alternative lda and mlr approaches and is comparable to the ann methods. in terms of running time, k-nn classifier is considerably faster than the ann approach especially when large data sets are used. furthermore, k-nn classifier is capable of quantification of the level of bioactivity rather than returning a binary decision and can bring more insight to the nature of the activity via eliminating unrelated descriptors of the compounds with respect to the activity in question.
data mining and audience intelligence for advertising. growth in the global advertising industry - especially the recent rapid growth in online advertising - has generated large volumes of data, bringing along with it many challenging data mining problems. researchers from various disciplines have brought their expertise to solve these exciting problems, leading to a plethora of novel applications and new algorithms. we strongly felt that we needed a forum where data mining researchers and practitioners, from both academia and the industry, could come together to share their experience on advertising. to this end, we organized adkdd 2007 1, the first international workshop on data mining and audience intelligence for advertising, in conjunction with kdd 2007 at san jose, california, usa. in this report, we will present a summary of the workshop.
report on biokdd04: workshop on data mining in bioinformatics. biokdd'04 was held in conjunction with the 10th acm sigkdd international conference on knowledge discovery and data mining, in seattle, wa, in august 2004. there are numerous sources of biological data that provides challenging opportunities for data mining. for example, the structural genomics initiative aims to catalog the structure-function information for proteins. advances in technology such as microarrays have launched the subfield of genomics and proteomics to study the genes, proteins, and the regulatory gene expression circuitry inside the cell. other sources of data include the rapidly growing literature in bioinformatics (e.g., pubmed), the data on biochemical pathways, the evolutionary relationships among organisms in the tree of life, high throughput drug design combinatorial libraries, and so on. in addition to the data from biology and genomics, there are rich sources of data from other biosciences, including biomedical, and neuroscience data.
visa: visual subspace clustering analysis. to gain insight into today's large data resources, data mining extracts interesting patterns. to generate knowledge from patterns and benefit from human cognitive abilities, meaningful visualization of patterns are crucial. clustering is a data mining technique that aims at grouping data to patterns based on mutual (dis)similarity. for high dimensional data, subspace clustering searches patterns in any subspace of the attributes as patterns are typically obscured by many irrelevant attributes in the full space. for visual analysis of subspace clusters, their comparability has to be ensured. existing subspace clustering approaches, however, lack interactive visualization and show bias with respect to the dimensionality of subspaces. in this work, dimensionality unbiased subspace clustering and a novel distance function for subspace clusters are proposed. we suggest two visualization techniques that allow users to browse the entire subspace clustering, to zoom into individual objects, and to analyze subspace cluster characteristics in-depth. bracketing of different parameter settings enable users to immediately see the effect of parameters on their data and hence to choose the best clustering result for further analysis. usage of user analysis for feedback to the subspace clustering algorithm directly improves the subspace clustering. we demonstrate our visualization techniques on real world data and confirm results through additional accuracy measurements and comparison with existing subspace clustering algorithms.
biokdd01: workshop on data mining in bioinformatics. in this report we provide a summary of the biokdd01 workshop on data mining in bioinformatics, held in conjunction with the 7th acm sigkdd international conference on knowledge discovery and data mining, august 26, 2001 at san francisco, california, usa.
more bang for their bucks: assessing new features for online advertisers. online search systems that display ads continually offer new features that advertisers can use to fine-tune and enhance their ad campaigns. an important question is whether a new feature actually helps advertisers. in an ideal world for statisticians, we would answer this question by running a statistically designed experiment. but that would require randomly choosing a set of advertisers and forcing them to use the feature, which is not realistic. accordingly, in the real world, new features for advertisers are seldom evaluated with a traditional experimental protocol. instead, customer service representatives select advertisers who are invited to be among the first to test a new feature (i.e., white-listed), and then each white-listed advertiser chooses whether or not to use the new feature. neither the customer service representative nor the advertiser chooses at random. this paper addresses the problem of drawing valid inferences from whitelist trials about the effects of new features on advertiser happiness. we are guided by three principles. first, statistical procedures for whitelist trials are likely to be applied in an automated way, so they should be robust to violations of modeling assumptions. second, standard analysis tools should be preferred over custom-built ones, both for clarity and for robustness. standard tools have withstood the test of time and have been thoroughly debugged. finally, it should be easy to compute reliable confidence intervals for the estimator. we review an estimator that has all these attributes, allowing us to make valid inferences about the effects of a new feature on advertiser happiness.
kdd cup and workshop 2007. the kdd cup is the oldest of the many data mining competitions that are now popular [1]. it is an integral part of the annual acm sigkdd international conference on knowledge discovery and data mining (kdd). in 2007, the traditional kdd cup competition was augmented with a workshop with a focus on the concurrently active netflix prize competition [2]. the kdd cup itself in 2007 consisted of a prediction competition using netflix movie rating data, with tasks that were different and separate from those being used in the netflix prize itself. at the workshop, participants in both the kdd cup and the netflix prize competition presented their results and analyses, and exchanged ideas.
trajectory-based visual analysis of large financial time series data. visual analytics seeks to combine automatic data analysis with visualization and human-computer interaction facilities to solve analysis problems in applications characterized by occurrence of large amounts of complex data. the financial data analysis domain is a promising field for research and application of visual analytics technology, as it prototypically involves the analysis of large data volumes in solving complex analysis tasks. we introduce a visual analytics system for supporting the analysis of large amounts of financial time-varying indicator data. a system, driven by the idea of extending standard technical chart analysis from one to two-dimensional indicator space, is developed. the system relies on an unsupervised clustering algorithm combined with an appropriately designed movement data visualization technique. several analytical views on the full market and specific assets are offered for the user to navigate, to explore, and to analyze. the system includes automatic screening of the potentially large visualization space, preselecting possibly interesting candidate data views for presentation to the user. the system is applied to a large data set of time varying 2-d stock market data, demonstrating its effectiveness for visual analysis of financial data. we expect the proposed techniques to be beneficial in other application areas as well.
correlating summarization of multi-source news with k-way graph bi-clustering. with the emergence of enormous amount of online news, it is desirable to construct text mining methods that can extract, compare and highlight similarities of them. in this paper, we explore the research issue and methodology of correlated summarization for a pair of news articles. the algorithm aligns the (sub)topics of the two news articles and summarizes their correlation by sentence extraction. a pair of news articles are modelled with a weighted bipartite graph. a mutual reinforcement principle is applied to identify a dense subgraph of the weighted bipartite graph. sentences corresponding to the subgraph are correlated well in textual content and convey the dominant shared topic of the pair of news articles. as a further enhancement for lengthy articles, a k-way bi-clustering algorithm can first be used to partition the bipartite graph into several clusters, each containing sentences from the two news reports. these clusters correspond to shared subtopics, and the above mutual reinforcement principle can then be applied to extract topic sentences within each subtopic group.
mining motion patterns using color motion map clustering. automatically extracting previously unknown behavior patterns from videos that track animals with various physical conditions can accelerate our understanding of animal behaviors and their influential factors, resulting in major medical and economic benefits. unfortunately, extracting behavior patterns from videos recordings remains as a very challenging task due to their extensive duration and the unstructured natures. this task is further complicated in a completely darken animal cage with inconsistent infrared lighting, moving reflections, or other cage debris such as the cage bedding. in this research, we propose a new motion model that enables us to measure the similarities among different animal movements in high precision so a clustering method can correctly separate recurring movements from infrequent random movements. more specifically, our model first transforms the spatial and temporal features of animal movements into a sequence of color images, referred to as color motion maps (cmms). the task of mining recurring behavior patterns is then reduced to clustering similar color images in a database. we will use a real infrared video to demonstrate the capability of our model in capturing distinguished but brief animal movements that are embedded within a sequence of other animal movements.
market basket recommendations for the hp smb store. the analytics team at hewlett-packard recently executed a manually-driven cross-sell/up-sell pilot in the small and medium business online store and call center. the pilot, for which management dictated a 1 month development timeframe, utilized sales transaction, product configuration, and product availability data. leveraging market basket analysis techniques among a small subset of available product skus, the pilot yielded a roi of more than $300k/month and more importantly, gave birth to greater opportunities to further showcase the power of analytics and data driven decision-making at hp.
visual analysis of dynamic group membership in temporal social networks. c-group is a tool for analyzing dynamic group membership in temporal social networks over time. unlike most network visualization tools, which show the group structure within an entire network, or the group membership for a single actor, c-group allows users to focus their analysis on a pair of individuals. while c-group allows for viewing the addition and deletion of nodes (actors) and edges (relationships) over time, its major contribution is its focus on changing group memberships over time. by doing so, users can investigate the context of temporal group memberships for the pair. c-group provides users with a flexible interface for defining (and redefining) groups interactively, and supports two novel visual representations of the evolving group memberships. this flexibility gives users alternate views that are appropriate for different network sizes and provides users with different insights into the grouping behavior. we demonstrate the utility of the tool on a scientific publication network.
interview with jon kleinberg. interview with jon kleinberg, a pioneer in web mining, social network analysis, and other fields and a winner of many awards, including 2 kdd best papers and a macarthur 'genius' award.
predicting who rated what in large-scale datasets. kdd cup 2007 focuses on movie rating behaviors. the goal of the task "who rated what" is to predict whether "existing" users will review "existing" movies in the future. we cast the task as a link prediction problem and address it via a simple classification approach. compared with other applications for link prediction, there are two major challenges in our task: (1) the huge size of the netflix data; (2) the prediction target is complicated by many factors, such as a general decrease of interest in old movies and more tendency to review more movies by netflix users due to the success of the internet dvd rental industries. we address the first challenge by "selective" subsampling and the second by combining information from the review scores, movie contents and graph topology effectively.
pinkdd'07: privacy, security, and trust in kdd post-workshop report. in this report, we summarize the events of the first international workshop on privacy, security, and trust in kdd (pinkdd), which was held in conjunction with the 13th acm sigkdd international conference on knowledge discovery and data mining. the workshop convened on august 12, 2007 in san jose, california and brought together researchers, as well as practitioners, working on how privacy, security, and trust can be resolved or modeled within a data mining framework.
dddm2007: domain driven data mining. real-world data mining generally must consider and involve domain and business oriented factors such as human knowledge, constraints and business expectations. this encourages the development of a domain driven methodology to strengthen data-centered pattern mining. this report presents a review of the acm sigkdd workshop on domain driven data mining (dddm2007), held in conjunction with the thirteenth acm sigkdd international conference on knowledge discovery and data mining (kdd07), which was held in san jose, usa on 12 august, 2007. the aims and objectives of this workshop were to provide a premier forum for sharing innovative findings, knowledge, insights, experiences and lessons in tackling challenges met in domain driven, actionable knowledge discovery in the real world.
managing discoveries in the visual analytics process. visualization systems traditionally focus on graphical representation of information. they tend not to provide integrated analytical services that could aid users in tackling complex knowledge discovery tasks. users' exploration in such environments is usually impeded due to several problems: 1) valuable information is hard to discover when too much data is visualized on the screen; 2) users have to manage and organize their discoveries off line, because no systematic discovery management mechanism exists; 3) their discoveries based on visual exploration alone may lack accuracy; and 4)they have no convenient access to the important knowledge learned by other users. to tackle these problems, it has been recognized that analytical tools must be introduced into visualization systems. in this paper, we present a novel analysis-guided exploration system, called the nugget management system (nms). it leverages the collaborative effort of human comprehensibility and machine computations to facilitate users' visual exploration processes. specifically, nms first helps users extract the valuable information (nuggets) hidden in datasets based on their interests. given that similar nuggets may be rediscovered by different users, nms consolidates the nugget candidate set by clustering based on their semantic similarity. to solve the problem of inaccurate discoveries, localized data mining techniques are applied to refine the nuggets to best represent the captured patterns in datasets. visualization techniques are then employed to present our collected nugget pool and thus create the nugget view. based on the nugget view, interaction techniques are designed to help users observe and organize the nuggets in a more intuitive manner and eventually faciliate their sense-making process. we integrated nms into xmdvtool, a freeware multivariate visualization system. user studies were performed to compare the users' efficiency and accuracy in finishing tasks on real datasets, with and without the help of nms. our user studies confirmed the effectiveness of nms.
major components of the gravity recommendation system. the netflix prize is a collaborative filtering problem. this subfield of machine learning became popular in the late 1990s with the spread of online services that used recommendation systems (e.g. amazon, yahoo! music, and of course netflix). the aim of such a system is to predict what items a user might like based on his/her and other users' previous ratings. the netflix prize dataset is much larger than former benchmark datasets, therefore the scalability of the algorithms is a must. this paper describes the major components of our blending based solution, called the gravity recommendation system (grs). in the netflix prize contest, it attained rmse 0.8743 as of november 2007. we now compare the effectiveness of some selected individual and combined approaches on a particular subset of the prize dataset, and discuss their important features and drawbacks.
kdd cup 2007 task 1 winner report. kdd cup 2007 focuses on predicting aspects of movie rating behavior. we present our prediction method for task 1 "who rated what in 2006" where the goal is to predict which users rated which movies in 2006. we use the combination of the following methods, listed in the order of their accuracy: &bull; the predicted number of ratings for each movie based on time series analysis, also using movie and dvd release dates and movie series detection by the edit distance of the titles. &bull; the predicted number of ratings by each user by using the fact that ratings were sampled proportional to the margin. &bull; the low rank approximation of the 0-1 matrix of known user-movie pairs with rating. &bull; prediction by using the movie-movie similarity matrix. &bull; association rules obtained by frequent sequence mining of user ratings considered as ordered itemsets. by combining the predictions by linear regression we obtained a prediction with root mean squared error 0.256. the first runner up result was 0.263 while a pure all zeroes prediction already gives 0.279, indicating the hardness of the task.
a combination of approaches to solve task "how many ratings" of the kdd cup 2007. this paper presents a solution to the kdd cup 2007 task "how many ratings?". the combination of three different approaches is used to produce a final solution which improves the results obtained by each of these procedures by itself.
lessons from the netflix prize challenge. this article outlines the overall strategy and summarizes a few key innovations of the team that won the first netflix progress prize.
introduction. the information overload is a well-known phenomenon of the information age, since due to the progress in computer power and storage capacity over the last decades, data is produced at an incredible rate, and our ability to collect and store these data is increasing at a faster rate than our ability to analyze it. but, the analysis of these massive, typically messy and inconsistent, volumes of data is crucial in many application domains. for decision makers, analysts or emergency response teams it is an essential task to rapidly extract relevant information from the flood of data.
webkdd/snakdd 2007: web mining and social network analysis post-workshop report. in this report, we summarize the contents and outcomes of the recent joint webkdd/snakdd 2007 workshop on web mining and social network analysis that was held in conjunction with the 13th acm sigkdd international conference on knowledge discovery and data mining (kdd 2007), august 12-15, 2007, in san jose, california. in 2007, webkdd was organized for the ninth time in a successful series of workshops on knowledge discovery on the web. the first sna-kdd workshop is created to bring together researchers who currently contribute to different aspects of social network analysis, including knowledge discovery and data mining in social network, social network modeling, multi-agent based social network simulation, complex generic network analysis. the joint 9th webkdd and 1st sna-kdd workshop was co-held with kdd 2007 and solicited papers on broad overview subject "web mining and social network analysis". we reflect on the results of the workshop, as captured in the invited talk and presentations.
making the most of your data: kdd cup 2007 "how many ratings" winner's report. we describe the ideas and methodologies that we developed in addressing the kdd cup 2007 how many ratings task, and discuss how they contributed to our success.
visual analytics tools for analysis of movement data. with widespread availability of low cost gps devices, it is becoming possible to record data about the movement of people and objects at a large scale. while these data hide important knowledge for the optimization of location and mobility oriented infrastructures and services, by themselves they lack the necessary semantic embedding which would make fully automatic algorithmic analysis possible. at the same time, making the semantic link is easy for humans who however cannot deal well with massive amounts of data. in this paper, we argue that by using the right visual analytics tools for the analysis of massive collections of movement data, it is possible to effectively support human analysts in understanding movement behaviors and mobility patterns. we suggest a framework for analysis combining interactive visual displays, which are essential for supporting human perception, cognition, and reasoning, with database operations and computational methods, which are necessary for handling large amounts of data. we demonstrate the synergistic use of these techniques in case studies of two real datasets.
a classical predictive modeling approach for task "who rated what?" of the kdd cup 2007. this paper describes one possible way to solve task "who rated what?" of the kdd cup 2007. the proposed solution is a history-based model that predicts whether a user will vote a given movie. key points to our approach are (1) the estimation of the model baseline, (2) the definition of the explanatory variables and (3) the mathematical model form. given the binary outcome of the problem, the estimation of the true baseline (ratio of 1's in the test data) is critical in order to correctly make predictions. in parallel, to improve the model predictive power, we have developed a careful construction of the input variables. these explanatory variables can be grouped as: user voting behaviour variables, the movie characteristics and user-movie interactions. finally, the mathematical model form (linear logistic regression) has been chosen among various model form competitors.
8 french-speaking conference on knowledge discovery and management (egc2008): conference report. in this paper, we provide a report about the 8th french-speaking conference on knowledge discovery and management (egc'2008) [1] held in sophia antipolis, france, from january 29th to february 1st, 2008. since 2001, this annual conference has been supported by the french-speaking association (egc association) which aims at promoting data mining and knowledge management for both research issues and applications in companies. egc2008 may be summarized in some key figures: 130 submitted papers, 40 accepted long papers (33% selection ratio) published in a special issue of a review and completed with 30 short papers, 15 posters, and 8 software demonstrations; 9 joined workshops and 2 tutorials; 4 keynote talks; a best paper contest rewarded by 2 prizes of 1500 euros each; and 250 participants from 14 countries. the 9th egc conference will be held in strasbourg, france, in january 27-30, 2009 [2].
higher order mining. the value of knowledge obtainable by analysing large quantities of data is widely acknowledged. however, so-called primary or raw data may not always be available for knowledge discovery for several reasons. first, cooperating institutions that are interested in sharing knowledge may not be willing (or allowed) to disclose their primary data. second, data in the form of streams are only temporarily available for processing. if stored at all, stream data are maintained in the form of synopses or derived, abstract representations of the original data. finally, even for non-stream data, there are limits on the computation speed to be achieved -- such limits are set by hardware and firmware technologies. this problem can only be partially solved through parallelization and increased processing power. ultimately, in many cases data must be summarized to be processed efficiently. in the light of these observations, we anticipate the need for defining and practising data mining without the luxury of primary data. to that end, we formally introduce the paradigm of higher order mining as a form of data mining that is applied over non-primary, derived data or patterns. although higher order mining is a new paradigm, there are already research advances on knowledge discovery methods from patterns rather than data. we discuss them and organize them under the light of the new paradigm. we show that the hom paradigm reveals further potential for knowledge discovery, including the delivery of rules and patterns with semantics that are closer to human intuition and are thus more appropriate for human inspection.
blogosphere: research issues, tools, and applications. weblogs, or blogs, have facilitated people to express their thoughts, voice their opinions, and share their experiences and ideas. individuals experience a sense of community, a feeling of belonging, a bonding that members matter to one another and their niche needs will be met through online interactions. its open standards and low barrier to publication have transformed information consumers to producers. this has created a plethora of open-source intelligence, or "collective wisdom" that acts as the storehouse of over-whelming amounts of knowledge about the members, their environment and the symbiosis between them. nonetheless, vast amounts of this knowledge still remain to be discovered and exploited in its suitable way. in this paper, we introduce various state-of-the-art research issues, review some key elements of research such as tools and methodologies in blogosphere, and present a case study of identifying the influential bloggers in a community to exemplify the integration of some major aspects discussed in this paper. towards the end, we also compare and contrast the blogosphere and social networks and the research therein.
a privacy-aware trajectory tracking query engine. advances in telecommunications and gps sensors technology have made possible the collection of data like time series of locations, related to the movement of individuals. the analysis of this, so-called trajectory data, is beneficial both for the individuals (e.g., through location-based services) and for the community as a whole (e.g., decision support for urban planning or traffic control). however, because of the very nature of this data, strict safeguards must be enforced to ensure the privacy of the individuals, whose movement is recorded. in this paper, we present a privacy-aware trajectory tracking query engine that offers strict guarantees about what can be observed by untrusted third parties. through the query engine, subscribed users can gain restricted access to an in-house trajectory data warehouse, to perform certain analysis tasks. in addition to regular queries involving non-spatial non-temporal attributes, the engine supports a variety of spatiotemporal queries, including range queries, nearest neighbor queries and queries for aggregate statistics. the query results are augmented with fake trajectory data (dummies) to fulfil the requirements of k-anonymity. through qualitative analysis, we prove the effectiveness of our approach towards blocking certain types of attacks, while minimally distorting the dataset.
data mining with cellular automata. a cellular automaton is a discrete, dynamical system composed of very simple, uniformly interconnected cells. cellular automata may be seen as an extreme form of simple, localized, distributed machines. many researchers are familiar with cellular automata through conway's game of life. researchers have long been interested in the theoretical aspects of cellular automata. this article explores the use of cellular automata for data mining, specifically for classification tasks. we demonstrate that reasonable generalization behavior can be achieved as an emergent property of these simple automata.
optimal parallel selection. we present an optimal parallel selection algorithm on the erew pram. this algorithm runs in o(log n) time with n/log n processors. this complexity matches the known lower bound for parallel selection on the erew pram model. we therefore close this problem which has been open for more than a decade.
approximating rank-width and clique-width quickly. rank-width was defined by oum and seymour [2006] to investigate clique-width. they constructed an algorithm that either outputs a rank-decomposition of width at most f(k) for some function f or confirms that rank-width is larger than k in time o(&verbar;v&verbar;9log &verbar;v&verbar;) for an input graph g &equals; (v,e) and a fixed k. we develop three separate algorithms of this kind with faster running time. we construct an o(&verbar;v&verbar;4)-time algorithm with f(k) &equals; 3k + 1 by constructing a subroutine for the previous algorithm; we avoid generic algorithms minimizing submodular functions used by oum and seymour. another one is an o(&verbar;v&verbar;3)-time algorithm with f(k) &equals; 24k, achieved by giving a reduction from graphs to binary matroids; then we use an approximation algorithm for matroid branch-width by hlin&ecaron;n&yacute; [2005]. finally we construct an o(&verbar;v&verbar;3)-time algorithm with f(k) &equals; 3k &minus; 1 by combining the ideas of the two previously cited papers.
pricing multicasting in more flexible network models. the problem of designing efficient algorithms for sharing the cost of multicasting has recently received considerable attention. in this article, we examine the effect on the complexity of pricing when two flexibility-enhancing mechanisms are incorporated into the network model. in particular, we study a model where the session is offered at a number of different rates of transmission, and where there is a cost for enabling multicasting at each node of the network. we consider two techniques that have been used in practice to provide multiple rates: using a layered transmission scheme (called the layered paradigm) and using different multicast groups for each possible rate (called the split session paradigm). we demonstrate that the difference between these two paradigms has a significant impact on the complexity of pricing multicasting.for the layered paradigm, we provide a distributed algorithm for computing pricing efficiently in terms of local computation and message complexity. for the split session paradigm, on the other hand, we demonstrate that this problem can be solved in polynomial time if the number of possible rates is fixed, but if the number of rates is part of the input, then the problem becomes np-hard even to approximate. we also examine the effect of delivering the transmissions for the various rates from different locations within the network. we show that, in this case, the pricing problem becomes np-hard for the split session paradigm even for a fixed constant number of possible rates but if layering is used, then it can be solved in polynomial time by formulating the problem as a totally unimodular integer program.
oblivious routing on node-capacitated and directed graphs. oblivious routing algorithms for general undirected networks were introduced by r&auml;cke [2002], and this work has led to many subsequent improvements and applications. comparatively little is known about oblivious routing in general directed networks, or even in undirected networks with node capacities. we present the first nontrivial upper bounds for both these cases, providing algorithms for k-commodity oblivious routing problems with competitive ratio o(&sqrt;k log(n)) for undirected node-capacitated graphs and o(&sqrt;k n1/4 log(n)) for directed graphs. in the special case that all commodities have a common source or sink, our upper bound becomes o(&sqrt;n log(n)) in both cases, matching the lower bound up to a factor of log(n). the lower bound (which first appeared in azar et al. [2003]) is obtained on a graph with very high degree. we show that, in fact, the degree of a graph is a crucial parameter for node-capacitated oblivious routing in undirected graphs, by providing an o(&delta; polylog(n))-competitive oblivious routing scheme for graphs of degree &delta;. for the directed case, however, we show that the lower bound of &omega;(&sqrt;n) still holds in low-degree graphs. finally, we settle an open question about routing problems in which all commodities share a common source or sink. we show that even in this simplified scenario there are networks in which no oblivious routing algorithm can achieve a competitive ratio better than &omega;(log n).
provably good moving least squares. we analyze a moving least squares (mls) interpolation scheme for reconstructing a surface from point cloud data. the input is a sufficiently dense set of sample points that lie near a closed surface f with approximate surface normals. the output is a reconstructed surface passing near the sample points. for each sample point s in the input, we define a linear point function that represents the local shape of the surface near s. these point functions are combined by a weighted average, yielding a three-dimensional function i. the reconstructed surface is implicitly defined as the zero set of i. we prove that the function i is a good approximation to the signed distance function of the sampled surface f and that the reconstructed surface is geometrically close to and isotopic to f. our sampling requirements are derived from the local feature size function used in delaunay-based surface reconstruction algorithms. our analysis can handle noisy data provided the amount of noise in the input dataset is small compared to the feature size of f.
black box for constant-time insertion in priority queues (note). we present a simple black box that takes a priority queue q which supports find-min, insert, and delete in x-time at most t. here x-time may be worst-case, expected, or amortized. the black-box transforms q into a priority queue q* that supports find-min in constant time, insert in constant x-time, and delete in x-time o(t). moreover, if q supports dec-key in constant time, then so does q*.
compact name-independent routing with minimum stretch. given a weighted undirected network with arbitrary node names, we present a compact routing scheme, using a&otilde;(&sqrt;n,) space routing table at each node, and routing along paths of stretch 3, that is, at most thrice as long as the minimum cost paths. this is optimal in a very strong sense. it is known that no compact routing using o(n) space per node can route with stretch below 3. also, it is known that any stretch below 5 requires &omega;(&sqrt;n,)space per node.
an () algorithm for ear decompositions of matching-covered graphs. our main result is an o(nm)-time (deterministic) algorithm for constructing an ear decomposition of a matching-covered graph, where n and m denote the number of nodes and edges. the improvement in the running time comes from new structural results that give a sharpened version of lov&aacute;sz and plummer's two-ear theorem. our algorithm is based on o(nm)-time algorithms for two other fundamental problems in matching theory, namely, finding all the allowed edges of a graph, and finding the canonical partition of an elementary graph. to the best of our knowledge, no faster deterministic algorithms are known for these two fundamental problems.
clustering, community partition and disjoint spanning trees. clustering method is one of the most important tools in statistics. in a graph theory model, clustering is the process of finding all dense subgraphs. a mathematically well-defined measure for graph density is introduced in this article as follows. let g &equals; (v, e) be a graph (or multi-graph) and h be a subgraph of g. the dynamic density of h is the greatest integer k such that min&forall;p {&verbar;e(h/p)&verbar;/&verbar;v(h/p)&verbar; &minus; 1} > k where the minimum is taken over all possible partitions p of the vertex set of h, and h/p is the graph obtained from h by contracting each part of p into a single vertex. a subgraph h of g is a level-k community if h is a maximal subgraph of g with dynamic density at least k. an algorithm is designed in this paper to detect all level-h communities of an input multi-graph g. the worst-case complexity of this algorithm is upper bounded by o(&verbar;v(g)&verbar;2h2). this new method is one of few available clustering methods that are mathematically well-defined, supported by rigorous mathematical proof and able to achieve the optimization goal with polynomial complexity. as a byproduct, this algorithm also can be applied for finding edge-disjoint spanning trees of a multi-graph. the worst-case complexity is lower than all known algorithms for multi-graphs.
on a generalization of the stable roommates problem. we consider two generalizations of the stable roommates problem: a) we allow parallel edges in the underlying graph, and b) we study a problem with multiple partners. we reduce both problems to the classical stable roommates problem and describe an extension of irving's algorithm that solves the generalized problem efficiently. we give a direct proof of a recent result on the structure of stable many-to-many matchings (so called stable b-matchings) as a by-product of the justification of the algorithm.
optimal branch-decomposition of planar graphs in () time. we give an o(n3) time algorithm for constructing a minimum-width branch-decomposition of a given planar graph with n vertices. this is achieved through a refinement to the previously best known algorithm of seymour and thomas, which runs in o(n4) time.
the greedy algorithm for the minimum common string partition problem. in the minimum common string partition problem (mcsp), we are given two strings on input, and we wish to partition them into the same collection of substrings, minimizing the number of the substrings in the partition. this problem is np-hard, even for a special case, denoted 2-mcsp, where each letter occurs at most twice in each input string. we study a greedy algorithm for mcsp that at each step extracts a longest common substring from the given strings. we show that the approximation ratio of this algorithm is between &omega;(n0.43) and o(n0.69). in the case of 2-mcsp, we show that the approximation ratio is equal to 3. for 4-mcsp, we give a lower bound of &omega;(log n).
average-case lower bounds for the plurality problem. given a set of n elements, each of which is colored one of c &ge; 2 colors, we have to determine an element of the plurality (most frequently occurring) color by pairwise equal/unequal color comparisons of elements. we derive lower bounds for the expected number of color comparisons when the cn colorings are equally probable. we prove a general lower bound of c/3n &minus; o(&sqrt;n) for c &ge; 2; we prove the stronger particular bounds of 7/6 n &minus; o(&sqrt;n) for c &equals; 3, 54/35n &minus; o(&sqrt;n) for c &equals; 4, 607/315n &minus; o(&sqrt;n) for c &equals; 5, 1592/693n &minus; o(&sqrt;n) for c &equals; 6, 7985/3003n &minus; o(&sqrt;n) for c &equals; 7, and 19402/6435n &minus; o(&sqrt;n) for c &equals; 8.
fixed-parameter algorithms for (, )-center in planar graphs and map graphs. the (k, r)-center problem asks whether an input graph g has &le;k vertices (called centers) such that every vertex of g is within distance &le;r from some center. in this article, we prove that the (k, r)-center problem, parameterized by k and r, is fixed-parameter tractable (fpt) on planar graphs, i.e., it admits an algorithm of complexity f(k, r)no(1) where the function f is independent of n. in particular, we show that f(k,r) = 2o(r log r) &ksqrt;, where the exponent of the exponential term grows sublinearly in the number of centers. moreover, we prove that the same type of fpt algorithms can be designed for the more general class of map graphs introduced by chen, grigni, and papadimitriou. our results combine dynamic-programming algorithms for graphs of small branchwidth and a graph-theoretic result bounding this parameter in terms of k and r. finally, a byproduct of our algorithm is the existence of a ptas for the r-domination problem in both planar graphs and map graphs.our approach builds on the seminal results of robertson and seymour on graph minors, and as a result is much more powerful than the previous machinery of alber et al. for exponential speedup on planar graphs. to demonstrate the versatility of our results, we show how our algorithms can be extended to general parameters that are &ldquo;large&rdquo; on grids. in addition, our use of branchwidth instead of the usual treewidth allows us to obtain much faster algorithms, and requires more complicated dynamic programming than the standard leaf/introduce/forget/join structure of nice tree decompositions. our results are also unique in that they apply to classes of graphs that are not minor-closed, namely, constant powers of planar graphs and map graphs.
testing euclidean minimum spanning trees in the plane. given a euclidean graph g over a set p of n points in the plane, we are interested in verifying whether g is a euclidean minimum spanning tree (emst) of p or g differs from it in more than &epsi; n edges. we assume that g is given in adjacency list representation and the point/vertex set p is given in an array. we present a property testing algorithm that accepts graph g if it is an emst of p and that rejects with probability at least 2/3 if g differs from every emst of p in more than &epsi;, n edges. our algorithm runs in o(&sqrt;n/&epsi; &sdot; log2 (n/&epsi;)) time and has a query complexity of o(&sqrt;n/&epsi; &sdot; log (n/&epsi;)).
a maiden analysis of longest wait first. we consider server scheduling strategies to minimize average flow time in a multicast pull system where data items have uniform size. the algorithm longest wait first (lwf) always services the page where the aggregate waiting times of the outstanding requests for that page is maximized. we provide the first non-trivial analysis of the worst case performance of lwf. on the negative side, we show that lwf is not s-speed o(1)-competitive for s < 1+&sqrt;5/2. on the positive side, we show that lwf is 6-speed o(1)-competitive.
determining plurality. given a set of n elements, each of which is colored one of c colors, we must determine an element of the plurality (most frequently occurring) color by pairwise equal/unequal color comparisons of elements. we prove that (c &minus; 1)(n &minus; c)/2 color comparisons are necessary in the worst case to determine the plurality color and give an algorithm requiring (0.775c + 5.9)n + o(c2) color comparisons for c &ge; 9.
computing almost shortest paths. we study the <i>s-sources almost shortest paths</i> (abbreviated <i>s-asp</i>) problem. given an unweighted graph <i>g</i> equals; (<i>v,e</i>), and a subset <i>s</i> sube; <i>v</i> of <i>s</i> nodes, the goal is to compute almost shortest paths between all the pairs of nodes <i>s</i> times; <i>v</i>. we devise an algorithm with running time <i>o</i>( mid;<i>e</i> mid;<i>n</i><sup> rho;</sup> plus; <i>s</i> middot; <i>n</i><sup>1 plus; zeta;)</sup> for this problem that computes the paths <i>p</i><sub><i>u,w</i></sub> for all pairs (<i>u,w</i>) isin; <i>s</i> times; <i>v</i> such that the length of <i>p</i><sub><i>u,w</i></sub> is at most (1 plus; epsi;) <i>d</i><sub><i>g</i></sub>(<i>u,w</i>) plus; beta;( zeta;, rho;, epsi;), and beta;( zeta;, rho;, epsi;) is constant when zeta;, rho;, and epsi; are arbitrarily small constants. we also devise a distributed protocol for the <i>s</i>-asp problem that computes the paths <i>p</i><inf><i>u,w</i></inf> as above, and has time and communication complexities of <i>o</i>(<i>s</i> middot; <i>diam(g)</i> plus; <i>n</i><sup>1 plus; zeta;/2</sup>) (respectively, <i>o</i>(<i>s</i> middot; <i>diam(g)</i> log<sup>3</sup> <i>n</i> plus; <i>n</i><sup>1 plus; zeta;/2</sup> log <i>n</i>)) and <i>o</i>( mid;<i>e</i> mid; <i>n</i><sup> rho;</sup> plus; <i>s</i> middot; <i>n</i><sup>1 plus; zeta;)</sup> (respectively, <i>o</i>( mid;<i>e</i> mid; <i>n</i><sup> rho;</sup> plus; <i>s</i> middot; <i>n</i><sup>1 plus; zeta;</sup> plus; <i>n</i><sup>1 plus; rho; plus; zeta;( rho; minus; zeta;/2)/2)) in the synchronous (respectively asynchronous) setting. our sequential algorithm, as well as the distributed protocol, is based on a novel algorithm for constructing (1 plus; epsi;, beta;( zeta;, rho;, epsi;))-spanners of size <i>o</i>(<i>n</i><sup>1 plus; zeta;</sup>), developed in this article. this algorithm has running time of <i>o</i>( mid;<i>e</i> mid; <i>n</i><sup> rho;</sup>), which is significantly faster than the previously known algorithm given in elkin and peleg [2001], whose running time is <i> otilde;</i>(<i>n</i><sup>2 plus; rho;</sup>). we also develop the first distributed protocol for constructing (1 plus; epsi;, beta;)-spanners. the communication complexity of this protocol is near optimal.
optimality of an algorithm solving the bottleneck tower of hanoi problem. we study the bottleneck tower of hanoi puzzle posed by d. wood in 1981. there, a relaxed placement rule allows a larger disk to be placed higher than a smaller one if their size difference is less than a pregiven value k. a shortest sequence of moves (optimal algorithm) transferring all the disks placed on some peg in decreasing order of size, to another peg in the same order is in question. in 1992, d. poole suggested a natural disk-moving strategy for this problem, and computed the length of the shortest move sequence under its framework. however, other strategies were overlooked, so the lower bound/optimality question remained open. in 1998, benditkis, berend, and safro proved the optimality of poole's algorithm for the first nontrivial case k &equals; 2. we prove poole's algorithm to be optimal in the general case.
on network design problems: fixed cost flows and the covering steiner problem. network design problems, such as generalizations of the steiner tree problem, can be cast as edge-cost-flow problems. an edge-cost flow problem is a min-cost flow problem in which the cost of the flow equals the sum of the costs of the edges carrying positive flow.we prove a hardness result for the minimum edge cost flow problem (mecf). using the one-round two-prover scenario, we prove that mecf does not admit a 2log1-&epsiv; n-ratio approximation, for every constant &epsiv; > 0, unless np &sube; dtime(npolylogn).a restricted version of mecf, called infinite capacity mecf (icf), is defined. the icf problem is defined as follows: (i) all edges have infinite capacity, (ii) there are multiple sources and sinks, where flow can be delivered from every source to every sink, (iii) each source and sink has a supply amount and demand amount, respectively, and (iv) the required total flow is given as part of the input. the goal is to find a minimum edge-cost flow that meets the required total flow while obeying the demands of the sinks and the supplies of the sources. this problem naturally arises in practical scheduling applications, and is equivalent to the special case of single source mecf, with all edges not touching the source or the sink having infinite capacity.the directed icf generalizes the covering steiner problem in directed and undirected graphs. the undirected version of icf generalizes several network design problems, such as: steiner tree problem, k-mst, point-to-point connection problem, and the generalized steiner tree problem.an o(log x)-approximation algorithm for undirected icf is presented. we also present a bi-criteria approximation algorithm for directed icf. the algorithm for directed icf finds a flow that delivers half the required flow at a cost that is at most o(n&epsiv;/&epsiv;4) times bigger than the cost of an optimal flow. the running time of the algorithm is o(x2/&epsiv; &cdot; n1+1/&epsiv;), where x denotes the required total flow.randomized approximation algorithms for the covering steiner problem in directed and undirected graphs are presented. the algorithms are based on a randomized reduction to a problem called 1/2-group steiner. in undirected graphs, the approximation ratio matches the approximation ratio of konjevod et al. [2002]. however, our algorithm is much simpler. in directed graphs, the algorithm is the first nontrivial approximation algorithm for the covering steiner problem. deterministic algorithms are obtained by derandomization.
balanced parentheses strike back. an ordinal tree is an arbitrary rooted tree where the children of each node are ordered. succinct representations for ordinal trees with efficient query support have been extensively studied. the best previously known result is due to geary et al. [2004b, pages 1--10]. the number of bits required by their representation for an n-node ordinal tree t is 2n + o(n), whose first-order term is information-theoretically optimal. their representation supports a large set of o(1)-time queries on t. based upon a balanced string of 2n parentheses, we give an improved 2n + o(n)-bit representation for t. our improvement is two-fold: first, the set of o(1)-time queries supported by our representation is a proper superset of that supported by the representation of geary, raman, and raman. second, it is also much easier for our representation to support new queries by simply adding new auxiliary strings.
improved algorithms for the minmax-regret 1-center and 1-median problems. in this article, efficient algorithms are presented for the minmax-regret 1-center and 1-median problems on a general graph and a tree with uncertain vertex weights. for the minmax-regret 1-center problem on a general graph, we improve the previous upper bound from o(mn2 log n) to o(mn log n). for the problem on a tree, we improve the upper bound from o(n2) to o(n log2 n). for the minmax-regret 1-median problem on a general graph, we improve the upper bound from o(mn2 log n) to o(mn2 + n3 log n). for the problem on a tree, we improve the upper bound from o(n log2 n) to o(n log n).
approximate majorization and fair online load balancing. this article relates the notion of fairness in online routing and load balancing to vector majorization as developed by hardy et al. [1929]. we define &alpha;-supermajorization as an approximate form of vector majorization, and show that this definition generalizes and strengthens the prefix measure proposed by kleinberg et al. [2001] as well as the popular notion of max-min fairness.the article revisits the problem of online load-balancing for unrelated 1-&infin; machines from the viewpoint of fairness. we prove that a greedy approach is o(log n)-supermajorized by all other allocations, where n is the number of jobs. this means the greedy approach is globally o(log n)-fair. this may be contrasted with polynomial lower bounds presented by goel et al. [2001] for fair online routing.we also define a machine-centric view of fairness using the related concept of submajorization. we prove that the greedy online algorithm is globally o(log m)-balanced, where m is the number of machines.
algorithms for capacitated rectangle stabbing and lot sizing with joint set-up costs. in the rectangle stabbing problem, we are given a set of axis parallel rectangles and a set of horizontal and vertical lines, and our goal is to find a minimum size subset of lines that intersect all the rectangles. in this article, we study the capacitated version of this problem in which the input includes an integral capacity for each line. the capacity of a line bounds the number of rectangles that the line can cover. we consider two versions of this problem. in the first, one is allowed to use only a single copy of each line (hard capacities), and in the second, one is allowed to use multiple copies of every line, but the multiplicities are counted in the size (or weight) of the solution (soft capacities). we present an exact polynomial-time algorithm for the weighted one dimensional case with hard capacities that can be extended to the one dimensional weighted case with soft capacities. this algorithm is also extended to solve a certain capacitated multi-item lot-sizing inventory problem with joint set-up costs. for the case of d-dimensional rectangle stabbing with soft capacities, we present a 3d-approximation algorithm for the unweighted case. for d-dimensional rectangle stabbing problem with hard capacities, we present a bi-criteria algorithm that computes 4d-approximate solutions that use at most two copies of every line. finally, we present hardness results for rectangle stabbing when the dimension is part of the input and for a two-dimensional weighted version with hard capacities.
analysis of linear combination algorithms in cryptography. several cryptosystems rely on fast calculations of linear combinations in groups. one way to achieve this is to use joint signed binary digit expansions of small &ldquo;weight.&rdquo; we study two algorithms, one based on nonadjacent forms of the coefficients of the linear combination, the other based on a certain joint sparse form specifically adapted to this problem. both methods are sped up using the sliding windows approach combined with precomputed lookup tables. we give explicit and asymptotic results for the number of group operations needed, assuming uniform distribution of the coefficients. expected values, variances and a central limit theorem are proved using generating functions.furthermore, we provide a new algorithm that calculates the digits of an optimal expansion of pairs of integers from left to right. this avoids storing the whole expansion, which is needed with the previously known right-to-left methods, and allows an online computation.
individual displacements for linear probing hashing with different insertion policies. we study the distribution of the individual displacements in hashing with linear probing for three different versions: first come, last come and robin hood. asymptotic distributions and their moments are found when the the size of the hash table tends to infinity with the proportion of occupied cells converging to some &alpha;, 0 < &alpha; < 1. (in the case of last come, the results are more complicated and less complete than in the other cases.)we also show, using the diagonal poisson transform studied by poblete, viola and munro, that exact expressions for finite m and n can be obtained from the limits as m,n &rarr; &infin;.we end with some results, conjectures and questions about the shape of the limit distributions. these have some relevance for computer applications.
writing-all deterministically and optimally using a nontrivial number of asynchronous processors. the problem of performing n tasks on p asynchronous or undependable processors is a basic problem in distributed computing. this article considers an abstraction of this problem called write-all: using p processors write 1's into all locations of an array of size n. in this problem writing 1 abstracts the notion of performing a simple task. despite substantial research, there is a dearth of efficient deterministic asynchronous algorithms for write-all/. efficiency of algorithms is measured in terms of work that accounts for all local steps performed by the processors in solving the problem. thus, an optimal algorithm would have work &theta;(n), however it is known that optimality cannot be achieved when p &equals; &omega;(n). the quest then is to obtain work-optimal solutions for this problem using a nontrivial, compared to n, number of processors p. the algorithm presented in this article has work complexity of o(n + p2 + &epsi;), and it achieves work optimality for p &equals; o(n1/(2 + &epsiv;)) for any &epsiv; > 0, while the previous best result achieved optimality for p&le;4&sqrt;n/log n. additionally, the new result uses only the atomic read/write memory, without resorting to using the test-and-set primitive that was necessary in the previous solution.
the np-completeness column. this is the 24th edition of a column that covers new developments in the theory of np-completeness. the presentation is modeled on that which m. r. garey and i used in our book &ldquo;computers and intractability: a guide to the theory of np-completeness,&rdquo; w. h. freeman & co., new york, 1979, hereinafter referred to as &ldquo;[g&j].&rdquo; previous columns, the first 23 of which appeared in j. algorithms, will be referred to by a combination of their sequence number and year of appearance, e.g. &ldquo;[col 1, 1981].&rdquo; this edition of the column describes the history and purpose of the column and the status of the open problems from [g&j] and previous columns.
optimally scheduling video-on-demand to minimize delay when sender and receiver bandwidth may differ. we establish tight bounds on the intrinsic cost (either minimizing delay d for fixed sender and receiver bandwidths, or minimizing sender bandwidth for fixed delay and receiver bandwidth) of broadcasting a video of length m over a channel of bandwidth s in such a way that a receiver (with bandwidth r), starting at an arbitrary time s, can download the video so that it can begin playback at time s &plus; d.our bounds are realized by a simple just-in-time protocol that partitions the video into a fixed number of segments, partitions the sender bandwidth into an equivalent number of equal bandwidth subchannels, and broadcasts each segment repeatedly on its own subchannel. the protocol is suitable for the broadcast of compressed video and it can be implemented so that video information is packaged into discrete fixed length packets incurring only a modest overhead (measured in terms of increased delay).our primary contribution is a lower bound on the required delay that applies to all protocols. this lower bound matches the behavior of our just-in-time protocol in the limit as the number of segments approaches infinity, provided the video compression satisfies some uniform upper bound. for a fixed number of segments, our protocol is optimal within a broad class of protocols, even if the video is compressed arbitrarily.
approximation algorithms for the capacitated minimum spanning tree problem and its variants in network design. given an undirected graph g = (v,e) with nonnegative costs on its edges, a root node r v, a set of demands d v with demand v d wishing to route w(v) units of flow (weight) to r, and a positive number k, the capacitated minimum steiner tree (cmstt) problem asks for a minimum steiner tree, rooted at r, spanning the vertices in d * lcub;r rcub;, in which the sum of the vertex weights in every subtree connected to r is at most k. when d equals; v, this problem is known as the capacitated minimum spanning tree (cmst) problem. both cmst and cmst problems are np-hard. in this article, we present approximation algorithms for these problems and several of their variants in network design. our main results are the following: ---we present a (&sup3; &aacute;st + 2)-approximation algorithm for the cmstt problem, where &sup3; is the inverse steiner ratio, and &aacute;st is the best achievable approximation ratio for the steiner tree problem. our ratio improves the current best ratio of 2&aacute;st + 2 for this problem. ---in particular, we obtain (&sup3; + 2)-approximation ratio for the cmst problem, which is an improvement over the current best ratio of 4 for this problem. for points in euclidean and rectilinear planes, our result translates into ratios of 3.1548 and 3.5, respectively. ---for instances in the plane, under the lp norm, with the vertices in d having uniform weights, we present a nontrivial (7/5&aacute;st + 3/2)-approximation algorithm for the cmstt problem. this translates into a ratio of 2.9 for the cmst problem with uniform vertex weights in the lpmetric plane. our ratio of 2.9 solves the long-standing open problem of obtaining any ratio better than 3 for this case. ---for the cmst problem, we show how to obtain a 2-approximation for graphs in metric spaces with unit vertex weights and k = 3,4. ---for the budgeted cmst problem, in which the weights of the subtrees connected to r could be up to &plusmn; k instead of k (&plusmn; e 1), we obtain a ratio of &sup3; plus; 2/&plusmn;.
approximation schemes for wireless networks. wireless networks are created by the communication links between a collection of radio transceivers. the nature of wireless transmissions does not lead to arbitrary undirected graphs but to structured graphs which we characterize by the polynomially bounded growth property. in contrast to many existing graph models for wireless networks, the property of polynomially bounded growth is defined independently of geometric data such as positional information. on such wireless networks, we present an approach that can be used to create polynomial-time approximation schemes for several optimization problems called the local neighborhood-based scheme. we apply this approach to the problems of seeking maximum (weight) independent sets and minimum dominating sets. these are two important problems in the area of wireless communication networks and are also used in many applications ranging from clustering to routing strategies. however, the approach is presented in a general fashion since it can be applied to other problems as well. the approach for the approximation schemes is robust in the sense that it accepts any undirected graph as input and either outputs a solution of desired quality or correctly asserts that the graph presented as input does not satisfy the structural assumption of a wireless network (an np-hard problem).
problems column. computing professionals must beware when exclusive rights tip out of balance with obligations, unreasonably invalidating intellectual capital.
atomic congestion games among coalitions. we consider algorithmic questions concerning the existence, tractability, and quality of nash equilibria, in atomic congestion games among users participating in selfish coalitions. we introduce a coalitional congestion model among atomic players and demonstrate many interesting similarities with the noncooperative case. for example, there exists a potential function proving the existence of pure nash equilibria (pne) in the unrelated parallel links setting; in the network setting, the finite improvement property collapses as soon as we depart from linear delays, but there is an exact potential (and thus pne) for linear delays. the price of anarchy on identical parallel links demonstrates a quite surprising threshold behavior: it persists on being asymptotically equal to that in the case of the noncooperative kp-model, unless the number of coalitions is sublogarithmic. we also show crucial differences, mainly concerning the hardness of algorithmic problems that are solved efficiently in the noncooperative case. although we demonstrate convergence to robust pne, we also prove the hardness of computing them. on the other hand, we propose a generalized fully mixed nash equilibrium that can be efficiently constructed in most cases. finally, we propose a natural improvement policy and prove its convergence in pseudopolynomial time to pne which are robust against (even dynamically forming) coalitions of small size.
a linear-time approximation algorithm for weighted matchings in graphs. approximation algorithms have so far mainly been studied for problems that are not known to have polynomial time algorithms for solving them exactly. here we propose an approximation algorithm for the weighted matching problem in graphs which can be solved in polynomial time. the weighted matching problem is to find a matching in an edge weighted graph that has maximum weight. the first polynomial-time algorithm for this problem was given by edmonds in 1965. the fastest known algorithm for the weighted matching problem has a running time of o(nm+n2log n). many real world problems require graphs of such large size that this running time is too costly. therefore, there is considerable need for faster approximation algorithms for the weighted matching problem. we present a linear-time approximation algorithm for the weighted matching problem with a performance ratio arbitrarily close to 2/3. this improves the previously best performance ratio of 1/2. our algorithm is not only of theoretical interest, but because it is easy to implement and the constants involved are quite small it is also useful in practice.
approximation algorithms for a facility location problem with service capacities. we present the first constant-factor approximation algorithms for the following problem. given a metric space (v, c), a finite set d &sube; v of terminals/customers with demands d : d &rarr; r+, a facility opening cost f &isin; r+ and a capacity u &isin;r+, find a partition d &equals; d1&cupdot;&hellip;&cupdot;dk and steiner trees ti for di (i &equals; 1, &hellip;,k) with c(e(ti)) + d(di) &le; u for i &equals; 1,&hellip;,k such that &sumi &equals; 1k c(e(ti)) + kf is minimum. this problem arises in vlsi design. it generalizes the bin-packing problem and the steiner tree problem. in contrast to other network design and facility location problems, it has the additional feature of upper bounds on the service cost that each facility can handle. among other results, we obtain a 4.1-approximation in polynomial time, a 4.5-approximation in cubic time, and a 5-approximation as fast as computing a minimum spanning tree on (d, c).
exact distribution of individual displacements in linear probing hashing. this paper studies the distribution of individual displacements for the standard and the robin hood linear probing hashing algorithms. when the a table of size m has n elements, the distribution of the search cost of a random element is studied for both algorithms. specifically, exact distributions for fixed m and n are found as well as when the table is &alpha;-full, and &alpha; strictly smaller than 1. moreover, for full tables, limit laws for both algorithms are derived.
label-guided graph exploration by a finite automaton. a finite automaton, simply referred to as a robot, has to explore a graph, that is, visit all the nodes of the graph. the robot has no a priori knowledge of the topology of the graph, nor of its size. it is known that for any k-state robot, there exists a graph of maximum degree 3 that the robot cannot explore. this article considers the effects of allowing the system designer to add short labels to the graph nodes in a preprocessing stage, for helping the exploration by the robot. we describe an exploration algorithm that, given appropriate 2-bit labels (in fact, only 3-valued labels), allows a robot to explore all graphs. furthermore, we describe a suitable labeling algorithm for generating the required labels in linear time. we also show how to modify our labeling scheme so that a robot can explore all graphs of bounded degree, given appropriate 1-bit labels. in other words, although there is no robot able to explore all graphs of maximum degree 3, there is a robot r, and a way to color in black or white the nodes of any bounded-degree graph g, so that r can explore the colored graph g. finally, we give impossibility results regarding graph exploration by a robot with no internal memory (i.e., a single-state automaton).
fast sparse matrix multiplication. let a and b two n&times;n matrices over a ring r (e.g., the reals or the integers) each containing at most m nonzero elements. we present a new algorithm that multiplies a and b using o(m0.7n1.2+n2+o(1)) algebraic operations (i.e., multiplications, additions and subtractions) over r. the na&iuml;ve matrix multiplication algorithm, on the other hand, may need to perform &ohm;(mn) operations to accomplish the same task. for m&le;n1.14, the new algorithm performs an almost optimal number of only n2+o(1) operations. for m&le;n1.68, the new algorithm is also faster than the best known matrix multiplication algorithm for dense matrices which uses o(n2.38) algebraic operations. the new algorithm is obtained using a surprisingly straightforward combination of a simple combinatorial idea and existing fast rectangular matrix multiplication algorithms. we also obtain improved algorithms for the multiplication of more than two sparse matrices. as the known fast rectangular matrix multiplication algorithms are far from being practical, our result, at least for now, is only of theoretical value.
algorithmic construction of sets for -restrictions. this work addresses k-restriction problems, which unify combinatorial problems of the following type: the goal is to construct a short list of strings in &sigma;m that satisfies a given set of k-wise demands. for every k positions and every demand, there must be at least one string in the list that satisfies the demand at these positions. problems of this form frequently arise in different fields in computer science.the standard approach for deterministically solving such problems is via almost k-wise independence or k-wise approximations for other distributions. we offer a generic algorithmic method that yields considerably smaller constructions. to this end, we generalize a previous work of naor et al. [1995]. among other results, we enhance the combinatorial objects in the heart of their method, called splitters, and construct multi-way splitters, using a new discrete version of the topological necklace splitting theorem [alon 1987].we utilize our methods to show improved constructions for group testing [ngo and du 2000] and generalized hashing [alon et al. 2003], and an improved inapproximability result for set-cover under the assumption p &neq; np.
approximate distance oracles for unweighted graphs in expected () time. let g &equals; (v, e) be an undirected graph on n vertices, and let &delta;(u, v) denote the distance in g between two vertices u and v. thorup and zwick showed that for any positive integer t, the graph g can be preprocessed to build a data structure that can efficiently report t-approximate distance between any pair of vertices. that is, for any u, v &isin; v, the distance reported is at least &delta;(u, v) and at most t&delta;(u, v). the remarkable feature of this data structure is that, for t&ge;3, it occupies subquadratic space, that is, it does not store all-pairs distances explicitly, and still it can answer any t-approximate distance query in constant time. they named the data structure &ldquo;approximate distance oracle&rdquo; because of this feature. furthermore, the trade-off between the stretch t and the size of the data structure is essentially optimal.in this article, we show that we can actually construct approximate distance oracles in expected o(n2) time if the graph is unweighted. one of the new ideas used in the improved algorithm also leads to the first expected linear-time algorithm for computing an optimal size (2, 1)-spanner of an unweighted graph. a (2, 1) spanner of an undirected unweighted graph g &equals; (v, e) is a subgraph (v, &ecirc;), &ecirc; &sube; e, such that for any two vertices u and v in the graph, their distance in the subgraph is at most 2&delta;(u, v) &plus; 1.
faster fixed parameter tractable algorithms for finding feedback vertex sets. a feedback vertex set (fvs) of a graph is a set of vertices whose removal results in an acyclic graph. we show that if an undirected graph on n vertices with minimum degree at least 3 has a fvs on at most 1/3n1 &minus; &epsi; vertices, then there is a cycle of length at most 6/&epsi; (for &epsi; &ge; 1/2, we can even improve this to just 6).using this, we obtain a o((12 log k/log log k &plus; 6)k n&omega; algorithm for testing whether an undirected graph on n vertices has a fvs of size at most k. here n&omega; is the complexity of the best matrix multiplication algorithm. the previous best parameterized algorithm for this problem took o((2k &plus; 1)kn2) time.we also investigate the fixed parameter complexity of weighted feedback vertex set problem in weighted undirected graphs.
finding 3-shredders efficiently. a shredder in an undirected graph is a set of vertices whose removal results in at least three components. a 3-shredder is a shredder of size three. we present an algorithm that, given a 3-connected graph, finds its 3-shredders in time proportional to the number of vertices and edges, when implemented on a ram (random access machine).
succinct ordinal trees with level-ancestor queries. we consider succinct or space-efficient representations of trees that efficiently support a variety of navigation operations. we focus on static ordinal trees, that is, arbitrary static rooted trees where the children of each node are ordered. the set of operations is essentially the union of the sets of operations supported by previous succinct representations [jacobson 1989; munro and raman 2001; benoit et al. 1999] to which we add the level-ancestor operation.our representation takes 2n &plus; o(n) bits to represent an n-node tree, which is within o(n) bits of the information-theoretic minimum, and supports all operations in o(1) time on the ram model. these operations also provide a mapping from the n nodes of the tree onto the integers &lcub;1, &hellip;, n&rcub;. in addition to the existing motivations for studying such data structures, we are motivated by the problem of representing xml documents compactly so that xpath queries can be supported efficiently.
bipartite roots of graphs. graph h is a root of graph g if there exists a positive integer k such that x and y are adjacent in g if and only if their distance in h is at most k. motwani and sudan [1994] proved the np-completeness of graph square recognition and conjectured that it is also np-complete to recognize squares of bipartite graphs. the main result of this article is to show that squares of bipartite graphs can be recognized in polynomial time. in fact, we give a polynomial-time algorithm to count the number of different bipartite square roots of a graph, although this number could be exponential in the size of the input graph. by using the ideas developed, we are able to give a new and simpler linear-time algorithm to recognize squares of trees and a new algorithmic proof that tree square roots are unique up to isomorphism. finally, we prove the np-completeness of recognizing cubes of bipartite graphs.
the cyclic multi-peg tower of hanoi. variants of the classical tower of hanoi problem evolved in various directions. allowing more than 3 pegs, and imposing limitations on the possible moves among the pegs, are two of these. here, we deal with the case of h&ge;3 pegs arranged on a circle, where moves are allowed only from a peg to the next peg (in the clockwise direction). unlike the multi-peg problem without restrictions on moves between pegs, the complexity of this variant as a function of the number of disks is exponential. we find explicit lower and upper bounds for its complexity for any h, and show how this complexity can be estimated arbitrarily well for any specific h.
secure multiparty computation of approximations. approximation algorithms can sometimes provide efficient solutions when no efficient exact computation is known. in particular, approximations are often useful in a distributed setting where the inputs are held by different parties and may be extremely large. furthermore, for some applications, the parties want to compute a function of their inputs securely without revealing more information than necessary. in this work, we study the question of simultaneously addressing the above efficiency and security concerns via what we call secure approximations.we start by extending standard definitions of secure (exact) computation to the setting of secure approximations. our definitions guarantee that no additional information is revealed by the approximation beyond what follows from the output of the function being approximated. we then study the complexity of specific secure approximation problems. in particular, we obtain a sublinear-communication protocol for securely approximating the hamming distance and a polynomial-time protocol for securely approximating the permanent and related &num;p-hard problems.
when indexing equals compression: experiments with compressing suffix arrays and applications. we report on a new experimental analysis of high-order entropy-compressed suffix arrays, which retains the theoretical performance of previous work and represents an improvement in practice. our experiments indicate that the resulting text index offers state-of-the-art compression. in particular, we require roughly 20&percnt; of the original text size---without requiring a separate instance of the text. we can additionally use a simple notion to encode and decode block-sorting transforms (such as the burrows--wheeler transform), achieving a compression ratio comparable to that of bzip2. we also provide a compressed representation of suffix trees (and their associated text) in a total space that is comparable to that of the text alone compressed with gzip.
minimizing mean flow time for uet tasks. we consider the problem of scheduling a set of n unit-execution-time (uet) tasks, with precedence constraints, on m &ge; 1 parallel and identical processors so as to minimize the mean flow time. for two processors, the coffman--graham algorithm gives a schedule that simultaneously minimizes the mean flow time and the makespan. the problem becomes strongly np-hard for an arbitrary number of processors, although the complexity is not known for each fixed m &ge; 3. for arbitrary precedence constraints, we show that the coffman--graham algorithm gives a schedule with a worst-case bound no more than 2, and we give examples showing that the bound is tight. for intrees, the problem can be solved in polynomial time for each fixed m &ge; 1, although the complexity is not known for an arbitrary number of processors. we show that hu's algorithm (which is optimal for the makespan objective) yields a schedule with a worst-case bound no more than 1.5, and we give examples showing that the ratio can approach 1.308999.
the register function for -ary trees. for the register function for t-ary trees, recently introduced by auber et al., we prove that the average is log4n &plus; o(1), if all such trees with n internal nodes are considered to be equally likely.this result remains true for rooted trees where the set of possible out-degrees is finite. furthermore we obtain exponential tail estimates for the distribution of the register function. thus, the distribution is highly concentrated around the mean value.
quasiconvex analysis of multivariate recurrence equations for backtracking algorithms. we consider a class of multivariate recurrences frequently arising in the worst-case analysis of davis-putnam-style exponential-time backtracking algorithms for np-hard problems. we describe a technique for proving asymptotic upper bounds on these recurrences, by using a suitable weight function to reduce the problem to that of solving univariate linear recurrences; show how to use quasiconvex programming to determine the weight function yielding the smallest upper bound; and prove that the resulting upper bounds are within a polynomial factor of the true asymptotics of the recurrence. we develop and implement a multiple-gradient descent algorithm for the resulting quasiconvex programs, using a real-number arithmetic package for guaranteed accuracy of the computed worst-case time bounds.
online topological ordering. it is shown that the problem of maintaining the topological order of the nodes of a directed acyclic graph while inserting m edges can be solved in o(min&lcub;m3/2logn, m3/2 &plus; n2logn&rcub;) time, an improvement over the best known result of o(mn). in addition, we analyze the complexity of the same algorithm with respect to the treewidth k of the underlying undirected graph. we show that the algorithm runs in time o(mklog2n) for general k and that it can be implemented to run in o(nlog n) time on trees, which is optimal. the algorithm also detects cycles in the input.
this side up! we consider two- and three-dimensional bin-packing problems where 90&deg; rotations are allowed. we improve all known asymptotic performance bounds for these problems. in particular, we show how to combine ideas from strip packing and two-dimensional bin packing to give a new algorithm for the three-dimensional strip packing problem where boxes can only be rotated sideways. we propose to call this problem &ldquo;this side up&rdquo;. our algorithm has an asymptotic performance bound of 9/4.
dense subgraph problems with output-density conditions. we consider the dense subgraph problem that extracts a subgraph, with a prescribed number of vertices, having the maximum number of edges (or total edge weight, in the weighted case) in a given graph. we give approximation algorithms with improved theoretical approximation ratios assuming that the density of the optimal output subgraph is high, where density is the ratio of number of edges (or sum of edge weights) to the number of edges in the clique on the same number of vertices. moreover, we investigate the case where the input graph is bipartite and design a randomized pseudopolynomial time approximation scheme that can become a randomized ptas, even if the size of the optimal output graph is comparatively small. this is a significant improvement in a theoretical sense, since no constant-ratio approximation algorithm was known previously if the output graph has o(n) vertices.
experimental analysis of dynamic all pairs shortest path algorithms. we present the results of an extensive computational study on dynamic algorithms for all pairs shortest path problems. we describe our implementations of the recent dynamic algorithms of king [1999] and of demetrescu and italiano [2006], and compare them to the dynamic algorithm of ramalingam and reps and to static algorithms on random, real-world and hard instances. our experimental data suggest that some of the dynamic algorithms and their algorithmic techniques can be really of practical value in many situations.
an approximation algorithm for scheduling malleable tasks under general precedence constraints. in this article, we study the problem of scheduling malleable tasks with precedence constraints. we are given m identical processors and n tasks. for each task the processing time is a function of the number of processors allotted to it. in addition, the tasks must be processed according to the precedence constraints. the goal is to minimize the makespan (maximum completion time) of the resulting schedule. the best previous approximation algorithm (that works in two phases) in lep&egrave;re et al. [2002b] has a ratio 3 &plus; &sqrt;5&approx; 5.236. we develop an improved approximation algorithm with a ratio at most 100/43 &plus; 100(&sqrt;4349 &minus; 7)/2451 &approx; 4.730598. we also show that our resulting ratio is asymptotically tight.
the minimum generalized vertex cover problem. let g &equals; (v, e) be an undirected graph, with three numbers d0(e) &ge; d1(e) &ge; d2(e) &ge; 0 for each edge e &isin; e. a solution is a subset u &sube; v and di(e) represents the cost contributed to the solution by the edge e if exactly i of its endpoints are in the solution. the cost of including a vertex v in the solution is c(v). a solution has cost that is equal to the sum of the vertex costs and the edge costs. the minimum generalized vertex cover problem is to compute a minimum cost set of vertices. we study the complexity of the problem with the costs d0(e) &equals; 1, d1(e) &equals; &alpha; and d2(e) &equals; 0 &forall;e &isin; e and c(v) &equals; &beta;&forall;v &isin; v, for all possible values of &alpha; and &beta;. we also provide 2-approximation algorithms for the general case.
generic quantum fourier transforms. the quantum fourier transform (qft) is a principal ingredient appearing in many efficient quantum algorithms. we present a generic framework for the construction of efficient quantum circuits for the qft by &ldquo;quantizing&rdquo; the highly successful separation of variables technique for the construction of efficient classical fourier transforms. specifically, we apply bratteli diagrams, gel'fand-tsetlin bases, and strong generating sets of small adapted diameter to provide efficient quantum circuits for the qft over a wide variety of finite abelian and non-abelian groups, including all families of groups for which efficient qfts are currently known and many new families as well. moreover, our method provides the first subexponential-size quantum circuits for the qft over the linear groups glk(q), slk(q), and the finite groups of lie type, for any fixed prime power q.
minimizing total completion time on uniform machines with deadline constraints. consider n independent jobs and m uniform machines in parallel. each job has a processing requirement and a deadline. all jobs are available for processing at time t &equals; 0. job j must complete its processing before or at its deadline and preemptions are allowed. a set of jobs is said to be feasible if there exists a schedule that meets all the deadlines. we present a polynomial-time algorithm that given a feasible set of jobs, constructs a schedule that minimizes the total completion time &sum;cj. in the classical &alpha; &verbar; &beta; &verbar; &gamma; scheduling notation, this problem is referred to as qm &verbar; prmt, &dmacr;j &verbar; &sum;cj. it is well known that a generalization of this problem with regard to its machine environment results in an np-hard problem.
fault-tolerant facility location. we consider a fault-tolerant generalization of the classical uncapacitated facility location problem, where each client j has a requirement that rj distinct facilities serve it, instead of just one. we give a 2.076-approximation algorithm for this problem using lp rounding, which is currently the best-known performance guarantee. our algorithm exploits primal and dual complementary slackness conditions and is based on clustered randomized rounding. a technical difficulty that we overcome is the presence of terms with negative coefficients in the dual objective function, which makes it difficult to bound the cost in terms of dual variables. for the case where all requirements are the same, we give a primal-dual 1.52-approximation algorithm. we also consider a fault-tolerant version of the k-median problem. in the metric k-median problem, we are given n points in a metric space. we must select k of these to be centers, and then assign each input point j to the selected center that is closest to it. in the fault-tolerant version we want j to be assigned to rj distinct centers. the goal is to select the k centers so as to minimize the sum of assignment costs. the primal-dual algorithm for fault-tolerant facility location with uniform requirements also yields a 4-approximation algorithm for the fault-tolerant k-median problem for this case. this the first constant-factor approximation algorithm for the uniform requirements case.
efficient algorithms for bichromatic separability. a closed solid body separates one point set from another if it contains the former and the closure of its complement contains the latter. we present a near-linear algorithm for deciding whether two sets of n points in &#x211d;3 can be separated by a prism, near-quadratic algorithms for separating by a slab or a wedge, and a near-cubic algorithm for separating by a double wedge. the latter three algorithms improve the previous best known results by an order of magnitude, while the prism separability algorithm constitutes an improvement of two orders of magnitude.
robust subgraphs for trees and paths. consider a graph problem which is associated with a parameter, for example, that of finding a longest tour spanning k vertices. the following question is natural: is there a small subgraph that contains an optimal or near optimal solution for every possible value of the given parameter? such a subgraph is said to be robust. in this article we consider the problems of finding heavy paths and heavy trees of k edges. in these two cases, we prove surprising bounds on the size of a robust subgraph for a variety of approximation ratios. for both problems, we show that in every complete weighted graph on n vertices there exists a subgraph with approximately &alpha;/1&minus;&alpha;2n edges that contains an &alpha;-approximate solution for every k &equals; 1,&hellip;, n &minus; 1. in the analysis of the tree problem, we also describe a new result regarding balanced decomposition of trees. in addition, we consider variants in which the subgraph itself is restricted to be a path or a tree. for these problems, we describe polynomial time algorithms and corresponding proofs of negative results.
oracles for bounded-length shortest paths in planar graphs. we present a new approach for answering short path queries in planar graphs. for any fixed constant k and a given unweighted planar graph g &equals; (v, e), one can build in o(&verbar;v&verbar;) time a data structure, which allows to check in o(1) time whether two given vertices are at distance at most k in g and if so a shortest path between them is returned. graph g can be undirected as well as directed.our data structure works in fully dynamic environment. it can be updated in o(1) time after removing an edge or a vertex while updating after an edge insertion takes polylogarithmic amortized time. besides deleting elements one can also disable ones for some time. it is motivated by a practical situation where nodes or links of a network may be temporarily out of service.our results can be easily generalized to other wide classes of graphs---for instance we can take any minor-closed family of graphs.
the np-completeness column: the many limits on approximation. this is the 25th edition of a column that covers new developments in the theory of np-completeness. the presentation is modeled on that which m. r. garey and i used in our book computers and intractability: a guide to the theory of np-completeness, w. h. freeman & co., new york, 1979, hereinafter referred to as &ldquo;[g&j].&rdquo; previous columns, the first 23 of which appeared in journal of algorithms, will be referred to by a combination of their sequence number and year of appearance, for example, [col 1, 1981]. full bibliographic details on the previous columns as well as downloadable unofficial versions of them can be found at http://www.reseach.att.com/~dsj/columns/. this edition of the column discusses the wide range of lower bounds on approximation guarantees for np-hard optimization problems both in their functional forms and in the hypotheses on which they depend.
online scheduling of splittable tasks. we consider online scheduling of splittable tasks on parallel machines, where the goal is to minimize the last completion time (the makespan). in our model, each task can be split into a limited number of parts, that can then be scheduled independently and in parallel. we consider both the case where the machines are identical and the case where some subset of the machines have a (fixed) higher speed than the others. we design a class of algorithms that allows us to give tight bounds for a large class of cases where tasks may be split into relatively many parts. for identical machines, we also improve upon the natural greedy algorithm in other classes of cases.
an improved algorithm for cioq switches. the problem of maximizing the weighted throughput in various switching settings has been intensively studied recently through competitive analysis. to date, the most general model that has been investigated is the standard cioq (combined input and output queued) switch architecture with internal fabric speedup s &ge; 1. cioq switches, that comprise the backbone of packet routing networks, are n &times; n switches controlled by a switching policy that incorporates two components: admission control and scheduling. an admission control strategy is essential to determine the packets stored in the fifo queues in input and output ports, while the scheduling policy conducts the transfer of packets through the internal fabric, from input ports to output ports. the online problem of maximizing the total weighted throughput of cioq switches was recently investigated by kesselman and ros&eacute;n [2003]. they presented two different online algorithms for the general problem that achieve non-constant competitive ratios (linear in either the speedup or the number of distinct values, or logarithmic in the value range). we introduce the first constant-competitive algorithm for the general case of the problem, with arbitrary speedup and packet values. specifically, our algorithm is 8-competitive, and is also simple and easy to implement.
improved results for data migration and open shop scheduling. the data migration problem is to compute an efficient plan for moving data stored on devices in a network from one configuration to another. we consider this problem with the objective of minimizing the sum of completion times of all storage devices. it is modeled by a transfer graph, where vertices represent the storage devices, and the edges indicate the data transfers required between pairs of devices. each vertex has a nonnegative weight, and each edge has a release time and a processing time. a vertex completes when all the edges incident on it complete; the constraint is that two edges incident on the same vertex cannot be processed simultaneously. the objective is to minimize the sum of weighted completion times of all vertices. kim (journal of algorithms, 55:42--57, 2005) gave a 9-approximation algorithm for the problem when edges have arbitrary processing times and are released at time zero. we improve kim's result by giving a 5.06-approximation algorithm. we also address the open shop scheduling problem, o&verbar;rj&verbar; &sum;wjcj, and show that it is a special case of the data migration problem. queyranne and sviridenko (journal of scheduling, 5:287-305, 2002) gave a 5.83-approximation algorithm for the nonpreemptive version of the open shop problem. they state as an obvious open question whether there exists an algorithm for open shop scheduling that gives a performance guarantee better than 5.83. our 5.06 algorithm for data migration proves the existence of such an algorithm. crucial to our improved result is a property of the linear programming relaxation for the problem. similar linear programs have been used for various other scheduling problems. our technique may be useful in obtaining improved results for these problems as well.
optimal constrained graph exploration. we address the problem of constrained exploration of an unknown graph g &equals; (v, e) from a given start node s with either a tethered robot or a robot with a fuel tank of limited capacity, the former being a tighter constraint. in both variations of the problem, the robot can only move along the edges of the graph, for example, it cannot jump between nonadjacent nodes. in the tethered robot case, if the tether (rope) has length l, then the robot must remain within distance l from the start node s. in the second variation, a fuel tank of limited capacity forces the robot to return to s after traversing c edges. the efficiency of algorithms for both variations of the problem is measured by the number of edges traversed during the exploration. we present an algorithm for a tethered robot that explores the graph in &theta;(&verbar;e&verbar;) edge traversals. the problem of exploration using a robot with a limited fuel tank capacity can be solved with a simple reduction from the tethered robot case and also yields a &theta;(&verbar;e&verbar;) algorithm. this improves on the previous best-known bound of o(&verbar;e&verbar; &plus; &verbar;v&verbar;log2&verbar;v&verbar;). since the lower bound for the graph exploration problems is &ohm;(&verbar;e&verbar;), our algorithm is optimal within a constant factor.
rank-maximal matchings. suppose that each member of a set a of applicants ranks a subset of a set p of posts in an order of preference, possibly involving ties. a matching is a set of (applicant, post) pairs such that each applicant and each post appears in at most one pair. a rank-maximal matching is one in which the maximum possible number of applicants are matched to their first choice post, and subject to that condition, the maximum possible number are matched to their second choice post, and so on. this is a relevant concept in any practical matching situation and it was first studied by irving [2003].we give an algorithm to compute a rank-maximal matching with running time o(min(n &plus; c,c &sqrt;n)m), where c is the maximal rank of an edge used in a rank-maximal matching, n is the number of applicants and posts and m is the total size of the preference lists.
a loopless gray code for rooted trees. beyer and hedetniemi [1980] gave the first constant average-time algorithm for the generation of all rooted trees with n nodes. this article presents the first combinatorial gray code for these trees and a loopless algorithm for its generation.
generating rooted and free plane trees. this article has two main results. first, we develop a simple algorithm to list all nonisomorphic rooted plane trees in lexicographic order using a level sequence representation. then, by selecting a unique centroid to act as the root of a free plane tree, we apply the rooted plane tree algorithm to develop an algorithm to list all nonisomorphic free plane trees. the latter algorithm also uses a level sequence representation and lists all free plane trees with a unique centroid first followed by all free plane trees with two centroids. both algorithms are proved to run in constant amortized time using straightforward bounding methods.
pattern matching for arc-annotated sequences. we study pattern matching for arc-annotated sequences. an o(nm) time algorithm is given for the problem to determine whether a length m sequence with nested arc annotation is an arc-preserving subsequence (aps) of a length n sequence with nested arc annotation, called aps(nested,nested). arc-annotated sequences and, in particular, those with nested arc annotation are motivated by applications in rna structure comparison. our algorithm generalizes results for ordered tree inclusion problems and it is useful for recent fixed-parameter algorithms for lapcs(nested,nested), which is the problem of computing a longest arc-preserving common subsequence of two sequences with nested arc annotations. in particular, the presented dynamic programming methodology implies a quadratic-time algorithm for an open problem posed by vialette.
melding priority queues. we show that any priority queue data structure that supports insert, delete, and find-min operations in pq(n) amortized time, where n is an upper bound on the number of elements in the priority queue, can be converted into a priority queue data structure that also supports fast meld operations with essentially no increase in the amortized cost of the other operations. more specifically, the new data structure supports insert, meld and find-min operations in o(1) amortized time, and delete operations in o(pq(n) &plus; &alpha;(n)) amortized time, where &alpha;(n) is a functional inverse of the ackermann function, and where n this time is the total number of operations performed on all the priority queues. the construction is very simple. the meldable priority queues are obtained by placing a nonmeldable priority queues at each node of a union-find data structure. we also show that when all keys are integers in the range [1, n], we can replace n in the bound stated previously by min&lcub;n, n&rcub;.applying this result to the nonmeldable priority queue data structures obtained recently by thorup [2002b] and by han and thorup [2002] we obtain meldable ram priority queues with o(log log n) amortized time per operation, or o(&sqrt;log log n) expected amortized time per operation, respectively. as a by-product, we obtain improved algorithms for the minimum directed spanning tree problem on graphs with integer edge weights, namely, a deterministic o(m log log n)-time algorithm and a randomized o(m&sqrt;log log n)-time algorithm. for sparse enough graphs, these bounds improve on the o(m &plus; n log n) running time of an algorithm by gabow et al. [1986] that works for arbitrary edge weights.
a general approach to online network optimization problems. we study a wide range of online graph and network optimization problems, focusing on problems that arise in the study of connectivity and cuts in graphs. in a general online network design problem, we have a communication network known to the algorithm in advance. what is not known in advance are the connectivity (bandwidth) or cut demands between vertices in the network which arrive online.we develop a unified framework for designing online algorithms for problems involving connectivity and cuts. we first present a general o(log m)-competitive deterministic algorithm for generating a fractional solution that satisfies the online connectivity or cut demands, where m is the number of edges in the graph. this may be of independent interest for solving fractional online bandwidth allocation problems, and is applicable to both directed and undirected graphs. we then show how to obtain integral solutions via an online rounding of the fractional solution. this part of the framework is problem dependent, and applies various tools including results on approximate max-flow min-cut for multicommodity flow, the hierarchically separated trees (hst) method and its extensions, certain rounding techniques for dependent variables, and r&auml;cke's new hierarchical decomposition of graphs.specifically, our results for the integral case include an o(log mlog n)-competitive randomized algorithm for the online nonmetric facility location problem and for a generalization of the problem called the multicast problem. in the nonmetric facility location problem, m is the number of facilities and n is the number of clients. the competitive ratio is nearly tight. we also present an o(log2nlog k)-competitive randomized algorithm for the online group steiner problem in trees and an o(log3nlog k)-competitive randomized algorithm for the problem in general graphs, where n is the number of vertices in the graph and k is the number of groups. finally, we design a deterministic o(log3nlog log n)-competitive algorithm for the online multi-cut problem.
an improved algorithm for radio broadcast. we show that for every radio network g &equals; (v, e) and source s &isin; v, there exists a radio broadcast schedule for g of length rad(g, s) &plus; o(&sqrt;rad(g, s) &sdot;log2 n) &equals; o(rad(g, s) &plus; log4 n), where rad(g, s) is the radius of the radio network g with respect to the source s. this result improves the previously best-known upper bound of o(rad(g, s) &plus; log5 n) due to gaber and mansour [1995]. for graphs with small genus, particularly for planar graphs, we provide an even better upper bound of rad(g, s) &plus; o(&sqrt;rad(g,s) &sdot; log n &plus; log3 n) &equals; o(rad(g, s) &plus; log3 n).
on the difficulty of some shortest path problems. we prove superlinear lower bounds for some shortest path problems in directed graphs, where no such bounds were previously known. the central problem in our study is the replacement paths problem: given a directed graph g with non-negative edge weights, and a shortest path p &equals; &lcub;e1, e2, &hellip;, ep&rcub; between two nodes s and t, compute the shortest path distances from s to t in each of the p graphs obtained from g by deleting one of the edges ei. we show that the replacement paths problem requires &omega;(m &sqrt;n) time in the worst case whenever m &equals; o(n &sqrt;n). our construction also implies a similar lower bound on the k shortest simple paths problem for a broad class of algorithms that includes all known algorithms for the problem. to put our lower bound in perspective, we note that both these problems (replacement paths and k shortest simple paths) can be solved in near-linear time for undirected graphs.
querying priced information in databases: the conjunctive case. query optimization that involves expensive predicates has received considerable attention in the database community. typically, the output to a database query is a set of tuples that satisfy certain conditions, and, with expensive predicates, these conditions may be computationally costly to verify. in the simplest case, when the query looks for the set of tuples that simultaneously satisfy k expensive predicates, the problem reduces to ordering the evaluation of the predicates so as to minimize the time to output the set of tuples comprising the answer to the query. we study different cases of the problem: the sequential case, in which a single processor is available to evaluate the predicates, and the distributed case, in which there are k processors available, each dedicated to a different attribute (column) of the database, and there is no communication cost between the processors. for the sequential case, we give a simple and fast deterministic k-approximation algorithm, and prove that k is the best possible approximation ratio for a deterministic algorithm, even if exponential time algorithms are allowed. we also propose a randomized, polynomial time algorithm with expected approximation ratio 1 &plus; &sqrt;2/2 &ap; 1.707 for k &equals; 2, and prove that 3/2 is the best possible expected approximation ratio for randomized algorithms. we also show that given 0 &le; &epsiv; &le; 1, no randomized algorithm achieves approximation ratio smaller than 1 &plus; &epsiv; with probability larger than (1 &plus; &epsiv;)/2. for the distributed case, we consider two different models: the preemptive model, in which a processor is allowed to interrupt the evaluation of a predicate, and the nonpreemptive model, in which the evaluation of a predicate must be completed once started. we show that k is the best possible approximation ratio for a deterministic algorithm, even if exponential time algorithms are allowed. for the preemptive model, we introduce a polynomial time k-approximation algorithm. for the nonpreemptive model, we introduce a polynomial time o(k log2 k)-approximation algorithm.
the string edit distance matching problem with moves. the edit distance between two strings s and r is defined to be the minimum number of character inserts, deletes, and changes needed to convert r to s. given a text string t of length n, and a pattern string p of length m, informally, the string edit distance matching problem is to compute the smallest edit distance between p and substrings of t. we relax the problem so that: (a) we allow an additional operation, namely, substring moves; and (b) we allow approximation of this string edit distance. our result is a near-linear time deterministic algorithm to produce a factor of o(log n log&ast; n) approximation to the string edit distance with moves. this is the first known significantly subquadratic algorithm for a string edit distance problem in which the distance involves nontrivial alignments. our results are obtained by embedding strings into l1 vector space using a simplified parsing technique, which we call edit-sensitive parsing (esp).
tight bounds for worst-case equilibria. we study the problem of traffic routing in noncooperative networks. in such networks, users may follow selfish strategies to optimize their own performance measure and therefore, their behavior does not have to lead to optimal performance of the entire network. in this article we investigate the worst-case coordination ratio, which is a game-theoretic measure aiming to reflect the price of selfish routing. following a line of previous work, we focus on the most basic networks consisting of parallel links with linear latency functions. our main result is that the worst-case coordination ratio on m parallel links of possibly different speeds is &theta;(log m/log log log m). in fact, we are able to give an exact description of the worst-case coordination ratio, depending on the number of links and ratio of speed of the fastest link over the speed of the slowest link. for example, for the special case in which all m parallel links have the same speed, we can prove that the worst-case coordination ratio is &gamma;(&minus;1) (m) &plus; &theta;(1), with &gamma; denoting the gamma (factorial) function. our bounds entirely resolve an open problem posed recently by koutsoupias and papadimitriou [1999].
entropy-based bounds for online algorithms. we focus in this work on an aspect of online computation that is not addressed by standard competitive analysis, namely, identifying request sequences for which nontrivial online algorithms are useful versus request sequences for which all algorithms perform equally poorly. the motivations for this work are advanced system and architecture designs which allow the operating system to dynamically allocate resources to online protocols such as prefetching and caching. to utilize these features, the operating system needs to identify data streams that can benefit from more resources. our approach in this work is based on the relation between entropy, compression, and gambling, extensively studied in information theory. it has been shown that in some settings, entropy can either fully or at least partially characterize the expected outcome of an iterative gambling game. our goal is to study the extent to which the entropy of the input characterizes the expected performance of online algorithms for problems that arise in computer applications. we study bounds based on entropy for three classical online problems---list accessing, prefetching, and caching. our bounds relate the performance of the best online algorithm to the entropy, a parameter intrinsic to characteristics of the request sequence. this is in contrast to the competitive ratio parameter of competitive analysis, which quantifies the performance of the online algorithm with respect to an optimal offline algorithm. for the prefetching problem, we give explicit upper and lower bounds for the performance of the best prefetching algorithm in terms of the entropy of the request sequence. in contrast, we show that the entropy of the request sequence alone does not fully capture the performance of online list accessing and caching algorithms.
a data structure for a sequence of string accesses in external memory. we introduce a new paradigm for querying strings in external memory, suited to the execution of sequences of operations. formally, given a dictionary of n strings s1, &hellip;, sn, we aim at supporting a search sequence for m not necessarily distinct strings t1, t2, &hellip;, tm, as well as inserting and deleting individual strings. the dictionary is stored on disk, where each access to a disk page fetches b items, the cost of an operation is the number of pages accessed (i/os), and efficiency must be attained on entire sequences of string operations rather than on individual ones. our approach relies on a novel and conceptually simple self-adjusting data structure (sasl) based on skip lists, that is also interesting per se. the search for the whole sequence t1, t2, &hellip;, tm can be done in an expected number of i/os: o(&sum;j&equals;1m &verbar;tj&verbar;/b &plus; &sum;i&equals;1nn (ni logb m/ni)), where each tj may or may not be present in the dictionary, and ni is the number of times si is queried (i.e., the number of tjs equal to si). moreover, inserting or deleting a string si takes an expected amortized number o(&verbar;si&verbar;/b &plus; logb n) of i/os. the term &sum;j&equals;1m &verbar;tj&verbar;/b in the search formula is a lower bound for reading the input, and the term &sum;i&equals;1n ni logb m/ni (entropy of the query sequence) is a standard information-theoretic lower bound. we regard this result as the static optimality theorem for external-memory string access, as compared to sleator and tarjan's classical theorem for numerical dictionaries [sleator and tarjan 1985]. finally, we reformulate the search bound if a cache is available, taking advantage of common prefixes among the strings examined in the search.
algorithmic aspects of bandwidth trading. we study algorithmic problems that are motivated by bandwidth trading in next-generation networks. typically, bandwidth trading involves sellers (e.g., network operators) interested in selling bandwidth pipes that offer to buyers a guaranteed level of service for a specified time interval. the buyers (e.g., bandwidth brokers) are looking to procure bandwidth pipes to satisfy the reservation requests of end-users (e.g., internet subscribers). depending on what is available in the bandwidth exchange, the goal of a buyer is to either spend the least amount of money so as to satisfy all the reservations made by its customers, or to maximize its revenue from whatever reservations can be satisfied. we model this as a real-time nonpreemptive scheduling problem in which machine types correspond to bandwidth pipes and jobs correspond to end-user reservation requests. each job specifies a time interval during which it must be processed, and a set of machine types on which it can be executed. if necessary, multiple machines of a given type may be allocated, but each must be paid for. finally, each job has associated with it a revenue, which is realized if the job is scheduled on some machine. there are two versions of the problem that we consider. in the cost minimization version, the goal is to minimize the total cost incurred for scheduling all jobs, and in the revenue maximization version the goal is to maximize the revenue of the jobs that are scheduled for processing on a given set of machines. we consider several variants of the problems that arise in practical scenarios, and provide constant factor approximations.
minimizing weighted flow time. we consider the problem of minimizing the total weighted flow time on a single machine with preemptions. we give an online algorithm that is o(k)-competitive for k weight classes. this implies an o(log w)-competitive algorithm, where w is the maximum to minimum ratio of weights. this algorithm also implies an o(log n &plus; log p)-approximation ratio for the problem, where p is the ratio of the maximum to minimum job size and n is the number of jobs. we also consider the nonclairvoyant setting where the size of a job is unknown upon its arrival and becomes known to the scheduler only when the job meets its service requirement. we consider the resource augmentation model, and give a (1 &plus; &epsiv;)-speed, (1 &plus;1/&epsiv;)-competitive online algorithm.
an () algorithm for incremental topological ordering. we present a simple algorithm which maintains the topological order of a directed acyclic graph (dag) with n nodes, under an online edge insertion sequence, in o(n2.75) time, independent of the number m of edges inserted. for dense dags, this is an improvement over the previous best result of o(min{m3/2 log n, m3/2 + n2 log n}) by katriel and bodlaender [2006]. we also provide an empirical comparison of our algorithm with other algorithms for incremental topological sorting.
computing equilibria for a service provider game with (im)perfect information. we study fundamental algorithmic questions concerning the complexity of market equilibria under perfect and imperfect information by means of a basic microeconomic game. suppose a provider offers a service to a set of potential customers. each customer has a particular demand of service and her behavior is determined by a utility function that is nonincreasing in the sum of demands that are served by the provider.classical game theory assumes complete information: the provider has full knowledge of the behavior of all customers. we present a complete characterization of the complexity of computing optimal pricing strategies and of computing best/worst equilibria in this model. basically, we show that most of these problems are inapproximable in the worst case but admit an fpas in the average case. our average case analysis covers large classes of distributions for customer utilities. we generalize our analysis to robust equilibria in which players change their strategies only when this promises a significant utility improvement.a more realistic model considers providers with incomplete information. following the game theoretic framework of bayesian games introduced by harsanyi, the provider is aware of probability distributions describing the behavior of the customers and aims at estimating its expected revenue under best/worst equilibria. somewhat counterintuitively, we obtain an fpras for the equilibria problem in the model with imperfect information although the problem with perfect information is inapproximable under the worst-case measures. in particular, the worst-case complexity of the considered problems increases with the precision of the available knowledge.
improved approximation results for the stable marriage problem. the stable marriage problem has recently been studied in its general setting, where both ties and incomplete lists are allowed. it is np-hard to find a stable matching of maximum size, while any stable matching is a maximal matching and thus trivially we can obtain a 2-approximation algorithm. in this article, we give the first nontrivial result for approximation of factor less than two. our algorithm achieves an approximation ratio of 2/(1 &plus; l&minus;2) for instances in which only men have ties of length at most l. when both men and women are allowed to have ties but the lengths are limited to two, then we show a ratio of 13/7(<1.858). we also improve the lower bound on the approximation ratio to 21/19(>1.1052).
dynamic text and static pattern matching. in this article, we address a new version of dynamic pattern matching. the dynamic text and static pattern matching problem is the problem of finding a static pattern in a text that is continuously being updated. the goal is to report all new occurrences of the pattern in the text after each text update. we present an algorithm for solving the problem where the text update operation is changing the symbol value of a text location. given a text of length n and a pattern of length m, our algorithm preprocesses the text in time o(n log log m), and the pattern in time o(m log m). the extra space used is o(n &plus; m log m). following each text update, the algorithm deletes all prior occurrences of the pattern that no longer match, and reports all new occurrences of the pattern in the text in o(log log m) time. we note that the complexity is not proportional to the number of pattern occurrences, since all new occurrences can be reported in a succinct form.
compressed indexes for dynamic text collections. let t be a string with n characters over an alphabet of constant size. a recent breakthrough on compressed indexing allows us to build an index for t in optimal space (i.e., o(n) bits), while supporting very efficient pattern matching [ferragina and manzini 2000; grossi and vitter 2000]. yet the compressed nature of such indexes also makes them difficult to update dynamically. this article extends the work on optimal-space indexing to a dynamic collection of texts. our first result is a compressed solution to the library management problem, where we show an index of o(n) bits for a text collection l of total length n, which can be updated in o(&verbar;t&verbar; log n) time when a text t is inserted or deleted from l; also, the index supports searching the occurrences of any pattern p in all texts in l in o(&verbar;p&verbar; log n &plus; occ log2 n) time, where occ is the number of occurrences. our second result is a compressed solution to the dictionary matching problem, where we show an index of o(d) bits for a pattern collection d of total length d, which can be updated in o(&verbar;p&verbar; log2 d) time when a pattern p is inserted or deleted from d; also, the index supports searching the occurrences of all patterns of d in any text t in o((&verbar;t&verbar; &plus; occ)log2 d) time. when compared with the o(d log d)-bit suffix-tree-based solution of amir et al. [1995], the compact solution increases the query time by roughly a factor of log d only. the solution to the dictionary matching problem is based on a new compressed representation of a suffix tree. precisely, we give an o(n)-bit representation of a suffix tree for a dynamic collection of texts whose total length is n, which supports insertion and deletion of a text t in o(&verbar;t&verbar; log2 n) time, as well as all suffix tree traversal operations, including forward and backward suffix links. this work can be regarded as a generalization of the compressed representation of static texts. in the study of the aforementioned result, we also derive the first o(n)-bit representation for maintaining n pairs of balanced parentheses in o(log n/log log n) time per operation, matching the time complexity of the previous o(n log n)-bit solution.
compressed representations of sequences and full-text indexes. given a sequence s &equals; s1s2&hellip;sn of integers smaller than r &equals; o(polylog(n)), we show how s can be represented using nh0(s) &plus; o(n) bits, so that we can know any sq, as well as answer rank and select queries on s, in constant time. h0(s) is the zero-order empirical entropy of s and nh0(s) provides an information-theoretic lower bound to the bit storage of any sequence s via a fixed encoding of its symbols. this extends previous results on binary sequences, and improves previous results on general sequences where those queries are answered in o(log r) time. for larger r, we can still represent s in nh0(s) &plus; o(n log r) bits and answer queries in o(log r/log log n) time. another contribution of this article is to show how to combine our compressed representation of integer sequences with a compression boosting technique to design compressed full-text indexes that scale well with the size of the input alphabet &sigma;. specifically, we design a variant of the fm-index that indexes a string t[1, n] within nhk(t) &plus; o(n) bits of storage, where hk(t) is the kth-order empirical entropy of t. this space bound holds simultaneously for all k &le; &alpha; log&verbar;&sigma;&verbar; n, constant 0 < &alpha; < 1, and &verbar;&sigma;&verbar; &equals; o(polylog(n)). this index counts the occurrences of an arbitrary pattern p[1, p] as a substring of t in o(p) time; it locates each pattern occurrence in o(log1&plus;&epsiv; n) time for any constant 0 < &epsiv; < 1; and reports a text substring of length &ell; in o(&ell; &plus; log1&plus;&epsiv; n) time. compared to all previous works, our index is the first that removes the alphabet-size dependance from all query times, in particular, counting time is linear in the pattern length. still, our index uses essentially the same space of the kth-order entropy of the text t, which is the best space obtained in previous work. we can also handle larger alphabets of size &verbar;&sigma;&verbar; &equals; o(n&beta;), for any 0 < &beta; < 1, by paying o(n log&verbar;&sigma;&verbar;) extra space and multiplying all query times by o(log &verbar;&sigma;&verbar;/log log n).
a simple entropy-based algorithm for planar point location. given a planar polygonal subdivision s, point location involves preprocessing this subdivision into a data structure so that given any query point q, the cell of the subdivision containing q can be determined efficiently. suppose that for each cell z in the subdivision, the probability pz that a query point lies within this cell is also given. the goal is to design the data structure to minimize the average search time. this problem has been considered before, but existing data structures are all quite complicated. it has long been known that the entropy h of the probability distribution is the dominant term in the lower bound on the average-case search time. in this article, we show that a very simple modification of a well-known randomized incremental algorithm can be applied to produce a data structure of expected linear size that can answer point-location queries in o(h) average time. we also present empirical evidence for the practical efficiency of this approach.
nearest-neighbor-preserving embeddings. in this article we introduce the notion of nearest-neighbor-preserving embeddings. these are randomized embeddings between two metric spaces which preserve the (approximate) nearest-neighbors. we give two examples of such embeddings for euclidean metrics with low &ldquo;intrinsic&rdquo; dimension. combining the embeddings with known data structures yields the best-known approximate nearest-neighbor data structures for such metrics.
phase changes in random point quadtrees. we show that a wide class of linear cost measures (such as the number of leaves) in random d-dimensional point quadtrees undergo a change in limit laws: if the dimension d &equals; 1, &hellip;, 8, then the limit law is normal; if d &ge; 9 then there is no convergence to a fixed limit law. stronger approximation results such as convergence rates and local limit theorems are also derived for the number of leaves, additional phase changes being unveiled. our approach is new and very general, and also applicable to other classes of search trees. a brief discussion of devroye's grid trees (covering m-ary search trees and quadtrees as special cases) is given. we also propose an efficient numerical procedure for computing the constants involved to high precision.
an algorithm for deciding zero equivalence of nested polynomially recurrent sequences. we introduce the class of nested polynomially recurrent sequences which includes a large number of sequences that are of combinatorial interest. we present an algorithm for deciding zero equivalence of these sequences, thereby providing a new algorithm for proving identities among combinatorial sequences: in order to prove an identity, decide by the algorithm whether the difference of lefthand-side and righthand-side is identically zero. this algorithm is able to treat mathematical objects which are not covered by any other known symbolic method for proving combinatorial identities. despite its theoretical flavor and high complexity, an implementation of the algorithm can be successfully applied to nontrivial examples.
windows scheduling as a restricted version of bin packing. given is a sequence of n positive integers w1,w2,&hellip;,wn that are associated with the items 1,2,&hellip;n, respectively. in the windows scheduling problem, the goal is to schedule all the items (equal-length information pages) on broadcasting channels such that the gap between two consecutive appearances of page i on any of the channels is at most wi slots (a slot is the transmission time of one page). in the unit-fractions bin packing problem, the goal is to pack all the items in bins of unit size where the size (width) of item i is 1/wi. the optimization objective is to minimize the number of channels or bins. in the offline setting, the sequence is known in advance, whereas in the online setting, the items arrive in order and assignment decisions are irrevocable. since a page requires at least 1/wi of a channel's bandwidth, it follows that windows scheduling without migration (i.e., all broadcasts of a page must be from the same channel) is a restricted version of unit-fractions bin packing. let h &equals; &lceil;&sumi&equals;1n(1/wi) be the bandwidth lower bound on the required number of bins (channels). the best-known offline algorithm for the windows scheduling problem used h &plus; o(ln h) channels. this article presents an offline algorithm for the unit-fractions bin packing problem with at most h &plus; 1 bins. in the online setting, this article presents algorithms for both problems with h &plus; o(&sqrt;h) channels or bins, where the one for the unit-fractions bin packing problem is simpler. on the other hand, this article shows that already for the unit-fractions bin packing problem, any online algorithm must use at least h&plus;&omega(ln h) bins. for instances in which the window sizes form a divisible sequence, an optimal online algorithm is presented. finally, this article includes a new np-hardness proof for the windows scheduling problem.
multicommodity demand flow in a tree and packing integer programs. we consider requests for capacity in a given tree network t &equals; (v, e) where each edge e of the tree has some integer capacity ue. each request f is a node pair with an integer demand df and a profit wf which is obtained if the request is satisfied. the objective is to find a set of demands that can be feasibly routed in the tree and which provides a maximum profit. this generalizes well-known problems, including the knapsack and b-matching problems. when all demands are 1, we have the integer multicommodity flow problem. garg et al. [1997] had shown that this problem is np-hard and gave a 2-approximation algorithm for the cardinality case (all profits are 1) via a primal-dual algorithm. our main result establishes that the integrality gap of the natural linear programming relaxation is at most 4 for the case of arbitrary profits. our proof is based on coloring paths on trees and this has other applications for wavelength assignment in optical network routing. we then consider the problem with arbitrary demands. when the maximum demand dmax is at most the minimum edge capacity umin, we show that the integrality gap of the lp is at most 48. this result is obtained by showing that the integrality gap for the demand version of such a problem is at most 11.542 times that for the unit-demand case. we use techniques of kolliopoulos and stein [2004, 2001] to obtain this. we also obtain, via this method, improved algorithms for line and ring networks. applications and connections to other combinatorial problems are discussed.
multiplierless multiple constant multiplication. a variable can be multiplied by a given set of fixed-point constants using a multiplier block that consists exclusively of additions, subtractions, and shifts. the generation of a multiplier block from the set of constants is known as the multiple constant multiplication (mcm) problem. finding the optimal solution, namely, the one with the fewest number of additions and subtractions, is known to be np-complete. we propose a new algorithm for the mcm problem, which produces solutions that require up to 20&percnt; less additions and subtractions than the best previously known algorithm. at the same time our algorithm, in contrast to the closest competing algorithm, is not limited by the constant bitwidths. we present our algorithm using a unifying formal framework for the best, graph-based mcm algorithms and provide a detailed runtime analysis and experimental evaluation. we show that our algorithm can handle problem sizes as large as 100 32-bit constants in a time acceptable for most applications. the implementation of the new algorithm is available at www.spiral.net.
retroactive data structures. we introduce a new data structuring paradigm in which operations can be performed on a data structure not only in the present, but also in the past. in this new paradigm, called retroactive data structures, the historical sequence of operations performed on the data structure is not fixed. the data structure allows arbitrary insertion and deletion of operations at arbitrary times, subject only to consistency requirements. we initiate the study of retroactive data structures by formally defining the model and its variants. we prove that, unlike persistence, efficient retroactivity is not always achievable. thus, we present efficient retroactive data structures for queues, doubly ended queues, priority queues, union-find, and decomposable search structures.
strongly stable matchings in time () and extension to the hospitals-residents problem. an instance of the stable marriage problem is an undirected bipartite graph g &equals; (x &cup; w, e) with linearly ordered adjacency lists with ties allowed in the ordering. a matching m is a set of edges, no two of which share an endpoint. an edge e &equals; (a, b) &isin; e&setmn; m is a blocking edge for m if a is either unmatched or strictly prefers b to its partner in m, and b is unmatched, strictly prefers a to its partner in m, or is indifferent between them. a matching is strongly stable if there is no blocking edge with respect to it. we give an o(nm) algorithm for computing strongly stable matchings, where n is the number of vertices and m the number of edges. the previous best algorithm had running time o(m2). we also study this problem in the hospitals-residents setting, which is a many-to-one extension of the aforementioned problem. we give an o(m &sum;h&isin;hph) algorithm for computing a strongly stable matching in the hospitals-residents problem, where ph is the quota of a hospital h. the previous best algorithm had running time o(m2).
novel architectures for p2p applications: the continuous-discrete approach. we propose a new approach for constructing p2p networks based on a dynamic decomposition of a continuous space into cells corresponding to servers. we demonstrate the power of this approach by suggesting two new p2p architectures and various algorithms for them. the first serves as a dht (distributed hash table) and the other is a dynamic expander network. the dht network, which we call distance halving, allows logarithmic routing and load while preserving constant degrees. it offers an optimal tradeoff between degree and path length in the sense that degree d guarantees a path length of o(logd n). another advantage over previous constructions is its relative simplicity. a major new contribution of this construction is a dynamic caching technique that maintains low load and storage, even under the occurrence of hot spots. our second construction builds a network that is guaranteed to be an expander. the resulting topologies are simple to maintain and implement. their simplicity makes it easy to modify and add protocols. a small variation yields a dht which is robust against random byzantine faults. finally we show that, using our approach, it is possible to construct any family of constant degree graphs in a dynamic environment, though with worse parameters. therefore, we expect that more distributed data structures could be designed and implemented in a dynamic environment.
convergence time to nash equilibrium in load balancing. we study the number of steps required to reach a pure nash equilibrium in a load balancing scenario where each job behaves selfishly and attempts to migrate to a machine which will minimize its cost. we consider a variety of load balancing models, including identical, restricted, related, and unrelated machines. our results have a crucial dependence on the weights assigned to jobs. we consider arbitrary weights, integer weights, k distinct weights, and identical (unit) weights. we look both at an arbitrary schedule (where the only restriction is that a job migrates to a machine which lowers its cost) and specific efficient schedulers (e.g., allowing the largest weight job to move first). a by-product of our results is establishing a connection between various scheduling models and the game-theoretic notion of potential games. we show that load balancing in unrelated machines is a generalized ordinal potential game, load balancing in related machines is a weighted potential game, and load balancing in related machines and unit weight jobs is an exact potential game.
the relative worst order ratio for online algorithms. we define a new measure for the quality of online algorithms, the relative worst order ratio, using ideas from the max/max ratio [ben-david and borodin 1994] and from the random order ratio [kenyon 1996]. the new ratio is used to compare online algorithms directly by taking the ratio of their performances on their respective worst permutations of a worst-case sequence. two variants of the bin packing problem are considered: the classical bin packing problem, where the goal is to fit all items in as few bins as possible, and the dual bin packing problem, which is the problem of maximizing the number of items packed in a fixed number of bins. several known algorithms are compared using this new measure, and a new, simple variant of first-fit is proposed for dual bin packing. many of our results are consistent with those previously obtained with the competitive ratio or the competitive ratio on accommodating sequences, but new separations and easier proofs are found.
faster algorithms for sorting by transpositions and sorting by block interchanges. in this article, we present a new data structure, called the permutation tree, to improve the running time of sorting permutation by transpositions and sorting permutation by block interchanges. the existing 1.5-approximation algorithm for sorting permutation by transpositions has time complexity o(n3/2 &sqrt;logn). by means of the permutation tree, we can improve this algorithm to achieve time complexity o(nlogn). we can also improve the algorithm for sorting permutation by block interchanges to take its time complexity from o(n2) down to o(nlogn).
improved algorithms for weakly chordal graphs. we use a new structural theorem on the presence of two-pairs in weakly chordal graphs to develop improved algorithms. for the recognition problem, we reduce the time complexity from o(mn2) to o(m2) and the space complexity from o(n3) to o(m &plus; n), and also produce a hole or antihole if the input graph is not weakly chordal. for the optimization problems, the complexity of the clique and coloring problems is reduced from o(mn2) to o(n3) and the complexity of the independent set and clique cover problems is improved from o(n4) to o(mn). the space complexity of our optimization algorithms is o(m &plus; n).
routing and scheduling in multihop wireless networks with time-varying channels. we study routing and scheduling in multihop wireless networks. when data is transmitted from its source node to its destination node it may go through other wireless nodes as intermediate hops. the data transmission is node constrained, that is, every node can transmit data to at most one neighboring node per time step. the transmission rates are time varying as a result of changing wireless channel conditions. in this article, we assume that data arrivals and transmission rates are governed by an adversary. the power of the adversary is limited by an admissibility condition which forbids the adversary from overloading any wireless node a priori. the node-constrained transmission and time-varying nature of the transmission rates make our model different from and harder than the standard adversarial queueing model which relates to wireline networks. for the case in which the adversary specifies the paths that the data must follow, we design scheduling algorithms that ensure network stability. these algorithms try to give priority to the data that is closest to its source node. however, at each time step only a subset of the data queued at a node is eligible for scheduling. one of our algorithms is fully distributed. for the case in which the adversary does not dictate the data paths, we show how to route data so that the admissibility condition is satisfied. we can then schedule data along the chosen paths using our stable scheduling algorithms.
deterministic sampling and range counting in geometric data streams. we present memory-efficient deterministic algorithms for constructing &epsi;-nets and &epsi;-approximations of streams of geometric data. unlike probabilistic approaches, these deterministic samples provide guaranteed bounds on their approximation factors. we show how our deterministic samples can be used to answer approximate online iceberg geometric queries on data streams. we use these techniques to approximate several robust statistics of geometric data streams, including tukey depth, simplicial depth, regression depth, the thiel-sen estimator, and the least median of squares. our algorithms use only a polylogarithmic amount of memory, provided the desired approximation factors are at least inverse-polylogarithmic. we also include a lower bound for noniceberg geometric queries.
constructing pairwise disjoint paths with few links. let p be a simple polygon and let &lcub;(u1, u&prime;1), (u2, u&prime;2),&hellip;,(um, u&prime;m)&rcub; be a set of m pairs of distinct vertices of p, where for every distinct i, j &le; m, there exist pairwise disjoint (nonintersecting) paths connecting ui to u&prime;i and uj to u&prime;j. we wish to construct m pairwise disjoint paths in the interior of p connecting ui to u&prime;i for i &equals; 1, &hellip;,m, with a minimal total number of line segments. we give an approximation algorithm that constructs such a set of paths using o(m) line segments in o(n log m &plus; m log m) time, where m is the number of line segments in the optimal solution and n is the size of the polygon.
approximate parameterized matching. two equal length strings s and s&prime;, over alphabets &sigma;s and &sigma;s&prime;, parameterize match if there exists a bijection &pi; : &sigma;s &rightarrow; &sigma;s&prime; such that &pi; (s) &equals; s&prime;, where &pi; (s) is the renaming of each character of s via &pi;. parameterized matching is the problem of finding all parameterized matches of a pattern string p in a text t, and approximate parameterized matching is the problem of finding at each location a bijection &pi; that maximizes the number of characters that are mapped from p to the appropriate &verbar;p&verbar;-length substring of t. parameterized matching was introduced as a model for software duplication detection in software maintenance systems and also has applications in image processing and computational biology. for example, approximate parameterized matching models image searching with variable color maps in the presence of errors. we consider the problem for which an error threshold, k, is given, and the goal is to find all locations in t for which there exists a bijection &pi; which maps p into the appropriate &verbar;p&verbar;-length substring of t with at most k mismatched mapped elements. our main result is an algorithm for this problem with o(nk1.5 &plus; mk log m) time complexity, where m &equals; &verbar;p&verbar; and n&equals;&verbar;t&verbar;. we also show that when &verbar;p&verbar; &equals; &verbar;t&verbar; &equals; m, the problem is equivalent to the maximum matching problem on graphs, yielding a o(m &plus; k1.5) solution.
the np-completeness column: finding needles in haystacks. this is the 26th edition of a column that covers new developments in the theory of np-completeness. the presentation is modeled on that which m. r. garey and i used in our book &ldquo;computers and intractability: a guide to the theory of np-completeness,&rdquo; w. h. freeman & co., new york, 1979, hereinafter referred to as &ldquo;[g&j].&rdquo; previous columns, the first 23 of which appeared in j. algorithms, will be referred to by a combination of their sequence number and year of appearance, e.g., &ldquo;column 1 [1981].&rdquo; full bibliographic details on the previous columns, as well as downloadable unofficial versions of them, can be found at http://www.research.att.com/&sim;dsj/columns/. this column discusses the question of whether finding an object can be computationally difficult even when we know that the object exists.
sharing the cost more efficiently: improved approximation for multicommodity rent-or-buy. in the multicommodity rent-or-buy (mrob) network design problems, we are given a network together with a set of k terminal pairs (s1, t1), &hellip;, (sk, tk. the goal is to provision the network so that a given amount of flow can be shipped between si and ti for all 1 &le; i &le; k simultaneously. in order to provision the network, one can either rent capacity on edges at some cost per unit of flow, or buy them at some larger fixed cost. bought edges have no incremental, flow-dependent cost. the overall objective is to minimize the total provisioning cost. recently, gupta et al. [2003a] presented a 12-approximation for the mrob problem. their algroithm chooses a subset of the terminal pairs in the graph at random and then buys the edges of an approximate steiner forest for these pairs. this technique had previously been introduced [gupta et al. 2003b] for the single-sink rent-or-buy network design problem. in this article we give a 6.828-approximation for the mrob problem by refining the algorithm of gupta et al. and simplifying their analysis. the improvement in our article is based on a more careful adaptation and simplified analysis of the primal-dual algorithm for the steiner forest problem due to agrawal et al. [1995]. our result significantly reduces the gap between the single-sink and multisink case.
energy-efficient algorithms for flow time minimization. we study scheduling problems in battery-operated computing devices, aiming at schedules with low total energy consumption. while most of the previous work has focused on finding feasible schedules in deadline-based settings, in this article we are interested in schedules that guarantee good response times. more specifically, our goal is to schedule a sequence of jobs on a variable-speed processor so as to minimize the total cost consisting of the energy consumption and the total flow time of all jobs. we first show that when the amount of work, for any job, may take an arbitrary value, then no online algorithm can achieve a constant competitive ratio. therefore, most of the article is concerned with unit-size jobs. we devise a deterministic constant competitive online algorithm and show that the offline problem can be solved in polynomial time.
skip graphs. skip graphs are a novel distributed data structure, based on skip lists, that provide the full functionality of a balanced tree in a distributed system where resources are stored in separate nodes that may fail at any time. they are designed for use in searching peer-to-peer systems, and by providing the ability to perform queries based on key ordering, they improve on existing search tools that provide only hash table functionality. unlike skip lists or other tree data structures, skip graphs are highly resilient, tolerating a large fraction of failed nodes without losing connectivity. in addition, simple and straightforward algorithms can be used to construct a skip graph, insert new nodes into it, search it, and detect and repair errors within it introduced due to node failures.
guessing secrets efficiently via list decoding. we consider the guessing secrets problem defined by chung et al. [2001]. this is a variant of the standard 20 questions game where the player has a set of k > 1 secrets from a universe of n possible secrets. the player is asked boolean questions about the secret. for each question, the player picks one of the k secrets adversarially, and answers according to this secret. we present an explicit set of o(log n) questions together with an efficient (i.e., poly(log n) time) algorithm to solve the guessing secrets problem for the case of 2 secrets. this answers the main algorithmic question left unanswered by chung et al. [2001]. the main techniques we use are small &epsis;-biased spaces and the notion of list decoding. we also establish bounds on the number of questions needed to solve the k-secrets game for k > 2, and discuss how list decoding can be used to get partial information about the secrets, specifically to find a small core of secrets that must intersect the actual set of k secrets.
finding the shortest simple paths: a new algorithm and its implementation. we describe a new algorithm to enumerate the k shortest simple (loopless) paths in a directed graph and report on its implementation. our algorithm is based on a replacement paths algorithm proposed by hershberger and suri [2001], and can yield a factor &theta;(n) improvement for this problem. but there is a caveat: the fast replacement paths subroutine is known to fail for some directed graphs. however, the failure is easily detected, and so our k shortest paths algorithm optimistically uses the fast subroutine, then switches to a slower but correct algorithm if a failure is detected. thus, the algorithm achieves its &theta;(n) speed advantage only when the optimism is justified. our empirical results show that the replacement paths failure is a rare phenomenon, and the new algorithm outperforms the current best algorithms; the improvement can be substantial in large graphs. for instance, on gis map data with about 5,000 nodes and 12,000 edges, our algorithm is 4--8 times faster. in synthetic graphs modeling wireless ad hoc networks, our algorithm is about 20 times faster.
routing selfish unsplittable traffic. we consider general resource assignment games involving selfish users/agents in which users compete for resources and try to be assigned to those which maximize their own benefits (e.g., try to route their traffic through links which minimize the latency of their own traffic). we propose and study a mechanism design approach in which an allocation mechanism assigns users to resources and charges the users for using the resources so as to induce each user to truthfully report a private piece of information he/she holds (e.g., how much traffic he/she needs to transmit). this information is crucial for computing optimal (or close to optimal) allocations and an agent could misreport his/her information to induce the underlying allocation algorithm to output a solution which he/she likes more (e.g., which assigns better resources to him/her). for our resource allocation problems, we give an algorithmic characterization of the solutions for which truth-telling is a nash equilibrium. a natural application of these results is to a scheduling/routing problem which is the mechanism design counterpart of the selfish routing game of koutsoupias and papadimitriou [1999]: each selfish user wants to route a piece of unsplittable traffic using one of m links of different speeds so as to minimize his/her own latency. our mechanism design counterpart can be seen as the problem of scheduling selfish jobs on parallel related machines and is the dual of the problem of scheduling (unselfish) jobs on parallel selfish machines studied by archer and tardos [2001]. koutsoupias and papadimitriou studied an &ldquo;anarchic&rdquo; scenario in which each user chooses his/her own link, and this may produce nash equilibria of cost &omega;(log m/log log m) times the optimum. our mechanism design counterpart is a possible way of reducing the effect of selfish behavior via suitable incentives to the agents (i.e., taxes for using the links). we indeed show that in the resulting game, it is possible to guarantee an approximation factor of 8 for any number of links/machines (this solution also works for online settings). however, it remains impossible to guarantee arbitrarily good approximate solutions, even for 2 links/machines and even if the allocation algorithm is allowed superpolynomial time. this result shows that our scheduling problem with selfish jobs is more difficult than the scheduling problem with selfish machines by archer and tardos (which admits exact solutions). we also study some generalizations of this basic problem.
approximation algorithms and hardness results for cycle packing problems. the cycle packing number &nu;e(g) of a graph g is the maximum number of pairwise edge-disjoint cycles in g. computing &nu;e(g) is an np-hard problem. we present approximation algorithms for computing &nu;e(g) in both undirected and directed graphs. in the undirected case we analyze a variant of the modified greedy algorithm suggested by caprara et al. [2003] and show that it has approximation ratio &theta;(&sqrt;log n), where n &equals; &verbar;v(g)&verbar;. this improves upon the previous o(log n) upper bound for the approximation ratio of this algorithm. in the directed case we present a &sqrt;n-approximation algorithm. finally, we give an o(n2/3)-approximation algorithm for the problem of finding a maximum number of edge-disjoint cycles that intersect a specified subset s of vertices. we also study generalizations of these problems. our approximation ratios are the currently best-known ones and, in addition, provide upper bounds on the integrality gap of standard lp-relaxations of these problems. in addition, we give lower bounds for the integrality gap and approximability of &nu;e(g) in directed graphs. specifically, we prove a lower bound of &omega;(log n/loglog n) for the integrality gap of edge-disjoint cycle packing. we also show that it is quasi-np-hard to approximate &nu;e(g) within a factor of o(log1 &minus; &epsiv; n) for any constant &epsiv; > 0. this improves upon the previously known apx-hardness result for this problem.
packing element-disjoint steiner trees. given an undirected graph g(v, e) with terminal set t &sube; v, the problem of packing element-disjoint steiner trees is to find the maximum number of steiner trees that are disjoint on the nonterminal nodes and on the edges. the problem is known to be np-hard to approximate within a factor of &omega;(log n), where n denotes &verbar;v&verbar;. we present a randomized o(log n)-approximation algorithm for this problem, thus matching the hardness lower bound. moreover, we show a tight upper bound of o(log n) on the integrality ratio of a natural linear programming relaxation.
the -traveling repairmen problem. we consider the k-traveling repairmen problem, also known as the minimum latency problem, to multiple repairmen. we give a polynomial-time 8.497&alpha;-approximation algorithm for this generalization, where &alpha; denotes the best achievable approximation factor for the problem of finding the least-cost rooted tree spanning i vertices of a metric. for the latter problem, a (2 &plus; &epsiv;)-approximation is known. our results can be compared with the best-known approximation algorithm using similar techniques for the case k &equals; 1, which is 3.59&alpha;. moreover, recent work of chaudry et al. [2003] shows how to remove the factor of &alpha;, thus improving all of these results by that factor. we are aware of no previous work on the approximability of the present problem. in addition, we give a simple proof of the 3.59&alpha;-approximation result that can be more easily extended to the case of multiple repairmen, and may be of independent interest.
improved online algorithms for buffer management in qos switches. we consider the following buffer management problem arising in qos networks: packets with specified weights and deadlines arrive at a network switch and need to be forwarded so that the total weight of forwarded packets is maximized. packets not forwarded before their deadlines are lost. the main result of the article is an online 64/33 &ap; 1.939-competitive algorithm, the first deterministic algorithm for this problem with competitive ratio below 2. for the 2-uniform case we give an algorithm with ratio &ap; 1.377 and a matching lower bound.
partial fillup and search time in lc tries. andersson and nilsson introduced in 1993 a level-compressed trie (for short, lc trie) in which a full subtree of a node is compressed to a single node of degree being the size of the subtree. recent experimental results indicated a &ldquo;dramatic improvement&rdquo; when full subtrees are replaced by &ldquo;partially filled subtrees.&rdquo; in this article, we provide a theoretical justification of these experimental results, showing, among others, a rather moderate improvement in search time over the original lc tries. for such an analysis, we assume that n strings are generated independently by a binary memoryless source, with p denoting the probability of emitting a &ldquo;1&rdquo; (and q &equals; 1 &minus; p). we first prove that the so-called &alpha;-fillup level fn(&alpha;) (i.e., the largest level in a trie with &alpha; fraction of nodes present at this level) is concentrated on two values with high probability: either fn(&alpha;) &equals; kn or fn(&alpha;) &equals; kn &plus; 1, where kn &equals; log1/&sqrt;pq n &minus; &verbar;ln (p/q)&verbar;/2 ln3/2 (1&sqrt;pq) &phi;&minus;1 (&alpha;) &sqrt; ln n &plus; o(1) is an integer and &phi;(x) denotes the normal distribution function. this result directly yields the typical depth (search time) dn(&alpha;) in the &alpha;-lc tries, namely, we show that with high probability dn(&alpha;) &sim; c2 log log n, where c2 &equals; 1/&verbar;log(1 &minus; h/log(1/&sqrt;pq))&verbar; for p &ne; q and h &equals; &minus;plog p&minus;qlog q is the shannon entropy rate. this should be compared with recently found typical depth in the original lc tries, which is c1log log n, where c1 &equals; 1/&verbar;log(1&minus;h/log(1/min&lcub;p, 1&minus;p&rcub;))&verbar;. in conclusion, we observe that &alpha; affects only the lower term of the &alpha;-fillup level fn(&alpha;), and the search time in &alpha;-lc tries is of the same order as in the original lc tries.
edge-disjoint paths revisited. the approximability of the maximum edge-disjoint paths problem (edp) in directed graphs was seemingly settled by an &omega;(m1/2 &minus; &epsis;)-hardness result of guruswami et al. [2003], and an o(&sqrt;m) approximation achievable via a natural multicommodity-flow-based lp relaxation as well as a greedy algorithm. here m is the number of edges in the graph. we observe that the &omega;(m1/2 &minus; &epsis;)-hardness of approximation applies to sparse graphs, and hence when expressed as a function of n, that is, the number of vertices, only an &omega;(n1/2&minus; &epsis;)-hardness follows. on the other hand, o(&sqrt;m)-approximation algorithms do not guarantee a sublinear (in terms of n) approximation algorithm for dense graphs. we note that a similar gap exists in the known results on the integrality gap of the flow-based lp relaxation: an &omega;(&sqrt;n) lower bound and o(&sqrt;m) upper bound. motivated by this discrepancy in the upper and lower bounds, we study algorithms for edp in directed and undirected graphs and obtain improved approximation ratios. we show that the greedy algorithm has an approximation ratio of o(min(n2/3, &sqrt;m)) in undirected graphs and a ratio of o(min(n4/5, &sqrt;m)) in directed graphs. for acyclic graphs we give an o(&sqrt;n ln n) approximation via lp rounding. these are the first sublinear approximation ratios for edp. the results also extend to edp with weights and to the uniform-capacity unsplittable flow problem (ucufp).
succinct indexable dictionaries with applications to encoding -ary trees, prefix sums and multisets. we consider the indexable dictionary problem, which consists of storing a set s &sube; &lcub;0,&hellip;,m &minus; 1&rcub; for some integer m while supporting the operations of rank(x), which returns the number of elements in s that are less than x if x &isin; s, and &minus;1 otherwise; and select(i), which returns the ith smallest element in s. we give a data structure that supports both operations in o(1) time on the ram model and requires b(n, m) &plus; o(n) &plus; o(lg lg m) bits to store a set of size n, where b(n, m) &equals; &lfloor;lg (m/n)&rfloor; is the minimum number of bits required to store any n-element subset from a universe of size m. previous dictionaries taking this space only supported (yes/no) membership queries in o(1) time. in the cell probe model we can remove the o(lg lg m) additive term in the space bound, answering a question raised by fich and miltersen [1995] and pagh [2001]. we present extensions and applications of our indexable dictionary data structure, including: &mdash;an information-theoretically optimal representation of a k-ary cardinal tree that supports standard operations in constant time; &mdash;a representation of a multiset of size n from &lcub;0,&hellip;,m &minus; 1&rcub; in b(n, m &plus; n) &plus; o(n) bits that supports (appropriate generalizations of) rank and select operations in constant time; and &plus; o(lg lg m) &mdash;a representation of a sequence of n nonnegative integers summing up to m in b(n, m &plus; n) &plus; o(n) bits that supports prefix sum queries in constant time.
algorithms for power savings. this article examines two different mechanisms for saving power in battery-operated embedded systems. the first strategy is that the system can be placed in a sleep state if it is idle. however, a fixed amount of energy is required to bring the system back into an active state in which it can resume work. the second way in which power savings can be achieved is by varying the speed at which jobs are run. we utilize a power consumption curve p(s) which indicates the power consumption level given a particular speed. we assume that p(s) is convex, nondecreasing, and nonnegative for s &ge; 0. the problem is to schedule arriving jobs in a way that minimizes total energy use and so that each job is completed after its release time and before its deadline. we assume that all jobs can be preempted and resumed at no cost. although each problem has been considered separately, this is the first theoretical analysis of systems that can use both mechanisms. we give an offline algorithm that is within a factor of 2 of the optimal algorithm. we also give an online algorithm with a constant competitive ratio.
the priority r-tree: a practically efficient and worst-case optimal r-tree. we present the priority r-tree, or pr-tree, which is the first r-tree variant that always answers a window query using o((n/b)1&minus;1/d&plus;t/b) i/os, where n is the number of d-dimensional (hyper-) rectangles stored in the r-tree, b is the disk block size, and t is the output size. this is provably asymptotically optimal and significantly better than other r-tree variants, where a query may visit all n/b leaves in the tree even when t &equals; 0. we also present an extensive experimental study of the practical performance of the pr-tree using both real-life and synthetic data. this study shows that the pr-tree performs similarly to the best-known r-tree variants on real-life and relatively nicely distributed data, but outperforms them significantly on more extreme data.
finding a long directed cycle. consider a digraph with n vertices. for any fixed value k, we present linear- and almost-linear-time algorithms to find a cycle of length &ge; k, if one exists. we also find a cycle that has length &ge; log n/log log n in polynomial time, if one exists. under an appropriate complexity assumption it is known to be impossible to improve this guarantee by more than a log log n factor. our approach is based on depth-first search.
approximate distance oracles for geometric spanners. given an arbitrary real constant &epsiv; > 0, and a geometric graph g in d-dimensional euclidean space with n points, o(n) edges, and constant dilation, our main result is a data structure that answers (1 &plus; &epsiv;)-approximate shortest-path-length queries in constant time. the data structure can be constructed in o(n log n) time using o(n log n) space. this represents the first data structure that answers (1 &plus; &epsiv;)-approximate shortest-path queries in constant time, and hence functions as an approximate distance oracle. the data structure is also applied to several other problems. in particular, we also show that approximate shortest-path queries between vertices in a planar polygonal domain with &ldquo;rounded&rdquo; obstacles can be answered in constant time. other applications include query versions of closest-pair problems, and the efficient computation of the approximate dilations of geometric graphs. finally, we show how to extend the main result to answer (1 &plus; &epsiv;)-approximate shortest-path-length queries in constant time for geometric spanner graphs with m &equals; &omega;(n) edges. the resulting data structure can be constructed in o(m &plus; n log n) time using o(n log n) space.
improved bounds for scheduling conflicting jobs with minsum criteria. we consider a general class of scheduling problems where a set of conflicting jobs needs to be scheduled (preemptively or nonpreemptively) on a set of machines so as to minimize the weighted sum of completion times. the conflicts among jobs are formed as an arbitrary conflict graph. building on the framework of queyranne and sviridenko [2002b], we present a general technique for reducing the weighted sum of completion-times problem to the classical makespan minimization problem. using this technique, we improve the best-known results for scheduling conflicting jobs with the min-sum objective, on several fundamental classes of graphs, including line graphs, (k &plus; 1)-claw-free graphs, and perfect graphs. in particular, we obtain the first constant-factor approximation ratio for nonpreemptive scheduling on interval graphs. we also improve the results of kim [2003] for scheduling jobs on line graphs and for resource-constrained scheduling.
rectangular layouts and contact graphs. contact graphs of isothetic rectangles unify many concepts from applications including vlsi and architectural design, computational geometry, and gis. minimizing the area of their corresponding rectangular layouts is a key problem. we study the area-optimization problem and show that it is np-hard to find a minimum-area rectangular layout of a given contact graph. we present o(n)-time algorithms that construct o(n2)-area rectangular layouts for general contact graphs and o(n log n)-area rectangular layouts for trees. (for trees, this is an o(log n)-approximation algorithm.) we also present an infinite family of graphs (respectively, trees) that require &omega;(n2) (respectively, &omega;(n log n))area. we derive these results by presenting a new characterization of graphs that admit rectangular layouts, using the related concept of rectangular duals. a corollary to our results relates the class of graphs that admit rectangular layouts to rectangle-of-influence drawings.
path decomposition under a new cost measure with applications to optical network design. we introduce a problem directly inspired by its application to dwdm (dense wavelength division multiplexing) network design. we are given a set of demands to be carried over a network. our goal is to choose a route for each demand and to decompose the network into a collection of edge-disjoint simple paths. these paths are called optical line systems. the cost of routing one unit of demand is the number of line systems with which the demand route overlaps; our design objective is to minimize the total cost over all demands. this cost metric is motivated by the need to minimize o-e-o (optical-electrical-optical) conversions in optical transmission. for given line systems, it is easy to find the optimal demand routes. on the other hand, for given demand routes designing the optimal line systems can be np-hard. we first present a 2-approximation for general network topologies. as optical networks often have low node degrees, we offer an algorithm that finds the optimal solution for the special case in which the node degree is at most 3. our solution is based on a local greedy approach. if neither demand routes nor line systems are fixed, the situation becomes much harder. even for a restricted scenario on a 3-regular hamiltonian network, no efficient algorithm can guarantee a constant approximation better than 2. for general topologies, we offer a simple algorithm with an o(log k)- and an o(log n)-approximation, where k is the number of demands and n the number of nodes. this approximation ratio is almost tight. for rings, a common special topology, we offer a more complex 3/2-approximation algorithm.
faster approximation schemes for fractional multicommodity flow problems. we present fully polynomial approximation schemes for concurrent multicommodity flow problems that run in time of the minimum possible dependencies on the number of commodities k. we show that by modifying the algorithms by garg and k&ouml;nemann [1998] and fleischer [2000], we can reduce their running time on a graph with n vertices and m edges from &otilde;(&epsiv;&minus;2(m2 &plus; km)) to &otilde;(&epsiv;&minus;2m2) for an implicit representation of the output, or &otilde;(&epsiv;&minus;2(m2 &plus; kn for an explicit representation, where &otilde;(f) denotes a quantity that is o(f logo(1)m). the implicit representation consists of a set of trees rooted at sources (there can be more than one tree per source), and with sinks as their leaves, together with flow values for the flow directed from the source to the sinks in a particular tree. given this implicit representation, the approximate value of the concurrent flow is known, but if we want the explicit flow per commodity per edge, we would have to combine all these trees together, and the cost of doing so may be prohibitive. in case we want to calculate explicitly the solution flow, we modify our schemes so that they run in time polylogarithmic in nk (n is the number of nodes in the network). this is within a polylogarithmic factor of the trivial lower bound of time &omega;(nk) needed to explicitly write down a multicommodity flow of k commodities in a network of n nodes. therefore our schemes are within a polylogarithmic factor of the minimum possible dependencies of the running time on the number of commodities k.
thin heaps, thick heaps. the fibonacci heap was devised to provide an especially efficient implementation of dijkstra's shortest path algorithm. although asyptotically efficient, it is not as fast in practice as other heap implementations. expanding on ideas of h&oslash;yer [1995], we describe three heap implementations (two versions of thin heaps and one of thick heaps) that have the same amortized efficiency as fibonacci heaps, but need less space and promise better practical performance. as part of our development, we fill in a gap in h&oslash;yer's analysis.
alternation and redundancy analysis of the intersection problem. the intersection of sorted arrays problem has applications in search engines such as google. previous work has proposed and compared deterministic algorithms for this problem, in an adaptive analysis based on the encoding size of a certificate of the result (cost analysis). we define the alternation analysis, based on the nondeterministic complexity of an instance. in this analysis we prove that there is a deterministic algorithm asymptotically performing as well as any randomized algorithm in the comparison model. we define the redundancy analysis, based on a measure of the internal redundancy of the instance. in this analysis we prove that any algorithm optimal in the redundancy analysis is optimal in the alternation analysis, but that there is a randomized algorithm which performs strictly better than any deterministic algorithm in the comparison model. finally, we describe how these results can be extended beyond the comparison model.
a faster and simpler fully dynamic transitive closure. we obtain a new fully dynamic algorithm for maintaining the transitive closure of a directed graph. our algorithm maintains the transitive closure matrix in a total running time of o(mn &plus; (ins &plus; del) &middot; n2), where ins (del) is the number of insert (delete) operations performed. here n is the number of vertices in the graph and m is the initial number of edges in the graph. obviously, reachability queries can be answered in constant time. the algorithm uses only o(n2) time which is essentially optimal for maintaining the transitive closure matrix. our algorithm can also support path queries. if v is reachable from u, the algorithm can produce a path from u to v in time proportional to the length of the path. the best previously known algorithm for the problem is due to demetrescu and italiano [2000]. their algorithm has a total running time of o(n3 &plus; (ins &plus; del) &middot; n2). the query time is also constant. in addition, we also present a simple algorithm for directed acyclic graphs (dags) with a total running time of o(mn &plus; ins &middot; n2 &plus; del). our algorithms are obtained by combining some new ideas with techniques of italiano [1986, 1988], king [1999], king and thorup [2001] and frigioni et al. [2001]. we also note that our algorithms are extremely simple and can be easily implemented.
the collective memory of amnesic processes. this article considers the problem of robustly emulating a shared atomic memory over a distributed message-passing system where processes can fail by crashing and possibly recover. we revisit the notion of atomicity in the crash-recovery context and introduce a generic algorithm that emulates an atomic memory. the algorithm is instantiated for various settings according to whether processes have access to local stable storage, and whether, in every execution of the algorithm, a sufficient number of processes are assumed not to crash. we establish the optimality of specific instances of our algorithm in terms of resilience, log complexity (number of stable storage accesses needed in every read or write operation), as well as time complexity (number of communication steps needed in every read or write operation). the article also discusses the impact of considering a multiwriter versus a single-writer memory, as well as the impact of weakening the consistency of the memory by providing safe or regular semantics instead of atomicity.
uniform deterministic dictionaries. we present a new analysis of the well-known family of multiplicative hash functions, and improved deterministic algorithms for selecting &ldquo;good&rdquo; hash functions. the main motivation is realization of deterministic dictionaries with fast lookups and reasonably fast updates. the model of computation is the word ram, and it is assumed that the machine word-size matches the size of keys in bits. many of the modern solutions to the dictionary problem are weakly nonuniform, that is, they require a number of constants to be computed at &ldquo;compile time&rdquo; for the stated time bounds to hold. the currently fastest deterministic dictionary uses constants not known to be computable in polynomial time. in contrast, our dictionaries do not require any special constants or instructions, and running times are independent of word (and key) length. our family of dynamic dictionaries achieves a performance of the following type: lookups in time o(t) and updates in amortized time o(n1/t), for an appropriate parameter function t. update procedures require division, whereas searching uses multiplication only.
randomized minimum spanning tree algorithms using exponentially fewer random bits. for many fundamental problems there exist randomized algorithms that are asymptotically optimal and are superior to the best-known deterministic algorithm. among these are the minimum spanning tree (mst) problem, the mst sensitivity analysis problem, the parallel connected components and parallel minimum spanning tree problems, and the local sorting and set maxima problems. (for the first two problems there are provably optimal deterministic algorithms with unknown, and possibly superlinear, running times.) one downside of the randomized methods for solving these problems is that they use a number of random bits linear in the size of input. in this article we develop some general methods for reducing exponentially the consumption of random bits in comparison-based algorithms. in some cases we are able to reduce the number of random bits from linear to nearly constant, without affecting the expected running time. most of our results are obtained by adjusting or reorganizing existing randomized algorithms to work well with a pairwise or o(1)-wise independent sampler. the prominent exception, and the main focus of this article, is a linear-time randomized minimum spanning tree algorithm that is not derived from the well-known karger-klein-tarjan algorithm. in many ways it resembles more closely the deterministic minimum spanning tree algorithms based on soft heaps. further, using our algorithm as a guide, we present a unified view of the existing &ldquo;nongreedy&rdquo; minimum spanning tree algorithms. concepts from the karger-klein-tarjan algorithm, such as f-lightness, mst verification, and sampled graphs, are related to the concepts of edge corruption, subgraph contractibility, and soft heaps, which are the basis of the deterministic mst algorithms of chazelle and pettie-ramachandran.
embeddings of negative-type metrics and an improved approximation to generalized sparsest cut. in this article, we study metrics of negative type, which are metrics (v, d) such that &sqrt;d is an euclidean metric; these metrics are thus also known as &ell;2-squared metrics. we show how to embed n-point negative-type metrics into euclidean space &ell;2 with distortion d &equals; o(log3/4n). this embedding result, in turn, implies an o(log3/4k)-approximation algorithm for the sparsest cut problem with nonuniform demands. another corollary we obtain is that n-point subsets of &ell;1 embed into &ell;2 with distortion o(log3/4 n).
compact dictionaries for variable-length keys and data with applications. we consider the problem of maintaining a dynamic dictionary t of keys and associated data for which both the keys and data are bit strings that can vary in length from zero up to the length w of a machine word. we present a data structure for this variable-bit-length dictionary problem that supports constant time lookup and expected amortized constant-time insertion and deletion. it uses o(m &plus; 3n &minus; nlog2n) bits, where n is the number of elements in t, and m is the total number of bits across all strings in t (keys and data). our dictionary uses an array a&lsqb;1 &hellip; n&rsqb; in which locations store variable-bit-length strings. we present a data structure for this variable-bit-length array problem that supports worst-case constant-time lookups and updates and uses o(m &plus; n) bits, where m is the total number of bits across all strings stored in a. the motivation for these structures is to support applications for which it is helpful to efficiently store short varying-length bit strings. we present several applications, including representations for semidynamic graphs, order queries on integers sets, cardinal trees with varying cardinality, and simplicial meshes of d dimensions. these results either generalize or simplify previous results.
primal-dual approach for directed vertex connectivity augmentation and generalizations. in their seminal paper, frank and jord&aacute;n &lsqb;1995&rsqb; show that a large class of optimization problems, including certain directed graph augmentation, fall into the class of covering supermodular functions over pairs of sets. they also give an algorithm for such problems, however, it relies on the ellipsoid method. prior to our result, combinatorial algorithms existed only for the 0--1 valued problem. our key result is a combinatorial algorithm for the general problem that includes directed vertex or s&minus;t connectivity augmentation. the algorithm is based on bencz&uacute;r's previous algorithm for the 0--1 valued case &lsqb;bencz&uacute;r 2003&rsqb;. our algorithm uses a primal-dual scheme for finding covers of partially ordered sets that satisfy natural abstract properties as in frank and jord&aacute;n. for an initial (possibly greedy) cover, the algorithm searches for witnesses for the necessity of each element in the cover. if no two (weighted) witnesses have a common cover, the solution is optimal. as long as this is not the case, the witnesses are gradually exchanged for smaller ones. each witness change defines an appropriate change in the solution; these changes are finally unwound in a shortest-path manner to obtain a solution of size one less.
dissections, orientations, and trees with applications to optimal mesh encoding and random sampling. we present a bijection between some quadrangular dissections of an hexagon and unrooted binary trees with interesting consequences for enumeration, mesh compression, and graph sampling. our bijection yields an efficient uniform random sampler for 3-connected planar graphs, which turns out to be determinant for the quadratic complexity of the current best-known uniform random sampler for labelled planar graphs. it also provides an encoding for the set p(n) of n-edge 3-connected planar graphs that matches the entropy bound 1/n log2 &verbar;p(n)&verbar; &equals; 2 &plus; o(1) bits per edge (bpe). this solves a theoretical problem recently raised in mesh compression as these graphs abstract the combinatorial part of meshes with spherical topology. we also achieve the optimal parametric rate 1/n log2 &verbar;p(n, i, j)&verbar; bpe for graphs of p(n) with i vertices and j faces, matching in particular the optimal rate for triangulations. our encoding relies on a linear time algorithm to compute an orientation associated with the minimal schnyder wood of a 3-connected planar map. this algorithm is of independent interest, and it is, for instance, a key ingredient in a recent straight line drawing algorithm for 3-connected planar graphs.
limitations of cross-monotonic cost-sharing schemes. a cost-sharing scheme is a set of rules defining how to share the cost of a service (often computed by solving a combinatorial optimization problem) amongs serviced customers. a cost-sharing scheme is cross-monotonic if it satisfies the property that everyone is better off when the set of people who receive the service expands. in this article, we develop a novel technique for proving upper bounds on the budget-balance factor of cross-monotonic cost-sharing schemes or the worst-case ratio of recovered cost to total cost. we apply this technique to games defined, based on several combinatorial optimization problems, including the problems of edge cover, vertex cover, set cover, and metric facility location and, in each case, derive tight or nearly-tight bounds. in particular, we show that for the facility location game, there is no cross-monotonic cost-sharing scheme that recovers more than a third of the total cost. this result, together with a recent 1/3-budget-balanced cross-monotonic cost-sharing scheme of p&aacute;l and tardos &lsqb;2003&rsqb; closes the gap for the facility location game. for the vertex cover and set cover games, we show that no cross-monotonic cost-sharing scheme can recover more than a o(n&minus;1/3) and o(1/n) fraction of the total cost, respectively. finally, we study the implications of our results on the existence of group-strategyproof mechanisms. we show that every group-strategyproof mechanism corresponds to a cost-sharing scheme that satisfies a condition weaker than cross-monotonicity. using this, we prove that group-strategyproof mechanisms satisfying additional properties give rise to cross-monotonic cost-sharing schemes and therefore our upper bounds hold.
dynamic routing schemes for graphs with low local density. this article studies approximate distributed routing schemes on dynamic communication networks. the work focuses on dynamic weighted general graphs where the vertices of the graph are fixed, but the weights of the edges may change. our main contribution concerns bounding the cost of adapting to dynamic changes. the update efficiency of a routing scheme is measured by the time needed in order to update the routing scheme following a weight change. a naive dynamic routing scheme, which updates all vertices following a weight change, requires &omega;(diam) time in order to perform the updates after every weight change, where diam is the diameter of the underlying graph. in contrast, this article presents approximate dynamic routing schemes with average time complexity &theta;&tilde;(d) per topological change, where d is the local density parameter of the underlying graph. following a weight change, our scheme never incurs more than diam time; thus, our scheme is particularly efficient on graphs which have low local density and large diameter. the article also establishes upper and lower bounds on the size of the databases required by the scheme at each site.
on the approximability of some network design problems. consider the following classical network design problem: a set of terminals t &equals; &lcub;ti&rcub; wishes to send traffic to a root r in an n-node graph g &equals; (v, e). each terminal ti sends di units of traffic and enough bandwidth has to be allocated on the edges to permit this. however, bandwidth on an edge e can only be allocated in integral multiples of some base capacity ue and hence provisioning k &times; ue bandwidth on edge e incurs a cost of &lceil;k&rceil; times the cost of that edge. the objective is a minimum-cost feasible solution. this is one of many network design problems widely studied where the bandwidth allocation is governed by side constraints: edges can only allow a subset of cables to be purchased on them or certain quality-of-service requirements may have to be met. in this work, we show that this problem and, in fact, several basic problems in this general network design framework cannot be approximated better than &omega;(log log n) unless np &sube; dtime (no(log log log n)), where &verbar;v&verbar; &equals; n. in particular, we show that this inapproximability threshold holds for (i) the priority-steiner tree problem, (ii) the (single-sink) cost-distance problem, and (iii) the single-sink version of an even more fundamental problem, fixed charge network flow. our results provide a further breakthrough in the understanding of the level of complexity of network design problems. these are the first nonconstant hardness results known for all these problems.
an asymptotic approximation scheme for multigraph edge coloring. the edge coloring problem considers the assignment of colors from a minimum number of colors to edges of a graph such that no two edges with the same color are incident to the same node. we give polynomial time algorithms for approximate edge coloring of multigraphs, that is, parallel edges are allowed. the best previous algorithms achieve a fixed constant approximation factor plus a small additive offset. one of our algorithms achieves solution quality opt &plus; &sqrt;9opt/2 and has execution time polynomial in the number of nodes and the logarithm of the maximum edge multiplicity.
dynamic entropy-compressed sequences and full-text indexes. we give new solutions to the searchable partial sums with indels problem. given a sequence of n k-bit numbers, we present a structure taking kn + o(kn) bits of space, able of performing operations sum, search, insert, and delete, all in o(log n) worst-case time, for any k &equals; o(log n). this extends previous results by hon et al. [2003c] achieving the same space and o(log n/log log n) time complexities for the queries, yet offering complexities for insert and delete that are amortized and worse than ours, and supported only for k &equals; o(1). our result matches an existing lower bound for large values of k. we also give new solutions to the dynamic sequence problem. given a sequence of n symbols in the range [1,&sigma;] with binary zero-order entropy h0, we present a dynamic data structure that requires nh0 + o(n log &sigma;) bits of space, which is able of performing rank and select, as well as inserting and deleting symbols at arbitrary positions, in o(log n log &sigma;) time. our result is the first entropy-bound dynamic data structure for rank and select over general sequences. in the case &sigma; &equals; 2, where both previous problems coincide, we improve the dynamic solution of hon et al. [2003c] in that we compress the sequence. the only previous result with entropy-bound space for dynamic binary sequences is by blandford and blelloch [2004], which has the same complexities as our structure, but does not achieve constant 1 multiplying the entropy term in the space complexity. finally, we present a new dynamic compressed full-text self-index, for a collection of texts over an alphabet of size &sigma;, of overall length n and hth order empirical entropy hh. the index requires nhh + o(n log &sigma;) bits of space, for any h &le; &alpha; logsigma n and constant 0 < &alpha; < 1. it can count the number of occurrences of a pattern of length m in time o(m log n log &sigma;). each such occurrence can be reported in o(log2nlog log n) time, and displaying a context of length &ell; from a text takes time o(log n(&ell; log &sigma; + log n log log n)). insertion/deletion of a text to/from the collection takes o(log n log &sigma;) time per symbol. this significantly improves the space of a previous result by chan et al. [2004] in exchange for a slight time complexity penalty. we achieve at the same time the first dynamic index requiring essentially nhh bits of space, and the first construction of a compressed full-text self-index within that working space. previous results achieve at best o(nhh space with constants larger than 1 [ferragina and manzini 2000; arroyuelo and navarro 2005] and higher time complexities. an important result we prove in this paper is that the wavelet tree of the burrows-wheeler transform of a text, if compressed with a technique that achieves zero-order compression locally (e.g., raman et al. [2002]), automatically achieves hth order entropy space for any h. this unforeseen relation is essential for the results of the previous paragraph, but it also derives into significant simplifications on many existing static compressed full-text self-indexes that build on wavelet trees.
getting the best response for your erg. we consider the speed scaling problem of minimizing the average response time of a collection of dynamically released jobs subject to a constraint a on energy used. we propose an algorithmic approach in which an energy optimal schedule is computed for a huge a, and then the energy optimal schedule is maintained as a decreases. we show that this approach yields an efficient algorithm for equi-work jobs. we note that the energy optimal schedule has the surprising feature that the job speeds are not monotone functions of the available energy. we then explain why this algorithmic approach is problematic for arbitrary work jobs. finally, we explain how to use the algorithm for equi-work jobs to obtain an algorithm for arbitrary work jobs that is o(1)-approximate with respect to average response time, given an additional factor of (1 + &epsi;) energy.
a new approximation algorithm for the asymmetric tsp with triangle inequality. we present a polynomial time factor 0.999 &cdot; log n approximation algorithm for the asymmetric traveling salesperson problem with triangle inequality.
improved algorithms for optimal embeddings. in the last decade, the notion of metric embeddings with small distortion has received wide attention in the literature, with applications in combinatorial optimization, discrete mathematics, and bio-informatics. the notion of embedding is, given two metric spaces on the same number of points, to find a bijection that minimizes maximum lipschitz and bi-lipschitz constants. one reason for the popularity of the notion is that algorithms designed for one metric space can be applied to a different one, given an embedding with small distortion. the better distortion, the better the effectiveness of the original algorithm applied to a new metric space. the goal recently studied by kenyon et al. [2004] is to consider all possible embeddings between two finite metric spaces and to find the best possible one; that is, consider a single objective function over the space of all possible embeddings that minimizes the distortion. in this article we continue this important direction. in particular, using a theorem of albert and atkinson [2005], we are able to provide an algorithm to find the optimal bijection between two line metrics, provided that the optimal distortion is smaller than 13.602. this improves the previous bound of 3 + 2&sqrt;2, solving an open question posed by kenyon et al. [2004]. further, we show an inherent limitation of algorithms using the &ldquo;forbidden pattern&rdquo; based dynamic programming approach, in that they cannot find optimal mapping if the optimal distortion is more than 7 + 4&sqrt;3 (&sime; 13.928). thus, our results are almost optimal for this method. we also show that previous techniques for general embeddings apply to a (slightly) more general class of metrics.
fully dynamic algorithms for chordal graphs and split graphs. we present the first dynamic algorithm that maintains a clique tree representation of a chordal graph and supports the following operations: (1) query whether deleting or inserting an arbitrary edge preserves chordality; and (2) delete or insert an arbitrary edge, provided it preserves chordality. we give two implementations. in the first, each operation runs in o(n) time, where n is the number of vertices. in the second, an insertion query runs in o(log2 n) time, an insertion in o(n) time, a deletion query in o(n) time, and a deletion in o(n log n) time. we also present a data structure that allows a deletion query to run in o(&sqrt;m) time in either implementation, where m is the current number of edges. updating this data structure after a deletion or insertion requires o(m) time. we also present a very simple dynamic algorithm that supports each of the following operations in o(1) time on a general graph: (1) query whether the graph is split, and (2) delete or insert an arbitrary edge.
deterministic conflict-free coloring for intervals: from offline to online. we investigate deterministic algorithms for a frequency assignment problem in cellular networks. the problem can be modeled as a special vertex coloring problem for hypergraphs: in every hyperedge there must exist a vertex with a color that occurs exactly once in the hyperedge (the conflict-free property). we concentrate on a special case of the problem, called conflict-free coloring for intervals. we introduce a hierarchy of four models for the aforesaid problem: (i) static, (ii) dynamic offline, (iii) dynamic online with absolute positions, and (iv) dynamic online with relative positions. in the dynamic offline model, we give a deterministic algorithm that uses at most log3/2 n + 1 &;approx; 1.71 log2 n colors and show inputs that force any algorithm to use at least 3 log5 n + 1 &approx; 1.29 log2 n colors. for the online absolute-positions model, we give a deterministic algorithm that uses at most 3&lceil;log3 n&rceil; &approx; 1.89 log2 n colors. to the best of our knowledge, this is the first deterministic online algorithm using o(log n) colors in a nontrivial online model. in the online relative-positions model, we resolve an open problem by showing a tight analysis on the number of colors used by the first-fit greedy online algorithm. we also consider conflict-free coloring only with respect to intervals that contain at least one of the two extreme points.
the relative worst order ratio applied to seat reservation. the seat reservation problem is the problem of assigning passengers to seats on a train with n seats and k stations enroute in an online manner. the performance of algorithms for this problem is studied using the relative worst order ratio, a fairly new measure for the quality of online algorithms, which allows for direct comparisons between algorithms. this study has yielded new separations between algorithms. for example, for both variants of the problem considered, using the relative worst order ratio, first-fit and best-fit are shown to be better than worst-fit.
multipartite priority queues. we introduce a framework for reducing the number of element comparisons performed in priority-queue operations. in particular, we give a priority queue which guarantees the worst-case cost of o(1) per minimum finding and insertion, and the worst-case cost of o(log n) with at most log n + o(1) element comparisons per deletion, improving the bound of 2 log n + o(1) known for binomial queues. here, n denotes the number of elements stored in the data structure prior to the operation in question, and log n equals log2(max {2, n}). as an immediate application of the priority queue developed, we obtain a sorting algorithm that is optimally adaptive with respect to the inversion measure of disorder, and that sorts a sequence having n elements and i inversions with at most n log (i/n) + o(n) element comparisons.
on the minimum common integer partition problem. we introduce a new combinatorial optimization problem in this article, called the minimum common integer partition (mcip) problem, which was inspired by computational biology applications including ortholog assignment and dna fingerprint assembly. a partition of a positive integer n is a multiset of positive integers that add up to exactly n, and an integer partition of a multiset s of integers is defined as the multiset union of partitions of integers in s. given a sequence of multisets s1, s2, &hellip;, sk of integers, where k &ge; 2, we say that a multiset is a common integer partition if it is an integer partition of every multiset si, 1 &le; i &le; k. the mcip problem is thus defined as to find a common integer partition of s1, s2, &hellip;, sk with the minimum cardinality, denoted as mcip(s1, s2, &hellip;, sk). it is easy to see that the mcip problem is np-hard, since it generalizes the well-known subset sum problem. we can in fact show that it is apx-hard. we will also present a 5/4-approximation algorithm for the mcip problem when k &equals; 2, and a 3k(k&minus;1)/3k&minus;2-approximation algorithm for k &ge; 3.
online nonpreemptive scheduling of equal-length jobs on two identical machines. we consider the nonpreemptive scheduling of two identical machines for jobs with equal processing times yet arbitrary release dates and deadlines. our objective is to maximize the number of jobs completed by their deadlines. using standard nomenclature, this problem is denoted as p2 &verbar; pj &equals; p,rj &verbar; &sum; &uhorbar;j. the problem is known to be polynomially solvable in an offline setting. in an online variant of the problem, a job's existence and parameters are revealed to the scheduler only upon that job's release date. we present an online deterministic algorithm for the problem and prove that it is 3/2-competitive. a simple lower bound shows that this is the optimal deterministic competitiveness.
kinetic and dynamic data structures for closest pair and all nearest neighbors. we present simple, fully dynamic and kinetic data structures, which are variants of a dynamic two-dimensional range tree, for maintaining the closest pair and all nearest neighbors for a set of n moving points in the plane; insertions and deletions of points are also allowed. if no insertions or deletions take place, the structure for the closest pair uses o(n log n) space, and processes o(n2&beta;s+2(n)log n) critical events, each in o(log2n) time. here s is the maximum number of times where the distances between any two specific pairs of points can become equal, &beta;s(q) &equals; &lambda;s(q)/q, and &lambda;s(q) is the maximum length of davenport-schinzel sequences of order s on q symbols. the dynamic version of the problem incurs a slight degradation in performance: if m &ge; n insertions and deletions are performed, the structure still uses o(n log n) space, and processes o(mn&beta;s+2(n)log3 n) events, each in o(log3n) time. our kinetic data structure for all nearest neighbors uses o(n log2 n) space, and processes o(n2&beta;2s+2(n)log3 n) critical events. the expected time to process all events is o(n2&beta;s+22(n) log4n), though processing a single event may take &theta;(n) expected time in the worst case. if m &ge; n insertions and deletions are performed, then the expected number of events is o(mn&beta;2s+2(n) log3n) and processing them all takes o(mn&beta;2s+2(n) log4n). an insertion or deletion takes o(n) expected time.
combinatorial bounds via measure and conquer: bounding minimal dominating sets and applications. we provide an algorithm listing all minimal dominating sets of a graph on n vertices in time o(1.7159n). this result can be seen as an algorithmic proof of the fact that the number of minimal dominating sets in a graph on n vertices is at most 1.7159n, thus improving on the trivial o(2n/&sqrt;n) bound. our result makes use of the measure-and-conquer technique which was recently developed in the area of exact algorithms. based on this result, we derive an o(2.8718n) algorithm for the domatic number problem.
algorithms for center and tverberg points. given a set s of n points in r3, a point x in r3 is called center point of s if every closed halfspace whose bounding hyperplane passes through x contains at least &lceil;n/4&rceil; points from s. we present a near-quadratic algorithm for computing the center region, that is the set of all center points, of a set of n points in r3. this is nearly tight in the worst case since the center region can have &omega;(n2) complexity. we then consider sets s of 3n points in the plane which are the union of three disjoint sets consisting respectively of n red, n blue, and n green points. a point x in r2 is called a colored tverberg point of s if there is a partition of s into n triples with one point of each color, so that x lies in all triangles spanned by these triples. we present a first polynomial-time algorithm for recognizing whether a given point is a colored tverberg point of such a 3-colored set s.
competitive buffer management for shared-memory switches. we consider buffer management policies for shared memory switches. we study the case of overloads resulting in packet loss, where the constraint is the limited shared memory capacity. the goal of the buffer management policy is that of maximizing the number of packets transmitted. the problem is online in nature, and thus we use competitive analysis to measure the performance of the buffer management policies. our main result is to show that the well-known preemptive longest queue drop (lqd) policy is at most 2-competitive and at least &sqrt;2-competitive. we also demonstrate a general lower bound of 4/3 on the performance of any deterministic online policy. finally, we consider some other popular non-preemptive policies including complete partition, complete sharing, static threshold and dynamic threshold and derive almost tight bounds on their performance.
srpt optimally utilizes faster machines to minimize flow time. we analyze the shortest remaining processing time (srpt) algorithm with respect to the problem of scheduling n jobs with release times on m identical machines to minimize total flow time. it is known that srpt is optimal if m &equals; 1 but that srpt has a worst-case approximation ratio of &theta;(min(log n/m, log &delta;)) for this problem, where &delta; is the ratio of the length of the longest job divided by the length of the shortest job. it has previously been shown that srpt is able to use faster machines to produce a schedule as good as an optimal algorithm using slower machines. we now show that srpt optimally uses these faster machines with respect to the worst-case approximation ratio. that is, if srpt is given machines that are s &ge; 2 &minus; 1/m times as fast as those used by an optimal algorithm, srpt's flow time is at least s times smaller than the flow time incurred by the optimal algorithm. clearly, no algorithm can offer a better worst-case guarantee, and we show that existing algorithms with similar performance guarantees to srpt without resource augmentation do not optimally use extra resources.
structure and linear-time recognition of 4-leaf powers. a graph g is the k-leaf power of a tree t if its vertices are leaves of t such that two vertices are adjacent in g if and only if their distance in t is at most k. then t is a k-leaf root of g. this notion was introduced and studied by nishimura, ragde, and thilikos [2002], motivated by the search for underlying phylogenetic trees. their results imply an o(n3)-time recognition algorithm for 4-leaf powers. recently, rautenbach [2006] as well as dom et al. [2005] characterized 4-leaf powers without true twins in terms of forbidden subgraphs. we give new characterizations for 4-leaf powers and squares of trees by a complete structural analysis. as a consequence, we obtain a conceptually simple linear-time recognition of 4-leaf powers.
on hard instances of approximate vertex cover. we show that if there is a 2 &minus; &epsis; approximation algorithm for vertex cover on graphs with vector chromatic number at most 2 + &delta;, then there is a 2 &minus; f(&epsis;, &delta;) approximation algorithm for vertex cover for all graphs.
on an infinite family of solvable hanoi graphs. the tower of hanoi problem is generalized by placing pegs on the vertices of a given directed graph g with two distinguished vertices, s and d, and allowing moves only along arcs of this graph. an optimal solution for such a graph g is an algorithm that completes the task of moving a tower of any given number of disks from s to d in a minimal number of disk moves. in this article we present an algorithm which solves the problem for two infinite families of graphs, and prove its optimality. to the best of our knowledge, this is the first optimality proof for an infinite family of graphs. furthermore, we present a unified algorithm that solves the problem for a wider family of graphs and conjecture its optimality.
distributed weighted vertex cover via maximal matchings. in this article, we consider the problem of computing a minimum-weight vertex-cover in an n-node, weighted, undirected graph g &equals; (v,e). we present a fully distributed algorithm for computing vertex covers of weight at most twice the optimum, in the case of integer weights. our algorithm runs in an expected number of o(log n + log &wcirc;) communication rounds, where &wcirc; is the average vertex-weight. the previous best algorithm for this problem requires o(log n(log n + log&wcirc;)) rounds and it is not fully distributed. for a maximal matching m in g, it is a well-known fact that any vertex-cover in g needs to have at least &verbar;m&verbar; vertices. our algorithm is based on a generalization of this combinatorial lower-bound to the weighted setting.
combinatorial dominance guarantees for problems with infeasible solutions. the design and analysis of approximation algorithms for np-hard problems is perhaps the most active research area in the theory of combinatorial algorithms. in this article, we study the notion of a combinatorial dominance guarantee as a way for assessing the performance of a given approximation algorithm. an f(n) dominance bound is a guarantee that the heuristic always returns a solution not worse than at least f(n) solutions. we give tight analysis of many heuristics, and establish novel and interesting dominance guarantees even for certain inapproximable problems and heuristic search algorithms. for example, we show that the maximal matching heuristic of vertex cover offers a combinatorial dominance guarantee of 2n &minus; (1.839 + o(1))n. we also give inapproximability results for most of the problems we discuss.
a 1.8 approximation algorithm for augmenting edge-connectivity of a graph from 1 to 2. we present a 1.8-approximation algorithm for the following np-hard problem: given a connected graph g &equals; (v, e) and an edge set e on v disjoint to e, find a minimum-size subset of edges f &sube; e such that (v, e &cup; f) is 2-edge-connected. our result improves and significantly simplifies the approximation algorithm with ratio 1.875 + &epsiv; of nagamochi.
average-case analysis of some plurality algorithms. given a set of n elements, each of which is colored one of c colors, we must determine an element of the plurality (most frequently occurring) color by pairwise equal/unequal color comparisons of elements. we focus on the expected number of color comparisons when the cn colorings are equally probable. we analyze an obvious algorithm, showing that its expected performance is c2 + c &minus; 2/2c n &minus; o(c2), with variance &theta;(c2n). we present and analyze an algorithm for the case c &equals; 3 colors whose average complexity on the 3n equally probable inputs is 7083/5425n + o(&sqrt;n) &equals; 1.3056&hellip;n + o(&sqrt; n), substantially better than the expected complexity 5/3n + o(1) &equals; 1.6666&hellip;n + o(1) of the obvious algorithm. we describe a similar algorithm for c &equals;4 colors whose average complexity on the 4n equally probable inputs is 761311/402850n + o(log n) &equals; 1.8898&hellip;n + o(log n), substantially better than the expected complexity 9/4n + o(1) &equals; 2.25n + o(1) of the obvious algorithm.
testing bipartiteness of geometric intersection graphs. we show how to test the bipartiteness of an intersection graph of n line segments or simple polygons in the plane, or of an intersection graph of balls in d-dimensional euclidean space, in time o(n log n). more generally, we find subquadratic algorithms for connectivity and bipartiteness testing of intersection graphs of a broad class of geometric objects. our algorithms for these problems return either a bipartition of the input or an odd cycle in its intersection graph. we also consider lower bounds for connectivity and k-colorability problems of geometric intersection graphs. for unit balls in d dimensions, connectivity testing has equivalent randomized complexity to construction of euclidean minimum spanning trees, and for line segments in the plane connectivity testing has the same lower bounds as hopcroft's point-line incidence testing problem; therefore, for these problems, connectivity is unlikely to be solved as efficiently as bipartiteness. for line segments or planar disks, testing k-colorability of intersection graphs for k > 2 is np-complete.
algorithms for distributional and adversarial pipelined filter ordering problems. pipelined filter ordering is a central problem in database query optimization. the problem is to determine the optimal order in which to apply a given set of commutative filters (predicates) to a set of elements (the tuples of a relation), so as to find, as efficiently as possible, the tuples that satisfy all of the filters. optimization of pipelined filter ordering has recently received renewed attention in the context of environments such as the web, continuous high-speed data streams, and sensor networks. pipelined filter ordering problems are also studied in areas such as fault detection and machine learning under names such as learning with attribute costs, minimum-sum set cover, and satisficing search. we present algorithms for two natural extensions of the classical pipelined filter ordering problem: (1) a distributional-type problem where the filters run in parallel and the goal is to maximize throughput, and (2) an adversarial-type problem where the goal is to minimize the expected value of multiplicative regret. we present two related algorithms for solving (1), both running in time o(n2), which improve on the o(n3 log n) algorithm of kodialam. we use techniques from our algorithms for (1) to obtain an algorithm for (2).
approximating the distance to properties in bounded-degree and general sparse graphs. we address the problem of approximating the distance of bounded-degree and general sparse graphs from having some predetermined graph property p. that is, we are interested in sublinear algorithms for estimating the fraction of edge modifications (additions or deletions) that must be performed on a graph so that it obtains p. this fraction is taken with respect to a given upper bound m on the number of edges. in particular, for graphs with degree bound d over n vertices, m &equals; dn. to perform such an approximation the algorithm may ask for the degree of any vertex of its choice, and may ask for the neighbors of any vertex. the problem of estimating the distance to having a property was first explicitly addressed by parnas et al. [2006]. in the context of graphs this problem was studied by fischer and newman [2007] in the dense graphs model. in this model the fraction of edge modifications is taken with respect to n2, and the algorithm may ask for the existence of an edge between any pair of vertices of its choice. fischer and newman showed that every graph property that has a testing algorithm in this model, with query complexity independent of the size of the graph, also has a distance approximation algorithm with query complexity that is independent of the size of graph. in this work we focus on bounded-degree and general sparse graphs, and give algorithms for all properties shown to have efficient testing algorithms by goldreich and ron [2002]. specifically, these properties are k-edge connectivity, subgraph freeness (for constant-size subgraphs), being an eulerian graph, and cycle freeness. a variant of our subgraph-freeness algorithm approximates the size of a minimum vertex cover of a graph in sublinear time. this approximation improves on a recent result of parnas and ron [2007].
bicriteria approximation tradeoff for the node-cost budget problem. we consider an optimization problem consisting of an undirected graph, with cost and profit functions defined on all vertices. the goal is to find a connected subset of vertices with maximum total profit, whose total cost does not exceed a given budget. the best result known prior to this work guaranteed a (2, o(log n)) bicriteria approximation, that is, the solution's profit is at least a fraction of 1/o(log n) of an optimum solution respecting the budget, while its cost is at most twice the given budget. we improve these results and present a bicriteria tradeoff that, given any &epsiv; &isin; (0,1], guarantees a (1 + &epsis;, o(1/&epsiv; log n))-approximation.
a polynomial-time approximation scheme for embedding hypergraph in a cycle. we consider the problem of embedding hyperedges of a hypergraph as paths in a cycle such that the maximum congestion, namely the maximum number of paths that use any single edge in a cycle, is minimized. the minimum congestion hypergraph embedding in a cycle problem is known to be np-hard and its graph version, the minimum congestion graph embedding in a cycle, is solvable in polynomial-time. furthermore, for the graph problem, a polynomial-time approximation scheme for the weighted version is known. for the hypergraph model, several approximation algorithms with a ratio of two have been previously published. a recent paper reduced the approximation ratio to 1.5. we present a polynomial-time approximation scheme in this article, settling the debate regarding whether the problem is polynomial-time approximable.
throughput maximization of real-time scheduling with batching. we consider the following scheduling with batching problem that has many applications, for example, in multimedia-on-demand and manufacturing of integrated circuits. the input to the problem consists of n jobs and k parallel machines. each job is associated with a set of time intervals in which it can be scheduled (given either explicitly or nonexplicitly), a weight, and a family. each family is associated with a processing time. jobs that belong to the same family can be batched and executed together on the same machine. the processing time of each batch is the processing time of the family of jobs it contains. the goal is to find a nonpreemptive schedule with batching that maximizes the weight of the scheduled jobs. we give constant factor (4 or 4 + &epsiv;) approximation algorithms for two variants of the problem, depending on the precise representation of the input. when the batch size is unbounded and each job is associated with a time window in which it can be processed, these approximation ratios reduce to 2 and 2 + &epsiv;, respectively. we also give approximation algorithms for two special cases when all release times are the same.
linear time 3-approximation for the mast problem. given a set of leaf-labeled trees with identical leaf sets, the well-known maximum agreement subtree (mast) problem consists in finding a subtree homeomorphically included in all input trees and with the largest number of leaves. mast and its variant called maximum compatible tree (mct) are of particular interest in computational biology. this article presents a linear-time approximation algorithm to solve the complement version of mast, namely identifying the smallest set of leaves to remove from input trees to obtain isomorphic trees. we also present an o(n2 + kn) algorithm to solve the complement version of mct. for both problems, we thus achieve significantly lower running times than previously known algorithms. fast running times are especially important in phylogenetics where large collections of trees are routinely produced by resampling procedures, such as the nonparametric bootstrap or bayesian mcmc methods.
online conflict-free coloring for halfplanes, congruent disks, and axis-parallel rectangles. we present randomized algorithms for online conflict-free coloring (cf in short) of points in the plane, with respect to halfplanes, congruent disks, and nearly-equal axis-parallel rectangles. in all three cases, the coloring algorithms use o(log n) colors, with high probability. we also present a deterministic algorithm for online cf coloring of points in the plane with respect to nearly-equal axis-parallel rectangles, using o(log3n) colors. this is the first efficient (i.e, using polylog(n) colors) deterministic online cf coloring algorithm for this problem.
rigorous results for random (2+p)-sat. in recent years there has been significant interest in the study of random k-sat formulae. for a given set of n boolean variables, let bk denote the set of all possible disjunctions of k distinct, non-complementary literals from its variables (k-clauses). a random k-sat formula fk (n;m) is formed by selectinguniformly and independently m clauses from bk and takingtheir conjunction. motivated by insights from statistical mechanics that suggest a possible relationship between the "order" of phase transitions and computational complexity, monasson and zecchina (phys. rev. e 56(2) (1997) 1357) proposed the random (2+p)-sat model: for a given p . [0; 1], a random (2 + p)-sat formula, f2+p(n;m), has m randomly chosen clauses over n variables, where pm clauses are chosen from b3 and (1 - p)m from b2. usingthe heuristic "replica method" of statistical mechanics, monasson and zecchina gave a number of non-rigorous predictions on the behavior of random (2 + p)-sat formulae. in this paper we give the 1rst rigorous results for random (2 + p)-sat, including the following surprising fact: for p &le; 2/5, with probability 1 - o(1), a random (2 + p)-sat formula is satisfiable if its 2-sat subformula is satisfiable. that is, for p 6 2=5, random (2 + p)-sat behaves like random 2-sat.
infinite trees and completely iterative theories: a coalgebraic view. infinite trees form a free completely iterative theory over any given signature--this fact, proved by elgot, bloom and tindell, turns out to be a special case of a much more general categorical result exhibited in the present paper. we prove that whenever an endofunctor h of a category has final coalgebras for all functors h(-) + x, then those coalgebras, tx, form a monad. this monad is completely iterative, i.e., every guarded system of recursive equations has a unique solution. and it is a free completely iterative monad on h. the special case of polynomial endofunctors of the category set is the above mentioned theory, or monad, of infinite trees.this procedure can be generalized to monoidal categories satisfying a mild side condition: if, for an object h, the endofunctor h ⊗ _ + i has a final coalgebra, t, then t is a monoid. this specializes to the above case for the monoidal category of all endofunctors.
inheritance of workflows: an approach to tackling problems related to change. inheritance is one of the key issues of object-orientation. the inheritance mechanism allows for the definition of a subclass which inherits the features of a specific superclass. when adapting a workflow process definition to specific needs (ad-hoc change) or changing the structure of the workflow process as a result of reengineering efforts (evolutionary change), inheritance concepts are useful to check whether the new workflow process inherits some desirable properties of the old workflow process. today's workflow management systems have problems dealing with both ad-hoc changes and evolutionary changes. as a result, a workflow management system is not used to support dynamically changing workflow processes or the workflow processes are supported in a rigid manner, i.e., changes are not allowed or handled outside of the workflow management system. in this paper, we propose inheritance-preserving transformation rules for workflow processes and show that these rules can be used to avoid problems such as the "dynamic-change bug." the dynamic-change bug refers to errors introduced by migrating a case (i.e., a process instance) from an old process definition to a new one. a transfer from an old process to a new process can lead to duplication of work, skipping of tasks, deadlocks, and livelocks. restricting change to the inheritance-preserving transformation rules guarantees transfers without any of these problems. moreover, the transformation rules can also be used to extract aggregate management information in case more than one version of a workflow process cannot be avoided.
balances for fixed points of primitive substitutions. an infinite word defined over a finite alphabet a is balanced if for any pair (ω,ω') of factors of the same length and for any letter a in the alphabet ||ω|a - |ω'|a| ≤ 1, where |ω|a denotes the number of occurrences of the letter a in the word ω. in this paper, we generalize this notion and introduce a measure of balance for an infinite sequence. in the case of fixed points of primitive substitutions, we show that the asymptotic behaviour of this measure is in part ruled by the spectrum of the incidence matrix associated with the substitution. connections with frequencies of letters and other balance properties are also discussed.
on final coalgebras of continuous functors. continuous endofunctors f of locally finitely presentable categories carry a natural metric on their final coalgebra. whenever f(0) has an element, this metric is proved to be a cauchy completion of the initial algebra of f. this is illustrated on the poset of real numbers represented as a final coalgebra of an endofunctor of pos by pavlovic´ and pratt. under additional assumptions on the locally finitely presentable category, all finitary endofunctors are proved to have a final coalgebra constructed in ω + ω steps of the natural iteration construction.
the intersection of algebra and coalgebra. presheaf categories are well-known to be varieties of algebras and covarieties of coalgebras. we prove the converse: if a category is a variety as well as a covariety, then it is a presheaf category. our main result is that all coalgebras on a set functor h form a presheaf category iff h is a reduction of a polynomial functor.
deciding knowledge in security protocols under equational theories. the analysis of security protocols requires precise formulations of the knowledge of protocol participants and attackers. in formal approaches this knowledge is often treated in terms of message deducibility and indistinguishability relations. in this paper we study the decidability of these two relations. the messages in question may employ functions (encryption, decryption, etc.) axiomatized in an equational theory. one of our main positive results says that deducibility and indistinguishability are both decidable in polynomial time for a large class of equational theories. this class of equational theories is defined syntactically and includes, for example, theories for encryption, decryption, and digital signatures. we also establish general decidability theorems for an even larger class of theories. these theorems require only loose, abstract conditions, and apply to many other useful theories, for example with blind digital signatures, homomorphic encryption, xor, and other associative-commutative functions.
on abstract data types presented by multiequations. equational presentation of abstract data types is generalized to presentation by multiequations, i.e., exclusive-or's of equations, in order to capture parametric data types such as array or set. multiinitial-algebra semantics for such data types is introduced. classes of algebras described by multiequations are characterized.
formal parametric polymorphism. a polymorphic function is parametric if its behavior does not depend on the type at which it is instantiated. starting with reynolds' work, the study of parametricity is typically semantic. in this paper, we develop a syntactic approach to parametricity, and a formal system that embodies this approach: system r . girard's system f deals with terms and types; r is an extension of f that deals also with relations between types. in r **, it is possible to derive theorems about functions from their types, or &ldquo;theorems for free&rdquo;, as wadler calls them. an easy &ldquo;theorem for free&rdquo; asserts that the type &forall;xx&rarr; bool contains only constant functions; this is not provable in f. there are many harder and more substantial examples. various metatheorems can also be obtained, such as a syntactic version of reynolds' abstraction theorem.
private authentication. frequently, communication between two principals reveals their identities and presence to third parties. these privacy breaches can occur even if security protocols are in use; indeed, they may even be caused by security protocols. however, with some care, security protocols can provide authentication for principals that wish to communicate while protecting them from monitoring by third parties. we discuss the problem of private authentication and present two protocols for private authentication of mobile principals. our protocols allow two mobile principals to communicate when they meet at a location if they wish to do so, without the danger of tracking by third parties. we also present the analysis of one of the protocols in the applied pi calculus. we establish authenticity and secrecy properties. although such properties are fairly standard, their formulation in the applied pi calculus makes an original use of process equivalences. in addition, we treat identity-protection properties, thus exploring a formal model of privacy.
linearisability on datalog programs. linear datalog programs are programs whose clauses have at most one intensional atom in their bodies. we explore syntactic classes of datalog programs (syntactically non-linear) which turn out to express no more than the queries expressed by linear datalog programs. in particular, we investigate linearisability of (database queries corresponding to) piecewise linear datalog programs and chain queries: (a) we prove that piecewise linear datalog programs can always be transformed into linear datalog programs, by virtue of a procedure which performs the transformation automatically. the procedure relies upon conventional logic program transformation techniques. (b) we identify a new class of linearisable chain queries, referred to as pseudo-regular, and prove their linearisability constructively, by generating, for any given pseudo-regular chain query, the datalog program corresponding to it.
the expressiveness of dac. we define a new logic-based query language, called dac, which is an extension of data-log. a dac(w(n),h(n))(b(n))-program consists of a family of datalog programs pn such that w(n),h(n),b(n) bound the width of rules, the number of rules, and the recursion depth of any pn, respectively. we exhibit queries which are not datalog expressible but are dac expressible. we also prove non-expressiveness results for dac and we infer various strict hierarchies obtained by allowing more rapidly growing functions on the bound parameters.
projective topology on bifinite domains and applications. we revisit extension results from continuous valuations to radon measures for bifinite domains. in the framework of bifinite domains, the prokhorov theorem (existence of projective limits of radon measures) appears as a natural tool, and helps building a bridge between measure theory and domain theory. the study we present also fills a gap in the literature concerning the coincidence between projective and lawson topology for bifinite domains. motivated by probabilistic considerations, we study the extension of measures in order to define borel measures on the space of maximal elements of a bifinite domain.
open block scheduling in optical communication networks. in this paper the process of data transmission in star coupled optical communication networks is modelled as a shop-type scheduling problem, where channels (wavelengths) are treated as machines. we formulate an open block problem with the minimum makespan objective (o b||cmax) in which a relation of a new type between the operations of each job is introduced: any two operations of a job have identical processing times and may be processed either simultaneously (in a common block) or, alternatively, at disjoint time intervals. we show that the problem is polynomially solvable for 4 machines, np-hard for 6 machines and strongly np-hard for a variable number of machines. for the case of a variable number of machines we present a polynomial time √2-approximation algorithm and prove that there is no polynomial time ρ-approximation algorithm with ρ < 11/10, unless p = np. for the case when the number of machines is fixed, we show that the problem admits a linear time ptas. in addition, we show that the two-machine problem with release dates is np-hard in the strong sense.
containers: constructing strictly positive types. we introduce the notion of a martin-löf category--a locally cartesian closed category with disjoint coproducts and initial algebras of container functors (the categorical analogue of w-types)--and then establish that nested strictly positive inductive and coinductive types, which we call strictly positive types, exist in any martin-löf category.central to our development are the notions of containers and container functors. these provide a new conceptual analysis of data structures and polymorphic functions by exploiting dependent type theory as a convenient way to define constructions in martin-löf categories. we also show that morphisms between containers can be full and faithfully interpreted as polymorphic functions (i.e. natural transformations) and that, in the presence of w-types, all strictly positive types (including nested inductive and coinductive types) give rise to containers.
a functional correspondence between monadic evaluators and abstract machines for languages with computational effects. we extend our correspondence between evaluators and abstract machines from the pure setting of the λ-calculus to the impure setting of the computational λ-calculus. we show how to derive new abstract machines from monadic evaluators for the computational λ-calculus. starting from (1) a generic evaluator parameterized by a monad and (2) a monad specifying a computational effect, we inline the components of the monad in the generic evaluator to obtain an evaluator written in a style that is specific to this computational effect. we then derive the corresponding abstract machine by closure-converting, cps-transforming, and defunctionalizing this specific evaluator. we illustrate the construction with the identity monad, obtaining the cek machine, and with a lifted state monad, obtaining a variant of the cek machine with error and state.in addition, we characterize the tail-recursive stack inspection presented by clements and felleisen as a lifted state monad. this enables us to combine this stack-inspection monad with other monads and to construct abstract machines for languages with properly tail-recursive stack inspection and other computational effects. the construction scales to other monads--including one more properly dedicated to stack inspection than the lifted state monad--and other monadic evaluators.
scheduling with timed automata. in this work, we present timed automata as a natural tool for posing and solving scheduling problems. we show how efficient shortest path algorithms for timed automata can find optimal schedules for the classical job-shop problem. we then extend these results to synthesize adaptive scheduling strategies for problems with uncertainty in task durations.
model checking of systems with many identical timed processes. over the last years there has been an increasing research effort directed towards the automatic verification of infinite state systems, such as timed automata, hybrid automata, data-independent systems, relational automata, petri nets, lossy channel systems, context-free and push-down processes. we present a method for deciding reachability properties of networks of timed processes. such a network consists of an arbitrary set of identical timed automata, each with a single real-valued clock. using a standard reduction from safety properties to reachability properties, we can use our algorithm to decide general safety properties of timed networks. to our knowledge, this is the first decidability result concerning verification of systems that are infinite-state in "two dimensions": they contain an arbitrary set of (identical) processes, and they use infinite data-structures, viz real-valued clocks. we illustrate our method by showing how it can be used to automatically verify fischer's protocol, a timer-based protocol for enforcing mutual exclusion among an arbitrary number of processes.finally, we show undecidability of the recurrent state problem: given a state in a timed network, check whether there is a computation of the network visiting the state infinitely often. this implies undecidability of model checking for any temporal logic which is sufficiently expressive to encode the recurrent state problem, such as ptl, ctl, etc.
computational topology for isotopic surface reconstruction. new computational topology techniques are presented for surface reconstruction of 2-manifolds with boundary, while rigorous proofs have previously been limited to surfaces without boundary. this is done by an intermediate construction of the envelope (as defined herein) of the original surface. for any compact c2-manifold m embedded in r3, it is shown that its envelope is c1,1. then it is shown that there exists a piecewise linear (pl) subset of the reconstruction of the envelope that is ambient isotopic to m, whenever m is orientable. the emphasis of this paper is upon the formal mathematical proofs needed for these extensions. (practical application examples have already been published in a companion paper.) possible extensions to non-orientable manifolds are also discussed. the mathematical exposition relies heavily on known techniques from differential geometry and topology, but the specific new proofs are intended to be sufficiently specialized to prompt further algorithmic discoveries.
reductions for non-clausal theorem proving. this paper presents the tas methodology as a new framework for generating non-clausal automated theorem provers. we present a complete description of the atp for classical propositional logic, named tas-d, but the ideas, which make use of implicants and implicates can be extended in a natural manner to first-order logic, and non-classical logics. the method is based on the application of a number of reduction strategies on subformulas, in a rewrite-system style, in order to reduce the complexity of the formula as much as possible before branching. specifically, we introduce the concept of complete reduction, and extensions of the pure literal rule and ofthe collapsibility theorems; these strategies allow to limit the size ofthe search space. in addition, tas-d is a syntactical countermodel construction. as an example of the power of tas-d we study a class of formulas which has linear proofs (in the number of branchings) when either resolution or dissolution with factoring is applied. when applying our method to these formulas we get proofs without branching. in addition, some experimental results are reported. copyright 2001 elsevier science b.v.
a symbolical algorithm on additive basis and double-loop networks. a double-loop digraph g = g(n; s1, s2), with gcd(n, s1, s2) = 1, has the set of vertices v = zn and the adjacencies are given by u → u + si (mod n) i = 1, 2. the diameter of g, denoted by d(n; s1, s2), is known to be lower bounded by lb(n) with d(n) = min1 ≤ s1 < s2 < n, gcd(n, s1, s2)=1 d(n; s1, s2) ≥ ⌈ √3n ⌉ - 2 = lb(n). this lower bound is known to be sharp. for a fixed n ∈ n, some algorithms to find d(n) and steps 1 ≤ α < β < n such that d(n; α, β) = d(n) are known through the bibliography, being of numerical nature all of them.in this paper we propose a symbolic algorithm on the following problem: given a number of vertices n0 ∈ n, find if possible an infinite family of tiqht double-loop digraphs g(x) = g(n(x); s1(x), s2(x)) such that n(x0) = n0 and d(x) = d(n(x); s1(x),s2(x)) = lb(n(x)) ∀x ≥ x0. this family is parameterized by the integer x with n(x) ∈ z and s1(x); s2(x) ∈ z/(n(x)). as a direct consequence of such an explicit family of digraphs g(x), we also have an additive basis {s1(x), s2(x)} which covers the elements of z/(n(x)) with optimal order.the time cost of this algorithm is o(√n0 log n0), in the worst case.
iteration and coiteration schemes for higher-order and nested datatypes. this article studies the implementation of inductive and coinductive constructors of higher kinds (higher-order nested datatypes) in typed term rewriting, with emphasis on the choice of the iteration and coiteration constructions to support as primitive. we propose and compare several well-behaved extensions of system fω with some form of iteration and coiteration uniform in all kinds. in what we call mendler-style systems, the iterator and coiterator have a computational behavior similar to the general recursor, but their types guarantee termination. in conventional-style systems, monotonicity witnesses are used for a notion of monotonicity defined uniformly for all kinds. our most expressive systems gmitω and gitω of generalized mendler, resp. conventional (co)iteration encompass martin, gibbons and bailey's efficient folds for rank-2 inductive types. strong normalization of all systems considered is proved by providing an embedding of the basic mendler-style system mitω into system fω
competitive facility location: the voronoi game. we consider a competitive facility location problem with two players. players alternate placing points, one at a time, into the playing arena, until each of them has placed n points. the arena is then subdivided according to the nearest-neighbor rule, and the player whose points control the larger area wins. we present a winning strategy for the second player, where the arena is a circle or a line segment. we permit variations where players can play more than one point at a time, and show that the first player can ensure that the second player wins by an arbitrarily small margin.
games on triangulations. we analyze several perfect-information combinatorial games played on planar triangulations. we introduce three broad categories of such games--constructing, transforming, and marking triangulations--and several specific games within each category. in various situations of each game, we develop polynomial-time algorithms to determine who wins a given game position under optimal play, and to find a winning strategy. along the way, we show connections to existing combinatorial games such as kayles and nimstring (a variation on dots-and-boxes).
towards compatible triangulations. we state the following conjecture: any two planar n-point sets that agree on the number of convex hull points can be triangulated in a compatible manner, i.e., such that the resulting two triangulations are topologically equivalent. we first describe a class of point sets which can be triangulated compatibly with any other set (that satisfies the obvious size and shape restrictions). the conjecture is then proved true for point sets with at most three interior points. finally, we demonstrate that adding a small number of extraneous points (the number of interior points minus three) always allows for compatible triangulations. the linear bound extends to point sets of arbitrary size and shape.
the plurality problem with three colors and more. the plurality problem is a game between two participants: paul and carole. we are given n balls, each of them is colored with one out of c colors. at any step of the game, paul chooses two balls and asks whether they are of the same color, whereupon carole answers yes or no. the game ends when paul either produces a ball a of the plurality color (meaning that the number of balls colored like a exceeds those of the other colors), or when paul states that there is no plurality. how many questions lc(n) does paul have to ask in the worst case?for c = 2, the problem is equivalent to the well-known majority problem which has already been solved (combinatorica 11 (1991) 383-387). in this paper we show that 3 ⌊n/2⌋-2 ≤ l3(n) ≤ ⌊5n/3⌋ - 2. moreover, for any c ≤ n, we show that surprisingly the naive algorithm for the plurality problem is asymptotically optimal.
words whose complexity satisfies lim p(n)/n = 1. in this paper, we study the infinite words such that limn p(n)/n = 1, by using the rauzy graphs. we show that the infinite evolution of the graphs of these infinite words can be characterized by a rather simple condition, which ensures that the graphs with more than one right special factor appear rarely, so that makes the complexity very small.
the thue-morse word contains circular 5/2+ power free words of every length. a word is circular 5/2+ power free if none of its conjugates has period less than 2/5 of its length. we show that the thue-morse word contains words of every length which are circular 5/2+ power free.
correspondence and translation for heterogeneous data. data integration often requires a clean abstraction of the different formats in which data are stored, and means for specifying the correspondences/relationships between data in different worlds and for translating data from one world to another. for that, we introduce in this paper a middleware data model that serves as a basis for the integration task, and a declarative rules language for specifying the integration. we show that using the language, correspondences between data elements can be computed in polynomial time in many cases, and may require exponential time only when insensitivity to order or duplicates are considered. furthermore, we show that in most practical cases the correspondence rules can be automatically turned into translation rules to map data from one representation to another. thus, a complete integration task (derivation of correspondences, transformation of data from one world to the other, incremental integration of a new bulk of data, etc.) can be specified using a single set of declarative rules.
avoiding slack variables in the solving of linear diophantine equations and inequations. in this paper, we present an algorithm for solving directly linear diophantine systems of both equations and inequations. here directly means without adding slack variables for encoding inequalities as equalities. this algorithm is an extension of the algorithm due to contejean and devie (1994) for solving linear diophantine systems of equations, which is itself a generalization of the algorithm of fortenbacher (clausen and fortenbacher, 1989) for solving a single linear diophantine equation. all the nice properties of the algorithm of contejean and devie are still satisfied by the new algorithm: it is complete, i.e. provides a (finite) description of the set of solutions, it can be implemented with a bounded stack, and it admits an incremental version. all of these characteristics enable its integration in the clp paradigm. &mdash;authors' abstract
limiting partial combinatory algebras. from every partial combinatory algebra a we construct another partial combinatory algebra a-lim(a). in a-lim(a), every representable partial numerical function φ(n) is exactly of the form limtζ(t, n) for some representable partial numerical function ζ(t, n) of a. the partial combinatory algebra a-lim(a) is a quotient of a by a partial equivalence relation, and is equipped with a limit structure in the sense that each element of a-lim(a) is the limit of a countable sequence of a-elements. in this paper, we discuss the limit structures for a in terms of barendregt's range property (if the range of a combinator is finite, then it is a singleton). moreover, we repeat the construction a-lim(-) transfinite times to interpret infinitary λ-calculi. finally, we attempt to interpret type-free λµ-calculus by introducing another partial applicative structure which has an asynchronous application operator that allows a parallel limit operation.
self-stabilizing timestamps. the problem of implementing self-stabilizing timestamps with bounded values is investigated and a solution is found which is applied to the l-exclusion problem and to the multiwriter atomic register problem. thus we get self-stabilizing solutions to these two well-known problems. a new type of weak timestamps is identified here, and some evidence is brought to show its usefulness.
random lattices, threshold phenomena and efficient reduction algorithms. two new lattice reduction algorithms are presented and analyzed. these algorithms, called the schmidt reduction and the gram reduction, are obtained by relaxing some of the constraints of the classical lll algorithm. by analyzing the worst case behavior and the average case behavior in a tractable model, we prove that the new algorithms still produce "good" reduced basis while requiring fewer iterations on average. in addition, we provide empirical tests on random lattices coming from applications, that confirm our theoretical results about the relative behavior of the different reduction algorithms.
the optimal lll algorithm is still polynomial in fixed dimension. in this paper, we consider the open problem of the complexity of the lll algorithm in the case when the approximation parameter of the algorithm has as its extreme value 1. this case is of interest because the output is then the strongest lovász-reduced basis. experiments reported by lagarias and odlyzko (j. acm 32(1) (1985) 229) seem to show that the algorithm remains polynomial in average. however, no bound better than a naive exponential order one is established for the worst-case complexity of the optimal lll algorithm, even for fixed small dimension (higher than 2). here, we prove that, for any fixed dimension n, the number of iterations of the lll algorithm is linear with respect to the size of the input. it is easy to deduce from vallée (j. algorithms 12 (1991) 556) that the linear order is optimal. moreover in 3 dimensions, we give a tight bound for the maximum number of iterations and we characterize precisely the output basis. our bound also improves the known one for the usual (non-optimal) lll algorithm.
an assertion-based proof system for multithreaded java. besides the features of a class-based object-oriented language, java integrates concurrency via its thread classes, allowing for a multithreaded flow of control. the concurrency model includes synchronous message passing, dynamic thread creation, shared-variable concurrency via instance variables, and coordination via reentrant synchronization monitors.to reason about safety properties of multithreaded java programs, we introduce an assertional proof method for a multithreaded sublanguage of java, covering the mentioned concurrency issues as well as the object-based core of java. the verification method is formulated in terms of proof-outlines, where the assertions are layered into local ones specifying the behavior of a single instance, and global ones taking care of the connections between objects. we establish the soundness and the relative completeness of the proof system. from an annotated program, a number of verification conditions are generated and handed over to the interactive theorem prover pvs.
on canonical number systems. let p(x)=pdxd++p0z[x] be such that d1,pd=1,p02 and n={0,1,...,p01}. we are proving in this note a new criterion for the pair {p(x),n} to be a canonical number system. this enables us to prove that if p2,...,pd1,i=1dpi0 and p0>2i=1d|pi|, then {p(x),n} is a canonical number system.
self-stabilizing l-exclusion. our work presents a self-stabilizing solution to the l-exclusion problem. this problem is a well-known generalization of the mutual-exclusion problem in which up to l, but never more than l, processes are allowed simultaneously in their critical sections. self-stabilization means that even when transient failures occur and some processes crash, the system finally resumes its regular and correct behavior. the model of communication assumed here is that of shared memory, in which processes use single-writer multiple-reader regular registers. copyright 2001 elsevier science b.v.
a structural approach to reversible computation. reversibility is a key issue in the interface between computation and physics, and of growing importance as miniaturization progresses towards its physical limits. most foundational work on reversible computing to date has focussed on simulations of low-level machine models. by contrast, we develop a more structural approach. we show how high-level functional programs can be mapped compositionally (i.e. in a syntax-directed fashion) into a simple kind of automata which are immediately seen to be reversible. the size of the automaton is linear in the size of the functional term. in mathematical terms, we are building a concrete model of functional computation. this construction stems directly from ideas arising in geometry of interaction and linear logic--but can be understood without any knowledge of these topics. in fact, it serves as an excellent introduction to them. at the same time, an interesting logical delineation between reversible and irreversible forms of computation emerges from our analysis.
identification of genetic networks by strategic gene disruptions and gene overexpressions under a boolean model. analysis of the interactions between genes by systematic gene disruptions and gene overexpressions is an important topic in molecular biology. this paper analyses the problem of identifying a genetic network from the data obtained by multiple gene disruptions and overexpressions in regard to the number of experiments and the complexity of experiments. an experiment consists of simultaneous gene disruptions and overexpressions and the complexity of an experiment is the number of genes disrupted or overexpressed. we define a genetic network as a boolean network and show a series of algorithms which describe methods for identifying the underlying genetic network by such experiments. some lower bounds on the number of experiments required for the identification are also proved for some cases.
a simple greedy algorithm for finding functional relations: efficient implementation and average case analysis. inferring functional relations from relational databases is important for the discovery of scientific knowledge because many experimental data are represented in the form of tables and many rules are represented in the form of functions. a simple greedy algorithm has been known as an approximation algorithm for this problem. this paper presents an efficient implementation of the algorithm. this paper also shows that the algorithm can identify an exact solution for simple functions if input data for each function are generated uniformly at random and the size of the domain is bounded by a constant. results of computational experiments using artificially generated data are presented to verify the approach.
towards a semantics of proofs for non-commutative logic: multiplicatives and additives. interpretation of proofs of the multiplicative-additive fragment of non-commutative logic, by using bimodules on coherent spaces and bilinear functions.
computing the similarity of two sequences with nested arc annotations. we present exact algorithms for the np-complete longest common subsequence problem for sequences with nested arc annotations, a problem occurring in structure comparison of rna. given two sequences of length at most n and nested arc structure, one of our algorithms determines (if existent) in o(3.31k1+k2 ċ n) time an arc-preserving subsequence of both sequences, which can be obtained by deleting (together with corresponding arcs) k1 letters from the first and k2 letters from the second sequence. a second algorithm shows that, (in case of a four letter alphabet) we can find a length l arc-annotated subsequence in o(12lċlċn) time. this means that the problem is fixed-parameter tractable when parameterized by the number of deletions as well as when parameterized by the subsequence length. our findings complement known approximation results which give a quadratic time factor-2-approximation for the general and polynomial time approximation schemes for restricted versions of the problem. in addition, we obtain further fixed-parameter tractability results for these restricted versions.
the power of reachability testing for timed automata. the computational engine of the verification tool uppall consists of a collection of efficient algorithms for the analysis of teachability properties of systems. model-checking of properties other than plain reachability ones may currently be carried out in such a tool as follows. given a property φ to model-check, the user must provide a test automaton tφ for it. this test automaton must be such that the original system s has the property expressed by φ precisely when none of the distinguished reject states of tφ can be reached in the synchronized parallel composition of s with tφ. this raises the question of which properties may be analysed by uppaal in such a way. this paper gives an answer to this question by providing a complete characterization of the class of properties for which model-checking can be reduced to reachability testing in the sense outlined above. this result is obtained as a corollary of a stronger statement pertaining to the compositionality of the property language considered in this study. in particular, it is shown that our language is the least expressive compositional language that can express a simple safety property stating that no reject state can ever be reached.finally, the property language characterizing the power of reachability testing is used to provide a definition of characteristics properties with respect to a timed version of the ready simulation preorder, for nodes of τ-free, deterministic timed automata.
equational theories of tropical semirings. this paper studies the equational theories of various exotic semirings presented in the literature. exotic semirings are semirings whose underlying carrier set is some subset of the set of real numbers equipped with binary operations of minimum or maximum as sum, and addition as product. two prime examples of such structures are the (max,+) semiring and the tropical semiring. it is shown that none of the exotic semirings commonly considered in the literature has a finite basis for its equations, and that similar results hold for the commutative idempotent weak semirings that underlie them. for each of these commutative idempotent weak semirings, the paper offers characterizations of the equations that hold in them, decidability results for their equational theories, explicit descriptions of the free algebras in the varieties they generate, and relative axiomatization results.
regular closed sets of permutations. machines whose main purpose is to permute and sort data are studied. the sets of permtutations that can arise are analysed by means of finite automata and avoided pattern techniques. conditions are given for these sets to be enumerated by rational generating functions. as a consequence we give the first non-trivial examples of pattern closed sets of permutations all of whose closed subclasses have rational generating functions.
longest increasing subsequences in sliding windows. we consider the problem of finding the longest increasing subsequence in a sliding window over a given sequence (lisw). we propose an output-sensitive data structure that solves this problem in time o(n log log n+output) for a sequence of n elements. this data structure substantially improves over the naïve generalization of the longest increasing subsequence algorithm and in fact produces an output-sensitive optimal solution.
ccs with hennessy's merge has no finite-equational axiomatization. this paper confirms a conjecture of bergstra and klop's from 1984 by establishing that the process algebra obtained by adding an auxiliary operator proposed by hennessy in 1981 to the recursion free fragment of milner's calculus of communicating systems is not finitely based modulo bisimulation equivalence. thus, hennessy's merge cannot replace the left merge and communication merge operators proposed by bergstra and klop, at least if a finite axiomatization of parallel composition modulo bisimulation equivalence is desired.
normal form algorithms for extended context-free grammars. we investigate the complexity of a variety of normal-form transformations for extended context-free grammars, where by extended we mean that the set of right-hand sides for each nonterminal in such a grammar is a regular set. the study is motivated by the implementation project grama which will provide a c++ toolkit for the symbolic manipulation of context-free objects just as grail does for regular objects. our results generalize known complexity bounds for context-free grammars but do so in nontrivial ways. specifically, we introduce a new representation scheme for extended context-free grammars (the symbol-threaded expression forest), a new normal form for these grammars (dot normal form) and new regular expression algorithms. copyright 2001 elsevier science b.v.
bisimilarity is not finitely based over bpa with interrupt. this paper shows that bisimulation equivalence does not afford a finite equational axiomatization over the language obtained by enriching bergstra and klop's basic process algebra (bpa) with the interrupt operator. moreover, it is shown that the collection of closed equations over this language is also not finitely based. in sharp contrast to these results, the collection of closed equations over the language bpa enriched with the disrupt operator is proven to be finitely based.
a complete equational axiomatization for mpa with string iteration. we study equational axiomatizations of bisimulation equivalence for the language obtained by extending milner''s basic ccs with string iteration. string iteration is a variation on the original binary version of the kleene star operation $p^* q$ obtained by restricting the first argument to be a non-empty sequence of atomic actions. we show that, for every positive integer $k$, bisimulation equivalence over the set of processes in this language with loops of length at most $k$ is finitely axiomatizable, provided that the set of actions is finite. we also offer an infinite equational theory that completely axiomatizes bisimulation equivalence over the whole language. we prove that this result cannot be improved upon by showing that no finite equational axiomatization of bisimulation equivalence over basic ccs with string iteration can exist, unless the set of actions is empty.
a calculus for reasoning about software composition. although the term software component has become commonplace, there is no universally accepted definition of the term, nor does there exist a common foundation for specifying various kinds of components and their compositions. we propose such a foundation. the piccola calculus is a process calculus, based on the asynchronous π-calculus, extended with explicit namespaces. the calculus is high level, rather than minimal, and is consequently convenient for expressing and reasoning about software components, and different styles of composition. we motivate and present the calculus, and outline how it is used to specify the semantics of piccola, a small composition language. we demonstrate how the calculus can be used to simplify compositions by partial evaluation, and we briefly outline some other applications of the calculus to reasoning about compositional styles.
lower bounds for random 3-sat via differential equations. it is widely believed that the probability of satisfiability for random k-sat formulae exhibits a sharp threshold as a function of their clauses-to-variables ratio. for the most studied case, k= 3, there have been a number of results during the last decade providing upper and lower bounds for the threshold's potential location. all lower bounds in this vein have been algorithmic, i.e., in each case a particular algorithm was shown to satisfy random instances of 3-sat with probability 1- o(1) if the clauses-to-variables ratio is below a certain value. we show how differential equations can serve as a generic tool for analyzing such algorithms by rederiving most of the known lower bounds for random 3-sat in a simple, uniform manner.
on coalgebra based on classes. the category class of classes and functions is proved to have a number of properties suitable for algebra and coalgebra: every endofunctor is set-based, it has an initial algebra and a terminal coalgebra, the categories of algebras and coalgebras are complete and cocomplete, and every endofunctor generates a free completely iterative monad. a description of a terminal coalgebra for the power-set functor is provided.
on tree coalgebras and coalgebra presentations. for deterministic systems, expressed as coalgebras over polynomial functors, every tree t (an element of the final coalgebra) turns out to represent a new coalgebra at. the universal property of this family of coalgebras, resembling freeness, is that for every state s of every system s there exists a unique coalgebra homomorphism from a unique at which takes the root of t to s. consequently, the tree coalgebras are finitely presentable and form a strong generator. thus, these categories of coalgebras are locally finitely presentable; in particular every system is a filtered colimit of finitely presentable systems.in contrast, for transition systems expressed as coalgebras over the finite-power-set functor we show that there are systems which fail to be filtered colimits of finitely presentable (=finite) ones.surprisingly, if λ is an uncountable cardinal, then λ-presentation is always well-behaved: whenever an endofunctor f preserves λ-filtered colimits (i.e., is λ-accessible), then λ-presentable coalgebras are precisely those whose underlying objects are λ-presentable. consequently, every f coalgebra is a λ-filtered colimit of λ-presentable coalgebras; thus coalg f is a locally λ-presentable category. (this holds for all endofunctors of λ-accessible categories with colimits of ω-chains.) corollary: a set functor is bounded at λ in: the sense of kawahara and mori iff it is λ+-accessible.
on the usability of process algebra: an architectural view. despite its strengths like compositionality and equivalence checking, process algebra is rarely adopted outside the academia. in this paper we address the usability issue for process algebra along two different directions. on the modeling side, we provide a set of guidelines inspired by the software architecture field, which should enforce a clear component-oriented approach to the process algebraic design of system families. on the verification side, we propose a component-oriented technique based on equivalence checking for the detection of architecture-level mismatches and the provision of related diagnostic information. such a technique extends previous results in terms of generality of the considered mismatches, generality of the considered system topologies, and scalability to system families.
permuting machines and priority queues. machines whose sole function is to re-order their input data are considered. every such machine defines a set of allowable input-output pairs of permutations. these sets are studied in terms of the minimal disallowed pairs (the basis). some allowable sets with small bases are considered including the one defined by a priority queue machine. for more complex machines defined by two or more priority queues in series or parallel, the basis is proved to be infinite.
mutilated chessboard problem is exponentially hard for resolution. mutilated chessboard principle cbn says that it is impossible to cover by domino tiles the chessboard 2n × 2n with two diagonally opposite corners removed. we prove 2ω(√n) lower bound on the size of minimal resolution refutation of cbn.
coloring octrees. an octree is a recursive partition of the unit cube, such that in each step a cube is subdivided into eight smaller cubes. those cubes that are not further subdivided are the leaves of the octree. we consider the problem of coloring the leaves of an octree using as few colors as possible such that no two of them get the same color if they share a facet. it turns out that the number of colors needed depends on a parameter that we call unbalancedness. roughly speaking, this parameter measures how much adjacent cubes differ in size. for most values of this parameter we give tight bounds on the minimum number of colors, and extend the results to higher dimensions.
a new logic for electronic commerce protocols. the primary objective of this paper is to present the definition of a new dynamic, linear and modal logic for security protocols. the logic is compact, expressive and formal. it allows the specification of classical security properties (authentication, secrecy and integrity) and also electronic commerce properties (non-repudiation, anonymity, good atomicity, money atomicity, certified delivery, etc.). the logic constructs are interpreted over a trace-based model. traces reflect valid protocol executions in the presence of a malicious smart intruder. the logic is endowed with a tableau-based proof system that leads to a modular denotational semantics and local model checking.
divisibility problem for one relator monoids. we describe an algorithm which partially solves the divisibility problem for monoids with one defining relation of a special form. it can be shown that the word problem for one-relator monoids can be reduced to the problem studied here. it is conjectured that the presented algorithm can be completed to an algorithm which gives full solution of the problem. the validity of the conjecture would imply the decidability of the word problem for one-relator monoids.
intersection types and lambda models. invariance of interpretation by β-conversion is one of the minimal requirements for any standard model for the λ-calculus. with the intersection-type systems being a general framework for the study of semantic domains for the λ-calculus, the present paper provides a (syntactic) characterisation of the above mentioned requirement in terms of characterisation results ibr intersection-type assignment systems.instead of considering conversion as a whole, reduction and expansion will be considered separately. not only for usual computational rules like β η, but also for a number of relevant restrictions of those. characterisations will be also provided for (intersection) filter structures that are indeed λ-models.
a category of compositional domain-models for separable stone spaces. in this paper we introduce sfpm, a category of sfp domains which provides very satisfactory domain-models, i.e. "partializations", of separable stone spaces (2-stone spaces). more specifically, sfpm is a subcategory of sfpep, closed under direct limits as well as many constructors, such as lifting, sum, product and plotkin powerdomain (with the notable exception of the function space constructor). sfpm is "structurally well behaved", in the sense that the functor max, which associates to each object of sfpm the stone space of its maximal elements, is compositional with respect to the constructors above, and ω-continuous. a correspondence can be established between these constructors over sfpm and appropriate constructors on stone spaces, whereby sfpm domain-models of stone spaces defined as solutions of a vast class of recursive equations in sfpm, can be obtained simply by solving the corresponding equations in sfpm. moreover any continuous function between two 2-stone spaces can be extended to a continuous function between any two sfpm domain-models of the original spaces. the category sfpm does not include all the sfp's with a 2-stone space of maximal elements (csfp's). we show that the csfp's can be characterized precisely as suitable retracts of sfpm objects. then the results proved for sfpm easily extends to the wider category having csfp's as objects.using sfpm we can provide a plethora of "partializations" of the space of finitary hypersets (the hyperuniverse nω (ann. new york acad. sci. 806 (1996) 140). these includes the classical ones proposed in abramsky (a cook's tour of the finitary non-well-founded sets unpublished manuscript, 1988; inform. comput. 92(2) (1991) 161) and mislove et al. (inform. comput. 93(1) (1991) 16), which are also shown to be non-isomorphic, thus providing a negative answer to a problem raised in mislove et al.
an arithmetic for non-size-increasing polynomial-time computation. an arithmetical system is presented with the property that from every proof a realizing term can be extracted that is definable in a certain affine linear typed variant of gödel's t and therefore defines a non-size-increasing polynomial time computable function.
intersection types and domain operators. we use intersection types as a tool for obtaining λ-models. relying on the notion of easy intersection type theory, we successfully build a λ-model in which the interpretation of an arbitrary simple easy term is any filter which can be described by a continuous predicate. this allows us to prove two results. the first gives a proof of consistency of the λ-theory where the λ-term (λx.xx)(λx.xx) is forced to behave as the join operator. this result has interesting consequences on the algebraic structure of the lattice of λ-theories. the second result is that for any simple easy term, there is a λ-model, where the interpretation of the term is the minimal fixed point operator.
model checking discounted temporal properties. temporal logic is two-valued: formulas are interpreted as either true or false. when applied to the analysis of stochastic systems, or systems with imprecise formal models, temporal logic is therefore fragile: even small changes in the model can lead to opposite truth values for a specification. we present a generalization of the branching-time logic ctl which achieves robustness with respect to model perturbations by giving a quantitative interpretation to predicates and logical operators, and by discounting the importance of events according to how late they occur. in every state, the value of a formula is a real number in the interval [0,1], where 1 corresponds to truth and 0 to falsehood. the boolean operators and and or are replaced by min and max, the path quantifiers ∃ and ¬ determine sup and inf over all paths from a given state, and the temporal operators ♦ and □ specify sup and inf over a given path; a new operator averages all values along a path. furthermore, all path operators are discounted by a parameter that can be chosen to give more weight to states that are closer to the beginning of the path.we interpret the resulting logic dctl over transition systems, markov chains, and markov decision processes. we present two semantics for dctl: a path semantics, inspired by the standard interpretation of state and path formulas in ctl, and a fixpoint semantics, inspired by the µ-calculus evaluation of ctl formulas. we show that, while these semantics coincide for ctl, they differ for dctl, and we provide model-checking algorithms for both semantics.
hybrid diagrams. hybrid systems provide a formal model for physical systems controlled by discrete-state controllers. to help with the design of correct controllers, we present a methodology that enables the verification of linear-time temporal logic properties of general, non-linear hybrid systems. the methodology is based on the deductive transformation and algorithmic checking of hybrid diagrams.hybrid diagrams are graphs whose vertices and edges are labeled with first-order assertions; they represent system abstractions, together with the progress properties that have been proved about them. the verification process begins with the automatic construction of an initial diagram, whose behavior coincides with that of the hybrid system. the proof of a specification is constructed by applying a series of diagram transformations to this initial diagram. the transformations preserve behavior containment, and the aim of the transformations is to obtain a diagram that can be algorithmically shown to satisfy the specification. whenever the algorithmic check of a diagram fails, the check returns guidance for the further transformation of the diagram, or indications about possible counterexamples to the specification.we present four rules for transforming diagrams: each rule enables the study of a certain class of temporal logic properties. while some rules can be applied unconditionally, others require the proof of first-order verification conditions. we prove that the rules lead to the first verification methodology for general hybrid systems that is complete (relative to first-order reasoning) for proving specifications expressed in first-order linear-time temporal logic, provided no temporal operator appears in the scope of a quantifier.
an optimal pre-determinization algorithm for weighted transducers. we present a general algorithm, pre-determinization, that makes an arbitrary weighted transducer over the tropical semiring or an arbitrary unambiguous weighted transducer over a cancellative commutative semiring determinizable by inserting in it transitions labeled with special symbols. after determinization, the special symbols can be removed or replaced with ε-transitions. the resulting transducer can be significantly more efficient to use. we report empirical results showing that our algorithm leads to a substantial speed-up in large-vocabulary speech recognition. our pre-determinization algorithm makes use of an efficient algorithm for testing a general twins property, a sufficient condition for the determinizability of all weighted transducers over the tropical semiring and unambiguous weighted transducers over cancellative commutative semirings. based on the transitions marked by this test of the twins property, our pre-determinization algorithm inserts new transitions just when needed to guarantee that the resulting transducer has the twins property and thus is determinizable. it also uses a single-source shortest-paths algorithm over the min-max semiring for carefully selecting the positions for insertion of new transitions to benefit from the subsequent application of determinization. these positions are proved to be optimal in a sense that we describe.
nl-printable sets and nondeterministic kolmogorov complexity. p-printable sets were defined by hartmanis and yesha and have been investigated by several researchers. the analogous notion of l-printable sets was defined by fortnow et al.; both p-printability and l-printability were shown to be related to notions of resource-bounded kolmogorov complexity. nondeterministic logspace (nl)-printability was defined by jenner and kirsig, but some basic questions regarding this notion were left open. in this paper we answer a question of jenner and kirsig by providing a machine-based characterization of the nl-printable sets.in order to relate nl-printability to resource-bounded kolmogorov complexity, the paper introduces nondeterministic space-bounded kolmogorov complexity. we present some of the basic properties of this notion of kolmogorov complexity.using similar techniques, we investigate relationships among classes between nl and ul.
palindrome complexity. we study the palindrome complexity of infinite sequences on finite alphabets, i.e., the number of palindromic factors (blocks) of given length occurring in a given sequence. we survey the known results and obtain new results for some sequences, in particular for rote sequences and for fixed points of primitive morphisms of constant length belonging to "class p" of hof-knill-simon. we also give an upper bound for the palindrome complexity of a sequence in terms of its (block-)complexity.
branching bisimulation for probabilistic systems: characteristics and decidability. we address the concept of abstraction in the setting of probabilistic reactive systems, and study its formal underpinnings for the strictly alternating model of hansson. in particular, we define the notion of branching bisimilarity and study its properties by studying two other equivalence relations, viz. coloured trace equivalence and branching bisimilarity using maximal probabilities. we show that both alternatives coincide with branching bisimilarity. the alternative characterisations have their own merits and focus on different aspects of branching bisimilarity. coloured trace equivalence can be understood without knowledge of probability theory and is independent of the notion of a scheduler. branching bisimilarity, rephrased in terms of maximal probabilities gives rise to an algorithm of polynomial complexity for deciding the equivalence. together they give a better understanding of branching bisimilarity. furthermore, we show that the notions of branching bisimilarity in the alternating model of hansson and in the nonalternating model of segala differ: branching bisimilarity in the latter setting turns out to discriminate between systems that are intuitively branching bisimilar.
the ring of k-regular sequences, ii. in this paper, we continue our study of k-regular sequences begun in 1992. we prove some new results, give many new examples from the literature, and state some open problems.
lower bounds on the competitive ratio for mobile user tracking and distributed job scheduling. the authors prove a lower bound of omega (log n/log log n) on the competitive ratio of any (deterministic or randomised) distributed algorithm for solving the mobile user problem on certain networks of n processors. the lower bound holds for various networks, including the hypercube, any network with sufficiently large girth, and any highly expanding graph. a similar omega (log n/log log n) lower bound is proved for the competitive ratio of the maximum job delay of any distributed algorithm for solving a distributed scheduling problem on any of these networks. the proofs combine combinatorial techniques with tools from linear algebra and harmonic analysis and apply, in particular, a generalization of the vertex isoperimetric problem on the hypercube, which may be of independent interest.
a new algorithm for regularizing one-letter context-free grammars. constructive methods for obtaining regular grammar counterparts for some sub-classes of context-free grammars (cfgs) have been investigated by many researchers. an important class of grammars for which this is always possible is the one-letter cfg. we show in this paper a new constructive method for transforming an arbitrary one-letter cfg to an equivalent regular expression of star-height 0 or 1. our new result is considerably simpler than a previous construction by leiss, and we also propose a new normal form for a regular expression with only a single-star occurrence. through an alphabet factorization theorem, we show how to go beyond the one-letter cfg in a straight-forward way.
rules + strategies for transforming lazy functional logic programs. this work introduces a transformation methodology for functional logic programs based on needed narrowing, the optimal and complete operational principle for modern declarative languages which integrate the best features of functional and logic programming. we provide correctness results for the transformation system w.r.t, the set of computed values and answer substitutions and show that the prominent properties of needed narrowing--namely, the optimality w.r.t, the length of derivations and the number of computed solutions--carry over to the transformation process and the transformed programs. we illustrate the power of the system by taking on in our setting two well-known transformation strategies (composition and tupling). we also provide an implementation of the transformation system which, by means of some experimental results, highlights the potentiality of our approach.
deeper model endgame analysis. a reference model of fallible endgame play has been implemented and exercised with the chess-engine wilhelm. past experiments have demonstrated the value of the model and the robustness of decisions based on it: experiments agree well with a markov model theory. here, the reference model is exercised on the well-known endgame kbbkn.
a semantic framework for the abstract model checking of tccp programs. the timed concurrent constraint programming language (tccp) introduces time aspects into the concurrent constraint paradigm. this makes tccp especially appropriate for analyzing timing properties of concurrent systems by model checking. however, even if very compact state representations are obtained thanks to the use of constraints in tccp, large state spaces can still be generated, which may prevent model-checking tools from verifying tccp programs completely. model checking tccp programs is a difficult task due to the subtleties of the underlying operational semantics, which combines constraints, concurrency, non-determinism and time. currently, there is no practical model-checking tool that is applicable to tccp. in this work, we introduce an abstract methodology which is based on over-and under-approximating tccp models and which mitigates the state explosion problem that is common to traditional model-checking algorithms. we ascertain the conditions for the correctness of the abstract technique and show that this preliminary abstract semantics does not correctly simulate the suspension behavior, which is a key feature of tccp. then, we present a refined abstract semantics which correctly models suspension. finally, we complete our methodology by approximating the temporal properties that must be verified.
approximating the pareto curve with local search for the bicriteria tsp(1, 2) problem. local search has been widely used in combinatorial optimization (local search in combinatorial optimization, wiley, new york, 1997), however, in the case of multicriteria optimization almost no results are known concerning the ability of local search algorithms to generate "good" solutions with performance guarantee. in this paper, we introduce such an approach for the classical traveling salesman problem (tsp) problem (proc. stoc'00, 2000, pp. 126-133). we show that it is possible to get in linear time, a 3/2-approximate pareto curve using an original local search procedure based on the 2-opt neighborhood, for the bicriteria tsp(1,2) problem where every edge is associated to a couple of distances which are either 1 or 2 (math. oper. res. 18 (1) (1993) 1).
improved game play by multiple computer hint. humans and computers have different strengths, which should be combined, not wasted. multiple-choice systems are an efficient way to achieve this goal. an instructive example is 3-hirn, where two programs make one proposal each and a human boss has the final choice amongst them. in chess and several other brain games many experiments with 3-hirn and other settings proved the usefulness of multiple choice systems and the validity of the underlying ideas.
on the approximate tradeoff for bicriteria batching and parallel machine scheduling problems. we consider multiobjective scheduling problems, i.e. scheduling problems that are evaluated with respect to many cost criteria, and we are interested in determining a trade-off (pareto curve) among these criteria. we study two types of bicriteria scheduling problems: single-machine batching problems and parallel machine scheduling problems. instead of proceeding in a problem-by-problem basis, we identify a class of multiobjective optimization problems possessing a fully polynomial time approximation scheme (fptas) for computing an ε-approximate pareto curve. this class contains a set of problems whose pareto curve can be computed via a simple pseudo-polynomial dynamic program for which the objective and transition functions satisfy some, easy to verify, arithmetical conditions. our study is based on a recent work of woeginger (electronic colloquium on computational complexity, report 84 (short version appeared in soda'99, pp. 820-829)) for the single criteria optimization ex-benevolent problems. we show how our general result can be applied to the considered scheduling problems.
on the landscape ruggedness of the quadratic assignment problem. local-search-based heuristics have been demonstrated to give very good results to approximately solve the quadratic assignment problem (qap). in this paper, following the works of weinberger and stadler, we introduce a parameter, called the ruggedness coeffcient, which measures the ruggedness of the qap landscape which is the union of a cost function and a neighborhood. we give an exact expression, and a sharp lower bound for this parameter. we are able toderive from it that the landscape of the qap is rather flat, and so it gives a theoretical justification of the effectiveness of local-search-based heuristics for this problem. experimental results with simulated annealing are presented which con8rm this conclusion and also the influence of the ruggedness coe5cient on the quality of results obtained.
solution of a problem in dna computing. we answer a question of rozenberg and salomaa arising from a problem in dna computing. this problem was posed at the icalp conference in july 1999 in prague.
the algorithmic analysis of hybrid systems. we present a general framework for the formal specification and algorithmic analysis of hybrid systems. a hybrid system consists of a discrete program with an analog environment. we model hybrid systems as finite automata equipped with variables that evolve continuously with time according to dynamical laws. for verification purposes, we restrict ourselves to linear hybrid systems, where all variables follow piecewise-linear trajectories. we provide decidability and undecidability results for classes of linear hybrid systems, and we show that standard program-analysis techniques can be adapted to linear hybrid systems. in particular, we consider symbolic model-checking and minimization procedures that are based on the reachability analysis of an infinite state space. the procedures iteratively compute state sets that are definable as unions of convex polyhedra in multidimensional real space. we also present approximation techniques for dealing with systems for which the iterative procedures do not converge.
on the complexity of inducing categorical and quantitative association rules. inducing association rules is one of the central tasks in data mining applications. quantitative association rules induced from databases describe rich and hidden relationships to be found within data that can prove useful for various application purposes (e.g., market basket analysis, customer profiling, and others). although association rules are quite widely used in practice, a thorough analysis of the related computational complexity is missing. this paper intends to provide a contribution in this setting. to this end, we first formally define quantitative association rule mining problems, which include boolean association rules as a special case; we then analyze computational complexity of such problems. the general problem as well as some interesting special cases are considered.
counterexample-guided predicate abstraction of hybrid systems. predicate abstraction has emerged to be a powerful technique for extracting finite-state models from infinite-state systems, and has been recently shown to enhance the effectiveness of the teachability computation techniques for hybrid systems. given a hybrid system with linear dynamics and a set of linear predicates, the verifier performs an on-the-fly search of the finite discrete quotient whose states correspond to the truth assignments to the input predicates. the success of this approach depends on the choice of the predicates used for abstraction. in this paper, we focus on identifying these predicates automatically by analyzing spurious counterexamples generated by the search in the abstract state-space. we present the basic techniques for discovering new predicates that will rule out closely related spurious counterexamples, optimizations of these techniques, implementation of these in the verification tool, and case studies demonstrating the promise of the approach.
queries revisited. we begin with a brief tutorial on the problem of learning a finite concept class over a finite domain using membership queries and/or equivalence queries. we then sketch general results on the number of queries needed to learn a class of concepts, focusing on the various notions of combinatorial dimension that have been employed, including the teaching dimension, the exclusion dimension, the extended teaching dimension, the fingerprint dimension, the sample exclusion dimension, the vapnik-chervonenkis dimension, the abstract identification dimension, and the general dimension.
realizability and verification of msc graphs. scenario-based specifications such as message sequence charts (msc) offer an intuitive and visual way to describe design requirements. msc-graphs allow convenient expression of multiple scenarios, and can be viewed as an early model of the system that can be subjected to a variety of analyses. problems such as ltl model checking are undecidable for msc-graphs in general, but are known to be decidable for the class of bounded msc-graphs.our first set of results concerns checking realizability of bounded msc-graphs. an msc-graph is realizable if there is a distributed implementation that generates precisely the behaviors in the graph. there are two notions of realizability, weak and safe, depending on whether or not we require the implementation to be deadlock-free. it is known that for a finite set of mscs, weak realizability is conp-complete while safe realizability has a polynomial-time solution. we establish that for bounded msc-graphs, weak realizability is, surprisingly, undecidable, while safe realizability is in expspace.our second set of results concerns verification of msc-graphs. while checking properties of a graph g, besides verifying all the scenarios in the set l(g) of mscs specified by g, it is desirable to verify all the scenarios in the set lw(g)--the closure of g, that contains the implied scenarios that any distributed implementation of g must include. for checking whether a given msc m is a possible behavior, checking m ∈ l(g) is np-complete, but checking m ∈ lw(g) has a quadratic solution. for temporal logic specifications, considering the closure makes the verification problem harder: while checking ltl properties of l(g) is pspace-complete for bounded graphs g, checking even simple "local" properties of lw(g) is undecidable.
modular strategies for recursive game graphs. many problems in formal verification and program analysis can be formalized as computing winning strategies for two-player games on graphs. in this paper, we focus on solving games in recursive game graphs which can model the control flow in sequential programs with recursive procedure calls. while such games can be viewed as the pushdown games studied in the literature, the natural notion of winning in our framework requires the strategies to be modular with only local memory; that is, resolution of choices within a module does not depend on the context in which the module is invoked, but only on the history within the current invocation of the module. while reachability in (global) pushdown games is known to be exptime-complete, we show reachability in modular games to be np-complete. we present a fixed-point computation algorithm for solving modular games such that in the worst case the number of iterations is exponential in the total number of returned values from the modules. if the strategy within a module does not depend on the global history, but can remember the history of the past invocations of this module, that is, if memory is local but persistent, we show that reachability becomes undecidable.
neural learning methods yielding functional invariance. this paper investigates the functional invariance of neural network learning methods incorporating a complexity reduction mechanism, such as a regularizer. by functional invariance we mean the property of producing functionally equivalent minima as the size of the network grows, when the smoothing parameters are fixed. we study three different principles on which functional invariance can be based, and try to delimit the conditions under which each of them acts. we find out that, surprisingly, some of the most popular neural learning methods, such as weight-decay and input noise addition, exhibit this interesting property.
optimal paths in weighted timed automata. we consider the optimal-reachability problem for a timed automaton with respect to a linear cost function which results in a weighted timed automaton. our solution to this optimization problem consists of reducing it to computing (parametric) shortest paths in a finite weighted directed graph. we call this graph a parametric sub-region graph. it refines the region graph, a standard tool for the analysis of timed automata, by adding the information which is relevant to solving the optimal-teachability problem. we present an algorithm to solve the optimal-reachability problem for weighted timed automata that takes time exponential in o(<i>n</i>(|δ(<i>a</i>)| + |<i>w</i><inf>max</inf>|)), where <i>n</i> is the number of clocks, |δ(<i>a</i>)| is the size of the clock constraints and |<i>w</i><inf>max</inf>| is the size of the largest weight. we show that this algorithm can be improved, if we restrict to weighted timed automata with a single clock. in case we consider a single starting state for the optimal-reachability problem, our approach yields an algorithm that takes exponential time only in the length of clock constraints.
broadcasting in unstructured peer-to-peer overlay networks. peer-to-peer overlay networks present new opportunities and challenges for achieving enhanced network functionality at the application level. in this paper we study the impact of point-to-point network latency on flooding broadcast operations in peer-to-peer overlay networks. we show that two standard protocol mechanisms, used to control the amount of network resources used during flooding, can in combination, significantly reduce the reach of broadcast messages. we prove that these standard mechanisms, known as "time-to-live bounds" and "unique message identification", can result in broadcast operations that only reach a vanishing fraction of the nodes. in addition, we provide empirical evidence that the trend suggested by our formal results are found in data obtained from the gnutefla network and through network simulations.
weak linearization of the lambda calculus. we identify a restricted class of terms of the lambda calculus, here called weak linear, that includes the linear lambda-terms keeping their good properties of strong normalization, non-duplicating reductions and typability in polynomial time. the advantage of this class over the linear lambda-calculus is the possibility of transforming general terms into weak linear terms with the same normal form. we present such transformation and prove its correctness by showing that it preserves normal forms.
on the symbolic reduction of processes with cryptographic functions. we study the reachability problem for cryptographic protocols represented as processes relying on perfect cryptographic functions. we introduce a symbolic reduction system that can handle hashing functions, symmetric keys, and public keys. desirable properties such as secrecy or authenticity are specified by inserting logical assertions in the processes.we show that the symbolic reduction system provides a flexible decision procedure for finite processes and a reference for sound implementations. the symbolic reduction system can be regarded as a variant of syntactic unification which is compatible with certain set-membership constraints. for a significant fragment of our formalism, we argue that a dag implementation of the symbolic reduction system leads to an algorithm running in nptime thus matching the lower bound of the problem.in the case of iterated or finite control processes, we show that the problem is undecidable in general and in ptime for a subclass of iterated processes that do not rely on pairing. our technique is based on rational transductions of regular languages and it applies to a class of processes containing the ping-pong protocols presented in dolev et al. (inform. comput. (55) (1982) 57).
new operations and regular expressions for two-dimensional languages over one-letter alphabet. we consider the problem of defining regular expressions to characterize the class of recognizable picture languages in the case of a one-letter alphabet. we define a diagonal concatenation and its star and consider two different families, l(d) and l(crd), of languages denoted by regular expressions involving such operations plus classical operations. l(d) is characterized both in terms of rational relations and in terms of two-dimensional automata moving only right and down. l(crd) is included in rec and contains languages defined by three-way automata while languages in l(crd) necessarily satisfy some regularity conditions. finally, we introduce new definitions of advanced stars expressing the necessity of conceptually different definitions for iteration.
on learning monotone boolean functions under the uniform distribution. in this paper, we prove two general theorems on monotone boolean functions which are useful for constructing a learning algorithm for monotone boolean functions under the uniform distribution.a monotone boolean function is called fair if it takes the value 1 on exactly half of its inputs. the first result proved in this paper is that a single variable function f(x) = xi has the minimum correlation with the majority function among all fair monotone functions. this proves the conjecture by blum et al. (1998, proc. 39th focs, pp. 408-415) and improves the performance guarantee of the best known learning algorithm for monotone boolean functions under the uniform distribution they proposed.our second result is on the relationship between the influences and the average sensitivity of a monotone boolean function. the influence of variable xi on f is defined as the probability that f(x) differs from f(x ⊕ ei) where x is chosen uniformly from {0, 1}n and x ⊕ ei means x with its ith bit flipped. the average sensitivity of f is defined as the sum of the influences over all variables xi. we prove that a somewhat unintuitive result which says if the influence of every variable on a monotone boolean function is small, i.e., o(1/nc) for some constant c > 0, then the average sensitivity of the function must be large, i.e., ω(log n). we also discuss how to apply this result to the construction of a new learning algorithm for monotone boolean functions.
taming the complexity of biochemical models through bisimulation and collapsing: theory and practice. many biological systems can be modeled using systems of ordinary differential algebraic equations (e.g., s-systems), thus allowing the study of their solutions and behavior automatically with suitable software tools (e.g., plas, octave/matlabtm). usually, numerical solutions (traces or trajectories) for appropriate initial conditions are analyzed in order to infer significant properties of the biological systems under study. when several variables are involved and the traces span over a long interval of time, the analysis phase necessitates automation in a scalable and efficient manner. earlier, we have advocated and experimented with the use of automata and temporal logics for this purpose (xs-systems and simpathica) and here we continue our investigation more deeply.we propose the use of hybrid automata and we discuss the use of the notions of bisimulation and collapsing for a "qualitative" analysis of the temporal evolution of biological systems. as compared with our previous approach, hybrid automata allow maintenance of more information about the differential equations (s-system) than standard automata. the use of the notion of bisimulation in the definition of the projection operation (restrictions to a subset of "interesting" variables) makes it possible to work with reduced automata satisfying the same formulae as the initial ones. finally, the notion of collapsing is introduced to move toward still simpler and equivalent automaton taming the complexity in terms of states whose number depends on the attained level of approximation.
lower bounds for the rate of convergence in nonparametric pattern recognition. we show that there exist individual lower bounds corresponding to the upper bounds for the rate of convergence of nonparametric pattern recognition which are arbitrarily close to yang's minimax lower bounds, for certain "cubic" classes of regression functions used by stone and others. the rates are equal to the ones of the corresponding regression function estimation problem. thus for these classes classification is not easier than regression function estimation.
hierarchies of probabilistic and team fin-learning. a fin-learning machine m receives successive values of the function f it is learning and at some moment outputs a conjecture which should be a correct index of f. fin learning has two extensions: (1) if m flips fair coins and learns a function with certain probability p, we have fin (p)-learning. (2) when n machines simultaneously try to learn the same function f and at least k of these machines output correct indices of f, we have learning by a [k,n] fin team. sometimes a team or a probabilistic learner can simulate another one, if their probabilities p1, p2 (or team success ratios k1/n1,k2/n2) are close enough (daley et al., in: valiant, waranth (eds.), proc. 5th annual workshop on computational learning theory, acm press, new york, 1992, pp. 203-217; daley and kalyanasundaram, available from http://www.cs.pitt.edu/~daley/fin/fin.html, 1996). on the other hand, there are cut-points r which make simulation of fin (p2) by fin (p1) impossible whenever p2 < r < p1. cut-points above 10/21 are known (daley and kalyanasundaram, available from (www.cs.pitt.edu/~daley/fin/fin.html, 1996).
computational depth: concept and applications. we introduce computational depth, a measure for the amount of "nonrandom" or "useful" information in a string by considering the difference of various kolmogorov complexity measures. we investigate three instantiations of computational depth: • basic computational depth, a clean notion capturing the spirit of bennett's logical depth. we show that a turing machine m runs in time polynomial on average over the time-bounded universal distribution if and only if for all inputs x, m uses time exponential in the basic computational depth of x. • sublinear-time computational depth and the resulting concept of shallow sets, a generalization of sparse and random sets based on low depth properties of their characteristic sequences. we show that every computable set that is reducible to a shallow set has polynomial-size circuits. • distinguishing computational depth, measuring when strings are easier to recognize than to produce. we show that if a boolean formula has a nonnegligible fraction of its satisfying assignments with low depth, then we can find a satisfying assignment efficiently.
almost complete sets. we show that there is a set that is almost complete but not complete under polynomial-time many-one (p-m) reductions for the class e of sets computable in deterministic time 2lin. here a set in a complexity class c is almost complete for c under some given reducibility if the class of the problems in c that do not reduce to this set has measure 0 in c in the sense of lutz's resource-bounded measure theory. we also show that the almost complete sets for e under polynomial time-bounded length-increasing one-one reductions and truth-table reductions of norm 1 coincide with the almost p-m-complete sets for e. moreover, we obtain similar results for the class exp of sets computable in deterministic time 2poly.
on the approximability of the range assignment problem on radio networks in presence of selfish agents. we consider the range assignment problem in ad-hoc wireless networks in the context of selfish agents: a network manager aims to assigning transmission ranges to the stations in order to achieve strong connectivity of the network within a minimal overallpower consumption. station is not directly controlled by the manager and may refuse to transmit with a certain transmission range because it might be costly in terms of power consumption.we investigate the existence of payment schemes which induce the stations to follow the decisions of a network manager in computing a range assignment, that is, truthful mechanisms for the range assignment problem. we provide both positive and negative results on the existence of truthful vcg-based mechanisms for this np-hard problem. we prove that (i) in general, every polynomial-time truthful vcg-based mechanism computes a solution of cost far-off the optimum, unless p = np and (ii) there exists a polynomial-time truthful vcg-based mechanism achieving constant approximation for practically relevant, still np-hard versions, i.e., the metric and the well-spread case.
a new lower bound for the list update problem in the partial cost model. the optimal competitive ratio for a randomized online list update algorithm is known to be at least 1.5 and at most 1.6, but the remaining gap is not yet closed. we present a new lower bound of 1.50084 for the partial cost model. the construction is based on game trees with incomplete information, which seem to be generally useful for the competitive analysis of online algorithms. 2001 elsevier science b.v.
computational topology: ambient isotopic approximation of 2-manifolds. a fundamental issue in theoretical computer science is that of establishing unambiguous formal criteria for algorithmic output. this paper does so within the domain of computer-aided geometric modeling. for practical geometric modeling algorithms, it is often desirable to create piecewise linear approximations to compact manifolds embedded in r3, and it is usually desirable for these two representations to be "topologically equivalent". though this has traditionally been taken to mean that the two representations are homeomorphic, such a notion of equivalence suffers from a variety of technical and philosophical difficulties; we adopt the stronger notion of ambient isotopy. it is shown here, that for any c2, compact, 2-manifold without boundary, which is embedded in r3, there exists a piecewise linear ambient isotopic approximation. furthermore, this isotopy has compact support, with specific bounds upon the size of this compact neighborhood. these bounds may be useful for practical application in computer graphics and engineering design simulations. the proof given relies upon properties of the medial axis, which is explained in this paper.
two-dimensional pattern matching with rotations. the problem of pattern matching with rotation is that of finding all occurrences of a two-dimensional pattern in a text, in all possible rotations. we prove an upper and lower bound on the number of such different possible rotated patterns. subsequently, given an m × m array (pattern) and an n × n array (text) over some finite alphabet σ, we present a new method yielding an o(n2m3) time algorithm for this problem.
inplace run-length 2d compressed search. the recent explosion in the amount of stored data has necessitated the storage and transmission of data in compressed form. the need to quickly access this data has given rise to a new paradigm in searching, that of compressed matching (proc. data compression conf, snow bird, ut, 1992, pp. 279-288; proc. 8th annu. symp. on combinatorial pattern matching (cpm 97), lecture notes in computer science, vol. 1264, springer, berlin, 1997, pp. 40-51; proc. 7th annu. symp. on combinatorial pattern matching (cpm 96), lecture notes in computer science, vol. 1075, springer, berlin, 1996, pp. 39-49). the goal of the compressed pattern matching problem is to find a pattern in a text without decompressing the text.the criterion of extra space is very relevant to compressed searching. an algorithm is called inplace if the amount of extra space used is proportional to the input size of the pattern. in this paper we present a 2d compressed matching algorithm that is inplace. let compressed(t) and compressed(p) denote the compressed text and pattern, respectively. the algorithm presented in this paper runs in time o(|compressed(t)| + |p|log σ) where σ is min(|p|,|σ), and σ is the alphabet, for all patterns that have no trivial rows (rows consisting of a single repeating symbol). the amount of space used is o(|compressed(p)|). the compression used is the 2d run-length compression, used in fax transmission.
topics in the theory of dna computing. dna computing, or, more generally, molecular computing, is an exciting fast developing interdisciplinary area. research in this area concerns theory, experiments, and applications of dna computing. in this paper, we demonstrate the theoretical developments by discussing a number of selected topics. we also give an introduction to the basic structure of dna and the basic dna processing tools.
image reducing words and subgroups of free groups. a word w over a finite alphabet σ is said to be n-collapsing if for an arbitrary finite automaton a = 〈q,σ_._〉, the inequality |q ċ w| ≤ |q|- n holds provided that |q ċ u| ≤ |q|- n for some word u (depending on a). we give an algorithm to test whether a word is 2-collapsing. to this aim we associate to every word w a finite family of finitely generated subgroups in finitely generated free groups and prove that the property of being 2-collapsing reflects in the property that each of these subgroups has index at most 2 in the corresponding free group. we also find a similar characterization for the closely related class of so-called 2-synchronizing words.
closedness properties in ex-identification. in this paper we investigate in which cases unions of identifiable classes are also necessarily identifiable. we consider identification in the limit with bounds on mindchanges and anomalies. though not closed under the set union, these identification types still have features resembling closedness. for each of them we and n such that (1) if every union of n &minus; 1 classes out of u1, ... , un is identifiable, so is the union of all n classes; (2) there are classes u1, ... ,un&minus;1 such that every union of n&minus;2 classes out of them is identifiable, while the union of n &minus; 1 classes is not. we show that by finding these n we can distinguish which requirements put on the identifiability of unions of classes are satisfiable and which are not. we also show how our problem is connected with team learning. copyright 2001 elsevier science b.v. all rights reserved.
synchronizing monotonic automata. we show that if the state set q of a synchronizing automaton a = 〈q, σ, δ〉 admits a linear order such that for each letter a ∈ σ the transformation δ(_,a) of q preserves this order, then a possesses a reset word of length |q| - 1. we also consider two natural generalizations of the notion of a reset word and provide for them results of a similar flavour.
synchronizing generalized monotonic automata. in an earlier paper, we have studied reset words for synchronizing automata whose states admit a stable linear order. here we show that the same bound on the length of the shortest reset word persists for synchronizing automata satisfying much weaker stability restriction. this result supports our conjecture concerning the length of reset words for synchronizing automata accepting only star-free languages.
sturmian words and a criterium by michaux-villemaire. michaux and villemaire's proof of cobham's theorem relies on the characterization of ultimately periodic words by means of the behaviour of certain repetitions in the word. namely, they consider the length of the smallest shift between repetitions of a given length and the first position at which that smallest shift is observed. in this paper we study those properties for characteristic sturmian words. in particular we answer a question posed by michaux and villemaire in that context.
words derivated from sturmian words. a return word of a factor of a sturmian word starts at an occurrence of that factor and ends exactly before its next occurrence. derivated words encode the unique decomposition of a word in terms of return words. vuillon has proved that each factor of a sturmian word has exactly two return words. we determine these two return words, as well as their first occurrence, for the prefixes of characteristic sturmian words. we then characterize words derivated from a characteristic sturmian word and give their precise form. finally, we apply our results to obtain a new proof of the characterization of characteristic sturmian words which are fixed points of morphisms.
scalar aggregation in inconsistent databases. we consider here scalar aggregation queries in databases that may violate a given set of functional dependencies. we define consistent answers to such queries to be greatest-lowest/least-upper bounds on the value of the scalar function across all (minimal) repairs of the database. we show how to compute such answers. we provide a complete characterization of the computational complexity of this problem. we also show how tractability can be improved in several special cases (one involves a novel application of boyce-codd normal form) and present a practical hybrid query evaluation method.
nivat's processes and their synchronization. this short paper retraces how the notion of synchronization of processes introduced by maurice nivat in 1979 has evolved over more than 20 years.
weighted multirecombination evolution strategies. weighted recombination is a means for improving the local search performance of evolution strategies. it aims to make effective use of the information available, without significantly increasing computational costs per time step. in this paper, the potential speed-up resulting from using rank-based weighted multirecombination is investigated. optimal weights are computed for the infinite-dimensional sphere model, and comparisons with the performance of strategies that do not make use of weighted recombination are presented. it is seen that unlike strategies that rely on unweighted recombination and truncation selection, weighted multirecombination evolution strategies are able to improve on the serial efficiency of the (1 + 1)-es on the sphere. the implications of the use of weighted recombination for noisy optimization are studied, and parallels to the use of rescaled mutations are drawn. the significance of the findings is investigated in finite-dimensional search spaces.
performance analysis of evolution strategies with multi-recombination in high-dimensional rn-search spaces disturbed by noise. the presence of noise in real-world optimization problems poses difficulties to optimization strategies. it is frequently observed that evolutionary algorithms are quite capable of succeeding in noisy environments. intuitively, the use of a population of candidate solutions alongside with some implicit or explicit form of averaging inherent in the algorithms is considered responsible. however, so as to arrive at a deeper understanding of the reasons for the capabilities of evolutionary algorithms, mathematical analyses of their performance in select environments are necessary. such analyses can reveal how the performance of the algorithms scales with parameters of the problem--such as the dimensionality of the search space or the noise strength--or of the algorithms--such as population size or mutation strength. recommendations regarding the optimal sizing of such parameters can then be derived.the present paper derives an asymptotically exact approximation to the progress rate of the (µ/µi, λ)-evolution strategy (es) on a finite-dimensional noisy sphere. it is shown that, in contrast to results obtained in the limit of infinite search space dimensionality, there is a finite optimal population size above which the efficiency of the strategy declines, and that therefore it is not possible to attain the efficiency that can be achieved in the absence of noise by increasing the population size. it is also shown that nonetheless, the benefits of genetic repair and an increased mutation strength make it possible for the multi-parent (µ/µi, λ)-es to far outperform simple one-parent strategies.
synchronizing groups and automata. pin showed that every p-state automaton (p a prime) containing a cyclic permutation and a non-permutation has a synchronizing word of length at most (p - 1)2. in this paper, we consider permutation automata with the property that adding any nonpermutation will lead to a synchronizing word and establish bounds on the lengths of such synchronizing words. in particular, we show that permutation groups whose permutation character over the rationals splits into a sum of only two irreducible characters have the desired property.
games for synthesis of controllers with partial observation. the synthesis of controllers for discrete event systems, as introduced by ramadge and wonham, amounts to computing winning strategies in parity games. we show that in this framework it is possible to extend the specifications of the supervised systems as well as the constraints on the controllers by expressing them in the modal µ-calculus.in order to express unobservability constraints, we propose an extension of the modal µ-calculus in which one can specify whether an edge of a graph is a loop. this extended µ-calculus still has the interesting properties of the classical one. in particular it is equivalent to automata with loop testing. the problems such as emptiness testing and elimination of alternation are solvable for such automata.the method proposed in this paper to solve a control problem consists in transforming this problem into a problem of satisfiability of a µ-calculus formula so that the set of models of this formula is exactly the set of controllers that solve the problem. this transformation relies on a simple construction of the quotient of automata with loop testing by a deterministic transition system. this is enough to deal with centralized control problems. the solution of decentralized control problems uses a more involved construction of the quotient of two automata.this work extends the framework of ramadge and wonham in two directions. we consider infinite behaviours and arbitrary regular specifications, while the standard framework deals only with specifications on the set of finite paths of processes. we also allow dynamic changes of the sets of observable and controllable events.
two-dimensional iterated morphisms and discrete planes. iterated morphisms of the free monoid are very simple combinatorial objects which produce infinite sequences by replacing iteratively letters by words. the aim of this paper is to introduce a formalism for a notion of two-dimensional morphisms; we show that they can be iterated by using local rules, and that they generate two-dimensional patterns related to discrete approximations of irrational planes with algebraic parameters. we associate such a two-dimensional morphism with any usual pisot unimodular one-dimensional iterated morphism over a three-letter alphabet.
a generalization of the language of ukasiewicz coding rooted planar hypermaps. we introduce a coding of rooted planar hypermaps by words of a language generalizing the language of lukasiewicz. this code is obtained by a geometrical decomposition of hypermaps and leads to a new enumeration of rooted planar hypermaps with respect to the number of vertices, hyperfaces and hyperedges.
a note on first-order projections and games. we show how the fact that there is a first-order projection from the problem transitive closure (tc) to some other problem ω enables us to automatically deduce that a natural game problem, lg(ω), whose instances are labelled instances of ω, is complete for pspace (via log-space reductions). our analysis is strongly dependent upon the reduction from tc to ω being a logical projection in that it fails should the reduction be, for example, a log-space reduction or a quantifier-free first-order translation.
justified common knowledge. in this paper we introduce the justified knowledge operator j with the intended meaning of j ϕ as 'there is a justification for ϕ.' though justified knowledge appears here in a case study of common knowledge systems, a similar approach is applicable in more general situations. first we consider evidence-based common knowledge systems obtained by augmenting a multi-agent logic of knowledge with a system of evidence assertions t:ϕ, reflecting the notion 't is an evidence for ϕ,' such that evidence is respected by all agents. justified common knowledge is obtained by collapsing all evidence terms into one modality j. we show that in standard situations, when the base epistemic systems are t, s4, and s5, the resulting justified common knowledge systems are normal modal logics, which places them within the scope of well-developed machinery applicable to modal logic: kripke-style epistemic models, normalized proofs, automated proof search, etc. in the aforementioned situations, the intended semantics of justified knowledge is supported by a realization theorem stating that for any valid fact about justified knowledge, one could recover its constructive meaning by realizing all occurrences of justified knowledge modalities jϕ by appropriate evidence terms t:ϕ.
combining test case generation and runtime verification. software testing is typically an ad hoc process where human testers manually write test inputs and descriptions of expected test results, perhaps automating their execution in a regression suite. this process is cumbersome and costly. this paper reports results on a framework to further automate this process. the framework consists of combining automated test case generation based on systematically exploring the input domain of the program with runtime verification, where execution traces are monitored and verified against properties expressed in temporal logic. capabilities also exist for analyzing traces for concurrency errors, such as deadlocks and data races. the input domain of the program is explored using a model checker extended with symbolic execution. properties are formulated in an expressive temporal logic. a methodology is advocated that automatically generates properties specific to each input rather than formulating properties uniformally true for all inputs. the paper describes an application of the technology to a nasa rover controller.
a fast natural algorithm for searching. in this note we present two natural algorithms--one for sorting, and another for searching a sorted list of items. both algorithms work in o(√n) time, n being the size of the list. a combination of these algorithms can search an unsorted list in o(√n) time, an impossibility for classical algorithms. the same complexity is achieved by grover's quantum search algorithm; in contrast to grover's algorithm which is probabilistic, our method is guaranteed correct. two applications will conclude this note.
an improved analysis of goemans and williamson's lp-relaxation for max sat. for max sat, which is a well-known np-hard problem, many approximation algorithms have been proposed. two types of best approximation algorithms for max sat were proposed by asano and williamson: one with best proven performance guarantee 0.7846 and the other with performance guarantee 0.8331 if the performance guarantee of the zwick's algorithm for max sat is, as conjectured. both algorithms are based on their sharpened analysis of goemans and williamson's lp-relaxation for max sat. in this paper, we present an improved analysis which is simpler than the previous analysis. furthermore, algorithms based on this, analysis will play a role as a better building block in designing an improved approximation algorithm for max sat. actually we, show an example that algorithms based on this analysis lead to approximation algorithms with performance guarantee 0.7877 and, conjectured performance guarantee 0.8353 which are slightly better than the best known corresponding performance guarantees, 0.7846 and 0.8331, respectively.
the structure and number of global roundings of a graph. given a connected weighted graph g = (v,e), we consider a hypergraph hg = (v, pg) corresponding to the set of all shortest paths in g. for a given real assignment a on v satisfying 0≤a(v)≤1, a global rounding α with respect to hg is a binary assignment satisfying that |σv∈fa(v)-α(v)| <1 for every f ∈ pg. we conjecture that there are at most |v| + 1 global roundings for hg, and also the set of global roundings is an affine independent set. we give several positive evidences for the conjecture.
interaction systems ii: the practice of optimal reductions. lamping''s optimal graph reduction technique for the lambda-calculus is generalized to a new class of higher order rewriting systems, called interaction systems. interaction systems provide a nice integration of the functional paradigm with a rich class of data structures (all inductive types), and some basic control flow constructs such as conditionals and (primitive or general) recursion. we describe a uniform and optimal implementation, in lamping''s style, for all these features. this work is the natural continuation of our previous paper "interaction systems i, the theory of optimal reductions", where we focused on the theoretical aspects of optimal reductions in is''s (family relation, labeling, extraction, an so on).
subtyping dependent types. the need for subtyping in type systems with dependent types has been realized for some years. but it is hard to prove that systems combining the two features have fundamental properties such as subject reduction. here we investigate a subtyping extension of the system λp, which is an abstract version of the type system of the edinburgh logical framework lf. by using an equivalent formulation, we establish some important properties of the new system λp6=, including subject reduction. our analysis culminates in a complete and terminating algorithm which establishes the decidability of type-checking. copyright 2001 elsevier science b.v.
casl: the common algebraic specification language. the common algebraic specification language (casl) is an expressive language for the formal specification of functional requirements and modular design of software. it has been designed by cofi, the international common framework initiative for algebraic specification and development. it is based on a critical selection of features that have already been explored in various contexts, including subsorts, partial functions, first-order logic, and structured and architectural specifications. casl should facilitate interoperability of many existing algebraic prototyping and verification tools.this paper gives an overview of the casl design. the major issues that had to be resolved in the design process are indicated, and all the main concepts and constructs of casl are briefly explained and illustrated -- the reader is referred to the casl language summary for further details. some familiarity with the fundamental concepts of algebraic specification would be advantageous.
algebraic aspects of families of fuzzy languages. we study operations on fuzzy languages such as union, concatenation, kleene *, intersection with regular fuzzy languages, and several kinds of (iterated) fuzzy substitution. then we consider families of fuzzy languages, closed under a fixed collection of these operations, which results in the concept of full abstract family of fuzzy languages or full affl. this algebraic structure is the fuzzy counterpart of the notion of full abstract family of languages that has been encountered frequently in investigating families of crisp (i.e., non-fuzzy) languages. some simpler and more complicated algebraic structures (such as full substitution-closed affl, full super-affl, full hyper-affl) will be considered as well.in the second part of the paper we focus our attention to full affls closed under iterated parallel fuzzy substitution, where the iterating process is prescribed by given crisp control languages. proceeding inductively over the family of these control languages, yields an infinite sequence of full affl-structures with increasingly stronger closure properties.
fuzzy context-free languages - part 1: generalized fuzzy context-free grammars. motivated by aspects of robustness in parsing a context-free language, we study generalized fuzzy context-free grammars. these fuzzy context-free k-grammars provide a general framework to describe correctly as well as erroneously derived sentences by a single generating mechanism. they model the situation of making a finite choice out of an infinity of possible grammatical errors during each context-free derivation step. formally, a fuzzy context-free k-grammar is a fuzzy context-free grammar with a countable rather than a finite number of rules satisfying the following condition: for each symbol α, the set containing all right-hand sides of rules with left-hand side equal to α forms a fuzzy language that belongs to a given family k of fuzzy languages. we investigate the generating power of fuzzy context-free k-grammars, and we show that under minor assumptions on the parameter k, the family of languages generated by fuzzy context-free k-grammars possesses closure properties very similar to those of the family of ordinary context-free languages.
fuzzy context-free languages - part 2: recognition and parsing algorithms. in a companion paper [p.r.j. asveld, fuzzy context-free languages--part 1: generalized fuzzy context-free grammars, theoret. comput. sci. (2005)] we used fuzzy context-free grammars in order to model grammatical errors resulting in erroneous inputs for robust recognizing and parsing algorithms for fuzzy context-free languages. in particular, this approach enables us to distinguish between small errors ("tiny mistakes") and big errors ("capital blunders").in this paper, we present some algorithms to recognize fuzzy context-free languages: particularly, a modification of cocke-younger-kasami's algorithm and some recursive descent algorithms. then we extend these recognition algorithms to corresponding parsing algorithms for fuzzy context-free languages. these parsing algorithms happen to be robust in some very elementary sense.
generating all permutations by context-free grammars in chomsky normal form. let ln be the finite language of all n! strings that are permutations of n different symbols (n ≥ 1). we consider context-free grammars gn in chomsky normal form that generate ln. in particular we study a few families {gn}n ≥ 1, satisfying l(gn) = ln for n ≥ 1, with respect to their descriptional complexity, i.e. we determine the number of nonterminal symbols and the number of production rules of gn as functions of n.
sorting with two ordered stacks in series. the permutations that can be sorted by two stacks in series are considered, subject to the condition that each stack remains ordered. a forbidden characterisation of such permutations is obtained and the number of permutations of each length is determined by a generating function.
improved bounds on the weak pigeonhole principle and infinitely many primes from weaker axioms. we show that the known bounded-depth proofs of the weak pigeonhole principle phpn2n in size no(log(n)) are not optimal in terms of size. more precisely, we give a size-depth trade-off upper bound: there are proofs of size no(d(log(n))2/d) and depth o(d). this solves an open problem of maciel et al. (proceedings of the 32nd annual acm symposium on the theory of computing, 2000). our technique requires formalizing the ideas underlying nepomnjascij's theorem which might be of independent interest. moreover, our result implies a proof of the unboundedness of primes in iδ0 with a provably weaker 'large number assumption' than previously needed.
linear time approximation schemes for vehicle scheduling problems. we consider makespan minimization for vehicle scheduling problems on trees with job requests that have release and handling times. 2-approximation algorithms were known for several variants of the single vehicle problem on a path. a 3/2-approximation algorithm was known for the single vehicle problem on a path where there is a fixed starting point and the vehicle must return to the starting point upon completion. karuno, nagamochi and ibaraki give a 2-approximation algorithm for the single vehicle problem on trees. we develop a polynomial time approximation scheme (ptas) that runs in time linear in the number of job requests for the single vehicle scheduling problem on trees that have a constant number of leaves. this ptas can be easily adapted to accommodate various starting/ending constraints. we then extended this to a ptas for the multiple vehicle problem where vehicles operate in disjoint subtrees.
constructing divisions into power groups. the result, due to henckell, margolis, pin and rhodes modulo ash's solution to the pointlike conjecture, that every finite block group divides a power group, has long been considered to be one of the deepest results in finite semigroup and algebraic automata theory. however, the proof is not constructive. solving a long-standing problem, we provide in this paper an explicit construction of such a division. we also generalize the result to a large class of pseudovariefies of groups. local group pseudovarieties are also considered, generalizing (and making constructive) results of margolis and the second author. some applications to language theory are mentioned.
sparse and limited wavelength conversion in all-optical tree networks. we study the problem of assigning a minimum number of colors to directed paths (dipaths) if a tree, so that any two dipaths that share a directed edge of the tree are not assigned the same color. the problem has applications to wavelength routing in wdm all-optical tree networks, an important engineering problem. dipaths represent communication requests, while colors correspond to wavelengths that must be assigned to requests so that multiple users can communicate simultaneously through the same optical fiber. recent work on wavelength routing in trees has studied a special class of algorithms which are called greedy. although these algorithms are simple and implementable in a distributed setting, it has been proved that there are cases where a bandwidth utilization of 100% is not possible. thus, in this work, we relax the constraints of the original engineering problem and use devices called wavelength converters that are able to convert the wavelength assigned to a segment of a communication request to another wavelength that will be assigned to some other segment of the same request. the trade-off of the use of wavelength converters is increased cost and complexity; so, our aim is to use converters that have relatively simple functionality. we study the performance of greedy deterministic algorithms in tree-shaped all-optical networks that support wavelength conversion. we study both the case of sparse conversion and limited conversion. by sparse we mean that converters have full conversion capabilities and the objective is to minimize the number of converters employed. on the other hand, in limited conversion, we assume that converters with limited conversion capabilities are placed at each non-leaf node of the tree. by limited, we mean that converters are simple according to either their wavelength degree or their size. our results show that using converters of either low degree or small size, we can beat the known lower bounds and improve bandwidth utilization. in some cases we even achieve optimal bandwidth utilization. for the construction of the converters, we use special classes of graphs such as expanders, dispersers and depth-two superconcentrators. explicit constructions are known for most of the graphs used in this paper. copyright 2001 elsevier science b.v.
randomized path coloring on binary trees. motivated by the problem of wdm routing in all-optical networks, we study the following np-hard problem. we are given a directed binary tree t and a set r of directed paths on t. we wish to assign colors to paths of r, in such way that no two paths that share a directed arc of t are assigned the same color, and the total number of colors used is minimized. our results are expressed in terms of the depth of the tree and of the maximum load l of r, i.e. the maximum number of paths that go through a directed arc of t. so far, only deterministic greedy algorithms have been presented for the problem. the best known algorithm colors any set r of maximum load l using at most 5l/3 colors. alternatively, we say that this algorithm has performance ratio 5/3. it is also known that no deterministic greedy algorithm can achieve a performance ratio better than 5/3. in this paper we define the class of greedy algorithms that use randomization. we study their limitations and prove that, with high probability, randomized greedy algorithms cannot achieve a performance ratio better than 3/2 when applied for binary trees of depth ω(l), and 1.293-o(1) when applied for binary trees of constant depth. exploiting inherent properties of randomized greedy algorithms, we obtain the first randomized algorithm for the problem that uses at most 7l/5 + o(l) colors for coloring any set of paths of maximum load l on binary trees of depth o(l1/3-ε), with high probability. we also present an existential upper bound of 7l/5 + o(l) that holds on any binary tree. for the analysis of our bounds we develop tail inequalities for random variables following hypergeometrical probability distributions that might be of their own interest.
clock construction in fully asynchronous parallel systems and pram simulation. the authors discuss the question of simulating synchronous computations on asynchronous systems. they consider an asynchronous system with very weak, or altogether lacking any, atomicity assumptions. the first contribution of this paper is a novel clock for asynchronous systems. the clock is a basic tool for synchronization in the asynchronous environment. it is a very robust construction and can operate in a system with no atomicity assumptions, and in the presence of a dynamic scheduler. the behavior of the clock is obtained with overwhelming probability (1-2/sup - alpha n/, alpha >0). the authors show how to harness this clock to drive a pram simulation on an asynchronous system. the resulting simulation scheme is more efficient than existing ones, while actually relaxing the assumptions on the underlying asynchronous system.
approximating uniform triangular meshes in polygons. we consider the problem of triangulating a convex polygon using n steiner points under the following optimality criteria: (1) minimizing the overall edge length ratio; (2) minimizing the maximum edge length; and (3) minimizing the maximum triangle perimeter. we establish a relation of these problems to a certain extreme packing problem. based on this relationship, we develop a heuristic producing constant approximations for all the optimality criteria above (provided n is chosen sufficiently large). that is, the produced triangular mesh is uniform in these respects.the method is easy to implement and runs in o(n2log n) time and o(n) space. the observed runtime is much less. moreover, for criterion (1) the method works--within the same complexity and approximation bounds--for arbitrary polygons with possible holes, and for criteria (2) and (3) it does so for a large subclass.
a structural property of regular frequency computations. the notion of an (m,n)-computation was already introduced in 1960 by rose and further investigated by trakhtenbrot in 1963. it has been extended to finite automata by kinber in 1976 and he has shown an analogue of trakhtenbrot's result: the class of languages (m,n)-recognizable by deterministic finite automata is equal to the class of regular languages if and only if 2m > n. furthermore, for a unary alphabet, the class of (m,n)-recognizable languages coincides with the class of regular languages for all m and n. in this paper, we will present the first structural property of (m,n)-recognizable languages which is valid for all 1 ≤ m ≤ n and for all alphabets. kinber's result for unary alphabets becomes a corollary. this property is also used to show that certain non-unary languages are not (m,n)-regular and that the class of all (m,n)-recognizable languages is not closed under the reversal operation. however, this class forms a boolean algebra.
regular frequency computations. an (m, n)-computation of a function f is given by a deterministic turing machine which on n pairwise different inputs produces n output values where at least m of the n values are in accordance with f. in such a case, we say that the turing machine computes f with frequency ≥ m/n. the most prominent result for frequency computations is due to trakhtenbrot: the class of (m, n)-computable functions equals the class of computable functions if and only if 2m > n.via characteristic functions the definition of (m, n)-computability carries over to sets. here trakhtenbrot's result reads as: the class of (m, n)-computable sets equals the class of recursive sets if and only if 2m > n.the notion of frequency computation can be extended to other models of computation. for resource bounded computations, the behavior is completely different: for e.g., whenever n' - m' > n - m, it is known that under any reasonable resource bound there are sets (m', n')-computable, but not (m, n)- computable.however, scaling down to finite automata, the analogue of trakhtenbrot's result holds again: we show here that the class of languages (m, n)-recognizable by deterministic finite automata equals the class of regular languages if and only if 2m > n. this was originally stated by kinber, but his proof has a flaw, as pointed out by tantau.conversely, for 2m ≤ n, the class of languages (m, n)-recognizable by deterministic finite automata is uncountable for a two-letter alphabet. when restricted to a one-letter alphabet, then every (m, n)- recognizable language is regular. this was also shown by kinber. we give a new and more direct proof for this result.
on-line generalized steiner problem. the generalized steiner problem (gsp) is defined as follows. we are given a graph with non-negative edge weights and a set of pairs of vertices. the algorithm has to construct minimum weight subgraph such that the two nodes of each pair are connected by a path.off-line gsp approximation algorithms were given in agarwal et al. (siam j. comput. 24(3) (1995) 440) and goemans and williamson (siam j. comput. 24(2) (1995) 296). we consider the on-line gsp, in which pairs of vertices arrive on-line and are needed to be connected immediately.we show that the online min-cost (i.e. greedy) strategy for this problem has o(log2 n) competitive ratio. the previous best algorithm was o(√nlog n) competitive (workshop on algorithms and data structures, 1993, pp. 622-633). following this work a different (non-greedy) algorithm has been shown to achieve an o(log n) competitive ratio (proceedings of the 29th acm symposium on theory of computing, 1997, pp. 344-353).we also consider the network connectivity leasing problem which is a generalization of the gsp. here, edges of the graph can be either bought or leased for different costs. we provide simple randomized algorithm based on on-line generalized steiner algorithms whose competitive ratio is within a constant factor of the best competitive algorithm for the on-line gsp.
tradeoffs in worst-case equilibria. we investigate the problem of routing traffic through a congested network in an environment of non-cooperative users. we use the worst-case coordination ratio suggested by koutsoupias and papadimitriou to measure the performance degradation due to the lack of a centralized traffic regulating authority. we provide a full characterization of the worst-case coordination ratio in the restricted assignment and unrelated parallel links model. in particular, we quantify the tradeoff between the "negligibility" of the traffic controlled by each user and the worst-case coordination ratio. we analyze both pure and mixed strategies systems and identify the range where their performance is similar.
weak lighting functions and strong 26-surfaces. the goal of this paper is to introduce the notion of weak lighting function in order to replicate the "continuous perception" associated with strong 26-surfaces. as a consequence, the continuous analogue defined ad hoc by malgouyres and bertrand only for these surfaces is extended for arbitrary objects, and the local characterization of finite strong 26-surfaces given in (malgouyres and bertrand, int. j. pattern recognition art. intell. 13(4) (1999) 465-484) is generalized to possibly infinite surfaces. moreover, weak lighting functions also replicate the "continuous perception" associated with (,)-surfaces, (,)(6,6), since they are generalizing the lighting functions previously defined by the authors.
decision procedures for inductive boolean functions based on alternating automata. we show how alternating automata provide decision procedures for the equality of inductively defined boolean functions and present applications to reasoning about parameterized families of circuits. we use alternating word automata to formalize families of linearly structured circuits and alternating tree automata to formalize families of tree structured circuits. we provide complexity bounds for deciding the equality of function (or circuit) families and show how our decision procedures can be implemented using bdds. in comparison to previous work, our approach is simpler, has better complexity bounds, and, in the case of tree-structured families, is more general.
on-line load balancing. the setup for the authors' problem consists of n servers that must complete a set of tasks. each task can be handled only by a subset of the servers, requires a different level of service, and once assigned can not be re-assigned. they make the natural assumption that the level of service is known at arrival time, but that the duration of service is not. the on-line load balancing problem is to assign each task to an appropriate server in such a way that the maximum load on the servers is minimized. the authors derive matching upper and lower bounds for the competitive ratio of the on-line greedy algorithm for this problem, namely /sup (3n)2/3///sub 2/(1+o(1)), and derive a lower bound, omega ( square root n), for any other deterministic or randomized on-line algorithm.
load balancing of temporary tasks in the norm. we consider the on-line load balancing problem where there are m identical machines (servers). jobs arrive at arbitrary times, where each job has a weight and a duration. a job has to be assigned upon its arrival to exactly one of the machines. the duration of each job becomes known only upon its termination (this is called temporary tasks of unknown durations). once a job has been assigned to a machine it cannot be reassigned to another machine. the goal is to minimize the maximum over time of the sum (over all machines) of the squares of the loads, instead of the traditional maximum load.minimizing the sum of the squares is equivalent to minimizing the load vector with respect to the l2 norm. we show that for the l2 norm the greedy algorithm performs within at most 1.493 of the optimum. we show (an asymptotic) lower bound of 1.33 on the competitive ratio of the greedy algorithm. we also show a lower bound of 1.20 on the competitive ratio of any algorithm.we extend our techniques and analyze the competitive ratio of the greedy algorithm with respect to the lp norm. we show that the greedy algorithm performs within at most 2 - ω(1/p) of the optimum. we also show a lower bound of 2 - o(in p/p) on the competitive ratio of any on-line algorithm.
an improved algorithm for online coloring of intervals with bandwidth. we present an improved online algorithm for coloring interval graphs with bandwidth. this problem has recently been studied by adamy and erlebach and a 195-competitive online strategy has been presented. we improve this by presenting a 10-competitive strategy. to achieve this result, we use variants of an optimal online coloring algorithm due to kierstead and trotter.
on-line bin-stretching. we are given a sequence of items that can be packed into m unit size bins. in the classical bin packing problem we fix the size of the bins and try to pack the items in the minimum number of such bins. in contrast, in the bin-stretching problem we fix the number of bins and try to pack the items while stretching the size of the bins as least as possible. we present two on-line algorithms for the bin-stretching problem that guarantee a stretching factor of 5/3 for any number m of bins. we then combine the two algorithms and design an algorithm whose stretching factor is 1:625 for any m. the analysis for the performance of this algorithm is tight. the best lower bound for any algorithm is 4/3 for any m&ge;2. we note that the bin-stretching problem is also equivalent to the classical scheduling (load balancing) problem in which the value of the makespan (maximum load) is known in advance. copyright 2001 elsevier science b.v.
off-line temporary tasks assignment. in this paper we consider the temporary tasks assignment problem. in this problem, there are m parallel machines and n independent jobs. each job has an arrival time, a departure time and some weight. each job should be assigned to one machine. the load on a machine at a certain time is the sum of the weights of jobs assigned to it at that time. the objective is to find an assignment that minimizes the maximum load over machines and time.we present a polynomial time approximation scheme for the case in which the number of machines is fixed. we also show that for the case in which the number of machines is given as part of the input (i.e., not fixed), no polynomial algorithm can achieve a better approximation ratio than 3/2 unless p = np.
one query reducibilities between partial information classes. a partial information algorithm for a language a computes for m input words (x1,..., xm) a set of bitstrings containing χa(x1,..., xm). for a family d of sets of bitstrings of length m, a ∈ p[d] if there is a polynomial time partial information algorithm that always outputs a set from d. for the case m = 2 we investigate whether for families d1 and d2 the languages in p[d1] are reducible to languages in px[d2] for some x in the polynomial hierarchy ph or in exp. several nonreducibilities follow from known structural properties of classes p[d]. beigel et al. [membership comparable and p-selective sets, technical report 2002-006n, nec research institute, 2002] showed nonreducibility from strongly 2-membership comparable languages to p-selective languages. they also showed one query (1-tt, for short) reducibility from 2-cheatable languages to p-selective languages. a proof of tantau [combinatorial representations of partial information classes and their truth-table closures, master's thesis, tu berlin, germany, 1999] yields a 1-tt reducibility from 2-cheatable languages to languages in pς2p[min2]. we achieve results for all remaining non-trivial pairs of classes p[d] for m = 2. our positive results all show 1-tt reducibilities. our negative results even hold if the reducing machines as well as the partial information algorithms for the languages we try to reduce to have access to oracles in exp. we show: 1. the 2-cheatable languages are 1-tt δ2p-reducible to languages in δ2p[min2]. 2. languages in p[sel2 ∪ {xor2}] are 1-tt δ2p-reducible to δ2p-selective languages. 3. the easily 2-countable languages are 1-tt δ3p-reducible to δ3p-strongly-2-membership-comparable languages. 4. the 2-membership comparable languages are 1-tt e-reducible to e-strongly-2-membership-comparable languages. 5. there are easily 2-countable languages which are not turing exp-reducible to languages in exp[bottom2]. 6. there are languages in p[bottom2] which are not 1-tt exp-reducible to exp-selective languages.
compositional analysis of contract-signing protocols. we develop a general method for proving properties of contract-signing protocols using a specialized protocol logic. the method is applied to the asokan-shoup--waidner and the garay-jacobson-mackenzie protocols. our method offers certain advantages over previous analysis techniques. first, it is compositional: the security guarantees are proved by combining the independent proofs for the three subprotocols of each protocol. second, the formal proofs are carried out in a "template" form, which gives us a reusable proof that may he instantiated for the two example protocols, as well as for other protocols with the same arrangement of messages. third, the proofs follow the design intuition. in particular, in proving game-theoretic properties like fairness, we demonstrate success for the specific strategy that the protocol designer had in mind, instead of non-constructively proving that a strategy exists. finally, our logical proofs demonstrate security when an unbounded number of sessions are executed in parallel.
a brief history of process algebra. this note addresses the history of process algebra as an area of research in concurrency theory, the theory of parallel and distributed systems in computer science. origins are traced back to the early seventies of the twentieth century, and developments since that time are sketched. the author gives his personal views on these matters. he also considers the present situation, and states some challenges for the future.
fringe analysis of synchronized parallel insertion algorithms in 2-3 trees. fringe analysis uses the distribution of bottom subtrees or fringe of search trees under the assumption of random insertion of keys, yielding an average case analysis of the fringe. the results in the fringe give upper and lower bounds for several measures for the whole tree.we are interested in the fringe analysis of the synchronized parallel insertion algorithms of paul, vishkin, and wagener (pvw) on 2-3 trees. this algorithm inserts k keys with k processors into a tree of size n with time o(log n + log k). as the direct analysis of this algorithm is very difficult we tackle this problem by introducing a new family of algorithms, denoted by macrosplit algorithms, and our main theorem proves that two algorithms of this family, denoted maxmacrosplit and minmacrosplit, bound the behavior of the fringe in the pvw algorithm.previous work deals with the fringe analysis of sequential algorithms, but this type of analysis was still an open problem for parallel algorithms on search trees. we extend fringe analysis to parallel algorithms and we get a rich mathematical structure giving new interpretations even in the sequential case. we prove that random insertion of keys generates a binomial distribution, that the synchronized insertion of keys can be modeled by a markov chain, and that the coefficients of the transition matrix of the markov chain are related to the expected local behavior of our algorithm. finally, we show that the coefficients of the power expansion of this matrix over (n + 1)-1 are the binomial transform of the expected local behavior of the algorithm. we finally show that the fringe of the pvw algorithm asymptotically converges to the sequential case.
polynomial and apx-hard cases of the individual haplotyping problem. snp haplotyping problems have been the subject of extensive research in the last few years, and are one of the hottest areas of computational biology today. in this paper we report on our work of the last two years, whose preliminary results were presented at the european symposium on algorithms (proceedings of the annual european symposium on algorithms (esa), vol. 2161. lecture notes in computer science, springer, 2001, pp. 182-193.) and workshop on algorithms in bioinformatics (proceedings of the annual workshop on algorithms in bioinformatics (wabi), vol. 2452. lecture notes in computer science, springer, 2002, pp. 29-43.). we address the problem of reconstructing two haplotypes for an individual from fragment assembly data. this problem will be called the single individual haplotyping problem. on the positive side, we prove that the problem can be solved effectively for gapless data, and give practical, dynamic programming algorithms for its solution. on the negative side, we show that it is unlikely that polynomial algorithms exist, even to approximate the solution arbitrarily well, when the data contain gaps. we remark that both the gapless and gapped data arise in different real-life applications.
short length menger's theorem and reliable optical routing. in the minimun path coloring problem, we are given a graph and a set of pairs of vertices of the graph and we are asked to connect the pairs by colored paths in such a way that paths of the same color are edge disjoint. in this paper we deal with a generalization of this problem where we are asked to connect each pail by k edge disjoint paths of the same color. the objective is to minimize the number of colors. the reason for multiple paths between the same pair of vertices is to ensure fault tolerance of the connections. we propose an o(k2f) = o(k2δα-1 log n) approximation algorithm for this problem where f is the flow number of the graph, δ is the maximum degree and α is the expansion. this is an improvement even for the special case k = 1 where, to our knowledge, the best previously known bound is weaker by a factor of log n.the underlying problem is that of finding several disjoint paths between a given pair of vertices. menger's theorem provides a necessary and sufficient condition for the existence of k such paths. however, it does not say anything about the length of the paths although in communication problems the number of links used is an issue. we show that any two k-connected vertices are connected by k edge disjoint paths of average length o(kf) which improves an earlier result of galil and yu (proceedings of the 27th annual acm symposium on theory of computing, 1995) for several classes of graphs. in fact, this is only a corollary of a stronger result for multicommodity flow on networks with unit edge capacities: any multicommodity flow with k units for each commodity can be rerouted such that the flow for each commodity is shipped through k-tuples of edge disjoint paths of average length o(kf) without exceeding the edge capacities significantly.
set-sharing is redundant for pair-sharing. although the usual goal of sharing analysis is to detect which pairs of variables share, the standard choice for sharing analysis is a domain that characterizes set-sharing. in this paper, we question, apparently for the first time, whether this domain is over-complex for pair-sharing analysis. we show that the answer is yes. by defining an equivalence relation over the set-sharing domain we obtain a simpler domain, reducing the complexity of the abstract unification procedure. we present experimental results showing that, in practice, our domain compares favorably with the set-sharing one over a wide range of benchmark and real programs. copyright 2002 elsevier science b.v.
inverse eigenproblem for centrosymmetric and centroskew matrices and their approximation. in this paper, we first give the solvability condition for the following inverse eigenproblem (iep): given a set of vectors {xi}i=1m in cn and a set of complex numbers {λi}i=1m, find a centrosymmetric or centroskew matrix c in rn × n such that {xi}i-1m and {λi}i-1m are the eigenvectors and eigenvalues of c, respectively. we then consider the best approximation problem for the ieps that are solvable. more precisely, given an arbitrary matrix b in rn × n, we find the matrix c which is the solution to the iep and is closest to b in the frobenius norm. we show that the best approximation is unique and derive an expression for it.
efficient computation of time-bounded reachability probabilities in uniform continuous-time markov decision processes. a continuous-time markov decision process (ctmdp) is a generalization of a continuous-time markov chain in which both probabilistic and nondeterministic choices co-exist. this paper presents an efficient algorithm to compute the maximum (or minimum) probability to reach a set of goal states within a given time bound in a uniform ctmdp, i.e., a ctmdp in which the delay time distribution per state visit is the same for all states. it furthermore proves that these probabilities coincide for (time-abstract) history-dependent and markovian schedulers that resolve nondeterminism either deterministically or in a randomized way.
on the decidability of the termination problem of active database systems. active database systems enhance the functionality of traditional databases through the use of active rules or 'triggers'. one of the principal analysis questions for such systems is that of termination--is it possible for the rules to recursively activate one another indefinitely, given an initial triggering event. in this paper, we study the decidability of the termination problem, our aim being to delimit the boundary between the decidable and the undecidable. we present results for two broad types of variations, variations in rule syntax and variations in meta level features. within each of these, we identify members close to the boundary of (un)decidability and also look at the effect of combining members of each type. the maximal decidable class we present is capable of expressing some useful kinds of application requirements, such as checking and repairing inclusion constraints. the work is also interesting from a theoretical point of view, since the context is similar to the while query language and the dynamics gives an interesting contrast to datalog with negation.
stratified coherence spaces: a denotational semantics for light linear logic. light linear logic (lll) was introduced by girard as a logical system capturing the class of polytime functions within the proofs-as-programs approach. in the present paper, we undertake a semantical analysis of lll: a variant of coherence spaces is introduced and we prove that it is a sound model for this system, but not for usual linear logic. a simpler version of the model yields a sound semantics of elementary linear logic, which is the analog of lll for the class of kalmar elementary functions. we illustrate our semantical method by showing how various principles fail in these models.
component composition preserving behavioral contracts based on communication traces. this paper investigates the compositional properties of reusable software components defined with explicit dependencies and behavioural contracts expressing rely-guarantee specifications in the form of communication traces. in this setting, connection of components through their matching ports is indeed compositional and yields a new component or composite that respects its constituents' contracts. thus the behaviour of the composite is computed from the behaviours of its constituents and is known to conform to the contracts without any new proof.
normalization, approximation, and semantics for combinator systems. this paper studies normalization of typeable terms and the relation between approximation semantics and filter models for combinator systems. it presents notions of approximants for terms, intersection type assignment, and reduction on type derivations; the last will be proved to be strongly normalizable. with this result, it is proved that every typeable term has an approximant with the same type, and a characterization of the normalization behaviour of terms using their assignable types is given. then the two semantics are defined and compared, and it is shown that the approximants semantics is fully abstract but the filter semantics is not.
the consistency dimension and distribution-dependent learning from queries. we prove a new combinatorial characterization of polynomial learnability from equivalence queries, and state some of its consequences relating the learnability of a class with the learnability via equivalence and membership queries of its subclasses obtained by restricting the instance space. then we propose and study two models of query learning in which there is a probability distribution on the instance space, both as an application of the tools developed from the combinatorial characterization and as models of independent interest.
domain and event structure semantics for petri nets with read and inhibitor arcs. we propose a functorial concurrent semantics for petri nets extended with read and inhibitor arcs, that we call inhibitor nets. along the lines of the seminal work by winskel on safe (ordinary) nets, the truly concurrent semantics is given at a categorical level via a chain of coreflections leading from the category sw-in of semi-weighted inhibitor nets to the category dom of finitary prime algebraic domains (equivalent to the category pes of prime event structures). as an intermediate semantic model, we introduce inhibitor event structures, an event-based model able to faithfully capture the dependencies among events which arise in the presence of read and inhibitor arcs. inhibitor event structures generalise several event structure models in the literature, like prime, asymmetric and bundle event structures.
an improvement of the construction of the d.v. and g.v. chudnovsky algorithm for multiplication in finite fields. from an interpolation method on algebraic curves, due to d.v. chudnovsky and g.v. chudnovsky, we give a new method for the construction of bilinear algorithms for multiplication in the extensions of finite fields. we obtain algorithms better than known ones.
private computation using a pez dispenser. we show how a (big) pez dispenser can be used by two or more players to compute a function of their inputs while hiding the values of the inputs from each other. in contrast to traditional approaches for solving this problem, ours does not require any use of randomness.
on the edge-bandwidth of graph products. the edge-bandwidth of a graph g is the bandwidth of the line graph of g. we show asymptotically tight bounds on the edge-bandwidth of two-dimensional grids and tori, the product of two cliques and the n-dimensional hypercube.
an approximation algorithm for the precedence constrained scheduling problem with hierarchical communications. we study the problem of minimizing the makespan for the precedence multiprocessor constrained scheduling problem with hierarchical communications (parallel process. lett. 10(1) (2000) 133). we propose an 8/5-approximation algorithm for the unit communication time hierarchical problem with arbitrary but integer processing times and an unbounded number of biprocessor machines. we extend this result in the case where each cluster has m processors (where m is a fixed constant) by presenting a (2 - 2/(2m + 1))-approximation algorithm.
basic analytic combinatorics of directed lattice paths. this paper develops a unified enumerative and asymptotic theory of directed two-dimensional lattice paths in half-planes and quarter-planes. the lattice paths are specified by a finite set of rules that are both time and space homogeneous, and have a privileged direction of increase. (they are then essentially one-dimensional objects.) the theory relies on a specific "kernel method" that provides an important decomposition of the algebraic generating functions involved, as well as on a generic study of singularities of an associated algebraic curve. consequences are precise computable estimates for the number of lattice paths of a given length under various constraints (bridges, excursions, meanders) as well as a characterization of the limit laws associated to several basic parameters of paths.
a geometric interpretation of ld-resolution. we devise an interpretation of a binarised definite logic program in a geometric framework which is closer to dynamical systems than to logic. the building blocks of our framework are a family of affine sub-modules in a free finitely generated module over a special kind of ring. we describe sld-resolution of definite binary programs as the iterated action of a finite union of affine graphs, associated to the program clauses, on a certain set of affine varieties associated to the original syntactic terms. this action is shown to faithfully represent the running of the corresponding program on a given goal, since all answers and only those answers the program would output are obtained. hence, a programming language such as pure prolog completely falls within our description.
rearrangeability of bit permutation networks. in this paper, we introduce the concept of routing grid as a tool for analyzing realizability of permutations on bit permutation networks (bpns). we extend a result by linial and tarsi which characterizes permutations realizable on shuffle-exchange networks to any bpns. a necessary condition for a bpn to he rearrangeable is given, and the rearrangeability of two families of bpns are explored. finally, we present a method which may help to tackle one kind of balanced matrix problems whose solution implies an answer to benes conjecture. hopefully, our treatment brings some new insight into the problem of permutation routing.
on unique graph 3-colorability and parsimonious reductions in the plane. we prove that the satisfiability (resp. planar satisfiability) problem is parsimoniously p-time reducible to the 3-colorability (resp. planar 3-colorability) problem, that means that the exact number of solutions is preserved by the reduction, provided that 3-colorings are counted modulo their six trivial color permutations. in particular, the uniqueness of solutions is preserved, which implies that unique 3-colorability is exactly as hard as unique satisfiability in the general case as well as in the planar case. a consequence of our result is the dp-completeness of unique 3-colorability and unique planar 3-colorability under random p-time reductions. it also gives a finer and unified proof of the #p-completeness of #3-colorability that was first obtained by linial for the general case, and later by hunt et al. for the planar case. previous authors' reductions were either weakly parsimonious with a multiplication of the numbers of solutions by an exponential factor, or involved #p-complete intermediate counting problems derived from trivial "yes"-decision problems.
a full continuous model of polymorphism. we introduce a model of the second-order lambda calculus. such a model is a scott domain whose elements are themselves scott domains, and in it polymorphic maps are interpreted by generic continous maps.
symmetries of decimation invariant sequences and digit sets. a bi-infinite sequence is called p-decimation invariant if all p-decimations of it reproduce the sequence albeit with a shift. in this paper we discuss symmetry properties of decimation invariant sequences. a symmetry is a composition of a translation and a reflection. we establish the existence of translation invariant, i.e., periodic, decimation invariant sequences. moreover, we prove that there exist decimation invariant sequences which are left-periodic and right-periodic, i.e., they are partially translation invariant. we present several criteria for the existence of decimation invariant sequences with additional periodicity properties. finally, we discuss the existence of decimation invariant sequences that are invariant under reflections. moreover, in passing we demonstrate that properties of decimation invariant sequences are linked with properties of certain digit sets.
the pascal matroid as a home for generating sets of cellular automata configurations defined by quasigroups. consider a one-dimensional ca whose local evolution rule is defined by a quasigroup (g,*). when the initial state is only known over a finite string of adjacent cells, the ca's orbit (state-time diagram) is only defined on a triangular array of cells. this well-defined triangular part of the orbit, in which each cell has a value in g, is called a (g,*)-configuration. a generating set is a subset of the triangular array such that any attribution of g-values to the cells of this subset determines a unique (g,*)-configuration. it turns out that the collection of all potential generating sets form a particular matroid, which we have called the pascal matroid. the main subject of this work is related to the question whether every base of this matroid actually occurs as a generating set for a (g,*)-configuration.
averages of automatic sequences. we give some sufficient criteria for the existence of certain averages (mean, correlation functions) of generalized higher-dimensional automatic sequences and show how to calculate these averages. then follows an exploration of the nature of necessary and sufficient conditions for the existence of averages. some of these criteria are applied to averages which play a central role in the determination of the correlation function of an automatic sequence.
transposing partial components - an exercise on coalgebraic refinement. a partial component is a process which fails or dies at some stage, thus exhibiting a finite, more ephemeral behaviour man expected. partiality--which is the rule rather than exception in formal modelling--can be treated mathematically via totalization techniques. in the case of partial functions, totalization involves error values and exceptions.in the context of a coalgebraic approach to component semantics, this paper argues that the behavioural counterpart to such functional techniques should extend behaviour with try-again cycles preventing from component collapse, thus extending totalization or transposition from the algebraic to the coalgebraic context.we show that a refinement relationship holds between original and totalized components which is reasoned about in a coalgebraic approach to component refinement expressed in the pointfree binary relation calculus.as part of the pragmatic aims of this research, we also address the factorization of every such totalized coalgebra into two coalgebraic components--the original one and an added front-end--which cooperate in a client-server style.
asymptotic orbits of primitive substitutions. a primitive, aperiodic substitution on d letters has at most d2 asymptotic orbits; this bound is sharp. since asymptotic arc components in tiling spaces associated with substitutions are in 1-1 correspondence with asymptotic words, this provides a bound for those as well.
minimal change list for lucas strings and some graph theoretic consequences. we give a minimal change list for the set of order p length-n lucas strings, i.e., the set of length-n binary strings with no p consecutive 1's nor a 1l prefix and a 1m suffix with l+m ≥ p. the construction of this list proves also that the order p n-dimensional lucas cube has a hamiltonian path if and only if n is not a multiple of p + 1, and its second power always has a hamiltonian path.
reachability problems for sequential dynamical systems with threshold functions. a sequential dynamical system (sds) over a domain d is a triple (g, f, π), where (i) g(v,e) is an undirected graph with n nodes with each node having a state value from d, (ii) f = {f1, f2,..., fn} is a set of local transition functions with fi denoting the local transition function associated with node vi and (iii) π is a permutation of (i.e., a total order on) the nodes in v. a single sds transition is obtained by updating the states of the nodes in v by evaluating the function associated with each of them in the order given by π.we consider reachability problems for sdss with restricted local transition functions. our main intractability results show that the reachability problems for sdss are pspace-complete when either of the following restrictions hold: (i) f consists of both simple-threshold-functions and simple-inverted-threshold functions, or (ii) f consists only of threshold-functions that use weights in an asymmetric manner. moreover, the results hold even for sdss whose underlying graphs have bounded node degree and bounded pathwidth. our lower bound results also extend to reachability problems for hopfield networks and communicating finite state machines.on the positive side, we show that when f consists only of threshold functions that use weights in a symmetric manner, reachability problems can be solved efficiently provided all the weights are strictly positive and the ratio of the largest to the smallest weight is bounded by a polynomial function of the number of nodes.
gossiping in chordal rings under the line model. this paper is devoted to the gossip (or all-to-all) problem in the chordal ring under the one-port line model. the line model assumes long distance calls between non-neighboring processors. in this sense, the line model is strongly related to circuit-switched networks, wormhole routing, optical networks supporting wavelength division multiplexing, atm switching, and networks supporting connected mode routing protocols. since the chordal rings are competitors of networks as meshes or tori because of their short diameter and bounded degree, it is of interest to ask whether they can support intensive communications (typically all-to-all) as efficiently as these networks. we propose polynomial algorithms to derive optimal or near-optimal gossip protocols in the chordal ring.
on page migration and other relaxed task systems. this paper is concerned with the page migration (or file migration) problem (black and sleator, technical report cmu-cs-89-201, department of computer science, carnegie-mellon university, 1989) as part of a large class of on-line problems. the page migration problem deals with the management of pages residing in a network of processors. in the classical problem there is only one copy of each page which is accessed by different processors over time. the page is allowed to be migrated between processors. however a migration incurs higher communication cost than an access (proportionally to the page size). the problem is that of deciding when and where to migrate the page in order to lower access costs. a more general setting is the k-page migration problem where we wish to maintain k copies of the page. the page migration problems are concerned with a dilemma common to many on-line problems: determining when it is beneficial to make configuration changes. we deal with the relaxed task systems model which captures a large class of problems of this type, that can be described as the generalization of some original task system problem (borodin et al., j. acm 39(4) (1992) 745-763). given a c-competitive algorithm for a task system we show how to obtain a deterministic o(c2) and randomized o(c) competitive algorithms for the corresponding relaxed task system. the result implies deterministic algorithms for k-page migration by using k-server (manasse et al., j. algorithms 11(2) (1990) 208-230) algorithms, and for network leasing by using generalized steiner tree algorithms (awerbuch et al., proc 7th ann. acm-siam symp. on discrete algorithms, january 1996, pp. 68-74), as well as providing solutions for natural generalizations of other problems (e.g. storage rearrangement (fiat et al., proc. 36th ann. ieee symp. on foundations of computer science, october 1995, pp. 392-403)). we further study some special cases of the k-page migration problem and get optimal deterministic algorithms. for the classical page migration problem we present a deterministic algorithm that achieves a competitive ratio of ~ 4:086, improving upon the previously best competitive ratio of 7 (awerbuch et al., proc. 25th acm symp. on theory of computing, may 1993, pp. 164-173). (the current lower bound on the problem is ~ 3:148 (chrobak et al., j. algorithms 24(1) (1997) 124-157). copyright 2001 elsevier science b.v.
on the competitive ratio of the work function algorithm for the k-server problem. the k-server problem is one of the most fundamental online problems. the problem is to schedule k mobile servers to visit a sequence of points in a metric space with minimum total mileage. the k-server conjecture of manasse, mcgeogh, and sleator states that there exists a k-competitive online algorithm. the conjecture has been open for over 15 years. the top candidate online algorithm for settling this conjecture is the work function algorithm (wfa) which was shown to have competitive ratio at most 2k - 1. in this paper, we lend support to the conjecture that wfa is in fact k-competitive by proving that it achieves this ratio in several special metric spaces: the line, the star, and all metric spaces with k + 2 points.
a hierarchy of probabilistic system types. we arrange various classes of probabilistic systems studied in the literature in an expressiveness hierarchy. our expressiveness criterion is the existence of a system translation, from the less expressive type into the more expressive type, that preserves and reflects probabilistic bisimilarity. we model the different system types as coalgebras of suitable behaviour functors and argue that the corresponding coalgebraic bisimilarity coincides with probabilistic bisimilarity for the classes for which the latter notion has been proposed in the literature. the theory of coalgebras provides a unified framework for the presentation of the different classes and the system translations we needed to establish the hierarchy. all these translations arise in a standard way from natural transformations between the two behaviour functors involved. such a translation generally preserves coalgebraic bisimilarity. we exploit a new result that, under mild assumptions on the behaviour functors, a system translation induced by a natural transformation with injective components also reflects bisimilarity.
structuring the elementary components of graphs having a perfect internal matching. graphs with perfect internal matchings are decomposed into elementary components, and these components are given a structure reflecting the order in which they can be reached by external alternating paths. it is shown that the set of elementary components can be grouped into pairwise disjoint families determined by the "two-way accessible" relationship among them. a family free is established by which every family member, except the root, has a unique father and mother identified as another elementary component and one of its canonical classes, from which the given member is two-way accessible. it is proved that every member of the family is only accessible through a distinguished canonical class of the root by external alternating paths. the families themselves are arranged in a partial order according to the order they can be covered by external alternating paths, and a complete characterization of the graph's forbidden and impervious edges is elaborated.
an induction principle for pure type systems. we present an induction principle for pure type systems and use that principle to define cps translations and to solve the problem of expansion postponement for a large class of pure type systems. our principle strengthens and generalises similar principles by dowek et al. [12] and barthe et al. [6], which have been respectively used to define &eegr;-long normal forms and cps translations for the systems of barendregt's λ-cube [2; 3]. copyright 2001 elsevier science b.v.
hardness results for neural network approximation problems. we consider the problem of efficiently learning in two-layer neural networks. we investigate the computational complexity of agnostically learning with simple families of neural networks as the hypothesis classes. we show that it is np-hard to find a linear threshold network of a fixed size that approximately minimizes the proportion of misclassified examples in a training set, even if there is a network that correctly classifies all of the training examples. in particular, for a training set that is correctly classified by some two-layer linear threshold network with k hidden units, it is np-hard to find such a network that makes mistakes on a proportion smaller than c/k2 of the examples, for some constant c. we prove a similar result for the problem of approximately minimizing the quadratic loss of a two-layer network with a sigmoid output unit.
prime normal form and equivalence of simple grammars. a prefix-free language is prime if it cannot be decomposed into a concatenation of two prefix-free languages. we show that we can check in polynomial time if a language generated by a simple context-free grammar is prime. our algorithm computes a canonical representation of a simple language, converting its arbitrary simple grammar into prime normal form (pnf); a simple grammar is in pnf if all its nonterminals define primes. we also improve the complexity of testing the equivalence of simple grammars. the best previously known algorithm for this problem worked in o(n13) time. we improve it to o(n7 log2 n) and o(n5 polylog v) time, where n is the total size of the grammars involved, and v is the length of a shortest string derivable from a nonterminal, maximized over all nonterminals.
compositional analysis for verification of parameterized systems. many safety-critical systems that have been considered by the verification community are parameterized by the number of concurrent components in the system, and hence describe an infinite family of systems. traditional model checking techniques can only be used to verify specific instances of this family. in this paper, we present a technique based on compositional model checking and program analysis for automatic verification of infinite families of systems. the technique views a parameterized system as an expression in a process algebra (ccs) and interprets this expression over a domain of formulas (modal mu-calculus), considering a process as a property transformer. the transformers are constructed using partial model checking techniques. at its core, our technique solves the verification problem by finding the limit of a chain of formulas. we present a widening operation to find such a limit for properties expressible in a subset of modal mu-calculus. we describe the verification of a number of parameterized systems using our technique to demonstrate its utility.
embedding problems for paths with direction constrained edges. we determine the reachability properties of the embeddings in r3 of a directed path, in the graph-theoretic sense, whose edges have each been assigned a desired direction (east, west, north, south, up, or down) but no length. we ask which points of r3 can be reached by the terminus of an embedding of such a path, by choosing appropriate positive lengths for the edges, if the embedded path starts at the origin, does not intersect itself, and respects the directions pre-assigned to its edges. this problem arises in the context of extending planar graph embedding techniques and vlsi rectilinear layout techniques from 2d to 3d. we give a combinatorial characterization of reachability that yields linear time recognition and layout algorithms. finally, we extend our characterization to rd, d > 3.
node rewriting in graphs and hypergraphs: a categorical framework. vertex rewriting in graphs is a very powerful mechanism which has been studied for quite a long time. in this paper we eventually provide a categorical theory of vertex rewriting and show how it can extend in a uniform way to node and pattern rewriting mechanisms in hypergraphs. copyright 2001 elsevier science b.v.
equilogical spaces. it is well known that one can build models of full higher-order dependent-type theory (also called the calculus of constructions) using partial equivalence relations (pers) and assemblies over a partial combinatory algebra. but the idea of categories of pers and ers (total equivalence relations) can be applied to other structures as well. in particular, we can easily define the category of ers and equivalence-preserving continuous mappings over the standard category top0 of topological t0-spaces; we call these spaces (a topological space together with an er) equilogical spaces and the resulting category equ. we show that this category--in contradistinction to top0--is a cartesian closed category. the direct proof outlined here uses the equivalence of the category equ to the category pequ of pers over algebraic lattices (a full subcategory of top0 that is well known to be cartesian closed from domain theory). in another paper with carboni and rosolini (cited herein), a more abstract categorical generalization shows why many such categories are cartesian closed. the category equ obviously contains top0 as a full subcategory, and it naturally contains many other well known subcategories. in particular, we show why, as a consequence of work of ershov, berger, and others, the kleene-kreisel hierarchy of countable functionals of finite types can be naturally constructed in equ from the natural numbers object n by repeated use in equ of exponentiation and binary products. we also develop for equ notions of modest sets (a category equivalent to equ) and assemblies to explain why a model of dependent type theory is obtained. we make some comparisons of this model to other, known models.
propositional default logics made easier: computational complexity of model checking. liberatore and schaerf (proceedings of the ecai' 98, 1998) give a proof that model checking for propositional normal default theories is in δ2p and δ2p[o(log n)]-hard. however, the precise complexity is left as an open problem. we solve this problem by proving that model checking for normal default theories is complete for δ2p[o(log n)]. this is the class of decision problems solvable in polynomial time with a logarithmic number of calls to an oracle in np. additionally, we analyse the computational cost of model checking w.r.t, weak extensions, stable expansions and n-expansions and take a look at the complexity of model checking for disjunction-free default theories. furthermore, we show that not only for disjunction-free default theories, but also for a larger class of default theories, which we call default theories in extended horn normal form, the complexity of model checking is, in the case of normal default theories, tractable. additionally, the complexity results are used to draw some interesting conclusions on translatability issues. in particular, there exists no function from default logic into logic programming which is polynomial, faithful and modular unless conp = σ2p. finally, we give an overview of our results concerning model checking in case of disjunctive default logic and stationary default logic.
completeness in standard and differential approximation classes: poly-(d)apx- and (d)ptas-completeness. several problems are known to be apx-, dapx-, ptas-, or poly-apx-pb-complete under suitably defined approximation-preserving reductions. but, to our knowledge, no natural problem is known to be ptas-complete and no problem at all is known to be poly-apx-complete. on the other hand, dptas- and poly-dapx-completeness have not been studied until now. we first prove in this paper the existence of natural poly-apx- and poly-dapx-complete problems under the well known ptas-reduction and under the dptas-reduction (defined in "g. ausiello, c. bazgan, m. demange, and v. th. paschos, completeness in differential approximation classes, mfcs'03"), respectively. next, we deal with ptas- and dptas-completeness. we introduce approximation preserving reductions, called ft and dft, respectively, and prove that, under these new reductions, natural problems are ptas-complete, or dptas-complete. then, we deal with the existence of intermediate problems under our reductions and we partially answer this question showing that the existence of npo-intermediate problems under turing-reductions is a sufficient condition for the existence of intermediate problems under both ft- and dft-reductions. finally, we show that min coloring is dapx-complete under dptas-reductions. this is the first dapx-complete problem that is not simultaneously apx-complete.
partitioning vertices of 1-tough graphs into paths. in this paper we prove that every 1-tough graph has a partition of its vertices into paths of length at least two.
on the differential approximation of min set cover. we present in this paper differential approximation results for min set cover and min weighted set cover. we first show that the differential approximation ratio of the natural greedy algorithm for min set cover is bounded below by 1.365/δ and above by 4/(δ + 1), where δ is the maximum set-cardinality in the min set cover-instance. next, we study another approximation algorithm for min set cover that computes 2-optimal solutions, i.e., solutions that cannot be improved by removing two sets belonging to them and adding another set not belonging to them. we prove that the differential approximation ratio of this second algorithm is bounded below by 2/(δ + 1) and that this bound is tight. finally, we study an approximation algorithm for min weighted set cover and provide a tight lower bound of 1/δ. our results identically hold for max hypergraph independent set in both the standard and the differential approximation paradigms.
degree-constrained decompositions of graphs: bounded treewidth and planarity. we study the problem of decomposing the vertex set v of a graph into two nonempty parts v1, v2 which induce subgraphs where each vertex v ∈ v1 has degree at least a(v) inside v1 and each v ∈ v2 has degree at least b(v) inside v2. we give a polynomial-time algorithm for graphs with bounded treewidth which decides if a graph admits a decomposition, and gives such a decomposition if it exists. this result and its variants are then applied to designing polynomial-time approximation schemes for planar graphs where a decomposition does not necessarily exist but the local degree conditions should be met for as many vertices as possible.
an algorithmic view of gene teams. comparative genomics is a growing field in computational biology, and one of its typical problem is the identification of sets of orthologous genes that have virtually the same function in several genomes. many different bioinformatics approaches have been proposed to define these groups, often based on the detection of sets of genes that are "not too far" in all genomes. in this paper, we propose a unifying concept, called gene teams, which can be adapted to various notions of distance. we present two algorithms for identifying gene teams formed by n genes placed on m linear chromosomes. the first one runs in o(mn log2n) and uses a divide and conquer approach based on the formal properties of gene teams. we next propose an optimization of the original algorithm, and, in order to better understand the complexity bound of the algorithms, we recast the problem in the hopcroft's partition refinement framework. this allows us to analyze the complexity of the algorithms with elegant amortized techniques. both algorithms require linear space. we also discuss extensions to circular chromosomes that achieve the same complexity.
determinization of transducers over finite and infinite words. we study the determinization of transducers over finite and infinite words. the first part of the paper is devoted to finite words. we recall the characterization of subsequential functions due to choffrut. we describe here a known algorithm to determinize a transducer.in the case of infinite words, we consider transducers with all their states final. we give an effective characterization of sequential functions over infinite words. we describe an algorithm to determinize transducers over infinite words. this part contains the main novel results of the paper.
squaring transducers: an efficient procedure for deciding functionality and sequentiality. we describe here a construction on transducers that give a new conceptual proof for two classical decidability results on transducers: it is decidable whether a finite transducer realizes a functional relation, and whether a finite transducer realizes a sequential relation. a better complexity follows then for the two decision procedures.
a hierarchy of shift equivalent sofic shifts. we define new subclasses of the class of irreducible sofic shifts. these classes form an infinite hierarchy where the lowest class is the class of almost finite type shifts introduced by b. marcus. we give effective characterizations of these classes with the syntactic semigroups of the shifts. we prove that these classes define invariants for shift equivalence (and thus for conjugacy). finally, we extend the result to the case of reducible sofic shifts.
codes and sofic constraints. we study the notion of a code in a sofic subshift. we first give a generalization of the kraft-mcmillan inequality to this case. we then prove that the polynomial of the alphabet in an irreducible sofic shift divides the polynomial of any finite code which is complete for this sofic shift. this settles a conjecture from reutenauer.
codes, unambiguous automata and sofic systems. we study the relationship between codes and unambiguous automata inside a sofic system. we show that a recognizable set is a code in a sofic system if and only if a particular automaton associated to the set and the shift is unambiguous. we discuss an example of a finite complete code in a sofic system in connection with the factorization conjecture.
a common algebraic description for probabilistic and quantum computations. through the study of gate arrays we develop a unified framework to deal with probabilistic and quantum computations, where the former is shown to be a natural special case of the latter. on this basis we show how to encode a probabilistic or quantum gate array into a sum-free tensor formula which satisfies the conditions of the partial trace problem, and vice-versa; that is, given a tensor formula f of order n × 1 over a semiring i plus a positive integer k, deciding whether the kth partial trace of the matrix valin,n (f ċ ft) fulfills a certain property. we use this to show that a certain promise version of the sum-free partial trace problem is complete for the class pr- bpp (promise bpp) for formulas over the semiring (q+, +, ċ) of the positive rational numbers, for pr-bqp (promise bqp) in the case of formulas defined over the field (q+, +, ċ), and if the promise is given up, then completeness for pp is shown, regardless whether tensor formulas over positive rationals or rationals in general are used. this suggests that the difference between probabilistic and quantum polytime computers may ultimately lie in the possibility, in the latter case, of having destructive interference between computations occurring in parallel. moreover, by considering variants of this problem, classes like op, np, c=p, its complement co-c=p, the promise version of valiant's class up, its generalization promise spp, and unique polytime us can be characterized by carrying the problem properties and the underlying semiring.
mcnaughton families of languages. in 1988 the church-rosser languages were introduced by mcnaughton et al. as those languages that are recognized by finite, length-reducing and confluent string-rewriting systems using extra non-terminal symbols. here we generalize this concept by considering classes of languages that are obtained by other types of string-rewriting systems. to honour robert mcnaughton's original contribution we call the resulting families of languages mcnaughton families. here it is shown that the concept of mcnaughton families is as powerful as the notion of turing machine or the notion of phrase-structure grammar. we investigate the relationships between the various mcnaughton families, obtaining an extensive hierarchy of classes that includes many well-known language and complexity classes as well as some new classes. further, we consider some closure and non-closure properties for those mcnaughton families that are contained in the class of context-free languages, and we address the complexity of the fixed and the general membership problems for these families.
on probabilistic timed automata. we propose a model of probabilistic timed automaton which substitutes for the nondeterminism of an ordinary timed automaton, a new one (directly drawn from markov decision processes) by means of actions which provide a probabilistic distribution over transitions. using büchi acceptance conditions, timed automata can refer timing properties as "during every open time interval of length 1 at least one message is delivered". a policy is a mechanism which solves the non-determinism by choosing for each finite run an action and the time moment of the next transition step implied by this action. we prove that, given a probabilistic timed automaton a, there exists a markov (memoryless) policy which maximizes the probability p of the set of accepting runs realized by this policy. this policy as well as the maximal value of p are computable in polytime in the size of the region automaton of a. this result provides an algorithm of model-checking for properties like "there is a policy which realizes a correct behavior of the system with probability at least p".
groups and tilings. we prove that the word problem for the group of dominoes is equivalent to the existence of a directed tiling for the corresponding closed curve in the plane, which, in turn is equivalent to the fact that the curve is "balanced". this last property beeing decidable, the word problem is also decidable. moreover we prove that this result is transposable in any other regular grid (hexagonal or triangular) and we partially extend it to "exact" tiles.
a codicity undecidable problem in the plane. in this paper we give a new undecidability result about tiling problems. given a finite set of polyomino types, the problem whether this set is a code, is undecidable. the same result holds for dominoes.
decidable verification for reducible timed automata specified in a first order logic with time. we consider one type of first order timed logic (fotl) with explicit continuous time. fotl is sufficiently expressible from the user's point of view to rewrite directly requirements specifications often given in a language close to the natural one, and it permits to represent the set of runs of timed programs. thus, fotl is apt to formalize the verification problem for timed systems. our main goal is to describe in semantical terms interesting decidable classes of the verification problem within this setting. we prove that under some finiteness properties of the requirements and algorithm specifications the verification problem represented in fotl becomes decidable. the finiteness properties we introduce, "finite refutability" and "finite satisfiability", are undecidable in the general case. however, "finite refutability" is often easy to verify. on the other hand, we give a sufficient condition, namely reducibility, which ensures the "finite satisfiability" for timed automata, and we prove that the reducibility is decidable. this is the main result of the paper. as a consequence the verification of any finitely refutable requirements is decidable for reducible timed automata.
on the design of efficient atm routing schemes. in this paper we deal with the problem of designing virtual path layouts in atm networks when the hop-count is given and the load has to be minimized. we first prove a lower bound for networks with arbitrary topology and arbitrary set of connection requests. this result is then applied to derive lower bounds for the following settings: (i) one-to-all (one node has to be connected to all other nodes of the network) in arbitrary networks; (ii) all-to-all (each node has to be connected to all other nodes in the network) in several classes of networks, including planar and k-separable networks and networks of bounded genus. we finally study the all-to-all setting on two-dimensional meshes and we design a virtual path layout for this problem. when the hop-count and the network degree are bounded by constants, our results show that the upper bounds proposed in this paper for the one-to-all problem in arbitrary networks and for the all-to-all problem in two-dimensional mesh networks are asymptotically optimal. moreover, the general lower bound shows that the algorithm proposed in gerstel (ph.d. thesis, technion-haifa, israel, 1995) for the all-to-all problem in k-separable networks is also asymptotically optimal. the upper bound for mesh networks also shows that the lower bound presented in this paper for the all-to-all problem in planar networks is asymptotically tight.
semi-clairvoyant scheduling. in (symp. discrete algorithms 2002, p. 762) it was shown that the obvious semi-clairvoyant generalization of the shortest processing time is o(1)-competitive with respect to average stretch on a single machine. in (symp. discrete algorithms 2002, p. 762) it was left as an open question whether it was possible for a semi-clairvoyant algorithm to be o(1)-competitive with respect to average flow time on a single machine. here we settle this open question by giving a semi-clairvoyant algorithm that is o(1)-competitive with respect to average flow time on a single machine. we also show a semi-clairvoyant algorithm on parallel machines that achieves up to constant factors the best known competitive ratio for clairvoyant on-line algorithms. in some sense one might conclude from this that the qos achievable by semi-clairvoyant algorithms is competitive with clairvoyant algorithms. we finally show that, in contrast to the clairvoyant case, no semi-clairvoyant algorithm can be simultaneously o(1)-competitive with respect to average stretch and o(1)-competitive with respect to average flow time.
an example of a computable absolutely normal number. the first example of an absolutely normal number was given by sierpinski in 1916, twenty years before the concept of computability was formalized. in this note we give a recursive reformulation of sierpinski's construction which produces a computable absolutely normal number.
-valued non-associative lambek grammars are learnable from generalized functor-argument structures. this paper is concerned with learning categorial grammars from positive examples in the model of gold. functor-argument structures (written fa) are usual syntactical decompositions of sentences in sub-components distinguishing the functional parts from the argument parts defined in the case of classical categorial grammars also known as ab-grammars. in the case of nonassociative type-logical grammars, we propose a similar notion that we call generalized functor-argument structures and we show that these structures capture the essence of non-associative lambek (nl) calculus without product.we show that (i) rigid and k-valued non-associative lambek (nl without product) grammars are learnable from generalized functor-argument structured sentences.we also define subclasses of k-valued grammars in terms of arity. we first show that (ii) for each k and each bound on arity the class of fa-arity bounded k-valued nl languages of fa structures is finite and (iii) that fa-arity bounded k-valued nl grammars are learnable both from strings and from fa structures as a corollary.result (i) is obtained from (ii); this learnability result (i) is interesting and surprising when compared to other results: in fact we also show that (iv) this class has infinite elasticity. moreover, these classes are very close to classes like rigid associative lambek grammars learned from natural deduction structured sentences (that are different and much richer than fa or generalized fa) or to k-valued non-associative lambek grammars unlearnable from strings or even from bracketed strings. thus, the class of k-valued non-associative lambek grammars learned from generalized functor-argument sentences is at the frontier between learnable and unlearnable classes of languages.
notations for exponentiation. we define a coding of natural numbers--which we will call exponential notations--and interpretations of the less-than-relation, the successor, addition and exponentiation function on exponential notations. we prove that all these interpretations are polynomial time computable. as a corollary we obtain that feasible arithmetic can prove the consistency of the canonical equational theory for the language containing the successor, addition and exponentiation function.
synchronized shuffles. we extend the basic shuffle on words and languages, a well-known operation in theoretical computer science, by introducing three synchronized shuffles. these synchronized shuffles have some relevance to molecular biology since they may be viewed as the formal representations of various forms of gene linkage during genome shuffling. more precisely, each synchronized shuffle preserves the genetic backbone of the organisms, as well as the linked genes, by requiring the synchronization of some predefined genes while all other genes are arbitrarily shuffled. as for their mathematical properties, we prove that in a trio the closure under shuffle is equivalent to the closure under any of the synchronized shuffles studied here. finally, based on this result, we present an algorithm for deciding whether a given regular language is synchronized shuffle closed.
efficiently covering complex networks with cliques of similar vertices. we describe a polynomial time algorithm for covering graphs with cliques, prove its asymptotic optimality in a random intersection graph model and present experimental results on complex real-world networks.
the 3-server problem in the plane. in the k-server problem we wish to minimize, in an online fashion, the movement cost of k servers in response to a sequence of requests (we assume that k ≥ 2). the request issued at each step is specified by a point r in a given metric space m. to serve this request, one of the k servers must move to r. it is known that if m has at least k + 1 points then no online algorithm for the k-server problem in m has competitive ratio smaller than k. the best known upper bound on the competitive ratio in arbitrary metric spaces, by koutsoupias and papadimitriou (j. acm 42 (1995) 971), is 2k - 1. there are only a few special cases for which k-competitive algorithms are known: for k = 2, when m is a tree, or when m has at most k + 2 points. we prove that the work function algorithm is 3-competitive for the 3-server problem in the manhattan plane. as a corollary, we obtain a 4.243-competitive algorithm for 3 servers in the euclidean plane. the best previously known competitive ratio for 3 servers in these metric spaces was 5.
mod 3 arithmetic on triangulated riemann surfaces. let t be a triangulation of a riemann surface, orientable or non-orientable and of an arbitrary genus. suppose, a labeling of the vertices of t by three labels &thgr;, +1, and -1 is fixed. the present paper deals with the following problem: 2nd the number of labelings of the faces of t by two labels +1 and - 1, in such a way that the sum of the labels of the faces around any vertex is equal modulo 3 to the given label of the vertex. if t is a planar triangulation and all labels of vertices are zeros, then the problem of existence of such a labeling of faces is equivalent, according to p.j. heawood, to the four-colour problem for planar triangulations, and the corresponding counting problem is equivalent to that of counting the number of all proper four-colourings of t.
categorical proof theory of classical propositional calculus. we investigate semantics for classical proof based on the sequent calculus. we show that the propositional connectives are not quite well-behaved from a traditional categorical perspective, and give a more refined, but necessarily complex, analysis of how connectives may be characterised abstractly. finally we explain the consequences of insisting on more familiar categorical behaviour.
on probabilistic analog automata. we consider probabilistic automata on a general state space and study their computational power. the model is based on the concept of language recognition by probabilistic automata due to rabin (inform. control 3 (1963) 230) and models of analog computation in a noisy environment suggested by maass and orponen (neural comput. 10 (1998) 1071), and maass and sontag (neural comput. 11 (1999) 771). our main result is a generalization of rabin's reduction theorem that implies that under very mild conditions, the computational power of such automata is limited to regular languages.
the level ancestor problem simplified. we present a simple algorithm for the level ancestor problem. a level ancestor query la(v,d) requests the depth d ancestor of node v. the level ancestor problem is to preprocess a given rooted tree t to support level ancestor queries. while optimal solutions to this problem already exist, our new optimal solution is simple enough to be taught and implemented.
structural properties of xpath fragments. we study structural properties of each of the main sublanguages of navigational xpath (w3c recommendation) commonly used in practice. first, we characterize the expressive power of these language fragments in terms of both logics and tree patterns. second, we investigate closure properties, focusing on the ability to perform basic boolean operations while remaining within the fragment. we give a complete picture of the closure properties of these fragments, treating xpath expressions both as functions of arbitrary nodes in a document tree, and as functions that are applied only at the root of the tree. finally, we provide sound and complete axiom systems and normal forms for several of these fragments. these results are useful for simplification of xpath expressions and optimization of xml queries.
automated higher-order complexity analysis. this paper describes the automated complexity analysis (aca) system for automated higher-order complexity analysis of functional programs synthesized with the ncprd proof development system. we introduce a general framework for defining models of computational complexity for functional programs based on an annotation of a given operational language semantics. within this framework, we use type decomposition and polynomialization to express the complexity of higher-order terms. symbolic interpretation of open terms automates complexity analysis, which involves generating and solving higher-order recurrence equations. finally, the use of the aca system is demonstrated by analyzing three different implementations of the pigeonhole principle.
building continuous webbed models for system f. we present here a large family of concrete models for girard and reynolds polymorphism (system f), in a noncategorical setting. the family generalizes the construction of the model of barbanera and berardi (tech. report, university of turin, 1997), hence it contains complete models for fη (a βη-complete model for system f, preprint, june, 1998) and we conjecture that it contains models which are complete for f. it also contains simpler models, the simplest of them, e2, being a second-order variant of the engeler-plotkin model e. all the models here belong to the continuous semantics and have underlying prime algebraic domains, all have the maximum number of polymorphic maps. the class contains models which can be viewed as two intertwined compatible webbed models of untyped λ-calculus (in the sense of berline (from computations to foundations: the λ-calculus and its webbed models, revised version, theoret. comput. sci. 86 pp., to appear)), but it is much larger than this. finally, many of its models might he read as two intertwined strict intersection type systems.
from cascade decompositions to bit-vector algorithms. a vector algorithm is an algorithm that applies a bounded number of vector operations to an input vcctor, regardless of the length of the input. in this paper, we describe the links between the existence of vector algorithms and the cascade decompositions of counter-free automata.we show that any computation that can be carried out with a counter-free automaton can be recast as a vector algorithm. moreover, we show that for a class of automata that is closely related to algorithms in bio-computing, the complexity of the resulting algorithms is linear in the number of transitions of the original automaton.
computational complexity of some problems involving congruences on algebras. we prove that several problems concerning congruences on algebras are complete for nondeterministic log-space. these problems are: determining the congruence on a given algebra generated by a set of pairs, and determining whether a given algebra is simple or subdirectly irreducible. we also consider the problem of determining the smallest fully invariant congruence on a given algebra containing a given set of pairs. we prove that this problem is complete for nondeterministic polynomial time.
polarized process algebra with reactive composition. polarized processes are introduced to model the asymmetric interaction of systems. the asymmetry stems from the distinction between service and request. the scheduled concurrent composition of two polarized processes is called client-server composition or reactive composition, placing one process in the role of a client and the other process in the role of a server which is supposed to react on requests. the technical goal of this paper is to provide a definition of reactive composition for polarized processes and to prove that reactive composition thus defined is associative.
process algebra for hybrid systems. we propose a process algebra obtained by extending a combination of the process algebra with continuous relative timing from baeten and middelburg (process algebra with timing, springer, berlin, 2002, chapter 4), and the process algebra with propositional signals from baeten and bergstra (theoret. comput. sci. 177 (1977) 381-405). the proposed process algebra makes it possible to deal with the behaviour of hybrid systems, i.e. systems in which the instantaneous state transitions caused by performing actions are alternated with continuous state evolutions. this process algebra has, in addition to equational axioms, rules to derive equations with the help of real analysis.
branching time and orthogonal bisimulation equivalence. we propose a refinement of branching bisimulation equivalence that we call orthogonal bisimulation equivalence. typically, internal activity (the performance of τ-steps) may be compressed, but not completely discarded. hence, a process with τ-steps cannot be equivalent to one without τ-steps. also, we present a modal characterization of orthogonal bisimulation equivalence. this equivalence is a congruence for acp extended with abstraction and priority operators. we provide a complete axiomatization, and describe some expressiveness results. finally, we present the verification of a par protocol that is specified with use of priorities.
easiness in graph models. we generalize baeten and boerboom's method of forcing to show that there is a fixed sequence (uk)k∈ω of closed (untyped) λ-terms satisfying the following properties: (a) for any countable sequence (gk)k∈ω of scott continuous functions (of arbitrary arity) on the power set of an arbitrary countable set, there is a graph model such that (λx.xx)(λx.xx)uk represents gk in the model. (b) for any countable sequence (tk)k∈ω of closed λ-terms there is a graph model that satisfies (λx.xx)(λx.xx)uk = tk for all k. we apply these two results, which are corollaries of a unique theorem, to prove the existence of (1) a finitely axiomatized λ-theory l such that the interval lattice constituted by the λ-theories extending l is distributive; (2) a continuum of pairwise inconsistent graph theories (= λ-theories that can be realized as theories of graph models); (3) a congruence distributive variety of combinatory algebras (lambda abstraction algebras, respectively).
directed virtual path layouts in atm networks. motivated by asynchronous transfer mode in telecommunication networks, we investigate the problem of designing a directed virtual topology on a directed physical topology, which consists in finding a set of directed virtual paths (vps) satisfying some constraints in terms of load (the number of vps sharing a physical link) and hop count (the number of vps used to establish a connection). for both general and particular networks, such as paths, cycles, meshes, tori and trees, we derive tight bounds on the virtual diameter (the maximum hop count for a connection) as a function of the network capacity (the maximum load of a physical link).
a new dimension sensitive property for cellular automata. in this paper we study number-decreasing cellular automata. they form a super-class of standard number-conserving cellular automata. it is well-known that the property of being number-conserving is decidable in quasi-linear time. in this paper we prove that being number-decreasing is dimension sensitive, i.e. it is decidable for one-dimensional cellular automata and undecidable for dimension 2 or greater. there are only few known examples of dimension sensitive properties for cellular automata and this denotes some rich panel of phenomena in this class.
an algebraic model of observable properties in distributed systems. we propose orthomodular posets, algebraic models of quantum logic, as a formal tool in concurrency theory. we discuss their characteristics and study mutual relations with two other models of distributed systems: condition event net systems, a basic class of petri nets, and the transition systems modelling ce net system behaviour. central results are an adjointness situation among the three models and a strict relationship between fundamental notions in the different considered frameworks such as the relations of incompatibility and concurrency. furthermore, substructures of orthomodular posets, like boolean subalgebras or centres are interpreted, respectively, as state machine components of ce net systems or synchronization structures.
performance measure sensitive congruences for markovian process algebras. the modeling and analysis experience with process algebras has shown the necessity of extending them with priority, probabilistic internal/external choice, and time while preserving compositionality. the purpose of this paper is to make a further step by introducing a way to express performance measures, in order to allow the modeler to capture the qos metrics of interest. we show that the standard technique of expressing stationary and transient performance measures as weighted sums of state probabilities and transition frequencies can be imported in the process algebra framework. technically speaking, if we denote by n ∈ n the number of performance measures of interest, in this paper we define a family of extended markovian process algebras with generative master-reactive slaves synchronization mechanism called empagrn including probabilities, priorities, exponentially distributed durations, and sequences of rewards of length n. then we show that the markovian bisimulation equivalence ∼mbn is a congruence for empagrn which preserves the specified performance measures and we give a sound and complete axiomatization for finite empagrn terms. finally, we present a case study conducted with the software tool two towers in which we contrast the average performance of a selection of distributed algorithms for mutual exclusion modeled with empagrn.
a tutorial on empa: a theory of concurrent processes with nondeterminism, priorities, probabilities and time. we give an overview of empa, a process algebra for modeling and analyzing concurrent systems where nondeterminism, priorities, probabilities and time are present, aiming at a reasonable trade off between the expressive power of the calculus and the complexity of its underlying theory.
the complexity of computing the mcd-estimator. in modern statistics the robust estimation of parameters is a central problem, i.e., an estimation that is not or only slightly affected by outliers in the data. the minimum covariance determinant (mcd) estimator (j. amer. statist. assoc. 79 (1984) 871) is probably one of the most important robust estimators of location and scatter. the complexity of computing the mcd, however, was unknown and generally thought to be exponential even if the dimensionality of the data is fixed.here we present a polynomial time algorithm for mcd for fixed dimension of the data. in contrast we show that computing the mcd-estimator is np-hard if the dimension varies.
primality test for numbers m with a large power of 5 dividing m-1. the quintic reciprocity law is used to produce an algorithm, that runs in polynomial time, and that determines the primality of numbers m, such that m4 - 1, is divisible by a power of 5 which is larger that √m, provided that a small prime p, p ≡ 1 (mod 5) is given, such that m, is not a fifth power modulo p. the same test equations are used for all such m.a sufficiency test, together with its probability of succeeding in determining primality is given when the condition on m modulo p is omitted.
growth of repetition-free words -- a review. this survey reviews recent results on repetitions in words, with emphasis on the estimations for the number of repetition-free words.
shuffle factorization is unique. we prove that, given a finite set of words s, there exists at most one (normalized) multiset p such that s is the shuffle of the words in p. the multiset p is effectively computable.
operations preserving regular languages. given a strictly increasing sequence s of non-negative integers, filtering a word a0a1.... an by s consists in deleting the letters ai such that i is not in the set {s0,s1,...}. by a natural generalization, denote by l[s], where l is a language, the set of all words of l filtered by s. the filtering problem is to characterize the filters s such that, for every regular language l, l[s] is regular. in this paper, the filtering problem is solved, and a unified approach is provided to solve similar questions, including the removal problem considered by seiferas and mcnaughton. our approach relies on a detailed study of various residual notions, notably residually ultimately periodic sequences and residually rational transductions.
mixed languages. let t = a ∪ b ∪ c be an alphabet that is partitioned into three subalphabets. the mixing product of a word g over a ∪ b and of a word d over a ∪ c is the set of words w over t such that its projection onto a ∪ b gives g and its projection onto a ∪ c gives d.let r be a regular language over t such that xbcy is in r if and only if xcby is in r for any two letters b in b and c in c. in other words, r is commutative over b and c. is this property "structural" in the sense that r can then be obtained as a mixing product of a regular language over a ∪ b and of a regular language over a ∪ c?this question has a rather easy answer, but there are many cases where the answer is negative. a more interesting question is whether r can be represented as a finite union of mixed products of regular languages. for the moment, we do not have an answer to this question. however, we prove that it is decidable whether, for a given k, the language r is a union of at most k mixed products of regular languages.
coding rotations on intervals. we show that the coding of a rotation by on m intervals can be recoded over m sturmian words of angle.
smooth words over arbitrary alphabets. smooth infinite words over ∑ = {1, 2} are connected to the kolakoski word k = 221121 ..., defined as the fixpoint of the function δ that counts the length of the runs of 1's and 2's. in this paper we extend the notion of smooth words to arbitrary alphabets and study some of their combinatorial properties. using the run-length encoding δ, every word is represented by a word obtained from the iterations of δ. in particular we provide a new representation of the infinite fibonacci word f as an eventually periodic word. on the other hand, the thue-morse word is represented by a finite one.
balance properties of multi-dimensional words. a word u is called 1-balanced if for any two factors v and w of u of equal length, we have 1|v|i|w|i1 for each letter i, where |v|i denotes the number of occurrences of i in the factor v. the aim of this paper is to extend the notion of balance to multi-dimensional words. we first characterize all 1-balanced words on &zn. in particular, we prove they are fully periodic for n>1. we then give a quantitative measure of non-balancedness for some words on &z2 with irrational density, including two-dimensional sturmian words.
lattices and multi-dimensional words. in the present paper we develop a formalism to generate multi-dimensional words using lattices which generalizes the construction of real numbers (one-dimensional words) from a sequence of partial quotients using continued fractions. the construction was introduced in a special case by simpson and tijdeman in order to derive a multi-dimensional generalization of the theorem of fine and wilf. we show that the produced multi-dimensional words are intrinsically connected with k-dimensional sturmian words.
bounding the firing synchronization problem on a ring. in this paper we improve the upper and lower bounds on the complexity of solutions to the firing synchronization problem on a ring. in this variant of the firing synchronization problem the goal is to synchronize a ring of identical finite automata. initially, all automata are in the same state except for one automaton that is designated as the initiator for the synchronization. the goal is to define the set of states and the transition function for the automata so that all machines enter a special fire state for the first time and simultaneously during the final round of the computation. in our work we present two solutions to the ring firing synchronization problem, an 8-state minimal-time solution and a 6-state non-minimal-time solution. both solutions use fewer states than the previous best-known minimal-time automaton, a 16-state solution due to culik. we also give the first lower bounds on the number of states needed for solutions to the ring firing synchronization problem. we show that there is no 3-state solution and no 4-state, symmetric, minimal-time solution for the ring.
on the number of occurrences of a symbol in words of regular languages. we study the random variable yn representing the number of occurrences of a symbol a in a word of length n chosen at random in a regular language l ⊆ {a, b}*, where the random choice is defined via a non-negative rational formal series r of support l. assuming that the transition matrix associated with r is primitive we obtain asymptotic estimates for the mean value and the variance of yn and present a central limit theorem for its distribution. under a further condition on such a matrix, we also derive an asymptotic approximation of the discrete fourier transform of yn, that allows to prove a local limit theorem for yn. further consequences of our analysis concern the growth of the coefficients in rational formal series; in particular, it turns out that, for a wide class of regular languages l, the maximum number of words of length n in l having the same number of occurrences of a given symbol is of the order of growth λn/√n, for some constant λ>1.
small size quantum automata recognizing some regular languages. given a class {pα | α ∈ i} of stochastic events induced by m-state 1-way quantum finite automata (1qfa) on alphabet σ, we investigate the size (number of states) of 1qfa's that δ-approximate a convex linear combination of {pα | α ∈ i}, and we apply the results to the synthesis of small size 1qfa's. we obtain: • an o((md/δ3) log2(d/δ2)) general size bound, where d is the vapnik dimension of {pα(w) | w ∈ σ*}. • for commutative n-periodic events p on σ with |σ| = h, we prove an o((h log n/δ2)) size bound for inducing a δ-approximation of ½ + ½ p whenever ||f(p)||1 ≤nh, where f(p) is the discrete fourier transform of (the vector p associated with) p. • if the characteristic function χl of an n-periodic unary language l satisfies ||f(χl))||1 ≤ n, then l is recognized with isolated cut-point by a 1qfa with o(log n) states. vice versa, if l is recognized with isolated cut-point by a 1qfa with o(log n) state, then ||f(χl))||1 = o(n log n).
some formal tools for analyzing quantum automata. results in the area of compact monoids and groups are useful in the analysis of quantum automata (lqfa's). in this paper: (1) we settle isolated cut point rabin's theorem in the context of compact monoids, and we prove a lower bound on the state complexity of lqfa's accepting regular languages. (2) we use a method pointed out by blondel et al. [decidable and undecidable problems about quantum automata, technical report rr2003-24, lip, ens lyon, 2003] based on compact groups theory to design an algorithm for testing whether a k-tuple of lqfa's is a classifier of words in σ*; this problem turns out to be undecidable if the completeness of the classifier is required. (3) in the unary case, we give an exponential time algorithm for computing the descriptional complexity of periodic languages. moreover, we present a probabilistic method to construct lqfa's exponentially succinct in the period and polynomially succinct in the inverse of the bounded error.
gemmating p systems: collapsing hierarchies. we continue the analysis of p systems with gemmation of mobile membranes. we solve an open problem from besozzi et al. (proc. italian conf. on theoretical computer science 2001, lecture notes in computer science, vol. 2202, springer, berlin, 2001, pp. 136-153), showing that the hierarchy on the number of membranes collapses: systems with eight membranes characterize the recursively enumerable languages (seven membranes are enough in the case of extended systems). we also prove that p systems, which use only gemmation, but neither classical rewriting rules nor in/out communications, can generate the same family of languages. in this case, the hierarchy on the number of membranes collapses to level nine.
proof-carrying code from certified abstract interpretation and fixpoint compression. proof-carrying code (pcc) is a technique for downloading mobile code on a host machine while ensuring that the code adheres to the host's safety policy. we show how certified abstract interpretation can be used to build a pcc architecture where the code producer can produce program certificates automatically. code consumers use proof checkers derived from certified analysers to check certificates. proof checkers carry their own correctness proofs and accepting a new proof checker amounts to type checking the checker in coq. certificates take the form of strategies for reconstructing a fixpoint and are kept small due to a technique for fixpoint compression. the pcc architecture has been implemented and evaluated experimentally on a byte code language for which we have designed an interval analysis that allows to generate certificates ascertaining that no array-out-of-bounds accesses will occur.
how to analyse evolutionary algorithms. many variants of evolutionary algorithms have been designed and applied. the experimental knowledge is immense. the rigorous analysis of evolutionary algorithms is difficult, but such a theory can help to understand, design, and teach evolutionary algorithms. in this survey, first the history of attempts to analyse evolutionary algorithms is described and then new methods for continuous as well as discrete search spaces are presented and discussed.
the enumerability of p collapses p to nc. we show that one cannot rule out even a single possibility for the value of an arithmetic circuit on a given input using an nc algorithm, unless p collapses to nc (i.e., unless all problems with polynomial-time sequential solutions can be efficiently parallelized). in other words, excluding any possible solution in this case is as hard as actually finding the solution. the result is robust with respect to nc algorithms that err (i.e., exclude the correct value) with small probability. we also show that p collapses all the way down to nc1 when the characteristic of the field that the problem is over is sufficiently large (but in this case under a stronger elimination hypothesis that depends on the characteristic).
edge-isoperimetric problems for cartesian powers of regular graphs. we consider an edge-isoperimetric problem (eip) on the cartesian powers of graphs. one of our objectives is to extend the list of graphs for whose cartesian powers the lexicographic order provides nested solutions for the eip. we present several new classes of such graphs that include as special cases all presently known graphs with this property. our new results are applied to derive best possible edge-isoperimetric inequalities for the cartesian powers of arbitrary regular, resp. regular bipartite, graphs with a high density.
new spectral lower bounds on the bisection width of graphs. the communication overhead is a major bottleneck for the execution of a process graph on a parallel computer system. in the case of two processors, the minimization of the communication can be modeled using the graph bisection problem. the spectral lower bound of λ2|v|/4 for the bisection width of a graph is widely known. the bisection width is equal to λ2|v|/4 iff all vertices are incident to λ2/2 cut edges in every optimal bisection.we present a new method of obtaining tighter lower bounds on the bisection width. this method makes use of the level structure defined by the bisection. we define some global expansion properties and we show that the spectral lower bound increases with this global expansion. under certain conditions we obtain a lower bound depending on λ2β|v with ½ < β ≤ 1. we also present examples of graphs for which our new bounds are tight up to a constant factor. as a by-product, we derive new lower bounds for the bisection widths of 3- and 4-regular ramanujan graphs.
a semantics for web services authentication. we consider the problem of specifying and verifying cryptographic security protocols for xml web services. the security specification ws-security describes a range of xml security elements, such as username tokens, public-key certificates, and digital signatures, amounting to a flexible vocabulary for expressing protocols. to describe the syntax of these elements, we extend the usual xml data model with symbolic representations of cryptographic values. we use predicates on this data model to describe the semantics of security elements and of sample protocols distributed with the microsoft wse implementation of ws-security. by embedding our data model within abadi and fournet's applied pi calculus, we formulate and prove security properties with respect to the standard dolev-yao threat model. moreover, we informally discuss issues not addressed by the formal model. to the best of our knowledge, this is the first approach to the specification and verification of security protocols based on a faithful account of the xml wire format.
observational logic, constructor-based logic, and their duality. observability and reachability are important concepts for formal software development. while observability concepts are used to specify the required observable behavior of a program or system, teachability concepts are used to describe the underlying data in terms of datatype constructors. in this paper we first reconsider the observational logic institution which provides a logical framework for dealing with observabifity. then we develop in a completely analogous way the constructor-based logic institution which formalizes a novel treatment of reachability. both institutions are tailored to capture the semantically correct realizations of a specification from either the observational or the reachability point of view. we show that there is a methodological and even formal duality between both frameworks. in particular, we establish a correspondence between observer operations and datatype constructors, observational and constructor-based algebras, fully abstract and reachable algebras, and observational and inductive consequences of specifications. the formal duality between the observability and reachability concepts is established in a category-theoretic setting.
palindrome recognition using a multidimensional tape. the problem of palindrome recognition using a turing machine with one multidimensional tape is proved to, require θ(n2/log n) time.
finding hidden independent sets in interval graphs. we design efficient competitive algorithms for discovering hidden information using few queries. specifically, consider a game in a given set of intervals (and their implied interval graph g) in which our goal is to discover an (unknown) independent set x by making the fewest queries of the form "is point p covered by an interval in x?" our interest in this problem stems from two applications: experimental gene discovery with pcr technology and the game of battleship (in a 1-dimensional setting). we provide adaptive algorithms for both the verification scenario (given an independent set, is it x?) and the discovery scenario (find x without any information). under some assumptions, these algorithms use an asymptotically optimal number of queries in every instance.
global convergence for evolution strategies in spherical problems: some simple proofs and difficulties. this paper presents simple proofs for the global convergence of evolution strategies in spherical problems. we investigate convergence properties for both adaptive and self-adaptive strategies. regarding adaptive strategies, the convergence rates are computed explicitly and compared with the results obtained in the so-called "rate-of-progress" theory. regarding self-adaptive strategies, the computation is conditional to the knowledge of a specific induced markov chain. an explicit example of chaotic behavior illustrates the complexity in dealing with such chains. in addition to these proofs, this work outlines a number of difficulties in dealing with evolution strategies.
lyndon words and shuffle algebras for generating the coloured multiple zeta values relations tables. we study here the coloured multiple zeta values, obtained by extending the usual notion of the multiple zeta values by adding roots of unity. we state their main combinatorial properties. and we give, as a result, a maple algorithm which generates the relations table between these values.
quantum computing without entanglement. it is generally believed that entanglement is essential for quantum computing. we present here a few simple examples in which quantum computing without entanglement is better than anything classically achievable, in terms of the reliability of the outcome after a fixed number of oracle calls. using a separable (that is, unentangled) state, we show that the deutsch-jozsa problem and the simon problem can be solved more reliably by a quantum computer than by the best possible classical algorithm, even probabilistic. we conclude that: (a) entanglement is not essential for quantum computing; and (b) some advantage of quantum algorithms over classical algorithms persists even when the quantum state contains an arbitrarily small amount of information--that is, even when the state is arbitrarily close to being totally mixed.
a survey on tree edit distance and related problems. we survey the problem of comparing labeled trees based on simple local operations of deleting, inserting, and relabeling nodes. these operations lead to the tree edit distance, alignment distance, and inclusion problem. for each problem we review the results available and present, in detail, one or more of the central algorithms for solving the problem.
bernstein-bezoutian matrices. several computational and structural properties of bezoutian matrices expressed with respect to the bernstein polynomial basis are shown. the exploitation of such properties allows the design of fast algorithms for the solution of bernstein-bezoutian linear systems without never making use of potentially ill-conditioned reductions to the monomial basis. in particular, we devise an algorithm for the computation of the greatest common divisor (gcd) of two polynomials in bernstein form. a series of numerical tests are reported and discussed, which indicate that bernstein-bezoutian matrices are much less sensitive to perturbations of the coefficients of the input polynomials compared to other commonly used resultant matrices generated after having performed the explicit conversion between the bernstein and the power basis.
theoretical foundations of dynamic program slicing. this paper presents a theory of dynamic slicing, which reveals that the relationship between static and dynamic slicing is more subtle than previously thought. the definitions of dynamic slicing are formulated in terms of the projection theory of slicing. this shows that existing forms of dynamic slicing contain three orthogonal dimensions in their slicing criteria and allows for a lattice-theoretic study of the subsumption relationship between these dimensions and their relationship to static slicing formulations.
on-line scheduling of parallel jobs with runtime restrictions. consider the execution of a parallel application that dynamically generates parallel jobs with specified resource requirements during its execution. we assume that there is not suffucient knowledge about the running times and the number of jobs generated in order to precompute a schedule for such applications. rather, the scheduling decisions have to be made on-line during runtime based on incomplete information. we present several on-line scheduling algorithms for various interconnection topologies that use some a priori information about the job running times or guarantee a good competitive ratio that depends on the runtime ratio of all generated jobs. all algorithms presented have optimal competitive ratio up to small additive constants, and are easy to implement. copyright 2001 elsevier science b.v.
memoryless determinacy of parity and mean payoff games: a simple proof. we give a simple, direct, and constructive proof of memoryless determinacy for parity and mean payoff games. first, we prove by induction that the finite duration versions of these games, played until some vertex is repeated, are determined and both players have memoryless winning strategies. in contrast to the proof of ehrenfeucht and mycielski, internat. j. game theory, 8 (1979) 109-113, our proof does not refer to the infinite-duration versions. second, we show that memoryless determinacy straightforwardly generalizes to infinite duration versions of parity and mean payoff games.
combinatorial structure and randomized subexponential algorithms for infinite games. the complexity of solving infinite games, including parity, mean payoff, and simple stochastic, is an important open problem in verification, automata, and complexity theory. in this paper, we develop an abstract setting for studying and solving such games, based on function optimization over certain discrete structures. we introduce new classes of recursively local-global (rlg) and partial recursively local-global (prlg) functions, and show that strategy evaluation functions for simple stochastic, mean payoff, and parity games belong to these classes.in this setting, we suggest randomized subexponential algorithms appropriate for rlg-and prlg-function optimization. we show that the subexponential algorithms for combinatorial linear programming, due to kalai and matoušek, sharir, welzl, can be adapted for optimizing the rlg-and prlg-functions.
some results about the chaotic behavior of cellular automata. we study the behavior of cellular automata (ca for short) in the cantor, besicovitch and weyl topologies. we solve an open problem about the existence of transitive ca in the besicovitch topology. the proof of this result has some interest of its own since it is obtained by using kolmogorov complexity. to our knowledge it is the first result about discrete dynamical systems obtained using kolmogorov complexity. we also prove that in the besicovitch topology every ca has either a unique periodic point (thus a fixed point) or an uncountable set of periodic points. this result underlines the fact that ca have a great degree of stability; it may be considered a further step towards the understanding of ca periodic behavior.moreover, we prove that in the besicovitch topology there is a special set of configurations, the set of toeplitz configurations, that plays a role similar to that of spatially periodic configurations in the cantor topology, that is, it is dense and has a central role in the study of surjectivity and injectivity. finally, it is shown that the set of spatially quasi-periodic configurations is not dense in the weyl topology.
codes, orderings, and partial words. codes play an important role in the study of the combinatorics of words. in this paper, we introduce pcodes that play a role in the study of combinatorics of partial words. partial words are strings over a finite alphabet that may contain a number of "do not know" symbols. pcodes are defined in terms of the compatibility relation that considers two strings over the same alphabet that are equal except for a number of insertions and/or deletions of symbols. we describe various ways of defining and analyzing pcodes, in particular, many pcodes can be obtained as antichains with respect to certain partial orderings. using a technique related to dominoes, we show that the pcode property is decidable.
local periods and binary partial words: an algorithm. the study of the combinatorial properties of strings of symbols from a finite alphabet (also referred to as words) is profoundly connected to numerous fields such as biology, computer science, mathematics, and physics. research in combinatorics on words goes back roughly a century. there is a renewed interest in combinatorics on words as a result of emerging new application areas such as molecular biology. partial words were recently introduced in this context. the motivation behind the notion of a partial word is the comparison of genes (or proteins). alignment of two genes (or two proteins) can be viewed as a construction of partial words that are said to be compatible. while a word can be described by a total function, a partial word can be described by a partial function. more precisely, a partial word of length n over a finite alphabet a is a partial function from {1,...,n} into a. elements of {1,...,n} without an image are called holes. a word is just a partial word without holes. the notion of period of a word is central in combinatorics on words. in the case of partial words, there arc two notions: one is that of period, the other is that of local period. this paper extends to partial words with one hole the well known result of guibas and odlyzko which states that for every word u, there exists a word v of same length as u over the alphabet {0, 1} such that the set of all periods of u coincides with the set of all periods of v. our result states that for every partial word u with one hole, there exists a partial word v of same length as u with at most one hole over the alphabet {0, 1} such that the set of all periods of u coincides with the set of all periods of v and the set of all local periods of u coincides with the set of all local periods of v. to prove our result, we use the technique of halava, harju and ilie which they used to characterize constructively the set of periods of a given word. as a consequence of our constructive proof, we obtain a linear time algorithm which, given a partial word with one hole, computes a partial word with at most one hole over the alphabet {0, 1} with the same length and the same sets of periods and local periods. a world wide web server interface at http://www.uncg.edu/mat/algbin/ has been established for automated use of the program.
partial words and a theorem of fine and wilf revisited. a word of length n over a finite alphabet a is a map from {0,...,n_1} into a. a partial word of length n over a is a partial map from {0,...,n_1} into a. in the latter case, elements of {0,...,n1} without image are called holes (a word is just a partial word without holes). in this paper, we extend a fundamental periodicity result on words due to fine and wilf to partial words with two or three holes. this study was initiated by berstel and boasson for partial words with one hole. partial words are motivated by molecular biolog
conjugacy on partial words. the study of the combinatorial properties of strings of symbols from a finite alphabet (also referred to as words) is profoundly connected to numerous fields such as biology, computer science, mathematics, and physics. in this paper, we examine to which extent some fundamental combinatorial properties of words, such as conjugacy, remain true for partial words. the motivation behind the notion of a partial word is the comparison of two genes (alignment of two such strings can be viewed as a construction of two partial words that are said to be compatible). this study on partial words was initiated by berstel and boasson.
verification of cryptographic protocols: tagging enforces termination. we investigate a resolution-based verification method for secrecy and authentication properties of cryptographic protocols. in experiments, we could enforce its termination by tagging, a syntactic transformation of messages that leaves attack-free executions invariant. in this paper, we generalize the experimental evidence: we prove that the verification method always terminates for tagged protocols.
domain representations of partial functions, with applications to spatial objects and constructive volume geometry. a partial spatial object is a partial map from space to data. data types of partial spatial objects are modelled by topological algebras of partial maps and are the foundation for a high level approach to volume graphics called constructive volume geometry (cvg), where space and data are subspaces of n dimensional euclidean space. we investigate the computability of partial spatial object data types, in general and in volume graphics, using the theory of effective domain representations for topological algebras. the basic mathematical problem considered is to classify which partial functions between topological spaces can be represented by total continuous functions between given domain representations of the spaces. we prove theorems about partial functions on regular hausdorff spaces and their domain representations, and apply the results to partial spatial objects and cvg algebras.
inductive-data-type systems. in a previous work ("abstract data type systems", tcs 173(2), 1997), the last two authors presented a combined language made of a (strongly normalizing) algebraic rewrite system and a typed &lambda;-calculus enriched by pattern-matching definitions following a certain format, called the "general schema", which generalizes the usual recursor definitions for natural numbers and similar "basic inductive types". this combined language was shown to be strongly normalizing. the purpose of this paper is to reformulate and extend the general schema in order to make it easily extensible, to capture a more general class of inductive types, called "strictly positive", and to ease the strong normalization proof of the resulting system. this result provides a computation model for the combination of an algebraic specification language based on abstract data types and of a strongly typed functional language with strictly positive inductive types. copyright 2002 elsevier science b.v.
the complexity of bivariate power series arithmetic. inspired by schönhage's discussion in the proc. 11th applied algebra and error correcting codes conference (aaecc), lecture notes in comput. sci., springer, berlin, vol. 948, 1995 pp. 70, we study the multiplicative complexity of the multiplication, squaring, inversion, and division of bivariate power series modulo the "triangular" and "quadratic" ideals (xd+1, xdy,xd-1 y2,..., yd+1) and (xd+1, yd+1), respectively. for multiplication, we obtain the lower bounds 5/4 d2 - o(d) and 2 1/3 d2 o(d) for the triangular and quadratic case, respectively, opposed to the upper bounds 3/2 d2 + o(d) and 3d2 + o(d). for squaring, we prove the lower bounds 7/8 d2-o(d) and 1 3/5 d2- o(d). as upper bounds, we have d2+o(d) and 2 ½ d2+o(d) for the triangular and quadratic case, respectively. concerning inversion, the obtained lower bounds coincide with those of squaring. as upper bounds, we show 3 5/6 d2 + o(d) and 8 1/3 d2 + o(d), respectively. the lower bounds for division are those of multiplication. the upper bounds follow from combining the bounds for inversion and multiplication. all of the above lower bounds hold over arbitrary fields (in the case of multiplication and division) and over fields of characteristic distinct from two (in the case of squaring and inversion), respectively. all upper bounds are valid for fields that "support ffts", that is, fields that have characteristic zero and contain all roots of unity.
beyond the alder-strassen bound. we prove a lower bound of 5/2n2 - 3n for the multiplicative complexity of n × n-matrix multiplication over arbitrary fields. more general, we show that for any finite dimensional semisimple algebra a with unity, the multiplicative complexity c (a) of the multiplication in a is bounded from below by 5/2 dim a - 3(n1 +...+ nt) if the decomposition of a ≃ a1 × ... × at into simple algebras aτ ≃ dτnτ×nτ contains only noncommutative factors, that is, the division algebra dτ is noncommutative or nτ≥2.we also deal with the complexity of multiplication in algebras with nonzero radical. we present an example that shows that our methods in the semisimple case cannot be applied directly to this problem. we exhibit lower bound techniques for c(a) that yield bounds still significantly above the alder-strassen bound. the main application is the lower bound c (tn(k)) ≥ (21/8-o(1)) dim tn(k) for the multiplicative complexity of multiplication in the algebra tn(k) of upper triangular n × n-matrices.
orphan gene finding - an exon assembly approach. this paper introduces an algorithm for finding eukaryotic genes. it particularly addresses the problem of orphan genes, that is of genes that cannot, based on homology alone, be connected to any known gene family and to which it is therefore not possible to apply traditional gene finding methods. to the best of our knowledge, this is also the first algorithm that attempts to compare in an exact way two dna sequences that contain both coding (i.e. exonic) and non-coding (i.e. intronic and, possibly, intergenic) parts. the comparison is performed following an algorithmical model of a gene that is as close as possible to the biological one (we consider in this paper the "one orf, one gene" problem only). a gene is seen as a set of exons that are pieces of an assembly and are not independent. the algorithm is efficient enough: although the constants are higher than for usual sequence comparison, its time complexity is proportional to the product of the sequences lengths while its space complexity scales linearly with the length of the smallest sequence.
complexity of dna sequencing by hybridization. in the paper, the question of the complexity of the combinatorial part of the dna sequencing by hybridization, is analyzed. subproblems of the general problem, depending on the type of error (positive, negative), are distinguished. since decision versions of the subproblems assuming only one type of error are trivial, complexities of the search counterparts are studied. both search subproblems are proved to be strongly np-hard, as well as their uniquely promised versions.
on the presence of periodic configurations in turing machines and in counter machines. a configuration of a turing machine is given by a tape content together with a particular state of the machine. petr kůrka has conjectured that every turing machine--when seen as a dynamical system on the space of its configurations--has at least one periodic orbit. in this paper, we provide an explicit counterexample to this conjecture. we also consider counter machines and prove that, in this case, the problem of determining if a given machine has a periodic orbit in configuration space is undecidable.
structural operational semantics for weak bisimulations. in this study, we present rule formats for four main notions of bisimulation with silent moves. weak bisimulation is a congruence for any process algebra defined by wb cool rules; we have similar results for rooted weak bisimulation (milner''s ``observational equivalence''''), branching bisimulation, and rooted branching bisimulation. the theorems stating that, say, observational equivalence is an appropriate notion of equality for ccs are corollaries of the results of this paper. we also give sufficient conditions under which equational axiom systems can be generated from operational rules. indeed, many equational axiom systems appearing in the literature are instances of this general theory.
online learning in online auctions. we consider the problem of revenue maximization in online auctions, that is, auctions in which bids are received and dealt with one-by-one. in this paper, we demonstrate that results from online learning can be usefully applied in this context, and we derive a new auction for digital goods that achieves a constant competitive ratio with respect to the optimal (offline) fixed price revenue. this substantially improves upon the best previously known competitive ratio for this problem of o(exp(√log log h)). we also apply our techniques to the related problem of designing online posted price mechanisms, in which the seller declares a price for each of a series of buyers, and each buyer either accepts or rejects the good at that price. despite the relative lack of information in this setting, we show that online learning techniques can be used to obtain results for online posted price mechanisms which are similar to those obtained for online auctions.
bounds and constructions for unconditionally secure distributed key distribution schemes for general access structures. in this paper we investigate the issues concerning the use of a single server across a network, the key distribution center (kdc) to enable private communications within groups of users. after providing several motivations, showing the advantages related to the distribution of the task accomplished by this server, we describe a model for such a distribution, and present bounds on the amount of resources required in a real-world implementation: random bits, memory storage, and messages to be exchanged. moreover, we introduce a linear algebraic approach to design optimal schemes distributing a kdc, and we point out that some previous constructions belong to the proposed framework.
on the hardness of constructing minimal 2-connected spanning subgraphs in complete graphs with sharpened triangle inequality. in this paper we investigate the problem of finding a 2-connected spanning subgraph of minimal cost in a complete and weighted graph g. this problem is known to be apx-hard, for both the edge and the vertex connectivity case. here we prove that the apx-hardness still holds even if one restricts the edge costs to an interval [1, 1 + ε], for an arbitrary small ε > 0. this result implies the first explicit lower bound on the approximability of the general version (i.e., for arbitrary graphs) of the problem. on the other hand, if the input graph satisfies the sharpened β-triangle inequality, then a (2/3 + 1/3 ċ β/1-β)-approximation algorithm is designed. this ratio tends to 1 with β tending to ½, and it improves the previous known bound of 3/2, holding for graphs satisfying the triangle inequality, as soon as β < 5/7furthermore, a generalized problem of increasing to 2 the edge-connectivity of any spanning subgraph of g by means of a set of edges of minimum cost is considered. this problem is known to admit a 2-approximation algorithm. here we show that whenever the input graph satisfies the sharpened β-triangle inequality with β < 2/3, then this ratio can be improved to β/1-β.
primitives for authentication in process algebras. we extend the &pgr;-calculus and the spi-calculus with two primitives that guarantee authentication. they enable us to abstract from various implementations/specifications of authentication, and to obtain idealized protocols which are "secure by construction". the main underlying idea, originally proposed in focardi (proc. sixth italian conf. on theoretical computer science, november 1998) for entity authentication, is to use the locations of processes in order to check who is sending a message (authentication of a party) and who originated a message (message authentication). the theory of local names, developed in bodei et al. (theoret. comput. sci. 253(2) (2001) 155) for the &pgr;-calculus, gives us almost for free both the partner authentication and the message authentication primitives.
tilings with trichromatic colored-edges triangles. this paper studies the tilings with colored-edges triangles constructed on a triangulation of a simply connected orientable surface such that the degree of each interior vertex is even (such as, for (fundamental) example, a part of the triangular lattice of the plane). the constraints are that we only use three colors, all the colors appear in each tile and two tile can share an edge only if this edge has the same color in both tiles.using previous results on lozenge tilings, we give a linear algorithm of coloration for triangulations of the sphere, or of planar regions with the constraint that the boundary is monochromatic.we define a flip as a shift of colors on a cycle of edges using only two colors. we prove flip connectivity of the set of solutions for the cases seen above (i.e. two tiling are mutually accessible by a sequence of flips), and prove that there is no flip accessibility in the general case where the boundary is not assumed to be monochromatic. nevertheless, using flips, we obtain a tiling invariant, even in the general case.we finish relaxing the condition, allowing monochromatic triangles. with this hypothesis, some local flips are sufficient for connectivity. we give a linear algorithm of coloration, and strong structural results on the set of solutions.
on algorithms for (, gem)-free graphs. a graph is (p5, gem)-free, when it does not contain p5 (an induced path with five vertices) or a gem (a graph formed by making an universal vertex adjacent to each of the four vertices of the induced path p4) as an induced subgraph.we present o(n2) time recognition algorithms for chordal gem-free graphs and for(p5, gem)-free graphs. using a characterization of (p5, gem)-free graphs by their prime graphs with respect to modular decomposition and their modular decomposition trees [a. brandstädt, d. kratsch, on the structure of (p5, gem)-free graphs, discrete appl. math. 145 (2005), 155-166], we give linear time algorithms for the following np-complete problems on (p5, gem)-free graphs: minimum coloring; maximum weight stable set; maximum weight clique; and minimum clique cover.
equitable colorings of bounded treewidth graphs. a proper coloring of a graph g is equitable if the sizes of any two color classes differ by at most one. a proper coloring is l-bounded, when each color class has size at most l. we consider the problems to determine for a given graph g (and a given integer l) whether g has an equitable (l-bounded) k-coloring. we prove that both problems can be solved in polynomial time on graphs of bounded treewidth, and show that a precolored version remains np-complete on trees.
a fully abstract model for the exchange of information in multi-agent systems. in this paper, we present a semantic theory for the exchange of information in multi-agent systems. we consider the multi-agent programming language agent communication programming language, which integrates the paradigms of concurrent constraint programming and communicating sequential processes (csp). the constraint programming techniques are used to represent and process information, whereas the synchronous communication mechanism from csp is generalised to enable the exchange of information. the semantics of the language, which is based on a generalisation of traditional failure semantics, is shown to be fully abstract with respect to observing of each terminating computation its final global store of information.
generation problems. given a fixed computable binary operation f, we study the complexity of the following generation problem: the input consists of strings a1, ..., an, b. the question is whether b is in the closure of {a1, ..., an} under operation f.for several subclasses of operations we prove tight upper and lower bounds for the generation problems. for example, we prove exponential-time upper and lower bounds for generation problems of length-monotonic polynomial-time computable operations. other bounds involve classes like np and pspace.here, the class of bivariate polynomials with positive coefficients turns out to be the most interesting class of operations. we show that many of the corresponding generation problems belong to np. however, we do not know this for all of them, e.g., for x2 + 2y this is an open question. we prove np-completeness for polynomials xaybc where a, b, c ≥ 1. also, we show np-hardness for polynomials like x2 + 2y. as a by-product we obtain np-completeness of the extended sum-of-subset problem sosc = {(w1, ..., wn, z) : ∃i ⊆ {1, ..., n}(σi∈i wic = z)} for any c ≥ 1.
on iterating linear transformations over recognizable sets of integers. it has been known for a long time that the sets of integer vectors that are recognizable by finite-state automata are those that can be defined in an extension of presburger arithmetic. in this paper, we address the problem of deciding whether the closure of a linear transformation preserves the recognizable nature of sets of integer vectors. we solve this problem by introducing an original extension of the concept of recognizability to sets of vectors with complex components. this generalization allows to obtain a simple necessary and sufficient condition over linear transformations, in terms of the eigenvalues of the transformation matrix. we then show that these eigenvalues do not need to be computed explicitly in order to evaluate the condition, and we give a full decision procedure based on simple integer arithmetic. the proof of this result is constructive, and can be turned into an algorithm for applying the closure of a linear transformation that satisfies the condition to a finite-state representation of a set. finally, we show that the necessary and sufficient condition that we have obtained can straightforwardly be turned into a sufficient condition for linear transformations with linear guards.
counting the solutions of presburger equations without enumerating them. the number decision diagram (ndd) has recently been introduced as a powerful representation system for sets of integer vectors. ndds can notably be used for handling sets defined by arbitrary presburger formulas, which makes them well suited for representing the set of reachable states of finite-state systems extended with unbounded integer variables. in this paper, we address the problem of counting the number of distinct elements in a set of numbers or, more generally, of vectors, represented by an ndd. we give an algorithm that is able to produce an exact count without enumerating explicitly the vectors, which makes it capable of handling very large sets. as an auxiliary result, we also develop an efficient projection method that allows to construct efficiently ndds from quantified formulas, and thus makes it possible to apply our counting technique to sets specified by formulas. our algorithms have been implemented in the verification tool lash, and applied successfully to various counting problems.
an analysis of loop checking mechanisms for logic programs. we systemically study loop checking mechanisms for logic programs by considering their soundness, completeness, relative strength and related concepts. we introduce a natural concept of a simple loop check and prove that no sound and complete simple loop check exists, even for programs without function symbols. then we introduce a number of sound simple loop checks and identify natural classes of prolog programs without function symbols for which they are complete. in these classes a limited form of recursion is allowed. as a by-product we obtain an implementation of the closed world assumption of reiter and a query evaluation algorithm for these classes of logic programs.
measuring with jugs. we study the jug problem in its most general form: given a set of jugs of fixed capacities, find out which quantities are measurable, and provide upper and lower bounds on the number of steps necessary for measurements.
independent domination in finitely defined classes of graphs. we study the independent dominating set problem restricted to graph classes defined by finitely many forbidden induced subgraphs. the main result is two sufficient conditions for the problem to be np-hard in a finitely defined class of graphs. we conjecture that those conditions are also necessary and describe several classes of graphs verifying the conjecture.
message-passing automata are expressively equivalent to emso logic. we study the expressiveness of finite message-passing automata with a priori unbounded fifo channels and show them to capture exactly the class of msc languages that are definable in existential monadic second-order logic interpreted over mscs. furthermore, we prove the monadic quantifier-alternation hierarchy over mscs to be infinite and conclude that the class of msc languages accepted by message-passing automata is not closed under complement.
parity graph-driven read-once branching programs and an exponential lower bound for integer multiplication. branching programs are a well-established computation model for boolean functions, especially read-once branching programs have been studied intensively. exponential lower bounds for read-once branching programs are known for a long time. on the other hand, the problem of proving superpolynomial lower bounds for parity read-once branching programs is still open. in this paper restricted parity read-once branching programs are considered and an exponential lower bound on the size of the so-called well-structured parity graph-driven read-once branching programs for integer multiplication is proven. this is the first strongly exponential lower bound on the size of a parity nonoblivious read-once branching program model for an explicitly defined boolean function. in addition, more insight into the structure of integer multiplication is yielded.
union of shadows. our aim in this note is to show that if a is a family of (k 3) 3-sets then there are at least (k 4) 4-sets that may be written as unions of two 2-sets in the shadow of a. this is the first non-trivial case of a more general conjecture about unions of shadows.
a hierarchy of failures-based models: theory and application. consistency between a process and its specification expressed in csp is typically presented as a refinement check. within the traces model consistency is measured by examining only the traces of the systems, whilst in the finer stable failures model the possibility of subsequently refusing a combination of events is also taken into consideration.in this paper, we begin by motivating the need for alternative measures of consistency. we then identify the failures class-a class of semantic models for describing concurrent systems in which each model is associated with a predicate that determines how much availability information is recorded. we show how refinement within members of this class corresponds to confirmation of non-standard measures of consistency, and identify application areas for these measures of consistency. we show how refinement in each model can be automatically tested.we also carry out a theoretical examination of the failures class. we prove that the class forms a complete lattice, and investigate the positions of particular models within that lattice. we also identify the maximal subset of the language over which each model is compositional.
polynomial equation solving by lifting procedures for ramified fibers. let be given a parametric polynomial equation system which represents a generically unramified family of zero-dimensional algebraic varieties. we exhibit an efficient algorithm which computes a complete description of the solution set of an arbitrary parameter instance from a complete description of the infinitesimal structure of a particular ramified parameter instance of our family. this generalizes in the case of space curves previous methods of heintz et al. and schost, which require the given parameter instance to be unramified. we illustrate our method solving particular polynomial equation systems by deformation techniques.
normalisation for higher-order calculi with explicit substitutions. explicit substitutions (es) were introduced as a bridge between the theory of rewrite systems with binders and substitution, such as the λ-calculus, and their implementation. in a seminal paper melliès observed that the dynamical properties of a rewrite system and its es-based implementation may not coincide: he showed that a strongly normalising term (i.e. one which does not admit infinite derivations) in the λ-calculus may lose this status in its es-based implementation. this paper studies normalisation for the latter systems in the general setting of higher-order rewriting: based on recent work extending the theory of needed strategies to non-orthogonal rewrite systems we show that needed strategies normalise in the es-based implementation of any orthogonal pattern higher-order rewrite system.
when ambients cannot be opened. we investigate expressiveness of a fragment of the ambient calculus, a formalism for describing distributed and mobile computations. more precisely, we study expressiveness of the pure and public ambient calculus from which the capability open has been removed, in terms of the reachability problem of the reduction relation. surprisingly, we show that even for this very restricted fragment, the reachability problem is not decidable. at a second step, for a slightly weaker reduction relation, we prove that reachability can be decided by reducing this problem to markings reachability for petri nets. finally, we show that the name-convergence problem as well as the model-checking problem turn out to be undecidable for both the original and the weaker reduction relation.
watermelon uniform random generation with applications. watermelons are particular configurations of vicious walkers. in these configurations, each path starts and ends at the same ordinate. we present a simple uniform random generation algorithm of watermelons based on enumeration formulas of star configurations (with or without a wall). the performance of this algorithm is better than earlier ones in the case of watermelons with few walkers.using appropriate bijections, these algorithms can also generate underdiagonal paths, realizers (or schnyder trees), twin parallelogram polyominoes according to their perimeter and width, baxter permutations according to the number of rises, etc. moreover, we present some experimental results on the height of watermelons and realizers.
randomness in secret sharing and visual cryptography schemes. secret sharing schemes allow a secret to be shared among a group of participants so that only qualified subsets of participants can recover the secret. a visual cryptography scheme (vcs) is a special kind of secret sharing scheme in which the secret to share consists of an image and the shares consist of xeroxed transparencies which are stacked to recover the shared image.in this paper, we analyze the relationship between secret sharing schemes and vcss, focusing our attention on the amount of randomness required to generate the shares. we prove that secret sharing schemes for a set of secrets of size two (bsss) and vcss are "equivalent" with respect to the randomness. indeed, we show how to transform a bss for a given access structure into a vcs for the same access structure while preserving the randomness of the original scheme. we provide both upper and lower bounds on the randomness of bsss.all vcss presented in this paper allow a perfect reconstruction of black pixels.
constructions of generalized superimposed codes with applications to group testing and conflict resolution in multiple access channels. in this paper we introduce a parameterized generalization of the well known superimposed codes. we give algorithms for their construction and provide non-existential results. we apply our new combinatorial structures to the efficient solution of new group testing problems and access coordination issues in multiple access channels.
the structure of reflexive regular splicing languages via sch6uuml;tzenberger constants. the splicing operation was introduced in 1987 by head as a mathematical model of the recombination of dna molecules under the influence of restriction and ligases enzymes. this operation allows us to define a computing (language generating) device, called a splicing system. other variants of this original definition were also proposed by paun and pixton respectively. the computational power of splicing systems has been thoroughly investigated. nevertheless, an interesting problem is still open, namely the characterization of the class of regular languages generated by finite splicing systems. in this paper, we will solve the problem for a special class of finite splicing systems, termed reflexive splicing systems, according to each of the definitions of splicing given by paun and pixton. this special class of systems contains, in perticular, finite head splicing systems. the notion of a constant, given by schützenberger, once again intervenes.
regular splicing languages and subclasses. recent developments in the theory of finite splicing systems have revealed surprising connections between long-standing notions in the formal language theory and splicing operation. more precisely, the syntactic monoid and schützenberger constant have strong interaction with the investigation of regular splicing languages. this paper surveys results of structural characterization of classes of regular splicing languages based on the above two notions and discusses basic questions that motivate further investigations in this field.in particular, we improve the result in [6] that provides a structural characterization of reflexive symmetric splicing languages by showing that it can be extended to the class of all reflexive splicing languages: this is the larger class for which a characterization is known.
reconciling a gene tree to a species tree under the duplication cost model. the general problem of reconciling the information from evolutionary trees representing the relationships between distinct gene families is of great importance in bioinformatics and has been popularized among the computer science researchers by ma et al. [from gene trees to species trees, siam j. comput. 30(3) (2000) 729-752] where the authors pose the intriguing question if a certain definition of minimum tree that reconciles a gene tree and a species tree is correct. we answer affirmatively to this question; moreover, we show an efficient algorithm for computing such minimum-leaf reconciliation trees and prove the uniqueness of such trees. we then tackle some different versions of the biological problem by showing that the exemplar problem, arising from the exemplar analysis of multigene genomes, is np-hard even when the number of copies of a given label is at most two. finally, we introduce two novel formulations for the problem of recombining evolutionary trees, extending the gene duplication problem studied in [ma et al., from gene trees to species trees, siam j. comput. 30(3) (2000) 729-752; m. fellows et al., on the multiple gene duplication problem, in: proc. ninth internat. symp. on algorithms and computation (isaac98), 1998; r. page, maps between trees and cladistic analysis of historical associations among genes, systematic biology 43 (1994) 58-77; r.m. page, j. cotton, vertebrate phylogenomics: reconciled trees and gene duplications, in: proc. pacific symp. on biocomputing 2002 (psb2002), 2002, pp. 536-547; r. guigò et al., reconstruction of ancient molecular phylogeny, mol. phy. and evol. 6(2) (1996) 189-213], and we give an exact algorithm (via dynamic programming) for one of these formulations.
a transition system semantics for the control-driven coordination language manifold. coordination languages are a new class of parallel programming languages which manage the interactions among concurrent programs. basically, coordination is achieved either by manipulating data values shared among all active processes or by dynamically evolving the interconnections among the processes as a consequence of observations of their state changes. the latter, also called control-driven coordination, is supported by manifold. we present the formal semantics of a kernel of manifold, based on a two-level transition system model: the first level is used to specify the ideal behavior of each single component in a manifold system, whereas the second level captures their interactions. although we apply our two-level model in this paper to define the semantics of a control-oriented coordination language, this approach is useful for the formal studies of other coordination models and languages as well.
generalized metric spaces: completion, topology, and powerdomains via the yoneda embedding. generalized metric spaces are a common generalization of preorders and ordinary metric spaces (lawvere 1973). combining lawvere''s (1973) enriched-categorical and smyth'' (1988, 1991) topological view on generalized metric spaces, it is shown how to construct 1. completion, 2. topology, and 3. powerdomains for generalized metric spaces. restricted to the special cases of preorders and ordinary metric spaces, these constructions yield, respectively: 1. chain completion and cauchy completion; 2. the alexandroff and the scott topology, and the epsilon-ball topology; 3. lower, upper, and convex powerdomains, and the hyperspace of compact subsets. all constructions are formulated in terms of (a metric version of) the yoneda (1954) embedding.
context-freeness of the power of context-free languages is undecidable. the power of a language l is the set of all powers of the words in l. in this paper, the following decision problem is investigated. given a context-free language l, is the power of l context-free? we show that this problem is decidable for languages over unary alphabets, but it is undecidable whenever languages over alphabets with at least two letters are considered.
on the number of components in cooperating distributed grammar systems. it is proved that the number of components in context-free cooperating distributed (cd) grammar systems can be reduced to 3 when they are working in the so-called sf-mode of derivation, which is the cooperation protocol which has been considered first for cd grammar systems, in this derivation mode, a component continues the derivation until and unless there is a nonterminal in the sentential form which cannot be rewritten according to that component. moreover, it is shown that cd grammar systems in sf-mode with only one component can generate only the context-free languages but they can generate non-context-free languages if two components are used. the sf-mode of derivation is compared with other well-known cooperation protocols with respect to the hierarchies induced by the number of components.
a method for symbolic analysis of security protocols. in security protocols, message exchange between the intruder and honest participants induces a form of state explosion which makes protocol models infinite. we propose a general method for automatic analysis of security protocols based on the notion of frame, essentially a rewrite system plus a set of distinguished terms called messages. frames are intended to model generic crypto-systems. based on frames, we introduce a process language akin to abadi and fournet's applied pi. for this language, we define a symbolic operational semantics that relies on unification and provides finite and effective protocol models. next, we give a method to carry out trace analysis directly on the symbolic model. we spell out a regularity condition on the underlying frame, which guarantees completeness of our method for the considered class of properties, including secrecy and various forms of authentication. we show how to instantiate our method to some of the most common crypto-systems, including shared-and public-key encryption, hashing and diffie-hellman key exchange.
processes as formal power series: a coinductive approach to denotational semantics. we characterize must testing equivalence on csp in terms of the unique homomorphism from the moore automaton of csp processes to the final moore automaton of partial formal power series over a certain semiring. the final automaton is then turned into a csp-algebra: operators and fixpoints are defined, respectively, via behavioural differential equations and simulation relations. this structure is then shown to be preserved by the final homomorphism. as a result, we obtain a fully abstract compositional model of csp phrased in purely set-theoretical terms.
divergence in testing and readiness semantics. many variants of must-testing semantics have been put forward that are equally sensitive to deadlock, but differ for the stress they put on divergence, i.e. on the possibility for systems of getting involved in infinite internal computations. safe-testing is one such variant, that naturally pops up when studying the behavioural pre-congruences induced by certain basic observables. here, we study the relationship between safe-testing and olderog's readiness semantics, a semantics induced by a natural process logic. we show that safe-testing is finer than readiness, and coincides with a refinement of readiness obtained by tuning olderog's definition. for both safe-testing and the original readiness semantics we propose simple complete axiomatizations, which permit a fuller appreciation of their similarities and differences. copyright 2001 elsevier science b.v.
palindromic factors of billiard words. we study palindromic factors of billiard words, in any dimension. there are differences between the two-dimensional case, and higher dimension. arbitrary long palindrome factors exist in any dimension, but arbitrary long palindromic prefixes exist in general only in dimension 2.
a high-level modular definition of the semantics of c#. we propose a structured mathematical definition of the semantics of c# programs to provide a platform-independent interpreter view of the language for the c# programmer, which can also be used for a precise analysis of the ecma standard of the language and as a reference model for teaching. the definition takes care to reflect directly and faithfully--as much as possible without becoming inconsistent or incomplete--the descriptions in the c# standard to become comparable with the corresponding models for java in stärk et al. (java and java virtual machine--definition, verification, validation, springer, berlin, 2001) and to provide for implementors the possibility to check their basic design decisions against an accurate high-level model. the model sheds light on some of the dark corners of c# and on some critical differences between the ecma standard and the implementations of the language.
flow metrics. we introduce flow metrics as a relaxation of path metrics (i.e. linear orderings). they are defined by polynomial-sized linear programs and have interesting properties including spreading. we use them to obtain relaxations for several np-hard linear ordering problems such as minimum linear arrangement and minimum pathwidth. our approach has the advantage of achieving the best-known approximation guarantees for these problems using the same relaxation and essentially the same rounding algorithm for all the problems while varying only the objective function from problem to problem. this is in contrast to the current state of the literature where each problem either has a new relaxation or a new rounding or both. we also characterize a natural projection of the flow polyhedron.
elan from a rewriting logic point of view. elan implements computational systems, a concept that combines two first class entities: rewrite rules and rewriting strategies. elan can be used either as a logical framework or to describe and execute deterministic as well as non-deterministic rule-based processes. with the general goal to make precise a rewriting logic-based semantics of elan, this paper has three contributions: a presentation of the concepts of rules and strategies available in elan, an expression of rewrite rules with matching conditions in conditional rewriting logic, and finally an enrichment mechanism of a rewrite theory into a strategy theory in conditional rewriting logic.
logical systems for structured specifications. we study proof systems for reasoning about logical consequences and refinement of structured specifications, based on similar systems proposed earlier in the literature (inform. and comput. 76 (1988) 165; in: f.l. bauer, w. brauer, h. schwichtenberg (eds.), logic and algebra of specification, nato asi series f: computer and systems sciences, vol. 94, springer, berlin, 1991, p. 411). following goguen and burstall, the notion of an underlying logical system over which we build specifications is formalized as an institution and extended to a more general notion, called (d, j)-institution. we show that under simple assumptions (essentially: amalgamation and interpolation) the proposed proof systems are sound and complete. the completeness proofs are inspired by proofs due to cengarle (ph.d. thesis, institut für informatik, ludwig-maximilians-universität müenchen, 1994) for specifications in first-order logic and the logical systems for reasoning about them. we then propose a methodology for reusing proof systems built over institutions rich enough to satisfy the properties required for the completeness results for specifications built over poorer institutions where these properties need not hold.
transition systems without transitions. we study the problem of embedding partial 2-structures into set 2-structures such that the target structure is full and forward closed and it is minimal w.r.t, these properties.ehrenfeucht and rozenberg introduced the notion of partial 2-structures--an abstract form of transition systems--and studied the problem of representing them as partial set 2-structures--directed graphs made of sets and their ordered symmetric differences. they constructed a representation and gave the conditions under which the representation is an isomorphism.we propose an alternative representation of partial 2-structures by partial set 2-structures which are complete graphs, hence their transitions may be left implicit, yielding a static representation of dynamic systems.
competitive online routing in geometric graphs. we consider online routing algorithms for finding paths between the vertices of plane graphs. although it has been shown in bose et al. (internat. j. comput. geom. 12(4) (2002) 283) that there exists no competitive routing scheme that works on all triangulations, we show that there exists a simple online o(1)-memory c-competitive routing strategy that approximates the shortest path in triangulations possessing the diamond property, i.e., the total distance travelled by the algorithm to route a message between two vertices is at most a constant c times the shortest path. our results imply a competitive routing strategy for certain classical triangulations such as the delaunay, greedy, or minimum-weight triangulation, since they all possess the diamond property. we then generalize our results to show that the o(1)-memory c-competitive routing strategy works for all plane graphs possessing both the diamond property and the good convex polygon property.
automatic verification of recursive procedures with one integer parameter. context-free processes (bpa) have been used for dataflow analysis in recursive procedures with applications in optimizing compilers (proceedings of fossacs'99, lecture notes in computer science, vol. 1578, springer, berlin, 1999, pp. 14-30). we introduce a more refined model called bpa(z) that can model not only recursive dependencies, but also the passing of an integer parameter to a subroutine. moreover, this parameter can be tested against conditions expressible in presburger arithmetic. this new and more expressive model can still be analyzed automatically. we define z-input 1-cm, a new class of 1-counter machines (cm) that take integer numbers as input, to describe sets of configurations of bpa(z). we show that the post* (the set of successors) of a set of bpa(z)-configurations described by a z-input 1-cm can be effectively constructed. the pre* (set of predecessors) of a regular set can be effectively constructed as well. however, the pre* of a set described by a z-input 1-cm cannot be represented by a z-input 1-cm, in general, and has an undecidable membership problem. then we develop a new temporal logic based on reversal-bounded counter machines (i.e. machines which use counters such that the change between increasing and decreasing mode of each counter is bounded (j. assoc. comput. mach. 25 (1978) 116) that can be used to describe properties of bpa(z) and show that the model-checking problem is decidable.
model checking for time petri nets. this paper aims at applying the ctl* model checking method to the time petri net (tpn) model. we show here how to contract its generally infinite state space into a graph that captures all its ctl* properties. this graph, called atomic state class graph (ascg), is finite if and only if, the model is bounded. our approach is based on a partition refinement technique, similarly to what is proposed in [berthomieu, vernadat, state class constructions for branching analysis of time petri nets, lecture notes in computer science, vol. 2619, 2003; yoneda, ryuba, ctl model checking of time petri nets using geometric regions, ieice trans. inf. syst. e99-d(3) (1998)]. in such a technique, an intermediate abstraction (contraction) of the tpn state space is first built, then refined until ctl* properties are restored. our approach improves the construction of the ascg in two ways. the first way deals with speeding up the refinement process by using a much more compact intermediate contraction of the tpn state space than those used in [berthomieu, vernadat, state class constructions for branching analysis of time petri nets, lecture notes in computer science, vol. 2619, 2003; yoneda, ryuba, ctl model checking of time petri nets using geometric regions, ieice trans. inf. syst. e99-d(3) (1998)]. the second way deals with computing each ascg node in o(n2) instead of o(n3), n being the number of transitions enabled at the node. experimental results have shown that our improvements have a good impact on performances.
listing all potential maximal cliques of a graph. a potential maximal clique of a graph is a vertex set that induces a maximal clique in some minimal triangulation of that graph. it is known that if these objects can be listed in polynomial time for a class of graphs, the treewidth and the minimum fill-in are polynomially tractable for these graphs. we show here that the potential maximal cliques of a graph can be generated in polynomial time in the number of minimal separators of the graph. thus, the treewidth and the minimum fill-in are polynomially tractable for all classes of graphs with a polynomial number of minimal separators.
noninterference for concurrent programs and thread systems. we propose a type system to ensure the property of noninterference in a system of concurrent programs, described in a standard imperative language enriched with parallelism. our proposal is in the line of some recent work by irvine, volpano and smith. our type system seems more natural and less restrictive than that originally presented by these authors for the concurrent case. moreover, we show how to extend the language in order to formalise scheduling policies for systems of sequential threads. the type system is extended to the new constructs, and we show that noninterference still holds, while remaining in a nonprobabilistic setting.
reconstructing (h, v)-convex 2-dimensional patterns of objects from approximate horizontal and vertical projections. the problem of reconstructing a pattern of an object from its approximate discrete orthogonal projections in a 2-dimensional grid, may have no solution because the inaccuracy in the measurements of the projections may generate an inconsistent problem. to attempt to overcome this difficulty, one seeks to reconstruct a pattern with projection values having possibly some bounded differences with the given projection values and minimizing the sum of the absolute differences.this paper addresses the problem of reconstructing a pattern with a difference at most equal to +1 or -1 between each of its projection values and the corresponding given projection value. we deal with the case of patterns which have to be horizontally and vertically convex and the case of patterns which have to be moreover connected, the so-called convex polyominoes. we show that in both cases, the problem of reconstructing a pattern can be transformed into a satisfiability (sat) problem. this is done in order to take advantage of the recent advances in the design of solvers for the sat problem. we show, experimentally, that by adding two important features to csat (an efficient sat solver), optimal patterns can be found if there exist feasible ones. these two features are: first, a method that extracts in linear time an optimal pattern from a set of feasible patterns grouped in a generic pattern (obtaining a generic pattern may be exponential in the worst case) and second, a method that computes actively a lower bound of the sum of absolute differences that can be obtained from a partially defined pattern. this allows to prune the search tree if this lower bound exceeds the best sum of absolute differences found so far.
observational proofs by rewriting. observability concepts contribute to a better understanding of software correctness. in order to prove observational properties, the concept of context induction has been developed by hennicker (hennicker, formal aspects of computing 3(4) (1991) 326-345). we propose in this paper to embed context induction in the implicit induction framework of (bouhoula and rusinowitch, journal of automated reasoning 14(2) (1995) 189-235). the proof system we obtain applies to conditional specifications. it allows for many rewriting techniques and for the refutation of false observational conjectures. under reasonable assumptions our method is refutationally complete, i.e. it can refute any conjecture which is not observationally valid. moreover this proof system is operational: it has been implemented within the spike prover and interesting computer experiments are reported.
counting with range concatenation grammars. the class of range concatenation grammars appears to be a convincing challenger as a syntactic base for various tasks, especially in natural language processing. these grammars are powerful, since they strictly contain the class of mildly context-sensitive formalisms, while staying computationally tractable, since their sentences can be parsed in polynomial time. the output of their parsers are structures of polynomial size that can be seen as a generalization of classical context-free shared forest. moreover, this formalism allows a form of modularity which may lead to the design of libraries of reusable grammatical components. and, finally, it can act as a syntactic backbone upon which decorations from other domains (say feature structures) can be grafted. in this paper we explore the behavior of range concatenation grammars in counting, a domain in which bad reputation of other classical syntactic formalisms is well known. this study leads to some surprising results.
entropy rates and finite-state dimension. the effective fractal dimensions at the polynomial-space level and above can all be equivalently defined as the c-entropy rate where c is the class of languages corresponding to the level of effectivization. for example, pspace-dimension is equivalent to the pspace-entropy rate.at lower levels of complexity the equivalence proofs break down. in the polynomial-time case, the p-entropy rate is a lower bound on the p-dimension. equality seems unlikely, but separating the p-entropy rate from p-dimension would require proving p ≠ np.we show that at the finite-state level, the opposite of the polynomial-time case happens: the reg-entropy rate is an upper bound on the finite-state dimension. we also use the finite-state genericity of ambos-spies and busse [automatic forcing and genericity: on the diagonalization strength of finit automata, in: proc. fourth int. conf. on discrete mathematics and theoretical computer science, 2003, springer, berlin, pp. 97-108] to separate finite-state dimension from the reg-entropy rate.however, we point out that a block-entropy rate characterization of finite-state dimension follows from the work of ziv and lempel [compression of individual sequences via variable rate coding, ieee trans. inform. theory 24 (1978) 530-536] on finite-state compressibility and the compressibility characterization of finite-state dimension by dai et al. [finite-state dimension, theoret. comput. sci. 310(1-3) (2004) 1-33].as applications of the reg-entropy rate upper bound and the block-entropy rate characterization, we prove that every regular language has finite-state dimension 0 and that normality is equivalent to finite-state dimension 1.
elementarily computable functions over the real numbers and r-sub-recursive functions. we present an analog and machine-independent algebraic characterization of elementarily computable functions over the real numbers in the sense of recursive analysis: we prove that they correspond to the smallest class of functions that contains some basic functions, and closed by composition, linear integration, and a simple limit schema.we generalize this result to all higher levels of the grzegorczyk hierarchy.this paper improves several previous partial characterizations and has a dual interest: • concerning recursive analysis, our results provide machine-independent characterizations of natural classes of computable functions over the real numbers, allowing to define these classes without usual considerations on higher-order (type 2) turing machines. • concerning analog models, our results provide a characterization of the power of a natural class of analog models over the real numbers and provide new insights for understanding the relations between several analog computational models.
chess endgames: 6-man data and strategy. while nalimov's endgame tables for western chess are the most used today, their depth-to-mate metric is not the most efficient or effective in use. the authors have developed and used new programs to create tables to alternative metrics and recommend better strategies for endgame play.
walks confined in a quadrant are not always d-finite. we consider planar lattice walks that start from a prescribed position, take their steps in a given finite subset of z2, and always stay in the quadrant x ≥ 0, y ≥ 0. we first give a criterion which guarantees that the length generating function of these walks is d-finite, that is, satisfies a linear differential equation with polynomial coefficients. this criterion applies, among others, to the ordinary square lattice walks. then, we prove that walks that start from (1,1), take their steps in {(2,-1), (-1, 2)} and stay in the first quadrant have a non-d-finite generating function. our proof relies on a functional equation satisfied by this generating function, and on elementary complex analysis.
two bijective proofs for the arborescent form of the good-lagrange formula and some applications to colored rooted trees and cacti. goulden and kulkarni (j. combin. theory ser. a 80 (2) (1997) 295) give a bijective proof of an arborescent form of the good-lagrange multivariable inversion formula. this formula was first stated explicitly by bender and richmond (electron. j. combin. 5 (1) (1998) 4pp) but is implicit in goulden and kulkarni (1997). in this paper, we propose two new simple bijective proofs of this formula and we illustrate the interest of these proofs by applying them to the enumeration and random generation of colored rooted trees and rooted m-ary cacti.
updatable timed automata. we investigate extensions of alur and dill's timed automata, based on the possibility to update the clocks in a more elaborate way than simply reset them to zero. we call these automata updatable timed automata. they form an undecidable class of models, in the sense that emptiness checking is not decidable. however, using an extension of the region graph construction, we exhibit interesting decidable subclasses. in a surprising way, decidability depends on the nature of the clock constraints which are used, diagonal-free or not, whereas these constraints play identical roles in timed automata. we thus describe in a quite precise way the thin frontier between decidable and undecidable classes of updatable timed automata.we also study the expressive power of updatable timed automata. it turns out that any up-datable automaton belonging to some decidable subclass can be effectively transformed into an equivalent timed automaton without updates but with silent transitions. the transformation suffers from an enormous combinatorics blow-up which seems unavoidable. therefore, updatable timed automata appear to be a concise model for representing and analyzing large classes of timed systems.
the maximum resource bin packing problem. usually, for bin packing problems, we try to minimize the number of bins used or in the case of the dual bin packing problem, maximize the number or total size of accepted items. this paper presents results for the opposite problems, where we would like to maximize the number of bins used or minimize the number or total size of accepted items. we consider off-line and on-line variants of the problems.for the off-line variant, we require that there be an ordering of the bins, so that no item in a later bin fits in an earlier bin. we find the approximation ratios of two natural approximation algorithms, first-fit-increasing and first-fit-decreasing for the maximum resource variant of classical bin packing.for the on-line variant, we define maximum resource variants of classical and dual bin packing. for dual bin packing, no on-line algorithm is competitive. for classical bin packing, we find the competitive ratio of various natural algorithms.we study the general versions of the problems as well as the parameterized versions where there is an upper bound of 1/k on the item sizes, for some integer k.
efficient exhaustive listings of reversible one dimensional cellular automata. this paper looks at an algebraic formulation of one dimensional cellular automata. using the formulation connections to combinatorial structures and graph theory become clear. strong results about uniqueness and isomorphism allows us to outline effective algorithms for the generation of exhaustive lists of reversible one dimensional cellular automata, and to count the number of distinct examples that exist. these algorithms use the "orderly algorithm" methods to avoid the pitfalls of brute force searches.
model checking for process rewrite systems and a class of action-based regular properties. we consider the model checking problem for process rewrite systems (prs), an infinite-state formalism (non turing-powerful) which subsumes many common models such as pushdown processes and petri nets. prs can be adopted as a formal model for programs with dynamic creation and synchronization of concurrent processes, and with recursive procedures. the model-checking problem of prs against action-based linear temporal logic (altl) is undecidable. however, decidability for some interesting fragment of altl remains an open question. in this paper, we state decidability results concerning generalized acceptance properties about infinite derivations (infinite term rewriting) in prs. as a consequence, we obtain decidability of the model-checking problem (restricted to infinite runs) of prs against a meaningful fragment of altl.
labelled domains and automata with concurrency. we investigate an operational model of concurrent systems, called automata with concurrency relations. these are labelled transition systems a in which the event set is endowed with a collection of binary concurrency relations which indicate when two events, in a particular state of the automaton, commute. this model generalizes asynchronous transition systems, and as in trace theory we obtain, through a permutation equivalence for computation sequences of a , an induced domain da, &le; . here, we construct a categorical equivalence between a large category of (&ldquo;cancellative&rdquo;) automata with concurrency relations and the associated domains. we show that each cancellative automaton can be reduced to a minimal cancellative automaton generating, up to isomorphism, the same domain. furthermore, when fixing the event set, this minimal automaton is unique. &mdash;authors' abstract
finite graph automata for linear and boundary graph languages. graph grammars can be regarded as a generalization of context-free grammars from strings to graphs. over the past 30 years a rich theory of graph grammars and their languages has been developed. however, there are no graph automata. there is no duality between generative and recognizing devices, as it is known for the chomsky hierarchy of formal languages.here we introduce graph automata as devices for the recognition of sets of undirected node labelled graphs. a graph automaton consists of a finite state control, a finite set of instructions, and a collection of heads or guards. it reads an input graph in a systematic way and performs a graph search directed by the instructions. as our main results we show that finite graph automata recognize exactly the set of graph languages generated by linear nce graph grammars and that alternating finite graph automata recognize exactly the languages of boundary graph grammars. finally, we generalize some automata theoretic properties from string to graph automata, integrate the connectivity of graphs into graph automata, and explain why graph automata cannot be generalized to deal with dynamic edge relabellings and ence graph languages.
tree spanners on chordal graphs: complexity and algorithms. a tree t-spanner t in a graph g is a spanning tree of g such that the distance in t between every pair of vertices is at most t times their distance in g. the tree t-spanner problem asks whether a graph admits a tree t-spanner, given t. we substantially strengthen the hardness result of cai and corneil (siam j. discrete math. 8 (1995) 359-387) by showing that, for any t ≥ 4, tree t-spanner is np-complete even on chordal graphs of diameter at most t + 1 (if t is even), respectively, at most t + 2 (if t is odd). then we point out that every chordal graph of diameter at most t - 1 (respectively, t - 2) admits a tree t-spanner whenever t ≥ 2 is even (respectively, t ≥ 3 is odd), and such a tree spanner can be constructed in linear time.the complexity status of tree 3-spanner still remains open for chordal graphs, even on the subclass of undirected path graphs that are strongly chordal as well. for other important subclasses of chordal graphs, such as very strongly chordal graphs (containing all interval graphs), 1-split graphs (containing all split graphs) and chordal graphs of diameter at most 2, we are able to decide tree 3-spanner efficiently.
recursive quasi-metric spaces. in computable analysis recursive metric spaces play an important role, since these are, roughly speaking, spaces with computable metric and limit operation. unfortunately, the concept of a metric space is not powerful enough to capture all interesting phenomena which occur in computable analysis. some computable objects are naturally considered as elements of asymmetric spaces which are not metrizable. nevertheless, most of these spaces are t0-spaces with countable bases and thus at least quasi-metrizable. we introduce a definition of recursive quasi-metric spaces in analogy to recursive metric spaces. we show that this concept leads to similar results as in the metric case and we prove that the most important spaces of computable analysis can be naturally considered as recursive quasi-metric spaces. especially, we discuss some hyper and function spaces.
topological properties of real number representations. we prove three results about representations of real numbers (or elements of other topological spaces) by infinite strings. such representations are useful for the description of real number computations performed by digital computers or by turing machines. first, we show that the so-called admissible representations, a topologically natural class of representations introduced by kreitz and weihrauch, are essentially the continuous extensions (with a well-behaved domain) of continuous and open representations. second, we show that there is no admissible representation of the real numbers such that every real number has only finitely many names. third, we show that a rather interesting property of admissible real number representations holds true also for a certain non-admissible representation, namely for the naive cauchy representation: the property that continuity is equivalent to relative continuity with respect to the representation.
computability on subsets of metric spaces. the notions "recursively enumerable" and "recursive" are the basic notions of effectivity in classical recursion theory. in computable analysis, these notions are generalized to closed subsets of euclidean space using their metric distance functions. we study a further generalization of these concepts to subsets of computable metric spaces. it appears that different characterizations, which coincide in case of euclidean space, lead to different notions in the general case. however, under certain additional conditions, such as completeness and effective local compactness, the situation is similar to the euclidean case. we present all results in the framework of "type-2 theory of effectivity" which allows to express effectivity properties in a very uniform way: instead of comparing properties of single subsets, we compare corresponding representations of the hyperspace of closed subsets. such representations do not only induce a concept of computability for single subsets, but they even yield a concept of computability for operations on hyperspaces, such as union, intersection, etc. we complete our investigation by studying the special situation of compact subsets.
discrete time generative-reactive probabilistic processes with different advancing speeds. we present a process algebra expressing probabilistic external/internal choices, multi-way synchronizations, and processes with different advancing speeds in the context of discrete time, i.e. where time is not continuous but is represented by a sequence of discrete steps as in discrete time markov chains (dtmcs). to this end, we introduce a variant of csp that employs a probabilistic asynchronous parallel operator whose synchronization mechanism is based on a mixture of the classical generative and reactive models of probability. in particular, differently from existing discrete time process algebras, where parallel processes are executed in synchronous locksteps, the parallel operator that we adopt allows processes with different probabilistic advancing speeds (mean number of actions executed per time unit) to be modeled. moreover, our generative-reactive synchronization mechanism makes it possible to always derive dtmcs in the case of fully specified systems. we then present a sound and complete axiomatization of probabilistic bisimulation over finite processes of our calculus, that is a smooth extension of the axiom system for a standard process algebra, thus solving the open problem of cleanly axiomatizing action restriction in the generative model. as a further result, we show that, when evaluating steady state based performance measures which are expressible by attaching rewards to actions, our approach provides an exact solution even if the advancing speeds are considered not to be probabilistic, without incurring the state space explosion problem that arises with standard synchronous approaches. we finally present a case study on multi-path routing showing the expressiveness of our calculus and that it makes it particularly easy to produce scalable specifications.
the theory of interactive generalized semi-markov processes. in this paper we introduce the calculus of interactive generalized semi-markov processes (igsmps), a stochastic process algebra which can express probabilistic timed delays with general distributions and synchronizable actions with zero duration, and where choices may be probabilistic, non-deterministic and prioritized. igsmp is equipped with a structural operational semantics which generates semantic models in the form of generalized semi-markov processes (gsmps), i.e. probabilistic systems with generally distributed time, extended with action transitions representing interaction among system components. this is obtained by expressing the concurrent execution of delays through a variant of st semantics which is based on dynamic names. the fact that names for delays are generated dynamically by the semantics makes it possible to define a notion of observational congruence for igsmp (that abstracts from internal actions with zero duration) simply as a combination of standard observational congruence and probabilistic bisimulation. we also present a complete axiomatization for observational congruence over igsmp. finally, we show how to derive a gsmp from a given igsmp specification in order to evaluate the system performance and we present a case study.
quantitative information in the tuple space coordination model. tuple spaces is a well-known coordination model at the basis of coordination languages such as linda, javaspaces and tspaces. tuple spaces are flat and unstructured multisets of tuples that can be accessed via output, read, and input operations. we investigate, from an expressiveness viewpoint, the impact of the introduction of quantitative information in the tuple space coordination model in order to quantify the relevance or importance of each tuple. we consider two possible interpretations for this information: in the first case it quantifies a weight indicating how much frequently each tuple should be retrieved, in the second case it expresses a priority level for the tuples.
strand design for biomolecular computation. the design of dna or rna strands for dna computations poses many new questions in algorithms and coding theory. dna strand design also arises in use of molecular bar codes to manipulate and identify individual molecules in complex chemical libraries, and to attach molecules to dna chips. we survey several formulations of the dna strand design problem, along with results and open questions in this area.
compatible topologies on graphs: an application to graph isomorphism problem complexity. in one hand the graph isomorphism problem (gi) has received considerable attention due to its unresolved complexity status and is many practical applications. on the other hand a notion of compatible topologies on graphs has emerged from digital topology (see [a. bretto, comparability graphs and digital topology, comput. vision graphic image process. (image understanding), 82 (2001) 33-41; j.m. chassery, connectivity and consecutivity in digital pictures, comput. vision graphic image process. 9 (1979) 294-300; l.j. latecki, topological connectedness and 8-connectness in digital pictures, cvgip image understanding 57(2) (1993) 261-262; u. eckhardt, l.j. latecki, topologies for digital spaces z2 and z3, comput. vision image understanding 95 (2003) 261-262; t.y. kong, r. kopperman, p.r. meyer, a topological approach to digital topology, amer. math. monthly archive 98(12) (1991) 901-917; r. kopperman, topological digital topology, discrete geometry for computer imagery, 11th international conference, lecture notes in computer science, vol. 2886, dgci 2003, naples, italy, november 19-21, pp. 1-15]).in this article we study gi from the topological point of view. firstly, we explore the poset of compatible topologies on graphs and in particular on bipartite graphs. then, from a graph we construct a particular compatible alexandroff topological space said homeomorphic-equivalent to the graph. conversely, from any alexandroff topology we construct an isomorphic-equivalent graph on which the topology is compatible. finally, using these constructions, we show that gi is polynomial-time equivalent to the topological homeomorphism problem (tophomeo). hence gi and tophomeo are in the same class of complexity.
terminal metric spaces of finitely branching and image finite linear processes. well-known metric spaces for modelling finitely branching and image finite systems are shown to be (the carrier of) terminal coalgebras.
domain theory, testing and simulation for labelled markov processes. this paper presents a fundamental study of similarity and bisimilarity for labelled markov processes (lmps). the main results characterize similarity as a testing preorder and bisimilarity as a testing equivalence. in general, lmps are not required to satisfy a finite-branching condition--indeed the state space may be a continuum, with the transitions given by arbitrary probability measures. nevertheless we show that to characterize bisimilarity it suffices to use finitely-branching labelled trees as tests.our results involve an interaction between domain theory and measure theory. one of the main technical contributions is to show that a final object in a suitable category of lmps can be constructed by solving a domain equation d ≃v(d)act, where v is the probabilistic powerdomain. given an lmp whose state space is an analytic space, bisimilarity arises as the kernel of the unique map to the final lmp. we also show that the metric for approximate bisimilarity introduced by desharnais, gupta, jagadeesan and panangaden generates the lawson topology on the domain d.
a behavioural pseudometric for probabilistic transition systems. discrete notions of behavioural equivalence sit uneasily with semantic models featuring quantitative data, like probabilistic transition systems. in this paper, we present a pseudometric on a class of probabilistic transition systems yielding a quantitative notion of behavioural equivalence. the pseudometric is defined via the terminal coalgebra of a functor based on a metric on the space of borel probability measures on a metric space. states of a probabilistic transition system have distance 0 if and only if they are probabilistic bisimilar. we also characterize our distance function in terms of a real-valued modal logic.
approximating and computing behavioural distances in probabilistic transition systems. in an earlier paper we presented a pseudometric on the states of a probabilistic transition system, yielding a quantitative notion of behavioural equivalence. the behavioural pseudometric was defined via the terminal coalgebra of a functor based on a metric on borel probability measures. in the present paper we give a polynomial-time algorithm, based on linear programming, to calculate the distances between states up to a prescribed degree of accuracy.
making knowledge explicit: how hard it is. artemov's logic of proofs lp is a complete calculus of propositions and proofs, which is now becoming a foundation for the evidence-based approach to reasoning about knowledge. additional atoms in lp have form t: f, read as "t is a proof of f" (or, more generally, as "t is an evidence for f") for an appropriate system of terms t called proof polynomials. in this paper, we answer two well-known questions in this area. one of the main features of lp is its ability to realize modalities in any s4-derivation by proof polynomials thus revealing a statement about explicit evidences encoded in that derivation. we show that the original artemov's algorithm of building such realizations can produce proof polynomials of exponential length in the size of the initial s4-derivation. we modify the realization algorithm to produce proof polynomials of at most quadratic length. we also found a modal formula, any realization of which necessarily requires self-referential constants of type c: a(c). this demonstrates that the evidence-based reasoning encoded by the modal logic s4 is inherently self-referential.
kernels of seminorms in constructive analysis. the kernel of a seminorm on a normed space is examined constructively--that is, using intuitionistic logic. in particular, conditions are given that ensure that (i) the kernel is located and (ii) the kernel is nontrivial.
implementing exact real arithmetic in python, c++ and c. i discuss the design and performance issues arising in the efficient implementation of the scaled-integer exact real arithmetic model introduced by boehm and others. this system represents a real number with a automatically controlled level of precision by a rational with implicit denominator. i describe three practical codes, in python, c++ and c. these allow the convenient use of this computational paradigm in commonly used imperative languages.
reducibility of gene patterns in ciliates using the breakpoint graph. gene assembly in ciliates is one of the most involved dna processings going on in any organism. this process transforms one nucleus (the micronucleus) into another functionally different nucleus (the macronucleus). we continue the development of the theoretical models of gene assembly, and in particular we demonstrate the use of the concept of the breakpoint graph, known from another branch of dna transformation research. more specifically: (1) we characterize the intermediate gene patterns that can occur during the transformation of a given micronuclear gene pattern to its macronuclear form; (2) we determine the number of applications of the loop recombination operation (the most basic of the three molecular operations that accomplish gene assembly) needed in this transformation; (3) we generalize previous results (and give elegant alternatives for some proofs) concerning characterizations of the micronuclear gene patterns that can be assembled using a specific subset of the three molecular operations.
graceful planes and lines. in the framework of the theory of arithmetic geometry (reveills, gomtrie discrte, calcul en nombres entiers et algorithmique, thse d'tat, universit louis pasteur, strasbourg, 1991), we propose an approach to discretize polyhedra by meshes of discrete triangles. we propose a general discretization scheme based on reducing the 3d problem to a 2d problem. we introduce new classes of discrete planes and lines called graceful planes and graceful lines. naive planes and graceful lines are used to construct as thin as possible triangular mesh discretization admitting an analytical description. the interiors of the triangles are portions of naive planes, while the sides are graceful lines. these primitives serve as an optimal ground for obtaining thin tunnel-free discretizations, within the adopted generation scheme. we also extend our considerations to arbitrary surfaces and curves.
connectivity of discrete planes. studying connectivity of discrete objects is a major issue in discrete geometry and topology. in the present work, we deal with connectivity of discrete planes in the framework of réveillès analytical definition (thèse d'état, université louis pasteur, strasbourg, france, 1991). accordingly, a discrete plane is a set p(a, b, c, µ, ω) of integer points (x, y, z) satisfying the diophantine inequalities 0 ≤ ax + by + cz + µ < ω. the parameter µ ∈ z estimates the plane intercept while ω ∈ n is the plane thickness. given three integers (plane coefficients) a, b, and c with 0 ≤ a ≤ b ≤ c, one can seek the value of ω beyond which the discrete plane p(a, b, c, µ, ω) is always connected. we call this remarkable topological invariable the connectivity number of p(a, b, c, µ, ω) and denote it ω(a, b, c). despite several attempts over the last 10 years to determine the connectivity number, this is still an open question. in the present paper, we propose a solution to the problem. for this, we first investigate some combinatorial properties of discrete planes. these structural results facilitate the deeper understanding of the discrete plane structure. on this basis, we obtain a series of results, in particular, we provide an explicit solution to the problem under certain conditions. we also obtain exact upper and lower bounds on ω(a, b, c) and design an o(alogb) algorithm for its computation.
the modal argument for hypercomputing minds. we now know both that hypercomputation (or super-recursive computation) is mathematically well-understood, and that it provides a theory that according to some accounts for some real-life computation (e.g., operating systems that, unlike turing machines, never simply output an answer and halt) better than the standard theory of computation at and below the "turing limit." but one of the things we do not know is whether the human mind hypercomputes, or merely computes--this despite informal arguments from gödel, lucas, penrose and others for the view that, in light of incompleteness theorems, the human mind has powers exceeding those of tms and their equivalents. all these arguments fail; their fatal flaws have been repeatedly exposed in the literature. however, we give herein a novel, formal modal argument showing that since it's mathematically possible that human minds are hypercomputers, such minds are in fact hypercomputers. we take considerable pains to anticipate and rebut objections to this argument.
public data structures: counters as a special case. a public data structure is required to work correctly in a concurrent environment where many processes may try to access it, possibly at the same time. in implementing such a structure nothing can be assumed in advance about the number or the identities of the processes that might access it.while most of the known concurrent data structures are not public, there are few which are public. interestingly, these public data structures all deal with various variants of counters, which are data structures that support two operations: increment and read.in this paper, we define the notion of a public data structure, and investigate several types of public counters. then we give an optimal construction of public counters which satisfies a weak correcness condition, and show that there is no public counter which satisfies a stronger condition. it is hoped that this work will provide insights into the design of other, more complicated, public data structures.
combinatorial properties of smooth infinite words. we describe some combinatorial properties of an intriguing class of infinite words, called smooth, connected with the kolakoski one, k, defined as the fixed point of the run-length encoding δ. it is based on a bijection on the free monoid over σ = {1, 2}, that shows some surprising mixing properties. all words contain the same finite number of square factors, and consequently they are cube-free. this suggests that they have the same complexity as confirmed by extensive computations. we further investigate the occurrences of palindromic subwords. finally, we show that there exist smooth words obtained as fixed points of substitutions (realized by transducers) as in the case of k.
a note on differentiable palindromes. we give a characterization of the palindromes in a class of infinite words over σ = {1,2} related to the kolakoski word k. this characterization, based on the left palindromic closure of all prefixes of k, is obtained by using a bijection between the class of right infinite words over σ and a class of words over the same alphabet, and reveals the first link between the existence of some palindromes and the recurrence of k. indeed, the existence of arbitrarily long palindromes implies the recurrence of k, and a stronger assumption implies the closure of the set of its factors by permutation of the letters in σ.
the discrete green theorem and some applications in discrete geometry. the discrete version of green's theorem and bivariate difference calculus provide a general and unifying framework for the description and generation of incremental algorithms. it may be used to compute various statistics about regions bounded by a finite and closed polygonal path. more specifically, we illustrate its use for designing algorithms computing many statistics about polyominoes, regions whose boundary is encoded by four letter words: area, coordinates of the center of gravity, moment of inertia, set characteristic function, the intersection with a given set of pixels, hook-lengths, higher order moments and also q-statistics for projections.
on the power of non-local boxes. a non-local box is a virtual device that has the following property: given that alice inputs a bit at her end of the device and that bob does likewise, it produces two bits, one at alice's end and one at bob's end, such that the xor of the outputs is equal to the and of the inputs. this box, inspired from the chsh inequality, was first proposed by popescu and rohrlich to examine the question: given that a maximally entangled pair of qubits is non-local, why is it not maximally non-local? we believe that understanding the power of this box will yield insight into the non-locality of quantum mechanics. it was shown recently by cerf, gisin, massar and popescu, that this imaginary device is able to simulate correlations from any measurement on a singlet state. here, we show that the non-local box can in fact do much more: through the simulation of the magic square pseudo-telepathy game and the mermin-ghz pseudo-telepathy game, we show that the non-local box can simulate quantum correlations that no entangled pair of qubits can, in a bipartite scenario and even in a multi-party scenario. finally we show that a single non-local box cannot simulate all quantum correlations and propose a generalization for a multi-party non-local box. in particular, we show quantum correlations whose simulation requires an exponential amount of non-local boxes, in the number of maximally entangled qubit pairs.
the decidability of a fragment of bb'iw-logic. despite its simple formulation, the decidability of the logic <b>bb'iw</b> has remained an open problem. we present here a decision procedure for a fragment of it, called the arity-1 formulas. the decidability proof is based on a representation of formulas called formula-trees, which is coupled with a proof method that computes long normal λ-terms that inhabit a formula. a rewriting-system is associated with such λ-terms, and we show that a formula admits a <b>bb'iw</b>-λ-term if and only if the associated rewriting-system terminates. the fact that termination is decidable is proved using a result on the finiteness of non-ascending sequences of <i>n</i>-tuples in n<sup><i>n</i></sup>, which is equivalent to kripke's lemma.
space-efficient planar convex hull algorithms. a space-efficient algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. we describe four space-efficient algorithms for computing the convex hull of a planar point set.
the design of the boost interval arithmetic library. we present the design of the boost interval arithmetic library, a c++ library designed to handle mathematical intervals efficiently and in a generic way. interval computations are an essential tool for reliable computing. increasingly a number of mathematical proofs have relied on global optimization problems solved using branch-and-bound algorithms with interval computations; it is therefore extremely important to have a mathematically correct implementation of interval arithmetic. various implementations exist with diverse semantics. our design is unique in that it uses policies to specify three independent variable behaviors: rounding, checking, and comparisons. as a result, with the proper policies, our interval library is able to emulate almost any of the specialized libraries available for interval arithmetic, without any loss of performance nor sacrificing the ease of use. this library is openly available at www.boost.org.
applications of standard sturmian words to elementary number theory. this note is a short survey, by no means intended to be complete, of some of the descriptions which have been given of standard sturmian words, and of some of the applications of these descriptions to elementary number theory. (`elementary number theory' is interpreted fairly broadly.) the descriptions and applications below have appeared before, except for fact 4, application 1, and the proof of application 2.
an improved deterministic local search algorithm for 3-sat. we slightly improve the pruning technique presented in dantsin et al. (theoret. comput. sci. 289 (2002) 69) to obtain an o*(1.473n) deterministic algorithm for 3-sat.
the complexity of fibonacci-like kneading sequences. the fibonacci(-like) unimodal maps that have been studied in recent years give rise to a zero-entropy minimal subshift on two symbols, generated by the kneading sequence. in this paper we computed the word-complexity of such subshifts exactly.
an algorithm reconstructing convex lattice sets. in this paper, we study the problem of reconstructing special lattice sets from x-rays in a finite set of prescribed directions. we present the class of "q-convex" sets which is a new class of subsets of z2 having a certain kind of weak connectedness. the main result of this paper is a polynomial-time algorithm solving the reconstruction problem for the "q-convex" sets. these sets are uniquely determined by certain finite sets of directions. as a result, this algorithm can be used for reconstructing convex subsets of z2 from their x-rays in some suitable sets of four lattice directions or in any set of seven mutually nonparallel lattice directions.
random generation of q-convex sets. the problem of randomly generating q-convex sets is considered. we present two generators. the first one uses the q-convex hull of a set of random points in order to generate a q-convex set included in the square [0, n)2. this generator is very simple, but is not uniform and its performance is quadratic in n. the second one exploits a coding of the salient points, which generalizes the coding of a border of polyominoes. it is uniform, and is based on the method by rejection. experimentally, this algorithm works in linear time in the length of the word coding the salient points. besides, concerning the enumeration problem, we determine an asymptotic formula for the number of q-convex sets according to the size of the word coding the salient points in a special case, and in general only an experimental estimation.
normal forms for algebras of connection. recent years have seen a growing interest towards algebraic structures that are able to express formalisms different from the standard, tree-like presentation of terms. many of these approaches reveal a specific interest towards the application to the 'distributed and concurrent systems' field, but an exhaustive comparison between them is sometimes difficult, because their presentations can be quite dissimilar. this work is a first step towards a unified view: focusing on the primitive ingredients of distributed spaces (namely interfaces, links and basic modules), we introduce a general schema for describing a normal form presentation of many algebraic formalisms, and show that those normal forms can be thought of as arrows of suitable monoidal categories.
a basic algebra of stateless connectors. the conceptual separation between computation and coordination in distributed computing systems motivates the use of peculiar entities commonly called connectors, whose task is managing the interaction among distributed components. different kinds of connectors exist in the literature at different levels of abstraction. we focus on an algebra of connectors that exploits five kinds of basic connectors (plus their duals), namely symmetry, synchronization, mutual exclusion, hiding and inaction. basic connectors can be composed in series and in parallel. we first define the operational, observational and denotational semantics of connectors, then we show that the observational and denotational semantics coincide and finally we give a complete normal-form axiomatization. the expressiveness of the framework is witnessed by the ability to model all the (stateless) connectors of the architectural design language community and of the coordination language reo.
dynamic connectors for concurrency. we propose a metatheoretic approach to the definition of operational and abstract concurrent semantics for systems where name handling is a key issue. the main ingredients of our framework are connectors and tile logic. the former allow for the modeling of various kinds of graph-like and term-like structures, which can be useful in representing system distribution and causal histories. the latter is used to combine the use of connectors in space and in time (i.e., according to configurations and computations). as a detailed case study, we show how to define a concurrent operational semantics and causal weak bisimilarity for a flavor of basic parallel processes.
semantic foundations for generalized rewrite theories. rewriting logic (rl) is a logic of actions whose models are concurrent systems. rewrite theories involve the specification of equational theories of data and state structures together with a set of rewrite rules that model the dynamics of concurrent systems. since its introduction, more than one decade ago, rl has attracted the interest of both theorists and practitioners, who have contributed in showing its generality as a semantic and logical framework and also as a programming paradigm. the experimentation conducted in these years has suggested that some significant extensions to the original definition of the logic would be very useful in practice. these extensions may develop along several dimensions, like the choice of the underlying equational logic, the kind of side conditions allowed in rewrite rules and operational concerns for the execution of certain rewrites. in particular, the maude system now supports subsorting and conditional sentences in the equational logic for data, and also frozen arguments to block undesired nested rewrites; moreover, it allows equality and membership assertions in rule conditions. in this paper, we give a detailed presentation of the inference rules, model theory, and completeness of such generalized rewrite theories. our results provide a mathematical semantics for maude, and a foundation for formal reasoning about maude specifications.
observational congruences for dynamically reconfigurable tile systems. the sos formats that ensure that bisimilarity is a congruence tail in the presence ot structural axioms on states. dynamic bisimulation, introduced to characterize the coarsest congruence for ccs which is also a weak bisimulation, reconciles the 'bisimilarity is a congruence' property with structural axioms and also with the specification of open ended systems, where states can be reconfigured at runtime. we show that the compositional framework offered by tile logic handles structural axioms and specifications of reconfigurable systems successfully. this allows for a finitary presentation of dynamic context closure, as internalized in the tile language. the case study of the π-calculus illustrates the main features of our approach. moreover, duality is exploited to model a second kind of reconfiguration: dynamic specialization.
on structuring proof search for first order linear logic. full first-order linear logic can be presented as an abstract logic programming language in miller's system forum, which yields a sensible operational interpretation in the 'proof search as computation' paradigm. however, forum still has to deal with syntactic details that would normally be ignored by a reasonable operational semantics. in this respect, forum improves on gentzen systems for linear logic by restricting the language and the form of inference rules. we further improve on forum by restricting the class of formulae allowed, in a system we call g-forum, which is still equivalent to full first-order linear logic. the only formulae allowed in g-forum have the same shape as forum sequents: the restriction does not diminish expressiveness and makes g-forum amenable to proof theoretic analysis. g-forum consists of two (big) inference rules, for which we show a cut elimination procedure. this does not need to appeal to finer detail in formulae and sequents than is provided by g-forum, thus successfully testing the internal symmetries of our system.
cumulative defect. we prove that if x is a finite code and s is an infinite word with 3 x-factorizations, then the rank r(x) of x is at most |x| - 2. more generally, if x belongs to a certain family of codes and s has l ≥ 2 x-factorizations, then the rank is at most |x| - l+ 1.
compatibility of unrooted phylogenetic trees is fpt. a collection of t1, t2,...,tk of unrooted, leaf labelled (phylogenetic) trees, all with different leaf sets, is said to be compatible if there exists a tree t such that each tree ti can be obtained from t by deleting leaves and contracting edges. determining compatibility is np-hard, and the fastest algorithm to date has worst case complexity of around ω(nk) time, n being the number of leaves. here, we present an o(nf(k)) algorithm, proving that compatibility of unrooted phylogenetic trees is fixed parameter tractable (fpt) with respect to the number k of trees.
representation of a class of nondeterministic semiautomata by canonical words. it has been shown recently that deterministic semiautomata can be represented by canonical words and equivalences; that work was motivated by the trace-assertion method for specifying software modules. here, we generalize these ideas to a class of nondeterministic semiautomata. a semiautomaton is settable if, for every state q, there exists a word wq such that q, and no other state, can be reached from some initial state by a path spelling wq. we extend many results from the deterministic case to settable nondeterministic semiautomata. now each word has a number of canonical representatives. we show that a prefix-rewriting system exists for transforming any word to any of its representatives. if the set of canonical words is prefix-continuous (meaning that, if w and a prefix u of w are in the set, then all prefixes of w longer than u are also in the set), the rewriting system has no infinite derivations. examples of specifications of nondeterministic modules are given.
maximizing agreements and coagnostic learning. this paper studies α-coagnostic learnability of classes of boolean formulas. to α-coagnostic learn c from h, the learner seeks a hypothesis h ∈ h whose probability of agreement (rather than disagreement as in agnostic learning) with a labeled example is within a factor α of the best agreement probability achieved by any f ∈ c. although 1-coagnostic learning is equivalent to agnostic learning, this is not true for α-coagnostic learning for 1/2 < α < 1.it can be seen that α-coagnostic learnability is equivalent to the α-approximability of the maximum agreement problems. for these problems we are given a labeled sample s and must find an h ∈ h that agrees with as many examples in s as the best f ∈ c does. many studies have been done on maximum agreement problems, for classes such as monomials, monotone monomials, antimonotone monomials, halfspaces and balls. we further the study of these problems and some extensions of them. for the above classes we improve the best previously known factors α for the hardness of α-coagnostic learning. we also find the first constant lower bounds for decision lists, exclusive-or, halfsaces (over the boolean domain), 2-term dnf and 2-term multivariate polynomials.
an equational notion of lifting monad. we introduce the notion of an equational lifting monad: a commutative strong monad satisfying one additional equation (valid for monads arising from partial map classifiers). we prove that any equational lifting monad has a representation by a partial map classifier such that the kleisli category of the former fully embeds in the partial category of the latter. thus, equational lifting monads precisely capture the equational properties of partial maps as induced by partial map classifiers. the representation theorem also provides a tool for transferring nonequational properties of partial map classifiers to equational lifting monads. it is proved using a direct axiomatization of kleisli categories of equational lifting monads. this axiomatization is of interest in its own right.
relative definability of boolean functions via hypergraphs. the aim of this work is to show how hypergraphs can be used as a systematic tool in the classification of continuous boolean functions according to their degree of parallelism. intuitively f is "less parallel" than g if it can be defined by a sequential program using g as its only free variable. it turns out that the poset induced by this preorder is (as for the degrees of recursion) a sup-semilattice. although hypergraphs have already been used in bucciarelli (theoret. comput. sci., to appear) as a tool for studying degrees of parallelism, no general result relating the former to the latter has been proved in that work. we show that the sup-semilattice of degrees has a categorical counterpart: we define a category of hypergraphs such that every object "represents" a monotone boolean function; finite coproducts in this category correspond to lubs of degrees. unlike degrees of recursion, where every set has a recursive upper bound, monotone boolean functions may have no sequential upper bound. however the ones which do have a sequential upper bound can be nicely characterised in terms of hypergraphs. these subsequential functions play a major role in the proof of our main result, namely that f is less parallel than g if there exists a morphism between their associated hypergraphs.
on finding common neighborhoods in massive graphs. we consider the problem of finding pairs of vertices that share large common neighborhoods in massive graphs. we prove lower bounds on the resources needed to solve this problem on resource-bounded models of computation. in streaming models, in which algorithms can access the input only a constant number of times and only sequentially, we show that, even with randomization, any algorithm that determines if there exists any pair of vertices with a large common neighborhood must essentially store and process the input graph off line. in sampling models, in which algorithms can only query an oracle for the common neighborhoods of specified vertex pairs, we show that any algorithm must sample almost every pair of vertices for their respective common neighborhoods.
a translation of tpal into a class of timed-probabilistic petri nets. tpalp is an algebraic language for the description of concurrent systems with capabilities to express timed and probabilistic behaviours, as well as urgent interactions. in this paper we present the main features of the language, its operational semantics, and a translation of tpalp terms into a particular class of timed-probabilistic petri nets. the language includes a probabilistic choice operator, a timed prefix operator, and an urgent prefix operator, as well as some other operators that we may find in classical process algebras. an important feature of the language is that urgency is considered at any instant by executing as many urgent actions as possible, with the goal of complying in a great extent with the urgent actions indicated in the user specifications.
complexity measures and decision tree complexity: a survey. we discuss several complexity measures for boolean functions: certificate complexity, sensitivity, block sensitivity, and the degree of a representing or approximating polynomial. we survey the relations and biggest gaps known between these measures, and show how they give bounds for the decision tree complexity of boolean functions on deterministic, randomized, and quantum computers.
h-coloring dichotomy revisited. the h-coloring problem can be expressed as a particular case of the constraint satisfaction problem (csp) whose computational complexity has been intensively studied under various approaches in the last several years. we show that the dichotomy theorem proved by hell and nešetřil [on the complexity of h-coloring, j. combin. theory ser. b 48 (1990) 92-110] for the complexity of the h-coloring problem for undirected graphs can be obtained using general methods for studying csp and that the criterion distinguishing the tractable cases of the h-coloring problem agrees with that conjectured in [a.a. bulatov, p.g. jeavons, a.a. krokhin, constraint satisfaction problems and finite algebras, in: proc. 27th internat. colloq. on automata, languages and programming--icalp'00, lecture notes in computer science, vol. 1853, springer, berlin, 2000, pp. 272-282] for the complexity of the general csp.
the complexity of partition functions. we give a complexity theoretic classification of the counting versions of so-called h-colouring problems for graphs h that may have multiple edges between the same pair of vertices. more generally, we study the problem of computing a weighted sum of homomorphisms to a weighted graph h.the problem has two interesting alternative formulations: first, it is equivalent to computing the partition function of a spin system as studied in statistical physics. and second, it is equivalent to counting the solutions to a constraint satisfaction problem whose constraint language consists of two equivalence relations.in a nutshell, our result says that the problem is in polynomial time if the adjacency matrix of h has row rank 1, and #p-hard otherwise.
lorentz gas cellular automata on graphs. lorentz gas cellular automata (lgca) are models of parallel many-tape turing machines generated by the motion of localized (point) objects (particles, signals, wave trains, etc.) on a graph. in each vertex v of the graph we store a symbol. a read/write head of the turing machine is represented as an object that hops from one vertex of the graph to another according to a rule (symbol) stored in the vertex. thus, the symbols stored in the vertices represent scattering rules (or simply scatterers) of the lattice gas. it is assumed that initially the scatterers are randomly distributed among the vertices of the graph. the random environment formed by the scatterers may either be fixed or evolve due to collisions with the moving object. the collisions simulate storing of a new symbol in the vertex of the graph. we investigate these models with fixed environment in general types of graphs and the models with evolving environments on trees. remarkably, it occurred that all models with fixed environments and many models with evolving environment behave like a depth-first search on the underlying graph. observe that such behavior occurs for any initial random distribution of scatterers rather than for some "specially prepared" initial configurations of scatterers. we also give estimates of periods of orbits on finite graphs.
projections of vector addition system reachability sets are semilinear. the reachability sets of vector addition systems of dimension six or more can be non-semilinear. this may be one reason why the inclusion problem (as well as the equality problem) for reachability sets of vector addition systems in general is undecidable, even though the reachability problem itself is known to be decidable. we show that any one-dimensional projection of the reachability set of an arbitrary vector addition system is semilinear, and hence, "simple".
approximating shortest path for the skew lines problem in time doubly logarithmic in 1/epsilon. we consider two three-dimensional situations when a polytime algorithm for approximating a shortest path can be constructed. the main part of the paper treats a well-known problem of constructing a shortest path touching lines in r3: given a list of straight lines l = (l1,..., ln) in r3 and two points s and t, find a shortest path that, starting from s, touches the lines li in the given order and ends at t. we remark that such a shortest path is unique. we show that it can be length--position ε-approximated (i.e. both its length and its position can be found approximately) in time (rn/dα)16 + o(n2 log log 1/ε), where d is the minimal distance between consecutive lines of l, α˜ is the minimum of sines of angles between consecutive lines, and r is the radius of a ball where the initial approximation can be placed (such a radius can be easily computed from the initial data).as computational model we take real ram extended by square and cubic roots extraction. this problem of constructing a shortest path touching lines is known for quite some time to be a challenging problem. the existing methods for approximating shortest paths based on adding steiner points which form a grid and subsequently applying dijkstra's algorithm for finding a shortest path in the grid, provide a complexity bound which depends polynomially on 1/ε, while our algorithm for the problem under consideration has complexity linear in log log 1/ε. our algorithm is motivated by the observation that the shortest path in question is a geodesic in a certain length space of non-positive curvature (in the sense of a.d. alexandrov), and it relies on the (elementary) theory of cat(0)-spaces.in the second part of the paper we analyze very simple grid approximations. we assume that a parameter a > 0 describing separability of obstacles is given and the part of a grid with mesh size a outside the obstacles is built (for semi-algebraic obstacles all these precalculations are polytime). we show that there is an algorithm of time complexity o((1/a)6) which, given a-separated obstacles in a unit cube, finds a path (between given vertices s and t of the grid) whose length is bounded from above by (84π* + 96a), where π* is the length of a shortest path. on the other hand, as we show by an example, one cannot approximate the length of a shortest path better than 7π* if one uses only grid polygons (constructed only from grid edges). for semi-algebraic obstacles our computational model is bitwise. for a general type of obstacles the model is bitwise modulo constructing the part of the grid admissible for our paths. observe that the existing methods for approximating shortest paths are not directly applicable for semi-algebraic obstacles since they usually place the steiner points forming a grid on the edges of polyhedral obstacles.
sequential computation of linear boolean mappings. we prove that any linear boolean mapping of dimension n can be computed with a double sequence of linear assignments of the n variables. the proof is effective and gives a decomposition of boolean matrices and directed graphs.
a note on iterated duals of certain topological spaces. problem 540 in open problems in topology (1990) asks whether iterating the operation of taking the dual topology eventually leads to a mutually dual pair of topologies. we give an affirmative answer to problem 540 for several classes of spaces. some of the special cases covered are: any t1 space (already solved in 1966 by strecker), the lower vietoris topology on any hyperspace, the scott topology for reverse inclusion on any hyperspace, and the upper vietoris topology on the hyperspace of a regular space. we find in all these cases that tdd=tdddd, and therefore at most four distinct topologies, t,td,tdd,tddd, can be created by iterating the dual operator starting with any one of these special cases.
algorithmic complexity of recursive and inductive algorithms. the main goal of this paper is to compare recursive algorithms such as turing machines with such super-recursive algorithms as inductive turing machines. this comparison is made in a general setting of dual complexity measures such as kolmogorov or algorithmic complexity. to make adequate comparison, we reconsider the standard axiomatic approach to complexity of algorithms. the new approach allows us to achieve a more adequate representation of static system complexity in the axiomatic context. it is demonstrated that for solving many problems inductive turing machines have much lower complexity than turing machines and other recursive algorithms. thus, inductive turing machines are not only more powerful, but also more efficient than turing machines.
experience, generations, and limits in machine learning. this paper extends traditional models of machine learning beyond their one-level structure by introducing previously obtained problem knowledge into the algorithm or automaton involved. some authors studied more advanced than traditional models that utilize some kind of predetermined knowledge, having a two-level structure. however, even in this case, the model has not reflected the source and inherited properties of predetermined knowledge. in society, knowledge is often transmitted from previous generations. the aim of this paper is to construct and study algorithmic models of learning processes that utilize predetermined or prior knowledge. the models use recursive, subrecursive, and super-recursive algorithms. predetermined knowledge includes: a text description, activity rules (e.g., for cognition), and specific structured personal or social memory. algorithmic models represent these three forms as separate structured processing systems: automata with (1) advice; (2) structured program; and (3) structured memory. that yields three basic models for learning systems: polynomially bounded turing machines, turing machines, and inductive turing machines of the first order.
threshold counters with increments and decrements. a threshold counter is a shared data structure that assumes integer values. it provides two operations: increment changes the current counter value from v to v+1, while read returns the value [v/w], where v is the current counter value and w is a fixed constant. thus, the read operation returns the "approximate" value of the counter to within the constant w. threshold counters have many potential uses, including software barrier synchronization. threshold networks are a class of distributed data structures that can be used to construct highly-concurrent, low-contention implementations of shared threshold counters. in this paper, we give the first proof that any threshold network construction of a threshold counter can be extended to support a decrement operation that changes the counter value from v to v ---1.
analysis issues in petri nets with inhibitor arcs. we investigate the problem of extending the analysis techniques developed for p/t systems to a proper subclass of p/t systems with inhibitor arcs. we start proposing an extension of the coverability tree construction to a subclass of p/t systems with inhibitor arcs, whose elements will be called henceforth primitive systems. we show that the coverability tree corresponding to a primitive system is finite and is a good representation of its behaviour; hence, it can be used as an analysis tool to check properties such as place boundedness, the existence of dead transitions and of a reachable marking larger than a given one. then we provide an encoding of primitive systems in p/t systems, which permits to retrieve the firing sequences of the primitive system from the firing sequences of the corresponding p/t system. the close correspondence between the firing sequences of the two systems is used prove the decidability of reachability, deadlock and liveness for primitive systems. we also obtain that the model checking problem for the linear time -calculus and labelled primitive systems is decidable. we show that primitive systems coincide with the largest class of p/t systems with inhibitor arcs whose transition sequences can be simulated by a standard p/t system; we also show that in general the step behaviour of a primitive system cannot be simulated by any p/t system. these results are then used to investigate the expressiveness of inhibitor arcs regarding the class of generated languages.
comparing three semantics for linda-like languages. a simple calculus based on generative communication is introduced; among its primitives, it contains a conditional input operation that tests for presence (or absence) of an output, reminiscent of the inp predicate of linda. we study three different operational semantics for the output operation, called instantaneous, ordered and unordered. the associated behavioural semantics are obtained as the coarsest congruence contained in the corresponding strong barbed semantics. we prove that when the output operation is instantaneous, the obtained semantics is a sort of asynchronous bisimulation; on the contrary, for the ordered semantics, as well as for the unordered one, the resulting semantics is a small variant of the classic (synchronous) bisimulation. further rusults are related to the expressiveness of the language. the language is turing powerful under both the instantaneous and ordered semantics, but there exists a series of problems having solution under the instantaneous interpretation that cannot be solved under the ordered one. instead, the language is not turing powerful under the unordered semantics. thus, we conclude that there exists a precise expressiveness hierarchy among the three semantics.
a process algebraic view of linda coordination primitives. the main linda coordination primitives (asynchronous communication, read operation, nonblocking in/rd predicates) are studied in a process algebraic setting. a lattice of eight languages is proposed, where its bottom element l is a process algebra differing from ccs only for the asynchrony of the output operation, while all the other languages in the lattice are obtained as extension of this basic language by adding some of the linda coordination primitives. the observational semantics for these languages are all obtained as the coarsest congruences contained in the barbed semantics, where only tuples are observable. the lattice of the eight languages collapses to a smaller four-points lattice of different bisimulation-based semantics. notably, for l this semantics is the standard notion of strong bisimulation, where inputs and outputs/tuples are treated symmetrically.
expired data collection in shared dataspaces. the shared dataspace metaphor is historically the most prominent representative of the family of coordination models. according to this approach, concurrent processes interact via the production, consumption, and test for presence/absence of data in a common repository. recently, the problem of the accumulation of outdated and unwanted information in the shared repository has been addressed. typical garbage collection algorithms cannot be adopted in this context because there is no notion of unaccessible data. the most promising solution to this problem consists of the introduction of the notion of temporary data, intended as data with an associated expiration time. in this paper, we investigate the impact of different mechanisms for expired data collection on the expressiveness of shared dataspace coordination systems with temporary data.
on the expressive power of movement and restriction in pure mobile ambients. pure mobile ambients is a process calculus suitable to focus on issues related to mobility, abstracting away from aspects concerning process communication. however, it incorporates name restriction (i.e. the (vn) binder) and ambient movement (i.e. the in and out capabilities) that can be seen as characteristics adapted, or directly borrowed, from the tradition of communication-based process calculi. for this reason, we retain that it is worth to investigate whether or not these features can be removed from pure mobile ambients without losing expressive power.to this aim, we consider two variants of pure mobile ambients which differ in the way infinite processes can be defined; the former exploits process replication, while the latter is more general and permits recursive process definition. we analyse whether or not the elimination of ambient movement and/or name restriction reduces the expressive power of these two calculi, using the decidability of process termination as a yardstick. we prove that name restriction can be removed from both calculi without reducing the expressive power. on the other hand, the elimination of both ambient movement and name restriction strictly reduces the expressive power of both calculi. as far as the elimination of only ambient movement is concerned, we prove an interesting discrimination result: process termination is undecidable under recursive process definition, while it turns out to be decidable under process replication.
polynomial-size frege and resolution proofs of -connectivity and hex tautologies. a grid graph has rectangularly arranged vertices with edges permitted only between orthogonally adjacent vertices. the st- connectivity principle states that it is not possible to have a red path of edges and a green path of edges which connect diagonally opposite corners of the grid graph unless the paths cross somewhere.we prove that the propositional tautologies which encode the st-connectivity principle have polynomial-size frege proofs and polynomial-size tc0-frege proofs. for bounded-width grid graphs, the st-connectivity tautologies have polynomial-size resolution proofs. a key part of the proof is to show that the group with two generators, both of order two, has word problem in alternating logtime (alogtime) and even in tc0.conversely, we show that constant depth frege proofs of the st-connectivity tautologies require near-exponential size. the proof uses a reduction from the pigeonhole principle, via tautologies that express a "directed single source" principle sink, which is related to papadimitriou's search classes ppad and ppads (or, psk).the st-connectivity principle is related to urquhart's propositional hex tautologies, and we establish the same upper and lower bounds on proof complexity for the hex tautologies. in addition, the hex tautology is shown to be equivalent to the sink tautologies and to the one-to-one onto pigeonhole principle.
simplifying the weft hierarchy. we give simple, self-contained proofs of the basic hardness results for the classes w[t] of the weft hierarchy. we extend these proofs to higher levels of the hierarchy and illuminate the distinctions among its classes. the anti-monotone collapse at w[1, s] and the normalization of weft-t formulas arise as by-products of the proofs.
formal analysis of kerberos 5. we report on the detailed verification of a substantial portion of the kerberos 5 protocol specification. because it targeted a deployed protocol rather than an academic abstraction, this multiyear effort led to the development of new analysis methods in order to manage the inherent complexity. this enabled proving that kerberos supports the expected authentication and confidentiality properties, and that it is structurally sound; these results rely on a pair of intertwined inductions. our work also detected a number of innocuous but nonetheless unexpected behaviors, and it clearly described how vulnerable the cross-realm authentication support of kerberos is to the compromise of remote administrative domains.
new algorithms for exact satisfiability. the exact satisfiability problem is to determine if a cnf-formula has a truth assignment satisfying exactly one literal in each clause; exact 3-satisfiability is the version in which each clause contains at most three literals. in this paper, we present algorithms for exact satisfiability and exact 3-satisfiability running in time o(20.2325n) and o(20.1379n), respectively. the previously best algorithms have running times o(20.2441n) for exact satisfiability (methods oper. res. 43 (1981) 419-431) and o(20.1626n) for exact 3-satisfiability (annals of mathematics and artificial intelligence 43 (1) (2005) 173-193 and zapiski nauchnyh seminarov pomi 293 (2002) 118-128). we extend the case analyses of these papers and observe that a formula not satisfying any of our cases has a small number of variables, for which we can try all possible truth assignments and for each such assignment solve the remaining part of the formula in polynomial time.
extracting a data flow analyser in constructive logic. a constraint-based data flow analysis is formalised in the specification language of the coq proof assistant. this involves defining a dependent type of lattices together with a library of lattice functors for modular construction of complex abstract domains. constraints are represented in a way that allows for both efficient constraint resolution and correctness proof of the analysis with respect to an operational semantics. the proof of existence of a solution to the constraints is constructive which means that the extraction mechanism of coq provides a provably correct data flow analyser in ocaml from the proof. the library of lattices and the representation of constraints are defined in an analysis-independent fashion that provides a basis for a generic framework for proving and extracting static analysers in coq.
effective category and measure in abstract complexity theory. strong variants of the operator speed-up theorem, operator gap theorem and compression theorem are obtained using an effective version of baire category theorem. it is also shown that all complexity classes of recursive predicates have effective measure zero in the space of recursive predicates and, on the other hand, the class of predicates with almost everywhere complexity above an arbitrary recursive threshold has recursive measure one in the class of recursive predicates.
decidable containment of recursive queries. one of the most important reasoning tasks on queries is checking containment, i.e., verifying whether one query yields necessarily a subset of the result of another one. query containment is crucial in several contexts, such as query optimization, query reformulation, knowledge-base verification, information integration, integrity checking, and cooperative answering. containment is undecidable in general for datalog, the fundamental language for expressing recursive queries. on the other hand, it is known that containment between monadic datalog queries and between datalog queries and unions of conjunctive queries are decidable. it is also known that containment between unions of conjunctive two-way regular path queries, which are queries used in the context of semistructured data models containing a limited form of recursion in the form of transitive closure, is decidable. in this paper, we combine the automata-theoretic techniques at the base of these two decidability results to show that containment of datalog in union of conjunctive two-way regular path queries is decidable in 2exptime. by sharpening a known lower bound result for containment of datalog in union of conjunctive queries we show also a matching lower bound.
computation of arbitrage in frictional bond markets. in this paper we study the computational problem of arbitrage in a frictional market with a finite number of bonds and finite and discrete times to maturity. types of frictions under consideration include fixed and proportional transaction costs, bid-ask spreads, taxes, and upper bounds on the number of units for transaction. we develop a necessary and sufficient condition for the existence of arbitrage. in addition, we obtain some negative result on computational difficulty in general for arbitrage under those frictions: it is np-complete to identify whether there exists a cash-and-carry arbitrage transaction and it is np-hard to find an optimal cash-and-carry arbitrage transaction.
approximate sequencing for variable length tasks. based on applications to efficient information gathering over the web, czumaj et al. (algorithms and data structures (vancouver, bc, 1999), lecture notes in computer science, vol. 1663, springer, berlin, 1999, p. 297) studied the variable length sequencing problem (vlsp), showed it is np-complete, presented a polynomial time algorithm for a very restricted version and an approximation algorithm for a slightly less restricted version. in this paper, we pin-point the difficulty by showing that it is n-p-complete in a strong sense even to approximating the vlsp within a factor nk for any fixed integer k. in addition, we show it is np-hard to find the optimal solution even when all jobs follow the periodic property. motivated by the np-hardness of approximating vlsp, we consider an optimal version of maximizing the number of completed tasks and present an approximation algorithm with factor 2 and a polynomial time algorithm for optimal solution in the special case when the number of different types of tasks is restricted.
continuous-time computation with restricted integration capabilities. recursion theory on the reals, the analog counterpart of recursive function theory, is an approach to continuous-time computation inspired by the models of classical physics. in recursion theory on the reals, the discrete operations of standard recursion theory are replaced by operations on continuous functions such as composition and various forms of differential equations like indefinite integrals, linear differential equations and more general cauchy problems. we define classes of real recursive functions in a manner similar to the standard recursion theory and we study their complexity. we prove both upper and lower bounds for several classes of real recursive functions, which lie inside the elementary functions, and can be characterized in terms of space complexity. in particular, we show that hierarchies of real recursive classes closed under restricted integration operations are related to the exponential space hierarchy. the results in this paper, combined with earlier results, suggest that there is a close connection between analog complexity classes and subrecursive classes, at least in the region between flinspace and the primitive recursive functions.
the inapproximability of non-np-hard optimization problems. the inapproximability of non-np-hard optimization problems is investigated. techniques are given to show that the problems log dominating set and log hypergraph vertex cover cannot be approximated to a constant ratio in polynomial time unless the corresponding np-hard versions are also approximable in deterministic subexponential time. a direct connection is established between non-np-hard problems and a pcp characterization of np. reductions from the pcp characterization show that log clique is not approximable in polynomial time and max sparse sat does not have a fptas under the assumption that np ⊈ dtime(2o(√ n log n). a number of nontrivial approximation-preserving reductions are also presented, making it possible to extend inapproximability results to more natural non-np-hard problems such as tournament dominating set and rich hypergraph vertex cover.
incremental construction of minimal deterministic finite cover automata. we present a fast incremental algorithm for constructing minimal deterministic finite cover automata (dfca) for a given language. since it was shown that the minimal dfca for a language l has less states than the minimal deterministic finite automata (dfa) for the same language l, this technique seems to be the best choice for incrementally building the automaton for a large language, especially when the number of states in the dfca is significantly less than the number of states in the corresponding minimal dfa. we have implemented the proposed algorithm and have tested it against the best-known dfca minimization technique.
mergible states in large nfa. quite often, trivial problems stated for deterministic finite automata (dfa) are surprisingly difficult for the non-deterministic case (nfa). in any non-minimal dfa for a given regular language, we can find two equivalent states which can be "merged" without changing the accepted language. this is not the case for nfa, where we can have non-minimal automata with no "mergible" states. in this paper, we prove a very basic result for nfa, that for a given regular language, any nfa of size greater than a computable constant must contain mergible states. even more, we parameterized this constant in order to guarantee groups of an arbitrary number of mergible states.
a spatial logic for concurrency - ii. we present a modal logic for describing the spatial organization and the behavior of distributed systems. in addition to standard logical and temporal operators, our logic includes spatial operations corresponding to process composition and name hiding, and a fresh name quantifier. in part i of this work we study the fundamental semantic properties of our logic; the focus of the present part ii is on proof theory. the main contributions are a sequent-based proof system for our logic, and a proof of cut-elimination for its first-order fragment.
elimination of quantifiers and undecidability in spatial logics for concurrency. the introduction of spatial logics in concurrency is motivated by a shift of focus from concurrent systems towards distributed systems. aiming at a deeper understanding of the essence of dynamic spatial logics, we study a minimal spatial logic without quantifiers or any operators talking about names. the logic just includes the basic spatial operators void, composition and its adjunct, and the next step modality; for the model we consider a tiny fragment of ccs. we show that this core logic can already encode its own extension with quantification over actions, and modalities for actions. from this result, we derive several consequences. firstly, we establish the intensionality of the logic, we characterize the equivalence it induces on processes, and we derive characteristic formulas. secondly, we show that, unlike in static spatial logics, the composition adjunct adds to the expressiveness of the logic, so that adjunct elimination is not possible for dynamic spatial logics, even quantifier-free. finally, we prove that both model-checking and satisfiability problems are undecidable in our logic. we also conclude that our results extend to other calculi, namely the π-calculus and the ambient calculus.
integer partitions and the sperner property. the objectives of this paper are three-fold. first, we would like to call attention to a very attractive problem, the question of whether or not the poset of integer partitions ordered by refinement has the sperner property. we provide all necessary definitions, and enough bibliography to interest a newcomer in the problem. second, we prove four new theorems, two by exhaustive computation and two in the more traditional manner. finally, we highlight the central role played by larry harper in the literature of this subject.
new results on edge-bandwidth. the edge-bandwidth problem is an analog of the classical bandwidth problem, in which one has to label the edges of a graph by distinct integers such that the maximum difference of labels of any two incident edges is minimized. we prove tight bounds on the edge-bandwidth of hypercube and butterfly graphs, and complete k-ary trees which extends and improves on previous known results.
formal and incremental construction of distributed algorithms: on the distributed reference counting algorithm. the development of distributed algorithms and, more generally, distributed systems, is a complex, delicate and challenging process. refinement techniques of (system) models improve the process by using a proof assistant, and by applying a design methodology aimed at starting from the most abstract model and leading, in an incremental way, to the most concrete model, for producing a distributed solution. we show, using the distributed reference counting (drc) problem as our study, how models can be produced in an elegant and progressive way, thanks to the refinement and how the final distributed algorithm is built starting from these models. the development is carried out within the framework of the event b method and models are validated with a proof assistant.
two-level languages for program optimization. two-level languages incorporate binding time information inside types, that is, whether a piece of code is completely known at compile-time, or needs some more inputs and can be evaluated only at run-time. we consider the use of 2-level languages in the framework of partial evaluation, and use a 2-level version of the simply typed lambda calculus with recursion. we give an operational semantics, an equational theory and a denotational semantics, that give an account of the distinction between compilation and execution phases. an adequacy theorem is given to relate the two semantics, showing in particular how they agree on non-termination at compile time. we finally give a more refined model using functor categories.
program logic and equivalence in the presence of garbage collection. it is generally thought that reasoning about programs in memory safe, garbage collected languages is much easier than in languages where the programmer has more explicit control over memory. paradoxically, existing program logics are based on a low-level view of storage that is sensitive to the presence or absence of unreachable cells, and reynolds has pointed out that the hoare triples derivable in these logics are even incompatible with garbage collection. we present a study of a small language whose operational semantics includes a rule for reclaiming garbage. our main results include an analysis of propositions that are garbage insensitive, and full abstraction results connecting partial and total correctness to two natural notions of observational equivalence between programs.
compiling dyadic first-order specifications into map algebra. two techniques are designed for eliminating quantifiers from an existentially quantified conjunction of dyadic literals, in terms of the operators o, ∩, and -1 of the tarski-chin-givant formalism of relations. the use of such techniques is illustrated through increasingly challenging examples, and their algorithmic complexity is assessed.
axiomatization of frequent itemsets. mining association rules is very popular in the data mining community. most algorithms designed for finding association rules start with searching for frequent itemsets. typically, in these algorithms, counting phases and pruning phases are interleaved. in the counting phase, partial information about the frequencies of selected itemsets is gathered. in the pruning phase as much as possible of the search space is pruned, based on the counting information. we introduce frequent set expressions to represent (possible partial) information acquired in the counting phase. a frequent set expression is a pair containing an itemset and a fraction that is a lower bound on the actual frequency of the itemset. a system of frequent sets is a collection of such pairs. we give an axiomatization for those systems that are complete in the sense that they explicitly contain all information they logically imply. every system of frequent sets has a unique completion that actually represents all knowledge that can be derived. we also study sparse systems, in which not for every frequent set an expression is given. furthermore, we explore the links with probabilistic logics.
checkpointing with mutable checkpoints. there are two approaches to reduce the overhead associated with coordinated checkpointing: first is to minimize the number of synchronization messages and the number of checkpoints; the other is to make the checkpointing process non-blocking. in our previous work (ieee parallel distributed systems 9 (12) (1998) 1213), we proved that there does not exist a nonblocking algorithm which forces only a minimum number of processes to take their checkpoints. in this paper, we present a min-process algorithm which relaxes the non-blocking condition while tries to minimize the blocking time, and a non-blocking algorithm which relaxes the min-process condition while minimizing the number of checkpoints saved on the stable storage. the proposed non-blocking algorithm is based on the concept of "mutable checkpoint", which is neither a tentative checkpoint nor a permanent checkpoint. based on mutable checkpoints, our nonblocking algorithm avoids the avalanche effect and forces only a minimum number of processes to take their checkpoints on the stable storage.
combinatorial optimization algorithms for radio network planning. this paper uses a realistic problem taken from the telecommunication world as the basis for comparing different combinatorial optimization algorithms. the problem recalls the minimum hitting set problem, and is solved with greedy-like, darwinism and genetic algorithms. these three paradigms are described and analyzed with emphasis on the darwinism approach, which is based on the computation of &egr;-nets.
some properties of the factors of sturmian sequences. in this paper, we introduce the singular words of sturmian sequences, which play an important role in studying the properties of the factors of sturmian sequence. we also completely determine the powers of the factors, the overlaps of the factors and the structure of the palindromes of the factors.
splittable traffic partition in wdm/sonet rings to minimize sonet adms. sonet adms are the dominant cost factor in the wdm/sonet rings. recently several articles (belvaux et al., european j. oper. res. 108 (1) (1998) 26-35; clinescu and wan, traffic partition in wdm/sonet rings to minimize sonet adms, submitted for publication; gerstel et al., proc. ieee infocom'98, vol. 1, pp. 94-101; liu et al., proc. infocom, vol. 2, 2000, pp.~1020-1025; sutter et al., oper. res. 46 (5) (1998) 719-728) proposed a number of heuristics for traffic partition so as to use as few sonet adms as possible. most of these heuristics assumes wavelength-continuity, i.e., the same wavelength is allocated on all of the links in the path established for a traffic stream. it was first observed and argued by gerstel et al. that the number of adms can be potentially reduced by allowing a traffic stream to be locally transferred from one adm in a wavelength to another adm in a different wavelength at any intermediate node, in other words, the traffic streams are splittable. in this paper, we study two variations of this minimum adm problem with splittable traffic streams: all traffic streams have prespecified routings, and all traffic streams have no prespecified routings respectively. both variations are shown to be np-hard. for the former variation, a heuristic with approximation ratio at most 5/4 is proposed. for the latter variation, a similar heuristic with approximation ratio 3/2 is proposed.
a characterization of c.e. random reals. a real α is computably enumerable if it is the limit of a computable, increasing, converging sequence of rationals. a real α is random if its binary expansion is a random sequence. our aim is to offer a self-contained proof, based on the papers (calude et al., in: m. morvan, c. meinel, d. krob (eds.), proc. 15th symp. on theoretical aspects of computer science, paris, springer, berlin, 1998, pp. 596-606; chaitin, j. assoc. comput. mach. 22 (1975) 329; slaman, manuscript, 14 december 1998, 2 pp.; solovay, unpublished manuscript, ibm thomas j. watson research center, yorktown heights, new york, may 1975, 215 pp.), of the following theorem: a real is c.e. and random if and only if it is a chaitin&ohgr; real, i.e., the halting probability of some universal self-delimiting turing machine.
on the number of inductively minimal geometries. we count the number of inductively minimal geometries for any given rank by exhibiting a correspondence between the inductively minimal geometries of rank n and the trees with n + 1vertices. the proof of this correspondence uses the van rooij-wilf characterization of line graphs(see [11]).
edge coloring of bipartite graphs with constraints. a classical result from graph theory states that the edges of an l-regular bipartite graph can be colored using exactly l colors so that edges that share an endpoint are assigned different colors. in this paper, we study two constrained versions of the bipartite edge coloring problem. some of the edges adjacent to a specific pair of opposite vertices of an l-regular bipartite graph are already colored with s colors that appear only on one edge (single colors) and d colors that appear on two edges (double colors). we show that the rest of the edges can be colored using at most max{min{l+d,3l/2},l+(s+d)/2} total colors. we also show that this bound is tight by constructing instances in which max{min{l+d,3l/2},l+(s+d)/2} colors are indeed necessary. - some of the edges of an l-regular bipartite graph are already colored with s colors that appear only on one edge. we show that the rest of the edges can be colored using at most max{l+s/2,s} total colors. we also show that this bound is tight by constructing instances in which max{l+s/2,s} total colors are necessary.
streams and strings in formal proofs. streams are acyclic directed subgraphs of the logical flow graph of a proof representing bundles of paths with the same origin and the same end. the notion of stream is used to describe the evolution of proofs during cut-elimination in purely algebraic terms. the algebraic and combinatorial properties of flow graphs emerging from our analysis serve to elucidate logical phenomena. however, the full logical significance of the combinatorics, e.g. the absence of certain patterns within flow graphs, remains unclear.
on the size complexity of hybrid networks of evolutionary processors. the goal of this paper is twofold. firstly, to survey in a systematic and uniform way the main results regarding the size descriptional complexity measures of hybrid networks of evolutionary processors as generating devices. secondly, we improve some results about a size measure, prove that it is connected, and discuss the possibility of computing this measure for regular and context-free languages. we also briefly present a few np-complete problems and recall how they can be solved in linear time by accepting networks of evolutionary processors with linearly bounded resources (nodes, rules, symbols). finally, the size complexity of accepting hybrid networks of evolutionary processors recognizing all np languages in polynomial time is briefly discussed.
functional labels and syntactic entropy on dna strings and proteins. the dna of a cell is an object which admits a simple mathematical description and a convenient representation in a computer (it is given by an easily manipulatable list, a finite sequence in four letters typically of length between one million and 10 billions). in contrast to this, there is no simple way of describing the cell neither statically and even less temporally (dynamically). we shall indicate here a possible formalism of combinatorial and numerical (entropic) structures on spaces of sequences which reflect, up to some degree, the organization and functions of dna and proteins.
designing small keyboards is hard. we study the problem of placing symbols of an alphabet onto the minimum number of keys of a small keyboard so that any word of a given dictionary can be recognized univoquely only by looking at the corresponding sequence of keys. this problem is motivated by the design of small keyboards for mobile devices. we show that the problem is hard in general, and np-complete even if we only wish to decide whether two keys are sufficient. we also consider two variants of the problem. in the first one, symbols on a key must be contiguous in an ordered alphabet. in the second variant, a well-chosen measure of ambiguity in the recognition of the words is minimized given the number of keys. hardness and approximability results are given.
a coinductive completeness proof for the equivalence of recursive types. we prove that the equivalence of recursive types induced by the equality of their infinite unfoldings coincides with the equality of their interpretations as closures over the -model p.
a new proof-theoretic proof of the independence of kirby-paris' hydra theorem. a new proof is given for the independence of the termination of kirby-paris' hydra game from peano arithmetic by showing that it is strong enough to entail the termination of gentzen's reduction strategy for proof figures via an appropriate translation from derivations to hydras.
searching in random partially ordered sets. we consider the problem of searching for a given element in a partially ordered set. more precisely, we address the problem of computing efficiently near-optimal search strategies for typical partial orders under two classical models for random partial orders, the random graph model and the uniform model.we shall show that the problem of determining an optimal strategy is np-hard, but there are simple, fast algorithms able to produce near-optimal search strategies for typical partial orders under the two models of random partial orders that we consider. we present a (1 + o(1))- approximation algorithm for typical partial orders under the random graph model (constant p) and present a 6.34-approximation algorithm for typical partial orders under the uniform model. both algorithms run in polynomial time.
on the simulation of quantum turing machines. in this article we shall review several basic definitions and results regarding quantum computation. in particular, after defining quantum turing machines and networks the paper contains an exposition on continued fractions and on errors in quantum networks. the topic of simulation of quantum turing machines by means of obvious computation is introduced. we give a full discussion of the simulation of multitape quantum turing machines in a slight generalization of the class introduced by bernstein and vazirani. as main result we show that the fisher-pippenger technique can be used to give an o(tlogt) simulation of a multi-tape quantum turing machine by another belonging to the extended bernstein and vazirani class. this result, even if regarding a slightly restricted class of quantum turing machines improves the simulation results currently known in the literature.
semiperiodic words and root-conjugacy. a factor u of a word w is called right special if there exist two distinct letters a and b such that both ua and ub are factors of w. left special factors are defined symmetrically. by rw (resp. lw) we denote the minimal natural number such that there is no right (resp. left) special factor of w of length rw (resp. lw). moreover, hw (resp. kw) denotes the length of the shortest prefix (resp. suffix) which cannot be extended on the left (resp. right) in w. the parameters rw, lw, hw, and kw give interesting information on the structure of the word w. we consider the class of all finite words w such that rw > hw. these words are called semiperiodic. any periodic word is semiperiodic, whereas the converse is not generally true. several characterizations of semiperiodic words can be given. in particular, a word w is semiperiodic if and only if it has a period p ≤ |w| - rw. a further characterization of semiperiodic words relates with their infinite extensions. from this characterization one derives the following result, deeply related to the theorem of fine and wilf: if w is a (semiperiodic) word having two periods p,q ≤ |w| - rw, then also d = gcd(p,q) is a period of w. the root rw of a word w is its prefix whose length is equal to the minimal period of w. two words u and v are root-conjugate if their roots ru and rv are conjugate. one of the main results of the paper is the following. let w be a semiperiodic word. a word v has the same set of factors of length 1 +rw of w if and only if v is semiperiodic and root-conjugate with w. some applications and extensions of this result are proved.
completions in measure of languages and related combinatorial problems. we consider measures of languages induced by bernoulli distributions on the letters of a given alphabet. of particular interest are languages having a measure equal to 1 with respect to all positive bernoulli distributions (bernoulli sets). the main object of the paper is to study conditions ensuring that a given language has a finite bernoulli completion, i.e., it is included in a finite bernoulli set. some characterizations of languages having finite bernoulli completions are given. in the case of a two-letter alphabet it is shown that one can decide whether a finite language has a finite bernoulli completion or not. moreover, any finite code over a two-letter alphabet has a finite bernoulli completion. finally, we prove that two finite languages have the same measure with respect to all bernoulli distributions if and only if each of the two languages can be obtained from the other by using a finite number of times three suitable measure-invariant transformations.
codes of central sturmian words. a central sturmian word, or simply central word, is a word having two coprime periods p and q and length equal to p + q - 2. we consider sets of central words which are codes. some general properties of central codes are shown. in particular, we prove that a non-trivial maximal central code is infinite. moreover, it is not maximal as a code. a central code is called prefix central code if it is a prefix code. we prove that a central code is a prefix (resp., maximal prefix) central code if and only if the set of its 'generating words' is a prefix (resp., maximal prefix) code. a suitable arithmetization of the theory is obtained by considering the bijection θ, called ratio of periods, from the set of all central words to the set of all positive irreducible fractions defined as: θ(ε) = 1/1 and θ(w) = p/q (resp., θ(w) = q/p) if w begins with the letter a (resp., letter b), p is the minimal period of w, and q = |w| - p + 2. we prove that a central code x is prefix (resp., maximal prefix) if and only if θ(x) is an independent (resp., independent and full) set of fractions. finally, two interesting classes of prefix central codes are considered. one is the class of farey codes which are naturally associated with the farey series; we prove that farey codes are maximal prefix central codes. the other is given by uniform central codes. a noteworthy property related to the number of occurrences of the letter a in the words of a maximal uniform central code is proved.
fault-diagnosis of grid structures. the problem of fault diagnosis in grid-connected systems is considered. a diagnosis algorithm, called dags and based on the pmc model, is presented. dags provides a diagnosis which is shown to be correct, although possibly incomplete, if the cardinality of the actual fault set is below a bound tσ, dependent of the actual syndrome σ. a bound t independent of σ is also derived by a worst-case analysis covering the cases of triangular, square, hexagonal and octagonal grids. t is shown to be θ(n2/3), where n is the size of the system, for all the grids considered.
predictive learning models for concept drift. concept drift means that the concept about which data is obtained may shift from time to time, each time after some minimum permanence. except for this minimum permanence, the concept shifts may not have to satisfy any further requirements and may occur infinitely often. within this work is studied to what extent it is still possible to predict or learn values for a data sequence produced by drifting concepts. various ways to measure the quality of such predictions, including martingale betting strategies and density and frequency of correctness, are introduced and compared with one another. for each of these measures of prediction quality, for some interesting concrete classes, (nearly) optimal bounds on permanence for attaining learnability are established. the concrete classes, from which the drifting concepts are selected, include regular languages accepted by finite automata of bounded size, polynomials of bounded degree, and sequences defined by recurrence relations of bounded size. some important, restricted cases of drifts are also studied, for example, the case where the intervals of permanence are computable. in the case where the concepts shift only among finitely many possibilities from certain infinite, arguably practical classes, the learning algorithms can be considerably improved. copyright 2001 elsevier science b.v. all rights reserved.
synthesizing noise-tolerant language learners. an index for an r.e. class of languages (by definition) generates a sequence of grammars defining the class. an index for an indexed family of languages (by definition) generates a sequence of decision procedures defining the family. f. stephen's model of noisy data is empoloyed, in which, roughly, correct data crops up infintely often, and incorrect data only finitely often. studied, then, is the synthesis from indices for r.e. classes and for indexed families of languages of various kinds of noise-tolerant language-learners for the corresponding classes or families indexed. many positive results, as well as some negative results, are presented regarding the existence of such synthesizers. the proofs of most of the positive resutls yield, as pleasant corollaries, strict subset-principle or tell-tale style characterization for the noise-tolerant learn-ability of the corresponding classes or families indexed.
control structures in hypothesis spaces: the influence on learning. in any learnability setting, hypotheses are conjectured from some hypothesis space. studied herein are the influence on learnability of the presence or absence of certain control structures in the hypothesis space. first presented are control structure characterizations of some rather specific but illustrative learnability results. the presence of these control structures is thereby shown essential to maintain full learning power. then presented are the main theorems. each of these non-trivially characterizes the invariance of a learning class over hypothesis space v and the presence of a particular projection control structure, called proj, in v as: v has suitable instances of all denotational control structures. in a sense, then, proj epitomizes the control structures whose presence need not help and whose absence need not hinder learning power.
examples of undecidable problems for 2-generator matrix semigroups. examples of undecidable problems for 2-generator matrix semigroups
random generation of dfas. this document gives a generalization on the alphabet size of the method that is described in nicaud's thesis for randomly generating complete dfas. first, we recall some properties of m-ary trees and we give a bijection between the set of m-ary trees and the set r(m, n) of generalized tuples. we show that this bijection can be built on any total prefix order on σ*, then we give the relations that exist between the elements of r(m,n) and complete dfas built on an alphabet of size greater than 2. we give algorithms that allow us to randomly generate accessible complete dfas. finally, we provide experimental results that show that most of the accessible complete dfas built on an alphabet of size greater than 2 are minimal.
nfa reduction algorithms by means of regular inequalities. we present different techniques for reducing the number of states and transitions in nondeterministic automata. these techniques are based on the two preorders over the set of states, related to the inclusion of left and right languages. since their exact computation is np-hard, we focus on polynomial approximations which enable a reduction of the nfa all the same. our main algorithm relies on a first approximation, which can be easily implemented by means of matrix products with an o(mn3) time complexity, and optimized to an o(mn) time complexity, where m is the number of transitions and n is the number of states. this first algorithm appears to be more efficient than the known techniques based on equivalence relations as described by lucian ilie and sheng yu. afterwards, we briefly describe some more accurate approximations and the exact (but exponential) calculation of these preorders by means of determinization.
enumeration of l-convex polyominoes by rows and columns. in this paper, we consider the class of l-convex polyominoes, i.e. the convex polyominoes in which any two cells can be connected by a path of cells in the polyomino that switches direction between the vertical and the horizontal at most once.using the eco method, we prove that the number fn of l-convex polyominoes with perimeter 2(n + 2) satisfies the rational recurrence relation fn = 4fn-1 - 2fn-2, with f0 = 1, f1 = 2, f2 = 7. moreover, we give a combinatorial interpretation of this statement. in the last section, we present some open problems.
a reconstruction algorithm for l-convex polyominoes. we give an algorithm that uniquely reconstruct an l-convex polyomino from the size of some special paths, called bordered l-paths.
canonical derivatives, partial derivatives and finite automaton constructions. let e be a regular expression. our aim is to establish a theoretical relation between two well-known automata recognizing the language of e, namely the position automaton pe constructed by glushkov or mcnaughton and yamada, and the equation automaton ee constructed by mirkin or antimirov. we define the notion of c-derivative (for canonical derivative) of a regular expression e and show that if e is linear then two brzozowski's derivatives of e are aci-similar if and only if the corresponding c-derivatives are identical. it allows us to represent the berry-sethi's set of continuations of a position by a unique c-derivative, called the c-continuation of the position. hence the definition of ce, the c-continuation automaton of e, whose states are pairs made of a position of e and of the associated c-continuation. if states are viewed as positions, ce is isomorphic to pe. on the other hand, a partial derivative, as defined by antimirov, is a class of c-derivatives for some equivalence relation, thus ce reduces to ee. finally ce makes it possible to go from pe to ee, while this cannot be achieved directly (from the state graphs). these theoretical results lead to an o(|e|2) space and time algorithm to compute the equation automaton, where |e| is the size of the expression. this is the complexity of the most efficient constructions yielding the position automaton, while the size of the equation automaton is not greater and generally much smaller than the size of the position automaton.
solution of some conjectures about topological properties of linear cellular automata. we study two dynamical properties of linear d-dimensional cellular automata over zm namely, denseness of periodic points and topological mixing. for what concerns denseness of periodic points, we complete the work initiated in (theoret. comput. sci. 174 (1997) 157, theoret. comput. sci. 233 (1-2) (2000) 147, 14th annual symp. on theoretical aspects of computer science (stacs '97), lncs n. 1200, springer, berlin, 1997, pp. 427-438) by proving that a linear cellular automata has dense periodic points over the entire space of configurations if and only if it is surjective (as conjectured in (cattaneo et al., 2000)). for non-surjective linear ca we give a complete characterization of the subspace where periodic points are dense. for what concerns topological mixing, we prove that this property is equivalent to transitivity and then easily checkable. finally, we classify linear cellular automata according to the definition of chaos given by devaney in (an introduction to chaotic dynamical systems, 2nd ed., addison-wesley, reading, ma, usa, 1989).
new resource augmentation analysis of the total stretch of srpt and sjf in multiprocessor scheduling. this paper studies online job scheduling on multiprocessors and, in particular, investigates the algorithms shortest remaining processing time first (srpt) and shortest job first (sjf) for minimizing total stretch, where the stretch of a job is its flow time (response time) divided by its processing time. srpt is perhaps the most well-studied algorithm for minimizing total flow time or stretch. this paper gives the first resource augmentation analysis of the total stretch of srpt, showing that it is indeed o(1)-speed 1-competitive. this paper also gives a simple lower bound result showing that srpt is not s-speed 1-competitive for any s < 1.5.this paper also makes contribution to the analysis of sjf. extending the work of [l. becchetti, s. leonardi, a. marchetti-spaccamela, k. pruhs, online weighted flow time and deadline scheduling, in: random-approx, 2001, pp. 36-47], we are able to show that sjf is o(1)-speed 1-competitive for minimizing total stretch. more interestingly, we find that the competitiveness of sjf can be reduced arbitrarily by increasing the processor speed (precisely, sjf is o(s)-speed (1/s)-competitive for any s ≥ 1). we conjecture that srpt also admits a similar result.
on-line stream merging in a general setting. this paper is concerned with on-line scheduling algorithms for merging streams in a video-on-demand system so as to minimize the server bandwidth. we present the first algorithm that has a constant competitive factor (precisely, 5). our algorithm, unlike previous ones, is not limited to the scenario where clients are equipped with large buffer and client receiving bandwidth. it remains 5-competitive in all settings of buffer size and receiving bandwidth. technically speaking, our algorithm is based on a novel observation that the behavior of any schedule can be modeled by a rectilinear (binary) tree on a grid. this observation eases the analysis of our algorithm as well as the optimal algorithm.
presheaf models for ccs-like languages. the aim of this paper is to harness the mathematical machinery around presheaves for the purposes of process calculi. joyal, nielsen and winskel proposed a general definition of bisimulation from open maps. here we show that open-map bisimulations within a range of presheaf models are congruences for a general process language, in which ccs and related languages are easily encoded. the results are then transferred to traditional models for processes. by first establishing the congruence results for presheaf models, abstract, general proofs of congruence properties can be provided and the awkwardness caused through traditional models not always possessing the cartesian liftings, used in the breakdown of process operations, are side stepped. the abstract results are applied to show that hereditary history-preserving bisimulation is a congruence for ccs-like languages to which is added a refinement operator on event structures as proposed by van glabbeek and goltz.
generating and characterizing the perfect elimination orderings of a chordal graph. we develop a constant time transposition "oracle" for the set of perfect elimination orderings of chordal graphs. using this oracle, we can generate a gray code of all perfect elimination orderings in constant amortized time using known results about antimatroids. using clique trees, we show how the initialization of the algorithm can be performed in linear time. we also develop two new characterizations of perfect elimination orderings: one in terms of chordless paths, and the other in terms of minimal u-v separators.
on infinite transition graphs having a decidable monadic theory. we define a family of graphs whose monadic theory is (in linear space) reducible to the monadic theory s2s of the complete ordered binary tree. this family contains strictly the context-free graphs investigated by muller and schupp, and also the equational graphs defined by courcelle. using words as representations of vertices, we give a complete set of representatives by prefix rewriting of rational languages. this subset of possible representatives is a boolean algebra preserved by transitive closure of arcs and by rational restriction on vertices.
on the transition graphs of turing machines. as for pushdown automata, we consider labelled turing machines with ε-rules. with any turing machine m and with a rational set c of configurations, we associate the restriction to c of the ε-closure of the transition set of m. we get the same family of graphs by using the labelled word rewriting systems. we show that this family is the set of graphs obtained from the binary tree by applying an inverse mapping into f followed by a rational restriction, where f is any family of recursively enumerable languages containing the rational closure of all linear languages. we show also that this family is obtained from the rational graphs by inverse rational mappings. finally we show that this family is also the set of graphs recognized by (unlabelled) turing machines with labelled final states, and even if we restrict to deterministic turing machines.
wide-sense nonblocking for symmetric or asymmetric 3-stage clos networks under various routing strategies. benes established the notion of wide-sense nonblocking by constructing an example on the symmetric 3-stage clos network under packing which requires less hardware compared to strict nonblocking. this has remained the only example of a wide-sense non-blocking 3-stage clos network which is not strictly nonblocking. in this paper, we study packing as well as several other routing strategies which have been studied in the literature and proved that no other example exists for the symmetric 3-stage clos network. we then extend the study to asymmetric 3-stage clos network for the first time. in particular, we extend benes example to asymmetric 3-stage clos network and show that these are the only two possible examples for the strategies under study.
periodicity, morphisms, and matrices. in 1965, fine and wilf proved the following theorem: if (fn)n≥0 and (gn)n≥0 are periodic sequences of real numbers, of period lengths h and k, respectively, and fn = gn for 0 ≤ n > h + k - gcd(h,k), then fn = gn for all n ≥ 0. furthermore, the constant h + k - gcd(h,k) is best possible. in this paper, we consider some variations on this theorem. in particular, we study the case where fn ≤ gn, instead of fn = gn. we also obtain generalizations to more than two periods.we apply our methods to a previously unsolved conjecture on iterated morphisms, the decreasing length conjecture: if h : σ* → σ* is a morphism with |σ|= n, and w is a word with |w| < |h(w)| < |h2(w)| < ... < |hk(w)|, then k ≤ n.
oblivious polynomial evaluation and oblivious neural learning. we study the problem of oblivious polynomial evaluation (ope). there are two parties, alice who has a polynomial p, and bob who has an input x. the goal is for bob to compute p(x) in such a way that alice learns nothing about x and bob learns only what can be inferred from p(x). previously existing protocols were based on some newly-invented intractability assumptions that have not been well studied, so one may have doubts about the security of these protocols. in this paper, we propose ope protocols which are only based on the standard primitive oblivious transfer, and still our protocols are more efficient in several natural cases. our protocols can also be easily modified to handle multivariate polynomials and polynomials over floating-point numbers. as an application, we study the problem of oblivious neural learning, where one party has a neural network and the other, with some training set, wants to train the neural network in an oblivious way. we provide a protocol for this problem, which is based on our protocol for ope.
evolution and observation--a non-standard way to generate formal languages. in biology and chemistry a standard proceeding is to conduct an experiment, observe its progress, and then take the result of this observation as the final output. inspired by this, we have introduced p/o systems (a. alhazov, c. martín-vide, gh. paun, pre-proc. of the workshop on membrane computing 2003, tarrragona, spain; http://pizarro.fll.urv.es/continguts/linguistica/ proyecto/reports/wmc03.html), where languages are generated by multiset automata that observe the evolution of membrane systems.now we apply this approach also to more classical devices of formal language theory. namely, we use finite automata observing the derivations of grammars or of lindenmayer systems. we define several modes of operation for grammar/observer systems. in two of these modes a context-free grammar (or even a locally commutative context-free grammar) with a finite automaton as observer suffices to generate any recursively enumerable language. in a third case, we obtain a class of languages between the context-free and context-sensitive ones.
cartesian authentication codes from functions with optimal nonlinearity. in this paper, we present several classes of authentication codes using functions with perfect nonlinearity and optimum nonlinearity. some of the authentication codes are optimal. on the other hand, these authentication codes are easy to implement due to their simple algebraic structures.
an algorithm for reporting maximal -cliques. given two graphs, a fundamental task faced by matching algorithms consists of computing either the (connected) maximal common induced subgraphs ((c)mcis) or the (connected) maximal common edge subgraphs ((c)mces). in particular, computing the cmcis or cmces reduces to reporting so-called c-connected cliques in product graphs, a problem for which an algorithm has been presented in i. koch, fundamental study: enumerating all connected maximal common subgraphs in two graphs, theoret. comput. sci. 250 (1-2), (2001) 1-30. this algorithm suffers from two problems which are corrected in this note.
model checking mobile ambients. we settle the complexity bounds of the model checking problem for the ambient calculus with public names against the ambient logic. we show that if either the calculus contains replication or the logic contains the guarantee operator, the problem is undecidable. in the case of the replication-free calculus and guarantee-free logic we prove that the problem is pspace-complete. for the complexity upper bound, we devise a new representation of processes that remains of polynomial size during process execution; this allows us to keep the model checking procedure in polynomial space. moreover, we prove pspace-hardness of the problem for several quite simple fragments of the calculus and the logic; this suggests that there are no interesting fragments with polynomial-time model checking algorithms.
finding frequent items in data streams. we present a 1-pass algorithm for estimating the most frequent items in a data stream using limited storage space. our method relies on a data structure called a count sketch, which allows us to reliably estimate the frequencies of frequent items in the stream. our algorithm achieves better space bounds than the previously known best algorithms for this problem for several natural distributions on the item frequencies. in addition, our algorithm leads directly to a 2-pass algorithm for the problem of estimating the items with the largest (absolute) change in frequency between two data streams. to our knowledge, this latter problem has not been previously studied in the literature.
on factorization forests of finite height. simon (theoret. comput. sci. 72 (1990) 65-94) has proved that every morphism from a free semigroup to a finite semigroup s admits a ramseyan factorization forest of height at most 9|s|. in this paper, we prove the same result of simon with an improved bound of 7|s|. we provide a simple algorithm for constructing a factorization forest. in addition, we show that the algorithm cannot be improved significantly. we give examples of semigroup morphism such that any ramseyan factorization forest for the morphism would require a height not less than |s|.
probabilistic analysis of algorithms for the dutch national flag problem. a detailed probabilistic analysis is given of algorithms for the dutch national flag problem. we derive central and local limit theorems for the cost, as well as probabilities of large deviations. performance of a related algorithm is also studied.
on the entropy of regular languages. let l be an irreducible regular language. let w be a non-empty set of words (or sub-words) of l and denote by lw = {v ∈ l:w ⊏ v, ∀w ∈ w} the language obtained from l by forbidding all the words w in w. then the entropy decreases strictly: ent(lw) < ent(l). in this note we present a new proof of this fact, based on a method of gromov, which avoids the perron-frobenius theory. this result applies to the regular languages of finitely generated free groups and an additional application is presented.
subset construction complexity for homogeneous automata, position automata and zpc-structures. the aim of this paper is to investigate how subset construction performs on specific families of automata. a new upper bound on the number of states of the subset-automaton is established in the case of homogeneous automata. the complexity of the two basic steps of subset construction, i.e. the computation of deterministic transitions and the set equality tests, is examined depending on whether the nondeterministic automaton is an unrestricted one, an homogeneous one, a position one or a zpc-structure, which is an implicit construction for a position automaton. copyright 2001 elsevier science b.v.
growth-sensitivity of context-free languages. a language l over a finite alphabet σ is called growth-sensitive if forbidding any set of subwords f yields a sub-language lf whose exponential growth rate is smaller than that of l. it is shown that every (essentially) ergodic non-linear context-free language of convergent type is growth-sensitive. "ergodic" means that the dependency di-graph of the generating context-free grammar is strongly connected, and "essentially ergodic" means that there is only one nonregular strong component in that graph. the methods combine (1) an algorithm for constructing from a given grammar one that generates the associated 2-block language and (2) a generating function technique regarding systems of algebraic equations. furthermore, the algorithm of (1) preserves unambiguity as well as the number of non-regular strong components of the dependency di-graph.
minimizing the size of an identifying or locating-dominating code in a graph is np-hard. let g = (v,e) be an undirected graph and c a subset of vertices. if the sets br(υ) ∩ c, υ ∈ v (respectively, υ ∈ v\c), are all nonempty and different, where br(υ) denotes the set of all points within distance r from υ, we call c an r-identifying code (respectively, an r-locating-dominating code). we prove that, given a graph g and an integer k, the decision problem of the existence of an r-identifying code, or of an r-locating-dominating code, of size at most k in g, is np-complete for any r.
on the amplitude of intervals of natural numbers whose every element has a common prime divisor with at least an extremity. an interval [a, a + d] of natural numbers verifies the property of no coprimeness if and only if every element a + 1, a + 2,..., a + d - 1 has a common prime divisor with extremity a or a + d. we show the set of such a and the set of such d are recursive. the computation of the first d leads to rise a lot of open problems.
an inexact-suffix-tree-based algorithm for detecting extensible patterns. given an input sequence of data, a rigid pattern is a repeating sequence, possibly interspersed with dont-care characters. the data could be a sequence of characters or sets of characters or even real values. in practice, the patterns or motifs of interest are the ones that also allow a variable number of gaps (or dont-care characters): these are patterns with spacers termed extensible patterns in a bioinformatics context, similar patterns have also been called flexible patterns or motifs. the extensibility is succinctly defined by a single integer parameter d ≥ 1 which is interpreted as the allowable space to be between 1 and d characters between two successive solid characters in a reported motif. we introduce a data structure called the inexact-suffix tree and present an algorithm based on this data structure. this has been tested on primarily biological data such as dna and protein sequences. however the generality of the system makes it equally applicable in other data mining, clustering, and knowledge extraction applications.
effectively closed sets and graphs of computable real functions. in this paper, we compare the computability and complexity of a continuous real function f with the computability and complexity of the graph g of the function f. a similar analysis will be carried out for functions on subspaces of the real line such as the cantor space, the baire space and the unit interval. in particular, we define four basic types of effectively closed sets c depending on whether (i) the set of closed intervals which with nonempty intersection with c is recursively enumerable (r.e.), (ii) the set of closed intervals with empty intersection with c is r.e., (iii) the set of open intervals which with nonempty intersection with c is r.e., and (iv) the set of open intervals with empty intersection with c is r.e. we study the relationships between these four types of effectively closed sets in general and the relationships between these four types of effectively closed sets for closed sets which are graphs of continuous functions.
probable innocence revisited. in this paper we propose a formalization of probable innocence, a notion of probabilistic anonymity that is associated to "realistic" protocols such as crowds. we analyze critically two different definitions of probable innocence from the literature. the first one, corresponding to the property that reiter and rubin have proved for crowds, aims at limiting the probability of detection. the second one, by halpern and o'neill, aims at constraining the attacker's confidence. our proposal combines the spirit of both these definitions while generalizing them. in particular, our definition does not need symmetry assumptions, and it does not depend on the probabilities of the users to perform the action of interest. we show that, in case of a symmetric system, our definition corresponds exactly to the one of reiter and rubin. furthermore, in the case of users with uniform probabilities, it amounts to a property similar to that of halpern and o'neill.another contribution of our paper is the study of probable innocence in the case of protocol composition, namely when multiple runs of the same protocol can be linked, as in the case of crowds.
actions, wreath products of -varieties and concatenation product. the framework of c-varieties, introduced by the third author, extends the scope of eilenberg's variety theory to new classes of languages. in this paper, we first define c-varieties of actions, which are closely related to automata, and prove their equivalence with the original definition of c-varieties of stamps. next, we complete the study of the wreath product initiated by ésik and ito by extending its definition to c-varieties in two different ways, which are proved to be equivalent. we also state an extension of the wreath product principle, a standard tool of language theory. finally, our main result generalizes to c-varieties the algebraic characterization of the closure under product of a variety of languages.
on maximal instances for the original syntenic distance. the syntenic distance between two genomes has been introduced by ferretti, nadeau and sankoff as an approximation of the evolutionary distance between genomes for which the gene order is not known. this distance is the minimum number of fusions, fissions and translocations required to transform a genome into another. kleinberg and liben-nowell, as well as pisanti and sagot, proved independently that for genomes with n chromosomes the diameter for this distance is 2n - 4. pisanti and sagot also generalized this result, showing that the maximal distance between a genome with m chromosomes and a genome with n chromosomes is n + m - 4. kleinberg and liben-nowell asked for a characterization of maximal instances for the syntenic distance (pairs of n-chromosome genomes at a distance of 2n - 4). in this paper, we give such a characterization, and show that we can extend it to pairs of genomes with, respectively, n and m chromosomes that are at maximal distance.
graph encoding of 2-gon tilings. 2d-gon tilings with parallelograms are a model used in physics to study quasicrystals, and they are also important in combinatorics for the study of aperiodic structures. in this paper, we study the graph induced by the adjacency relation between tiles. this relation can been used to encode simply and efficiently 2d-gon tilings for algorithmic manipulation. we show for example how it can be used to sample random 2d-gon tilings.
pattern matching as cut elimination. we present a typed pattern calculus with explicit pattern matching and explicit substitutions, where both the typing rules and the reduction rules are modeled on the same logical proof system, namely gentzen sequent calculus for intuitionistic minimal logic. our calculus is inspired by the curry-howard isomorphism, in the sense that types, both for patterns and terms, correspond to propositions, terms correspond to proofs, and term reduction corresponds to sequences of sequent proof normalization steps performed by cut elimination. the calculus enjoys subject reduction, confluence, preservation of strong normalization w.r.t a system with meta-level substitutions and strong normalization for well-typed terms. as a consequence, it can be seen as an implementation calculus for functional formalisms defined with meta-level operations for pattern matching and substitutions. this work is a revised and extended version of cerrito and kesner (14th annual ieee symposium on logic in computer science (lics), ieee computer society press, silver spring, md, 1999, pp. 98-108).
tilings: recursivity and regularity. we establish a first step towards a "rice theorem" for tilings: for non-trivial sets, it is undecidable to know whether two different tile sets produce the same tilings of the plane. then, we study quasiperiodicity functions associated with tilings. this function is a way to measure the regularity of tilings. we prove that, not only almost all recursive functions can be obtained as quasiperiodicity functions, but also, a function which overgrows any recursive function.
derivatives of rational expressions and related theorems. our aim is to study the set of k-rational expressions describing rational series. more precisely we are concerned with the definition of quotients of this set by coarser and coarser congruences which lead to an extension--in the case of multiplicities--of some classical results stated in the boolean case. in particular, multiplicity analogues of the well known theorems of brzozowski and antimirov are provided.
synchronization of musical words. we study the synchronization of musical sequences by means of an operation defined on finite or infinite words called superimposition. this operation can formalize basic musical structures such as melodic canons and serial counterpoint. in the case of circular canons, we introduce the superimposition of infinite words, and we present an enumeration algorithm involving lyndon words, which appear to be a useful tool for enumerating periodic musical structures. we also define the superimposition of finite words, the superimposition of languages, and the iterated superimposition of a language, which is applied to the study of basic aspects of serial music. this leads to the study of closure properties of rational languages of finite words under superimposition and iterated superimposition. the rationality of the transduction associated with the superimposition appears to be a powerful argument in the proof of these properties. since the superimposition of finite words is the max operation of a sup-semilattice, the last section addresses the link between the rationality of a sup-semilattice operation and the rationality of the order relation associated with it.
the structure of a linear chip firing game and related models. in this paper, we study the dynamics of sand grains falling in sand piles. usually sand piles are characterized by a decreasing integer partition and grain moves are described in terms of transitions between such partitions. we study here four main transition rules. the worst classical one, introduced by brylawski (discrete math. 6 (1973) 201) induces a lattice structure lb(n) (called dominance ordering) between decreasing partitions of a given integer n. we prove that a more restrictive transition rule, called spm rule, induces a natural partition of lb(n) in suborders, each one is associated to a fixed point for the spm rule. in the second part, we extend the spm rule in a natural way and obtain a model called linear chip firing game (theoret. comput. sci. 115 (1993) 321). we prove that this new model has interesting properties: the induced order is a lattice, a natural greedoid can be associated to the model and it also defines a strongly convergent game. in the last section, we generalize the spm rule in another way and obtain other lattice structure parametrized by some , denoted by l(n,), which form a decreasing sequence of lattices when varies in [n+2,n]. for each , we characterize the fixed point of l(n,) and give the value of its maximal sized chain's length. we also note that l(n,n+2) is the lattice of all compositions of n.
modeling and querying biomolecular interaction networks. we introduce a formalism to represent and analyze protein-protein and protein-dna interaction networks. we illustrate the expressivity of this language, by proposing a formal counterpart of kohn's compilation on the mammalian cell-cycle control. this effectively turns an otherwise static knowledge into a discrete transition system incorporating a qualitative description of the dynamics. we then propose to use the computation tree logic (ctl) as a query language for querying the possible behaviors of the system. we provide examples of biologically relevant queries expressed in ctl about the mammalian cell-cycle control and show the effectiveness of symbolic model checking tools to evaluate ctl queries in this context.
optimizing stable in-place merging. in 2000, geffert et al. (theoret. comput. sci. 237 (2000) 159) presented an asymptotically efficient algorithm for stable merging in constant extra space. the algorithm requires at most m1(t + 1) + m2/2t + o(m1) comparisons (t = ⌊log2(m2/m1)⌋) and 5m2 + 12m1 + o(m1) moves, where m1 and m2 are the sizes of two ordered sublists to be merged, and m1 ≤ m2. this paper optimizes the algorithm. the optimized algorithm is simpler than their algorithm, and makes at most m1(t + 1) + m2/2t + o(m1 + m2) comparisons and 6m2 + 7m1 + o(m1 + m2) moves.
a fixpoint theory for non-monotonic parallelism. this paper studies parallel recursion. the trace specification language used in this paper incorporates sequentially, nondeterminism, reactiveness (including infinite traces), three forms of parallelism (including conjunctive, fair-interleaving and synchronous parallelism) and general recursion. in order to use tarski's theorem to determine the fixpoints of recursions, we need to identify a well-founded partial order. several orders are considered, including a new order called the lexical order, which tends to simulate the execution of a recursion in a similar manner as the egli-milner order. a theorem of this paper shows that no appropriate order exists for the language. tarski's theorem alone is not enough to determine the fixpoints of parallel recursions. instead of using tarski's theorem directly, we reason about the fixpoints of terminating and nonterminating behaviours separately. such reasoning is supported by the laws of a new composition called partition. we propose a fixpoint technique called the partitioned fixpoint, which is the least fixpoint of the nonterminating behaviours after the terminating behaviours reach their greatest fixpoint. the surprising result is that although a recursion may not be lexical-order monotonic, it must have the partitioned fixpoint, which is equal to the least lexical-order fixpoint. since the partitioned fixpoint is well defined in any complete lattice, the results are applicable to various semantic models. existing fixpoint techniques simply become special cases of the partitioned fixpoint. for example, an egli-milner-monotonic recursion has its least egli-milner fixpoint, which can be shown to be the same as the partitioned fixpoint. the new technique is more general than the least egli-milner fixpoint in that the partitioned fixpoint can be determined even when a recursion is not egli-milner monotonic. examples of non-monotonic recursions are studied. their partitioned fixpoints are shown to be consistent with our intuition.
divide-and-conquer recurrences associated with generalized heaps, optimal merge, and related structures. an elementary approach is given to studying the recurrence relations associated with generalized heaps (or d-heaps), cost of optimal merge, and generalized divide-and-conquer minimization problems. we derive exact formulae for the solutions of all such recurrences and give some applications. in particular, we present a precise probabilistic analysis of floyd's algorithm for constructing d-heaps when the input is randomly given. a variant of d-heap having some interesting combinatorial properties is also introduced.
the best expert versus the smartest algorithm. in this paper, we consider the problem of online prediction using expert advice. under different assumptions, we give tight lower bounds on the gap between the best expert and any online algorithm that solves the problem.
approximations for steiner trees with minimum number of steiner points. given n terminals in the euclidean plane and a positive constant, find a steiner tree interconnecting all terminals with the minimum number of steiner points such that the euclidean length of each edge is no more than the given positive constant. this problem is np-hard with applications in vlsi design, wdm optical networks and wireless communications. in this paper, we show that (a) the steiner ratio is 1/ 4, that is, the minimum spanning tree yields a polynomial-time approximation with performance ratio exactly 4, (b) there exists a polynomial-time approximation with performance ratio 3, and (c) there exists a polynomial-time approxi-mation scheme under certain conditions.
on miniaturized problems in parameterized complexity theory. we introduce a general notion of miniaturization of a problem that comprises the different miniaturizations of concrete problems considered so far. we develop parts of the basic theory of miniaturizations. using the appropriate logical formalism, we show that the miniaturization of a definable problem in w[t] lies in w[t], too. in particular, the miniaturization of the dominating set problem is in w[2]. furthermore, we investigate the relation between f(k)ċno(k) time and subexponential time algorithms for the dominating set problem and for the clique problem.
machine-based methods in parameterized complexity theory. we give machine characterizations of most parameterized complexity classes, in particular, of w[p], of the classes of the w-hierarchy, and of the a-hierarchy. for example, we characterize w[p] as the class of all parameterized problems decidable by a nondeterministic fixed-parameter tractable algorithm whose number of nondeterministic steps is bounded in terms of the parameter. the machine characterizations suggest the introduction of a hierarchy wfunc between the w- and the a-hierarchy. we study the basic properties of this hierarchy.
a space-efficient algorithm for sequence alignment with inversions and reversals. a dynamic programming algorithm to find an optimal alignment for a pair of dna sequences has been described by schöniger and waterman. the alignments use not only substitutions, insertions, and deletions of single nucleotides, but also inversions, which are the reversed complements, of substrings of the sequences. with the restriction that the inversions are pairwise non-intersecting, their proposed algorithm runs in o(n2m2) time and consumes o(n2m2) space, where n and m are the lengths of the input sequences, respectively. we develop a space-efficient algorithm to compute such an optimal alignment which consumes only o(nm) space within the same amount of time. our algorithm enables the computation for a pair of dna sequences of length up to 10,000 to be carried out on an ordinary desktop computer. simulation study is conducted to verify some biological facts about gene shuffling across species.
approximation algorithms for nmr spectral peak assignment. we study a constrained bipartite matching problem where the input is a weighted bipartite graph g = (u, v, e), u is a set of vertices following a sequential order, v is another set of vertices partitioned into a collection of disjoint subsets, each following a sequential order, and e is a set of edges between u and v with non-negative weights. the objective is to find a matching in g with the maximum weight that satisfies the given sequential orders on both u and v, i.e. if ui+1 follows ui in u and if vj+1 follows vj in v, then ui is matched with vj if and only if ui+1 is matched with vj+1. the problem has recently been formulated as a crucial step in an algorithmic approach for interpreting nmr spectral data (ieee comput sci. eng. 4 (2002) 50-62). the interpretation of nmr spectral data is known as a key problem in protein structure determination via nmr spectroscopy. unfortunately, the constrained bipartite matching problem is np-hard (ieee comput. sci. eng. 4 (2002) 50-62). we first propose a 2-approximation algorithm for the problem, which follows directly from the recent result of bar-noy et al. (proc. 32nd acm symp. on theory of computing (stoc'00), 2000, pp. 735 -744) on interval scheduling. however, our extensive experimental results on real nmr spectral data illustrate that the algorithm perform poorly in terms of recovering target-matching edges. we then propose another approximation algorithm that tries to take advantage of the "density" of the sequential order information in v. although we are only able to prove an approximation ratio of 3 log2d for this algorithm, where d is the length of a longest string in v, the experimental results demonstrate that this new algorithm performs much better on real data, i.e. it is able to recover a large fraction of target-matching edges and the weight of its output matching is often in fact close to the maximum. we also prove that the problem is max snp-hard, even if the input bipartite graph is unweighted. we further present an approximation algorithm for a nontrivial special case that breaks the ratio 2 barrier.
on approximating minimum vertex cover for graphs with perfect matching. it has been a challenging open problem whether there is a polynomial time approximation algorithm for the vertex cover problem whose approximation ratio is bounded by a constant less than 2. in this paper, we study the vertex cover problem on graphs with perfect matching (shortly, vc-pm). we show that if the vc-pm problem has a polynomial time approximation algorithm with approximation ratio bounded by a constant less than 2, then so does the vertex cover problem on general graphs. approximation algorithms for vc-pm are developed, which induce improvements over previously known algorithms on sparse graphs. for example, for graphs of average degree 5, the approximation ratio of our algorithm is 1.414, compared with the previously best ratio 1.615 by halldórsson and radhakrishnan.
an efficient algorithm to find a double-loop network that realizes a given l-shape. double-loop networks have been widely studied as an architecture for local area networks. it is well known that the minimum distance diagram of a double-loop network yields an l-shape. given a positive integer n, it is desirable to find a double-loop network with its diameter being the minimum among all double-loop networks with n nodes. since the diameter of a double-loop network can be easily computed from its l-shape, one method is to start with a desirable l-shape and then find a double-loop network to realize it. this is a problem discussed by many authors [f. aguiló, m.a. fiol, an efficient algorithm to find optimal double loop networks, discrete math. 138 (1995) 15-29, r.c. chan, c.y. chen, z.x. hong, a simple algorithm to find the steps of double-loop networks, discrete appl. math. 121 (2002) 61-72, c.y. chen, f.k. hwang, the minimum distance diagram of double-loop networks, ieee trans. comput. 49 (2000) 977-979, p. esqué, f. aguiló, m.a. fiol, double commutative-step diagraphs with minimum diameters, discrete math. 114 (1993) 147-157] and it has been open for a long time whether this problem can be solved in o(log n) time. in this paper, we will provide a simple and efficient o(log n)-time algorithm for solving this problem.
a coalgebraic approach to kleene algebra with tests. kleene algebra with tests is an extension of kleene algebra, the algebra of regular expressions, which can be used to reason about programs. we develop a coalgebraic theory of kleene algebra with tests, along the lines of the coalgebraic theory of regular expressions based on deterministic automata. since the known automata-theoretic presentation of kleene algebra with tests does not lend itself to a coalgebraic theory, we define a new interpretation of kleene algebra with tests expressions and a corresponding automata-theoretic presentation. one outcome of the theory is a coinductive proof principle, that can be used to establish equivalence of our kleene algebra with tests expressions.
robust algorithms for constructing strongly convex hulls in parallel. given a set s of n points in the plane, an ε-strongly convex δ-hull of s is defined as a convex polygon p with the vertices taken from s such that no point of s lies farther than δ outside p and such that even if the vertices of p are perturbed by as much as ε, p remains convex. this paper presents the first parallel robust method for this generalized convex hull problem (note that the convex hull of s is the 0-strongly convex 0-hull of s). we show that an ε-strongly convex o(ε + β)-hull of s can be constructed in o(log3n) time using n processors with imprecise computations, where β is the error unit of primitive operations. this result also implies an improved sequential algorithm. our algorithm consists of two parts: (1) computing a convex o(ε + β) -hull of n points, in o(log3n) time using n processors, and (2) constructing an ε-strongly convex o(ε + β)-hull of a convex polygon with n vertices, in o(log2n) time with n processors. we also find an approximate bridge of two sets with n points each, in o(log2n) time using n processors, which we use as a subroutine. all these algorithms are fundamental and have their own applications. the parallel computational model in this paper is the erew pram.
a ptas for weight constrained steiner trees in series-parallel graphs. in this paper, we study the problem of computing a minimum cost steiner tree subject to weight constraint in a series-parallel graph where each edge has a nonnegative integer cost and a nonnegative integer weight. we present a strongly polynomial time approximation scheme for this np-complete problem.
on product covering in 3-tier supply chain models: natural complete problems for [3] and [4]. the field of supply chain management has been growing at a rapid pace in recent years, both as a research area and as a practical discipline. in this paper, we study the computational complexity of product covering problems in 3-tier supply chain models, and present natural complete problems for the classes w[3] and w[4] in parameterized complexity theory. this seems the first group of natural complete problems for higher levels in the parameterized intractability hierarchy (i.e., the w-hierarchy), and the first precise complexity characterizations of certain optimization problems in the research of supply chain management. our results also derive strong computational lower bounds and inapproximability for these optimization problems.
on the ultimate complexity of factorials. it has long been observed that certain factorization algorithms provide a way to write the product of many different integers succinctly. in this paper, we study the problem of representing the product of all integers from 1 to n (i.e. n!) by straight-line programs. formally, we say that a sequence of integers an is ultimately f(n)-computable, if there exists a nonzero integer sequence mn such that for any n, anmn can be computed by a straight-line program (using only additions, subtractions and multiplications) of length at most f(n). shub and smale [12] showed that if n! is ultimately hard to compute, then the algebraic version of np ≠ p is true. assuming a widely believed number theory conjecture concerning smooth numbers in a short interval, a subexponential upper bound (exp(c√log n log log n)) for the ultimate complexity of n! is proved in this paper, and a randomized subexponential algorithm constructing such a short straight-line program is presented as well.
semi-on-line multiprocessor scheduling with given total processing time. we are given a set of identical machines and a sequence of jobs, the sum of whose weights is known in advance. the jobs are to be assigned on-line to one of the machines and the objective is to minimize the makespan. an algorithm with performance ratio 1.6 and a lower bound of 1.5 is presented. these results improve on the recent results by azar and regev, who proposed an algorithm with performance ratio 1.625 for the less general problem that the optimal makespan is known in advance.
an improvement on a spernerity proof of horrocks. in horrocks' proof (horrocks, european journal of combinatorics 20 (1999) 131-148) of lih's conjecture about the spernerity of filters in a boolean algebra generated by 2-subsets, there are 116 exceptional graphs to be checked case by case. the details of the analysis could not be published in its entirety. in this paper we carry horrocks' method much further to reduce the exceptional cases to a manageable number. a complete examination can thus be exhibited.
multi-agent scheduling on a single machine to minimize total weighted number of tardy jobs. we consider the feasibility model of multi-agent scheduling on a single machine, where each agent's objective function is to minimize the total weighted number of tardy jobs. we show that the problem is strongly np-complete in general. when the number of agents is fixed, we first show that the problem can be solved in pseudo-polynomial time for integral weights, and can be solved in polynomial time for unit weights; then we present a fully polynomial-time approximation scheme for the problem.
computing farthest neighbors on a convex polytope. let n be a set of n points in convex position in r3. the farthest point voronoi diagram of n partitions r3 into n convex cells. we consider the intersection g(n) of the diagram with the boundary of the convex hull of n. we give an algorithm that computes an implicit representation of g(n) in expected o(n log2 n) time. more precisely, we compute the combinatorial structure of g(n), the coordinates of its vertices, and the equation of the plane defining each edge of g(n). the algorithm allows us to solve the all-pairs farthest neighbor problem for n in expected time o(n log2 n), and to perform farthest-neighbor queries on n in o(log2 n) time with high probability.
additive sparse spanners for graphs with bounded length of largest induced cycle. in this paper, we show that every chordal graph with n vertices and m edges admits an additive 4-spanner with at most 2n - 2 edges and an additive 3-spanner with at most o(n log n) edges. this significantly improves results of peleg and schäffer from [graph spanners, j. graph theory 13 (1989) 99-116]. our spanners are additive and easier to construct. an additive 4-spanner can be constructed in linear time while an additive 3-spanner is constructable in o(m log n) time. furthermore, our method can be extended to graphs with largest induced cycles of length k. any such graph admits an additive (k + 1)-spanner with at most 2n - 2 edges which is constructable in o(nk + m) time.
interval routing in some planar networks. in this article, we design optimal or near optimal interval routing schemes (irs, for short) with small compactness for several classes of plane quadrangulations and triangulations (by optimality or near optimality we mean that messages are routed via shortest or almost shortest paths). we show that the subgraphs of the rectilinear grid bounded by simple circuits allow optimal irs with at most two circular intervals per edge (2-irs). we extend this result to all plane quadrangulations in which all inner vertices have degrees ≥ 4. namely, we establish that every such graph has an optimal irs with at most seven linear intervals per edge (7-lirs). this leads to a 7-lirs with the stretch factor 2 for all plane triangulations in which all inner vertices have degrees ≥ 6. all routing schemes can be implemented in linear time.
upper semi-lattice of binary strings with the relation "x is simple conditional to y". in this paper we construct a structure r that is a "finite version" of the semi-lattice of turing degrees. its elements are strings (technically, sequences of strings) and xy means thatk(x|y)=(conditional kolmogorov complexity of x relative to y) is small. we construct two elements in r that do not have greatest lower bound. we give a series of examples that show how natural algebraic constructions give two elements that have lower bound 0 (minimal element) but significant mutual information. (a first example of that kind was constructed by g&aacute;cs-k&ouml;rner (problems control inform. theory 2 (1973) 149) using a completely different technique.) we define a notion of "complexity profile" of the pair of elements of r and give (exact) upper and lower bounds for it in a particular case.
associative language descriptions. the new associative language description (ald) model, a combination of locally testable and constituent structure ideas, is proposed, arguing that in practice it equals context-free (cf) grammars in explanatory adequacy, yet it provides a simple description and it excludes mathematical sets based on counting properties, which are rarely (if ever) used in compiler construction or in computational linguistics. the ald model has been recently proposed as an approach consistent with current views on brain organization. ald is a "pure", i.e., nonterminal-free definition. the strict inclusion of ald languages in cf languages is proved, based on a lemma which strengthens the pumping lemma for cf languages. basic nonclosure and undecidability properties are considered and compared with those of cf languages. it is shown that the hardest context-free language is in ald, that there exists a hierarchy of ald languages and that each ald tree language enjoys the noncounting property of parenthesized cf languages. typical technical languages (pascal, html) can be rather conveniently described by ald rules
picture languages: tiling systems versus tile rewriting grammars. two formal models of pictures, i.e., two dimensional (2d) languages are compared: tiling systems and tile rewriting grammars, which resp. extend to 2d the regular and context-free languages. two results extending classical language properties into 2d are proved. first, non-recursive tile writing grammars (trg) coincide with tiling systems (ts). second, non-self-embedding trg are suitably defined as corner grammars, showing that they generate ts languages. the proofs exploit newly introduced language substitutions, also nested and iterated.
load-balanced parallel banded-system solvers. solving banded systems is important in the applications of science and engineering. this paper presents a load-balancing strategy for solving banded systems in parallel when the number of processors used is small. an optimization-based load-balancing analysis is given to determine how many loads should be assigned to each processor in order to minimize the time requirement. some experimentations are carried out on the ncube 2e multiprocessor to demonstrate the speedup advantage of the proposed load-balancing strategy. the speedup improvement ratio ranges from 47% to 66% (from 12% to 24%) when using 4 (8) processors.
about local configurations in arithmetic planes. in vittone and chassery (proc. of dgci'97, vol. 1347 of lecture notes in computer sciences, 1997, pp. 87-98) j.-m. chassery and j. vittone studied local configurations of (m,n)-cubes in naive planes in function of the parameters of these naive planes. more precisely, they enumerated the bicubes and the tricubes that appear in a naive hyperplane of parameters (a,b,c). a symmetry about the line c=a+b appears clearly in this enumeration. the aim of this paper is to prove that the configurations of (nn)-cubes in the plane of parameters (a,b,c) are in one-to-one relation with those in the plane of parameters (c-b, c-a,c). if we restrict the parameters to the planes such that a+bc, we note a second symmetry about the line c=2b; we also prove this symmetry. we generalize a theorem established by rveilles and grard (grard, proc. of dgci'99, vol. 1568 of lecture notes in computer sciences, 1999, pp. 65-75, reveilles, vision geometry 4, vol. 2573 of spie 95, san diego, 1995) and these symmetries to the local configurations of planes of given thickness.
relating defeasible and normal logic programming through transformation properties. this paper relates the defeasible logic programming (delp) framework and its semantics semdelp to classical logic programming frameworks. in delp, we distinguish between two different sorts of rules: strict and defeasible rules. negative literals (∼a) in these rules are considered to represent classical negation. in contrast to this, in normal logic programming (nlp), there is only one kind of rules, but the meaning of negative literals (not a) is different: they represent a kind of negation as failure, and thereby introduce defeasibility. various semantics have been defined for nlp, notably the well-founded semantics (wfs) (van gelder et al., proceedings of the seventh symposium on principles of database systems, 1988, pp. 221-230; j. acm 38 (3) (1991) 620) and the stable semantics stable (gelfond and lifschitz, fifth conference on logic programming, mit press, cambridge, ma, 1988, pp. 1070-1080; proceedings of the seventh international conference on logical programming, jerusalem, mit press, cambridge, ma, 1991, pp. 579-597).in this paper we consider the transformation properties for nlp introduced by brass and dix (j. logic programming 38(3) (1999) 167) and suitably adjusted for the delp framework. we show which transformation properties are satisfied, thereby identifying aspects in which nlp and delp differ. we contend that the transformation rules presented in this paper can help to gain a better understanding of the relationship of delp semantics with respect to more traditional logic programming approaches. as a byproduct, we obtain the result that delp is a proper extension of nlp.
switched pioa: parallel composition via distributed scheduling. this paper presents the framework of switched probabilistic input/output automata (or switched pioa), augmenting the original pioa framework with an explicit control exchange mechanism. using this mechanism, we model a network of processes passing a single token among them, so that the location of this token determines which process is scheduled to make the next move. this token structure therefore implements a distributed scheduling scheme: scheduling decisions are always made by the (unique) active component.distributed scheduling allows us to draw a clear line between local and global nondeterministic choices. we then require that local nondeterministic choices are resolved using strictly local information. this eliminates unrealistic schedules that arise under the more common centralized scheduling scheme. as a result, we are able to prove that our trace-style semantics is compositional.
locating factors of the infinite fibonacci word. let τ = (√5 - 1)/2. let a, b be two distinct letters. the infinite fibonacci word is the infinite word g = babbababbabbababbababbabba... whose nth letter is a (resp., b) if [(n + 1)τ] - [nτ] = 0 (resp., 1). for a factor w of g, the location of w is the set of all positions in g at which w occurs. only the locations of the following factors of g are already known: squares, singular words and those factors of g whose lengths are fibonacci numbers. the purpose of this paper is to determine the locations of all factors of g. our results contain all the known ones as consequences. moreover, using our results, we are able to identify any factor of g whenever its starting position and length are given; also we are able to tell whether two suffixes of g have a common prefix of a certain length.
an np decision procedure for protocol insecurity with xor. we provide a method for deciding the insecurity of cryptographic protocols in the presence of the standard dolev-yao intruder (with a finite number of sessions) extended with so-called oracle rules, i.e., deduction rules that satisfy certain conditions. as an instance of this general framework, we obtain that protocol insecurity is in np for an intruder that can exploit the properties of the exclusive or (xor) operator. this operator is frequently used in cryptographic protocols but cannot be handled in most protocol models. an immediate consequence of our proof is that checking whether a message can be derived by an intruder (using xor) is in ptime. we also apply our framework to an intruder that exploits properties of certain encryption modes such as cipher block chaining (cbc).
a certified, corecursive implementation of exact real numbers. we implement exact real numbers in the logical framework coq using streams, i.e., infinite sequences, of digits, and characterize constructive real numbers through a minimal axiomatization. we prove that our construction inhabits the axiomatization, working formally with coinductive types and corecursive proofs. thus we obtain reliable, corecursive algorithms for computing on real numbers.
approximate and dynamic rank aggregation. rank aggregation, originally an important issue in social choice theory, has become more and more important in information retrieval applications over the internet, such as meta-search, recommendation system, etc. in this work, we consider an aggregation function using a weighted version of the normalized kendall-τ distance. we propose a polynomial time approximation scheme, as well as a practical heuristic algorithm with the approximation ratio two for the np-hard problem. in addition, we discuss issues and models for the dynamic rank aggregation problem.
least adaptive optimal search with unreliable tests. we consider the basic problem of searching for an unknown m-bit number by asking the minimum possible number of yes-no questions, when up to a finite number e of the answers may be erroneous. in case the (i+1)th question is adaptively asked after receiving the answer to the ith question, the problem was posed by ulam and r&&eacute;nyi and is strictly related to berlekamp's theory of error correcting communication with noiseless feedback. conversely, in the fully non-adaptive model when all questions are asked before knowing any answer, the problem amounts to finding a shortest e-error correcting code. let qe(m) be the smallest integer q satisfying berlekamp's bound i=0e()2qm. then at least qe(m) questions are necessary, in the adaptive, as well as in the non-adaptive model. in the fully adaptive case, optimal searching strategies using exactly qe(m) questions always exist up to finitely many exceptional m's. at the opposite non-adaptive case, searching strategies with exactly qe(m) questions or equivalently, e-error correcting codes with 2m codewords of length qe(m)---are rather the exception, already for e=2, and are generally not known to exist for e>2. in this paper, for each e>1 and all sufficiently large m, we exhibit searching strategies that use a first batch of m non-adaptive questions and then, only depending on the answers to these m questions, a second batch of qe(m)m non-adaptive questions. these strategies are automatically optimal. since even in the fully adaptive case, qe(m)1 questions do not suffice to find the unknown number, and qe(m) questions generally do not suffice in the non-adaptive case, the results of our paper provide e, fault tolerant searching strategies with minimum adaptiveness and minimum number of tests.
improved competitive algorithms for online scheduling with partial job values. this paper considers an online scheduling problem arising from quality-of-service (qos) applications. we are required to schedule a set of jobs, each with release time, deadline, processing time and weight. the objective is to maximize the total value obtained for scheduling the jobs. unlike the traditional model of this scheduling problem, in our model unfinished jobs also get partial values proportional to their amounts processed.no non-timesharing algorithm for this problem with competitive ratio better than 2 is known. we give a new non-timesharing algorithm gap that improves this ratio for bounded values of m, where m can be the number of concurrent jobs or the number of weight classes. the competitive ratio is improved from 2 to 1.618 (golden ratio) which is optimal for m = 2, and when applied to cases with m > 2 it still gives a competitive ratio better than 2, e.g. 1.755 when m = 3. we also give a new study of the problem in the multiprocessor setting, giving an upper bound of 2 and a lower bound of 1.25 for the competitiveness. finally, we consider resource augmentation and show that o(log α) speedup or extra processors is sufficient to achieve optimality, where α is the importance ratio. we also give a tradeoff result, showing that in fact a small amount of extra resources is sufficient for achieving close-to-optimal competitiveness.
static and dynamic low-congested interval routing schemes. interval routing schemes (irs) have been extensively investigated in the past years with special emphasis on shortest paths. besides their theoretical interest, irs have practical applications, as they have been implemented with wormhole routing in the last generation of inmos transputer router chips. in this paper we consider irs that are optimal with respect to the congestion of the induced path system. in fact, wormhole routing is strongly influenced by the maximum number of paths that share a physical link and from low to moderate congestion it outperforms the packet switching technique. we provide a general framework able to deal with the various congestion issues in irs. in fact, we will distinguish between static cases, in which the source-destination configurations are fixed, and dynamic cases, where they vary over time. all these situations can be handled in a unified setting, thanks to the notion of competitiveness introduced in this paper. we first give some general results not related to specific traffic demands. then, in the one-to-all communication pattern, we show that constructing competitive irs for a given network is an intractable problem, both for the static and the dynamic case, that is when the root vertex is fixed and when it can change along the time, respectively. finally, both for one-to-all and all-to-all communication patterns, we provide nicely competitive k-irs for relevant topologies. networks considered are chains, trees, rings, chordal rings and multi-dimensional grids and tori. we consider both the directed congestion case, in which there are pairwise opposite unidirectional links connecting two neighbor processors, and the undirected congestion case, in which two neighbors are connected by a single bi-directional link.
improved approximation of the minimum cover time. feige and rabinovich, in [feige and rabinovich, rand. struct. algorithms 23(1) (2003) 1-22], gave a deterministic o(log4n) approximation for the time it takes a random walk to cover a given graph starting at a given vertex. this approximation algorithm was shown to work for arbitrary reversible markov chains. we build on the results of [feige and rabinovich, rand. struct. algorithms 23(1) (2003) 1-22], and show that the original algorithm gives a o(log2n) approximation as it is, and that it can be modified to give a o(log n(log log n)2) approximation. moreover, we show that given any c(n)-approximation algorithm for the maximum cover time (maximized over all initial vertices) of a reversible markov chain, we can give a corresponding algorithm for the general cover time (of a random walk or reversible markov chain) with approximation ratio o(c(n) log n).
complexity of approximating bounded variants of optimization problems. we study low degree graph problems such as maximum independent set and minimum vertex cover. the goal is to improve approximation lower bounds for them and for a number of related problems like max-b-set packing, min-b-set cover, and max-b-dimensional matching, b≥3. we prove, for example, that it is np-hard to achieve an approximation factor of 95/94 for max-3-dm, and a factor of 48/47 for max-4-dm. in both cases the hardness result applies even to instances with exactly two occurrences of each element.
partial digest is hard to solve for erroneous input data. the partial digest problem asks for the coordinates of m points on a line such that the pairwise distances of the points form a given multiset of (m 2) distances. partial digest is a well-studied problem with important applications in physical mapping of dna molecules. its computational complexity status is open. input data for partial digest from real-life experiments are always prone to error, which suggests to study variations of partial digest that take this fact into account. in this paper, we study the computational complexity of partial digest variants that model three different error types that can occur in the data: additional distances, missing distances, and erroneous fragment lengths. we show that these variations are np-hard, hard to approximate, and strongly np-hard, respectively.
three-player partizan games. conway's theory of partizan games is both a theory of games and a theory of numbers. we present here an extension such a theory to classify three-player partizan games. we apply this extension to solve a restricted version of three-player hackenbush.
molecular interaction. we introduce and study abstract structures which are suitable for expressing molecular interaction. the abstract structures are able to manage shared resources and to describe the use of shared resources. we show that these structures can provide an interpretation of the π-calculus, a known calculus of communicating concurrent systems. we briefly describe dna methylation by using the π-calculus. molecular interactions during dna methylation imply changes of conformation and other modifications; these changes can be modelled by substitutions. formally, we use some notions and results of the concurrency theory, particularly related to the π-calculus and multiset semantics.
a coalgebraic equational approach to specifying observational structures. a coalgebraic, equational approach to the specification of observational structures allowing for a choice in the result type of observations is presented. observers whose result type is structured as a coproduct of basic types are considered, and notions of covariable, coterm and coequation, dual to the algebraic notions of variable, term and equation are used to specify the associated structures. a sound and complete deduction calculus for reasoning about observational structures is then formulated. finally, the approach is extended in order to account for the availability of a fixed data universe in the specification of such structures.
a compositional approach to defining logics for coalgebras. we present a compositional approach to defining expressive logics for coalgebras of endofunctors on set. this approach uses a notion of language constructor and an associated notion of semantics to capture one inductive step in the definition of a language for coalgebras and of its semantics. we show that suitable choices for the language constructors and for their associated semantics yield logics which are both adequate and expressive w.r.t, behavioural equivalence. moreover, we show that type-building operations give rise to corresponding operations both on language constructors and on their associated semantics, thus allowing the derivation of expressive logics for increasingly complex coalgebraic types. our framework subsumes several existing approaches to defining logics for coalgebras, and at the same time allows the derivation of new logics, with logics for probabilistic systems being the prime example.
collage of two-dimensional words. we consider a new operation on one-dimensional (resp. two-dimensional) word languages, obtained by piling up, one on top of the other, words of a given recognizable language (resp. two-dimensional recognizable language) on a previously empty one-dimensional (resp. two-dimensional) array. the resulting language is the set of words "seen from above": a position in the array is labeled by the topmost letter. we show that in the one-dimensional case, the language is always recognizable. this is no longer true in the two-dimensional case which is shown by a counter-example, and we investigate in which particular cases the result may still hold.
maude: specification and programming in rewriting logic. maude is a high-level language and a high-performance system supporting executable specification and declarative programming in rewriting logic. since rewriting logic contains equational logic, maude also supports equational specification and programming in its sublanguage of functional modules and theories. the underlying equational logic chosen for maude is membership equational logic, that has sorts, subsorts, operator overloading, and partiality definable by membership and equality conditions. rewriting logic is reflective, in the sense of being able to express its own metalevel at the object level. reflection is systematically exploited in maude endowing the language with powerful metaprogramming capabilities, including both user-definable module operations and declarative strategies to guide the deduction process. this paper explains and illustrates with examples the main concepts of maude's language design, including its underlying logic, functional, system and object-oriented modules, as well as parameterized modules, theories, and views. we also explain how maude supports reflection, metaprogramming and internal strategies. the paper outlines the principles underlying the maude system implementation, including its semicompilation techniques. we conclude with some remarks about applications, work on a formal environment for maude, and a mobile language extension of maude.
reflection in conditional rewriting logic. we recall general metalogical axioms for a reflective logic based on the notion of a universal theory, that is, a theory that can simulate the deductions of all other theories in a class of theories of interest, including itself. we then show that conditional rewriting logic is reflective, generalizing in two stages: first to the unsorted conditional case, and then to the many-sorted conditional case, the already known result for unconditional and unsorted rewriting logic (reflection in rewriting logic: metalogical foundations and metaprogramming applications. csli publications, 2000). this work should be seen as providing foundations for many useful applications of rewriting logic reflection. the results presented here have greatly influenced the design of the maude language, which implements rewriting logic and supports its reflective capabilities, and have been used as a theoretical foundation for applications such as internal rewrite strategies, reflective design of theorem proving tools, module algebra and metaprogramming, and metareasoning in metalogical frameworks.
string-matching with obdds. ordered binary decision diagrams (obdds) are a very popular graph representation for boolean functions. they can be viewed as finite automata recognizing sets of strings of a fixed length, where the letters of the input strings are read at most once in a predefined ordering. the string matching problem with string w as pattern, consists of determining, given an input string, whether or not it contains w as substring. we show that for a fraction of orderings tending to i when n increases arbitrarily, the minimal size of an obdd solving the string matching problem for strings of length n has a growth which is an exponential in n.
probabilistic temporal logics via the modal mu-calculus. this paper presents a mu-calculus-based modal logic for describing properties of reactive probabilistic labeled transition systems (rpltss) and develops a model-checking algorithm for determining whether or not states in finite-state rpltss satisfy formulas in the logic. the logic is based on the distinction between (probabilistic) "systems" and (nonprobabilistic) "observations": using the modal mu-calculus, one may specify sets of observations, and the semantics of our logic then enable statements to be made about the measures of such sets at various system states. the logic may be used to encode a variety of probabilistic modal and temporal logics; in addition, the model-checking problem for it may be reduced to the calculation of solutions to systems of non-linear equations. finally, the logic induces an equivalence on rpltss that coincides with accepted notions of probabilistic bisimulation in the literature.
a note on decidability questions on presentations of word semigroups. we apply automata-theoretic tools and some recently established compactness properties in the study of f-semigroups, that is, subsemigroups of free semigroups. with each f-semigroup we associate an f-presentation, which turns out to be finite for all finitely generated f-semigroups. connections between f-presentations and ordinary presentations of semigroups are also pointed out. it is also shown that it is undecidable whether two finitely generated f-semigroups satisfy a common relation in their f-presentation.
the commutation of finite sets: a challenging problem. we prove that given a set x of two nonempty words, a set y of nonempty words commutes with x if and only if either y is a union of powers of x or x,yt+ for some primitive word t. we also show that the same holds for certain special types of codes, but does not hold, in general, for sets of cardinality at least 4.
the concept of computability. i explore the conceptual foundations of alan turing's analysis of computability, which still dominates thinking about computability today. i argue that turing's account represents a last vestige of a famous but unsuccessful program in pure mathematics, viz., hilbert's formalist program. it is my contention that the plausibility of turing's account as an analysis of the computational capacities of physical machines rests upon a number of highly problematic assumptions whose plausibility in turn is grounded in the formalist stance towards mathematics. more specifically, the turing account conflates concepts that are crucial for understanding the computational capacities of physical machines. these concepts include the idea of an "operation" or "action" that is "formal," "mechanical," "well-defined," and "precisely described," and the idea of a "symbol" that is "formal," "uninterpreted," and "shaped". when these concepts are disentangled, the intuitive appeal of turing's account is significantly undermined. this opens the way for exploring models of hypercomputability that are fundamentally different from those currently entertained in the literature.
parsing with a finite dictionary. we address the following issue: given a word w ∈ a* and a set of n nonempty words x, how does one determine efficiently whether w ∈ x* or not? we discuss several methods including an o(r × |w| + |x|) algorithm for this problem where r ≤ n is the length of a longest suffix chain of x and |x| is the sum of the lengths of words in x. we also consider the more general problem of providing all the decompositions of w in words of x.
the minimum broadcast range assignment problem on linear multi-hop wireless networks. given a set n of radio stations located on an euclidean space, a source station s and an integer h (1 ≤ h ≤ |n| - 1), the minimum bounded-hop broadcast range assignment problem consists in finding a range assignment for n of minimum total power consumption that allows broadcast operations from s to every station in n in at most h hops. the problem is known to be np-hard on d-dimensional spaces for any d ≥ 2 (18th annual symp. on theoretical aspects of computer science (stacs'01), lecture notes in computer science, vol. 1770, 2000, pp. 651-660.) and some efficient approximation algorithms have been given in clementi et al. and wann et al. (18th annual symp. on theoretical aspects of computer science (stacs'01), lecture notes in computer science, vol. 1770, 2000, pp. 651-660, ieee infocom'01, 2001). in this paper, we address the case in which the stations are arbitrarily located along a line (i.e., the linear case). we provide the first polynomial-time algorithm that returns an optimal solution for any instance of the linear case. the algorithm works in o(h|n|2) time.
distributed broadcast in radio networks of unknown topology. a multi-hop synchronous radio network is said to be unknown if the nodes have no knowledge of the topology. a basic task in radio network is that of broadcasting a message (created by a fixed source node) to all nodes of the network. typical operations in real-life radio networks is the multi-broadcast that consists in performing a set of r independent broadcasts. the study of broadcast operations on unknown radio network is started by the seminal paper of bar-yehuda et al. [j. comput. system sci. 45 (1992) 104] and has been the subject of several recent works.in this paper, we study the completion and the termination time of distributed protocols for both the (single) broadcast and the multi-broadcast operations on unknown networks as functions of the number of nodes n, the maximum eccentricity d, the maximum in-degree δ, and the congestion c of the networks. we establish new connections between these operations and some combinatorial concepts, such as selective families, strongly selective families (also known as superimposed codes), and pairwise r-different families. such connections, combined with a set of new lower and upper bounds on the size of the above families, allow us to derive new lower bounds and new distributed protocols for the broadcast and multi-broadcast operations. in particular, our upper bounds are almost tight and strongly improve over the previous bounds for a large class of networks.
minimal schedulability interval for real-time systems of periodic tasks with offsets. we consider real-time systems in highly safety context where tasks have to meet strict deadlines. tasks are periodic, may have offsets, share critical resources and be precedence constrained. off-line scheduling should be of great help for such systems, but methods proposed in the literature cannot deal with them. our aim is to extend and improve the well-known cyclicity result of leung and merill to every scheduling algorithm and to systems of interacting tasks with offsets. one of the main benefit of our result is to enable the use of off-line scheduling methods for those real-time critical systems.
abstractions for fault-tolerant global computing. global computing (wan programming, internet programming) distinguishes itself from local computing (lan computing) by the fact that it exposes some aspects of the network to the application, rather than seeking to hide them with network transparency, as in lan programming. global computing languages seek to provide useful abstractions for building applications in such environments. the lqp(ċ)-calculus is a family of programming languages that use the abstraction of logs to specify application-specific protocols for distributed agreement and fault tolerance in global applications. reflecting the motivation for global computing, the abstraction of logs isolates the communication requirements of such protocols. two specific instances of the lqp(ċ)-calculus are provided, the lqp(dc)-calculus and the lqp(dcu)-calculus. these are intended as kernel programming languages for fault-tolerant distributed programming. the calculi incorporate various abstractions for fault tolerance, from which several forms of distributed transactions and optimistic computation may be built. as an example application, a calculus of atomic failures is presented, the atf-calculus, and its encoding in the lqp(dc)-calculus used to verify a correctness property.
the computational complexity of distance functions of two-dimensional domains. we study the computational complexity of the distance function associated with a polynomial-time computable two-dimensional domains, in the context of the turing machine-based complexity theory of real functions. it is proved that the distance function is not necessarily computable even if a two-dimensional domain is polynomial-time recognizable. on the other hand, if both the domain and its complement are strongly polynomial-time recognizable, then the distance function is polynomial-time computable if and only if p = np.
computing the maximum agreement of phylogenetic networks. we introduce the maximum agreement phylogenetic subnetwork problem (masn) for finding branching structure shared by a set of phylogenetic networks. we prove that the problem is np-hard even if restricted to three phylogenetic networks and give an o(n2)-time algorithm for the special case of two level-1 phylogenetic networks, where n is the number of leaves in the input networks and where n is called a level-f phylogenetic network if every biconnected component in the underlying undirected graph induces a subgraph of n containing at most f nodes with indegree 2. we also show how to extend our technique to yield a polynomial-time algorithm for any two level-f phylogenetic networks n1, n2 satisfying f = o(log n); more precisely, its running time is o(|v (n1)| ċ |v (n2)| ċ 2f1 + f2), where v (ni) and fi denote the set of nodes in ni and the level of ni, respectively, for i ∈ {1, 2}.
heuristic average-case analysis of the backtrack resolution of random 3-satisfiability instances. an analysis of the average-case complexity of solving random 3-satisfiability (sat) instances with backtrack algorithms is presented. we first interpret previous rigorous works in a unifying framework based on the statistical physics notions of dynamical trajectories, phase diagram and growth process. it is argued that, under the action of the davis-putnam-loveland logemann (dpll) algorithm, 3-sat instances are turned into 2+p-sat instances whose characteristic parameters (ratio α of clauses per variable, fraction p of 3-clauses) can be followed during the operation, and define resolution trajectories. depending on the location of trajectories in the phase diagram of the 2+p-sat model, easy (polynomial) or hard (exponential) resolutions are generated. three regimes are identified, depending on the ratio α of the 3-sat instance to be solved. lower satisfiable (sat) phase: for small ratios, dpll almost surely finds a solution in a time growing linearly with the number n of variables. upper sat phase: for intermediate ratios, instances are almost surely satisfiable but finding a solution requires exponential time (∼ 2nω with ω ≥ 0) with high probability. unsat phase: for large ratios, there is almost always no solution and proofs of refutation are exponential. an analysis of the growth of the search tree in both upper sat and unsat regimes is presented, and allows us to estimate ω as a function of α. this analysis is based on an exact relationship between the average size of the search tree and the powers of the evolution operator encoding the elementary steps of the search heuristic.
on tiling under tomographic constraints. given a tiling of a 2d grid with several types of files, we can count for every row and column how many tiles of each type it intersects. these numbers are called the projections. we are interested in the problem of reconstructing a tiling which has given projections. some simple variants of this problem, involving files that are 1 × 1 or 1 × 2 rectangles, have been studied in the past, and were proved to be either solvable in polynomial time or np-complete. in this note, we make progress toward a comprehensive classification of various tiling reconstrction problems, by proving np-completeness results for several sets of tiles.
restriction categories i: categories of partial maps. given a category with a stable system of monics, one can form the corresponding category of partial maps. to each map in this category there is, on the domain of the map, an associated idempotent, which measures the degree of partiality. this structure is captured abstractly by the notion of a restriction category, in which every arrow is required to have such an associated idempotent. categories with a stable system of monics, functors preserving this structure, and natural transformations which are cartesian with respect to the chosen monics, form a 2-category which we call mcat. the construction of categories of partial maps provides a 2-functor par:mcat&rarr;cat. we show that par can be made into an equivalence of 2-categories between mcat and a 2-category of restriction categories. the underlying ordinary functor par&r0:mcat&0 &rarr; ca t0 of the above 2-functor par turns out to be monadic, and, from this, we deduce the completeness and cocompleteness of the 2-categories of m-categories and of restriction categories. we also consider the problem of how to turn a formal system of subobjects into an actual system of subobjects. a formal system of subobjects is given by a functor into the category slat of semilattices. this structure gives rise to a restriction category which, via the above equivalence of 2-categories, gives an m-category. this m-category contains the universal realization of the given formal subobjects as actual subobjects.
restriction categories ii: partial map classification. an algebraic characterization of monads which are abstract partial map classifiers is provided, without the assumption that the categories of total maps possess products. by an abstract partial map classifier we mean a monad whose kleisli category is a full subcategory of a partial map category wherein the induced comonad classifies partial maps in the usual sense. a construction of the corresponding actual partial map classifier from an abstract one is described, and conditions for an abstract partial map classifier to be a real one are provided. the paper uses the notion of a restriction category developed in earlier work, and the characterization of these as full subcategories of partial map categories.
more on randomized on-line algorithms for caching. we address the tradeoff between the competitive ratio and the resources used by randomized on-line algorithms for caching. two algorithms reported in the literature that achieve the optimal ratio hk require a lot of memory and perform extensive computation at each step. on the other hand, a very simple algorithm called rmark has competitive ratio 2hk -- 1, within a factor of 2 of the optimum. a natural question that arises here is whether there is a tradeoff between simplicity and the competitive ratio. in particular, is it possible to achieve a competitive ratio better than 2hk - 1 with a simple algorithm like rmark?we first consider marking algorithms that are natural generalizations of rmark, and we prove that, for any ε > 0, there is no randomized marking algorithm for caching with competitive ratio (2 - ε)hk. thus rmark is essentially optimal among marking algorithms.another model of simple caching algorithms is that of trackless algorithms. these are algorithms that do not store any information about items that are not in the cache. it is known that, for k = 2, there is no randomized trackless algorithm for caching with ratio better than 37/24;≈ 1.5416; the trivial upper bound is 2, achieved even by deterministic algorithms lru and fifo. we reduce this gap by giving a trackless randomized algorithm with competitive ratio 1/4(3 + √13) ≈ 1.6514.
the weighted 2-server problem. we consider a generalization of the 2-server problem in which servers have different costs. we prove that, in uniform spaces, a version of the work function algorithm is 5-competitive, and that no better ratio is possible. we also give a 5-competitive randomized, memoryless algorithm for uniform spaces, and a matching lower bound.for arbitrary metric spaces, in contrast with the non-weighted case, we prove that there is no memoryless randomized algorithm with finite competitive ratio. we also propose a version of the problem in which a request specifies two points to be covered by the servers, and the algorithm must decide which server to move to which point. for this version, we show a 9-competitive algorithm and we prove that no better ratio is possible.
moments of conjugacy classes of binary words. for each nonempty binary word w = c1c2...cq, where ci ∈ {0, 1}, the nonnegative integer σi=1q (q + 1 - i)ci is called the moment of w and is denoted by m(w). let [w] denote the conjugacy class of w. define m([w]) = {m(u): u ∈ [w]}, n(w) = {m(u) - m(w): u ∈ [w]} and δ(w) = max{m(u) - m(v): u, v ∈ [w]}. using these objects, we obtain equivalent conditions for a binary word to be an α-word (respectively, a power of an α-word). for instance, we prove that the following statements are equivalent for any binary word w with |w| ≥ 2: (a) w is an α-word, (b) δ(w)= |w| - 1, (c) w is a cyclic balanced primitive word, (d) m([w]) is a set of |w| consecutive positive integers, (c) n(w) is a set of |w| consecutive integers and 0 ∈ n(w), (f) w is primitive and [w] ⊂ st.
factors of characteristic words of irrational numbers. let β be an irrational number between 0 and 1. the characteristic word f(β) of β is defined to be the infinite word over {0, 1} whose nth letter is [(n + 1)β] -[nβ], n ≥ 1. it is well known that, for each m ≥ 1, f(β) has exactly m + 1 distinct factors of length m. in this paper, we shall develop a method to construct these factors. under our construction, the 1-sets of these m + 1 factors x0(m), x1(m),..., xm(m) are determined, these factors are increasing in the lexicographic order and their moments m(x0(m)), m(x1(m)),..., m(xm(m)) form an increasing sequence of m + 1 consecutive integers. some known results about generating factors of f(β) using the unbordered α-words and their conjugates turn out to be consequences of our main theorem.
performance aspects of distributed caches using ttl-based consistency. the web is the largest distributed database deploying time-to-live-based weak consistency. each object has a lifetime-duration assigned to it by its origin server. a copy of the object fetched from its origin server is received with maximum time-to-live (ttl) that equals its lifetime duration. in contrast a copy obtained through a cache have shorter ttl since the age (elapsed time since fetched from the origin) is deducted from its lifetime duration. a request served by a cache constitutes a hit if the cache has a fresh copy of the object. otherwise, the request is considered a miss and is propagated to another server. it is evident that the number of cache misses depends on the age of the copies the cache receives. thus, a cache that sends requests to another cache would suffer more misses than a cache that sends requests directly to an authoritative server.in this paper, we model and analyze the effect of age on the performance of various cache configurations. we consider a low-level cache that fetches objects either from their origin servers or from other caches and analyze its miss-rate as function of its fetching policy. we distinguish between three basic fetching policies, namely, fetching always from the origin, fetching always from the same high-level cache, and fetching from a "random" high-level cache. we explore the relationships between these policies in terms of the miss-rate achieved by the low-level cache, both on worst-case sequences, and on sequences generated using particular probability distributions.guided by web caching practice, we consider two variations of the basic policies. in the first variation the high-level cache uses pre-term refreshes to keep a copy with lower age. in the second variation the low-level cache uses extended lifetime duration. we analyze how these variations affect the miss-rates. our theoretical results help to understand how age may affect the miss-rate, and imply guidelines for improving performance of web caches.
techniques from combinatorial approximation algorithms yield efficient algorithms for random 2k-sat. we apply techniques from the theory of approximation algorithms to the problem of deciding whether a random k-sat formula is satisfiable. let form n,k,m denote a random k-sat instance with n variables and m clauses. using known approximation algorithms for max cut or min bisection, we show how to certify that formn,4,m is unsatisfiable efficiently, provided that m ≥ cn2 for a sufficiently large constant c > 0. in addition, we present an algorithm based on the lovász υ' function that decides within polynomial expected time whether formn,k,m is satisfiable, provided that k is even and m ≥ c ċ 4knk/2. finally, we present an algorithm that approximates random max 2-sat on input formn,2,m within a factor of 1 - o(n/m)1/2 in expected polynomial time. for m ≥ cn.
automated techniques for provably safe mobile code. we present a general framework for provably safe mobile code. it relies on a formal definition of a safety policy and explicit evidence for compliance with this policy which is attached to a binary. concrete realizations of this framework are proof-carrying code, where the evidence for safety is a formal proof generated by a certifying compiler, and typed assembly language, where the evidence for safety is given via type annotations propagated throughout the compilation process in typed intermediate languages. validity of the evidence is established via a small trusted type checker, either directly on the binary or indirectly on proof representations in a logical framework.
on the positional determinacy of edge-labeled games. it is well known that games with the parity winning condition admit positional determinacy: the winner has always a positional (memoryless) strategy. this property continues to hold if edges rather than vertices are labeled. we show that in this latter case the converse is also true. that is, a winning condition over arbitrary set of colors admits positional determinacy in all games if and only if it can be reduced to a parity condition with some finite number of priorities.
continuity and computability of reachable sets. the computation of reachable sets of nonlinear dynamic and control systems is an important problem of systems theory. in this paper we consider the computability of reachable sets using turing machines to perform approximate computations. we use weihrauch's type-two theory of effectivity for computable analysis and topolgy, which provides a natural setting for performing computations on sets and maps. the main result is that the reachable set is lower-computable, but is only outer-computable if it equals the chain-reachable set. in the course of the analysis, we extend the computable topology theory to locally-compact hausdorff spaces and semicontinuous set-valued maps, and provide a framework for computing approximations.
the evaluation of first-order substitution is monadic second-order compatible. we denote first-order substitutions of finite and infinite terms by function symbols indexed by the sequences of first-order variables to which substitutions are made. we consider the evaluation mapping from infinite terms to infinite terms that evaluates these substitution operations. this mapping may perform infinitely many nested substitutions, so that a term which has the structure of an infinite string can be transformed into one isomorphic to an infinite binary tree. we prove that this mapping is monadic second-order compatible which means that a monadic second-order formula expressing a property of the output term produced by the evaluation mapping can be translated into a monadic second-order formula expressing this property over the input term. this implies that, deciding the monadic second-order theory of the output term reduces to deciding that of the input term. as an application, we obtain another proof that the monadic second-order properties of the algebraic trees, which represent the behaviours of recursive applicative program schemes, are decidable. this proof extends to hyperalgebraic trees. these infinite trees correspond to certain recursive program schemes with functional parameters of arbitrary high type.
the recognizability of sets of graphs is a robust property. once the set of finite graphs is equipped with an algebra structure (arising from the definition of operations that generalize the concatenation of words), one can define the notion of a recognizable set of graphs in terms of finite congruences. applications to the construction of efficient algorithms and to the theory of context-free sets of graphs follow naturally. the class of recognizable sets depends on the signature of graph operations. we consider three signatures related respectively to hyperedge replacement (hr) context-free graph grammars, to vertex replacement (vr) context-free graph grammars, and to modular decompositions of graphs. we compare the corresponding classes of recognizable sets. we show that they are robust in the sense that many variants of each signature (where in particular operations are defined by quantifier-free formulas, a quite flexible framework) yield the same notions of recognizability. we prove that for graphs without large complete bipartite subgraphs, hr-recognizability and vr-recognizability coincide. the same combinatorial condition equates hr-context-free and vr-context-free sets of graphs. inasmuch as possible, results are formulated in the more general framework of relational structures.
tilings as a programming exercise. we investigate the problem of producing symmetric tilings by programs in a uniform way. by this, we mean that the construction of a tiling should be parameterized by the geometric model in which the tiling is defined (euclidean, hyperbolic, etc.), its formal symmetry group, the interpretation of this symmetry group in the geometric model and a specific tile that fits this interpretation. this parameterization can be obtained at a basic level using higher order functions as described in cousineau and mauny (the functional approach to programming, cambridge university press, cambridge, 1997) but this fails to reflect in the program the mathematical structure of tilings in an adequate way. we therefore explore the use of more abstract constructs such as modules and show that they allow to structure the program in a satisfying way. the objective caml programming language (objective caml, o'reilly, 2000) allows us to place this study in a convenient setting.
tree automata with one memory set constraints and cryptographic protocols. we introduce a class of tree automata that perform tests on a memory that is updated using function symbol application and projection. the language emptiness problem for this class of tree automata is shown to be in dexptime.we also introduce a class of set constraints with equality tests and prove its decidability by completion techniques and a reduction to tree automata with one memory.finally, we show how to apply these results to cryptographic protocols. we introduce a class of cryptographic protocols and show the decidability of secrecy for an arbitrary number of agents and an arbitrary number of (concurrent or successive) sessions, provided that only a bounded number of new data is generated. the hypothesis on the protocol (a restricted copying ability) is shown to be necessary: without this hypothesis, we prove that secrecy is undecidable, even for protocols without nonces.
constructive design of a hierarchy of semantics of a transition system by abstract interpretation. we construct a hierarchy of semantics by successive abstract interpretations. starting from the maximal trace semantics of a transition system, we derive the big-step semantics, termination and nontermination semantics, plotkin's natural, smyth's demoniac and hoare's angelic relational semantics and equivalent nondeterministic denotational semantics (with alternative powerdomains to the egli-milner and smyth constructions), d. scott's deterministic denotational semantics, the generalized and dijkstra's conservative/liberal predicate transformer semantics, the generalized/total and hoare's partial correctness axiomatic semantics and the corresponding proof methods. all the semantics are presented in a uniform fixpoint form and the correspondences between these semantics are established through composable galois connections, each semantics being formally calculated by abstract interpretation of a more concrete one using kleene and/or tarski fixpoint approximation transfer theorems. copyright 2002 elsevier science b.v.
parsing as abstract interpretation of grammar semantics. earley's parsing algorithm is shown to be an abstract interpretation of a refinement of the derivation semantics of context-free grammars.
strategies for combining decision procedures. implementing efficient algorithms for combining decision procedures has been a challenge and their correctness precarious. in this paper we describe an inference system that has the classical nelson-oppen procedure at its core and includes several optimizations: variable abstraction with sharing, canonization of terms at the theory level, and shostak's streamlined generation of new equalities for theories with solvers. the transitions of our system are fine-grained enough to model most of the mechanisms currently used in designing combination procedures. in particular, with a simple language of regular expressions we are able to describe several combination algorithms as strategies for our inference system, from the basic nelson-oppen to the very highly optimized one recently given by shankar and rueß. presenting the basic system at a high level of generality and nondeterminism allows transparent correctness proofs that can be extended in a modular fashion when new features are introduced in the system.
classifying rna pseudoknotted structures. computational prediction of the minimum free energy (mfe) secondary structure of an rna molecule from its base sequence is valuable in understanding the structure and function of the molecule. since the general problem of predicting pseudoknotted secondary structures is np-hard, several algorithms have been proposed that find the mfe secondary structure from a restricted class of secondary structures. in this work, we order the algorithms by generality of the structure classes that they handle. we provide simple characterizations of the classes of structures handled by four algorithms, as well as linear time methods to test whether a given secondary structure is in three of these classes. we report on the percentage of biological structures from the pseudobase and gutell databases that are handled by these three algorithms.
generalized satisfiability problems: minimal elements and phase transitions. we develop a probabilistic model on the generalized satisfiability problems defined by schaefer (in: proceedings of the 10th stoc, san diego, ca, usa, association for computing machinery, new york, 1978, pp. 216-226) for which the arity of the constraints is fixed in order to study the associated phase transition. we establish new results on minimal elements associated with such generalized satisfiability problems. these results are the keys of the exploration we conduct on the location and on the nature of the phase transition for generalized satisfiability. we first prove that the phase transition occurs at the same scale for every reasonable problem and we provide lower and upper bounds for the associated critical ratio. our framework allows one to get these bounds in a uniform way, in particular, we obtain a lower bound proportional to the number of variables for k-sat without analyzing any algorithm. finally, we reveal the seed of coarseness for the phase transition of generalized satisfiability: 2-xor-sat.
generalised fine and wilf's theorem for arbitrary number of periods. the well known fine and wilf's theorem for words states that if a word has two periods and its length is at least as long as the sum of the two periods minus their greatest common divisor, then the word also has as period the greatest common divisor. we generalise this result for an arbitrary number of periods. our bound is strictly better in some cases than previous generalisations. moreover, we prove it optimal. we show also that any extrenal word is unique up to letter renaming and give an algorithm to compute both the bound and a corresponding extremal word.
hypercomputation: philosophical issues. a survey of the field of hypercomputation, including discussion of four a priori objections to the possibility of hypercomputation. an exegesis of turing's pre- and post-war writings on the mind is given, and turing's views on the scope of machines are discussed.
injective synchronisation: an extension of the authentication hierarchy. authentication is one of the foremost goals of many security protocols. it is most often formalised as a form of agreement, which expresses that the communicating partners agree on the values of a number of variables. in this paper we formalise and study an intensional form of authentication which we call synchronisation. synchronisation expresses that the messages are transmitted exactly as prescribed by the protocol description. synchronisation is a strictly stronger property than agreement for the standard intruder model, because it can be used to detect preplay attacks. in order to prevent replay attacks on simple protocols, we also define injective synchronisation. given a synchronising protocol, we show that a sufficient syntactic criterion exists that guarantees that the protocol is injective as well.
strictness, totality, and non-standard-type inference. in this paper we present two non-standard-type inference systems for conjunctive strictness and totality analyses of higher-order-typed functional programs and prove completeness results for both the strictness and the totality-type entailment relations. we also study the interactions between strictness and totality analyses, showing that the information obtainable by a system that combines the two analyses, even though more refined than the information given by the two separate systems, cannot be effectively used. a main feature of our approach is that all the results are proved by relying directly on the operational semantics of the programming language considered. this leads to a rather direct presentation which involves relatively little mathematical overhead. copyright 2002 elsevier science b.v.
a syntactical proof of the marriage lemma. we give a proof of the classical marriage lemma (amer. j. math. 72 (1950) 214) using completeness of hyperresolution. this argument is purely syntactical, and extends directly to the infinite case. as an application we give a purely syntactical version of a proof that resolution is exponential on the pigeon-hole principle.
on the hamming distance of constraint satisfaction problems. in this paper we consider a new optimization problem, called max hammingdistance(f) where f is a family of boolean constraints. this problem consists in finding two satisfying assignments that differ in the maximum number of variable values: in other words, the problem looks for the maximum difference between two models of the constraints given in input. we give a complete classification of the approximability properties of max hammingdistance(f) by using a specialization of the criteria introduced by schaefer in order to classify constraint satisfaction problems and subsequently used by khanna, sudan, trevisan, and williamson to classify constraint satisfaction optimization problems.
sharing one secret vs. sharing many secrets. a secret sharing scheme is a method for distributing a secret among several parties in such a way that only qualified subsets of the parties can reconstruct it and unqualified subsets receive no information about the secret. a multi-secret sharing scheme is the natural extension of a secret sharing scheme to the case in which many secrets need to be shared, each with respect to possibly different subsets of qualified parties. a multi-secret sharing scheme can be trivially realized by realizing a secret sharing scheme for each of the secrets.in this paper we address the natural questions of whether this simple construction is the most efficient as well, and, if not, how much improvement is possible over it, with respect to both efficiency measures used in the literature; namely, the maximum piece of information and the sum of all pieces of information distributed to all parties. we completely answer these questions, as follows. we show the first instance for which an improvement is possible; we prove a bound on how much improvement is possible with respect to both measures; and we show instances of multi-secret sharing schemes which achieve this improvement, with respect to both measures, thus showing that the above bound is tight.
a representation of stably compact spaces, and patch topology. this note presents a concrete representation of stably compact spaces. this is used to give a simple, and predicative, description of the patch topology of a stably compact space (j. pure appl. algebra, to appear).
tile rewriting grammars and picture languages. tile rewriting grammars (trg) are a new model for defining picture languages. a rewriting rule changes a homogeneous rectangular subpicture into an isometric one tiled with specified tiles. derivation and language generation with trg rules are similar to context-free grammars. a normal form and some closure properties are presented. we prove this model has greater generative capacity than the tiling systems of giammarresi and restivo and the grammars of matz, another generalization of context-free string grammars to 2d. examples are shown for pictures made by nested frames and spirals.
reducing space for index implementation. this article considers several strategies to implement efficiently full indexes on raw textual data. indexes are based on representations of all the suffixes of the original text, for which we describe three types of implementations aimed at reducing the memory space. the first method is a combination of compaction and minimization that leads to the compact suffix automaton. as a second method we show that considering a complement language can be useful especially when it is related to data compression. finally, approximation of the set of suffixes is the third technique used to reduce the space of the implementation.
description trees and tutte formulas. in this paper we introduce and enumerate families of description trees. these families of trees consist of plane trees in which the nodes are labelled by nonnegative integers, and where the label of each node satisfies a condition relating it to the labels of its sons.we give a recursive construction of these trees which translates simply in an equation for their generating function. by solving this equation via the quadratic method introduced by brown and tutte, we prove that this generating function is algebraic. for some families the number of trees we obtain is equal to the numbers given by tutte to enumerate different kinds of planar maps. we provide bijections between description trees and corresponding families of planar maps to explain these equalities.description trees are instances of objects that can be described by description operators; we conjecture that such families of objects have algebraic generating functions. they were find also to be related to the enumeration of pattern avoiding permutations.
longest repeats with a block of don't cares. a k-repeat is a string wk = u*k v that matches more than one substring of x, where * is the don't care letter and k > 0. we propose an o(n log n)-time algorithm for computing all longest k-repeats in a given string x = x[1..n]. the proposed algorithm uses suffix trees to fulfill this task and relies on the ability to answer lowest common ancestor queries in constant time.
the abc conjecture and correctly rounded reciprocal square roots. the reciprocal square root calculation α = 1/√ x is very common in scientific computations. having a correctly rounded implementation of it is of great importance in producing numerically predictable code among today's heterogenous computing environment. existing results suggest that to get the correctly rounded α in a floating point number system with p significant bits, we may have to compute up to 3p + 1 leading bits of α. however, numerical evidence indicates the actual number may be as small as 2p plus a few more bits. this paper attempts to bridge the gap by showing that this is indeed true, assuming the abc conjecture which is widely purported to hold. (but our results do not tell exactly how many more bits beyond the 2p bits, due to the fact that the constants involved in the conjecture are ineffective.) along the way, rough bounds which are comparable to the existing ones are also proven. the technique used here is a combination of the classical liouville's estimation and contemporary number theory.
a functorial semantics for multi-algebras and partial algebras, with applications to syntax. multi-algebras allow for the modelling of nondeterminism in an algebraic framework by interpreting operators as functions from individual arguments to sets of possible results. we propose a functorial presentation of various categories of multi-algebras and partial algebras, analogous to the classical presentation of algebras over a signature σ as cartesian functors from the algebraic theory over σ to set. we introduce two different notions of theory over a signature, both having a structure weaker than cartesian, and we consider functors from them to rel or pfn, the categories of sets and relations or partial functions, respectively.next we discuss how the functorial presentation provides guidelines when choosing syntactical notions for a class of algebras, and as an application we argue that the natural generalization of usual terms are "conditioned terms" for partial algebras, and "term graphs" for multi-algebras.
on axioms for commutative regular equations without addition. algebras of commutative languages consist of all subsets of a free commutative monoid over a given alphabet σ, and they are endowed with the operations of union, complex multiplication, kleene iteration (submonoid generation), and the empty set and the set whose unique element is the unit of the free monoid, as constants. there is a well-known equational axiomatization for these algebras. however, any such axiomatization is necessarily infinite. now, by removing the operation of union (addition) from the described algebras, the corresponding equational theory reduces to the collection of those equations which contain no symbols of addition. we supply a nontrivial list of equational axioms for the so obtained equational theory, and prove that it has no finite equational base, too.
compositional sos and beyond: a coalgebraic view of open systems. in this paper we address the issue of providing a structured coalgebra presentation of transition systems with algebraic structure on states determined by an equational specification . more precisely, we aim at representing such systems as coalgebras for an endofunctor on the category of -algebras. the systems we consider are specified by using arbitrary sos rules, which in general do not guarantee that bisimilarity is a congruence. we first show that the structured coalgebra representation works only for systems where transitions out of complex states can~be derived from transitions out of corresponding component states. this decomposition property of transitions indeed ensures that bisimilarity is a congruence. for a system not satisfying this requirement, next we propose a closure construction which adds context transitions, i.e., transitions that spontaneously embed a state into a bigger context or vice versa. the notion of bisimulation for the enriched system coincides with the notion of dynamic bisimilarity for the original one, i.e., with the coarsest bisimulation which is a congruence. this is sufficient to ensure that the structured coalgebra representation works for the systems obtained as result of the closure construction.
measuring the performance of asynchronous systems with pafas. based on process algebra for faster asynchronous systems (pafas), a testing-based faster-than relation has previously been developed that compares the worst-case efficiency of asynchronous systems. this approach reveals that pipelining does not improve efficiency in general; that it does so in practice depends on assumptions about the user behaviour. as a case study for testing under such assumptions, we adapt the pafas-approach to a setting where user behaviour is known to belong to a specific, but often occurring class of request-response behaviours.just as the testing preorder in classical testing, the original faster-than relation is qualitative. we give it a quantitative reformulation for the general approach; based on this, we demonstrate in our case study how to determine an asymptotic performance measure for finite-state processes. with this result, we can show that pipelining indeed improves efficiency in our setting, and we discuss additional examples.
the permutation-path coloring problem on trees. in this paper we first show that the permutation-path coloring problem is np-hard even for very restrictive instances like involutions, which are permutations that contain only cycles of length at most two, on both binary trees and on trees having only two vertices with degree greater than two, and for circular permutations, which are permutations that contain exactly one cycle, on trees with maximum degree greater than or equal to 4. we calculate a lower bound on the average complexity of the permutation-path coloring problem on arbitrary networks. then we give combinatorial and asymptotic results for the permutation-path coloring problem on linear networks in order to show that the average number of colors needed to color any permutation on a linear network on n vertices is n/4 + o(n). we extend these results and obtain an upper bound on the average complexity of the permutation-path coloring problem on arbitrary trees, obtaining exact results in the case of generalized star trees. finally we explain how to extend these results for the involutions-path coloring problem on arbitrary trees.
operational and abstract semantics of the query language g-log. the amount and variety of data available electronically have dramatically increased in the last decade; however, data and documents are stored in different ways and do not usually show their internal structure. in order to take full advantage of the topological structure of digital documents, and particularly web sites, their hierarchical organization should be exploited by introducing a notion of query similar to the one used in database systems. a good approach, in that respect, is the one provided by graphical query languages, originally designed to model object bases and later proposed for semistructured data, like g-log. the aim of this paper is to provide suitable graph-based semantics to this language, supporting both data structure variability and topological similarities between queries and document structures. a suite of operational semantics based on the notion of bisimulation is introduced both at the concrete level (instances) and at the abstract level (schemata), giving rise to a semantic framework that benefits from the cross-fertilization of tools originally designed in quite different research areas (databases, concurrency, logics, static analysis).
pc grammar systems with five context-free components generate all recursively enumerable languages. parallel communicating grammar systems (pc grammar systems, in short) are language generating devices consisting of several context-free grammars which work synchronously on their own sentential forms and communicate the generated strings to each other by request. these systems with eleven components are known to have the power of the turing machines. we considerably improve this result, proving that five components suffice in order to generate any recursively enumerable language.
parallel communicating grammar systems with bounded resources. in this paper we study size properties of context-free returning parallel communicating grammar systems (pc grammar systems). we show that for each context-free returning pc grammar system an equivalent system of this type can be constructed, where the total number of symbols used for describing a component can be bounded by a reasonably small constant. since context-free returning pc grammar systems determine the class of recursively enumerable languages, the result also demonstrates that the recursively enumerable language class can be economically described in terms of parallel communicating grammar systems.
biinfinite words with maximal recurrent unbordered factors. a finite non-empty word z is said to be a border of a finite non-empty word w if w = uz = zυ for some non-empty words u and υ. a finite non-empty word is said to be bordered if it admits a border, and it is said to be unbordered otherwise. in this paper, we give two characterizations of the biinfinite words of the form ωuυuω, where u and υ are finite words, in terms of its unbordered factors.the main result of the paper states that the words of the form ωuυuω are precisely the biinfinite words w=...a-2a-1a0a1a2... for which there exists a pair (l0, r0) of integers with l0 < r0 such that, for every integers l ≤ l0 and r ≥ r0, the factor al... al0...ar0...ar is a bordered word.the words of the form ωuυuω are also characterized as being those biinfinite words w that admit a left recurrent unbordered factor (i.e., an unbordered factor of w that has an infinite number of occurrences "to the left" in w) of maximal length that is also a right recurrent unbordered factor of maximal length. this last result is a biinfinite analogue of a result known for infinite words.
adding symbolic information to picture models: definitions and properties. in the paper we propose extensions of some picture models, such as colored, drawn and pixel pictures. such extensions are conceived by observing that a picture may embed more information than the shape, such as colors, labels, etc., which can be represented by a symbol from an alphabet and can be associated to segments, points or pixels. new interesting issues derived from the introduction of symbols will be investigated together with some complexity and decidability questions for the proposed extensions.
frozen development in graph coloring. we define the 'frozen development' of coloring random graphs. we identify two nodes in a graph as frozen if they are of the same color in all legal colorings and define the collapsed graph as the one in which all frozen pairs are merged. this is analogous to studies of the development of a backbone or spine in sat (the satisfiability problem). we first describe in detail the algorithmic techniques used to study frozen development. we present strong empirical evidence that freezing in 3-coloring is sudden. a single edge typically causes the size of the graph to collapse in size by 28%. we also use the frozen development to calculate unbiased estimates of probability of colorability in random graphs. this applies even where this probability is infinitesimal such as 10-300, although our estimates might be subject to very high variance. we investigate the links between frozen development and the solution cost of graph coloring. in sat, a discontinuity in the order parameter has been correlated with the hardness of sat instances, and our data for coloring are suggestive of an asymptotic discontinuity. the uncolorability threshold is known to give rise to hard test instances for graph-coloring. we present empirical evidence that the cost of coloring threshold graphs grows exponentially, when using either a specialist coloring program, or encoding into sat, or even when using the best of both techniques. hard instances seem to appear over an increasing range of graph connectivity as graph size increases. we give theoretical and empirical evidence to show that the size of the smallest uncolorable subgraphs of threshold graphs becomes large as the number of nodes in graphs increases. finally, we discuss some of the issues involved in applying our work to the statistical mechanics analysis of coloring.
the monadic second-order logic of graphs xiv: uniformly sparse graphs and edge set quantifications. we consider the class usk of uniformly k-sparse simple graphs, i.e., the class of finite or countable simple graphs, every finite subgraph of which has a number of edges bounded by k times the number of vertices. we prove that for each k, every monadic second-order formula (intended to express a graph property) that uses variables denoting sets of edges can be effectively translated into a monadic second-order formula where all set variables denote sets of vertices and that expresses the same property of the graphs in usk. this result extends to the class of uniformly k-sparse simple hypergraphs of rank at most m (for any k and m).it follows that every subclass of usk consisting of finite graphs of bounded clique-width has bounded tree-width. clique-width is a graph complexity measure similar to tree-width and relevant to the construction of polynomial algorithms for np-complete problems on special classes of graphs.
constructive metrisability in point-free topology. the notion of elementary diameter is introduced to provide, in the context of locale theory, a constructive notion of metrisability, besides foundational aspects, elementary diameters allow to express metrisability in locales more simply with respect to the existing (non-constructive) approach based on diameters. by relying on the presentation of locale theory provided by formal topology, the notions to be presented may be conceived as phrased within (martin-löf) type theory. a type-theoretic version of urysohn metrisation theorem is thus obtained. as an application, a set (data type) of indexes for the points of locally compact metrisable formal spaces is shown to exist.
the number of binary words avoiding abelian fourth powers grows exponentially. we show that the number of binary words of length n avoiding abelian fourth powers grows faster than rn, where r = 21/16.
pattern avoidance: themes and variations. we review results concerning words avoiding powers, abelian powers or patterns. in addition we collect/pose a large number of open problems.
on the size of the inverse neighborhoods for one-dimensional reversible cellular automata. in this paper we investigate the possible neighborhood size of the inverse automaton of some types of one-dimensional reversible cellular automata. considering only the case when the local function is a size two map, we give a quadratic upper bound for the neighborhood size of the inverse automaton. we show that this bound can be lowered in some particular cases, and give an algorithm for computing these better bounds.
the non-parametrizability of the word equation =: a short proof. although makanin proved the problem of satisfiability of word equations to be decidable, the general structure of solutions is difficult to describe. in particular, hmelevskii proved that the set of solutions of xyz = zvx cannot be described using only finitely many parameters, contrary to the case of equations in three unknowns. in this paper we give a short, elementary proof of hmelevskii's result.
on the power of parallel communicating watson-crick automata systems. parallel communicating watson-crick automata systems were introduced in [e. czeizler, e. czeizler, parallel communicating watson-crick automata systems, in: z. ésik, z. fülöp (eds.), proc. automata and formal languages, dobogókö, hungary, 2005, pp. 83-96] as possible models of dna computations. this combination of watson-crick automata and parallel communicating systems comes as a natural extension due to the new developments in dna manipulation techniques. it is already known, see [d. kuske, p. weigel, the role of the complementarity relation in watson-crick automata and sticker systems, dlt 2004, lecture notes in computer science, vol. 3340, auckland, new zealand, 2004, pp. 272-283], that for watson-crick finite automata, the complementarity relation plays no active role. however, this is not the case when considering parallel communicating watson-crick automata systems. in this paper we prove that non-injective complementarity relations increase the accepting power of these systems. we also prove that although watson-crick automata are equivalent to two-head finite automata, this equivalence is not preserved when comparing parallel communicating watson-crick automata systems and multi-head finite automata.
on polynomial-time approximation algorithms for the variable length scheduling problem. this paper may be viewed as a corrigendum as well as an extension of the paper by (czumaj et al., theoret. comput. sci. 262 (1-2), (2001) 569-582) where they deal with the variable length scheduling problem (vlsp) with parameters k1,k2, denoted vlsp(k1,k2). in the current paper, we first discuss an error in the analysis of one of the approximation algorithms described in (czumaj et al., theoret. comput. sci. 262 (1-2), (2001) 569-582), where an approximation algorithm for vlsp(k1,k2), k1 < k2, was presented and it was claimed that the algorithm achieves the approximation ratio of 1 + (k1(k2-k1))/k2. in this paper we give a problem instance for which the same algorithm obtains the approximation ratio ≈ k2/k1. we then present two simple approximation algorithms, one for the case k1 = 1 with an approximation ratio of 2, and one for the case k1 > 1 with an approximation ratio of 2 + (k2/2k1). this corrects the result claimed in (czumaj et al., theoret. comput. sci. 262 (1-2), (2001) 569-582).
testing hypergraph colorability. we study the problem of testing properties of hypergraphs. the goal of property testing is to distinguish between the case whether a given object has a certain property or is "far away" from the property. we prove that the fundamental problem of l-colorability of k-uniform hypergraphs can be tested in time independent of the size of the hypergraph. we present a testing algorithm that examines only (k l/ε)o(k) entries of the adjacency matrix of the input hypergraph, where ε is a distance parameter independent of the size of the hypergraph. the algorithm tests only a constant number of entries in the adjacency matrix provided that l, k, and ε are constants. this result is a generalization of previous results about testing graph colorability.
a combinatorial problem on trapezoidal words. in this paper, we investigate some combinatorial properties concerning the family of the so-called trapezoidal words. trapezoidal words, considered in de luca (theoret. comput. sci. 218 (1999) 13-39 are finite words over the two-letter alphabet a={a,b} whose subword complexity has the same behaviour as that of finite sturmian words. in de luca (theoret. comput. sci. 218 (1999) 13-39 it has been proved that the family of finite sturmian words is properly contained in that one of trapezoidal words. we carry on with the studying of the family of trapezoidal words and, in particular, of its relation with that one of finite sturmian words.
on quasi-open bisimulation. quasi-open bisimilarity is a variant of the open bisimilarity based on a closer examination of the observationality of local names. the paper investigates two alternative characterizations of the quasi-open bisimilarity and provides a complete system for the weak quasi-open congruence.
on the structure of the counting function of sparse context-free languages. we give an exact description of the counting function of a sparse context-free language. let l be a sparse context-free language and let fl be its counting function. then there exist polynomials p0, p1,...,pk - 1, with rational coefficients, and an integer constant k0, such that for any n ≥ k0 one has fl (n) = pj (n) where j is such that j ≡ n mod k. as a consequence one can easily show the decidability of some questions concerning sparse context-free languages. finally, we show that for any sparse context-free language l there exists a regular language l' such that for any n ≥ 0 one has fl (n) = fl' (n) and, therefore, fl is rational.
well quasi-orders and context-free grammars. let g be a context-free grammar and let l be the language of all the words derived from any variable of g. we prove the following generalization of higman's theorem: any division order on l is a well quasi-order on l. we also give applications of this result to some quasi-orders associated with unitary grammars.
additive symmetries: the non-negative case. an additive symmetric value b of a with respect to c satisfies c = (a + b)/2. existence and uniqueness of such b are basic properties in exact arithmetic that fail when a and b are floating point numbers and the computation of c performed in ieee-754-like arithmetic. we exhibit and prove conditions on the existence, the uniqueness and the consistency of an additive symmetric value when b and c have the same sign.
finite automata for compact representation of tuple dictionaries. a generalization of the dictionary data structure is described, called tuple dictionary. a tuple dictionary represents the mapping of n-tuples of strings to some value. this data structure is motivated by practical applications in speech and language processing, in which very large instances of tuple dictionaries are used to represent language models. a technique for compact representation of tuple dictionaries is presented. the technique can be seen as an application and extension of perfect hashing by means of finite-state automata. preliminary practical experiments indicate that the technique yields considerable and important space savings of up to 90% in practice.
determination of q-convex sets by x-rays. in this paper, the problem of the determination of lattice sets from x-rays is studied. we define the class of q-convex sets along a set d of directions which generalizes classical lattice convexity and we prove that for any d, the x-rays along d determine all the convex sets if and only if it determines all the q-convex sets along d. as a consequence, any algorithm which reconstructs q-convex sets from x-rays can be used to reconstruct convex lattice sets from x-rays along directions which provide uniqueness. this gives a constructive answer to the discrete version of hammer's x-ray problem.
the chords' problem. the chords' problem is a variant of an old problem of computational geometry: given a set of points of rn, one can easily build the multiset of the distances between the points of the set but the converse construction is known, for a longtime, as to be difficult. the problem that we are going to investigate is also a converse construction with the difference that it is not one of the distances' multisets but one of the chords' multisets. in dimension 1, the old distances' problem and the chords' problem coincide with each other whereas in other dimensions, the chords' multisets contain more information on the sets than their distances' multisets. this paper provides, in dimension 1, two different algorithms to reconstruct the set of points according to their chords' multiset. the first one is given for its effectiveness in spite of an uncertain complexity whereas the second one is the first polynomial algorithm solving the chords' problem. at least, we will explain how to transform a chords' problem in dimension n into an equivalent chords' problem in dimension 1.
some necessary clarifications about the chords' problem and the partial digest problem. we state in previous paper [a. daurat, y. gérard, m. nivat, the chords' problem, theoret. comput. sci. 282(2) (2002) 319-336] that the chords' problem can be solved in polynomial time. this result is however ambiguous and some people have been abused because the encoding of the data has not been given. the correctness of the result requires to specify the encoding of the data that we have used and to highlight the difference with the usual encoding implicitly considered in partial digest problem.
parallel construction of perfect matchings and hamiltonian cycles on dense graphs. the intensive study of fast parallel and distributed algorithms for various routing (and communications) problems on graphs with good expanding properties \ref{pu1}, \ref{pu2}, \ref{ss} is being carried out recently. the parallel solutions for expanders that already exist \ref{pu 2} required an extensive randomization and an application of a randomized subroutine for the maximum matching problem. in this paper we attack the problem of fast parallel algorithms for constructing perfect matchings and hamiltonian cycles on dense graph-networks (undirected graphs of minimal degree ${|v|\over 2}$). somewhat surprisingly, we design fast deterministic parallel algorithms for constructing both the perfect matchings and the hamiltonian cycles on the dense graphs. the algorithm for constructing perfect matchings on dense graphs works in $o(\log^2 n)$ parallel time and $o(n^8)$ processors or $o(\log^4 n)$ parallel time and $o(n^4)$ processors on a crew-pram. the algorithm for constructing hamiltonian cycles on dense graphs works in $o(\log^5 n)$ parallel time and $o(n^4)$ processors on a crew-pram. our method of the parallel solution involves a development of new dense graph combinatorics suitable for fast parallelization.
on the asymptotic behaviour of primitive recursive algorithms. this paper develops a new semantics (the trace of a computation) that is used to study intensional properties of primitive recursive algorithms. it gives a new proof of the "ultimate obstination theorem" of l. colson and extends it to the case when mutual recursion is permitted. the ultimate obstination theorem fails when other data types (e.g. lists) are used. i define another property (the backtracking property) of the same nature but which is weaker than the ultimate obstination. this property is proved for every primitive recursive algorithm using any kind of data types. copyright 2001 elsevier science b.v.
an efficient parallel algorithm for the minimal elimination ordering (meo) of an arbitrary graph. the first efficient parallel algorithm for computing minimal elimination ordering (meo) of an arbitrary graph is designed. the algorithm works in o(log/sup 3/n) parallel time and o(nm) processors on a concurrent-read-concurrent-write parallel random-access machine (crcw pram) for an n-vertex, m-edge graph and is optimal up to polylogarithmic factor with respect to the best sequential algorithm of d. rose et. al. (siam j. comput., vol.5, p.266-83, 1976). as an application, the first efficient parallel solution to the problem of minimal fill-in for arbitrary graphs is given. the method of solution involves the development of new techniques for solving the connected minimal set system problem and combining them with some new divide-and-conquer methods.
decidability results for primitive recursive algorithms. in this paper i use the notion of trace defined in (theoret. comput. sci. 266 (2001) 159) to extend coquand's constructive proof (c. r. acad. sci. ser. i 314 (1992)) of the ultimate obstination theorem of colson to the case when mutual recursion is allowed. as a by-product i get an algorithm that computes the value of a primitive recursive combinator applied to lazy integers (infinite or partially undefined arguments may appear). i also get, as coquand got from his proof, that, even when mutual recursion is allowed, there is no primitive recursive definition f such that f(sn(⊥)) = sn2 (⊥).
algorithms for four variants of the exact satisfiability problem. we present four polynomial space and exponential time algorithms for variants of the exact satisfiability problem. first, an o(1.1120n) (where n is the number of variables) time algorithm for the np-complete decision problem of exact 3-satisfiability, and then an o(1.1907n) time algorithm for the general decision problem of exact satisfiability. the best previous algorithms run in o(1.1193n) and o(1.2299n) time, respectively. for the #p-complete problem of counting the number of models for exact 3-satisfiability we present an o(1.1487n) time algorithm. we also present an o(1.2190n) time algorithm for the general problem of counting the number of models for exact satisfiability; presenting a simple reduction, we show how this algorithm can be used for computing the permanent of a 0/1 matrix.
counting models for 2sat and 3sat formulae. we here present algorithms for counting models and max-weight models for 2sat and 3sat formulae. they use polynomial space and run in o(1.2561n) and o(1.6737n) time, respectively, where n is the number of variables. this is faster than the previously best algorithms for counting nonweighted models for 2sat and 3sat, which run in o(1.3247n) and o(1.6894n) time, respectively. in order to prove these time bounds, we develop new measures of formula complexity, allowing us to conveniently analyze the effects of certain factors with a large impact on the total running time. we also provide an algorithm for the restricted case of separable 2sat formulae, with fast running times for well-studied input classes. for all three algorithms we present interesting applications, such as computing the permanent of sparse 0/1 matrices.
finite-state dimension. classical hausdorff dimension (sometimes called fractal dimension) was recently effectivized using gales (betting strategies that generalize martingales), thereby endowing various complexity classes with dimension structure and also defining the constructive dimensions of individual binary (infinite) sequences. in this paper we use gales computed by multi-account finite-state gamblers to develop the finite-state dimensions of sets of binary sequences and individual binary sequences. the theorem of eggleston (quart. j. math. oxford ser. 20 (1949) 31-36) relating hausdorff dimension to entropy is shown to hold for finite-state dimension, both in the space of all sequences and in the space of all rational sequences (binary expansions of rational numbers). every rational sequence has finite-state dimension 0, but every rational number in [0,1] is the finite-state dimension of a sequence in the low-level complexity class ac0. our main theorem shows that the finite-state dimension of a sequence is precisely the infimum of all compression ratios achievable on the sequence by information-lossless finite-state compressors.
backtracking games and inflationary fixed points. we define a new class of games, called backtracking games. backtracking games are essentially parity games with an additional rule allowing players, under certain conditions, to return to an earlier position in the play and revise a choice or to force a countback of the number of moves. this new feature makes backtracking games more powerful than parity games. as a consequence, winning strategies become more complex objects and computationally harder. the corresponding increase in expressiveness allows us to use backtracking games as model-checking games for inflationary fixed-point logics such as ifp or mic. we identify a natural subclass of backtracking games, the simple games, and show that these are the "right" model-checking games for ifp by (a) giving a translation of formulae ϕ and structures u into simple games such that u = φ if, and only if, player 0 wins the corresponding game and (b) showing that the winner of simple backtracking games can again be defined in ifp.
closure and decidability properties of some language classes with respect to ciliate bio-operations. the process of gene unscrambling in ciliates (a type of unicellular protozoa), which accomplishes the difficult task of re-arranging gene segments in the correct order and deleting non-coding sequences from an "encrypted" version of a dna strand, has been modeled and studied so far from the point of view of the computational power of the dna bio-operations involved. here we concentrate on a different aspect of the process, by considering only the linear version of the bio-operations, that do not involve thus any circular strands, and by studying the resulting formal operations from a purely language-theoretic point of view. we investigate closure properties of language families under the mentioned bio-operations and study language equations involving them. we also study the decidability of the existence of solutions to equations of the form l ♦ y = r, x ♦ l = r where l and r are given languages, x and y are unknowns, and ♦ signifies one of the defined bio-operations.
template-guided dna recombination. the family of stichotrichous ciliates have received a great deal of study due to the presence of scrambled genes in their genomes. the mechanism by which these genes are descrambled is of interest both as a biological process and as a model of natural computation. several formal models of this process have been proposed, the most recent of which involves the recombination of dna strands based on template guides. we generalize this template-guided dna recombination model proposed by prescott, ehrenfeucht and rozenberg to an operation on strings and languages. we then proceed to investigate the properties of this operation with the intention of viewing ciliate gene descrambling as a computational process.
learnability of quantified formulas. we consider the following classes of quantified formulas. fix a set of basic relations called a basis. take conjunctions of these basic relations applied to variables and constants in arbitrary ways. finally, quantify existentially or universally some of the variables. we introduce some conditions on the basis that guarantee efficient learnability. furthermore, we show that with certain restrictions on the basis the classification is complete. we introduce, as an intermediate tool, a link between this class of quantified formulas and some well-studied structures in universal algebra called clones. more precisely, we prove that the computational complexity of the learnability of these formulas is completely determined by a simple algebraic property of the basis of relations: their clone of polymorphisms. finally, we use this technique to give a simpler proof of the already known dichotomy theorem over boolean domains.
the complexity of counting homomorphisms seen from the other side. for every class of relational structures c, let hom(c, _) be the problem of deciding whether a structure a ∈ c has a homomorphism to a given arbitrary structure b. grohe has proved that, under a certain complexity-theoretic assumption, hom(c, _) is solvable in polynomial time if and only if the cores of all structures in c have bounded tree-width. we prove (under a weaker complexity-theoretic assumption) that the corresponding counting problem #hom(c, _) is solvable in polynomial time if and only if all structures in c have bounded tree-width. this answers an open question posed by grohe.
a 5/4-approximation algorithm for scheduling identical malleable tasks. we consider the problem of finding a schedule for n-independent identical malleable tasks on p identical processors with minimal completion time. this problem arises while using the branch-and-bound or the divide-and-conquer strategy to solve a problem on a parallel system. if nothing is known about the subproblems, then they are assumed to be identical. we assume that the execution time decreases with the number of processors while the computational work increases. we give an algorithm with execution time exponential in p which computes an optimal schedule. in order to approximate an optimal schedule, we use the concept of phase-by-phase schedules. here schedules consist of phases in which every job uses the same number of processors. we prove that one can approximate an optimal schedule up to a factor of 5/4 using constant time, and we show that this is optimal. furthermore, we give an ε-approximation algorithm if the speed-up is optimal up to a constant factor.
two short notes on the on-line travelling salesman: handling times and lookahead. we study extensions of the on-line travelling salesman problem. our results are: the optimal competitive ratio 2 for arbitrary metric spaces also holds in the case of nonzero handling times. the optimal competitive ratio 3/2 on the half-line cannot be improved by randomization, but there is a 4/3-competitive algorithm under the assumption that the server is notified when the last request has been released. this ratio is also optimal.
nearly optimal strategies for special cases of on-line capital investment. suppose that some job must be done for a period of unspecified duration. the market offers a selection of devices that can do this job, each characterized by purchase and running costs. which of them should we buy at what times, in order to minimize the total costs? as usual in competitive analysis, the cost of an on-line solution is compared to the optimum costs paid by a clearvoyant buyer. this problem which generalizes the basic rent-to-buy problem has been introduced by azar et al. in the so-called convex case where lower running costs always imply higher prices, a strategy with competitive ratio 4+2√2 ≈ 6.83 has been proposed. here we consider two natural subcases of the convex case in a continuous-time model where new devices can be bought at any time. for the static case where all devices are available at the beginning, we give a simple 4-competitive deterministic algorithm, and we show that 3.618 is a lower bound. (this is also the first non-trivial lower bound for the convex case, both for discrete and continuous time.) furthermore, we give a 2.88-competitive randomized algorithm. in the case that all devices have equal prices but are not all available at the beginning, we show that a very simple algorithm is 2-competitive, and we derive a 1.618 lower bound.
a causal semantics for ccs via rewriting logic. we consider two operational semantics for ccs defined in the literature: the first exploits proved transition systems (pts) and the second rewriting logic (rl). we show that the interleaving interpretation of both semantics agree, in that they define the same transitions and exhibit the same non-deterministic structure. in addition, we study causality in ccs computations. we recall its treatment via pts, exhibiting the notion of causality presented in the literature, and we show how to recast it in the rl semantics via suitable axioms. also in this case, the two semantics agree.
parameterized enumeration, transversals, and imperfect phylogeny reconstruction. we study parameterized enumeration problems where we are interested in all solutions of limited size rather than just some solution of minimum cardinality. (actually, we have to enumerate the inclusion-minimal solutions in order to get fixed-parameter tractable (fpt) results.) two novel concepts are the notion of a full kernel that contains all small solutions and implicit enumeration of solutions in form of compressed descriptions. in particular, we study combinatorial and computational bounds for the transversal hypergraph (vertex covers in graphs is a special case), restricted to hyperedges with at most k elements. as an example, we apply the results and further special-purpose techniques to almost-perfect phylogeny reconstruction, a problem in computational biology.
on queuing lengths in on-line switching. queues that temporarily store fixed-length packets are ubiquitous in network switches. scheduling algorithms that prevent packet-loss are always desirable. longest-queue-first (lqf) is an on-line greedy algorithm widely exploited because of its simplicity and efficiency. in this paper, we give improved bounds on the competitive ratio of lqf in terms of the worst-case queuing length, parameterized with respect to the optimal queuing length of a clairvoyant adversary. this gives a better picture of lqf's performance under heavy traffic than the usual (unparameterized) competitive ratio. we also discuss randomization, and we conclude with some intriguing open problems regarding a two-dimensional generalization of the problem.
a simple paradigm for graph recognition: application to cographs and distance hereditary graphs. an easy way for graph recognition algorithms is to use a two-step process: first, compute a characteristic feature as if the graph belongs to that class; second, check whether the computed characteristic feature as if the graph belongs to that class; second, check whether the computed separating them may yield new and much more easily understood algorithms. in this paper we apply that paradigm to the cograph and distance hereditary graph recognition problems.
on computing the entropy of cellular automata. we study the topological entropy of a particular class of dynamical systems: cellular automata. the topological entropy of a dynamical system (x,f) is a measure of the complexity of the dynamics of f over the space x. the problem of computing (or even approximating) the topological entropy of a given cellular automata is algorithmically undecidable (ergodic theory dynamical systems 12 (1992) 255). in this paper, we show how to compute the entropy of two important classes of cellular automata namely, linear and positively expansive cellular automata. in particular, we prove a closed formula for the topological entropy of d-dimensional (d ≥ 1) linear cellular automata over the ring zm (m ≥ 2) and we provide an algorithm for computing the topological entropy of positively expansive cellular automata.
formalizing generalized maps in coq. this paper is the first half of a two-part series devoted to an exemplary formal proof of a fundamental result in the field of geometry--the theorem of classification of surfaces--which has major implications in computer graphics. we study here the specification of generalized maps, a topological combinatory model for surfaces subdivisions. we show how we developed in coq two fundamentally distinct formalizations of generalized maps, each based on one of the standard definitions, in a single common framework, then used this specification to prove for the first time their complete equivalence.
formalizing the trading theorem in coq. this paper is the second half of a two-part series devoted to the formalization of a combinatorial model of geometric varieties, generalized maps. we study here how to express continuous notions like homeomorphisms in the combinatorial world, in order to constructively describe the well-known theorem of surface classification according to genus, number of boundaries and orientability coefficient. we then use the coq specification elaborated in the previous paper to prove the first half of this theorem, called the trading theorem.
pushdown timed automata: a binary reachability characterization and safety verification. we consider pushdown timed automata (ptas) that are timed automata (with dense clocks) augmented with a pushdown stack. a configuration of a pta includes a state, dense clock values and a stack word. by using the pattern technique, we give a decidable characterization of the binary reachability (i.e., the set of all pairs of configurations such that one can reach the other) of a pta. since a timed automaton can be treated as a pta without the pushdown stack, we can show that the binary reachability of a timed automaton is definable in the additive theory of reals and integers. the results can be used to verify a class of properties containing linear relations over both dense variables and unbounded discrete variables. the properties previously could not be verified using the classic region technique nor expressed by timed temporal logics for timed automata and ctl* for pushdown systems. the results are also extended to other generalizations of timed automata.
past pushdown timed automata and safety verification. we consider past pushdown timed automata that are discrete pushdown timed automata with past formulas as enabling conditions. using past formulas allows a past pushdown timed automaton to access the past values of the finite state variables in the automaton. we prove that the reachability (i.e., the set of reachable configurations from an initial configuration) of a past push-down timed automaton can be accepted by a nondeterministic reversal-bounded counter-machine augmented with a pushdown stack (i.e., a reversal-bounded npcm). by using the known fact that the emptiness problem for reversal-bounded npcms is decidable, we show that model-checking past pushdown timed automata against presburger safety properties on discrete clocks and stack word counts is decidable. we also investigate the reachability problem for a class of transition systems under some fairness constraints in the form of generalized past formulas. finally, we present an example astral specification to demonstrate the usefulness of the results.
generalized discrete timed automata: decidable approximations for safety verificatio. we consider generalized discrete timed automata with general linear relations over clocks and parameterized constants as clock constraints and with parameterized durations. we look at three approximation techniques (i.e., the r-reset-bounded approximation, the b-bounded approximation, and the 〈b, r〉-crossing-bounded approximation), and derive automata-theoretic characterizations of the binary reachability under these approximations. the characterizations allow us to show that the safety analysis problem is decidable for generalized discrete timed automata with unit durations and for deterministic generalized discrete timed automata with parameterized durations. an example specification written in astral is used to run a number of experiments using one of the approximation techniques.
on two-way nondeterministic finite automata with one reversal-bounded counter. we show that the emptiness problem for two-way nondeterministic finite automata augmented with one reversal-bounded counter (i.e., the counter alternates between nondecreasing and nonincreasing modes for a fixed number of times) operating on bounded languages (i.e., subsets of w*1 ... w*k for some nonnull words w1, ...., wk) is decidable, resolving an open problem. the proof is a rather involved reduction to the solution of a special class of diophantine systems of degree 2 via a class of programs called two-phase programs.
on feasible cases of checking multi-agent systems behavior. the complexity of multi-agent systems behavior properties is studied. the behavior properties are formulated using classical temporal logic languages and are checked relative to the transition system induced by the multi-agent system definition. we show that there are deterministic or nondeterministic polynomial time check algorithms under some realistic structural and semantic restrictions on agent programs and actions.
on composition and lookahead delegation of -services modeled by automata. let m be a class of (possibly nondeterministic) language acceptors with a one-way input tape. a system (a; a1,..., ar) of automata in m is composable if for every string w = a1...an of symbols accepted by a, there is an assignment of each symbol aj in w to one of the ai's such that for each 1 ≤ i ≤ r, the subsequence of w assigned to ai is accepted by ai. for a nonnegative integer k, a k-lookahead delegator for (a; a1,..., ar) is a deterministic machine d in m which, knowing (a) the current states of a, a1,...,ar and the accessible "local" information of each machine (e.g., the top of the stack if each machine is a pushdown automaton, whether a counter is zero or nonzero if each machine is a multicounter automaton, etc.), and (b) the k lookahead symbols to the right of the current input symbol being processed, can uniquely determine the ai to assign the current symbol. moreover, every string w accepted by a is also accepted by d; i.e., the subsequence of string w delegated by d to each ai is accepted by ai. thus, k-lookahead delegation is a stronger requirement than composability, since the delegator d must be deterministic. a system that is composable may not have a k-delegator for any k.we study the decidability of composability and existence of k-delegators for various classes of machines m. our results generalize earlier ones (and resolve some open questions) concerning composability of deterministic finite automata as e-services to finite automata that are augmented with unbounded storage (e.g., counters and pushdown stacks) and finite automata with discrete clocks (i.e., discrete timed automata). the results have applications to automated composition of e-services.
presburger liveness verification of discrete timed automata. using an automata-theoretic approach, we investigate the decidability of liveness properties (called presburger liveness properties) for timed automata when presburger formulas on configurations are allowed. while the general problem of checking a temporal logic such as tptl augmented with presburger clock constraints is undecidable, we show that there are various classes of presburger liveness properties which are decidable for discrete timed automata. for instance, it is decidable, given a discrete timed automaton a and a presburger property p, whether there exists an ω-path of a where p holds infinitely often. we also show that other classes of presburger liveness properties are indeed undecidable for discrete timed automata, e.g., whether p holds infinitely often for each ω-path of a. these results might give insights into the corresponding problems for timed automata over dense domains, and help in the definition of a fragment of linear temporal logic, augmented with presburger conditions on configurations, which is decidable for model checking timed automata.
identifying codes in some subgraphs of the square lattice. an identifying code of a graph is a subset of vertices c such that the sets b(v) ∩ c are all nonempty and different. in this paper, we investigate the problem of finding identifying codes of minimum cardinality in strips and finite grids. we first give exact values for the strips of height 1 and 2, then we give general bounds for strips and finite grids. finally, we give a sublinear algorithm which finds the minimum cardinality of an identifying code in a restricted class of graphs which includes the grid.
using interval arithmetic to prove that a set is path-connected. in this paper, we give a numerical algorithm able to prove whether a set s described by nonlinear inequalities is path-connected or not. to our knowledge, no other algorithm (numerical or symbolic) is able to deal with this type of problem. the proposed approach uses interval arithmetic to build a graph which has exactly the same number of connected components as s. examples illustrate the principle of the approach.
minimization and np multifunctions. the implicit characterizations of the polynomial-time computable functions fp given by bellantoni-cook and leivant suggest that this class is the complexity-theoretic analog of the primitive recursive functions. hence, it is natural to add minimization operators to these characterizations and investigate the resulting class of partial functions as a candidate for the analog of the partial recursive functions. we do so in this paper for cobham's definition of fp by bounded recursion and for bellantoni-cook's safe recursion and prove that the resulting classes capture exactly npmv, the nondeterministic polynomial-time computable partial multifunctions. we also consider the relationship between our schemes and a notion of nondeterministic recursion defined by leivant and show that the latter characterizes the total functions of npmv. we view these results as giving evidence that npmv is the appropriate analog of partial recursive. this view is reinforced by earlier results of spreen and stahl who show that for many of the relationships between partial recursive functions and r.e. sets, analogous relationships hold between npmv and np sets. furthermore, since npmv is obtained from fp in the same way as the recursive functions are obtained from the primitive recursive functions (when defined via function schemes), this also gives further evidence that fp is properly seen as playing the role of primitive recursion.
enumeration of polyominoes using macsyma. this paper shows the use of a symbolic language, macsyma, to obtain new exact or asymptotic results in combinatorics. the examples are taken among polyominoes [sic] objects. the main purpose of the paper is to show how easy it is to bring some methods into operation in order to obtain new results in enumerative combinatorics. &mdash;from the abstract
computational isomorphisms in classical logic. all standard 'linear' boolean equations are shown to be computationally realized within a suitable classical sequent calculus lkηp. specifically, lkηp can be equipped with a cut-elimination compatible equivalence on derivations based upon reversibility properties of logical rules. so that any pair of derivations, without structural rules, of f → g and g → f, where f, g are first-order formulas 'without any qualities', defines a computational isomorphism.
formal molecular biology. a language of formal proteins, the k-calculus, is introduced. interactions are modeled at the domain level, bonds are represented by means of shared names, and reactions are required to satisfy a causality requirement of monotonicity.an example of a simplified signalling pathway is introduced to illustrate how standard biological events can be expressed in our protein language. a more comprehensive example, the lactose operon, is also developed, bringing some confidence in the formalism considered as a modeling language.then a finer-grained concurrent model, the mk-calculus, is considered, where interactions have to be at most binary. we show how to embed the coarser-grained language in the latter, a properly which we call self-assembly.finally we show how the finer-grained language can itself be encoded in π-calculus, a standard foundational language for concurrency theory.
a deterministic (2-2/(k+1)) algorithm for k-sat based on local search. local search is widely used for solving the propositional satisfiability problem. papadimitriou (1991) showed that randomized local search solves 2-sat in polynomial time. recently, schöning (1999) proved that a close algorithm for k-sat takes time (2 - 2/k)n up to a polynomial factor. this is the best known worst-case upper bound for randomized 3-sat algorithms (cf. also recent preprint by schuler et al.).we describe a deterministic local search algorithm for k-sat running in time (2-2/(k+ 1))n up to a polynomial factor. the key point of our algorithm is the use of covering codes instead of random choice of initial assignments. compared to other "weakly exponential" algorithms, our algorithm is technically quite simple. we also describe an improved version of local search. for 3-sat the improved algorithm runs in time 1.481n up to a polynomial factor. our bounds are better than all previous bounds for deterministic k-sat algorithms.
a first-order one-pass cps transformation. we present a new transformation of λ-terms into continuation-passing style (cps). this transformation operates in one pass and is both compositional and first-order. previous cps transformations only enjoyed two out of the three properties of being first-order, one-pass, and compositional, but the new transformation enjoys all three properties. it is proved correct directly by structural induction over source terms instead of indirectly with a colon translation, as in plotkin's original proof. similarly, it makes it possible to reason about cps-transformed terms by structural induction over source terms, directly.the new cps transformation connects separately published approaches to the cps transformation. it has already been used to state a new and simpler correctness proof of a direct-style transformation, and to develop a new and simpler cps transformation of control-flow information.
quasi-periodic configurations and undecidable dynamics for tilings, infinite words and turing machines. we describe turing machines, tilings and infinite words as dynamical systems and analyze some of their dynamical properties. it is known that some of these systems do not always have periodic configurations; we prove that they always have quasi-periodic configurations and we quantify quasi-periodicity. we then study the decidability of dynamical properties for these systems. in analogy to rice's theorem for computable functions, we derive a theorem that characterizes dynamical system properties that are undecidable. as an illustration of this result, we prove that topological entropy is undecidable for turing machines and for tilings.
solitaire clobber. clobber is a new two-player board game. in this paper, we introduce the one-player variant solitaire clobber where the goal is to remove as many stones as possible from the board by alternating white and black moves. we show that a n stone checkerboard configuration on a single row (or single column) can be reduced to about n/4 stones. for boards with at least two rows and two columns, we show that a checkerboard configuration can be reduced to a single stone if and only if the number of stones is not a multiple of three, and otherwise it can be reduced to two stones. we also show that in general it is np-complete to decide whether an arbitrary clobber configuration can be reduced to a single stone.
correlation clustering in general weighted graphs. we consider the following general correlation-clustering problem [n. bansal, a. blum, s. chawla, correlation clustering, in: proc. 43rd annu. ieee symp. on foundations of computer science, vancouver, canada, november 2002, pp. 238-250]: given a graph with real nonnegative edge weights and a 〈+〉/〈-〉 edge labelling, partition the vertices into clusters to minimize the total weight of cut 〈+〉 edges and uncut 〈-〉 edges. thus, 〈+〉 edges with large weights (representing strong correlations between endpoints) encourage those endpoints to belong to a common cluster while 〈-〉 edges with large weights encourage the endpoints to belong to different clusters. in contrast to most clustering problems, correlation clustering specifies neither the desired number of clusters nor a distance threshold for clustering; both of these parameters are effectively chosen to be best possible by the problem definition.correlation clustering was introduced by bansal et al. [correlation clustering, in: proc. 43rd annu. ieee syrup. on foundations of computer science, vancouver, canada, november 2002, pp. 238-250], motivated by both document clustering and agnostic learning. they proved np-hardness and gave constant-factor approximation algorithms for the special case in which the graph is complete (full information) and every edge has the same weight. we give an o(log n)-approximation algorithm for the general case based on a linear-programming rounding and the "region-growing" technique. we also prove that this linear program has a gap of ω(log n), and therefore our approximation is tight under this approach. we also give an o(r3)-approximation algorithm for kr, r-minor-free graphs. on the other hand, we show that the problem is equivalent to minimum multicut, and therefore apx-hard and difficult to approximate better than θ(log n).
operations and language generating devices suggested by the genome evolution. language-theoretic problems arising from the genome evolution discussed in series of papers (dassow and mitrana, proc. 2nd pacific symp. on biocomputing, world scientific, singapore, 1997, pp. 97-108; bioinformatics, lecture notes in computer science, vol. 1278, springer, berlin, pp. 199-209; dassow et al., biosystems 43 (1997) 169-177; dassow, jewels are forever, springer, berlin, 1999, pp. 171-181) are presented in a uniform way. the main emphasis is on the operations of inversion, transposition, duplication and deletion suggested by the genome evolution. basic problems concerning these operations and their iterated versions are settled. a generative device (evolutionary grammar) based on these operations is investigated from different points of view (computational power, decidability problems, descriptional complexity). "adult languages" (sets of stable strings) of such evolutionary grammars possess a surprising generative power.
understanding the mismatch combinator in chi calculus. the theory of chi processes with the mismatch operator is studied. four congruence relations are investigated. these are late open congruence, early open congruence, ground congruence and barbed congruence. the late and early open congruence relations are the chi calculus counterparts of the weak late and early congruence relations of pi calculus. both turn out to be special cases of the ground congruence and the barbed congruence. the ground congruence is essentially the open congruence. complete systems are given for all the four congruence relations. these systems use some interesting tau laws unknown from previous studies of the chi calculus without the mismatch combinator. the results of this paper point out that the mismatch operator changes the algebraic semantics of chi calculus dramatically. they also correct some common mistakes in literature.
online searching with turn cost. we consider the problem of searching for an object on a line at an unknown distance opt from the original position of the searcher, in the presence of a cost of d for each time the searcher changes direction. this is a generalization of the well-studied linear-search problem. we describe a strategy that is guaranteed to find the object at a cost of at most 9 ċ opt + 2d, which has the optimal competitive ratio 9 with respect to opt plus the minimum corresponding additive term. our argument for upper and lower bound uses an infinite linear program, which we solve by experimental solution of an infinite series of approximating finite linear programs, estimating the limits, and solving the resulting recurrences for an explicit proof of optimality. we feel that this technique is interesting in its own right and should help solve other searching problems. in particular, we consider the star search or cowpath problem with turn cost, where the hidden object is placed on one of m rays emanating from the original position of the searcher. for this problem we give a tight bound of (1 + 2mm/(m - 1)m-1)opt + m((m/(m - 1))m-1 - 1)d. we also discuss tradeoffs between the corresponding coefficients and we consider randomized strategies on the line.
range assignment for energy efficient broadcasting in linear radio networks. given a set s of n radio-stations located on a d-dimensional space, a source node s (∈ s) and an integer h (1 ≤ h ≤ n - 1), the h-hop broadcast range assignment problem deals with assigning ranges to the members in s so that s can communicate with all other members in s in at most h-hops, and the total power consumption is minimum. the problem is known to be np-hard for d ≥ 2. we propose an o(n2) time algorithm for the one dimensional version (d = 1) of the problem. this is an improvement over the existing result on this problem by a factor of h [a.e.f clementi et al. the minimum broadcast range assignment problem on linear multi-hop wireless networks, theoret. comput. sci. 299 (2003) 751-761].
on approximate learning by multi-layered feedforward circuits. we deal with the problem of efficient learning of feedforward neural networks. first, we consider the objective to maximize the ratio of correctly classified points compared to the size of the training set. we show that it is np-hard to approximate the ratio within some constant relative error if architectures with varying input dimension, one hidden layer, and two hidden neurons are considered where the activation function in the hidden layer is the sigmoid function, and the situation of epsilon-separation is assumed, or the activation function is the semilinear function. for single hidden layer threshold networks with varying input dimension and n hidden neurons, approximation within a relative error depending on n is np-hard even if restricted to situations where the number of examples is limited with respect to n.afterwards, we consider the objective to minimize the failure ratio in the presence of misclassification errors. we show that it is np-hard to approximate the failure ratio within any positive constant for a multilayered threshold network with varying input dimension and a fixed number of neurons in the hidden layer if the thresholds of the neurons in the first hidden layer are zero. furthermore, even obtaining weak approximations is almost np-hard in the same situation.
(, )-coloring problems in line graphs. the (p, k)-coloring problems generalize the usual coloring problem by replacing stable sets by cliques and stable sets. complexities of some variations of (p, k)-coloring problems (split-coloring and cocoloring) are studied in line graphs; polynomial algorithms or proofs of np-completeness are given according to the complexity status. we show that the most general (p, k)-coloring problems are more difficult than the cocoloring and the split-coloring problems while there is no such relation between the last two problems. we also give complexity results for the problem of finding a maximum (p, k)-colorable subgraph in line graphs. finally, upper bounds on the optimal values are derived in general graphs by sequential algorithms based on welsh-powell and matula orderings.
on-line vertex-covering. we study the minimum vertex-covering problem under two on-line models corresponding to two different ways vertices are revealed. the former one implies that the input-graph is revealed vertex-by-vertex. the second model implies that the input-graph is revealed per clusters, i.e. per induced subgraphs of the final graph. under the cluster-model, we then relax the constraint that the choice of the part of the final solution dealing with each cluster has to be irrevocable, by allowing backtracking. we assume that one can change decisions upon a vertex membership of the final solution, this change implying, however, some cost depending on the number of the vertices changed.
a polynomial space construction of tree-like models for logics with local chains of modal connectives. the la-logics ("logics with local agreement") are polymodal logics defined semantically such that at any world of a model, the sets of successors for the different accessibility relations can be linearly ordered and the accessibility relations are equivalence relations. in a previous work, we have shown that every la-logic defined with a finite set of modal indices has an np-complete satisfiability problem. in this paper, we introduce a class of la-logics with a countably infinite set of modal indices and we show that the satisfiability problem is pspace-complete for every logic of such a class. the upper bound is shown by exhibiting a tree structure of the models. this allows us to establish a surprising correspondence between the modal depth of formulae and the number of occurrences of distinct modal connectives. more importantly, as a consequence, we can show the pspace-completeness of gargov's logic dalla and nakamura's logic lgm restricted to modal indices that are rational numbers, for which the computational complexity characterization has been open until now. these logics are known to belong to the class of information logics and fuzzy modal logics, respectively.
ltl over integer periodicity constraints. periodicity constraints are used in many logical formalisms, in fragments of presburger ltl, in calendar logics, and in logics for access control, to quote a few examples. in the paper, we introduce the logic pltlmod, an extension of linear-time temporal logic ltl with past-time operators whose atomic formulae are defined from a first-order constraint language dealing with periodicity. although the underlying constraint language is a fragment of presburger arithmetic shown to admit a pspace-complete satisfiability problem, we establish that pltlmod model-checking and satisfiability problems remain in pspace as plain ltl (full presburger ltl is known to be highly undecidable). this is particularly interesting for dealing with periodicity constraints since the language of pltlmod has a language more concise than existing languages and the temporalization of our first-order language of periodicity constraints has the same worst case complexity as the underlying constraint language. finally, we show examples of introduction the quantification in the logical language that provide to pltlmod, expspace-complete problems. as another application, we establish that the equivalence problem for extended single-string automata, known to express the equality of time granularities, is pspace-complete by designing a reduction from qbf and by using our results for pltlmod.
towards an algebraic theory of typed mobile processes. the impact of types on the algebraic theory of the π-calculus is studied. the type system has capability types. they allow one to distinguish between the ability to read from a channel, to write to a channel, and both to read and to write. they also give rise to a natural and powerful subtyping relation.two variants of typed bisimilarity are considered, both in their late and in their early version. for both of them, proof systems that are sound and complete on the closed finite terms are given. for one of the two variants, a complete axiomatisation for the open finite terms is also presented.
learning from positive and unlabeled examples. in many machine learning settings, labeled examples are difficult to collect while unlabeled data are abundant. also, for some binary classification problems, positive examples which are elements of the target concept are available. can these additional data be used to improve accuracy of supervised learning algorithms? we investigate in this paper the design of learning algorithms from positive and unlabeled data only. many machine learning and data mining algorithms, such as decision tree induction algorithms and naive bayes algorithms, use examples only to evaluate statistical queries (sq-like algorithms). kearns designed the statistical query learning model in order to describe these algorithms. here, we design an algorithm scheme which transforms any sq-like algorithm into an algorithm based on positive statistical queries (estimate for probabilities over the set of positive instances) and instance statistical queries (estimate for probabilities over the instance space). we prove that any class learnable in the statistical query learning model is learnable from positive statistical queries and instance statistical queries only if a lower bound on the weight of any, target concept f can be estimated in polynomial time. then, we design a decision tree induction algorithm posc4.5, based on c4.5, that uses only positive and unlabeled examples and we give experimental results for this algorithm. in the case of imbalanced classes in the sense that one of the two classes (say the positive class) is heavily underrepresented compared to the other class, the learning problem remains open. this problem is challenging because it is encountered in many real-world applications.
learning regular languages using rfsas. residual languages are important and natural components of regular languages and several grammatical inference algorithms naturally rely on this notion. in order to identify a given target language l, classical inference algorithms try to identify words which define identical residual languages of l. here, we study whether it could be interesting to perform a tighter analysis by identifying inclusion relations between the residual languages of l. we consider the class of residual finite state automata (rfsas). an rfsa a is a nondeterministic automaton whose states corresponds to residual languages of the language la it recognizes. the inclusion relations between residual languages of la can be naturally materialized on a. we prove that the class of rfsas is not polynomially characterizable. we lead some experiments which show that when a regular language is randomly drawn by using a nondeterministic representation, the number of inclusion relations between its residual languages is very important. moreover, its minimal rfsa representation is much smaller than its minimal dfa representation. finally, we design a new learning algorithm, delete2, based on the search for the inclusion relations between the residual languages of the target language. we give sufficient conditions for the identifiability of the target language. we experimentally compare the performance of delete2 to those of classical inference algorithms.
correctness of java card method lookup via logical relations. this article presents a formalisation of the bytecode optimisation of sun's java card language from the class file to cap file format as a set of constraints between the two formats, and defines and proves its correctness. java card bytecode is formalised using an abstract operational semantics, which can then be instantiated into the two formats. the optimisation is given as a logical relation such that the instantiated semantics are observably equal.
strategies for the renyi-ulam game with fixed number of lies. we consider the problem of finding the minimal number ll(m) of binary questions needed to find an unknown element of a set of cardinality m with a sequential strategy if at most l of the answers are lies. obviously, in the case l = 0 ⌈ log m ⌉ questions are needed. thus, one more question is necessary if the number of elements is doubled. we show that for every fixed l and sufficiently large m, then ll(2m) ≤ ll(m) + 2 and moreover ll(3/2m) ≤ ll(m)+ 1. these bounds are sharp in infinitely many cases. as a consequence, at most one question more than the information theoretic lower bound is needed to successfully find the unknown number. one of our strategies uses the minimum amount of adaptiveness during the search process.
abstract canonical presentations. solving goals--like proving properties, deciding word problems or resolving constraints--is much easier with some presentations of the underlying theory than with others. typically, what have been called "completion processes", in particular in the study of equational logic, involve finding appropriate presentations of a given theory to more easily solve a given class of problems.we provide a general proof-theoretic setting that relies directly on the fundamental concept of "good", that is, normal-form, proofs, itself defined using well-founded orderings on proof objects. this foundational framework allows for abstract definitions of canonical presentations and very general characterizations of saturation and redundancy criteria.
metrics for labelled markov processes. the notion of process equivalence of probabilistic processes is sensitive to the exact probabilities of transitions. thus, a slight change in the transition probabilities will result in two equivalent processes being deemed no longer equivalent. this instability is due to the quantitative nature of probabilistic processes. in a situation where the process behavior has a quantitative aspect there should be a more robust approach to process equivalence. this paper studies a metric between labelled markov processes. this metric has the property that processes are at zero distance if and only if they are bisimilar. the metric is inspired by earlier work on logics for characterizing bisimulation and is related, in spirit, to the hutchinson metric.
an algorithm to generate exactly once every tiling with lozenges of a domain. we first show that the tilings of a domain d form a lattice (using the same kind of arguments as in (research report no. 1999-25)) which we then undertake to decompose and generate without any redundance. to this end, we study extensively the relatively simple case of hexagons and their deformations. we show that general domains can be broken up into hexagon-like parts. finally we give an algorithm to generate exactly once every element in the lattice of the tilings of a general domain d.
domino tilings and related models: space of configurations of domains with holes. we first prove that the set of domino tilings of a fixed finite figure is a distributive lattice, even in the case when the figure has holes. we then give a geometrical interpretation of the order given by this lattice, using (not necessarily local) transformations called flips.this study allows us to formulate an exhaustive generation algorithm and a uniform random sampling algorithm.we finally extend these results to other types of tilings (calisson tilings, tilings with bicolored wang tiles).
optimal graph exploration without good maps. a robot has to visit all nodes and traverse all edges of an unknown undirected connected graph, using as few edge traversals as possible. the quality of an exploration algorithm a is measured by comparing its cost (number of edge traversals) to that of the optimal algorithm having full knowledge of the graph. the ratio between these costs, maximized over all starting nodes in the graph and over all graphs in a given class u, is called the overhead of algorithm a for the class u of graphs. we consider three scenarios, providing the robot with varying amount of information. the robot may either know nothing about the explored graph, or have an unlabeled isomorphic copy of it (an unanchored map), or have such a copy with a marked starting node (an anchored map).for all of the above scenarios, we construct natural exploration algorithms that have smallest, or--in one case--close to smallest, overhead. while for the class of all graphs, depth-first search turns out to be an optimal algorithm for all scenarios, the situation for trees is much different. we show that, under the scenario without any knowledge, dfs is still optimal for trees but this is not the case if a map is available. under the scenario with an unanchored map, we show that optimal overhead is at least √3 but strictly below 2 (and thus dfs is not optimal). under the scenario with an anchored map, we construct an optimal algorithm for trees and show that its overhead is 3/2. we also consider exploration of the class of lines (simple paths). in this case, depth-first search remains optimal for the scenario without any knowledge, with overhead 2. under the scenario with an unanchored map, we construct an optimal algorithm and show that its overhead is √3. finally, under the scenario with an anchored map, we construct an optimal algorithm and show that its overhead is 7/5. an important contribution of this paper is establishing lower bounds that prove optimality of these exploration algorithms.
a formula for the number of tilings of an octagon by rhombi. we propose the first algebraic determinantal formula to enumerate tilings of a centrosymmetric octagon of any size by rhombi. this result uses the gessel-viennot technique and generalizes to any octagon a formula given by elnitsky in a special case.
a bijection between directed column-convex polyominoes and ordered trees of height at most three. a bijection is given between the set of directed column-convex polyominoes of area n and the set of ordered trees of height at most three and having n edges. additional bijections with less well known combinatorial objects are sketched.
xml queries and constraints, containment and reformulation. starting from the xquery language we define xbind, an xml analog of relational conjunctive queries as well as a related class of xml integrity constraints (dependencies). we identify a fragment of xbind for which containment is decidable, in fact π2p-complete, and a further fragment for which containment is np-complete. we extend the containment algorithm to take xml dependencies into account. we give an algorithm for the reformulation of xbind queries under combinations of gav and lav xquery views, as well as additional dependencies. we prove a completeness theorem which guarantees that under certain conditions, our algorithm will find a minimal reformulation if one exists. moreover, we identify conditions when this algorithm achieves optimal complexity bounds. our results on containment and reformulation depend on certain restrictions on the query and constraint languages. we calibrate the results by showing that lifting these restrictions significantly changes the complexity of the problems.
rounding voronoi diagram. computational geometry classically assumes real-number arithmetic which does not exist in actual computers. a solution consists in using integer coordinates for data and exact arithmetic for computations. this approach implies that if the results of an algorithm are the input of another, these results must be rounded to match this hypothesis of integer coordinates. in this paper, we treat the case of two-dimensional voronoi diagrams and are interested in rounding the voronoi vertices to grid points while interesting properties of the voronoi diagram are preserved. these properties are the planarity of the embedding and the convexity of the cells. we give a condition on the grid size to ensure that rounding to the nearest grid point preserves the properties. we also present heuristics to round vertices (not to the nearest grid point) and preserve these properties.
general parameterised refinement and recursion for the m-net calculus. the algebra of m-nets, a high-level class of labelled petri nets, was introduced in order to cope with the size problem of the low-level petri box calculus, especially when applied as semantical domain for parallel programming languages. general, unrestricted and parameterised refinement and recursion operators, allowing to represent the (possibly recursive and concurrent) procedure call mechanism, are introduced into the m-net calculus.
a note on dimensions of polynomial size circuits. in this paper, we use resource-bounded dimension theory to investigate polynomial size circuits. we show that for every i ≥0, p/poly has ith-order scaled p3-strong dimension 0. we also show that p/polyi.o. has p3-dimension 1/2 and p3-strong dimension 1. our results improve previous measure results of lutz [almost everywhere high nonuniform complexity, j. comput. syst. sci. 44(2) (1992) 220-258] and dimension results of hitchcock and vinodchandran [dimension, entropy rates, and compression, in: proc. 19th ieee conf. computational complexity, 2004, pp. 174-183, j. comput. syst. sci., to appear]. additionally, we establish a supergale dilation theorem, which extends the martingale dilation technique introduced implicitly by ambos-spies, terwijn, and zheng [resource bounded randomness and weakly complete problems, theoret. comput. sci. 172(1-2)(1997) 195-207] and made explicit by juedes and lutz [weak completeness in e and e2, theoret. comput. sci. 143(1) (1995) 149-158].
an efficient approach for the rank aggregation problem. this paper presents some computational properties of the rank-distance, a measure of similarity between partial rankings. we show how this distance generalizes the spearman footrule distance, preserving its good computational complexity: the rank-distance between two partial rankings can be computed in linear time, and the rank aggregation problem can be solved in polynomial time. further, we present a generalization of the rank-distance to strings, which permits to solve the median string problem in polynomial time. this appears rather surprising to us given the fact that for other non-trivial string distances, such as edit-distance, this problem is np-hard.
efficiency and equilibrium in the electronic mail game; the general case. in the email game (amer. econom. rev. 79 (1989) 385) noisy information channels may prevent risky-efficient coordination, even when the game is almost common knowledge. in this paper, we show that this is the case whenever message failure probabilities are not sufficiently different. quite intuitively, the extent of the difference is governed by the game payoffs, and in particular by the mixed nash equilibrium strategy of one of the two games to be played. this is because, conditionally to having observed one's type, a player's beliefs on the opponent's choices are governed by the reliability of communication channels.
eigenvariables, bracketing and the decidability of positive minimal predicate logic. we give a new proof of a theorem of mints that the positive fragment of minimal predicate logic is decidable. the idea of the proof is to replace the eigenvariable condition of sequent calculus by an appropriate scoping mechanism. the algorithm given by this proof seems to be more practical than that given by the original proof. a naive implementation is given at the end of the paper. another contribution is to show that this result extends to a large class of theories, including simple type theory (higher-order logic) and second-order propositional logic. we obtain this way a new proof of the decidability of the inhabitation problem for positive types in system f.
infinitary lambda calculus and discrimination of berarducci trees. we propose an extension of lambda calculus for which the berarducci trees equality coincides with observational equivalence, when we observe rootstable or rootactive behavior of terms. in one direction the proof is an adaptation of the classical böhm out technique. in the other direction the proof is based on confluence for strongly converging reductions in this extension.
a coding theory construction of new systematic authentication codes. there are several approaches to the construction of authentication codes without secrecy using error correcting codes. in this paper, we describe one approach and construct several classes of authentication codes using several types of error correcting codes. some of the authentication codes constructed here are asymptotically optimal, and some are optimal.
typical rounding problems. the linear discrepancy problem is to round a given [0, 1]-vector x to a binary vector y such that the rounding error with respect to a linear form is small, i.e., such that ||a(x - y)||∞ is small for some given matrix a. the combinatorial discrepancy problem is the special case of x=(1/2,...,1/2)t. a famous result of beck and spencer [math. programming 30 (1984) 88] as well as lovász et al. [european j. combin. 7 (1986) 151] shows that the linear discrepancy problem is not much harder than this special case: any linear discrepancy problem can be solved with at most twice the maximum rounding error among the discrepancy problems of the submatrices of a.in this paper, we strengthen this result for the common situation that the discrepancy of submatrices having n0 columns is bounded by cn0α for some c > 0, α ∈ [0, 1]. in this case, we improve the constant by which the general problem is harder than the discrepancy one from 2 down to 2(2/3)α. we also find that a random vector has expected linear discrepancy 2(1/2)αcnα only. hence in the typical situation that the discrepancy is decreasing for smaller matrices, the linear discrepancy problem is even less difficult compared to the discrepancy one than assured by previous results. we also obtain the bound lindisc(a,x) ≤ 2(2α/(21-α- 1))c||x||1α. our proofs use a reduction to pusher-chooser games.
interpolation in grothendieck institutions. it is well known that interpolation properties of logics underlying specification formalisms play an important rule in the study of structured specifications, they have also many other useful logical consequences.in this paper, we solve the interpolation problem for grothendieck institutions which have recently emerged as an important mathematical structure underlying heterogenous multilogic specification. our main result can be used in the applications in several different ways. it can be used to establish interpolation properties for multi-logic grothendieck institutions, but also to lift interpolation properties from unsorted logics to their many sorted variants. the importance of the latter resides in the fact that, unlike other structural properties of logics, many sorted interpolation is a non-trivial generalisation of unsorted interpolation.the concepts, results, and the applications discussed in this paper are illustrated with several examples from conventional logic and algebraic specification theory.
behavioural specification for hierarchical object composition. behavioural specification based on hidden (sorted) algebra constitutes one of the most promising recently developed formal specification and verification paradigms for system development.here we formally introduce novel concepts of behavioural object and equivalence between behavioural objects within the hidden algebra framework. we formally define several object composition operators on behavioural objects corresponding to the hierarchical object composition methodology introduced by cafeobj. we study their basic semantical properties and show that our most general form of behavioural object composition with synchronisation has final semantics and a composability property of behavioural equivalence supporting a high reusability of verifications. we also show the commutativity and the associativity of parallel compositions without synchronisation.
european tenure games. we study a variant of the tenure game introduced by spencer (theoret. comput. sci. 131 (1994) 415). in this version, faculty is not fired, but downgraded to the lowest rung instead.for the upper bound we give a potential function argument showing that the value υd of the game starting with d faculty on the first rung satisfies υd ≤ ⌊log2d + log2 log2d + 1.98⌋. we prove a nearly matching lower bound of ⌊log2d + log2 log2d⌋ using a strategy that can be interpreted as an antirandomization of spencer's original game. for d tending to infinity, these bounds improve to ⌊ log2d + log2 log2d + 1 + o(1)⌋ ≤ υd ⌊log2d + log2 log2d + 1.73 + o(1)⌋. in particular, the set of all d ∈ n such that the value of the game is precisely ⌊log2d + log2 log2d+ 1⌋ has lower density greater than 1/5.
logical foundations of cafeobj. this paper surveys the logical and mathematical foundations of cafeobj, which is a successor of the famous algebraic specification language obj but adds to it several new primitive paradigms such as behavioural concurrent specification and rewriting logic.we first give a concise overview of cafeobj. then we focus on the actual logical foundations of the language at two different levels: basic specification and structured specification, including also the definition of the cafeobj institution. we survey some novel or more classical theoretical concepts supporting the logical foundations of cafeobj, pointing out the main results but without giving proofs and without discussing all mathematical details. novel theoretical concepts include the coherent hidden algebra formalism and its combination with rewriting logic, and grothendieck (or fibred) institutions. however, for proofs and for some of the mathematical details not discussed here we give pointers to relevant publications.the logical foundations of cafeobj are structured by the concept of institution. moreover, the design of cafeobj emerged from its logical foundations, and institution concepts played a crucial rôle in structuring the language design.
improved bounds and schemes for the declustering problem. the declustering problem is to allocate given data on parallel working storage devices in such a manner that typical requests find their data evenly distributed on the devices. using deep results from discrepancy theory, we improve previous work of several authors concerning range queries to higher-dimensional data. we give a declustering scheme with an additive error of od (logd-1m) independent of the data size, where d is the dimension, m the number of storage devices and d - 1 does not exceed the smallest prime power in the canonical decomposition of m into prime powers. in particular, our schemes work for arbitrary-m in dimensions two and three. for general d, they work for all m≥d - 1 that are powers of two. concerning lower bounds, we show that a recent proof of a ωd (log(d-1)/2m) bound contains an error. we close the gap in the proof and thus establish the bound.
the stable marriage problem with restricted pairs. a stable matching is a complete matching of men and women such that no man and woman who are not partners both prefer each other to their actual partners under the matching. in an instance of the stable marriage problem, each of the n men and n women ranks the members of the opposite sex in order of preference. it is well known that at least one stable matching exists for every stable marriage problem instance. we consider extensions of the stable marriage problem obtained by forcing and by forbidding sets of pairs. we present a characterization for the existence of a solution for the stable marriage with forced and forbidden pairs problem. in addition, we describe a reduction of the stable marriage with forced and forbidden pairs problem to the stable marriage with forbidden pairs problem. finally, we also present algorithms for finding a stable matching, all stable pairs and all stable matchings for this extension. the complexities of the proposed algorithms are the same as the best known algorithms for the unrestricted version of the problem.
generating bicliques of a graph in lexicographic order. an independent set of a graph is a subset of pairwise non-adjacent vertices. a complete bipartite set b is a subset of vertices admitting a bipartition b = x ∪ y, such that both x and y are independent sets, and all vertices of x are adjacent to those of y. if both x, y ≠ 0, then b is called proper. a biclique is a maximal proper complete bipartite set of a graph. we present an algorithm that generates all bicliques of a graph in lexicographic order, with polynomial-time delay between the output of two successive bicliques. we also show that there is no polynomial-time delay algorithm for generating all bicliques in reverse lexicographic order, unless p = np. the methods are based on those by johnson, papadimitriou and yannakakis, in the solution of these two problems for independent sets, instead of bicliques.
bounds on the max and min bisection of random cubic and random 4-regular graphs. in this paper, we present a randomized algorithm to compute the bisection width of cubic and 4-regular graphs. the analysis of the proposed algorithms on random graphs provides asymptotic upper bounds for the bisection width of random cubic and random 4-regular graphs with n vertices, giving upper bounds of 0.174039n for random cubic, and of 0.333333n for random 4-regular. we also obtain asymptotic lower bounds for the size of the maximum bisection, for random cubic and random 4-regular graphs with n vertices, of 1.32697n and 1.66667n, respectively. the randomized algorithms are derived from initial greedy algorithm and their analysis is based on the differential equation method.
the multiplicative fragment of the yanov equational theory. we give a finite equational axiomatization for +-free identities of (regular) languages which contain the empty word. the axioms for the whole equational theory of such languages were given by yanov.
deletion along trajectories. we describe a new way to model deletion operations on formal languages, called deletion along trajectories. we examine its closure properties, which differ from those of shuffle on trajectories, previously introduced by mateescu et al. in particular, we define classes of nonregular sets of trajectories such that the associated deletion operation preserves regularity. our results give uniform proofs of closure properties of the regular languages for several deletion operations.we also show that deletion along trajectories serves as an inverse to shuffle on trajectories. this leads to results on the decidability of certain language equations, including those of the form ltx = r, where l,r are regular languages and x is unknown.
representing recursively enumerable languages by iterated deletion. a characterization of the recursively enumerable languages in terms of the iterated deletion operation is given. this solves two open problems posed by ito and silva on the closure properties and decidability of iterated deletion.
the chromatic and clique numbers of random scaled sector graphs. random scaled sector graphs were introduced as a generalization of random geometric graphs to model networks of sensors using optical communication. in the random scaled sector graph model vertices are placed uniformly at random into the [0, 1]2 unit square. each vertex i is assigned uniformly at random sector si, of central angle αi, in a circle of radius ri (with vertex i as the origin). an arc is present from vertex i to any vertex j, if j falls in si. in this work, we study the value of the chromatic number χ(gn), directed clique number ω(gn), and undirected clique number ω2 (gn) for random scaled sector graphs with n vertices, where each vertex spans a sector of α degrees with radius rn = √ln n/n. we prove that for values α < π, as n → ∞ w.h.p., χ(gn) and ω2 (gn) are θ(ln n/ln ln n), while ω(gn) is o(1), showing a clear difference with the random geometric graph model. for α > π w.h.p., χ(gn) and ω2 (gn) are θ (ln n), being the same for random scaled sector and random geometric graphs, while ω(gn) is θ(ln n/ln ln n).
decidability of trajectory-based equations. we consider the decidability of existence of solutions to language equations involving the operations of shuffle and deletion along trajectories. these operations generalize the operations of catenation, insertion, shuffle, quotient, sequential and scattered deletion, as well as many others. our results are constructive in the sense that if a solution exists, it can be effectively represented. we show both positive and negative decidability results. we also briefly consider systems of language equations.
counting h-colorings of partial k-trees. the problem of counting all h-colorings of a graph g with n vertices is considered. while the problem is, in general, #p-complete, we give linear time algorithms that solve the main variants of this problem when the input graph g is a k-tree or, in the case where g is directed, when the underlying graph of g is a k-tree. our algorithms remain polynomial even in the case where k=o(logn) or in the case where the size of h is o(n). our results are easy to implement and imply the existence of polynomial time algorithms for a series of problems on partial k-trees such as core checking and chromatic polynomial computation.
codes defined by multiple sets of trajectories. we investigate the use of shuffle on trajectories to model certain classes of languages arising in the theory of codes. in particular, for each finite set of sets of trajectories, which we call a hyperset of trajectories, we define a class of languages induced by that hyperset of trajectories. we investigate the properties of hypersets of trajectories and the associated classes of languages, including the problem of decidability of membership and the problem of equivalence of hypersets of trajectories.
finite semigroups, feedback, and the letichevsky criteria on non-empty words in finite automata. this paper relates classes of finite automata under various feedback products to some well-known pseudovarieties of finite semigroups via a study of their irreducible divisors (in the sense of krohn-rhodes). in particular, this serves to relate some classical results of krohn, rhodes, stiffler, eilenberg, letichevsky, gécseg, ésik, and horváth. we show that for a finite automaton satisfaction of (1) the letichevsky criterion for non-empty words, (2) the semi-letichevsky criterion for non-empty words, or (3) neither criterion, corresponds, respectively, to the following properties of the characteristic semigroup of the automaton: (1) non-constructability as a divisor of a cascade product of copies of the two-element monoid with zero u, (2) such constructability while having u but no other non-trivial irreducible semigroup as a divisor, or (3) having no non-trivial irreducible semigroup divisors at all. the latter two cases are exactly the cases in which the characteristic semigroup is r-trivial.this algebraic characterization supports the transfer of results about finite automata to results about finite semigroups (and vice versa), and yields insight into the lattice of pseudovarieties of finite semigroups--or, equivalently via the eilenberg correspondence, the lattice of +-varieties of regular languages--and the operators on these lattices that are naturally associated to various automata products with bounded feedback. in particular, all operators with non-trivial feedback are shown to be equivalent, and we characterize all pseudovarieties of finite semigroups closed under each type of feedback product either explicitly or by reducing the question to closure under the cascade product.
from local to global temporal logics over mazurkiewicz traces. we review some results on global and local temporal logic on mazurkiewicz traces. our main contribution is to show how to derive the expressive completeness of global temporal logic with respect to first-order logic [v. diekert, p. gastin, ltl is expressively complete for mazurkiewicz traces, j. comput. system sci. 64 (2002) 396-418] from the similar result on local temporal logic [v. diekert, p. gastin, pure future local temporal logics are expressively complete for mazurkiewicz traces, in: m. farach-colton (ed.), proc. latin'04, lecture notes in computer science, vol. 2976, springer, berlin, 2004, pp. 232-241, full version available as research report lsv-05-22, laboratoire spécification et vérification, ens cachan, france].
selecting evaluation functions in opponent-model search. opponent-model search is a game-tree search method that explicitly uses knowledge of the opponent. there is some risk involved in using opponent-model search. for adequate forecasting, two conditions should be imposed. both the prediction of the opponent's moves and the judgement of future positions should be of good quality. the two conditions heavily depend on the evaluation functions used.in the article we distinguish evaluation functions by type. three fundamentally different types are introduced. thorough analysis of a variety of characteristics leads to eight possible orderings. the role of the evaluation functions is studied by attempting to answer five research questions. moreover, actual computer game-playing programs investigate the research questions by a series of experiments in which opponent-model search is performed. the game of bao is our test bed, it was selected because of its relatively narrow game tree, which allowed for an appropriate search depth in the experiments. we restrict ourselves to five evaluation functions generated with the help of machine-learning techniques. a set of round-robin tournaments between these evaluation functions show that when the above conditions are met, opponent-model search can be applied successfully. answers to the research questions are given in the conclusions.
er modelling from first relational principles. entity-relationship (er) modelling as a popular technique for data modelling. despite its popularity and widespread use, it lacks a firm semantic foundation. we propose a translation of an er-model into relation algebra, suggesting that this kind of algebra does provide suitable mechanisms for establishing a formal semantics of er modelling. the work reported on here deals first with the techniques necessary for the translation, thus constructing a static view of an er-model in an abstract setting of what might be called logic without variables. we then undertake a detailed analysis of the insertion and deletion operations for an er-model represented in terms of the relation calculus.
optimal semi-online preemptive algorithms for machine covering on two uniform machines. in this paper, we consider the semi-online preemptive scheduling problem with decreasing job sizes on two uniform machines. our goal is to maximize the continuous period of time (starting from time zero) when both machines are busy, which is equivalent to maximizing the minimum machine completion time if idle time is not introduced before all the jobs are completed. we design optimal deterministic semi-online algorithms for every machine speed ratio s ∈ [1, ∞), and show that idle time is required during the assignment procedure of algorithms for any s > √6/2. the competitive ratios of the algorithms match the randomized lower bound for every 1 ≤ s ≤ 3. the problem of whether randomization still does not help for the discussed preemptive scheduling problem remains open.
ant colony optimization theory: a survey. research on a new metaheuristic for optimization is often initially focused on proof-of-concept applications. it is only after experimental work has shown the practical interest of the method that researchers try to deepen their understanding of the method's functioning not only through more and more sophisticated experiments but also by means of an effort to build a theory. tackling questions such as "how and why the method works" is important, because finding an answer may help in improving its applicability. ant colony optimization, which was introduced in the early 1990s as a novel technique for solving hard combinatorial optimization problems, finds itself currently at this point of its life cycle. with this article we provide a survey on theoretical results on ant colony optimization. first, we review some convergence results. then we discuss relations between ant colony optimization algorithms and other approximate methods for optimization. finally, we focus on some research efforts directed at gaining a deeper understanding of the behavior of ant colony optimization algorithms. throughout the paper we identify some open questions with a certain interest of being solved in the near future.
the impact of information on broadcasting time in linear radio networks. we consider the problem of distributed deterministic broadcasting in radio networks whose nodes are located on a line. nodes send messages in synchronous time-slots. each node υ has a given transmission range. all nodes located within this range can receive messages from υ. however, a node situated in the range of two or more nodes that send messages simultaneously, cannot receive these messages and hears only noise. each node knows only its own position and range, as well as the maximum of all ranges. broadcasting is adaptive: nodes can decide on the action to take on the basis of previously received messages, silence or noise. we prove lower bounds on broadcasting time in this model and construct broadcasting protocols whose performance nearly matches these bounds for the simplest case when nodes are situated on a line. we also show that if nodes do not even know their own range, every broadcasting protocol must be hopelessly slow. while distributed randomized broadcasting algorithms, and, on the other hand, deterministic off-line broadcasting algorithms assuming full knowledge of the radio network, have been extensively studied in the literature, ours are the first results concerning broadcasting algorithms that are distributed and deterministic at the same time. we show that in this case, information available to nodes influences the efficiency of broadcasting in a significant way.
normal forms for binary relations. we consider the representable equational theory of binary relations, in a language expressing composition, converse, and lattice operations. by working directly with a presentation of relation expressions as graphs we are able to define a notion of reduction which is confluent and strongly normalizing and induces a notion of computable normal form for terms. this notion of reduction thus leads to a computational interpretation of the representable theory.
an efficient algorithm for computing bisimulation equivalence. we propose an efficient algorithmic solution to the problem of determining a bisimulation relation on a finite structure working both on the explicit and on the implicit (symbolic) representation. as far as the explicit case is concerned, starting from a set-theoretic point of view we propose an algorithm that optimizes the solution to the relational coarsest partition problem given by paige and tarjan (siam j. comput. 16(6) (1987) 973); its use in model-checking packages is also discussed and tested. for well-structured graphs our algorithm reaches a linear worst-case behaviour. the proposed algorithm is then re-elaborated to produce a symbolic version.
neural computation, social networks, and topological spectra. this paper emphasizes some intriguing links between neural computation on graphical domains and social networks, like those used in nowadays search engines to score the page authority. it is pointed out that the introduction of web domains creates a unified mathematical framework for these computational schemes. it is shown that one of the major limitations of currently used connectionist models, namely their scarce ability to capture the topological features of patterns, can be effectively faced by computing the node rank according to social-based computation, like google's pagerank. the main contribution of the paper is the introduction of a novel graph spectral notion, which can be naturally used for the graph isomorphism problem. in particular, a class of graphs is introduced for which the problem is proven to be polynomial. it is also pointed out that the derived spectral representations can be nicely combined with learning, thus opening the doors to many applications typically faced within the framework of neural computation.
uniformly hard languages. ladner (j. assoc. comput. mach. 22 (1975) 155) showed that there are no minimal recursive sets under polynomial-time reductions. given any recursive set a, ladner constructs a set b such that b strictly reduces to a but b does not lie in p. the set b does have very long sequences of input lengths of easily computable instances.we examine whether ladner's results hold if we restrict ourselves to "uniformly hard languages" which have no long sequences of easily computable instances. under a hard to disprove assumption, we show that there exists a minimal recursive uniformly hard set under honest many-one polynomial-time reductions.
a representation theorem for boolean contact algebras. we prove a representation theorem for boolean contact algebras which implies that the axioms for the region connection calculus (rcc) [d.a. randell, a.g. cohn, z. cui, computing transitivity tables: a challenge for automated theorem provers, in: d. kapur (ed.), proceedings of the 11th international conference on automated deduction (cade-11), lecture notes in artificial intelligence, vol. 607, springer, saratoga, springs, ny, 1992, pp. 786-790] are complete for the class of subalgebras of the algebras of regular closed sets of weakly regular connected t1 spaces.
on kurtz randomness. kurtz randomness is a notion of algorithmic randomness for real numbers. in particular a real x is called kurtz random (or weakly random) iff it is contained in every computably enumerable set u of (lebesgue) measure 1. we prove a number of characterizations of this notion, relating it to other notions of randomness such as the well-known notions of computable randomness, martin-löf randomness and schnorr randomness. for the first time we give machine characterizations of kurtz randomness. whereas the turing degree of every martin-löf random c.e. real is the complete degree, and the degrees of schnorr random c.e. reals are all high, we show that kurtz random c.e. reals occur in every non-zero c.e. degree. additionally, we show that the sets that are low for kurtz randomness are all hyperimmune and include those that are low for schnorr randomness, characterized previously by terwijn and zambella.@ 2004 elsevier b.v. all rights reserved.
structured theories and institutions. category theory provides an excellent foundation for studying structured specifications and their composition. for example, theories can be structured together in a diagram, and their composition can be obtained as a colimit. there is, however, a growing awareness, both in theory and in practice, that structured theories should not be viewed just as the "scaffolding" used to build unstructured theories: they should become first-class citizens in the specification process. given a logic formalized as an institution i, we therefore ask whether there is a good definition of the category of structured i-theories, and whether they can be naturally regarded as the ordinary theories of an appropriate institution j(i) generalizing the original institution i. we answer both questions in the affirmative, and study good properties of the institution i inherited by j(i). we show that, under natural conditions, a number of important properties are indeed inherited, including cocompleteness of the category of theories, liberality, and extension of the basic framework by freeness constraints. the results presented here have been used as a foundation for the module algebra of the maude language, and seem promising as a semantic basis for a generic module algebra that could be both specified and executed within the logical framework of rewriting logic.
presentations of computably enumerable reals. we study the relationship between a computably enumerable real and its presentations: ways of approximating the real by enumerating a prefix-free set of binary strings.
de la logique aux pavages. l'objectif de cet article de synth&eacute;se est de pr&eacute;senter ensemble un certain nombre de r&eacute;sultats liant les pavages &aacute; la logique suivant divers points de vue: certains structurels, d'autres plus algorithmiques en termes d'ind&eacute;cidabilit&eacute;, de complexit&eacute;s.
number-conserving cellular automata i: decidability. we prove that definitions of number-conserving cellular automata found in literature are equivalent. a necessary and sufficient condition for cellular automata to be number-conserving is proved. using this condition, we give a quasi-linear time algorithm to decide number-conservation.
criteria to disprove context freeness of collage languages. collage grammars are context-free devices which generate picture languages consisting of collages--sets of parts, where a part is a set of points in a given space. in order to show that certain collage languages cannot be generated, the well-known pumping technique turns out to be rather useless. to circumvent this difficulty, other necessary criteria for context-freeness are established in this paper. roughly speaking, these criteria reveal that (1) the collages in a context-free collage language can be deflated stepwise in such a manner that the difference between subsequent collages in the resulting chain is small and (2) the volume of parts can grow or shrink only exponentially.
on the complexity of recognizing the hilbert basis of a linear diophantine system. the problem of computing the hilbert basis of a homogeneous linear diophantine system over nonnegative integers is often considered in automated deduction and integer programming. in automated deduction, the hilbert basis of a corresponding system serves to compute the minimal complete set of associative-commutative unifiers, whereas in integer programming the hilbert bases are tightly connected to integer polyhedra and to the notion of total dual integrality. in this paper, we sharpen the previously known result that the problem, asking whether a given solution belongs to the hilbert basis of a given system, is conp-complete. we show that the problem has a pseudopolynomial algorithm if the number of equations in the system is fixed, but it is conp-complete in the strong sense if the given system is unbounded. this result is important in the scope of automated deduction, where the input is given in unary and therefore the previously known conp-completeness result was unusable. moreover, we show that, from the complexity standpoint, it is not important to know the underlying homogeneous linear diophantine system when we ask whether a given set of vectors constitutes a hilbert basis.
the variance of the height of binary search trees. by using analytic tools it is shown that the variance e(hnehn)2 of the height hn of binary search trees of size n is bounded.
subtractive reductions and complete problems for counting complexity classes. we introduce and investigate a new type of reductions between counting problems, which we call subtractive reductions. we show that the main counting complexity classes #p, #np, as well as all higher counting complexity classes # ċ πkp, k ≥ 2, are closed under subtractive reductions. we then pursue problems that are complete for these classes via subtractive reductions. we focus on the class #np (which is the same as the class # ċ conp) and show that it contains natural complete problems via subtractive reductions, such as the problem of counting the minimal models of a boolean formula in conjunctive normal form and the problem of counting the cardinality of the set of minimal solutions of a homogeneous system of linear diophantine inequalities.
on robson's convergence and boundedness conjectures concerning the height of binary search trees. let cn denote the number of nodes in a random binary search tree (of n nodes) at the maximal level. in this paper we present a direct proof of robson's boundedness conjecture saying that the expected values e cn remain bounded as n → ∞. we also prove that e cn is asymptotically (multiplicatively) periodic which shows that robson's convergence conjecture (that is, e cn is convergent) is only true if the limiting periodic function c˜(x) is constant. interestingly, it can be shown that c˜(x) is almost constant in the sense that possible oscillations are very small. however, it seems to be a difficult problem to decide whether c˜(x) is really constant or not.we present similar properties for the variance of the height var hn, too.
do stronger definitions of randomness exist? in this paper, we investigate refined definition of random sequences. classical definitions (martin-löf tests of randomness, uncompressibility, unpredictability, or stochasticness) make use of the notion of algorithm. we present alternative definitions based on set theory and explain why they depend on the model of zfc that is considered. we also present a possible generalization of the definition when small infinite regularities are allowed.
comparison between the complexity of a function and the complexity of its graph. this paper investigates in terms of kolmogorov complexity the differences between the information necessary to compute a recursive function and the information contained in its graph. our first result is that the complexity of the initial parts of the graph of a recursive function, although bounded, has almost never a limit. the second result is that the complexity of these initial parts approximate the complexity of the function itself in most cases (and in the average) but not always.
descriptive complexity of computable sequences. our goal is to study the complexity of infinite binary recursive sequences. we introduce several measures of the quantity of information they contain. some measures are based on size of programs that generate the sequence, the others are based on the kolmogorov complexity of its finite prefixes. the relations between these complexity measures are established. the most surprising among them are obtained using a specific two-players game2.
a generic causal model for place latency. for a prototypical class of time-extended petri nets it is shown that the extension does not increase their expressive power. the nets in this class have token latencies attributed to places. place latency nets are formally defined together with their firing semantics. for any place latency system, an explicit construction of an elementary net system is given as an implementation, which is proven to be behaviourally equivalent. the adequacy problem of deciding which equivalence notion to apply is moderated by the fact that the implementation satisfies the b-condition, under which all better known equivalence notions coincide.
on the analysis of the (1+1) evolutionary algorithm. many experimental results are reported on all types of evolutionary algorithms but only few results have been proved. a step towards a theory on evolutionary algorithms, in particular, the so-called (1+1) evolutionary algorithm, is performed. linear functions are proved to be optimized in expected time o(nlnn) but only mutation rates of size (1/n) can ensure this behavior. for some polynomial of degree 2 the optimization needs exponential time. the same is proved for a unimodal function. both results were not expected by several other authors. finally, a hierarchy result is proved. moreover, methods are presented to analyze the behavior of the (1+1) evolutionary algorithm.
optimization with randomized search heuristics - the (a)nfl theorem, realistic scenarios, and difficult functions. the no free lunch (nfl) theorem due to wolpert and macready (ieee trans. evol. comput. 1(1) (1997) 67) has led to controversial discussions on the usefulness of randomized search heuristics, in particular, evolutionary algorithms. here a short and simple proof of the nfl theorem is given to show its elementary character. moreover, the proof method leads to a generalization of the nfl theorem. afterwards, realistic complexity theoretical-based scenarios for black box optimization are presented and it is argued why nfl theorems are not possible in such situations. however, an almost no free lunch (anfl) theorem shows that for each function which can be optimized efficiently by a search heuristic there can be constructed many related functions where the same heuristic is bad. as a consequence, search heuristics use some idea how to look for good points and can be successful only for functions "giving the right hints". the consequences of these theoretical considerations for some well-known classes of functions are discussed.
skew and infinitary formal power series. we investigate finite-state systems with weights. departing from the classical theory, in this paper the weight of an action does not only depend on the state of the system, but also on the time when it is executed; this reflects the usual human evaluation practices in which later events are considered less urgent and carry less weight than close events. we first characterize the terminating behaviors of such systems in terms of rational formal power series. this generalizes a classical result of schützenberger. secondly, we deal with nonterminating behaviors and their weights. this includes an extension of the büchi-acceptance condition from finite automata to weighted automata and provides a characterization of these nonterminating behaviors in terms of ω-rational formal power series. this generalizes a classical theorem of büchi.
weighted tree automata and weighted logics. we define a weighted monadic second order logic for trees where the weights are taken from a commutative semiring. we prove that a restricted version of this logic characterizes the class of formal tree series which are accepted by weighted bottom-up finite state tree automata. the restriction on the logic can be dropped if additionally the semiring is locally finite. this generalizes corresponding classical results of thatcher, wright, and doner for tree languages and it extends recent results of droste and gastin [weighted automata and weighted logics, in: automata, languages and programrning--32nd international colloquium, icalp 2005, lisbon, portugal, 2005, proceedings, lecture notes in computer science, vol. 3580, springer, berlin, 2005, pp. 513-525, full version in theoretical computer science, to appear.] from formal power series on words to formal tree series.
object grammars and bijections. a new systematic approach for the specification of bijections between sets of combinatorial objects is presented. it is based on the notion of object grammars. object grammars give recursive descriptions of objects and generalize context-free grammars. the study of a particular substitution in these object grammars confirms once more the key role of dyck words in the domain of enumerative and bijective combinatorics.
linear-time computation of local periods. we present a linear-time algorithm for computing all local periods of a given word. this subsumes (but is substantially more powerful than) the computation of the (global) period of the word and on the other hand, the computation of a critical factorization, implied by the critical factorization theorem.
upper bounds on the satisfiability threshold. we present a survey of upper bounds which has been established up to now on the satisfiability threshold of random k-sat formulae. the ideas which led to these bounds and the techniques used to obtain them, are explained. a companion paper in this volume present a survey of the lower bounds.
on the support of graph lie algebras. we deal with the support of graph lie algebras and we characterize the set of independence alphabets for which the noncommutative result can naturally be extended. we also provide an algorithm which decides if an independence alphabet fulfills the preceding condition.
from object grammars to eco systems. in this paper we make a comparison between two methods for the enumeration of combinatorial objects, namely the eco method and object grammars, both based on a recursive description for the examined class of objects. in particular, we study the problem of passing from an object grammar to an "equivalent" eco system. first, we solve this problem for any unidimensional, unambiguous, and complete object grammar, with any linear parameter. then we treat the more complex cases of q-linear parameters, and of multidimensional object grammars, giving some explanatory examples. in particular, we determine a new eco system for the class of directed convex polyominoes.
dominance constraints with boolean connectives: a model-eliminative treatment. dominance constraints are a language of tree descriptions. tree descriptions are widely used in computational linguistics for talking and reasoning about trees. while previous research has focused on the conjunctive fragment, we now extend the account to all boolean connectives and propose a new formalism that combines dominance constraints with a feature tree logic.although the satisfiability problem in the conjunctive fragment is known to be np-complete, we have previously demonstrated that it can be addressed very effectively by constraint propagation: we developed an encoding that transforms a dominance constraint into a constraint satisfaction problem on finite sets solvable by constraint programming. we present a generalization of this encoding for our more expressive formalism, and prove soundness and completeness. our main contribution is a treatment of disjunction suitable for constraint propagation.
could any graph be turned into a small-world? in addition to statistical graph properties (diameter, degree, clustering, etc.), kleinberg [the small-world phenomenon: an algorithmic perspective, in: proc. 32nd acm symp. on theory of computing (stoc), 2000, pp. 163-170] showed that a small-world can also be seen as a graph in which the routing task can be efficiently and easily done in spite of a lack of global knowledge. more precisely, in a lattice network augmented by extra random edges (but not chosen uniformly), a short path of polylogarithmic expected length can be found using a greedy algorithm with a local knowledge of the nodes. we call such a graph a navigable small-world since short paths exist and can be followed with partial knowledge of the network. in this paper, we show that a wide class of graphs can be augmented into navigable small-worlds.
a geometric approach to leveraging weak learners. adaboost is a popular and effective leveraging procedure for improving the hypotheses generated by weak learning algorithms. adaboost and many other leveraging algorithms can be viewed as performing a constrained gradient descent over a potential function. at each iteration the distribution over the sample given to the weak learner is proportional to the direction of steepest descent. we introduce a new leveraging algorithm based on a natural potential function. for this potential function, the direction of steepest descent can have negative components. therefore, we provide two techniques for obtaining suitable distributions from these directions of steepest descent. the resulting algorithms have bounds that are incomparable to adaboost's. the analysis suggests that our algorithm is likely to perform better than adaboost on noisy data and with weak learners returning low confidence hypotheses. modest experiments confirm that our algorithm can perform better than adaboost in these situations.
open and closed scopes for constrained genericity. constrained genericity is an extension of parametric polymorphism, that allows type parameters in polymorphic procedures to be constrained to have certain operations defined over them. it is realized in the ada and haskell programming languages, as exemplified by type classes in haskell. type classes only allow a single global scope for instances of type classes. this article introduces a type system and a semantics that allows both dynamic and static scoping of such operations to be mixed in a program. applications include overcoming scoping problems with constrained genericity, enabling program optimizations, and programming with dynamic data structures. type classes with "open" scope obey the usual semantics for haskell type classes, based on call-site "type dictionaries". type classes with "closed" scope use run-time type descriptions to dispatch to instances. the type system to support this combines operator kinds, refinement kinds and singleton kinds. the system is extended to allow overlapping specialized instance types, in order to support specialized representations for data structures (for example, arrays of integers, arrays of floats and arrays of boxed values). this extension requires the combination of both type dictionaries and run-time type information for type class dispatching.
a combinatorial error bound for t-point-based sampling. the method of two-point-based sampling using orthogonal arrays (inform. process. lett. 60 (1996) 91) is extended to consider t-wise independent sampling using orthogonal arrays of higher strength t. using combinatorial considerations, an error bound is calculated which agrees with the previously known result when t = 2, and has the advantage of exponentially decreasing in t. the result is shown to be strictly sharper than that arising from the generalized chebyshev inequality. finally, the behavior of the family of error bounds we obtain for increasing values of t is analyzed.
rna secondary structure comparison: exact analysis of the zhang-shasha tree edit algorithm. we are interested in rna secondary structure comparison, using an approach which consists to represent these structures by labeled ordered trees. following the problem considered, this tree representation can be rough (considering only the structural patterns), or refined until an exact coding of the structure is obtained. after some preliminary definitions and the description of the zhang-shasha (siam j. comput. 18 (6) (1989) 1245) tree edit algorithm, which is on the one hand the reference when dealing with ordered labeled trees comparison, and on the other hand the starting point of our work, this article will present an exact analysis of its complexity. the purpose of this work is also to lead us to a better comprehension of the parameters of this algorithm, in order to be able to modify it more easily without changing its time complexity to take into account biological constraints that occur when comparing rna secondary structures.
a halfliar's game. in ulam's game paul tries to find one of n possibilities with q yes-no questions, while responder carole is allowed to lie a fixed number k of times. we consider an asymmetric variant in which carole must say yes when that is the correct answer (whence the halflie). we show that this variation allows paul to distinguish between roughly 2k as many possibilities as in ulam's game.
mining for empty spaces in large data sets. many data mining approaches focus on the discovery of similar (and frequent) data values in large data sets. we present an alternative, but complementary approach in which we search for empty regions in the data. we consider the problem of finding all maximal empty rectangles in large, two-dimensional data sets. we introduce a novel, scalable algorithm for finding all such rectangles. the algorithm achieves this with a single scan over a sorted data set and requires only a small bounded amount of memory. we extend the algorithm to find all maximal empty hyper-rectangles in a multi-dimensional space. we consider the complexity of this search problem and present new bounds on the number of maximal empty hyper-rectangles. we briefly overview experimental results obtained by applying our algorithm to real and synthetic data sets and describe one application of empty-space knowledge to query optimization.
polynomial time algorithms for three-label point labeling. in this paper, we present an o(n2 log n) time solution for the following multi-label map labeling problem: given a set s of n distinct sites in the plane, place at each site a triple of uniform squares of maximum possible size such that all the squares are axis-parallel and a site is on the boundaries of its three labeling squares. we also study the problem under the discrete model, i.e., a site must be at the corners of its three label squares. we obtain an optimal θ(n log n) time algorithm for the latter problem.
on representations of positive integers in the fibonacci base. we exhibit and study various regularity properties of the sequence (r(n))n ≥ 1 which counts the number of different representations of the positive integer n in the fibonacci numeration system. the regularity properties in question are observed by representing the sequence as a two-dimensional array consisting of an infinite number of rows l1, l2, l3 .... where each lk contains fk-1 (the k - 1st fibonacci number) entries of the sequence (r(n)). we give a purely combinatorial recursive algorithm for generating each row lk from previous rows lj with j < k. we then show that for each positive integer m, and for all k ≥ 2m, the number of occurrences of m in lk is a constant rk(m) depending only on m. the function rk(m) has many interesting number theoretic properties and is intimately connected to the euler φ-function.
approximation schemes for scheduling and covering on unrelated machines. we examine the problem of assigning n independent jobs to m unrelated parallel machines, so that each job is processed without interruption on one of the machines, and at any time, every machine processes at most one job. we focus on the case where m is a fixed constant, and present a new rounding approach that yields approximation schemes for multi-objective minimum makespan scheduling with a fixed number of linear cost constraints. the same approach gives approximation schemes for covering problems like maximizing the minimum load on any machine, and for assigning specific or equal loads to the machines.
exponentiation using canonical recoding. the canonical bit recoding technique can be used to reduce the average number of multiplications required to compute $x^e$ provided that $x^{-1}$ is supplied along with $x$. we model the generation of the digits of the canonical recoding $d$ of an $n$-bit long exponent $e$ as a markov chain, and show that binary, quaternary, and octal methods applied to $d$ require $\frac{4}{3}\,n$, $\frac{4}{3}\,n$, and $ \frac{23}{18}\,n $ multiplications, compared to $\frac{3}{2} \, n$, $\frac{11}{8} \, n$, and $\frac{31}{24}n$ required by these methods applied to $e$. we show that in general the canonically recoded $m$-ary method for constant $m$ requires fewer multiplications than the standard $m$-ary method. however, when $m$ is picked optimally for each method for a given $n$, then the average number of multiplications required by the standard method is fewer than those required by the recoded version.
formal systems for gene assembly in ciliates. dna processing in ciliates, a very ancient group of organisms, is among the most sophisticated dna processing in living organisms. it has a quite clear computational structure and even uses explicitly the linked list data structure! particularly interesting from the computational point of view is the process of gene assembly from its micronuclear to its macronuclear form. we investigate here the string rewriting and the graph rewriting models of this process, involving three molecular operations, which together form a universal set of operations in the sense that they can assembly any macronuclear gene from its micronuclear form. in particular we prove that although the graph rewriting system is more "abstract" than the string rewriting system, no "essential information" is lost, in the sense that one can translate assembly strategies from one system into the other.
on the sequential access theorem and deque conjecture for splay trees. we give a new, simple proof for the sequential access theorem for splay trees. for an n-node splay tree, our bound on the number of rotations is 4.5n, with a smaller constant than the bound of 10.8n concluded by tarjan. we extend our proof to prove the deque conjecture for output-restricted deques. our proofs provide additional insights into the workings of splay trees.
gene assembly through cyclic graph decomposition. we present in this paper a graph theoretical model of gene assembly, where (segments of) genes are distributed over a set of circular molecules. this model is motivated by the process of gene assembly in ciliates, but it is more general. in this model a set of circular dna molecules is represented by a bicoloured and labelled graph consisting of cyclic graphs, and the recombination takes place in two stages: first, by folding *p with respect to a set p of pairs of vertices of the graph (representing pointers in the micronuclear genes of the ciliate), and secondly, by unfolding the so obtained graph to p with respect to vertices of higher valency. the final graph p is again a set of bicoloured cyclic graphs, where the genes are present as maximal monochromatic paths. thus, the process of gene assembly corresponds to the dynamic process of changing cyclic graph decompositions. we show that the operation is well behaved in many respects, and that there is a sequence of pointer sets p1,...,pm consisting of one or two pairs such that p=(((p1)p2)pm) and each intermediate step i=(((p1)p2)pi) is intracyclic, that is, the segments of a gene that lie in the same connected component of i, will lie in the same connected component of the successor graph i+1.
the bounded eight-vertex model. the bounded version of the eight-vertex model of statistical mechanics is investigated. we study square, diamond and general finite domains on the square lattice and give exact characterizations to legal boundary conditions and number of fill-ins. the sets of legal configurations with a given boundary turn out always to have the graph topology of a hypercube with a particularly simple edge action. this enables a simple probabilistic description of the configurations as well as an efficient configuration generation using a cellular automaton. finally, by invoking height functions we study restricted edge action which leads to ice-model as well as to lesser know vertex models, some subsets of the eight-vertex model, some not.
two undecidability results for chain code picture languages. it is undecidable whether or not two 1-retreat-bounded regular languages describe exactly the same set of pictures or they describe a picture in common.
sparse topologies with small spectrum size. one of the fundamental properties of a graph is the number of distinct eigenvalues of its adjacency or laplace matrix. determining this number is of theoretical interest as well as of practical impact. sparse graphs with small spectra exhibit excellent structural properties and can act as interconnection topologies. in this paper, for any n we present graphs, for which the product of their vertex degree and the number of different eigenvalues is small. it is known that load balancing can be performed on such graphs in a small number of steps.
on groups whose word problem is solved by a~counter automaton. we prove that a group g has a word problem that is accepted by a deterministic counter automaton with a weak inverse property if and only if g is virtually abelian. we extend this result to larger classes of groups by considering a generalization of finite state automata, counter automata and pushdown automata. natural corollaries of our general result include a restricted version of herbst's classification of groups for which the word problem is a one counter language and a new classification of automata that accept context-free word problems.
forbidding-enforcing systems. this paper presents a model of molecular computing that is based on two kinds of "boundary conditions": forbidding and enforcing. forbidding conditions require that a contradictory (or conflicting) group of components (molecules) may not be present in a (molecular) system, as otherwise the system will "die". an enforcing condition requires that if a certain group of components (molecules) is present in a system, then eventually other components will be present in the system -- hence such an enforcing condition models a molecular reaction. thus the evolution of a system is determined by the enforcing conditions, but it is constraint by the forbidding conditions. such forbidding-enforcing systems (fe systems) are investigated in this paper in the framework of strings--i.e., molecules are represented by strings. each fe system defines a family of languages (rather than just one language, which is standard in formal language theory)--each language in this family presents a set of molecules that satisfy both forbidding and enforcing constraints. in this paper we investigate basic computational properties of fe systems operating on strings.
scale-free aggregation in sensor networks. sensor networks are distributed data collection systems, frequently used for monitoring environments in which "nearby" data have a high degree of correlation. this induces opportunities for data aggregation, that are crucial given the severe energy constraints of the sensors. thus, it is very desirable to take advantage of data correlations in order to avoid transmitting redundancy. in our model, we formalize a notion of correlation, that can vary according to a parameter k. then we relate the expected collision time of "nearby" walks on the grid to the optimum cost of scale-free aggregation.we also propose a very simple randomized algorithm for routing information on a grid of sensors that satisfies the appropriate collision time condition. thus, we prove that this simple scheme is a constant factor approximation (in expectation) to the optimum aggregation tree simultaneously for all correlation parameters k. the key contribution in our randomized analysis is to bound the average expected collision time of non-homogeneous random walks on the grid, i.e. the next hop probability depends on the current position.
towards optimal lower bounds for clique and chromatic number. it was previously known that neither max clique nor min chromatic number can be approximated in polynomial time within n1-ε, for any constant ε > 0, unless np = zpp. in this paper, we extend the reductions used to prove these results and combine the extended reductions with a recent result of samorodnitsky and trevisan to show that unless np ⊆ zptime(2o(log n(log log n)3/2)), neither max clique nor min chromatic number can be approximated in polynomial time within n1-ε(n) where ε ∈ o((log log n)-1/2). since there exists polynomial time algorithms approximating both problems within n1-ε(n) where ε(n) ∈ ω(log log n/log n), our result shows that the best possible ratio we can hope for is of the form n1-o(1), for some--yet unknown--value of o(1) between o((log log n)-1/2) and ω(log log n/log n).
inapproximability results for equations over finite groups. an equation over a finite group g is an expression of form w1w2...wk = 1g, where each wi is a variable, an inverted variable, or a constant from g; such an equation is satisfiable if there is a setting of the variables to values in g so that the equality is realized. we study the problem of simultaneously satisfying a family of equations over a finite group g and show that it is np-hard to approximate the number of simultaneously satisfiable equations to within |g|-ε for any ε > 0. this generalizes results of håstad (j. acm 48 (4) (2001) 798), who established similar bounds under the added condition that the group g is abelian.
complexity of learning in artificial neural networks. some basic issues in the statistical mechanics of learning from examples are reviewed. the approach of statistical physics is contrasted with the analysis of learning within the framework of mathematical statistics and the question of the algorithmic complexity of explicit learning prescriptions is addressed. even in very simple learning scenarios, the typical properties of which can be analyzed in great quantitative detail by methods from statistical mechanics, the determination of a suitable hypothesis approximating the target rule may be an np-complete problem. some special learning setups are suggested as model systems for the comparison between the approaches of statistical mechanics and computer science to the theory of computationally hard problems.
combinatory differential fields. combinatory differential fields arise if differential fields are augmented by operations which allow functions that are programmable in the usual recursive sense to be denoted. the present paper defines this concept. it is shown that every differential field whose field of constants is ordered can be extended to a combinatory field. we generalize the basic notions of the liouville-ritt-risch theory of closed-form solvability to combinatory field extensions and present some explorative examples of problems and solutions. &mdash;author's abstract
applications of graphical condensation for enumerating matchings and tilings. a technique called graphical condensation is used to prove various combinatorial identities among numbers of (perfect) matchings of planar bipartite graphs and tilings of regions. graphical condensation involves superimposing matchings of a graph onto matchings of a smaller subgraph, and then re-partitioning the united matching (actually a multigraph) into matchings of two other subgraphs, in one of two possible ways. this technique can be used to enumerate perfect matchings of a wide variety of planar bipartite graphs. applications include domino tilings of aztec diamonds and rectangles, diabolo tilings of fortresses, plane partitions, and transpose complement plane partitions.
completing comma-free codes. we prove that for every regular comma-free code there exists a maximal comma-free code containing it which is still regular and, moreover, we can effectively locate such a completion. in particular, we can decide whether a given regular comma-free code is maximal.
the differential lambda-calculus. we present an extension of the lambda-calculus with differential constructions. we state and prove some basic results (confluence, strong normalization in the typed case), and also a theorem relating the usual taylor series of analysis to the linear head reduction of lambda-calculus.
differential interaction nets. we introduce interaction nets for a fragment of the differential lambda-calculus and exhibit in this framework a new symmetry between the of course and the why not modalities of linear logic, which is completely similar to the symmetry between the tensor and par connectives of linear logic. we use algebraic intuitions for introducing these nets and their reduction rules, and then we develop two correctness criteria (weak typability and acyclicity) and show that they guarantee strong normalization. finally, we outline the correspondence between this interaction nets formalism and the resource lambda-calculus.
on a conjecture on bidimensional words. we prove that, given a double sequence w over the alphabet a (i.e. a mapping from z2 to a), if there exists a pair (n0, m0) ∈ z2 such that pw(n0, m0) < 1/100n0m0, then w has a periodicity vector, where pw is the complexity function in rectangles of w.
a multidimensional critical factorization theorem. the critical factorization theorem is one of the principal results in combinatorics on words. it relates local periodicities of a word to its global periodicity. in this paper we give a multidimensional extension of it. more precisely, we give a new proof of the critical factorization theorem, but in a weak form, where the weakness is due to the fact that we loose the tightness of the local repetition order. in exchange, we gain the possibility of extending our proof to the multidimensional case. indeed, this new proof makes use of the theorem of fine and wilf, that has several classical generalizations to the multidimensional case.
more on weighted servers or fifo is better than lru. we consider a generalized two-server problem on the uniform space in which servers have different costs. previous work focused on the case where the ratio between these costs was very large. we give results for varying ratios. for ratios below 2.2, we present a best possible algorithm which is trackless. we present a general lower bound for trackless algorithms depending on the cost ratio, proving that our algorithm is the best possible trackless algorithm up to a constant factor for any cost ratio. the results are extended for the case where we have two sets of servers with different costs.
the chord version for sonet adms minimization. we consider a problem which arises in optical routing. wdm/sonet rings are a network architecture used by telecommunications carriers for traffic streams. the dominant cost factor in such networks is the total number of add-drop multiplexers (adms) used. a list of traffic streams to be routed between pairs of nodes is given. in this paper we consider the problem where we need to assign a route and a wavelength to each traffic stream, minimizing the total number of used sonet adms. this is called the chord version of the sonet adms minimization problem, to denote the fact that the routing is not given a priori. the best previously known approximation algorithms for this problem have the performance guarantee of 3/2. we present an improved algorithm with performance guarantee of exactly 10/7 ≈ 1.42857. moreover, we study some natural heuristics for this problem, and give tight analysis of their approximation ratios.
the conference call search problem in wireless networks. cellular telephony systems, where locations of mobile users are unknown at some times, are becoming more common. in such systems, mobile users are roaming in a zone and a user reports its location only if it leaves the zone entirely. the conference call search (ccs) problem deals with tracking a set of mobile users in order to establish a call. to find a single roaming user, the system may need to search each cell where the user may be located. the goal is to identify the location of all users, within bounded time, satisfying some additional constraints on the search scheme.we consider cellular systems with n cells and m mobile users (cellular phones). the uncertain location of users is given by m probability distribution vectors. whenever the system needs to find the users, it conducts a search operation lasting at most d rounds. a request for a single search step specifies a user and a cell. in this search step, the cell is asked whether the given user is located there. in each round the system may perform an arbitrary number of such requests. an integer number b ≥ 1 bounds the number of distinct requests per cell in every round. the bound d results from quality of service considerations, whereas the bound b results from the wireless bandwidth allocated for signaling being scarce.every search step consumes expensive wireless links, which motivates search techniques minimizing the expected number of requests thus reducing the total search costs.we distinguish between oblivious, semi-adaptive and adaptive search protocols. an oblivious search protocol decides on all requests in advance, and stops only when all users are found. a semi-adaptive search protocol decides on all the requests in advance, but it stops searching for a user once it is found. an adaptive search protocol stops searching for a user once it has been found (and its search strategy may depend on the subsets of users that were found in each previous round). we establish the difference between those three search models. we show that for oblivious "single query per cell" systems (b = 1), and a tight environment (d = m), it is np-hard to compute an optimal solution (the case d = m = 2 was proven to be np-hard already by bar-noy and naor) and we develop a ptas for these cases (for fixed values of d = m). however, we show that semi-adaptive systems allow polynomial time algorithms. this last result also shows that the case b = 1 and d = m = 2 is polynomially solvable also for adaptive search systems, answering an open question of bar-noy and naor.
lower bounds for on-line single-machine scheduling. the problem of scheduling jobs that arrive over time on a single machine is well studied. we study the preemptive model and the model with restarts. we provide lower bounds for deterministic and randomized algorithms for several optimality criteria: weighted and unweighted total completion time, and weighted and unweighted total flow time. by using new techniques, we provide the first lower bounds for several of these problems, and we significantly improve the bounds that were known.
on stable cutsets in line graphs. we answer a question of brandstädt et al. by showing that deciding whether a line graph with maximum degree 5 has a stable cutset is np-complete. conversely, the existence of a stable cutset in a line graph with maximum degree at most 4 can be decided efficiently. the proof of our np-completeness result is based on a refinement on a result due to chvátal that recognizing decomposable graphs with maximum degree 4 is an np-complete problem. here, a graph is decomposable if its vertices can be colored red and blue in such a way that each color appears on at least one vertex but each vertex v has at most one neighbor having a different color from v. we also discuss some open problems on stable cutsets.
the complexity of the characterization of networks supporting shortest-path interval routing. interval routing is a routing method that was proposed in order to reduce the size of the routing tables by using intervals and was extensively studied and implemented. some variants of the original method were also defined and studied. the question of characterizing networks which support optimal (i.e., shortest path) interval routing has been thoroughly investigated for each of the variants and under different models, with only partial answers, both positive and negative, given so far. in this paper, we study the characterization problem under the most basic model (the one unit cost), and with the most restrictive memory requirements (one interval per edge). we prove that this problem is np-hard (even for the restricted class of graphs of diameter at most 3). our result holds for all variants of interval routing. it significantly extends some related np-hardness result, and implies that, unless p = np, partial characterization results of some classes of networks which support shortest path interval routing, cannot be pushed further to lead to efficient characterizations for these classes.
note on the game chromatic index of trees. we study edge coloring games defining the so-called game chromatic index of a graph. it has been reported that the game chromatic index of trees with maximum degree δ = 3 is at most δ + 1. we show that the same holds true in case δ ≥ 6, which would leave only the cases δ = 4 and 5 open.
on the complexity of fixed parameter clique and dominating set. we provide simple, faster algorithms for the detection of cliques and dominating sets of fixed order. our algorithms are based on reductions to rectangular matrix multiplication. we also describe an improved algorithm for diamonds detection.
decision lists and related boolean functions. we consider boolean functions represented by decision lists, and study their relationships to other classes of boolean functions. it turns out that the elementary class of 1-decision lists has interesting relationships to independently defined classes such as disguised horn functions, read-once functions, nested differences of concepts, threshold functions, and 2-monotonic functions. in particular, 1-decision lists coincide with fragments of the mentioned classes. we further investigate the recognition problem for this class, as well as the extension problem in the context of partially defined boolean functions (pdbfs). we show that finding an extension of a given pdbf in the class of 1-decision lists is possible in linear time. this improves on previous results. moreover, we present an algorithm for enumerating all such extensions with polynomial delay.
on the complexity of data disjunctions. we study the complexity of data disjunctions in disjunctive deductive databases (dddbs). a data disjunction is a disjunctive ground clause r(c-1pt1)...r(ck),k ≥ 2, which is derived from the database such that all atoms in the clause involve the same predicate r. we consider the complexity of deciding existence and uniqueness of a minimal data disjunction, as well as actually computing one, both for propositional (data) and nonground (program) complexity of the database. our results extend and complement previous results on the complexity of disjunctive databases, and provide newly developed tools for the analysis of the complexity of function computation.
learning one-variable pattern languages very efficiently on average, in parallel, and by asking queries. a pattern is a finite string of constant and variable symbols. the langauge generated by a pattern is the set of all strings of constant symbols which can be obtained from the pattern by substituting non-empty strings for variables. we study the learnability of one-variable pattern languages in the limit with respect to the update time needed for computing a new single hypothesis and the expected total learning time taken until convergence to a correct hypothesis. our results are as follows. first, we design a consistent and set-driven learner that, using the concept of descriptive patterns, achieves update time o(n2logn), where n is the size of the input sample. the best previously known algorithm for computing descriptive one-variable patterns requires time o(n4logn) (cf. angluin, j. comput. systems sci. 21 (1) (1980) 46-62). second, we give a parallel version of this algorithm that requires time o(logn) and o(n3/logn) processors on an erew-pram. third, using a modified version of the sequential algorithm as a subroutine, we devise a learning algorithm for one-variable patterns whose expected total learning time is o(l2logl) provided that sample strings are drawn from the target language according to a probability distribution with expected string length l. the probability distribution must be such that strings of equal length have equal probability, but can be arbitrary otherwise. thus, we establish the first algorithm for learning one-variable pattern languages having an expected total learning time that provably differs from the update time by a constant factor only. finally, we show how the algorithm for descriptive one-variable patterns can be used for learning one-variable patterns with a polynomial number of superset queries with respect to the one-variable patterns as query language.
convexity and logical analysis of data. a boolean function is called $k$-convex if for any pair $x,y$ of its true points at hamming distance at most $k$, every point ``between'''' $x$ and $y$ is also true. given a set of true points and a set of false points, the central question of logical analysis of data is the study of those boolean functions whose values agree with those of the given points. in this paper we examine data sets which admit $k$-convex boolean extensions. we provide polynomial algorithms for finding a $k$-convex extension, if any, and for finding the maximum $k$ for which a $k$-convex extension exists. we study the problem of uniqueness, and provide a polynomial algorithm for checking whether all $k$-convex extensions agree in a point outside the given data set. we estimate the number of $k$-convex boolean functions, and show that for small $k$ this number is doubly exponential. on the other hand, we also show that for large $k$ the class of $k$-convex boolean functions is pac-learnable.
progressive solutions to a parallel automata equation. in this paper, we consider the problem of deriving a component x of a system knowing the behavior of the whole system c and the other components a. the component x is derived by solving the parallel automata equation a ⋄ x ≃ c. we present an algorithm for deriving a largest progressive solution to the equation that combined with a does not block any possible action in c and we establish conditions that allow us to characterize all progressive solutions.
deterministic analysis of queueing systems with heterogeneous servers. using deterministic (sample-path) analysis, we generalize and extend fundamental properties of systems with &ldquo;stationary deterministic flows&rdquo; as introduced by gelenbe (1983) and gelenbe and finkel (1987). primarily, we provide conditions for stability and instability for general queueing models, and focus attention on multichannel queueing systems with servers that work at different rates. stability analysis is important in computer applications and usually precedes any further investigation of the system in question. our results complement and extend those of gelenbe and finkel by making weaker assumptions, allowing multichannel facilities with heterogeneous servers, and including more general queueing disciplines such as processor sharing and lcfs-pr. the key to our stability analysis is a deterministic version of the renewal-reward theorem which we call y=lx , and a relationship that shows the &ldquo;operational analysis&rdquo; definition of average service times, when considered as the observation period t&rarr;&infin; , coincides with the standard definition of average service times for all stable queueing systems. our analysis is completely deterministic and avoids any stochastic assumptions about the system under investigation; thus, it provides the practitioner with a method that often leads to a better and deeper understanding of the system under consideration. it also gives a powerful tool to determine which properties of the system are independent of the usually needed probabilistic assumptions. as an illustration, a sample-path relationship that gives the long-run average busy period (cycle) for a general queueing model is given and utilized to derive several well-known results under weaker conditions. &mdash;authors' abstract
a context-free and a 1-counter geodesic language for a baumslag-solitar group. we give a language of unique geodesic normal forms for the baumslag-solitar group bs(1,2) that is context-free and 1-counter. we discuss the classes of context-free, 1-counter and counter languages, and explain how they are inter-related.
pcf extended with real numbers. we extend the programming language pcf with a type for (total and partial) real numbers. by a partial real number we mean an element of a cpo of intervals, whose subspace of maximal elements (single-point intervals) is homeomorphic to the euclidean real line. we show that partial real numbers can be considered as &ldquo;continuous words&rdquo;. concatenation of continuous words corresponds to refinement of partial information. the usual basic operations cons, head and tail used to explicitly or recursively define functions on words generalize to partial real numbers. we use this fact to give an operational semantics to the above referred extension of pcf. we prove that the operational semantics is sound and complete with respect to the denotational semantics. a program of real number type evaluates to a head-normal form iff its value is different from &bottom; ; if its value is different from &bottom; then it successively evaluates to head-normal forms giving better and better partial results converging to its value. &mdash;author's abstract
symmetry groups for beta-lattices. we present a construction of symmetry plane-groups for quasiperiodic point-sets named beta-lattices. the framework is issued from beta-integers counting systems. beta-lattices are vector superpositions of beta-integers. when β > 1 is a quadratic pisot-vijayaraghavan algebraic unit, the set of beta-integers can be equipped with an abelian group structure and an internal multiplicative law. when β = (1 + √5)/2, 1 + √2 and 2 + √3, we show that these arithmetic and algebraic structures lead to freely generated symmetry plane-groups for beta-lattices. these plane-groups are based on repetitions of discrete adapted rotations and translations we shall refer to as "beta-rotations" and "beta-translations". hence beta-lattices, endowed with beta-rotations and beta-translations, can be viewed like lattices. the quasiperiodic function ρs(n), defined on the set of beta-integers as counting the number of small tiles between the origin and the nth beta-integer, plays a central part in these new group structures. in particular, this function behaves asymptotically like a linear function. as an interesting consequence, beta-lattices and their symmetries behave asymptotically like lattices and lattice symmetries, respectively.
a rewriting-based inference system for the nrl protocol analyzer and its meta-logical properties. the nrl protocol analyzer (npa) is a tool for the formal specification and analysis of cryptographic protocols that has been used with great effect on a number of complex real-life protocols. one of the most interesting of its features is that it can be used to reason about security in face of attempted attacks on low-level algebraic properties of the functions used in a protocol. indeed, it has been used successfully to either reproduce or discover a number of such attacks. in this paper we give for the first time a precise formal specification of the main features of the npa inference system: its grammar-based techniques for invariant generation and its backwards reachability analysis method. this formal specification is given within the well-known rewriting framework so that the inference system is specified as a set of rewrite rules modulo an equational theory describing the behavior of the cryptographic algorithms involved. we then use this formalization to prove some important meta-logical properties about the npa inference system, including the soundness and completeness of the search algorithm and soundness of the grammar generation algorithm. the formalization and soundness and completeness theorems not only provide also a better understanding of the npa as it currently operates, but provide a modular basis which can be used as a starting point for increasing the types of equational theories it can handle.
completeness in approximation classes beyond apx. we present a reduction that allows us to establish completeness results for several approximation classes mainly beyond apx. using it, we extend one of the basic results of s. khanna, r. motwani, m. sudan, and u. vazirani (on syntactic versus computational views of approximability, siam j. comput. 28 (1998) 164-191) by proving sufficient conditions for getting complete problems for the whole log-apx, the class of problems approximable within ratios that are logarithms of the size of the instance, as well as for any approximability class beyond apx. we also introduce a new approximability class, called poly-apx(δ), dealing with graph-problems approximable with ratios functions of the maximum degree δ of the input-graph. for this class also, using the proposed reduction, we establish complete problems.
euclidean strings. a string p = p0p1...pn-1 of non-negative integers is a euclidean string if the string (p0 + 1)p1...(pn-1 - 1) is rotationally equivalent (i.e., conjugate) to p. we show that euclidean strings exist if and only if n and p0 + p1 + ... + pn-1 are relatively prime and that, if they exist, they are unique. we show how to construct them using an algorithm with the same structure as the euclidean algorithm, hence the name. we show that euclidean strings are lyndon words and we describe relationships between euclidean strings and the stem-brocot tree, fibonacci strings, beatty sequences, and sturmian sequences. we also describe an application to a graph embedding problem.
on the complexity of resolution with bounded conjunctions. we analyze size and space complexity of res(k), a family of propositional proof systems introduced by krajíček in (fund. math. 170 (1-3) (2001) 123) which extend resolution by allowing disjunctions of conjunctions of up to k ≥ 1 literals. we show that the treelike res(k) proof systems form a strict hierarchy with respect to proof size and also with respect to space. moreover resolution, while simulating treelike res(k), is almost exponentially separated from treelike res(k). to study space complexity for general res(k) we introduce the concept of dynamical satisfiability which allows us to prove in a unified way all known space lower bounds for resolution and to extend them to res(k).
transformations of clp modules. we propose a transformation system for clp programs and modules. the framework is inspired by the one of tamaki and sato for pure logic programs. however, the use of clp allows us to introduce some new operations such as splitting and constraint replacement. we provide two sets of applicability conditions. the first one guarantees that the original and the transformed programs have the same computational behaviour, in terms of answer constraints. the second set contains more restrictive conditions that ensure compositionality: we prove that under these conditions the original and the transformed modules have the same answer constraints also when they are composed with other modules. this result is proved by first introducing a new formulation, in terms of trees, of a resultants semantics for clp. as corollaries we obtain the correctness of both the modular and the non-modular system w.r.t. the least model semantics.
characterizing bipartite toeplitz graphs. a toeplitz graph is a symmetric graph whose adjacency matrix is toeplitz. if such a graph has neither loops nor multiple edges it can be defined by a 0-1 sequence. in euler et al. (in: ku tung-hsin (ed.), combinatorics and graph theory '95, vol. 1, academia sinica, world scientific, singapore, 1995, pp. 119-130) infinite, bipartite toeplitz graphs have been fully characterized. in this paper we complete these results by some structural and algorithmic properties and then turn ourselves to study the .nite case. we present a complete solution for bipartite toeplitz graphs that are defined by a 0-1 sequence with two 1-entries, and we present several partial results for those defined by a 0-1 sequence with three 1-entries.
on the complexity of finding common approximate substrings. problems associated with finding strings that are within a specified hamming distance of a given set of strings occur in several disciplines. in this paper, we use techniques from parameterized complexity to assess non-polynomial time algorithmic options and complexity for the common approximate substring (cas) problem. our analyses indicate under which parameter restrictions useful algorithms are possible, and include both class membership and parameterized reductions to prove class hardness. in order to achieve fixed-parameter tractability, either a fixed string length or both a fixed size alphabet and fixed substring length are sufficient. fixing either the string length or the alphabet size and hamming distance is shown to be necessary, unless w[1] = fpt. an assortment of parameterized class membership and hardness results cover all other parameterized variants, showing in particular the effect of fixing the number of strings.
a multi-scale constraint programming model of alternative splicing regulation. alternative splicing is a key process in post-transcriptional regulation, by which different mature rna can be obtained from the same premessenger rna. the resulting combinatorial complexity contributes to biological diversity, especially in the case of the human immunodeficiency virus hiv-1. using a constraint programming approach, we develop a model of the alternative splicing regulation in hiv-1. our model integrates different scales (single site vs. multiple sites), and thus allows us to exploit several types of experimental data available to us.
on the parametric complexity of schedules to minimize tardy tasks. given a set t of tasks, each of unit length and having an individual deadline d(t) ∈ z+, a set of precedence constraints on t, and a positive integer k ≤ |t|, we can ask "is there a one-processor schedule for t that obeys the precedence constraints and contains no more than k late tasks?" this is a well-known np-complete problem.we might also inquire "is there a one-processor schedule for t that obeys the precedence constraints and contains at least k tasks that are on time i.e. no more than |t| - k late tasks?"within the framework of classical complexity theory, these two questions are merely different instances of the same problem. within the recently developed framework of parameterized complexity theory, however, they give rise to two separate problems that may be studied independently of one another.we investigate these problems from the parameterized point of view. we show that, in the general case, both these problems are hard for the parameterized complexity class w[1].in contrast, in the case where the set of precedence constraints can be modelled by a partial order of bounded width, we show that both these problems are fixed parameter tractable.
on finding short resolution refutations and small unsatisfiable subsets. we consider the parameterized problems of whether a given set of clauses can be refuted within k resolution steps, and whether a given set of clauses contains an unsatisfiable subset of size at most k. we show that both problems are complete for the class w[1], the first level of the w-hierarchy of fixed-parameter intractable problems. our results remain true if restricted to 3-sat instances and/or to various restricted versions of resolution including tree-like resolution, input resolution, and read-once resolution. applying a metatheorem of frick and grohe, we show that, restricted to classes of sets of clauses of locally bounded treewidth, the considered problems are fixed-parameter tractable. for example, the problems are fixed-parameter tractable for planar cnf formulas.
a pumping lemma for random permitting context languages. random context grammars belong to the class of context-free grammars with regulated rewriting. their productions depend on context that may be randomly distributed in a sentential form. context is classified as either permitting or forbidding, where permitting context enables the application of a production and forbidding context inhibits it. for random context languages of finite index a generalization of the well-known pumping lemma for context-free languages has been proven. we drop the finite index restriction and concentrate on non-erasing grammars that use permitting context only. we prove a pumping lemma for their languages that generalizes and refines the existing one, and show that these grammars are strictly weaker than the non-erasing random context grammars
kolmogorov complexities , on computable partially ordered sets. we introduce a machine free mathematical framework to get a natural formalization of some general notions of infinite computation in the context of kolmogorov complexity. namely, the classes maxp rx → d and maxrecx → d of functions x → d which are pointwise maximum of partial or total computable sequences of functions where d = (d, <) is some computable partially ordered set. the enumeration theorem and the invariance theorem always hold for maxp rx → d, leading to a variant kmaxd of kolmogorov complexity. we characterize the orders d such that the enumeration theorem (resp. the invariance theorem) also holds for maxrecx → d. it turns out that maxrecx → d may satisfy the invariance theorem but not the enumeration theorem. also, when maxrecx → d satisfies the invariance theorem then the kolmogorov complexities associated to maxrecx → d and maxp rx → d are equal (up to constant).letting kmind = kmaxdrev where drev is the reverse order, we prove that either kmind = ctkmaxd = ctkd (=ct is equality up to a constant) or kmind, kmaxdare ≤ ct incomparable and <ct kd and > ct k0',d. we characterize the orders leading to each case. we also show that kmind, kmaxd cannot be both much smaller than kd at any point.these results are proved in a more general setting with two orders on d, one extending the other.
a -enumeration of convex polyominoes by the festoon approach. in 1938, pólya stated an identity involving the perimeter and area generating function for parallelogram polyominoes. to obtain that identity, pólya presumably considered festoons. a festoon (so named by flajolet) is a closed path w which can be written as w = uv, where each step of u is either (1, 0) or (0, 1), and each step of v is either (-1, 0) or (0, -1).in this paper, we introduce four new festoon-like objects. as a result, we obtain explicit expressions (and not just identities) for the generating functions of parallelogram polyominoes, directed convex polyominoes, and convex polyominoes.
interactive observability in ludics: the geometry of tests. ludics [j.-y. girard, locus solum, math. structures in comput. sci. 11 (2001) 301-506] is a recent proposal of analysis of interaction, developed by abstracting away from proof-theory. it provides an elegant, abstract setting in which interaction between agents (proofs/programs/processes) can be studied at a foundational level, together with a notion of equivalence from the point of view of the observer.an agent should be seen as some kind of black box. an interactive observation on an agent is obtained by testing it against other agents.in this paper we explore what can be observed interactively in this setting. in particular, we characterize the objects that can be observed in a single test: the primitive observables of the theory.our approach builds on an analysis of the geometrical properties of the agents, and highlights a deep interleaving between two partial orders underlying the combinatorial structures: the spatial one and the temporal one.
data exchange: semantics and query answering. data exchange is the problem of taking data structured under a source schema and creating an instance of a target schema that reflects the source data as accurately as possible. in this paper, we address foundational and algorithmic issues related to the semantics of data exchange and to the query answering problem in the context of data exchange. these issues arise because, given a source instance, there may be many target instances that satisfy the constraints of the data exchange problem.we give an algebraic specification that selects, among all solutions to the data exchange problem, a special class of solutions that we call universal. we show that a universal solution has no more and no less data than required for data exchange and that it represents the entire space of possible solutions. we then identify fairly general, yet practical, conditions that guarantee the existence of a universal solution and yield algorithms to compute a canonical universal solution efficiently. we adopt the notion of the "certain answers" in indefinite databases for the semantics for query answering in data exchange. we investigate the computational complexity of computing the certain answers in this context and also address other algorithmic issues that arise in data exchange. in particular, we study the problem of computing the certain answers of target queries by simply evaluating them on a canonical universal solution, and we explore the boundary of what queries can and cannot be answered this way, in a data exchange setting.
decomposable multi-parameter matroid optimization problems. a framework for solving certain multi-dimensional parametric matroid optimization problems in randomized linear time by prune-and-search is presented. the common feature of these problems, which include the multi-parameter minimum spanning tree problem on planar and dense graphs, is that their fixed-parameter versions are solvable by tournament-like algorithms whose structure is represented by a balanced decomposition tree.
the do-all problem with byzantine processor failures. do-all is the abstract problem of using n processors to cooperatively perform m independent tasks in the presence of failures. this problem and its derivatives have been a centerpiece in the study of trade-offs between efficiency and fault-tolerance in cooperative computing environments. many algorithms have been developed for do-all in various models of computation, including message-passing, partitionable networks, and shared-memory models under a variety of failure models.this work initiates the study of the do-all problem for synchronous message-passing processors prone to byzantine failures. in particular, upper and lower bounds are given on the complexity of do-all for several cases: (a) the case where the maximum number of faulty processors f is known a priori, (b) the case where f is not known, (c) the case where a task execution can be verified (without re-executing the task), and (d) the case where task executions cannot be verified. the efficiency of algorithms is evaluated in terms of work and message complexities. the work complexity accounts for all computational steps taken by the processors and the message complexity accounts for all messages sent by the processors during the computation. the work and messages of a faulty processor are counted only until the processor fails to follow the algorithm. it is shown that in some cases obtaining work θ(mn) is the best one can do. it is also shown that in certain cases communication cannot help improve work efficiency.
operational equivalence for interaction nets. the notion of contextual (or operational) equivalence is fundamental in the theory of programming languages. by setting up a notion of bisimilarity, and showing that it coincides with contextual equivalence, one obtains a simple coinductive proof technique for showing that two programs are equivalent in all contexts. in this paper we apply these (now standard) techniques to interactions nets, a graphical programming language characterized by local reduction. this work generalizes previous studies of operational equivalence in typed interaction nets since it can be applied to untyped systems, thus all systems of interaction nets are captured.
cubical local partial orders on cubically subdivided spaces - existence and construction. the geometric models of higher dimensional automata (hda) and dijkstra's pv-model are cubically subdivided topological spaces with a local partial order. if a cubicalization of a topological space is free of immersed cubic möbius bands, then there are consistent choices of direction in all cubes, such that any n-cube in the cubic subdivision is dihomeomorphic to [0, 1]n with the induced partial order from rn. after subdivision once, any cubicalized space has a cubical local partial order. in particular, all triangularized spaces have a cubical local partial order. this implies in particular that the underlying geometry of an hda may be quite complicated.
algebraic topology and concurrency. we show in this article that some concepts from homotopy theory, in algebraic topology, are relevant for studying concurrent programs. we exhibit a natural semantics of semaphore programs, based on partially ordered topological spaces, which are studied up to "elastic deformation" or homotopy, giving information about important properties of the program, such as deadlocks, unreachables, serializability, essential schedules, etc. in fact, it is not quite ordinary homotopy that has to be used, but rather a "directed homotopy" that does not reverse the flow of time. we show some of the essential differences between ordinary and directed homotopy through examples. we also relate the topological view to a combinatorial view of concurrent programs closer to transition systems, through the notion of a cubical set. finally we apply some of these concepts to the proof of the safeness of a two-phase protocol, well-known and used in concurrent database theory. we end up with a list of problems from both a mathematical and a computer-scientific point of view.
even linear simple matrix languages: formal language properties and grammatical inference. we show that so-called deterministic even linear simple matrix grammars can be inferred in polynomial time using the query-based learner-teacher model (minimally adequate teacher-learning model) proposed by angluin (inform. and comput. 75 (1987) 87) for learning deterministic regular languages. in this way, we extend the class of efficiently learnable languages beyond both the even linear languages and the even equal matrix languages (pattern recognition 21 (1988) 55; proc. 2nd internat. colloq. on grammatical inference (icgi-94): grammatical inference and applications, lecture notes in computer science/lecture notes in artificial intelligence, vol. 862, springer, berlin, 1994, p. 38; inform. process. lett. 28 (1988) 193; technical report iias-rr-93-6e, fujitsu laboratories, 1992; parallel image analysis, icpia'92, lecture notes in computer science, vol. 652, springer, berlin, 1992, p. 274; inform. and comput. 123 (1995) 138; algorithmic learning for knowledge-based systems, lecture notes in computer science/lecture notes in artificial intelligence, springer, berlin, 1995, p. 317). moreover, we investigate formal language properties of even linear simple matrix languages and related language classes. more precisely, we discuss characterizations, (proper) inclusion relations, closure properties and decidability questions. this way, we also show that, in a certain sense, the idea of iterating the control language approach for learning purposes, as undertook by takada (1995), could be seen as a special case of using deterministic even linear simple matrix grammars as basic and uniform learning target.
identification of function distinguishable languages. we show how appropriately chosen functions f which we call distinguishing can be used to make deterministic finite automata backward deterministic. this idea can be exploited to design regular language classes called f-distinguishable which are identifiable in the limit from positive samples. special cases of this approach are the k-reversible and terminal distinguishable languages, as discussed in angluin (j. assoc. comput. mach. 29 (3) (1982) 741), fernau (technical report wsi-99-23, universität tübingen (germany), wilhelm-schickard-institut für informatik, 1999, short version published in the proceedings of amai 2000, see http://rutcot. rutgers. edu/~amai/aimath00/acceptedcont.htm, proc. 15th internat. conf. on pattern recognition (icpr 2000), vol. 2, ieee press, new york, 2000, pp. 125-128), radhakrishnan (ph.d. thesis, department of computer science and engineering, indian institute of technology, bombay, india, 1987), radhakrishnan and nagaraja (ieee trans. systems, man cybernet. 17 (6) (1987) 982). moreover, we show that all regular languages may be approximated in the setting introduced by kobayashi and yokomori (in: k. p. jantke, t. shinohara, th. zeugmann (eds.), proc. sixth internat. conf. algorithmic learning theory (alt'95), lecture notes in computer science/lecture notes in artificial intelligence, vol. 997, springer, berlin, 1995, pp. 298-312), (theoret. comput. sci. 174 (1997) 251-257) by any class of f-distinguishable languages. observe that the class of all function-distinguishable languages is equal to the class of regular languages.
nonterminal complexity of programmed grammars. we show that, in the case of context-free programmed grammars with appearance checking working under free derivations, three nonterminals are enough to generate every recursively enumerable language. this improves the previously published bound of eight for the nonterminal complexity of these grammars. this also yields an improved nonterminal complexity bound of four for context-free matrix grammars with appearance checking. moreover, we establish an upperbound of four on the nonterminal complexity of context-free programmed grammars without appearance checking working under leftmost derivations of type 2. we derive nonterminal complexity bounds for context-free programmed and matrix grammars with appearance checking or with unconditional transfer working under leftmost derivations of types 2 and 3, as well. more specifically, a first nonterminal complexity bound for context-free programmed grammars with unconditional transfer (working under leftmost derivations of type 3) which depends on the size of the terminal alphabet is proved.
additives of linear logic and normalization - part i: a (restricted) church-rosser property. we define a generalized cut-elimination procedure for proof-nets of fall linear logic (without constants), for which we prove a (restricted) church-rosser property.
frequency of symbol occurrences in bicomponent stochastic models. we give asymptotic estimates of the frequency of occurrences of a symbol in a random word generated by any bicomponent stochastic model. more precisely, we consider the random variable yn, representing the number of occurrences of a given symbol in a word of length n generated at random; the stochastic model is defined by a rational formal series r having a linear representation with two primitive components. this model includes the case when r is the product or the sum of two primitive rational formal series. we obtain asymptotic evaluations for the mean value and the variance of yn and its limit distribution.
on the degree of scattered context-sensitivity. in this paper, we prove that every recursively enumerable language can be generated by a scattered context grammar with no more than two context-sensitive productions.
the go polynomials of a graph. this paper introduces graph polynomials based on a concept from the game of go. suppose that, for each vertex of a graph, we either leave it uncoloured or choose a colour uniformly at random from a set of available colours, with the choices for the vertices being independent and identically distributed. we ask for the probability that the resulting partial assignment of colours has the following property: for every colour class, each component of the subgraph it induces has a vertex that is adjacent to an uncoloured vertex. in go terms, we are requiring that every group is uncaptured. this definition leads to go polynomials for a graph. although these polynomials are based on properties that are less "local" in nature than those used to define more traditional graph polynomials such as the chromatic polynomial, we show that they satisfy recursive relations based on local modifications similar in spirit to the deletion-contraction relation for the chromatic polynomial. we then show that they are #p-hard to compute in general, using a result on linear forms in logarithms from transcendental number theory. we also briefly record some correlation inequalities.
sequential grammars and automata with valences. we discuss the model of valence grammars, a simple extension of context-free grammars. we show closure properties of context-free valence languages over arbitrary monoids. chomsky and greibach normal form theorems and an iteration lemma for context-free valence grammars over the groups zk are proved. the generative power of different control monoids is investigated. in particular, we show that context-free valence grammars over finite monoids or commutative monoids have the same power as valence grammars over finite groups or commutative groups, respectively.
bounded-connect noncanonical discriminating-reverse parsers. the precision of right-hand context covering for conflict resolution is improved over previous ndr parsers, resulting in acceptation of wider subsets of lr-regular and lr-nonregular grammars, including all lalr(k) grammars for a given k. parser generation combines a new form of dr items and subgraph connections of bounded length, without the need to implement subgraph copies. the ndr parser, whose algorithm remains essentially unchanged, is presented as an extended two-stack pushdown automaton. the technique is illustrated with a detailed example.
fully asynchronous behavior of double-quiescent elementary cellular automata. in this paper we propose a probabilistic analysis of the fully asynchronous behavior (i.e., two cells are never simultaneously updated, as in a continuous time process) of elementary finite cellular automata (i.e., {0, 1} states, radius 1 and unidimensional) for which both states are quiescent (i.e., (0, 0, 0) ↦ 0 and (1, 1, 1) ↦ 1). it has been experimentally shown in previous works that introducing asynchronism in the global function of a cellular automata was perturbing its behavior, but as far as we know, only few theoretical work exists on the subject. the cellular automata we consider live on a ring of size n and asynchronism is introduced as follows: at each time step one cell is selected uniformly at random and the transition is made on this cell while the others stay in the same state. among the 64 cellular automata belonging to the class we consider, we show that 9 of them diverge on all non-trivial configurations while the 55 other converge almost surely to a random fixed point. we show that the exact convergence time of these 55 automata can only take the following values: either 0, θ(n ln n), θ(n2), θ(n3 ) or θ(n2n). furthermore, the global behavior of each of these cellular automata is fully determined by reading its code.
an algebraic characterization of the set of succession rules. in this paper we will give a formal description of succession rules in terms of linear operators satisfying certain conditions. this representation allows us to introduce a system of well-defined operations into the set of succession rules and then to tackle problems of combinatorial enumeration simply by using operators instead of generating functions. finally, we will suggest several open problems whose solution should lead to an algebraic characterization of the set of succession rules.
neighborhood unions and regularity in graphs. one way to generalize the concept of degree in a graph is to consider the neighborhood n(s) of an independent set s instead of a simple vertex. the minimum generalized degree of order t of g is then defined, for 1&le;t&le;&agr; (the independence number of g), by ut=min{|n(s)|: s (semi-circle right) v; s is independent and |s| = t}. the graph g is said to be u(sub)t-regular if |n(s1)| = |n(s2)| for every pair s1; s2 of independent sets of t elements, totally u(sub)t-regular (resp. totally u(sub)t&le;s-regular where s is given &le;&agr;) if it is u(sub)t-regular for every t&le;&agr; (resp. for every t&le;s), strongly u(sub)t-regular (resp. strongly u(sub)t6s-regular) if |n(s1)| = |n(s2)| for every pair s1; s2 of independent sets of g (resp. every pair of independent sets of order at most s). we determine the strongly u(sub)t&le;2-regular graphs and give some properties of the totally u(sub)t&le;2-regular and totally u(sub)t-regular graphs. some of our results improve already known results.
list matrix partitions of chordal graphs. it is well known that a clique with k + 1 vertices is the only minimal obstruction to k-colourability of chordal graphs. a similar result is known for the existence of a cover by l cliques. both of these problems are in fact partition problems, restricted to chordal graphs. the first seeks partitions into k independent sets, and the second is equivalent to finding partitions into l cliques. in an earlier paper we proved that a chordal graph can be partitioned into k independent sets and l cliques if and only if it does not contain an induced disjoint union of l + 1 cliques of size k + 1. (a linear time algorithm for finding such partitions can be derived from the proof.)in this paper we expand our focus and consider more general partitions of chordal graphs. for each symmetric matrix m over 0, 1, *, the m-partition problem seeks a partition of the input graph into independent sets, cliques, or arbitrary sets, with certain pairs of sets being required to have no edges, or to have all edges joining them, as encoded in the matrix m. moreover, the vertices of the input chordal graph can be equipped with lists, restricting the parts to which a vertex can be placed. such (list) partitions generalize (list) colourings and (list) homomorphisms, and arise frequently in the theory of graph perfection. we show that many m-partition problems that are np-complete in general become solvable in polynomial time for chordal graphs, even in the presence of lists. on the other hand, we show that there are m-partition problems (without lists) that remain np-complete for chordal graphs. it is not known whether or not each list m-partition problem is np-complete or polynomial, but it has been shown that each is np-complete or quasi-polynomial (no(log n)). for chordal graphs even this 'quasi-dichotomy' is not known, but we do identify large families of matrices m for which dichotomy, or at least quasi-dichotomy, holds.we also discuss forbidden subgraph characterizations of graphs admitting an m-partition. such characterizations have recently been investigated for partitions of perfect graphs, and we focus on highlighting the improvements one can obtain for the class of chordal, rather than just perfect, graphs.
combining request scheduling with web caching. we extend the classic paging model by allowing reordering of requests under the constraint that a request is delayed by no longer than a predetermined number of time steps. we first give a dynamic programming algorithm to solve the offline case. then we give tight bounds on competitive ratios for the online case. for caches of size k, we obtain bounds of k + o(1) for deterministic algorithms and θ(log k) for randomized algorithms. we also give bounds for the case where either the online or the offline algorithm can reorder the requests, but not both. finally, we extend our analysis to the case where pages have different sizes.
dichotomies for classes of homomorphism problems involving unary functions. we study non-uniform constraint satisfaction problems where the underlying signature contains constant and function symbols as well as relation symbols. amongst our results are the following. we establish a dichotomy result for the class of non-uniform constraint satisfaction problems over the signature consisting of one unary function symbol by showing that every such problem is either complete for l, via very restricted logical reductions, or trivial (depending upon whether the template function has a fixed point or not). we show that the class of non-uniform constraint satisfaction problems whose templates are structures over the signature λ2 consisting of two unary function symbols reflects the full computational significance of the class of non-uniform constraint satisfaction problems over relational structures. we prove a dichotomy result for the class of non-uniform constraint satisfaction problems where the template is a λ2-structure with the property that the two unary functions involved are the reverse of one another, in that every such problem is either solvable in polynomial-time or np-complete. finally, we extend some of our results to the situation where instances of non-uniform constraint satisfaction problems come equipped with lists of elements of the template structure which restrict the set of allowable homomorphisms.
on three variants of rewriting p systems. we continue here the study of p systems with string objects processed by rewriting rules, by investigating some questions which are classic in formal language theory: leftmost derivation, conditional use of rules (permitting and forbidding conditions), relationships with language families in chomsky and lindenmayer hierarchies.
schedulability analysis of fixed-priority systems using timed automata. in classic scheduling theory, real-time tasks are usually assumed to be periodic, i.e. tasks are released and computed with fixed rates periodically. to relax the stringent constraints on task arrival times, we propose to use timed automata to describe task arrival patterns. in a previous work, it is shown that the general schedulability checking problem for such models is a reachability problem for a decidable class of timed automata extended with subtraction. unfortunately, the number of clocks needed in the analysis is proportional to the maximal number of schedulable task instances associated with a model, which is in many cases huge. in this paper, we show that for fixed-priority scheduling strategy, the schedulability checking problem can be solved using standard timed automata with two extra clocks in addition to the clocks used in the original model to describe task arrival times. the analysis can be done in a similar manner to response time analysis in classic rate-monotonic analysis (rma). the result is further extended to systems with data-dependent control, in which the release time of a task may depend on the time-point at which other tasks finish their execution. for the case when the execution times of tasks are constants, we show that the schedulability problem can be solved using n + 1 extra clocks, where n is the number of tasks. the presented analysis techniques have been implemented in the times tool. for systems with only periodic tasks, the performance of the tool is comparable with tools implementing the classic rma technique based on equation-solving, without suffering from the exponential explosion in the number of tasks.
on the drift of short schedules. for the job shop scheduling problem, the drift of a schedule is the maximum difference between the number of operations performed by two jobs within a time interval. we show instances of the problem for which every short schedule must allow for nonconstant drift.
an enhanced property of factorizing codes. the investigation of the factorizing codes c, i.e., codes satisfying schützenberger's factorization conjecture, has been carried out from different viewpoints, one of them being the description of structural properties of the words in c. in this framework, we can now improve an already published result. more precisely, given a factorizing code c over a two-letter alphabet a = {a, b}, it was proved by de felice that the words in the set c1 = c ∩ a*ba* could be arranged over a matrix related to special factorizations of the cyclic groups. we now prove that, in addition, these matrices can be recursively constructed starting with those corresponding to prefix/suffix codes.
computation in a distributed information market. according to economic theory--supported by empirical and laboratory evidence--the equilibrium price of a financial security reflects all of the information regarding the security's value. we investigate the computational process on the path toward equilibrium, where information distributed among traders is revealed step-by-step over time and incorporated into the market price. we develop a simplified model of an information market, along with trading strategies, in order to formalize the computational properties of the process. we show that securities whose payoffs cannot be expressed as weighted threshold functions of distributed input bits are not guaranteed to converge to the proper equilibrium predicted by economic theory. on the other hand, securities whose payoffs are threshold functions are guaranteed to converge, for all prior probability distributions. moreover, these threshold securities converge in at most n rounds, where n is the number of bits of distributed information. we also prove a lower bound, showing a type of threshold security that requires at least n/2 rounds to converge in the worst case.
is dna computing viable for 3-sat problems? adleman reported how to solve a 7-vertex instance of the hamiltonlan path problem by means of dna manipulations. after that a major goal of subsequent research is how to use dna manipulations to solve np-hard problems, especially 3-sat problems. lipton proposed dna experiments on test tubes to solve 3-sat problems. liu et al. reported how to solve a simple case of 3-sat using dna computing on surfaces. lipton's model of dna computing is simple and intuitive for 3-sat problems. the separate (or extract) operation, which is a key manipulation of dna computing, only extracts some of the required dna strands and lipton thinks that a typical percentage might be 90. but it is unknown what would happen due to imperfect extract operation. let p be the rate, where 0 < p < 1. assume that for each distinct string s in a test tube, there are 10l (l=13 proposed by adleman) copies of s and that extracting each of the required dna strands is equally likely. here, the present paper will report, no matter how large l is and no matter how close to 1 p is, there always exists a class of 3-sat problems such that dna computing error must occur. therefore, dna computing is not viable for 3-sat.
on graph problems in a semi-streaming model. we formalize a potentially rich new streaming model, the semi-streaming model, that we believe is necessary for the fruitful study of efficient algorithms for solving problems on massive graphs whose edge sets cannot be stored in memory. in this model, the input graph, g = (v, e), is presented as a stream of edges (in adversarial order), and the storage space of an algorithm is bounded by o(n ċ polylog n), where n = |v|. we are particularly interested in algorithms that use only one pass over the input, but, for problems where this is provably insufficient, we also look at algorithms using constant or, in some cases, logarithmically many passes. in the course of this general study, we give semi-streaming constant approximation algorithms for the unweighted and weighted matching problems, along with a further algorithmic improvement for the bipartite case. we also exhibit log n/log log n semi-streaming approximations to the diameter and the problem of computing the distance between specified vertices in a weighted graph. these are complemented by ω(log(1-ε) n) lower bounds.
generating well-shaped d-dimensional delaunay meshes. a d-dimensional simplicial mesh is a delaunay triangulation if the circumsphere of each of its simplices does not contain any vertices inside. a mesh is well shaped if the maximum aspect ratio of all its simplices is bounded from above by a constant. it is a long-term open problem to generate well-shaped d-dimensional delaunay meshes for a given polyhedral domain. in this paper, we present a refinement-based method that generates well-shaped d-dimensional delaunay meshes for any plc domain with no small input angles. furthermore, we show that the generated well-shaped mesh has o(n) d-simplices, where n is the smallest number of d-simplices of any almost-good meshes for the same domain. here a mesh is almost-good if each of its simplices has a bounded circumradius to the shortest edge length ratio.
traveling salesmen in the presence of competition. we propose the "competing salesmen problem" (csp), a two-player competitive version of the classical traveling salesman problem. this problem arises when considering two competing salesmen instead of just one. the concern for a shortest tour is replaced by the necessity to reach any of the customers before the opponent does.in particular, we consider the situation where players take turns, moving along one edge at a time within a graph g = (v,e). the set of customers is given by a subset vc ⊆ v of the vertices. at any given time, both players know of their opponent's position. a player wins if he is able to reach a majority of the vertices in vc before the opponent does.we prove that the csp is pspace-complete, even if the graph is bipartite, and both players start at distance 2 from each other. furthermore, we show that the starting player may not be able to avoid losing the game, even if both players start from the same vertex. however, for the case of bipartite graphs, we show that the starting player always can avoid a loss. on the other hand, we show that the second player can avoid to lose by more than one customer, when play takes place on a graph that is a tree t, and vc consists of leaves of t. it is unclear whether a polynomial strategy exists for any of the two players to force this outcome. for the case where t is a star (i.e., a tree with only one vertex of degree higher than two) and vc consists of n leaves of t, we give a simple and fast strategy which is optimal for both players. if vc consists not only of leaves, we point out that the situation is more involved.
on-line single-server dial-a-ride problems. in this paper results on the dial-a-ride problem with a single server are presented. requests for rides consist of two points in a metric space, a source and a destination. a ride has to be made by the server from the source to the destination. the server travels at unit speed in the metric space and the objective is to minimize some function of the delivery times at the destinations. we study this problem in the natural on-line setting. calls for rides come in while the server is traveling. this models, e.g. the taxi problem, or, if the server has capacity more than a minibus or courier service problem. for the version of this problem in which the server has infinite capacity having as objective minimization of the time the last destination is served, we design an algorithm that has competitive ratio 2. we also show that this is best possible, since no algorithm can have competitive ratio better than 2 independent of the capacity of the server. besides, we give a simple 2.5-competitive algorithm for the case with finite capacity. then we study the on-line problem with objective minimization of the sum of completion times of the rides. we prove a lower bound on the competitive ration of any algorithm of 1 + 2 for a server with any capacity and of 3 for a server has infinite capacity and the metric space is the real line. the algorithm has competitive ration 15. copyright 2001 elsevier science b.v.
on distance constrained labeling of disk graphs. a disk graph is the intersection graph of a set of disks in the plane. for a k-tuple (p1 ..... pk) of positive integers, a distance constrained labeling of a graph g is an assignment of labels to the vertices of g such that the labels of any pair of vertices at graph distance i in g differ by at least pi, for i = 1,...,k. in the case when k = 1 and p1 = 1, this gives a traditional coloring of g. we propose and analyze several online and offiine labeling algorithms for the class of disk graphs.
a complete complexity classification of the role assignment problem. in social network theory a society is often represented by a simple graph g, where vertices stand for individuals and edges represent relationships between those individuals. the description of the social network is tried to be simplified by assigning roles to the individuals, such that the neighborhood relation is preserved. formally, for a fixed graph r we ask for a vertex mapping r: vg → vr, such that r(ng(u)) = nr(r(u)) for all u ∈ vg.if such a mapping exists the graph g is called r-role assignable and the corresponding decision problem is called the r-role assignment problem. kristiansen and telle conjectured that the r-role assignment problem is an np-complete problem for any simple connected graph r on at least three vertices. in this paper we prove their conjecture. in addition, we determine the computational complexity of the role assignment problem for nonsimple and disconnected role graphs, as these are considered in social network theory as well.
word assembly through minimal forbidden words. we give a linear-time algorithm to reconstruct a finite word w over a finite alphabet a of constant size starting from a finite set of factors of w verifying a suitable hypothesis. we use combinatorics techniques based on the minimal forbidden words, which have been introduced in previous papers. this improves a previous algorithm which worked under the assumption of stronger hypothesis.
compact factors of countable state markov shifts. we study continuous shift commuting maps from transitive countable state markov shifts into compact subshifts. the closure of the image is a coded system. on the other hand, any coded system is the surjective image of some transitive markov shift, which may be chosen locally compact by construction. these two results yield a formal analogy to "the transitive sofic systems are the subshift factors of transitive shifts of finite type". then we consider factor maps which have bounded coding length in some graph presentation (label maps). now the image has to be synchronized, but not every synchronized system can be obtained in this way. we show various restrictions for a surjective label map to exis
polymorphic lambda calculus and subtyping. we present a denotational model for f, the extension of second-order lambda calculus with subtyping defined in cardelli and wegner (acm comput. surveys 17(4) (1985) 471-522.) types are interpreted as arbitrary cpos and elements of types as natural transformations. we prove the soundness of our model with respect to the equational theory of f (cardelli et al. (internat. conf. on theoretical aspects of computer software, lecture notes in computer science, vol. 526, springer, berlin, 1991, pp. 750-770)) and show coherence. our model is of independent interest, because it integrates ad hoc and parametric polymorphism in an elegant fashion, admits nontrivial records and record update operations, and formalizes an "order faithfulness" criterion for well-behaved multiple subtyping.
analysis of randomized load distribution for reproduction trees in linear arrays and rings. high performance computing requires high quality load distribution of processes of a parallel application over processors in a parallel computer at runtime such that both maximum load and dilation are minimized. the performance of a simple randomized load distribution algorithm that dynamically supports tree-structured parallel computations on two simple static networks, namely, linear arrays and rings, is analyzed in this paper. the algorithm spreads newly created tree nodes to neighboring processors, which actually provides randomized dilation-1 tree embedding in a static network. we develop linear systems of equations that characterize expected loads on all processors, and find their closed form solutions under the reproduction tree model, which can generate trees of arbitrary size and shape. the main contribution of the paper is to show that the above simple randomized algorithm is able to generate high-quality dynamic tree embeddings even in very simple and sparse networks such as linear arrays, and rings. in particular, we prove that as tree size becomes large, the asymptotic performance ratio of such a randomized dilation-1 tree embedding is n/(n-1) in linear arrays and is optimal in rings.
decompositions for the edge colouring of reduced indifference graphs. the chromatic index problem--finding the minimum number of colours required for colouring the edges of a graph--is still unsolved for indifference graphs, whose vertices can be linearly ordered so that the vertices contained in the same maximal clique are consecutive in this order. we present new positive evidence for the conjecture: every non neighbourhood-overfull indifference graph can be edge coloured with maximum degree colours. two adjacent vertices are twins if they belong to the same maximal cliques. a graph is reduced if it contains no pair of twin vertices. a graph is overfull if the total number of edges is greater than the product of the maximum degree by ⌈n/2⌉, where n is the number of vertices. we give a structural characterization for neighbourhood-overfull indifference graphs proving that a reduced indifference graph cannot be neighbourhood-overfull. we show that the chromatic index for all reduced indifference graphs is the maximum degree. we present two decomposition methods for edge colouring reduced indifference graphs with maximum degree colours.
polynomial-time recognition of minimal unsatisfiable formulas with fixed clause-variable difference. a formula (in conjunctive normal form) is said to be minimal unsatisfiable if it is unsatisfiable and deleting any clause makes it satisfiable. the deficiency of a formula is the difference of the number of clauses and the number of variables. it is known that every minimal unsatisfiable formula has positive deficiency. until recently, polynomial-time algorithms were known to recognize minimal unsatisfiable formulas with deficiency 1 and 2. we state an algorithm which recognizes minimal unsatisfiable formulas with any fixed deficiency in polynomial time.
sense of direction in distributed computing. sense of direction is a property of labeled graphs which has been shown to have a definite impact on computability and complexity in systems of communicating entities, and whose applicability ranges from the analysis of graph classes to distributed object systems. the full consequences of this property are still not known; in fact, the ongoing investigations continue to bring new (often surprising) results, to establish unsuspected links with other research and/or application areas, and to pose more questions than they answer. the aim of this paper is to provide a view of the current status of research, describing some of the relevant results, and providing pointers to future research directions.
gathering of asynchronous robots with limited visibility. in this paper we study the problem of gathering a collection of identical oblivious mobile robots in the same location of the plane. previous investigations have focused mostly on the unlimited visibility setting, where each robot can always see all the others regardless of their distance.in the more difficult and realistic setting where the robots have limited visibility, the existing algorithmic results are only for convergence (towards a common point, without ever reaching it) and only for semi-synchronous environments, where robots' movements are assumed to be performed instantaneously.in contrast, we study this problem in a totally asynchronous setting, where robots' actions, computations, and movements require a finite but otherwise unpredictable amount of time. we present a protocol that allows anonymous oblivious robots with limited visibility to gather in the same location in finite time, provided they have orientation (i.e., agreement on a coordinate system).our result indicates that, with respect to gathering, orientation is at least as powerful as instantaneous movements.
computing on anonymous networks with sense of direction. sense of direction refers to a set of global consistency constraints of the local labeling of the edges of a network. sense of direction has a large impact on the communication complexity of many distributed problems. in this paper, we study the impact that sense of direction has on computability and we focus on anonymous networks. we establish several results. in particular, we prove that with weak sense of direction, the intuitive knowledge-computability hierarchy between levels of a priori structural knowledge collapses. a powerful implication is the formal proof that shortest path routing is possible in anonymous networks with sense of direction. we prove that weak sense of direction is computationally stronger than topological awareness. we also consider several fundamental problems; for each, we provide a complete characterization of the anonymous networks on which it is computable with sense of direction.
limiting distributions for additive functionals on catalan trees. additive tree functionals represent the cost of many divide-and-conquer algorithms. we derive the limiting distribution of the additive functionals induced by toll functions of the form (a) nα when α > 0 and (b) log n (the so-called shape functional) on uniformly distributed binary trees, sometimes called catalan trees. the gaussian law obtained in the latter case complements the central limit theorem for the shape functional under the random permutation model. our results give rise to an apparently new family of distributions containing the airy distribution (α = 1) and the normal distribution [case (b), and case (a) as α ↓ 0]. the main theoretical tools employed are recent results relating asymptotics of the generating functions of sequences to those of their hadamard product, and the method of moments.
exact and approximate balanced data gathering in energy-constrained sensor networks. we consider the problem of gathering data from a wireless multi-hop network of energy-constrained sensor nodes to a common base station. specifically, we aim to balance the total amount of data received from the sensor network during its lifetime against a requirement of sufficient coverage for all the sensor locations surveyed. our main contribution lies in formulating this balanced data gathering task, studying the effects of balancing, and proposing an approximation algorithm for the problem. based on an lp network flow formulation, we present experimental results on both optimal and approximate data routing designs, in open transmission ranges and with impenetrable obstacles between the nodes.
query by committee, linear separation and random walks. a long-standing goal in the realm of machine learning is to minimize sample-complexity, i.e. to reduce as much as possible the number of examples used in the course of learning. the active learning paradigm is one such method aimed at achieving this goal by transforming the learner from a passive participant in the information gathering process to an active one. vaguely speaking, the learner tries to minimize the number of labeled instances used in the course of learning, relaying also on unlabelled instances in order to acquire the needed information whenever possible. the reasoning comes from many real-life problems where the teacher's activity is an expensive resource (e.g. text categorization, part of speech tagging). the query by committee (qbc) (seung et al., query by committee, proceedings of the fifth workshop on computational learning theory, morgan kaufman, san mateo, ca, 1992, pp. 287-294) is an active learning algorithm acting in the bayesian model of concept learning (haussler et al., mach. learning 14 (1994) 83), i.e. it assumes that the concept to be learned is chosen according to some fixed and known distribution. trying to apply the qbc algorithm for learning the class of linear separators, one faces the problem of implementing the mechanism of sampling hypotheses (the gibbs oracle). the major problem is computational-complexity, since the straightforward monte carlo method takes exponential time. in this paper we address the problems involved in the implementation of such a mechanism. we show how to convert them to questions about sampling from convex bodies or approximating the volume of such bodies. similar problems have recently been solved in the field of computational geometry based on random walks. these techniques enable us to device efficient implementations of the qbc algorithm. we also give few improvements and corrections to the qbc algorithm, the most important one is dropping the bayes assumption when the concept classes possess a sort of symmetry property (which holds for linear separators). we draw attention to a useful geometric lemma which bounds the maximal radius of a ball contained in a convex body. finally, this paper exhibits a connection between random walks and certain machine learning notions such as ε-net and support vector machines.
the universe of propositional approximations. the idea of approximate entailment has been proposed by schaerf and cadoli [tractable reasoning via approximation, artif. intell. 74(2) (1995) 249-310] as a way of modelling the reasoning of an agent with limited resources. in that framework, a family of logics, parameterised by a set of propositional letters, approximates classical logic as the size of the set increases.the original proposal dealt only with formulas in clausal form, but in finger and wassermann [approximate and limited reasoning: semantics, proof theory, expressivity and control, j. logic comput. 14(2) (2004) 179-204], one of the approximate systems was extended to deal with full propositional logic, giving the new system semantics, an axiomatisation, and a sound and complete proof method based on tableaux. in this paper, we extend another approximate system by schaerf and cadoli, presented in a subsequent work [m. cadoli, m. schaerf, the complexity of entailment in propositional multivalued logics, ann. math. artif. intell. 18(1) (1996) 29-50] and then take the idea further, presenting a more general approximation framework of which the previous ones are particular cases, and show how it can be used to formalise heuristics used in theorem proving.
a comparison of three authentication properties. authentication is a slippery security property that has been formally defined only recently; among the recent definitions, two rather interesting ones have been proposed for the spi-calculus by (abadi and gordon (in: proc. concur'97, lecture notes in computer science, vol. 1243, springer, berlin, 1997, pp. 59-73; inform. and comput. 148(1) (1999) 1-70) and for csp by lowe (in: proc. 10th computer security foundation workshop, ieee press, 1997, pp. 31-43). on the other hand, in a recent paper (in: proc. world congr. on formal methods (fm'99), lecture notes in computer science, vol. 1708, springer, berlin, 1999, pp. 794-813), we have proved that many existing security properties can be seen uniformly as specific instances of a general scheme based on the idea of non-interference. the purpose of this paper is to show that, under reasonable assumptions, spi-authentication can be recast in this general framework as well, by showing that it is equivalent to the non-interference property called ndc of focardi and gorrieri (j. comput. security 3(1) (1994/1995) 5-33; ieee trans. software eng. 23(9) (199) 550-571). this allows for the comparison between such a property and the one based on csp, which was already recast under the general scheme of focardi and martinelli (1999).
compositionality of hennessy-milner logic by structural operational semantics. this paper presents a method for the decomposition of hml formulas. it can be used to decide whether a process algebra term satisfies a hml formula, by checking whether subterms satisfy certain formulas, obtained by decomposing the original formula. the method uses the structural operational semantics of the process algebra. the main contribution of this paper is the extension of an earlier decomposition method for the de simone format from the ph.d. thesis of larsen in 1986, to more general formats.
borel hierarchy and omega context free languages. we give in this paper additional answers to questions of lescow and thomas (a decade of concurrency, lecture notes in computer science, vol. 803, springer, berlin, 1994, pp. 583-621), proving topological properties of omega context free languages (ω-cfl) which extend those of o. finkel (theoret. comput. sci. 262 (1-2) (2001) 669-697): there exist some ω-cfl which are non borel sets and one cannot decide whether an ω-cfl is a borel set. we give also an answer to a question of niwinski (problem on ω-powers posed in the proceedings of the workshop "logics and recognizable sets, 1990") and of simonnet (automates et thérie descriptive, ph.d. thesis, université paris 7, 1992) about ω-powers of finitary languages, giving an example of a finitary context free language l such that lω is not a borel set. then we prove some recursive analogues to preceding properties: in particular one cannot decide whether an ω-cfl is an arithmetical set. finally we extend some results to context free sets of infinite trees.
ambiguity in omega context free languages. we extend the well-known notions of ambiguity and of degrees of ambiguity of finitary context free languages to the case of omega context free languages (ω-cfl) accepted by büchi or muller pushdown automata. we show that these notions may be defined independently of the büchi or muller acceptance condition which is considered. we investigate first properties of the subclasses of omega context free languages we get in that way, giving many examples and studying topological properties of ω-cfl of a given degree of ambiguity.
on omega context free languages which are borel sets of infinite rank. this paper is a continuation of the study of topological properties of omega context free languages (ω-cfl). we proved in (topological properties of omega context free languages, theoretical computer science, 262 (1-2) (2001) 669-697) that the class of ω-cfl exhausts the finite ranks of the borel hierarchy, and in (borel hierarchy and omega context free languages, theoretical computer science, to appear) that there exist some ω-cfl which are analytic but non borel sets. we prove here that there exist some omega context free languages which are borel sets of infinite (but not finite) rank, giving additional answer to questions of lescow and thomas [logical specifications of infinite computations in: "a decade of concurrency" (j.w. de bakker et al. (eds.), springer lncs 803 (1994) 583-621).
on the sensitivity of additive cellular automata in besicovitch topologies. we prove that additive cellular automata in the besicovitch topology that have a willson limit set of hausdorff dimension strictly bigger than 1 are sensitive to initial conditions.
number conserving cellular automata ii: dynamics. in this second part, we study the dynamics of the number conserving cellular automata. we give a classification which focuses on pattern divergence and chaoticity. moreover we prove that in the case of number-conserving cellular automata, surjectivity is equivalent to regularity. as a byproduct we obtain a strong characterization of the class of cellular automata with bounded evolutions on finite configurations.
on decidability properties of local sentences. local (first order) sentences, introduced by ressayre, enjoy very nice decidability properties, following from some stretching theorems stating some remarkable links between the finite and the infinite model theory of these sentences [j.-p. ressayre, formal languages defined by the underlying structure of their words, j. symbolic logic 53 (4) (1988) 1009-1026]. another stretching theorem of finkel and ressayre implies that one can decide, for a given local sentence ϕ and an ordinal α < ωω, whether ϕ has a model of order type α. this result is very similar to büchi's one who proved that the monadic second order theory of the structure (α, <), for a countable ordinal α, is decidable. it is in fact an extension of that result, as shown in [o. finkel, finite languages, theoret. comput. sci. 255 (1-2) (2001) 223-261] by considering the expressive power of monadic sentences and of local sentences over languages of words of length α. the aim of this paper is twofold. we wish first to attract the reader's attention on these powerful decidability results proved using methods of model theory and which should find some applications in computer science and we prove also here several additional results on local sentences.the first one is a new decidability result in the case of local sentences whose function symbols are at most unary: one can decide, for every regular cardinal ωα (the αth infinite cardinal), whether a local sentence ϕ has a model of order type ωα.secondly we show that this result cannot be extended to the general case. assuming the consistency of an inaccessible cardinal we prove that the set of local sentences having a model of order type ω2 is not determined by the axiomatic system zfc + gch, where gch is the generalized continuum hypothesis.next we prove that for all integers n, p ≥ 1, if n < p then the local theory of ωn, i.e. the set of local sentences having a model of order type ωn, is recursive in the local theory of ωp and also in the local theory of α where α is any ordinal of cofinality ωn.
better-quasi-orderings and coinduction. we can characterise the class of bqos as the largest class of well-founded quasiorders closed under the hoare powerdomain construction and colimits.
on the smallest possible dimension and the largest possible margin of linear arrangements representing given concept classes. this paper discusses theoretical limitations of classification systems that are based on feature maps and use a separating hyperplane in the feature space. in particular, we study the embeddability of a given concept class into a class of euclidean half spaces of low dimension, or of arbitrarily large dimension but realizing a large margin. new bounds on the smallest possible dimension or on the largest possible margin are presented. in addition, we present new results on the rigidity of matrices and briefly mention applications in complexity and learning theory.
independent triangles covering given vertices of a graph. let g be a simple graph of order n, k a positive integer with n&ge;3k and x a set of any k vertices of g. we show that if the minimum degree g)&ge;(n + k)=2, then g contains k independent triangles covering all vertices of x ; and if the minimum degree (g)&ge;(n+2k)=2, then g contains k independent triangles such that each triangle contains exactly one vertex of x . the bounds on the minimum degree of g in above results are sharp. some conjectures about independent triangles covering some given vertices are proposed.
a new framework for declarative programming. we propose a new framework for the syntax and semantics of weak hereditarily harrop logic programming with constraints, based on resolution over τ-categories: finite product categories with canonical structure.constraint information is directly built-in to the notion of signature via categorical syntax. many-sorted equational are a special case of the formalism which combines features of uniform logic programming languages (moduels and hypothetical implication) with those of constraint logic programming. using the cannoical structure supplied by τ-categories, we define a diagrammatic generalization of formulas, goals, programs and resolution proofs up to equality (rather than just up to isomorphism).we extend the kowalski-van emden fixed point interpretation, a cornerstone of declarative semantics, to an operational, non-ground, categorical semantics based on indexing over sorts and programs.we also introduce a topos-theoretic declarative semantics and show soundness and completeness of resolution proofs and of a sequent calculus over the categorical signature. we conclude with a discussion of semantic perspectives on uniform logic programming.
on the bahncard problem. in this paper, we generalize the ski-rental problem to the bahncard problem which is an online problem of practical relevance for all travelers. the bahncard is a railway pass of the deutsche bundesbahn (the german railway company) which entitles its holder to a 50% price reduction on nearly all train tickets. it costs 240dm, and it is valid for 12 months. similar bus or railway passes can be found in many other countries. for the common traveler, the decision at which time to buy a bahncard is a typical online problem, because she usually does not know when and where she will travel next. we show that the greedy algorithm applied by most travelers and clerks at ticket offices is not better in the worst case than the trivial algorithm which never buys a bahncard. we present two optimal deterministic online algorithms, an optimistic one and a pessimistic one. we further give a lower bound for randomized online algorithms and present an algorithm which we conjecture to be optimal; a proof of the conjecture is given for a special case of the problem. it turns out that the optimal competitive ratio only depends on the price reduction factor (50% for the german bahncard problem), but does not depend on the price or validity period of a bahncard. copyright 2001 elsevier science b.v.
determination of equivalence between quantum sequential machines. quantum sequential machines (qsms) that may be viewed as a quantum variant of stochastic sequential machines (ssms) are one of the important quantum computing models. a very crucial result on ssms is that two ssms with n and n' states, respectively, and the same input and output alphabets are equivalent if and only if they are (n + n' - 1)-equivalent. therefore, gudder asked whether or not it holds for qsms, as an open problem in this direction, since the further study is closely related to this result. qiu demonstrated that in qsms this result does not hold, and therefore answered in part the problem. however, as qiu indicated, the sufficient and necessary conditions for the equivalence between two qsms are still not discovered. in this paper, we show that if the condition of (n + n' -1)-equivalence is appropriately relaxed, then we can give a sufficient and necessary condition for justifying the equivalence between two qsms. more precisely, we show that any two qsms m and m' are equivalent if and only if they are (n + n')2-equivalent, where n and n' are, respectively, the numbers of states in m and m'. we therefore solve the open problem suggested by gudder, and provide a basic result for further developing qsms. as well, we discuss strongly factorizable qsms and present the conditions for the equivalence between two strongly factorizable qsms.
from hopfield nets to recursive networks to graph machines: numerical machine learning for structured data. the present paper is a short survey of the development of numerical learning from structured data, an old problem that was first addressed by the end of the years 1980, and has recently undergone exciting developments, both from a theoretical point of view and for applications. traditionally, numerical machine learning deals with unstructured data, in the form of vectors: neural networks, graphical models, support vector machines, handle vectors of features that are assumed to be relevant for solving the problem at hand (classification or regression). it is often the case, however, that data is structured, i.e. is in the form of graphs; three examples will be described here: prediction of the properties of molecules, image analysis, and natural language processing. the traditional approach consists in handcrafting a vector representation of the structured data (features describing the molecules, "bag of words" for language processing), and subsequently training a machine to perform the task from that representation. by contrast, we describe here a family of approaches (raams, lraams, recursive or folding networks, graph machines) that are specifically designed to learn from structured data. we show that, despite the apparent diversity, two basic principles underlie the recent approaches: first, use structured machines to learn structured data; second, learn representations instead of handcrafting them; although neither principle is really new, they proved very successful for handling structured data, to the point of generating a novel branch of numerical machine learning.
one complexity theorist's view of quantum computing. the complexity of quantum computation remains poorly understood. while physicists attempt to find ways to create quantum computers, we still do not have much evidence one way or the other as to how useful these machines will be. the tools of computational complexity theory should come to bear on these important questions.quantum computing often scares away many potential researchers in computer science because of the apparent background need in quantum mechanics and the alien looking notation used in papers on the topic.this paper will give an overview of quantum computation from the point of view of a complexity theorist. we will see that one can think of bqp as yet another complexity class and study its power without focusing on the physical aspects behind it.
linear tolls suffice: new bounds and algorithms for tolls in single source networks. we show that tolls that are linear in the latency of the maximum latency path are necessary and sufficient to induce heterogeneous network users to independently choose routes that lead to traffic with minimum average latency. this improves upon the earlier bound of o(n3lmax) given by cole, dodis, and roughgarden in stoc 03. (here, n is the number of nodes in the network; and lmax is the maximum latency of any edge.) our proof is also simpler, relating the nash flow to the optimal flow as flows rather than cuts.we model the set of users as the set [0, 1] ordered by their increasing willingness to pay tolls to reduce latency--their valuation of time. cole et al. give an algorithm that computes optimal tolls for a bounded number of agent valuations, under the very strong assumption that they know which path each user type takes in the nash flow imposed by these (unknown) tolls. we show that in series parallel graphs, the set of paths traveled by users in any nash flow with optimal tolls is independent of the distribution of valuations of time of the users. in particular, for any continuum of users (not restricted to a finite number of valuation classes) in series parallel graphs, we show how to compute these paths without knowing α.we give a simple example to demonstrate that if the graph is not series parallel, then the set of paths traveled by users in the nash flow depends critically on the distribution of users' valuations of time.
domains in h. we give various internal descriptions of the category &ohgr;-cpo of &ohgr;-complete posets and &ohgr;-continuous functions in the model h of synthetic domain theory introduced in fiore and rosolini (j. pure appl. algebra 116 (1997) 151-162). it follows that the &ohgr;-cpos lie between the two extreme synthetic notions of domain given by repleteness and well-completeness.
combining word problems through rewriting in categories with products. we give an algorithm solving combined word problems (over non-necessarily disjoint signatures) based on rewriting of equivalence classes of terms. the canonical rewriting system we introduce consists of few transparent rules and is obtained by applying knuth-bendix completion procedure to presentations of pushouts among categories with products. it applies to pairs of theories which are both constructible over their common reduct (on which we do not make any special assumption).
cellular automata and strongly irreducible shifts of finite type. if a is a finite alphabet and γ is a finitely generated amenable group, ceccherini-silberstein, machì and scarabotti have proved that a local transition function defined on the full shift aγ is surjective if and only if it is pre-injective; this equivalence is the so-called garden of eden theorem. on the other hand, when γ is the group of the integers, the theorem holds in the case of irreducible shifts of finite type as a consequence of a theorem of lind and marcus but it no longer holds in the two-dimensional case.recently, gromov has proved a goe-like theorem in the much more general framework of the spaces of bounded propagation. in this paper we apply gromov's theorem to our class of spaces proving that all the properties required in the hypotheses of this theorem are satisfied.we give a definition of strong irreducibility that, together with the finite-type condition, it allows us to prove the goe theorem for the strongly irreducible shifts of finite type in aγ (provided that γ is amenable). finally, we prove that the bounded propagation property for a shift is strictly stronger than the union of strong irreducibility and finite-type condition.
the directed subgraph homeomorphism problem. the set of pattern graphs for which the directed subgraph homeomorphism problem is np-complete is characterized. a polynomial time algorithm is given for the remaining cases. the restricted problem where the input graph is a directed acyclic graph is in polynomial time for all pattern graphs and an algorithm is given.
semiretracts--a counterexample and some results. in the paper (theoret. comput. sci. 237 (2000)) anderson present a theorem which characterizes any semiretract s by means of two retracts rα and rω. the first part of the paper contains a counterexample for this characterization. then some results are presented which finally lead to the theorem which determines for a given semiretract s the minimal number of retracts r1,...,rm such that the equality s = ∩i=1m ri holds.
incremental algorithms for facility location and -median. in the incremental versions of facility location and k-median, the demand points arrive one at a time and the algorithm maintains a good solution by either adding each new demand to an existing cluster or placing it in a new singleton cluster. the algorithm can also merge some of the existing clusters at any point in time.for facility location, we consider the case of uniform facility costs, where the cost of opening a facility is the same for all points, and present the first incremental algorithm which achieves a constant performance ratio. using this algorithm as a building block, we obtain the first incremental algorithm for k-median which achieves a constant performance ratio using o(k) medians.the algorithm is based on a novel merge rule which ensures that the algorithm's configuration monotonically converges to the optimal facility locations according to a certain notion of distance. using this property, we reduce the general case to the special case when the optimal solution consists of a single facility.
selfish unsplittable flows. what is the price of anarchy when unsplittable demands are routed selfishly in general networks with load-dependent edge delays? motivated by this question we generalize the model of koutsoupias and papadimitriou (worst-case equilibria, in: proc. of the 16th annual symp. on theoretical aspects of computer science (stacs '99), lecture notes in computer science, vol. 1563, springer, berlin, 1999, pp. 404-413) to the case of weighted congestion games. we show that varying demands of users crucially affect the nature of these games, which are no longer isomorphic to exact potential games, even for very simple instances. indeed we construct examples where even a single-commodity (weighted) network congestion game may have no pure nash equilibrium.on the other hand, we prove that any weighted network congestion game with linear edge delays admits a pure nash equilibrium that can be found in pseudo-polynomial time. finally, we consider the family of l-layered networks and give a surprising answer to the question above: the price of anarchy of any weighted congestion game in a l-layered network with m edges and edge delays equal to the loads is θ(log m/log log m).
radiocoloring in planar graphs: complexity and approximations. the frequency assignment problem (fap) in radio networks is the problem of assigning frequencies to transmitters, by exploiting frequency reuse while keeping signal interference to acceptable levels. the fap is usually modelled by variations of the graph coloring problem. a radiocoloring (rc) of a graph g(v, e) is an assignment function φ : v → n such that |φ(u) - φ(v) | ≥ 2, when u, v are neighbors in g, and |φ(u) - φ(v)| ≥ 1 when the distance of u, v in g is two. the number of discrete frequencies and the range of frequencies used are called order and span, respectively. the optimization versions of the radiocoloring problem (rcp) are to minimize the span or the order. in this paper we prove that the radiocoloring problem for general graphs is hard to approximate (unless np = zpp) within a factor of n1/2-ε (for any ε > 0), where n is the number of vertices of the graph. however, when restricted to some special cases of graphs, the problem becomes easier. we prove that the min span rcp is np-complete for planar graphs. next, we provide an o(nδ) time algorithm (|v| = n) which obtains a radiocoloring of a planar graph g that approximates the minimum order within a ratio which tends to 2 (where δ the maximum degree of g). finally, we provide a fully polynomial randomized approximation scheme (fpras) for the number of valid radiocolorings of a planar graph g with λ colors, in the case where λ ≥ 4δ + 50.
the one-dimensional ising model: mutation versus recombination. the investigation of genetic and evolutionary algorithms on ising model problems gives much insight into how these algorithms work as adaptation schemes. the one-dimensional ising model with periodic boundary conditions has been considered as a typical example with a clear building block structure suited well for two-point crossover. it has been claimed that gas based on recombination and appropriate diversity-preserving methods by far outperform eas based on mutation only. here, a rigorous analysis of the expected optimization time proves that mutation-based eas are surprisingly effective. the (1 +λ) ea with an appropriate λ-value is almost as efficient as typical gas. moreover, it is proved that specialized gas do even better and this holds for two-point crossover as well as for one-point crossover.
intersection number and topology preservation within digital surfaces. in this paper, we prove a new result of digital topology which states that the digital fundamental groupa notion previously introduced by kong (comput. graphics 13 (1989) 159-166)is sufficient to characterize topology preservation within digital surfaces. this proof involves a new tool for proving theorems in this field: the intersection number which counts the number of real intersections between two surfels loops lying on a digital surface. the main property of the intersection number and the reason why it is useful is the following: the intersection number between two paths does not change after any continuous deformation applied to the paths.
cryptographic limitations on parallelizing membership and equivalence queries with applications to random-self-reductions. we assume wlog that every learning algorithm with membership and equivalence queries proceeds in rounds. in each round it puts in parallel a polynomial number of queries and after receiving the answers, it performs internal computations before starting the next round. the query depth is defined by the number of rounds. in this paper we show that, assuming the existence of cryptographic one-way functions, for any fixed polynomial d(n) there exists a concept class that is efficiently and exactly learnable with membership queries in query depth d(n)+1, but cannot be weakly predicted with membership and equivalence queries in depth d(n). hence, concerning the query depth, efficient learning algorithms for this concept class cannot be parallelized. we also discuss applications to random-self-reductions and coherent sets. copyright 2001 elsevier science b.v. all rights reserved.
bisimulations in the join-calculus. we develop a theory of bisimulations in the join-calculus. we introduce a refined operational model that makes interactions with the environment explicit, and discuss the impact of the lexical scope discipline of the join-calculus on its extensional semantics. we propose several formulations of bisimulation and establish that all formulations yield the same equivalence. we prove that this equivalence is finer than barbed congruence, but that both relations coincide in the presence of name matching. copyright 2001 elsevier science b.v.
on maximizing the throughput of multiprocessor tasks. we consider the problem of scheduling n independent multiprocessor tasks with due dates and unit processing times, where the objective is to compute a schedule maximizing the throughput. we derive the complexity results and present several approximation algorithms. for the parallel variant of the problem, we introduce the first-fit increasing algorithm and the latest-fit increasing algorithm, and prove that their worst-case ratios are 2 and 2 - 1/m, respectively (m ≥ 2 is the number of processors). then we propose a revised algorithm with a worst-case ratio bounded by 3/2- 1/(2m) (m is odd) and 3/2-1/(2m-2) (m is even). for the dedicated variant, we present a simple greedy algorithm. we show that its worst-case ratio is bounded by √m + 1. we straighten this result by showing that the problem cannot be approximated within a factor of m1/2-ε for any ε > 0, unless np = zpp.
combinatorics of perfect matchings in plane bipartite graphs and application to tilings. let g be a plane bipartite graph which admits a perfect matching and with distinguished faces called holes. let mg denote the perfect matchings graph: its vertices are the perfect matchings of g, two of them being joined by an edge, if and only if they differ only on an alternating cycle bounding a face which is not a hole. we solve the following problem: find a criterion for two perfect matchings of g to belong to the same connected component of mg and in particular determine in which case mg is connected. the motivation of this work is a result on tilings of saldanha et al. (comput. geom. 14 (1995) 207).
a weakly mixing tiling dynamical system with a smooth model. we describe a weakly mixing one-dimensional tiling dynamical system in which the tiling space is modeled by a surface m of genus 2. the tiling system satisfies an inflation, and the inflation map is modeled by a pseudo-anosov diffeomorphism d on m. the expansion coefficient θ for d is a non-pisot number. in particular, the leaves of the expanding foliation for d are tiled by their visits to the elements of a markov partition for d. the tiling dynamical system is an almost 1:1 extension of the unit speed flow along these leaves.
arrays, numeration systems and frankenstein games. we define an infinite array a of nonnegative integers based on a linear recurrence, whose second row provides basis elements of an exotic ternary numeration system. using the numeration system we explore many properties of a. further, we propose and analyze a family frankenstein of 2-player pebbling games played on a semi-infinite strip, and present a winning strategy based on certain subarrays of a. though the strategy looks easy, it is actually computationally hard. the numeration system is then used to decide whether the family has an efficient strategy or not.
complexity, appeal and challenges of combinatorial games. studying the precise nature of the complexity of games enables gamesters to attain a deeper understanding of the difficulties involved in certain new and old open game problems, which is a key to their solution. for algorithmicians, such studies provide new interesting algorithmic challenges, substantiations of these assertions are illustrated on hand of many sample games, leading to a definition of the tractability, polynomiality and efficiency of subsets of games. in particular, there are tractable games that need not be polynomial, polynomial games that need not be efficient. we also define and explore the nature of the subclasses playgames and mathgames.
the essence of ideal completion in quantitative form. if a poset lacks joins of directed subsets, one can pass to its ideal completion. but doing this means also changing the setting: the universal property of ideal completion of posets suggests that it should be regarded as a functor from the category of posets with monotone maps to the category of dcpos with scott-continuous functions as morphisms. the same applies for the quantitative version of ideal completion suggested in the literature. as in the case of posets, it seems advantageous to consider a different topology with the completed spaces. we introduce topological v-continuity spaces and their smyth completion and show that this is an adequate setting to consider ideal completion of quantitative domains: performing the smyth completion of a v-continuity space regarded as topological v-continuity space gives the ideal completion of the original space together with its scott topology.
adjoining to wythoff's game its -positions as moves. a rewarding method for generating a new game g>sub<i+1>/sub< from a known game g>sub/sub< is to adjoin an appropriate subset of the p-positions (2nd player winning positions) of g>sub/sub< to g>sub<i+1>/sub< as moves. we illustrate this statement by adjoining to the generalized wythoff game three subsets of its p-positions as moves, resulting in three different classes of games. we analyze these classes, characterizing the p-positions of some and exhibiting equivalences between others.
new results for online page replication. we study the online page replication problem. we present a new randomized online algorithm for rings which is 2.37297-competitive, improving the best previous result of 3.16396. we also show that no randomized online algorithm is better than 1.75037-competitive on the ring; previously, only a 1.58198 bound for a single edge was known. we extend the problem in several new directions: continuous metrics, variable size requests, and replication before service. this yields simplified proofs of several known results.
on the robustness of interconnections in random graphs: a symbolic approach. graphs are models of communication networks. this paper applies symbolic combinatorial techniques in order to characterize the interplay between two parameters of a random graph, namely its density (the number of edges in the graph) and its robustness to link failures. here, robustness means multiple connectivity by short disjoint paths: a triple (g,s,t), where g is a graph and s, t are designated vertices, is called l-robust if s and t are connected via at least two edge-disjoint paths of length at most l. we determine the expected number of ways to get from s to t via two edge-disjoint paths of length l in the classical random graph model gn.p by means of "symbolic" combinatorial methods. we then derive bounds on related threshold probabilities as functions of l and n.
the scientific works of rainer kemp (1949-2004). this short note presents a summary of the scientific contributions of rainer kemp (1949-2004) in the area of discrete mathematics, combinatorial enumeration, and analysis of algorithms. a complete bibliography of kemp's publications is included.
the exact number of squares in fibonacci words. all our words (sequences) are binary. a square is a subword of the form uu (concatenation). two squares are distinct if they are of different shape, not just translates of each other. otherwise they are repeated. fibonacci words are defined by f>sub<0>/sub< = 0, f>sub<1>/sub< = 1, f>sub<m>/sub< = f>sub<m-1>/sub<f>sub<m-2>/sub< for m ? 2. let f>sub<m>/sub< = |f>sub<m>/sub<|. then f>sub<0>/sub< = 1, f>sub<1>/sub< = 1, f>sub<m>/sub< = f>sub<m-1>/sub<+f>sub<m-2>/sub< (m ? 2) are the fibonacci numbers. let d(n) and r(n) be the exact number of distinct and repeated squares respectively in f>sub<n>/sub<. we prove: d(n) = 2(f>sub<n-2>/sub<-1) (n ? 5), which implies, asymptotically, d(n) = 2(2-j)f>sub<n>/sub<+o(1)&#x00a0;&#x00a0;&#x00a0; (2(2-j) < 0.7639), where j is the golden section. we also prove: r(n) = 4/>sub<5>/sub< nf>sub<n>/sub<-2/>sub<5>/sub< (n+6)f>sub<n-1>/sub<-f>sub<n-2>/sub<+n+1 (n ? 3). this yields r(n) = 2/>sub<5>/sub< (3-j)nf>sub<n>/sub<+o(f>sub<n>/sub<) = [(2(3-j))/( 5log>sub<2>/sub< j)]f>sub<n>/sub<log>sub<2>/sub< f>sub<n>/sub<+o(f>sub<n>/sub<) &#x00a0;&#x00a0;&#x00a0; ([(2(3-j))/( 5log>sub<2>/sub< j)] < 0.7962).
d2b: a de bruijn based content-addressable network. we show that the de bruijn graph is appropriate for maintaining dynamic connections, e.g., between the members of a p2p application who join and leave the system at their convenience. we describe the content-addressable network d2b, based on an overlay network preserving de bruijn connections dynamically, and on a distributed hash table (dht) supporting efficient publish and search procedures. the overlay network has constant expected degree, and any publish or search operation in the dht takes a logarithmic expected number of steps.
graph exploration by a finite automaton. a finite automaton, simply referred to as a robot, has to explore a graph whose nodes are unlabeled and whose edge ports are locally labeled at each node. the robot has no a priori knowledge of the topology of the graph or of its size. its task is to traverse all the edges of the graph. we first show that, for any k-state robot and any d ≥ 3, there exists a planar graph of maximum degree d with at most k + 1 nodes that the robot cannot explore. this bound improves all previous bounds in the literature. more interestingly, we show that, in order to explore all graphs of diameter d and maximum degree d, a robot needs ω(d log d) memory bits, even if we restrict the exploration to planar graphs. this latter bound is tight. indeed, a simple dfs up to depth d + 1 enables a robot to explore any graph of diameter d and maximum degree d using a memory of size o(d log d) bits. we thus prove that the worst case space complexity of graph exploration is θ(d log d) bits.
rush hour is pspace-complete, or "why you should generously tip parking lot attendants". rush hour is a children's game that consists of a grid board, several cars that are restricted to move either vertically or horizontally (but not both), a special target car, and a single exit on the perimeter of the grid. the goal of the game is to find a sequence of legal moves that allows the target car to exit the grid. we consider a slightly generalized version of the game that uses an nn grid and assume that we can place the single exit and target car at any location we choose on initialization of the game. in this work, we show that deciding if the target car can legally exit the grid is pspace-complete. our constructive proof uses a lazy form of dual-rail reversible logic such that movement of "output" cars can only occur if logical combinations of "input" cars can also move. emulating this logic only requires three types of devices (two switches and one crossover); thus, our proof technique can be easily generalized to other games and planning problems in which the same three primitive devices can be constructed.
an algebraic characterization of deterministic regular languages over infinite alphabets. we state and prove an infinite alphabet counterpart of the classical myhill-nerode theorem.
on routing of wavebands for all-to-all communications in all-optical paths and cycles. we discuss a model of the all-optical communication technology and an implementation of a simple task, all-to-all, in simple topologies like paths and cycles. the model assumes a single interval (variant of band-pass) filter extracting signal wavelengths for processing and forwarding in intermediate communication nodes. in an attempt to use a minimum number of wavelengths, we give lower and upper bounds on the cardinality of the spectrum used in four cases arising from different assumptions on the topology and the filters. in particular, we propose efficient schedules of directed paths between all pairs of nodes in graphs of maximum node degree two, under the assumption of either a "linear" or "wrapped-around" wavelength spectrum.
semi-dynamic breadth-first search in digraphs. when creating a family of systems, i.e. several systems of similar type which differ within some aspects, it is desirable to be able to express these differences already at the level of the specification, and to automatically obtain systems from it which are ready to run. the use of generic methods may lead to substantial progress in this area. this report explores two aspects: parameterization concepts at the specification level, which can be used to describe variants of a system, and generator programs, which produce runnable systems from prefabricated components.
modular verification of multithreaded programs. multithreaded software systems are prone to errors due to the difficulty of reasoning about multiple interleaved threads operating on shared data. static checkers that analyze a program's behavior over all execution paths and all thread interleavings are a powerful approach to identifying bugs in such systems. in this paper, we present calvin, a scalable and expressive static checker for multithreaded programs based on automatic theorem proving. to handle realistic programs, calvin performs modular checking of each procedure called by a thread using specifications of other procedures and other threads. our experience applying calvin to several real-world programs indicates that calvin has a moderate annotation overhead and can catch common defects in multithreaded programs, such as synchronization errors and violations of data invariants.
results related to threshold phenomena research in satisfiability: lower bounds. we present a history of results related to the threhold phenomena which arise in the study of random conjunctive normal form (cnf) formulas. in a companion paper (d. achlioptas, theoret. comput. sci., this volume) the major ideas used to achieve many of the lower bounds results on the location of the threshold are described in an informal, intuitive manner.
efficient algorithms for robustness in resource allocation and scheduling problems. the robustness function of an optimization (minimization) problem measures the maximum increase in the value of its optimal solution that can be produced by spending a given amount of resources increasing the values of the elements in its input. we present efficient algorithms for computing the robustness function of resource allocation and scheduling problems that can be modeled with partition and scheduling matroids. for the case of scheduling matroids, we give an o(m2n2) time algorithm for computing a complete description of the robustness function, where m is the number of elements in the matroid and n is its rank. for partition matroids, we give two algorithms: one that computes the complete robustness function in o(m log m) time, and other that optimally evaluates the robustness function at only a specified point.
sequential and indexed two-dimensional combinatorial template matching allowing rotations. we present new and faster algorithms to search for a two-dimensional pattern in a two-dimensional text allowing any rotation of the pattern. this has applications such as image databases and computational biology. we consider the cases of exact and approximate matching under several matching models, using a combinatorial approach that generalizes string matching techniques. we focus on sequential algorithms, where only the pattern can be preprocessed, as well as on indexed algorithms, where the text is preprocessed and an index built on it. on sequential searching we derive average-case lower bounds and then obtain optimal average-case algorithms for all the matching models. at the same time, these algorithms are worst-case optimal. on indexed searching we obtain search time polylogarithmic on the text size, as well as sublinear time in general for approximate searching.
computationally universal p systems without priorities: two catalysts are sufficient. the original model of p systems with symbol objects introduced by paun was shown to be computationally universal, provided that catalysts and priorities of rules are used. by reduction via register machines sosík and freund proved that the priorities may be omitted from the model without loss of computational power. freund, oswald, and sosík considered several variants of p systems with catalysts (but without priorities) and investigated the number of catalysts needed for these specific variants to be computationally universal. it was shown that for the classic model of p systems with the minimal number of two membranes the number of catalysts can be reduced from six to five; using the idea of final states the number of catalysts could even be reduced to four. in this paper we are able to reduce the number of catalysts again: two catalysts are already sufficient. for extended p systems we even need only one membrane and two catalysts. for the (purely) catalytic systems considered by ibarra only three catalysts are already enough.
from regulated rewriting to computing with membranes: collapsing hierarchies. in addressing certain problems about membrane computing, a recent and active branch of natural computing, it first was necessary to address certain problems from the area of regulated rewriting. thus, the present paper is a contribution to both these domains.a central problem in membrane computing is that of the hierarchy with respect to the number of membranes: are systems with n + 1 membranes more powerful than systems with n membranes? does the number of membranes induce an infinite hierarchy of the computed functions? usually, when proving the universality of membrane systems (also called p systems), one starts from a matrix grammar and the number of membranes depends on the number of non-terminal symbols used by this grammar in the so-called appearance checking mode. we first prove that recursively enumerable languages can be generated by matrix grammars with only two non-terminal symbols being used in the appearance checking mode. the proofs of this fact and of several related results are based on a simulation of register machines by means of graph-controlled grammars.then, we consider three classes of membrane systems, and in all the three cases the hierarchies with respect to the number of membranes are shown to collapse at level four: systems with four membranes are computationally universal (but we do not know whether or not this result is optimal).
tissue p systems with channel states. we consider tissue-like p systems with states associated with the links (we call them synapses) between cells, controlling the passage of objects across the links. we investigate the computing power of such devices for the case of using--in a sequential manner--antiport rules of small weights. systems with two cells are proved to be universal when having arbitrarily many states and minimal antiport rules, or one state and antiport rules of weight two. also the systems with arbitrarily many cells, three states, and minimal antiport rules are universal. in contrast, the systems with one cell and any number of states and rules of any weight only compute parikh sets of matrix languages (generated by matrix grammars without appearance checking); characterizations of parikh images of matrix languages are obtained for such one-cell systems with antiport rules of a reduced weight.
satisfying subtype inequalities in polynomial space. this paper studies the complexity of type inference in &lgr;-calculus with subtyping. infering types is equivalent to solving systems of subtype inequalities. these inequalities are solved over simple types ordered structurally from an arbitrary set of base subtype assumptions. in this case, we give a new pspace upper bound. together with the previously known lower bound, this result settles completely the complexity of the problem, which is pspace-complete. we use a technique of independent theoretical interest that simplifies existing methods developed in the literature. finally, we show how our polynomial space algorithm, although mainly theoretical, can lead to a slight practical improvement of existing implementations. copyright 2002 elsevier science b.v.
finite-state transducer cascades to extract named entities in texts. a lot of named entity extraction systems were created in english thanks to the impulse of muc conferences. this article describes a finite-state transducer cascade for the extraction of named entities in french journalistic texts. finite-state cascades are widely used for natural language processing: a cascade is a series of finite-state transducers applied to a text transforming it. such transducer cascades allow implementation of syntactic analysis, translation memory and information extraction. we present our general system named cassys: this system uses the intex natural language processing features to realize a transducer cascade. cassys is not dedicated to the extraction of named entity; we use it for this task but thanks to intex, it allows syntactic analyses, information extraction or other tasks.
arithmetical complexity of symmetric d0l words. we characterize and count words which occur in arithmetical subsequences of fixed points of symmetric morphisms.
sequences of linear arithmetical complexity. arithmetical complexity of infinite sequences is the number of all words of a given length whose symbols occur in the sequence at positions which constitute arithmetical progressions. we show that uniformly recurrent sequences whose arithmetical complexity grows linearly are precisely toeplitz words of a specific form.
data structures and algorithms for tilings i. based on the mathematical theory of delaney symbols, data structures and algorithms are presented for the analysis and manipulation of generalized periodic tilings in arbitrary dimensions.
a modal proof theory for final polynomial coalgebras. an infinitary proof theory is developed for modal logics whose models are coalgebras of polynomial functors on the category of sets. the canonical model method from modal logic is adapted to construct a final coalgebra for any polynomial functor. the states of this final coalgebra are certain "maximal" sets of formulas that have natural syntactic closure properties.the syntax of these logics extends that of previously developed modal languages for polynomial coalgebras by adding formulas that express the "termination" of certain functions induced by transition paths. a completeness theorem is proven for the logic of functors which have the lindenbaum property that every consistent set of formulas has a maximal extension. this property is shown to hold if the deducibility relation is generated by countably many inference rules.a counter-example to completeness is also given. this is a polynomial functor that is not lindenbaum: it has an uncountable set of formulas that is deductively consistent but has no maximal extension and is unsatisfiable, even though all of its countable subsets are satisfiable.
direct constructions of universal extended h systems. a direct universal extended h system receives as input the coding of an extended h system with a particular control mechanism and simulates it. we present a direct construction for five kinds of control for the extended h systems under consideration. it is the first time that a direct construction is described: universal results obtained until now were based on the simulation of universal type-0 grammars or turing machine.
the conformon-p system: a molecular and cell biology-inspired computability model. a new theoretical computational model, called conformon-p system, based on simple and basic concepts inspired from a theoretical model of the living cell and membrane computing is presented.the computational power of it and of some natural variants are studied.links with petri nets, reversible computation, other interpretations and variants of the model are briefly outlined.
hypothesis finding with proof theoretical appropriateness criteria. for two given formulae b and e with b≠e hypothesis finding means to produce a formula s such that b ∨ s ?? c. hypothesis finding, or variants thereof, is central to various types of inference, e.g., abductive inference, inductive inference, machine learning, and machine discovery. clarifying the nature of hypothesis finding is still in its infancy, a situation similar to the establishment of logical foundations of inference related to induction and discovery. although trivial solutions to hypothesis finding are easy to give, finding appropriate hypotheses still remains as a great challenge. a central role in this context plays the question, what it means for a hypothesis to be appropriate? in this paper we propose an answer to this question, which is based on proof theoretical criteria. this is in contrast to most previous approaches where appropriateness of hypotheses was based on concepts of semantical weakness in classical logic. more precisely, we use provability in relevance logic instead of classical semantical entailment, we demand utmost exploitation of the inferential potential (deductive content) inherent in b → c and we demand s to be a minimal deductive supplement to b → c. along these lines we developed the concept of a minimized residue hypothesis which also constitutes an interesting trade-off between 'logical smallness' and 'syntactical smallness'.
an introduction to periodical discrete sets from a tomographical perspective. in this paper we introduce a new class of binary matrices whose entries show periodical configurations, and we furnish a first approach to their analysis from a tomographical point of view. in particular we propose a polynomial-time algorithm for reconstructing matrices with a special periodical behavior from their horizontal and vertical projections. we succeeded in our aim by using a reduction involving polyominoes which can be characterized by means of 2 - sat formulas.
the np-completeness of a tomographical problem on bicolored domino tilings. in this paper we study the problem of reconstructing a bicolored domino tiling of a rectangular surface from its horizontal and vertical projections. we use a reduction from the np-complete problem numerical matching with target sums in order to prove that, unless p = np, this task cannot be performed in polynomial time. the reconstruction of monochromatic domino tilings is still open.
on-line digit set conversion in real base. let β be a real number > 1. the digit set conversion between real numbers represented in fixed base β is shown to be computable by an on-line algorithm, and thus is a continuous function. when β is a pisot number the digit set conversion is computable by an on-line finite automaton.
additive and multiplicative properties of point sets based on beta-integers. to each number β > 1 correspond abelian groups in rd, of the form λβ = σi=1d zβei, which obey βλβ ⊂ λβ. the set zβ of beta-integers is a countable set of numbers: it is precisely the set of real numbers which are polynomial in β when they are written in "basis β", and zβ = z when β ∈ n. we prove here a list of arithmetic properties of zβ: addition, multiplication, relation with integers, when β is a quadratic pisot-vijayaraghavan unit (quasicrystallographic inflation factors are particular examples). we also consider the case of a cubic pisot-vijayaraghavan unit associated with the seven-fold cyclotomic ring. at the end, we show how the point sets λβ are vertices of d-dimensional tilings.
conversation protocols: a formalism for specification and verification of reactive electronic services. this paper focuses on the realizability problem of a framework for modeling and specifying the global behaviors of reactive electronic services (e-services). in this framework, web accessible programs (peers) communicate by asynchronous message passing, and a virtual global watcher silently listens to the network. the global behavior is characterized by a "conversation", which is the infinite sequence of messages observed by the watcher. we show that given a büchi automaton specifying the desired set of conversations, called a "conversation protocol", it is possible to realize the protocol using a set of finite state peers if three realizability conditions are satisfied. in particular, the synthesized peers will conform to the protocol by generating only those conversations specified by the protocol. our results enable a top-down verification strategy where (1) a conversation protocol is specified by a realizable büchi automaton, (2) the properties of the protocol are verified on the büchi automaton specification, and (3) the peer implementations are synthesized from the protocol via projection.
tau laws for pi calculus. the paper investigates the nonsymbolic algebraic semantics of the weak bisimulation congruences on finite pi processes. the weak bisimulation congruences are studied both in the absence and in the presence of the mismatch operator. some interesting phenomena about the open congruences are revealed. several new tau laws are discovered and their relationship is discussed. the contributions of the paper are mainly as follows: 1. it is proved that milner's three tau laws fail to lift a complete system for the strong open congruence to a complete system for the weak open congruence in the absence of both the mismatch operator and the restriction operator. a fourth tau law is proposed to deal with the match operator under the prefix operation. it is shown that for this calculus a complete system for the strong open congruence extended with all the four tau laws is complete for the weak open congruence. 2. it is verified that the four tau laws are also enough for the weak open congruence of the pi calculus without the mismatch operator. a complete system using distinctions is given. 3. it is pointed out that the standard definition of the weak open congruence gives rise to a bad equivalence relation in the presence of the mismatch operator. two alternatives are proposed. these are the late open congruence and the early open congruence. their difference is similar to that between the weak late congruence and the weak early congruence. complete axiomatic systems for the two weak open congruences are given.
online matching on a line. given a set s ⊆ r of points on the line, we consider the task of matching a sequence (r1, r1,... ) of requests in r to points in s. it has been conjectured [online algorithms: the state of the art, lecture notes in computer science, vol. 1442, springer, berlin, 1998, pp. 268-280] that there exists a 9-competitive online algorithm for this problem, similar to the so-called "cow path" problem [inform. and comput. 106 (1993) 234-252]. we disprove this conjecture and show that no online algorithm can achieve a competitive ratio strictly less than 9.001.our argument is based on a new proof for the optimality of the competitive ratio 9 for the "cow path" problem.
time-minimal paths amidst moving obstacles in three dimensions. a path-planning problem is considered in the presence of moving polygonal obstacles in three dimensions. a particle is to be moved from a given initial position to a destination position amidst polygonal disjoint barriers moving along known linear trajectories. the particle can move in any direction in space with a single constraint that it cannot move faster than a given speed bound. all obstacles are slowly moving, i.e., their speeds are strictly slower than the maximum speed of the particle. the destination point is also permitted to move along a known trajectory and is assumed to be collision-free at all times. three properties are stated and proved for a time-minimal path amidst moving polygonal barriers. a few extensions are considered, including piecewise linear motions of the obstacle
two-dimensional on-line bin packing problem with rotatable items. in this paper, we consider a two-dimensional version of the on-line bin packing problem, in which each rectangular item that should be packed into unit square bins is "rotatable" by 90°. two on-line algorithms for solving the problem are proposed. the second algorithm is an extension of the first algorithms, and the worst-case ratio of the second one is at least 2.25 and at most 2.565.
notes on acyclic orientations and the shelling lemma. in this paper we study two lemmas on acyclic orientations and totally cyclic orientations of a graph, which can be derived from the shelling lemma in vector subspaces. we give simple graph theoretical proofs as well as a proof by the interpretations of the shelling lemma in the special setting of graphs. furthermore, we present similar interpretations of closely related theorems in vector subspaces, which do not seem to admit simple graph theoretical proofs.
a nim game played on graphs. we propose a new impartial game played by two players, which can be compared to the well-known nim game (winning ways for your mathematical plays, academic press, new york, 1982; on numbers and games, academic press, london and new york, 1976; combinatorial games: back and front, springer, tokyo, 1989) played on graphs. in this paper, we consider this game and investigate its winning strategies. in the proof, menger's theorem (graph theory, an introductory course, springer, new york, 1979) noted in graph theory plays a crucial role.
a nim game played on graphs ii. we consider a nim game played on graphs, which was proposed and was named nim on graphs in [4], and investigate its grundy number using matchings of graphs. especially, by virtue of this investigation, we can find the grundy number of nim on trees completely. another result is that the problem of finding the grundy number of nim on cycles is resolved into that of nim on trees. thus, we find also the grundy number of nim on cycles completely.
shape preserving top-down tree transducers. as top-down tree transducers generalize generalized sequential machines, shape preserving top-down tree transducers naturally generalize length preserving generalized sequential machines. for instance, top-down relabeling tree transducers are shape preserving top-down tree transducers. we show that a top-down tree transducer is shape preserving if and only if it is equivalent to a top-down relabeling tree transducer. we also prove that it is decidable if a top-down tree transducer is shape preserving.
hierarchies of tree series transformations. we study bottom-up and top-down tree series transducers over a semiring a and denote the tree series transformation classes computed by them by bott-ts(a) and topt-ts(a), respectively. we present the inclusion diagram of the classes p-bott-tsn(a), p-topt-tsn(a), p-botn+1t-ts(a), and p-topn+1t-ts(a) and prove its correctness, where a is a commutative izz-semiring (izz=idempotent, zero-divisor free, and zero-sum free) and the prefix p stands for polynomial. this inclusion diagram implies the properness of the following four hierarchies: p, topt-ts(a) ⊆ p-top2t-ts(a) ⊆ p-top3t-ts(a) ⊆ ..., p, bott-ts(a) ⊆ p-bot2t-ts(a) ⊆ p-bot3t-ts(a) ⊆ ..., p, topt-ts(a) ⊆ p-bot2t-ts(a) ⊆ p-top3t-ts(a) ⊆ p-bot4t-ts(a) ⊆ ..., p, bott-ts(a) ⊆ p-top2t-ts(a) ⊆ p-bot3t-ts(a) ⊆ p-top4t-ts(a) ⊆ ..., where the first hierarchy generalizes the famous top-down tree transformation hierarchy of engelfriet (math. systems theory 15 (1982) 92-125). as the second main result we prove that the first two hierarchies are proper even for arbitrary (i.e., not necessarily commutative) izz-semirings.
linear deterministic multi bottom-up tree transducers. in general, top-down and bottom-up tree transducers lead to incomparable classes of tree transformations, both for the nondeterministic and the deterministic case. if deterministic top-down tree transducers are extended by the capability to recognize regular tree properties and deterministic bottom-up tree transducers are generalized by allowing states with arbitrary finite rank, then the two devices, now called deterministic top-down tree transducers with regular look-ahead and deterministic multi bottom-up tree transducers, respectively, become equivalent [z. fülöp, a. kühnemann, h. vogler, a bottom-up characterization of deterministic top-down tree transducers with regular look-ahead, inform. process. lett. 91 (2004) 57-67].in this paper we focus on the class ld-mbot of tree transformations which are computed by linear deterministic multi bottom-up tree transducers. we investigate the relationship among ld-mbot and the classes of tree transformations computed by (restricted) deterministic bottom-up tree transducers and by (restricted) deterministic top-down tree transducers with regular look-ahead. in fact, we show the inclusion diagram of nine such classes.
iterated relabeling tree transducers. in this paper we consider the closure uci(rel) of the class of relabeling tree transformations, under u=union, c=composition and i=iteration. we give a characterization of uci(rel) in terms of a short expression built up from rel with composition and iteration. we also give a characterization of uci(rel) in terms of one-step rewrite relations of very simple term rewrite systems. we give a similar characterization of uc(frel+), where frel+ is the class consisting of the transitive closures of all functional relabeling tree transformations. finally we show that uci(rel)=uci(frel).
minimal length test vectors for multiple-fault detection. a methodology for circuit testing is proposed for detecting multiple circuit faults in the course of a minimal length "guided tour" of the circuit transition structure. deriving a test vector to guide this tour through an n state subsystem with at most i inputs possible in situ at each state, corresponds to solving an open tour multigraph version of the "chinese postman" problem, in which out-degrees are bounded by i. in this case, the length l of a minimal length open tour is shown to satisfy l ≤ in2; a minimal length open tour is computable in o(n3 + ni) steps for undirected multigraphs and o(n3 + (ni)2logn/logi) steps for directed multigraphs, both one-time costs, using weighted matching and bipartite weighted matching, respectively. an open tour can result in a test vector as much as ½ shorter than the test vector associated with a closed tour, without any loss in error detection. examples show that for a directed graph, the length of a minimal length open tour may be as great as n3/6 for i = n, or ω(n2) when i is bounded, while in an undirected multigraph, a minimal length tour requires no more than n - 3 repeated state transitions. this mitigates in favor of "mixed" circuits in which certain transitions are reversible and need be tested in only one direction.the practicality of this approach rests with the ability to apply it separately to small sub-systems, in conjunction with symbolic testing of inter-subsystem coordination. the former is feasible with existing commercial technologies, such as electron beam scanning, while the latter is feasible with a finite-state model-checker.in summary, the proposed methodology comprises three steps: 1. decompose a circuit into subsystems sufficiently small to be model-checked exhaustively; 2. perform symbolic tests of inter-subsystem coordination and conclude that if each subsystem is correctly implemented, then the entire circuit will behave as required; 3. for each circuit subsystem, exercise every realizable transition through a minimal length (open) tour, comparing the actual transitions with those of the specification.
deciding sequentiability of finite-state transducers by finite-state pattern-matching. sequentiality (input-side determinism) is a desirable property of finite-state transducers: such transducers are optimal for time efficiency. not all transducers are sequentiable and those that are may not be sequential. sequentialization algorithms of finite-state transducers do not recognize whether a transducer is sequentiable or not and simply do not ever halt when it is not. choffrut proved that sequentiality of finite-state transducers is decidable. béal et al. (in: d. gonnet, g. panario, a. viola (eds.), proceedings of latin 2000, lecture notes in computer science, vol. c1776, springer, heidelberg, 2000, p. 397) have proposed squaring to decide sequentiality. we propose a different procedure, which, with ε-closure extension, is able to handle letter transducers with arbitrary ε-ambiguities, too. our algorithm is more economical than squaring, in terms of size. in different cases of non-sequentiability, necessary and sufficient conditions of one of the four possible ambiguity classes of the transducer can be observed. these ambiguities can be mapped bijectively to particular basic patterns in the structure of the transducer. the non-presence of both the infinitely ambiguous and the unboundedly ambiguous patterns is the condition of sequentiability. these patterns can be recognized, using finite-state methods, in any transducer. the method shows both sequentiability and, if present, sequentiality on the given side of the transducer.
approximation algorithms for facility location problems with a special class of subadditive cost functions. in this article we focus on approximation algorithms for facility location problems with subadditive costs. as examples of such problems, we present three facility location problems with stochastic demand and exponential servers, respectively inventory. we present a (1 + ε, 1)-reduction of the facility location problem with subadditive costs to the soft capacitated facility location problem, which implies the existence of a 2(1 + ε)-approximation algorithm. for a special subclass of subadditive functions, we obtain a 2-approximation algorithm by reduction to the linear cost facility location problem.
linear constructions for dna codes. in this paper we translate in terms of coding theory constraints that are used in designing dna codes for use in dna computing or as bar-codes in chemical libraries. we propose new constructions for dna codes satisfying either a reverse-complement constraint, a gc-content constraint, or both, that are derived from additive and linear codes over four-letter alphabets. we focus in particular on codes over gf (4), and we construct new dna codes that are in many cases better (sometimes far better) than previously known codes. we provide updated tables up to length 20 that include these codes as well as new codes constructed using a combination of lexicographic techniques and stochastic search.
uniform test of algorithmic randomness over a general space. the algorithmic theory of randomness is well developed when the underlying space is the set of finite or infinite sequences and the underlying probability distribution is the uniform distribution or a computable distribution. these restrictions seem artificial. some progress has been made to extend the theory to arbitrary bernoulli distributions (by martin-löf) and to arbitrary distributions (by levin). we recall the main ideas and problems of levin's theory, and report further progress in the same framework. the issues are the following: • allow non-compact spaces (like the space of continuous functions, underlying the brownian motion). • the uniform test (deficiency of randomness) dp(x) (depending both on the outcome x and the measure p) should be defined in a general and natural way. • see which of the old results survive: existence of universal tests, conservation of randomness, expression of tests in terms of description complexity, existence of a universal measure, expression of mutual information as "deficiency of independence". • the negative of the new randomness test is shown to be a generalization of complexity in continuous spaces; we show that the addition theorem survives.the paper's main contribution is introducing an appropriate framework for studying these questions and related ones (like statistics for a general family of distributions).
comparing logics for rewriting: rewriting logic, action calculi and tile logic. the large diffusion of concurrent and distributed systems has spawned in recent years a variety of new formalisms, equipped with features for supporting an easy specification of such systems. the aim of our paper is to analyze three proposals, namely rewriting logic, action calculi and tile logic, chosen among those formalisms designed for the description of rule-based systems. for each of these logics we first try to understand their foundations, then we briefly sketch some applications. the overall goal of our work is to find out a common layout where these logics can be recast, thus allowing for a comparison and an evaluation of their specific features.
on separating the erew and crew pram models. in [6], snir proposed the selection problem (searching in a sorted table) to show that the crew pram is strictly more powerful than the erew pram. this problem defines a partial function, that is, one that is defined only on a restricted set of inputs. recognizing whether an arbitrary input belongs to this restricted set is hard for both crew and erew prams. the existence of a total function that exhibits the power of the crew model over the erew model was an open problem. here we solve this problem by generalizing the selection problem to a decision tree problem which is defined on a full domain and to which snir''s lower bound applies.
on the submodular matrix representation of a digraph. we reexamine the class of (0,±1) matrices called submodular, which we introduced in (ann. discrete math. 15 (1982) 189). our key idea in this paper is to define, for each submodular matrix m, a corresponding digraph g whose nodes are the columns of m. our principal results are as follows: (a) a graph-theoretic interpretation of the polyhedron p(m) = {x: x ≥ 0, mx ≥ - 1}, and (b) for a given g, the description of a submodular matrix contained in all submodular matrices representing g.
structure and complexity of extreme nash equilibria. we study extreme nash equilibria in the context of a selfish routing game. specifically, we assume a collection of n users, each employing a mixed strategy, which is a probability distribution over m parallel identical links, to control the routing of its own assigned traffic. in a nash equilibrium, each user selfishly routes its traffic on those links that minimize its expected latency cost. the social cost of a nash equilibrium is the expectation, over all random choices of the users, of the maximum, over all links, latency through a link.we provide substantial evidence for the fully mixed nash equilibrium conjecture, which states that the worst nash equilibrium is the fully mixed nash equilibrium, where each user chooses each link with positive probability. specifically, we prove that the fully mixed nash equilibrium conjecture is valid for pure nash equilibria. furthermore, we show, that under a certain condition, the social cost of any nash equilibrium is within a factor of 2h(1 + ε) of that of the fully mixed nash equilibrium, where h is the factor by which the largest user traffic deviates from the average user traffic.considering pure nash equilibria, we provide a ptas to approximate the best social cost, we give an upper bound on the worst social cost and we show that it is n p-hard to approximate the worst social cost within a multiplicative factor better than 2 - 2/(m + 1).
a format for semantic equivalence comparison. this paper presents a new format for process algebras, the extended tyft/tyxt format which generalises the tyft/tyxt format of groote and vaandrager. the format differs from most previous formats in that the labels on transitions are treated as many-sorted terms. bisimulation is a congruence for all operators defined by extended transition system specifications in this format.when one extended transition system specification is summed with another, the resulting bisimulation can either identify more terms (an abstracting extension up to bisimulation) or fewer terms (a refining extension up to bisimulation) than the original bisimulation on the individual system. the notions of abstracting extension and refining extension are defined, and two theorems are presented giving conditions required for achieving each type of extension. these results provide a way to compare different semantic equivalences defined for different process algebras.finally, an application of this theory to semantic equivalence comparison is given for a new result relating castellani's pomset equivalence and krishan's multiprocessor equivalence.
iterative bayes. naive bayes is a well-known and studied algorithm both in statistics and machine learning. bayesian learning algorithms represent each concept with a single probabilistic summary. in this paper we present an iterative approach to naive bayes. the iterative bayes begins with the distribution tables built by the naive bayes. those tables are iteratively updated in order to improve the probability class distribution associated with each training example. in this paper we argue that iterative bayes minimizes a quadratic loss function instead of the 0-1 loss function that usually applies to classification problems. experimental evaluation of iterative bayes on 27 benchmark data sets shows consistent gains in accuracy. an interesting side effect of our algorithm is that it shows to be robust to attribute dependencies.
prediction algorithms and confidence measures based on algorithmic randomness theory. this paper reviews some theoretical and experimental developments in building computable approximations of kolmogorov's algorithmic notion of randomness. based on these approximations a new set of machine learning algorithms have been developed that can be used not just to make predictions but also to estimate the confidence under the usual iid assumption.
characterization of networks supporting multi-dimensional linear interval routing schemes. an interval routing scheme (irs) is a well-known, space efficient routing strategy for routing messages in a distributed network. in this scheme, each node of the network is assigned an integer label and each link at each node is labeled with an interval. the interval assigned to a link e at a node v indicates the set of destination addresses of the messages which should be forwarded through e at v. a multi-dimensional interval routing scheme (mirs) is a generalization of irs in which each node is assigned a multi-dimensional label (which is a list of d integers for the d-dimensional case). the labels assigned to the links of the network are also multi-dimensional (a list of d 1-dimensional intervals). the class of networks supporting linear irs (in which the intervals are not cyclic) is already known for the one-dimensional case (13th annu. acm symp. principles of distributed computing (podc), acm press, new york, august 1994, pp. 216-224). in this paper, we generalize this result and completely characterize the class of networks supporting linear mirs (or mlirs) for a given number of dimensions d. we show that by increasing d, the class of networks supporting mlirs is strictly expanded. we also give a characterization of the class of networks supporting strict mlirs (which ia an mlirs is which the interval assigned to the links incident to a node v, does not contain the label of v).
state space reduction for process algebra specifications. data-flow analysis to identify "dead" variables and reset them to an "undefined" value is an effective technique for fighting state explosion in the enumerative verification of concurrent systems. although this technique is well-adapted to imperative languages, it is not directly applicable to value-passing process algebras, in which variables cannot be reset explicitly due to the single-assignment constraints of the functional programming style. this paper addresses this problem by performing data-flow analysis on an intermediate model (petri nets extended with state variables) into which process algebra specifications can be translated automatically. it also addresses important issues such as avoiding the introduction of useless reset operations and handling shared read-only variables that child processes inherit from their parents.
connectionist computations of intuitionistic reasoning. the construction of computational models with provision for effective learning and added reasoning is a fundamental problem in computer science. in this paper, we present a new computational model for integrated reasoning and learning that combines intuitionistic reasoning and neural networks. we use ensembles of neural networks to represent intuitionistic theories, and show that for each intuitionistic theory and intuitionistic modal theory there exists a corresponding neural network ensemble that computes a fixed-point semantics of the theory. this provides a massively parallel model for intuitionistic reasoning. in our model, the neural networks can be trained from examples to adapt to new situations using standard neural learning algorithms, thus providing a unifying foundation for intuitionistic reasoning, knowledge representation, and learning.
learning in varieties of the form vli from positive data. grammatical inference and finite semigroup theory are continuously developing. nevertheless it seems that they are not interacting too much. we propose in this paper an inference method for languages that belong to varieties of the form v*li. many well known families of languages like locally testable, reversible, dot-depth one, etc. are of that form. the method unifies existing algorithms for inference of some of those families and can be applied to some others that had not been inferred yet. it uses a result about the cascade product in which one of the factors is a transducer and the second is the automaton obtained by inferring the base case of the family using the transduction of the sample as input.
bilateral locally testable languages. we give an algebraic characterization of a new variety of languages that will be called bilateral locally testable languages and denoted as blt. given k > 0, the membership of a word x to a blt (k-bt) language can be decided by means of exploring the segments of length k of x, as well as considering the order of appearance of those segments when we scan the prefixes and the suffixes of x. in this paper, we also characterize the syntactic semigroup of blt languages in terms of the equations of the variety they belong to, as well as in terms of the join of two previously studied varieties.
power simulation and its relation to traces and failures refinement. there are two quite distinct approaches commonly used when giving meaning to process algebra expressions: an operational semantics, often associated with the ccs language, defines an equivalence between terms by considering whether each can simulate the other; a denotational semantics, often associated with csp, provides a mapping, recursively defined over the structure of the language, taking each term into a carefully chosen collection of set-theoretic objects. (the traces and failures models are well-known examples of such semantic domains.) we present a formal link between the two approaches, consisting in defining a variant of the bisimulation equivalence that naturally gives rise to the traces and failures ordering. we have no way at present to extend this result to the failures/divergence model.
modelling dynamic web data. we introduce the xdπ calculus, a peer-to-peer model for reasoning about dynamic web data. web data is not just stored statically. rather it is referenced indirectly, for example using hyperlinks, service calls, or scripts for dynamically accessing data, which require the complex coordination of data and processes between sites. the xdπ calculus models this coordination by integrating the xml data structure with process orchestration techniques associated with the distributed pi-calculus. we study behavioural equivalences for xdπ, to analyze the various possible patterns of data and process interaction.
implicit surface visualization of reconstructed biological molecules. an implicit surface of a density function is the set of points at which the value of the function is equal to a fixed threshold. an object that is defined as the collection of points at which the density function value is above the threshold can be visualized by displaying the implicit surface. some methods for the reconstruction of biological macromolecules from their electron microscopic projections produce density functions that are specified by a linear combination of smoothly-varying radially-symmetric basis functions of finite support, also known as blobs. when density functions are determined by such a blob representation, the implicit surfaces are smoothly varying and the normal at any point on such a surface can be analytically calculated. this property can be utilized to produce high-quality visualizations by raycasting. while raycasting tends to be computationally expensive, we present a methodology that uses techniques of computer graphics and image processing to significantly reduce the cost of visualization.
the generalized weil pairing and the discrete logarithm problem on elliptic curves. we review the construction of a generalization of the weil pairing, which is nondegenerate and bilinear, and use it to construct a reduction from the discrete logarithm problem on elliptic curves to the discrete logarithm problem in finite fields. we show that the new pairing can be computed efficiently for curves with trace of frobenius congruent to 2 modulo the order of the base point. this leads to an efficient reduction for this class of curves. the reduction is as simple to construct as that of menezes et al. (ieee trans. inform. theory, 39, 1993), and is provably equivalent to that of frey and rück (math. comput. 62 (206) (1994) 865).
algorithmic combinatorics based on slicing posets. a combinatorial problem usually requires enumerating, counting or ascertaining existence of structures that satisfy a given property b in a set of structures l. this paper describes a technique based on a generalization of birkhoff's theorem of representation of finite distributive lattices that can be used for solving such problems mechanically and efficiently. specifically, we give an efficient (polynomial time) algorithm to enumerate, count or detect structures that satisfy b when the total set of structures is large but the set of structures satisfying b is small. we illustrate our techniques by analyzing problems in integer partitions, set families, and set of permutations.
regular component decomposition of regular languages. a language is regular if it can be recognized by a finite automaton. according to the pumping lemma, every infinite regular language contains a regular subset of the form uv+w, where u, v, w are words and v is not empty. it is known that every regular language can be expressed as (∪i∈iuivi+wi) ∪f, where i is an index set, ui, wi∈a*,vi∈a+,i∈i and f is a finite set of words over the alphabet a. this expression is called a regular component decomposition of the language. a language is called regular component splittable if it can be expressed as a disjoint union of regular components and a finite set. a language which has a regular component decomposition with finite index is called a finite regular component representable language. it has been shown that every finite regular component representable language is regular component splittable by shyr and yu in (discrete appl. math. 82 (1998) 219). they conjectured that every regular language is regular component splittable in (acta math. hung. 78(3) (1998) 251). the conjecture is proved in this paper.
space efficient search for maximal repetitions. we study here a problem of finding all maximal repetitions in a string of length n. we show that the problem can be solved in time o(n log n) in the presence of constant extra space and general (unbounded) alphabets. subsequently we show that in the model with a constant size alphabet the problem can be solved in time o(n) with a help of o(n) extra space. previously best known algorithms require linear additional space in both models.
deterministic m2m multicast in radio networks. we study the problem of exchanging messages within a fixed group of k nodes, called participants, in an n-node radio network, modeled as an undirected graph. this communication task was previously considered in the setting of atm video applications, in [j.m. tsai, h.-h. fang, c.-y. lee, a multicast solution for atm video applications, ieee trans. circuits systems video technol. 7 (1997) 675-686], and was called multipoint-to-multipoint (m2m) multicasting. while the radio network topology is known to all nodes, it is assumed that no node is aware of the location of the participants. we give a distributed deterministic algorithm for the m2m multicasting problem in radio networks, and analyze its time complexity. we show that if the maximum distance between any two out of k participants is d then this local information exchange problem can be solved in time o(d log2 n + k log4 n).
a truly concurrent semantics for a process algebra using resource pomsets. in this paper we study a process algebra whose semantics is based on true concurrency. in our model, actions are defined in terms of the resources they need to execute, which allows a simple definition of a weak sequential composition operator. this operator allows actions which do not share any resources to execute concurrently, while dependent actions have to occur sequentially. this weak sequential composition operator may be used to automatically parallelize a sequential process. we add the customary (strict) sequential composition and a parallel composition operator allowing synchronization on specified actions. our language also supports a hiding operator that allows the hiding of actions and even of individual resources used by actions. strict sequential composition and hiding require that we generalize from the realm of mazurkiewicz traces to that of pomsets, since these operations introduce "over-synchronized" tracesones for which a pair of independent actions may occur sequentially. our language also supports recursion and our semantics makes the unwinding of recursion visible by the use of special resources used to label unwindings. this is done on purpose in order to make divergence observable, but the usual semantics that does not observe unwindings can be obtained by using the hiding operator to abstract away from these special resources. we give both an sos-style operational semantics for our language, as well as a denotational semantics based on resource pomsets. generalizing results from our earlier work in this area, we derive a congruence theorem for our language which shows that the sos-style operational rules induce the same equivalence relation on the language as the denotational semantic map does. a corollary is that our denotational model is both adequate and fully abstract relative to the behavior function defined from our operational semantics. this behavior consists naturally of the strings of actions the process can perform. this work continues our study into modelling concurrency in the absence of nondeterminism. in particular, our language is deterministic.
resource traces: a domain for processes sharing exclusive resources. the domain of partially terminated finite and infinite words is commonly used to give denotational semantics for process algebras such as csp. in this well-known framework the denotational semantics of concurrency is derived via power-domains from that of non-deterministic choice and interleaving to the effect that the denotational semantics of a concurrent process is equal to the set of all its possible finite and infinite sequential behaviours. in this paper, we define a more versatile domain of the so-called finite and infinite resource traces which allows to capture the concurrent behaviour of a process and encode the static concurrency of a system directly into the domains definition. the approach we present refines the previous work of diekert and gastin (lecture notes in computer science, vol. 944, springer, berlin, pp. 15-26) on - and -traces. we start with an alphabet of atomic actions, a set of resources, and a resource map assigning to each action the non-empty subset of resources it uses. actions that do not share common resources are called independent and considered to be able to execute concurrently. a partially terminated concurrent process is specified by a resource trace which consists of two components: an already observed part represented as an action-labeled partial order (mazurkiewicz trace), and a guard set containing the resources granted to the process for its further development. a process concatenation is then defined, which allows independent actions to execute concurrently. specification refinement leads to a natural approximation ordering between processes. it confers to the set of all processes the structure of a coherently complete prime algebraic scott domain, whereby, process concatenation is scott-continuous in both arguments. furthermore, we define a natural ultrametric on processes based on prefix information. the induced topology is shown to be equivalent to the compact lawson topology induced by the approximation ordering. process concatenation is moreover shown to be uniformly continuous with respect to the defined ultrametric. the mathematical theory we develop thus extends the central order and metric properties of the domain of partially terminated finite and infinite words which are needed in order to devise truly concurrent semantics for process algebras much in the style of classical csp semantics.
fast arithmetic with general gauß periods. we show how to apply fast arithmetic in conjunction with general gauß periods in finite fields. this is an essential ingredient for some efficient exponentiation algorithms.
interval routing in reliability networks. in this paper, we consider routing with compact tables in reliability networks. more precisely, we study interval routing on random graphs g(b, p) obtained from a base graph b by independently removing each edge with a failure probability 1 - p. we focus on additive stretched routing for n-node random graphs for which the base b is a square mesh and p = 0.5, that is the percolation model at the critical phase. we show a lower bound of ω(√log n/(δ+2)) on the number of intervals required per edge for every additive stretch δ≥0. on the other side, our experimental results show that the size of the largest biconnected components is θ(n0.827), and thus that there exists a trivial shortest-path routing scheme using at most o(n0.827) intervals per edge.the results are extended to random meshes of higher dimension. we show that, asymptotically almost surely, the number of intervals per edge for a random r-dimensional mesh with n nodes is ω(16-r (δ + 2)1-r r-4(log n)1-1/r), for every additive stretch δ≥0 and for every integral dimension r ∈ [1, log2n].
on the decidability of termination of query evaluation in transitive-closure logics for polynomial constraint databases. the formalism of constraint databases, in which possibly infinite data sets are described by boolean combinations of polynomial inequality and equality constraints, has its main application area in spatial databases. the standard query language for polynomial constraint databases is first-order logic over the reals. because of the limited expressive power of this logic with respect to queries that are important in spatial data base applications, various extensions have been introduced. we study extensions of first-order logic with different types of transitive-closure operators and we are in particular interested in deciding the termination of the evaluation of queries expressible in these transitive-closure logics. it turns out that termination is undecidable in general. however, we show that the termination of the transitive closure of a continuous function graph in the two-dimensional plane, viewed as a binary relation over the reals, is decidable, and even expressible in first-order logic over the reals. based on this result, we identify a particular transitive-closure logic for which termination of query evaluation is decidable and which is more expressive than first-order logic over the reals. furthermore, we can define a guarded fragment in which exactly the terminating queries of this language are expressible.
converting two-way nondeterministic unary automata into simpler automata. we show that, on inputs of length exceeding 5n2, any n-state unary two-way nondeterministic finite automaton (2nfa) can be simulated by a (2n + 2)-state quasi-sweeping 2nfa. such a result, besides providing a "normal form" for 2nfa's, enables us to get a subexponential simulation of unary 2nfa's by two-way deterministic finite automata (2dfa's). in fact, we prove that any n-state unary 2nfa can be simulated by a sweeping 2dfa with o(n ⌈log2(n+1)+3⌉) states.
more efficient on-the-fly ltl verification with tarjan's algorithm. state-of-the-art algorithms for on-the-fly automata-theoretic ltl model checking make use of nested depth-first search to look for accepting cycles in the product of the system and the büchi automaton. here, we present two new single depth-first search algorithms that accomplish the same task. the first is based on tarjan's algorithm for detecting strongly connected components, while the second is a combination of the first and couvreur's algorithm for finding acceptance cycles in the product of a system and a generalized büchi automaton. both new algorithms report an accepting cycle immediately after all transitions in the cycle have been investigated. we show their correctness, describe efficient implementations and discuss how they interact with some other model checking techniques, such as bitstate hashing. the algorithms are compared to the nested search algorithms in experiments on both random and actual state spaces, using random and real formulas. our measurements indicate that our algorithms investigate at most as many states as the old ones. in the case of a violation of the correctness property, the algorithms often explore significantly fewer states.
scheduling hard sporadic tasks with regular languages and generating functions. in this paper, we consider offline validation of hard real-time systems composed of both periodic and sporadic tasks, embedded on centralized multi-processor architectures. to model hard real-time systems, we use untimed finite automata: each accepted word is a valid operational behavior of the periodic component of the system. then, by associating generating functions with edges of the automaton, we give a modular decisional technique to decide the feasibility of sporadic tasks.
arborescence optimization problems solvable by edmonds' algorithm. we consider a general class of optimization problems regarding spanning trees in directed graphs (arborescences). we present an algorithm for solving such problems, which can be considered as a generalization of edmonds' algorithm for the solution of the minimum sum arborescence problem. the considered class of optimization problems includes as special cases the standard minimum sum arborescence problem, the bottleneck and lexicographically optimal arborescence problem, as well as the widest-minimum sum arborescence problem.
efficient gossip and robust distributed computation. this paper presents an efficient deterministic gossip algorithm for p synchronous, crash-prone, message-passing processors. the algorithm has time complexity t = o(log2p) and message complexity m = o(p1+ε), for any ε > 0. this substantially improves the message complexity of the previous best algorithm that has m = o(p1.77), while maintaining the same time complexity.the strength and utility of the new result is demonstrated by constructing a deterministic algorithm for performing n tasks in this distributed setting. previous solutions used coordinator or checkpointing approaches, immediately incurring a work penalty ω(n + f ċ p) for f crashes, or relied on strong communication primitives, such as reliable broadcast, or had work too close to the trivial θ(p ċ n) bound of oblivious algorithms. the new algorithm uses p crash-prone processors to perform n similar and idempotent tasks so long as one processor remains active. the work of the algorithm is w = o(n + p ċ min{f + 1, log3p}) and its message complexity is m = o(fpepsiv; + p min{f + 1, log p}), for any ε > 0. this substantially improves the work complexity of previous solutions using simple point-to-point messaging, while "meeting or beating" the corresponding message complexity bounds.the new algorithms use communication graphs and permutations with certain combinatorial properties that are shown to exist. the algorithms are correct for any permutations, and in particular, the same expected bounds can be achieved using random permutations.
periodic graphs and connectivity of the rational digital hyperplanes. given a digital hyperplane of zn defined by a double-inequality hi=1naixi<h+, we want to determine whether it is connected. the problem consists of computing the connectivity of a graph whose set of vertices is not finite. the classical algorithms of labelling are not deterministic in this framework but we can think of using the properties of the digital hyperplanes and in particular their periodicity to provide a deterministic method. it leads to introduce a special kind of graphs that we call periodic and whose properties allow to compute connective components of infinite size. it provides a deterministic algorithm determining whether a given rational digital hyperplane is connecte
reduction from three-dimensional discrete tomography to multicommodity flow problem. the reduction from two-dimensional-discrete tomography to max-flow problem is well-known [gale, a theorem on flows in networks, pacific j. math. 7 (1957) 1073-1082]. this approach is based on the natural correspondence between two-dimensional lattices and bipartite graphs. we extend this result in dimension 3 by reducing three-dimensional discrete tomography to multicommodity flow problems. two reductions are presented, one considering discrete tomography with multisets while the other one works with sets.
algorithms for vertex-partitioning problems on graphs with fixed clique-width. many vertex-partitioning problems can be expressed within a general framework introduced by telle and proskurowski. they showed that optimization problems in this framework can be solved in polynomial time on classes of graphs with bounded tree-width. in this paper, we consider a very similar framework, in relationship with more general classes of graphs: we propose a polynomial time algorithm on classes of graphs with bounded clique-width for all the optimization problems in our framework. these classes of graphs are more general than the classes of graphs with bounded tree-width in the sense that classes of graphs with bounded tree-width have also bounded clique-width (but not necessarily the inverse).our framework includes problems such as independent (dominating) set, p-dominating set, induced bounded degree subgraph, induced p-regular subgraph, perfect matching cut, graph k-coloring and graph list-k-coloring with cardinality constraints (fixed k). this paper thus provides a second (distinct) framework within which the optimization problems can be solved in polynomial time on classes of graphs with bounded clique-width, after a first framework (called ms1) due to the work of courcelle, makowsky and rotics (for which they obtained a linear time algorithm).
architecture independent parallel selection with applications to parallel priority queues. we present a randomized selection algorithm whose performance is analyzed in an architecture independent way on the bulk-synchronous parallel (bsp) model of computation along with an application of this algorithm to dynamic data structures, namely parallel priority queues. we show that our algorithms improve previous results upon both the communication requirements and the amount of parallel slack required to achieve optimal performance. we also establish that optimality to within small multiplicative constant factors can be achieved for a wide range of parallel machines. while these algorithms are fairly simple themselves, descriptions of their performance in terms of the bsp parameters is somewhat involved; the main reward of quantifying these complications is that it allows transportable software to be written for parallel machines that fit the model.
an upper bound for the largest lyapunov exponent of a markovian product of nonnegative matrices. we derive an upper bound for the largest lyapunov exponent of a markovian product of nonnegative matrices using markovian type counting arguments. the bound is expressed as the maximum of a nonlinear concave function over a finite-dimensional convex polytope of probability distributions.
the regular-language semantics of second-order idealized a. we explain how recent developments in game semantics can be applied to reasoning about equivalence of terms in a non-trivial fragment of idealized algol (ia) by expressing sets of complete plays as regular languages. being derived directly from the fully abstract game semantics for ia, our model inherits its good theoretical properties; in fact, for second-order ia taken as a stand-alone language the regular language model is fully abstract. the method is algorithmic and formal, which makes it suitable for automation. we show how reasoning is carried out using a meta-language of extended regular expressions, a language for which equivalence is decidable.
syntactic control of concurrency. we consider a finitary procedural programming language (finite data-types, no recursion) extended with parallel composition and binary semaphores. having first shown that may-equivalence of second-order open terms is undecidable we set out to find a framework in which decidability can be regained with minimum loss of expressivity. to that end we define an annotated type system that controls the number of concurrent threads created by terms and give a fully abstract game semantics for the notion of equivalence induced by typable terms and contexts. finally, we show that the semantics of all typable terms, at any order and in the presence of iteration, has a regular-language representation and thus the restricted observational equivalence is decidable.
transforming semantics by abstract interpretation. in 1997, cousot introduced a hierarchy where semantics are related with each other by abstract interpretation. in this field we consider the standard abstract domain transformers, devoted to refine abstract domains in order to include attribute independent and relational information, respectively the reduced product and power of abstract domains, as domain operations to systematically design and compare semantics of programming languages by abstract interpretation. we first prove that natural semantics can be decomposed in terms of complementary attribute independent observables, leading to an algebraic characterization of the symmetric structure of the hierarchy. moreover, we characterize some structural property of semantics, such as their compositionality, in terms of simple abstract domain equations. this provides an equational presentation of most well known semantics, which is parametric on the observable and structural property of the semantics, making it possible to systematically derive abstract semantics, e.g. for program analysis, as solutions of abstract domain equations.
rotation sequences and edge-colouring of binary tree pairs. the famous four-colour problem of planar maps is equivalent, by an optimally fast reduction, to the problem of colouring pairs of binary trees (cpbt). extant proofs of the four colour theorem lack conciseness, are not lucid in their detail and require hours of electronic computation. the search for a more satisfactory proof continues and, in this spirit, we explore one approach to cpbt based upon the rotation operation in binary trees. we prove that a more satisfactory proof exists if a rotational path between the two trees of every problem instance satisfies our non-colour-clashing sequence conjecture.
logical foundations for programming semantics. this paper was presented to the sixth workshop on mathematical foundations of programming semantics held at queen''s university, may 15-19,1990. \n\nthe paper provides an introduction to a natural deduction based set theory, nadset, and illustrates its use in programming semantics. the need for such a set theory for the development of programming semantics is motivated by contrasting the presentation of recursive definitions within first order logic with their presentation within nadset. within first order logic such definitions are always incomplete in a very simple sense: induction axioms must be added to the given definitions and extended with every new recursive definition. within a set theory such as nadset, recursive definitions of sets are represented as terms in the theory and are complete in the sense that all properties of the set can be derived from its definition. such definitions not only have this advantage of completeness, but they also permit recursively defined sets to be members of the universe of discourse of the logic and thereby be shown to be members of other defined sets. \nthe resolution of the paradoxes provided by nadset is dependant upon replacing the naive comprehension axiom scheme of an inconsistent first order logic with natural deduction rules for the introduction of abstraction terms into arguments. the abstraction terms admitted are a generalization of the abstraction terms usually admitted into set theory. in order to avoid a confusion of use and mention, the nominalist interpretation of the atomic formulas of the logic forces nadset to be second order, although only a single kind of quantifier and variable is required. \nthe use of nadset for programming semantics is illustrated for a simple flow diagram language that has been used to illustrate the principles of denotational semantics. the presentation of the semantics within nadset is not only fully formal, in contrast to the simply mathematical presentation of denotational semantics, but because nadset is formalized as a natural deduction logic, its derivations can be simply checked by machine.
an asymptotic study for path reversal. a path reversal is performed in a rooted tree when a node becomes the root of all the nodes along the path from it to the former root. this algorithm on trees is presented as a transition system specified by induction over a convenient view of the tree structure. when each tree node is assigned a fixed weight representing its relative probability to move to the root, the transition system defines a finite markov chain. this paper presents some of its asymptotic properties. a closed formula for the stationary distribution and a tight upper bound for the average computational complexity of path reversal are also given as new results.
on the expressiveness of higher dimensional automata. in this paper i compare the expressive power of several models of concurrency based on their ability to represent causal dependence. to this end, i translate these models, in behaviour preserving ways, into the model of higher dimensional automata (hda), which is the most expressive model under investigation. in particular, i propose four different translations of petri nets, corresponding to the four different computational interpretations of nets found in the literature.i also extend various equivalence relations for concurrent systems to hda. these include the history preserving bisimulation, which is the coarsest equivalence that fully respects branching time, causality and their interplay, as well as the st-bisimulation, a branching time respecting equivalence that takes causality into account to the extent that it is expressible by actions overlapping in time. through their embeddings in hda, it is now well-defined whether members of different models of concurrency are equivalent.
well-behaved flow event structures for parallel composition and action refinement. flow event structures were introduced as a model for giving semantics to process algebras. however, it turned out that certain restrictions have to be made to make them suitable for this purpose. in this paper, we investigate subclasses of flow event structures which are both suited for the process algebraic composition operators, and for action refinement as a means of regarding processes on different levels of abstraction.first, suitable subclasses are characterised. then two specific subclasses are proposed. the larger class generalises the one from castellani and zhang (theoret. comput. sci. 179 (1997) 203-215), which is not suitable for action refinement. the smaller one is still sufficiently expressive for dealing with all standard process algebras and action refinement.
formal description and analysis of a distributed location service for mobile ad hoc networks. in this paper, we define a distributed abstract state machine (dasm) model of the network or routing layer protocol for mobile ad hoc networks. in conjunction with the chosen routing strategy, we propose a distributed logical topology based location service (ltls) protocol and give a formal description and analysis of this protocol on the dasm model. the high dynamics of mobile ad hoc networks require routing strategies substantially different from those used in static communication networks. a strategy for such networks is geographic routing in which each network node can find its physical location via gps or other navigation technologies. to send a packet, the sender needs to know the most recent physical location of the destination node. this location information is provided by a location service protocol. the ltls protocol has short message delivery delay, requires small routing tables, uses relatively few administrative packets, and has very good fault tolerance properties. our goal in defining the network layer protocol in terms of a dasm model is twofold. first, we feel that the mathematical modeling paradigm of distributed abstract state machines provides an ideal formal basis for constructing, analyzing, and validating abstract requirements specifications of mobile ad hoc network protocols. second, we intend to utilize the resulting behavior model as a formal basis for developing executable specifications serving as a platform for experimental validation of key system attributes and exploration of alternative design choices.
occurrences of palindromes in characteristic sturmian words. this paper is concerned with palindromes occurring in characteristic sturmian words cα of slope α, where α ∈ (0, 1) is an irrational. as cα is a uniformly recurrent infinite word, any (palindromic) factor of cαoccurs infinitely many times in cα with bounded gaps. our aim is to completely describe where palindromes occur in cα. in particular, given any palindromic factor u of cα, we shall establish a decomposition of cα with respect to the occurrences of u. such a decomposition shows precisely where u occurs in cα, and this is directly related to the continued fraction expansion of α.
what is the coalgebraic analogue of birkhoff's variety theorem? logical definability is investigated for certain classes of coalgebras related to state-transition systems, hidden algebras and kripke models. the filter enlargement of a coalgebra a is introduced as a new coalgebra a+ whose states are special "observationally rich" filters on the state set of a. the ultra filter enlargement is the subcoalgebra a* of a+ whose states are ultrafilters. boolean combinations of equations between terms of observable (or output) type are identified as a natural class of formulas for specifying properties of coalgebras. these observable formulas are permitted to have a single-state variable, and form a language in which modalities describing the effects of state transitions are implicitly present. a* and a+ validate the same observable formulas. it is shown that a class of coalgebras is definable by observable formulas iff the class is closed under disjoint unions, images of bisimulations, and (ultra)filter enlargements. (closure under images of bisimulations is equivalent to closure under images and domains of coalgebraic morphisms.) moreover, every set of observable formulas has the same models as some set of conditional equations. examples are constructed to show that the use of enlargements is essential in these characterisations, and that there are classes of coalgebras definable by conditional observable equations, but not by equations alone. the main conclusion of the paper is that to structurally characterise classes of coalgebras that are logically definable by modal languages requires a new construction, of "stone space" type, in addition to the coalgebraic duals of the three constructions (homomorphisms, subalgebras, direct products) that occur in birkhoff's original variety theorem for algebras. copyright 2001 elsevier science b.v.
on learning unions of pattern languages and tree patterns in the mistake bound model. we present efficient on-line algorithms for learning unions of a constant number of tree patterns, unions of a constant number of one-variable pattern languages, and unions of a constant number of pattern languages with fixed length substitutions. by fixed length substitutions we mean that each occurrence of variable xi must be substituted by terminal strings of fixed length l(xi). we prove that if arbitrary unions of pattern languages with fixed length substitutions can be learned efficiently then dnfs are efficiently learnable in the mistake bound model. since we use a reduction to winnow, our algorithms are robust against attribute noise. furthermore, they can be modified to handle concept drift. also, our approach is quite general and we give results to learn a class that generalizes pattern languages.
1-optimality of static bsp computations: scheduling independent chains as a case study. the aim of this work is to study a specific scheduling problem under the machine-independent model bsp. the problem of scheduling a set of independent chains in this context is shown to be a difficult optimization problem, but it can be easily approximated in practice. efficient heuristics taking into account communications are proposed and analyzed in this paper. we particularly focus on the influence of synchronization between consecutive supersteps. a family of algorithms is proposed with the best possible load-balancing. then, a strategy for determining a good compromise between the two opposite criteria of minimizing the number of supersteps and a good balance of the load is derived. finally, a heuristic which considers the influence of the latency is presented. simulations of a large number of instances have been carried out to complement the theoretical worst case analysis. they confirm the very good behavior of the algorithms on the average cases.
pattern statistics and vandermonde matrices. in this paper, we determine some limit distributions of pattern statistics in rational stochastic models. we present a general approach to analyze these statistics in rational models having an arbitrary number of strongly connected components. we explicitly establish the limit distributions in most significant cases; they are characterized by a family of unimodal density functions defined by means of confluent vandermonde matrices.
a combinatorial approach to golomb forests. optimal binary prefix-free codes for infinite sources with geometrically distributed frequencies, e.g., p = {pi(1 - p)}i=0; 0p1, were first (implicitly) suggested by golomb over 30 years ago in the context of run-length encodings. ten years later gallager and van voorhis exhibited such optimal codes for all values of p. these codes were derived by using the hu2man encoding algorithm to build optimal codes for finite sources and then showing that the finite codes converge in a very specific sense to the infinite one. in this note, we present a new combinatorial approach to solve the same problem, one that does not use the hu2man algorithm, but instead treats a coding tree as an infinite sequence of integers and derives properties of the sequence. one consequence of this new approach is a complete characterization of all of the optimal codes; in particular, it shows that for all p; 0p1; except for an easily describable countable set, there is a unique optimal code, but for each p in this countable set there are an uncountable number of optimal codes. another consequence is a derivation of infinite codes for geometric sources when the encoding alphabet is no longer restricted to be the binary one. a final consequence is the extension of the results to optimal forests instead of being restricted to optimal trees.
tuning evaluation functions by maximizing concordance. heuristic search effectiveness depends directly upon the quality of heuristic evaluations of states in a search space. given the large amount of research effort devoted to computer chess throughout the past half-century, insufficient attention has been paid to the issue of determining if a proposed change to an evaluation function is beneficial.we argue that the mapping of an evaluation function from chess positions to heuristic values is of ordinal, but not interval scale. we identify a robust metric suitable for assessing the quality of an evaluation function, and present a novel method for computing this metric efficiently. finally, we apply an empirical gradient-ascent procedure, also of our design, over this metric to optimize feature weights for the evaluation function of a computer-chess program. our experiments demonstrate that evaluation function weights tuned in this manner give equivalent performance to hand-tuned weights.
shuffle on positive varieties of languages. we show there is a unique maximal positive variety of languages which does not contain the language (ab)*. this variety is the unique maximal positive variety satisfying the two following conditions: it is strictly included in the class of rational languages and is closed under the shuffle operation. it is also the largest proper positive variety closed under length preserving morphisms. the ordered monoids of the corresponding variety of ordered monoids are characterized as follows: for every pair (a,b) of mutually inverse elements, and for every element z of the minimal ideal of the submonoid generated by a and b, (abzab)ω ≤ ab. in particular this variety is decidable.
complexity of pairwise shortest path routing in the grid. in parallel and distributed systems many communications take place concurrently. the efficient delivery of all the messages depends on the routing algorithms as well as the underlying interconnection network topology. the grid is a planar network topology that lends itself for efficient vlsi implementation and therefore is of interest for theoretical analysis. frequently, networks and switches achieve high performance by delivering the messages through shortest paths. in addition, network fault tolerance improves through insuring that the traversed paths are both edge and/or node disjoint. the edge disjoint criterion is useful when network links are the predominant constraint, and the node disjoint criterion becomes important when switches are the fault tolerant bottleneck. because the latter necessarily implies the former, it is apparent that node disjointness contributes to fault tolerance and enhanced performance. in this paper, we examine the k-pairwise node and edge disjoint shortest paths problem in the undirected graph topology of the grid. herein it is shown that the k-pairwise node as well as the k-pairwise edge disjoint shortest paths decision problems are np-hard, and remain np-hard even for many different restrictions on the problem. we also discuss polynomial time algorithms for restricted versions of our problems.
complete axiomatization and decidability of alternating-time temporal logic. alternating-time temporal logic (atl), introduced by alur, henzinger and kupferman, is a logical formalism for the specification and verification of open systems involving multiple autonomous players (agents, components). in particular, this logic allows for the explicit expression of coalition abilities in such systems, modelled as infinite transition games between the coalition and its complement.formally, atl is a non-normal multi-modal extension of ctl (regarded as a one-player fragment of atl) with temporal operators indexed by coalitions of players, and thus expressing selective quantification over those paths which can be effected as outcomes of infinite transition games between the coalition and its complement.we present a sound and complete axiomatization of the logic atl, based on pauly's axiomatization of his coalition logic, augmented with axioms and rules for fixed point formulae characterizing the temporal operators. the completeness proof is by construction of a bounded branching tree model for each atl-consistent formula. these models can be folded into finite models, thus rendering the finite model property for atl.we also describe an automata-based decision procedure for atl by translating the satisfiability problem to the nonemptiness problem for alternating automata on infinite trees. when considering formulae over a fixed finite set of players the decidability problem is shown to be exptime-complete.
typing correspondence assertions for communication protocols. woo and lam propose correspondence assertions for specifying authenticity properties of security protocols. prior work on checking correspondence assertions depends on model-checking and is limited to finite-state systems. we propose a dependent type and effect system for checking correspondence assertions. since it is based on type-checking, our method is not limited to finite-state systems. this paper presents our system in the simple and general setting of the π-calculus. we show how to type-check correctness properties of example communication protocols based on secure channels. in a related paper, we extend our system to the more complex and specific setting of checking cryptographic protocols based on encrypted messages sent over insecure channels.
dls-trees: a model of evolutionary scenarios. we present a model of evolution of gene trees in the context of species evolution. its concept is similar to reconciliation models. we assume that the gene evolution is modelled by duplications and losses. evolution of species is modelled by speciation events. we define an evolutionary scenario (called a dls-tree) which can represent an evolution of genes in species. we are interested in all scenarios for a given species tree and a given gene tree--not only parsimonious ones. we propose a rewrite system for transforming the scenarios. we prove that the system is confluent, sound and strongly normalizing. we show that a scenario in normal form (i.e., non-reducible) is unique and minimal in the sense of the cost computed as the total number of gene duplications and losses (mutation cost). we present a classification of the scenarios and analyze their hierarchy. finally, we prove that the reconciled tree can be easily transformed into dls-tree in normal form. this solves some open problems for reconciled trees.
an abstract interpretation framework to reason on finite failure and other properties of finite and infinite computations. we extend the framework of comini et al. (inform. comput. (1999), to appear) in order to be able to reason on properties (of abstractions) of possibly infinite sld-derivations. this issue is relevant since some important operational properties such as finite failure, infinite behavior can only be addressed as abstraction of finite and infinite sld-derivations. the framework allows us to define new fixpoint semantics correctly modelling such properties and address problems such as compositionality w.r.t. various syntactic operators, correctness and minimality of the chosen denotations. in this paper we also apply the framework in order to obtain a new fixpoint semantics, based on a co-continuous operator, which correctly models finite failure and is compositional w.r.t. the syntactic operators.
a theory of processes with durational actions. a new bisimulation-based semantics, called performance equivalence, is proposed for a process algebra equipped with tcsp parallel operator. this semantics relies on the basic assumption that actions are time-consuming, where their duration is statically fixed. performance equivalence equates systems whenever they perform the same actions in the same amount of time, thus introducing a simple form of performance evaluation in process algebras. a comparison with other equivalences is provided; in particular, we show that performance equivalence is strictly finer than step bisimulation equivalence and strictly coarser than partial ordering bisimulation equivalence.
asymmetry in -center variants. this paper explores three concepts: the k-center problem, some of its variants, and asymmetry. the k-center problem is fundamental in location theory. variants of k-center may more accurately model real-life problems than the original formulation. asymmetry is a significant impediment to approximation in many graph problems, such as k-center, facility location, k-median, and the tsp.we give an o(log*n)-approximation algorithm for the asymmetric weighted k-center problem. here, the vertices have weights and we are given a total budget for opening centers. in the p-neighbor variant each vertex must have p (unweighted) centers nearby: we give an o(log*k)-bicriteria algorithm using 2k centers, for small p.finally, we show the following three versions of the asymmetric k-center problem to be inapproximable: priority k-center, k-supplier, and outliers with forbidden centers.
computing logcfl certificates. the complexity class logcfl consists of all languages (or decision problems) which are logspace reducible to a context-free language. since logcfl is included in ac1, the problems in logcfl are highly parallelizable. by results of ruzzo (jcss 21 (1980) 218), the complexity class logcfl can be characterized as the class of languages accepted by alternating turing machines (atms) which use logarithmic space and have polynomially sized accepting computation trees. we show that for each such atm m recognizing a language a in logcfl, it is possible to construct an llogcfl transducer tm such that tm on input w &&egr; a outputs an accepting tree for m on w. it follows that computing single logcfl certificates is feasible in functional ac1 and is thus highly parallelizable.wanke (j. algorithms 16 (1994) 470) has recently shown that for any fixed k, deciding whether the treewidth of a graph is at most k is in the complexity-class logcfl. as an application of our general result, we show that the task of computing a tree-decomposition for a graph of constant treewidth is in functional logcfl, and thus in ac1. we also show that the following tasks are all highly parallelizable: computing a solution to an acyclic constraint satisfaction problem; computing an m-coloring for a graph of bounded treewidth; computing the chromatic number and minimal colorings for graphs of bounded tree- width.
enumeration of symmetry classes of convex polyominoes on the honeycomb lattice. we enumerate the symmetry classes of convex polyominoes on the hexagonal (honeycomb) lattice. here convexity is to be understood as convexity along the three main column directions. we deduce the generating series of free (i.e. up to reflection and rotation) and of asymmetric convex hexagonal polyominoes, according to area and half-perimeter. we give explicit formulas or implicit functional equations for the generating series, which are convenient for computer algebra. thus, computations can be carried out up to area 70.
on the completeness and decidability of duration calculus with iteration. the extension of the duration calculus (dc) by iteration, which is also known as kleene star, enables the straightforward specification of repetitive behaviour in dc and facilitates the translation of design descriptions between dc, timed regular expressions and timed automata. in this paper we present axioms and a proof rule about iteration in dc. we consider abstract-time dc and its extension by a state-variable binding existential quantifier known as higher-order dc (hdc). we show that the ω-complete proof systems for dc and hdc known from our earlier work can be extended by our axioms and rule in various ways in order to axiomatise iteration completely. the additions we propose include either the proof rule or an induction axiom. we also present results on the decidability of a subset of the extension dc* of dc by iteration.
distribution results for low-weight binary representations for pairs of integers. we discuss an optimal method for the computation of linear combinations of elements of abelian groups, which uses signed digit expansions. this has applications in elliptic curve cryptography. we compute the expected number of operations asymptotically (including a periodically oscillating second order term) and prove a central limit theorem. apart from the usual right-to-left (i.e., least significant digit first) approach we also discuss a left-to-right computation of the expansions. this exhibits fractal structures that are studied in some detail.
combinatorics of geometrically distributed random variables: run statistics. for words of length n, generated by independent geometric random variables, we consider the mean and variance, and thereafter the distribution of the number of runs of equal letters in the words. in addition, we consider the mean length of a run as well as the length of the longest run over all words of length n.
parsing mell proof nets. we propose a new formulation for full (weakening and constants included) multiplicative and exponential (mell) proof nets, allowing a complete set of rewriting rules to parse them. the recognizing grammar defined by such a rewriting system (confluent and strong normalizing on the new proof nets) gives a correctness criterion that we show equivalent to the danos-regnier one.
sorting algorithms for broadcast communications: mathematical analysis. we study three algorithms for sorting under the broadcast communication model. two algorithms are based on the maximum finding and the loser selection strategy, the third one is the naïve strategy based on loser selection only. while a precise description of the algorithms can be found in the paper [15], we concentrate here on the mathematical aspects of the analysis. from these elementary considerations it follows that the average time complexities of the non-naïve algorithms are θ(n). we give precise expressions for the constants involved by writing them as contour integrals involving zeta functions. the numerical evaluation via residues leads to slowly converging series, and the acceleration of them is a non-trivial task that is done in a slightly more general fashion in order to fit all the applications.
coherence for sharing proof-nets. sharing graphs are an implementation of linear logic proof-nets in which a redex is never duplicated. in their usual formulation, sharing graphs present a problem of coherence: if the proof-net n reduces by standard cut-elimination to n', then, by reducing the sharing graph of n we do not obtain the sharing graph of n'. we solve this problem by changing the way the information is coded into sharing graphs and introducing a new reduction rule (absorption). the rewriting system is confluent and terminating. the proof exploits an algebraic semantics for sharing graphs.
guarded fixed point logics and the monadic theory of countable trees. different variants of guarded logics (a powerful generalization of modal logics) are surveyed and an elementary proof for the decidability of guarded fixed point logics is presented. in a joint paper with igor walukiewicz, we proved that the satisfiability problems for guarded fixed point logics are decidable and complete for deterministic double exponential time (e. grädel and i. walulkiewicz, proc. 14th ieee symp. on logic in computer science, 1999, pp. 45-54). that proof relies on alternating automata on trees and on a forgetful determinacy theorem for games on graphs with unbounded branching. the exposition given here emphasizes the tree model property of guarded logics: every satisfiable sentence has a model of bounded tree width. based on the tree model property, we show that the satisfiability problem for guarded fixed point formulae can be reduced to the monadic theory of countable trees (sωs), or to the µ-calculus with backwards modalities.
on maximal codes with a finite interpreting delay. the notion of codes with a finite interpreting delay (f.i.d.) was introduced in (guesnet, theoret. inform. appl. 34 (2000) 47-59). in this paper, we are interested in the notion of maximality for f.i.d. codes. we characterize the maximal f.i.d. codes in terms of completeness. we also present an embedding procedure keeping thinness, rationality and the delay.
on maximal synchronous codes. in this paper, we are interested in maximal synchronous codes. more precisely, we prove that we can embed any synchronous code in a maximal one. moreover, we establish that, for synchronous codes, the notion of maximality in the family of synchronous codes is equivalent to the notion of maximality in the family of codes.
on temporal logic versus datalog. we provide a direct and modular translation from the temporal logics ctl, etl, fctl (ctl extended with the ability to express fairness) and the modal µ-calculus to monadic inf-datalog with built-in predicates. we call it inf-datalog because the semantics we provide is a little different from the conventional datalog least fixed point semantics, in that some recursive rules (corresponding to least fixed points) are allowed to unfold only finitely many times, whereas others (corresponding to greatest fixed points) are allowed to unfold infinitely many times.we characterize the fragments of monadic inf-datalog that have the same expressive power as modal logic (resp. ctl, alternation-free modal µ-calculus and modal µ-calculus). our translation is interesting because it is direct and succinct. moreover the fragments of monadic inf-datalog that we have exhibited have very simple syntactic characterizations as subsets of what we call modal inf-datalog programs.
algebraic rewritings for optimizing regular path queries. rewriting queries using views is a powerful technique that has applications in query optimization, data integration, data warehousing, etc. query rewriting in relational databases is by now rather well investigated. however, in the framework of semistructured data the problem of rewriting has received much less attention. in this paper we focus on extracting as much information as possible from algebraic rewritings for the purpose of optimizing regular path queries. the cases when we can find a complete exact rewriting of a query using a set a views are very "ideal". however, there is always information available in the views, even if this information is only partial. we introduce "lower" and "possibility" partial rewritings and provide algorithms for computing them. these rewritings are algebraic in their nature, i.e. we use only the algebraic view definitions for computing the rewritings. we do not use any pairs (tuples) of objects for computing the rewritings. this fact makes them a main memory product, which can be used for reducing secondary memory and remote access. after the main memory algebraic computation of the rewritings there is a second phase, with secondary memory access, for deriving the pairs of objects in the query answer. we give two algorithms for utilizing the partial lower and partial possibility rewritings to decrease the number of secondary memory accesses.
sorted dependency insertion grammars. an enhanced generative formalism is proposed based on the combination of two features: contextual derivation (as in marcus contextual grammars) and sorted dependency structures (as in dependency grammars). the model is related to a variant of restarting automaton with rewriting and deletion. preliminary results on the generative power as well as closure and decidability properties of the new model are presented.
acyclic networks maximizing the printing complexity. this article estimates the worst-case running time complexity for traversing and printing all successful paths of a normalized trim acyclic automaton. first, we show that the worst-case structure is a festoon. then, we prove that the complexity is maximal when we have a distribution of e (napier constant) outgoing arcs per state on average, and that it can be exponential in the number of arcs.
two polygraphic presentations of petri nets. this document gives an algebraic and two polygraphic translations of petri nets, all three providing an easier way to describe reductions and to identify some of them. the first one sees places as generators of a commutative monoid and transitions as rewriting rules on it: this setting is totally equivalent to petri nets, but lacks any graphical intuition. the second one considers places as one-dimensional cells and transitions as two-dimensional ones: this translation recovers a graphical meaning but raises many diffficulties since it uses explicit permutations. finally, the third translation sees places as degenerated two-dimensional cells and transitions as three-dimensional ones: this is a setting equivalent to petri nets, equipped with a graphical interpretation.
distributivity of categories of coalgebras. for any set-endofunctor f, the category setf of f-coalgebras has preimages, i.e. pullbacks along an injective map. if f preserves preimages, then setf is distributive, and the converse holds, whenever setf has finite products.
a spatial view of information. spatial representation has two contrasting but interacting aspects (i) representation of spaces and (ii) representation by spaces. in this paper we will examine two aspects that are common to both interpretations of the theme of spatial representation, namely nerve-type constructions and refinement. we consider the induced structures, in which some of the attributes of the informational context are sampled.
on a modular domination game. we present a generalization of the so-called σ-game, introduced by sutner (math. intelligencer 11 (1989) 49), a combinatorial game played on a graph, with relations to cellular automata, as well as odd domination in graphs. a configuration on a graph is an assignment of values in {0,...,p- 1} (where p is an arbitrary positive integer) to all the vertices of g. one may think of a vertex v of g as a button the player can press at his discretion. if vertex v is chosen, the value of all the vertices adjacent to v increases by 1 modulo p. this defines an equivalence relation between the configurations: two configurations are in relation if it is possible to reach one from the other by a sequence of such operations. we investigate the number of equivalence classes that a given graph has, and we give formulas for trees and special regular graphs.
truly concurrent constraint programming. we study "causality" relationships in concurrent constraint programming: what is observed is not just the conjunction of constraints deposited in the store, but also the causal dependencies between these constraints. we describe a denotational semantics for cc that is fully abstract with respect to observing this "causality" relation on constraints. this semantics preserves more fine-grained structure of computation; in particular the interleaving law is not verified ( is indeterminate choice). relationships between such a denotational approach to true concurrency and different powerdomain constructions are explored.
semantic essence of asml. the abstract state machine language, asml, is a novel executable specification language based on the theory of abstract state machines. asml is object-oriented, provides high-level mathematical data-structures, and is built around the notion of synchronous updates and finite choice. asml is fully integrated into the .net framework and microsoft development tools. in this paper, we explain the design rationale of asml and provide static and dynamic semantics for a kernel of the language.
partial updates. a datastructure instance, e.g. a set or file or record, may be modified independently by different parts of a computer system. the modifications may be nested. such hierarchies of modifications need to be efficiently checked for consistency and integrated. this is the problem of partial updates in a nutshell. in our first paper on the subject, we developed an algebraic framework which allowed us to solve the partial update problem for some useful datastructures including counters, sets and maps. these solutions are used for the efficient implementation of concurrent data modifications in the specification language asml. the two main contributions of this paper are (i) a more general algebraic framework for partial updates and (ii) a solution of the partial update problem for sequences and labeled ordered trees.
modelization of deterministic rational relations. the definition of the class of deterministic rational relations is fundamentally based on the read-only one-way turing machine approach. the notion of deterministic automata developed up to now is too strong and asks for an unnatural detour via end-markers to give all deterministic rational relations (cf. section 3.1). we stress that several conditions usually considered as related to determinism are mere normalizations of determinism and are not inherent to the notion (cf. section 3.2). in this paper, we introduce pertinent notions of deterministic labelled graph automata (cf. section 3.3) which avoid any use of end-markers: strong deterministic, n-deterministic automata for nn. these notions form an increasing infinite hierarchy of classes of automata which all lead to the same usual class of deterministic rational relations. moreover, the class corresponding to the natural extension to the case n= is exactly the class of unambiguous automata. we also consider nivat's characterization via multimorphisms applied to rational languages and introduce a hierarchy of deterministic versions of multimorphisms. properties of determinism and unambiguity are compared. the decision problems for ambiguity or determinism relative to automata and multimorphisms are settled. roughly, all problems are undecidable in case of arity 2 with at least two non-binary alphabets, else they are decidable, most being even polynomial time decidable.
on the relationship between nlc-width and linear nlc-width. in this paper, we consider nlc-width, nlct-width, and linear nlc-width bounded graphs. we show that the set of all complete binary trees has unbounded linear nlc-width and that the set of all co-graphs has unbounded nlct-width. since trees have nlct-width 3 and co-graphs have nlc-width 1, it follows that the family of linear nlc-width bounded graph classes is a proper subfamily of the family of nlct-width bounded graph classes and that the family of nlct-width bounded graph classes is a proper subfamily of the family of nlc-width bounded graph classes.
vertex disjoint paths on clique-width bounded graphs. we show that the l vertex disjoint paths problem between l pairs of vertices can be solved in linear time for co-graphs but is np-complete for graphs of clique-width at most 6 and nlc-width at most 4. the np-completeness follows from the fact that the line graph of a graph of tree-width k has clique-width at most 2k + 2 and nlc-width at most k + 2, and a result by nishizeki et al. [the edge-disjoint paths problem is np-complete for series-parallel graphs, discrete appl. math. 115 (2001) 177-186]. the vertex disjoint paths problem is the first graph problem shown to be np-complete on graphs of bounded clique-width but solvable in linear time on co-graphs and graphs of bounded tree-width. additionally, we show that the r vertex disjoint paths problem between each of l pairs of vertices can be solved in polynomial time for co-graphs, if l is given to the input, and for graphs of bounded clique-width, if l is fixed.
kolmogorov complexity and non-determinism. we are concerned with kolmogorov complexity of strings produced by non-deterministic algorithms. for this, we consider five classes of non-deterministic description modes: (i) non-bounded description modes in which the number of outputs depends on programs, (ii) distributed description modes in which the number of outputs depends on the size of the outputs, (iii) spread description modes in which the number of outputs depends on both programs and the size of the outputs, (iv) description modes for which each string has a unique minimal description, and lastly (v) description modes for which the set of minimal length descriptions is a prefix set.
a note on a scale-sensitive dimension of linear bounded functionals in banach spaces. we show that "b is of type p > 1" is a necessary and sufficient condition for a learnability of a class of linear bounded functionals with norm < 1 restricted to the unit ball in banach space b. on the way, we give very short probabilistic proof for vapnik's result (hilbert space and improved) and improve our result with pascal koiran for convex halls of indicator functions. the approach we use in this paper allows to connect various results about learnability and approximation.
metaphors and heuristic-driven theory projection (hdtp). a classical approach of modeling metaphoric expressions uses a source concept network that is mapped to a target concept network. both networks are often represented as algebras. in this paper, a representation using the mathematically sound framework of heuristic-driven theory projection (hdtp) is presented which is--although quite different from classical approaches--algebraic in nature, too. hdtp has the advantage that a structural description of source and target can be given and the connection between both domains are more clearly specified. the major aspects of the formal properties of hdtp, the specification of the underlying algorithm hdtp-a, and the development of a formal semantics for analogical reasoning will be discussed. we will apply hdtp to different types of metaphors.
equations in free semigroups with involution and their relation to equations in free groups. a free semigroup with involution (fsi) is essentially the set of words over a given alphabet plus an operator which reverses words. the paper introduces equations in fsi and show that they are the right objects to deal with when studying the complexity of equations in free groups. on these lines, we generalize to fsi several results valid for word equations, like the overlapping lemma, the 2o(|e|)-bound on the exponent of periodicity of minimal solutions, and the np-hard lower bound.the main result of the paper is the reduction of the problem of satisfiability of equations in free groups to the satisfiability of equations in fsi by a non-deterministic polynomial time transformation.
algebraic proof systems over formulas. we introduce two algebraic propositional proof systems f-ns and f-pc. the main difference of our systems from (customary) nullstellensatz and polynomial calculus is that the polynomials are represented as arbitrary formulas (rather than sums of monomials). short proofs of tseitin's tautologies in the constant-depth version of f-ns provide an exponential separation between this system and polynomial calculus.we prove that f-ns (and hence f-pc) polynomially simulates frege systems, and that the constant-depth version of f-pc over finite field polynomially simulates constant-depth frege systems with modular counting. we also present a short constant-depth f-pc (in fact, f-ns) proof of the propositional pigeon-hole principle. finally, we introduce several extensions of our systems and pose numerous open questions.
how to whack moles. in the classical whack-a-mole game moles that pop up at certain locations must be whacked by means of a hammer before they go under ground again. the goal is to maximize the number of moles whacked. this problem can be formulated as an online optimization problem: requests (moles) appear over time at points in a metric space and must be served (whacked) by a server (hammer) before their deadlines (i.e., before they disappear). an online algorithm learns each request only at its release time and must base its decisions on incomplete information. we study the online whack-a-mole problem (wham) on the real line and on the uniform metric space. while on the line no deterministic algorithm can achieve a constant competitive ratio, we provide competitive algorithms for the uniform metric space. our online investigations are complemented by complexity results for the offline problem.
computability of the additive complexity of algebraic circuits with root extracting. we design an algorithm for computing the generalized (algebraic circuits with root extraction) {\em additive complexity} of any rational function. it is the first computability result of this sort on the additive complexity of algebraic circuits (cf.~\cite{sw80}).
authentication tests and the structure of bundles. suppose a principal in a cryptographic protocol creates and transmits a message containing a new value v, later receiving v back in a different cryptographic context. it can be concluded that some principal possessing the relevant key has received and transformed the message in which v was emitted. in some circumstances, this principal must be a regular participant of the protocol, not the penetrator. an inference of this kind is an authentication test. we introduce two main kinds of authentication test. an outgoing test is one in which the new value v is transmitted in encrypted form, and only a regular participant can extract it from that form. an incoming test is one in which v is received back in encrypted form, and only a regular participant can put it in that form. we combine these two tests with a supplementary idea, the unsolicited test, and a related method for checking that keys remain secret. together, these techniques determine what authentication properties are achieved by a wide range of cryptographic protocols. in this paper we introduce authentication tests and prove their soundness. we illustrate their power by giving new and straightforward proofs of security goals for several protocols. we also illustrate how to use the authentication tests as a heuristic for finding attacks against incorrect protocols. finally, we suggest a protocol design process. we express these ideas in the strand space formalism (thayer et al. j. comput. security 7 (1999) 191-230), which provides a convenient context to prove them correct.
on the algorithmic inversion of the discrete radon transform. the present paper deals with the computational complexity of the discrete inverse problem of reconstructing finite point sets and more general functionals with finite support that are accessible only through some of the values of their discrete radon transform. it turns out that this task behaves quite differently from its well-studied companion problem involving 1-dimensional x-rays. concentrating on the case of coordinate hyperplanes in rd and on functionals :zdd with d{{0,1,...,r},n0} for some arbitrary but fixed r, we show in particular that the problem can be solved in polynomial time if information is available for m such hyperplanes when md1 but is np-hard for m=d and d={0,1,...,r}. however, for d=n0, a case that is relevant in the context of contingency tables, the problem is still in p. similar results are given for the task of determining the uniqueness of a given solution and for a related counting problem.
a relation algebraic model of robust correctness. we propose a new and uniform abstract relational approach to demonic nondeterminism and robust correctness similar to hoare's chaos semantics. it is based on a specific set of relations on flat lattices. this set forms a complete lattice. furthermore, we deal with the refinement of programs. among other things, we show the correctness of the unfold/fold method for demonic nondeterminism and robust correctness as refinement relation and investigate relationships to dijkstra's wp-calculus and morgan's specification statement. &mdash;authors' abstract
chordless paths through three vertices. consider the following problem, which we call "chordless path through three vertices" or cp3v, for short: given a simple undirected graph g = (v, e), a positive integer k, and three distinct vertices s, t, and v ∈ v, is there a chordless path of length at most k from s via v to t in g? in a chordless path, no two vertices are connected by an edge that is not in the path. alternatively, one could say that the subgraph induced by the vertex set of the path in g is the path itself. the problem has arisen in the context of service deployment in communication networks. we resolve the parametric complexity of cp3v by proving it w[1]-complete with respect to its natural parameter k. our reduction extends to a number of related problems about chordless paths and cycles. in particular, deciding on the existence of a single directed chordless (s, t)-path in a digraph is also w[1]-complete with respect to the length of the path.
the parallel composition of uniform processes with data. a general basis for the definition of a finite but unbounded number of parallel processes is the equation s(n; dt)=p(0; get(0; dt)) &dgr; eq(n; 0). (p(n; get(n; dt)) //s(n&minus; 1; dt)). in this formula eq(n; 0) is an equality test, and get(n; dt) denotes the nth data element in table dt. we derive a linear process equation with the same behaviour as s(n; dt), and show that this equation is well-defined, provided one adopts the principle cl-rsp from bezem and groote proceedings of concur'94, springer, berlin, 1994, pp. 401-416). in order to demonstrate the strength of our result, we use it for the analysis of a standard example. we show that n + 1 concatenated buffers form a queue of capacity n + 1. copyright 2001 elsevier science b.v.
parameterised boolean equation systems. boolean equation system are a useful tool for verifying formulas from modal µ-calculus on transition systems (see [mader, lecture notes in computer science, vol. 1019, 1995, pp. 72-88] for an excellent treatment). we are interested in an extension of boolean equation systems with data. this allows to formulate and prove a substantially wider range of properties on much larger and even infinite state systems. in previous works [groote and mateescu, lecture notes in computer science, vol. 1548, 1999, pp. 74-90; groote and willemse, sci. comput. program., 2005] it has been outlined how to transform a modal formula and a process, both containing data, to a so-called parameterised boolean equation system, or equation system for short. in this article we focus on techniques to solve such equation systems.we introduce a new equivalence between equation systems, because existing equivalences are not compositional. we present techniques similar to gauß elimination as outlined in [mader, lecture notes in computer science, vol. 1019, 1995, pp. 72-88] that allow to solve each equation system provided a single equation can be solved. we give several techniques for solving single equations, such as approximation (known), patterns (new) and invariants (new). finally, we provide several small but illustrative examples of verifications of modal µ-calculus formulas on concrete processes to show the use of the techniques.
computational aspects of the 2-dimension of partially ordered sets. a well-known method to represent a partially ordered set p (order for short) consists in associating to each element of p a subset of a fixed set s = { 1,..., k} such that the order relation coincides with subset inclusion. such an embedding of p into 2s (the lattice of all subsets of s) is called a bit-vector encoding of p. these encodings provide an interesting way to store an order. they are economical with space and comparisons between elements can be performed efficiently via subset inclusion tests.given an order p, minimizing the size of the encoding, i.e. the cardinal of s, is however a difficult problem. the smallest size is called the 2-dimension of p and denoted by dim2(p). in the literature, the decision problem for the 2-dimension has been classified as np-complete and generating small bit-vector encodings is a challenging issue.several works deal with bit-vector encodings from a theoretical point of view in this article, we focus on computational complexity results. after a synthesis of known results, we come back on the np-completeness by detailing a proof and enforcing the conclusion with non-approximability ratios. besides this general result, we investigate the complexity of the 2-dimension for the class of trees. we describe a 4-approximation algorithm for this class. it uses an optimal balancing strategy which solves a conjecture of krall, vitek and horspool. several interesting open problems are listed.
periodicity in one-dimensional peg duotaire. we consider the single-hop version of one-dimensional peg duotaire, a two player version of peg solitaire in which players move alternatively and the last player to move wins. we determine the nim-values of all positions consisting of two sets of consecutive pegs separated by a hole. we show that two classes of positions produce periodic sequences of nim-values, and we conjecture that two other classes exhibit similar periodicity.
speeding up the detection of evolutive tandem repeats. we recently introduced evolutive tandem repeats with jump (using hamming distance) (proc. mfcs'02: the 27th internat. symp. mathematical foundations of computer science, warszawa, otwock, poland, august 2002, lecture notes in computer science, vol. 2420, springer, berlin, pp. 292-304) which consist in a series of almost contiguous copies having the following property: the hamming distance between two consecutive copies is always smaller than a given parameter e. in this article, we present a significative improvement that speeds up the detection of evolutive tandem repeats. it is based on the progressive computation of distances between candidate copies participating to the evolutive tandem repeat. it leads to a new algorithm, still quadratic in the worst case, but much more efficient on average, authorizing larger sequences to be processed.
a categorical model for the geometry of interaction. we consider the multiplicative and exponential fragment of linear logic (mell) and give a geometry of interaction (goi) semantics for it based on unique decomposition categories. we prove a soundness and finiteness theorem for this interpretation. we show that girard's original approach to goi 1 via operator algebras is exactly captured in this categorical framework.
bisimulation relations for dynamical, control, and hybrid systems. the fundamental notion of bisimulation equivalence for concurrent processes, has escaped the world of continuous, and subsequently, hybrid systems. inspired by the categorical framework of joyal, nielsen and winskel, we develop novel notions of bisimulation equivalence for dynamical systems as well as control systems. we prove that these notions can be captured by the abstract notion of bisimulation as developed by joyal, nielsen and winskel. this is the first unified notion of system equivalence that transcends discrete and continuous systems. furthermore, this enables the development of a novel and natural notion of bisimulation for hybrid systems, which is the final goal of this paper.
routing algorithm for multicast under multi-tree model in optical networks. to establish a multicast connection in a wavelength routed optical network, two steps are needed under the multi-tree model. one is to construct a set of light-trees rooted at the source node such that in each of them at most a specified number of destination nodes are allowed to receive the data and every destination node must be designated in one of them to receive the data. the other is to assign a wavelength to each of the produced light-trees in such a way that two light-trees must be assigned two distinct wavelengths if they use a common link. in this paper we mainly study how to construct a multicast routing of minimal cost under the multitree model in optical networks, where the routing cost is total costs of the produced light-trees. we propose a 4-approximation algorithm for this np-hard problem.
approximability results for stable marriage problems with ties. we consider instances of the classical stable marriage problem in which persons may include ties in their preference lists. we show that, in such a setting, strong lower bounds hold for the approximability of each of the problems of finding an egalitarian, minimum regret and sex-equal stable matching. we also consider stable marriage instances in which persons may express unacceptable partners in addition to ties. in this setting, we prove that there are constants δ, δ' such that each of the problems of approximating a maximum and minimum cardinality stable matching within factors of δ, δ' (respectively) is np-hard, under strong restrictions. we also give an approximation algorithm for both problems that has a performance guarantee expressible in terms of the number of lists with ties. this significantly improves on the best-known previous performance guarantee, for the case that the ties are sparse. our results have applications to large-scale centralized matching schemes.
complexity analysis of the sat engine: dna algorithms as probabilistic algorithms. taking advantage of the power of dna molecules to spontaneously form hairpin structures, sakamoto et al. designed a molecular algorithm to solve instances of the satisfiability problem on boolean expressions in clausal form (the sat problem), and by developing new experimental techniques for molecular biology, they succeeded in solving a 6-variable, 10-clause instance of the 3-sat problem (sakamoto et al., science 288 (2000) 1223). sakamoto et al. call this computational architecture the sat engine. in this paper, we analyze the complexity of the sat engine as a probabilistic algorithm. we first estimate the time dependence of the probability of hairpin formation using standard chemical kinetics and the jacobson-stockmayer expression. we then estimate the number of dna molecules required to solve the satisfiability problem with a given error probability. by taking the number of dna molecules into account, we finally estimate the minimum total time and number of strands, respectively, required to achieve combined error rates of < ε1 (the probability of a false positive) and ε2 (the probability of a false negative). if the number of clauses is n, then the time required for solving the problem is proportional to n1.5(ln(1/ε1)+ln(ln(1/ε2)))+n2.5 ln(3+α),and the number of necessary dna molecules is proportional to (3 + α)n ln(1/ε2) with arbitrarily small α > 0.
algebraic aspects of emission tomography with absorption. in a previous paper the authors analysed the classical discrete tomography problem to construct a 0-1-matrix with given line sums in some given directions. one of the physical representations is that material at the lattice points corresponding to 1's emit units of radiation and that the radiation is measured along the given lines. in the present paper they extend their approach to the case that the intermediate material is absorbing the radiation. they generalise results obtained by kuba and nivat.
formal logics of discovery and hypothesis formation by machine. the following are the aims of the paper: (1) to call the attention of the community of discovery science (ds) to certain existing formal systems for ds developed in prague in the 1960s through the 1980s suitable for ds and unfortunately largely unknown. (2) to illustrate the use of the calculi in question by the example of the guha method of hypothesis generation by computer, subjecting this method to a critical evaluation in the context of contemporary data mining. (3) to stress the importance of fuzzy logic for ds and to present the state of mathematical foundations of fuzzy logic. (4) finally, to present a running research program of developing calculi of symbolic fuzzy logic for ds and for a fuzzy guha method.
on the max-flow min-cut ratio for directed multicommodity flows. we present a pure combinatorial problem whose solution determines max-flow min-cut ratio for directed multicommodity flows. in addition, this combinatorial problem has applications in improving the approximation factor of the greedy algorithm for the maximum edge disjoint path problem. more precisely, our upper bound improves the approximation factor for this problem to o(n3/4).
binary (generalized) post correspondence problem. we give a new proof for the decidability of the binary post correspondence problem (pcp) originally proved in 1982 by ehrenfeucht, karhumki and rozenberg. our proof is complete and somewhat shorter than the original proof although we use the same basic. copyright 2002 elsevier science b.v. all rights reserved.
on a problem of fagin concerning multivalued dependencies in relational databases. multivalued dependencies (mvds) are an important class of relational constraints that is fundamental to relational database design. reflexivity axiom, complementation rule, and pseudo-transitivity rule form a minimal set of inference rules for the implication of mvds. the complementation rule plays a distinctive role as it takes into account the underlying relation schema r which the mvds are defined on. the r-axiom 0 ↠--r is much weaker than the complementation rule, but is sufficient to form a minimal set of inference rules together with augmentation and pseudo-difference rule. fagin has asked whether it is possible to reduce the power of the complementation rule and drop the augmentation rule at the same time and still obtain a complete set. it was argued that there is a trade-off between complementation rule and augmentation rule, and one can only dispense with one of these rules at the same time. it is shown in this paper that an affirmative answer to fagin's problem can nevertheless be achieved. in fact, it is proven that r-axiom together with a weaker form of the reflexivity axiom, pseudo-transitivity rule and exactly one of union, intersection or difference rule form such desirable minimal sets. the positive solution to this problem gives further insight into the difference between the notions of functional and multivalued dependencies.
a new routing algorithm for multirate rearrangeable clos networks. in this paper, we study the problem of finding routing algorithms on the multirate rearrangeable clos networks which use as few number of middle-stage switches as possible. we propose a new routing algorithm called the "grouping algorithm". this is a simple algorithm which uses fewer middle-stage switches than all known strategies, given that the number of input-stage switches and output-stage switches are relatively small compared to the size of input and output switches. in particular, the grouping algorithm implies that m = 2n + [(n - 1)/2k] is a sufficient number of middle-stage switches for the symmetric three-stage clos network c(n, m, r) to be multirate rearrangeable, where k is any positive integer and r ≤ n/(2k - 1).
online independent sets. we study the online version of the independent set problem in graphs. the vertices of an input graph are given one by one along with their edges to previous vertices, and the task is to decide whether to add each given vertex to an independent set solution. the goal is to maximize the size of the independent set, relative to the size of the optimal independent set. since it is known that no online algorithm can attain competitive ratio better than n - 1, where n denotes the number of vertices, we study here relaxations where the algorithm can hedge its bets by maintaining multiple alternative solutions.we introduce two models. in the first model, the algorithm can maintain a multiple number (r(n)) of solutions (independent sets) and choose the largest one as the final solution. we show that the best competitive ratio for this model is θ(n/logn) when r(n) is a polynomial and θ(n) when r(n) is a constant. in the second more powerful model, the algorithm can copy intermediate solutions and extend the copied solutions in different ways. we obtain an upper bound o(n/logn) and a lower bound ω(n/log3n) for the best possible competitive ratio when r(n) is a polynomial. furthermore, we show a tight θ(n) bound when r(n) is a constant. lower bound results of this paper hold also for randomized online algorithms against an oblivious adversary.
deciding implication for functional dependencies in complex-value databases. modern applications increasingly require the storage of data beyond relational structure. the challenge of providing well-founded data models that can handle complex objects such as lists, sets, multisets, unions and references has not been met yet in a completely satisfactory way. the success of such data models will greatly depend on the existence of automated database design techniques that generalise achievements from relational databases. in this paper, we study the implication problem of functional dependencies (fds) in the presence of records, sets, multisets and lists. database schemata are defined as nested attributes, database instances as nested relations and fds are defined in terms of subattributes of the database schema. the expressiveness of fds deviates fundamentally from previous approaches in different data models including the nested relational data model and xml.the implication problem is to decide whether for an arbitrary database schema, and an arbitrary set σ ∪ {σ} of fds defined on that schema, every database instance that satisfies all fds in σ also satisfies σ. the difficulty in generalising the solution from the relational data model to the presence of sets and multisets is caused by the fact that the value on the join of subattributes is no longer determined by the values on the subattributes. based on the notion of a unit, we propose to decompose the database schema in such a way that the closure of a set of nested attributes can be computed on the components of the schema. the implementation of the algorithm is based on a representation theorem for brouwerian algebras. the main contribution is the proof that the algorithm works correctly and in polynomial-time in the size of the input. defining the size of the input is not trivial since the measure should both generalise the one that is used for relational databases and do justice to the presence of sets and multisets. our solution to the implication problem allows to solve other important problems that occur in database design. we present polynomial-time algorithms to determine non-redundant covers of sets of fds, and to decide whether a given set of subattributes forms a superkey.
graphs determined by polynomial invariants. many polynomials have been defined associated to graphs, like the characteristic, matchings, chromatic and tutte polynomials. besides their intrinsic interest, they encode useful combinatorial information about the given graph. it is natural then to ask to what extent any of these polynomials determines a graph and, in particular, whether one can find graphs that can be uniquely determined by a given polynomial. in this paper we survey known results in this area and, at the same time, we present some new results.
randomized approximation of the stable marriage problem. while the original stable marriage problem requires all participants to rank all members of the opposite sex in a strict order, two natural variations are to allow for incomplete preference lists and ties in the preferences. either variation is polynomially solvable, but it has recently been shown to be np-hard to find a maximum cardinality stable matching when both of the variations are allowed. it is easy to see that the size of any two stable matchings differ by at most a factor of two, and so, an approximation algorithm with a factor two is trivial. in this paper, we give a randomized approximation algorithm randbrk and show that its expected approximation ratio is at most 10/7 (< 1.4286) for a restricted but still np-hard case, where ties occur in only men's lists, each man writes at most one tie, and the length of ties is two. we also show that our analysis is nearly tight by giving a lower bound 32/23(≥ 1.3913) for randbrk. furthermore, we show that these restrictions except for the last one can be removed without increasing the approximation ratio too much.
axiomatisations of functional dependencies in the presence of records, lists, sets and multisets. we investigate functional dependencies in databases that support complex values such as records, lists, sets anu multisets. therefore, an abstract algebraic framework is proposed that classifies data models according to the underlying types they support. this allows to emphasise the impact of the data types rather than the specifics of a particular data model.the main results are finite, minimal, sound and complete sets of inference rules for the implication of functional dependencies in the presence of records and all combinations of lists, sets and multisets. the inference rules are similar to armstrong's original axioms for the relational data model, thanks to the algebraic framework. the completeness result, however, requires a deep analysis in the case of sets and, in particular, multisets.
unsupervised learning in neural computation. in this article, we consider unsupervised learning from the point of view of applying neural computation on signal and data analysis problems. the article is an introductory survey, concentrating on the main principles and categories of unsupervised learning. in neural computation, there are two classical categories for unsupervised learning methods and models: first, extensions of principal component analysis and factor analysis, and second, learning vector coding or clustering methods that are based on competitive learning. these are covered in this article. the more recent trend in unsupervised learning is to consider this problem in the framework of probabilistic generative models. if it is possible to build and estimate a model that explains the data in terms of some latent variables, key insights may be obtained into the true nature and structure of the data. this approach is also briefly reviewed.
the minimum-entropy set cover problem. we consider the minimum entropy principle for learning data generated by a random source and observed with random noise.in our setting we have a sequence of observations of objects drawn uniformly at random from a population. each object in the population belongs to one class. we perform an observation for each object which determines that it belongs to one of a given set of classes. given these observations, we are interested in assigning the most likely class to each of the objects.this scenario is a very natural one that appears in many real life situations. we show that under reasonable assumptions finding the most likely assignment is equivalent to the following variant of the set cover problem. given a universe u and a collection i = (s1, ..., st) of subsets of u, we wish to find an assignment f : u → i such that u ∈ f(u) and the entropy of the distribution defined by the values |f-1 (si)| is minimized.we show that this problem is np-hard and that the greedy algorithm for set cover s with an additive constant error with respect to the optimal cover. this sheds a new light on the behavior of the greedy set cover algorithm. we further enhance the greedy algorithm and show that the problem admits a polynomial time approximation scheme (ptas).finally, we demonstrate how this model and the greedy algorithm can be useful in real life scenarios, and in particular, in problems arising naturally in computational biology.
the propositional dynamic logic of deterministic, well-structured programs. we consider a restricted propositional dynamic logic, strict deterministic propositional dynamic logic (sdpdl), which is appropriate for reasoning about deterministic well-structured programs. in contrast to pdl, for which the validity problem is known to be complete in deterministic exponential time, the validity problem for sdpdl is shown to be polynomial space complete. we also show that sdpdl is less expressive than pdl. the results rely on structure theorems for models of satisfiable sdpdl formulas, and the proofs give insight into the effects of nondeterminism on intractability and expressiveness in program logics.
two applications of analytic functors. we apply the theory of analytic functors to two topics related to theoretical computer science. one is a mathematical foundation of certain syntactic well-quasi-orders and well-orders appearing in graph theory, the theory of term rewriting systems, and proof theory. the other is a new verification of the lagrange-good inversion formula using several ideas appearing in semantics of lambda calculi, especially the relation between categorical traces and fixpoint operators. copyright 2002 elsevier science b.v.
competitive exploration of rectilinear polygons. exploring a polygon with robots when the robots do not have knowledge of the surroundings can be viewed as an online problem. typical for online problems is that decisions must be made based on past events without complete information about the future. in our case the robots do not have complete information about the environment. competitive analysis can be used to measure the performance of methods solving online problems. the competitive ratio of such a method is the ratio between the method's performance and the performance of the best method having full knowledge of the future. we prove constant competitive strategies and lower bounds for exploring a simple rectilinear polygon in the l1 metric.
two categories of effective continuous cpos. this paper presents two categories of effective continuous complete partial orders (cpos). we define a new criterion on the basis of a cpo so as to make the resulting category of consistently complete continuous cpos cartesian closed. we also generalise to continuous cpos the definition of a complete set, which was used as a definition of effective bifinite domains in hamrin and stoltenberg-hansen [cartesian closed categories of effective domains, in: h. schwichtenberg, r. steinbrüggen (eds.), proof and system-reliability, kluwer academic publishers, dordrecht, 2002, pp. 1-20], and investigate the closure results that can be obtained.
density results on floating-point invertible numbers. let fk denote the k-bit mantissa floating-point (fp) numbers. we prove a conjecture of muller according to which the proportion of numbers in fk with no fp-reciprocal (for rounding to the nearest element) approaches ½ - 3/2log4/3 ≈ 0.06847689 as k → ∞. we investigate a similar question for the inverse square root.
regular binoid expressions and regular binoid languages. a bisemigroup consists of a set of elements and two associative operations. a bimonoid is a bisemigroup which has an identity to each associative operation. a binoid is a bimonoid which has the same identity to the two associative operations. in a previous paper, we introduced these three notions, and studied formal languages over free binoids (which are subsets of a free binoid where any element of a free binoid is denoted by its standard form which is a sequence of symbols). in this paper, we introduce a class of expressions called regular binoid expressions and show that any binoid language denoted by a regular binoid expression can be regarded to be a set of the standard forms of elements of a free binoid which can be recognized as a regular (monoid) language.
equivalence of regular binoid expressions and regular expressions denoting binoid languages over free binoids. a free binoid σ*(○, •) over a finite alphabet σ is a free algebra generated by σ with two independent associative operators, ○ and •. it has also the same identity λ to both operations. any element of σ*(○, •) is denoted uniquely by a sequence of symbols from the extended alphabet e(σ) = σ ∪ {○, • (,)}, and any subset of a free binoid is called a binoid language. the set of regular binoid expressions are introduced so that all languages denoted by regular binoid expressions are those which contain finite binoid languages, and closed under five operations, ∪, ○-concatenation, •-concatenation, ○-closure and •-closure. it is shown that for any regular (monoid) expression denoting a binoid language r, there exists a regular binoid expression denoting r. this result together with the main result in a previous paper implies that the class of binoid languages denoted by binoid regular expressions is the same as the class of binoid languages denoted by regular expressions over free binoids.
on the lengths of symmetry breaking-preserving games on graphs. given a graph g, we consider a game where two players, a and b, alternatingly, color edges of g in red and in blue, respectively. let lsym(g) be the maximum number of moves in which b is able to keep the red and the blue subgraphs isomorphic, if a plays optimally to destroy the isomorphism. this value is a lower bound for the duration of any avoidance game on g under the assumption that b plays optimally. we prove that if g is a path or a cycle of odd length n, then ω(logn) ≤ lsym(g) ≤ o(log2 n). the lower bound is based on relations with ehrenfeucht-fraïssé games from model theory. we also consider complete graphs and prove that lsym(kn) = o(1).
a typed context calculus. this paper develops a typed calculus for contexts i.e., lambda terms with "holes". in addition to ordinary lambda terms, the calculus contains labeled holes, hole abstraction and context application for manipulating first-class contexts. the primary operation for contexts is hole-filling, which captures free variables. this operation conflicts with substitution of the lambda calculus, and a straightforward mixture of the two results in an inconsistent system. we solve this problem by defining a type system that precisely specifies the variable-capturing nature of contexts and that keeps track of bound variable renaming. these mechanisms enable us to define a reduction system that properly integrates&brg;-reduction and hole-filling. the resulting calculus is church-rosser and the type system has the subject reduction property. we believe that the context calculus will serve as a basis for developing a programming language with advanced features that call for manipulation of open terms. copyright 2001 elsevier science b.v.
efficient reconfiguration algorithms of de bruijn and kautz networks into linear arrays. in this paper, we prove the existence of ranking and unranking algorithms on d-ary de bruijn and kautz graphs. a ranking algorithm takes as input the label of a node and returns the rank r of that node in a hamiltonian path (06r6n - 1, where n is the order of the considered graph). an unranking algorithm takes as input an integer r (06r6n - 1) and returns the label of the rth ranked node in a hamiltonian path. our results generalize results given by annexstein for binary de bruijn graphs. the key of our framework is based on a recursive construction of hamiltonian paths in de bruijn and kautz graphs. the construction uses suitable uniform homomorphisms of de bruijn and kautz graphs of diameter d on de bruijn graphs of diameter d - 1. our ranking and unranking algorithms have sequential time complexity in o(d2), where d is the length of node labels.
a non-hausdorff quaternion multiplication. we denote by (s3)' the barycentric subdivision of the minimal model s3 of the three-dimensional sphere in the category of finite posets and order-preserving functions, op(x) is the poset obtained by reversing the order relations in a poset x. we describe a finite model of a quaternion multiplication in the form of a morphism op(s3)' × (s3)' → s3 that restricts to weak homotopy equivalences on the axes. for such multiplications a version of hopf's construction can be defined that yields finite models of non-trivial homotopy classes.
a coalgebraic approach to the semantics of the ambient calculus. recently, various process calculi have been introduced which are suited for the modelling of mobile computation and in particular the mobility of program code; a prominent example is the ambient calculus. due to the complexity of the involved spatial reduction, there is--in contrast to the situation in standard process algebra--up to now no satisfying coalgebraic representation of a mobile process calculus. here, we discuss a coalgebraic denotational semantics for the ambient calculus, viewed as a step towards a generic coalgebraic framework for modelling mobile systems. crucial features of our modelling are a set of gsos style transition rules for the ambient calculus, a hardwiring of the so-called hardening relation in the functorial signature, and a set-based treatment of hidden name sharing. the formal representation of this framework is cast in the algebraic-coalgebraic specification language cocasl.
on quasi orders of words and the confluence property. we investigate the confluence property, that is, the property of a language to contain, for any two words of it, one which is bigger, with respect to a given quasi order on the respective free monoid, than each of the former two. this property is investigated mainly for regular and context-free languages. as a consequence of our study, we give an answer to an old open problem raised by haines concerning the effective regularity of the sets of subwords. namely, we prove that there are families with a decidable emptiness problem for which the regularity of the sets of subwords is not effective.
many aspects of defect theorems. we give a survey and a unified presentation of the defect theorem, its generalizations and recent aspects of interest. in its basic form, the defect theorem states that if a set of n words satisfies a nontrivial relation, then these words can be expressed simultaneously as products of at most n - 1 words. in other words, dependency of words causes a defect effect. there does not exist just one defect theorem, but several ones depending on the restrictions that are put to the n - 1 words. the defect theorem is closely related to equations of words, and in this way to the compactness theorem for systems of word equations.
mathematics based on incremental learning - excluded middle and inductive inference. learning theoretic aspects of mathematics and logic have been studied by many authors. they study how mathematical and logical objects are algorithmically "learned" (inferred) from finite data. although they study mathematical objects, the objective of the studies is learning. in this paper, a mathematics whose foundation itself is learning theoretic will be introduced. it is called limit-computable mathematics. it was originally introduced as a means for "proof animation", which is expected to make interactive formal proof development easier. although the original objective was not learning theoretic at all, learning theory is indispensable for our research. it suggests that logic and learning theory are related in a still unknown but deep new way.
uniform characterizations of polynomial-query learnabilities. we consider the exact learning in the query model. we deal with all types of queries introduced by angluin: membership, equivalence, superset, subset, disjointness and exhaustiveness queries, and their weak (or restricted) versions where no counterexample is returned. for each of all possible combinations of these queries, we uniformly give complete characterizations of boolean concept classes that are learnable using a polynomial number of polynomial-sized queries. our characterizations show the equivalence between the learnability of a concept class c using queries and the existence of a good query for any subset h of c which is guaranteed to reject a certain fraction of candidate concepts in h regardless of the answer. as a special case for equivalence queries alone, our characterizations directly correspond to the lack of the approximate fingerprint property, which is known to be a sufficient and necessary condition for the learnability using equivalence queries.
towards the animation of proofs - testing proofs by examples. in this paper, we introduce the notion of proof animation, which is a new application of the principle of "curry-howard isomorphism" to formal proof development. logically, proof animation is merely a contrapositive of "proofs as programs", which is an application of curry-howard isomorphism to formal program development. nonetheless, this new perspective is completely different. the motivation, aims, problems, and a prototype tool under development are presented in this paper. we also discuss possibility of "proof engineering" guided by the curry-howard isomorphism. copyright 2002 elsevier science b.v.
a characterization of periodicity of bi-infinite words. a finite word is called bordered if it has a proper prefix which is also a suffix of that word. costa proves in [theoret. comput. sci. 290(3) (2003) 2053-2061] that a bi-infinite word w is of the form ωf g fω, for some finite words f and g, if, and only if, there is a factorization w = suv, with u ∈ a* such that every factor s'uv', with s' ≤ s and v' ≤ v, is bordered. we present a shorter proof of that result in this paper.
the wide window string matching algorithm. generally, current string matching algorithms make use of a window whose size is equal to pattern length. in this paper, we present a novel string matching algorithm named ww (for wide window) algorithm, which divides the text into [n/m] overlapping windows of size 2m - 1. in the windows, the algorithm attempts m possible occurrence positions in parallel. it firstly searches pattern suffixes from middle to right with a forward suffix automaton, shifts the window directly when it fails, otherwise, scans the corresponding prefixes backward with a reverse prefix automaton. theoretical analysis shows that ww has optimal time complexity of o(n) in the worst, o(n/m) best and o(n(logσm)/m) for average case. experimental comparison of ww with existing algorithms validates our theoretical claims for searching long patterns. it further reveals that ww is also efficient for searching short patterns.
on the independence of equations in three variables. we prove that an independent system of equations in three variables with a nonperiodic solution and at least two equations consists of balanced equations only. for that, we show that the intersection of two different entire systems contains only balanced equations, where an entire system is the set of all equations solved by a given morphism. furthermore, we establish that two equations which have a common nonperiodic solution have the same set of periodic solutions or are not independent.
improved algorithms for two single machine scheduling problems. in this paper, we investigate two single machine scheduling problems. the first problem addresses a class of the two-stage scheduling problems in which the first stage is job production and the second stage is job delivery. for the case that jobs are processed on a single machine and delivered by a single vehicle to one customer area, with the objective of minimizing the time when all jobs are completed and delivered to the customer area and the vehicle returns to the machine, an approximation algorithm with a worst-case ratio of 5/3 is known and no approximation can have a worst-case of 3/2 unless p = np. we present an improved approximation algorithm with a worst-case ratio of 53/35, which only leaves a gap of 1/70. the second problem is a single machine scheduling problem subject to a period of maintenance. the objective is to minimize the total completion time. the best known approximation algorithm has a worst-case ratio of 20/17 we present a polynomial time approximation scheme.
counting bordered and primitive words with a fixed weight. a word w is primitive if it is not a proper power of another word, and w is unbordered if it has no prefix that is also a suffix of w. we study the number of primitive and unbordered words w with a fixed weight, that is, words for which the parikh vector of w is a fixed vector. moreover, we estimate the number of words that have a unique border.
on unique factorizations of primitive words. we give a short proof of a result by weinbaum [unique sunwords in nonperiodic words, proc. amer. math. soc. 109(3) (1990) 615-619] stating that each primitive word of length at least 2 has a conjugate w' = uv such that both u and v have a unique position in the cyclic word of w. we emphasize the connection of weinbaum's result to the critical factorization theorem.
on the bandwidth of a hamming graph. the bandwidth of the hamming graph (the product, (kn)d, of complete graphs) has been an open question for many years. recently berger-wolf and rheingold [1] pointed out that the bandwidth of a numbering of the hamming graph may be interpreted as a measure of the effects of noise in the multi-channel transmission of data with that numbering. they also gave lower and upper bounds for it. in this paper we present better lower and upper bounds, showing that the bandwidth of kn)d is asymptotic to √(2/πd)nd as d → ∞.
uniqueness logic. a uniqueness type system is used to distinguish values which are referenced at most once from values which may be referenced an arbitrary number of times in a program. uniqueness type systems are used in the clean and mercury programming languages to provide efficiently updatable data-structures and i/o without compromising referential transparency.in this paper we establish a curry-howard-lambek equivalence between a form of uniqueness types and a 'resource-sensitive' logic. this logic is similar to intuitionistic linear logic, however the modality, which moderates the structural rules in the antecedent in the same way as !, is introduced via the dual ? rules. we discuss the categorical proof theory and models of this new logic, as well as its computational interpretation.
turning back time in markovian process algebra. product-form solutions in markovian process algebra (mpa) are constructed using properties of reversed processes. the compositionality of mpas is directly exploited, allowing a large class of hierarchically constructed systems to be solved for their state probabilities at equilibrium. the paper contains new results on both reversed stationary markov processes as well as mpa itself and includes a mechanisable proof in mpa notation of jackson's theorem for product-form queueing networks. several examples are used to illustrate the approach.
algorithms for multi-level graph planarity testing and layout. in this paper we consider the problems of testing a multi-level graph for planarity and laying out or, drawing, a multi-level graph in a clear way. we introduce a new abstraction of a common integer linear programming formulation of the problems that we call a vertex-exchange graph. we demonstrate how this concept can be used to solve the problems by providing clear and simple algorithms for testing a multi-level graph for planarity and laying out a multi-level graph when planar.
some complexity results for polynomial rational expressions. it is known that any languages of level 3/2 of the straubing-thérien hierarchy can be written as a polynomial expression, that is, a finite union of languages of the form a0*b1a*1 ... b*kak where the ai and bi are subsets of the alphabet. in this paper we prove that such a polynomial expression for a 3/2-level language can be of exponential size. more precisely we exhibit an n-state minimal automaton recognizing a level 3/2 language for which the shortest polynomial expresion has exponential size in n.
pspace-completeness of sliding-block puzzles and other problems through the nondeterministic constraint logic model of computation. we present a nondeterministic model of computation based on reversing edge directions in weighted directed graphs with minimum in-flow constraints on vertices. deciding whether this simple graph model can be manipulated in order to reverse the direction of a particular edge is shown to be pspace-complete by a reduction from quantified boolean formulas. we prove this result in a variety of special cases including planar graphs and highly restricted vertex configurations, some of which correspond to a kind of passive constraint logic. our framework is inspired by (and indeed a generalization of) the "generalized rush hour logic" developed by flake and baum [theoret. comput. sci. 270(1-2) (2002) 8951.we illustrate the importance of our model of computation by giving simple reductions to show that several motion-planning problems are pspace-hard. our main result along these lines is that classic unrestricted sliding-block puzzles are pspace-hard, even if the pieces are restricted to be all dominoes (1 × 2 blocks) and the goal is simply to move a particular piece. no prior complexity results were known about these puzzles. this result can be seen as a strengthening of the existing result that the restricted rush hourtm puzzles are pspace-complete [theoret. comput. sci. 270(1-2) (2002) 895], of which we also give a simpler proof. we also greatly strengthen the conditions for the pspace-hardness of the warehouseman's problem [int. j. robot. res. 3(4) (1984) 76], a classic motion-planning problem. finally, we strengthen the existing result that the pushing-blocks puzzle sokoban is pspace-complete [in: proc. internat. conf. on fun with algorithms, elba, italy, june 1998, pp. 65-76.], by showing that it is pspace-complete even if no barriers are allowed.
separable equilibrium state probabilities via time reversal in markovian process algebra. the reversed compound agent theorem (rcat) is a compositional result that uses markovian process algebra (mpa) to derive the reversed process of certain interactions between two continuous time markov chains at equilibrium. from this reversed process, together with the given, forward process, the joint state probabilities can be expressed as a product-form, although no general algorithm has previously been given. this paper first generalises rcat to multiple (more than two) cooperating agents, which removes the need for multiple applications and inductive proofs in cooperations of an arbitrary number of processes. a new result shows a simple stochastic equivalence between cooperating, synchronised processes and corresponding parallel, asynchronous processes. this greatly simplifies the proof of the new, multi-agent theorem, which includes a statement of the desired product-form solution itself as a product of given state probabilities in the parallel components. the reversed process and product-form thus derived rely on a solution to certain rate equations and it is shown, for the first time, that a unique solution exists under mild conditions--certainly for queueing networks and g-networks.
characterising fs domains by means of power domains. fs domains can be characterised using the upper or lower power domain construction. in these characterisations, separation by the elements of a finite set is replaced by separation by a continuous non-deterministic function with finite image. this notion of separation can be formalised in many different, but equivalent ways.
canonical substitutions tilings of ammann-beenker type. we present a large class of parallelogram tilings that have two important features in common with the ammann-beenker tiling: they can be constructed by canonical projection from z4 ⊂ r4 to a plane, and they admit substitution rules.
contractivity of linear fractional transformations. one possible approach to exact real arithmetic is to use linear fractional transformations (lfts) to represent real numbers and computations on real numbers. recursive expressions built from lfts are only convergent (i.e., denote a well-defined real number) if the involved lfts are sufficiently contractive. in this paper, we define a notion of contractivity for lfts. it is used for convergence theorems and for the analysis and improvement of algorithms for elementary functions.
on log-tape isomorphisms of complete sets. in this paper we study $\log n$-tape computable reductions between sets and investigate conditions under which $\log n$-tape reductions between sets can be extended to $\log n$-tape computable isomorphisms of these sets. as an application of these results we obtain easy to check necessary and sufficient conditions that sets complete under $\log n$-tape reductions in nl, csl, p, np, ptape, etc. are $\log n$-tape isomorphic to the previously known complete sets in the respective classes. as a matter of fact, all the "known" complete sets for nl, csl, p, np, ptape, etc. are now easily seen to be, respectively, $\log n$-tape isomorphic. these results strengthen and extend substantially the previously known results about polynomial time computable reductions and isomorphisms of np and ptape complete sets. furthermore, we show that any set complete in csl, ptape, etc. must be dense and therefore, for example, cannot be over a single letter alphabet.
a non-topological view of dcpos as convergence spaces. the category top of topological spaces is not cartesian closed, but can be embedded into the cartesian closed category conv of converyence spaces. it is well known that the category dcpo of dcpos and scott continuous functions can be embedded into top, and so into conv, by considering the scott topology. we propose a different, "cotopological" embedding of dcpo into conv, which, in contrast to the topological embedding, preserves products. if x is a cotopological dcpo, i.e. a dcpo with the cotopological conv-structure, and y is a topological space, then [x → y] is again topological, and conversely, if x is a topological space, and y a cotopological complete lattice, then [x → y] is again a cotopological complete lattice. for a dcpo d, the topological and the cotopological convergence structures coincide if and only if d is a continuous dcpo. moreover, cotopological dcpos still enjoy some of the properties which characterise continuous dcpos. for instance, all cotopological complete lattices are injective spaces (in conv) w.r.t. topological subspace embeddings.
relations between diagonalization, proof systems, and complexity gaps. in this paper we study diagonal processes over time-bounded computations of one-tape turing machines by diagonalizing only over those machines for which there exist formal proofs that they operate in the given time bound. this replaces the traditional &ldquo;clock&rdquo; in resource bounded diagonalization by formal proofs about running times and establishes close relations between properties of proof systems and existence of sharp time bounds for one-tape turing machine complexity classes. furthermore, these diagonalization methods show that the gap theorem for resource bounded computations does not hold for complexity classes consisting only of languages accepted by turing machines for which it can be formally proven that they run in the required time bound.
a note on natural complete sets and gödel numberings. creative sets (or the complete recursively enumerable sets) play an important role in logic and mathematics and they are known to be recursively isomorphic. therefore, on the one hand, all the creative sets can be viewed as equivalent, on the other hand, we intuitively perceive some creative sets as more ``natural and simpler'''' than others. in this note, we try to capture this intuitive concept precisely by defining a creative set to be natural if all other recursively enumerable sets can be reduced to it by computationally simple reductions and show that these natural creative sets are all isomorphic under the same type of computationally simple mappings. the same ideas are also applied to define natural goedel numberings.
on gödel speed-up and succinctness of language representations. in this note we discuss the similarities and differences between goedel''s result about non-recursive shortening of proofs of formal systems by additional axioms and the corresponding results about the succinctness of different representations of languages.
computation times of np sets of different densities. in this paper, we study the computational complexity of sets of different densities in np. we show that the deterministic computation time for sets in np can depend on their density if and only if there is a collapse or partial collapse of the corresponding higher nondeterministic and deterministic time bonded complexity classes. we show also that for np sets of different densities there exist complete sets of the corresponding density under polynomial time turing reductions. finally, we show that these results can be interpreted as results about the complexity of theorem proving and proof presentation in axiomatized mathematical systems. this interpretation relates fundamental questions about the complexity of our intellectual tools to basic structural problems about p, np, conp, and pspace, discussed in this paper.
erratum to "axiomatisations of functional dependencies in the presence of records, lists, sets and multisets". this note corrects two errors that occurred during the typesetting of our paper "axiomatisations of functional dependencies in the presence of records, lists, sets and multisets", which appeared in hartmann et al. [axiomatisations of functional dependencies in the presence of records, lists, sets and multisets, theoret. comput. sci. 353(2) (2006) 167-196].
towards categorical models for fairness: fully abstract presheaf semantics of sccs with finite delay. we present a presheaf model for the observation of infinite as well as finite computations. we give a concrete representation of the presheaf model as a category of generalised synchronisation trees and show that it is coreflective in a category of generalised transition systems, which are a special case of the general transition systems of hennessy and stirling. this can be viewed as a first step towards representing fairness in categorical models for concurrency. the open map bisimulation is shown to coincide with extended bisimulation of hennessy and stirling, which is essentially fair ctl*-bisimulation. we give a denotational semantics of milner's sccs with finite delay in the presheaf model, which differs from previous semantics by giving the meanings of recursion by final coalgebras and meanings of finite delay by initial algebras of the process equations for delay. finally, we formulate milner's operational semantics of sccs with finite delay in terms of generalised transition systems and prove that the presheaf semantics is fully abstract with respect to extended bisimulation.
split algorithms for skewsymmetric toeplitz matrices with arbitrary rank profile. split levinson-type and schur-type algorithms for the solutions of linear systems with a nonsingular skewsymmetric toeplitz matrix are designed. in contrast to previous ones, the algorithms work for any nonsingular skewsymmetric toeplitz matrix. moreover, generalizations of zw- and wz-factorizations of skewsymmetric toeplitz matrices related to the new split algorithms are presented.
quadrature using 64-bit ieee arithmetic for integrands over [0, 1] with a singularity at 1. we present a detailed study of some problems encountered when quadrature over [0, 1] is attempted with integrands that have a singularity at 1. methods designed to increase the accuracy of such quadratures, for example, the application of periodising transformations, are examined in the context of the representational limitations of 64-bit ieee arithmetic near 1 in [0, 1 ]. a heuristic is proposed for the forecasting of a lower bound on the irremovable error due to these limitations. we conclude by affirming the commonly accepted procedure that where possible, integrals should be symbolically transformed so that any remaining singularity occurs at 0.
a language for configuring multi-level specifications. this paper shows how systems can be built from their component parts with specified sharing. its principle contribution is a modular language for configuring systems. a configuration is a description in the new language of how a system is constructed hierarchically from specifications of its component parts. category theory has been used to represent the composition of specifications that share a component part by constructing colimits of diagrams. we reformulated this application of category theory to view both configured specifications and their diagrams as algebraic presentations of presheaves. the framework of presheaves leads naturally to a configuration language that expresses structuring from instances of specifications, and also incorporates a new notion of instance reduction to extract the component instances from a particular configuration. the configuration language now expresses the hierarchical structuring of multi-level configured specifications. the syntax is simple because it is independent of any specification language; structuring a diagram to represent a configuration is simple because there is no need to calculate a colimit; and combining specifications is simple because structuring is by configuration morphisms with no need to flatten either specifications or their diagrams to calculate colimits.
computing queries with higher-order logics. in the present article, we study the expressive power of higher-order logics on finite relational structures or databases. first, we give a characterization of the expressive power of the fragments σji and πji, for each i ≥ 1 and each number of alternations of quantifier blocks j. then, we get as a corollary the expressive power of hoi for each order i ≥ 2. from our results, as well as from the results of r. hull and j. su, it turns out that no higher-order logic can be complete. even if we consider the union of higher-order logics of all natural orders, i.e., ∪i ≥ 2 hoi, we still do not get a complete logic. so, we define a logic which we call variable order logic (vo) which permits the use of untyped relation variables, i.e., variables of variable order, by allowing quantification over orders. we show that this logic is complete, though even non-recursive queries can be expressed in vo. then we define a fragment of vo and we prove that it expresses exactly the class of r.e. queries. we finally give a characterization of the class of computable queries through a fragment of vo, which is undecidable.
a practical algorithm to find the best subsequence patterns. given two sets of strings, consider the problem to find a subsequence that is common to one set but never appears in the other set. we regard it to find a subsequence pattern which separates these two sets. the problem is known to be np-complete. we naturally generalize it to an optimization problem, where we try to find a subsequence pattern which maximally separates these two sets. we provide a practical algorithm to solve it exactly. our algorithm uses two pruning heuristics based on the properties of subsequence languages, and utilizes the data structure called subsequence automata. we report some experimental results, which show these heuristics and the data structure contribute to reduce the search time.
direct and indirect algorithms for on-line learning of disjunctions. it is easy to design on-line learning algorithms for learning k out of n variable monotone disjunctions by simply keeping one weight per disjunction. such algorithms use roughly o(nk) weights which can be prohibitively expensive. surprisingly, algorithms like winnow require only n weights (one per variable or attribute) and the mistake bound of these algorithms is not too much worse than the mistake bound of the more costly algorithms. the purpose of this paper is to investigate how exponentially many weights can be collapsed into only o(n) weights. in particular, we consider probabilistic assumptions that enable the bayes optimal algorithm's posterior over the disjunctions to be encoded with only o(n) weights. this results in a new o(n) algorithm for learning disjunctions which is related to the bylander's beg algorithm originally introduced for linear regression. besides providing a bayesian interpretation for this new algorithm, we are also able to obtain mistake bounds for the noise free case resembling those that have been derived for the winnow algorithm. the same techniques used to derive this new algorithm also provide a bayesian interpretation for a normalized version of winnow.
tile invariants: new horizons. let t be a finite set of tiles. the group of invariants g(t), introduced by pak (trans. ams 352 (2000) 5525), is a group of linear relations between the number of copies of tiles in tilings of the same region. we survey known results about g, the height function approach, the local move property, various applications and special cases.
approximate algorithms for neural-bayesian approaches. we describe two specific examples of neural-bayesian approaches for complex modeling tasks: survival analysis and multitask learning. in both cases, we can come up with reasonable priors on the parameters of the neural network. as a result, the bayesian approaches improve their (maximum likelihood) frequentist counterparts dramatically. by illustrating their application on the models under study, we review and compare algorithms that can be used for bayesian inference: laplace approximation, variational algorithms, monte carlo sampling, and empirical bayes.
the dynamic complexity of transitive closure is in dyntc. this paper presents a fully dynamic algorithm for maintaining the transitive closure of a binary relation. all updates and queries can be computed by constant depth threshold circuits of polynomial size (tc0 circuits). this places dynamic transitive closure in the dynamic complexity class dyntc0, and implies that transitive closure can be maintained in database systems that include first-order update queries and aggregation operators, using a database with size polynomial in the size of the relation.
p-immune sets with holes lack self-reducibility properties. no p-immune set having exponential gaps is positive-turing self-reducible.
algebraic tools for the concatenation product. this paper is a contribution to the algebraic study of the concatenation product. in the first part of the paper, we extend to the ordered case standard algebraic tools related to the concatenation product, like the schützenberger product and the relational morphisms. we show in a precise way how the ordered schützenberger product corresponds to polynomial operations on languages. in the second part of the paper, we apply these results to establish a bridge between the three standard concatenation hierarchies, namely the straubing-thérien hierarchy, the brzozowski's (or dot-depth) hierarchy and the group hierarchy.
all superlinear inverse schemes are conp-hard. how hard is it to invert np-problems? we show that all superlinearly certified inverses of np problems are conp-hard. to do so, we develop a novel proof technique that builds diagonalizations against certificates directly into a circuit.
reducibility classes of p-selective sets. a set is p-selective if there is a polynomial-time semi-decision algorithm for the set---an algorithm that given any two strings decides which is ``more likely'''' to be in the set. this paper establishes a strict hierarchy among the various reductions and equivalences to p-selective sets.
p-selectivity: intersections and indices. the p-selective sets are those sets for which there is a polynomial-time algorithm that, given any two strings, determines which is ``more likely'''' to belong to the set: if either of the strings is in the set, the algorithm chooses one that is in the set. we prove that, for each k, the k-ary boolean connectives under which the p-selective sets are closed are exactly those that are either completely degenerate or almost-completely degenerate. we determine the complexity of the index set of the r.e. p-selective sets: \sigma_3^0-complete.
the alternating greedy expansion and applications to computing digit expansions from left-to-right in cryptography. the central topic of this paper is the alternating greedy expansion of integers, which is defined to be a binary expansion with digits {0, ±1} with the property that the nonzero digits have alternating signs. we collect known results about this alternating greedy expansion and complement it with other useful properties and algorithms. in the second part, we apply it to give an algorithm for computing a joint expansion of d integers of minimal joint hamming weight from left to right, i.e., from the column with the most significant bits towards the column with the least significant bits. furthermore, we also compute an expansion equivalent to the so-caled w-naf from left to right using the alternating greedy expansion.
electronic jury voting protocols. this work stresses the fact that all current proposals for electronic voting schemes disclose the final tally of the votes. in certain situations, like jury voting, this may be undesirable. we present a robust and universally verifiable membership testing scheme (mts) that allows, among other things, a collection of voters to cast votes and determine whether their tally belongs to some pre-specified small set (e.g., exceeds a given threshold)--our scheme discloses no additional information than that implied from the knowledge of such membership. we discuss several extensions of our basic mts. all the constructions presented combine features of two parallel lines of research concerning electronic voting schemes, those based on mix-networks and in homomorphic encryption.
testing conformance of a deterministic implementation against a non-deterministic stream x-machine. stream x-machines are a formalisation of extended finite state machines that have been used to specify systems. one of the great benefits of using stream x-machines, for the purpose of specification, is the associated test generation technique which produces a test that is guaranteed to determine correctness under certain design for test conditions. this test generation algorithm has recently been extended to the case where the specification is non-deterministic. however, the algorithms for testing from a non-deterministic stream x-machine currently have limitations: either they test for equivalence, rather than conformance or they restrict the source of nondeterminism allowed in the specification. this paper introduces a new test generation algorithm that overcomes both of these limitations, for situations where the implementation is known to be deterministic.
probabilistic quickest path algorithm. due to the increasing role of quickest paths for on-demand routing in computer networks, it is important to compute them faster, perhaps, by trading-off the quality for computational speed. we consider the computation of a quickest path from a source node to a destination node for a given message size in a network with n nodes and m links each of which is specified by bandwidth and delay. every known quickest path algorithm computes m shortest paths either directly or indirectly, and this step contributes to most of its computational complexity which is generally of the form o(m2 + mnlogn). we present a probabilistic quickest path algorithm that computes an approximate quickest path with time complexity o(pm + pn log n) by randomly selecting p ≤ m bandwidths at which the shortest paths are computed. we show that the delay of the computed path is close to optimal with a high probability that approaches 1 exponentially fast with respect to p/m. simulation results indicate that this algorithm computes the optimal quickest paths with p/m < 0.1 for almost all randomly generated networks with n > 40. we also present an algorithm to compute the path-table consisting of these approximate quickest paths with the same time complexity of o(pm + pn log n)
the complexity of kemeny elections. kemeny proposed a voting scheme which is distinguished by the fact that it is the unique voting scheme that is neutral, consistent, and condorcet. bartholdi, tovey, and trick showed that determining the winner in kemeny's system is np-hard. we provide a stronger lower bound and an upper bound matching the lower bound, namely, we show that determining the winner in kemeny's system is complete for p||np, the class of sets solvable via parallel access to np.
unavoidable sets. we obtain new results on minimum lengths of words in an unavoidable set of words of cardinality n before introducing the notion of aperiodic unavoidable sets, a natural extension of unavoidable sets.
lower bounds and the hardness of counting properties. rice's theorem states that all nontrivial language properties of recursively enumerable sets are undecidable. borchert and stephan (math. logic quart. 46 (4) (2000) 489-504) started the search for complexity-theoretic analogs of rice's theorem, and proved that every nontrivial counting property of boolean circuits is up-hard. hemaspaandra and rothe (theoret. comput. sci. 244 (1-2) (2000) 205-217) improved the up-hardness lower bound to upo(1)-hardness. the present paper raises the lower bound for nontrivial counting properties from upo(1)-hardness to fewp-hardness, i.e., from constant-ambiguity nondeterminism to polynomial-ambiguity nondeterminism. furthermore, we prove that no relativizable technique can raise this lower bound to fewp-≤1-ttp -hardness. we also prove a rice-style theorem for np, namely that every nontrivial language property of np sets is np-hard, and for a broad class of leaf-language classes we prove a sufficient condition for the natural analog of rice's theorem to hold.
a comparison of statecharts step semantics. the paper studies some variants of statecharts step semantics in the framework of structural operational semantics. the chosen framework allows to study precongruence and congruence properties of behavioral preorders and equivalences and to compare, with respect to these properties, the different step semantics considered.
optimal advice. ko [1983] proved that the p-selective sets are in the advice class p/quadratic. we prove that the p-selective sets are in np/linear \cap conp/linear. we show this to be optimal in terms of the amount of advice needed.
prediction-hardness of acyclic conjunctive queries. a conjunctive query problem is a problem to determine whether or not a tuple belongs to the answer of a conjunctive query over a database. in this paper, a tuple, a conjunctive query and a database in relational database theory are regarded as a ground atom, a nonrecursive function-free definite clause and a finite set of ground atoms, respectively, in inductive logic programming terminology. an acyclic conjunctive query problem is a conjunctive query problem with acyclicity. concerned with the acyclic conjunctive query problem, in this paper, we present the hardness results of predicting acyclic conjunctive queries from an instance with a j-database of which predicate symbol is at most j-ary. also we deal with two kinds of instances, a simple instance as a set of ground atoms and an extended instance as a set of pairs of a ground atom and a description. we mainly show that, from both a simple and an extended instances, acyclic conjunctive queries are not polynomial-time predictable with j-databases (j ≥ 3) under the cryptographic assumptions, and predicting acyclic conjunctive queries with 2-databases is as hard as predicting dnf formulas. hence, the acyclic conjunctive queries become a natural example that the equivalence between subsumption-efficiency and efficient pac-learnability from both a simple and an extended instances collapses.
effective metric spaces and representations of the reals. based on standard notions of classical recursion theory, a natural model of approximate computability for partial functions between effective metric spaces is presented. it generalizes the ko-friedman approach to computability of real functions by means of oracle turing machines, follows the main ideas of weihrauch's type 2 theory of effectivity, but it avoids the explicit use of representations. the topological arithmetical hierarchy is introduced and shown to be strict if the underlying space contains an effectively discrete sequence. the domains of computable functions are exactly the π2-sets of this hierarchy if the space admits a finitary stratification. finally, this framework is used to investigate and characterize the standard representations of the real numbers. they are just those functions from the name space onto the reals which have both computable extensions and inversions that are computable as relations.
a comparison of identification criteria for inductive inference of recursive real-valued functions. in this paper we investigate the inductive inference of recursive real-valued functions from data. a recursive real-valued function is regarded as a computable interval mapping. the learning model we consider in this paper is an extension of gold's inductive inference. we first introduce some criteria for successful inductive inference of recursive real-valued functions. then we show a recursively enumerable class of recursive real-valued functions which is not inferable in the limit. this should be an interesting contrast to the result by wiehagen (1976, elektronische informationsverarbeitung und kybernetik, vol. 12, pp. 93--99) that every recursively enumerable subset of recursive functions from n to n is consistently inferable in the limit. we also show that every recursively enumerable class of recursive real-valued functions on a fixed rational interval is consistently inferable in the limit. furthermore, we show that our consistent inductive inference coincides with the ordinary inductive inference, when we deal with recursive real-valued functions on a fixed closed rational interval. copyright 2001 elsevier science b.v. all rights reserved.
towards a behavioural theory of access and mobility control in distributed systems. we define a typed bisimulation equivalence for the language dpi, a distributed version of the π-calculus in which processes may migrate between dynamically created locations. it takes into account resource access policies, which can be implemented in dpi using a novel form of dynamic capability types. the equivalence, based on typed actions between configurations, is justified by showing that it is fully abstract with respect to a natural distributed version of a contextual equivalence.in the second part of the paper we study the effect of controlling the migration of processes. this affects the ability to perform observations at specific locations, as the observer may be denied access. we show how the typed actions can be modified to take this into account, and generalise the full-abstraction result to this more delicate scenario.
a polynomial algorithm for deciding bisimilarity of normed context-free processes. the previous best upper bound on the complexity of deciding bisimilarity between normed context-free processes, due to huynh and tian, is that the problem lies in the second level of the polynomial hierarchy: their algorithm guesses a proof of equivalence and validates this proof in polynomial time using oracles freely answering questions which are in np. in this paper we improve on this result by presenting a polynomial-time algorithm which solves this problem. as a corollary, we have a polynomial algorithm for the equivalence problem for simple context-free grammars.
computing with quanta - impacts of quantum theory on computation. this is a survey article to quantum computing. we begin with a brief introduction on the theory of computing and represent the hilbert space formalism of quantum physics. we study some devices for quantum computing, and finally mention some important achievements and restrictions of quantum computing.
max3sat is exponentially hard to approximate if np has positive dimension. under the hypothesis that np has positive p-dimension, we prove that any approximation algorithm a for max3sat must satisfy at least one of the following: 1. for some δ > 0, a uses at least 2nδ time. 2. for all ε > 0, a has performance ratio less than 7/8 + ε on an exponentially dense set of satisfiable instances. as a corollary, this solves one of lutz and mayordomo's "twelve problems on resource-bounded measure" (bull. european assoc. theoret. comput. sci. 68 (1999) 64-80).
the size of spp. derandomization techniques are used to show that at least one of the following holds regarding the size of the counting complexity class spp: 1. µp(spp)=0. 2. ph ⊆ spp. in other words, spp is small by being a negligible subset of exponential time or large by containing the entire polynomial-time hierarchy. this addresses an open problem about the complexity of the graph isomorphism problem: it is not weakly complete for exponential time unless ph is contained in spp. it is also shown that the polynomial-time hierarchy is contained in sppnp if np does not have p-measure 0.
hausdorff dimension and oracle constructions. bennett and gill [relative to a random oracle a, pa ≠ npa ≠ co-npa with probability 1, siam j. comput. 10 (1981) 96-113] proved that pa ≠ npa relative to a random oracle a, or in other words, that the set o[p=np] = {a | pa = npa} has lebesgue measure 0. in contrast, we show that o[p=np] has hausdorff dimension 1.this follows from a much more general theorem: if there is a relativizable and paddable oracle construction for a complexity-theoretic statement φ, then the set of oracles relative to which φ holds has hausdorff dimension 1.we give several other applications including proofs that the polynomial-time hierarchy is infinite relative to a hausdorff dimension 1 set of oracles and that pa ≠ npa ∩ conpa relative to a hausdorff dimension 1 set of oracles.
distribution of a class of divide and conquer recurrences arising from the computation of the walsh-hadamard transform. this paper explores the performance of a family of algorithms for computing the walsh-hadamard transform, a useful computation in signal and image processing. recent empirical work has shown that the family of algorithms exhibit a wide range of performance and that it is non-trivial to determine which algorithm is optimal on a given computer. this paper provides a theoretical basis for the performance distribution. performance is modeled by a family of recurrence relations that determine the number of instructions required to execute a given algorithm, and the recurrence relations can be used to explore the performance of the space of algorithms. the recurrence relations are related to standard divide and conquer recurrences, however, there are a variable number of recursive parts which can grow to infinity as the input size increases. thus standard approaches to solving such recurrences cannot be used and new techniques must be developed. in this paper, the minimum, maximum, expected values, and variances are calculated and the limiting distribution is obtained.
generalized metrics and uniquely determined logic programs. the introduction of negation into logic programming brings the benefit of enhanced syntax and expressibility, but creates some semantical problems. specifically, certain operators which are monotonic in the absence of negation become non-monotonic when it is introduced, with the result that standard approaches to denotational semantics then become inapplicable. in this paper, we show how generalized metric spaces can be used to obtain fixed-point semantics for several classes of programs relative to the supported model semantics, and investigate relationships between the underlying spaces we employ. our methods allow the analysis of classes of programs which include the acyclic, locally hierarchical, and acceptable programs, amongst others, and draw on fixed-point theorems which apply to generalized ultrametric spaces and to partial metric spaces.
the algebra of binary search trees. we introduce a monoid structure on the set of binary search trees, by a process very similar to the construction of the plactic monoid, the robinson-schensted insertion being replaced by the binary search tree insertion. this leads to a new construction of the algebra of planar binary trees of loday-ronco, defining it in the same way as non-commutative symmetric functions and free symmetric functions. we briefly explain how the main known properties of the loday-ronco algebra can be described and proved with this combinatorial point of view, and then discuss it from a representation theoretical point of view, which in turns leads to new combinatorial properties of binary trees.
trees, grids, and mso decidability: from graphs to matroids. monadic second order (mso) logic has proved to be a useful tool in many areas of application, reaching flom decidability and complexity to picture processing, correctness of programs and parallel processes. to characterize the structural borderline between decidability and undecidability is a classical research problem here. this problem is related to questions in computational complexity, especially to the model checking problem, for which many tools developed in the area of decidability have proved to be useful for more than two decades it was conjectured in [d. seese, the structure of the models of decidable monadic theories of graphs, ann. pure appl. logic 53 (1991) 169-195] that decidability of monadic theories of countable structures implies that the theory can be reduced via interpretability to a theory of trees.it is one of the main goals of this article to prove a variant of this conjecture for matroids representable over a finite field. (matroids can be viewed as a wide generalization of graphs, and they seem to capture some second order properties in a more suitable way than graphs themselves, cf. the recent development in matroid structure theory [j.f. geelen, a.h.m. gerards, g.p. whittle, branch-width and well-quasi-ordering in matroids and graphs, j. combin. theory ser. b 84 (2002) 270-290; j.f. geelen, a.h.m. gerards, n. robertson, g.p. whittle, excluding a planar graph from a gf(q)-representable matroid, manuscript, 2003].) more exactly we prove, for every finite field f, that any class of f-representable matroids with a decidable mso theory must have uniformly bounded branch-width. moreover, we show that bounding the branch-width of all matroids in general is not sufficient to obtain a decidable mso theory.our paper gives a (rather detailed) introduction to these different subjects, and shows that a blend of ideas and methods from logic together with structural matroid theory can lead to new tools and algorithms, and can shed light on some old open problems.
deterministic parallel backtrack search. the backtrack search problem involves visiting all the nodes of an arbitrary binary tree given a pointer to its root subject to the constraint that the children of a node are revealed only after their parent is visited. we present a fast, deterministic backtrack search algorithm for a p-processor common crcw-pram, which visits any n-node tree of height h in time o((n/p+h)(logloglogp)22). this upper bound compares favourably with a natural &ohgr;(n/p+h) lower bound for this problem. our approach embodies novel, efficient techniques for dynamically assigning tree-nodes to processors to ensure that the work is shared equitably among them.
a classification of wait-free loop agreement tasks. loop agreement is a family of wait-free tasks that includes instances of set agreement and approximate agreement tasks. a task g implements task f if one can construct a solution to f from a solution to g, possibly followed by access to a read/write memory. loop agreement tasks form a lattice under this notion of implementation.this paper presents a classification of loop agreement tasks. each loop agreement task can be assigned an algebraic signature consisting of a finitely presented group g and a distinguished element g in g. this signature characterizes the task's power to implement other tasks. if f and g are loop agreement tasks with respective signatures 〈f,f〉 and 〈g,g〉, then f implements g if and only if there exists a group homomorphism h : f → g carrying f to g.
the complexity of the characteristic and the minimal polynomial. we investigate the complexity of (1) computing the characteristic polynomial, the minimal polynomial, and all the invariant factors of an integer matrix, and of (2) verifying them, when the coefficients are given as input.it is known that each coefficient of the characteristic polynomial of a matrix a is computable in gapl, and the constant term, the determinant of a, is complete for gapl. we show that the verification of the characteristic polynomial is complete for complexity class c=l (exact counting logspace).we show that each coefficient of the minimal polynomial of a matrix a can be computed in ac0(gapl), the ac0-closure of gapl, and there is a coefficient which is hard for gapl. furthermore, the verification of the minimal polynomial is in ac0(c=l) and is hard for c=l. the hardness result extends to (computing and verifying) the system of all invariant factors of a matrix.
process algebra for performance evaluation. this paper surveys the theoretical developments in the field of stochastic process algebras, process algebras where action occurrences may be subject to a delay that is determined by a random variable. a huge class of resource-sharing systems - like large-scale computers, client-server architectures, networks - can accurately be described using such stochastic specification formalisms. the main emphasis of this paper is the treatment of operational semantics, notions of equivalence, and (sound and complete) axiomatisations of these equivalences for different types of markovian process algebras, where delays are governed by exponential distributions. starting from a simple actionless algebra for describing time-homogeneous continuous-time markov chains, we consider the integration of actions and random delays both as a single entity (like in known markovian process algebras like tipp, pepa and empa) and as separate entities (like in the timed process algebras timed csp and tccs). in total we consider four related calculi and investigate their relationship to existing markovian process algebras. we also briefly indicate how one can profit from the separation of time and actions when incorporating more general, non-markovian distributions.
paracategories i: internal paracategories and saturated partial algebras. based on the monoid classifier δ, we give an alternative axiomatization of freyd's paracategories, which can be interpreted in any bicategory of partial maps. assuming furthermore a free-monoid monad t in our ambient category, and coequalisers satisfying some exactness conditions, we give an abstract envelope construction, putting paramonoids (and paracategories) in the more general context of partial algebras. we introduce for the latter the crucial notion of saturation, which characterises those partial algebras which are isomorphic to the ones obtained from their enveloping algebras. we also set up a factorisation system for partial algebras, via epimorphisms and (monic) kleene morphisms and relate the latter to saturation.
paracategories ii: adjunctions, fibrations and examples from probabilistic automata theory. in this sequel to hermida and mateus (paracategories i: internal paracategories and saturated partial algebras, theoret. comput. sci., in press), we explore some of the global aspects of the category of paracategories. we establish its (co)completeness and cartesian closure. from the closed structure we derive the relevant notion of transformation for paracategories. we set up the relevant notion of adjunction between paracategories and apply it to define (co)completeness and cartesian closure, exemplified by the paracategory of bivariant functors and dinatural transformations. we introduce partial multicategories to account for partial tensor products. we also consider fibrations for paracategories and their indexed-paracategory version. finally, we instantiate all these concepts in the context of probabilistic automata.
a complexity analysis of functional interpretations. we give a quantitative analysis of gödel's functional interpretation and its monotone variant. the two have been used for the extraction of programs and numerical bounds as well as for conservation results. they apply both to (semi-)intuitionistic as well as (combined with negative translation) classical proofs. the proofs may be formalized in systems ranging from weak base systems to arithmetic and analysis (and numerous fragments of these). we give upper bounds in basic proof data on the depth, size, maximal type degree and maximal type arity of the extracted terms as well as on the depth of the verifying proof. in all cases terms of size linear in the size of the proof at input can be extracted and the corresponding extraction algorithms have cubic worst-time complexity. the verifying proofs have depth linear in the depth of the proof at input and the maximal size of a formula of this proof.
computations with effective real numbers. a real number x is said to be effective if there exists an algorithm which, given a required tolerance ε ∈ z2z, returns a binary approximation x˜ ∈, z2z for x with |x˜-x| < ε. effective real numbers are interesting in areas of numerical analysis where numerical instability is a major problem.one key problem with effective real numbers is to perform intermediate computations at the smallest precision which is sufficient to guarantee an exact end-result. in this paper we first review two classical techniques to achieve this: a priori error estimates and interval analysis. we next present two new techniques: "relaxed evaluations" reduce the amount of re-evaluations at larger precisions and "balanced error estimates" automatically provide good tolerances for intermediate computations.
a universal cellular automaton in the hyperbolic plane. the paper gives the construction of a universal ca with 22 states in the regular rectangular pentagonal grid of the hyperbolic plane. the ca implements a railway circuit which simulates a register machine and which improves a bit already known railway simulations of a turing machine.
deleting string rewriting systems preserve regularity. a string rewriting system is called deleting if there exists a partial ordering on its alphabet such that each letter in the right-hand side of a rule is less than some letter in the corresponding left-hand side. we show that the rewrite relation induced by a deleting system can be represented as the composition of a finite substitution (into an extended alphabet), a rewrite relation of an inverse context-free system (over the extended alphabet), and a restriction (to the original alphabet). here, a system is called inverse context-free if the length of the right-hand side of any rule does not exceed one. the decomposition result directly implies that deleting systems preserve regularity and that inverse deleting systems preserve context-freeness. the latter result was already obtained by hibbard (j. acm 21(3) (1974) 446-453).
a computational interpretation of dolev-yao adversaries. the dolev-yao model is a simple and useful framework in which to analyze security protocols, but it assumes that the adversary is extremely limited. we show that it is possible for the results of this model to remain valid even if the adversary is given additional power. in particular, we show that there exist situations in which dolev-yao adversary can be viewed as a valid abstraction of all realistic adversaries. we do this in a number of steps: (1) the dolev-yao model places strong assumptions on the adversary. we capture those assumptions in the computational model (an alternate framework with a very powerful adversary) as a nonmalleability property of public-key encryption. (2) we prove an abadi-rogaway-style indistinguishability property (j. cryptol. 15(2) (2002) 103-127) for the public-key setting. that is, we show that if two dolev-yao expressions are indistinguishable to the dolev-yao adversary, then their computational interpretations (via a chosen-ciphertext secure encryption scheme) are computationally indistinguishable. (3) we show that any encryption scheme that satisfies the indistinguishability property also satisfies our (more natural) non-malleability property.
realizability models for bll-like languages. we give a realizability model of girard-scedrov-scott's bounded linear logic (bll). this gives a new proof that all numerical functions representable in that system are polytime. our analysis naturally justifies the design of the bll syntax and suggests further extensions.
graph traversal and graph transformation. graph traversal algorithms are important since graphs are a common data structure in which information is distributed. none of the existing algorithmic paradigms focuses on graph traversal. this article introduces ennce substitution as an extension to ence substitution. the relationship between ennce substitution and ence substitution is explored. moreover, an ennce graph transformation system is defined and then used to generate depth-first and breadth-first graph traversal. thus, ennce graph transformation shows potential as a fundamental concept for a traversal-oriented algorithmic paradigm.
on deterministic finite automata and syntactic monoid size. we investigate the relationship between regular languages and syntactic monoid size. in particular, we consider the transformation monoids of n-state (minimal) deterministic finite automata. we show tight upper and lower bounds on the syntactic monoid size depending on the number of generators (input alphabet size) used. it turns out, that the two generator case is the most involved one. there we show a lower bound of nn (1 - 2/√n) for the size of the syntactic monoid of a language accepted by an n-state deterministic finite automaton with binary input alphabet. moreover, we prove that for every prime n ≥ 7, the maximal size semigroup w.r.t. its size among all (transformation) semigroups which can be generated with two generators, is generated by a permutation with two cycles (of appropriate lengths) and a non-bijective mapping merging elements from these two cycles. as a by-product of our investigations we determine the maximal size among all semigroups generated by two transformations, where one is a permutation with a single cycle and the other is a non-bijective mapping.
on the descriptional complexity of finite automata with modified acceptance conditions. we consider deterministic and nondeterministic finite automata with acceptance conditions that rely on the whole history of a computation on a given word and not only on the last state of the computation under consideration. formally, these conditions can be seen as the natural analogies of the büchi and muller acceptance for finite automata on infinite words. we study the computational power of these new acceptance mechanisms and prove some results on the descriptional complexity of conversions between automata with these new acceptance criteria and finite automata with ordinary acceptance.
alternating and empty alternating auxiliary stack automata. we consider variants of alternating auxiliary stack automata and characterize their computational power when the number of alternations is bounded by a constant or unlimited. in this way we get new characterizations of np, the polynomial hierarchy, pspace, and bounded query classes like co-dp=nl〈np[1]〈 and θ2p=pnp[o(logn)], in a uniform framework.
assembling molecules in atomix is hard. it is shown that assembling molecules in the atomix game can be used to simulate finite automata. in particular, an instance of atomix is constructed that has a solution if and only if the non-emptiness intersection problem for finite automata is solvable. this shows that the game under consideration is pspace-complete, improving a recent result of hüffner et al. (lecture notes in computer science, vol. 2174, springer, vienna, austria, 2001, pp. 229-243). moreover, the given reduction shows that there are atomix games which have exponentially long optimal solutions. we also give an easy construction of atomix game levels whose optimal solutions meet the worst case.
lower bounds for restricted read-once parity branching programs. we prove the first lower bounds for restricted read-once parity branching programs with unlimited parity nondeterminism where for each input the variables may be tested according to several orderings. namely, sums of k graph-driven ⊕ bp1s with polynomial size graph-orderings are under consideration. we prove lower bounds for the characteristic function of linear codes. we generalize a lower bound by savický and sieling (see [p. savický, d. sieling, a hierarchy result for read-once branching programs with restricted parity nondeterminism, theoret. comput. sci. 340 (2005) 594-605]) and recent results on graph-driven parity branching programs.
on d0l power series. we study d0l power series. we show how elementary morphisms introduced by ehrenfeucht and rozenberg can be used in connection with power series, characterize the sequences of rational numbers and integers which can be appear as coefficients in d0l power series and establish various decidability results.
a short solution for the hdt0l sequence equivalence problem. we give a solution for the hdt0l sequence equivalence problem which uses hilbert''s basis theorem but avoids the use of makanin''s algorithm or hall''s results about metabelian groups.
on parikh slender context-free languages. in a recent paper we defined and studied parikh slender languages and showed that they can be used in simplifying ambiguity proofs of context-free languages. in this paper parikh slender context-free languages are characterized. the characterization has diverse applications.
on images of d0l and dt0l power series. the d0l and dt0l power series are generalizations of d0l and dt0l languages. we continue the study of these series by investigating various decidability questions concerning the images of d0l and dt0l power series.
decidability results for watson-crick d0l systems with nonregular triggers. we show that sequence equivalence, language equivalence, growth equivalence and road equivalence are decidable for standard watson-crick d0l systems having bounded balance.
the language equivalence problem for hd0l systems having d0l growths. we show that language equivalence is decidable for hd0l systems having d0l growths. by definition, an hd0l system h has d0l growth if the length sequence of h is a d0l length sequence.
watson-crick d0l systems with regular triggers. watson-crick complementarity has been used as a basis for massive paral- lelism in dna computing. also its use in an operational sense has turned out to be very promising in the study of watson-crick d0l systems. the latter generalize d0l systems in a way not investigated so far in the the- ory of lindenmayer systems. the complexity of the "trigger" is crucial for decidability properties concerning watson-crick d0l systems. the purpose of this paper is to settle the basic decision problems in the case of regular triggers.
semantic models of a timed distributed dataspace architecture. we investigate various formal aspects of a distributed dataspace architecture in which data storage is based on time stamps. an operational and a denotational semantics have been defined and the equivalence of these two formulations has been proved. moreover, the denotational semantics is fully abstract with respect to the observation of produced data items. it is used as a basis for compositional reasoning about components, supported by the interactive theorem prover pvs. we use this framework for a small example where components make mutual assumptions about each other's output.
simple permutations mix well. we study the random composition of a small family of o(n3) simple permutations on {0, 1}n. specifically, we ask what is the number of compositions needed to achieve a permutation that is close to k-wise independent. we improve on a result of gowers [an almost m-wise independent random permutation of the cube, combin. probab. comput. 5(2) (1996) 119-130] and show that up to a polylogarithmic factor, n3k3 compositions of random permutations from this family suffice. we further show that the result applies to the stronger notion of k-wise independence against adaptive adversaries. this question is essentially about the rapid mixing of the random walk on a certain graph, and we approach it using a new technique to construct canonical paths. we also show that if we are willing to use a much larger family of simple permutations then we can guarantee closeness to k-wise independence with fewer compositions and fewer random bits.
computing unsatisfiable k-sat instances with few occurrences per variable. (k, s)-sat is the propositional satisfiability problem restricted to instances where each clause has exactly k distinct literals and every variable occurs at most s times. it is known that there exists an exponential function f such that for s ≤ f(k) all (k, s)-sat instances are satisfiable, but (k, f (k) + 1)- sat is already np-complete (k ≥ 3). exact values of f are only known for k = 3 and 4, and it is open whether f is computable. we introduce a computable function f1 which bounds f from above and determine the values of f1 by means of a calculus of integer sequences. this new approach enables us to improve the best known upper bounds for f(k), generalizing the known constructions for unsatisfiable (k, s)-sat instances for small k.
on the reachability problem for 5-dimensional vector addition systems. the reachability set for vector addition systems of dimension less than or equal to five are shown to be effectively computable semilinear sets. thus reachability, equvalence and containment are decidable up to dimension 5. an example of a non-semilinear reachability set is given for dimension 6. keywords and phrases: vector addition system, petri net, semilinear set, algorithms, decidability.
storage-to-tree transducers with look-ahead. we generalize engelfriet's decomposition result stating that the class of transformations induced by top-down tree transducers with regular look-ahead is equal to the composition of the class of top-down tree transformations and the class of linear tree homomorphisms. replacing the input trees with an arbitrary storage type, the top-down tree transducers are turned into regular storage-to-tree transducers. we show that the class of transformations induced by regular storage-to-tree transducers with positive look-ahead is equal to the composition of the class of transformations induced by regular storage-to-tree transducers with the class of linear tree homomorphisms. we also show that the classes of transformations induced by both io and oi context-free storage-to-tree transducers are closed under positive look-ahead, and are closed under composition with linear tree homomorphisms.
rank two bipartite bound entangled states do not exist. we explore the relation between the rank of a bipartite density matrix and the existence of bound entanglement. we show a relation between the rank, marginal ranks, and distillability of a mixed state and use this to prove that any rank n bound entangled state must have support on no more than an n × n hilbert space. a direct consequence of this result is that there are no bipartite bound entangled states of rank two. we also show that a separability condition in terms of a quantum entropy inequality is associated with the above results. we explore the idea of how many pure states are needed in a mixture to cancel the distillable entanglement of a schmidt rank n pure state and provide a lower bound of n - 1. we also prove that a mixture of a non-zero amount of any pure entangled state with a pure product state is distillable.
boolean operations and inclusion test for attribute-element constraints. the history of schema languages for xml is (roughly) an increase of expressiveness. while early schema languages mainly focused on the element structure, clark first paid an equal attention to attributes by allowing both element and attribute constraints in a single constraint expression (we call his mechanism "attribute-element constraints"). in this paper, we investigate intersection and difference operations and inclusion test for attribute-element constraints, in view of their importance in static typechecking for xml processing programs. the contributions here are (1) proofs of closure under intersection and difference as well as decidability of inclusion test and (2) algorithm formulations incorporating a "divide-and-conquer" strategy for avoiding an exponential blowup for typical inputs.
periodicity and arithmetic-periodicity in hexadecimal games. we investigate 1-, 2- and some k-digit (k ≥ 3) hexadecimal games with the help of a new arithmetic-periodicity theorem. we also note that not all hexadecimal games are periodic or arithmetic-periodic.
on the power of randomized multicounter machines. one-way two-counter machines represent a universal model of computation. here we consider the polynomial-time classes of multicounter machines with a constant number of reversals and separate the computational power of nondeterminism, randomization and determinism. for instance, we show that polynomial-time one-way multicounter machines, with error probability tending to zero with growing input length, can recognize languages that cannot be accepted by polynomial-time nondeterministic two-way multicounter machines with a bounded number of reversals. a similar result holds for the comparison of determinism and one-sided-error randomization, and of determinism and las vegas randomization.
dependences related to strict binary relations. in this paper we study dependences on a free monoid x* and their relations to strict binary relations on x*. as a consequence we characterize strict binary relations by the notion of dependence. moreover, some results concerning the relationship between dependences and codes are also obtained. a visualization of this work is provided by the theory of graph.
embedding longest fault-free paths onto star graphs with more vertex faults. the n-dimensional star graph sn belongs to a class of bipartite graphs, and it is recognized as an attractive alternative to the hypercube. since s1, s2, and s3 have trivial structures, we focus our attention on sn with n ≥ 4 in this paper. let f(sn) be the set of vertex faults. previously, it was shown that when |f(sn)| ≤ n -5, sn with n ≥ 6 can embed a longest fault-free path of length at least n! -2|f(sn)| -1 (respectively, n! -2|f(sn)| -2) between two arbitrary vertices in different partite sets (respectively, the same partite set) [longest fault-free paths in star graphs with vertex faults, theoretical computer science 262 (2001) 215-227]. in this paper, we improve the above result by tolerating more faults (|f(sn)|≤ n -3) to embed a longest fault-free path between two arbitrary vertices in sn, n ≥ 4.
pc trees and circular-ones arrangements. a 0-1 matrix has the consecutive-ones property if its columns can be ordered so that the ones in every row are consecutive. it has the circular-ones property if its columns can be ordered so that, in every row, either the ones or the zeros are consecutive. pq trees are used for representing all consecutive-ones orderings of the columns of a matrix that have the consecutive-ones property. we give an analogous structure, called a pc tree, for representing all circular-ones orderings of the columns of a matrix that has the circular-ones property. no such representation has been given previously. in contrast to pq trees, pc trees are unrooted. we obtain a much simpler algorithm for computing pq trees that those that were previously available, by adding a zero column, x, to a matrix, computing the pc tree, and then picking the pc tree up by x to root it.
property-preserving subnet reductions for designing manufacturing systems with shared resources. this paper handles two problems in manufacturing system design: resource sharing and system abstraction. in a manufacturing system, resources such as robots, machines, etc. are shared by several processes. when the resources are switched from one process to another, they may need some modifications such as cleaning oil, adding equipments and so on. previous designing methods assume that the resources have no intermediate modifications. hence, they need to be extended to handle such kinds of resource-sharing problems. as for abstraction, modeling operations with single places in manufacturing system design is very popular. from the viewpoint of verification, the objective is to verify whether the reduced model has the same desirable properties as the original one. this paper presents three kinds of property-preserving subnet reduction methods. for each reduction method, conditions are presented for ensuring that the properties liveness, boundedness and reversibility are preserved. applications of these reduction methods to handling the above resource sharing and system abstraction problems are illustrated with an example from the manufacturing system.
approximation of walrasian equilibrium in single-minded auctions. we consider a social optimization model of pricing scheme in single-minded auctions, in cases where walrasian equilibrium does not exist. we are interested in the maximization of the ratio, r, of happy bidders over all agents, in a feasible allocation-pricing scheme. we show np-hardness of the optimization problem, establish lower and upper bounds of r, as well as develop greedy algorithms to approximate the optimal value of r.
simulations in coalgebra. a new approach to simulations is proposed within the theory of coalgebras by taking a notion of order on a functor as primitive. such an order forms a basic building block for a "lax relation lifting", or "relator" as used by other authors. simulations appear as coalgebras of this lifted functor, and similarity as greatest simulation. two-way similarity is then similarity in both directions. in general, it is different from bisimilarity (in the usual coalgebraic sense), but a sufficient condition is formulated (and illustrated) to ensure that bisimilarity and two-way similarity coincide. also, suitable conditions are identified which ensures that similarity on a final coalgebra forms an (algebraic) dcpo structure. this involves a close investigation of the iterated applications fn(0) and fn(1) of a functor f with an order to the initial algebras and final objects.
admissible digit sets. we examine a special case of admissible representations of the closed interval, namely those which arise via sequences of a finite number of möbius transformations. we regard certain sets of möbius transformations as a generalized notion of digits and introduce sufficient conditions that such a "digit set" yields an admissible representation of [0,+ ∞]. furthermore, we establish the productivity and correctness of the homographic algorithm for such "admissible" digit sets. we present the stern-brocot representation and a modification of same as a working example throughout.
counting lattice paths taking steps in infinitely many directions under special access restrictions. we count lattice paths that are confined to the first quadrant by the nature of their step vectors. if no further restrictions apply, a path can go from any point to infinitely many others, but each point on the path has only finitely many predecessors. by "further restrictions" we mean a boundary line above which the paths may have to stay. access privilege to the boundary line itself is granted from certain lattice points in the form of a special access step set, which itself may be infinite. we also count the number of paths that contact the weak boundary a given number of times. we approach explicit solutions of such enumeration problems via sheffer polynomials and functionals, using results of the umbral calculus.
linear-time algorithms for the hamiltonian problems on distance-hereditary graphs. a hamiltonian path of a graph g is a simple path that contains each vertex of g exactly once. a hamiltonian cycle of a graph is a simple cycle with the same property. the hamiltonian path (resp. cycle) problem involves testing whether a hamiltonian path (resp. cycle) exists in a graph. the 1hp (resp. 2hp) problem is to determine whether a graph has a hamiltonian path starting from a specified vertex (resp. starting from a specified vertex and ending at the other specified vertex). the hamiltonian problems include the hamiltonian path, hamiltonian cycle, 1hp, and 2hp problems. a graph is a distance-hereditary graph if each pair of vertices is equidistant in every connected induced subgraph containing them. in this paper, we present a unified approach to solving the hamiltonian problems on distance-hereditary graphs in linear time.
chebyshev polynomials over finite fields and reversibility of -automata on square grids. using number theory on function fields and algebraic number fields, we prove results about chebyshev polynomials over finite prime fields to investigate reversibility of two-dimensional additive cellular automata on finite square grids. for example, we show that there are infinitely many primitive irreversible additive cellular automata on square grids when the base field has order two or three.
probabilistic guarded commands mechanized in . the probabilistic guarded-command language (pgcl) contains both demonic and probabilistic non-determinism, which makes it suitable for reasoning about distributed random algorithms. proofs are based on weakest precondition semantics, using an underlying logic of real- (rather than boolean-)valued functions.we present a mechanization of the quantitative logic for pgcl using the hol theorem prover, including a proof that all pgcl commands, satisfy the new condition sublinearity, the quantitative generalization of conjunctivity for standard gcl.the mechanized theory also supports the creation of an automatic proof tool which takes as input an annotated pgcl program and its partial correctness specification, and derives from that a sufficient set of verification conditions. this is employed to verify the partial correctness of the probabilistic voting stage in rabin's mutual-exclusion algorithm.
utilization of nonclairvoyant online schedules. this paper addresses the analysis of nondelay, nonpreemptive, nonclairvoyant online schedules for independent jobs on m identical machines. in our online model, all jobs are submitted over time. we show that the commonly used makespan criterion is not well suited to describe utilization for this online problem. therefore, we directly address utilization and determine the maximum deviation from the optimal utilization for the given scheduling problem.
coding properties of dna languages. the computation language of a dna-based system consists of all the words (dna strands) that can appear in any computation step of the system. in this work we define properties of languages which ensure that the words of such languages will not form undesirable bonds when used in dna computations. we give several characterizations of the desired properties and provide methods for obtaining languages with such properties. the decidability of these properties is addressed as well. as an application we consider splicing systems whose computation language is free of certain undesirable bonds and is generated by nearly optimal comma-free codes.
on finite-state approximants for probabilistic computation tree logic. we generalize the familiar semantics for probabilistic computation tree logic from finite-state to infinite-state labelled markov chains such that formulas are interpreted as measurable sets. then we show how to synthesize finite-state abstractions which are sound for full probabilistic computation tree logic and in which measures are approximated by monotone set functions. this synthesis of sound finite-state approximants also applies to finite-state systems and is a probabilistic analogue of predicate abstraction. sufficient and always realizable conditions are identified for obtaining optimal such abstractions for probabilistic propositional modal logic.
approximate string matching using compressed suffix arrays. let t be a text of length n and p be a pattern of length m, both strings over a fixed finite alphabet a. the k-difference (k-mismatch, respectively) problem is to find all occurrences of p in t that have edit distance (hamming distance, respectively) at most k from p. in this paper we investigate a well-studied case in which t is fixed and preprocessed into an indexing data structure so that any pattern query can be answered faster. we give a solution using an o(n log n) bits indexing data structure with o(|a|kmkċmax(k, log n) +occ) query time, where occ is the number of occurrences. the best previous result requires o(n log n) bits indexing data structure and gives o(|a|kmk+2 + occ) query time. our solution also allows us to exploit compressed suffix arrays to reduce the indexing space to o(n) bits, while increasing the query time by an o(log n) factor only.
uniform asymptotics of some abel sums arising in coding theory. we derive uniform asymptotic expressions of some abel sums appearing in some problems in coding theory and indicate the usefulness of these sums in other fields, like empirical processes, machine maintenance, analysis of algorithms, probabilistic number theory, queuing models, etc.
a complementary survey on double-loop networks. we give a survey on double-loop networks with emphasis on new development since the surveys in 1986, 1991 and 1995.
a survey on multi-loop networks. bermond, comellas and hsu gave an excellent survey on multi-loop networks, directed and undirected, in 1995, but only one and half page is on loop networks other than the directed double-loop. hwang recently gave a substantial survey, but only on the directed double-loop. this survey is a companion of the latter survey by focusing on the other loop networks.
an asymptotic theory for recurrence relations based on minimization and maximization. we derive asymptotic approximations for the sequence f(n) defined recursively by f(n) = min1≤j<n {f(j) + f(n - j)} + g(n), when the asymptotic behavior of g(n) is known. our tools are general enough and applicable to another sequence f(n) = max1 ≤j<n{f(j) + f(n - j) + min{g(j),g(n-j)}}, also frequently encountered in divide-and-conquer problems. applications of our results to algorithms, group testing, dichotomous search, etc. are discussed.
some permutation routing algorithms for low-dimensional hypercubes. oblivious permutation routing in binary d-cubes has been well studied in the literature. in a permutation routing, each node initially contains a packet with a destination such that all the 2d destinations are distinct. kaklamanis et al. (math. syst. theory 24 (1991) 223-232) used the decomposability of hypercubes into hamiltonian circuits to give an asymptotically optimal routing algorithm. the notion of "destination graph" was first introduced by borodin and hopcroft to derive lower bounds on routing algorithms. this idea was recently used by grammatikakis et al. (proceedings of the advancement in parallel computing, elsevier, amsterdam, 1993) to construct many-one routing algorithms for the binary 2-cube and 3-cube. in the present paper, further theoretical development is made along this line. it is then applied to obtain algorithms for binary d-cubes with d up to 12, which compare favorably with the above-mentioned "hamiltonian circuit" algorithm. some results on t-nary cubes with t&ge;3 are also obtained.
discrete lawvere theories and computational effects. countable lawvere theories model computational effects such as exceptions, side-effects, interactive input/output, nondeterminism and probabilistic nondeterminism. the category of countable lawvere theories has sums, tensors, and distributive tensors, modelling natural combinations of such effects. it is also closed under taking images. enrichment in a category such as ωcpo allows one to extend this modelling of computational effects to account for partiality and recursion. sum and tensor extend to enriched countable lawvere theories, but distributive tensor and image do not. so here we introduce discrete countable enriched lawvere theories in order to allow natural definitions and accounts of distributive tensor and image. a discrete countable enriched lawvere theory is, in a sense we make precise, an enriched lawvere theory with discrete arities. we show that they include all our leading examples of computational effects and are closed under sum and tensor. and we develop notions of enriched operad and enriched multicategory to support the definition.
combining effects: sum and tensor. we seek a unified account of modularity for computational effects. we begin by reformulating moggi's monadic paradigm for modelling computational effects using the notion of enriched lawvere theory, together with its relationship with strong monads; this emphasises the importance of the operations that produce the effects. effects qua theories are then combined by appropriate bifunctors on the category of theories. we give a theory for the sum of computational effects, which in particular yields moggi's exceptions monad transformer and an interactive input/output monad transformer. we further give a theory of the commutative combination of effects, their tensor, which yields moggi's side-effects monad transformer. finally, we give a theory of operation transformers, for redefining operations when adding new effects; we derive explicit forms for the operation transformers associated to the above monad transformers.
glueing and orthogonality for models of linear logic. we present the general theory of the method of glueing and associated technique of orthogonality for constructing categorical models of all the structure of linear logic: in particular we treat the exponentials in detail. we indicate simple applications of the methods and show that they cover familiar examples.
on the computational complexity of membrane systems. we show how techniques in machine-based complexity can be used to analyze the complexity of membrane computing systems. we focus on catalytic syslems, communicating p systems, and systems with only symport/antiport rules, but our techniques are applicable to other p systems that are universal. we define space and time complexity measures and show hierarchies of complexity classes similar to well-known results concerning turing machines and counter machines. we also show that the deterministic communicating p system simulating a deterministic counter machine in (sosik (2002)) (pre-proc. of workshop on membrane computing (wmc-cdea2002), curtea de arges, romania, 2002, pp. 371-382), (sosik and matysek (2002)) (unconventional models of computation 2002, lecture notes in computer science, vol. 2509, springer, berlin, 2002, pp. 264-275.) can be constructed to have a fixed number of membranes, answering positively an open question in sosik (2002), sosik and matysek (2002). we prove that reachability of extended configurations for symport/antiport systems (as well as for catalytic systems and communicating p systems) can be decided in nondeterministic log n space and, hence, in deterministic log2 n space or in polynomial time, improving the main result in paun et al. (2002) (on the reachability problem for p systems with symport/antiport, 2002, submitted for publication.), we propose two equivalent systems that define languages (instead of multisets of objects): the first is a catalytic system language generator and the other is a communicating p system acceptor (or a symport/antiport system acceptor). these devices are universal and therefore can also be analyzed with respect to space and time complexity. finally, we give a characterization of semilinear languages in terms of a restricted form of catalytic system language generator.
on membrane hierarchy in p systems. we look at a restricted model of a communicating p system, called rcps, whose environment does not contain any object initially. the system can expel objects into the environment but only expelled objects can be retrieved from the environment. such a system is initially given an input a1i1 ... anin (with each ij representing the multiplicity of distinguished object ai, 1≤i≤n) and is used as an acceptor. we show that rcpss are equivalent to two-way multihead finite automata over bounded languages (i.e., subsets of a1* ... an*, for some distinct symbols a1 ..... an). we then show that there is an infinite hierarchy of rcps's in terms of the number of membranes: for every r, there is an s > r and a unary language l accepted by an rcps with s membranes that cannot be accepted by an rcps with r membranes. this provides an answer to an open problem in (membrane computing: an introduction, springer, berlin, 2002) which asks whether there is a nonuniversal model of a membrane computing system which induces an infinite hierarchy on the number of membranes. we also consider variants/generalizations of rcpss, e.g, acceptors of languages; models that allow a "polynomial bounded" supply of objects in the environment initially; models with tentacles, etc. we show that they also form an infinite hierarchy with respect to the number of membranes (or tentacles). the proof techniques can be used to obtain similar results for other restricted models of p systems, like symport/antiport systems.
on determinism versus nondeterminism in p systems. an important open problem in the area of membrane computing is whether there is a model of p systems for which the nondeterministic version is strictly more powerful than the deterministic version. we resolve this problem in the following sense--we exhibit two classes of p system acceptors with only communicating rules and show: 1. for the first class, the deterministic and nondeterministic versions are equivalent if and only if deterministic and nondeterministic linear bounded automata are equivalent. the latter problem is a long-standing open question in complexity theory. 2. for the second class, the deterministic version is strictly weaker than the nondeterministic version. both classes are nonuniversal, but can accept fairly complex languages.
eliminating the storage tape in reachability constructions. a discrete pushdown timed automaton is a pushdown machine with integer-valued clocks. it has been shown recently that the binary reachability of a discrete pushdown timed automaton can be accepted by a two-tape pushdown acceptor with reversal-bounded counters. we improve this result by showing that the stack can be eliminated from the acceptor, i.e., the binary reachability can be accepted by a two-tape finite-state acceptor with reversal-bounded counters. we calso obtain similar results for other machine models. our results can be used to verify certain properties concerning these machines that were not verifiable before using previous techniques. for example, we are able to formulate a subset of presburger ltl that is decidable for satisfiability checking with respect to these machines. we also discuss the "boundedness problem" for reachability sets. finally, we explain how the storage tape elimination technique can be applied to machines with real-valued clocks.
on two-way fa with monotonic counters and quadratic diophantine equations. we show an interesting connection between two-way deterministic finite automata with monotonic counters and quadratic diophantine equations. the automaton m operates on inputs of the form a1i1...anin for some fixed n and distinct symbols a1,...,an, where i1,...,in are nonnegative integers. we consider the following reachability problem: given a machine m, a state q, and a presburger relation e over counter values, is there (i1,...,in) such that m, when started in its initial state on the left end of the input a1i1...anin with all counters initially zero, reaches some configuration where the state is q and the counter values satisfy e? in particular, we look at the case when the relation e is an equality relation, i.e., a conjunction of relations of the form ci = cj. we show that this case and variations of it are equivalent to the solvability of some special classes of systems of quadratic diophantine equations. we also study the nondeterministic version of two-way finite automata augmented with monotonic counters with respect to the reachability problem. finally, we introduce a technique which uses decidability and undecidability results to show "separation" between language classes.
on the solvability of a class of diophantine equations and applications. for 1 ≤ i ≤ k, let ri denote pi(y)fi + gi, where pi(y) is a polynomial in y with integer coefficients, and fi, gi are linear polynomials in x1,..., xn with integer coefficients. let p(z1,..., zk) be a presburger relation over the nonnegative integers. we show that the following problem is decidable:given: r1,..., rk and a presburger relation p.question: are there nonnegative integer values for y, x1,..., xn such that for these values, (r1,..., rk) satisfies p? we also give some applications to decision problems concerning counter machines.
catalytic p systems, semilinear sets, and vector addition systems. we look at 1-region membrane computing systems which only use rules of the form ca → cv, where c is a catalyst, a is a noncatalyst, and v is a (possibly null) string of noncatalysts. there are no rules of the form a → v. thus, we can think of these systems as "purely" catalytic. we consider two types: (1) when the initial configuration contains only one catalyst, and (2) when the initial configuration contains multiple catalysts. we show that systems of the first type are equivalent to communication-free petri nets, which are also equivalent to commutative context-free grammars. they define precisely the semilinear sets. this partially answers an open question (in: wmc-cdea'02, lecture notes in computer science, vol. 2597, springer, berlin, 2003, pp. 400-409; computationally universal p systems without priorities: two catalysts are sufficient, available at http://psystems.disco.unimib.it, 2003). systems of the second type define exactly the recursively enumerable sets of tuples (i.e., turing machine computable). we also study an extended model where the rules are of the form q:(p, ca → cv) (where q and p are states), i.e., the application of the rules is guided by a finite-state control. for this generalized model, type (1) as well as type (2) with some restriction correspond to vector addition systems. finally, we briefly investigate the closure properties of catalytic systems.
verification in loosely synchronous queue-connected discrete timed automata. we look at a model of a queue system that consists of the following components: 1. two discrete timed automata w (the "writer") and r ("the reader"). 2. one unrestricted queue that can be used to send messages from w to r. there is no bound on the length of the queue. w and r do not share a global clock and operate in a loosely synchronous way. that is, the absolute value of the difference between the local time of w and the local time of r is always bounded by a positive constant. we show that the binary reachability for these systems is effectively computable, and this result is generalized to the case when there are two queues (one from w to r and the other from r to w) that operate in half-duplex. we then present some properties (e.g., safety, invariance, etc.) that can be verified for loosely synchronous queue-connected discrete timed automata and give an example of a system composed of a sensor and a controller that is verifiable using our results.
characterizations of context-sensitive languages and other language classes in terms of symport/antiport p systems. we give "syntactic" characterizations of context-sensitive languages (csls) in terms of some restricted models of symport/antiport p systems. these are the first such characterizations of csls in terms of p systems. in particular, we show the following for any language l over a binary alphabet: (1) let m be any integer ≥ 1. then l is a csl if and only if it can be accepted by a restricted symport/antiport p system with m membranes and multiple number of symbols (objects). moreover, holding the number of membranes at m, there is an infinite hierarchy in computational power (within the class of binary csls) with respect to the number of symbols. (2) let s be any integer ≥ 14. then l is a csl if and only if it can be accepted by a restricted symport/antiport p system with s symbols and multiple number of membranes. moreover, holding the number of symbols at s, there is an infinite hierarchy in computational power with respect to the number of membranes. (similar results hold for languages over an alphabet of k ≥ 2 symbols.) thus (1) and (2) say that in order for the restricted symport/antiport p systems to accept all binary csls, at least one parameter (either the number of symbols or the number of membranes) must grow. these are the first results of their kind in the p systems area. they contrast a known result that (unrestricted) symport/antiport p systems with s ≥ 2 symbols and m ≥ 1 membranes accept (or generate) exactly the recursively enumerable sets of numbers even for s + m = 6. we also note that previous characterizations of formal languages in the membrane computing literature are mostly for the parikh images of languages.variations of our model yield characterizations of regular languages, languages accepted by one-way log n space-bounded turing machines, and recursively enumerable languages.
on partially blind multihead finite automata. this work is concerned with 1-way multihead finite automata (fa), both deterministic and nondeterministic, in which the symbol under only one head controls its move. we call such a fa a partially blind multihead fa. we show some results regarding the decision problems and closure properties of blind multihead dfa and nfa. we also compare these devices with 1-way nfa augmented by reversal bounded counters. finally, we also present some results regarding the simulation of a partially blind dfa and nfa by a probabilistic finite automaton.
augmenting the discrete timed automaton with other data structures. we describe a general automata-theoretic approach for analyzing the verification problems of discrete timed automata (i.e., timed automata with integer-valued clocks) augmented with various data structures. formally, let c be a class of nondeterministic machines with reversal-bounded counters and possibly other data structures (e.g., a pushdown stack, a queue, a read-write work-tape, etc.). let a be a discrete timed automaton and m be a machine in b. denote by a ⊕ m the combined automaton, i.e., a augmented with m (in some precise sense to be defined). we show that if c has a decidable emptiness problem, then the (binary, forward, backward) reachability, safety, and invariance for a ⊕ m are solvable. we give examples of such c's and exhibit some new properties of discrete timed automata that can be verified. we also briefly consider reachability in discrete timed automata operating in parallel.
counter machines and verification problems. we study various generalizations of reversal-bounded multicounter machines and show that they have decidable emptiness, infiniteness, disjointness, containment, and equivalence problems. the extensions include allowing the machines to perform linear-relation tests among the counters and parameterized constants (e.g., "is 3x-5y-2d1 + 9d2 < 12?", where x, y are counters, and d1,d2 are parameterized constants). we believe that these machines are the most powerful machines known to date for which these decision problems are decidable. decidability results for such machines are useful in the analysis of reachability problems and the verification/debugging of safety properties in infinite-state transition systems. for example, we show that (binary, forward, and backward) reachability and safety are solvable for these machines.
deterministic catalytic systems are not universal. we look at a 1-membrane catalytic p system with evolution rules of the form ca → cv or a → v, where c is a catalyst, a is a noncatalyst symbol, and v is a (possibly null) string representing a multiset of noncatalyst symbols. (note that we are only interested in the multiplicities of the symbols.) a catalytic system (cs) can be regarded as a language acceptor in the following sense. given an input alphabet σ consisting of noncatalyst symbols, the system starts with an initial configuration wz, where w is a fixed string of catalysts and noncatalysts not containing any symbol in z, and z = a1n1...aknk for some nonnegative integers n1,..., nk, with (a1,...,ak) ⊆ σ. at each step, a maximal multiset of rules is nondeterministically selected and applied in parallel to the current configuration to derive the next configuration (note that the next configuration is not unique, in general). the string z is accepted if the system eventually halts.it is known that a 1-membrane cs is universal in the sense that any unary recursively enumerable language can be accepted by a 1-membrane cs (even by purely css, i.e., when all rules are of the form ca → cv). a cs is said to be deterministic if at each step there is a unique maximally parallel multiset of rules applicable. it has been an open problem whether deterministic systems of this kind are universal. we answer this question negatively. we show that the membership problem for deterministic css is decidable. in fact, we show that the parikh map of the language (⊆a1*...ak*) accepted by any deterministic cs is a simple semilinear set which can be effectively constructed. since nondeterministic 1-membrane cs acceptors (with two catalysts) are universal, our result gives the first example of a variant of p systems for which the nondeterministic version is universal, but the deterministic version is not.we also show that for a deterministic 1-membrane cs using only rules of type ca → cv, the set of reachable configurations from a given initial configuration is an effective semilinear set. the application of rules of type a → v, however, is sufficient to render the reachability set nonsemilinear. our results generalize to multimembrane deterministic css. we also consider deterministic css which allow rules to be prioritized and investigate three classes of such systems, depending on how priority in the application of the rules is interpreted. for these three prioritized systems, we obtain contrasting results: two are universal and one only accepts semilinear sets.
a generic type system for the pi-calculus. we propose a general, powerful framework of type systems for the π-calculus, and show that we can obtain as its instances a variety of type systems guaranteeing non-trivial properties like deadlock-freedom and race-freedom. a key idea is to express types and type environments as abstract processes: we can check various properties of a process by checking the corresponding properties of its type environment. the framework clarifies the essence of recent complex type systems, and it also enables sharing of a large amount of work such as a proof of type preservation, making it easy to develop new type systems.
on lengths of words in context-free languages. we consider slender languages, that is, languages for which the number of words of the same length is bounded from above by a constant. we prove that the slenderness problem is decidable for context-free languages and that the maximal number of words of the same length in a given context-free language is computable. some effective representations of slender context-free languages, as well as other related decidability problems are investigated.
on computational complexity of contextual languages. we consider the following restriction of internal contextual grammars, called local: in any derivation in a grammar, after applying a context, further contexts can be added only inside of or at most adjacent to the previous ones. we further consider a natural restriction of this derivation mode by requiring that no superword of the word considered as selector can be used as selector. we investigate the relevance of the latter type of grammars for natural language study. in this aim, we show that all the three basic non-context-free constructions in natural languages, that is, multiple agreements, crossed agreements, and duplication, can be realized using this type of grammars. our main result is that these languages are parsable in polynomial time. the problem of semilinearity remains open.
a generalization of repetition threshold. brandenburg and (implicitly) dejean introduced the concept of repetition threshold: the smallest real number α such that there exists an infinite word over a k-letter alphabet that avoids β-powers for all β > α. we generalize this concept to include the lengths of the avoided words. we give some conjectures supported by numerical evidence and prove some of these conjectures. as a consequence of one of our results, we show that the pattern abcbabc is 2-avoidable. this resolves a question left open in cassaigne's thesis.
on well quasi orders of free monoids. the paper investigates down-sets associated to well quasi orders. of particular language-theoretic interest is the quasi order $u\leq_s v$ (resp.$\!$ $u\leq_{\cp}v$) of $u$ being a subword (resp.$\!$ a parikh subword) of $v$, as well as their inverses. we establish a number of results about the regularity and effective regularity of the down-sets, in particular, a general condition for the effective regularity of the down-set associated to an inverse well quasi order (theorem 7.1). it is decidable whether or not an arbitrary regular language results as a down-set from an infinite or bi-infinite word, whereas the same problem is undecidable for context-free language. a quasi order being a well quasi order is connected to arbitrary languages being confluent.
reducing nfas by invariant equivalences. we give new general methods for constructing small non-deterministic finite automata (nfa) from arbitrary ones. given an nfa, we compute the largest right-invariant equivalence on the set of states and then merge the equivalent states to obtain a smaller automaton. when applying this method to position automata, we get a way to convert regular expressions into nfas which are always smaller than or equal to the position, partial derivative, and follow automata; it can be arbitrarily smaller. the construction can be dually made for left-invariant equivalences and then the two can be combined for even better results.
formal design and verification of operational transformation algorithms for copies convergence. distributed groupware systems provide computer support for manipulating objects such as a text document or a filesystem, shared by two or more geographically separated users. data replication is a technology to improve performance and availability of data in distributed groupware systems. indeed, each user has a local copy of the shared objects, upon which he may perform updates. locally executed updates are then transmitted to the other users. this replication potentially leads, however, to divergent (i.e. different) copies. in this respect, operational transformation (ot) algorithms are applied for achieving convergence of all copies, i.e. all users view the same objects. using these algorithms users can exchange their updates in any order since the convergence should be ensured in all cases. however, the design of such algorithms is a difficult and error-prone activity since building the correct updates for maintaining good convergence properties of the local copies requires examining a large number of situations. in this paper, we present the modelling and deductive verification of ot algorithms with algebraic specifications. we show in particular that many ot algorithms in the literature do not satisfy convergence properties unlike what was stated by their authors.
voronoi diagrams on piecewise flat surfaces and an application to biological growth. this paper introduces the notion of voronoi diagrams and delaunay triangulations generated by the vertices of a piecewise flat, triangulated surface. based on properties of such structures, a generalized flip algorithm to construct the delaunay triangulation and voronoi diagram is presented. an application to biological membrane growth modeling is then given. a voronoi partition of the membrane into cells is maintained during the growth process, which is driven by the creation of new cells and by restitutive forces of the elastic membrane.
some properties of one-pebble turing machines with sublogarithmic space. this paper investigates some aspects of the accepting powers of deterministic, nondeterministic, and alternating one-pebble turing machines with spaces between log log n and log n. we first investigate a relationship between the accepting powers of two-way deterministic one-counter automata and deterministic (or nondeterministic) one-pebble turing machines, and show that they are incomparable. then we investigate a relationship between nondeterminism and alternation, and show that there exists a language accepted by a strongly log log n space-bounded alternating one-pebble turing machine, but not accepted by any weakly o(log n) space-bounded nondeterministic one-pebble turing machine. finally, we investigate a space hierarchy, and show that for any one-pebble (fully) space constructible function l(n) ≤ log n, and for any function l'(n) = o(l(n)), there exists a language accepted by a strongly l(n) space-bounded deterministic one-pebble turing machine, but not accepted by any weakly l'(n) space-bounded nondeterministic one-pebble turing machine.
testing against a non-controllable stream x-machine using state counting. stream x-machines are a form of extended finite state machines that has received extensive study in recent years. a stream x-machine describes a system as a finite set of states, an internal store, called memory, and a finite number of transitions between the states, labelled by function names (the processing functions). one of the great benefits of using a stream x-machine to specify a system is its associated testing method. under certain design for test conditions, this method produces a test suite that can determine the correctness of the implementation, provided that the processing functions of the stream x-machine specification have been correctly implemented (this can be checked by a separate testing process, using the same method or alternative functional methods). however, the application of the stream x-machine based testing method is often encumbered by the restrictive design for test conditions required. in practical applications, these conditions are achieved by designing extra functionality that will have to be disabled after testing has been completed. this is a time consuming process and can often be a source of error. this paper provides a strong generalisation of the existing method, which requires much laxer design for test conditions; these are naturally satisfied in practical applications and, furthermore, can be introduced into any stream x-machine specification without the need to add extra functionality. consequently, the generalised method can be applied to virtually any system that can be specified by a stream x-machine.
the passport control problem or how to keep a dynamic service system load balanced? in many real life situations (such as department stores, or passport control booths in airports) parallel queues are formed in front of control stations. typically, some of the stations are manned while others are not. classical queuing theory considers the configuration constant, and concentrates on the arrival process. this work explores a new line of research--the case in which the configuration is dynamic, and the customers can plan to cope with anticipated changes. specifically, as the queues build up, management assigns additional officers to the unmanned stations. when this happens--some people move to the newly manned queues from nearby busy queues. in anticipation, people may prefer to line up in busy queues next to unmanned ones.mathematically we discuss the problem of dynamic arrangement of the queues in a service system where at any time each server can be in either an active or an inactive mode. a balancing strategy determines how customers will be reallocated when a station becomes active. given a balancing strategy, we seek a partition of customers to queues that minimizes the maximum wait time of a customer in each of the active stations, thereby keeping the system balanced at all times. we study two balancing strategies that we call split and trim. for the split strategy we discuss a special case (the stations are ordered on a line and a single unmanned station is at one end). we show how an optimal partition can be calculated recursively. we then give partitions that approximate the minimal expected wait time within a factor of 1 + o(1/n), under each of these strategies, where n is the number of stations. we obtain similar bounds (to within factor 2) for the case, where the number of active servers can be any 1 ≤ n ≤ n - 1, and the balancing strategy is trim.
single backup table schemes for shortest-path routing. we introduce a new recovery scheme that needs only one extra backup routing table for networks employing shortest-path routing. by precomputing this backup table, the network recovers from any single link failure immediately after the failure occurs. to compute the backup routing table for this scheme, we use an almost linear time algorithm to solve the {r, v}-problem, which is a variation of the best swap problem presented by nardelli et al. we further show that the same solution can be computed in exactly linear time if the underlying graph is unweighted.
constructible functions in cellular automata and their applications to hierarchy results. we investigate time-constructible functions in one-dimensional cellular automata (ca). it is shown that (i) if a function t(n) is computable by an o(t(n)n)-time turing machine, then t(n) is time constructible by ca and (ii) if two functions are time constructible by ca, then the sum, product, and exponential functions of them are time constructible by ca. as an application, it is shown that if t1(n) and t2(n) are time constructible functions such that limnt1(n)/t2(n)=0 and t1(n)n, then there is a language which can be recognized by a ca in t2(n) time but not by any ca in t1(n) time.
non-cryptographic primitive for pseudorandom permutation. four round feistel permutation (like des) is super-pseudorandom if each round function is random or a secret universal hash function. a similar result is known for five round misty type permutation. it seems that each round function must be at least either random or secret in both cases.in this paper, however, we show that the second round permutation g in five round misty type permutation need not be cryptographic at all, i.e., no randonmess nor secrecy is required. g has only to satisfy that g(x)⊕x ≠ g(x')⊕x' for any x ≠ x'. this is the first example such that a non-cryptographic primitive is substituted to construct the minimum round super-pseudorandom permutation. further we show efficient constructions of super-pseudorandom permutations by using above mentioned g.
coalgebras and monads in the semantics of java. this paper describes the basic structures in the denotational and axiomatic semantics of sequential java, both from a monadic and a coalgebraic perspective. this semantics is an abstraction of the one used for the verification of (sequential) java programs using proof tools in the loop project at the university of nijmegen. it is shown how the monadic perspective gives rise to the relevant computational structure in java (composition, extension and repetition), and how the coalgebraic perspective offers an associated program logic (with invariants, bisimulations, and hoare logics) for reasoning about the computational structure provided by the monad.
analytical depoissonization and its applications. in combinatorics and analysis of algorithms a poisson version of a problem (henceforth called a poisson model or poissonization) is often easier to solve than the original one, which we name here the bernoulli model. poissonization is a technique that replaces the original input (e.g., think of balls thrown into urns) by a poisson process (e.g., think of balls arriving according to a poisson process into urns). more precisely, analytical poisson transform maps a sequence (e.g., characterizing the bernoulli model) into a generating function of a complex variable. however, after poissonization one must depoissonize in order to translate the results of the poisson model into the original (i.e., bernoulli) model. we present in this paper several analytical depoissonization results that fall into the following general scheme: if the poisson transform has an appropriate growth in the complex plane, then an asymptotic expansion of the sequence can be expressed in terms of the poisson transform and its derivatives evaluated on the real line. not surprisingly, actual formulations of depoissonization results depend on the nature of the growth of the poisson transform, and thus we have polynomial and exponential depoissonization theorems. normalization (e.g., as in the central limit theorem) introduces another twist that led us to formulate the so-called diagonal depoissonization theorems. finally, we illustrate our results on numerous examples from combinatorics and the analysis of algorithms and data structures (e.g., combinatorial assemblies, digital trees, multiaccess protocols, probabilistic counting, selecting a leader, data compression, etc.). &mdash;authors' abstract
on the computational content of the lawson topology. an element of an effectively given domain is computable iff its basic scott open neighbourhoods are recursively enumerable. we thus refer to computable elements as scott computable and define an element to be lawson computable if its basic lawson open neighbourhoods are recursively enumerable. since the lawson topology is finer than the scott topology, a stronger notion of computability is obtained. for example, in the powerset of the natural numbers with its standard effective presentation, an element is scott computable iff it is a recursively enumerable set, and it is lawson computable iff it is a recursive set. among other examples, we consider the upper powerdomain of euclidean space, for which we prove that scott and lawson computability coincide with two notions of computability for compact sets recently proposed by brattka and weihrauch in the framework of type-two recursion theory.
how the (1+1) es using isotropic mutations minimizes positive definite quadratic forms. the (1+1) evolution strategy (es), a simple, mutation-based evolutionary algorithm for continuous optimization problems, is analyzed. in particular, we consider the most common type of mutations, namely gaussian mutations, and the 1/5-rule for mutation adaptation, and we are interested in how the runtime/number of function evaluations to obtain a predefined reduction of the approximation error depends on the dimension of the search space.the most discussed function in the area of es is the so-called sphere-function given by sphere: rn → r with x↦x⊤ix (where i ∈ rn×n is the identity matrix), which also has already been the subject of a runtime analysis. this analysis is extended to arbitrary positive definite quadratic forms that induce ellipsoidal fitness landscapes which are "close to being spherically symmetric", showing that the order of the runtime does not change compared to sphere. furthermore, certain positive definite quadratic forms frn → r with x↦x⊤qx, where q ∈ rn×n, inducing ellipsoidal fitness landscapes that are "far away from being spherically symmetric" are exemplarily investigated, namely f(x)=ξċ(x12 +...+ xn/22)+xn/2+12 +...+ xn2 with ξ= poly(n) such that 1/ξ → 0 as n → ∞. it is proved that the optimization very quickly stabilizes and that, subsequently, the runtime to halve the approximation error is θ(ξ ċ n) compared to θ(n) for sphere.
on learning of functions refutably. learning of recursive functions refutably informally means that for every recursive function, the learning machine has either to learn this function or to refute it, that is to signal that it is not able to learn it. three modi of making precise the notion of refuting are considered. we show that the corresponding types of learning refutably are of strictly increasing power, where already the most stringent of them turns out to be of remarkable topological and algorithmical richness. furthermore, all these types are closed under union, though in different strengths. also, these types are shown to be different with respect to their intrinsic complexity; two of them do not contain function classes that are "most difficult" to learn, while the third one does. moreover, we present several characterizations for these types of learning refutably. some of these characterizations make clear where the refuting ability of the corresponding learning machines comes from and how it can be realized, in general.for learning with anomalies refutably, we show that several results from standard learning without refutation stand refutably. from this we derive some hierarchies for refutable learning. finally, we prove that in general one cannot trade stricter refutability constraints for more liberal learning criteria.
on the learnability of recursively enumerable languages from good examples. the present paper investigates identification of indexed families l of recursively enumerable languages from good examples. we distinguish class-preserving learning from good examples (the good examples have to be generated with respect to a hypothesis space having the same range as l) and class-comprising learning from the good examples (the good examples have to be selected with respect to a hypothesis space comprising the range of l). a learner is required to learn a target language on every finite superset of the good examples for it. if the learner's first and only conjecture is correct then the underlying learning model is referred to as finite identification from good examples and if the learner makes a finite number of incorrect conjectures before always outputting a correct one, the model is referred to as limit identification from good examples. in the context of class-preserving learning, it is shown that the learning power of finite and limit identification from good text examples coincide. when class comprising learning from good text examples is concerned, limit identification is strictly more powerful than finite learning. furthermore, if learning from good informant examples is considered, limit identification is superior to finite identification in the class preserving as well as in the class-comprising case. finally, we relate the models of learning from good examples to one another as well as to the standard learning models in the context of gold-style language learnin
mind change complexity of learning logic programs. the present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. it establishes ordinal mind change complexity bounds for learnability of these classes both from positive facts and from positive and negative facts. building on angluin's notion of finite thickness and wright's work on finite elasticity, shinohara defined the property of bounded finite thickness to give a sufficient condition for learnability of indexed families of computable languages from positive data. this paper shows that an effective version of shinohara's notion of bounded finite thickness gives sufficient conditions for learnability with ordinal mind change bound, both in the context of learnability from positive data and for learnability from complete (both positive and negative) data. let ω be a notation for the first limit ordinal. then, it is shown that if a language defining framework yields a uniformly decidable family of languages and has effective bounded finite thickness, then for each natural number m > 0, the class of languages defined by formal systems of length ≤ m: • is identifiable in the limit from positive data with a mind change bound of ω m; • is identifiable in the limit from both positive and negative data with an ordinal mind change bound of ω × m. the above sufficient conditions are employed to give an ordinal mind change bound for learnability of minimal models of various classes of length-bounded prolog programs, including shapiro's linear programs, arimura and shinohara's depth-bounded linearly covering programs, and krishna rao's depth-bounded linearly moded programs. it is also noted that the bound for learning from positive data is tight for the example classes considered.
learning how to separate. the main question addressed in the present work is how to find effectively a recursive function separating two sets drawn arbitrarily from a given collection of disjoint sets. in particular, it is investigated when one can find better learners which satisfy additional constraints. such learners are the following: confident learners which converge on all data-sequences; conservative learners which abandon only definitely wrong hypotheses; set-driven learners whose hypotheses are independent of the order and the number of repetitions of the data-items supplied; learners where either the last or even all hypotheses are programs of total recursive functions.the present work gives a complete picture of the relations between these notions: the only implications are that whenever one has a learner which only outputs programs of total recursive functions as hypotheses, then one can also find learners which are conservative and set-driven. the following two major results need a nontrivial proof: (1) there is a class for which one can find, in the limit, recursive functions separating the sets in a confident and conservative way, but one cannot find even partial-recursive functions separating the sets in a set-driven way. (2) there is a class for which one can find, in the limit, recursive functions separating the sets in a confident and set-driven way, but one cannot find even partial-recursive functions separating the sets in a conservative way.
approximate strong separation with application in fractional graph coloring and preemptive scheduling. in this paper we show that approximation algorithms for the weighted independent set and s-dimensional knapsack problem with ratio a can be turned into approximation algorithms with the same ratio for fractional weighted graph coloring and preemptive resource constrained scheduling. in order to obtain these results, we generalize known results by grötschel, lovasz and schrijver on separation, non-emptiness test, optimization and violation in the direction of approximability.
an asymptotic fully polynomial time approximation scheme for bin covering. in the bin covering problem there is a group l = (a1,...,an) of items with sizes s(ai) ∈ (0, 1), and the goal is to find a packing of the items into bins to maximize the number of bins that receive items of total size at least 1. this is a dual problem to the classical bin packing problem. in this paper we present the first asymptotic fully polynomial-time approximation scheme for the problem.
on average sequence complexity. in this paper we study the average behavior of the number of distinct substrings in a text of size n over an alphabet of cardinality k. this quantity is called the complexity index and it captures the "richness of the language" used in a sequence. for example, sequences with low complexity index contain a large number of repeated substrings and they eventually become periodic (e.g., tandem repeats in a dna sequence). in order to identify unusually low- or high-complexity strings one needs to determine how far are the complexities of the strings under study from the average or maximum string complexity. while the maximum string complexity was studied quite extensively in the past, to the best of our knowledge there are no results concerning the average complexity. we first prove that for a sequence generated by a mixing model (which includes markov sources) the average complexity is asymptotically equal to n2/2 which coincides with the maximum string complexity. however, for a memoryless source we establish a more precise result, namely the average string complexity is n2/2 - n logk n + (1 + ( 1 - γ)/ln k + φk (logkn) + o(1))n where γ ≈ 0.577 and φk(x) is a periodic function with a small amplitude for small alphabet size.
inferring a level-1 phylogenetic network from a dense set of rooted triplets. we consider the following problem: given a set j of rooted triplets with leaf set l, determine whether there exists a phylogenetic network consistent with j, and if so, construct one. we show that if no restrictions are placed on the hybrid nodes in the solution, the problem is trivially solved in polynomial time by a simple sorting network-based construction. for the more interesting (and biologically more motivated) case where the solution is required to be a level-1 phylogenetic network, we present an algorithm solving the problem in o(|t|2) time when t is dense, i.e., when t contains at least one rooted triplet for each cardinality three subset of l. we also give an o(|t|5/3)-time algorithm for finding the set of all phylogenetic networks having a single hybrid node attached to exactly one leaf (and having no other hybrid nodes) that are consistent with a given dense set of rooted triplets.
from truth to computability i. the recently initiated approach called computability logic is a formal theory of interactive computation. it understands computational problems as games played by a machine against its environment, and uses logical formalism to describe valid principles of computability, with formulas representing computational problems and logical operators standing for operations on computational problems. the concept of computability that lies under this approach is a generalization of church-turing computability from simple, two-step (question/answer, input/output) problems to problems of arbitrary degrees of interactivity. restricting this concept to predicates, which are understood as computational problems of zero degree of interactivity, yields exactly classical truth. this makes computability logic a generalization and refinement of classical logic.the foundational paper "introduction to computability logic" [g. japaridze, ann. pure appl. logic 123 (2003) 1-99] was focused on semantics rather than syntax, and certain axiomatizability assertions in it were only stated as conjectures. the present contribution contains a verification of one of such conjectures: a soundness and completeness proof for the deductive system cl3 which axiomatizes the most basic first-order fragment of computability logic called the finite-depth, elementary-base fragment. cl3 is a conservative extension of classical predicate calculus in the language which, along with all of the (appropriately generalized) logical operators of classical logic, contains propositional connectives and quantifiers representing the so called choice operations. the atoms of this language are interpreted as elementary problems, i.e. predicates in the standard sense. among the potential application areas for cl3 are the theory of interactive computation, constructive applied theories, knowledgebase systems, systems for resource-bound planning and action.this paper is self-contained as it reintroduces all relevant definitions as well as main motivations. it is meant for a wide audience and does not assume that the reader has specialized knowledge in any particular subarea of logic or computer science.
a theory of bisimulation for a fragment of concurrent ml with local names. concurrent ml is an extension of standard ml with π-calculus-like primitives for multithreaded programming. cml has a reduction semantics, but to date there has been no labelled transition system semantics provided for the entire language. in this paper, we present a labelled transition semantics for a fragment of cml called µvcml which includes features not covered before: dynamically generated local channels and thread identifiers. we show that weak bisimilarity for µvcml is a congruence, and coincides with barbed bisimulation congruence. we also provide a variant of sangiorgi's normal bisimulation for µvcml, and show that this too coincides with bisimilarity.
a fully abstract may testing semantics for concurrent objects. this paper provides a fully abstract semantics for a variant of the concurrent object calculus. we define may testing for concurrent object components and then characterise it using a trace semantics inspired by uml interaction diagrams. the main result of this paper is to show that the trace semantics is fully abstract for may testing. this is the first such result for a concurrent object language.
least-recently-used caching with dependent requests. we investigate a widely popular least-recently-used (lru) cache replacement algorithm with semi-markov modulated requests. semi-markov processes provide the flexibility for modeling strong statistical correlation, including the widely reported long-range dependence in the world wide web page request patterns. when the frequency of requesting a page n is equal to the generalized zipf's law c/nα, α > 1, our main result shows that the cache fault probability is asymptotically, for large cache sizes, the same as in the corresponding lru system with i.i.d. requests. the result is asymptotically explicit and appears to be the first computationally tractable average-case analysis of lru caching with statistically dependent request sequences. the surprising insensitivity of lru caching performance demonstrates its robustness to changes in document popularity. furthermore, we show that the derived asymptotic result and simulation experiments are in excellent agreement, even for relatively small cache sizes.
characterisations of balanced words via orderings. three new characterisations of balanced words are presented. each of these characterisations is based on the ordering of a shift orbit, either lexicographically or with respect to the norm |ċ|1 (which counts the number of occurrences of the symbol 1).
a lower bound on compression of unknown alphabets. many applications call for universal compression of strings over large, possibly infinite, alphabets. however, it has long been known that the resulting redundancy is infinite even for i.i.d distributions. it was recently shown that the redundancy of the strings' patterns, which abstract the values of the symbols, retaining only their relative precedence, is subliner in the blocklength n, hence the per-symbol redundancy diminishers to zero. in this paper we show that pattern redundancy is at least (1.5log2e)n1/3 bits to do so, we construct a generating function whose coefficients lower bound the redundancy, and use hayman's saddle-point approximation technique to determine the coefficients' asymptotic behavior.
scheduling linear deteriorating jobs with an availability constraint on a single machine. we consider a single machine scheduling problem in which the processing time of a job is a simple linear increasing function of its starting time and the machine is subject to an availability constraint. we consider the non-resumable case. the objectives are to minimize the makespan and the total completion time. we show that both problems are np-hard and present pseudopolynomial time optimal algorithms to solve them. furthermore, for the makespan problem, we present an optimal approximation algorithm for the on-line case, and a fully polynomial time approximation scheme for the off-line case. for the total completion time problem, we provide a heuristic and evaluate its efficiency by computational experiments.
unification and extension of weighted finite automata applicable to image compression. weighted finite automata (wfa), including the linear wfa due to culik and kari and the acyclic wfa due to hafner, have been under investigation over the years for their applications to image compression. we shall in this work first examine in great details the underlying wfa structure and propose the most systematic extension, along with its full legitimacy analysis, to the wfa that are applicable to image compression. a new mechanism based on the concept of resolution-wise and resolution-driven image mappings is developed to create rich families of legitimate similarity images so as to reduce the overall wfa size, a property that is critically related the performance of wfa-based compression codecs. moreover, we shall also unify the relevant wfa by showing an acyclic wfa can always be merged into a linear wfa but not vice versa.
on liveness and boundedness of asymmetric choice nets. this paper concerns two important techniques, characterization and property-preserving transformation, for verifying some basic properties of asymmetric choice petri nets (ac nets). in the literature, a majority of the characterizations are for ordinary free choice nets. this paper presents many extended (from free choice nets) and new characterizations for four properties: liveness with respect to an initial marking, liveness monotonicity with respect to an initial marking, well-formedness, liveness and boundedness with respect to an initial marking. the nets involved are extended to homogeneous free choice nets, ordinary ac nets and homogeneous ac nets. this paper also investigates the transformation of merging a set of places of an ordinary ac net and proposes the conditions for it to preserve the siphon-trap-property (st-property), liveness, boundedness and reversibility. the results are then applied to the verification of resource-sharing systems. at present, the major approaches for solving this problem are based on state machines or marked graphs and are not based on property preservation. our approach extends the scopes of the underlying nets to ac nets and the verification techniques. it is found that the st-property plays a very important role in many of the results. furthermore, mainly through examples, the importance of the assumptions in the proposed characterizations and transformation and the limitation on further extensions are pointed out.
on the -path cover problem for cacti. in this paper we investigate the k-path cover problem for graphs, which is to find the minimum number of vertex disjoint k-paths that cover all the vertices of a graph. the k-path cover problem for general graphs is np-complete. though notable applications of this problem to database design, network, vlsi design, ring protocols, and code optimization, efficient algorithms are known for only few special classes of graphs. in order to solve this problem for cacti, i.e., graphs where no edge lies on more than one cycle, we introduce the so-called steiner version of the k-path cover problem, and develop an efficient algorithm for the steiner k-path cover problem for cacti, which finds an optimal k-path cover for a given cactus in polynomial time.
state complexity of some operations on binary regular languages. we investigate the state complexity of some operations on binary regular languages. in particular, we consider the concatenation of languages represented by deterministic finite automata, and the reversal and complementation of languages represented by nondeterministic finite automata. we prove that the upper bounds on the state complexity of these operations, which were known to be tight for larger alphabets, are tight also for binary alphabets.
creol: a type-safe object-oriented model for distributed concurrent systems. object-oriented distributed computing is becoming increasingly important for critical infrastructure in society. in standard object-oriented models, objects synchronize on method calls. these models may be criticized in the distributed setting for their tight coupling of communication and synchronization; network delays and instabilities may locally result in much waiting and even deadlock. the creol model targets distributed objects by a looser coupling of method calls and synchronization. asynchronous method calls and high-level local control structures allow local computation to adapt to network instability. object variables are typed by interfaces, so communication with remote objects is independent from their implementation. the inheritance and subtyping relations are distinct in creol. interfaces form a subtype hierarchy, whereas multiple inheritance is used for code reuse at the class level. this paper presents the creol syntax, operational semantics, and type system. it is shown that runtime type errors do not occur for well-typed programs.
recognizing frozen variables in constraint satisfaction problems. in constraint satisfaction problems over finite domains, some variables can be frozen, that is, they take the same value in all possible solutions. we study the complexity of the problem of recognizing frozen variables with restricted sets of constraint relations allowed in the instances. we show that the complexity of such problems is determined by certain algebraic properties of these relations. under the assumption that np ≠ conp (and consequently ptime ≠ np), we characterize all tractable problems, and describe large classes of np-complete, conp-complete, and dp-complete problems. as an application of these results, we completely classify the complexity of the problem in two cases: (1) with domain size 2; and (2) when all unary relations are present. we also give a rough classification for domain size 3.
a note on the strong and weak generative powers of formal systems. this paper is a note on some relationships between the strong and weak generative powers of formal systems, in particular, from the point of view of squeezing more strong power out of a formal system without increasing its weak generative power. we will comment on some old and new results from this perspective. our main goal of this note is to comment on the strong generative power of context-free grammars, lexicalized tree-adjoining grammars (and some of their variants) and lambek grammars, especially in the context of crossing dependencies, in view of the recent work of tiede (ph.d. dissertation, indiana university, bloomington, 1999).
an efficient deterministic parallel algorithm for two processors precedence constraint scheduling. we present here a new deterministic parallel algorithm for the two-processor scheduling problem. the algorithm uses only o(n3) processors and takes o(log2n) time on a crew pram. in order to prove the above bounds we show how to compute in nc the lexicographically first matching for a special kind of convex bipartite graphs.
restarting automata with restricted utilization of auxiliary symbols. the restarting automaton is a restricted model of computation that was introduced by jančar et al. to model the so-called analysis by reduction, which is a technique used in linguistics to analyse sentences of natural languages. the most general models of restarting automata make use of auxiliary symbols in their rewrite operations, although this ability does not directly correspond to any aspect of the analysis by reduction. here we put restrictions on the way in which restarting automata use auxiliary symbols, and we investigate the influence of these restrictions on their expressive power. in fact, we consider two types of restrictions. first, we consider the number of auxiliary symbols in the tape alphabet of a restarting automaton as a measure of its descriptional complexity. secondly, we consider the number of occurrences of auxiliary symbols on the tape as a dynamic complexity measure. we establish some lower and upper bounds with respect to these complexity measures concerning the ability of restarting automata to recognize the (deterministic) context-free languages and some of their subclasses.
episturmian words and episturmian morphisms. infinite episturmian words are a generalization of sturmian words which includes the arnoux-rauzy sequences. we continue their study and that of episturmian morphisms, begun previously, in relation with the action of the shift operator. palindromic and periodic factors of these words are described. we consider, in particular, the case where these words are generated by morphisms and introduce then a notion of intercept generalizing that of sturmian words. finally, we prove that the frequencies of the factors in a strong sense do exist for all episturmian words.
general linear relations between different types of predictive complexity. in this paper we introduce a general method of establishing tight linear inequalities between different types of predictive complexity. predictive complexity is a generalization of kolmogorov complexity and it bounds the ability of an algorithm to predict elements of a sequence. our method relies upon probabilistic considerations and allows us to describe explicitly the sets of coefficients which correspond to true inequalities. we apply this method to two particular types of predictive complexity, namely, logarithmic complexity, which coincides with a variant of kolmogorov complexity, and square-loss complexity, which is interesting for applications.
loss functions, complexities, and the legendre transformation. the paper introduces a way of re-constructing a loss function from predictive complexity. we show that a loss function and expectations of the corresponding predictive complexity w.r.t. the bernoulli distribution are related through the legendre transformation. it is shown that if two loss functions specify the same complexity then they are equivalent in a strong sense. the expectations are also related to the so-called generalized entropy.
maximal pattern complexity of two-dimensional words. the maximal pattern complexity of one-dimensional words has been studied in several papers [t. kamae, l. zamboni, sequence entropy and the maximal pattern complexity of infinite words, ergodic theory dynam. systems 22(4) (2002) 1191-1199; t. kamae, l. zamboni, maximal pattern complexity for discrete systems, ergodic theory dynam. systems 22(4) (2002) 1201-1214; t. kamae, h. rao, pattern complexity over l letters, e. comb. j., to appear; t. kamae, y.m. xue, two dimensional word with 2k maximal pattern complexity, osaka j. math. 41(2) (2004) 257-265]. we study the maximal pattern complexity pα(k) of two-dimensional words α. a two-dimensional version of the notion of strong recurrence is introduced. it is shown that if α is strongly recurrent, then either α is doubly periodic or pα(k≥2k (k = 1, 2,...). accordingly, we define a two-dimensional pattern sturmian word as a strongly recurrent word α with pα(k = 2k. examples of pattern sturmian words are given.
automatic semigroups and categories. we consider various automata-theoretic properties of semigroupoids and small categories and their relationship to the corresponding properties in semigroups and monoids. we introduce natural definitions of finite automata and regular languages over finite graphs, generalising the usual notions over finite alphabets. these allow us to introduce a definition of automaticity for semi-groupoids and small categories, which generalises those introduced for semigroups by hudson and for groupoids by epstein. we also introduce a definition of prefix-automaticity for semigroupoids and small categories, generalising that for certain monoids introduced by silva and steinberg.we study the relationship between automaticity properties in a semigroupoid and in a certain associated semigroup. this allows us to extend to semigroupoids and small categories a number of results about automatic and prefix-automatic semigroups and monoids. in the course of our study, we also prove some new results about automaticity and prefix-automaticity in semigroups and monoids. these include the fact that prefix-automaticity is preserved under the taking of cofinite subsemigroups.
word problems recognisable by deterministic blind monoid automata. we consider blind, deterministic, finite automata equipped with a register which stores an element of a given monoid, and which is modified by right multiplication by monoid elements. we show that, for monoids m drawn from a large class including groups, such an automaton accepts the word problem of a group h if and only if h has a finite index subgroup which embeds in the group of units of m. in the case that m is a group, this answers a question of elston and ostheimer.
strong normalizability of the non-deterministic catch/throw calculi. the catch/throw mechanism in common lisp provides a simple control mechanism for non-local exits. we study typed calculi by nakano and sato which formalize the catch/throw mechanism. these calculi correspond to classical logic through the curry-howard isomorphism, and one of their characteristic points is that they have non-deterministic reduction rules. these calculi can represent various computational meaning of classical proofs. this paper is mainly concerned with the strong normalizability of these calculi. namely, we prove the strong normalizability of these calculi, which was an open problem. we first formulate a non-deterministic variant of parigot's &lambda;&mu;-calculus, and show it is strongly normalizing. we then translate the catch/throw calculi to this variant. since the translation preserves typing and reduction, we obtain the strong normalization of the catch/throw calculi. we also briefly consider second-order extension of the catch/throw calculi. copyright 2002 elsevier science b.v
linear and affine logics with temporal, spatial and epistemic operators. a temporal spatial epistemic intuitionistic linear logic (tseill) is introduced, and the completeness theorem for this logic is proved with respect to kripke semantics. tseill has three temporal modal operators: [f] (any time in the future), [n] (next time) and [p] (past), some spatial modal operators [li] (locations), two epistemic modal operators; [k] (know) and (k), and a linear modal operator ! (exponential). a basic normal modal intuitionistic affine logic (bial) and its normal extensions are also defined, and the completeness theorems for these logics are proved with respect to kripke semantics. in the proposed semantic framework of these normal extensions, a simple correspondence can be given between frame conditions and lemmon-scott axioms. a dynamic intuitionistic affine logic (dial) is proposed as an affine version of (test-free) dynamic logic, and the completeness theorem for this logic is shown with respect to kripke semantics. finally, some intuitive interpretations, such as resource and informational interpretations, are given for the proposed logics and semantics. by using these logics, semantics and interpretations, various kinds of fine-grained resource-sensitive reasoning can be expressed.
finite-memory automata. a model of computation dealing with infinite alphabets is proposed. the model is based on replacing the equality test by unification. it appears to be a natural generalization of the classical rabin-scott finite-state automata and possesses many of their properties.
default theories over monadic languages. in this paper we compare the semantical and syntactical definitions of extensions for open default theories. we prove that, over monadic languages, these definitions are equivalent and do not depend on the cardinality of the underlying infinite world. we also show that, under the domain closure assumption, one free variable open default theories are decidable.
lower bounds on the minus domination and k-subdomination numbers. a three-valued function f defined on the vertex set of a graph g=(v,e), f:v → {-1,0,1} is a minus dominating function if the sum of its function values over any closed neighborhood is at least one. that is, for every v ∈ v, f(n[v]) ≥ 1, where n[v] consists of v and all vertices adjacent to v. the weight of a minus function is f(v)= σv ∈ v f(v). the minus domination number of a graph g, denoted by γ-(g), equals the minimum weight of a minus dominating function of g. in this paper, sharp lower bounds on minus domination of a bipartite graph are given. thus, we prove a conjecture proposed by dunbar et al. (discrete math. 199 (1999) 35), and we give a lower bound on γks(g) of a graph g.
paired-domination in inflated graphs. the inflation g1 of a graph g with n(g) vertices and m(g) edges is obtained from g by replacing every vertex of degree d of g by a clique kd. a set s of vertices in a graph g is a paired dominating set of g if every vertex of g is adjacent to some vertex in s and if the subgraph induced by s contains a perfect matching. the paired domination number λp(g) is the minimum cardinality of a paired dominating set of g. in this paper, we show that if a graph g has a minimum degree δ(g) ≥ 2, then n(g) ≤ λp(g1) ≤ 4m(g)/[δ(g) + 1], and the equality λp(g1)=n(g) holds if and only if g has a perfect matching. in addition, we present a linear time algorithm to compute a minimum paired-dominating set for an inflation tree.
phase semantics for light linear logic. light linear logic (girard, inform. comput. 14 (1998) 175-204) is a refinement of the propositions-as-types paradigm to polynomial-time computation. a semantic setting for the underlying logical system is introduced here in terms of fibred phase spaces. strong completeness is established, with a purely semantic proof of cut elimination as a consequence. a number of mathematical examples of fibred phase spaces are presented that illustrate subtleties of light linear logic.
the aggregation and cancellation techniques as a practical tool for faster matrix multiplication. the main purpose of this paper is to present a fast matrix multiplication algorithm taken from the paper of laderman et al. (linear algebra appl. 162-164 (1992) 557) in a refined compact "analytical" form and to demonstrate that it can be implemented as quite efficient computer code. our improved presentation enables us to simplify substantially the analysis of the computational complexity and numerical stability of the algorithm as well as its computer implementation. the algorithm multiplies two n × n matrices using o(n2.7760) arithmetic operations. in the case where n = 18 ċ 48k, for a positive integer k, the total number of flops required by the algorithm is 4.894n2.7760 - 16.165n2, which may be compared to a similar estimate for the winograd algorithm, 3.732n2.8074 - 5n2 flops, n = 8 ċ 2k, the latter being current record bound among all known practical algorithms. moreover, we present a pseudo-code of the algorithm which demonstrates its very moderate working memory requirements, much smaller than that of the best available implementations of strassen and winograd algorithms. for matrices of medium-large size (say, 2000 ≤ n < 10,000) we consider one-level algorithms and compare them with the (multilevel) strassen and winograd algorithms. the results of numerical tests clearly indicate that our accelerated matrix multiplication routines implementing two or three disjoint product-based algorithm are comparable in computational time with an implementation of winograd algorithm and clearly outperform it with respect to working space and (especially) numerical stability. the tests were performed for the matrices of the order of up to 7000, both in double and single precision.
succinct representations of languages by dfa with different levels of reliability. in this paper, we propose qualitative measures for the reliability of representations of languages by deterministic finite automata. we analyze the relationships between different qualitative features and investigate tradeoffs between different qualitative levels of reliability. furthermore, we prove that the savings in the number of states between representations having different qualitative features cannot be bounded by any function. these results hold even when the descriptions are required to exceed any given fixed level of quantified reliability.
weak repetitions in sturmian strings. in this paper, we analyze the weak repetitions in sturmian strings and show that an optimally efficient algorithm to compute the weak repetitions in sturmian strings according to the output encodings defined in the literature is quadratic in the string length. finally, we present an encoding that leads to a linear-time algorithm.
computing by commuting. we consider the power of the following rewriting: given a finite or regular set x of words and an initial word w, apply iteratively the operation which deletes a word from x from one of the ends of w and simultaneously catenates another word from x to the opposite end of w. we show that if the deletion is always done at the beginning and the catenation at the end, and the choice of a word to be catenated does not depend on the word erased, then the generated language is always regular, though the derivability relation is not, in general, rational. if the deletion and the catenation are done arbitrarily at the opposite ends, the language need not be regular. if the catenation is done at the same end as the deletion, the relation of derivability is rational even if the catenated word can depend on the word erased.
commutation with codes. the centralizer of a set of words x is the largest set of words c(x)commuting with x: xc(x) = c(x)x. it has been a long standing open question due to [j.h. conway, regular algebra and finite machines, chapman & hall, london (1971).], whether the centralizer of any rational set is rational. while the answer turned out to be negative in general, see [m. kunc, proc. of icalp 2004, lecture notes in computer science, vol. 3142, springer, berlin, 2004, pp. 870-881.], we prove here that the situation is different for codes: the centralizer of any rational code is rational and if the code is finite, then the centralizer is finitely generated. this result has been previously proved only for binary and ternary sets of words in a series of papers by the authors and for prefix codes in an ingenious paper by [b. ratoandromanana, rairo inform. theor. 23(4) (1989) 425-444.]--many of the techniques we use in this paper follow her ideas. we also give in this paper an elementary proof for the prefix case.
multiple factorizations of words and defect effect. we prove that if x is a finite prefix set and w is a non-periodic bi-infinite word, possessing 3 disjoint x-factorizations, then the combinatorial rank of x is at most card(x)2. this is one of the rare cases when a cumulative defect effect is known to hold. finally, connections to the critical factorization theorem are discussed.
a defect theorem for bi-infinite words. we formulate and prove a defect theorem for bi-infinite words. let x be a finite set of words over a finite alphabet. if a nonperiodic bi-infinite word w has two x-factorizations, then the combinatorial rank of x is at most card(x)- 1, i.e., there exists a set f such that x ⊆ f+ with card(f) > card(x). moreover, in the case when the combinatorial rank of x equals card(x), the number of periodic bi-infinite words which have two different x-factorizations is finite.
conway's problem for three-word sets. we prove two results on commutation of languages. first, we show that the maximal language commuting with a three-element language, i.e. its centralizer, is rational, thus giving an affirmative answer to a special case of a problem proposed by conway in 1971. second, we characterize all languages commuting with a three-element code. the characterization is similar to the one proved by bergman for polynomials over noncommuting variables (see trans. am. math. soc. 137 (1969) 327 and algebraic combinatorics on words, cambridge university press, cambridge, 2000): a language commutes with a three-element code x if and only if it is a union of powers of x.
on the complexity of decidable cases of the commutation problem of languages. we investigate the complexity of basic decidable cases of the commutation problem for languages: testing the equality xy = yx for two languages x and y. we show that it varies from co-nexptime complete through pspace complete and co-np complete to deterministic polynomial time, when y is an explicitly given finite language and x is given by a cf grammar generating a finite language, a nondeterministic finite automaton (or a regular expression), an acyclic nondeterministic finite automaton or an explicitly given finite language, respectively. interestingly in most cases the complexity status does not change if instead of explicitly given finite y we consider general y of the same type as x. for deterministic finite automata the problem remains open, due to the asymmetry of the catenation.
generalized factorizations of words and their algorithmic properties. we formalize the notion of a factorization of a word, a so-called f-factorization, introduced in \cite{kmp} when solving some open problems on word equations. we show that most of the factorizations considered in the literature fit well into that framework, and in particular that central algorithmic problems, such as the uniqueness or the synchronizability, remain polynomial time solvable for an important and large class of f-factorizations, namely for regular f-factorizations.
synchronizing finite automata on eulerian digraphs. cerný's conjecture and the road coloring problem are two open problems concerning synchronization of finite automata. we prove these conjectures in the special case that the vertices have uniform in- and outdegrees.
theory of cellular automata: a survey. this article surveys some theoretical aspects of cellular automata ca research. in particular, we discuss classical and new results on reversibility, conservation laws, limit sets, decidability questions, universality and topological dynamics of ca. the selection of topics is by no means comprehensive and reflects the research interests of the author. the main goal is to provide a tutorial of ca theory to researchers in other branches of natural computing, to give a compact collection of known results with references to their proofs, and to suggest some open problems.
on properties of bond-free dna languages. the input data for dna computing must be encoded into the form of single or double dna strands. as complementary parts of single strands can bind together forming a double-stranded dna sequence, one has to impose restrictions on these sets of dna words (languages) to prevent them from interacting in undesirable ways. we recall a list of known properties of dna languages which are free of certain types of undesirable bonds. then we introduce a general framework in which we can characterize each of these properties by a solution of a uniform formal language inequation. this characterization allows us among others to construct (i) a uniform algorithm deciding in polynomial time whether a given dna language possesses any of the studied properties, and (ii) in many cases also an algorithm deciding whether a given dna language is maximal with respect to the desired property.
aspects of shuffle and deletion on trajectories. word and language operations on trajectories provide a general framework for the study of properties of sequential insertion and deletion operations. a trajectory gives a syntactical constraint on the scattered insertion (deletion) of a word into(from) another one, with an intuitive geometrical interpretation. moreover, deletion on trajectories is an inverse of the shuffle on trajectories. these operations are a natural generalization of many binary word operations like catenation, quotient, insertion, deletion, shuffle, etc. besides they were shown to be useful, e.g. in concurrent processes modelling and recently in biocomputing area.we begin with the study of algebraic properties of the deletion on trajectories. then we focus on three standard decision problems concerning linear language equations with one variable, involving the above mentioned operations. we generalize previous results and obtain a sequence of new ones. particularly, we characterize the class of binary word operations for which the validity of such a language equation is (un)decidable, for regular and context-free operands.
continuous monoids and semirings. different kinds of monoids and semirings have been defined in the literature, all of them named "continuous". we show their relations. the main technical tools are suitable topologies, among others a variant of the well-known scott topology for complete partial orders.
generalized and geometric ramsey numbers for cycles. let cn denote the cycle of length n. the generalized ramsey number of the pair (cn , ck) denoted by; r(cn, ck)is the smallest positive integer rsuch that any complete graph with r vertices whose edges are coloured with two di/erent colours contains either a monochromatic cycle of length n in the 1rst colour or a monochromatic cycle of length k in the second colour. generalized ramsey numbers for cycles were completely determined by faudree-schelp and rosta, based on earlier works of bondy, erd&ohuml;s and gallai. unfortunately, both proofs are quite involved and di9cult to follow. in the present paper we treat this problem in a uni1ed, self-contained and simpli1ed way. we also extend this study to a related geometric problem, where we colour the straight-line segments determined by a 1nite number of points in the plane. in this case, the monochromatic subgraphs are required to satisfy an additional (non-crossing) geometric condition.
correctness of constructing optimal alphabetic trees revisited. several new observations which lead to new correctness proofs of two known algorithms (hu-tucker and garsia-wachs) for construction of optimal alphabetic trees are presented. a generalized version of the garsia-wachs algorithm is given. proof of this generalized version works in a structured and illustrative way and clarifies the usually poorly-understood behavior of both the hu-tucker and garsia-wachs algorithms. the generalized version permits any non-negative weights, as opposed to strictly positive weights required in the original garsia-wachs algorithm. new local structural properties of optimal alphabetic trees are given. the concept of {\em well-shaped segment\/} (a part of an optimal tree) is introduced. it is shown that some parts of the optimal tree are known in advance to be well-shaped, and this implies correctness of the algorithms rather easily. the crucial part of the correctness proof of the garsia-wachs algorithm, namely the {\em structural theorem}, is identified. the correctness proof of the hu-tucker algorithm consists of showing a very simple mutual simulation between this algorithm and the garsia-wachs algorithm. for this proof, it is essential to use the generalized version of garsia-wachs algorithm, in which an arbitrary locally minimal pair is processed, not necessarily the rightmost minimal pair. such a generalized version is also needed for parallel implementations. another result presented in this paper is the clarification of the problem of resolving ties (equalities between weights of items) in the hu-tucker algorithm. this is related to the proof, by simulation, of correctness of the hu-tucker algorithm. it is shown that the condition that there are no ties may generally be assumed without harm and that, essentially, the hu-tucker algorithm avoids ties automatically.
zero testing of p-adic and modular polynomials. we obtain new algorithms to test if a given multivariate polynomial over p-adic fields is identical to zero. we also consider zero testing of polynomials in residue rings. the results complement a series of known results about zero testing of polynomials over integers, rationals and finite fields.
alphabet-independent optimal parallel search for three-dimensional patterns. we give an alphabet-independent optimal parallel algorithm for the searching phase of three-dimensional pattern-matching. all occurrences of a three dimensional pattern p of shape $m \times m \times m$ in a text t of shape $n \times n \times n$ are to be found. our algorithm works in $\log m$ time with ${\mathcal o}(n/\log(m))$ processors of a {\em crew pram}, where $n = n^3$. the ideas from \cite{abf93} are used. surprisingly, the extension of the two dimensional matching to the three dimensional one is not a trivial modification. the searching phase in three dimensions explores classification of two-dimensional periodicities of the cubic pattern. some projection techniques are developed to deal with three dimensions. the periodicites of the patern with respect to its faces are investigated. the nonperiodicities imply some sparseness properties, while periodicities imply other special useful properties ({\ie} monotonicity) of the set of occurrences. both types of properties are useful in deriving an efficient algorithm.
an approximability result of the multi-vehicle scheduling problem on a path with release and handling times. in this paper, we consider a scheduling problem of vehicles on a path g with n vertices and n - 1 edges. there are m identical vehicles. each vertex in g has exactly one job. any of the n jobs must be processed by some vehicle. each job has a release time and a handling time. with the edges, symmetric travel times are associated. the problem asks to find an optimal schedule of the m vehicles that minimizes the maximum completion time of all the jobs. the problem is known to be np-hard for any fixed m ≥ 2. in this paper, we show that the problem with a fixed m admits a polynomial time approximation scheme. our algorithm can be extended to the case where g is a tree so that a polynomial time approximation scheme is obtained if m and the number of leaves in g are fixed.
enhancements of partitioning techniques for image compression using weighted finite automata. weighted finite automata are efficient structures for the storage of digital images. the choice of the image partitioning technique is important to achieve good compression results. in this paper we examine two promising techniques by measuring the compression performance at well-known test images.
undecidable properties of monoids with word problem solvable in linear time. let c1 be the class of finitely presented monoids with word problem solvable in linear time. let p be a markov property of monoids related to class c1 in some sense. it is undecidable given a monoid in c1 whether it satisfies p. let c and c' be classes of finitely presented monoids with word problem solvable in some time-bounds. if c contains c1 and c' properly contains c, then it is undecidable given a monoid in c' whether it belongs to c.
undecidable properties of monoids with word problem solvable in linear time. part ii-- cross sections and homological and homotopical finiteness conditions. using a particular simulation of single-tape turing machines by finite string-rewriting systems the first two authors have shown that all linear markov properties are undecidable for the class of finitely presented monoids with linear-time decidable word problem. expanding on this construction it is shown here that also many properties that are not known to be linear markov properties are undecidable for this class of monoids. these properties include the existence of context-free or regular cross-sections, the existence of finite convergent presentations, the property of being automatic, and the homological and homotopical finiteness properties left- and right-fpn (n ≥ 3), fht, and fdt.
universal test for quantum one-way permutations. the next bit test was introduced by blum and micali and proved by yao to be a universal test for cryptographic pseudorandom generators. on the other hand, no universal test for the cryptographic one-wayness of functions (or permutations) is known, although the existence of cryptographic pseudorandom generators is equivalent to that of cryptographic one-way functions. in the quantum computation model, kashefi, nishimura and vedral gave a sufficient condition of (cryptographic) quantum one-way permutations and conjectured that the condition would be necessary. in this paper, we affirmatively settle their conjecture and complete a necessary and sufficient condition for quantum one-way permutations. the necessary and sufficient condition can be regarded as a universal test for quantum one-way permutations, since the condition is described as a collection of stepwise tests similar to the next bit test for pseudorandom generators.
a unified language processing methodology. this paper discusses a mathematical concept of language that models both artificial and natural languages and thus provides a framework for a unified language processing methodology. this concept of a language is regarded as a communication tool that allows language users to develop knowledges, while interacting with their universe of discourse, and to communicate with each other, while exchanging knowledges. criteria for consistent usage of a language are established using a galois connection between language syntax and language semantics. solutions to ambiguity, paraphrase, attitude, and other problems concerning the relationship between syntax and semantics are addressed. a general schema for language specification is introduced and algorithms that perform language generation and language analysis are discussed as universal tools defined by the specification schema. language transformations performed by various kinds of translators are examined and correctness criteria of these translators are defined using the language galois connection. the paper is structured as follows: section1 introduces the framework and justifies the necessity of a unified methodology for language processing. section2 presents the mathematical concept of a language. section3 illustrates the mathematical concept of a language with three kinds of language structures: natural language, logical language, and programming language. section4 discusses the algebraic mechanism of language specification that unifies the methodology for language processing tool development. section5 formalizes the criterion for the consistency of the language usage, defines the architecture of a unified language processing system, and shows how the consistency criteria for language usage can be employed as correctness criteria for the algorithms performing various language transformations.
on congruences of automata defined by directed graphs. we consider automata defined by graph algebras of directed graphs, characterize all congruences on these automata, and give a complete description of all automata of this type satisfying three properties for congruences introduced and considered in the literature by analogy with classical semisimplicity conditions that play important roles in structure theory.
clustering for petri nets. this work builds a bridge from • clustering techniques--merging neighbouring nodes which is a key feature for software engineering and the practical applications of petri nets--to • folding techniques--merging only transitions with transitions and places with places, preserving behaviour and allowing theoretical connections to many models of concurrency.a new category of petri nets is introduced. morphisms support clustering, offering attractive properties to software engineering and integrating smoothly with invariants. a computationally reasonable adjunction connects it to folding-based petri nets, namely, to two new cocomplete and complete categories. the dichotomy of structure and behaviour of petri nets is expressed as compatible adjunctions to behavioural categories. finally reachability and process semantics are attached categorically and a new variant of occurrence nets is proposed as a purer image of causality and branching. this framework offers categorical support for practical applications of petri nets.
uncomputability: the problem of induction internalized. i argue that uncomputable formal problems are intuitively, mathematically, and methodologically analogous to empirical problems in which hume's problem of induction arises. in particular, i show that a version of ockham's razor (a preference for simple answers) is advantageous in both domains when infallible inference is infeasible. a familiar response to the empirical problem of induction is to conceive of empirical inquiry as an unending process that converges to the truth without halting or announcing for sure when the truth has been reached. on the strength of the analogies developed, i recommend the adoption of a similar perspective on uncomputable formal problems. one obtains, thereby, a well-defined notion of "hyper-computability" based entirely on classical computational models and on standards of success that have long been regarded as natural in the empirical domain.
infinitary lambda calculus. in a previous paper we have established the theory of transfinite reduction for orthogonal term rewriting systems. in this paper we perform the same task for the lambda calculus. from the viewpoint of infinitary rewriting, the böhm model of the lambda calculus can be seen as an infinitary term model. in contrast to term rewriting, there are several different possible notions of infinite term, which give rise to different böhm-like models, which embody different notions of lazy or eager computation.
securing the .net programming model. the security of the .net programming model is studied from the standpoint of fully abstract compilation of c#. a number of failures of full abstraction are identified, and fixes described. the most serious problems have recently been fixed for version 2.0 of the .net common language runtime.
closure properties of linear context-free tree languages with an application to optimality theory. context-free tree grammars, originally introduced by rounds [math. systems theory 4(3) (1970) 257-287], are powerful grammar devices for the definition of tree languages. the properties of the class of context-free tree languages have been studied for more than three decades now. particularly important here is the work by engelfriet and schmidt [j. comput. system sci. 15(3) (1977) 328-353, 16(1) (1978) 67-99]. in the present paper, we consider a subclass of the class of context-free tree languages, namely the class of linear context-free tree languages. a context-free tree grammar is linear, if no rule permits the copying of subtrees. for this class of linear context-free tree languages we show that the grammar derivation mode, which is very important for the general class of context-free tree languages, is immaterial. the main result we present is the closure of the class of linear context-free tree languages under linear frontier-to-root tree transduction mappings. two further results are the closure of this class under linear root-to-frontier tree transduction mappings and under intersection with regular tree languages.the results of the first part of the paper are applied to the formalisation of optimality theory. optimality theory (ot), introduced by prince and smolensky [tech. report 1993], is a linguistic framework in which the mapping of one level of linguistic representation to another is based on rules and filters. the rules generate candidate expressions in the target representation, which are subsequently checked against the filters, so that only those candidates remain that survive this filtering process. a proposal to formalise the description of ot using formal language theory and in particular automata theory was presented by karttunen [proceedings of international workshop on finite-state methods in natural language processing, 1998, pp. 1-12] and frank and satta [comput. linguistics 24 (1998) 307-315]. the main result of these papers is that if the generator is defined as a finite-state string transducer and the filters are defined by finite-state string automata, then the whole ot-system can be defined by means of a finite-state string transducer. considering the fact that most parts of linguistics have trees as their underlying data structures instead of strings, we show here that generators can be extended to linear frontier-to-root tree transducers on linear context-free tree languages--with constraints being regular tree languages--while the computation of optimal candidates can still be performed using finite-state techniques (over trees).
harmonic buffer management policy for shared memory switches. in this paper we consider shared-memory switches. we introduce a novel general nonpreemptive buffer management scheme, which considers the queues ordered by their size. we propose a new scheduling policy, based on our general scheme, which we call the harmonic policy. we analyze the performance of the harmonic policy by means of competitive analysis and demonstrate that its throughput competitive ratio is at most ln(n) + 2, where n is the number of output ports. we also present a lower bound of ω(log n/log log n) on the performance of any online deterministic policy. our simulations also show that the harmonic policy achieves high throughput and easily adapts to changing load conditions.
a compositional approach to ctl* verification. the paper presents a compositional approach to the verification of ctl* properties over reactive systems. both symbolic model-checking (smc) and deductive verification are considered. both methods are based on two decomposition principles. a general state formula is decomposed into basic state formulas which are ctl* formulas with no embedded path quantifiers. to deal with arbitrary basic state formulas, we introduce another reduction principle which replaces each basic path formula, i.e., path formulas whose principal operator is temporal and which contain no embedded temporal operators or path quantifiers, by a newly introduced boolean variable which is added to the system. thus, both the algorithmic and the deductive methods are based on two statification transformations which successively replace temporal formulas by assertions which contain no path quantifiers or temporal operators. performing these decompositions repeatedly, we remain with basic assertional formulas, i.e., formulas of the form efp and afp for some assertion p. in the model-checking method we present a single symbolic algorithm to verify both universal and existential basic assertional properties. in the deductive method we present a small set of proof rules and show that this set is sound and relatively complete for verifying universal and existential basic assertional properties over reactive systems. together with two proof rules for the decompositions, we obtain a sound and relatively complete proof system for arbitrary ctl* properties. interestingly, the deductive approach for ctl* presented here, offers a viable new approach to the deductive verification of arbitrary ltl formulas.
principality and type inference for intersection types using expansion variables. principality of typings is the property that for each typable term, there is a typing from which all other typings are obtained via some set of operations. type inference is the problem of finding a typing for a given term, if possible. we define an intersection type system which has principal typings and types exactly the strongly normalizable λ-terms. more interestingly, every finite-rank restriction of this system (using leivant's first notion of rank) has principal typings and also has decidable type inference. this is in contrast to system f where the finite rank restriction for every finite rank at 3 and above has neither principal typings nor decidable type inference. furthermore, the notion of principal typings for our system involves only one operation, substitution, rather than several operations (not all substitution-based) as in earlier presentations of principality for intersection types (without rank restrictions). in our system the earlier notion of expansion is integrated in the form of expansion variables, which are subject to substitution as are ordinary variables. a unification-based type inference algorithm is presented using a new form of unification, β-unification.
on the longest perpetual reductions in orthogonal expression reduction systems. we study perpetual reductions in orthogonal (or conflict-free) fully extended expression reduction systems (oers). ers is a formalism for rewriting that subsumes term rewriting systems (trss) and the &lgr;-calculus. we design a strategy that, for any given term t in a fully extended oers, constructs a longest reduction starting from t if t is strongly normalizing and otherwise constructs an infinite reduction. we call this strategy a limit strategy. for a large class of oerss a limit strategy is computable. the conservation theorem for fully extended oerss follows easily from the properties of the strategy. we develop a method for computing the lengths of longest developments in oerss. copyright 2001 elsevier science b.v.
relating conflict-free stable transition and event models via redex families. we describe an event-style (or poset) semantics for conflict-free rewrite systems, including term and graph rewriting (possibly with bound variables), the λ-calculus, and other stable transition systems with a residual relation. our interpretation is based on considering redex-families as events. it treats permutation-equivalent reductions as representing the same concurrent computation. due to erasure of redexes, event structures are inadequate for such an interpretation. we therefore extend the prime event structure model in two different but equivalent ways: by axiomatizing permutation-equivalence on finite configurations, and by axiomatizing the erasure of events, for the conflict-free case, and show that these extended models are equivalent to stable transition models with axiomatized residual and family relations. we then construct finitary prime algebraic domains from the set of configurations in these extended models by defining orderings relative to stable sets of 'results'. all useful sets of results for which the normalization (by neededness) theorem can be proved are stable.
the conflict-free reduction geometry. we investigate mutual dependencies of subexpressions of computable expressions in orthogonal rewrite systems, and identify conditions for their independent concurrent computation. to this end, we introduce concepts familiar from ordinary euclidean geometry (such as basis, projection, distance, etc.) for reduction spaces. we show how a basis at an expression can be constructed so that any reduction starting from that expression can be decomposed as the sum of its projections on the axes of the basis. to make the concepts computationally more relevant, we relativize them w.r.t. stable sets of results (such as the set of normal forms, head-normal forms, and weak-head-normal forms, in the λ-calculus), and show that an optimal concurrent computation of an expression w.r.t. s consists of optimal computations of its s-independent subexpressions. all these results are obtained in the framework of deterministic family structures, which are abstract reduction systems with axiomatized residual and family relations on redexes, that model all orthogonal rewrite systems.
parameterized complexity of finding subgraphs with hereditary properties. we consider the parameterized complexity of the following problem under the framework introduced by downey and fellows: given a graph g, an integer parameter k and a nontrivial hereditary property ii, are there k vertices of g that induce a subgraph with property ii? this problem has been proved np-hard by lewis and yannakakis. we show that if ii includes all trivial graphs but not all complete graphs or vice versa, then the problem is complete for the parameterized class w[1] and is fixed parameter tractable otherwise. our proofs of both the tractability and hardness involve nontrivial use of the theory of ramsey numbers.
on algebraic and logical specifications of classes of regular languages. the paper studies classes of regular languages based on algebraic constraints imposed on transitions of automata and discusses issues related to specifications of these classes from algebraic, computational and logical points of view.
collage system: a unifying framework for compressed pattern matching. we introduce a general framework which is suitable to capture the essence of compressed pattern matching according to various dictionary-based compressions. it is a formal system to represent a string by a pair of dictionary d and sequence s of phrases in d. the basic operations are concatenation, truncation, and repetition. we also propose a compressed pattern matching algorithm for the framework. the goal is to find all occurrences of a pattern in a text without decompression, which is one of the most active topics in string matching. our framework includes such compression methods as lempel-ziv family (lz77, lzss, lz78, lzw), re-pair, sequitur, and the static dictionary-based method. the proposed algorithm runs in o((||d|| + |s|)- height(d) + m2 + r) time with o(||d|| + m2) space, where ||d|| is the size of d, |s| is the number of tokens in s, height(d) is the maximum dependency of tokens in d, m is the pattern length, and r is the number of pattern occurrences. for a subclass of the framework that contains no truncation, the time complexity is o(||d|| + |s| + m2 + r).
hypercomputation with quantum adiabatic processes. despite the recursive non-computability of hilbert's tenth problem, we outline and argue for a quantum algorithm that is based on the quantum adiabatic theorem. it is explained how this algorithm can solve hilbert's tenth problem. the algorithm is then considered in the context of several "no-go" arguments against such hypercomputation. logical arguments are usually based on cantor's diagonal technique used for proving non-computability of the turing halting problem, which is related to hilbert's tenth problem. physical arguments are related to the limited computability of a class of quantum computation based on qubits and dimensionally finite quantum logical gates.
scheduling broadcasts with deadlines. we investigate the problem of scheduling broadcasts in data delivering systems via broadcast, where a number of requests from several clients can be simultaneously satisfied by one broadcast of a server. most of prior work has focused on minimizing the total flow time of requests. it assumes that once a request arrives, it will be held until satisfied. in this paper, we are concerned with the situation that clients may leave the system if their requests are still unsatisfied after waiting for some time, that is, each request has a deadline. the problem of maximizing the throughput, for example, the total number of satisfied requests, is developed, and there are given online algorithms achieving constant competitive ratios.
generalizations of suffix arrays to multi-dimensional matrices. we propose multi-dimensional index data structures that generalize suffix arrays to square matrices and cubic matrices. giancarlo proposed a two-dimensional index data structure, the lsuffix tree, that generalizes suffix trees to square matrices. however, the construction algorithm for lsuffix trees maintains complicated data structures and uses a large amount of space. we present simple construction algorithms for multi-dimensional suffix arrays by applying a new partitioning technique to lexicographic sorting. our contributions are the first efficient algorithms for constructing two-dimensional and three-dimensional suffix arrays directly.
generalizations of suffix arrays to multi-dimensional matrices. we propose multi-dimensional index data structures that generalize suffix arrays to square matrices and cubic matrices. giancarlo proposed a two-dimensional index data structure, the lsuffix tree, that generalizes suffix trees to square matrices. however, the construction algorithm for lsuffix trees maintains complicated data structures and uses a large amount of space. we present simple construction algorithms for multi-dimensional suffix arrays by applying a new partitioning technique to lexicographic sorting. our contributions are the first efficient algorithms for constructing two-dimensional and three-dimensional suffix arrays directly.
online paging and file caching with expiration times. we consider a paging problem in which each page is assigned an expiration time at the time it is brought into the cache. the expiration time indicates the latest time that the fetched copy of the page may be used. requests that occur later than the expiration time must be satisfied by bringing a new copy of the page into the cache. the problem has applications in caching of documents on the world wide web (www). we show that a natural extension of the well-studied least recently used (lru) paging algorithm is strongly competitive for the uniform retrieval cost, uniform size case. we then describe a similar extension of the recently proposed landlord algorithm for the case of arbitrary retrieval costs and sizes, and prove that it is strongly competitive. the results extend to the loose model of competitiveness as well. copyright 2001 elsevier science b.v.
upper bounds for sorting integers on random access machines. two models of random access machines suitable for sorting integers are presented. our main results show that i) a ram with addition, subtraction, multiplication, and integer division can sort $n$ integers in the range $[0,2^{cn}]$ in $o(n \log c + n)$ steps; ii) a ram with addition, subtraction, and left and right shifts can sort any $n$ integers in linear time; iii) a ram with addition, subtraction, and left and right shifts can sort $n$ integers in the range $[0,n^{c}]$ in $o(n \log c + n)$ steps, where all intermediate results are bounded in value by the largest input.
two techniques in the area of the star problem in trace monoids. this paper deals with decision problems related to the star problem in trace monoids which means to determine whether the iteration of a recognizable trace language is recognizable. due to a theorem by richomme (in: i. privara et al. (eds.), mfcs'94 proc., lecture notes in computer science, vol. 841, springer, berlin, 1994, pp. 577-586), we know that the star problem is decidable in trace monoids which do not contain a submonoid of the form {a,c}* × {b,d}*. [cf. theory comput. systems 34(3) (2001) 193-227].here, we consider a more general problem: is it decidable whether for some recognizable trace language r and some recognizable or finite trace language p the intersection r ∩ p* is recognizable? if p is recognizable, then we show that this problem is decidable iff the underlying trace monoid does not contain a submonoid of the form {a, c}* × b*. in the case of finite languages p, this problem is decidable in {a,c}* × b* but undecidable in {a,c}* × {b,d}*.
segmental partially ordered generalized patterns. we continue the study of partially ordered generalized patterns (pogps) considered in [e. babson, e. steingrímsson, generalized permutation patterns and a classification of the mahonian statistics, séminaire lotharingien de combinatoire, 2000, b44b:18pp] for permutations and in [a. burstein, t. mansour, words restricted by patterns with at most 2 distinct letters, electron. j. combin. 9 (2) (2002) #r3] for words. we deal with segmental pogps (spogps). we state some general results and treat a number of patterns of length 4. we prove a result from [s. kitaev, multi-avoidance of generalized patterns, discrete math. 260 (2003) 89-100] in a much simpler way and also establish a connection between spogps and walks on lattice points starting from the origin and remaining in the positive quadrant. we give a combinatorial interpretation of the powers of the (generalized) fibonacci numbers. the entire distribution of the maximum number of non-overlapping occurrences of a generalized pattern with no dashes in permutations or words studied in [s. kitaev, partially ordered generalized patterns, discrete math. to appear, s. kitaev, t. mansour, partially ordered generalized patterns and k-ary words, ann. combin. 7 (2003) 191-200], respectively, has its counterpart in case of spogps.
smoothness prior approach to explore mean structure in large-scale time series. this article is addressed to the problem of modeling and exploring mean value structure of large-scale time series data and time-space data. a smoothness prior modeling approach (smoothness prior analysis of time series, lecture notes in statistics, vol. 116, springer, new york, 1996.) is taken. in this approach, the observed series are decomposed into several components each of which are expressed by smoothness priors models. in the analysis of pos and gps data, various useful information were extracted by this decomposition, and result in discoveries in these areas.
algebraic testing and weight distributions of codes. we study the testing problem, that is, the problem of determining (maybe probabilistically) if a function to which one has oracle access satisfies a given property.we propose a framework in which to formulate and carry out the analysis of several known tests. this framework establishes a connection between testing and the theory of weight distributions of codes. we illustrate this connection by giving a coding theoretic interpretation of several tests that fall under the label of low-degree tests. we also show how the connection naturally suggests a new way of testing for linearity over finite fields.we derive from the macwilliams theorems a general result, the duality testing lemma, and use it to analyze the simpler tests that fall into our framework. in contrast to other analyses of tests, the ones we present elicit the fact that a test's probability of rejecting a fuction depends on how far away the function is from every function that satisfies the property of interest.
the chilean highway problem. we consider the problem faced by a server offering multiple services with adversarial service request sequences. the server may offer a single service at a time and suffers a fixed latency whenever it switches the type of offered service. this problem captures realistic features of traffic and packet routing on network components such as multiplexers. we state the problem as a packet routing problem on bounded size buffer networks and then examine the crucial issue of stability--under what conditions will the number of unserviced requests remain bounded as the system runs for an arbitrarily long period of time? we obtain a tight characterization in terms of a natural packet density criterion for star networks with bounded buffer size.
on floyd and rivest's select algorithm. we show that several versions of floyd and rivest's algorithm select for finding the kth smallest of n elements require at most n + min{k, n - k} + o (n) comparisons on average and with high probability. this rectifies the analysis of floyd and rivest, and extends it to the case of nondistinct elements. our computational results confirm that select may be the best algorithm in practice.
shallow grates. this note proves the existence of acyclic directed graphs of logarithmic depth, such that a superlinear number of input-output pairs remain connected after the removal of any sufficiently small linearly sized subset of the vertices. the technique can be used to prove the analogous, and asymptotically optimal, result for graphs of arbitrary depth, generalizing schnitger''s grate construction for graphs large depth. interest in this question relates to efforts to use graph theoretic methods to prove circuit complexity lower bounds for algebraic problems such as matrix multiplication. in particular, it establishes the optimality of valiant''s depth reduction technique as a method of reducing the number of connected input-output pairs. the proof uses schnitger''s grate construction, but also involves a lemma on expanding graphs which may be of independent interest.
on the least exponential growth admitting uncountably many closed permutation classes. we show that the least exponential growth of counting functions which admits uncountably many closed permutation classes lies between 2n and (2.33529...)n.
deterministic turing machines in the range between real-time and linear-time. deterministic k-tape and multitape turing machines with one-way, two-way and without a separated input tape are considered. we investigate the classes of languages acceptable by such devices with time bounds of the form n + r(n), where r ∈ o(n) is a sublinear function. it is shown that there exist infinite time hierarchies of separated complexity classes in that range. for these classes weak closure properties are proved.
fast one-way cellular automata. space-bounded one-way cellular language acceptors (oca) are investigated. the only inclusion known to be strict in their time hierarchy from real-time to exponential-time is between real-time and linear-time! we show the surprising result that there exists an infinite hierarchy of properly included oca-language families in that range. a generalization of a method in terrier (theoret. comput. sci. 156 (1-2) (1996) 281) is shown which provides a tool for proving that languages are not acceptable by ocas with small time bounds. the hierarchies are established by such a language and a translation result. in addition, a notion of constructibility for cas is introduced, along with some of its properties. we prove several closure properties of the families in the hierarchy.
verified bytecode verifiers. using the theorem prover isabelle/hol we have formalized and proved correct and executable bytecode verifier in the style of kildall's algorithm for a significant subset of the java virtual machine (jvm). first an abstract framework for proving correctness of data flow based type inference algorithms for assembly languages is formalized. it is shown that under certain conditions kildall's algorithm yields a correct bytecode verifier. then the framework is instantiated with our previous work about the jvm. finally, we demonstrate the flexibility of the framework by extending our previous jvm model and the executable bytecode verifier with object initialization.
a tight upper bound for the path length of avl trees. we prove that the internal path length of an avl tree of size $n$ is bounded from above by 1.4404n(\log_2 n-\log_2\log_2 n)+o(n) and show that this bound is achieved by an infinite family of avl trees. but avl trees of maximal height do not have maximal path length. these results carry over to the comparison cost of brother trees.
a ptas for the minimization of polynomials of fixed degree over the simplex. we consider the problem of computing the minimum value pmin taken by a polynomial p(x) of degree d over the standard simplex δ. this is an np-hard problem already for degree d = 2. for any integer k ≥ 1, by minimizing p(x) over the set of rational points in δ with denominator k, one obtains a hierarchy of upper bounds pδ(k) converging to pmin as k → ∞. these upper approximations are intimately linked to a hierarchy of lower bounds for pmin constructed via pólya's theorem about representations of positive forms on the simplex. revisiting the proof of pólya's theorem allows us to give estimates on the quality of these upper and lower approximations for pmin. moreover, we show that the bounds pδ(k) yield a polynomial time approximation scheme for the minimization of polynomials of fixed degree d on the simplex, extending an earlier result of bomze and de klerk for degree d = 2.
deciding unambiguity and sequentiality from a finitely ambiguous max-plus automaton. finite automata with weights in the max-plus semiring are considered. the main result is: it is decidable whether a series that is recognized by a finitely ambiguous max-plus automaton is unambiguous, or is sequential. furthermore, the proof is constructive. a collection of examples is given to illustrate the hierarchy of max-plus series with respect to ambiguity.
specification and refinement of mobile systems in mtla and mobile uml. we define the spatio-temporal logic mtla as an extension of lamport's temporal logic of actions tla for the specification, verification, and formal development of systems that rely on mobile code. the formalism is validated by an encoding of models written in the mobile uml notation. we identify refinement principles for mobile systems and justify refinements of mobile uml state machines with the help of the mtla semantics.
the height of a binary search tree: the limiting distribution perspective. we study the height of the binary search tree--the most fundamental data structure used for searching. we assume that the binary search tree is built from a random permutation of n elements. under this assumption, we study the limiting distribution of the height as n → ∞. we show that the distribution has six asymptotic regions (scales). these correspond to different ranges of k and n, where pr{hn ≤ k} is the height distribution. in the critical region (the so-called central region), where most of the probability mass is concentrated, the limiting distribution satisfies a non-linear integral equation. while we cannot solve this equation exactly, we show that both tails of the distribution are roughly of a double exponential form. from our analysis, we conclude that the average height e[hn] ∼ a log n - 3/2[a/(a-1)]log log n, where a = 4.311 ... is the unique solution of x logx - x - xlog2 + 1 = 0, x > 1, while the variance var[hn] = o(1). the second term in the expansion of e[{kn] and the rate of growth of the variance were also recently obtained by b. reed who used probabilistic arguments, while m. drmota established the growth of the variance by analytic methods. our analysis makes certain assumptions about the forms of some asymptotic expansions, as well as their asymptotic matching.
multiple splicing systems and the universal computability. we propose a new extension of splicing systems, called multiple splicing systems, based on a kind of logic grammars. first, we introduce a class of elementary formal systems, called simple h-form efs, and show that its generative power is equivalent to the class of basic splicing systems (the original head's splicing system) and is more adequate as representation device for formal languages. next, we gradually extend the simple class of efss and get a very natural extension of splicing systems, multiple splicing systems. we show that multiple splicing systems have universal computability.
the complexity of learning concept classes with polynomial general dimension. the general dimension is a combinatorial measure that characterizes the number of queries needed to learn a concept class. we use this notion to show that any p-evaluatable concept class with polynomial query complexity can be learned in polynomial time with the help of an oracle in the polynomial hierarchy, where the complexity of the required oracle depends on the query-types used by the learning algorithm. in particular, we show that for subset and superset queries an oracle in σ3p suffices. since the concept class of dnf formulas has polynomial query complexity with respect to subset and superset queries with dnf formulas as hypotheses, it follows that dnf formulas are properly learnable in polynomial time with subset and superset queries and the help of an oracle in σ3p. we also show that the required oracle in our main theorem cannot be replaced by an oracle in a lower level of the polynomial-time hierarchy, unless the hierarchy collapses.
list version of (, )-labelings. let g = (v, e) be a simple graph, and for all v ∈ v, let l(v) be a list of colors assigned to v. we shall assume throughout that the colors are natural numbers. for nonnegative integers d, s, define χd,sl (g) to be the smallest integer k such that for every list assignment with |l(v)| = k for all v ∈ v one can choose a color c(v) ∈ l(v) for every vertex in such a way that |c(v) - c(w)| ≥ d for all vw ∈ e and |c(v) - c(w)| ≥ s for all pairs v, w of vertices having distance 2 in g. for a given list assignment such a coloring c is called an l(d, s)-list labeling.we prove a general bound for χd,sl (g) depending on the maximum degree of g. furthermore, we study this parameter for trees, and also for the particular classes of paths and stars. polynomial algorithms are designed for deciding whether a given list assignment admits an l(d, s)-list labeling on paths (for a given s unrestricted) and on trees (for s = 1).
proof assistance for real-time systems using an interactive theorem prover. this paper discusses the adaptation of the pvs theorem prover for performing analysis of real-time systems written in the astral formal specification language. several issues arose during the encoding of astral that are relevant to the encoding of many real-time specification languages such as encoding formulas as types, handling partial functions, dealing with noninterleaved concurrency, and defining irregular operators. these issues and possible solutions are presented as well as how they were handled in the astral encoding. a translator was written that translates any astral specification into its corresponding pvs encoding. after performing the proofs of several systems using their translations, pvs strategies were developed to automate the proofs of certain types of properties. in particular, strategies are presented for fully automating the proofs of certain classes of untimed properties. in addition, strategies were developed for partially automating the derivation of timed executions using transition steps. the encoding was used as the basis for a fully automated transition sequence generator tool, which has a wide variety of applications.
an operational and denotational approach to non-context-freeness. the main result of this paper is a description of linguistically motivated non-context-free phenomena equivalently in terms of regular tree languages (to express the recursive properties) and both a logical and an operational perspective (to establish the intended linguistic relations). the result is exemplified with a particular non-context-free phenomenon, namely cross-serial dependencies in natural languages such as swiss german or dutch. the logical description is specified in terms of binary monadic second-order (mso) formulas and the operational description is achieved by means of a linear and non-deleting macro tree transducer. besides giving a grammatical presentation for the regular tree language we shall also specify an implementation in the form of a finite-state (tree) automaton to emphasize the effectivity of our approach.
approximation algorithms for minimizing the total weighted tardiness on a single machine. given a single machine and a set of jobs with due dates, the classical np-hard problem of scheduling to minimize total tardiness is a well-understood one. lawler gave a fully polynomial-time approximation scheme (fptas) for it some 20 years ago. if the jobs have positive weights the problem of minimizing total weighted tardiness seems to be considerably more intricate, it. in this paper, we give some of the first approximation algorithms for it. we examine first the weighted problem with a fixed number of due dates and we design a pseudopolynomial algorithm for it. we show how to transform the pseudopolynomial algorithm to an fptas for the case where the weights are polynomially bounded.for the case with an arbitrary number of due dates and polynomially bounded processing times, we provide a quasipolynomial algorithm which produces a schedule whose value has an additive error proportional to the weighted sum of the due dates. we also investigate the performance of algorithms for minimizing the related total weighted late work objective.
finding approximate repetitions under hamming distance. the problem of computing periodicities with k possible mismatches is studied. two main definitions are considered, and for both of them an o(nk logk + s) algorithm is proposed (n the word length and s the size of the output). this improves, in particular, the bound obtained by g. landan and j. schmidt in 1993 (proceedings of the fourth annual symposium on combinatorial pattern matching, lecture notes in computer science, vol. 684, springer, berlin, padova, italy, pp. 120-133). finally, other possible definitions are briefly analyzed.
real functions computable by finite automata using affine representations. this paper tries to classify the functions of type in → i (for some interval i ⊆ r) that can be exactly realized by a finite transducer. such a class of functions strongly depends on the choice of real number representation. this paper considers only the so-called affine representations where numbers are represented by infinite compositions of affine contracting functions on i. affine representations include the radix (e.g. decimal, signed binary) representations. the first result is that all piecewise affine functions of n variables with rational coefficients are computable by a finite transducer which uses the signed binary representation. the second and main result is that any function computable by a finite transducer using an affine representation is affine on any open connected subset of in on which it is continuously differentiable. this limitation theorem shows that the set of finitely computable functions is very restricted.
real functions incrementally computable by finite automata. this is an investigation into exact real number computation using the incremental approach of potts (ph.d. thesis, department of computing, imperial college, 1998), edalat and potts (electronic notes in computer science, vol. 6, elsevier science publishers, amsterdam, 2000), nielsen and kornerup (j. universal comput. sci. 1(7) (1995) 527), and vuillemin (ieee trans. on comput. 39(8) (1990) 1087) where numbers are represented as infinite streams of digits, each of which is a möbius transformation. the objective is to determine for each particular system of digits which functions r → r can be computed by a finite transducer and ultimately to search for the most finitely expressible möbius representations of real numbers. the main result is that locally such functions are either not continuously differentiable or equal to some möbius transformation. this is proved using elementary properties of finite transition graphs and möbius transformations. applying the results to the standard signed-digit representations, we can classify functions that are finitely computable in such a representation and are continuously differentiable everywhere except for finitely many points. they are exactly those functions whose graph is a fractured line connecting finitely many points with rational coordinates.
the khalimsky topologies are precisely those simply connected topologies on z whose connected sets include all 2n-connected sets but no (3n-1)-disconnected sets. we give a proof of the result stated in the title. here the concepts of 2n- and (3n- 1)- (dis)connected sets are the natural generalizations to zn of the standard concepts of 4- and 8-(dis)connected sets in 2d digital topology.suppose we have an n-dimensional scanner that digitizes n-dimensional objects to subsets of zn. we are interested in topological spaces (zn, τ) that might allow standard concepts and methods of general topology to be directly and usefully applied to good digitizations produced by the scanner. but our result suggests that if a topological space (zn, τ) is not a khalimsky space, then it will not satisfy our requirement.our proof involves some purely discrete arguments and a fact about simply connected polyhedra that is a well-known consequence of the simplicial approximation theorem, but also uses the following fact (which was one of the main results in an earlier paper (in: r.m. shortt (ed.), general topology and applications: proc. 1988 northeast conf., marcel dekker, new york, 1990, pp. 153-164) by the author and khalimsky): for any t0 topological space in which each point lies in a finite open set and a finite closed set there exists a polyhedron, whose vertices are in 1-1 correspondence with the points of the space, such that the homotopy classes of continuous maps into the topological space from any metric space are in 1-1 correspondence with the homotopy classes of continuous maps from that metric space into the polyhedron.
rasiowa-sikorski deduction systems in computer science applications. a rasiowa-sikorski system is a sequence-type formalization of logics. the system uses invertible decomposition rules which decompose a formula into sequences of simpler formulae whose validity is equivalent to validity of the original formula. there may also be expansion rules which close indecomposable sequences under certain properties of relations appearing in the formulae, like symmetry or transitivity. proofs are finite decomposition trees with leaves having "fundamental", valid labels. the author describes a general method of applying the rs formalism to develop complete deduction systems for various brands of c.s and a.i. logic, including a logic for reasoning about relative similarity, a three-valued software specification logic with mccarthy's connectives and kleene quantifiers, a logic for nondeterministic specifications, many-sorted fol with possibly empty carriers of some sorts, and a three-valued logic for reasoning about concurrency.
error-detecting properties of languages. the language property of error-detection ensures that the communications medium cannot transform a word of the language to another word of the language. in this paper we provide some insights on the notion of error-detection from a language theoretic point of view. we define certain error-detecting properties of languages and codes including the notion of error-detection with finite delay which is a natural extension of unique decodability with finite delay. we obtain results about the error-detecting capabilities of regular and other languages, and of known classes of codes. moreover, we consider the problem of estimating the optimal redundancy of infinite languages with the property of detecting errors of the deletion type.
uniquely decodable n-gram embeddings. we define the family of n-gram embeddings from strings over a finite alphabet into the semimodule nk. we classify all ξ ∈ nk that are valid images of strings under such embeddings, as well as all ξ whose inverse image consists of exactly 1 string (we call such ξ uniquely decodable). we prove that for a fixed alphabet, the set of all strings whose image is uniquely decodable is a regular language.
on-line scheduling with tight deadlines. this paper is concerned with the on-line problem of scheduling jobs with tight deadlines in a uni-processor system. it has been known for long that in such a setting, no on-line algorithm is 1-competitive (i.e., optimal) in the sense of matching the optimal off-line algorithm on the total value of jobs that meet the deadlines; indeed, no algorithm can be better than k-competitive, where k is the importance ratio of the jobs. recent work, however, reveals that the competitive ratio can be improved to a constant if the on-line scheduler is equipped with a processor o(1) times faster (j. acm 47(4) (2000) 617), and further to one when using a processor o(logk) times faster (proc. 12th ann. acm-siam symp. on discrete algorithms, 2001, p. 755). this paper presents a new on-line algorithm for scheduling jobs with tight deadlines and shows that it is 1-competitive when using a processor that is only o(1) times faster.
tilings of rectangles with t-tetrominoes. we prove that any two tilings of a rectangular region by t-tetrominoes are connected by moves involving only 2 and 4 tiles. we also show that the number of such tilings is an evaluation of the tutte polynomial. the results are extended to a more general class of regions.
choosing starting values for certain newton-raphson iterations. we aim at finding the best possible seed values when computing a1/p using the newton-raphson iteration in a given interval. a natural choice of the seed value would be the one that best approximates the expected result. it turns out that in most cases, the best seed value can be quite far from this natural choice. when we evaluate a monotone function f(a) in the interval [amin, amax], by building the sequence xn defined by the newton-raphson iteration, the natural choice consists in choosing x0 equal to the arithmetic mean of the endpoint values. this minimizes the maximum possible distance between x0 and f(a). and yet, if we perform n iterations, what matters is to minimize the maximum possible distance between xn and f(a). in several examples, the value of the best starting point varies rather significantly with the number of iterations.
tractable disjunctions of linear constraints: basic results and applications to temporal reasoning. we study the problems of deciding consistency and performing variable elimination for disjunctions of linear inequalities and disequations with at most one inequality per disjunction. this new class of constraints extends the class of generalized linear constraints originally studied by lassez and mcaloon. we show that deciding consistency of a set of constraints in this class can be done in polynomial time. we also present a variable elimination algorithm which is similar to fourier's algorithm for linear inequalities. finally, we use these results to provide new temporal reasoning algorithms for the ord-horn subclass of allen's interval formalism. we also show that there is no low level of local consistency that can guarantee global consistency for the ord-horn subclass. this property distinguishes the ord-horn subclass from the pointizable subclass (for which strong 5-consistency is sufficient to guarantee global consistency), and the continuous endpoint subclass (for which strong 3-consistency is sufficient to guarantee global consistency). copyright 2001. elsevier science b.v.
the cnn problem and other k-server variants. we study several interesting variants of the k-server problem. in the cnn problem, one server services requests in the euclidean plane. the difference from the k-server problem is that the server does not have to move to a request, but it has only to move to a point that lies in the same horizontal or vertical line with the request. this, for example, models the problem faced by a crew of a certain news network trying to shoot scenes on the streets of manhattan from a distance; for any event at an intersection, the crew has only to be on a matching street or avenue. the cnn problem contains as special cases two important problems: the bridge problem, also known as the cow-path problem, and the weighted 2-server problem in which the 2 servers may have different speeds. we show that any deterministic online algorithm has competitive ratio at least 6 + √17. we also show that some successful algorithms for the k-server problem fail to be competitive. in particular, no memoryless randomized algorithm can be competitive.we also consider another variant of the k-server problem, in which servers can move simultaneously, and we wish to minimize the time spent waiting for service. this is equivalent to the regular k-server problem under the l∞ norm for movement costs. we give a ½ k(k + 1) upper bound for the competitive ratio on trees.
time complexity of radio broadcasting: adaptiveness vs. obliviousness and randomization vs. determinism. we consider the time of broadcasting in ad hoc radio networks modeled as undirected graphs. in such networks, every node knows only its own label and a linear bound on the number of nodes but is unaware of the topology of the network, or even of its own neighborhood. our aim is to study to what extent the availability of two important characteristics of a broadcasting algorithm influences optimal broadcasting time. these characteristics are adaptiveness and randomization. our contribution is establishing upper and lower bounds on optimal broadcasting time for three classes of algorithms: adaptive deterministic, oblivious randomized and oblivious deterministic. in two cases we present tight bounds, and in one case a small gap remains. we show that for deterministic adaptive algorithms time ω(n) is required even for n-node networks of constant diameter. this lower bound is strongest possible, since linear time algorithms are known, and hence establishes optimal time θ(n) for this class. for oblivious randomized algorithms we show an upper bound o(n min{d, log n}) and a lower bound ω(n) on optimal expected broadcasting time in n-node networks of diameter d. finally, for oblivious deterministic algorithms we show matching upper and lower bounds θ(n min{d, √n}) on optimal broadcasting time. our results imply that enforcing obliviousness has at least as strong negative impact on broadcasting time as enforcing determinism, and that algorithms having both these features are strictly less efficient than those having only one of them.
partial algebras, meaning categories and algebraization. many approaches to natura language semantics are essentially model-theoretic, typically cast in type theoretic terms. many linguists have adopted type theory or many-sorted algebras [see h. hendriks, compositionality and model-theoretic interpretation, j. logic, language inform. 10 (2001) 29-48 and references therein]. however, recently hodges [formal features of compositionality, j. logic, language inform. 10 (2001) 7-28] has offered an approach to compositionality using just partial algebras. an approach in terms of partial algebras seems at the outset more justified, since the typing is often just artificially superimposed on language (and makes many words massively polymorphic). on the other hand, many-sorted algebras are easier to handle than partial algebras, and are therefore generally preferred. this paper investigates the dialectics between partial algebras and many-sorted algebras and tries to set the background for an approach in the spirit of hodges [formal features of compositionality, j. logic, language inform. 10 (2001) 7-28], which also incorporates insights from algebraic logic, in particular from blok and pigozzi [algebraizable logics, mem. amer. math. soc. 77 (396) (1990)]. the analytic methods that we shall develop here shall also be applied to combinatory algebras and algebraizations of predicate logic.
mixed hypergraphs with bounded degree: edge-coloring of mixed multigraphs. a mixed hypergraph h is a triple (v, c, d) where v is its vertex set and c and d are families of subsets of v (c-edges and d-edges). the degree of a vertex is the number of edges in which it is contained. a vertex coloring of h is proper if each c-edge contains two vertices with the same color and each d-edge contains two vertices with different colors. the feasible set of h is the set of all k's such that there exists a proper coloring using exactly k colors. the lower (upper) chromatic number of h is the minimum (maximum) number in the feasible set.we restrict our attention to mixed hypergraphs with maximum degree two; those with maximum degree three are not simpler than general ones. mixed hypergraphs with maximum degree two were suggested as an interesting subclass of mixed hypergraphs in voloshin (austral. j. combin. 11 (1995) 25-45). we prove that feasible sets of mixed hypergraphs with maximum degree two are intervals. we present a linear time algorithm for determining the lower chromatic number, a linear 5/3-approximation algorithm and a polynomial 3/2-approximation algorithm for the upper chromatic number. we prove that there is no ptas for the upper chromatic number unless p = np.
it is tough to be a plumber. in the linux computer game kplumber, the objective is to rotate tiles in a raster of squares so as to complete a system of pipes. we give a complexity classification for the original game and various special cases of it that arise from restricting the set of six possible tiles.most of the cases are np-complete. one polynomially solvable case is settled by formulating it as a perfect matching problem; other polynomial cases are settled by simple sweepline techniques. moreover, we show that all the unsettled cases are polynomial time equivalent.
approximate maxima finding of continuous functions under restricted budget. a function is distributed among nodes of a graph in a &ldquo;continuous&rdquo; (or &ldquo;slowly changing&rdquo;) way, i.e., such that the difference between values stored at adjacent nodes is small. the goal is to find a node of maximum value by probing some nodes under a restricted budget. every node has an associated cost which has to be paid for probing it and a probe reveals the value of the node. if the total budget is too small to allow probing every node, it is impossible to find the maximum value in the worst case. hence we seek an approximate maxima finding (amf) algorithm that offers the best worst-case guarantee g, i.e., for any continuous distribution of values it finds a node whose value differs from the maximum value by at most g. amf in graphs is related to a generalization of the multicenter problem and we get new results for this problem as well. for example, we give a polynomial algorithm to find a minimum cost solution for the multicenter problem on a tree, with arbitrary node costs. &mdash;authors' abstract
encoding hamiltonian circuits into multiplicative linear logic. we give a new proof of the np-completeness of multiplicative linear logic without constants by a direct encoding of the hamiltonian circuit decision problem.
the black-box complexity of nearest-neighbor search. we define a natural notion of efficiency for approximate nearest-neighbor (ann) search in general n-point metric spaces, namely the existence of a randomized algorithm which answers (1 + ε)-ann queries in polylog(n) time using only polynomial space. we then study which families of metric spaces admit efficient ann schemes in the black-box model, where only oracle access to the distance function is given, and any query consistent with the triangle inequality may be asked.for ε < 2/5, we offer a complete answer to this problem. using the notion of metric dimension defined in [a. gupta, et al., bounded geometries, fractals, and low-distortion embeddings, in: 44th annu. ieee symp. on foundations of computer science, 2003, pp. 534-543] (à la [p. assouad, plongements lipschitziens dans rn, bull. soc. math. france 111 (4) (1983) 429-448]), we show that a metric space x admits an efficient (1+ε)-ann scheme for any ε < 2/5 if and only if dim(x) = o(log log n). for coarser approximations, clearly the upper bound continues to hold, but there is a threshold at which our lower bound breaks down--this is precisely when points in the "ambient space" may begin to affect the complexity of "hard" subspaces s ⊆ x. indeed, we give examples which show that dim(x) does not characterize the black-box complexity of ann above the threshold.our scheme for ann in low-dimensional metric spaces is the first to yield efficient algorithms without relying on any additional assumptions on the input. in previous approaches (e.g., [k.l. clarkson, nearest neighbor queries in metric spaces, discrete comput. geom. 22(1) (1999) 63-93; d. karger, m. ruhl, finding nearest neighbors in growth-restricted metrics, in: 34th annu. acm symp. on the theory of computing, 2002, pp. 63-66; r. krauthgamer, j.r. lee, navigating nets: simple algorithms for proximity search, in: 15th annu. acm-siam symp. on discrete algorithms, 2004, pp. 791-801; k. hildrum, et al., a note on finding nearest neighbors in growth-restricted metrics, in: proc. of the 15th annu. acm-siam symp. on discrete algorithms, 2004, pp. 560-561]), even spaces with dim(x) = o(1) sometimes required ω(n) query times.
breaking des using p systems. membrane systems, also called p systems, were introduced by gh. paun, as a new class of biologically inspired distributed computing models. several variants of p systems were already shown to be computationally universal. one of these variants, introduced in gh. paun (j. automata languages combin. 6 (1) (2001) 75), is able to solve sat in linear time. in this paper, we show how this class of p systems (with membrane division) can theoretically break the most widely used cryptosystem, des. we prove that given an arbitrary (plain-text, cipher-text) pair, one can recover the des key in linear time with respect to the length of the key.
automatic synthesis of a subclass of schedulers in timed systems. in this article we present a synthesis technique for generating schedulers for real-time systems. the aim of the scheduler is to ensure (via restricting the general behaviour) that the real-time system satisfies the specification. the real-time system and the specification are described as alur-dill timed automata while the synthesised scheduler is a type of timed trajectory automaton. this allows us to perform the synthesis without incurring the cost of constructing timed regions. we also note a simple constraint that the specification has to satisfy for this technique to be useful.
on the computational complexity of imperative programming languages. two restricted imperative programming languages are considered: one is a slight modification of a loop language studied intensively in the literature, the other is a stack programming language over an arbitrary but fixed alphabet, supporting a suitable loop concept over stacks. the paper presents a purely syntactical method for analysing the impact of nesting loops on the running time. this gives rise to a uniform measure µ on both loop and stack programs, that is, a function that assigns to each such program p a natural number µ(p) computable from the syntax of p.it is shown that stack programs of µ-measure n compute exactly those functions computed by a turing machine whose running time lies in grzegorczyk class εn-2. in particular, stack programs of µ-measure 0 compute precisely the polynomial-time computable functions.furthermore, it is shown that loop programs of µ-measure n compute exactly the functions in εn-2. in particular, loop programs of µ-measure 0 compute precisely the linear-space computable functions.
effective simultaneous approximability of reals. the effective simultaneous approximability of real vectors and sets of reals is studied. a hierarchy of real vectors based on the kolmogorov complexity of computable approximations is constructed. we prove that the hierarchy is nontrivial at the bottom levels but collapses on the top levels. a hierarchy theorem which gives a simple test for proper inclusion between two classes is established. we also show that an effective approximation problem for a finite set may be hard (have no computable solutions) when the corresponding problems for all its proper subsets are simple (have computable solutions).
on the complexity of the reflected logic of proofs. artemov's propositional logic of proofs lp captures all invariant properties of proof predicates "t is a proof of f" which are represented in lp as formulas t: f. kuznets in [on the complexity of explicit modal logics, in: computer science logic 2000, lecture notes in computer science, vol. 1862, springer, berlin, 2000, pp. 371-383] showed that the satisfiability problem for lp belongs to the class π2p of the polynomial hierarchy. in this paper we consider the reflected logic of proofs, rlp, consisting of formulas t: f derivable in lp. the system rlp is as expressible as lp itself, since every f derivable in lp is represented in rlp by t: f for an appropriate proof term t. we prove a better upper bound (np) for the decision procedure in rlp. in addition we prove the disjunctive property for the original logic of proofs lp, thus answering a well-known question in this area.
referential logic of proofs. we introduce an extension of the propositional logic of single-conclusion proofs by the second-order variables denoting the reference constructors of the type "the formula which is proved by x." the resulting logic of proofs with references, flpref, is shown to be decidable, and to enjoy soundness and completeness with respect to the intended provability semantics. we show that flpref provides a complete test of admissibility of inference rules in a sound extension of arithmetic. this paper may be regarded as a contribution to the theory of automated reasoning systems.
efficient approximation algorithms for the achromatic number. the achromatic number problem is, given a graph g = (v, e), to find the greatest number of colors, ψ(g), in a coloring of the vertices of g such that adjacent vertices get distinct colors and for every pair of colors some vertex of the first color and some vertex of the second color are adjacent. this problem is np-complete even for trees. we obtain the following new results using combinatorial approaches to the problem. (1) a polynomial time o(|v|3/8)-approximation algorithm for the problem on graphs with girth at least six. (2) a polynomial time 2-approximation algorithm for the problem on trees. this is an improvement over the best previous 7-approximation algorithm. (3) a linear time asymptotic 1.414-approximation algorithm for the problem when graph g is a tree with maximum degree d(|v|), where d : n → n, such that d(|v|) = o(ψ(g)). for example, d(|v|) = θ(1) or d(|v|) = θ(log |v|). (4) a linear time asymptotic 1.118-approximation algorithm for binary trees. we also improve the lower bound on the achromatic number of binary trees.
reconstruction of convex 2d discrete sets in polynomial time. the reconstruction problem is considered in those classes of discrete sets where the reconstruction can be performed from two projections in polynomial time. the reconstruction algorithms and complexity results are summarized in the case of hv-convex sets, hv-convex 8-connected sets, hv-convex polyominoes, and directed h-convex sets. as new results some properties of the feet and spines of the hv-convex 8-connected sets are proven and it is shown that the spine of such a set can be determined from the projections in linear time. two algorithms are given to reconstruct hv-convex 8-connected sets. finally, it is shown that the directed h-convex sets are uniquely reconstructible with respect to their row and column sum vectors.
a sufficient condition for non-uniqueness in binary tomography with absorption. a new kind of discrete tomography problem is introduced: the reconstruction of discrete sets from their absorbed projections. a special case of this problem is discussed, namely, the uniqueness of the binary matrices with respect to their absorbed row and column sums when the absorption coefficient is µ = log((1 + √5)/2). it is proved that if a binary matrix contains a special structure of 0s and 1s, called alternatively corner-connected component, then this binary matrix is non-unique with respect to its absorbed row and column sums. since it has been proved in another paper [a. kuba, m. nivat, reconstruction of discrete sets with absorption, linear algebra appl. 339 (2001) 171-194] that this condition is also necessary, the existence of alternatively corner-connected component in a binary matrix gives a characterization of the non-uniqueness in this case of absorbed projections.
the complexity of bisimilarity-checking for one-counter processes. we study the problem of bisimilarity-checking between processes of one-counter automata and finite-state processes. we show that deciding weak bisimilarity between processes of one-counter nets (which are 'restricted' one-counter automata where the counter cannot be tested for zero) and finite-state processes is dp-hard. in particular, this means that the problem is both np and co-np hard. the same technique is used to demonstrate co-np-hardness of strong bisimilarity between processes of one-counter nets. then we design an algorithm which decides weak bisimilarity between processes of one-counter automata and finite-state processes in time which is polynomial for a large subclass of instances, giving a kind of characterization of all hard instances as a byproduct. moreover, we show how to efficiently estimate the time which is needed to solve a given instance. finally, we prove that the problem of strong bisimilarity between processes of one-counter automata and finite-state processes is in p.
weak bisimilarity between finite-state systems and bpa or normed bpp is decidable in polynomial time. we prove that weak bisimilarity is decidable in polynomial time between finite-state systems and several classes of infinite-state systems: context-free processes and normed basic parallel processes (normed bpp). to the best of our knowledge, these are the first polynomial algorithms for weak bisimilarity problems involving infinite-state systems.
data abstractions for decision tree induction. when descriptions of data values in a database are too concrete or too detailed, the computational complexity needed to discover useful knowledge from the database will be generally increased. furthermore, discovered knowledge tends to become complicated. a notion of data abstraction seems useful to resolve this kind of problems, as we obtain a smaller and more general database after the abstraction, from which we can quickly extract more abstract knowledge that is expected to be easier to understand. in general, however, since there exist several possible abstractions, we have to carefully select one according to which the original database is generalized. an inadequate selection would make the accuracy of extracted knowledge worse.from this point of view, we propose in this paper a method of selecting an appropriate abstraction from possible ones, assuming that our task is to construct a decision tree from a relational database. suppose that, for each attribute in a relational database, we have a class of possible abstractions for the attribute values. as an appropriate abstraction for each attribute, we prefer an abstraction such that, even after the abstraction, the distribution of target classes necessary to perform our classification task can be preserved within an acceptable error range given by user.by the selected abstractions, the original database can be transformed into a small generalized database written in abstract values. therefore, it would be expected that, from the generalized database, we can construct a decision tree whose size is much smaller than one constructed from the original database. furthermore, such a size reduction can be justified under some theoretical assumptions. the appropriateness of abstraction is precisely defined in terms of the standard information theory. therefore, we call our abstraction framework information theoretical abstraction.we show some experimental results obtained by a system ita that is an implementation of our abstraction method. from those results, it is verified that our method is very effective in reducing the size of detected decision tree without making classification errors so worse.
toward a theory of intelligence. in 1950, turing suggested that intelligent behavior might require "a departure from the completely disciplined behavior involved in computation", but nothing that a digital computer could not do. in this paper, i want to explore turing's suggestion by asking what it is, beyond computation, that intelligence might require, why it might require it and what knowing the answers to the first two questions might do to help us understand artificial and natural intelligence.
analysis of a multiobjective evolutionary algorithm on the 0-1 knapsack problem. multiobjective evolutionary algorithms (moeas) are increasingly being used for effectively solving many real-world problems, and many empirical results are available. however, theoretical analysis is limited to a few simple toy functions. in this work, we select the well-known knapsack problem for the analysis. the multiobjective knapsack problem in its general form is np-complete. moreover, the size of the set of pareto-optimal solutions can grow exponentially with the number of items in the knapsack. thus, we formalize a (1 + ε)-approximate set of the knapsack problem and attempt to present a rigorous running time analysis of a moea to obtain the formalized set. the algorithm used in the paper is based on a restricted mating pool with a separate archive to store the remaining population; we call the algorithm a restricted evolutionary multiobjective optimizer (remo). we also analyze the running time of remo on a special bi-objective linear function, known as lotz (leading ones : trailing zeros), whose pareto set is shown to be a subset of the knapsack. an extension of the analysis to the simple evolutionary multiobjective optimizer (semo) is also presented. a strategy based on partitioning of the decision space into fitness layers is used for the analysis.
the topology of mazurkiewicz traces. the present paper characterizes the topological structure of real traces. this is done in terms of graph-theoretic properties of the underlying (possibly infinite) dependence alphabet. the topological space of real traces is shown to be homeomorphic to the direct product of (at most) the full binary tree and the full countably branching tree and one higher-dimensional grid. the occurrence of each of these factors depends on the existence of finite non-trivial and of infinite connected components and on the number of isolated letters of the dependence alphabet.
undecidability of the trace coding problem and some decidable cases. we introduce and investigate the notion of weak morphisms of trace monoids with the aim of dealing with the problem of deciding the existence of codings between trace monoids. we prove that this problem is not recursively enumerable, which answers the question raised by ochmanski in 1988. on the other hand, we show its decidability when restricted to instances with domain monoids defined by acyclic dependence graphs. we also partially answer the question of diekert from 1990 about the number of free monoids needed for encoding a given trace monoid into their direct product.
regular solutions of language inequalities and well quasi-orders. by means of constructing suitable well quasi-orders of free monoids we prove that all maximal solutions of certain systems of language inequalities are regular. this way we deal with a wide class of systems of inequalities where all constants are languages recognized by finite simple semigroups. in a similar manner we also demonstrate that the largest solution of the inequality xk ⊆ lx is regular provided the language l is regular.
refinement calculus: a basis for translation validation, debugging and certification. in this paper, we show how refinement calculus provides a basis for translation validation of optimized programs written in high level languages. towards such a direction, we shall provide a generalized proof rule for establishing refinement of source and target programs for which one need not have to know the underlying program transformations. our method is supported by a semi-automatic tool that uses a theorem prover for validating the verification conditions. we further show that the translation validation infrastructure provides an effective basis for deriving semantic debuggers and illustrate the development of a simple debugger for optimized programs using this approach using prolog. a distinct advantage of semantic debugging is that it permits the user to change values at run-time only when the values are consistent with the underlying semantics.
partial quasi-metrics. in this article we introduce and investigate the concept of a partial quasi-metric and some of its applications. we show that many important constructions studied in matthews's theory of partial metrics can still be used successfully in this more general setting. in particular, we consider the bicompletion of the quasi-metric space that is associated with a partial quasi-metric space and study its applications in groups and bck-algebras.
on the yoneda completion of a quasi-metric space. several theories aimed at reconciling the partial order and the metric space approaches to domain theory have been presented in the literature (e.g. flagg and kopperman, theoret. comput. sci. 177 (1) (1997) 111-138; bonsangue et al., theoret. comput. sci. 193 (1998) 1-51; symth, quasi-uniformities: reconciling domains with metric spaces, lectures notes in computer science, vol. 298, springer, berlin, 1987, pp. 236-253; wagner, ph.d. thesis, carnegie mellon university, pittsburgh, july 1994, technical report cmu-cs-94-159). we focus in this paper on two of these approaches: the yoneda completion of generalized metric spaces of (bonsangue et al., theoret. comput. sci 193 (1998) 1-51) which finds its roots in work by lawvere (lawvere, rend. sem. mat. fis. milano 43 (1973) 135-166; cf. also wagner, ph.d. thesis, carnegie mellon university, pittsburgh, july 1994, technical report cmu-cs-94-159) and which is related to early work by stoltenberg (e.g. stoltenberg, proc. london. math. soc. (3) 17 (1967) 226-240; stoltenberg, proc. amer. math. soc. 18 (1967) 864-867 and ferrer and gregori, proc. london math. soc. (3) 49 (1984) 36), and the smyth completion (smyth, quasi-uniformities: reconciling domains with metric spaces, lecture notes in computer science, vol. 298, springer, berlin, 1987, pp. 236-253; smyth, in: g.m. reed, a.w. roscoe, r.f. wachter (eds.), topology and category theory in computer science, oxford university press, oxford, 1991, pp. 207-229; smyth, j. london math. soc. 49 (1994) 385-400; snderhauf, in: m. droste, y. gurevich (eds.), semantics of programming languages and model theory, algebra, logic and applications, vol. 5, gordon and breach, london, 1993, pp. 189-212; snderhauf, acta math. hungar. 69 (1995) 47-54). a net-version of the yoneda completion, complementing the net-version of the smyth completion (snderhauf, acta. math. hungar. 69 (1995) 47-54), is given and a comparison between the two types of completion is presented. the following open question is raised in bonsangue et al. (theoret. comput. sci. 193 (1998) 1-51): "an interesting question is to characterize the family of generalized metric spaces for which [the yoneda] completion is idempotent (it contains at least all ordinary metric spaces)". we show that the largest class of quasi-metric spaces idempotent under the yoneda completion is precisely the class of smyth-completabe spaces. a similar result has been obtained independently by flagg and snderhauf in flagg and snderhauf (preprint, available at: ftp://theory.doc.ic.ac.uk/theory/papers/sunderhauf/eicqf.ps). 2 we present an entirely new proof of the result via concrete standard techniques and compare this approach with the more abstract categorical machinery of flagg and snderhauf (preprint, available at: ftp://theory.doc.ic.ac.uk/theory/papers/sunderhauf/eicqf.ps). our proof is based on a new characterization of smyth-completability of quasi-metric spaces in terms of sequences, which considerably simplifies prior characterizations for quasi-uniform spaces (e.g. snderhauf, in: m. droste, y. gurevich (eds.), semantics of programming languages and model theory, algebra, logic and applications, vol. 5, gordon and breach, london, 1993, pp. 189-212; sunderhauf, acta math. hungar. 69 (1995) 715-720) we also show that the ideal completion, and hence the yoneda completion and the smyth completion, are not sequentially adequate in general. the study of the properties of total boundedness, precompactness, hereditary precompactness and compactness is motivated and we analyze the preservation of these properties under the two kinds of completion in the possible absence of idempotency.
on the complexity of queries in the logical data model. we investigate the complexity of query processing in the logical data model (ldm). we use two measures: data complexity, which is complexity with respect to the size of the data, and expression complexity, which is complexity with respect to the size of the expressions denoting the queries. our investigation shows that while the operations of product and union are essentially first-order operations, the power set operation is inherently a higher-order operation and is exponentially expensive. we define a hierarchy of queries based on the depth of nesting of power set operations and show that this hierarchy corresponds to a natural hierarchy of turing machines that run in multiply exponential time.
from complementation to certification. in the automata-theoretic approach to model checking we check the emptiness of the product of a system s with an automaton a-ψ for the complemented specification. this gives rise to two automata-theoretic problems: complementation of word automata, which is used in order to generate a-ψ, and the emptiness problem, to which model checking is reduced. both problems have numerous other applications, and have been extensively studied for nondeterministic büchi word automata (nbw). nondeterministic generalized büchi word automata (ngbw) have become popular in specification and verification and are now used in applications traditionally assigned to nbw. this is due to their richer acceptance condition, which leads to automata with fewer states and a simpler underlying structure.in this paper we analyze runs of ngbw and use the analysis in order to describe a new complementation construction and a symbolic emptiness algorithm for ngbw. the complementation construction exponentially improves the best known construction for ngbw and is easy to implement. the emptiness algorithm is almost identical to a known variant of the emerson-lei algorithm, and our contribution is the strong relation we draw between the complementation construction and the emptiness algorithm--both naturally follow from the analysis of the runs, which easily implies their correctness. this relation leads to a new certified model-checking procedure, where a positive answer to the model-checking query is accompanied by a certificate whose correctness can be checked by methods independent of the model checker. unlike certificates generated in previous works on certified model checking, our analysis enables us to generate a certificate that can be checked automatically and symbolically.
stone coalgebras. we argue that the category of stone spaces forms an interesting base category for coalgebras, in particular, if one considers the vietoris functor as an analogue to the power set functor on the category of sets.we prove that the so-called descriptive general frames, which play a fundamental role in the semantics of modal logics, can be seen as stone coalgebras in a natural way. this yields a duality between modal algebras and coalgebras for the vietoris functor.building on this idea, we introduce the notion of a vietoris polynomial functor over the category of stone spaces. for each such functor t we provide an adjunction between t-sorted boolean algebras with operators and the stone coalgebras for t. we also identify the subcategory of algebras on which the adjunction restricts to an equivalence and show that the final t-coalgebra is the dual of the initial t-bao.
towards a language theory for infinite n-free pomsets. n-free or series-parallel pomsets are a model for the behavior of modularly constructed concurrent systems. the investigation of recognizable languages of finite n-free pomsets was initiated by lodaya and weil who extended the theorems by kleene and by myhill and nerode on recognizable word languages to this setting. in this paper, we extend lodaya and weil's results in several aspects: (a) we consider the relation of recognizable sets to monadic second order logic in order to generalize büchi's theorem. (b) we prove our results (and extensions of results by lodaya and weil) for sets of infinite n-free pomsets. and (c), we investigate first-order axiomatizable, starfree, and aperiodic sets of infinite n-free pomsets and prove results in the spirit of mcnaughton and papert's and schützenberger's theorems for finite words.
on the descriptional power of heads, counters, and pebbles. we investigate the descriptional complexity of deterministic two-way k-head finite automata (k- dha). it is shown that between non-deterministic pushdown automata and any k-dha, k ≥ 2, there are savings in the size of description which cannot be bounded by any recursive function. the same is true for the other end of the hierarchy. such non-recursive trade-offs are also shown between any k-dha, k ≥ 1, and dspace(log) = multi-dha. we also address the particular case of unary languages. in general, it is possible that non-recursive trade-offs for arbitrary languages reduce to recursive trade-offs for unary languages. here we present huge lower bounds for the unary trade-offs between non-deterministic finite automata and any k-dha, k ≥ 2. furthermore, several known simulation results imply the presented trade-offs for other descriptional systems, e.g., deterministic two-way finite automata with k pebbles or with k linearly bounded counters.
the complexity of boolean matrix root computation. we show that finding roots of boolean matrices is an np-hard problem. this answers a 20 year old question from semigroup theory. interpreting boolean matrices as directed graphs, we further reveal a connection between boolean matrix roots and graph isomorphism, which leads to a proof that for a certain subclass of boolean matrices related to subdivision digraphs, root finding is of the same complexity as the graph-isomorphism problem.
conway's angel in three dimensions. the angel-devil game is an infinite game played on an infinite chess board: in each move the angel, a generalized chess king, jumps from his current square to some location at distance at most k, while his opponent, the devil, blocks squares trying to strand the angel. the angel wins if he manages to fly on forever. it is a long-standing open question whether some angel of sufficiently large power k can escape.we show that in the three-dimensional analog of the game the 13-angel can win. our proof is constructive and provides an explicit infinite escape strategy.
automatic verification of real-time systems with discrete probability distributions. we consider the timed automata model of alur and dill (theoret. comput. sci. 126 (1994) 183-235), which allows the analysis of real-time systems expressed in terms of quantitative timing constraints. traditional approaches to real-time system description express the model purely in terms of nondeterminism; however, it is often desirable to express the likelihood of the system making certain transitions. in this paper, we present a model for real-time systems augmented with discrete probability distributions. furthermore, two approaches to model checking are introduced for this model. the first uses the algorithm of baier and kwiatkowska (distributed comput. 11 (1998) 125-155) to provide a verification technique against temporal logic formulae which can refer both to timing properties and probabilities. the second, generally more efficient, technique concerns the verification of probabilistic, real-time reachability properties.
proving sequential function chart programs using timed automata. applications described by sequential function chart (sfc) often being critical, we have investigated the possibilities of program checking. in particular, physical time can be handled by sfc programs using temporizations, which is why we are interested in the quantitative temporal properties. we have proposed a modeling of sfc in timed automata, a formalism which takes time into account. in this modeling, we use the physical constraints of the environment. verification of properties can be carried out using the model-checker kronos. we apply this method to sfc programs of average size like that of the control part of the production cell korso. the size of the programs remains however a limit and we are studying the means of solving this problem. copyright 2001 elsevier science b.v.
a classification of plane and planar 2-trees. we present new functional equations for the species of plane and of planar (in the sense of harary and palmer, graphical enumeration, academic press, new york, 1973) 2-trees and some associated pointed species. we then deduce the explicit molecular expansion of these species, i.e. a classification of their structures according to their stabilizers. therein result explicit formulas in terms of catalan numbers for their associated generating series, including the asymmetry index series. this work is related to the enumeration of polyene hydrocarbons of molecular formula cnhn+2.
a strategy for searching with different access costs. let us consider an ordered set of keys a = {a1 > ... > an}, where the probability of searching ai is 1/n, for i = 1,..., n. if the cost of testing each key is similar, then the standard binary search is the strategy with minimum expected access cost. however, if the cost of testing ai is ci, for i = 1 .... , n, then the standard binary search is not necessarily the best strategy.in this paper, we prove that the expected access cost of an optimal search strategy is bounded above by 4cln(n + 1)/n, where c= σi=1n ci . furthermore, we show that this upper bound is asymptotically tight up to constant factors. the proof of this upper bound is constructive and generates a 4ln(n + 1)-approximated algorithm for constructing near-optimal search strategies. this algorithm runs in o(n2) time and requires o(n) space, which can be useful for practical cases, since the best known exact algorithm for this problem runs in o(n3) time and requires o(n2) space.
soft linear logic and polynomial time. we present a subsystem of second-order linear logic with restricted rules for exponentials so that proofs correspond to polynomial time algorithms, and vice versa.
phase semantics and decidability of elementary affine logic. light, elementary and soft linear logics are formal systems derived from linear logic, enjoying remarkable normalization properties. in this paper, we prove decidability of elementary affine logic, eal. the result is obtained by semantical means, first defining a class of phase models for eal and then proving soundness and (strong) completeness, following okada's technique. phase models for light affine logic and soft linear logic are also defined and shown complete.
strong rabin numbers of folded hypercubes. the strong rabin number of a network w of connectivity k is the minimum l so that for any k + 1 nodes s, d1, d2, ...,dk of w, there exist k node-disjoint paths from s to d1, d2, ..., dk, respectively, whose maximal length is not greater than l, where s ∉ {d1, d2, ...,dk} and d1, d2, ..., dk are not necessarily distinct. in this paper, we show that the strong rabin number of a k-dimensional folded hypercube is ⌈k/2⌉ + 1, where ⌈k/2⌉ is the diameter of the k-dimensional folded hypercube. each node-disjoint path we obtain has length not greater than the distance between the two end nodes plus two. this paper solves an open problem raised by liaw and chang.
game semantics and linear cps interpretation. we present a semantic analysis of the "linearly used continuation-passing interpretation" of functional languages, based on game semantics. this consists of a category of games with a coherence condition on moves--yielding a fully complete model of an affine-type theory--and a syntax-independent and full embedding of a category of hyland-ong/nickau-style "well-bracketed" games into it. we show that this embedding corresponds precisely to linear cps interpretation in its action on a games model of call-by-value pcf, yielding a proof of full abstraction for the associated translation. we discuss extensions of the semantics to deal with recursive types, call-by-name evaluation, nonlocal jumps, and state.
locally boolean domains. bistable bidomains have been used to give a simple order-theoretic construction of a cartesian closed category of sequential functions. in this paper, we investigate the intensional properties of a full subcategory, the locally boolean domains, in which the bistable structure is given by an involution operation. we show that every pointed locally boolean domain is the limit of an ω-chain of "prenex normal forms" constructed using only products and lifted sums. we use this result to describe a model of linear logic (incorporating both intuitionistic and polarized classical fragments). we show that affine and bistable functions correspond to unique "strategies" on the associated normal forms, and that function composition corresponds to "parallel composition plus hiding" of these strategies.
a calculus of coroutines. we describe a simple but expressive calculus of sequential processes, represented as coroutines. we show that this calculus can be used to express a variety of programming language features including procedure calls, labelled jumps, integer references and stacks. we describe the operational properties of the calculus using reduction rules and equational axioms.we describe a notion of categorical model for our calculus, and give a simple example of such a model based on a category of games and strategies. we prove full abstraction results showing that equivalence in the categorical model corresponds to observational equivalence in the calculus, and also to equivalence of evaluation trees, which are infinitary normal forms for the calculus.we show that our categorical model can be used to interpret the untyped λ-calculus and use this fact to extract a sound translation of the latter into our calculus of coroutines.
forcing numbers of stop signs. let g be a graph with a perfect matching m. the forcing number of m is the smallest number of edges in a subset s ⊂ m such that s is contained in no other perfect matching of g. we present methods for determining bounds on forcing numbers and apply these methods to find bounds for the forcing numbers of stop signs. a consequence of our main result is that every perfect matching of a stop sign of size (n,k) contains at least n disjoint alternating cycles.
on-line load balancing of temporary tasks revisited. we study load balancing problems of temporary jobs (i.e., jobs that arrive and depart at unpredictable time) in two different contexts, namely, machines and network paths. such problems are known as machine load balancing and virtual circuit routing in the literature. we present new on-line algorithms and improved lower bounds.
quantifier-free logic for nondeterministic theories. we develop a quantifier-free logic for deriving consequences of multialgebraic theories. multialgebras are used as models for nondeterminism in the context of algebraic specifications. they are many sorted algebras with set-valued operations. formulae are sequents over atoms allowing one to state set-inclusion or identity of 1-element sets (determinacy). we introduce a sound and weakly complete rasiowa-sikorski (r-s) logic for proving multialgebraic tautologies. we then extend this system for proving consequences of specifications based on translation of finite theories into logical formulae. finally, we show how such a translation may be avoided--introduction of the specific cut rules leads to a sound and strongly complete gentzen system for proving directly consequences of specifications. besides giving examples of the general techniques of r-s and the specific cut rules, we improve the earlier logics for multialgebras by providing means to handle empty carriers (as well as empty result-sets) without the use of quantifiers, and to derive consequences of theories without translation into another format and without using general cut.
a type system for jvm threads. the current definition of the java bytecode verifier, as well as the proposals to formalize it, does not include any check about the structured use of locks by monitorenter and monitorexit instructions. so code is run, even if critical sections are corrupted. in this paper, we isolate a sublanguage of the java virtual machine with thread creation and mutual exclusion. for this subset, we define a semantics and a formal verifier that enforces basic properties of threads and lock and unlock operations. the verifier integrates well with previous formalizations of the java bytecode verifier. our analysis of structured use of locks reveals the presence of bugs in the current compilers from sun, ibm and microsoft.
on the power of incremental learning. this paper provides a systematic study of incremental learning from noise-free and from noisy data. as usual, we distinguish between learning from positive data and learning from positive and negative data, synonymously called learning from text and learning from informant. our study relies on the notion of noisy data introduced by stephan.the basic scenario, named iterative learning, is as follows. in every learning stage, an algorithmic learner takes as input one element of an information sequence for some target concept and its previously made hypothesis and outputs a new hypothesis. the sequence of hypotheses has to converge to a hypothesis describing the target concept correctly.we study the following refinements of this basic scenario. bounded example-memory inference generalizes iterative inference by allowing an iterative learner to additionally store an a priori bounded number of carefully chosen data elements, while feedback learning generalizes it by allowing the iterative learner to additionally ask whether or not a particular data element did already appear in the input data seen so far.for the case of learning from noise-free data, we show that, when both positive and negative data are available, restrictions on the accessibility of the input data do not limit the learning capabilities if and only if the relevant iterative learners are allowed to query the history of the learning process or to store at least one carefully selected data element. this insight nicely contrasts the fact that, in case only positive data are available, restrictions on the accessibility of the input data seriously affect the learning capabilities of all versions of incremental learners.for the case of learning from noisy data, we present characterizations of all kinds of incremental learning in terms being independent from learning theory. the relevant conditions are purely structural ones. surprisingly, when learning from noisy text and noisy informant is concerned, even iterative learners are exactly as powerful as unconstrained learning devices.
variants of iterative learning. we investigate the principal learning capabilities of iterative learners in some more details. thereby, we confine ourselves to study the learnability of indexable concept classes. the general scenario of iterative learning is as follows. an iterative learner successively takes as input one element of a text (an informant) for a target concept as well as its previously made hypothesis and outputs a new hypothesis about the target concept. the sequence of hypotheses has to converge to a hypothesis correctly describing the target concept.we study two variants of this basic scenario and compare the learning capabilities of all resulting models of iterative learning to one another as well to the standard learning models finite inference, conservative identification, and learning in the limit.first, we consider the case that an iterative learner has to learn from fat texts (fat informants), only. in this setting, it is guaranteed that relevant information is, in principle, accessible at any time in the learning process. second, we study a variant of iterative learning, where an iterative learner is supposed to learn no matter which initial hypothesis is actually chosen. this variant is suited to describe scenarios that are typical for case-based reasoning.
advanced elementary formal systems. an elementary formal system (efs) is a logic program such as a prolog program, for instance, that directly manipulates strings. arikawa and his co-workers proposed elementary formal systems as a unifying framework for formal language learning.in the present paper, we introduce advanced elementary formal systems (aefss), i.e., elementary formal systems which allow for the use of a certain kind of negation, which is nonmonotonic, in essence, and which is conceptually close to negation as failure.we study the expressiveness of this approach by comparing certain aefs definable language classes to the levels in the chomsky hierarchy and to the language classes that are definable by efss that meet the same syntactical constraints.moreover, we investigate the learnability of the corresponding aefs definable language classes in two major learning paradigms, namely in gold's model of learning in the limit and valiant's model of probably approximately correct learning. in particular, we show which learnability results achieved for efss extend to aefss and which do not.
inductive inference of approximations for recursive concepts. this paper provides a systematic study of inductive inference of indexable concept classes in learning scenarios where the learner is successful if its final hypothesis describes a finite variant of the target concept, i.e., learning with anomalies. learning from positive data only and from both positive and negative data is distinguished.the following learning models are studied: learning in the limit, finite identification, set-driven learning, conservative inference, and behaviorally correct learning.the attention is focused on the case that the number of allowed anomalies is finite but not a priori bounded. however, results for the special case of learning with an a priori bounded number of anomalies are presented, too. characterizations of the learning models with anomalies in terms of finite tell-tale sets are provided. the observed varieties in the degree of recursiveness of the relevant tell-tale sets are already sufficient to quantify the differences in the corresponding learning models with anomalies. finally, a complete picture concerning the relations of all models of learning with and without anomalies mentioned above is derived.
decision lists over regular patterns. the paper introduces the notion of decision lists over regular patterns. this formalism provides a strict extension of regular erasing pattern languages and of containment decision lists.formal properties of the resulting language class, a subclass of the regular languages, are investigated. in particular, we show that decision lists over regular patterns have exactly the same expressive power as decision trees over regular patterns.moreover, we study the learnability of the resulting language class within different formal settings including gold's model of learning in the limit as well as valiant's model of approximately correct learning.
concurrency in timed automata. we introduce concurrent timed automata (ctas) where automata running in parallel are synchronized. we consider the subclasses of ctas obtained by admitting, or not, diagonal clock constraints and constant updates, and by letting, or not, sequential automata to update the same clocks. we prove that such subclasses recognize the same languages but differ w.r.t. the succinctness of the models. moreover, we distinguish between subclasses that are polynomially closed w.r.t. finite union and finite intersection, and subclasses that do not have such properties.
efficient timed model checking for discrete-time systems. we consider model checking of timed temporal formulae in durational transition graphs (dtgs), i.e., kripke structures where transitions have integer durations. two semantics for dtgs are presented and motivated. we consider timed versions ofctl where subscripts put quantitative constraints on the time it takes before a property is satisfied.we exhibit an important gap between logics where subscripts of the form "c" (exact duration) are allowed, and simpler logics that only allow subscripts of the form "≤ c" or " ≥ c" (bounded duration).without exact durations, model checking can be done in polynomial time, but with exact durations, it becomes δ2p-complete or pspace-complete depending on the considered semantics.
coalgebra morphisms subsume open maps. we relate two abstract notions of bisimulation, induced by open maps and by coalgebra morphisms, respectively. we show that open maps correspond to coalgebra morphisms for a suitable chosen endofunctor in a category of many sorted sets. this demonstrates that the notion of open-maps bisimilarity is of essentially coalgebraic nature. a central role in our development is played by a category of presheaves, which we show as corresponding to the subcategory of consistent coalgebras with lax cohomomorphisms.
decidability of performance equivalence for basic parallel processes. we study an extension of the class of basic parallel processes (bpp), in which actions are durational and urgent and parallel components have independent local clocks. the main result is decidability of strong bisimilarity, known also as performance equivalence, in this class. this extends the earlier decidability result for plain bpp by christensen et al. our decision procedure is based on decidability of the validity problem for presburger arithmetic. we prove also polynomial complexity in positive-duration fragment, thus properly extending a previous result by bérard et al. both ill-timed and well-timed semantics are treated.
identification of birfsa languages. the task of identifying a language from a set of its words is not an easy one. for instance, it is not feasible to identify regular languages in the general case. therefore, looking for subclasses of regular languages that can be identified in this framework is an interesting problem. one of the most classical identifiable classes is the class of reversible languages, introduced by d. angluin, also called bideterministic languages as they can be represented by deterministic automata (dfa) whose reverse is also deterministic. residual finite state automata (rfsa) on the other hand is a class of non-deterministic automata that shares some properties with dfa. in particular, dfa are rfsa and rfsa can be much smaller. we study here learnability of the class of languages that can be represented by birfsa: rfsa whose reverse are rfsa. we prove that this class is not identifiable in general but we present two subclasses that are learnable, the second one being identifiable in polynomial time.
type systems equivalent to data-flow analyses for imperative languages. we show that a large class of data-flow analyses for imperative languages are describable as type systems in the following technical sense: possible results of an analysis can be described in a language of types so that a program checks with a type if and only if this type is a supertype of the result of applying the analysis. type-checking is easy with the help of a certificate that records the "eureka"-bits of a typing derivation. certificate-assisted type-checking amounts to a form of lightweight analysis à la rose. for secure information flow, we obtain a type system that is considerably more precise than that of volpano et al., but not more sophisticated. importantly, our type systems are compositional.
equivalence of conservative, free, linear program schemas is decidable. a program schema defines a class of programs, all of which have identical statement structures, but whose expressions may differ. we prove that given any two structured schemas which are conservative, linear and free, it is decidable whether they are equivalent.
syntax vs. semantics: a polarized approach. we present a notion of sliced proof-nets for the polarized fragment of linear logic and a corresponding game model. we show that the connection between them is very strong through an equivalence of categories (this contains soundness, full completeness and faithful completeness).
asymptotic analysis of a leader election algorithm. itai and rodeh showed that, on the average, the communication of a leader election algorithm takes no more than ln bits, where l ≃ 2.441716 and n denotes the size of the ring. we give a precise asymptotic analysis of the average number of rounds m(n) required by the algorithm, proving for example that m(∞) := limn→∞ m(n) = 2.441715879..., where n is the number of starting candidates in the election. accurate asymptotic expressions of the second moment m(2)(n) of the discrete random variable at hand, its probability distribution, and the generalization to all moments are given. corresponding asymptotic expansions (n → ∞) are provided for sufficiently large j, where j counts the number of rounds. our numerical results show that all computations perfectly fit the observed values. finally, we investigate the generalization to probability t/n, where t is a non-negative real parameter. the real function m(∞, t) := limn →∞ m(n, t) is shown to admit one unique minimum m(∞, t) on the real segment (0, 2). furthermore, the variations of m(∞, t) on the whole real line are also studied in detail.
competitive analysis of incentive compatible on-line auctions. this paper studies auctions in a setting where the different bidders arrive at different times and the auction mechanism is required to make decisions about each bid as it is received. such settings occur in computerized auctions of computational resources as well as in other settings. we call such auctions, on-line auctions.we first characterize exactly on-line auctions that are incentive compatible, i.e. where rational bidders are always motivated to bid their true valuation. we then embark on a competitive worst-case analysis of incentive compatible on-line auctions. we obtain several results, the cleanest of which is an incentive compatible on-line auction for a large number of identical items. this auction has an optimal competitive ratio, both in terms of seller's revenue and in terms of the total social efficiency obtained.
idempotent analysis and continuous semilattices. in this survey article we give a brief overview of various aspects of the recently emerging field of idempotent analysis and suggest potential connections with domain theory.
riemann and edalat integration on domains. the main result of this paper is that the domain-theoretic approach to the generalized riemann integral first introduced by edalat extends to a large class of spaces that can be realized as the set of maximal points of domains.the approach is based on the theory of a riemann-stieltjes type integral on a topological space with respect to a finitely additive measure. we develop the theory of this integral for a bounded function f defined on the maximal points of a continuous domain and show that it gives an alternate approach to the edalat integral.
posets having continuous intervals. in this paper we consider posets in which each order interval [a, b] is a continuous poset or continuous domain. after developing some basic theory for such posets, we derive our major result: if x is a core compact space and l is a poset equipped with the scott topology (assumed to satisfy a mild extra condition) for which each interval is a continuous sup-semilattice, then the function space of continuous locally bounded functions from x into l has intervals that are continuous sup-semilattices. this substantially generalizes known results for continuous domains.
left and right adjoint operations on spaces and data types. formal theories of higher types need to be augmented to permit treatment of some additional right adjoints which arise in mathematical practice. the concomitant mathematical scrutiny of supposedly well-established left adjoints resurrects a "critique of foundations" which may not be irrelevant for practice. categorical methods based on mathematical experience with the diversity of toposes allow us to address such problems without getting entangled in sterile ontological debates.
close to optimal decentralized routing in long-range contact networks. in order to explain the ability of individuals to find short paths to route messages to an unknown destination, based only on their own local view of a social network (the small world phenomenon), kleinberg [the small-world phenomenon: an algorithmic perspective, proc. 32nd acm symp. on theory of computing, 2000, pp. 163-170] proposed a network model based on a d-dimensional lattice of size n augmented with k long-range directed links per node. individuals behavior is modeled by a greedy algorithm that, given a source and destination, forwards a message to the neighbor of the current holder, which is the closest to the destination. this algorithm computes paths of expected length θ(log2 n/k) between any pair of nodes. other topologies have been proposed later on to improve greedy algorithm performance. but, aspnes et al. [fault-tolerant routing in peer-to-peer systems, in: proc. of acm 3st symp. on princ. of distr. comp. (podc 2002), vol. 31, 2002, pp. 223-232] shows that for a wide class of long-range link distributions, the expected length of the path computed by this algorithm is always ω(log2 n/(k2 log log n)).we design and analyze a new decentralized routing algorithm, in which nodes consult their neighbors near by, before deciding to whom forward the message. our algorithm uses similar amount of computational resources as kleinberg's greedy algorithm: it is easy to implement, visits o(log2 n/log2 (1 +k)) nodes on expectation and requires only θ(log2 n/log(1 +k)) bits of memory--note that [g.s. manku, m. naor, u. wieder, know thy neighbor's neighbor: the power of lookahead in randomized p2p networks, in: proc. of 36th acm stoc 2004, 2004, to appear], shows that any decentralized algorithm visits at least ω(log2 n/k) on expectation. our algorithm computes however a path of expected length o(log n (log log n)2/log2 (1 + k)) between any pair of nodes. our algorithm might fit better some human social behaviors (such as web browsing) and may also have successful applications to peer-to-peer networks where the length of the path along which the files are downloaded, is a critical parameter of the network performance.
simulation of one-dimensional cellular automata by uniquely parallel parsable grammars. a uniquely parsable grammar (upg) introduced by morita et al. (acta inform. 34 (1997) 389) is a special kind of generative grammar where parsing can be performed without backtracking. by extending a upg, a uniquely parallel parsable grammar (uppg) was proposed and its unique parallel parsability has been investigated. in this paper, we show any one-dimensional cellular automaton, as a parallel language recognition device, can be simply simulated by a parallel reduction in an equivalent uppg.
resource bounded symmetry of information revisited. the information contained in a string x about a string y is the difference between the kolmogorov complexity of y and the conditional kolmogorov complexity of y given x, i.e., i(x : y)=c(y)-c(y|x). the kolmogorov-levin theorem says that i(x : y) is symmetric up to a small additive term. we investigate if this property also holds for several versions of polynomial time-bounded kolmogorov complexity.we study symmetry of information for some variants of distinguishing complexity cd where cd(x) is the length of a shortest program which accepts x and only x. we show relativized worlds where symmetry of information does not hold in a strong way for deterministic and nondeterministic polynomial time distinguishing complexities cdpoly and cndpoly. on the other hand, for nondeterministic polynomial time distinguishing complexity with randomness, camdpoly, we show that symmetry of information holds for most pairs of strings in any set in np. our techniques extend work of buhrman et al. (language compression and pseudorandom generators, in: proc. 19th ieee conf. on computational complexity, ieee, new york, 2004, pp. 15-28) on language compression by am algorithms, and have the following application to the compression of samplable sources, introduced in trevisan et al. (compression of sample sources, in: proc. 19th ieee conf. on computational complexity, ieee, new york, 2004, pp. 1-15): any element x in the support of a polynomial time samplable source x can be given a description of size - log pr[x = x] + o(log3 n), from which x can be recovered by an am algorithm.
large triangles in the -dimensional unit cube. we consider a variant of heilbronn's triangle problem by asking for a distribution of n points in the d-dimensional unit cube [0, 1]d such that the minimum (two-dimensional) area of a triangle among these n points is as large as possible. denoting by δdoff-line (n) and δdon-line (n) the supremum of the minimum area of a triangle among n points over all distributions of n points in [0, 1]d for the off-line and the on-line situation, respectively, for fixed dimension d ≥ 2 we show that c1ċ(log n)1/(d-1)/n2/(d-1) ≤ δdoff-line(n) ≤ c'1/n2/d and c2/n2/(d-1) ≤ δdon-line (n) ≤ c'2/n2/d for constants c1, c2, c'1,c'2 > 0 which depend on d only. moreover, we provide a deterministic polynomial time algorithm that achieves the lower bound ω((log n)1/(d-1))/n2/(d-1)) on the minimum area of a triangle among n points in [0, 1]d in the off-line case.
neural circuits for pattern recognition with small total wire length. one of the most basic pattern recognition problems is whether a certain local feature occurs in some linear array to the left of some other local feature. we construct in this article circuits that solve this problem with an asymptotically optimal number of threshold gates. furthermore it is shown that much fewer threshold gates are needed if one employs in addition a small number of winner-take-all gates. in either case the circuits that are constructed have linear or almost linear total wire length, and are therefore not unrealistic from the point of view of physical implementations.
intrinsic reasoning about functional programs ii: unipolar induction and primitive-recursion. we continue from (ann. pure appl. logic 114 (2002) 117) our study of reasoning about recursion equations in rudimentary theories for inductive data, dubbed intrinsic theories. we show that the functions that are provable using unipolar induction are precisely the primitive-recursive functions, where we call an instance of induction unipolar if data pledicates do not occur in the induction formula both positively and negatively.two special cases of this result are well known, namely induction over σ10 and π10. here, however, induction formulas may have unrestricted quantifier alternations as long as those quantifiers that are relativized to data do not violate the prescribed restriction. the main technical challenge is in showing that the functions provable by unipolar induction, even in classical logic, are primitive-recursive.the result is generic with respect to the underlying inductive data, suggesting a potentially useful formalization of primitive-recursive mathematics.
competitive caching of query results in search engines. we study the problem of caching query result pages in web search engines. popular search engines receive millions of queries per day, and for each query, return a result page to the user who submitted the query. the user may request additional result pages for the same query, submit a new query, or quit searching altogether. an efficient scheme for caching query result pages may enable search engines to lower their response time and reduce their hardware requirements.this work studies query result caching within the framework of the competitive analysis of algorithms. we define a discrete time stochastic model for the manner in which queries are submitted to search engines by multiple user sessions. we then present an adaptation of a known online paging scheme to this model. the expected number of cache misses of the resulting algorithm is no greater than 4 times the expected number of misses that any online caching algorithm will experience under our specific model of query generation.
approximate pattern matching and transitive closure logics. a sartorial query language facilitates the formulation of queries to a (string) database. one step towards an implementation of such a query language can be taken by defining a logical formalism expressing a known solution for the particular problem at hand. the simplicity of the logic is a desired property, because the simpler the logic that the query language is based on, the more efficiently it can be implemented. we introduce a logical formalism for expressing approximate pattern matching. the formalism uses properties of the dynamic programming approach; a minimizing path of a dynamic programming table is expressed by using a formula in an extension of first order logic (fo). we consider the well-known problems of k-mismatches and k-differences. assuming first that k is given as a part of the input, those problems are expressed by using deterministic transitive closure logic (fo(dtc)) and transitive closure logic (fo(tc)), respectively. we show how to adapt the formalisms to allow individual costs for the editing operations, and consider music information retrieval (mir) as a case study.we believe that in the general case k-differences is not expressible in fo(dtc). however, we show that proving this is at least as hard as separating logspace from nlogspace. on the other hand, we show that if k is fixed, the k-differences problem can be expressed by an fo(dtc) formula.
the drawability problem for minimum weight triangulations. a graph is minimum weight drawable if it admits a straight-line drawing that is a minimum weight triangulation of the set of points representing the vertices of the graph. we study the problem of characterizing those graphs that are minimum weight drawable. our contribution is twofold: we show that there exist infinitely many triangulations that are not minimum weight drawable. furthermore, we present non-trivial classes of triangulations that are minimum weight drawable, along with corresponding linear time algorithms that take as input any graph from one of these classes and produce as output such a drawing. one consequence of our work is the construction of triangulations that are minimum weight drawable but not delaunay drawable - that is, not drawable as a delaunay triangulatio
category theory for operational semantics. we use the concept of a distributive law of a monad over a copointed endofunctor to define and develop a reformulation and mild generalisation of turi and plotkin's notion of an abstract operational rule. we make our abstract definition and give a precise analysis of the relationship between it and turi and plotkin's definition. following tuff and plotkin, our definition, suitably restricted, agrees with the notion of a set of gsos-rules, allowing one to construct both an operational model and a canonical, internally fully abstract denotational model. going beyond turi and plotkin, we construct what might be seen as large-step operational semantics from small-step operational semantics and we show how our definition allows one to combine distributive laws, in particular accounting for the combination of operational semantics with congruences.
hierarchical structures in sturmian dynamical systems. the paper is concerned with hierarchical stuctures in subshifis over a finite alphabet. in particular, we present a hierarchy-based approach to sturmian systems. this approach is then used to characterize the linearly repetitive sturmian systems (among the sturmian systems) by uniform positivity of certain weights. more generally, we discuss various bounds on weights and their relationship.finally, we combine hierarchies and bounds on a weights to study a thermodynamic formalism for lattice gas models associated to arbitrary linearly repetitive subshifts.
cross-monotonic cost sharing methods for connected facility location games. we present cost sharing methods for connected facility location games that are cross-monotonic and competitive and that recover a constant fraction of the cost of the constructed solution. the novelty of this paper is that we use randomized algorithms and that we share the expected cost among the participating users. as a consequence, our cost sharing methods are simple and achieve attractive approximation ratios. we also provide a primal-dual cost sharing method for the connected facility location game with opening costs.
towards a dynamical model for wireless sensor networks. in this paper we introduce two dynamical models for a broadcast process in wireless sensor networks. we obtain a convergent martingale sequence for the two models. to our knowledge, such martingales were unknown previously. we look at the formal models using the formalisms of martingales, dynamical systems and markov chains, each formalism providing complementary and coherent information with each other. the dynamics of both models are comparable and are validated in their domain of application with numerical simulation of wireless sensor networks. we make explicit the situations where the models are realistic. we also provide a formal analysis of the quasi-stationary distribution associated to the markov chain corresponding to the second model proposed.
a formal model of real-time program compilation. program compilation can be formally defined as a sequence of equivalence-preserving transformations, or refinements, from high-level language programs to assembler code. recent models also incorporate timing properties, but the resulting formalisms are intimidatingly complex. here we take advantage of a new, simple model of real-time refinement, based on predicate transformer semantics, to present a straightforward compilation formalism that incorporates real-time constraints.
a theory for execution-time derivation in real-time programs. we provide an abstract command language for real-time programs and outline how a partial correctness semantics can be used to compute execution times. the notions of a timed command, refinement of a timed command, the command traversal condition, and the worst-case and best-case execution time of a command are formally introduced and investigated with the help of an underlying weakest liberal precondition semantics. the central result is a theory for the computation of worst-case and best-case execution times from the underlying semantics based on supremum and infimum calculations. the framework is applied to the analysis of a message transmitter program and its implementation.
refinement and state machine abstraction. precise module interface specifications are essential in modular software development. the role of state in these specifications has been the issue of some debate and is central to the notion of data refinement. in previous work, hoffman and strooper introduce a state-abstraction lattice that defines a partial order on specifications for deterministic and complete languages. they use this lattice to define a notion of state abstractness and show that this intuitive notion corresponds to the use of the terms "abstract" and "concrete" as used in data-refinement proofs. in this paper, we extend this work for a class of specifications and languages that we call demonic and semi-deterministic. we also introduce a notion of backward refinement and prove that backward refinement together with the common forward refinement of vdm and z form a sound and complete refinement technique with respect to a partial order on languages defined by demonic specifications. we illustrate the ideas using simple languages and specifications. copyright 2001 elsevier science b.v.
a constructive algorithm for finding the exact roots of polynomials with computable real coefficients. in this paper we will show that it is possible to generate the roots of monic polynomials with computable real coefficients as computable complex numbers. a result from constructive analysis has already shown that the roots are computable numbers; however, because the proof is non-constructive it does not provide an effective method for finding the roots. in this work we combine two extra stages to a standard numerical algorithm: an exact error analysis, and a method for aligning sets of complex rational numbers so that the result is a set of computable complex numbers. the method of effectivization is of interest as it can be used in other situations where an algorithm will work with rational approximations, but comparison operations prevent its use with computable numbers.
using pvs to validate the algorithms of an exact arithmetic. the whole point of exact arithmetic is to generate answers to numeric problems, within some user-specified error. an implementation of exact arithmetic is therefore of questionable value, if it cannot be shown that it is generating correct answers. in this paper, we show that the algorithms used in an exact real arithmetic are correct. a program using the functions defined in this paper has been implemented in 'c' (a haskell version of which we provide as an appendix), and we are now convinced of its correctness. the table presented at the end of the paper shows that performing these proofs found three logical errors which had not been discovered by testing. one of these errors was only detected when the theorems were validated with pvs.
the limitedness problem on distance automata: hashiguchi's method revisited. hashiguchi has studied the limitedness problem of distance automata (da) in a series of paper [(j. comput. system sci. 24 (1982) 233; theoret. comput. sci. 72 (1990) 27; theoret. comput. sci. 233 (2000) 19)]. the distance of a da can be limited or unbounded. given that the distance of a da is limited, hashiguchi has proved in hashiguchi (2000) that the distance of the automaton is bounded by 24n3+n lg(n+2)+n, where n is the number of states. in this paper, we study again hashiguchi's solution to the limitedness problem. we have made a number of simplification and improvement on hashiguchi's method. we are able to improve the upper bound to 23n3+n lg n+n-1.
an efficient algorithm for online square detection. a square is a string that can be divided into two identical substrings. the problem of square detection has found applications in areas such as bioinformatics and data compression. there are many offline algorithms for the problem. in this paper, we give the first online algorithm for deciding whether a string contains a square. our algorithm runs in total o(h log2 h) time where h is the length of the longest prefix of the input string that does not contain a square.
on a conjecture about finite fixed points of morphisms. a conjecture of m. billaud is: given a word w, if, for each letter x occurring in w, the word obtained by erasing all the occurrences of x in w is a fixed point of a nontrivial morphism fx, then w is also a fixed point of a non-trivial morphism. we prove that this conjecture is equivalent to a similar one on sets of words. using this equivalence, we solve these conjectures in the particular case where each morphism fx has only one expansive letter.
newton's method with deflation for isolated singularities of polynomial systems. we present a modification of newton's method to restore quadratic convergence for isolated singular solutions of polynomial systems. our method is symbolic-numeric: we produce a new polynomial system which has the original multiple solution as a regular root. using standard bases, a tool for the symbolic computation of multiplicities, we show that the number of deflation stages is bounded by the multiplicity of the isolated root. our implementation performs well on a large class of applications.
performance evaluation for energy efficient topologic control in ad hoc wireless networks. minimizing total energy to keep an ad hoc wireless network symmetrically connected is an np-hard problem. recently, several greedy approximations have been proposed, based on k-restricted decompositions of the network. their performance ratios are established through estimations of the least upper bound ρk for the ratio between total powers of best possible k-restricted decomposition and the optimal solution. in this paper, we determine the exact value of ρk for all k.
a 3d graphical representation of dna sequences and its application. a 3d graphical representation of dna sequences has been derived from mathematical denotation of dna sequence. the 3d graphical representation also avoids loss of information accompanying alternative 2d and 3d representation in which the curve standing for dna overlaps and intersects itself. the geometrical centers of the 3d graph of dna sequences indicate the distribution of base frequencies. an interesting phenomenon is observed for goat and gallus β-globin genomes with high g+c content. the examination of similarities/dissimilarities among the coding sequences of the first exon of β-globin gene of different species illustrates the utility of the approach.
expressive power of sql. it is a folk result in database theory that sql cannot express recursive queries such as reachability; in fact, a new construct was added to sql3 to overcome this limitation. however, the evidence for this claim is usually given in the form of a reference to a proof that relational algebra cannot express such queries. sql, on the other hand, in all its implementations has three features that fundamentally distinguish it from relational algebra: namely, grouping, arithmetic operations, and aggregation.in the past few years, most questions about the additional power provided by these features have been answered. this paper surveys those results, and presents new simple and self-contained proofs of the main results on the expressive power of sql. somewhat surprisingly, tiny differences in the language definition affect the results in a dramatic way: under some very natural assumptions, it can be proved that sql cannot define recursive queries, no matter what aggregate functions and arithmetic operations are allowed. but relaxing these assumptions just a tiny bit makes the problem of proving expressivity botmds for sql as hard as some long-standing open problems in complexity theory.
lower bounds for invariant queries in logics with counting. we study the expressive power of counting logics in the presence of auxiliary relations such as orders and preorders. the simplest such logic is the first-order logic with counting. this logic captures the complexity class tc0 over ordered structures. we also consider first-order logic with arbitrary unary quantifiers and with infinitary extensions.we start by giving a simple direct proof that first-order logic with counting, in the presence of pre-orders that are almost-everywhere linear orders, cannot express the transitive closure of a binary relation. the proof is based on locality of formulae. we then show that the technique cannot be extended to linear orders. we further show that this result does not say anything about the power of invariant queries in first-order logic with counting vs. the class tc0, in the presence of these preorders.in the second part of the paper, we prove a separation result showing that, for all the counting logics above, a linear order is more powerful than a preorder that is a linear order almost everywhere. in fact, we prove that the expressive power of invariant queries in the presence of such preorders can be characterized by a property normally associated with first-order definability over unordered structures. we do this by using locality techniques from finite-model theory. however, as some standard notions of locality fail in this setting, we have to modify them to prove the main result.
an evaluation function for the game of amazons. amazons is a fascinating game that shares properties of chess and go. designing a computer program that plays amazons on the level of human experts and beyond is a real challenge. this article emphasizes the secret of such a program, viz. its evaluation function. we describe the function by using explicit formulas, we mention the ideas and goals behind these formulas, we discuss possible refinements, and study in detail methods for special endgame problems. by analyzing a tournament game of amazong against the threefold computer world champion 8qp we illustrate how the new features of our evaluation function can lead to victory.
k-center problems with minimum coverage. in this work, we study an extension of the k-center facility location problem, where centers are required to service a minimum of clients. this problem is motivated by requirements to balance the workload of centers while allowing each center to cater to a spread of clients. we study three variants of this problem, all of which are shown to be n p-hard. in-approximation hardness and approximation algorithms with factors equal or close to the best lower bounds are provided. generalizations, including vertex costs and vertex weights, are also studied.
fast inversion of triangular toeplitz matrices. in this paper, we present an approximate inversion method for triangular toeplitz matrices based on trigonometric polynomial interpolation. to obtain an approximate inverse of high accuracy for a triangular toeplitz matrix of size n, our algorithm requires two fast fourier transforms (ffts) and one fast cosine transform of 2n-vectors. we then revise the approximate method proposed by bini (siam j. comput. 13 (1984) 268). the complexity of the revised bini algorithm is two ffts of 2n-vectors.
towards area requirements for drawing hierarchically planar graphs. hierarchical graphs are an important class of graphs for modeling many real applications in software and information visualization. in this paper, we investigate area requirements for drawing hierarchically planar graphs regarding two different drawing standards. firstly, we show an exponential lower bound for the area needed for straight-line drawing of hierarchically planar graphs. the lower bound holds even for s-t hierarchical graphs without transitive arcs, in contrast to the results for upward planar drawing. this motivates our investigation of another drawing standard grid visibility representation, as a relaxation of straight-line drawing. an application of the existing results from upward drawing can guarantee a quadric drawing area for grid visibility representation but does not necessarily guarantee the minimum drawing area. motivated by this, we will present a new grid visibility drawing algorithm which is efficient and guarantees the minimum drawing area with respect to a given topological embedding. this implies that the area minimization problem is polynomial time solvable restricted to the class of graphs whose planar embeddings are unique. however, we can show that the problem of area minimization of grid visibility for hierarchically planar graphs is generally np-hard, even restricted to s-t graphs.
the super connectivity of the pancake graphs and the super laceability of the star graphs. a k-container c(u, v) of a graph g is a set of k-disjoint paths joining u to v. a k-container c(u, v) of g is a k*-container if it contains all the vertices of g. a graph g is k*-connected if there exists a k*-container between any two distinct vertices. let κ(g) be the connectivity of g. a graph g is super connected if g is i*-connected for all 1 ≤ i ≤ κ(g). a bipartite graph g is k*-laceable if there exists a k*-container between any two vertices from different parts of g. a bipartite graph g is super laceable if g is i*-laceable for all 1 ≤ i ≤ κ(g). in this paper, we prove that the n-dimensional pancake graph pn is super connected if and only if n ≠ 3 and the n-dimensional star graph sn is super laceable if and only if n ≠ 3.
graph bandwidth of weighted caterpillars. graph bandwidth minimization (gbm) is a classical and challenging problem in graph algorithms and combinatorial optimization. most of existing researches on this problem have focused on unweighted graphs. in this paper, we study the bandwidth minimization problem of weighted caterpillars, and propose several algorithms for solving various types of caterpillars and general graphs. more specifically, we show that the gbm problem on caterpillars with hair-length at most 2 and the gbm problem on star-shape caterpillars are np-complete, and give a lower bound of the graph bandwidth for general weighted graphs. for caterpillars with hair-length at most 1, we present an o(n log n log(nwmax))-time algorithm to compute an optimal bandwidth layout, where n is the total number of vertices in the graph and wmax is the maximum wedge weight. for caterpillars with hair-length at most k, we give a k-approximation algorithm. for arbitrary caterpillars and general graphs, we give a heuristic algorithm and some experimental results. experiments show that the solutions obtained by our heuristic algorithm are roughly within a factor of clog(n) of the lower bound for a small number c, which is consistent with the inapproximability results of this problem (i.e., no constant approximation for the gbm problem unless p = np).
the complexity of counting self-avoiding walks in subgraphs of two-dimensional grids and hypercubes. valiant (siam j. comput. 8 (1979) 410-421) showed that the problem of computing the number of simple s-t paths in graphs is #p-complete both in the case of directed graphs and in the case of undirected graphs. welsh (complexity: knots, colourings and counting, cambridge university press, cambridge, 1993, p. 17) asked whether the problem of computing the number of self-avoiding walks of a given length in the complete two-dimensional grid is complete for #p1, the tally-version of #p. this paper offers a partial answer to the question of welsh: it is #p-complete to compute the number of self-avoiding walks of a given length in a subgraph of a two-dimensional grid. several variations of the problem are also studied and shown to be #p-complete. this paper also studies the problem of computing the number of self-avoiding walks in a subgraph of a hypercube. similar completeness results are shown for the problem. by scaling the computation time to exponential, it is shown that computing the number of self-avoiding walks in hypercubes is a complete problem for #exp in the case when a subgraph of a hypercube is specified by its dimension and a boolean circuit that accepts the nodes.finally, this paper studies the complexity of testing whether a given word over the four-letter alphabet {u,d,l,r} represents a self-avoiding walk in a two-dimensional grid. a linear-space lower bound is shown for nondeterministic turing machines with a 1-way input head to make this test.
approximation schemes for minimizing total (weighted) completion time with release dates on a batch machine. a batch machine is a machine that can process a number of jobs simultaneously as a batch, and the processing time of a batch is equal to the longest processing time of the jobs assigned to it. in this paper, we present a polynomial time approximation scheme (ptas) for scheduling a batch machine to minimize the total completion time with job release dates. also, we present a fully polynomial time approximation scheme (fptas) for scheduling an unbounded batch machine, which can process an arbitrary number of jobs simultaneously, to minimize the total weighted completion time with job release dates.
finitary pcf is not decidable. the question of the decidability of the observational ordering of finitary pcf was raised (jung and stoughton, in: m. bezem, j.f. groote (eds.), typed lambda calculi and applications, lecture notes in computer science, vol. 664, springer, berlin, 1993, pp. 230-244) to give mathematical content to the full abstraction problem for pcf (milner, theoret. comput. sci. 4 (1977) 1-22). we show that the ordering is in fact undecidable. this result places limits on how explicit a representation of the fully abstract model can be. it also gives a slight strengthening of the author's earlier result on typed ability (loader, in: a. anderson, m. zeleny (eds.), church memorial volume, kluwer academic press, dordrecht, to appear). copyright 2001 elsevier science b.v.
realizability of high-level message sequence charts: closing the gaps. we study the notion of safe realizability for high-level message sequence charts (hmscs) (proceedings of the 28th international colloquium on automata, languages and programming (icalp 2001), crete (greece), lecture notes in computer science, vol. 2076, springer, berlin, 2001, pp. 797-808). we show that safe realizability is expspace-complete for bounded hmscs but undecidable for the class of all hmscs. this solves two open problems from alur et al. moreover we prove that safe realizability is also expspace-complete for the larger class of globally-cooperative hmscs.
the complexity of tree automata and xpath on grammar-compressed trees. the complexity of various membership problems for tree automata on compressed trees is analyzed. two compressed representations are considered: dags, which allow to share identical subtrees in a tree, and straight-line context-free tree grammars, which moreover allow to share identical intermediate parts in a tree. several completeness results for the classes nl, p, and pspace are obtained. finally, the complexity of the evaluation problem for (structural) xpath queries on trees that are compressed via straight-line context-free tree grammars is investigated.
introducing va. this paper reports on a new software platform called vaucanson and dedicated to the computation with automata and transducers. its main feature is the capacity of dealing with automata whose labels may belong to various algebraic structures.the paper successively describes the main features of the vaucanson platform, including the fact that the very rich data structure used to implement automata does not weigh too much on the performance, shows how vaucanson allows to program algorithms on automata in a way which is very close to the mathematical expression of the algorithm and finally explains the main choices of the programming design that enable to achieve both genericity and efficiency.
derivatives of rational expressions with multiplicity. this paper addresses the problem of turning a rational (i.e. regular) expression into a finite automaton. we formalize and generalize the idea of "partial derivatives" introduced in 1995 by antimirov, in order to obtain a construction of an automaton with multiplicity from a rational expression describing a formal power series with coefficients in a semiring.we first define precisely what is such a rational expression with multiplicity and which hypothesis should be put on the semiring of coefficients in order to keep the usual identities.we then define the derivative of such a rational expression as a linear combination of expressions called derived terms and we show that all derivatives of a given expression are generated by a finite set of derived terms, that yields a finite automaton with multiplicity whose behaviour is the series denoted by the expression. we also prove that this automaton is a quotient of the standard (or glushkov) automaton of the expression. finally, we propose and discuss some possible modifications to our definition of derivation.
sequential? this paper is a survey where we try to organise the known answers to the question whether a given finite automaton with multiplicity in a semiring k is equivalent to a sequential, or input deterministic, one. we shall see that depending on k, the question goes from obvious to open, that the answer goes from yes to undecidable. we review results on sequentiality in the cases of series of finite image, of series with multiplicity in fields, and of series with multiplicity in idempotent semirings.
an alternative definition of splicing. in this paper, we propose a new definition of the language generated by a splicing system, motivated by both biochemical and mathematical considerations. the main feature of the new definition is that by applying a splicing rule, we not only create new strings, but also allow for the removal of the strings entering the rule. this behaviour seems to correspond better to biochemical reality and is in fact used as a tool in several experimental dna computations. we show that using this new definition, finite extended h systems can generate all recursively enumerable languages. even a weaker version of these h systems, defined using the new notion of delay, is shown to be strictly more powerful than h systems defined in the traditional way.
on-line parallel heuristics, processor scheduling and robot searching under the competitive framework. in this paper we investigate parallel searches on m concurrent rays for a point target t located at some unknown distance along one of the rays. a group of p agents or robots moving at unit speed searches for t. the search succeeds when an agent reaches the point t. given a strategy s the competitive ratio is the ratio of the time needed by the agents to find t using s and the time needed if the location of t had been known in advance. we provide a strategy with competitive ratio of 1 + 2(m/p - 1)(m/(m - p))m/p and prove that this is optimal. this problem has applications in multiple heuristic searches in ai as well as robot motion planning. the case p = 1 is known in the literature as the cow path problem.
a mathematical model for the tcp tragedy of the commons. this paper presents a novel mathematical model for the tcp tragedy of the commons, using game theory concepts. this tragedy may appear in a tcp/ip-based network when hosts do not respect the protocol rules and try to monopolize the shared network resources by using a selfish strategy. our model quantifies the effects of this evil behavior in a simple and standard network topology and allows to obtain some interesting results which we prove formally. finally, we validate the model results by comparing its predictions with a set of extensive simulations carried out using the ns network simulator.
specification, testing and implementation relations for symbolic-probabilistic systems. we consider the specification and testing of systems where probabilistic information is not given by means of fixed values but as intervals of probabilities. we will use an extension of the finite state machines model where choices among transitions labelled by the same input action are probabilistically resolved. we will introduce our notion of test and we will define how tests are applied to implementations under test. we will also present implementation relations to assess the conformance, up to a level of confidence, of an implementation to a specification. in order to define these relations we will take finite samples of executions of the implementation and compare them with the probabilistic constraints imposed by the specification. finally, we will give an algorithm for deriving sound and complete test suites.
error analysis in minimax trees. game tree search deals with the problems that arise, when computers play two-person-zero-sum-games such as chess, checkers, othello, etc. the greatest success of game tree search so far, was the victory of the chess machine 'deep blue' vs. g. kasparov (icca j. 20 (1997) 95), the best human chess player in the world at that time. in spite of the enormous popularity of computer chess and in spite of the successes of game tree search in game playing programs, we do not know much about a useful theoretical background that could explain the usefulness of (selective) search in adversary games.we introduce a combinatorial model, which allows us to model errors of a heuristic evaluation function, with the help of coin tosses. as a result, we can show that searching in a game tree will be 'useful' if, and only if, there are at least two leaf-disjoint strategies which prove the root value. in addition, we show that the number of leaf-disjoint strategies, contained in a game tree, determines the order of the quality of a heuristic minimax value. the model is integrated into the context of average-case analyses.
new approximation algorithm for rtile problem. for a given two-dimensional array of nonnegative numbers and a positive integer p we want to find a covering of the array with p tiles so as to minimize the weight of the heaviest tile. we present a 9/4-approximation linear-time algorithm for this problem, which improves on the previous best result.
monotone runs of uniformly distributed integer random variables: a probabilistic analysis. using a markov chain approach and a polyomino-like description, we study some asymptotic properties of monotone increasing runs of uniformly distributed integer random variables. we analyze the limiting trajectories, which after suitable normalization, lead to a brownian motion, the number of runs, which is asymptotically gaussian, the run length distribution, the hitting time to a large length k run, which is asymptotically exponential, and the maximum run length which is related to the gumbel extreme-value distribution function. a preliminary application to dna analysis is also given.
ascending runs of sequences of geometrically distributed random variables: a probabilistic analysis. using a markov chain approach and a polyomino-like description, we study some asymptotic properties of sequences of ascending runs of geometrically distributed random variables. we analyze the limiting trajectories, the number of runs and the run length distribution, the hitting time to a length k run and the maximum run length.
generalized covariances of multi-dimensional brownian excursion local times. expressions for the generalized covariances of multi-dimensional brownian excursion local times are derived from corresponding densities transforms. typical applications are moments of the cost of structures such as m/g/1 queue, random trees, markov stack or priority queue in knuth's model. brownian excursion area and a result of biane and yor are also revisited.
simulations among multidimensional turing machines. for all d ≥ 1 and all e > d, every deterministic multihead e-dimensional turing machine of time complexity t(n) can be simulated on-line by a deterministic multihead d-dimensional turing machine in time o(t(n)1+1/d-1/e(log t(n))o(1)). this simulation almost achieves the known lower bound ω(t(n)1+1/d-1/e) on the time required. furthermore, there is a deterministic d-dimensional machine with just two worktape heads that simulates the e-dimensional machine on-line in time o(t(n)1+1/d-1/delog t(n)). these simulations are interpreted in terms of dynamic embeddings among data structures.
semantic models for information flow. in the past, several definitions of information flow have been presented, based upon process algebras. unfortunately, all these appear to be either too weak--failing to identify certain subtle forms of information flow or too strong--indicating information flow when there is none. in this paper, we produce a definition that aims to overcome these shortcomings. we base our definition upon an operational model of csp that reasons about the ways in which nondeterministic choices can be resolved, and so is more discriminating than previous models. our definition of information flow is then that the behaviour of one agent can have some influence upon another agent's view of the system. this definition gives the expected results on all thought experiments tried to date, and also satisfies certain desirable properties.
any-world assumptions in logic programming. due to the usual incompleteness of information representation, any approach to assign a semantics to logic programs has to rely on a default assumption on the missing information. the stable model semantics, that has become the dominating approach to give semantics to logic programs, relies on the closed world assumption (cwa), which asserts that by default the truth of an atom is false. there is a second well-known assumption, called open world assumption (owa), which asserts that the truth of the atoms is supposed to be unknown by default. however, the cwa, the owa and the combination of them are extremal, though important, assumptions over a large variety of possible assumptions on the truth of the atoms, whenever the truth is taken from an arbitrary truth space.the topic of this paper is to allow any assignment (i.e. interpretation), over a truth space, to be a default assumption. our main result is that our extension is conservative in the sense that under the "everywhere false" default assumption (cwa) the usual stable model semantics is captured. due to the generality and the purely algebraic nature of our approach, it abstracts from the particular formalism of choice and the results may be applied in other contexts as well.
parametrized semantics of logic programs--a unifying framework. the different semantics that can be assigned to a logic program correspond to different assumptions made concerning the atoms that are rule heads and whose logical values cannot be inferred from the rules. for example, the well founded semantics corresponds to the assumption that every such atom is false, while the kripke-kleene semantics corresponds to the assumption that every such atom is unknown. in this paper, we propose to unify and extend this assumption-based approach by introducing parameterized semantics for logic programs. the parameter holds the value that one assumes for all rule heads whose logical values cannot be inferred from the rules. we work within multi-valued logic with bilattice structure, and we consider the class of logic programs defined by fitting.following fitting's approach, we define an operator that allows us to compute the parameterized semantic, and to compare and combine semantics obtained for different values of the parameter. we show that our approach captures and extends the usual semantics of conventional logic programs thereby unifying their computation.
automatic workflow verification and generation. correctness is an important aspect of workflow management systems. however, most of the workflow literature focuses only on the modeling aspects and assumes that a workflow is correct if during the execution it respects the control and data dependency specified by the workflow designer. to address the correctness question properly we propose a new workflow model based on hoare semantics that allows to: (1) automatically check if the desired outcome of a workflow can be produced by its actual implementation, (2) automatically synthesize a workflow implementation from the workflow specification and a given task library.in particular we: (1) formalize the semantics of workflows and tasks with pre-and postconditions, (2) for each control construct we provide a set of sound inference rules formalizing its semantics. while most of our workflow constructs are standard, two of them are new: the universal and the existential constructs. we then describe algorithms for automatically checking the correctness of workflows and for automatic workflow generation.
finding the shortest boundary guard of a simple polygon. there are many different kinds of guards in a simple polygon that have been proposed and discussed. in this paper, we consider a new type of guard, boundary guard, which is a guard capable of moving along a boundary of a polygon and every interior point of the polygon can be seen by the mobile guard. we propose an algorithm to 1nd the shortest boundary guard of a simple polygon p in o(n log n) time, where n is the number of vertices of p.
efficient minus and signed domination in graphs. an efficient minus (respectively, signed) dominating function of a graph g = (v,e) is a function f: v → {-1,0,1} (respectively, {-1, 1}) such that σu∈m[v] f(u) = 1 for all v ∈ v, where n[v] = {v} ∪ {u|(u,v) ∈ e}. the efficient minus (respectively, signed) domination problem is to find an efficient minus (respectively, signed) dominating function of g. in this paper, we show that the efficient minus (respectively, signed) domination problem is np-complete on chordal graphs, chordal bipartite graphs, planar bipartite graphs and planar graphs of maximum degree 4 (respectively, on chordal graphs). based on the forcing property on blocks of vertices and automata theory, we provide a uniform approach to show that in a special class of interval graphs, every graph (respectively, every graph with no vertex of odd degree) has an efficient minus (respectively, signed) dominating function. we also give linear-time algorithms to find these functions. besides, we show that the efficient minus domination problem is equivalent to the efficient domination problem on trees.
absolute exponential stability of a class of recurrent neural networks with multiple and variable delays. in this paper, we derive some new conditions for absolute exponential stability (aest) of a class of recurrent neural networks with multiple and variable delays. by using the holder's inequality and the young's inequality to estimate the derivatives of the lyapunov functionals, we are able to establish more general results than some existing ones. the first type of conditions established involves the convex combinations of column-sum and row-sum dominance of the neural network weight matrices, while the second type involves the p-norm of the weight matrices with p ∈ [1, +∞].
the full steiner tree problem. motivated by the reconstruction of phylogenetic tree in biology, we study the full steiner tree problem in this paper. given a complete graph g = (v,e) with a length function on e and a proper subset r ⊆ v, the problem is to find a full steiner tree of minimum length in g, which is a kind of steiner tree with all the vertices of r as its leaves. in this paper, we show that this problem is np-complete and max snp-hard, even when the lengths of the edges are restricted to either 1 or 2. for the instances with lengths either 1 or 2, we give a 8/5-approximation algorithm to find an approximate solution for the problem.
some combinatorial results on bernoulli sets and codes. a bernoulli set is a set x of words over a finite alphabet a such that for any positive bernoulli distribution in a* one has that (x)=1. in the case of a two-letter alphabet a={a,b} a characterization of finite bernoulli sets is given in terms of the function &xi,j counting the number of words of x having i occurrences of the letter a and j occurrences of the letter b. moreover, we also derive a necessary and sufficient condition on the distribution &xi, j which characterizes bernoulli sets which are commutatively equivalent to prefix codes
pseudopalindrome closure operators in free monoids. we consider involutory antimorphisms ϕ of a free monoid a* and their fixed points, called ϕ-palindromes or pseudopalindromes. a ϕ-palindrome reduces to a usual palindrome when ϕ is the reversal operator. for any word w ∈ a* the right (resp. left) ϕ-palindrome closure of w is the shortest ϕ-palindrome having w as a prefix (resp. suffix). we prove some results relating ϕ-palindrome closure operators with periodicity and conjugacy, and derive some interesting closure properties for the languages of finite sturmian and episturmian words. in particular, a finite word w is sturmian if and only if both its palindromic closures are so. moreover, in such a case, both the palindromic closures of w share the same minimal period of w. a new characterization of finite sturmian words follows, in terms of periodicity and special factors of their palindromic closures. some weaker results can be extended to the episturmian case. by using the right ϕ-palindrome closure, we extend the construction of standard episturmian words via directive words. in this way one obtains a family of infinite words, called ϕ-standard words, which are morphic images of episturmian words, as well as a wider family of infinite words including the thue-morse word on two symbols.
some characterizations of finite sturmian words. in this paper, we give some new characterizations of words which are finite factors of sturmian words. an enumeration formula for primitive finite sturmian words is given. moreover, we provide two linear-time algorithms to recognize whether a finite word is sturmian.
relaxed models for rewriting logic. we modify the definition of the models for rewrite theories by replacing the equality of functors, defined by e-equal terms, with the equality via a natural isomorphism, called natural symmetry. the relaxation process can be adapted by relaxing all or only a part of the equations, and by relaxing the state structure (and implicitly the computation structure) or just the computation structure. we also consider the subclasses of c-coherent models, where c is a set of equations specifying a collection of commutative symmetry diagrams. the result is a wide palette of model classes which offers more flexibility in modeling concurrent systems.
algorithms, nymphs, and shepherds. computability and complexity are the two major lines along which the science of algorithms has evolved; but the same concepts guide many human activities. we try to catch some glimpses of the connections between these two worlds, to meet the expectations of the audience. we will encounter nymphs and universal turing machines, ancient traditions and randomized procedures, all tending to the same end: having fun with algorithms.
multitree automata that count. multitree are unranked, unordered trees and occur in many computer science applications like rewriting and logic, knowledge representation, xml queries, typing for concurrent systems, cryptographic protocols, etc. we define constrained multitree automata which accept sets of multitrees where the constraints are expressed in a first-order theory of multisets with counting formulas which is very expressive. we give constructions for union, intersection, determinization. then, we give an algorithm to decide emptiness when the constraints belong to a subclass where counting is limited to distinct elements. we show that many classes of tree automata that have been defined for a wide variety of applications can be seen as instance of our general framework. finally, we describe the quantifier elimination procedure used to decide the theory of constraints.
a partial order semantics approach to the clock explosion problem of timed automata. we present a new approach to the symbolic model checking of timed automata based on a partial order semantics. it relies on event zones that use vectors of event occurrences instead of clock zones that use vectors of clock values grouped in polyhedral clock constraints. we provide a description of the different congruences that arise when we consider an independence relation in a timed framework. we introduce a new abstraction, called catchup equivalence which is defined on event zones and which can be seen as an implementation of one of the (more abstract) previous congruences. this formal language approach helps clarifying what the issues are and which properties abstractions should have. the catchup equivalence yields an algorithm to check emptiness which has the same complexity bound in the worst case as the algorithm to test emptiness in the classical semantics of timed automata. our approach works for the class of timed automata proposed by alur-dill, except for state invariants (an extension including state invariants is discussed informally). first experiments show that the approach is promising and may yield very significant improvements.
the regular viewpoint on pa-processes. pa is the process algebra allowing non-determinism, sequential and parallel compositions, and recursion. we suggest viewing pa-processes astrees, and usingtree-automata techniques for verification problems on pa. our main result is that the set of iterated predecessors of a regular set of pa-processes is a regular tree language, and similarly for iterated successors. furthermore, the corresponding tree automata can be built effectively in polynomial time. this has many immediate applications to verification problems for pa-processes, among which a simple and general model-checking algorithm.
reconstructing permutation matrices from diagonal sums. in this paper, we present a result concerning the reconstruction of permutation matrices from their diagonal sums. the problem of reconstructing a sum of k permutation matrices from its diagonal sums is np-complete. we prove that a simple variant of this problem in which the permutation matrices lie on a cylinder instead of on a plane can be solved in polynomial time. we give an exact, algebraic characterization of the diagonal sums that correspond to a sum of permutation matrices. then, we derive an o(kn2)-time algorithm for reconstructing the sum of k permutation matrices of order n from their diagonal sums. we obtain these results by means of a generalization of a classical theorem of hall on the finite abelian groups.
bisimulation on speed: a unified approach. two process-algebraic approaches have been developed for comparing two bisimulation-equivalent processes with respect to speed: the one of moller/tofts equips actions with lower time bounds, while the other by lüttgen/vogler considers upper time bounds instead.this article sheds new light on both approaches by testifying to their close relationship. we introduce a general, intuitive concept of "faster-than", which is formalised by a notion of amortised faster-than preorder. when closing this preorder under all contexts, exactly the two faster-than preorders investigated by moller/tofts and lüttgen/vogler arise. for processes incorporating both lower and upper time bounds we also show that the largest precongruence contained in the amortised faster-than preorder is not a proper preorder but a timed bisimulation. in the light of this result we systematically investigate under which circumstances the amortised faster-than preorder degrades to an equivalence.
decomposition orders another generalisation of the fundamental theorem of arithmetic. we discuss unique decomposition in partial commutative monoids. inspired by a result from process theory, we propose the notion of decomposition order for partial commutative monoids, and prove that a partial commutative monoid has unique decomposition iff it can be endowed with a decomposition order. we apply our result to establish that the commutative monoid of weakly normed processes modulo bisimulation definable in acpε with linear communication, with parallel composition as binary operation, has unique decomposition. we also apply our result to establish that the partial commutative monoid associated with a well-founded commutative residual algebra has unique decomposition.
computing similarity between rna structures. the primary structure of a ribonucleic acid (rna) molecule is a sequence of nucleotides (bases) over the four-letter alphabet {a,c,g,u}. the secondary or tertiary structure of an rna is a set of base-pairs (nucleotide pairs) which forms bonds between au and cg. for secondary structures, these bonds have been traditionally assumed to be one to one and non-crossing. this paper considers a notion of similarity between two rna molecule structures taking into account the primary, the secondary and the tertiary structures. we show that, for tertiary structures, it is max snp-hard for both minimization and maximization versions. we show a stronger result for the maximization version where it cannot be approximated within ratio 2logn in polynomial time, unless npdtime[2polylogn]. we then present an algorithm that can be used for practical application. our algorithm will produce an optimal solution for the case where at least one of the rna involved is of a secondary structure. we also show an approximation algorithm.
on the relevance of time in neural computation and learning. we discuss models for computation in biological neural systems that are based on the current state of knowledge in neurophysiology. differences and similarities to traditional neural network models are highlighted. it turns out that many important questions regarding computation and learning in biological neural systems cannot be adequately addressed in traditional neural network models. in particular, the role of time is quite different in biologically more realistic models, and many fundamental questions regarding computation and learning have to be rethought for this context. simultaneously, a somewhat related new generation of vlsi-chips is emerging ("pulsedvlsi") where new ideas about computing and learning with temporal coding can be tested in an engineering context. articles with details to models and results that are sketched in this article can be found at http://www.tu-graz.ac.at/igi/maass/. we refer to maass and bishop(eds.,pulsed neural network, mit press, cambridge, ma, 1999) for a collection of survey articles that contain further details and references.
natural computation and non-turing models of computation. we propose certain non-turing models of computation, but our intent is not to advocate models that surpass the power of turing machines (tms), but to defend the need for models with orthogonal notions of power. we review the nature of models and argue that they are relative to a domain of application and are ill-suited to use outside that domain. hence we review the presuppositions and context of the tm model and show that it is unsuited to natural computation (computation occurring in or inspired by nature). therefore we must consider an expanded definition of computation that includes alternative (especially analog) models as well as the tm. finally we present an alternative model, of continuous computation, more suited to natural computation. we conclude with remarks on the expressivity of formal mathematics.
properties of probabilistic pushdown automata. properties of probabilistic as well as ``probabilistic plus nondeterministic'''' pushdown automata and auxiliary pushdown automata are studied. these models are analogous to their counterparts with nondeterministic and alternating states. complete characterizations in terms of well-known complexity classes are given for the classes of languages recognized by polynomial time-bounded, logarithmic space-bounded auxiliary pushdown automata with probabilistic states and with ``probabilistic plus nondeterministic'''' states. also, complexity lower bounds are given for the classes of languages recognized by these automata with unlimited running time. it follows that, by fixing an appropriate mode of computation, the difference between classes of languages such as p and pspace, nl and sac^1, pl and diff_<(#sac^1) is characterized as the difference between the number of stack symbols; that is, whether the stack alphabet contains one versus two distinct symbols.
branching time controllers for discrete event systems. we study the problem of synthesizing controllers for discrete event systems in a branching time framework. we use a class of labelled transition systems to model both plants and specifications. we use first simulations and later bisimulations to capture the role of a controller; the controlled behaviour of the plant should be related via a simulation (bisimulation) to the specification. for both simulations and bisimulations we show that the problem of checking if a pair of finite transition systems - one modelling the plant and the other the specification - admits a controller is decidable in polynomial time. we also show that the size of the controller, if one exists, can be bounded by a polynomial in the sizes of the plant and the specification and can be effectively constructed in polynomial time. finally, we prove that in the case of simulations, the problem of checking for the existence of a controller is undecidable in a natural concurrent setting.
when does a planar bipartite framework admit a continuous deformation? let k(x,y) denote the bipartite framework in the plane that realizes the complete bipartite graph km, n with partite sets x,y; |x| = m, |y| = n. we show that for m&ge;3, n&ge;5, k(x,y) admits a continuous deformation if and only if x lies on a line l and y lies on a line perpendicular to l.
on the computational strength of pure ambient calculi. cardelli and gordon's calculus of mobile ambients has attracted widespread interest as a model of mobile computation. the standard calculus is quite rich, with a variety of operators, together with capabilities for entering, leaving and dissolving ambients. the question arises of what is a minimal turing-complete set of constructs. previous work has established that turing completeness can be achieved without using communication or restriction. we show that it can be achieved merely using movement capabilities (and not dissolution). we also show that certain smaller sets of constructs are either terminating or have decidable termination.
pac learning of probability distributions over a discrete domain. we investigate learning of classes of distributions over a discrete domain in a pac context. we introduce two paradigms of pac learning, namely absolute pac learning, which is independent of the representation of the class of hypotheses, and pac learning wrt the indexes, which heavily depends on such representations. we characterize non-computable learnability in both contexts. then we investigate efficient learning strategies which are simulated by a polynomial-time turing machine. one strategy is the frequentist one. according to this strategy, the learner conjectures a hypothesis which is as close as possible to the distribution given by the frequency relative to the examples. we characterize the classes of distributions which are absolutely pac learnable by means of this strategy, and we relate frequentist learning wrt the indexes to the np = rp problem. finally, we present another strategy for learning wrt the indexes, namely learning by tests.
underspecification for a simple process algebra of recursive processes. this paper deals with underspecification for process algebras which is relevant in early design stages. we consider a form of underspecification that arises from a situation where at a certain design stage the decision between several options of system behaviour is to be postponed until more information is available. we follow an approach of veglioni and de nicola (lecture notes in computer science 1466 (1998) 179) who propose to interpret the choice operator of a simple class of finite process terms as underspecification whenever it combines two processes that have some initial action in common, as e.g. in (a.p + v.q) + (a.r + s.s). in particular, we consider recursive processes and discuss several extensions. copyright 2001 elsevier science b.v.
asymptotic behavior in a heap model with two pieces. in a heap model, solid blocks, or pieces, pile up according to the tetris game mechanism. an optimal schedule is an infinite sequence of pieces minimizing the asymptotic growth rate of the heap. in a heap model with two pieces, we prove that there always exists an optimal schedule which is balanced, either periodic or sturmian. we also consider the model where the successive pieces are chosen at random, independently and with some given probabilities. we study the expected growth rate of the heap. for a model with two pieces, the rate is either computed explicitly or given as an infinite series. we show an application for a system of two processes sharing a resource, and we prove that a greedy schedule is not always optimal.
results on multiples of primitive polynomials and their products over gf(2). linear feedback shift registers (lfsr) are important building blocks in stream cipher cryptosysterns. to be cryptographically secure, the connection polynomials of the lfsrs need to be primitive over gf(2). moreover, the polynomials should have high weight and they should not have sparse multiples at low or moderate degree. here we provide results on t-nomial multiples of primitive polynomials and their products. we present results for counting t-nomial multiples and also analyse the statistical distribution of their degrees. the results in this paper helps in deciding what kind of primitive polynomial should be chosen and which should be discarded in terms of cryptographic applications. further the results involve important theoretical identities in terms of t-nomial multiples which were not known earlier.
cryptographically significant boolean functions with five valued walsh spectra. we describe methods to construct balanced (resp. 1-resilient) functions of odd number of variables n achieving the bent concatenation nonlinearity and having algebraic degree n1 (resp. n-2). the technique is to algebraically modify the concatenation of two properly chosen (n-1)-variable maiorana-mcfarland bent functions. the constructed functions can be used with certain recursive operators to provide higher order resilient functions with maximum possible degree and high nonlinearity. such functions are well suited for stream cipher applications. interestingly, all the constructed functions have a five valued walsh spectr
deterministic broadcasting time with partial knowledge of the network. we consider the time of deterministic broadcasting in networks whose nodes have limited knowledge of network topology. each node υ knows only the part of the network within knowledge radius r from it, i.e., it knows the graph induced by all nodes at distance at most r from υ. apart from that, each node knows the maximum degree δ of the network. one node of the network, called the source, has a message which has to reach all other nodes. we adopt the widely studied communication model called the one-way model in which, in every round, each node can communicate with at most one neighbor, and in each pair of nodes communicating in a given round, one can only send a message while the other can only receive it. this is the weakest of all store-and-forward models for point-to-point networks, and hence our algorithms work for other models as well, in at most the same time.we show trade-offs between knowledge radius and time of deterministic broadcasting, when the knowledge radius is small, i.e., when nodes are only aware of their close vicinity. while for knowledge radius 0, minimum broadcasting time is θ(e), where e is the number of edges in the network, broadcasting can be usually completed faster for positive knowledge radius. our main results concern knowledge radius 1. we develop fast broadcasting algorithms and analyze their execution time. we also prove lower bounds on broadcasting time, showing that our algorithms are close to optimal.
a class of polynomially solvable range constraints for interval analysis without widenings. in this paper, we study the problem of solving integer range constraints that arise in many static program analysis problems. in particular, we present the first polynomial time algorithm for a general class of integer range constraints. in contrast with abstract interpretation techniques based on widenings and narrowings, our algorithm computes, in polynomial time, the optimal solution of the arising fixpoint equations. our result implies that "precise" range analysis can be performed in polynomial time without widening and narrowing operations.
towards the hierarchical verification of reactive systems. the hierarchical design approach for action based systems that is known as action refinement has been studied in the literature extensively. in a paper of m. huhn published in concur 1996 a refinement operator on a linear time logic is presented that mimics precisely a semantic action refinement on synchronisation structures. we present here an alternative approach where our starting point is a process algebraic setting with a syntactic action refinement. we present a refinement operator on the modal mu-calculus that conforms with the process algebraic refinement in the following sense: provided some reasonable conditions are met, the transition system induced by a process term <i>p</i> satisfies a modal mu-calculus-specification ϕ if and only if the system which is induced by a refinement of <i>p</i> satisfies a particular refinement of ϕ. alleviating these conditions, we show that each of the two implications in the equivalence assertion above can be separately proven valid for a particular fragment of the modal mu-calculus. we demonstrate that the obtained results can indeed be used as a hierarchical verification technique. as a further application of our results, we explain how they can be employed as an abstraction technique in order to enhance model checking techniques.
tree-width and the monadic quantifier hierarchy. it is well known that on classes of graphs of bounded tree-width, every monadic second-order property is decidable in polynomial time. the converse is not true without further assumptions. it follows from the work of robertson and seymour, that if a class of graphs k has unbounded tree-width and is closed under minors, then k contains all planar graphs. but on planar graphs, three-colorability is np-complete. hence, if p ≠ np and on k every existential monadic second-order property is in p, then k has bounded tree-width. in other words, for k closed under minors, k is of bounded tree-width iff all monadic second-order properties are decidable in p.in this note we prove that in order to characterize classes of graphs of bounded tree-width where the monadic quantifier hierarchy collapses, closure under minors can be replaced by closure under topological minors. closure under minors of k implies that k is in p, whereas we also note that there is a class of graphs k closed under topological minors which is not even r.e.we also show, that closure under induced subgraphs or even under subgraphs alone does not suffice to show that the collapse of the monadic quantifier hierarchy on k implies that k is of bounded tree-width or clique-width.other characterizations of classes of bounded tree-width in terms of collapses of the monadic quantifier hierarchy to levels above the existential are discussed.
complexity of some problems in positive and related calculi. a problem of recognizing important properties of propositional calculi is considered, and complexity bounds for some decidable properties are found. for a given logical system l, a property p of logical calculi is called decidable over l if there is an algorithm which for any finite set ax of new axiom schemes decides whether the calculus l + ax has the property p or not. in maksimova and voronkov (bull symbol. logic 6 (2000) 118) the complexity of tabularity, pretabularity, and interpolation problems over the intuitionistic logic (int) and over modal logic s4 was studied.in the present paper, positive and positively axiomatizable calculi are investigated. we prove np-completeness of tabularity, dp-hardness of pretabularity and pspace-completeness of interpolation and projective beth's property over the positive fragment int+ of the intuitionistic logic. some complexity bounds for properties of propositional calculi over the intuitionistic or the minimal logic are found.
lower bounds for some decision problems over c. lower bounds for some explicit decision problems over the complex numbers are given. the decision problems considered are certain zero-dimensional subsets of nc, and can be assimilated to a countable family of polynomials gi. more precisely, one should decide for input (i,x) if gi(x)=0. a lower bound for deciding if a polynomial gi vanishes at some x can be derived from a uniform lower bound for the evaluation of all f(gi). that bound is obtained by means of an arithmetic invariant of the roots of gi, the newton diagram of f and other known techniques.
context-free insertion-deletion systems. we consider a class of insertion-deletion systems which have not been investigated so far, those without any context controlling the insertion-deletion operations. rather unexpectedly, we found that context-free insertion-deletion systems characterize the recursively enumerable languages. moreover, this assertion is valid for systems with only one axiom, and also using inserted and deleted strings of a small length. as direct consequences of the main result we found that set-conditional insertion-deletion systems with two axioms generate any recursively enumerable language (this solves an open problem), as well as that membrane systems with one membrane having context-free insertion-deleletion rules without conditional use of them generate all recursively enumerable languages (this improves an earlier result). some open problems are also formulated.
minimizing finite automata is computationally hard. it is known that deterministic finite automata (dfas) can be algorithmically minimized, i.e., a dfa m can be converted to an equivalent dfa m' which has a minimal number of states. the minimization can be done efficiently (in: z. kohavi (ed.), theory of machines and computations, academic press, new york, 1971, pp. 189-196). on the other hand, it is known that unambiguous finite automata and nondeterministic finite automata can be algorithmically minimized too, but their minimization problems turn out to be np-complete and pspace-complete, respectively (siam j. comput. 22(6) (1993) 1117-1141). in this paper, the time complexity of the minimization problem for two restricted types of finite automata is investigated. these automata are nearly deterministic, since they only allow a small amount of nondeterminism to be used. the main result is that the minimization problems for these models are computationally hard, namely np-complete. hence, even the slightest extension of the deterministic model towards a nondeterministic one, e.g., allowing at most one nondeterministic move in every accepting computation or allowing two initial states instead of one, results in computationally intractable minimization problems.
on two-way communication in cellular automata with a fixed number of cells. the effect of adding two-way communication to k cells one-way cellular automata (kc-ocas) on their size of description is studied, kc-ocas are a parallel model for the regular languages that consists of an array of k identical deterministic finite automata (dfas), called cells, operating in parallel. each cell gets information from its right neighbor only. in this paper, two models with different amounts of two-way communication are investigated. both models always achieve quadratic savings when compared to dfas. when compared to a one-way cellular model, the result is that minimum two-way communication can achieve at most quadratic savings whereas maximum two-way communication may provide savings bounded by a polynomial of degree k.
model checking restricted sets of timed paths. in this paper, we study the complexity of model-checking formulas of four important real-time logics (tptl, mtl, mitl, and tctl) over restricted sets of timed paths. the classes of restricted sets of timed paths that we consider are (i) a single finite (or ultimately periodic) timed path, (ii) an infinite set of finite (or infinite) timed paths defined by a finite (or ultimately periodic) path in a region graph, (iii) an infinite set of finite (or infinite) timed paths defined by a finite (or ultimately periodic) path in a zone graph.several results are quite negative: tptl and mtl remain undecidable along region-and zone-paths. on the other hand, we obtained ptime algorithms for model-checking tctl along a region path, and for mtl along a single timed path.
hasse diagrams for classes of deterministic bottom-up tree-to-tree-series transformations. the relationship between classes of tree-to-tree-series and o-tree-to-tree-series transformations computed by restricted deterministic bottom-up weighted tree transducers is investigated. essentially, these transducers are deterministic bottom-up tree series transducers, except that the former are defined over monoids whereas the latter are defined over semirings and only use the multiplicative monoid thereof. in particular, the common restrictions of nondeletion, linearity, totality, and homomorphism can equivalently be defined for deterministic bottom-up weighted tree transducers.using well-known results of classical tree transducer theory and also new results on deterministic weighted tree transducers, classes of tree-to-tree-series and o-tree-to-tree-series transformations computed by restricted deterministic bottom-up weighted tree transducers are ordered by set inclusion. more precisely, for every commutative monoid and all sensible combinations of the above mentioned restrictions, the inclusion relation of the classes of tree-to-tree-series and o-tree-to-tree-series transformations is completely conveyed by means of hasse diagrams.
compositions of tree series transformations. tree series transformations computed by bottom-up and top-down tree series transducers are called bottom-up and top-down tree series transformations, respectively. (functional) compositions of such transformations are investigated. it turns out that the class of bottom-up tree series transformations over a commutative and complete semiring is closed under left-composition with linear bottom-up tree series transformations and right-composition with boolean deterministic bottom-up tree series transformations. moreover, it is shown that the class of top-down tree series transformations over a commutative and complete semiring is closed under right-composition with linear, nondeleting top-down tree series transformations. finally, the composition of a boolean, deterministic, total top-down tree series transformation with a linear top-down tree series transformation is shown to be a top-down tree series transformation.
genomic distances under deletions and insertions. as more and more genomes are sequenced, evolutionary biologists are becoming increasingly interested in evolution at the level of whole genomes, in scenarios in which the genome evolves through insertions, deletions, and movements of genes along its chromosomes. in the mathematical model pioneered by sankoff and others, a unichromosomal genome is represented by a signed permutation of a multiset of genes; hannenhalli and pevzner showed that the edit distance between two signed permutations of the same set can be computed in polynomial time when all operations are inversions. el-mabrouk extended that result to allow deletions (or conversely, a limited form of insertions which forbids duplications). in this paper, we extend el-mabrouk's work to handle duplications as well as insertions and present an alternate framework for computing (near) minimal edit sequences involving insertions, deletions, and inversions. we derive an error bound for our polynomial-time distance computation under various assumptions and present preliminary experimental results that suggest that performance in practice may be excellent, within a few percent of the actual distance.
a tight analysis and near-optimal instances of the algorithm of anderson and woll. this paper shows an asymptotically tight analysis of the certified write-all algorithm called awt that was introduced by anderson and woll, siam j. comput. 26 (1997) 1277, and a method for creating near-optimal instances of the algorithm. this algorithm is the best known deterministic algorithm that can be used to simulate n synchronous parallel processors on n asynchronous processors. the algorithm is instantiated with q permutations on {1,...,q}, where q can be chosen from a wide range of values. when implementing a simulation on a specific parallel system with n processors, one would like to select the best possible value of q and the best possible q permutations, in order to maximize the efficiency of the simulation.this paper shows that work complexity of any instance of awt is θ (q2/c ċ n1+logq(c/q)), where q is the number of permutations selected, and c is a value related to their combinatorial properties. the choice of q turns out to be critical for obtaining an instance of the awt algorithm with near-optimal work. for any ε > 0, and any large enough n, work of any instance of the algorithm must be at least n1+(1+n)√2 ln ln n/ln n. under certain conditions, however, that q is about e√1/2 ln n ln ln n and for infinitely many large enough n, this lower bound can be nearly attained by instances of the algorithm that use certain q permutations and have work at most n1+(1+n)√2 ln ln n/ln n. the paper also shows a penalty for not selecting q well. when q is significantly away from e√1/2 ln n ln ln n, then work of any instance of the algorithm with this displaced q must be considerably higher than otherwise.
on the complexity of typechecking top-down xml transformations. we investigate the typechecking problem for xml transformations: statically verifying that every answer to a transformation conforms to a given output schema, for inputs satisfying a given input schema. as typechecking quickly turns undecidable for query languages capable of testing equality of data values, we return to the limited framework where we abstract xml documents as labeled ordered trees. we focus on simple top-down recursive transformations motivated by xslt and structural recursion on trees. we parameterize the problem by several restrictions on the transformations (deleting, non-deleting, bounded width) and consider both tree automata and dtds as input and output schemas. the complexity of the typechecking problems in this scenario ranges from ptime to exptime.
tissue p systems. starting from the way the inter-cellular communication takes place by means of protein channels (and also from the standard knowledge about neuron functioning), we propose a computing model called a tissue p system, which processes symbols in a multiset rewriting sense, in a net of cells. each cell has a finite state memory, processes multisets of symbol-impulses, and can send impulses ("excitations") to the neighboring cells. such cell nets are shown to be rather powerful: they can simulate a turing machine even when using a small number of cells, each of them having a small number of states. moreover, in the case when each cell works in the maximal manner and it can excite all the cells to which it can send impulses, then one can easily solve the hamiltonian path problem in linear time. a new characterization of the parikh images of etol languages is also obtained in this framework. besides such basic results, the paper provides a series of suggestions for further research.
on the computational complexity of reachability in 2d binary images and some basic problems of 2d digital topology. we study the computational complexity of some well-known problems of 2d digital topology. we prove that all considered problems (including reachability in 2d binary images, connectivity, lower homotopy and symmetric homotopy) are in logspace. we prove that reachability in 2d binary images and some other problems are nc1-hard. finally, we prove that most of the considered problems are not in ac0.
membrane systems with carriers. a membrane system is a model of computation which is inspired by some basic features of biological membranes. in this paper we consider another biologically inspired notion, viz., the notion of a carrier (or vehicle), as, e.g., used in gene cloning. we investigate the power of membrane systems where the rules for the evolving of objects are replaced by the rules that carry objects (by vehicles) through membranes. it turns out that these systems (even with a small number of membranes, a small number of carriers, and a small number of passengers taken by carriers) are computationally universal.
finite derivation type for rees matrix semigroups. this paper introduces the topological finiteness condition finite derivation type (fdt) on the class of semigroups. this notion is naturally extended from the monoid case. with this new concept we are able to prove that if a rees matrix semigroup m[s; i, j; p] has fdt then the semigroup s also has fdt. given a monoid s and a finitely presented rees matrix semigroup m[s; i, j; p] we prove that if the ideal of s generated by the entries of p has fdt, then so does m[s; i, j; p]. in particular, we show that, for a finitely presented completely simple semigroup m, the rees matrix semigroup m = m[s; i, j; p] has fdt if and only if the group s has fdt.
diffusion without false rumors: on propagating updates in a byzantine environment. we study how to efficiently diffuse updates to a large distributed system of data replicas, some of which may exhibit arbitrary (byzantine) failures. we assume that strictly fewer than t replicas fail, and that each update is initially received by at least t correct replicas. the goal is to diffuse each update to all correct replicas while ensuring that correct replicas accept no updates generated spuriously by faulty replicas. to achieve this, each correct replica further propagates an update only after receiving it from at least t others. in this way, no correct replica will ever propagate or accept an update that only faulty replicas introduce, since it will receive that update from only the t - 1 faulty replicas.we provide the first analysis of diffusion protocols for such environments. this analysis is fundamentally different from known analyses for the benign case due to our treatment of fully byzantine failures--which, among other things, precludes the use of digital signatures for authenticating forwarded updates. we propose two measures that characterize the efficiency of diffusion algorithms, delay and fan-in, and prove general lower bounds with regards to these measures. we then provide a family of diffusion algorithms that have nearly optimal delay/fan-in product.
a simulation of cellular automata on hexagons by cellular automata on rings. we consider cellular automata on cayley graphs and compare their computational power according to their topology. we prove that cellular automata de)ned over a hexagonal grid can be simulated by cellular automata over a ring.
ideal models of spaces. ideal domains have an elementary order theoretic structure: every element is either compact or maximal. despite this, we establish that (1) they can model any space currently known to possess a countably based model, and (2) the metric spaces with ideal models are exactly the completely metrizable spaces.
minimal invariant sets in a vertex-weighted graph. a weighting of vertices of a graph is admissible if there exists an edge weighting such that the weight of each vertex equals the sum of weights of its incident edges. given an admissible vertex weighting of a graph, an invariant set is an edge set such that the sum of the weights of its edges is the same for every edge weighting, and a nonempty invariant set is minimal if none of its nonempty proper subsets is an invariant set. it is easily seen that every nonempty invariant set is a disjoint union of minimal invariant sets. a graphical characterisation of minimal invariant sets in a bipartite graph is known both in the case the vertex weights are reals and in the case the vertex weights are nonnegative reals. we shall state a graphical characterisation of minimal invariant sets in an arbitrary vertex-weighted graph. moreover, we give a linear algorithm to test an invariant set for minimality. finally, we state a complete axiomatisation of invariant sets and give a polynomial algorithm to find a set of minimal invariant sets that completely characterise the set of all invariant sets.
the regular spaces with countably based models. the regular spaces which may be realized as the set of maximal elements in an ω-continuous dcpo are the polish spaces. in addition, we give a new and conceptually simple model for complete metric spaces. these results enable us to prove that the probabilistic powerdomain of a countably based model of a metric space always contains a copy of the normalized borel measures in their weak topology, and to establish the hierarchy for countably based models.
quantum evolution of words. quantum evolution of words is defined. the existence of the evolution semigroup is proved. the spectrum of its generator is calculated for right-linear grammars and expansion-contraction evolutions.
entropy as a fixed point. we study complexity and information and introduce the idea that while complexity is relative to a given class of processes, information is process independent: information is complexity relative to the class of all conceivable processes. in essence, the idea is that information is an extension of the concept 'algorithmic complexity' from a class of desirable and concrete processes, such as those represented by binary decision trees, to a class more general that can only in pragmatic terms be regarded as existing in the conception. it is then precisely the fact that information is defined relative to such a large class of processes that it becomes an effective tool for analyzing phenomena in a wide range of disciplines.we test these ideas on the complexity of classical states. a domain is used to specify the class of processes, and both qualitative and quantitative notions of complexity for classical states emerge. the resulting theory is used to give new proofs of fundamental results from classical information theory, to give a new characterization of entropy in quantum mechanics, to establish a rigorous connection between entanglement transformation and computation, and to derive lower bounds on algorithmic complexity. all of this is a consequence of the setting which gives rise to the fixed point theorem: the least fixed point of the copying operator above complexity is information.
()-arbiters for -out-of- mutual exclusion problem. h-out-of-k mutual exclusion is a generalization of the 1-mutual exclusion problem, where there are k units of shared resources and each process requests h (1 ≤ h ≤ k) units at the same time. though k-arbiter has been shown to be a quorum-based solution to this problem, quorums in k-arbiter are much larger than those in the 1-coterie for 1-mutual exclusion. thus, the algorithm based on k-arbiter needs many messages. this paper introduces the new notion that each request uses different quorums depending on the number of units of its request. based on the notion, this paper defines two (h,k)-arbiters for h-out-of-k mutual exclusion: a uniform (h,k)-arbiter and a (k + 1)-cube (h,k)-arbiter. the quorums in each (h,k)-arbiter are not larger than the ones in the corresponding k-arbiter; consequently, it is more efficient to use (h,k)-arbiters than the k-arbiters. a uniform (h,k)-arbiter is a generalization of the majority coterie for 1-mutual exclusion. a (k + 1)-cube (h,k)-arbiter is a generalization of square grid coterie for 1-mutual exclusion.
measuring the probabilistic powerdomain. in this paper we initiate the study of measurements on the probabilistic powerdomain. we show how measurements on an underlying domain naturally extend to its probabilistic powerdomain, so that the kernel of the extension consists of exactly those normalized measures on the kernel of the measurement on the underlying domain. this result is combined with now-standard results from the theory of measurements to obtain a new proof that the fixed point associated with a weakly hyperbolic ifs with probabilities is the unique invariant measure whose support is the attractor of the underlying ifs.
learning power and language expressiveness. the topic of the present work is to study the relationship between the power of the learning algorithms on the one hand, and the expressive power of the logical language which is used to represent the problems to be learned on the other hand. the central question is whether enriching the language results in more learning power. in order to make the question relevant and nontrivial, it is required that both texts (sequences of data) and hypotheses (guesses) be translatable from the "rich" language into the "poor" one. the issue is considered for several logical languages suitable to describe structures whose domain is the set of natural numbers. it is shown that enriching the language does not give any advantage for those languages which define a monadic second-order language being decidable in the following sense: there is a fixed interpretation in the structure of natural numbers such that the set of sentences of this extended language true in that structure is decidable. but enriching the original language even by only one constant gives an advantage if this language contains a binary function symbol (which will be interpreted as addition). furthermore, it is shown that behaviourally correct learning has exactly the same power as learning in the limit for those languages which define a monadic second-order language with the property given above, but has more power in case of languages containing a binary function symbol. adding the natural requirement that the set of all structures to be learned is recursively enumerable, it is shown that it pays off to enrich the language of arithmetics for both finite learning and learning in the limit, but it does not pay off to enrich the language for behaviourally correct learning.
unifying logic, topology and learning in parametric logic. many connections have been established between learning and logic, or learning and topology, or logic and topology. still, the connections are not at the heart of these fields. each of them is fairly independent of the others when attention is restricted to basic notions and main results. we show that connections can actually be made at a fundamental level, and result in a logic with parameters that needs topological notions for its early developments, and notions from learning theory for interpretation and applicability.one of the key properties of first-order logic is that the classical notion of logical consequence is compact. we generalize the notion of logical consequence, and we generalize compactness to β-weak compactness where β is an ordinal. the effect is to stratify the set of generalized logical consequences of a theory into levels, and levels into layers. deduction corresponds to the lower layer of the first level above the underlying theory, learning with less than β mind changes to layer β of the first level, and learning in the limit to the first layer of the second level. refinements of borel-like hierarchies provide the topological tools needed to develop the framework.
analysis of security protocols as open systems. we propose a methodology for the formal analysis of security protocols. this originates from the observation that the verification of security protocols can be conveniently treated as the verification of open systems, i.e. systems which may have unspecified components. these might be used to represent a hostile environment wherein the protocol runs and whose behavior cannot be predicted a priori. we define a language for the description of security protocols, namely crypto-ccs, and a logical language for expressing their properties. we provide an effective verification method for security protocols which is based on a suitable extension of partial model checking. indeed, we obtain a decidability result for the secrecy analysis of protocols with a finite number of sessions, bounded message size and new nonce generation.
boolean restriction categories and taut monads. a boolean category is a restriction category if and only if it has one exception and all morphisms are deterministic. in the category of sets, taut monads are precisely the boolean ones. it follows that collection monad types in haskell inherit an assertion calculus based on dynamic logic.
efficient iteration in admissible combinatorial classes. the exhaustive generation of combinatorial objects has a vast range of practical applications and is a common theme in the combinatorial research field. but most previous works in this area concentrate in the efficient generation of particular families of combinatorial objects. the novel approach of the work presented here is to provide efficient generic algorithms, where the input is not just the size n of the objects to be generated but a finite specification of the combinatorial class whose objects we want to list. since the algorithms are generic, they do not exploit any particular feature of the class to be generated; nevertheless, they work in constant amortized time per generated object, that is, they generate all n objects of a given size in θ(n) time. these algorithms are useful for both rapid prototyping and for inclusion into general purposes libraries because of their flexibility, with only a relatively modest penalty on efficiency. furthermore, the framework presented in this paper nicely combines with the framework developed by flajolet et al. for the enumeration and random generation of combinatorial objects, and with the framework developed by the authors for the unranking of combinatorial objects.
hard variants of stable marriage. the stable marriage problem and its many variants have been widely studied in the literature (gusfield and irving, the stable marriage problem: structure and algorithms, mit press, cambridge, ma, 1989; roth and sotomayor, two-sided matching: a study in game-theoretic modeling and analysis, econometric society monographs, vol. 18, cambridge university press, cambridge, 1990; knuth, stable marriage and its relation to other combinatorial problems, crm proceedings and lecture notes, vol. 10, american mathematical society, providence, ri, 1997), partly because of the inherent appeal of the problem, partly because of the elegance of the associated structures and algorithms, and partly because of important practical applications, such as the national resident matching program (roth, j. political economy 92(6) (1984) 991) and similar large-scale matching schemes. here, we present the first comprehensive study of variants of the problem in which the preference lists of the participants are not necessarily complete and not necessarily totally ordered. we show that, under surprisingly restrictive assumptions, a number of these variants are hard, and hard to approximate. the key observation is that, in contrast to the case where preference lists are complete or strictly ordered (or both), a given problem instance may admit stable matchings of different sizes. in this setting, examples of problems that are hard are: finding a stable matching of maximum or minimum size, determining whether a given pair is stableeven if the indifference takes the form of ties on one side only, the ties are at the tails of lists, there is at most one tie per list, and each tie is of length 2; and finding, or approximating, both an `egalitarian' and a `minimum regret' stable matching. however, we give a 2-approximation algorithm for the problems of finding a stable matching of maximum or minimum size. we also discuss the significant implications of our results for practical matching schemes.
the convergence of functions to fixedpoints of recursive definitions. the classical method for constructing the least fixedpoint of a recursive definition is to generate a sequence of functions whose initial element is the totally undefined function and which converges to the desired least fixedpoint. this method, due to kleene, cannot be generalized to allow the construction of other fixedpoints. in this paper we present an alternate definition of convergence and a new fixedpoint access method of generating sequences of functions for a given recursive definition. the initial function of the sequence can be an arbitrary function, and the sequence will always converge to a fixedpoint that is "close" to the initial function. this defines a monotonic mapping from the set of partial functions onto the set of all fixedpoints of the given recursive definition.
some results on hahn-banach-type theorems for continuous d-cones. like the extended non-negative reals r+ equipped with the scott topology, there are other real topological cones such that the specialisation order yields a directed complete partially ordered set (dcpo). we will call them d-cones. further examples are the extended probabilistic powerdomain, the set of all lower semicontinuous functions f : x ->r+ for any topological space x and arbitrary products of given d-cones. the dual cone c* for a given d-cone c consists of all linear continuous functions &lgr; :c -> r+. with respect to the pointwise order, addition and scalar multiplication the dual cone becomes also a d-cone. we are interested in obtaining results with our concept of d-cones that are comparable to hahn-banach-type theorems in functional analysis. indeed, we can prove an extension theorem and a separation theorem for the continuous d-cones. in particular, the second implies that the elements of the dual cone c* separate the points of c. as a consequence of the extension theorem, we obtain a sum theorem for continuous d-cones. we will give some suffcient conditions when the previous examples of d-cones are continuous and have an additive way-below relation
ramsey numbers for tournaments. the ramsey number r(d1,...,dk) of acyclic directed graphs d1,...,dk is defined as the largest integer r for which there exists a tournament t = (v, a) on r vertices with a k-coloring &fgr; : a &rarr; {1,...,k} of the are set a such that no dt occurs in color i for any i &egr; {1,...,k} . we discuss recursive techniques to compute r(d1,...,dk) in the case where there are paths and/or stars among the dr in particular, solving a problem of bialostocki and dierker [congr. numer. 47 (1985) 119-123], we prove that r(d1d2)= r(d1)&bull;r(d2)holds if dt is transistive and d2 = sn is an out-going star on n vertices. our main result is an asymptotic formula for r(d1,...,d1, sn) where the digraphs d1,..., dk are fixed arbitrarily and n&rarr;(infinity sign).
parameterized graph separation problems. we consider parameterized problems where some separation property has to be achieved by deleting as few vertices as possible. the following five problems are studied: delete k vertices such that (a) each of the given l terminals is separated from the others, (b) each of the given l pairs of terminals is separated, (c) exactly l vertices are cut away from the graph, (d) exactly l connected vertices are cut away from the graph, (e) the graph is separated into at least l components. we show that if both k and l are parameters, then (a), (b) and (d) are fixed-parameter tractable, while (c) and (e) are w[1]-hard.
codes and equations on trees. the objective of this paper is to study, by new formal methods, the notion of tree code introduced by m. nivat in \cite{n92}. in particular we introduce the notion of stability for sets of trees closed under concatenation. this allows us to give a characterization of tree codes which is very close to the algebraic characterization of word codes in terms of free monoids. we further define the stable hull of a set of trees and derive a defect theorem for trees, which generalizes the analogous result for words. as a consequence we obtain some properties of tree codes having two elements. moreover we propose a new algorithm to test whether a finite set of trees is a tree code. the running time of the algorithm is polynomial in the size of the input. we also introduce the notion of tree equation as a complementary point of view to tree codes. the main problem emerging in this approach is to decide the satisfiability of tree equations: it is a special case of second order unification, and it remains still open.
parameterized coloring problems on chordal graphs. in the precoloring extension problem (prext) a graph is given with some of the vertices having preassigned colors and it has to be decided whether this coloring can be extended to a proper coloring of the graph with the given number of colors. two parameterized versions of the problem are studied in the paper: either the number of precolored vertices or the number of colors used in the precoloring is restricted to be at most k. we show that for chordal graphs these problems are polynomial-time solvable for every fixed k, but w[1]-hard if k is the parameter. for a graph class f, let f + ke (resp., f + kv) denote those graphs that can be made to be a member of f by deleting at most k edges (resp., vertices). we investigate the connection between prext in f (with the two parameters defined above) and the coloring of f + ke, f + kv graphs (with k being the parameter). answering an open question of leizhen cai [parameterized complexity of vertex colouring, discrete appl. math. 127 (2003) 415-429], we show that coloring chordal+ke graphs is fixed-parameter tractable.
non-approximability of weighted multiple sequence alignment. we consider a weighted generalization of multiple sequence alignment (msa) with sum-of-pair score. msa without weights is known to be np-complete and can be approximated within a constant factor, but it is unknown whether it has a polynomial time approximation scheme. weighted multiple sequence alignment (wmsa) can be approximated within a factor of o(log2n) where n is the number of sequences.we prove that wmsa alignment is max jnp-hard and establish a numerical lower bound on its approximability, namely 324/323 - ε this lower bound is obtained already for the simple binary weighted case where the weights are restricted to 0 and 1. furthermore, we show that wmsa and its restriction to binary weights can be approximated to the same degree.
minimum sum multicoloring on the edges of trees. the edge multicoloring problem is that given a graph g and integer demands x (e) for every edge e, assign a set of x(e) colors to edge e, such that adjacent edges have disjoint sets of colors. in the minimum sum edge multicoloring problem the finish time of an edge is defined to be the highest color assigned to it. the goal is to minimize the sum of the finish times. the main result of the paper is a polynomial-time approximation scheme for minimum sum multicoloring the edges of trees. we also show that the problem is strongly np-hard for trees, even if every demand is at most 2.
the intractability of computing the hamming distance. given a string x and a language l, the hamming distance of x to l is the minimum hamming distance of x to any string in l. the edit distance of a string to a language is analogously defined.first, we prove that there is a language in ac0 such that both hamming and edit distance to this language are hard to approximate; they cannot be approximated with factor o(n(1/3)-ε), for any ε > 0, unless p = np (n denotes the length of the input string).second, we show the parameterized intractability of computing the hamming distance. we prove that for every t ∈ n there exists a language in ac0 for which computing the hamming distance is w[t]-hard. moreover, there is a language in p for which computing the hamming distance is wp-hard.then we show that the problems of computing the hamming distance and of computing the edit distance are in some sense equivalent by presenting approximation ratio preserving reductions from the former to the latter and vice versa.finally, we define hamp to be the class of languages to which the hamming distance can efficiently, i.e. in polynomial time, be computed. we show some properties of the class hamp. on the other hand, we give evidence that a characterization in terms of automata or formal languages might be difficult.
on computing the coefficients of bivariate holonomic formal series. in this work, we study the problem of computing the coefficients of holonomic formal series in two commuting variables. given a formal series φ(x, y) = σn,k ≥ 0 cnkxnyk specified by a holonomic system σj=0d1 pj(x, y)∂xjφ = 0 and σj=0d2qj(x, y)∂yjφ = 0 with a suitable finite set of intial conditions {[xayb]φ(x, y)}, we show that the coefficient [xiyj]φ(x, y) can be computed in time o(i + j) under the uniform cost criterion.
a new framework for addressing temporal range queries and some preliminary results. given a set of n objects, each characterized by d attributes specified at m fixed time instances, we are interested in the problem of designing space efficient indexing structures such that a class of temporal range search queries can be handled efficiently. when m = 1, our problem reduces to the d-dimensional orthogonal search problem. we establish efficient data structures to handle several classes of the general problem. our results include a linear size data structure that enables a query time of o(log n log m + f) for one-sided queries when d = 1, where f is the number of objects satisfying the query. a similar result is shown for counting queries. we also show that the most general problem can be solved with a polylogarithmic query time using superlinear space data structures.
quantum and classical tradeoffs. we initiate the study of quantifying the quantumness of a quantum circuit by the number of gates that do not preserve the computational basis, as a means to understand the nature of quantum algorithmic speedups. intuitively, a reduction in the quantumness requires an increase in the amount of classical computation, thus giving a "quantum and classical tradeoff'.in this paper we present two results on this measure of quantumness. the first gives almost matching upper and lower bounds on the question: "what is the minimum number of non-basis-preserving gates required to generate a good approximation to a given state". this question is the quantum analogy of the following classical question, "how many fair coins are needed to generate a given probability distribution", which was studied and resolved by knuth and yao in 1976 [algorithms and complexity: new directions and recent results, academic press, new york, 1976, pp. 357-428]. our second result shows that any quantum algorithm that solves grover's problem of size n using k queries and l levels of non-basis-preserving gates must have kl = ω(n).
asynchronous deterministic rendezvous in graphs. two mobile agents (robots) having distinct labels and located in nodes of an unknown anonymous connected graph have to meet. we consider the asynchronous version of this well-studied rendezvous problem and we seek fast deterministic algorithms for it. since in the asynchronous setting, meeting at a node, which is normally required in rendezvous, is in general impossible, we relax the demand by allowing meeting of the agents inside an edge as well. the measure of performance of a rendezvous algorithm is its cost: for a given initial location of agents in a graph, this is the number of edge traversals of both agents until rendezvous is achieved. if agents are initially situated at a distance d in an infinite line, we show a rendezvous algorithm with cost o(d|lmin|2) when d is known and o((d + |lmax|)3) if d is unknown, where |lmin| and |lmax| are the lengths of the shorter and longer label of the agents, respectively. these results still hold for the case of the ring of unknown size, but then we also give an optimal algorithm of cost o(n|lmin|), if the size n of the ring is known, and of cost o(n|lmax|), if it is unknown. for arbitrary graphs, we show that rendezvous is feasible if an upper bound on the size of the graph is known and we give an optimal algorithm of cost o(d|lmin|) if the topology of the graph and the initial positions are known to agents.
design of abstract domains using first-order logic. in this paper we propose a simple framework based on first-order logic, for the design and decomposition of abstract domains for static analysis. an assertion language is chosen that specifies the properties of interest, and abstract domains are defined to be suitably chosen sets of assertions. composition and decomposition of abstract domains is facilitated by their logical specification in first-order logic. in particular, the operations of reduced product and disjunctive completion are formalized in this framework. moreover, the notion of (conjunctive) factorization of sets of assertions is introduced, that allows one to decompose domains in `disjoint'' parts. we illustrate the use of this framework by studying typical abstract domains for ground-dependency and aliasing analysis in logic programming.
shuffle on trajectories: syntactic constraints. we introduce and investigate new methods to define parallel composition of words and languages. the operation of parallel composition leads to new shuffle-like operations defined by syntactic constraints on the usual shuffle operation. the approach is applicable to concurrency, providing a method to define parallel composition of processes. it is also applicable to parallel computation. the operations are introduced using a uniform method based on the notion of trajectory. as a consequence, we obtain a very intuitive geometrical interpretation of the parallel composition operation. these operations lead in a natural way to a large class of semirings. the approach is amazingly flexible, diverse concepts from the theory of concurrency can be introduced and studied in this framework. for instance, we provide examples of applications to fairness property and to parallelization of non-context-free languages in terms of context-free and even regular languages. this paper concetrates on syntactic constraints. semantic constraints will be dealt with in a forthcoming contribution.
categorical foundations for randomly timed automata. the general theory of randomly timed automata is developed: starting with the practical motivation and presentation of the envisaged notion, the categorical theory of minimization, aggregation, encapsulation, interconnection and realization of such automata is worked out. all these constructions are presented universally: minimization and realization as adjunctions, aggregation as product, interconnection as cartesian lifting, and encapsulation as co-cartesian lifting. stochastic timed automata are shown to be a particular case of randomly timed automata. the notion of stochastic timed automaton is shown to be too restrictive to establish a self contained theory of combination and realization.
decision problems for semi-thue systems with a few rules. we show that the accessibility problem, the common descendant problem, the termination problem and the uniform termination problem are undecidable for 3-rules semi-thue systems. as a corollary we obtain the undecidability of the post correspondence problem for 7 rules.
linear programs in a simple reversible language. very simple reversible programming languages can be useful for the study of reversible transformations. for this purpose we define simple reversible language (srl), a very simple reversible language, and analyse its properties. the language srl is similar to the "loop" languages that have been used by several authors to characterise the set of primitive recursive functions. there are, however, important differences: srl has domain z instead of n and only reversible programs can be written in srl. the reversibility of linear homogeneous srl programs is related to the fact that the corresponding set of matrices has the algebraic structure of a group. we show that such programs implement exactly the linear transformations corresponding to the group of integer positive modular matrices, while in esrl, an extended version of srl, the set of transformations that can be implemented by linear homogeneous programs corresponds exactly to the group of integer modular matrices.
np-completeness for calculating power indices of weighted majority games. in this paper, we prove that both problems for calculating the banzhaf power index and the shapley-shubik power index for weighted majority games are np-complete.
the accepting power of unary string logic programs. the set of programs written in a small subset of pure prolog called us is shown to accept exactly the class of regular languages. the language us contains only unary predicates and unary function symbols. also, a subset of us called rus is shown to be equivalent to us in its ability in accepting the class of regular languages. every clause in rus contains at most one function symbol in the head and at most one literal with no function symbol in the body. the result is very close to a theorem of matos (tcs april 1997) but our proof is quite different. though us and rus have the same accepting power, their conciseness of expression is dramatically different: if we try to write an rus program equivalent to a us program, the number of predicates in the rus program could be o(22n2) where n is the sum of the number of predicates and the number of functors in the us program. copyright 2001 elsevier science b.v.
substitution in non-wellfounded syntax with variable binding. inspired from the recent developments in theories of non-wellfounded syntax (coinductively defined languages) and of syntax with binding operators, the structure of algebras of wellfounded and non-wellfounded terms is studied for a very general notion of signature permitting both simple variable binding operators as well as operators of explicit substitution. this is done in an extensional mathematical setting of initial algebras and final coalgebras of endofunctors on a functor category. the main technical tool is a novel concept of heterogeneous substitution systems.
an extensional treatment of lazy data flow deadlock. in an extensional treatment of dataflow deadlock [wa81] wadge introduced an elegant non operational test for proving that many of kahn''s data flow message passing networks [ka74] must be free of deadlock; a test that "should extend to a much wider context" in the study of program correctness. such a context has now been provided with the introduction of partial metric spaces [ma92]. these spaces can be used to describe semantic domains such as those used in lazy data flow languages [w &a85]. this paper develops wadge''s ideas on establishing an extensional theory of program correctness by using partial metric spaces to give a non operational treatment of lazy data flow deadlock. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
dot-depth, monadic quantifier alternation, and first-order closure over grids and pictures. this paper presents results from two different areas. the first area is monadic second-order logic (mso) over finite structures, in particular over the so-called grids. these are structures whose elements can be arranged as a matrix and which have two binary relations corresponding to vertical and horizontal successors. for this logic, we study the expressive power of the alternation of existential and universal monadic second-order quantifiers, i.e., set quantifiers. in matz et al. (information and computation, lics' 97, 1999, to appear) it had been shown that these alternations cannot be limited to a fixed number without loss of expressiveness. in this paper, we strengthen this result in several ways. firstly, we show that there are mso formulas that have a very restricted form of k+1 set quantifiers but are not equivalent to a formula with k quantifiers. secondly, we show that if we fix the number of such alternations, the expressive power of formulas that start with a block of universal quantifiers differs from the power of those that start with an existential one this was previously known only for coloured grids. thirdly, we investigate how an additional prefix of first-order (i.e., element) quantifiers influences the expressive power of mso formulas. the second area that this paper is concerned with is two-dimensional formal language theory. we study how the alternation of (first- and monadic second-order) quantifications, on the one hand, relates to the dot-depth measure of two-dimensional (i.e., picture) languages, on the other hand. that measure is the two-dimensional version of the classical notion of dot-depth for (one-dimensional) starfree word languages. we show that the hierarchy induced by this dot-depth cuts through the hierarchy given by monadic second-order quantifications. in particular, beyond each level of the monadic second-order alternation hierarchy, there is a starfree picture language.
finite and infinite pseudorandom binary words. we present a notion of pseudorandomness for finite binary words based on the measure of the well distribution in arithmetic progressions and of the correlations. we give several examples and we focuss our interest on two arithmetical constructions connected to the legendre symbol and the liouville function.
the syntactic prediction with token automata: application to handias system. this paper presents a finite-state machine to compute the probability of a word appearance when one knows the left syntactic context. we memorize the token number of words in a dictionary and the token number of syntactic categories on finite-state automata. we compute a word probability with these numbers. if we have not predicted the awaited word , we take into account the first letter for a new prediction, and so on. this system has been implemented on a prototype software for disabled communication aid, called handias and it is a part of the research project cnhl of the li, the computer laboratory of the tours university. copyright 2001 elsevier science b.v.
algorithms for pattern matching and discovery in rna secondary structure. text-indexing structures provide significant advantages in the solution of many problems related to string analysis and comparison, and are nowadays widely used in the analysis of biological sequences. in this paper, we present some applications of affix trees to problems of exact and approximate pattern matching and discovery in rna sequences. by allowing bidirectional search for symmetric patterns in the sequences, affix trees permit to discover and locate in the sequences patterns describing not only sequence regions, but also containing information about the secondary structure that a given region could form, with improvements in terms of theoretical and practical efficiency over the existing methods. the search can be either exact or approximate, where the approximation can be defined simultaneously both for the sequence and the structure of patterns. the approach presented in this paper could provide significant help in the analysis of rna sequences, where the functional motifs often involve not only sequence, but also the structural constraints.
trade-off results for connection management. a connection management protocol establishes and handles a connection between two hosts across a wide-area network to allow reliable message delivery. we continue the previous work of kleinberg et al. (proceedings of the 3rd israel symposium on the theory of computing and systems, january (1995), pp. 258-267) to study the precise impact of the level of synchrony provided by the processors' clocks on the performance of connection management protocols, under common assumptions on the pattern of failures of the network and the host nodes. two basic timing models are assumed: clocks that exhibit a certain kind of a drift from the rate of real time, and clocks that display a pattern of synchronization to real time. we consider networks that can duplicate and reorder messages, and nodes that can crash. we are interested in simultaneously optimizing the following performance parameters: the message delivery time, which is the time required to deliver a message, and the quiescence time, which is the time that elapses between periods of quiescence, in which the receiving host deletes all earlier connection records and returns to an initial state. we establish natural trade-offs between message delivery time and quiescence time, in the form of tight lower and upper bounds, for each combination of the timing models and failure types. several of our trade-off results significantly improve upon or extend previous ones shown by kleinberg et al.
weak bisimilarity and regularity of context-free processes is exptime-hard. we show that checking weak bisimulation equivalence of two context-free processes (also called bpa-processes) is exptime-hard, even under the condition that the processes are normed. furthermore, checking weak regularity (finiteness up to weak bisimilarity) for context-free processes is exptime-hard as well. adding a finite control of the minimal non-trivial size of 2 to the bpa process already makes weak bisimilarity undecidable.
encoding transition systems in sequent calculus. intuitionistic and linear logics can be used to specify the operational semantics of transition systems in various ways. we consider here two encodings: one uses linear logic and maps states of the transition system into formulas, and the other uses intuitionistic logic and maps states into terms. in both cases, it is possible to relate transition paths to proofs in sequent calculus. in neither encoding, however, does it seem possible to capture properties, such as simulation and bisimulation, that need to consider all possible transitions or all possible computation paths. we consider augmenting both intuitionistic and linear logics with a proof theoretical treatment of definitions. in both cases, this addition allows proving various judgments concerning simulation and bisimulation (especially for noetherian transition systems). we also explore the use of infinite proofs to reason about infinite sequences of transitions. finally, combining definitions and induction into sequent calculus proofs makes it possible to reason more richly about properties of transition systems completely within the formal setting of sequent calculus.
quantitative program logic and expected time bounds in probabilistic distributed algorithms. in this paper we show how quantitative program logic (morgan et al., acm trans. programming languages systems 18 (1996) 325) provides a formal framework in which to promote standard techniques of program analysis to a context where probability and nondeterminism interact, a situation common to probabilistic distributed algorithms. we show that overall expected time can be formulated directly in the logic and that it can be derived from local properties of components. we illustrate the methods with an analysis of expected running time of the probabilistic dining philosophers (lehmann and ravin, proc 8th annu. acm. symp. on principles of programming languages, acm, new york, 1981, p. 133).
partial correctness for probabilistic demonic programs. recent work in sequential program semantics has produced both an operational (he et al., sci. comput. programming 28(2, 3) (1997) 171-192) and an axiomatic (morgan et al., acm trans. programming languages systems 18(3) (1996) 325-353; seidel et al., tech report prg-tr-6-96, programming research group, february 1996) treatment of total correctness for probabilistic demonic programs, extending kozen's original work (j. comput. system sci. 22 (1981) 328-350; kozen, proc. 15th acm symp. on theory of computing, acm, new york, 1983) by adding demonic nondeterminism. for practical applications (e.g. combining loop invariants with termination constraints) it is important to retain the traditional distinction between partial and total correctness. jones (monograph ecs-lfcs-90-105, ph.d. thesis, edinburgh university, edinburgh, uk, 1990) defines probabilistic partial correctness for probabilistic, but again not demonic programs. in this paper we combine all the above, giving an operational and axiomatic framework for both partial and total correctness of probabilistic and demonic sequential programs; among other things, that provides the theory to support our earlier---and practical---publication on probabilistic demonic loops (morgan, in: jifeng et al. (eds.), proc. bcs-facs seventh refinement workshop, workshops in computing, springer, berlin, 1996. copyright 2001 elsevier science b.v.
almost-certain eventualities and abstract probabilities in the quantitative temporal logic qtl. 'almost-certain eventualities' are liveness properties that hold with probability 1. 'abstract probabilities' in transition systems are those known only to be bounded away from zero and one.vardi (proceedings of the 26th ieee symposium on foundations of computer science, portland, 1985, p. 327) showed that almost-certain properties in linear temporal logic depend only on abstract probabilities rather than on the probabilities' precise values. we discuss the extent to which a similar result holds in the quantitative temporal logic qtl derived from the quantitative modal µ,calculus qmµ (proceedings the formal methods pacific '97, springer, singapore, 1997, also available http://web.comlab.ox.ac.uk/oucl/research/areas/probs/bibliography.html; logic j, igpl 7(6) (1999) 779, http://www3.oup.co.uk/igpl/volume_07/issue_06, http://web.comlab. ox.ac.uk/oucl/research/areas/probs/bibliography.html), and we show how to specialise the logic to these cases. the aim is to provide a simpler calculus than the full logic, one that is in a certain sense complete for proving almost-certain eventualities from abstract-probabilistic assumptions.we concinde by considering the complexity of the specialised logic.
an interpolating theorem prover. we present a method of deriving craig interpolants from proofs in the quantifier-free theory of linear inequality and uninterpreted function symbols, and an interpolating theorem prover based on this method. the prover has been used for predicate refinement in the blast software model checker, and can also be used directly for model checking infinite-state systems, using interpolation-based image approximation.
the generative capacity of block-synchronized context-free grammars. we consider the yield languages of synchronized tree automata, called the synchronized context-free (scf) languages. we show that their language family coincides with the family of etol languages using both studied types of synchronization. furthermore, we examine a generalization of scf grammars, the block-synchronized context-free (bscf) grammars and determine that their generated language family is equal to that of the indexed languages using the same two types of synchronization. however, when the nesting depth of bscf grammars is bounded above by some constant, the generated language family is also equal to the family of et0l languages. this shows that the unbounded nesting depth language family is strictly larger than the bounded nesting depth family, as previously conjectured.
decision tree approximations of boolean functions. decision trees are popular representations of boolean functions. we show that, given an alternative representation of a boolean function f, say as a read-once branching program, one can find a decision tree t which approximates f to any desired amount of accuracy. moreover, the size of the decision tree is at most that of the smallest decision tree which can represent f and this construction can be obtained in quasi-polynomial time. we also extend this result to the case where one has access only to a source of random evaluations of the boolean function f instead of a complete representation. in this case, we show that a similar approximation can be obtained with any specified amount of confidence (as opposed to the absolute certainty of the former case.) this latter result implies proper pac-learnability of decision trees under the uniform distribution without using membership queries.
extended games-chan algorithm for the 2-adic complexity of fcsr-sequences. binary sequences generated by feedback shift registers with carry operation (fcsr) share many of the important properties enjoyed by sequences generated by linear feedback shift registers. we present an fcsr analog of the (extended) games-chan algorithm, which efficiently determines the linear complexity of a periodic binary sequence with period length t = 2n or pn, where p is an odd prime and 2 is a primitive element modulo p2. the algorithm to be presented yields an upper bound for the 2-adic complexity, an fcsr analog of the linear complexity, of a pn-periodic binary sequence.
a time lower bound for satisfiability. we show that a deterministic turing machine with one d-dimensional work tape and random access to the input cannot solve satisfiability in time na for a < √(d + 2)/(d + 1). for conondeterministic machines, we obtain a similar lower bound for any a such that a3 < 1 + a/(d + 1). the same bounds apply to almost all natural np-complete problems known.
sequential algorithms and strongly stable functions. intuitionistic proofs and pcf programs may be interpreted as functions between domains, or as strategies on games. the two kinds of interpretation are inherently different: static vs. dynamic, extensional vs. intentional. it is thus extremely instructive to compare and to connect them. in this article, we investigate the extensional content of the sequential algorithm hierarchy [-]sds introduced by berry and curien. we equip every sequential game [t]sds of the hierarchy with a realizability relation between plays and extensions. in this way, the sequential game [t]sds becomes a directed acyclic graph, instead of a tree. this enables to define a hypergraph [t]hc on the extensions (or terminal leaves) of the game [t]sds. we establish that the resulting hierarchy [-]hc coincides with the strongly stable hierarchy introduced by bucciarelli and ehrhard. we deduce from this a gametheoretic proof of ehrhard's collapse theorem, which states that the strongly stable hierarchy coincides with the extensional collapse of the sequential algorithm hierarchy.
asynchronous games 2: the true concurrency of innocence. in game semantics, the higher-order value passing mechanisms of the λ-calculus are decomposed as sequences of atomic actions exchanged by a player and its opponent. seen from this angle, game semantics is reminiscent of trace semantics in concurrency theory, where a process is identified to the sequences of requests it generates in the course of time. asynchronous game semantics is an attempt to bridge the gap between the two subjects, and to see mainstream game semantics as a refined and interactive form of trace semantics. asynchronous games are positional games played on mazurkiewicz traces, which reformulate (and generalize) the familiar notion of arena game. the interleaving semantics of λ-terms, expressed as innocent strategies, may be analysed in this framework, in the perspective of true concurrency. the analysis reveals that innocent strategies are positional strategies regulated by forward and backward confluence properties. this captures, we believe, the essence of innocence. we conclude the article by defining a non-uniform variant of the λ-calculus, in which the game semantics of a λ-term is formulated directly as a trace semantics, performing the syntactic exploration or parsing of that λ-term.
components as coalgebras: the refinement dimension. this paper characterises refinement of state-based software components modelled as pointed coalgebras for some set endofunctors. the proposed characterisation is parametric on a specification of the underlying behaviour model introduced as a strong monad. this provides a basis to reason about (and transform) state-based software designs. in particular, it is shown how refinement can be applied to the development of the inequational subset of a calculus of generic software components.
complementing unary nondeterministic automata. we compare the nondeterministic state complexity of unary regular languages and that of their complements: if a unary language l has a succinct nondeterministic finite automaton, then nondeterminism is useless in order to recognize its complement, namely, the smallest nondeterministic automaton accepting the complement of l has as many states as the minimum deterministic automaton accepting it. the same property does not hold in the case of automata and languages defined over larger alphabets. we also show the existence of infinitely many unary regular languages for which nondeterminism is useless in their recognition and in the recognition of their complements.
a strip-like tiling algorithm. we extend our previous results on the connection between strip tiling problems and regular grammars by showing that an analogous algorithm is applicable to other tiling problems, not necessarily related to rectangular strips. we find generating functions for monomer and dimer tilings of t- and l-shaped figures, holed and slotted strips, diagonal strips and combinations of them, and show how analogous results can be obtained by using different pieces.
a physicist's approach to number partitioning. the statistical physics approach to the number partioning problem, a classical np-hard problem, is both simple and rewarding. very basic notions and methods from statistical mechanics are enough to obtain analytical results for the phase boundary that separates the "easy-to-solve" from the "hard-to-solve" phase of the npp as well as for the probability distributions of the optimal and sub-optimal solutions. in addition, it can be shown that solving a number portioning problem of size n to some extent corresponds to locating the minimum in an unsorted list of o(2n ) numbers. considering this correspondence it is not surprising that known heuristics for the partitioning problem are not signi4cantly better than simple random search.
aspects of complexity of probabilistic learning under monotonicity constraints. in the setting of learning indexed families, probabilistic learning under monotonicity constraints is more powerful than deterministic learning under monotonicity constraints, even if the probability is close to 1, provided the learning machines are restricted to proper or class preserving hypothesis spaces (cf. meyer, theoret. comput. sci. 185 (1997) 81--128). in this paper, we investigate the relation between probabilistic learning and oracle identification under monotonicity constraints. in particular, we deal with the question how much additional information provided by oracles is necessary for compensating the additional power of probabilistic learning machines. in section 1, we show that k is necessary and sufficient to compensate the additional power of probabilistic learning machines in the case of conservative (monotonic) probabilistic learning with p > 1/2 (p > 2/3), and for strong-monotonic probabilistic learning with 1/2 < p &le; 2/3. in the case of strong-monotonic learning with p, however, every peano-complete oracle is sufficient for compensating the power of probabilistic learning machines. in contrast, the oracle k is not sufficient for compensating the power of conservative and strong-monotonic probabilistic learning with probability p=1/2, and monotonic probabilistic learning with p=2=3. the main result in section 2 is that for each oracle a &le; tk, there exists an indexed family la which is properly conservatively identifiable with p=1/2, and which exactly reflects the turing degree of a, i.e., la is properly conservatively identi/able by an oracle machine m[b] iff a&le;t b. thus, for every oracle a below k, we can construct a learning problem characterizing a within proper conservative learning. however, not every indexed family which is conservatively identifiable with probability p=1/2 reflects the turing degree of an oracle. hence, the conservative probabilistic learning classes are higher structured than the turing degrees below k. finally, we prove that there exist learning problems which are conservatively (monotonically) identifiable with probability p=1/2 (p=2/3), but conservatively (monotonically) identifiable only by oracle machines having access to tot. for strong-monotonic learning, this result does not hold. copyright 2001 elsevier science b.v. all rights reserved.
quantization of games: towards quantum artificial intelligence. we discuss the impact of quantum game theory on information processing and the emerging information society. the framework, that we establish, encompasses various particular models considered in the field of artificial intelligence. this paper provides insight into the following issues: detailed analysis of a quantum algorithm solving newcombs' paradox, the elitzur-vaidman circuit breaker and the metropolis algorithm is presented.
small turing machines and generalized busy beaver competition. let tm(k,l) be the set of one-tape turing machines with k states and l symbols. it is known that the halting problem is decidable for machines in tm(2,3) and tm(3,2). we prove that the decidability of machines in tm(2,4) and tm(3,3) will be difficult to settle, by giving machines in these sets for which the halting problem depends on an open problem in number theory. a machine in tm(5,2) with the same result is already known, and, moreover, this machine is the record holder for the busy beaver competitions: this is the machine in tm(5,2) which halts when starting from a blank tape, making the greatest number of steps and leaving the greatest number of non-blank symbols. we give potential winners for similar generalized busy beaver competitions in tm(2,3), tm(2,4) and tm(3,3).
interfaces as functors, programs as coalgebras - a final coalgebra theorem in intensional type theory. in [p. hancock, a. setzer, interactive programs in dependent type theory, in: p. clote, h. schwichtenberg (eds.), proc. 14th annu. conf. of eacsl, csl'00, fischbau, germany, 21-26 august 2000, vol. 1862, springer, berlin, 2000, pp. 317-331, url 〈citeseer.ist.psu.edu/article/hancock00interactive.html〉 p. hancock, a. setzer, interactive programs and weakly final coalgebras in dependent type theory, in: l. crosilla, p. schuster (eds.), from sets and types to topology and analysis. towards practicable foundations for constructive mathematics, oxford logic guides, clarendon press, 2005, url 〈www.cs.swan.ac.uk/~csetzer/〉] hancock and setzer introduced rules to extend martin-löf's type theory in order to represent interactive programming. the rules essentially reflect the existence of weakly final coalgebras for a general form of polynomial functor. the standard rules of dependent type theory allow the definition of inductive types, which correspond to initial algebras. coalgebraic types are not represented in a direct way. in this article we show the existence of final coalgebras in intensional type theory for these kind of functors, where we require uniqueness of identity proofs (uip) for the set of states s and the set of commands c which determine the functor. we obtain the result by identifying programs which have essentially the same behaviour, viz. are bisimular. this proves the rules of setzer and hancock admissible in ordinary type theory, if we replace definitional equality by bisimulation. all proofs [m. michelbrink, verifications of final coalgebra theorem in: interfaces as functors, programs as coalgebras-a final coalgebra theorem in intensional type theory, 2005, url 〈www.cs.swan.ac.uk/~csmichel/〉] are verified in the theorem prover agda [c. coquand, agda, internet, url 〈www.cs.chalmers.se/~catarina/agda/〉; k. peterson, a programming system for type theory, technical report, s-412 96, chalmers university of technology, göteborg, 1982], which is based on intensional martin-löf type theory.
combined super-/substring and super-/subsequence problems. super-/substring problems and super-/subsequence problems are well-known problems in stringology that have applications in a variety of areas, such as manufacturing systems design and molecular biology. here we investigate the complexity of a new type of such problem that forms a combination of a super-/substring and a super-/subsequence problem. moreover we introduce different types of minimal superstring and maximal substring problems. in particular, we consider the following problems: given a set l of strings and a string s, (i) find a minimal superstring (or maximal substring) of l that is also a supersequence (or a subsequence) of s, (ii) find a minimal supersequence (or maximal subsequence) of l that is also a superstring (or a substring) of s. in addition some non-super-/non-substring and non-super-/nonsubsequence variants are studied. we obtain several np-hardness or even max snp-hardness results and also identify types of "weak minimal" superstrings and "weak maximal" substrings for which (i) is polynomial-time solvable.
a solution to the tennis ball problem. we present a complete solution to the so-called tennis ball problem, which is equivalent to counting the number of lattice paths in the plane that use north and east steps and lie between certain boundaries. the solution takes the form of explicit expressions for the corresponding generating functions.our method is based on the properties of tutte polynomials of matroids associated to lattice paths. we also show how the same method provides a solution to a wide generalization of the problem.
words and forbidden factors. given a finite or infinite word v, we consider the set m(v) of minimal forbidden factors of v. we show that the set m(v) is of fundamental importance in determining the structure of the word v. in the case of a finite word w we consider two parameters that are related to the size of m(w): the first counts the minimal forbidden factors of w and the second gives the length of the longest minimal forbidden factor of w. we derive sharp upper and lower bounds for both parameters. we prove also that the second parameter is related to the minimal period of the word w. we are further interested to the algorithmic point of view. indeed, we design linear time algorithm for the following two problems: (i) given w, construct the set m(w) and, conversely, (ii) given m(w), reconstruct the word w. in the case of an infinite word x, we consider the following two functions: gx that counts, for each n, the allowed factors of x of length n and fx that counts, for each n, the minimal forbidden factors of x of length n. we address the following general problem: what information about the structure of x can be derived from the pair (gx,fx)? we prove that these two functions characterize, up to the automorphism exchanging the two letters, the language of factors of each single infinite sturmian word.
on fine and wilf's theorem for bidimensional words. generalizations of fine and wilf's periodicity theorem are obtained for the case of bidimensional words using geometric arguments. the domains considered constitute a large class of convex subsets of r2 which include most parallelograms. a complete discussion is provided for the parallelogram case.
language-theoretic aspects of dna complematarity. the optimism about the possibilities of dna computing is based on two central issues: the watson-crick complementarity and the massive parallelism of dna strands. while the latter issue renders exhaustive searches possible and thus may settle problems previously considered intractable, the former issue is the cause behind the universality of many models of dna computing. moreover, complementarity can be viewed as a purely language-theoretic operation: undesirable circumstances in a string trigger a transition to the complementary string. this aspect of complementarity is investigated in the present paper, mainly from the point of view of $l$ systems. new types of word sequences will be discovered. sometimes the resulting decision problems are equivalent to well-known open problems from other areas.
the complexity of makespan minimization for pipeline transportation. sptp is a model for the pipeline transportation of petroleum products. it uses a directed graph g, where arcs represent pipes and nodes represent locations. in this paper, we analyze the complexity of finding a minimum makespan solution to sptp. this problem is called sptmp. we prove that, for any fixed ε > 0, there is no η1-ε-approximate algorithm for the sptmp unless p = np, where η is the input size. this result also holds if g is both planar and acyclic. if g is acyclic, then we give a m-approximate algorithm to sptmp, where m is the number of arcs in g.
the category-theoretic solution of recursive program schemes. this paper provides a general account of the notion of recursive program schemes, studying both uninterpreted and interpreted solutions. it can be regarded as the category-theoretic version of the classical area of algebraic semantics. the overall assumptions needed are small indeed: working only in categories with "enough final coalgebras" we show how to formulate, solve, and study recursive program schemes. our general theory is algebraic and so avoids using ordered or metric structures. our work generalizes the previous approaches which do use this extra structure by isolating the key concepts needed to study substitution in infinite trees, including second-order substitution. as special cases of our interpreted solutions we obtain the usual denotational semantics using complete partial orders, and the one using complete metric spaces. our theory also encompasses implicitly defined objects which are not usually taken to be related to recursive program schemes. for example, the classical cantor two-thirds set falls out as an interpreted solution (in our sense) of a recursive program scheme.
on the cell probe complexity of polynomial evaluation. we consider the cell probe complexity of the polynomial evaluation problem with preprocessing of coefficients, for polynomials of degree at most n over a finite field k. we show that the trivial cell probe algorithm for the problem is optimal if k is sufficiently large compared to n. as an application, we give a new proof of the fact that p != ncr - time (o (log n/ log log n) ).
on converting cnf to dnf. we study how big the blow-up in size can be when one switches between the cnf and dnf representations of boolean functions. for a function f : {0, 1}n → {0, 1}, cnfsize(f) denotes the minimum number of clauses in a cnf for f; similarly, dnfsize(f) denotes the minimum number of terms in a dnf for f. for 0 ≤ m ≤ 2n-1, let dnfsize(m, n) be the maximum dnfsize(f) for a function f : {0, 1}n → {0, 1} with cnfsize(f) ≤ m. we show that there are constants c1, c2 ≥ 1 and ε > 0, such that for all large n and all m ∈ [ 1/ε n, 2εn], we have 2n-c1(n/log(m/n)) ≤ dnfsize(m, n) ≤ 2n-c2(n/log(m/n)). in particular, when m is the polynomial nc, we get dnfsize(nc, n) = 2n-θ(c-1(n/log n)).
a termination proof for epsilon substitution using partial derivations. epsilon substitution method introduced by hilbert is a successive approximation process providing numerical realizations from proofs of existential formulas. most convergence (termination) proofs for it use assignments of decreasing ordinals to stages of the process and work only for predicative systems. we describe a new ordinal assignment for the case of first-order arithmetic admitting extension to impredicative systems. it is based on an interpretation of individual epsilon substitutions forming the substitution process as incomplete finite proofs, each encoding a complete but infinite proof.
some results about the markov chains associated to gps and general eas. geiringer's theorem is a statement which tells us something about the limiting frequency of occurrence of a certain individual when a classical genetic algorithm is executed in the absence of selection and mutation. recently poll, stephens, wright and rowe extended the original theorem of geiringer to include the case of variable-length genetic algorithms and linear genetic programming. in the current paper a rather powerful finite population version of geiringer's theorem which has been established recently by mitavskiy is used to derive a schema-based version of the theorem for nonlinear genetic programming with homologous crossover. the theorem also applies in the presence of "node mutation". the corresponding formula in case when "node mutation" is present has been established.the limitation of the finite population geiringer result is that it applies only in the absence of selection. in the current paper we also observe some general inequalities concerning the stationary distribution of the markov chain associated to an evolutionary algorithm in which selection is the last (output) stage of a cycle. moreover we prove an "anti-communism" theorem which applies to a wide class of eas and says that for small enough mutation rate, the stationary distribution of the markov chain modelling the ea cannot be uniform.
a probabilistic polynomial-time process calculus for the analysis of cryptographic protocols. we prove properties of a process calculus that is designed for analysing security protocols. our long-term goal is to develop a form of protocol analysis, consistent with standard cryptographic assumptions, that provides a language for expressing probabilistic polynomial-time protocol steps, a specification method based on a compositional form of equivalence, and a logical basis for reasoning about equivalence.the process calculus is a variant of ccs, with bounded replication and probabilistic polynomial-time expressions allowed in messages and boolean tests. to avoid inconsistency between security and nondeterminism, messages are scheduled probabilistically instead of nondeterministically. we prove that evaluation of any process expression halts in probabilistic polynomial time and define a form of asymptotic protocol equivalence that allows security properties to be expressed using observational equivalence, a standard relation from programming language theory that involves quantifying over all possible environments that might interact with the protocol.we develop a form of probabilistic bisimulation and use it to establish the soundness of an equational proof system based on observational equivalences. the proof system is illustrated by a formation derivation of the assertion, well-known in cryptography, that el gamal encryption's semantic security is equivalent to the (computational) decision diffie-hellman assumption. this example demonstrates the power of probabilistic bisimulation and equational reasoning for protocol security.
on the complexity of finding a local maximum of functions on discrete planar subsets. we study how many values of an unknown integer-valued function f one needs to know in order to find a local maximum of f. we consider functions defined on finite subsets of discrete plane. we prove upper bounds for functions defined on rectangles and present lower bounds for functions defined on arbitrary domains in terms of the size of the domain and the size of its border.
ternary directed acyclic word graphs. given a set s of strings, a dfa accepting s offers a very time-efficient solution to the pattern matching problem over s. the key is how to implement such a dfa in the trade-off between time and space, and especially the choice of how to implement the transitions of each state is critical. bentley and sedgewick proposed an effective tree structure called ternary trees. the idea of ternary trees is to 'implant' the process of binary search for transitions into the structure of the trees themselves. this way the process of binary search becomes visible, and the implementation of the trees becomes quite easy. the directed acyelic word graph (dawg) of a string w is the smallest dfa that accepts all suffixes of w, and requires only linear space. we apply the scheme of ternary trees to dawgs, introducing a new data structure named ternary dawgs (tdawgs). furthermore, the scheme of avl trees is applied to the tdawgs, yielding a more time-efficient structure avl tdawgs. we also perform some experiments that show the efficiency of tdawgs and avl tdawgs, compared to dawgs in which transitions are implemented by linked lists.
algebras of modal operators and partial correctness. modal kleene algebras are kleene algebras enriched by forward and backward box and diamond operators. we formalise the symmetries of these operators as galois connections, complementarities and dualities. we study their properties in the associated operator algebras and show that the axioms of relation algebra are theorems at the operator level. modal kleene algebras provide a unifying semantics for various program calculi and enhance efficient cross-theory reasoning in this class, often in a very concise pointfree style. this claim is supported by novel algebraic soundness and completeness proofs for hoare logic and by connecting this formalism with an algebraic decision procedure.
two-sorted metric temporal logics. temporal logic has been successfully used for modeling and analyzing the behavior of reactive and concurrent systems.one shortcoming of (standard) temporal logic is that it is inadequate for real-time applications, because it only deals with qualitative timing properties.this is overcome by metric temporal logics which offer a uniform logical framework in which both qualitative and quantitative timing properties can be expressed by making use of a parameterized operator of relative temporal realization. in this paper we deal with completeness issues for basic systems of metric temporal logic --- despite their relevance, such issues have been ignored or only partially addressed in the literature.we view metric temporal logics as two-sorted formalisms having formulae ranging over time instants and parameters ranging over an (ordered) abelian group of temporal displacements.we first provide an axiomatization of the pure metric fragment of the logic, and prove its soundness and completeness.then, we show how to obtain the metric temporal logic of linear orders by adding an ordering over displacements.finally, we consider general metric temporal logic allowing quantification over algebraic variables and free mixing of algebraic formulae and temporal propositional symbols.
set of periods of additive cellular automata. it is shown that the set of periods of any additive cellular automata f, where the addition is done modulo a prime p, can be determined using some simple conditions on the coefficients in the linear expression of f. in particular, we establish that the set of periods has only four possibilities: {1, m} for some m where 1 ≤ m < p, n\{pm : m ∈ n}, n\{2pm : m ∈ n ∪ {0}} or the whole set n = {1,2,3,...}. using our results, the set of periods of any additive cellular automata, where the addition is done modulo a square-free positive integer, is easily obtained.
universality and decidability of number-conserving cellular automata. number-conserving cellular automata (ncca) are particularly interesting, both because of their natural appearance as models of real systems, and because of the strong restrictions that number-conservation implies. here we extend the definition of the property to include cellular automata with any set of states in z, and show that they can be always extended to "usual" ncca with contiguous states. we show a way to simulate any one dimensional ca through a one-dimensional ncca, proving the existence of intrinsically universal ncca. finally, we give an algorithm to decide, given a ca, if its states can be labeled with integers to produce a ncca, and to find this relabeling if the answer is positive.
on conservative and monotone one-dimensional cellular automata and their particle representation. number-conserving (or conservative) cellular automata (ca) have been used in several contexts, in particular traffic models, where it is natural to think about them as systems of interacting particles. in this article we consider several issues concerning one-dimensional cellular automata which are conservative, monotone (specially "non-increasing"), or that allow a weaker kind of conservative dynamics. we introduce a formalism of "particle automata", and discuss several properties that they may exhibit, some of which, like anticipation and momentum preservation, happen to be intrinsic to the conservative ca they represent. for monotone ca we give a characterization, and then show that they too are equivalent to the corresponding class of particle automata. finally, we show how to determine, for a given ca and a given integer b, whether its states admit a b-neighborhood-dependent relabeling whose sum is conserved by the ca iteration; this can be used to uncover conservative principles and particle-like behavior underlying the dynamics of some ca. compliments at http://www.dim.uchile.cl/~anmoreir/ncca
on the computability of walsh functions. the haar and the walsh functions are proved to be computable with respect to the fine-metric df which is induced from the infinite product ω = {0,1}{1,2,...} with the weighted product metric dc of the discrete metric on {0, 1}. although they are discontinuous functions on [0, 1] with respect to the euclidean metric, they are continuous functions on (ω, dc) and on ([0, 1], df).on (ω, dc), computable real-valued cylinder functions, which include the walsh functions, become computable and every computable function can be approximated effectively by a computable sequence of cylinder functions. the metric space ([0, 1], df) is separable but not complete nor effectively complete. we say that a function on [0, 1] is uniformly fine-computable if it is sequentially computable and effectively uniformly continuous with respect to the metric df. it is proved that a uniformly fine-computable function is essentially a computable function on ω.it is also proved that walsh-fourier coefficients of a uniformly fine-computable function f form a computable sequence of reals and there exists a subsequence of the walsh-fourier series which fine-converges effectively uniformly to f.
on state-alternating context-free grammars. state-alternating context-free grammars are introduced, and the language classes obtained from them are compared to the classes of the chomsky hierarchy as well as to some well-known complexity classes. in particular, state-alternating context-free grammars are compared to alternating context-free grammars (theoret. comput. sci. 67 (1989) 75-85) and to alternating pushdown automata. further, various derivation strategies are considered, and their influence on the expressive power of (state-) alternating context-free grammars is investigated.
some minimum merging networks. let m(m, n) be the minimum number of comparators which constructs an (m, n)-merging network. batcher's odd-even merge, which is a merging network constructed by his algorithm, provides the best upper bound for m(m, n) to date. recently iwata (inform. and comput. 168 (2001) 187) analyzed the property of leftmost comparators, and showed m(m1 + m2, n) ≥ [(m(m1, n) + m(m2, n) + m1 + m2 + n - 2)/2]. we extend iwata's proofs and show that batcher's (6, 8k + 7)-, (9, 16k + 9)-, (7, 8)-merging networks are optimal for all k ≥ 0.in batcher's (m, n)-merging network, the ith smallest element out of m elements and another ith smallest element out of n elements are first compared for all i (1 ≤ i ≤ min{m, n}). under an assumption of existence of such min{m, n} comparators in optimal (m, n)-merging networks, we show that m(n, n) = m(n - 1, n) + 1 = m(n - 2, n) + 3.
counting by quantum eigenvalue estimation. for every "computation" there corresponds the physical task of manipulating a starting state into an output state with a desired property. as the classical theory of physics has been replaced by quantum physics, it is interesting to consider the capabilities of a computer that can exploit the distinctive quantum features of nature. the extra capabilities seem enormous. for example, with only an expected o(square rootn) evaluations of a function f : {0; 1; : : : ; n - 1} &rarr; {0; 1}, we can find a solution to f(x) = 1 provided one exists. another example is the ability to 1nd efficiently the order of an element g in a group by using a quantum computer to estimate a random eigenvalue of the unitary operator that multiplies by g in the group. by using this eigenvalue estimation algorithm to estimate an eigenvalue of the unitary operator used in quantum searching we can approximately count the number of solutions to f(x) = 1. this paper describes this eigenvector approach to quantum counting and related algorithms.
on primitive recursive algorithms and the greatest common divisor function. we establish linear lower bounds for the complexity of non-trivial, primitive recursive algorithms from piecewise linear given functions. the main corollary is that logtime algorithms for the greatest common divisor from such givens (such as stein's) cannot be matched in efficiency by primitive recursive algorithms from the same given functions. the question is left open for the euclidean algorithm, which assumes the remainder function.
on the relationship between compact regularity and gentzen's cut rule. the patch topology on a stably compact space, generalizing the lawson topology on a domain, is a coreflection of stably compact spaces in compact regular spaces. this paper investigates compact regularity and the patch coreflection in multilingual sequent calculus (mls), which can be regarded as a category of predicative representations of stably compact spaces. an object of mls is a certain sort of generalization of the positive fragment of gentzen's sequent calculus. we show that an object of mls represents a compact regular space if and only if every sequent arises as an instance of gentzen's cut rule with complete freedom to choose the placement of the cut formula.the relationship between compact regularity and gentzen's cut rule is further explicated by the patch coreflection in mls. the construction is a universal solution (up to a certain equivalence of tokens) to the problem of adding opposites to a logic, i.e., tokens that obey gentzen's rules for negation. in the spectral case, this is equivalent to adding boolean complements. the paper closes by considering the full subcategory of mls consisting of objects with opposites. by taking contrapositives of sequents, we obtain an anti-involution on morphisms making this category equivalent to the freyd/scedrov allegory of compact regular spaces and closed binary relations. moreover, the category of "maps" of this allegory is predicatively equivalent to the image of the patch functor.
recursion and corecursion have the same equational logic. this paper is concerned with the equational logic of definitions whose semantics is given in terms of final coalgebra maps. the framework for our study is iteration theories (cf. e.g. bloom and ésik, iteration theories: the equational logic of iterative processes, eatcs monographs on theoretical computer science, springer, berlin, 1993; theoret. comput. sci. 179 (1-2) (1997)), recently re-introduced as models of the flr0 fragment of the formal language of recursion (hurkens et al., j. symbolic logic 63 (2) (1998) 45; mos chovakis, j. symbolic logic 54 (1989) 1216; in: m.l. dalla chiara et al. (eds.), logic and scientific methods, kluwer, dordrecht, 1997, p. 179). we present a new class of iteration theories derived from final coalgebras. this allows us to reason with a number of types of fixed-point equations which heretofore seemed to require metric or order-theoretic ideas. all of the work can be done using finality properties and equational reasoning. having a semantics, we obtain the following completeness result: the equations involving fixed-point terms which are valid for final coalgebra interpretations are exactly those valid in a number of contexts pertaining to recursion. for example, they coincide with the equations valid for least-fixed-point recursion on dcpo's. we also present a new version of the proof of the well-known completeness result for iteration theories (see ésik, comput. linguistics comput. languages 4 (1982) 95; hurkens et al., 1998). our work brings out a connection between coalgebraic reasoning and recursion.
relating casl with other specification languages: the institution level. in this work, we investigate various specification languages and their relation to casl, the recently developed common algebraic specification language. in particular, we consider the languages larch, obj3 and functional cafeobj, act one, asf, and hep-theories, as well as various sublanguages of casl. all these languages are translated to an appropriate sublanguage of casl.the translation mainly concerns the level of specification in-the-small: the logics underlying the languages are formalized as institutions, and representations among the institutions are developed. however, it is also considered how these translations interact with specification in-the-large.thus, we obtain, on the one hand, translations of any of the above-mentioned specification languages to an appropriate sublanguage of casl. this allows us to take libraries and case studies that have been developed for other languages and re-use them in casl.on the other hand, we set up institution representations going from the casl institution (and some of its subinstitutions) to simpler subinstitutions. given a theorem proving tool for such a simpler subinstitution, with the help of a representation, it can also be used for a more complex institution. thus, first-order theorem provers and conditional term rewriting tools become usable for casl.
dependable computing: an overview. dependability is carving out a more and more important place in computer science. to introduce this special issue on dependable computing, we present a synthetic overview of this domain, intended for computer scientists. this paper attempts neither to enumerate nor to detail the numerous particular research work leads on this theme. it rather introduces the requirements from which research activities are stemmed. it synthesises the various issues handled by these activities as well as the various solutions they propose. the content aims at providing to computer scientists a pedagogical survey of the various problems, concepts and classes of studies relating to dependable computing. supplying a synthetic article does not allow, in particular, numerous contributory persons and teams to be quoted or publications to be listed. the five following papers of this special issue tackle deeply specific aspects of this area.
rank inequalities and separation algorithms for packing designs and sparse triple systems. combinatorial designs find numerous applications in computer science, and are closely related to problems in coding theory. packing designs correspond to codes with constant weight; 4-sparse partial steiner triple systems (4-sparse pstss) correspond to erasure-resilient codes that are useful in handling failures in large disk arrays (chee, colbourn, ling, discrete appl. math., to appear; hellerstein, gibson, karp, katz, paterson, algorithmica 12 (1994) 182-208). the study of polytopes associated with combinatorial problems has proven to be important for both algorithms and theory, but only recently the study of design polytopes has been pursued (moura, math. appl. 368 (1996) 227-254; moura, ph.d. thesis, university of toronto, 1999; moura, proc. seventh annu. european symp. prague, 1999, lecture notes in computer science, vol. 1643, springer, berlin, 1999, pp. 462-475; wengrzik, master's thesis, universität berlin, 1995; zehendner, doctoral thesis, universität augsburg, 1986). in this article, we study polytopes associated with t-(v,k,λ) packing designs and with m-sparse pstss. subpacking and l-sparseness inequalities are introduced and studied. they can be regarded as rank inequalities for the independence systems associated with these designs. conditions under which subpacking inequalities define facets are derived; in particular, those which define facets for pstss are determined. for m ≥ 4, the l-sparseness inequalities with 2 ≤ l ≤ m are proven to induce facets for the m-sparse psts polytope; this proof uses extremal families of pstss known as erdös configurations. separation algorithms for these inequalities are proposed. we incorporate some of the sparseness inequalities in a polyhedral algorithm, and determine maximal 4-sparse psts(v), v ≤ 16. an upper bound on the size of m-sparse pstss is presented.
marcus t-contextual grammars and cut hierarchies and monotonicity for restarting automata. the t-contextual grammars are generalizations of marcus contextual grammars, which insert t contexts in each derivation step. if the selection mappings are regular and satisfy an additional locality restriction, then these grammars correspond in their expressive power to restarting automata with cut-index t. in the first part of the paper classes of languages are studied that are accepted by certain types of restarting automata with limited cut-index. as already r-automata with cut-index 1 accept np-complete languages, additional restrictions in the form of certain monotonicity conditions are also considered. without the locality restriction t-contextual grammars with regular selection correspond to t- rr-automata with cut-index one. these are rr-automata that are allowed to perform up to t deletion operations in each cycle that each delete a single factor only. in the second part of the paper the expressive power of these automata is studied, where the focus is on the special case that certain monotonicity conditions are satisfied.
the dnf exception problem. given a disjunctive normal form (dnf) expression ϕ and a set a of vectors satisfying the expression, called the set of exceptions, we would like to update ϕ to get a new dnf which is false on a, and otherwise is equivalent to ϕ. is there an algorithm with running time polynomial in the number of variables, the size of the original formula and the number of exceptions, which produces an updated formula of size bounded by a certain type of function of the same parameters?we give an efficient updating algorithm, which shows that the previously known best upper bound for the size of the updated expression is not optimal in order of magnitude. we then present a lower bound for the size of the updated formula in terms of the parameters, which is the first known lower bound for this problem. we also consider the special case (studied previously in the complexity theory of disjunctive normal forms) where the initial formula is identically true, and give efficient updating algorithms, providing new upper bounds for the size of the updated expression.
conditional complexity and codes. let x and y be binary strings. we prove that there exists a program p of size about k(x|y) that maps y tox and has small complexity when x is known (k(p|x)0)*#8776;0). having in mind the parallelism between shannon information theory and algorithmic information theory, one can say that this result is parallel to wolf-slepian and k&ouml;rner-csiszar-marton theorems, see (i. csiszar and j. k&ouml;rner, information theory, coding theorems for discrete memoryless systems, akad&eacute;miai kiad&oacute;, budapest, 1981). we show also that for any three stringsx,y,z of length at most n the length of the shortest program p that maps both y and z to x (i.e., p(y)=p(z)=x) equals max(k(x|y),k(x|z)+o(logn.
the definable criterion for definability in presburger arithmetic and its applications. in section 1 of present paper we construct a formula φn(a) of presburger arithmetic (integers with addition and order) with additional n-ary predicate variable a. this formula is true if and only if predicate a is definable in presburger arithmetic (theorem 2).this formula is used to prove the following facts: (1) given a finite synchronous automaton recognizing a set of n-tuples of integers written in positional notation one can effectively decide whether this set is definable in presburger arithmetic; (2) every predicate (set of n-tuples of integers) recognizable in two essentially different positional systems is definable in presburger arithmetic. the last result was proved by cobham (math. systems theory, 3(2) (1969) 186) for the case n= 1. in general case both (1) and (2) were proved by semenov (ph.d. thesis, moscow state university; siberian math. j. 18(2) (1977) 403) (semenov's proofs are very difficult).
one application of real-valued interpretation of formal power series. we define two natural properties of context-free grammars. the first property generalizes linearity and the second property strengthens nonlinearity. a language generated by an unambiguous grammar of the first type is called the language with weak linear structure and a language generated by an unambiguous grammar of the second type is called the language with strong nonlinear structure. our main theorem states that the family of unambiguous grammars generating languages with weak linear structure and the family of unambiguous grammars generating languages with strong nonlinear structure are effectively separable.
kolmogorov entropy in the context of computability theory. we consider the overgraph of the kolmogorov entropy function and study whether it is a complete enumerable set with respect to different types of reductions. it turns out that (for any type of entropy) the overgraph of the conditional entropy function is m-.
almost periodic sequences. this paper studies properties of almost periodic sequences (also known as uniformly recursive).a sequence is almost periodic if for every finite string that ccurs infinitely many times in the sequence there exists a number m such that every segment of length m contains an ccurrence of the word.we study closure properties of the set of almost periodic sequences, ways to generate such sequences (including a general way), computability issues and kolmogorov complexity of prefixes of almost periodic sequences.
a general method to construct oracles realizing given relationships between complexity classes. we present a method to prove oracle results of the following type. let k_1, \ldots, k_{2n}, and l_1, \ldots, l_{2m} be complexity classes. our method provides a general framework for constructing an oracle a such that k^a_{2i-1} \neq k^a_{2i} for i=1, \ldots, n and l^a_{2j-1} = l^a_{2j} for j=1, \ldots, m. using that method we prove several results of this kind. the hardest of them is the existence of an oracle a such that p^a \neq np^a, p^a = bpp^a, and both conp^a-sets and np^a-sets are p^a-separable. we exhibit also two theorems that cannot be proved by that method.
evolutionary computation and wright's equation. in this paper, wright's equation formulated in 1931 is proven and applied to evolutionary computation. wright's equation shows that evolution is doing gradient ascent in a landscape defined by the average fitness of the population. the average fitness w is defined in terms of marginal gene frequencies pi. wright's equation is only approximately valid in population genetics, but it exactly describes the behavior of our univariate marginal distribution algorithm (umda). we apply wright's equation to a specific fitness function defined by wright. furthermore we introduce mutation into wright's equation and umda. we show that mutation moves the stable attractors from the boundary into the interior. we compare wright's equation with the diversified replicator equation. we show that a fast version of wright's equation gives very good results for optimizing a class of binary fitness functions.
bounded time-stamping in message-passing systems. consider a distributed system running a protocol in which processes exchange information by passing messages. the gossip problem for the protocol is the following: whenever a process q receives a message from another process p, q must be able to decide which of p and q has more recent information about r, for every other process r in the system. with this data, q is in a position to update its knowledge about the global state of the system.we propose a solution wherein to each message of the protocol, the sender adds information about its current state of knowledge about other processes. we do not add any new messages to the underlying computation. the additional information tagged onto each message is uniformly bounded if the channels are bounded. this means that for systems with bounded channels, the overhead of maintaining the latest gossip is a constant, independent of the length of the underlying computation. moreover, gossip information can be used to implement bounded channels by inhibiting the sending of new messages over channels that are potentially full.our solution to the gossip problem has several applications in the analysis of distributed systems. many distributed algorithms rely, either explicitly or implicitly, on the local information available at a process about the global state of the system. using our scheme, each process can ensure that during a computation it always maintains the best possible information about every other process. at a theretical level, the gossip problem plays an important role in formal characterizations of finite-state message-passing systems.
moving policies in cyclic assembly line scheduling. we consider an assembly line problem that occurs in various kinds of production automation. our original motivation lies in the automated manufacturing of pc boards. the assembly line has to process a (potentially infinite) number of identical workpieces in a cyclic fashion. in contrast to common variants of assembly line scheduling, the forward steps are variable and may be smaller than the distance of two stations. therefore, each station may process parts of several workpieces at the same time, and parts of a workpiece may be processed by several stations at the same time. the throughput rate is determined by the number of (cyclic) forward steps, the offsets of the individual forward steps, and the distribution of jobs over the stationary stages between the forward steps. the number of forward steps as well as the offsets are part of the output. however, no matter whether they are part of the input or the output, the optimal assignment of the jobs to the stationary stages is np-hard.we will base our algorithmic considerations on some quite conservative assumptions, which are greatly fulfilled in various application scenarios, including the one in our application: the number of jobs may be huge, but the number of stations and the number of forward steps in an optimal solution are small, the granularity of forward steps is quite coarse, and the processing times of the individual items do not differ by several orders of magnitude from each other. we will present an algorithm that is polynomial and provably deviates from optimality to a negligible extent (under these assumptions). this result may be viewed as an application of fixed-parameter tractability.
precise interprocedural dependence analysis of parallel programs. it is known that interprocedural detection of copy constants and elimination of faint code in parallel programs are undecidable problems, if base statements are assumed to execute atomically. we show that these problems become decidable, if this assumption is abandoned. so, the (unrealistic) idealization from program verification "atomic execution of base statements" introduced in order to simplify matters, actually increases the difficulty of these problems from the point of view of program analysis: amazingly these problems become more tractable if we adopt a less idealized, more realistic model of execution.we introduce an effective abstract domain of antichains of dependence traces that allows us to perform a precise interprocedural dependence analysis in (non-atomically executing) parallel programs. the main idea is to trace sequences of dependences exhibited successively by program executions. we define operations on antichains of dependence traces and show that they precisely abstract the corresponding operations on sets of non-atomic program executions. using these operations, we can analyze dependences by means of an abstract interpretation of constraint systems that characterize sets of program executions of interest. the result of the dependence analysis can in turn be used to detect all copy constants and to eliminate faint code.while the run-time of the algorithms is exponential in the number of program variables, it is polynomial in the program size. hence, they are polynomial-time algorithms if the number of program variables is bounded. in order to justify their overall exponential run-time, we show that both detection of copy constants and elimination of faint code are intractable (np-hard) even when the atomic execution idealization is abandoned. this holds already for parallel programs without loops or procedures.
lifting results for categories of algebras. in this paper, we present results that provide an abstract setting for the construction and interpretation of categories of algebras appearing in various semantic examples including those related to scott domains and cartesian closed categories. a methodology is introduced that lifts adjoint pairs on categories with monads to categories whose objects are algebras for these monads. results are achieved by exploiting prior work on kleisli liftings and the existence of key isomorphisms. while applicable to domain theory and the semantics of partiality, the construction at work is considerably more general and is applicable to other settings as well.
cayley continuants. in 1858 cayley considered a particular kind of tridiagonal determinants (or continuants). by a direct inspection of the first cases, he conjectured an identity expressing these determinants in terms of certain other determinants considered by sylvester in 1854. then cayley proved the conjectured identity by induction but, as he wrote, he felt unsatisfied with his proof. the main aim of this paper is to give a straightforward proof of cayley's identity using the method of formal series. moreover we use this method and umbral calculus techniques to obtain several other identities.cayley continuants appear in several contexts and in particular in enumerative combinatorics. mittag-leffler polynomials, meixner polynomials of the first kind, the falling and the raising factorials are just few instances of these continuants. they can be interpreted in terms of weighted permutations. moreover, as we prove in this paper, they also appear in the context of hankel determinants generated by certain catalan-like numbers.
proof-term synthesis on dependent-type systems via explicit substitutions. typed λ-terms are used as a compact and linear representation of proofs in intuitionistic logic. this is possible since the curry-howard isomorphism relates proof-trees with typed λ-terms. the proofs-as-terms principle can be used to verify the validity of a proof by type checking the λ term extracted from the complete proof-tree. in this paper we present a proof synthesis method for dependent-type systems where typed open terms are built incrementally at the same time as proofs are done. this way, every construction step, not just the last one, may be type checked. the method is based on a suitable calculus where substitutions as well as meta-variables are first-class objects. copyright 2001 elsevier science b.v.
selection from read-only memory and sorting with minimum data movement. selecting an element of given rank, for example the median, is a fundamental problem in data organization and the computational complexity of comparison based problems. here, we consider the scenario in which the data resides in an array of read-only memory and hence the elements cannot be moved within the array. under this model, we develop efficient selection algorithms using very little extra space ( ologn extra storage cells). these include an on1+3 worst case algorithm and an onloglogn average case algorithm, both using a constant number of extra storage cells or indices. our algorithms complement the upper bounds for the time-space tradeoffs obtained by munro and paterson [9] and frederickson [4] who developed algorithms for selection in the same model when wlogn 2 extra storage cells are available. we apply our selection algorithms to obtain sorting algorithms that perform the minimum number of data moves on any given array. we also derive upper bounds for time-space tradeoffs for sorting with minimum data movement. &mdash;authors' abstract
the bandwidth minimization problem for cyclic caterpillars with hair length 1 is np-complete. in this paper, we show that the bandwidth minimization problem remains np-complete for cyclic caterpillars with hair length 1. cyclic caterpillars with hair length 1 are graphs in which the removal of all pendant vertices results in a simple cycle.
a priori optimization for the probabilistic maximum independent set problem. we first propose a formal definition for the concept of probabilistic combinatorial optimization problem (under the a priori method). next, we study the complexity of optimally solving probabilistic maximum independent set problem under several a priori optimization strategies as well as the complexity of approximating optimal solutions. for the different strategies studied, we present results about the restriction of probabilistic independent set on bipartite graphs.
functions with local state: regularity and undecidability. we study programs of a finitary ml-like language rmlf with ground-type references. rmlf permits the use of functions with locally declared variables that remain private and persist from one use of the function to the next. using game semantics we show that this leads to undecidability of program equivalence already at second order. we also examine the extent to which this feature can be captured by regular languages. this gives a decidability result for a second-order fragment rmlf- of rmlf, which comprises many examples studied in the literature.
games for complexity of second-order call-by-name programs. we use game semantics to show that program equivalence and program approximation in a second-order fragment of idealized algol are pspace-complete. the result relies on a pspace construction of deterministic finite automata representing strategies defined by second-order programs and is an improvement over the at least exponential space bounds implied by the work of other authors in which extended regular expressions were used.the approach makes it possible to study the contribution of various constructs of the language to the complexity of program equivalence and demonstrates a similarity between call-by-name game semantics and call-by-name interpreters.
exhausting strategies, joker games and full completeness for imll with unit. we present a game description of free symmetric monoidal closed categories, which can also be viewed as a fully complete model for intuitionistic multiplicative linear logic with the tensor unit. we model the unit by a distinguished one-move game called joker. special rules apply to the joker move. proofs are modelled by what we call conditionally exhausting strategies, which are deterministic and total only at positions where no joker move exists in the immediate neighbourhood, and satisfy a kind of teachability condition called p-exhaustion. we use the model to give an analysis of a counting problem in free autonomous categories which generalizes the triple unit problem.
on an interpretation of safe recursion in light affine logic. we introduce a subalgebra bc of bellantoni and cook's safe-recursion function algebra bc. functions of the subalgebra have safe arguments that are non-contractible (i.e non-duplicable). we propose a definition of safe and normal variables in light affine logic (lal), and show that bc- is the largest subalgebra that is interpretable in lal, relative to that definition. though bc- itself is not pf complete, there are extensions of it (by additional schemes for defining functions with safe arguments) that are, and are still interpretable in lal and so preserve pf closure. we focus on one such which is bc- augmented by a definition-by-cases construct and a restricted form of definition-by-recursion scheme over safe arguments. as a corollary we obtain a new proof of the pf completeness of lal.
an efficient algorithm for sequence comparison with block reversals. given two sequences x and y that are strings over some alphabet set, we consider the distance d(x,y) between them defined to be minimum number of character replacements and block (substring) reversals needed to transform x to y (or vice versa). the operations are required to be disjoint. this is the "simplest" sequence comparison problem we know of that allows natural block edit operations. block reversals arise naturally in genomic sequence comparison; they are also of interest in matching music data. we present an algorithm for exactly computing the distance d(x,y); it takes time o(|x|log2|x|), and hence, is near-linear. trivial approach takes quadratic time.
rewriting p systems: improved hierarchies. generally, for proving universality results about rewriting p systems one considers matrix grammars in the strong binary normal form. such grammars contain both matrices with rules used in the appearance checking mode and matrices without appearance checking rules. in the proofs of most of the universality theorems reported in the literature, appearance checking matrices are simulated by using only two membranes, while four membranes are used for simulating matrices without appearance checking rules. thus, a way to improve these theorems is to diminish the number of membranes used for simulating matrices without appearance checking rules. in this paper we address this problem, and give first a general improved result about simulating matrix grammars without appearance checking: three membranes are shown to suffice. this result is then used to improve several universality results from various membrane computing papers, for instance, about p systems with replicated rewriting, with leftmost rewriting, with conditional communication, as well as for hybrid p systems with finite choice.
truncated suffix trees and their application to data compression. the suffix tree is a fundamental data structure in the area of string algorithms and it has been used in many applications including data compression. in this paper we propose a data structure called the truncated suffix tree, which is a truncated version of the suffix tree. we also present two linear-time construction algorithms for truncated suffix trees and two algorithms that delete suffixes from truncated suffix trees.the truncated suffix tree is particularly a useful data structure for lz77 that compresses using a sliding window of a fixed size. our algorithms lead to two implementations of lz77 that maintain sliding windows by truncated suffix trees. we also present a technique of finding the longest match in a sliding window, which is a crucial step in lz77.
a notation for lambda terms: a generalization of environments. a notation for lambda terms is described that is useful in contexts where the intensions of these terms need to be manipulated. the scheme of de bruijn is used for eliminating variable names, thus obviating alpha conversion in comparing terms. a category of terms is provided that can encode other terms together with substitutions to be performed on them. the notion of an environment is used to realize this `delaying'' of substitutions. however, the precise environment mechanism employed here is more complex than the usual one because the ability to examine subterms embedded under abstractions has to be supported. the representation presented permits a beta contraction to be realized via an atomic step that generates a substitution and associated steps that percolate this substitution over the structure of a term. operations on terms are provided that allow for the combination and hence the simultaneous performance of substitutions. our notation eventually provides a basis for efficient realizations of beta reduction and also serves as a means for interleaving steps inherent in this operation with steps in other operations such as higher-order unification. manipulations on our terms are described through a system of rewrite rules whose correspondence to the usual notion of beta reduction is exhibited and exploited in establishing confluence and other similar properties. our notation is similar in spirit to recent proposals deriving from the categorical combinators of curien, and the relationship to these is discussed. refinements to our notation and their use in describing manipulations on lambda terms are considered in a companion paper.
on the one-sided crossing minimization in a bipartite graph with large degrees. given a bipartite graph g = (v, w, e), a 2-layered drawing consists of placing nodes in the first node set v on a straight line l1 and placing nodes in the second node set w on a parallel line l2. for a given ordering of nodes in w on l2, the one-sided crossing minimization problem asks to find an ordering of nodes in v on l1 so that the number of arc crossings is minimized. a well-known lower bound lb on the minimum number of crossings is obtained by summing up min{cuv, cvu} over all node pairs u, v ∈ v, where cuv denotes the number of crossings generated by arcs incident to u and v when u precedes v in an ordering. in this paper, we prove that there always exists a solution whose crossing number is at most (1.2964 + 12/(δ - 4))lb if the minimum degree δ of a node in v is at least 5.
a robust algorithm for bisecting a triconnected graph with two resource sets. given two disjoint subsets t1 and t2 of nodes in a 3-connected graph g = (v,e) with a node set v and an arc set e, where |t1| and |t2| are even numbers, it is known that v can be partitioned into two sets v1 and v2 such that the graphs induced by v1 and v2 are both connected and |v1 ∩ tj| = |v2 ∩ tj| = |tj|/2 holds for each j = 1.2. an o(|v|2 log |v|) time and o(|v| + |e|) space algorithm lbr finding such a bipartition has been proposed based on a geometric argument, where g is embedded m the plane r2 and the node set is bipartitioned by a ham-sandwich cut on the embedding. a naive implementation of the algorithm, however, requires high precision real arithmetic to distinguish two close points in a large set of points on r2. in this paper, we propose an o(|v|2) time and space algorithm to the problem. the new algorithm, which remains to be based on the geometric embedding, can construct a solution purely combinatorially in the sense that it does not require computing actual embedded points in r2 and thereby no longer needs to store any real number for embedded points. although the new algorithm seems to need more space complexity, it can be implemented only with |v| linked lists such that each element stores an integer in [1,|v|].
a graph-theoretic characterization theorem for multiplicative fragment of non-commutative linear logic. it is well known that every proof net of a non-commutative version of mll (multiplicative fragment of commutative linear logic) can be drawn as a plane danos-regnier graph (drawing) satisfying the switching condition of danos-regnier [3]. in this paper, we study the reverse direction; we introduce a system mncll which is logically equivalent to the multiplicative fragment of cyclic linear logic introduced by yetter [9], and show that any plane danos-regnier graph drawing with one terminal edge satisfying the switching condition represents a unique non-commutative proof net (i.e., a proof net of mncll). in the course of proving this, we also give the characterization of the non-commutative proof nets by means of the notion of strong planarity, as well as the notion of a certain long-trip condition, called the stack-condition, of a danos-regnier graph, the latter of which is related to abrusci's balanced long-trip condition [2].
static analysis based on formal models and incremental computation in go programming. computer-go programs have high computational costs for static analysis, even though most intersections of the board remain unchanged by one move. therefore, incremental computation as well as theoretical models are essential features for static analysis. this paper describes some formal models for static analysis, and explores how incremental computation is applied to the static analysis in go programs. the static analysis in this paper includes (1) recognizing blocks and groups of stones and evaluating their properties, (2) determining the life and death of a group by numerical features, (3) finding the numbers of regions enclosed by the groups based on euler's formula, and (4) analysing capturing races (semeai) and sekis based on an abstract description called the semeai graph. several operations on the sets of intersections on the board are used for defining the notions on go boards as well as for describing the analysis methods.
a time-optimal solution for the path cover problem on cographs. we show that the notoriously difficult problem of finding and reporting the smallest number of vertex-disjoint paths that cover the vertices of a graph can be solved time- and work-optimally for cographs. our result implies that for this class of graphs the task of finding a hamiltonian path can be solved time- and work-optimally in parallel.it was open for more than 10 years to find a time- and work-optimal parallel solution for this important problem. our contribution is to offer an optimal solution to this important problem. we begin by showing that any algorithm that solves an instance of size n of the problem must take ω(logn) time on the crew, even if an infinite number of processors are available. we then go on to show that this time lower bound is tight by devising an erew algorithm that, given an n-vertex cograph g represented by its cotree, finds and reports all the paths in a minimum path cover in o(logn) time using n/logn processors.
on the expected time for herman's probabilistic self-stabilizing algorithm. in this article we investigate the expected time for herman's probabilistic self-stabilizing algorithm in distributed systems: suppose that the number of identical processes in a unidirectional ring, say n, is odd and n ≥ 3. if the initial configuration of the ring is not "legitimate", that is, the number of tokens differs from one, then execution of the algorithm made up of synchronous probabilistic procedures with a local parameter 0 < r < 1 results in convergence to a legitimate configuration with a unique token (herman's algorithm). we then show that the expected time of the convergence is less than ((π2-8)/8r(1-r))n2. note that if r = ½ then it is bounded by 0.936n2. moreover, there exists a configuration whose expected time is θ(n2). the method of the proof is based on the analysis of coalescing random walks.
a logic for secure memory access of abstract state machines. we extend the logic for abstract state machines by a read predicate that allows to make precise statements about the accesses of locations of an asm. the logic can be used to prove security properties of asms like that the machine does not read locations containing critical information or that all accesses of the machine to the abstract memory are permitted. the new read predicate is also useful for proving refinements of parallel asms to sequential c-like programs. the logic is complete for hierarchical asms and still sound for turbo asms. it is integrated in the asmkey theorem prover.
an efficient k nearest neighbors searching algorithm for a query line. we present an algorithm for finding k nearest neighbors of a given query line among a set of n points distributed arbitrarily on a two-dimensional plane. our algorithm requires o(n2) time and o(n2/log n) space to preprocess the given set of points, and it answers the query for a given line in o(k + log n) time, where k may also be an input at the query time. almost a similar technique works for finding k farthest neighbors of a query line, keeping the time and space complexities invariant. we also show that if k is known at the time of preprocessing, the time and space complexities for the preprocessing can be reduced keeping the query times unchanged.
a framework for security analysis of mobile wireless networks. we present a framework for specification and security analysis of communication protocols for mobile wireless networks. this setting introduces new challenges which are not being addressed by classical protocol analysis techniques. the main complication stems from the fact that the actions of intermediate nodes and their connectivity can no longer be abstracted into a single unstructured adversarial environment as they form an inherent part of the system's security. in order to model this scenario faithfully, we present a broadcast calculus which makes a clear distinction between the protocol processes and the network's connectivity graph, which may change independently from protocol actions. we identify a property characterising an important aspect of security in this setting and express it using behavioural equivalences of the calculus. we complement this approach with a control flow analysis which enables us to automatically check this property on a given network and attacker specification.
finding the most vital node of a shortest path. in an undirected, 2-node connected graph g=(v,e) with positive real edge lengths, the distance between any two nodes r and s is the length of a shortest path between r and s in g. the removal of a node and its incident edges from g may increase the distance from r to s. a most vital node of a given shortest path from r to s is a node (other than r and s) whose removal from g results in the largest increase of the distance from r to s. in the past, the problem of finding a most vital node of a given shortest path has been studied because of its implications in network management, where it is important to know in advance which component failure will affect network efficiency the most. in this paper, we show that this problem can be solved in o(m+n log n) time and o(m) space, where m and n denote the number of edges and the number of nodes in g.
spiking neurons and the induction of finite state machines. we discuss in this short survey article some current mathematical models from neurophysiology for the computational units of biological neural systems: neurons and synapses. these models are contrasted with the computational units of common artificial neural network models, which reflect the state of knowledge in neurophysiology 50 years ago. we discuss the problem of carrying out computations in circuits consisting of biologically realistic computational units, focusing on the biologically particularly relevant case of computations on time series. finite state machines are frequently used in computer science as models for computations on time series. one may argue that these models provide a reasonable common conceptual basis for analyzing computations in computers and biological neural systems, although the emphasis in biological neural systems is shifted more towards asynchronous computation on analog time series. in the second half of this article some new computer experiments and theoretical results are discussed, which address the question whether a biological neural system can, in principle, learn to behave like a given simple finite state machine.
ga performance distributions and randomly generated binary constraint satisfaction problems. we investigate the variable performance of a genetic algorithm (ga) on randomly generated binary constraint satisfaction problem instances which occur near the phase transition from soluble to non-soluble. we first carry out a conventional landscape analysis and observe, next to a number of common features related to the interaction structure, important differences between the instances, such as the number of solutions, the quality of the paths to the solutions, and the lengths and extent of the neutral paths for mutation. we then split the dynamics of the ga into two phases: the ascent towards the high fitness region, and from this high fitness region to a solution. to gain further information about the ga's behavior in the first phase, we construct two models based on the much simpler fully separable functions, and try to match instances which show a similar performance distribution. although far from exact, this technique of comparing with analog search problems gives a hint about the landscape elements that are responsible for the ga's slow ascent.
soundness of data refinement for a higher-order imperative language. using a set-theoretic model of predicate transformers and ordered data types, we give a semantics for an oberon-like higher-order imperative language with record subtyping and procedure-type variables and parameters. data refinement is shown to be sound for this language: it implies algorithmic refinement when suitably localized. all constructs are shown to preserve simulation, so data refinement can be carried out piecewise.
towards imperative modules: reasoning about invariants and sharing of mutable state. imperative and object-oriented programs make ubiquitous use of shared mutable objects. updating a shared object can and often does transgress a boundary that was supposed to be established using static constructs such as a class with private fields. this paper shows how auxiliary fields can be used to express two state-dependent encapsulation disciplines: ownership, a kind of separation, and friendship, a kind of sharing. a methodology is given for specification and modular verification of encapsulated object invariants and shown sound for a class-based language. as an example the methodology is used to specify iterators, which are problematic for previous ownership systems.
logic of subtyping. we introduce new modal logical calculi that describe subtyping properties of cartesian product and disjoint union type constructors as well as mutually recursive types defined using those type constructors.basic logic of subtyping s extends classical propositional logic by two new binary modalities ⊗ and ⊕. an interpretation of s is a function that maps standard connectives into set-theoretical operations (intersection, union, and complement) and modalities into cartesian product and disjoint union type constructors. this allows s to capture many subtyping properties of the above type constructors. we also consider logics sρ and sρω that incorporate into s mutually recursive types over arbitrary and well-founded universes correspondingly.the main results are completeness of the above three logics with respect to appropriate type universes. in addition, we prove cut elimination theorem for s and establish decidability of s and sρω.
a metric index for approximate string matching. we present a radically new indexing approach for approximate string matching. the scheme uses the metric properties of the edit distance and can be applied to any other metric between strings. we build a metric space where the sites are the nodes of the suffix tree of the text, and the approximate query is seen as a proximity query on that metric space. this permits us finding the occ occurrences of a pattern of length m, permitting up to r differences, in a text of length n over an alphabet of size σ, in average time o(m1+ε + occ) for any ε > 0, if r = o(m/logσm) and m > ((1 + ε)/ε)logσ n. the index works well up to r < (3 - √2)m/logσm, where it achieves its maximum average search complexity o(m1+√2+ε + occ). the construction time of the index is o(m1+√2+ε nlog n) and its space is o(m1+√2+εn). this is the first index achieving average search time polynomial in m and independent of n, for r = o(m/logσm). previous methods achieve this complexity only for r = o(m/logσ n). we also present a simpler scheme needing o(n) space.
average complexity of exact and approximate multiple string matching. we show that the average number of characters examined to search for r random patterns of length m in a text of length n over a uniformly distributed alphabet of size σ cannot be less than ω(n logσ(rm)/m). when we permit up to k insertions, deletions, and/or substitutions of characters in the occurrences of the patterns, the lower bound becomes ω(n(k + logσ(rm))/m). this generalizes previous single-pattern lower bounds of yao (for exact matching) and of chang and marr (for approximate matching), and proves the optimality of several existing multipattern search algorithms.
exponential transient length generated by a neuronal recurrence equation. we study the sequences generated by neuronal recurrence equations of the form x(n) = 1[σj=1k ajx(n - j) - θ], where k is the size of memory (k represents the number of previous states x(n - 1), x(n - 2),...,x(n - k) which intervene in the calculation of x(n)). we are interested in the number of steps (transient length) from an initial configuration to the cycle, where the length of the cycle represents the period. we show that under certain hypotheses it is possible to build a neuronal recurrence equation of memory size (s + 1)6m, whose dynamics contains an evolution of transient length (s + 1)(3m + 1 + lcm(p0, p1,...,ps-1,3m-1)) and a cycle of length (s + 1) lcm(p0, p1,....,ps-1), where lcm denotes the least common multiple and p0, p1,....,ps-1 are prime numbers lying between 2m and 3m.
small fast universal turing machines. we present deterministic polynomial time universal turing machines (utms) with state-symbol pairs of (3, 11), (5, 7), (6, 6), (7, 5) and (8, 4). these are the smallest known utms that simulate turing machines in polynomial time.
the stack-size of tries: a combinatorial study. in this paper, we introduce a class of extended binary trees that resembles all possible tree-structures of binary tries. assuming a uniform distribution of those trees we prove that for being the number of internal nodes the average stack-size is given by . since this result is quite similar to that for ordinary extended binary trees an attempt to find an explanation for that similarity using a quantitative level is made.
fast string matching by using probabilities: on an optimal mismatch variant of horspool's algorithm. the string matching problem, i.e. the task of finding all occurrences of one string as a substring of another one, is a fundamental problem in computer science. recently, this problem received a great deal of attention due to numerous applications in computational biology. in this paper we address a modified version of horspool's string matching algorithm using the probabilities of the different symbols to speed up the search. we show that the modified algorithm has a linear average running time; a precise asymptotical representation of the running time will be proven. a comparison of the average running time of the modified algorithm with well-known results for the original method shows that a substantial speed up for most of the symbol distributions has been achieved. finally, we show that the distribution of the symbols can be approximated to a high precision using a random sample of sublinear size.
note on ramsey theorems for spatial graphs. to show that ramsey theorem for spatial graphs without local knots does not hold in general, we construct a spatial embedding of kn;n which has no local knots on edges and which contains any subdivision of a given nonsplittable 2-component link.
completing prefix codes in submonoids. let m be a submonoid of the free monoid a*, and let x ⊆ m be a variable length code (for short a code). x is weakly m-complete if any word in m is a factor of some word in x* [j. néraud, c. selmi, free monoid theory: maximality and completeness in arbitrary submonoids, internat. j. algorithms comput. 13(5) (2003) 507-516]. given a code x ⊆ m, we are interested in the construction of a weakly m-complete code that contains x, if it exists. in the case where m and x are regular sets, the existence of such a code has been established [j. néraud, completing a code in a regular submonoid of the free monoid, in acts of mcu'2004, lecture notes in computer sciences, vol. 3354, springer, berlin, 2005, pp. 281-291; j. néraud, on the completion of codes in submonoids with finite rank, fund. inform., to appear]. actually, this result lays upon a method of construction that preserves the regularity of sets. as well known, any regular (or finite) code may be embedded into a regular (finite) prefix code that is complete in a*: instance: a regular submonoid m of a*, and a regular (or finite) prefix code x ⊆ m. question: does a weakly m-complete regular (finite) prefix code containing x exist?
locally complete sets and finite decomposable codes. we are interested in the concept of locally complete set: a subset x of the free monoid is locally complete if a code y a exists, with y a, x y, and such that both the sets of xand y have the same sets of factors. our contribution is based on the three following results: * a characterization of local completeness for very thin sets in terms of morphic images. * a polynomial time algorithm for deciding whether a finite code is locally complete. * a polynomial time algorithm for deciding whether a finite maximal code is decomposable
density via duality. we present an unexpected correspondence between homomorphism duality theorems and gaps in the poset of graphs and their homomorphisms. this gives a new proof of the density theorem for undirected graphs and solves the density problem for directed graphs.
learning erasing pattern languages with queries. a pattern is a finite string of constant and variable symbols. the non-erasing language generated by a pattern is the set of all strings of constant symbols that can be obtained by substituting non-empty strings for variables. in order to build the erasing language generated by a pattern, it is also admissible to substitute the empty string.the present paper deals with the problem of learning erasing pattern languages within angluin's model of learning with queries. moreover, the learnability of erasing pattern languages with queries is studied when additional information is available. the results obtained are compared with previously known results in case non-erasing pattern languages have to be learned.first, when regular pattern languages have to be learned, it is shown that the learnability results for the non-erasing case remain valid, if the proper superclass of all erasing regular pattern languages is the object of learning. second, in the general case, serious differences have been observed. for instance, it turns out that arbitrary erasing pattern languages cannot be learned in settings in which, in the non-erasing case, even polynomially many queries will suffice.
query automata over finite trees. a main task in document transformation and information retrieval is locating subtrees satisfying some pattern. therefore, unary queries, i.e., queries that map a tree to a set of its nodes, play an important role in the context of structured document databases. the motivation of this work is to understand how the natural and well-studied computation model of tree automata can be used to compute such queries. we define a query automaton (qa) as a deterministic two-way finite automaton over trees that has the ability to select nodes depending on the state and the label at those nodes. we study qas over ranked as well as over unranked trees. unranked trees differ from ranked ones in that there is no bound on the number of children of nodes. we characterize the expressiveness of the different formalisms as the unary queries definable in monadic second-order logic (mso). in contrast to the ranked case, special stay transitions had to be added to qas over unranked trees to capture mso. we establish the complexity of the non-emptiness, containment, and equivalence of qas to be complete for exptime.
multimodal logic programming. we give a framework for developing the least model semantics, fixpoint semantics, and sld-resolution calculi for logic programs in multimodal logics whose frame restrictions consist of the conditions of seriality (i.e. ∀x ∃y ri (x, y)) and some classical first-order horn clauses. our approach is direct and no special restriction on occurrences of □i and ♦i is required. we apply our framework for a large class of basic serial multimodal logics, which are parametefized by an arbitrary combination of generalized versions of axioms t, b, 4, 5 (in the form, e.g. 4 : □iϕ → □j □kϕ) and i: □i ϕ → □j ϕ. another part of the work is devoted to programming in multimodal logics intended for reasoning about multidegree belief, for use in distributed systems of belief, or for reasoning about epistemic states of agents in multiagent systems. for that we also use the framework, and although these latter logics belong to the mentioned class of basic serial multimodal logics, the special sld-resolution calculi proposed for them are more efficient.
leader election in plane cellular automata, only with left-right global convention. we give a linear time algorithm to elect a leader. this problem originated in networking and distributed computing research. given a graph, its vertices represent processors (here finite state machines), and its edges communication lines (here synchronous). the leader election problem consists in finding a protocol for a family of graphs which, upon iteration, distinguishes a vertex, edge or cycle by a special state called leader. here, the graphs are only required to be connected, and without holes. we describe the algorithm on a special class of planar graphs, prove its correctness and show how it extends to other classes.
nondeterministic regular expressions as solutions of equational systems. we define the class of the linear systems whose solution is expressible as a tuple of nondeterministic regular expressions when they are interpreted as trees of actions rather than as sets of sequences. we precisely characterize those systems that have a regular expression as "canonical" solution, and show that any regular expression can be obtained as a canonical solution of a system of the defined class.
an approximate a* algorithm and its application to the scs problem. in this paper we deal with algorithm a* and its application to the problem of finding the shortest common supersequence of a set of sequences. a* is a powerful search algorithm which may be used to carry out concurrently the construction of a network and the solution of a shortest path problem on it. we prove a general approximation property of a* which, by building a smaller network, allows us to find a solution with a given approximation ratio. this is particularly useful when dealing with large instances of some problem. we apply this approach to the solution of the shortest common supersequence problem and show its effectiveness.
a concurrent lambda calculus with futures. we introduce a new lambda calculus with futures, λ(fut), that models the operational semantics of concurrent statically typed functional programming languages with mixed eager and lazy threads such as alice ml, a concurrent extension of standard ml. λ(fut) is a minimalist extension of the call-by-value λ-calculus that is sufficiently expressive to define and combine a variety of standard concurrency abstractions, such as channels, semaphores, and ports. despite its minimality, the basic machinery of λ(fut) is sufficiently powerful to support explicit recursion and call-by-need evaluation.we present a static type system for λ(fut) and distinguish a fragment of λ(fut) that we prove to be uniformly confluent. this result confirms our intuition that reference cells are the sole source of indeterminism. this fragment assumes the absence of so called handle errors that violate the single assignment assumption of λ(fut)'s handled future-construct.finally, we present a linear type system for λ(fut) by which to prove the absence of handle errors. our system is rich enough to type definitions of the above mentioned concurrency abstractions. consequently, these cannot be corrupted in any (not necessarily linearly) well-typed context.
on point covers of c-oriented polygons. let s be any family of n c-oriented polygons of the two-dimensional euclidean plane e2, i.e., bounded intersection of halfplanes whose normal directions of edges belong to a fixed collection of c distinct directions. let (s) denote the packing number of s, that is the maximum number of pairwise disjoint objects of s. let (s) be the transversal number of s, that is the minimum number of points required so that each object contains at least one of those points. we provide linear-time algorithms t(n, c) = &thgr;(nc) for &agr;-fat c-oriented polytopes, translates or homothets of ed proving that g(2, c) = o(&agr;)d, g(2, c)&le;dd and g(2, c)&le;(3d3/2)d respectively
validating firewalls using flow logics. the ambient calculus is a calculus of computation that allows active processes to communicate and to move between sites. a site is said to be a protective firewall whenever it denies entry to all attackers not possessing the required passwords. we devise a computationally sound test for validating the protectiveness of a proposed firewall and show how to perform the test in polynomial time. the first step is the definition of a flow logic for analysing the flow of control in mobile ambients; it amounts to a syntax-directed specification of the acceptability of a control flow estimate. the second step is to define a hardest attacker and to determine whether or not there exists a control flow estimate that shows the inability of the hardest attacker to enter; if such an estimate exists, then none of the infinitely many attackers can enter unless they contain at least one of the passwords, and consequently the firewall cannot contain any trap doors.
secure multiparty computations without computers. many simple calculations can be done easier without computers than by using them. we show that the same holds for secure multiparty computations if the function to be computed is simple enough. our starting point is an observation of bert den boer: a multiparty computation of a logical and-gate can be performed by five simple playing cards. we show that by using a reasonable amount of cards many useful functions can be computed in such way that each input stays private.
computational complexity of uniform quantum circuit families and quantum turing machines. deutsch proposed two sorts of models of quantum computers, quantum turing machines (qtms) and quantum circuit families (qcfs). in this paper we explore the computational powers of these models and re-examine the claim of the computational equivalence of these models often made in the literature without detailed investigations. for this purpose, we formulate the notion of the codes of qcfs and the uniformity of qcfs by the computability of the codes. various complexity classes are introduced for qtms and qcfs according to constraints on the error probability of algorithms or transition amplitudes. their interrelations are examined in detail. for monte carlo algorithms, it is proved that the complexity classes based on uniform qcfs are identical with the corresponding classes based on qtms. however, for las vegas algorithms, it is still open whether the two models are equivalent. we indicate the possibility that they are not equivalent. in addition, we give a complete proof of the existence of a universal qtm efficiently simulating multi-tape qtms. we also examine the simulation of various types of qtms such as multi-tape qtms, single tape qtms, stationary, normal form qtms (snqtms), and qtms with the binary tapes. as a result, we show that these qtms are computationally equivalent to one another as computing models implementing not only monte carlo algorithms but also exact (or error-free) ones
uniformity of quantum circuit families for error-free algorithms. in order to establish the computational equivalence between quantum turing machines (qtms) and quantum circuit families (qcfs) using yao's quantum circuit simulation of qtms, we have previously introduced the class of uniform qcfs based on an infinite set of elementary gates, which has been shown to be computationally equivalent to polynomial-time qtms up to bounded error simulation. however, the complexity classes zqp and eqp introduced by bernstein and vazirani for qtms do not appear to equal their counterparts for uniform qcfs. recently, we have introduced a subclass of uniform qcfs, the class of finitely generated uniform qcfs, and showed that they are perfectly equivalent to the class of polynomial-time qtms in the sense that both classes can be exactly simulated with each other. here, we further investigate the power of uniform qcfs comparing with that of finitely generated uniform qcfs in detail. we obtain the following results: (i) if a permutation mf: |x)〉 ↦ |f(x)〉 can be implemented with zero error by a uniform qcf, then both f and f-1 can be exactly computed by uniform qcfs. (ii) the quantum fourier transform (qft) of any order cannot be implemented with zero error by any finitely generated uniform qcf, while it has been shown, in contrast, by mosca and zalka that the qft of any order can be exactly implemented by a uniform qcf.
a gap property of deterministic tree languages. we show that a tree language recognized by a deterministic parity automaton is either hard for the co-büchi level and therefore cannot be recognized by a weak alternating automaton, or is on a very low level in the hierarchy of weak alternating automata. a topological counterpart of this property is that a deterministic tree language is either π11 complete (and hence nonborel), or it is on the level π30 of the borel hierarchy. we also give a new simple proof of the strictness of the hierarchy of weak alternating automata.
complexity in the case against accuracy estimation. some authors have repeatedly pointed out that the use of the accuracy, in particular for comparing classifiers, is not adequate. the main argument concerns some assumptions of seldom validity or correctness underlying the use of this criterion. in this paper, we study the computational burden of the accuracy's replacement for building and comparing classifiers, using the framework of inductive logic programming. replacement is investigated in three ways: completion of the accuracy with an additional requirement, replacement of the accuracy with a bi-criterion recently introduced from statistical decision theory: the receiver operating characteristic analysis, and replacement of the accuracy by a single criterion. we prove very hard results for most of the possible replacements. a first result shows that allowing the arbitrary multiplication of clauses appears to be totally useless. "arbitrary" is to be taken in its broadest meaning, in particular exponential. the second point is the sudden appearance of the negative result, which is not a function of the criteria's demands. the third point is the equivalence in difficulty of all these different criteria. in contrast, the single accuracy's optimization appears to be tractable in this framework.
on domain-partitioning induction criteria: worst-case bounds for the worst-case based. one of the most popular induction scheme for supervised learning is also one of the oldest. it builds a classifier in a top-down fashion, following the minimization of a so-called index criterion. while numerous papers have reported experiments on this scheme, little has been known on its theoretical aspect until recent works on decision trees and branching programs using a powerful classification tool: boosting.in this paper, we look at this problem from a worst-case computational (rather than informational) standpoint. our conclusions for the ranking of these indexes minimization follow almost exactly that of boosting (with matching upper and lowerbounds), and provide extensions to more classes of boolean formulas such as decision lists, multilinear polynomials and symmetric functions. our results also exhibit a strong worst-case for the induction scheme, as we build particularly hard samples for which the replacement of most index criteria, or the class of concept representation, even when producing the same ranking as boosting does for the indexes, makes no difference at all for the concept induced. this is clearly not a limit of previous analyses, but a consequence of the induction scheme.
an optimal online algorithm for scheduling two machines with release times. we present a deterministic online algorithm for scheduling two parallel machines when jobs arrive over time and show that it is (1/2) (5&minus;v5) 1.38198-competitive. the best previously known algorithm is (3/2)-competitive. our upper bound matches a previously known lower bound, and thus our algorithm has the best possible competitive ratio. we also present a lower bound of 1.21207 on the competitive ratio of any randomized online algorithm for any number of machines. this improves a previous result of 4 &minus; 2v2 ?1.17157. copyright 2001 elsevier science b.v.
simple 8-state minimal time solution to the firing squad synchronization problem. the objective of the firing squad synchronization problem is to define sets of states and transition rules of a finite-state machine so that a one-dimensional array of such machines work synchronously. a minimal time solution to this problem was first found by goto in 1961. thereafter, other minimal time solutions were reported. i studied this problem and found an 8-state 119-rule solution by using a simple algorithm. the number of rules is much less than in baltzer's 8-state solution and the same as in mazoyer's 6-state solution.
temporal stratification tests for linear and branching-time deductive databases. we consider the problem of extending temporal deductive databases with stratified negation. we argue that the classical stratification test for deductive databases is too restrictive when one shifts attention to the temporal case. moreover, as we demonstrate, the (more general) local stratification approach is impractical: detecting whether a temporal deductive database is locally stratified is shown to be co-np hard (even if one restricts attention to programs that only use one predicate symbol and two constants). for these reasons we define temporal stratification, an intermediate notion between stratification and local stratification. we demonstrate that for the temporal deductive databases we consider, temporal stratification coincides with local stratification in certain important cases in which the latter is polynomial-time decidable. we then develop two algorithms for detecting temporal stratification. the first algorithm applies to linear-time temporal deductive databases and it is efficient and more general than existing approaches; however, the algorithm sacrifices completeness for efficiency since it does not cover the whole class of temporally stratified programs. the second algorithm applies to branching-time temporal deductive databases (which include as a special case the linear-time ones). this algorithm is more expensive from a computational point of view, but it covers the whole class of temporally stratified programs. we discuss the relative merits of the two algorithms and compare them with other existing approaches.
the complexity of equivalence and isomorphism of systems of equations over finite groups. we study the computational complexity of the isomorphism and equivalence problems on systems of equations over a fixed finite group. we show that the equivalence problem is in p if the group is abelian, and conp-complete if the group is non-abelian. we prove that if the group is non-abelian, then the problem of deciding whether two systems of equations over the group are isomorphic is conp-hard. if the group is abelian, then the isomorphism problem is graph isomorphism-hard. moreover, if we impose the restriction that all equations are of bounded length, then we prove that the isomorphism problem for systems of equations over finite abelian groups is graph isomorphism-complete. finally, we prove that the problem of counting the number of isomorphisms of systems of equations is no harder than deciding whether there exist any isomorphisms at all.
exact real number computations relative to hereditarily total functionals. we show that the continuous existential quantifier ∃ω is not definable in escardó's real-pcf from all functionals equivalent to a given total one in a uniform way. we further prove that relative to any total functional of type (i → i) → i which gives the maximum-value for any total input, we may, given a computable, total functional φ of type (r → r) → r find a real-pcf-definable total ψ equivalent to φ.
hierarchies of total functionals over the reals. we compare two natural constructions, the a-hierarchy and the r-hierarchy, of hereditarily total, continuous and extensional functionals of finite types over the reals. the a-hierarchy is based on the closed interval domain representation of the reals while the r-hierarchy is based on the binary negative digit representation. we show that the two hierarchies share a common maximal core. to this end, we construct an alternative to the r-hierarchy and prove a density theorem for this alternative hierarchy.
simple proof of the completeness theorem for second-order classical and intuitionistic logic by reduction to first-order mono-sorted logic. we present a simpler way than usual to deduce the completeness theorem for the second-order classical logic from the first-order one. we also extend our method to the case of second-order intuitionistic logic.
matrix algebra preconditioners for multilevel toeplitz systems do not insure optimal convergence rate. in the last decades several matrix algebra optimal and superlinear preconditioners (those assuring a strong clustering at the unity) have been proposed for the solution of polynomially ill-conditioned toeplitz linear systems. the corresponding generalizations for multilevel structures are neither optimal nor superlinear (see e.g. contemp. math. 281 (2001) 193). concerning the notion of superlinearity, it has been recently shown that the proper clustering cannot be obtained in general (see linear algebra appl. 343-344 (2002) 303; siam j. matrix anal. appl. 22(1) (1999) 431; math. comput. 72 (2003) 1305). in this paper, by exploiting a proof technique previously proposed by the authors (see contemp. math. 323 (2003) 313), we prove that the spectral equivalence and the essential spectral equivalence (up to a constant number of diverging eigenvalues) are impossible too. in conclusion, optimal matrix algebra preconditioners in the multilevel setting simply do not exist in general and therefore the search for optimal iterative solvers should be oriented to different directions with special attention to multilevel/multigrid techniques.
domain theory for concurrency. a simple domain theory for concurrency is presented. based on a categorical model of linear logic and associated comonads, it highlights the role of linearity in concurrent computation. two choices of comonad yield two expressive metalanguages for higher-order processes, both arising from canonical constructions in the model. their denotational semantics are fully abstract with respect to contextual equivalence. one language derives from an exponential of linear logic; it supports a straightforward operational semantics with simple proofs of soundness and adequacy. the other choice of comonad yields a model of affine-linear logic, and a process language with a tensor operation to be understood as a parallel composition of independent processes. the domain theory can be generalised to presheaf models, providing a more refined treatment of nondeterministic branching. the article concludes with a discussion of a broader programme of research, towards a fully fledged domain theory for concurrency.
using acceptors as transducers. we wish to use a given nondeterministic two-way multi-tape acceptor as a transducer by supplying the contents for only some of its input tapes, and asking it to generate the missing contents for the other tapes. we provide here an algorithm for assuring beforehand that this transduction always results in a finite set of answers. we also develop an algorithm for evaluating these answers whenever the previous algorithm indicated their finiteness. furthermore, our algorithms can be used for speeding up the simulation of these acceptors even when not used as transducers. copyright 2001 elsevier science b.v.
theoretical aspects of connectivity-based multi-hop positioning. we investigate the theoretical limits of positioning algorithms. in particular, we study scenarios where the nodes do not receive anchors directly (multi-hop) and where no physical distance or angle information whatsoever is available (connectivity-based). since we envision large-scale sensor networks as an application, we are interested in fast, distributed algorithms. as such, we show that plain hop algorithms are not competitive. instead, for one-dimensional unit disk graphs we present an optimal algorithm hs. for two or more dimensions, we propose an algorithm ghost which improves upon the basic hop algorithm in theory and in simulations.
algebraic and model-theoretic properties of tilings. we investigate the relations between the geometric properties of tilings and the algebraic and model-theoretic properties of associated relational structures. isomorphism and local isomorphism of tilings up to translation correspond to isomorphism and elementary equivalence of relational structures. in particular, two penrose tilings, or two robinson tilings, are elementarily equivalent. classical results concerning the local isomorphism property and the "extraction preorder" for tilings are generalized to uniformly locally finite relational structures.then, we define "equational structures", which generalize both cayley graphs of groups and relational structures associated to tilings, and for which we have an appropriate notion of free structure relative to a system of equations. for each finite system σ of prototiles and local configurations, we give a finite set of local conditions characterizing the connected relational structures which are homomorphic images of σ-tilings. it follows that tilings are free relative to finite systems of equations which express these conditions. we also prove that the theory of a tiling is superstable, model-complete, and can be axiomatized by ∀∃ sentences. one ∀∃ sentence suffices in the case of penrose tilings or robinson tilings.
integrating information visualization and retrieval for www information discovery. an important technology in knowledge discovery is to access the desired information from the large amount of data stored on the www. at present, such information can be accessed by a browser itself or by using a keyword search function. however, browsing is a time consuming task where a user must access individual pages one by one. furthermore, in keyword searches, it is difficult for users to provide reasonable keywords in knowledge discovery processes. this paper outlines an approach for integrating information visualization and retrieval into www information discovery. in this approach, the link structure of a web site is displayed in a 3-d hyperbolic tree in which the height of a node (corresponding to a web page) within the tree indicates a user's "interest" for each page. here, interest is calculated by a fitting function between a page and a user-supplied query (nested keywords). this measure can be used to filter uninteresting pages, reducing the size of the link structure. furthermore, each web page is modeled as semi-structured data and can also be displayed as a hyperbolic tree in which the result of query evaluation is visible. such functions are incorporated within our browser, allowing us to interactively discover desired pages from a large web site. we selected typical web sites to show the performance of the proposed method with improved accuracy and efficiency in www information discovery. here, accuracy indicates how surely the user accesses his/her desired documents, and efficiency indicates how quickly the user reaches the documents.
a uniform semantic proof for cut-elimination and completeness of various first and higher order logics. we present a natural generalization of girard's (first order) phase semantics of linear logic (theoret. comput. sci. 50 (1987)) to intuitionistic and higher-order phase semantics. then we show that this semantic framework allows us to derive a uniform semantic proof of the (first order and) higher order cut-elimination theorem (as well as a (first order and) higher order phase-semantic completeness theorem) for various different logical systems at the same time. our semantic proof works for various different logical systems uniformly in a strong sense (without any change of the argument of proof): it works for both first order and higher order versions and for linear, substructural, and standard logics uniformly, and for both their intuitionistic and classical versions uniformly.
effects of domain characteristics on instance-based learning algorithms. this paper presents average-case analyses of instance-based learning algorithms. the algorithms analyzed employ a variant of k-nearest neighbor classifier (k-nn). our analysis deals with a monotone m-of-n target concept with irrelevant attributes, and handles three types of noise: relevant attribute noise, irrelevant attribute noise, and class noise. we formally represent the expected classification accuracy of k-nn as a function of domain characteristics including the number of training instances, the number of relevant and irrelevant attributes, the threshold number in the target concept, the probability of each attribute, the noise rate for each type of noise, and k. we also explore the behavioral implications of the analyses by presenting the effects of domain characteristics on the expected accuracy of k-nn and on the optimal value of k for artificial domains.
a recognition and parsing algorithm for arbitrary conjunctive grammars. conjunctive grammars are basically context-free grammars with an explicit set intersection operation added to the formalism of rules. this paper presents a cubic-time recognition and parsing algorithm for this family of grammars, which is applicable to an arbitrary conjunctive grammar without any initial transformations.the algorithm is in fact an extension of the context-free recognition and parsing algorithm due to graham, harrison and ruzzo, and it retains the cubic time complexity of its prototype. it is shown that for the case of linear conjunctive grammars this algorithm can be modified to work in quadratic time and use linear space.the given algorithm is then applied to solve the membership problem for conjunctive grammars in polynomial time, and subsequently to prove the problem's p-completeness, as well as p-completeness of the membership problem for linear conjunctive grammars.
on the closure properties of linear conjunctive languages. linear conjunctive grammars are conjunctive grammars in which the body of each conjunct contains no more than a single nonterminal symbol. they can at the same time be thought of as a special case of conjunctive grammars and as a generalization of linear context-free grammars that provides an explicit intersection operation.although the set of languages generated by these grammars is known to include many important noncontext-free languages, linear conjunctive languages are still all square-time, and several practical algorithms have been devised to handle them, which makes this class of grammars quite suitable for use in applications.in this paper we investigate the closure properties of the language family generated by linear conjunctive grammars; the main result is its closure under complement, which implies that it is closed under all set-theoretic operations. we also consider several cases in which the concatenation of two linear conjunctive languages is certain to be linear conjunctive. in addition, it is demonstrated that linear conjunctive languages are closed under quotient with finite languages, not closed under quotient with regular languages, and not closed under ε-free homomorphism.
on the number of nonterminals in linear conjunctive grammars. the number of nonterminals in a linear conjunctive grammar is considered as a descriptional complexity measure of this family of languages. it is proved that a hierarchy collapses, and for every linear conjunctive grammar there exists and can be effectively constructed a linear conjunctive grammar that accepts the same language and contains exactly two nonterminals. this yields a partition of linear conjunctive languages into two nonempty disjoint classes of those with nonterminal complexity 1 and 2. the basic properties of the family of languages for which one nonterminal suffices are established. nonterminal complexity of grammars in the linear normal form is also investigated.
the dual of concatenation. a binary language-theoretic operation is proposed, which is dual to the concatenation of languages in the same sense as the universal quantifier in logic is dual to the existential quantifier; the dual of kleene star is defined accordingly. these operations arise whenever concatenation or star appear in the scope of negation. the basic properties of the new operations are determined in the paper. their use in regular expressions and in language equations is considered, and it is shown that they often eliminate the need of using negation, at the same time having an important technical advantage of being monotone. a generalization of context-free grammars featuring dual concatenation is introduced and proved to be equivalent to the recently studied boolean grammars.
unresolved systems of language equations: expressive power and decision problems. unresolved language equations and inequalities with various sets of operations are considered. it is proved that systems of unresolved equations with linear concatenation and union only, as well as systems with linear concatenation and intersection only, are as expressive as the more general unresolved inequalities with all boolean operations and unrestricted concatenation: the class of languages defined by unique (least, greatest) solutions of these systems is shown to coincide with the families of recursive (re, co-re, resp.) sets, which result extends even to individual equations of the form ∪ujxijvj = w∪∪yjxtjzj. on the other hand, unresolved equations with different sets of operations are shown to differ in the hardness of their decision problems, and it is demonstrated that several types of unresolved equations cannot effectively simulate each other in spite of the equality of the language families they define.
precedence-inclusion patterns and relational learning. in this paper we introduce precedence-inclusion patterns, which are sets with a strictly partially ordered set of strict partial orders, along with some additional structure. the definition of these structures reflects how multiple partial orders interact in a number of situations such as in text, images, and video. in particular, precedence-inclusion patterns generalize constituent structure trees familiar to computational linguists. our interest in these objects was initially sparked by their connection with problems of relational learning. we develop the general mathematical theory of precedence-inclusion patterns, we show that each finite set of finite precedence-inclusion relations has a minimal most specific generalization that is unique up to isomorphism, and we explain how this result relates to relational learning.
games characterizing levy-longo trees. we present a simple strongly universal innocent game model for levy-longo trees, i.e. every point in the model is the denotation of a unique levy-longo tree. the observational quotient of the model then gives a universal, and hence fully abstract, model of the pure lazy lambda calculus.
logical analysis of data with decomposable structures. in such areas as knowledge discovery, data mining and logical analysis of data, methodologies to find relations among attributes are considered important. in this paper, given a data set (t,f) where t ⊆ {0,1}n denotes a set of positive examples and f ⊆ {0,1}n denotes a set of negative examples, we propose a method to identify decomposable structures among the attributes of the data. we first study computational complexity of the problem of finding decomposable boolean extensions. since the problem turns out to be intractable (i.e., np-complete), we propose a heuristic algorithm in the second half of the paper. our method searches a decomposable partition of the set of all attributes by using the error sizes of almost-fit decomposable extensions as a guiding measure, and then finds structural relations among the attributes in the obtained partition. some results of numerical experiment on randomly generated data sets are also reported.
proof by computation in the coq system. in informal mathematics, statements involving computations are seldom proved. instead, it is assumed that readers of the proof can carry out the computations on their own. however, when using an automated proof development system based on type theory, the user is forced to find proofs for all claimed propositions, including computational statements. this paper presents a method to automatically prove statements from primitive recursive arithmetic. the method replaces logical formulas by boolean expressions. a correctness proof is constructed, which states that the original formula is derivable, if and only if the boolean expression equals true. because the boolean expression reduces to true, the conversion rule yields a trivial proof of the equality. by combining this proof with the correctness proof, we get a proof for the original statement.
optimal oblivious routing on d-dimensional meshes. in this work we consider deterministic oblivious k-k routing algorithms with buffer size o(k). we present an asymptotically optimal o(k√nd) step oblivious k-k routing algorithm for d-dimensional n × .... × n meshes of nd processors for all k ≥ 1 and d > 1. we further show how the algorithm can be used to achieve asymptotically optimal oblivious k-k routing algorithms on other networks.
avoiding coding tricks by hyperrobust learning. the present work introduces and justifies the notion of hyperrobust learning where one fixed learner has to learn all functions in a given class plus their images under primitive recursive operators. the following are shown: the notion of learnability does not change if the class of primitive recursive operators is replaced by a larger enumerable class of operators. a class is hyperrobustly ex-learnable iff it is a subclass of a recursively enumerable family of total functions. so, the notion of hyperrobust learning overcomes a problem of the traditional definitions of robustness which either do not preserve learning by enumeration or still permit topological coding tricks for the learning criterion ex. hyperrobust bc-learning as well as the hyperrobust version of ex-learning by teams are more powerful than hyperrobust ex-learning. the notion of bounded totalty reliable bc-learning is properly between hyperrobust ex-learning and hyperrobust bc-learning. furthermore, the bounded totally reliable bc-learnable classes are characterized in terms of infinite branches of certain enumerable families of bounded recursive trees. a class of infinite branches of another family of trees separates hyperrobust bc-learning from totally reliable bc-learning. furthermore, the notion of hyperrobust learning aided by selected context turns out to be much more restrictive than its counterpart for robust learning.
on the covering radius problem for ternary self-dual codes. in the present paper we develop a method to determine the cost weight distributions and covering radius of extremal ternary self-dual codes of various lengths. the notion of modified jacobi polynomials is introduced and elementary aspects of it art discussed. algebraic foundation has much room for further investigations. since the algorithms underlining in our approach to this problem are sound, and we can bet many numerical results as far as the computer runs in a reasonable time.
a coalgebraic view on positive modal logic. positive modal logic is the restriction of the modal local consequence relation defined by the class of all kripke models to the propositional negation-free modal language. the class of positive modal algebras is the one canonically associated with pml according to the theory of the algebrization of logics (lecture notes in logic, springer, berlin, 1996). a priestley-style duality is established between the category of positive modal algebras and the category of k+-spaces in (j. igpl 7 (6) (1999) 683). in this paper, we establish a categorical equivalence between the category k+ of k+-spaces and the category coalg(v) of coalgebras of a suitable endofunctor v on the category of priestley spaces.
sequential and parallel algorithms for the nca problem on pure pointer machines. we present a simple, arithmetic-free, efficient scheme to compress trees maintaining the nca information. we use this compression scheme to provide an o(n + q lg lg n) solution for solving the nca problem on pure pointer machines (ppms)--i.e., pointer machines with no arithmetic capabilities--in both the static and dynamic case, where n is the number of add-leaf/delete operations and q is the number of nca queries. this solution is optimal. we also extend the solution to a parallel pointer machine algorithm. the algorithm assumes that the tree t is known in advance and it requires o(lg n) parallel time and o(n) processors for pre-processing where n is the number of nodes in the tree. thereafter, it can answer any nca query in o(lg lg n) time using a single processor. to our knowledge, this is the best known parallel pointer machine algorithm for the nca problem. our nca algorithm requires an efficient parallel solution of the temporal precedence problem [ranjan et al., the temporal precedence problem, algorithmica 28 (2000) 288-306]. we provide an efficient parallel pointer machine algorithm to solve this problem as well.
iterative inversion of structured matrices. iterative processes for the inversion of structured matrices can be further improved by using a technique for compression and refinement via the least-squares computation. we review such processes and elaborate upon incorporation of this technique into the known frameworks.
quantifiers and approximation. we investigate the relationship between logical expressibility of np optimization problems and their approximation properties. first such attempt was made by papadimitriou and yannakakis, who defined the class of npo problems max np. we show that many important optimization problems do not belong to max np and that in fact there are problems in p which are not is maxnp. the problems we consider fit naturally in a new complexity class that we call max ii sub 1. we prove that several natural optimization problems are complete for max ii sub 1 under approximation preserving reductions. all these complete problems are non-approximable unless p=np. this motivates the definition of subclasses of max ii sub 1 that only contain problems which are presumably easier with respect to approximation. in particular, the class that we call rmax(2), contains approximable problems and problems like max clique that are not known to be non-approximable. we prove that max clique and other natural optimization problems are complete for rmax(2). all the complete problems in rmax(2) share the interesting property that they either are non-approximable or are approximable to any degree of accuracy.
analysis of multiple quickselect variants. multiple quickselect is an algorithm that uses the idea of quicksort to search for several order statistics simultaneously. in order to improve the efficiency of quicksort, one can use the median of 2t + 1 randomly chosen elements as pivot element in the partitioning stage. such a median of 2t + 1 partition can also be applied to multiple quickselect to reduce the number of comparisons. here we give an analysis of such multiple quickselect variants that use median of 2t + 1 partition and describe for these algorithms the asymptotic behaviour of the expected number of required comparisons to find p-order statistics in a data set of size n for n → ∞ and fixed p.
on a conjecture related to geometric routing. we conjecture that any planar 3-connected graph can be embedded in the plane in such a way that for any nodes s and t, there is a path from s to t such that the euclidean distance to t decreases monotonically along the path. a consequence of this conjecture would be that in any ad hoc network containing such a graph as a spanning subgraph, two-dimensional virtual coordinates for the nodes can be found for which the method of purely greedy geographic routing is guaranteed to work. we discuss this conjecture and its equivalent forms show that its hypothesis is as weak as possible, and show a result delimiting the applicability of our approach: any 3-connected k3,3-free graph has a planar 3-connected spanning subgraph. we also present two alternative versions of greedy routing on virtual coordinates that provably work. using steinitz's theorem we show that any 3-connected planar graph can be embedded in three dimensions so that greedy routing works, albeit with a modified notion of distance; we present experimental evidence that this scheme can be implemented effectively in practice. we also present a simple but provably robust version of greedy routing that works for any graph with a 3-connected planar spanning subgraph.
hierarchies for classes of priority algorithms for job scheduling. priority algorithm is a model of computation capturing the notion of greedy and greedy-like algorithm. this paper concerns priority algorithms for job scheduling. three main restrictions are defined for priority algorithms, namely: memoryless, greedy and fixed. it was asked in [a. borodin, m.n. nielsen, c. rackoff, (incremental) priority algorithms, in: proc. 13th annu. symp. discrete algorithms (soda), january 2002, pp. 752-761 (also in algorithmica 37(4) (2003) 295-326] whether the general class of priority algorithms is of different power from the restricted class of greedy-priority algorithms (for the job scheduling problem). we answer this question affirmatively by showing that a specific priority algorithm cannot be simulated by any greedy-priority algorithm on every input. furthermore we systematically compare every two classes of priority algorithms for different settings of job scheduling. we also define a hierarchy for priority algorithms of bounded memory which lies between the class of memoryless and the class of priority algorithms with memory, and we show that this memory hierarchy is robust.
deformation techniques to solve generalised pham systems. in heintz et al. (electron. j. sadio 1(1) (1998) 37), castro et al. (found., comput. math. (2003) to appear) and pardo (proceedings eaca'2000, 2000, pp. 25-51), the authors have shown that universal solving procedures require exponential running time. roughly speaking, a universal solving procedure takes as input a system of multivariate polynomial equations and outputs complete symbolic information on the solution variety. here, we introduce a nonuniversal solving procedure adapted to generalised pham systems. the aim is to compute partial information of the variety defined by the input system. the algorithm is based on an homotopic deformation and on a non-archimedean lifting procedure from a non-singular zero of the homotopy curve. the complexity of the procedure is also stated and it depends on some intrinsic quantity called the deformation degree of the given input system.
three concepts of decidability for general subsets of uncountable spaces. there is no uniquely standard concept of an effectively decidable set of real numbers or real n-tuples. here we consider three notions: decidability up to measure zero [m.w. parker, undecidability in rn: riddled basins, the kam tori, and the stability of the solar system, phil. sci. 70(2) (2003) 359-382], which we abbreviate d.m.z.; recursive approximability [or r.a.; k.-i. ko, complexity theory of real functions, birkhäuser, boston, 1991]; and decidability ignoring boundaries [d.i.b.; w.c. myrvold, the decision problem for entanglement, in: r.s. cohen et al. (eds.), potentiality, entanglement, and passion-at-a-distance: quantum mechanical studies fo abner shimony, vol. 2, kluwer academic publishers, great britain, 1997, pp. 177-190]. unlike some others in the literature, these notions apply not only to certain nice sets, but to general sets in rn and other appropriate spaces. we consider some motivations for these concepts and the logical relations between them. it has been argued that d.m.z. is especially appropriate for physical applications, and on rn with the standard measure, it is strictly stronger than r.a. [m.w. parker, undecidability in rn: riddled basins, the kam toil, and the stability of the solar system, phil. sci. 70(2) (2003) 359-382]. here we show that this is the only implication that holds among our three decidabilities in that setting. under arbitrary measures, even this implication fails. yet for intervals of non-zero length, and more generally, convex sets of non-zero measure, the three concepts are equivalent.
on computing hilbert bases via the elliot-macmahon algorithm. the ways of using the elliot-macmahon algorithm to compute the hilbert base of a system of linear diophantine equations known so far are either not efficient or can fail to terminate. we present a version of an algorithm exploiting this range of ideas, which however is reasonably efficient as well as finite.
coalgebraic modal logic: soundness, completeness and decidability of local consequence. this paper studies finitary modal logics, interpreted over coalgebras for an endofunctor, and establishes soundness, completeness and decidability results. the logics are studied within the abstract framework of coalgebraic modal logic, which can be instantiated with arbitrary endofunctors on the category of sets. this is achieved through the use of predicate liftings, which generalise atomic propositions and modal operators from kripke models to arbitrary coalgebras. predicate liftings also allow us to use induction along the terminal sequence of the underlying endofunctor as a proof principle. this induction principle is systematically exploited to establish soundness, completeness and decidability of the logics. we believe that this induction principle also opens new ways for reasoning about modal logics: our proof of completeness does not rely on a canonical model construction, and the proof of the finite model property does not use filtrations.
a coordination approach to mobile components. we present a calculus for mobile systems, the main novel feature of which is the separation between dynamic and topological aspects of distributed computations. our calculus realises the following basic assumptions: (1) every computation executes in a uniquely determined location, (2) processes modify the distributed structure by means of predefined operations, (3) the underlying programming language can be changed easily, and (4) locations are hierarchically organised. this paper introduces our calculus, and shows, that this separation of concerns leads to a perfect match between the logical, syntactical and algebraic theory. we discuss a core calculus, and extensions with local names and with multiple names.
realizing boolean functions on disjoint sets of variables. for switching functions $f$ let $c(f)$ be the combinatorial complexity of $f$. we prove that for every $\varepsilon < 0$ there are arbitrarily complex functions $f:\{0,1\}^{n} \rightarrow \{0,1\}^{n}$ such that $c(fxf) \leq (1+ \varepsilon) c(f)$ and arbitrarily complex functions $g:\{0,1\}$ such that $c(v c(fxf)) \leq (1 + \varepsilon)c(f)$. these results and the techniques developed to obtain them are used to show, that ashenhurst decomposition of switching functions does not always yield optimal circuits and to prove a new result concerning the trade-off between circuit size and monotone circuit size. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
a guide to membrane computing. membrane systems are models of computation which are inspired by some basic features of biological membranes. in a membrane system multisets of objects are placed in the compartments defined by the membrane structure, and the objects evolve by means of "reaction rules" also associated with the compartments, and applied in a maximally parallel, nondeterministic manner. the objects can pass through membranes, the membranes can change their permeability, they can dissolve, and they can divide. these features are used in defining transitions between configurations of the system, and sequences of transitions are used to define computations. in the case of symbol-objects, we compute a set of numbers, and in the case of string-objects we compute a set of strings, hence a language. many different classes of such computing devices (now called p systems) have already been investigated. most of them are computationally universal, i.e., equal in power to turing machines. systems with an enhanced parallelism are able to trade space for time and solve in this way (at least in principle), by making use of an exponential space, intractable problems in a feasible time.the present paper presents the basic ideas of computing with membranes and some fundamental properties (mostly concerning the computational power and efficiency) of p systems of various types.
the continuum as a final coalgebra. we define the continuum up to order isomorphism, and hence up to homeomorphism via the order topology, in terms of the final coalgebra of either the functor nx, product with the set of natural numbers, or the functor 1+nx. this makes an attractive analogy with the definition of n itself as the initial algebra of the functor 1+x, disjoint union with a singleton. we similarly specify baire space and cantor space in terms of these final coalgebras. we identify two variants of this approach, a coinductive definition based on final coalgebraic structure in the category of sets, and a direct definition as a final coalgebra in the category of posets. we conclude with some paradoxical discrepancies between continuity and constructiveness in this setting.
greedy expansions and sets with deleted digits. we generalize a result of daróczy and kátai, on the characterization of univoque numbers with respect to a non-integer base (publ. math. debrecen 46(3-4) (1995) 385) by relaxing the digit alphabet to a generic set of real numbers. we apply the result to derive the construction of a büchi automaton accepting all and only the greedy sequences for a given base and digit set. in the appendix, we prove a more general version of the fact that the expansion of an element x ∈ q(q) is ultimately periodic, if q is a pisot number.
optimistic atomic broadcast: a pragmatic viewpoint. this paper presents the optimistic atomic broadcast algorithm (opt-abcast) which exploits the spontaneous total-order property experienced in local-area networks in order to allow fast delivery of messages. the opt-abcast algorithm is based on a sequence of stages, and messages can be delivered during a stage or at the end of a stage. during a stage, processes deliver messages fast. whenever the spontaneous total-order property does not hold, processes terminate the current stage and start a new one by solving a consensus problem which may lead to the delivery of some messages. we evaluate the efficiency of the opt-abcast algorithm using the notion of delivery latency.
playing by searching: two strategies against a linearly bounded liar. the problem of searching in the presence of errors is modeled as a game between a questioner and a responder. the responder chooses an integer x ∈ {1,..., n}, and the questioner has to determine x by asking a predetermined number of queries. the responder can lie at his pleasure, provided that at the end of the game the fraction of lies does not exceed a certain constant r. it is known that the questioner may win the game if and only if r < 1/3;. under the latter hypothesis, we state a lower bound on the number q(n, r) of queries needed by the questioner to win the game, even if he is allowed for arbitrary membership queries. next, we analyze two questioning strategies for the model where only comparison queries are allowed. the first strategy improves on the known upper bound on q(n,r); the second one achieves the same value of q(n,r), but makes also sure that each query can be formulated in constant time.
searching games with errors - fifty years of coping with liars. this is a survey on searching with errors, considered in the framework of two-person games. the responder thinks of an object in the search space, and the questioner has to find it by asking questions to which the responder provides answers, some of which are erroneous. we give a taxonomy of such games, depending on the type of questions allowed, on the degree of interactivity between the players, and on the imposed limitations on errors. we survey the existing results concerning such games, concentrating on the issue of optimizing the questioner's querying strategy, and pointing out open problems. we show the relations between searching games with errors and problems concerning communication through a noisy channel and error-correcting codes. finally, we discuss other search and computation problems with faulty feedback which are related to searching with errors
a compositional framework for fault tolerance by specification transformation. the incorporation of a recovery algorithm into a program can be viewed as a program transformation, converting the basic program into a fault-tolerant version. we present a framework in which such program transformations are accompanied by a corresponding formula transformation which obtains properties of the fault-tolerant versions of the programs from properties of the basic programs. compositionality is achieved when every property of the fault-tolerant version can be obtained from a transformed property of the basic program. a verification method for proving the correctness of formula transformations is presented. this makes it possible to prove just once that a formula transformation corresponds to a program transformation, removing the need to prove separately the correctness of each transformed program. keywords: parallel algorithms, distributed algorithms, fault-tolerance, specification, verification.
local majorities, coalitions and monopolies in graphs: a review. this paper provides an overview of recent developments concerning the process of local majority voting in graphs, and its basic properties, from graph theoretic and algorithmic standpoints.
informative labeling schemes for graphs. this paper introduces the notion of informative labeling schemes for arbitrary graphs. let f(w) be a function on subsets of vertices w. an f labeling scheme labels the vertices of a weighted graph g in such a way that f(w) can be inferred (or at least approximated) efficiently for any vertex subset w of g by merely inspecting the labels of the vertices of w, without having to use any additional information sources.a number of results illustrating this notion are presented in the paper. we begin by developing f labeling schemes for three functions f over the class of n-vertex trees. the first function, seplevel, gives the separation level of any two vertices in the tree, namely, the depth of their least common ancestor. the second, lca, provides the least common ancestor of any two vertices. the third, center, yields the center of any three given vertices v1, v2, v3 in the tree, namely, the unique vertex z connected to them by three edge-disjoint paths. all of these three labeling schemes use o(log2 n)-bit labels, which is shown to be asymptotically optimal.our main results concern the function steiner(w), defined for weighted graphs. for any vertex subset w in the weighted graph g, steiner(w) represents the weight of the steiner tree spanning the vertices of w in g. considering the class of n-vertex trees with m-bit edge weights, it is shown that for this class there exists a steiner labeling scheme using o((m + log n)log n) bit labels, which is asymptotically optimal. it is then shown that for the class of arbitrary n-vertex graphs with m-bit edge weights, there exists an approximate-steiner labeling scheme, providing an estimate (up to a factor of o(log n)) for the steiner weight steiner(w) of a given set of vertices w, using o((m + log n)log2 n) bit labels.
the first order theory of primal grammars is decidable. the formalism of primal grammars is one of the most powerful term schematization languages (theoret. comput. sci. 176(1-2) (1997) 111). in this paper, we describe an algorithm to check the satisfiability of first-order formulae in the theory of primal grammars. the correctness, completeness and termination of the algorithm are proven. the core of the procedure is the universal quantifier elimination method, which is based on a new explosion rule especially devoted to handle primal terms.
efficient transitive closure of sparse matrices over closed semirings. this paper surveys several alternative data structures and algorithms for multiplying sparse upper-triangular matrices over closed semirings, and evaluates their efficiency in computing transitive closures of matrices over the boolean semiring. two new variants are introduced that outperform previously known methods on a collection of large data-sets drawn from linguistic applications.
lambek calculus is np-complete. we prove that for both the lambek calculus l and the lambek calculus allowing empty premises l* the derivability problem is np-complete. it follows that also for the multiplicative fragments of cyclic linear logic and noncommutative linear logic the derivability problem is np-complete.
parametrization of approximate algebraic curves by lines. it is well known that irreducible algebraic plane curves having a singularity of maximum multiplicity are rational and can be parametrized by lines. in this paper, given a tolerance ε > 0 and an ε-irreducible algebraic plane curve l of degree d having an ε-singularity of multiplicity d - 1, we provide an algorithm that computes a proper parametrization of a rational curve that is exactly parametrizable by lines. furthermore, the error analysis shows that under certain initial conditions that ensures that points are projectively well defined, the output curve lies within the offset region of l at distance at most 2√2ε1(2d)exp(2).
approximating algebraic functions by means of rational ones. in this paper, we use eco method and the concept of succession rule to enumerate restricted classes of combinatorial objects. let &&ohgr; be the succession rule describing a construction of a combinatorial objects class, then the construction of the restricted class is described by means of an approximating succession rule &ohgr;rk obtained from &&ohgr; in a natural way. we give sufficient conditions for the rule k to be finite; finally we determine finite approximating rules for various classes of paths, and the approximation of the corresponding algebraic language with a regular one.
the asymptotic distribution of elements in automatic sequences. in an automatic sequence an element need not have an asymptotic density. in this paper a necessary and sufficient criterion is proved for the existence of the asymptotic density of a given element. if it does not exist the asymptotic distribution of the element can be described in terms of a function h whose graph is self-similar. an algorithm is given to decide whether h is piecewise continuously differentiable, and in this case it can be computed effectively. finally, it is shown that the h∞-density of an element in an automatic sequence always exists and equals its logarithmic density.
unary algebras, semigroups and congruences on free semigroups. in the triangle consisting of automata, languages and semigroups various correspondences of eilenberg's type between languages and semigroups and between automata and languages are known, and it remains to establish similar connections between automata and semigroups. in this paper we consider a more general case by taking unary x-algebras instead of automata and we establish complete lattice isomorphisms between the lattices of σ-varieties of x-algebras, κ-varieties of semigroups and weakly invariant congruences on the free semigroup x+, where κ is the cardinality of x, between the lattices of generalized σ-varieties of x-algebras, generalized κ-varieties of semigroups and filters of the lattice of weakly invariant congruences on x+, and between the lattices of pseudo-σ-varieties of x-algebras and pseudo-κ-varieties of semigroups.
positive varieties of tree languages. pin's variety theorem for positive varieties of string languages and varieties of finite ordered semigroups is proved for trees, i.e., a bijective correspondence between positive varieties of tree languages and varieties of finite ordered algebras is established. this, in turn, is extended to generalized varieties of finite ordered algebras, which corresponds to steinby's generalized variety theorem. also, families of tree languages and classes of ordered algebras that are definable by ordered (syntactic or translation) monoids are characterized.
a new approach to all-pairs shortest paths on real-weighted graphs. we present a new all-pairs shortest path algorithm that works with real-weighted graphs in the traditional comparison-addition model. it runs in o(mn + n2 log log n) time, improving on the long-standing bound of o(mn + n2 log n) derived from an implementation of dijkstra's algorithm with fibonacci heaps. here m and n are the number of edges and vertices, respectively.our algorithm is rooted in the so-called component hierarchy approach to shortest paths invented by thorup for integer-weighted undirected graphs, and generalized by hagerup to integer-weighted directed graphs. the technical contributions of this paper include a method for approximating shortest path distances and a method for leveraging approximate distances in the computation of exact ones. we also provide a simple, one line characterization of the class of hierarchy-type shortest path algorithms. this characterization leads to some pessimistic lower bounds on computing single-source shortest paths with a hierarchy-type algorithm.
the factor composition matrix of sequences. let s = {a, b} be a two-letter alphabet and s a sequence over s. an infinite matrix (ti,j)i,j ≥ 0 is associated with s in the following way: ti,j = 1 if s has a factor which contains i times a and j times b; otherwise ti,j = 0. this matrix will be called the factor composition matrix (fcm) of the sequence s. in this paper, combinatorial properties of certain sequences are studied via their fcms. in particular (i) the fcm of the thue-morse sequence is shown to be pentadiagonal, and substitutions whose fixed points have the same fcm as the thue-morse sequence are determined; (ii) an algorithm for computing the fcm of a sturmian sequence is presented; (iii) the fcms of fixed points of invertible substitutions are characterized in terms of their singular decompositions.
finite transducers for divisibility monoids. divisibility monoids are a natural lattice-theoretical generalization of mazurkiewicz trace monoids, namely monoids in which the distributivity of the involved divisibility lattices is kept as an hypothesis, but the relations between the generators are not supposed to necessarily be commutations. here, we show that every divisibility monoid admits an explicit finite transducer which allows to compute normal forms in quadratic time. in addition, we prove that every divisibility monoid is biautomatic.
explicit versus implicit representations of subsets of the herbrand universe. in lassez and marriott (j. automat. reson. 3 (3) (1987) 301-317), explicit and implicit generalizations were studied as representations of subsets of some fixed herbrand universe h. an explicit generalization e = r1v ... v rl represents all ground terms that are instances of at least one of the terms ti, whereas an implicit generalization i = t/t1 v ... v tm represents all h-ground instances of t that are not instances of any term ti. more generally, a disjunction i = i1 v ... v in of implicit generalizations contains all ground terms that are contained in at least one of the implicit generalizations ij.implicit generalizations have applications to many areas of computer science like machine learning, unification, specification of abstract data types, logic programming, functional programming, etc. in these areas, the so-called finite explicit representability problem plays an important role, i.e. given a disjunction of implicit generalizations i =i1 v ... v in, does there exist an explicit generalization e, s.t. i and e are equivalent? we shall prove the conp-completeness of this decision problem.implicit generalizations can be represented as equational formulae, i.e., first-order formulae whose only predicate symbol is syntactic equality. closely related to the finite explicit representability problem is the so-called negation elimination problem of equational formulae, i.e. given an arbitrary equational formula p is p semantically equivalent to an equational formula without universal quantifiers and negation. in this work we study the negation elimination problem of equational formulae with purely existential quantifier prefix. we prove the conp-completeness for such formulae in dnf and the π2p -hardness in case of cnf.
reconstruction of convex polyominoes from orthogonal projections of their contours. the problem of reconstructing a convex polyominoes from its horizontal and vertical projections when the projections are defined as the number of cells of the polyomino in the different lines and columns was studied by del lungo and m. nivat. in this paper, we study the reconstruction of any convex polyomino when the orthogonal projections are defined as the contour length of the object intercepted by the ray. we prove the np-hardness of this problem for several classes of polyominoes: general, h-convex, v-convex. for hv-convex polyominoes we give a polynomial time algorithm for the reconstruction problem.
a proof outline logic for object-oriented programming. this paper describes a proof outline logic that covers most typical object-oriented language constructs in the presence of inheritance and subtyping. the logic is based on a weakest precondition calculus for assignments and object allocation which takes field shadowing into account. dynamically bound method calls are tackled with a variant of hoare's rule of adaptation that deals with the dynamic allocation of objects in object-oriented programs. the logic is based on an assertion language that is closely tailored to the abstraction level of the programming language.
measuring the confinement of probabilistic systems. in this paper we lay the semantic basis for a quantitative security analysis of probabilistic systems by introducing notions of approximate confinement based on various process equivalences. we recast the operational semantics classically expressed via probabilistic transition systems (pts) in terms of linear operators and we present a technique for defining approximate semantics as probabilistic abstract interpretations of the pts semantics. an operator norm is then used to quantify this approximation. this provides a quantitative measure ε of the indistinguishability of two processes and therefore of their confinement. in this security setting a statistical interpretation is then given of the quantity ε which relates it to the number of tests needed to breach the security of the system.
a topological approach to transductions. this paper is a contribution to the mathematical foundations of the theory of automata. we give a topological characterization of the transductions τ from a monoid m into a monoid n, such that if r is a recognizable subset of n, τ-1(r) is a recognizable subset of m. we impose two conditions on the monoids, which are fullfilled in all cases of practical interest: the monoids must be residually finite and, for every positive integer n, must have only finitely many congruences of index n. our solution proceeds in two steps. first we show that such a monoid, equipped with the so-called hall distance, is a metric space whose completion is compact. next we prove that τ can be lifted to a map τ from m into the set of compact subsets of the completion of n. this latter set, equipped with the hausdorff metric, is again a compact monoid. finally, our main result states that τ-1 preserves recognizable sets if and only if τ is continuous.
accumulators: new logic variable abstractions for functional languages. much attention has been focused by the declarative languages community on combining the functional and logic programming paradigms. in particular, there are many efforts to incorporate logic variables into functional languages. we propose a generalization of logic variables called accumulators which are eminently suited for incorporation into functional languages. we demonstrate the utility of accumulators by presenting examples which show that accumulators can be used profitably in many scientific applications to enhance storage efficiency and parallelism.
on the rate of convergence of error estimates for the partitioning classification rule. the error probability of the partitioning classification rule is shown to converge to the bayes error faster than 1/√n under certain conditions. the resubstitution and the deleted error estimates for the partitioning classification rule from a sample (x1, y1),..., (xn, yn) are studied. the random part of the resubstitution estimate is shown to be small for arbitrary partition and for any distribution of (x, y). if we assume that x has a density f and the partitions consist of rectangles, then the difference between the expected value of the estimate and the bayes error restricted to the partition is less than a constant times 1/√n. the main result of the paper is that, under the same conditions, for both estimates the difference between the estimate and the real error probability of the classification rule is asymptotically normal with 0 mean and variance l*/2, where l* is the bayes error.
inequalities characterizing standard sturmian and episturmian words. considering the smallest and the greatest factors with respect to the lexicographic order we associate to each infinite word r two other infinite words min(r) and max(r). in this paper we prove that the inequalities as ≤ min(s) ≤ max(s) ≤ bs characterize standard sturmian words (proper ones and periodic ones) and that the condition "for any x ∈ a and lexicographic order < satisfying x = min(a) one has xs ≤ min(s)" characterizes standard episturmian words.
a maude specification of an object-oriented model for telecommunication networks. this paper presents an object-oriented model for broadband telecommunication networks, which can be used both for network management and for network planning purposes. the object-oriented model has been developed using the parallel object-oriented specification language maude, which allows us to define not only structural aspects of the model but also procedural aspects. the reflective properties of rewriting logic are applied to control the rewriting process, using a strategy language that can be specified internally to the logic. several modeling approaches are compared, emphasizing the definition of the object relationships and the benefits obtained from using reflection as opposed to the extra effort required to control the process at the object level itself.
the accelerated k-in-a-row game. we investigate two versions of the well-known k-in-a-row game. while in the most intriguing k=5 case the outcome of the game has been recently settled, very little is known about what happens when the rules are changed. a natural modification is that the players take more than one square of the board per move in order to speed up the game. our main goal is to improve the quadratic bound on the error term, given by csirmaz in csirmaz (discrete math. 29 (1980) 19-23), to a logarithmic one for the accelerated k-in-a-row. the other issue is the extreme sensitivity of k-in-a-row under biased rules. beck proposed in beck (unpublished lecture notes) that a player may trade some of his freedom of choice for the right of taking more squares than his opponent. we prove logarithmic bounds on the error term in that case, too.
the binomial transform and the analysis of skip lists. to any sequence of real numbers 〈an〉 n ≥ 0, we can associate another sequence 〈âs〉s ≥ 0 which knuth calls its binomial transform. this transform is defined through the rule âs = bsan=σn(-1)n(s n) an.we study the properties of this transform, obtaining rules for its manipulation and a table of transforms, that allow us to invert many transforms by inspection.we use these methods to perform a detailed analysis of skip lists, a probabilistic data structure introduced by pugh as an alternative to balanced trees. in particular, we obtain the mean and variance for the cost of searching for the first or the last element in the list (confirming results obtained previously by other methods), and also for the cost of searching for a random element (whose variance was not known).we obtain exact solutions, although not always in closed form. from them we are able to find the corresponding asymptotic expressions.
dynamic orthogonal range queries in olap. we study the problem of pre-computing auxillary information to support on-line range queries for the sum and max functions on a datacube. for a d-dimensional datacube with size n in each dimension, we propose a dynamic range max data structure with o(αd(s,n)ld) query time, o(αd(s, n)l2dnd/l) update time and o(sd) storage where l and s are parameters chosen by the user before the construction of the data structure such that l ∈ { 1,..., ⌈log n⌉ } and s is a non-negative multiple of n; and α(s, n) is the functional inverse of ackermann's function. moreover, the data structure can be initialized in time linear to its size. there are three major techniques employed in designing the data structure, namely, a technique for trading query and update times, a technique for trading query time and storage and a technique for extending one-dimensional data structures to d-dimensional ones. our techniques are also applicable to range queries over any semigroup and group operation, such as min, sum and count.
interpreted systems and kripke models for multiagent systems from a categorical perspective. both kripke models and interpreted systems have been put forward as basic models of multi-agent systems and for reasoning about knowledge in such systems. this paper enriches previous comparisons of these two forms of semantics by considering categories of models in both cases and then shows that constructions given by lomuscio and ryan, extend to give an adjoint equivalence between the two settings. this equivalence is exploited in a discussion of colimits of interpreted systems.
zeno machines and hypercomputation. this paper reviews the church-turing thesis (or rather, theses) with reference to their origin and application and considers some models of "hypercomputation", concentrating on perhaps the most straight-forward option: zeno machines (turing machines with accelerating clock). the halting problem is briefly discussed in a general context and the suggestion that it is an inevitable companion of any reasonable computational model is emphasised. it is suggested that claims to have "broken the turing barrier" could be toned down and that the important and well-founded rôle of turing computability in the mathematical sciences stands unchallenged.
a bijection for triangulations of a polygon with interior points and multiple edges. loopless triangulations of a polygon with k vertices in k + 2n triangles (with interior points and possibly multiple edges) were enumerated by mullin in 1965, using generating functions and calculations with the quadratic method.in this article we propose a simple bijective interpretation of mullin's formula. the argument rests on the method of conjugacy classes of trees, a variation of the cycle lemma designed for planar maps. in the much easier case of loopless triangulations of the sphere (k = 3), we recover and prove correct an unpublished construction of the second author.
a note on measuring in p. we revisit the problem of generalising lutz's resource-bounded measure (rbm) to small complexity classes, and propose a definition of a random-based rbm on p=∪k∈n dtime (o(nk)), which we argue as being a good generalisation to p of lutz's rbm. we cannot unconditionally prove the existence of such a measure, but we give sufficient and necessary conditions for its existence. we also revisit µτ, an rbm for p defined by strauss [inform. comput. 136(1) (1997) 1], and correct an erroneous claim concerning the relations between µτ and random sets. a correction to this mistake is then proposed, which is a less powerful but accurate relation between µτ and random sets.in order to obtain these results, we introduce a mathematical structure called a measuring system, which is a general setting that can be used to compare different rbms on any fixed complexity class through a partial ordering relation.
premonoidal categories as categories with algebraic structure. we develop the study of premonoidal categories. specifically, we reconcile premonoidal categories with the usual study of categories with algebraic structure by adding a little extra structure. we further give a notion of closedness for a premonoidal category with such extra structure, and show that every premonoidal category fully embeds into a closed one.
generic models for computational effects. a freyd-category is a subtle generalisation of the notion of a category with finite products. it is suitable for modelling environments in call-by-value programming languages, such as the computational λ-calculus, with computational effects. we develop the theory of freyd-categories with that in mind. we first show that any countable lawvere theory, hence any signature of operations with countable arity subject to equations, directly generates a freyd-category. we then give canonical, universal embeddings of freyd-categories into closed freyd-categories, characterised by being free cocompletions. the combination of the two constructions sends a signature of operations and equations to the kleisli category for the monad on the category set generated by it, thus refining the analysis of computational effects given by monads. that in turn allows a more structural analysis of the λc-calculus. our leading examples of signatures arise from side-effects, interactive input/output and exceptions. we extend our analysis to an enriched setting in order to account for recursion and for computational effects and signatures that inherently involve it, such as partiality, nondeterminism and probabilistic nondeterminism.
fixpoint operators for domain equations. we investigate fixpoint operators for domain equations. it is routine to verify that if every endofunctor on a category has an initial algebra, then one can construct a fixpoint operator from the category of endofunctors to the category. that construction does not lift routinely to enriched categories, using the usual enriched notion of initiality of an endofunctor. we show that by embedding the 2-category of small enriched categories into the 2-category of internal categories of a presheaf topos, we can recover the fixpoint construction elegantly. also, we show that in the presence of cotensors, an enriched category allows the fixpoint construction.
combining a monad and a comonad. we give a systematic treatment of distributivity for a monad and a comonad as arises in giving category theoretic accounts of operational and denotational semantics, and in giving an intensional denotational semantics. we do this axiomatically, in terms of a monad and a comonad in a 2-category, giving accounts of the eilenberg-moore and kleisli constructions. we analyse the eight possible relationships, deducing that two pairs are isomorphic, but that the other pairs are all distinct. we develop those 2-categorical definitions necessary to support this analysis.
factorizing fault tolerance. this paper presents a theory of component based development for exception-handling in fault tolerant systems. the theory is based on a general theory of composition, which enables us to factorize the temporal specification of a system into the specifications of its components. this is a new development because in the past efforts to set up such a theory have always been hindered by the problem of composing progress properties.
chu spaces as a semantic bridge between linear logic and mathematics. the motivating role of linear logic is as a "logic behind logic". we propose a sibling role for it as a logic of transformational mathematics via the self-dual category of chu spaces, a generalization of topological spaces. these create a bridge between linear logic and mathematics by soundly and fully completely interpreting linear logic while fully and concretely embedding a comprehensive range of concrete categories of mathematics. our main goal is to treat each end of this bridge in expository detail. in addition, we introduce the dialectic lambda-calculus, and show that dinaturality semantics is not fully complete for the chu interpretation of linear logic.
looking at the stars. the problem of packing k vertex-disjoint copies of a graph h into another graph g is np-complete if h has more than two vertices in some connected component. in the framework of parameterized complexity, we analyze a particular family of instances of this problem, namely the packing of stars. we give a quadratic kernel for packing k copies of h = k1,s. when we consider the special case of s = 2, i.e. h being a star with two leaves, we give a linear kernel and an algorithm running in time o(25.301kk2.5 + n3).
generalized domino-shuffling. the problem of counting tilings of a plane region using specified tiles can often be recast as the problem of counting (perfect) matchings of some subgraph of an aztec diamond graph an, or more generally calculating the sum of the weights of all the matchings, where the weight of a matching is equal to the product of the (pre-assigned) weights of the constituent edges (assumed to be non-negative). this article presents efficient algorithms that work in this context to solve three problems: finding the sum of the weights of the matchings of a weighted aztec diamond graph an; computing the probability that a randomly-chosen matching of an, will include a particular edge (where the probability of a matching is proportional to its weight); and generating a matching of an at random. the first of these algorithms is equivalent to a special case of mihai ciucu's cellular complementation algorithm (j. combin. theory ser. a 81 (1998) 34) and can be used to solve many of the same problems. the second of the three algorithms is a generalization of not-yet-published work of alexandru ionescu, and can be employed to prove an identity governing a three-variable generating function whose coefficients are all the edge-inclusion probabilities; this formula has been used (duke math. j. 85 (1996) 117) as the basis for asymptotic formulas for these probabilities, but a proof of the generating function identity has not hitherto been published. the third of the three algorithms is a generalization of the domino-shuffling algorithm presented in (j. algebraic combin. 1 (1992) 111); it enables one to generate random "diabolo-tilings of fortresses" and thereby to make intriguing inferences about their asymptotic behavior.
when a genetic algorithm outperforms hill-climbing. a toy optimisation problem is introduced which consists of a fitness gradient broken up by a series of hurdles. the performance of a hill-climber and a stochastic hill-climber are computed. these are compared with the empirically observed performance of a genetic algorithm (ga) with and without. the hill-climber with a sufficiently large neighbourhood outperforms the stochastic hill-climber, but is outperformed by a ga both with and without crossover. the ga with crossover substantially outperforms all the other heuristics considered here. the relevance of this result to real world problems is discussed.
on the expressive power of first-order boolean functions in pcf. recent results of bucciarelli show that the semilattice of degrees of parallelism of first-order boolean functions in pcf has both infinite chains and infinite antichains. by considering a simple subclass of sieber's sequentiality relations, we identify levels in the semilattice and derive inexpressibility results concerning functions on different levels. this allows us to further explore the structure of the semilattice of degrees of parallelism: we identify semilattices characterized by simple level properties, and show the existence of new infinite hierarchies which are in a certain sense natural with respect to the levels. copyright 2001 elsevier science b.v.
on reducibility and symmetry of disjoint np pairs. we consider some problems about pairs of disjoint np sets. the theory of these sets with a natural concept of reducibility is, on the one hand, closely related to the theory of proof systems for propositional calculus, and, on the other, it resembles the theory of np completeness. furthermore, such pairs are important in cryptography. among others, we prove that the broken mosquito screen pair of disjoint np sets can be polynomially reduced to clique-coloring pair and thus is polynomially separable and we show that the pair of disjoint np sets canonically associated with the resolution proof system is symmetric.
on the power of membrane division in p systems. first, we consider p systems with active membranes, hence with the possibility that the membranes can be divided, with non-cooperating evolution rules (the objects always evolve separately). these systems are known to be able to solve np-complete problems in linear time. here we give a normal form theorem for such systems: their computational universality is preserved even if only the elementary membranes are divided. the possibility of solving sat in linear time is preserved only when non-elementary membranes may also be divided under the influence of objects in their region.second, we consider a slight generalization, namely, we allow that a membrane can produce by division both a copy of itself and a copy of a membrane with a different label; again, only elementary membranes may be divided. in this case, we prove that the hierarchy on the maximal number of membranes present in the system collapses: three membranes at a time are sufficient in order to characterize the recursively enumerable sets of vectors of natural numbers. this result is optimal, two membranes are shown not to be sufficient.third, we consider p systems with cooperating rules (several objects may evolve together). making use of this powerful feature, we show that many np-complete problems can be solved in linear time in a quite uniform way (by systems which are very similar to each other), using only elementary membranes division (and not further ingredients, such as electrical charges). the degree of cooperation is minimal: two objects at a time.
greedy algorithms, h-colourings and a complexity-theoretic dichotomy. let h be a fixed undirected graph. an h-colouring of an undirected graph g is a homomorphism from g to h. if the vertices of g are partially ordered then there is a generic non-deterministic greedy algorithm which computes all lexicographically first maximal h- colourable subgraphs of g. we show that the complexity of deciding whether a given vertex of g is in a lexicographically first maximal h-colourable subgraph of g is np-complete, if h is bipartite, and σ2p-complete, if h is non-bipartite. this result complements hell and nesetril's seminal dichotomy result that the standard h-colouring problem is in p, if h is bipartite, and np-complete, if h is non-bipartite. our proofs use the basic techniques established by hell and nesetril, combinatorially adapted to our scenario.
possible worlds and resources: the semantics of bi. the logic of bunched implications, bi, is a substructural system which freely combines an additive (intuitionistic) and a multiplicative (linear) implication via bunches (contexts with two combining operations, one which admits weakening and contraction and one which does not). bi may be seen to arise from two main perspectives. on the one hand, from proof-theoretic or categorical concerns and, on the other, from a possible-worlds semantics based on preordered (commutative) monoids. this semantics may be motivated from a basic model of the notion of resource. we explain bi's proof-theoretic, categorical and semantic origins. we discuss in detail the question of completeness, explaining the essential distinction between bi with and without ⊥ (the unit of v). we give an extensive discussion of bi as a semantically based logic of resources, giving concrete models based on petri nets, ambients, computer memory, logic programming, and money.
characterizations of quantum automata. we define q quantum finite automata (qqfas) and q quantum regular grammars (qqrgs), and verify that they are exactly equivalent to those measure-once quantum finite automata (mo-qfas) in the literature. in particular, we define q quantum pushdown automata (qqpdas) and qpdas that are at least as powerful as those defined by moore and crutchfield, and especially we focus on demonstrating the equivalence between qqpdas and qpdas. also, we discuss some of the properties of languages accepted by qqpdas; for example, every cut-point language accepted by qqpda is independent of the cut-point
periodicity and local complexity. we consider the complexity of bi-infinite words in one and two dimensions. a result of morse and hedlund in one dimension states that if the complexity, pξ(n), of a word satisfies pξ(n) ≤ n for some n, then the word ξ is periodic. the corresponding question in two dimensions (whether pξ(m, n) ≤ mn implies that ξ is periodic) is known as the nivat conjecture. in this paper, we strengthen the one-dimensional result of morse and hedlund and prove a weak form of the nivat conjecture, namely that if for a bi-infinite two-dimensional word ξ, pξ(m, n) ≤ mn/16 then ξ is periodic.
convexity and global optimization: a theoretical link. here we propose a characterization of the subsets of rn which are the sets of local optima of the restriction of some convex function to some discrete subset, and we prove that, under some conditions, recognizing these subsets can be done in polynomial time. we discuss eventual applications of these results to global optimization problems.
finite variability interpretation of monadic logic of order. we consider an interpretation of monadic second-order logic of order in the continuous time structure of finitely variable signals. we provide a characterization of the expressive power of monadic logic. as a by-product of our characterization we show that many fundamental theorems which hold in the discrete time interpretation of monadic logic are still valid in the continuous time interpretation.
automata over continuous time. the principal objective of this paper is to lift basic concepts of the classical automata theory from discrete to continuous (real) time. it is argued that the set of finite memory retrospective functions is the set of functions realized by finite state devices. we show that the finite memory retrospective functions are speed-independent, i.e., they are invariant under 'stretchings' of the time axis. therefore, such functions cannot deal with metrical aspects of the reals.we classify and analyze phenomena which appear at continuous time and are invisible at discrete time.
improving time bounds on maximum generalised flow computations by contracting the network. we consider the maximum generalised network flow problem and a supply-scaling algorithmic framework for this problem. we present three network-modification operations, which may significantly decrease the size of the network when the remaining node supplies become small. we use these three operations in goldfarb et al.'s supply-scaling algorithm and prove an õ(m2n log b) bound on the running time of the resulting algorithm. the previous best time bounds on computing maximum generalised flows are the o(m1.5n log b) bound of kapoor and vaidya's algorithm based on the interior-point method, and the õ(m3 log b) bound of goldfarb et al.'s algorithm.
getting results from programs extracted from classical proofs. we present a new method to extract from a classical proof of ∀x(i[x] → ??(o[y] ∧ s[x,y])) a program computing y from x. this method applies when o is a data type and s is a decidable predicate. algorithms extracted this way are often far better than a stupid enumeration of all the possible outputs and this is verified on a nontrivial example: a proof of dickson's lemma.
on sparse evaluation representations. the sparse evaluation graph has emerged over the past several years as an intermediate representation that captures the dataflow information in a program compactly and helps perform dataflow analysis efficiently. the contributions of this paper are three-fold: we present a linear time algorithm for constructing a variant of the sparse evaluation graph for any dataflow analysis problem. our algorithm has two advantages over previous algorithms for constructing sparse evaluation graphs. first, it is simpler to understand and implement. second, our algorithm generates a more compact representation than the one generated by previous algorithms. (our algorithm is also as efficient as the most efficient known algorithm for the problem.) we present a formal definition of an equivalent flow graph, which attempts to capture the goals of sparse evaluation. we present a quadratic algorithm for constructing an equivalent flow graph consisting of the minimum number of vertices possible. we show that the problem of constructing an equivalent flow graph consisting of the minimum number of vertices and edges is np-hard. we generalize the notion of an equivalent flow graph to that of a partially equivalent flow graph, an even more compact representation, utilizing the fact that the dataflow solution is not required at every node of the control-flow graph. we also present an efficient linear time algorithm for constructing a partially equivalent flow graph. copyright 2002 elsevier science b.v.
parameterized algorithms for feedback set problems and their duals in tournaments. the parameterized feedback vertex (arc) set problem is to find whether there are k vertices (arcs) in a given graph whose removal makes the graph acyclic. the parameterized complexity of this problem in general directed graphs is a long standing open problem. we investigate the problems on tournaments, a well studied class of directed graphs. we consider both weighted and unweighted versions.we also address the parametric dual problems which are also natural optimization problems. we show that they are fixed parameter tractable not just in tournaments but in oriented directed graphs (where there is at most one directed arc between a pair of vertices). more specifically, the dual problem we show fixed parameter tractable are: given an oriented directed graph, is there a subset of k vertices (arcs) that forms an acyclic directed subgraph of the graph?our main results include: • an o((2.4143)knω)1 algorithm for weighted feedback vertex set problem, and an o((2.415)knω) algorithm for weighted feedback arc set problem in tournaments; • an o((e2k/k)kk2 + min{m ig n, n2}) algorithm for the dual of feedback vertex set problem (maximum vertex induced acyclic graph) in oriented directed graphs, and an o(4kk + m) algorithm for the dual of feedback arc set problem (maximum arcinduced acyclic graph) in general directed graphs.we also show that the dual of feedback vertex set is w[1]--hard in general directed graphs and the feedback arc set problem is fixed parameter tractable in dense directed graphs. our results are the first non-trivial results for these problems.
a (restricted) quantifier elimination for security protocols. while reasoning about security protocols, most of the difficulty of reasoning relates to the complicated semantics (with freshness of nonces, multisessions, etc.). while logics for security protocols need to be abstract (without explicitly dealing with nonces, encryption, etc.), ignoring details may result in rendering any verification of abstract properties worthless. we would like the verification problem for the logic to be decidable as well, to allow for automated methods for detecting attacks. from this viewpoint, we study a logic with session abstraction and quantifiers over session names. we show that interesting security properties like secrecy and authentication can be described in the logic. we prove the existence of a normal form for runs of tagged protocols. this leads to a quantifier elimination result for the logic which establishes the decidability of the verification problem for tagged protocols, when we assume a fixed finite set of nonces.
avoiding large squares in infinite binary words. we consider three aspects of avoiding large squares in infinite binary words. first, we construct an infinite binary word avoiding both cubes xxx and squares yy with |y| ≥4; our construction is somewhat simpler than the original construction of dekking. second, we construct an infinite binary word avoiding all squares except 02, 12, and (01)2; our construction is somewhat simpler than the original construction of fraenkel and simpson. in both cases, we also show how to modify our construction to obtain exponentially many words of length n with the given avoidance properties. finally, we answer an open question of prodinger and urbanek from 1979 by demonstrating the existence of two infinite binary words, each avoiding arbitrarily large squares, such that their perfect shuffle has arbitrarily large squares.
polynomial-time learnability of logic programs with local variables from entailment. in this paper, we study exact learning of logic programs from entailment and present a polynomial time algorithm to learn a rich class of logic programs that allow local variables and include many standard programs like append, merge, split, delete, member, prefix, suffix, length, reverse, append/4 on lists, tree traversal programs on binary trees and addition, multiplication and exponentiation on natural numbers. grafting a few aspects of incremental learning (krishna rao, proc. algorithmic learning theory, alt'95, lecture notes in artificial intelligence, vol. 997, pp. 95--109. revised version in theoret. comput. sci. special issue on alt'95 185 (1995) 193--213) onto the framework of learning from entailment (arimura, proc. algorithmic learning theory, alt'97, lecture notes in artificial intelligence, vol. 1316, 1997, pp. 432--445), we generalize the existing results to allow local variables, which play an important role of sideways information passing in the paradigm of logic programming. 2001 elsevier science b.v. all rights reserved
complexity of hyperconcepts. in machine-learning, maximizing the sample margin can reduce the learning generalization error. samples on which the target function has a large margin (γ) convey more information since they yield more accurate hypotheses. let x be a finite domain and s denote the set of all samples s ⊆ x of fixed cardinality m. let h be a class of hypotheses h on x. a hyperconcept h' is defined as an indicator function for a set a ⊆ s of all samples on which the corresponding hypothesis h has a margin of at least γ. an estimate on the complexity of the class h' of hyperconcepts h' is obtained with explicit dependence on γ, the pseudodimension of h and m.
deadlocks and dihomotopy in mutual exclusion models. higher dimensional automata (hda) represent a promising tool for modelling ("true") concurrency in a both combinatorial and topological framework. within these models, fast algorithms investigating deadlocks and unreachable regions have been devised previously on a background of easily understandable "directed" geometric ideas. in this article, we modify notions and methods from homotopy theory to define and investigate "essentially different" schedules in a hda and to detect whether two given runs are essentially different using an algorithm again based on "directed geometry".
forbidden subgraphs in connected graphs. given a set ξ = {h1,h2,...} of connected non-acyclic graphs, a ξ-free graph is one which does not contain any member of ξ as copy. define the excess of a graph as the difference between its number of edges and its number of vertices. let wk,ξ be the exponential generating function (egf for brief) of connected ξ-free graphs of excess equal to k (k ≥ 1). for each fixed ξ, a fundamental differential recurrence satisfied by the egfs wk,ξ is derived. we give methods on how to solve this nonlinear recurrence for the first few values of k by means of graph surgery. we also show that for any finite collection ξ of non-acyclic graphs, the egfs wk,ξ are always rational functions of the generating function, t, of cayley's rooted (non-planar) labelled trees. from this, we prove that almost all connected graphs with n nodes and n + k edges are ξ-free, whenever k = o(n1/3) and |ξ| < ∞ by means of wright's inequalities and saddle point method. limiting distributions are derived for sparse connected ξ-free components that are present when a random graph on n nodes has approximately n/2 edges. in particular, the probability distribution that it consists of trees, unicyclic components, ..., (q + 1)-cyclic components all ξ-free is derived. similar results are also obtained for multigraphs, which are graphs where self-loops and multiple-edges are allowed.
peg-solitaire, string rewriting systems and finite automata. we consider a class of length-preserving string rewriting systems and show that the set of encodings of pairs of strings 〈s, f〉 such that f can be derived from s using the rewriting rules can be accepted by finite automata. as a consequence, we show the existence of a linear time algorithm for determining the solvability of a given k × n peg-solitaire board, for any fixed k. this result is in contrast to the results of (13) and (1) that the same problem is np-hard for n × n boards. we look at some related string rewriting systems and find conditions under which the encodings of the pairs 〈s,f〉 where f can be derived from s is regular.
weak minimization of dfa - an algorithm and applications. dfa minimization is an important problem in algorithm design and is based on the notion of dfa equivalence: two dfa's are equivalent if and only if they accept the same set of strings. in this paper, we propose a new notion of dfa equivalence (that we call weak-equivalence): we say that two dfa's are weakly equivalent if they both accept the same number of strings of length k for every k. the motivation for this problem is as follows. a large number of counting problems can be solved by encoding the combinatorial objects we want to count as strings over a finite alphabet. if the collection of encoded strings is accepted by a dfa, then standard algorithms from computational linear algebra can be used to solve the counting problem efficiently. when applying this approach to large-scale applications, the bottleneck is the space complexity since the computation involves a matrix of order k × k if k is the size of the underlying dfa m. this leads to the natural question: is there a smaller dfa that is weakly equivalent to m? we present an algorithm of time complexity o(k3) to find a compact dfa weakly equivalent to a given dfa. we illustrate, in the case of a tiling problem, that our algorithm reduces a (strongly minimal) dfa by a factor close to 1/2.
dense edge-disjoint embedding of complete binary trees in interconnection networks. we describe dense edge-disjoint embeddings of the complete binary tree with n leaves in the following n-node communication networks: the hypercube, the de bruijn and shuffle-exchange networks and the two-dimensional mesh. for the mesh and the shuffle-exchange graphs each edge is regarded as two parallel (or anti-parallel) edges. the embeddings have the following properties: paths of the tree are mapped onto edge-disjoint paths of the host graph and at most two tree nodes (just one of which is a leaf) are mapped onto each host node. we prove that the maximum distance from a leaf to the root of the tree is asymptotically as short as possible in all host graphs except in the case of the shuffle-exchange, in which case we conjecture that it is as short as possible. the embeddings facilitate efficient implementation of many p-ram algorithms on these networks.
resolution lower bounds for the weak functional pigeonhole principle. we show that every resolution proof of the functional version fphpnm of the pigeonhole principle (in which one pigeon may not split between several holes) must have size exp(ω(n/(log m)2)). this implies an exp(ω(n1/3)) bound when the number of pigeons m is arbitrary.
bioambients: an abstraction for biological compartments. biomolecular systems, composed of networks of proteins, underlie the major functions of living cells. compartments are key to the organization of such systems. we have previously developed an abstraction for biomolecular systems using the π-calculus process algebra, which successfully handled their molecular and biochemical aspects, but provided only a limited solution for representing compartments. in this work, we extend this abstraction to handle compartments. we are motivated by the ambient calculus, a process algebra for the specification of process location and movement through computational domains. we present the bioambients calculus, which is suitable for representing various aspects of molecular localization and compartmentalization, including the movement of molecules between compartments, the dynamic rearrangement of cellular compartments, and the interaction between molecules in a compartmentalized setting. guided by the calculus, we adapt the biospi simulation system, to provide an extended modular framework for molecular and cellular compartmentalization, and we use it to model and study a complex multi-cellular system.
a non-learnable class of e-pattern languages. we investigate the inferrability of e-pattern languages (also known as extended or erasing pattern languages) from positive data in gold's learning model. as the main result, our analysis yields a negative outcome for the full class of e-pattern languages--and even for the subclass of terminal-free e-pattern languages--if the corresponding terminal alphabet consists of exactly two distinct letters. furthermore, we present a positive result for a manifest subclass of terminal-free e-pattern languages. we point out that the considered problems are closely related to fundamental questions concerning the nondeterminism of e-pattern languages.
on boundaries of highly visible spaces and applications. the purpose of this paper is to investigate the properties of a certain class of highly visible spaces. for a given geometric space c containing obstacles specified by disjoint subsets of c, the free space f is defined to be the portion of c not occupied by these obstacles. the space is said to be highly visible if at each point in f a viewer can see at least an ε fraction of the entire f. this assumption has been used for robotic motion planning in the analysis of random sampling of points in the robot's configuration space, as well as the upper bound of the minimum number of guards needed for art gallery problems. however, there is no prior result on the implication of this assumption to the geometry of the space under study. for the two-dimensional case, with the additional assumptions that c is bounded within a rectangle of constant aspect ratio and that the volume ratio between f and c is a constant, we use the proof technique of "charging" each obstacle boundary segment by a certain portion of c to show that the total length of all obstacle boundaries in c is o(√nµ(f)/ε), if f contains polygonal obstacles with a total of n boundary edges; or o(√nµ(f)/ε), if c contains n convex obstacles that are piecewise smooth. in both cases, µ(f) is the volume of f. for the polygonal case, this bound is tight as we can construct a space whose boundary size is θ(√nµ(f)/ε). these results can be partially extended to three dimensions. we show that these results can be applied to the analysis of certain probabilistic roadmap planners, as well as a variant of the art gallery problem. we also propose a number of conjectures on the properties of these highly visible, spaces.
localic sup-lattices and tropological systems. the approach to process semantics using quantales and modules is topologized by considering tropological systems whose sets of states are replaced by locales and which satisfy a suitable stability axiom. a corresponding notion of localic sup-lattice (algebra for the lower powerlocale monad) is described, and it is shown that there are contravariant functors from sup-lattices to localic sup-lattices and, for each quantale q, from left q-modules to localic right q-modules. a proof technique for third completeness due to abramsky and vickers is reset constructively, and an example of application to failures semantics is given.
on the lattice of prefix codes. the natural correspondence between prefix codes and trees is explored, generalizing the results obtained in giammarresi et al. (theoret. comput. sci. 205 (1998) 1459) for the lattice of finite trees under division and the lattice of finite maximal prefix codes. joins and meets of prefix codes are studied in this light in connection with such concepts as finiteness, maximality and varieties of rational languages. decidability results are obtained for several problems involving rational prefix codes, including the solution to the primeness problem.
handsome proof-nets: perfect matchings and cographs. we first extract the combinatorial result behind various proofs of the sequentialisation theorem for multiplicative proof-nets. this result is an inductive characterisation of graphs with a unique perfect matching.extending these techniques, we give a definition of multiplicative proof-nets in which commutativity but also associativity of the multiplicative connectives is interpreted as equality. this is done by representing a sequent by a cograph and axioms by a perfect matching. the main advantage of this presentation is aesthetic: any such graph, without any further requirement is a proof-structure and the correctness criterion also is a natural graph-theoretical property.a direct and purely graph theoretical proof of these results is available as a research report in which more details can be found (c. retoré, handsome proof-nets: r&b-graphs, perfect matchings and series-parallel graphs, rapport de recherche rr-3652, inria, march 1999. http://www.inria.fr/rrrt/publications-eng.html).
semantics and logic of object calculi. the main contribution of this paper is a formal characterization of recursive object specifications and their existence based on a denotational untyped semantics of the object calculus. existence is not guaranteed but can be shown employing pitts' results on relational properties of domains. the semantics can be used to analyse and verify abadi and leino's object logic but it also suggests extensions. for example, specifications of methods may not only refer to fields but also to methods of objects in the store. this can be achieved without compromising the existence theorem. an informal logic of predomains is in use intentionally in order to avoid any commitment to a particular syntax of specification logic.
some results on tries with adaptive branching. we study a modification of digital trees (or tries) with adaptive multi-digit branching. such tries can dynamically adjust degrees of their nodes by choosing the number of digits to be processed per lookup. while we do not specify any particular method for selecting the degrees of nodes, we assume that such selection can be accomplished by examining the number of strings remaining in each sub-tree, and/or estimating parameters of the input distribution. we call this class of digital trees adaptive multi-digit tries (or amd-tries) and provide a preliminary analysis of their expected behavior in a memoryless model. we establish the following results: (1) there exist amd-tries attaining a constant expected time of a successful search; (2) there exist amd-tries consuming a linear (in the number of strings inserted) amount of space; (3) both constant search time and linear space usage can be attained if the (memoryless) source is symmetric. we accompany our analysis with a brief survey of several known types of adaptive trie structures, and show how our analysis extends (and/or complements) previous results.
conjugacy and episturmian morphisms. episturmian morphisms generalize sturmian morphisms. here, we study some intrinsic properties of these morphisms: invertibility, presentation, cancellativity, unitarity, characterization by conjugacy. most of them are generalizations of known properties of sturmian morphisms. but we present also some results on episturmian morphisms that have not already been stated in the particular case of sturmian morphisms: characterization of the episturmian morphisms that preserve palindromes, new algorithms to compute conjugates.we also study the conjugation of morphisms in the general case and show that the monoid of invertible morphisms on an alphabet containing at least three letters is not finitely generated.
some results on k-power-free morphisms. one way to generate infinite k-power-free words is to iterate a k-power-free morphism, that is a morphism that preserves finite k-power-free words. we first prove that the monoid of k-power-free endomorphisms on an alphabet containing at least three letters is not finitely generated. test-sets for k-power-free morphisms (that is, the sets t such that a morphism f is k-power-free if and only if f(t) is k-power-free) give characterizations of these morphisms. in the case of binary morphisms and k=3, we prove that a set t of cube-free words is a test-set for cube-freeness if and only if it contains 12 particular factors. consequently, a morphism f on {a,b} is cube-free if and only if f(aabbababbabbaabaababaabb) is cube-free (length 24 is optimal). another consequence is an unpublished result of leconte: a binary morphism is cube-free if and only if the images of all cube-free words of length 7 are cube-free. when k3, we show that no finite test-set exists for morphisms defined on an alphabet containing at least three letters. in the last part, we show that to generate an infinite cube-free word by iterating a morphism, we do not necessarily need a cube-free morphism. we give a new characterization of some morphisms that generate infinite cube-free words.
online request server matching. in the following paper an alternative online variant of the matching problem in bipartite graphs is presented. it is triggered by a scheduling problem. there, a task is unknown up to its disclosure. however, when a task is revealed, it is not necessary to take a decision on the service of that particular task. on the contrary, an online scheduler has to decide on how to use the current resources. therefore, the problem is called online request server matching (orsm). it differs substantially from the online bipartite matching problem of karp et al. (proc. 22nd annual acm symp. on theory of computing, baltimore, maryland, may 14-16, 1990, acm press, new york, 1990). hence, the analysis of an optimal, deterministic online algorithm for the orsm problem results in a smaller competitive ratio of 1.5. an extension to a weighted bipartite matching problem is also introduced, and results of its investigation are presented. additional concepts for the orsm model (e.g. lookahead, parallel resources, deadlines) are studied. all of these modifications are realized by restrictions on the input structure. decreased competitive ratios are presented for some of these modified models. copyright 2001 elsevier science b.v.
distributed processes and location failures. site failure is an essential aspect of distributed systems; nonetheless its effect on programming language semantics remains poorly understood. to model such systems, we define a process calculus in which processes are run at distributed locations. the language provides operators to kill locations, to test the status (dead or alive) of locations, and to spawn processes at remote locations. using a variation of bisimulation, we provide alternative characterizations of strong and weak barbed congruence for this language, based on an operational semantics that uses congurations to record the status of locations. we then derive a second, symbolic characterization in which configurations are replaced by logical formulae. in the strong case the formulae come from a standard propositional logic, while in the weak case a temporal logic with past time modalities is required. the symbolic characterization establishes that, in principle, barbed congruence for such languages can be checked using existing symbolic techniques. copyright 2001 elsevier science b.v.
semantics of plan revision in intelligent agents. in this paper, we give an operational and denotational semantics for a meta-language of the 3apl agent programming language. with this meta-language, various 3apl interpreters can be programmed. we prove equivalence of the operational and denotational semantics. furthermore, we give an operational semantics for object-level 3apl. using this semantics, we relate the 3apl meta-language to object-level 3apl by providing a specific interpreter, the semantics of which will prove to be equivalent to object-level 3apl.
constant bounds on the moments of the height of binary search trees. we show that binary search trees of a given size tend to have smaller height when the root division is into two subtrees of more balanced sizes. we deduce that the expectation of the absolute value of the difference in height of two binary search trees of the same number of nodes is less than 3.135 infinitely often. we also deduce strong upper bounds on the probability of large deviations from the median. putting together these two conclusions and a simple and plausible conjecture on critical nodes leads to o(1) bounds on all moments of binary search tree heights.
wmso theories as grammar formalisms. we explore the use of weak monadic second-order languages over structures of varying dimension as specification languages for grammars and automata, focusing, in particular, on the extension of the longstanding results characterizing the regular and context-free languages in terms of definability in ws1s (one-dimensional) and wsns (two-dimensional), respectively, to a characterization of the tree-adjoining languages in terms of definability in the weak monadic second-order theory of certain three-dimensional tree-like structures. we then explore the application of these results to aspects of an existing large-scale tree-adjoining grammar for english and close with some speculation on the feasibility of this approach as a means of building and maintaining such grammars.
phase transitions and symmetry breaking in genetic algorithms with crossover. in this paper, we consider the role of the crossover operator in genetic algorithms. specifically, we study optimisation problems that exhibit many local optima and consider how crossover affects the rate at which the population breaks the symmetry of the problem. as an example of such a problem, we consider the subset sum problem. in doing so, we demonstrate a previously unobserved phenomenon, whereby the genetic algorithm with crossover exhibits a critical mutation rate, at which its performance sharply diverges from that of the genetic algorithm without crossover. at this critical mutation rate, the genetic algorithm with crossover exhibits a rapid increase in population diversity. we calculate the details of this phenomenon on a simple instance of the subset sum problem and show that it is a classic phase transition between ordered and disordered populations. finally, we show that this critical mutation rate corresponds to the transition between the genetic algorithm accelerating or preventing symmetry breaking and that the critical mutation rate represents an optimum in terms of the balance of exploration and exploitation within the algorithm.
csp-casl - a new integration of process algebra and algebraic specification. csp-casl integrates the process algebra csp [t. hoare, communicating sequential processes, prentice-hall, englewood cliffs, nj, 1985; a.w. roscoe, the theory and practice of concurrency, prentice-hall, englewood cliffs, nj, 1998] with the algebraic specification language casl [p.d. mosses (ed.), casl reference manual, lecture notes in computer science, vol. 2960, springer, berlin, 2004; e. astesiano, m. bidoit, b. krieg-brückner, h. kirchner, p.d. mosses, d. sannella, a. tarlecki, casl--the common algebraic specification language, theoret. comput. sci. 286 (2002) 153-196]. its novel aspects include the combination of denotational semantics in the process part and, in particular, loose semantics for the data types covering both concepts of partiality and sub-sorting. technically, this integration involves the development of a new so-called data-logic formulated as an institution. this data-logic serves as a link between the institution underlying casl and the alphabet of communications necessary for the csp semantics. besides being generic in the various denotational csp semantics, this construction leads also to an appropriate notion of refinement with clear relations to both data refinement in casl and process refinement in csp.
using data-independence in the analysis of intrusion detection systems. in this paper we demonstrate the modelling and analysis of intrusion detection systems and their environment using the process algebra communicating sequential processes and its model checker fdr. we show that this analysis can be used to discover attack strategies that can be used to blind an intrusion detection system, even a hypothetically perfect one that knows all the weaknesses of its protected host. we give an exhaustive analysis of all such attack possibilities. we discuss how to strengthen the intrusion detection systems to prevent these attacks, and finally we show how we can use data independence techniques to verify the corrected versions.
a principled exploration of coordination models. coordination is a style of interaction in which information exchange among independent system components is accomplished by means of high-level constructs designed to enhance the degree of decoupling among participants. a decoupled mode of computation is particularly important in the design of mobile systems which emerge dynamically through the composition of independently developed components meeting under unpredictable circumstances and thrust into achieving purposeful cooperative behaviors. this paper examines a range of coordination models tailored for use in mobile computing and shows that the constructs they provide are reducible to simple schema definitions in mobile unity. intellectually, this exercise contributes to achieving a better operational-level understanding of the relation among several important classes of models of mobility. pragmatically, this work demonstrates the immediate applicability of mobile unity to the formal specification of coordination constructs supporting mobile computing. moreover, the resulting schemas are shown to be helpful in reducing the complexity of the formal verification effort.
hybrid action systems. in this paper we investigate the use of action systems with differential actions in the specification of hybrid systems. as the main contribution we generalize the definition of a differential action, allowing the use of arbitrary relations over model variables and their time derivatives in modelling continuous-time dynamics. the generalized differential action has an intuitively appealing predicate transformer semantics, which we show to be both conjunctive and monotonic. in addition, we show that differential actions blend smoothly with conventional actions in action systems even under parallel composition. moreover, as the strength of the action system formalism is the support for stepwise development by refinement, we investigate refinement involving a differential action. we show that, due to the predicate transformer semantics, standard action refinement techniques apply also to the differential action, thus, allowing stepwise development of hybrid systems.
the word problem for 1lc congruences is np-hard. in this paper, it is proved that the word problem for congruences generated by subsets of {(abc,acb)|a ∈ a ∪ {ε},b, c ∈ a) is np-hard. these congruences are a generalization of mazurkiewicz's traces.
an algebraic view of the relation between largest common subtrees and smallest common supertrees. the relationship between two important problems in tree pattern matching, the largest common subtree and the smallest common supertree problems, is established by means of simple constructions, which allow one to obtain a largest common subtree of two trees from a smallest common supertree of them, and vice versa. these constructions are the same for isomorphic, homeomorphic, topological, and minor embeddings, they take only time linear in the size of the trees, and they turn out to have a clear algebraic meaning.
behavioral abstraction is hiding information. we show that for any behavioral σ-specification b there is an ordinary algebraic specification b˜ over a larger signature, such that a model behaviorally satisfies b iff it satisfies, in the ordinary sense, the σ-theorems of b˜. the idea is to add machinery for contexts and experiments (sorts, operations and equations), use it, and then hide it. we develop a procedure, called unhiding, which takes a finite b and produces a finite b˜. the practical aspect of this procedure is that one can use any standard equational inductive theorem prover to derive behavioral theorems, even if neither equational reasoning nor induction is sound for behavioral satisfaction.
revision by comparison as a unifying framework: severe withdrawal, irrevocable revision and irrefutable revision. fermé and rott [revision by comparison, art. intell. 157 (2004) 5-47] introduced a binary operation of 'revision by comparison' and pointed out that this method of changing epistemic states has both characteristics of belief contraction (with respect to the 'reference sentence') and characteristics of belief revision (with respect to the 'input sentence'). using revision by comparison as a unifying framework, the present paper studies the unary limiting cases of severe withdrawal, irrevocable revision and irrefutable revision. while variants of the first two operations are well-known from the literature, the last one is new.
differentiable coarse graining. coarse graining is defined in terms of a commutative diagram. necessary and sufficient conditions are given in the continuously differentiable case. the theory is applied to linear coarse grainings arising from partitioning the population space of a simple genetic algorithm (ga). cases considered include proportional selection, binary tournament selection, ranking selection, and mutation. a nonlinear coarse graining for ranking selection is also presented. a number of results concerning "form invariance" are given. within the context of gas, the primary contribution made is the illustration of a technique by which coarse grainings may be analyzed. it is applied to obtain a number of new coarse graining results.
on the computational complexity of longley's h functional. longley discovered a functional h that, when added to pcf, yields a language that computes exactly sr, the sequentially realizable functionals of van oosten. we show that if p ≠ np, then the computational complexity of h (and of similar sr-functionals) is inherently infeasible.
icalp, eatcs and maurice nivat. the purpose of this writing is to tell something about the quite unique and fundamental role of maurice nivat, both in launching icalp and eatcs, as well as in guiding them through the difficult early stages. our account is based on personal recollections, as well as some original documents and letters. to preserve the personal character of our recollections, we have not tried to fill the gaps in our information through other channels such as interviewing some of the people involved. in other words, our personal account is not intended to be a comprehensive history. it only tells how things seemed to us.
dna computing by blocking. we present a method for molecular computing which relies on blocking (inactivating) this part of the total library of molecules that does not contribute to (finding) a solution--this happens essentially in one biostep (after the input has been read). the method is explained by presenting a dna based algorithm for solving (albeit in the theoretical sense only!) the satisfiability problem.
a greedy approximation for minimum connected dominating sets. given a graph, a connected dominating set is a subset of vertices such that every vertex is either in the subset or adjacent to a vertex in the subset and the subgraph induced by the subset is connected. a minimum connected dominating set is such a vertex subset with minimum cardinality. in this paper, we present a new one-step greedy approximation with performance ratio ln δ + 2 where δ is the maximum degree in the input graph. the interesting aspect is that the greedy potential function of this algorithm is not supmodular while all previously known one-step greedy algorithms with similar performance have supmodular potential functions.
exists-universal termination of logic programs. we introduce the notion of $\exists$-universal termination of logic programs. a program p and a goal g $\exists$-universally terminate iff there exists a selection rule s such that every sld-derivation of p u { g }$via s is finite. we claim that it is an essential concept for declarative programming, where a crucial point is to associate a terminating control strategy to programs and goals. we show that $\exists$-universal termination and universal termination via fair selection rules coincide. then we offer a characterization of $\exists$-universal termination by defining fair-bounded programs and goals. they provide us with a correct and complete method of proving $\exists$-universal termination. we show other valuable properties of fair-bounded programs and goals, including persistency, modularity, ease of use in paper & pencil proofs, automatization of proofs. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
polynat in per models. the polymorphic lambda-calculus can be modelled using pers on a partial combinatory algebra. we say that the type of natural numbers (polynat) is polymorphically standard in such a model if the interpretation of the type only contains (the interpretations of) the church numerals. we show that this is not always the case by constructing an explicit counterexample. on the other hand, when the pca has either (strong) equality or weak equality plus a form of continuity, we show polynat is standard.
explicit test sets for iterated morphisms in free monoids and metabelian groups. for checking equivalence of any two word morphisms, restricted on a subset (language), it suffices to do this for a finite subset of the language, the so-called finite test set. a way of effectively obtaining a finite test set for a special class of languages, the so-called iterated morphisms, is presented here together with an explicit upper bound for its size. the method can be extended to free metabelian groups, and to certain other metabelian groups.
universal coalgebra: a theory of systems. in the semantics of programming, finite data types such as finite lists, have traditionally been modelled by initial algebras. later final coalgebras were used in order to deal with infinite data types. coalgebras, which are the dual of algebras, turned out to be suited, moreover, as models for certain types of automata and more generally, for (transition and dynamical) systems. an important property of initial algebras is that they satisfy the familiar principle of induction. such a principle was missing for coalgebras until the work of aczel (1988) on a theory of non-wellfounded sets, in which he introduced a proof principle nowadays called coinduction. it was formulated in terms of bisimulation, a notion originally stemming from the world of concurrent programming languages (milner, 1980; park, 1981). using the notion of coalgebra homomorphism, the definition of bisimulation on coalgebras can be shown to be formally dual to that of congruence on algebras (aczel and mendler, 1989). thus the three basic notions of universal algebra: algebra, homomorphism of algebras, and congruence, turn out to correspond to: coalgebra, homomorphism of coalgebras, and bisimulation, respectively. in this paper, the latter are taken as the basic ingredients of a theory called universal coalgebra. some standard results from universal algebra are reformulated (using the afore mentioned correspondence) and proved for a large class of coalgebras, leading to a series of results on, e.g., the lattices of subcoalgebras and bisimulations, simple coalgebras and coinduction, and a covariety theorem for coalgebras similar to birkhoff''s variety theorem.
behavioural differential equations: a coinductive calculus of streams, automata, and power series. we present a theory of streams (infinite sequences), automata and languages, and formal power series, in terms of the notions of homomorphism and bisimulation, which are the cornerstones of the theory of (universal) coalgebra. this coalgebraic perspective leads to a unified theory, in which the observation that each of the aforementioned sets carries a so-called final automaton structure, plays a central role. finality forms the basis for both definitions and proofs by coinduction, the coalgebraic counterpart of induction. coinductive definitions take the shape of what we have called behavioural differential equations, after brzozowski's notion of input derivative. a calculus is developed for coinductive reasoning about all of the afore mentioned structures, closely resembling calculus from classical analysis.
a tutorial on coinductive stream calculus and signal flow graphs. this paper presents an application of coinductive stream calculus to signal flow graphs. in comparison to existing approaches, which are usually based on z-transforms (a discrete version of laplace transforms) and transfer functions, the model presented in these notes is very elementary. the formal treatment of flow graphs is interesting because it deals with two fundamental phenomena in the theory of computation: memory (in the form of register or delay elements) and infinite behaviour (in the form of feedback).
elements of generalized ultrametric domain theory. a generalized ultrametric space is an ordinary ultrametric space in which the distance need not be symmetric, and where different elements may have distance 0. our interest in generalized ultrametric spaces is primarily motivated by the following observations: 1. (possibly nondeterministic) transition systems can be naturally endowed with a generalized ultrametric that captures their operational behavior in terms of simulations; 2. the category of generalized ultrametric spaces contains both the categories of preorders and of ordinary ultrametric spaces as full subcategories. a theory of generalized ultrametric spaces is developed along the lines of the work by smyth and plotkin (1982) and america and rutten (1989), such that its restriction to preorders and ordinary ultrametric spaces yields (more and less) familiar facts. our work has in common with other recent work along the same lines---by flagg and kopperman, and wagner---that it is directly based on lawvere''s v-categorical interpretation of metric spaces, and uses results on quasimetrics by smyth. it is different in being far less general, and consequently a number of new results, specific for generalized ultrametric spaces, is obtained. in particular, domain equations are solved by means of metric adjoint pairs, and the notions of (generalized) totally-boundedness and bifinite (or `sfu'') domain are introduced and characterized.
application of kolmogorov complexity and universal codes to identity testing and nonparametric testing of serial independence for time series. we show that kolmogorov complexity and such its estimators as universal codes (or data compression methods) can be applied for hypotheses testing in a framework of classical mathematical statistics. the methods for identity testing and nonparametric testing of sérial independence for time series are suggested.
on the p-np problem over real matrix rings. we prove that p ≠ dnp over rings of matrices with real elements in a restricted blum-shub-smale computational model. the restriction is that machines can use only two constants (zero-matrix and identity matrix) in computations. also we show that in the unrestricted blum-shub-smale model p = dnp over real matrix rings iff p = dnp over the non-ordered real ring and the same is true for the equality p = np. the latter assertion implies that p ≠ np over real matrix rings.
the structure of subword graphs and suffix trees of fibonacci words. we use automata-theoretic approach to analyze properties of fibonacci words. the directed acyclic subword graph (dawg) is a useful deterministic automaton accepting all suffixes of the word. we show that dawg's of fibonacci words have particularly simple structure. our main result is a unifying framework for a large collection of relatively simple properties of fibonacci words. the simple structure of dawgs of fibonacci words gives in many cases simplified alternative proofs and new interpretation of several well-known properties of fibonacci words. in particular, the structure of lengths of paths corresponds to a number-theoretic characterization of occurrences of any subword. using the structural properties of dawg's it can be easily shown that for a string ω we can check if ω is a subword of a fibonacci word in time o(|ω|) and o(1) space. compact dawg's of fibonacci words show a very regular structure of their suffix trees and show how the suffix tree for the fibonacci word grows (extending the leaves in a very simple way) into the suffix tree for the next fibonacci word.
multiple points of tilings associated with pisot numeration systems. this paper deals with a kind of aperiodic tilings associated with pisot numeration systems, originally due to w.p. thurston, in the formulation of s. akiyama. we treat tilings whose generating pisot units β are cubic and not totally real. each such tiling gives a numeration system on the complex plane; we can express each complex number z in the following form: z = ck α-k + ck-1 α-k+1 +...+ c1 α-1 + c0 + c-1 α1 + c-2 α2 +..., where α is a conjugate of β, and c-m c-m+1... ck-1 ck is the β-expansion of some real number for any integer m. we determine the set of complex numbers which have three or more representations. this is equivalent to determining the triple points of the tiling, which is shown to be a collection of model sets (or cut-and-project sets). we also determine the set of complex numbers with eventually periodic representations.
combinatorics and algorithms for low-discrepancy roundings of a real sequence. we discuss the problem of computing all the integer sequences obtained by rounding an input sequence of n real numbers such that the discrepancy between the input sequence and each output binary sequence is less than one. the problem arises in the design of digital halftoning methods in computer graphics. we show that the number of such roundings is at most n + 1 if we consider the discrepancy with respect to the set of all subintervals, and give an efficient algorithm to report all of them. then, we give an optimal method to construct a compact graph to represent the set of global roundings satisfying a weaker discrepancy condition.
bias and pathology in minimax search. this article presents the results of experiments designed to gain insight into the effect of the minimax algorithm on the error of a heuristic evaluation function. two types of effect of minimax are considered: (a) evaluation accuracy (are the minimax backed-up values more accurate than the heuristic values themselves?), and (b) decision accuracy (are moves played by deeper minimax search better than those by shallower search?). the experiments were performed in the king-rook-king (krk) chess endgame and in randomly generated game trees. the results show that, counter-intuitively, evaluation accuracy may decline with search depth, whereas at the same time decision accuracy improves with depth. in the article, this is explained by the fact that minimax in combination with a noisy evaluation function introduces a bias into the backed-up evaluations, which masks the evaluation effectiveness of minimax, but this bias still permits decision accuracy to improve with depth. this observed behaviour of minimax in the krk endgame is discussed in the light of previous studies of pathology in minimax. it is shown that explaining the behaviour of minimax in an actual chess endgame in terms of previously known results requires special care.
on an optimal propositional proof system and the structure of easy subsets of taut. in this paper we develop a connection between optimal propositional proof systems and structural complexity theory--specifically, there exists an optimal propositional proof system if and only if there is a suitable recursive presentation of the class of all easy (polynomial time recognizable) subsets of taut. as a corollary we obtain the result that if there does not exist an optimal propositional proof system, then for every theory t there exists an easy subset of taut which is not t-provably easy.
ordering default theories and nonmonotonic logic programs. first-order theories are ordered under logical entailment based on the amount of information derived from theories. in default logic, on the other hand, a theory contains default information as well as definite information. to order default theories, distinguishing different sorts of information is necessary to assess the information content of a default theory. for this purpose, we first introduce a multi-valued interpretation of default theories using a ten-valued bilattice. it distinguishes between definite and credulous/skeptical default information derived from a theory, and is used for ordering default theories based on their information contents. we then apply the technique to order nonmonotonic logic programs under the answer set semantics. the results of this paper provide a method for comparing default theories or nonmonotonic logic programs in a manner different from the conventional extension/model-based viewpoint. moreover, they have important application to induction from nonmonotonic theories.
learning elementary formal systems with queries. the elementary formal system (efs) is a kind of logic programs which directly manipulates strings, and the learnability of the subclass called hereditary efss (hefss) has been investigated in the frameworks of the pac-learning, query-learning, and inductive inference models. the hierarchy of hefs is expressed by hefs(m,k,t,r), where m, k, t and r denote the number of clauses, the occurrences of variables in the head, the number of atoms in the body, and the arity of predicate symbols. the present paper deals with the learnability of hefs in the query learning model using equivalence queries and additional queries such as membership, predicate membership, entailment membership, and dependency queries. we show that the class hefs(*, k, t, r) is polynomial-time learnable with the equivalence and predicate membership queries and the class hefs(*,k,*,r) with termination property is polynomial-time learnable with the equivalence, entailment membership, and dependency queries for the unbounded parameter *. a lowerbound on the number of queries is presented. we also show that the class hefs(*,k,t,r) is hard to learn with the equivalence and membership queries under the cryptographic assumptions. furthermore, the learnability of the class of unions of regular pattern languages, which is a subclass of hefss, is investigated. the bounded unions of regular pattern languages are polynomial-time predictable with membership query. however, all unbounded unions of regular pattern languages are not polynomial-time predictable with membership queries if neither are the dnf formulas.
on dart-free perfectly contractile graphs. the dart is a graph obtained from a 4-clique by removing one edge and adding a pendant vertex adjacent to one vertex of degree three. an even pair is pair of vertices such that every chordless path between them has even length. a graph is perfectly contractile if every induced subgraph has a sequence of even-pair contractions that leads to a clique. we show that the dart-free graphs satisfy the conjecture of everett and reed about the forbidden structures for perfectly contractile graphs. our proof yields a polynomial-time algorithm to recognize dart-free perfectly contractile graphs.
uni-transitional watson-crick d0l systems. the phenomenon known as watson-crick complementarity is basic both in the experiments and theory of dna computing. while the massive parallelism of dna strands makes exhaustive searches possible, complementarity constitutes a powerful computational tool. it is also very fruitful to view complementarity as a language-theoretic operation: "bad" words obtained through a generative process are replaced by their complementary ones. this idea seems particularly suitable for lindenmayer systems. d0l systems augmented with a specific complementarity transition, watson-crick d0l systems, have turned out to be a most interesting model and have already been extensively studied. a language is generated by a watson-crick d0l system as a sequence of words. consequently, the systems can be applied also to compute functions in a natural way. in the present paper, attention is focused on uni-transitional systems, where at most one complementarity transition takes place in the generated sequence. in spite of their seeming simplicity, uni-transitional systems represent a vast extension of ordinary d0l systems. this becomes apparent in their capacity of defining functions. quite remarkably, all basic decision problems for uni-transitional systems are algorithmically equivalent among themselves, as well as equivalent to a celebrated open problem. we investigate also a simpler case of systems with regular triggers, as well as pose some open problems.
composition sequences for functions over a finite domain. diverse problems ranging from many-valued logics to finite automata can be expressed as questions concerning compositions of functions over a finite domain. we develop a theory dealing with the depth and complete depth of such functions. interconnections with synchronizable finite automata are also discussed. many of the very basic problems turn out to be np-hard. also several open problems are pointed out.
connections between subwords and certain matrix mappings. parikh matrices recently introduced have turned out to be a powerful tool in the arithmetizing of the theory of words. in particular, many inequalities between (scattered) subword occurrences have been obtained as consequences of the properties of the matrices. this paper continues the investigation of parikh matrices and subword occurrences. in particular, we study certain inequalities, as well as information about subword occurrences sufficient to determine the whole word uniquely. some algebraic considerations, facts about forbidden subwords, as well as some open problems are also included.
independence of certain quantities indicating subword occurrences. when words are characterized in terms of numerical quantities, awkward considerations due to the noncommutativity of words are avoided. the numerical quantity investigated in this paper is |w|u, the number of occurrences of a word u as a (scattered) subword of a word w. parikh matrices recently introduced have these quantities as their entries. according to the main result in this paper, no entry in a parikh matrix, no matter how high the dimension, can be computed in terms of the other entries. consequences concerning various inference problems between numbers |w|u themselves, as well as of the word w from these numbers, are obtained.
watson-crick d0l systems: the power of one transition. we investigate the class of functions computable by uni-transitional watson-crick d0l systems: only one complementarity transition is possible during each derivation. the class is characterized in terms of a certain min-operation applied to z-rational functions. we also exhibit functions outside the class, and show that the basic decision problems are equivalent or harder than a celebrated open problem. for instance, the latter alternative applies to the growth-bound problem for functions in the class.
on the state complexity of reversals of regular languages. we compare the number of states between minimal deterministic finite automata accepting a regular language and its reversal (mirror image). in the worst case the state complexity of the reversal is 2n for an n-state language. we present several classes of languages where this maximal blow-up is actually achieved and study the conditions for it. in the case of finite languages the maximal blow-up is not possible but still a surprising variely of different growth types can be exhibited.
decidability of edt0l structural equivalence. we show that a tree pushdown automaton can verify, for an arbitrary nondeterministically constructed structure tree t, that t does not correspond to any valid derivation of a given edt0l grammar. in this way we reduce the structural equivalence problem for edt0l grammars to deciding emptiness of the tree language recognized by a tree pushdown automaton, i.e., to the emptiness problem for context-free tree languages. thus we establish that structural equivalence for edt0l grammars can be decided effectively. the result contrasts the known undecidability result for et0l structural equivalence.
reductions in binary search trees. we analyze two bottom-up reduction algorithms over binary trees that represent replaceable data within a certain system, assuming the binary search tree (bst) probabilistic model. these reductions are based on idempotent and nilpotent operators, respectively. in both cases, the average size of the reduced tree, as well as the cost to obtain it, is asymptotically linear with respect to the size of the original tree. additionally, the limiting distributions of the size of the trees obtained by means of these reductions satisfy a central limit law of gaussian type.
the rectangle complexity of functions on two-dimensional lattices. let x be a non-empty set. let f:z2x. all vectors which occur have integer coefficients, and for =(a1,a2), =(b1,b2) we write or < if ajbj or aj < bj for j=1,2, respectively. let >0. a -block is a set of the form b(){z2| < +}. a -pattern is the restriction of f to some -block. the total number of distinct -patterns is called the -complexity of f. a conjecture of the authors implies that f is periodic if there is a >0 such that the -complexity of f does not exceed b1b2. in this paper, we prove the statement for b=(n,2) where n is any positive integer.
m-balanced words: a generalization of balanced words. consider to construct an infinite sequence, or an infinite word, from a finite set of letters such as each letter is distributed with "good balance," that is, as evenly as possible, when the densities of letters are provided. such words have been applied to many scheduling and routing problems in various areas. concerning the balancedness of words, the notions of regularity and balanced words have been exploited. however, it is known that there does not always exist a balanced word for given densities of letters. in this paper, we introduce a new notion called m-balanced words, which gives a measure of "well balancedness" for any words with any densities of letters. we derive some properties of m-balanced words and give a set of algorithms generating well balanced words. we further give a few examples of applications to simple network scheduling problems.
on the equational definition of the least prefixed point. we propose a method to axiomatize by equations the least prefixed point of an order preserving function. we discuss its domain of application and show that the boolean modal µ-calculus has a complete equational axiomatization. the method relies on the existence of a "closed structure" and its relationship to the equational axiomatization of action logic is made explicit. the implication operation of a closed structure is not monotonic in one of its variables; we show that the existence of such a term that does not preserve the order is an essential condition for defining by equations the least prefixed point. we stress the interplay between closed structures and fixed point operators by showing that the theory of boolean modal µ-algebras is not a conservative extension of the theory of modal µ-algebras. the latter is shown to lack the finite model property.
on the design of a constructive algorithm to solve the multi-peg towers of hanoi problem. this paper describes a placement strategy to compute a set of ``good'' locations where visual sensing will be most effective. throughout this paper it is assumed that a {\em polygonal 2-d map} of a workspace is given as input. this polygonal map --- also known as a {\em floor plan} or {\em layout} --- is used to compute a set of locations where expensive sensing tasks (such as 3-d image acquisition) could be executed. a map-building robot, for example, can visit these locations in order to build a full 3-d model of the workspace.the sensor placement strategy relies on a randomized algorithm that solves a variant of the {\em art-gallery problem}~\cite{oro87,she92,urr97}: find the minimum set of guards inside a polygonal workspace from which the entire workspace boundary is visible. to better take into account the limitations of physical sensors, the algorithm computes a set of guards that satisfies incidence and range constraints. although the computed set of guards is not guaranteed to have minimum size, the algorithm does compute with high probability a set whose size is at most a factor $\bigo{ (n + h) \cdot \log(c \ (n + h) ) }$ from the optimal size $c$, where $n$ is the number of edges in the input polygonal map and $h$ the number of obstacles in its interior (holes).
scalable percolation search on complex networks. we introduce a scalable searching protocol for locating and retrieving content in random networks with heavy-tailed and in particular power-law (pl) degree distributions. the proposed algorithm is capable of finding any content in the network with probability one in time o(log n), with a total traffic that provably scales sub-linearly with the network size, n. unlike other proposed solutions, there is no need to assume that the network has multiple copies of contents; the protocol finds all contents reliably, even if every node in the network starts with a unique content. the scaling behavior of the size of the giant connected component of a random graph with heavy-tailed degree distributions under bond percolation is at the heart of our results. the percolation search algorithm can be directly applied to make unstructured peer-to-peer (p2p) networks, such as gnutella, limewire and other file-sharing systems (which naturally display heavy-tailed degree distributions and approximate scale-free network structures), scalable. for example, simulations of the protocol on the limewire crawl number 5 network [ripeanu et al., mapping the gnutella network: properties of large-scale peer-to-peer systems and implications for system design, ieee internet comput. j. 6 (1) (2002)], consisting of over 65,000 links and 10,000 nodes, shows that even for this snapshot network, the traffic can be reduced by a factor of at least 100, and yet achieve a hit-rate greater than 90%.
locating reaction with 2-categories. groupoidal relative pushouts (grpos) have recently been proposed by the authors as a new foundation for leifer and milner's approach to deriving labelled bisimulation congruences from reduction systems. in this paper, we develop the theory of grpos further, proving that well-known equivalences, other than bisimulation, are congruences. to demonstrate the type of category theoretic arguments which are inherent in the 2-categorical approach, we construct grpos in a category of 'bunches and wirings.' finally, we prove that the 2-categorical theory of grpos is a generalisation of the approaches based on milner's precategories and leifer's functorial reactive systems.
learning taxonomic relation by case-based reasoning. in this paper, we propose a learning method of minimal casebase to represent taxonomic relation in a tree-structured concept hierarchy. we firstly propose case-based taxonomic reasoning and show an upper bound of necessary positive cases and negative cases to represent a relation. then, we give a learning method of a minimal casebase with sampling and membership queries. we analyze this learning method by sample complexity and query complexity in the framework of pac learning.
approximation of boolean functions by combinatorial rectangles. this paper deals with the number of monochromatic combinatorial rectangles required to approximate a boolean function on a constant fraction of all inputs, where each rectangle may use its own partition of the input variables. the main result of the paper is that the number of rectangles required for the approximation of boolean functions in this model is very sensitive to the allowed error. there is an explicitly defined sequence of boolean functions fn on n variables such that fn, has rectangle approximations with a constant number of rectangles and one-sided error 1/3 + o(1) or two-sided error 1/4 + o(1), but, on the other hand, fn requires exponentially many rectangles if the error bounds are decreased by an arbitrarily small constant.as applications of this result, the following separation results for read-once branching programs are obtained. the functions from the main result require only linear size for nondeterministic read-once branching programs and randomized read-once branching programs with two-sided error 1/3 + o(1), while randomized read-once branching programs with constant two-sided error smaller than 1/3 and unambiguous nondeterministic read-once branching programs require exponential size.
quantum branching programs and space-bounded nonuniform quantum complexity. in this paper, the space complexity of non-uniform quantum algorithms is investigated using the model of quantum branching programs (qbps). in order to clarify the relationship between qbps and non-uniform quantum turing machines, simulations between these two models are presented which allow to transfer upper and lower bound results. exploiting additional insights about the connection between the running time and the precision of amplitudes, it is shown that non-uniform quantum turing machines with algebraic amplitudes and qbps with a suitable analogous set of amplitudes are equivalent in computational power if both models work with bounded or unbounded error. furthermore, quantum ordered binary decision diagrams (qobdds) are considered, which are restricted qbps that can be regarded as a non-uniform analog of one-way quantum finite automata. upper and lower bounds are proved that allow a classification of the computational power of qobdds in comparison to usual deterministic and randomized variants of the model. finally, an extension of qbps is proposed where the performed unitary operation may depend on the result of a previous measurement. a simulation of randomized bps by this generalized qbp model as well as exponential lower bounds for its ordered variant are presented.
improved shortest path algorithms for nearly acyclic graphs. dijkstra's algorithm solves the single-source shortest path problem on any directed graph in o(m + n log n) time when a fibonacci heap is used as the frontier set data structure. here n is the number of vertices and m is the number of edges in the graph. if the graph is nearly acyclic, other algorithms can achieve a time complexity lower than that of dijkstra's algorithm. abuaiadh and kingston gave a single-source shortest path algorithm for nearly acyclic graphs with o(m + n log t) time complexity, where the new parameter, t, is the number of delete-min operations performed in priority queue manipulation. if the graph is nearly acyclic, then t is expected to be small, and the algorithm out-performs dijkstra's algorithm. takaoka, using a different definition for acyclicity, gave an algorithm with o(m + n log k) time complexity. in this algorithm, the new parameter, k, is the maximum cardinality of the strongly connected components in the graph.the generalised single-source (gss) problem allows an initial distance to be defined at each vertex in the graph. decomposing a graph into r trees allows the gss problem to be solved within o(m + r logr) time. this paper presents a new all-pairs algorithm with a time complexity of o(mn + nr log r), where r is the number of acyclic parts resulting when the graph is decomposed into acyclic parts. the acyclic decomposition used is setwise unique and can be computed in o(mn) time. if the decomposition has been pre-calculated, then gss can be solved within o(m + r log r) time whenever edge-costs in the graph change. a second new all-pairs algorithm is presented, with o(mn + nr2) worst-case time complexity, where r is the number of vertices in a pre-calculated feedback vertex set for the nearly acyclic graph. for certain graphs, these new algorithms offer an improvement on the time complexity of the previous algorithms.
a hierarchy result for read-once branching programs with restricted parity nondeterminism. restricted branching programs are considered in complexity theory in order to study the space complexity of sequential computations and in applications as a data structure for boolean functions. in this paper (⊕, k)-branching programs and (∨, k)-branching programs are considered, i.e., branching programs starting with a ⊕- (or ∨-)node with a fan-out of k whose successors are k read-once branching programs. this model is motivated by the investigation of the power of nondeterminism in branching programs and of similar variants that have been considered as a data structure. lower bound methods and hierarchy results for polynomial size (⊕, k)- and (∨, k)-branching programs with respect to k are presented.
a fast algorithm to generate necklaces with fixed content. we develop a fast algorithm for listing all necklaces with fixed content. by fixed content, we mean the number of occurrences of each alphabet symbol is fixed. initially, we construct a simple but inefficient algorithm by making some basic modifications to a recursive necklace generation algorithm. we then improve it by using two classic combinatorial optimization techniques. an analysis using straight forward bounding techniques is used to prove that the algorithm runs in constant amortized time.
oracles for vertex elimination orderings. by maintaining appropriate data structures, we develop constant-time transposition oracles that answer whether or not two adjacent vertices in a simple elimination ordering (seo) or a semiperfect elimination ordering (semipeo) can be swapped to produce a new seo or semipeo, respectively. combined with previous results regarding convex geometries and antimatroids, this allows us to list all seos of a strongly chordal graph and all semipeos of an hhda-free graph in gray code order. by applying a new amortized analysis we show that the algorithms run in constant amortized time.additionally, we provide a simple framework that can be used to exhaustively list the basic words for other antimatroids.
precise goal-independent abstract interpretation of constraint logic programs. we present a goal-independent abstract interpretation framework for constraint logic programs, and prove the sufficiency of a set of conditions for abstract domains to ensure that the analysis will never lose precision. along the way, we formally define constraint logic programming systems, give a formal semantics that is independent of the actual constraint domain and the details of the proof algorithm, and formally define the maximally precise abstraction of a constraint logic program.
topology matters: smoothed competitiveness of metrical task systems. borodin et al. (j. acm 39 (1992) 745) introduced metrical task systems, a framework to model a large class of online problems. metrical task systems can be described as follows. we are given a graph g = (v, e) with n nodes and a positive edge length λ(e) for every edge e ∈ e. an online algorithm resides in g and has to service a sequence of tasks that arrive online. a task τ specifies for each node v; ∈ v a request cost r (v) ∈ r0+ ∪ {∞}. if the algorithm resides in node u before the arrival of task τ, the cost to service task τ in node v is equal to the shortest path distance from u to v plus the request cost r(v). the objective is to service all tasks at minimum total cost. borodin et al. showed that every deterministic online algorithm has a competitive ratio of at least 2n - 1, independent of the underlying metric. moreover, they presented an online work function algorithm (wfa) that achieves this competitive ratio.we present a smoothed competitive analysis of wfa. that is, given an adversarial task sequence, we randomly perturb the request costs and analyze the competitive ratio of wfa on the perturbed sequence. here, we are mainly interested in the asymptotic behavior of wfa. our analysis reveals that the smoothed competitive ratio of wfa is much better than o(n) and that it depends on several topological parameters of the underlying graph g, such as the minimum edge length λmin, the maximum degree δ, the edge diameter emax, etc. for example, if the ratio between the maximum and the minimum edge length of g is bounded by a constant, the smoothed competitive ratio of wfa is o(emax (λmin/σ + log(δ))) and o(√nċ (λmin/sigma + log(δ))), where σ denotes the standard deviation of the smoothing distribution. that is, already for perturbations with σ= θ(λmin) the competitive ratio reduces to o(log(n)) on a clique and to o(√/n) on a line. furthermore, we provide lower bounds on the smoothed competitive ratio of any deterministic algorithm. we prove two general lower bounds that hold independently of the underlying metric. moreover, we show that our upper bounds are asymptotically tight for a large class of graphs.we also provide the first average case analysis of wfa. we prove that wfa has o(log(δ)) expected competitive ratio if the request costs are chosen randomly from an arbitrary non-increasing distribution with standard deviation σ = θ(λmin).
poset-valued sets or how to build models for linear logics. we describe a method for constructing models of linear logic based on the category of sets and relations. the resulting categories are non-degenerate in general; in particular they are not compact closed nor do they have biproducts. the construction is simple, lifting the structure of a poset to the new category. the underlying poset thus controls the structure of this category, and different posets give rise to differently-flavoured models. as a result, this technique allows the construction of models for both, intuitionistic or classical linear logic as desired. a number of well-known models, for example coherence spaces and hypercoherences, are instances of this method.
a characterization of partial metrizability: domains are quantifiable. a characterization of partial metrizability is given which provides a partial solution to an open problem stated by künzi in the survey paper non-symmetric topology (in: proceedings of the szekszard conference, bolyai soc. math. studies, vol. 4, 1993, pp. 303-338; problem 7 ). the characterization yields a powerful tool which establishes a correspondence between partial metrics and special types of valuations, referred to as q-valuations (cf. also theoret. comput. sci., to appear). the notion of a q-valuation essentially combines the well-known notion of a valuation with a weaker version of the notion of a quasi-unimorphism, i.e. an isomorphism in the context of quasi-uniform spaces. as an application, we show that ω-continuous directed complete partial orders (dcpos) are quantifiable in the sense of o'neill (in: s. andima et al. (eds.), proceedings of the 11th summer conference on general topology and applications, annals of the new york academy of sciences, vol. 86, 1997, pp. 304-315), i.e. the scott topology and partial order are induced by a partial metric. for ω-algebraic dcpos the lawson topology is induced by the associated metric. the partial metrization of general domains improves prior gpproaches in two ways: • the partial metric is guaranteed to capture the scott topology as opposed to e.g. smyth (quasi-uniformities: reconciling domains with metric spaces, lecture notes in computer science, vol. 298, springer, berlin, 1987, pp. 236-253), bonsangue et al. (theoret. comput. sci. 193 (1998) 1), flagg (theoret. comput. sci., to appear) and flagg (theoret. comput. sci. 177 (1) (1997) 1), which in general yield a coarser topology. • partial metric spaces are smyth-completable and hence their smyth-completion reduces to the standard bicompletion. this type of simplification is advocated in smyth (in: g.m. reed, a.w. roscoe, r.f. wachter (eds.), topology and category theory in computer science, oxford university press, oxford, 1991, pp. 207-229). our results extend smyth (1991)'s scope of application from the context of 2/3 sfp domains to general domains.the quantification of general domains solves an open problem on the partial metrizability of domains stated in o'neil (1997) and heckmann (appl. categor. struct. (1999) 71 ).our proof of the quantifiability of domains is novel in that it relies on the central notion of a semivaluation (schellekens, the correspondence between partial metrics and semivaluations, theoret. comput. sci., to appear). the characterization of partial metrizability is entirely new and sheds light on the deeper connections between partial metrics and valuations commented on in [bukatin and shorina (in: m. nivat (ed.), foundations of software science and computation structures, lecture notes in computer science, vol. 1378, springer, berlin, 1998, pp. 125-139)]. based on (schellekens, the correspondence between partial metrics and semivaluations, theoret. comput. sci., to appear) and our present characterization, we conclude that the notion of a (semi)valuation is central in the context of quantitative domain theory since it can be shown to underlie the various mode s arising in the applications.
the correspondence between partial metrics and semivaluations. partial metrics, or the equivalent weightable quasi-metrics, have been introduced in matthews (proc. 8th summer conf. on general topology and applications; ann. new york acad. sci. 728 (1994) 183) as part of the study of the denotational semantics of data flow networks (theoret. comput. sci. 151 (1995) 195). the interest in valuations in connection to domain theory derives from e.g. jones and plotkin (lics '89, ieee computer society press, silver spring, md, 1998, pp. 186-195), jones (ph.d. thesis, university of edinburgh, 1989), edalat (lics'94, ieee computer society press, silver spring, md, 1994) and heckmann (fund. inform. 24(3) (1995) 259). connections between partial metrics and valuations have been discussed in the literature, e.g. o'neill (in: s. andima et al. (eds.), proc. 11th summer conf. on general topology and applications; ann. new york acad. sci. 806 (1997) 304), bukatin and scott (in: s. adian, a. nerode (eds.), logical foundations of computer science, lecture notes in computer science, vol. 1234, springer, berlin, 1997, pp. 33-43) and bukatin and shorina (in: m. nivat (ed.), foundations of software science and computation structures, lecture notes in computer science, vol. 1378, springer, berlin, 1998, pp. 125-139). in each case, partial metrics are generated from strictly increasing valuations.we analyze the precise relationship between these two notions. it is well known that characterizations of partial metrics in general are hard to obtain, as witnessed by the open characterization problems in the survey paper nonsymmetric topology (kúnzi (bolyai soc. math. stud. 4 (1993) 303). our approach to obtaining such a characterization involves the isolation of a "mathematically nice" class of spaces, which is sufficiently large to incorporate the quantitative domain theoretic examples involving partial metric spaces.for these purposes we focus on the class of quasi-metric semilattices. these structures, as will be illustrated, arise naturally in quantitative domain theory and include in particular the class of totally bounded scott domains discussed in smyth (in: g.m. reed, a.w. roscoe, r.f. wachter (ed.), topology and category theory in computer science, oxford university press, oxford, 1991, pp. 207-229), the baire quasi-metric spaces of (theoret. comput. sci. 151 (1995) 195), the complexity spaces of schellekens (in: proc. mfps 11, electronic notes in theoretical computer science, vol. i, elsevier, amsterdam, 1995, pp. 211-232) and the interval domain (proc. twelfth ann. ieee symp. on logic in computer science, ieee press, new york, 1997, pp. 248-257).we introduce the notion of a semivaluation, which generalizes the fruitful notion of a valuation on a lattice to the context of semilattices and establish a correspondence between partial metric semilattices and semivaluation spaces.
asm refinement and generalizations of forward simulation in data refinement: a comparison. in (j. universal comput. sci. 7 (2001) 952), we have formalized börger's refinement notion for abstract state machines (asms). the formalization was based on transition systems and verification conditions were expressed in dynamic logic.in this paper, the relation between asm refinement and data refinement is explored. data refinement expresses operations and verification conditions using relational calculus.we show how to bridge the gap between the different notations, and that forward simulation in the behavioral approach to data refinement can be viewed as a specific instance of asm refinement with 1:1 diagrams, where control structure is not refined.we also prove that two recent generalizations of data refinement, weak refinement and coupled refinement can be derived from asm refinement.
explaining updates by minimal sums. human reasoning about developments of the world involves always an assumption of inertia. we discuss two approaches for formalizing such an assumption, based on the concept of an explanation: (1) there is a general preference relation given on the set of all explanations and (2) there is a notion of a distance between models and explanations are preferred if their sum of distances is minimal. each distance dist naturally induces a preference relation dist. we show exactly under which conditions the converse is true as well and therefore both approaches are equivalent modulo these conditions. our main result is a general representation theorem in the spirit of kraus, lehmann and magidor. copyright 2001 elsevier science b.v.
theory of genetic algorithms ii: models for genetic operators over the string-tensor representation of populations and convergence to global optima for arbitrary fitness function under scaling. we present a theoretical framework for an asymptotically converging, scaled genetic algorithm which uses an arbitrary-size alphabet and common scaled genetic operators. the alphabet can be interpreted as a set of equidistant real numbers and multiple-spot mutation performs a scalable compromise between pure random search and neighborhood-based change on the alphabet level. we discuss several versions of the crossover operator and their interplay with mutation. in particular, we consider uniform crossover and gene-lottery crossover which does not commute with mutation. the vose-liepins version of mutation-crossover is also integrated in our approach. in order to achieve convergence to global optima, the mutation rate and the crossover rate have to be annealed to zero in proper fashion, and unbounded, power-law scaled proportional fitness selection is used with logarithmic growth in the exponent. our analysis shows that using certain types of crossover operators and large population size allows for particularly slow annealing schedules for the crossover rate. in our discussion, we focus on the following three major aspects based upon contraction properties of the mutation and fitness selection operators: (i) the drive towards uniform populations in a genetic algorithm using standard operations, (ii) weak ergodicity of the inhomogeneous markov chain describing the probabilistic model for the scaled algorithm, (iii) convergence to globally optimal solutions. in particular, we remove two restrictions imposed in theorem 8.6 and remark 8.7 of (theoret. comput. sci. 259 (2001) 1) where a similar type of algorithm is considered as described here: mutation need not commute with crossover and the fitness function (which may come from a coevolutionary single species setting) need not have a single maximum.
tabular parsing and algebraic transformations. tabular parsing is described by means of two homomorphic algebras. in this setting, the parsing problem is described as the computation of the inverse image of an input string with respect to the homomorphism. tabulation is obtained by constructing a quotient of the first algebra and using a finite subalgebra of the second algebra. the valid parse items are the elements generated by the variable-free terms in the product of these two algebras. this yields an algebraic construction method for tabular algorithms. we demonstrate the method by constructing a tabular bottom-up head-corner algorithm for context-free grammars. we then use the algebraic description of this algorithm to construct a tabular algorithm for linear indexed grammars, using a correctness-preserving algebraic transformation. this transformation is a formalization of the idea of an efficient representation of the unbounded lig stacks that is stated only informally in previous constructions of lig algorithms. the main feature of this method is the modularity of the construction, by allowing simpler tabular algorithms to be reused for the construction of more complex ones.
axioms for real-time logics. this paper presents a complete axiomatization of two decidable propositional real-time linear temporal logics: event clock logic (eventclocktl) and metric interval temporal logic with past (metricintervaltl). the completeness proof consists of an effective proof building procedure for eventclocktl. from this result we obtain a complete axiomatization of metricintervaltl by providing axioms translating metricintervaltl formulae into eventclocktl formulae, the two logics being equally expressive. our proof is structured to yield axiomatizations also for interesting fragments of these logics, such as the linear temporal logic of the real numbers (tlr).
two optimal parallel algorithms on the commutation class of a word. the free partially commutative monoid m(a,θ) defined by a set of commutation relations θ on an alphabet a can be viewed as a model for concurrent computing: indeed, the independence or the simultaneity of two actions can be interpreted by the commutation of two letters that encode them. in this context, the commutation class cθ(w) of a word w of the free monoid a* plays a crucial role. the main results presented in this paper are the following: - a characterization of the minimal automaton aθ(w) for cθ(w) with the help of the new notion of θ-dissection. - a parallel algorithm which computes the minimal automaton aθ(w). this algorithm is optimal if the size of a is constant. - an optimal parallel algorithm for testing if a word belongs to the commutation class cθ(w).our approach differs completely from the methods (based on foata's normal form) used by cérin and petit (application de la théorie des traces à l'implantation et à la mesure d'algorithmes de distribution, thèse université paris 11, centre d'orsay, 1993; proc. 6th internat. parallel processing symp. (ipps), ieee press, new york, 1992, pp. 374-379; proc. mfcs'93, lecture notes in computer science, vol. 711, springer, berlin, 1993, pp. 332-341) for solving similar problems. under some assumptions the first algorithm achieves an optimal speedup. the second algorithm achieves also an optimal speedup and has a time complexity in o(log n) if the number of processors is in o(n) where n is the length of the word w, the total number of operations is in o(n) and does not depend on the size of the alphabet a as for the classical sequential algorithm.
extended admissibility. we give a new definition of admissible representations which allows to handle also non countably-based topological spaces in the framework of type-2 theory of effectivity. we prove that admissible representations δx, δy of topological spaces x,y have the desirable property that every partial function f :⊆ x → y is continuously realizable with respect to δx, δy if and only if f is sequentially continuous. furthermore, we characterize the class of the spaces having an admissible representation. many interesting operators creating new topological spaces from old ones are shown to preserve the property of having an admissible representation. in particular, the class of sequential spaces with admissible representations turns out to be cartesian-closed. thus, a reasonable computability theory is possible on important non countably-based spaces.
amalgamation in the semantics of casl. we present a semantics for architectural specifications in the common algebraic specification language (casl), including an extended static analysis compatible with model-theoretic requirements. the main obstacle here is the lack of amalgamation for casl models. to circumvent this problem, we extend the casl logic by introducing enriched signatures, where subsort embeddings form a category rather than just a preorder. the extended model functor satisfies the amalgamation property as well as its converse, which makes it possible to express the amalgamability conditions in the semantic rules in static terms. using these concepts, we develop the semantics at various levels in an institution-independent fashion. moreover, amalgamation for enriched casl means that a variety of results for institutions with amalgamation, such as computation of normal forms and theorem proving for structured specifications, can now be used for casl.
combination of constraint systems ii: rational amalgamation. in two earlier papers (baader, schulz, in: u. montanari, f. rossi (eds.), proc. cp'95 springer lecture notes in computer science, vol. 976, springer, berlin, pp. 380-397; theoret. comput. sci 192 (1998) 107-161), the concept of "free amalgamation" has been introduced as a general methodology for interweaving solution structures for symbolic constraints, and it was shown how constraint solvers for two components can be lifted to a constraint solver for the free amalgam. here we discuss a second general way for combining solution domains, called rational amalgamation. in praxis, rational amalgamation seems to be the preferred combination principle if the two solution structures to be combined are "rational" or "non-wellfounded" domains. it represents, e.g., the way how rational trees and rational lists are interwoven in the solution domain of prolog iii, and a variant has been used by w. rounds for combining feature structures and hereditarily finite non-wellfounded sets. we show that rational amalgamation is a general combination principle, applicable to a large class of structures. as in the case of free amalgamation, constraint solvers for two component structures can be combined to a constraint solver for their rational amalgam. from this algorithmic point of view, rational amalgamation seems to be interesting since the combination technique for rational amalgamation avoids one source of non-determinism that is needed in the corresponding scheme for free amalgamation. copyright 2001 elsevier science b.v.
primitive recursion for higher-order abstract syntax. higher-order abstract syntax is a central representation technique in logical frameworks which maps variables of the object language into variables of the meta-language. it leads to concise encodings, but is incompatible with functions defined by primitive recursion or proofs by induction. in this paper we propose an extension of the simply typed lambda-calculus with iteration and case constructs which preserves the adequacy of higher-order abstract syntax encodings. the well-known paradoxes are avoided through the use of a modal operator which obeys the laws of s4. in the resulting calculus many functions over higher-order representations can be expressede legantly. our central technical result, namely that our calculus is conservative over the simply typed lambda-calculus, is proved by a rather complex argument using logical relations. we view our system as an important first step towards allowing the methodology of lf to be employed effectively in systems based on induction principles such as alf, coq, or nuprl, leading to a synthesis of currently incompatible paradigms. copyright 2001 elsevier science b.v.
unique existence, approximate solutions, and countable choice. an existential statement seems to admit of a constructive proof without countable choice only if the object to be constructed is uniquely determined, or is intended as an approximate solution of the problem in question. this conjecture is substantiated by re-examining some basic tools of mathematical analysis from a choice-free constructive point of view, starting from dedekind cuts as an appropriate notion of real numbers. by establishing a fairly general version of the approximate intermediate value theorem, we also indicate that strong continuity is a practicable substitute for uniform continuity, where a mapping between metric spaces is called strongly continuous if two subsets of its domain are bounded away from each other whenever so are their images.
efficient data mappings for parity-declustered data layouts. the joint demands of high performance and fault tolerance in a large array of disks can be satisfied by a parity-declustered data layout. such a data layout is generated by partitioning the data on the disks into stripes and choosing a part of each stripe to hold redundant information. thus the data layout can be represented as a table of stripes. the data mapping problem is the problem of translating a data address into a disk identifier and an offset on that disk. recent work has yielded mappings that compute disks and offsets directly from data addresses without the need to store tables. in this paper, we show that parity-declustered data layouts based on commutative rings yield mappings with improved computational efficiency and wider applicability.
on the expressive power of monadic least fixed point logic. monadic least fixed point logic mlfp is a natural logic whose expressiveness lies between that of first-order logic fo and monadic second-order logic mso. in this paper, we take a closer look at the expressive power of mlfp. our results are: (1) mlfp can describe graph properties beyond any fixed level of the monadic second-order quantifier alternation hierarchy. (2) on strings with built-in addition, mlfp can describe at least all languages that belong to the linear time complexity class dlin. (3) settling the question whether addition-invariant mlfp = addition-invariant mso on finite strings or, equivalently, settling the question whether mlfp = mso on finite strings with addition would solve open problems in complexity theory: "=" would imply that ph = ptime whereas "≠" would imply that dlin ≠ linh. apart from this we give a self-contained proof of the previously known result that mlfp is strictly less expressive than mso on the class of finite graphs.
an arithmetic for polynomial-time computation. we define a restriction lha of heyting arithmetic ha with the property that all extracted programs are feasible. the restrictions consist in linearity and ramification requirements.
logical optimality of groundness analysis. in the context of the abstract interpretation theory, we study the relations among various abstract domains for groundness analysis of the logic programs. we reconstruct the well-known domain as a logical domain in a fully automatic way and we prove that it is the best abstract domain which can be set up from the property of groundness by applying logic operators only. we propose a new notion of optimality which precisely captures the relation between and its natural concrete domain. this notion enables us to discriminate between the various abstract domains for groundness analysis from a computational point of view and to compare their relative precision. finally, we propose a new domain for groundness analysis which has the advantage of being independent from the specific program and we show it optimality. copyright 2002 elsevier science b.v.
on some generalizations of the thue-morse morphism. in 1912, the norwegian mathematician axel thue was the first to describe an overlap-free binary infinite word. this word was generated by a morphism which is called, since the works of morse, the thue-morse morphism. here, we present two generalizations of the thue-morse morphism in the case of alphabets with more than two letters. the extension of the characteristic properties of the word of thue to the words generated by these morphisms is considered. one of these generalizations corresponds to the construction of prouhet and a link with the arshon words is given. in particular, we prove that if n is an even number then the n-letter arshon word is generated by morphism.
lyndon factorization of the prouhet words. prouhet words are a natural generalization, over alphabets with more than two letters, of the well known binary thue-morse word.we give a unique factorization of these words in a sequence of decreasing lyndon words, then generalizing such a decomposition given by ido and melançon for the thue-morse word.
a manifesto for the computational method. we promote the much maligned computational method. the computational method is a paradigm for proving mathematical results where the burden of doing the "grunt work" is given to our able research assistant, the computer. we assert that proofs using the computational method, also known as computer aided proofs, are here to stay. in fact, the use of a computer can make the analysis of complicated algorithms fun. we illustrate the usefulness of the method by analyzing a randomized algorithm for multi-processor scheduling with rejection. more specifically, we present a randomized algorithm which is 1.44127-competitive. the best previously known result is a 1.5-competitive algorithm.
online companion caching. this paper is concerned with online caching algorithms for the (n, k)-companion cache, defined by brehob et al. (j. scheduling 6 (2003) 149). in this model the cache is composed of two components: a k-way set-associative cache and a companion fully associative cache of size n. we show that the deterministic competitive ratio for this problem is (n + 1)(k + 1) - 1, and the randomized competitive ratio is o(log n log k) and ω(log n + log k).
new bounds for randomized busing. we consider anonymous secure communication, where parties not only wish to conceal their communications from outside observers, but also wish to conceal the very fact that they are communicating. we consider the bus framework introduced by beimel and dolev (j. cryptology 16 (2003) 25), where messages are delivered by a bus traveling on a random walk. we generalize this idea to consider more than one bus. we show that if w buses are allowed, then the expected delivery time for a message can be decreased from θ(n) to θ(n/√w) in the case of a complete graph. additionally, we introduce a class of graphs called r-partite directed collars and obtain analogous bounds on the expected delivery time for these graphs. we also propose several new features that resolve possible shortcomings in the systems proposed by beimel and dolev.
verification and refinement with fine-grained action-based concurrent objects. action-based concurrent object-oriented programs express autonomous behavior of objects through actions that, like methods, are attached to objects but, in contrast to methods, may execute autonomously whenever their guard is true. the promise is a streamlining of the program structure by eliminating the distinction between processes and objects and a streamlining of correctness arguments. in this paper we illustrate the use of action-based object-oriented programs and study their verification and their refinement from specifications, including the issue of non-atomic operations.
order-incompleteness and finite lambda reduction models. many familiar models of the untyped lambda calculus are constructed by order-theoretic methods. this paper provides some basic new facts about ordered models of the lambda calculus. we show that in any partially ordered model that is complete for the theory of β- or βη-conversion, the partial order is trivial on term denotations. equivalently, the open and closed term algebras of the untyped lambda calculus cannot be non-trivially partially ordered. our second result is a syntactical characterization, in terms of so-called generalized mal'cev operators, of those lambda theories which cannot be induced by any non-trivially partially ordered model. we also consider a notion of finite models for the untyped lambda calculus, or more precisely, finite models of reduction. we demonstrate how such models can be used as practical tools for giving finitary proofs of term inequalities.
towards a descriptive set theory for domain-like structures. this is a survey of results in descriptive set theory for domains and similar spaces, with the emphasis on the ω-algebraic domains. we try to demonstrate that the subject is interesting in its own right and is closely related to some areas of theoretical computer science. since the subject is still in its beginning, we discuss in detail several open questions and possible future development. we also mention some relevant facts of (effective) descriptive set theory.
a reducibility for the dot-depth hierarchy. hierarchies considered in computability theory and in complexity theory are related to some reducibilities in the sense that levels of the hierarchies are downward closed and have complete sets. in this paper we propose a reducibility having similar relationship to the brzozowski's dot-depth hierarchy and some its refinements. we prove some basic facts on the corresponding degree structure and discuss relationships of the reducibility to complexity theory (via the leaf-language approach).
l(a)=l(b)? a simplified decidability proof. we give a proof of decidability of the equivalence problem for deterministic pushdown automata, which simplifies that of s&eacute;nizergues (theoret. comput. sci. 251 (2000) 1).
the approximability of non-boolean satisfiability problems and restricted integer programming. in this paper we present improved approximation algorithms for two classes of maximization problems defined in barland et al. (j. comput. system sci. 57(2) (1998) 144). our factors of approximation substantially improve the previous known results and are close to the best possible. on the other hand, we show that the approximation results in the framework of barland et al. hold also in the parallel setting, and thus we have a new common framework for both computational settings. we prove almost tight non-approximability results, thus solving a main open question of barland et al.we obtain the results through the constraint satisfaction problem over multi-valued domains, for which we develop approximation algorithms and show non-approximability results. our parallel approximation algorithms are based on linear programming and random rounding; they are better than previously known sequential algorithms. the non-approximability results are based on new recent progress in the fields of probabilistically checkable proofs and multi-prover one-round proof systems.
vectorial languages and linear temporal logic. determining for a given deterministic complete automaton the sequence of visited states while reading a given word is the core of important problems with automata-based solutions, such as approximate string matching. the main difficulty is to do this computation efficiently. considering words as vectors and working on them using vectorial operations allows to solve the problem faster than using local operations.in this paper, we show first that the set of vectorial operations needed by an algorithm representing a given automaton depends on the language accepted by the automaton. we give precise characterizations for star-free, solvable and regular languages using vectorial algorithms. we also study classes of languages associated with restricted sets of vectorial operations and relate them with languages defined by fragments of linear temporal logic.finally, we consider the converse problem of constructing an automaton from a given vectorial algorithm. as a byproduct, we show that the satisfiability problem for some extensions of ltl characterizing solvable and regular languages is pspace-complete.
games with winning conditions of high borel complexity. we first consider infinite two-player games on pushdown graphs. in previous work, cachat et al. [solving pushdown games with a σ3-winning condition, in: proc. 11th annu. conf. of the european association for computer science logic, csl 2002, lecture notes in computer science, vol. 2471, springer, berlin, 2002, pp. 322-336] have presented a winning decidable condition that is σ3-complete in the borel hierarchy. this was the first example of a decidable winning condition of such borel complexity. we extend this result by giving a family of decidable winning conditions of arbitrary finite borel complexity. from this family, we deduce a family of decidable winning conditions of arbitrary finite borel complexity for games played on finite graphs. the problem of deciding the winner for these conditions is shown to be non-elementary.
on learning embedded midbit functions. a midbit function on l binary inputs x1,...,xl outputs the middle bit in the binary representation of x1+...+xl. we consider the problem of probably approximately correct (pac) learning embedded midbit functions, where the set s ⊂ {x1,...,xn} of relevant variables on which the midbit depends is unknown to the learner.to motivate this problem, we first point out that a result of green et al. implies that a polynomial time learning algorithm for the class of embedded midbit functions would immediately yield a fairly efficient (quasipolynomial time) (pac) learning algorithm for the entire complexity class acc. we then give two different subexponential learning algorithms, each of which learns embedded midbit functions under any probability distribution in 2√n log n time. finally, we give a polynomial time algorithm for learning embedded midbit functions under the uniform distribution.
approximate reasoning by similarity-based sld resolution. in (gerla and sessa, fuzzy logic and soft computing, kluwer, norwell, 1999, pp. 19-31) a methodology that allows to manage uncertain and imprecise information in the frame of the declarative paradigm of logic programming has been proposed. with this aim, a similarity relation r between function and predicate symbols in the language of a logic program is considered. approximate inferences are then possible since similarity relation allows us to manage alternative instances of entities that can be considered "equal" with a given degree. the declarative semantics of the proposed transformation technique of logic programs is analyzed. the notion of fuzzy least herbrand model is also introduced. in this paper the corresponding operational semantics is provided by introducing a modified version of sld resolution. this top-down refutation procedure overcomes failure situations in the unification process by using the similarity relation. a generalized notion of most general unifier provides a numeric value which gives a measure of the exploited approximation. in this way, the sld resolution is enhanced since it is possible both to handle uncertain or imprecise information, and to compute approximate answer substitutions, with an associated approximation-degree, when failures of the exact inference process occur. it can lead to the implementation of a more general prolog interpreter, without detracting from the elegance of the language.
smaller solutions for the firing squad. in this paper we improve the bounds on the complexity of solutions to the firing squad problem, also known as the firing synchronization problem. in the firing synchronization problem we consider a one-dimensional array of n identical finite automata. initially all automata are in the same state except for one automaton designated as the initiator for the synchronization. our results hold for the original problem, where the initiator may be located at either endpoint, and for the variant where any one of the automata may be the initiator, called the generalized problem. in both cases, the goal is to define the set of states and transition rules for the automata so that all machines enter a special fire state simultaneously and for the first time during the final round of the computation. in our work we improve the construction for the best known minimal-time solution to the generalized problem by reducing the number of states needed and give non-minimal-time solutions to the original and generalized problem that use fewer states than the corresponding minimal-time solutions.
from rewrite rules to bisimulation congruences. the dynamics of many calculi can be most clearly defined by a reduction semantics. to work with a calculus, however, an understanding of operational congruences is fundamental; these can often be given tractable definitions or characterisations using a labelled transition semantics. this paper considers calculi with arbitrary reduction semantics of three simple classes, firstly ground term rewriting, then left-linear term rewriting, and then a class which is essentially the action calculi lacking substantive name binding. general definitions of labelled transitions are given in each case, uniformly in the set of rewrite rules, and without requiring the prescription of additional notions of observation. they give rise to bisimulation congruences. as a test of the theory it is shown that bisimulation for a fragment of ccs is recovered. the transitions generated for a fragment of the ambient calculus of cardelli and gordon, and for ski combinators, are also discussed briefly.
optimal insertion in deterministic dawgs. in this paper, we present an on-line algorithm for adding words (strings) in deterministic directed acyclic word graphs (dawgs) i.e. acyclic deterministic finite-state automata (dfas). the proposed algorithm performs optimal insertion, meaning that if applied to a minimal dawg, the dawg after the insertion will also be minimal. the time required to add a new word is o(n) with respect to the size of the dawg. repetitive application of the proposed insertion algorithm can be used to construct minimal deterministic dawgs incrementally, although the algorithm is not time-efficient for building minimal dawgs from a set of words: to build a dawg of n words this way, o(n2) time is required. however, the algorithm is quite useful in cases where existing minimal dawgs have to be updated rapidly (e.g. speller dictionaries), since each word insertion traverses only a limited portion of the graph and no additional minimization operation is required. this makes the process very efficient to be used on-line. this paper provides a proof of correctness for the algorithm, a calculation of its time-complexity and experimental results.
tight bounds for online class-constrained packing. we consider class-constrained packing problems, in which we are given a set of bins, each having a capacity v and c compartments, and n items of m different classes and the same (unit) size. we need to fill the bins with items, subject to capacity constraints, such that items of different classes are placed in separate compartments; thus, each bin can contain items of at most c distinct classes. we consider two optimization goals. in the class-constrained bin-packing problem (ccbp), our goal is to pack all the items in a minimal number of bins; in the class-constrained multiple knapsack problem (ccmk), we wish to maximize the total number of items packed in m bins, for m > 1. the ccbp and ccmk problems model fundamental resource allocation problems in computer and manufacturing systems. both are known to be strongly np-hard.in this paper we derive tight bounds for the online variants of these problems. we first present a lower bound of (1 + α) on the competitive ratio of any deterministic algorithm for the online ccbp, where α ∈ (0,1) depends on v, c, m and n. we show that this ratio is achieved by the algorithm first-fit. we then consider the temporary ccbp, in which items may be packed for a bounded time interval (that is unknown in advance). we obtain a lower bound of v/c on the competitive ratio of any (deterministic or randomized) algorithm. we show that this ratio is achieved by all any-fit algorithms. finally, tight bounds are derived for the online ccmk and the temporary ccmk problems.
super-tasks, accelerating turing machines and uncomputability. accelerating turing machines are devices with the same computational structure as turing machines (tm), but able to perform super-tasks. we ask whether performing super-tasks alone produces more computational power; for example, whether accelerating tm can solve the halting problem. we conclude that this is not the case. no accelerating tm solves the halting problem. the argument rests on an analysis of the reasoning that leads to thomson's paradox. the key point is that the paradox rests on a conflation of different perspectives of accelerating processes. this leads to concluding that the same conflation underlies the claim that accelerating tm can solve the halting problem.
on two-sided infinite fixed points of morphisms. let &sgr; be a finite alphabet, and let h:&sgr;*&sgr; be a morphism. finite and infinite fixed points of morphismsi.e., those words w such that h(w)=wplay an important role in formal language theory. head characterized the finite fixed points of h, and later, head and lando characterized the one-sided infinite fixed points of h. our paper has two main results. first, we complete the characterization of fixed points of morphisms by describing all two-sided infinite fixed points of h, for both the "pointed" and "unpointed" cases. second, we completely characterize the solutions to the equation h(xy)=yx in finite words.
on viewing block codes as finite automata. block codes are viewed from a formal language theoretic perspective. it is shown that properties of trellises for subclasses of block codes called rectangular codes follow naturally from the myhill nerode theorem. a technique termed subtrellis overlaying is introduced with the object of reducing decoder complexity. necessary and sufficient conditions for trellis overlaying are derived from the representation of the block code as a group, partitioned into a subgroup and its cosets. the conditions turn out to be simple constraints on coset leaders. it is seen that overlayed trellises are tail-biting trellises for which decoding is generally more efficient than that for conventional trellises. finally, a decoding algorithm for tail-biting trellises is described, and the results of some simulations are presented.
bijections and the riordan group. one of the cornerstone ideas in mathematics is to take a problem and to look at it in a bigger space. in this paper we examine combinatorial sequences in the context of the riordan group. various subgroups of the riordan group each give us a different view of the original sequence. in many cases this leads to both a combinatorial interpretation and to eco rewriting rules. in this paper we will concentrate on just four of the subgroups of the riordan group to demonstrate some of the possibilities of this approach.
logical operations and kolmogorov complexity. conditional kolmogorov complexity k(x|y) can be understood as the complexity of the problem "y&rarr;x", where x is the problem "construct x" and y is the problem "construct y". other logical operations (&uarr;, &darr;, &harr;) can be interpreted in a similar way, extending kolmogorov interpretation of intuitionistic logic and kleene realizability. this leads to interesting problems in algorithmic information theory. some of these questions are discussed.
loop checks for logic programs with functions. two complete loop checking mechanisms have been presented in the literature for logic programs with functions: os-check and eva-check. os-check is computationally efficient but quite unreliable in that it often misidentifies infinite loops, whereas eva-check is reliable for a majority of cases but quite expensive. in this paper, we develop a series of new complete loop checking mechanisms, called vaf-checks. the key technique we introduce is the notion of expanded variants, which captures a key structural characteristic of in finite loops. we show that our approach is superior to both os-check and eva-check in that it is as efficient as os-check and as reliable as eva-check. copyright 2001 elsevier science b.v.
2-role assignments on triangulated graphs. if g is a graph, a k-role assignment is a function mapping each vertex into a role, a positive integer 1, 2,...,k, so that if x and y have the same role, then the sets of roles assigned to their neighbors are the same. a graph is called a triangulated graph if it contains no chord-less cycle of four or more vertices. one interesting type of triangulated graph is the indifference graph, that is a graph for which we can find a function on its vertex set so that if x and y are adjacent, then their assigned function values are close. we study 2-role assignments for triangulated graphs. we provide a "greedy" algorithm for finding a 2-role assignment on a connected, nonbipartite triangulated graph with at most one pendant vertex. we characterize indifference graphs that have a 2-role assignment.
edge-colouring of join graphs. a join graph is the complete union of two arbitrary graphs. we give sufficient conditions for a join graph to be 1-factorizable. as a consequence of our results, the hilton's overfull subgraph conjecture holds true for several subclasses of join graphs.
asymptotically optimal declustering schemes for 2-dim range queries. declustering techniques have been widely adopted in parallel storage systems (e.g. disk arrays) to speed up bulk retrieval of multidimensional data. a declustering scheme distributes data items among multiple disks, thus enabling parallel data access and reducing query response time. we measure the performance of any declustering scheme as its worst case additive deviation from the ideal scheme. the goal thus is to design declustering schemes with as small an additive error as possible. we describe a number of declustering schemes with additive error o(log m) for 2-dimensional range queries, where m is the number of disks. these are the first results giving o(logm) upper bound for all values of m. our second result is a lower bound on the additive error. it is known that except for a few stringent cases, additive error of any 2-dimensional declustering scheme is at least one. we strengthen this lower bound to ω((logm)(d-1/2)) for d-dimensional schemes and to ω(logm) for 2-dimensional schemes, thus proving that the 2-dimensional schemes described in this paper are (asymptotically) optimal. these results are obtained by establishing a connection to geometric discrepancy. we also present simulation results to evaluate the performance of these schemes in practice.
on a monadic semantics for freshness. a standard monad of continuations, when constructed with domains in the world of fm-sets [m.j. gabbay, a.m. pitts, a new approach to abstract syntax with variable binding, formal aspects comput. 13 (2002) 341-363], is shown to provide a model of dynamic allocation of fresh names that is both simple and useful. in particular, it is used to prove that the powerful facilities for manipulating fresh names and binding operations provided by the "fresh" series of metalanguages [m.r. shinwell, swapping the atom: programming with binders in fresh o'caml, proc. merλin, 2003; m.r. shinwell, a.m. pitts, fresh o'caml user manual, cambridge university computer laboratory, september 2003, available at 〈http://www.freshml.org/foc/〉 m.r. shinwell, a.m. pitts, m.j. gabbay, freshml: programming with binders made simple, in: proc. icfp '03, acm press, 2003, pp. 263-274] respect α-equivalence of object-level languages up to meta-level contextual equivalence.
finite-state analysis of two contract signing protocols. optimistic contract signing protocols allow two parties to commit to a previously agreed upon contract, relying on a third party to abort or confirm the contract if needed. these protocols are relatively subtle, since there may be interactions between the subprotocols used for normal signing without the third party, aborting the protocol through the third party, or requesting confirmation from the third party. with the help of mur, a finite-state verification tool, we analyze two related contract signing protocols: the optimistic contract signing protocol of asokan, shoup, and waidner, and the abuse-free contract signing protocol of garay, jakobsson, and mackenzie. for the first protocol, we discover that a malicious participant can produce inconsistent versions of the contract or mount a replay attack. for the second protocol, we discover that negligence or corruption of the trusted third party may allow abuse or unfairness. in this case, contrary to the intent of the protocol, the cheated party is not able to hold the third party accountable. we present and analyze modifications to the protocols that avoid these problems and discuss the basic challenges involved in formal analysis of fair exchange protocols.
non-cooperative computation: boolean functions with correctness and exclusivity. we introduce the concept of non-cooperative computation (ncc), which is the joint computation of a function by self-motivated agents, where each of the agents possesses one of the inputs to the function. in ncc the agents communicate their input (truthfully or not) to a trusted center, which performs a commonly-known computation and distributes the results to the agents. the question is whether the agents can be incented to communicate their true input to the center, allowing all agents to compute the function correctly. ncc is a game theoretic concept and specifically is couched in terms of mechanism design. ncc is a very broad framework and is specialized by imposing specific structure on the agents' utility functions. the technical results we present are specific to the setting in which each agent has a primary interest in computing the function and a secondary interest in preventing the others from computing it (properties called correctness and exclusivity). for this setting we provide a complete characterization of the boolean functions that are non-cooperatively computable. we do this for three versions of ncc: a basic deterministic version, a probabilistic version and a version in which the computation can be subsidized by the center. the analysis turns out to depend on whether the inputs of the agents are probabilistically correlated or not and we analyze both cases.
correlation immunity and resiliency of symmetric boolean functions. correlation immunity of symmetric boolean functions is studied in this paper. lower bounds on the number of constructible correlation immune symmetric functions are given. constructions for such new balanced functions are presented. these functions are also known as 1-resilient functions. in 1985, chor et al. conjectured that the only 1-resilient symmetric functions are the exclusive-or of all n variables and its negation. this conjecture, however, was disproved by gopalakrishnan, hoffman and stinson in 1993 by giving a class of infinite counterexamples, and they noted that it does not seem to extend any further in an obvious way. in this paper two more infinite classes of such examples are presented for n being even and being odd, respectively, and consequently one of the two open problems proposed by gopalakrishnan et al., is addressed by constructing new symmetric resilient functions.
faster deterministic sorting through better sampling. in this paper, a refined deterministic sampling strategy is presented. it allows to improve the performance of deterministic sample-sort algorithms to the point that they can compete with their randomized counterparts. the method is illustrated by a detailed analysis for the cases of sorting on meshes and for sorting in external memory on a single processor machine.
faster gossiping on butterfly networks. gossiping has been considered intensively for butterflies and "simple" butterflies (which have no wrap-around connections). in the "telephone" communication model, for a butterfly of order k, the best previous gossiping algorithms require 2½k and 3k communication rounds, respectively. by new asymptotic methods we break through these bounds. we show that gossiping on a class of "column-based" networks, which also contains the cube-connected cycles, can be reduced to the simpler problem of "row-gossiping". row-gossiping in turn is reduced to "coherent row-broadcasting". this latter problem is sufficiently simple to be solved by a sophisticated computer program for butterflies with up to 15 × 215 nodes. out of the produced solutions a pattern is distilled, which can be used to perform gossiping on butterflies and simple butterflies of order k in 21/4k + o(k) and 2½k + o(k) rounds, respectively, for any k, considerably reducing the gap with the lower bounds. the new upper bounds also hold for gossiping in the weaker "telegraph" model.
endgame problems of sim-like graph ramsey avoidance games are pspace-complete. in sim, two players compete on a complete graph of six vertices (k6). the players alternate in coloring one as yet uncolored edge using their color. the player who first completes a monochromatic triangle (k3) loses. replacing k6 and k3 by arbitrary graphs generalizes sim to graph ramsey avoidance games. given an endgame position in these games, the problem of deciding whether the player who moves next has a winning strategy is shown to be pspace-complete. it can be reduced from the problem of whether the first player has a winning strategy in the game gpos(pos cnf) (schacfer, j. comput. system sci. 16 (2) (1978) 185-225). the following game variants are also shown to have pspace-complete endgame problems: (1) completing a monochromatic subgraph isomorphic to a is forbidden and the player who is first unable to move loses, (2) both players are allowed to color one or more edges in each move, (3) more than two players take part in the game, and (4) each player has to avoid a separate graph. in all results, the graphs to be avoided can be restricted to the bowtie graph (⋈, i.e., two triangles with one common vertex).
geometrical semantics for linear logic (multiplicative fragment). linear logic was described by girard as a logic of dynamic interactions. on the other hand, girard suggested an analogy between ll and quantum theory. following these two intuitions we give an interpretation of linear logic in the language, which is common for both dynamical systems and quantization. thus, we propose a denotational semantics for multiplicative linear logic using the language of symplectic geometry.we construct a category of coherent phase spaces and show that this category provides a model for mll. a coherent phase space is a pair: a symplectic manifold and a distinguished field of contact cones on this manifold. the category of coherent phase spaces is a refinement of the symplectic "category" introduced by weinstein. a morphism between two coherent phase spaces is a lagrangian submanifold of their product, which is tangent to some distinguished field of contact cones. thus, we interpret formulas of mll as fields of contact cones on symplectic manifolds, and proofs as integral submanifolds of corresponding fields.in geometric and asymptotic quantization symplectic manifolds are phase spaces of classical systems, and lagrangian submanifolds represent asymptotically states of quantized systems. typically, a lagrangian submanifold is the best possible localization of a quantum system in the classical phase space, as follows from the heisenberg uncertainty principle. lagrangian submanifolds are called sometimes "quantum points".from this point of view we interpret linear logic proofs as (geometric approximations to) quantum states and formulas as specifications for these states. in particular, the interpretation of linear negation suggests that the dual formulas a and a⊥ stand in the same relationship as the position and momentum observables. these two observables cannot simultaneously have definite values, much like the case of two dual formulas, which cannot simultaneously have proofs.
the homomorphism problem for trace monoids. it is proved to be decidable, for any given finite subset f of x*, dependency alphabet (y, τ) and mapping φ : f → y*, whether or not φ can be extended to a monoid homomorphism φ : f* → m(y,τ). this contrasts with the undecidability of the symmetric problem, when we consider the dependency alphabet (x, τ) instead. some other particular cases of homomorphism and isomorphism problems among trace monoids are also discussed.
constructing an asymptotic phase transition in random binary constraint satisfaction problems. the standard models used to generate random binary constraint satisfaction problems are described. at the problem sizes studied experimentally, a phase transition is seen as the constraint tightness is varied. however, achlioptas et al. showed that if the problem size (number of variables) increases while the remaining parameters are kept constant, asymptotically almost all instances are unsatisfiable. in this paper, an alternative scheme for one of the standard models is proposed in which both the number of values in each variable's domain and the average degree of the constraint graph are increased with problem size. it is shown that with this scheme there is asymptotically a range of values of the constraint tightness in which instances are trivially satis-able with probability at least 0.5 and a range in which instances are almost all unsatisfiable; hence there is a crossover point at some value of the constraint tightness between these two ranges. this scheme is compared to a similar scheme due to xu and li.
extensions and submonoids of automatic monoids. in this paper, submonoids and extensions of automatic and p-automatic monoids are studied. the concept of a p-automatic monoid is a variant on the usual concept of an automatic monoid designed to allow a geometric characterization analogous to the group case. in the case of right cancellative monoids, the two concepts coincide. here, we study rational submonoids of (p-)automatic monoids, being able to show in many cases that (p-)automaticity is inherited. our sharpest results concern rational subgroups. also, closure properties are established for various notions of extensions of (p-)automatic monoids, including different types of products, ideal extensions, and rees matrix constructions.
a linear time algorithm for binary tree sequences transformation using left-arm and right-arm rotations. in this paper, we consider a transformation on binary trees using new types of rotations. each of the newly proposed rotations is permitted only at nodes on the left-arm or the fight-arm of a tree. consequently, we develop a linear time algorithm with at most n - 1 rotations for converting weight sequences between any two binary trees. in particular, from an analysis of aggregate method for a sequence of rotations, each rotation of the proposed algorithm can be performed in a constant amortized time. next, we show that a specific directed rooted tree called rotation tree can be constructed using one of the new type rotations. as a by-product, a naive algorithm for enumerating weight sequences of binary trees in lexicographic order can be implemented by traversing the rotation tree.
an analysis of the lpt algorithm for the max-min and the min-ratio partition problems. given a set of positive numbers, the max-min partition problem asks for a k-partition such that the minimum part is maximized. the min-ratio partition problem has the similar definition but the objective is to minimize the ratio of the maximum to the minimum parts. in this paper, we analyze the performances of the longest processing time (lpt) algorithm for the two problems. we show that the tight bounds of the lpt are, respectively (4k - 2)/(3k - 1) and 7/5.
new results of exhaustive search in the game amazons. amazons is a young, abstract, strategic, two-player game, in which the first player unable to move loses. we present a database for small amazons positions, which for every position holds the canonical combinatorial game theory values, its thermograph and the corresponding move for every canonical option.such a database is useful to find values and structures in games that were unknown before and hard or impossible to find or verify by hand. in amazons we were able to prove the existence of numbers, of fractions down to 1/64 and of various infinitesimals, but these results also suggest that there is no easy construction for most of these values. the database also demonstrates how complex canonical forms in amazons can be and that many amazons positions have properties and values that are totally counterintuitive.
the computational power of benenson automata. the development of autonomous molecular computers capable of making independent decisions in vivo regarding local drug administration may revolutionize medical science. recently benenson et al. [an autonomous molecular computer for logical control of gene expression, nature 429 (2004) 423-429.] have envisioned one form such a "smart drug" may take by implementing an in vitro scheme, in which a long dna state molecule is cut repeatedly by a restriction enzyme in a manner dependent upon the presence of particular short dna "rule molecules." to analyze the potential of their scheme in terms of the kinds of computations it can perform, we study an abstraction assuming that a certain class of restriction enzymes is available and reactions occur without error. we also discuss how our molecular algorithms could perform with known restriction enzymes. by exhibiting a way to simulate arbitrary circuits, we show that these "benenson automata" are capable of computing arbitrary boolean functions. further, we show that they are able to compute efficiently exactly those functions computable by log-depth circuits. computationally, we formalize a new variant of limited width branching programs with a molecular implementation.
on categorical equivalence of gentzen-style derivations in imll. a new deciding algorithm for categorical equivalence of derivations in intuitionistic multiplicative linear logic (imll) is proposed. the algorithm is based uniquely on manipulations with gentzen-style derivations. the algorithm has low polynomial complexity. the paper also contains results concerning permutability of rules and its connection with categorical equivalence.
numerical factorization of multivariate complex polynomials. one can consider the problem of factoring multivariate complex polynomials as a special case of the decomposition of a pure dimensional solution set of a polynomial system into irreducible components. the importance and nature of this problem however justify a special treatment. we exploit the reduction to the univariate root finding problem as a way to sample the polynomial more efficiently, certify the decomposition with linear traces, and apply interpolation techniques to construct the irreducible factors. with a random combination of differentials we lower multiplicities and reduce to the regular case. estimates on the location of the zeroes of the derivative of polynomials provide bounds on the required precision. we apply our software to study the singularities of stewart-gough platforms.
universal computation with watson-crick d0l systems. watson-crick d0l systems, introduced in 1997 by mihalache and salomaa, arise from two major principles: the lindenmayer rewriting and the watson-crick complementarity principle. complementarity can be viewed as a purely language-theoretic operation. majority of a certain type of symbols in a string (purines vs. pyrimidines) triggers a transition to the complementary string. the paper deals with an expressive power of deterministic interactionless watson-crick lindenmayer systems. a rather surprising result is obtained: these systems, consisting of iterated morphism and a basic dna operation, are able to compute any turing computable function.
watson-crick d0l systems: generative power and undecidable problems. the properties of watson-crick d0l system, a language-theoretical formalism inspired by natural dna processing, are studied. the model incorporates the iterated d0l-like morphism and the dna complementarity principle represented by a letter-to-letter morphism. these two morphisms are connected by a natural condition called the trigger.we show first that this very simple model has rather unexpected power; it can closely and simply simulate any minsky register machine. as a consequence, any recursively enumerable language can be obtained as a projection of the language of some standard watson-crick d0l system. finally, we show that the graph reachability problem, equivalence problems and some other problems of standard watson-crick d0l systems are undecidable.
pert scheduling with convex cost functions. this paper deals with the problem of finding a minimum cost schedule for a set of dependent activities when a convex cost function is attached to the starting time of each activity. a first optimality necessary and sufficient condition bearing on the head and tail blocks of a schedule is first established. a second such condition that uses the spanning active equality trees of a schedule leads to design a generic algorithm for the general case. when the cost function is the usual earliness-tardiness linear function with assymetric and independent penalty coefficients, the problem is shown to be solved in o(n max{n,m}). finally, the special cases when the precedence graph is an intree or a family of chains are then also shown to be solved by efficient polynomial algorithms.
basic process algebra with deadlocking states. bisimilarity and regularity are decidable properties for the class of bpa (or context-free) processes (christensen et al., inform. and comput. 121 (1995) 143-148; burkart et al., proc. concur'96, lecture notes in computer science, vol. 1119, springer, berlin, 1996, pp. 247-262). we extend bpa with a deadlocking state obtaining bpa &dgr;systems. we show that the bpa &dgr; class is more expressive w.r.t. bisimilarity, but it remains language equivalent to bpa. we prove that bisimilarity and regularity remain decidable for bpa &dgr;. finally, we give a characterisation of those bpa&dgr; processes that can be equivalently (up to bisimilarity) described within the "pure" bpa syntax. copyright 2001 elsevier science b.v.
structural similarity within and among languages. linguists rely on intuitive conceptions of structure when comparing expressions and languages. in an algebraic presentation of a language, some natural notions of similarity can be rigorously defined (e.g. among elements of a language, equivalence w.r.t. isomorphisms of the language; and among languages, equivalence w.r.t. isomorphisms of symmetry groups), but it turns out that slightly more complex and nonstandard notions are needed to capture the kinds of comparisons linguists want to make. this paper identifies some of the important notions of structural similarity, with attention to similarity claims that are prominent in the current linguistic tradition of transformational grammar.
fast periodic correction networks. we consider the problem of sorting n-element inputs differing from already sorted sequences by t small changes. to perform this task we construct a constant depth comparator network that is applied periodically. the two constructions for this problem made, by previous authors required o(log n + t) iterations of the network. our construction requires o(log n + (log log n)2(log t)3) iterations which makes it asymptotically faster for t > log n.
formal specification and verification of the c# thread model. we present a high-level abstract state machine (asm) model of cg threads and the .net memory model. we focus on purely managed, fully portable threading features of c#. the sequential model interleaves the computation steps of the currently running threads and is suitable for uniprocessors. the parallel model addresses problems of true concurrency on multi-processor systems. the models provide a sound basis for the development of multi-threaded applications in c#. the thread and memory models complete the abstract operational semantics of c# in [börger et al. theoret. comput. sci., to appear]. the main invariants of the thread model concerning locks, monitors and mutual exclusion are formally verified in the asmtp system, an interactive proof assistant based on asm logic.
local heuristics and the emergence of spanning subgraphs in complex networks. we study the use of local heuristics to determine spanning subgraphs for use in the dissemination of information in complex networks. we introduce two different heuristics and analyze their behavior in giving rise to spanning subgraphs that perform well in terms of allowing every node of the network to be reached, of requiting relatively few messages and small node bandwidth for information dissemination, and also of stretching paths with respect to the underlying network only modestly. we contribute a detailed mathematical analysis of one of the heuristics and provide extensive simulation results on random graphs for both of them. these results indicate that, within certain limits, spanning subgraphs are indeed expected to emerge that perform well in respect to all requirements. we also discuss the spanning subgraphs' inherent resilience to failures and adaptability to topological changes.
formal analysis of pin block attacks. personal identification number (pin) blocks are 64-bit strings that encode a pin ready for encryption and secure transmission in banking networks. these networks employ tamper-proof hardware security modules (hsms) to perform sensitive cryptographic operations, such as checking the correctness of a pin typed by a customer. the use of these hsms is controlled by an api designed to enforce security. pin block attacks are unanticipated sequences of api commands which allow an attacker to determine the value of a pin in an encrypted pin block. this paper describes a framework for formal analysis of such attacks. our analysis is probabilistic, and is automated using constraint logic programming and probabilistic model checking.
on the k-path partition of graphs. the k-path partition problem is to partition a graph into the minimum number of paths, so that none of them has length more than k, for a given positive integer k. the problem is a generalization of the hamiltonian path problem and the problem of partitioning a graph into the minimum number of paths. the k-path partition problem remains np-complete on the class of chordal bipartite graphs if k is part of the input, and we show that it is np-complete on the class of comparability graphs even for k = 3. on the positive side, we present a polynomial-time solution for the problem, with any k, on bipartite permutation graphs, which form a subclass of chordal bipartite graphs.
learning algebraic structures from text. the present work investigates the learnability of classes of substructures of some algebraic structures: submonoids and subgroups of given groups, ideals of given commutative rings, subfields of given vector spaces. the learner sees all positive data but no negative one and converges to a program enumerating or computing the set to be learned. besides semantical (bc) and syntactical (ex) convergence also the more restrictive ordinal bounds on the number of mind changes are considered. the following is shown: (a) learnability depends much on the amount of semantic knowledge given at the synthesis of the learner where this knowledge is represented by programs for the algebraic operations, codes for prominent elements of the algebraic structure (like 0 and 1 fields) and certain parameters (like the dimension of finite-dimensional vector spaces). for several natural examples, good knowledge of the semantics may enable to keep ordinal mind change bounds while restricted knowledge may either allow only bc-convergence or even not permit learnability at all. (b) the class of all ideals of a recursive ring is bc-learnable iff the ring is noetherian. furthermore, one has either only a bc-learner outputting enumerable indices or one can already get an ex-learner converging to decision procedures and respecting an ordinal bound on the number of mind changes. the ring is artinian iff the ideals can be ex-learned with a constant bound on the number of mind changes, this constant is the length of the ring. ex-learnability depends not only on the ring but also on the representation of the ring. polynomial rings over the field of rationals with n variables have exactly the ordinal mind change bound in the standard representation. similar results can be established for unars. noetherian unars with one function can be learned with an ordinal mind change bound a&ohgr; for some a. copyright 2001 elsevier science b.v. all rights reserved.
learning classes of approximations to non-recursive function. blum and blum (inform. and control 28 (1975) 125-155) showed that a class b of suitable recursive approximations to the halting problem k is reliably ex-learnable but left it open whether or not b is in num. by showing b to be not in num we resolve this old problem.moreover, variants of this problem obtained by approximating any given recursively enumerable set a instead of the halting problem k are studied. all corresponding function classes u(a) are still ex-inferable but may fail to be reliably ex-learnable, for example if a is non-high and hypersimple.blum and blum (1975) considered only approximations to k defined by monotone complexity functions. we prove this condition to be necessary for making learnability independent of the underlying complexity measure. the class b of all recursive approximations to k generated by all total complexity functions is shown to be not even behaviorally correct learnable for a class of natural complexity measures. on the other hand, there are complexity measures such that b is ex-learnable. a similar result is obtained for all classes u(a).for natural complexity measures, b is shown to be not robustly learnable, but again there are complexity measures such that b and, more generally, every class u(a) is robustly ex-learnable. this result extends the criticism of jain et al. (j. comput. system sci. 62(1) (2001) 178-212), since the classes defined by artificial complexity measures turn out to be robustly learnable while those defined by natural complexity measures are not robustly learnable.
packing arrays. a packing array is a b × k array of values from a g-ary alphabet such that given any two columns, i and j, and for all ordered pairs of elements from the g-ary alphabet, (g1, g2), there is at most one row, r, such that ar,i = g1, and ar,j = g2. a central question is to determine, for given g and k, the maximum possible b. we develop general direct and recursive constructions and upper bounds on the sizes of packing arrays. we introduce the consideration of a set of disjoint rows in a packing array which allows these constructions and additionally gives a new upper bound on the size of all packing arrays. we also shove the equivalence of the problem to a matching problem on graphs and a class of resolvable pairwise balanced designs. we provide tables of the best known upper and lower bounds.
correctness of substring-preprocessing in boyer-moore's pattern matching algorithm. one of the main reasons for the high efficiency of the fast pattern matching algorithm of boyer and moore is preprocessing. the boyer-moore pattern matching algorithm utilizes two preprocessing algorithms: one on single characters and the other one on substrings. it is the latter which makes the pattern matching algorithm extremely fast (especially on natural language text). in the current paper we present a formal correctness proof of the program describing the substring-preprocessing algorithm. the proof is carried out within linear time temporal logic. during the process of our verification we found that indices of auxiliary arrays, as used in published high-level descriptions of the preprocessing algorithm, may run out of bounds. we demonstrate that this is the case and correct that undesirable aspect in the current paper.
real royal road functions for constant population size. evolutionary and genetic algorithms (eas and gas) are quite successful randomized function optimizers. this success is mainly based on the interaction of different operators like selection, mutation, and crossover. since this interaction is still not well understood, one is interested in the analysis of the single operators. jansen and wegener [proceedings of gecco'2001, 2001, pp. 375-382] have described so-called real royal road functions where simple steady-state gas have a polynomial expected optimization time while the success probability of mutation-based eas is exponentially small even after an exponential number of steps. this success of the ga is based on the crossover operator and a population whose size is moderately increasing with the dimension of the search space. here new real royal road functions are presented where crossover leads to a small optimization time, although the ga works with the smallest possible population size--namely 2.
simple and flexible detection of contiguous repeats using a suffix tree. we study the problem of detecting all occurrences of (primitive) tandem repeats and tandem arrays in a string. we first give a simple time- and space-optimal algorithm to find all tandem repeats, and then modify it to become a time and space-optimal algorithm for finding only the primitive tandem repeats. both of these algorithms are then extended to handle tandem arrays. the contribution of this paper is both pedagogical and practical, giving simple algorithms and implementations based on a suffix tree, using only standard tree traversal techniques
a proof-theoretic characterization of the basic feasible functionals. we provide a natural characterization of the type two mehlhorn-cook-urquhart basic feasible functionals as the provably total type two functionals of our (classical) applicative theory pt introduced in (inform. comput. 185 (2003) 263), thus providing a proof of a result claimed in the conclusion of strahm (2003). this further characterization of the basic feasible functionals underpins their importance as a key candidate for the notion of type two feasibility.
mell in the calculus of structures. the calculus of structures is a new proof theoretical formalism, like natural deduction, the sequent calculus and proof nets, for specifying logical systems syntactically. in a rule in the calculus of structures, the premise as well as the conclusion are structures, which are expressions that share properties of formulae and sequents. in this paper, i study a system for mell, the multiplicative exponential fragment of linear logic, in the calculus of structures. it has the following features: a local promotion rule, no non-deterministic splitting of the context in the times rule and a modular proof for the cut elimination theorem. further, derivations have a new property, called decomposition, that cannot be observed in any other known proof theoretical formalism.
the expected uncertainty of range-free localization protocols in sensor networks. we consider three range-free localization protocols for sensor networks and analyze their accuracy in terms of the expected area of uncertainty of position per sensor. assuming a small set of anchor nodes that know their position and broadcast it, we consider at first the simple intersection protocol. in this protocol a sensor assumes its position is within the part of the plane that is covered by all the broadcasts it can receive. we then extend this protocol by assuming every sensor is preloaded with the entire arrangement of anchors before being deployed. we show that in this case the same expected uncertainty can be achieved with 1/2 the anchor nodes. finally, we propose an approximation for the arrangement-based protocol which does not require any preliminary steps and prove that its expected accuracy converges to that of the arrangement protocol as the number of anchors increases.
lyndon trees. lyndon trees are introduced as a generalization of lyndon words, and the basic properties studied. a correspondence between the sets of lyndon words and lyndon trees is established. a unique factorization theorem for factoring a tree in terms of lyndon trees is proved. as an application of this result, a public key cryptosystem for trees is constructed, for which encryption and decryption are easy but cryptanalysis is hard. &mdash;authors' abstract
the bancomat problem: an example of resource allocation in a partitionable asynchronous system. a partition-aware application is an application that can make progress in multiple connected components. in this paper, we examine a particular partition-aware application to evaluate the properties provided by different partitionable group membership protocols. the application we examine is a simple resource allocation problem that we call the bancomat problem. we define a metric specific to this application, which we call the cushion, that captures the effects of the uncertainty of the global state caused from partitioning. we solve the bancomat problem using four different approaches for building partition-aware applications. we compare the approaches in terms of their cushions and discuss how well different group membership protocols support the different approaches.
cellular automata and intermediate degrees. we study a classification of cellular automata based on the turing degree of the orbits of the automaton. the difficulty of determining the membership of a cellular automaton in any one of these classes is characterized in the arithmetical hierarchy.
the size of power automata. we describe a class of simple transitive semiautomata that exhibit full exponential blowup during deterministic simulation. for arbitrary semiautomata we show that it is pspace-complete to decide whether the size of the accessible part of their power automata exceeds a given bound. we comment on the application of these results to the study of cellular automata.
the complexity of reversible cellular automata. we study the orbits of reversible one-dimensional cellular automata. it is shown that the turing degree structure of the orbits of these automata is the same as for general cellular automata. in particular there are reversible cellular automata whose orbits have arbitrary recursively enumerable degree.
ordered term tree languages which are polynomial time inductively inferable from positive data. in the fields of data mining and knowledge discovery, many semistructured data such as html/xml files are represented by rooted trees t such that all children of each internal vertex of t are ordered and t has edge labels. in order to represent structural features common to such semistructured data, we propose a linear ordered term tree, which is a rooted tree pattern consisting of ordered tree structures and internal structured variables with distinct variable labels. for a set of edge labels λ, let ottλ be the set of all linear ordered term trees. for a linear ordered term tree t in ottλ, the term tree language of t, denoted by lλ (t), is the set of all ordered trees obtained from t by substituting arbitrary ordered trees for all variables in t. given a set of ordered trees s, the minimal language problem for ottlλ = {lλ (t) | t ∈ ottλ} is to find a linear ordered term tree t in ottλ such that lλ (t) is minimal among all term tree languages which contain all ordered trees in s. we show that the class ottlλ is polynomial time inductively inferable from positive data, by giving a polynomial time algorithm for solving the minimal language problem for ottlλ.
optimal binary search trees with costs depending on the access paths. we describe algorithms for constructing optimal binary search trees, in which the access cost of a key depends on the k preceding keys which were reached in the path to it. this problem has applications to searching on secondary memory and robotics. two kinds of optimal trees are considered, namely optimal worst case trees and weighted average case trees. the time and space complexities of both algorithms are o(nk+2) and o(nk+1), respectively. the algorithms are based on a convenient decomposition and characterizations of sequences of keys which are paths of special kinds in binary search trees. finally, using generating functions, we present an exact analysis of the number of steps performed by the algorithms.
metaml and multi-stage programming with explicit annotations. we introduce metaml, a practically-motivated, statically-typed multi-stage programming language. metaml is a ``real'''' language. we have built an implementation and used it to solve multi-stage problems. % metaml allows the programmer to construct, combine, and execute code fragments in a type-safe manner. code fragments can contain free variables, but they obey the static-scoping principle. metaml performs type-checking for all stages once and for all before the execution of the first stage. % certain anomalies with our first metaml implementation has led us to formalize an illustrative subset of the metaml implementation. we present both a big-step semantics and type system for this subset, and prove the type system''s soundness with respect to a big-step semantics. from a software engineering point of view, this means that generators written in the metaml subset never generate unsafe programs. a type system and semantics for full metaml is still ongoing work. we argue that multi-stage languages are useful as programming languages in their own right, that they supply a sound basis for high-level program generation technology, and that they should support features that make it possible for programmers to write staged computations without significantly changing their normal programming style. to illustrate this we provide a simple three stage example elaborating a number of practical issues. % the design of metaml was based on two main principles that we identified as fundamental for high-level program generation, namely, cross-stage persistence and cross-stage safety. we present these principles, explain the technical problems they give rise to, and how we address with these problems in our implementation.
polynomial time learning of simple deterministic languages via queries and a representative sample. we show that simple deterministic languages are polynomial time learnable via membership queries if the learner knows a special finite set of positive examples. this finite set is called a representative sample and has been introduced by angluin inform. control 51 (1981) to show that regular languages are polynomial time learnable via membership queries. if simple deterministic languages are learnable in polynomial time via membership and equivalence queries, we can obtain a representative sample of a target language in polynomial time from a correct hypothesis. thus, our result implies that the polynomial time learning problem of simple deterministic languages via membership and equivalence queries is solvable if and only if we can find a representative sample in polynomial time via these queries. we show the learnability of simple deterministic languages by giving a learning algorithm. the algorithm, at the first stage, makes all possible candidate rules to generate the target language and a set of simple deterministic grammars which are little different each other. then, comparing them, the algorithm eliminates inappropriate rules.
topological properties of hausdorff discretization, and comparison to other discretization schemes. we study a new framework for the discretization of closed sets and operators based on hausdorff metric: a hausdorff discretization of an n-dimensional euclidean figure f of rn, in the discrete space d=zn, is a subset s of d whose hausdorff distance to f is minimal ( can be considered as the resolution of the discrete space d); in particular such a discretization depends on the choice of a metric on rn. this paper is a continuation of our works (ronse and tajine, j. math. imaging vision 12 (3) (2000) 219; hausdorff discretization for cellular distances, and its relation to cover and supercover discretization (to be revised for jvcir), 2000, wagner et al., an approach to discretization based on the hausdorff metric. i. ismm'98, kluwer academic publishers, dordrecht, 1998, pp. 67-74), in which we have studied some properties of hausdorff discretizations of compact sets. in this paper, we study the properties of hausdorff discretization for metrics induced by a norm and we refine this study for the class of homogeneous metrics. we prove that for such metrics the popular covering discretizations are hausdorff discretizations. we also compare the hausdorff discretization with the bresenham discretization (bresenham, ibm systems j. 4 (1) (1965) 25). actually, we prove that the bresenham discretization of a straight line of r2 is not always a good discretization relatively to the hausdorff metric. this result is an extension of tajine et al. (hausdorff discretization and its comparison with other discretization schemes, dgci'99, paris, lecture notes in computer sciences vol. 1568, springer, berlin, 1999, pp. 399-410), in which we prove the same result for a segment of r2. finally, we study how some topological properties of the euclidean plane r2 are translated in discrete space for hausdorff discretizations. actually, we prove that a hausdorff discretization of a connected closed set is 8-connected and its maximal hausdorff discretization is 4-connected for homogeneous metrics. we study a new framework for the discretization of closed sets and operators based on hausdorff metric: a hausdorff discretization of an n-dimensional euclidean figure f of rn, in the discrete space d=zn, is a subset s of d whose hausdorff distance to f is minimal ( can be considered as the resolution of the discrete space d); in particular such a discretization depends on the choice of a metric on rn. this paper is a continuation of our works (ronse and tajine, j. math. imaging vision 12 (3) (2000) 219; hausdorff discretization for cellular distances, and its relation to cover and supercover discretization (to be revised for jvcir), 2000, wagner et al., an approach to discretization based on the hausdorff metric. i. ismm'98, kluwer academic publishers, dordrecht, 1998, pp. 67-74), in which we have studied some properties of hausdorff discretizations of compact sets. in this paper, we study the properties of hausdorff discretization for metrics induced by a norm and we refine this study for the class of homogeneous metrics. we prove that for such metrics the popular covering discretizations are hausdorff discretizations. we also compare the hausdorff discretization with the bresenham discretization (bresenham, ibm systems j. 4 (1) (1965) 25). actually, we prove that the bresenham discretization of a straight line of r2 is not always a good discretization relatively to the hausdorff metric. this result is an extension of tajine et al. (hausdorff discretization and its comparison with other discretization schemes, dgci'99, paris, lecture notes in computer sciences vol. 1568, springer, berlin, 1999, pp. 399-410), in which we prove the same result for a segment of r2. finally, we study how some topological properties of the euclidean plane r2 are translated in discrete space for hausdorff discretizations. actually, we prove that a hausdorff discretization of a connected closed set is 8-connected and its maximal hausdorff discretization is 4-connected for homogeneous metrics. we study a new framework for the discretization of closed sets and operators based on hausdorff metric: a hausdorff discretization of an n-dimensional euclidean figure f of rn, in the discrete space d=zn, is a subset s of d whose hausdorff distance to f is minimal ( can be considered as the resolution of the discrete space d); in particular such a discretization depends on the choice of a metric on rn. this paper is a continuation of our works (ronse and tajine, j. math. imaging vision 12 (3) (2000) 219; hausdorff discretization for cellular distances, and its relation to cover and supercover discretization (to be revised for jvcir), 2000, wagner et al., an approach to discretization based on the hausdorff metric. i. ismm'98, kluwer academic publishers, dordrecht, 1998, pp. 67-74), in which we have studied some properties of hausdorff discretizations of compact sets. in this paper, we study the properties of hausdorff discretization for metrics induced by a norm and we refine this study for the class of homogeneous metrics. we prove that for such metrics the popular covering discretizations are hausdorff discretizations. we also compare the hausdorff discretization with the bresenham discretization (bresenham, ibm systems j. 4 (1) (1965) 25). actually, we prove that the bresenham discretization of a straight line of r2 is not always a good discretization relatively to the hausdorff metric. this result is an extension of tajine et al. (hausdorff discretization and its comparison with other discretization schemes, dgci'99, paris, lecture notes in computer sciences vol. 1568, springer, berlin, 1999, pp. 399-410), in which we prove the same result for a segment of r2. finally, we study how some topological properties of the euclidean plane r2 are translated in discrete space for hausdorff discretizations. actually, we prove that a hausdorff discretization of a connected closed set is 8-connected and its maximal hausdorff discretization is 4-connected for homogeneous metrics.
discovering instances of poetic allusion from anthologies of classical japanese poems. waka is a form of traditional japanese poetry with a 1300-year history. in this paper, we attempt to semi-automatically discover instances of poetic allusion, or more generally, to find similar poems in anthologies of waka poems. one reasonable approach would be to arrange all possible pairs of poems in two anthologies in decreasing order of similarity values, and to scrutinize high-ranked pairs by human effort. the means of defining similarity between waka poems plays a key role in this approach. in this paper, we generalize existing (dis)similarity measures into a uniform framework, called string resemblance systems, and using this framework, we develop new similarity measures suitable for finding similar poems. using the measures, we report successful results in finding instances of poetic allusion between two anthologies kokin-shu and shin-kokin-shu. most interestingly, we have found an instance of poetic allusion that has never before been pointed out in the long history of waka research.
discovering characteristic expressions in literary works. we attempt to extract characteristic expressions from literary works. that is, given two collections of literary works, one of which is written by a particular author (positive examples) and the other by a different author (negative examples), the problem is to find expressions that appear frequently in the positive examples but which are seldom found in the negative examples. this is considered as a special case of the optimal pattern discovery from textual data, in which only the substring patterns are considered. one approach would be to create a list of text substrings sorted according to goodness, and to scrutinize the first part of the list by human efforts. since there is no word boundary in japanese texts, a substring is often a fragment of a word or phrase. a method to assist domain experts who are involved in this task is a key problem. in this paper, we propose partitioning the text substrings into equivalence classes under an equivalence relation on strings, originally defined by blumer et al. (j. acm 34(3) (1987) 578). the equivalence relation has the desirable property that all members of each equivalence class necessarily have a unique goodness value. this idea effectively reduces the inefficiency of the task of evaluating mined patterns. we also present a method for browsing possible superstrings of a focused string as well as its context. we report successful results with two pairs of anthologies of classical japanese poems. we expect that the extracted expressions may lead to discovering overlooked aspects of individual poets.
top-down decision tree learning as information based boosting. we consider a boosting technique that can be directly applied to multiclass classification problems. although many boosting algorithms have been proposed so far, most of them are developed essentially for binary classification problems, and in order to handle multiclass classification problems, they need to be reduced somehow to binary ones. in order to avoid such reductions, we introduce a notion of the pseudo-entropy function g that gives an information-theoretic criterion, called the conditional g-entropy, for measuring the loss of hypotheses. the conditional g-entropy turns out to be useful for defining the weakness of hypotheses that approximate, in some way, a multiclass function in general, so that we can consider the boosting problem without reduction. we show that the top-down decision tree learning algorithm using the conditional g-entropy as its splitting criterion is an efficient boosting algorithm. namely, the algorithm intends to minimize the conditional g-entropy, rather than the classification error. in the binary case, our algorithm turns out to be identical to the error-based boosting algorithm proposed by kearns and mansour, and our analysis gives a simpler proof of their results.
predicting nearly as well as the best pruning of a decision tree through dynamic programming scheme. helmbold and schapire gave an on-line prediction algorithm that, when given an unpruned decision tree, produces predictions not much worse than the predictions made by the best pruning of the given decision tree. in this paper, we give two new on-line algorithms. the first algorithm is based on the observation that finding the best pruning can be efficiently solved by a dynamic programming in the "batch" setting where all the data to be predicted are given in advance. this algorithm works well for a wide class of loss functions, whereas the one given by helmbold and schapire is only described for the absolute loss function. moreover, the algorithm given in this paper is so simple and general that it could be applied to many other on-line optimization problems solved by dynamic programming. we also explore the second algorithm that is competitive not only with the best pruning but also with the best prediction values which are associated with nodes in the decision tree. in this setting, a greatly simplified algorithm is given for the absolute loss function. it can be easily generalized to the case where, instead of using decision trees, data are classified in some arbitrarily fixed manner.
rigorous results for mean field models for spin glasses. in this paper i explain why i believe that it is important to prove rigorous results about mean field models for spin glasses, and why i think it is difficult. i also describe at a high level what mathematicians have been able to prove.
actor theories in rewriting logic. the actor theory framework is a general semantic framework, based on the actor computation model, for specifying and reasoning about components of open distributed systems. it can be used to define both operational and trace-like interaction semantics for actor programming languages and specification notations. it can also be used to directly specify actor system components. the framework allows descriptions of system components written using different notations or at different levels of abstraction to be related: translations between actor programming languages can be shown to preserve interaction semantics, notions of satisfaction and refinement for specification notations can be defined and, using actor theory transformations, different descriptions of a component can be shown to be equivalent. in this paper we define the notion of an equationally presented actor theory and a mapping of equational presentations to theories in rewriting logic. we show that this mapping gives a correct representation of actor theory semantics by defining a correspondence between finite actor theory computations and rewrite theory proofs. to treat infinite computations and admissibility we extend the rewriting logic initial model construction to include infinite proofs, extend the mapping to infinite computations, and show that the correspondence preserves interaction semantics.
on size reduction techniques for multitape automata. we present a method for size reduction of two-way multitape automata. our algorithm applies local transformations that change the order in which transitions concerning different tapes occur in the automaton graph, and merge suitable states into a single state. our work is motivated by implementation of a language for string manipulation in database systems where string predicates are compiled into two-way multitape automata. additionally, we present a (one-tape) nfa reduction algorithm that is based on a method proposed for dfa minimization by kameda and weiner, and apply this algorithm, combined with the multitape automata reduction algorithm, on our multitape automata. empirical results on the performance of our method when applied on some multitape automata originating from string predicates are reported.
bideterministic automata and minimal representations of regular languages. bideterministic automata are deterministic automata with the property of their reversal automata also being deterministic. it has been known that a bideterministic automaton is the minimal deterministic automaton accepting its language. this paper shows that any bideterministic automaton is the unique minimal automaton among all (including nondeterministic) automata accepting the same language. we also present a more general result that shows that under certain conditions a minimal deterministic automaton accepting some language or the reversal of the minimal deterministic automaton of the reversal language is a minimal automaton representation of the language. these conditions can be checked in polynomial time.
on syntactic monoids of biunitary submonoids determined by homomorphisms from free semigroups onto completely simple semigroups. we deal with the maximal bifix code construction which is a natural generalization of a group code construction. for a surjective morphism ϕ from a free monoid a* onto a completely simple semigroup with an adjoined identity m (g; i, j; σ)1 and a submonoid s of m(g; i, j; σ)1, under certain conditions, the base of a submonoid ϕ-1 (s) is a maximal bifix code x. we investigate the relationships between the surjective morphism ϕ and the syntactic monoid of the monoid generated by x.
query complexity of membership comparable sets. this paper investigates how many queries to k-membership comparable sets are needed in order to decide all (k + 1)-membership comparable sets. for k ≥ 2 this query complexity is at least linear and at most cubic. as a corollary, we obtain that more languages are o(log n)-membership comparable than truth-table reducible to p-selective sets.
emerging behavior as binary search trees are symmetrically updated. when repeated updates are made to a binary search tree, the expected search cost tends to improve, as observed by knott. for the case in which the updates use an asymmetric deletion algorithm, the knott effect is swamped by the behavior discovered by eppinger. the knott effect applies also to updates using symmetric deletion algorithms, and it remains unexplained, along with several other trends in the tree distribution. it is believed that updates using symmetric deletion do not cause search cost to deteriorate, but the evidence is all experimental. the contribution of this paper is to model separately several different trends which may contribute to or detract from the knott effect, including a previously unreported centripetal tendency.
detecting quantum entanglement. we review the criteria for separability and quantum entanglement, both in a bipartite as well as a multipartite setting. we discuss bell inequalities, entanglement witnesses, entropic inequalities, bound entanglement and several features of multipartite entanglement. we indicate how these criteria bear on the experimental detection of quantum entanglement.
characterization of real time iterative array by alternating device. in this paper, we show that real time k-dimensional iterative arrays are equivalent through reverse to real time one-way alternating k-counter automata.
two-dimensional cellular automata and deterministic on-line tessalation automata. in this work we consider the relationships between the classes of two-dimensional languages defined by deterministic on-line tessellation automata and by real time two-dimensional cellular automata with moore and von neumann neighborhood. we generalize the result known for one-dimensional cellular automata to two-dimensional cellular automata with von neumann neighborhood: the class of real time cellular automata is closed under rotation of 180° if and only if real time cellular automata is equivalent to linear time cellular automata.
two-dimensional cellular automata and their neighborhoods. we investigate how the choice of the neighborhood can influence the computation ability of two-dimensional cellular automata. we present also a strict inclusion between low and high complexity classes of two-dimensional cellular automata.
closure properties of cellular automata. concerning the power of one-dimensional cellular automata recognizers, ibarra and jiang have proved that real time cellular automata (ca) and linear time ca are equivalent if and only if real time ca is closed under reverse. in this paper we investigate the question of equality of real time ca and linear time ca with respect to the operations of concatenation and cycle. in particular, we prove that if real time ca is closed under concatenation then real time ca is as powerful as linear time ca on the unary languages. we also prove that the question of knowing whether real time ca is as powerful than linear time ca is equivalent to the question of whether real time ca is closed under cycle. moreover, in the case of two-dimensional ca recognizers, we investigate how restricted communication reduces the computational power. in particular, we show that real time ca and linear time ca with restricted variants of moore and von neumann neighborhoods are not closed under rotation. furthermore, they are not equivalent to real time ca with moore or von neumann neighborhoods.
complete symbolic reachability analysis using back-and-forth narrowing. we propose a method called back-and-forth narrowing for solving reachability goals of the form (∃x→).t1 → *t'1...∧tn→*t'n in general term rewrite systems. the method is a complete semi-decision procedure in the sense that it is guaranteed to find a solution when one exists, but in general it may not terminate when there are no solutions. the completeness result is very general in that it makes no assumptions about the given term rewrite system. specifically, the rewrite rules need not be linear, confluent, or terminating, and can even have extra-variables in the right-hand side. such generality is often essential while modeling concurrent systems or axiomatizing inference systems as rewrite rules, and in such applications back-and-forth narrowing can be used as a sound and complete technique for symbolic reachability analysis or as a deductive procedure for proving existential formulae.
an o(n log n)-algorithm for finding a domino tiling of a plane picture whose number of holes is bounded. we consider the problem of tiling a plane picture with dominoes, this picture can be with holes or without holes. we give a necessary and sufficient condition for the existence of such a tiling and then we deduce an algorithm to decide whether a picture is tileable or not and if it is, to determine a tiling. this algorithm runs in o(kn + n log n) time, where n and k are the respective numbers of cells and holes. we also propose a simplified version of this algorithm which is linear in the area enclosed by the outer boundary, provided the picture has a bounded number of holes.
on the approximability of the steiner tree problem. we show that it is not possible to approximate the minimum steiner tree problem within 1+1/162 unless rp=np. the currently best known lower bound is 1 +1/400. the reduction is from hastad's nonapproximability result for maximum satisfiability of linear equation modulo 2. the improvement on the nonapproximability ratio is mainly based on the fact that our reduction does not use variable gadgets, this idea was introduced by papadimitriou and vempala.
uniform and nonuniform recognizability. deterministic and nondeterministic finite-state recognizability over finite structures are introduced in an algebraic setting, avoiding detailed computational conventions as needed in the definition of finite-state acceptors. for deterministic recognizability, the classical approach is adopted, using a "uniform" homomorphism from the input domain (consisting of terms) into a finite algebra. for the nondeterministic case, we refer to relational input structures and to an acceptance via relational homomorphisms (which are applied "nonuniformly" since they depend on the input structures). we show how this approach encompasses known models of nondeterministic automata over finite words, trees, pictures, and graphs, and present some elementary metaresults connecting uniform recognizability, nonuniform recognizability, and monadic second-order logic.
rauzy substitutions and multi-dimensional sturmian words. recently, berthé and the author developed a method to construct a multi-dimensional sturmian word as a limit of a sequence of words on lattice domains. in the present paper, the reach of the approach is studied in the special case of rauzy substitutions.
unions of non-disjoint theories and combinations of satisfiability procedures. in this paper we outline a theoretical framework for the combination of decision procedures for constraint satisfiability. we describe a general combination method which, given a procedure that decides constraint satisfiability with respect to a constraint theory t1 and one that decides constraint satisfiability with respect to a constraint theory t2, produces a procedure that (semi-)decides constraint satisfiability with respect to the union of t1 and t2. we provide a number of model-theoretic conditions on the constraint language and the component constraint theories for the method to be sound and complete, with special emphasis on the case in which the signatures of the component theories are non-disjoint. we also describe some general classes of theories to which our combination results apply, and relate our approach to some of the existing combination methods in the field.
petri net reactive modules. in this paper we model (discrete) reactive systems that may interact with each other by petri net reactive modules (modules, for short) which are classical petri nets together with a distinguished subset of interface places. we consider then an asynchronous composition operation of modules and, closely related to it, a decomposition operation. we show that any process (concurrent execution) of a composition of two modules can be decomposed into processes of "shifted" components for which a p-composition function exists, and vice versa. based on this result, a compositional semantics of modules is then defined. applications of process decomposition to replacement techniques of petri nets and in proving correctness of petri net structural transformations, are further discussed.
some relationships between logics of programs and complexity theory. the aim of this paper is to show that some open problems in comparative schematology and in logics of programs are equivalent to open problems in complexity theory. in particular we show that pspace = ptime holds if and only if flow-diagrams with arrays are of the same computational power as recursive procedures. these statements are also equivalent to the following statement: logics based on the above-mentioned classes of program schemes have equal expressive power. a similar characterization may be given for other complexity classes.
how to turn a second-order cellular automaton into a lattice gas: a new inversion scheme. in second-order cellular automata, the signals made available to the local transition function include, besides the current state of a site's neighbors, also the previous state of the site itself. some similarities had been noted, especially in physics simulations, between certain second-order cellular automata and certain lattice gases.here we show how to construct, for any second-order cellular automaton, a lattice gas having isomorphic functional behavior. (paradoxically, this isomorphism of function is achieved by compromising on the isomorphism of structure: namely, the group of translation symmetries of the resulting lattice gas is coarser than that of the original cellular automaton.) the advantage of our construction is that, while invertibility in cellular automata is not directly deducible from the local map (indeed, it is in general undecidable), in the second-order case the invertibility of the cellular automaton goes hand-in-hand with that of the corresponding lattice gas--and for lattices gases invertibility is trivially decidable on the basis of the local structure.from a physical viewpoint, our construction illustrates a trade-off between two ways of achieving a "force" of a given range. in a cellular automaton, multiple copies of a signal are made and distributed in parallel to several sites, explicitly providing the desired fanout width. in a lattice gas, with our construction, one can let a single signal serially service a number of sites along an appropriate spacetime route. the latter method is better suited to a nondissipative implementation of the dynamics.
on reasoning about structural equality in xml: a description logic approach. we define a boolean complete dialect of description logic called dlfdreg that can be used to reason about structural equality in semistructured ordered data in the presence of document type definitions. this application depends on the novel ability of dlfdreg to express functional dependencies over possibly infinite sets of feature paths defined by regular languages. we also present a decision procedure for the associated logical implication problem. the procedure underlies a mapping of such problems to satisfiability problems of datalog¬ns.
on the number of occurrences of all short factors in almost all words. we previously proved that almost all words of length n over a finite alphabet a with m letters contain as factors all words of length k(n) over a as n → ∞, provided lim supn → ∞k(n)/logn<1/ logm.in this note it is shown that if this condition holds, then the number of occurrences of any word of length k(n) as a factor into almost all words of length n is at least s(n), where limn → ∞log s(n)/log(n)=0, in particular, this number of occurrences is bounded below by c log n as n → ∞, for any absolute constant c > 0.
a characterization of the words occurring as factors in a minimum number of words. we show by an injective proof that a word w of length k≥2 occurs as a factor in a minimum number of length n (n > k) if and only if all letters of w are equal.
the worst-case time complexity for generating all maximal cliques and computational experiments. we present a depth-first search algorithm for generating all maximal cliques of an undirected graph, in which pruning methods are employed as in the bron-kerbosch algorithm. all the maximal cliques generated are output in a tree-like form. subsequently, we prove that its worst-case time complexity is o(3n/3) for an n-vertex graph. this is optimal as a function of n, since there exist up to 3n/3 maximal cliques in an n-vertex graph. the algorithm is also demonstrated to run very fast in practice by computational experiments.
channel graphs of bit permutation networks. channel graphs have been widely used in the study of blocking networks. in this paper, we show that a bit permutation network has a unique channel graph if and only if it is connected, and two connected bit permutation networks are isomorphic if and only if their channel graphs are isomorphic.
weak muller acceptance conditions for tree automata. over the last decades the theory of automata on infinite objects has been an important source of tools for the specification and the verification of computer programs. trees are more suitable than words to model nondeterminism and concurrency. in the literature, there are several examples of acceptance conditions that have been proposed for automata on infinite words and then have been fruitfully extended to infinite trees. the type of acceptance condition can influence both the succinctness of the language acceptors and the computational complexity of the decision problems. here we consider, relatively to automata on infinite trees, two acceptance conditions that are obtained by a relaxation of the muller acceptance condition: the landweber and the muller-superset conditions. we prove that muller-superset tree automata accept the same class of languages as büchi tree automata. also, we show that for such languages the minimal muller-superset acceptor is at least as succinct as the minimal büchi acceptor and, in some cases, it can be exponentially more succinct. landweber tree automata, instead, define a class of languages that is not comparable with that defined by büchi tree automata. the main result we prove is that the emptiness problem for this class of automata is decidable in polynomial time, and thus we extend the class of automata with a tractable emptiness problem.
compact representations as a search strategy: compression edas. the choice of representation crucially determines the capability of search processes to find complex solutions in which many variables interact. the question is how good representations can be found and how they can be adapted online to account for what can be learned about the structure of the problem from previous samples. we address these questions in a scenario that we term indirect estimation-of-distribution: we consider a decorrelated search distribution (mutational variability) on a variable length genotype space. a one-to-one encoding onto the phenotype space then needs to induce an adapted phenotypic search distribution incorporating the dependencies between phenotypic variables that have been observed successful previously. formalizing this in the framework of estimation-of-distribution algorithms, an adapted phenotypic search distribution can be characterized as minimizing the kullback-leibler divergence (kld) to a population of previously selected samples (parents). the paper derives a relation between this kld and the description length of the encoding, stating that compact representations provide a way to minimize the divergence. a proposed class of compression evolutionary algorithms and experiments with an grammar-based compression scheme illustrate the new concept.
reducing the time complexity of testing for local threshold testability. a locally threshold testable language l is a language with the property that for some non-negative integers k and l and for some word u from l, a word v belongs to l iff: (1) the prefixes [suffixes] of length k - 1 of words u and v coincide, (2) the number of occurrences of every factor of length k in both words u and v are either the same or greater than l - 1.a deterministic finite automaton is called locally threshold testable if the automaton accepts a locally threshold testable language for some l and k.new necessary and sufficient conditions for a deterministic finite automaton to be locally threshold testable are found. on the basis of these conditions, we modify the algorithm to verify local threshold testability of the automaton, and to reduce the time complexity of the algorithm. the algorithm is implemented as a part of the c/c++ package testas. http://www.cs.biu.ac.il/ ~trakht/testas.html.
the finiteness of synchronous, tabled picture languages is decidable. in the present paper, synchronous, tabled chain code picture systems based on lindenmayer systems (stol system) are studied with respect to the finiteness of their picture languages. the finiteness is proved to be decidable. additionally, a method is given for deciding whether or not an stol system generates a finite picture language.
linear array and ring embeddings in conditional faulty hypercubes. the n-dimensional hypercube qn is a graph having 2n vertices labeled from 0 to 2n - 1. two vertices are connected by an edge if their binary labels differ in exactly one bit position. in this paper, we consider the faulty hypercube qn with n ≥ 3 that each vertex of qn is incident to at least two nonfaulty edges. based on this requirement, we prove that qn contains a hamiltonian path joining any two different colored vertices even if it has up to 2n - 5 edge faults, moreover, we show that there exists a path of length 2n - 2 between any two the same colored vertices in this faulty qn. furthermore, we also prove that the faulty qn still contains a cycle of every even length from 4 to 2n inclusive.
new bounds for multi-label interval routing. interval routing (ir) is a space-efficient routing method for computer networks. for longest routing path analysis, researchers have focused on lower bounds for many years. for any n-node graph g of diameter d, there exists an upper bound of 2d for ir using one or more labels, and an upper bound of ⌈3/2d⌉ for ir using o(√nlogn) or more labels. we present two upper bounds in the first part of the paper. we show that for every integer i > 0, every n-node graph of diameter d has a k-dominating set of size o(i+1√n) for k ≤ (1 - 1/3i)d. this result implies a new upper bound of ⌈(2 - 1/3i)d⌉ for ir using o(i+1√n) or more labels, where i is any positive integer constant. we apply the result by kutten and peleg [7] to achieve an upper bound of (1 + α)d for ir using o(n/d) or more labels, where α is any constant in (0, 1). the second part of the paper offers some lower bounds for planar graphs. for any m-label interval routing scheme (m-irs), where m = o(3√n), we derive a lower bound of [(2m + 1)/(2m)]d - 1 on the longest path for m = o(√n), and a lower bound of [(2(1 + δ)m + 1)/(2(1 + δ)m)]d, where δ ∈ (0, 1], for m = o(√n). the latter result implies a lower bound of ω(√n) on the number of labels needed to achieve optimality.
real number computation through gray code embedding. we propose an embedding g of the unit open interval to the set {0, 1}⊥,1ω of infinite sequences of {0, 1} with at most one undefined element. this embedding is based on gray code and it is a topological embedding with a natural topology on {0, 1}⊥,1ω. we also define a machine called an indeterministic multihead type 2 machine which input/output sequences in {0, 1}ω⊥,1, and show that the computability notion induced on real functions through the embedding g is equivalent to the one induced by the signed digit representation and type 2 machines. we also show that basic algorithms can be expressed naturally with respect to this embedding.
a domain-theoretic semantics of lax generic functions. the semantic structure of a polymorphic calculus λm is studied. λm is defined over a hierarchical type structure, and a function in this calculus, called a generic function, can be composed from more than one lambda expression and the ways it behaves on each type are weakly related in that it lax commutes with the coercion functions defined from the subtypes to the supertypes.since laxness is intermediate between ad hocness (behaviors on each type are not related) and coherency (commuting with the coercion functions), λm has syntactic properties lying between those of calculi with ad hoc generic functions and coherent generic functions studied in tsuiki (math. struct. comput. sci. 8 (1998) 321). that is, although λm allows self application and thus is not normalizing, it does not have any unsolvable terms. for this reason, all the semantic domains are connected by mutually recursive equations and, at the same time, they do not have the least elements. we solve them by considering fibrations and expressing the equations as a recursive equation about fibrations. we also show the adequacy theorem for λm following the construction of pitts and use it to derive some syntactic properties.
computing phylogenetic roots with bounded degrees and errors is np-complete. in this paper we study the computational complexity of the following optimization problem: given a graph g = (v, e), we wish to find a tree t such that (1) the degree of each internal node of t is at least 3 and at most δ, (2) the leaves of t are exactly the elements of v, and (3) the number of errors, that is, the symmetric difference between e and {{u, v} : u, v are leaves of t and dt (u, v) ≤ k}, is as small as possible, where dt (u, v) denotes the distance between u and v in tree t. we show that this problem is np-hard for all fixed constants δ, k ≥ 3.let sδ(k) be the size of the largest clique for which an error-free tree t exists. in the course of our proof, we will determine all trees (possibly with degree 2 nodes) that approximate the (sδ(k) - 1)-clique by errors at most 2.
sequencing by hybridization with errors: handling longer sequences. sequencing by hybridization (sbh) is a method for reconstructing a dna sequence given the set of all subsequences of length k of the target sequence. this set, called the spectrum of the sequence, can be obtained from hybridization with a universal dna chip. however, the hybridization experiments are error prone, so this leads to the computational problem of reconstructing a sequence from a noisy spectrum. halperin et al. gave an algorithm for this problem with provable performance in the presence of both false positive and false negative errors. assuming, for example, that the false positive rate is small, and the probability of false negative is 0.1, the algorithm can reconstruct a random sequence of length o(20.7k) with an arbitrary small probability of failure. in this paper, we give an algorithm that can reconstruct longer sequences: under the assumptions above, our algorithm can reconstruct sequences of length o(20.942k). this bound is almost optimal as the bound for the errorless case is θ(2k).
type inference for set theory. weak set theories are employed for set-theoretic specification. we develop and explore type inference systems for such set theories.
residue polynomial systems. in this paper, we present the basic ideas of the residue polynomial system (rps), a polynomial analog of the familiar residue number systems (rns) of integer arithmetic. many of the properties of the rns are shared by the rps. the main exception is that division of polynomials in the rps is much more tractable than its integer counterpart. examples are included throughout. the underlying field of coefficients for polynomials under consideration can be the reals or the rationals, though extension to the complex field will be needed for division by irreducible quadratic factors.
investigations on the dual calculus. the dual calculus, proposed recently by wadler, is the outcome of two distinct lines of research in theoretical computer science: (a) efforts to extend the curry-howard isomorphism, established between the simply-typed lambda calculus and intuitionistic logic, to classical logic. (b) efforts to establish the tacit conjecture that call-by-value (cbv) reduction in lambda calculus is dual to call-by-name (cbn) reduction.this paper initially investigates relations of the dual calculus to other calculi, namely the simply-typed lambda calculus and the symmetric lambda calculus. moreover, church-rosser and strong normalization properties are proven for the calculus' cbv reduction relation. finally, extensions of the calculus to second-order types are briefly introduced.
a computable version of the daniell-stone theorem on integration and linear functionals. for every measure µ, the integral i: f ↦ ∫ f dµ is a linear functional on the set of real measurable functions. by the daniell-stone theorem, for every abstract integral λ: f → r on a stone vector lattice f of real functions f: ω → r there is a measure µ such that ∫ f dµ = λ(f) for all f ∈ f. in this paper we prove a computable version of this theorem.
approximate string matching with q-grams and maximal matches. we study approximate string matching in connection with two string distance functions that are computable in linear time. the first function is based on the so-called $q$-grams. an algorithm is given for the associated string matching problem that finds the locally best approximate occurences of pattern $p$, $|p|=m$, in text $t$, $|t|=n$, in time $o(n\log (m-q))$. the occurences with distance $\leq k$ can be found in time $o(n\log k)$. the other distance function is based on finding maximal common substrings and allows a form of approximate string matching in time $o(n)$. both distances give a lower bound for the edit distance (in the unit cost model), which leads to fast hybrid algorithms for the edit distance based string matching.
on the relationship between combinatorial and lp-based lower bounds for np-hard scheduling problems. enumerative approaches to solving optimization problems, such as branch and bound, require a subroutine that produces a lower bound on the value of the optimal solution. in the domain of scheduling problems the requisite lower bound has typically been derived from either the solution to a linear-programming (lp) relaxation of the problem or the solution to a combinatorial relaxation. in this paper we investigate, from a theoretical perspective, the relationship between several lp-based lower bounds and combinatorial lower bounds for three scheduling problems in which the goal is to minimize the average weighted completion time of the jobs scheduled.we establish a number of facts about the relationship between these different sorts of lower bounds, including the equivalence of certain lp-based lower bounds for these problems to combinatorial lower bounds used in successful branch-and-bound algorithms. as a result, we obtain the first worst-case analysis of the quality of the lower bounds delivered by these combinatorial relaxations.
nominal unification. we present a generalisation of first-order unification to the practically important case of equations between terms involving binding operations. a substitution of terms for variables solves such an equation if it makes the equated terms α-equivalent, i.e. equal up to renaming bound names. for the applications we have in mind, we must consider the simple, textual form of substitution in which names occurring in terms may be captured within the scope of binders upon substitution. we are able to take a "nominal" approach to binding in which bound entities are explicitly named (rather than using nameless, de bruijn-style representations) and yet get a version of this form of substitution that respects α-equivalence and possesses good algorithmic properties. we achieve this by adapting two existing ideas. the first one is terms involving explicit substitutions of names for names, except that here we only use explicit permutations (bijective substitutions). the second one is that the unification algorithm should solve not only equational problems, but also problems about the freshness of names for terms. there is a simple generalisation of classical first-order unification problems to this setting which retains the latter's pleasant properties: unification problems involving α-equivalence and freshness are decidable; and solvable problems possess most general solutions.
sound generalizations in mathematical induction. many proofs by induction diverge without a suitable generalization of the goal to be proved.the aim of the present paper is to propose a method that automatically finds a generalized form of the goal before the induction sub-goals are generated and failure begins. the method works in the case of monomorphic theories (see section 1). however, in contrast to all heuristic-based methods, our generalization method is sound: a goal is an inductive theorem if and only if its generalization is an inductive theorem. as far as we know this is the first approach that proposes sound generalizations for mathematical induction.
least and greatest fixed points in intuitionistic natural deduction. this paper is a comparative study of a number of (intensional-semantically distinct) least and greatest fixed point operators that natural-deduction proof systems for intuitionistic logics can be extended with in a proof-theoretically defendable way. eight pairs of such operators are analysed. the exposition is centred around a cube-shaped classification where each node stands for an axiomatization of one pair of operators as logical constants by intended proof and reduction rules and each arc for a proof- and reduction-preserving encoding of one pair in terms of another. the three dimensions of the cube reflect three orthogonal binary options: conventional-style vs. mendler-style, basic ("[co]iterative") vs. enhanced ("primitive-[co]recursive"), simple vs. course-of-value [co]induction. some of the axiomatizations and encodings are well known; others, however, are novel; the classification into a cube is also new. the differences between the least fixed point operators considered are illustrated on the example of the corresponding natural number types.
term rewriting restricted to ground terms. we study rewriting of ground terms. for an arbitrary term rewrite system r over a ranked alphabet σ, we restrict the rewriting relation →r to ground terms. we introduce the relation →r,g = →r ∩(tς × tς). we show that ↔r,g* = ↔r* ∩(tς × tς). we show that for a given term rewrite system r and a given ground term rewrite system s over a ranked alphabet σ it is decidable if ↔r,g* ⊆ ↔s* we show that for a given left-linear right-ground term rewrite system r over a ranked alphabet ∑ it is decidable if there is a ground term rewrite system s over σ such that →r,g* = →s*.
intersection of finitely generated congruences over term algebra. we show that it is decidable for any given ground term rewrite systems r and s if there is a ground term rewrite system u such that ↔u* = ↔r* ∩ ↔s*. if the answer is yes, then we can effectively construct such a ground term rewrite system u. in other words, for any given finitely generated congruences ρ and τ over the term algebra, it is decidable if ρ ∩ τ is a finitely generated congruence. if the answer is yes, then we can effectively construct a ground term rewrite system u such that ↔u* = ρ ∩ τ.
right-linear half-monadic term rewrite systems. we show that termination and convergence are decidable properties for right-linear half-monadic term rewrite systems.
a loopless algorithm for generating the permutations of a multiset. many combinatorial structures can be constructed from simpler components. for example, a permutation can be constructed from cycles, or a motzkin word from a dyck word and a combination. in this paper we present a constructor for combinatorial structures, called shuffle on trajectories (defined previously in a non-combinatorial context), and we show how this constructor enables us to obtain a new loopless generating algorithm for multiset permutations from similar results for simpler objects.
decidability of infinite-state timed ccp processes and first-order ltl. the ntcc process calculus is a timed concurrent constraint programming (ccp) model equipped with a first-order linear-temporal logic (ltl) for expressing process specifications. a typical behavioral observation in ccp is the strongest postcondition (sp). the ntcc sp denotes the set of all infinite output sequences that a given process can exhibit. the verification problem is then whether the sequences in the sp of a given process satisfy a given ntcc ltl formula.this paper presents new positive decidability results for timed ccp as well as for ltl. in particular, we shall prove that the following problems are decidable: (1) the sp equivalence for the so-called locally-independent ntcc fragment; unlike other fragments for which similar results have been published, this fragment can specify infinite-state systems, (2) verification for locally-independent processes and negation-free first-order formulae of the ntcc ltl, (3) implication for such formulae, (4) satisfiability for a first-order fragment of manna and pnueli's ltl. the purpose of the last result is to illustrate the applicability of ccp to well-established formalisms for concurrency.
expressiveness of matchgates. matchgates have been used to simulate classically in polynomial time assemblies of quantum gates. in this paper it is shown that every matchgate for 2-input 2-output functions has to obey a certain set of five polynomial identities. it is also shown that no matchgate can realize a nontrivial control gate for any number of inputs. on the other hand, it is proved that classical boolean formulae can be expressed as matchcircuits of polynomial size.
dynamical analysis of a class of euclidean algorithms. we develop a general framework for the analysis of algorithms of a broad euclidean type. the average-case complexity of an algorithm is seen to be related to the analytic behaviour in the complex plane of the set of elementary transformations determined by the algorithm. the methods rely on properties of transfer operators suitably adapted from dynamical systems theory. as a consequence, we obtain precise average-case analyses of algorithms for evaluating the jacobi symbol of computational number theory fame, thereby solving conjectures of bach and shallit. these methods also provide a unifying framework for the analysis of an entire class of gcd-like algorithms together with new results regarding the probable behaviour of their cost functions.
probabilistic event structures and domains. this paper studies how to adjoin probability to event structures, leading to the model of probabilistic event structures. in their simplest form, probabilistic choice is localised to cells, where conflict arises; in which case probabilistic independence coincides with causal independence. an event structure is associated with a domain--that of its configurations ordered by inclusion. in domain theory, probabilistic processes are denoted by continuous valuations on a domain. a key result of this paper is a representation theorem showing how continuous valuations on the domain of a confusion-free event structure correspond to the probabilistic event structures it supports. we explore how to extend probability to event structures which are not confusion-free via two notions of probabilistic runs of a general event structure. finally, we show how probabilistic correlation and probabilistic event structures with confusion can arise from event structures which are originally confusion-free by using morphisms to rename and hide events.
efficiently computing succinct trade-off curves. trade-off (aka pareto) curves are typically used to represent the trade-off among different objectives in multiobjective optimization problems. although trade-off curves are exponentially large for typical combinatorial optimization problems (and infinite for continuous problems), it was observed in papadimitriou and yannakakis [on the approximability of trade-offs and optimal access of web sources, in: proc. 41st ieee symp. on foundations of computer science, 2000] that there exist polynomial size ε approximations for any ε > 0, and that under certain general conditions, such approximate ε-pareto curves can be constructed in polynomial time. in this paper we seek general-purpose algorithms for the efficient approximation of trade-off curves using as few points as possible. in the case of two objectives, we present a general algorithm that efficiently computes an ε-pareto curve that uses at most 3 times the number of points of the smallest such curve; we show that no algorithm can be better than 3-competitive in this setting. if we relax ε to any ε' > ε, then we can efficiently construct an ε'-curve that uses no more points than the smallest ε-curve. with three objectives we show that no algorithm can be c-competitive for any constant c unless it is allowed to use a larger ε value. we present an algorithm that is 4-competitive for any ε' > (1 + ε)2 - 1. we explore the problem in high dimensions and give hardness proofs showing that (unless p=np) no constant approximation factor can be achieved efficiently even if we relax ε by an arbitrary constant.
on the descriptional complexity of some rewriting mechanisms regulated by context conditions. we improve the upper bounds of certain descriptional complexity measures of two types of rewriting mechanisms regulated by context conditions. we prove that scattered context grammars having two context sensing productions and five nonterminals are sufficient to generate all recursively enumerable languages and we also show that the same power can be reached by simple semi-conditional grammars having 10 conditional productions with conditions of the length two or eight conditional productions with conditions of length three. the results are based on the common idea of using the so called geffert normal forms for phrase structure grammars.
random 2-sat: results and problems. in the random 2-sat problem, we are given a set c of m disjunctions of two literals chosen at random within the ( 2n2 ) pairs of distinct literals coming from n logical variables. the basic problem is to /nd out for which values of the ratio _=m=n the disjunctions in c are almost surely simultaneously satisfiable (or almost surely not simultaneously satisfiable) as n tends to infinity. the purpose of this paper is to review the main steps in the solution of this problem, starting with the location of the asymptotic critical ratio around 8 years ago and ending with the recent almost complete solution due to bollob4as et al. thus, this paper is not a review in the usual sense of the word, i.e., it does not include all the known results about random 2-sat. we will also make a few comments concerning the behaviour of the number of satisfying assignments of random instances of 2-sat below the critical ratio, a problem relevant to theoretical physics.
the first order definability of graphs with separators via the ehrenfeucht game. we say that a first order formula φ defines a graph g if φ is true on g and false on every grap g' non-isomorphic with g. let d(g) be the minimum quantifier rank of a such formula. we prove that, if g is a tree of bounded degree or a hamiltonian (equivalently, 2-connected) outerplanar graph, then d(g) = o (log n), where n denotes the order of g. this bound is optimal up to a constant factor. if h is a constant, for connected graphs with no minor kh and degree o (√nlog n), we prove the bound d(g) = o (√n). this result applies to planar graphs and, more generally, to graphs of bounded genus.our proof techniques are based on the characterization of the quantifier rank as the length of the ehrenfeucht game on non-isomorphic graphs. we use the separator theorems to design a winning strategy for spoiler in this game.
kolmogorov complexity conditional to large integers. the main result of the paper states that the following two values coincide for any string x: limsupnk(x|n) and the minimum length of a program that producesx given all sufficiently large integers. previously it was known that the latter value is equal to the kolmogorov complexity of x relativized by 0. (all equalities hold up to a constant additive term.)
independent minimum length programs to translate between given strings. a string p is called a program to compute y given x if u(p,x)=y, where u denotes universal programming language. kolmogorov complexity k(y|x) of y relative to x is defined as minimum length of a program to compute y given x. let k(x) denote k(x|emptystring) (kolmogorov complexity of x) and let i(x:y)=k(x)+k(y)-k(x,y) (the amount of mutual information in x,y). in the present paper, we answer in the negative the following question posed in bennett et al., ieee trans. inform. theory 44 (4) (1998) 1407-1423. is it true that for any strings x,y there are independent minimum length programs p,q to translate between x,y, that is, is it true that for any x,y there are p,q such that u(p,x)=y, u(q,y)=x, the length of p is k(y|x), the length of q is k(x|y), and i(p:q)=0 (where the last three equalities hold up to an additive o(log(k(x|y)+k(y|x))) term)?
a lower bound on the competitivity of memoryless algorithms for a generalization of the cnn problem. we consider the cnn problem in arbitrary dimension, and over any metric space containing the integers. we prove that, in every dimension at least 2, no memoryless online algorithm can achieve a constant competitive ratio, under a weak symmetry constraint on the algorithm. this generalizes in several aspects the lower bounds obtained by koutsoupias and taylor [the cnn problem and other k-server variants, theoret. comput. sci. 324 (2004) 347-359] for the original problem. the proof consists in the analysis of carefully selected random walks, which appear naturally in the framework of memoryless algorithms.
a boundary result on enhanced time-varying distributed h systems with parallel computations. enhanced time-varying distributed h systems (etvdh systems) are a variant of time-varying distributed h systems (tvdh systems), which is a well-known theoretical model of dna computing based on splicing. we show that etvdh systems with 2 components, i.e., having two sets of rules which act periodically, may generate all recursively enumerable languages by simulating type-0 grammars. we also present a new approach to control the computations that can be used in other models of dna computing based on splicing.
on the computational complexity of 2-interval pattern matching problems. the focus of this paper is on the computational complexity of pattern matching problems over set of 2-intervals. these problems occur in the context of molecular biology when a structured pattern, i.e., a rna secondary structure given in the form of a 2-interval pattern, has to be found in a sequence database. we show that finding a 2-interval pattern in a set of 2-intervals is a np-complete problem even if no 2-interval of the pattern precedes the other, but can be solved in polynomial time for several interesting special cases. in particular, it is shown that the pseudo-knot free rna secondary structure case is polynomial time solvable in our 2-interval formalism. also, we investigate the computational complexity of finding the longest 2-interval pattern in a set of 2-intervals and prove several np-completeness results as well as polynomial time solvable special cases.
entailment systems for stably locally compact locales. the category scfru of stably continuous frames and preframe homomorphisms (preserving finite meets and directed joins) is dual to the karoubi envelope of a category ent whose objects are sets and whose morphisms x → y are upper closed relations between the finite powersets fx and fy. composition of these morphisms is the "cut composition" of jung et al. that interfaces disjunction in the codomains with conjunctions in the domains, and thereby relates to their multi-lingual sequent calculus. thus stably locally compact locales are represented by "entailment systems" (x, ⊢) in which ⊢, a generalization of entailment relations, is idempotent for cut composition. some constructions on stably locally compact locales are represented in terms of entailment systems: products, duality and powerlocales. relational converse provides ent with an involution, and this gives a simple treatment of the duality of stably locally compact locales. if a and b are stably continuous frames, then the internal preframe hom aψb is isomorphic to ã ⊗ b where ã is the hofmann-lawson dual. for a stably locally compact locale x, the lower powerlocale of x is shown to be the dual of the upper powerlocale of the dual of x.
a universal characterization of the double powerlocale. the double powerlocale p(x) (found by composing, in either order, the upper and lower powerlocale constructions pu and pl) is shown to be isomolphic in [locop, set] to the double exponential ssx where s is the sierpinski locale. further pu(x) and pl(x) are shown to be the subobjects of p(x) comprising, respectively, the meet semilattice and join semilattice homomorphisms. a key lemma shows that, for any locales x and y, natural transformations from sx (the presheaf loc(_ × x, s)) to sy (i.e. loc(_ × y, s)) are equivalent to dcpo morphisms (scott continuous maps) from the flame ωx to ωy. it is also shown that sx has a localic reflection in [locop, set] whose frame is the scott topology on ωx.the reasoning is constructive in the sense of topos validity.
a note on the circuit complexity of pp. in this short note, we show that for any integer k, there are languages in the complexity class pp that do not have boolean circuits of size nk.
equational rules for rewriting logic. in addition to equations and rules, we introduce equational rules that are oriented while having an equational interpretation. correspondence between operational behavior and intended semantics is guaranteed by a property of coherence, which can be checked by examination of critical pairs and linearity conditions. we present applications of this theory to three examples where the rewrite relation is interpreted, respectively, as equality, transition and deduction.
a constructive theory of point-set nearness. an axiomatic constructive development of the theory of nearness and apartness of a point and a set is introduced as a setting for topology.
on the number of hexagonal polyominoes. a combination of the refined finite lattice method and transfer matrices allows a radical increase in the computer enumeration of polyominoes on the hexagonal lattice (equivalently, site clusters on the triangular lattice), pn with n hexagons. we obtain pn for n ≤ 35. we prove that pn=τn+o(n), obtain the bounds 4.8049 ≤ τ ≤ 5.9047, and estimate that τ=5.1831478(17). finally, we provide compelling numerical evidence that the generating function σ pnzn ≈ a(z)log(1-τz), for z → (1/τ)- with a(z) holomorphic in a cut plane, estimate a(1/τ) and predict the sub-leading asymptotic behaviour, identifying a non-analytic correction-to-scaling term with exponent δ=3/2. on the basis of universality and previous numerical work we argue that the mean-square radius of gyration 〈rg2〉n of polyominoes of size n grows as n2v, with v = 0.64115(5).
efficiency of asynchronous systems, read arcs, and the mutex-problem. two solutions to the mutex-problem are compared w.r.t. their temporal efficiency. for this, a formerly developed efficiency testing for asynchronous systems is adapted to petri nets with so-called read arcs. furthermore, a compositional semantics for fair behaviour (in the sense of the progress assumption) is presented. on the one hand, this semantics is related to efficiency testing. on the other hand, it is used to specify formally what a solution to the mutex-problem is. it is shown that one of our solutions indeed satisfies this specification and that ordinary nets without read arcs cannot solve the mutex-problem.
probability theory for the brier game. the usual theory of prediction with expert advice does not differentiate between good and bad "experts": its typical results only assert that it is possible to efficiently merge not too extensivepools of experts, no matter how good or how bad they are. on the other hand, it is natural toexpect that good experts' predictions will in some way agree with the actual outcomes (e.g., theywill be accurate on the average). in this paper we show that, in the case of the brier predictiongame (also known as the square-loss game), the predictions of a good (in some weak andnatural sense) expert must satisfy the law of large numbers (both strong and weak) and the lawof the iterated logarithm; we also show that two good experts' predictions must be in asymtoticagreement. to help the reader's intuition, we give a kolmogorov-complexity interpretation ofour results. finally, we briefly discuss possible extensions of our results to more general games;the limit theorems for sequences of events in conventional probability theory correspond to thelog-loss game.
information distance and conditional complexities. c.h. bennett, p. g&aacute;cs, m. li, p.m.b. vit&aacute;nyi, and w.h. zurek have defined information distance between two strings x, y as d(x,y)= maxk (x|y), where" k(x|y) is conditional kolmogorov complexity. it is easy to see that for any string x and any integer n there is a string y such that d(x,y)=n+o(1). in this paper we prove the following (stronger) result: for any n and for any string x such that k(x)&ge;2n+o(1) there exists a string y such that both k(x|y) and k(y|x) are equal to n+o(1).
does snooping help? one of the most efficient way of improving the performance of learning algorithms is "snooping", i.e. using some information about the data to be predicted for choosing the parameters of the learning algorithm or the learning algorithm itself. allowing different degrees of snooping makes it possible to attain a better performance lossp(x) of a prediction strategy p on the given data set x. we study the "snooping curves" lx()=infk(p)lossp(x), where k(p) is the kolmogorov complexity of the prediction strategy p. we prove that every non-increasing function can be approximated with arbitrary precision by some snooping function lx. our framework is that of on-line prediction; for simplicity we assume that sequences x are binary.
induction in the timed interval calculus. the timed interval calculus, a timed-trace formalism based on set theory, is introduced. it is extended with an induction law and a unit for concatenation, which facilitates the proof of properties over trace histories. the effectiveness of the extended timed interval calculus is demonstrated via a benchmark case study, the mine pump. specifically, a safety property relating to the operation of a mine shaft is proved, based on an implementation of the mine pump and assumptions about the environment of the mine.
a property of random context picture grammars. we use random context picture grammers to generate pictures through successive refinement. the productions of such a grammar are context free, but their application is regulated by context randomly distributed in the developing picture. grammars using this relatively weak context often succeed where context-free grammars fail, e.g., in generating the typical iteration sequence of the sierpiński carpet. on the other hand, it proved possible to develop iteration theorems for three subclasses of these grammars; finding necessary conditions is problematic in the case of most models of context-free picture grammars with context-sensing ability, since they consider a variable and its context as a connected unit.we present a property of all picture sets generated with random context picture grammers, and then construct a picture set that does not belong to this class.
the customizable fault/error model for dependable distributed systems. dependability is a qualitative term referring to a system's ability to meet its service requirements in the presence of faults. the types and number of faults covered by a system play a primary role in determining the level of dependability which that system can potentially provide. given the variety and multiplicity of fault types, to simplify the design process, the system algorithm design often focuses on specific fault types, resulting in either over-optimistic (all fault permanent) or over-pessimistic (all faults malicious) dependable system designs.a more practical and realistic approach is to recognize that faults of varied severity levels and of differing occurrence probabilities may appear as combinations rather than the assumed single fault type occurrences. the ability to allow the user to select/customize a particular combination of fault types of varied severity characterizes the proposed customizable fault/error model (cfem). the cfem organizes diverse fault categories into a cohesive framework by classifying faults according to the effect they have on the required system services rather than by targeting the source of the fault condition. in this paper, we develop (a) the complete framework for the cfem fault classification, (b) the voting functions applicable under the cfem, and (c) the fundamental distributed services of consensus and convergence under the cfem on which dependable distributed functionality can be supported.
monadic second-order logic on tree-like structures. an operation m* which constructs from a given structure m a tree-like structure whose domain consists of the finite sequences of elements of m is considered. a notion of automata running on such tree-like structures is defined. it is shown that automata of this kind characterise expressive power of monadic second-order logic (msol) over tree-like structures. using this characterisation it is proved that msol theory of a tree-like structure is effectively reducible to that of the original structure. as another application of the characterisation it is shown that msol on trees of arbitrary degree is equivalent to first-order logic extended with unary least fixpoint operator.
algorithms for computing lengths of chains in integral partition lattices. let pl,n denote the partition lattice of l with n parts, ordered by hardy-littlewood-polya majorization. for any two comparable elements x and y of pl,n, we denote by m(x, y), m(x, y), f(x, y), and f(x, y), respectively, the sizes of four typical chains between x and y: the longest chain, the shortest chain, the lexicographic chain, and the counter-lexicographic chain. the covers u=(u1..., un) ≻ v =(v1...,vn) in pl,n , are of two types: n-shift (nearby shift) where vi=ui- 1, vi+1 = ui+1 + 1 for some i; and d-shift (distant shift) where ui - 1 = vi = vi+1 =...= vj = uj + 1 for some i and j. an n-shift (a d-shift) is pure if it is not a d-shift (an n-shift). we develop linear algorithms for calculating m(x, y), m(x, y), f(x, y), and f(x, y), using the leftmost pure n-shift first search, the rightmost pure d-shift first search, the leftmost n-shift first search, and the rightmost d-shift first search, respectively. those algorithms have significant applications in complexity analysis of biological sequences.
a comparison of two approaches to pseudorandomness. the concept of pseudorandomness plays an important role in cryptography. in this note, we contrast the notions of complexity-theoretic pseudorandom strings (from algorithmic information theory) and pseudorandom strings (from cryptography). for example, we show that we can easily distinguish a complexity-theoretic pseudorandom ensemble from the uniform ensemble. both notions of pseudorandom strings are uniformly unpredictable; in contrast with pseudorandom strings, complexity-theoretic pseudorandom strings are not polynomial-time unpredictable.
on the complexity of finding emerging patterns. emerging patterns have been studied as a useful type of pattern for the diagnosis and understanding of diseases based on the analysis of gene expression profiles. they are useful for capturing interactions among genes (or other biological entities), for capturing signature patterns for disease subtypes, and deriving potential disease treatment plans, etc. in this paper we study the complexity of finding emerging patterns (with the highest frequency). we first show that the problem is max snp-hard. this implies that polynomial time approximation schemes do not exist for the problem unless p = np. we then prove that for any constant δ < 1, the emerging pattern problem cannot be approximated within ratio 2logδn in polynomial time unless np ⊆ dtime[2polylog n], where n is the number of positions in a pattern.
sequential sampling techniques for algorithmic learning theory. a sequential sampling algorithm or adaptive sampling algorithm is a sampling algorithm that obtains instances sequentially one by one and determines from these instances whether it has already seen enough number of instances for achieving a given task. in this paper, we present two typical sequential sampling algorithms. by using simple estimation problems for our example, we explain when and how to use such sampling algorithms for designing adaptive learning algorithms.
function-dependent teams in eco-grammar systems. in this paper, we investigate simple eco-grammar systems with n agents. the number of agents which are active at each derivation step depends on the number of steps which have already been carried out since the beginning of the development. this dependency is expressed by a function f. for each pair of n and f, corresponding language families are defined. these families are compared with each other according to the different values of n and f.
pspace has constant-round quantum interactive proof systems. in this paper we introduce quantum interactive proof systems, which are interactive proof systems in which the prover and verifier may perform quantum computations and exchange quantum messages. it is proved that every language in pspace has a quantum interactive proof system that requires a total of only three messages to be sent between the prover and verifier and has exponentially small (one-sided) probability of error. it follows that quantum interactive proof systems are strictly more powerful than classical interactive proof systems in the constant-round case unless the polynomial time hierarchy collapses to the second level.
a new regular grammar pattern matching algorithm. this paper presents a boyer-moore type algorithm for regular grammar pattern matching, answering a variant of an open problem posed by aho (pattern matching in strings, academic press, new york, 1980, p. 342). the new algorithm handles patterns specified by regular (left linear) grammars--a generalization of the boyer-moore (single keyword) and commentz-walter (multiple keyword) algorithms.like the boyer-moore and commentz-walter algorithms, the new algorithm makes use of shift functions which can be precomputed and tabulated. the precomputation functions are derived, and it is shown that they can be obtained from commentz-walter's d1 and d2 shift functions.in most cases, the boyer-moore (respectively, commentz-walter) algorithm has greatly outperformed the knuth-morris-pratt (respectively, aho-corasick) algorithm. in practice, an earlier version of the algorithm presented in this paper also frequently outperforms the regular grammar generalization of the aho-corasick algorithm.
cell complexes, oriented matroids and digital geometry. abstract cell complexes (accs) were introduced by kovalevsky as a means of solving certain connectivity paradoxes in graph-theoretic digital topology, and to this extent provide an improved theoretical basis for image analysis. in this work we argue that accs are a very natural setting for digital geometry, to the extent that their use permits simple, almost trivial formulations of major convexity results, including caratheodory's, helly's and radon's theorems. we also discuss the relevance of oriented matroids to digital geometry.
slicing techniques for verification re-use. in this paper we discuss which properties of a formally verified component are preserved when the component is changed due to an adaption to a new use. more specifically, we will investigate when a temporal logic property of an object-z class is preserved under a modification or extension of the class with new features. to this end, we use the slicing technique from program analysis which provides us with a representation of the dependencies within the class in the form of a program dependence graph. this graph can be used to determine the effect of a change to the class's behaviour and thus to the validity of a temporal logic formula.
hypercomputation by definition. hypercomputation refers to computation surpassing the turing model, not just exceeding the von neumann architecture. algebraic constructions yield a finitely based pseudorecursive equational theory (internat. j. algebra comput. 6 (1996) 457-510). it is not recursive, although for each given number n, its equations in n variables form a recursive set. hypercomputation is therefore required for an algorithmic answer to the membership problem of such a theory. yet alfred tarski declared these theories to be decidable. the dilemma of a decidable but not recursive set presents an impasse to standard computability theory. one way to break the impasse is to predicate that the theory is computable--in other words, hypercomputation by definition.
learning to score final positions in the game of go. this article investigates the application of machine-learning techniques for the task of scoring final positions in the game of go. neural network classifiers are trained to classify life and death from labelled 9 × 9 game records. the performance is compared to standard classifiers from statistical pattern recognition. a recursive framework for classification is used to improve performance iteratively. using a maximum of four iterations our cascaded scoring architecture (csa*) scores 98.9% of the positions correctly. nearly all incorrectly scored positions are recognised (they can be corrected by a human operator). by providing reliable score information csa* opens the large source of go knowledge implicitly available in human game records for automatic extraction. it thus paves the way for a successful application of machine learning in go.
sublogarithmic ambiguity. context-free grammars and languages with infinite ambiguity can be distinguished by the growth rate of their ambiguity with respect to the length of the words. so far the least growth rate known for a divergent inherent ambiguity function was logarithmic. roughly speaking we show that it is possible to stay below any computable function. more precisely let f : n → n be an arbitrary computable divergent total non-decreasing function. then there is a context-free language l with a divergent inherent ambiguity function g below f, i.e., g(n) ≤ f(n) for each n ∈ n. this result is an immediate consequence of two other results which are of independent interest. the first result says that there is a linear context-free grammar g with so called unambiguous turn position whose ambiguity function is below f. the second one states that any ambiguity function of a cycle-free context-free grammar is an inherent ambiguity function of some context-free language.
characterizing the super-turing computing power and efficiency of classical fuzzy turing machines. the first attempts concerning formalization of the notion of fuzzy algorithms in terms of turing machines are dated in late 1960s when this notion was introduced by zadeh. recently, it has been observed that corresponding so-called classical fuzzy turing machines can solve undecidable problems. in this paper we will give exact recursion-theoretical characterization of the computational power of this kind of fuzzy turing machines. namely, we will show that fuzzy languages accepted by these machines with a computable t-norm correspond exactly to the union σ10 ∪ π10 of recursively enumerable languages and their complements. moreover, we will show that the class of polynomially time-bounded computations of such machines coincides with the union np ∪ co-np of complexity classes from the first level of the polynomial hierarchy.
normal forms and syntactic completeness proofs for functional independencies. we prove normal form theorems of a complete axiom system for the inference of functional dependencies and independencies in relational databases. we also show that all proofs in our system have a normal form where the application of independency rules is limited to three levels. our normal form results in a faster proof-search engine in deriving consequences of functional independencies. as a result, we get a new construction of an armstrong relation for a given set of functional dependencies. it is also shown that an armstrong relation for a set of functional dependencies and independencies do not exist in general, and this generalizes the same result valid under the closed-world assumption. copyright 2001 elsevier science b.v.
idempotent and co-idempotent stack filters and min-max operators. viewing the elements of rs as images f with pixels i ∈ s of grey-scale value f(i) motivates the study of certain nonlinear operators φ : rs → rs. for translation invariant φ (called stack filters in the signal processing literature) we derive the first necessary and sufficient condition for idempotency which can be tested in polynomial time. various related properties can be tested in polynomial time as well, and many results still apply when the linear lattice (r, ≤ ) is replaced by an arbitrary distributive lattice (r, ≤), or when the condition of translation invariance is dropped. although the main application is in nonlinear image processing several other fields will be touched upon.
a new algorithm for optimal 2-constraint satisfaction and its implications. we present a novel method for exactly solving (in fact, counting solutions to) general constraint satisfaction optimization with at most two variables per constraint (e.g. max-2-csp and min-2-csp), which gives the first exponential improvement over the trivial algorithm. more precisely, the runtime bound is a constant factor improvement in the base of the exponent: the algorithm can count the number of optima in max-2-sat and max-cut instances in o(m32ωn/3) time, where ω < 2.376 is the matrix product exponent over a ring. when the constraints have arbitrary weights, there is a (1 + ε)-approximation with roughly the same runtime, modulo polynomial factors. our construction shows that improvement in the runtime exponent of either k-clique solution (even when k = 3) or matrix multiplication over gf(2) would improve the runtime exponent for solving 2-csp optimization.our approach also yields connections between the complexity of some (polynomial time) high-dimensional search problems and some np-hard problems. for example, if there are sufficiently faster algorithms for computing the diameter of n points in l1, then there is an (2 - ε)n algorithm for max-lin. these results may be construed as either lower bounds on the high-dimensional problems, or hope that better algorithms exist for the corresponding hard problems.
an effective two-level proof-number search algorithm. the paper presents a new proof-number (pn) search algorithm, called pds-pn. it is a two-level search (like pn2), which performs at the first level a depth-first proof-number and disproof-number search (pds), and at the second level a best-first pn search. hence, pds-pn selectively exploits the power of both pn2 and pds. experiments in the domain of lines of action are performed. they show that within an acceptable time frame pds-pn is more effective for really hard endgame positions than αβ and any other pn-search algorithm.
a formal approach to object-oriented software engineering. we show how formal specifications can be integrated into one of the current pragmatic object-oriented software development methods. jacobson's "object-oriented software engineering" process is combined with object-oriented algebraic specifications by extending object and interaction diagrams with formal annotations. the specifications are based on meseguer's rewriting logic and are written in a meta-level extension of the language maude by process expressions. as a result any such diagram can be associated with a formal specification, proof obligations ensuring invariant properties can be automatically generated, and the refinement relations between documents at different abstraction levels can be formally stated and proved.
explicit fusions. we introduce explicit fusions of names. an explicit fusion is a process that exists concurrently with the rest of the system and enables two names to be used interchangeably. explicit fusions provide a small-step account of reaction in process calculi such as the pi calculus and the fusion calculus. in this respect they are similar to the explicit substitutions of abadi, cardelli and curien, which do the same for the lambda calculus. in this paper, we give a technical foundation for explicit fusions. we present the pi-f calculus, a simple process calculus with explicit fusions, and define a strong bisimulation congruence. we study the embeddings of the fusion calculus and the pi calculus. the former is fully abstract with respect to bisimulation.
a construction method for optimally universal hash families and its consequences for the existence of rbibds. we introduce a method for constructing optimally universal hash families and equivalently rbibds. as a consequence of our construction we obtain minimal optimally universal hash families, if the cardinalities of the universe and the range are powers of the same prime. a corollary of this result is that the necessary conditions for the existence of an rbibd with parameters v, k, λ, namely v ≡ 0 (mod k) and λ(v - 1) ≡ 0(mod k - 1), are sufficient, if v and k are powers of the same prime. as an application of our construction, we show that the k-maxcut algorithm of hofmeister and lefmann [a combinatorial design approach to maxcut, random struct. algorithms 9 (1996) 163-173] can be implemented such that it has a polynomial running time, in the case that the number of vertices and k are powers of the same prime.
seventeen lines and one-hundred-and-one points. we investigate a curious problem from additive number theory: given two positive integers s and q, does there exist a sequence of positive integers that add up to s and whose squares add up to q? we show that this problem can be solved in time polynomially bounded in the logarithms of s and q.as a consequence, also the following question can be answered in polynomial time: for given numbers n and m, do there exist n lines in the euclidean plane with exactly m points of intersection?
quantum communication and complexity. in the setting of communication complexity, two distributed parties want to compute a function depending on both their inputs, using as little communication as possible. the required communication can sometimes be significantly lowered if we allow the parties the use of quantum communication. we survey the main results of the young area of quantum communication complexity; its relation to teleportation and dense coding, the main examples of fast quantum communication protocols, lower bounds, and some applications.
counting the number of games. we give upper and lower bounds on g(n) equal to the number of games born by day n. in particular, we give an upper bound of g(n + 1) ≤ g(n) + 2g(n) + 2. for the lower bound, for all α < 1, for sufficiently large n, g(n + 1) ≥ 2g(n)z.
csp, partial automata, and coalgebras. the paper presents a first reconstruction of hoare's theory of csp in terms of partial automata and related coalgebras. we show that the concepts of processes in hoare (communicating sequential processes, prentice-hall, englewood cliffs, nj, 1985) are strongly related to the concepts of states for special, namely, final partial automata. moreover, we show how the deterministic and nondeterministic operations in hoare (1985) can be interpreted in a compatible way by constructions on the semantical level of automata. based on this, we are able to interpret finite process expressions as representing finite partial automata with designated initial states. in such a way we provide a new method for solving recursive process equations which is based on the concept of final automata. the coalgebraic reconstruction of csp allows us to use coinduction as a new proof principle. to make evident the usefulness of this principle we prove some example laws from hoare (1985).
optimal three-dimensional orthogonal graph drawing in the general position model. let g be a graph with maximum degree at most six. a three-dimensional orthogonal drawing of g positions the vertices at grid-points in the three-dimensional orthogonal grid, and routes edges along grid lines such that edge routes only intersect at common end-vertices. in this paper, we consider three-dimensional orthogonal drawings in the general position model; here no two vertices are in a common grid-plane. minimising the number of bends in an orthogonal drawing is an important aesthetic criterion, and is np-hard for general position drawings. we present an algorithm for producing general position drawings with an average of at most 2 2/7 bends per edge. this result is the best known upper bound on the number of bends in three-dimensional orthogonal drawings, and is optimal for general position drawings of k7. the same algorithm produces drawings with two bends per edge for graphs with maximum degree at most five; this is the only known non-trivial class of graphs admitting two-bend drawings.
an optical model of computation. we prove computability and complexity results for an original model of computation called the continuous space machine. our model is inspired by the theory of fourier optics. we prove our model can simulate analog recurrent neural networks, thus establishing a lower bound on its computational power. we also define a θ(log2n) unordered search algorithm with our model.
on the final sequence of a finitary set functor. a standard construction of the final coalgebra of an endofunctor involves defining a chain of iterates, starting at the final object of the underlying category and successively applying the functor. in this paper we show that, for a finitary set functor, this construction always yields a final coalgebra in ω2 = ω + ω steps.
some properties of ising automata. in this work, we shall present some arithmetical and topological properties of ising automata. more precisely, we shall study many different notions, such as faithful and strictly faithful automata, factor aud product automata, irreducible and weakly irreducible automata, prime automata, homogeneous automata, minimal automata, invertible automata, etc., and discuss their related properties. we shall also define and study three different topologies over the set of all minimal automata, and discuss the topological closure property of automatic sequences. as application, we shall use the obtained results to give a somewhat detailed analysis of ising automata.
minimum connected dominating sets and maximal independent sets in unit disk graphs. in ad hoc wireless networks, a connected dominating set can be used as a virtual backbone to improve the performance. many constructions for approximating the minimum connected dominating set are based on the construction of a maximal independent set. the relation between the size mis(g) of a maximum independent set and the size cds(g) of a minimum connected dominating set in the same graph g plays an important role in establishing the performance ratio of those approximation algorithms. previously, it is known that mis(g) ≤ 4ċcds(g) + 1 for all unit disk graphs g. in this paper, we improve it by showing mis(g) ≤ 3.8ċcds(g) + 1.2.
majority-based reversible logic gates. reversible logic plays an important role in the synthesis of circuits for quantum computing. in this paper, we introduce families of reversible gates based on the majority boolean function (mbf) and we prove their properties in reversible circuit synthesis. these gates can be used to synthesize reversible circuits of minimum "scratchpad register width" for arbitrary reversible functions. we show that, given a mbf f with 2k + 1 inputs, f can be implemented by a reversible logic gate with 2k + 1 inputs and 2k + 1 outputs, i.e., without any constant inputs. we also demonstrate new gates from this family with very efficient quantum realizations for majority-based applications. they can be used to synthesize any reversible function of the same width in conjunction with inverters and feynman (2-qubit controlled-not) gates. the gate universality problem is formulated in terms of elementary group theory and solved using the algebraic software gap.
the approximability of the weighted hamiltonian path completion problem on a tree. given a graph, the hamiltonian path completion problem is to find an augmenting edge set such that the augmented graph has a hamiltonian path. in this paper, we show that the hamiltonian path completion problem will unlikely have any constant ratio approximation algorithm unless np = p. this problem remains hard to approximate even when the given subgraph is a tree. moreover, if the edge weights are restricted to be either 1 or 2, the hamiltonian path completion problem on a tree is still np-hard. then it is observed that this problem is strongly np-hard, so it does not have any fully polynomial-time approximation scheme (fptas) unless np = p when the given tree is a k-tree, we give an approximation algorithm with performance ratio 1.5.
on the time-space tradeoff for sorting with linear queries. extending a result of borodin, et al., we show that any branching program using linear queries " $\sum_{i} {\lambda}_i {x_i}: c$ " to sort n numbers $x_1$,$x_2$,...,$x_n$ must satisfy the time-space tradeoff relation ts = $\omega (n_2)$. the same relation is also shown to be true for branching programs that use queries " min r = ? " where r is any subset of {$x_1$,$x_2$,...,$x_n$}.
completeness of type assignment systems with intersection, union, and type quantifiers. this paper develops type assignment systems with intersection and union types, and type quantifiers. we show that the known system for these types is not semantically complete. however, the following two hold for a certain class of typing statements, called stable statements, which include all statements without type quantifier: (1) the validity of stable statements for kripke models is equivalent to that for standard models, (2) if we add two axioms expressing the distributive laws of intersection over union and existential-type quantifier, then the resulting system is complete for kripke models. as a consequence, the known system with the axioms for distributive laws is complete for standard models if we restrict statements to stable ones. all the results are obtained in a systematic way with sequent-style formulations of type assignment and the cut-elimination property for them.
specification languages in algebraic compilers. algebraic compilers provide a powerful and convenient mechanism for specifying language translators. with each source language operation one associates a computation for constructing its target language image; these associated computations, called derived operations, are expressed in terms of operations from the target language. sometimes the target language is not powerful enough to specify the required translation and one may then need to extend the target language algebras with more computationally expressive operations or elements. a better solution is to package these extensions in a specification language which can be composed with the target language to ensure that all operations and elements needed or desired for performing the translation are provided. in the example in this paper, we show how imperative and functional specification languages can be composed with a target language to implement a temporal logic model checker as an algebraic compiler and show how specification languages can be seen as components to be combined with a source and target language to generate an algebraic compiler.
approximation schemes for knapsack problems with shelf divisions. given a knapsack of size k, non-negative values d and δ, and a set s of items, each item e ∈ s with size se and value ve, we define a shelf as a subset of items packed inside a bin with total items size at most δ. two subsequent shelves must be separated by a shelf divisor of size d. the size of a shelf is the total size of its items plus the size of the shelf divisor. the shelf-knapsack problem (sk) is to find a subset s' ⊆ s partitioned into shelves with total shelves size at most k and maximum value. the class constrained shelf knapsack (ccsk) is a generalization of the problem sk, where each item in s has a class and each shelf in the solution must have only items of the same class. we present approximation schemes for the sk and the ccsk problems. to our knowledge, these are the first approximation results where shelves of non-null size are used in knapsack problems.
power domination in block graphs. the problem of monitoring an electric power system by placing as few measurement devices in the system as possible is closely related to the well-known domination problem in graphs. in 2002, haynes et al. considered the graph theoretical representation of this problem as a variation of the domination problem. they defined a set s to be a power dominating set of a graph if every vertex and every edge in the system is monitored by the set s (following a set of rules for power system monitoring). the power domination number γp(g) of a graph g is the minimum cardinality of a power dominating set of g. this problem was proved np-complete even when restricted to bipartite graphs and chordal graphs. in this paper, we present a linear time algorithm for solving the power domination problem in block graphs. as an application of the algorithm, we establish a sharp upper bound for power domination number in block graphs and characterize the extremal graphs.
minimality and separation results on asynchronous mobile processes - representability theorems by concurrent combinators. in honda and yoshida (tacs'94, lecture notes in computer science, vol. 789, springer, berlin, 1994, pp. 786-805; popl'94, acm press, new york, 1994, pp. 348-360) we presented a theory of concurrent combinators for the asynchronous monadic calculus without match or summation operator. the system of concurrent combinators is based on a finite number of atoms and fixed interaction rules, but is as expressive as the original calculus, so that it can represent diverse interaction structures, including polyadic synchronous name passing and input guarded summations. the present paper shows that each of the five basic combinators introduced in honda and yoshida (popl'94, acm press, new york, 1994, pp. 348-360) is indispensable to represent the whole computation, i.e. if one of the combinators is missing, we can no longer express the original calculus up to semantic equalities. expressive power of several interesting subsystems of the asynchronous calculus is also measured by using appropriate subsets of the combinators and their variants. finally, as an application of the main result, we show there is no semantically sound encoding of the calculus into its proper subsystem under a certain condition.
many hard examples in exact phase transitions. this paper analyzes the resolution complexity of two random constraint satisfaction problem (csp) models (i.e. model rb/rd) for which we can establish the existence of phase transitions and identify the threshold points exactly. by encoding csps into cnf formulas, it is proved that almost all instances of model rb/rd have no tree-like resolution proofs of less than exponential size. thus, we not only introduce new families of csps and cnf formulas hard to solve, which can be useful in the experimental evaluation of csp and sat algorithms, but also propose models with both many hard instances and exact phase transitions. finally, conclusions are presented, as well as a detailed comparison of model rb/rd with the hamiltonian cycle problem and random 3-sat, which, respectively, exhibit three different kinds of phase transition behavior in np-complete problems.
exact matching of rna secondary structure patterns. many rna structures are assembled from a collection of rna motifs, which appear repeatedly and in various combinations. identification of rna structural motifs will enhance our understanding of rna structures and functions. searching for secondary structural patterns in sequence databases is the basic technique and fundamental problem for extracting and identifying such motifs. a number of algorithms and programs have been developed for this purpose.in this paper, we adopt a representation of secondary structure called secondary expressions, and present two algorithms for finding all exact matches of a given secondary expression.
interpolation functor and computability. computability of banach spaces is discussed. a compatible relation is shown to hold between the complex interpolation spaces of calderón (studia math. 24 (1964) 113) and the computability structures introduced by pour-el and richards (computability in analysis and physics, springer, berlin, 1989). namely, it is verified that calderón's original construction of the complex interpolation functor is valid in the context of computability if a mild effective separability condition is fulfilled by a compatible couple of banach spaces.
weighted connected k-domination and weighted k-dominating clique in distance-hereditary graphs. a graph is distance-hereditary if the distance between any two vertices in a connected induced subgraph is the same as in the original graph. this paper presents efficient algorithms for solving the weighted connected k-domination and the weighted k-dominating clique problems in distance-hereditary graphs.
graph colourings and partitions. in this paper we have investigated mainly the three colouring parameters of a graph g, viz., the chromatic number, the achromatic number and the pseudoachromatic number. the importance of their study in connection with the computational complexity, partitions, algebra, projective plane geometry and analysis were briefly surveyed. some new results were found along these directions. we have rede0ned the concept of perfect graphs in terms of these parameters and obtained a few results. some open problems are raised.
similarity between preferential models. the notion of bisimulation is an important concept in process algebra and modern modal logic. this paper explores the notion of b-similarity, which is a kind of bisimulation between preferential models. we characterize the equivalence of preferential models in terms of b-similarity. however, this result is applicable only for preferential models of finite depth. to overcome this defect, we introduce a weak notion of similarity called m-similarity, and obtain a result corresponding to hennessy-milner theorem and keisler-shelah's isomorphism theorem in modal logic and first-order logic, respectively. as its application, we investigate the expressive power of boolean combinations of conditional assertions (bca, for short), and prove that bcas are the fragments of first-order language preserved under m-similarity. moreover, we obtain a characterization for elementary classes defined by bcas. a notion of first-order translation originating from modal logic plays an important role in this paper. in order to illustrate that first-order translation is a powerful tool in the study of nonmonotonic logic, some model-theoretic results about preferential models are proved based on this translation.
resource-sharing system scheduling and circular chromatic number. a graph g is used as a model for a resource sharing system, where each vertex represents a process and an edge joining two vertices means that the corresponding processes share a resource. a scheduling of g is a mapping f : {1, 2, 3, ... } → 2v(g), where f(i) consists of processes that are operating at round i. the rate of f is defined as rate(f) = lim supn → ∞ σi=1n|f(i)|/n|v(g)|, which is the average fraction of operating processes at each round. a scheduling is fair if adjacent vertices alternate their turns in operating. the operating rate γ*(g) of g is the maximum rate of a fair scheduling. fair schedulings of a graph was first studied by barbosa and gafni. they introduced the method of "scheduling by edge reversal" which derives a fair scheduling through an acyclic orientation. through scheduling by edge reversal, barbosa and gafni related γ* (g) to the structure of acyclic orientations of g. we point out that this relation implies that γ* (g) is equal to the reciprocal of the circular chromatic number of g. both circular coloring and scheduling by edge reversal have been studied extensively in the past decade. the former by graph theorists, and the latter by computer scientists. however, it seems that neither side knew the existence of the other. this paper intends to build a connection between the two sides. we show that certain open problems concerning scheduling by edge reversal are indeed solved under the language of circular coloring. in the study of fair scheduling, barbosa and gafni defined a variation of multiple coloring of graphs: the interleaved p-color, q-tuple colorings. we formulate the interleaved coloring as a graph homomorphism problem. in the study of circular chromatic number, bondy and hell defined (p, q)-colorings and also formulated it as a graph homomorphism problem. we prove that the target graph for the interleaved p-color, q-tuple coloring and the target graph of (p, q)-coloring are homomorphically equivalent. this gives another proof of the fact that γ* (g) = 1/χc (g). moreover, the proof gives an explicit formula which deduces an optimal circular coloring of g from an optimal interleaved coloring of g, and vice versa. this paper also introduces two other schedulings of a graph, the weakly fair scheduling and the strongly fair scheduling. it is proved that the rate of an optimal strongly fair scheduling of a graph g is also equal to the reciprocal of the circular chromatic number of g, and the rate of an optimal weakly fair scheduling of g is equal to the reciprocal of the fractional chromatic number of g. barbosa and gafni presented an algorithm that determines the rate γo(w) of the scheduling induced by an acyclic orientation ω of g. by using karp's minimum mean cycle algorithm, we give a faster algorithm to calculate γo(w).
resource bounded immunity and simplicity. revisiting the 30-years-old notions of resource-bounded immunity and simplicity, we investigate the structural characteristics of various immunity notions: strong immunity, almost immunity, and hyperimmunity as well as their corresponding simplicity notions. we also study limited immunity and simplicity, called k-immunity and feasible k-immunity, and their simplicity notions. finally, we propose the k-immune hypothesis as a working hypothesis that guarantees the existence of simple sets in np.
hypothesis finding based on upward refinement of residue hypotheses. for given logical formulae b and e such that b n e, hypothesis finding means the generation of a formula h such that b ∧ h ⊧ e. hypothesis finding constitutes a basic technique for fields of inference, like inductive inference and knowledge discovery. in order to put various hypothesis finding methods proposed previously on one general ground, we use upward refinement and residue hypotheses. we show that their combination is a complete method for solving any hypothesis finding problem in clausal logic. we extend the relative subsumption relation, and show that some hypothesis finding methods previously presented can be regarded as finding hypotheses which subsume examples relative to a given background theory. noting that the weakening rule may make hypothesis finding difficult to solve, we propose restricting this rule either to the inverse of resolution or to that of subsumption. we also note that this work is related to relevant logic.
on the intercluster distance of a tree metric. for two vertex clusters of a tree metric, we show that the sum of the average intracluster distances is always less than or equal to twice of the average intercluster distance. we show the feature in a more general form of weighted distance. this feature provides a 2-approximation algorithm for the minimum average intercluster distance spanning tree problem, which is a generalization of the minimum routing cost spanning tree or minimum average distance spanning tree problem. the results in this paper can be further generalized to more than two clusters.
on-line scheduling mesh jobs with dependencies. we study an on-line problem of scheduling parallel jobs on two-dimensional meshes. parallel jobs arrive dynamically according to the dependencies between them, which are unknown before the jobs appear. each job may need more than one processor simultaneously and is required to be scheduled on a submesh of the processors which are located on a two-dimensional mesh, i.e., a job must be scheduled on a rectangle of given dimensions. the objective is to minimize the maximum completion time (makespan). we deal with a uet job system, in which all job processing times are equal. we show a lower bound of 3.859 and present a 5.25-competitive algorithm. it significantly improves a previous lower bound of 3.25 and a previous upper bound of 46/7. we consider also the rotated two-dimensional mesh, in which the parallel jobs can be rotated and the rotation of all the jobs is feasible. a lower bound of 3.535 is proven and an on-line algorithm with competitive ratio of at most 4.25 is derived.
global exponential convergence of recurrent neural networks with variable delays. convergence analysis of recurrent neural networks is an important research direction in the field of neural networks. novel methods to study the global exponential convergence of recurrent neural networks with variable delays are proposed. a condition for global exponential stability, which is independent of the delays, is derived by the method of delayed inequalities analysis. another condition for global exponential stability, which depends on the delays, is obtained via the method of constructing a suitable and interesting lyapunov functional.
classifying regular languages by a split game. in this paper, we introduce the split game, a variant of the ehrenfeucht-fraisse game from logic, which is useful for analyzing the expressive power of classes of generalized regular expressions. an extension of the split game to generalized @w-regular expressions is also established. to gain insight into how the split game can be applied to attack the long-standing generalized star height 2 problem, we propose and solve the omega power problem, a similar but tractable problem in the context of @w-languages. namely we show that omega powers, together with boolean combinations and concatenations, are not sufficient to express the class of @w-regular languages.
authenticated key agreement in dynamic peer groups. many group-oriented applications in distributed systems, such as teleconferencing and cooperative works, involve dynamic peer groups. in order to secure communications in dynamic peer groups, authenticated key agreement protocols are required. in this paper, we propose a new authenticated key agreement protocol, composed of a basic protocol and a dynamic protocol, for dynamic peer groups. with the basic protocol, a secret group key can be achieved in a peer group via group handshake, secret broadcast, key derivation and key confirmation phases. by the dynamic protocol, a new secret group key can be reached when member or mass join, group mergence, group division, member or mass quit occurs in a dynamic peer group. security analysis shows that our protocol offers explicit group key authentication and prevents from both passive and active attacks. in our basic protocol, each group member equally contributes to the secret group key in parallel and guarantees key freshness.
k-partitioning problems with partition matroid constraint. in this paper, we consider the k-partitioning problems with partition matroid constraint and present an algorithm called the layered lpt algorithm. with the objective of minimizing the maximum load, we show that the layered lpt algorithm has a tight worst case ratio of 2-1/m. with the objective of maximizing the minimum load, we show that the layered lpt algorithm has a tight worst case ratio of 1/m for the general case and, with certain conditions, the worst ratio can be improved to m/(2m-1) for the general k case and to (m-1)/(2m-3) for the k=3 case.
a cost-effective estimation of uncaught exceptions in standard ml programs. we present a static analysis that detects potential runtime exceptions that are raised and never handled inside standard ml (sml) programs. this analysis will predict abrupt termination of sml programs, which is smls only one "safety hole". even though sml program's control flow and exception flow are in general mutually dependent, analyzing the two flows are safely decoupled. program's control flow is firstly estimated by simple case analysis of call expressions. using this call-graph information, program's exception flow is derived as set constraints, whose least model is our analysis result. both of these two analyses are proven safe and the reasons behind each design decision are discussed. our implementation of this analysis has been applied to realistic sml programs and shows a promising cost-accuracy performance. for the ml-lex program, for example, the analysis takes 1.36 s and it reports 3 may-uncaught exceptions, which are exactly the exceptions that can really escape. our final goal is to make the analysis overhead less than 10% of the compilation time (compiling the ml-lex takes 6-7 s) and to analyze modules in isolation. copyright 2002 elsevier science b.v.
msol partitioning problems on graphs of bounded treewidth and clique-width. we show that a class of vertex partitioning problems that can be expressed in monadic second order logic (msol) are polynomials on graphs of bounded clique-width. this class includes coloring, h-free coloring, domatic number and partition into perfect graphs. moreover we show that a class of vertex and edge partitioning problems are polynomials on graphs of bounded treewidth.
exchange market equilibria with leontief's utility: freedom of pricing leads to rationality. this paper studies the equilibrium property and algorithmic complexity of the exchange market equilibrium problem with concave piecewise linear functions, which include linear and leontief's utility functions as special cases. we show that the fisher model again reduces to the weighted analytic center problem, and the same linear programming complexity bound applies to computing its equilibrium. however, the story for the arrow-debreu model with leontief's utility becomes quite different. we show that, for the first time, solving this class of leontief exchange economies is equivalent to solving a linear complementarity problem whose algorithmic complexity is finite but not polynomially bounded.
a sound and complete procedure for a general logic program in non-floundering derivations with respect to the 3-valued stable model semantics. this paper presents a sound and complete procedure with respect to the 3-valued stable model semantics. the procedure is regarded as an extension of eshghi and kowalski abductive proof procedure, involving finite or countably infinite sld resolution, as well as finite or countably infinite negative recursion caused by negation as failure. the procedure makes use of the set of negative literals (the set of abducibles) for the negation as failure to be implemented. the set of abducibles is not only applicable to the extraction of explanations for abduction as in kakas et al. (j. logic comput. 2 (1992) 719-770) but also specified for what stable model is now computed in the procedure, because a 3-valued stable model is not always the least (that is, the well-founded model). the procedure also contains nondeterminism in the choices of what ground negative literals are used for negation as failure. by the assumptions of some adequate choices, the procedure is well-defined inductively. copyright 2001 elsevier science b.v.
bisimulation indexes and their applications. bisimulation expresses the equivalence of processes whose external actions are identical. sometimes we may meet two processes which are not exactly bisimilar but more or less bisimilar in the sense that whenever a process makes an action the other can make an action different from but very similar to the action performed by the first one. to describe this kind of looser bisimulations we propose the concept of bisimulation index in a labelled transition system and give its various properties, especially those properties related to the operations of transition systems. furthermore, we establish a modal logical characterization of bisimulation indexes. this characterization is a generalization of hennessy-milner logic. we study strong and weak bisimulation indexes in the basic asynchronous process calculus, and some of their fundamental properties are derived. bisimulation indexes are not substitutive under composition. to overcome this defect we introduce an approximate communication rule to replace the original rule in process calculus. this enables us to recover some useful properties of composition with respect to bisimulation indexes. finally, we present three examples in timed ccs and real time acp to demonstrate the usage of bisimulation indexes in the analysis of real time systems. these examples show that bisimulation indexes are suitable formal tools for describing approximate implementations of real time systems.
additive models of probabilistic processes. we propose a new model of probabilistic processes. in this model, a probability is assigned to the action of a prefix and a probability distribution is assigned to the components of a parallel composition. in addition, the probability of a transition of a probabilistic summation is evaluated as the sum of the probabilities of the same transition of summands multiplied by the probabilities associated to them in the summation. the concepts of strong bisimulation degree and (weak) bisimulation degree are introduced. these notions provide us with continuous spectra of strong bisimilarities, (weak) bisimilarities and observation congruences which equate probabilistic processes with different degrees of belief. various equational laws of probabilistic processes with respect to these equivalence relations are presented and substitutivities of these equivalence relations under various combinators are established.
quantum versus deterministic counter automata. this paper focuses on quantum analogues of various models of counter automata, and almost completely proves the relation between the classes of languages recognizable by bounded error quantum ones and classical deterministic ones in every model of counter automata. it is proved that (i) there are languages that can be recognized by two-way quantum one-counter automata with bounded error, but cannot be recognized by two-way deterministic one-counter automata, (ii) under some reasonable restriction, every language that can be recognized by two-way deterministic one-counter automata can also be recognized by two-way reversible one-counter automata (and hence by bounded error two-way quantum one-counter automata), and (iii) for any fixed k, quantum ones and deterministic ones are incomparable in one-way k-counter automata.
a theory of computation based on quantum logic (i). the (meta)logic underlying classical theory of computation is boolean (two-valued) logic. quantum logic was proposed by birkhoff and von neumann as a logic of quantum mechanics more than 60 years ago. it is currently understood as a logic whose truth values are taken from an orthomodular lattice. the major difference between boolean logic and quantum logic is that the latter does not enjoy distributivity in general. the rapid development of quantum computation in recent years stimulates us to establish a theory of computation based on quantum logic. the present paper is the first step toward such a new theory and it focuses on the simplest models of computation, namely finite automata. we introduce the notion of orthomodular lattice-valued (quantum) automaton. various properties of automata are carefully reexamined in the framework of quantum logic by employing an approach of semantic analysis. we define the class of regular languages accepted by orthomodular lattice-valued automata. the acceptance abilities of orthomodular lattice-valued nondeterministic automata and their various modifications (such as deterministic automata and automata with ε-moves) are compared. the closure properties of orthomodular lattice-valued regular languages are derived. the kleene theorem about equivalence of regular expressions and finite automata is generalized into quantum logic. we also present a pumping lemma for orthomodular lattice-valued regular languages. it is found that the universal validity of many properties (for example, the kleene theorem, the equivalence of deterministic and nondeterministic automata) of automata depend heavily upon the distributivity of the underlying logic. this indicates that these properties does not universally hold in the realm of quantum logic. on the other hand, we show that a local validity of them can be recovered by imposing a certain commutativity to the (atomic) statements about the automata under consideration. this reveals an essential difference between the classical theory of computation and the computation theory based on quantum logic.
one-way probabilistic reversible and quantum one-counter automata. kravtsev introduced 1-way quantum 1-counter automata (1q1cas), and showed that several non-context-free languages can be recognized by bounded error 1q1cas. in this paper, we first show that all of these non-context-free languages can be also recognized by bounded error 1pr1cas (and so 1q1cas). moreover, the accepting probability of each of these 1pr1cas is strictly greater than, or at least equal to, that of corresponding kravtsev's original 1q1ca. second, we show that there exists a bounded error 1pr1ca (and so 1q1ca) which recognizes {a1na2n...akn}, for each k ≥ 2. we also show that, in a quantum case, we can improve the accepting probability in a strict sense by using quantum interference. third, we state the relation between 1-way deterministic 1-counter automata (1d1cas) and 1q1cas. on one hand, all of above mentioned languages cannot be recognized by 1d1cas because they are non-context-free. on the other hand, we show that a regular language {{a, b}*a} cannot be recognized by bounded error 1q1cas.
recursive equations in higher-order process calculi. regarding behaviour equivalence in higher-order process calculi, sangiorgi (inform. and comput. 131 (1996) 141) and thomsen (inform. and comput. 116 (1995) 38) introduced context and higher-order bisimulations, respectively. in this paper, uniqueness of solutions of equations with respect to strong context and higher-order bisimilarities and compatibility of strong context and higher-order bisimilarities with recursive definitions are shown. copyright 2001 elsevier science b.v.
polynomial-time identification of very simple grammars from positive data. this paper concerns a subclass of simple deterministic grammars, called very simple grammars, and studies the problem of identifying the subclass in the limit from positive data. the class of very simple languages forms a proper subclass of simple deterministic languages and is incomparable to the class of regular languages. this class of languages is also known as the class of left szilard languages of context-free grammars.after providing some properties of very simple languages, we show that the class of very simple grammars is polynomial-time identifiable in the limit from positive data in the following sense. that is, we show that there effectively exists an algorithm that, given a target very simple grammar g* over alphabet σ, identifies a very simple grammar g equivalent to g* in the limit from positive data, satisfying the property that the time for updating a conjecture is bounded by o(m), and the total number of prediction errors made by the algorithm is bounded by o(n), where n is the size of g*, m = max{n|σ|+1, |σ|3} and n is the total length of all positive data provided.
graphical condensation of plane graphs: a combinatorial approach. the method of graphical vertex-condensation for enumerating perfect matchings of plane bipartite graph was found by propp [generalized domino-shuffling, theoret. comput. sci. 303 (2003) 267-301], and was generalized by kuo [applications of graphical condensation for enumerating matchings and tilings, theoret. comput. sci. 319 (2004) 29-57] and yah and zhang [graphical condensation for enumerating perfect matchings, j. combin. theory ser. a 110 (2005) 113-125]. in this paper, by a purely combinatorial method some explicit identities on graphical vertex-condensation for enumerating perfect matchings of plane graphs (which do not need to be bipartite) are obtained. as applications of our results, some results on graphical edge-condensation for enumerating perfect matchings are proved, and we count the sum of weights of perfect matchings of weighted aztec diamond.
encoding types in ml-like languages. this article presents several general approaches to programming with type-indexed families of values within a hindley-milner type system. a type-indexed family of values is a function that maps a family of types to a family of values. the function performs a case analysis on the input types and returns values of possibly different types. such a case analysis on types seems to be prohibited by the hindley-milner type system. our approaches solve the problem by using type encodings. the compile-time types of the type encodings reflect the types themselves, thereby making the approaches type-safe, in the sense that the underlying type system statically prevents any mismatch between the input type and the function arguments that depend on this type.a type encoding could be either value-dependent, meaning that the type encoding is tied to a specific type-indexed family, or value-independent, meaning that the type encoding can be shared by various type-indexed families. our first approach is value-dependent: we simply interpret a type as its corresponding value. our second approach provides value-independent type encodings through embedding and projection functions; they are universal type interpretations, in that they can be used to compute other type interpretations. we also present an alternative approach to value-independent type encodings, using higher-order functors.we demonstrate our techniques through applications such as c printf-like formatting, type-directed partial evaluation, and subtype coercions.
synthesis of multi-qudit hybrid and d-valued quantum logic circuits by decomposition. recent research in generalizing quantum computation from 2-valued qudits to d-valued qudits has shown practical advantages for scaling up a quantum computer. a further generalization leads to quantum computing with hybrid qudits where two or more qudits have different finite dimensions. advantages of hybrid and d-valued gates (circuits) and their physical realizations have been studied in detail by muthukrishnan and stroud [multi-valued logic gates for quantum computation, phys. rev. a 62 (2000) 052309. [10]], daboul et al. [quantum gates on hybrid qudits, j. phys. a math. gen. 36 (2003) 2525-2536. [5]], and bartlett et al. [quantum encodings in spin systems and harmonic oscillators, phys. rev. a 65 (2002) 052316. [17]]. in both cases, a quantum computation is performed when a unitary evolution operator, acting as a quantum logic gate, transforms the state of qudits in a quantum system. unitary operators can be represented by square unitary matrices. if the system consists of a single qudit, then tilma et al. [generalized euler angle parameterization for su(n), j. phys. a math. gen. 35 (2002) 10467-10501. [15]] have shown that the unitary evolution matrix (gate) can be synthesized in terms of its euler angle parametrization. however, if the quantum system consists of multiple qudits, then a gate may be synthesized by matrix decomposition techniques such as qr factorization and the cosine-sine decomposition (csd). in this article, we present a csd based synthesis method for n qudit hybrid quantum gates, and as a consequence, derive a csd based synthesis method for n qudit gates where all the qudits have the same dimension.
computational aspects of mining maximal frequent patterns. in this paper we study the complexity-theoretic aspects of mining maximal frequent patterns, from the perspective of counting the number of all distinct solutions. we present the first formal proof that the problem of counting the number of maximal frequent itemsets in a database of transactions, given an arbitrary support threshold, is #p-complete, thereby providing theoretical evidence that the problem of mining maximal frequent itemsets is np-hard. we also extend our complexity analysis to other similar data mining problems that deal with complex data structures, such as sequences, trees, and graphs. we investigate several variants of these mining problems in which the patterns of interest are subsequences, subtrees, or subgraphs, and show that the associated problems of counting the number of maximal frequent patterns are all either #p-complete or #p-hard.
jordan curves with polynomial inverse moduli of continuity. computational complexity of two-dimensional domains whose boundaries are polynomial-time computable jordan curves with polynomial inverse moduli of continuity is studied. it is shown that the membership problem of such a domain can be solved in p^n^p, i.e., in polynomial time relative to an oracle in np, in contrast to the higher upper bound p^m^p for domains without the property of polynomial inverse modulus of continuity. on the other hand, the lower bound of up for the membership problem still holds for domains with polynomial inverse moduli of continuity. it is also shown that the shortest path problem of such a domain can be solved in pspace, close to its known lower bound, while no fixed upper bound was known for domains without this property.
on linear complexity of sequences over (2). in this paper, we consider some aspects related to determining the linear complexity of sequences over gf(2n). in particular, we study the effect of changing the finite field basis on the minimal polynomials, and thus on the linear complexity, of sequences defined over gf(2n) but given in their binary representation. let a = {ai} be a sequence over gf(2n). then ai can be represented by ai =σj=0n-1 aijαj,aij ∈ gf(2), where α is the root of the irreducible polynomial defining the field. consider the sequence b = {bi} whose elements are obtained from the same binary representation of a but assuming a different set of basis (say {γ0, γ1,..., γn-1}), i.e. bi = σj=0r-1 aijγj, we study the relation between the minimal polynomial of a and b.
the unbounded single machine parallel batch scheduling problem with family jobs and release dates to minimize makespan. in this paper we consider the unbounded single machine parallel batch scheduling problem with family jobs and release dates to minimize makespan. we show that this problem is strongly np-hard, and give an o(n(n/m+1)m) time dynamic programming algorithm and an o(mkk-1p2k-1) time dynamic programming algorithm, where n is the number of jobs, m is the number of families, k is the number of distinct release dates and p is the sum of the processing times of all families. we further give a heuristic with a performance ratio 2. we also give a polynomial-time approximation scheme for the problem.
probability distribution for simple tautologies. in this paper we investigate the size of the fraction of tautologies of the given length n against the number of all formulas of length n for implicational logic. we are specially interested in asymptotic behavior of this fraction. we demonstrate the relation between a number of premises of implicational formula and asymptotic probability of finding formula with this number of premises. furthermore, we investigate the distribution of this asymptotic probabilities. distribution for all formulas is contrasted with the same distribution for tautologies only. we prove those distributions to be so different that enable us to estimate likelihood of truth for a given long formula. despite the fact that all discussed problems and methods in this paper are solved by mathematical means, the paper may have some philosophical impact on the understanding how much the phenomenon of truth is sporadic or frequent in random logical sentences.
on the power of ambainis lower bounds. the polynomial method and the ambainis lower bound (or alb, for short) method are two main quantum lower bound techniques. while recently ambainis showed that the polynomial method is not tight, the present paper aims at studying the power and limitation of alb's. we first use known alb's to derive ω(n1.5) lower bounds for bipartiteness, bipartiteness matching and graph matching, in which the lower bound for bipartiteness improves the previous ω(n) one. we then show that all the three known ambainis lower bounds have a limitation √n min{c0(f), c1(f)}, where c0(f) and c1(f) are the 0- and 1-certificate complexities, respectively. this implies that for many problems such as triangle, k-clique, bipartiteness and bipartite/graph matching which draw wide interest and whose quantum query complexities are still open, the best known lower bounds cannot be further improved by using ambainis techniques. another consequence is that all the ambainis lower bounds are not tight. for total functions, this upper bound for alb's can be further improved to min{√c0(f)c1(f), √nċci(f)}, where ci(f) is the size of max intersection of a 0- and a 1-certificate set. again this implies that alb's cannot improve the best known lower bound for some specific problems such as and-or tree, whose precise quantum query complexity is still open. finally, we generalize the three known alb's and give a new alb style lower bound method, which may be easier to use for some problems.
structure of proofs and the complexity of cut elimination. the importance of the structure of cut-formulas with respect to proof length and proof depth has been studied in various occasions. it has been illustrated that a quantifier may be more powerful than a binary connective in cut-formulas with respect to the reduction (or increase) of proof length and proof depth, and a sequence of quantifiers of the same type (existential or universal) may be less powerful than a sequence of quantifiers of alternating types. this paper provides a refined view on cut-elimination through an analysis of the structure of proofs, brings new insight into the relation between cut-formulas and short proofs, and illustrates that a mixture of quantifiers and binary connectives could be important for achieving the maximal benefit of cut-formulas for obtaining short proofs.
approximating the minimum weight weak vertex cover. accurate network flow measurement is important for a variety of network applications, where the "flow" over an edge in the network is intuitively the rate of data traffic. the problem of efficiently monitoring the network flow can be regarded as finding the minimum weight weak vertex cover for a given graph. in this paper, we present a (2 - 2/v(g)-approximation algorithm solving for this problem, which improves previous results, where v(g) is the cyclomatic number of g.
probabilistic rebound turing machines. this paper introduces a probabilistic rebound turing machine (prtm), and investigates the fundamental property of the machine. we first prove a sublogarithmic lower space bound on the space complexity of this model with bounded errors for recognizing specific languages. this lower bound strengthens a previous lower bound for conventional probabilistic turing machines with bounded errors. we then show, by using our lower space bound and an idea in the proof of it, that i) [prtm(o(logn))] is incomparable with the class of context-free languages, ii) there is a language accepted by a two-way deterministic one counter automaton, but not in [prtm(o(logn))], and where [prtm(o(logn))] denotes the class of languages recognized by o(logn) space-bounded prtms with error probability less than . furthermore, we show that there is an infinite space hierarchy for [prtm(o(logn))]. we finally show that [prtm(o(logn))] is not closed under concatenation, kleene +, and length-preserving homomorphism. this paper answers two open problems in a previous paper.
reasoning with power defaults. this paper introduces power default reasoning (pdr), a framework for non-monotonic reasoning based on the domain-theoretic idea of modeling default rules with partial-information in a higher-order setting. pdr lifts a non-monotonic operator at the base (syntactic) level to a well-behaved, almost monotonic operator in the higher-order space of the smyth power-domain --effectively a space of sets of models. working in the model space allows us to prove the dichotomy theorem and the extension splitting theorem, leading to a more well-behaved logic and (modulo the usual complexity conjectures) a less complex logic than standard default logic. specifically, we prove that skeptical normal default inference is a problem complete for co-np(3) in the boolean hierarchy for strict propositional logic and np(4)-complete in general. these results (by changing the underlying semantics) contrasts favorably with similar results of gottlob (j. logic comput. 2(3) (1992) 397-425), who proves that standard skeptical default reasoning is π2p-complete. furthermore, we show that the skeptical non-monotonic consequence relation, defined using our domain-theoretic semantics, obeys all of the laws for preferential consequence relations defined by kraus, lehmann, and magidor. in particular, we get the property of being able to reason by cases, and the so-called law of cautious monotony. both of these laws fail for the standard propositional default logic of reiter (artificial intelligence 13 (1980) 81-132), but hold in pdr as a consequence of the dichotomy theorem and the extension splitting theorem.
completion of codes with finite bi-decoding delays. let a* be a free monoid generated by a set a and let x ⊆ a* be a code with property p. the embedding of x into a complete code y ⊆ a* with the same property p is called the completion of x. the method of completion of rational bifix codes and codes with finite decoding delays have been investigated by a number of authors. in this paper, we provide a general method of construction for completing the codes with finite bi-decoding delays. as a consequence, the completion method of rational bifix codes and codes with finite decoding delays is extended and applied to codes with finite bi-decoding delays.
security analysis of a password-based authentication protocol proposed to ieee 1363. in recent years, several protocols for password-based authenticated key exchange have been proposed. these protocols aim to be secure even though the sample space of passwords may be small enough to be enumerated by an off-line adversary. in eurocrypt 2000, bellare, pointcheval and rogaway (bpr) presented a model and security definition for authenticated key exchange. they claimed that in the ideal-cipher model (random oracles), the two-flow protocol at the core of encrypted key exchange (eke) is secure. bellare and rogaway suggested several instantiations of the ideal cipher in their proposal to the ieee p1363.2 working group. since then there has been an increased interest in proving the security of password-based protocols in the ideal-cipher model. for example, bresson, chevassut, and pointcheval have recently showed that the one-encryption-key-exchange (oeke) protocol is secure in the ideal cipher model. in this paper, we present examples of real (not ideal) ciphers (including naive implementations of the instantiations proposed to ieee p1363.2) that would result in broken instantiations of the idealised autha protocol and oeke protocol. our result shows that the autha protocol can be instantiated in an insecure way, and that there are no well defined (let alone rigorous) ways to distinguish between secure and insecure instantiations. thus, without a rigorous metric for ideal-ciphers, the value of provable security in ideal cipher model is limited.
the closure properties on real numbers under limits and computable operators. in effective analysis, various classes of real numbers are discussed. for example, the classes of computable, semi-computable, weakly computable, recursively approximable real numbers, etc. all these classes correspond to some kind of (weak) computability of the real numbers. in this paper we discuss mathematical closure properties of these classes under the limit, effective limit and computable function. among others, we show that the class of weakly computable real numbers is not closed under effective limit and partial computable functions while the class of recursively approximable real numbers is closed under effective limit and partial computable functions.
divergence bounded computable real numbers. a real x is called h-bounded computable, for some function h: n → n, if there is a computable sequence (xs) of rational numbers which converges to x such that, for any n ∈ at most h(n) non-overlapping pairs of its members are separated by a distance larger than 2-n. in this paper we discuss properties of h-bounded computable reals for various functions h. we will show a simple sufficient condition for a class of functions h such that the corresponding h-bounded computable reals form an algebraic field. a hierarchy theorem for h-bounded computable reals is also shown. besides we compare semi-computability and weak computability with the h-bounded computability for special functions h.
connections among nonlinearity, avalanche and correlation immunity. nonlinear boolean functions play an important role in the design of block ciphers, stream ciphers and one-way hash functions. over the years researchers have identified a number of indicators that forecast nonlinear properties of these functions. studying the relationships among these indicators has been an area that has received extensive research. the focus of this paper is on the interplay of three notable nonlinear indicators, namely nonlinearity, avalanche and correlation immunity. we establish, for the first time, an explicit and simple lower bound on the nonlinearity nf of a boolean function f of n variables satisfying the avalanche criterion of degree p, namely, nf ≥ 2n-1 -2n-1-(1/2)p. we also identify all the functions whose nonlinearity attains the lower bound. as a further contribution of this paper, we prove that except for very few cases, the sum of the degree of avalanche and the order of correlation immunity of a boolean function of n variables is at most n-2. the new results obtained in this work further highlight the significance of the fact that while avalanche property is in harmony with nonlinearity, both go against correlation immunity.
the generalized xor lemma. the xor lemma states that a mapping is regular or balanced if and only if all the linear combinations of the component functions of the mapping are balanced boolean functions. the main contribution of this paper is to extend the xor lemma to more general cases where a mapping may not be necessarily regular. the extended xor lemma has applications in the design of substitution boxes or s-boxes used in secret key ciphers. it also has applications in the design of stream ciphers as well as one-way hash functions. of independent interest is a new concept introduced in this paper that relates the regularity of a mapping to subspaces.
a channel assignment problem for optical networks modelled by cayley graphs. a problem arising from a recent study of scalability of optical networks seeks to assign channels to the vertices of a network so that vertices distance 2 apart receive distinct channels. in this paper we introduce a general channel assignment scheme for cayley graphs on abelian groups, and derive upper bounds for the minimum number of channels needed for such graphs. as application we give a systematic way of producing near-optimal channel assignments for connected graphs admitting a vertex-transitive abelian group of automorphisms. hypercubes are examples of such graphs, and for them our near-optimal upper bound gives rise to the one obtained recently by wan.
a representation theorem for recovering contraction relations satisfying wci. a notion of an image structure associated with the canonical epistemic state is introduced. based on it, we get a representation result for recovering contraction inference relations satisfying the condition weak conjunctive inclusion (wci) in terms of f-standard epistemic agm states. in effect, this result establishes a representation theorem for belief contraction functions satisfying agm postulates (k-1) - (k-7), and rott's (wci) and (k-8c), and hence generalizes rott's corresponding result in the finite framework.
on the complexity of unsigned translocation distance. translocation is one of the basic operations for genome rearrangement. translocation distance is the minimum number of translocations required to transform one genome into the other. in this paper, we show that computing the translocation distance for unsigned genomes is np-hard. moreover, we show that approximating the translocation distance for unsigned genomes within ratio 1.00017 is np-hard.
normal conditions for inference relations and injective models. although fruitful representation results induced by some kinds of injective models, e.g., filtered, ranked and quasi-linear injective models, etc., have been established in the literature, it is still an open problem to characterize the family of all injective inference relations in terms of rules. the type of postulates appearing in recent literature seems to be unable to characterize this family. this brings up an interesting theoretical problem: what kind of injective inference relations may be characterized by existent types of postulates? this paper makes an initial step to answer this question. to this end, a notion of a normal condition is introduced, which subsumes all horn and non-horn conditions presented in the literature. we obtain some results on injective models generating inferences characterized by normal conditions, and show that these injective models must be specific standard models. moreover, for any set of injective models determined only by a structural property of preferential orders, if the family of inference relations induced by it can be characterized by normal conditions, then it must be a subset of filtered models in this circumstance. thus, its associated inference relations satisfy the non-horn rule disjunctive rationality.
a characterization theorem for injective model classes axiomatized by general rules. we continue the work in zhu et al. [normal conditions for inference relations and injective models, theoret. comput. sci. 309 (2003) 287-311]. a class ω of strict partial order structures (posets, for short) is said to be axiomatizable if the class of all injective preferential models from ω may be characterized in terms of general rules. this paper aims to obtain some characteristics of axiomatizable classes. to do this, a monadic second-order frame language is presented. the relationship between χ0-axiomatizability and second-order definability is explored. then a notion of an admissible set is introduced. based on this notion, we show that any preferential model, which does not contain any four-node substructure, must be a reduct of some injective model. furthermore, we furnish a necessary and sufficient condition for the axiomatizability of classes of injective preferential models using general rules. finally, we show that, in some sense, the class of all posets without any four-node substructure is the largest among axiomatizable classes.
stability versus speed in a computable algebraic model. algebraic models of real computation and their induced notions of time complexity neglect stability issues of numerical algorithms. recursive analysis on the other hand appropriately describes stable numerical computations while, based on turing machines, usually lacks significant lower complexity bounds.we propose a synthesis of the two models, namely a restriction of algebraic algorithms to computable primitives. these are thus inherently stable and allow for nontrivial complexity considerations. in this model, one can prove on a sound mathematical foundation the empirically well-known observation that stability and speed may be contradictory goals in algorithm design.more precisely we show that solving the geometric point location problem among hyperplanes by means of a total computable decision tree (i.e., one behaving numerically stable for all possible input points) has in general complexity exponentially larger than when permitting the tree to be partial, that is, to diverge (behave in an instable way) on a 'small' set of arguments.the trade-off between the extremes is investigated quantitatively for the planar case. proofs involve both topological and combinatorial arguments.
computability in linear algebra. many problems in linear algebra can be solved by gaussian elimination. this famous algorithm applies to an algebraic model of real number computation where operations +, -, *, / and tests like, e.g., < and == are presumed exact. implementations of algebraic algorithms on actual digital computers often lead to numerical instabilities, thus revealing a serious discrepancy between model and reality.a different model of real number computation dating back to alan turing considers real numbers as limits of rational approximations. in that widely believed to be more realistic notion of computability, we investigate problems from linear algebra. our central results yield algorithms which in this sense • solve systems of linear equations a ċ x = b, • determine the spectral resolution of a symmetric matrix b, • and compute a linear subspace's dimension from its euclidean distance function, provided the rank of a and the number of distinct eigenvalues of b are known. without such restrictions, the first two problems are shown to be, in general, uncomputable.
time-stamps for mazurkiewicz traces. we construct a new time-stamp system for mazurkiewicz traces. we begin by constructing a sequential time-stamp system which turns out to be optimal for a certain class of time-stamps. in the next step we show that this time-stamp system can be adapted for mazurkiewicz traces, i.e. it can be used also in a distributed environment.
generalized acceptance, succinctness and supernondeterministic finite automata. we define generalized, acceptance in nondeterministic finite automata, in order to achieve more instances of succinct descriptions of regular languages in practical applications. we show that generalized acceptance enable the construction of a hierarchy of succinct nondeterministic descriptions for finite automata. the hierarchy corresponds to deterministic finite automata on level 0 and nondeterministic finite automata on level 1 by default, and we prove that the hierarchy corresponds to alternating (boolean) finite automata on level 2. we show that there exists an 2-state level 3 finite automaton with generalized acccptance, such that its equivalent minimal deterministic finite automaton has more that 222 states.
separation of uniform learning classes. within the scope of inductive inference a recursion theoretic approach is used to model learning behaviour. the fundamental model considered is gold's identification of recursive functions in the limit. modifying the corresponding definition has proposed several inference classes, which have been compared regarding the capacities of the relevant learners. the present paper is concerned with a meta-version of this learning model. given a description of a class of target functions, a uniform learner is supposed to develop a specific successful method for learning the represented class. the same modifications as in the elementary model are considered in the context of uniform learning, especially respecting identification capacities. it turns out that the former separations of inference classes are reflected on the meta-level, in particular finite classes of recursive functions--which constitute the most simple learning problems in the elementary model--are evidence of these separations.
on the topological size of p-m-complete degrees. all polynomial many-one degrees are shown to be of second baire category in the superset topology when witness functions are allowed to run in 2^{\log^hn} time, for any h. any improvement of this result for the complete p-m-degrees of re, exp or np implies p \neq np.
on the size of classes with weak membership properties. it is shown that the following classes have measure 0 in e: the class of p-selective sets, the class of p-multiselective sets, the class of cheatable sets, the class of easily countable sets, the class of easily approximable sets, the class of near-testable sets, the class of nearly near-testable sets, the class of sets that are not p-bi-immune. these are corollaries of a more general result stating that the class of sets that are p-isomorphic to p-quasi-approximable sets has measure 0 in e. by considering the recent approach of allender and strauss for measuring in subexponential classes, we obtain similar results with respect to p for classes having weak logarithmic time membership properties.
peirce's rule in natural deduction. in stark contrast to natural deduction for intuitionistic logic, natural deduction for classical logic suffers from some well-known limitations: although normalisation can be proved, the standard proof of prawitz (natural deduction. a proof theoretical study, almquist and wiksell, stockholm, 1965) is restricted to a fragment of classical predicate logic without and without due to some effects of the rule of classical negation, and a proof for classical predicate logic without and without cannot be given; the extension of prawitz' proof to a language with and due to stalmarck (j. symbolic logic 56 (1991) 129) still remaining language dependent on and . such facts raise some doubts about the proof theoretical significance of the classical negation rule, the reductio ad absurdum, introduced by prawitz. instead of this rule, peirce's rule may be chosen, a purely implicative elimination rule, proposed for classical natural deduction by curry (foundations of mathematical logic, mcgraw-hill, new york, 1963): this rule can be proved to be deductively equivalent with the classical negation rule, and this rule admits formulations of classical predicate logic without and without . in the following paper, it is shown that with peirce's rule, several theorems of weak normalisation for classical logic are provable, i.e. weak normalisation for any fragment of classical logic containing and being enriched with any of the signs and respective rules ,,,,thus the most general proofs of normalisation for classical predicate logic are given.
solving the generalized mask constraint for test generation of binary floating point add operation. the mathematical problem discussed is important for generating test cases in order to debug floating point adders designs.floating point numbers are assumed to be written as strings of {0, 1} bits, in a format compatible with ieee standard 754. a mask is a string of characters, composed of {'0', '1', 'x'}. a number and a mask are compatible if they have the same length and each numerical character of the mask ('0' or '1') is equal, numerically, to the bit of the number, in the same position. the problem discussed is: given masks ma, mb, mc, of identical lengths, generate three floating point numbers a,b,c which are compatible with the masks and satisfy c=round(a±b)). if there are many solutions, choose one at random. a fast algorithm is given which solves the problem for all ieee floating point data types and all rounding modes.
weakening the perfect encryption assumption in dolev-yao adversaries. we consider secrecy and authentication in a simple process calculus with cryptographic primitives. the standard dolev-yao adversary is enhanced so that it can guess the key required to decrypt an intercepted message. we borrow from the computational complexity approach the assumptions that guessing succeeds with a given negligible probability and that the resources available to adversaries are polynomially bounded. under these hypotheses we prove that the standard dolev-yao adversary is as powerful as the enhanced one.
satgraphs and independent domination. part 1. a graph g is called a satgraph if there exists a partition a ∪ b = v(g) such that • a induces a clique [possibly, a = 0], • b induces a matching [i.e., g(b) is a 1-regular subgraph, possibly, b = 0], and • there are no triangles (a, b, b'), where a ∈ a and b, b' ∈ b.we also introduce the hereditary closure of iaj, denoted by hiaj [hereditary satgraphs]. the class hiaj contains split graphs. in turn, hiaj is contained in the class of all (1, 2)-split graphs [a. gyárfás, generalized split graphs and ramsey numbers, j. combin. theory ser. a 81 (2) (1998) 255-261], the latter being still not characterized. we characterize satgraphs in terms of forbidden induced subgraphs.there exist close connections between satgraphs and the satisfiability problem [sat]. in fact, sat is linear-time equivalent to finding the independent domination number in the corresponding satgraph. it follows that the independent domination problem is np-complete for the hereditary satgraphs. in particular, it is np-complete for perfect graphs.
independent domination in hereditary classes. we investigate independent domination problem within hereditary classes of graphs. boliac and lozin [independent domination in finitely defined classes of graphs, theoret. comput. sci. 301 (1-3) (2003) 271-284] proved some sufficient conditions for independent domination problem to be np-complete within finitely defined hereditary classes of graphs. they posed a question whether the conditions are also necessary. we show that the conditions are not necessary, since independent domination problem is np-hard within 2p3-free graphs.moreover, we show that the problem remains np-hard for a new hereditary class of graphs, called hereditary 3-satgraphs. we characterize hereditary 3-satgraphs in terms of forbidden induced subgraph. as corollaries, we prove that independent domination problem is np-hard within the class of all 2p3-free perfect graphs and for k1,5-free weakly chordal graphs.finally, we compare complexity of independent domination problem with that of independent set problem for a hierarchy of hereditary classes recently proposed by hammer and zverovich [construction of maximal stable sets with k-extensions, combin. probab. comput. 13 (2004) 1-8]. for each class in the hierarchy, a maximum independent set can be found in polynomial time, and the hierarchy covers all graphs. however, our characterization of hereditary 3-satgraphs implies that independent domination problem is np-hard for almost all classes in the hierarchy. this fact supports a conjecture that independent domination is harder than independent set problem within hereditary classes.
the memory game. the memory game is a popular card game played by children and adults around the world. good memory is one of the qualities required in order to succeed in it. this however is not enough.when it is assumed that the players have perfect memory, the memory game can be seen as a game of strategy. the game is analysed under this assumption and the optimal strategy is found. this is simple and perhaps unexpected. in contrast to the simplicity of the optimal strategy, the analysis leading to its optimality proof is rather involved. it supplies an interesting example of concrete mathematics of the sort used in the analysis of algorithms. it is doubtful whether this analysis could have been carried out without resort to experimentation and substantial use of automated symbolic computation.
martin's game: a lower bound for the number of sets. we investigate martin's game (as described in arruda et al. (eds.), on random r. e. sets, non-classical logics, model theory and computability, north-holland, amsterdam, 1977, p. 283) and prove that the upper bound from the above mentioned reference for the number of sets needed to construct a winning strategy, is almost tight.
a genetic system based on simulated crossover of sequences of two-bit genes. we introduce a genetic model based on simulated crossover of fixed sequences of two-bit genes. results are(1)a lower bound on population size is exhibited such that a transition takes the stochastic finite population genetic system near the next state of the deterministic infinite population genetic system (provided both begin in the same state); (2)states and dynamics of the deterministic infinite population genetic system are derived for arbitrary (finite) fitness functions (expressed in terms of multivariate polynomials); (3)in the case of quadratic fitness defined by weight matrices with m nonnull entries it is shown that each state transition can be implemented in time o(m+l), where l is the chromosome length; (4)the genetic algorithm (implementing the proposed infinite population system) is experimentally compared with the infinite population genetic algorithm with bit-based simulated crossover for the max-cut problem; the results show that the extension to sequences of genes with four alleles is useful to improve performances.
global convergence of oja's pca learning algorithm with a non-zero-approaching adaptive learning rate. a non-zero-approaching adaptive learning rate is proposed to guarantee the global convergence of oja's principal component analysis (pca) learning algorithm. most of the existing adaptive learning rates for oja's pca learning algorithm are required to approach zero as the learning step increases. however, this is not practical in many applications due to the computational round-off limitations and tracking requirements. the proposed adaptive learning rate overcomes this shortcoming. the learning rate converges to a positive constant, thus it increases the evolution rate as the learning step increases. this is different from learning rates which approach zero which slow the convergence considerably and increasingly with time. rigorous mathematical proofs for global convergence of oja's algorithm with the proposed learning rate are given in detail via studying the convergence of an equivalent deterministic discrete time (ddt) system. extensive simulations are carried out to illustrate and verify the theory derived. simulation results show that this adaptive learning rate is more suitable for oja's pca algorithm to be used in an online learning situation.
chosen ciphertext attacks on lattice-based public key encryption and modern (non-quantum) cryptography in a quantum environment. modern cryptography is based on various building blocks such as one way functions with or without trapdoors, pseudo-random functions, one way permutations with or without trapdoors, etc. in a quantum world some of the main candidates for these building blocks are broken. for instance, the security of the most popular public-key cryptosystem-rsa-is related to the difficulty of factoring large numbers, and is broken (in principle) by a quantum computer. we investigate some of the remaining candidates, and discuss the resulting ''post-quantum cryptography'' (namely, the resulting ''modern cryptography in a quantum environment''). about half a decade ago ajtai and dwork (and later on, also goldreich, goldwasser and halevi) proposed a public key cryptosystem that has a proven security under a plausible complexity assumption. the plausible assumption is that the so-called unique shortest vector problem (u-svp) is hard on the worst case. this problem is potentially still hard also in a quantum environment. recently, regev introduced a new (and much simpler) public key cryptosystem, based on the same u-svp hardness assumption, but with improved parameters. in this paper we present chosen ciphertext attacks (cca) against all three cryptosystems. our attack shows that these cryptosystems are totally insecure against cca, because the private keys can be recovered in polynomial time. we then discuss the possibility of making public key encryption (pke) secure against cca, without adding stronger assumptions than the assumption that u-svp is hard. we conclude that the current understanding of modern cryptography in a quantum environment can only suggest cca-secure interactive-pke, which is obviously weaker than cca-secure pke. finally, we discuss the relation of our attack to the reaction attack of hall, goldberg and schneier, which we only recently became aware of.
rewriting queries using views in the presence of arithmetic comparisons. we consider the problem of answering queries using views, where queries and views are conjunctive queries with arithmetic comparisons over dense orders. previous work only considered limited variants of this problem, without giving a complete solution. we first show that obtaining equivalent rewritings for conjunctive queries with arithmetic comparisons is decidable. then, we consider the problem of finding maximally contained rewritings (mcrs) where the decidability proof does not carry over. we investigate two special cases of this problem where the query uses only semi-interval comparisons. in both cases decidability of finding mcrs depends on the query containment test. first, we address the case where the homomorphism property holds in testing query containment. in this case decidability is easy to prove but developing an efficient algorithm is not trivial. we develop such an algorithm and prove that it is sound and complete. this algorithm applies in many cases where the query uses only left (or right) semi-interval comparisons. then, we develop a new query containment test for the case where the containing query uses both left and right semi-interval comparisons but with only one left (or right) semi-interval subgoal. based on this test, we show how to produce an mcr which is a datalog query with arithmetic comparisons. the containment test that we develop obtains a result of independent interest. it finds another special case where query containment in the presence of arithmetic comparisons can be tested in nondeterministic polynomial time.
a formal fuzzy reasoning system and reasoning mechanism based on propositional modal logic. we establish in this paper a fuzzy propositional modal logic, fpml, and the associated semantics, fuzzy kripke semantics. we prove that fpml is sound and complete. furthermore, we set up a formalized reasoning mechanism based on fpml.
a flexible model for dynamic linking in java and c#. dynamic linking supports flexible code deployment, allowing partially linked code to link further code on the fly, as needed. thus, end-users enjoy the advantage of automatically receiving any updates, without any need for any explicit actions on their side, such as re-compilation, or re-linking. on the down side, two executions of a program may link in different versions of code, which in some cases causes subtle errors, and may mystify end-users. dynamic linking in java and c# are similar: the same linking phases are involved, soundness is based on similar ideas, and executions which do not throw linking errors give the same result. they are, however, not identical: the linking phases are combined differently, and take place in different order. consequently, linking errors may be detected at different times by java and c# runtime systems. we develop a non-deterministic model, which describes the behaviour of both java and c# program executions. the non-determinism allows us to describe the design space, to distill the similarities between the two languages, and to use one proof of soundness for both. we also prove that all execution strategies are equivalent with respect to terminating executions that do not throw link errors: they give the same results.
a simple optimal representation for balanced parentheses. we consider succinct, or highly space-efficient, representations of a (static) string consisting of n pairs of balanced parentheses, which support natural operations such as finding the matching parenthesis for a given parenthesis, or finding the pair of parentheses that most tightly enclose a given pair. this problem was considered by jacobson [space-efficient static trees and graphs, in: proc. of the 30th focs, 1989, pp. 549-554] and munro and raman [succinct representation of balanced parentheses and static trees, siam j. comput. 31 (2001) 762-776] who gave o(n)-bit and 2n+o(n)-bit representations, respectively, that supported the above operations in o(1) time on the ram model of computation. this data structure is a fundamental tool in succinct representations, and has applications in representing suffix trees, ordinal trees, planar graphs and permutations. we consider the practical performance of parenthesis representations. first, we give a new 2n+o(n)-bit representation that supports all the above operations in o(1) time. this representation is conceptually simpler, its space bound has a smaller o(n) term and it also has a simple and uniform o(n) time and space construction algorithm. we implement our data structure and a variant of jacobson's, and evaluate their practical performance (speed and memory usage), when used in a succinct representation of trees derived from xml documents. as a baseline, we compare our representations against a widely used implementation of the standard dom (document object model) representation of xml documents. both succinct representations use orders of magnitude less space than dom and tree traversal operations are usually only slightly slower than in dom.
type checking a multithreaded functional language with session types. we define a language whose type system, incorporating session types, allows complex protocols to be specified by types and verified by static type checking. a session type, associated with a communication channel, specifies the state transitions of a protocol and also the data types of messages associated with transitions; thus type checking can verify both correctness of individual messages and correctness of sequences of transitions. previously, session types have mainly been studied in the context of the @p-calculus; instead, our formulation is based on a multithreaded functional language with side-effecting input/output operations. our typing judgements statically describe dynamic changes in the types of channels, and our function types not only specify argument and result types but also describe changes in channels. we formalize the syntax, semantics and type checking system of our language, and prove subject reduction and runtime type safety theorems.
a computational model for rna multiple structural alignment. this paper addresses the problem of aligning multiple sequences of noncoding rna (ncrna) genes. we approach this problem with the biologically motivated paradigm that scoring of ncrna alignments should be based primarily on secondary structure rather than nucleotide conservation. we introduce a novel graph theoretic model (nlg) for analyzing algorithms based on this approach, prove that the rna multiple alignment problem is np-complete in this model, and present a polynomial time algorithm that approximates the optimal structure of size s within a factor of o(log^2s).
a logical approach to stable domains. building on earlier work by guo-qiang zhang on disjunctive information systems, and by thomas ehrhard, pasquale malacaria, and the first author on stable stone duality, we develop a framework of disjunctive propositional logic in which theories correspond to algebraic l-domains. disjunctions in the logic can be indexed by arbitrary sets (as in geometric logic) but must be provably disjoint. this raises several technical issues which have to be addressed before clean notions of axiom system and theory can be defined. we show soundness and completeness of the proof system with respect to distributive disjunctive semilattices, and prove that every such semilattice arises as the lindenbaum algebra of a disjunctive theory. via stable stone duality, we show how to use disjunctive propositional logic for a logical description of algebraic l-domains.
generalized ultrametric spaces in quantitative domain theory. domains and metric spaces are two central tools for the study of denotational semantics in computer science, but are otherwise very different in many fundamental aspects. a construction that tries to establish links between both paradigms is the space of formal balls, a continuous poset which can be defined for every metric space and that reflects many of its properties. on the other hand, in order to obtain a broader framework for applications and possible connections to domain theory, generalized ultrametric spaces (gums) have been introduced. in this paper, we employ the space of formal balls as a tool for studying these more general metrics by using concepts and results from domain theory. it turns out that many properties of the metric can be characterized via its formal-ball space. furthermore, we can state new results on the topology of gums as well as two new fixed point theorems, which may be compared to the priesz-crampe and ribenboim theorem, and the banach fixed point theorem, respectively. deeper insights into the nature of formal-ball spaces are gained by applying methods from category theory. our results suggest that, while being a useful tool for the study of gums, the space of formal balls does not provide the hoped-for general connection to domain theory.
faster two-dimensional pattern matching with rotations. the most efficient currently known algorithms for two-dimensional pattern matching with rotations have a worst case time complexity of o(n^2m^3), where the size of the text is nxn and the size of the pattern is mxm. in this paper we present a new algorithm for the problem whose running time is o(n^2m^2).
invariance under stuttering in a temporal logic of actions. we show that some simple and useful stutter-invariant properties definable in the language of lamport's simple temporal logic of actions (stla) are not definable in stla and present a natural extension of stla that allows one to express all stutter-invariant properties definable in the language of stla.
complexity and approximability of k-splittable flows. let g = (v, e) be a graph with a source node s and a sink node t, |v| = n, |e| = m. for a given number k, the maximum k-splittable flow problem (mksf) is to find an s, t-flow of maximum value with a flow decomposition using at most k paths. in the multicommodity case this problem generalizes disjoint paths problems and unsplittable flow problems. we provide a comprehensive overview of the complexity and approximability landscape of mksf on directed and undirected graphs. we consider constant values of k and k depending on graph parameters. for arbitrary constant values of k, we prove that the problem is strongly np-hard on directed and undirected graphs already for k = 2. this extends a known np-hardness result for directed graphs that could not be applied to undirected graphs. furthermore, we show that mksf cannot be approximated with a performance ratio better than 5/6. this is the first constant bound given for arbitrary constant values of k. for non-constant values of k, the polynomial solvability was known before for all k ≥ m, but open for smaller k. we prove that mksf is np-hard for all k fulfilling 2 ≤ k ≤ m - n + 1 (for n ≥ 3). for all other values of k the problem is shown to be polynomially solvable.
dynamic load balancing with group communication. this work considers the problem of efficiently performing a set of tasks using a network of processors in the setting where the network is subject to dynamic reconfigurations, including partitions and merges. a key challenge for this setting is the implementation of dynamic load balancing that reduces the number of tasks that are performed redundantly because of the reconfigurations. we explore new approaches for load balancing in dynamic networks that can be employed by applications using a group communication service (gcs). the gcs that we consider include a membership service (establishing new groups to reflect dynamic changes) but does not include maintenance of a primary component. for the n-processor, n-task load balancing problem defined in this work, the following specific results are obtained. for the case of fully dynamic changes including fragmentation and merges we show that the termination time of any on-line task assignment algorithm is greater than the termination time of an off-line task assignment algorithm by a factor greater than n/12. we present a load balancing algorithm that guarantees completion of all tasks in all fragments caused by partitions with work o(n + f ċ n) in the presence of f fragmentation failures. we develop an effective scheduling strategy for minimizing the task execution redundancy and we prove that our strategy provides each of the n processors with a schedule of θ(n1/3) tasks such that at most one task is performed redundantly by any two processors.
reasoning under minimal upper bounds in propositional logic. reasoning from the minimal models of a theory, as fostered by circumscription, is in the area of artificial intelligence an important method to formalize common sense reasoning. however, as it appears, minimal models may not always be suitable to capture the intuitive semantics of a knowledge base, aiming intuitively at an exclusive interpretation of disjunctions of atoms, i.e., if possible then assign at most one of the disjuncts the value true in a model. in this paper, we consider an approach which is more lenient and also admits non-minimal models, such that inclusive interpretation of disjunction also may be possible in cases where minimal model reasoning adopts an exclusive interpretation. nonetheless, in the spirit of minimization, the approach aims at including only positive information that is necessary. this is achieved by closing the set of admissible models of a theory under minimal upper bounds in the set of models of the theory, which we refer to as curbing. we demonstrate this method on some examples, and investigate its semantical and computational properties. we establish that curbing is an expressive reasoning method, since the main reasoning tasks are shown to be pspace-complete. on the other hand, we also present cases of lower complexity, and in particular cases in which the complexity is located, just as for ordinary minimal model reasoning, at the second level of the polynomial hierarchy, or even below.
coding with variable block maps. in this article we study a special class of sliding block maps that we call variable block maps. we characterize the subsets of finite and infinite sequences that can be obtained as the image of another subset of symbolic sequences by a variable block map. on the other way, we show that the coding process induced by such kind of block maps can be reversed, even with partial knowledge about the variable block maps, and we give an explicit construction of a canonical antecedent.
visual cryptography schemes with optimal pixel expansion. a visual cryptography scheme encodes a black and white secret image into n shadow images called shares which are distributed to the n participants. such shares are such that only qualified subsets of participants can "visually" recover the secret image. usually, the reconstructed image will be darker than the background of the image itself. in this paper we consider visual cryptography schemes satisfying the model introduced by tzeng and hu [a new approach for visual cryptography, designs, codes and cryptography 27 (3) (2002) 207-227]. in such a model, the recovered secret image can be darker or lighter than the background. we prove a lower bound on the pixel expansion of the scheme and, for (2, n)-threshold visual cryptography schemes, we provide schemes achieving the bound. our schemes improve on the ones proposed by tzeng and hu.
two algebraic approaches to variants of the concatenation product. we extend an existing approach of the bideterministic concatenation product of languages aiming at the study of three other variants: unambiguous, left deterministic and right deterministic. such an approach is based on monoid expansions. the proofs are purely algebraic and use another approach, based on properties on the kernel category of a monoid relational morphism, without going through the languages. this gives a unified fashion to deal with all these variants and allows us to better understand the connections between these two approaches. finally, we show that local finiteness of an m-variety is transferred to the m-varieties corresponding to these variants and apply the general results to the m-variety of idempotent and commutative monoids.
degrees of non-monotonicity for restarting automata. in the literature various notions of monotonicity for restarting automata have been studied. here we introduce two new variants of monotonicity for restarting automata and for two-way restarting automata: left-monotonicity and right-left-monotonicity. it is shown that for the various types of deterministic and nondeterministic (two-way) restarting automata without auxiliary symbols, these notions yield infinite hierarchies, and we compare these hierarchies to each other. further, as a tool used to simplify some of the proofs, the shrinking restarting automaton is introduced, which is a generalization of the standard (length-reducing) restarting automaton to the weight-reducing case. some of the consequences of this generalization are also discussed.
an algorithmic approach to the problem of a semiretract base. a semiretract of a free monoid a* is an intersection of a family of retracts of a* and it is a free submonoid. in the paper we propose an algorithmic approach to the problem of finding the base (code) of a semiretract.
the degree distribution of the generalized duplication model. we study and generalize the duplication model of pastor-satorras et al. [evolving protein interaction networks through gene duplication, j. theor. biol. 222 (2003) 199-210]. this model generates a graph by iteratively "duplicating" a randomly chosen node as follows: we start at t0 with a fixed graph g(t0) of size t0. at each step t > t0 a new node vt is added. the node vt selects an existing node u from v(g(t - 1)) = {v1,...,vt-1} uniformly at random (uar). the node vt then connects to each neighbor of the node u in g(t - 1) independently with probability p. additionally, vt connects uar to every node of v(g(t - 1)) independently with probability r/t, and parallel edges are merged. unlike other copy-based models, the degree of the node vt in this model is not fixed in advance; rather it depends strongly on the degree of the original node u it selected. our main contributions are as follows: we show that (1) the duplication model of pastor-satorras et al. does not generate a truncated power-law degree distribution as stated in pastor-satorras et al. [evolving protein interaction networks through gene duplication, j. theor. biol. 222 (2003) 199-210]. (2) the special case where r = 0 does not give a power-law degree distribution as stated in chung et al. [duplication models for biological networks, j. comput. biol. 10 (2003) 677-687]. (3) we generalize the pastor-satorras et al. duplication process to ensure (if required) that the minimum degree of all vertices is positive. we prove that this generalized model has a power-law degree distribution.
a network flow approach to the minimum common integer partition problem. in the k-minimum common integer partition problem, abbreviated as k-mcie we are given k multisets x1,...,xk of positive integers, the goal is to find an integer multiset t of the minimum size such that for every i, we can partition each of the integers in xi so that the disjoint (multiset) union of their partitions equals t. this problem has applications in computational molecular biology, in particular, ortholog assignment and dna hybridization fingerprint assembly. the problem is known to be np-hard for any k ≥ 2. in this article, we improve the approximation ratio for k-mcip by viewing this problem as a flow decomposition problem in some flow network. we show an efficient 0.5625k-approximation algorithm, improving upon the previously best known 0.6139k-approximation algorithm for this problem.
a note on ambiguity of internal contextual grammars. in this paper, we continue the study of ambiguity of internal contextual grammars which was investigated in ilie [on ambiguity in internal contextual languages, in: c. martin-vide (ed.), second int. conf. on mathematical linguistics, tarragona, 1996, john benjamins, amsterdam, 1997, pp. 29-45] and martin-vide et al. [attempting to define the ambiguity in internal contextual languages, in: c. martin-vide (ed.), second int. conf. on mathematical linguistics, tarragona, 1996, john benjamins, amsterdam, 1997, pp. 59-81]. we solve some open problems formulated in these papers. the main results are: (i) there are inherently 1-ambiguous languages with respect to internal contextual grammars with arbitrary choice which are 0-unambiguous with respect to finite choice, (ii) there are inherently 2-ambiguous languages with respect to internal contextual grammars with arbitrary choice which are 1-unambiguous with respect to regular choice, and (iii) there are inherently 2-ambiguous languages with respect to depth-first internal contextual grammars with arbitrary choice which are 1-unambiguous with respect to finite choice.
iterated sequential transducers as language generating devices. iterated finite state sequential transducers are considered as language generating devices. the hierarchy induced by the size of the state alphabet is proved to collapse to the fourth level. the corresponding language families are related to the families of languages generated by lindenmayer systems and chomsky grammars. finally, some results on deterministic and extended iterated finite state transducers are established.
edge-bandwidth of grids and tori. the edge-bandwidth of a graph g is the smallest number b' for which there is a bijective labeling of e(g) with {1,...,e(g)} such that the difference between the labels at any adjacent edges is at most b'. here we compute the edge-bandwidth for rectangular grids: b'(pm⊕pn)=2 min(m,n) - 1 if max(m,n) ≥ 3, where ⊕ is the cartesian product and pn denotes the path on n vertices. this settles a conjecture of calamoneri et al. [new results on edge-bandwidth, theoret. comput. sci. 307 (2003) 503-513]. we also compute the edge-bandwidth of any torus (a product of two cycles) within an additive error of 5.
on a question of leiss regarding the hanoi tower problem. the tower of hanoi problem is generalized in such a way that the pegs are located at the vertices of a directed graph g, and moves of disks may be made only along edges of g. leiss obtained a complete characterization of graphs in which arbitrarily many disks can be moved from the source vertex s to the destination vertex d. here we consider graphs which do not satisfy this characterization; hence, there is a bound on the number of disks which can be handled. denote by gn the maximal such number as g varies over all such graphs with n vertices and s, d vary over the vertices. answering a question of leiss [finite hanoi problems: how many discs can be handled? congr. numer. 44 (1984) 221-229], we prove that gn grows sub-exponentially fast. moreover, there exists a constant c such that gn ≤ cn1/2 log2n for each n. on the other hand, for each ε > 0 there exists a constant cε > 0 such that gn ≥ cεn(1/2-ε)log2n for each n.
cost distribution of the chang-roberts leader election algorithm and related problems. a detailed probabilistic analysis is proposed of the total number of messages of the chang-roberts leader election algorithm. the cost is shown to be closely related to the total path length in random recursive trees, the total left-path length in increasing binary trees and the major cost of an in situ permutation algorithm.
constructive root bound for k-ary rational input numbers. guaranteeing accuracy is the critical capability in exact geometric computation, an important paradigm for constructing robust geometric algorithms. constructive root bounds is the fundamental technique needed to achieve such guaranteed accuracy. current bounds are overly pessimistic in the presence of general rational input numbers. in this paper, we introduce a method which greatly improves the known bounds for k-ary rational input numbers. since a majority of input numbers in scientific and engineering applications are either binary (k = 2) or decimal (k = 10), our results could lead to a significant speedup for a large class of applications. we apply our method to two of the best available constructive root bounds, the bfmss bound and the degree-measure bound. implementation and experimental results based on the core library are reported.
truthful algorithms for scheduling selfish tasks on parallel machines. we consider the problem of designing truthful mechanisms for scheduling selfish tasks (or agents)--whose objective is the minimization of their completion times--on parallel identical machines in order to minimize the makespan. a truthful mechanism can be easily obtained in this context (if we, of course, assume that the tasks cannot shrink their lengths) by scheduling the tasks following the increasing order of their lengths. the quality of a mechanism is measured by its approximation factor (price of anarchy, in a distributed system) w.r.t. the social optimum. the previous mechanism, known as spt, produces a (2 - 1/m)-approximate schedule, where m is the number of machines. the central question in this paper is the following: "are there other truthful mechanisms with better approximation guarantee (price of anarchy) for the considered scheduling problem?" this question has been raised by christodoulou et al. [coordination mechanisms, in: proc. of icalp 2004, lecture notes in computer science, vol. 3142, 345-357.] in the context of coordination mechanisms, but it is also relevant in centrally controlled systems. we present (randomized) truthful mechanisms for both the centralized and the distributed settings that improve the (expected) approximation guarantee (price of anarchy) of the spt mechanism. our centralized mechanism holds for any number of machines and arbitrary task lengths, while the coordination mechanism holds only for two machines and task lengths that are powers of a certain constant.
a fully polynomial approximation scheme for the single machine weighted total tardiness problem with a common due date. we develop a fully polynomial-time approximation scheme (fptas) for minimizing the weighted total tardiness on a single machine, provided that all due dates are equal. the fptas is obtained by converting an especially designed pseudopolynomial dynamic programming algorithm.
scheduling resource allocation with timeslot penalty for changeover. given a time slotted list of resource capacities, we address the problem of scheduling resource allocation considering that a change in allocation results in the changeover penalty of one timeslot. the goal is to maximize the overall allocation of resources. we prove that no 1-lookahead algorithm can be better than 8/5-competitive. we provide improved analysis of wait dominate hold (wdh) algorithm that was previously known to be 4-competitive. we prove that wdh is 8/3-competitive. we also consider k-lookahead algorithms, and prove lower bound of (k + 2)/(k + 1) on their competitiveness and give an online algorithm that is 2-competitive.
list edge and list total colorings of planar graphs without 4-cycles. let g be a planar graph with maximum degree δ such that g has no cycle of length from 4 to k, where k ≥ 4. then the list chromatic index χ′1(g) = δ and the list total chromatic number χ″1(g) = δ + 1 if (δ, k) ∈ {(7, 4), (6, 5), (5, 8)}. furthermore, χ′1(g) = δ if (δ, k) ∈ {(4, 14)}.
on the edge l radius of saitou and nei's method for phylogenetic reconstruction. in this paper, we study the performance of saitou and nei's neighbor-joining method for phylogenetic reconstruction. we show that the edge l∞ radius of the method is 1/4. this improves an result by atteson [the performance of neighbor-joining methods of phylogenetic reconstruction, algorithmica 25 (1999) 251-278] and xu et al. [a lower bound on the edge l∞ radius of saitou and nei's method for phylogenetic reconstruction, inform. process. lett. 94(5) (2005) 225-230]. previously, only an upper bound 1/4 and a lower bound 1/6 were known.
efficient sample sort and the average case analysis of pesort. the purpose of the paper is twofold. first, we want to search for a more efficient sample sort. secondly, by analyzing a variant of samplesort, we want to settle an open problem: the average case analysis of proportion extend sort (pesort for short). an efficient variant of samplesort given in the paper is called full sample sort. this algorithm is simple. it has a shorter object code and is almost as fast as pesort. theoretically, we show that full sample sort with a linear sampling size performs at most n log n = o(n) comparisons and o(n log n) exchanges on the average, but o(n log2 n) comparisons in the worst case. this is an improvement on the original samplesort by frazer and mckellar, which requires n log n + o(n log log n) comparisons on the average and o(n2) comparisons in the worst case. on the other hand, we use the same analyzing approach to show that pesort, with any p > 0, performs also at most n log n + o(n) comparisons on the average. notice, cole and kandathil analyzed only the case p = 1 of pesort. for any p > 0, they did not. namely, their approach is suitable only for a special case such as p = 1, while our approach is suitable for the generalized case.
the price of anarchy for polynomial social cost. in this work, we consider an interesting variant of the well studied kp model for selfish routing on parallel links, which reflects some influence from the much older wardrop model [j.g. wardrop, some theoretical aspects of road traffic research, proc. inst. of civil eng. part ii 1 (1956) 325-378]. in the new model, user traffics are still unsplittable and links are identical. social cost is now the expectation of the sum, over all links, of latency costs; each latency cost is modeled as a certain polynomial latency cost function evaluated at the latency incurred by all users choosing the link. the resulting social cost is called polynomial social cost, or monomial social cost when the latency cost function is a monomial. all considered polynomials are of degree d, where d ≥ 2, and have non-negative coefficients. we are interested in evaluating nash equilibria in this model, and we use the monomial price of anarchy (mpoa) and the polynomial price of anarchy (ppoa) as our evaluation measures. through establishing some remarkable relations of these costs and measures to some classical combinatorial numbers such as the stirling numbers of the second kind and the bell numbers, we obtain a multitude of results: • for the special case of identical users: the fully mixed nash equilibrium, where all probabilities are strictly positive, maximizes polynomial social cost. the mpoa is no more than bd, the bell number of order d. this immediately implies that the ppoa is no more than σ1 ≤ t ≤ dbt. for the special case of two links, the mpoa is no more than 2d-2(1 + (1/n)d-1), and this bound is tight for n = 2. • the mpoa is exactly ((2d - 1)d/(d - 1)(2d - 2)d-1)((d - 1)/d)d for pure nash equilibria. this immediately implies that the ppoa is no more than σ2 ≤ t ≤ d ((2t - 1)t/(t - 1)(2t - 2)t-1)((t - 1)/t)t.
the complexity of membership problems for circuits over sets of integers. we investigate the complexity of membership problems for {∪, ∩, -, +, ×}-circuits computing sets of integers. these problems are a natural modification of the membership problems for circuits computing sets of natural numbers studied by mckenzie and wagner [the complexity of membership problems for circuits over sets of natural numbers, lecture notes in computer science, vol. 2607, 2003, pp. 571-582]. we show that there are several membership problems for which the complexity in the case of integers differs significantly from the case of the natural numbers: testing membership in the subset of integers produced at the output of a {∪, +, ×}-circuit is nexptime-complete, whereas it is pspace-complete for the natural numbers. as another result, evaluating {-, +}-circuits is shown to be p-complete for the integers and pspace-complete for the natural numbers. the latter result extends mckenzie and wagner's work in nontrivial ways. furthermore, evaluating {×}-circuits is shown to be nl ∧ ⊕l-complete, and several other cases are resolved.
low complexity classes of multidimensional cellular automata. in this paper, multidimensional cellular automaton are considered. we investigate the hierarchy designed by the low complexity classes when the dimensionality is increased. whether this hierarchy is strict, is an open problem. however, we compare different variants and study their closure properties. we present also a correspondence between a main variant of multidimensional real-time cellular automata and one-way multihead alternating finite automata.
label updating to avoid point-shaped obstacles in fixed model. in this paper, we present efficient algorithms for updating the labeling of a set of n points after the presence of a random obstacle that appears on the map repeatedly. we update the labeling so that the given obstacle does not appear in any of the labels, the new labeling is valid, and the labels are as large as possible (called the optimal labeling). each point is assumed to have an axis-parallel, square-shaped label of unit size, attached exclusively to that point in the middle of one of its edges. we consider two models: (1) the 2pm model, where each label is attached to its feature only on the middle of one of its horizontal edges, and (2) the r4pm model, where each label is attached to its feature on the middle of either one of its horizontal or vertical edges (known in advance). we assume that a sequence of point-shaped obstacles appear on the map on random locations. three settings are considered for the behavior of the obstacle: (1) the obstacle is removed afterwards, (2) it remains on the map, and (3) it receives a similar label and remains on the map. only two operations are permitted on the labels: flipping one or more labels, and/or resizing all labels. in the first setting, we suggest a data structure of o(n) space and o(n lg n) time in the 2pm model, and of o(n2) time in the r4pm model, so that the updated labeling can be constructed for any obstacle position in o(lgn + k) time, where k is the minimum number of operations needed. for the second and third problems, we suggest an o(n) space and o(n lg n) time data structure that can place each obstacle (possibly with a label) on the map in o(lgn + k) time, if k label flips are sufficient to make room to place the new obstacle. otherwise, two o(n) time algorithms are suggested when a relabeling of all points is required.
on the remote server problem or more about tcp acknowledgments. we study an on-line problem that is motivated by service calls management in a remote support center. when a customer calls the remote support center of a software company, a technician opens a service request and assigns it a severity rating. this request is then transferred to the appropriate support engineer (se) who establishes a connection to the customer's site and uses remote diagnostic capabilities to resolve the problem. we assume that the se can service at most one customer at time and a request service time is negligible. there is a constant setup cost of creating a new connection to a customer's site and a specific cost per request for delaying its service that depends on the severity of the request. the problem is to decide which customers to serve first so as to minimize the incurred cost. this problem with just two customers is a natural generalization of the tcp acknowledgment problem. for the on-line version of the remote server problem (rsp), we present algorithms for the general case and for a special case of two customers that achieve competitive ratios of exactly 4 and 3, respectively. we also show that no deterministic on-line algorithm can have competitive ratio better than 3. then we study generalized versions of our model, these are the case of an asymmetric setup cost function and the case of multiple ses. for the off-line version of the rsp, we derive an optimal algorithm with a polynomial running time for a constant number of customers.
pairwise edge disjoint shortest paths in the n-cube. complexity issues intrinsic to certain fundamental data dissemination problems in high-performance network topologies are discussed. in particular, we study the p-pairwise edge disjoint shortest paths problem. an efficient algorithm for the case when every source point is at a distance at most two from its target is presented and for pairs at a distance at most three we show that the problem is np-complete.
sharing the cost of multicast transmissions in wireless networks. a crucial issue in non-cooperative wireless networks is that of sharing the cost of multicast transmissions to different users residing at the stations of the network. each station acts as a selfish agent that may misreport its utility (i.e., the maximum cost it is willing to incur to receive the service, in terms of power consumption) in order to maximize its individual welfare, defined as the difference between its true utility and its charged cost. a provider can discourage such deceptions by using a strategyproof cost sharing mechanism, that is a particular public algorithm that, by forcing the agents to truthfully reveal their utility, starting from the reported utilities, decides who gets the service (the receivers) and at what price. a mechanism is said budget balanced (bb) if the receivers pay exactly the (possibly minimum) cost of the transmission, and β-approximate budget balanced (β-bb) if the total cost charged to the receivers covers the overall cost and is at most β times the optimal one, while it is efficient if it maximizes the sum of the receivers' utilities minus the total cost over all receivers' sets. in this paper, we first investigate cost sharing strategyproof mechanisms for symmetric wireless networks, in which the powers necessary for exchanging messages between stations may be arbitrary and we provide mechanisms that are either efficient or bb when the power assignments are induced by a fixed universal spanning tree, or (3 ln(k + 1))-bb (k is the number of receivers), otherwise. then we consider the case in which the stations lay in a d-dimensional euclidean space and the powers fall as 1/dα, and provide strategyproof mechanisms that are either 1-bb or efficient for α = 1 or d = 1. finally, we show the existence of 2(3d - 1)-bb strategyproof mechanisms in any d-dimensional space for every α ≥ d. for the special case of d = 2 such a result can be improved to achieve 12-bb mechanisms.
algebraic properties of substitution on trajectories. language operations on trajectories provide a generalization of many common operations such as concatenation, quotient, shuffle and others. a trajectory is a syntactical condition determining positions where an operation is applied. besides their elegant language-theoretical properties, the operations on trajectories have been used to solve problems in coding theory, bioinformatics and concurrency theory. we focus on algebraic properties of substitution on trajectories. their characterization in terms of language-theoretical properties of the associated sets of trajectories is given. the transitivity property is of particular interest. unlike, e.g., shuffle on trajectories, in the case of substitution the transitive closure of a regular set of trajectories is again regular. this result has consequences in the above-mentioned application areas.
a geometric characterization of automatic semigroups. in the study of automatic groups, the geometrical characterization of automaticity (in terms of the "fellow traveller property") plays a fundamental role. when we move to the study of automatic semigroups, we no longer have this simple formulation. the purpose of this paper is to give a general geometric characterization of automaticity in semigroups.
partial multicuts in trees. let t = (v, e) be an undirected tree, in which each edge is associated with a non-negative cost, and let {s1, t1},..., {sk, tk} be a collection of k distinct pairs of vertices. given a requirement parameter t ≤ k, the partial multicut on a tree problem asks to find a minimum cost set of edges whose removal from t disconnects at least t out of these k pairs. this problem generalizes the well-known multicut on a tree problem, in which we are required to disconnect all given pairs. the main contribution of this paper is an (8/3 + ε)-approximation algorithm for partial multicut on a tree, whose run time is strongly polynomial for any fixed ε > 0. this result is achieved by introducing problem-specific insight to the general framework of using the lagrangian relaxation technique in approximation algorithms. our algorithm utilizes a heuristic for the closely related prize-collecting variant, in which we are not required to disconnect all pairs, but rather incur penalties for failing to do so. we provide a lagrangian multiplier preserving algorithm for the latter problem, with an approximation factor of 2. finally, we present a new 2-approximation algorithm for multicut on a tree, based on lp-rounding.
enumeration of subtrees of trees. let t be a weighted tree. the weight of a subtree t1 of t is defined as the product of weights of vertices and edges of t1. we obtain a linear-time algorithm to count the sum of weights of subtrees of t. as applications, we characterize the tree with the diameter at least d, which has the maximum number of subtrees, and we characterize the tree with the maximum degree at least δ, which has the minimum number of subtrees.
one head machines from a symbolic approach. we consider the turing machine as a dynamical system and we study a particular partition projection of it. in this way, we define a language (a subshift) associated to each machine. the classical definition of turing machines over a one-dimensional tape is generalized to allow for a tape in the form of a cayley graph. we study the complexity of the language of a machine in terms of realtime recognition by putting it in relation with the structure of its tape. in this way, we find a large set of realtime subshifts some of which are proved not to be deterministic in realtime. sofic subshifts of this class correspond to machines that cannot make arbitrarily large tours. we prove that these machines always have an ultimately periodic behavior when starting with a periodic initial configuration, and this result is proved for any cayley graph.
binary matrices under the microscope: a tomographical problem. a binary matrix can be scanned by moving a fixed rectangular window (sub-matrix) across it, rather like examining it closely under a microscope. with each viewing, a convenient measurement is the number of 1s visible in the window, which might be thought of as the luminosity of the window. the rectangular scan of the binary matrix is then the collection of these luminosities presented in matrix form. we show that, at least in the technical case of a smoothmxn binary matrix, it can be reconstructed from its rectangular scan in polynomial time in the parameters m and n, where the degree of the polynomial depends on the size of the window of inspection. for an arbitrary binary matrix, we then extend this result by determining the entries in its rectangular scan that preclude the smoothness of the matrix.
an efficient alignment algorithm for masked sequences. we consider the alignment problem where sequences may have masked regions. the bases in masked regions are either unspecified or unknown, and they will be denoted by n. we present an efficient algorithm that finds an optimal local alignment by skipping such masked regions of sequences. our algorithm works for both the affine gap penalty model and the linear gap penalty model. the time complexity of our algorithm is o((n-t)(m-s)+vm+wn) time, where n and m are the lengths of given sequences a and b, t and s are the numbers of base n in a and b, and v and w are the numbers of masked regions in a and b, respectively.
on searching a table consistent with division poset. suppose p"n={1,2,...,n} is a partially ordered set with the partial order defined by divisibility, that is, for any two elements i,j@?p"n satisfying i divides j, we have i@?"p"""nj. a table a"n={a"i|i=1,2,...,n} of real numbers is said to be consistent with p"n, provided that for any two elements i,j@?{1,2,...,n} satisfying i divides j, a"i@?a"j. given a real number x, we want to determine whether x@?a"n, by comparing x with as few entries of a"n as possible. in this paper, we investigate the complexity @t(n), measured by the number of comparisons, of the above search problem. we present a 55n72+o(ln^2n) search algorithm for a"n and prove a lower bound (34+172160)n+o(1) on @t(n) using an adversary argument.
solving shortest paths efficiently on nearly acyclic directed graphs. shortest path problems can be solved very efficiently when a directed graph is nearly acyclic. earlier results defined a graph decomposition, now called the 1-dominator set, which consists of a unique collection of acyclic structures with each single acyclic structure dominated by a single associated trigger vertex. in this framework, a specialised shortest path algorithm only spends delete-min operations on trigger vertices, thereby making the computation of shortest paths through non-trigger vertices easier. a previously presented algorithm computed the 1-dominator set in o(mn) worst-case time, which allowed it to be integrated as part of an o(mn+nrlogr) time all-pairs algorithm. here m and n respectively denote the number of edges and vertices in the graph, while r denotes the number of trigger vertices. a new algorithm presented in this paper computes the 1-dominator set in just o(m) time. this can be integrated as part of the o(m+rlogr) time spent solving single-source, improving on the value of r obtained by the earlier tree-decomposition single-source algorithm. in addition, a new bidirectional form of 1-dominator set is presented, which further improves the value of r by defining acyclic structures in both directions over edges in the graph. the bidirectional 1-dominator set can similarly be computed in o(m) time and included as part of the o(m+rlogr) time spent computing single-source. this paper also presents a new all-pairs algorithm under the more general framework where r is defined as the size of any predetermined feedback vertex set of the graph, improving the previous all-pairs time complexity from o(mn+nr^2) to o(mn+r^3).
on the relationship between atsp and the cycle cover problem. in this paper, we study the relationship between the asymmetric traveling salesman problem (atsp) and the cycle cover problem in terms of the strength of the triangle inequality on the edge costs in the given complete directed graph instance, g=(v,e). the strength of the triangle inequality is captured by parametrizing the triangle inequality as follows. a complete directed graph g=(v,e) with a cost function c:e->r^+ is said to satisfy the @c-parametrized triangle inequality if @c(c(u,w)+c(w,v))>=c(u,v) for all distinct u,v,w@?v. then the graph g is called a @c-triangular graph. for any @c-triangular graph g, for @c=1, the ratio atsp(g)ap(g) can become unbounded. the upper bound is shown constructively and can also be viewed as an approximation algorithm for atsp with parametrized triangle inequality. we also consider the following problem: in a @c-triangular graph, does there exist a function f(@c) such that c"m"a"xc"m"i"n is bounded above by f(@c)? (here c"m"a"x and c"m"i"n are the costs of the maximum cost and minimum cost edges respectively.) we show that when @c=13, no such function f(@c) exists.
induced-path partition on graphs with special blocks. in a graph, an induced path is a path v"0,v"1,...,v"r in which a vertex v"i is adjacent to another vertex v"j if and only if |i-j|=1. an induced-path partition of a graph is a collection of vertex-disjoint induced paths that cover all vertices of the graph. the induced-path-partition problem is to determine the minimum cardinality of an induced-path partition of a graph. this paper presents an o(|v|+|e|)-time algorithm for the induced-path-partition problem on graphs whose blocks are complete graphs, cycles or complete bipartite graphs.
obtaining shorter regular expressions from finite-state automata. we consider the use of state elimination to construct shorter regular expressions from finite-state automata (fas). although state elimination is an intuitive method for computing regular expressions from fas, the resulting regular expressions are often very long and complicated. we examine the minimization of fas to obtain shorter expressions first. then, we introduce vertical chopping based on bridge states and horizontal chopping based on the structural properties of given fas. we prove that we should not eliminate bridge states until we eliminate all non-bridge states to obtain shorter regular expressions. in addition, we suggest heuristics for state elimination that leads to shorter regular expressions based on vertical chopping and horizontal chopping.
feasibility and complexity of broadcasting with random transmission failures. fault-tolerant broadcasting in the message passing and radio models is considered under a probabilistic failure model. at each step, the transmitter of each node may fail with fixed constant probability p
quantifier elimination for the reals with a predicate for the powers of two. in 1985, van den dries showed that the theory of the reals with a predicate for the integer powers of two admits quantifier elimination in an expanded language, and is hence decidable. he gave a model-theoretical argument, which provides no apparent bounds on the complexity of a decision procedure. we provide a syntactical argument that yields a procedure that is primitive recursive, although not elementary. in particular, we show that it is possible to eliminate a single block of existential quantifiers in time 2"o"("n")^0, where n is the length of the input formula and 2"k^x denotes k-fold iterated exponentiation.
the left-right-imbalance of binary search trees. we present a detailed study of left-right-imbalance measures for random binary search trees under the random permutation model, i.e., where binary search trees are generated by random permutations of {1,2,...,n}. for random binary search trees of size n we study (i) the difference between the left and the right depth of a randomly chosen node, (ii) the difference between the left and the right depth of a specified node j=j(n), and (iii) the difference between the left and the right pathlength, and show for all three imbalance measures limiting distribution results.
a note on efficient aggregate queries in sensor networks. we consider a scenario where nodes in a sensor network hold numeric items, and the task is to evaluate simple functions of the distributed data. in this note we present distributed protocols for computing the median with sublinear space and communication complexity per node. specifically, we give a deterministic protocol for computing median with polylog complexity and a randomized protocol that computes an approximate median with polyloglog communication complexity per node. on the negative side, we observe that any deterministic protocol that counts the number of distinct data items must have linear complexity in the worst case.
longest common subsequence problem for unoriented and cyclic strings. given a finite set of strings x, the longest common subsequence problem (lcs) consists in finding a subsequence common to all strings in x that is of maximal length. lcs is a central problem in stringology and finds broad applications in text compression, conception of error-detecting codes, or biological sequence comparison. however, in numerous contexts, words represent cyclic or unoriented sequences of symbols and lcs must be generalized to consider both orientations and/or all cyclic shifts of the strings involved. this occurs especially in computational biology when genetic material is sequenced from circular dna or rna molecules. in this work, we define three variants of lcs when the input words are unoriented and/or cyclic. we show that these problems are np-hard, and w[1]-hard if parameterized in the number of input strings. these results still hold even if the three lcs variants are restricted to input languages over a binary alphabet. we also settle the parameterized complexity of our problems for most relevant parameters. moreover, we study the approximability of these problems: we discuss the existence of approximation bounds depending on the cardinality of the alphabet, on the length of the shortest sequence, and on the number of input sequences. for this we prove that maximum independent set in r-uniform hypergraphs is w[1]-hard if parameterized in the cardinality of the sought independent set and at least as hard to approximate as maximum independent set in graphs.
new applications of clique separator decomposition for the maximum weight stable set problem. graph decompositions such as decomposition by clique separators and modular decomposition are of crucial importance for designing efficient graph algorithms. clique separators in graphs were used by tarjan as a divide-and-conquer approach for solving various problems such as the maximum weight stable set (mws) problem, colouring and minimum fill-in. the basic tool is a decomposition tree of the graph whose leaves have no clique separator (so-called atoms), and the problem can be solved efficiently on the graph if it is efficiently solvable on its atoms. we give new examples where the clique separator decomposition works well for the mws problem; our results improve and extend various recently published results. in particular, we describe the atom structure for some new classes of graphs whose atoms are p"5-free (the p"5 is the induced path with five vertices) and obtain new polynomial time results for the mws problem. the complexity of this problem on the class of p"5-free graphs is still unknown.
languages generated by iterated idempotency. duplication languages are generated from an initial word by iterated application of string-rewriting rules of the form u->uu. in several recent articles such languages have been investigated with a main focus on finding their placement in the chomsky hierarchy. we generalize the generating rules to u^m->u^n with arbitrary m and n. when the length of the factor u is a fixed number, most cases result in regular languages. if there is just some bound on the length, then often non-regular but always context-free languages are generated. the regularity conditions for both variants are fully characterized, and confluence for the underlying rewrite relations is determined. for the unrestricted case only some results are presented which carry over from restricted variants.
all minimal prime extensions of hereditary classes of graphs. the substitution composition of two disjoint graphs g"1 and g"2 is obtained by first removing a vertex x from g"2 and then making every vertex in g"1 adjacent to all neighbours of x in g"2. let f be a family of graphs defined by a set z of forbidden configurations. giakoumakis [v. giakoumakis, on the closure of graphs under substitution, discrete mathematics 177 (1997) 83-97] proved that f^*, the closure under substitution of f, can be characterized by a set z^* of forbidden configurations - the minimal prime extensions of z. he also showed that z^* is not necessarily a finite set. since substitution preserves many of the properties of the composed graphs, an important problem is the following: find necessary and sufficient conditions for the finiteness of z^*. giakoumakis [v. giakoumakis, on the closure of graphs under substitution, discrete mathematics 177 (1997) 83-97] presented a sufficient condition for the finiteness of z^* and a simple method for enumerating all its elements. since then, many other researchers have studied various classes of graphs for which the substitution closure can be characterized by a finite set of forbidden configurations. the main contribution of this paper is to completely solve the above problem by characterizing all classes of graphs having a finite number of minimal prime extensions. we then go on to point out a simple way for generating an infinite number of minimal prime extensions for all the other classes of f^*.
well-definedness and semantic type-checking for the nested relational calculus. the well-definedness problem for a programming language consists of checking, given an expression and an input type, whether the semantics of the expression is defined for all inputs adhering to the input type. a related problem is the semantic type-checking problem which consists of checking, given an expression, an input type, and an output type whether the expression always returns outputs adhering to the output type on inputs adhering to the input type. both problems are undecidable for general-purpose programming languages. in this paper we study these problems for the nested relational calculus, a specific-purpose database query language. we also investigate how these problems behave in the presence of programming language features such as singleton coercion and type tests.
conjunctive query evaluation by search-tree revisited. the most natural and perhaps most frequently used method for testing membership of an individual tuple in a conjunctive query is based on searching trees of partial solutions, or search-trees. we investigate the question of evaluating conjunctive queries with a time-bound guarantee that is measured as a function of the size of the optimal search-tree. we provide an algorithm that, given a database d, a conjunctive query q, and a tuple a, tests whether q(a) holds in d in time bounded by a polynomial in (sn)^l^o^g^k(sn)^l^o^g^l^o^g^n and n^r, where n is the size of the domain of the database, k is the number of bound variables of the conjunctive query, s is the size of the optimal search-tree, and r is the maximum arity of the relations. in many cases of interest, this bound is significantly smaller than the n^o^(^k^) bound provided by the naive search-tree method. moreover, our algorithm has the advantage of guaranteeing the bound for any given conjunctive query. in particular, it guarantees the bound for queries that admit an equivalent form that is much easier to evaluate, even when finding such a form is an np-hard task. concrete examples include the conjunctive queries that can be non-trivially folded into a conjunctive query of bounded size or bounded treewidth. all our results translate to the context of constraint-satisfaction problems via the well-publicized correspondence between both frameworks.
connectionist modal logic: representing modalities in neural networks. modal logics are amongst the most successful applied logical systems. neural networks were proved to be effective learning systems. in this paper, we propose to combine the strengths of modal logics and neural networks by introducing connectionist modal logics (cml). cml belongs to the domain of neural-symbolic integration, which concerns the application of problem-specific symbolic knowledge within the neurocomputing paradigm. in cml, one may represent, reason or learn modal logics using a neural network. this is achieved by a modalities algorithm that translates modal logic programs into neural network ensembles. we show that the translation is sound, i.e. the network ensemble computes a fixed-point meaning of the original modal program, acting as a distributed computational model for modal logic. we also show that the fixed-point computation terminates whenever the modal program is well-behaved. finally, we validate cml as a computational model for integrated knowledge representation and learning by applying it to a well-known testbed for distributed knowledge representation. this paves the way for a range of applications on integrated knowledge representation and learning, from practical reasoning to evolving multi-agent systems.
computability of analog networks. we define a general concept of a network of analog modules connected by channels, processing data from a metric space a, and operating with respect to a global continuous clock t. the inputs and outputs of the network are continuous streams u:t->a, and the input-output behaviour of the network with system parameters from a is modelled by a function @f:a^rxc[t,a]^p->c[t,a]^q(p,q>0,r>=0), where c[t,a] is the set of all continuous streams equipped with the compact-open topology. we give an equational specification of the network, and a semantics which involves solving a fixed point equation over c[t,a] using a contraction principle based on the fact that c[t,a] can be approximated locally by metric spaces. we show that if the module functions are continuous then so is the network function @f. we analyse in detail two case studies involving mechanical systems. finally, we introduce a custom-made concrete computation theory over c[t,a] and show that if the module functions are concretely computable then so is @f.
accepting networks of splicing processors: complexity results. in this paper we consider a new, bio-inspired computing model: the accepting network of splicing processors. we define two computational complexity classes based on this model and show how they are related to the classical ones defined for turing machines, namely np and pspace. furthermore, we approach the topic of problem solving using these newly defined devices. in this context, a linear time solution for one of the most interesting np-complete problems, the sat problem, is presented. the results presented here suggest once more that nondeterminism might be approached in a deterministic way by means of multiplicities.
horn axiomatizations for sequential data. we propose a notion of deterministic association rules for ordered data. we prove that our proposed rules can be formally justified by a purely logical characterization, namely, a natural notion of empirical horn approximation for ordered data which involves background horn conditions; these ensure the consistency of the propositional theory obtained with the ordered context. the whole framework resorts to concept lattice models from formal concept analysis, but adapted to ordered contexts. we also discuss a general method to mine these rules that can be easily incorporated into any algorithm for mining closed sequences, of which there are already some in the literature.
can newtonian systems, bounded in space, time, mass and energy compute all functions? in the theoretical analysis of the physical basis of computation there is a great deal of confusion and controversy (e.g., on the existence of hyper-computers). first, we present a methodology for making a theoretical analysis of computation by physical systems. we focus on the construction and analysis of simple examples that are models of simple sub-theories of physical theories. then we illustrate the methodology by presenting a simple example for newtonian kinematics, and a critique that leads to a substantial extension of the methodology. the example proves that for any set a of natural numbers there exists a 3-dimensional newtonian kinematic system m"a, with an infinite family of particles p"n whose total mass is bounded, and whose observable behaviour can decide whether or not n@?a for all n@?n in constant time. in particular, the example implies that simple newtonian kinematic systems that are bounded in space, time, mass and energy can compute all possible sets and functions on discrete data. the system is a form of marble run and is a model of a small fragment of newtonian kinematics. next, we use the example to extend the methodology. the marble run shows that a formal theory for computation by physical systems needs strong conditions on the notion of experimental procedure and, specifically, on methods for the construction of equipment. we propose to extend the methodology by defining languages to express experimental procedures and the construction of equipment. we conjecture that the functions computed by experimental computation in newtonian kinematics are ''equivalent'' to those computed by algorithms, i.e. the partial computable functions.
on the structure and complexity of worst-case equilibria. in the resource allocation game introduced by koutsoupias and papadimitriou, n jobs of different weights are assigned to m identical machines by selfish agents. for this game, it has been conjectured by several authors that the fully mixed nash equilibrium (fmne) is the worst possible w.r.t. the expected maximum load over all machines. assuming the validity of this conjecture, computing a worst-case nash equilibrium for a given instance was trivial, and approximating the price of anarchy for this instance would be possible by approximating the expected social cost of the fmne by applying a known fpras. we present a counter-example to this conjecture showing that fully mixed nash equilibria cannot be used to approximate the price of anarchy. we show that the factor between the social cost of the worst nash equilibrium and the social cost of the fmne can be as large as the price of anarchy itself, up to a constant factor. in addition, we present an algorithm that constructs so-called concentrated equilibria that approximate the worst-case nash equilibria within constant factors.
rewriting queries using views with access patterns under integrity constraints. we study the problem of rewriting queries using views in the presence of access patterns, integrity constraints, disjunction and negation. we provide asymptotically optimal algorithms for (1) finding minimally containing and (2) maximally contained rewritings respecting the access patterns (which we call executable) and for (3) deciding whether an exact executable rewriting exists. we show that rewriting queries using views in this case reduces (a) to rewriting queries with access patterns and constraints without views and also (b) to rewriting queries using views under constraints without access patterns. we show how to solve (a) directly and how to reduce (b) to rewriting queries under constraints only (semantic optimization). these reductions provide two separate routes to a unified solution for problems 1, 2 and 3 based on an extension of the relational chase theory to queries and constraints with disjunction and negation. we also handle equality and arithmetic comparisons. we also show that in an information integration setting, maximally contained rewritings are given by the certain answers (under the usual semantics) for a set of constraints derived from the binding patterns. that is, except for defining the appropriate constraints, binding patterns do not need special treatment. finally, we show that if there is an exact executable rewriting, there is an executable rewriting which is a union of conjunctive queries with negation.
a note on discreteness and virtuality in analog computing. the need for physically motivated discreteness and finiteness conditions emerges in models of both analog and digital computing that are genuinely concerned with physically realizable computational processes. this is brought out by a critical examination of notional analog superturing devices which involve physically untenable idealizations about the perfect functioning of analog apparatuses and infinite precision of physical measurements. the capability for virtual behaviour, that is, the capability of interpreting, storing, transforming, creating the code, and thereby mimicking the behaviour of (turing) machines, is used here to introduce a new dimension in the discussion of the analog-digital watershed. in the light of recent results on the analog simulation of digital computing, we examine the role of virtuality as a discriminating factor between these two species of computing, and immerse this problem in the context of natural computing. is virtuality instantiated in parts of the natural world other than computer technology? this broad issue is examined in connection with the computational modelling of brain and mental information processing.
quorum sensing p systems. this paper continues the investigation of population p systems model [f. bernardini, m. gheorghe, population p systems, journal of universal computer science 10 (5) (2004) 509-539] by considering bacterium quorum sensing (qs) phenomena as the basis of the new approach. a new computational model called qs p system is introduced. it is proved that qs p systems are able to simulate counter machines, and hence they are equivalent in power to turing machines. an example of a qs p system modelling the behaviour of vibrio fischeri bacteria colonies is also presented and the emergence of the qs mechanism is illustrated.
influence of data dimensionality on the quality of forecasts given by a multilayer perceptron. one of the phenomena that can be observed when using neural networks for time series prediction is that the quality of the forecasts obtained is correlated with the dimensionality of the data. higher data dimensionality leads, in most cases, to higher prediction errors. this phenomenon is connected by some authors to the decrease in variance of the distances between the data points, which occurs when the lengths of the predicted vectors increase. in this paper, a proof is given that the variance of the distances between data points also decreases with the so-called correlation dimension of the data. therefore, a drop in forecast quality might be expected not only when the lengths of the data vectors are increased, but also when using vectors of the same length to represent data of increasing dimensionality. we also present some experimental results that illustrate the dependence between data dimensionality and the variance of the distances between the data points, and the forecast error obtained when using a multilayer perceptron to predict future values of some time series.
optimal workload-based weighted wavelet synopses. in recent years wavelets were shown to be effective data synopses. we are concerned with the problem of finding efficiently wavelet synopses for massive data sets, in situations where information about query workload is available. we present linear time, i/o optimal algorithms for building optimal workload-based wavelet synopses for point queries. the synopses are based on a novel construction of weighted inner products and use weighted wavelets that are adapted to those products. the synopses are optimal in the sense that the subset of retained coefficients is the best possible for the bases in use with respect to either the mean-squared absolute or relative errors. for the latter, this is the first optimal wavelet synopsis even for the regular, non-workload-based case. experimental results demonstrate the advantage obtained by the new optimal wavelet synopses.
view-based query processing: on the relationship between rewriting, answering and losslessness. as a result of the extensive research in view-based query processing, three notions have been identified as fundamental, namely rewriting, answering, and losslessness. answering amounts to computing the tuples satisfying the query in all databases consistent with the views. rewriting consists in first reformulating the query in terms of the views and then evaluating the rewriting over the view extensions. losslessness holds if we can answer the query by solely relying on the content of the views. while the mutual relationship between these three notions is easy to identify in the case of conjunctive queries, the terrain of notions gets considerably more complicated going beyond such a query class. in this paper, we revisit the notions of answering, rewriting, and losslessness and clarify their relationship in the setting of semistructured databases, and in particular for the basic query class in this setting, i.e., two-way regular path queries. our first result is a clean explanation of the relationship between answering and rewriting, in which we characterize rewriting as a ''linear approximation'' of query answering. we show that applying this linear approximation to the constraint-satisfaction framework yields an elegant automata-theoretic approach to query rewriting. as for losslessness, we show that there are indeed two distinct interpretations for this notion, namely with respect to answering, and with respect to rewriting. we also show that the constraint-theoretic approach and the automata-theoretic approach can be combined to give algorithmic characterization of the various facets of losslessness. finally, we deal with the problem of coping with loss, by considering mechanisms aimed at explaining lossiness to the user.
universality results for p systems based on brane calculi operations. operations with membranes are essential both in brane calculi as well as in membrane computing. in this paper, we attempt to express six basic operations of brane calculi, viz., pino, exo, phago, bud, mate, drip in terms of the membrane computing formalism. we also investigate the computing power of p systems controlled by phago/exo, pino/exo, bud/mate as well as the mate/drip operations. we give an improvement to a characterization of re using mate/drip operations given in [l. cardelli, gh. paun, an universality result based on mate/drip operations, international journal of foundations of computer science (in press)]. we also give a characterization of re using a new operation, called selective mate. we conjecture that it is not possible to obtain turing completeness using only one of the six operations. we also conjecture that the pairs of operations we have considered for completeness, in this paper, are complete: it is impossible to obtain turing completeness with any other pair of operations.
axiomatizing the identities of binoid languages. we present a nontrivial axiomatization for the equational theory of binoid languages, the subsets of a free binoid. in doing so, we prove that a conjecture given in our previous paper was true: the identical laws of ordinary (string) languages, written separately using 'horizontal' and 'vertical' operation symbols form a required complete system of axioms.
quasiperiodic sturmian words and morphisms. we characterize all quasiperiodic sturmian words: a sturmian word is not quasiperiodic if and only if it is a lyndon word. moreover, we study links between sturmian morphisms and quasiperiodicity.
using well-structured transition systems to decide divergence for catalytic p systems. p systems are a biologically inspired model introduced by gheorghe paun with the aim of representing the structure and the functioning of the cell. since their introduction, several variants of p systems have been proposed and explored. we concentrate on the class of catalytic p systems without priorities associated with the rules. we show that the theory of well-structured transition systems can be used to decide the divergence problem (i.e. checking for the existence of an infinite computation) for such a class of p systems. as a corollary, we obtain an alternative proof of the nonuniversality of deterministic catalytic p systems, an open problem recently solved by ibarra and yen.
convergence analysis of the ojan mca learning algorithm by the deterministic discrete time method. minor component analysis (mca) is a statistical method of extracting the eigenvector associated with the smallest eigenvalue of the covariance matrix of input signals. convergence is essential for mca algorithms towards practical applications. traditionally, the convergence of mca algorithms is indirectly analyzed via their corresponding deterministic continuous time (dct) systems. however, the dct method requires the learning rate to approach zero, which is not reasonable in many applications due to the round-off limitation and tracking requirements. this paper studies the convergence of the deterministic discrete time (ddt) system associated with the ojan mca learning algorithm. unlike the dct method, the ddt method does not require the learning rate to approach zero. in this paper, some important convergence results are obtained for the ojan mca learning algorithm via the ddt method. simulations are carried out to illustrate the theoretical results achieved.
on rearrangeable multirate three-stage clos networks. since 1989 when melen and turner introduced an elegant model for interconnection networks that carry multirate traffic, the theory and applications of the three-stage clos network has been extended from circuit switching to the multirate environment. chung and ross conjectured that c(n,2n-1,r) is rearrangeable if each call has weight chosen from a given set of k weights. lin et al. confirmed the conjecture for a restricted discrete bandwidth case only. in this paper we show that the conjecture of chung and ross holds not only in the discrete bandwidth case but also in the continuous bandwidth case for r@?2n5-235.
optimal semi-online algorithms for machine covering. this paper investigates the semi-online machine covering problems on m>=3 parallel identical machines. three different semi-online versions are studied and optimal algorithms are proposed. we prove that if the total processing time of all jobs or the largest processing time of all jobs is known in advance, the competitive ratios of the optimal algorithms are both m-1. if the total processing time and the largest processing time of all jobs are both known in advance, the competitive ratios of the optimal algorithms are 32 when m=3, and m-2 when m>=4.
on the membership of invertible diagonal and scalar matrices. in this paper, we consider decidability questions that are related to the membership problem in matrix semigroups. in particular, we consider the membership of a given invertible diagonal matrix in a matrix semigroup and then a scalar matrix, which has a separate geometric interpretation. both problems have been open for any dimensions and are shown to be undecidable in dimension 4 with integral matrices by a reduction of the post correspondence problem (pcp). although the idea of pcp reduction is standard for such problems, we suggest a new coding technique to cover the case of diagonal matrices.
multiset random context grammars, checkers, and transducers. we introduce a general model of random context multiset grammars as well as the concept of multiset random context checkers and transducers. our main results show how recursively enumerable sets of finite multisets can be generated using these models of computing; corresponding results for antiport p systems are established, too.
three "quantum" algorithms to solve 3-sat. in this paper we borrow some ideas from quantum computing, and we propose three ''quantum'' brute force algorithms to solve the 3-sat np-complete decision problem. the first algorithm builds, for any instance @f of 3-sat, a quantum fredkin circuit that computes a superposition of all classical evaluations of @f in a given output line. similarly, the second and third algorithms compute the same superposition on a given register of a quantum register machine, and as the energy of a given membrane in a quantum p system, respectively. assuming that a specific non-unitary operator, built using a truncated version of the well known creation and annihilation operators, can be realized as a quantum gate, as an instruction of the quantum register machine, and as a rule of the quantum p system, respectively, we show how to decide whether @f is a positive instance of 3-sat. the construction relies also upon the assumption that an external observer is able to discriminate, as the result of a measurement, a null vector from a non-null vector.
a simple storage scheme for strings achieving entropy bounds. we propose a storage scheme for a string s[1, n], drawn from an alphabet &sigma;, that requires space close to the &kappa;-th order empirical entropy of s, and allows to retrieve any l-long substring of s in optimal o(1+l/log|&sum;|n) time. this matches the best known bounds [14, 7], via the use of binary encodings and tables only. we also apply this storage scheme to prove new time vs space trade-offs for compressed self-indexes [5, 12] and the burrows-wheeler transform [2].
minimum cost source location problem with local 3-vertex-connectivity requirements. let g=(v,e) be a simple undirected graph with a set v of vertices and a set e of edges. each vertex v@?v has a demand d(v)@?z"+ and a cost c(v)@?r"+, where z"+ and r"+ denote the set of nonnegative integers and the set of nonnegative reals, respectively. the source location problem with vertex-connectivity requirements in a given graph g requires finding a set s of vertices minimizing @?"v"@?"sc(v) such that there are at least d(v) pairwise vertex-disjoint paths from s to v for each vertex v@?v-s. it is known that if there exists a vertex v@?v with d(v)>=4, then the problem is np-hard even in the case where every vertex has a uniform cost. in this paper, we show that the problem can be solved in o(|v|^4log^2|v|) time if d(v)@?3 holds for each vertex v@?v.
normal forms for spiking neural p systems. the spiking neural p systems are a class of computing devices recently introduced as a bridge between spiking neural nets and membrane computing. in this paper we prove a series of normal forms for spiking neural p systems, concerning the regular expressions used in the firing rules, the delay between firing and spiking, the forgetting rules used, and the outdegree of the graph of synapses. in all cases, surprising simplifications are found, without losing the computational completeness - sometimes at the price of (slightly) increasing other parameters which describe the complexity of these systems.
cycles and communicating classes in membrane systems and molecular dynamics. we are considering sequential membrane systems and molecular dynamics from the viewpoint of markov chain theory. the configuration space of these systems (including the transitions) is a special kind of directed graph, called a pseudo-lattice digraph, which is closely related to the stoichiometric matrix. taking advantage of the monoidal structure of this space, we introduce the algebraic notion of precycle. a precycle leads to the identification of cycles by means of the concept of defect, which is a set of geometric constraints on configuration space. two efficient algorithms for evaluating precycles and defects are given: one is an algorithm due to contejean and devie, the other is a novel branch-and-bound tree search procedure. cycles partition configuration space into equivalence classes, called the communicating classes. the structure of the communicating classes in the free regime-where all rules are enabled-is analyzed: testing for communication can be done efficiently. we show how to apply these ideas to a biological regulatory system.
on small universal antiport p systems. it is known that p systems with antiport rules simulate register machines, i.e., they are computationally complete. hence, due to the existence of universal register machines, there exist computationally complete subclasses of antiport p systems with bounded size, i.e., systems where each size parameter is limited by some constant. however, so far there has been no estimation of these numbers given in the literature. in this article, three universal antiport p systems of bounded size are demonstrated, different from each other in their size parameters. we present universal antiport p systems with 73, 43, and 30 rules where the maximum of the weight of the rules is 4, 5, and 6, respectively.
optimal trade-off for merkle tree traversal. in this paper we describe optimal trade-offs between time and space complexity of merkle tree traversals with their associated authentication paths, improving on the previous results of m. jakobsson, t. leighton, s. micali, and m. szydlo [fractal merkle tree representation and traversal, in: rsa cryptographers track, rsa security conference, 2003] and m. szydlo [merkle tree traversal in log space and time, in: proc. eurocrypt, in: lncs, vol. 3027, 2004, pp. 541-554; merkle tree traversal in log space and time, preprint version 2003, available at http://www.szydlo.com]. in particular, we show that our algorithm requires 2logn/log^(^3^)n hash function computations and storage for less than (logn/log^(^3^)n+1)loglogn+2logn hash values, where n is the number of leaves in the merkle tree. we also prove that these trade-offs are optimal, i.e. there is no algorithm that requires less than o(logn/logt) time and less than o(tlogn/logt) space for any choice of parameter t>=2. our algorithm could be of special interest in the case when both time and space are limited.
reallife: the continuum limit of larger than life cellular automata. let a@?{0,1}. a cellular automaton (ca) is a shift-commuting transformation of a^z^^^d determined by a local rule. likewise, a euclidean automaton (ea) is a shift-commuting transformation of a^r^^^d determined by a local rule. larger than life (ltl) ca are long-range generalizations of j.h. conway's game of life ca, proposed by k.m. evans. we prove a conjecture of evans: as their radius grows to infinity, ltl ca converge to a 'continuum limit' ea, which we call reallife. we also show that the life forms (fixed points, periodic orbits, and propagating structures) of ltl ca converge to life forms of reallife. finally we prove a number of existence results for fixed points of reallife.
discrete solutions to differential equations by metabolic p systems. the relationships existing between metabolic p systems and ode systems are investigated. formal results show that every mp system determines a structure, called an mp graph, which results in an ode system whose solution equals, in the limit, the evolution of any non-cooperative mp system that can be derived from the initial one by means of a systematic procedure. examples based on the model of a mitotic oscillator in early amphibian embryos, the lotka-volterra predator-prey population dynamics, and the lorenz strange attractor are provided, showing the applicability of the proposed computational approach.
an efficient identity-based key exchange protocol with kgs forward secrecy for low-power devices. for an id-based key exchange (ke) protocol, kgs forward secrecy is about the protection of previously established session keys after the master secret key of the key generation server (kgs) is compromised. this is the strongest notion of forward secrecy that one can provide for an id-based ke protocol. among all the comparable protocols, there are only a few of them that provide this level of forward secrecy, and all of these protocols require expensive bilinear pairing operations and map-to-point hash operations that may not be suitable for implementation on low-power devices such as sensors. in this paper, we propose a new id-based ke protocol which does not need any pairing or map-to-point hash operations. it also supports the strongest kgs forward secrecy. on its performance, we show that it is faster than previously proposed protocols in this category. our protocol is a signature-based one, in which the signature scheme is a variant of a scheme proposed by bellare et al. in eurocrypt 2004. we show that the variant we proposed is secure, and also requires either less storage space or runtime computation than the original scheme.
smoothed analysis of binary search trees. binary search trees are one of the most fundamental data structures. while the height of such a tree may be linear in the worst case, the average height with respect to the uniform distribution is only logarithmic. the exact value is one of the best studied problems in average-case complexity. we investigate what happens in between by analysing the smoothed height of binary search trees: randomly perturb a given (adversarial) sequence and then take the expected height of the binary search tree generated by the resulting sequence. as perturbation models, we consider partial permutations, partial alterations, and partial deletions. on the one hand, we prove tight lower and upper bounds of roughly @q((1-p)@?n/p) for the expected height of binary search trees under partial permutations and partial alterations, where n is the number of elements and p is the smoothing parameter. this means that worst-case instances are rare and disappear under slight perturbations. on the other hand, we examine how much a perturbation can increase the height of a binary search tree, i.e. how much worse well balanced instances can become.
on the degree of parallelism in membrane systems. in the literature, several designs of p systems might be found for performing the same task. the use of different techniques or even different p system models makes it very difficult to compare these designs. in this paper, we introduce a new criterion for such a comparison: the degree of parallelism of a p system. with this aim, we define the labelled dependency graph associated with a p system, and we use this new concept for proving some results concerning the maximum number of applications of rules in a single step through the computation of a p system.
learning of erasing primitive formal systems from positive examples. the present paper considers the learning problem of erasing primitive formal systems, pfss for short, in view of inductive inference in gold framework from positive examples. a pfs is a kind of logic program over strings called regular patterns, and consists of exactly two axioms of the forms p(π) ← and p(τ) ← p(x1),..., p(xn), where p is a unary predicate symbol, π and τ are regular patterns, and xis are distinct variables. a pfs is erasing or nonerasing according to allowing the empty string substitution for some variables or not. we investigate the learnability of the class pfsl of languages generated by the erasing pfss satisfying a certain condition. we first show that the class pfsl has m-finite thickness. moriyama and sato showed that a language class with m-finite thickness is learnable if and only if there is a finite tell tale set for each language in the class. we then introduce a particular type of finite set of strings for each erasing pfs, and show that the set is a finite tell tale set of the language. these imply that the class pfsl is learnable from positive examples.
from learning in the limit to stochastic finite learning. inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. we survey results recently obtained and show their impact to potential applications.since the main focus is put on the efficiency of learning, we also deal with postulates of naturalness and their impact to the efficiency of limit learners. in particular, we look at the learnability of the class of all pattern languages and ask whether or not one can design a learner within the paradigm of learning in the limit that is nevertheless efficient.for achieving this goal, we deal with iterative learning and its interplay with the hypothesis spaces allowed. this interplay has also a severe impact to postulates of naturalness satisfiable by any learner.furthermore, since a limit learner is only supposed to converge, one never knows at any particular learning stage whether or not the learner did already succeed. the resulting uncertainty may be prohibitive in many applications. we survey results to resolve this problem by outlining a new learning model, called stochastic finite learning. though pattern languages can neither be finitely inferred from positive data nor pac-learned, our approach can be extended to a stochastic finite learner that exactly infers all pattern languages from positive data with high confidence.finally, we apply the techniques developed to the problem of learning conjunctive concepts.
on generalized computable universal priors and their convergence. solomonoff unified occam's razor and epicurus' principle of multiple explanations to one elegant, formal, universal theory of inductive inference, which initiated the field of algorithmic information theory. his central result is that the posterior of the universal semimeasure m converges rapidly to the true sequence generating posterior µ, if the latter is computable. hence, m is eligible as a universal predictor in case of unknown µ. the first part of the paper investigates the existence and convergence of computable universal (semi) measures for a hierarchy of computability classes: recursive, estimable, enumerable, and approximable. for instance, m is known to be enumerable, but not estimable, and to dominate all enumerable semimeasures. we present proofs for discrete and continuous semimeasures. the second part investigates more closely the types of convergence, possibly implied by universality: in difference and in ratio, with probability 1, in mean sum, and for martin-löf random sequences. we introduce a generalized concept of randomness for individual sequences and use it to exhibit difficulties regarding these issues. in particular, we show that convergence fails (holds) on generalized-random sequences in gappy (dense) bernoulli classes.
an approach to intrinsic complexity of uniform learning. inductive inference is concerned with algorithmic learning of recursive functions. in the model of learning in the limit a learner successful for a class of recursive functions must eventually find a program for any function in the class from a gradually growing sequence of its values. this approach is generalised in uniform learning, where the problem of synthesising a successful learner for a class of functions from a description of this class is considered.a common reduction-based approach for comparing the complexity of learning problems in inductive inference is intrinsic complexity. informally, if a learning problem (a class of recursive functions) a is reducible to a learning problem (a class of recursive functions) b, then a solution for b can be transformed into a solution for a. in the context of intrinsic complexity, reducibility between two classes is expressed via recursive operators transforming target functions in one direction and sequences of corresponding hypotheses in the other direction.the present paper is concerned with intrinsic complexity of uniform learning. the relevant notions are adapted and illustrated by several examples. characterisations of complete classes finally allow for various insightful conclusions. the connection to intrinsic complexity of non-uniform learning is revealed within several analogies concerning first the structure of complete classes and second the general interpretation of the notion of intrinsic complexity.
learning a subclass of regular patterns in polynomial time. an algorithm for learning a subclass of erasing regular pattern languages is presented. on extended regular pattern languages generated by patterns π of the form x0α1x1... αmxm, where x0,..., xm are variables and α1,..., αm strings of terminals of length c each, it runs with arbitrarily high probability of success using a number of examples polynomial in m (and exponential in c). it is assumed that m is unknown, but c is known and that samples are randomly drawn according to some distribution, for which we only require that it has certain natural and plausible properties.aiming to improve this algorithm further we also explore computer simulations of a heuristic.
signal extraction and knowledge discovery based on statistical modeling. in the coming post it era, the problems of signal extraction and knowledge discovery from huge data sets will become very important. for these problems, the use of good model is crucial and thus the statistical modeling will play an important role. in this paper, we show two basic tools for statistical modeling, namely the information criteria for the evaluation of the statistical models and generic state-space model which provides us with a very flexible tool for modeling complex and time-varying systems. as examples of these methods we shall show some applications in seismology and macro economics.
on ordinal vc-dimension and some notions of complexity. we generalize the classical notion of vapnik-chernovenkis (vc) dimension to ordinal vc-dimension, in the context of logical learning paradigms. logical learning paradigms encompass the numerical learning paradigms commonly studied in inductive inference. a logical learning paradigm is defined as a set w of structures over some vocabulary, and a set d of first-order formulas that represent data. the sets of models of ϕ in w, where ϕ varies over d, generate a natural topology w over w.we show that if d is closed under boolean operators, then the notion of ordinal vc-dimension offers a perfect characterization for the problem of predicting the truth of the members of d in a member of w, with an ordinal bound on the number of mistakes. this shows that the notion of vc-dimension has a natural interpretation in inductive inference, when cast into a logical setting. we also study the relationships between predictive complexity, selective complexity--a variation on predictive complexity--and mind change complexity. the assumptions that d is closed under boolean operators and that w is compact often play a crucial role to establish connections between these concepts.we then consider a computable setting with effective versions of the complexity measures, and show that the equivalence between ordinal vc-dimension and predictive complexity fails. more precisely, we prove that the effective ordinal vc-dimension of a paradigm can be defined when all other effective notions of complexity are undefined. on a better note, when w is compact, all effective notions of complexity are defined, though they are not related as in the noncomputable version of the framework.
well-calibrated predictions from on-line compression models. it has been shown recently that transductive confidence machine (tcm) is automatically well-calibrated when used in the on-line mode and provided that the data sequence is generated by an exchangeable distribution. in this paper we strengthen this result by relaxing the assumption of exchangeability of the data-generating distribution to the much weaker assumption that the data agrees with a given "on-line compression model".
criterion of calibration for transductive confidence machine with limited feedback. this paper is concerned with the problem of on-line prediction in the situation where some data are unlabelled and can never be used for prediction, and even when the data are labelled, the labels may arrive with a delay. we construct a modification of randomised transductive confidence machine for this case and prove a necessary and sufficient condition for its predictions being calibrated, in the sense that in the long run they are wrong with a prespecified probability under the assumption that the data are generated independently by the same distribution. the condition for calibration turns out to be very weak: feedback should be given on more than a logarithmic fraction of steps.
conjunction on processes: full abstraction via ready-tree semantics. a key problem in mixing operational (e.g. process-algebraic) and declarative (e.g. logical) styles of specification is how to deal with inconsistencies arising when composing processes under conjunction. this article introduces a conjunction operator on labelled transition systems capturing the basic intuition of 'a and b = false', and considers a naive preorder that demands that an inconsistent specification can only be refined by an inconsistent implementation. the main body of the article is concerned with characterizing the largest precongruence contained in the naive preorder. this characterization will be based on what we call ready-tree semantics, which is a variant of path-based possible-worlds semantics. we prove that the induced ready-tree preorder is compositional and fully abstract, and that the conjunction operator indeed reflects conjunction. the article's results provide a foundation for, and an important step towards a unified framework that allows one to freely mix operators from process algebras and linear-time temporal logics.
towards "dynamic domains": totally continuous cocomplete -categories. it is common practice in both theoretical computer science and theoretical physics to describe the (static) logic of a system by means of a complete lattice. when formalizing the dynamics of such a system, the updates of that system organize themselves quite naturally in a quantale, or more generally, a quantaloid. in fact, we are led to consider cocomplete quantaloid-enriched categories as a fundamental mathematical structure for a dynamic logic common to both computer science and physics. here we explain the theory of totally continuous cocomplete categories as a generalization of the well-known theory of totally continuous suplattices. that is to say, we undertake some first steps towards a theory of ''dynamic domains''.
reflection in membership equational logic, many-sorted equational logic, horn logic with equality, and rewriting logic. we show that the generalized variant of formal systems where the underlying equational specifications are membership equational theories, and where the rules are conditional and can have equations, memberships and rewrites in the conditions is reflective. we also show that membership equational logic, many-sorted equational logic, and horn logic with equality are likewise reflective. these results provide logical foundations for reflective languages and tools based on these logics.
axiomatizations for probabilistic finite-state behaviors. we study a process calculus which combines both nondeterministic and probabilistic behavior in the style of segala and lynch's probabilistic automata. we consider various strong and weak behavioral equivalences, and we provide complete axiomatizations for finite-state processes, restricted to guarded recursion in case of the weak equivalences. we conjecture that in the general case of unguarded recursion the ''natural'' weak equivalences are undecidable. this is the first work, to our knowledge, that provides a complete axiomatization for weak equivalences in the presence of recursion and both nondeterministic and probabilistic choice.
compact and tractable automaton-based representations of time granularities. most approaches to time granularity proposed in the literature are based on algebraic and logical formalisms [j. euzenat, a. montanari, time granularity, in: m. fisher, d. gabbay, l. vila (eds.), handbook of temporal reasoning in artificial intelligence, elsevier, 2005, pp. 59-118]. here we follow an alternative automaton-based approach, originally outlined in [u. dal lago, a. montanari, calendars, time granularities, and automata, in: proceedings of the 7th international symposium on spatial and temporal databases, sstd, in: lncs, vol. 2121, springer, 2001, pp. 279-298], which makes it possible to deal with infinite time granularities in an effective and efficient way. such an approach provides a neat solution to fundamental algorithmic problems, such as the granularity equivalence and granule conversion problems, which have been often neglected in the literature. in this paper, we focus our attention on two basic optimization problems for the automaton-based representation of time granularities, namely, the problem of computing the smallest representation of a time granularity and that of computing the most tractable representation of it, that is, the one on which crucial algorithms, such as granule conversion algorithms, run fastest.
space-aware ambients and processes. resource control has attracted increasing interest in foundational research on distributed systems. this paper focuses on space control and develops an analysis of space usage in the context of an ambient calculus with bounded capacities and weighed processes, where migration and activation require space. a type system controls the dynamics of the calculus by providing static guarantees that the intended capacity bounds are preserved throughout the computation. we investigate various term-level mechanisms to complement the typed control on the dynamics of space allocation and acquisition, and study their consequences on the semantic theory of the calculus.
equivalence of linear, free, liberal, structured program schemas is decidable in polynomial time. a program schema defines a class of programs, all of which have identical statement structure, but whose expressions may differ. we define a class of syntactic similarity binary relations between linear structured schemas, which characterise schema equivalence for structured schemas that are linear, free and liberal. in this paper we report that similarity implies equivalence for linear schemas, and that a near-converse holds for schemas that are linear, free and liberal. we also show that the similarity of two linear schemas is polynomial-time decidable. our main result considerably extends the class of program schemas for which equivalence is known to be decidable, and suggests that linearity is a constraint worthy of further investigation.
a compositional natural semantics and hoare logic for low-level languages. the advent of proof-carrying code has generated significant interest in reasoning about low-level languages. it is widely believed that low-level languages with jumps must be difficult to reason about because of being inherently non-modular. we argue that this is untrue. we take it seriously that, unlike statements of a high-level language, pieces of low-level code are multiple-entry and multiple-exit. and we define a piece of code as consisting of either a single labelled instruction or a finite union of pieces of code. thus we obtain a compositional natural semantics and a matching hoare logic for a basic low-level language with jumps. by their simplicity and intuitiveness, these are comparable to the standard natural semantics and hoare logic of while. the hoare logic is sound and complete wrt the semantics and allows for compilation of proofs of the hoare logic of while.
polynomial time algorithm for an optimal stable assignment with multiple partners. this paper considers the many-to-many version of the stable marriage problem where each man and woman has a strict preference ordering on the members of the opposite sex that he or she considers acceptable. further, each man and woman wishes to be matched to as many acceptable partners as possible, up to his or her specified quota. in this setup, a polynomial time algorithm for finding a stable matching that minimizes the sum of partner ranks across all men and women is provided. it is argued that this sum can be used as an optimality criterion for minimizing total dissatisfaction if the preferences over partner-combinations satisfy a no-complementarities condition. the results in this paper extend those already known for the one-to-one version of the problem.
adding recursion to dpi. dpi is a distributed version of the pi-calculus, in which processes are explicitly located, and a migration construct may be used for moving between locations. we argue that adding a recursion operator to the language increases significantly its descriptive power. but typing recursive processes requires the use of potentially infinite types. we show that the capability-based typing system of dpi can be extended to co-inductive types so that recursive processes can be successfully supported. we also show that, as in the pi-calculus, recursion can be implemented via iteration. this translation improves on the standard ones by being compositional but still requires co-inductive types and comes with a significant migration overhead in our distributed setting.
a rewriting logic framework for operational semantics of membrane systems. existing results in membrane computing refer mainly to p systems' characterization of turing computability, also to some polynomial solutions to np-complete problems by using an exponential workspace created in a ''biological way''. in this paper we define an operational semantics of a basic class of p systems, and give two implementations of the operational semantics using rewriting logic. we present some results regarding these implementations, including two operational correspondence results, and discuss why these implementations are relevant in order to take advantage of good features of both structural operational semantics and rewriting logic.
the rewriting logic semantics project. rewriting logic is a flexible and expressive logical framework that unifies algebraic denotational semantics and structural operational semantics (sos) in a novel way, avoiding their respective limitations and allowing succinct semantic definitions. the fact that a rewrite logic theory's axioms include both equations and rewrite rules provides a useful ''abstraction dial'' to find the right balance between abstraction and computational observability in semantic definitions. such semantic definitions are directly executable as interpreters in a rewriting logic language such as maude, whose generic formal tools can be used to endow those interpreters with powerful program analysis capabilities.
generating labeled planar graphs uniformly at random. we present a deterministic polynomial time algorithm to sample a labeled planar graph uniformly at random. our approach uses recursive formulae for the exact number of labeled planar graphs with n vertices and m edges, based on a decomposition into 1-, 2-, and 3-connected components. we can then use known sampling algorithms and counting formulae for 3-connected planar graphs.
hybrid commitments and their applications to zero-knowledge proof systems. we introduce the notion of hybrid trapdoor commitment schemes. intuitively a hybrid trapdoor commitment scheme is a primitive which can be either an unconditionally binding commitment scheme or a trapdoor commitment scheme depending on the distribution of commitment parameters. moreover, such two possible distributions are computationally indistinguishable. hybrid trapdoor commitments are related but different with respect to mixed commitments (introduced by damgard and nielsen at crypto 2002). in particular hybrid trapdoor commitments can either be polynomially trapdoor commitments or unconditionally binding commitments, while mixed commitments can be either trapdoor commitments or extractable commitments. in this paper we show that strong notions (e.g., simulation sound, multi-trapdoor) of hybrid trapdoor commitments admit constructions based on the sole assumption that one-way functions exist as well as efficient constructions based on standard number-theoretic assumptions. to further stress the difference between hybrid and mixed commitments, we remark here that mixed commitments seem to require stronger theoretical assumptions (and the known number-theoretic constructions are less efficient). our main result, is to show how to construct concurrent and simulation-sound zero-knowledge proof systems (in contrast to the arguments recently presented in [i. damgard, efficient concurrent zero-knowledge in the auxiliary string model, in: advances in cryptology - eurocrypt'00, in: lecture notes in computer science, vol. 1807, springer-verlag, 2000, pp. 418-430; p. mackenzie, k. yang, on simulation-sound trapdoor commitments, in: advances in cryptology - eurocrypt'04, in: lecture notes in computer science, vol. 3027, springer-verlag, 2004, pp. 382-400; r. gennaro, multi-trapdoor commitments and their applications to proofs of knowledge secure under concurrent man-in-the-middle attacks, in: advances in cryptology - crypto'04, in: lecture notes in computer science, vol. 3152, springer-verlag, 2004, pp. 220-236]) in the common reference string model. we crucially use hybrid trapdoor commitments since we present general constructions based on the sole assumption that one-way functions exist and very efficient constructions based on number-theoretic assumptions.
characterizations of recognizable picture series. the theory of two-dimensional languages as a generalization of formal string languages was motivated by problems arising from image processing and pattern recognition, and also concerns models of parallel computing. here we investigate power series on pictures. these are functions that map pictures to elements of a semiring and provide an extension of two-dimensional languages to a quantitative setting. we assign weights to different devices, ranging from picture automata to tiling systems. we will prove that, for commutative semirings, the behaviours of weighted picture automata are precisely alphabetic projections of series defined in terms of rational operations, and also coincide with the families of series characterized by weighted tiling or weighted domino systems.
approximating the maximum clique minor and some subgraph homeomorphism problems. we consider the ''minor'' and ''homeomorphic'' analogues of the maximum clique problem, i.e., the problems of determining the largest h such that the input graph (on n vertices) has a minor isomorphic to k"h or a subgraph homeomorphic to k"h, respectively, as well as the problem of finding the corresponding subgraphs. we term them as the maximum clique minor problem and the maximum homeomorphic clique problem, respectively. we observe that a known result of kostochka and thomason supplies an o(n) bound on the approximation factor for the maximum clique minor problem achievable in polynomial time. we also provide an independent proof of nearly the same approximation factor with explicit polynomial-time estimation, by exploiting the minor separator theorem of plotkin et al. next, we show that another known result of bollobas and thomason and of komlos and szemeredi provides an o(n) bound on the approximation factor for the maximum homeomorphic clique achievable in polynomial time. on the other hand, we show an @w(n^1^/^2^-^o^(^1^/^(^l^o^g^n^)^^^@c^)) lower bound (for some constant @c, unless np@?zptime(2^(^l^o^g^n^)^^^o^^^(^^^1^^^))) on the best approximation factor achievable efficiently for the maximum homeomorphic clique problem, nearly matching our upper bound. finally, we derive an interesting trade-off between approximability and subexponential time for the problem of subgraph homeomorphism where the guest graph has maximum degree not exceeding three and low treewidth.
intersecting periodic words. let a=a[1..2v] be a word which is a square and for which a[1..2u] is also a square and a[k+1..min(k+2w,2v)] has period w where u
the maximum agreement forest problem: approximation algorithms and computational experiments. there are various techniques for reconstructing phylogenetic trees from data, and in this context the problem of determining how distant two such trees are from each other arises naturally. various metrics for measuring the distance between two phylogenies have been defined. another way of comparing two trees t and u is to compute the so called maximum agreement forest of these trees. informally, the number of components of an agreement forest tells how many edges from each of t and u need to be cut so that the resulting forests agree, after performing all forced edge contractions. this problem is np-hard even when the input trees have maximum degree 2. hein et al. [j. hein, t. jiang, l. wang, k. zhang, on the complexity of comparing evolutionary trees, discrete applied mathematics 71 (1996) 153-169] presented an approximation algorithm for it, claimed to have performance ratio 3. we show that the performance ratio of the algorithm proposed by hein et al. is 4, and we also present two new 3-approximation algorithms for this problem. we show how to modify one of the algorithms into a (d+1)-approximation algorithm for trees with bounded degree d, d>=2. finally, we report on some computational experiments comparing the performance of the algorithms presented in this paper.
lattice grids and prisms are antimagic. an antimagic labelling of a finite undirected simple graph with m edges and n vertices is a bijection from the set of edges to the integers 1,...,m such that all n vertex sums are pairwise distinct, where a vertex sum is the sum of labels of all edges incident with the same vertex. a graph is called antimagic if it has an antimagic labelling. in 1990, hartsfield and ringel conjectured that every connected graph, but k"2, is antimagic. in [t.-m. wang, toroidal grids are antimagic, in: proc. 11th annual international computing and combinatorics conference, cocoon'2005, in: lncs, vol. 3595, springer, 2005, pp. 671-679], wang showed that the toroidal grids (the cartesian products of two or more cycles) are antimagic. two open problems left in wang's paper are about the antimagicness of lattice grid graphs and prism graphs, which are the cartesian products of two paths, and of a cycle and a path, respectively. in this article, we prove that these two classes of graphs are antimagic, by constructing such antimagic labellings.
an external-memory depth-first search algorithm for general grid graphs. graph data in modern scientific and engineering applications are often too large to fit in the computer's main memory. input/output (i/o) complexity is a major research issue in this context. minimization of the number of i/o operations (in external memory graph algorithms) is the main focus of current research while classical (internal memory) graph algorithms were designed to minimize temporal complexity. in this paper, we propose an external memory depth first search algorithm for general grid graphs. the i/o-complexity of the algorithm is o(sort(n)log"2nm), where n=|v|+|e|, sort(n)=@q(nblog"m"/"bnb) is the sorting i/o-complexity, m is the memory size, and b is the block size. the best known algorithm for this class of graph is the standard (internal memory) dfs algorithm with appropriate block (sub-grid) i/o-access. its i/o-complexity is o(n/b). recently, the authors proposed an o(sort(n)) algorithm for solid grid graphs.
fast algorithms for computing jones polynomials of certain links. we give a fast algorithm for computing jones polynomials of 2-bridge links. given the tait graph with n edges of a 2-bridge diagram, this algorithm runs with o(n) additions and multiplications in polynomials of degree o(n), namely in o(n^2logn) time. we also propose an algorithm that, given the tait graph with n edges of a closed 3-braid diagram, computes the jones polynomial of the closed 3-braid link in o(n^2logn) time.
the cell probe complexity of succinct data structures. we consider time-space tradeoffs for static data structure problems in the cell probe model with word size 1 (the bit probe model). in this model, the goal is to represent n-bit data with s=n+r bits such that queries (of a certain type) about the data can be answered by reading at most t bits of the representation. ideally, we would like to keep both s and t small, but there are tradeoffs between the values of s and t that limit the possibilities of keeping both parameters small. in this paper, we consider the case of succinct representations, where s=n+r for some redundancyr@?n. for a boolean version of the problem of polynomial evaluation with preprocessing of coefficients, we show a lower bound on the redundancy-query time tradeoff of the form (r+1)t>=@w(n/logn). in particular, for very small redundancies r, we get an almost optimal lower bound stating that the query algorithm has to inspect almost the entire data structure (up to a logarithmic factor). we show similar lower bounds for problems satisfying a certain combinatorial properties of a coding theoretic flavor, and obtain (r+1)t>=@w(n) for certain problems. previously, no @w(m) lower bounds were known on t in the general model for explicit boolean problems, even for very small redundancies. by restricting our attention to systematic or index structures @f satisfying @f(x)=x@?@f^*(x) for some map @f^* (where @? denotes concatenation), we show similar lower bounds on the redundancy-query time tradeoff for the natural data structuring problems of prefix sum and substring search.
reversal and transposition medians. in determining phylogenetic trees using gene order information, medians provide a powerful alternative to pairwise distances. on the other hand, both breakpoint and reversal medians are np-hard to compute and the use of medians has been limited to relatively closely related genomes. in this paper, we show that in spite of the greater non-uniqueness of reversal medians, compared to breakpoint medians, medians of moderately distant genomes are often widely spread. this means that regardless of which approximation algorithms one may devise for computing reversal medians, the genomes need to be closely related for phylogenetic tree computations to be successful. to show this, we use results on transposition medians, which behave similarly, and also support our claims with simulations and a real data example with widely spread medians.
a new conceptual framework for analog computation. in this paper we show how to explore the classical theory of computability using the tools of analysis: a differential scheme is substituted for the classical recurrence scheme and a limit operator is substituted for the classical minimization. we show that most relevant problems of computability over the non-negative integers can be dealt with over the reals: elementary functions are computable, turing machines can be simulated, the hierarchy of non-computable functions can be represented (the classical halting problem being solvable at some level). the most typical concepts in analysis become natural in this framework. the most relevant question is posed: can we solve open problems of classical computability and computational complexity using, as popper says, the toolbox of analysis?
on the (n, t)-antipodal gray codes. an n-bit gray code is a circular listing of all 2^nn-bit binary strings in which consecutive strings differ at exactly one bit. for n@?t@?2^n^-^1, an (n,t)-antipodal gray code is a gray code in which the complement of any string appears t steps away from the string, clockwise or counterclockwise. killian and savage proved that an (n,n)-antipodal gray code exists when n is a power of 2 or n=3, and does not exist for n=6 or odd n>3. motivated by these results, we prove that for odd n>=3, an (n,t)-antipodal gray code exists if and only if t=2^n^-^1-1. for even n, we establish two recursive constructions for (n,t) codes from smaller (n^',t^'). consequently, various (n,t)-antipodal gray codes are found for even n's. examples are for t=2^n^-^1-2^k with k odd and 1@?k@?n-3 when n>=4, for t=2^n^-^k when n>=2k with 1@?k@?3, for t=n when n=2^k>=2 (an alternative proof for killian and savage's result) ...etc.
weighted asynchronous cellular automata. we study weighted systems whose behavior is described as a formal power series over a free partially commutative or trace monoid. it is shown that the interleaving approach and the distributed approach are equivalent in this setting. this holds, both in the deterministic and in the nondeterministic case. consequently, we obtain a particularly simple class of sequential weighted automata that already have full expressive power.
ranks of graphs: the size of acyclic orientation cover for deadlock-free packet routing. given a graph g, the problem is to determine an acyclic orientation of g which minimizes the maximal number of changes of orientation along any shortest path in g. the corresponding value is called the rank of the graph g. the motivation for this graph theoretical problem comes from the design of deadlock-free packet routing protocols [g. tel, deadlock-free packet switching networks, in: introduction to distributed algorithms, cambridge university press, cambridge, uk, 1994 (chapter 5)]. this acyclic orientation covering problem on the shortest path systems has been studied in [j.-c. bermond, m. di ianni, m. flammini, s. perennes, acyclic orientations for deadlock prevention in interconnection networks, in: 23rd international workshop on graph-theoretic concepts in computer science (wg), in: lecture notes in computer science, vol. 1335, springer-verlag, 1997, pp. 52-64] where it was shown that the general problem of determining the rank is np-complete and some upper and lower bounds on the rank were presented for particular topologies, such as grids, tori and hypercubes. the main unresolved problem stated in [j.-c. bermond, m. di ianni, m. flammini, s. perennes, acyclic orientations for deadlock prevention in interconnection networks, in: 23rd international workshop on graph-theoretic concepts in computer science (wg), in: lecture notes in computer science, vol. 1335, springer-verlag, 1997, pp. 52-64] was to determine the rank values for other well-known interconnection networks and also for more general classes of graphs. in this paper we give a general lower bound argument for the rank problem and apply it to the class of involution-generated cayley graphs which among others include hypercubes, star graphs, pancake graphs and transposition-tree based graphs [s.b. akers, b. krishnamurthy, a group-theoretic model for symmetric interconnection networks, ieee transactions on computers 38 (4) (1989) 555-565]. we also present a large class lcp"("t","s"p") of graphs with constant rank. this class of graphs is defined as the layered cross product [s. even, a. litman, layered cross product-a technique to construct interconnection networks, networks 29 (1997) 219-223] of layered trees and series-parallel graphs and includes among others butterflies, benes networks, fat-trees and meshes of trees. for some special topologies, improved lower bounds on the rank are also presented. we consider some of the modified versions of the rank problem as well.
about frequencies of letters in generalized automatic sequences. we present some asymptotic results about the frequency of a letter appearing in a generalized unidimensional automatic sequence. next, we study multidimensional generalized automatic sequences and the corresponding frequencies.
scheduling jobs with agreeable processing times and due dates on a single batch processing machine. in this paper we study the problems of scheduling jobs with agreeable processing times and due dates on a single batch processing machine to minimize total tardiness, and weighted number of tardy jobs. we prove that the problem of minimizing total tardiness is np-hard even if the machine capacity is two jobs and we develop a pseudo-polynomial-time algorithm for an np-hard special case of this problem. we also develop a pseudo-polynomial-time algorithm for the np-hard problem of minimizing weighted number of tardy jobs, which suggests that this problem cannot be strongly np-hard unless p=np.
self-assembly of strings and languages. self-assembly is the process in which simple objects autonomously aggregate into large structures and it has become one of the major tools for nano-scale engineering. we propose in this paper a string-based framework inspired by the principle of self-assembly: two strings with a common overlap, say uv and vw, yield a string uvw; we say that string uvw has been assembled from strings uv and vw. the operation may be extended in a natural way also to sets of strings. we answer several questions: what is the assembly power of a given set of strings, can a given set of strings be generated through assembly and if so, what is a minimal generator for it?
on-line scheduling with delivery time on a single batch machine. we consider a single batch machine on-line scheduling problem with jobs arriving over time. a batch processing machine can handle up to b jobs simultaneously as a batch, and the processing time for a batch is equal to the longest processing time among the jobs in it. each job becomes available at its arrival time, which is not known in advance, and its characteristics, such as processing time and delivery time, become known at its arrival. once the processing of a job is completed we deliver it to the destination. the objective is to minimize the time by which all jobs have been delivered. in this paper, we deal with two variants: the unbound model where b is sufficiently large and the bounded model where b is finite. we provide on-line algorithms with competitive ratio 2 for the unbounded model and with competitive ratio 3 for the bounded model. for when each job has the same processing time, we provide on-line algorithms with competitive ratios (5+1)/2, and these results are the best possible.
degree distribution of the fkp network model. power laws, in particular power-law degree distributions, have been observed in real-world networks in a very wide range of contexts, including social networks, biological networks, and artificial networks such as the physical internet or abstract world wide web. recently, these observations have triggered much work attempting to explain the power laws in terms of new 'scale-free' random graph models. so far, perhaps the most effective mechanism for explaining power laws is the combination of growth and preferential attachment. in [a. fabrikant, e. koutsoupias, c.h. papadimitriou, heuristically optimized trade-offs: a new paradigm for power laws in the internet icalp 2002, in: lncs, vol. 2380, pp. 110-122], fabrikant, koutsoupias and papadimitriou propose a new 'paradigm' for explaining power laws, based on trade-offs between competing objectives. they also introduce a new, simple and elegant parametrized model for the internet, and prove some kind of power-law bound on the degree sequence for a wide range of scalings of the trade-off parameter. here we shall show that this model does not have the usual kind of power-law degree distribution observed in the real world: for the most interesting range of the parameter, neither the bulk of the nodes, nor the few highest degree nodes have degrees following a power law. we shall show that almost all nodes have degree 1, and that there is a strong bunching of degrees near the maximum.
on being a student of john reynolds. the editors of this volume asked me to put together a description of what it was like to be a ph.d. student of john c. reynolds. with the assistance of his other students, this is exactly what i have done. i have asked each of them to contribute their reminiscences on what it was like to work with john, to describe how they came to know john, and to say whatever they would like about how john affected their lives. these contributions will be found below, ordered by the year that each student formally finished his studies. all in all, this piece serves to document the very positive effect that working under john had for those of us lucky enough to work under him.
relational separation logic. in this paper, we present a hoare-style logic for specifying and verifying how two pointer programs are related. our logic lifts the main features of separation logic, from an assertion to a relation, and from a property about a single program to a relationship between two programs. we show the strength of the logic, by proving that the schorr-waite graph marking algorithm is equivalent to the depth-first traversal.
the girard-reynolds isomorphism (second edition). jean-yves girard and john reynolds independently discovered the second-order polymorphic lambda calculus, f2. girard additionally proved a representation theorem: every function on natural numbers that can be proved total in second-order intuitionistic predicate logic, p2, can be represented in f2. reynolds additionally proved an abstraction theorem: every term in f2 satisfies a suitable notion of logical relation; and formulated a notion of parametricity satisfied by well-behaved models. we observe that the essence of girard's result is a projection from p2 into f2, and that the essence of reynolds's result is an embedding of f2 into p2, and that the reynolds embedding followed by the girard projection is the identity. we show that the inductive naturals are exactly those values of type natural that satisfy reynolds's notion of parametricity, and as a consequence characterize situations in which the girard projection followed by the reynolds embedding is also the identity. an earlier version of this paper used a logic over untyped terms. this version uses a logic over typed term, similar to ones considered by abadi and plotkin and by takeuti, which better clarifies the relationship between f2 and p2. this paper uses colour to enhance its presentation. if the link below is not blue, follow it for the colour version. http://homepages.inf.ed.ac.uk/wadler
core algebra revisited. reynolds's work in parametric polymorphism when specialized to a particular example gives rise to the notion of the core of a category and its associated equational theory of core algebras.
on the relations between monadic semantics. we present a simple computational metalanguage with general recursive types and multiple notions of effects, through which a variety of concrete denotational semantics can be conveniently factored, by suitably interpreting the effects as monads. we then propose a methodology for relating two such interpretations of the metalanguage, with the aim of showing that the semantics they induce agree for complete programs. as a prototypical instance of such a relation, we use the framework to show agreement between a direct and a continuation semantics of the simple, untyped functional language from reynolds's original paper on the subject.
combining algebraic effects with continuations. we consider the natural combinations of algebraic computational effects such as side-effects, exceptions, interactive input/output, and nondeterminism with continuations. continuations are not an algebraic effect, but previously developed combinations of algebraic effects given by sum and tensor extend, with effort, to include commonly used combinations of the various algebraic effects with continuations. continuations also give rise to a third sort of combination, that given by applying the continuations monad transformer to an algebraic effect. we investigate the extent to which sum and tensor extend from algebraic effects to arbitrary monads, and the extent to which felleisen et al.'s c operator extends from continuations to its combination with algebraic effects. to do all this, we use dubuc's characterisation of strong monads in terms of enriched large lawvere theories.
flow analysis of lazy higher-order functional programs. in recent years much interest has been shown in a class of functional languages including haskell, lazy ml, sasl/krc/miranda, alfl, orwell, and ponder. it has been seen that their expressive power is great, programs are compact, and program manipulation and transformation is much easier than with imperative languages or more traditional applicative ones. common characteristics: they are purely applicative, manipulate trees as data objects, use pattern matching both to determine control flow and to decompose compound data structures, and use a ''lazy'' evaluation strategy. in this paper we describe a technique for data flow analysis of programs in this class by safely approximating the behavior of a certain class of term rewriting systems. in particular we obtain ''safe'' descriptions of program inputs, outputs and intermediate results by regular sets of trees. potential applications include optimization, strictness analysis and partial evaluation. the technique improves earlier work because of its applicability to programs with higher-order functions, and with either eager or lazy evaluation. the technique addresses the call-by-name aspect of laziness, but not memoization.
a few exercises in theorem processing. the realization of inference rules as the primitive operations of a type ''theorem'' in a type-safe programming language that has so well served lcf and its descendants may, it is suggested, be of interest aside from any immediate context of theorem proving or hardware or software verification. using the general ''conversions'' introduced by paulson, a couple of simple programming exercises with theorem data, imitative of list processing, are presented. an example of a potentially useful notational definition in the hol object language is given as an application.
a syntactic correspondence between context-sensitive calculi and abstract machines. we present a systematic construction of environment-based abstract machines from context-sensitive calculi of explicit substitutions, and we illustrate it with ten calculi and machines for applicative order with an abort operation, normal order with generalized reduction and call/cc, the lambda-mu-calculus, delimited continuations, stack inspection, proper tail-recursion, and lazy evaluation. most of the machines already exist but they have been obtained independently and are only indirectly related to the corresponding calculi. all of the calculi are new and they make it possible directly to reason about the execution of the corresponding machines.
a bisimulation for dynamic sealing. we define @l"s"e"a"l, an untyped call-by-value @l-calculus with primitives for protecting abstract data by sealing, and develop a bisimulation proof method that is sound and complete with respect to contextual equivalence. this provides a formal basis for reasoning about data abstraction in open, dynamic settings where static techniques such as type abstraction and logical relations are not applicable.
analyzing the environment structure of higher-order languages using frame strings. reasoning about program behaviour in programming languages based on the @l calculus requires reasoning in a unified way about control, data and environment structure. previous analysis work has done an inadequate job on the environment component of this task. we develop a new analytic framework, @dcfa, which is based on a new abstraction: frame strings, an enriched variant of procedure strings that can be used to model both control flow and environment allocation. this abstraction enables new environment-sensitive analyses and transformations that have not been previously attainable. we state the critical theorems needed to establish correctness of the entire technology suite, with their proofs.
a semantics for concurrent separation logic. we present a trace semantics for a language of parallel programs which share access to mutable data. we introduce a resource-sensitive logic for partial correctness, based on a recent proposal of o'hearn, adapting separation logic to the concurrent setting. the logic allows proofs of parallel programs in which ''ownership'' of critical data, such as the right to access, update or deallocate a pointer, is transferred dynamically between concurrent processes. we prove soundness of the logic, using a novel ''local'' interpretation of traces which allows accurate reasoning about ownership. we show that every provable program is race-free.
language equations with complementation: decision problems. systems of language equations of the form x"i=@f"i(x"1,...,x"n)(1=
attributed graph transformation with node type inheritance. the aim of this paper is to integrate typed attributed graph transformation with node type inheritance. borrowing concepts from object oriented systems, the main idea is to enrich the attributed type graph with an inheritance relation and a set of abstract nodes. in this way, a node type inherits the attributes and edges of all its ancestors. based on these concepts, it is possible to define abstract productions, containing abstract nodes. these productions are equivalent to a number of concrete productions, resulting from the substitution of the abstract node types by the node types in their inheritance clan. therefore, productions become more compact and suitable for their use in combination with meta-modelling. the main results of this paper show that attributed graph transformation with node type inheritance is fully compatible with the existing concept of typed attributed graph transformation.
context-dependent nondeterminism for pushdown automata. pushdown automata using a limited and unlimited amount of nondeterminism are investigated. moreover, nondeterministic steps are allowed only within certain contexts, i.e., in configurations that meet particular conditions. the relationships of the accepted language families with closures of the deterministic context-free languages (dcfl) under regular operations are studied. for example, automata with unbounded nondeterminism that have to empty their pushdown store up to the initial symbol in order to make a guess are characterized by the regular closure of dcfl. automata that additionally have to reenter the initial state are (almost) characterized by the kleene star closure of the union closure of the prefix-free deterministic context-free languages. pushdown automata with bounded nondeterminism are characterized by the union closure of dcfl in any of the considered contexts. proper inclusions between all language classes discussed are shown. finally, closure properties of these families under afl operations are investigated.
automated compositional proofs for real-time systems. we present a framework for formally proving that the composition of the behaviors of the different parts of a complex, real-time system ensures a desired global specification of the overall system. the framework is based on a simple compositional rely/guarantee circular inference rule, plus a methodology concerning the integration of the different parts into a whole system. the reference specification language is the trio metric linear temporal logic. the novelty of our approach with respect to existing compositional frameworks-most of which do not deal explicitly with real-time requirements-consists mainly in its generality and abstraction from any assumptions about the underlying computational model and from any semantic characterizations of the temporal logic language used in the specification. moreover, the framework deals equally well with continuous and discrete time. it is supported by a tool, implemented on top of the proof-checker pvs, to perform deduction-based verification through theorem-proving of modular real-time axiom systems. as an example of application, we show the verification of a real-time version of the old-fashioned but still relevant ''benchmark'' of the dining philosophers problem.
on some variations of two-way probabilistic finite automata models. rabin [m. rabin, probabilistic finite automata, information and control (1963) 230-245] initiated the study of probabilistic finite automata (pfa). rabin's work showed a crucial role of the gap in the error bound (for accepting and non-accepting computations) in the power of the model. further work resulted in the identification of qualitatively different error models (one-sided error, bounded and unbounded errors, no error etc.) karpinski and verbeek [m. karpinski, r. verbeek, there is no polynomial deterministic simulation of probabilistic space with two-way random-tape generator, information and control 67 (1985) 158-162] and nisan [n. nisan, on read-once vs. multiple access to randomness in logspace, in: proc. of fifth ieee structure in complexity theory, barcelona, spain, 1990, pp. 179-184] studied a model of probabilistic automaton in which the tape containing random bits can be read by a two-way head. they presented results comparing models with one-way vs. two-way access to randomness. dwork and stockmeyer [c. dwork, l. stockmeyer, interactive proof systems with finite state verifiers, ibm report rj 6262, 1988] and condon et al. [a. condon, et al., on the power of finite automata with both nondeterministic and probabilistic states, siam journal on computing (1998) 739-762] studied a model of 2-pfa with nondeterministic states (2-npfa). in this paper, we present some results about the above mentioned variations of probabilistic finite automata, as well as a model of 2-pfa augmented with a pebble studied in [b. ravikumar, some observations on two-way probabilistic finite automata, in: proc. of the foundations of software technology and theoretical computer science, 1992, pp. 392-403]. our observations indicate that these models exhibit subtle variations in their computational power. we also mention many open problems about these models. complete characterizations of their power will likely provide deeper insights about the role of randomness in space-bounded computations.
can abstract state machines be useful in language theory? the abstract state machine (asm) is a modern computation model. asms and asm based tools are used in academia and industry, albeit on a modest scale. they allow you to give high-level operational semantics to computer artifacts and to write executable specifications of software and hardware at the desired abstraction level. in connection with the 2006 conference on developments in language theory, we point out several ways that we believe abstract state machines can be useful to the dlt community.
events and modules in reaction systems. reaction systems are a formal model of interactions between biochemical reactions. they are based on the observation that two basic mechanisms behind the functioning of biochemical reactions are facilitation and inhibition. in this paper we continue the investigation of reaction systems, and in particular we introduce the notion of a module, and then we investigate the formation and evolution of modules. among others we prove that reaction systems can be viewed as self-organizing systems, where the organizing goal is to ensure a specific property of the set of all modules (of a state of a process).
synchronizing automata with a letter of deficiency 2. we present two infinite series of synchronizing automata with a letter of deficiency 2 whose shortest reset words are longer than those for synchronizing automata obtained by a straightforward modification of cerny's construction.
modeling adaptive behaviors in context unity. context-aware computing refers to a paradigm in which applications sense aspects of the environment and use this information to adjust their behavior in response to changing circumstances. in this paper, we present a formal model and notation (context unity) for expressing quintessential aspects of context-aware computations; existential quantification, for instance, proves to be highly effective in capturing the notion of discovery in open systems. furthermore, context unity treats context in a manner that is relative to the specific needs of an individual application and promotes an approach to context maintenance that is transparent to the application. in this paper, we construct the model from first principles, introduce its proof logic, and demonstrate how the model can be used as an effective abstraction tool for context-aware applications and middleware.
equivalence of simple functions. a partial function f:@s^*->@w^* is called a simple function if f(w)@?@w^* is the output produced in the leftmost derivation of a word w@?@s^* from a nonterminal of a simple context free grammar g with output alphabet @w. in this paper we present an efficient algorithm for testing the equivalence of simple functions. such functions correspond also to one-state deterministic pushdown transducers. our algorithm works in time polynomial with respect to |g|+v(g), where |g| is the size of the textual description of g, and v(g) is the maximum of the shortest lengths of words generated by nonterminals of g.
on the existence of prime decompositions. we investigate factorizations of regular languages in terms of prime languages. a language is said to be strongly prime decomposable if any way of factorizing it yields a prime decomposition in a finite number of steps. we give a characterization of the strongly prime decomposable regular languages and using the characterization we show that every regular language over a unary alphabet has a prime decomposition. we show that there exist non-regular unary languages that do not have prime decompositions. we also consider infinite factorizations of unary languages.
observational purity and encapsulation. practical specification languages for imperative and object-oriented programs, such as jml, eiffel, and spec#, allow the use of program expressions including method calls in specification formulas. for coherent semantics of specifications, and to avoid anomalies with runtime assertion checking, expressions in specifications and assertions are typically required to be weakly pure in the sense that their evaluation has no effect on the state of preexisting objects. for specification of large systems using standard libraries this restriction is impractical: it disallows many standard methods that mutate state for purposes such as caching or lazy initialization. calls of such methods can sensibly be used for specifications and annotations in contexts where their effects cannot be observed. this paper formalizes a notion of observational purity, justifies the use of weakly and observationally pure methods in specifications, and shows that a method is observationally pure if it simulates a weakly pure method.
the growth ratio of synchronous rational relations is unique. we introduce @a-synchronous relations for a rational number @a. we show that if a rational relation is both @a- and @a^'-synchronous for two different numbers @a and @a^', then it is recognizable. we give a synchronization algorithm for @a-synchronous transducers. we also prove the closure under boolean operations and composition of @a-synchronous relations.
polynomials, fragments of temporal logic and the variety da over traces. we show that some language-theoretic and logical characterizations of recognizable word languages whose syntactic monoid is in the variety da also hold over traces. to this end we give algebraic characterizations for the language operations of generating the polynomial closure and generating the unambiguous polynomial closure over traces. we also show that there exist natural fragments of local temporal logic that describe this class of languages corresponding to da. all characterizations are known to hold for words.
on critical exponents in fixed points of non-erasing morphisms. let @s be an alphabet of size t, let f:@s^*->@s^* be a non-erasing morphism, let w be an infinite fixed point of f, and let e(w) be the critical exponent of w. we prove that if e(w) is finite, then for a uniform f it is rational, and for a non-uniform f it lies in the field extension q[r,@l"1,...,@l"@?], where r,@l"1,...,@l"@? are the eigenvalues of the incidence matrix of f. in particular, e(w) is algebraic of degree at most t. under certain conditions, our proof implies an algorithm for computing e(w).
the multi-multiway cut problem. in this paper, we define and study a natural generalization of the multicut and multiway cut problems: the minimum multi-multiway cut problem. the input to the problem is a weighted undirected graph g=(v,e) and k sets s"1,s"2,...,s"k of vertices. the goal is to find a subset of edges of minimum total weight whose removal completely disconnects each one of the sets s"1,s"2,...,s"k, i.e., disconnects every pair of vertices u and v such that u,v@?s"i, for some i. this problem generalizes both the multicut problem, when |s"i|=2, for 1@?i@?k, and the multiway cut problem, when k=1. we present an approximation algorithm for the multi-multiway cut problem with an approximation ratio which matches that obtained by garg, vazirani, and yannakakis on the standard multicut problem. namely, our algorithm has an o(logk) approximation ratio. moreover, we consider instances of the minimum multi-multiway cut problem which are known to have an optimal solution of light weight. we show that our algorithm has an approximation ratio substantially better than o(logk) when restricted to such ''light'' instances. specifically, we obtain an o(loglp)-approximation algorithm for the problem when all edge weights are at least 1 (here lp denotes the value of a natural linear programming relaxation of the problem). the latter improves the o(loglplogloglp) approximation ratio for the minimum multicut problem (implied by the work of seymour and even et al.).
turing's unpublished algorithm for normal numbers. in an unpublished manuscript, alan turing gave a computable construction to show that absolutely normal real numbers between 0 and 1 have lebesgue measure 1; furthermore, he gave an algorithm for computing instances in this set. we complete his manuscript by giving full proofs and correcting minor errors. while doing this, we recreate turing's ideas as accurately as possible. one of his original lemmas remained unproved, but we have replaced it with a weaker lemma that still allows us to maintain turing's proof idea and obtain his result.
bernstein-bezoutian matrices and curve implicitization. a new application of bernstein-bezoutian matrices, a type of resultant matrices constructed when the polynomials are given in the bernstein basis, is presented. in particular, the approach to curve implicitization through sylvester and bezout resultant matrices and bivariate interpolation in the usual power basis is extended to the case in which the polynomials appearing in the rational parametric equations of the curve are expressed in the bernstein basis, avoiding the basis conversion from the bernstein to the power basis. the coefficients of the implicit equation are computed in the bivariate tensor-product bernstein basis, and their computation involves the bidiagonal factorization of the inverses of certain totally positive matrices.
paging with connections: fifo strikes again. we continue the study of the integrated document and connection caching problem. we focus on the case where the connection cache has a size of one and show that this problem is not equivalent to standard paging, even if there are only two locations for the pages, by giving the first lower bound that is strictly higher than k for this problem. we then give the first upper bound below the trivial value of 2k for this problem. our upper bound is k+4@? where @? is the number of locations where the requested pages in a phase come from. this algorithm groups pages by location. in each phase, it evicts all pages from one location before moving on to the next location. in contrast, we show that the lru algorithm is not better than 2k-competitive. we also examine the resource augmented model and show that the plain fifo algorithm is optimal for the case h=2 and all k>=2, where h is the size of the offline document cache. we show that also in this case fifo is better than lru, although this is not true for standard paging.
digital lines with irrational slopes. how to construct a digitization of a straight line and how to be able to recognize a straight line in a set of pixels are very important topics in computer graphics. the aim of the present paper is to give a mathematically exact and consistent description of digital straight lines according to rosenfeld's definition. the digitizations of lines with slopes 0
randomized algorithm for the sum selection problem. let a be a sequence of n real numbers a"1,a"2,...,a"n. we consider the sum selection problem as that of finding the segment a(i^*,j^*) such that the rank of s(i^*,j^*)=@?"t"="i"^"*^j^^^*a"t over all possible feasible segments is k, where a feasible segment a(i,j)=a"i,a"i"+"1,...,a"j is a consecutive subsequence of a, and its width j-i+1 satisfies @?@?j-i+1@?u for some given integers @? and u, and @?@?u. it is a generalization of two well-known problems: the selection problem in computer science for which @?=u=1, and the maximum sum segment problem in bioinformatics for which the rank k is the total number of possible feasible segments. we will give a randomized algorithm for the sum selection problem that runs in expected o(nlog(u-@?)) time. it matches the optimal o(n) time randomized algorithm for the selection problem. we can also solve the k maximum sums problem, to enumerate the k largest sums, in expected o(nlog(u-@?)+k) time. the previously best known result was an algorithm that solves this problem for the case when @?=1, u=n and runs in o(nlog^2n+k) time in the worst case.
self-improved gaps almost everywhere for the agnostic approximation of monomials. given a learning sample, we focus on the hardness of finding monomials having low error, inside the interval bounded below by the smallest error achieved by a monomial (the best rule), and bounded above by the error of the default class (the poorest rule). it is well-known that when its lower bound is zero, it is an easy task to find, in linear time, a monomial with zero error. what we prove is that when this bound is not zero, regardless of the location of the default class in (0,1/2), it becomes a huge complexity burden to beat significantly the default class. in fact, under some complexity-theoretical assumptions, it may already be hard to beat the trivial approximation ratios, even when relaxing the time complexity constraint to be quasi-polynomial or sub-exponential. our results also hold with uniform weights over the examples.
ranking k maximum sums. given a sequence of n real numbers and an integer parameter k, the problem studied in this paper is to compute k subsequences of consecutive elements with the sums of their elements being the largest, the second largest, ..., and the kth largest among all possible range sums of the input sequence. for any value of k, 1@?k@?n(n+1)/2, we design a fast algorithm that takes o(n+klogn) time in the worst case to compute and rank all such subsequences. we also prove that our algorithm is optimal for k=o(n) by providing a matching lower bound. moreover, our algorithm is an improvement over the previous results on the maximum sum subsequences problem (where only the subsequences are requested and no ordering with respect to their relative sums will be determined). furthermore, given the fact that we have computed the @?th largest sums, our algorithm retrieves the (@?+1)th largest sum in o(logn) time, after o(n) time of preprocessing.
semi-online scheduling problems on two identical machines with inexact partial information. in semi-online scheduling problems, we always assume that some partial additional information is exactly known in advance. this may not be true in some applications. this paper considers semi-online scheduling problems on two identical machines with inexact partial information. three versions are considered, where we know in advance that the total size of all jobs, the optimal value, and the largest job size are in given intervals, respectively, while their exact values are unknown. we give both lower bounds of the problems and competitive ratios of algorithms as functions of a so-called disturbance parameter r@?[1,~). we establish for which r the inexact partial information is useful to improve the performance of a semi-online algorithm with respect to its pure online problem. optimal or near optimal algorithms are then obtained.
acknowledged broadcasting and gossiping in ad hoc radio networks. a radio network is a collection of transmitter-receiver devices (referred to as nodes). acknowledged radio broadcasting (arb) means transmitting a message from one special node called the source to all other nodes and informing the source about its completion. in our model, each node takes a synchronization per round and performs transmission or reception at one round. each node does not have a collision detection capability, and knows only its own id. in [b.s. chlebus, l. ga@?sieniec, a.m. gibbons, a. pelc, w. rytter, deterministic broadcasting in ad hoc radio networks, distributed computing 15 (2002) 27-38], it is proved that no arb algorithm exists in the model without collision detection. in this paper, we show that if n>=2, where n is the number of nodes in the network, we can construct arb algorithms in o(n) rounds for bidirectional graphs and in o(n^4^/^3log^1^0^/^3n) rounds for strongly connected graphs and construct acknowledged radio gossiping (arg) algorithms in o(nlog^3n) rounds for bidirectional graphs and in o(n^4^/^3log^1^0^/^3n) rounds for strongly connected graphs without collision detection.
defect particle kinematics in one-dimensional cellular automata. let a^z be the cantor space of bi-infinite sequences in a finite alphabet a, and let @s be the shift map on a^z. a cellular automaton is a continuous, @s-commuting self-map @f of a^z, and a @f-invariant subshift is a closed, (@f,@s)-invariant subset s@?a^z. suppose a@?a^z is s-admissible everywhere except for some small region we call a defect. it has been empirically observed that such defects persist under iteration of @f, and often propagate like 'particles'. we characterize the motion of these particles, and show that it falls into several regimes, ranging from simple deterministic motion, to generalized random walks, to complex motion emulating turing machines or pushdown automata. one consequence is that some questions about defect behaviour are formally undecidable.
an extremal graph with given bandwidth. the graph bandwidth problem is a well-known np-complete problem. the relation between size of a graph and bandwidth is very interesting. the minimum size required in g with bandwidth b is denoted as m(n,b) while the graph g of order n and bandwidth b with size m(n,b) is called an extremal graph. this paper provides the minimum size for a graph of odd order n, n>=9, and bandwidth (n+1)/2, and shows that k"2","n"-"2 is the only extremal graph of m(n,(n+1)/2).
coordinating team players within a noisy iterated prisoner's dilemma tournament. in this paper, we present our investigation into the use of a team of players within a noisy iterated prisoner's dilemma (ipd) tournament. we show that the members of such a team are able to use a pre-arranged sequence of moves that they make at the start of each interaction in order to recognise one another, and that by coordinating their actions they can increase the chances that one of the team members wins the round-robin style tournament. we consider, in detail, the factors that influence the performance of this team and we show that the problem that the team members face, when they attempt to recognise one another within the noisy ipd tournament, is exactly analogous to the problem, studied in information theory, of communicating reliably over a noisy channel. thus we demonstrate that we can use error-correcting codes to implement this recognition, and by doing so, further optimise the performance of the team.
classes of representable disjoint np-pairs. for a propositional proof system p we introduce the complexity class dnpp(p) of all disjoint np-pairs for which the disjointness of the pair is efficiently provable in the proof system p. we exhibit structural properties of proof systems which make canonical np-pairs associated with these proof systems hard or complete for dnpp(p). moreover, we demonstrate that non-equivalent proof systems can have equivalent canonical pairs and that depending on the properties of the proof systems different scenarios for dnpp(p) and the reductions between the canonical pairs exist.
algorithms for long paths in graphs. we obtain a polynomial algorithm in o(nm) time to find a long path in any graph with n vertices and m edges. the length of the path is bounded by a parameter defined on neighborhood condition of any three independent vertices of the path. an example is given to show that this bound is better than several classic results.
faster and simpler approximation algorithms for mixed packing and covering problems. we propose an algorithm for approximately solving the mixed packing and covering problem; given a convex compact set 0@?=(1-@e)b or decide that {x@?b|f(x)@?a,g(x)>=b}=0@?. here f,g:b->r"+^m are vectors whose components are m non-negative convex and concave functions, respectively, and a,b@?r"+"+^m are constant positive vectors. our algorithm requires an efficient feasibility oracle or block solver which, given vectors c,d@?r"+^m and @a@?r"+, computes x@?@?b such that c^tf(x@?)-d^tg(x@?)@?@a or correctly decides that no such x@?@?b exists. our algorithm, which is based on the lagrangian or price-directive decomposition method, generalizes the result from [k. jansen, approximation algorithm for the mixed fractional packing and covering problem, in: proceedings of 3rd ifip conference on theoretical computer science, ifip tcs 2004, kluwer, 2004, pp. 223-236; siam journal on optimization 17 (2006) 331-352] and needs only o(m(lnm+@e^-^2ln@e^-^1)) iterations or calls to the feasibility oracle. furthermore we show that a more general block solver can be used to obtain a more general approximation within the same runtime bound.
panconnectivity and pancyclicity of hypercube-like interconnection networks with faulty elements. in this paper, we deal with the graph g"0@?g"1 obtained from merging two graphs g"0 and g"1 with n vertices each by n pairwise nonadjacent edges joining vertices in g"0 and vertices in g"1. the main problems studied are how fault-panconnectivity and fault-pancyclicity of g"0 and g"1 are translated into fault-panconnectivity and fault-pancyclicity of g"0@?g"1, respectively. many interconnection networks such as hypercube-like interconnection networks can be represented in the form of g"0@?g"1 connecting two lower dimensional networks g"0 and g"1. applying our results to a class of hypercube-like interconnection networks called restricted hl-graphs, we show that in a restricted hl-graph g of degree m(>=3), each pair of vertices are joined by a path in g@?f of every length from 2m-3 to |v(g@?f)|-1 for any set f of faulty elements (vertices and/or edges) with |f|@?m-3, and there exists a cycle of every length from 4 to |v(g@?f)| for any fault set f with |f|@?m-2.
well quasi-orders generated by a word-shuffle rewriting. given a set i of words, the set l"@?"""i^@e of all words obtained by the shuffle of (copies of) words of i is naturally provided with a partial order: for u,v in l"@?"""i^@e, u@?"i^*v if and only if v is the shuffle of u and another word of l"@?"""i^@e. in [f. d'alessandro, s. varricchio, well quasi-orders, unavoidable sets and derivation systems, in: word avoidability complexity and morphisms (wacam), rairo theoretical informatics and applications 40 (3) (2006) 407-426 (special issue)], the authors have opened the problem of the characterization of the finite sets i such that @?"i^* is a well quasi-order on l"@?"""i^@e. in this paper we give an answer in the case when i consists of a single word w.
improved algorithms for quantum identification of boolean oracles. the oracle identification problem (oip) was introduced by ambainis et al. [a. ambainis, k. iwama, a. kawachi, h. masuda, r.h. putra, s. yamashita, quantum identification of boolean oracles, in: proc. of stacs'04, in: lncs, vol. 2996, 2004, pp. 105-116]. it is given as a set s of m oracles and a blackbox oracle f. our task is to figure out which oracle in s is equal to the blackbox f by making queries to f. oip includes several problems such as the grover search as special cases. in this paper, we improve the algorithms in [a. ambainis, k. iwama, a. kawachi, h. masuda, r.h. putra, s. yamashita, quantum identification of boolean oracles, in: proc. of stacs'04, in: lncs, vol. 2996, 2004, pp. 105-116] by providing a mostly optimal upper bound of query complexity for this problem: (i) for any oracle set s such that |s|@?2^n^^^d(d
closure properties for the class of behavioral models. hidden k-logics can be considered as the underlying logics of program specification. they constitute natural generalizations of k-deductive systems and encompass deductive systems as well as hidden equational logics and inequational logics. in our abstract algebraic approach, the data structures are sorted algebras endowed with a designated subset of their visible parts, called filter, which represents a set of truth values. we present a hierarchy of classes of hidden k-logics. the hidden k-logics in each class are characterized by three different kinds of conditions, namely, properties of their leibniz operators, closure properties of the class of their behavioral models, and properties of their equivalence systems. using equivalence systems, we obtain a new and more complete analysis of the axiomatization of the behavioral models. this is achieved by means of the leibniz operator and its combinatorial properties.
sos formats and meta-theory: 20 years after. in 1981 structural operational semantics (sos) was introduced as a systematic way to define operational semantics of programming languages by a set of rules of a certain shape [g.d. plotkin, a structural approach to operational semantics, technical report daimi fn-19, computer science department, aarhus university, aarhus, denmark, september 1981]. subsequently, the format of sos rules became the object of study. using so-called transition system specifications (tss's) several authors syntactically restricted the format of rules and showed several useful properties about the semantics induced by any tss adhering to the format. this has resulted in a line of research proposing several syntactical rule formats and associated meta-theorems. properties that are guaranteed by such rule formats range from well-definedness of the operational semantics and compositionality of behavioral equivalences to security-, time- and probability-related issues. in this paper, we provide an overview of sos rule formats and meta-theorems formulated around them.
an auction-based market equilibrium algorithm for a production model. we present an auction-based algorithm for computing market equilibrium prices in a production model, in which producers have a single linear production constraint, and consumers have linear utility functions. we provide algorithms for both the fisher and arrow-debreu versions of the problem.
a primal-dual algorithm for computing fisher equilibrium in the absence of gross substitutability property. we provide the first strongly polynomial time exact combinatorial algorithm to compute fisher equilibrium for the case when utility functions do not satisfy the gross substitutability property. the motivation for this comes from the work of kelly, maulloo, and tan [f.p. kelly, a.k. maulloo, d.k.h. tan, rate control for communication networks: shadow prices, proportional fairness and stability, journal of operational research (1998)] and kelly and vazirani [f.p. kelly, vijay v. vazirani, rate control as a market equilibrium (2003) (in preparation)] on rate control in communication networks. we consider a tree like network in which root is the source and all the leaf nodes are the sinks. each sink has got a fixed amount of money which it can use to buy the capacities of the edges in the network. the edges of the network sell their capacities at certain prices. the objective of each edge is to fix a price that can fetch the maximum money for it, and the objective of each sink is to buy capacities on edges in such a way that it can facilitate the sink to pull maximum flow from the source. in this problem, the edges and the sinks play precisely the role of sellers and buyers, respectively, in fisher's market model. the utility of a buyer (or sink) takes the form of a leontief function which is known for not satisfying gross substitutability property. we develop an o(m^3) exact combinatorial algorithm for computing equilibrium prices of the edges. the time taken by our algorithm is independent of the values of sink money and edge capacities. a corollary of our algorithm is that equilibrium prices and flows are rational numbers. although there are algorithms to solve this problem they are all based on convex programming techniques. to the best of our knowledge, ours is the first strongly polynomial time exact combinatorial algorithm for computing equilibrium prices of fisher's model under the case when buyers' utility functions do not satisfy gross substitutability property.
colored visual cryptography without color darkening. in a visual cryptography scheme a secret image is encoded into n shares, in the form of transparencies. the shares are then distributed to n participants. qualified subsets of participants can recover the secret image by superimposing their transparencies. non-qualified subsets of participants have no information about the secret image. in this paper we consider the case when the secret image is a colored image. most of the previous work on colored visual cryptography allows the superposition of pixels having the same color assuming that the resulting pixel still has the same color. this is not what happens in reality since when superimposing two pixels of the same color one gets a darker version of that color, which effectively is a different color. superimposing many pixels of the same color might result in a so dark version of the color that the resulting pixel might not be distinguishable from a black pixel. in this paper we propose a model where the reconstruction has to guarantee that the reconstructed secret pixel has the exact same color of the original one and not a darker version of it. we consider (k,n)-threshold schemes where a qualified set of participants consists of any k participants. we provide a general construction for any k, 2@?k@?n and a construction for the special case k=2. we also prove lower bounds on the pixel expansion (which is a measure of the goodness of the scheme) for the cases k=2 and k=n. the lower bounds match the pixel expansion of the schemes provided in these two cases, thus proving that our schemes are optimal with respect to the pixel expansion. we also provide an upper bound on the contrast of (k,n)-threshold schemes and (2,n)-threshold schemes with optimal contrast.
p systems with minimal parallelism. a current research topic in membrane computing is to find more realistic p systems from a biological point of view, and one target in this respect is to relax the condition of using the rules in a maximally parallel way. we contribute in this paper to this issue by considering the minimal parallelism of using the rules: if at least a rule from a set of rules associated with a membrane or a region can be used, then at least one rule from that membrane or region must be used, without any other restriction (e.g., more rules can be used, but we do not care how many). weak as it might look, this minimal parallelism still leads to universality. we first prove this for the case of symport/antiport rules. the result is obtained both for generating and accepting p systems, in the latter case also for systems working deterministically. then, we consider p systems with active membranes, and again the usual results are obtained: universality and the possibility to solve np-complete problems in polynomial time (by trading space for time).
algorithmic analysis of polygonal hybrid systems, part i: reachability. in this work we are concerned with the formal verification of two-dimensional non-deterministic hybrid systems, namely polygonal differential inclusion systems (spdis). spdis are a class of non-deterministic systems that correspond to piecewise constant differential inclusions on the plane, for which we study the reachability problem. our contribution is the development of an algorithm for solving exactly the reachability problem of spdis. we extend the geometric approach due to maler and pnueli [o. maler, a. pnueli. reachability analysis of planar multi-linear systems. in: c. courcoubetis (ed.), cav'93, in: lncs, vol. 697, springer-verlag, 1993, pp. 194-209] to non-deterministic systems, based on the combination of three techniques: the representation of the two-dimensional continuous-time dynamics as a one-dimensional discrete-time system (using poincare maps), the characterization of the set of qualitative behaviors of the latter as a finite set of types of signatures, and acceleration used to explore reachability according to each of these types.
hardness of approximating the minimum solutions of linear diophantine equations. let 1@?pnp, it is hard to approximate the minimum solutions of linear diophantine equations in @?"p norm within any constant factor and it is also hard to approximate the minimum solutions of linear diophantine equations in @?"p norm within the factor n^c^/^l^o^g^l^o^g^n for some constant c>0 where n is the number of variables in the equations.
from truth to computability ii. computability logic is a formal theory of computational tasks and resources. formulas in it represent interactive computational problems, and ''truth'' is understood as algorithmic solvability. interactive computational problems, in turn, are defined as games between a machine and its environment, with logical operators standing for operations on games. within the program of finding axiomatizations for incrementally rich fragments of this semantically introduced logic, the earlier article ''from truth to computability i'' proved soundness and completeness for system cl3, whose language has the so-called parallel connectives (including negation), choice connectives, choice quantifiers, and blind quantifiers. the present paper extends that result to the significantly more expressive system cl4 with the same collection of logical operators. what makes cl4 expressive is the presence of two sorts of atoms in its language: elementary atoms, representing elementary computational problems (i.e. predicates, i.e. problems of zero degree of interactivity), and general atoms, representing arbitrary computational problems. cl4 conservatively extends cl3, with the latter being nothing but the general-atom-free fragment of the former. removing the blind (classical) group of quantifiers from the language of cl4 is shown to yield a decidable logic despite the fact that the latter is still first-order.
splitting atoms safely. the aim of this paper is to make a contribution to (compositional) development methods for concurrent programs. in particular, it takes a fresh look at a number of familiar ideas including the problem of interference. some subtle issues of observability-including granularity-are explored. based on these points, the paper sets out some requirements for an approach to developing systems by ''splitting atoms safely''.
average case analysis for tree labelling schemes. we study how to label the vertices of a tree in such a way that we can decide the distance of two vertices in the tree given only their labels. gavoille et al. proved that for any such distance labelling scheme, the maximum label length is at least 18log^2n-o(logn) bits, where n is the number of vertices in the input tree t. they also gave a separator-based labelling scheme that has the optimal label length @q(logn@?log(h"n(t))), where h"n(t) is the height of t. we present two distance labelling schemes, namely, the backbone-based scheme and rake-based scheme, which also achieve the optimal label length. the two schemes always perform at least as well as the separator scheme. furthermore, the rake-based scheme has a much smaller expected label length under certain tree distributions. with these new schemes, we also can find the least common ancestor of any two vertices based on their labels only.
on codes defined by bio-operations. we consider the classes of @?-codes and @?-codes, which are superclasses of outfix and hyper-codes, respectively. these restrictions are based on the synchronized insertion operation, which serves as a model for the gene rearrangement function in certain unicellular organisms. we investigate the classes of @?-codes and @?-codes from a theoretical perspective, examine their relationships with traditional code classes and consider related decidability problems.
efficient algorithms for center problems in cactus networks. efficient algorithms for solving the center problems in weighted cactus networks are presented. in particular, we have proposed the following algorithms for the weighted cactus networks of size n: an o(nlogn) time algorithm to solve the 1-center problem, and an o(nlog^3n) time algorithm to solve the weighted continuous 2-center problem. we have also provided improved solutions to the general p-center problems in cactus networks. the developed ideas are then applied to solve the obnoxious 1-center problem in weighted cactus networks.
a uniform solution to sat using membrane creation. in living cells, new membranes are produced basically through two processes: mitosis and autopoiesis. these two processes have inspired two variants of cell-like membrane systems, namely p systems with active membranes and p systems with membrane creation. in this paper, we provide the first uniform, efficient solution to the sat problem in the framework of recogniser p systems with membrane creation using dissolution rules. recently the authors have proved that if the dissolution rules are not allowed to be used, then the polynomial complexity class associated with this variant of p systems is the standard complexity class p. this result, together with the main result of this paper, shows the surprising role of the apparently ''innocent'' operation of membrane dissolution. the use of this type of rule establishes the difference between efficiency and non-efficiency for p systems with membrane creation, and provides a barrier between p and np (assuming p
subjective-cost policy routing. we study a model of path-vector routing in which nodes' routing policies are based on subjective cost assessments of alternative routes. the routes are constrained by the requirement that all routes to a given destination must be confluent. we show that it is np-hard to determine whether there is a set of stable routes. we also show that it is np-hard to find a set of confluent routes that minimizes the total subjective cost; it is hard even to approximate the minimum cost closely. these hardness results hold even for very restricted classes of subjective costs. we then consider a model in which the subjective costs are based on the relative importance nodes place on a small number of objective cost measures. we show that a small number of confluent routing trees is sufficient for each node to have a route that nearly minimizes its subjective cost. we show that this scheme is trivially strategy proof and that it can be computed easily with a distributed algorithm. furthermore, we prove a lower bound on the number of trees required to contain a (1+@e)-approximately optimal route for each node and show that our scheme is nearly optimal in this respect.
fitness landscape of the cellular automata majority problem: view from the "olympus". in this paper we study cellular automata (cas) that perform the computational majority task. this task is a good example of what the phenomenon of emergence in complex systems is. we take an interest in the reasons that make this particular fitness landscape a difficult one. the first goal is to study the landscape as such, and thus it is ideally independent from the actual heuristics used to search the space. however, a second goal is to understand the features a good search technique for this particular problem space should possess. we statistically quantify in various ways the degree of difficulty of searching this landscape. due to neutrality, investigations based on sampling techniques on the whole landscape are difficult to conduct. so, we go exploring the landscape from the top. although it has been proved that no ca can perform the task perfectly, several efficient cas for this task have been found. exploiting similarities between these cas and symmetries in the landscape, we define the olympus landscape which is regarded as the ''heavenly home'' of the best local optima known (blok). then we measure several properties of this subspace. although it is easier to find relevant cas in this subspace than in the overall landscape, there are structural reasons that prevent a searcher from finding overfitted cas in the olympus. finally, we study dynamics and performance of genetic algorithms on the olympus in order to confirm our analysis and to find efficient cas for the majority problem with low computational cost.
randomized local search, evolutionary algorithms, and the minimum spanning tree problem. randomized search heuristics, among them randomized local search and evolutionary algorithms, are applied to problems whose structure is not well understood, as well as to problems in combinatorial optimization. the analysis of these randomized search heuristics has been started for some well-known problems, and this approach is followed here for the minimum spanning tree problem. after motivating this line of research, it is shown that randomized search heuristics find minimum spanning trees in expected polynomial time without employing the global technique of greedy algorithms.
counting distinct items over update streams. in data streaming applications, data arrives at rapid rates and in high volume, thus making it essential to process each stream update very efficiently in terms of both time and space. a data stream is a sequence of data records that must be processed continuously in an online fashion using sub-linear space and sub-linear processing time. we consider the problem of tracking the number of distinct items over data streams that allow insertion and deletion operations. we present two algorithms that improve on the space and time complexity of existing algorithms.
statistical zero knowledge and quantum one-way functions. one-way functions are a fundamental notion in cryptography, since they are the necessary condition for the existence of secure encryption schemes. most examples of such functions, including factoring, discrete logarithm or the rsa function, however, can be inverted with the help of a quantum computer. hence, it is very important to study the possibility of quantum one-way functions, i.e. functions which are easily computable by a classical algorithm but are hard to invert even by a quantum adversary. in this paper, we provide a set of problems that are good candidates for quantum one-way functions. these problems include graph non-isomorphism, approximate closest lattice vector and group non-membership. more generally, we show that any hard instance of circuit quantum sampling gives rise to a quantum one-way function. by the work of aharonov and ta-shma [d. aharonov, a. ta-shma, adiabatic quantum state generation and statistical zero knowledge, in: proceedings of stoc02 - symposium on the theory of computing, 2001], this implies that any language in statistical zero knowledge which is hard-on-average for quantum computers leads to a quantum one-way function. moreover, extending the result of impagliazzo and luby [r. impagliazzo, m. luby, one-way functions are essential for complexity based cryptography, in: proceedings of focs89 - symposium on foundations of computer science, 1989] to the quantum setting, we prove that quantum distributionally one-way functions are equivalent to quantum one-way functions.
longest increasing subsequences in windows based on canonical antichain partition. given a sequence @p"1@p"2...@p"n, a longest increasing subsequence (lis) in a window @p=@p"l@p"l"+"1...@p"r is a longest subsequence @s=@p"i"""1@p"i"""2...@p"i"""t such that l@?i"1|0@?i@?n-w}@?{@p,@p|i
a new algorithm based on copulas for var valuation with empirical calculations. this paper concerns the application of copula functions in var valuation. the copula function is used to model the dependence structure of multivariate assets. after the introduction of the traditional monte carlo simulation method and the pure copula method we present a new algorithm based on mixture copula functions and the dependence measure, spearman's rho. this new method is used to simulate daily returns of two stock market indices in china, shanghai stock composite index and shenzhen stock composite index, and then empirically calculate six risk measures including var and conditional var. the results are compared with those derived from the traditional monte carlo method and the pure copula method. from the comparison we show that the dependence structure between asset returns plays a more important role in valuating risk measures comparing with the form of marginal distributions.
decision-making based on approximate and smoothed pareto curves. we consider bicriteria optimization problems and investigate the relationship between two standard approaches to solving them: (i) computing the pareto curve and (ii) the so-called decision maker's approach in which both criteria are combined into a single (usually nonlinear) objective function. previous work by papadimitriou and yannakakis showed how to efficiently approximate the pareto curve for problems like shortest path, spanning tree, and perfect matching. we wish to determine for which classes of combined objective functions the approximate pareto curve also yields an approximate solution to the decision maker's problem. we show that an fptas for the pareto curve also gives an fptas for the decision-maker's problem if the combined objective function is growth bounded like a quasi-polynomial function. if the objective function, however, shows exponential growth then the decision-maker's problem is np-hard to approximate within any polynomial factor. in order to bypass these limitations of approximate decision making, we turn our attention to pareto curves in the probabilistic framework of smoothed analysis. we show that in a smoothed model, we can efficiently generate the (complete and exact) pareto curve with a small failure probability if there exists an algorithm for generating the pareto curve whose worst-case running time is pseudopolynomial. this way, we can solve the decision-maker's problem w.r.t. any non-decreasing objective function for randomly perturbed instances of, e.g. shortest path, spanning tree, and perfect matching.
arithmetic computation in the tile assembly model: addition and multiplication. formalized study of self-assembly has led to the definition of the tile assembly model [erik winfree, algorithmic self-assembly of dna, ph.d. thesis, caltech, pasadena, ca, june 1998; paul rothemund, erik winfree, the program-size complexity of self-assembled squares, in: acm symposium on theory of computing, stoc02, montreal, quebec, canada, 2001, pp. 459-468]. research has identified two issues at the heart of self-assembling systems: the number of steps it takes for an assembly to complete, assuming maximum parallelism, and the minimal number of tiles necessary to assemble a shape. in this paper, i define the notion of a tile assembly system that computes a function, and tackle these issues for systems that compute the sum and product of two numbers. i demonstrate constructions of such systems with optimal @q(1) distinct tile types and prove the assembly time is linear in the size of the input.
complexity and approximation of the minimum recombinant haplotype configuration problem. we study the complexity and approximation of the problem of reconstructing haplotypes from genotypes on pedigrees under the mendelian law of inheritance and the minimum recombinant principle (mrhc). first, we show that the mrhc for simple pedigrees where each member has at most one mate and at most one child (i.e. binary-tree pedigrees) is np-hard. second, we present some approximation results for the mrhc problem, which are the first approximation results in the literature to the best of our knowledge. we prove that the mrhc on two-locus pedigrees or binary-tree pedigrees with missing data cannot be approximated unless p=np. next we show that the mrhc on two-locus pedigrees without missing data cannot be approximated within any constant ratio under the unique games conjecture and can be approximated within the ratio o(log(n)). our l-reduction for the approximation hardness gives a simple alternative proof that the mrhc on two-locus pedigrees is np-hard, which is much easier to understand than the original proof. we also show that the mrhc for tree pedigrees without missing data cannot be approximated within any constant ratio under the unique games conjecture, too. finally, we explore the hardness and approximation of the mrhc on pedigrees where each member has a bounded number of children and mates mirroring real pedigrees.
semantics of a sequential language for exact real-number computation. we study a programming language with a built-in ground type for real numbers. in order for the language to be sufficiently expressive but still sequential, we consider a construction proposed by boehm and cartwright. the non-deterministic nature of the construction suggests the use of powerdomains in order to obtain a denotational semantics for the language. we show that the construction cannot be modelled by the plotkin or smyth powerdomains, but that the hoare powerdomain gives a computationally adequate semantics. as is well known, hoare semantics can be used in order to establish partial correctness only. since computations on the reals are infinite, one cannot decompose total correctness into the conjunction of partial correctness and termination as is traditionally done. we instead introduce a suitable operational notion of strong convergence and show that total correctness can be proved by establishing partial correctness (using denotational methods) and strong convergence (using operational methods). we illustrate the technique with a representative example.
algorithmic analysis of a basic evolutionary algorithm for continuous optimization. in practical optimization, applying evolutionary algorithms has nearly become a matter of course. their theoretical analysis, however, is far behind practice. so far, theorems on the runtime are limited to discrete search spaces; results for continuous search spaces are limited to convergence theory or even rely on validation by experiments, which is unsatisfactory from a theoretical point of view. the simplest, or most basic, evolutionary algorithms use a population consisting of only one individual and use random mutations as the only search operator. here the so-called (1+1) evolution strategy for minimization in r^n is investigated when it uses isotropically distributed mutation vectors. in particular, so-called gaussian mutations are analyzed when the so-called 1/5-rule is used for their adaptation. obviously, a reasonable analysis must respect the function to be minimized, and furthermore, the runtime must be measured with respect to the approximation error. a first algorithmic analysis of how the runtime depends on n, the dimension of the search space, is presented. this analysis covers all unimodal functions that are monotone with respect to the distance from the optimum. it turns out that, in the scenario considered, gaussian mutations in combination with the 1/5-rule indeed ensure asymptotically optimal runtime; namely, @q(n) steps/function evaluations are necessary and sufficient to halve the approximation error.
map construction of unknown graphs by multiple agents. we consider a distributed version of the graph exploration and mapping problem where a mobile agent has to traverse the edges of an unlabelled (i.e., anonymous) graph and return to its starting point, building a map of the graph in the process. in our case, instead of a single agent, there are k identical (i.e., mutually indistinguishable) agents initially dispersed among the n nodes of the graph. the agents can communicate by writing to the small public bulletin boards available at each node. the objective is for each agent to build an identically labelled map of the graph; we call this the labelled map construction problem. this problem is much more difficult than exploration by a single agent, because it involves achieving cooperation among multiple agents. in fact, this problem is deterministically unsolvable in some cases. we present deterministic algorithms that successfully and efficiently solve the problem under the condition that the values of n and k are co-prime with each other. we also show how the problem of labelled map construction is related to other problems like leader election and rendezvous of agents.
efficient pebbling for list traversal synopses with application to program rollback. we show how to support efficient back traversal in a unidirectional list, using small memory and with essentially no slowdown in forward steps. using o(lgn) memory for a list of size n, the i'th back-step from the farthest point reached so far takes o(lgi) time in the worst case, while the overhead per forward step is at most @e for arbitrary small constant @e>0. an arbitrary sequence of forward and back steps is allowed. a full trade-off between memory usage and time per back-step is presented: k vs. kn^1^/^k and vice versa. our algorithms are based on a novel pebbling technique which moves pebbles on a virtual binary, or n^1^/^k-ary, tree that can only be traversed in a pre-order fashion. the compact data structures used by the pebbling algorithms, called list traversal synopses, extend to general directed graphs, and have other interesting applications, including memory efficient hash-chain implementation. perhaps the most surprising application is in showing that for any program, arbitrary rollback steps can be efficiently supported with small overhead in memory, and marginal overhead in its ordinary execution. more concretely: let p be a program that runs for at most t steps, using memory of size m. then, at the cost of recording the input used by the program, and increasing the memory by a factor of o(lgt) to o(mlgt), the program p can be extended to support an arbitrary sequence of forward execution and rollback steps: the i'th rollback step takes o(lgi) time in the worst case, while forward steps take o(1) time in the worst case, and 1+@e amortized time per step.
multicommodity flows over time: efficient algorithms and complexity. flow variation over time is an important feature in network flow problems arising in various applications such as road or air traffic control, production systems, communication networks (e.g. the internet) and financial flows. the common characteristic are networks with capacities and transit times on the arcs which specify the amount of time it takes for flow to travel through a particular arc. moreover, in contrast to static flow problems, flow values on arcs may change with time in these networks. while the 'maximum s-t-flow over time' problem can be solved efficiently and 'min-cost flows over time' are known to be np-hard, the complexity of (fractional) 'multicommodity flows over time' has been open for many years. we prove that this problem is np-hard, even for series-parallel networks, and present new and efficient algorithms under certain assumptions on the transit times or on the network topology. as a result, we can draw a complete picture of the complexity landscape for flow over time problems.
complexity results on branching-time pushdown model checking. the model checking problem of pushdown systems (pmc problem, for short) against standard branching temporal logics has been intensively studied in the literature. in particular, for the modal @m-calculus, the most powerful branching temporal logic used for verification, the problem is known to be exptime-complete (even for a fixed formula). the problem remains exptime-complete also for the logic ctl, which corresponds to a fragment of the alternation-free modal @m-calculus. for the logic ctl^*, the problem is known to be in 2exptime. in this paper, we show that the complexity of the pmc problem for ctl^* is in fact 2exptime-complete. moreover, we give a new optimal algorithm to solve this problem based on automata theoretic techniques. finally, we prove that the program complexity of the pmc problem against ctl (i.e., the complexity of the problem in terms of the size of the system) is exptime-complete.
ultraproducts and possible worlds semantics in institutions. we develop possible worlds (kripke) semantics at the categorical abstract model theoretic level provided by the so-called 'institutions'. our general abstract modal logic framework provides a method for systematic kripke semantics extensions of logical systems from computing science and logic. we also extend the institution-independent method of ultraproducts of [r. diaconescu, institution-independent ultraproducts, fundamenta informaticae 55 (3-4) (2003) 321-348] to possible worlds semantics and prove a fundamental preservation result for abstract modal satisfaction. as a consequence we develop a generic compactness result for possible worlds semantics.
losing recognizability. we consider the ranked alphabet @s consisting of a binary symbol. we give a rewrite system r over @s such that r effectively preserves recognizability on any ranked alphabet obtained by adding finitely many nullary symbols to @s. however, r does not preserve recognizability on the ranked alphabet obtained by adding one unary and one nullary symbol to @s.
decoding interleaved reed-solomon codes over noisy channels. we consider error correction over the non-binary symmetric channel (nbsc) which is a natural probabilistic extension of the binary symmetric channel (bsc). we propose a new decoding algorithm for interleaved reed-solomon codes that attempts to correct all ''interleaved'' codewords simultaneously. in particular, interleaved encoding gives rise to multi-dimensional curves and more specifically to a variation of the polynomial reconstruction problem, which we call simultaneous polynomial reconstruction. we present and analyze a novel probabilistic algorithm that solves this problem. our construction yields a decoding algorithm for interleaved rs codes that allows efficient transmission arbitrarily close to the channel capacity in the nbsc model.
generalising automaticity to modal properties of finite structures. we introduce a complexity measure of modal properties of finite structures which generalises the automaticity of languages. it is based on graph-automata-like devices called labelling systems. we define a measure of the size of a structure that we call rank, and show that any modal property of structures can be approximated up to any fixed rank n by a labelling system. the function that takes n to the size of the smallest labelling system doing this is called the labelling index of the property. we demonstrate that this is a useful and fine-grained measure of complexity and show that it is especially well suited to characterise the expressive power of modal fixed-point logics. from this we derive several separation results of modal and non-modal fixed-point logics, some of which are already known whereas others are new.
operational semantics for petri net components. we propose a calculus for marked labelled nets (components), with places and transitions as atoms and merge, addition, fusion and relabelling as operators. the operators are defined using graph-based transformations; each net can be represented by a term. next, we define both a step semantics for nets and a plotkin-style sos semantics for net terms and show their equivalence. in the semantics, both state-oriented and event-oriented properties of components can be expressed. we give a few rules for reducing components to smaller equivalent ones.
strong planning under uncertainty in domains with numerous but identical elements (a generic approach). the typical ai problem is that of making a plan of the actions to be performed by a robot so that the robot could get into a set of final situations, if it started with a certain initial situation. the planning problem is known to be generally very complex. even within the case of 'well-balanced' actions, strong planning under uncertainty about the effects of actions, or games such as 'robot against nature', is exptime-complete. as a result, ai planners are very sensitive to the number of the variables involved in making a plan, the inherent symmetry of the problem, and the nature of the logical formalisms being used. this paper shows that linear logic provides a convenient and adequate tool for representing strong and weak planning problems in non-deterministic domains. a particular focus of this paper is on planning problems with an unbounded number of functionally identical objects. we show that for such problems linear logic is especially effective and leads to a dramatic contraction of the search space from exponential to polynomial in size. we employ the ability of linear logic to reason about multisets, which in this instance are created by identifying several distinct objects as being functionally equivalent for the problem at hand (think of a number of balls, each of which must be moved to some new location - the balls are distinct, but are functionally equivalent for the problem). in linear logic terms, we establish a clear syntactic condition that allows us to show that solving a generic planning problem where there is only one generic object, directly implies a solution to the original real planning problem over several real objects, the isomorphic copies of the generic object. moreover, this correspondence also guarantees to produce a real solution that works in polynomial time.
local rule substitutions and stepped surfaces. substitutions on words, i.e., non-erasing morphisms of the free monoid, are simple combinatorial objects which produce infinite words by iteratively replacing letters by words. this paper introduces a notion of substitution acting on multi-dimensional words, namely local rule substitutions. roughly speaking, local rules play for multi-dimensional words the role played by the concatenation product for substitutions on words. we then particularly focus on the local rule substitutions which act on the two-dimensional words coding stepped surfaces, and we show that a wide class of them can be derived from generalized substitutions.
extension of the decidability of the marked pcp to instances with unique blocks. in the post correspondence problem (pcp) an instance (h,g) consists of two morphisms h and g, and the problem is to determine whether or not there exists a nonempty word w such that h(w)=g(w). here we prove that the pcp is decidable for instances with unique blocks using the decidability of the marked pcp. also, we show that it is decidable whether an instance satisfying the uniqueness condition for continuations has an infinite solution. these results establish a new and larger class of decidable instances of the pcp, including the class of marked instances.
on the cover time and mixing time of random geometric graphs. the cover time and mixing time of graphs has much relevance to algorithmic applications and has been extensively investigated. recently, with the advent of ad hoc and sensor networks, an interesting class of random graphs, namely random geometric graphs, has gained new relevance and its properties have been the subject of much study. a random geometric graph g(n,r) is obtained by placing n points uniformly at random on the unit square and connecting two points iff their euclidean distance is at most r. the phase transition behavior with respect to the radius r of such graphs has been of special interest. we show that there exists a critical radius r"o"p"t such that for any r>=r"o"p"tg(n,r) has optimal cover time of @q(nlogn) with high probability, and, importantly, r"o"p"t=@q(r"c"o"n) where r"c"o"n denotes the critical radius guaranteeing asymptotic connectivity. moreover, since a disconnected graph has infinite cover time, there is a phase transition and the corresponding threshold width is o(r"c"o"n). on the other hand, the radius required for rapid mixing r"r"a"p"i"d=@w(r"c"o"n), and, in particular, r"r"a"p"i"d=@q(1/poly(logn)). we are able to draw our results by giving a tight bound on the electrical resistance and conductance of g(n,r) via certain constructed flows.
factor versus palindromic complexity of uniformly recurrent infinite words. we study the relation between the palindromic and factor complexity of infinite words. we show that for uniformly recurrent words one has p(n)+p(n+1)@?@dc(n)+2, for all n@?n. for a large class of words this is a better estimate of the palindromic complexity in terms of the factor complexity than the one presented in [j.-p. allouche, m. baake, j. cassaigne, d. damanik, palindrome complexity, theoret. comput. sci. 292 (2003) 9-31]. we provide several examples of infinite words for which our estimate reaches its upper bound. in particular, we derive an explicit prescription for the palindromic complexity of infinite words coding r-interval exchange transformations. if the permutation @p connected with the transformation is given by @p(k)=r+1-k for all k, then there is exactly one palindrome of every even length, and exactly r palindromes of every odd length.
discrete random variables over domains. in this paper we initiate the study of discrete random variables over domains. our work is inspired by that of daniele varacca, who devised indexed valuations as models of probabilistic computation within domain theory. our approach relies on new results about commutative monoids defined on domains that also allow actions of the non-negative reals. using our approach, we define two such families of real domain monoids, one of which allows us to recapture varacca's construction of the plotkin indexed valuations over a domain. each of these families leads to the construction of a family of discrete random variables over domains, the second of which forms the object level of a continuous endofunctor on the categories rb (domains that are retracts of bifinite domains), and on fs (domains where the identity map is the directed supremum of deflations finitely separated from the identity). the significance of this last result lies in the fact that there is no known category of continuous domains that is closed under the probabilistic power domain, which forms the standard approach to modelling probabilistic choice over domains. the fact that rb and fs are cartesian closed and also are closed under a power domain of discrete random variables means we can now model, e.g. the untyped lambda calculus extended with a probabilistic choice operator, implemented via random variables.
on dynamic bit-probe complexity. this work present several advances in the understanding of dynamic data structures in the bit-probe model: *we improve the lower bound record for dynamic language membership problems to @w((lgnlglgn)^2). surpassing @w(lgn) was listed as the first open problem in a survey by miltersen. *we prove a bound of @w(lgnlglglgn) for maintaining partial sums in z/2z. previously, the known bounds were @w(lgnlglgn) and o(lgn). *we prove a surprising and tight upper bound of o(lgnlglgn) for the greater-than problem, and several predecessor-type problems. we use this to obtain the same upper bound for dynamic word and prefix problems in group-free monoids. we also obtain new lower bounds for the partial-sums problem in the cell-probe and external-memory models. our lower bounds are based on a surprising improvement of the classic chronogram technique of fredman and saks [michael l. fredman, michael e. saks, the cell probe complexity of dynamic data structures, in: proc. 21st acm symposium on theory of computing stoc, 1989, pp. 345-354], which makes it possible to prove logarithmic lower bounds by this approach. before the work of m. pa@?trascu and demaine [mihai pa@?trascu, erik d. demaine, logarithmic lower bounds in the cell-probe model, siam journal on computing 35 (4) (2006) 932-963. see also soda'04 and stoc'04], this was the only known technique for dynamic lower bounds, and surpassing @w(lgnlglgn) was a central open problem in cell-probe complexity.
new up-to techniques for weak bisimulation. up-to techniques have been introduced to enhance the bisimulation proof method for establishing bisimilarity results. while up-to techniques for strong bisimilarity are well understood, the irregularities that appear in the weak case make it difficult to give a unified presentation. we propose a uniform and modular theory of up-to techniques for weak bisimulation that captures most of the existing proof technology and introduces new techniques. some proofs rely on nontrivial-and new-commutation results based on termination guarantees. all results presented in this paper have been formally proved using the coq proof assistant.
functional stepped surfaces, flips, and generalized substitutions. a substitution is a non-erasing morphism of the free monoid. the notion of multidimensional substitution of non-constant length acting on multidimensional words is proved to be well-defined on the set of two-dimensional words related to discrete approximations of irrational planes. such a multidimensional substitution can be associated with any usual unimodular substitution. the aim of this paper is to extend the domain of definition of such multidimensional substitutions to functional stepped surfaces. one central tool for this extension is the notion of flips acting on tilings by lozenges of the plane.
recursively defined metric spaces without contraction. in this paper we use the theory of accessible categories to find fixed points of endofunctors on the category of 1-bounded complete metric spaces and nonexpansive functions. in contrast to previous approaches, we do not assume that the endofunctors are locally contractive, and our results do not depend on banach's fixed-point theorem. our approach is particularly suitable for constructing models of systems that feature quantitative data. for instance, using the kantorovich metric on probability measures we construct a quantitative model for probabilistic transition systems. the metric in our model can reasonably be seen as measuring the behavioural distance between states of the system; it depends exclusively on the transition probabilities and not on an arbitrary discount factor.
a faster combinatorial approximation algorithm for scheduling unrelated parallel machines. we consider the problem of scheduling n independent jobs on m unrelated parallel machines without preemption. job i takes processing time p"i"j on machine j, and the total time used by a machine is the sum of the processing times for the jobs assigned to it. the objective is to minimize makespan. the best known approximation algorithms for this problem compute an optimum fractional solution and then use rounding techniques to get an integral 2-approximation. in this paper we present a combinatorial approximation algorithm that matches this approximation quality. it is much simpler than the previously known algorithms and its running time is better. this is the first time that a combinatorial algorithm always beats the interior point approach for this problem. our algorithm is a generic minimum cost flow algorithm, without any complex enhancements, tailored to handle unsplittable flow. it pushes unsplittable jobs through a two-layered bipartite generalized network defined by the scheduling problem. in our analysis, we take advantage from addressing the approximation problem directly. in particular, we replace the classical technique of solving the lp-relaxation and rounding afterwards by a completely integral approach. we feel that this approach will be helpful also for other applications.
transposition invariant words. we define an operation called transposition on words of fixed length. this operation arises naturally when the letters of a word are considered as entries of a matrix. words that are invariant with respect to transposition are of special interest. it turns out that transposition invariant words have a simple interpretation by means of elementary group theory. this leads us to investigate some properties of the ring of integers modulo n and primitive roots. in particular, we show that there are infinitely many prime numbers p with a primitive root dividing p+1 and infinitely many prime numbers p without a primitive root dividing p+1. we also consider the orbit of a word under transposition.
on alpha-adic expansions in pisot bases. we study @a-adic expansions of numbers, that is to say, left infinite representations of numbers in the positional numeration system with the base @a, where @a is an algebraic conjugate of a pisot number @b. based on a result of bertrand and schmidt, we prove that a number belongs to q(@a) if and only if it has an eventually periodic @a-adic expansion. then we consider @a-adic expansions of elements of the ring z[@a^-^1] when @b satisfies the so-called finiteness property (f). we give two algorithms for computing these expansions - one for positive and one for negative numbers. in the particular case that @b is a quadratic pisot unit satisfying (f), we inspect the unicity and/or multiplicity of @a-adic expansions of elements of z[@a^-^1]. we also provide algorithms to generate @a-adic expansions of rational numbers in that case.
infinite unfair shuffles and associativity. we consider a general shuffling operation for finite and infinite words which is not necessarily fair. this means that it may be the case that in a shuffle of two words, from some point onwards, one of these words prevails ad infinitum even though the other word still has letters to contribute. prefixes and limits of shuffles are investigated, leading to a characterization of general shuffles in terms of shuffles of finite words, a result which does not hold for fair shuffles. associativity of shuffling is an immediate corollary.
a tight linear bound on the synchronization delay of bijective automata. reversible cellular automata (rca) are models of massively parallel computation that preserve information. we generalize these systems by introducing the class of ^@w^@wbijective finite automata. it consists of those finite automata where for any bi-infinite word there exists a unique path labelled by that word. these systems are strictly included in the class of local automata. although the synchronization delay of an n-state local automaton is known to be @q(n^2) in the worst case, we prove that in the case of ^@w^@wbijective finite automata the synchronization delay is at most n-1. based on this we prove that for a one-dimensional n-state rca where the neighborhood consists of m consecutive cells, the neighbourhood of the inverse automaton consists of at most n^m^-^1-(m-1) cells. similar bounds are obtained also in [e. czeizler, j. kari, a tight linear bound on the neighborhood of inverse cellular automata, in: proceedings of icalp 2005, in: lncs, vol. 3580, 2005, pp. 410-420] but here the result comes as a direct consequence of the more general result. we also construct examples of rca with large inverse neighbourhoods proving that the upper bounds provided here are the best possible in the case m=2.
faster algorithms for finding lowest common ancestors in directed acyclic graphs. we present two new methods for finding a lowest common ancestor (lca) for each pair of vertices of a directed acyclic graph (dag) on n vertices and m edges. the first method is surprisingly natural and solves the all-pairs lca problem for the input dag on n vertices and m edges in time o(nm). the second method relies on a novel reduction of the all-pairs lca problem to the problem of finding maximum witnesses for boolean matrix product. we solve the latter problem (and hence also the all-pairs lca problem) in time o(n^2^+^@l), where @l satisfies the equation @w(1,@l,1)=1+2@l and @w(1,@l,1) is the exponent of the multiplication of an nxn^@l matrix by an n^@lxn matrix. by the currently best known bounds on @w(1,@l,1), the running time of our algorithm is o(n^2^.^5^7^5). our algorithm improves the previously known o(n^2^.^6^8^8) time-bound for the general all-pairs lca problem in dags by bender et al. our additional contribution is a faster algorithm for solving the all-pairs lowest common ancestor problem in dags of small depth, where the depth of a dag is defined as the length of the longest path in the dag. for all dags of depth at most h@?n^@a, where @a~0.294, our algorithm runs in a time that is asymptotically the same as that required for multiplying two nxn matrices, that is, o(n^@w); we also prove that this running time is optimal even for dags of depth 1. for dags with depth h>n^@a, the running time of our algorithm is at most o(n^@w@?h^0^.^4^6^8). this algorithm is faster than our algorithm for arbitrary dags for all values of h@?n^0^.^4^2.
the quantum query complexity of the abelian hidden subgroup problem. simon, in his focs'94 paper, was the first to show an exponential gap between classical and quantum computation. the problem he dealt with is now part of a well-studied class of problems, the hidden subgroup problems. we study simon's problem from the point of view of quantum query complexity and give here a first non-trivial lower bound on the query complexity of a hidden subgroup problem, namely simon's problem. more generally, we give a lower bound which is optimal up to a constant factor for any abelian group.
a geometrical characterization of factors of multidimensional billiard words and some applications. we consider billiard words in alphabets with k>2 letters. such words are associated with some k-dimensional positive vector @a->=(@a"1,@a"2,...,@a"k). the language of these words is already known in the usual case, i.e. when the @a"j are linearly independent over q and so for their inverses. here we study the language of these words when there exist some linear relationships. we give a new geometrical characterization of the factors of billiard words. as a consequence, we get some results on the associated language, and on the complexity and palindromic complexity of these words. the situation is quite different from the usual case. the languages of two distinct billiard words with the same direction generally have a finite intersection. as examples, we get some standard billiard words of three letters without any palindromic factor of even length, or billiard words of three letters whose palindromic factors have a bounded length. these results are obtained by geometrical methods.
a note on the number of squares in a word. fraenkel and simpson [a.s. fraenkel, j. simpson, how many squares can a string contain? j. combin. theory ser. a 82 (1998) 112-120] proved that the number of squares in a word of length n is bounded by 2n. in this note we improve this bound to 2n-@q(logn). based on the numerical evidence, the conjectured bound is n.
conjugacy of morphisms and lyndon decomposition of standard sturmian words. using the notions of conjugacy of morphisms and of morphisms preserving lyndon words, we answer a question of g. melancon. we characterize cases where the sequence of lyndon words in the lyndon factorization of a standard sturmian word is morphic. in each possible case, the corresponding morphism is given.
letter frequency in infinite repetition-free words. we estimate the extremal letter frequency in infinite words over a finite alphabet avoiding some repetitions. for ternary square-free words, we improve the bounds of tarannikov on the minimal letter frequency, and prove that the maximal letter frequency is 255653. kolpakov et al. have studied the function @r such that @r(x) is the minimal letter frequency in an infinite binary x-free word. in particular, they have shown that @r is discontinuous at 73 and at every integer at least 3. we answer one of their questions by providing some other points of discontinuity for @r. finally, we propose stronger versions of dejean's conjecture on repetition threshold in which unequal letter frequencies are required.
weighted automata and weighted logics. weighted automata are used to describe quantitative properties in various areas such as probabilistic systems, image compression, speech-to-text processing. the behaviour of such an automaton is a mapping, called a formal power series, assigning to each word a weight in some semiring. we generalize buchi's and elgot's fundamental theorems to this quantitative setting. we introduce a weighted version of mso logic and prove that, for commutative semirings, the behaviours of weighted automata are precisely the formal power series definable with particular sentences of our weighted logic. we also consider weighted first-order logic and show that aperiodic series coincide with the first-order definable ones, if the semiring is locally finite, commutative and has some aperiodicity property.
balanced allocation and dictionaries with tightly packed constant size bins. we study a particular aspect of the balanced allocation paradigm (also known as the ''two-choices paradigm''): constant sized bins, packed as tightly as possible. let d>=1 be fixed, and assume there are m bins of capacity d each. to each of n@?dm balls two possible bins are assigned at random. how close can dm/n=1+@e be to 1 so that with high probability each ball can be put into one of the two bins assigned to it without any bin overflowing? we show that @e>(2/e)^d^-^1 is sufficient. if a new ball arrives with two new randomly assigned bins, we wish to rearrange some of the balls already present in order to accommodate the new ball. we show that on average it takes constant time to rearrange the balls to achieve this, for @e>@b^d, for some constant @b=1. keys are assigned to buckets by two fully random hash functions. how many keys can be placed in these bins, if key x may go to bin h"1(x) or to bin h"2(x)? we obtain an implementation of a dictionary that accommodates n keys in m=(1+@e)n/d buckets of size d=o(log(1/@e)), so that key x resides in bucket h"1(x) or h"2(x). for a lookup operation, only two hash functions have to be evaluated and two segments of d contiguous memory cells have to be inspected. if d>=1+3.26@?ln(1/@e), a static arrangement exists with high probability. if d>=16@?ln(1/@e), a dynamic version of the dictionary exists so that the expected time for inserting a new key is log(1/@e)^o^(^l^o^g^l^o^g^(^1^/^@e^)^).
powers in a class of a-strict standard episturmian words. this paper concerns a specific class of strict standard episturmian words whose directive words resemble those of characteristic sturmian words. in particular, we explicitly determine all integer powers occurring in such infinite words, extending recent results of damanik and lenz [d. damanik, d. lenz, powers in sturmian sequences, european j. combin. 24 (2003) 377-390, doi:10.1016/s0195-6698(03)00026-x], who studied powers in sturmian words. the key tools in our analysis are canonical decompositions and a generalization of singular words, which were originally defined for the ubiquitous fibonacci word. our main results are demonstrated via some examples, including the k-bonacci word, a generalization of the fibonacci word to a k-letter alphabet (k>=2).
on the arithmetical complexity of sturmian words. using the geometric dual technique by berstel and pocchiola, we give a uniform o(n^3) upper bound for the arithmetical complexity of a sturmian word. we also give explicit expressions for the arithmetical complexity of sturmian words of slope between 1/3 and 2/3 (in particular, of the fibonacci word). in this case, the difference between the genuine arithmetical complexity function and our upper bound is bounded, and ultimately 2-periodic. in fact, our formula is valid not only for sturmian words but for rotation words from a wider class.
discrete rotations and symbolic dynamics. the aim of this paper is to study local configurations issued from discrete rotations. the algorithm of discrete rotations that we consider is the discretized rotation. it simply consists in the composition of a euclidean rotation with a rounding operation, as studied in [b. nouvel, e. remila, on colorations induced by discrete rotations, in: dgci, in: lncs, vol. 2886, 2003, pp. 174-183; b. nouvel, e. remila, characterization of bijective discretized rotations, in: international workshop on combinatorial images analysis, 10th international conference, iwcia 2004, auckland, new zealand, december 1-4, 2004, in: lncs, vol. 3322, 2004, pp. 248-259; b. nouvel, e. remila, configurations induced by discrete rotations: periodicity and quasiperiodicity properties, discrete appl. math. 2-3 (147) (2005) 325-343]. it is possible to encode all the information concerning a discrete rotation as two multidimensional words c"@a and c"@a^' that we call configurations. in this paper, we introduce two discrete dynamical systems defined by a z^2-action on the two-dimensional torus that allow us to describe the configurations c"@a and c"@a^' via a suitable symbolic coding; we then deduce various combinatorial properties for both families of configurations, and in particular, results concerning densities of symbol occurrence.
tight lower bounds for query processing on streaming and external memory data. it is generally assumed that databases have to reside in external, inexpensive storage because of their sheer size. current technology for external storage systems presents us with a reality that, performance-wise, a small number of sequential scans of the data is strictly preferable over random data accesses. database technology-in particular query processing technology-has developed around a notion of memory hierarchies with layers of greatly varying sizes and access times. it seems that the current technologies scale up to their tasks and are very successful, but on closer investigation it may appear that our theoretical understanding of the problems involved-and of optimal algorithms for these problems-is not quite as developed. recently, data stream processing has become an object of study by the database management community, but from the viewpoint of database theory, this is really a special case of the query processing problem on data in external storage where we are limited to a single scan of the input data. in the present paper we study a clean machine model for external memory and stream processing. we establish tight bounds for the data complexity of core xpath evaluation and filtering. we show that the number of scans of the external data induces a strict hierarchy (as long as internal memory space is sufficiently small, e.g., polylogarithmic in the size of the input). we also show that neither joins nor sorting are feasible if the product of the number r(n) of scans of the external memory and the size s(n) of the internal memory buffers is sufficiently small, i.e., of size o(n).
reversals and palindromes in continued fractions. several results on continued fractions expansions are on indirect consequences of the mirror formula. we survey occurrences of this formula for sturmian real numbers, for (simultaneous) diophantine approximation and for formal power series.
partial words and the critical factorization theorem revisited. in this paper, we consider one of the most fundamental results on the periodicity of words, namely the critical factorization theorem. given a word w and nonempty words u,v satisfying w=uv, the minimal local period associated with the factorization (u,v) is the length of the shortest square at position |u|-1. the critical factorization theorem shows that for any word, there is always a factorization whose minimal local period is equal to the minimal period (or global period) of the word. crochemore and perrin presented a linear time algorithm (in the length of the word) that finds a critical factorization from the computation of the maximal suffixes of the word with respect to two total orderings on words: the lexicographic ordering related to a fixed total ordering on the alphabet, and the lexicographic ordering obtained by reversing the order of letters in the alphabet. here, by refining crochemore and perrin's algorithm, we give a version of the critical factorization theorem for partial words (such sequences may contain "do not know" symbols or "holes"). our proof provides an efficient algorithm which computes a critical factorization when one exists. our results extend those of blanchet-sadri and duncan for partial words with one hole. a world wide web server interface at http://www.uncg.edu/mat/research/cft2/ has been established for automated use of the program.
finding large cliques in sparse semi-random graphs by simple randomized search heuristics. surprisingly, general heuristics often solve some instances of hard combinatorial problems quite sufficiently, although they do not outperform specialized algorithms. here, the behavior of simple randomized optimizers on the maximum clique problem is investigated. we focus on semi-random models for sparse graphs, in which an adversary is even allowed to insert a limited number of edges (and not only to remove them). in the course of these investigations the approximation behavior on general graphs and the optimization behavior for sparse graphs and further semi-random graph models are also considered. with regard to the optimizers, particular interest is given to the influences of the population size and the search operator.
reasoning about probabilistic sequential programs. a complete and decidable hoare-style calculus for iteration-free probabilistic sequential programs is presented using a state logic with truth-functional propositional (not arithmetical) connectives.
the bipanconnectivity and m-panconnectivity of the folded hypercube. the interconnection network considered in this paper is the folded hypercube that is an attractive variance of the well-known hypercube. the folded hypercube is superior to the hypercube in many criteria, such as diameter, connectivity and fault diameter. in this paper, we study the path embedding aspects, bipanconnectivity and m-panconnectivity, of the n-dimensional folded hypercube. a bipartite graph is bipanconnected if each pair of vertices x and y are joined by the bipanconnected paths that include a path of each length s satisfying and is even, where n is the number of vertices, and denotes the shortest distance between x and y. a graph is m-panconnected if each pair of vertices x and y are joined by the paths that include a path of each length ranging from m to n-1. in this paper, we introduce a new graph called the path-of-ladders. by presenting algorithms to embed the path-of-ladders into the folded hypercube, we show that the n-dimensional folded hypercube is bipanconnected for n is an odd number. we also show that the n-dimensional folded hypercube is strictly (n-1)-panconnected for n is an even number. that is, each pair of vertices are joined by the paths that include a path of each length ranging from n-1 to n-1; and the value n-1 reaches the lower bound of the problem.
on approximation algorithms of k-connected m-dominating sets in disk graphs. connected dominating set (cds) has been proposed as the virtual backbone to alleviate the broadcasting storm in wireless ad hoc networks. most recent research has extensively focused on the construction of 1-connected 1-dominating set (1-cds) in homogeneous networks. however, the nodes in the cds need to carry other node's traffic and nodes in wireless networks are subject to failure. therefore, it is desirable to construct a fault tolerant cds. in this paper, we study a general fault tolerant cds problem, called k-connected m-dominating set (k-m-cds), in heterogeneous networks. we first present two approximation algorithms for 1-m-cds and k-k-cds problems. using disk graphs to model heterogeneous networks, we show that our algorithms have a constant approximation ratio. based on these two algorithms, we further develop a general algorithm for k-m-cds. we also provide an interesting analysis for a special case of k-m-cds, where k=m+1.
automata theory based on quantum logic: reversibilities and pushdown automata. automata theory based on quantum logic, called l-valued finite automata (l-vfas), may be viewed as a logical approach to quantum computing. this work is mainly divided into two parts: one part deals with reversibility of l-vfas, and the other establishes a basic framework of l-valued pushdown automata (l-vpdas). first we provide some preliminaries concerning quantum logic and l-vfas, and we prove a useful property of l-valued successor and source operators. then we clarify the relationships between various reversibilities closely related to quantum finite automata in the literature. in particular, we define a reversibility of l-vfas which is termed as retrievability, and we clarify the relationships between a number of different fashions regarding retrievability of l-vfas. we prove that some of them are equivalent, but for the others to be equivalent the truth-value set is required to satisfy a certain condition. this is an essential difference from the classical situation. afterwards, we introduce l-vpdas and show that the class of the languages accepted by l-vpdas by empty stack coincides with that accepted by l-vpdas by final state. finally, we provide some examples of l-vfas and conclude with some remarks.
dual-bounded generating problems: efficient and inefficient points for discrete probability distributions and sparse boxes for multidimensional data. we show that |x|@?n|y| must hold for two finite sets x,y@?r^n whenever they can be separated by a nonnegative linear function such that x is above y and the componentwise minimum of any two distinct points in x is dominated by some point in y. as a consequence, we obtain an incremental quasi-polynomial time algorithm for generating all maximal integer feasible solutions for a given monotone system of separable inequalities, for generating all p-inefficient points of a given discrete probability distribution, and for generating all maximal hyper-rectangles which contain a specified fraction of points of a given set in r^n. this provides a substantial improvement over previously known exponential time algorithms for these generation problems related to integer and stochastic programming, and data mining. furthermore, we give an incremental polynomial time generation algorithm for monotone systems with fixed number of separable inequalities, implying that for discrete probability distributions with independent coordinates, both p-efficient and p-inefficient points can be separately generated in incremental polynomial time.
communication tree problems. in this paper, we deal with the problem of constructing optimal communication trees satisfying given communication requirements. we consider two constant degree tree communication models and several cost measures. first, we analyze whether a tree selected at random provides a good randomized approximation algorithm, and we show that such a construction fails for some of the measures. secondly, we provide approximation algorithms for the case in which the communication requirements are given by a random graph in two different random models, namely the classical g"n","p and random geometric graphs. finally, we conclude with some open problems.
pushdown dimension. resource-bounded dimension is a notion of computational information density of infinite sequences based on computationally bounded gamblers. this paper develops the theory of pushdown dimension and explores its relationship with finite-state dimension. the pushdown dimension of any sequence is trivially bounded above by its finite-state dimension, since a pushdown gambler can simulate any finite-state gambler. we show that for every rational 0
optimal routing in double loop networks. in this paper, we study the problem of finding the shortest path in circulant graphs with an arbitrary number of jumps. we provide algorithms specifically tailored for weighted undirected and directed circulant graphs with two jumps which compute the shortest path. our method only requires o(logn) arithmetic operations and the total bit complexity is o(log^2nloglognlogloglogn), where n is the number of the graph's vertices. this elementary and efficient shortest path algorithm has been derived from the closest vector problem (cvp) of lattices in dimension two and with an @?"1 norm.
algorithms for minimum m-connected k-tuple dominating set problem. in wireless sensor networks, a virtual backbone has been proposed as the routing infrastructure to alleviate the broadcasting storm problem and perform some other tasks such as area monitoring. previous work in this area has mainly focused on how to set up a small virtual backbone for high efficiency, which is modelled as the minimum connected dominating set (cds) problem. in this paper we consider how to establish a small virtual backbone to balance efficiency and fault tolerance. this problem can be formalized as the minimum m-connected k-tuple dominating set problem, which is a general version of minimum cds problem with m=1 and k=1. we propose three centralized algorithms with small approximation ratios for small m and improve the current best results for small k.
every real number greater than 1 is a critical exponent. we prove that for every real number @a>1 there exists an infinite word w over a finite alphabet such that @a is the critical exponent of w.
np-completeness results for some problems on subclasses of bipartite and chordal graphs. extending previous np-completeness results for the harmonious coloring problem and the pair-complete coloring problem on trees, bipartite graphs and cographs, we prove that these problems are also np-complete on connected bipartite permutation graphs. we also study the k-path partition problem and, motivated by a recent work of steiner [g. steiner, on the k-path partition of graphs, theoret. comput. sci. 290 (2003) 2147-2155], where he left the problem open for the class of convex graphs, we prove that the k-path partition problem is np-complete on convex graphs. moreover, we study the complexity of these problems on two well-known subclasses of chordal graphs namely quasi-threshold and threshold graphs. based on the work of bodlaender [h.l. bodlaender, achromatic number is np-complete for cographs and interval graphs, inform. process. lett. 31 (1989) 135-138], we show np-completeness results for the pair-complete coloring and harmonious coloring problems on quasi-threshold graphs. concerning the k-path partition problem, we prove that it is also np-complete on this class of graphs. it is known that both the harmonious coloring problem and the k-path partition problem are polynomially solvable on threshold graphs. we show that the pair-complete coloring problem is also polynomially solvable on threshold graphs by describing a linear-time algorithm.
approximating the minimum vertex cover in sublinear time and a connection to distributed algorithms. for a given graph g over n vertices, let opt"g denote the size of an optimal solution in g of a particular minimization problem (e.g., the size of a minimum vertex cover). a randomized algorithm will be called an @a-approximation algorithm with an additive error for this minimization problem if for any given additive error parameter @e>0 it computes a value opt@? such that, with probability at least 2/3, it holds that opt"g@?opt@?@?@a@?opt"g+@en. assume that the maximum degree or average degree of g is bounded. in this case, we show a reduction from local distributed approximation algorithms for the vertex cover problem to sublinear approximation algorithms for this problem. this reduction can be modified easily and applied to other optimization problems that have local distributed approximation algorithms, such as the dominating set problem. we also show that for the minimum vertex cover problem, the query complexity of such approximation algorithms must grow at least linearly with the average degree d@? of the graph. this lower bound holds for every multiplicative factor @a and small constant @e as long as d@?=o(n/@a). in particular this means that for dense graphs it is not possible to design an algorithm whose complexity is o(n).
polylogarithmic-round interactive proofs for conp collapse the exponential hierarchy. if every language in conp has a constant-round interactive proof system, then the polynomial-time hierarchy collapses [r.b. boppana, j. håstad, s. zachos, does co-np have short interactive proofs? information processing letters 25 (2) (1987) 127-132]. on the other hand, the well-known lfkn protocol gives o(n)-round interactive proof systems for all languages in conp [c. lund, l. fortnow, h. karloff, n. nisan, algebraic methods for interactive proof systems, journal of the association for computing machinery 39 (4) (1992) 859-868]. we consider the question of whether it is possible for conp to have interactive proof systems with polylogarithmic-round complexity. we show that this is unlikely by proving that if a conp-complete set has a polylogarithmic-round interactive proof system, then the exponential-time hierarchy collapses. we also consider exponential versions of the karp-lipton theorem and yap's theorem.
block lu factors of generalized companion matrix pencils. we present formulas for computations involving companion matrix pencils as may arise in considering polynomial eigenvalue problems. in particular, we provide explicit companion matrix pencils for matrix polynomials expressed in a variety of polynomial bases including monomial, orthogonal, newton, lagrange, and bernstein/bezier bases. additionally, we give a pair of explicit lu factors associated with each pencil and a prescription for block pivoting when required.
finite automata encoding geometric figures. finite automata are used for the encoding and compression of images. for black-and-white images, for instance, using the quad-tree representation, the black points correspond to @w-words defining the corresponding paths in the tree that lead to them. if the @w-language consisting of the set of all these words is accepted by a deterministic finite automaton then the image is said to be encodable as a finite automaton. for grey-level images and colour images similar representations by automata are in use. in this paper we address the question of which images can be encoded as finite automata with full infinite precision. in applications, of course, the image would be given and rendered at some finite resolution-this amounts to considering a set of finite prefixes of the @w-language-and the features in the image would be approximations of the features in the infinite precision rendering. we focus on the case of black-and-white images-geometrical figures, to be precise-but treat this case in a d-dimensional setting, where d is any positive integer. we show that among all polygons and convex polyhedra in d-dimensional space exactly those with rational corner points are encodable as finite automata. in the course of proving this we show that the set of images encodable as finite automata is closed under rational affine transformations. several properties of images encodable as finite automata are consequences of this result. finally we show that many simple geometric figures such as circles and parabolas are not encodable as finite automata.
enumeration and random generation of accessible automata. we present a bijection between the set a"n of deterministic and accessible automata with n states on a k-letters alphabet and some diagrams, which can themselves be represented as partitions of a set of kn+1 elements into n non-empty subsets. this combinatorial construction shows that the asymptotic order of the cardinality of a"n is related to the stirling number {knn}. our bijective approach also yields an efficient random sampler, for the uniform distribution, of automata with n states, its complexity is o(n^3^/^2), using the framework of boltzmann samplers.
non-unique probe selection and group testing. a minimization problem that has arisen from the study of non-unique probe selection with group testing technique is as follows: given a binary matrix, find a d-disjunct submatrix with the minimum number of rows and the same number of columns. we show that when every probe hybridizes to at most two viruses, i.e., every row contains at most two 1s, this minimization is still max snp-complete, but has a polynomial-time approximation with performance ratio 1+2/(d+1). this approximation is constructed based on an interesting result that the above minimization is polynomial-time solvable when every probe hybridizes to exactly two viruses.
on the spanning connectivity and spanning laceability of hypercube-like networks. let u and v be any two distinct nodes of an undirected graph g, which is k-connected. for 1@?w@?k, a w-containerc(u,v) of a k-connected graph g is a set of w-disjoint paths joining u and v. a w-container c(u,v) of g is a w^*-container if it contains all the nodes of g. a graph g is w^*-connected if there exists a w^*-container between any two distinct nodes. a bipartite graph g is w^*-laceable if there exists a w^*-container between any two nodes from different parts of g. let g"0=(v"0,e"0) and g"1=(v"1,e"1) be two disjoint graphs with |v"0|=|v"1|. let e={(v,@f(v))|v@?v"0,@f(v)@?v"1, and @f:v"0->v"1 is a bijection}. let g=g"0@?g"1=(v"0@?v"1,e"0@?e"1@?e). the set of n-dimensional hypercube-like graph h"n^' is defined recursively as (a) h"1^'={k"2}, k"2= complete graph with two nodes, and (b) if g"0 and g"1 are in h"n^', then g=g"0@?g"1 is in h"n"+"1^'. let b"n^'={g@?h"n^' and g is bipartite} and n"n^'=h"n^'@?b"n^'. in this paper, we show that every graph in b"n^' is w^*-laceable for every w, 1@?w@?n. it is shown that a constructed n"n^'-graph h can not be 4^*-connected. in addition, we show that every graph in n"n^' is w^*-connected for every w, 1@?w@?3.
the increase of the instability of networks due to quasi-static link capacities. in this work, we study the impact of the dynamic changing of the network link capacities on the stability properties of packet-switched networks. especially, we consider the adversarial, quasi-static queuing theory model, where each link capacity may take on only two possible (integer) values, namely 1 and c>1 under a (w,@r)-adversary. we obtain the following results: *allowing such dynamic changes to the link capacities of a network with just ten nodes that uses the lis (longest-in-system) protocol for contention-resolution results in instability at rates @r>2-1 and for large enough values of c. *the combination of dynamically changing link capacities with compositions of contention-resolution protocols on network queues suffices for similar instability bounds: the composition of lis with any of sis (shortest-in-system), nts (nearest-to-source), and ftg (furthest-to-go) protocols is unstable at rates @r>2-1 for large enough values of c. *the instability bound of the network subgraphs that are forbidden for stability is affected by the dynamic changes to the link capacities: we present improved instability bounds for all the directed subgraphs that were known to be forbidden for stability on networks running a certain greedy protocol.
bicriteria scheduling on a batching machine to minimize maximum lateness and makespan. this paper studies the bicriteria problem of scheduling n jobs on a batching machine to minimize maximum lateness and makespan simultaneously. a parallel-batching machine is a machine that can handle up to b jobs in a batch. the jobs in a batch start and complete at the same time, respectively, and the processing time of a batch is equal to the largest processing time of jobs in the batch. we analyse the unbounded model, where b>=n. we present a polynomial-time algorithm for finding all pareto optimal solutions of this bicriteria scheduling problem.
some approximation algorithms for the clique partition problem in weighted interval graphs. interval graphs play important roles in analysis of dna chains in benzer [s. benzer, on the topology of the genetic fine structure, proceedings of the national academy of sciences of the united states of america 45 (1959) 1607-1620], restriction maps of dna in waterman and griggs [m.s. waterman, j.r. griggs, interval graphs and maps of dna, bulletin of mathematical biology 48 (2) (1986) 189-195] and other related areas. in this paper, we study a new combinatorial optimization problem, named the minimum clique partition problem with constrained bounds, in weighted interval graphs. for a weighted interval graph g and a bound b, partition the weighted intervals of this graph g into the smallest number of cliques, such that each clique, consisting of some intervals whose intersection on a real line is not empty, has its weight not beyond b. we obtain the following results: (1) this problem is np-hard in a strong sense, and it cannot be approximated within a factor 32-@e in polynomial time for any @e>0; (2) we design three approximation algorithms with different constant factors for this problem; (3) for the version where all intervals have the same weights, we design an optimal algorithm to solve the problem in linear time.
the linear arboricity of planar graphs with no short cycles. the linear arboricity of a graph g is the minimum number of linear forests which partition the edges of g. akiyama, exoo and harary conjectured that @?@d(g)2@?@?la(g)@?@?@d(g)+12@? for any simple graph g. in the paper, it is proved that if g is a planar graph with @d>=7 and without i-cycles for some i@?{4,5}, then la(g)=@?@d(g)2@?.
efficient algorithms for generalized stable marriage and roommates problems. we consider a generalization of the stable roommates problem (sr), in which preference lists may be partially ordered and forbidden pairs may be present, denoted by srpf. this includes, as a special case, a corresponding generalization of the classical stable marriage problem (sm), denoted by smpf. by extending previous work of feder, we give a two-step reduction from srpf to 2-sat. this has many consequences, including fast algorithms for a range of problems associated with finding ''optimal'' stable matchings and listing all solutions, given variants of sr and sm. for example, given an smpf instance i, we show that there exists an o(m) ''succinct'' certificate for the unsolvability of i, an o(m) algorithm for finding all the super-stable pairs in i, an o(m+kn) algorithm for listing all the super-stable matchings in i, an o(m^1^.^5) algorithm for finding an egalitarian super-stable matching in i, and an o(m) algorithm for finding a minimum regret super-stable matching in i, where n is the number of men, m is the total length of the preference lists, and k is the number of super-stable matchings in i. analogous results apply in the case of srpf.
bounds on the bisection width for random d -regular graphs. in this paper we provide an explicit way to compute asymptotically almost sure upper bounds on the bisection width of random d-regular graphs, for any value of d. the upper bounds are obtained from the analysis of the performance of a randomized greedy algorithm to find bisections of d-regular graphs. we provide bounds for 5&le;d&le;12. we also give empirical values of the size of the bisection found by the algorithm for some small values of d and compare them with numerical approximations of our theoretical bounds. our analysis also gives asymptotic lower bounds for the size of the maximum bisection.
model checking mobile stochastic logic. the temporal mobile stochastic logic (mosl) has been introduced in previous work by the authors for formulating properties of systems specified in stoklaim, a markovian extension of klaim. the main purpose of mosl is to address key functional aspects of global computing such as distribution awareness, mobility, and security and their integration with performance and dependability guarantees. in this paper, we present mosl^+, an extension of mosl, which incorporates some basic features of the modal logic for mobility (momo), a logic specifically designed for dealing with resource management and mobility aspects of concurrent behaviours. we also show how mosl^+ formulae can be model-checked against stoklaim specifications. for this purpose, we show how existing state-based stochastic model-checkers, like e.g. the markov reward model checker (mrmc), can be exploited by using a front-end for stoklaim that performs appropriate pre-processing of mosl^+ formulae. the proposed approach is illustrated by modelling and verifying a sample system.
complexity of the bisection method. the bisection method is the consecutive bisection of a triangle by the median of the longest side. in this paper we prove a subexponential asymptotic upper bound for the number of similarity classes of triangles generated on a mesh obtained by iterative bisection, which previously was known only to be finite. the relevant parameter is &gamma;/&sigma;, where &gamma; is the biggest and &sigma; is the smallest angle of the triangle. we get this result by introducing a taxonomy of triangles that precisely captures the behaviour of the bisection method. we also prove that the number of directions on the plane given by the sides of the triangles generated is finite. additionally, we give purely geometrical and intuitive proofs of classical results for the bisection method.
on dejean's conjecture over large alphabets. the (maximal) exponent of a non-empty finite word is the ratio of its length to its period. dejean (1972) conjectured that for any n≥5 there exists an infinite word over n letters with no factor of its exponent larger than n/(n-1). we prove that this conjecture is true for n≥33.
mixing logics and rewards for the component-oriented specification of performance measures. formal notations for system performance modeling need to be equipped with suitable notations for specifying performance measures. these companion notations have been traditionally based on reward structures and, more recently, on temporal logics. in this paper we propose an approach that combines logics and rewards, together with a definition mechanism that allows performance measures to be specified in a component-oriented way, thus facilitating the task for non-experts. the resulting measure specification language (msl) is interpreted both on action-labeled continuous-time markov chains and on stochastic process algebras. the latter interpretation provides a compositional framework for performance-sensitive model manipulations and emphasizes the increased expressiveness with respect to traditional reward structures for implicit-state modeling notations.
csl model checking algorithms for qbds. we present an in-depth treatment of model checking algorithms for a class of infinite-state continuous-time markov chains known as quasi-birth death processes. the model class is described in detail, as well as the logic csl to express properties of interest. using a new property-independency concept, we provide model checking algorithms for all the csl operators. special emphasis is given to the time-bounded until operator for which we present a new and efficient computational procedure named uniformization with representatives. by the use of an application-driven dynamic stopping criterion, the algorithm stops whenever the property to be checked can be certified (or falsified). a comprehensive case study of a connection management system shows the versatility of our new algorithms.
learning intersection-closed classes with signatures. intersection-closed classes of concepts arise naturally in many contexts and have been intensively studied in computational learning theory. in this paper, we study intersection-closed classes that contain the concepts invariant under an operation satisfying a certain algebraic condition. we give a learning algorithm in the exact model with equivalence queries for such classes. this algorithm utilizes a novel encoding scheme, which we call a signature.
learning tree languages from positive examples and membership queries. we investigate regular tree languages' exact learning from positive examples and membership queries. input data are trees of the language to infer. the learner computes new trees from the inputs and asks the oracle whether or not they belong to the language. from the answers, the learner may ask further membership queries until he finds the correct grammar that generates the target language. this paradigm was introduced by angluin in the seminal work [d. angluin, a note on the number of queries needed to identify regular languages, information and control 51 (1981) 76-87] for the case of regular word languages. neither negative examples, equivalence queries nor counter-examples are allowed in this paradigm. we describe an efficient algorithm which is polynomial in the size of the examples for learning the whole class of regular tree languages. the convergence is ensured when the set of examples contains a representative sample of the language to guess. a finite subset of a regular tree language is representative for if every transition of the minimal tree automaton for is used at least once for the derivation of an element of the set .
on the complexity of working set selection. the decomposition method is currently one of the major methods for solving the convex quadratic optimization problems being associated with support vector machines (svm-optimization). a key issue in this approach is the policy for working set selection. we would like to find policies that realize (as well as possible) three goals simultaneously: ''(fast) convergence to an optimal solution'', ''efficient procedures for working set selection'', and ''a high degree of generality'' (including typical variants of svm-optimization as special cases). in this paper, we study a general policy for working set selection that has been proposed in [nikolas list, hans ulrich simon, a general convergence theorem for the decomposition method, in: proceedings of the 17th annual conference on computational learning theory, 2004, pp. 363-377] and further analyzed in [nikolas list, hans ulrich simon, general polynomial time decomposition algorithms, in: proceedings of the 17th annual conference on computational learning theory, 2005, pp. 308-322]. it is known that it efficiently approaches feasible solutions with minimum cost for any convex quadratic optimization problem. here, we investigate its computational complexity when it is used for svm-optimization. it turns out that, for a variable size of the working set, the general policy poses an np-hard working set selection problem. but a slight variation of it (sharing the convergence properties with the original policy) can be solved in polynomial time. for working sets of fixed size 2, the situation is even better. in this case, the general policy coincides with the ''rate certifying pair approach'' (introduced by hush and scovel). we show that maximum rate certifying pairs can be found in linear time, which leads to a quite efficient decomposition method with a polynomial convergence rate for svm-optimization.
formalization of the standard uniform random variable. continuous random variables are widely used to mathematically describe random phenomena in engineering and the physical sciences. in this paper, we present a higher-order logic formalization of the standard uniform random variable as the limit value of the sequence of its discrete approximations. we then show the correctness of this specification by proving the corresponding probability distribution properties within the hol theorem prover, summarizing the proof steps. the formalized standard uniform random variable can be transformed to formalize other continuous random variables, such as uniform, exponential, normal, etc., by using various non-uniform random number generation techniques. the formalization of these continuous random variables will enable us to perform an error free probabilistic analysis of systems within the framework of a higher-order-logic (hol) theorem prover. for illustration purposes, we present the formalization of the continuous uniform random variable based on the formalized standard uniform random variable, and then utilize it to perform a simple probabilistic analysis of roundoff error in hol.
complexity of pattern classes and the lipschitz property. rademacher and gaussian complexities are successfully used in learning theory for measuring the capacity of the class of functions to be learnt. one of the most important properties for these complexities is their lipschitz property: a composition of a class of functions with a fixed lipschitz function may increase its complexity by at most twice the lipschitz constant. the proof of this property is non-trivial (in contrast to the case for the other properties) and it is believed that the proof in the gaussian case is conceptually more difficult than the one for the rademacher case. in this paper we give a detailed proof of the lipschitz property for the general case of a symmetric complexity measure that includes the rademacher and gaussian complexities as special cases. we also consider the rademacher complexity of a function class consisting of all the lipschitz functions with a given lipschitz constant. we show that the complexity of the class is surprisingly low in the one-dimensional case. finally, we introduce a relaxation of the definition of rademacher complexity to rademacher free complexity and show that not only can this complexity replace the standard definition in the key theorem, but also the bounds for composed function classes are tighter.
approximation schemes for a class of subset selection problems. in this paper we develop an easily applicable algorithmic technique/tool for developing approximation schemes for certain types of combinatorial optimization problems. special cases that are covered by our result show up in many places in the literature. for every such special case, a particular rounding trick has been implemented in a slightly different way, with slightly different arguments, and with slightly different worst case estimations. usually, the rounding procedure depended on certain upper or lower bounds on the optimal objective value that have to be justified in a separate argument. our easily applied result unifies many of these results, and sometimes it even leads to a simpler proof. we demonstrate how our result can be easily applied to a broad family of combinatorial optimization problems. as a special case, we derive the existence of an fptas for the scheduling problem of minimizing the weighted number of late jobs under release dates and preemption on a single machine. the approximability status of this problem has been open for some time.
revising threshold functions. a revision algorithm is a learning algorithm that identifies the target concept, starting from an initial concept. such an algorithm is considered efficient if its complexity (in terms of the resource one is interested in) is polynomial in the syntactic distance between the initial and the target concept, but only polylogarithmic in the number of variables in the universe. we give an efficient revision algorithm in the model of learning with equivalence and membership queries for threshold functions, and some negative results showing, for instance, that threshold functions cannot be revised efficiently from either type of query alone. the algorithms work in a general revision model where both deletion and addition type revision operators are allowed.
on the data consumption benefits of accepting increased uncertainty. in the context of learning paradigms of identification in the limit, we address the question: why is uncertainty sometimes desirable? we use mind change bounds on the output hypotheses as a measure of uncertainty and interpret 'desirable' as reduction in data memorization, also defined in terms of mind change bounds. the resulting model is closely related to iterative learning with bounded mind change complexity, but the dual use of mind change bounds - for hypotheses and for data - is a key distinctive feature of our approach. we show that situations exist where the more mind changes the learner is willing to accept, the less the amount of data it needs to remember in order to converge to the correct hypothesis. we also investigate relationships between our model and learning from good examples, set-driven, monotonic and strong-monotonic learners, as well as class-comprising versus class-preserving learnability.
on the (im)possibility of non-interactive correlation distillation. we study the problem of non-interactive correlation distillation (nicd). suppose that alice and bob each have a string, denoted by a=a0a1&hellip;an-1 and b=b0b1&hellip;bn-1, respectively. furthermore, for every k=0,1,&hellip;,n-1, (ak,bk) is drawn independently from a distribution , known as the 'noise model'. alice and bob wish to 'distill' the correlation non-interactively, i.e., they wish to each apply a function to their strings, and output one random bit, denoted by x and y, such that pr[x=y] can be made as close to 1 as possible. the problem is, for what noise models can they succeed? this problem is related to various topics in computer science, including information reconciliation and random beacons. in fact, if nicd is indeed possible for some general class of noise models, then some of these topics would, in some sense, become straightforward corollaries. we prove two negative results on nicd for various noise models. we prove that, for these models, it is impossible to distill the correlation to be arbitrarily close to 1. we also give an example where alice and bob can increase their correlation with one bit of communication (in this case they need to each output two bits). this example, which may be of interest on its own, demonstrates that even the smallest amount of communication is provably more powerful than no communication.
applications of regularized least squares to pattern classification. we survey a number of recent results concerning the behaviour of algorithms for learning classifiers based on the solution of a regularized least-squares problem.
on coding labeled trees. we consider the problem of coding labeled trees by means of strings of node labels. different codes have been introduced in the literature by pr&uuml;fer, neville, and deo and micikevičius. for all of them, we show that both coding and decoding can be reduced to integer (radix) sorting, closing several open problems within a unified framework that can be applied both in a sequential and in a parallel setting. our sequential coding and decoding schemes require optimal o(n) time when applied to n-node trees, yielding the first linear time decoding algorithm for a code presented by neville. these schemes can be parallelized on the erew pram model, so as to work in o(logn) time with cost o(n), , or o(nlogn), depending on the code and on the operation: in all cases, they either match or improve the performances of the best ad hoc approaches known so far.
a unified access bound on comparison-based dynamic dictionaries. we present a dynamic comparison-based search structure that supports insertions, deletions, and searches within the unified bound. the unified bound specifies that it is quick to access an element that is near a recently accessed element. more precisely, if w(y) distinct elements have been accessed since the last access to element y, and d(x,y) denotes the rank distance between x and y among the current set of elements, then the amortized cost to access element x is o(minylog[w(y)+d(x,y)+2]). this property generalizes the working-set and dynamic-finger properties of splay trees.
complementation of rational sets on scattered linear orderings of finite rank. in a preceding paper [v. bruy&egrave;re, o. carton, automata on linear orderings, in: j. sgall, a. pultr, p. kolman (eds.), mfcs'2001, in: lect. notes in comput. sci., vol. 2136, 2001, pp. 236-247. igm report 2001-12], automata have been introduced for words indexed by linear orderings. these automata are a generalization of automata for finite, infinite, bi-infinite, and even transfinite words studied by b&uuml;chi. kleene's theorem has been generalized to these words. we show that deterministic automata do not have the same expressive power. despite this negative result, we prove that rational sets of words of finite ranks are closed under complementation.
centralized asynchronous broadcast in radio networks. we study asynchronous broadcasting in packet radio networks. a radio network is represented by a directed graph, in which one distinguished source node stores a message that needs to be disseminated among all the remaining nodes. an asynchronous execution of a protocol is a sequence of events, each consisting of simultaneous deliveries of messages. the correctness of protocols is considered for specific adversarial models defined by restrictions on events the adversary may schedule. a protocol specifies how many times the source message is to be retransmitted by each node. the total number of transmissions over all the nodes is called the work of the broadcast protocol; it is used as complexity measure. we study computational problems, to be solved by deterministic centralized algorithms, either to find a broadcast protocol or to verify the correctness of a protocol, for a given network. the amount of work necessary to make a protocol correct may have to be exponential in the size of network. there is a polynomial-time algorithm to find a broadcast protocol for a given network. we show that certain problems about broadcasting protocols for given networks are complete in np and co-np complexity classes.
ockham's razor, empirical complexity, and truth-finding efficiency. the nature of empirical simplicity and its relationship to scientific truth are long-standing puzzles. in this paper, empirical simplicity is explicated in terms of empirical effects, which are defined in terms of the structure of the inference problem addressed. problem instances are classified according to the number of empirical effects they present. simple answers are satisfied by simple worlds. an efficient solution achieves the optimum worst-case cost over each complexity class with respect to such costs as the number of retractions or errors prior to convergence and elapsed time to convergence. it is shown that always choosing the simplest theory compatible with experience and hanging on to it while it remains the simplest is both necessary and sufficient for efficiency.
feedback vertex sets in mesh-based networks. in this paper, we consider the minimum feedback vertex set problem in graphs, i.e., the problem of finding a minimal cardinality subset of the vertices, whose removal makes a graph acyclic. the problem is np-hard for general topologies, but optimal and near-optimal solutions have been provided for particular networks. in this paper, the problem is considered for undirected graphs with the following topologies: two- and higher-dimensional meshes of trees, trees of meshes, and pyramid networks. for the two-dimensional meshes of trees the results are optimal; for the higher-dimensional meshes of trees and the tree of meshes the results are asymptotically optimal. for the pyramid networks, there remains a small factor between the upper and the lower bounds.
a comparison of simulated annealing with a simple evolutionary algorithm on pseudo-boolean functions of unitation. the development in the area of randomized search heuristics has shown the importance of a rigorous theoretical analysis of the performance of these heuristics. unfortunately, the analysis of the expected optimization time of a specific algorithm has in general no implications on the behaviour of other algorithms - even if they differ only in some aspects. indeed, small differences may imply large differences in the optimization time. hence, it is an important issue to compare fundamental heuristics and to find out for which problems they behave in such a similar way that results on one heuristic can be transferred to the other one and to describe problems where they behave quite differently. such an approach is performed here to the simple and well-known (1+1) ea, which is based on elitist selection and a global search operator, and simulated annealing, which is based on nonelitist selection and a local search operator.
swapping a failing edge of a shortest paths tree by minimizing the average stretch factor. we consider a two-edge connected, undirected graph g=(v,e), with n nodes and m non-negatively real weighted edges, and a single source shortest paths tree (spt) t of g rooted at an arbitrary node r. if an edge in t is temporarily removed, it makes sense to reconnect the nodes disconnected from the root by adding a single non-tree edge, called a swap edge, instead of rebuilding a new optimal spt from scratch. in the past, several optimality criteria have been considered to select a best possible swap edge. in this paper we focus on the most prominent one, that is the minimization of the average distance between the root and the disconnected nodes. to this respect, we present an o(mlog2n) time and o(m) space algorithm to find a best swap edge for every edge of t, thus improving for m=o(n2/log2n) the previously known o(n2) time and space complexity algorithm.
a lower bound on complexity of optimization on the wiener space. this paper is a study of the complexity of optimization of continuous univariate functions using a fixed number of sequentially selected function evaluations. the complexity is studied in the average case under a conditioned wiener measure. we show that to obtain an error of at most &epsilon;, on the order of loglog(1/&epsilon;)log(1/&epsilon;) function evaluations are required.
autopoietic automata: complexity issues in offspring-producing evolving processes. we introduce a new formal computational model designed for studying the information transfer among the generations of offspring-producing evolving machines - so-called autopoietic automata. these can be seen as nondeterministic finite state transducers whose ''program'' can become a subject of their own processing. an autopoietic automaton can algorithmically generate an offspring controlled by a program which is a modification of its parent's program. autopoietic automata offer a neat framework for investigating computational and complexity issues in the evolutionary self-reproducing processes. we show that the computational power of lineages of autopoietic automata is equal to that of an interactive nondeterministic turing machine. we also prove that there exists an autopoietic automaton giving rise to an unlimited evolution, provided that suitable inputs are delivered to individual automata. however, the problem of sustainable evolution, asking whether for an arbitrary autopoietic automaton and arbitrary inputs there is an infinite lineage of its offspring, is undecidable.
state complexity of combined operations. we study the state complexity of combined operations. two particular combined operations are studied: star of union and star of intersection. it is shown that the state complexity of a combined operation is not necessarily similar to the combination of the individual state complexities of the participating operations.
approximation algorithm for hotlink assignment in the greedy model. link-based information structures such as the web can be enhanced through the addition of hotlinks. assume that each node in the information structure is associated with a weight representing the access frequency of the node by users. in order to access a particular node, the user must follow a path leading to it from the root. by adding new hotlinks to the tree, it may be possible to reduce the access cost of the system, namely, the expected number of steps needed to reach a leaf from the root, assuming the user can decide which hotlinks to follow in each step. the hotlink assignment problem involves finding a set of hotlinks (with at most k=o(1) hotlinks emanating from every node) maximizing the gain in the expected cost. the paper addresses this problem in two user models, namely, the traditional clairvoyant user model employed in [p. bose, j. czyzowicz, l. gasieniec, e. kranakis, d. krizanc, a. pelc, m.v. martin, strategies for hotlink assignments, in: proc. 11th symp. on algorithms and computation, 2000, pp. 23-34; e. kranakis, d. krizanc, s. shende, approximating hotlink assignments, in: proc. 12th symp. on algorithms and computation, 2001, pp. 756-767; p. bose, d. krizanc, s. langerman, p. morin, asymmetrical communication protocols via hotlink assignments, in: proc. 9th colloq. on structural information and communication complexity, 2002, pp. 33-39; r. matichin, d. peleg, approximation algorithm for hotlink assignments in web directories, in: proc. workshop on algorithms and data structures, 2003, pp. 271-280] and the more realistic greedy user model recently introduced in [o. gerstel, s. kutten, r. matichin, d. peleg, hotlink enhancement algorithms for web directories, in: proc. 14th symp. on algorithms and computation, 2003, pp. 68-77], and presents a polynomial time 2-approximation algorithm for the hotlink assignment problem on rooted directed trees.
long-lived rambo: trading knowledge for communication. shareable data services providing consistency guarantees, such as atomicity (linearizability), make building distributed systems easier. however, combining linearizability with efficiency in practical algorithms is difficult. a reconfigurable linearizable data service, called rambo, was developed by lynch and shvartsman. this service guarantees consistency under dynamic conditions involving asynchrony, message loss, node crashes, and new node arrivals. the specification of the original algorithm is given at an abstract level aimed at concise presentation and formal reasoning about correctness. the algorithm propagates information by means of gossip messages. if the service is in use for a long time, the size and the number of gossip messages may grow without bound. this paper presents a consistent data service for long-lived objects that improves on rambo in two ways: it includes an incremental communication protocol and a leave service. the new protocol takes advantage of the local knowledge, and carefully manages the size of messages by removing redundant information, while the leave service allows the nodes to leave the system gracefully. the new algorithm is formally proved correct by forward simulation using levels of abstraction. an experimental implementation of the system was developed for networks-of-workstations. the paper also includes selected analytical and preliminary empirical results that illustrate the advantages of the new algorithm.
spanners for bounded tree-length graphs. this paper concerns construction of additive stretched spanners with few edges for n-vertex graphs having a tree-decomposition into bags of diameter at most @d, i.e., the tree-length @d graphs. for such graphs we construct additive 2@d-spanners with o(@dn+nlogn) edges, and additive 4@d-spanners with o(@dn) edges. this provides new upper bounds for chordal graphs for which @d=1. we also show a lower bound, and prove that there are graphs of tree-length @d for which every multiplicative @d-spanner (and thus every additive (@d-1)-spanner) requires @w(n^1^+^1^/^@q^(^@d^)) edges.
circuit principles and weak pigeonhole variants. this paper considers the relational versions of the surjective, partial surjective, and multifunction weak pigeonhole principles for pv, @?"1^b, @?"1^b, and b(@?"1^b) formulas as well as relativizations of these formulas to higher levels of the bounded arithmetic hierarchy. we show that the partial surjective weak pigeonhole principle for @?"1^b formulas implies that for each k there is a string of length 2^2^n^^^k which is hard to block-recognize by circuits of size n^k. these principles in turn imply the partial surjective principle for @?"1^b formulas. we show that the surjective weak pigeonhole principle for b(@?"1^b) formulas in s"2^1 implies our hard-string principle which in turn implies the surjective weak pigeonhole principle for @?"1^b formulas. we introduce a class of predicates corresponding to poly-log length iterates of polynomial time computable predicates and show that over s"2^1, the multifunction weak pigeonhole principle for such predicates is equivalent to an ''iterative'' circuit block-recognition principle. a consequence of this is that if s"2^1 proves this principle then rsa is vulnerable to polynomial time attacks.
query-monotonic turing reductions. we study reductions that limit the extreme adaptivity of turing reductions. in particular, we study reductions that make a rapid, structured progression through the set to which they are reducing: each query is strictly longer (shorter) than the previous one. we call these reductions query-increasing (query-decreasing) turing reductions. we also study query-nonincreasing (query-nondecreasing) turing reductions. these are turing reductions in which the sequence of query lengths is nonincreasing (nondecreasing). we ask whether these restrictions in fact limit the power of reductions. we prove that query-increasing and query-decreasing turing reductions are incomparable with (that is, are neither strictly stronger than nor strictly weaker than) truth-table reductions and are strictly weaker than turing reductions. in addition, we prove that query-nonincreasing and query-nondecreasing turing reductions are strictly stronger than truth-table reductions and strictly weaker than turing reductions. despite the fact that we prove query-increasing and query-decreasing turing reductions to in the general case be strictly weaker than turing reductions, we identify a broad class of sets a for which any set that turing reduces to a will also reduce to a via both query-increasing and query-decreasing turing reductions. in particular, this holds for all tight paddable sets, where a set is said to be tight paddable exactly if it is paddable via a function whose output length is bounded tightly both from above and from below in the length of the input. we prove that many natural np-complete problems such as satisfiability, clique, and vertex cover are tight paddable.
the kolmogorov complexity of infinite words. we present a brief survey of results on relations between the kolmogorov complexity of infinite strings and several measures of information content (dimensions) known from dimension theory, information theory or fractal geometry. special emphasis is placed on bounds on the complexity of strings in constructively given subsets of the cantor space. finally, we compare the kolmogorov complexity to the subword complexity of infinite strings.
the $-calculus process algebra for problem solving: a paradigmatic shift in handling hard computational problems. the $-calculus is the extension of the &pi;-calculus, built around the central notion of cost and allowing infinity in its operators. we propose the $-calculus as a more complete model for problem solving to provide a support to handle intractability and undecidability. it goes beyond the turing machine model. we define the semantics of the $-calculus using a novel optimization method (the k&omega;-optimization), which approximates a nonexisting universal search algorithm and allows the simulation of many other search methods. in particular, the notion of total optimality has been utilized to provide an automatic way to deal with intractability of problem solving by optimizing together the quality of solutions and search costs. the sufficient conditions needed for completeness, optimality and total optimality of problem solving search are defined. a very flexible classification scheme of problem solving methods into easy, hard and solvable in the limit classes has been proposed. in particular, the third class deals with non-recursive solutions of undecidable problems. the approach is illustrated by solutions of some intractable and undecidable problems. we also briefly overview two possible implementations of the $-calculus.
time efficient centralized gossiping in radio networks. in this paper we study the gossiping problem (all-to-all communication) in radio networks where all nodes are aware of the network topology. we start our presentation with a deterministic gossiping algorithm that works in at most n units of time in any radio network of size n. this algorithm is optimal in the worst case scenario since there exist radio network topologies, such as lines, stars and complete graphs in which radio gossiping cannot be completed in less than n communication rounds. furthermore, we show that there does not exist any radio network topology in which the gossiping task can be solved in less than @?log(n-1)@?+2 rounds. we also show that this lower bound can be matched from above for a fraction of all possible integer values of n, and for all other values of n we propose a solution which accomplishes gossiping in @?log(n-1)@?+2 rounds. then we show an almost optimal radio gossiping algorithm in trees, which misses the optimal time complexity by a single round. finally, we study asymptotically optimal o(d)-time gossiping (where d is the diameter of the network) in graphs with the maximum degree @d=o(d^1^-^1^/^(^i^+^1^)log^in), for any integer constant i>=0 and d large enough.
algorithmic complexity as a criterion of unsolvability. there is a dependency between computability of algorithmic complexity and decidability of different algorithmic problems. it is known that computability of the algorithmic complexity c(x) is equivalent to decidability of the halting problem for turing machines. here we extend this result to the realm of superrecursive algorithms, considering algorithmic complexity for inductive turing machines. we study two types of algorithmic complexity: recursive (classical) and inductive algorithmic complexities. relations between these types of algorithmic complexity and decidability of algorithmic problems for turing machines and inductive turing machines are considered. in particular, it is demonsrated that computability of algorithmic complexity is equivalent not only to decidability of the halting problem, but also to decidability by inductive turing machines of the first order of many other problems for turing machines, such as: if a turing machine computes a recursive (total) function; if a turing machine gives no result only for n inputs; if a turing machine gives results only for n inputs.
a simple randomized scheme for constructing low-weight k-connected spanning subgraphs with applications to distributed algorithms. the main focus of this paper is the analysis of a simple randomized scheme for constructing low-weight k-connected spanning subgraphs. in this paper, we focus on the metric graph. we use the term metric graph for a complete graph with metric weights. we first show that our scheme gives a simple approximation algorithm to construct a minimum-weight k-connected spanning subgraph in a metric graph, an np-hard problem. we show that our algorithm gives an approximation ratio of o(klogn) for a metric graph, o(k) for a random graph with nodes uniformly randomly distributed in [0,1]2 and for a complete graph with random edge weights u(0,1). we show that our scheme is optimal with respect to the amount of "local information" needed to compute any connected spanning subgraph. we then show that our scheme can be applied to design an efficient distributed algorithm for constructing such an approximate k-connected spanning subgraph (for any k≥1) in a point-to-point distributed model, where the processors form a complete network. our algorithm takes time and an expected number of messages. our result in conjunction with a result of korach et al. [e. korach, s. moran, s. zaks, the optimality of distributive constructions of minimum weight and degree restricted spanning trees in a complete network of processors, siam journal on computing 16 (2) (1987) 231-236] implies that the expected message complexity of our algorithm is significantly better than the best distributed algorithm that finds an optimal k-connected subgraph. we also show that for geometric instances, our randomized scheme constructs low-degree k-connected spanning subgraphs which have o(klogn) maximum degree, with high probability.
alphabet-independent linear-time construction of compressed suffix arrays using o(nlogn)-bit working space. the suffix array is a fundamental index data structure in string algorithms and bioinformatics, and the compressed suffix array (csa) and the fm-index are its compressed versions. many algorithms for constructing these index data structures have been developed. recently, hon et al. [w.k. hon, k. sadakane, w.k. sung, breaking a time-and-space barrier in constructing full-text indices, in: proceedings of the 44th annual ieee symposium on foundations of computer science, 2003, pp. 251-260] proposed a construction algorithm using o(nloglog|σ|) time and o(nlog|σ|)-bit working space, which is the fastest algorithm using o(nlog|σ|)-bit working space. in this paper we give an efficient algorithm to construct the index data structures. our algorithm constructs the suffix array, the csa, the fm-index, and burrows-wheeler transform using alphabet-independent o(n) time and -bit working space, where &alpha;=log32. our algorithm takes less time and more space than hon et al.'s algorithm. our algorithm uses least working space among alphabet-independent linear-time algorithms.
parallel computation in spiking neural nets. numerical quantities can be represented as phase differences between equiperiodic oscillating subsystems in a spiking neural net. it is then possible to represent integer variables, and the increment and decrement operations, x:=x+1, x:=x-1. it is possible to represent the if construction, the while construction, and some other programming language constructions, including variants of the seq, par, and alt constructors, which were used in occam. we give a general purpose parallel programming language with integer variables which can be systematically implemented in spiking neural networks. addition, subtraction and multiplication are done, albeit inefficiently, as examples.
on the complexity of the sandwich problems for strongly chordal graphs and chordal bipartite graphs. golumbic, kaplan, and shamir, in their paper [m.c. golumbic, h. kaplan, r. shamir, graph sandwich problems, j. algorithms 19 (1995) 449-473] on graph sandwich problems published in 1995, left the status of sandwich problems for strongly chordal graphs and chordal bipartite graphs open. we prove that the sandwich problem for strongly chordal graphs is np-complete. we also give some comments on the computational complexity of the sandwich problem for chordal bipartite graphs.
on the fairness and complexity of generalized k-in-a-row games. recently, wu and huang [i.-c. wu, d.-y. huang, a new family of k-in-a-row games, in: the 11th advances in computer games conference, acg'11, taipei, taiwan, september 2005] introduced a new game called connect6, where two players, black and white, alternately place two stones of their own color, black and white respectively, on an empty go-like board, except for that black (the first player) places one stone only for the first move. the one who gets six consecutive (horizontally, vertically or diagonally) stones of his color first wins the game. unlike go-moku, connect6 appears to be fairer and has been adopted as an official competition event in computer olympiad 2006. connect(m,n,k,p,q) is a generalized family of k-in-a-row games, where two players place p stones on an mxn board alternatively, except black places q stones in the first move. the one who first gets his stones k-consecutive in a line (horizontally, vertically or diagonally) wins. connect6 is simply the game of connect(m,n,6,2,1). in this paper, we study two interesting issues of connect(m,n,k,p,q): fairness and complexity. first, we prove that no one has a winning strategy in connect(m,n,k,p,q) starting from an empty board when k>=4p+7 and p>=q. second, we prove that, for any fixed constants k,p such that k-p>=max{3,p} and a given connect(m,n,k,p,q) position, it is pspace-complete to determine whether the first player has a winning strategy. consequently, this implies that connect6 played on an mxn board (i.e., connect(m,n,6,2,1)) is pspace-complete.
path constraints in semistructured data. we consider semistructured data as multirooted edge-labelled directed graphs, and path inclusion constraints on these graphs. a path inclusion constraint p@?q is satisfied by a semistructured data if any node reached by the regular query p is also reached by the regular query q. in this paper, two problems are mainly studied: the implication problem and the problem of the existence of a finite exact model. -we give a new decision algorithm for the implication problem of a constraint p@?q by a set of bounded path constraints p"i@?u"i where p, q, and the p"i's are regular path expressions and the u"i's are words, improving in this particular case, the more general algorithms of s. abiteboul and v. vianu, and n. alechina et al. in the case of a set of word equalities u"i=v"i, we provide a more efficient decision algorithm for the implication of a word equality u=v, improving the more general algorithm of p. buneman et al. we prove that, in this case, implication for nondeterministic models is equivalent to implication for (complete) deterministic ones. -we introduce the notion of exact model: an exact model of a set of path constraints c satisfies the constraint p@?q if and only if this constraint is implied by c. we prove that any set of constraints has an exact model and we give a decidable characterization of data which are exact models of bounded path inclusion constraints sets.
compressing table data with column dependency. tables are two-dimensional arrays given in row-major order. such data have unique features that could be exploited for effective compression. for example, tables often represent database files with rows as records so certain columns or fields in a table may have few distinct values. this means that simply transposing the data can make it compress better. further, a large source of information redundancy in a table is the correlation among columns representing related types of data. this paper formalizes the notion of column dependency as a way to capture this information redundancy across columns and discusses how to automatically compute and use it to substantially improve table compression.
on the dualization of hypergraphs with bounded edge-intersections and other related classes of hypergraphs. given a finite set v, and integers k&ge;1 and r&ge;0, let us denote by the class of hypergraphs with (k,r)-bounded intersections, i.e. in which the intersection of any k distinct hyperedges has size at most r. we consider the problem : given a hypergraph , and a subfamily of its maximal independent sets (mis) , either extend this subfamily by constructing a new mis or prove that there are no more mis, that is . it is known that, for hypergraphs of bounded dimension , as well as for hypergraphs of bounded degree (where &delta; is a constant), problem can be solved in incremental polynomial time. in this paper, we extend this result to any integers k,r such that k+r=&delta; is a constant. more precisely, we show that for hypergraphs with k+r&le;const, problem is nc-reducible to the problem of generating a single mis for a partial subhypergraph of . in particular, this implies that is polynomial, and we get an incremental polynomial algorithm for generating all mis. furthermore, combining this result with the currently known algorithms for finding a single maximally independent set of a hypergraph, we obtain efficient parallel algorithms for incrementally generating all mis for hypergraphs in the classes , , and , where &delta; is a constant. we also show that, for , where k+r&le;const, the problem of generating all mis of can be solved in incremental polynomial-time and with space polynomial only in the size of .
approximability of the capacitated b-edge dominating set problem. in this paper, we discuss the approximability of the capacitated b-edge dominating set problem, which generalizes the edge dominating set problem by introducing capacities and demands on the edges. we present an approximation algorithm for this problem and show that it achieves a factor of 8/3 for general graphs and a factor of 2 for bipartite graphs. moreover, we discuss the relationships of the edge dominating set problem and the vertex cover problem. the results show that improving the approximation factor beyond 8/3 using our approach of adding valid inequalities to a natural linear programming relaxation is as hard as improving the approximation factor for vertex cover beyond 2.
proof rules for the correctness of quantum programs. we apply the notion of quantum predicate proposed by d'hondt and panangaden to analyze a simple language fragment which may describe the quantum part of a future quantum computer in knill's architecture. the notion of weakest liberal precondition semantics, introduced by dijkstra for classical deterministic programs and by mciver and morgan for probabilistic programs, is generalized to our quantum programs. to help reasoning about the correctness of quantum programs, we extend the proof rules presented by morgan for classical probabilistic loops to quantum loops. these rules are shown to be complete in the sense that any correct assertion about the quantum loops can be proved using them. some illustrative examples are also given to demonstrate the practicality of our proof rules.
two absolute bounds for distributed bit complexity. the concept of distributed communication bit complexity was introduced by dinitz, rajsbaum, and moran. they studied the bit complexity of consensus and leader election, arriving at more or less exact bounds. this paper answers two questions on leader election, which remained there open. the first is to close the gap between the known upper and lower bounds, for electing a leader by two linked processors. the second is whether the suggested algorithm, sending 1.5n bits while electing a leader in a chain of even length n, is optimal, in the case when n is known to the processors. for both problems, absolutely exact bounds are found. moreover, the presented lower bound proofs show that there is no optimal algorithm other than the suggested ones.
traffic grooming on the path. in a wdm network, routing a request consists in assigning it a route in the physical network and a wavelength. if each request uses at most 1/c of the bandwidth of the wavelength, we will say that the grooming factor is c. that means that on a given edge of the network we can groom (group) at most c requests on the same wavelength. with this constraint the objective can be either to minimize the number of wavelengths (related to the transmission cost) or minimize the number of add drop multiplexers (shortly adm) used in the network (related to the cost of the nodes). we consider here the case where the network is a path on n nodes, pn. thus the routing is unique. for a given grooming factor c minimizing the number of wavelengths is an easy problem, well known and related to the load problem. but minimizing the number of adms is np-complete for a general set of requests and no results are known. here we show how to model the problem as a graph partition problem and using tools of design theory we completely solve the case where c=2 and where we have a static uniform all-to-all traffic (one request for each pair of vertices).
impossibility of gathering by a set of autonomous mobile robots. given a set of n autonomous mobile robots that can freely move on a two dimensional plane, they are required to gather in a position on the plane not fixed in advance (gathering problem). the main research question we address in this paper is: under which conditions can this task be accomplished by the robots? the studied robots are quite simple: they are anonymous, totally asynchronous, they do not have any memory of past computations, they cannot explicitly communicate between each other. we show that this simple task cannot be in general accomplished by the considered system of robots.
agreement in synchronous networks with ubiquitous faults. in this paper we are interested in synchronous distributed systems subject to transient and ubiquitous failures. this includes systems where failures will occur on any communication link, systems where every processor will experience at one time or another send or receive failure, etc., and, following a failure, normal functioning resuming after a finite time. notice that these cases cannot be handled by the traditional component failure models. the model we use is the communication failure model, also called the transmission failure or dynamic faults or mobile faults model. using this model, we study the fundamental problem of agreement in synchronous networks of arbitrary topology with ubiquitous faults. we establish bounds on the number of dynamic faults that make any non-trivial form of agreement (even strong majority) impossible; in turn, these bounds express connectivity requirements that must be met to achieve any meaningful form of agreement. we also provide, constructively, bounds on the number of dynamic faults in spite of which any non-trivial form of agreement (even unanimity) is possible. these bounds are shown to be tight for a large class of networks, which includes hypercubes, toruses, rings, and complete graphs; incidentally, we close the existing gap between possibility and impossibility of non-trivial agreement in complete graphs in the presence of dynamic byzantine faults. none of these results is derivable in the component failure models; in particular, all our possibility results hold in situations for which those models indicate impossibility.
hardness and approximation results for black hole search in arbitrary networks. a black hole is a highly harmful stationary process residing in a node of a network and destroying all mobile agents visiting the node without leaving any trace. the black hole search is the task of locating all black holes in a network by exploring it with mobile agents. we consider the problem of designing the fastest black hole search, given the map of the network and the starting node. we study the version of this problem that assumes that there is at most one black hole in the network and there are two agents, which move in synchronized steps. we prove that this problem is np-hard in arbitrary graphs (even in planar graphs), solving an open problem stated in [j. czyzowicz, d. kowalski, e. markou, a. pelc, searching for a black hole in tree networks, in: proc. 8th int. conf. on principles of distributed systems, opodis 2004, 2004, pp. 34-35. also: springer lncs, vol. 3544, pp. 67-80]. we also give a -approximation algorithm, showing the first non-trivial approximation ratio upper bound for this problem. our algorithm follows a natural approach of exploring networks via spanning trees. we prove that this approach cannot lead to an approximation ratio bound better than 3/2.
communications in unknown networks: preserving the secret of topology. in cryptography we investigate security aspects of data distributed in a network. this kind of security does not protect the secrecy of the network topology against being discovered if some kind of communication has taken place. but there are several scenarios where the network topology has to be a part of the secret. in this paper we study the question of communication within a secret network where the processing nodes of the network have only partial knowledge (e.g. given as routing tables) of the topology. we introduce a model for measuring the loss of security of the topology when far distance communication takes place. a communication protocol preserves the secret of topology if no processing node can deduce additional information about the topology from the communication. we will investigate lower bounds on the knowledge that can be revealed from the communication string and show, for instance, that some knowledge about distances can always be revealed. then, we consider routing tables. we show that several kinds of routing tables are not sufficient to guarantee the secrecy of topology. on the other hand, if a routing table allows us to specify the direction from which a message is coming, we can run a protocol solving the all-to-all communication problem such that no processing node can gain additional knowledge about the network. finally, we investigate the problem of whether routing tables can be generated from the local knowledge of the processing nodes without losing the secrecy of the network topology with respect to the resulting knowledge base. it will be shown that this is not possible for static networks and most kinds of dynamic networks.
a tight bound for online colouring of disk graphs. we present an improved upper bound on the competitiveness of the online colouring algorithm first-fit in disk graphs, which are graphs representing overlaps of disks on the plane. we also show that this bound is best possible for deterministic online colouring algorithms that do not use the disk representation of the input graph. we also present a related new lower bound for unit disk graphs.
minimization of the number of adms in sonet rings with maximum throughput with implications to the traffic grooming problem. sonet adms are dominant cost factors in wdm/sonet rings. whereas most previous papers on the topic concentrated on the number of wavelengths assigned to a given set of lightpaths, recent papers argue that the number of adms is a more realistic cost measure. the minimization of this cost factor has been investigated in recent years, where single-hop and multi-hop communication models, with arbitrary traffic and uniform traffic loads have been investigated. as a first attempt to understand the trade-off between the number of wavelengths and the number of adms, we concentrate on the all-to-all, uniform traffic instance with multi-hop, splittable communication. we look for a solution which makes full use of the bandwidth and uses the minimum possible number of adms. we develop an architecture based on successive nested polygons and present a necessary and sufficient condition for a solution in this architecture to be feasible. this architecture leads to a solution using o(wlogw+n) adms where w is the number of wavelengths used, and n is the number of nodes in the ring. this is a substantial improvement compared to nw adms for the basic architecture in [o. gerstel, p. lin, g. sasaki, combined wdm and sonet network design, in: infocom'99, eighteenth annual joint conference of the ieee computer and communications societies, vol. 2, 1999, pp. 734-743], and optimal for w=o(n/logn). we further improve this result to o(wlog$/overline{w}$+n) adms, where $/overline{w}$=o(w). this architecture constitutes a solution for the traffic grooming problem, which is the subject of many recent works.
optimal gossiping in square 2d meshes. gossiping is the communication problem in which each node has a unique message to be transmitted to every other node. the nodes exchange their message by packets. a solution to the problem is judged by how many rounds of packet sending it requires. in this paper, we consider the version of the problem in which small-size packets each carrying exactly one message are used. the nodes of the target meshes are assumed to be all-port (a node's incident edges can all be active at the same time); and their edges are either half-duplex or full-duplex, which are also known as the h* model and the f* model, respectively. we study the class of 2d square meshes. soch and tvrdik (sirocco'97, pp. 253-265; tech. rep. dc-97-04, dept. of cs&e, czech technical university) have obtained optimal algorithms for the f* model (for square or nonsquare meshes). lau and zhang (ieee trans. parallel distribut. syst. 13 (4) (2002) 349-358) have obtained fast algorithms for the h* model. we present optimal algorithms for both models, with the interesting property that they route their messages along the same paths and in the same order, i.e. for any edge {u,v}, the i-th message from u to v under either model is the same message.
on the bounded-hop mst problem on random euclidean instances. the d-dimh-hops mst problem is defined as follows: given a set s of points in the d-dimensional euclidean space and s&epsilon;s, find a minimum-cost spanning tree for s rooted at s with height at most h. we investigate the problem for any constant h and d >0. we prove the first nontrivial lower bound on the solution cost for almost all euclidean instances (i.e. the lower bound holds with high probability). then we introduce an easy-to-implement, fast divide et impera heuristic and we prove that its solution cost matches the lower bound.
languages with mismatches. in this paper we study some combinatorial properties of a class of languages that represent sets of words occurring in a text s up to some errors. more precisely, we consider sets of words that occur in a text s with k mismatches in any window of size r. the study of this class of languages mainly focuses both on a parameter, called repetition index, and on the set of the minimal forbidden words of the language of factors of s with errors. the repetition index of a string s is defined as the smallest integer such that all strings of this length occur at most in a unique position of the text s up to errors. we prove that there is a strong relation between the repetition index of s and the maximal length of the minimal forbidden words of the language of factors of s with errors. moreover, the repetition index plays an important role in the construction of an indexing data structure. more precisely, given a text s over a fixed alphabet, we build a data structure for approximate string matching having average size o(|s|log k+1|s|) and answering queries in time o(|x|+|occ(x)|) for any word x, where occ is the list of all occurrences of x in s up to errors.
on the complexity of dominating set problems related to the minimum all-ones problem. the minimum all-ones problem and the connected odd dominating set problem were shown to be np-complete in different papers for general graphs, while they are solvable in linear time (or trivial) for trees, unicyclic graphs, and series-parallel graphs. the complexity of both problems when restricted to bipartite graphs was raised as an open question. here we solve both problems. for this purpose, we introduce the related decision problem of the existence of an odd dominating set without isolated vertices, and study its complexity. our main result shows that this new problem is np-complete, even when restricted to bipartite graphs. we use this result to deduce that the minimum all-ones problem and the connected odd dominating set problem are also np-complete for bipartite graphs. we show that all three problems are solvable in linear time for graphs with bounded treewidth. we also show that the new problem remains np-complete when restricted to other graph classes, e.g., planar graphs, graphs with girth at least five, and graphs with a small maximum degree, in particular 3-regular graphs.
an exact algorithm for the minimum dominating clique problem. a subset of vertices d⊆v of a graph g=(v,e) is a dominating clique if d is a dominating set and a clique of g. the existence problem 'given a graph g, is there a dominating clique in g?' is np-complete, and thus both the minimum and the maximum dominating clique problems are np-hard. we present an o(1.3387n) time and polynomial space algorithm that for an input graph on n vertices either computes a minimum dominating clique or reports that the graph has no dominating clique. the algorithm uses the branch reduce paradigm and its time analysis is based on the measure conquer approach. we also establish a lower bound of ω(1.2599n) for the worst case running time of the algorithm. finally using memorization we obtain an o(1.3234n) time and exponential space algorithm for the same problem.
multiple genome rearrangement by swaps and by element duplications. we consider the swap distance and the element duplication distance. we show that the swap centre permutation problem is np-complete. we show that the element duplication centre problem is np-complete.
a sufficient condition for a planar graph to be class 1. we prove that every planar graph g with @d=6 is of class 1 if it does not contain a 5-cycle with a chord.
on the minimum monochromatic or multicolored subgraph partition problems. let g=(v,e) be an edge-colored graph. a subgraph h is said to be monochromatic if all the edges of h have the same color, and multicolored if no two edges of h have the same color. we investigate the complexity of the problems for finding the minimum number of monochromatic or multicolored subgraphs, such as cliques, cycles, trees and paths, partitioning v(g), depending on the number of colors used and the maximal number of times a color appears in a coloring. we also present a greedy scheme that yields a (lnm+1)-approximation for the problem of finding the minimum number of monochromatic cliques partitioning v(g) for a k"4^--free graph g, where m is the size of the largest monochromatic clique in g. by a slightly modification of the approximation algorithm, it can be used for the multicolored case. we show that unless np@?dtime(n^o^(^l^o^g^l^o^g^n^)), for any @e>=0 there is no approximation algorithm for finding the minimum number of multicolored trees partitioning v(g) with performance 50/521(1-@e)ln|v|.
an analytical approach to the inference of summary data of additive type. summary data take the form of a triple that consists of a summary attribute, a category and a numeric value. the inference problem of summary data consists in deciding whether or not a summary data of interest is evaluable (i.e., can be computed) from a given set of summary data. we address the special case of the inference problem with homogeneous summary data (i.e., summary data with the same summary attribute), where the summary attribute is of additive nature. owing to additivity, one can model the information content of the given summary data by a linear equation system whose variables are constrained to take their values from the domain of the summary attribute. we state two evaluability criteria, one for a real or integral summary attribute, and the other for a nonnegative-real or nonnegative-integral summary attribute. using the two evaluability criteria, we show that our inference problem can be solved in strongly polynomial time for a real or integral or nonnegative real summary attribute, and is co>i>np-complete for a nonnegative-integral summary attribute. moreover, we prove that, given a summary data of interest that is not evaluable, even in the (simplest) case that the summary attribute is of a real type, finding an evaluable summary data whose category is maximally contained in (or minimally contains) the category of the summary data of interest is an np-hard problem.
classification of rotations on the torus t. we consider rotations on the torus , and we classify them with respect to the complexity functions. in dimension one, a minimal rotation can be coded by a sturmian word. a sturmian word has complexity n+1 by the morse-hedlund theorem. here we make a generalization in dimension two.
approximation algorithms for maximum cut with limited unbalance. we consider the problem of partitioning the vertices of a weighted graph into two sets of sizes that differ at most by a given threshold b, so as to maximize the weight of the crossing edges. for b equal to 0 this problem is known as max bisection, whereas for b equal to the number n of nodes it is the maximum cut problem. we present polynomial time randomized approximation algorithms with non trivial performance guarantees for its solution. the approximation results are obtained by extending the methodology used by y. ye for max bisection and by combining this technique with another one that uses the algorithm of goemans and williamson for the maximum cut problem. when b is equal to zero the approximation ratio achieved coincides with the one obtained by y. ye; otherwise it is always above this value and tends to the value obtained by goemans and williamson as b approaches the number n of nodes.
extracting constrained 2-interval subsets in 2-interval sets. 2-interval sets were used in [s. vialette, pattern matching over 2-intervals sets, in: proc. 13th annual symposium combinatorial pattern matching, cpm 2002, in: lecture notes in computer science, vol. 2373, springer-verlag, 2002, pp. 53-63; s. vialette, on the computational complexity of 2-interval pattern matching, theoret. comput. sci. 312 (2-3) (2004) 223-249] for establishing a general representation for macroscopic describers of rna secondary structures. in this context, we have a 2-interval for each legal local fold in a given rna sequence, and a constrained pattern made of disjoint 2-intervals represents a putative rna secondary structure. we focus here on the problem of extracting a constrained pattern in a set of 2-intervals. more precisely, given a set of 2-intervals and a model r describing if two disjoint 2-intervals in a solution can be in precedence order (<), be allowed to nest () and/or be allowed to cross (), we consider the problem of finding a maximum cardinality subset of disjoint 2-intervals such that any two 2-intervals in agree with r. the different combinations of restrictions on model r alter the computational complexity of the problem, and need to be examined separately. in this paper, we improve the time complexity of [s. vialette, on the computational complexity of 2-interval pattern matching, theoret. comput. sci. 312 (2-3) (2004) 223-249] for model r={} by giving an optimal o(nlogn) time algorithm, where n is the cardinality of the 2-interval set . we also give a graph-like relaxation for model r={,} that is solvable in time. finally, we prove that the considered problem is np-complete for model r={<,} even for same-length intervals, and give a fixed-parameter tractability result based on the crossing structure of .
optimal parameters for search using a barrier tree markov model. the performance, on a given problem, of search heuristics such as simulated annealing and descent with variable mutation can be described as a function of, and optimised over, the parameters of the heuristic (e.g. the annealing or mutation schedule). we describe heuristics as markov processes; the search for optimal parameters is then rendered feasible by the use of level-accessible barrier trees for state amalgamation. results are presented for schedules minimising ''where-you-are'' and ''best-so-far'' cost, over binary perceptron, spin-glass and max-sat problems. we also compute first-passage time for several ''toy heuristics'', including constant-temperature annealing and fixed-rate mutation search.
the magnus-derek game. we introduce a new combinatorial game between two players: magnus and derek. initially, a token is placed at position 0 on a round table with n positions. in each round of the game magnus chooses the number of positions for the token to move, and derek decides in which direction, + (clockwise) or - (counterclockwise), the token will be moved. magnus aims to maximize the total number of positions visited during the course of the game, while derek aims to minimize this quantity. we define f^*(n) to be the eventual size of the set of visited positions when both players play optimally. we prove a closed form expression for f^*(n) in terms of the prime factorization of n, and provide algorithmic strategies for magnus and derek to meet this bound. we note the relevance of the game for a mobile agent exploring a ring network with faulty sense of direction, and we pose variants of the game for future study.
complexity theory for splicing systems. this paper proposes a notion of time complexity in splicing systems. the time complexity of a splicing system at length n is defined to be the smallest integer t such that all the words of the system having length n are produced within t rounds. for a function t from the set of natural numbers to itself, the class of languages with splicing system time complexity t(n) is denoted by spltime[f(n)]. this paper presents fundamental properties of spltime and explores its relation to classes based on standard computational models, both in terms of upper bounds and in terms of lower bounds. as to upper bounds, it is shown that for any function t(n)spltime[t(n)] is included in 1-nspace[t(n)]; i.e., the class of languages accepted by a t(n)-space-bounded non-deterministic turing machine with one-way input head. expanding on this result, it is shown that 1-nspace[t(n)] is characterized in terms of splicing systems: it is the class of languages accepted by a t(n)-space uniform family of extended splicing systems having production time o(t(n)) with the additional property that each finite automaton appearing in the family of splicing systems has at most a constant number of states. as to lower bounds, it is shown that for all functions t(n)>=logn, all languages accepted by a pushdown automaton with maximal stack height t(|x|) for a word x are in spltime[t(n)]. from this result, it follows that the regular languages are in spltime[o(logn)] and that the context-free languages are in spltime[o(n)].
single machine scheduling with release dates and job delivery to minimize the makespan. in single machine scheduling with release dates and job delivery, jobs are processed on a single machine and then delivered by a capacitated vehicle to a single customer. only one vehicle is employed to deliver these jobs. the vehicle can deliver at most c jobs at a shipment. the delivery completion time of a job is defined as the time at which the delivery batch containing the job is delivered to the customer and the vehicle returns to the machine. the objective is to minimize the makespan, i.e., the maximum delivery completion time of the jobs. when preemption is allowed to all jobs, we give a polynomial-time algorithm for this problem. when preemption is not allowed, we show that this problem is strongly np-hard for each fixed c>=1. we also provide a 53-approximation algorithm for this problem, and the bound is tight.
bisimulation relations for weighted automata. bisimulation is a well known equivalence relation for discrete event systems and has been extended to probabilistic and stochastic systems. this paper introduces a general definition of bisimulation which can be applied to finite automata where weights and labels are assigned to transitions. it is shown that this general view contains several known bisimulations as special cases and defines naturally equivalences for different classes of models. apart from the well known forward bisimulation, also backward bisimulation is introduced and it is shown that both types of bisimulation preserve different types of results. furthermore it is shown that forward and backward bisimulation are congruences according to commonly known composition operations for automata.
the 2nd-order conditional 3-coloring of claw-free graphs. a 2nd-order conditionalk-coloring of a graph g is a proper k-coloring of the vertices of g such that every vertex of degree at least 2 in g will be adjacent to vertices with at least 2 different colors. the smallest number k for which a graph g can have a 2nd-order conditional k-coloring is the 2nd-order conditional chromatic number, denoted by @g"d(g). in this paper, we investigate the 2nd-order conditional 3-colorings of claw-free graphs. first, we prove that it is np-complete to determine if a claw-free graph with maximum degree 3 is 2nd-order conditionally 3-colorable. second, by forbidding a kind of subgraphs, we find a reasonable subclass of claw-free graphs with maximum degree 3, for which the 2nd-order conditionally 3-colorable problem can be solved in linear time. third, we give a linear time algorithm to recognize this subclass of graphs, and a linear time algorithm to determine whether it is 2nd-order conditionally 3-colorable. we also give a linear time algorithm to color the graphs in the subclass by 3 colors.
predecessor existence problems for finite discrete dynamical systems. we study the predecessor existence problem for finite discrete dynamical systems. given a finite discrete dynamical system s and a configuration c, the predecessor existence (or pre) problem is to determine whether there is a configuration c^' such that s has a transition from c^' to c. in addition to the decision version, we also study the following variants: the #-predecessor existence (or #pre) problem-counting the number of predecessors, the unique-predecessor existence (or upre) problem-deciding whether there is a unique predecessor and the ambiguous-predecessor existence (or apre) problem-given a configuration c and a predecessor c^' of c, deciding whether there is a different predecessor c^'' of c. general techniques are presented for simultaneously characterizing the computational complexity of the pre problem and its three variants. our hardness results are based on the concept of simultaneous reductions: single transformations that can be used to simultaneously prove the hardness of the different variants of the pre problem for their respective complexity classes. our easiness results are based on dynamic programming and they extend the previous results on pre problem for one-dimensional cellular automata. the hardness results together with the easiness results provide a tight separation between easy and hard instances. further, the results imply similar bounds for other classes of finite discrete dynamical systems including discrete hopfield and recurrent neural networks, concurrent state machines, systolic networks and one- and two-dimensional cellular automata. our results extend the earlier results of green, sutner and orponen on the complexity of the predecessor existence problem and its variants.
the complexity of fixed point models of trust in distributed networks. in this paper we consider the complexity of some problems arising in a fixed point model of trust in large-scale distributed systems, based on the notion of trust structures introduced by carbone, nielsen and sassone; a set of trust levels with two distinct partial orderings. in the trust model, a global trust state exists as the least fixed point of a collection of local policy functions of nodes in the network. we first show that it is possible to efficiently compute a single component of the global trust state using a simple, robust and totally asynchronous distributed algorithm. we complement this with a lower bound which shows that, if the policies are unrestricted then communication and time linear in the number of distinct trust levels is required in the worst case. we then consider the notion of distributed proof carrying requests previously introduced as a means of safely approximating the global trust state without computing its exact value. we present a new result that enables us to give a continuum of proof carrying protocols, the previously known protocol being one extreme of this. the theorem allows us to generate protocols that can prove all possible trust values (previously, it was only possible to prove trust values representing 'not too much bad behaviour'). however, we show that such a general protocol may not be efficient - it is np-hard to construct an approximately minimal size proof in our model, and in the worst case the nodes must communicate almost as much data as if they were to compute the global trust state from scratch. the implications of our negative results are that it may be necessary to restrict the policy language in order to efficiently implement a fixed point model of trust in a distributed network.
formalising java rmi with explicit code mobility. this paper presents an object-oriented, java-like core language with primitives for distributed programming and explicit code mobility. we apply our formulation to prove the correctness of several optimisations for distributed programs. our language captures crucial but often hidden aspects of distributed object-oriented programming, including object serialisation, dynamic class downloading and remote method invocation. it is defined in terms of an operational semantics that concisely models the behaviour of distributed programs using machinery from calculi of mobile processes. type safety is established using invariant properties for distributed runtime configurations. we argue that primitives for explicit code mobility offer a programmer fine-grained control of type-safe code distribution, which is crucial for improving the performance and safety of distributed object-oriented applications.
a formal semantics for protocol narrations. protocol narrations are a widely-used informal means to describe, in an idealistic manner, the functioning of cryptographic protocols as a single intended sequence of cryptographic message exchanges among the protocol's participants. protocol narrations have also been informally ''turned into'' a number of formal protocol descriptions, e.g., using the spi-calculus. in this paper, we propose a direct formal operational semantics for protocol narrations that fixes a particular and, as we argue, well-motivated interpretation on how the involved protocol participants are supposed to execute. based on this semantics, we explain and formally justify a natural and precise translation of narrations into spi-calculus. an optimised translation has been implemented in ocaml, and we report on case studies that we have carried out using the tool.
a semantic framework for open processes. we propose a general methodology for analysing the behaviour of open systems modelled as coordinators, i.e., open terms of suitable process calculi. a coordinator is understood as a process with holes or placeholders where other coordinators and components (i.e., closed terms) can be plugged in, thus influencing its behaviour. the operational semantics of coordinators is given by means of a symbolic transition system, where states are coordinators and transitions are labeled by spatial/modal formulae expressing the potential interaction that plugged components may enable. behavioural equivalences for coordinators, like strong and weak bisimilarities, can be straightforwardly defined over such a transition system. different from other approaches based on universal closures, i.e., where two coordinators are considered equivalent when all their closed instances are equivalent, our semantics preserves the openness of the system during its evolution, thus allowing dynamic instantiation to be accounted for in the semantics. to further support the adequacy of the construction, we show that our symbolic equivalences provide correct approximations of their universally closed counterparts, coinciding with them over closed components. for process calculi in suitable formats, we show how tractable symbolic semantics can be defined constructively using unification.
a framework for analyzing probabilistic protocols and its application to the partial secrets exchange. we propose a probabilistic variant of the pi-calculus as a framework to specify randomized security protocols and their intended properties. in order to express and verify the correctness of the protocols, we develop a probabilistic version of the testing semantics. we then illustrate these concepts on an extended example: the partial secret exchange, a protocol which uses a randomized primitive, the oblivious transfer, to achieve fairness of information exchange between two parties.
a program logic for resources. we introduce a reasoning infrastructure for proving statements about resource consumption in a fragment of the java virtual machine language (jvml). the infrastructure is based on a small hierarchy of program logics, with increasing levels of abstraction: at the top there is a type system for a high-level language that encodes resource consumption. the infrastructure is designed to be used in a proof-carrying code (pcc) scenario, where mobile programs can be equipped with formal evidence that they have predictable resource behaviour. this article focuses on the core logic in our infrastructure, a vdm-style program logic for partial correctness, which can make statements about resource consumption alongside functional behaviour. we establish some important results for this logic, including soundness and completeness with respect to a resource-aware operational semantics for the jvml. we also present a second logic built on top of the core logic, which is used to express termination; it too is shown to be sound and complete. we then outline how high-level language type systems may be connected to these logics. the entire infrastructure has been formalized in isabelle/hol, both to enhance the confidence in our meta-theoretical results, and to provide a prototype implementation for pcc. we give examples to show the usefulness of this approach, including proofs of resource bounds on code resulting from compiling high-level functional programs.
concurrent reachability games. we consider concurrent two-player games with reachability objectives. in such games, at each round, player 1 and player 2 independently and simultaneously choose moves, and the two choices determine the next state of the game. the objective of player 1 is to reach a set of target states; the objective of player 2 is to prevent this. these are zero-sum games, and the reachability objective is one of the most basic objectives: determining the set of states from which player 1 can win the game is a fundamental problem in control theory and system verification. there are three types of winning states, according to the degree of certainty with which player 1 can reach the target. from type-1 states, player 1 has a deterministic strategy to always reach the target. from type-2 states, player 1 has a randomized strategy to reach the target with probability 1. from type-3 states, player 1 has for every real @e>0 a randomized strategy to reach the target with probability greater than 1-@e. we show that for finite state spaces, all three sets of winning states can be computed in polynomial time: type-1 states in linear time, and type-2 and type-3 states in quadratic time. the algorithms to compute the three sets of winning states also enable the construction of the winning and spoiling strategies.
open bisimulation, revisited. in the context of the @p-calculus, open bisimulation is prominent and popular due to its congruence properties and its easy implementability. motivated by the attempt to generalise it to the spi-calculus, we offer a new, more refined definition and show how far it coincides with the original one.
separation of synchronous and asynchronous communication via testing. one of the early results concerning the asynchronous @p-calculus which significantly contributed to its popularity is the capability of encoding the output prefix of the (choiceless) @p-calculus in a natural and elegant way. encodings of this kind were proposed by honda and tokoro, by nestmann and (independently) by boudol. we investigate whether the above encodings preserve de nicola and hennessy's testing semantics. in this sense, it turns out that, under some general conditions, no encoding of the output prefix is able to preserve the must testing. this negative result is due to (a) the non-atomicity of the sequences of steps which are necessary in the asynchronous @p-calculus to mimic synchronous communication, and (b) testing semantics' sensitivity to divergence.
causality versus true-concurrency. category theory has been successfully employed to structure the confusing set-up of models and equivalences for concurrency: winskel and nielsen have related the standard models via adjunctions and (co)reflections while joyal et al. have defined an abstract notion of equivalence, known as open map bisimilarity. one model has not been integrated into this framework: the causal trees of darondeau and degano. here we fill this gap. in particular, we show that there is an adjunction from causal trees to event structures, which we bring to light via a mediating model, that of event trees. further, we achieve an open map characterization of history preserving bisimilarity: the latter is captured by the natural instantiation of the abstract bisimilarity for causal trees.
the size of higman-haines sets. we show that for the family of church-rosser languages the higman-haines sets, which are the sets of all scattered subwords of a given language and the sets of all words that contain some word of a given language as a scattered subword, cannot be effectively constructed, although both these sets are regular for any language. this nicely contrasts the result on the effectiveness of the higman-haines sets for the family of context-free languages. the non-effectiveness is based on a non-recursive trade-off result between the language description mechanism of church-rosser languages and the corresponding higman-haines sets, which in turn is also valid for all supersets of the language family under consideration, and in particular for the family of recursively enumerable languages. finally for the family of regular languages we prove an upper and a matching lower bound on the size of the higman-haines sets in terms of nondeterministic finite automata.
transition complexity of language operations. the number of transitions required by a nondeterministic finite automaton (nfa) to accept a regular language is a natural measure of the size of that language. there has been a significant amount of work related to the trade-off between the number of transitions and other descriptional complexity measures for regular languages. in this paper, we consider the effect of language operations on the number of transitions required to accept a regular language. this work extends previous work on descriptional complexity of regular language operations, in particular, under the measures of deterministic state complexity, nondeterministic state complexity and regular expression size.
learning multiple languages in groups. we consider a variant of gold's learning paradigm where a learner receives as input n different languages (in the form of one text where all input languages are interleaved). our goal is to explore the situation when a more ''coarse'' classification of input languages is possible, whereas more refined classification is not. more specifically, we answer the following question: under which conditions, a learner, being fed n different languages, can produce m grammars covering all input languages, but cannot produce k grammars covering input languages for any k>m. we also consider a variant of this task, where each of the output grammars may not cover more than r input languages. our main results indicate that the major factor affecting classification capabilities is the difference n-m between the number n of input languages and the number m of output grammars. we also explore the relationship between classification capabilities for smaller and larger groups of input languages. for the variant of our model with the upper bound on the number of languages allowed to be represented by one output grammar, for classes consisting of disjoint languages, we found complete picture of relationship between classification capabilities for different parameters n (the number of input languages), m (number of output grammars), and r (bound on the number of languages represented by each output grammar). this picture includes a combinatorial characterization of classification capabilities for the parameters n,m,r of certain types.
optimal lower bounds for rank and select indexes. we develop a new lower bound technique for data structures. we show an optimal @w(nlglgn/lgn) space lower bounds for storing an index that allows to implement rank and select queries on a bit vector b provided that b is stored explicitly. these results improve upon [peter bro miltersen, lower bounds on the size of selection and rank indexes, in: proceedings of the 16th annual acm-siam symposium on discrete algorithms, 2005, pp. 11-12]. we show @w((m/t)lgt) lower bounds for storing rank/select index in the case where b has m 1-bits in it and the algorithm is allowed to probe t bits of b. we also present an improved data structure that implements both rank and select queries with an index of size (1+o(1))(nlglgn/lgn)+o(n/lgn), that is, compared to existing results we give an explicit constant for storage in the ram model with word size lgn. an advantage of this data structure is that both rank and select indexes share the most space consuming part of order @q(nlglgn/lgn) making it more practical for implementation.
regulated rna rewriting: modelling rna editing with guided insertion. rna editing is an important alternative genetic processing event that is known to take place in all higher eukaryotes. we study a model of string rewriting based on the sophisticated rna editing mechanism found in trypanosome kinetoplasts. we demonstrate basic properties of three principal variants of this model which we show to form a strict hierarchy in terms of expressive power. we also present a method and software for simulating real biological rna editing via this model and apply the theoretical results to suggest real biological constraints on this process.
non-asymptotic calibration and resolution. we analyze a new algorithm for probability forecasting of binary observations on the basis of the available data, without making any assumptions about the way the observations are generated. the algorithm is shown to be well-calibrated and to have good resolution for long enough sequences of observations and for a suitable choice of its parameter, a kernel on the cartesian product of the forecast space [0, 1] and the data space. our main results are non-asymptotic: we establish explicit inequalities, shown to be tight, for the performance of the algorithm.
an infinite hierarchy induced by depth synchronization. depth-synchronization measures the number of parallel derivation steps in a synchronized context-free (scf) grammar. when not bounded by a constant the depth-synchronization measure of an scf grammar is at least logarithmic and at most linear with respect to the word length. languages with linear depth-synchronization measure and languages with a depth-synchronization measure in between logarithmic and linear are proven to exist. this gives rise to a strict infinite hierarchy within the family of scf (and et0l) languages.
stochastic complexity for mixture of exponential families in generalized variational bayes. the variational bayesian learning, proposed as an approximation of the bayesian learning, has provided computational tractability and good generalization performance in many applications. however, little has been done to investigate its theoretical properties. in this paper, we discuss the variational bayesian learning of the mixture of exponential families and derive the asymptotic form of the stochastic complexities in a generalized setting of the prior distribution. we show that the stochastic complexities become smaller than those of regular statistical models, which implies that the advantage of the bayesian learning still remains in the variational bayesian learning. stochastic complexity, which is called the marginal likelihood or the free energy, not only becomes important in addressing the model selection problem but also enables us to discuss the accuracy of the variational bayesian approach as an approximation of the true bayesian learning. the main result also shows the effects of the prior distribution under the generalized setting.
fast bwt in small space by blockwise suffix sorting. we present a new space- and time-efficient algorithm for computing the burrow-wheeler transform (bwt). for any choice of a parameter v@?[3,n^2^/^3], the computation of bwt for a text of length n takes o(nlogn+vn) worst-case time and o(nlogn+vn) average-case time using o(nlogn/v) bits of space in addition to the text and the bwt. for example, if v=log^2n, the time is o(nlog^2n) in the worst case and o(nlogn) on an average with the additional space requirement of o(n) bits. the algorithm is alphabet-independent: it uses only character comparisons, and the complexities do not depend on the alphabet size unless v does. a practical implementation is 2-3 times slower than one of the fastest and most space-efficient previous algorithms while needing only one-third of the main memory. the algorithm is based on suffix arrays, but unlike any other algorithm, it can construct the suffix array a small block at a time without storing the rest of the suffix array anywhere.
quantum automata for some multiperiodic languages. we exhibit small size measure-once one-way quantum finite automata (mo-1qfa's) inducing multiperiodic stochastic events. moreover, for certain classes of multiperiodic languages, we exhibit: (i) isolated cut point mo-1qfa's whose size logarithmically depends on the periods; (ii) monte carlo mo-1qfa's whose size logarithmically depends on the periods and polynomially on the inverse of the error probability.
adaptive searching in succinctly encoded binary relations and tree-structured documents. the methods most heavily used by search engines to answer conjunctive queries on binary relations (such as one associating keywords with web-pages) are based on computing the intersection of postings lists stored as sorted arrays and using variants of binary search. we show that a succinct representation of the binary relation permits much better results, while using less space than traditional methods. we apply our results not only to conjunctive queries on binary relations, but also to queries on semi-structured documents such as xml documents or file-system indexes, using a variant of an adaptive algorithm used to solve conjunctive queries on binary relations.
rank and select revisited and extended. the deep connection between the burrows-wheeler transform (bwt) and the so-called rank and select data structures for symbol sequences is the basis of most successful approaches to compressed text indexing. rank of a symbol at a given position equals the number of times the symbol appears in the corresponding prefix of the sequence. select is the inverse, retrieving the positions of the symbol occurrences. it has been shown that improvements to rank/select algorithms, in combination with the bwt, turn into improved compressed text indexes. this paper is devoted to alternative implementations and extensions of rank and select data structures. first, we show that one can use gap encoding techniques to obtain constant time rank and select queries in essentially the same space as what is achieved by the best current direct solution (and sometimes less). second, we extend symbol rank and select to substring rank and select, giving several space/time trade-offs for the problem. an application of these queries is in position-restricted substring searching, where one can specify the range in the text where the search is restricted to, and only occurrences residing in that range are to be reported. in addition, arbitrary occurrences are reported in text position order. several byproducts of our results display connections with searchable partial sums, chazelle's two-dimensional data structures, and grossi et al.'s wavelet trees.
on the existence of regular approximations. we approximate context-free, or more general, languages using finite automata. the degree of approximation is measured, roughly speaking, by counting the number of incorrect answers an automaton gives on inputs of length m and observing how these values behave for large m. more restrictive variants are obtained by requiring that the automaton never accepts words outside the language or that it accepts all words in the language. a further distinction is whether a given (context-free) language has a regular approximation which is optimal under the measure of approximation degree or an approximation which is arbitrarily close to optimal. we study closure and decision properties of the approximation measure.
burrows-wheeler compression: principles and reflections. after a general description of the burrows-wheeler transform and a brief survey of recent work on processing its output, the paper examines the coding of the zero-runs from the mtf recoding stage, an aspect with little prior treatment. it is concluded that the original scheme proposed by wheeler is extremely efficient and unlikely to be much improved. the paper then proposes some new interpretations and uses of the burrows-wheeler transform, with new insights and approaches to lossless compression, perhaps including techniques from error correction.
a general comparison of language learning from examples and from queries. in language learning, strong relationships between gold-style models and query models have recently been observed: in some quite general setting gold-style learners can be replaced by query learners and vice versa, without loss of learning capabilities. these 'equalities' hold in the context of learning indexable classes of recursive languages. former studies on gold-style learning of such indexable classes have shown that, in many settings, the enumerability of the target class and the recursiveness of its languages are crucial for learnability. moreover, studying query learning, non-indexable classes have been mainly neglected up to now. so it is conceivable that the recently observed relations between gold-style and query learning are not due to common structures in the learning processes in both models, but rather to the enumerability of the target classes or the recursiveness of their languages. in this paper, the analysis is lifted onto the context of learning arbitrary classes of recursively enumerable languages. still, strong relationships between the approaches of gold-style and query learning are proven, but there are significant changes to the former results. though in many cases learners of one type can still be replaced by learners of the other type, in general this does not remain valid vice versa. all results hold even for learning classes of recursive languages, which indicates that the recursiveness of the languages is not crucial for the former 'equality' results. thus we analyze how constraints on the algorithmic structure of the target class affect the relations between two approaches to language learning.
learning attribute-efficiently with corrupt oracles. we study learning in a modified exact model, where the oracles are corrupt and only few of the presented attributes are relevant. both modifications were already studied in the literature [dana angluin, martins krikis, learning with malicious membership queries and exceptions (extended abstract), in: colt '94: proceedings of the seventh annual conference on computational learning theory, acm press, 1994, pp. 56-57 [3]; dana angluin, martins krikis, robert h. sloan, gyorgy turan, malicious omissions and errors in answers to membership queries, machine learning 28 (1997) 211-255; laurence bisht, nader h. bshouty, lawrance khoury, learning with errors in answers to membership queries (extracted abstract), in: focs '04: proceedings of the 45th annual ieee symposium on foundations of computer science, focs'04, ieee computer society, 2004, pp. 611-620; nader h. bshouty, lisa hellerstein, attribute-efficient learning in query and mistake-bound models, j. comput. system sci. 56 (3) (1998) 310-319 [12]; nick littlestone, learning quickly when irrelevant attributes abound: a new linear-threshold algorithm, machine learning 2 (4) (1988) 285-318; robert h. sloan, gyorgy turan, learning with queries but incomplete information (extended abstract), in: colt '94: proceedings of the seventh annual conference on computational learning theory, acm press, 1994, pp. 237-245 [5]], and efficient solutions were found to most of their variants. nonetheless, their reasonable combination is yet to be studied, and integrating the existing solutions either fails or works with a complexity that can be significantly improved. in this paper we prove the equivalence of exact learning attribute-efficiently with and without corrupt oracles. for each of the possible scenarios we describe a generic scheme that enables learning in these cases using modifications of the standard learning algorithms. we also generalize and improve previous non-attribute-efficient algorithms for learning with corrupt oracles.
faster suffix sorting. we propose a fast and memory-efficient algorithm for lexicographically sorting the suffixes of a string, a problem that has important applications in data compression as well as string matching. our algorithm eliminates much of the overhead of previous specialized approaches while maintaining their robustness for degenerate inputs. for input size n, our algorithm operates in only two integer arrays of size n, and has worst-case time complexity o(nlogn). we demonstrate experimentally that our algorithm has stable performance compared with other approaches.
enumeration and generation with a string automata representation. the representation of combinatorial objects is decisive for the feasibility of several enumerative tasks. in this work, we present a unique string representation for complete initially-connected deterministic automata (icdfas) with n states over an alphabet of k symbols. for these strings we give a regular expression and show how they are adequate for exact and random generation, allow an alternative way for enumeration and lead to an upper bound for the number of icdfas. the exact generation algorithm can be used to partition the set of icdfas in order to parallelize the counting of minimal automata, and thus of regular languages. a uniform random generator for icdfas is presented that uses a table of pre-calculated values. based on the same table, an optimal coding for icdfas is obtained.
an extension of the burrows-wheeler transform. we describe and highlight a generalization of the burrows-wheeler transform (bwt) to a multiset of words. the extended transformation, denoted by ebwt, is reversible. moreover, it allows to define a bijection between the words over a finite alphabet a and the finite multisets of conjugacy classes of primitive words in a^*. besides its mathematical interest, the extended transform can be useful for applications in the context of string processing. in the last part of this paper we illustrate one such application, providing a similarity measure between sequences based on ebwt.
pac-learnability of probabilistic deterministic finite state automata in terms of variation distance. we consider the problem of pac-learning distributions over strings, represented by probabilistic deterministic finite automata (pdfas). pdfas are a probabilistic model for the generation of strings of symbols, that have been used in the context of speech and handwriting recognition, and bioinformatics. recent work on learning pdfas from random examples has used the kl-divergence as the error measure; here we use the variation distance. we build on recent work by clark and thollard, and show that the use of the variation distance allows simplifications to be made to the algorithms, and also a strengthening of the results; in particular that using the variation distance, we obtain polynomial sample size bounds that are independent of the expected length of strings.
a complete characterization of deterministic regular liveness properties. many systems can be modeled formally by nondeterministic buchi-automata. the complexity of model checking then essentially depends on deciding subset conditions on languages that are recognizable by these automata and that represent the system behavior and the desired properties of the system. the involved complementation process may lead to an exponential blow-up in the size of the automata. we investigate a rich subclass of properties, called deterministic regular liveness properties, for which complementation at most doubles the automaton size if the properties are represented by deterministic buchi-automata. in this paper, we will present a decomposition theorem for this language class that entails a complete characterization of the deterministic regular liveness properties, and extend an existing incomplete result which then, too, characterizes the deterministic regular liveness properties completely.
from first principles to the burrows and wheeler transform and beyond, via combinatorial optimization. we introduce a combinatorial optimization framework that naturally induces a class of optimal word permutations with respect to a suitably defined cost function taking into account various measures of relatedness between words. the burrows and wheeler transform (bwt) (cf. [m. burrows, d. wheeler, a block sorting lossless data compression algorithm, technical report 124, digital equipment corporation, 1994]), and its analog for labelled trees (cf. [p. ferragina, f. luccio, g. manzini, s. muthukrishnan, structuring labeled trees for optimal succinctness, and beyond, in: proc. of the 45th annual ieee symposium on foundations of computer science, 2005, pp. 198-207]), are special cases in the class. we also show that the class of optimal word permutations defined here is identical to the one identified by ferragina et al. for compression boosting [p. ferragina, r. giancarlo, g. manzini, m. sciortino, boosting textual compression in optimal linear time, journal of the acm 52 (2005) 688-713]. therefore, they are all highly compressible. we also provide, by using techniques from combinatorics on words, a fast method to compute bwt without using any end-of-string symbol. we also investigate more general classes of optimal word permutations, where relatedness of symbols may be measured by functions more complex than context length. for this general problem we provide an instance that is max-snp hard, and therefore unlikely to be solved or approximated efficiently. the results presented here indicate that a key feature of the burrows and wheeler transform seems to be, besides compressibility, the existence of efficient algorithms for its computation and inversion.
on the average state and transition complexity of finite languages. we investigate the average-case state and transition complexity of deterministic and nondeterministic finite automata, when choosing a finite language of a certain ''size'' n uniformly at random from all finite languages of that particular size. here size means that all words of the language are either of length n, or of length at most n. it is shown that almost all deterministic finite automata accepting finite languages over a binary input alphabet have state complexity @q(2^nn), while nondeterministic finite automata are shown to perform better, namely the nondeterministic state complexity is in @q(2^n). interestingly, in both cases the aforementioned bounds are asymptotically like in the worst case. however, the nondeterministic transition complexity is shown to be again @q(2^nn). the case of unary finite languages is also considered. moreover, we develop a framework that allows us to investigate the average-case complexity of operations like, e.g., union, intersection, complementation, and reversal, on finite languages in this setup.
on the number of components for some parallel communicating grammar systems. in natural languages, there occur phenomena like multiple agreements, crossed agreements and replication. these aspects are represented by the three languages k"1={a^nb^nc^n|n>=1}, k"2={a^nb^mc^nd^m|m,n>=1} and k"3={ww|w@?{a,b}^+}, respectively. these languages are of interest, when modeling natural languages. in the present paper, we give parallel communicating grammar systems (pc grammar systems) that generate the languages k"1, k"2 and k"3 but use less or less-powerful components than those used by systems published so far.
compressed data structures: dictionaries and data-aware measures. in this paper, we propose measures for compressed data structures, in which space usage is measured in a data-aware manner. in particular, we consider the fundamental dictionary problem on set data, where the task is to construct a data structure for representing a set s of n items out of a universe u={0,...,u-1} and supporting various queries on s. we use a well-known data-aware measure for set data called gap to bound the space of our data structures. we describe a novel dictionary structure that requires gap+o(nlog(u/n)/logn)+o(nloglog(u/n)) bits. under the ram model, our dictionary supports membership, rank, and predecessor queries in nearly optimal time, matching the time bound of andersson and thorup's predecessor structure [a. andersson, m. thorup, tight(er) worst-case bounds on dynamic searching and priority queues, in: acm symposium on theory of computing, stoc, 2000], while simultaneously improving upon their space usage. we support select queries even faster in o(loglogn) time. our dictionary structure uses exactly gap bits in the leading term (i.e., the constant factor is 1) and answers queries in near-optimal time. when seen from the worst-case perspective, we present the first o(nlog(u/n))-bit dictionary structure that supports these queries in near-optimal time under the ram model. we also build a dictionary which requires the same space and supports membership, select, and partial rank queries even more quickly in o(loglogn) time. we go on to show that for many (real-world) datasets, data-aware methods lead to a worthwhile compression over combinatorial methods. to the best of our knowledge, these are the first results that achieve data-aware space usage and retain near-optimal time.
the class constrained bin packing problem with applications to video-on-demand. in this paper we present approximation results for the class constrained bin packing problem that has applications to video-on-demand systems. in this problem we are given bins of size b with c compartments, and n items of q different classes, each item i@?{1,...,n} with class c"i and size s"i. the problem is to pack the items into bins, where each bin contains at most c different classes and has total items size at most b. we present several approximation algorithms for offline and online versions of the problem.
s4 enriched multimodal categorial grammars are context-free. bar-hillel et al. [y. bar-hillel, c. gaifman, e. shamir, on categorial and phrase structure grammars, bulletin of the research council of israel f (9) (1960) 1-16] prove that applicative categorial grammars weakly recognize the context-free languages. buszkowski [w. buszkowski, generative capacity of non-associative lambek calculus, bulletin of the polish academy of sciences: mathematics 34 (1986) 507-518] proves that grammars based on the product-free fragment of the non-associative lambek calculus nl recognize exactly the context-free languages. kandulski [m. kandulski, the equivalence of non-associative lambek categorial grammars and context-free grammars, zeitschrift fur mathematische logik und grundlagen der mathematik 34 (1988) 41-52] furthers this result by proving that grammars based on nl also recognize exactly the context-free languages. jager [g. jager, residuation, structural rules and context freeness, journal of logic, language and information 13 (2004) 47-59] proves that categorial grammars based on nl@?, the non-associative lambek calculus enriched with residuated modalities, weakly recognize exactly the context-free languages. we extend this result, proving that categorial grammars based on nl"s"4, the enrichment of nl@? by the axioms 4 and t, weakly recognize exactly the context-free languages.
modular construction of complete coalgebraic logics. we present a modular approach to defining logics for a wide variety of state-based systems. the systems are modelled as coalgebras, and we use modal logics to specify their observable properties. we show that the syntax, semantics and proof systems associated with such logics can all be derived in a modular fashion. moreover, we show that the logics thus obtained inherit soundness, completeness and expressiveness properties from their building blocks. we apply these techniques to derive sound, complete and expressive logics for a wide variety of probabilistic systems, for which no complete axiomatisation has been obtained so far.
control of discrete-event systems with modular or distributed structure. most of the large scale state transition (also called discrete-event) systems are formed as parallel compositions of many small subsystems (modules). control of modular and distributed discrete-event systems appears as an approach to handle computational complexity of synthesizing supervisory controllers for large scale systems. for both modular and distributed discrete-event systems sufficient and necessary conditions are derived for modular control synthesis to equal global control synthesis, while enforcing a safety specification in an optimal way (the language of the controlled system is required to be the supremal one achievable by an admissible controller and included in a safety specification language). the two cases of local (decomposable) and global (indecomposable) specifications are considered. the modular control synthesis has a much lower computational complexity than the corresponding global control synthesis for the respective sublanguages. the complexity is compared using explicit formulas.
wcet free time analysis of hard real-time systems on multiprocessors: a regular language-based model. this paper presents the initial step of an aid design method earmarked for operational validation of hard real-time systems. we consider systems that are composed of sequential hard real-time tasks, which are embedded on centralized multiprocessor architectures. we introduce a model based upon untimed finite automata and meant to collect the operational behaviors of the system compatible with its time specifications, and we go on to provide a feasibility decision result for systems composed of tasks presenting cpu loads which are exact values: execution times are not wcet values. this is why we call this approach wcet-free analysis. the results we have achieved likewise involve hardware specifications such as multiprocessors and speeds of processors.
belnap's logic and conditional composition. we study two alternative bases for belnap's four-valued logic and provide complete equational axiomatizations for them. one is called conditional composition logic. it has a single, ternary if-then-else connective with a sequential, operational reading, and four constants for the truth values. the other logic is called guard logic. the main motivation for this logic lies in its technical properties. it admits a useful type of canonical form (term representation), and a relatively simple strategy for equational reasoning.
tutorial on separation results in process calculi via leader election problems. we compare the expressive power of process calculi by studying the problem of electing a leader in a symmetric network of processes. we consider the @p-calculus with mixed choice, separate choice and internal mobility, value-passing ccs and mobile ambients, together with other ambient calculi (safe ambients, the push and pull ambient calculus and boxed ambients). we provide a unified approach for all these calculi using reduction semantics.
verification of boolean programs with unbounded thread creation. most symbolic software model checkers use abstraction techniques to reduce the verification of infinite-state programs to that of decidable classes. boolean programs [t. ball, s.k. rajamani, bebop: a symbolic model checker for boolean programs, in: spin 00, in: lecture notes in computer science, vol. 1885, springer, 2000, pp. 113-130] are the most popular representation for these abstractions. unfortunately, today's symbolic software model checkers are limited to the analysis of sequential programs due to the fact that reachability in boolean programs with unbounded thread creation is undecidable. we address this limitation with a novel algorithm for over-approximating reachability in boolean programs with unbounded thread creation. although the boolean programs are not of finite state, the algorithm always reaches a fix-point. the fixed points are detected by projecting the state of the threads to the globally visible parts, which are finite.
optimality and condensing of information flow through linear refinement. detecting information flows inside a program is useful to check non-interference or independence of program variables, an important aspect of software security. in this paper we present a new abstract domain c expressing constancy of program variables. we then apply giacobazzi and scozzari's linear refinement to build a domain c->c which contains all input/output dependences between the constancy of program variables. we show that c->c is optimal, in the sense that it cannot be further linearly refined, and condensing, in the sense that a compositional, input-independent static analysis over c->c has the same precision as a non-compositional, input-driven analysis. moreover, we show that c->c has a natural representation in terms of boolean formulas, which is important since it allows one to use the efficient binary decision diagrams in its implementation. we then prove that c->c coincides with genaim, giacobazzi and mastroeni's if domain for information flows and with amtoft and banerjee's independ domain for independence. this lets us extend to if and independ the properties that we proved for c->c: optimality, condensing and representation in terms of boolean formulas. as a secondary result, it lets us conclude that if and independ are actually the same abstract domain, although completely different static analyses have been based on them.
algebras with parametrized iterativity. iterative algebras, as studied by nelson and tiuryn, are generalized to algebras whose iterativity is parametrized in the sense that only some variables can be used for iteration. for example, in the case of one binary operation, the free iterative algebra is the algebra of all rational binary trees; if only the left-hand variable is allowed to be iterated, then the free iterative algebra is the algebra of all right-well-founded rational binary trees. in order to express such parametrized iterativity, we work with parametrized endofunctors of set, i.e. finitary endofunctors h:setxset->set, and introduce the concept of iterativity for algebras for the endofunctor x@?h(x,x). we then describe free iterative h-algebras.
selective strictness and parametricity in structural operational semantics, inequationally. parametric polymorphism constrains the behavior of pure functional programs in a way that allows the derivation of interesting theorems about them solely from their types, i.e., virtually for free. the formal background of such 'free theorems' is well developed for extensions of the girard-reynolds polymorphic lambda calculus by algebraic datatypes and general recursion, provided the resulting calculus is endowed with either a purely strict or a purely nonstrict semantics. but modern functional languages like clean and haskell, while using nonstrict evaluation by default, also provide means to enforce strict evaluation of subcomputations at will. the resulting selective strictness gives the advanced programmer explicit control over evaluation order, but is not without semantic consequences: it breaks standard parametricity results. this paper develops an operational semantics for a core calculus supporting all the language features emphasized above. its main achievement is the characterization of observational approximation with respect to this operational semantics via a carefully constructed logical relation. this establishes the formal basis for new parametricity results, as illustrated by several example applications, including the first complete correctness proof for short cut fusion in the presence of selective strictness. the focus on observational approximation, rather than equivalence, allows a finer-grained analysis of computational behavior in the presence of selective strictness than would be possible with observational equivalence alone.
domain-theoretical models of parametric polymorphism. we present a domain-theoretical model of parametric polymorphism based on admissible per's over a domain-theoretical model of the untyped lambda calculus. the model is shown to be a model of abadi & plotkin's logic for parametricity, by the construction of an lapl-structure as defined by the authors in [l. birkedal, r.e. mogelberg, r.l. petersen, parametric domain-theoretical models of polymorphic intuitionistic/linear lambda calculus, in: m. escardo, a. jung, m. mislove (eds.), proceedings of mathematical foundations of programming semantics 2005, vol. 155, 2005, pp. 191-217; l. birkedal, r.e. mogelberg, r.l. petersen, category theoretical models of linear abadi & plotkin logic, 2006 (submitted for publication)]. this construction gives formal proof of solutions to a large class of recursive domain equations, which we explicate. as an example of a computation in the model, we explicitly describe the natural numbers object obtained using parametricity. the theory of admissible per's can be considered a domain theory for (impredicative) polymorphism. by studying various categories of admissible and chain complete per's and their relations, we discover a picture very similar to that of domain theory.
concurrent games with tail objectives. we study infinite stochastic games played by two players over a finite state space, with objectives specified by sets of infinite traces. the games are concurrent (players make moves simultaneously and independently), stochastic (the next state is determined by a probability distribution that depends on the current state and chosen moves of the players) and infinite (proceed for an infinite number of rounds). the analysis of concurrent stochastic games can be classified into: quantitative analysis, analyzing the optimum value of the game and @e-optimal strategies that ensure values within @e of the optimum value; and qualitative analysis, analyzing the set of states with optimum value 1 and @e-optimal strategies for the states with optimum value 1. we consider concurrent games with tail objectives, i.e., objectives that are independent of the finite-prefix of traces, and show that the class of tail objectives is strictly richer than that of the @w-regular objectives. we develop new proof techniques to extend several properties of concurrent games with @w-regular objectives to concurrent games with tail objectives. we prove the positive limit-one property for tail objectives. the positive limit-one property states that for all concurrent games if the optimum value for a player is positive for a tail objective @f at some state, then there is a state where the optimum value is 1 for the player for the objective @f. we also show that the optimum values of zero-sum (strictly conflicting objectives) games with tail objectives can be related to equilibrium values of nonzero-sum (not strictly conflicting objectives) games with simpler reachability objectives. a consequence of our analysis presents a polynomial time reduction of the quantitative analysis of tail objectives to the qualitative analysis for the subclass of one-player stochastic games (markov decision processes).
component refinement and csc-solving for stg decomposition. stgs (signal transition graphs) give a formalism for the description of asynchronous circuits based on petri nets. to overcome the state explosion problem one may encounter during circuit synthesis, a nondeterministic algorithm for decomposing stgs was suggested by chu and improved by one of the present authors. here we study how csc-solving-which is essential for circuit synthesis-can be combined with decomposition. for this purpose, the correctness definition for decomposition is enhanced with internal signals and hierarchical decomposition is proven correct. based on this, it is shown that speed-independent csc-solving preserves correctness and can be combined with decomposition. furthermore, we use our new correctness definition to give the first correctness proof for the decomposition method of carmona and cortadella. finally, we compare three different implementation relations for stgs: one derived from our correctness definition; one defined by dill based on trace structures; and one derived from i/o-compatibility defined by carmona and cortadella.
query-point visibility constrained shortest paths in simple polygons. in this paper, we study the problem of finding the shortest path between two points inside a simple polygon such that there is at least one point on the path from which a query point is visible. we provide an algorithm which preprocesses the input in o(n^2+nk) time and space and provides logarithmic query time. the input polygon has n vertices and k is a parameter dependent on the input polygon which is o(n^2) in the worst case but is much smaller for most polygons. the preprocessing algorithm sweeps an angular interval around every reflex vertex of the polygon to store the optimal contact points between the shortest paths and the windows separating the visibility polygons of the query points from the source and the destination.
the complexity of two problems on arithmetic circuits. by using arithmetic circuits, encoding multivariate polynomials may be drastically more efficient than writing down the list of monomials. via the study of two examples, we show however that such an encoding can be hard to handle with a turing machine even if the degree of the polynomial is low. namely we show that deciding whether the coefficient of a given monomial is zero is hard for p^#^p under strong nondeterministic turing reductions. as a result, this problem does not belong to the polynomial hierarchy unless this hierarchy collapses. for polynomials over fields of characteristic k>0, this problem is mod"kp-complete. this gives a conp^m^o^d^"^k^p algorithm for deciding an upper bound on the degree of a polynomial given by a circuit in fields of characteristic k>0.
on complexity of grammars related to the safety problem. leftist grammars were introduced by motwani et al., who established the relationship between the complexity of the accessibility problem (or safety problem) for certain general protection systems and the membership problem for these grammars. the membership problem for leftist grammars is decidable. this implies the decidability of the accessibility problem. it is shown that the membership problem for leftist grammars is pspace-hard. therefore, the accessibility problem in the appropriate protection systems is pspace-hard as well. furthermore, the pspace-hardness result is adapted to a very restricted class of leftist grammars, if the grammar is a part of the input.
identity-based ring signatures from rsa. shamir proposed in 1984 the first identity-based signature scheme, whose security relies on the rsa problem. a similar scheme was proposed by guillou and quisquater in 1988. formal security of these schemes was not argued and/or proved until many years later [d. pointcheval, j. stern, security arguments for digital signatures and blind signatures, journal of cryptology 13 (3) (2000) 361-396; y. dodis, j. katz, s. xu, m. yung, strong key-insulated signature schemes, in: proceedings of pkc'03, in: lncs, vol. 2567, springer-verlag, 2002, pp. 130-144; m. bellare, c. namprempre, g. neven, security proofs for identity-based identification and signature schemes, in: proceedings of eurocrypt'04, in: lncs, vol. 3027, springer-verlag, 2004, pp. 268-286]. taking the guillou-quisquater scheme as the starting point, we design and analyze in this work ring signature schemes and distributed ring signature schemes for identity-based scenarios whose security is based on the hardness of the rsa problem. these are the first identity-based ring signature schemes which do not employ bilinear pairings. furthermore, the resulting schemes satisfy an interesting property: the real author(s) of a ring signature can later open the anonymity and prove that he is actually the person who signed the message.
mirror substitutions and palindromic sequences. by introducing the notion of mirror substitution, we show that, given a substitutive sequence over two letters, it is palindromic (that is, it contains arbitrarily long palindromes) if and only if its language is mirror-invariant (that is, it is closed under the mirror image map). then we solve a question of hof, knill and simon in the 2-letter case, and also, by constructing a counterexample, we give a negative answer to the open problem 4 in the webpage: http://iml.univ-mrs.fr/~bernat/openquestions.html.
upward separations and weaker hypotheses in resource-bounded measure. we consider resource-bounded measure in double-exponential-time complexity classes. in contrast to complexity class separation translating downwards, we show that measure separation translates upwards. for example, @m"p(np)0@?@m"e"x"p(nexp)
a solution to the angel problem. we solve the angel problem, by describing a strategy that guarantees the win of an angel of power 2 or greater. basically, the angel should move north as quickly as possible. however, he should detour around eaten squares, as long as the extra distance does not exceed twice the number of eaten squares evaded. we show that an angel following this strategy will always spot a trap early enough to avoid it.
np-hard graph problems and boundary classes of graphs. any graph problem, which is np-hard in general graphs, becomes polynomial-time solvable when restricted to graphs in special classes. when does a difficult problem become easy? to answer this question we study the notion of boundary classes. in the present paper we define this notion in its most general form, describe several approaches to identify boundary classes and apply them to various graph problems.
towards a theory of data entanglement. we give a formal model for systems that store data in entangled form. we propose a new notion of entanglement, called all-or-nothing integrity (aoni) that binds the users' data in a way that makes it hard to corrupt the data of any one user without corrupting the data of all users. aoni can be a useful defense against negligent or dishonest storage providers who might otherwise be tempted to discard documents belonging to users without much clout. we show that, if all users use a fixed standard recovery algorithm, we can implement aoni using a mac, but, if some of the users adopt instead a non-standard recovery algorithm provided by the dishonest storage provider, aoni can no longer be achieved. however, even for the latter scenario, we describe a simple entangling mechanism that provides aoni for a restricted class of destructive adversaries.
strict partitions and discrete dynamical systems. we prove that the set of partitions with distinct parts of a given positive integer under dominance ordering can be considered as a configuration space of a discrete dynamical model with two transition rules and with the initial configuration being the singleton partition. this allows us to characterize its lattice structure, fixed point, and longest chains as well as their length, using chip firing game theory. finally, we study the recursive structure of infinite extension of the lattice of strict partitions.
on the subword complexity of thue-morse polynomial extractions. let the (subword) complexity of a sequence u=(u"n)"n"="0^~ over a finite set @s be the function m@?p"u(m), where p"u(m) is the number of distinct blocks of length m in u. let t=(t"n)"n"="0^~ denote the thue-morse sequence. in this paper we study the complexity of the sequences t"h=(t"h"("n"))"n"="0^~, when h(n)@?q[n] is a polynomial with h(n)@?n. in particular, we solve an open problem of allouche and shallit regarding (t"n"^"2)"n"="0^~. we also study the vector space over z/2z, spanned by the sequences t"h.
relational codes of words. we consider words, i.e. strings over a finite alphabet together with a similarity relation induced by a compatibility relation on letters. this notion generalizes that of partial words. the theory of codes on combinatorics on words is revisited by defining (r,s)-codes for arbitrary similarity relations r and s. we describe an algorithm to test whether or not a finite set of words is an (r,s)-code. coding properties of finite sets of words are explored by finding maximal and minimal relations with respect to relational codes.
algorithms for terminal steiner trees. the terminal steiner tree problem (tst) consists of finding a minimum cost steiner tree where each terminal is a leaf. we describe a factor 2@r-@r/(3@r-2) approximation algorithm for the tst, where @r is the approximation factor of a given algorithm for the steiner tree problem. considering the current best value of @r, this improves a previous 3.10 factor to 2.52. for the tst restricted to instances where all edge costs are either 1 or 2, we improve the approximation factor from 1.60 to 1.42.
on the hardness of inferring phylogenies from triplet-dissimilarities. this work considers the problem of reconstructing a phylogenetic tree from triplet-dissimilarities, which are dissimilarities defined over taxon-triplets. triplet-dissimilarities are possibly the simplest generalization of pairwise dissimilarities, and were used for phylogenetic reconstructions in the past few years. we study the hardness of finding a tree best fitting a given triplet-dissimilarity table under the @?"~ norm. we show that the corresponding decision problem is np-hard and that the corresponding optimization problem cannot be approximated in polynomial time within a constant multiplicative factor smaller than 1.4. on the positive side, we present a polynomial time constant-rate approximation algorithm for this problem. we also address the issue of best-fit under maximal distortion, which corresponds to the largest ratio between matching entries in two triplet-dissimilarity tables. we show that it is np-hard to approximate the corresponding optimization problem within any constant multiplicative factor.
canonical scattered context generators of sentences with their parses. scattered context generators derive their sentences followed by the corresponding parses. this paper discusses their two canonical versions, which make this derivation either in a leftmost or rightmost way. it demonstrates that for every recursively enumerable language, l, there exists a canonical scattered context generator whose language consists of l's sentences followed by their parses. in fact, this result is established based on the generators containing no more than six nonterminals.
edge-colouring of regular graphs of large degree. we consider the following conjecture: letgbe ak-regular simple graph with an even numbernof vertices. ifk>=n/2thengisk-edge-colourable. we show that this conjecture is true for graphs that are join of two graphs and we provide a polynomial time algorithm for finding a k-edge-colouring of these graphs.
a tight analysis of the katriel-bodlaender algorithm for online topological ordering. katriel and bodlaender [irit katriel, hans l. bodlaender, online topological ordering, acm transactions on algorithms 2 (3) (2006) 364-379] modify the algorithm proposed by alpern et al. [bowen alpern, roger hoover, barry k. rosen, peter f. sweeney, f. kenneth zadeck, incremental evaluation of computational circuits, in: proceedings of the first annual acm-siam symposium on discrete algorithms (soda), 1990, pp. 32-42] for maintaining the topological order of the n nodes of a directed acyclic graph while inserting m edges and prove that their algorithm runs in o(min{m^3^/^2logn,m^3^/^2+n^2logn}) time and has an @w(m^3^/^2) lower bound. in this paper, we give a tight analysis of their algorithm by showing that it runs in time @q(m^3^/^2+mn^1^/^2logn).
learning languages from positive data and a limited number of short counterexamples. we consider two variants of a model for learning languages in the limit from positive data and a limited number of short negative counterexamples (counterexamples are considered to be short if they are smaller than the largest element of input seen so far). negative counterexamples to a conjecture are examples which belong to the conjectured language but do not belong to the input language. within this framework, we explore how/when learners using n short (arbitrary) negative counterexamples can be simulated (or simulate) using least short counterexamples or just 'no' answers from a teacher. we also study how a limited number of short counterexamples fairs against unconstrained counterexamples, and also compare their capabilities with the data that can be obtained from subset, superset, and equivalence queries (possibly with counterexamples). a surprising result is that just one short counterexample can sometimes be more useful than any bounded number of counterexamples of arbitrary sizes. most of the results exhibit salient examples of languages learnable or not learnable within corresponding variants of our models.
on a class of infinite words with affine factor complexity. in this article, we consider the fixed point of a primitive substitution canonically defined by a @b-numeration system. the problem of determination of the factor complexity of such an infinite word has been solved only partially. here we provide a necessary and sufficient condition on the renyi expansion of one for having an affine factor complexity map c(n), that is, such that c(n)=an+b for any positive integer n.
on clique separators, nearly chordal graphs, and the maximum weight stable set problem. clique separators in graphs are a helpful tool used by tarjan as a divide-and-conquer approach for solving various graph problems such as the maximum weight stable set (mws) problem, maximum clique, graph coloring and minimum fill-in, but few examples of graph classes having clique separators are known. we use this method to solve mws in polynomial time for two classes where the unweighted maximum stable set (ms) problem is solvable in polynomial time by augmenting techniques but the complexity of the mws problem was open. another example, namely a result by alekseev for the mws problem on a subclass of p"5-free graphs obtained by clique separators, can be improved by our techniques. we also combine clique separators with decomposition by homogeneous sets in graphs and use the following notion: a graph is nearly@p if for each of its vertices, the subgraph induced by the set of its nonneighbors has property @p. we deal with the cases @p@?{chordal,perfect}. this also simplifies a result obtained by a method called struction.
the affix array data structure and its applications to rna secondary structure analysis. efficient string-processing in large data sets like complete genomes is strongly connected to the suffix tree and similar index data structures. with respect to complex structural string analysis like the search for rna secondary structure patterns, unidirectional suffix tree algorithms are inferior to bidirectional algorithms based on the affix tree data structure. the affix tree incorporates the suffix tree and the suffix tree of the reverse text in one tree structure but suffers from its large memory requirements. in this paper i present a new data structure, denoted affix array, which is equivalent to the affix tree with respect to its algorithmic functionality, but with smaller memory requirements and improved performance. i will show a linear time construction of the affix array without making use of the linear time construction of the affix tree. i will also show how bidirectional affix tree traversals can be transferred to the affix array and present the impressive results of large scale rna secondary structure analysis based on the new data structure.
freeness of partial words. the paper approaches the classical combinatorial problem of freeness of words, in the more general case of partial words. first, we propose an algorithm that tests efficiently whether a partial word is k-free or not, for a given k. then, we show that there exist arbitrarily many k-free infinite partial words, over a binary alphabet, containing an infinite number of holes, for k>=3. moreover, we present an efficient algorithm for the construction of a cube-free partial word with a given number of holes, over a binary alphabet. in the final section of the paper, we show that there exists an infinite word, over a four-symbol alphabet, in which we can substitute randomly one symbol with a hole, and still obtain a cube-free word; we show that such a word does not exist for alphabets with fewer symbols. further, we prove that in this word we can replace arbitrarily many symbols with holes, such that each two consecutive holes are separated by at least two symbols, and obtain a cube-free partial word. this result seems interesting because any partial word containing two holes with less than two symbols between them is not cube-free. finally, we modify the previously presented algorithm to construct, over a four-symbol alphabet, a cube-free partial word with exactly n holes, having minimal length, among all the possible cube-free partial words with at least n holes.
reducing rank-maximal to maximum weight matching. given a bipartite graph g(v,e), v=a@?@?b where |v|=n,|e|=m and a partition of the edge set into r@?m disjoint subsets e=e"1@?@?e"2@?@?...@?@?e"r, which are called ranks, the rank-maximal matching problem is to find a matching m of g such that |m@?e"1| is maximized and given that |m@?e"1| is maximized, |m@?e"2| is also maximized, and so on. such a problem arises as an optimization criteria over a possible assignment of a set of applicants to a set of posts. the matching represents the assignment and the ranks on the edges correspond to a ranking of the posts submitted by the applicants. the rank-maximal matching problem and several other optimization variants, e.g. fair matching and maximum cardinality rank-maximal matching, can be solved by a reduction to the weight matching problem in time o(rnmlogn). recently, irving et al. developed a combinatorial approach which improves the running time for the rank-maximal matching problem to o(min(n+r,rn)m). they raised the open questions on (a) whether such a running time can be achieved by the weight matching reduction and (b) whether such a running time can be achieved for the other variants of the problem. in this work we show how the reduction to the weight matching problem can also be used to achieve the same running time. our algorithm is simpler and more intuitive.
on the hardness of minimizing space for all-shortest-path interval routing schemes. k-interval routing scheme (k-irs) is a compact routing method that allows up to k interval labels to be assigned to an arc; and global k-irs allows not more than a total of k interval labels in the whole network. a fundamental problem is to characterize the networks that admit k-irs (or global k-irs). many of the problems related to single-shortest-path k-irs have already been shown to be np-complete. for all-shortest-path k-irs, the characterization problem remains open for k>=1. in this paper, we study the time complexity of devising minimal-space all-shortest-path k-irss and show that it is np-complete to decide whether a graph admits an all-shortest-path k-irs, for every integer k>=3, and so is that of deciding whether a graph admits an all-shortest-path k-strict irs, for every integer k>=4. these are the first np-completeness results for all-shortest-path k-irs where k is a constant and the graph is unweighted. the np-completeness holds also for the linear case. we also prove that it is np-complete to decide whether an unweighted graph admits an all-shortest-path irs with global compactness of at most k, which also holds for the linear and strict cases.
triangulating a convex polygon with fewer number of non-standard bars. for a given convex polygon with inner angle no less than 23@p and boundary edge bounded by [l,@al] for 1@?@a@?1.4, where l is a given standard bar's length, we investigate the problem of triangulating the polygon using some steiner points such that (i) the length of each edge in triangulation is bounded by [@bl,2l], where @b is a given constant and meets 0
prefix-free regular languages and pattern matching. we explore the regular-expression matching problem with respect to prefix-freeness of the pattern. we prove that a prefix-free regular expression gives only a linear number of matching substrings in the size of a given text. based on this observation, we propose an efficient algorithm for the prefix-free regular-expression matching problem. furthermore, we suggest an algorithm to determine whether or not a given regular language is prefix-free.
tag systems and collatz-like functions. tag systems were invented by emil leon post and proven recursively unsolvable by marvin minsky. these production systems have proved to be very useful in constructing small universal (turing complete) systems for several different classes of computational systems, including turing machines, and are thus important instruments for studying limits or boundaries of solvability and unsolvability. although there are some results on tag systems and their limits of solvability and unsolvability, there are hardly any that consider both the shift number v and the number of symbols @m. this paper aims to contribute to research on limits of solvability and unsolvability for tag systems, taking into account these two parameters. the main result is the reduction of the 3n+1-problem to a surprisingly small tag system. it indicates that the present unsolvability line-defined in terms of @m and v-for tag systems might be significantly decreased.
an improved approximation algorithm for capacitated multicast routings in networks. let g=(v,e) be a connected graph such that each edge e@?e is weighted by nonnegative real w(e). let s be a vertex designated as a source, k be a positive integer, and s@?v be a set of terminals. the capacitated multicast tree routing problem (cmtr) asks to find a partition {z"1,z"2,...,z"@?} of s and a set {t"1,t"2,...,t"@?} of trees of g such that z"i consists of at most k terminals and each t"i spans z"i@?{s}. the objective is to minimize @?"i"="1^@?w(t"i), where w(t"i) denotes the sum of weights of all edges in t"i. in this paper, we propose a (3/2+(4/3)@r)-approximation algorithm to the cmtr, where @r is the best achievable approximation ratio for the steiner tree problem.
true-concurrency probabilistic models: markov nets and a law of large numbers. we introduce the model of markov nets, a probabilistic extension of safe petri nets under the true-concurrency semantics-this means that traces, not firing sequences, are given a probability. this model builds upon our previous work on probabilistic event structures. we use the notion of a branching cell for event structures, and show that the latter provides an adequate conception of local state for nets. we prove a law of large numbers (lln) for markov nets, which constitutes the main contribution of the paper. this lln allows for the characterization, in a quantitative way, of the asymptotic behavior of markov nets.
online bin packing with arbitrary release times. we study a new variant of the online bin-packing problem, in which each item a"i is associated with a size a"i and also a release time r"i so that it must be placed at least r"i above the bottom of a bin. items arrive in turn and must be assigned without any knowledge of subsequent items. the goal is to pack all items into unit-size bins using the minimum number of bins. we study the problem with all items have equal size. first, we show that the any fit algorithm cannot be approximated within any constant. then we present a best possible online algorithm with asymptotic competitive ratio of two.
a rounding algorithm for approximating minimum manhattan networks. for a set t of n points (terminals) in the plane, a manhattan network on t is a network n(t)=(v,e) with the property that its edges are horizontal or vertical segments connecting points in v@?t and for every pair of terminals, the network n(t) contains a shortest l"1-path between them. a minimum manhattan network on t is a manhattan network of minimum possible length. the problem of finding minimum manhattan networks has been introduced by gudmundsson, levcopoulos, and narasimhan [j. gudmundsson, c. levcopoulos, g. narasimhan, approximating a minimum manhattan network, nordic journal of computing 8 (2001) 219-232. proc. approx'99, 1999, pp. 28-37] and its complexity status is unknown. several approximation algorithms (with factors 8, 4, and 3) have been proposed; recently kato, imai, and asano [r. kato, k. imai, t. asano, an improved algorithm for the minimum manhattan network problem, isaac'02, in: lncs, vol. 2518, 2002, pp. 344-356] have given a factor 2-approximation algorithm, however their correctness proof is incomplete. in this paper, we propose a rounding 2-approximation algorithm based on an lp-formulation of the minimum manhattan network problem.
motif patterns in 2d. motif patterns consisting of sequences of intermixed solid and don't-care characters have been introduced and studied in connection with pattern discovery problems of computational biology and other domains. in order to alleviate the exponential growth of such motifs, notions of maximal saturation and irredundancy have been formulated, whereby more or less compact subsets of the set of all motifs can be extracted, that are capable of expressing all others by suitable combinations. in this paper, we introduce the notion of maximal irredundant motifs in a two-dimensional array and develop initial properties and a combinatorial argument that poses a linear bound on the total number of such motifs. the remainder of the paper presents approaches to the discovery of irredundant motifs both by offline and incremental algorithms.
third-order idealized algol with iteration is decidable. the problems of contextual equivalence and approximation are studied for the third-order fragment of idealized algol with iteration (ia"3^*). they are approached via a combination of game semantics and language theory. it is shown that for each ia"3^*-term one can construct a pushdown automaton recognizing a representation of the strategy induced by the term. the automata have some additional properties ensuring that the associated equivalence and inclusion problems are solvable in ptime. this gives an exptime decision procedure for the problems of contextual equivalence and approximation for @b-normal terms. exptime-hardness of the problems, even for terms without iteration, is also shown.
expressivity of coalgebraic modal logic: the limits and beyond. modal logic has a good claim to being the logic of choice for describing the reactive behaviour of systems modelled as coalgebras. logics with modal operators obtained from so-called predicate liftings have been shown to be invariant under behavioural equivalence. expressivity results stating that, conversely, logically indistinguishable states are behaviourally equivalent depend on the existence of separating sets of predicate liftings for the signature functor at hand. here, we provide a classification result for predicate liftings which leads to an easy criterion for the existence of such separating sets, and we give simple examples of functors that fail to admit expressive normal or monotone modal logics, respectively, or in fact an expressive (unary) modal logic at all. we then move on to polyadic modal logic, where modal operators may take more than one argument formula. we show that every accessible functor admits an expressive polyadic modal logic. moreover, expressive polyadic modal logics are, unlike unary modal logics, compositional.
optimal reachability for multi-priced timed automata. in this paper, we prove the decidability of the minimal and maximal reachability problems for multi-priced timed automata, an extension of timed automata with multiple cost variables evolving according to given rates for each location. more precisely, we consider the problems of synthesizing the minimal and maximal costs of reaching a given target location. these problems generalize conditional optimal reachability, i.e., the problem of minimizing one primary cost under individual upper bound constraints on the remaining, secondary, costs, and the problem of maximizing the primary cost under individual lower bound constraints on the secondary costs. furthermore, under the liveness constraint that all traces eventually reach the goal location, we can synthesize all costs combinations that can reach the goal. the decidability of the minimal reachability problem is proven by constructing a zone-based algorithm that always terminates while synthesizing the optimal cost tuples. for the corresponding maximization problem, we construct two zone-based algorithms, one with and one without the above liveness constraint. all algorithms are presented in the setting of two cost variables and then lifted to an arbitrary number of cost variables.
panconnectivity and edge-pancyclicity of faulty recursive circulant g(2, 4). in this paper, we investigate a problem on embedding paths into recursive circulant g(2^m,4) with faulty elements (vertices and/or edges) and show that each pair of vertices in recursive circulant g(2^m,4), m>=3, are joined by a fault-free path of every length from m+1 to |v(g(2^m,4)@?f)|-1 inclusive for any fault set f with |f|@?m-3. the bound m-3 on the number of acceptable faulty elements is the maximum possible. moreover, recursive circulant g(2^m,4) has a fault-free cycle of every length from 4 to |v(g(2^m,4)@?f)| inclusive excluding 5 passing through an arbitrary fault-free edge for any fault set f with |f|@?m-3.
algorithmic analysis of polygonal hybrid systems, part ii: phase portrait and tools. polygonal differential inclusion systems (spdi) are a subclass of planar hybrid automata which can be represented by piecewise constant differential inclusions. the reachability problem as well as the computation of certain objects of the phase portrait is decidable. in this paper we show how to compute the viability, controllability and invariance kernels, as well as semi-separatrix curves for spdis. we also present the tool speedi^+, which implements a reachability algorithm and computes phase portraits of spdis.
gathering asynchronous oblivious mobile robots in a ring. we consider the problem of gathering identical, memoryless, mobile robots in one node of an anonymous unoriented ring. robots start from different nodes of the ring. they operate in look-compute-move cycles and have to end up in the same node. in one cycle, a robot takes a snapshot of the current configuration (look), makes a decision to stay idle or to move to one of its adjacent nodes (compute), and in the latter case makes an instantaneous move to this neighbor (move). cycles are performed asynchronously for each robot. for an odd number of robots we prove that gathering is feasible if and only if the initial configuration is not periodic, and we provide a gathering algorithm for any such configuration. for an even number of robots we decide the feasibility of gathering except for one type of symmetric initial configurations, and provide gathering algorithms for initial configurations proved to be gatherable.
parikh matrices and amiable words. using the fact that the parikh matrix mapping is not an injective mapping, the paper investigates some properties of the set of words with the same parikh matrix; these words are called ''amiable''. the presented results extend the results obtained in [a. atanasiu, binary amiable words, int. j. found. comput. sci. 18 (2) (2007) 387-400] for the binary case. in particular it is shown that all the words having the same parikh matrix can be obtained one from another by applying only two types of transformations. moreover, the mirrors of two amiable words are also amiable (thus forming a symmetrical class of words).
generalized approximate counting revisited. a large class of q-distributions is defined on the stochastic model of bernoulli trials in which the probability of success (= advancing to the next level) depends geometrically on the number of trials and the level already reached. if the dependency is only on the level already reached, this is an algorithm called approximate counting. two random variables, x"n (level reached after n trials) and y"k (number of trials to reach level k) are of interest. we rederive known results and obtain new ones in a consistent way, based on generating functions. we also discuss asymptotics. the classical instance of approximate counting is more interesting from a mathematical point of view. on the other hand, if the number of trials also decreases the probability of success (advancing to the next level), then the limits are constants which are straightforward to compute.
on periodicity of two-dimensional words. a two-dimensional word is a function on z^2 with finite number of values. the main problem we are interested in is the periodicity of two-dimensional words satisfying some local conditions. in this paper we prove that every bounded centered function on the infinite rectangular grid is periodic. a function is called centered if the sum of its values in every ball is equal to 0. similar results are obtained for the infinite triangular and hexagonal grids.
optimal computation with non-unitary quantum walks. quantum versions of random walks on the line and the cycle show a quadratic improvement over classical random walks in their spreading rates and mixing times, respectively. non-unitary quantum walks can provide a useful optimisation of these properties, producing a more uniform distribution on the line, and faster mixing times on the cycle. we investigate the interplay between quantum and random dynamics by comparing the resources required, and examining numerically how the level of quantum correlations varies during the walk. we show numerically that the optimal non-unitary quantum walk proceeds such that the quantum correlations are nearly all removed at the point of the final measurement. this requires only o(logt) random bits for a quantum walk of t steps.
an algorithm for recognition of n-collapsing words. a word w over a finite alphabet @s is n-collapsing if for an arbitrary deterministic finite automaton a=, the inequality |@d(q,w)|@?|q|-n holds provided that |@d(q,u)|@?|q|-n for some word u@?@s^+ (depending on a). we prove that the property of n-collapsing is algorithmically recognizable for any given positive integer n. we also prove that the language of all n-collapsing words is context-sensitive.
multiple constraints on three and four words. in this paper we consider several questions related to the defect theorem for sets of three and four words. we start by investigating how large systems of pairwise independent or pairwise non-equivalent equations over three unknowns possessing purely non-periodic solutions can be. in other words, we analyze how weak the cumulative defect effect of such systems is. then, we investigate the maximal size of chains of equations over three or four words such that every time we add a new equation the set of solutions strictly decreases.
completing circular codes in regular submonoids. let m be an arbitrary submonoid of the free monoid a^*, and let x@?m be a variable length code (for short a code). x is weakly m-complete iff any word in m is a factor of some word in x^* [j. neraud, c. selmi, free monoid theory: maximality and completeness in arbitrary submonoids, internat. j. algebra comput. 13 (5) (2003) 507-516]. given a regular submonoid m, and given an arbitrary code x@?m, we are interested in the existence of a weakly m-complete code x@? that contains x. actually, in [j. neraud, completing a code in a regular submonoid, in: acts of mcu'2004, lect. notes comput. sci. 3354 (2005) 281-291; j. neraud, completing a code in a submonoid of finite rank, fund. inform. 74 (2006) 549-562], by presenting a general formula, we have established that, in any case, such a code x@? exists. in the present paper, we prove that any regular circular code x@?m may be embedded into a weakly m-complete one iff the minimal automaton with behavior m has a synchronizing word. as a consequence of our result an extension of the famous theorem of schutzenberger is stated for regular circular codes in the framework of regular submonoids. we study also the behaviour of the subclass of uniformly synchronous codes in connection with these questions.
shuffle operations on discrete paths. we consider the shuffle operation on paths and study some parameters. in the case of square lattices, shuffling with a particular periodic word (of period 2) corresponding to paperfoldings reveals some characteristic properties: closed paths remain closed; the area and perimeter double; the center of gravity moves under a 45^@? rotation and a 2 zoom factor. we also observe invariance properties for the associated dragon curves. moreover, replacing square lattice paths by paths involving 2k@p/n-turns, we find analogous results using more general shuffles.
a conversion algorithm based on the technique of singularization. we present a simple conversion algorithm which allows to rewrite the two-dimensional brun algorithm in terms of the podsypanin algorithm. further, we demonstrate how this conversion process can be used to transfer certain (statistical, approximation) properties from the original to the resulting algorithm.
on undecidability bounds for matrix decision problems. in this paper we consider several reachability problems such as vector reachability, membership in matrix semigroups and reachability problems in piecewise linear maps. since all of these questions are undecidable in general, we work on lowering the bounds for undecidability. in particular, we show an elementary proof of undecidability of the reachability problem for a set of 5 two-dimensional affine transformations. then, using a modified version of a standard technique, we also prove that the vector reachability problem is undecidable for two (rational) matrices in dimension 11. the above result can be used to show that the system of piecewise linear functions of dimension 12 with only two intervals has an undecidable set-to-point reachability problem. we also show that the ''zero in the upper right corner'' problem is undecidable for two integral matrices of dimension 18 lowering the bound from 23.
regular languages and their generating functions: the inverse problem. the technique of determining a generating function for an unambiguous context-free language is known as the schutzenberger methodology. for regular languages, elena barcucci et al. proposed an approach for inverting this methodology based on soittola's theorem. this idea allows a combinatorial interpretation (by means of a regular language) of certain positive integer sequences that are defined by c-finite recurrences. in this paper we present a maple implementation of this inverse methodology and describe various applications. we give a short introduction to the underlying theory, i.e., the question of deciding n-rationality. in addition, some aspects and problems concerning the implementation are discussed; some examples from combinatorics illustrate its applicability.
a characterization of fine words over a finite alphabet. to any infinite word t over a finite alphabet a we can associate two infinite words min(t) and max(t) such that any prefix of min(t) (resp. max(t)) is the lexicographically smallest (resp. greatest) amongst the factors of t of the same length. we say that an infinite word t over a is fine if there exists an infinite word s such that, for any lexicographic order, min(t)=as where a=min(a). in this paper, we characterize fine words; specifically, we prove that an infinite word t is fine if and only if t is either a strict episturmian word or a strict ''skew episturmian word''. this characterization generalizes a recent result of g. pirillo, who proved that a fine word over a 2-letter alphabet is either an (aperiodic) sturmian word, or an ultimately periodic (but not periodic) infinite word, all of whose factors are (finite) sturmian.
cobham-semenov theorem and n-subshifts. we give a new proof of cobham's first theorem using ideas from symbolic dynamics and of cobham-semenov theorem (in the primitive case) using ideas from tiling dynamics.
words avoiding repetitions in arithmetic progressions. carpi constructed an infinite word over a 4-letter alphabet that avoids squares in all subsequences indexed by arithmetic progressions of odd difference. we show a connection between carpi's construction and the paperfolding words. we extend carpi's result by constructing uncountably many words that avoid squares in arithmetic progressions of odd difference. we also construct infinite words avoiding overlaps and infinite words avoiding all sufficiently large squares in arithmetic progressions of odd difference. we use these words to construct labelings of the 2-dimensional integer lattice such that any line through the lattice encounters a squarefree (resp. overlapfree) sequence of labels.
self-dual tilings with respect to star-duality. the concept of star-duality is described for self-similar cut-and-project tilings in arbitrary dimensions. this generalises thurston's concept of a galois-dual tiling. the dual tilings of the penrose tilings as well as the ammann-beenker tilings are calculated. conditions for a tiling to be self-dual are obtained.
cancellation and periodicity properties of iterated morphisms. in this note we prove two cancellation properties of iterated morphisms and use these properties to give a simple method for deciding whether or not a given infinite d0l word is ultimately periodic.
semi-online scheduling on two uniform processors. in this paper we consider the problem of semi-online scheduling on two uniform processors, in the case where the total sum of the tasks is known in advance. tasks arrive one at a time and have to be assigned to one of the two processors before the next one arrives. the assignment cannot be changed later. the objective is the minimization of the makespan. assume that the speed of the fast processor is s, while the speed of the slow one is normalized to 1. as a function of s, we derive general lower bounds on the competitive ratio achievable with respect to offline optimum, and design on-line algorithms with guaranteed upper bound on their competitive ratio. the algorithms presented for s>=3 are optimal, as well as for s=1 and for 1+174@?s@?1+32.
sound and complete computational interpretation of symbolic hashes in the standard model. this paper provides one more step towards bridging the gap between the formal and computational approaches to the verification of cryptographic protocols. we extend the well-known abadi-rogaway logic with probabilistic hashes and give a precise semantic interpretation to it using canetti's oracle hashes. these are probabilistic polynomial-time hashes that hide all partial information. we show that, under appropriate conditions on the encryption scheme, this interpretation is computationally sound and complete. this can be used to port security results from the formal world to the computational world when considering passive adversaries. we also give an explicit example showing that oracle hashing is not strong enough to obtain such a result for active adversaries.
unconditional competitive auctions with copy and budget constraints. this paper investigates a new auction model in which bidders have both copy and budget constraints. this new model has extensive and interesting applications in auctions of online ad-words, software licenses, etc. we consider the following problem: supposing all participators are rational, how does one allocate the objects and at what price so as to maximize the auctioneer's revenue. we introduce new kinds of mechanisms called auctioneer-advantaged mechanisms and present the notion of unconditional competitive auctions. a notably interesting property of auctioneer-advantaged mechanisms is that each bidder's self-interested strategy brings better utility not only to himself but also to the auctioneer. then we present auctioneer-advantaged mechanisms for multi-unit auctions with copy and budget constraints. we prove that these auctions are unconditional competitive under the situation of both limited and unlimited supply.
mixed nash equilibria in selfish routing problems with dynamic constraints. we study the problem of routing traffic through a congested network consisting of m parallel links, each having a certain speed. moreover, we are given n selfish (non-cooperative) agents, each of them willing to route her own piece of traffic on exactly one link. agents are selfish in that they only pick a link which minimize the delay of their own piece of traffic. in this context much effort has been lavished in the framework of mixed nash equilibria where the agent's routing choices are regulated by probability distributions, one for each agent, which let the system thus enter a steady state from which no agent is willing to unilaterally deviate. in this work we consider situations in which some agents have constraints on the routing choice: in a sense they are forbidden to route their traffic on some links. we show that at most one nash equilibrium may exist and, in some cases with equal speed links and where each agent is forbidden to route on at most one link, we give necessary and sufficient conditions on its existence; these conditions correlate the traffic load of the agents. we consider also a dynamic behaviour of the network when the constraints may vary, in particular when a constraint is removed: we establish under which conditions the network is still in equilibrium. these conditions are all effective in the sense that, given a set of yes/no routing constraints on each link for each agent, we provide the probability distributions corresponding to the unique nash equilibrium associated to the constraints (if it exists). moreover these conditions and the possible nash equilibrium are computed in time o(mn).
fibrations and universal view updatability. maintainability and modifiability of information system software can be enhanced by the provision of comprehensive support for views, since view support allows application programs to continue to operate unchanged when the underlying information system is modified. supporting views depend upon a solution to the view update problem. this paper presents a new treatment of view updates for formally specified semantic data models based on the category theoretic sketch data model. the sketch data model has been the basis of a number of successful major information system consultancies. we define view updates by a universal property in models of the formal specification, and explain why this indeed gives a complete and correct treatment of view updatability, including a solution to the view update problem. however, a definition of updatability which is based on models causes some inconvenience in applications, so we prove that in a variety of circumstances updatability is guaranteed independently of the current model. this is done first with a very general criterion, and then for some specific cases relevant to applications. we include some details about the sketch data model, noting that it involves extensions of algebraic data specification techniques.
gemcell: a generic platform for modeling multi-cellular biological systems. the mass and complexity of biological information requires computer-aided simulation and analysis to help scientists achieve understanding and guide experimentation. although living organisms are composed of cells, actual genomic and proteomic data have not yet led to a satisfactory model of working cell in silico. we have set out to devise a user-friendly generic platform, gemcell, for generic executable modeling of cells, based on whole, functioning cells. starting with the cell simplifies life, because all cells expresses essentially five generic types of behavior: replication, death, movement (including change of shape and adherence), export (secretion, signaling, etc.) and import (receiving signals, metabolites, phagocytosis, etc.). the details of these behaviors are specified in gemcell for particular kinds of cells as part of a database of biological specifics (the dbs), which specifies the cell properties and functions that depend on the cell's history, state, environment, etc. the dbs is designed in an intuitive fashion, so users are able to easily insert their data of interest. the generic part of gemcell, built using statecharts, is a fully dynamic model of a cell, its interactions with the environment and its resulting behavior, individually and collectively. model specificity emerges from the dbs, so that model execution is carried out by the statecharts executing with the aid of specific data extracted from the dbs dynamically. our long term goal is for gemcell to serve as a broadly applicable platform for biological modeling and analysis, supporting user-friendly in silico experimentation, animation, discovery of emergent properties, and hypothesis testing, for a wide variety of biological systems.
a multiset-based model of synchronizing agents: computability and robustness. we introduce a modelling framework and computational paradigm called colonies of synchronizing agents (csas) inspired by the intracellular and intercellular mechanisms in biological tissues. the model is based on a multiset of agents in a common environment. each agent has a local state stored in the form of a multiset of atomic objects, which is updated by global multiset rewriting rules either independently or synchronously with another agent. we first define the model then study its computational power, considering trade-offs between internal rewriting (intracellular mechanisms) and synchronization between agents (intercellular mechanisms). we also investigate dynamic properties of csas, including behavioural robustness (ability to generate a core behaviour despite agent loss or rule failure) and safety of synchronization (ability of an agent to synchronize with some other agent whenever needed).
temporal constraints in the logical analysis of regulatory networks. starting from the logical description of gene regulatory networks developed by r. thomas, we introduce an enhanced modeling approach based on timed automata. we obtain a refined qualitative description of the dynamical behavior by exploiting not only information on ratios of kinetic parameters related to synthesis and decay, but also constraints on the time delays associated with the operations of the system. we develop a formal framework for handling such temporal constraints using timed automata, discuss the relationship with the original thomas formalism, and demonstrate the potential of our approach by analyzing an illustrative gene regulatory network of bacteriophage @l.
on process rate semantics. we provide translations between process algebra and systems of chemical reactions. we show that the translations preserve discrete-state (stochastic) and continuous-state (concentration) semantics, and in particular that the continuous-state semantics of processes corresponds to the differential equations of chemistry based on the law of mass action. the novel semantics of processes so obtained equates processes that have the same state occupation dynamics, but which may have different interaction interfaces.
probabilistic model checking of complex biological pathways. probabilistic model checking is a formal verification technique that has been successfully applied to the analysis of systems from a broad range of domains, including security and communication protocols, distributed algorithms and power management. in this paper we illustrate its applicability to a complex biological system: the fgf (fibroblast growth factor) signalling pathway. we give a detailed description of how this case study can be modelled in the probabilistic model checker prism, discussing some of the issues that arise in doing so, and show how we can thus examine a rich selection of quantitative properties of this model. we present experimental results for the case study under several different scenarios and provide a detailed analysis, illustrating how this approach can be used to yield a better understanding of the dynamics of the pathway. finally, we outline a number of exact and approximate techniques to enable the verification of larger and more complex pathways and apply several of them to the fgf case study.
making the use of maximal ideals constructive. the purpose of this paper is to decipher constructively a lemma of suslin which played a central role in his second solution of serre's problem on projective modules over polynomial rings. this lemma says that for a commutative ring a if =a[x] where v"1 is monic and n>=3, then there exist @c"1,...,@c"@?@?e"n"-"1(a[x]) such that, denoting by w"i the first coordinate of @c"it(v"2,...,v"n), we have =a. by the constructive proof we give, suslin's proof of serre's problem becomes fully constructive. moreover, the new method with which we treat this academic example may be a model for miming constructively abstract proofs in which one works modulo a generic maximal ideal in order to prove that an ideal contains 1.
reeb graphs for shape analysis and applications. reeb graphs are compact shape descriptors which convey topological information related to the level sets of a function defined on the shape. their definition dates back to 1946, and finds its root in morse theory. reeb graphs as shape descriptors have been proposed to solve different problems arising in computer graphics, and nowadays they play a fundamental role in the field of computational topology for shape analysis. this paper provides an overview of the mathematical properties of reeb graphs and reconstructs its history in the computer graphics context, with an eye towards directions of future research.
uniform approximation of near-singular surfaces. we consider the problem of a piecewise-polynomial (spline) approximation of algebraic surfaces of a given degree. conventional accuracy estimates in such approximations include bounds on the high-order derivatives, or on the surface curvature. as an algebraic surface degenerates to a singular one, the curvature blows up. consequently, the same happens with the complexity of the approximation: to keep the required accuracy, we need more and more patches at near-singular (high curvature) areas. this indeed happens in any conventional ''triangulation'' algorithm. nevertheless, using ''c^k-reparametrization'' theorem (which originally appeared in dynamical applications) we show in this paper that for such near-singular families of surfaces there exist approximations of any fixed accuracy and of a uniformly bounded complexity. to give an example of a situation, where our construction becomes explicit, we consider one of the possible models for singular (and near-singular) surfaces. in this model, developed in [y. yomdin, generic singularities of surfaces, in: d. cheniot, n. dutertre, c. murolo, d. trotman, a. pichon, (eds), singularity theory, dedicated to j.-p. brasselet on his 60-th birthday (proceedings of the 2005 marseille singularity school and conference, marseille, france), 2005, pp. 24.1-25.2; d. haviv, ma thesis, weizmann institute, 2006] a surface appears as a part of the level surface f=c, with f=f"1f"2...f"m having a product form. the advantage of this approach is that ''edges'' and ''corners'' appear in a generic and stable way, as well as ''near-edges'' and ''near-corners''. using special model-based representation developed in [y. yomdin, generic singularities of surfaces, in: d. cheniot, n. dutertre, c. murolo, d. trotman, a. pichon, (eds), singularity theory, dedicated to j.-p. brasselet on his 60-th birthday (proceedings of the 2005 marseille singularity school and conference, marseille, france), 2005, pp. 24.1-25.2; d. haviv, ma thesis, weizmann institute, 2006], we produce explicit formulae for the uniform c^2-reparametrization of some of these near-singularities.
change of order for regular chains in positive dimension. we discuss changing the variable order for a regular chain in positive dimension. this quite general question has applications going from implicitization problems to the symbolic resolution of some systems of differential algebraic equations. we propose a modular method, reducing the problem to computations in dimension zero and one. the problems raised by the choice of the specialization points and the lack of the (crucial) information of what are the free and algebraic variables for the new order are discussed. strong (but not unusual) hypotheses for the initial regular chain are required; the main required subroutines are change of order in dimension zero and a formal newton iteration.
curves and surfaces represented by polynomial support functions. this paper studies shapes (curves and surfaces) which can be described by (piecewise) polynomial support functions. the class of these shapes is closed under convolutions, offsetting, rotations and translations. we give a geometric discussion of these shapes and present methods for the approximation of general curves and surfaces by them. based on the rich theory of spherical spline functions, this leads to computational techniques for rational curves and surfaces with rational offsets, which can deal with shapes without inflections/parabolic points.
algebraic cycles from a computational point of view. the hodge conjecture implies decidability of the question whether a given topological cycle on a smooth projective variety over the field of algebraic complex numbers can be represented by an algebraic cycle. we discuss some details concerning this observation, and then propose that it suggests going on to actually implement an algorithmic search for algebraic representatives of classes which are known to be hodge classes.
swept regions and surfaces: modeling and volumetric properties. we consider ''swept regions'' @w and ''swept hypersurfaces'' b in r^n^+^1 (and especially r^3) which are a disjoint union of subspaces @w"t=@w@?@p"t or b"t=b@?@p"t obtained from a varying family of affine subspaces {@p"t:t@?@c}. we concentrate on the case where @w and b are obtained from a skeletal structure (m,u). this generalizes the blum medial axis m of a region @w, which consists of the centers of interior spheres tangent to the boundary b at two or more points, with u denoting the vectors from the centers of the spheres to the points of tangency. we extend methods developed for skeletal structures so that they can be deduced from the properties of the individual intersections @w"t or b"t and a relative shape operator s"r"e"l, which we introduce to capture changes relative to the varying family {@p"t}. we use these results to deduce modeling properties of the global b in terms of the individual b"t, and determine volumetric properties of regions @w expressed as global integrals of functions g on @w in terms of iterated integrals over the skeletal structure of @w"t which is then integrated over the parameter space @c.
seminormal rings (following thierry coquand). the traverso-swan theorem says that a reduced ring a is seminormal if and only if the natural homomorphism pica->pica[x] is an isomorphism [c. traverso, seminormality and the picard group, ann. sc. norm. sup. pisa 24 (1970) 585-595; r.g. swan, on seminormality, j. algebra 67 (1980) 210-229]. we give here all the details needed to understand the elementary constructive proof for this result given by coquand in [t. coquand, on seminormality, j. algebra 305 (2006) 577-584]. this example is typical of a new constructive method. the final proof is simpler than the initial classical one. more important: the classical argument by absurdum using ''an abstract ideal object'' is deciphered with a general technique based on the following idea: purely ideal objects constructed using tem and choice may be replaced by concrete objects that are ''finite approximations'' of these ideal objects.
on multiplier sequences. in the present paper we consider real polynomials in one real variable of a given degree n. such a polynomial is called hyperbolic if it has only real roots. a finite multiplier sequence of lengthn+1 (fms(n+1)) is a tuple (c"0,...,c"n), c"i@?r, such that if @?"i"="0^nb"ix^n^-^i, b"i@?r, is a hyperbolic polynomial, then @?"i"="0^nc"ib"ix^n^-^i is also such a polynomial. the set of fms(n+1) coincides with the set of tuples such that @?"i"="0^nc"n^ic"ix^n^-^i is a hyperbolic polynomial with all roots of the same sign. in the paper we prove several geometric properties of the set of fms(n+1) formulated in terms of its stratification (defined by the multiplicity vectors of the polynomials) and of the whitney property (the curvilinear distance to be equivalent to the euclidean one).
the moving curve ideal and the rees algebra. the rees algebra of an ideal in a commutative ring is the quotient of a polynomial ring by its ideal of defining relations. for a polynomial ring in two variables, this ideal was discovered independently by the geometric modeling community, where it is called the moving curve ideal. we review some properties of the rees algebra and discuss one result and one conjecture concerning the structure of the moving curve ideal and its relation to adjoint curves. some parts of the paper are purely expository.
on the complexity of real root isolation using continued fractions. we present algorithmic, complexity and implementation results concerning real root isolation of integer univariate polynomials using the continued fraction expansion of real algebraic numbers. one motivation is to explain the method's good performance in practice. we derive an expected complexity bound of o@?"b(d^6+d^4@t^2), where d is the polynomial degree and @t bounds the coefficient bit size, using a standard bound on the expected bit size of the integers in the continued fraction expansion, thus matching the current worst-case complexity bound for real root isolation by exact methods (sturm, descartes and bernstein subdivision). moreover, using a homothetic transformation we improve the expected complexity bound to o@?"b(d^3@t). we compute the multiplicities within the same complexity and extend the algorithm to non-square-free polynomials. finally, we present an open-source c++ implementation in the algebraic library synaps, and illustrate its completeness and efficiency as compared to some other available software. for this we use polynomials with coefficient bit size up to 8000 bits and degree up to 1000.
on different generalizations of episturmian words. in this paper we study some classes of infinite words generalizing episturmian words, and analyse the relations occurring among such classes. in each case, the reversal operator r is replaced by an arbitrary involutory antimorphism @q of the free monoid a^*. in particular, we define the class of @q-words with seed, whose ''standard'' elements (@q-standard words with seed) are constructed by an iterative @q-palindrome closure process, starting from a finite word u"0 called the seed. when the seed is empty, one obtains @q-words; episturmian words are exactly the r-words. one of the main theorems of the paper characterizes @q-words with seed as infinite words closed under @q and having at most one left special factor of each length n>=n (where n is some nonnegative integer depending on the word). when n=0 we call such words @q-episturmian. further results on the structure of @q-episturmian words are proved. in particular, some relationships between @q-words (with or without seed) and @q-episturmian words are shown.
smooth words on 2-letter alphabets having same parity. in this paper, we consider smooth words over 2-letter alphabets {a,b}, where a,b are integers having same parity, with 0
simple permutations: decidability and unavoidable substructures. we prove that it is decidable whether a finitely based permutation class contains infinitely many simple permutations, and establish an unavoidable substructure result for simple permutations: every sufficiently long simple permutation contains an alternation or oscillation of length k.
energy conservation in wireless sensor networks and connectivity of graphs. in wireless sensor networks (wsns), the energy source is usually a battery cell, which is impossible to recharge while wsns are working. therefore, one of the main issues in wireless sensor networks is how to prolong the network lifetime of wsns with certain energy sources as well as how to maintain coverage and connectivity. in this paper, we consider wireless sensor networks satisfying the case that each node either monitors one target or is just for connection. assume that the wireless sensor network has l targets, and that each is monitored by k sensor nodes. if k=2 and the graph g corresponding to the wireless sensor network is (l+max{1,l-4})-connected, or k>=3 and g is (l(k-1)+1)-connected, then we can find k (the maximum number) disjoint sets, each of which completely covers all the targets and remains connected to one of the central processing nodes. the disjoint sets are activated successively, and only the sensor nodes from the active set are responsible for monitoring the targets and connectivity; all other nodes are in a sleep mode. in addition, we also give the related algorithms to find the k disjoint sets.
graph automata. magmoids satisfying the 15 fundamental equations of graphs, namely graphoids, are introduced. automata on directed hypergraphs are defined by virtue of a relational graphoid. the closure properties of the so-obtained class are investigated, and a comparison is being made with the class of syntactically recognizable graph languages.
on the hardness of optimization in power-law graphs. our motivation for this work is the remarkable discovery that many large-scale real-world graphs ranging from internet and world wide web to social and biological networks appear to exhibit a power-law distribution: the number of nodes y"i of a given degree i is proportional to i^-^@b where @b>0 is a constant that depends on the application domain. there is practical evidence that combinatorial optimization in power-law graphs is easier than in general graphs, prompting the basic theoretical question: is combinatorial optimization in power-law graphs easy? does the answer depend on the power-law exponent @b? our main result is the proof that many classical np-hard graph-theoretic optimization problems remain np-hard on power-law graphs for certain values of @b. in particular, we show that some classical problems, such as clique and coloring, remain np-hard for all @b>=1. moreover, we show that all the problems that satisfy the so-called ''optimal substructure property'' remain np-hard for all @b>0. this includes classical problems such as minimum vertex cover, maximum independent set, and minimum dominating set. our proofs involve designing efficient algorithms for constructing graphs with prescribed degree sequences that are tractable with respect to various optimization problems.
the computational complexity of the parallel knock-out problem. we consider computational complexity questions related to parallel knock-out schemes for graphs. in such schemes, in each round, each remaining vertex of a given graph eliminates exactly one of its neighbours. we show that the problem of whether, for a given bipartite graph, such a scheme can be found that eliminates every vertex is np-complete. moreover, we show that, for all fixed positive integers k>=2, the problem of whether a given bipartite graph admits a scheme in which all vertices are eliminated in at most (exactly) k rounds is np-complete. for graphs with bounded tree-width, however, both of these problems are shown to be solvable in polynomial time. we also show that r-regular graphs with r>=1, factor-critical graphs and 1-tough graphs admit a scheme in which all vertices are eliminated in one round.
approximating a vehicle scheduling problem with time windows and handling times. in this paper, we study a problem of finding a vehicle scheduling to process a set of n jobs which are located in an asymmetric metric space. each job j has a positive handling time h(j), a time window [r(j),d(j)], and a benefit b(j). we consider the following two problems: max-vsp asks to find a schedule for a single vehicle to process a subset of jobs with the maximum benefit; and min-vsp asks to find a schedule to process all given jobs with the minimum number of vehicles. we first give an o(@rn^3^+^@c) time algorithm that delivers a 2-approximate solution to max-vsp, where @r=max"j","j"^"'(d(j)-r(j))/h(j^') and @c is the maximum number of jobs that can be processed by the vehicle after processing a job j and before visiting the processed job j again by deadline d(j). we then present an o(@rn^4^+^@c) time algorithm that delivers a 2h(n)-approximate solution to min-vsp, where h(n) is the nth harmonic number.
the cost of offline binary search tree algorithms and the complexity of the request sequence. in evaluating the performance of online algorithms for search trees, one wants to compare them to the best offline algorithm available. in this paper we lower bound the cost of an optimal offline binary search tree using the kolmogorov complexity of the request sequence. we obtain several applications for this result. first, any offline binary search tree algorithm can be at most a constant factor away from the entropy of the process producing the request sequence. second, for a fraction 1-1/2^m of request sequences of length m on n items the cost of any offline algorithm is @w(m(logn-1)). third, the expected cost of splay trees is within a constant factor of the expected cost of an optimal offline binary search tree algorithm in a subset of markov chains.
another proof of soittola's theorem. soittola's theorem characterizes r"+- or n-rational formal power series in one variable among the rational formal power series with nonnegative coefficients. we present here a new proof of the theorem based on soittola's and perrin's proofs together with some new ideas that allows us to separate algebraic and analytic arguments.
competitive graph searches. we exemplify an optimization criterion for divide-and-conquer algorithms with a technique called generic competitive graph search. the technique is then applied to solve two problems arising from biocomputing, so-called common connected components and cograph sandwich. the first problem can be defined as follows: given two graphs on the same set of n vertices, find the coarsest partition of the vertex set into subsets which induce connected subgraphs in both input graphs. the second problem is an instance of sandwich problems: given a partial subgraph g"1 of g"2, find a partial subgraph g of g"2 that is partial supergraph of g"1 (sandwich), and that is a cograph. for the former problem our generic algorithm not only achieves the current best known performance on arbitrary graphs and forests, but also improves by a logn factor when the input is made of planar graphs. however, our complexity for intervals graphs is slightly lower than a recent result. for the latter problem, we first study the relationship between the common connected components problem and the cograph sandwich problem, then, using our competitive graph search paradigm, we improve the computation of cograph sandwiches from o(n(n+m)) down to o(n+mlog^2n), where n is the number of vertices and m of total edges.
parallel-machine scheduling with time dependent processing times. in the literature, most of the parallel-machine scheduling problems, in which the processing time of a job is a linear function of its starting time, are proved to be np-hard. in this paper, we study a parallel-machine scheduling problem in which the processing time of a job is a linear function of its starting time. the objectives are to minimize the total completion of all jobs and the total load on all machines respectively. we consider two linear functions of job starting time and show that the problems are polynomially solvable.
a fast asymptotic approximation scheme for bin packing with rejection. ''bin packing with rejection'' is the following problem: given a list of items with associated sizes and rejection costs, find a packing into unit bins of a subset of the list such that the number of bins used plus the sum of rejection costs of unpacked items is minimized. we show that bin packing with rejection can be reduced to n multiple knapsack problems and, based on techniques for the multiple knapsack problem, we give a fast asymptotic polynomial time approximation scheme,''reject&pack'', with time complexity o(n^o^(^@e^^^-^^^2^)). this improves a recent approximation scheme given by epstein, which has time complexity o(n^o^(^(^@e^^^-^^^4^)^^^@e^^^^^^^-^^^^^^^1^)). we also show that reject&pack can be extended to variable-sized bin packing with rejection and give an asymptotic polynomial time approximation scheme.
approximating the online set multicover problems via randomized winnowing. in this paper, we consider the weighted online set k-multicover problem. in this problem, we have a universe v of elements, a family s of subsets of v with a positive real cost for every s@?s, and a ''coverage factor'' (positive integer) k. a subset {i"0,i"1,...}@?v of elements are presented online in an arbitrary order. when each element i"p is presented, we are also told the collection of all (at least k) sets s"i"""p@?s and their costs to which i"p belongs and we need to select additional sets from s"i"""p if necessary such that our collection of selected sets contains at leastk sets that contain the element i"p. the goal is to minimize the total cost of the selected sets. in this paper, we describe a new randomized algorithm for the online multicover problem based on a randomized version of the winnowing approach of [n. littlestone, learning quickly when irrelevant attributes abound: a new linear-threshold algorithm, machine learning 2 (1988) 285-318]. this algorithm generalizes and improves some earlier results in [n. alon, b. awerbuch, y. azar, n. buchbinder, j. naor, a general approach to online network optimization problems, in: proceedings of the 15th acm-siam symposium on discrete algorithms, 2004, pp. 570-579; n. alon, b. awerbuch, y. azar, n. buchbinder, j. naor, the online set cover problem, in: proceedings of the 35th annual acm symposium on the theory of computing, 2003, pp. 100-105]. we also discuss lower bounds on competitive ratios for deterministic algorithms for general k based on the approaches in [n. alon, b. awerbuch, y. azar, n. buchbinder, j. naor, the online set cover problem, in: proceedings of the 35th annual acm symposium on the theory of computing, 2003, pp. 100-105].
move-optimal gossiping among mobile agents. mobile-agent-based distributed systems are attracting widespread attention because of their adaptability and flexibility; mobile agents traverse the system and carry out a task at each node. in mobile-agent-based systems, gossip is a fundamental task in cooperation among mobile agents. it requires one to accomplish all-to-all information exchange over all agents so that each agent can obtain the information each agent initially has. while rendezvous algorithms, which require that all agents rendezvous on a node at the same time, can achieve this requirement, it takes excessive cost for our objective. in this paper, we introduce the mobile agent gossip problem, in which each agent must obtain the information all other agents have. each agent p"i can obtain the information of p"j(
decidability and syntactic control of interference. we investigate the decidability of observational equivalence and approximation in reynolds' ''syntactic control of interference'' (sci), a prototypical functional-imperative language in which covert interference between functions and their arguments is prevented by the use of an affine typing discipline. by associating denotations of terms in a fully abstract ''relational'' model of finitary basic sci (due to reddy) with multitape finite state automata, we show that observational approximation is not decidable (even at first order), but that observational equivalence is decidable for all terms. we then consider the same problems for basic sci extended with non-local control in the form of backwards jumps. we show that both observational approximation and observational equivalence are decidable in this ''observably sequential'' version of the language by describing a fully abstract games model in which strategies are regular languages.
constructibility and decidability versus domain independence and absoluteness. we develop a unified framework for dealing with constructibility and absoluteness in set theory, decidability of relations in effective structures (like the natural numbers) and domain independence of queries in database theory. our framework and results suggest that domain-independence and absoluteness might be the key notions in a general theory of constructibility, predicativity and computability.
minimality considerations for ordinal computers modeling constructibility. we describe a simple model of ordinal computation which can compute truth in the constructible universe. we try to use well-structured programs and direct limits of states at limit times whenever possible. this may make it easier to define a model of ordinal computation within other systems of hypercomputation, especially systems inspired by physical models. we write a program to compute truth in the constructible universe on an ordinal register machine. we prove that the number of registers in a well-structured universal ordinal register machine is always >=4, greater than the minimum number of registers in a well-structured universal finite-time natural number-storing register machine, but that it can always be kept finite. we conjecture that this number is four. we compare the efficiency of our program which computes the constructible sets to that of a similar program for an ordinal turing machine.
dynamics of a generic brownian motion: recursive aspects. we study the local fluctuations of brownian motions which are represented by infinite binary strings which are random in the sense of kolmogorov-chaitin. we show how the dynamical properties of such a brownian motion at a point depend on its recursive properties.
itemset frequency satisfiability: complexity and axiomatization. computing frequent itemsets is one of the most prominent problems in data mining. we study the following related problem, called freqsat, in depth: given some itemset-interval pairs, does there exist a database such that for every pair the frequency of the itemset falls into the interval? this problem is shown to be np-complete. the problem is then further extended to include arbitrary boolean expressions over items and conditional frequency expressions in the form of association rules. we also show that, unless p equals np, the related function problem-find the best interval for an itemset under some frequency constraints-cannot be approximated efficiently. furthermore, it is shown that freqsat is recursively axiomatizable, but that there cannot exist an axiomatization of finite arity.
interval-valued computations and their connection with pspace. at the conference cie 2005, the first author introduced a new model for analog computations, namely interval-valued computations. in this model, computations work on the so-called interval-valued bytes, which are special subsets of the interval [0,1) rather than a finite sequence of bits. the question was posed there, which complexity is needed to solve pspace-complete problems in this paradigm. in this paper, after formalizing the computational model, we answer this question. we show that the validity problem of quantified propositional formulae is decidable by a linear interval-valued computation. as a consequence, all polynomial space problems are decidable by a polynomial interval-valued computation. furthermore, it is proven that pspace coincides with the class of languages which are decidable by a restricted polynomial interval-valued computation.
physical constraints on hypercomputation. many attempts to transcend the fundamental limitations to computability implied by the halting problem for turing machines depend on the use of forms of hypercomputation that draw on notions of infinite or continuous, as opposed to bounded or discrete, computation. thus, such schemes may include the deployment of actualised rather than potential infinities of physical resources, or of physical representations of real numbers to arbitrary precision. here, we argue that such bases for hypercomputation are not materially realisable and so cannot constitute new forms of effective calculability.
bounding lemmata for non-deterministic halting times of transfinite turing machines. we use the methods of descriptive set theory and generalized recursion theory to prove various bounding lemmata that contribute to a body of results on halting times of non-deterministic infinite time turing machine computations. in particular we observe that there is a uniform bounding lemma which states that if any total algorithm halts before the first ordinal admissible in the input x, then there is a recursive ordinal @c by which the algorithm halts on all inputs.
cryptographic logical relations. using contextual equivalence (a.k.a. observational equivalence) to specify security properties is an important idea in the field of formal verification of cryptographic protocols. while contextual equivalence is difficult to prove directly, one is usually able to deduce it using the so-called logical relations in typed @l-calculi. we apply this technique to the cryptographic metalanguage-an extension of moggi's computational @l-calculus, where we use stark's model for name creation to explore the difficult aspect of dynamic key generation. the categorical construction of logical relations for monadic types (by goubault-larrecq et al.) then allows us to derive logical relations over the category set^i. although set^i is a perfectly adequate model of dynamic key generation, it lacks in some aspects when we study relations between programs in the metalanguage. this leads us to an interesting exploration of what should be the proper category to consider. we show that, to define logical relations in the cryptographic metalanguage, a better choice of category is set^i^^^-> that we proposed in [y. zhang, d. nowak, logical relations for dynamic name creation, in: proceedings of the 17th international workshop of computer science logic and the 8th kurt godel colloqium, csl & kgl, in: lecture notes in computer science, vol. 2803, springer-verlag, 2003, pp. 575-588]. however, this category is still lacking in some subtler aspects and we propose a refined category set^p^i^^^-> to fix the flaws, but our final choice is set^i^x^i, which is equivalent to set^p^i^^^->. we define the contextual equivalence based on set^i^x^i and show that the cryptographic logical relation derived over set^i^x^i is sound and can be used to verify protocols in practice.
a graphical criterion of planarity for rna secondary structures with pseudoknots in rivas-eddy class. an rna secondary structure is considered to be planar if its arc graph can be embedded into a plane without edge crossing. in this paper, a graphical criterion of planarity is presented based on graphical composition for rna secondary structures with pseudoknots in rivas-eddy class. effective planar testing algorithms are introduced based on our graphical criterion.
multi-break rearrangements and chromosomal evolution. most genome rearrangements (e.g., reversals and translocations) can be represented as 2-breaks that break a genome at 2 points and glue the resulting fragments in a new order. multi-break rearrangements break a genome into multiple fragments and further glue them together in a new order. while multi-break rearrangements were studied in depth for k=2 breaks, the k-break distance problem for arbitrary k remains unsolved. we prove a duality theorem for multi-break distance problem and give a polynomial algorithm for computing this distance.
compositional semantics and behavioral equivalences for p systems. the aim of the paper is to give a compositional semantics in the style of the structural operational semantics (sos) and to study behavioral equivalence notions for p systems. firstly, we consider p systems with maximal parallelism and without priorities. we define a process algebra, called p algebra, whose terms model membranes, we equip the algebra with a labeled transition system (lts) obtained through sos transition rules, and we study how some equivalence notions defined over the lts model apply in our case. then, we consider p systems with priorities and extend the introduced framework to deal with them. we prove that our compositional semantics reflects correctly maximal parallelism and priorities.
property matching and weighted matching. in many pattern matching applications the text has some properties attached to its various parts. pattern matching with properties (property matching, for short), involves a string matching between the pattern and the text, and the requirement that the text part satisfies some property. some immediate examples come from molecular biology where it has long been a practice to consider special areas in the genome by their structures. it is straightforward to do sequential matching in a text with properties. however, indexing in a text with properties becomes difficult if we desire the time to be output dependent. we present an algorithm for indexing a text with properties in o(nlog|@s|+nloglogn) time for preprocessing and o(|p|log|@s|+tocc"@p) per query, where n is the length of the text, p is the sought pattern, @s is the alphabet, and tocc"@p is the number of occurrences of the pattern that satisfy some property @p. as a practical use of property matching we show how to solve weighted matching problems using techniques from property matching. weighted sequences have recently been introduced as a tool to handle a set of sequences that are not identical but have many local similarities. the weighted sequence is a ''statistical image'' of this set, where we are given the probability of every symbol's occurrence at every text location. weighted matching problems are pattern matching problems where the given text is weighted. we present a reduction from weighted matching to property matching that allows off-the-shelf solutions to numerous weighted matching problems including indexing, swapped matching, parameterized matching, approximate matching, and many more. assuming that one seeks the occurrence of pattern p with probability @e in weighted text t of length n, we reduce the problem to a property matching problem of pattern p in text t^' of length o(n(1@e)^2log1@e).
computation of distances for regular and context-free probabilistic languages. several mathematical distances between probabilistic languages have been investigated in the literature, motivated by applications in language modeling, computational biology, syntactic pattern matching and machine learning. in most cases, only pairs of probabilistic regular languages were considered. in this paper we extend the previous results to pairs of languages generated by a probabilistic context-free grammar and a probabilistic finite automaton.
counting suffix arrays and strings. suffix arrays are used in various applications and research areas like data compression or computational biology. in this work, our goal is to characterise the combinatorial properties of suffix arrays and their enumeration. for a fixed alphabet size and string length, we divide the set of all strings into equivalence classes of strings that share the same suffix array. for each such equivalence class, we count the number of strings contained in it. we also give exact formulas for computing the number of equivalence classes. our methods yield a lower bound for the compressibility of suffix arrays and build the foundation for the efficient generation of appropriate test data sets for suffix array based algorithms. we also show that summing up the elements of all equivalence classes forms a particular instance for some summation identities of eulerian numbers.
solving np-complete problems in the tile assembly model. formalized study of self-assembly has led to the definition of the tile assembly model, a highly distributed parallel model of computation that may be implemented using molecules or a large computer network such as the internet. previously, i defined deterministic and nondeterministic computation in the tile assembly model and showed how to add, multiply and factor. here, i extend the notion of computation to include deciding subsets of the natural numbers, and present a system that decides subsetsum, a well-known np-complete problem. the computation is nondeterministic and each parallel assembly executes in time linear in the input. the system requires only a constant number of different tile types: 49. i describe mechanisms for finding the successful solutions among the many parallel assemblies and explore bounds on the probability of such a nondeterministic system succeeding and prove that probability can be made arbitrarily close to one.
detection of subtle variations as consensus motifs. we address the problem of detecting consensus motifs, that occur with subtle variations, across multiple sequences. these are usually functional domains in dna sequences such as transcriptional binding factors or other regulatory sites. the problem in its generality has been considered difficult and various benchmark data serve as the litmus test for different computational methods. we present a method centered around unsupervised combinatorial pattern discovery. the parameters are chosen using a careful statistical analysis of consensus motifs. this method works well on the benchmark data and is general enough to be extended to a scenario where the variation in the consensus motif includes indels (along with mutations). we also present some results on detection of transcription binding factors in human dna sequences.
computing similarity of run-length encoded strings with affine gap penalty. the problem of computing the similarity of two run-length encoded strings has been studied for various scoring metrics. many algorithms have been developed for the longest common subsequence metric and some algorithms for the levenshtein distance metric and the weighted edit distance metric. in this paper we consider similarity based on the affine gap penalty metric which is a more general and rather complicated scoring metric than the weighted edit distance. to compute the similarity in this model efficiently, we convert the problem into a path problem on a directed acyclic graph and use some properties of maximum paths in this graph. we present an o(nm^'+n^'m) time algorithm for computing the similarity of two run-length encoded strings in the affine gap penalty model, where n and m are the lengths of given two strings whose run-length encoded lengths are n^' and m^', respectively.
sequential vs. parallel complexity in simple gene assembly. we investigate some differences between the general intramolecular model for gene assembly and its restricted simple model. although both models satisfactorily sort all current experimental data, we show that the general model offers assembly strategies for a given string that vary in both assembly length and the operations used, while the simple model will always use the same number of each type of operation to sort a gene. when simple operations are applied in parallel this is given a new twist. we prove that for any n>=1, there exists a string having maximally parallel assemblies of any length between n and 2n.
reversible computing and cellular automata - a survey. reversible computing is a paradigm where computing models are defined so that they reflect physical reversibility, one of the fundamental microscopic physical property of nature. in this survey/tutorial paper, we discuss how computation can be carried out in a reversible system, how a universal reversible computer can be constructed by reversible logic elements, and how such logic elements are related to reversible physical phenomena. we shall see that, in reversible systems, computation can often be carried out in a very different manner from conventional (i.e., irreversible) computing systems, and even very simple reversible systems or logic elements have computation- or logical-universality. we discuss these problems based on reversible logic elements/circuits, reversible turing machines, reversible cellular automata, and some other related models of reversible computing.
fast profile matching algorithms - a survey. position-specific scoring matrices are a popular choice for modelling signals or motifs in biological sequences, both in dna and protein contexts. a lot of effort has been dedicated to the definition of suitable scores and thresholds for increasing the specificity of the model and the sensitivity of the search. it is quite surprising that, until very recently, little attention has been paid to the actual process of finding the matches of the matrices in a set of sequences, once the score and the threshold have been fixed. in fact, most profile matching tools still rely on a simple sliding window approach to scan the input sequences. this can be a very time expensive routine when searching for hits of a large set of scoring matrices in a sequence database. in this paper we will give a survey of proposed approaches to speed up profile matching based on statistical significance, multipattern matching, filtering, indexing data structures, matrix partitioning, fast fourier transform and data compression. these approaches improve the expected searching time of profile matching, thus leading to implementation of faster tools in practice.
algorithms for computing variants of the longest common subsequence problem. the longest common subsequence (lcs) problem is one of the classical and well-studied problems in computer science. the computation of the lcs is a frequent task in dna sequence analysis, and has applications to genetics and molecular biology. in this paper we introduce new variants of lcs problem and present efficient algorithms to solve them. in particular we introduce the notion of gap constraints in the lcs problems. for the lcs problem with fixed gap, we first present a naive algorithm runs in o(n^2+r(k+1)^2) time, where r is the total number of ordered pairs of positions at which the two strings match and k is the fixed gap constraint. we then improve the running time to o(n^2+rk+rloglogn) using some novel techniques. furthermore, we present an algorithm that is independent of k and runs in o(n^2+rloglogn) time. using these techniques, we also present a new o(n^2) algorithm to solve the original lcs problem. additionally, we modify our algorithms to handle elastic and rigid gaps. we also apply the notion of rigidness to the original lcs problem and modify the traditional dynamic programming solution to handle the rigidness presenting a o(n^2) algorithm to solve the problem. finally, we also improve the solution to rigid fixed gap lcs to o(n^2). notably, in all of the above cases, we assume that the two given strings are of equal length i.e. n. but our results can be easily extended to handle two strings of different length.
nondeterministic polynomial time factoring in the tile assembly model. formalized study of self-assembly has led to the definition of the tile assembly model, previously i presented ways to compute arithmetic functions, such as addition and multiplication, in the tile assembly model: a highly distributed parallel model of computation that may be implemented using molecules or a large computer network such as the internet. here, i present tile assembly model systems that factor numbers nondeterministically using @q(1) distinct components. the computation takes advantage of nondeterminism, but theoretically, each of the nondeterministic paths is executed in parallel, yielding the solution in time linear in the size of the input, with high probability. i describe mechanisms for finding the successful solutions among the many parallel executions and explore bounds on the probability of such a nondeterministic system succeeding and prove that the probability can be made arbitrarily close to 1.
modeling spiking neural networks. a notation for the functional specification of a wide range of neural networks consisting of temporal or non-temporal neurons, is proposed. the notation is primarily a mathematical framework, but it can also be illustrated graphically and can be extended into a language in order to be automated. its basic building blocks are processing entities, finer grained than neurons, connected by instant links, and as such they form sets of interacting entities resulting in bigger and more sophisticated structures. the hierarchical nature of the notation supports both top-down and bottom-up specification approaches. the use of the notation is evaluated by a detailed example of an integrated tangible agent consisting of sensors, a computational part, and actuators. a process from specification to both software and hardware implementation is proposed.
on the entropy of a hidden markov process. we study the entropy rate of a hidden markov process (hmp) defined by observing the output of a binary symmetric channel whose input is a first-order binary markov process. despite the simplicity of the models involved, the characterization of this entropy is a long standing open problem. by presenting the probability of a sequence under the model as a product of random matrices, one can see that the entropy rate sought is equal to a top lyapunov exponent of the product. this offers an explanation for the elusiveness of explicit expressions for the hmp entropy rate, as lyapunov exponents are notoriously difficult to compute. consequently, we focus on asymptotic estimates, and apply the same product of random matrices to derive an explicit expression for a taylor approximation of the entropy rate with respect to the parameter of the binary symmetric channel. the accuracy of the approximation is validated against empirical simulation results. we also extend our results to higher-order markov processes and to renyi entropies of any order.
approximating the 2-interval pattern problem. we address the issue of approximating the 2-interval pattern problem over its various models and restrictions. this problem, motivated by rna secondary structure prediction, asks to find a maximum cardinality subset of a 2-interval set with respect to some prespecified geometric constraints. we present several constant factor approximation algorithms whose performance guarantee depends on the different possible restrictions imposed on the input 2-interval set. in addition, we show that our results extend to the weighted variant of the problem.
partitioned probe comparability graphs. given a class of graphs g, a graph g is a probe graph of g if its vertices can be partitioned into a set of probes and an independent set of nonprobes such that g can be embedded into a graph of g by adding edges between certain nonprobes. if the partition of the vertices is part of the input, we call g a partitioned probe graph of g. in this paper we show that there exists a polynomial-time algorithm for the recognition of partitioned probe graphs of comparability graphs. this immediately leads to a polynomial-time algorithm for the recognition of partitioned probe graphs of cocomparability graphs. we then show that a partitioned graph g is a partitioned probe permutation graph if and only if g is at the same time a partitioned probe graph of comparability and cocomparability graphs.
on approximate optimal dual power assignment for biconnectivity and edge-biconnectivity. topology control is one of the major approaches to achieve energy efficiency as well as fault tolerance in wireless networks. in this paper, we study the dual power assignment problem for 2-edge connectivity and 2-vertex connectivity in the symmetric graphical model. the problem has arisen from the following practical origin. in a wireless ad hoc network where each node can switch its transmission power between high-level and low-level, how can we establish a fault-tolerant connected network topology in the most energy-efficient way? specifically, the objective is to minimize the number of nodes assigned with high power and yet achieve 2-edge connectivity or 2-vertex connectivity. note that to achieve a minimum number of high-power nodes is harder than an optimization problem in the same model whose objective is to minimize the total power cost. we first address these two optimization problems (2-edge connectivity and 2-vertex connectivity version) under the general graph model. due to the np-hardness, we propose an approximation algorithm, called prioritized edge selection algorithm, which achieves a 4-ratio approximation for 2-edge connectivity. after that, we modify the algorithm to solve the problem for 2-vertex connectivity and also achieve the same approximation ratio. we also show that the 4-ratio is tight for our algorithms in both cases.
on a quasi-ordering on boolean functions. it was proved few years ago that classes of boolean functions definable by means of functional equations [o. ekin, s. foldes, p.l. hammer, l. hellerstein, equational characterizations of boolean functions classes, discrete mathematics 211 (2000) 27-51], or equivalently, by means of relational constraints [n. pippenger. galois theory for minors of finite functions, discrete mathematics 254 (2002) 405-419], coincide with initial segments of the quasi-ordered set (@w,@?) made of the set @w of boolean functions, suitably quasi-ordered. furthermore, the classes defined by finitely many equations [o. ekin, s. foldes, p.l. hammer, l. hellerstein, equational characterizations of boolean functions classes, discrete mathematics 211 (2000) 27-51] coincide with the initial segments of (@w,@?) which are definable by finitely many obstructions. the resulting ordered set (@w@?,@?) embeds into ([@w]^
weak-vertex-pancyclicity of (n, k)-star graphs. the (n,k)-star graph (s"n","k for short) is an attractive alternative to the hypercube and also a generalized version of the n-star. it is isomorphic to the n-star (n-complete) graph if k=n-1 (k=1). jwo et al. have already demonstrated in 1991 that an n-star contains a cycle of every even length from 6 to n!. this work shows that every vertex in an s"n","k lies on a cycle of length l for every 3@?l@?n!/(n-k)! when 1@?k@?n-4 and n>=6. additionally, for n-3@?k@?n-2, each vertex in an s"n","k is contained in a cycle of length ranged from 6 to n!/(n-k)!. moreover, each constructed cycle of an available length in an s"n","k can contain a desired 1-edge.
tight bounds for the multiplicative complexity of symmetric functions. the multiplicative complexity of a boolean function f is defined as the minimum number of binary conjunction (and) gates required to construct a circuit representing f, when only exclusive-or, conjunction and negation gates may be used. this article explores in detail the multiplicative complexity of symmetric boolean functions. new techniques that allow such exploration are introduced. they are powerful enough to give exact multiplicative complexities for several classes of symmetric functions. in particular, the multiplicative complexity of computing the hamming weight of n bits is shown to be exactly n-h^n(n), where h^n(n) is the hamming weight of the binary representation of n. we also show a close relationship between the complexities of basic symmetric functions and the fractal known as sierpinski's gasket.
covering by squares. in this paper we introduce the ''do not touch'' condition for squares in the discrete plane. we say that two squares ''do not touch'' if they do not share any vertex or any segment of an edge. using this condition we define a covering of the discrete plane, the covering can be strong or weak, regular or non-regular. for simplicity, in this article, we will restrict our attention to regular coverings, i.e., only a size is allowed for the squares and all the squares have the same number of adjacent squares. we establish minimal conditions for the existence of a weak or strong regular covering of the discrete plane, and we give a bound for the number of adjacent squares with respect to the size of the squares in the regular covering.
a better differential approximation ratio for symmetric tsp. in this paper, we study the approximability properties of symmetric tsp under an approximation measure called the differential ratio. more precisely, we improve up to 3/4-@e (for any @e>0) the best differential ratio of 2/3 known so far, given in hassin and khuller, [r. hassin, s. khuller, z-approximations, j. algorithms, 41 (2) (2001) 429-442].
inverse min-max spanning tree problem under the weighted sum-type hamming distance. the inverse optimization problem is to modify the weight (or cost, length, capacity and so on) such that a given feasible solution becomes an optimal solution. in this paper, we consider the inverse min-max spanning tree problem under the weighted sum-type hamming distance. for the model considered, we present its combinatorial algorithm that runs in strongly polynomial times.
world-set decompositions: expressiveness and efficient algorithms. uncertain information is commonplace in real-world data management scenarios. the ability to represent large sets of possible instances (worlds) while supporting efficient storage and processing is an important challenge in this context. the recent formalism of world-set decompositions (wsds) provides a space-efficient representation for uncertain data that also supports scalable processing. wsds are complete for finite world-sets in that they can represent any finite set of possible worlds. for possibly infinite world-sets, we show that a natural generalization of wsds precisely captures the expressive power of c-tables. we then show that several important problems are efficiently solvable on wsds while they are np-hard on c-tables. finally, we give a polynomial-time algorithm for factorizing wsds, i.e. an efficient algorithm for minimizing such representations.
competitive analysis of most-request-first for scheduling broadcasts with start-up delay. in this paper, we give a tight and complete mathematical analysis of the most-request-first algorithm for scheduling on-demand broadcasts with start-up delay. the algorithm is natural and simple, yet its practical performance is surprisingly good. we derive tight upper and lower bounds on its competitive ratio under different system configurations. our results reveal an interesting relationship between the start-up delay and the competitiveness of the algorithm.
combinatorial gray codes for classes of pattern avoiding permutations. the past decade has seen a flurry of research into pattern avoiding permutations but little of it is concerned with their exhaustive generation. many applications call for exhaustive generation of permutations subject to various constraints or imposing a particular generating order. in this paper we present generating algorithms and combinatorial gray codes for several families of pattern avoiding permutations. among the families under consideration are those counted by catalan, large schroder, pell, even-index fibonacci numbers and the central binomial coefficients. we thus provide gray codes for the set of all permutations of {1,...,n} avoiding the pattern @t for all @t@?s"3 and the gray codes we obtain have distances 4 or 5.
non-uniform circle formation algorithm for oblivious mobile robots with convergence toward uniformity. this paper presents a distributed algorithm whereby a group of mobile robots self-organize and position themselves into forming a circle in a loosely synchronized environment. in spite of its apparent simplicity, the difficulty of the problem comes from the weak assumptions made on the system. in particular, robots are anonymous, oblivious (i.e., stateless), unable to communicate directly, and disoriented in the sense that they share no knowledge of a common coordinate system. furthermore, robots' activations are not synchronized. more specifically, the proposed algorithm ensures that robots deterministically form a non-uniform circle in a finite number of steps and converges to a situation in which all robots are located evenly on the boundary of the circle.
modelling the navigation potential of a web page. navigating the web involves pruning (or discounting) some of the outgoing links and following one of the others. more pruning is likely to happen for deeper navigation. under this model of navigation, we call the number of nodes that are available after pruning, for browsing within a session, the potential gain of the starting web page. we first consider the case when the discounting factor is geometric. we show that the distribution of the effective number of links that the user can follow at each navigation step after pruning, i.e. the number of nodes added to the potential gain at that step, is given by the erf function, which is related to the probability density function for the normal distribution. we derive an approximation to the potential gain of a web page and show numerically that it is very accurate; we also obtain lower and upper bounds. we then consider a harmonic discounting factor and show that, in this case, the potential gain at each step is closely related to the probability density function for the poisson distribution. the potential gain has been applied to web navigation where, given no other information, it helps the user to choose a good starting point for initiating a ''surfing'' session. another application is in social network analysis, where the potential gain could provide a novel measure of centrality.
probabilistic analysis for scheduling with conflicts. in this paper, we consider scheduling jobs that may be competing for mutually exclusive resources. we model the conflicts between jobs with a conflict graph, so that all concurrently running jobs must form an independent set in the graph. our goal is to bound the maximum response time of any job in the system. we adopt a discrete model of time and assume that each job requires one time unit to be completed once it is started. it has been previously shown [s. irani, v. leung, scheduling with conflicts, and applications to traffic signal control, in: proceedings of the seventh annual acm-siam symposium on discrete algorithms, siam, 1996] that the best competitive ratio achievable by any online algorithm is @w(n), where n is the number of nodes in the graph. as a result, we study scheduling with conflicts under probabilistic assumptions about the input. each node i has a value p"i such that a job arrives at node i in any given time unit with probability p"i. arrivals at different nodes and during different time periods are independent. under reasonable assumptions on the value for the p"i's, we are able to obtain a bounded competitive ratio for an arbitrary conflict graph. in addition, if the conflict graph is a perfect graph, we give an algorithm whose competitive ratio converges to 1.
jug measuring: algorithms and complexity. we study the hardness of the optimal jug measuring problem. by proving tight lower and upper bounds on the minimum number of measuring steps required, we reduce an inapproximable np-hard problem (i.e., the shortest gcd multiplier problem [g. havas, j.-p. seifert, the complexity of the extended gcd problem, in: lncs, vol. 1672, springer, 1999]) to it. it follows that the optimal jug measuring problem is np-hard and so is the problem of approximating the minimum number of measuring steps within a constant factor. along the way, we give a polynomial-time approximation algorithm with an exponential error based on the well-known lll basis reduction algorithm.
an improved lower bound for approximating minimum gcd multiplier in l norm (gcdm). in this paper, we study the inapproximability of the following np-complete number theoretic optimization problems introduced by rossner and seifert [c. rossner, j.p. seifert, the complexity of approximate optima for greatest common divisor computations, in: proceedings of the 2nd international algorithmic number theory symposium, ants-ii, 1996, pp. 307-322]: given n numbers a"1,...,a"n@?z, find an @?"~-minimum gcd multiplier for a"1,...,a"n, i.e., a vector x@?z^n with minimum max"1"@?"i"@?"n|x"i| satisfying @?"i"="1^nx"ia"i=gcd(a"1,...,a"n). we show that assuming p0 where n is the dimension of the given vector. this improves on the best previous result. the best result so far gave 2^(^l^o^g^n^)^^^1^^^-^^^@e factor hardness by rossner and seifert [c. rossner, j.p. seifert, the complexity of approximate optima for greatest common divisor computations, in: proceedings of the 2nd international algorithmic number theory symposium, ants-ii, 1996, pp. 307-322], where @e>0 is an arbitrarily small constant.
the complexity of deciding reachability properties of distributed negotiation schemes. distributed negotiation schemes offer one approach to agreeing an allocation of resources among a set of individual agents. such schemes attempt to agree a distribution via a sequence of locally agreed 'deals'-reallocations of resources among the agents-ending when the result satisfies some accepted criteria. our aim in this article is to demonstrate that some natural decision questions arising in such settings can be computationally significantly harder than questions related to optimal clearing strategies in combinatorial auctions. in particular we prove that the problem of deciding whether it is possible to progress from a given initial allocation to some desired final allocation via a sequence of ''rational'' steps is pspace-complete.
measuring teachability using variants of the teaching dimension. in a typical algorithmic learning model, a learner has to identify a target object from partial information. conversely, in a teaching model a teacher has to give information that allows the learners to identify a target object. we devise two variants of the classical teaching model for boolean concept classes, based on the teaching dimension, and describe them by teaching-dimension-like combinatorial parameters. in the first model, the learners choose consistent hypotheses with least complexity. we show that 1-decision lists are the harder to teach the longer they are and that 2-term dnfs are the harder to teach the more terms they have. this contrasts with the teachability results for these classes in the teaching-dimension model. in our second model, the learners choose consistent hypotheses based on the assumption that the teacher is optimal. we show that monomials can be taught with a linear number of examples, whereas some 1-decision lists need exponentially many.
developments from enquiries into the learnability of the pattern languages from positive data. the pattern languages are languages that are generated from patterns, and were first proposed by angluin as a non-trivial class that is inferable from positive data [d. angluin, finding patterns common to a set of strings, journal of computer and system sciences 21 (1980) 46-62; d. angluin, inductive inference of formal languages from positive data, information and control 45 (1980) 117-135]. in this paper we chronologize some results that developed from the investigations on the inferability of the pattern languages from positive data.
reflective inductive inference of recursive functions. in this paper, we investigate reflective inductive inference of recursive functions. a reflective iim is a learning machine that is additionally able to assess its own competence. first, we formalize reflective learning from arbitrary, and from canonical, example sequences. here, we arrive at four different types of reflection: reflection in the limit, optimistic, pessimistic and exact reflection. then, we compare the learning power of reflective iims with each other as well as with the one of standard iims for learning in the limit, for consistent learning of three different types, and for finite learning.
some classes of term rewriting systems inferable from positive data. in this paper, we study the inferability of term rewriting systems (trss, for short) from positive examples alone. two classes of trss inferable from positive data are presented, namely, simple flat trss and linear-bounded trss. these classes of trss are rich enough to include many divide-and-conquer programs like addition, doubling, logarithm, tree-count, list-count, split, append, reverse, etc. the classes of simple flat trss and linear-bounded trss are incomparable, i.e., there are functions that can be computed by simple flat trss but not by linear-bounded trss and vice versa.
learning and extending sublanguages. a number of natural models for learning in the limit are introduced to deal with the situation when a learner is required to provide a grammar covering the input even if only a part of the target language is available. examples of language families are exhibited that are learnable in one model and not learnable in another one. some characterizations for learnability of algorithmically enumerable families of languages for the models in question are obtained. since learnability of any part of the target language does not imply monotonicity of the learning process, we consider our models also under the additional monotonicity constraint.
quantum inductive inference by finite automata. freivalds and smith [r. freivalds, c.h. smith memory limited inductive inference machines, springer lecture notes in computer science 621 (1992) 19-29] proved that probabilistic limited memory inductive inference machines can learn with probability 1 certain classes of total recursive functions, which cannot be learned by deterministic limited memory inductive inference machines. we introduce quantum limited memory inductive inference machines as quantum finite automata acting as inductive inference machines. these machines, we show, can learn classes of total recursive functions not learnable by any deterministic, nor even by probabilistic, limited memory inductive inference machines.
learning indexed families of recursive languages from positive data: a survey. in the past 40 years, research on inductive inference has developed along different lines, e.g., in the formalizations used, and in the classes of target concepts considered. one common root of many of these formalizations is gold's model of identification in the limit. this model has been studied for learning recursive functions, recursively enumerable languages, and recursive languages, reflecting different aspects of machine learning, artificial intelligence, complexity theory, and recursion theory. one line of research focuses on indexed families of recursive languages - classes of recursive languages described in a representation scheme for which the question of membership for any string in any of the given languages is effectively decidable with a uniform procedure. such language classes are of interest because of their naturalness. the survey at hand picks out important studies on learning indexed families (including basic as well as recent research), summarizes and illustrates the corresponding results, and points out links to related fields such as grammatical inference, machine learning, and artificial intelligence in general.
learning recursive functions: a survey. studying the learnability of classes of recursive functions has attracted considerable interest for at least four decades. starting with gold's (1967) model of learning in the limit, many variations, modifications and extensions have been proposed. these models differ in some of the following: the mode of convergence, the requirements intermediate hypotheses have to fulfill, the set of allowed learning strategies, the source of information available to the learner during the learning process, the set of admissible hypothesis spaces, and the learning goals. a considerable amount of work done in this field has been devoted to the characterization of function classes that can be learned in a given model, the influence of natural, intuitive postulates on the resulting learning power, the incorporation of randomness into the learning process, the complexity of learning, among others. on the occasion of rolf wiehagen's 60th birthday, the last four decades of research in that area are surveyed, with a special focus on rolf wiehagen's work, which has made him one of the most influential scientists in the theory of learning recursive functions.
discontinuities in pattern inference. this paper deals with the inferrability of classes of e-pattern languages-also referred to as extended or erasing pattern languages-from positive data in gold's model of identification in the limit. the first main part of the paper shows that the recently presented negative result on terminal-free e-pattern languages over binary alphabets does not hold for other alphabet sizes, so that the full class of these languages is inferrable from positive data if and only if the corresponding terminal alphabet does not consist of exactly two distinct letters. the second main part yields the insight that the positive result on terminal-free e-pattern languages over alphabets with three or four letters cannot be extended to the class of general e-pattern languages. with regard to larger alphabets, the extensibility remains open. the proof methods developed for these main results do not directly discuss the (non-)existence of appropriate learning strategies, but they deal with structural properties of classes of e-pattern languages, and, in particular, with the problem of finding telltales for these languages. it is shown that the inferrability of classes of e-pattern languages is closely connected to some problems on the ambiguity of morphisms so that the technical contributions of the paper largely consist of combinatorial insights into morphisms in word monoids.
nonstochastic bandits: countable decision set, unbounded costs and reactive environments. the nonstochastic multi-armed bandit problem, first studied by auer, cesa-bianchi, freund, and schapire in 1995, is a game of repeatedly choosing one decision from a set of decisions (''experts''), under partial observation: in each round t, only the cost of the decision played is observable. a regret minimization algorithm plays this game while achieving sublinear regret relative to each decision. it is known that an adversary controlling the costs of the decisions can force the player a regret growing as t^1^2 in the time t. in this work, we propose the first algorithm for a countably infinite set of decisions, that achieves a regret upper bounded by o(t^1^2^+^@e), i.e. arbitrarily close to optimal order. to this aim, we build on the ''follow the perturbed leader'' principle, which dates back to work by hannan in 1957. our results hold against an adaptive adversary, for both the expected and high probability regret of the learner w.r.t. each decision. in the second part of the paper, we consider reactive problem settings, that is, situations where the learner's decisions impact on the future behaviour of the adversary, and a strong strategy can draw benefit from well chosen past actions. we present a variant of our regret minimization algorithm which has still regret of order at most t^1^2^+^@e relative to such strong strategies, and even sublinear regret not exceeding o(t^4^5) w.r.t. the hypothetical (without external interference) performance of a strong strategy. we show how to combine the regret minimizer with a universal class of experts, given by the countable set of programs on some fixed universal turing machine. this defines a universal learner with sublinear regret relative to any computable strategy.
absolute versus probabilistic classification in a logical setting. suppose we are given a set w of logical structures, or possible worlds, a set of logical formulas called possible data and a logical formula @f. we then consider the classification problem of determining in the limit and almost always correctly whether a possible world m satisfies @f, from a complete enumeration of the possible data that are true in m. one interpretation of almost always correctly is that the classification might be wrong on a set of possible worlds of measure 0, with respect to some natural probability distribution over the set of possible worlds. another interpretation is that the classifier is only required to classify a set w^' of possible worlds of measure 1, without having to produce any claim in the limit on the truth of @f for the members of the complement of w^' in w. we compare these notions with absolute classification of w with respect to a formula that is almost always equivalent to @f in w, hence we investigate whether the set of possible worlds on which the classification is correct is definable. we mainly work with the probability distribution that corresponds to the standard measure on the cantor space, but we also consider an alternative probability distribution proposed by solomonoff and contrast it with the former. finally, in the spirit of the kind of computations considered in logic programming, we address the issue of computing almost correctly in the limit witnesses to leading existentially quantified variables in existential formulas.
access control in mobile ambient calculi: a comparative view. ambient calculi represent a class of process calculi used to describe and model mobile and distributed computations. this paper examines the most relevant of these calculi and focuses on an important dimension: the access control problem. in the security world, a system is considered trusted if it controls the access to its resources, i.e. every request for the access to a resource is honored if and only if the subject requiring the resource is an authorized user of the system and the request agrees with a given policy. so the security problem for ambient calculi is investigated considering the authentication mechanism and the possibility to implement security policies. two examples have been chosen to illustrate these topics: the firewall and the communication by means of named channels.
a type assignment system for game semantics. we present a type assignment system that provides a finitary interpretation of lambda terms in a game semantics model. traditionally, type assignment systems describe the semantic interpretation of terms in domain-theoretic models. quite surprisingly, the type assignment system presented in this paper is very similar to the traditional ones, the main difference being the omission of the subtyping rules.
semantic subtyping for the pi-calculus. subtyping relations for the @p-calculus are usually defined in a syntactic way, by means of structural rules. we propose a semantic characterisation of channel types and use it to derive a subtyping relation. the type system we consider includes read-only and write-only channel types, as well as boolean combinations of types. a set-theoretic interpretation of types is provided, in which boolean combinations of types are interpreted as the corresponding set-theoretic operations. subtyping is defined as inclusion of the interpretations. we prove decidability of the subtyping relation and sketch the subtyping algorithm. in order to fully exploit the type system, we define a variant of the @p-calculus where communication is subjected to pattern matching that performs dynamic typecase.
extending feathertrait java with interfaces. in the context of featherweight java by igarashi, pierce, and wadler, and its recent extension feathertrait java (ftj) by the authors, we investigate classes that can be extended with trait composition. a trait is a collection of methods, i.e., behaviors without state; it can be viewed as an ''incomplete stateless class'' i.e., an interface with some already written behavior. traits can be composed in any order, but only make sense when ''imported'' by a class that provides state variables and additional methods to disambiguate conflicting names arising between the imported traits. we introduce feathertrait java with interfaces (iftj), where traits need to be typechecked only once, which is necessary for compiling them in isolation, and considering them as regular types, like java-interfaces with a behavioral content.
a typed lambda calculus with intersection types. intersection types are well known to type theorists mainly for two reasons. firstly, they type all and only the strongly normalizable lambda terms. secondly, the intersection type operator is a meta-level operator, that is, there is no direct logical counterpart in the curry-howard isomorphism sense. in particular, its meta-level nature implies that it does not correspond to the intuitionistic conjunction. the intersection type system is naturally a type inference system (system a la curry), but the meta-level nature of the intersection operator does not allow to easily design an equivalent typed system (system a la church). there are many proposals in the literature to design such systems, but none of them gives an entirely satisfactory answer to the problem. in this paper, we will review the main results in the literature both on the logical interpretation of intersection types and on proposed typed lambda calculi. the core of this paper is a new proposal for a true intersection typed lambda calculus, without any meta-level notion. namely, any typable term (in the intersection type inference) has a corresponding typed term (which is the same as the untyped term by erasing the type decorations and the typed term constructors) with the same type, and vice versa. the main idea is to introduce a relevant parallel term constructor which corresponds to the intersection type constructor, in such a way that terms in parallel share the same resources, that is, the same context of free typed variables. three rules allow us to generate all typed terms. the first two rules, application and lambda-abstraction, are performed on all the components of a parallel term in a synchronized way. finally, via the third rule of local renaming, once a free typed variable is bounded by lambda-abstraction, each of the terms in parallel can do its local renaming, with type refinement, of that particular resource.
towards the range property for the lambda theory h. a sketch of the proof is given for an open problem, the range property forh: the range of a closed @l-term in the closed term model modulo @b-conversion and equating unsolvable terms is either a singleton or infinite. the proof depends on one unresolved technical conjecture.
the weak lambda calculus as a reasonable machine. we define a new cost model for the call-by-value lambda-calculus satisfying the invariance thesis. that is, under the proposed cost model, turing machines and the call-by-value lambda-calculus can simulate each other within a polynomial time overhead. the model only relies on combinatorial properties of the usual beta-reduction, without any reference to a specific machine or evaluator. in particular, the cost of a single beta reduction is proportional to the difference between the size of the redex and the size of the reduct. in this way, the total cost of normalizing a lambda term will take into account the size of all intermediate results (as well as the number of steps to normal form).
on strong normalization and type inference in the intersection type discipline. we introduce a new unification procedure for the type inference problem in the intersection type discipline. it is well known that type inference in this case should succeed exactly for the strongly normalizing expressions. we give a proof for the strong normalization result in the intersection type discipline, which we obtain by putting together some well-known results and proof techniques. our proof uses a variant of klop's extended @l-calculus, for which it is shown that strong normalization is equivalent to weak normalization. this is proved here by means of a finiteness of developments theorem, obtained following de vrijer's combinatory technique. the main property of this extended calculus is uniformity, i.e. weak and strong normalizabilities coincide. the strong normalizability result is therefore a consequence of the fact, first established by coppo and dezani (for the @l-calculus) that typability implies weak normalizability. we then show that the unification process which is the basis for type inference exactly corresponds to reduction in the extended @l-calculus. finally we show that our notion of unification allows us to compute a principal typing for any typable @l-expression.
characterizing strong normalization in the curien-herbelin symmetric lambda calculus: extending the coppo-dezani heritage. we develop an intersection type system for the @l@?@m@m@? calculus of curien and herbelin. this calculus provides a symmetric computational interpretation of classical sequent style logic and gives a simple account of call-by-name and call-by-value. the present system improves upon earlier type disciplines for @l@?@m@m@?: in addition to characterizing the @l@?@m@m@? expressions that are strongly normalizing under free (unrestricted) reduction, the system enjoys the subject reduction and the subject expansion properties.
role-based access control for boxed ambients. our society is increasingly moving towards richer forms of information exchange where mobility of processes and devices plays a prominent role. this tendency has prompted the academic community to study the security problems arising from such mobile environments, and in particular, the security policies regulating who can access the information in question. in this paper we describe a calculus for mobile processes and propose a mechanism for specifying access privileges based on a combination of the identity of the users seeking access, their credentials, and the location from which they seek it, within a reconfigurable nested structure. we define baci"r, a boxed ambient calculus extended with a distributed role-based access control mechanism where each ambient controls its own access policy. a process in baci"r is associated with an owner and a set of activated roles that grant permissions for mobility and communication. the calculus includes primitives to activate and deactivate roles. the behavior of these primitives is determined by the process's owner, its current location and its currently activated roles. we consider two forms of security violations that our type system prevents: (1) attempting to move into an ambient without having the authorizing roles granting entry activated and (2) trying to use a communication port without having the roles required for access activated. we accomplish (1) and (2) by giving a static type system, an untyped transition semantics, and a typed transition semantics. we then show that a well-typed program never violates the dynamic security checks.
lambda calculus with patterns. in this paper we revisit the @l-calculus with patterns, originating from the practice of functional programming language design. we treat this feature in a framework ranging from pure @l-calculus to orthogonal combinatory reduction systems.
computability and the morphological complexity of some dynamics on continuous domains. the partially ordered set of compact intervals provides a convenient embedding space for the analysis of some dynamical systems. crucial dynamical properties are transferred to it, while allowing an investigation of stability and chaoticity, in terms of computability, in particular in the presence of singularities. we will survey some results which display the connections between the geometric complexity of the dynamics and computability issues, as well as new relations between dynamic predictability and effective decidability.
the heart of intersection type assignment: normalisation proofs revisited. this paper gives a new proof for the approximation theorem and the characterisation of normalisability using intersection types for a system with 'w and a @?-relation that is contra-variant over arrow types. the technique applied is to define reduction on derivations and to show a strong normalisation result for this reduction. from this result, the characterisation of strong normalisation and the approximation result will follow easily; the latter, in its turn, will lead to the characterisation of (head) normalisability.
distance- k knowledge in self-stabilizing algorithms. many graph problems seem to require knowledge that extends beyond the immediate neighbors of a node. the usual self-stabilizing model only allows for nodes to make decisions based on the states of their immediate neighbors. we provide a general transformation for constructing self-stabilizing algorithms which utilize distance-k knowledge. our transformation has both a slowdown and space overhead in n^o^(^l^o^g^k^), and might be thought of as a distance-k resource allocation algorithm. our main application is a polynomial-time self-stabilizing algorithm for finding maximal irredundant sets, a problem which seems to require distance-4 information. these results can be generalized to efficiently find maximal p-sets, for properties p which we call local monotonic. our techniques extend results in a recent paper by gairing et al. for achieving distance-two information.
digraph measures: kelly decompositions, games, and orderings. we consider various well-known, equivalent complexity measures for graphs such as elimination orderings, k-trees and cops and robber games and study their natural translations to digraphs. we show that on digraphs the translations of these measures are also equivalent and induce a natural connectivity measure. we introduce a decomposition for digraphs and an associated width, kelly-width, which is equivalent to the aforementioned measure. we demonstrate its usefulness by exhibiting potential applications including polynomial-time algorithms for np-complete problems on graphs of bounded kelly-width, and complexity analysis of asymmetric matrix factorization. finally, we compare the new width to other known decompositions of digraphs.
how to meet in anonymous network. a set of k mobile agents with distinct identifiers and located in nodes of an unknown anonymous connected network, have to meet at some node. we show that this gathering problem is no harder than its special case for k=2, called the rendezvous problem, and design deterministic protocols solving the rendezvous problem with arbitrary startups in rings and in general networks. the measure of performance is the number of steps since the startup of the last agent until the rendezvous is achieved. for rings we design an oblivious protocol with cost o(nlog@?), where n is the size of the network and @? is the minimum label of participating agents. this result is asymptotically optimal due to the lower bound showed by [a. dessmark, p. fraigniaud, d. kowalski, a. pelc, deterministic rendezvous in graphs, algorithmica 46 (2006) 69-96]. for general networks we show a protocol with cost polynomial in n and log@?, independent of the maximum difference @t of startup times, which answers in the affirmative the open question by [a. dessmark, p. fraigniaud, d. kowalski, a. pelc, deterministic rendezvous in graphs, algorithmica 46 (2006) 69-96].
local spreading algorithms for autonomous robot systems. this paper studies local algorithms for autonomous robot systems, namely, algorithms that use only information of the positions of a bounded number of their nearest neighbors. the paper focuses on the spreading problem. it defines measures for the quality of spreading, presents a local algorithm for the one-dimensional spreading problem, proves its convergence to the equally spaced configuration and discusses its convergence rate in the synchronous and semi-synchronous settings. it then presents a local algorithm achieving the exact equally spaced configuration in finite time in the synchronous setting, and proves it is time optimal for local algorithms. finally, the paper also proposes a possible algorithm for the two-dimensional case and presents partial simulation results of its effectiveness.
an annotated bibliography on guaranteed graph searching. graph searching encompasses a wide variety of combinatorial problems related to the problem of capturing a fugitive residing in a graph using the minimum number of searchers. in this annotated bibliography, we give an elementary classification of problems and results related to graph searching and provide a source of bibliographical references on this field.
cleaning a network with brushes. following the decontamination metaphor for searching a graph, we introduce a cleaning process, which is related to both the chip-firing game and edge searching. brushes (instead of chips) are placed on some vertices and, initially, all the edges are dirty. when a vertex is 'fired', each dirty incident edge is traversed by only one brush, cleaning it, but a brush is not allowed to traverse an already cleaned edge; consequently, a vertex may not need degree-many brushes to fire. the model presented is one where the edges are continually recontaminated, say by algae, so that cleaning is regarded as an on-going process. ideally, the final configuration of the brushes, after all the edges have been cleaned, should be a viable starting configuration to clean the graph again. we show that this is possible with the least number of brushes if the vertices are fired sequentially but not if fired in parallel. we also present bounds for the least number of brushes required to clean graphs in general and some specific families of graphs.
fast deterministic distributed algorithms for sparse spanners. this paper concerns the efficient construction of sparse and low stretch spanners for unweighted arbitrary graphs with n nodes. all previous deterministic distributed algorithms, for constant stretch spanners of o(n^2) edges, have a running time @w(n^@e) for some constant @e>0 depending on the stretch. our deterministic distributed algorithms construct constant stretch spanners of o(n^2) edges in o(n^@e) time for any constant @e>0. more precisely, in linial's free model a.k.a local model, we construct in n^o^(^1^/^l^o^g^n^) time, for every graph, a (3,2)-spanner of o(n^3^/^2) edges, i.e., a spanning subgraph in which the distance is at most 3 times the distance of the original graph plus 2. the result is extended to (@a"k,@b"k)-spanners with o(n^1^+^1^/^klogk) edges for every integer parameter k>=1, where @a"k+@b"k=o(k^l^o^g^"^2^5). if the minimum degree of the graph is @w(n), then, in the same time complexity, a (5,4)-spanner with o(n) edges can be constructed.
distributed chasing of network intruders. graph searching is one of the most popular tools for analyzing the chase for a powerful and hostile software agent (called the ''intruder''), by a set of software agents (called the ''searchers'') in a network. the existing solutions for the graph searching problem suffer however from a serious drawback: they are mostly centralized and assume a global synchronization mechanism for the searchers. in particular: (1) the search strategy for every network is computed based on the knowledge of the entire topology of the network, and (2) the moves of the searchers are controlled by a centralized mechanism that decides at every step which searcher has to move, and what movement it has to perform. this paper addresses the graph searching problem in a distributed setting. we describe a distributed protocol that enables searchers with logarithmic size memory to clear any network, in a fully decentralized manner. the search strategy for the network in which the searchers are launched is computed online by the searchers themselves without knowing the topology of the network in advance. it performs in an asynchronous environment, i.e., it implements the necessary synchronization mechanism in a decentralized manner. in every network, our protocol performs a connected strategy using at most k+1 searchers, where k is the minimum number of searchers required to clear the network in a monotone connected way using a strategy computed in the centralized and synchronous setting.
minimum-energy broadcast and disk cover in grid wireless networks. the minimum-energy broadcast problem is to assign a transmission range to every station of an ad hoc wireless networks so that (i) a given source station is allowed to perform broadcast operations and (ii) the overall energy consumption of the range assignment is minimized. we prove a nearly tight asymptotical bound on the optimal cost for the minimum-energy broadcast problem on square grids. we also derive near-tight bounds for the bounded-hop version of this problem. our results imply that the best-known heuristic, the mst-based one, for the minimum-energy broadcast problem is far to achieve optimal solutions (even) on very regular, well-spread instances: its worst-case approximation ratio is about @p and it yields @w(n) hops, where n is the number of stations. as a by product, we get nearly tight bounds for the minimum-disk cover problem and for its restriction in which the allowed disks must have non-constant radius. finally, we emphasize that our upper bounds are obtained via polynomial time constructions.
election and rendezvous with incomparable labels. in ''can we elect if we cannot compare'' (spaa'03), barriere, flocchini, fraigniaud and santoro consider a qualitative model of distributed computing, where the labels of the entities are distinct but mutually incomparable. they study the leader election problem in a distributed mobile environment and they wonder whether there exists an algorithm such that for each distributed mobile environment, it either states that the problem cannot be solved in this environment, or it successfully elects a leader. in this paper, we give a positive answer to this question. we also give a characterization of the distributed mobile environments where election and rendezvous can be solved.
time constrained graph searching. we consider time constraints for four models of searching graphs for intruders. one model is the standard cops and robber vertex-searching model with complete visibility. the second model differs from the preceding one only in that none of the searchers can see the intruder. the third model is a vertex-searching model in which searchers and an intruder move simultaneously and none of the searchers can see the intruder. the fourth model is simultaneous edge searching with an arbitrarily fast intruder.
the role of information in the cop-robber game. we investigate the role of the information available to the players on the outcome of the cops and robbers game. this game takes place on a graph and players move along the edges in turns. the cops win the game if they can move onto the robber's vertex. in the standard formulation, it is assumed that the players can ''see'' each other at all times. a graph g is called cop-win if a single cop can capture the robber on g. we study the effect of reducing the cop's visibility. on the positive side, with a simple argument, we show that a cop with small or no visibility can capture the robber on any cop-win graph (even if the robber still has global visibility). on the negative side, we show that the reduction in cop's visibility can result in an exponential increase in the capture time. finally, we start the investigation of the variant where the visibility powers of the two players are symmetrical. we show that the cop can establish eye contact with the robber on any graph and present a sufficient condition for capture. in establishing this condition, we present a characterization of graphs on which a natural greedy pursuit strategy suffices for capturing the robber.
optimal delay for media-on-demand with pre-loading and pre-buffering. broadcasting popular media to clients is the ultimate scalable solution for media-on-demand. the simple solution of downloading and viewing the medium from one channel cannot guarantee a reasonable start-up delay for viewing with no interruptions. two known techniques to reduce the delay are pre-loading and pre-buffering. in the former an initial segment of the medium is already in the client buffer, and in the latter segments of the medium are not transmitted in sequence and clients may pre-buffer latter segments of the medium before viewing them. in both techniques, clients should be capable to receive streams from channels at the same time of handling their own buffer and view the medium from either one of the channels or the buffer. this paper considers broadcasting schemes that combine pre-loading and pre-buffering. we present a complete tradeoff between (i) the size of the pre-loading; (ii) the maximum delay for an uninterrupted playback; (iii) the number of media; and (iv) the number of channels allocated per one medium. for a given b the size of the pre-loading as a fraction of the medium length, for m media, and for h channels per medium, we first establish a lower bound for the maximum delay, d, as a fraction of the medium length, for an uninterrupted playback of any medium out of the m media. we then present an upper bound that approaches this lower bound when each medium can be fragmented into many segments.
the maximum edge-disjoint paths problem in complete graphs. in this paper, we consider the undirected version of the well known maximum edge-disjoint paths problem, restricted to complete graphs. we propose an off-line 3.75-approximation algorithm and an on-line 6.47-approximation algorithm, improving the earlier 9-approximation algorithm proposed by carmi, erlebach, and okamoto [p. carmi, t. erlebach, y. okamoto, greedy edge-disjoint paths in complete graphs, in: proc. 29th workshop on graph theoretic concepts in computer science, in: lncs, vol. 2880, 2003, pp. 143-155]. moreover, we show that for the general case, no on-line algorithm is better than a (2-@e)-approximation, for all @e>0. for the special case when the number of paths is within a linear factor of the number of vertices of the graph, it is established that the problem can be optimally solved in polynomial time by an off-line algorithm, but that no on-line algorithm is better than a (1.5-@e)-approximation. finally, the proposed techniques are used to obtain off-line and on-line algorithms with a constant approximation ratio for the related problems of edge congestion routing and wavelength routing in complete graphs.
monotonicity of non-deterministic graph searching. in graph searching, a team of searchers are aiming at capturing a fugitive moving in a graph. in the initial variant, called invisible graph searching, the searchers do not know the position of the fugitive until they catch it. in another variant, the searchers permanently know the position of the fugitive, i.e. the fugitive is visible. this latter variant is called visible graph searching. a search strategy that catches any fugitive in such a way that the part of the graph reachable by the fugitive never grows is called monotone. a priori, monotone strategies may require more searchers than general strategies to catch any fugitive. this is however not the case for visible and invisible graph searching. two important consequences of the monotonicity of visible and invisible graph searching are: (1) the decision problem corresponding to the computation of the smallest number of searchers required to clear a graph is in np, and (2) computing optimal search strategies is simplified by taking into account that there exist some that never backtrack. fomin et al. [f.v. fomin, p. fraigniaud, n. nisse, nondeterministic graph searching: from pathwidth to treewidth, in: proceedings of the 30th international symposium on mathematical foundations of computer science, mfcs'05, 2005, pp. 364-375] introduced an important graph searching variant, called non-deterministic graph searching, that unifies visible and invisible graph searching. in this variant, the fugitive is invisible, and the searchers can query an oracle that permanently knows the current position of the fugitive. the question of the monotonicity of non-deterministic graph searching was however left open. in this paper, we prove that non-deterministic graph searching is monotone. in particular, this result is a unified proof of monotonicity for visible and invisible graph searching. as a consequence, the decision problem corresponding to non-deterministic graph searching belongs to np. moreover, the exact algorithms designed by fomin et al. do compute optimal non-deterministic search strategies.
on some questions regarding k -regular and k -context-free sequences. we answer two questions of allouche and shallit regarding k-regular sequences and k-context-free sequences. one of these has been solved independently in another way by bell. we also provide a partial solution to another question of allouche and shallit regarding the subword complexity of k-context-free sequences.
martingale families and dimension in p. we introduce a new measure notion on small complexity classes (called f-measure), based on martingale families, that gets rid of some drawbacks of previous measure notions: it can be used to define dimension because martingale families can make money on all strings, and it yields random sequences with an equal frequency of 0's and 1's. on larger complexity classes (e and above), f-measure is equivalent to lutz resource-bounded measure. as applications to f-measure, we answer a question raised in [e. allender, m. strauss, measure on small complexity classes, with application for bpp, in: proc. of the 35th ann. ieee symp. on found. of comp. sci., 1994, pp. 807-818] by improving their result to: for almost every language a decidable in subexponential time, p^a=bpp^a. we show that almost all languages in pspace do not have small non-uniform complexity. we compare f-measure to previous notions and prove that martingale families are strictly stronger than @c-measure [e. allender, m. strauss, measure on small complexity classes, with application for bpp, in: proc. of the 35th ann. ieee symp. on found. of comp. sci., 1994, pp. 807-818], we also discuss the limitations of martingale families concerning finite unions. we observe that all classes closed under polynomial many-one reductions have measure zero in exp iff they have measure zero in subexp. we use martingale families to introduce a natural generalization of lutz resource-bounded dimension [j.h. lutz, dimension in complexity classes, in: proceedings of the 15th annual ieee conference on computational complexity, 2000, pp. 158-169] on p, which meets the intuition behind lutz's notion. we show that p-dimension lies between finite-state dimension and dimension on e. we prove an analogue of a theorem of eggleston in p, i.e. the class of languages whose characteristic sequence contains 1's with frequency @a, has dimension the shannon entropy of @a in p.
approximation algorithms for partially covering with edges. the edge dominating set (eds) and edge-cover (ec) problems are classical graph covering problems in which one seeks a minimum cost collection of edges which covers the edges or vertices, respectively, of a graph. we consider the generalized partial cover version of these problems, in which failing to cover an edge, in the eds case, or vertex, in the ec case, induces a penalty. given a bound on the total amount of penalties that we are permitted to pay, the objective is to find a minimum cost cover with respect to this bound. we give an 8/3-approximation for generalized partial eds. this result matches the best-known guarantee for the {0,1}-eds problem, a specialization in which only a specified set of edges need to be covered. moreover, 8/3 corresponds to the integrality gap of the natural formulation of the {0,1}-eds problem. our techniques can also be used to derive an approximation scheme for the generalized partial edge-cover problem, which is np-complete even though the uniform penalty version of the partial edge-cover problem is in p.
on the structure of graphs in the caucal hierarchy. we investigate the structure of graphs in the caucal hierarchy. we provide criteria concerning the degree of vertices or the length of paths which can be used to show that a given graph does not belong to a certain level of this hierarchy. each graph in the caucal hierarchy corresponds to the configuration graph of some higher-order pushdown automaton. the main part of the paper consists of a study of such configuration graphs. we provide tools to decompose and reassemble their runs, and we prove a pumping lemma for higher-order pushdown automata.
polyomino coloring and complex numbers. usually polyominoes are represented as subsets of the lattice z^2. in this paper we study a representation of polyominoes by gaussian integers. polyomino {(x"1,y"1),(x"2,y"2),...,(x"s,y"s)}@?z^2 is represented by the set {(x"1+iy"1),(x"2+iy"2),...,(x"s+iy"s)}@?z[i]. then we consider functions of type f:p->g from the set p of all polyominoes to an abelian group g, given by f(x,y)=(x+iy)^m(modv), where v is prime in z[i],1@?m
turing machines and bimachines. we associate the iterated block product of a bimachine with a deterministic turing machine. this allows us to introduce new algebraic notions to study the behavior of the turing machine. namely, we introduce double semidirect products through matrix multiplication of upper triangular matrices with coefficients in certain semigroups, which leads in turn to the study of the iterations of bimachines. by passing to the profinite (or projective) limit, we obtain an algebraic profinite description of the limit behavior of the turing machine. finally, we analyze the proof that all languages in np can be reduced to circuit sat from this viewpoint.
heuristic algorithms for two machine re-entrant flow shop. this paper focuses on a two machine re-entrant flow shop scheduling problem with the objective of minimizing makespan. in the re-entrant flow shop considered here, each job has the processing route (m"1, m"2, m"1, m"2, ..., m"1, m"2). we present heuristic algorithms, some are modified from existing algorithms and some are newly developed. extensive computational experiments are performed to evaluate the performance of the heuristics. results of the experiments show that the performance of heuristics is significantly affected by the distribution of workloads on machines and some of them are excellent.
a unified approach to finding good stable matchings in the hospitals/residents setting. the hospitals/residents (hr) problem is a many-to-one generalization of the stable marriage (sm) problem. researchers have been interested in variants of stable matchings that either satisfy a set of additional contraints or are optimal with respect to some cost function. in this paper, we show that broad classes of feasibility and optimization stable matching problems in the hr setting can be solved efficiently provided certain tasks (such as checking the feasibility of a stable matching or computing the cost of a stable matching) can also be done efficiently. to prove our results, we make use of an hr instance's meta-rotation poset to explore its stable matchings. an algorithm that can discover all the meta-rotations of the instance serves as a starting point for all our algorithms.
reconstruction of a word from a multiset of its factors. let d"k(w) be the multiset containing all factors of w of length k including repetitions. one of the main results is that if d"k(w)=d"k(v) for all k@?@?|w|2@?+1, then w=v. the bound @?|w|2@?+1 is optimal; however we will also show that if d"k(w)=d"k(v) for all k@?@?|w|2@?, then w and v are structurally similar.
on stabilizers of infinite words. the stabilizer of an infinite word w over a finite alphabet @s is the monoid of morphisms over @s that fix w. in this paper we study various problems related to stabilizers and their generators. we show that over a binary alphabet, there exist stabilizers with at least n generators for all n. over a ternary alphabet, the monoid of morphisms generating a given infinite word by iteration can be infinitely generated, even when the word is generated by iterating an invertible primitive morphism. stabilizers of strict epistandard words are cyclic when non-trivial, while stabilizers of ultimately strict epistandard words are always non-trivial. for this latter family of words, we give a characterization of stabilizer elements.
matrices of 3-iet preserving morphisms. we study matrices of morphisms preserving the family of words coding 3-interval exchange transformations. it is well known that matrices of morphisms preserving sturmian words (i.e. words coding 2-interval exchange transformations with the maximal possible factor complexity) form the monoid {m@?n^2^x^2|detm=+/-1}={m@?n^2^x^2|mem^t=+/-e}, where e=(01-10). we prove that in the case of exchange of three intervals, the matrices preserving words coding these transformations and having the maximal possible subword complexity belong to the monoid {m@?n^3^x^3|mem^t=+/-e,detm=+/-1}, where e=(011-101-1-10).
extension of brzozowski's derivation calculus of rational expressions to series over the free partially commutative monoids. we introduce an extension of the derivatives of rational expressions to expressions denoting formal power series over partially commuting variables. the expressions are purely noncommutative, however they denote partially commuting power series. the derivations (which are so-called @f-derivations) are shown to satisfy the commutation relations. our main result states that for every so-called rigid rational expression, there exists a stable finitely generated submodule containing it. moreover, this submodule is generated by what we call words, that is by products of letters and of pure stars. consequently this submodule is free and it follows that every rigid rational expression represents a recognizable series in k>. this generalizes the previously known property where the star was restricted to mono-alphabetic and connected series.
on the complexity of minimizing interference in ad-hoc and sensor networks. one of the most critical factors for lifetime and operability of ad-hoc and sensor networks is the limited amount of available energy. to this respect, minimizing the interference in the network (i.e., the overlapping of signals at network nodes) has certainly a positive effect, because it induces a reduction of the number of conflicting transmissions, and then results in an overall saving of energy consumption. along this direction, in this paper we study the computational hardness of several interference minimization problems which arise while supporting some classic network communication patterns such as broadcasting (one-to-all), gossiping (all-to-all), and symmetric gossiping (symmetric all-to-all). in particular, concerning the non-approximability results, we prove that for any of the above communication patterns, the prominent problem of minimizing the maximum interference experienced by any node in the network is hard to approximate within better than a logarithmic factor, unless np admits slightly superpolynomial time algorithms. on a positive side, we show that any approximation algorithm for the problem of minimizing the total transmission power assigned to the nodes in order to guarantee any of the above communication patterns, can be transformed, by maintaining the same performance ratio, into an approximation algorithm for the problem of minimizing the total interference experienced by all the nodes in the network.
determining the equivalence for one-way quantum finite automata. two quantum finite automata are equivalent if for any input string x the two automata accept x with equal probability. in this paper, we first focus on determining the equivalence for one-way quantum finite automata with control language (cl-1qfas) defined by bertoni et al., and then, as an application, we address the equivalence problem for measure-many one-way quantum finite automata (mm-1qfas) introduced by kondacs and watrous. more specifically, we obtain that: (i)two cl-1qfas a"1 and a"2 with control languages (regular languages) l"1 and l"2, respectively, are equivalent if and only if they are (c"1n"1^2+c"2n"2^2-1)-equivalent, where n"1 and n"2 are the numbers of states in a"1 and a"2, respectively, and c"1 and c"2 are the numbers of states in the minimal dfas that recognize l"1 and l"2, respectively. furthermore, if l"1 and l"2 are given in the form of dfas, with m"1 and m"2 states, respectively, then there exists a polynomial-time algorithm running in time o((m"1n"1^2+m"2n"2^2)^4) that takes as input a"1 and a"2 and determines whether they are equivalent. (ii)(as an application of item (i)): two mm-1qfas a"1 and a"2 with n"1 and n"2 states, respectively, are equivalent if and only if they are (3n"1^2+3n"2^2-1)-equivalent. furthermore, there is a polynomial-time algorithm running in time o((3n"1^2+3n"2^2)^4) that takes as input a"1 and a"2 and determines whether a"1 and a"2 are equivalent.
cryptographically-masked flows. cryptographic operations are essential for many security-critical systems. reasoning about information flow in such systems is challenging because typical (noninterference-based) information-flow definitions allow no flow from secret to public data. unfortunately, this implies that programs with encryption are ruled out because encrypted output depends on secret inputs: the plaintext and the key. however, it is desirable to allow flows arising from encryption with secret keys provided that the underlying cryptographic algorithm is strong enough. in this article we conservatively extend the noninterference definition to allow safe encryption, decryption, and key generation. to illustrate the usefulness of this approach, we propose (and implement) a type system that guarantees noninterference for a small imperative language with primitive cryptographic operations. the type system prevents dangerous program behavior (e.g., giving away a secret key or confusing keys and nonkeys), which we exemplify with secure implementations of cryptographic protocols. because the model is based on a standard noninterference property, it allows us to develop some natural extensions. in particular, we consider public-key cryptography and integrity, which accommodate reasoning about primitives that are vulnerable to chosen-ciphertext attacks.
efficient corona training protocols for sensor networks. phenomenal advances in nano-technology and packaging have made it possible to develop miniaturized low-power devices that integrate sensing, special-purpose computing, and wireless communications capabilities. it is expected that these small devices, referred to as sensors, will be mass-produced and deployed, making their production cost negligible. due to their small form factor and modest non-renewable energy budget, individual sensors are not expected to be gps-enabled. moreover, in most applications, exact geographic location is not necessary, and all that the individual sensors need is a coarse-grain location awareness. the task of acquiring such a coarse-grain location awareness is referred to as training. in this paper, two scalable energy-efficient training protocols are proposed for massively-deployed sensor networks, where sensors are initially anonymous and unaware of their location. the training protocols are lightweight and simple to implement; they are based on an intuitive coordinate system imposed onto the deployment area which partitions the anonymous sensors into clusters where data can be gathered from the environment and synthesized under local control.
on fractional dynamic faults with thresholds. unlike localized communication failures that occur on a fixed (although a priori unknown) set of links, dynamic faults can occur on any link. known also as mobile or ubiquitous faults, their presence makes many tasks difficult, if not impossible to solve, even in synchronous systems. in this paper, we introduce a new model for dynamic faults in synchronous distributed systems. this model includes as special cases the existing settings studied in the literature. we focus on the hardest setting of this model, called the simple threshold, where to be guaranteed that at least one message is delivered in a time step, the total number of transmitted messages in that time step must reach a threshold t@?c(g), where c(g) is the edge connectivity of the network. we investigate the problem of broadcasting under this model for the worst threshold t=c(g) in several classes of graphs, as well as in arbitrary networks. we design solution protocols, proving that broadcasting is possible even in this harsh environment. we analyze the time costs, showing that broadcasts can be completed in (low) polynomial time for several networks including rings (with or without knowledge of n), complete graphs (with or without a chordal sense of direction), hypercubes (with or without orientation), and constant-degree networks (with or without full topological knowledge).
solving difference equations whose coefficients are not transcendental. we consider a large class of sequences which are defined by systems of (possibly nonlinear) difference equations. a procedure for recursively enumerating the algebraic dependencies of such sequences is presented. also a procedure for solving linear difference equations with such sequences as coefficients is proposed. the methods are illustrated on some problems arising in the literature on special functions and combinatorial sequences.
complexity and approximation for precedence constrained scheduling problems with large communication delays. we investigate the problem of minimizing the makespan (resp. the sum of completion time) for the multiprocessor scheduling problem. we show that there is no hope of finding a @r-approximation with @r=2.
reversal complexity revisited. we study a generalized version of reversal bounded turing machines where, apart from several tapes on which the number of head reversals is bounded by r(n), there are several further tapes on which head reversals remain unrestricted, but size is bounded by s(n) (where n denotes the input length). recently [m. grohe, c. koch, n. schweikardt, tight lower bounds for query processing on streaming and external memory data, theoretical computer science 380 (1-2) (2007) 199-217; m. grohe, n. schweikardt, lower bounds for sorting with few random accesses to external memory, in: proc. pods'05, acm press, 2005, pp. 238-249], such machines were introduced as a formalization of a computation model that restricts random access to external memory and internal memory space. here, each of the tapes with a restriction on the head reversals corresponds to an external memory device, and the tapes of restricted size model internal memory. we use st(r(n),s(n),o(1)) to denote the class of all problems that can be solved by deterministic turing machines that comply to the above resource bounds. similarly, nst(...) and rst(...), respectively, are used for the corresponding nondeterministic and randomized classes. while previous papers focused on lower bounds for particular problems, including sorting, the set equality problem, and several query evaluation problems, the present paper addresses the relations between the (r,n) st(...)-classes and classical complexity classes and investigates the structural complexity of the (r,n) st(...)-classes. our main results are (1) a trade-off between internal memory space and external memory head reversals, (2) correspondences between the (r,n) st(...) classes and ''classical'' time-bounded, space-bounded, reversal-bounded, and circuit complexity classes, and (3) hierarchies of (r) st(...)-classes in terms of increasing numbers of head reversals on external memory tapes.
the complexity of tarski's fixed point theorem. tarski's fixed point theorem guarantees the existence of a fixed point of an order-preserving function f:l->l defined on a nonempty complete lattice (l,@?) [b. knaster, un theoreme sur les fonctions d'ensembles, annales de la societe polonaise de mathematique 6 (1928) 133-134; a. tarski, a lattice theoretical fixpoint theorem and its applications, pacific journal of mathematics 5 (1955) 285-309]. in this paper, we investigate several algorithmic and complexity-theoretic topics regarding tarski's fixed point theorem. in particular, we design an algorithm that finds a fixed point of f when it is given (l,@?) as input and f as an oracle. our algorithm makes o(log|l|) queries to f when @? is a total order on l. we also prove that when both f and (l,@?) are given as oracles, any deterministic or randomized algorithm for finding a fixed point of f makes an expected @w(|l|) queries for some (l,@?) and f.
complexity of unique list colorability. given a list l(v) for each vertex v, we say that the graph g is l-colorable if there is a proper vertex coloring of g where each vertex v takes its color from l(v). the graph is uniquelyk-list colorable if there is a list assignment l such that |l(v)|=k for every vertex v and the graph has exactly one l-coloring with these lists. mahdian and mahmoodian [m. mahdian, e.s. mahmoodian, a characterization of uniquely 2-list colorable graphs, ars combin. 51 (1999) 295-305] gave a polynomial-time characterization of uniquely 2-list colorable graphs. answering an open question from [m. ghebleh, e.s. mahmoodian, on uniquely list colorable graphs, ars combin. 59 (2001) 307-318; m. mahdian, e.s. mahmoodian, a characterization of uniquely 2-list colorable graphs, ars combin. 51 (1999) 295-305], we show that uniquely 3-list colorable graphs are unlikely to have such a nice characterization, since recognizing these graphs is @s"2^p-complete.
online scheduling of equal-processing-time task systems. we consider the problem of online scheduling a set of equal-processing-time tasks with precedence constraints so as to minimize the makespan. for arbitrary precedence constraints, it is known that any list scheduling algorithm has a competitive ratio of 2-1/m, where m is the number of machines. we show that for intree precedence constraints, hu's algorithm yields an asymptotic competitive ratio of 3/2.
group-strategyproof cost sharing mechanisms for makespan and other scheduling problems. classical results in economics show that no truthful mechanism can achieve budget balance and efficiency simultaneously. roughgarden and sundararajan recently proposed an alternative efficiency measure, which was subsequently used to exhibit that many previously known cost sharing mechanisms approximate both budget balance and efficiency. in this work, we investigate cost sharing mechanisms for combinatorial optimization problems using this novel efficiency measure, with a particular focus on scheduling problems. our contribution is threefold: first, for a large class of optimization problems that satisfy a certain cost-stability property, we prove that no budget balanced moulin mechanism can approximate efficiency better than @w(logn), where n denotes the number of players in the universe. second, we present a group-strategyproof cost sharing mechanism for the minimum makespan scheduling problem that is tight with respect to budget balance and efficiency. finally, we show a general lower bound on the budget balance factor for cost sharing methods, which can be used to prove a lower bound of @w(n) on the budget balance factor for completion and flow time scheduling objectives.
a relation between trinucleotide comma-free codes and trinucleotide circular codes. the comma-free codes and circular codes are two important classes of codes in code theory and in genetics. fifty years ago before the discovery of the genetic code, a trinucleotide (triletter) comma-free code was proposed for associating the codons of genes with the amino acids of proteins. more recently, in the last ten years, trinucleotide circular codes have been identified statistically in different genomes. here, we identify a relation between these two classes of trinucleotide codes by constructing a hierarchy of comma-free and circular codes.
enforcing and defying associativity, commutativity, totality, and strong noninvertibility for worst-case one-way functions. rabi and sherman [m. rabi, a. sherman, an observation on associative one-way functions in complexity theory, information processing letters 64 (5) (1997) 239-244; m. rabi, a. sherman, associative one-way functions: a new paradigm for secret-key agreement and digital signatures, tech. rep. cs-tr-3183/umiacs-tr-93-124, department of computer science, university of maryland, college park, md, 1993] proved that the hardness of factoring is a sufficient condition for there to exist one-way functions (i.e., p-time computable, honest, p-time noninvertible functions; this paper is in the worst-case model, not the average-case model) that are total, commutative, and associative but not strongly noninvertible. in this paper we improve the sufficient condition to pnp. we look at the four attributes used in rabi and sherman's seminal work on algebraic properties of one-way functions (see [m. rabi, a. sherman, an observation on associative one-way functions in complexity theory, information processing letters 64 (5) (1997) 239-244; m. rabi, a. sherman, associative one-way functions: a new paradigm for secret-key agreement and digital signatures, tech. rep. cs-tr-3183/umiacs-tr-93-124, department of computer science, university of maryland, college park, md, 1993]) and subsequent papers-strongness (of noninvertibility), totality, commutativity, and associativity-and for each attribute, we allow it to be required to hold, required to fail, or ''don't care''. in this categorization there are 3^4=81 potential types of one-way functions. we prove that each of these 81 feature-laden types stands or falls together with the existence of (plain) one-way functions.
approximation algorithms for forests augmentation ensuring two disjoint paths of bounded length. given a forest f=(v,e) and a positive integer d, we consider the problem of finding a minimum number of new edges e^' such that in the augmented graph h=(v,e@?e^') any pair of vertices can be connected by two vertex-disjoint paths of length @?d. we show that this problem and some of its variants are np-hard, and we present approximation algorithms with worst-case bounds 6 and 4. these algorithms can be implemented in o(|v|log|v|) time.
convergence of the diffusion method for weighted torus graphs using fourier analysis. this paper studies the diffusion method for the load balancing problem in the case of weighted torus graphs. closed form formulae for the optimum values of the edge weights are determined using local fourier analysis. it is shown that an extrapolated version of diffusion can become twice as fast for the stretched torus graphs.
generalising submodularity and horn clauses: tractable optimization problems defined by tournament pair multimorphisms. the submodular function minimization problem (sfm) is a fundamental problem in combinatorial optimization and several fully combinatorial polynomial-time algorithms have recently been discovered to solve this problem. the most general versions of these algorithms are able to minimize any submodular function whose domain is a set of tuples over any totally-ordered finite set and whose range includes both finite and infinite values. in this paper we demonstrate that this general form of sfm is just one example of a much larger class of tractable discrete optimization problems defined by valued constraints. these tractable problems are characterized by the fact that their valued constraints have an algebraic property which we call a tournament pair multimorphism. this larger tractable class also includes the problem of satisfying a set of horn clauses (horn-sat), as well as various extensions of this problem to larger finite domains.
a near optimal scheduler for on-demand data broadcasts. on-demand data broadcasting is a new and important technique for information dissemination. in this paper, we design and analyse a novel online scheduler balance for scheduling on-demand data broadcasts. balance has competitive ratio 6@dlog@d+o(@d^5^/^6), which improves significantly the previous best upper bound of @d+@d+2. we also prove that any online scheduler for the problem cannot have competitive ratio smaller than @d2ln@d-1. it follows that balance is optimal within a constant factor.
optimizing deletion cost for secure multicast key management. multicast and broadcast are efficient ways to deliver messages to a group of recipients in a network. due to the growing security concerns in various applications, messages are often encrypted with a secret group key. the key tree model which has been widely adopted maintains a set of keys in a tree structure so that in case of group member change, the group key can be updated in a secure and efficient way. in this paper, we focus on the updating cost incurred by member deletions. to implement a sequence of member deletions in any key tree, a certain number of encrypted messages need to be broadcast to accomplish the updates. our goal is to identify the best key tree which can minimize the worst-case deletion cost (i.e., the amortized cost over n member deletions). we prove that there is an optimal tree in which each internal node has at most five children and each internal node with at least one non-leaf child has exactly three children. based on these characterizations, we present a dynamic programming algorithm that computes an optimal key tree in o(n^2) time.
the complexity of uniform nash equilibria and related regular subgraph problems. we investigate the complexity of finding nash equilibria in which the strategy of each player is uniform on its support set. we show that, even for a restricted class of win-lose bimatrix games, deciding the existence of such uniform equilibria is an np-complete problem. our proof is graph-theoretical. motivated by this result, we also give np-completeness results for the problems of finding regular induced subgraphs of large size or regularity, which can be of independent interest.
seeing the trees and their branches in the network is hard. phylogenetic networks are a restricted class of directed acyclic graphs that model evolutionary histories in the presence of reticulate evolutionary events, such as horizontal gene transfer, hybrid speciation, and recombination. characterizing a phylogenetic network as a collection of trees and their branches has long been the basis for several methods of reconstructing and evaluating phylogenetic networks. further, these characterizations have been used to understand molecular sequence evolution on phylogenetic networks. in this paper, we address theoretical questions with regard to phylogenetic networks, their characterizations, and sequence evolution on them. in particular, we prove that the problem of deciding whether a given tree is contained inside a network is np-complete. further, we prove that the problem of deciding whether a branch of a given tree is also a branch of a given network is polynomially equivalent to that of deciding whether the evolution of a molecular character (site) on a network is governed by the infinite site model. exploiting this equivalence, we establish the np-completeness of both problems, and provide a parameterized algorithm that runs in time o(2^k^/^2n^2), where n is the total number of nodes and k is the number of recombination nodes in the network, which significantly improves upon the trivial brute-force o(2^kn) time algorithm for the problem. this reduction in time is significant, particularly when analyzing recombination hotspots.
analysis of set-up time models: a metric perspective. we consider model based estimates for set-up time. the general setting we are interested in is the following: given a disk and a sequence of read/write requests to certain locations, we would like to know the total time of transitions (set-up time) when these requests are served in an orderly fashion. the problem becomes nontrivial when we have, as is typically the case, only the counts of requests to each location rather then the whole input, and we can only hope to estimate the required time. models that estimate set-up time have been suggested and heavily used as far back as the sixties. however, not much theory exists to enable a qualitative understanding of such models. to this end we introduce several properties such as (i) super-additivity which means that the set-up time estimate decreases as the input data is refined (ii) monotonicity which means that more activity produces more set-up time, (iii) dominance which means that one model always produces higher estimates than a second model and (iv) approximation guarantees for the estimate with respect to the worst possible time, by which we can study different models. we provide criteria for super-additivity and monotonicity to hold for popular models such as the partial markov model (pmm). the criteria show that the estimate produced by these models will be monotone for any reasonable system. we also show that the independent reference model (irm) based estimate functions as a worst case estimate in the sense that the estimate is guaranteed to be at least half of the actual set-up time. we also show that it dominates the pmm based estimates. using our criteria we prove that pmm based estimates are always super additive when applied to the special metrics that correspond to seek times of disk drives. to establish our theoretical results we use the theory of finite metric spaces, and en route show a result of independent interest in that theory, which is a strengthening of a theorem of j.b. kelly [j.b. kelly, hypermetric spaces and metric transforms, in: o. shisha (ed.), inequalities iii, 1972, pp. 149-158] about the properties of metrics that are formed by concave functions on the line.
how many runs can a string contain? given a string x=x[1..n], a repetition of period p in x is a substring u^r=x[i+1..i+rp], p=|u|, r>=2, where neither u=x[i+1..i+p] nor x[i+1..i+(r+1)p+1] is a repetition. the maximum number of repetitions in any string x is well known to be @q(nlogn). a run or maximal periodicity of period p in x is a substring u^rt=x[i+1..i+rp+|t|] of x, where u^r is a repetition, t a proper prefix of u, and no repetition of period p begins at position i of x or ends at position i+rp+|t|+1. in 2000 kolpakov and kucherov showed that the maximum number @r(n) of runs in any string x[1..n] is o(n), but their proof was nonconstructive and provided no specific constant of proportionality. at the same time, they presented experimental data to prompt the conjecture: @r(n)
a randomized competitive algorithm for evaluating priced and/or trees. recently, charikar et al. investigated the problem of evaluating and/or trees, with non-uniform costs on its leaves, from the perspective of the competitive analysis. for an and/or tree t they presented a @m(t)-competitive deterministic polynomial time algorithm, where @m(t) is the number of leaves that must be read, in the worst case, in order to determine the value of t. furthermore, they proved that @m(t) is a lower bound on the deterministic competitiveness, which assures the optimality of their algorithm. the power of randomization in this context has remained as an open question. here, we take a step towards solving this problem by presenting a 56@m(t)-competitive randomized polynomial time algorithm. this contrasts with the best known lower bound @m(t)/2.
self-deployment of mobile sensors on a ring. mobile sensors can self-deploy in a purely decentralized and distributed fashion, so as to reach in a finite time a state of static equilibrium in which they uniformly cover the environment. we consider the self-deployment problem in a ring (e.g., a circular rim); in particular we investigate under what conditions the problem is solvable by a collection of identical sensors without a global coordinate system, however capable of determining the location (in their local coordinate system) of the other sensors within a fixed distance (called visibility radius). a self-deployment is exact if within finite time the distance between any two consecutive sensors along the ring is the same, d; it is @e-approximate if within finite time the distance between two consecutive sensors is between d-@e and d+@e. we prove that exact self-deployment is impossible if the sensors do not share a common orientation of the ring. this impossibility result holds even if the sensors have unlimited memory of the past, their visibility radius is unlimited, and all their actions, when active, are instantaneous. we thus consider the problem in an oriented ring. we prove that if the sensors know the desired final distance d, then exact self-deployment is possible. if the desired final distance d is not known, we prove that @e-approximate self-deployment is possible for any chosen @e>0. the proofs of these results are constructive. in each case we present a simple protocol that allows the sensors to achieve the claimed level of self-deployment. these positive results hold even if sensors are oblivious (i.e., have no memory of past actions and computations), asynchronous (i.e., a sensor becomes active at unpredictable times and the duration of its actions is unpredictable), and have limited visibility radius. our protocols can be employed, without modifications, on the perimeter of any convex region.
efficient sensor network design for continuous monitoring of moving objects. we study the problem of localizing and tracking multiple moving targets in wireless sensor networks, from a network design perspective i.e. towards estimating the least possible number of sensors to be deployed, their positions and operation characteristics needed to perform the tracking task. to avoid an expensive massive deployment, we try to take advantage of possible coverage overlaps over space and time, by introducing a novel combinatorial model that captures such overlaps. under this model, we abstract the tracking network design problem by a combinatorial problem of covering a universe of elements by at least three sets (to ensure that each point in the network area is covered at any time by at least three sensors, and thus being localized). we then design and analyze an efficient approximate method for sensor placement and operation, that with high probability and in polynomial expected time achieves a @q(logn) approximation ratio to the optimal solution. our network design solution can be combined with alternative collaborative processing methods, to suitably fit different tracking scenarios.
integration of a security type system into a program logic. type systems and program logics are often thought to be at opposing ends of the spectrum of formal software analyses. in this paper we show that a flow-sensitive type system ensuring non-interference in a simple while-language can be expressed through specialised rules of a program logic. in our framework, the structure of non-interference proofs resembles the corresponding derivations in a state-of-the-art security type system, meaning that the algorithmic version of the type system can be used as a proof procedure for the logic. we argue that this is important for obtaining uniform proof certificates in a proof-carrying code framework. we discuss in which cases the interleaving of approximative and precise reasoning allows us to deal with delimited information release. finally, we present ideas on how our results can be extended to encompass features of realistic programming languages such as java.
memoryless search algorithms in a network with faulty advice. in this paper, we present a randomized algorithm for a mobile agent to search for an item stored at a node t of a network, without prior knowledge of its exact location. each node of the network has a database that will answer queries of the form ''how do i find t?'' by responding with the first edge on a shortest path to t. it may happen that some nodes, called liars, give bad advice. we investigate a simple memoryless algorithm which follows the advice with some fixed probability q>1/2 and otherwise chooses a random edge. if the degree of each node and number of liars k are bounded, we show that the expected number of edges traversed by the agent before finding t is bounded from above by o(d+r^k), where d is the distance between the initial and target nodes and r=q1-q. we also show that this expected number of steps can be significantly improved for particular topologies such as the complete graph and the torus.
security types for dynamic web data. we describe a type system for the xd@p calculus of gardner and maffeis. an xd@p-network is a network of locations, where each location consists of both a data tree (which contains scripts and pointers to nodes in trees at different locations) and a process, for modeling process interaction, process migration and interaction between processes and data. our type system is based on types for locations, data and processes, expressing security levels. a tree can store data of different security level, independently from the security level of the enclosing location. the access and mobility rights of a process depend on the security level of the ''source'' location of the process itself, i.e. of the location where the process was in the initial network or where the process was created by the activation of a script. the type system enjoys type preservation under reduction (subject reduction). in consequence of subject reduction we prove the following security properties. in a well-typed xd@p-network, a process p whose source location is of level h can copy data of security level at most h and update data of security level less than h. moreover, the process p can only communicate data and go to locations of security level equal or less than h.
spatial-behavioral types for concurrency and resource control in distributed systems. we develop a notion of spatial-behavioral typing suitable to discipline concurrent interactions and resource usage in distributed object systems. our type structure reflects a resource sensitive model, where a parallel composition type operator expresses resource independence, a sequential composition type operator expresses resource synchronization, and a type modality expresses resource ownership. we model the intended computational systems using a concurrent object calculus. soundness of our type system is established using a logical relations technique, building on a interpretation of types as properties expressible in a spatial logic.
adaptive initialization algorithm for ad hoc radio networks with carrier sensing. we propose an algorithm for coordinating access to a shared broadcast channel in an ad hoc network of unknown size n. we reduce the runtime necessary to self-organize access to the channel over the previous algorithm of cai, lu and wang. the runtime of that algorithm is o(n). the goal of our work is to improve the constant factor in this estimation. apart from the experimental evidence of algorithm quality, we provide a rigorous probabilistic analysis of its behavior.
using bisimulation proof techniques for the analysis of distributed abstract machines. we illustrate the use of recently developed proof techniques for weak bisimulation by analysing a generic framework for the definition of distributed abstract machines based on a message-passing implementation. we first define this framework, and then focus on the algorithm which is used to route messages asynchronously to their destination. a first version of this algorithm can be analysed using the standard bisimulation up to expansion proof technique. we show that in a second, optimised version, rather complex behaviours appear, for which more sophisticated techniques, relying on termination arguments, are necessary to establish behavioural equivalence.
minimizing interference of a wireless ad-hoc network in a plane. we consider interference minimization in wireless ad-hoc networks. this is formulated as assigning a suitable transmission radius to each of the given points in the plane, so as to minimize the maximum number of transmission ranges overlapping any point. using ideas from computational geometry and @e-net theory, we attain an o(@d) bound for the maximum interference where @d is the interference of a uniform-radius ad-hoc network. this generalizes a result given in [p. von rickenbach, s. schmid, r. wattenhofer, a. zollinger, a robust interference model for wireless ad-hoc networks, in: proc. 5th international workshop on algorithms for wireless, mobile, ad hoc and sensor networks (wman), denver, colorado, usa, april 2005] for the special case of highway model (i.e., one-dimensional problem) to the two-dimensional case. we show how a distributed algorithm can achieve a slightly weaker bound. we also give a method based on quad-tree decomposition and bucketing that has another provable interference bound in terms of the ratio of the minimum distance to the radius of a uniform-radius ad-hoc network.
a timed semantics of orc. orc is a kernel language for structured concurrent programming. orc provides three powerful combinators that define the structure of a concurrent computation. these combinators support sequential and concurrent execution, and concurrent execution with blocking and termination. orc is particularly well-suited for task orchestration, a form of concurrent programming with applications in workflow, business process management, and web service orchestration. orc provides constructs to orchestrate the concurrent invocation of services while managing time-outs, priorities, and failures of services or communication. our previous work on the semantics of orc focused on its asynchronous behavior. the inclusion of time or the effect of delay on a computation had not been modeled. in this paper, we define an operational semantics of orc that allows reasoning about delays, which are introduced explicitly by time-based constructs or implicitly by network delays. we develop a number of identities among orc expressions and define an equality relation that is a congruence. we also present a denotational semantics in which the meaning of an orc program is a set of traces, and show that the two semantics are equivalent.
scheduling to maximize participation. we study a problem of scheduling client requests to servers. each client has a particular latency requirement at each server and may choose either to be assigned to some server in order to get serviced provided that her latency requirement is met, or not to participate in the assignment at all. from a global perspective, in order to optimize the performance of such a system, one would aim to maximize the number of clients that participate in the assignment. however, clients may behave selfishly in the sense that, each of them simply aims to participate in an assignment and get serviced by some server where her latency requirement is met with no regard to overall system performance. we model this selfish behavior as a strategic game, show how to compute pure nash equilibria efficiently, and assess the impact of selfishness on system performance. we also show that the problem of optimizing performance is computationally hard to solve, even in a coordinated way, and present efficient approximation and online algorithms.
on the limits of cache-oblivious rational permutations. permuting a vector is a fundamental primitive which arises in many applications. in particular, rational permutations, which are defined by permutations of the bits of the binary representations of the vector indices, are widely used. matrix transposition and bit-reversal are notable examples of rational permutations. in this paper we contribute a number of results regarding the execution of these permutations in cache hierarchies, with particular emphasis on the cache-oblivious setting. we first bound from below the work needed to execute a rational permutation with an optimal cache complexity. then, we develop a cache-oblivious algorithm to perform any rational permutation, which exhibits optimal work and cache complexities under the tall cache assumption. we finally show that for certain families of rational permutations (including matrix transposition and bit reversal) no cache-oblivious algorithm can exhibit optimal cache complexity for all values of the cache parameters. this latter result specializes the one proved by brodal and fagerberg for general permutations to the case of rational permutations, and provides further evidence that the tall cache assumption is often necessary to attain cache optimality in the context of cache-oblivious algorithms.
parametric synchronizations in mobile nominal calculi. we present and compare p-prisma and f-prisma, two parametric calculi that can be instantiated with different interaction policies, defined as synchronization algebras with mobility of names (sams). in particular, p-prisma is based on name transmission (p-sam), like @p-calculus, and thus exploits directional (input-output) communication only, while f-prisma is based on name fusion (f-sam), like fusion calculus, and thus exploits a more symmetric form of communication. however, p-prisma and f-prisma can easily accommodate many other high-level synchronization mechanisms than the basic ones available in @p-calculus and fusion, hence allowing for the development of a general meta-theory of mobile calculi. we define for both the labeled operational semantics and a form of strong bisimilarity, showing that the latter is compositional for any sam. we also discuss reduction semantics and weak bisimilarity. we give several examples based on heterogeneous sams, we investigate the case studies of @p-calculus and fusion calculus giving correspondence theorems, and we show how p-prisma can be encoded in f-prisma. finally, we show that basic categorical tools can help to relate and to compose sams and prisma processes in an elegant way.
theoretical advances in artificial immune systems. artificial immune systems (ais) constitute a relatively new area of bio-inspired computing. biological models of the natural immune system, in particular the theories of clonal selection, immune networks and negative selection, have provided the inspiration for ais algorithms. moreover, such algorithms have been successfully employed in a wide variety of different application areas. however, despite these practical successes, until recently there has been a dearth of theory to justify their use. in this paper, the existing theoretical work on ais is reviewed. after the presentation of a simple example of each of the three main types of ais algorithm (that is, clonal selection, immune network and negative selection algorithms respectively), details of the theoretical analysis for each of these types are given. some of the future challenges in this area are also highlighted.
weighted monadic datalog. based on monadic datalog, we introduce the concept of weighted monadic datalog over unranked trees. this provides a query language that can be used to extract quantitative information from semi-structured databases where the quantities are taken from some semiring s. we show that weighted monadic datalog is as expressive as weighted tree automata on unranked trees. moreover, we prove that a query can be evaluated efficiently on an unranked tree provided that (i) s is commutative and the underlying datalog program is non-circular or (ii) s is a finite and commutative @w-cpo semiring.
a polynomial nominal unification algorithm. nominal syntax includes an abstraction operator and a primitive notion of name swapping, that can be used to represent in a simple and natural way systems that include binders. nominal unification (i.e., solving @a-equality constraints between nominal terms) has applications in rewriting and logic programming, amongst others. it is decidable: urban, pitts and gabbay gave a nominal unification algorithm that finds the most general solution to a nominal matching or unification problem, if one exists. a naive implementation of this algorithm is exponential in time; here we describe an algorithm based on a graph representation of nominal terms with lazy propagation of swappings, and show that it is polynomial.
testing data processing-oriented systems from stream x-machine models. one of the great benefits of using a stream x-machine to specify a system is its associated testing method. under certain design for test conditions, this method produces a test suite that can determine the correctness of the implementation under test (iut), provided that the processing functions of the stream x-machine specification have been correctly implemented. the method was originally developed for controllable stream x-machines. a recent paper generalizes the original method by considering specifications that do not meet the controllability requirement. however, it is still required that a controllable stream x-machine model of the iut exists and the size of the test suite produced strongly depends on the (estimated) upper bound on the number of states of this controllable model. while this assumption is in general reasonable for most interactive systems, it may produce unmanageable test suites for even simple data processing-oriented applications. this paper provides a new variant of the stream x-machine based testing method that no longer depends on the size of a controllable model of the iut. in data processing-oriented applications, the new method can drastically reduce the size of the test suite produced at the expense of a (possibly) more complex generation process.
population size versus runtime of a simple evolutionary algorithm. evolutionary algorithms (eas) find numerous applications, and practical knowledge on eas is immense. in practice, sophisticated population-based eas employing selection, mutation and crossover are applied. in contrast, theoretical analysis of eas often concentrates on very simple algorithms such as the (1+1) ea, where the population size equals 1. in this paper, the question is addressed whether the use of a population by itself can be advantageous. a population-based ea that neither makes use of crossover nor any diversity-maintaining operator is investigated on an example function. it is shown that an increase of the population size by a constant factor decreases the expected runtime from exponential to polynomial. thereby, the best gap known so far is improved from superpolynomial vs. polynomial to exponential vs. polynomial. moreover, it is proved that the exponential and polynomial runtime bounds occur with a probability exponentially close to one if the population size is a constant (resp., a small polynomial). finally, a second example function, where only a small population leads to a polynomial runtime, and a hierarchy result on the appropriate population size are presented. the analyses show formally how the population size can lead to different attractors in the search space.
comparing evolutionary algorithms to the (1+1)-ea. in this paper, we study the conditions in which the random hill-climbing algorithm (1 + 1)-ea compares favorably to other evolutionary algorithms (eas) in terms of fitness function distribution at a given iteration and with respect to the average optimization time. our approach is applicable when the reproduction operator of an evolutionary algorithm is dominated by the mutation operator of the (1 + 1)-ea. in this case one can extend the lower bounds obtained for the expected optimization time of the (1 + 1)-ea to other eas based on the dominated reproduction operator. this method is demonstrated on the sorting problem with ham landscape and the exchange mutation operator. we consider several simple examples where the (1 + 1)-ea is the best possible search strategy in the class of the eas.
arity hierarchy for temporal logics. a major result concerning temporal logics is kamp's theorem which states that the pair of modalities ''until'' and ''since'' is expressively complete for the first-order fragment of the monadic logic over the linear-time canonical model of naturals. the paper concerns the expressive power of temporal logics over trees. the main result states that in contrast to kamp's theorem, for every n there is a modality of arity n definable by a monadic logic formula, which is not equivalent over trees to any temporal logic formula which uses modalities of arity less than n. its proof takes advantage of an instance of shelah's composition theorem.this result has interesting corollaries, for instance reproving that ctl^* and ectl^+ have no finite basis.
density elimination. density elimination, a close relative of cut elimination, consists of removing applications of the takeuti-titani density rule from derivations in gentzen-style (hypersequent) calculi. its most important use is as a crucial step in establishing standard completeness for syntactic presentations of fuzzy logics; that is, completeness with respect to algebras based on the real unit interval [0,1]. this paper introduces the method of density elimination by substitutions. for general classes of (first-order) hypersequent calculi, it is shown that density elimination by substitutions is guaranteed by known sufficient conditions for cut elimination. these results provide the basis for uniform characterizations of calculi complete with respect to densely and linearly ordered algebras. standard completeness follows for many first-order fuzzy logics using a dedekind-macneille-style completion and embedding.
abstract interpretation and types for systems biology. abstract interpretation is a theory of abstraction that has been introduced for the analysis of programs. in particular, it has proved useful for organizing the multiple semantics of a given programming language in a hierarchy corresponding to different detail levels, and for defining type systems for programming languages and program analyzers in software engineering. in this paper, we investigate the application of these concepts to systems biology formalisms. more specifically, we consider the systems biology markup language sbml, and the biochemical abstract machine biocham with its differential, stochastic, discrete and boolean semantics. we first show how all of these different semantics, except the differential one, can be formally related by simple galois connections. then we define three type systems: one for checking or inferring the functions of proteins in a reaction model, one for checking or inferring the activation and inhibition effects of proteins in a reaction model, and another one for checking or inferring the topology of compartments or locations. we show that the framework of abstract interpretation elegantly applies to the formalization of these further abstractions, and to the implementation of linear or quadratic time type checking as well as type inference algorithms. furthermore, we show a theorem of independence of the graph of activation and inhibition effects from the kinetic expressions in the reaction model, under general conditions. through some examples, we show that the analysis of biochemical models by type inference provides accurate and useful information. interestingly, such a mathematical formalization of the abstractions commonly used in systems biology already provides some guidelines for the extensions of biochemical reaction rule languages.
universality and programmability of quantum computers. manin, feynman, and deutsch have viewed quantum computing as a kind of universal physical simulation procedure. much of the writing about quantum logic circuits and quantum turing machines has shown how these machines can simulate an arbitrary unitary transformation on a finite number of qubits. the problem of universality has been addressed most famously in a paper by deutsch, and later by bernstein and vazirani as well as kitaev and solovay. the quantum logic circuit model, developed by feynman and deutsch, has been more prominent in the research literature than deutsch's quantum turing machines. quantum turing machines form a class closely related to deterministic and probabilistic turing machines and one might hope to find a universal machine in this class. a universal machine is the basis of a notion of programmability. the extent to which universality has in fact been established by the pioneers in the field is examined and this key notion in theoretical computer science is scrutinised in quantum computing by distinguishing various connotations and concomitant results and problems.
when-and how-can a cellular automaton be rewritten as a lattice gas? both cellular automata (ca) and lattice-gas automata (lg) provide finite algorithmic presentations for certain classes of infinite dynamical systems studied by symbolic dynamics; it is customary to use the terms 'cellular automaton' and 'lattice gas' for a dynamic system itself as well as for its presentation. the two kinds of presentation share many traits but also display profound differences on issues ranging from decidability to modeling convenience and physical implementability. following a conjecture by toffoli and margolus, it had been proved by kari that any invertible ca, at least up to two dimensions, can be rewritten as an isomorphic lg. but until now it was not known whether this is possible in general for noninvertible ca-which comprise ''almost all'' ca and represent the bulk of examples in theory and applications. even circumstantial evidence-whether in favor or against-was lacking. here, for noninvertible ca, (a) we prove that an lg presentation is out of the question for the vanishingly small class of surjective ones. we then turn our attention to all the rest-noninvertible and nonsurjective-which comprise all the typical ones, including conway's 'game of life'. for these (b) we prove by explicit construction that all the one-dimensional ones are representable as lg, and (c) we present and motivate the conjecture that this result extends to any number of dimensions. the tradeoff between dissipation rate and structural complexity implied by the above results have compelling implications for the thermodynamics of computation at a microscopic scale.
interference automata. we propose a computing model, the two-way optical interference automata (2oia), that makes use of the phenomenon of optical interference. we introduce this model to investigate the increase in power, in terms of language recognition, of a classical deterministic finite automaton (dfa) when endowed with the facility of interference. the question is in the spirit of two-way finite automata with quantum and classical states (2qcfa) [a. ambainis, j. watrous, two-way finite automata with quantum and classical states, theoret. comput. sci. 287 (1) (2002) 299-311] wherein the classical dfa is augmented with a quantum component of constant size. we test the power of 2oia against the languages mentioned in the above paper. we give efficient 2oia algorithms to recognize languages for which 2qcfa machines have been shown to exist, as well as languages whose status vis-a-vis 2qcfa has been posed as open questions. having a dfa as a component, it trivially recognizes regular languages. we show that our model can recognize all languages recognized by 1-way deterministic blind counter automata. finally we show the existence of a language that cannot be recognized by a 2oia but which can be recognized by an o(n^3) space turing machine.
uniformity and the taylor expansion of ordinary lambda-terms. we define the complete taylor expansion of an ordinary lambda-term as an infinite linear combination-with rational coefficients-of terms of a resource calculus similar to boudol's lambda-calculus with multiplicities (or with resources). in our resource calculus, all applications are (multi)linear in the algebraic sense, i.e. commute with linear combinations of the function or the argument. we study the collective behaviour of the beta-reducts of the terms occurring in the taylor expansion of any ordinary lambda-term, using, in a surprisingly crucial way, a uniformity property that they enjoy. as a corollary, we obtain (the main part of) a proof that this taylor expansion commutes with bohm tree computation, syntactically.
polyhedra genus theorem and euler formula: a hypermap-formalized intuitionistic proof. this article presents formalized intuitionistic proofs for the polyhedra genus theorem, the euler formula and a sufficient condition of planarity. they are based on a hypermap model for polyhedra and on formal specifications in the calculus of inductive constructions. first, a type of free maps is inductively defined from three atomic constructors. next, a hierarchy of types defined by invariants, with operations constrained by preconditions, is built on the free maps: hypermaps, orientated combinatorial maps and a central notion of quasi-hypermaps. besides, the proofs of their properties are established until the genus theorem and the euler formula, mainly using a simple induction principle based on the free map term algebra. finally, a constructive sufficient condition for polyhedra to be planar is set and proved. the whole process is assisted by the interactive coq proof system.
a dna computing inspired computational model. in this paper we propose a universal rewriting system whose computational steps closely resemble the manner in which nature computes double stranded dna molecules. the basic data structure is given by a couple of strings paired by a complementarity relation (such as the watson-crick one), and the rewriting rules have a biotechnological implementation as dna computing standard procedures. the antiparallel orientation of the formal strings laying on the double structure is taken into consideration, as in [g. franco, v. manca, an algorithmic analysis of dna structure, soft computing-a fusion of foundations, methodologies and applications 9 (10) (2005) 761-768] it was shown to be essential for some informational and computational aspects underlying the dna autoduplication process. the universality of such a system has been proved and the biotechnological details of a possible implementation have been outlined. moreover, the membrane system which turned out to be the natural context to describe our system in [g. franco, m. margenstern, computing by floating strings, in: n. busi, c. zandron (eds.), proceedings of the first workshop on membrane computing and biologically inspired process calculi (mecbic 2006), july 9, s. servolo, venice, italy, in: entcs, vol. 171(issue 2), july 2007, pp. 95-104] has been proposed here in more technical detail, and the announced extension work has been developed.
(mem)brane automata. we introduce the notion of a p automaton with marked membranes, a p"p"p automaton for short, which is an accepting variant of p systems. the concept is motivated by the theory of p systems, brane calculi, and the traditional concept of automata. in p systems with marked membranes, bio-molecules (proteins) are allowed to move through the membranes and to attach onto or to de-attach from the membranes. the membrane system evolves according to rules which are defined over multisets of proteins and describe the above actions. in addition to these features, the p automaton with marked membranes is able to consume inputs from its environment, i.e. multisets of proteins, which might influence the behaviour of the system. the result of the computation is the set of multiset sequences consumed by the skin membrane, supposing that the p"p"p automaton started functioning in the initial configuration and entered a final configuration at halting. we show that any recursively enumerable language can be obtained as the language accepted by a p"p"p automaton modulo a simple computable mapping.
relating continuous and discrete pepa models of signalling pathways. pepa and its semantics have recently been extended to model biological systems. in order to cope with massive quantities of processes (as is usually the case when considering biological reactions) the model is interpreted in terms of a small set of coupled ordinary differential equations (odes) instead of a large state space continuous time markov chain (ctmc). so far the relationship between these two semantics of pepa had not been established. this is the goal of the present paper. after introducing a new extension of pepa, denoted pepa+@p, that allows models to capture both mass action law and bounded capacity law cooperations, the relationship between these two semantics is demonstrated. the result relies on kurtz's theorem that expresses that a set of odes can be, in some sense, considered as the limit of pure jump markov processes.
a uniform family of tissue p systems with cell division solving 3-col in a linear time. several examples of the efficiency of cell-like p systems regarding the solution of np-complete problems in polynomial time can be found in the literature(obviously, trading space for time). recently, different new models of tissue-like p systems have received much attention from the scientific community. in this paper we present a linear-time solution to an np-complete problem from graph theory, the 3-coloring problem, and we discuss the suitability of tissue-like p systems as a framework to address the efficient solution to intractable problems.
generalized communicating p systems. this paper considers a generalization of various communication models based on the p system paradigm where two objects synchronously move across components. more precisely, the model uses blocks of four cells such that pairs of objects from two input cells travel together to target output cells. it is shown that the model introduced, based on interactions between blocks, is complete, being able to generate all recursively enumerable sets of natural numbers. it is also proven that completeness is achievable by using a minimal interaction between blocks, i.e. every pair of cells is the input or output for at most one block. it is also shown that the concepts introduced in this paper to define the model may be simulated by more particular communication primitives, including symport, antiport and uniport rules. this enables us to automatically translate a system using interaction rules in any of minimal symport, minimal antiport or conditional uniport p systems.
the metabolic algorithm for p systems: principles and applications. metabolic p systems, shortly mp systems, are a special class of p systems, introduced for expressing biological metabolism. an mp system evolution is given by a metabolic algorithm, a deterministic strategy, where the classical viewpoint on metabolic dynamics, in terms of ordinary differential equations, is replaced by suitable generalizations of chemical principles. the basic principles of mp systems are given and their main aspects are explained by means of examples of biological modeling. a new kind of regulation mechanism is outlined, which could be the basis for a more efficient construction of computational models from experimental data of specific metabolic processes.
processes of membrane systems with promoters and inhibitors. membrane systems (with promoters and inhibitors) are a computational model inspired by the way living cells are divided by membranes into compartments where chemical reactions may take place. we consider synchrony and asynchrony between executed reactions in the computations of such systems using petri nets and their processes as a formal behavioural model. we first discuss different definitions of individual computational steps, and show how they can be rendered within the petri net domain by assigning all transitions localities corresponding to the compartments, and using activator and inhibitor arcs. the non-sequential semantics of the resulting nets is formalised through processes based on occurrence nets augmented with additional information about localities and activator/inhibitor arcs. such processes provide a convenient tool for analysing synchrony and asynchrony in the executions of membrane systems and shed light on the causal relationships between the reactions taking place.
on the decidability and complexity of the structural congruence for beta-binders. beta-binders is a recent process calculus developed for modelling and simulating biological systems. as usual for process calculi, the semantic definition heavily relies on a structural congruence. the treatment of the structural congruence is essential for implementation. we present a subset of the calculus for which the structural congruence is decidable and a subset for which it is also efficiently solvable. the obtained results are a first step towards implementations.
a simple calculus for proteins and cells. the use of process calculi to represent biological systems has led to the design of different formalisms such as brane calculi and @k-calculus. both have proved to be useful to model different types of biological systems. as an attempt to unify the formalisms, we introduce the bio@k-calculus, a simple calculus for describing proteins and cells, in which bonds are represented by means of shared names and interactions are modelled at the domain level. in bio@k-calculus, protein-protein interactions have to be at most binary and cell interactions have to fit with sort constraints. in this contribution we define the semantics of bio@k-calculus, analyse its properties, discuss the expressivity of the calculus by modelling two significant examples-a signalling pathway and a virus infection-and study an implementation in milner's @p-calculus.
computational self-assembly. the object of this paper is to probe the computational limits of an applied concurrent language called @k. this language describes how agents can bind and modify each other. it is meant as a syntactic medium to build, discuss and execute descriptions of cellular signalling pathways. however, it can be studied independently of its intended interpretation, and this is what we are doing here. specifically, we define a reduction of @k to a fragment where interactions can involve at most two agents at a time. the translation relies on an implicit causality analysis which permits escaping deadlocks. it incurs only a linear blow up in the number of rules. its correctness is spelt out in terms of the existence of a specific weak bisimulation and is proved in detail. to compensate for the binary restriction, one allows components to create unique names. when using acyclic rules, this additional facility of name creation is not needed and @k can be reduced to a binary form as is.
membrane systems with proteins embedded in membranes. membrane computing is a biologically inspired computational paradigm. motivated by brane calculi we investigate membrane systems which differ from conventional membrane systems by the following features: (1) biomolecules (proteins) can move through the regions of the systems, and can attach onto (and de-attach from) membranes, and (2) membranes can evolve depending on the attached molecules. the evolution of membranes is performed by using rules that are motivated by the operation of pinocytosis (the pino rule) and the operation of cellular dripping (the drip rule) that take place in living cells. we show that such membrane systems are computationally universal. we also show that if only the second feature is used then one can generate at least the family of parikh images of the languages generated by programmed grammars without appearance checking (which contains non-semilinear sets of vectors). if, moreover, the use of pino/drip rules is non-cooperative (i.e., not dependent on the proteins attached to membranes), then one generates a family of sets of vectors that is strictly included in the family of semilinear sets of vectors. we also consider a number of decision problems concerning reachability of configurations and boundness.
membrane computing and brane calculi. old, new, and future bridges. after a short discussion about similarities and dissimilarities of membrane computing and brane calculi, insisting mainly on some recent ideas of bridging the two areas of research, one recalls some details concerning certain classes of p systems based on brane calculi operations. several open problems are formulated in this context.
decision problems in membrane systems with peripheral proteins, transport and evolution. transport of substances and communication between compartments are fundamental biological processes, often mediated by the presence of complementary proteins attached to the surfaces of membranes. within compartments, substances are acted upon by local biochemical rules. inspired by this behaviour we present a model based on membrane systems, with objects attached to the sides of the membranes and floating objects that can be moved between the regions of the system. moreover, in each region there are evolution rules that rewrite the transported objects, mimicking chemical reactions. we investigate qualitative properties, like configuration reachability, in relation to the use of cooperative or non-cooperative evolution and transport rules and in the contexts of free- and maximal-parallel evolution.
elementary differences among jump classes. it is shown that th(h"1)1, where h"m is the upper semi-lattice of all high"m computably enumerable (c.e.) degrees for m>0, giving a first elementary difference among the highness hierarchies of the c.e. degrees.
semi-formal verification of the steady state behavior of mixed-signal circuits by sat-based property checking. in this article, a verification methodology for mixed-signal circuits is presented that can easily be integrated into industrial design flows. the proposed verification methodology is based on formal verification methods. a vhdl behavioral description of a mixed-signal circuit is transformed into a discrete model and then verified using well-established tools from formal digital verification. using the presented methodology, a much higher coverage of the functionality of a mixed-signal circuit can be achieved than with simulation based verification methods. the approach has already been successfully applied to industrial mixed-signal circuits.
embedding finite automata within regular expressions. regular expressions and their extensions have become a major component of industry-oriented specification languages such as ieee psl [ieee standard for property specification language (psl). ieee std 1850(tm)-2005]. the model checking procedure of regular expression based formulas, involves constructing an automaton which runs in parallel with the model. in this paper we re-examine the automata construction. we propose an algorithm that allows an intermediate representation mixing both regular expressions and automata. this representation can be thought of as plugging an automaton inside a regular expression, to replace an existing sub-expression. in order to be verified, the intermediate representation is then translated into another automaton, resulting in a set of automata running in parallel. a key feature of this algorithm is that the plug-in automaton is independent of the regular expression from which it originated, and thus can be used in several different properties. we demonstrate the usefulness of our method by providing a set of applications. we show how the use of our method allows modularity and flexibility of the automata construction, and can increase expressiveness when seres are mixed with ctl. we give two applications for which it significantly reduces the size of the automata built for formulas, thus reducing the overall run time of the model checking procedure.
on model checking multiple hybrid views. many applications, for instance the ms .net global assembly cache (gac), are naturally expressed as 3-valued models where an additional third truth value models uncertainty or under-specification. an example of under-specification is that a component in a gac may or may not have a main method. models described in this manner can then be analyzed to refute or verify properties about the concrete systems they intend to model. this approach to system validation traditionally considers only one model at a time, even though this model may evolve if subjected to analysis. many applications, however, benefit from or require the simultaneous consideration of multiple models of systems. we mention here requirements from different stake holders, and data drawn from federated databases. this paper therefore builds the mathematical foundations for property verification and refutation as applied to finitely many 3-valued models, where each model is endowed with states - possibly named by nominals, also known as hybrid constraints - labelled transitions, and atomic propositions. specifically, we show that deciding whether a finite set of models has a common concrete system (consistency) is typically in ptime, and that deciding whether a common concrete system satisfies a formula of the hybrid mu-calculus (satisfiability), and its dual (validity), are exptime-complete. we propose sound and efficient approximations of these exptime-complete checks by synthesizing and checking ''summary'' models. these approximations are optimal if all models are deterministic. finally, we point out that such optimality of summary models is unattainable whenever not all summarized models are deterministic.
a probabilistic alternative to regression suites. automated regression suites are essential in developing large applications, while maintaining reasonable quality and timetables. the main argument against the automation of regression suites, in addition to the cost of creation and maintenance, is the observation that if you run the same test many times, it becomes increasingly less likely to find bugs. to alleviate such problems, a new regression suite practice, using random test generators to create regression suites on-the-fly, is becoming more common. in this practice, instead of maintaining tests, we generate test suites on-the-fly by choosing several specifications and generating a number of tests from each specification. we describe techniques for optimizing random generated test suites. we first show how the set cover greedy algorithms, commonly used for selecting tests for regression suites, may be adapted to selecting specifications for randomly generated regression suites. we then introduce a new class of greedy algorithms, referred to as future-aware greedy algorithms. the algorithms are computationally efficient and generate more effective regression suites.
an automatic abstraction technique for verifying featured, parameterised systems. a general technique combining model checking and abstraction is presented that allows property based analysis of systems consisting of an arbitrary number of featured components. we show how parameterised systems can be specified in a guarded command form with constraints placed on variables which occur in guards. we prove that results that hold for a small number of components can be shown to scale up. we then show how featured systems can be specified in a similar way, by relaxing constraints on guards. the main result is a generalisation theorem for featured systems which we apply to two well known examples.
automatic generation of path conditions for concurrent timed systems. this paper presents an automatic method for calculating the path condition for programs with real time constraints. we model concurrent systems using timed transition systems and translate them into extended timed automata. then an acyclic extended timed automaton is constructed and the path condition is calculated backwards over it. this method can be used for semiautomatic verification of a unit of code in isolation, i.e., without providing the exact values of parameters with which it is called. it can also be used for test case generation for real-time systems. such a symbolic model checking algorithm was implemented previous in the pet system [e. gunter, d. peled, unit checking: symbolic model checking for a unit of code, verification: theory and practice 2003, essays dedicated to zohar manna on the occasion of his 64th birthday, lecture notes in computer science, vol. 2772, springer, 548-567] for untimed systems. our method can also be used for the automatic generation of test cases for unit testing. the current generalization of the calculation of path condition for the timed case turns out to be quite tricky, since not only the selected path contributes to the path condition, but also timing constraints of alternative choices in the code.
efficient sat-based bounded model checking for software verification. this paper discusses our methodology for formal analysis and automatic verification of software programs. it is applicable to a large subset of the c programming language that includes pointer arithmetic and bounded recursion. we consider reachability properties, in particular whether certain assertions or basic blocks are reachable in the source code, or whether certain standard property violations can occur. we perform this analysis via a translation to a boolean circuit representation based on modeling basic blocks. the program is then analyzed by a back-end sat-based bounded model checker, where each unrolling is mapped to one step in a block-wise execution of the program. the main contributions of this paper are as follows: (1) use of basic block-based unrollings with sat-based bounded model checking of software programs. this allows us to take advantage of sat-based learning inherent to the best performing bounded model checkers. (2) various heuristics customized for models automatically generated from software, allowing a more efficient sat-based analysis. (3) a prototype tool called f-soft has been implemented using our methodology. we present experimental results based on multiple case studies including a c-based implementation of a network protocol, and compare the performance gains using the proposed heuristics.
consistency of discrete bayesian learning. bayes' rule specifies how to obtain a posterior from a class of hypotheses endowed with a prior and the observed data. there are three fundamental ways to use this posterior for predicting the future: marginalization (integration over the hypotheses w.r.t. the posterior), map (taking the a posteriori most probable hypothesis), and stochastic model selection (selecting a hypothesis at random according to the posterior distribution). if the hypothesis class is countable, and contains the data generating distribution (this is termed the ''realizable case''), strong consistency theorems are known for the former two methods in a sequential prediction framework, asserting almost sure convergence of the predictions to the truth as well as loss bounds. we prove corresponding results for stochastic model selection, for both discrete and continuous observation spaces. as a main technical tool, we will use the concept of a potential: this quantity, which is always positive, measures the total possible amount of future prediction errors. precisely, in each time step, the expected potential decrease upper bounds the expected error. we introduce the entropy potential of a hypothesis class as its worst-case entropy, with regard to the true distribution. our results are proven within a general stochastic online prediction framework, that comprises both online classification and prediction of non-i.i.d. sequences.
leading strategies in competitive on-line prediction. we start from a simple asymptotic result for the problem of on-line regression with the quadratic loss function: the class of continuous limited-memory prediction strategies admits a ''leading prediction strategy'', which not only asymptotically performs at least as well as any continuous limited-memory strategy, but also satisfies the property that the excess loss of any continuous limited-memory strategy is determined by how closely it imitates the leading strategy. more specifically, for any class of prediction strategies constituting a reproducing kernel hilbert space, we construct a leading strategy, in the sense that the loss of any prediction strategy whose norm is not too large is determined by how closely it imitates the leading strategy. this result is extended to the loss functions given by bregman divergences and by strictly proper scoring rules.
finite relational structure models of topological spaces and maps. we define the notion of homotopy pushout in the category of binary reflexive relational structures and explore its basic properties. we construct finite models in this category, of spaces and maps in top with a view to developing systematic methods in this regard.
kernel methods for learning languages. this paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane in that space. such mappings can often be represented flexibly with string kernels, with the additional benefit of computational efficiency. the paradigm inspected can thus be viewed as that of using kernel methods for learning languages. we initiate the study of the linear separability of automata and languages by examining the rich class of piecewise-testable languages. we introduce a subsequence feature mapping to a hilbert space and prove that piecewise-testable languages are linearly separable in that space. the proof makes use of word combinatorial results relating to subsequences. we also show that the positive definite symmetric kernel associated to this embedding is a rational kernel and show that it can be computed in quadratic time using general-purpose weighted automata algorithms. our examination of the linear separability of piecewise-testable languages leads us to study the general problem of separability with other finite regular covers. we show that all languages linearly separable under a regular finite cover embedding, a generalization of the subsequence embedding we use, are regular. we give a general analysis of the use of support vector machines in combination with kernels to determine a separating hyperplane for languages and study the corresponding learning guarantees. our analysis includes several additional linear separability results in abstract settings and partial characterizations for the linear separability of the family of all regular languages.
topology in information theory in topology. we prove that timed capacity in information theory is a euclidean continuous function of noise. this is a result based on topological methods that benefits work in information theory. then we show that binary timing capacity is a measure of distance which yields the euclidean topology on the unit interval, despite the fact that it does not satisfy the triangle inequality. this is a result based on information theoretic methods that benefits topology. these results have important applications in an area known as information hiding, in the study of quantum communication and in domain theory. they appear to raise fundamental questions about the nature of distance itself.
computational complexity of determining which statements about causality hold in different space-time models. causality is one of the most fundamental notions of physics. it is therefore important to be able to decide which statements about causality are correct in different models of space-time. in this paper, we analyze the computational complexity of the corresponding decision problems. in particular, we show that: *for minkowski space-time, the decision problem is as difficult as tarski's decision problem for elementary geometry, while *for a natural model of primordial space-time, the corresponding decision problem is of the lowest possible complexity among all possible space-time models.
causal set topology. the causal set theory (cst) approach to quantum gravity is motivated by the observation that, associated with any causal spacetime (m,g) is a poset (m,@?), with the order relation @? corresponding to the spacetime causal relation. spacetime in cst is assumed to have a fundamental atomicity or discreteness, and is replaced by a locally finite poset, the causal set. in order to obtain a well defined continuum approximation, the causal set must possess the requisite intrinsic topological and geometric properties that characterise a continuum spacetime in the large. the study of causal set topology is thus dictated by the nature of the continuum approximation. we review the status of causal set topology and present some new results relating poset and spacetime topologies. the hope is that in the process, some of the ideas and questions arising from cst will be made accessible to the larger community of computer scientists and mathematicians working on posets.
unsupervised slow subspace-learning from stationary processes. we propose a method of unsupervised learning from stationary, vector-valued processes. a projection to a low-dimensional subspace is selected on the basis of an objective function which rewards data-variance and penalizes the variance of the velocity vector, thus exploiting the short-time dependencies of the process. we prove bounds on the estimation error of the objective in terms of the @b-mixing coefficients of the process. it is also shown that maximizing the objective minimizes an error bound for simple classification algorithms on a generic class of learning tasks. experiments with image recognition demonstrate the algorithms ability to learn geometrically invariant feature maps.
lawson topology of the space of formal balls and the hyperbolic topology. let (x,d) be a metric space and bx=xxr denote the partially ordered set of (generalized) formal balls in x. we investigate the topological structures of bx, in particular the relations between the lawson topology and the product topology. we show that the lawson topology coincides with the product topology if (x,d) is a totally bounded metric space, and show examples of spaces for which the two topologies do not coincide in the spaces of their formal balls. then, we introduce a hyperbolic topology, which is a topology defined on a metric space other than the metric topology. we show that the hyperbolic topology and the metric topology coincide on x if and only if the lawson topology and the product topology coincide on bx.
information systems revisited - the general continuous case. in this paper a new notion of continuous information system is introduced. it is shown that the information systems of this kind generate exactly the continuous domains. the new information systems are of the same logic-oriented style as the information systems first introduced by scott in 1982: they consist of a set of tokens, a consistency predicate and an entailment relation satisfying a set of natural axioms. it is shown that continuous information systems are closely related to abstract bases. indeed, both categories are equivalent. since it is known that the categories of abstract bases and/or continuous domains are equivalent, it follows that the category of continuous information systems is also equivalent to that of continuous domains. in applications, mostly subclasses of continuous domains are considered. for example, the domains have to be pointed, algebraic, bounded-complete or fs. conditions are presented that, when fulfilled by a continuous information system, force the generated domain to belong to the required subclass. in most cases the requirements are not only sufficient but also necessary.
apartness, compactness and nearness. we investigate constructively a pre-apartness structure that is classically important in the characterisation of compact proximity spaces, and that may help identify a good constructive notion of compactness for not-necessarily-uniform apartness spaces. in addition, we produce what may be the right notion of ''nearness'' in the theory of apartness spaces.
on computational environments of topological spaces. as has been disclosed by k. martin, a large number of important topological spaces do not have any continuous domain as their computational model. so it is of interest to study new kinds of pragmatic computational environments so as to model more topological spaces. in this paper we focus on bounded complete continuous posets with enough maximal points, which are shown to be a good choice for computational environments of tychonoff spaces with no directed complete model. it is proved that the maximal point space of a choquet complete weak domain is also choquet complete. furthermore, it is proved that x is a tychonoff space iff x has a bounded complete weak domain environment. and it is also shown that hausdorff compactifications of tychonoff spaces can be realized via some of their computational environments.
on the possibility of learning in reactive environments with arbitrary dependence. we address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions, i.e. environments more general than (po)mdps. the task for an agent is to attain the best possible asymptotic reward where the true generating environment is unknown, but belongs to a known countable family of environments. we find some sufficient conditions on the class of environments under which an agent exists which attains the best asymptotic reward for any environment in the class. we analyze how tight these conditions are, and how they relate to different probabilistic assumptions known in reinforcement learning and related fields, such as markov decision processes and mixing conditions.
static space-times naturally lead to quasi-pseudometrics. the standard 4-dimensional minkowski space-time of special relativity is based on the 3-dimensional euclidean metric. in 1967, h. busemann showed that similar static space-time models can be based on an arbitrary metric space. in this paper, we search for the broadest possible generalization of a metric under which a construction of a static space-time leads to a physically reasonable space-time model. it turns out that this broadest possible generalization is related to the known notion of a quasi-pseudometric.
modeling time and topology for animation and visualization with examples on parametric geometry. the art of animation relies upon modeling objects that change over time. a sequence of static images is displayed to produce an illusion of motion. even for simple cases, a careful analysis exposes that formal topological guarantees are often lacking. this absence of rigor can result in subtle, but significant, topological flaws. a new modeling approach is proposed to integrate topological rigor with a continuous model of time. examples will be given for bezier curves, while indicating extensions to a richer class of parametric curves and surfaces. applications to scientific visualization for molecular modeling are discussed. prototype animations are available for viewing over the web.
metric spaces and fs-domains. in this article we give general conditions on a metric space to insure that the poset of closed formal balls is an fs-domain.
the zariski spectrum as a formal geometry. we choose formal topology to deal in a basic manner with the zariski spectra of commutative rings and their structure sheaves. by casting prime and maximal ideals in a secondary role, we thus wish to prepare a constructive and predicative framework for abstract algebraic geometry. in contrast to the classical approach, neither points nor stalks need occur, let alone any instance of the axiom of choice. as compared with the topos-theoretic treatments that may be rendered predicative as well, the road we follow is built from more elementary material. the formal counterpart of the structure sheaf which we present first is our guiding example for a notion of a sheaf on a formal topology. we next define the category of formal geometries, a natural abstraction from that of locally ringed spaces. this allows us to eventually phrase and prove, still within the language of opens and sections, the universal property of the zariski spectrum. our version appears to be the only one that is explicitly point-free.
fine hierarchies and m-reducibilities in theoretical computer science. this is a survey of results about versions of fine hierarchies and many-one reducibilities that appear in different parts of theoretical computer science. these notions and related techniques play a crucial role in understanding complexity of finite and infinite computations. we try not only to present the corresponding notions and facts from the particular fields but also to identify the unifying notions, techniques and ideas.
finitary formal topologies and stone's representation theorem. we study the concept of finitary formal topology, a point-free version of a topological space with a basis of compact open subsets. the notion of finitary formal topology is defined from the perspective of the basic picture (introduced by the second author) and thus it is endowed with a binary positivity relation. as an application, we prove a constructive version of stone's representation theorem for distributive lattices. we work within the framework of a minimalist foundation (as proposed by maria emilia maietti and the second author). both inductive and co-inductive methods are used in most proofs.
enriched categories and models for spaces of evolving states. partially ordered sets, causets, partially ordered spaces, and their local counterparts are now often used to model systems in computer science and theoretical physics. the order models 'time' which is often not globally given. in this setting, directed paths are important objects of study, as they correspond to an evolving state or particle traversing the system. we model both the 'space' and the directed paths by a simplicially enriched category, and show how to adapt some classical constructions to produce a differential graded enrichment.
scanning integer matrices by means of two rectangular windows. this paper deals with the reconstruction of integer matrices from rectangular scans. in particular, since the case of one rectangular scan has already been treated in a previous paper, we consider two rectangular scans, given as two integer matrices, and we investigate the existence and the possibility of reconstruction of a third binary matrix which is compatible with them. furthermore, our inspection implies interesting side results about the number of these reconstructed matrices for different choices of the dimensions of two windows used in the input scans.
on the complexity of bandwidth allocation in radio networks. we define and study an optimization problem that is motivated by bandwidth allocation in radio networks. because radio transmissions are subject to interference constraints in radio networks, physical space is a common resource that the nodes have to share in such a way, that concurrent transmissions do not interfere. the bandwidth allocation problem we study under these constraints is the following. given bandwidth (traffic) demands between the nodes of the network, the objective is to schedule the radio transmissions in such a way that the traffic demands are satisfied. the problem is similar to a multicommodity flow problem, where the capacity constraints are replaced by the more complex notion of non-interfering transmissions. we provide a formal specification of the problem that we call round weighting. by modeling non-interfering radio transmissions as independent sets, we relate the complexity of round weighting to the complexity of various independent set problems (e.g. maximum weight independent set, vertex coloring, fractional coloring). from this relation, we deduce that in general, round weighting is hard to approximate within n^1^-^@e (n being the size of the radio network). we also provide polynomial (exact or approximation) algorithms e.g. in the following two cases: (a) when the interference constraints are specific (for instance for a network whose vertices belong to the euclidean space), or (b) when the traffic demands are directed towards a unique node in the network (also called gathering, analogous to single commodity flow).
reconstruction of binary matrices under fixed size neighborhood constraints. using a dynamic programming approach, we prove that a large variety of matrix reconstruction problems from two projections can be solved in polynomial time whenever the number of rows (or columns) is fixed. we also prove some complexity results for several problems concerning the reconstruction of a binary matrix when a neighborhood constraint occurs.
reconstruction of convex lattice sets from tomographic projections in quartic time. filling operations are procedures which are used in discrete tomography for the reconstruction of lattice sets having some convexity constraints. many algorithms have been published giving fast implementations of these operations, and the best running time [s. brunetti, a. daurat, a. kuba, fast filling operations used in the reconstruction of convex lattice sets, in: proc. of dgci 2006, in: lecture notes in comp. sci., vol. 4245, 2006, pp. 98-109] is o(n^2logn) time, where n is the size of projections. in this paper we improve this result by providing an implementation of the filling operations in o(n^2). as a consequence, we reduce the time-complexity of the reconstruction algorithms for many classes of lattice sets having some convexity properties. in particular, the reconstruction of convex lattice sets satisfying the conditions of gardner-gritzmann [r.j. gardner, p. gritzmann, discrete tomography: determination of finite sets by x-rays, trans. amer. math. soc. 349 (1997) 2271-2295] can be performed in o(n^4)-time.
large independent sets in general random intersection graphs. we investigate the existence and efficient algorithmic construction of close to optimal independent sets in random models of intersection graphs. in particular, (a) we propose a new model for random intersection graphs (g"n","m","p"->) which includes the model of [m. karonski, e.r. scheinerman, k.b. singer-cohen, on random intersection graphs: the subgraph problem, combinatorics, probability and computing journal 8 (1999), 131-159] (the ''uniform'' random intersection graph models) as an important special case. we also define an interesting variation of the model of random intersection graphs, similar in spirit to random regular graphs. (b) for this model we derive exact formulae for the mean and variance of the number of independent sets of size k (for any k) in the graph. (c) we then propose and analyse three algorithms for the efficient construction of large independent sets in this model. the first two are variations of the greedy technique while the third is a totally new algorithm. our algorithms are analysed for the special case of uniform random intersection graphs. our analyses show that these algorithms succeed in finding close to optimal independent sets for an interesting range of graph parameters.
the supercover of an m-flat is a discrete analytical object. the aim of this paper is to show that the supercover of an m-flat (i.e. a euclidean affine subspace of dimension m) in euclidean n-space is a discrete analytical object. the supercover of a euclidean object f is a discrete object consisting of all the voxels that intersect f. a discrete analytical object is a set of discrete points that is defined by a finite set of inequalities. a method to determine the inequalities defining the supercover of an m-flat is provided.
on image reconstruction algorithms for binary electromagnetic geotomography. in this paper we discuss the selected image reconstruction methods of binary tomography in the context of their application to geophysical imaging. we restrict our considerations to a discrete version of high-frequency electromagnetic geotomography, which we label as binary electromagnetic geotomography (beg). basically, such an imaging technique may be applied to detect subsurface anomalies (air-filled voids) whose attenuation coefficient is very low (nearly zero-value) and considerably different from that for the background. the assumption for a binary representation of the image to be reconstructed substantially relaxes image reconstruction problems related to ill-posedness that comes from an intrinsic limitation of an angular range of projections. we test two algorithms for binary tomography, where the penalty term is based on the markov random field (mrf) model. the mean-field reference distribution and mean-field annealing are applied to estimate the global maximizer of the gibbs-boltzmann distribution associated with the objective function. we also apply the projected gradient algorithm that uses a binary steering. very efficient implementations of the algorithms are also given. the numerical results are presented for noise-free, noisy, and real data.
finding a minimum medial axis of a discrete shape is np-hard. the medial axis is a classical representation of digital objects widely used in many applications. however, such a set of balls may not be optimal: subsets of the medial axis may exist without changing the reversivility of the input shape representation. in this article, we first prove that finding a minimum medial axis is an np-hard problem for the euclidean distance. then, we compare two algorithms which compute an approximation of the minimum medial axis, one of them providing bounded approximation results.
discrete sets with minimal moment of inertia. we analyze the moment of inertia i(s), relative to the center of gravity, of finite plane lattice sets s. we classify these sets according to their roundness: a set s is rounder than a set t if i(s)
high level communication functionalities for wireless sensor networks. in this paper we show how to establish a reliable and efficient high level communication system in a randomly deployed network of sensors equipped with directional antennas. this high level communication system enables the programming of the sensor network using high level communication functionalities without the burden of taking care of their physical capacities (low range, unidirectional links, single frequency, presence of collisions, etc.). the high level communication functionalities we offer include point-to-point communication, point-to-area communication, and one-to-all communication. the basic idea to implement this system is to simulate a virtual network that emerges from the ad-hoc network using self-organization, self-discovery and collaborative methods. we also analyse the efficiency, scalability and robustness of the proposed protocols.
on the polyhedral complexity of the integer points in a hyperball. let b^n be a hyperball in r^n, n>=2, and denote b"z^n=b^n@?z^n. define polyhedral facet complexity of b"z^n as fc(b"z^n)=min"p{f"n"-"1(p)} where p is an enclosing polyhedron for b"z^n (i.e., p"z=p@?z^n=b"z^n) and f"n"-"1(p) is the number of the (n-1)-facets of p. analogously, define polyhedral vertex complexity of b"z^n as vc(b"z^n)=min"p{f"0(p)} where p is an enclosing polyhedron for b"z^n and f"0(p) is the number of the 0-facets (vertices) of p. upper bounds for fc(b"z^n) follow from a well-known bound for the number of facets and vertices of the convex hull of b"z^n [i. barany, d.g. larman, the convex hull of the integer points in a large ball, math. ann. 312 (1998) 167-181]. in this note we provide the first nontrivial lower bounds on fc(b"z^n) and vc(b"z^n).
convex decomposition of u-polygons. when parallel x-rays are considered in any finite set u of directions, switching components with respect to u can be constructed. this is true for u@?r^n, and also for any finite set of lattice directions. r.j. gardner raised the problem of looking for a characterization of switching components. in 2001, l. hajdu and r. tijdeman gave an answer by proving that a switching component is always the linear combination of switching elements. though splendid, this result fails to be a characterization theorem inside the class of convex bodies, meaning that the switching element of the linear combination could be not convex even if the switching component is convex. the purpose of this paper is to investigate the problem in the plane, where a convex switching component with respect to u is a u-polygon. we prove that a u-polygon can always be decomposed as a linear sum inside the class of u-polygons.
the steiner tree problem on graphs: inapproximability results. the steiner tree problem on weighted graphs seeks a minimum weight subtree containing a given subset of the vertices (terminals). we show that it is np-hard to approximate the steiner tree problem within a factor 96/95. our inapproximability results are stated in a parametric way, and explicit hardness factors would be improved automatically by providing gadgets and/or expanders with better parameters.
a 3d fully parallel surface-thinning algorithm. the thinning is an iterative layer by layer erosion until only the ''skeletons'' of the objects are left. this paper presents a thinning algorithm for extracting medial surfaces from 3d binary pictures. the strategy which is used is called fully parallel, which means that the same parallel operator is applied at each iteration. an efficient implementation of the proposed algorithm on conventional sequential computers is given and the topological correctness for (26, 6) binary pictures is proved.
a randomized algorithm for the joining protocol in dynamic distributed networks. we describe a randomized algorithm for assigning neighbours to vertices joining a dynamic distributed network. the aim of the algorithm is to maintain connectivity, low diameter and constant vertex degree. on joining each vertex donates a constant number of tokens to the network. these tokens contain the address of the donor vertex. the tokens make independent random walks in the network. a token can be used by any vertex it is visiting to establish a connection to the donor vertex. this allows joining vertices to be allocated a random set of neighbours although the overall vertex membership of the network is unknown. the network we obtain in this way is robust under adversarial deletion of vertices and edges and actively reconnects itself. one model we consider is a network constructed in this fashion, in which vertices join but never leave. if t is the size of the network, then the diameter of the network is o(logt) for all t, with high probability. as an example of the robustness of this model, suppose an adversary deletes edges from the network leaving components of size at least t^1^/^2^+^@d. with high probability the network reconnects itself by replacing lost edges using tokens from the token pool.
deterministic monotone algorithms for scheduling on related machines. we consider the problem of designing monotone deterministic algorithms for scheduling tasks on related machines in order to minimize the makespan. several recent papers showed that monotonicity is a fundamental property to design truthful mechanisms for this scheduling problem. we give both theoretical and experimental results. first of all we consider the case of two machines when speeds of the machines are restricted to be powers of a given constant c>0. we prove that algorithm largest processing time (lpt) is monotone for any c>=2 while it is not monotone for c@?1.78; algorithm list scheduling (ls), instead, is monotone only for c>2. in the case of m>2 machines we restrict our attention to the class of ''greedy-like'' monotone algorithms defined in [vincenzo auletta, roberto de prisco, paolo penna, giuseppe persiano, deterministic truthful approximation mechanisms for scheduling related machines, in: proceedings of 21st annual symposium on theoretical aspects of computer science. stacs '04, in: lecture notes in computer science, vol. 2996, springer, 2004, pp. 608-619]. it has been shown that greedy-like monotone algorithms can be used to design a family of 2+@e-approximate truthful mechanisms. in particular, in [vincenzo auletta, roberto de prisco, paolo penna, giuseppe persiano, deterministic truthful approximation mechanisms for scheduling related machines, in: proceedings of 21st annual symposium on theoretical aspects of computer science. stacs '04, in: lecture notes in computer science, vol. 2996, springer, 2004, pp. 608-619], the greedy-like algorithm uniform is proposed and it is proved that it is monotone when machine speeds are powers of a given integer constant c>0. in this paper we propose a new algorithm, called uniform_rr, that is still monotone when speeds are powers of a given integer constant c>0 and we prove that its approximation factor is not worse than that of uniform. we also experimentally compare the performance of uniform, uniform_rr, lpt, and several other monotone and greedy-like heuristics.
on the reconstruction of binary and permutation matrices under (binary) tomographic constraints. the paper studies the problem of reconstructing binary matrices constrained by binary tomographic information. we prove new np-hardness results that sharpen previous complexity results in the realm of discrete tomography but also allow applications to related problems for permutation matrices. hence our results can be interpreted in terms of other combinatorial problems including the queens' problem.
minimal non-deletable sets and minimal non-codeletable sets in binary images. the concepts of strongly 8-deletable and strongly 4-deletable sets of 1s in binary images on the 2d cartesian grid were introduced by ronse in the mid-1980s to formalize the connectivity preservation conditions that parallel thinning algorithms are required to satisfy. in this paper we call these sets deletable and codeletable, respectively. to establish that a proposed parallel thinning algorithm for binary images on the 2d cartesian grid preserves 8-(4-)connected foreground components and 4-(8-)connected background components, it is enough to prove that the set of 1s which are changed to 0s at each pass of the algorithm is always a deletable (codeletable) set. ronse established results that are very useful in this context for proving that a finite set d of 1s is deletable or codeletable. in particular, he showed that d and its proper subsets are all codeletable in a binary image if each singleton and each pair of 8-adjacent pixels in d is codeletable. he further showed that d and its proper subsets are all deletable in a binary image if (1) each singleton and each pair of 4-adjacent pixels in d is deletable, and (2) no set of 2, 3, or 4 pairwise 8-adjacent pixels that is an 8-connected foreground component of the image is entirely contained in d. in the 1990s and early 2000s analogous results were obtained by hall, ma, gau, and the author for binary images on the 2d hexagonal grid, the 3d cartesian and face-centered cubic grids, and the 4d cartesian grid. this paper extends the above-mentioned work to binary images on almost any polytopal complex whose union is n-dimensional euclidean space, for n@?4. our main results generalize and unify the corresponding results of the earlier work.
additivity obstructions for integral matrices and pyramids. in discrete tomography there are two related notions of interest: h-uniqueness and h-additivity of finite subsets of n^m, which are defined for certain finite sets h of linear subspaces of r^m. one knows complete sets of obstructions for h-uniqueness (bad h-configurations) and for h-additivity (weakly bad h-configurations). the classical case, when h is the set of coordinate axes in r^2, is well known. let h"m denote the set of the m coordinate hyperplanes of r^m. the following question was raised in [p.c. fishburn, j.c. lagarias, j.a. reeds, l.a. shepp, sets uniquely determined by projections on axes ii. discrete case, discrete math. 91 (1991) 149-159]. is there an upper bound on the weights of the bad h"m-configurations one needs to consider to determine h"m-uniqueness (m>=3) of an arbitrary set in n^m? this question can be asked for other sets h of linear subspaces and also for h-additivity. the answer to this question, in the case of uniqueness, is known when h is a set of lines. in this paper we answer this question for uniqueness and additivity in the case of h"3. we show that there is no upper bound on the weights of the bad configurations (resp. weakly bad configurations) one needs to consider to determine h"3-uniqueness (resp. h"3-additivity).
on isoperimetrically optimal polyforms. in the plane, the way to enclose the most area with a given perimeter and to use the shortest perimeter to enclose a given area, is always to use a circle. if we replace the plane by a regular tiling of it, and construct polyforms i.e. shapes as sets of tiles, things become more complicated. we need to redefine the area and perimeter measures, and study the consequences carefully. a spiral construction often provides, for every integer number of tiles (area), a shape that is most compact in terms of the perimeter or boundary measure; however it may not exhibit all optimal shapes. we characterize in this paper all shapes that have both shortest boundaries and maximal areas for three common planar discrete spaces.
a new model for selfish routing. in this work, we introduce and study a new, potentially rich model for selfish routing over non-cooperative networks, as an interesting hybridization of the two prevailing such models, namely the kpmodel [e. koutsoupias, c.h. papadimitriou, worst-case equilibria, in: g. meinel, s. tison (eds.), proceedings of the 16th annual symposium on theoretical aspects of computer science, in: lecture notes in computer science, vol. 1563, springer-verlag, 1999, pp. 404-413] and the wmodel [j.g. wardrop, some theoretical aspects of road traffic research, proceedings of the of the institute of civil engineers 1 (pt. ii) (1952) 325-378]. in the hybrid model, each of nusers is using a mixed strategy to ship its unsplittable traffic over a network consisting of m parallel links. in a nash equilibrium, no user can unilaterally improve its expected individual cost. to evaluate nash equilibria, we introduce quadratic social cost as the sum of the expectations of the latencies, incurred by the squares of the accumulated traffic. this modeling is unlike the kp model, where social cost [e. koutsoupias, c.h. papadimitriou, worst-case equilibria, in: g. meinel, s. tison (eds.), proceedings of the 16th annual symposium on theoretical aspects of computer science, in: lecture notes in computer science, vol. 1563, springer-verlag, 1999, pp. 404-413] is the expectation of the maximum latency incurred by the accumulated traffic; but it is like the w model since the quadratic social cost can be expressed as a weighted sum of expected individual costs. we use the quadratic social cost to define quadratic coordination ratio. here are our main findings: *quadratic social cost can be computed in polynomial time. this is unlike the #p-completeness [d. fotakis, s. kontogiannis, e. koutsoupias, m. mavronicolas, p. spirakis, the structure and complexity of nash equilibria for a selfish routing game, in: p. widmayer, f. triguero, r. morales, m. hennessy, s. eidenbenz, r. conejo (eds.), proceedings of the 29th international colloquium on automata, languages and programming, in: lecture notes in computer science, vol. 2380, springer-verlag, 2002, pp. 123-134] of computing social cost for the kp model. *for the case of identical users and identical links, the fully mixed nash equilibrium [m. mavronicolas, p. spirakis, the price of selfish routing, algorithmica 48 (1) (2007) 91-126], where each user assigns positive probability to every link, maximizes quadratic social cost. *as our main result, we present a comprehensive collection of tight, constant (that is, independent of m and n), strictly less than 2, lower and upper bounds on the quadratic coordination ratio for several, interesting special cases. some of the bounds stand in contrast to corresponding super-constant bounds on the coordination ratio previously shown in [a. czumaj, b. vocking, tight bounds for worst-case equilibria, acm transactions on algorithms 3 (1) (2007); e. koutsoupias, m. mavronicolas, p. spirakis, approximate equilibria and ball fusion, theory of computing systems 36 (6) (2003) 683-693; e. koutsoupias, c.h. papadimitriou, worst-case equilibria, in: g. meinel, s. tison (eds.), proceedings of the 16th annual symposium on theoretical aspects of computer science, in: lecture notes in computer science, vol. 1563, springer-verlag, 1999, pp. 404-413; m. mavronicolas, p. spirakis, the price of selfish routing, algorithmica 48 (1) (2007) 91-126] for the kp model.
a framework for generating some discrete sets with disjoint components by using uniform distributions. discrete tomography deals with the reconstruction of discrete sets from few projections. assuming that the set to be reconstructed belongs to a certain class of discrete sets with some geometrical properties is a commonly used technique to reduce the number of possibly many different solutions of the same reconstruction problem. the average performance of reconstruction algorithms are often tested on such classes by choosing elements of a given class from uniform random distributions. this paper presents a general framework for generating discrete sets with disjoint connected components using uniform distributions. especially, the uniform random generation of hv-convex discrete sets and q-convex discrete sets according to the size of the minimal bounding rectangle are discussed.
a finite set of functions with an exptime-complete composition problem. we exhibit a finite family of functions over a finite set (i.e. a finite algebra), such that the problem whether a given function can be obtained as a composition of the members of this family (i.e. is a member of the clone generated by the algebra) is exptime-complete.
time separations of cyclic event rule systems with min-max timing constraints. the analysis of the time separations of events is a fundamental problem in the design and evaluation of discrete event systems. important progresses have been made based on the event rule system model in the last decade. the existing results for event rule systems with min and max constraints can be summarized briefly as: the exact evaluation of time separations for acyclic systems is np-complete; for cyclic systems, the structural condition of being tightly coupled is sufficient for long-term time separations of events to be bounded. in this paper, we establish a necessary and sufficient structural boundedness condition-uniformity for cyclic event rule systems with both min and max constraints. tightly coupled systems are shown to be a special class of uniform systems. the well-known cas algorithm for finding bounds on long-term time separations is adapted to find finite bounds for uniform systems. our results are obtained by exploring the algebraic structures guiding the evolution of the systems.
subword histories and associated matrices. the basic numerical quantity investigated in this paper is |w|"u, the number of occurrences of a word u as a scattered subword of a word w. arithmetical combinations of such quantities yield a so-called subword history. we investigate the information content of subword histories. reducing subword histories to linear ones, as well as the recently introduced parikh matrices, will be important tools. simple polynomial formulas for computing the value of a subword history for arbitrary powers of a word are obtained.
on the bandwidth of 3-dimensional hamming graphs. this paper presents strategies for improving the known upper and lower bounds for the bandwidth of hamming graphs (k"n)^d and [0,1]^d. our labeling strategy lowers the upper bound on the bandwidth of the continuous hamming graph, [0,1]^3, from .5 to .4497. a lower bound of .4439 on bw([0,1]^3) follows from known isoperimetric inequalities and a related dynamic program is conjectured to raise that lower bound to 4/9=.4444.... in particular, showing the power of our method, we prove that the bandwidth of k"6xk"6xk"6 is exactly 101.
main-memory triangle computations for very large (sparse (power-law)) graphs. finding, counting and/or listing triangles (three vertices with three edges) in massive graphs are natural fundamental problems, which have recently received much attention because of their importance in complex network analysis. here we provide a detailed survey of proposed main-memory solutions to these problems, in a unified way. we note that previous authors have paid surprisingly little attention to space complexity of main-memory solutions, despite its both fundamental and practical interest. we therefore detail space complexities of known algorithms and discuss their implications. we also present new algorithms which are time optimal for triangle listing and beats previous algorithms concerning space needs. they have the additional advantage of performing better on power-law graphs, which we also detail. we finally show with an experimental study that these two algorithms perform very well in practice, allowing us to handle cases which were previously out of reach.
parallel time and space upper-bounds for the subset-sum problem. three new parallel scalable algorithms for solving the subset-sum problem in o(np(c-w"m"i"n)) time and o(n+c) space in the pram model are presented, where n is the number of objects, c is the capacity, w"m"i"n is the smallest weight and p is the number of processors. these time and space bounds are better than the direct parallelization of bellman's algorithm, which was the most efficient known result.
lower bounds and new constructions on secure group communication schemes. this paper presents both the theoretical and practical aspects of secure group communication schemes. we pointed out that multiple revocation is a fundamentally time-consuming task in secure group communication, by establishing lower bounds for broadcast encryption and group key distribution schemes. we showed that they are o(n) for be and o(n/m) for gkd respectively, where m is storage requirement and n is the number of users. thus, they are clearly far more costly than the ideal log bound. in practice, we designed a new broadcast encryption scheme rbe that actually achieves these lower bounds. rbe is shown to outperform most efficient be schemes in mass revocation. we discuss the influence of join as well as the feasibility of adding it in be schemes by means of performing full updating or overprovisioning.
on complexity functions of infinite words associated with generalized dyck languages. in this article, we construct a family of infinite words, generated by countable automata and also generated by substitutions over infinite alphabets, closely related to parenthesis languages and we study their complexity functions. we obtain a family of binary infinite words m^(^b^), indexed on the number b>=1 of parenthesis types, such that the growth order of the complexity function of m^(^b^) is n(logn)^2 if b=1 and n^1^+^l^o^g^"^2^"^b^b if b>=2.
exponential lower bounds on the size of constant-depth threshold circuits with small energy complexity. a complexity measure for threshold circuits, called the energy complexity, has been proposed to measure an amount of energy consumed during computation in the brain. biological neurons need more energy to transmit a ''spike'' than not to transmit one, and hence the energy complexity of a threshold circuit is defined as the number of gates in the circuit that output ''1'' during computation. since the firing activity of neurons in the brain is quite sparse, the following question arises: what boolean functions can or cannot be computed by threshold circuits with small energy complexity. in the paper, we partially answer the question, that is, we show that there exists a trade-off among three complexity measures of threshold circuits: the energy complexity, size, and depth. the trade-off implies an exponential lower bound on the size of constant-depth threshold circuits with small energy complexity for a large class of boolean functions.
universal automata and nfa learning. the aim of this paper is to develop a new algorithm that, with a complete sample as input, identifies the family of regular languages by means of nondeterministic finite automata. it is a state-merging algorithm. one of its main features is that the convergence (which is proved) is achieved independently from the order in which the states are merged, that is, the merging of states may be done ''randomly''.
tiling problems, automata, and tiling graphs. this paper continues the investigation of tiling problems via formal languages, which was begun in papers by merlini, sprugnoli, and verri. those authors showed that certain tiling problems could be encoded by regular languages, which lead automatically to generating functions and other combinatorial information on tilings. we introduce a method of simplifying the dfa's recognizing these language, which leads to bijective proofs of certain tiling identities. we apply these ideas to some other tiling problems, including three-dimensional tilings and tilings with triangles and rhombi. we also study graph-theoretic variations of these tiling problems.
game chromatic index of graphs with given restrictions on degrees. given a graph g and an integer k, two players alternatively color the edges of g using k colors so that adjacent edges get different colors. the game chromatic index@g"g^'(g) is the minimum k for which the first player has a strategy that ensures that all edges of g get colored. the trivial bounds are @d(g)@?@g"g^'(g)@?2@d(g)-1, where @d(g) denotes the maximal degree of g. lam, shiu, and xu and, independently, bartnicki and grytczuk asked whether there is a constant c such that @g"g^'(g)@?@d(g)+c for every graph g. we show that the answer is in the negative by constructing graphs g such that @g"g^'(g)>=1.008@d(g) and @d(g)->~. on the other hand, we show that for every @m>0 there is @e>0 such that for any graph g with @d(g)>=(1/2+@m)v(g), we have @g"g^'(g)@?(2-@e)@d(g), where v(g) denotes the number of vertices of g.
equitable list colorings of planar graphs without short cycles. a graph g is equitably k-choosable if, for any k-uniform list assignment l, g is l-colorable and each color appears on at most @?|v(g)|k@? vertices. a graph g is equitably k-colorable if g has a proper k-vertex coloring such that the sizes of any two color classes differ by at most 1. in this paper, we prove that every planar graph g is equitably k-choosable and equitably k-colorable if one of the following conditions holds: (1) g is triangle-free and k>=max{@d(g),8}; (2) g has no 4- and 5-cycles and k>=max{@d(g),7}.
fault-tolerant embedding of paths in crossed cubes. the crossed cube cq"n is an important variant of the hypercube q"n and possesses many desirable properties for interconnection networks. this paper shows that in cq"n with f"v faulty vertices and f"e faulty edges there exists a fault-free path of length @? between any two distinct fault-free vertices for each @? satisfying 2^n^-^1-1@?@?@?2^n-f"v-1 provided that f"v+f"e@?n-3, where the lower bound of @? and the upper bound of f"v+f"e are tight for some n. moreover, this result improves the known result that cq"n is (n-3)-hamiltonian connected.
testing whether a digraph contains h-free k-induced subgraphs. a subgraph induced by k vertices is called a k-induced subgraph. we prove that determining if a digraph g contains h-free k-induced subgraphs is @w(n^2)-evasive. then we construct an @e-tester to test this property. (an @e-tester for a property @p is guaranteed to distinguish, with probability at least 2/3, between the case of g satisfying @p and the case of g being @e-far from satisfying @p.) the query complexity of the @e-tester is independent of the size of the input digraph. an (@e,@d)-tester for a property @p is an @e-tester for @p that is furthermore guaranteed to accept with probability at least 2/3 any input that is @d-close to satisfying @p. this paper presents an (@e,@d)-tester for whether a digraph contains h-free k-induced subgraphs.
arbitrary pattern formation by asynchronous, anonymous, oblivious robots. from an engineering point of view, the problem of coordinating a set of autonomous, mobile robots for the purpose of cooperatively performing a task has been studied extensively over the past decade. in contrast, in this paper we aim to understand the fundamental algorithmic limitations on what a set of autonomous mobile robots can or cannot achieve. we therefore study a hard task for a set of weak robots. the task is for the robots in the plane to form any arbitrary pattern that is given in advance. this task is fundamental in the sense that if the robots can form any pattern, they can agree on their respective roles in a subsequent, coordinated action. the robots are weak in several aspects. they are anonymous; they cannot explicitly communicate with each other, but only observe the positions of the others; they cannot remember the past; they operate in a very strong form of asynchronicity. we show that the tasks that such a system of robots can perform depend strongly on their common agreement about their environment, i.e. the readings of their environment sensors. if the robots have no common agreement about their environment, they cannot form an arbitrary pattern. if each robot has a compass needle that indicates north (the robot world is a flat surface, and compass needles are parallel), then any odd number of robots can form an arbitrary pattern, but an even number cannot (in the worst case). if each robot has two independent compass needles, say north and east, then any set of robots can form any pattern.
a dynamic data structure for top-k queries on uncertain data. in an uncertain data sets=(s,p,f) where s is the ground set consisting of n elements, p:s->[0,1] a probability function, and f:s->r a score function, each element i@?s with score f(i) appears independently with probability p(i). the top-k query on s asks for the set of k elements that has the maximum probability of appearing to be the k elements with the highest scores in a random instance of s. computing the top-k answer on a fixed s is known to be easy. in this paper, we consider the dynamic problem, that is, how to maintain the top-k query answer when s changes, including element insertions and deletions in the ground set s, changes in the probability function p and in the score function f. we present a fully dynamic data structure that handles an update in o(klogn) time, and answers a top-j query in o(logn+j) time for any j@?k. the structure has o(n) size and can be constructed in o(nlogk) time. as a building block of our dynamic structure, we present an algorithm for the all-top-k problem, that is, computing the top-j answers for all j=1,...,k, which may be of independent interest.
computational complexity of quantified boolean formulas with fixed maximal deficiency. the paper investigates the computational complexity of quantified boolean formulas with fixed maximal deficiency. the satisfiability problem for quantified boolean formulas with maximal deficiency 1 is shown to be solvable in polynomial time. for k>=1, it is shown that true formulas with fixed maximal deficiency k have models in which all boolean functions can be represented as cnf formulas over at most 2^4^k^/^3 universal variables. as a consequence, the satisfiability problem for qcnf formulas with fixed maximal deficiency is in np and for fixed deficiency the minimal falsity problem is in d^p. for two subclasses of quantified boolean formulas with pspace-complete evaluation problem, qehorn and qe2-cnf , we show that for fixed deficiency the minimal falsity problem can be decided in polynomial time.
on varieties of meet automata. eilenberg's variety theorem gives a bijective correspondence between varieties of languages and varieties of finite monoids. the second author gave a similar relation between conjunctive varieties of languages and varieties of semiring homomorphisms. in this paper, we add a third component to this result by considering varieties of meet automata. we consider three significant classes of languages, two of them consisting of reversible languages. we present conditions on meet automata and identities for semiring homomorphisms for their characterization.
dense open-shop schedules with release times. we study open-shop scheduling problems with job release times. the objective is to minimize the makespan. dense schedules, easy to construct, are often used as approximate solutions. performance ratios of the makespans from dense schedules and that of the optimal schedule of the problem are used to evaluate the quality of approximate schedules. it is conjectured (proved for a limited number of machines) that this performance ratio is bounded above by (2-1/m) for m-machine open-shop problems without job release times. in this paper, we extend the conjecture to open-shop problems with job release times. the results proved in this paper are: 1. dense schedule performance ratio is bounded above by 2 for three-machine open-shop problems with job release times; 2. the conjectured performance ratio upper bound of 5/3 is proved for two special cases of three-machine open-shop problems with job release times; 3. a performance ratio upper bound of 7/4 is proved for three-machine problems.
monotonicity in digraph search problems. in this paper, we study the monotonicity and complexity of five digraph search problems: directed searching, mixed directed searching, internal directed searching, internal strong searching, and internal weak searching. in the first three search problems, both searchers and intruder must follow the edge directions when they move along edges. in the internal strong search problem, the intruder must move in the edge directions but searchers need not. in the internal weak search problem, searchers must move in the edge directions but the intruder need not. there are three actions for searchers in the first two search problems: placing, removing and sliding, and there are only two actions for searchers in the last three internal search problems: placing and sliding. note that the internal strong searching is a ''strong'' version of the internal directed searching, the internal weak searching is a ''weak'' version of the internal directed searching, and the internal edge searching is an analogy of the internal directed searching on undirected graphs. we prove that the first three problems are monotonic and the last two problems are non-monotonic, respectively. it is interesting that the internal directed searching is monotonic while the internal strong searching, the internal weak searching and the internal edge searching are all non-monotonic. we also show that the first four problems are np-complete and the last problem is np-hard. we solve the open problem on whether a non-monotonic searching problem can be np-complete.
the 2-radius and 2-radiian problems on trees. in this paper, we consider two facility location problems on tree networks. one is the 2-radius problem, whose goal is to partition the vertex set of the given network into two non-empty subsets such that the sum of the radii of these two induced subgraphs is minimum. the other is the 2-radiian problem, whose goal is to partition the network into two non-empty subsets such that the sum of the centdian values of these two induced subgraphs is minimum. we propose an o(n)-time algorithm for the 2-radius problem on trees and an o(nlogn)-time algorithm for the 2-radiian problem on trees, where n is the number of vertices in the given tree.
solving structured linear systems with large displacement rank. linear systems with structures such as toeplitz, vandermonde or cauchy-likeness can be solved in o@?(@a^2n) operations, where n is the matrix size, @a is its displacement rank, and o@? denotes the omission of logarithmic factors. we show that for such matrices, this cost can be reduced to o@?(@a^@w^-^1n), where @w is a feasible exponent for matrix multiplication over the base field. the best known estimate for @w is @w
online unit clustering: variations on a theme. online unit clustering is a clustering problem where classification of points is done in an online fashion, but the exact location of clusters can be modified dynamically. we study several variants and generalizations of the online unit clustering problem, which are inspired by variants of packing and scheduling problems in the literature.
fault-free hamiltonian cycles in twisted cubes with conditional link faults. the n-dimensional twisted cube, denoted by tq"n, a variation of the hypercube, possesses some properties superior to the hypercube. in this paper, assuming that each vertex is incident with at least two fault-free links, we show that tq"n can tolerate up to 2n-5 edge faults, while retaining a fault-free hamiltonian cycle. the result is optimal with respect to the number of edge faults tolerated.
arbitrage opportunities across sponsored search markets. we model and study arbitrage across sponsored search markets, created by search engines. we identify and focus on traffic arbitrage and click arbitrage by auctioneers. we derive and characterize equilibria of such arbitrage behaviors across multiple markets.
bincoloring. we introduce a new problem that was motivated by a (more complicated) problem arising in a robotized assembly environment. the bin coloring problem is to pack unit size colored items into bins, such that the maximum number of different colors per bin is minimized. each bin has size b@?n. the packing process is subject to the constraint that at any moment in time at most q@?n bins are partially filled. moreover, bins may only be closed if they are filled completely. we settle the computational complexity of the problem and design an approximation algorithm for a natural version which gives a solution whose value is at most one greater than the optimal one. we also investigate the existence of competitive online algorithms, which must pack each item without knowledge of any future items. we prove an upper bound of 3q-1 and a lower bound of 2q for the competitive ratio of a natural greedy-type algorithm, and show that surprisingly a trivial algorithm which uses only one open bin has a strictly better competitive ratio of 2q-1. moreover, we show that any deterministic algorithm has a competitive ratio @w(q) and that randomization does not improve this lower bound even when the adversary is oblivious.
new results for finding common neighborhoods in massive graphs in the data stream model. we consider the problem of finding pairs of vertices that share large common neighborhoods in massive graphs. we give lower bounds for randomized, two-sided error algorithms that solve this problem in the data-stream model of computation. our results correct and improve those of buchsbaum, giancarlo, and westbrook [on finding common neighborhoods in massive graphs, theoretical computer science, 299 (1-3) 707-718 (2004)]
algorithms for finding the weight-constrained k longest paths in a tree and the length-constrained k maximum-sum segments of a sequence. in this work, we obtain the following new results: -given a tree t=(v,e) with a length function @?:e->r and a weight function w:e->r, a positive integer k, and an interval [l,u], the weight-constrainedklongest paths problem is to find the k longest paths among all paths in t with weights in the interval [l,u]. we show that the weight-constrainedklongest paths problem has a lower bound @w(vlogv+k) in the algebraic computation tree model and give an o(vlogv+k)-time algorithm for it. -given a sequence a=(a"1,a"2,...,a"n) of numbers and an interval [l,u], we define the sum and length of a segment a[i,j] to be a"i+a"i"+"1+...+a"j and j-i+1, respectively. the length-constrainedkmaximum-sum segments problem is to find the k maximum-sum segments among all segments of a with lengths in the interval [l,u]. we show that the length-constrainedkmaximum-sum segments problem can be solved in o(n+k) time.
pattern matching with pair correlation distance. in pattern matching with pair correlation distance problem, the goal is to find all occurrences of a pattern p of length m, in a text t of length n, where the distance between them is less than a threshold k. for each text location i, the distance is defined as the number of different kinds of mismatched pairs (&alpha;,&beta;), between p and t[i ...i + m]. we present an algorithm with running time of $o\left(min\{\left|\sigma_p\right|^2 n \log m,n \!\left({m \log m}\right)^\frac{2}{3}\}\right)\!$ for this problem. another interesting problem is the one-side pair correlation distance where it is desired to find all occurrences of p where the number of mismatched characters in p is less than k. for this problem, we present an algorithm with running time of $o\left(min\{\left|\sigma_p\right| n \log m,n\right.\left.\sqrt{m \log m}\}\right)$.
heuristic algorithms for hadamard matrices with two circulant cores. we design heuristic algorithms to construct hadamard matrices with two circulant cores. this hard combinatorial problem can be formulated in terms of objective functions of several binary variables, so that heuristic methodologies can be used. our algorithms are based on local and tabu search and they use information on the geometry of the objective function landscapes. in addition, we use the supplementary difference sets formalism to detect when solutions of a special structure exist. using these algorithms we have computed at least one hadamard matrix with two circulant cores of the sixteen orders 56, 60, 64, 68, 72, 76, 80, 84, 88, 92, 96, 100, 104, 108, 112, 116. in particular, the hadamard matrix with two circulant cores of order 116 is constructed here for the first time, indeed it was accidentally reported as known in an earlier paper.
efficient on-line repetition detection. a repetition is a nonempty string of the form x^q, where q>=2. given a string s character by character and the value of q, the on-line repetition detection problem is to detect and report the first repetition in s, if it exists, in an on-line manner. leung, peng and ting first studied the problem for q=2 and gave an o(mlog^2m) time algorithm (refer to [h.-f. leung, z. peng, h.-f. ting, an efficient algorithm for online square detection, theoretical computer science 363 (1) (2006) 69-75]), where m is the ending position of the first repetition in s. in this paper, we improve the above cited work by reducing the time complexity to o(mlog@b), where @b is the number of distinct characters in the first m characters of s. moreover, we also solve the problem for q>=3 with the same time complexity.
a new framework for the design and analysis of identity-based identification schemes. constructing an identification scheme is one of the fundamental problems in cryptography, and is very useful in practice. an identity-based identification (ibi) scheme allows a prover to identify himself to a public verifier who knows only the claimed identity of the prover and some public information. in this paper, we propose a new framework for both the design and analysis of ibi schemes. our approach works in an engineering way. we first identify an ibi scheme as the composition of two building blocks, and then show that, with different security properties of these building blocks, the corresponding ibi schemes can achieve security against impersonation under different levels of attacks, namely, passive attack (id-imp-pa), active attack (id-imp-aa) or concurrent attack (id-imp-ca). in particular, we show that an id-imp-pa secure ibi scheme can be built if there exists a trapdoor weak-one-more relation and an honest verifier zero-knowledge proof with special soundness, while an id-imp-aa and id-imp-ca secure ibi scheme can be built if there exists a trapdoor strong-one-more relation and a witness dualism proof with special soundness (wd-ss). this new framework can capture ibi construction techniques that are not captured by other known frameworks. it also helps to construct new and efficient schemes. we demonstrate this by proposing two new ibi schemes, one achieving id-imp-pa, and the other one achieving both id-imp-aa and id-imp-ca, and neither of them can be captured by existing frameworks.
modelling co-transcriptional cleavage in the synthesis of yeast pre-rrna. in this paper we present a quantified model of the synthesis of pre-rrnas in yeast. the chemical kinetics simulation software dizzy has been used as both the modelling and simulation framework of our study. the simulations have been used to investigate the mechanism of co-transcriptional cleavage which can occur during the synthesis of pre-rrnas. throughout the paper we emphasise the strong role of experimental data both in shaping the model and in guiding the analysis which is carried out. parameter estimation procedures have been used to fit the model to the data and we discuss the validation of the model against the available experimental data. simulation based on gillespie's algorithm is considered to be the reference method for our analysis and a comparison with other simulators is reported. finally, we define an extended model, that relaxes one of the assumptions of the initial model.
incremental discovery of the irredundant motif bases for all suffixes of a string in o(nlogn) time. compact bases formed by motifs called ''irredundant'' and capable of generating all other motifs in a sequence have been proposed in recent years and successfully tested in tasks of biosequence analysis and classification. given a sequence s of n characters drawn from an alphabet @s, the problem of extracting such a base from s had been previously solved in time o(n^2lognlog|@s|) and o(|@s|n^2log^2nloglogn), respectively, using the fft-based string searching by fischer and paterson. more recently, a solution on binary strings taking time o(n^2) without resorting to the fft was also proposed. in the present paper, we considered the problem of incrementally extracting the bases of all suffixes of a string. this problem was solved in a previous work in time o(n^3). a much faster incremental algorithm is described here, which takes time o(n^2logn) for binary strings. although this algorithm does not make use of the fft, its performance is comparable to the one exhibited by the previous fft-based algorithms involving the computation of only one base. the implicit representation of a single base requires o(n) space, whence for finite alphabets the proposed solution is within a logn factor from optimality.
reductions for monotone boolean circuits. the large class, say nlog, of boolean functions, including 0-1 sort and 0-1 merge, have an upper bound of o(nlogn) for their monotone circuit size, i.e., they have circuits with o(nlogn) and/or gates of fan-in two. suppose that we can use, besides such normal and/or gates, any number of more powerful ''f-gates'' which realize a monotone boolean function f with r(>=2) inputs and r^'(>=1) outputs. note that the cost of each and/or gate is one and we assume that the cost of each f-gate is r. now we define: a boolean function f in nlog is said to be f-easy if f can be constructed by a circuit with and/or/f gates whose total cost is o(nlogn). in this paper we show that 0-1 merge is not f-easy for an arbitrary monotone function f such that r^'@?r/logr.
bayesian inference for differential equations. nonlinear dynamic systems such as biochemical pathways can be represented in abstract form using a number of modelling formalisms. in particular differential equations provide a highly expressive mathematical framework with which to model dynamic systems, and a very natural way to model the dynamics of a biochemical pathway in a deterministic manner is through the use of nonlinear ordinary or time delay differential equations. however if, for example, we consider a biochemical pathway the constituent chemical species and hence the pathway structure are seldom fully characterised. in addition it is often impossible to obtain values of the rates of activation or decay which form the free parameters of the mathematical model. the system model in many cases is therefore not fully characterised either in terms of structure or the values which parameters take. this uncertainty must be accounted for in a systematic manner when the model is used in simulation or predictive mode to safeguard against reaching conclusions about system characteristics that are unwarranted, or in making predictions that are unjustifiably optimistic given the uncertainty about the model. the bayesian inferential methodology provides a coherent framework with which to characterise and propagate uncertainty in such mechanistic models and this paper provides an introduction to bayesian methodology as applied to system models represented as differential equations.
the complexity of equilibria: hardness results for economies via a correspondence with games. we give a reduction from any two-player game to a special case of the leontief exchange economy, with the property that the nash equilibria of the game and the equilibria of the market are in one-to-one correspondence. our reduction exposes a computational hurdle inherent in solving certain families of market equilibrium problems: finding an equilibrium for leontief economies is at least as hard as finding a nash equilibrium for two-player nonzero sum games, a problem recently proven to be ppad-complete. as a corollary of the one-to-one correspondence, we obtain a number of hardness results for questions related to the computation of market equilibria, using results already established for games [i. gilboa, e. zemel, nash and correlated equilibria: some complexity considerations, games and economic behavior 1 (1989) 80-93]. in particular, among other results, we show that it is np-hard to say whether a particular family of leontief exchange economies, that is guaranteed to have at least one equilibrium, has more than one equilibrium. perhaps more importantly, we also prove that it is np-hard to decide whether a leontief exchange economy has an equilibrium. this fact should be contrasted against the known ppad-completeness result of [c.h. papadimitriou, on the complexity of the parity argument and other inefficient proofs of existence, journal of computer and system sciences 48 (1994) 498-532], which holds when the problem satisfies some standard sufficient conditions that make it equivalent to the computational version of brouwer's fixed point theorem.
pipelined algorithms to detect cheating in long-term grid computations. this paper studies pipelined algorithms for protecting distributed grid computations from cheating participants, who wish to be rewarded for tasks they receive but don't perform. we present improved cheater detection algorithms that utilize natural delays that exist in long-term grid computations. in particular, we partition the sequence of grid tasks into two interleaved sequences of task rounds, and we show how to use those rounds to devise the first general-purpose scheme that can catch all cheaters, even when cheaters collude. the main idea of this algorithm might at first seem counter-intuitive-we have the participants check each other's work. a naive implementation of this approach would, of course, be susceptible to collusion attacks, but we show that by, adapting efficient solutions to the parallel processor diagnosis problem, we can tolerate collusions of lazy cheaters, even if the number of such cheaters is a fraction of the total number of participants. we also include a simple economic analysis of cheaters in grid computations and a parameterization of the main deterrent that can be used against them-the probability of being caught.
on the power of lookahead in on-line server routing problems. we study the usefulness of lookahead in on-line server routing problems: if an on-line algorithm is not only informed about the requests released so far, but also has a limited ability to foresee future requests, what is the improvement that can be achieved in terms of the competitive ratio? we consider several on-line server routing problems in this setting, such as the on-line traveling salesman and the on-line traveling repairman problem. we show that the influence of lookahead can change considerably depending on the particular objective function and metric space considered.
succinct representations of planar maps. this paper addresses the problem of representing the connectivity information of geometric objects, using as little memory as possible. as opposed to raw compression issues, the focus here is on designing data structures that preserve the possibility of answering incidence queries in constant time. we propose, in particular, the first optimal representations for 3-connected planar graphs and triangulations, which are the most standard classes of graphs underlying meshes with spherical topology. optimal means that these representations asymptotically match the respective entropy of the two classes, namely 2 bits per edge for 3-connected planar graphs, and 1.62 bits per triangle, or equivalently 3.24 bits per vertex for triangulations. these representations support adjacency queries between vertices and faces in constant time.
nanok: a calculus for the modeling and simulation of nano devices. we develop a process calculus-the nano@k calculus-for modeling, analyzing and predicting the properties of molecular devices. the nano@k calculus is equipped with a simple stochastic model, that we use to model and simulate the behavior of a molecular shuttle, a basic nano device currently used for building more complex systems.
on temporal logic constraint solving for analyzing numerical data time series. temporal logics and model-checking have proved successful in expressing biological properties of complex biochemical systems, and automatically verify their satisfaction, in both qualitative and quantitative models. in this article, we go beyond model-checking and present a constraint solving algorithm for quantifier-free first-order temporal logic formulae, with constraints over the reals. this algorithm computes the domain of the real valued variables occurring in a formula that makes it true in a model. we illustrate this approach for the automatic generation of a temporal logic specification from biological data time series. we provide a set of biologically relevant patterns of formulae, and apply them to numerical data time series of models of the cell cycle control and mapk signal transduction. we show in these examples that this approach infers automatically semi-qualitative, semi-quantitative information about concentration thresholds, amplitude of oscillations, stability properties, checkpoints and influences between species.
area-time tradeoffs for universal vlsi circuits. an area-universal vlsi circuit can be programmed to emulate every circuit of a given area, but at the cost of lower area-time performance. in particular, if a circuit with area-time bounds (a,t) is emulated by a universal circuit with bounds (a"u,t"u), we say that the universal circuit has blowup a"u/a and slowdown t"u/t. a central question in vlsi theory is to investigate the inherent costs and tradeoffs of universal circuit designs. prior to this work, universal designs were known for area-a circuits with o(1) blowup and o(loga) slowdown. universal designs for the family of area-a circuits containing o(a^1^+^@eloga) vertices, with o(a^@e) blowup and o(logloga) slowdown had also been developed. however, the existence of universal circuits with o(1) slowdown and relatively small blowup was an open question. in this paper, we settle this question by designing an area-universal circuit u"a^^^@e with o(1/@e) slowdown and o(a^@e) blowup, for any value of the parameter @e, with 4logloga/loga@?@e@?1. by varying @e, we obtain universal circuits which operate at different points in the spectrum of the slowdown-blowup tradeoff. in particular, when @e is chosen to be a constant, our universal circuit yields o(1) slowdown.
algorithms for computing a parameterized st-orientation. st-orientations (st-numberings) or bipolar orientations of undirected graphs are central to many graph algorithms and applications. several algorithms have been proposed in the past to compute an st-orientation of a biconnected graph. in this paper, we present new algorithms that compute such orientations with certain (parameterized) characteristics in the final st-oriented graph, such as the length of the longest path. this work has many applications, including graph drawing and network routing, where the length of the longest path is vital in deciding certain features of the final solution. this work applies to other difficult problems as well, such as graph coloring and of course longest path. we present extended theoretical and experimental results which show that our technique is efficient and performs well in practice.
cavity detection and matching for binding site recognition. we developed a suite of methods for the problem of protein binding site recognition, based on a representation of the protein structures by a collection of spin-images. a procedure for cavity detection is coupled with a method previously developed for the recognition of similar regions in two proteins, and applied to the comparison of two protein's cavities, the all-to-all pairwise comparison of a set of cavities, and the recognition of multiple binding sites in one cavity. all the presented methods can be used to screen large collections of proteins. the detection of cavities in a given protein is often the preliminary step in protein binding site recognition, since binding sites usually lie in cavities. the comparison of two cavities identifies two similar regions in the two cavities, and hints at a common functional structure when one or both regions include a binding site. the all-to-all pairwise comparison of a set of cavities is clustered according to the measure of similarity of the cavities, obtaining a clustering that groups together cavities with the same binding sites, when their structures are similar enough. recognition of multiple binding sites in one cavity is performed by the comparison of a cavity, called background cavity, with a dataset of cavities, and clustering its residues that match the residues of other cavities in the data set. the four methods are benchmarked on different databases, and their effectiveness is discussed.
evolving blenx programs to simulate the evolution of biological networks. we present a formal approach to study the evolution of biological networks. we use the beta workbench and its blenx language to model and simulate networks in connection with evolutionary algorithms. mutations are done on the structure of blenx programs and networks are selected at any generation by using a fitness function. the feasibility of the approach is illustrated with a simple example.
synapses as stochastic concurrent systems. we present a stochastic model of the presynaptic terminal in the calyx of held synapse. this model exploits process calculi as a representation language and has a direct computational implementation that supports quantitative simulation trials of the behaviour of the synapse. to our knowledge, it represents the first model of synaptic activity based on process calculi. the model builds upon available data, the fitting of some parameters and developed working hypotheses. experiments about plasticity have been carried out regarding synaptic facilitation and potentiation. also, synaptic depression has been considered in a model exhibiting dynamical equilibrium. overall, the simulation results are coherent with the experimental findings appearing in the literature about the modeled reality. these results represent a quite detailed description of the presynaptic activity. this multidisciplinary work validates some aspects of the approach based on process calculi with respect to the new application domain, such as abstraction, expressiveness and compositionality.
the nearest polynomial with a zero in a given domain. for a real univariate polynomial f and a closed domain d@?c whose boundary c is represented by a piecewise rational function, we provide a rigorous method for finding a real univariate polynomial f@? such that f@? has a zero in d and @?f-f@?@?"~ is minimal. first, we prove that if a nearest polynomial exists, there is a nearest polynomial f@? such that the absolute value of every coefficient of f-f@? is @?f-f@?@?"~ with at most one exception. using this property and the representation of c, we reduce the problem to solving systems of algebraic equations, each of which consists of two equations with two variables.
schur aggregation for linear systems and determinants. we apply our recent preconditioning techniques to the solution of linear systems of equations and computing determinants. we combine these techniques with the sherman-morrison-woodbury formula, its new variations, aggregation, iterative refinement, and advanced algorithms that rapidly compute sums and products either error-free or with the desired high accuracy. our theoretical and experimental study shows the power of this approach.
stable normal forms for polynomial system solving. the paper describes and analyzes a method for computing border bases of a zero-dimensional ideal i. the criterion used in the computation involves specific commutation polynomials, and leads to an algorithm and an implementation extending the ones in [b. mourrain, ph. trebuchet, generalised normal forms and polynomial system solving, in: m. kauers (ed.), proc. intern. symp. on symbolic and algebraic computation, acm press, new-york, 2005, pp. 253-260]. this general border basis algorithm weakens the monomial ordering requirement for grobner bases computations. it is currently the most general setting for representing quotient algebras, embedding into a single formalism grobner bases, macaulay bases and a new representation that does not fit into the previous categories. with this formalism, we show how the syzygies of the border basis are generated by commutation relations. we also show that our construction of normal form is stable under small perturbations of the ideal, if the number of solutions remains constant. this feature has a huge impact on practical efficiency, as illustrated by the experiments on classical benchmark polynomial systems, at the end of the paper.
a fast hermite transform. we present algorithms for fast and stable approximation of the hermite transform of a compactly supported function on the real line, attainable via an application of a fast algebraic algorithm for computing sums associated with a three-term relation. trade-offs between approximation in bandlimit (in the hermite sense), and size of the support region are addressed. numerical experiments are presented that show the feasibility and utility of our approach. generalizations to any family of orthogonal polynomials are outlined. applications to various problems in tomographic reconstruction, including the determination of protein structure, are discussed.
real algebraic numbers and polynomial systems of small degree. based on precomputed sturm-habicht sequences, discriminants and invariants, we classify, isolate with rational points, and compare the real roots of polynomials of degree up to 4. in particular, we express all isolating points as rational functions of the input polynomial coefficients. although the roots are algebraic numbers and can be expressed by radicals, such representation involves some roots of complex numbers. this is inefficient, and hard to handle in applications in geometric computing and quantifier elimination. we also define rational isolating points between the roots of the quintic. we combine these results with a simple version of rational univariate representation to isolate all common real roots of a bivariate system of rational polynomials of total degree @?2 and to compute the multiplicity of these roots. we present our software within library synaps and perform experiments and comparisons with several public-domain implementations. our package is 2-10 times faster than numerical methods and exact subdivision-based methods, including software with intrinsic filtering.
cpo semantics of timed interactive actor networks. we give a denotational framework for composing interactive components into closed or open systems and show how to adapt classical domain-theoretic approaches to open systems and to timed systems. for timed systems, prior approaches are based on temporal logics, automata theory, or metric spaces. in this paper, we base the semantics on a cpo with a prefix order, as has been done previously for untimed systems. we show that existence and uniqueness of behaviors are ensured by continuity with respect to this prefix order. existence and uniqueness of behaviors, however, do not imply that a composition of components yields a useful behavior. the unique behavior could be empty or smaller than expected. we define liveness and show that appropriately defined causality conditions ensure liveness and freedom from zeno conditions. in our formulation, causality does not require a metric and can embrace a wide variety of models of time.
the computable kernel of abstract state machines. abstract state machines (asms) were introduced as ''a computation model that is more powerful and more universal than standard computation models'', by yuri gurevich in 1985. asms gained much attention as a specification method. it is extremely flexible because any mathematical structure may serve as a state. gurevich characterized the expressive power of asms in terms of intuitively convincing postulates. the core result of this paper shows that the next-state function m of an abstract state machine m can be described on a symbolic level, notwithstanding the generality of the model: the successor state m(s) of a state s is fully specified by the equivalence ~"s induced by s on the terms over the signature of m. consequently, m(s) is computable in case ~"s is decidable. furthermore, this result implies a notion of computability for general structures, e.g. for algorithms operating on real numbers.
optimization techniques for propositional intuitionistic logic and their implementation. this paper presents some techniques which bound the proof search space in propositional intuitionistic logic. these techniques are justified by kripke semantics and are the backbone of a tableau based theorem prover (pitp) implemented in c++. pitp and some known theorem provers are compared using the formulas of iltp benchmark library. it turns out that pitp is, at the moment, the propositional prover that solves most formulas of the library.
a numerical elimination method for polynomial computations. a numerical elimination method is presented in this paper for floating-point computation in polynomial algebra. the method is designed to calculate one or more polynomials in an elimination ideal by a sequence of matrix rank/kernel computation. the method is reliable in numerical computation with verifiable stability and a sensitivity measurement. computational experiment shows that the method possesses significant advantages over classical resultant computation in numerical stability and in producing eliminant polynomials with lower degrees and fewer extraneous factors. the elimination algorithm combined with an approximate gcd finder appears to be effective in solving polynomial systems for positive dimensional solutions.
complexity of real root isolation using continued fractions. in this paper, we provide polynomial bounds on the worst case bit-complexity of two formulations of the continued fraction algorithm. in particular, for a square-free integer polynomial of degree n with coefficients of bit-length l, we show that the bit-complexity of akritas' formulation is o@?(n^8l^3), and the bit-complexity of a formulation by akritas and strzebonski is o@?(n^7l^2); here o@? indicates that we are omitting logarithmic factors. the analyses use a bound by hong to compute the floor of the smallest positive root of a polynomial, which is a crucial step in the continued fraction algorithm. we also propose a modification of the latter formulation that achieves a bit-complexity of o@?(n^5l^2).
computing sum of squares decompositions with rational coefficients. sum of squares (sos) decompositions for nonnegative polynomials are usually computed numerically, using convex optimization solvers. although the underlying floating point methods in principle allow for numerical approximations of arbitrary precision, the computed solutions will never be exact. in many applications such as geometric theorem proving, it is of interest to obtain solutions that can be exactly verified. in this paper, we present a numeric-symbolic method that exploits the efficiency of numerical techniques to obtain an approximate solution, which is then used as a starting point for the computation of an exact rational result. we show that under a strict feasibility assumption, an approximate solution of the semidefinite program is sufficient to obtain a rational decomposition, and quantify the relation between the numerical error versus the rounding tolerance needed. furthermore, we present an implementation of our method for the computer algebra system macaulay 2.
responsiveness in process calculi. a system guarantees responsive usage of a channel r if a communication along r is guaranteed to eventually take place. responsiveness is important, for instance, to ensure that any request to a service be eventually replied. we propose two distinct type systems, each of which statically guarantees responsive usage of names in well-typed pi-calculus processes. in the first system, we achieve responsiveness by combining techniques for deadlock and livelock avoidance with linearity and receptiveness. the latter is a guarantee that a name is ready to receive as soon as it is created. these conditions imply relevant limitations on the nesting of actions and on multiple use of names in processes. in the second system, we relax these requirements so as to permit certain forms of nested inputs and multiple outputs. we demonstrate the expressive power of the two systems by showing that primitive recursive functions-in the case of the first system-and cook and misra's service orchestration language orc-in the case of the second system-can be encoded into well-typed processes.
approximate gcds of polynomials and sparse sos relaxations. the problem of computing approximate gcds of several polynomials with real or complex coefficients can be formulated as computing the minimal perturbation such that the perturbed polynomials have an exact gcd of given degree. we present algorithms based on sos (sums of squares) relaxations for solving the involved polynomial or rational function optimization problems with or without constraints.
machine semantics. using simple systems with a notion of discrete deterministic evolution over time, we study discrete causality via tools from theoretical computer science and logic. we consider the set of all representations (i.e. partial descriptions) of such systems, from algebraic, domain-theoretic, and categorical viewpoints. the order theory introduced, is based in the notion of comparing high-level and low-level descriptions of the same system. this is shown to give a complete partial order where the down-closure of each element is a locale. this partial order has a very close connection to a categorical construction known as the 'particle-style' trace, via analogues of domain-theoretic equations. thus, the trace may be thought of as the computation of suprema in this partial order. as a sample application, we show how to construct algebraic models of space-bounded turing machines in these terms, and derive compositionality from the abstract properties of the trace.
verification of qualitative z constraints. we introduce an ltl-like logic with atomic formulae built over a constraint language interpreting variables in z. the constraint language includes periodicity constraints and comparison constraints of the form x=y and x
computations with quasiseparable polynomials and matrices. in this paper, we survey several recent results that highlight an interplay between a relatively new class of quasiseparable matrices and univariate polynomials. quasiseparable matrices generalize two classical matrix classes, jacobi (tridiagonal) matrices and unitary hessenberg matrices that are known to correspond to real orthogonal polynomials and szego polynomials, respectively. the latter two polynomial families arise in a wide variety of applications, and their short recurrence relations are the basis for a number of efficient algorithms. for historical reasons, algorithm development is more advanced for real orthogonal polynomials. recent variations of these algorithms tend to be valid only for the szego polynomials; they are analogues and not generalizations of the original algorithms. herein, we survey several recent results for the ''superclass'' of quasiseparable matrices, which includes both jacobi and unitary hessenberg matrices as special cases. the interplay between quasiseparable matrices and their associated polynomial sequences (which contain both real orthogonal and szego polynomials) allows one to obtain true generalizations of several algorithms. specifically, we discuss the bjorck-pereyra algorithm, the traub algorithm, certain new digital filter structures, as well as qr and divide and conquer eigenvalue algorithms.
gravitational wave signal templates, pattern recognition, and reciprocal eulerian gamma functions. the direct detection of gravitational waves (gws) is one of the most challenging problems in experimental gravitation today. it necessitates the use of highly advanced large laser interferometers such as ligo, virgo, lisa, tama 300, geo 600 and aigo. the analysis of the data from such instruments requires and combines the expertise from a multitude of scientific disciplines. the verification of a detected signal demands an effective way to distinguish the source signal from the background noise. such a study is required for an all-sky search to determine the @f and @q angles on the sky of gravitational wave sources and their frequencies. in this paper, we present analytical solutions and associated numerical approximations for the inner products employed in matched filtering a gw signal using templates. an exact closed-form expression for the inner products is rigourously derived using the special functions of mathematical physics. the inner products involve reciprocal eulerian gamma functions, which occur in the study of many diverse phenomena. the spectral noise density of the virgo gw detector is shown to be amenable to our analysis. spectral noise densities like those for ligo and geo 600, although different and in a slightly more restricted frequency band, are likewise amenable. we study numerical computation of the inner products, estimate the computational time of the solution on serial and parallel computers, and show the efficiency of the resulting algorithms. the fitting factor that indicates the goodness of fit between a signal and a template is given in closed-form and computed numerically. the numerical plots display an approximate symmetry in the template @f and @q domain.
a new algorithm for sparse interpolation of multivariate polynomials. to reconstruct a black box multivariate sparse polynomial from its floating point evaluations, the existing algorithms need to know upper bounds for both the number of terms in the polynomial and the partial degree in each of the variables. here we present a new technique, based on rutishauser's qd-algorithm, in which we overcome both drawbacks.
the identity type weak factorisation system. we show that the classifying category c(t) of a dependent type theory t with axioms for identity types admits a non-trivial weak factorisation system. we provide an explicit characterisation of the elements of both the left class and the right class of the weak factorisation system. this characterisation is applied to relate identity types and the homotopy theory of groupoids.
expanders and time-restricted branching programs. the replication number of a branching program is the minimum number r such that along every accepting computation at most r variables are tested more than once; the sets of variables re-tested along different computations may be different. for every branching program, this number lies between 0 (read-once programs) and the total number n of variables (general branching programs). the best results so far were exponential lower bounds on the size of branching programs with r=o(n/logn). we improve this to r@?@en for a constant @e>0. this also gives an alternative and simpler proof of an exponential lower bound for (1+@e)n time branching programs for a constant @e>0. we prove these lower bounds for quadratic functions of ramanujan graphs.
games to induce specified equilibria. media access protocols in wireless networks require each contending node to wait for a backoff time, chosen randomly from a fixed range, before attempting to transmit on a shared channel. however, nodes acting in their own selfish interest may not follow the protocol. in this paper, a static version of the problem is modeled as a strategic game played by non-cooperating, rational players (the nodes). the objective is to design a game which exhibits a unique, a priori mixed-strategy nash equilibrium. in the context of the media access problem, the equilibrium of the game would correspond to nodes choosing backoff times randomly from a given range of values, according to the given distribution. we consider natural variations of the problems concerning the number of actions available to the players and show that it is possible to design such a game when there are at least two players that each have the largest number of possible actions among all players. in contrast, we show that if there are exactly two players with different number of actions available to them, then it becomes impossible to design a strategic game with a unique such nash equilibrium.
playing with conway's problem. the centralizer of a language is the maximal language commuting with it. the question, raised by conway in [j.h. conway, regular algebra and finite machines, chapman hall, 1971], whether the centralizer of a rational language is always rational, recently received a lot of attention. in kunc [m. kunc, the power of commuting with finite sets of words, in: proc. of stacs 2005, in: lncs, vol. 3404, springer, 2005, pp. 569-580], a strong negative answer to this problem was given by showing that even complete co-recursively enumerable centralizers exist for finite languages. using a combinatorial game approach, we give here an incremental construction of rational languages embedding any recursive computation in their centralizers.
a new self-stabilizing maximal matching algorithm. the maximal matching problem has received considerable attention in the self-stabilizing community. previous work has given several self-stabilizing algorithms that solve the problem for both the adversarial and the fair distributed daemon, the sequential adversarial daemon, as well as the synchronous daemon. in the following we present a single self-stabilizing algorithm for this problem that unites all of these algorithms in that it has the same time complexity as the previous best algorithms for the sequential adversarial, the distributed fair, and the synchronous daemon. in addition, the algorithm improves the previous best time complexities for the distributed adversarial daemon from o(n^2) and o(@dm) to o(m) where n is the number of processes, m is the number of edges, and @d is the maximum degree in the graph.
quasiperiodic and lyndon episturmian words. recently the second two authors characterized quasiperiodic sturmian words, proving that a sturmian word is non-quasiperiodic if and only if, it is an infinite lyndon word. here we extend this study to episturmian words (a natural generalization of sturmian words) by describing all the quasiperiods of an episturmian word, which yields a characterization of quasiperiodic episturmian words in terms of their directive words. even further, we establish a complete characterization of all episturmian words that are lyndon words. our main results show that, unlike the sturmian case, there is a much wider class of episturmian words that are non-quasiperiodic, besides those that are infinite lyndon words. our key tools are morphisms and directive words, in particular normalized directive words, which we introduced in an earlier paper. also of importance is the use of return words to characterize quasiperiodic episturmian words, since such a method could be useful in other contexts.
paths and trails in edge-colored graphs. this paper deals with the existence and search for properly edge-colored paths/trails between two, not necessarily distinct, vertices s and t in an edge-colored graph from an algorithmic perspective. first we show that several versions of the s-t path/trail problem have polynomial solutions including the shortest path/trail case. we give polynomial algorithms for finding a longest properly edge-colored path/trail between s and t for a particular class of graphs and characterize edge-colored graphs without properly edge-colored closed trails. next, we prove that deciding whether there exist k pairwise vertex/edge disjoint properly edge-colored s-t paths/trails in a c-edge-colored graph g^c is np-complete even for k=2 and c=@w(n^2), where n denotes the number of vertices in g^c. moreover, we prove that these problems remain np-complete for c-edge-colored graphs containing no properly edge-colored cycles and c=@w(n). we obtain some approximation results for those maximization problems together with polynomial results for some particular classes of edge-colored graphs.
generalized lcs. the longest common subsequence (lcs) is a well studied problem, having a wide range of implementations. its motivation is in comparing strings. it has long been of interest to devise a similar measure for comparing higher dimensional objects, and more complex structures. in this paper we study the longest common substructure of two matrices and show that this problem is np-hard. we also study the longest common subforest problem for multiple trees including a constrained version, as well. we show np-hardness for k>2 unordered trees in the constrained lcs. we also give polynomial time algorithms for ordered trees and prove a lower bound for any decomposition strategy for k trees.
sequential and parallel triangulating algorithms for elimination game and new insights on minimum degree. elimination game is a well-known algorithm that simulates gaussian elimination of matrices on graphs, and it computes a triangulation of the input graph. the number of fill edges in the computed triangulation is highly dependent on the order in which elimination game processes the vertices, and in general the produced triangulations are neither minimum nor minimal. in order to obtain a triangulation which is close to minimum, the minimum degree heuristic is widely used in practice, but until now little was known on the theoretical mechanisms involved. in this paper we show some interesting properties of elimination game; in particular that it is able to compute a partial minimal triangulation of the input graph regardless of the order in which the vertices are processed. this results in a new algorithm to compute minimal triangulations that are sandwiched between the input graph and the triangulation resulting from elimination game. one of the strengths of the new approach is that it is easily parallelizable, and thus we are able to present the first parallel algorithm to compute such sandwiched minimal triangulations. in addition, the insight that we gain through elimination game is used to partly explain the good behavior of the minimum degree algorithm. we also give a new algorithm for producing minimal triangulations that is able to use the minimum degree idea to a wider extent.
structural presburger digit vector automata. the least significant digit first decomposition of integer vectors into words of digit vectors provides a natural way for representing sets of integer vectors by automata. in this paper, the minimal automata representing presburger sets are proved structurally presburger: automata obtained by moving the initial state and replacing the accepting condition represent presburger sets.
edge-fault-tolerant hamiltonicity of pancake graphs under the conditional fault model. the conditional fault model imposes a constraint on the fault distribution. for example, the most commonly imposed constraint for edge faults is that each vertex is incident with two or more non-faulty edges. in this paper, subject to this constraint, we show that an n-dimensional pancake graph can tolerate up to 2n-7 edge faults, while retaining a fault-free hamiltonian cycle, where n>=4. previously, at most n-3 edge faults can be tolerated for the same problem, if the edge faults may occur anywhere without imposing any constraint.
a quadratic identity for the number of perfect matchings of plane graphs. we present a quadratic identity on the number of perfect matchings of plane graphs by the method of graphical condensation, which generalizes the results found by propp [j. propp, generalized domino-shuffling, theoret. comput. sci. 303 (2003) 267-301], kuo [e.h. kuo, applications of graphical condensation for enumerating matchings and tilings, theoret. comput. sci. 319 (2004) 29-57], and yan, yeh, and zhang [w.g. yan, y.-n. yeh, f.j. zhang, graphical condensation of plane graphs: a combinatorial approach, theoret. comput. sci. 349 (2005) 452-461].
long binary patterns are abelian 2-avoidable. we show that every long binary pattern is abelian 2-avoidable.
minimum-cost delegation in service composition. the paradigm of automated service composition through the integration of existing services promises a fast and efficient development of new services in cooperative service (e.g., business) environments. although the ''why'' part of this paradigm is well understood, many key pieces are missing to utilize the available opportunities. recently ''service communities'' where service providers with similar interests can register their services are proposed toward realizing this goal. in these communities, requests for services posed by users can be processed by delegating them to existing services, and orchestrating their executions. we use a service framework similar to the ''roman'' model departing from it particularly assuming service requirements are specified in a sequence form. we also extend the framework to integrate activity processing costs into the delegation computation and to have services with bounded storage as opposed to finite storage. we investigate the problem of efficient processing of service requests in service communities and develop polynomial time delegation techniques guaranteeing optimality.
a palindromization map for the free group. we define a self-map pal:f"2->f"2 of the free group on two generators a,b, using automorphisms of f"2 that form a group isomorphic to the braid group b"3. the map pal restricts to de luca's right iterated palindromic closure on the submonoid generated by a,b. we show that pal is continuous for the profinite topology on f"2; it is the unique continuous extension of de luca's right iterated palindromic closure to f"2. the values of pal are palindromes and coincide with the elements g@?f"2 such that abg and bag are conjugate.
deadline guaranteed packet scheduling for overloaded traffic in input-queued switches. many applications need to solve the deadline guaranteed packet scheduling problem. however, it is a very difficult problem if three or more deadlines are present in a set of packets to be scheduled. the traditional approach to dealing with this problem is to use edf (earliest deadline first) or similar methods. recently, a non-edf based algorithm was proposed that constantly produces a higher throughput than edf-based algorithms by repeatedly finding an optimal scheduling for two classes. however, this new method requires the two classes be non-overloaded, which greatly restricts its applications. since the overloaded situation is not avoidable from one iteration to the next in dealing with multiple classes, it is compelling to answer the open question: can we find an optimal schedule for two overloaded classes efficiently? this paper first proves that this problem is np-complete. then, this paper proposes an optimal preprocessing algorithm that guarantees to drop a minimum number of packets from the two classes such that the remaining set is non-overloaded. this result directly improves on the new method.
strategic attack on the shrinking generator. the shrinking generator is a simple keystream generator with applications in stream ciphers, which is still considered as a secure generator. this work shows that, in order to cryptanalyze it, fewer intercepted bits than indicated by the linear complexity are necessary. indeed, whereas the linear complexity of shrunken sequences is between a@?2^(^s^-^2^) and a@?2^(^s^-^1^), we claim that the initial states of both component registers are easily computed with fewer than a@?s shrunken bits located at particular positions. such a result is proven thanks to the definition of shrunken sequences as interleaved sequences. consequently, it is conjectured that this statement can be extended to all interleaved sequences. furthermore, this paper confirms that certain bits of the interleaved sequences have a greater strategic importance than others, which must be considered as a proof of weakness of interleaved generators.
sequential vector packing. we introduce a novel variant of the well known d-dimensional bin (or vector) packing problem. given a sequence of non-negative d-dimensional vectors, the goal is to pack these into as few bins as possible, of the smallest possible size. in the classical problem, the bin size vector is given and the sequence can be partitioned arbitrarily. we study a variation where the vectors have to be packed in the order in which they arrive, and the bin size vector can be chosen once in the beginning. this setting gives rise to two combinatorial problems: one in which we want to minimize the number of bins used for a given total bin size, and one in which we want to minimize the total bin size for a given number of bins. we prove that both problems are np-hard, and propose an lp based bicriteria (1@e,11-@e)-approximation algorithm. we give a 2-approximation algorithm for the version with a bounded number of bins. furthermore, we investigate properties of natural greedy algorithms, and present an easy to implement heuristic, which is fast and performs well in practice. experiments with the heuristic and an ilp formulation yield promising results on real world data.
generating all permutations by context-free grammars in greibach normal form. we consider context-free grammars g"n in greibach normal form and, particularly, in greibach m-form (m=1,2) which generates the finite language l"n of all n! strings that are permutations of n different symbols (n>=1). these grammars are investigated with respect to their descriptional complexity, i.e., we determine the number of nonterminal symbols and the number of production rules of g"n as functions of n. as in the case of chomsky normal form, these descriptional complexity measures grow faster than any polynomial function.
complexity of question/answer games. question/answer games (q/a games for short) are a generalization of the renyi-ulam game and they are a model for information extraction in parallel. a q/a game, g=(d,s,(q"1,...,q"k)), is played on a directed acyclic graph, d=(v,e), with a distinguished start vertex s. in the ith round, paul selects a set, q"i@?v, of at most q"i non-terminal vertices. carole responds by choosing an outgoing edge from each vertex in q"i. at the end of k rounds, paul wins if carole's answers define a unique path from the root to one of the terminal vertices in d. in this paper we analyze the complexity of q/a games and explore the notion of fixed strategies. we show that the problem of determining if paul wins the game played on a rooted tree via a fixed strategy is in np. the same problem is @s"2p-complete for arbitrary digraphs. for general strategies, the problem is np-complete if we restrict a two-round game to a digraph of depth three. an interesting aspect of this game is that it captures the even levels of the polynomial-time hierarchy when restricted to a fixed number of rounds; that is, determining if paul wins a k-round game is @s"2"k"-"2p-complete. the general version of the game is known to be pspace-complete [s. abbasi, n. sheikh, some hardness results for q/a games, integers 7 (2007) g08]. in this paper we show that it remains pspace-complete even if each round consists of only two questions.
rational subsets of partially reversible monoids. a class of monoids that can model partial reversibility allowing simultaneously instances of two-sided reversibility, one-sided reversibility and no reversibility is considered. some of the basic decidability problems involving their rational subsets, syntactic congruences and characterization of recognizability, are solved using purely automata-theoretic techniques, giving further insight into the structure of recognizable languages.
algorithms for subsequence combinatorics. a subsequence is obtained from a string by deleting any number of characters; thus in contrast to a substring, a subsequence is not necessarily a contiguous part of the string. counting subsequences under various constraints has become relevant to biological sequence analysis, to machine learning, to coding theory, to the analysis of categorical time series in the social sciences, and to the theory of word complexity. we present theorems that lead to efficient dynamic programming algorithms to count (1) distinct subsequences in a string, (2) distinct common subsequences of two strings, (3) matching joint embeddings in two strings, (4) distinct subsequences with a given minimum span, and (5) sequences generated by a string allowing characters to come in runs of a length that is bounded from above.
fast and compact regular expression matching. we study 4 problems in string matching, namely, regular expression matching, approximate regular expression matching, string edit distance, and subsequence indexing, on a standard word ram model of computation that allows logarithmic-sized words to be manipulated in constant time. we show how to improve the space and/or remove a dependency on the alphabet size for each problem using either an improved tabulation technique of an existing algorithm or by combining known algorithms in a new way.
simulating one-reversal multicounter machines by partially blind multihead finite automata. this work is concerned with simulating nondeterministic one-reversal multicounter automata (ncms) by nondeterministic partially blind multihead finite automata (nfas). we show that any one-reversal ncm with k counters can be simulated by a partially blind nfa with k blind heads. this provides a nearly complete categorization of the computational power of partially blind automata, showing that the power of a (k+1)-nfa lies between that of a k-ncm and a (k+1)-ncm.
the pruning-grafting lattice of binary trees. we introduce a new lattice structure b"n on binary trees of size n. we exhibit efficient algorithms for computing meet and join of two binary trees and give several properties of this lattice. more precisely, we prove that the length of a longest (resp. shortest) path between 0 and 1 in b"n equals to the eulerian numbers 2^n-(n+1) (resp. (n-1)^2) and that the number of coverings is (2nn-1). finally, we exhibit a matching in a constructive way. then we propose some open problems about this new structure.
rectangular polyomino set weak (1, 2)-achievement games. in a polyomino set (1, 2)-achievement game the maker and the breaker alternately mark one and two previously unmarked cells respectively. the maker's goal is to mark a set of cells congruent to one of a given set of polyominoes. the breaker tries to prevent the maker from achieving his goal. the teams of polyominoes for which the maker has a winning strategy is determined up to size 4. in set achievement games, it is natural to study infinitely large polyominoes. this enables the construction of super winners that characterize all winning teams up to a certain size.
dynamic bin packing of unit fractions items. this paper studies the dynamic bin packing problem, in which items arrive and depart at arbitrary times. we want to pack a sequence of unit fractions items (i.e., items with sizes 1/w for some integer w>=1) into unit-size bins, such that the maximum number of bins ever used over all time is minimized. tight and almost-tight performance bounds are found for the family of any-fit algorithms, including first-fit, best-fit, and worst-fit. in particular, we show that the competitive ratio of best-fit and worst-fit is 3, which is tight, and the competitive ratio of first-fit lies between 2.45 and 2.4942. we also show that no on-line algorithm is better than 2.428-competitive.
a shared-variable concurrency analysis of multi-threaded object-oriented programs. in this paper a proof outline logic is introduced for the partial correctness of multi-threaded object-oriented programs like in java. the main contribution is a generalization of the owicki& gries proof method for shared-variable concurrency to dynamic thread creation. this paper also provides a formal justification of this generalization in terms of soundness and completeness proofs.
reactors: a data-oriented synchronous/asynchronous programming model for distributed applications. our aim is to define the kernel of a simple and uniform programming model-the reactor model-which can serve as a foundation for building and evolving internet-scale programs. such programs are characterized by collections of loosely-coupled distributed components that are assembled on the fly to produce a composite application. a reactor consists of two principal components: mutable state, in the form of a fixed collection of relations, and code, in the form of a fixed collection of rules in the style of datalog. a reactor's code is executed in response to an external stimulus, which takes the form of an attempted update to the reactor's state. as in classical process calculi, the reactor model accommodates collections of distributed, concurrently executing processes. however, unlike classical process calculi, our observable behaviors are sequences of states, rather than sequences of messages. similarly, the interface to a reactor is simply its state, rather than a collection of message channels, ports, or methods. one novel feature of our model is the ability to compose behaviors both synchronously and asynchronously. also, our use of datalog-style rules allows aspect-like composition of separately-specified functional concerns in a natural way.
scala actors: unifying thread-based and event-based programming. there is an impedance mismatch between message-passing concurrency and virtual machines, such as the jvm. vms usually map their threads to heavyweight os processes. without a lightweight process abstraction, users are often forced to write parts of concurrent applications in an event-driven style which obscures control flow, and increases the burden on the programmer. in this paper we show how thread-based and event-based programming can be unified under a single actor abstraction. using advanced abstraction mechanisms of the scala programming language, we implement our approach on unmodified jvms. our programming model integrates well with the threading model of the underlying vm.
pict correctness revisited. the pict programming language is an implementation of the @p-calculus in which executions of @p-calculus terms are specified via an abstract machine. an important property of any concurrent programming language implementation is the fair execution of threads. after defining fairness for the @p-calculus, we show that pict abstract machine executions implement fair @p-calculus executions. we also give new proofs of soundness and liveness for the pict abstract machine.
on the parameterized complexity of multiple-interval graph problems. multiple-interval graphs are a natural generalization of interval graphs where each vertex may have more than one interval associated with it. many applications of interval graphs also generalize to multiple-interval graphs, often allowing for more robustness in the modeling of the specific application. with this motivation in mind, a recent systematic study of optimization problems in multiple-interval graphs was initiated. in this sequel, we study multiple-interval graph problems from the perspective of parameterized complexity. the problems under consideration are k-independent set, k-dominating set, and k-clique, which are all known to be w[1]-hard for general graphs, and np-complete for multiple-interval graphs. we prove that k-clique is in fpt, while k-independent set and k-dominating set are both w[1]-hard. we also prove that k-independent dominating set, a hybrid of the two above problems, is also w[1]-hard. our hardness results hold even when each vertex is associated with at most two intervals, and all intervals have unit length. furthermore, as an interesting byproduct of our hardness results, we develop a useful technique for showing w[1]-hardness via a reduction from the k-multicolored clique problem, a variant of k-clique. we believe this technique has interest in its own right, as it should help in simplifying w[1]-hardness results which are notoriously hard to construct and technically tedious.
single-edge monotonic sequences of graphs and linear-time algorithms for minimal completions and deletions. we study graph properties that admit an increasing, or equivalently decreasing, sequence of graphs on the same vertex set such that for any two consecutive graphs in the sequence their difference is a single edge. this is useful for characterizing and computing minimal completions and deletions of arbitrary graphs into having these properties. we prove that threshold graphs and chain graphs admit such sequences. based on this characterization and other structural properties, we present linear-time algorithms both for computing minimal completions and deletions into threshold, chain, and bipartite graphs, and for extracting a minimal completion or deletion from a given completion or deletion. minimum completions and deletions into these classes are np-hard to compute.
a cyclic binary morphism avoiding abelian fourth powers. we exhibit a cyclic binary morphism avoiding abelian fourth powers.
the hitting and cover times of random walks on finite graphs using local degree information. standard random walks on finite graphs select the vertex visited next to the adjacent vertices at random with the same probability. despite not using any global topological information, they guarantee o(n^3) hitting and cover times for any graph, where n is the order of the graph. motivated by network protocol applications, this paper investigates the impact of local topological information on designing ''better'' random walks. we first show that (a) for any transition probability matrix, the hitting (and hence the cover) time of a path graph is @w(n^2). we next investigate for any graph g=(v,e) a transition probability matrix p=(p(u,v))"u","v"@?"v defined by p(u,v)={deg^-^1^/^2(v)@?w@?n(u)deg^-^1^/^2(w)if v@?n(u),0otherwise ,where n(u) and deg(u) are respectively the set of adjacent vertices of u and the u's degree. random walks obeying this transition probability matrix are shown to guarantee the following: for any graph, (b) the hitting time is o(n^2), and (c) the cover time is o(n^2logn). facts (a) and (b) show that the degree information on the adjacent vertices is powerful enough for random walks to achieve the optimum hitting time.
finite n-tape automata over possibly infinite alphabets: extending a theorem of eilenberg et al. eilenberg, elgot and shepherdson showed in 1969, [s. eilenberg, c.c. elgot, j.c. shepherdson, sets recognized by n-tape automata, journal of algebra 13 (1969) 447-464], that a relation on finite words over a finite, non-unary alphabet with p letters is definable in first order logic with p+2 predicates for the relations equal length, prefix and last letter isa (for each letter a@?@s) if and only if it can be recognized by a finite multitape synchronous automaton, i.e., one whose read heads move simultaneously. they left open the characterization in the case of infinite alphabets, and proposed some conjectures concerning them. we solve all problems and sharpen the main theorem of [s. eilenberg, c.c. elgot, j.c. shepherdson, sets recognized by n-tape automata, journal of algebra 13 (1969) 447-464].
the minimal laplacian spectral radius of trees with a given diameter. for a graph g, its laplacian matrix is the difference of the diagonal matrix of its vertex degrees and its adjacency matrix. let t"n","d be the set of trees on n vertices with diameter d. in this paper, for d@?{1,2,3,4,n-3,n-2,n-1}, trees with minimal laplacian spectral radii in the set t"n","d are characterized.
amalgamating sessions and methods in object-oriented languages with generics. we suggest an amalgamation of communication-based programming (centered on sessions) and object-oriented programming, whereby sessions between concurrent threads are amalgamated with methods. in our proposal, threads consist of the execution of session bodies on objects and communicate with each other by asynchronously sending/receiving objects on channels. the response to a session request is based on the name of the request and the class of the object receiving the request. the decision of how to continue a session is based on the class of the object sent/received. sessions can be delegated to other sessions, although sessions themselves are not first class objects. we demonstrate our ideas through a core language with generic types, sam^g, and an example. we then formalize a small calculus, fsam^g, and prove subject reduction and progress. the latter property is notoriously difficult to achieve in concurrent calculi.
fault-tolerant computation of distributed regular path queries. regular path queries are the building blocks of almost any mechanism for querying semistructured data. despite the fact that the main applications of such data are distributed, there are only few works dealing with distributed evaluation of regular path queries. in this paper we present a message-efficient and truly distributed algorithm for computing the answer to regular path queries in a multi-source semistructured database setting. our algorithm is general as it works for the larger class of weighted regular path queries on weighted semistructured databases. also, we show how to make our algorithm fault-tolerant to smoothly work in environments prone to process (or machine) failures. this is very desirable in a grid setting, which is today's new paradigm of distributed computing, and where one does not have full control over machines that can unexpectedly leave in the middle of computation.
minimal interval completion through graph exploration. given an arbitrary graph g=(v,e) and an interval graph h=(v,f) with e@?f we say that h is an interval completion of g. the graph h is called a minimal interval completion of g if, for any sandwich graph h^'=(v,f^') with e@?f^'@?f, h^' is not an interval graph. in this paper we give a o(nm) time algorithm computing a minimal interval completion of an arbitrary graph. the output is an interval model of the completion.
fully abstract models and refinements as tools to compare agents in timed coordination languages. coordination languages and models promote the idea of separating computation and interaction aspects. as for traditional concurrency models, the question of safely replacing an agent by another one in any interacting context naturally appears. this paper proposes two tools to answer that question. on the one hand, a fully abstract semantics allows us to identify two processes which behave similarly in any context. on the other hand, a refinement theory allows us to compare processes that appear to be different in view of the fully abstract semantics but which satisfy the substitutability property: if the implementation i refines the specification s and if c[s] is deadlock free, for some context c, then c[i] is also deadlock free. both theories are novel, are exposed in the context of our timed coordination languages but may actually be transposed in the context of almost any data-driven coordination language.
complexity classes for self-assembling flexible tiles. we present a theoretical model for self-assembling dna tiles with flexible branches. we encode an instance of a ''problem'' as a pot of such tiles for which a ''solution'' is an assembled complete complex without any free sticky ends. using the number of tiles in an assembled complex as a measure of complexity we show how ntime classes (such as np and nexp) can be represented with corresponding classes of the model.
quantum approaches to graph colouring. in this paper, we investigate quantum algorithms for graph colouring problems, in particular for 2- and 3-colouring of graphs. our main goal is to establish a set of quantum representations and operations suitable for the problem at hand. we propose unitary- as well as measurement-based quantum computations, also taking inspiration from answer set programming, a form of declarative programming close to traditional logic programming. the approach used is one in which we first generate arbitrary solutions to the problem, then constraining these according to the problem's input. though we do not achieve fundamental speed-ups, our algorithms show how quantum concepts can be used for programming and moreover exhibit structural differences. for example, we compute all possible colourings at the same time. we compare our algorithms with classical ones, highlighting how the same type of difficulties give rise to np-complete behaviour, and propose possible improvements.
a more effective linear kernelization for cluster editing. in the np-hard cluster editing problem, we have as input an undirected graph g and an integer k>=0. the question is whether we can transform g, by inserting and deleting at most k edges, into a cluster graph, that is, a union of disjoint cliques. we first confirm a conjecture by michael fellows [iwpec 2006] that there is a polynomial-time kernelization for cluster editing that leads to a problem kernel with at most 6k vertices. more precisely, we present a cubic-time algorithm that, given a graph g and an integer k>=0, finds a graph g^' and an integer k^'@?k such that g can be transformed into a cluster graph by at most k edge modifications iff g^' can be transformed into a cluster graph by at most k^' edge modifications, and the problem kernel g^' has at most 6k vertices. so far, only a problem kernel of 24k vertices was known. second, we show that this bound for the number of vertices of g^' can be further improved to 4k vertices. finally, we consider the variant of cluster editing where the number of cliques that the cluster graph can contain is stipulated to be a constant d>0. we present a simple kernelization for this variant leaving a problem kernel of at most (d+2)k+d vertices.
on weighted balls-into-bins games. we consider the well-known problem of randomly allocating m balls into n bins. we investigate various properties of single-choice games as well as multiple-choice games in the context of weighted balls. we are particularly interested in questions that are concerned with the distribution of ball weights, and the order in which balls are allocated. do any of these parameters influence the maximum expected load of any bin, and if yes, then how? the problem of weighted balls is of practical relevance. balls-into-bins games are frequently used to conveniently model load balancing problems. here, weights can be used to model resource requirements of the jobs, i.e., memory or running time.
the subdivision-constrained minimum spanning tree problem. motivated by the constrained minimum spanning tree (cst) problem in hassin and levin [r. hassin, a. levin, an efficient polynomial time approximation scheme for the constrained minimum spanning tree problem using matroid intersection, siam journal on computing 33 (2) (2004) 261-268], we study a new combinatorial optimization problem in this paper, called the general subdivision-constrained spanning tree problem (gscst): given a graph g=(v,e;w,c) with two nonnegative integers w(e) and c(e) for each edge e&isin;e, two positive integers b and d, the gscst problem is to first find a spanning tree t=(v,et) of g with weight &sigma;e&isin;etw(e)&le;b and then to insert some new vertices on some suitable edges in t such that each edge in the subdivision tree t' of t has its weight not beyond d. the objective is to minimize the cost &sigma;e&isin;etinsert(e)c(e) of such new vertices inserted on the suitable edges among all spanning trees of g subject to the two preceding constraints, where a subdivision tree t' of t is constructed by inserting some new vertices on the suitable edges in t, the value insert(e)=[w(e)/d] - 1 is the least number of vertices inserted and c(e) is the cost of each vertex inserted on the edge e. we obtain the following main results: (1) the gscst problem and its variant are still np-hard, by a reduction from the 0-1 knapsack problem, respectively; (2) the gscst problem as well as its variant is polynomially equivalent to the cst problem, which implies the existence of a polynomial time approximation scheme to solve the gscst problem and its variant; (3) we finally design three strongly polynomial time algorithms to solve the special versions of the gscst problem and its variant, respectively.
efficient algorithms to compute compressed longest common substrings and compressed palindromes. this paper studies two problems on compressed strings described in terms of straight line programs (slps). one is to compute the length of the longest common substring of two given slp-compressed strings, and the other is to compute all palindromes of a given slp-compressed string. in order to solve these problems efficiently (in polynomial time w.r.t. the compressed size) decompression is never feasible, since the decompressed size can be exponentially large. we develop combinatorial algorithms that solve these problems in o(n4logn) time with o(n3) space, and in o(n4) time with o(n2) space, respectively, where n is the size of the input slp-compressed strings.
towards a real-time distributed computing model. this paper introduces a simple real-time distributed computing model for message-passing systems, which reconciles the distributed computing and the real-time systems perspective: by just replacing instantaneous computing steps with computing steps of non-zero duration, we obtain a model that both facilitates real-time scheduling analysis, and retains compatibility with classic distributed computing analysis techniques and results. we provide general simulations and validity conditions for transforming algorithms from the classic synchronous model to our real-time model and vice versa, and investigate whether/which properties of real systems are inaccurately or even wrongly captured when resorting to zero step-time models. we revisit the well-studied problem of deterministic drift- and failure-free internal clock synchronization for this purpose, and show that no clock synchronization algorithm with constant running time can achieve optimal precision in our real-time model. since such an algorithm is known for the classic model, this is an instance of a problem where the standard distributed computing analysis gives too optimistic results. we prove that optimal precision is only achievable with algorithms that take @w(n) time in our model, and establish several additional algorithms and lower bounds.
approximation algorithm for maximum edge coloring. we propose a polynomial time approximation algorithm for a novel maximum edge coloring problem which arises from wireless mesh networks [ashish raniwala, tzi-cker chiueh, architecture and algorithms for an ieee 802.11-based multi-channel wireless mesh network, in: infocom 2005, pp. 2223-2234; ashish raniwala, kartik gopalan, tzi-cker chiueh, centralized channel assignment and routing algorithms for multi-channel wireless mesh networks, mobile comput. commun. rev. 8 (2) (2004) 50-65]. the problem is to color all the edges in a graph with maximum number of colors under the following q-constraint: for every vertex in the graph, all the edges incident to it are colored with no more than q (q@?z,q>=2) colors. we show that the algorithm is a 2-approximation for the case q=2 and a (1+4q-23q^2-5q+2)-approximation for the case q>2 respectively. the case q=2 is of great importance in practice. for complete graphs and trees, polynomial time accurate algorithms are found for them when q=2. the approximation algorithm gives a feasible solution to channel assignment in multi-channel wireless mesh networks.
the price of optimum in stackelberg games on arbitrary single commodity networks and latency functions. let m be a single s-t network of parallel links with load dependent latency functions shared by an infinite number of selfish users. this may yield a nash equilibrium with unbounded coordination ratio [e. koutsoupias, c. papadimitriou, worst-case equilibria, in: 16th annual symposium on theoretical aspects of computer science, stacs, vol. 1563, 1999, pp. 404-413; t. roughgarden, e. tardos, how bad is selfish routing? in: 41st ieee annual symposium of foundations of computer science, focs, 2000, pp. 93-102]. a leader can decrease the coordination ratio by assigning flow &alpha;r on m, and then all followers assign selfishly the (1-&alpha;)r remaining flow. this is a stackelberg scheduling instance(m,r,&alpha;),0&le;&alpha;&le;1. it was shown [t. roughgarden, stackelberg scheduling strategies, in: 33rd annual symposium on theory of computing, stoc, 2001, pp. 104-113] that it is weakly np-hard to compute the optimal leader's strategy. for any such network m we efficiently compute the minimum portion @b"m of flow r>0 needed by a leader to induce m's optimum cost, as well as her optimal strategy. this shows that the optimal leader's strategy on instances (m,r,@a>=@b"m) is in p. unfortunately, stackelberg routing in more general nets can be arbitrarily hard. roughgarden presented a modification of braess's paradox graph, such that no strategy controlling &alpha;r flow can induce &le;1/&alpha; times the optimum cost. however, we show that our main result also applies to any s-t net g. we take care of the braess's graph explicitly, as a convincing example. finally, we extend this result to k commodities. a conference version of this paper has appeared in [a. kaporis, p. spirakis, the price of optimum in stackelberg games on arbitrary single commodity networks and latency functions, in: 18th annual acm symposium on parallelism in algorithms and architectures, spaa, 2006, pp. 19-28]. some preliminary results have also appeared as technical report in [a.c. kaporis, e. politopoulou, p.g. spirakis, the price of optimum in stackelberg games, in: electronic colloquium on computational complexity, eccc, (056), 2005].
adversarial queuing theory with setups. we look at routing and scheduling problems on kelly type networks where the injection process is under the control of an adversary. the novelty of the model we consider is that the adversary injects requests of distinct types. resources are subject to switch-over delays or setups when they begin servicing a new request class. in this new setting, we study the behavior of sensible policies as introduced by dai and jennings [j. dai, o. jennings, stabilizing queueing networks with setups, math. oper. res. (2004) 891-922]. we first show that the model is robust in the sense that under some mild conditions universal stability of work conserving packet routing protocols is preserved for natural variants of the underlying model. also, the model's equivalence to so called token networks is established. we adapt to the multi-type request and setup setting, standard arguments for proving stability. nevertheless, we provide counterexamples that show that for several reasonable adaptations of contention resolution protocols to the multi-type case, stability results do not carry over from the single-type scenario. this motivates us to explore fluid model based arguments that could be used for proving stability for a given network. specifically we show analogues of results obtained by gamarnik [d. gamarnik, stability of adversarial queues via fluid model, in: proc. of the 39th annual symposium on foundations of computer science, 1998, pp. 60-70] but in the multi-type request with setups scenario.
safe termination detection in an asynchronous distributed system when processes may crash and recover. the termination detection problem involves detecting whether an ongoing distributed computation has ceased all its activities. we investigate the termination detection problem in an asynchronous distributed system under the crash-recovery model. it has been shown that the problem is impossible to solve under the crash-recovery model in general. we identify two conditions under which the termination detection problem can be solved in a safe manner. we also propose algorithms to detect termination under the conditions identified.
glance: a lightweight querying service for wireless sensor networks. distance-sensitivity guarantee in querying is a highly desirable property in wireless sensor networks as it limits the cost of executing a ''query'' operation to be within a constant factor of the distance to the nearest node that contains an answer. however, such a tight guarantee may require building an infrastructure for efficient resolution of queries, and the cost of maintaining this infrastructure may be prohibitive. here we show that it is possible to implement distance-sensitive querying in an efficient way by exploiting the geometry of the network. our querying service glance ensures that a ''query'' operation invoked within d distance of an event intercepts the event's ''advertise'' operation within d*s distance, where s is a ''stretch-factor'' tunable by the user.
a quadratic time 2-approximation algorithm for block sorting. the block sorting problem is the problem of minimizing the number of steps to sort a list of distinct items, where a sublist of items which are already in sorted order, called a block, can be moved in one step. we give an approximation algorithm for the block sorting problem with an approximation ratio of 2 and run time o(n^2). the approximation algorithm is based on the related concept of block deletion. we show that finding an optimum block deletion sequence can be done in o(n^2) time, even though block sorting is known to be np-hard. block sorting has importance in connection with optical character recognition (ocr) and is related to transposition sorting in computational biology.
meadows and the equational specification of division. the rational, real and complex numbers with their standard operations, including division, are partial algebras specified by the axiomatic concept of a field. since the class of fields cannot be defined by equations, the theory of equational specifications of data types cannot use field theory in applications to number systems based upon rational, real and complex numbers. we study a new axiomatic concept for number systems with division that uses only equations: a meadow is a commutative ring with a total inverse operator satisfying two equations which imply 0^-^1=0. all fields and products of fields can be viewed as meadows. after reviewing alternate axioms for inverse, we start the development of a theory of meadows. we give a general representation theorem for meadows and find, as a corollary, that the conditional equational theory of meadows coincides with the conditional equational theory of zero totalized fields. we also prove representation results for meadows of finite characteristic.
on the support size of stable strategies in random games. in this paper we study the support sizes of evolutionary stable strategies (ess) in random evolutionary games. we prove that, when the elements of the payoff matrix behave either as uniform, or normally distributed random variables, almost all ess have support sizes o(n), where n is the number of possible types for a player. our arguments are based exclusively on a stability property that the payoff submatrix indicated by the support of an ess must satisfy. we then combine this result with a recent result of mclennan and berg [a. mclennan, j. berg, the asymptotic expected number of nash equilibria of two player normal form games, games and economic behavior 51 (2005) 264-295], concerning the expected number of nash equilibria in normal-random bimatrix games, to show that the expected number of ess is significantly smaller than the expected number of symmetric nash equilibria of the underlying symmetric bimatrix game.
fast payment schemes for truthful mechanisms with verification. in this paper we study optimization problems with verifiable one-parameter selfish agents introduced by auletta et al. [v. auletta, r. de prisco, p. penna, p. persiano, the power of verification for one-parameter agents, in: proceedings of the 31st international colloquium on automata, languages and programming, icalp, in: lncs, vol. 3142, 2004, pp. 171-182]. our goal is to allocate load among the agents, provided that the secret data of each agent is a single positive real number: the cost they incur per unit load. in such a setting the payment is given after the load completion, therefore if a positive load is assigned to an agent, we are able to verify if the agent declared to be faster than she actually is. we design truthful mechanisms when the agents' type sets are upper-bounded by a finite value. we provide a truthful mechanism that is c&middot;(1+&epsilon;)-approximate if the underlying algorithm is c-approximate and weakly-monotone. moreover, if type sets are also discrete, we provide a truthful mechanism preserving the approximation ratio of its algorithmic part. our results improve the existing ones which provide truthful mechanisms dealing only with finite type sets and do not preserve the approximation ratio of the underlying algorithm. finally, we give applications for our payment schemes. firstly, we give a full characterization of the q‖cmax problem by using our techniques. even if our payment schemes need upper-bounded type sets, every instance of q‖cmax can be "mapped" into an instance with upper-bounded type sets preserving the approximation ratio. in conclusion, we turn our attention to binary demand games. in particular, we show that the minimum radius spanning tree admits an exact truthful mechanism with verification achieving time (and space) complexity of the fastest centralized algorithm for it. this contrasts with a recent truthful mechanism for the same problem [g. proietti, p. widmayer, a truthful mechanism for the non-utilitarian minimum radius spanning tree problem, in: proceedings of the 17th acm symposium on parallelism in algorithms and architectures, spaa, acm press, 2005, pp. 195-202] which pays a linear factor with respect to the complexity of the fastest centralized algorithm. such a result is extended to several binary demand games studied in literature.
robust self-stabilizing weight-based clustering algorithm. ad hoc networks consist of wireless hosts that communicate with each other in the absence of a fixed infrastructure. such networks cannot rely on centralized and organized network management. the clustering problem consists of partitioning network nodes into non-overlapping groups called clusters. clusters give a hierarchical organization to the network that facilitates network management and that increases its scalability. in a weight-based clustering algorithm, the clusterheads are selected according to their weight (a node's parameter). the higher the weight of a node, the more suitable this node is for the role of clusterhead. in ad hoc networks, the amount of bandwidth, memory space or battery power of a node could be used to determine weight values. a self-stabilizing algorithm, regardless of the initial system configuration, converges to legitimate configurations without external intervention. due to this property, self-stabilizing algorithms tolerate transient faults and they are adaptive to any topology change. in this paper, we present a robust self-stabilizing weight-based clustering algorithm for ad hoc networks. the robustness property guarantees that, starting from an arbitrary configuration, after one asynchronous round, the network is partitioned into clusters. after that, the network stays partitioned during the convergence phase toward a legitimate configuration where the clusters verify the ''ad hoc clustering properties''.
on small, reduced, and fast universal accepting networks of splicing processors. in this paper, we show that accepting networks of splicing processors (ansps) of size 2 are computationally complete. since, by definition, an ansp needs at least two nodes to perform non-trivial computations, this completely settles the question of designing complete ansps of minimal size. also, we derive from this result the fact that all the languages in pspace can be accepted by ansps of size 2, having polynomial length complexity (the ansp complexity measure for the space used in a computation). however, the construction that we propose, although efficient from the descriptional complexity and space complexity points of view, does not seem to have good properties from the time complexity point of view. in this respect, we prove that ansps of size three can decide all languages in np in polynomial time. the previous lower bound on size for both completeness and efficient acceptance of np-languages was seven. we also consider ansps with restricted features, proving the following normal forms: for any ansp there exists an equivalent ansp without input filters, and one without output filters. finally, we show how to construct a small universal ansp and make several considerations on the computational efficiency of universal ansps.
a note on universal composable zero-knowledge in the common reference string model. pass observed that universal composable zero-knowledge (uczk) protocols in the common reference string (crs) model lose deniability that is a natural security property and implication of the zk functionality in accordance with the uc framework. an open problem (or, natural query) raised in the literature is: are there any other essential security properties, other than the well-known deniability property, that could be lost by uczk in the crs model, in comparison with the zk functionality in accordance with the uc framework? in this work, we answer this open question (or, natural query), by showing that when running concurrently with other protocols uczk in the crs model can lose proof of knowledge (pok) property that is very essential and core security implication of the zk functionality. this is demonstrated by concrete attack against naturally existing uczk protocols in the crs model. then, motivated by our attack, we make further clarifications of the underlying reasons beneath the concrete attack, and investigate the precise security guarantee of uc with crs.
the complexity of the matroid-greedoid partition problem. we show that the maximum matroid-greedoid partition problem is np-hard to approximate to within 1/2+&epsilon; for any &epsilon;>0, which matches the trivial factor 1/2 approximation algorithm. the main tool in our hardness of approximation result is an extractor code with polynomial rate, alphabet size and list size, together with an efficient algorithm for list-decoding. we show that the recent extractor construction of guruswami, umans and vadhan [v. guruswami, c. umans, s.p. vadhan, unbalanced expanders and randomness extractors from parvaresh-vardy codes, in: ieee conference on computational complexity, ieee computer society, 2007, pp. 96-108] can be used to obtain a code with these properties. we also show that the parameterized matroid-greedoid partition problem is fixed-parameter tractable.
short fail-stop signature scheme based on factorization and discrete logarithm assumptions. fail-stop signature (fss) schemes protect a signer against a forger with unlimited computational power by enabling the signer to provide a proof of forgery, if it occurs. a decade after its invention, there have been several fss schemes proposed in the literature. nonetheless, the notion of short fss scheme has not been addressed yet. furthermore, the short size in signature schemes has been done mainly with the use of pairings. in this paper, we propose a construction of short fss scheme based on factorization and discrete logarithm assumption. however, in contrast to the known notion in the literature, our signature scheme does not incorporate any pairing operations. nonetheless, our scheme is the shortest fss scheme compared to all existing schemes in the literature that are based on the same assumption. the efficiency of our scheme is comparable to the best known fss scheme, that is based on the discrete logarithm assumption.
robust random number generation for peer-to-peer systems. we consider the problem of designing an efficient and robust distributed random number generator for peer-to-peer systems that is easy to implement and works even if all communication channels are public. a robust random number generator is crucial for avoiding adversarial join-leave attacks on peer-to-peer overlay networks. we show that our new generator together with a light-weight rule recently proposed in [b. awerbuch, c. scheideler, towards a scalable and robust dht, in: proc. of the 18th acm symp. on parallel algorithms and architectures, spaa, 2006. see also http://www14.in.tum.de/personen/scheideler] for keeping peers well distributed can keep various structured overlay networks in a robust state even under a constant fraction of adversarial peers.
on the bipanpositionable bipanconnectedness of hypercubes. a bipartite graph g is bipanconnected if, for any two distinct vertices x and y of g, it contains an [x,y]-path of length l for each integer l satisfying dg(x,y)&le;/&le;|v(g)|-1 and 2|(l-dg(x,y)), where dg(x,y) denotes the distance between vertices x and y in g and v(g) denotes the vertex set of g. we say a bipartite graph g is bipanpositionably bipanconnected if, for any two distinct vertices x and y of g and for any vertex z&isin;v(g)-{x,y}, it contains a path pl,k of length l such that x is the beginning vertex of pl,k, z is the (k+1)-th vertex of pl,k, and y is the ending vertex of pl,k for each integer l satisfying dg(x,z)+dg(y,z)&le;/&le;|v(g)|-1 and 2|(l-dg(x,z)-dg(y,z)) and for each integer k satisfying dg(x,z)&le;k&le;l-dg(y,z) and 2|(k-dg(x,z)). in this paper, we prove that an n-cube is bipanpositionably bipanconnected if n&ge;4. as a consequence, many properties of hypercubes, such as bipancyclicity, bipanconnectedness, bipanpositionable hamiltonicity, etc., follow directly from our result.
approximately optimal trees for group key management with batch updates. we investigate the group key management problem for broadcasting applications. previous work showed that, in handling key updates, batch rekeying can be more cost effective than individual rekeying. one model for batch rekeying is to assume that every user has probability p of being replaced by a new user during a batch period with the total number of users unchanged. under this model, it was recently shown that an optimal key tree can be constructed in linear time when p is a constant and in o(n^4) time when p->0. in this paper, we investigate more efficient algorithms for the case p->0, i.e., when membership changes are sparse. we design an o(n) heuristic algorithm for the sparse case and show that it produces a nearly 2-approximation to the optimal key tree. simulation results show that its performance is even better in practice. we also design a refined heuristic algorithm and show that it achieves an approximation ratio of 1+@e for any fixed @e>0 and n, as p->0. finally, we give another approximation algorithm for any p@?(0,0.693) which is shown to be quite good by our simulations.
improving the average delay of sorting. in previous work we have introduced an average case measure for the time complexity of boolean circuits. instead of fixed circuit depth, for each input we take the minimal number of time steps necessary to perform the computation for that particular input using gates that forward their output values as soon as possible. this measure is called delay. based on it, the complexity of a whole class of functions that can be described as prefix computations has been analysed in detail. here we consider the problem to sort large integers that are given in binary notation. contrary to a word comparator sorting circuitc where a basic computational element, a comparator, is charged with a single time step to compare two elements, in a bit comparator circuitc^' a comparison of two binary numbers has to be implemented by a boolean subcircuit cm called comparator module that is built from boolean gates of bounded fanin. thus, compared to c, the depth of c^' will be larger by a factor up to the depth of cm. our goal is to minimize the average delay of bit comparator sorting circuits. the worst-case delay can be estimated by the depth of the circuit. for this worst-case measure two topologically quite different designs seem to be appropriate for the comparator modules: a tree-like one if the inputs are long numbers, otherwise a linear array working in a pipelined fashion. inserting these into a word comparator circuit we get bit level sorting circuits for binary numbers of length m, for which the depth is either increased by a multiplicative factor of order logm or by an additive term of order m. we show that these obvious solutions can be improved significantly by constructing efficient sorting and merging circuits for the bit model that only suffer a constant factor time loss on the average if the inputs are uniformly distributed. this is done by designing suitable hybrid architectures of tree compaction and pipelining. these results can also be extended to classes of nonuniform distributions if we put a bound on the complexity of the distributions themselves.
data aggregation in sensor networks: balancing communication and delay costs. in a sensor network the sensors, or nodes, obtain data and have to communicate these data to a central node. because sensors are battery powered they are highly energy constrained. data aggregation can be used to combine data of several sensors into a single message, thus reducing sensor communication costs at the expense of message delays. thus, the main problem of data aggregation is to balance the communication and delay costs. in this paper we study the data aggregation problem as a bicriteria optimization problem; the objectives we consider are to minimize maximum energy consumption of a sensor and a function of the maximum latency costs of a message. we consider distributed algorithms under a synchronous time model, under an asynchronous time model, and under an almost synchronous time model, where sensor clocks are synchronized up to a small drift. we use competitive analysis to assess the quality of the algorithms.
drawing slicing graphs with face areas. we consider orthogonal drawings of a plane graph g with specified face areas. for a natural number k, a k-gonal drawing of g is an orthogonal drawing such that the boundary of g is drawn as a rectangle and each inner face is drawn as a polygon with at most k corners whose area is equal to the specified value. in this paper, we show that every slicing graph g with a slicing tree t and a set of specified face areas admits a 10-gonal drawing d such that the boundary of each slicing subgraph that appears in t is also drawn as a polygon with at most 10 corners. such a drawing d can be found in linear time.
a generalization of thue freeness for partial words. this paper approaches the combinatorial problem of thue freeness for partial words. partial words are sequences over a finite alphabet that may contain a number of ''holes''. first, we give an infinite word over a three-letter alphabet which avoids squares of length greater than two even after we replace an infinite number of positions with holes. then, we give an infinite word over an eight-letter alphabet that avoids longer squares even after an arbitrary selection of its positions are replaced with holes, and show that the alphabet size is optimal. we find similar results for overlap-free partial words.
the antimagicness of the cartesian product of graphs. an antimagic labeling of a graph with m edges and n vertices is a bijection from the set of edges to the set {1,2,3,...,m} such that all the nvertex-sums are pairwise distinct, where the vertex-sum of a vertex v is the sum of labels of all edges incident with v. a graph is called antimagic if it has an antimagic labeling. the antimagicness of the cartesian product of graphs in several special cases has been studied [tao-ming wang, toroidal grids are anti-magic, in: proc. 11th annual international computing and combinatorics conference, coocoon'2005, in: lncs, vol. 3595, springer, 2005, pp. 671-679, yongxi cheng, a new class of antimagic cartesian product graphs, discrete mathematics 308 (24) (2008) 6441-6448]. in this paper, we develop new construction methods that are applied to more general cases. we prove that the cartesian product of paths is antimagic, if one of them has at least three edges. this (almost) answers the open problems in [yongxi cheng, lattice grids and prisms are antimagic, theoretical computer science 374 (2007) 66-73]. we also prove that the cartesian product of an antimagic regular graph and a connected graph is antimagic, which extends the results of the latter of the two references, where several special cases are studied.
graph searching with advice. fraigniaud et al. [l. blin, p. fraigniaud, n. nisse, s. vial, distributing chasing of network intruders, in: 13th colloquium on structural information and communication complexity, sirocco, in: lncs, vol. 4056, springer-verlag, 2006, pp. 70-84] introduced a new measure of difficulty for a distributed task in a network. the smallest number of bits of advice of a distributed problem is the smallest number of bits of information that has to be available to nodes in order to accomplish the task efficiently. our paper deals with the number of bits of advice required to perform efficiently the graph searching problem in a distributed setting. in this variant of the problem, all searchers are initially placed at a particular node of the network. the aim of the team of searchers is to clear a contaminated graph in a monotone connected way, i.e., the cleared part of the graph is permanently connected, and never decreases while the search strategy is executed. moreover, the clearing of the graph must be performed using the optimal number of searchers, i.e. the minimum number of searchers sufficient to clear the graph in a monotone connected way in a centralized setting. we show that the minimum number of bits of advice permitting the monotone connected and optimal clearing of a network in a distributed setting is @q(nlogn), where n is the number of nodes of the network. more precisely, we first provide a labelling of the vertices of any graph g, using a total of o(nlogn) bits, and a protocol using this labelling that enables the optimal number of searchers to clear g in a monotone connected distributed way. then, we show that this number of bits of advice is optimal: any distributed protocol requires @w(nlogn) bits of advice to clear a network in a monotone connected way, using an optimal number of searchers.
computational prediction of nucleic acid secondary structure: methods, applications, and challenges. rna molecules are crucial in different levels of cellular function, ranging from translation and regulating genes to coding for proteins. additionally, nucleic acids (rna and dna molecules) are designed for novel applications in biotechnology. understanding the structure of a molecule is important in inferring its function, and computational methods for structure prediction have captured the interest of many researchers. some functions of rna molecules in cells, such as gene regulation, result from the binding of one rna molecule to another, so-called target rna molecule. this has led to recent interest in prediction of the secondary structure formed from interacting molecules. in this paper, we provide a brief overview of methods, applications, and challenges in computational prediction of nucleic acid secondary structure, both for single strands and for interacting strands.
copower functors. we give a common generalization of two earlier constructions in [h.p. gumm, t. schroder, monoid-labeled transition systems, electronic notes in theoretical computer science 44 (1) (2001) 184-203], that yielded coalgebraic type functors for weighted, resp. fuzzy transition systems. transition labels for these systems were drawn from a commutative monoid m or a complete semilattice l, with the transition structure interacting with the algebraic structure on the labels. here, we show that those earlier signature functors are in fact instances of a more general construction, provided by the so-called copower functor. exemplary, we instantiate this functor in categories given by varieties v of algebras. in particular, for the variety s of all semigroups, or the variety m of all (not necessarily commutative) monoids, and with m any monoid, we find that the resulting copower functors m"s[-] (resp m"m[-]) weakly preserve pullbacks if and only if m is equidivisible (resp. conical and equidivisible). finally, we show that copower functors are universal in the sense that every faithful set-functor can be seen as an instance of an appropriate copower functor.
executability of scenarios in petri nets. in this paper, we show that it can be tested in polynomial time as to whether a scenario is an execution of a petri net. this holds for a wide variety of petri net classes, ranging from elementary nets to general inhibitor nets. scenarios are given by causal structures expressing causal dependencies and concurrency among events. in the case of elementary nets and of place/transition nets, such causal structures are partial orders among transition occurrences. for several extended petri net classes, the extension of partial orders to stratified order structures is considered. the algorithms are based on the representation of the non-sequential behavior of petri nets by so-called token flow functions and a characterization of petri net executions called token flow property. this property allows nontrivial transformations into flow optimization problems, which can be solved in polynomial time. the paper is a revised, consolidated and extended version of the conference papers [g. juhas, r. lorenz, j. desel, can i execute my scenario in your net?, in: g. ciardo, p. darondeau (eds.), icatpn, in: lecture notes in computer science, springer, 2005, pp. 289-308; r. lorenz, s. mauser, r. bergenthum, testing the executability of scenarios in general inhibitor nets, in: acsd, ieee computer society, 2007, pp. 167-176] and includes parts of the habilitation thesis [r. lorenz, szenario-basierte verifikation und synthese von perinetzen: theorie und anwendungen, habilitation, 2006].
treewidth and logical definability of graph products. in this paper we describe an algorithm that, given a tree-decomposition of a graph g and a tree-decomposition of a graph h, provides a tree-decomposition of the cartesian product of g and h. using this algorithm, we derive upper bounds on the treewidth (resp. on the pathwidth) of the cartesian product of two graphs, expressed in terms of the treewidth (resp. pathwidth) and the size of the factor graphs. in the context of graph grammars and graph logic, we prove that the cartesian product of a class of graphs by a finite set of graphs preserves the property of being a context-free set, and that the cartesian product by a finite set of connected graphs preserves ms"1-definability and ms"2-definability. we also prove that the cartesian product of two ms"2-definable classes of connected graphs is ms"2-definable.
computational expressiveness of genetic systems. we introduce genetic systems, a formalism inspired by genetic regulatory networks and suitable for modeling the interactions between the genes and the proteins, acting as regulatory products. the generation of new objects, representing proteins, is driven by genetic gates: a new object is produced when all the activator objects are available in the system, and no inhibitor object is available. activators are not consumed by the application of such an evolution rule. objects disappear because of degradation: each object is equipped with a lifetime, and the object decays when such a lifetime expires. we investigate the computational expressiveness of genetic systems: we show that they are turing equivalent by providing encodings of random access machines in genetic systems.
on the pseudo-achromatic number problem. we study the parameterized complexity of the pseudo-achromatic number problem: given an undirected graph and a parameter k, determine if the graph can be partitioned into k groups such that every two groups are connected by at least one edge. this problem has been extensively studied in graph theory and combinatorial optimization. we show that the problem has a kernel of at most (k-2)(k+1) vertices that is constructable in time o(mn), where n and m are the number of vertices and edges, respectively, in the graph, and k is the parameter. this directly implies that the problem is fixed-parameter tractable. we also study generalizations of the problem and show that they are parameterized intractable.
membrane computing with transport and embedded proteins. in this paper, we look at the expressive power of p systems with proteins embedded on the membranes. the rules governing the evolution of the embedded proteins are inspired from brane calculi. we use some basic operations of brane calculi, namely, exo, endo, bud, mate, pino, wrap in the formalism of membrane computing. we also use rules allowing the movement of proteins, to pass through membranes and attach to and detach from the membranes. combining the two kinds of operations, namely, brane calculi operations as well as protein movement operations, we have obtained some universality results of p systems. we have also identified some decidable sub-classes of p systems by restricting the use of the protein movement rules.
on existence of reporter strands in dna-based graph structures. through self-assembly of branched junction molecules many different dna structures (graphs) can be assembled. we show that every multigraph can be assembled by dna such that there is a single strand that traces each edge in the graph at least once. this strand corresponds to a boundary component of a two-dimensional orientable surface that has the given graph as a deformation retract. this boundary component traverses every edge at least once, and it defines a circular path in the graph that ''preserves the graph structure'' and traverses each edge.
linear-size log-depth negation-limited inverter for k-tonic binary sequences. in negation-limited complexity, one considers circuits with a limited number of not gates, being motivated by the gap in our understanding of monotone versus general circuit complexity. in this context, the study of inverters, i.e., circuits with inputs x"1,...,x"n and outputs @?x"1,...,@?x"n, is fundamental since an inverter with r nots can be used to convert a general circuit to one with only r nots. beals, nishino, and tanaka [r. beals, t. nishino, k. tanaka, on the complexity of negation-limited boolean networks, siam journal on computing 27 (5) (1998) 1334-1347. a preliminary version appears in: proceedings of stoc95: the 27th annual acm symposium on theory of computing, 1995, pp. 585-595] gave a construction of an n-inverter with size o(nlogn), depth o(logn), and @?log"2(n+1)@? nots. a zero-one sequence x"1,...,x"n is k-tonic if the number of i's such that x"i
two semi-online scheduling problems on two uniform machines. this paper considers two semi-online scheduling problems, one with known optimal value and the other with known total sum, on two uniform machines with a machine speed ratio of s&ge;1. for the first problem, we provide an optimal algorithm for s&isin;[1+&radic;3/2, 1+&radic;21/4], and improved algorithms or/and lower bounds for s&isin;[1+&radic;21/4, &radic;3], over which the optimal algorithm is unknown. as a result, the largest gap between the competitive ratio and the lower bound decreases to 0.02192. for the second problem, we also present algorithms and lower bounds for s&ge;1. the largest gap between the competitive ratio and the lower bound is 0.01762, and the length of the interval over which the optimal algorithm is unknown is 0.47382. our algorithms and lower bounds for these two problems provide insights into their differences, which are unusual from the viewpoint of the known results on these two semi-online scheduling problems in the literature.
path finding in the tile assembly model. swarm robotics, active self-assembly, and amorphous computing are fields that focus on designing systems of large numbers of small, simple components that can cooperate to complete complex tasks. many of these systems are inspired by biological systems, and all attempt to use the simplest components and environments possible, while still being capable of achieving their goals. the canonical problems for such biologically-inspired systems are shape assembly and path finding. in this paper, we demonstrate path finding in the well-studied tile assembly model, a model of molecular self-assembly that is strictly simpler than other biologically-inspired models. as in related work, our systems function in the presence of obstacles and can be made fault-tolerant. the path-finding systems use @q(1) distinct components and find minimal-length paths in time linear in the length of the path.
optimal conclusive sets for comparator networks. a set of input vectors s is conclusive for a certain functionality if, for every comparator network, correct functionality for all input vectors is implied by correct functionality for all vectors in s. we consider four functionalities of comparator networks: sorting, merging, sorting of bitonic vectors, and halving. for each of these functionalities, we present two conclusive sets of minimal cardinality. the members of the first set are restricted to be binary, while the members of the second set are unrestricted. for all the above functionalities, except halving, the unrestricted conclusive set is much smaller than the binary one.
efficient algorithms for two generalized 2-median problems and the group median problem on trees. the p-median problem on a tree t is to find a set s of p vertices on that minimizes the sum of distances from t's vertices to s. in this paper, we study two generalizations of the 2-median problem, which are obtained by imposing constraints on the two vertices selected as a 2-median: one is to limit their distance while the other is to limit their eccentricity. previously, both the best upper bounds of these two generalizations were o(n2) [a. tamir, d. perez-brito, j.a. moreno-perez, a polynomial algorithm for the p-centdian problem on a tree, networks 32 (1998) 255-262; b.-f. wang, s.-c. ku, k.-h. shi, cost-optimal parallel algorithms for the tree bisector problem and applications, ieee transactions on parallel and distributed systems 12 (9) (2001) 888-898]. in this paper, we solve both in o(nlogn) time. we also study cases when linear time algorithms exist for the two generalizations. for example, we solve both in linear time when edge lengths and vertex weights are all polynomially bounded integers. furthermore, we consider the relaxation of the two generalized problems by allowing 2-medians on any position of edges, instead of just on vertices, and we give o(nlogn)-time algorithms for them. a problem, named the tree marker problem, arises several times in our approaches to the two generalized 2-median problems, and we give an o(nlogn)-time algorithm for this problem. we also use this algorithm to speedup an algorithm of gupta and punnen [s.k. gupta, a.p. punnen, group center and group median of a tree, european journal of operational research 65 (1993) 400-406] for the group median problem, improving the running time from o(kn) to o(n+klogn), where k is the number of groups in the input.
rapid almost-complete broadcasting in faulty networks. this paper studies the problem of broadcasting in synchronous point-to-point networks, where one initiator owns a piece of information that has to be transmitted to all other vertices as fast as possible. the model of fractional dynamic faults with threshold is considered: in every step either a fixed number c(g)-1, where c(g) is the edge connectivity of the communication graph, or a fraction @a of sent messages can be lost depending on which quantity is larger. as the main result we show that in complete graphs and hypercubes it is possible to inform all but a constant number of vertices, exhibiting only a logarithmic slowdown, i.e. in time o(dlogn) where d is the diameter of the network and n is the number of vertices. moreover, for complete graphs under some additional conditions (sense of direction, or @a
what does it mean to say that a physical system implements a computation? when we are concerned with the logical form of a computation and its formal properties, then it can be theoretically described in terms of mathematical and logical functions and relations between abstract entities. however, actual computation is realised by some physical process, and the latter is of course subject to physical laws and the laws of thermodynamics in particular. an issue that has been the subject of much controversy is that of whether or not there are any systematic connections between the logical properties of computations considered abstractly and the thermodynamical properties of their concrete physical realizations. landauer [r. landauer, irreversibility and heat generation in the computing process, ibm journal of research and development 5 (1961) 183-191. reprinted in leff and rex (1990)] proposed such a general connection, known as landauer's principle. to resolve this matter an analysis of the notion of the implementation of a computation by a physical system is clearly required. another issue that calls for an analysis of implementation is that of realism about computation. the account of implementation presented here is based on the notion of an l-machine. this is a hybrid physical-logical entity that combines a physical device, a specification of which physical states of that device correspond to various logical states, and an evolution of that device which corresponds to the logical transformation l. the most general form of landauer's principle can be precisely stated in terms of l-machines, namely that the logical irreversibility of l implies the thermodynamic irreversibility of every corresponding l-machine.
an approximation algorithm to the k-steiner forest problem. given a graph g, an integer k, and a demand set d={(s"1,t"1),...,(s"l,t"l)}, the k-steiner forest problem finds a forest in graph g to connect at least k demands in d such that the cost of the forest is minimized. this problem was proposed by hajiaghayi and jain in soda'06. thereafter, using a lagrangian relaxation technique, segev et al. gave the first approximation algorithm to this problem in esa'06, with performance ratio o(n^2^/^3logl). we give a simpler and faster approximation algorithm to this problem with performance ratio o(n^2^/^3logk) via greedy approach, improving the previously best known ratio in the literature.
empire of colonies: self-stabilizing and self-organizing distributed algorithm. self-stabilization ensures automatic recovery from an arbitrary state; we define self-organization as a property of algorithms which display local attributes. more precisely, we say that an algorithm is self-organizing if (1) it converges in sublinear time and (2) reacts ''fast'' to topology changes. if s(n) is an upper bound on the convergence time and d(n) is an upper bound on the convergence time following a topology change, then s(n)@?o(n) and d(n)@?o(s(n)). the self-organization property can then be used for gaining, in sub-linear time, global properties and reaction to changes. we present self-stabilizing and self-organizing algorithms for many distributed algorithms, including distributed snapshot and leader election. we present a new randomized self-stabilizing distributed algorithm for cluster definition in communication graphs of bounded degree processors. these graphs reflect sensor networks deployment. the algorithm converges in o(logn) expected number of rounds, handles dynamic changes locally and is, therefore, self-organizing. applying the clustering algorithm to specific classes of communication graphs, in o(logn) levels, using an overlay network abstraction, results in a self-stabilizing and self-organizing distributed algorithm for hierarchy definition. given the obtained hierarchy definition, we present an algorithm for hierarchical distributed snapshots. the algorithms are based on a new basic snap-stabilizing snapshot algorithm, designed for message passing systems in which a distributed spanning tree is defined and in which processors communicate using bounded links capacity. the algorithm is on-demand self-stabilizing when no such distributed spanning tree is defined. namely, it stabilizes regardless of the number of snapshot invocations. the combination of the self-stabilizing and self-organizing distributed hierarchy construction and the snapshot algorithm forms an efficient self-stabilizer transformer. given a distributed algorithm for a specific task, we are able to convert the algorithm into a self-stabilizing algorithm for the same task with an expected convergence time of o(log^2n) rounds.
the consequence relation in the logic of commutative gbl-algebras is pspace-complete. commutative, integral and bounded gbl-algebras form a subvariety of residuated lattices which provides the algebraic semantics of an interesting common fragment of intuitionistic logic and of several fuzzy logics. it is known that both the equational theory and the quasiequational theory of commutative gbl-algebras are decidable (in contrast to the noncommutative case), but their complexity has not been studied yet. in this paper, we prove that both theories are in pspace, and that the quasiequational theory is pspace-hard.
from adaptive renaming to set agreement. the adaptive m-renaming problem consists of providing processes with a new name taken from a name space whose size m depends only on the number p of processes that participate in the renaming (and not on the total number n of processes that could ask for a new name). the k-set agreement problem allows each process that proposes a value to decide a proposed value in such a way that at most k different values are decided. in an asynchronous system prone to up to t process crash failures, and where processes can cooperate by accessing atomic read/write registers only, the best that can be done is a renaming space of size m=p+t. in the same setting, the k-set agreement problem cannot be solved when t>=k. this paper focuses on the way a solution to the adaptive renaming problem can help in solving the k-set agreement problem when t>=k. it has two contributions. considering the case k=t (1@?t2k (i.e. adaptive (p+k-1)-renaming allows progressing from k>t to k=t, but does not allow bypassing the ''k=t'' frontier when n>2k).
probabilistic mobile ambients. the calculus of mobile ambients has been introduced for expressing mobility and mobile computation. in this paper we present a probabilistic version of mobile ambients by augmenting the syntax of the original ambient calculus with a (guarded) probabilistic choice operator. to allow for the representation of both the probabilistic behaviour introduced through the new probabilistic choice operator and the nondeterminism present in the original ambient calculus we use probabilistic automata as the underpinning semantic model. the ambient logic is a logic for mobile ambients that contains a novel treatment of both locations and hidden names. for specifying properties of probabilistic mobile ambients, we extend this logic to specify probabilistic behaviour. in addition, to show the utility of our approach we present an example of a virus infecting a network.
hascasl: integrated higher-order specification and program development. we lay out the design of hascasl, a higher order extension of the algebraic specification language casl that serves both as a wide-spectrum language for the rigorous specification and development of software, in particular but not exclusively in modern functional programming languages, and as an expressive standard language for higher-order logic. distinctive features of hascasl include partial higher order functions, higher order subtyping, shallow polymorphism, and an extensive type-class mechanism. moreover, hascasl provides dedicated specification support for monad-based functional-imperative programming with generic side effects, including a monad-based generic hoare logic.
single machine parallel-batch scheduling with deteriorating jobs. we consider several single machine parallel-batch scheduling problems in which the processing time of a job is a linear function of its starting time. we give a polynomial-time algorithm for minimizing the maximum cost, an o(n5) time algorithm for minimizing the number of tardy jobs, and an o(n2) time algorithm for minimizing the total weighted completion time. furthermore, we prove that the problem for minimizing the weighted number of tardy jobs is binary np-hard.
two improved range-efficient algorithms for f estimation. we present two new algorithms for the range-efficient f"0 estimating problem and improve the previously best known result, proposed by pavan and tirthapura in 2005. furthermore, our algorithms can be applied to improve the previously best known result for the max-dominance norm problem.
a variant of the tandem duplication - random loss model of genome rearrangement. in [k. chaudhuri, k. chen, r. mihaescu, s. rao, on the tandem duplication-random loss model of genome rearrangement, in: soda, 2006, pp. 564-570], chaudhuri, chen, mihaescu and rao study algorithmic properties of the tandem duplication - random loss model of genome rearrangement, well-known in evolutionary biology. in their model, the cost of one step of duplication-loss of width k is &alpha;k for &alpha;=1 or &alpha;&ge;2. in this paper, we study a variant of this model, where the cost of one step of width k is 1 if k&le;k and &infin; if k>k, for any value of the parameter k&epsilon;ℕ&cup;{&infin;}. we first show that permutations obtained after p steps of width k define classes of pattern-avoiding permutations. we also compute the numbers of duplication-loss steps of width k necessary and sufficient to obtain any permutation of sn, in the worst case and on average. in this second part, we may also consider the case k=k(n), a function of the size n of the permutation on which the duplication-loss operations are performed.
computational virtuality in biological systems. computational virtuality is introduced as a key distinguishing feature of genuinely computational systems. evidence is provided that the basic cellular machinery possesses virtuality. accordingly, one can step beyond the commonplace metaphor of computation as applied to molecular biology, and come to view the cell as a genuine computing system. the human nervous system is analyzed in the same light, setting an agenda for research on virtuality in recurrent neural networks, whose outcomes in the way of theoretical results and simulation of biological neural systems may heuristically guide neuroscientists in the search for virtual computing in the brain.
two complementary operations inspired by the dna hairpin formation: completion and reduction. we consider two complementary operations: hairpin completion introduced in [d. cheptea, c. martin-vide, v. mitrana, a new operation on words suggested by dna biochemistry: hairpin completion, in: proc. transgressive computing, 2006, pp. 216-228] with motivations coming from dna biochemistry and hairpin reduction as the inverse operation of the hairpin completion. both operations are viewed here as formal operations on words and languages. we settle the closure properties of the classes of regular and linear context-free languages under hairpin completion in comparison with hairpin reduction. while the class of linear context-free languages is exactly the weak-code image of the class of the hairpin completion of regular languages, rather surprisingly, the weak-code image of the class of the hairpin completion of linear context-free languages is a class of mildly context-sensitive languages. the closure properties with respect to the hairpin reduction of some time and space complexity classes are also studied. we show that the factors found in the general cases are not necessary for regular and context-free languages. this part of the paper completes the results given in the earlier paper, where a similar investigation was made for hairpin completion. finally, we briefly discuss the iterated variants of these operations.
improved approximation bounds for edge dominating set in dense graphs. we analyze the simple greedy algorithm that iteratively removes the endpoints of a maximum-degree edge in a graph, where the degree of an edge is the sum of the degrees of its endpoints. this algorithm provides a 2-approximation to the minimum edge dominating set and minimum maximal matching problems. we refine its analysis and give an expression of the approximation ratio that is strictly less than 2 in the cases where the input graph has n vertices and at least @e(n2) edges, for @e>1/2. this ratio is shown to be asymptotically tight for @e>1/2.
hop chains: secure routing and the establishment of distinct identities. we present a secure routing protocol that is immune to sybil attacks and that can tolerate collusion of byzantine routers. it can tolerate either initial collusion of byzantine routers or runtime collusion of non-adjacent byzantine routers, both in the absence of runtime collusion between adjacent routers. for these settings, the calculated distance from a destination to a node is not smaller than the actual shortest distance from the destination to the node. the protocol can also simultaneously tolerate initial collusion of byzantine routers and runtime collusion of adjacent byzantine routers but in the absence of runtime collusion between non-adjacent routers. for this setting, it guarantees a bound on the difference between the calculated distance and the actual shortest distance. the bound depends on the number of byzantine routers on a path. the protocol makes very weak timing assumptions and requires synchronization only between neighbors or second neighbors. we propose to use this protocol for secure localization of routers using hop-count distances, which can be then used as a proof of identity of nodes.
nadia busi (1968-2007). nadia busi obtained a master in computer science in 1993, at the university of bologna. in 1997 she obtained a phd in theoretical computer science at the university of siena; her thesis entitled "petri nets with inhibitor and read arcs: semantics, analysis and application to process calculi" won the annual prize of the italian chapter of eatcs for the best italian phd thesis.the scientific activity of nadia was very broad, and covered different aspects of theoretical computer science. her first interests concerned the investigation of expressiveness problems in concurrency theory. in collaboration with roberto gorrieri and gianluigi zavattaro, she studied primitive nets, a subclass of petri nets with inhibitor arcs, investigating various decidable properties of such nets. she also studied different properties of various process calculi, by mapping them on primitive nets.
computing on a partially eponymous ring. we study the partially eponymous model of distributed computation, which simultaneously generalizes the anonymous and the eponymous models. in this model, processors have identities, which are neither necessarily all identical (as in the anonymous model) nor necessarily unique (as in the eponymous model). in a decision problem formalized as a relation, processors receive inputs and seek to reach outputs respecting the relation. we focus on the partially eponymous ring, and we shall consider the computation of circularly symmetric relations on it. we consider sets of rings where all rings in the set have the same multiset of identity multiplicities. *we distinguish between solvability and computability: in solvability, processors are required to always reach outputs respecting the relation; in computability, they must do so whenever this is possible, and must otherwise report impossibility. -we present a topological characterization of solvability for a relation on a set of rings, which can be expressed as an efficiently checkable, number-theoretic predicate. -we present a universal distributed algorithm for computing a relation on a set of rings; it runs any distributed algorithm for constructing views, followed by local steps. *we derive, as our main result, a universal upper bound on the message complexity to compute a relation on a set of rings; this bound demonstrates a graceful degradation with the least minimum base, a parameter indicating the degree of least possible eponymity for a set of rings. thereafter, we identify two cases where a relation can be computed on a set of rings, with rings of size n, with an efficient number of o(n@?lgn) messages.
how liquid is biological signalling? this paper proposes an investigation of the global statistics of synthetic protein networks-a step towards a systemic understanding of their design space. we derive a liquidity index which describes the onset of the phase transition where an ensemble of agents aggregates into a giant cluster. this index captures the influence of both the domain distribution of agents and the binding strengths of their various domains in the limit of infinite populations. in simple cases it is possible to derive an explicit analytical expression of this index, which allows one to compare with simulations, and get a sense of how it transfers to the concrete finite case.
constructing edge-disjoint spanning trees in locally twisted cubes. the use of edge-disjoint spanning trees for data broadcasting and scattering problem in networks provides a number of advantages, including the increase of bandwidth and fault-tolerance. in this paper, we present an algorithm for constructing n edge-disjoint spanning trees in an n-dimensional locally twisted cube. since the n-dimensional locally twisted cube is regular with the common degree n, the number of constructed trees is optimal.
upper bounds and algorithms for parallel knock-out numbers. we study parallel knock-out schemes for graphs. these schemes proceed in rounds in each of which each surviving vertex simultaneously eliminates one of its surviving neighbours; a graph is reducible if such a scheme can eliminate every vertex in the graph. we resolve the square-root conjecture, first posed at mfcs 2004, by showing that for a reducible graph g, the minimum number of required rounds is o(n); in fact, our result is stronger than the conjecture as we show that the minimum number of required rounds is o(@a), where @a is the independence number of g. this upper bound is tight. we also show that for reducible k"1","p-free graphs at most p-1 rounds are required. it is already known that the problem of whether a given graph is reducible is np-complete. for claw-free graphs, however, we show that this problem can be solved in polynomial time. we also pinpoint a relationship with (locally bijective) graph homomorphisms.
a study of substitution, using nominal techniques and fraenkel-mostowksi sets. fraenkel-mostowski (fm) set theory delivers a model of names and alpha-equivalence. this model, now generally called the 'nominal' model, delivers inductive datatypes of syntax with alpha-equivalence - rather than inductive datatypes of syntax, quotiented by alpha-equivalence. the treatment of names and alpha-equivalence extends to the entire sets universe. this has proven useful for developing 'nominal' theories of reasoning and programming on syntax with alpha-equivalence, because a sets universe includes elements representing functions, predicates, and behaviour. often, we want names and alpha-equivalence to model capture-avoiding substitution. in this paper we show that fm set theory models capture-avoiding substitution for names in much the same way as it models alpha-equivalence; as an operation valid for the entire sets universe which coincides with the usual (inductively defined) operation on inductive datatypes. in fact, more than one substitution action is possible (they all agree on sets representing syntax). we present two distinct substitution actions, making no judgement as to which one is 'right' - we suspect this question has the same status as asking whether classical or intuitionistic logic is 'right'. we describe the actions in detail, and describe the overall design issues involved in creating any substitution action on a sets universe. along the way, we think in new ways about the structure of elements of fm set theory. this leads us to some interesting mathematical concepts, including the notions of planes and crucial elements, which we also describe in detail.
fault-free longest paths in star networks with conditional link faults. the star network, which belongs to the class of cayley graphs, is one of the most versatile interconnection networks for parallel and distributed computing. in this paper, adopting the conditional fault model in which each node is assumed to be incident with two or more fault-free links, we show that an n-dimensional star network can tolerate up to 2n-7 link faults, and be strongly (fault-free) hamiltonian laceable, where n>=4. in other words, we can embed a fault-free linear array of length n!-1 (n!-2) in an n-dimensional star network with up to 2n-7 link faults, if the two end nodes belong to different partite sets (the same partite set). the result is optimal with respect to the number of link faults tolerated. it is already known that under the random fault model, an n-dimensional star network can tolerate up to n-3 faulty links and be strongly hamiltonian laceable, for n>=3.
dna duplex cage structures with icosahedral symmetry. a construction method for duplex cage structures with icosahedral symmetry made out of single-stranded dna molecules is presented and applied to an icosidodecahedral cage. it is shown via a mixture of analytic and computer techniques that there exist realisations of this graph in terms of two circular dna molecules. these blueprints for the organisation of a cage structure with a noncrystallographic symmetry may assist in the design of containers made from dna for applications in nanotechnology.
a constrained edit distance algorithm between semi-ordered trees. in this paper, we propose a formal definition of a new class of trees called semi-ordered trees and a polynomial dynamic programming algorithm to compute a constrained edit distance between such trees. the core of the method relies on a similar approach to compare unordered [kaizhong zhang, a constrained edit distance between unordered labeled trees, algorithmica 15 (1996) 205-222] and ordered trees [kaizhong zhang, algorithms for the constrained editing distance between ordered labeled trees and related problems, pattern recognition 28 (3) (1995) 463-474]. the method is currently applied to evaluate the similarity between architectures of apple trees [vincent segura, aida ouangraoua, pascal ferraro, evelyne costes, comparison of tree architecture using tree edit distances: application to two-year-old apple tree, euphytica 161 (2007) 155-164].
the complexity of small universal turing machines: a survey. we survey some work concerned with small universal turing machines, cellular automata, tag systems, and other simple models of computation. for example, it has been an open question for some time as to whether the smallest known universal turing machines of minsky, rogozhin, baiocchi and kudlek are efficient (polynomial time) simulators of turing machines. these are some of the most intuitively simple computational devices and previously the best known simulations were exponentially slow. we discuss recent work that shows that these machines are indeed efficient simulators. as a related result, we also find that rule 110, a well-known elementary cellular automaton, is also efficiently universal. we also review a large number of old and new universal program size results, including new small universal turing machines and new weakly, and semi-weakly, universal turing machines. we then discuss some ideas for future work arising out of these, and other, results.
a topological treatment of early-deciding set-agreement. the k-set-agreement problem consists for a set of n processes to agree on less than k among n possibly different values, each initially known to only one process. the problem is at the heart of distributed computing and generalizes the celebrated consensus problem. this paper considers the k-set-agreement problem in a synchronous message passing distributed system where up to t processes can fail by crashing. we determine the number of communication rounds needed for all correct processes to reach a decision in a given run, as a function of the degree of coordination k and the number of processes that actually fail in the run, f@?t. we prove that, for any integer 1@?k
construction of strongly connected dominating sets in asymmetric multihop wireless networks. consider an asymmetric wireless network represented by a digraph g=(v,e). a subset of vertices u is called a strongly connected dominating set (scds) if the subgraph induced by u is strongly connected and every vertex not in u has both an in-neighbor in u and an out-neighbor in u. scds plays an important role of the virtual backbone in asymmetric wireless networks. motivated by the construction of a small virtual backbone, we study the problem minimum scds, which seeks a smallest scds of a digraph. for any constant 0
distributed algorithms for partitioning a swarm of autonomous mobile robots. a number of recent studies address systems of mobile autonomous robots from a distributed computing point of view. although such systems employ robots that are relatively weak and simple (i.e., dimensionless, oblivious and anonymous), they are nevertheless expected to have strong fault tolerance capabilities as a group. this paper studies the partitioning problem, where n robots must divide themselves into k size-balanced groups, and examines the impact of common orientation on the solvability of this problem. first, deterministic crash-fault-tolerant algorithms are given for the problem in the asynchronous full-compass and semi-synchronous half-compass models, and a randomized algorithm is given for the semi-synchronous no-compass model. next, the role of common orientation shared by the robots is examined. necessary and sufficient conditions for the partitioning problem to be solvable are given in the different timing models. finally, the problem is proved to be unsolvable in the no-compass synchronous model.
autonomous programmable dna nanorobotic devices using dnazymes. a major challenge in nanoscience is the design of synthetic molecular devices that run autonomously (that is, without externally mediated changes per work-cycle) and are programmable (that is, their behavior can be modified without complete redesign of the device). dna-based synthetic molecular devices have the advantage of being relatively simple to design and engineer, due to the predictable secondary structure of dna nanostructures and the well-established biochemistry used to manipulate dna nanostructures. however, ideally we would like to minimize the use of protein enzymes in the design of a dna-based synthetic molecular device. we present the design of a class of dna-based molecular devices using dnazyme. these dnazyme-based devices are autonomous, programmable, and further require no protein enzymes. the basic principle involved is inspired by a simple but ingenious molecular device due to tian et al. [y. tian, y. he, y. chen, p. yin, c. mao, a dnazyme that walks processively and autonomously along a one-dimensional track, angew. chem. intl. ed. 44 (2005) 4355-4358] that used dnazyme to traverse on a dna nanostructure, but was not programmable in the sense defined above (it did not execute computations). our dnazyme-based designs include (1) a finite state automaton, dnazyme fsa that executes finite state transitions using dnazymes, (2) extensions to it including probabilistic automaton and non-deterministic automaton, and (3) its application as a dnazyme router for programmable routing of nanostructures on a 2d dna addressable lattice. furthermore, we give a medical-related application, dnazyme doctor that provides transduction of nucleic acid expression: it can be programmed to respond to the underexpression or overexpression of various strands of rna, with a response by the release of an rna. (the behavior of our nucleic acid transduction devices is similar to those of the prior paper of benenson [y. benenson, b. gil, u. ben-dor, r. adar, e. shapiro, an autonomous molecular computer for logical control of gene expression, nature 429 (2004) 423-429], but ours have the advantage that they operate without the use of any protein enzymes.)
overlap-freeness in infinite partial words. we prove that there exist infinitely many infinite overlap-free binary partial words containing at least one hole. moreover, we show that these words cannot contain more than one hole and the only hole must occur either in the first or in the second position. we define that a partial word is k-overlap-free if it does not contain a factor of the form xyxyx where the length of x is at least k. we prove that there exist infinitely many 2-overlap-free binary partial words containing an infinite number of holes.
algorithms for connected set cover problem and fault-tolerant connected set cover problem. given a set v of elements, s a family of subsets of v, and g a connected graph on vertex set s,a connected set cover (csc) is a subfamily r of s such that every element in v is covered by at least one set of r, and the subgraph g[r] of g induced by r is connected. if furthermore g[r] is k-connected and every element in v is covered by at least m sets in r, then r is a (k,m)-csc. in this paper, we present two approximation algorithms for the minimum csc problem, and one approximation algorithm for the minimum (2,m)-csc problem. performance ratios are analyzed. these are the first approximation algorithms for csc problems in general graphs with guaranteed performance ratios.
local edge colouring of yao-like subgraphs of unit disk graphs. the focus of the present paper is on providing a local deterministic algorithm for colouring the edges of yao-like subgraphs of unit disk graphs. these are geometric graphs such that for some positive integers l,k the following property holds at each node v: if we partition the unit circle centered at v into 2k equally sized wedges then each wedge can contain at most l points different from v. we assume that the nodes are location aware, i.e. they know their cartesian coordinates in the plane. the algorithm presented is local in the sense that each node can receive information emanating only from nodes which are at most a constant (depending on k and l, but not on the size of the graph) number of hops (measured in the original underlying unit disk graph) away from it, and hence the algorithm terminates in a constant number of steps. the number of colours used is 2kl+1 and this is optimal for local algorithms (since the maximal degree is 2kl and a colouring with 2kl colours can only be constructed by a global algorithm), thus showing that in this class of graphs the price for locality is only one additional colour.
on the cost of uniform protocols whose memory consumption is adaptive to interval contention. recently, we introduced a novel term, memory-adaptive, whose goal it is to capture what it means for a distributed protocol to most efficiently make use of its shared memory. we proved three results that relate to the memory-adaptive model in the uniform setting. we considered a store/release protocol where processes are required to store a value in shared mwmr memory so that it cannot be overwritten until it has been released by the process. we showed that there do not exist uniformly wait-free store/release protocols using only the basic operations read and write that are memory-adaptive to point contention. we further showed that there exists a uniformly wait-free store/release protocol using only the basic operations read, write, and read-modify-write that is memory-adaptive to interval contention and time-adaptive to total contention. this left a significant gap - it remained open as to whether there exists a uniform, memory adaptive to interval contention store/release protocol that only uses read/write (no read-modify-write) registers. in this paper, we close this gap by showing that no such protocol can exist. we furthermore illustrate the validity and practicality of the concept of memory adaptiveness by providing a uniform, memory-adaptive to interval contention store/release protocol for network attached disks.
gathering few fat mobile robots in the plane. autonomous identical robots represented by unit discs move deterministically in the plane. they do not have any common coordinate system, do not communicate, do not have memory of the past and are totally asynchronous. gathering such robots means forming a configuration for which the union of all discs representing them is connected. we solve the gathering problem for at most four robots. this is the first algorithmic result on gathering robots represented by two-dimensional figures rather than points in the plain: we call such robots fat.
convergence rates of markov chains for some self-assembly and non-saturated ising models. algorithms based on markov chains are ubiquitous across scientific disciplines as they provide a method for extracting statistical information about large, complicated systems. for some self-assembly models, markov chains can be used to predict both equilibrium and non-equilibrium dynamics. in fact, the efficiency of these self-assembly algorithms can be related to the rate at which simple chains converge to their stationary distribution. we give an overview of the theory of markov chains and show how many natural chains, including some relevant in the context of self-assembly, undergo a phase transition as a parameter representing temperature is varied in the model. we illustrate this behavior for the non-saturated ising model in which there are two types of tiles that prefer to be next to other tiles of the same type. unlike the standard ising model, we also allow empty spaces that are not occupied by either type of tile. we prove that for a local markov chain that allows tiles to attach and detach from the lattice, the rate of convergence is fast at high temperature and slow at low temperature.
characteristics of discrete transfinite time turing machine models: halting times, stabilization times, and normal form theorems. we give an acount of the basic determinants of the courses of computation of the infinite time turing machine model of hamkins and kidder, a model of computation which allows for transfinitely many steps of computation, and therefore may accept and output infinite strings of bits. we provide, inter alia, a normal form theorem, and a characterisation of which ordinals start gaps in halting times of such machines.
strict self-assembly of discrete sierpinski triangles. winfree (1998) showed that discrete sierpinski triangles can self-assemble in the tile assembly model. a striking molecular realization of this self-assembly, using dna tiles a few nanometers long and verifying the results by atomic-force microscopy, was achieved by rothemund, papadakis, and winfree (2004). precisely speaking, the above self-assemblies tile completely filled-in, two-dimensional regions of the plane, with labeled subsets of these tiles representing discrete sierpinski triangles. this paper addresses the more challenging problem of the strict self-assembly of discrete sierpinski triangles, i.e., the task of tiling a discrete sierpinski triangle and nothing else. we first prove that the standard discrete sierpinski triangle cannot strictly self-assemble in the tile assembly model. we then define the fibered sierpinski triangle, a discrete sierpinski triangle with the same fractal dimension as the standard one but with thin fibers that can carry data, and show that the fibered sierpinski triangle strictly self-assembles in the tile assembly model. in contrast with the simple xor algorithm of the earlier, non-strict self-assemblies, our strict self-assembly algorithm makes extensive, recursive use of optimal counters, coupled with measured delay and corner-turning operations. we verify our strict self-assembly using the local determinism method of soloveichik and winfree (2007).
introducing time in reaction systems. reaction systems are a formal model of interactions between biochemical reactions. the main observation underlying the formulation of this model is that such interactions are based on two basic mechanisms: facilitation and inhibition. this paper continues the investigation of reaction systems, and in particular, it proposes a formal framework for introducing time into reaction systems. within this framework one can formally define and investigate notions such as reaction times, creation times of compounds, their life spans, etc.
combinatorial and spectral aspects of nearest neighbor graphs in doubling dimensional and nearly-euclidean spaces. miller, teng, thurston, and vavasis proved a geometric separator theorem which implies that the k-nearest neighbor graph (k-nng) of every set of n points in r^d has a balanced vertex separator of size o(n^1^-^1^/^dk^1^/^d). spielman and teng then proved that the fiedler value - the second smallest eigenvalue of the laplacian matrix - of the k-nng of any n points in r^d is o((k/n)^2^/^d). in this paper, we extend these two results to nearest neighbor graphs in a metric space with a finite doubling dimension and in a metric space that is nearly-euclidean. we prove that for every l>0, if (x,dist) forms a metric space with doubling dimension @c, then the k-nng of every set p of n points in x has a vertex separator of size o(k^2l(64l+8)^2^@clog^2lslogn+nl), where l and s are, respectively, the maximum and minimum distances between any two points in p. we show how to use the singular value decomposition method to approximate a k-nng in a nearly-euclidean space by a euclidean k-nng. this approximation enables us to obtain an upper bound on the fiedler value of k-nngs in a nearly-euclidean space.
dynamic tcp acknowledgment with sliding window. the dynamic tcp acknowledgement problem which focuses the acknowledgment mechanism in tcp protocol has been intensively studied in the area of competitive analysis. however, its framework does not consider the sliding window in the tcp protocol that restricts the maximum number of packets that the sender can inject into the network without an acknowledgement. this paper proposes a new problem in which the sliding window is realistically integrated. we study how the ability of on-line algorithms changes, depending on whether the receiver is taught the window size. the greater part of this paper assumes that the window size is a constant integer w. we first show that, if w is given, the optimal on-line algorithm for the previous framework can be extended to our new framework and achieves the optimal competitive ratio of 2. next we prove that, if w is not given, the lower bound of the competitive ratio for an algorithm class which contains the optimal algorithm for the previous framework depends on the peak packet rate t from the sender and w, and is not better than (t/w+[t/w]-1)-competitive. then, we prove that there exists an on-line algorithm that is ([t/w]+2)-competitive, when w is unknown. an optimal off-line algorithm is also presented in this paper. significantly, our problem models the situation in which an on-line algorithm involuntarily transforms the input and processes the modified input without noticing the transformation.
the degree distribution of random k-trees. a power law degree distribution is established for a graph evolution model based on the graph class of k-trees. this k-tree-based graph process can be viewed as an idealized model that captures some characteristics of the preferential attachment and copying mechanisms that existing evolving graph processes fail to model due to technical obstacles. the result also serves as a further cautionary note reinforcing the point of view that a power law degree distribution should not be regarded as the only important characteristic of a complex network, as has been previously argued [d. achlioptas, a. clauset, d. kempe, c. moore, on the bias of traceroute sampling, or power-law degree distribution in regular graphs, in: proceedings of the 37th acm symposium on theory of computing, stoc'05, 2005, pp. 694-703; l. li, d. alderson, j. doyle, w. willinger, towards a theory of scale-free graphs: definition, properties, and implications, internet mathematics 2 (4) (2005) 431-523; m. mitzenmacher, the future of power law research, internet mathematics, 2 (4) (2005) 525-534].
effective dimension of points visited by brownian motion. we consider the individual points on a martin-lof random path of brownian motion. we show that (1) khintchine's law of the iterated logarithm holds at almost all points; and (2) there exist points (besides the trivial example of the origin) having effective dimension
regular production systems and triangle tilings. we discuss regular production systems as a tool for analyzing tilings in general. as an application we give necessary and sufficient conditions for a generic triangle to admit a tiling of and show that almost every triangle that admits a tiling is "weakly aperiodic". we pause for informal discussion of a variety of other applications, such as non-quasi-isometric maps between regular tilings, non-periodic archimedean tilings, growth, and decidability. most generally, regular production systems provide a model for the organized growth of surfaces along a front, subject to local rules.
polynomial algorithms for approximating nash equilibria of bimatrix games. we focus on the problem of computing an @e-nash equilibrium of a bimatrix game, when @e is an absolute constant. we present a simple algorithm for computing a 34-nash equilibrium for any bimatrix game in strongly polynomial time and we next show how to extend this algorithm so as to obtain a (potentially stronger) parameterized approximation. namely, we present an algorithm that computes a 2+@l4-nash equilibrium, where @l is the minimum, among all nash equilibria, expected payoff of either player. the suggested algorithm runs in time polynomial in the number of strategies available to the players.
private multiparty sampling and approximation of vector combinations. we consider the problem of private efficient data mining of vertically-partitioned databases. each of several parties holds a column of a data matrix (a vector) and the parties want to investigate the componentwise combination of their vectors. the parties want to minimize communication and local computation while guaranteeing privacy in the sense that no party learns more than necessary. sublinear-communication private protocols have primarily been studied only in the two-party case. in contrast, this work focuses on multi-party settings. first, we give efficient private multiparty protocols for sampling a row of the data matrix and for computing arbitrary functions of a random row, where the row index is additively shared among two or more parties. these results can be used to obtain private approximation protocols for several useful combination functionalities. moreover, these results have some interesting consequences for the general problem of reducing sublinear-communication secure multiparty computation to two-party private information retrieval (pir). second, we give protocols for computing approximations (summaries) of the componentwise sum, minimum, and maximum of the columns. here, while providing a weaker privacy guarantee (where the approximation may leak up to the entire output vector), our protocols are extremely efficient. in particular, the required cryptographic overhead (compared to non-private solutions) is polylogarithmic in the number of rows.
strongly polynomial-time truthful mechanisms in one shot. one of the main challenges in algorithmic mechanism design is to turn (existing) efficient algorithmic solutions into efficient truthful mechanisms. building a truthful mechanism is indeed a difficult process since the underlying algorithm must obey certain ''monotonicity'' properties and suitable payment functions need to be computed (this task usually represents the bottleneck in the overall time complexity). we provide a general technique for building truthful mechanisms that provide optimal solutions in strongly polynomial time. we show that the entire mechanism can be obtained if one is able to express/write a strongly polynomial-time algorithm (for the corresponding optimization problem) as a ''suitable combination'' of simpler algorithms. this approach applies to a wide class of mechanism design graph problems, where each selfish agent corresponds to a weighted edge in a graph (the weight of the edge is the cost of using that edge). our technique can be applied to several optimization problems which prior results cannot handle (e.g., min-max optimization problems). as an application, we design the first (strongly polynomial-time) truthful mechanism for the minimum diameter spanning tree problem, by obtaining it directly from an existing algorithm for solving this problem. for this non-utilitarian min-max problem, no truthful mechanism was known, even considering those running in exponential time (indeed, exact algorithms do not necessarily yield truthful mechanisms). also, standard techniques for payment computations may result in a running time which is not polynomial in the size of the input graph. the overall running time of our mechanism, instead, is polynomial in the number n of nodes and m of edges, and it is only a factor o(n@a(n,n)) away from the best known canonical centralized algorithm.
market equilibria with hybrid linear-leontief utilities. we introduce a new family of utility functions for exchange markets. this family provides a natural and ''continuous'' hybridization of the traditional linear and leontief utilities and might be useful in understanding the complexity of computing approximating market equilibria, although computing an equilibrium in a market with this family of utility functions, this is ppad-hard in general. in this paper, we present an algorithm for finding an approximate arrow-debreu equilibrium when the leontief components of the market are grouped, finite and well-conditioned.
on the construction of free algebras for equational systems. the purpose of this paper is threefold: to present a general abstract, yet practical, notion of equational system; to investigate and develop the finitary and transfinite construction of free algebras for equational systems; and to illustrate the use of equational systems as needed in modern applications.
universal augmentation schemes for network navigability. augmented graphs were introduced for the purpose of analyzing the ''six degrees of separation between individuals'' observed experimentally by the sociologist standley milgram in the 60's. we define an augmented graph as a pair (g,m) where g is an n-node graph with nodes labeled in {1,...,n}, and m is an nxn stochastic matrix. every node u@?v(g) is given an extra link, called a long range link, pointing to some node v, called the long range contact of u. the head v of this link is chosen at random by pr{u->v}=m"u","v. in augmented graphs, greedy routing is the oblivious routing process in which every intermediate node chooses from among all its neighbors (including its long range contact) the one that is closest to the target according to the distance measured in the underlying graph g, and forwards to it. the best augmentation scheme known so far ensures that, for any n-node graph g, greedy routing performs in o(n) expected number of steps. our main result is the design of an augmentation scheme that overcomes the o(n) barrier. precisely, we prove that for any n-node graph g whose nodes are arbitrarily labeled in {1,...,n}, there exists a stochastic matrix m such that greedy routing in (g,m) performs in o@?(n^1^/^3), where the o@? notation ignores the polylogarithmic factors. we prove additional results when the stochastic matrix m is universal to all graphs. in particular, we prove that the o(n) barrier can still be overcame for large graph classes even if the matrix m is universal. this however requires an appropriate labeling of the nodes. if the node labeling is arbitrary, then we prove that the o(n) barrier cannot be overcome with universal matrices.
investigating the existence and the regularity of logarithmic harary graphs. this paper studies the existence and the regularity of logarithmic harary graphs (lhgs). this study is motivated by the fact that these graphs are employed for modeling the communication topology to support efficient flooding in the presence of link and node failures when considering an initial arbitrary number of nodes n. therefore, the capability to identify graph constraints that allow the construction of lhgs for the largest number of pairs (n,k) (where k is the desired degree of connectivity to be tolerant to failures) becomes of primary importance. the paper presents several results in that direction. we introduce a graph constraint, namely k-pasted-tree, that allows the construction of a lhg for every pair (n,k) such that n>=2k. secondly we present another graph constraint for lhg, namely k-diamond, which is equivalent to k-pasted-tree in terms of capability to construct lhgs for any pair (n,k). the interest of k-diamond lies in the fact that, for a given k, k-diamond allows us to construct more regular graphs than k-pasted-tree does. a k-regular graph shows the minimal number of links required by a k-connected graph, leading to minimal flooding cost. the paper formally shows, in particular, that there are an infinite number of pairs (n,k), such that there exists a k-regular lhg for the pair (n,k) that satisfies k-diamond and does not satisfy k-pasted-tree.
computational complexity of computing a partial solution for the graph automorphism problems. it is known that a nontrivial automorphism on a given graph is computed by using any oracle that computes a pair of vertices (u,v) such that u is mapped to v by some nontrivial automorphism. in this paper, we consider a weaker oracle acting as follows. for a given graph, the oracle returns a pair (v,b) of a vertex v and a bit b@?{0,1} with the promise that if it returns (v,0), then the vertex v is fixed by some nontrivial automorphism, but if it returns (v,1), then the vertex v is moved by some nontrivial automorphism, provided that the given graph has a nontrivial automorphism. we here note that the oracle may return an arbitrary pair as its answer in case that the given graph has no nontrivial automorphism. we then show a stronger result that such an oracle is still powerful enough to compute a nontrivial automorphism. we also show that a similar result holds for rightga, a ga-complete problem. we further investigate the computational complexity of computing a partial solution for prefixga which is known to be gi-complete. for this problem, we show that, when we consider any oracle similar to one mentioned above, the oracle does not help us to solve prefixga unless gi @?"t^p ga.
a generalization of cobham's theorem to automata over real numbers. this article studies the expressive power of finite-state automata recognizing sets of real numbers encoded positionally. it is known that the sets that are definable in the first-order additive theory of real and integer variables can all be recognized by weak deterministic buchi automata, regardless of the encoding base r>1. in this article, we prove the reciprocal property, i.e., a subset of r that is recognizable by weak deterministic automata in every base r>1 is necessarily definable in . this result generalizes to real numbers the well-known cobham's theorem on the finite-state recognizability of sets of integers. our proof gives interesting insight into the internal structure of automata recognizing sets of real numbers, which may lead to efficient data structures for handling these sets.
affine systems of equations and counting infinitary logic. we study the definability of constraint satisfaction problems (csps) in various fixed-point and infinitary logics. we show that testing the solvability of systems of equations over a finite abelian group, a tractable csp that was previously known not to be definable in datalog, is not definable in the infinitary logic with finitely many variables and counting. this implies that it is not definable in least fixed-point logic or its extension with counting. we relate definability of csps to their classification obtained from tame congruence theory of the varieties generated by the algebra of polymorphisms of the template structure. in particular, we show that if this variety admits either the unary or affine type, the corresponding csp is not definable in the infinitary logic with counting.
the 4-way deterministic tiling problem is undecidable. it is shown that the (infinite) tiling problem by wang tiles is undecidable even if the given tile set is deterministic by all four corners, i.e. a tile is uniquely determined by the colors of any two adjacent edges. the reduction is done from the turing machine halting problem and uses the aperiodic tile set of kari and papasoglu.
pictures worth a thousand tiles, a geometrical programming language for self-assembly. we present a novel way to design self-assembling systems using a notion of signal (or ray) akin to what is used in analyzing the behaviour of cellular automata. this allows purely geometrical constructions, with a smaller specification and easier analysis. we show how to design a system of signals for a given set of shapes, and how to transform these signals into a set of tiles which self-assemble into the desired shapes. we show how to use this technique on two examples: squares (with optimal assembly time and a small number of tiles) and general polygons with arbitrarily good resolution.
optimal construction of k-nearest-neighbor graphs for identifying noisy clusters. we study clustering algorithms based on neighborhood graphs on a random sample of data points. the question we ask is how such a graph should be constructed in order to obtain optimal clustering results. which type of neighborhood graph should one choose, mutual k-nearest-neighbor or symmetric k-nearest-neighbor? what is the optimal parameter k? in our setting, clusters are defined as connected components of the t-level set of the underlying probability distribution. clusters are said to be identified in the neighborhood graph if connected components in the graph correspond to the true underlying clusters. using techniques from random geometric graph theory, we prove bounds on the probability that clusters are identified successfully, both in a noise-free and in a noisy setting. those bounds lead to several conclusions. first, k has to be chosen surprisingly high (rather of the order n than of the order logn) to maximize the probability of cluster identification. secondly, the major difference between the mutual and the symmetric k-nearest-neighbor graph occurs when one attempts to detect the most significant cluster only.
coordination mechanisms for selfish scheduling. in machine scheduling, a set of jobs must be scheduled on a set of machines so as to minimize some global objective function, such as the makespan, which we consider in this paper. in practice, jobs are often controlled by independent, selfishly acting agents, which each select a machine for processing that minimizes the (expected) completion time. this scenario can be formalized as a game in which the players are job owners, the strategies are machines, and a player's disutility is the completion time of its jobs in the corresponding schedule. the equilibria of these games may result in larger-than-optimal overall makespan. the price of anarchy is the ratio of the worst-case equilibrium makespan to the optimal makespan. in this paper, we design and analyze scheduling policies, or coordination mechanisms, for machines which aim to minimize the price of anarchy of the corresponding game. we study coordination mechanisms for four classes of multiprocessor machine scheduling problems and derive upper and lower bounds on the price of anarchy of these mechanisms. for several of the proposed mechanisms, we also prove that the system converges to a pure-strategy nash equilibrium in a linear number of rounds. finally, we note that our results are applicable to several practical problems arising in communication networks.
online scheduling on two uniform machines to minimize the makespan. we consider two problems of online scheduling on two uniform machines: online scheduling under a grade of service (gos) and online scheduling with reassignment. these problems are online in the sense that when a job presents, we have to irrevocably assign it to one of the machines before the next job is seen. the objective is to minimize the makespan. in the first problem, gos means that some jobs have to be processed by some machine so that they can be guaranteed a higher quality. assume that the speed of the higher gos machine is normalized to 1, while the speed of the other one is s. we show that a lower bound of competitive ratio is 1+2ss+2 in the case 01. then we propose and analyze two online algorithms: hsf algorithm and ex-online algorithm. hsf is optimal in the case where s>1 and @s"1>=@s"2s, where @s"1 and @s"2 denote the total processing time of jobs which request higher gos machine and the total processing time of jobs which request the normal one, respectively. ex-online is optimal in the case 2(2-1)@?s@?1. in the second problem, we study two subproblems p"l and p"a proposed in [z. tan, s. yu, online scheduling with reassignment, operations research letters 36 (2008) 250-254]. assume that the speeds of 2 uniform machines are 1 and s>=1, respectively. for p"l where we can reassign the last k jobs of the sequence, we show a lower bound of competitive ratio 1+11+s. for p"a where we can reassign arbitrary k jobs, we show a lower bound of competitive ratio (s+1)^2s^2+s+1. we propose a s+1s-competitive algorithm hsf-1 for both p"l and p"a. for p"a, we propose a (s+1)^2s+2-competitive algorithm ex-ra, which is superior to hsf-1 when 1@?s@?2.
dynamic mechanism design. in this paper we address the question of designing truthful mechanisms for solving optimization problems on dynamic graphs with selfish edges. more precisely, we are given a graph g of n nodes, and we assume that each edge of g is owned by a selfish agent. the strategy of an agent consists in revealing to the system-at each time instant-the cost at the actual time for using its edge. additionally, edges can enter into and exit from g. among the various possible assumptions which can be made to model how this edge-cost modifications take place, we focus on two settings: (i) the dynamic, in which modifications can happen at any time, and for a given optimization problem on g, the mechanism has to maintain efficiently the output specification and the payment scheme for the agents; (ii) the time-sequenced, in which modifications happens at fixed time steps, and the mechanism has to minimize an objective function which takes into consideration both the quality and the set-up cost of a new solution. in both settings, we investigate the existence of exact and approximate truthful (w.r.t. to suitable equilibrium concepts) mechanisms. in particular, for the dynamic setting, we analyze the minimum spanning tree problem, and we show that if edge costs can only decrease and each agent adopts a myopic best response strategy (i.e., its utility is only measured instantaneously), then there exists an efficient dynamic truthful (in myopic best response equilibrium) mechanism for handling a sequence of k declarations of edge-cost reductions having runtime o((h+k)logn), where h is the overall number of payment changes.
efficient approximation of min set cover by moderately exponential algorithms. we study the approximation of min set cover combining ideas and results from polynomial approximation and from exact computation (with non-trivial worst case complexity upper bounds) for np-hard problems. we design approximation algorithms for min set cover achieving ratios that cannot be achieved in polynomial time (unless problems in np could be solved by slightly super-polynomial algorithms) with worst-case complexity much lower (though super-polynomial) than those of an exact computation.
perfectly quilted rectangular snake tilings. we introduce a particular form of snake tilings to define picture languages, and relate the obtained family to the recognizable picture languages (as defined by wang tiles). the correspondence for substitution tilings is even closer, and hence is applicable to the hilbert curve.
pure nash equilibria in player-specific and weighted congestion games. unlike standard congestion games, weighted congestion games and congestion games with player-specific delay functions do not necessarily possess pure nash equilibria. it is known, however, that there exist pure equilibria for both of these variants in the case of singleton congestion games, i.e., if the players' strategy spaces contain only sets of cardinality one. in this paper, we investigate how far such a property on the players' strategy spaces guaranteeing the existence of pure equilibria can be extended. we show that both weighted and player-specific congestion games admit pure equilibria in the case of matroid congestion games, i.e., if the strategy space of each player consists of the bases of a matroid on the set of resources. we also show that the matroid property is the maximal property that guarantees pure equilibria without taking into account how the strategy spaces of different players are interweaved. additionally, our analysis of player-specific matroid congestion games yields a polynomial time algorithm for computing pure equilibria. we also address questions related to the convergence time of such games. for player-specific matroid congestion games, in which the best response dynamics may cycle, we show that from every state there exists a short sequences of better responses to an equilibrium. for weighted matroid congestion games, we present a superpolynomial lower bound on the convergence time of the best response dynamics showing that players do not even converge in pseudopolynomial time.
the simultaneous consecutive ones problem. the standard consecutive ones problem is concerned with permuting the columns of a 0/1-matrix in such a way that in every row all 1-entries occur consecutively. in this paper we study this problem with the additional requirement that also in every column the 1-entries have to be consecutive. to achieve this column permutations have to be allowed as well. we show that the weighted simultaneous consecutive ones problem is np-hard and consider two special cases with fixed row and column permutations where one is still np-hard and the other one turns out to be easy.
quasi-linear transformations and discrete tilings. tilings of the discrete plane z^2 generated by quasi-linear transformations (qlt) have been introduced by nehlig [p. nehlig, applications quasi-affines: pavages par images reciproques, theoretical computer science 156 (1995) 1-38]. we studied these tilings and gave some results, such as periodicity and the number of neighbours of each of them [m.-a. jacob-da col, applications quasi-affines et pavages du plan discret, theoretical computer science 259 (2001) 245-269. also available in english: http://dpt-info.u-strasbg.fr/~jacob/articles/paving.pdf]. the aim of this paper is to go on with this study in the discrete n-dimensional space z^2; we give a lower and an upper bound to the number of distinct tiles. we also give an algorithm to determine the points of a given tile, this algorithm will induce another algorithm to determine the number of distinct tiles associated to a qlt.
maximal infinite-valued constraint languages. we systematically investigate the computational complexity of constraint satisfaction problems for constraint languages over an infinite domain. in particular, we study a generalization of the well-established notion of maximal constraint languages from finite to infinite domains. if the constraint language can be defined with an @w-categorical structure, then maximal constraint languages are in one-to-one correspondence to minimal oligomorphic clones. based on this correspondence, we derive general tractability and hardness criteria for the corresponding constraint satisfaction problems.
a constructive borel-cantelli lemma. constructing orbits with required statistical properties. in the general context of computable metric spaces and computable measures we prove a kind of constructive borel-cantelli lemma: given a sequence (constructive in some way) of sets a"i with effectively summable measures, there are computable points which are not contained in infinitely many a"i. as a consequence of this we obtain the existence of computable points which follow the typical statistical behavior of a dynamical system (they satisfy the birkhoff theorem) for a large class of systems, having computable invariant measure and a certain ''logarithmic'' speed of convergence of birkhoff averages over lipschitz observables. this is applied to uniformly hyperbolic systems, piecewise expanding maps, systems on the interval with an indifferent fixed point and it directly implies the existence of computable numbers which are normal with respect to any base.
improved constructions of quantum automata. we present a simple construction of quantum automata which achieve an exponential advantage over classical finite automata. our automata use 4@elog2p states to recognize a language that requires p states classically. the construction is both substantially simpler and achieves a better constant in the front of logp than the previously known construction. our construction is by a probabilistic argument. we consider the possibility to derandomize it and present some results in this direction.
morphically primitive words. in the present paper, we introduce an alternative notion of the primitivity of words, that-unlike the standard understanding of this term-is not based on the power (and, hence, the concatenation) of words, but on morphisms. for any alphabet @s, we call a word w@?@s^*morphically imprimitive provided that there are a shorter word v and morphisms h,h^':@s^*->@s^* satisfying h(v)=w and h^'(w)=v, and we say that w is morphically primitive otherwise. we explain why this is a well-chosen terminology, we demonstrate that morphic (im-) primitivity of words is a vital attribute in many combinatorial domains based on finite words and morphisms, and we study a number of fundamental properties of the concepts under consideration.
approximation hardness of deadline-tsp reoptimization. given an instance of an optimization problem together with an optimal solution, we consider the scenario in which this instance is modified locally. in graph problems, e.g., a singular edge might be removed or added, or an edge weight might be varied, etc. for a problem u and such a local modification operation, let lm-u (local-modification-u) denote the resulting problem. the question is whether it is possible to exploit the additional knowledge of an optimal solution to the original instance or not, i.e.,whether lm-u is computationally more tractable than u. while positive examples are known e.g. for metric tsp, we give some negative examples here: metric tsp with deadlines (time windows), if a single deadline or the cost of a single edge is modified, exhibits the same lower bounds on the approximability in these local-modification versions as those currently known for the original problem.
the complexity of clique graph recognition. a complete set of a graph g is a subset of vertices inducing a complete subgraph. a clique is a maximal complete set. denote by c(g) the clique family of g. the clique graph of g, denoted by k(g), is the intersection graph of c(g). say that g is a clique graph if there exists a graph h such that g=k(h). the clique graph recognition problem asks whether a given graph is a clique graph. a sufficient condition was given by hamelink in 1968, and a characterization was proposed by roberts and spencer in 1971. however, the time complexity of the problem of recognizing clique graphs is a long-standing open question. we prove that the clique graph recognition problem is np-complete.
fast neighbor joining. reconstructing the evolutionary history of a set of species is a fundamental problem in biology and methods for solving this problem are gaged based on two characteristics: accuracy and efficiency. neighbor joining (nj) is a so-called distance-based method that, thanks to its good accuracy and speed, has been embraced by the phylogeny community. it takes the distances between n taxa and produces in @q(n^3) time a phylogenetic tree, i.e., a tree which aims to describe the evolutionary history of the taxa. in addition to performing well in practice, the nj algorithm has optimal reconstruction radius. the contribution of this paper is twofold: (1) we present an algorithm called fast neighbor joining (fnj) with optimal reconstruction radius and optimal run time complexity o(n^2) and (2) we present a greatly simplified proof for the correctness of nj. initial experiments show that fnj in practice has almost the same accuracy as nj, indicating that the property of optimal reconstruction radius has great importance to their good performance. moreover, we show how improved running time can be achieved for computing the so-called correction formulas.
deterministic bottom-up tree transducers and ground term rewrite systems. we show that it is decidable for any deterministic bottom-up tree transducer a and ground term rewrite system r, which one of the following conditions holds: (i) @t(a)@?@?"r^*, (ii) @?"r^*@?@t(a), (iii) @t(a)=@?"r^*, (iv) @t(a) and @?"r^* are incomparable. here @t(a) is the tree transformation induced by a, and @?"r^* is the congruence generated by r.
matrix columns allocation problems. orthogonal frequency division multiple access (ofdma) transmission technique is gaining popularity as a preferred technique in the emerging broadband wireless access standards. motivated by the ofdma transmission technique we define the following problem: let m be a matrix (over r) of size axb. given a vector of non-negative integers c->= such that @?c"j=a, we would like to allocate a cells in m such that (i) in each row of m there is a single allocation, and (ii) for each element c"i@?c-> there is a unique column in m which contains exactly c"i allocations. our goal is to find an allocation with minimal value, that is, the sum of all the a cells of m which were allocated is minimal. the nature of the suggested new problem is investigated in this paper. efficient algorithms are suggested for some interesting cases. for other cases of the problem, np-hardness proofs are given followed by inapproximability results.
exploration-exploitation tradeoff using variance estimates in multi-armed bandits. algorithms based on upper confidence bounds for balancing exploration and exploitation are gaining popularity since they are easy to implement, efficient and effective. this paper considers a variant of the basic algorithm for the stochastic, multi-armed bandit problem that takes into account the empirical variance of the different arms. in earlier experimental works, such algorithms were found to outperform the competing algorithms. we provide the first analysis of the expected regret for such algorithms. as expected, our results show that the algorithm that uses the variance estimates has a major advantage over its alternatives that do not use such estimates provided that the variances of the payoffs of the suboptimal arms are low. we also prove that the regret concentrates only at a polynomial rate. this holds for all the upper confidence bound based algorithms and for all bandit problems except those special ones where with probability one the payoff obtained by pulling the optimal arm is larger than the expected payoff for the second best arm. hence, although upper confidence bound bandit algorithms achieve logarithmic expected regret rates, they might not be suitable for a risk-averse decision maker. we illustrate some of the results by computer simulations.
covering graphs with few complete bipartite subgraphs. we consider computational problems on covering graphs with bicliques (complete bipartite subgraphs). given a graph and an integer k, the biclique cover problem asks whether the edge-set of the graph can be covered with at most k bicliques; the biclique partition problem is defined similarly with the additional condition that the bicliques are required to be mutually edge-disjoint. the biclique vertex-cover problem asks whether the vertex-set of the given graph can be covered with at most k bicliques, the biclique vertex-partition problem is defined similarly with the additional condition that the bicliques are required to be mutually vertex-disjoint. all these four problems are known to be np-complete even if the given graph is bipartite. in this paper, we investigate them in the framework of parameterized complexity: do the problems become easier if k is assumed to be small? we show that, considering k as the parameter, the first two problems are fixed-parameter tractable, while the latter two problems are not fixed-parameter tractable unless p=np.
truthful mechanisms for two-range-values variant of unrelated scheduling. in this paper, we consider a restricted variant of the scheduling problem, where the machines are the strategic players. for this multi-parameter mechanism design problem, the only known truthful mechanisms use task independent allocation algorithms and only have approximation ratio o(m) [n. nisan, a. ronen. algorithmic mechanism design (extended abstract), in: stoc'99: proceedings of the thirty-first annual acm symposium on theory of computing, acm, new york, ny, usa, 1999. pp. 129-140; a. mu'alem, m. schapira, setting lower bounds on truthfulness: extended abstract, in: soda'07: proceedings of the eighteenth annual acm-siam symposium on discrete algorithms, society for industrial and applied mathematics, philadelphia, pa, usa, 2007, pp. 1143-1152; p. lu, c. yu, an improved randomized truthful mechanism for scheduling unrelated machines, in: 25th international symposium on theoretical aspects of computer science, stacs, 2008, pp. 527-538; p. lu, c. yu, randomized truthful mechanisms for scheduling unrelated machines, in: c.h. papadimitriou, s. zhang (eds.), proceedings of wine, in: lecture notes in computer science, vol. 5385, springer, 2008, pp. 402-413]. lavi and swamy first use the cycle monotone condition and design a 3-approximation truthful mechanism for a two value variant in [r. lavi, c. swamy, truthful mechanism design for multi-dimensional scheduling via cycle monotonicity, in: ec'07: proceedings of the 8th acm conference on electronic commerce, acm, new york, ny, usa, 2007, pp. 252-261], where the processing time of task j on machine i, say t"i"j, can only be either a lower value l"j or a higher value h"j. we consider a generalized variant, where t"i"j lies in [l"j,l"j(1+@e)]@?[h"j,h"j(1+@e)] and @e is a parameter satisfying some condition. we consider two special cases, case a when h"j/l"j>2,@?j and case b when h"j/l"j@?2,@?j, and give randomized truthful mechanisms with approximation ratio 4(1+@e) for both cases. based on these two cases' results, we are also able to deal with the general case of our two-range-values scheduling problem. we use a combination of two mechanisms, which is also a novel method in mechanism design for scheduling problems, and finally we give a randomized truthful mechanism with approximation ratio 7(1+@e). although the generalization seems a little incremental, we actually use a very novel technique in the key step of proving truthfulness for case a, as well as a new mechanism scheme for case b. besides, the results in this paper are the first truthful mechanisms with constant approximation ratios when a machine (player) can report infinitely possible values, which is quite different from the two value variant, in which only finite values are available. furthermore, together with lavi and swamy's work, our results suggest that such a task-dependent approach can really do much better for the scheduling unrelated machines problem.
improved constructions of mixed state quantum automata. quantum finite automata with mixed states are proved to be super-exponentially more concise rather than quantum finite automata with pure states. it was proved earlier by a. ambainis and r. freivalds that quantum finite automata with pure states can have an exponentially smaller number of states than deterministic finite automata recognizing the same language. there was an unpublished ''folk theorem'' proving that quantum finite automata with mixed states are no more super-exponentially more concise than deterministic finite automata. it was not known whether the super-exponential advantage of quantum automata is really achievable. we prove that there is an infinite sequence of distinct integers n, languages l"n, and quantum finite automata with mixed states with 5n states recognizing language l"n with probability 34, while any deterministic finite automaton recognizing l"n needs at least e^o^(^n^l^n^n^) states. unfortunately, the alphabet for these languages grows with n. in order to prove a similar result for languages in a fixed alphabet we consider a counterpart of hamming codes for permutations of finite sets, i.e. sets of permutations such that any two distinct permutations in the set have hamming distance at least d. the difficulty arises from the fact that in the traditional hamming codes for binary strings, positions in the string are independent while positions in a permutation are not independent. for instance, any two permutations of the same set either coincide or their hamming distance is at least 2. the main combinatorial problem still remains open.
on a class of languages recognizable by probabilistic reversible decide-and-halt automata. we analyze the properties of probabilistic reversible decide-and-halt automata (dh-pra) and show that there is a strong relationship between dh-pra and 1-way quantum automata. we show that a general class of regular languages is not recognizable by dh-pra by proving that two ''forbidden'' constructions in minimal deterministic automata correspond to languages not recognizable by dh-pra. the shown class is identical to a class known to be not recognizable by 1-way quantum automata. we also prove that the class of languages recognizable by dh-pra is not closed under union and other non-trivial boolean operations.
a note on approximate nash equilibria. in view of the intractability of finding a nash equilibrium, it is important to understand the limits of approximation in this context. a subexponential approximation scheme is known [richard j. lipton, evangelos markakis, aranyak mehta, playing large games using simple strategies, in: ec, 2003], and no approximation better than 14 is possible by any algorithm that examines equilibria involving fewer than logn strategies [ingo althofer, on sparse approximations to randomized strategies and convex combinations, linear algebra and its applications (1994) 199]. we give a simple, linear-time algorithm examining just two strategies per player and resulting in a 12-approximate nash equilibrium in any 2-player game. for the more demanding notion of approximately well supported nash equilibrium due to [constantinos daskalakis, paul w. goldberg, christos h. papadimitriou, the complexity of computing a nash equilibrium, siam journal on computing (in press) preliminary version appeared in stoc (2006)] no nontrivial bound is known; we show that the problem can be reduced to the case of win-lose games (games with all utilities 0 or 1), and that an approximation of 56 is possible, contingent upon a graph-theoretic conjecture. subsequent work extends the 14 impossibility result of ingo althofer's paper, as mentioned above, to 12 [tomas feder, hamid nazerzadeh, amin saberi, approximating nash equilibria using small-support strategies, in: ec, 2007], making our 12-approximate nash equilibrium algorithm optimal among the algorithms that only consider mixed strategies of sublogarithmic size support. moreover, techniques similar to our techniques for approximately well supported nash equilibria are used in [spyros kontogiannis, paul g. spirakis, efficient algorithms for constant well supported approximate equilibria in bimatrix games, in: icalp, 2007] for obtaining an efficient algorithm for 0.658-approximately well supported nash equilibria, unconditionally.
inapproximability of survivable networks. in the survivable network design problem (sndp) one seeks to find a minimum cost subgraph that satisfies prescribed node-connectivity requirements. we give a novel approximation ratio preserving reduction from directed sndp to undirected sndp. our reduction extends and widely generalizes as well as significantly simplifies the main results of [g. kortsarz, r. krauthgamer, j.r. lee, hardness of approximation for vertex-connectivity network design problems, siam journal on computing 33 (3) (2004) 704-720]. using it, we derive some new hardness of approximation results, as follows. we show that directed and undirected variants of sndp and of k-connected subgraph are equivalent w.r.t. approximation, and that a @r-approximation for undirected rooted sndp implies a @r-approximation for directed steiner tree.
classifying rendezvous tasks of arbitrary dimension. the rendezvous is a type of distributed decision tasks including many well-known tasks such as set agreement, simplex agreement, and approximation agreement. an n-dimensional rendezvous task, n>=1, allows n+2 distinct input values, and each execution produces at most n+2 distinct output values. a rendezvous task is said to implement another if an instance of its solution, followed by a protocol based on shared read/write registers, solves the other. the notion of implementation induces a classification of rendezvous tasks of every dimension: two tasks belong to the same class if they implement each other. previous work on classifying rendezvous tasks only focused on 1-dimensional ones. this paper solves an open problem by presenting the classification of nice rendezvous of arbitrary dimension. an n-dimensional rendezvous task is said to be nice if the qth reduced homology group of its decision space is trivial for q
separating models of learning with faulty teachers. we study the power of two models of faulty teachers in valiant's pac learning model and angluin's exact learning model. the first model we consider is learning from an incomplete membership oracle introduced by angluin and slonim [d. angluin, d.k. slonim, randomly fallible teachers: learning monotone dnf with an incomplete membership oracle, machine learning 14 (1) (1994) 7-26]. in this model, the answers to a random subset of the learner's membership queries may be missing. the second model we consider is random persistent classification noise in membership queries introduced by goldman, kearns and schapire [s. goldman, m. kearns, r. schapire, exact identification of read-once formulas using fixed points of amplification functions, siam journal on computing 22 (4) (1993) 705-726]. in this model, the answers to a random subset of the learner's membership queries are flipped. we show that in both the pac and the exact learning models the incomplete membership oracle is strictly stronger than the noisy membership oracle under the assumption that the problem of pac learning parities with random classification noise is intractable. we also show that under the standard cryptographic assumptions the incomplete membership oracle is strictly weaker than the perfect membership oracle. this generalizes the result of simon [h. simon, how many missing answers can be tolerated by query learners? theory of computing systems 37 (1) (2004) 77-94] and resolves an open question of bshouty and eiron [n. bshouty, n. eiron, learning monotone dnf from a teacher that almost does not answer membership queries, journal of machine learning research 3 (2002) 49-57].
tight rank lower bounds for the sherali-adams proof system. we consider a proof (more accurately, refutation) system based on the sherali-adams (sa) operator associated with integer linear programming. if f is a cnf contradiction that admits a resolution refutation of width k and size s, then we prove that the sa rank of f is @?k and the sa size of f is @?(k+1)s+1. we establish that the sa rank of both the pigeonhole principle php"n"-"1^n and the least number principle lnp"n is n-2. since the sa refutation system rank-simulates the refutation system of lovasz-schrijver without semidefinite cuts (ls), we obtain as a corollary linear rank lower bounds for both of these principles in ls.
collapsing words, permutation conditions and coherent colorings of trees. given a word w over a finite alphabet @s and a finite deterministic automaton a=, the inequality |@d(q,w)|@?|q|-n means that under the natural action of the word w the image of the state set q is reduced by at least n states. a word w is n-collapsing if this inequality holds for any deterministic finite automaton that satisfies such an inequality for at least one word. in this paper we prove that the problem of recognizing n-collapsing words is generally co-np-complete, while restricted to 2-collapsing words over 2-element alphabet it belongs to p. this is connected with introducing a new approach to collapsing words, which is shown to be much more effective in solving various problems in the area. it leads to interesting connections with combinatorial problems concerning solving systems of permutation conditions on one hand, and coloring trees with distinguished nodes on the other hand.
on parameterized complexity of the multi-mcs problem. we introduce the maximum common subgraph problem for multiple graphs (multi-mcs) inspired by various biological applications such as multiple alignments of gene sequences, protein structures, metabolic pathways, or protein-protein interaction networks. multi-mcs is a generalization of the two-graph maximum common subgraph problem (mcs). on the basis of the framework of parameterized complexity theory, we derive the parameterized complexity of multi-mcs for various parameters for different classes of graphs. for example, for directed graphs with labeled vertices, we prove that the parameterized m-multi-mcs problem is w[2]-hard, while the parameterized k-multi-mcs problem is w[t]-hard (@?t>=1), where m and k are the size of the maximum common subgraph and the number of multiple graphs, respectively. we show similar results for other parameterized versions of the multi-mcs problem for directed graphs with vertex labels and undirected graphs with vertex and edge labels by giving linear fpt reductions of the problems from parameterized versions of the longest common subsequence problem. likewise, for unlabeled undirected graphs, we show that a parameterized version of the multi-mcs problem with a fixed number of input graphs is w[1]-complete by showing a linear fpt reduction to and from a parameterized version of the maximum clique problem.
deterministic and unambiguous two-dimensional languages over one-letter alphabet. the paper focuses on deterministic and unambiguous recognizable two-dimensional languages with particular attention to the case of a one-letter alphabet. the family drec(1) of deterministic languages over a one-letter alphabet is characterized as both l(dota)(1), the class of languages accepted by deterministic on-line tessellation acceptors, and l(2afa)(1), the class of languages recognized by 2-way alternating finite automata. we show that there are inherently ambiguous languages and unambiguously recognizable languages that cannot be deterministically recognized even in the case of a one-letter alphabet. in particular we show that on-line tessellation acceptors are more powerful than their deterministic counterpart, even in the case of a one-letter alphabet. finally we show that drec(1) is complex enough not to be characterized in terms of classical operations.
mathematical logic and quantum finite state automata. this paper is a review of the connection between formulas of logic and quantum finite-state automata in respect to the language recognition and acceptance probability of quantum finite-state automata. as is well known, logic has had a great impact on classical computation, it is promising to study the relation between quantum finite-state automata and mathematical logic. after a brief introduction to the connection between classical computation and logic, the required background of the logic and quantum finite-state automata is provided and the results of the connection between quantum finite-state automata and logic are presented.
paths, cycles and circular colorings in digraphs. in this paper, we consider the paths, cycles and circular colorings of digraphs. let d be a digraph. we show that if the complement of d contains no directed hamiltonian cycle, then @g"c(d)=@g(d). also, we give two results which concern directed paths meeting all colors in digraphs with proper colorings.
efficient probability amplification in two-way quantum finite automata. in classical computation, one only needs to sequence o(log1@e) identical copies of a given probabilistic automaton with one-sided error p0}, kondacs and watrous use a different probability amplification method, which yields machines with o((1@e)^2) states, and with runtime o(1@e|w|), where w is the input string. in this paper, we examine significantly more efficient techniques of probability amplification. one of our methods produces machines which decide l in o(|w|) time (i.e. the running time does not depend on the error bound) and which have o((1@e)^2^c) states for any given constant c>1. other methods, yielding machines whose state complexities are polylogarithmic in 1@e, including one which halts in o(log(1@e)|w|) time, are also presented.
holographic algorithms: the power of dimensionality resolved. valiant's theory of holographic algorithms is a novel methodology to achieve exponential speed-ups in computation. a fundamental parameter in holographic algorithms is the dimension of the linear basis vectors. we completely resolve the problem of the power of higher dimensional bases. we prove that 2-dimensional bases are universal for holographic algorithms.
coloring artemis graphs. we consider the class of graphs that contain no odd hole, no antihole, and no ''prism'' (a graph consisting of two disjoint triangles with three disjoint paths between them). we give an algorithm that can optimally color the vertices of these graphs in time o(n^2m).
universal algebra and hardness results for constraint satisfaction problems. we present algebraic conditions on constraint languages @c that ensure the hardness of the constraint satisfaction problem csp(@c) for complexity classes l, nl, p, np and mod"pl. these criteria also give non-expressibility results for various restrictions of datalog. furthermore, we show that if csp(@c) is not first-order definable then it is l-hard. our proofs rely on tame congruence theory and on a fine-grain analysis of the complexity of reductions used in the algebraic study of csp. the results pave the way for a refinement of the dichotomy conjecture stating that each csp(@c) lies in p or is np-complete and they match the recent classification of [e. allender, m. bauland, n. immerman, h. schnoor, h. vollmer, the complexity of satisfiability problems: refining schaefer's theorem, in: proc. 30 th math. found. of comp. sci., mfcs'05, 2005, pp. 71-82] for boolean csp. we also infer a partial classification theorem for the complexity of csp(@c) when the associated algebra of @c is the full idempotent reduct of a preprimal algebra.
maximum scan statistics and channel assignment problems in homogeneous wireless networks. in wireless networks, to avoid collisions of simultaneous transmissions over the same channel, adjacent nodes are assigned distinct channels, and the least number of channels used in an assignment is called the chromatic number. the determination of the chromatic number is np-hard. in this paper, we introduce an analytic tool called maximum scan statistics. for a finite point set v and a convex compact set c, the maximum scan statistic of v with respect to the scanning set c is the largest number of points in v covered by a copy c. based on the study of asymptotic maximum scan statistics, we obtain the asymptotics of the maximum degree and the clique number of homogeneous wireless networks. the results imply that the chromatic number is almost surely at most four times the clique number. we further prove that the approximation ratios of some vertex-ordering-based first-fit channel assignment algorithms are almost surely bounded by 2. in the analysis, we also learn that the chromatic number is almost surely at most twice the clique number.
an infinite hierarchy of language families generated by scattered context grammars with n-limited derivations. this paper introduces scattered context grammars without erasing productions, in which an application of a production always occurs within the first n nonterminals of the current sentential form. it demonstrates that this restriction gives rise to an infinite hierarchy of language families each of which is properly included in the family of context-sensitive languages. in addition, it proves analogous results for unordered scattered context grammars. some consequences of these results are derived and open problems formulated.
asymptotic subword complexity of fixed points of group substitutions. the subword complexity of fixed points of some types of substitutions was studied by various authors. here we introduce a family of substitutions, arising from multiplication tables of finite groups and other similar structures, and analyze their subword complexity.
sampling methods for shortest vectors, closest vectors and successive minima. we study four problems from the geometry of numbers, the shortest vector problem(svp), the closest vector problem(cvp), the successive minima problem(smp), and the shortest independent vectors problem (sivp). extending and generalizing results of ajtai, kumar, and sivakumar we present probabilistic single exponential time algorithms for all four problems for all @?"p norms. the results on smp and sivp are new for all norms. the results on svp and cvp generalize previous results of ajtai et al. for the euclidean @?"2 norm to arbitrary @?"p norms. we achieve our results by introducing a new lattice problem, the generalized shortest vector problem (gsvp). we describe a single exponential time algorithm for gsvp. we also describe polynomial time reductions from svp,cvp,smp, and sivp to gsvp, establishing single exponential time algorithms for the four classical lattice problems. this approach leads to a unified algorithmic treatment of the lattice problems svp,cvp,smp, and sivp.
multiple pass streaming algorithms for learning mixtures of distributions in r. we present a multiple pass streaming algorithm for learning the density function of a mixture of k uniform distributions over rectangles in r^d, for any d>0. our learning model is: samples drawn according to the mixture are placed in arbitrary order in a data stream that may only be accessed sequentially by an algorithm with a very limited random access memory space. our algorithm makes 2@?+2 passes, for any @?>0, and requires memory at most o@?(@e^-^2^/^@?k^2d^4+(4k)^d), where @e is the tolerable error of the algorithm. this exhibits a strong memory-pass tradeoff in terms of @e: a few more passes significantly lower its memory requirements, thus trading one of the two most important resources in streaming computation for the other. chang and kannan first considered this problem for d=1,2. our learning algorithm is especially appropriate for situations where massive data sets of samples are available, but computation with such large inputs requires very restricted models of computation.
on outer bounds to the capacity region of wireless networks. in this correspondence, we study the capacity region of a general wireless network by deriving fundamental upper bounds on a class of linear functionals of the rate tuples at which joint reliable communication can take place. the widely studied transport capacity is a specific linear functional: the coefficient of the rate between a pair of nodes is equal to the euclidean distance between them. the upper bound on the linear functionals of the capacity region is used to derive upper bounds to scaling laws for generalized transport capacity: the coefficient of the rate between a pair of nodes is equal to some arbitrary function of the euclidean distance between them, for a class of minimum distance networks. this upper bound to the scaling law meets that achievable by multihop communication over these networks for a wide class of channel conditions; this shows the optimality, in the scaling-law sense, of multihop communication when studying generalized transport capacity of wireless networks.
new upper bounds on generalized weights. we derive new asymptotic upper bounds on the generalized weights of a binary linear code of a given size. we also prove some asymptotic results on the distance distribution of binary codes.
coding on demand by an informed source (iscod) for efficient broadcast of different supplemental data to caching clients. the informed-source coding on demand (iscod)approach for efficiently supplying nonidentical data from a central server to multiple caching clients over a broadcast channel is presented. the key idea underlying iscod is the joint exploitation of the data blocks already cached by each client, the server's full knowledge of client-cache contents and client requests, and the fact that each client only needs to be able to derive the blocks requested by it rather than all the blocks ever transmitted or even the union of the blocks requested by the different clients. we present two-phase iscod algorithms: the server first creates ad-hoc error-correction sets based on its knowledge of client states; next, it uses erasure-correction codes to construct the data for transmission. each client uses its cached data and the received supplemental data to derive its requested blocks. the result is up to a several-fold reduction in the amount of transmitted supplemental data. also, we define k-partial cliques in a directed graph and cast iscod in terms of partial-clique covers.
the feasibility of matchings in a wireless network. the problem of determining what links can be simultaneously activated in a wireless network such that a signal-to-interference-and-noise (sinr) constraint is satisfied at all receivers is considered. the term "feasible matching" is introduced to describe a set of (transmitter, receiver) pairs for which there exists some set of transmit powers which can simultaneously meet the sinr equirements at the receivers. given disjoint equally sized sets of transmitters and receivers, it is shown that when the sinr requirement at the receivers is greater than 1, no more than one feasible matching between the transmitters and the receivers exists. sufficient conditions are provided under which certain broad classes of matchings in a network are guaranteed to be feasible; for example all matchings involving k or fewer links. the application of these results to ad hoc wireless networks and to scheduling is discussed.
randomized gossip algorithms. motivated by applications to sensor, peer-to-peer, and ad hoc networks, we study distributed algorithms, also known as gossip algorithms, for exchanging information and for computing in an arbitrarily connected network of nodes. the topology of such networks changes continuously as new nodes join and old nodes leave the network. algorithms for such networks need to be robust against changes in topology. additionally, nodes in sensor networks operate under limited computational, communication, and energy resources. these constraints have motivated the design of "gossip" algorithms: schemes which distribute the computational burden and in which a node communicates with a randomly chosen neighbor.we analyze the averaging problem under the gossip constraint for an arbitrary network graph, and find that the averaging time of a gossip algorithm depends on the second largest eigenvalue of a doubly stochastic matrix characterizing the algorithm. designing the fastest gossip algorithm corresponds to minimizing this eigenvalue, which is a semidefinite program (sdp). in general, sdps cannot be solved in a distributed fashion; however, exploiting problem structure, we propose a distributed subgradient method that solves the optimization problem over the network.the relation of averaging time to the second largest eigenvalue naturally relates it to the mixing time of a random walk with transition probabilities derived from the gossip algorithm. we use this connection to study the performance and scaling of gossip algorithms on two popular networks: wireless sensor networks, which are modeled as geometric random graphs, and the internet graph under the so-called preferential connectivity (pc) model.
bounds on approximate steepest descent for likelihood maximization in exponential families. an approximate steepest descent strategy converging, in families of regular exponential densities, to maximum likelihood estimates of density functions is described. these density estimates are also obtained by an application of the principle of minimum relative entropy subject to empirical constraints. we prove tight bounds on the increase of the log-likelihood at each iteration of our strategy for families of exponential densities whose log-densities are spanned by a set of bounded basis functions.
constructions of optical fifo queues. discrete-time queues are infinite dimensional switches in time. ever since shannon published his paper ("memory requirements in telephone exchange," bell syst. tech. j., pp. 343-349, vol. 29, 1950) on the memory requirements in a telephone exchange, there have been tremendous efforts in the search for switches with minimum complexity. constructing queues with minimum complexity has not received the same amount of attention as queues are relatively cheap to build via electronic memory. recent advances in optical technologies, however, have spurred interest in building optical queues with minimum complexity. in this correspondnece, we develop mathematical theory of constructing discrete-time optical first-in-first-out (fifo) queues. to our surprise, we find that many classical constructions for switches have their counterparts for constructing queues. analogous to the three-stage construction of clos networks, we develop three-stage construction of optical fifo queues via switched delay lines (sdls). via recursively expanding the three-stage construction, we show that an optical fifo queue with buffer 2n -- 1 can be constructed by using 2n 2 × 2 switches with the total fiber length 3, 2n-1 -- 2.
on average throughput and alphabet size in network coding. we examine the throughput benefits that network coding offers with respect to the average throughput achievable by routing, where the average throughput refers to the average of the rates that the individual receivers experience. we relate these benefits to the integrality gap of a standard linear programming formulation for the directed steiner tree problem. we describe families of configurations over which network coding at most doubles the average throughput, and analyze a class of directed graph configurations with n receivers where network coding offers benefits proportional to √n. we also discuss other throughput measures in networks, and show how in certain classes of networks, average throughput bounds can be translated into minimum throughput bounds, by employing vector routing and channel coding. finally, we show configurations where use of randomized coding may require an alphabet size exponentially larger than the minimum alphabet size required.
scaling properties of statistical end-to-end bounds in the network calculus. the stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. this paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. the presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad classes of arrival and service distributions. the benefits of the derived service curve are illustrated for the exponentially bounded burstiness (ebb) traffic model. it is shown that end-to-end performance measures computed with a network service curve are bounded by o (h log h), where h is the number of nodes traversed by a flow. using currently available techniques, which compute end-to-end bounds by adding single node results, the corresponding performance measures are bounded by o (h3).
algebraic gossip: a network coding approach to optimal multiple rumor mongering. the problem of simultaneously disseminating k messages in a large network of n nodes, in a decentralized and distributed manner, where nodes only have knowledge about their own contents, is studied. in every discrete time-step, each node selects a communication partner randomly, uniformly among all nodes and only one message can be transmitted. the goal is to disseminate rapidly, with high probability, all messages to all nodes. it is shown that a random linear coding (rlc) based protocol disseminates all messages to all nodes in time ck + o (√k ln(k) ln(n)), where c < 3.46 using pull-based dissemination and c < 5.96 using push-based dissemination. simulations suggest that c < 2 might be a tighter bound. thus, if k ≫ (ln(n))3, the time for simultaneous dissemination rlc is asymptotically at most ck, versus the ω(k log2(n))3 time of sequential dissemination. furthermore, when k ≫ (ln(n))3, the dissemination time is order optimal. when k ≪ (ln(n))2, rlc reduces dissemination time by a factor of ω(√k/ln k) over sequential dissemination. the overhead of the rlc protocol is negligible for messages of reasonable size. a store-and-forward mechanism without coding is also considered. it is shown that this approach performs no better than a sequential approach when k=∞ n. owing to the distributed nature of the system, the proof requires analysis of an appropriate time-varying bernoulli process.
on the security of public key protocols. recently, the use of public key encryption to provide secure network communication has received considerable attention. such public key systems are usually effective against passive eavesdroppers, who merely tap the lines and try to decipher the message. it has been pointed out, however, that an improperly designed protocol could be vulnerable to an active saboteur, one who may impersonate another user or alter the message being transmitted. in this paper we formulate several models in which the security of protocols can be discussed precisely. algorithms and characterizations that can be used to determine protocol security in these models will be given.
unachievability of network coding capacity. the coding capacity of a network is the supremum of ratios k/n for which there exists a fractional (k, n) coding solution, where k is the source message dimension and n is the maximum edge dimension. the coding capacity is referred to as routing capacity in the case when only routing is allowed. a network is said to achieve its capacity if there is some fractional (k, n) solution for which k/n equals the capacity. the routing capacity is known to be achievable for arbitrary networks.we give an example of a network whose coding capacity (which is 1) cannot be achieved by a network code. we do this by constructing two networks, one of which is solvable if and only if the alphabet size is odd, and the other of which is solvable if and only if the alphabet size is a power of 2. no linearity assumptions are made.
on the throughput scaling of wireless relay networks. the throughput of wireless networks is known to scale poorly when the number of users grows. the rate at which an arbitrary pair of nodes can communicate must decrease to zero as the number of users tends to infinity, under various assumptions. one of them is the requirement that the network is fully connected: the computed rate must hold for any pair of nodes of the network. we show that this requirement can be responsible for the lack of throughput scalability. we consider a two-dimensional (2-d) network of extending area with only one active source-destination pair at any given time, and all remaining nodes acting only as possible relays. allowing an arbitrary small fraction of the nodes to be disconnected, we show that the per-node throughput remains constant as the network size increases. as a converse bound, we show that communications occurring at fixed nonzero rate imply a fraction of the nodes to be disconnected. our results are of information theoretic flavor, as they hold without assumptions on the communication strategies employed by the network nodes.
on the shape of a set of points in the plane. a generalization of the convex hull of a finite set of points in the plane is introduced and analyzed. this generalization leads to a family of straight-line graphs, called ``shapes'''', which seem to capture the intuitive notion of ``fine shape'''' and ``crude shape'''' of point sets. .br additionally, close relationships with delaunay triangulations are revealed and, relying on these results, an optimal algorithm that constructs ``shapes'''' is developed.
suboptimality of the karhunen-loe`ve transform for transform coding. we examine the performance of the klt for transform coding applications.theklt has long been viewed as the best available block transform for transform coding.this paper treats fixed-rate and variable-rate transform codes.the fixed-rate approachuses an optimal fixed-rate scalar quantizer to describe the transform coefficients; thevariable-rate approach uses a uniform scalar quantizer followed by an optimal entropycode.earlier work shows that for the variable-rate case there exist sources on whichthe klt is not unique and the optimal transform code matched to a "worst" klt yieldsperformance as much as 1.5 db worse than the optimal transform code matched to a"best" klt. in this paper, we strengthen that result to show that in both the fixed-rateand the variable-rate coding frameworks there exist sources for which the performancepenalty for using a "worst" klt can be made arbitrarily large.further, we demonstratein both frameworks that there exist sources for which even a best klt gives suboptimalperformance.finally, we show that even for vector sources where the klt yieldsindependent coefficients, the klt can be suboptimal for fixed-rate coding.
on the maximum tolerable noise for reliable computation by formulas. it is shown that if a formula is constructed from noisy 2-input nand gates, with each gate failing independently with probability e, then reliable computation can or cannot take place according as e is less than or greater than e_0 = (3-sqrt(7))/4 = 0.08856....
critical node lifetimes in random networks via the chen-stein method. this correspondence considers networks where nodes are connected randomly and can fail at random times. it provides scaling laws that allow to find the critical time at which isolated nodes begin to appear in the system as its size tends to infinity. applications are in the areas of sensor and ad-hoc networks where nodes are subject to battery drainage and 'blind spots' formation becomes a primary concern. the techniques adopted are based on the chen-stein method of poisson approximation, which allows to obtain elegant derivations that are shown to improve upon and simplify previous related results that appeared in the literature. since blind spots are strongly related to full connectivity, we also obtain some scaling results about the latter.
optimal overload response in sensor networks. a single commodity network that models the information flow in an arbitrary topology sensor field that collects and forwards information to a backbone through certain designated gateway nodes is considered. resilient operation in overload stress situations caused by unpredictable traffic or topology variations is investigated. that amounts to studying the network in instability mode, where the traffic load distribution is outside the throughput region. a fluid model is adopted where superflows model traffic forwarding and backlog formations at the network level. quantitative performance metrics of the overload including throughput, lexicographic minimization, most balanced allocation, and amount of lost traffic due to buffer overflow are considered to capture the information loss process due to overflow in the network. optimal superflows with respect to these metrics are characterized and a distributed asynchronous algorithm that computes such superflows is given. the characterization of the optimal superflow amounts to obtaining a structural decomposition of the network in a sequence of disjoint subregions with decreasing overload such that traffic flows only from regions of higher overload to regions of lower overload. the optimal superflow represents the smoothest trajectory to overflow, followed by the network in case of instability.
optimal throughput-delay scaling in wireless networks: part i: the fluid model. gupta and kumar (2000) introduced a random model to study throughput scaling in a wireless network with static nodes, and showed that the throughput per source-destination pair is θ (1/√n log n). grossglauser and tse (2001) showed that when nodes are mobile it is possible to have a constant throughput scaling per source-destination pair. in most applications, delay is also a key metric of network performance. it is expected that high throughput is achieved at the cost of high delay and that one can be improved at the cost of the other. the focus of this paper is on studying this tradeoff for wireless networks in a general framework. optimal throughput-delay scaling laws for static and mobile wireless networks are established. for static networks, it is shown that the optimal throughput-delay tradeoff is given by d(n) = θ (nt(n)), where t(n) and d(n) are the throughput and delay scaling, respectively. for mobile networks, a simple proof of the throughput scaling of θ(1) for the grossglauser-tse scheme is given and the associated delay scaling is shown to be θ(n log n). the optimal throughput-delay tradeoff for mobile networks is also established. to capture physical movement in the real world, a random-walk (rw) model for node mobility is assumed. it is shown that for throughput of o (1/√n log n), which can also be achieved in static networks, the throughput-delay tradeoff is the same as in static networks, i.e., d(n) = θ (nt(n)). surprisingly, for almost any throughput of a higher order, the delay is shown to be θ (n log n), which is the delay for throughput of θ(1). our result, thus, suggests that the use of mobility to increase throughput, even slightly, in real-world networks would necessitate an abrupt and very large increase in delay.
one-way delay estimation using network-wide measurements. we present a novel approach for the estimation of one-way delays between network nodes without any time synchronization in the network. it is based on conducting multiple and simple one-way measurements among pairs of nodes, and estimating the one-way delays by optimizing the value of a global objective function that is affected by the overall network topology and not just by individual measurements. we examine two objective functions. the first intuitive choice is the least square error (lse). using a novel concept of delay-induced link probabilities, we develop a second objective function that is based on the maximum-entropy (me) principle. extensive numerical experiments show that both functions considerably outperform the common method of halving the round-trip delays. they also show that me outperforms the commonly used lse.
on the capacity of information networks. an outer bound on the rate region of noise-free information networks is given. this outer bound combines properties of entropy with a strong information inequality derived from the structure of the network. this blend of information theoretic and graph theoretic arguments generates many interesting results. for example, the capacity of directed cycles is characterized. also, a gap between the sparsity of an undirected graph and its capacity is shown. extending this result, it is shown that multicommodity flow solutions achieve the capacity in an infinite class of undirected graphs, thereby making progress on a conjecture of li and li. this result is in sharp contrast to the situation with directed graphs, where a family of graphs is presented in which the gap between the capacity and the rate achievable using multicommodity flows is linear in the size of the graph.
a general minimax result for relative entropy. suppose nature picks a probability measure p on a complete separable metric space x at random from a fixed set of probability measures. then, without knowing which measure is picked, a statistician picks a measure q on x. finally, the statistician suffers a loss equal to the relative entropy between p and q. we show that the minimax and maximin values of this game are always equal, and there is always a minimax strategy in the closure of the set of all bayes strategies. this generalizes previous results of gallager, and davisson and leon-garcia.
the probability of undetected error can have several local maxima. we show that for a code used for error detection in the bsc, the probability of an undetected error can have several local maxima. in particular, we construct a code with three local maxima in (0,1/2), a code with five local maxima in (0,1); and a linear code with two local maxima in (0,1/2) and a linear code with three local maxima in (0,1).
on the capacity of multiple unicast sessions in undirected graphs. li and li conjectured that in an undirected network with multiple unicast sessions, network coding does not lead to any coding gain. surprisingly enough, this conjecture could not so far be verified even for the simple network consisting of k 3, 2 with four source-sink pairs. using entropy calculus, we provide the first verification of the li-li conjecture for this network. we extend our bound to the case of an arbitrary directed bipartite network.
relaying protocols for two colocated users. we consider a wireless network where a remote source sends information to one of two colocated users, and where the second user can serve as a relay. the source's transmission is subjected to quasi-static flat rayleigh fading, while the transmission of the relay experiences a fixed amplitude gain with a uniform random phase, capturing its close proximity to the destination. all communications share the same time/bandwith resources, and perfect channel state information is known only to the receivers. we propose relaying protocols which are based on wyner-ziv quantization at the relay, and demonstrate their high efficiency (in terms of expected throughput) with respect to previously reported relaying schemes based on amplify-and-forward and decode-and-forward. a salient feature of these protocols is that the relay need not know the actual fading gain experienced by the destination in order to perform the quantization. we also consider a hybrid amplify-quantize-decode-and-forward scheme which exhibits superior performance.
the encoding complexity of network coding. in the multicast network coding problem, a source s needs to deliver h packets to a set of k terminals over an underlying communication network g. the nodes of the multicast network can be broadly categorized into two groups. the first group incudes encoding nodes, i.e., nodes that generate new packets by combining data received from two or more incoming links. the second group includes forwarding nodes that can only duplicate and forward the incoming packets. encoding nodes are, in general, more expensive due to the need to equip them with encoding capabilities. in addition, encoding nodes incur delay and increase the overall complexity of the network.accordingly, in this paper, we study the design of multicast coding networks with a limited number of encoding nodes. we prove that in a directed acyclic coding network, the number of encoding nodes required to achieve the capacity of the network is bounded by h3 k2. namely, we present (efficiently constructible) network codes that achieve capacity in which the total number of encoding nodes is independent of the size of the network and is bounded by h3k2. we show that the number of encoding nodes may depend both on h and k by presenting acyclic coding networks that require ω (h2k) encoding nodes. in the general case of coding networks with cycles, we show that the number of encoding nodes is limited by the size of the minimum feedback link set, i.e., the minimum number of links that must be removed from the network in order to eliminate cycles. we prove that the number of encoding nodes is bounded by (2b + 1) h3k2, where bis the minimum size of a feedback link set. finally, we observe that determining or even crudely approximating the minimum number of required encoding nodes is an np-hard problem.
matrix games in the multicast networks: maximum information flows with network switching. network coding for achieving the maximum information flow in the multicast networks has been proposed by ahlswede, cai, li, and yeung. they have demonstrated that the conventional network switching, without resort to network coding, is in general not able to achieve the optimum information flow that has been promised by network coding. a basic problem arising here is that, for a given multicast network, what is the switching gap of the network defined as the ratio of the maximum information flow in the multicast network with network coding to that only with network switching.in the paper, by considering network switching as a special form of network coding, we make a complete theoretical and computational determination of the achievable information rate region for multisource multicast network switching. the multicast networks are allowed to be cyclic or acyclic with links having arbitrary positive integer or real-valued capacity. network switching is essentially a problem of multicast-route packing in the multicast networks. based on this, we use the theory of games to formulate the network switching as a matrix game between the first "player" of links and the second "player" of multicast routes in the multicast networks. we prove that the maximum achievable information rate at each probabilistic direction in the information rate region is the reciprocal of the value of the corresponding game. consequently, the maximum achievable information rate can be computed in a simple way by applying the existing theory and algorithms for the computation of the value of a matrix game, especially for such multicast networks with links all having unit capacity as the ahlswede-cai-li-yeung multicast networks. for multicast networks with links having arbitrary positive real-valued capacity, by using convex optimization, we develop a simple and efficient iterative algorithm to find the maximum achievable information rates for multisource multicast network switching.for single-source multicast networks whose links have arbitrary positive real-valued capacity, we present two max-flow min-cut theorems. the maximum information flow for single-source network switching is the minimum capacity among all soft link-cuts of the multicast network, while the maximum information flow for single-source network coding is the minimum capacity among all hard link-cuts. consequently, by applying the theory of approximation algorithms for the set-covering problem, we demonstrate that the switching gap of a single-source multicast network is upper-bounded by the th harmonic number hn=1 + ½ +.....+ 1/n where nis the largest number of multicast routes containing a given link in the network. this harmonic-number bound is asymptotically tight as o(ln n) for the combination multicast network. for the special class of multisource multicast networks with the same set of sink nodes, we make a comparison between the achievable information rate regions for network switching and network coding.
a fast lightweight approach to origin-destination ip traffic estimation using partial measurements. in this paper, a novel approach is proposed for estimating traffic matrices. our method, called pamtram for partial measurement of traffic matrices, couples lightweight origin-destination (od) flow measurements along with a computationally lightweight algorithm for producing od estimates. the first key aspect of our method is to actively select a small number of informative od flows to measure in each estimation interval. to avoid the heavy computation of optimal selection, we use intuition from game theory to develop randomized selection rules, with the goals of reducing errors and adapting to traffic changes. we show that it is sufficient to measure only one flow per measurement period to drastically reduce errors--thus rendering our method lightweight in terms of measurement overhead. the second key aspect is an explanation and proof that an iterative proportional fitting algorithm approximates traffic matrix estimates when the goal is a minimum mean-squared error; this makes our method lightweight in terms of computation overhead. a one-step error bound is provided for pamtram that bounds the average error for the worst scenario. we validate our method using data from sprint's european tier-1 ip backbone network and demonstrate its consistent improvement over previous methods.
on achieving maximum multicast throughput in undirected networks. the transmission of information within a data network is constrained by the network topology and link capacities. in this paper, we study the fundamental upper bound of information dissemination rates with these constraints in undirected networks, given the unique replicable and encodable properties of information flows. based on recent advances in network coding and classical modeling techniques in flow networks, we provide a natural linear programming formulation of the maximum multicast rate problem. by applying lagrangian relaxation on the primal and the dual linear programs (lps), respectively, we derive a) a necessary and sufficient condition characterizing multicast rate feasibility, and b) an efficient and distributed subgradient algorithm for computing the maximum multicast rate. we also extend our discussions to multiple communication sessions, as well as to overlay and ad hoc network models. both our theoretical and simulation results conclude that, network coding may not be instrumental to achieve better maximum multicast rates in most cases; rather, it facilitates the design of significantly more efficient algorithms to achieve such optimality.
degenerate delay-capacity tradeoffs in ad-hoc networks with brownian mobility. there has been significant recent interest within the networking research community to characterize the impact of mobility on the capacity and delay in mobile ad hoc networks.in this correspondence, the fundamental tradeoff between the capacity and delay for a mobile ad hoc network under the brownian motion model is studied. it is shown that the two-hop relaying scheme proposed by grossglauser and tse (2001), while capable of achieving a per-node throughput of θ(1), incurs an expected packet delay of ω(logn/αn2), where αn2) is the variance parameter of the brownian motion model. it is then shown that an attempt to reduce the delay beyond this value results in the throughput dropping to its value under static settings.in particular, it is shown that under a large class of scheduling and relaying schemes, if the mean packet delay is o(nα/αn2), for any α ≤ 0, then the per-node throughput must be o(1/√n). this result is in sharp contrast to other results that have recently been reported in the literature.
nonhomogeneous trellis codes for the quasi-synchronous multiple-access binary adder channel with two users. a trellis code is {em homogeneous} if the number of branches emanating from each node (or state) in the trellis diagram is constant. for example, convolutional codes are linear homogeneous trellis codes. a trellis code is {em nonhomogeneous} if the number of branches emanating from each node in the trellis diagram is not the same. the two-user binary adder channel is a multiple-access channel with two binary inputs,x_{1}andx_{2}, and one ternary output,y = x_{1} + x_{2}, where the addition is done in the real number field. the adder channel is synchronous if both encoders and the decoder maintain block (frame) synchronism. it is quasi-synchronous if the encoders do not start their blocks at the same time, but the decoder knows the position of each block. the difference between the starting times of the blocks is called the slippage. the channel is asynchronous if no block synchronism exists among the encoders and the decoder. some uniquely decodable code pairs(c_{1}, c_{2})are presented that can be used to transmit information reliably over the quasi-synchronous binary adder channel with two users. one of the codes is a nonhomogeneous trellis code, the other is a common block code. our code rates are better than deaett-wolf codes and are close to or equal to the asymptotic rates of kasami {em et al}. a method for calculating the rates of nonhomogeneous trellis codes is described. an algorithm for finding more uniquely decodable code pairs for the quasi-synchronous binary adder channel is formulated.
on the throughput, capacity, and stability regions of random multiple access. this paper studies finite-terminal random multiple access over the standard multipacket reception (mpr) channel. we characterize the relations among the throughput region of random multiple access, the capacity region of multiple access without code synchronization, and the stability region of aloha protocol. in the first part of the paper, we show that if the mpr channel is standard, the throughput region of random multiple access is coordinate convex. we then study the information capacity region of multiple access without code synchronization and feedback. inner and outer bounds to the capacity region are derived. we show that both the inner and the outer bounds converge asymptotically to the throughput region. in the second part of the paper, we study the stability region of finite-terminal aloha multiple access. for a class of packet arrival distributions, we demonstrate that the stationary distribution of the queues possesses positive and strong positive correlation properties, which consequently yield an outer bound to the stability region. we also show the major challenge in obtaining the closure of the stability region is due to the lack of sensitivity analysis results with respect to the transmission probabilities. particularly, if a conjectured "sensitivity monotonicity" property held for the stationary distribution of the queues, then equivalence between the closure of the stability region and the throughput region follows as a direct consequence, irrespective of the packet arrival distributions.
set reconciliation with nearly optimal communication complexity. we consider a fundamental problem that arises in the context of gossip protocols. specifically, we consider the problem of efficiently reconciling two similar sets held by different hosts while minimizing the communication complexity. we provide two surprisingly simple and efficient protocols that exhibit tractable computational complexity and nearly optimal communication complexity. these protocols can be adapted to work over a broadcast channel, allowing many clients to reconcile with one host based on a broadcasted signal.\note{we keep on bouncing back and forth on whether the ``a''''s are necessary. i like it better without, but it''s not a big deal.} thus, an arbitrary number of clients each of whose data differs from that of the host by no more than $n$ bits can be reconciled by a single broadcast of $o(n)$ bits, independent of the the number of clients and independent of the size of the data sets.
overcoming untuned radios in wireless networks with network coding. the drive toward the implementation and massive deployment of wireless sensor networks calls for ultralow-cost and low-power nodes. while the digital subsystems of the nodes are still following moore's law, there is no such trend regarding the performance of analog components. this work proposes a fully integrated architecture of both digital and analog components (including local oscillator) that offers significant reduction in cost, size, and overall power consumption of the node. even though such a radical architecture cannot offer the reliable tuning of standard designs, it is shown that by using random network coding, a dense network of such nodes can achieve throughput linear in the number of channels available for communication. moreover, the ratio of the achievable throughput of the untuned network to the throughput of a tuned network with perfect coordination is shown to be close to 1/e. this work uses network coding to leverage the fact that throughput equal to the max-flow in a graph is achievable even if the topology is not know a priori. however, the challenge here is finding the max-flow of the random graph corresponding to the network.
quantum signal propagation in depolarizing channels. quantum signal propagation in depolarizing channels nicholas pippenger abstract: let x be an unbiassed random bit, let y be a qubit whose mixed state depends on x, and let the qubit z be the result of passing y through a depolarizing channel, which replaces y with a completely random qubit with probability p. we measure the quantum mutual information between x and y by t(x; y) = s(x) + s(y) - s(x,y), where s(...) denotes von neumann''s entropy. (since x is a classical bit, the quantity t(x; y) agrees with holevo''s bound chi(x; y) to the classical mutual information between x and the outcome of any measurement of y.) we show that t(x;z) >= (1-p)^2 t(x;y). this generalizes an analogous bound for classical mutual information due to evans and schulman, and provides a new proof of their result.
the inequalities of quantum information theory. the inequalities of quantum information theory nicholas pippenger given an n-part quantum state, we consider the 2^n substates obtained by restricting attention to a subset of the parts. the entropies (in the sense of von neumann) of these substates may be regarded as a point, called the allocation of entropy, in a (2^n)-dimensional real vector space. we show that the topological closure of the set of allocations of entropy form a convex cone. we show that a set of inequalities due to lieb and ruskai characterize this cone when n is at most 3. we also consider the symmetric situation in which the entropy depends only on the number of parts in the substate. in this case, the topological closure of the set of allocations of entropy (in (n+1)-dimensional space) again form a convex cone, and we give inequalities characterizing this cone for all n.
entropy and expected acceptance counts for finite automata. entropy and expected acceptance counts for finite automata nicholas pippenger if a sequence of independent unbiased random bits is fed into a finite automaton, it is straightforward to calculate the expected number of acceptances among the first n prefixes of the sequence. this paper deals with the situation in which the random bits are neither independent nor unbiased, but are nearly so. we show that, under suitable assumptions concerning the automaton, if the the difference between the entropy of the first n bits and n converges to a constant exponentially fast, then the change in the expected number of acceptances also converges to a constant exponentially fast. we illustrate this result with a variety of examples in which numbers following the reciprocal distribution, which governs the significands of floating-point numbers, are recoded in the execution of various multiplication algorithms.
on a lower bound for the redundancy of reliable networks with noisy gates. we prove that a logarithmic redundancy factor is necessary for the reliable computation of the parity function by means of a networks with noisy gates. this result is the same as one claimed by dobrushin and ortyukov in 1977, but the proof they gave appears to be incorrect.
two families of optimal identifying codes in binary hamming spaces. a motivation for identifying codes comes from quality control in multiprocessor systems, that is, we are able to find faulty processors in such a system with the aid of these codes. in this paper we give a construction of two infinite families of optimal codes, which identify up to two malfunctioning processors in hamming spaces.
the multicast capacity of deterministic relay networks with no interference. the multicast capacity is determined for networks that have deterministic channels with broadcasting at the transmitters and no interference at the receivers. the multicast capacity is shown to have a cut-set interpretation. it is further shown that one cannot always layer channel and network coding in such networks. the proof of the latter result partially generalizes to discrete memoryless broadcast channels and is used to bound the common rate for problems where one achieves a cut bound on throughput.
statistical location detection with sensor networks. the paper develops a systematic framework for designing a stochastic location detection system with associated performance guarantees using a wireless sensor network. to detect the location of a mobile sensor, the system relies on rf-characteristics of the signal transmitted by the mobile sensor, as it is received by stationary sensors (clusterheads). location detection is posed as a hypothesis testing problem over a discretized space. large deviations results enable the characterization of the probability of error leading to a placement problem that maximizes an information-theoretic distance (chernoff distance) among all pairs of probability distributions of observations conditional on the sensor locations. the placement problem is shown to be np-hard and is formulated as a linear integer programming problem; yet, large instances can be solved efficiently by leveraging special-purpose algorithms from the theory of discrete facility location. the resultant optimal placement is shown to provide asymptotic guarantees on the probability of error in location detection under quite general conditions by minimizing an upper bound of the error-exponent. numerical results show that the proposed framework is computationally feasible and the resultant clusterhead placement performs near-optimal even with a small number of observation samples in a simulation environment.
separating distributed source coding from network coding. this correspondence considers the problem of distributed source coding of multiple sources over a network with multiple receivers. each receiver seeks to reconstruct all of the original sources. the work by ho et al. 2004 demonstrates that random network coding can solve this problem at the potentially high cost of jointly decoding the source and the network code. motivated by complexity considerations we consider the performance of separate source and network codes. previous work by effros et al. 2003 demonstrates the failure of separation between source and network codes for nonmulticast networks.we demonstrate that failure for multicast networks. we study networks with capacity constraints on edges. it is shown that the problem with two sources and two receivers is always separable. counterexamples are presented for other cases.
distributed network protocols. the primary topic of this dissertation is disjoint np-pairs. a disjoint np-pair is a pair of disjoint, nonempty sets in np. the study of disjoint np-pairs is motivated by its connections to secure public-key cryptosystems and to propositional proof complexity. one fundamental question in the study of disjoint np-pairs is whether there exist p-inseparable or np-hard disjoint np-pairs. this question is closely related to the existence of secure public-key cryptosystems. another important question on disjoint np-pairs is whether the class of all disjoint np-pairs has a complete pair. a negative answer to this question would imply non-existence of optimal propositional proof systems, which is a well-studied but still open question in proof theory. we study these questions and obtain results that give better understandings of these questions, as well as the relations between disjoint np-pairs and propositional proof systems. in particular, we show that the above questions cannot be settled with relativizable techniques. it has been recently known that the degree structure of disjoint np-pairs is identical to the degree structure of canonical np-pairs of propositional proof systems. this makes it interesting and important to study the degree structure of disjoint np-pairs. we study this and prove that the degree structure of disjoint np-pairs is "universal'' in the sense that every countable distributive lattice can be embedded into every interval of degrees of disjoint np-pairs by maps that preserve the least or greatest elements. we also study the question how much information canonical np-pairs contain of their corresponding propositional proof systems. we obtain various results demonstrating that canonical np-pairs reflect the properties of their corresponding propositional proof systems, but only to certain extent. the secondary topic of this dissertation is structural properties of complete sets. what structural properties complete sets of different complexity classes have is a basic problem in computational complexity. it is important to study such computational structure of complete sets, because they, by reductions of all the sets in the class to the complete sets, represent all of the structure that a class might have. for this reason, the study of structural properties of complete sets gave us a better understanding of the computational power of various complexity classes, and also might lead to proofs of separation results in complexity theory. we mainly study robustness, autoreducibility, and mitoticity of complete sets. in particular we solve the open question whether polynomial 2-tt autoreducibilty implies polynomial-time 2-tt mitoticity.
raptor codes. lt-codes are a new class of codes introduced by luby for the purpose of scalable and fault-tolerant distribution of data over computer networks. in this paper, we introduce raptor codes, an extension of lt-codes with linear time encoding and decoding. we will exhibit a class of universal raptor codes: for a given integer k and any real ε > 0, raptor codes in this class produce a potentially infinite stream of symbols such that any subset of symbols of size k(1 + ε) is sufficient to recover the original k symbols with high probability. each output symbol is generated using o(log(1/ ε)) operations, and the original symbols are recovered from the collected ones with o(k log(1/ε)) operations.we will also introduce novel techniques for the analysis of the error probability of the decoder for finite length raptor codes. moreover, we will introduce and analyze systematic versions of raptor codes, i.e., versions in which the first output elements of the coding system coincide with the original k elements.
bandwidth- and power-efficient routing in linear wireless networks. the goal of this paper is to establish which practical routing schemes for wireless networks are most suitable for power-limited and bandwidth-limited communication regimes. we regard channel state information (csi) at the receiver and point-to-point capacity-achieving codes for the additive white gaussian noise (awgn) channel as practical features, interference cancellation (ic) as possible, but less practical, and synchronous cooperation (csi at the transmitters) as impractical. we consider a communication network with a single source node, a single destination node, and n-1 intermediate nodes placed equidistantly on a line between them. we analyze the minimum total transmit power needed to achieve a desired end-to-end rate for several schemes and demonstrate that multihop communication with spatial reuse performs very well in the power-limited regime, even without ic. however, within a class of schemes not performing ic, single-hop transmission (directly from source to destination) is more suitable for the bandwidth-limited regime, especially when higher spectral efficiencies are required. at such higher spectral efficiencies, the gap between single-hop and multihop can be closed by employing ic, and we present a scheme based upon backward decoding that can remove all interference from the multihop system with an arbitrarily small rate loss. this new scheme is also used to demonstrate that rates of o(log n) are achievable over linear wireless networks even without synchronous cooperation.
asymptotic analysis of multistage cooperative broadcast in wireless networks. cooperative broadcast aims to deliver a source message to a locally connected network by means of collaborating nodes. in traditional architectures, node cooperation has been at the network layer. recently, physical layer cooperative schemes have been shown to offer several advantages over the network layer approaches. this form of cooperation employs distributed transmission resources at the physical layer as a single radio with spatial diversity. in decentralized cooperation schemes, collaborating nodes make transmission decisions based on the quality of the received signal, which is the only parameter available locally. in this case, critical parameters that influence the broadcast performance include the source/relay transmission powers and the decoding threshold (the minimum signal-to-noise ratio (snr) required to decode a transmission). we study the effect of these parameters on the number of nodes reached by cooperative broadcast. in particular, we show that there exists a phase transition in the network behavior: if the decoding threshold is below a critical value, the message is delivered to the whole network. otherwise, only a fraction of the nodes is reached, which is proportional to the source transmit power. our approach is based on the idea of continuum approximation, which yields closed-form expressions that are accurate when the network density is high.
capacity of queues via point-process channels. a conceptually simple proof for the capacity formula of an exponential server timing channel is provided. the proof links the timing channel to the point-process channel with instantaneous noiseless feedback. this point-process approach enables a study of timing channels that arise in multiserver queues, queues in tandem, and other simple configurations. although the capacities of such channels remain to be found, the paper provides some analytical bounds and highlights a method to find achievable rates via simulations.
design of some new efficient balanced codes. a balanced code with r check bits and k information bits is a binary code of length k+r and cardinality 2k such that each codeword is balanced; that is, it has [k+ r/1] 1''s and [k+r /2] 0''s. this paper contains new methods to construct efficient balance codes based on the concept of tail-map. a tail-map is and injective function from the set of the very unbalanced words to the set of the balanced ones. to design balanced codes, those information words with a low number of 1''s or 0''s are encoded using tail-maps, while those that have almost the same number of 1''s and 0''s are encoded using the single maps defined by knuth''s complementation method. three different tail-map constructions are presented. balanced codes with r check bits and k > 2r +1-2, k > 3.2r -8 and k > 5.2r -10r + c(r )(c(r )e{ -15,-10,-5, 0,+5}) information bits are given, improving the constructions found in the literature. the tail-maps used in the first two constructions can be computed using a parallel scheme. key words: balanced codes, data integrity, data synchronization, dc-free codes, unidirectional errors. cstr 93-60-19 jiang zhu, lihua zhao, ted lewis, weldon jackson, and russel wilson, "harts: hard real-time software development environment we introduce a hard real-time software development environment, called harts, which consists of a design tool and a scheduling tool. the design tool supports a hierarchical design diagram which combines the control and data flow of a hard real-time application. the design hierarchy separates a design into self-contained subdesigns. yet, the design can be flattened to give you a global view. in a distributed environment, the hierarchy provides a natural way for assigning subdesigns to different processors. the design diagram is quite intuitive, and yet it can be automatically analyzed for scheduleability. the scheduling tool schedules task graphs (directed acyclic graphs whose nodes are periodic tasks) with its heuristic algorithms which try to use as few processors as possible to meet both the timing and precedence constraints. based on a generated schedule, the scheduling tool can further simulate the task execution with highly animated user interfaces, which goes beyond the traditional way of examining a schedule as a static gannett chart. although the design tool and the scheduling tool has not been fully integrated, we show that the current scheduling tool can be easily extended to schedule the precedence-constrained periodic task set derived from a design diagram. keywords: real-time, hard real-time, hard real-time system design, real-time control, scheduling, real-time scheduling, hard real-time scheduling.
a unification of network coding and tree-packing (routing) theorems. given a network of lossless links with rate constraints, a source node, and a set of destination nodes, the multicast capacity is the maximum rate at which the source can transfer common information to the destinations. the multicast capacity cannot exceed the capacity of any cut separating the source from a destination; the minimum of the cut capacities is called the cut bound. a fundamental theorem in graph theory by edmonds established that if all nodes other than the source are destinations, the cut bound can be achieved by routing. in general, however, the cut bound cannot be achieved by routing. ahlswede et al. established that the cut bound can be achieved by performing network coding, which generalizes routing by allowing information to be mixed. this paper presents a unifying theorem that includes edmonds' theorem and ahlswede et al.'s theorem as special cases. specifically, it shows that the multicast capacity can still be achieved even if information mixing is only allowed on edges entering relay nodes. this unifying theorem is established via a graph theoretic hardwiring theorem, together with the network coding theorems for multicasting. the proof of the hardwiring theorem implies a new proof of edmonds' theorem.
on the path-loss attenuation regime for positive cost and linear scaling of transport capacity in wireless networks. wireless networks with a minimum inter-node separation distance are studied where the signal attenuation grows in magnitude as 1/ρδ with distance ρ. two performance measures of wireless networks are analyzed. the transport capacity is the supremum of the total distance-rate products that can be supported by the network. the energy cost of information transport is the infimum of the ratio of the transmission energies used by all the nodes to the number of bit-meters of information thereby transported.if the phases of the attenuations between node pairs are uniformly and independently distributed, it is shown that the expected transport capacity is upper-bounded by a multiple of the total of the transmission powers of all the nodes, whenever δ > 2 for two-dimensional networks or δ > 5/4 for one-dimensional networks, even if all the nodes have full knowledge of all the phases, i.e., full channel state information. if all nodes have an individual power constraint, the expected transport capacity grows at most linearly in the number of nodes due to the linear growth of the total power. this establishes the best case order of expected transport capacity for these ranges of path-loss exponents since linear scaling is also feasible.if the phases of the attenuations are arbitrary, it is shown that the transport capacity is upper-bounded by a multiple of the total transmission power whenever δ > 5/2 for two-dimensional networks or δ > 3/2 for one-dimensional networks, even if all the nodes have full channel state information. this shows that there is indeed a positive energy cost which is no less than the reciprocal of the above multiplicative constant. it narrows the transition regime where the behavior is still open, since it is known that when δ < 3/2 for two-dimensional networks, or δ < 1 for one-dimensional networks, the transport capacity cannot generally be bounded by any multiple of the total transmit power.
an outer bound for multisource multisink network coding with minimum cost consideration. the max-flow min-cut bound is a fundamental result in the theory of communication networks, which characterizes the optimal throughput for a point-to-point communication network. the recentwork of ahlswede et al. extended it to single-source multisink multicast networks and li et al. proved that this bound can be achieved by linear codes. following this line, erez and feder as well as ngai and yeung proved that the max-flow min-cut bound remains tight in single-source two-sink nonmulticast networks. but the max-flow min-cut bound is in general quite loose (see yeung, 2002). on the other hand, the admissible rate region of communication networks has been studied by yeung and zhang as well as song and yeung, but the bounds obtained by these authors are not explicit. in this work, we prove a new explicit outer bound for arbitrary multisource multisink networks and demonstrate its relation with the minimum cost network coding problem. we also determine the capacity region for a special class of three-layer networks.
properties and applications of preimage distributions of perfect nonlinear functions. the preimage distributions of perfect nonlinear functions from an abelian group of order n to an abelian group of order 3 or 4, respectively, are studied. based on the properties of the preimage distributions of perfect nonlinear functions from an abelian group of order 3r to an abelian group of order 3, the weight distributions of the ternary linear codes cπ from the perfect nonlinear functions π(x) from f3r to itself are determined. these results suggest that two open problems, proposed by carlet, ding, and yuan in 2005 and 2006, respectively, are answered.
optimal constellations for the low-snr noncoherent mimo block rayleigh-fading channel. reliable communication over the discrete-input/continuous-output noncoherent multiple-input multiple-output (mimo) rayleigh block-fading channel is considered when the signal-to-noise ratio (snr) per degree of freedom is low. two key problems are posed and solved to obtain the optimum discrete input. in both problems, the average and peak power per space-time slot of the input constellation are constrained. in the first one, the peak power to average power ratio (ppapr) of the input constellation is held fixed, while in the second problem, the peak power is fixed independently of the average power. in the first ppapr-constrained problem, the mutual information, which grows as o(snr2), is maximized up to second order in snr. in the second peak-constrained problem, where the mutual information behaves as o(snr), the structure of constellations that are optimal up to first order, or equivalently, that minimize energy per bit, are explicitly characterized. furthermore, among constellations that are first-order optimal, those that maximize the mutual information up to second order, or equivalently, the wideband slope, are characterized. in both ppapr-constrained and peak-constrained problems, the optimal constellations are obtained in closed form as solutions to nonconvex optimizations, and interestingly, they are found to be identical. due to its special structure, the common solution is referred to as space-time orthogonal rank one modulation, or storm. in both problems, it is seen that storm provides a sharp characterization of the behavior of noncoherent mimo capacity.
recursive space-time trellis codes using differential encoding. differential space-time modulation (dstm) has been recently proposed by hughes, and hochwald and sweldens when the channel information is not known at the receiver, where the demodulation is in fact the same as the coherent demodulation of space-time block coding by replacing the channel matrix with the previously received signal matrix. on the other hand, the dstm also needs a recursive memory of a matrix block at the encoder and therefore provides a trellis structure when the channel information is known at the receiver, which is the interest of this paper. this recursive structure of the dstm has been adopted lately by schlegel and grant in joint with a conventional binary code and joint iterative decoding/demodulation with a superior performance. the number of states of the trellis from the recursive structure depends on both the memory size, which is fixed in this case, and the unitary space-time code (ustc). when a ustc for the dstm forms a group, the number of states is the same as the size of the ustc, otherwise the number of the states is the size of the semi-group generated by the ustc from all the multiplications of the matrices in the ustc. it is well known in the conventional convolutional coding (cc) or the trellis coded modulation (tcm), the free (hamming or euclidean) distance (or the performance) increases when the number of states increases by adding more memory with a properly designed cc or tcm. in this paper, we systematically study and design the ustc/dstm for the recursive space-time trellis modulation and show that the diversity product increases when the number of states increases, which is not because of the memory size but because of the different ustc designs that generate different sizes of semi-groups. we propose a new ustc design criterion to ensure that the trellis structure improves the diversity product over the ustc as a block code. based on the new criterion, we propose a new class of ustc design for an arbitrary number of transmit antennas that has an analytical diversity product formula for two transmit antennas. we then follow schlegel and grant's approach for joint encoding and iterative decoding of a binary coded dstm (turbo space-time coding) and numerically show that our new ustc designs for the recursive space-time trellis modulation outperforms the group ustc used by schlegel and grant.
joint source-channel coding excess distortion exponent for some memoryless continuous-alphabet systems. we investigate the joint source-channel coding (jscc) excess distortion exponent ej (the exponent of the probability of exceeding a prescribed distortion level) for some memoryless communication systems with continuous alphabets. we first establish upper and lower bounds for ej for systems consisting of a memoryless gaussian source under the squared-error distortion fidelity criterion and a memoryless additive gaussian noise channel with a quadratic power constraint at the channel input. a necessary and sufficient condition for which the two bounds coincide is provided, thus exactly determining the exponent. this condition is observed to hold for a wide range of source-channel parameters. as an application, we study the advantage in terms of the excess distortion exponent of jscc over traditional tandem (separate) coding for gaussian systems. a formula for the tandem exponent is derived in terms of the gaussian source and gaussian channel exponents, and numerical results show that jscc often substantially outperforms tandem coding. the problem of transmitting memoryless laplacian sources over the gaussian channel under the magnitude-error distortion is also carried out. finally, we establish a lower bound for ej for a certain class of continuous source-channel pairs when the distortion measure is a metric.
random sensory networks: a delay analysis. a fundamental function performed by a sensory network is the retrieval of data gathered collectively by sensor nodes. the metrics that measure the efficiency of this data collection process are time and energy. in this paper, we study via simple discrete mathematical models, the statistics of the data collection time in sensory networks. specifically, we analyze the average minimum delay in collecting randomly located/distributed sensors data for networks of various topologies when the number of nodes becomes large. furthermore, we analyze the impact of various parameters such as size of packet, transmission range, and channel erasure probability on the optimal time performance. our analysis applies to directional antenna systems as well as omnidirectional ones. this paper focuses on directional antenna systems and briefly presents results on omnidirectional antenna systems. finally, a simple comparative analysis shows the respective advantages of the two systems.
a finite-length algorithm for ldpc codes without repeated edges on the binary erasure channel. this paper considers the performance, on the binary erasure channel, of low-density parity-check (ldpc) codes without repeated edges in their tanner graphs. a modification to existing finite-length analysis algorithms is presented for these codes.
linear-codes-based lossless joint source-channel coding for multiple-access channels. a general lossless joint source-channel coding (jscc) scheme based on linear codes and random interleavers for multiple-access channels (macs) is presented and then analyzed in this paper. by the information-spectrum approach and the code-spectrum approach, it is shown that a linear code with a good joint spectrum can be used to establish limit-approaching lossless jscc schemes for correlated general sources and general macs, where the joint spectrum is a generalization of the input-output weight distribution. some properties of linear codes with good joint spectra are investigated. a formula on the "distance" property of linear codes with good joint spectra is derived, based on which, it is further proved that, the rate of any systematic codes with good joint spectra cannot be larger than the reciprocal of the corresponding alphabet cardinality, and any sparse generator matrices cannot yield linear codes with good joint spectra. the problem of designing arbitrary rate coding schemes is also discussed. a novel idea called "generalized puncturing" is proposed, which makes it possible that one good low-rate linear code is enough for the design of coding schemes with multiple rates. finally, various coding problems of macs are reviewed in a unified framework established by the code-spectrum approach, under which, criteria and candidates of good linear codes in terms of spectrum requirements for such problems are clearly presented.
performance of sigma-delta quantizations in finite frames. in this paper, we extend the results that we derived in [1], [2] to the case of filter banks (fbs) based transmission. we consider first- and second-order sigma-delta (sd) quantization in the context of an oversampled digital fourier transform (dft) fbs (dft-fbs). in this context, we investigate the case of odd-and even-stacked dft fbs. we establish the set of conditions that guarantee that the reconstruction minimum squares error (mse) behaves as 1/r2 where r denotes the frame redundancy and we derive the corresponding mse upper-bounds closed-form expressions. the obtained results demonstrate that overoversampled fbs that are subject to the first- and second-order sd can exhibit a reconstruction error behavior according to 1/r2. furthermore, the established results are shown to be true under the quantization model used in [3]-[6], as well as under the widely used additive white quantization noise assumption.
estimation of a regression function by maxima of minima of linear functions. in this paper, estimation of a regression function from independent and identically distributed random variables is considered. estimates are defined by minimization of the empirical l2 risk over a class of functions, which are defined as maxima of minima of linear functions. results concerning the rate of convergence of the estimates are derived. in particular, it is shown that for smooth regression functions satisfying the assumption of single index models, the estimate is able to achieve (up to some logarithmic factor) the corresponding optimal one-dimensional rate of convergence. hence, under these assumptions, the estimate is able to circumvent the so-called curse of dimensionality. the small sample behavior of the estimates is illustrated by applying them to simulated data.
analysis of a mixed strategy for multiple relay networks. infrastructure-based wireless communications systems as well as ad-hoc networks experience a growing importance in present-day telecommunications. an increased density and popularity of mobile terminals poses the question how to exploit wireless networks more efficiently. one possibility is to use relay nodes supporting the end-to-end communication of two nodes. in their landmark paper, cover and el gamal proposed different coding strategies for the single-relay channel. these strategies are the decode-and-forward and compress-and-forward approach, as well as a general lower bound on the capacity of a single-relay network which relies on the combined application of the previous two strategies. so far, only parts of their work-the decode-and-forward and the compress-and-forward strategy-have been applied to networks with multiple relays. in this paper a generalizing framework for multiple-relay networks is derived using a combined approach of partial decode-and-forward and the ideas of successive refinement with different side information. after describing the protocol structure, the achievable rates for the discrete memoryless relay channel as well as the gaussian multiple-relay channel are presented and analyzed. using these results the derived framework is compared with protocols of lower complexity, e.g., multilevel decode-and-forward and distributed compress-and-forward.
new optimal quadriphase sequences with larger linear span. in this paper, two new optimal families s and u of quadriphase sequences are presented. compared to the family a constructed by boztas et al. and the family d investigated by tang et al. respectively, the proposed families have the same optimal correlation properties and family size, but larger linear spans.
dynamic algorithms for multicast with intra-session network coding. the problem of multiple multicast sessions with intra-session network coding in time-varying networks is considered. the network-layer capacity region of input rates that can be stably supported is established. dynamic algorithms for multicast routing, network coding, power allocation, session scheduling, and rate allocation across correlated sources, which achieve stability for rates within the capacity region, are presented. this work builds on the back-pressure approach introduced by tassiulas et al., extending it to network coding and correlated sources. in the proposed algorithms, decisions on routing, network coding, and scheduling between different sessions at a node are made locally at each node based on virtual queues for different sinks. for correlated sources, the sinks locally determine and control transmission rates across the sources. the proposed approach yields a completely distributed algorithm for wired networks. in the wireless case, power control among different transmitters is centralized while routing, network coding, and scheduling between different sessions at a given node are distributed.
sinkhorn solves sudoku. the sudoku puzzle is a discrete constraint satisfaction problem, as is the error correction decoding problem. we propose here an algorithm for solution to the sinkhorn puzzle based on sinkhorn balancing. sinkhorn balancing is an algorithm for projecting a matrix onto the space of doubly stochastic matrices. the sinkhorn balancing solver is capable of solving all but the most difficult puzzles. a proof of convergence is presented, with some information theoretic connections. a random generalization of the sudoku puzzle is presented, for which the sinkhorn-based solver is also very effective.
on optimal quasi-orthogonal space-time block codes with minimum decoding complexity. orthogonal space-time block codes (ostbc) from orthogonal designs have both advantages of complex symbolwise maximum-likelihood (ml) decoding and full diversity. however, their symbol rates are upper bounded by 3/4 for more than two antennas for complex symbols. to increase the symbol rates, they have been generalized to quasi-orthogonal space-time block codes (qostbc) in the literature but the diversity order is reduced by half and the complex symbol-wise ml decoding is significantly increased to complex symbol pair-wise (pair of complex symbols) ml decoding. the qostbc has been modified by rotating half of the complex symbols for achieving the full diversity while maintaining the complex symbol pair-wise ml decoding. the optimal rotation angles for any signal constellation of any finite symbols located on both square lattices and equal-literal triangular lattices have been found by su-xia, where the optimality means the optimal diversity product (or product distance). qostbc has also been modified by yuen-guan-tjhung by rotating information symbols in another way such that it has full diversity and in the meantime it has real symbol pair-wise ml decoding (the same complexity as complex symbol-wise decoding) and the optimal rotation angle for square and rectangular qam constellations has been found. in this paper, we systematically study general linear transformations of information symbols for qostbc to have both full diversity and real symbol pair-wise ml decoding. we present the optimal transformation matrices (among all possible linear transformations not necessarily symbol rotations) of information symbols for qostbc with real symbol pair-wise ml decoding such that the optimal diversity product is achieved for both general square qam and general rectangular qam signal constellations. furthermore, our newly proposed optimal linear transformations for qostbc also work for general qam constellations in the sense that qostbc have full diversity with good diversity product property and real symbol pair-wise ml decoding. interestingly, the optimal diversity products for square qam constellations from the optimal linear transformations of information symbols found in this paper coincide with the ones presented by yuen-guan-tjhung by using their optimal rotations. however, the optimal diversity products for (nonsquare) rectangular qam constellations from the optimal linear transformations of information symbols found in this paper are better than the ones presented byyuen-guan-tjhung by using their optimal rotations. in this paper, we also present the optimal transformations for the co-ordinate interleaved orthogonal designs (ciod) proposed by khan-rajan for rectangular qam constellations.
construction methods for asymmetric and multiblock space-time codes. in this paper, the need for the construction of asymmetric and multiblock space-time codes is discussed. above the trivial puncturing method, i.e., switching off the extra layers in the symmetric multiple-input multiple-output (mimo) setting, two more sophisticated asymmetric construction methods are proposed. the first method, called the block diagonal method (bdm), can be converted to produce multiblock space-time codes that achieve the diversity-multiplexing tradeoff (dmt). it is also shown that maximizing the density of the newly proposed block diagonal asymmetric space-time (ast) codes is equivalent to minimizing the discriminant of a certain order, a result that also holds as such for the multiblock codes. an implicit lower bound for the density is provided and made explicit for an important special case that contains e.g., the systems equipped with 4tx +2rx antennas. further, an explicit scheme achieving the bound is given. another method proposed here is the smart puncturing method (spm) that generalizes the subfield construction method proposed in earlier work by hollanti and ranto and applies to any number of transmitting and lesser receiving antennas. the use of the general methods is demonstrated by building explicit, sphere decodable codes using different cyclic division algebras (cdas). computer simulations verify that the newly proposed methods can compete with the trivial puncturing method, and in some cases clearly outperform it. the conquering construction exploiting maximal orders improves upon the punctured perfect code and the djabba code as well as the icosian code. also extensive dmt analysis is provided.
reed-solomon and simplex codes for peak-to-average power ratio reduction in ofdm. new schemes for peak-to-average power ratio reduction in orthogonal frequency-division multiplexing (ofdm) systems are proposed. reed-solomon (rs) and simplex codes are employed to create a number of candidates, from which the best are selected. thereby, in contrast to existing approaches, the codes are arranged over a number of ofdm frames rather than over the carriers, hence a combination of the principles of multiple signal representation with selection (as done in selected mapping) and the use of channel coding is present. in particular, in multiple-antenna transmission, the proposed schemes do not cause any additional delay, but due to the utilization of the dimension space, additional gains can be achieved. moreover, the schemes are very flexible; due to the selection step, any criterion of optimality can be taken into account. besides multiple-antenna transmission, packet transmission is briefly considered, which, moreover, covers the appealing similarities with incremental redundancy check schemes in automatic repeat request (arq) applications and with decoding of codes transmitted over the erasure channel. the performance of the schemes is (using some approximations) derived analytically and is covered by numerical results that are in very good agreement with the theory. significant gains can be achieved with these very flexible and versatile methods.
performance bounds for nonbinary linear block codes over memoryless symmetric channels. the performance of nonbinary linear block codes is studied in this paper via the derivation of new upper bounds on the block error probability under maximum-likelihood (ml) decoding. the transmission of these codes is assumed to take place over a memoryless and symmetric channel. the new bounds, which are based on the gallager bounds and their variations, are applied to the gallager ensembles of nonbinary and regular low-density parity-check (ldpc) codes. these upper bounds are also compared with sphere-packing lower bounds. this study indicates that the new upper bounds are useful for the performance evaluation of coded communication systems which incorporate nonbinary coding techniques.
authentication over noisy channels. an authentication counterpart of wyner's study of the wiretap channel is developed in this work. more specifically, message authentication over noisy channels is studied while impersonation and substitution attacks are investigated for both single-and multiple-message scenarios. for each scenario, information-theoretic lower and upper bounds on the opponent's success, or cheating, probability are derived. remarkably, in both scenarios, the lower and upper bounds are shown to match, and hence, the fundamental limits on message authentication over noisy channels are fully characterized. the opponent's success probability is further shown to be smaller than that derived in the classical noiseless channel model. these results rely on a novel authentication scheme in which shared key information is used to provide simultaneous protection against both types of attacks. finally, message authentication for the case in which the source and receiver possess only correlated sequences is studied.
density evolution for nonbinary ldpc codes under gaussian approximation. this paper extends the work on density evolution for binary low-density parity-check (ldpc) codes with gaussian approximation to ldpc codes over gf (q). we first generalize the definition of channel symmetry for nonbinary inputs to include q-ary phase-shift keying (psk) modulated channels for prime q and binary-modulated channels for q that is a power of 2. for the well-defined q-ary-input symmetric-output channel, we prove that under the gaussian assumption, the density distribution for messages undergoing decoding is fully characterized by (q - 1) quantities. assuming uniform edge weights, we further show that the density of messages computed by the check node decoder (cnd) is fully defined by a single number. we then present the approximate density evolution for regular and irregular ldpc codes, and show that the (q - 1)-dimensional integration involved can be simplified using a dimensionality reduction algorithm for the important case of q = 2p. through application of approximate density evolution and linear programming, we optimize the degree distribution of ldpc codes over gf(3) and gf(4). the optimized irregular ldpc codes demonstrate performance close to the shannon capacity for long codewords. we also design gf (q) codes for high-order modulation by using the idea of a channel adapter. we find that codes designed in this fashion outperform those optimized specifically for the binary additive white gaussian noise (awgn) channel for a short codewords and a spectral efficiency of 2 bits per channel use (b/cu).
adaptive alternating minimization algorithms. the classical alternating minimization (or projection) algorithm has been successful in the context of solving optimization problems over two variables. the iterative nature and simplicity of the algorithm has led to its application in many areas such as signal processing, information theory, control, and finance. a general set of sufficient conditions for the convergence and correctness of the algorithm are known when the underlying problem parameters are fixed. in many practical situations, however, the underlying problem parameters are changing over time, and the use of an adaptive algorithm is more appropriate. in this paper, we study such an adaptive version of the alternating minimization algorithm. more precisely, we consider the impact of having a slowly time-varying domain over which the minimization takes place. as a main result of this paper, we provide a general set of sufficient conditions for the convergence and correctness of the adaptive algorithm. perhaps somewhat surprisingly, these conditions seem to be the minimal ones one would expect in such an adaptive setting. we present applications of our results to adaptive decomposition of mixtures, adaptive log-optimal portfolio selection, and adaptive filter design.
the weight distribution of some irreducible cyclic codes. irreducible cyclic codes have been an interesting subject of study for a long time. their weight distribution is known in only a few cases. in this paper, the weight distribution of the irreducible cyclic codes in a number of other cases is determined. the number of nonzero weights in the codes dealt with in this paper varies between one and four.
distinguishability of quantum states by separable operations. in this paper, we study the distinguishability of multipartite quantum states by separable operations. we first present a necessary and sufficient condition for a finite set of orthogonal quantum states to be distinguishable by separable operations. an analytical version of this condition is derived for the case of (d - 1) pure states, where d is the total dimension of the state space under consideration. a number of interesting consequences of this result are then carefully investigated. remarkably, we show there exists a large class of 2 ⊗ 2 separable operations not being realizable by local operations and classical communication. before our work, only a class of 3 ⊗ 3 nonlocal separable operations was known [bennett et al., phys. rev. a 59, 1070 (1999)]. we also show that any basis of the orthogonal complement of a multipartite pure state is indistinguishable by separable operations if and only if this state cannot be a superposition of one or two orthogonal product states, i.e., has an orthogonal schmidt number not less than three, thus generalize the recent work about indistinguishable bipartite subspaces [watrous, phys. rev. lett. 95, 080505 (2005)]. notably, we obtain an explicit construction of indistinguishable subspaces of dimension 7 (or 6) by considering a composite quantum system consisting of two qutrits (resp., three qubits), which is slightly better than the previously known indistinguishable bipartite subspace with dimension 8.
improvements on parameters of algebraic-geometry codes from hermitian curves. using the vladut-xing method, we refine a construction of xu to improve the parameters of algebraic-geometry codes based on hermitian curves. the parameters of these hermitian codes are arbitrarily close to the singleton bound, provided that the length of the code is sufficiently large. we also exhibit a class of hermitian codes over any finite field fq2(q > 2) with good parameters.
a note on limited-trial chase-like algorithms achieving bounded-distance decoding. for the decoding of a binary linear block code of minimal hamming distance d over additive white gaussian noise (awgn) channels, a soft-decision decoder achieves bounded-distance (bd) decoding if its squared error-correction radius is equal to d. a chase-like algorithm outputs the best (most likely) codeword in a list of candidates generated by a conventional algebraic binary decoder in a few trials. it is of interest to design chase-like algorithms that achieve bd decoding with as least trials as possible. in this paper, we show that chase-like algorithms can achieve bd decoding with only o(d1/2+ε trials for any given positive number ε.
error-correction of multidimensional bursts. we present several methods and constructions to generate binary codes for correction of a multidimensional cluster-error, whose shape can be a box-error, a lee sphere error, or an error with an arbitrary shape. our codes have very low redundancy, close to optimal, and a large range of parameters of arrays and clusters. our main results are summarized as follows. 1) a construction of two-dimensional codes capable to correct a rectangular-error with considerably more flexible parameters from previously known constructions. this construction is easily generalized for d dimensions. 2) a novel method based on d colorings of the d-dimensional space for constructing d-dimensional codes correcting a d-dimensional cluster-error of various shapes. 3) a transformation of the d-dimensional space into another d-dimensional space in a way that a d-dimensional lee sphere is transformed into a shape located in a d-dimensional box of a relatively small size. 4) applying the coloring method to correct more efficiently a two-dimensional error whose shape is a lee sphere. 5) a construction of d-dimensional codes capable to correct a d-dimensional cluster-error of size b in which the number of erroneous positions is relatively small compared to b. 6) we present a code which corrects a d-dimensional arbitrary cluster-error with relatively small redundancy.
capacity of a multiple-antenna fading channel with a quantized precoding matrix. given a multiple-input multiple-output (mimo) channel, feedback from the receiver can be used to specify a transmit precoding matrix, which selectively activates the strongest channel modes. here we analyze the performance of random vector quantization (rvq), in which the precoding matrix is selected from a random codebook containing independent, isotropically distributed entries.we assume that channel elements are independent and identically distributed (i.i.d.) and known to the receiver, which relays the optimal (rate-maximizing) precoder codebook index to the transmitter using b bits.we first derive the large system capacity of beamforming (rank-one precoding matrix) as a function of b, where large system refers to the limit as b and the number of transmit and receive antennas all go to infinity with fixed ratios. rvq for beamforming is asymptotically optimal, i.e., no other quantization scheme can achieve a larger asymptotic rate.we subsequently consider a precoding matrix with arbitrary rank, and approximate the asymptotic rvq performance with optimal and linear receivers (matched filter and minimum mean squared error (mmse)). numerical examples show that these approximations accurately predict the performance of finite-size systems of interest. given a target spectral efficiency, numerical examples show that the amount of feedback required by the linear mmse receiver is only slightly more than that required by the optimal receiver, whereas the matched filter can require significantly more feedback.
diversity-multiplexing tradeoff in isi channels. the optimal diversity-multiplexing tradeoff curve for the intersymbol interference (isi) channel is computed and various equalizers are analyzed using this performance metric. maximum-likelihood signal decoding (mlsd) and decision feedback equalization (dfe) equalizers achieve the optimal tradeoff without coding, but zero forcing (zf) and minimum mean-square-error (mmse) equalizers do not. however if each transmission block is ended with a period of silence lasting the coherence time of the channel, both zf and mmse equalizers become diversity-multiplexing optimal. this suggests that the bulk of the performance gain obtained by replacing linear decoders with computationally intensive ones such as orthogonal frequency-division multiplexing (ofdm) or viterbi, can be realized in much simpler fashion-with a small modification to the transmit scheme.
optimization of information rate upper and lower bounds for channels with memory. we consider the problem of minimizing upper bounds and maximizing lower bounds on information rates of stationary and ergodic discrete-time channels with memory. the channels we consider can have a finite number of states, such as partial response channels, or they can have an infinite state space, such as time-varying fading channels. we optimize recently proposed information rate bounds for such channels, which make use of auxiliary finite-state machine channels (fsmcs). our main contribution in this paper is to provide iterative expectation-maximization (em) type algorithms to optimize the parameters of the auxiliary fsmc to tighten these bounds. we provide an explicit, iterative algorithm that improves the upper bound at each iteration. we also provide an effective method for iteratively optimizing the lower bound. to demonstrate the effectiveness of our algorithms, we provide several examples of partial response and fading channels where the proposed optimization techniques significantly tighten the initial upper and lower bounds. finally, we compare our results with results obtained by the conjugate gradient optimization algorithm and an improved variation of the simplex algorithm, called soblex. while the computational complexities of our algorithms are similar to the conjugate gradient method and less than the soblex algorithm, our algorithms robustly find the tightest bounds. interestingly, from a channel coding/decoding perspective, optimizing the lower bound is related to increasing the achievable mismatched information rate, i.e., the information rate of a communication system where the decoder at the receiver is matched to the auxiliary channel, and not to the original channel.
capacity of steganographic channels. this work investigates a central problem in steganography, that is: how much data can safely be hidden without being detected? to answer this question, a formal definition of steganographic capacity is presented. once this has been defined, a general formula for the capacity is developed. the formula is applicable to a very broad spectrum of channels due to the use of an information-spectrum approach. this approach allows for the analysis of arbitrary steganalyzers as well as nonstationary, nonergodic encoder and attack channels. after the general formula is presented, various simplifications are applied to gain insight into example hiding and detection methodologies. finally, the context and applications of the work are summarized in a general discussion.
optimal frequency hopping sequences: auto- and cross-correlation properties. frequency hopping (fh) sequences play a key role in frequency hopping spread spectrum communication systems. in order to evaluate the performance of fh sequences, lempel and greenberger (1974) and peng and fan (2004) derived lower bounds on their hamming auto- and cross-correlations. in this paper, we construct families of fh sequences with hamming correlations meeting those bounds by combinatorial and algebraic techniques. we first construct optimal families consisting of a single fh sequence with maximum hamming correlation equal to 2 from a combinatorial approach. then we investigate families consisting of multiple fh sequences. we provide a combinatorial characterization for such families, and present a recursive method to construct them by means of this characterization. we also describe two algebraic constructions for such families of fh sequences, generalizing those of ding, moisio, and yuan (2007). as a consequence, many new optimal families of fh sequences are obtained.
parity forwarding for multiple-relay networks. this paper proposes a relaying strategy for the multiple-relay network in which each relay decodes a selection of transmitted messages by other transmitting terminals, and forwards parities of the decoded codewords. this protocol improves the previously known achievable rate of the decode-and-forward (df) strategy for multirelay networks by allowing relays to decode only a selection of messages from relays with strong links to it. hence, each relay may have several choices as to which messages to decode, and for a given network many different parity forwarding protocols may exist. a tree structure is devised to characterize a class of parity forwarding protocols for an arbitrary multirelay network. based on this tree structure, closed-form expressions for the achievable rates of these df schemes are derived. it is shown that parity forwarding is capacity achieving for new forms of degraded relay networks.
reliable communication in the absence of a common clock. we introduce the continuous time asynchronous channel as a model for time jitter in a communication system with no common clock between the transmitter and the receiver. we have obtained a simple characterization for an optimal zero-error self-synchronizable code for the asynchronous channel. the capacity of this channel is determined by both a combinatorial approach and a probabilistic approach. our results unveil the somewhat surprising fact that it is not necessary for the receiver clock to resynchronize with the transmitter clock within a fixed maximum time in order to achieve reliable communication. this means that no upper limit should be imposed on the run lengths of the self-synchronization code as in the case of run-length limited (rll) codes which are commonly used in magnetic recording.
a family of m -sequences with five-valued cross correlation. finding the cross correlation between two m-sequences {st} and {sdt} of the same period 2m - 1, that differ by a decimation d, has been a popular research problem since the 1960s. many cases with three- and four-valued correlation have been determined. several values of d are known to lead to five-valued cross correlation but their exact correlation distribution has been open. the correlation distribution is completely determined for one of these families with five-valued cross correlation by using evaluations of certain exponential sums including kloosterman sums. the decimation considered is the special decimation d = 22k+1/2k+1 where m is odd and k = 1, i.e., d = 5/3. the paper introduces some techniques that may be useful to obtain further results on related decimations.
the minimum distance of turbo-like codes. worst-case upper bounds are derived on the minimum distance of parallel concatenated turbo codes, serially concatenated convolutional codes, repeat-accumulate codes, repeat-convolute codes, and generalizations of these codes obtained by allowing nonlinear and large-memory constituent codes. it is shown that parallel-concatenated turbo codes and repeat-convolute codes with sub-linear memory are asymptotically bad. it is also shown that depth-two serially concatenated codes with constant-memory outer codes and sublinear-memory inner codes are asymptotically bad. most of these upper bounds hold even when the convolutional encoders are replaced by general finite-state automata encoders. in contrast, it is proven that depth-three serially concatenated codes obtained by concatenating a repetition code with two accumulator codes through random permutations can be asymptotically good.
recursive constructions of detecting matrices for multiuser coding: a unifying approach. detecting matrices are a class of combinatorial objects originated from the coin weighing problem of söderberg and shapiro in the early 1960s. in this paper, various known recursive construction techniques for binary, bipolar, and ternary detecting matrices are reexamined in a unifying framework. new, general recursive constructions of detecting matrices, which include previous recursive constructions as special cases, are derived. such matrices find applications in multiuser coding since they are equivalent to a certain class of uniquely decodable multiuser codes for the binary adder channel. interestingly, it is found that among the three kinds of detecting matrices, ternary detecting matrices are of fundamental significance from the combinatorial theoretic, as well as from the multiuser coding application, point of view.
a new outer bound and the noisy-interference sum-rate capacity for gaussian interference channels. a new outer bound on the capacity region of gaussian interference channels is developed. the bound combines and improves existing genie-aided methods and is shown to give the sum-rate capacity for noisy interference as defined in this paper. specifically, it is shown that if the channel crosstalk coefficient magnitudes lie below thresholds defined by the power constraints then single-user detection at each receiver is sum-rate optimal, i. treating the interference as noise incurs no loss in performance. this is the first capacity result for the gaussian interference channel with weak to moderate interference. furthermore, for certain mixed (weak and strong) interference scenarios, the new outer bounds give a corner point of the capacity region.
the capacity region of a class of semideterministic interference channels. the capacity region of a class of discrete memoryless interference channels with common information is established. the setup is similar to the class of deterministic interference channels without common information studied by el gamal and costa, which was later extended to the class of deterministic interference channels with common information. in this paper, certain conditions that were originally imposed by el gamal and costa are relaxed and it is shown, by a specific example, that this new class of interference channels is strictly larger than the class of deterministic interference channels previously studied. in fact, the result of this paper is obtained by combining the class of deterministic interference channels with the class of discrete memoryless interference channels with strong interference. hence, it also includes the capacity region of the class of discrete memoryless interference channels with strong interference as a special case.
high-snr analysis of outage-limited communications with bursty and delay-limited information. this work analyzes the high-snr asymptotic error performance of outage-limited communications with fading, where the number of bits that arrive at the transmitter during any timeslot is random but the delivery of bits at the receiver must adhere to a strict delay limitation. specifically, bit errors are caused by erroneous decoding at the receiver or violation the strict delay constraint. under certain scaling of the statistics of the bit-arrival process with snr, this paper shows that the optimal decay behavior of the asymptotic total probability of bit error depends on how fast the burstiness of the source scales down with snr. if the source burstiness scales down too slowly, the total probability of error is asymptotically dominated by delay-violation events. on the other hand, if the source burstiness scales down too quickly, the total probability of error is asymptotically dominated by channel-error events. however, at the proper scaling, where the burstiness scales linearly with 1/√log snr and at the optimal coding duration and transmission rate, the occurrences of channel errors and delay-violation errors are asymptotically balanced. in this latter case, the optimal exponent of the total probability of error reveals a tradeoff that addresses the question of how much of the allowable time and rate should be used for gaining reliability over the channel and how much for accommodating the burstiness with delay constraints.
short additive quaternary codes. in this paper, the best parameters of quaternary additive codes of small length are determined using the geometric description. only one open question remains for length ≤ 13. among the results obtained in this work are the nonexistence of [12, 7, 5]-codes and [12, 4.5, 7]-codes as well as the existence of a [13, 7.5, 5]-code.
generally explicit space-time codes with nonvanishing determinants for arbitrary numbers of transmit antennas. nonvanishing determinants have emerged as an attractive criterion enabling a space-time code achieve the optimal diversity-multiplexing gains tradeoff. it seems that cyclic division algebras play the most crucial role in designing a space-time code with nonvanishing determinants. in this paper, we explicitly construct space-time codes for arbitrary numbers of transmit antennas that achieve nonvanishing determinants and the optimal diversity-multiplexing gains tradeoff over z[i]. unlike previous methods usually arising a field compositum for two or more fields, our scheme, which only requires one simple extension, constitutes a much more efficient and feasible advancement whether in theory or practice.
on the cusick-cheon conjecture about balanced boolean functions in the cosets of the binary reed-muller code. in this paper, an amplification of the cusick-cheon conjecture on balanced boolean functions in the cosets of the binary reed-muller code rm(k,m) of order k and length 2m, in the cases where k = 1 or k ≥ (m-1)/2, is proved.
detection of gauss-markov random fields with nearest-neighbor dependency. the problem of hypothesis testing against independence for a gauss-markov random field (gmrf) is analyzed. assuming an acyclic dependency graph, an expression for the log-likelihood ratio of detection is derived. assuming random placement of nodes over a large region according to the poisson or uniform distribution and nearest-neighbor dependency graph, the error exponent of the neyman-pearson detector is derived using large-deviations theory. the error exponent is expressed as a dependency-graph functional and the limit is evaluated through a special law of large numbers for stabilizing graph functionals. the exponent is analyzed for different values of the variance ratio and correlation. it is found that a more correlated gmrf has higher exponent at low values of the variance ratio whereas the situation is reversed at high values of the variance ratio.
two new families of optimal binary sequences obtained from quaternary sequences. in this paper, we present two optimal binary families of sequences of length 2n - 1 and 2(2n - 1) for odd integer n. they are obtained as the images of recently proposed optimal quaternary sequences under the most significant bit and the gray maps. the first family has 2n + 1 sequences of length 2n - 1 and the identical correlation distribution to that of gold sequences and gold-like sequences, and the second family of sequences of length 2(2n - 1) has 2n sequences and the same correlation values as those of kerdock sequences.
the construction of variable length codes with good synchronization properties. variable length codes offer advantages for data compression, but are susceptible to loss of synchronization if a bit error occurs. this can be mitigated by the use of variable length codes with specific mechanisms for resynchronization. such mechanisms exist in the codes known as huffman equivalent (he) codes and t-codes. these have been extensively studied in the literature. for optimal compression a length vector is obtained from the probabilities of the symbols of the alphabet used. however, he-codes and t-codes do not exist for all length vectors. in this paper, a new class of variable length codes with good synchronization properties is developed. these are referred to as ordered termination (ot) codes. ot-codes do exist for all length vectors. experimental results and some theoretical support suggest that ot-codes compare favorably with he- and t-codes.
secrecy capacity region of a multiple-antenna gaussian broadcast channel with confidential messages. wireless communication is particularly susceptible to eavesdropping due to its broadcast nature. security and privacy systems have become critical for wireless providers and enterprise networks. this paper considers the problem of secret communication over the gaussian broadcast channel, where a multiple-antenna transmitter wishes to send independent confidential messages to two users with information-theoretic secrecy. that is, each user would like to obtain its own confidential message in a reliable and safe manner. this communication model is referred to as the multiple-antenna gaussian broadcast channel with confidential messages (mgbc-cm). under this communication scenario, a secret dirty-paper coding scheme and the corresponding achievable secrecy rate region are first developed based on gaussian codebooks. next, a computable sato-type outer bound on the secrecy capacity region is provided for the mgbc-cm. furthermore, the sato-type outer bound proves to be consistent with the boundary of the secret dirty-paper coding achievable rate region, and hence, the secrecy capacity region of the mgbc-cm is established. finally, two numerical examples demonstrate that both users can achieve positive rates simultaneously under the information-theoretic secrecy requirement.
code rate-diversity-multiplexing tradeoff. multiple antenna systems can be used to increase system reliability or to increase system capacity. initially, space-time codes were designed to achieve one of these two types of gain. recently, though, a tradeoff between these two system resources has been characterized by the diversity-multiplexing tradeoff. achieving this optimal performance frontier requires proper coding. for diversity optimality, the signal transmitted from each antenna must redundantly describe the message bits. this redundancy has been quantified by the rate of a space-time code, which relates space-time codebook size to constituent single-input-single-output (siso) constellation size. achievable diversity has also been shown to decrease with increasing rates, which establishes the diversity-rate tradeoff. in this work, we consider a generalized notion of the rate of the space-time code, which we refer to as the code rate rc, and the associated diversity-code rate tradeoff. we then generalize the diversity-multiplexing and diversity-code rate tradeoffs and find that a new diversity-multiplexing tradeoff exists as a function of the code rate.
general paradigm for distilling classical key from quantum states. in this paper, we develop a formalism for distilling a classical key from a quantum state in a systematic way, expanding on our previous work on a secure key from bound entanglement (horodecki et. al., 2005). more detailed proofs, discussion, and examples are provided of the main results. namely, we demonstrate that all quantum cryptographic protocols can be recast in a way which looks like entanglement theory, with the only change being that instead of distilling einstein-podolsky-rosen (epr) pairs, the parties distill private states. the form of these general private states are given, and we show that there are a number of useful ways of expressing them. some of the private states can be approximated by certain states, which are bound entangled. thus, distillable entanglement is not a requirement for a private key. we find that such bound entangled states are useful for a cryptographic primitive we call a controlled private quantum channel (pqc). we also find a general class of states, which have negative partial transpose (are npt), but which appear to be bound entangled. the relative entropy distance is shown to be an upper bound on the rate of a key. this allows us to compute the exact value of a distillable key for a certain class of private states.
computing partial walsh transform from the algebraic normal form of a boolean function. we study the relationship between the walsh transform and the algebraic normal form (anf) of a boolean function. in the first part of the paper, we obtain a formula for the walsh transform at a certain point in terms of parameters derived from the algebraic normal form. we use previous results by carlet and guillot to obtain an explicit expression for thewalsh transform at a point in terms of parameters derived from the anf. the second part of the paper is devoted to simplify this formula and develop an algorithm to evaluate it. this algorithm can be applied in situations where it is practically impossible to use the fastwalsh transform algorithm. experimental results show that under certain conditions it is possible to execute our algorithm to evaluate thewalsh transform (at a small set of points) of functions on a few scores of variables having a few hundred terms in the algebraic normal form.
exact characterization of the minimax loss in error exponents of universal decoders. universally achievable error exponents pertaining to certain families of channels (most notably, discrete memoryless channels (dmcs) and various ensembles of random codes, are studied by combining the competitive minimax approach, proposed by feder and merhav, with chernoff bound and gallager's techniques for the analysis of error exponents. in particular, we derive a single-letter expression for the largest, universally achievable fraction ξ of the optimum error exponent pertaining to the optimum maximum-likelihood (ml) decoding. moreover, a simpler single-letter expression for a lower bound to ξ is presented. to demonstrate the tightness of this lower bound, we use it to show that ξ = 1, for the binary symmetric channel (bsc), when the random coding distribution is uniform over: i) all codes (of a given rate), and ii) all linear codes, in agreement with well-known results. we also show that ξ =1 for the uniform ensemble of systematic linear codes, and for that of time-varying convolutional codes in the bit-error-rate sense. for the latter case, we also derive the corresponding universal decoder explicitly and show how it can be efficiently implemented using a slightly modified version of the viterbi algorithm which employs two trellises.
the trapping redundancy of linear block codes. we generalize the notion of the stopping redundancy in order to study the smallest size of a trapping set in tanner graphs of linear block codes. in this context, we introduce the notion of the trapping redundancy of a code, which quantifies the relationship between the number of redundant rows in any parity-check matrix of a given code and the size of its smallest trapping set. trapping sets with certain parameter sizes are known to cause error-floors in the performance curves of iterative belief propagation (bp) decoders, and it is therefore important to identify decoding matrices that avoid such sets. bounds on the trapping redundancy are obtained using probabilistic and constructive methods, and the analysis covers both general and elementary trapping sets. numerical values for these bounds are computed for the [2640,1320] margulis code and the class of projective geometry codes, and compared with some new code-specific trapping set size estimates.
new results on multiple descriptions in the wyner-ziv setting. some new results of multiple descriptions in the wyner-ziv setting (mdwz) are presented. mdwz uses two pieces of side information (si) for two different side decoders. both si are available to the central decoder, but none to the encoder. the complete achievable region for a quadratic gaussian mdwz system is derived. this result is an extension of ozarow's result on multiple descriptions of a gaussian source without si and diggavi-vaishampayan's result on common si. it is shown that a refinement layer for the central decoder is indispensable if the central distortion is sufficiently small. the tight rate distortion region is also given if one of the side decoders is required to perfectly reconstruct a deterministic function of the source.
approximation of the two-part mdl code. approximation of the optimal two-part minimum description length (mdl) code for given data, through successive monotonically length-decreasing two-part mdl codes, has the following properties: i) computation of each step may take arbitrarily long; ii) we may not know when we reach the optimum, or whether we will reach the optimum at all; iii) the sequence of models generated may not monotonically improve the goodness of fit; but iv) the model associated with the optimum has (almost) the best goodness of fit. to express the practically interesting goodness of fit of individual models for individual data sets we have to rely on kolmogorov complexity.
an elementary condition for non-norm elements. cyclic division algebra (cda) has recently become a major technique to construct space-time block codes with nonvanishing determinant (nvd). one of the key steps in this technique is the determination of non-norm elements and a sufficient condition for the determination has been given by kiran and rajan lately based on algebraic number theory. in this paper, based on kiran and rajan's condition, we present a more elementary condition for non-norm elements when signals are qam or hex, which is easier to check. with this elementary condition, non-norm elements with smaller absolute values than the existing ones can be found.
representation and compression of multidimensional piecewise functions using surflets. we study the representation, approximation, and compression of functions in m dimensions that consist of constant or smooth regions separated by smooth (m - 1)-dimensional discontinuities. examples include images containing edges, video sequences of moving objects, and seismic data containing geological horizons. for both function classes, we derive the optimal asymptotic approximation and compression rates based on kolmogorov metric entropy. for piecewise constant functions, we develop a multiresolution predictive coder that achieves the optimal rate-distortion performance; for piecewise smooth functions, our coder has near-optimal rate-distortion performance. our coder for piecewise constant functions employs surflets, a new multiscale geometric tiling consisting of m-dimensional piecewise constant atoms containing polynomial discontinuities. our coder for piecewise smooth functions uses surfprints, which wed surflets to wavelets for piecewise smooth approximation. both of these schemes achieve the optimal asymptotic approximation performance. key features of our algorithms are that they carefully control the potential growth in surflet parameters at higher smoothness and do not require explicit estimation of the discontinuity. we also extend our results to the corresponding discrete function spaces for sampled data. we provide asymptotic performance results for both discrete function spaces and relate this asymptotic performance to the sampling rate and smoothness orders of the underlying functions and discontinuities. for approximation of discrete data, we propose a new scale-adaptive dictionary that contains few elements at coarse and fine scales, but many elements at medium scales. simulation results on synthetic signals provide a comparison between surflet-based coders and previously studied approximation schemes based on wedgelets and wavelets.
analysis of optimal high resolution and fixed rate scalar quantization. in 2001, hui and neuhoff proposed a uniform quantizer with overload for the quantization of scalar signals and derived the asymptotically optimal size of the quantization bins in the high-bitrate limit. the purpose of the present paper is to prove a quantitatively more precise version of this result which, at the same time, is valid for a more general, quite natural class of probability distributions that requires only little regularity and includes, for instance, positive lipschitz-continuous functions of unit integral.
hybrid digital-analog relaying for cooperative transmission over slow fading channels. hybrid digital-analog coding schemes have been proposed in source-channel coding to increase the robustness toward channel mismatch, in the absence of transmitter channel state information (csit). recognizing that the same kind of robustness is needed at the relay in a three-node relay network, we propose several novel relaying protocols based on hybrid digital-analog transmission. we compare the performance of the new schemes with traditional digital-only (decode-and-forward or compress-and-forward) or analog-only (amplify-and-forward) relaying, as well as to performance bounds corresponding to genie-aided compress-and-forward relaying. our new protocols achieve significant gains in terms of achievable expected rates, and they are able to close in on the performance bounds. in particular, we conclude that the best overall performance is obtained by an adaptive combination of decode-and-forward and hybrid digital-analog relaying.
sampling and ergodic theorems for weakly almost periodic signals. the theory of abstract harmonic analysis on commutative groups is used to prove sampling and ergodic theorems concerning a particular class of finite-power signals, which are known as weakly almost periodic. the analysis brings to light some noteworthy differences between finite-energy and finite-power signal sampling. it is shown that the bandwidth of the fourier transform of a weakly almost periodic signal is generally larger than the bandwidth of the power spectrum of the signal. consequently, the signal power spectrum by itself does not generally provide enough information to determine the value of the time-domain nyquist rate, that is, the minimum sampling rate necessary for exact signal reconstruction in the time-domain. on the other hand, it is also shown that the minimum sampling rate needed to obtain alias-free spectral estimates is determined by the bandwidth of the power spectrum and, consequently, may be lower than the time-domain nyquist rate. finally, the sampling and ergodic theorems established in this paper are used in an analysis of averaged periodogram estimates of the power spectrum of a weakly almost periodic signal. it is shown that the value of the time shift between consecutive windows may contribute to the asymptotic bias of the estimates.
testing for image symmetries - with application to confocal microscopy. statistical tests are introduced for checking whether an image function f (x, y) defined on the unit disc d = {(x, y) : x2 + y2 ≤ 1} is invariant under certain symmetry transformations of d, given that discrete and noisy data are observed. invariance under reflections or under rotations by rational angles is considered, as well as rotational invariance. these symmetry relations can be naturally expressed as restrictions for the zernike moments of f (x, y). therefore, the test statistics are based on the l2 distance between zernike series estimates of the image function itself and its version obtained after applying the symmetry transformation. the asymptotic distribution of the test statistics under both the hypothesis of symmetry as well as under fixed alternatives is derived. furthermore, the quality of the asymptotic approximations via simulation studies is investigated. the usefulness of our theory is verified by examining an important problem in confocal microscopy, i.e., possible imprecise alignments in the optical path of the microscope are investigated. for optical systems with rotational symmetry, the theoretical point-spread function (psf) is reflection symmetric with respect to two orthogonal axes, and rotationally invariant if the detector plane matches the optical plane of the microscope. the tests are used to investigate whether the required symmetries can indeed be detected in the empirical psf.
a two-stage capacity-achieving demodulation/decoding method for random matrix channels. iterative processing for linear matrix channels, aka turbo equalization, turbo demodulation, or turbo code-division multiple access (cdma), has traditionally been addressed as the concatenation of conventional error control codes with the linear (matrix) channel. however, in several situations, such as cdma, multiple-input-multiple-output (mimo) channels, orthogonal frequency-division multiplexing (ofdm), and intersymbol-interference (isi) channels, the channel itself either contains inherent signal redundancy or such redundancy can readily be introduced at the transmitter. for such systems, iterative demodulation of the linear channel exploiting this redundancy using simple iterative cancellation demodulators, followed by conventional feedforward error control decoding, provides a low-complexity, but extremely efficient decoding alternative. this two-stage demodulator/decoder outperforms more complex turbo cdma methods for equal power modes (users). furthermore, it is shown that arbitrary numbers of modes can be supported if an unequal power distribution is adopted. these power distributions are nested, which means that additional modes can be added without disturbing an existing mode population. the main result shows that these nested power distributions enable the two-stage receiver to approach the shannon capacity of the channel to within less than one bit for any signal-to-noise ratio (snr).
relations between random coding exponents and the statistical physics of random codes. the partition function pertaining to finite-temperature decoding of a (typical) randomly chosen code is known to have three types of behavior, corresponding to three phases in the plane of rate versus temperature: the ferromagnetic phase, corresponding to correct decoding, the paramagnetic phase, of complete disorder, which is dominated by exponentially many incorrect codewords, and the glassy phase (or the condensed phase), where the system is frozen at minimum energy and dominated by subexponentially many incorrect codewords.we show that the statistical physics associated with the two latter phases are intimately related to random coding exponents. in particular, the exponent associated with the probability of correct decoding at rates above capacity is directly related to the free energy in the glassy phase, and the exponent associated with probability of error (the error exponent) at rates below capacity, is strongly related to the free energy in the paramagnetic phase. in fact, we derive alternative expressions of these exponents in terms of the corresponding free energies, and make an attempt to obtain some insights from these expressions. finally, as a side result, we also compare the phase diagram associated with a simple finite-temperature universal decoder, for discrete memoryless channels, to that of the finite-temperature decoder that is aware of the channel statistics.
space-time codes from structured lattices. we present constructions of space-time (st) codes based on lattice coset coding. first, we focus on st code constructions for the short block-length case, i.e., when the block length is equal to or slightly larger than the number of transmit antennas. we present constructions based on dense lattice packings and nested lattice (voronoi) shaping. our codes achieve the optimal diversity-multiplexing tradeoff (dmt) of quasi-static multiple-input multiple-output (mimo) fading channels for any fading statistics, and perform very well also at practical, moderate values of signal-to-noise ratios (snr). then, we extend the construction to the case of large block lengths, by using trellis coset coding. we provide constructions of trellis coded modulation (tcm) schemes that are endowed with good packing and shaping properties. both short-block and trellis constructions allow for a reduced complexity decoding algorithm based on minimum mean-squared error generalized decision feedback equalizer (mmse-gdfe) lattice decoding and a combination of this with a viterbi tcm decoder for the tcm case. beyond the interesting algebraic structure, we exhibit codes whose performance is among the state-of-the art considering codes with similar encoding/decoding complexity.
bat chirps with good properties: zak space construction of perfect polyphase sequences. previously, a discretization of the linear fm chirp of length n = kl2, l and kl ∈ z, was given and the conditions for its minimal zak space support were derived. chirps satisfying these conditions are known as finite chirps. in this work, subsets of finite chirps of length n = l2, l a prime, are examined. the investigation leads to a new, zak space construction of general polyphase sequence sets of size l - 1 with optimal auto and cross-correlation properties, known as perfect sequence sets. it is shown that perfect sequence sets are closely related to sets of finite chirps and, in particular, include the sets of zadoff-chu sequences (which are identical with subsets of finite chirps) and the sets of generalized frank sequences (which are identical with sets of modulations of finite chirps), as special cases. the entire collection of perfect sequence sets is then given by a partition of the set of perfect auto correlation sequences, obtained by right coset decomposition of the group of all permutations with respect to a certain cyclic group. the construction suggests several further generalizations that can be obtained by operating exclusively on subgroups of the permutation group.
large system spectral analysis of covariance matrix estimation. eigendecomposition of estimated covariance matrices is a basic signal processing technique arising in a number of applications, including direction-of-arrival estimation, power allocation in multiple-input/multiple-output (mimo) transmission systems, and adaptive multiuser detection. this paper uses the theory of non-crossing partitions to develop explicit asymptotic expressions for the moments of the eigenvalues of estimated covariance matrices, in the large system asymptote as the vector dimension and the dimension of signal space both increase without bound, while their ratio remains finite and nonzero. the asymptotic eigenvalue distribution is also obtained from these eigenvalue moments and the stieltjes transform, and is extended to first-order approximation in the large sample-size limit. numerical simulations are used to demonstrate that these asymptotic results provide good approximations for finite systems of moderate size.
markov random processes are neither bandlimited nor recoverable from samples or after quantization. this paper considers basic questions regarding markov random processes. it shows that continuous-time, continuous-valued, wide-sense stationary, markov processes that have absolutely continuous second-order distribution and finite second moment are not bandlimited. it also shows that continuous-time, stationary, markov processes that are continuous-valued or discrete-valued and satisfy additional mild conditions cannot be recovered from uniform sampling. further it shows that continuous-time, continuous-valued, stationary, markov processes that have absolutely continuous second-order distributions and are continuous almost surely, cannot be recovered without error after quantization. finally, it provides necessary and sufficient conditions for stationary, discrete-time, markov processes to have zero entropy rate, and relates this to information singularity.
further results on the optimality of the likelihood-ratio test for local sensor decision rules in the presence of nonideal channels. in this paper, we consider the design of local decision rules for distributed detection systems where decisions from peripheral detectors are transmitted over dependent nonideal channels. under the conditional independence assumption among multiple sensor observations, we show that the optimal detection performance can be achieved by employing likelihood-ratio quantizers (lrq) as local decision rules under both the bayesian criterion and neyman-pearson (np) criterion even for the cases where the channels between the fusion center and local sensors are dependent and noisy. this work generalizes the previous work where independence among such channels was assumed. a person-by-person optimization (pbpo) procedure to obtain the solution is presented along with an illustrative example.
capacity of cognitive interference channels with and without secrecy. like the conventional two-user interference channel, the cognitive interference channel consists of two transmitters whose signals interfere at two receivers. it is assumed that there is a common message (message 1) known to both transmitters, and an additional independent message (message 2) known only to the cognitive transmitter (transmitter 2). the cognitive receiver (receiver 2) needs to decode messages 1 and 2, while the noncognitive receiver (receiver 1) should decode only message 1. furthermore, message 2 is assumed to be a confidential message which needs to be kept as secret as possible from receiver 1, which is viewed as an eavesdropper with regard to message 2. the level of secrecy is measured by the equivocation rate. in this paper, a single-letter expression for the capacity-equivocation region of the discrete memoryless cognitive interference channel is obtained. the capacity-equivocation region for the gaussian cognitive interference channel is also obtained explicitly. moreover, particularizing the capacity-equivocation region to the case without a secrecy constraint, the capacity region for the two-user cognitive interference channel is obtained, by providing a converse theorem.
quaternary constant-amplitude codes for multicode cdma. a constant-amplitude code is a code that reduces the peak-to-average power ratio (papr) in multicode code-division multiple access (mc-cdma) systems to the favorable value 1. in this paper, quaternary constant-amplitude codes (codes over z4) of length 2m with error-correction capabilities are studied. these codes exist for every positive integer m, while binary constant-amplitude codes cannot exist if m is odd. every word of such a code corresponds to a function from the binary m-tuples to z4 having the bent property, i.e., its fourier transform has magnitudes 2m/2. several constructions of such functions are presented, which are exploited in connection with algebraic codes over z4 (in particular quaternary reed-muller, kerdock, and delsarte-goethals codes) to construct families of quaternary constant-amplitude codes. mappings from binary to quaternary constant-amplitude codes are presented as well.
multigroup decodable stbcs from clifford algebras. a space-time block code (stbc) in k symbols (variables) is called a g-group decodable stbc if its maximum-likelihood (ml) decoding metric can be written as a sum of g terms, for some positive integer g greater than one, such that each term is a function of a subset of the k variables and each variable appears in only one term. in this paper, we provide a general structure of the weight matrices of multigroup decodable codes using clifford algebras. without assuming that the number of variables in each group is the same, a method of explicitly constructing the weight matrices of full-diversity, delay-optimal multigroup decodable codes is presented for arbitrary number of antennas. for the special case of 2a number of transmit antennas, we construct two subclass of2a codes: 1) a class of 2a-group decodable codes with rate a/2(a-1), which is, equivalently, a class of single-symbol decodable codes, and 2) a class of (2a-2) -group decodable codes with rate (a-1)/2(a-2), i.e., a class of double-symbol decodable codes.
codeword stabilized quantum codes. we present a unifying approach to quantum error correcting code design that encompasses additive (stabilizer) codes, as well as all known examples of nonadditive codes with good parameters. we use this framework to generate new codes with superior parameters to any previously known. in particular, we find ((10,18,3)) and ((10,20,3)) codes. we also show how to construct encoding circuits for all codes within our framework.
universal estimation of erasure entropy. erasure entropy rate differs from shannon's entropy rate in that the conditioning occurs with respect to both the past and the future, as opposed to only the past (or the future). in this paper, consistent universal algorithms for estimating erasure entropy rate are proposed based on the basic and extended context-tree weighting (ctw) algorithms. simulation results for those algorithms applied to markov sources, tree sources, and english texts are compared to those obtained by fixed-order plug-in estimators with different orders.
on the existence of (10, 2, 7, 488) resilient functions. using a heuristic search combined with some algebraic techniques, several examples for 10-variable boolean functions with nonlinearity 488, algebraic degree 7, and resiliency degree 2, were constructed. this construction affirmatively answers the open problem about the existence of such functions.
bounds and constructions of optimal (n, 4, 2, 1) optical orthogonal codes. in this paper, a tight upper bound on the maximum possible code size of (n 4, 2, 1,)-oocs and some direct and recursive constructions of optimal (n 4, 2, 1,)-oocs attaining the upper bound are given. as consequences, the following new infinite series of optimal (gn 4, 2, 1,)-oocs are obtained: i) g ∈ {1, 7, 11, 19, 23, 31, 35, 59, 71, 79, 131, 179, 191, 239, 251, 271, 311, 359, 379, 419, 431, 439, 479, 491, 499, 571, 599, 631, 659, 719, 739, 751, 839, 971} or g is a prime > 1000 and ≡ 5 (mod 8), and n = 9h 25i 49j p1 p2...pr where h ∈ {0, 1}, i and j are arbitrary nonnegative integers, and each pi is a prime ≡ 1 (mod 8); ii) g = 2g′ where g′ ∈ {1, 7, 11, 19, 23, 31, 47, 71, 127, 151, 167, 191, 263, 271, 311, 359, 367, 383, 431, 439, 463, 479, 503, 631, 647, 719, 727, 743, 823, 839, 863, 887, 911, 919, 967, 983, 991} and n = p1 p2...pr where each pi is a prime ≡ 1 (mod 4); iii) g ∈ {4, 20} and n is any positive integer prime to 30; iv) g = 8 and n = p1 p2...pr where each pi is a prime ≡ 1 (mod 4) greater than 5.
the effect of noise correlation in amplify-and-forward relay networks. in wireless relay networks, noise at the relays can be correlated possibly due to common interference or noise propagation from preceding hops. a parallel relay network with noise correlation is considered in this network. for the relay strategy of amplify and forward (af), the optimal rate maximizing relay gains when correlation knowledge is available at the relays are determined. interestingly, it is shown that, on average, noise correlation is beneficial regardless of whether the relays know the noise covariance matrix. however, the knowledge of correlation can greatly improve the performance. typically, the performance improvement from correlation knowledge increases with the relay power and the number of relays. with perfect correlation knowledge the system capable of canceling interference if the number of interferers is less than the number of relays. for a two-hop multiple-access parallel network, closed-form expressions for the maximum sum rate and the optimal relay strategy are determined. relay optimization for networks with three hops is also considered. based on the result of two-hop network with noise correlation, an iterative algorithm proposed for solving the relay optimization problem for three-hop networks.
performance analysis of contention based medium access control protocols. this paper studies the performance of contention based medium access control (mac) protocols. in particular, a simple and accurate technique for estimating the throughput of the ieee 802.11 dcf protocol is developed. the technique is based on a rigorous analysis of the markov chain that corresponds to the time evolution of the back-off processes at the contending nodes. an extension of the technique is presented to handle the case where service differentiation is provided with the use of heterogeneous protocol parameters, as, for example, in ieee 802.11e edca protocol. our results provide new insights into the operation of such protocols. the techniques developed in the paper are applicable to a wide variety of contention based mac protocols.
data synchronization with timing: the variable-rate case. this paper extends the theory of data synchronization with timing for fixed-rate codes, previously developed by the authors, to the variable-rate case. given a source code, a class of synctiming codes called variable-rate cascaded (vrc) codes is considered that "wrap around" the source code in such a way as to enable the decoder to not only resynchronize rapidly when the encoded bits are corrupted by insertion, deletion, or substitution errors, but also produce estimates of the time indices of the data symbols encoded by the source code. the estimates of the time indices are modulo-t reductions of the actual time indices, for some integer t called the timing span of the code. these sync-timing codes are analyzed on the basis of the maximum timing span achievable for a given coding rate r and permissible resynchronization delay d. it is shown that the timing span of vrc codes is upper-bounded by 2d(1-r)+o(d), and that this upper bound is achievable asymptotically in d. this exponential rate of growth of timing span with delay is the same as that found previously for certain fixed-rate sync-timing codes, e.g., (fixed-rate) cascaded codes.
asymptotic-information-lossless designs and the diversity-multiplexing tradeoff. it is known that neither the alamouti nor the v-blast scheme achieves the zheng-tse diversity-multiplexing tradeoff (dmt) of the multiple-input multiple-output (mimo) channel. with respect to the dmt curve, the alamouti scheme achieves the point corresponding to maximum diversity gain only, whereas v-blast meets only the point corresponding to maximum multiplexing gain. it is also known that d-blast achieves the optimal dmt for n transmit and n receive antennas, but only under the assumption that the leading and trailing zeros are ignored. when these zeros are taken into account, d-blast achieves the point corresponding to zero multiplexing gain, but not the point corresponding to zero diversity gain. the first scheme to achieve the dmt is the coding scheme of yao and wornell for the case of two transmit and two receive antennas. in this paper, we introduce the notion of an asymptotic-information-lossless (aill) design and obtain a necessary and sufficient condition under which a design is aill. analogous to the result that full-rank designs achieve the point corresponding to the zero multiplexing gain of the optimal dmt curve, we show aill to be a necessary and sufficient condition for a design to achieve the point on the dmt curve corresponding to zero diversity gain. we also derive a lower bound on the tradeoff achieved by designs from field extensions and show that the tradeoff is very close to the optimal tradeoff in the case of a single receive antenna. a lower bound to the tradeoff achieved by designs from division algebras is presented which indicates that these designs achieve both extreme points (corresponding to zero diversity and zero multiplexing gain) of the optimal dmt curve. finally, we present simulations results for n transmit and n receive antennas, for n = 2,3,4, which suggest that designs from division algebras are likely to have the property of being dmt achieving.
the capacity of channels with feedback. in this paper, we introduce a general framework for treating channels with memory and feedback. first, we prove a general feedback channel coding theorem based on massey's concept of directed information. second, we present coding results for markov channels. this requires determining appropriate sufficient statistics at the encoder and decoder. we give a recursive characterization of these sufficient statistics. third, a dynamic programming framework for computing the capacity of markov channels is presented. fourth, it is shown that the average cost optimality equation (acoe) can be viewed as an implicit single-letter characterization of the capacity. fifth, scenarios with simple sufficient statistics are described. sixth, error exponents for channels with feedback are presented.
on the expected codeword length per symbol of optimal prefix codes for extended sources. given a discrete memoryless source x, it is well known that the expected codeword length per symbol ln(x) of an optimal prefix code for the extended source xn converges to the source entropy as n approaches infinity. however, the sequence ln(x) need not be monotonic in n, which implies that the coding efficiency cannot be increased by simply encoding a larger block of source symbols (unless the block length is appropriately chosen). as the encoding and decoding complexity increases exponentially with the block length, from a practical perspective it is useful to know when an increase in the block length guarantees a decrease in the expected codeword length per symbol. while this paper does not provide a complete answer to that question, we give some properties of ln(x) and obtain for each n ≥ 1 and nondyadic p1n (p1 is the probability of the most likely source symbol) an integer k* for which lkn(x) < ln(x) for all k ≥ k*, implying that the coding efficiency of encoding blocks of length kn is higher than that of encoding blocks of length n for all k ≥ k*. this question is simpler in part because lkn(x) ≤ ln(x) is guaranteed for all n ≥ 1 and k ≥ 1, but our results distinguish scenarios where increasing the multiplicative factor guarantees strict improvement. these results extend and generalize those by montgomery and kumar.
information theoretic bounds for compound mimo gaussian channels. in this paper, achievable rates for compound gaussian multiple-input-multiple-output (mimo) channels are derived. two types of channels, modeled in the frequency domain, are considered when: 1) the channel frequency response matrix h belongs to a subset of h∞ normed linear space, and 2) the power spectral density (psd) matrix of the gaussian noise belongs to a subset of l1 space. the achievable rates of these two compound channels are related to the maximin of the mutual information rate. the minimum is with respect to the set of all possible h matrices or all possible psd matrices of the noise. the maximum is with respect to all possible psd matrices of the transmitted signal with bounded power. for the compound channel modeled by the set of h matrices, it is shown, under certain conditions, that the code for the worst case channel can be used for the whole class of channels. for the same model, the water-filling argument implies that the larger the set of matrices h, the smaller the bandwidth of the transmitted signal will be. for the second compound channel, the explicit relation between the maximizing psd matrix of the transmitted signal and the minimizing psd matrix of the noise is found. two psd matrices are related through a riccati equation, which is always present in kalman filtering and liner-quadratic gaussian control problems.
error event characterization on 2-d isi channels. in this paper, we analyze the distance properties of two-dimensional (2-d) intersymbol interference (isi) channels, in particular the 2-d partial response class-1 (pr1) channel which is an extension of the one-dimensional (1-d) pr1 channel. the minimum squared-euclidean distance of this channel is proved to be 4 and a complete characterization of the squared-euclidean distance 4 error events is provided. as for 1-d channels, we can construct error-state diagrams for 2-d channels to help characterize error events. we propose an efficient error event search algorithm operating on the error-state diagram that is applicable to any 2-d channel.
spectrum management for interference-limited multiuser communication systems. consider a multiuser communication system in a frequency selective environment whereby users share a common spectrum and can interfere with each other. assuming gaussian signaling and no interference cancelation, we study optimal spectrum sharing strategies for the maximization of sum-rate under separate power constraints for individual users. since the sum-rate function is nonconcave in terms of the users' power allocations, there can be multiple local maxima for the sum-rate maximization problem in general. in this paper, we show that, if the normalized crosstalk coefficients are larger than a given threshold (roughly equal to 1/2), then the optimal spectrum sharing strategy is frequency division multiple access (fdma). in case of arbitrary positive crosstalk coefficients, if each user's power budget exceeds a given threshold, then fdma is again sum-rate optimal, at least in a local sense. in addition, we show that the problem of finding the optimal fdma spectrum allocation is np-hard, implying that the general problem of maximizing sum-rate is also np-hard, even in the case of two users. we also propose several simple distributed spectrum allocation algorithms that can approximately maximize sum-rates. numerical results indicate that these algorithms are efficient and can achieve substantially larger sum-rates than the existing iterative waterfilling solutions, either in an interference-rich environment or when the users' power budgets are sufficiently high.
doubly-generalized ldpc codes: stability bound over the bec. the iterative decoding threshold of low-density parity-check (ldpc) codes over the binary erasure channel (bec) fulfills an upper bound depending only on the variable and check nodes with minimum distance 2. this bound is a consequence of the stability condition, and is here referred to as stability bound. in this paper, a stability bound over the bec is developed for doubly-generalized ldpc codes, where variable and check nodes can be generic linear block codes, assuming maximum a posteriori erasure correction at each node. it is proved that also in this generalized context the bound depends only on the variable and check component codes with minimum distance 2. a condition is also developed, namely, the derivative matching condition, under which the bound is achieved with equality. the stability bound leads to consider single parity-check codes used as variable nodes as an appealing option to overcome common problems created by generalized check nodes.
low-snr capacity of noncoherent fading channels. discrete-time rayleigh-fading single-input single-output (siso) and multiple-input multiple-output (mimo) channels are considered, with no channel state information at the transmitter or the receiver. the fading is assumed to be stationary and correlated in time, but independent from antenna to antenna. peak-power and average-power constraints are imposed on the transmit antennas. for mimo channels, these constraints are either imposed on the sum over antennas, or on each individual antenna. for siso channels and mimo channels with sum power constraints, the asymptotic capacity as the peak signal-to-noise ratio (snr) goes to zero is identified; for mimo channels with individual power constraints, this asymptotic capacity is obtained for a class of channels called transmit separable channels. the results for mimo channels with individual power constraints are carried over to siso channels with delay spread (i.e., frequency-selective fading).
nonlinear estimation for a class of systems. this paper considers nonlinear estimation problems for classes of models, and employs relative entropy to describe the uncertainty classes. two optimization problems are formulated on general banach spaces, and their solutions are sought: 1) when the transition probability between the signal to be estimated x and the measurement y or stochastic kernel is unknown, and 2) when the joint probability induced by the random variables (rvs) x,y is unknown. for both problems, the uncertainty is described by a relative entropy constraint between the unknown distribution and a fixed nominal distribution. the results include existence of the optimal measures using weak convergence techniques, and properties associated with the estimate of the true distribution. classical examples are chosen to illustrate the applicability of the results.
on fast-decodable space-time block codes. we focus on full-rate, fast-decodable space-time block codes (stbcs) for 2×2 and 4×2 multiple-input multiple-output (mimo) transmission. we first derive conditions and design criteria for reduced-complexity maximum-likelihood (ml) decodable 2×2 stbcs, and we apply them to two families of codes that were recently discovered. next, we derive a novel reduced-complexity 4×2 stbc, and show that it outperforms all previously known codes with certain constellations.
interference alignment on the deterministic channel and application to fully connected gaussian interference networks. an interference alignment example is constructed for the deterministic channel model of the k-user interference channel. the deterministic channel example is then translated into the gaussian setting, creating the first known example of a fully connected gaussian k-user interference network with single antenna nodes, real, nonzero and constant channel coefficients, and no propagation delays where the degrees of freedom outerbound is achieved. an analogy is drawn between the propagation delay based interference alignment examples and the deterministic channel model which also allows similar constructions for the two-user x channel as well.
orthogonal space-time block codes with sphere packing. orthogonal designs have received considerable attention in the development of efficient modulation and coding methods for future multi-antenna wireless communication systems due to their special properties. in this paper, we propose a class of space-time block codes constructed by combining orthogonal designs with sphere packing for an arbitrary number of transmit antennas. the structure of the orthogonal designs is exploited to guarantee full diversity, and sphere packing is used to improve the coding advantage. space-time block code construction from block-orthogonal designs is also considered: the full-diversity property is ensured by rotating the sphere packing underlying the code, and the optimal rotation angle is determined for a class of sphere packing. code design examples are provided for two and four transmit antennas and various transmission rates. the simulation results show that by jointly designing the symbols in the orthogonal designs, the performance of the block codes can be significantly increased.
achieving the empirical capacity using feedback: memoryless additive models. we address the problem of universal communications over an unknown channel with an instantaneous noiseless feedback, and show how rates corresponding to the empirical behavior of the channel can be attained, although no rate can be guaranteed in advance. first, we consider a discrete modulo-additive channel with alphabet x, where the noise sequence zn is arbitrary and unknown and may causally depend on the transmitted and received sequences and on the encoder's message, possibly in an adversarial fashion. although the classical capacity of this channel is zero, we show that rates approaching the empirical capacity |x| - hemp (zn) can be universally attained, where hemp (zn) is the empirical entropy of zn. for the more general setting, where the channel can map its input to an output in an arbitrary unknown fashion subject only to causality, we model the empirical channel actions as the modulo-addition of a realized noise sequence, and show that the same result applies if common randomness is available. the results are proved constructively, by providing a simple sequential transmission scheme approaching the empirical capacity.
on certain large random hermitian jacobi matrices with applications to wireless communications. in this paper we study the spectrum of certain large random hermitian jacobi matrices. these matrices are known to describe certain communication setups. in particular, we are interested in an uplink cellular channel which models mobile users experiencing a soft-handoff situation under joint multicell decoding. considering rather general fading statistics we provide a closed-form expression for the per-cell sum-rate of this channel in high signal-to-noise ratio (snr), when an intra-cell time-division multiple-access (tdma) protocol is employed. since the matrices of interest are tridiagonal, their eigenvectors can be considered as sequences with second-order linear recurrence. therefore, the problem is reduced to the study of the exponential growth of products of two-by-two matrices. for the case where k users are simultaneously active in each cell, we obtain a series of lower and upper bound on the high-snr power offset of the per-cell sum-rate, which are considerably tighter than previously known bounds.
distributed opportunistic scheduling for ad hoc networks with random access: an optimal stopping approach. in this paper, we study distributed opportunistic scheduling (dos) in an ad hoc network, where many links contend for the same channel using random access. in such a network, dos involves a process of joint channel probing and distributed scheduling. due to channel fading, the link condition corresponding to a successful channel probing could be either good or poor. in the latter case, further channel probing, although at the cost of additional delay, may lead to better channel conditions and hence yield higher throughput. the desired tradeoff boils down to judiciously choosing the optimal stopping rule for channel probing and distributed scheduling. in this paper, we pursue a rigorous characterization of the optimal strategies from two perspectives, namely, a network-centric perspective and a user-centric perspective. we first consider dos from a network-centric point of view, where links cooperate to maximize the overall network throughput. using optimal stopping theory, we show that the optimal scheme for dos turns out to be a pure threshold policy, where the rate threshold can be obtained by solving a fixed-point equation. we further devise iterative algorithms for computing the threshold. we also generalize the studies to take into account fairness requirements. next, we explore dos from a user-centric perspective, where each link seeks to maximize its own throughput. we treat the problem of threshold selection across different links as a noncooperative game. we explore the existence and uniqueness of the nash equilibrium, and show that the nash equilibrium can be approached by the best response strategy. since the best response strategy requires message passing from neighboring nodes, we then develop an online stochastic iterative algorithm based on local observations only, and establish its convergence to the nash equilibrium. because there is an efficiency loss at the nash equilibrium, we then study pricing-based mechanisms to mitigate the loss. our results reveal that rich physical layer/mac layer (phy/mac) diversities are available for exploitation in ad hoc networks.we believe that these initial steps open a new avenue for channel-aware distributed scheduling.
new m -ary sequence families with low correlation and large size. in this paper, we construct four m-ary sequence families from a power residue sequence of odd prime period p and its constant multiple sequences using the shift-and-add method, when m is a divisor of p - 1. we show that the maximum correlation values of the proposed sequence families are upper-bounded by 2√p+5 or 3√p+4. in addition, we prove that the linear complexity of each sequence in the proposed families is either p-1 or p-p-1/m-1. we also construct an m-ary sequence family from sidel'nikov sequences of period pm - 1. by applying the same method, when m is a divisor of pm - 1. the proposed sequence family fs has larger size than the known m-ary sidel'nikov sequence families, whereas they all have the same upper bound on the maximum correlation.
low-density graph codes that are optimal for binning and coding with side information. in this paper, we describe and analyze the source and channel coding properties of a class of sparse graphical codes based on compounding a low-density generator matrix (ldgm) code with a low-density parity-check (ldpc) code. our first pair of theorems establishes that there exist codes from this ensemble, with all degrees remaining bounded independently of block length, that are simultaneously optimal for both channel coding and source coding with binary data when encoding and decoding are performed optimally. more precisely, in the context of lossy compression, we prove that finite-degree constructions can achieve any pair (r, d) on the rate-distortion curve of the binary symmetric source. in the context of channel coding, we prove that the same finite-degree codes can achieve any pair (c, p) on the capacity-noise curve of the binary symmetric channel (bsc). next, we show that our compound construction has a nested structure that can be exploited to achieve the wyner-ziv bound for source coding with side information (scsi), as well as the gelfand-pinsker bound for channel coding with side information (ccsi). although the results described here are based on optimal encoding and decoding, the proposed graphical codes have sparse structure and high girth that renders them well suited to message passing and other efficient decoding procedures.
diversity gains of power control with noisy csit in mimo channels. a multiantenna channel with partial channel state information at the transmitter (csit) is studied. the partial csit takes the form of the channel matrix corrupted by additive white gaussian noise (awgn) with a variance that is assumed to decay as a power of the signal-to-noise ratio (snr). it is shown that under a long-term power constraint and in the regime of asymptotically high snr, a large diversity gain over the channel can be achieved by using rarely a high power at the transmitter that compensates for bad channel realizations. examples relating the diversity gain of the systems with the channel doppler bandwidth are discussed.
a constant bound on throughput improvement of multicast network coding in undirected networks. recent research in network coding shows that, joint consideration of both coding and routing strategies may lead to higher information transmission rates than routing only. a fundamental question in the field of network coding is: how large can the throughput improvement due to network coding be? in this paper, we prove that in undirected networks, the ratio of achievable multicast throughput with network coding to that without network coding is bounded by a constant ratio of 2, i.e., network coding can at most double the throughput. this result holds for any undirected network topology, any link capacity configuration, any multicast group size, and any source information rate. this constant bound 2 represents the tightest bound that has been proved so far in general undirected settings, and is to be contrasted with the unbounded potential of network coding in improving multicast throughput in directed networks.
noise enhanced nonparametric detection. this paper investigates potential improvement of nonparametric detection performance via addition of noise and evaluates the performance of noise modified nonparametric detectors. detection performance comparisons are made between the original detectors and noise modified detectors. conditions for improvability as well as the optimum additive noise distributions of the widely used sign detector, the wilcoxon detector, and the dead-zone limiter detector are derived. finally, a simple and fast learning algorithm to find the optimal noise distribution solely based on received data is presented. a near-optimal solution can be found quickly based on a relatively small dataset.
a coding algorithm for constant weight vectors: a geometric approach based on dissections. we present a novel technique for encoding and decoding constant weight binary vectors that uses a geometric interpretation of the codebook. our technique is based on embedding the codebook in a euclidean space of dimension equal to the weight of the code. the encoder and decoder mappings are then interpreted as a bijection between a certain hyper-rectangle and a polytope in this euclidean space. an inductive dissection algorithm is developed for constructing such a bijection. we prove that the algorithm is correct and then analyze its complexity. the complexity depends on the weight of the vector, rather than on the block length as in other algorithms. this approach is advantageous when the weight is smaller than the square root of the block length.
a collaborative training algorithm for distributed learning. in this paper, an algorithm is developed for collaboratively training networks of kernel-linear least-squares regression estimators. the algorithm is shown to distributively solve a relaxation of the classical centralized least-squares regression problem. a statistical analysis shows that the generalization error afforded agents by the collaborative training algorithm can be bounded in terms of the relationship between the network topology and the representational capacity of the relevant reproducing kernel hilbert space. numerical experiments suggest that the algorithm is effective at reducing noise. the algorithm is relevant to the problem of distributed learning in wireless sensor networks by virtue of its exploitation of local communication. several new questions for statistical learning theory are proposed.
golden space-time block-coded modulation. in this paper, block-coded modulation is used to design a 2×2 multiple-input multiple-output (mimo) space-time code for slow fading channels. the golden code is chosen as the inner code; the scheme is based on a set partitioning of the golden code using two-sided ideals whose norm is a power of two. in this case, a lower bound for the minimum determinant is given by the minimum hamming distance. the description of the ring structure of the quotients suggests further optimization in order to improve the overall distribution of determinants. simulation results show that the proposed schemes achieve a significant gain over the uncoded golden code.
diversity product properties of lu-kumar's space-time codes. in this paper, we show that the diversity products of the full transmit diversity space-time block codes proposed by lu-kumar (we call them lu-kumar's codes) with quadratic-amplitude modulation (qam) constellations are lower bounded by 4. we present a sufficient condition on the minimum hamming weight of the linear binary full-rank space-time code such that this lower bound is met. we show that the special lu-kumar codes does satisfy the sufficient condition, and therefore, the diversity products of the special lu-kumar codes are 4, where "special" means that the linear binary full-rank space-time codes are general but specially constructed by lu-kumar.
capacity bounds for the gaussian interference channel. the capacity region of the two-user gaussian interference channel (ic) is studied. three classes of channels are considered: weak, one-sided, and mixed gaussian ics. for the weak gaussian ic, a new outer bound on the capacity region is obtained that outperforms previously known outer bounds. the sum capacity for a certain range of channel parameters is derived. for this range, it is proved that using gaussian codebooks and treating interference as noise are optimal. it is shown that when gaussian codebooks are used, the full han-kobayashi achievable rate region can be obtained by using the naive han-kobayashi achievable scheme over three frequency bands (equivalently, three subspaces). for the one-sided gaussian ic, an alternative proof for the sato's outer bound is presented. we derive the full han-kobayashi achievable rate region when gaussian codebooks are utilized. for the mixed gaussian ic, a new outer bound is obtained that outperforms previously known outer bounds. for this case, the sum capacity for the entire range of channel parameters is derived. it is proved that the full han-kobayashi achievable rate region using gaussian codebooks is equivalent to that of the one-sided gaussian ic for a particular range of channel parameters.
robust precoder adaptation for mimo links with noisy limited feedback. in this paper, we propose two robust limited feedback designs for multiple-input multiple-output (mimo) adaptation. the first scheme, namely, the combined design jointly optimizes the adaptation, csit (channel state information at the transmitter) feedback as well as index assignment strategies. the second scheme, namely, the decoupled design, focuses on the index assignment problem given an error-free limited feedback design. simulation results show that the proposed framework has significant capacity gain compared to the naive design (designed assuming there is no feedback error). furthermore, for large number of feedback bits cfb, we show that under two-nearest constellation feedback channel assumption, the mimo capacity loss (due to noisy feedback) of the proposed robust design scales like o(pe2-cfb/t+1 for some positive integer t. hence, the penalty due to noisy limited feedback in the proposed robust design approaches zero as cfb increases.
sampling theorems for signals from the union of finite-dimensional linear subspaces. compressed sensing is an emerging signal acquisition technique that enables signals to be sampled well belowthe nyquist rate, given that the signal has a sparse representation in an orthonormal basis. in fact, sparsity in an orthonormal basis is only one possible signal model that allows for sampling strategies below the nyquist rate. in this paper, we consider a more general signal model and assume signals that live on or close to the union of linear subspaces of lowdimension.we present sampling theorems for this model that are in the same spirit as the nyquist-shannon sampling theorem in that they connect the number of required samples to certain model parameters. contrary to the nyquist-shannon sampling theorem, which gives a necessary and sufficient condition for the number of required samples as well as a simple linear algorithm for signal reconstruction, the model studied here is more complex. we therefore concentrate on two aspects of the signal model, the existence of one to one maps to lower dimensional observation spaces and the smoothness of the inverse map. we show that almost all linear maps are one to one when the observation space is at least of the same dimension as the largest dimension of the convex hull of the union of any two subspaces in the model. however, we also show that in order for the inverse map to have certain smoothness properties such as a given finite lipschitz constant, the required observation dimension necessarily depends logarithmically on the number of subspaces in the signal model. in other words, while unique linear sampling schemes require a small number of samples depending only on the dimension of the subspaces involved, in order to have stable sampling methods, the number of samples depends necessarily logarithmically on the number of subspaces in the model. these results are then applied to two examples, the standard compressed sensing signal model in which the signal has a sparse representation in an orthonormal basis and to a sparse signal model with additional tree structure.
some designs and normalized diversity product upper bounds for lattice-based diagonal and full-rate space-time block codes. in this paper, we first present two tight upper bounds for the normalized diversity products (or product distances) of 2 × 2 diagonal space-time block codes from quadratic extensions on q(i) and q(ζ6), where i = √-1 and ζ6 = exp(i2π/6). two such codes are shown to reach the tight upper bounds and therefore have the maximal normalized diversity products. we present two new diagonal space-time block codes from higher order algebraic extensions on q(i) and q(ζ6) for three and four transmit antennas. we also present a nontight upper bound for normalized diversity products of 2 × 2 diagonal space-time block codes with qam information symbols, i.e., in z [i], from general 2 × 2 complex-valued generating matrices. we then present an n × n-diagonal space-time code design method directly from 2n real integers based on extended complex lattices (of generating matrix size n × 2n) that are shown to have better normalized diversity products than the optimal diagonal cyclotomic codes do. we finally use the optimal 2 × 2 diagonal space-time codes from the optimal quadratic extensions to construct two 2 × 2 full-rate space-time block codes and find that both of them have better normalized diversity products than the golden code does.
noncoherent mimo communication: grassmannian constellations and efficient detection. this paper considers the design of both a transmitter and a receiver for noncoherent communication over a frequency-flat, richly scattered multiple-input multiple-output (mimo) channel. the design is guided by the fact that at high signal-to-noise ratios (snrs), the ergodic capacity of the channel can be achieved by input signals that are isotropically distributed on the (compact) grassmann manifold. the first part of the paper considers the design of grassmannian constellations that mimic the isotropic distribution. a subspace perturbation analysis is used to determine an appropriate metric for the distance between grassmannian constellation points, and using this metric, greedy, direct and rotation-based techniques for designing constellations are proposed. these techniques offer different tradeoffs between the minimum distance of the constellation and the design complexity. in addition, the rotation-based technique results in constellations that have lower storage requirements and admit a natural "quasi-set-partitioning" binary labeling. in the second part of the paper, a reduced search suboptimum detector is proposed. the development of this detector relies on the subspace perturbation analysis and exploits the geometric properties of the grassmann manifold and the isotropic distribution of the constellation points and the noise realizations. the performance of this detector is comparable to that of the maximum likelihood detector, but it requires considerably less computational effort. finally, in order to assess the performance of a given constellation, an exact expression is provided for the pairwise error probability of the ml detector. in comparison to existing pairwise error probability expressions, the proposed expression is numerically stable and does not require the evaluation of residues at poles with high multiplicities.
efficient and generalized pairing computation on abelian varieties. in this paper, we propose a new method for constructing a bilinear pairing over (hyper)elliptic curves, which we call the r-ate pairing. this pairing is a generalization of the ate and atei pairing, and can be computed more efficiently. using the r-ate pairing, the loop length in miller's algorithm can be as small as log(r1/φ(k)) for some pairing-friendly elliptic curves which have not reached this lower bound. therefore, we obtain savings of between 29% and 69% in overall costs compared to the atei pairing. on supersingular hyperelliptic curves of genus 2, we show that this approach makes the loop length in miller's algorithm shorter than that of the ate pairing.
asymptotic analysis of outage region in cdma mimo systems. uplink code-division multiple access (cdma) multiple-input and multiple-output (mimo) systems are considered in the large system limit within the assumptions of synchrony and frequency flat fading. the outage region maximizing the sum capacity of non-outage users is obtained, which extends the criterion of outage in single-input and single-output (siso) cdma systems.
further results on stable recovery of sparse overcomplete representations in the presence of noise. sparse overcomplete representations have attracted much interest recently for their applications to signal processing. in a recent work, donoho, elad, and temlyakov (2006) showed that, assuming sufficient sparsity of the ideal underlying signal and approximate orthogonality of the overcomplete dictionary, the sparsest representation can be found, at least approximately if not exactly, by either an orthogonal greedy algorithm or by l1-norm minimization subject to a noise tolerance constraint. in this paper, we sharpen the approximation bounds under more relaxed conditions. we also derive analogous results for a stepwise projection algorithm.
compressed and privacy-sensitive sparse regression. recent research has studied the role of sparsity in high-dimensional regression and signal reconstruction, establishing theoretical limits for recovering sparse models. this line of work shows that l1-regularized least squares regression can accurately estimate a sparse linear model from noisy examples in high dimensions. we study a variant of this problem where the original n input variables are compressed by a random linear transformation to m ≪ n examples in p dimensions, and establish conditions under which a sparse linear model can be successfully recovered from the compressed data. a primary motivation for this compression procedure is to anonymize the data and preserve privacy by revealing little information about the original data. we characterize the number of projections that are required for l1-regularized compressed regression to identify the nonzero coefficients in the true model with probability approaching one, a property called "sparsistence." we also show that l1-regularized compressed regression asymptotically predicts as well as an oracle linear model, a property called "persistence." finally, we characterize the privacy properties of the compression procedure, establishing upper bounds on the mutual information between the compressed and uncompressed data that decay to zero.
error-pattern-correcting cyclic codes tailored to a prescribed set of error cluster patterns. a new class of cyclic codes is discussed which is highly tailored to a prescribed set of dominant error cluster patterns. the cyclic code construction is based on a generator polynomial that produces a distinct syndrome set for each error pattern in the target set. by tailoring the generator polynomial specifically to the set of dominant error patterns, the code becomes highly effective in handling single and multiple occurrences of dominant error patterns at a very high code rate. a list decoding strategy based on a set of test word-error events is developed for the proposed codes, which efficiently utilizes both the algebraic information from the captured syndrome and the reliability measures provided by the local correlators matched to the dominant error patterns. by forcing a decoder to correct a single-pattern event for each test input word, multiple decoders running in parallel on the list of test words can effectively correct multiple error-pattern occurrences within the channel detector output word.
tracking stopping times through noisy observations. a novel quickest detection setting is proposed, generalizing the well-known bayesian change-point detection model. suppose {(xi,yi)}i≥1 is a sequence of pairs of random variables, and that s is a stopping time with respect to {xi}i≥1. the problem is to find a stopping time t with respect to {yi}i≥1 that optimally tracks s, in the sense that t minimizes the expected reaction delay e(t-s)+, while keeping the false-alarm probability p(t < s) below a given threshold α ∈ [0,1]. this problem formulation applies in several areas, such as in communication, detection, forecasting, and quality control. our results relate to the situation where the xi's and yi's take values in finite alphabets and where s is bounded by some positive integer κ. by using elementary methods based on the analysis of the tree structure of stopping times, we exhibit an algorithm that computes the optimal average reaction delays for all α ∈ [0,1], and constructs the associated optimal stopping times t. under certain conditions on {(xi,yi)}i≥1 and s, the algorithm running time is polynomial in κ.
shortening array codes and the perfect 1-factorization conjecture. the existence of a perfect 1-factorization of the complete graph with n nodes, namely, kn, for arbitrary even number n, is a 40-year-old open problem in graph theory. so far, two infinite families of perfect 1-factorizations have been shown to exist, namely, the factorizations of kp+1 and k2p, where p is an arbitrary prime number (p < 2). it was shown in previous work that finding a perfect 1-factorization of kn is related to a problem in coding, specifically, it can be reduced to constructing an mds (minimum distance separable), lowest density array code. in this paper, a new method for shortening arbitrary array codes is introduced. it is then used to derive the kp+1 family of perfect 1-factorization from the k2p family. namely, techniques from coding theory are used to prove a new result in graph theory--that the two factorization families are related.
self-organization properties of csma/ca systems and their consequences on fairness. decentralized medium access control schemes for wireless networks based on csma/ca, such as the ieee 802.11 protocol, are known to be unfair. in multihop networks, they can even favor some links to such an extent that the others suffer from virtually complete starvation. this observation has been reported in quite a few works, but the factors causing it are still not well understood. we find that the capture effect and the relative values of the receive and carrier sensing ranges play a crucial role in the performance of these protocols. using a simple markovian model, we show that an idealized csma/ca protocol suffers from starvation when the receiving and sensing ranges are equal, but quite surprisingly that this unfairness is reduced or even disappears when these two ranges are sufficiently different. we also show that starvation has a positive counterpart, namely organization. when its access intensity is large the protocol organizes the transmissions in space in such a way that it maximizes the number of concurrent successful transmissions. we obtain exact formulæ for the so-called spatial reuse of the protocol on large line networks.
combinatorial constructions for optimal two-dimensional optical orthogonal codes. optical orthogonal codes (oocs) have been designed for ocdma. a one-dimensional (1-d) optical orthogonal code (1-d ooc) is a set of one-dimensional binary sequences having good auto and cross-correlations. one limitation of 1-d ooc is that the length of the sequence increases rapidly when the number of users or the weight of the code is increased, which means large bandwidth expansion is required if a big number of codewords is needed. to lessen this problem, two-dimensional (2-d) coding (also called multiwavelength oocs) was invested. a two dimensional (2-d) optical orthogonal code (2-d ooc) is a set of u × v matrices with (0, 1) elements having good auto and cross-correlations. recently, many researchers are working on constructions and designs of 2-d oocs. in this paper, we shall reveal the combinatorial properties of 2-d oocs and give an equivalent combinatorial description of a 2-d ooc. based on this, we are able to use combinatorial methods to obtain many optimal 2-d oocs.
vector gaussian multiple description with two levels of receivers. the problem of l multiple descriptions of a stationary and ergodic gaussian source with two levels of receivers is investigated. each of the first-level receivers receive (an arbitrary subset) k of the l descriptions, (k < l). the second-level receiver receives all l descriptions. all the receivers, both at the first level and the second level, reconstruct the source using the subset of descriptions they receive. the corresponding reconstructions are subject to quadratic distortion constraints. our main result is the derivation of an outer bound on the sum rate of the descriptions so that the distortion constraints are met. we show that an analog-digital separation architecture involving joint gaussian vector quantizers and a binning scheme meets this outer bound with equality for several scenarios. these scenarios include the case when the distortion constraints are symmetric and the case for general distortion constraints with k = 2 and l = 3.
classification of unique mappings for 8psk based on bit-wise distance spectra. the performance of bit-interleaved coded modulation (bicm) with (or without) iterative decoding (id) is significantly influenced by the mapping of bits to the symbol constellation. our main objective in this paper is to develop a systematic design approach for bicm-id schemes, ensuring the best possible performance with iterative decoding. although useful mappings for bicm-id have been found based on various search strategies, no attempt has been made to systematically enumerate and classify all unique mappers for a given constellation. as the basis for a systematic enumeration and classification, we define the average bit-wise distance spectrum for a mapping from bits to symbols. different bit-wise distance spectra are derived assuming no prior information or full prior information, respectively. the bitwise distance spectra determine corresponding bit-wise error probability and bit-wise mutual information. the latter allows us to use the classification of mappings with unique bit-wise distance spectra to also classify mappings with unique extremal points in the corresponding extrinsic information transfer (exit) curves. as an example of our approach, we classify 8psk mappings into 86 classes of unique mappings according to bit-wise distance spectra. the classification can be used to significantly reduce the complexity of the search for suitable mappers for bicm-id. for 8psk and a given encoder, only 86 different mappings need to be investigated. as examples of the systematic design approach, the best 8psk mappings for minimizing the convergence threshold are found for concatenation with the rate 1/2 (5, 7)8 and (133,171)8 convolutional codes, and the rate 1/2 umts turbo code with identical constituent convolutional codes (15/13)8.
lower limits of discrete universal denoising. in the spirit of results on universal compression, we compare the performance of universal denoisers on discrete memoryless channels to that of the best performance obtained by an omniscient kth-order sliding-window denoiser, namely, one that is tuned to the transmitted noiseless sequence. we show that the additional loss incurred in the worst case by any universal denoiser on a length-n sequence grows at least like ω(ck/√n), where c is a constant depending on the channel parameters and the loss function. this shows that for fixed k the additional loss incurred by the discrete universal denoiser (dude) is no larger than a constant multiplicative factor of the best possible. furthermore, we compare universal denoisers to denoisers that are aware of the distribution of the transmitted noiseless sequence. we show that, even for this weaker target loss, for any universal denoiser there exists some distribution for the noiseless sequence corresponding to a sequence of independent and identically distributed (i.i.d.) random variables whose optimum expected loss is lower than that incurred by the universal denoiser by ω(1/√n).
ergodic channel capacities for the amplify-and-forward half-duplex cooperative systems. in this paper, the ergodic channel capacities are established for the amplify-and-forward (af) half-duplex cooperative systems, which consist of a source node, a destination, and multiple-relay nodes. the relay nodes assist the transmission from the source node to the destination. since the channel matrices for the cooperative systems involve product of gaussian random variables, which are no longer gaussian, the approach in obtaining the ergodic channel capacity for conventional multiple-input-multiple-output (mimo) gaussian channels (telatar, 1999) is not applicable. by using a novel approach, we have arrived at the following conclusions about the ergodic channel capacities for the af cooperative systems. for the single antenna af relay systems in which all nodes are equipped with one antenna, the optimal covariance matrix of the input signals to achieve the ergodic channel capacity is diagonal, and the diagonal elements are obtained by solving optimization problems of multidimensional integrals. these diagonal entries are not all equal even if all the channel gains in the cooperative systems are independent and identically distributed (i.i.d.) gaussian with unit variance. therefore, a white input signal for the af cooperative system may not achieve the ergodic channel capacity of the system. this is in direct contrast to the case of conventional multiple-input-single-output (miso) systems having i.i.d. gaussian channel gains of unit variance, in which case, the ergodic capacity is achieved if the input covariance matrix is a scaled identity matrix. for the mimo relay system in which the nodes have multiple antennas, the input covariance matrix to achieve the ergodic capacity is block diagonal and each block diagonalizes the autocorrelation of channel matrix from the source to the destination. this is different from the case of conventional mimo systems, where the input covariance matrix to achieve the ergodic channel capacity diagonalizes the channel autocorrelation matrix of the mimo system (tulina, lozano, and verdú, 2006). if the channel gains in conventional mimo systems are correlated gaussian random variables, the input covariance matrix is a full matrix, not block diagonal; and if the channel gains are i.i.d. gaussians, the optimal input covariance matrix is a scaled identity. the observations obtained in this paper reveal useful insights of how the af cooperative systems "mimic" the conventional miso and mimo systems from the ergodic channel capacity perspective.
on the entropy rate of hidden markov processes observed through arbitrary memoryless channels. this paper studies the entropy rate of hidden markov processes (hmps) which are generated by observing a discrete-time binary homogeneous markov chain through an arbitrary memoryless channel. a fixed-point functional equation is derived for the stationary distribution of an input symbol conditioned on all past observations. while the existence of a solution to the fixed-point functional equation is guaranteed by martingale theory, its uniqueness follows from the fact that the solution is the fixed point of a contraction mapping. the entropy or differential entropy rate of the hmp can then be obtained through computing the average entropy of each input symbol conditioned on past observations. in absence of an analytical solution to the fixed-point functional equation, a numerical method is proposed in which the fixed-point functional equation is first converted to a discrete linear system using uniform quantization and then solved efficiently. the accuracy of the computed entropy rate is shown to be proportional to the quantization interval. unlike many other numerical methods, this numerical solution is not based on averaging over a sample path of the hmp.
universal simulation with fidelity criteria. we consider the problem of universal simulation of a memoryless source (with some partial extensions to markov sources), based on a training sequence emitted from the source. the objective is to maximize the conditional entropy of the simulated sequence given the training sequence, subject to a certain distance constraint between the probability distribution of the output sequence and the probability distribution of the input, training sequence. we derive, for several distance criteria, single-letter expressions for the maximum attainable conditional entropy as well as corresponding universal simulation schemes that asymptotically attain these maxima.
on the capacity of the discrete-time poisson channel. the large-inputs asymptotic capacity of a peak-power and average-power limited discrete-time poisson channel is derived using a new firm (nonasymptotic) lower bound and an asymptotic upper bound. the upper bound is based on the dual expression for channel capacity and the notion of capacity-achieving input distributions that escape to infinity. the lower bound is based on a lower bound on the entropy of a conditionally poisson random variable in terms of the differential entropy of its conditional mean.
the generalized random energy model and its application to the statistical physics of ensembles of hierarchical codes. in an earlier work, the statistical physics associated with finite-temperature decoding of code ensembles, along with the relation to their random coding error exponents, were explored in a framework that is analogous to derrida's random energy model (rem) of spin glasses, according to which the energy levels of the various spin configurations are independent random variables. the generalized rem (grem) extends the rem in that it introduces correlations between energy levels in an hierarchical structure. in this paper, we explore some analogies between the behavior of the grem and that of code ensembles which have parallel hierarchical structures. in particular, in analogy to the fact that the grem may have different types of phase transition effects, depending on the parameters of the model, then the above-mentioned hierarchical code ensembles behave substantially differently in the various domains of the design parameters of these codes.we make an attempt to explore the insights that can be imported from the statistical mechanics of the grem and be harnessed to serve for code design considerations and guidelines.
optimal monotone encodings. moran, naor, and segev have asked what is the minimal r = r(n, k) for which there exists an (n, k)-monotone encoding of length r, i.e., a monotone injective function from subsets of size up to k of {1, 2,..., n} to r bits. monotone encodings are relevant to the study of tamper-proof data structures and arise also in the design of broadcast schemes in certain communication networks. to answer this question, we develop a relaxation of k-superimposed families, which we call α-fraction k-multiuser tracing (k, α)-fut (fraction user-tracing) families). we show that r(n, k) = θ(klog(n/k)) by proving tight asymptotic lower and upper bounds on the size of (k, α)-fut families and by constructing an (n, k)-monotone encoding of length o(k log (n/k)). we also present an explicit construction of an (n, 2)-monotone encoding of length 2logn + o(1), which is optimal up to an additive constant.
better binary list decodable codes via multilevel concatenation. a polynomial time construction of binary codes with the currently best known tradeoff between rate and error-correction radius is given. specifically, linear codes over fixed alphabets are constructed that can be list decoded in polynomial time up to the so-called blokh-zyablov bound. the work builds upon earlier work by the authors where codes list decodable up to the zyablov bound (the standard product bound on distance of concatenated codes) were constructed. the new codes are constructed via a (known) generalization of code concatenation called multilevel code concatenation. a probabilistic argument, which is also derandomized via conditional expectations, is used to show the existence of inner codes with a certain nested list decodability property that is appropriate for use in multilevel concatenated codes. a "level-by-level" decoding algorithm, which crucially uses the list recovery algorithm for the outer folded reed-solomon codes, enables list decoding up to the designed distance bound, aka the blokh-zyablov bound, for multilevel concatenated codes.
two batch search with lie cost. we consider the problem of searching for an unknown number in the search space u = {0,..., m -1}. qary questions can be asked and some of the answers may be wrong. an arbitrary integer weighted bipartite graph γ is given, stipulating the cost γ(i,j) of each answer j ≠ i when the correct answer is i, i.e., the cost of a wrong answer. correct answers are supposed to be cost-less. it is assumed that a maximum cost e for the sum of the cost of all wrong answers can be afforded by the responder during the whole search. we provide tight upper and lower bounds for the largest size m = m (q, e, γ, n) for which it is possible to find an unknown number x* ∈ u with n q-ary questions and maximum lie cost e. our results improve the bounds of cicalese et al. (2004) and ahlswede et al. (2008). the questions in our strategies can be asked in two batches of nonadaptive questions. finally, we remark that our results can be further generalized to a wider class of error models including also unidirectional errors.
network coding: a computational perspective. in this work, we study the computational perspective of network coding, focusing on two issues. first, we address the computational complexity of finding a network code for acyclic multicast networks. second, we address the issue of reducing the amount of computation performed by network nodes. in particular, we consider the problem of finding a network code with the minimum possible number of encoding nodes, i.e., nodes that generate new packets by performing algebraic operations on packets received over incoming links. we present a deterministic algorithm that finds a feasible network code for a multicast network over an underlying graph g(v,e) in time o(|e|kh + |v|k2h2 + h4k3(k+h)), where k is the number of destinations and h is the number of packets. our algorithm improves the best known running time for network code construction. in addition, our algorithm guarantees that the number of encoding nodes in the obtained network code is upper-bounded by o(h3k2). next, we address the problem of finding integral and fractional network codes with the minimum number of encoding nodes. we prove that in the majority of settings this problem is np-hard. however, we show that if h = o(1),k = o(1), and the underlying communication graph is acyclic, then there exists an algorithm that solves this problem in polynomial time.
on the throughput of secure hybrid-arq protocols for gaussian block-fading channels. the focus of this paper is an information-theoretic study of retransmission protocols for reliable packet communication under a secrecy constraint. the hybrid automatic retransmission request (harq) protocol is revisited for a block-fading wiretap channel. here, two legitimate users communicate over a block-fading channel in the presence of a passive eavesdropper who intercepts the transmissions through an independent block-fading channel. in this model, the transmitter obtains a 1-bit ack/nack feedback from the legitimate receiver via an error-free public channel. both reliability and confidentiality of secure harq protocols are studied through the joint consideration of channel coding, secrecy coding, and retransmission protocols. in particular, the error and secrecy performance of repetition time diversity (rtd) and incremental redundancy (inr) protocols are investigated based on wyner code sequences. these protocols ensure that the confidential message is decoded successfully by the legitimate receiver and is kept completely secret from the eavesdropper for a set of channel realizations. this paper illustrates that there exists a rate-compatible wyner code family which ensures a secure inr protocol. further, it defines the connection outage and secrecy outage probabilities to characterize the tradeoff between the reliability of the legitimate communication link and the confidentiality with respect to the eavesdropper's link. for a given connection/secrecy outage probability pair, an achievable throughput of secure harq protocols is derived for block-fading channels. finally, both asymptotic analysis and numerical calculations demonstrate the benefits of harq protocols to throughput and secrecy.
performance analysis and design criteria of bicm-id with signal space diversity for keyhole nakagami-m fading channels. this paper generalizes the application bit-interleaved coded modulation with iterative decoding (bicm-id) using signal space diversity (ssd) over keyhole nakagami-m fading channels. the tight union bound on the asymptotic error performance is first analytically derived. the near-optimal rotation matrix with respect to both the asymptotic performance and the convergence behavior is then determined. in particular, it is demonstrated that the suitable rotation matrix is the one that has 1) all entries equal in magnitude, 2) a high diversity order, and 3) a large minimum product of the ratios between squared distances to the power m and log-squared distances to the power m of the rotated constellation scaled by factors of signal-to-noise ratio (snr) and the parameter m. various analytical and simulation results show that by employing ssd with a sufficiently large dimension, the error performance can closely approach that over an additive white gaussian noise (awgn) channel, even in the worst case of keyhole fading.
on the relay channel with receiver-transmitter feedback. an achievable rate for the discrete memoryless relay channel with receiver-transmitter feedback is proposed based on block-markov superposition encoding. the achievable rate can also be extended to gaussian channels. a second achievable rate for the gaussian relay channel based on a schalkwijk-kailath type scheme is presented. for some channels both achievable rates strictly improve upon all previously known achievable rates. for the discrete memoryless relay channel also a converse result is provided.
cyclic lowest density mds array codes. three new families of lowest density maximum-distance separable (mds) array codes are constructed, which are cyclic or quasi-cyclic. in addition to their optimal redundancy (mds) and optimal update complexity (lowest density), the symmetry offered by the new codes can be utilized for simplified implementation in storage applications. the proof of the code properties has an indirect structure: first mds codes that are not cyclic are constructed, and then transformed to cyclic codes by a minimum-distance preserving transformation.
finite state channels with time-invariant deterministic feedback. we consider capacity of discrete-time channels with feedback for the general case where the feedback is a time-invariant deterministic function of the output samples. under the assumption that the channel states take values in a finite alphabet, we find a sequence of achievable rates and a sequence of upper bounds on the capacity. the achievable rates and the upper bounds are computable for any n, and the limits of the sequences exist. we show that when the probability of the initial state is positive for all the channel states, then the capacity is the limit of the achievable-rate sequence. we further show that when the channel is stationary, indecomposable, and has no intersymbol interference (isi), its capacity is given by the limit of the maximum of the (normalized) directed information between the input xn and the output yn, i.e., c = limn → ∞ 1/n max i(xn → yn) where the maximization is taken over the causal conditioning probability q(xn∥zn-1) defined in this paper. the main idea for obtaining the results is to add causality into gallager's results on finite state channels. the capacity results are used to show that the source-channel separation theorem holds for time-invariant determinist feedback, and if the state of the channel is known both at the encoder and the decoder, then feedback does not increase capacity.
coding on countably infinite alphabets. this paper describes universal lossless coding strategies for compressing sources on countably infinite alphabets. classes of memoryless sources defined by an envelope condition on the marginal distribution provide benchmarks for coding techniques originating from the theory of universal coding over finite alphabets. we prove general upper bounds on minimax regret and lower bounds on minimax redundancy for such source classes. the general upper bounds emphasize the role of the normalized maximum likelihood (nml) codes with respect to minimax regret in the infinite alphabet context. lower bounds are derived by tailoring sharp bounds on the redundancy of krichevsky-trofimov coders for sources over finite alphabets. up to logarithmic (resp., constant) factors the bounds are matching for source classes defined by algebraically declining (resp., exponentially vanishing) envelopes. effective and (almost) adaptive coding techniques are described for the collection of source classes defined by algebraically vanishing envelopes. those results extend our knowledge concerning universal coding to contexts where the key tools from parametric inference are known to fail.
provably good codes for hash function design. a new technique to lower-bound the minimum distance of certain types of quasi-cyclic codes with large dimension by reducing the problem to lower-bounding the minimum distance of a few significantly smaller codes has been developed. these codes have the property that they have extremely efficient software encoders. using this technique, it is proved that a code which is similar to the sha-1 (secure hash algorithm, to be explained shortly) message expansion code has minimum distance 82, and that too in just the last 64 of the 80 expanded words. in fact, the proposed code has much greater distance than that of sha-1 code, which makes our proposed hashing scheme robust against cryptographic attacks. the technique is further used to find the minimum weight of the sha-1 code itself (25 in last 60 words), which was an open problem. estimating minimum distance of a code given by its parity-check matrix is well known to be a hard problem. our technique is expected to be helpful in estimating minimum distance of similar codes as well as in designing future practical cryptographic hash functions.
channel simulation with quantum side information. we study and solve the problem of classical channel simulation with quantum side information at the receiver. this is a generalization of both the classical reverse shannon theorem, and the classical-quantum slepian-wolf problem. the optimal noiseless communication rate is found to be reduced from the mutual information between the channel input and output by the holevo information between the channel output and the quantum side information. our main theorem has two important corollaries. the first is a quantum generalization of thewyner-ziv problem: ratedistortion theory with quantum side information. the second is an alternative proof of the tradeoff between classical communication and common randomness distilled from a quantum state. the fully quantum generalization of the problem considered is quantum state redistribution. here the sender and receiver share a mixed quantum state and the sender wants to transfer part of her state to the receiver using entanglement and quantum communication. we present outer and inner bounds on the achievable rate pairs.
constrained capacities for faster-than-nyquist signaling. this paper deals with capacity computations of fasterthan-nyquist (ftn) signaling. it shows that the capacity of ftn higher than the orthogonal pulse linear modulation capacity for all pulse shapes except the sinc. ftn signals can in fact achieve the ultimate capacity for the signal power spectral density (psd). the paper lower- and upper-bounds the ftn capacity under the constraint of finite input alphabet. it is often higher than the capacity for comparable orthogonal pulse systems; sometimes it is superior to all forms of orthogonal signaling with the same psd.
robust hypothesis testing with a relative entropy tolerance. this paper considers the design of a minimax test for two hypotheses where the actual probability densities of the observations are located in neighborhoods obtained by placing a bound on the relative entropy between actual and nominal densities. the minimax problem admits a saddle point which is characterized. the robust test applies a nonlinear transformation which flattens the nominal likelihood ratio in the vicinity of one. results are illustrated by considering the transmission of binary data in the presence of additive noise.
local base station cooperation via finite-capacity links for the uplink of linear cellular networks. cooperative decoding at the base stations (or access points) of an infrastructure wireless network is currently well recognized as a promising approach for intercell interference mitigation, thus enabling high frequency reuse. deployment of cooperative multicell decoding depends critically on the tolopology and quality of the available backhaul links connecting the base stations. this work studies a scenario where base stations are connected only if in adjacent cells, and via finite-capacity links. relying on a linear wyner-type cellular model with no fading, achievable rates are derived for the two scenarios where base stations are endowed only with the codebooks of local (in-cell) mobile stations, or also with the codebooks used in adjacent cells. moreover, both uni- and bidirectional backhaul links are considered. the analysis sheds light on the impact of codebook information, decoding delay, and network planning (frequency reuse) on the performance of multicell decoding as enabled by local and finite-capacity backhaul links. analysis in the high-signal-to-noise ratio (snr) regime and numerical results validate the main conclusions.
capacity of a class of modulo-sum relay channels. this paper characterizes the capacity of a class of modular additive noise relay channels, in which the relay observes a corrupted version of the noise and has a separate channel to the destination. the capacity is shown to be strictly below the cut-set bound in general and adhievable using a quantize-and-forward strategy at the relay. this result confirms a previous conjecture on the capacity of channels with rate-limited side information at the receiver for this particular class of modulo-sum channels. this paper also considers a more general setting in which the relay is capable of conveying noncausal rate-limited side information about the noise to both the transmitter and the receiver. the capacity is characterized for the case where the channel is binary symmetric with a crossover probability 1/2. in this case, the rates available for conveying side information to the transmitter and to the receiver can be traded with each other arbitrarily--the capacity is a function of the sum of the two rates.
quantifying the loss of compress-forward relaying without wyner-ziv coding. the compress-and-forward (cf) strategy achieves the optimal diversity-multiplexing tradeoff (dmt) of a three-node half-duplex relay network in slow fading, under the assumption that the relay has perfect knowledge of all three channel coefficients and that the relay makes use of wyner-ziv (wz) source coding with side information. this paper studies the achievable dmt of the same network when the relay is constrained to make use of standard (non-wz) source coding. under a short-term power constraint at the relay, using source coding without side information results in a significant loss in terms of the dmt. for multiplexing gains r ≤ 2/3, this loss can be fully compensated for by using power control at the relay. on the contrary, for r ∈ (2/3,1), the loss with respect to wz coding remains significant.
quantum covariance, quantum fisher information, and the uncertainty relations. in this paper, the relation between quantum covariances and quantum fisher informations is studied. this study is applied to generalize a recently proved uncertainty relation based on quantum fisher information. the proof given here considerably simplifies the previously proposed proofs and leads to more general inequalities.
error exponents for asymmetric two-user discrete memoryless source-channel coding systems. we study the transmission of two discrete memoryless correlated sources, consisting of a common and a private source, over a discrete memoryless multiterminal channel with two transmitters and two receivers. at the transmitter side, the common source is observed by both encoders but the private source can only be accessed by one encoder. at the receiver side, both decoders need to reconstruct the common source, but only one decoder needs to reconstruct the private source. we hence refer to this system by the asymmetric two-user source-channel coding system. we derive a universally achievable lossless joint source-channel coding (jscc) error exponent pair for the two-user system by using a technique which generalizes csiszár's type-packing lemma (1980) for the point-to-point (single-user) discrete memoryless source-channel system. we next investigate the largest convergence rate of asymptotic exponential decay of the system (overall) probability of erroneous transmission, i.e., the system jscc error exponent. we obtain lower and upper bounds for the exponent. as a consequence, we establish a jscc theorem with single-letter characterization and we show that the separation principle holds for the asymmetric two-user scenario. by introducing common randomization, we also provide a formula for the tandem (separate) source-channel coding error exponent. numerical examples show that for a large class of systems consisting of two correlated sources and an asymmetric multiple-access channel with additive noise, the jscc error exponent considerably outperforms the corresponding tandem coding error exponent.
on practical design for joint distributed source and network coding. this paper considers the problem of communicating correlated information from multiple source nodes over a network of noiseless channels to multiple destination nodes, where each destination node wants to recover all sources. the problem involves a joint consideration of distributed compression and network information relaying. although the optimal rate region has been theoretically characterized, it was not clear how to design practical communication schemes with low complexity. this work provides a partial solution to this problem by proposing a low-complexity scheme for the special case with two sources whose correlation is characterized by a binary symmetric channel. our scheme is based on a careful combination of linear syndrome-based slepian-wolf coding and random linear mixing (network coding). it is in general suboptimal; however, its low complexity and robustness to network dynamics make it suitable for practical implementation.
finite-length scaling for iteratively decoded ldpc ensembles. we investigate the behavior of iteratively decoded low-density parity-check (ldpc) codes over the binary erasure channel in the so-called "waterfall region". we show that the performance curves in this region follow a simple scaling law. we conjecture that essentially the same scaling behavior applies in a much more general setting and we provide some empirical evidence to support this conjecture. the scaling law, together with the error floor expressions developed previously, can be used for a fast finite-length optimization.
teleoperation of mobile robots with time-varying delay. this paper proposes a stable control structure for the bilateral teleoperation of mobile robots. the proposed control structure includes a time-delay compensation placed on both the local and remote sites of the teleoperation system. to illustrate the performance and stability of the proposed control structure, experiences on a pioneer 2dx mobile robot teleoperated through a commercial joystick with visual feedback, are shown.
autonomous driving in urban environments: boss and the urban challenge. boss is an autonomous vehicle that uses on-board sensors (global positioning system, lasers, radars, and cameras) to track other vehicles, detect static obstacles, and localize itself relative to a road model. a three-layer planning system combines mission, behavioral, and motion planning to drive in urban environments. the mission planning layer considers which street to take to achieve a mission goal. the behavioral layer determines when to change lanes and precedence at intersections and performs error recovery maneuvers. the motion planning layer selects actions to avoid obstacles while making progress toward local goals. the system was developed from the ground up to address the requirements of the darpa urban challenge using a spiral system development process with a heavy emphasis on regular, regressive system testing. during the national qualification event and the 85-km urban challenge final event, boss demonstrated some of its capabilities, qualifying first and winning the challenge. &copy; 2008 wiley periodicals, inc.
autonomous underground tramming for center-articulated vehicles. this paper describes the design, implementation, and field testing of an infrastructureless system for autonomous tramming (or hauling) of a center-articulated underground mining vehicle. such vehicles are ubiquitous in underground mining, and effective automation of their tramming function has been a sought-after technology for more than a decade. this paper reports on the successful development of a fast, reliable, and robust &ldquo;autotramming&rdquo; technology that does not require the installation of fixed infrastructure. included are descriptions of the chosen control architecture, map-based localization technique, and the results of integration and field testing. &copy; 2008 wiley periodicals, inc.
robust trajectory tracking for a reversing tractor trailer. tractor-trailer reversing is a classical nonlinear control problem in which many of the solutions proposed in the literature perform poorly in the presence of real-world constraints such as steering angle, rate limits, and lags. in this paper we describe a new method in which an inner loop controls the hitch angle of the trailer, creating a virtual articulated vehicle to which existing control techniques can be applied. we provide an analysis of the stability and convergence properties of this control approach, as well as experimental results that illustrate the robustness of this approach to model estimation errors, low-level control loop dynamics, and other disturbances introduced by, for example, state estimation errors. &copy; 2008 wiley periodicals, inc.
cooperative use of unmanned sea surface and micro aerial vehicles at hurricane wilma. on oct. 24, 2005, hurricane wilma, a category 5 storm, made landfall at cape romano, florida. three days later, the center for robot-assisted search and rescue at the university of south florida deployed an isenys helicopter and a prototype unmanned water surface vehicle, aeos-1, to survey damage in parts of marco island, 14 km from landfall. the effort was the first known use of unmanned sea surface vehicles (usvs) for emergency response and established their suitability for the recovery phase of disaster management by detecting damage to seawalls and piers, locating submerged debris (moorings and handrails), and determining safe lanes for sea navigation. it provides a preliminary domain theory of postdisaster port and littoral inspection with unmanned vehicles for use by the human&ndash;robot interaction community. it was also the first known demonstration of the strongly heterogeneous usv&ndash;micro aerial vehicle (mav) team for any domain. the effort identified cooperative uav&ndash;usv strategies and open issues for autonomous operations near structures. the effort showed that the mav provided a much-needed external view for situation awareness and provided spotting for areas to be inspected. concepts of operations for usv damage inspection and usv&ndash;mav cooperation emerged, including a formula for computing the human&ndash;robot ratio: nh = (2 &times; nv) + 1, where nh is the number of humans and nv is the number of vehicles. the outstanding research issues span three areas: challenges for usvs operating near littoral structures, general issues for usv&ndash;mav cooperation, and new applications. it is expected that the lessons learned will be transferrable to defense and homeland safety and security applications, such as port security, and other phases of emergency response, including rescue. &copy; 2008 wiley periodicals, inc.
benchmarking urban six-degree-of-freedom simultaneous localization and mapping. quite a number of approaches for solving the simultaneous localization and mapping (slam) problem exist by now. some of them have recently been extended to mapping environments with six-degree-of-freedom poses, yielding 6d slam approaches. to demonstrate the capabilities of the respective algorithms, it is common practice to present generated maps and successful loop closings in large outdoor environments. unfortunately, it is nontrivial to compare different 6d slam approaches objectively, because ground truth data about the outdoor environments used for demonstration are typically unavailable. we present a novel benchmarking method for generating the ground truth data based on reference maps. the method is then demonstrated by comparing the absolute performance of some previously existing 6d slam algorithms that build a large urban outdoor map. &copy; 2008 wiley periodicals, inc.
on the dynamic version of the minimum hand jerk criterion. this paper is concerned with the problem of trajectory formation of humanlike reaching movements. first, we review conventional criteria of optimality adopted in robotics and computational neuroscience for the prediction of reaching movements and formulate a dynamic version of the minimum hand jerk criteria. we call it a minimum driving force change criterion and check its performance for the free-space movements. next, we test the performance of the new criterion for the movements where the human hand is geometrically constrained by the external environment, and for the movements with flexible objects. the main feature of these movements is that the hand velocity profiles are not always bell shaped. our simulations and initial experimental results show that the minimum driving force change criterion can roughly capture this feature and, therefore, can be a reasonable candidate for modeling of humanlike reaching movements. &copy; 2005 wiley periodicals, inc.
autonomous docking of a smart wheelchair for the automated transport and retrieval system (atrs). the automated transport and retrieval system (atrs) represents a technology-based alternative to van conversions for automobile drivers in wheelchairs. rather than requiring dramatic, permanent, and expensive modifications to the host vehicle, atrs employs robotics and automation technologies and can be integrated noninvasively into a standard minivan or sport utility vehicle. at the core of atrs is a &ldquo;smart&rdquo; wheelchair system that autonomously navigates between the driver's position and a powered lift at the rear of the vehicle, eliminating the need for an attendant. from an automation perspective, autonomously docking the wheelchair onto the lift platform presented the most significant technical challenge due to limited clearance between the chair wheels and the lift platform rails. to solve the docking task, we employed a light detection and ranging (lidar)&ndash;based approach for wheelchair localization coupled with a hybrid motion controller design. extensive testing from the localization subsystem to the complete atrs was conducted under representative usage conditions. this included 3 days of public demonstrations indoors at the world congress on disabilities, where potential end users were able to evaluate the system. in this environment, atrs performed more than 300 consecutive cycles without failure. during 2 days of outdoor reliability testing, 97.5&percnt; docking reliability was observed. the system is scheduled to enter the commercial market in 2008. &copy; 2008 wiley periodicals, inc.
biologically inspired climbing with a hexapedal robot. this paper presents an integrated, systems-level view of several novel design and control features associated with the biologically inspired, hexapedal, rise (robots in scansorial environments) robot. rise is the first legged machine capable of locomotion on both the ground and a variety of vertical building surfaces including brick, stucco, and crushed stone at speeds up to 4 cm-s, quietly and without the use of suction, magnets, or adhesives. it achieves these capabilities through a combination of bioinspired and traditional design methods. this paper describes the design process and specifically addresses body morphology, hierarchical compliance in the legs and feet, and sensing and control systems that enable robust and reliable climbing on difficult surfaces. experimental results illustrate the effects of various behaviors on climbing performance and demonstrate the robot's ability to climb reliably for long distances. &copy; 2008 wiley periodicals, inc.
a practical approach to robotic design for the darpa urban challenge. this article presents a practical approach to engineering a robot to effectively navigate in an urban environment. inherent in this approach is the use of relatively simple sensors, actuators, and processors to generate robot vision, intelligence, and planning. sensor data are fused from multiple low-cost, two-dimensional laser scanners with an innovative rotational mount to provide three-dimensional coverage with image processing using both range and intensity data. information is combined with doppler radar returns to yield a world view processed by a context-based reasoning control system to yield tactical mission commands forwarded to traditional proportional-integral-derivative (pid) control loops. as an example of simplicity and robustness, steering control successfully utilized a relatively simple follow-the-carrot guidance approach that has been successfully demonstrated at speeds of 60 mph (97 km-h). the approach yielded a robot that reached the finals of the urban challenge and completed approximately 2 h of the event before being forced to withdraw as a result of a global positioning system data failure. &copy; 2008 wiley periodicals, inc.
monte carlo localization in outdoor terrains using multilevel surface maps. we propose a novel combination of techniques for robustly estimating the position of a mobile robot in outdoor environments using range data. our approach applies a particle filter to estimate the full six-dimensional state of the robot and utilizes multilevel surface maps, which, in contrast to standard elevation maps, allow the robot to represent vertical structures and multiple levels in the environment. we describe probabilistic motion and sensor models to calculate the proposal distribution and to evaluate the likelihood of observations. we furthermore describe an active localization approach that actively selects the sensor orientation of the two-dimensional laser range scanner to improve the localization results. to efficiently calculate the appropriate orientation, we apply a clustering operation on the particles and evaluate potential orientations on the basis of these clusters. experimental results obtained with a mobile robot in large-scale outdoor environments indicate that our approach yields robust and accurate position estimates. the experiments also demonstrate that multilevel surface maps lead to a significantly better localization performance than standard elevation maps. they additionally show that further accuracy is obtained from the active sensing approach. &copy; 2008 wiley periodicals, inc.
long-baseline acoustic navigation for under-ice autonomous underwater vehicle operations. the recent arctic gakkel vents expedition (agave) to the arctic ocean's gakkel ridge (july-august 2007) aboard the swedish icebreaker i-b oden employed autonomous underwater vehicles (auvs) for water-column and ocean bottom surveys. these surveys were unique among auv operations to date in requiring georeferenced navigation in proximity to the seafloor beneath permanent and moving ice cover. we report results for long-baseline (lbl) acoustic navigation during autonomous under-ice surveys near the seafloor and adaptation of the lbl concept for several typical operational situations including navigation in proximity to the ship during vehicle recoveries. fixed seafloor transponders were free-fall deployed from the ship for deep positioning. the ship's helicopter collected acoustic travel times from several locations to georeference the transponders' locations, subject to the availability of openings in the ice. two shallow beacons suspended from the ship provided near-surface spherical navigation in ship-relative coordinates. during routine recoveries, we used this system to navigate the vehicles into open water near the ship before commanding them to surface. in cases in which a vehicle was impaired, its position was still determined acoustically through some combination of its acoustic modem, the fixed seafloor transponders, the ship-deployed transponders, and an onboard backup relay transponder. the techniques employed included ranging adapted for a moving origin and hyperbolic navigation. &copy; 2008 wiley periodicals, inc.
team annieway's autonomous system for the 2007 darpa urban challenge. this paper reports on annieway, an autonomous vehicle that is capable of driving through urban scenarios and that successfully entered the finals of the 2007 darpa urban challenge competition. after describing the main challenges imposed and the major hardware components, we outline the underlying software structure and focus on selected algorithms. environmental perception mainly relies on a recent laser scanner that delivers both range and reflectivity measurements. whereas range measurements are used to provide three-dimensional scene geometry, measuring reflectivity allows for robust lane marker detection. mission and maneuver planning is conducted using a hierarchical state machine that generates behavior in accordance with california traffic laws. we conclude with a report of the results achieved during the competition. &copy; 2008 wiley periodicals, inc.
terrain-based vehicle orientation estimation combining vision and inertial measurements. a novel method for estimating vehicle roll, pitch, and yaw using machine vision and inertial sensors is presented that is based on matching images captured from an on-vehicle camera to a rendered representation of the surrounding terrain obtained from a three-dimensional (3d) terrain map. u.s. geographical survey digital elevation maps were used to create a 3d topology map of the geography surrounding the vehicle, and it is assumed in this work that large segments of the surrounding terrain are visible, particularly the horizon lines. the horizon lines seen in the captured video from the vehicle are compared to the horizon lines obtained from a rendered geography, allowing absolute comparisons between rendered and actual scene in roll, pitch, and yaw. a kinematic kalman filter modeling an inertial navigation system then uses the scene matching to generate filtered estimates of orientation. numerical simulations verify the performance of the kalman filter. experiments using an instrumented vehicle operating at the test track of the pennsylvania transportation institute were performed to check the validity of the method. when compared to estimates from a global positioning system-inertial measurement unit (imu) system, the roll, pitch, and yaw estimates from vision-imu kalman filter show an agreement with a (2&sigma;) bound of 0.5, 0.26, and 0.8 deg, respectively. &copy; 2008 wiley periodicals, inc.
development and application of an autonomous unmanned aerial vehicle for precise aerobiological sampling above agricultural fields. remote-controlled (rc) unmanned aerial vehicles (uavs) have been used to study the movement of agricultural threat agents (e.g., plant and animal pathogens, invasive weeds, and exotic insects) above crop fields, but these rc uavs are operated entirely by a ground-based pilot and often demonstrate large fluctuations in sampling height, sampling pattern, and sampling speed. in this paper, we describe the development and application of an autonomous uav for precise aerobiological sampling tens to hundreds of meters above agricultural fields. we equipped a senior telemaster uav with four aerobiological sampling devices and a micropilot-based autonomous system, and we conducted 25 sampling flights for potential agricultural threat agents at virginia tech's kentland farm. to determine the most appropriate sampling path for aerobiological sampling above crop fields with an autonomous uav, we explored five different sampling patterns, including multiple global positioning system (gps) waypoints plotted over a variety of spatial scales. an orbital sampling pattern around a single gps waypoint exhibited high positional accuracy and produced altitude standard deviations ranging from 1.6 to 2.8 m. autonomous uavs have the potential to extend the range of aerobiological sampling, improve positional accuracy of sampling paths, and enable coordinated flight with multiple uavs sampling at different altitudes. &copy; 2008 wiley periodicals, inc.
compact image stabilization system using camera posture information. a teleoperated robot that works in unstructured environments such as disaster sites is mainly controlled based on images obtained from cameras mounted on the robot. because the robot runs on rough terrains, the images from the mounted camera are nonsteady ones. these nonsteady images will make it difficult for the operator to understand the surrounding information and will cause the camera motion sickness. we have developed an image stabilization system using camera posture information for a mobile robot that moves on uneven terrains. because the camera posture information is detected by a three-dimensional-motion sensor separately from the camera image, this system works even in bad light condition environments and is robust for light condition changes. the wide-field-of-view images obtained by the fish-eye-lens camera are used to handle a large-amplitude disturbance. the sphere mapping and the image shifting of a region of &copy; 2008 wiley periodicals, inc.
team cornell's skynet: robust perception and planning in an urban environment. team cornell's skynet is an autonomous chevrolet tahoe built to compete in the 2007 darpa urban challenge. skynet consists of many unique subsystems, including actuation and power distribution designed in-house, a tightly coupled attitude and position estimator, a novel obstacle detection and tracking system, a system for augmenting position estimates with vision-based detection algorithms, a path planner based on physical vehicle constraints and a nonlinear optimization routine, and a state-based reasoning agent for obeying traffic laws. this paper describes these subsystems in detail before discussing the system's overall performance in the national qualifying event and the urban challenge. logged data recorded at the national qualifying event and the urban challenge are presented and used to analyze the system's performance. &copy; 2008 wiley periodicals, inc.
odin: team victortango's entry in the darpa urban challenge. the darpa urban challenge required robotic vehicles to travel more than 90 km through an urban environment without human intervention and included situations such as stop intersections, traffic merges, parking, and roadblocks. team victortango separated the problem into three parts: base vehicle, perception, and planning. a ford escape outfitted with a custom drive-by-wire system and computers formed the basis for odin. perception used laser scanners, global positioning system, and a priori knowledge to identify obstacles, cars, and roads. planning relied on a hybrid deliberative-reactive architecture to analyze the situation, select the appropriate behavior, and plan a safe path. all vehicle modules communicated using the jaus (joint architecture for unmanned systems) standard. the performance of these components in the urban challenge is discussed and successes noted. the result of victortango's work was successful completion of the urban challenge and a third-place finish. &copy; 2008 wiley periodicals, inc.
force cooperation in a reconfigurable field multirobot system. force cooperation between robots can enhance the mobility of robots in the field. this paper presents the multirobot system jl-1, in which the robots can dock and adjust their posture in relation to each other to execute force cooperation if necessary. to reveal how force cooperation enhances the terrain adaptability of jl-1 and to discover the limits of the current reconfiguration mechanism, this paper analyzes the forces arising between robots during force cooperation. by examining one typical, flexible force cooperation, the docking action, we deduce the self-aligning conditions of the current docking mechanism, which is useful to improve the mechanism and clarify the demands on the docking guidance sensors. the static analysis of the posture-adjusting mechanism yields the force-amplifying feature and the drivable work space of this motorized spherical joint consisting of a parallel and serial mechanism. the analysis also explains why some locomotion types of jl-1 are performed the way they are. after that, a series of on-site experiments confirm the abilities of the locomotion and the force cooperation of jl-1. as the basis of the analysis, the mechanical structure and control system architecture of jl-1 are also briefly introduced. &copy; 2008 wiley periodicals, inc.
junior: the stanford entry in the urban challenge. this article presents the architecture of junior, a robotic vehicle capable of navigating urban environments autonomously. in doing so, the vehicle is able to select its own routes, perceive and interact with other traffic, and execute various urban driving skills including lane changes, u-turns, parking, and merging into moving traffic. the vehicle successfully finished and won second place in the darpa urban challenge, a robot competition organized by the u.s. government. &copy; 2008 wiley periodicals, inc.
data-driven identification of group dynamics for motion prediction and control. a distributed model structure for representing groups of coupled dynamic agents is proposed, and the least-squares method is used for fitting model parameters based on measured position data. the difference equation model embodies a minimalist approach, incorporating only factors essential to the movement and interaction of physical bodies. the model combines effects from an agent's inertia, interactions between agents, and interactions between each agent and its environment. global positioning system tracking data were collected in field experiments from a group of 3 cows and a group of 10 cows over the course of several days using custom-designed, head-mounted sensor boxes. these data are used with the least-squares method to fit the model to the cow groups. the modeling technique is shown to capture overall characteristics of the group as well as attributes of individual group members. applications to livestock management are described, and the potential for surveillance, prediction, and control of various kinds of groups of dynamic agents are suggested. &copy; 2008 wiley periodicals, inc.
underwater slam in man-made structured environments. this paper describes a navigation system for autonomous underwater vehicles (auvs) in partially structured environments, such as dams, harbors, marinas, and marine platforms. a mechanically scanned imaging sonar is used to obtain information about the location of vertical planar structures present in such environments. a robust voting algorithm has been developed to extract line features, together with their uncertainty, from the continuous sonar data flow. the obtained information is incorporated into a feature-based simultaneous localization and mapping (slam) algorithm running an extended kalman filter. simultaneously, the auv's position estimate is provided to the feature extraction algorithm to correct the distortions that the vehicle motion produces in the acoustic images. moreover, a procedure to build and maintain a sequence of local maps and to posteriorly recover the full global map has been adapted for the application presented. experiments carried out in a marina located in the costa brava (spain) with the ictineu auv show the viability of the proposed approach. &copy; 2008 wiley periodicals, inc.
a perspective on emerging automotive safety applications, derived from lessons learned through participation in the darpa grand challenges. this paper reports on various aspects of the intelligent vehicle systems (ivs) team's involvement in the recent 2007 darpa urban challenge, wherein our platform, the autonomous &ldquo;xav-250,'' competed as one of the 11 finalists qualifying for the event. we provide a candid discussion of the hardware and software design process that led to our team's entry, along with lessons learned at this event and derived from participation in the two previous grand challenges. in addition, we give an overview of our vision-, radar-, and lidar-based perceptual sensing suite, its fusion with a military-grade inertial navigation package, and the map-based control and planning architectures used leading up to and during the event. the underlying theme of this article is to elucidate how the development of future automotive safety systems can potentially be accelerated by tackling the technological challenges of autonomous ground vehicle robotics. of interest, we will discuss how a production manufacturing mindset imposes a unique set of constraints upon approaching the problem and how this worked for and against us, given the very compressed timeline of the contests. &copy; 2008 wiley periodicals, inc.
co-design of fast biologically-plausible vision-based systems for controlling the reactive behaviors of mobile robots. this paper addresses the co-design of biologically-plausible vision-based algorithms applied to control the reactive behaviors of mobile robots and, especially, the control of collision avoidance in unknown and dynamic worlds. our main tools are programmable logic devices like fpga (field programmable gate arrays) to implement real-time perception&#x002f;actions schemes. &copy; 2005 wiley periodicals, inc.
evaluation of semi-autonomous convoy driving. autonomous mobility technologies may have applications to manned vehicle convoy operations&mdash;they have the ability to enhance both system performance and operator capability. this effort examines the potential impact of introducing semi-autonomous mobility [convoy active safety technologies (cast)] into manned vehicles. twelve civilians with experience driving military vehicles in convoy-type operations participated in this experiment. for the experiment, they were tasked with following a lead vehicle while completing a concurrent security task (scanning the local environment for targets). the control of the manned vehicle was varied between cast and manual control at several different speed levels. several objective speed and accuracy variables along with subjective operator assessment variables were examined for each task. the results support the potential benefits of incorporating semi-autonomous mobility technologies into manned vehicle convoy operations. the semi-autonomous mobility system was associated with significantly better performance in several aspects of operator situational awareness and convoy integrity, including enhanced target identification, improved maintenance of following distance, and improved performance for unanticipated stops. this experiment also highlighted a critical human factors issue associated with the incorporation of autonomy in real-world applications: participants felt that, overall, they outperformed the semi-autonomous system on the simulated convoy operation. the operator's perception of the system's performance could potentially affect his or her willingness to use the system in real-world applications. this experiment demonstrated that enhancements to overall system performance in real-world applications are achieved by considering both technological and human factors solutions. published 2008 wiley periodicals, inc. this article is a us government work and, as such, is in the public domain of the united states of america.
motion planning in urban environments. we present the motion planning framework for an autonomous vehicle navigating through urban environments. such environments present a number of motion planning challenges, including ultrareliability, high-speed operation, complex intervehicle interaction, parking in large unstructured lots, and constrained maneuvers. our approach combines a model-predictive trajectory generation algorithm for computing dynamically feasible actions with two higher level planners for generating long-range plans in both on-road and unstructured areas of the environment. in the first part of this article, we describe the underlying trajectory generator and the on-road planning component of this system. we then describe the unstructured planning component of this system used for navigating through parking lots and recovering from anomalous on-road scenarios. throughout, we provide examples and results from &ldquo;boss&rdquo; an autonomous sport utility vehicle that has driven itself over 3,000 km and competed in, and won, the darpa urban challenge. &copy; 2008 wiley periodicals, inc.
state space sampling of feasible motions for high-performance mobile robot navigation in complex environments. sampling in the space of controls or actions is a well-established method for ensuring feasible local motion plans. however, as mobile robots advance in performance and competence in complex environments, this classical motion-planning technique ceases to be effective. when environmental constraints severely limit the space of acceptable motions or when global motion planning expresses strong preferences, a state space sampling strategy is more effective. although this has been evident for some time, the practical question is how to achieve it while also satisfying the severe constraints of vehicle dynamic feasibility. the paper presents an effective algorithm for state space sampling utilizing a model-based trajectory generation approach. this method enables high-speed navigation in highly constrained and-or partially known environments such as trails, roadways, and dense off-road obstacle fields. &copy; 2008 wiley periodicals, inc.
little ben: the ben franklin racing team's entry in the 2007 darpa urban challenge. this paper describes "little ben," an autonomous ground vehicle constructed by the ben franklin racing team for the 2007 darpa urban challenge in under a year and for less than $250,000. the sensing, planning, navigation, and actuation systems for little ben were carefully designed to meet the performance demands required of an autonomous vehicle traveling in an uncertain urban environment. we incorporated an array of a global positioning system (gps)-inertial navigation system, lidars, and stereo cameras to provide timely information about the surrounding environment at the appropriate ranges. this sensor information was integrated into a dynamic map that could robustly handle gps dropouts and errors. our planning algorithms consisted of a high-level mission planner that used information from the provided route network definition and mission data files to select routes, whereas the lower level planner used the latest dynamic map information to optimize a feasible trajectory to the next waypoint. the vehicle was actuated by a cost-based controller that efficiently handled steering, throttle, and braking maneuvers in both forward and reverse directions. our software modules were integrated within a hierarchical architecture that allowed rapid development and testing of the system performance. the resulting vehicle was one of six to successfully finish the urban challenge. &copy; 2008 wiley periodicals, inc.
vision-based terrain following for an unmanned rotorcraft. experiments from biology suggest that the sensing of image motion or optic flow in insects provides a means of determining the range to obstacles and terrain. when combined with a measure of ground speed from another sensor such as global positioning system, optic flow can be used to provide a measure of an aircraft's height above terrain. we apply this principle to the control of height in a helicopter, leading to the first optic flow&ndash;based terrain-following system for an unmanned helicopter. using feedback of the height estimated from optic flow ranging to the collective pitch control of the helicopter, it has been possible to maintain terrain clearance in flights of up to 2 km. in this paper, we present flight test data demonstrating the successful application of this to an 80-kg yamaha rmax unmanned helicopter and an 8-kg electric helicopter. to complete this work, we have extended the optic flow image interpolation algorithm (i2a) to include an adaptive capability providing a greater dynamic range. the new algorithm, called the iterative image interpolation algorithm (i2a), exhibits excellent robustness in an outdoor environment and makes it suitable for flight control in a real-world environment. &copy; 2008 wiley periodicals, inc.
a perception-driven autonomous urban vehicle. this paper describes the architecture and implementation of an autonomous passenger vehicle designed to navigate using locally perceived information in preference to potentially inaccurate or incomplete map data. the vehicle architecture was designed to handle the original darpa urban challenge requirements of perceiving and navigating a road network with segments defined by sparse waypoints. the vehicle implementation includes many heterogeneous sensors with significant communications and computation bandwidth to capture and process high-resolution, high-rate sensor data. the output of the comprehensive environmental sensing subsystem is fed into a kinodynamic motion planning algorithm to generate all vehicle motion. the requirements of driving in lanes, three-point turns, parking, and maneuvering through obstacle fields are all generated with a unified planner. a key aspect of the planner is its use of closed-loop simulation in a rapidly exploring randomized trees algorithm, which can randomly explore the space while efficiently generating smooth trajectories in a dynamic and uncertain environment. the overall system was realized through the creation of a powerful new suite of software tools for message passing, logging, and visualization. these innovations provide a strong platform for future research in autonomous driving in global positioning system&ndash;denied and highly dynamic environments with poor a priori information. &copy; 2008 wiley periodicals, inc.
vision-based operations of a large industrial vehicle: autonomous hot metal carrier. hot metal carriers (hmcs) are large forklift-type vehicles used to move molten metal in aluminum smelters. this paper reports on field experiments that demonstrate that hmcs can operate autonomously and in particular can use vision as a primary sensor to locate the load of aluminum. we present our complete system but focus on the vision system elements and also detail experiments demonstrating reliable operation of the materials handling task. two key experiments are described, lasting 2 and 5 h, in which the hmc traveled 15 km in total and handled the load 80 times. &copy; 2008 wiley periodicals, inc.
caroline: an autonomously driving vehicle for urban environments. the 2007 darpa urban challenge afforded the golden opportunity for the technische universit&auml;t braunschweig to demonstrate its abilities to develop an autonomously driving vehicle to compete with the world's best. after several stages of qualification, our team carolo qualified early for the darpa urban challenge final event and was among only 11 teams from initially 89 competitors to compete in the final. we had the ability to work together in a large group of experts, each contributing his expertise in his discipline, and significant organizational, financial, and technical support by local sponsors, who helped us to become the best non-u.s. team. in this report, we describe the 2007 darpa urban challenge, our contribution, &ldquo;caroline,&rdquo; the technology, and algorithms, along with her performance in the darpa urban challenge final event on november 3, 2007. &copy; 2008 wiley periodicals, inc.
shared environment representation for a human-robot team performing information fusion. this paper addresses the problem of building a shared environment representation by a human-robot team. rich environment models are required in real applications for both autonomous operation of robots and to support human decision-making. two probabilistic models are used to describe outdoor environment features such as trees: geometric (position in the world) and visual. the visual representation is used to improve data association and to classify features. both models are able to incorporate observations from robotic platforms and human operators. physically, humans and robots form a heterogeneous sensor network. in our experiments, the human-robot team consists of an unmanned air vehicle, a ground vehicle, and two human operators. they are deployed for an information gathering task and perform information fusion cooperatively. all aspects of the system including the fusion algorithms are fully decentralized. experimental results are presented in form of the acquired multi-attribute feature map, information exchange patterns demonstrating human-robot information fusion, and quantitative model evaluation. learned lessons from deploying the system in the field are also presented. &copy; 2007 wiley periodicals, inc.
design and control of a planar haptic device with passive actuators based on passive force manipulability ellipsoid (fme) analysis. in this paper, we propose an optimal design for a passive haptic device with brakes and its control method. the inability of a brake to generate torque significantly affects the performance of a multi-dof haptic device, in that a desired force can be generated only approximately in some workspace and, in some cases, the device may become stuck contrary to the user's intention. in this research, these limitations are analyzed by means of the so-called passive force manipulability ellipsoid. through the analysis, performance indices are developed for evaluating the limitations associated with passive haptic devices. optimization is conducted for a 5-bar mechanism with redundant actuation, and a coercive force approximation scheme is developed to avoid unsmooth motion during the wall-following task along the virtual wall. it is experimentally shown that the performance in relation to the limitations is greatly improved for the optimized mechanism. &copy; 2005 wiley periodicals, inc.
development and implementation of a team of robotic tractors for autonomous peat moss harvesting. this paper describes the key system components of a team of three tractors in a peat moss harvesting operation. the behavior and actions of the tractors were designed to mimic manual harvest operations while maintaining a safe operating environment. to accomplish this objective, each of the three tractors was equipped with a bolt-on automation package, and a human operator (team leader) was given a remote user interface to command and monitor the mission. the automation package included positioning, planning, and control, as well as coordination and perception systems to preserve field harvesting order, detect obstacles, and report physical changes in the operating environment. the system performed more than 100 test field harvesting missions during one season in a working peat bog, including three complete system tests with the end users. &copy; 2009 wiley periodicals, inc.
path planning in image space for autonomous robot navigation in unstructured environments. path planning systems using graph-search algorithms such as a* usually operate in uniform plan-view occupancy grids. however, the sensors used to construct these grids observe the environment in their own sample space based on sensor type and viewpoint. in this paper we present an image space technique for path planning in unknown unstructured outdoor environments. our method differs from previous techniques in that we perform path search directly in image space&mdash;the native sensor space of the imaging sensor. after an image space path has been found, it is used for navigation in the real world. by operating at the resolution of the image sensor, image space planning facilitates accurate robot vs. obstacle localization and enables a high degree of movement precision. our image space planning techniques can potentially be used with many different kinds of sensor data, and we experimentally evaluate the use of stereo disparity and color information. we present an extension to the basic image space planning system called the cylindrical planner that simulates a 2&pi; field of view with a cylindrically shaped occupancy grid. we believe that image space planning is well suited for use in the local subsystem of a hierarchical planner and implement a hybrid hierarchical planner that utilizes the cylindrical planner as a local planning subsystem and a two-dimensional cartesian planner as the global planning subsystem. all three systems are implemented and experimentally tested on a real robot. we evaluate the failure modes of image space planning and discuss how to avoid them. we find that image space enables precise real-time, near-field planning. &copy; 2009 wiley periodicals, inc.
learning long-range vision for autonomous off-road driving. most vision-based approaches to mobile robotics suffer from the limitations imposed by stereo obstacle detection, which is short range and prone to failure. we present a self-supervised learning process for long-range vision that is able to accurately classify complex terrain at distances up to the horizon, thus allowing superior strategic planning. the success of the learning process is due to the self-supervised training data that are generated on every frame: robust, visually consistent labels from a stereo module; normalized wide-context input windows; and a discriminative and concise feature representation. a deep hierarchical network is trained to extract informative and meaningful features from an input image, and the features are used to train a real-time classifier to predict traversability. the trained classifier sees obstacles and paths from 5 to more than 100 m, far beyond the maximum stereo range of 12 m, and adapts very quickly to new environments. the process was developed and tested on the lagr (learning applied to ground robots) mobile robot. results from a ground truth data set, as well as field test results, are given. &copy; 2009 wiley periodicals, inc.
mapping, navigation, and learning for off-road traversal. the challenge in the darpa learning applied to ground robots (lagr) project is to autonomously navigate a small robot using stereo vision as the main sensor. during this project, we demonstrated a complete autonomous system for off-road navigation in unstructured environments, using stereo vision as the main sensor. the system is very robust&mdash;we can typically give it a goal position several hundred meters away and expect it to get there. in this paper we describe the main components that comprise the system, including stereo processing, obstacle and free space interpretation, long-range perception, online terrain traversability learning, visual odometry, map registration, planning, and control. at the end of 3 years, the system we developed outperformed all nine other teams in final blind tests over previously unseen terrain. &copy; 2008 wiley periodicals, inc.
cad-based automated robot programming in adhesive spray systems for shoe outsoles and uppers. most shoe manufacturing processes are not yet automated; it puts restrictions on increasing productivity. among them, adhesive application processes particularly are holding the most workers and working hours. in addition, the working environment is very poor due to the toxicity of adhesive agents. in the case of automating an adhesive application process by using a robot, robot teaching by playback is difficult to produce high productivity because the kinds of shoes to be taught mount up to several thousands. to cope with it, it is necessary to generate robot working paths automatically according to the kind, the size, or the right and the left of shoes, and also to teach the generated paths to a robot automatically. this paper presents a method to generate three-dimensional robot working paths off-line based on cad data in an automatic adhesive spray system for shoe outsoles and uppers. first, this paper describes how to extract the three-dimensional data of an outsole outline from a two-dimensional cad drawing file. second, it describes how to extract the three-dimensional data of an upper profiling line from the three-dimensional scanning data that is opened in a three-dimensional cad program. third, it describes how to generate robot working paths based on the extracted data and the nozzle setting parameters for adhesive spray. also, a series of experiments for adhesive spray is performed to verify the effectiveness of the presented methods. this study will do much for increasing productivity in shoe manufacturing as a core work of a robotic adhesive spray system. &copy; 2004 wiley periodicals, inc.
adaptive steering control of a farm tractor with varying yaw rate properties. this paper presents a novel application of a model reference adaptive control (mrac) system to control the lateral position of a farm tractor tracking a straight path. farm tractors can be configured with various implements, and the tractor yaw rate dynamics vary with each implement. it is desired that the lateral position response of the farm tractor remain consistent with respect to different implement configurations. therefore, a mrac system is implemented on the farm tractor to compensate for yaw rate plant variations by adapting the feed-forward yaw rate controller. simulation results of the algorithm are shown that display poor performance due to neglected steering actuator dynamics and saturation. modifications are made to the algorithm to account for the steering actuator properties, and more simulated results are presented that display ideal performance. finally, the mrac algorithm is implemented on a john deere 8420 farm tractor, and experimental results are presented. &copy; 2009 wiley periodicals, inc.
driving with tentacles: integral structures for sensing and motion. in this paper we describe a lidar-based navigation approach applied at both the c-elrob (european land robot trial) 2007 and the 2007 darpa urban challenge. at the c-elrob 2007 the approach was used without any prior knowledge about the terrain and without global positioning system (gps). at the urban challenge the approach was combined with a gps-based path follower. at the core of the method is a set of &ldquo;tentacles&rdquo; that represent precalculated trajectories defined in the ego-centered coordinate space of the vehicle. similar to an insect's antennae or feelers, they fan out with different curvatures discretizing the basic driving options of the vehicle. we detail how the approach can be used for exploration of unknown environments and how it can be extended to combined gps path following and obstacle avoidance allowing safe road following in case of gps offsets. &copy; 2008 wiley periodicals, inc.
reactive navigation of multiple moving agents by collaborative resolution of conflicts. in navigation that involves several moving agents or robots that are not in possession of each other's plans, a scheme for resolution of collision conflicts between them becomes mandatory. a resolution scheme is proposed in this paper specifically for the case where it is not feasible to have a priori the plans and locations of all other robots, robots can broadcast information between one another only within a specified communication distance, and a robot is restricted in its ability to react to collision conflicts that occur outside of a specified time interval called the reaction time interval. collision conflicts are resolved through velocity control by a search operation in the robot's velocity space. the existence of a cooperative phase in conflict resolution is indicated by a failure of the search operation to find velocities in the individual velocity space of the respective robots involved in the conflict. a scheme for cooperative resolution of conflicts is modeled as a search in the joint velocity space of the robots involved in conflict when the search in the individual space yields a failure. the scheme for cooperative resolution may further involve modifying the states of robots not involved in any conflict. this phenomenon is characterized as the propagation phase where cooperation spreads to robots not directly involved in the conflict. apart from presenting the methodology for the resolution of conflicts at various levels (individual, cooperative, and propagation), the paper also formally establishes the existence of the cooperative phase during real-time navigation of multiple mobile robots. the effect of varying robot parameters on the cooperative phase is presented and the increase in requirement for cooperation with the scaling up of the number of robots in a system is also illustrated. simulation results involving several mobile robots are presented to indicate the efficacy of the proposed strategy. &copy; 2005 wiley periodicals, inc.
magnebike: a magnetic wheeled robot with high mobility for inspecting complex-shaped structures. this paper describes the magnebike robot, a compact robot with two magnetic wheels in a motorbike arrangement, which is intended for inspecting the inner casing of ferromagnetic pipes with complex-shaped structures. the locomotion concept is based on an adapted magnetic wheel unit integrating two lateral lever arms. these arms allow for slight lifting off the wheel in order to locally decrease the magnetic attraction force when passing concave edges, as well as laterally stabilizing the wheel unit. the robot has the main advantage of being compact (180 &times; 130 &times; 220 mm) and mechanically simple: it features only five active degrees of freedom (two driven wheels each equipped with an active lifter stabilizer and one steering unit). the paper presents in detail design and implementation issues that are specific to magnetic wheeled robots. low-level control functionalities are addressed because they are necessary to control the active system. the paper also focuses on characterizing and analyzing the implemented robot. the high mobility is shown through experimental results: the robot not only can climb vertical walls and follow circumferential paths inside pipe structures but it is also able to pass complex combinations of 90-deg convex and concave ferromagnetic obstacles with almost any inclination regarding gravity. it requires only limited space to maneuver because turning on the spot around the rear wheel is possible. this high mobility enables the robot to access any location in the specified environment. finally the paper analyzes the maximum payload for different types of environment complexities because this is a key feature for climbing robots and provides a security factor about the risk of falling and slipping. &copy; 2009 wiley periodicals, inc.
optimal robot arm control using the minimum variance model. models of human movement from computational neuroscience provide a starting point for building a system that can produce flexible adaptive movement on a robot. there have been many computational models of human upper limb movement put forward, each attempting to explain one or more of the stereotypical features that characterize such movements. while these models successfully capture some of the features of human movement, they often lack a compelling biological basis for the criteria they choose to optimize. one that does provide such a basis is the minimum variance model (and its extension&mdash;task optimization in the presence of signal-dependent noise). here, the variance of the hand position at the end of a movement is minimized, given that the control signals on the arm's actuators are subject to random noise with zero mean and variance proportional to the amplitude of the signal. since large control signals, required to move fast, would have higher amplitude noise, the speed-accuracy trade-off emerges as a direct result of the optimization process. we chose to implement a version of this model that would be suitable for the control of a robot arm, using an optimal control scheme based on the discrete-time linear quadratic regulator. this implementation allowed us to examine the applicability of the minimum variance model to producing humanlike movement. in this paper, we describe our implementation of the minimum variance model, both for point-to-point reaching movements and for more complex trajectories involving via points. we also evaluate its performance in producing humanlike movement and show its advantages over other optimization based models (the well-known minimum jerk and minimum torque-change models) for the control of a robot arm. &copy; 2005 wiley periodicals, inc.
robust vision-based underwater homing using self-similar landmarks. next-generation autonomous underwater vehicles (auvs) will be required to robustly identify underwater targets for tasks such as inspection, localization, and docking. given their often unstructured operating environments, vision offers enormous potential in underwater navigation over more traditional methods; however, reliable target segmentation often plagues these systems. this paper addresses robust vision-based target recognition by presenting a novel scale and rotationally invariant target design and recognition routine based on self-similar landmarks that enables robust target pose estimation with respect to a single camera. these algorithms are applied to an auv with controllers developed for vision-based docking with the target. experimental results show that the system performs exceptionally on limited processing power and demonstrates how the combined vision and controller system enables robust target identification and docking in a variety of operating conditions. &copy; 2008 wiley periodicals, inc.
transmission line maintenance robots capable of crossing obstacles: state-of-the-art review and challenges ahead. power line inspection and maintenance already benefit from developments in mobile robotics. this paper presents a comprehensive review of the state of the art. it focuses on mobile robots designed to cross obstacles found on a typical transmission line while using the conductor as support for traveling. promising areas of research and development as well as challenges that remain to be solved are discussed with a view to developing fully autonomous technologies. maintenance tasks, including inspection and repairs, are identified as high-value applications in transmission live-line work. conclusions are drawn from experience, and the future of mobile robotics applied to transmission line maintenance is discussed. &copy; 2009 wiley periodicals, inc.
vision-based navigation through urban canyons. we address the problem of navigating unmanned vehicles safely through urban canyons in two dimensions using only vision-based techniques. two commonly used vision-based obstacle avoidance techniques (namely stereo vision and optic flow) are implemented on an aerial and a ground-based robotic platform and evaluated for urban canyon navigation. optic flow is evaluated for its ability to produce a centering response between obstacles, and stereo vision is evaluated for detecting obstacles to the front. we also evaluate a combination of these two techniques, which allows a vehicle to detect obstacles to the front while remaining centered between obstacles to the side. through experiments on an unmanned ground vehicle and in simulation, this combination is shown to be beneficial for navigating urban canyons, including t-junctions and 90-deg bends. experiments on a rotorcraft unmanned aerial vehicle, which was constrained to two-dimensional flight, demonstrate that stereo vision allowed it to detect an obstacle to the front, and optic flow allowed it to turn away from obstacles to the side. we discuss the theory behind these techniques, our experience in implementing them on the robotic platforms, and their suitability to the urban canyon navigation problem. &copy; 2009 wiley periodicals, inc.
toward elevated agrobotics: development of a scaled-down prototype for visually guided date palm tree sprayer. agricultural operations at great heights are typically laborious, expensive, and dangerous for human workers. spraying and pollinating date palm trees, for instance, is currently done manually by a team of several workers from a platform lifted 18 m or more above the ground. this method is extremely unsafe, and many accidents have occurred due to instability when the platform is in a lifted position. in this paper we present the concept of an autonomous field robot that will effectively and accurately spray and pollinate date clusters. a scaled-down prototype has been designed and consists of a visually controlled robotic arm that guides the jet of a mounted sprayer directly to the date clusters completely autonomously and from a short distance. rather than requiring an expensive dedicated platform, this robotic apparatus can be towed by a standard tractor operated by a single driver, with no human worker operating in the heights. this system can minimize risk of injury, significantly save manpower, and deliver the spray with maximum accuracy, thereby reducing chemical disposal. the spraying guidance system is based on a proportional controller that uses feedback from an image processing system combined with a small dead band. the system was modeled mathematically, and the effect of each component on overall performance was evaluated by simulation. results were used for tuning the experimental system controller parameters. experiments were performed to evaluate the tracking performance of the visually guided tracking system on a single tree and a 10-m-long runway at a distance of 6 m. these dimensions were inspired by the conditions at a typical orchard. during the experiment the sprayer was towed along the runway 19 times, during which the speed of the wagon was varied between 0.7 km-h (0.2 m-s) and 12 km-h (3.3 m-s). experimental results indicate that up to a wagon ve1ocity of 1.25 m-s the tracking error was reasonably low and stayed below 10 deg from the center of the target (typical date spraying speed is 1.1 m-s). however, at higher speeds the tracking quality reduced progressively and some drift (i.e., accumulated error) was noticed in the pan axis due to image processing speed. the simulations and experiments with a scaled-down prototype show feasibility of the presented method and demonstrate how this new approach facilitates more efficient high-altitude agricultural robotics. &copy; 2009 wiley periodicals, inc.
learning outdoor mobile robot behaviors by example. we present an implementation and analysis of a real-time, online, supervised learning system for nonparametrically learning behaviors from a human trainer on a mobile robot in outdoor environments. this approach enables a human operator to train and tune robot behaviors simply by driving the robot with a remote control. hand-designed behaviors for outdoor environments often require many parameters, and complicated behaviors can be difficult or impossible to specify with a manageable number of parameters. furthermore, their design requires knowledge of the robot's internal models and knowledge of the environment in which the behaviors will be used. in real-world scenarios, we can design new behaviors using our learning system much more quickly than we can write hand-crafted behaviors. we present the results of training the robot to execute several specialized and general-purpose behaviors, including traversing a slalom, staying near &ldquo;cover,&rdquo; navigating on paths, navigating in an obstacle field, and general-purpose navigation. our system learns and executes most of these behaviors well after 1&ndash;4 h of operator training time. in quantitative tests, the learned behavior is not as robust as a hand-crafted behavior but often completes obstacle courses more quickly. additionally, we identify the factors that influence the effectiveness of this approach and investigate the properties of the training data provided by the human trainer. on the basis of our analyses, we suggest future work to ensure sufficient training, handle conflicting training examples, model robot dynamics, and further investigate dimensionality reduction of perception features. &copy; 2009 wiley periodicals, inc.
terrain adaptive navigation for planetary rovers. this paper describes the design, implementation, and experimental results of a navigation system for planetary rovers called terrain adaptive navigation (tanav). this system was designed to enable greater access to and more robust operations within terrains of widely varying slippage. the system achieves this goal by using onboard stereo cameras to remotely classify surrounding terrain, predict the slippage of that terrain, and use this information in the planning of a path to the goal. this navigation system consists of several integrated techniques: goodness map generation, terrain triage, terrain classification, remote slip prediction, path planning, high-fidelity traversability analysis, and slip-compensated path following. results from experiments with an end-to-end onboard implementation of the tanav system in a mars analog environment are shown and compared to results from experiments with a more traditional navigation system that does not account for terrain properties. &copy; 2009 wiley periodicals, inc.
global planning on the mars exploration rovers: software integration and surface testing. in january 2004, nasa's twin mars exploration rovers (mers), spirit and opportunity, began searching the surface of mars for evidence of past water activity. to localize and approach scientifically interesting targets, the rovers employ an onboard navigation system. given the latency in sending commands from earth to the martian rovers (and in receiving return data), a high level of navigational autonomy is desirable. autonomous navigation with hazard avoidance (autonav) is currently performed using a local path planner called gestalt (grid-based estimation of surface traversability applied to local terrain) that incorporates terrain and obstacle information generated from stereo cameras. gestalt works well at guiding the rovers around narrow and isolated hazards; however, it is susceptible to failure when clusters of closely spaced, nontraversable rocks form extended obstacles. in may 2005, a new technology task was initiated at the jet propulsion laboratory to address this limitation. specifically, a version of the field d* global path planner was integrated into mer flight software, enabling simultaneous local and global planning during autonav. a revised version of autonav was then uploaded to the rovers during the summer of 2006. in this paper we describe how this integration of global planning into the mer flight software was performed and provide results from both the mer surface system test bed rover and five fully autonomous runs by opportunity on mars. &copy; 2009 wiley periodicals, inc.
image-based path planning for outdoor mobile robots. mobile robots operating in natural terrain need some sort of long-range perception in order to navigate efficiently. whereas ladar is a commonly used sensor on such systems, providing range data out to 25 m and beyond, we have instead focused on what information can be extracted from vision. our robot has only two stereo camera pairs for terrain sensing; they provide reliable stereo data up to 5 m away, but this is not enough to prevent myopic behavior. to overcome this problem, we have developed a novel approach to navigation using monocular imagery by planning a path in the image space. we take a monocular image and apply a learned color-to-cost mapping to transform the raw image into a cost image. then, after a pseudo-configuration-space transform, we search for a pixel-to-pixel path from a point in front of the robot to the projected goal point in the cost image. our implementation has been shown to react to obstacles at a range of 93 m, far beyond the range of our stereo perception. we describe the details of our method and results from testing under the darpa learning applied to ground robots (lagr) program and discuss the characteristics and trade-offs of our approach. &copy; 2009 wiley periodicals, inc.
autonomous off-road navigation with end-to-end learning for the lagr program. we describe a fully integrated real-time system for autonomous off-road navigation that uses end-to-end learning from onboard proprioceptive sensors, operator input, and stereo cameras to adapt to local terrain and extend terrain classification into the far field to avoid myopic behavior. the system consists of two learning algorithms: a short-range, geometry-based local terrain classifier that learns from very few proprioceptive examples and is robust in many off-road environments; and a long-range, image-based classifier that learns from geometry-based classification and continuously generalizes geometry to appearance, making it effective even in complex terrain and varying lighting conditions. in addition to presenting the learning algorithms, we describe the system architecture and results from the learning applied to ground robots (lagr) program's field tests. &copy; 2008 wiley periodicals, inc.
corn plant sensing using real-time stereo vision. though some two-dimensional (2d) machine vision&ndash;based systems for early-growth-stage corn plant sensing exist, some of their shortcomings are difficult to overcome. the greatest challenge comes from separating individual corn plants with overlapped plant canopies. with 2d machine vision, variation in outdoor lighting conditions and weeds in the background also pose difficulties in corn plant identification. adding the depth dimension has the potential to improve the performance of such a sensing system. a new corn plant sensing system using a real-time stereo vision system was investigated in this research. top-view depth images of corn plant canopy were acquired. by processing the depth images, the algorithm effectively updated the plant skeleton structures and finally recognized individual corn plants and detected their center positions. the stereo vision system was tested over corn plants of v2&ndash;v3 growth stages in both laboratory and field conditions. experimental results showed that the stereo vision system was capable of detecting both separated and overlapped corn plants. during the field test, 96.7&percnt; of the corn plants were correctly detected, and plant center positions were estimated with maximum distance errors of 5 and 1 cm for 74.6&percnt; and 62.3&percnt; of detections, respectively. &copy; 2009 wiley periodicals, inc.
toward extraplanetary under-ice exploration: robotic steps in the arctic. this paper describes the design and use of two new autonomous underwater vehicles, jaguar and puma, which were deployed in the summer of 2007 at sites at 85&deg;n latitude in the ice-covered arctic ocean to search for hydrothermal vents. these robots are the first to be deployed and recovered through ice to the deep ocean (>3,500 m) for scientific research. we examine the mechanical design, software architecture, navigation considerations, sensor suite, and issues with deployment and recovery in the ice based on the missions they carried out. successful recoveries of vehicles deployed under the ice require two-way acoustic communication, flexible navigation strategies, redundant localization hardware, and software that can cope with several different kinds of failure. the ability to direct an autonomous underwater vehicle via the low-bandwidth and intermittently functional acoustic channel is of particular importance. on the basis of our experiences, we also discuss the applicability of the technology and operational approaches of this expedition to the exploration of jupiter's ice-covered moon europa. &copy; 2009 wiley periodicals, inc.
learning terrain segmentation with classifier ensembles for autonomous robot navigation in unstructured environments. autonomous robot navigation in unstructured outdoor environments is a challenging area of active research and is currently unsolved. the navigation task requires identifying safe, traversable paths that allow the robot to progress toward a goal while avoiding obstacles. stereo is an effective tool in the near field, but used alone leads to a common failure mode in autonomous navigation in which suboptimal trajectories are followed due to nearsightedness, or the robot's inability to distinguish obstacles and safe terrain in the far field. this can be addressed through the use of machine learning methods to accomplish near-to-far learning, in which near-field terrain appearance and stereo readings are used to train models able to predict far-field terrain. this paper proposes to enhance existing, memoryless near-to-far learning approaches through the use of classifier ensembles that allow terrain models trained on data seen at different points in time to be preserved and referenced later. these stored models serve as memory, and we show that they can be leveraged for more effective far-field terrain classification on future images seen by the robot. a five-factor, full-factorial, repeated-measures experimental evaluation is performed on hand-labeled data sets taken directly from the problem domain. the experiments result in many statistically significant findings, the most important being that the proposed near-to-far best-k ensemble algorithm, with appropriate parameter selection, outperforms the single-model, nonensemble baseline approach in far-field terrain classification. several other findings that inform the use of near-to-far ensemble methods are also presented. &copy; 2009 wiley periodicals, inc.
slope traversal controls for planetary exploration rover on sandy terrain. in this paper, two control approaches are presented for exploration rovers traversing sandy-sloped terrain. one of the proposed controls is a model-based feed-forward control using a characteristic diagram, called a thrust-cornering characteristic diagram. it consists of various characteristic curves of wheel forces for varied wheel slip conditions. an appropriate steering maneuver for slope traversal can be found using the diagram with slope traversal criteria. the other control is a sensor-based feedback control. a key approach to this feedback control is to compensate for three types of slip, namely, the vehicle sideslip and longitudinal-lateral slips of a wheel. the feedback control calculates both steering and driving maneuvers that can compensate for these slips and also allow the rover to successfully traverse a sandy slope. the performances of these two control approaches are confirmed in slope traversal experiments using a four-wheeled rover test bed. the proposed controls are verified by quantitative evaluations of distance and orientation errors. through the experiment, it was found that the two controls have advantages and disadvantages, and the possibility of merging the model-based control and the sensor-based control is discussed. &copy; 2009 wiley periodicals, inc.
automatic guidance of a four-wheel-steering mobile robot for accurate field operations. as world population growth requires an increasing level of farm production at the same time that environmental preservation is a priority, the development of new agricultural tools and methods is required. in this framework, the development of robotic devices can provide an attractive solution, particularly in the field of autonomous vehicles. accurate automatic guidance of mobile robots in farming constitutes a challenging problem for researchers, mainly due to the low grip conditions usually found in such a context. from assisted-steering systems to agricultural robotics, numerous control algorithms have been studied to achieve high-precision path tracking and have reached an accuracy within &plusmn;10 cm, whatever the ground configuration and the path to be followed. however, most existing approaches consider classical two-wheel-steering vehicles. unfortunately, by using such a steering system, only the lateral deviation with respect to the path to be followed can be satisfactorily controlled. indeed, the heading of the vehicle remains dependent on the grip conditions, and crabwise motions, for example, are systematically observed on a slippery slope, leading to inaccurate field operations. to tackle this drawback, a four-wheel-steering (4ws) mobile robot is considered, enabling servo of both lateral and angular deviations with respect to a desired trajectory. the path tracking control is designed using an extended kinematic representation, allowing account to be taken online of wheel skidding, while a backstepping approach permits management of the 4ws structure. the result is an approach taking advantage of both rear and front steering actuations to fully compensate for sliding effects during path tracking. moreover, a predictive algorithm is developed in order to address delays induced by steering actuators, compensating for transient overshoots in curves. experimental results demonstrate that despite sliding phenomena, the mobile robot is able to automatically and accurately achieve a desired path, with lateral and angular errors, respectively, within &plusmn;10 cm and &plusmn;2 deg, whatever its shape and whatever the terrain conditions. this constitutes a promising result in efforts to define efficient tools with which to tackle tomorrow's agriculture challenge. &copy; 2009 wiley periodicals, inc.
gamma-slam: visual slam in unstructured environments using variance grid maps. this paper describes an online stereo visual simultaneous localization and mapping (slam) algorithm developed for the learning applied to ground robotics (lagr) program. the gamma-slam algorithm uses a rao&ndash;blackwellized particle filter to obtain a joint posterior over poses and maps: the pose distribution is estimated using a particle filter, and each particle has its own map that is obtained through exact filtering conditioned on the particle's pose. visual odometry is used to provide good proposal distributions for the particle filter, and maps are represented using a cartesian grid. unlike previous grid-based slam algorithms, however, the gamma-slam map maintains a posterior distribution over the elevation variance in each cell. this variance grid map can capture rocks, vegetation, and other objects that are typically found in unstructured environments but are not well modeled by traditional occupancy or elevation grid maps. the algorithm runs in real time on conventional processors and has been evaluated for both qualitative and quantitative accuracy in three outdoor environments over trajectories totaling 1,600 m in length. &copy; 2008 wiley periodicals, inc.
targeted driving using visual tracking on mars: from research to flight. this paper presents the development, validation, and deployment of the visual target tracking capability onto the mars exploration rover (mer) mission. visual target tracking enables targeted driving, in which the rover approaches a designated target in a closed visual feedback loop, increasing the target position accuracy by an order of magnitude and resulting in fewer ground-in-the-loop cycles. as a result of an extensive validation, we developed a reliable normalized cross-correlation visual tracker. to enable tracking with the limited computational resources of a planetary rover, the tracker uses the vehicle motion estimation to scale and roll the template image, compensating for large image changes between rover steps. the validation showed that a designated target can be reliably tracked within several pixels or a few centimeters of accuracy over a 10-m traverse using a rover step size of 10% of the target distance in any direction. it also showed that the target is not required to have conspicuous features and can be selected anywhere on natural rock surfaces excluding rock boundary and shadowed regions. the tracker was successfully executed on the opportunity rover near victoria crater on four distinct runs, including a single-sol instrument placement. we present the flight experiment data of the tracking performance and execution time. &copy; 2009 wiley periodicals, inc.
a multirange architecture for collision-free off-road robot navigation. we present a multilayered mapping, planning, and command execution system developed and tested on the lagr mobile robot. key to robust performance under uncertainty is the combination of a short-range perception system operating at high frame rate and low resolution and a long-range, adaptive vision system operating at lower frame rate and higher resolution. the short-range module performs local planning and obstacle avoidance with fast reaction times, whereas the long-range module performs strategic visual planning. probabilistic traversability labels provided by the perception modules are combined and accumulated into a robot-centered hyperbolic-polar map with a 200-m effective range. instead of using a dynamical model of the robot for short-range planning, the system uses a large lookup table of physically possible trajectory segments recorded on the robot in a wide variety of driving conditions. localization is performed using a combination of global positioning system, wheel odometry, inertial measurement unit, and a high-speed, low-complexity rotational visual odometry module. the end-to-end system was developed and tested on the lagr mobile robot and was verified in independent government tests. &copy; 2008 wiley periodicals, inc.
differentially constrained mobile robot motion planning in state lattices. we present an approach to the problem of differentially constrained mobile robot motion planning in arbitrary cost fields. the approach is based on deterministic search in a specially discretized state space. we compute a set of elementary motions that connects each discrete state value to a set of its reachable neighbors via feasible motions. thus, this set of motions induces a connected search graph. the motions are carefully designed to terminate at discrete states, whose dimensions include relevant state variables (e.g., position, heading, curvature, and velocity). the discrete states, and thus the motions, repeat at regular intervals, forming a lattice. we ensure that all paths in the graph encode feasible motions via the imposition of continuity constraints on state variables at graph vertices and compliance of the graph edges with a differential equation comprising the vehicle model. the resulting state lattice permits fast full configuration space cost evaluation and collision detection. experimental results with research prototype rovers demonstrate that the planner allows us to exploit the entire envelope of vehicle maneuverability in rough terrain, while featuring real-time performance. &copy; 2009 wiley periodicals, inc.
an autonomous rice transplanter guided by global positioning system and inertial measurement unit. this paper reports the development of an automated rice transplanter guided by a global positioning system and an inertia measurement unit using the controller area network bus. the actuator control command and data communication protocols comply with the iso 11783. the project aims to develop an autonomous agricultural system for operation in the paddy field. the automated rice transplanter presented in this paper is the first stage in achieving the project objective. this paper focuses on the development of sensor and main computer connections to the operating autonomous unit and the use of common control protocols for each of the automated machines. a simple steering control algorithm was used for straight traveling. the automated rice transplanter made a turn at the headland of the paddy field and moved to the next desired path. after 12 straight operations, the rms lateral deviation was observed to be less than 0.04 m and the rms heading angle error was less than 3.6 deg. &copy; 2009 wiley periodicals, inc.
ground verification of the feasibility of telepresent on-orbit servicing. in an ideal case telepresence achieves a state in which a human operator can no longer differentiate between an interaction with a real environment and a technical mediated one. this state is called transparent telepresence. the applicability of telepresence to on-orbit servicing (oos), i.e., an unmanned servicing operation in space, teleoperated from ground in real time, is verified in this paper. for this purpose, a communication test environment was set up on the ground, which involved the institute of astronautics (lrt) ground station in garching, germany, and the european space agency (esa) ground station in redu, belgium. both were connected via the geostationary esa data relay satellite artemis. utilizing the data relay satellite, a teleoperation was accomplished in which the human operator as well as the (space) teleoperator was located on the ground. the feasibility of telepresent oos was evaluated, using an oos test bed at the institute of mechatronics and robotics at the german aerospace center (dlr). the manipulation task was representative for oos and supported real-time feedback from the haptic-visual workspace. the tests showed that complex manipulation tasks can be fulfilled by utilizing geostationary data relay satellites. for verifying the feasibility of telepresent oos, different evaluation methods were used. the properties of the space link were measured and related to subjective perceptions of participants, who had to fulfill manipulation tasks. an evaluation of the transparency of the system, including the data relay satellite, was accomplished as well. &copy; 2009 wiley periodicals, inc.
a tele-experiment on rover motor control via internet. modern internet and multimedia techniques enable experiments with remote hardware. this way engineering students can gather practical experience even in areas where their own university does not have the related equipment in place. the focus of this paper is on an experiment to develop a motor controller for a remote mobile robot. implementation details of such an experiment are addressed with emphasis placed on the subject of tuning a pid controller for steering and speed adaptation of a rover. the complete experiment is conceived as a self-explaining learning unit on the web. the learning unit comprises material on theory, exercises to provide feedback to the student about his learning progress, simulations to study motor control effects, and finally the experiment with remote robot hardware. this paper presents software techniques to realize a robust system implementation, the educational considerations necessary to present the experiment material properly for the tele-education context, and experiences obtained during the use of this remote experiment in previously taught classes. &copy; 2005 wiley periodicals, inc.
manipulating deformable linear objects: sensor-based skills of adjustment motions for vibration reduction. the vibration of a deformable object is often problematic during automatic handling by robot manipulators. however, humans can often handle and damp the vibration of deformable objects with ease. this paper presents force&sol;torque sensor-based skills for handling deformable linear objects in a manner suitable to reduce acute vibration with simple human skill inspired strategies that consist of one or two adjustment motions. the adjustment motion is a simple open-loop motion that can be attached to the end of any arbitrary end-effector's trajectory. as an ordinary industrial robot's simple action, it has three periods, i.e., acceleration, constant speed, and deceleration period; it starts from a predicted time tightly close to a force&sol;moment maximum. the predicted time for the adjustment action is generated automatically on-line based on the vibration rhythm and the data sensed by a force&sol;torque sensor mounted on the robot's wrist. to find the matching point between the vibrational signal of the deformable object and a template, template matching techniques including cross-correlation and minimum squared error methods are used and compared. experiments are conducted with an industrial robot to test the new skills under various conditions. the results demonstrate that an industrial robot could perform effective vibration reduction skills with simple strategies. &copy; 2005 wiley periodicals, inc.
forces, activation and displacement prediction during free movement in the hand and forearm. this paper deals with the development of a highly realistic human hand and forearm model. the model contains 38 muscles and 24 degrees of freedom representing the joints of the system. the adopted model has to be as close as possible to the reality of the human being hand, to address several features linked to manipulation tasks, grasping objects and daily routine movements like shaving, writing, etc. in addition, a better comprehension of the biomechanical and neuromuscular behavior of the system is aimed. this will allow having a tool for the simulation of repairing surgery, acts such as tendon transfer. in this paper, we focus on the muscle forces determination for a given task. an optimization technique is used to resolve the redundant problem over the 24 joints of the system. also, a muscle model is used and is integrated in the optimization technique, in order to determine measurable values, like the activation and the displacement of each muscle in the system. the calculation is made during a real-time simulation. &copy; 2005 wiley periodicals, inc.
robot perception of impedance. this paper proposes an algorithm for robot perception of impedance, which can be used as a fundamental technique for real-time and qualitative perception of physical constraints imposed on the robot's end-effector. this algorithm (1) estimates the impedance that represents the motion-force relation of the end-effector; (2) calculates the uncertainties of the estimates; and (3) detects discontinuous changes in the impedance. the estimated impedance can be used to recognize local dynamic properties of the environment and temporary constraint conditions imposed on the end-effector. the detected discontinuities can be used to segment the manipulated tasks and to recognize the geometric structure of the environment. this method can be implemented in both autonomous and remote-controlled robots because it is designed separately from control methodologies. results of preliminary experiments are presented. &copy; 2005 wiley periodicals, inc.
the spatial conservative congruence transformation for manipulator stiffness modeling with coordinate and noncoordinate bases. this paper presents systematic methods to approach the spatial conservative congruence transformation (scct) and applies it to the stiffness transformation and matrices of robotic systems via the strategy of changing basis. through geometrical analysis, the realization of the cartesian stiffness of manipulators is shown to be basis dependent. we illustrate that the scct is conservative as well as directly represents the spatial stiffness mapping relationship for robotic stiffness control. examples of the serial manipulators are given to help one to better understand the source of the asymmetric 6&times;6 cartesian stiffness matrix in the presence of external loads using the scct algorithm. the scct suggests an explicit and generalized stiffness transformation relationship for robotic systems. &copy; 2005 wiley periodicals, inc. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
2d map-building and localization in outdoor environments. determining the pose (position and orientation) of a vehicle at any time is termed localization and is of paramount importance in achieving reliable and robust autonomous navigation. knowing the pose it is possible to achieve high level tasks such as path planning. a new map-based algorithm for the localization of vehicles operating in harsh outdoor environments is presented in this article. a map building algorithm using observations from a scanning laser rangefinder is developed for building a polyline map that adequately captures the geometry of the environment. using this map, the iterative closest point (icp) algorithm is employed for matching laser range images from the rangefinder to the polyline map. once correspondences are established, an extended kalman filter (ekf) algorithm provides reliable vehicle state estimates using a nonlinear observation model based on the vertices of the polyline map. data gathered during field trials in an outdoor environment is used to test the efficiency of the proposed icp-ekf algorithm in achieving the localization of a four-wheel drive (4wd) vehicle. &copy; 2005 wiley periodicals, inc.
fuzzy control of robot manipulator with a flexible tool. in some tasks, a rigid robot manipulator handles a long, slender, and flexible tool, which usually has not been equipped with vibration measuring devices. this situation makes a different tool tip position control problem. in this paper, a new method will be presented for simultaneous tip position and vibration suppression control of a flexible tool on a rigid-link 3-dof robot. this approach uses fuzzy logic rule-based controllers without using any sensors and actuators on the tool or a priori knowledge about the tool. numerical simulation of robot and tool set has been accomplished and results support the fact that designed fuzzy controllers perform remarkably well in reducing vibrations and precision guidance of robot tool tip for tracking various trajectories. &copy; 2005 wiley periodicals, inc.
kinematic path-tracking of mobile robot using iterative learning control. this paper develops a kinematic path-tracking algorithm for a nonholonomic mobile robot using an iterative learning control (ilc) technique. the proposed algorithm produces a robot velocity command, which is to be executed by the proper dynamic controller of the robot. the difference between the velocity command and the actual velocity acts as state disturbances in the kinematic model of the mobile robot. given the kinematic model with state disturbances, we present an ilc-based path-tracking algorithm. an iterative learning rule with both predictive and current learning terms is used to overcome uncertainties and the disturbances in the system. it shows that the system states, outputs, and control inputs are guaranteed to converge to the desired trajectories with or without state disturbances, output disturbances, or initial state errors. simulations and experiments using an actual mobile robot verify the feasibility and validity of the proposed learning algorithm. &copy; 2005 wiley periodicals, inc.
safe planning for human-robot interaction. this paper presents a strategy for improving the safety of human-robot interaction by minimizing a danger criterion during the planning stage. this strategy is one part of the overall methodology for safe planning and control in human-robot interaction. the focus application is a hand-off task between an articulated robot and an inexpert human user. two formulations of the danger criterion are proposed: a criterion assuming independent safety-related factors, and a criterion assuming mutually dependent factors. simulations of the proposed planning strategy are presented for both 2d and 3d robots. the results indicate that a criterion based on scaled mutually dependent factors such as the robot inertia and the human robot distance generates safe, feasible paths for interaction. &copy; 2005 wiley periodicals, inc.
compliant grasping with passive forces. because friction is central to robotic grasp, developing an accurate and tractable model of contact compliance, particularly in the tangential direction, and predicting the passive force closure are crucial to robotic grasping and contact analysis. this paper analyzes the existence of the uncontrollable grasping forces (i.e., passive contact forces) in enveloping grasp or fixturing, and formulates a physical model of compliant enveloping grasp. first, we develop a locally elastic contact model to describe the nonlinear coupling between the contact force with friction and elastic deformation at the individual contact. further, a set of &ldquo;compatibility&rdquo; equations is given so that the elastic deformations among all contacts in the grasping system result in a consistent set of displacements of the object. then, combining the force equilibrium, the locally elastic contact model, and the &ldquo;compatibility&rdquo; conditions, we formulate the natural compliant model of the enveloping grasp system where the passive compliance in joints of fingers is considered, and investigate the stability of the compliant grasp system. the crux of judging passive force closure is to predict the passive contact forces in the grasping system, which is formulated into a nonlinear least square in this paper. using the globally convergent levenberg-marquardt method, we predict contact forces and estimate the passive force closure in the enveloping grasps. finally, a numerical example is given to verify the proposed compliant enveloping grasp model and the prediction method of passive force closure. &copy; 2005 wiley periodicals, inc.
sensory-motor control mechanism for reaching movements of a redundant musculo-skeletal arm. this paper studies the human arm's sensory-motor control mechanism in reaching movements. first, we formulate both the kinematics and dynamics of a two-link planar arm model with six redundant muscles. the nonlinear muscle dynamics is modeled based on several biological understandings. we then show the stability of the overall system and perform some numerical simulations. by considering the internal forces induced by the redundant muscles, we show that the damping factors in each joint can be regulated, and as the result, it can realize humanlike quasistraight line reaching movements. in addition, we also propose the gravity compensation method at the muscle input level and present the result of numerical simulation to verify the usefulness of this method. &copy; 2005 wiley periodicals, inc.
geometrical conditions for the design of partial or full isotropic hexapods. this paper presents a methodology for the design of pkms (parallel kinematic machines) with defined isotropy and stiffness. partial isotropy or full isotropy can be achieved by suitable design choices. the former is useful for five axis applications, while the latter for six axis manipulators. the paper summarizes the concept of full and partial isotropy, and for a wide class of hexapods defines in analytical form the conditions to achieve it exactly. these conditions can be used to design isotropic parallel manipulators. the methodology requires that the six legs have to be divided into two groups (terns). the legs belonging to one tern are mutually identical and are positioned with radial symmetry with respect to the tcp (tool center point). the paper shows that the manipulator structure can be defined in term of 13 design parameters, the value of six of them are chosen in order to achieve the required isotropy and stiffness properties, while the remaining seven parameters can be used to optimize the structure. the design criterion here presented assures that stiffness isotropy, force, and velocity isotropy are all achieved contemporarily. this methodology can be practically applied to a large family of hexapods. &copy; 2005 wiley periodicals, inc.
telerobotic systems design based on real-time corba. a new class of telerobotic applications is making its way into research laboratories, fine arts or science museums, and industrial installations. virtual laboratories and remote equipment maintenance are examples of these applications, which are built exploiting distributed computing systems and internet technologies. distributed computing technologies provide several advantages to telerobotic applications, such as dynamic and multiuser access to remote resources and arbitrary user locations. nonetheless, building these applications remains a substantial endeavor, especially when performance requirements must be met. the aim of this paper is to investigate how mainstream and advanced features of the corba object-oriented middleware can be put to work to meet the requirements of novel telerobotic applications. we show that real-time corba extensions and asynchronous method invocation of corba services can be relied upon to meet performance and functional requirements, thereby enabling teleoperation on local area networks. furthermore, corba services for concurrency control and large-scale data distribution enable geographic-scale access for robot teleprogramming. limitations in the currently available implementations of the corba standard are also discussed, along with their implications. the effectiveness and suitability for telerobotic applications of several corba mechanisms are tested first individually and then by means of a software framework exploiting corba services and ensuring component-based development, software reuse, low development cost, fully portable real-time and communication support. a comprehensive telerobotic application built based on the framework is described in the paper and evaluated on both local and wide area networks. the application includes a robot manipulator and several sensory subsystems under concurrent access by multiple competing or collaborating operators, one of which is equipped with a multimodal user interface acting as the master device. &copy; 2005 wiley periodicals, inc.
a bio-inspired approach for regulating and measuring visco-elastic properties of a robot arm. this work focuses on interaction control of robot manipulators in unstructured environments, with special regard for situations of unpredictable contact&#x002f;noncontact transitions. it is basically addressed to those environments where a high level of robot adaptability is required and no information on the geometry of the environment is available. by pointing out the main limitations of standard interaction control schemes in managing situations of contact&#x002f;noncontact transitions, this paper proposes a new control solution that is inspired by the biological model of motor control in voluntary movements. it consists of a combination of a feedforward loop and a proportional-derivative plus gravity compensation control in the feedback loop. the control law is named coactivation-based compliance control in the joint space since a unique function, called coactivation function, is evaluated for regulating robot visco-elasticity in an unpredictably variable environment. it resumes the mechanism of adjustable visco-elastic properties acting on the agonist and antagonist muscles of a human arm. the work also proposes a methodology for evaluating performance of interaction control schemes that is based on stiffness graphical representation through ellipses. the method replicates the experimental setup used in neuroscience to measure stiffness in human limbs. it is regarded as a powerful tool for evaluating robot behavior over space and time, since it allows both a visual representation of stiffness variation during motion and a quantitative measure of robot performance. it is shown how the method can be used to evaluate a control scheme and how it can provide indications to improve a control law. in this paper, an application to the standard compliance control in the joint space and the coactivation-based compliance control is presented. &copy; 2005 wiley periodicals, inc.
stereoscopic video images for telerobotic applications. this article addresses the use of stereoscopic images in teleoperated tasks. depth perception is a key point in the ability to skillfully manipulate in remote environments. displaying three-dimensional images is a complex process but it is possible to design a teleoperation interface that displays stereoscopic images to assist in manipulation tasks. the appropriate interface for image viewing must be chosen and the stereoscopic video cameras must be calibrated so that the image disparity is natural for the observer. attention is given to the calculation of stereoscopic image disparity, and suggestions are made as to the limits within which adequate stereoscopic image perception takes place. the authors have designed equipment for image visualization in teleoperated systems. these devices are described and their performance evaluated. finally, an architecture for the transmission of stereoscopic video images via network is proposed, which in the future will substitute for current image processing devices. &copy; 2005 wiley periodicals, inc.
case study: a novel surface scanning system. this paper presents the design and development of a novel surface scanning system that employs an array of 144 equal spaced probing pins for capturing the surface coordinates of an object simultaneously. operation of the system is computer driven. the captured surface data is saved in a point-cloud data file, which can be postprocessed by a cad system to construct a surface model of the scanned object. the created cad model can be used to facilitate the design and making of thermoforming moulds. the thermoforming moulds are to be used for forming plastic sheets for packaging consumer products for retail selling. a prototype of the system has been built. test results demonstrate that the developed system can satisfy the technical and economical requirements of the packaging industry. &copy; 2005 wiley periodicals, inc.
formulation of dynamics, actuation, and inversion of a three-dimensional two-link rigid body system. in this paper, three issues related to three-dimensional multilink rigid body systems are considered: dynamics, actuation, and inversion. based on the newton-euler equations, a state space formulation of the dynamics is discussed that renders itself to inclusion of actuators, and allows systematic ways of stabilization and construction of inverse systems. the development here is relevant to robotic systems, biological modeling, humanoid studies, and collaborating man-machine systems. the recursive dynamic formulation involves a method for sequential measurement and estimation of joint forces and couples for an open chain system. the sequence can start from top downwards or from the ground upwards. three-dimensional actuators that produce couples at the joints are included in the dynamics. inverse methods that allow estimation of these couples from the kinematic trajectories and physical parameters of the system are developed. the formulation and derivations are carried out for a two-link system. digital computer simulations of a two-rigid body system are presented to demonstrate the feasibility and effectiveness of the methods. &copy; 2005 wiley periodicals, inc.
kinetostatic modeling of the clearance-affected prismatic pair. the presence of clearance in the kinematic pairs of mechanisms has a strong influence on the mechanism performances. where positioning tasks are concerned, clearance can be considered as one of the most relevant error sources, since it affects both accuracy and repeatability. the development of predictive models then becomes relevant, suitable for assessing in advance the influence of clearance and for correcting unacceptable effects. several deterministic techniques assessing the accuracy of clearance-affected mechanisms have been proposed in the literature; these techniques require the development of kinetostatic models for clearance-affected pairs. this paper presents a modeling for clearance-affected prismatic pairs. such a model determines the three-dimensional displacement between the pairing elements in the prismatic pair, and relates it to the load acting on the pair. since the displacement depends strongly on the actual pair design, the model is described in detail for a particular pair geometry; in principle, however, this approach could be used for any geometry. the proposed model may be implemented in kinematic, kinetostatic, or dynamic analyses as well, with the purpose of computing the influence of clearance on the position and orientation error of any link of a mechanism. &copy; 2005 wiley periodicals, inc.
generation of natural motions for redundant multi-joint systems: a differential-geometric approach based upon the principle of least actions. this article challenges bernstein's problem of redundant degrees of freedom (dof) that remains unsolved from both the standpoints of physiology and robotics. a rather simpler but difficult control problem of movements of human-like multi-joint reaching with excess dof is analyzed from newtonian mechanics and differential geometry. it is shown that, regardless of ill-posedness of inverse kinematics for such a redundant system, a simpler control signal composed of a well-tuned (synergistic) combination of task-space position feedback (corresponding to spring-like forces) and joint velocity feedback (viscous-like forces) leads to a skilled motion of reaching in a natural way without solving inverse kinematics or dynamics. fundamental characteristics of human skilled multi-joint movements such as (1) generation of a quasi-straight line trajectory of the endpoint and (2) a little &ldquo;variability&rdquo; in task space but notable &ldquo;variability&rdquo; in joint space are analyzed from the concepts of &ldquo;stability on an ep (equilibrium-point) manifold&rdquo; and &ldquo;transferability to an ep submanifold.&rdquo; it is claimed that the control signal exerts torques on joints of the whole arm just like a single virtual-spring drawing the endpoint of the arm to the target while giving a specified viscosity to each joint. this leads to an interpretation that skilled reaching movements emerge through formation of a set of neuro-motor signals exerting relevant group of muscles to generate a total potential energy equivalent to that of the spring. discussions are presented on how such control signals in case of human reaching can be generated in a feedforward manner with capability of anticipatory adjustments of stiffness. &copy; 2005 wiley periodicals, inc.
reliable computation of minimum-time motions for manipulators moving in obstacle fields using a successive search for minimum-overload trajectories. in this paper we present a practical method for finding obstacle-free minimum-time motions for manipulators subject to the limits of velocity-dependent actuator forces. an optimal motion-planning problem is converted into a finite-dimensional nonlinear programming problem by means of parameter optimization with quintic b-splines. we introduce the concept of the minimum-overload trajectory in which the motion time is specified to be faster than the actuators can handle, and the actuator overloads are minimized with the motion time fixed. by successive searches for minimum-overload trajectories, minimum-time motions are determined for three example manipulators without simplifying any of the kinematic, dynamic or geometric properties of the manipulators or the obstacles. in the resultant minimum-time motions, almost all of the joint actuators are close to saturation during the motions. &copy; 2005 wiley periodicals, inc.
from task parameters to motor synergies: a hierarchical framework for approximately optimal control of redundant manipulators. we present a hierarchical framework for approximately optimal control of redundant manipulators. the plant is augmented with a low-level feedback controller, designed to yield input-output behavior that captures the task-relevant aspects of plant dynamics but has reduced dimensionality. this makes it possible to reformulate the optimal control problem in terms of the augmented dynamics, and optimize a high-level feedback controller without running into the curse of dimensionality. the resulting control hierarchy compares favorably to existing methods in robotics. furthermore, we demonstrate a number of similarities to (nonhierarchical) optimal feedback control. besides its engineering applications, the new framework addresses a key unresolved problem in the neural control of movement. it has long been hypothesized that coordination involves selective control of task parameters via muscle synergies, but the link between these parameters and the synergies capable of controlling them has remained elusive. our framework provides this missing link. &copy; 2005 wiley periodicals, inc.
type synthesis of 5-dof parallel manipulators based on screw theory. with the introduction of virtual chains to represent the motion patterns of 5-dof motions, a classification of 5-dof pms (parallel manipulators) is proposed at first. a general method for the type synthesis of 5-dof pms is then proposed based on screw theory and using the concept of virtual chains. the type synthesis of us-equivalent pms is presented in detail to show the application of the proposed approach. us-equivalent pms are the parallel counterparts of the 5-dof us serial manipulators. for a us-equivalent pm, the moving platform can rotate arbitrarily about a point moving along a spherical surface. the type synthesis of legs for us-equivalent pkcs (parallel kinematic chains), the type synthesis of us-equivalent pkcs, as well as the selection of actuated joints of us-equivalent pms are dealt with in sequence. us-equivalent pkcs with and without inactive joints are synthesized. several us-equivalent pms as well as other classes of 5-dof pms with identical type of legs are obtained. &copy; 2005 wiley periodicals, inc.
bio-mimetic trajectory generation using a neural time-base generator. this paper presents a neural time-base generator (tbg) that can generate a family of neural control signals with a controllable finite duration and bell-shaped velocity profile. then, a bio-mimetic trajectory generation method using the neural tbg model is explained. using the proposed model, the generation ability of human-like trajectories is examined through comparisons between computer simulations and human arm trajectories during reaching movements according to the curvature of constrained trajectories. &copy; 2005 wiley periodicals, inc.
grasping determination experiments within the uji robotics telelab. as a result of new technology becoming available it is increasingly possible to develop more natural human-robot interfaces. in particular, interaction channels based on both voice and synthesis recognition, and combined with other sensors, mainly computer vision, are now implemented in current robots. these capabilities enable a more natural face-to-face dialogue in the human-robot interaction. currently, they are demonstrating their potential in many service robot applications, such as museums, hospitals, and so on. one area where these new forms of interaction have been extensively tested recently is within the educational robotics context. this article addresses a novel user-interface implemented in such a system developed in our lab, namely &ldquo;the uji robotics telelab&rdquo;, where the word uji is the acronym for the name of our university. in order to develop this kind of complex system, several years of intensive research have been necessary in both multimedia tutoring systems and robotics. the principal motive for the project was the experimentation and validation of a complete telelaboratory, including an internet-based robot system, with off-line and on-line control possibilities, and other different facilities (e.g., multimedia tutorial, chat channel, etc.) aimed at teaching undergraduate students in the robotics subject in our university campus. finally, taking into account experience gained from using this system for regular undergraduate courses in robotics, new facilities have been implemented, and results showing the user performance, usability, and reliability of this novel contribution are discussed, including its advantages and limitations. &copy; 2005 wiley periodicals, inc.
potential-based path planning for robot manipulators. in this paper, a potential-based path-planning algorithm for a high dof robot manipulator is proposed. unlike some c-space-based approaches, which often require expensive preprocessing for the construction of the c-space, the proposed approach uses the workspace information directly. the approach computes, similar to that done in electrostatics, repulsive force and torque between objects in the workspace. a collision-free path of a manipulator will then be obtained by locally adjusting the manipulator configuration to search for minimum potential configurations using that force and torque. the proposed approach is efficient because these potential gradients are analytically tractable. simulation results show that the proposed algorithm works well, in terms of computation time and collision avoidance, for manipulators up to 9 degrees of freedom (dof). &copy; 2005 wiley periodicals, inc.
adaptive position and orientation regulation for the camera-in-hand problem. this paper considers the camera-space position and orientation regulation problem for the camera-in-hand problem via visual serving in the presence of parametric uncertainty associated with the robot dynamics and the camera system. specifically, an adaptive robot controller is developed that forces the end-effector of a robot manipulator to move such that the position and orientation of an object are regulated to a desired position and orientation in the camera-space, despite parametric uncertainty throughout the entire robot-camera system. an extension is also provided that illustrates how slight modifications can be made to the camera-in-hand control law to achieve adaptive position and orientation tracking of the end-effector in the camera-space for a fixed-camera configuration. simulation results are provided to illustrate the performance of the adaptive, camera-in-hand controller. &copy; 2005 wiley periodicals, inc.
neural virtual sensors for terrain adaptation of walking machines. when walking in realistic conditions, accurate, reliable sensorial information is critical to ensure the safe operation of legged robots. that means a large number of sensors, cabling, and electronic systems must be used, complicating the robot. on the other hand, the great complexity of the hardware of walking machines is one of the main obstacles preventing the introduction of this kind of vehicle in real applications; consequently this hardware should be simplified. these antagonistic requirements can be reconciled by the use of what are called virtual sensors. this paper addresses the design of virtual sensors for terrain adaptation developed with the aims of simplifying the hardware of the walking machine or increasing the reliability of the sensorial information available. these virtual sensors are based on neural networks and can estimate the forces exerted by the feet from data extracted from joint-position sensors, which are mandatory in all robotic systems. the force estimates are used to detect foot&#x002f;ground contact. some experiments carried out with the silo4 walking robot are reported to prove the efficacy of this method. &copy; 2005 wiley periodicals, inc.
a new revolute robot manipulator adapting the closed-chain mechanism. conventional robot manipulators actuated by motors with conventional speed reducers such as the harmonic drive or rv have weakness in the load capacity since the speed reducers are not stiff enough. to overcome this, we propose a four-bar-link actuator driven by the ball screw, which has a high stiffness and high torque transmission ability, and propose a new type of four degree-of-freedom revolute robot manipulator adapting the proposed actuators. the base joint of the robot is actuated by the motor with the conventional speed reducer, and the other joints are actuated by the proposed actuators. the kinematics and dynamics of the robot are analyzed in the joint coordinate and in the cartesian coordinate. for the performance tests of the robot, a four degree-of-freedom revolute robot was built. through the performance tests, the results of superior load capacity and positioning accuracy are presented. &copy; 2005 wiley periodicals, inc.
motion capture from demonstrator's viewpoint and its application to robot teaching. in this paper, we propose a kind of &ldquo;teaching by demonstration&rdquo; method, aiming at its application to humanoid robots at home in the future. the demonstrator's motion is captured by a pair of stereo cameras mounted on his&sol;her head, locating very close to his&sol;her eyes. by tracking the landmarks attached to the demonstrator's hand and the working environment, one can estimate not only the demonstrator's hand motion but also his&sol;her head motion, which can be used for the active vision system. experimental result shows the effectiveness of the proposed framework. &copy; 2005 wiley periodicals, inc.
a new family of hybrid 4-dof parallel mechanisms with two platforms and its application to a footpad device. this paper proposes a new family of 4-degrees-of-freedom (dof) parallel mechanisms with two platforms and its application to a footpad device that can simulate the spatial motions of the human foot. the new mechanism consists of front and rear platforms, and three limbs. two limbs with 6-dof serial joints ( <und>p</und>-s-p-p) are attached to each platform and are perpendicular to the base plate, while the middle limb is attached to the revolute joint that connects the front and rear platforms. the middle limb is driven by the 2-dof driving mechanism that is equivalent to active serial prismatic and revolute joints ( <und>pe</und>- <und>re</und>), or prismatic and prismatic joints ( <und>pe</und>- <und>pe</und>) with two base-fixed prismatic actuators. since the middle limb perpendicular to the base plate has 3-dof serial joints ( <und>pe</und>- <und>re</und>-r or <und>pe</und>- <und>pe</und>-r), two new 4-dof parallel mechanisms with two platforms can generate pitch motion of each platform, and roll and heave motions (1t-3r) or pitch motion of each platform and two translational motions (2t-2r) at both platforms, according to the type of the 2-dof driving mechanism. kinematic analyses of the 1t-3r mechanism were performed, including inverse and forward kinematics and velocity analysis. based on the 1t-3r mechanism, a footpad device was designed to generate foot trajectories for natural walking. &copy; 2005 wiley periodicals, inc.
visual map-less navigation based on homographies. we introduce a method for autonomous robot navigation based on homographies computed between the current image and images taken in a previous teaching phase with a monocular vision system. the features used to estimate the homography are vertical lines automatically extracted and matched. from homography, the underlying motion correction between the reference path and the current robot location is computed. the proposed method, which uses a sole calibration parameter, has turned out to be especially useful to correct heading and lateral displacement, which are critical in systems based on odometry. we have tested the proposal in simulation, and with real images. besides, the visual system has been integrated into an autonomous wheelchair for handicapped, working in real time with robustness. &copy; 2005 wiley periodicals, inc.
a natural redundancy-resolution for 3-d multi-joint reaching under the gravity effect. a simple control method for 3-dimensional multi-joint reaching movements under redundancy of degrees of freedom (dof) is proposed, which need neither introduce any performance index to solve inverse kinematics uniquely nor calculate pseudo-inverse of the jacobian matrix of task coordinates with respect to joint coordinates. the proposed control signal is composed of linear superposition of three terms: (1) angular-velocity feedback for damping shaping, (2) task-space position error feedback with a single stiffness parameter, and (3) compensation for gravity force on the basis of estimates for uncertain parameters of the potential energy without calculation any inverse joint position to the target in task space. through a theoretical analysis of the closed-loop dynamics and a variety of computer simulations by using a whole arm model with five dofs, the importance of synergistic adjustments of damping factors as well as its relation to selection of the stiffness parameter is pointed out. it is shown that if damping factors are chosen synergistically corresponding to the inertia matrix at the initial time and the stiffness parameter then the endpoint converges asymptotically to the target position and reaches it smoothly without incurring any self-motion. &copy; 2005 wiley periodicals, inc.
online robotic experiments for tele-education at the university of pisa. in this paper we describe work being done at our department to make the robotics laboratory accessible to students and colleagues to execute and watch real-time experiments at any time and from anywhere. we describe a few different installations and highlight the underlying philosophy, which is aimed at enlarging the lab in all the dimensions of space, time, and available resources, through the use of internet technologies. in particular, four experimental setups with hardware and software architecture description are presented: the dc motor, the magnetic levitator, the nonholomonic motion planner (nhmp), and the graphic environment tool. &copy; 2005 wiley periodicals, inc.
collision-free control of robotic manipulators in the task space. this paper addresses the problem of position control of robotic manipulators in the task space with obstacles. a computationally simple class of task space regulators consisting of a transpose jacobian controller plus an integral term including the task error and the gradient of a penalty function generated by obstacles is proposed. the lyapunov stability theory is used to derive the control scheme. through the use of the exterior penalty function approach, collision avoidance of the robot with obstacles is ensured. the performance of the proposed control strategy is illustrated through computer simulations for a direct-drive arm of a scara type manipulator operating in both an obstacle-free task space and a task space including obstacles. &copy; 2005 wiley periodicals, inc.
analyzing unidentified locked-joint failures in kinematically redundant manipulators. robots are frequently used for operations in hostile environments. the very nature of these environments, however, increases the likelihood of robot failures. common failure-tolerance techniques rely on effective failure detection and identification. since a failure may not always be successfully identified, or, even if identified, may not be identified soon enough, it becomes important to consider the behavior of manipulators with unidentified failures. this work investigates the behavior of robots experiencing unidentified locked-joint failures in a general class of tasks characterized by point-to-point motion. based on the analysis, a procedure for workspace evaluation is developed that allows for the identification of regions in the manipulator's workspace in which tasks may be completed even with such failures. &copy; 2005 wiley periodicals, inc.
range error detection caused by occlusion in non-coaxial ladars for scene interpretation. when processing laser detection and ranging (ladar) sensor data for scene interpretation, for example, for the purposes of feature extraction and&#x002f;or data association in mobile robotics, most previous work models such devices as processing range data which follows a normal distribution. in this paper, it is demonstrated that commonly used ladars suffer from incorrect range readings at changes in surface reflectivity and&#x002f;or range discontinuities, which can have a much more detrimental effect on such algorithms than random noise. most ladars fall into two categories: coaxial and separated transmitter and receiver configurations. the latter offer the advantage that optical crosstalk is eliminated, since it can be guaranteed that all of the transmitted light leaves the ladar and is not in any way partially reflected within it due to the beam-splitting techniques necessary in coaxial ladars. however, they can introduce a significant disparity effect, as the reflected laser energy from the target can be partially occluded from the receiver. as well as demonstrating that false range values can result due to this occlusion effect from scanned ladars, the main contribution of this paper is that the occurrence of these values can be reliably predicted by monitoring the received signal strength and a quantity we refer to as the &ldquo;transceiver separation angle&rdquo; of the rotating mirror. this paper will demonstrate that a correct understanding of such systematic errors is essential for the correct further processing of the data. a useful design criterion for the optical separation of the receiver and transmitter is also derived for noncoaxial ladars, based on the minimum detectable signal amplitude of a ladar and environmental edge constraints. by investigating the effects of various sensor and environmental parameters on occlusion, some advice is given on how to make use of noncoaxial ladars correctly so as to avoid range errors when scanning environmental discontinuities. &copy; 2005 wiley periodicals, inc.
dynamic virtual environment to test teleoperated systems with time delay communications. this paper presents a dynamic virtual environment tool for training operators and to prove different control schemes in telerobotic systems, and describes virtual reality environments used in teleoperated robotic systems. in the presented tool, the kinematic and dynamic model of the remote environment which is manipulating the operator is considered. the paper also describes how time delays in the communication channel can be easily added to the simulator, in order to analyze their effects in the teleoperated system. finally, some experimental results achieved with this virtual teleoperated system are shown. with the presented dynamic simulator, different control schemes designed to overcome the time delay problem could be tested. &copy; 2005 wiley periodicals, inc.
projective virtual reality as a basis for on-line control of complex systems-not only-over the internet. already in 1994 the term projective virtual reality was coined and a first implementation was used to control a complex multirobot system in germany over the internet from california. building on this foundation, the general aim of the development of virtual reality technology for automation applications at the institute of robotics research (irf) today is to provide the framework for projective virtual reality for a broad range of applications. the general idea of projective virtual reality is to allow users to &ldquo;project&rdquo; actions carried out in the virtual world into the real world by means of robots or other means of automation. the framework is based on a task-oriented approach which builds on the &ldquo;task deduction&rdquo; capabilities of a newly developed virtual reality system and a task planning component. the advantage of this approach is that robots which work at great distances from the control station can be controlled as easily and intuitively as robots that work right next to the control station. robot control technology now provides the user in the virtual world with a &ldquo;prolonged arm&rdquo; into the physical environment, thus paving the way for intuitive control of complex systems over the internet&mdash;and in general for a new quality of user-friendly man-machine interfaces for automation applications. lately, this work has been enhanced by a new structure that allows one to distribute the virtual reality application over multiple computers on a network. with this new feature, it is now possible for multiple users to share the same virtual room, although they may physically be thousands of miles apart. they only need an internet connection to share this new experience. lately, the network distribution techniques have been further developed to not just allow users to cooperate over networked pcs but also to be able to set up a panorama projection or a cave running of a networked cluster of pcs. this approach cuts down the costs for such a high-end visualization environment drastically and allows for a new range of applications. &copy; 2005 wiley periodicals, inc.
the optimum design of 6-dof isotropic parallel manipulators. how to obtain 6-dof parallel manipulators with optimum global isotropy is investigated in this paper. a systematic method is first presented to get isotropic parallel designs. a measure for spatial isotropy is then proposed to evaluate and compare the global isotropy of obtained manipulators. efficient methods to find the minimum and maximum singular values of matrices are developed to facilitate the evaluation process. &copy; 2005 wiley periodicals, inc.
analytical identification of limb structures for translational parallel manipulators. a systematic analytical method, based on the theory of screws, is presented for identification of limb structures of general and over-constrained 3-degree-of-freedom (dof) translational parallel manipulators. given a system of wrenches of constraint, the corresponding reciprocal basis screws are determined. then, the joint screws of a limb are obtained by a linear combination of these basis screws. feasible limbs that can be used for construction of translational platforms are enumerated according to the type of constraint and the number of joints making up the limbs. &copy; 2004 wiley periodicals, inc.
the synthesis of three-degree-of-freedom planar parallel mechanisms with revolute joints (3-rrr) for an optimal singularity-free workspace. in this paper, a method is presented for the synthesis of 3-<und>r</und>rr planar parallel mechanisms. the method uses a genetic algorithm while considering three different design criteria: the optimization of the mechanism workspace to approach a prescribed workspace, the maximization of the mechanism's dexterity, and the avoidance of singularities inside the mechanism workspace. it is shown that, for a given mechanism, some working modes do not have any corresponding singularity curves located inside the mechanism workspace. furthermore, a case is presented where, for a given orientation range of the mechanism's end-effector, there are no parallel singularities located inside the workspace. finally, two methods are described and compared to deal with the nonuniform units of the mechanism's jacobian matrix during the dexterity computation. &copy; 2004 wiley periodicals, inc.
vision based intelligent wheel chair control: the role of vision and inertial sensing in topological navigation. this paper describes ongoing research on vision based mobile robot navigation for wheel chairs. after a guided tour through a natural environment while taking images at regular time intervals, natural landmarks are extracted to automatically build a topological map. later on this map can be used for place recognition and navigation. we use visual servoing on the landmarks to steer the robot. in this paper, we investigate ways to improve the performance by incorporating inertial sensors. &copy; 2004 wiley periodicals, inc.
dynamics modeling and analysis of a biped walking robot actuated by a closed-chain mechanism. we developed a new type of human-sized biped walking robot (bwr) driven by the closed-chain type of joint actuator. each leg of the robot is composed of three pitch joints and one roll joint. in all, a 15 degree-of-freedom robot including four arm joints and three joints for the head was developed. the bwr was developed to walk autonomously such that all leg joints are actuated by small 90 w dc motors&sol;drivers and dc batteries and controllers which are boarded. the joint actuator for the bwr is composed of the four-bar-link mechanism driven by the ball screw which has high strength and high gear ratio. a dynamics modeling of the developed bwr for forward walking is presented in which the revolute joint dynamics are transformed into the prismatic joint dynamics of the ball screw. also, an analysis on the four-bar-link mechanism applied to the joint actuator and on the structure of the bwr is shown. the design specification of the actuating motor for the bwr is analyzed through the torque analysis of the four-bar-link actuator. through walking experiments of the bwr, the walking performance and trajectory tracking ability is shown. &copy; 2004 wiley periodicals, inc.
a new 6-dof parallel robotic structure actuated by wires: the wiro-6.3. this paper describes a novel parallel robotic structure with six degrees of freedom, whose end effector is driven by nine wires operated by motors: the wiro-6.3. the ideas that led to the conception of the robot are thoroughly discussed and analyzed. the workspace of wiro-6.3 has been numerically analyzed, and it is significantly larger than the one of other analogous seven-wire structures. the forward and inverse kinematics are both solved in closed form. &copy; 2004 wiley periodicals, inc.
optimal path planning of mobile robots for sample collection. in this paper, the problem of path planning for sample collection using single or multiple mobile robots such as mars rovers is formulated as a mathematical optimization problem involving a performance metric based on the scientific values of the collected rock and soil samples. the posed optimization problem is np-hard and more complex than the well-known traveling salesman problem. algorithms are proposed for obtaining near-optimal solutions for both single and multiple robots. their application is illustrated using real mars surface data. the dependence of the optimal performance on the number of mobile robots is studied numerically. &copy; 2004 wiley periodicals, inc.
vision based robotic control. the university of colorado at denver robotics society is constructing an autonomous ground vehicle (agv) capable of accomplishing the association of unmanned vehicle systems international (auvsi) competition objectives. the design presented features an engineering focus on a statistical, vision based discrete-time control system optimized for an exterior robotic vehicle. a simple robust strategy incorporates ultrasonic ranging to make this vehicle capable of negotiating the features presented in the autonomous challenge. &copy; 2004 wiley periodicals, inc.
minimum jerk motion planning for a prosthetic finger. in this paper we propose a method, based on both physiologic and engineering considerations, for the motion planning of a prosthetic finger. in particular, we exploit a minimum jerk approach to define the trajectory in the cartesian space. then, cubic splines are adopted in the joint space. the redundancy problem arising from the presence of three links is solved by assuming that there is a constant ratio between the second and the third joint motion. the value of the proportional constant is determined by minimizing the maximum jerk in the joint space. it is found that this constant value can be suboptimally but effectively set to one for all the movements. this approach guarantees a natural movement of the finger as well as reduced vibrations in the mechanical structure and increased control performances. &copy; 2004 wiley periodicals, inc.
modeling and control for a gough-stewart platform cnc machine. in this paper, a complete dynamic model on task space for a 6 degrees of freedom (dof) gough-stewart platform-type computer numerical control (cnc) machine is derived. the rotation terms of the legs are included for those inertia effects cannot be negligible in the machine tool applications. the formulation derived by means of the euler-lagrange method is convenient for designing the adaptive control law. also, the average-type force model for end milling process is derived and included in the dynamic model and control. a composite adaptive control scheme is developed by use of filtering dynamics technique. an appropriate estimator gain is designed in the parameter adaptation law that is useful for estimating the selected important cutting parameters. experimental results verify the proposed adaptive control scheme can achieve good tracking performance. &copy; 2004 wiley periodicals, inc.
navigation aided image processing in uav surveillance: preliminary results and design of an airborne experimental system. this paper describes an airborne reconfigurable measurement system being developed at swedish defence research agency (foi), sensor technology, sweden. an image processing oriented sensor management architecture for uav (unmanned aerial vehicles) ir&sol;eo-surveillance is presented. some preliminary results of navigation aided image processing in uav applications are demonstrated, such as slam (simultaneous localization and mapping), structure from motion and geolocation, target tracking, and detection of moving objects. the design goal of the measurement system is to emulate a uav-mounted sensor gimbal using a stand-alone system. the minimal configuration of the system consists of a gyro-stabilized gimbal with ir and ccd sensors and an integrated high-performance navigation system. the navigation system combines dgps real-time kinematics (rtk) data with data from an inertial measurement unit (imu) mounted with reference to the optical sensors. the gimbal is to be used as an experimental georeferenced sensor platform, using a choice of carriers, to produce military relevant image sequences for studies of image processing and sensor control on moving surveillance and reconnaissance platforms. furthermore, a high resolution synthetic environment, developed for sensor simulations in the visual and infrared wavelengths, is presented. &copy; 2004 wiley periodicals, inc.
an affordable modular mobile robotic platform with fuzzy logic control and evolutionary artificial neural networks. autonomous robotics projects encompass the rich nature of integrated systems that includes mechanical, electrical, and computational software components. the availability of smaller and cheaper hardware components has helped make possible a new dimension in operational autonomy. this paper describes a mobile robotic platform consisting of several integrated modules including a laptop computer that serves as the main control module, microcontroller-based motion control module, a vision processing module, a sensor interface module, and a navigation module. the laptop computer module contains the main software development environment with a user interface to access and control all other modules. programming language independence is achieved by using standard input&sol;output computer interfaces including rs-232 serial port, usb, networking, audio input and output, and parallel port devices. however, with the same hardware technology available to all, the distinguishing factor in most cases for intelligent systems becomes the software design. the software for autonomous robots must intelligently control the hardware so that it functions in unstructured, dynamic, and uncertain environments while maintaining an autonomous adaptability. this paper describes how we introduced fuzzy logic control to one robot platform in order to solve the 2003 intelligent ground vehicle competition (igvc) autonomous challenge problem. this paper also describes the introduction of hybrid software design that utilizes fuzzy evolutionary artificial neural network techniques. in this design, rather than using a control program that is directly coded, the robot's artificial neural net is first trained with a training data set using evolutionary optimization techniques to adjust weight values between neurons. the trained neural network with a weight average defuzzification method was able to make correct decisions to unseen vision patterns for the igvc autonomous challenge. a comparison of the lawrence technological university robot designs and the design of the other competing schools shows that our platforms were the most affordable robot systems to use as tools for computer science and engineering education. &copy; 2004 wiley periodicals, inc.
kinematic optimal design of a paramill: a multi-sp device. in this paper, a manipulability analysis of a new parallel-type rolling mill, named &ldquo;paramill,&rdquo; in its conceptual design stage is investigated. the paramill considered uses two stewart platforms (sps) in opposite directions for the generation of 6 degree-of-freedom motions of individual work-rolls. the objective of this new approach is to pursue an integrated control of the strip thickness, strip shape, pair-crossing angle, uniform wear of the rolls, and tension of the strip. the forward&sol;inverse kinematics problems are formulated. two main kinematic parameters, the size of the base and the acute angle made by two neighboring joints for a given size of the work-roll, have been determined in the way that the force and moment transmission from the actuators to the work-rolls is maximized. &copy; 2004 wiley periodicals, inc.
3d cable-based cartesian metrology system. a novel cable-based metrology system is presented wherein six cables are connected in parallel from ground-mounted string pots to the moving object or tool of interest. cartesian pose can be determined for feedback control and other purposes by reading the lengths of the six cables via the string pots and using closed-form forward pose kinematics. this article focuses on a sculpting metrology tool, assisting a human artist in generating a piece from a computer model, but applications exist in manufacturing, rapid prototyping, robotics, and automated construction. we present experimental data to demonstrate the operation of our system, we study the absolute accuracy and also measurement resolution, and we discuss various error sources. the proposed real-time cable-based metrology system is less complex and more economical than existing commercial cartesian metrology technologies. &copy; 2004 wiley periodicals, inc.
an inertial and visual sensing system for a small autonomous helicopter. this paper describes the design and architecture of a low-cost and light-weight inertial and visual sensing system for a small-scale autonomous helicopter. a custom 6-axis imu and a stereo vision system provide vehicle attitude, height, and velocity information. we discuss issues such as robust visual processing, motion resolution, dynamic range, and sensitivity. &copy; 2004 wiley periodicals, inc.
optimal representative blocks for the efficient tracking of a moving object. optimal representative blocks are proposed for an efficient tracking of a moving object and it is verified experimentally by using a mobile robot with a pan-tilt camera. the key idea comes from the fact that when the image size of a moving object is shrunk in an image frame according to the distance between the camera of mobile robot and the moving object, the tracking performance of a moving object can be improved by shrinking the size of representative blocks according to the object image size. motion estimation using edge detection (ed) and block-matching algorithm (bma) are often used in the case of moving object tracking by vision sensors. however, these methods often miss the real-time vision data since these schemes suffer from the heavy computational load. to overcome this problem and to improve the tracking performance, the optimal representative block that can reduce a lot of data to be computed is defined and optimized by changing the size of the representative block according to the size of object in the image frame. the proposed algorithm is verified experimentally by using a mobile robot with a two degree-of-freedom active camera. &copy; 2004 wiley periodicals, inc.
design and prototype of parallel, wire-actuated robots with a constraining linkage. currently, wire-actuated robots are not used extensively in industry, but they are gaining more attention due to advantages they possess. low weight, cost, and power consumption are features that make wire-controlled robots worth researching. this article investigates the designs of two different, 4 degrees of freedom parallel, wire-actuated robots so that a prototype of one of these can be built. a design methodology is developed and presented. the process will be beneficial to those working on designing and prototyping a new robot or modifying an existing robot. stability of both designs is considered first to ensure that the robots are able to exert and withstand end effector forces in different positions throughout their respective workspaces. the stiffness and strength of the materials used in the designs is also investigated using finite element analysis. &copy; 2004 wiley periodicals, inc.
vasilius: the design of an autonomous ground robotic vehicle. this paper presents the design and provides a partial analysis of the performance of an autonomous ground robotic vehicle called vasilius. applications for vasilius include autonomous navigation on a somewhat marked path with obstacles, leader following, and waypoint navigation. the paper focuses on three aspects of vasilius: the design, the performance, and a technique for filtering, mapping, and learning. the design of vasilius embodies a novel idea of modeling an autonomous vehicle after human senses and the human decision-making process. for instance, vasilius integrates information from seven types of independent sensors, and categorizes them into either short-range reaction sensors and&sol;or long-range planning sensors, analogous to what the human brain does. the paper also analyzes the performance of vasilius, relating theoretical predictions to actual behavior. some of these analyses, especially for the filtering, mapping, and learning, are still in progress. performance measures that have been measured include speed, ramp climbing, turn reaction time, battery life, stop reaction time, object detection, and waypoint accuracy. finally, the paper discusses vasilius' use of a new approach to filtering, mapping, and learning to enhance its performance. &copy; 2004 wiley periodicals, inc.
on the validation of spdm task verification facility. this paper describes a methodology for validating a ground-based, hardware-in-the-loop, space-robot simulation facility. this facility, called &ldquo;spdm task verification facility,&rdquo; is being developed by the canadian space agency for the purpose of verifying the contact dynamics performance of the special purpose dexterous manipulator (spdm) performing various maintenance tasks on the international space station because the real spdm cannot be physically tested for 3d operations on the ground due to the gravity. the facility uses a high-fidelity spdm mathematical model, known as the &ldquo;truth model&rdquo; of the space robot, to drive a hydraulic robot to mimic the space robot performing contact operations. in this research different techniques were studied for practically verifying that the complex simulation facility preserves the dynamics of the truth model of the space robot for space-representative contact robotic tasks. based upon the study and many years of experience in developing and verifying space robotic systems, a practical validation strategy including detailed test cases was developed along with a set of quantitative criteria for judging the validation test results. &copy; 2004 wiley periodicals, inc.
dynamic control of a large scale of pneumatic multichain systems. the aim of this paper is to propose a general principle able to manage the supervision, coordination, and control problems of a large scale of multichain structures in dynamic and interacting tasks. the main originality lays in its modular feature. the number of chains and of joint per chain are indeed not restricted. the only assumption is that all the chains are linked to a principal element from which the dynamic stability will be computed. this is for example the case for multi-finger and multi-legged structures for which respectively the palm and the trunk represent the principal element. the principle consists in controlling the stability of this element and distributing the effort on the other chains to maintain the stability of the whole. to increase the compliant feature, we consider that each joint is pneumatically actuated. each joint is then dynamically controlled to ensure the asymptotic stability of the local chain it belongs to. a global architecture is presented where each part is detailed. an example is then displayed showing the performances of a two-legged robot in the standing posture under external perturbation effects. &copy; 2004 wiley periodicals, inc.
a flexible software architecture for hybrid tracking. fusion of vision-based and inertial pose estimation has many high-potential applications in navigation, robotics, and augmented reality. our research aims at the development of a fully mobile, completely self-contained tracking system, that is able to estimate sensor motion from known 3d scene structure. this requires a highly modular and scalable software architecture for algorithm design and testing. as the main contribution of this paper, we discuss the design of our hybrid tracker and emphasize important features: scalability, code reusability, and testing facilities. in addition, we present a mobile augmented reality application, and several first experiments with a fully mobile vision-inertial sensor head. our hybrid tracking system is not only capable of real-time performance, but can also be used for offline analysis of tracker performance, comparison with ground truth, and evaluation of several pose estimation and information fusion algorithms. &copy; 2004 wiley periodicals, inc.
a voronoi diagram-visibility graph-potential field compound algorithm for robot path planning. numerous methods have been developed to solve the motion planning problem, among which the voronoi diagram, visibility graph, and potential fields are well-known techniques. in this paper, a new path planning algorithm is presented where these three methods are integrated for the first time in a single architecture. after constructing the generalized voronoi diagram of c-space, we introduce a novel procedure for its abstraction, producing a pruned generalized voronoi diagram. a broad freeway net is then developed through a new &agr;-mid (maximal inscribed discs) concept. a potential function is assigned to the net to form an obstacle-free network of valleys. afterwards we take advantage of a bidirectional search, where the visibility graph and potential field modules execute alternately from both start and goal configurations. a steepest descent mildest ascent search technique is used for local planning and avoiding local minima. the algorithm provides a parametric tradeoff between safest and shortest paths and generally yields shorter paths than the voronoi and potential field methods, and faster than the visibility graph. it also performs well in complicated environments. &copy; 2004 wiley periodicals, inc.
on using flexure-hinge five-bar linkages to develop novel walking mechanisms and small-scale grippers for microrobots. this paper presents the micromotion analysis of five-bar linkages and demonstrates the approximate linearity of motion transmission of five-bar mechanisms within a micromotion range. a novel walking mechanism used for a microrobot and a small-scale gripper with a high transmission ratio are introduced, based on the flexure-hinge five-bar mechanism analysis. results of numerical simulation show the validity of design and analysis on the introduced mechanisms and the feasibility of corresponding thoughts. the presented micromotion-based robot mechanisms are devoid of friction and fitting errors, and particularly suitable for microrobot applications. &copy; 2004 wiley periodicals, inc.
multi-objective learning control for robotic manipulator. several types of learning controllers have been proposed in the literature to improve the tracking performance of robot manipulators. in most cases, the learning algorithms emphasize mainly on a single objective of learning a desired motion of the end-effector. in some applications, more than one objective may be specified at the same time. for example, a robot may be required to follow a desired trajectory (primary objective) and at the same time avoid an obstacle (secondary objective). thus, multi-objective learning control can be more effective to realize the collision-free tasks. in this paper, a multi-objective learning control problem is formulated and solved. in the proposed learning control system, the primary objective is to track a desired end-effector's motion and several secondary objectives can be specified for the desired orientation and for obstacles avoidance. to avoid obstacles in the workspace, a new learning concept called &ldquo;region learning control&rdquo; is also proposed in this paper. the proposed learning controllers do not require the exact knowledge of robot kinematics and dynamics. sufficient condition is presented to guarantee the convergence of the learning system. the proposed learning controllers are applied to a four-link planar redundant manipulator and simulation results are presented to illustrate the performance. &copy; 2004 wiley periodicals, inc.
control of teleoperators with communication time delay through state convergence. this paper describes a new control method of teleoperation systems with communication time delay. this method models the teleoperation system in the state space, considering all the possible interactions that could appear in the operator-master-slave-environment set, and it uses the taylor expansion to model the time delay. the control system allows that the slave manipulator follows the master in spite of the time delay in the communication channel. the tracking is achieved by state convergence between the master and the slave. the method is also able to establish the desired dynamics of this convergence and the dynamics of the slave manipulator. furthermore, a simple design procedure is provided to obtain the control system gains. these control gains are calculated solving a set of seven equations. the control method is robust to the uncertainty of the design parameters, so it is not necessary to obtain good estimations of these parameters. simulations and experiments with a one dof teleoperation system are presented to verify the control method. &copy; 2004 wiley periodicals, inc.
a guideline for specifying compliance in multi-fingered operations. in this paper, we present a fundamental compliance analysis for multi-fingered hands and also provide a guideline for specifying compliance characteristics in the three-dimensional operational space of multi-fingered hands. through the analysis of the stiffness relation between the operational space and the fingertip space of multi-fingered hands, it is shown that some of the coupling stiffness elements cannot be planned arbitrarily. also, an independent finger-based compliance control method to achieve the given compliance characteristics is described. conclusively, when we specify the operational stiffness matrix, the contents of the operational stiffness matrix cannot be fully achieved by influence of the grasp geometry of multi-fingered hands. the grasp positions of fingers as well as the rcc point, which are shown important factors, should be chosen to achieve the specified operational stiffness matrix for the given task. the cases of a point contact with friction and soft contact are examined as illustrative examples. it is observed that a five-fingered robotic hand is sufficient for implementation of proper three-dimensional compliance characteristics. &copy; 2004 wiley periodicals, inc.
adaptive tracking control of flexible-joint manipulators without overparametrization. in this paper, an adaptive controller is designed for rigid-link flexible-joint robot manipulators based on link and actuator position measurements only. it is based on the adaptive integrator backstepping method and the link and actuator velocity filters are used to estimate the unknown velocity terms. moreover, the proposed controller exploits the estimate of the joint stiffness matrix inverse to overcome the overparametrization problem, which has been a significant drawback in adaptive partial state feedback controllers. it achieves asymptotic tracking of link positions while keeping all states and signals bounded. the tracking capability of the presented method is shown through simulation results of one- and two-link flexible joint manipulators. &copy; 2004 wiley periodicals, inc.
design of a reconfigurable planar parallel manipulator. this work presents the design of a reconfigurable planar parallel manipulator (rppm). the rppm is designed to act as a testbed manipulator for theories on redundant actuation of parallel manipulators and can reconfigure into three different revolute-jointed mechanism types: a 2-branch 2-dof (degree-of-freedom) 5-bar mechanism; a 2-branch 3-dof 6-bar mechanism; and a 3-branch 3-dof 8-bar mechanism. the design of the rppm allows for any shoulder or elbow joint to be actuated. in this work, the criteria and constraints of the design are presented. the final design of the rppm is shown, followed by a discussion of the final design and how it relates to the initial design criteria and constraints. &copy; 2004 wiley periodicals, inc.
three-dimensional map building for mobile robot navigation environments using a self-organizing neural network. in recent years, mobile robots have been required to become more and more autonomous in such a way that they are able to sense and recognize the three-dimensional space in which they live or work. in this paper, we deal with such an environment map building problem from three-dimensional sensing data for mobile robot navigation. in particular, the problem to be dealt with is how to extract and model obstacles which are not represented on the map but exist in the real environment, so that the map can be newly updated using the modeled obstacle information. to achieve this, we propose a three-dimensional map building method, which is based on a self-organizing neural network technique called &ldquo;growing neural gas network.&rdquo; using the obstacle data acquired from the 3d data acquisition process of an active laser range finder, learning of the neural network is performed to generate a graphical structure that reflects the topology of the input space. for evaluation of the proposed method, a series of simulations and experiments are performed to build 3d maps of some given environments surrounding the robot. the usefulness and robustness of the proposed method are investigated and discussed in detail. &copy; 2004 wiley periodicals, inc.
kinematic modeling of mobile robots by transfer method of augmented generalized coordinates. a kinematic modeling method, which is directly applicable to any type of planar mobile robots, is proposed in this work. since holonomic constraints have the same differential form as nonholonomic constraints, the instantaneous motion of the mobile robot at current configuration can be modeled as that of a parallel manipulator. a pseudo joint model denoting the interface between the wheel and the ground (i.e., the position of base of the mobile robot) enables the derivation of this equivalent kinematic model. the instantaneous kinematic structures of four different wheels are modeled as multiple pseudo joints. then, the transfer method of augmented generalized coordinates, which has been popularly employed in modeling of parallel manipulators, is applied to obtain the instantaneous kinematic models of mobile robots. the kinematic models of six different types of planar mobile robots are derived to show the effectiveness of the proposed modeling method. lastly, for the mobile robot equipped with four conventional wheels, an algorithm estimating a sensed forward solution for the given information of the rotational velocities of the four wheels is discussed. &copy; 2004 wiley periodicals, inc.
design evolution of the trinity college igvc robot alvin. in this paper we discuss the design and evolution of trinity college's alvin robot, an autonomous ground vehicle that has participated in the association for unmanned vehicle systems international intelligent ground vehicle competition (igvc) since 2000. the paper first discusses the trinity robot study team, which has been responsible for developing alvin. we then illustrate the four generations of alvin, focusing on improvements made as the result of performance shortcomings and outright failures. the discussion considers the robot's body design, drive system, sensors, navigation algorithms, and vision systems. we focus especially on the vision and navigation systems developed for trinity's fourth-generation igvc robot, alvin iv. the paper concludes with a plan for future work on alvin and with a discussion of educational outcomes resulting from the alvin project. &copy; 2004 wiley periodicals, inc.
fusion of vision and inertial data for motion and structure estimation. this paper presents a method to fuse measurements from a rigid sensor rig with a stereo vision system and a set of 6 dof inertial sensors for egomotion estimation and external structure estimation. no assumptions about the sampling rate of the two sensors are made. the basic idea is a common state vector and a common dynamic description which is stored together with the time instant of the estimation. every time one of the sensor sends new data, the corresponding filter equation is updated and a new estimation is generated. in this paper the filter equations for an extended kalman filter are derived together with considerations of the tuning. simulations with real sensor data show the successful implementation of this concept. &copy; 2004 wiley periodicals, inc.
mathematical modeling and experimental identification of an unmanned helicopter robot with flybar dynamics. this paper presents a mathematical model for a model-scale unmanned helicopter robot, with emphasis on the dynamics of the flybar. the interaction between the flybar and the main rotor blade is explained in detail; it is shown how the flapping of the flybar increases the stability of the helicopter robot as well as assists in its actuation. the model helicopter has a fast time-domain response due to its small size, and is inherently unstable. therefore, most commercially available model helicopters use the flybar to augment stability and make it easier for a pilot to fly. working from first principles and basic aerodynamics, the equations of motion for full six degree-of-freedom with flybar-degree of freedom are derived. system identification experiments and results are presented to verify the mathematical model structure and to identify model parameters such as inertias and aerodynamic constants. &copy; 2004 wiley periodicals, inc.
design and control of a four-wheeled omnidirectional mobile robot with steerable omnidirectional wheels. omnidirectional mobile robots are capable of arbitrary motion in an arbitrary direction without changing the direction of wheels, because they can perform 3 degree-of-freedom (dof) motion on a two-dimensional plane. in this research, a new class of omnidirectional mobile robot is proposed. since it has synchronously steerable omnidirectional wheels, it is called an omnidirectional mobile robot with steerable omnidirectional wheels (omr-sow). it has 3 dofs in motion and one dof in steering. one steering dof can function as a continuously variable transmission (cvt). cvt of the omr-sow increases the range of velocity ratio from the wheel velocities to robot velocity, which may improve performance of the mobile robot. the omr-sow with four omnidirectional wheels has been developed in this research. kinematics and dynamics of this robot will be analyzed in detail. various tests have been conducted to demonstrate the validity and feasibility of the proposed mechanism and control algorithm. &copy; 2004 wiley periodicals, inc.
dynamic process programming for a robotic manipulator based on hopfield nn monotonous optimization searching. a new approach to programming the optimal dynamic process for an n-joint rigid robotic manipulator with the use of the monotonous optimization searching ability of a hopfield nn is presented. by combining robotic dynamics, this paper designs a programmed controller, which satisfies the aforementioned dynamic process. the convergence of the programmed controller is investigated. simulations and experiments demonstrate the effectiveness of the scheme described. &copy; 2004 wiley periodicals, inc.
rider's net moment estimation using control force of motion system for bicycle simulator. one of the challenging problems with bicycle simulators is to deal with the virtual bicycle dynamics that is coupled with rider's motion. for the virtual bicycle dynamics calculation and the real time simulation, it is necessary to identify the control inputs from the rider as well as the virtual environments. the steering, pedaling, and braking torques can be easily measured by using torque sensors and the virtual environments can be generated and provided by a visual system. however, direct measurement of the rider's net moment that significantly affects the bicycle motion is not practical. in this work, it is shown that six control forces of the stewart platform-based motion system can be used for effective estimation of the rider's net moment, incorporated with the sliding mode controller with perturbation estimation. &copy; 2004 wiley periodicals, inc.
formation of a geometric pattern with a mobile wireless sensor network. mobile wireless sensor networks (mwsns) will enable information systems to gather detailed information about the environment on an unprecedented scale. these self-organizing, distributed networks of sensors, processors, and actuators that are capable of movement have a broad range of potential applications, including military reconnaissance, surveillance, planetary exploration, and geophysical mapping. in many of the foreseen applications, the mwsn will need to form a geometric pattern without assistance from the user. in military reconnaissance, for example, the nodes will be dropped onto the battlefield from a plane and land at random positions. the nodes will be expected to arrange themselves into a predetermined formation in order to perform a specific task. thus, we present algorithms for forming a line, circle, and regular polygon from a given set of random positions. the algorithms are distributed and use no communication between the nodes to minimize energy consumption. unlike past studies of geometric problems where algorithms are either tested in simulations where each node has global knowledge of all the other nodes or implemented on a small number of robots, the robustness of our algorithms has been studied with simulations that model the sensor system in detail. the simulations demonstrate that the algorithms are robust against random errors in the sensors and actuators. &copy; 2004 wiley periodicals, inc.
a distributed fuzzy logic controller for an autonomous vehicle. autonomous vehicles can be used in a variety of applications such as hazardous environments or intelligent highway systems. fuzzy logic is an appropriate choice for this application as it can describe human behavior well. this paper proposes two fuzzy logic controllers for the steering and the velocity control of an autonomous vehicle. the two controllers are divided into separate modules to mimic the way humans think while driving. the steering controller is divided into four modules; one module drives the vehicle toward the target while another module avoids collision with obstacles. a third module drives the vehicle through mazes. the fourth module adjusts the final orientation of the target. the velocity controller is divided into three modules; the first module speeds up the vehicle to reach the target and slows it down as it moves toward the target. the second module controls the velocity in the neighborhood of obstacles. a third module controls the velocity of the vehicle as it turns sharp corners. a method for automatic tuning of the first module of the velocity controller is proposed to stabilize the velocity of the vehicle as it approaches the target. two examples to demonstrate the interaction among the seven control modules are included. results of the simulation are compared with those in the literature. &copy; 2004 wiley periodicals, inc.
omnidirectional vision and inertial clues for robot navigation. the structural features inherent in the visual motion field of a mobile robot contain useful clues about its navigation. the combination of these visual clues and additional inertial sensor information may allow reliable detection of the navigation direction for a mobile robot and also the independent motion that might be present in the 3d scene. the motion field, which is the 2d projection of the 3d scene variations induced by the camera-robot system, is estimated through optical flow calculations. the singular points of the global optical flow field of omnidirectional image sequences indicate the translational direction of the robot as well as the deviation from its planned path. it is also possible to detect motion patterns of near obstacles or independently moving objects of the scene. in this paper, we introduce the analysis of the intrinsic features of the omnidirectional motion fields, in combination with gyroscopical information, and give some examples of this preliminary analysis. &copy; 2004 wiley periodicals, inc.
a new space and time sensor fusion method for mobile robot navigation. to fully utilize the information from the sensors of mobile robot, this paper proposes a new sensor-fusion technique where the sample data set obtained at a previous instant is properly transformed and fused with the current data sets to produce a reliable estimate for navigation control. exploration of an unknown environment is an important task for the new generation of mobile service robots. the mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. notice that in the conventional fusion schemes, the measurement is dependent on the current data sets only. therefore, more sensors are required to measure a given physical parameter or to improve the reliability of the measurement. however, in this approach, instead of adding more sensors to the system, the temporal sequences of the data sets are stored and utilized for the purpose. the basic principle is illustrated by examples and the effectiveness is proved through simulations and experiments. the newly proposed stsf (space and time sensor fusion) scheme is applied to the navigation of a mobile robot in an environment using landmarks, and the experimental results demonstrate the effective performance of the system. &copy; 2004 wiley periodicals, inc.
a new immune genetic algorithm and its application in redundant manipulator path planning. in this paper, first the immune system is analyzed in a relatively deeper and all-sided point of view reflecting the fresh research in biology. second, based on the previous statements, a new optimization method, the immune genetic algorithm (iga), is presented by simulating the behavior of the biological immune system and is proved to converge to the global optimum with probability 1. third, a new method on the multi-object optimization that is transformed into a single-object one is proposed based on the joints' best compliance in the redundant robot path planning using iga. last, the experiment results show that the method of this article behaves more successfully. &copy; 2004 wiley periodicals, inc.
fusing visual and inertial sensing to recover robot ego-motion. a method for estimating mobile robot ego-motion is presented, which relies on tracking contours in real-time images acquired with a calibrated monocular video system. after fitting an active contour to an object in the image, 3d motion is derived from the affine deformations suffered by the contour in an image sequence. more than one object can be tracked at the same time, yielding some different pose estimations. then, improvements in pose determination are achieved by fusing all these different estimations. inertial information is used to obtain better estimates, as it introduces in the tracking algorithm a measure of the real velocity. inertial information is also used to eliminate some ambiguities arising from the use of a monocular image sequence. as the algorithms developed are intended to be used in real-time control systems, considerations on computation costs are taken into account. &copy; 2004 wiley periodicals, inc.
black knight: an autonomous vehicle for competition. black knight, the university of central florida's vehicle in the 11th intelligent ground vehicle competition (igvc) competed in 2003. completing in 5th place in the navigational challenge and 10th in the autonomous challenge in its first competition has proven our vehicle to be a strong competitor in this competition. the vehicle has many interesting features that allow it to achieve its success. the vehicle's 300 lb. capacity allows for two onboard full-sized computers and two 12 v marine batteries that power the computers for up to 2 h. the vision system is not a simple reactive system but rather it classifies its view into objects and builds a map of the territory as it learns of its features while traveling. two transformations and the location data from the gps and other sensors are used to associate the locations in the image to locations in the map. the operations of the vehicle are modeled after the typical operations of a ship. we have programs that perform the functions of the captain, the helm, the navigator, and the engineer. in addition we have a program performing sensor data fusion from the gps, compass, and wheel encoder data. the navigation uses an adapted two-dimensional approximate cell decomposition method that satisfies the nonholononic constraints of our vehicle and allows it to find the shortest path to the goal while avoiding all obstacles. &copy; 2004 wiley periodicals, inc.
design of an unmanned ground vehicle, bearcat iii, theory and practice. the purpose of this paper is to describe the design and implementation of an unmanned ground vehicle, called the bearcat iii, named after the university of cincinnati mascot. the bearcat iii is an electric powered, three-wheeled vehicle that was designed for the intelligent ground vehicle competition and has been tested in the contest for 5 years. the dynamic model, control system, and design of the sensory systems are described. for the autonomous challenge line following, obstacle detection and pothole avoidance are required. line following is accomplished with a dual camera system and video tracker. obstacle detection is accomplished with either a rotating ultrasound or laser scanner. pothole detection is implemented with a video frame grabber. for the navigation challenge waypoint following and obstacle detection are required. the waypoint navigation is implemented with a global positioning system. the bearcat iii has provided an educational test bed for not only the contest requirements but also other studies in developing artificial intelligence algorithms such as adaptive learning, creative control, automatic calibration, and internet-based control. the significance of this effort is in helping engineering and technology students understand the transition from theory to practice. &copy; 2004 wiley periodicals, inc.
an autonomous tracked vehicle with omnidirectional sensing. operation of an autonomous vehicle along a marked path, in an obstacle-laden environment, requires path detection, relative position detection and control, and obstacle detection and avoidance. the design solution of the team from the u.s. military academy is a tracked vehicle operating open-loop in response to position information from an omnidirectional mirror, and to obstacle-detection input from the mirror and from a scanning laser. the use of a tracked rather than a wheeled vehicle is the team's open-loop solution to the problem of wheeled-vehicle slippage on wet and sandy surfaces. the vehicleresponds to sensor information from (1) a digital camera-mounted parabolic omnidirectional mirror for visual inputs and (2) a scanning laser for detecting obstacles in relief. raw sensor data is converted synchronously into a global virtual context, which places the vehicle's center at the origin of a 2-d cartesian coordinate system. a four-phase process is used to convert the camera's inputs into the data structures needed to reason about the vehicle's position relative to the course. development of the path plan proceeds incrementally, using a space-sweeping algorithm to identify safe paths along waypoints within the course boundaries. an attempt is made to minimize translation errors by favoring paths which exhibit fewer sharp turns. integration of intel's opencv computer vision library and the independent jpeg group's jpeg library allow for very good encapsulation of the low-level functions needed to do most of the image processing. ada95 is the language of choice for the majority of the team-developed software, except where needed to interface to motors and sensors. use of an object-oriented high-level language has been invaluable in leveraging the efforts of previous years' development activities, and for maximizing the ability to log or otherwise respond to anomalous behavior. &copy; 2004 wiley periodicals, inc.
principles of fusion of inertial navigation and dynamic vision. the possibility of fusion of navigation data obtained by two separate navigation systems (strap-down inertial one and dynamic vision based one) is considered in this paper. the attention is primarily focused on principles of validation of separate estimates before their use in a combined algorithm. the inertial navigation system (ins) based on sensors of medium level quality has been analyzed on one side, while a visual navigation method is based on the analysis of a sequence of images of ground landmarks produced by an on-board tv camera. the accuracy of ins estimations is being improved continuously by optimal estimation of a flying object's angular orientation while the visual navigation system offers discrete corrections during the intervals of presence of landmarks inside the camera's field of view. the concept is illustrated by dynamic simulation of a realistic flight scenario. &copy; 2004 wiley periodicals, inc.
inertial sensed ego-motion for 3d vision. inertial sensors attached to a camera can provide valuable data about camera pose and movement. in biological vision systems, inertial cues provided by the vestibular system are fused with vision at an early processing stage. in this article we set a framework for the combination of these two sensing modalities. cameras can be seen as ray direction measuring devices, and in the case of stereo vision, depth along the ray can also be computed. the ego-motion can be sensed by the inertial sensors, but there are limitations determined by the sensor noise level. keeping track of the vertical direction is required, so that gravity acceleration can be compensated for, and provides a valuable spatial reference. results are shown of stereo depth map alignment using the vertical reference. the depth map points are mapped to a vertically aligned world frame of reference. in order to detect the ground plane, a histogram is performed for the different heights. taking the ground plane as a reference plane for the acquired maps, the fusion of multiple maps reduces to a 2d translation and rotation problem. the dynamic inertial cues can be used as a first approximation for this transformation, allowing a fast depth map registration method. they also provide an image independent location of the image focus of expansion and center of rotation useful during visual based navigation tasks. &copy; 2004 wiley periodicals, inc.
autonomous ground vehicle path tracking. autonomous ground vehicle navigation requires the integration of many technologies such as path planning, position and orientation sensing, vehicle control, and obstacle avoidance. the work presented here focuses on the control of a nonholonomic ground vehicle as it tracks a given path. a new path tracking technique called &ldquo;vector pursuit&rdquo; is presented. this new technique is based on the theory of screws, which was developed by sir robert ball in 1900. it generates a desired vehicle turning radius based on the vehicle's current position and orientation relative to the position of a point ahead on the planned path and the desired orientation along the path at that point. the vector pursuit algorithm is compared to other geometrical approaches, and it is shown to be more robust, resulting in more accurate path tracking. &copy; 2004 wiley periodicals, inc.
serpent. standardization is one of the hallmarks of an industrial society. as a society becomes increasingly complex and its industrial base begins to emerge, it becomes necessary for the products, processes, and procedures of the society to fit together and to interoperate. this interoperation provides the basis for greater integration of the elements of the society, which in turn causes increased social interdependency and complexity. this trend has recently been accelerated by the so-called "global economy," and further spurred by the creation of seamless methods of transnational transfer of information and knowledge via the the internet (q.v.) and the world wide web (q.v.). both the internet and the web are currently based entirely upon voluntary standardization. their result is increased information interdependence, which in turn will feed the need for increased application standardization. however, the standardization that will result from the application of these technologies will include social and economic standardization, a phenomenon whose depth and implications are just now beginning to be appreciated.
data remanence. something is wrong, now what: this article will help you figure out what went wrong, how to get started on fixing it, or now to prepare for possible crashes.
mars. graphic artists have a wide variety of applications to use for digital painting. although each application has its own solution to enhance the user experience, most of them rely on the same standard feature; a single brush, which is completely dependent on user input for location. although this is required for a fully controlled painting process, making small changes on this feature yields unpredictable results. my proposal for an alternate brush paradigm is using multiple brushes (as seen in the application "pd particles"), which are not completely under control but rather moving within trajectories with random deviations, simultaneously. the trajectories are defined by controllable parameters and the user input. since the rate of obedience to user input is dependant on the parameters, users can define the rate of deviation and thus switch between finger painting and generative painting, without changing the set of tools.
compromising emanations. cybernetic concepts and design implications can be elucidated by means of computer experiments. a series of programs have been prepared which simulate the operation of typical control devices. the system of interest is first studied under uncontrolled conditions using typical input data for the process under study. the system is then &ldquo;connected&rdquo; to chosen control elements such as feedback transducers, comparitors and controllers. in a biological context homeostatic adjustment is considered as a function of the control parameters. transient response is noted as processes are switched on and off. regulatory conditions are determined by the goal state to maintain bounds on fluctuations or give rise to stable oscillatory cycles. sensitivity analysis is carried out with respect to competing control elements. the role of response lag is clearly demonstrated by simultaneous graphing of related state variables. only after the response of basic elements is ascertained are they joined in complex configurations. in this manner the behavior of a complex structure is understood in terms of its underlying elements.
birthday paradox. this paper focuses on art created by new techniques such as cellular machines, l-systems, genetic algorithms, neural networks ... we propose here several methods of implementation combining the rules of construction of cellular machines and l-systems with genetic, neuronal networks, couplings, translation of codes. these methods result in the morphogenesis of bodies, as well their structure (shape) and their functional aspect (neuronal networks with driving, sensory neurons, balance, etc.). it's a part of what we can call "a new kind of art", and we can see here how beings-paintings emerge.
sender anonymity. all complex systems fail, by some measure of the word "fail," with consequences ranging from benign to catastrophic. this article examines the process of to triage in the face of a failing system.
interactive argument. this paper addresses the question of attribution of agency to artifacts. taking an activity-theoretical perspective, i argue that artifacts are used to guide actions. in other words, i claim that artifacts have instructional impact. the introductory part of the paper is an account of how three kinds of artifacts - physical artifacts, linguistic representations, and graphic representations -- are instructionally used in coronary diagnostic work. the main part of the paper is an empirical exploration of how a forth kind of artifact, organization of work, is instructionally used. the empirical case analyzed involves clinical diagnostic work conducted as a video-mediated conference between two collaborating diagnostic subteams, one of which had made the coronary investigation by means of coronary angiography, while the other was to take actions in the form of by-pass surgery or balloon dilatation. in the concluding sections, i discuss in what way it makes sense to say that organization of work and other artifacts have instructional properties.
security. abstract: this keynote address reviews several techniques from morphometrics (the multivariate biometrics of shape) developed mainly in the context of medical image analysis over the last decade. the new techniques pro-vide powerful tools for geometric tasks that arise in the course of most analyses of medical images in groups. these tasks include standardizing against euclidean similarity transformations or shear transformations, en-coding informative prior knowledge about shape variation, and detecting, testing, and visualizing linear statistical patterns of variation within or between groups. i review the features of the present toolkit, the standard underlying data models entailed, and some of the extensions that reach out to the additional information content of medical images for common clinical or scientific applications.
threshold signature. in the late 1950s and early 1960s, computer systems were envisioned that could be used simultaneously by several people, each at a typewriter-like terminal, each appearing to have exclusive use of the computer. the computer was to take advantage of the typing time of one user by turning its attention to another. if the computational tasks requested were short enough, then all users could be serviced, and the illusion of a single-user private computer would be maintained. early systems served less than a dozen people, whereas modern systems service 10 to 1,000 or more. but what if there were one or more very long computational tasks?
credentials. the main trends discernible both in session iv and in the general discussion that ended the 1974 lake arrowhead workshop can be summarized as follows: the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
simultaneous exponentiation. software engineering is the disciplined application of theories and techniques from computer science to define, develop, deliver, and maintain, on time and within budget, software products that meet customers' needs and expectations. software products include the actual program source code and data structures (q.v.), as well as the documents necessary to produce these, and documents and interface programs necessary to use them in the intended environment.
towards the merging of multiple clinical protocols and guidelines via ontology-driven modeling. decision support systems based on computerized clinical protocols (cp) and clinical practice guidelines (cpg) fall short when dealing with patient co-morbidites, as this demands the concurrent merging of multiple cp/cpg. we present an ontology-based approach for the merging of cpg and cp at two levels---i.e. knowledge modeling level and knowledge execution level. we have developed specialized ontological modeling constructs to facilitate merging of cpg and cp. we demonstrate the merging of multiple location-specific cp and disease-specific cpg.
multiple terminologies in a health portal: automatic indexing and information retrieval. background: in the specific context of developing quality-controlled health gateways, several standards must be respected (e.g. dublin core for metadata element set; thesaurus mesh as the controlled vocabulary to index internet resources; hon code to accredit quality of health web sites). these standards were applied to create the cismef web site (french acronym for catalog & index of health internet resources in french). objective: in this work, the strategic shift of the cismef team is intended to index and retrieve french resources not anymore with a single terminology (mesh thesaurus) but with the main health terminologies available in french (icd 10, snomed international, ccam, atc). methods & results: since 2005, we have developed the french multi-terminology indexer (f-mti), using a multi-terminology approach and mappings between health terminologies. this tool is used for automatic indexing and information retrieval. conclusion: since the last quarter of 2008, f-mti is daily used in the cismef production environment and is connected to a french health multi-terminology server.
a knowledge-based system to support emergency medical services for disabled patients. this paper illustrates a knowledge based system devoted to help nurses and volunteers of emergency medical services (ems) in dealing with disabled patients during an emergency.
segmentation of lung tumours in positron emission tomography scans: a machine learning approach. lung cancer represents the most deadly type of malignancy. in this work we propose a machine learning approach to segmenting lung tumours in positron emission tomography (pet) scans in order to provide a radiation therapist with a "second reader" opinion about the tumour location. for each pet slice, our system extracts a set of attributes, passes them to a trained support vector machine (svm), and returns the optimal threshold value for distinguishing tumour from healthy voxels in that particular slice. we use this technique to analyse four different pet/ct 3d studies. the system produced fairly accurate segmentation, with jaccard and dice's similarity coefficients between 0.82 and 0.98 (the areas outlined by the returned thresholds vs. the ones outlined by the reference thresholds). besides the high level of geometric similarity, a significant correlation between the returned and the reference thresholds also indicates that during the training phase, the learning algorithm effectively acquired the dependency between the extracted attributes and optimal thresholds.
providing objective feedback on skill assessment in a dental surgical training simulator. dental students devote several years to the acquisition of sufficient psychomotor skills to prepare them for entry-level dental practice. traditional methods of dental surgical skills training and assessment are being challenged by the complications such as the lack of real-world cases, unavailability of expert supervision and the subjective manner of surgical skills assessment. to overcome these challenges, we developed a dental training system that provides a vr environment with a haptic device for dental students to practice tooth preparation procedures. the system monitors important features of the procedure, objectively assesses the quality of the performed procedure using hidden markov models, and provides objective feedback on the user's performance for each stage in the procedure. important features for characterizing the quality of the procedure were identified based on interviews with experienced dentists. we evaluated the accuracy of the skill assessment with data collected from novice dental students as well as experienced dentists. we also evaluated the quality of the system's feedback by asking a dental expert for comments. the experimental results show high accuracy in classifying users into novice and expert, and the evaluation indicated a high acceptance rate for the generated feedback.
genetic algorithm based scheduling of radiotherapy treatments for cancer patients. this paper presents a multi-objective model for scheduling of radiotherapy treatments for cancer patients based on genetic algorithms (ga). the model is developed and implemented considering real life radiotherapy treatment processes at arden cancer centre, coventry, uk. two objectives are defined: minimisation of the average patient waiting times and minimisation of average tardiness of the patient first treatment fractions. two scenarios are analysed considering the availability of the doctors to approve treatment plans. the schedules generated by the ga using real data collected from the collaborating cancer centre have good performance. it is demonstrated that enabling doctors to approve treatment plans instantly has a great impact on average waiting time and average tardiness for all patient categories.
homenl: homecare assistance in natural language. an intelligent conversational agent for hypertensive patients management. the prospective home-care management will probably offer intelligent conversational assistants for supporting patients at home through natural language interfaces. homecare assistance in natural language, homenl, is a proof-of-concept dialogue system for the management of patients with hypertension. it follows up a conversation with a patient in which the patient is able to take the initiative. homenl processes natural language, makes an internal representation of the patients' contributions, interprets sentences by reasoning about their meaning on the basis of a medical-knowledge representation and responds appropriately. homenl's aim is to provide a laboratory for studying natural language processing (nlp) and intelligent dialogues in clinical domains.
codeslinger: an interactive biomedical ontology browser. codeslinger is a highly interactive and semi-intelligent application designed to support the search and navigation of large biomedical coding schemes, thesauri, and ontologies. we discuss how codeslinger is used by epidemiologist/physicians in the creation of coding sets for data extraction and analysis, the exploratory nature of the application, and finally, the issues facing our knowledge-representation model and extension of the umls.
an advanced platform for managing complications of chronic diseases. this paper describes a generic platform for telemedicine services aimed at supporting chronic outpatients. the framework comprises a server agent and several cell phones as mobile agents through which patients and caregivers within their families may input data and receive back suggestions and advice. mobile agents and server are endowed with domain specific knowledge in order to support users in a flexible way structured on multiple levels.
on quality of different annotation sources for gene expression analysis. mining of biomedical data increasingly relies on utility of knowledge repositories. in gene expression analysis, these are often used for gene labeling with an assumption that similarly annotated genes have similar expression profiles. in the paper we use this assumption to craft a method with which we scored six different annotation sources (e.g., gene ontology, pubmed, and mesh annotations) for their utility in gene expression data analysis. experiments show that the sources that include manual curation perform well and, for instance, score better than automatic annotation from gene-related pubmed abstracts. we also show that there is no clear winner, pointing at the need for methods that could successfully integrate annotations from different sources.
an architecture for automated reasoning systems for genome-wide studies. the massive amounts of data generated by high-throughput experiments makes modern biomedical research a data-intensive discipline, shifting the research methodology from a hypothesis-based approach to a hypothesis-free one. a formal procedure should be defined to properly design a study, understand the outcomes and plan improvements for each task performed during the experiments. such formal approach needs the identification of a high-level conceptual model of the knowledge discovery process occurring in genome-wide studies: this is what existing computational tools lack. starting from an epistemological model of the discovery process proposed for diagnostic reasoning, we describe how the design and execution of modern genome-wide studies can be modelled using the same framework. we show the general validity of the model, how it can be instantiated to model typical scenarios of genome-wide studies, and how we use it to develop tools aimed at building semi-automated reasoning systems.
an ontology for the care of the elder at home. the health-care of the elder at home is highly demanded in modern societies. it is based on the difficult task of coordinating multiple professionals and procedures acting on the same patient. k4care is a project aiming at implementing and testing a technology-based incremental and adaptable model to assist health care systems in home care. one of the key components of this model is the case profile ontology (cpo) that is used to support the activities in the life-cycle of home care. these activities define a path that goes from assessing the problem to deploying a care plan. along this path several cpo-based tools have been implemented to ease the assessment step, to manage care plans as state-decision-action diagrams, to combine care plans for comorbid patients, and to personalize care plans. the use of these tools significantly reduces the complexity of dealing with patients at home.
voice pathology classification by using features from high-speed videos. for the diagnosis of pathological voices it is of particular importance to examine the dynamic properties of the underlying vocal fold (vf) movements occurring at a fundamental frequency of 100---300 hz. to this end, a patient's laryngeal oscillation patterns are captured with state-of-the-art endoscopic high-speed (hs) camera systems capable of recording 4000 frames/second. to date the clinical analysis of these hs videos is commonly performed in a subjective manner via slow-motion playback. hence, the resulting diagnoses are inherently error-prone, exhibiting high inter-rater variability. in this paper an objective method for overcoming this drawback is presented which employs a quantitative description and classification approach based on a novel image analysis strategy called phonovibrography. by extracting the relevant vf movement information from hs videos the spatio-temporal patterns of laryngeal activity are captured using a set of specialized features. as reference for performance, conventional voice analysis features are also computed. the derived features are analyzed with different machine learning (ml) algorithms regarding clinically meaningful classification tasks. the applicability of the approach is demonstrated using a clinical data set comprising individuals with normophonic and paralytic voices. the results indicate that the presented approach holds a lot of promise for providing reliable diagnosis support in the future.
severity evaluation support for burns unit patients based on temporal episodic knowledge retrieval. severity scores are a sort of medical algorithm commonly used in medicine. in practise, physicians only use a few of them, usually internationally accepted ones involving very simple calculations. however, their daily use in critical care services gives rise to two potential problems. first, they do not always cover the particularities of the local population or a specific pathology may not be considered in the score. second, these services (e.g. intensive care units or burns units) are strongly dependent on the evolution of the patients and, so the temporal component plays an essential role that should always be in mind. on the other hand, the knowledge required is at least partially present in the physician team of the medical unit due to the experience gained in treating individual patients, that is, in the form of episodic knowledge. therefore, the use of techniques based on analogy reasoning, such as case-based reasoning, would seem a suitable approach for dealing with part of this problem.in this work, we present an episodic knowledge retrieval system to support the physician in evaluating the severity patients from the temporal evolution point of view. to this end, we present different techniques for temporal retrieval based on previous works on temporal similarity. we also demonstrate the suitability of this system by applying it to a specific medical problem arising in a burns unit.
a novel multilingual report generation system for medical applications. there has been an increasing demand for high quality medical data that are in a standard electronic format and easily shared. although a great amount of effort has been invested to ease the process, an effective solution has yet to be found. in this study, we first discuss necessary features of an effective data collection and reporting system, and then reveal the conceptual view of a novel method that aims to encompass these features. we also present the design and implementation details of a web-based prototype.
subgroup discovery for weight learning in breast cancer diagnosis. in the recent years, there is an increasing interest of the use of case-based reasoning (cbr) in medicine. cbr is an approach to problem solving that is able to use specific knowledge of previous experiences. however, the efficiency of cbr strongly depends on the similarity metrics used to recover past experiences. in such metrics, the role of attribute weights is critical. in this paper we propose a methodology that use subgroup discovery methods to learn the relevance of the attributes. the methodology is applied to a breast cancer dataset obtaining significant improvements. ...
a temporal data mining approach for discovering knowledge on the changes of the patient's physiology. physiological data represent the health conditions of a patient over time. they can be analyzed to gain knowledge on the course of a disease or, more generally, on the physiology of a patient. typical approaches rely on background medical knowledge to track or recognize single stages of the disease. however, when no one domain knowledge is available these approaches become inapplicable. in this paper we describe a temporal data mining approach to acquire knowledge about the possible causes which can trigger particular stages of the disease or, more generally, which can determine changes in the patient's physiology. the analysis is performed in two steps: first, identification of the states of the disease (namely, the stages through which the physiology evolves), then detection of the events which may determine the change from a state to the next one. computational solutions to both issues are presented. the application to the scenario of the sleep disorders allows to discover events, in the form of breathing and cardiovascular disorders, which may trigger particular sleep stages. results are evaluated and discussed.
one telemedical solution in bulgaria. a new arena of healthcare is emerging, because physicians, hospitals, financial health planners and administrators are coming together in a single highly integrated and coordinated virtual health organization.the mission of telemedicine is to provide medical services independently of geographical distances between the involved sites. patients can get access to medical expertise that may not be available at the patients' site through telemedicine. experience over the last decade has shown that the goals of telemedicine are not automatically reached by the introduction and use of particular new technologies per se, but rather require the implementation of integral services and specialized information systems.software teleconsult aims are to provide logistic and telemedical services between two distant hospitals on the territory of bulgaria. the objectives of this development are to combine medicine field, e-health and informatics research so as to share information and experience in order to perform the best patient services at a reasonable price.
modeling clinical guidelines through petri nets. clinical guidelines (gls) play an important role to standardize and organize clinical processes according to evidence-based medicine. several computer-based gl representation languages have been defined, usually focusing on expressiveness and/or on user-friendliness. in many cases, the interpretation of some constructs in such languages is quite unclear. only recently researchers have started to provide a formal semantics for some of such languages, thus providing an unambiguous specification for implementers, and a formal ground in which different approaches can be compared, and verification techniques can be applied. petri nets are a natural candidate formalism to cope with gl semantics, since they are explicitly geared towards the representation of processes, and are paired with powerful verification mechanisms. we show how petri nets can cope with the semantics of gls in a clear way, taking the system glare formalism as a case study.
mining healthcare data with temporal association rules: improvements and assessment for a practical use. the regional healthcare agency (asl) of pavia has been maintaining a central data repository which stores healthcare data about the population of pavia area. the analysis of such data can be fruitful for the assessment of healthcare activities. given the crucial role of time in such databases, we developed a general methodology for the mining of temporal association rules on sequences of hybrid events. in this paper we show how the method can be extended to suitably manage the integration of both clinical and administrative data. moreover, we address the problem of developing an automated strategy for the filtering of output rules, exploiting the taxonomy underlying the drug coding system and considering the relationships between clinical variables and drug effects. the results show that the method could find a practical use for the evaluation of the pertinence of the care delivery flow for specific pathologies.
causal probabilistic modelling for two-view mammographic analysis. mammographic analysis is a difficult task due to the complexity of image interpretation. this results in diagnostic uncertainty, thus provoking the need for assistance by computer decision-making tools. probabilistic modelling based on bayesian networks is among the suitable tools, as it allows for the formalization of the uncertainty about parameters, models, and predictions in a statistical manner, yet such that available background knowledge about characteristics of the domain can be taken into account. in this paper, we investigate a specific class of bayesian networks--causal independence models--for exploring the dependencies between two breast image views. the proposed method is based on a multi-stage scheme incorporating domain knowledge and information obtained from two computer-aided detection systems. the experiments with actual mammographic data demonstrate the potential of the proposed two-view probabilistic system for supporting radiologists in detecting breast cancer, both at a location and a patient level.
steps on the road to clinical application of decision support - example treat. the decision support system treat advices on antibiotic treatment of severe infections. a multicenter randomized clinical trial has demonstrated that treat reduces inappropriate treatment by 50%. this paper will show that treat satisfies several features closely correlated with decision support systems's ability to improve clinical practice. examples of such criteria are: providing recommendations, not just assessments; transparent line of reasoning; convenience in use. additional design features, such as transferability and addressing an important clinical problem, will also be discussed.
an ontology-based method to link database integration and data mining within a biomedical distributed kdd. over the last years, collaborative research has been continuously growing in many scientific areas such as biomedicine. however, traditional knowledge discovery in databases (kdd) processes generally adopt centralized approaches that do not fully address many research needs in these distributed environments. this paper presents a method to improve traditional centralized kdd by adopting an ontology-based distributed model. ontologies are used within this model: (i) as virtual schemas (vs) to solve structural heterogeneities in databases and (ii) as frameworks to guide automatic transformations when data is retrieved by users--preprocessing ontologies (po). both types of ontologies aim to facilitate data gathering and preprocessing while maintaining data source decentralization. this ontology-based approach allows to link database integration and data mining, improving final results, reusability and interoperability. the results obtained present improvements in outcome performance and new capabilities compared to traditional kdd processes.
the role of biomedical dataset in classification. in this paper, we investigate the role of a biomedical dataset on the classification accuracy of an algorithm. we quantify the complexity of a biomedical dataset using five complexity measures: correlation-based feature selection subset merit, noise, imbalance ratio, missing values and information gain. the effect of these complexity measures on classification accuracy is evaluated using five diverse machine learning algorithms: j48 (decision tree), smo (support vector machines), naive bayes (probabilistic), ibk (instance based learner) and jrip (rule-based induction). the results of our experiments show that noise and correlation-based feature selection subset merit --- not a particular choice of algorithm --- play a major role in determining the classification accuracy. in the end, we provide researchers with a meta-model and an empirical equation to estimate the classification potential of a dataset on the basis of its complexity. this well help researchers to efficiently pre-process the dataset for automatic knowledge extraction.
coraal - towards deep exploitation of textual resources in life sciences. prominent biomedical literature search tools like sciencedirect, pubmed central or medline allow for efficient retrieval of resources based on key words. due to vast amounts of data available in life sciences, key word search is not always sufficient, though. one would often welcome more intelligent search for knowledge, i.e., for concepts and their mutual relations. this is, however, still a major challenge, since getting the necessary machine-readable knowledge manually is virtually impossible in large scale, while its automatic extraction is not particularly reliable. we have researched a novel framework actually enabling practical exploitation of automatically extracted knowledge, though. on the top of the framework, we implemented coraal, a prototype for knowledge-based biomedical literature search. this paper describes its essential principles, innovative capabilities and current results.
a mutual information approach to data integration for alzheimer's disease patients. clinical data alignment plays a critical role in identifying important features for significant experiments. a central problem is data fusion i.e., how to correctly integrate data provided by different labs. this integration is done in order to increase ability of inferring target classes of controls and patients. our paper proposes an approach based both on a information theoretic perspective, generally used in a feature construction problem [3] and on the approximated solution for a mathematical programming task (i.e. the weighted bipartite matching problem [6]). numerical evaluations with two competitive approaches show the improved performance of the proposed method. for this evaluation we used data sets from plasma / ethylenediaminetetraacetic acid (edta) of controls and alzheimer patients collected in three different hospitals.
computer vision: a plea for a constructivist view. computer vision is presented and discussed under two complementary views. the positivist view provides a formal background under which vision is approached as a problem-solving task. by contrast, the constructivist view considers vision as the opportunistic exploration of a realm of data. the former view is rather well supported by evidence in neurophysiology while the latter view rather relies on recent trends in the field of distributed and situated cognition. the notion of situated agent is presented as a way to design computer vision systems under a constructivist hypothesis. various applications in the medical domain are presented to support the discussion.
implementing a clinical decision support system for glucose control for the intensive cardiac care. adherence to guidelines and protocols in clinical practice can be difficult to achieve. we describe the implementation of a clinical decision support system (cdss) for glucose control on the intensive cardiac care unit (iccu) of the erasmus mc. an existing paper protocol for glucose control was used for the cdss rule set. in the first phase we implemented a proof of concept of a cdss: a web 2.0 ajax-driven web screen, which resulted in an improved adherence to the glucose guideline. this paper will reflect on the technical implementations and challenges of our experience with this process. the end product will allow: storage of guidelines in a shareable and uniform matter, presentation of guidelines in a more clear way to physicians, a more flexible platform to maintain guidelines, the ability to adjust guidelines to incorporate changes based on collected evidence from the cdss and/or literature review, and be able to better review the outcome.
using temporal constraints to integrate signal analysis and domain knowledge in medical event detection. the events which occur in an intensive care unit (icu) are many and varied. very often, events which are important to an understanding of what has happened to the patient are not recorded in the electronic patient record. this paper describes an approach to the automatic detection of such unrecorded 'target' events which brings together signal analysis to generate temporal patterns, and temporal constraint networks to integrate these patterns with other associated events which are manually or automatically recorded. this approach has been tested on real data recorded in a neonatal icu with positive results.
explaining anomalous responses to treatment in the intensive care unit. the intensive care unit (icu) provides treatment to critically ill patients. when a patient does not respond as expected to such treatment it can be challenging for clinicians, especially junior clinicians, as they may not have the relevant experience to understand the patient's anomalous response. datasets for 10 patients from glasgow royal infirmary's icu have been made available to us. we asked several icu clinicians to review these datasets and to suggest sequences which include anomalous or unusual reactions to treatment. further, we then asked two icu clinicians if they agreed with their colleagues' assessments, and if they did to provide possible explanations for these anomalous sequences. subsequently we have developed a system which is able to replicate the clinicians' explanations based on the knowledge contained in its several ontologies; further the system can suggest additional explanations which will be evaluated by the senior consultant.
goal-based decisions for dynamic planning. the need for clinical guidelines to be implemented at different sites, to adapt to rapidly changing environments, and to be carried out by distributed clinical teams, implies a degree of flexibility beyond that of current guideline languages. we propose an extension to the proforma language allowing hierarchical goal-based plans. sub-plans to achieve goals are proposed at runtime so that changing circumstances may be flexibly accommodated without redefining the workflow.
histopathology image classification using bag of features and kernel functions. image representation is an important issue for medical image analysis, classification and retrieval. recently, the bag of features approach has been proposed to classify natural scenes, using an analogy in which visual features are to images as words are to text documents. this process involves feature detection and description, construction of a visual vocabulary and image representation building through visual-word occurrence analysis. this paper presents an evaluation of different representations obtained from the bag of features approach to classify histopathology images. the obtained image descriptors are processed using appropriate kernel functions for support vector machines classifiers. this evaluation includes extensive experimentation of different strategies, and analyses the impact of each configuration in the classification result.
segmentation of text and non-text in on-line handwritten patient record based on spatio-temporal analysis. note taking is a common way for physicians to collect information from their patients in medical inquiries and diagnoses. many times, when describing the pathology in medical records, a physician also draws diagrams and/or anatomical sketches along with the free-text narratives. the ability to understand unstructured handwritten texts and drawings in patient record could lead to implementation of automated patient record systems with more natural interfaces than current highly structured systems. the first and crucial step in automated processing of free-hand medical records is to segment the record into handwritten text and drawings, so that appropriate recognizers can be applied to different regions. this paper presents novel algorithms that separate text from non-text strokes in an on-line handwritten patient record. the algorithm is based on analyses of spatio-temporal graphs extracted from an on-line patient record and support vector machine (svm) classification. experiments demonstrate that the proposed approach is effective and robust.
an ambient intelligent agent for relapse and recurrence monitoring in unipolar depression. mental healthcare is a prospective area for applying ai techniques. for example, a computerized system could support individuals with a history of depression in maintaining their well-being throughout their lifetime. in this paper, the design of an ambient intelligent agent to support these individuals is presented. it incorporates an analysis and support model for diagnostics based on observed features and for suggested actions. the model used is based on dynamic relations that describe the occurrence of relapse in unipolar depression. by incorporating this model into an ambient agent system, the agent is able to reason about the state of the human and the effect of possible actions. several simulation experiments have been conducted to illustrate the functioning of the proposed model in different scenarios.
optimization of online patient scheduling with urgencies and preferences. we consider the online problem of scheduling patients with urgencies and preferences on hospital resources with limited capacity. to solve this complex scheduling problem effectively we have to address the following sub problems: determining the allocation of capacity to patient groups, setting dynamic rules for exceptions to the allocation, ordering timeslots based on scheduling efficiency, and incorporating patient preferences over appointment times in the scheduling process. we present a scheduling approach with optimized parameter values that solves these issues simultaneously. in our experiments, we show how our approach outperforms standard scheduling benchmarks for a wide range of scenarios, and how we can efficiently trade-off scheduling performance and fulfilling patient preferences.
conversational case-based reasoning in medical classification and diagnosis. in case-based reasoning (cbr) approaches to classification and diagnosis, a description of the problem to be solved is often assumed to be available in advance. conversational cbr (ccbr) is a more interactive approach in which the system is expected to play an active role in the selection of relevant tests to help minimize the number of problem features that the user needs to provide. we present a new algorithm for ccbr called inn(k) and demonstrate its ability to achieve high levels of accuracy on a selection of datasets related to medicine and health care, while often requiring the user to provide only a small subset of the problem features required by a standard k-nn classifier. another important benefit of inn(k) is a goal-driven approach to feature selection that enables a ccbr system to explain the relevance of any question it asks the user in terms of its current goal.
data-efficient information-theoretic test selection. we use the concept of conditional mutual information (mi) to approach problems involving the selection of variables in the area of medical diagnosis. computing mi requires estimates of joint distributions over collections of variables. however, in general computing accurate joint distributions conditioned on a large set of variables is expensive in terms of data and computing power. therefore, one must seek alternative ways to calculate the relevant quantities and still use all the available observations. we describe and compare a basic approach consisting of averaging mi estimates conditioned on individual observations and another approach where it is possible to condition on all observations at once by making some conditional independence assumptions. this yields a data-efficient variant of information maximization for test selection. we present experimental results on public heart disease data and data from a controlled study in the area of breast cancer diagnosis.
predicting the need to perform life-saving interventions in trauma patients by using new vital signs and artificial neural networks. previous work in risk stratification of critically injured patients involved artificial neural networks (anns) of various configurations tuned to process traditional vital signs and demographical, clinical, and laboratory data obtained via direct contact with the patient. we now report "new vital signs" (nvss) that are superior in distinguishing the injured and can be derived without hands-on patient contact. data from 262 trauma patients are presented, in whom nvss derived from electrocardiogram (ekg) analysis (heart-rate complexity and variability) were input into a commercially available ann. the endpoint was performance of life-saving interventions (lsis) such as intubation, cardiopulmonary resuscitation, chest-tube placement, needle chest decompression, and blood transfusion. we conclude that based on ekg-derived nvs alone, it is possible to accurately identify trauma patients who undergo lsis. our approach may permit development of a next-generation decision support system.
analysing clinical guidelines' contents with deontic and rhetorical structures. the computerisation of clinical guidelines can greatly benefit from the automatic analysis of their content using natural language processing techniques. because of the central role played by specific deontic structures, known as recommendations, it is possible to tune the processing step towards the recognition of such expressions, which can be used to structure key sections of the document. in this paper, we extend previous work on the automatic identification of guidelines' recommendations, by showing how rhetorical structure theory can be used to characterise the actual contents of elementary recommendations. the emphasis on causality and time in rst proves a powerful complement to the recognition of deontic structures and supports the identification of relevant knowledge, in particular for the identification of conditional structures, which play an important role for the subsequent analysis of recommendations.
using existing biomedical resources to detect and ground terms in biomedical literature. we present an approach towards the automatic detection of names of proteins, genes, species, etc. in biomedical literature and their grounding to widely accepted identifiers. the annotation is based on a large term list that contains the common expression of the terms, a normalization step that matches the terms with their actual representation in the texts, and a disambiguation step that resolves the ambiguity of matched terms. we describe various characteristics of the terms found in existing term resources and of the terms that are used in biomedical texts. we evaluate our results against a corpus of manually annotated protein mentions and achieve a precision of 57% and recall of 72%.
integrating healthcare knowledge artifacts for clinical decision support: towards semantic web based healthcare knowledge morphing. healthcare decision making demands the systematic integration of knowledge from multiple sources, such as clinical guidelines, clinical pathways, knowledge of practitioners and so on. we present a semantic web based approach for synthesizing health knowledge through the semantic modeling of healthcare knowledge as ontologies and reasoning over the ontologies to derive a morphed knowledge object. we demonstrate the application of our approach by generating morphed knowledge about prostate cancer clinical pathways.
discovering novel adverse drug events using natural language processing and mining of the electronic health record. this talk presents an overview of our research in use of medical knowledge, natural language processing, the electronic health record, and statistical methods to automatically discover novel adverse drug events, which are serious problems world-wide.
mining discriminant sequential patterns for aging brain. discovering new information about groups of genes implied in a disease is still challenging. microarrays are a powerful tool to analyse gene expression. in this paper, we propose a new approach outlining relationships between genes based on their ordered expressions. our contribution is twofold. first, we propose to use a new material, called sequential patterns, to be investigated by biologists. secondly, due to the expression matrice density, extracting sequential patterns from microarray datasets is far away from being easy. the aim of our proposal is to provide the biological experts with an efficient approach based on discriminant sequential patterns. results of various experiments on real biological data highlight the relevance of our proposal.
analysis of eeg epileptic signals with rough sets and support vector machines. epilepsy is a common chronic neurological disorder that impacts over 1% of the population. animal models are used to better understand epilepsy, particularly the mechanisms and the basis for better antiepileptic therapies. for animal studies, the ability to identify accurately seizures in electroencephalographic (eeg) recordings is critical, and the use of computational tools is likely to play an important role. electrical recording electrodes were implanted in rats before kainate-induced status epilepticus (one in each hippocampus and one on the surface of the cortex), and eeg data were collected with radio-telemetry. several data mining methods, such as wavelets, ffts, and neural networks, were used to develop algorithms for detecting seizures. rough sets, which were used as an additional feature selection technique in addition to the daubechies wavelets and the ffts, were also used in the detection algorithm. compared with the seizure-at-once method by using the rbf neural network classifier used earlier on the same data [12], the new method achieved higher recognition rates (i.e., 91%). furthermore, when the entire dataset was used, as compared to only 50% used earlier, preprocessing using wavelets, principal component analysis, and rough sets in concert with support vector machines resulted in accuracy of 94% in identifying epileptic seizures.
modelling screening mammography images: a probabilistic relational approach. computer-aided detection systems have as aim the increase of detection rates when analysing mammograms, by identifying features that are characteristic for breast cancer. in this research we aimed at using the features extracted from mammographic images in order to analyse the development of suspicious lesions. different from other approaches, we based our data modelling on object orientation. this allowed not only for a description of domain entities and their intrinsic relationships, but also for the application of relational probabilistic techniques, which can handle heterogeneous data instances both in terms of learning and inference.
detecting intuitive mentions of diseases in narrative clinical text. a significant portion of the clinical information content of narrative text documents in the medical record is only mentioned intuitively, but automated information extraction systems typically focus on explicitly mentioned concepts only. to extend the extraction of clinical information to intuitively mentioned diseases, we have developed a natural language processing application based on mmtx and on context analysis algorithms, enhanced with the detection of disease-specific concepts (e.g. medications used only for this disease), and values of some specific biomarkers. this application was developed for the i2b2 obesity challenge, a competition focused on the detection of patients with obesity or common comorbidities.
learning approach to analyze tumour heterogeneity in dce-mri data during anti-cancer treatment. the paper proposes a learning approach to support medical researchers in the context of in-vivo cancer imaging, and specifically in the analysis of dynamic contrast-enhanced mri (dce-mri) data. tumour heterogeneity is characterized by identifying regions with different vascular perfusion. the overall aim is to measure volume differences of such regions for two experimental groups: the treated group, to which an anticancer therapy is administered, and a control group. the proposed approach is based on a three-steps procedure: (i) robust features extraction from raw time-intensity curves, (ii) sample-regions identification manually traced by medical researchers on a small portion of input data, and (iii) overall segmentation by training a support vector machine (svm) to classify the mri voxels according to the previously identified cancer areas. in this way a non-invasive method for the analysis of the treatment efficacy is obtained as shown by the promising results reported in our experiments.
mining safety signals in spontaneous reports database using concept analysis. in pharmacovigilance, linking the adverse reactions by patients to drugs they took is a key activity typically based on the analysis of patient reports. yet generating potentially interesting pairs (drug, reaction) from a record database is a complex task, especially when many drugs are involved. to limit the generation effort, we exploit the frequently occurring patterns in the database and form association rules on top of them. moreover, only rules of minimal premise are considered as output by concept analysis tools, which are then filtered through standard measures for statistical significance. we illustrate the process on a small database of anti-hiv drugs involved in the haart therapy while larger-scope validation within the database of the french medicines agency is also reported.
online prediction of ovarian cancer. in this paper we apply computer learning methods to the diagnosis of ovarian cancer using the level of the standard biomarker ca125 in conjunction with information provided by mass spectrometry. our algorithm gives probability predictions for the disease. to check the power of our algorithm we use it to test the hypothesis that ca125 and the peaks do not contain useful information for the prediction of the disease at a particular time before the diagnosis. it produces p-values that are less than those produced by an algorithm that has been previously applied to this data set. our conclusion is that the proposed algorithm is especially reliable for prediction the ovarian cancer on some stages.
subgroup discovery in data sets with multi-dimensional responses: a method and a case study in traumatology. biomedical experimental data sets may often include many features both at input (description of cases, treatments, or experimental parameters) and output (outcome description). state-of-the-art data mining techniques can deal with such data, but would consider only one output feature at the time, disregarding any dependencies among them. in the paper, we propose the technique that can treat many output features simultaneously, aiming at finding subgroups of cases that are similar both in input and output space. the method is based on k-medoids clustering and analysis of contingency tables, and reports on case subgroups with significant dependency in input and output space. we have used this technique in explorative analysis of clinical data on femoral neck fractures. the subgroups discovered in our study were considered meaningful by the participating domain expert, and sparked a number of ideas for hypothesis to be further experimentally tested.
automatic detecting documents containing personal health information. with the increasing usage of computers and internet, personal health information (phi) is distributed across multiple institutes and often scattered on multiple devices and stored in diverse formats. non-traditional medical records such as emails and e-documents containing phi are in a high risk of privacy leakage. we are facing the challenges of locating and managing phi in the distributed environment. the goal of this study is to classify electronic documents into phi and non-phi. a supervised machine learning method was used for this text categorization task. three classifiers: svm, decision tree and naive bayesian were used and tested on three data sets. lexical, semantic and syntactic features and their combinations were compared in terms of their effectiveness of classifying phi documents. the results show that combining semantic and/or syntactic with lexical features is more effective than lexical features alone for phi classification. the supervised machine learning method is effective in classifying documents into phi and non-phi.
a mobile clinical decision support system for clubfoot treatment. in current congenital clubfoot treatment, clinicians use paper forms to register and monitor the treatment process. routines for registration and archiving are scarce, and the guideline for treating clubfoot is not always followed strictly. this paper presents a pda-based system (gensupport) that can support the registration of patient information, supervise the treatment process, as well as provide advice during treatment. gensupport has been evaluated in a pilot study.
feasibility of case-based beam generation for robotic radiosurgery. robotic radiosurgery uses the kinematic flexibility of a robotic arm to target tumors and lesions from many different directions. this approach allows to focus the dose to the target region while sparing healthy surrounding tissue. however, the flexibility in the placement of treatment beams is also a challenge during treatment planning. so far, a randomized beam generation heuristic has been proven to be most robust in clinical practice. yet, for prevalent types of cancer similarities in patient anatomy and dose prescription exist. we propose a case-based method to solve the planning problem for a new patient by adapting beam sets from successful previous treatments. preliminary experimental results indicate that the novel method could lead to faster treatment planning.
mealtime blood glucose classifier based on fuzzy logic for the diabtel telemedicine system. the accurate interpretation of blood glucose (bg) values is essential for diabetes care. however, bg monitoring data does not provide complete information about associated meal and moment of measurement, unless patients fulfil it manually. an automatic classification of incomplete bg data helps to a more accurate interpretation, contributing to knowledge management (km) tools that support decision-making in a telemedicine system. this work presents a fuzzy rule-based classifier integrated in a km agent of the diabtel telemedicine architecture, to automatically classify bg measurements into meal intervals and moments of measurement. fuzzy logic (fl) tackles with the incompleteness of bg measurements and provides a semantic expressivity quite close to natural language used by physicians, what makes easier the system output interpretation. the best mealtime classifier provides an accuracy of 77.26% and does not increase significantly the km analysis times. results of classification are used to extract anomalous trends in the patient's data.
a system for the acquisition, interactive exploration and annotation of stereoscopic images. we present in the paper a system that integrates all hardware and software to extract information from 3d images of skin. it is composed of a lighting equipment and stereoscopic cameras, a camera calibration algorithm that uses evolutionary principles, virtual reality equipment to visualize the images and interact with them in 3d, a set of interactive features to annotate images, to create links between them and to build a 3d hypermedia. we present an experimental study and an application of our tool on faces skin.
effect of background correction on cancer classification with gene expression data. this paper empirically compares six background correction methods aimed at removing unspecific background noise of the overall signal level measured by a scanner across microarrays. using three published cdna microarray datasets we investigated the effect of background correction on cancer classification in terms of the predictive performance of two classifiers (k-nn and support vector machine with linear kernel) induced from microarray data where a particular background correction method is applied, individually and in combination with a single-bias or double-bias-removal normalization method.
a framework for multi-class learning in micro-array data analysis. a large pool of techniques have already been developed for analyzing micro-array datasets but less attention has been paid on multi-class classification problems. in this context, selecting features and quantify classifiers may be hard since only few training examples are available in each single class. this paper demonstrates a framework for multi-class learning that considers learning a classifier within each class independently and grouping all relevant features in a single dataset. next step, that dataset is presented as input to a classification algorithm that learns a global classifier across the classes. we analyze two micro-array datasets using the proposed framework. results demonstrate that our approach is capable of identifying a small number of influential genes within each class while the global classifier across the classes performs better than existing multi-class learning methods.
prediction of mechanical lung parameters using gaussian process models. mechanical ventilation can cause severe lung damage by inadequate adjustment of the ventilator. we introduce a machine learning approach to predict the pressure-dependent, non-linear lung compliance, a crucial parameter to estimate lung protective ventilation settings. features were extracted by fitting a generally accepted lumped parameter model to time series data obtained from ards (adult respiratory distress syndrome) patients. numerical prediction was performed by use of gaussian processes, a probabilistic, non-parametric modeling approach for non-linear functions.
a hybrid approach to clinical guideline and to basic medical knowledge conformance. several computer-based approaches to clinical guidelines have been developed in the last two decades. however, only recently the community has started to cope with the fact that clinical guidelines are just a part of the medical knowledge that physicians have to take into account when treating patients. the procedural knowledge in the guidelines have to be complemented by additional declarative medical knowledge. in this paper, we analyse such an interaction, by studying the conformance problem, defined as evaluating the adherence of a set of performed clinical actions w.r.t. the behaviour recommended by the guideline and by the medical knowledge.
temporal data mining of hiv registries: results from a 25 years follow-up. the human immunodeficiency virus (hiv) causes a pandemic infection in humans, with millions of people infected every year. although the highly active antiretroviral therapy reduced the number of aids cases since 1996 by significantly increasing the disease-free survival time, the therapy failure rate is still high due to hiv treatment complexity. to better understand the changes in the outcomes of hiv patients we have applied temporal data mining techniques to the analysis of the data collected since 1981 by the infectious diseases unit of the hospital clínic in barcelona, spain. we run a precedence temporal rule extraction algorithm on three different temporal periods, looking for two types of treatment failures: viral failure and toxic failure, corresponding to events of clinical interest to assess the treatment outcomes. the analysis allowed to extract different typical patterns related to each period and to meaningfully interpret the previous and current behaviour of hiv therapy.
ontology-based personalization and modulation of computerized cognitive exercises. cognitive rehabilitation may benefit from computer-based approaches that, with respect to paper-based ones, allow managing big amounts of stimuli (images, sounds, written texts) and combining them to create ever-new exercises. moreover, they allow storing and analysing patients' performance, that may vary in time, thus increasing/decreasing difficulty of the exercises accordingly. an ontological organisation of the stimuli may help to automatically generate patient-tailored exercises, accounting for patients' performance, skills and preferences.
analyzing critical process models through behavior model synthesis. process models capture tasks performed by agents together with their control flow. building and analyzing such models is important but difficult in certain areas such as safety-critical healthcare processes. tool-supported techniques are needed to find and correct flaws in such processes. on another hand, event-based formalisms such as labeled transition systems (lts) prove effective for analyzing agent behaviors.
using quantitative analysis to implement autonomic it systems. the software underpinning today's it systems needs to adapt dynamically and predictably to rapid changes in system workload, environment and objectives. we describe a software framework that achieves such adaptiveness for it systems whose components can be modelled as markov chains. the framework comprises (i) an autonomic architecture that uses markov-chain quantitative analysis to dynamically adjust the parameters of an it system in line with its state, environment and objectives; and (ii) a method for developing instances of this architecture for real-world systems. two case studies are presented that use the framework successfully for the dynamic power management of disk drives, and for the adaptive management of cluster availability within data centres, respectively.
a case-study on using an automated in-process software engineering measurement and analysis system in an industrial environment. automated systems for measurement and analysis are not adopted on a large scale in companies, despite the opportunities they offer. the fear of the “big brother” and the lack of reports giving insights into the real adoption process and concrete usages in industry are barriers to this adoption. we report on a case-study on the adoption and long-term usage (2 years of running system) of such a system in a company focusing on the adoption process and the related challenges we encountered.
taming dynamically adaptive systems using models and aspects. since software systems need to be continuously available under varying conditions, their ability to evolve at runtime is increasingly seen as one key issue. modern programming frameworks already provide support for dynamic adaptations. however the high-variability of features in dynamic adaptive systems (das) introduces an explosion of possible runtime system configurations (often called modes) and mode transitions. designing these configurations and their transitions is tedious and error-prone, making the system feature evolution difficult. while aspect-oriented modeling (aom) was introduced to improve the modularity of software, this paper presents how an aom approach can be used to tame the combinatorial explosion of das modes. using aom techniques, we derive a wide range of modes by weaving aspects into an explicit model reflecting the runtime system. we use these generated modes to automatically adapt the system. we validate our approach on an adaptive middleware for home-automation currently deployed in rennes metropolis.
predicting faults using the complexity of code changes. predicting the incidence of faults in code has been commonly associated with measuring complexity. in this paper, we propose complexity metrics that are based on the code change process instead of on the code. we conjecture that a complex code change process negatively affects its product, i.e., the software system. we validate our hypothesis empirically through a case study using data derived from the change history for six large open source projects. our case study shows that our change complexity metrics are better predictors of fault potential in comparison to other well-known historical predictors of faults, i.e., prior modifications and prior faults.
semdiff: analysis and recommendation support for api evolution. as a framework evolves, changes in its application programming interface (api) can break client programs that extend the framework. repairing a client program can be a challenging task because developers need to understand the context surrounding the api change. this paper describes semdiff, a tool that recommends replacements for framework methods that were accessed by a client program and deleted during the evolution of the framework. semdiff recommends replacements for non-trivial changes undiscovered by other change-detection techniques and also enables developers to look at the context of the changes that led to the deletion of a framework method.
feedback-driven requirements engineering: the heuristic requirements assistant. the complexity of today's software systems is constantly increasing. as a result, requirements for these systems become more comprehensive and complicated. in this setting, requirements engineers struggle to capture consistent and complete requirements of high quality. we propose a feedback-centric requirements editor to help analysts controlling the information overload. our hera tool provides analysts with important data from various feedback facilities. the feedback is directly given based on the input to the editor. on the one hand, it is based on heuristic rules, on the other hand, on automatically derived models. thus, when new requirements are added, the analyst gets important information on how consistent these requirements are with the existing ones.
early aspects at icse 2009: workshop on aspect-oriented requirements engineering and architecture design. the “early aspects @ icse'09” is the 15th edition of the workshops on early aspects. early aspects focuses on the systematic identification, modularization, representation and composition of crosscutting concerns, and their impact at the requirements engineering and architecture derivation activities. the primary aim of the present workshop is to continue the maturation of early aspects as a discipline in order to identify the problems and potential solutions in requirements engineering, domain engineering and software architecture design. the present edition of the workshop provides a forum for an open set of early-aspects related topics, without restricting to a specific theme or domain.
synthesis of timed behavior from scenarios in the fujaba real-time tool suite. based on a well-defined component architecture the tool supports the synthesis of so-called real-time statecharts from timed sequence diagrams. the two step synthesis process addresses the existing scalability problems by a proper decomposition and allows the user to define particular restrictions on the resulting statecharts.
model evolution by run-time parameter adaptation. models can help software engineers to reason about design-time decisions before implementing a system. this paper focuses on models that deal with non-functional properties, such as reliability and performance. to build such models, one must rely on numerical estimates of various parameters provided by domain experts or extracted by other similar systems. unfortunately, estimates are seldom correct. in addition, in dynamic environments, the value of parameters may change over time. we discuss an approach that addresses these issues by keeping models alive at run time and feeding a bayesian estimator with data collected from the running system, which produces updated parameters. the updated model provides an increasingly better representation of the system. by analyzing the updated model at run time, it is possible to detect or predict if a desired property is, or will be, violated by the running implementation. requirement violations may trigger automatic reconfigurations or recovery actions aimed at guaranteeing the desired goals. we illustrate a working framework supporting our methodology and apply it to an example in which a web service orchestrated composition is modeled through a discrete time markov chain. numerical simulations show the effectiveness of the approach.
lightweight fault-localization using multiple coverage types. lightweight fault-localization techniques use program coverage to isolate the parts of the code that are most suspicious of being faulty. in this paper, we present the results of a study of three types of program coverage—statements, branches, and data dependencies—to compare their effectiveness in localizing faults. the study shows that no single coverage type performs best for all faults—different kinds of faults are best localized by different coverage types. based on these results, we present a new coverage-based approach to fault localization that leverages the unique qualities of each coverage type by combining them. because data dependencies are noticeably more expensive to monitor than branches, we also investigate the effects of replacing data-dependence coverage with an approximation inferred from branch coverage. our empirical results show that (1) the cost of fault localization using combinations of coverage is less than using any individual coverage type and closer to the best case (without knowing in advance which kinds of faults are present), and (2) using inferred data-dependence coverage retains most of the benefits of combinations.
vida: visual interactive debugging. software debugging is time-consuming and effort-consuming. although software debugging, especially fault-localization, has been studied for long, few practical debugging tools have been developed and used by the industry. in this paper we present vida, a visual interactive debugging tool, which has been integrated with the eclipse integrated development environment to support a programmer's debugging process. during the programmer's conventional debugging process, vida continuously recommends break-points for the programmer based on the analysis of execution information and the gathered feedback from the programmer. moreover, vida provides a program outline to help the programmer choose breakpoints and visualizes the static dependency relation to help the programmer make estimation at breakpoints.
itaca: an integrated toolbox for the automatic composition and adaptation of web services. adaptation is of utmost importance in systems developed by assembling reusable software services accessed through their public interfaces. this process aims at solving, as automatically as possible, mismatch cases which may be given at the different interoperability levels among interfaces by synthesizing a mediating adaptor. in this paper, we present a toolbox that fully supports the adaptation process, including: (i) different methods to construct adaptation contracts involving several services; (ii) simulation and verification techniques which help to identify and correct erroneous behaviours or deadlocking executions; and (iii) techniques for the generation of centralized or distributed adaptor protocols based on the aforementioned contracts. our toolbox relates our models with implementation platforms, starting with the automatic extraction of behavioural models from existing interface descriptions, until the final adaptor implementation is generated for the target platform.
reman: a pro-active reputation management infrastructure for composite web services. reman is a reputation management infrastructure for composite web services. it supports the aggregation of client feedback on the perceived qos of external services, using reputation mechanisms to build service rankings. changes in rankings are pro-actively notified to composite service clients to enable self-tuning properties in their execution.
mining exception-handling rules as sequence association rules. programming languages such as java and c++ provide exception-handling constructs to handle exception conditions. applications are expected to handle these exception conditions and take necessary recovery actions such as releasing opened database connections. however, exception-handling rules that describe these necessary recovery actions are often not available in practice. to address this issue, we develop a novel approach that mines exception-handling rules as sequence association rules of the form “(fc1c1…fccn) ∧ fca ⇒ (fce1…fcem)”. this rule describes that function call fca should be followed by a sequence of function calls (fce1…fcem) when fca is preceded by a sequence of function calls (fce1…fccn). such form of rules is required to characterize common exception-handling rules. we show the usefulness of these mined rules by applying them on five real-world applications (including 285 kloc) to detect violations in our evaluation. our empirical results show that our approach mines 294 real exception-handling rules in these five applications and also detects 160 defects, where 87 defects are new defects that are not found by a previous related approach.
how we refactor, and how we know it. much of what we know about how programmers refactor in the wild is based on studies that examine just a few software projects. researchers have rarely taken the time to replicate these studies in other contexts or to examine the assumptions on which they are based. to help put refactoring research on a sound scientific basis, we draw conclusions using four data sets spanning more than 13 000 developers, 240 000 tool-assisted refactorings, 2500 developer hours, and 3400 version control commits. using these data, we cast doubt on several previously stated assumptions about how programmers refactor, while validating others. for example, we find that programmers frequently do not indicate refactoring activity in commit logs, which contradicts assumptions made by several previous researchers. in contrast, we were able to confirm the assumption that programmers do frequently intersperse refactoring with other program changes. by confirming assumptions and replicating studies made by other researchers, we can have greater confidence that those researchers' conclusions are generalizable.
tesseract: interactive visual exploration of socio-technical relationships in software development. software developers have long known that project success requires a robust understanding of both technical and social linkages. however, research has largely considered these independently. research on networks of technical artifacts focuses on techniques like code analysis or mining project archives. social network analysis has been used to capture information about relations among people. yet, each type of information is often far more useful when combined, as when the “goodness” of social networks is judged by the patterns of dependencies in the technical artifacts. to bring such information together, we have developed tesseract, an interactive exploratory environment that utilizes cross-linked displays to visualize the myriad relationships between artifacts, developers, bugs, and communications. we evaluated tesseract by (1) demonstrating its feasibility with gnome project data (2) assessing its usability via informal user evaluations, and (3) verifying its suitability for the open source community via semi-structured interviews.
the impact of process choice in high maturity environments: an empirical analysis. we present the results of a three year field study of the software development process choices made by project teams at two leading offshore vendors. in particular, we focus on the performance implications of project teams that chose to augment structured, plan-driven processes to implement the cmm level-5 key process areas (kpas) with agile methods. our analysis of 112 software projects reveals that the decision to augment the firm-recommended, plan-driven approach with improvised, agile methods was significantly affected by the extent of client knowledge and involvement, the newness of technology, and the project size. furthermore this decision had a significant and mostly positive impact on project performance indicators such as reuse, rework, defect density, and productivity
taming coincidental correctness: coverage refinement with context patterns to improve fault localization. recent techniques for fault localization leverage code coverage to address the high cost problem of debugging. these techniques exploit the correlations between program failures and the coverage of program entities as the clue in locating faults. experimental evidence shows that the effectiveness of these techniques can be affected adversely by coincidental correctness, which occurs when a fault is executed but no failure is detected. in this paper, we propose an approach to address this problem. we refine code coverage of test runs using control- and data-flow patterns prescribed by different fault types. we conjecture that this extra information, which we call context patterns, can strengthen the correlations between program failures and the coverage of faulty program entities, making it easier for fault localization techniques to locate the faults. to evaluate the proposed approach, we have conducted a mutation analysis on three real world programs and cross-validated the results with real faults. the experimental results consistently show that coverage refinement is effective in easing the coincidental correctness problem in fault localization techniques.
learning operational requirements from goal models. goal-oriented methods have increasingly been recognised as an effective means for eliciting, elaborating, analysing and specifying software requirements. a key activity in these approaches is the elaboration of a correct and complete set of opertional requirements, in the form of pre- and trigger-conditions, that guarantee the system goals. few existing approaches provide support for this crucial task and mainly rely on significant effort and expertise of the engineer. in this paper we propose a tool-based framework that combines model checking, inductive learning and scenarios for elaborating operational requirements from goal models. this is an iterative process that requires the engineer to identify positive and negative scenarios from counterexamples to the goals, generated using model checking, and to select operational requirements from suggestions computed by inductive learning.
succession: measuring transfer of code and developer productivity. code ownership transfer or succession is a crucial ingredient in open source code reuse and in offshoring projects. measuring succession can help understand factors that affect the success of such transfers and suggest ways to make them more efficient. we propose and evaluate several methods to measure succession based on the chronology and traces of developer activities. using ten instances of offshoring succession identified through interviews, we find that the best succession measure can accurately pinpoint the most likely mentors. we model the productivity ratio of more than 1000 developer pairs involved in the succession to test conjectures formulated using the organizational socialization theory and find the ratio to decrease for instances of offshoring and for mentors who have worked primarily on a single project or have transferred ownership for their non-primary project code, thus supporting a theory-based conjectures and providing practical suggestions on how to improve succession.
the secret life of bugs: going past the errors and omissions in software repositories. every bug has a story behind it. the people that discover and resolve it need to coordinate, to get information from documents, tools, or other people, and to navigate through issues of accountability, ownership, and organizational structure. this paper reports on a field study of coordination activities around bug fixing that used a combination of case study research and a survey of software professionals. results show that the histories of even simple bugs are strongly dependent on social, organizational, and technical knowledge that cannot be solely extracted through automation of electronic repositories, and that such automation provides incomplete and often erroneous accounts of coordination. the paper uses rich bug histories and survey results to identify common bug fixing coordination patterns and to provide implications for tool designers and researchers of coordination in software development.
transtrl: an automatic need-to-translate string locator for software internationalization. software internationalization is often necessary when distributing software applications to different regions around the world. in many cases, developers often do not internationalize a software application at the beginning of the development stage. to internationalize such an existing application, developers need to externalize some hard-coded constant strings to resource files, so that translators can easily translate the application to be in a local language without modifying its source code. since not all the constant strings require externalization, locating those need-to-translate constant strings is a basic task that the developers must conduct. in this paper, we present transtrl, an eclipse plug-in tool that automatically locates need-to-translate constant strings in java code. our tool maintains a pre-collected list of api methods related to the graphical user interface (gui), and then searches for need-to-translate strings in the source code starting from the invocations of these api methods using string-taint analysis.
flexsync: an aspect-oriented approach to java synchronization. designers of concurrent programs are faced with many choices of synchronization mechanisms, among which clear functional trade-offs exist. making synchronization customizable is highly desirable as different deployment scenarios of the same program often prioritize synchronization choices differently. unfortunately, such customizations cannot be accomplished in the conventional non-modular implementation of synchronization. to enable customizability, we present flexsync, an aspect oriented synchronization library, to enable the modular reasoning and the declarative specification of synchronization. complex java systems can simultaneously work with multiple synchronization mechanisms without any code changes. the flexsync load-time weaver performs deployment time optimizations and ensures these synchronization mechanisms consistently interact with each other and with the core system. we evaluated flexsync on commercially used complex java systems and observed significant speedups as a result of the deployment-specific customization.
refactoring sequential java code for concurrency via concurrent libraries. parallelizing existing sequential programs to run efficiently on multicores is hard. the java 5 package java.util.concurrent (j.u.c.) supports writing concurrent programs: much of the complexity of writing thread-safe and scalable programs is hidden in the library. to use this package, programmers still need to reengineer existing code. this is tedious because it requires changing many lines of code, is error-prone because programmers can use the wrong apis, and is omission-prone because programmers can miss opportunities to use the enhanced apis. this paper presents our tool, concurrencer, that enables programmers to refactor sequential code into parallel code that uses three j.u.c. concurrent utilities. concurrencer does not require any program annotations. its transformations span multiple, non-adjacent, program statements. a find-and-replace tool can not perform such transformations, which require program analysis. empirical evaluation shows that concurrencer refactors code effectively: concurrencer correctly identifies and applies transformations that some open-source developers overlooked, and the converted code exhibits good speedup.
alitheia core: an extensible software quality monitoring platform. research in the fields of software quality and maintainability requires the analysis of large quantities of data, which often originate from open source software projects. pre-processing data, calculating metrics, and synthesizing composite results from a large corpus of project artefacts is a tedious and error prone task lacking direct scientific value. the alitheia core tool is an extensible platform for software quality analysis that is designed specifically to facilitate software engineering research on large and diverse data sources, by integrating data collection and preprocessing phases with an array of analysis services, and presenting the researcher with an easy to use extension mechanism. the system has been used to process several projects successfully, forming the basis of an emerging ecosystem of quality analysis tools.
automatically finding patches using genetic programming. automatic program repair has been a longstanding goal in software engineering, yet debugging remains a largely manual process. we introduce a fully automated method for locating and repairing bugs in software. the approach works on off-the-shelf legacy applications and does not require formal specifications, program annotations or special coding practices. once a program fault is discovered, an extended form of genetic programming is used to evolve program variants until one is found that both retains required functionality and also avoids the defect in question. standard test cases are used to exercise the fault and to encode program requirements. after a successful repair has been discovered, it is minimized using structural differencing algorithms and delta debugging. we describe the proposed method and report experimental results demonstrating that it can successfully repair ten different c programs totaling 63,000 lines in under 200 seconds, on average.
ldiff: an enhanced line differencing tool. differencing tools are highly relevant for a series of software engineering tasks, including analyzing developers' activities, assessing the changeability of software artifacts, and monitoring the maintenance of critical assets such as source clones and vulnerable instructions. this tool demonstration shows the features of ldiff, an enhanced, language-independent line differencing tool. l-diff builds upon the unix diff and overcomes its limitations in determining whether an artifact line has been changed or is the result of additions and removals, and in tracking artifact fragments that have been moved upward or downward within the file. the paper describes the tool and shows its capability of analyzing changes on different kinds of software artifacts, including use cases, code developed with different programming languages, and test cases.
equality and hashing for (almost) free: generating implementations from abstraction functions. in an object-oriented language such as java, every class requires implementations of two special methods, one for determining equality and one for computing hash codes. although the specification of these methods is usually straightforward, they can be hard to code (due to subclassing, delegation, cyclic references, and other factors) and often harbor subtle faults. a technique is presented that simplifies this task. instead of writing code for the methods, the programmer gives, as a brief annotation, an abstraction function that defines an abstract view of an object's representation, and sometimes an additional observer in the form of an iterator method. equality and hash codes are then computed in library code that uses reflection to read the annotations. experiments on a variety of programs suggest that, in comparison to writing the methods by hand, our technique requires less text from the programmer and results in methods that are more often correct.
holmes: effective statistical debugging via efficient path profiling. statistical debugging aims to automate the process of isolating bugs by profiling several runs of the program and using statistical analysis to pinpoint the likely causes of failure. in this paper, we investigate the impact of using richer program profiles such as path profiles on the effectiveness of bug isolation. we describe a statistical debugging tool called holmes that isolates bugs by finding paths that correlate with failure. we also present an adaptive version of holmes that uses iterative, bug-directed profiling to lower execution time and space overheads. we evaluate holmes using programs from the sir benchmark suite and some large, real-world applications. our results indicate that path profiles can help isolate bugs more precisely by providing more information about the context in which bugs occur. moreover, bug-directed profiling can efficiently isolate bugs with low overheads, providing a scalable and accurate alternative to sparse random sampling.
validation of contracts using enabledness preserving finite state abstractions. pre/post condition-based specifications are common-place in a variety of software engineering activities that range from requirements through to design and implementation. the fragmented nature of these specifications can hinder validation as it is difficult to understand if the specifications for the various operations fit together well. in this paper we propose a novel technique for automatically constructing abstractions in the form of behaviour models from pre/post condition-based specifications. the level of abstraction at which such models are constructed preserves enabledness of sets of operations, resulting in a finite model that is intuitive to validate and which facilitates tracing back to the specification for debugging. the paper also reports on the application of the approach to an industrial strength protocol specification in which concerns were identified.
improving api documentation usability with knowledge pushing. the documentation of api functions typically conveys detailed specifications for the benefit of interested readers. in some cases, however, it also contains usage directives, such as rules or caveats, of which authors of invoking code must be made aware to prevent errors and inefficiencies. there is a risk that these directives may be “lost” within the verbose text, or that the text would not be read because there are so many invoked functions. to address these concerns for java, an eclipse plug-in named emoose decorates method invocations whose targets have associated directives. our goal is to lead readers to investigate further, which we aid by highlighting the tagged directives in the javadoc hover. we present a lab study that demonstrates the directive awareness problem in traditional documentation use and the potential benefits of our approach.
featurehouse: language-independent, automated software composition. superimposition is a composition technique that has been applied successfully in many areas of software development. although superimposition is a general-purpose concept, it has been (re)invented and implemented individually for various kinds of software artifacts. we unify languages and tools that rely on superimposition by using the language-independent model of feature structure trees (fsts). on the basis of the fst model, we propose a general approach to the composition of software artifacts written in different languages, furthermore, we offer a supporting framework and tool chain, called featurehouse. we use attribute grammars to automate the integration of additional languages, in particular, we have integrated java, c#, c, haskell, javacc, and xml. several case studies demonstrate the practicality and scalability of our approach and reveal insights into the properties a language must have in order to be ready for superimposition.
contextserv: a platform for rapid and flexible development of context-aware web services. context-aware web services are currently emerging as an important technology for building innovative context-aware applications. unfortunately, context-aware web services are still difficult to build. this paper describes contextserv, a platform for rapid development of context-aware web services. contextserv adopts model-driven development where context-aware web services are specified using contextuml, a uml based modeling language. the platform also offers a set of automated tools for generating and deploying executable implementations of context-aware web services. this paper presents the motivation, system design, implementation, and usage of contextserv.
a toolset for automated failure analysis. classic fault localization techniques can automatically provide information about the suspicious code blocks that are likely responsible for observed failures. this information is useful, but not sufficient to completely understand the causes of failing executions, which still require further (time-consuming) investigations to be exactly identified.
automatic dimension inference and checking for object-oriented programs. this paper introduces unifi, a tool that attempts to automatically detect dimension errors in java programs. unifi infers dimensional relationships across primitive type and string variables in a program, using an inter-procedural, context-sensitive analysis. it then monitors these dimensional relationships as the program evolves, flagging inconsistencies that may be errors. unifi requires no programmer annotations, and supports arbitrary program-specific dimensions, thus providing fine-grained dimensional consistency checking. unifi exploits features of object-oriented languages, but can be used for other languages as well. we have run unifi on real-life java code and found that it is useful in exposing dimension errors. we present a case study of using unifi on nightly builds of a 19,000 line code base as it evolved over 10 months.
junitmx - a change-aware unit testing tool. developers use unit testing to improve the quality of software systems. current development tools for unit testing help with automating test execution, with reporting results, and with generating test stubs. however, they offer no aid for designing tests aimed specifically at exercising the effects of changes to a program. this paper describes a unit testing tool that leverages a change model to assist developers in the creation of new unit tests. the tool provides developers with quantitative feedback and detailed information about change effects, which not only facilitate the writing of more effective tests, but also motivate developers with an achievable coverage goal.
smarttutor: creating ide-based interactive tutorials via editable replay. interactive tutorials, like eclipse's cheat sheets, are good for novice programmers to learn how to perform tasks (e.g., checking out a cvs project) in an integrated development environment (ide). creating these tutorials often requires programming effort that is time-consuming and difficult. in this paper, we propose an approach using editable replay of user actions to help authors create interactive tutorials with little programming effort. user actions of performing a task can be recorded, edited, and presented as a tutorial. the tutorial can be replayed interactively for mentoring. we present our smarttutor implementation in the eclipse ide and conduct a preliminary evaluation on it, which demonstrates efficiency gains for the tutorial authors.
reasoning about edits to feature models. features express the variabilities and commonalities among programs in a software product line (spl). a feature model defines the valid combinations of features, where each combination corresponds to a program in an spl. spls and their feature models evolve over time. we classify the evolution of a feature model via modifications as refactorings, specializations, generalizations, or arbitrary edits. we present an algorithm to reason about feature model edits to help designers determine how the program membership of an spl has changed. our algorithm takes two feature models as input (before and after edit versions), where the set of features in both models are not necessarily the same, and it automatically computes the change classification. our algorithm is able to give examples of added or deleted products and efficiently classifies edits to even large models that have thousands of features.
modular string-sensitive permission analysis with demand-driven precision. in modern software systems, programs are obtained by dynamically assembling components. this has made it necessary to subject component providers to access-control restrictions. what permissions should be granted to each component? too few permissions may cause run-time authorization failures, too many constitute a security hole. we have designed and implemented a composite algorithm for precise static permission analysis for java and the clr. unlike previous work, the analysis is modular and fully integrated with a novel slicing-based string analysis that is used to statically compute the string values defining a permission and disambiguate permission propagation paths. the results of our research prototype on production-level java code support the effectiveness, practicality, and precision of our techniques, and show outstanding improvement over previous work.
featureide: a tool framework for feature-oriented software development. tools support is crucial for the acceptance of a new programming language. however, providing such tool support is a huge investment that can usually not be provided for a research language. with featureide, we have built an ide for ahead that integrates all phases of feature-oriented software development. to reuse this investment for other tools and languages, we refactored featureide into an open source framework that encapsulates the common ideas of feature-oriented software development and that can be reused and extended beyond ahead. among others, we implemented extensions for featurec++ and featurehouse, but in general, featureide is open for everybody to showcase new research results and make them usable to a wide audience of students, researchers, and practitioners.
how tagging helps bridge the gap between social and technical aspects in software development. empirical research on collaborative software development practices indicates that technical and social aspects of software development are often intertwined. the processes followed are tacit and constantly evolving, thus not all of them are amenable to formal tool support. in this paper, we explore how “tagging”, a lightweight social computing mechanism, is used to bridge the gap between technical and social aspects of managing work items. we present the results from an empirical study on how tagging has been adopted and adapted over the past two years of a large project with 175 developers. our research shows that the tagging mechanism was eagerly adopted by the team, and that it has become a significant part of many informal processes. our findings indicate that lightweight informal tool support, prevalent in the social computing domain, may play an important role in improving team-based software development practices.
taint-based directed whitebox fuzzing. we present a new automated white box fuzzing technique and a tool, buzzfuzz, that implements this technique. unlike standard fuzzing techniques, which randomly change parts of the input file with little or no information about the underlying syntactic structure of the file, buzzfuzz uses dynamic taint tracing to automatically locate regions of original seed input files that influence values used at key program attack points (points where the program may contain an error). buzzfuzz then automatically generates new fuzzed test input files by fuzzing these identified regions of the original seed input files. because these new test files typically preserve the underlying syntactic structure of the original seed input files, they tend to make it past the initial input parsing components to exercise code deep within the semantic core of the computation. we have used buzzfuzz to automatically find errors in two open-source applications: swfdec (an adobe flash player) and mupdf (a pdf viewer). our results indicate that our new directed fuzzing technique can effectively expose errors located deep within large programs. because the directed fuzzing technique uses taint to automatically discover and exploit information about the input file format, it is especially appropriate for testing programs that have complex, highly structured input file formats.
concernlines: a timeline view of co-occurring concerns. understanding the evolution of a software system requires understanding how information about the release history, non-functional requirements and project milestones relates to functional requirements on the software components. this short paper describes a new tool, called concernlines, that supports this cognitive process by visualizing co-occurring concerns over time.
clonedetective - a workbench for clone detection research. the area of clone detection has considerably evolved over the last decade, leading to approaches with better results, but at the same time using more elaborate algorithms and tool chains. in our opinion a level has been reached, where the initial investment required to setup a clone detection tool chain and the code infrastructure required for experimenting with new heuristics and algorithms seriously hampers the exploration of novel solutions or specific case studies. as a solution, this paper presents clonedetective, an open source framework and tool chain for clone detection, which is especially geared towards configurability and extendability and thus supports the preparation and conduction of clone detection research.
how to avoid drastic software process change (using stochastic stability). before performing drastic changes to a project, it is worthwhile to thoroughly explore the available options within the current structure of a project. an alternative to drastic change are internal changes that adjust current options within a software project. in this paper, we show that the effects of numerous internal changes can out-weigh the effects of drastic changes. that is, the benefits of drastic change can often be achieved without disrupting a project.
mints: a general framework and tool for supporting test-suite minimization. test-suite minimization techniques aim to eliminate redundant test cases from a test-suite based on some criteria, such as coverage or fault-detection capability. most existing test-suite minimization techniques have two main limitations: they perform minimization based on a single criterion and produce suboptimal solutions. in this paper, we propose a test-suite minimization framework that overcomes these limitations by allowing testers to (1) easily encode a wide spectrum of test-suite minimization problems, (2) handle problems that involve any number of criteria, and (3) compute optimal solutions by leveraging modern integer linear programming solvers. we implemented our framework in a tool, called mints, that is freely-available and can be interfaced with a number of different state-of-the-art solvers. our empirical evaluation shows that mints can be used to instantiate a number of different test-suite minimization problems and efficiently find an optimal solution for such problems using different solvers.
wise: automated test generation for worst-case complexity. program analysis and automated test generation have primarily been used to find correctness bugs. we present complexity testing, a novel automated test generation technique to find performance bugs. our complexity testing algorithm, which we call wise (worst-case inputs from symbolic execution), operates on a program accepting inputs of arbitrary size. for each input size, wise attempts to construct an input which exhibits the worst-case computational complexity of the program. wise uses exhaustive test generation for small input sizes and generalizes the result of executing the program on those inputs into an “input generator.” the generator is subsequently used to efficiently generate worst-case inputs for larger input sizes. we have performed experiments to demonstrate the utility of our approach on a set of standard data structures and algorithms. our results show that wise can effectively generate worstcase inputs for several of these benchmarks.
does distributed development affect software quality? an empirical case study of windows vista. it is widely believed that distributed software development is riskier and more challenging than collocated development. prior literature on distributed development in software engineering and other fields discuss various challenges, including cultural barriers, expertise transfer difficulties, and communication and coordination overhead. we evaluate this conventional belief by examining the overall development of windows vista and comparing the post-release failures of components that were developed in a distributed fashion with those that were developed by collocated teams. we found a negligible difference in failures. this difference becomes even less significant when controlling for the number of developers working on a binary. we also examine component characteristics such as code churn, complexity, dependency information, and test code coverage and find very little difference between distributed and collocated components to investigate if less complex components are more distributed. further, we examine the software process and phenomena that occurred during the vista development cycle and present ways in which the development process utilized may be insensitive to geography by mitigating the difficulties introduced in prior work in this area.
automatic creation of sql injection and cross-site scripting attacks. we present a technique for finding security vulnerabilities in web applications. sql injection (sqli) and cross-site scripting (xss) attacks are widespread forms of attack in which the attacker crafts the input to the application to access or modify user data and execute malicious code. in the most serious attacks (called second-order, or persistent, xss), an attacker can corrupt a database so as to cause subsequent users to execute malicious code.
discovering and representing systematic code changes. software engineers often inspect program differences when reviewing others' code changes, when writing check-in comments, or when determining why a program behaves differently from expected behavior after modification. program differencing tools that support these tasks are limited in their ability to group related code changes or to detect potential inconsistencies in those changes. to overcome these limitations and to complement existing approaches, we built logical structural diff (lsdiff), a tool that infers systematic structural differences as logic rules. lsdiff notes anomalies from systematic changes as exceptions to the logic rules. we conducted a focus group study with professional software engineers in a large e-commerce company; we also compared lsdiff's results with textual differences and with structural differences without rules. our evaluation suggests that lsdiff complements existing differencing tools by grouping code changes that form systematic change patterns regardless of their distribution throughout the code, and its ability to discover anomalies shows promise in detecting inconsistent changes.
cocoviz with ambient audio software exploration. for ages we used our ears side by side with our ophthalmic stimuli to gather additional information, leading and supporting us in our visualization. nowadays numerous software visualization techniques exist that aim to facilitate program comprehension. in this paper we discuss how we can support such software comprehension visualization with environmental audio and lead users to identify relevant aspects. we use cognitive visualization techniques and audio concepts described in our previous work to create an ambient audio software exploration (aase) out of program entities (packages, classes …) and their mapped properties. the concepts where implemented in a extended version of our tool called cocoviz. our first results with the prototype shows that with this combination of visual and aural means we can provide additional information to lead users during program comprehension tasks.
automatically capturing source code context of nl-queries for software maintenance and reuse. as software systems continue to grow and evolve, locating code for maintenance and reuse tasks becomes increasingly difficult. existing static code search techniques using natural language queries provide little support to help developers determine whether search results are relevant, and few recommend alternative words to help developers reformulate poor queries. in this paper, we present a novel approach that automatically extracts natural language phrases from source code identifiers and categorizes the phrases and search results in a hierarchy. our contextual search approach allows developers to explore the word usage in a piece of software, helping them to quickly identify relevant program elements for investigation or to quickly recognize alternative words for query reformulation. an empirical evaluation of 22 developers reveals that our contextual search approach significantly outperforms the most closely related technique in terms of effort and effectiveness.
do code clones matter? code cloning is not only assumed to inflate maintenance costs but also considered defect-prone as inconsistent changes to code duplicates can lead to unexpected behavior. consequently, the identification of duplicated code, clone detection, has been a very active area of research in recent years. up to now, however, no substantial investigation of the consequences of code cloning on program correctness has been carried out. to remedy this shortcoming, this paper presents the results of a large-scale case study that was undertaken to find out if inconsistent changes to cloned code can indicate faults. for the analyzed commercial and open source systems we not only found that inconsistent changes to clones are very frequent but also identified a significant number of faults induced by such changes. the clone detection tool used in the case study implements a novel algorithm for the detection of inconsistent clones. it is available as open source to enable other researchers to use it as basis for further investigations.
effective static deadlock detection. we present an effective static deadlock detection algorithm for java. our algorithm uses a novel combination of static analyses each of which approximates a different necessary condition for a deadlock. we have implemented the algorithm and report upon our experience applying it to a suite of multi-threaded java programs. while neither sound nor complete, our approach is effective in practice, finding all known deadlocks as well as discovering previously unknown ones in our benchmarks with few false alarms.
in-field healing of integration problems with cots components. developers frequently integrate complex cots frameworks and components in software applications. cots products are often only partially documented, and developers may misuse technologies and introduce integration faults, as witnessed by the many entries in fault repositories. once identified, common integration problems and their fixes are usually documented in forums and fault repositories on the web, but this does not prevent them to occur in the field when cots products are reused.
listening to programmers - taxonomies and characteristics of comments in operating system code. innovations from multiple directions have been proposed to improve software reliability. unfortunately, many of the innovations are not fully exploited by programmers. to bridge the gap, this paper proposes a new approach to “listen” to thousands of programmers: studying their programming comments. since comments express programmers' assumptions and intentions, comments can reveal programmers' needs, which can provide guidance (1) for language/-tool designers on where they should develop new techniques or enhance the usability of existing ones, and (2) for programmers on what problems are most pervasive and important so that they should take initiatives to adopt some existing tools or language extensions. we studied 1050 comments randomly sampled from the latest versions of linux, freebsd, and opensolaris. we found that 52.6% of these comments could be leveraged by existing or to-be-proposed tools for improving reliability. our findings include: (1) many comments describe code relationships, code evolutions, or the usage and meaning of integers and integer macros, (2) a significant amount of comments could be expressed by existing annotation languages, and (3) many comments express synchronization related concerns but are not well supported by annotation languages.
save-ide - a tool for design, analysis and implementation of component-based embedded systems. the paper presents save-ide, an integrated development environment for the development of component-based embedded systems. save-ide supports efficient development of dependable embedded systems by providing tools for design of embedded software systems using a dedicated component model, formal specification and analysis of component and system behaviors already in early development phases, and a fully automated transformation of the system of components into an executable image.
locating need-to-translate constant strings for software internationalization. modern software applications require internationalization to be distributed to different regions of the world. in various situations, many software applications are not internationalized at early stages of development. to internationalize such an existing application, developers need to externalize some hard-coded constant strings to resource files, so that translators can easily translate the application into a local language without modifying its source code. since not all the constant strings require externalization, locating those need-to-translate constant strings is a necessary task that developers must complete for internationalization. in this paper, we present an approach to automatically locating need-to-translate constant strings. our approach first collects a list of api methods related to the graphical user interface (gui), and then searches for need-to-translate strings from the invocations of these api methods based on string-taint analysis. we evaluated our approach on four real-world open source applications: rtext, risk, artofillusion, and megamek. the results show that our approach effectively locates most of the need-to-translate constant strings in all the four applications.
synthesizing intensional behavior models by graph transformation. this paper describes an approach (spy) to recovering the specification of a software component from the observation of its run-time behavior. it focuses on components that behave as data abstractions. components are assumed to be black boxes that do not allow any implementation inspection. the inferred description may help understand what the component does when no formal specification is available. spy works in two main stages. first, it builds a deterministic finite-state machine that models the partial behavior of instances of the data abstraction. this is then generalized via graph transformation rules. the rules can generate a possibly infinite number of behavior models, which generalize the description of the data abstraction under an assumption of “regularity” with respect to the observed behavior. the rules can be viewed as a likely specification of the data abstraction. we illustrate how spy works on relevant examples and we compare it with competing methods.
ueman: a tool to manage user evaluation in development environments. one of the challenges in software development is to collect and analyze the end users' feedback in an effective and efficient manner. in this paper we present a tool to manage user evaluation alongside the process of software development. the tool is based on the idea that user evaluation should be managed iteratively from within the integrated development environment (ide) in order to provide high quality user interface. the main capabilities include creating the experiment object as part of the software project; deriving development tasks from the analysis of evaluation data; and tracing these tasks to and from the code. further, we provide a library to enable development of java aspects for creation of automatic measures to increase the body of the evaluation data. using this tool, development teams can manage user-centered design (ucd) activities at the ide level, hence developing software products with an adequate level of usability.
accurate interprocedural null-dereference analysis for java. null dereference is a commonly occurring defect in java programs, and many static-analysis tools identify such defects. however, most of the existing tools perform a limited interprocedural analysis. in this paper, we present an interprocedural path-sensitive and context-sensitive analysis for identifying null dereferences. starting at a dereference statement, our approach performs a backward demand-driven analysis to identify precisely paths along which null values may flow to the dereference. the demand-driven analysis avoids an exhaustive program exploration, which lets it scale to large programs. we present the results of empirical studies conducted using large open-source and commercial products. our results show that: (1) our approach detects fewer false positives, and significantly more interprocedural true positives, than other commonly used tools; (2) the analysis scales to large subjects; and (3) the identified defects are often deleted in subsequent releases, which indicates that the reported defects are important.
semantics-based code search. our goal is to use the vast repositories of available open source code to generate specific functions or classes that meet a user's specifications. the key words here are specifications and generate. we let users specify what they are looking for as precisely as possible using keywords, class or method signatures, test cases, contracts, and security constraints. our system then uses an open set of program transformations to map retrieved code into what the user asked for. this approach is implemented in a prototype system for java with a web interface.
complete and accurate clone detection in graph-based models. model-driven engineering (mde) has become an important development framework for many large-scale software. previous research has reported that as in traditional code-based development, cloning also occurs in mde. however, there has been little work on clone detection in models with the limitations on detection precision and completeness. this paper presents modelcd, a novel clone detection tool for matlab/simulink models, that is able to efficiently and accurately detect both exactly matched and approximate model clones. the core of modelcd is two novel graph-based clone detection algorithms that are able to systematically and incrementally discover clones with a high degree of completeness, accuracy, and scalability. we have conducted an empirical evaluation with various experimental studies on many real-world systems to demonstrate the usefulness of our approach and to compare the performance of modelcd with existing tools.
invariant-based automatic testing of ajax user interfaces. ajax-based web 2.0 applications rely on stateful asynchronous client/server communication, and client-side runtime manipulation of the dom tree. this not only makes them fundamentally different from traditional web applications, but also more error-prone and harder to test. we propose a method for testing ajax applications automatically, based on a crawler to infer a flow graph for all (client-side) user interface states. we identify ajax-specific faults that can occur in such states (related to dom validity, error messages, discoverability, back-button compatibility, etc.) as well as dom-tree invariants that can serve as oracle to detect such faults. we implemented our approach in atusa, a tool offering generic invariant checking components, a plugin-mechanism to add application-specific state validators, and generation of a test suite covering the paths obtained during crawling. we describe two case studies evaluating the fault revealing capabilities, scalability, required manual effort and level of automation of our approach.
license integration patterns: addressing license mismatches in component-based development. in this paper we address the problem of combining software components with different and possibly incompatible legal licenses to create a software application that does not violate any of these licenses while potentially having its own. we call this problem the license mismatch problem. the rapid growth and availability of open source software (oss) components with varying licenses, and the existence of more than 70 oss licenses increases the complexity of this problem. based on a study of 124 oss software packages, we developed a model which describes the interconnection of components in these packages from a legal point of view. we used our model to document integration patterns that are commonly used to solve the license mismatch problem in practice when creating both proprietary and oss applications. software engineers with little legal expertise could use these documented patterns to understand and address the legal issues involved in reusing components with different and possibly conflicting licenses.
the road not taken: estimating path execution frequency statically. a variety of compilers, static analyses, and testing frameworks rely heavily on path frequency information. uses for such information range from optimizing transformations to bug finding. path frequencies are typically obtained through profiling, but that approach is severely restricted: it requires running programs in an indicative environment, and on indicative test inputs. we present a descriptive statistical model of path frequency based on features that can be readily obtained from a program's source code. our model is over 90% accurate with respect to several benchmarks, and is sufficient for selecting the 5% of paths that account for over half of a program's total runtime. we demonstrate our technique's robustness by measuring its performance as a static branch predictor, finding it to be more accurate than previous approaches on average. finally, our qualitative analysis of the model provides insight into which source-level features indicate “hot paths.”
predicting build failures using social network analysis on developer communication. a critical factor in work group coordination, communication has been studied extensively. yet, we are missing objective evidence of the relationship between successful coordination outcome and communication structures. using data from ibm's jazz™ project, we study communication structures of development teams with high coordination needs. we conceptualize coordination outcome by the result of their code integration build processes (successful or failed) and study team communication structures with social network measures. our results indicate that developer communication plays an important role in the quality of software integrations. although we found that no individual measure could indicate whether a build will fail or succeed, we leveraged the combination of communication structure measures into a predictive model that indicates whether an integration will fail. when used for five project teams, our predictive model yielded recall values between 55% and 75%, and precision values between 50% to 76%.
safe-commit analysis to facilitate team software development. software development teams exchange source code in shared repositories. these repositories are kept consistent by having developers follow a commit policy, such as “program edits can be committed only if all available tests succeed.” such policies may result in long intervals between commits, increasing the likelihood of duplicative development and merge conflicts. furthermore, commit policies are generally not automatically enforceable. we present a program analysis to identify committable changes that can be released early, without causing failures of existing tests, even in the presence of failing tests in a developer's local workspace. the algorithm can support relaxed commit policies that allow early release of changes, reducing the potential for merge conflicts. in experiments using several versions of a non-trivial software system with failing tests, 3 newly enabled commit policies were shown to allow a significant percentage of changes to be committed.
maintaining and evolving gui-directed test scripts. since manual black-box testing of gui-based applications (gaps) is tedious and laborious, test engineers create test scripts to automate the testing process. these test scripts interact with gaps by performing actions on their gui objects. an extra effort that test engineers put in writing test scripts is paid off when these scripts are run repeatedly. unfortunately, releasing new versions of gaps with modified guis breaks their corresponding test scripts thereby obliterating benefits of test automation. we offer a novel approach for maintaining and evolving test scripts so that they can test new versions of their respective gaps. we built a tool to implement our approach, and we conducted a case study with forty five professional programmers and test engineers to evaluate this tool. the results show with strong statistical significance that users find more failures and report fewer false positives (p ≪ 0.02) in test scripts with our tool than with a flagship industry product and a baseline manual approach. our tool is lightweight and it takes less than eight seconds to analyze approximately 1kloc of test scripts.
leadership and management in software architecture. the workshop will be conducted primarily through discussion by the participants. the papers have opened up a wide number of issues that have no easy solution and where, most likely, the solutions will vary from case to case. the discussion portion of the workshop will be broad ranging over the topics we have introduced here.
2 international workshop on socio-technical congruence (stc 2009). socio-technical represents a new area of research that focuses on the alignment between the coordination requirements established by the dependencies among tasks and the actual coordination activities carried out by the developers and other stakeholders in software development projects. although the concept of congruence has been central in the system and organizational design literature [2,5], socio-technical congruence highlights the importance of identifying and tracking the dynamic relationship between social and technical dependencies. this change in focus allows us to make important progress in understanding and improving software development organizations, particularly those that are geographically distributed.
cooperative and human aspects of software engineering (chase 2009). the chase 2009 workshop is concerned with exploring the cooperative and human aspects of software engineering, and providing a forum for discussing high-quality research. accepted papers reflect the diversity of the field of software engineering - ranging from requirements to testing, and from ethnographic research to experiments. moreover, the background of attendees reflects the diversity of researchers in this domain, ranging from sociology to psychology, from informatics to software engineering. chase 2009 met its goals in presenting high-quality research and building community through a mixture of presentations, discussions, posters, and social activities.
workshop on software engineering in health care (sehc). the software engineering in health care workshop aims to explore the relevance and applicability of the techniques, approaches, and technologies of software engineering to problems in the domain of health care. health care is emerging as one of the largest industries in the global economy of the 21st century, and thus accounts for an enormous amount of capital expenditure, while also being responsible for assuring the health and comfort for all members of society. these twin drivers of cost and criticality have given rise to a great deal of interest in creating devices that provide support for the superior performance of key health care processes. these devices are now incorporating increasing amounts of software in order to help them provide increasingly better service. in addition there is also growing interest in support systems, such as electronic health records (ehrs) that are entirely software.
5 international workshop on traceability in emerging forms of software engineering (tefse 2009). traceability of emerging forms of software engineering (tefse) 2009 will bring together researchers and practitioners to examine the challenges of recovering and maintaining traceability for the myriad forms of software engineering, from user needs to models to source code. in the 2007 instalment, tefse focused on the grand challenges of traceability. the 2009 instalment will focus on these and other emerging challenges in traceability.
2 workshop on software development governance (sdg). the main role of software development governance is to achieve a strategic alignment with the business. exploring governance in software development environments is an important evolutionary step for software engineering. the implementation of governance through tools and techniques provides teams and organizations with the ability to effectively steer the business of software development.
seeup 2009: workshop on software engineering foundations for end-user programming. the goal of the seeup 2009 workshop is to discuss end-user programming with a specific focus on the software engineering that is required to make it a more disciplined process, while still hiding the complexities of greater discipline from the end user. the main topic is the understanding of the problems and needs of the real end users of end-user programming and a discussion of the software engineering and supporting technology that would have to be in place to address these problems and needs.
se-cse 2009: the second international workshop on software engineering for computational science and engineering. this workshop is concerned with the development of computational science & engineering (cs&e) software. this software includes: 1) scientific software applications, where the focus is on directly solving scientific problems, including, but not limited to, large parallel models/simulations of the physical world (high performance computing systems); and 2) applications that support scientific endeavors, including, but not limited to, systems for managing and/or manipulating large amounts of data. despite its importance in our everyday lives, the development of cs&e software has historically attracted little attention from the software engineering community. due to significant differences in the development context, cs&e software development needs to be studied in its own right. this workshop will devote approximately equal time to presentation of position papers and to discussing topics that arise out of those presentations.
seventh workshop on software quality. software quality has been a major challenge throughout information technology projects. whether it is in software development, in software integration or whether it is in the implementation or customization of shrink-wrapped software, quality is regarded as a major issue. in the last couple of decades, much software engineering research has focused on standards, methodologies and techniques for improving software quality, measuring software quality and software quality assurance. most of this research is focused on the internal/development view of quality. more recent studies have made attempts to understand the stakeholder view of quality. with globalization, many new challenges affect software quality. not only do we need to understand the many stakeholder views of quality, we now need to consider the cultural issues, and the outsourcing issues. the seventh workshop on software quality aims to bring together academic, industrial and commercial communities interested in software quality topics to discuss the different technologies being defined and used in the software quality area.
fourth international workshop on sharing and reusing architectural knowledge (shark 2009). architectural knowledge (ak) is defined as the integrated representation of the software architecture of a software-intensive system or family of systems along with architectural decisions and their rationale, external influence and the development environment. the shark workshop series focuses on current methods, languages, and tools that can be used to extract, represent, share, apply, and reuse ak, and the experimentation and/or exploitation thereof. this fifth edition of shark will discuss, among other topics, the contributions of this community to a body of knowledge on software architecture.
seams 2009: software engineering for adaptive and self-managing systems. with the rapid growth of web services and the continuous evolution from software-intensive systems to socio-technical ecosystems, the management of modern computing systems with many uncertainties in their environments presents significant challenges and risks for businesses. end-users increasingly demand software systems that are resilient, dependable, fault-tolerant, energy-efficient, or self-healing. one of the most promising approaches to engineering these properties is to equip software systems with feedback control to address the management of inherent system dynamics. the resulting self-adapting and self-managing computing systems are better able to cope with and even accommodate changing contexts and environments, shifting requirements, and computing-on-demand needs. the seams workshop series consolidates the interests in the software engineering community on self-adaptive and self-managing systems. seams provides a forum for researchers to share new results, raise awareness, and promote collaboration. seams 2009 builds on the success of the seams icse workshops of 2008 in leipzig, germany, 2007 in minneapolis, usa, and 2006 in shanghai, china.
icse cloud 09: first international workshop on software engineering challenges for cloud computing. cloud computing has emerged as a new paradigm for deploying, managing and offering services through a shared infrastructure. the projected benefits of cloud computing are very compelling both from a cloud consumer as well as a cloud services provider perspective: ease of deployment of services; low capital expenses and constant operational expenses leading to variable pricing schemes and reduced opportunity costs; leveraging the economies of scale for both services providers and users of the cloud. however, the actual realization of these perceived benefits are far from being well-achieved and pose a broad range of interesting questions.
modeling in software engineering (mise 09). the modeling in software engineering (mise) workshop series provides a forum for discussing the challenges associated with modeling software and with incorporating modeling practices into the software development process. the main goal is to further promote cross-fertilization between the modeling communities (e.g., models) and software-engineering communities.
international workshop on multicore software engineering (iwmse 2009). microprocessor performance can no longer be greatly improved by simply increasing clock frequencies; instead, higher performance will have to come from parallelism. as multi/manycore processors with multiple cpus on a chip become standard and affordable for everyone, software engineers face the challenge of parallelizing applications of all sorts. however, compared to sequential applications, our repertoire of tools and methods for cost-effectively developing reliable, parallel applications is spotty. the mission of this workshop is to bring together researchers and practitioners with diverse backgrounds in order to advance the state of the art in software engineering for multi/-manycore parallel applications. this is the second in a series of workshops specifically focusing on software engineering challenges of multi/manycore.
workshop on comparison and versioning of software models (cvsm 2009). comparison and versioning of software models is an important theoretical and practical problem area in the context of model-driven software development. a range of detailed issues of this domain are addressed by the contributions of cvsm 2009. this workshop summary introduces some important research areas and categorizes the contributions of the workshop.
expanding, theory, and practice: report on the 4 international workshop on the automation of software test. the fourth international workshop on automation of software test (ast 2009) at the 31st international conference on software engineering (icse 2009) expands to two days, supports a special theme of testing web services, adds a case studies from business and industry session, and includes a charette-style work session. 14 regular papers and 7 short case-study papers will be presented. this report summarizes the organization of the workshop as well as the sessions and papers to be presented.
principles of engineering service oriented systems. the objective of this workshop is to discuss about the importance of software engineering methods and techniques for service-oriented systems and, vice versa, about the impact that such kinds of open and natually adaptable systems can have on traditional software engineering. we think that discussing about these aspects within the icse community could be very beneficial for the progress of the field.
the 5 international workshop on software engineering for secure systems (sess'09). software is at core of most of the business transactions and its smart integration in an industrial setting may be the competitive advantage even when the core competence is outside the ict field. as a result, the revenues of a firm depend directly on several complex software-based systems. thus, stakeholders and users should be able to trust these systems to provide data and elaborations with a degree of confidentiality, integrity, and availability compatible with their needs. moreover, the pervasiveness of software products in the creation of critical infrastructures has raised the value of trustworthiness and new efforts should be dedicated to achieve it. however, nowadays almost every application has some kind of security requirement even if its use is not to be considered critical.
wikis4se'2009: wikis for software engineering. in recent years, wikis have gained a prominent position among web-based collaboration platforms. however, special practices and adaptations are necessary when applying wikis to software documentation and other development activities. the wikis for software engineering (wikis4se) workshop aims to bring together researchers and practitioners interested in the use of wiki technology in this domain. it serves as a forum for presenting new ideas and tools, and reporting on experiences, best practices, and newly discovered problems. the wikis4se'2009 workshop builds on the success of prior events at wikisym'2008 and wikisym'2007.
second international workshop on emerging trends in free/libre/open source software research and development - floss09. the workshop on “emerging trends in floss research and development” is based on the ever growing interest of researchers and practitioners on free/libre/open source software (floss), and will be specifically based on discussing the phenomenon of global floss development and how to identify and define, if any, how floss communities could benefit from traditional software engineering practices, and viceversa. for this purpose, the overarching theme of this workshop is “closing the gap between software engineering and floss development”. its main goal will be to bring together academic researchers, industry members and floss developers and to discuss what aspects and practices are common in both the software engineering and the floss development modes, and where and how these practices differ substantially.
suite 2009: first international workshop on search-driven development - users, infrastructure, tools and evaluation. suite is a new workshop series that specifically focuses on exploring the notion of search as a fundamental activity during software development. the goal of the workshop is to bring researchers and practitioners with special interest on search technology for software developers together. participants will have broad range of expertise in topics ranging from building software tools and infrastructure, information retrieval, user studies and human-computer interaction, benchmarking and evaluation. the first edition of suite is held in conjunction with the 31st international conference in software engineering (may 16–24, 2009. vancouver, canada).
score: the first student contest in software engineering. icse 2009 in vancouver has seen the first finals of the score software engineering contest. teams from all over the world have taken part in a competition open to students from undergraduate to master's level. each team has developed a system chosen from a list of projects and monitored by a committee member. the final outcome of their work has been a report and accompanying system. evaluation has been based on the quality of all aspects of the software engineering process followed, as well as the outcome.
model-based methodologies for pervasive and embedded software. model-based methodologies for pervasive and embedded software (mompes 2009) is the 6th edition of a workshop series. the workshops focus on the theoretical and practical aspects related to the adoption of model-based development methodologies for supporting the construction of software for pervasive and embedded systems. the workshops usually gather researchers from both industry and academia.
study of principal components on classification of problematic wine fermentations. data mining techniques have already shown useful to classify wine fermentations as problematic. then, these techniques are a good option for winemakers who currently lack the tools to identify early signs of undesirable fermentation behavior and, therefore, are unable to take possible mitigating actions. in this study we assessed how much the performance of a clustering k-means fermentation classification procedure is affected by the number of principal components (pcs), when principal component analysis (pca) is previously applied to reduce the dimensionality of the available data. it was observed that three pcs were enough to preserve the overall information of a dataset containing reliable measurements only. in this case, a 40% detection ability of problematic fermentations was achieved. in turn, using a more complete dataset, but containing unreliable measurements, the number of pcs yielded different classifications. here, 33%f the problematic fermentations were detected.
on cellular network channels data mining and decision making through ant colony optimization and multi agent systems strategies. finding suitable channels to allocate in order to serve increasing user demands in a cellular network, which is a dynamical system, constitute the most important issue in terms of network performance since they define the bandwidth management methodology. in modern cellular networks these strategies become challenging issues especially when advanced services are applied. the effectiveness of decision making for channel allocation in a cellular network is strongly connected to current traffic and wireless environment conditions. moreover, in large scale environments, network states change dynamically and the network performance prediction is a hard task. in the recent literature, the network adaptation to current real user needs seems it could be achieved through computational intelligence based channel allocation schemes mainly involving genetic algorithms. in this paper, a quite new approach for communication channels decision making, based on ant colony optimization, which is a special form of swarm intelligence, modelled through multi agent methodology is presented. the main novelty of this research lies on modelling this optimization scheme through multi agent systems. the simulation model architecture which includes network and ant agents are also presented as well as the performance results based on the above techniques. finally, the current study, also, shows that there is a great field of research concerning intelligent techniques modelled through multi-agent methodologies focused on channels decision making and bandwidth management in wireless communication systems.
responsible data releases. data releases to the public should ensure the privacy of individuals involved in the data. several privacy mechanisms have been proposed in the literature. one such technique is that of data anonymization. for example, synthetic data sets are generated and released. in this paper we analyze the privacy aspects of synthetic data sets. in particular, we introduce a natural notion of privacy and employ it for synthetic data sets.
online mass flow prediction in cfb boilers. fuel feeding and inhomogeneity of fuel typically cause process fluctuations in the circulating fluidized bed (cfb) process. if control systems fail to compensate for the fluctuations, the whole plant will suffer from fluctuations that are reinforced by the closed-loop controls. this phenomenon causes a reduction of efficiency and lifetime of process components. therefore, domain experts are interested in developing tools and techniques for getting better understanding of underlying processes and their mutual dependencies in cfb boilers. in this paper we consider an application of data mining technology to the analysis of time series data from a pilot cfb reactor. namely, we present a rather simple and intuitive approach for online mass flow prediction in cfb boilers. this approach is based on learning and switching regression models. additionally, noise canceling, and windowing mechanisms are used for improving the robustness of online prediction. we validate our approach with a set of simulation experiments with real data collected from the pilot cfb boiler.
evaluation of distraction in a driver-vehicle-environment framework: an application of different data-mining techniques. distraction during driving task is one of the most serious problems affecting traffic safety, being one of the main causes of accidents. therefore, a method to diagnose and evaluate distraction appears to be of paramount importance to study and implement efficient counter-measures. this research aims at illustrating our approach in diagnosis of distraction status, comparing some of the widely used data-mining techniques; in particular, fuzzy logic (with adaptive-network-based fuzzy inference system) and artificial neural networks. the results are compared to select which method gives the best performances.
the normalized compression distance as a distance measure in entity identification. the identification of identical entities accross heterogeneous data sources still involves a large amount of manual processing. this is mainly due to the fact that different sources use different data representations in varying semantic contexts. up to now entity identification requires either the --- often manual --- unification of different representations, or alternatively the effort of programming tools with specialized interfaces for each representation type. however, for large and sparse databases, which are common e.g. for medical data, the manual approach becomes infeasible.we have developed a widely applicable compression based approach that does not rely on structural or semantical unity. the results we have obtained are promising both in recognition precision and performance.
distances in classification. the notion of distance is the most important basis for classification. this is especially true for unsupervised learning, i.e. clustering, since there is no validation mechanism by means of objects of known groups. but also for supervised learning standard distances often do not lead to appropriate results. for every individual problem the adequate distance is to be decided upon. this is demonstrated by means of three practical examples from very different application areas, namely social science, music science, and production economics. in social science, clustering is applied to spatial regions with very irregular borders. then adequate spatial distances may have to be taken into account for clustering. in statistical musicology the main problem is often to find an adequate transformation of the input time series as an adequate basis for distance definition. also, local modelling is proposed in order to account for different subpopulations, e.g. instruments. in production economics often many quality criteria have to be taken into account with very different scaling. in order to find a compromise optimum classification, this leads to a pre-transformation onto the same scale, called desirability.
computer-aided diagnosis in brain computed tomography screening. currently, interpretation of medical images is almost exclusively made by specialized physicians. although, the next decades will most certainly be of change and computer-aided diagnosis systems will play an important role in the reading process. assisted interpretation of medical images has become one of the major research subjects in medical imaging and diagnostic radiology. from a methodological point of view, the main attraction for the resolution of this kind of problem arises from the combination of the image reading made by the radiologists, with the results obtained from using artificial intelligence based applications that will contribute to the reduction and eventually the elimination of perception errors. this article describes how machine learning algorithms can help distinguish normal readings in brain computed tomography from all its variations. the goal is to have a system that is able to detect normal appearing structures, thus identifying normal studies, making the reading by the radiologist unnecessary for a large proportion of the brain computed tomography scans.
data mining of agricultural yield data: a comparison of regression models. nowadays, precision agriculture refers to the application of state-of-the-art gps technology in connection with small-scale, sensor-based treatment of the crop. this introduces large amounts of data which are collected and stored for later usage. making appropriate use of these data often leads to considerable gains in efficiency and therefore economic advantages. however, the amount of data poses a data mining problem --- which should be solved using data mining techniques. one of the tasks that remains to be solved is yield prediction based on available data. from a data mining perspective, this can be formulated and treated as a multi-dimensional regression task. this paper deals with appropriate regression techniques and evaluates four different techniques on selected agriculture data. a recommendation for a certain technique is provided.
evaluation of fusion for similarity searching in online handwritten documents. with the spread of tabletpcs handwriting raises in its significance and importance in the digital domain. also there exist other devices with pen-based inputs like pdas, digitizer tablets and pads specially prepared with sensors. the advantage of handwritten input methods is their possibility of an ad hoc creation of technical sketches and drawings alongside with text and that keyboards may be in some cases and environments bothersome. therefore the amount of handwritten documents is likely to increase. but a great problem is a proper full text search on such documents. this paper discusses the effects of multi-sample and multi-algorithm fusion approaches, known from biometrics to increase the performance. the tests are done by using three different devices (logitech iopen, pegasus pc notesmaker, ace cad digimemo digital) and five different feature extraction methods (square grid, triangular grid, slope, curvature and slant of writing) and show that fusion can improve the retrieval performance in terms of precision and recall from 0.903 and 0.935 without fusion to 0.958 and 0.943 with fusion, respectively.
a sales forecast model for the german automobile market based on time series analysis and data mining methods. in this contribution, various sales forecast models for the german automobile market are developed and tested. our most important criteria for the assessment of these models are the quality of the prediction as well as an easy explicability. yearly, quarterly and monthly data for newly registered automobiles from 1992 to 2007 serve as the basis for the tests of these models. the time series model used consists of additive components: trend, seasonal, calendar and error component. the three latter components are estimated univariately while the trend component is estimated multivariately by multiple linear regression as well as by a support vector machine. possible influences which are considered include macro-economic and market-specific factors. these influences are analysed by a feature selection. we found the non-linear model to be superior. furthermore, the quarterly data provided the most accurate results.
knowledge representation in difficult medical diagnosis. this article is based on medical knowledge produced thought collaborative problem solving by a group of experts, in the field of medical diagnosis. in this work, we propose a representation format for a medical case base into a traditional rdbms representation, which is queryable using standard sql. we are concerned in difficult medical cases which imply a solution in several steps with several expert solvers (medical specialists). some queries on this case base are proposed. a case base was implemented and validated in real time with experts on the real scenarios.
forecasting product life cycle phase transition points with modular neural networks based system. management of the product life cycle and of the corresponding supply network largely depends on information in which specific phase of the life cycle one or another product currently is and when the phase will be changed. finding a phase of the product life cycle can be interpreted as forecasting transition points between phases of life cycle of these products. this paper provides a formulation of the above mentioned task of forecasting the transition points and presents the structured data mining system for solving that task. the developed system is based on the analysis of historical demand for products and on information about transitions between phases in life cycles of those products.the experimental results with real data display information about the potential of the created system.
clustering with domain value dissimilarity for categorical data. clustering is a representative grouping process to find out hidden information and understand the characteristics of dataset to get a view of the further analysis. the concept of similarity and dissimilarity of objects is a fundamental decisive factor for clustering and the measure of them dominates the quality of results. when attributes of data are categorical, it is not simple to quantify the dissimilarity of data objects that have unimportant attributes or synonymous values. we suggest a new idea to quantify dissimilarity of objects by using distribution information of data correlated to each categorical value. our method discovers intrinsic relationship of values and measures dissimilarity of objects effectively. our approach does not couple with a clustering algorithm tightly and so can be applied various algorithms flexibly. experiments on both synthetic and real datasets show propriety and effectiveness of this method. when our method is applied only to traditional clustering algorithms, the results are considerably improved than those of previous methods.
credit risk handling in telecommunication sector. this article presents an application of data mining methods in telecommunication sector. this sector becomes a new area of research for particular problem solving e.g. churn prediction, cross-up selling marketing campaigns, fraud detection, customer segmentation and profiling, data classification, association rules discovery, data clustering, parameter importance analysis etc. credit risk prediction became a new research domain in pattern recognition area aimed to find the most risky customers. this article is devoted to assessing credit risk from the moment of opening a customer account to the moment of closing an account due to non-payment. algorithms are used to identify and insolvency of a debtor. credit scoring is presented in a form of activation models, which are used to predict customers' debt as well as indicate clients with the highest, medium and smallest credit risk. practical part of the article is based on the real customer database in a telecommunication company.
combining multidimensional scaling and computational intelligence for industrial monitoring. large industrial complexes with hundreds of variables must be tightly monitored for safety, quality and resources optimization. multidimensional scaling and computational intelligence are proposed in this work as effective tools for building classifiers of the operating state of the industrial process into normal / abnormal working regions. the visred, visualization by data reduction computational framework, is extended with techniques from computational intelligence, such as neural networks (several architectures), support vector machines and neuro-fuzzy systems (in an evolving adaptive implementation) to build such classifiers. the visbreaker plant of an oil refinery is taken as case study and some scenarios show the potentiality of the combined approach.
integrating data mining and agent based modeling and simulation. in this paper, we introduce an integration study which combines data mining (dm) and agent based modeling and simulation (abms). this study, as a new paradigm for dm/abms, is concerned with two approaches: (i) applying dm techniques in abms investigation, and inversely (ii) utilizing abms results in dm research. detailed description of each approach is presented in this paper. a conclusion and the future work of this (integration) study are given at the end.
a data mining method for finding hidden relationship in blood and urine examination items for health check. our periodic health examination often describes whether each examination item in blood and urine takes in the reference range of each examination item and a simple summary report on checks in everyday life and the possibility of suspicious diseases. however, it uses n variable items such as ast(got), alt(gpt) which are less correlated, and often includes expensive tumor markers. therefore, this paper proposes a data mining method for finding hidden relationships between these items in order to reduce the examination fee and giving a report depending on individuals. since low correlation coefficients are shown in most pairs of items over all clients, a set of item's values in consecutive health examinations of each client is investigated for data mining. four groups are formed according to the frequency taking outside the reference range in an item for three consecutive examinations, and average values of the other items included in each group are calculated in all pairs of items. the experiment results for three consecutive health examinations show that a lot of item pairs have positive or negative correlations between different frequencies with an item and the averages with the other item despite the fact that their correlation coefficients are small. the result shows both possible reducting of reducing the examination fee as inexpensive as possible and the possibility of a health-care report reflecting individuals.
visualizing the competitive structure of online auctions. visualizations of product competition are common in marketing research. competitive product relationships can be modeled using data from a variety of sources, including questionnaires, surveys and brand switching data. product competition applications based on brand switching data are usually restricted to high volume, frequent purchase products such as coffee and frozen foods. analysis of competitive product structure requires data for multiple purchases from a single consumer, data that are not usually available for large value, rare purchase items such as cars and computers. we use bid information from online auctions as a source of competitive product structure information for these items. we develop a simple algorithm for creating a distance matrix representing market structure between brands and brand features from online auction data. we take data from ebay mobile phone auctions in the usa and based upon the auction data develop visualizations of product competition for brands and brand features.
ordinal evaluation: a new perspective on country images. we present a novel use of ordinal evaluation (ordeval) algorithm as a promising technique to study various marketing phenomena. ordeval algorithm has originated in data mining and is a general tool to analyze data with ordinal attributes, including surveys. its many favorable features, including context sensitivity, ability to exploit meaning of ordered features and ordered response, and robustness to noise and missing values in the data, offer marketing practitioners a perspective, not available with classical analytical toolbox.we present a case study applying ordeval algorithm on country-of-origin (coo) information. we demonstrate some interesting advantages it has to offer and show how to extract and interpret new insights allowing marketing practitioners to further optimize the management of products abroad.data for the empirical study was gathered by means of 1225 questionnaires. results indicate that, contrary to the classical view on coo-effects, the processing of country-related cognitions, affects and conations is a non-linear and asymmetric phenomenon. the practical implications of this finding for marketers are discussed more in detail.
sales intelligence using web mining. this paper presents a knowledge extraction system for providing sales intelligence based on information downloaded from the www. the information is first located and downloaded from relevant companies' websites and then machine learning is used to find these web pages that contain useful information where useful is defined as containing news about orders for specific products. several machine learning algorithms were tested from which k-nearest neighbour, support vector machines, multi-layer perceptron and c4.5 decision tree produced best results in one or both experiments however k-nearest neighbour and support vector machines proved to be most robust which is a highly desired characteristic in the particular application. k-nearest neighbour slightly outperformed the support vector machines in both experiments which contradicts the results reported previously in the literature.
a case of using formal concept analysis in combination with emergent self organizing maps for detecting domestic violence. in this paper, we propose a framework for iterative knowledge discovery from unstructured text using formal concept analysis and emergent self organizing maps. we apply the framework to a real life case study using data from the amsterdam-amstelland police. the case zooms in on the problem of distilling concepts for domestic violence from the unstructured text in police reports. our human-centered framework facilitates the exploration of the data and allows for an efficient incorporation of prior expert knowledge to steer the discovery process. this exploration resulted in the discovery of faulty case labellings, common classification errors made by police officers, confusing situations, missing values in police reports, etc. the framework was also used for iteratively expanding a domain-specific thesaurus. furthermore, we showed how the presented method was used to develop a highly accurate and comprehensible classification model that automatically assigns a domestic or non-domestic violence label to police reports.
on a new similarity analysis in frequency domain for mining faces within a complex background. a novel similarity analysis is presented in this paper for dealing with the problem of mining faces in a complex image background. the proposed approach integrates a robust feature extraction technique based on a specific method of eigenanalysis in the frequency domain of the unique classes identified in the problem at hand, with neural network based classifiers. such an eigenalysis aims at identifying principal characteristics in the frequency domain of the above mentioned uniquely identified classes. each unknown image, in the testing phase, is then, analyzed through a sliding window raster scanning procedure to sliding windows identified, through a first stage neural classifier, as belonging to one of the unique classes previously mentioned. after such a sliding window labeling procedure it is reasonable for a second stage neural classifier to be applied to the testing image viewed as a sequence of such labeled sliding windows for obtaining a final decision about whether a face exists within the given test image or not. although the proposed approach is a hierarchical procedure, its most critical stage is the similarity analysis performed through eigenanalysis in the frequency domain, since, if good identification/ labeling accuracy could be then obtained, it would facilitate final face mining.
on the integration of neural classifiers through similarity analysis of higher order features. a novel methodology is herein outlined for combining the classification decisions of different neural network classifiers. instead of the usual approach for applying voting schemes on the decisions of their output layer neurons, the proposed methodology integrates higher order features extracted by their upper hidden layer units. more specifically, different instances (cases) of each such classifier, derived from the same training process but with different training parameters, are investigated in terms of their higher order features, through similarity analysis, in order to find out repeated and stable higher order features. then, all such higher order features are integrated through a second stage neural network classifier having as inputs suitable similarity features of them. the herein suggested hierarchical neural system for pattern recognition shows improved classification performance in a computer vision task. the validity of this novel combination approach has been investigated when the first stage neural classifiers involved correspond to different feature extraction methodologies (fem) for shape classification. the experimental study illustrates that such an approach, integrating higher order features through similarity analysis of a committee of the same classifier instances (cases) and a second stage neural classifier, outperforms other combination methods, like voting combination schemes as well as single neural network classifiers having as inputs all fems derived features. in addition, it outperforms hierarchical combination methods non performing integration of cases through similarity analysis.
attribute constrained rules for partially labeled sequence completion. sequential pattern and rule mining have been the focus of much research, however predicting missing sets of elements within a sequence remains a challenge. recent work in survey design suggests that if these missing elements can be inferred with a higher degree of certainty, it could greatly reduce the time burden on survey participants. to address this problem and the more general problem of missing sensor data, we introduce a new form of constrained sequential rules that use attribute presence to better capture rule confidence in sequences with missing data than previous constraint based techniques. specifically we examine the problem of given a partially labeled sequence of sets, how well can the missing attributes be inferred. our study shows this technique significantly improves prediction robustness when even large amounts of data are missing compared to traditional techniques.
self-training strategies for handwriting word recognition. handwriting recognition is an emerging subfield of human-computer interaction that has many potential industrial applications, e.g. in postal automation, bank check processing, and automatic form reading. training a recognizer, however, requires a substantial amount of training examples together with their corresponding ground truth, which needs to be created by humans. a promising way to significantly reduce this effort, and hence cut system development costs, is offered by semi-supervised learning, in which both text with and text without transcription is used for training. however, until today there is no straightforward and established way of semi-supervised learning, particularly not for handwriting recognition. in the self-training approach, an initially trained recognition system creates a new training set from unlabeled data. using this set, a new recognizer is created. the creation of the training set is done by selecting elements from the unlabeled set, according to their recognition confidence. the success of self-training depends crucially on the data selected. in this paper, we test and compare different rules used to select new training data for single word recognition with and without additional language information in the form of a dictionary. we demonstrate that it is possible to substantially increase the recognition accuracy for both systems.
electronic nose ovarian carcinoma diagnosis based on machine learning algorithms. ovarian carcinoma is one of the most deadly diseases, especially in the case of late diagnosis. this paper describes the result of a pilot study on an early detection method that could be inexpensive and simple based on data processing and machine learning algorithms in an electronic nose system. experimental analysis using real ovarian carcinoma samples is presented in this study. the electronic nose used in this pilot test is very much the same as a nose used to detect and identify explosives. however, even if the apparatus used is the same, it is shown that the use of proper algorithms for analysis of the multi-sensor data from the electronic nose yielded surprisingly good results with more than 77% classification rate. these results are suggestive for further extensive experiments and development of the hardware as well as the software.
mining determining sets for partially defined functions. this paper describes an algorithm that determines the minimal sets of variables that determine the values of a discrete partial function. the apriori-like algorithm is based on the dual hereditary property of determining sets. experimental results are provided that demonstrate the efficiency of the algorithm for functions with up to 24 variables. the dependency of the number of minimal determining sets on the size of the specification of the partial function is also examined.
screening paper runnability in a web-offset pressroom by data mining. this paper is concerned with data mining techniques for identifying the main parameters of the printing press, the printing process and paper affecting the occurrence of paper web breaks in a pressroom. two approaches are explored. the first one treats the problem as a task of data classification into "break" and "non break" classes. the procedures of classifier design and selection of relevant input variables are integrated into one process based on genetic search. the search process results in a set of input variables providing the lowest average loss incurred in taking decisions. the second approach, also based on genetic search, combines procedures of input variable selection and data mapping into a low dimensional space. the tests have shown that the web tension parameters are amongst the most important ones. it was also found that, provided the basic off-line paper parameters are in an acceptable range, the paper related parameters recorded online contain more information for predicting the occurrence of web breaks than the off-line ones. using the selected set of parameters, on average, 93.7% of the test set data were classified correctly. the average classification accuracy of the break cases was equal to 76.7%.
so_mad: sensor mining for anomaly detection in railway data. today, many industrial companies must face problems raised by maintenance. in particular, the anomaly detection problem is probably one of the most challenging. in this paper we focus on the railway maintenance task and propose to automatically detect anomalies in order to predict in advance potential failures. we first address the problem of characterizing normal behavior. in order to extract interesting patterns, we have developed a method to take into account the contextual criteria associated to railway data (itinerary, weather conditions, etc.). we then measure the compliance of new data, according to extracted knowledge, and provide information about the seriousness and possible causes of a detected anomaly.
application of classification association rule mining for mammalian mesenchymal stem cell differentiation. in this paper, data mining is used to analyze the differentiation of mammalian mesenchymal stem cells (mscs). a database comprising the key parameters which, we believe, influence the destiny of mammalian mscs has been constructed. this paper introduces classification association rule mining (carm) as a data mining technique in the domain of tissue engineering and initiates a new promising research field. the experimental results show that the proposed approach performs well with respect to the accuracy of (classification) prediction. moreover, it was found that some rules mined from the constructed msc database are meaningful and useful.
time series shapelets: a new primitive for data mining. classification of time series has been attracting great interest over the past decade. recent empirical evidence has strongly suggested that the simple nearest neighbor algorithm is very difficult to beat for most time series problems. while this may be considered good news, given the simplicity of implementing the nearest neighbor algorithm, there are some negative consequences of this. first, the nearest neighbor algorithm requires storing and searching the entire dataset, resulting in a time and space complexity that limits its applicability, especially on resource-limited sensors. second, beyond mere classification accuracy, we often wish to gain some insight into the data. in this work we introduce a new time series primitive, time series shapelets, which addresses these limitations. informally, shapelets are time series subsequences which are in some sense maximally representative of a class. as we shall show with extensive empirical evaluations in diverse domains, algorithms based on the time series shapelet primitives can be interpretable, more accurate and significantly faster than state-of-the-art classifiers.
on the tradeoff between privacy and utility in data publishing. in data publishing, anonymization techniques such as generalization and bucketization have been designed to provide privacy protection. in the meanwhile, they reduce the utility of the data. it is important to consider the tradeoff between privacy and utility. in a paper that appeared in kdd 2008, brickell and shmatikov proposed an evaluation methodology by comparing privacy gain with utility gain resulted from anonymizing the data, and concluded that "even modest privacy gains require almost complete destruction of the data-mining utility". this conclusion seems to undermine existing work on data anonymization. in this paper, we analyze the fundamental characteristics of privacy and utility, and show that it is inappropriate to directly compare privacy with utility. we then observe that the privacy-utility tradeoff in data publishing is similar to the risk-return tradeoff in financial investment, and propose an integrated framework for considering privacy-utility tradeoff, borrowing concepts from the modern portfolio theory for financial investment. finally, we evaluate our methodology on the adult dataset from the uci machine learning repository. our results clarify several common misconceptions about data utility and provide data publishers useful guidelines on choosing the right tradeoff between privacy and utility.
co-clustering on manifolds. co-clustering is based on the duality between data points (e.g. documents) and features (e.g. words), i.e. data points can be grouped based on their distribution on features, while features can be grouped based on their distribution on the data points. in the past decade, several co-clustering algorithms have been proposed and shown to be superior to traditional one-side clustering. however, existing co-clustering algorithms fail to consider the geometric structure in the data, which is essential for clustering data on manifold. to address this problem, in this paper, we propose a dual regularized co-clustering (drcc) method based on semi-nonnegative matrix tri-factorization. we deem that not only the data points, but also the features are sampled from some manifolds, namely data manifold and feature manifold respectively. as a result, we construct two graphs, i.e. data graph and feature graph, to explore the geometric structure of data manifold and feature manifold. then our co-clustering method is formulated as semi-nonnegative matrix tri-factorization with two graph regularizers, requiring that the cluster labels of data points are smooth with respect to the data manifold, while the cluster labels of features are smooth with respect to the feature manifold. we will show that drcc can be solved via alternating minimization, and its convergence is theoretically guaranteed. experiments of clustering on many benchmark data sets demonstrate that the proposed method outperforms many state of the art clustering methods.
a principled and flexible framework for finding alternative clusterings. the aim of data mining is to find novel and actionable insights in data. however, most algorithms typically just find a single (possibly non-novel/actionable) interpretation of the data even though alternatives could exist. the problem of finding an alternative to a given original clustering has received little attention in the literature. current techniques (including our previous work) are unfocused/unrefined in that they broadly attempt to find an alternative clustering but do not specify which properties of the original clustering should or should not be retained. in this work, we explore a principled and flexible framework in order to find alternative clusterings of the data. the approach is principled since it poses a constrained optimization problem, so its exact behavior is understood. it is flexible since the user can formally specify positive and negative feedback based on the existing clustering, which ranges from which clusters to keep (or not) to making a trade-off between alternativeness and clustering quality.
learning optimal ranking with tensor factorization for tag recommendation. tag recommendation is the task of predicting a personalized list of tags for a user given an item. this is important for many websites with tagging capabilities like last.fm or delicious. in this paper, we propose a method for tag recommendation based on tensor factorization (tf). in contrast to other tf methods like higher order singular value decomposition (hosvd), our method rtf ('ranking with tensor factorization') directly optimizes the factorization model for the best personalized ranking. rtf handles missing values and learns from pairwise ranking constraints. our optimization criterion for tf is motivated by a detailed analysis of the problem and of interpretation schemes for the observed data in tagging systems. in all, rtf directly optimizes for the actual problem using a correct interpretation of the data. we provide a gradient descent algorithm to solve our optimization problem. we also provide an improved learning and prediction method with runtime complexity analysis for rtf. the prediction runtime of rtf is independent of the number of observations and only depends on the factorization dimensions. besides the theoretical analysis, we empirically show that our method outperforms other state-of-the-art tag recommendation methods like folkrank, pagerank and hosvd both in quality and prediction runtime.
efficiently learning the accuracy of labeling sources for selective sampling. many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. however, what if there are multiple labeling sources ('oracles' or 'experts') with different but unknown reliabilities? with the recent advent of inexpensive and scalable online annotation tools, such as amazon's mechanical turk, the labeling process has become more vulnerable to noise - and without prior knowledge of the accuracy of each individual labeler. this paper addresses exactly such a challenge: how to jointly learn the accuracy of labeling sources and obtain the most informative labels for the active learning task at hand minimizing total labeling effort. more specifically, we present iethresh (interval estimate threshold) as a strategy to intelligently select the expert(s) with the highest estimated labeling accuracy. iethresh estimates a confidence interval for the reliability of each expert and filters out the one(s) whose estimated upper-bound confidence interval is below a threshold - which jointly optimizes expected accuracy (mean) and need to better estimate the expert's accuracy (variance). our framework is flexible enough to work with a wide range of different noise levels and outperforms baselines such as asking all available experts and random expert selection. in particular, iethresh achieves a given level of accuracy with less than half the queries issued by all-experts labeling and less than a third the queries required by random expert selection on datasets such as the uci mushroom one. the results show that our method naturally balances exploration and exploitation as it gains knowledge of which experts to rely upon, and selects them with increasing frequency.
exploring social tagging graph for web object classification. this paper studies web object classification problem with the novel exploration of social tags. automatically classifying web objects into manageable semantic categories has long been a fundamental preprocess for indexing, browsing, searching, and mining these objects. the explosive growth of heterogeneous web objects, especially non-textual objects such as products, pictures, and videos, has made the problem of web classification increasingly challenging. such objects often suffer from a lack of easy-extractable features with semantic information, interconnections between each other, as well as training examples with category labels. in this paper, we explore the social tagging data to bridge this gap. we cast web object classification problem as an optimization problem on a graph of objects and tags. we then propose an efficient algorithm which not only utilizes social tags as enriched semantic features for the objects, but also infers the categories of unlabeled objects from both homogeneous and heterogeneous labeled objects, through the implicit connection of social tags. experiment results show that the exploration of social tags effectively boosts web object classification. our algorithm significantly outperforms the state-of-the-art of general classification methods.
efficient anomaly monitoring over moving object trajectory streams. lately there exist increasing demands for online abnormality monitoring over trajectory streams, which are obtained from moving object tracking devices. this problem is challenging due to the requirement of high speed data processing within limited space cost. in this paper, we present a novel framework for monitoring anomalies over continuous trajectory streams. first, we illustrate the importance of distance-based anomaly monitoring over moving object trajectories. then, we utilize the local continuity characteristics of trajectories to build local clusters upon trajectory streams and monitor anomalies via efficient pruning strategies. finally, we propose a piecewise metric index structure to reschedule the joining order of local clusters to further reduce the time cost. our extensive experiments demonstrate the effectiveness and efficiency of our methods.
audience selection for on-line brand advertising: privacy-friendly social network targeting. this paper describes and evaluates privacy-friendly methods for extracting quasi-social networks from browser behavior on user-generated content sites, for the purpose of finding good audiences for brand advertising (as opposed to click maximizing, for example). targeting social-network neighbors resonates well with advertisers, and on-line browsing behavior data counterintuitively can allow the identification of good audiences anonymously. besides being one of the first papers to our knowledge on data mining for on-line brand advertising, this paper makes several important contributions. we introduce a framework for evaluating brand audiences, in analogy to predictive-modeling holdout evaluation. we introduce methods for extracting quasi-social networks from data on visitations to social networking pages, without collecting any information on the identities of the browsers or the content of the social-network pages. we introduce measures of brand proximity in the network, and show that audiences with high brand proximity indeed show substantially higher brand affinity. finally, we provide evidence that the quasi-social network embeds a true social network, which along with results from social theory offers one explanation for the increase in brand affinity of the selected audiences.
doulion: counting triangles in massive graphs with a coin. counting the number of triangles in a graph is a beautiful algorithmic problem which has gained importance over the last years due to its significant role in complex network analysis. metrics frequently computed such as the clustering coefficient and the transitivity ratio involve the execution of a triangle counting algorithm. furthermore, several interesting graph mining applications rely on computing the number of triangles in the graph of interest. in this paper, we focus on the problem of counting triangles in a graph. we propose a practical method, out of which all triangle counting algorithms can potentially benefit. using a straightforward triangle counting algorithm as a black box, we performed 166 experiments on real-world networks and on synthetic datasets as well, where we show that our method works with high accuracy, typically more than 99% and gives significant speedups, resulting in even ≈ 130 times faster performance.
drosophila gene expression pattern annotation using sparse features and term-term interactions. the drosophila gene expression pattern images document the spatial and temporal dynamics of gene expression and they are valuable tools for explicating the gene functions, interaction, and networks during drosophila embryogenesis. to provide text-based pattern searching, the images in the berkeley drosophila genome project (bdgp) study are annotated with ontology terms manually by human curators. we present a systematic approach for automating this task, because the number of images needing text descriptions is now rapidly increasing. we consider both improved feature representation and novel learning formulation to boost the annotation performance. for feature representation, we adapt the bag-of-words scheme commonly used in visual recognition problems so that the image group information in the bdgp study is retained. moreover, images from multiple views can be integrated naturally in this representation. to reduce the quantization error caused by the bag-of-words representation, we propose an improved feature representation scheme based on the sparse learning technique. in the design of learning formulation, we propose a local regularization framework that can incorporate the correlations among terms explicitly. we further show that the resulting optimization problem admits an analytical solution. experimental results show that the representation based on sparse learning outperforms the bag-of-words representation significantly. results also show that incorporation of the term-term correlations improves the annotation performance consistently.
large-scale behavioral targeting. behavioral targeting (bt) leverages historical user behavior to select the ads most relevant to users to display. the state-of-the-art of bt derives a linear poisson regression model from fine-grained user behavioral data and predicts click-through rate (ctr) from user history. we designed and implemented a highly scalable and efficient solution to bt using hadoop mapreduce framework. with our parallel algorithm and the resulting system, we can build above 450 bt-category models from the entire yahoo's user base within one day, the scale that one can not even imagine with prior systems. moreover, our approach has yielded 20% ctr lift over the existing production system by leveraging the well-grounded probabilistic model fitted from a much larger training dataset. specifically, our major contributions include: (1) a mapreduce statistical learning algorithm and implementation that achieve optimal data parallelism, task parallelism, and load balance in spite of the typically skewed distribution of domain data. (2) an in-place feature vector generation algorithm with linear time complexity o(n) regardless of the granularity of sliding target window. (3) an in-memory caching scheme that significantly reduces the number of disk ios to make large-scale learning practical. (4) highly efficient data structures and sparse representations of models and data to enable fast model updates. we believe that our work makes significant contributions to solving large-scale machine learning problems of industrial relevance in general. finally, we report comprehensive experimental results, using industrial proprietary codebase and datasets.
multi-focal learning and its application to customer service support. in this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within each focal group. the multi-focal learning problem is motivated by numerous real-world learning applications. for instance, for the same type of problems encountered in a customer service center, the problem descriptions from different customers can be quite different. the experienced customers usually give more precise and focused descriptions about the problem. in contrast, the inexperienced customers usually provide more diverse descriptions. in this case, the examples from the same class in the training data can be naturally in different focal groups. as a result, it is necessary to identify those natural focal groups and exploit them for learning at different focuses. the key developmental challenge is how to identify those focal groups in the training data. as a case study, we exploit multi-focal learning for profiling problems in customer service centers. the results show that multifocal learning can significantly boost the learning accuracies of existing learning algorithms, such as support vector machines (svms), for classifying customer problems.
learning with a non-exhaustive training dataset: a case study: detection of bacteria cultures using optical-scattering technology. for a training dataset with a nonexhaustive list of classes, i.e. some classes are not yet known and hence are not represented, the resulting learning problem is ill-defined. in this case a sample from a missing class is incorrectly classified to one of the existing classes. for some applications the cost of misclassifying a sample could be negligible. however, the significance of this problem can better be acknowledged when the potentially undesirable consequences of incorrectly classifying a food pathogen as a nonpathogen are considered. our research is directed towards the real-time detection of food pathogens using optical-scattering technology. bacterial colonies consisting of the progeny of a single parent cell scatter light at 635 nm to produce unique forward-scatter signatures. these spectral signatures contain descriptive characteristics of bacterial colonies, which can be used to identify bacteria cultures in real time. one bottleneck that remains to be addressed is the nonexhaustive nature of the training library. it is very difficult if not impractical to collect samples from all possible bacteria colonies and construct a digital library with an exhaustive set of scatter signatures. this study deals with the real-time detection of samples from a missing class and the associated problem of learning with a nonexhaustive training dataset. our proposed method assumes a common prior for the set of all classes, known and missing. the parameters of the prior are estimated from the samples of the known classes. this prior is then used to generate a large number of samples to simulate the space of missing classes. finally a bayesian maximum likelihood classifier is implemented using samples from real as well as simulated classes. experiments performed with samples collected for 28 bacteria subclasses favor the proposed approach over the state of the art.
combining link and content for community detection: a discriminative approach. in this paper, we consider the problem of combining link and content analysis for community detection from networked data, such as paper citation networks and word wide web. most existing approaches combine link and content information by a generative model that generates both links and contents via a shared set of community memberships. these generative models have some shortcomings in that they failed to consider additional factors that could affect the community memberships and isolate the contents that are irrelevant to community memberships. to explicitly address these shortcomings, we propose a discriminative model for combining the link and content analysis for community detection. first, we propose a conditional model for link analysis and in the model, we introduce hidden variables to explicitly model the popularity of nodes. second, to alleviate the impact of irrelevant content attributes, we develop a discriminative model for content analysis. these two models are unified seamlessly via the community memberships. we present efficient algorithms to solve the related optimization problems based on bound optimization and alternating projection. extensive experiments with benchmark data sets show that the proposed framework significantly outperforms the state-of-the-art approaches for combining link and content analysis for community detection.
scalable pseudo-likelihood estimation in hybrid random fields. learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. in many interesting applications, the domain dimensionality is such as to prevent state-of-the-art statistical learning techniques from delivering accurate models in reasonable time. this paper presents a hybrid random field model for pseudo-likelihood estimation in high-dimensional domains. a theoretical analysis proves that the class of pseudo-likelihood distributions representable by hybrid random fields strictly includes the class of joint probability distributions representable by bayesian networks. in order to learn hybrid random fields from data, we develop the markov blanket merging algorithm. theoretical and experimental evidence shows that markov blanket merging scales up very well to high-dimensional datasets. as compared to other widely used statistical learning techniques, markov blanket merging delivers accurate results in a number of link prediction tasks, while achieving also significant improvements in terms of computational efficiency. our software implementation of the models investigated in this paper is publicly available at http://www.dii.unisi.it/~freno/. the same website also hosts the datasets used in this work that are not available elsewhere in the same preprocessing used for our experiments.
detection of unique temporal segments by information theoretic meta-clustering. the central challenge in temporal data analysis is to obtain knowledge about its underlying dynamics. in this paper, we address the observation of noisy, stochastic processes and attempt to detect temporal segments that are related to inconsistencies and irregularities in its dynamics. many conventional anomaly detection approaches detect anomalies based on the distance between patterns, and often provide only limited intuition about the generative process of the anomalies. meanwhile, model-based approaches have difficulty in identifying a small, clustered set of anomalies. we propose information-theoretic meta-clustering (itmc), a formalization of model-based clustering principled by the theory of lossy data compression. itmc identifies a 'unique' cluster whose distribution diverges significantly from the entire dataset. furthermore, itmc employs a regularization term derived from the preference for high compression rate, which is critical to the precision of detection. for empirical evaluation, we apply itmc to two temporal anomaly detection tasks. datasets are taken from generative processes involving heterogeneous and inconsistent dynamics. a comparison to baseline methods shows that the proposed algorithm detects segments from irregular states with significantly high precision and recall.
learning, indexing, and diagnosing network faults. modern communication networks generate massive volume of operational event data, e.g., alarm, alert, and metrics, which can be used by a network management system (nms) to diagnose potential faults. in this work, we introduce a new class of indexable fault signatures that encode temporal evolution of events generated by a network fault as well as topological relationships among the nodes where these events occur. we present an efficient learning algorithm to extract such fault signatures from noisy historical event data, and with the help of novel space-time indexing structures, we show how to perform efficient, online signature matching. we provide results from extensive experimental studies to explore the efficacy of our approach and point out potential applications of such signatures for many different types of networks including social and information networks.
cartesian contour: a concise representation for a collection of frequent sets. in this paper, we consider a novel scheme referred to as cartesian contour to concisely represent the collection of frequent itemsets. different from the existing works, this scheme provides a complete view of these itemsets by covering the entire collection of them. more interestingly, it takes a first step in deriving a generative view of the frequent pattern formulation, i.e., how a small number of patterns interact with each other and produce the complexity of frequent itemsets. we perform a theoretical investigation of the concise representation problem and link it to the biclique set cover problem and prove its np-hardness. we develop a novel approach utilizing the technique developed in frequent itemset mining, set cover, and max k-cover to approximate the minimal biclique set cover problem. in addition, we consider several heuristic techniques to speedup the construction of cartesian contour. the detailed experimental study demonstrates the effectiveness and efficiency of our approach.
mining broad latent query aspects from search sessions. search queries are typically very short, which means they are often underspecified or have senses that the user did not think of. a broad latent query aspect is a set of keywords that succinctly represents one particular sense, or one particular information need, that can aid users in reformulating such queries. we extract such broad latent aspects from query reformulations found in historical search session logs. we propose a framework under which the problem of extracting such broad latent aspects reduces to that of optimizing a formal objective function under constraints on the total number of aspects the system can store, and the number of aspects that can be shown in response to any given query. we present algorithms to find a good set of aspects, and also to pick the best k aspects matching any query. empirical results on real-world search engine logs show significant gains over a strong baseline that uses single-keyword reformulations: a gain of 14% and 23% in terms of human-judged accuracy and click-through data respectively, and around 20% in terms of consistency among aspects predicted for "similar" queries. this demonstrates both the importance of broad query aspects, and the efficacy of our algorithms for extracting them.
name-ethnicity classification from open sources. the problem of ethnicity identification from names has a variety of important applications, including biomedical research, demographic studies, and marketing. here we report on the development of an ethnicity classifier where all training data is extracted from public, non-confidential (and hence somewhat unreliable) sources. our classifier uses hidden markov models (hmms) and decision trees to classify names into 13 cultural/ethnic groups with individual group accuracy comparable accuracy to earlier binary (e.g., spanish/non-spanish) classifiers. we have applied this classifier to over 20 million names from a large-scale news corpus, identifying interesting temporal and spatial trends on the representation of particular cultural/ethnic groups.
grouped graphical granger modeling methods for temporal causal modeling. we develop and evaluate an approach to causal modeling based on time series data, collectively referred to as "grouped graphical granger modeling methods." graphical granger modeling uses graphical modeling techniques on time series data and invokes the notion of "granger causality" to make assertions on causality among a potentially large number of time series variables through inference on time-lagged effects. the present paper proposes a novel enhancement to the graphical granger methodology by developing and applying families of regression methods that are sensitive to group information among variables, to leverage the group structure present in the lagged temporal variables according to the time series they belong to. additionally, we propose a new family of algorithms we call group boosting, as an improved component of grouped graphical granger modeling over the existing regression methods with grouped variable selection in the literature (e.g group lasso). the introduction of group boosting methods is primarily motivated by the need to deal with non-linearity in the data. we perform empirical evaluation to confirm the advantage of the grouped graphical granger methods over the standard (non-grouped) methods, as well as that specific to the methods based on group boosting. this advantage is also demonstrated for the real world application of gene regulatory network discovery from time-course microarray data.
structured correspondence topic models for mining captioned figures in biological literature. a major source of information (often the most crucial and informative part) in scholarly articles from scientific journals, proceedings and books are the figures that directly provide images and other graphical illustrations of key experimental results and other scientific contents. in biological articles, a typical figure often comprises multiple panels, accompanied by either scoped or global captioned text. moreover, the text in the caption contains important semantic entities such as protein names, gene ontology, tissues labels, etc., relevant to the images in the figure. due to the avalanche of biological literature in recent years, and increasing popularity of various bio-imaging techniques, automatic retrieval and summarization of biological information from literature figures has emerged as a major unsolved challenge in computational knowledge extraction and management in the life science. we present a new structured probabilistic topic model built on a realistic figure generation scheme to model the structurally annotated biological figures, and we derive an efficient inference algorithm based on collapsed gibbs sampling for information retrieval and visualization. the resulting program constitutes one of the key ir engines in our slif system that has recently entered the final round (4 out 70 competing systems) of the elsevier grand challenge on knowledge enhancement in the life science. here we present various evaluations on a number of data mining tasks to illustrate our method.
toward autonomic grids: analyzing the job flow with affinity streaming. the affinity propagation (ap) clustering algorithm proposed by frey and dueck (2007) provides an understandable, nearly optimal summary of a dataset, albeit with quadratic computational complexity. this paper, motivated by autonomic computing, extends ap to the data streaming framework. firstly a hierarchical strategy is used to reduce the complexity to o(n1+ε); the distortion loss incurred is analyzed in relation with the dimension of the data items. secondly, a coupling with a change detection test is used to cope with non-stationary data distribution, and rebuild the model as needed. the presented approach strap is applied to the stream of jobs submitted to the egee grid, providing an understandable description of the job flow and enabling the system administrator to spot online some sources of failures.
mining web logs: applications and challenges. web logs record the primary interaction of users with web pages in general and search engines in particular. there are two sources for such logs: user trails obtained from toolbars and query/click information obtained from search engines. in this talk we will address the task of mining this rich data to improve user experience on the web. we will illustrate a few applications, together with the modeling and algorithmic challenges that stem from these applications. we will also discuss the privacy issues that arise in this context.
mining social networks for personalized email prioritization. email is one of the most prevalent communication tools today, and solving the email overload problem is pressingly urgent. a good way to alleviate email overload is to automatically prioritize received messages according to the priorities of each user. however, research on statistical learning methods for fully personalized email prioritization (pep) has been sparse due to privacy issues, since people are reluctant to share personal messages and importance judgments with the research community. it is therefore important to develop and evaluate pep methods under the assumption that only limited training examples can be available, and that the system can only have the personal email data of each user during the training and testing of the model for that user. this paper presents the first study (to the best of our knowledge) under such an assumption. specifically, we focus on analysis of personal social networks to capture user groups and to obtain rich features that represent the social roles from the viewpoint of a particular user. we also developed a novel semi-supervised (transductive) learning algorithm that propagates importance labels from training examples to test examples through message and user nodes in a personal email network. these methods together enable us to obtain an enriched vector representation of each new email message, which consists of both standard features of an email message (such as words in the title or body, sender and receiver ids, etc.) and the induced social features from the sender and receivers of the message. using the enriched vector representation as the input in svm classifiers to predict the importance level for each test message, we obtained significant performance improvement over the baseline system (without induced social features) in our experiments on a multi-user data collection. we obtained significant performance improvement over the baseline system (without induced social features) in our experiments on a multi-user data collection: the relative error reduction in mae was 31% in micro-averaging, and 14% in macro-averaging.
effective multi-label active learning for text classification. labeling text data is quite time-consuming but essential for automatic text classification. especially, manually creating multiple labels for each document may become impractical when a very large amount of data is needed for training multi-label text classifiers. to minimize the human-labeling efforts, we propose a novel multi-label active learning approach which can reduce the required labeled data without sacrificing the classification accuracy. traditional active learning algorithms can only handle single-label problems, that is, each data is restricted to have one label. our approach takes into account the multi-label information, and select the unlabeled data which can lead to the largest reduction of the expected model loss. specifically, the model loss is approximated by the size of version space, and the reduction rate of the size of version space is optimized with support vector machines (svm). an effective label prediction method is designed to predict possible labels for each unlabeled data point, and the expected loss for multi-label data is approximated by summing up losses on all labels according to the most confident result of label prediction. experiments on several real-world data sets (all are publicly available) demonstrate that our approach can obtain promising classification result with much fewer labeled data than state-of-the-art methods.
coco: coding cost for parameter-free outlier detection. how can we automatically spot all outstanding observations in a data set? this question arises in a large variety of applications, e.g. in economy, biology and medicine. existing approaches to outlier detection suffer from one or more of the following drawbacks: the results of many methods strongly depend on suitable parameter settings being very difficult to estimate without background knowledge on the data, e.g. the minimum cluster size or the number of desired outliers. many methods implicitly assume gaussian or uniformly distributed data, and/or their result is difficult to interpret. to cope with these problems, we propose coco, a technique for parameter-free outlier detection. the basic idea of our technique relates outlier detection to data compression: outliers are objects which can not be effectively compressed given the data set. to avoid the assumption of a certain data distribution, coco relies on a very general data model combining the exponential power distribution with independent components. we define an intuitive outlier factor based on the principle of the minimum description length together with an novel algorithm for outlier detection. an extensive experimental evaluation on synthetic and real world data demonstrates the benefits of our technique. availability: the source code of coco and the data sets used in the experiments are available at: http://www.dbs.ifi.lmu.de/forschung/kdd/boehm/coco.
meme-tracking and the dynamics of the news cycle. tracking new topics, ideas, and "memes" across the web has been an issue of considerable interest. recent work has developed methods for tracking topic shifts over long time scales, as well as abrupt spikes in the appearance of particular named entities. however, these approaches are less well suited to the identification of content that spreads widely and then fades over time scales on the order of days - the time scale at which we perceive news and events. we develop a framework for tracking short, distinctive phrases that travel relatively intact through on-line text; developing scalable algorithms for clustering textual variants of such phrases, we identify a broad class of memes that exhibit wide spread and rich variation on a daily basis. as our principal domain of study, we show how such a meme-tracking approach can provide a coherent representation of the news cycle - the daily rhythms in the news media that have long been the subject of qualitative interpretation but have never been captured accurately enough to permit actual quantitative analysis. we tracked 1.6 million mainstream media sites and blogs over a period of three months with the total of 90 million articles and we find a set of novel and persistent temporal patterns in the news cycle. in particular, we observe a typical lag of 2.5 hours between the peaks of attention to a phrase in the news media and in blogs respectively, with divergent behavior around the overall peak and a "heartbeat"-like pattern in the handoff between news and blogs. we also develop and analyze a mathematical model for the kinds of temporal variation that the system exhibits.
tangent: a novel, 'surprise me', recommendation algorithm. most of recommender systems try to find items that are most relevant to the older choices of a given user. here we focus on the "surprise me" query: a user may be bored with his/her usual genre of items (e.g., books, movies, hobbies), and may want a recommendation that is related, but off the beaten path, possibly leading to a new genre of books/movies/hobbies. how would we define, as well as automate, this seemingly selfcontradicting request? we introduce tangent, a novel recommendation algorithm to solve this problem. the main idea behind tangent is to envision the problem as node selection on a graph, giving high scores to nodes that are well connected to the older choices, and at the same time well connected to unrelated choices. the method is carefully designed to be (a) parameter-free (b) effective and (c) fast. we illustrate the benefits of tangent with experiments on both synthetic and real data sets. we show that tangent makes reasonable, yet surprising, horizon-broadening recommendations. moreover, it is fast and scalable, since it can easily use existing fast algorithms on graph node proximity.
collective annotation of wikipedia entities in web text. to take the first step beyond keyword-based search toward entity-based search, suitable token spans ("spots") on documents must be identified as references to real-world entities from an entity catalog. several systems have been proposed to link spots on web pages to entities in wikipedia. they are largely based on local compatibility between the text around the spot and textual metadata associated with the entity. two recent systems exploit inter-label dependencies, but in limited ways. we propose a general collective disambiguation approach. our premise is that coherent documents refer to entities from one or a few related topics or domains. we give formulations for the trade-off between local spot-to-entity compatibility and measures of global coherence between entities. optimizing the overall entity assignment is np-hard. we investigate practical solutions based on local hill-climbing, rounding integer linear programs, and pre-clustering entities followed by local optimization within clusters. in experiments involving over a hundred manually-annotated web pages and tens of thousands of spots, our approaches significantly outperform recently-proposed algorithms.
towards a universal marketplace over the web: statistical multi-label classification of service provider forms with simulated annealing. there is a growing number of service providers that a consumer can interact with over the web to learn their service terms. the service terms, such as price and time to completion of the service, depend on the consumer's particular specifications. for instance, a printing services provider would need from its customers specifications such as the size of paper, type of ink, proofing and perforation. in a few sectors, there exist marketplace sites that provide consumers with specifications forms, which the consumer can fill out to learn the service terms of multiple service providers. unfortunately, there are only a few such marketplace sites, and they cover a few sectors. at hp labs, we are working towards building a universal marketplace site, i.e., a marketplace site that covers thousands of sectors and hundreds of providers per sector. one issue in this domain is the automated discovery/retrieval of the specifications for each sector. we address it through extracting and analyzing content from the websites of the service providers listed in business directories. the challenge is that each service provider is often listed under multiple service categories in a business directory, making it infeasible to utilize standard supervised learning techniques. we address this challenge through employing a multilabel statistical clustering approach within an expectation-maximization framework. we implement our solution to retrieve specifications for 3000 sectors, representing more than 300,000 service providers. we discuss our results within the context of the services needed to design a marketing campaign for a small business.
grocery shopping recommendations based on basket-sensitive random walk. we describe a recommender system in the domain of grocery shopping. while recommender systems have been widely studied, this is mostly in relation to leisure products (e.g. movies, books and music) with non-repeated purchases. in grocery shopping, however, consumers will make multiple purchases of the same or very similar products more frequently than buying entirely new items. the proposed recommendation scheme offers several advantages in addressing the grocery shopping problem, namely: 1) a product similarity measure that suits a domain where no rating information is available; 2) a basket sensitive random walk model to approximate product similarities by exploiting incomplete neighborhood information; 3) online adaptation of the recommendation based on the current basket and 4) a new performance measure focusing on products that customers have not purchased before or purchase infrequently. empirical results benchmarking on three real-world data sets demonstrate a performance improvement of the proposed method over other existing collaborative filtering models.
constrained optimization for validation-guided conditional random field learning. conditional random fields(crfs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. the training of crfs is typically formulated as an unconstrained optimization problem that maximizes the conditional likelihood. however, maximum likelihood training is prone to overfitting. to address this issue, we propose a novel constrained nonlinear optimization formulation in which the prediction accuracy of cross-validation sets are included as constraints. instead of requiring multiple passes of training, the constrained formulation allows the cross-validation be handled in one pass of constrained optimization. the new formulation is discontinuous, and classical lagrangian based constraint handling methods are not applicable. a new constrained optimization algorithm based on the recently proposed extended saddle point theory is developed to learn the constrained crf model. experimental results on gene and stock-price prediction tasks show that the constrained formulation is able to significantly improve the generalization ability of crf training.
large-scale graph mining using backbone refinement classes. we present a new approach to large-scale graph mining based on so-called backbone refinement classes. the method efficiently mines tree-shaped subgraph descriptors under minimum frequency and significance constraints, using classes of fragments to reduce feature set size and running times. the classes are defined in terms of fragments sharing a common backbone. the method is able to optimize structural inter-feature entropy as opposed to occurrences, which is characteristic for open or closed fragment mining. in the experiments, the proposed method reduces feature set sizes by >90 % and >30 % compared to complete tree mining and open tree mining, respectively. evaluation using crossvalidation runs shows that their classification accuracy is similar to the complete set of trees but significantly better than that of open trees. compared to open or closed fragment mining, a large part of the search space can be pruned due to an improved statistical constraint (dynamic upper bound adjustment), which is also confirmed in the experiments in lower running times compared to ordinary (static) upper bound pruning. further analysis using large-scale datasets yields insight into important properties of the proposed descriptors, such as the dataset coverage and the class size represented by each descriptor. a final cross-validation run confirms that the novel descriptors render large training sets feasible which previously might have been intractable.
a case study of behavior-driven conjoint analysis on yahoo!: front page today module. conjoint analysis is one of the most popular market research methodologies for assessing how customers with heterogeneous preferences appraise various objective characteristics in products or services, which provides critical inputs for many marketing decisions, e.g. optimal design of new products and target market selection. nowadays it becomes practical in e-commercial applications to collect millions of samples quickly. however, the large-scale data sets make traditional conjoint analysis coupled with sophisticated monte carlo simulation for parameter estimation computationally prohibitive. in this paper, we report a successful large-scale case study of conjoint analysis on click through stream in a real-world application at yahoo!. we consider identifying users' heterogenous preferences from millions of click/view events and building predictive models to classify new users into segments of distinct behavior pattern. a scalable conjoint analysis technique, known as tensor segmentation, is developed by utilizing logistic tensor regression in standard partworth framework for solutions. in offline analysis on the samples collected from a random bucket of yahoo! front page today module, we compare tensor segmentation against other segmentation schemes using demographic information, and study user preferences on article content within tensor segments. our knowledge acquired in the segmentation results also provides assistance to editors in content management and user targeting. the usefulness of our approach is further verified by the observations in a bucket test launched in dec. 2008.
improving classification accuracy using automatically extracted training data. classification is a core task in knowledge discovery and data mining, and there has been substantial research effort in developing sophisticated classification models. in a parallel thread, recent work from the nlp community suggests that for tasks such as natural language disambiguation even a simple algorithm can outperform a sophisticated one, if it is provided with large quantities of high quality training data. in those applications, training data occurs naturally in text corpora, and high quality training data sets running into billions of words have been reportedly used. we explore how we can apply the lessons from the nlp community to kdd tasks. specifically, we investigate how to identify data sources that can yield training data at low cost and study whether the quantity of the automatically extracted training data can compensate for its lower quality. we carry out this investigation for the specific task of inferring whether a search query has commercial intent. we mine toolbar and click logs to extract queries from sites that are predominantly commercial (e.g., amazon) and non-commercial (e.g., wikipedia). we compare the accuracy obtained using such training data against manually labeled training data. our results show that we can have large accuracy gains using automatically extracted training data at much lower cost.
issues in evaluation of stream learning algorithms. learning from data streams is a research area of increasing importance. nowadays, several stream learning algorithms have been developed. most of them learn decision models that continuously evolve over time, run in resource-aware environments, detect and react to changes in the environment generating data. one important issue, not yet conveniently addressed, is the design of experimental work to evaluate and compare decision models that evolve over time. there are no golden standards for assessing performance in non-stationary environments. this paper proposes a general framework for assessing predictive stream learning algorithms. we defend the use of predictive sequential methods for error estimate - the prequential error. the prequential error allows us to monitor the evolution of the performance of models that evolve over time. nevertheless, it is known to be a pessimistic estimator in comparison to holdout estimates. to obtain more reliable estimators we need some forgetting mechanism. two viable alternatives are: sliding windows and fading factors. we observe that the prequential error converges to an holdout estimator when estimated over a sliding window or using fading factors. we present illustrative examples of the use of prequential error estimators, using fading factors, for the tasks of: i) assessing performance of a learning algorithm; ii) comparing learning algorithms; iii) hypothesis testing using mcnemar test; and iv) change detection using page-hinkley test. in these tasks, the prequential error estimated using fading factors provide reliable estimators. in comparison to sliding windows, fading factors are faster and memory-less, a requirement for streaming applications. this paper is a contribution to a discussion in the good-practices on performance assessment when learning dynamic models that evolve over time.
large human communication networks: patterns and a utility-driven generator. given a real, and weighted person-to-person network which changes over time, what can we say about the cliques that it contains? do the incidents of communication, or weights on the edges of a clique follow any pattern? real, and in-person social networks have many more triangles than chance would dictate. as it turns out, there are many more cliques than one would expect, in surprising patterns. in this paper, we study massive real-world social networks formed by direct contacts among people through various personal communication services, such as phone-call, sms, im etc. the contributions are the following: (a) we discover surprising patterns with the cliques, (b) we report power-laws of the weights on the edges of cliques, (c) our real networks follow these patterns such that we can trust them to spot outliers and finally, (d) we propose the first utility-driven graph generator for weighted time-evolving networks, which match the observed patterns. our study focused on three large datasets, each of which is a different type of communication service, with over one million records, and spans several months of activity.
on compressing social networks. motivated by structural properties of the web graph that support efficient data structures for in memory adjacency queries, we study the extent to which a large network can be compressed. boldi and vigna (www 2004), showed that web graphs can be compressed down to three bits of storage per edge; we study the compressibility of social networks where again adjacency queries are a fundamental primitive. to this end, we propose simple combinatorial formulations that encapsulate efficient compressibility of graphs. we show that some of the problems are np-hard yet admit effective heuristics, some of which can exploit properties of social networks such as link reciprocity. our extensive experiments show that social networks and the web graph exhibit vastly different compressibility characteristics.
using graph-based metrics with empirical risk minimization to speed up active learning on networked data. active and semi-supervised learning are important techniques when labeled data are scarce. recently a method was suggested for combining active learning with a semi-supervised learning algorithm that uses gaussian fields and harmonic functions. this classifier is relational in nature: it relies on having the data presented as a partially labeled graph (also known as a within-network learning problem). this work showed yet again that empirical risk minimization (erm) was the best method to find the next instance to label and provided an efficient way to compute erm with the semi-supervised classifier. the computational problem with erm is that it relies on computing the risk for all possible instances. if we could limit the candidates that should be investigated, then we can speed up active learning considerably. in the case where the data is graphical in nature, we can leverage the graph structure to rapidly identify instances that are likely to be good candidates for labeling. this paper describes a novel hybrid approach of using of community finding and social network analytic centrality measures to identify good candidates for labeling and then using erm to find the best instance in this candidate set. we show on real-world data that we can limit the erm computations to a fraction of instances with comparable performance.
temporal mining for interactive workflow data analysis. in the past few years there has been an increasing interest in the analysis of process logs. several proposed techniques, such as workflow mining, are aimed at automatically deriving the underlying workflow models. however, current approaches only pay little attention on an important piece of information contained in process logs: the timestamps, which are used to define a sequential ordering of the performed tasks. in this work we try to overcome these limitations by explicitly including time in the extracted knowledge, thus making the temporal information a first-class citizen of the analysis process. this makes it possible to discern between apparently identical process executions that are performed with different transition times between consecutive tasks. this paper proposes a framework for the user-interactive exploration of a condensed representation of groups of executions of a given process. the framework is based on the use of an existing mining paradigm: temporally-annotated sequences (tas). these are aimed at extracting sequential patterns where each transition between two events is annotated with a typical transition time that emerges from input data. with the extracted tas, which represent sets of possible frequent executions with their typical transition times, a few factorizing operators are built. these operators condense such executions according to possible parallel or possible mutual exclusive executions. lastly, such condensed representation is rendered to the user via the exploration graph, namely the temporally-annotated graph (tag). the user, the domain expert, is allowed to explore the different and alternative factorizations corresponding to different interpretations of the actual executions. according to the user choices, the system discards or retains certain hypotheses on actual executions and shows the consequent scenarios resulting from the coresponding re-aggregation of the actual data.
mismatched models, wrong results, and dreadful decisions: on choosing appropriate data mining tools. data mining techniques use 'score functions' to quantify how well a model fits a given data set. parameters are estimated by optimising the fit, as measured by the chosen score function, and model choice is guided by the size of the scores for the different models. since different score functions summarise the fit in different ways, it is important to choose a function which matches the objectives of the data mining exercise. for predictive classification problems, a wide variety of score functions exist, including measures such as precision and recall, the f measure, misclassification rate, the area under the roc curve (the auc), and others. the first four of these require a 'classification threshold' to be chosen, a choice which may not be easy, or may even be impossible, especially when the classification rule is to be applied in the future. in contrast, the auc does not require the specification of a classification threshold, but summarises performance over the range of possible threshold choices. however, unfortunately, and despite the widespread use of the auc, it has a previously unrecognised fundamental incoherence lying at the core of its definition. this means that using the auc can lead to poor model choice and unecessary misclassifications. the auc is set in context, its deficiency explained and the implications illustrated - with the bottom line being that the auc should not be used. a family of coherent alternative scores is described. the ideas are illustrated with examples from bank loans, fraud, face recognition, and health screening.
turning down the noise in the blogosphere. in recent years, the blogosphere has experienced a substantial increase in the number of posts published daily, forcing users to cope with information overload. the task of guiding users through this flood of information has thus become critical. to address this issue, we present a principled approach for picking a set of posts that best covers the important stories in the blogosphere. we define a simple and elegant notion of coverage and formalize it as a submodular optimization problem, for which we can efficiently compute a near-optimal solution. in addition, since people have varied interests, the ideal coverage algorithm should incorporate user preferences in order to tailor the selected posts to individual tastes. we define the problem of learning a personalized coverage function by providing an appropriate user-interaction model and formalizing an online learning framework for this task. we then provide a no-regret algorithm which can quickly learn a user's preferences from limited feedback. we evaluate our coverage and personalization algorithms extensively over real blog data. results from a user study show that our simple coverage algorithm does as well as most popular blog aggregation sites, including google blog search, yahoo! buzz, and digg. furthermore, we demonstrate empirically that our algorithm can successfully adapt to user preferences. we believe that our technique, especially with personalization, can dramatically reduce information overload.
large-scale sparse logistic regression. logistic regression is a well-known classification method that has been used widely in many applications of data mining, machine learning, computer vision, and bioinformatics. sparse logistic regression embeds feature selection in the classification framework using the l1-norm regularization, and is attractive in many applications involving high-dimensional data. in this paper, we propose lassplore for solving large-scale sparse logistic regression. specifically, we formulate the problem as the l1-ball constrained smooth convex optimization, and propose to solve the problem using the nesterov's method, an optimal first-order black-box method for smooth convex optimization. one of the critical issues in the use of the nesterov's method is the estimation of the step size at each of the optimization iterations. previous approaches either applies the constant step size which assumes that the lipschitz gradient is known in advance, or requires a sequence of decreasing step size which leads to slow convergence in practice. in this paper, we propose an adaptive line search scheme which allows to tune the step size adaptively and meanwhile guarantees the optimal convergence rate. empirical comparisons with several state-of-the-art algorithms demonstrate the efficiency of the proposed lassplore algorithm for large-scale problems.
towards combining web classification and web information extraction: a case study. web content analysis often has two sequential and separate steps: web classification to identify the target web pages, and web information extraction to extract the metadata contained in the target web pages. this decoupled strategy is highly ineffective since the errors in web classification will be propagated to web information extraction and eventually accumulate to a high level. in this paper we study the mutual dependencies between these two steps and propose to combine them by using a model of conditional random fields (crfs). this model can be used to simultaneously recognize the target web pages and extract the corresponding metadata. systematic experiments in our project ofcourse for online course search show that this model significantly improves the f1 value for both of the two steps. we believe that our model can be easily generalized to many web applications.
open standards and cloud computing: kdd-2009 panel report. at kdd-2009 in paris, a panel on open standards and cloud computing addressed emerging trends for data mining applications in science and industry. this report summarizes the answers from a distinguished group of thought leaders representing key software vendors in the data mining industry. supporting open standards and the predictive model markup language (pmml) in particular, the panel members discuss topics regarding the adoption of prevailing standards, benefits of interoperability for business users, and the practical application of predictive models. we conclude with an assessment of emerging technology trends and the impact that cloud computing will have on applications as well as licensing models for the predictive analytics industry.
characteristic relational patterns. research in relational data mining has two major directions: finding global models of a relational database and the discovery of local relational patterns within a database. while relational patterns show how attribute values co-occur in detail, their huge numbers hamper their usage in data analysis. global models, on the other hand, only provide a summary of how different tables and their attributes relate to each other, lacking detail of what is going on at the local level. in this paper we introduce a new approach that combines the positive properties of both directions: it provides a detailed description of the complete database using a small set of patterns. more in particular, we utilise a rich pattern language and show how a database can be encoded by such patterns. then, based on the mdlprinciple, the novel rdb-krimp algorithm selects the set of patterns that allows for the most succinct encoding of the database. this set, the code table, is a compact description of the database in terms of local relational patterns. we show that this resulting set is very small, both in terms of database size and in number of its local relational patterns: a reduction of up to 4 orders of magnitude is attained.
measuring the effects of preprocessing decisions and network forces in dynamic network analysis. social networks have become a major focus of research in recent years, initially directed towards static networks but increasingly, towards dynamic ones. in this paper, we investigate how different pre-processing decisions and different network forces such as selection and influence affect the modeling of dynamic networks. we also present empirical justification for some of the modeling assumptions made in dynamic network analysis (e.g., first-order markovian assumption) and develop metrics to measure the alignment between links and attributes under different strategies of using the historical network data. we also demonstrate the effect of attribute drift, that is, the importance of individual attributes in forming links change over time.
analyzing patterns of user content generation in online social networks. various online social networks (osns) have been developed rapidly on the internet. researchers have analyzed different properties of such osns, mainly focusing on the formation and evolution of the networks as well as the information propagation over the networks. in knowledge-sharing osns, such as blogs and question answering systems, issues on how users participate in the network and how users "generate/contribute" knowledge are vital to the sustained and healthy growth of the networks. however, related discussions have not been reported in the research literature. in this work, we empirically study workloads from three popular knowledge-sharing osns, including a blog system, a social bookmark sharing network, and a question answering social network to examine these properties. our analysis consistently shows that (1) users' posting behavior in these networks exhibits strong daily and weekly patterns, but the user active time in these osns does not follow exponential distributions; (2) the user posting behavior in these osns follows stretched exponential distributions instead of power-law distributions, indicating the influence of a small number of core users cannot dominate the network; (3) the distributions of user contributions on high-quality and effort-consuming contents in these osns have smaller stretch factors for the stretched exponential distribution. our study provides insights into user activity patterns and lays out an analytical foundation for further understanding various properties of these osns.
category detection using hierarchical mean shift. many applications in surveillance, monitoring, scientific discovery, and data cleaning require the identification of anomalies. although many methods have been developed to identify statistically significant anomalies, a more difficult task is to identify anomalies that are both interesting and statistically significant. category detection is an emerging area of machine learning that can help address this issue using a "human-in-the-loop" approach. in this interactive setting, the algorithm asks the user to label a query data point under an existing category or declare the query data point to belong to a previously undiscovered category. the goal of category detection is to bring to the user's attention a representative data point from each category in the data in as few queries as possible. in a data set with imbalanced categories, the main challenge is in identifying the rare categories or anomalies; hence, the task is often referred to as rare category detection. we present a new approach to rare category detection based on hierarchical mean shift. in our approach, a hierarchy is created by repeatedly applying mean shift with an increasing bandwidth on the data. this hierarchy allows us to identify anomalies in the data set at different scales, which are then posed as queries to the user. the main advantage of this methodology over existing approaches is that it does not require any knowledge of the dataset properties such as the total number of categories or the prior probabilities of the categories. results on real-world data sets show that our hierarchical mean shift approach performs consistently better than previous techniques.
network anomaly detection based on eigen equation compression. this paper addresses the issue of unsupervised network anomaly detection. in recent years, networks have played more and more critical roles. since their outages cause serious economic losses, it is quite significant to monitor their changes over time and to detect anomalies as early as possible. in this paper, we specifically focus on the management of the whole network. in it, it is important to detect anomalies which make great impact on the whole network, and the other local anomalies should be ignored. further, when we detect the former anomalies, it is required to localize nodes responsible for them. it is challenging to simultaneously perform the above two tasks taking into account the nonstationarity and strong correlations between nodes. we propose a network anomaly detection method which resolves the above two tasks in a unified way. the key ideas of the method are: (1)construction of quantities representing feature of a whole network and each node from the same input based on eigen equation compression, and (2)incremental anomalousness scoring based on learning the probability distribution of the quantities. we demonstrate through the experimental results using two benchmark data sets and a simulation data set that anomalies of a whole network and nodes responsible for them can be detected by the proposed method.
tell me something i don't know: randomization strategies for iterative data mining. there is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. this, however, leads to the problem of whether the results found by one method are a reflection of the phenomenon shown by the results of another method, or whether the results depict in some sense unrelated properties of the data. for example, using clustering can give indication of a clear cluster structure, and computing correlations between variables can show that there are many significant correlations in the data. however, it can be the case that the correlations are actually determined by the cluster structure. in this paper, we consider the problem of randomizing data so that previously discovered patterns or models are taken into account. the randomization methods can be used in iterative data mining. at each step in the data mining process, the randomization produces random samples from the set of data matrices satisfying the already discovered patterns or models. that is, given a data set and some statistics (e.g., cluster centers or co-occurrence counts) of the data, the randomization methods sample data sets having similar values of the given statistics as the original data set. we use metropolis sampling based on local swaps to achieve this. we describe experiments on real data that demonstrate the usefulness of our approach. our results indicate that in many cases, the results of, e.g., clustering actually imply the results of, say, frequent pattern discovery.
frequent pattern mining with uncertain data. this paper studies the problem of frequent pattern mining with uncertain data. we will show how broad classes of algorithms can be extended to the uncertain data setting. in particular, we will study candidate generate-and-test algorithms, hyper-structure algorithms and pattern growth based algorithms. one of our insightful observations is that the experimental behavior of different classes of algorithms is very different in the uncertain case as compared to the deterministic case. in particular, the hyper-structure and the candidate generate-and-test algorithms perform much better than tree-based algorithms. this counter-intuitive behavior is an important observation from the perspective of algorithm design of the uncertain variation of the problem. we will test the approach on a number of real and synthetic data sets, and show the effectiveness of two of our approaches over competitive techniques.
genre-based decomposition of email class noise. corruption of data by class-label noise is an important practical concern impacting many classification problems. studies of data cleaning techniques often assume a uniform label noise model, however, which is seldom realized in practice. relatively little is understood, as to how the natural label noise distribution can be measured or simulated. using email spam-filtering data, we demonstrate that class noise can have substantial content specific bias. we also demonstrate that noise detection techniques based on classifier confidence tend to identify instances that human assessors are likely to label in error. we show that genre modeling can be very informative in identifying potential areas of mislabeling. moreover, we are able to show that genre decomposition can also be used to substantially improve spam filtering accuracy, with our results outperforming the best published figures for the trec05-p1 and ceas-2008 benchmark collections.
optimizing web traffic via the media scheduling problem. website traffic varies through time in consistent and predictable ways, with highest traffic in the middle of the day. when providing media content to visitors, it is important to present repeat visitors with new content so that they keep coming back. in this paper we present an algorithm to balance the need to keep a website fresh with new content with the desire to present the best content to the most visitors at times of peak traffic. we formulate this as the media scheduling problem, where we attempt to maximize total clicks, given the overall traffic pattern and the time varying clickthrough rates of available media content. we present an efficient algorithm to perform this scheduling under certain conditions and apply this algorithm to real data obtained from server logs, showing evidence of significant improvements in traffic from our algorithmic schedules. finally, we analyze the click data, presenting models for why and how the clickthrough rate for new content declines as it ages.
opinionminer: a novel machine learning system for web opinion mining and extraction. merchants selling products on the web often ask their customers to share their opinions and hands-on experiences on products they have purchased. unfortunately, reading through all customer reviews is difficult, especially for popular items, the number of reviews can be up to hundreds or even thousands. this makes it difficult for a potential customer to read them to make an informed decision. the opinionminer system designed in this work aims to mine customer reviews of a product and extract high detailed product entities on which reviewers express their opinions. opinion expressions are identified and opinion orientations for each recognized product entity are classified as positive or negative. different from previous approaches that employed rule-based or statistical techniques, we propose a novel machine learning approach built under the framework of lexicalized hmms. the approach naturally integrates multiple important linguistic features into automatic learning. in this paper, we describe the architecture and main components of the system. the evaluation of the proposed method is presented based on processing the online product reviews from amazon and other publicly available datasets.
cross domain distribution adaptation via kernel mapping. when labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. however, the assumption made by existing approaches, that the marginal and conditional probabilities are directly related between source and target domains, has limited applicability in either the original space or its linear transformations. to solve this problem, we propose an adaptive kernel approach that maps the marginal distribution of target-domain and source-domain data into a common kernel space, and utilize a sample selection strategy to draw conditional probabilities between the two domains closer. we formally show that under the kernel-mapping space, the difference in distributions between the two domains is bounded; and the prediction error of the proposed approach can also be bounded. experimental results demonstrate that the proposed method outperforms both traditional inductive classifiers and the state-of-the-art boosting-based transfer algorithms on most domains, including text categorization and web page ratings. in particular, it can achieve around 10% higher accuracy than other approaches for the text categorization problem. the source code and datasets are available from the authors.
quantification and semi-supervised classification methods for handling changes in class distribution. in realistic settings the prevalence of a class may change after a classifier is induced and this will degrade the performance of the classifier. further complicating this scenario is the fact that labeled data is often scarce and expensive. in this paper we address the problem where the class distribution changes and only unlabeled examples are available from the new distribution. we design and evaluate a number of methods for coping with this problem and compare the performance of these methods. our quantification-based methods estimate the class distribution of the unlabeled data from the changed distribution and adjust the original classifier accordingly, while our semi-supervised methods build a new classifier using the examples from the new (unlabeled) distribution which are supplemented with predicted class values. we also introduce a hybrid method that utilizes both quantification and semi-supervised learning. all methods are evaluated using accuracy and f-measure on a set of benchmark data sets. our results demonstrate that our methods yield substantial improvements in accuracy and f-measure.
co-evolution of social and affiliation networks. in our work, we address the problem of modeling social network generation which explains both link and group formation. recent studies on social network evolution propose generative models which capture the statistical properties of real-world networks related only to node-to-node link formation. we propose a novel model which captures the co-evolution of social and affiliation networks. we provide surprising insights into group formation based on observations in several real-world networks, showing that users often join groups for reasons other than their friends. our experiments show that the model is able to capture both the newly observed and previously studied network properties. this work is the first to propose a generative model which captures the statistical properties of these complex networks. the proposed model facilitates controlled experiments which study the effect of actors' behavior on the evolution of affiliation networks, and it allows the generation of realistic synthetic datasets.
consensus group stable feature selection. stability is an important yet under-addressed issue in feature selection from high-dimensional and small sample data. in this paper, we show that stability of feature selection has a strong dependency on sample size. we propose a novel framework for stable feature selection which first identifies consensus feature groups from subsampling of training samples, and then performs feature selection by treating each consensus feature group as a single entity. experiments on both synthetic and real-world data sets show that an algorithm developed under this framework is effective at alleviating the problem of small sample size and leads to more stable feature selection results and comparable or better generalization performance than state-of-the-art feature selection algorithms. synthetic data sets and algorithm source code are available at http://www.cs.binghamton.edu/~lyu/kdd09/.
migration motif: a spatial - temporal pattern mining approach for financial markets. a recent study by two prominent finance researchers, fama and french, introduces a new framework for studying risk vs. return: the migration of stocks across size-value portfolio space. given the financial events of 2008, this first attempt to disentangle the relationships between migration behavior and stock returns is especially timely. their work, however, derives results only for market segments, not individual companies, and only for one-year moves. thus, we see a new challenge for financial data mining: how to capture and categorize the migration of individual companies, and how such behavior affects their returns. we propose a novel data mining approach to study the multi-year movement of individual companies. specifically, we address the question: "how does one discover frequent migration patterns in the stock market?" we present a new trajectory mining algorithm to discover migration motifs in financial markets. novel features of this algorithm are its handling of approximate pattern matching through a graph theoretical method, maximal clique identification, and incorporation of temporal and spatial constraints. we have performed a detailed study of the nasdaq, nyse, and amex stock markets, over a 43-year span. we successfully find migration motifs that confirm existing finance theories and other motifs that may lead to new financial models.
mining discrete patterns via binary matrix factorization. mining discrete patterns in binary data is important for subsampling, compression, and clustering. we consider rank-one binary matrix approximations that identify the dominant patterns of the data, while preserving its discrete property. a best approximation on such data has a minimum set of inconsistent entries, i.e., mismatches between the given binary data and the approximate matrix. due to the hardness of the problem, previous accounts of such problems employ heuristics and the resulting approximation may be far away from the optimal one. in this paper, we show that the rank-one binary matrix approximation can be reformulated as a 0-1 integer linear program (ilp). however, the ilp formulation is computationally expensive even for small-size matrices. we propose a linear program (lp) relaxation, which is shown to achieve a guaranteed approximation error bound. we further extend the proposed formulations using the regularization technique, which is commonly employed to address overfitting. the lp formulation is restricted to medium-size matrices, due to the large number of variables involved for large matrices. interestingly, we show that the proposed approximate formulation can be transformed into an instance of the minimum s-t cut problem, which can be solved efficiently by finding maximum flows. our empirical study shows the efficiency of the proposed algorithm based on the maximum flow. results also confirm the established theoretical bounds.
bgp-lens: patterns and anomalies in internet routing updates. the border gateway protocol (bgp) is one of the fundamental computer communication protocols. monitoring and mining bgp update messages can directly reveal the health and stability of internet routing. here we make two contributions: firstly we find patterns in bgp updates, like self-similarity, power-law and lognormal marginals; secondly using these patterns, we find anomalies. specifically, we develop bgp-lens, an automated bgp updates analysis tool, that has three desirable properties: (a) it is effective, able to identify phenomena that would otherwise go unnoticed, such as a peculiar 'clothesline' behavior or prolonged 'spikes' that last as long as 8 hours; (b) it is scalable, using algorithms are all linear on the number of time-ticks; and (c) it is admin-friendly, giving useful leads for phenomenon of interest. we showcase the capabilities of bgp-lens by identifying surprising phenomena verified by syadmins, over a massive trace of bgp updates spanning 2 years, from the publicly available site datapository.net.
wherenext: a location predictor on trajectory pattern mining. the pervasiveness of mobile devices and location based services is leading to an increasing volume of mobility data.this side eect provides the opportunity for innovative methods that analyse the behaviors of movements. in this paper we propose wherenext, which is a method aimed at predicting with a certain level of accuracy the next location of a moving object. the prediction uses previously extracted movement patterns named trajectory patterns, which are a concise representation of behaviors of moving objects as sequences of regions frequently visited with a typical travel time. a decision tree, named t-pattern tree, is built and evaluated with a formal training and test process. the tree is learned from the trajectory patterns that hold a certain area and it may be used as a predictor of the next location of a new trajectory finding the best matching path in the tree. three dierent best matching methods to classify a new moving object are proposed and their impact on the quality of prediction is studied extensively. using trajectory patterns as predictive rules has the following implications: (i) the learning depends on the movement of all available objects in a certain area instead of on the individual history of an object; (ii) the prediction tree intrinsically contains the spatio-temporal properties that have emerged from the data and this allows us to define matching methods that striclty depend on the properties of such movements. in addition, we propose a set of other measures, that evaluate a priori the predictive power of a set of trajectory patterns. this measures were tuned on a real life case study. finally, an exhaustive set of experiments and results on the real dataset are presented.
a lrt framework for fast spatial anomaly detection. given a spatial data set placed on an n x n grid, our goal is to find the rectangular regions within which subsets of the data set exhibit anomalous behavior. we develop algorithms that, given any user-supplied arbitrary likelihood function, conduct a likelihood ratio hypothesis test (lrt) over each rectangular region in the grid, rank all of the rectangles based on the computed lrt statistics, and return the top few most interesting rectangles. to speed this process, we develop methods to prune rectangles without computing their associated lrt statistics.
beyond blacklists: learning to detect malicious web sites from suspicious urls. malicious web sites are a cornerstone of internet criminal activities. as a result, there has been broad interest in developing systems to prevent the end user from visiting such sites. in this paper, we describe an approach to this problem based on automated url classification, using statistical methods to discover the tell-tale lexical and host-based properties of malicious web site urls. these methods are able to learn highly predictive models by extracting and automatically analyzing tens of thousands of features potentially indicative of suspicious urls. the resulting classifiers obtain 95-99% accuracy, detecting large numbers of malicious web sites from their urls, with only modest false positives.
predicting bounce rates in sponsored search advertisements. this paper explores an important and relatively unstudied quality measure of a sponsored search advertisement: bounce rate. the bounce rate of an ad can be informally defined as the fraction of users who click on the ad but almost immediately move on to other tasks. a high bounce rate can lead to poor advertiser return on investment, and suggests search engine users may be having a poor experience following the click. in this paper, we first provide quantitative analysis showing that bounce rate is an effective measure of user satisfaction. we then address the question, can we predict bounce rate by analyzing the features of the advertisement? an affirmative answer would allow advertisers and search engines to predict the effectiveness and quality of advertisements before they are shown. we propose solutions to this problem involving large-scale learning methods that leverage features drawn from ad creatives in addition to their keywords and landing pages.
clustering event logs using iterative partitioning. the importance of event logs, as a source of information in systems and network management cannot be overemphasized. with the ever increasing size and complexity of today's event logs, the task of analyzing event logs has become cumbersome to carry out manually. for this reason recent research has focused on the automatic analysis of these log files. in this paper we present iplom (iterative partitioning log mining), a novel algorithm for the mining of clusters from event logs. through a 3-step hierarchical partitioning process iplom partitions log data into its respective clusters. in its 4th and final stage iplom produces cluster descriptions or line formats for each of the clusters produced. unlike other similar algorithms iplom is not based on the apriori algorithm and it is able to find clusters in data whether or not its instances appear frequently. evaluations show that iplom outperforms the other algorithms statistically significantly, and it is also able to achieve an average f-measure performance 78% when the closest other algorithm achieves an f-measure performance of 10%.
dynammo: mining and summarization of coevolving sequences with missing values. given multiple time sequences with missing values, we propose dynammo which summarizes, compresses, and finds latent variables. the idea is to discover hidden variables and learn their dynamics, making our algorithm able to function even when there are missing values. we performed experiments on both real and synthetic datasets spanning several megabytes, including motion capture sequences and chlorine levels in drinking water. we show that our proposed dynammo method (a) can successfully learn the latent variables and their evolution; (b) can provide high compression for little loss of reconstruction accuracy; (c) can extract compact but powerful features for segmentation, interpretation, and forecasting; (d) has complexity linear on the duration of sequences.
incorporating site-level knowledge for incremental crawling of web forums: a list-wise strategy. we study in this paper the problem of incremental crawling of web forums, which is a very fundamental yet challenging step in many web applications. traditional approaches mainly focus on scheduling the revisiting strategy of each individual page. however, simply assigning different weights for different individual pages is usually inefficient in crawling forum sites because of the different characteristics between forum sites and general websites. instead of treating each individual page independently, we propose a list-wise strategy by taking into account the site-level knowledge. such site-level knowledge is mined through reconstructing the linking structure, called sitemap, for a given forum site. with the sitemap, posts from the same thread but distributed on various pages can be concatenated according to their timestamps. after that, for each thread, we employ a regression model to predict the time when the next post arrives. based on this model, we develop an efficient crawler which is 260% faster than some state-of-the-art methods in terms of fetching new generated content; and meanwhile our crawler also ensure a high coverage ratio. experimental results show promising performance of coverage, bandwidth utilization, and timeliness of our crawler on 18 various forums.
augmenting the generalized hough transform to enable the mining of petroglyphs. rock art is an archaeological term for human-made markings on stone. it is believed that there are millions of petroglyphs in north america alone, and the study of this valued cultural resource has implications even beyond anthropology and history. surprisingly, although image processing, information retrieval and data mining have had large impacts on many human endeavors, they have had essentially zero impact on the study of rock art. in this work we identify the reasons for this, and introduce a novel distance measure and algorithms which allow efficient and effective data mining of large collections of rock art.
adapting the right measures for k-means clustering. clustering validation is a long standing challenge in the clustering literature. while many validation measures have been developed for evaluating the performance of clustering algorithms, these measures often provide inconsistent information about the clustering performance and the best suitable measures to use in practice remain unknown. this paper thus fills this crucial void by giving an organized study of 16 external validation measures for k-means clustering. specifically, we first introduce the importance of measure normalization in the evaluation of the clustering performance on data with imbalanced class distributions. we also provide normalization solutions for several measures. in addition, we summarize the major properties of these external measures. these properties can serve as the guidance for the selection of validation measures in different application scenarios. finally, we reveal the interrelationships among these external measures. by mathematical transformation, we show that some validation measures are equivalent. also, some measures have consistent validation performances. most importantly, we provide a guide line to select the most suitable validation measures for k-means clustering.
feature shaping for linear svm classifiers. linear classifiers have been shown to be effective for many discrimination tasks. irrespective of the learning algorithm itself, the final classifier has a weight to multiply by each feature. this suggests that ideally each input feature should be linearly correlated with the target variable (or anti-correlated), whereas raw features may be highly non-linear. in this paper, we attempt to re-shape each input feature so that it is appropriate to use with a linear weight and to scale the different features in proportion to their predictive value. we demonstrate that this pre-processing is beneficial for linear svm classifiers on a large benchmark of text classification tasks as well as uci datasets.
mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation. effective diagnosis of alzheimer's disease (ad), the most common type of dementia in elderly patients, is of primary importance in biomedical research. recent studies have demonstrated that ad is closely related to the structure change of the brain network, i.e., the connectivity among different brain regions. the connectivity patterns will provide useful imaging-based biomarkers to distinguish normal controls (nc), patients with mild cognitive impairment (mci), and patients with ad. in this paper, we investigate the sparse inverse covariance estimation technique for identifying the connectivity among different brain regions. in particular, a novel algorithm based on the block coordinate descent approach is proposed for the direct estimation of the inverse covariance matrix. one appealing feature of the proposed algorithm is that it allows the user feedback (e.g., prior domain knowledge) to be incorporated into the estimation process, while the connectivity patterns can be discovered automatically. we apply the proposed algorithm to a collection of fdg-pet images from 232 nc, mci, and ad subjects. our experimental results demonstrate that the proposed algorithm is promising in revealing the brain region connectivity differences among these groups.
a multi-relational approach to spatial classification. spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their features. spatial data can be represented as multi-relational data, however it presents novel challenges not present in multi-relational problems. one such problem is that spatial relationships are embedded in space, unknown a priori, and it is part of the algorithm's task to determine which relationships are important and what properties to consider. in order to determine when two entities are spatially related in an adaptive and non-parametric way, we propose a voronoi-based neighbourhood definition upon which spatial literals can be built. properties of these neighbourhoods also need to be described and used for classification purposes. non-spatial aggregation literals already exist within the multi-relational framework, but are not sufficient for comprehensive spatial classification. a formal set of additions to the multi-relational data mining framework is proposed, to be able to represent spatial aggregations as well as spatial features and literals. these additions allow for capturing more complex interactions and spatial occurrences such as spatial trends. in order to more efficiently perform the rule learning and exploit powerful multi-processor machines, a scalable parallelized method capable of reducing the runtime by several factors is presented. the method is compared against existing methods by experimental evaluation on a real world crime dataset which demonstrate the importance of the neighbourhood definition and the advantages of parallelization.
data mining at nasa: from theory to applications. nasa has some of the largest and most complex data sources in the world, with data sources ranging from the earth sciences, space sciences, and massive distributed engineering data sets from commercial aircraft and spacecraft. this talk will discuss some of the issues and algorithms developed to analyze and discover patterns in these data sets. we will also provide an overview of a large research program in integrated vehicle health management. the goal of this program is to develop advanced technologies to automatically detect, diagnose, predict, and mitigate adverse events during the flight of an aircraft. a case study will be presented on a recent data mining analysis performed to support the flight readiness review of the space shuttle mission sts-119.
metafac: community discovery via relational hypergraph factorization. this paper aims at discovering community structure in rich media social networks, through analysis of time-varying, multi-relational data. community structure represents the latent social context of user actions. it has important applications in information tasks such as search and recommendation. social media has several unique challenges. (a) in social media, the context of user actions is constantly changing and co-evolving; hence the social context contains time-evolving multi-dimensional relations. (b) the social context is determined by the available system features and is unique in each social media website. in this paper we propose metafac (metagraph factorization), a framework that extracts community structures from various social contexts and interactions. our work has three key contributions: (1) metagraph, a novel relational hypergraph representation for modeling multi-relational and multi-dimensional social data; (2) an efficient factorization method for community extraction on a given metagraph; (3) an on-line method to handle time-varying relations through incremental metagraph factorization. extensive experiments on real-world social data collected from the digg social media website suggest that our technique is scalable and is able to extract meaningful communities based on the social media contexts. we illustrate the usefulness of our framework through prediction tasks. we outperform baseline methods (including aspect model and tensor analysis) by an order of magnitude.
regret-based online ranking for a growing digital library. the most common environment in which ranking is used takes a very specific form. users sequentially generate queries in a digital library. for each query, ranking is applied to order a set of relevant items from which the user selects his favorite. this is the case when ranking search results for pages on the world wide web or for merchandize on an e-commerce site. in this work, we present a new online ranking algorithm, called noregret klrank. our algorithm is designed to use "clickthrough" information as it is provided by the users to improve future ranking decisions. more importantly, we show that its long term average performance will converge to the best rate achievable by any competing fixed ranking policy selected with the benefit of hindsight. we show how to ensure that this property continues to hold as new items are added to the set thus requiring a richer class of ranking policies. finally, our empirical results show that, while in some context noregret klrank might be considered conservative, a greedy variant of this algorithm actually outperforms many popular ranking algorithms.
constant-factor approximation algorithms for identifying dynamic communities. we propose two approximation algorithms for identifying communities in dynamic social networks. communities are intuitively characterized as "unusually densely knit" subsets of a social network. this notion becomes more problematic if the social interactions change over time. aggregating social networks over time can radically misrepresent the existing and changing community structure. recently, we have proposed an optimization-based framework for modeling dynamic community structure. also, we have proposed an algorithm for finding such structure based on maximum weight bipartite matching. in this paper, we analyze its performance guarantee for a special case where all actors can be observed at all times. in such instances, we show that the algorithm is a small constant factor approximation of the optimum. we use a similar idea to design an approximation algorithm for the general case where some individuals are possibly unobserved at times, and to show that the approximation factor increases twofold but remains a constant regardless of the input size. this is the first algorithm for inferring communities in dynamic networks with a provable approximation guarantee. we demonstrate the general algorithm on real data sets. the results confirm the efficiency and effectiveness of the algorithm in identifying dynamic communities.
on burstiness-aware search for document sequences. as the number and size of large timestamped collections (e.g. sequences of digitized newspapers, periodicals, blogs) increase, the problem of efficiently indexing and searching such data becomes more important. term burstiness has been extensively researched as a mechanism to address event detection in the context of such collections. in this paper, we explore how burstiness information can be further utilized to enhance the search process. we present a novel approach to model the burstiness of a term, using discrepancy theory concepts. this allows us to build a parameter-free, linear-time approach to identify the time intervals of maximum burstiness for a given term. finally, we describe the first burstiness-driven search framework and thoroughly evaluate our approach in the context of different scenarios.
learning dynamic temporal graphs for oil-production equipment monitoring system. learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. most previous work focuses on learning and predicting with "static" temporal graphs only. however, in many applications such as mechanical systems and biology systems, the temporal dependencies might change over time. in this paper, we develop a dynamic temporal graphical models based on hidden markov model regression and lasso-type algorithms. our method is able to integrate two usually separate tasks, i.e. inferring underlying states and learning temporal graphs, in one unified model. the output temporal graphs provide better understanding about complex systems, i.e. how their dependency graphs evolve over time, and achieve more accurate predictions. we examine our model on two synthetic datasets as well as a real application dataset for monitoring oil-production equipment to capture different stages of the system, and achieve promising results.
social influence analysis in large-scale networks. in large social networks, nodes (users, entities) are influenced by others for various reasons. for example, the colleagues have strong influence on one's work, while the friends have strong influence on one's daily life. how to differentiate the social influences from different angles(topics)? how to quantify the strength of those social influences? how to estimate the model on real large networks? to address these fundamental questions, we propose topical affinity propagation (tap) to model the topic-level social influence on large networks. in particular, tap can take results of any topic modeling and the existing network structure to perform topic-level influence propagation. with the help of the influence analysis, we present several important applications on real data sets such as 1) what are the representative nodes on a given topic? 2) how to identify the social influences of neighboring nodes on a particular node? to scale to real large networks, tap is designed with efficient distributed learning algorithms that is implemented and tested under the map-reduce framework. we further present the common characteristics of distributed learning algorithms for map-reduce. finally, we demonstrate the effectiveness and efficiency of tap on real large data sets.
collaborative filtering with temporal dynamics. customer preferences for products are drifting over time. product perception and popularity are constantly changing as new selection emerges. similarly, customer inclinations are evolving, leading them to ever redefine their taste. thus, modeling temporal dynamics is essential for designing recommender systems or general customer preference models. however, this raises unique challenges. within the ecosystem intersecting multiple products and customers, many different characteristics are shifting simultaneously, while many of them influence each other and often those shifts are delicate and associated with a few data instances. this distinguishes the problem from concept drift explorations, where mostly a single concept is tracked. classical time-window or instance decay approaches cannot work, as they lose too many signals when discarding data instances. a more sensitive approach is required, which can make better distinctions between transient effects and long-term patterns. we show how to model the time changing behavior throughout the life span of the data. such a model allows us to exploit the relevant components of all data instances, while discarding only what is modeled as being irrelevant. accordingly, we revamp two leading collaborative filtering recommendation approaches. evaluation is made on a large movie-rating dataset underlying the netflix prize contest. results are encouraging and better than those previously reported on this dataset. in particular, methods described in this paper play a significant role in the solution that won the netflix contest.
bbm: bayesian browsing model from petabyte-scale data. given a quarter of petabyte click log data, how can we estimate the relevance of each url for a given query? in this paper, we propose the bayesian browsing model (bbm), a new modeling technique with following advantages: (a) it does exact inference; (b) it is single-pass and parallelizable; (c) it is effective. we present two sets of experiments to test model effectiveness and efficiency. on the first set of over 50 million search instances of 1.1 million distinct queries, bbm out-performs the state-of-the-art competitor by 29.2% in log-likelihood while being 57 times faster. on the second click-log set, spanning a quarter of petabyte data, we showcase the scalability of bbm: we implemented it on a commercial mapreduce cluster, and it took only 3 hours to compute the relevance for 1.15 billion distinct query-url pairs.
address standardization with latent semantic association. address standardization is a very challenging task in data cleansing. to provide better customer relationship management and business intelligence for customer-oriented cooperates, millions of free-text addresses need to be converted to a standard format for data integration, de-duplication and householding. existing commercial tools usually employ lots of hand-craft, domain-specific rules and reference data dictionary of cities, states etc. these rules work better for the region they are designed. however, rule-based methods usually require more human efforts to rewrite these rules for each new domain since address data are very irregular and varied with countries and regions. supervised learning methods usually are more adaptable than rule-based approaches. however, supervised methods need large-scale labeled training data. it is a labor-intensive and time-consuming task to build a large-scale annotated corpus for each target domain. for minimizing human efforts and the size of labeled training data set, we present a free-text address standardization method with latent semantic association (lasa). lasa model is constructed to capture latent semantic association among words from the unlabeled corpus. the original term space of the target domain is projected to a concept space using lasa model at first, then the address standardization model is active learned from lasa features and informative samples. the proposed method effectively captures the data distribution of the domain. experimental results on large-scale english and chinese corpus show that the proposed method significantly enhances the performance of standardization with less efforts and training data.
an association analysis approach to biclustering. the discovery of biclusters, which denote groups of items that show coherent values across a subset of all the transactions in a data set, is an important type of analysis performed on real-valued data sets in various domains, such as biology. several algorithms have been proposed to find different types of biclusters in such data sets. however, these algorithms are unable to search the space of all possible biclusters exhaustively. pattern mining algorithms in association analysis also essentially produce biclusters as their result, since the patterns consist of items that are supported by a subset of all the transactions. however, a major limitation of the numerous techniques developed in association analysis is that they are only able to analyze data sets with binary and/or categorical variables, and their application to real-valued data sets often involves some lossy transformation such as discretization or binarization of the attributes. in this paper, we propose a novel association analysis framework for exhaustively and efficiently mining "range support" patterns from such a data set. on one hand, this framework reduces the loss of information incurred by the binarization- and discretization-based approaches, and on the other, it enables the exhaustive discovery of coherent biclusters. we compared the performance of our framework with two standard biclustering algorithms through the evaluation of the similarity of the cellular functions of the genes constituting the patterns/biclusters derived by these algorithms from microarray data. these experiments show that the real-valued patterns discovered by our framework are better enriched by small biologically interesting functional classes. also, through specific examples, we demonstrate the ability of the rap framework to discover functionally enriched patterns that are not found by the commonly used biclustering algorithm isa. the source code and data sets used in this paper, as well as the supplementary material, are available at http://www.cs.umn.edu/vk/gaurav/rap.
randomization methods in data mining. data mining research has developed many algorithms for various analysis tasks on large and complex datasets. however, assessing the significance of data mining results has received less attention. analytical methods are rarely available, and hence one has to use computationally intensive methods. randomization approaches based on null models provide, at least in principle, a general approach that can be used to obtain empirical p-values for various types of data mining approaches. i review some of the recent work in this area, outlining some of the open questions and problems.
probabilistic frequent itemset mining in uncertain databases. probabilistic frequent itemset mining in uncertain transaction databases semantically and computationally differs from traditional techniques applied to standard "certain" transaction databases. the consideration of existential uncertainty of item(sets), indicating the probability that an item(set) occurs in a transaction, makes traditional techniques inapplicable. in this paper, we introduce new probabilistic formulations of frequent itemsets based on possible world semantics. in this probabilistic context, an itemset x is called frequent if the probability that x occurs in at least minsup transactions is above a given threshold τ. to the best of our knowledge, this is the first approach addressing this problem under possible worlds semantics. in consideration of the probabilistic formulations, we present a framework which is able to solve the probabilistic frequent itemset mining (pfim) problem efficiently. an extensive experimental evaluation investigates the impact of our proposed techniques and shows that our approach is orders of magnitude faster than straight-forward approaches.
efficient methods for topic model inference on streaming document collections. topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. fitting a topic model given a set of training documents requires approximate inference techniques that are computationally expensive. with today's large-scale, constantly expanding document collections, it is useful to be able to infer topic distributions for new documents without retraining the model. in this paper, we empirically evaluate the performance of several methods for topic inference in previously unseen documents, including methods based on gibbs sampling, variational inference, and a new method inspired by text classification. the classification-based inference method produces results similar to iterative inference methods, but requires only a single matrix multiplication. in addition to these inference methods, we present sparselda, an algorithm and data structure for evaluating gibbs sampling distributions. empirical results indicate that sparselda can be approximately 20 times faster than traditional lda and provide twice the speedup of previously published fast sampling methods, while also using substantially less memory.
ranking-based clustering of heterogeneous information networks with star network schema. a heterogeneous information network is an information network composed of multiple types of objects. clustering on such a network may lead to better understanding of both hidden structures of the network and the individual role played by every object in each cluster. however, although clustering on homogeneous networks has been studied over decades, clustering on heterogeneous networks has not been addressed until recently. a recent study proposed a new algorithm, rankclus, for clustering on bi-typed heterogeneous networks. however, a real-world network may consist of more than two types, and the interactions among multi-typed objects play a key role at disclosing the rich semantics that a network carries. in this paper, we study clustering of multi-typed heterogeneous networks with a star network schema and propose a novel algorithm, netclus, that utilizes links across multityped objects to generate high-quality net-clusters. an iterative enhancement method is developed that leads to effective ranking-based clustering in such heterogeneous networks. our experiments on dblp data show that netclus generates more accurate clustering results than the baseline topic model algorithm plsa and the recently proposed algorithm, rankclus. further, netclus generates informative clusters, presenting good ranking and cluster membership information for each attribute object in each net-cluster.
named entity mining from click-through data using weakly supervised latent dirichlet allocation. this paper addresses named entity mining (nem), in which we mine knowledge about named entities such as movies, games, and books from a huge amount of data. nem is potentially useful in many applications including web search, online advertisement, and recommender system. there are three challenges for the task: finding suitable data source, coping with the ambiguities of named entity classes, and incorporating necessary human supervision into the mining process. this paper proposes conducting nem by using click-through data collected at a web search engine, employing a topic model that generates the click-through data, and learning the topic model by weak supervision from humans. specifically, it characterizes each named entity by its associated queries and urls in the click-through data. it uses the topic model to resolve ambiguities of named entity classes by representing the classes as topics. it employs a method, referred to as weakly supervised latent dirichlet allocation (ws-lda), to accurately learn the topic model with partially labeled named entities. experiments on a large scale click-through data containing over 1.5 billion query-url pairs show that the proposed approach can conduct very accurate nem and significantly outperforms the baseline.
new ensemble methods for evolving data streams. advanced analysis of data streams is quickly becoming a key area of data mining research as the number of applications demanding such processing increases. online mining when such data streams evolve over time, that is when concepts drift or change completely, is becoming one of the core issues. when tackling non-stationary concepts, ensembles of classifiers have several advantages over single classifier methods: they are easy to scale and parallelize, they can adapt to change quickly by pruning under-performing parts of the ensemble, and they therefore usually also generate more accurate concept descriptions. this paper proposes a new experimental data stream framework for studying concept drift, and two new variants of bagging: adwin bagging and adaptive-size hoeffding tree (asht) bagging. using the new experimental framework, an evaluation study on synthetic and real-world datasets comprising up to ten million examples shows that the new ensemble methods perform very well compared to several known methods.
modeling and predicting user behavior in sponsored search. implicit user feedback, including click-through and subsequent browsing behavior, is crucial for evaluating and improving the quality of results returned by search engines. several recent studies [1, 2, 3, 13, 25] have used post-result browsing behavior including the sites visited, the number of clicks, and the dwell time on site in order to improve the ranking of search results. in this paper, we first study user behavior on sponsored search results (i.e., the advertisements displayed by search engines next to the organic results), and compare this behavior to that of organic results. second, to exploit post-result user behavior for better ranking of sponsored results, we focus on identifying patterns in user behavior and predict expected on-site actions in future instances. in particular, we show how post-result behavior depends on various properties of the queries, advertisement, sites, and users, and build a classifier using properties such as these to predict certain aspects of the user behavior. additionally, we develop a generative model to mimic trends in observed user activity using a mixture of pareto distributions. we conduct experiments based on billions of real navigation trails collected by a major search engine's browser toolbar.
mining for the most certain predictions from dyadic data. in several applications involving regression or classification, along with making predictions it is important to assess how accurate or reliable individual predictions are. this is particularly important in cases where due to finite resources or domain requirements, one wants to make decisions based only on the most reliable rather than on the entire set of predictions. this paper introduces novel and effective ways of ranking predictions by their accuracy for problems involving large-scale, heterogeneous data with a dyadic structure, i.e., where the independent variables can be naturally decomposed into three groups associated with two sets of elements and their combination. these approaches are based on modeling the data by a collection of localized models learnt while simultaneously partitioning (co-clustering) the data. for regression this leads to the concept of "certainty lift". we also develop a robust predictive modeling technique that identifies and models only the most coherent regions of the data to give high predictive accuracy on the selected subset of response values. extensive experimentation on real life datasets highlights the utility of our proposed approaches.
catching the drift: learning broad matches from clickthrough data. identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. effective broad matching leads to improvements in both relevance and monetization, while increasing advertisers' reach and making campaign management easier. in this paper, we present a learning-based approach to broad matching that is based on exploiting implicit feedback in the form of advertisement clickthrough logs. our method can utilize arbitrary similarity functions by incorporating them as features. we present an online learning algorithm, amnesiac averaged perceptron, that is highly efficient yet able to quickly adjust to the rapidly-changing distributions of bidded keywords, advertisements and user behavior. experimental results obtained from (1) historical logs and (2) live trials on a large-scale advertising platform demonstrate the effectiveness of the proposed algorithm and the overall success of our approach in identifying high-quality broad match mappings.
efficient influence maximization in social networks. influence maximization is the problem of finding a small subset of nodes (seed nodes) in a social network that could maximize the spread of influence. in this paper, we study the efficient influence maximization from two complementary directions. one is to improve the original greedy algorithm of [5] and its improvement [7] to further reduce its running time, and the second is to propose new degree discount heuristics that improves influence spread. we evaluate our algorithms by experiments on two large academic collaboration graphs obtained from the online archival database arxiv.org. our experimental results show that (a) our improved greedy algorithm achieves better running time comparing with the improvement of [7] with matching influence spread, (b) our degree discount heuristics achieve much better influence spread than classic degree and centrality-based heuristics, and when tuned for a specific influence cascade model, it achieves almost matching influence thread with the greedy algorithm, and more importantly (c) the degree discount heuristics run only in milliseconds while even the improved greedy algorithms run in hours in our experiment graphs with a few tens of thousands of nodes. based on our results, we believe that fine-tuned heuristics may provide truly scalable solutions to the influence maximization problem with satisfying influence spread and blazingly fast running time. therefore, contrary to what implied by the conclusion of [5] that traditional heuristics are outperformed by the greedy approximation algorithm, our results shed new lights on the research of heuristic algorithms.
towards efficient mining of proportional fault-tolerant frequent itemsets. fault-tolerant frequent itemsets (ftfi) are variants of frequent itemsets for representing and discovering generalized knowledge. however, despite growing interest in this field, no previous approach mines proportional ftfis with their exact support (ft-support). this problem is difficult because of two concerns: (a) non anti-monotonic property of ft-support when relaxation is proportional, and (b) difficulty in computing ft-support. previous efforts on this problem either simplify the general problem by adding constraints, or provide approximate solutions without any error guarantees. in this paper, we address these concerns in the general ftfi mining problem. we limit the search space by providing provably correct anti monotone bounds for ft-support and develop practically efficient means of achieving them. besides, we also provide an efficient and exact ft-support counting procedure. extensive experiments using real datasets validate that our solution is reasonably efficient for completely mining ftfis. implementations for the algorithms are available from www.cais.ntu.edu.sg/~vivek/pubs/ftfim09.
regression-based latent factor models. we propose a novel latent factor model to accurately predict response for large scale dyadic data in the presence of features. our approach is based on a model that predicts response as a multiplicative function of row and column latent factors that are estimated through separate regressions on known row and column features. in fact, our model provides a single unified framework to address both cold and warm start scenarios that are commonplace in practical applications like recommender systems, online advertising, web search, etc. we provide scalable and accurate model fitting methods based on iterated conditional mode and monte carlo em algorithms. we show our model induces a stochastic process on the dyadic space with kernel (covariance) given by a polynomial function of features. methods that generalize our procedure to estimate factors in an online fashion for dynamic applications are also considered. our method is illustrated on benchmark datasets and a novel content recommendation application that arises in the context of yahoo! front page. we report significant improvements over several commonly used methods on all datasets.
classification of software behaviors for failure detection: a discriminative pattern mining approach. software is a ubiquitous component of our daily life. we often depend on the correct working of software systems. due to the difficulty and complexity of software systems, bugs and anomalies are prevalent. bugs have caused billions of dollars loss, in addition to privacy and security threats. in this work, we address software reliability issues by proposing a novel method to classify software behaviors based on past history or runs. with the technique, it is possible to generalize past known errors and mistakes to capture failures and anomalies. our technique first mines a set of discriminative features capturing repetitive series of events from program execution traces. it then performs feature selection to select the best features for classification. these features are then used to train a classifier to detect failures. experiments and case studies on traces of several benchmark software systems and a real-life concurrency bug from mysql server show the utility of the technique in capturing failures and anomalies. on average, our pattern-based classification technique outperforms the baseline approach by 24.68% in accuracy.
mining rich session context to improve web search. user browsing information, particularly their non-search related activity, reveals important contextual information on the preferences and the intent of web users. in this paper, we expand the use of browsing information for web search ranking and other applications, with an emphasis on analyzing individual user sessions for creating aggregate models. in this context, we introduce clickrank, an efficient, scalable algorithm for estimating web page and web site importance from browsing information. we lay out the theoretical foundation of clickrank based on an intentional surfer model and analyze its properties. we evaluate its effectiveness for the problem of web search ranking, showing that it contributes significantly to retrieval performance as a novel web search feature. we demonstrate that the results produced by clickrank for web search ranking are highly competitive with those produced by other approaches, yet achieved at better scalability and substantially lower computational costs. finally, we discuss novel applications of clickrank in providing enriched user web search experience, highlighting the usefulness of our approach for non-ranking tasks.
can we learn a template-independent wrapper for news article extraction from a single training site? automatic news extraction from news pages is important in many web applications such as news aggregation. however, the existing news extraction methods based on template-level wrapper induction have three serious limitations. first, the existing methods cannot correctly extract pages belonging to an unseen template. second, it is costly to maintain up-to-date wrappers for a large amount of news websites, because any change of a template may invalidate the corresponding wrapper. last, the existing methods can merely extract unformatted plain texts, and thus are not user friendly. in this paper, we tackle the problem of template-independent web news extraction in a user-friendly way. we formalize web news extraction as a machine learning problem and learn a template-independent wrapper using a very small number of labeled news pages from a single site. novel features dedicated to news titles and bodies are developed. correlations between news titles and news bodies are exploited. our template-independent wrapper can extract news pages from different sites regardless of templates. moreover, our approach can extract not only texts, but also images and animates within the news bodies and the extracted news articles are in the same visual style as in the original pages. in our experiments, a wrapper learned from 40 pages from a single news site achieved an accuracy of 98.1% on 3,973 news pages from 12 news sites.
exploiting wikipedia as external knowledge for document clustering. in traditional text clustering methods, documents are represented as "bags of words" without considering the semantic information of each document. for instance, if two documents use different collections of core words to represent the same topic, they may be falsely assigned to different clusters due to the lack of shared core words, although the core words they use are probably synonyms or semantically associated in other forms. the most common way to solve this problem is to enrich document representation with the background knowledge in an ontology. there are two major issues for this approach: (1) the coverage of the ontology is limited, even for wordnet or mesh, (2) using ontology terms as replacement or additional features may cause information loss, or introduce noise. in this paper, we present a novel text clustering method to address these two issues by enriching document representation with wikipedia concept and category information. we develop two approaches, exact match and relatedness-match, to map text documents to wikipedia concepts, and further to wikipedia categories. then the text documents are clustered based on a similarity metric which combines document content information, concept information as well as category information. the experimental results using the proposed clustering framework on three datasets (20-newsgroup, tdt2, and la times) show that clustering performance improves significantly by enriching document representation with wikipedia concepts and categories.
primal sparse max-margin markov networks. max-margin markov networks (m3n) have shown great promise in structured prediction and relational learning. due to the kkt conditions, the m3n enjoys dual sparsity. however, the existing m3n formulation does not enjoy primal sparsity, which is a desirable property for selecting significant features and reducing the risk of over-fitting. in this paper, we present an l1-norm regularized max-margin markov network (l1-m3n), which enjoys dual and primal sparsity simultaneously. to learn an l1-m3n, we present three methods including projected sub-gradient, cutting-plane, and a novel em-style algorithm, which is based on an equivalence between l1-m3n and an adaptive m3n. we perform extensive empirical studies on both synthetic and real data sets. our experimental results show that: (1) l1-m3n can effectively select significant features; (2) l1-m3n can perform as well as the pseudo-primal sparse laplace m3n in prediction accuracy, while consistently outperforms other competing methods that enjoy either primal or dual sparsity; and (3) the em-algorithm is more robust than the other two in pre-diction accuracy and time efficiency.
spatial-temporal causal modeling for climate change attribution. attribution of climate change to causal factors has been based predominantly on simulations using physical climate models, which have inherent limitations in describing such a complex and chaotic system. we propose an alternative, data centric, approach that relies on actual measurements of climate observations and human and natural forcing factors. specifically, we develop a novel method to infer causality from spatial-temporal data, as well as a procedure to incorporate extreme value modeling into our method in order to address the attribution of extreme climate events, such as heatwaves. our experimental results on a real world dataset indicate that changes in temperature are not solely accounted for by solar radiance, but attributed more significantly to co2 and other greenhouse gases. combined with extreme value modeling, we also show that there has been a significant increase in the intensity of extreme temperatures, and that such changes in extreme temperature are also attributable to greenhouse gases. these preliminary results suggest that our approach can offer a useful alternative to the simulation-based approach to climate modeling and attribution, and provide valuable insights from a fresh perspective.
fast approximate spectral clustering. spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-scale problems due to its computational complexity of o(n3) in general, with n the number of data points. we extend the range of spectral clustering by developing a general framework for fast approximate spectral clustering in which a distortion-minimizing local transformation is first applied to the data. this framework is based on a theoretical analysis that provides a statistical characterization of the effect of local distortion on the mis-clustering rate. we develop two concrete instances of our general framework, one based on local k-means clustering (kasp) and one based on random projection trees (rasp). extensive experiments show that these algorithms can achieve significant speedups with little degradation in clustering accuracy. specifically, our algorithms outperform k-means by a large margin in terms of accuracy, and run several times faster than approximate spectral clustering based on the nystrom method, with comparable accuracy and significantly smaller memory footprint. remarkably, our algorithms make it possible for a single machine to spectral cluster data sets with a million observations within several minutes.
extracting discriminative concepts for domain adaptation in text mining. one common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributions. this poses a great difficulty for many statistical learning methods. however, when the distribution in the source domain and the target domain are not identical but related, there may exist a shared concept space to preserve the relation. consequently a good feature representation can encode this concept space and minimize the distribution gap. to formalize this intuition, we propose a domain adaptation method that parameterizes this concept space by linear transformation under which we explicitly minimize the distribution difference between the source domain with sufficient labeled data and target domains with only unlabeled data, while at the same time minimizing the empirical loss on the labeled data in the source domain. another characteristic of our method is its capability for considering multiple classes and their interactions simultaneously. we have conducted extensive experiments on two common text mining problems, namely, information extraction and document classification to demonstrate the effectiveness of our proposed method.
a generalized co-hits algorithm and its application to bipartite graphs. recently many data types arising from data mining and web search applications can be modeled as bipartite graphs. examples include queries and urls in query logs, and authors and papers in scientific literature. however, one of the issues is that previous algorithms only consider the content and link information from one side of the bipartite graph. there is a lack of constraints to make sure the final relevance of the score propagation on the graph, as there are many noisy edges within the bipartite graph. in this paper, we propose a novel and general co-hits algorithm to incorporate the bipartite graph with the content information from both sides as well as the constraints of relevance. moreover, we investigate the algorithm based on two frameworks, including the iterative and the regularization frameworks, and illustrate the generalized co-hits algorithm from different views. for the iterative framework, it contains hits and personalized pagerank as special cases. in the regularization framework, we successfully build a connection with hits, and develop a new cost function to consider the direct relationship between two entity sets, which leads to a significant improvement over the baseline method. to illustrate our methodology, we apply the co-hits algorithm, with many different settings, to the application of query suggestion by mining the aol query log data. experimental results demonstrate that coregu-0.5 (i.e., a model of the regularization framework) achieves the best performance with consistent and promising improvements.
connections between the lines: augmenting social networks with text. network data is ubiquitous, encoding collections of relationships between entities such as people, places, genes, or corporations. while many resources for networks of interesting entities are emerging, most of these can only annotate connections in a limited fashion. although relationships between entities are rich, it is impractical to manually devise complete characterizations of these relationships for every pair of entities on large, real-world corpora. in this paper we present a novel probabilistic topic model to analyze text corpora and infer descriptions of its entities and of relationships between those entities. we develop variational methods for performing approximate inference on our model and demonstrate that our model can be practically deployed on large corpora such as wikipedia. we show qualitatively and quantitatively that our model can construct and annotate graphs of relationships and make useful predictions.
snare: a link analytic system for graph labeling and risk detection. classifying nodes in networks is a task with a wide range of applications. it can be particularly useful in anomaly and fraud detection. many resources are invested in the task of fraud detection due to the high cost of fraud, and being able to automatically detect potential fraud quickly and precisely allows human investigators to work more efficiently. many data analytic schemes have been put into use; however, schemes that bolster link analysis prove promising. this work builds upon the belief propagation algorithm for use in detecting collusion and other fraud schemes. we propose an algorithm called snare (social network analysis for risk evaluation). by allowing one to use domain knowledge as well as link knowledge, the method was very successful for pinpointing misstated accounts in our sample of general ledger data, with a significant improvement over the default heuristic in true positive rates, and a lift factor of up to 6.5 (more than twice that of the default heuristic). we also apply snare to the task of graph labeling in general on publicly-available datasets. we show that with only some information about the nodes themselves in a network, we get surprisingly high accuracy of labels. not only is snare applicable in a wide variety of domains, but it is also robust to the choice of parameters and highly scalable-linearly with the number of edges in a graph.
correlated itemset mining in roc space: a constraint programming approach. correlated or discriminative pattern mining is concerned with finding the highest scoring patterns w.r.t. a correlation measure (such as information gain). by reinterpreting correlation measures in roc space and formulating correlated itemset mining as a constraint programming problem, we obtain new theoretical insights with practical benefits. more specifically, we contribute 1) an improved bound for correlated itemset miners, 2) a novel iterative pruning algorithm to exploit the bound, and 3) an adaptation of this algorithm to mine all itemsets on the convex hull in roc space. the algorithm does not depend on a minimal frequency threshold and is shown to outperform several alternative approaches by orders of magnitude, both in runtime and in memory requirements.
sustainable operation and management of data center chillers using temporal data mining. motivation: data centers are a critical component of modern it infrastructure but are also among the worst environmental offenders through their increasing energy usage and the resulting large carbon footprints. efficient management of data centers, including power management, networking, and cooling infrastructure, is hence crucial to sustainability. in the absence of a 'first-principles' approach to manage these complex components and their interactions, data-driven approaches have become attractive and tenable. results: we present a temporal data mining solution to model and optimize performance of data center chillers, a key component of the cooling infrastructure. it helps bridge raw, numeric, time-series information from sensor streams toward higher level characterizations of chiller behavior, suitable for a data center engineer. to aid in this transduction, temporal data streams are first encoded into a symbolic representation, next run-length encoded segments are mined to form frequent motifs in time series, and finally these metrics are evaluated by their contributions to sustainability. a key innovation in our application is the ability to intersperse "don't care" transitions (e.g., transients) in continuous-valued time series data, an advantage we inherit by the application of frequent episode mining to symbolized representations of numeric time series. our approach provides both qualitative and quantitative characterizations of the sensor streams to the data center engineer, to aid him in tuning chiller operating characteristics. this system is currently being prototyped for a data center managed by hp and experimental results from this application reveal the promise of our approach.
anomalous window discovery through scan statistics for linear intersecting paths (sslip). anomalous windows are the contiguous groupings of data points. in this paper, we propose an approach for discovering anomalous windows using scan statistics for linear intersecting paths (sslip). a linear path refers to a path represented by a line with a single dimensional spatial coordinate marking an observation point. our approach for discovering anomalous windows along linear paths comprises of the following distinct steps: (a) cross path discovery: where we identify a subset of intersecting paths to be considered, (b) anomalous window discovery: where we outline three order invariant algorithms, namely sslip, brute force-sslip and central brute force-sslip, for the traversal of the cross paths to identify varying size directional windows along the paths. for identifying an anomalous window we compute an unusualness metric, in the form of a likelihood ratio to indicate the degree of unusualness of this window with respect to the rest of the data. we identify the window with the highest likelihood ratio as our anomalous window, and (c) monte carlo simulations: to ascertain whether this window is truly anomalous and not just a random occurrence we perform hypothesis testing by computing a p-value using monte carlo simulations. we present extensive experimental results in real world accident datasets for various highways with known issues(code and data available from [27], [21]). our results show that our approach indeed is effective in identifying anomalous traffic accident windows along multiple intersecting highways.
user grouping behavior in online forums. online forums represent one type of social media that is particularly rich for studying human behavior in information seeking and diffusing. the way users join communities is a reflection of the changing and expanding of their interests toward information. in this paper, we study the patterns of user participation behavior, and the feature factors that influence such behavior on different forum datasets. we find that, despite the relative randomness and lesser commitment of structural relationships in online forums, users' community joining behaviors display some strong regularities. one particularly interesting observation is that the very weak relationships between users defined by online replies have similar diffusion curves as those of real friendships or co-authorships. we build social selection models, bipartite markov random field (bimrf), to quantitatively evaluate the prediction performance of those feature factors and their relationships. using these models, we show that some features carry supplementary information, and the effectiveness of different features vary in different types of forums. moreover, the results of bimrf with two-star configurations suggest that the feature of user similarity defined by frequency of communication or number of common friends is inadequate to predict grouping behavior, but adding node-level features can improve the fit of the model.
information theoretic regularization for semi-supervised boosting. we present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labeled and unlabeled training data. our approach is based on extending information regularization framework to boosting, bearing loss functions that combine log loss on labeled data with the information-theoretic measures to encode unlabeled data. even though the information-theoretic regularization terms make the optimization non-convex, we propose simple sequential gradient descent optimization algorithms, and obtain impressively improved results on synthetic, benchmark and real world tasks over supervised boosting algorithms which use the labeled data alone and a state-of-the-art semi-supervised boosting algorithm.
sentiment analysis of blogs by combining lexical knowledge with text classification. the explosion of user-generated content on the web has led to new opportunities and significant challenges for companies, that are increasingly concerned about monitoring the discussion around their products. tracking such discussion on weblogs, provides useful insight on how to improve products or market them more effectively. an important component of such analysis is to characterize the sentiment expressed in blogs about specific brands and products. sentiment analysis focuses on this task of automatically identifying whether a piece of text expresses a positive or negative opinion about the subject matter. most previous work in this area uses prior lexical knowledge in terms of the sentiment-polarity of words. in contrast, some recent approaches treat the task as a text classification problem, where they learn to classify sentiment based only on labeled training data. in this paper, we present a unified framework in which one can use background lexical information in terms of word-class associations, and refine this information for specific domains using any available training examples. empirical results on diverse domains show that our approach performs better than using background knowledge or training data in isolation, as well as alternative approaches to using lexical knowledge with text classification.
differentially private recommender systems: building privacy into the netflix prize contenders. we consider the problem of producing recommendations from collective user behavior while simultaneously providing guarantees of privacy for these users. specifically, we consider the netflix prize data set, and its leading algorithms, adapted to the framework of differential privacy. unlike prior privacy work concerned with cryptographically securing the computation of recommendations, differential privacy constrains a computation in a way that precludes any inference about the underlying records from its output. such algorithms necessarily introduce uncertainty--i.e., noise--to computations, trading accuracy for privacy. we find that several of the leading approaches in the netflix prize competition can be adapted to provide differential privacy, without significantly degrading their accuracy. to adapt these algorithms, we explicitly factor them into two parts, an aggregation/learning phase that can be performed with differential privacy guarantees, and an individual recommendation phase that uses the learned correlations and an individual's data to provide personalized recommendations. the adaptations are non-trivial, and involve both careful analysis of the per-record sensitivity of the algorithms to calibrate noise, as well as new post-processing steps to mitigate the impact of this noise. we measure the empirical trade-off between accuracy and privacy in these adaptations, and find that we can provide non-trivial formal privacy guarantees while still outperforming the cinematch baseline netflix provides.
intelligent file scoring system for malware detection from the gray list. currently, the most significant line of defense against malware is anti-virus products which focus on authenticating valid software from a white list, blocking invalid software from a black list, and running any unknown software (i.e., the gray list) in a controlled manner. the gray list, containing unknown software programs which could be either normal or malicious, is usually authenticated or rejected manually by virus analysts. unfortunately, along with the development of the malware writing techniques, the number of file samples in the gray list that need to be analyzed by virus analysts on a daily basis is constantly increasing. in this paper, we develop an intelligent file scoring system (ifss for short) for malware detection from the gray list by an ensemble of heterogeneous base-level classifiers derived by different learning methods, using different feature representations on dynamic training sets. to the best of our knowledge, this is the first work of applying such ensemble methods for malware detection. ifss makes it practical for virus analysts to identify malware samples from the huge gray list and improves the detection ability of anti-virus software. it has already been incorporated into the scanning tool of kingsoft's anti-virus software. the case studies on large and real daily collection of the gray list illustrate that the detection ability and efficiency of our ifss system outperforms other popular scanning tools such as nod32 and kaspersky.
: a random walk model for combining trust-based and item-based recommendation. collaborative filtering is the most popular approach to build recommender systems and has been successfully employed in many applications. however, it cannot make recommendations for so-called cold start users that have rated only a very small number of items. in addition, these methods do not know how confident they are in their recommendations. trust-based recommendation methods assume the additional knowledge of a trust network among users and can better deal with cold start users, since users only need to be simply connected to the trust network. on the other hand, the sparsity of the user item ratings forces the trust-based approach to consider ratings of indirect neighbors that are only weakly trusted, which may decrease its precision. in order to find a good trade-off, we propose a random walk model combining the trust-based and the collaborative filtering approach for recommendation. the random walk model allows us to define and to measure the confidence of a recommendation. we performed an evaluation on the epinions dataset and compared our model with existing trust-based and collaborative filtering methods.
improving data mining utility with projective sampling. overall performance of the data mining process depends not just on the value of the induced knowledge but also on various costs of the process itself such as the cost of acquiring and pre-processing training examples, the cpu cost of model induction, and the cost of committed errors. recently, several progressive sampling strategies for maximizing the overall data mining utility have been proposed. all these strategies are based on repeated acquisitions of additional training examples until a utility decrease is observed. in this paper, we present an alternative, projective sampling strategy, which fits functions to a partial learning curve and a partial run-time curve obtained from a small subset of potentially available data and then uses these projected functions to analytically estimate the optimal training set size. the proposed approach is evaluated on a variety of benchmark datasets using the rapidminer environment for machine learning and data mining processes. the results show that the learning and run-time curves projected from only several data points can lead to a cheaper data mining process than the common progressive sampling methods.
entity discovery and assignment for opinion mining applications. opinion mining became an important topic of study in recent years due to its wide range of applications. there are also many companies offering opinion mining services. one problem that has not been studied so far is the assignment of entities that have been talked about in each sentence. let us use forum discussions about products as an example to make the problem concrete. in a typical discussion post, the author may give opinions on multiple products and also compare them. the issue is how to detect what products have been talked about in each sentence. if the sentence contains the product names, they need to be identified. we call this problem entity discovery. if the product names are not explicitly mentioned in the sentence but are implied due to the use of pronouns and language conventions, we need to infer the products. we call this problem entity assignment. these problems are important because without knowing what products each sentence talks about the opinion mined from the sentence is of little use. in this paper, we study these problems and propose two effective methods to solve the problems. entity discovery is based on pattern discovery and entity assignment is based on mining of comparative sentences. experimental results using a large number of forum posts demonstrate the effectiveness of the technique. our system has also been successfully tested in a commercial setting.
applying syntactic similarity algorithms for enterprise information management. for implementing content management solutions and enabling new applications associated with data retention, regulatory compliance, and litigation issues, enterprises need to develop advanced analytics to uncover relationships among the documents, e.g., content similarity, provenance, and clustering. in this paper, we evaluate the performance of four syntactic similarity algorithms. three algorithms are based on broder's "shingling" technique while the fourth algorithm employs a more recent approach, "content-based chunking". for our experiments, we use a specially designed corpus of documents that includes a set of "similar" documents with a controlled number of modifications. our performance study reveals that the similarity metric of all four algorithms is highly sensitive to settings of the algorithms' parameters: sliding window size and fingerprint sampling frequency. we identify a useful range of these parameters for achieving good practical results, and compare the performance of the four algorithms in a controlled environment. we validate our results by applying these algorithms to finding near-duplicates in two large collections of hp technical support documents.
query result clustering for object-level search. query result clustering has recently attracted a lot of attention to provide users with a succinct overview of relevant results. however, little work has been done on organizing the query results for object-level search. object-level search result clustering is challenging because we need to support diverse similarity notions over object-specific features (such as the price and weight of a product) of heterogeneous domains. to address this challenge, we propose a hybrid subspace clustering algorithm called hydra. algorithm hydra captures the user perception of diverse similarity notions from millions of web pages and disambiguates different senses using feature-based subspace locality measures. our proposed solution, by combining wisdom of crowds and wisdom of data, achieves robustness and efficiency over existing approaches. we extensively evaluate our proposed framework and demonstrate how to enrich user experiences in object-level search using a real-world product search scenarios.
scalable graph clustering using stochastic flows: applications to community discovery. algorithms based on simulating stochastic flows are a simple and natural solution for the problem of clustering graphs, but their widespread use has been hampered by their lack of scalability and fragmentation of output. in this article we present a multi-level algorithm for graph clustering using flows that delivers significant improvements in both quality and speed. the graph is first successively coarsened to a manageable size, and a small number of iterations of flow simulation is performed on the coarse graph. the graph is then successively refined, with flows from the previous graph used as initializations for brief flow simulations on each of the intermediate graphs. when we reach the final refined graph, the algorithm is run to convergence and the high-flow regions are clustered together, with regions without any flow forming the natural boundaries of the clusters. extensive experimental results on several real and synthetic datasets demonstrate the effectiveness of our approach when compared to state-of-the-art algorithms.
network science: an introduction to recent statistical approaches. network science focuses on relationships between social entities. it is used widely in the social and behavioral sciences, as well as in political science, economics, organizational science, and industrial engineering. the social network perspective has been developed over the last sixty years by researchers in psychology, sociology, and anthropology, and morerecently, to a lesser extent, in physics. network science is gaining recognition and standing in the general social and behavioral science communities as the theoretical basis for examining social structures. this basis has been clearly defined by many theorists, and the paradigm convincingly applied to important substantive problems. however, the paradigm requires a new and different set of concepts and analytic tools, beyond those provided by standard quantitative (particularly, statistical) methods. these concepts and tools are the topics of this talk.
heterogeneous source consensus learning via decision propagation and negotiation. nowadays, enormous amounts of data are continuously generated not only in massive scale, but also from different, sometimes conflicting, views. therefore, it is important to consolidate different concepts for intelligent decision making. for example, to predict the research areas of some people, the best results are usually achieved by combining and consolidating predictions obtained from the publication network, co-authorship network and the textual content of their publications. multiple supervised and unsupervised hypotheses can be drawn from these information sources, and negotiating their differences and consolidating decisions usually yields a much more accurate model due to the diversity and heterogeneity of these models. in this paper, we address the problem of "consensus learning" among competing hypotheses, which either rely on outside knowledge (supervised learning) or internal structure (unsupervised clustering). we argue that consensus learning is an np-hard problem and thus propose to solve it by an efficient heuristic method. we construct a belief graph to first propagate predictions from supervised models to the unsupervised, and then negotiate and reach consensus among them. their final decision is further consolidated by calculating each model's weight based on its degree of consistency with other models. experiments are conducted on 20 newsgroups data, cora research papers, dblp author-conference network, and yahoo! movies datasets, and the results show that the proposed method improves the classification accuracy and the clustering quality measure (nmi) over the best base model by up to 10%. furthermore, it runs in time proportional to the number of instances, which is very efficient for large scale data sets.
seven pitfalls to avoid when running controlled experiments on the web. controlled experiments, also called randomized experiments and a/b tests, have had a profound influence on multiple fields, including medicine, agriculture, manufacturing, and advertising. while the theoretical aspects of offline controlled experiments have been well studied and documented, the practical aspects of running them in online settings, such as web sites and services, are still being developed. as the usage of controlled experiments grows in these online settings, it is becoming more important to understand the opportunities and pitfalls one might face when using them in practice. a survey of online controlled experiments and lessons learned were previously documented in controlled experiments on the web: survey and practical guide (kohavi, et al., 2009). in this follow-on paper, we focus on pitfalls we have seen after running numerous experiments at microsoft. the pitfalls include a wide range of topics, such as assuming that common statistical formulas used to calculate standard deviation and statistical power can be applied and ignoring robots in analysis (a problem unique to online settings). online experiments allow for techniques like gradual ramp-up of treatments to avoid the possibility of exposing many customers to a bad (e.g., buggy) treatment. with that ability, we discovered that it's easy to incorrectly identify the winning treatment because of simpson's paradox.
pskip: estimating relevance ranking quality from web search clickthrough data. in this article, we report our efforts in mining the information encoded as clickthrough data in the server logs to evaluate and monitor the relevance ranking quality of a commercial web search engine. we describe a metric called pskip that aims to quantify the ranking quality by estimating the probability of users encountering non relevant results that cost them the efforts to read and skip. a search engine with a lower pskip is regarded as having a better ranking quality. a key design goal of pskip is to integrate the findings from two sets of user studies that utilize eye-tracking devices to track users' browsing patterns on the search result pages, and that use specially instrumented browsers to actively solicit users' explicit judgments on their search activities. we present the derivation of the maximum likelihood estimation of pskip and demonstrate its efficacy in describing the user study data. the mathematical properties of pskip are further analyzed and compared with several objective metrics as well as the cumulated gain method that uses subjective judgments. experimental data show that pskip can measure aspects of the search quality that these existing metrics are not designed or fail to address, such as identifying the real search intents expressed in the ambiguous queries. although effective and superior in many ways, we also report a series of experiments that show pskip may be influenced by system issues that are not directly related to relevance ranking, suggesting that measurements complementary to pskip are still needed in order to form a holistic and accurate characterization of the ranking quality.
collusion-resistant anonymous data collection method. the availability and the accuracy of the data dictate the success of a data mining application. increasingly, there is a need to resort to on-line data collection to address the problem of data availability. however, participants in on-line data collection applications are naturally distrustful of the data collector as well as their peer respondents, resulting in inaccurate data collected as the respondents refuse to provide truthful data in fear of collusion attacks. the current anonymity-preserving solutions for on-line data collection are unable to adequately resist such attacks in a scalable fashion. in this paper, we present an efficient anonymous data collection protocol for a malicious environment such as the internet. the protocol employs cryptographic and random shuffling techniques to preserve participants' anonymity. the proposed method is collusion-resistant and guarantees that an attacker will be unable to breach an honest participant's anonymity unless she controls all n-1 participants. in addition, our method is efficient and achieved 15-42% communication overhead reduction in comparison to the prior state-of-the-art methods.
a viewpoint-based approach for interaction graph analysis. recent innovations have resulted in a plethora of social applications on the web, such as blogs, social networks, and community photo and video sharing applications. such applications can typically be represented as evolving interaction graphs with nodes denoting entities and edges representing their interactions. the study of entities and communities and how they evolve in such large dynamic graphs is both important and challenging. while much of the past work in this area has focused on static analysis, more recently researchers have investigated dynamic analysis. in this paper, in a departure from recent efforts, we consider the problem of analyzing patterns and critical events that affect the dynamic graph from the viewpoint of a single node, or a selected subset of nodes. defining and extracting a relevant viewpoint neighborhood efficiently, while also quantifying the key relationships among nodes involved are the key challenges we address. we also examine the evolution of viewpoint neighborhoods for different entities over time to identify key structural and behavioral transformations that occur.
enabling analysts in managed services for crm analytics. data analytics tools and frameworks abound, yet rapid deployment of analytics solutions that deliver actionable insights from business data remains a challenge. the primary reason is that on-field practitioners are required to be both technically proficient and knowledgeable about the business. the recent abundance of unstructured business data has thrown up new opportunities for analytics, but has also multiplied the deployment challenge, since interpretation of concepts derived from textual sources require a deep understanding of the business. in such a scenario, a managed service for analytics comes up as the best alternative. a managed analytics service is centered around a business analyst who acts as a liaison between the business and the technology. this calls for new tools that assist the analyst to be efficient in the tasks that she needs to execute. also, the analytics needs to be repeatable, in that the delivered insights should not depend heavily on the expertise of specific analysts. these factors lead us to identify new areas that open up for kdd research in terms of 'time-to-insight' and repeatability for these analysts. we present our analytics framework in the form of a managed service offering for crm analytics. we describe different analyst-centric tools using a case study from real-life engagements and demonstrate their effectiveness.
finding a team of experts in social networks. given a task t, a pool of individuals x with different skills, and a social network g that captures the compatibility among these individuals, we study the problem of finding x, a subset of x, to perform the task. we call this the team formation problem. we require that members of x' not only meet the skill requirements of the task, but can also work effectively together as a team. we measure effectiveness using the communication cost incurred by the subgraph in g that only involves x'. we study two variants of the problem for two different communication-cost functions, and show that both variants are np-hard. we explore their connections with existing combinatorial problems and give novel algorithms for their solution. to the best of our knowledge, this is the first work to consider the team formation problem in the presence of a social network of individuals. experiments on the dblp dataset show that our framework works well in practice and gives useful and intuitive results.
parallel community detection on large networks with propinquity dynamics. graphs or networks can be used to model complex systems. detecting community structures from large network data is a classic and challenging task. in this paper, we propose a novel community detection algorithm, which utilizes a dynamic process by contradicting the network topology and the topology-based propinquity, where the propinquity is a measure of the probability for a pair of nodes involved in a coherent community structure. through several rounds of mutual reinforcement between topology and propinquity, the community structures are expected to naturally emerge. the overlapping vertices shared between communities can also be easily identified by an additional simple postprocessing. to achieve better efficiency, the propinquity is incrementally calculated. we implement the algorithm on a vertex-oriented bulk synchronous parallel(bsp) model so that the mining load can be distributed on thousands of machines. we obtained interesting experimental results on several real network data.
the offset tree for learning with partial labels. we present an algorithm, called the offset tree, for learning to make decisions in situations where the payoff of only one choice is observed, rather than all choices. the algorithm reduces this setting to binary classification, allowing one to reuse any existing, fully supervised binary classification algorithm in this partial information setting. we show that the offset tree is an optimal reduction to binary classification. in particular, it has regret at most (k-1) times the regret of the binary classifier it uses (where k is the number of choices), and no reduction to binary classification can do better. this reduction is also computationally optimal, both at training and test time, requiring just o(log2 k) work to train on an example or make a prediction. experiments with the offset tree show that it generally performs better than several alternative approaches.
mind the gaps: weighting the unknown in large-scale one-class collaborative filtering. one-class collaborative filtering (occf) is a task that naturally emerges in recommender system settings. typical characteristics include: only positive examples can be observed, classes are highly imbalanced, and the vast majority of data points are missing. the idea of introducing weights for missing parts of a matrix has recently been shown to help in occf. while existing weighting approaches mitigate the first two problems above, a sparsity preserving solution that would allow to efficiently utilize data sets with e.g., hundred thousands of users and items has not yet been reported. in this paper, we study three different collaborative filtering frameworks: low-rank matrix approximation, probabilistic latent semantic analysis, and maximum-margin matrix factorization. we propose two novel algorithms for large-scale occf that allow to weight the unknowns. our experimental results demonstrate their effectiveness and efficiency on different problems, including the netflix prize data.
coa: finding novel patents through text analysis. in recent years, the number of patents filed by the business enterprises in the technology industry are growing rapidly, thus providing unprecedented opportunities for knowledge discovery in patent data. one important task in this regard is to employ data mining techniques to rank patents in terms of their potential to earn money through licensing. availability of such ranking can substantially reduce enterprise ip (intellectual property) management costs. unfortunately, the existing software systems in the ip domain do not address this task directly. through our research, we build a patent ranking software, named coa (claim originality analysis) that rates a patent based on its value by measuring the recency and the impact of the important phrases that appear in the "claims" section of a patent. experiments show that coa produces meaningful ranking when comparing it with other indirect patent evaluation metrics--citation count, patent status, and attorney's rating. in reallife settings, this tool was used by beta-testers in the ibm ip department. lawyers found it very useful in patent rating, specifically, in highlighting potentially valuable patents in a patent cluster. in this article, we describe the ranking techniques and system architecture of coa. we also present the results that validate its effectiveness.
causality quantification and its applications: structuring and modeling of multivariate time series. time series prediction is an important issue in a wide range of areas. there are various real world processes whose states vary continuously, and those processes may have influences on each other. if the past information of one process x improves the predictability of another process y, x is said to have a causal influence on y. in order to make good predictions, it is necessary to identify the appropriate causal relationships. in addition, the processes to be modeled may include symbolic data as well as numerical data. therefore, it is important to deal with symbolic and numerical time series seamlessly when attempting to detect causality. in this paper, we propose a new method for quantifying the strength of the causal influence from one time series to another. the proposed method can represent the strength of causality as the number of bits, whether each of two time series is symbolic or numerical. the proposed method can quantify causality even from a small number of samples. in addition, we propose structuring and modeling methods for multivariate time series using causal relationships of two time series. our structuring and modeling methods can also deal with data sets which include both types of time series. experimental results demonstrate that our methods can perform well even if the number of samples is small.
characterizing individual communication patterns. the increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for characterizing individual behavior and, by extension, identifying latent structure in human populations. here, we propose a model of individual e-mail communication that is sufficiently rich to capture meaningful variability across individuals, while remaining simple enough to be interpretable. we show that the model, a cascading non-homogeneous poisson process, can be formulated as a double-chain hidden markov model, allowing us to use an efficient inference algorithm to estimate the model parameters from observed data. we then apply this model to two e-mail data sets consisting of 404 and 6,164 users, respectively, that were collected from two universities in different countries and years. we find that the resulting best-estimate parameter distributions for both data sets are surprisingly similar, indicating that at least some features of communication dynamics generalize beyond specific contexts. we also find that variability of individual behavior over time is significantly less than variability across the population, suggesting that individuals can be classified into persistent "types". we conclude that communication patterns may prove useful as an additional class of attribute data, complementing demographic and network data, for user classification and outlier detection-a point that we illustrate with an interpretable clustering of users based on their inferred model parameters.
improving clustering stability with combinatorial mrfs. as clustering methods are often sensitive to parameter tuning, obtaining stability in clustering results is an important task. in this work, we aim at improving clustering stability by attempting to diminish the influence of algorithmic inconsistencies and enhance the signal that comes from the data. we propose a mechanism that takes m clusterings as input and outputs m clusterings of comparable quality, which are in higher agreement with each other. we call our method the clustering agreement process (cap). to preserve the clustering quality, cap uses the same optimization procedure as used in clustering. in particular, we study the stability problem of randomized clustering methods (which usually produce different results at each run). we focus on methods that are based on inference in a combinatorial markov random field (or comraf, for short) of a simple topology. we instantiate cap as inference within a more complex, bipartite comraf. we test the resulting system on four datasets, three of which are medium-sized text collections, while the fourth is a large-scale user/movie dataset. first, in all the four cases, our system significantly improves the clustering stability measured in terms of the macro-averaged jaccard index. second, in all the four cases our system managed to significantly improve clustering quality as well, achieving the state-of-the-art results. third, our system significantly improves stability of consensus clustering built on top of the randomized clustering solutions.
cp-summary: a concise representation for browsing frequent itemsets. this paper tackles the problem of summarizing frequent itemsets. we observe that previous notions of summaries cannot be directly used for analyzing frequent itemsets. in order to be used for analysis, one requirement is that the analysts should be able to browse all frequent itemsets by only having the summary. for this purpose, we propose to build the summary based upon a novel formulation, conditional profile (or c-profile). several features of our proposed summary are: (1) each profile in the summary can be analyzed independently, (2) it provides error guarantee (ε-adequate), and (3) it produces no false positives or false negatives. having the formulation, the next challenge is to produce the most concise summary which satisfies the requirement. in this paper, we also designed an algorithm which is both effective and efficient for this task. the quality of our approach is justified by extensive experiments. the implementations for the algorithms are available from www.cais.ntu.edu.sg/~vivek/pubs/cprofile09.
anonymizing healthcare data: a case study on the blood transfusion service. sharing healthcare data has become a vital requirement in healthcare system management; however, inappropriate sharing and usage of healthcare data could threaten patients' privacy. in this paper, we study the privacy concerns of the blood transfusion information-sharing system between the hong kong red cross blood transfusion service (bts) and public hospitals, and identify the major challenges that make traditional data anonymization methods not applicable. furthermore, we propose a new privacy model called lkc-privacy, together with an anonymization algorithm, to meet the privacy and information requirements in this bts case. experiments on the real-life data demonstrate that our anonymization algorithm can effectively retain the essential information in anonymous data for data analysis and is scalable for anonymizing large datasets.
relational learning via latent social dimensions. social media such as blogs, facebook, flickr, etc., presents data in a network format rather than classical iid distribution. to address the interdependency among data instances, relational learning has been proposed, and collective inference based on network connectivity is adopted for prediction. however, connections in social media are often multi-dimensional. an actor can connect to another actor for different reasons, e.g., alumni, colleagues, living in the same city, sharing similar interests, etc. collective inference normally does not differentiate these connections. in this work, we propose to extract latent social dimensions based on network information, and then utilize them as features for discriminative learning. these social dimensions describe diverse affiliations of actors hidden in the network, and the discriminative learning can automatically determine which affiliations are better aligned with the class labels. such a scheme is preferred when multiple diverse relations are associated with the same network. we conduct extensive experiments on social media data (one from a real-world blog site and the other from a popular content sharing site). our model outperforms representative relational learning methods based on collective inference, especially when few labeled data are available. the sensitivity of this model and its connection to existing methods are also examined.
pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse netflix data. all netflix prize algorithms proposed so far are prohibitively costly for large-scale production systems. in this paper, we describe an efficient dataflow implementation of a collaborative filtering (cf) solution to the netflix prize problem [1] based on weighted coclustering [5]. the dataflow library we use facilitates the development of sophisticated parallel programs designed to fully utilize commodity multicore hardware, while hiding traditional difficulties such as queuing, threading, memory management, and deadlocks. the dataflow cf implementation first compresses the large, sparse training dataset into co-clusters. then it generates recommendations by combining the average ratings of the co-clusters with the biases of the users and movies. when configured to identify 20x20 co-clusters in the netflix training dataset, the implementation predicted over 100 million ratings in 16.31 minutes and achieved an rmse of 0.88846 without any fine-tuning or domain knowledge. this is an effective real-time prediction runtime of 9.7 us per rating which is far superior to previously reported results. moreover, the implemented co-clustering framework supports a wide variety of other large-scale data mining applications and forms the basis for predictive modeling on large, dyadic datasets [4, 7].
learning patterns in the dynamics of biological networks. our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. the analysis of dynamic networks is important not only to understand life at the system-level, but also to discover novel patterns in other structural data. most current graph-based data mining approaches overlook dynamic features of biological networks, because they are focused on only static graphs. our approach analyzes a sequence of graphs and discovers rules that capture the changes that occur between pairs of graphs in the sequence. these rules represent the graph rewrite rules that the first graph must go through to be isomorphic to the second graph. then, our approach feeds the graph rewrite rules into a machine learning system that learns general transformation rules describing the types of changes that occur for a class of dynamic biological networks. the discovered graph-rewriting rules show how biological networks change over time, and the transformation rules show the repeated patterns in the structural changes. in this paper, we apply our approach to biological networks to evaluate our approach and to understand how the biosystems change over time. we evaluate our results using coverage and prediction metrics, and compare to biological literature.
olap on search logs: an infrastructure supporting data-driven applications in search engines. search logs, which contain rich and up-to-date information about users' needs and preferences, have become a critical data source for search engines. recently, more and more data-driven applications are being developed in search engines based on search logs, such as query suggestion, keyword bidding, and dissatisfactory query analysis. in this paper, by observing that many data-driven applications in search engines highly rely on online mining of search logs, we develop an olap system on search logs which serves as an infrastructure supporting various data-driven applications. an empirical study using real data of over two billion query sessions demonstrates the usefulness and feasibility of our design.
an integrated proof language for imperative programs. we present an integrated proof language for guiding the actions of multiple reasoning systems as they work together to prove complex correctness properties of imperative programs. the language operates in the context of a program verification system that uses multiple reasoning systems to discharge generated proof obligations. it is designed to 1) enable developers to resolve key choice points in complex program correctness proofs, thereby enabling automated reasoning systems to successfully prove the desired correctness properties; 2) allow developers to identify key lemmas for the reasoning systems to prove, thereby guiding the reasoning systems to find an effective proof decomposition; 3) enable multiple reasoning systems to work together productively to prove a single correctness property by providing a mechanism that developers can use to divide the property into lemmas, each of which is suitable for a different reasoning system; and 4) enable developers to identify specific lemmas that the reasoning systems should use when attempting to prove other lemmas or correctness properties, thereby appropriately confining the search space so that the reasoning systems can find a proof in an acceptable amount of time. the language includes a rich set of declarative proof constructs that enables developers to direct the reasoning systems as little or as much as they desire. because the declarative proof statements are embedded into the program as specialized comments, they also serve as verified documentation and are a natural extension of the assertion mechanism found in most program verification systems. we have implemented our integrated proof language in the context of a program verification system for java and used the resulting system to verify a collection of linked data structure implementations. our experience indicates that our proof language makes it possible to successfully prove complex program correctness properties that are otherwise beyond the reach of automated reasoning systems.
parallelizing sequential applications on commodity hardware using a low-cost software transactional memory. multicore designs have emerged as the mainstream design paradigm for the microprocessor industry. unfortunately, providing multiple cores does not directly translate into performance for most applications. the industry has already fallen short of the decades-old performance trend of doubling performance every 18 months. an attractive approach for exploiting multiple cores is to rely on tools, both compilers and runtime optimizers, to automatically extract threads from sequential applications. however, despite decades of research on automatic parallelization, most techniques are only effective in the scientific and data parallel domains where array dominated codes can be precisely analyzed by the compiler. thread-level speculation offers the opportunity to expand parallelization to general-purpose programs, but at the cost of expensive hardware support. in this paper, we focus on providing low-overhead software support for exploiting speculative parallelism. we propose stmlite, a light-weight software transactional memory model that is customized to facilitate profile-guided automatic loop parallelization. stmlite eliminates a considerable amount of checking and locking overhead in conventional software transactional memory models by decoupling the commit phase from main transaction execution. further, strong atomicity requirements for generic transactional memories are unnecessary within a stylized automatic parallelization framework. stmlite enables sequential applications to extract meaningful performance gains on commodity multicore hardware.
a decision procedure for subset constraints over regular languages. reasoning about string variables, in particular program inputs, is an important aspect of many program analyses and testing frameworks. program inputs invariably arrive as strings, and are often manipulated using high-level string operations such as equality checks, regular expression matching, and string concatenation. it is difficult to reason about these operations because they are not well-integrated into current constraint solvers. we present a decision procedure that solves systems of equations over regular language variables. given such a system of constraints, our algorithm finds satisfying assignments for the variables in the system. we define this problem formally and render a mechanized correctness proof of the core of the algorithm. we evaluate its scalability and practical utility by applying it to the problem of automatically finding inputs that cause sql injection vulnerabilities.
automatic generation of library bindings using static analysis. high-level languages are growing in popularity. however, decades of c software development have produced large libraries of fast, time-tested, meritorious code that are impractical to recreate from scratch. cross-language bindings can expose low-level c code to high-level languages. unfortunately, writing bindings by hand is tedious and error-prone, while mainstream binding generators require extensive manual annotation or fail to offer the language features that users of modern languages have come to expect. we present an improved binding-generation strategy based on static analysis of unannotated library source code. we characterize three high-level idioms that are not uniquely expressible in c's low-level type system: array parameters, resource managers, and multiple return values. we describe a suite of interprocedural analyses that recover this high-level information, and we show how the results can be used in a binding generator for the python programming language. in experiments with four large c libraries, we find that our approach avoids the mistakes characteristic of hand-written bindings while offering a level of python integration unmatched by prior automated approaches. among the thousands of functions in the public interfaces of these libraries, roughly 40% exhibit the behaviors detected by our static analyses.
chameleon: adaptive selection of collections. languages such as java and c#, as well as scripting languages like python, and ruby, make extensive use of collection classes. a collection implementation represents a fixed choice in the dimensions of operation time, space utilization, and synchronization. using the collection in a manner not consistent with this fixed choice can cause significant performance degradation. in this paper, we present chameleon, a low-overhead automatic tool that assists the programmer in choosing the appropriate collection implementation for her application. during program execution, chameleon computes elaborate trace and heap-based metrics on collection behavior. these metrics are consumed on-thefly by a rules engine which outputs a list of suggested collection adaptation strategies. the tool can apply these corrective strategies automatically or present them to the programmer. we have implemented chameleon on top of a ibm's j9 production jvm, and evaluated it over a small set of benchmarks. we show that for some applications, using chameleon leads to a significant improvement of the memory footprint of the application.
program verification using templates over predicate abstraction. we address the problem of automatically generating invariants with quantified and boolean structure for proving the validity of given assertions or generating pre-conditions under which the assertions are valid. we present three novel algorithms, having different strengths, that combine template and predicate abstraction based formalisms to discover required sophisticated program invariants using smt solvers. two of these algorithms use an iterative approach to compute fixed-points (one computes a least fixed-point and the other computes a greatest fixed-point), while the third algorithm uses a constraint based approach to encode the fixed-point. the key idea in all these algorithms is to reduce the problem of invariant discovery to that of finding optimal solutions for unknowns (over conjunctions of some predicates from a given set) in a template formula such that the formula is valid. preliminary experiments using our implementation of these algorithms show encouraging results over a benchmark of small but complicated programs. our algorithms can verify program properties that, to our knowledge, have not been automatically verified before. in particular, our algorithms can generate full correctness proofs for sorting algorithms (which requires nested universally-existentially quantified invariants) and can also generate preconditions required to establish worst-case upper bounds of sorting algorithms. furthermore, for the case of previously considered properties, in particular sortedness in sorting algorithms, our algorithms take less time than reported by previous techniques.
sharing classes between families. class sharing is a new language mechanism for building extensible software systems. recent work has separately explored two different kinds of extensibility: first, family inheritance, in which an entire family of related classes can be inherited, and second, adaptation, in which existing objects are extended in place with new behavior and state. class sharing integrates these two kinds of extensibility mechanisms. with little programmer effort, objects of one family can be used as members of another, while preserving relationships among objects. therefore, a family of classes can be adapted in place with new functionality spanning multiple classes. object graphs can evolve from one family to another, adding or removing functionality even at run time. several new mechanisms support this flexibility while ensuring type safety. class sharing has been implemented as an extension to java, and its utility for evolving and extending software is demonstrated with realistic systems.
softbound: highly compatible and complete spatial memory safety for c. the serious bugs and security vulnerabilities facilitated by c/c++'s lack of bounds checking are well known, yet c and c++ remain in widespread use. unfortunately, c's arbitrary pointer arithmetic, conflation of pointers and arrays, and programmer-visible memory layout make retrofitting c/c++ with spatial safety guarantees extremely challenging. existing approaches suffer from incompleteness, have high runtime overhead, or require non-trivial changes to the c source code. thus far, these deficiencies have prevented widespread adoption of such techniques. this paper proposes softbound, a compile-time transformation for enforcing spatial safety of c. inspired by hardbound, a previously proposed hardware-assisted approach, softbound similarly records base and bound information for every pointer as disjoint metadata. this decoupling enables softbound to provide spatial safety without requiring changes to c source code. unlike hardbound, softbound is a software-only approach and performs metadata manipulation only when loading or storing pointer values. a formal proof shows that this is sufficient to provide spatial safety even in the presence of arbitrary casts. softbound's full checking mode provides complete spatial violation detection with 67% runtime overhead on average. to further reduce overheads, softbound has a store-only checking mode that successfully detects all the security vulnerabilities in a test suite at the cost of only 22% runtime overhead on average.
semantics-aware trace analysis. as computer systems continue to become more powerful and complex, so do programs. high-level abstractions introduced to deal with complexity in large programs, while simplifying human reasoning, can often obfuscate salient program properties gleaned from automated source-level analysis through subtle (often non-local) interactions. consequently, understanding the effects of program changes and whether these changes violate intended protocols become difficult to infer. refactorings, and feature additions, modifications, or removals can introduce hard-to-catch bugs that often go undetected until many revisions later. to address these issues, this paper presents a novel dynamic program analysis that builds a semantic view of program executions. these views reflect program abstractions and aspects; however, views are not simply projections of execution traces, but are linked to each other to capture semantic interactions among abstractions at different levels of granularity in a scalable manner. we describe our approach in the context of java and demonstrate its utility to improve regression analysis. we first formalize a subset of java and a grammar for traces generated at program execution. we then introduce several types of views used to analyze regression bugs along with a novel, scalable technique for semantic differencing of traces from different versions of the same program. benchmark results on large open-source java programs demonstrate that semantic-aware trace differencing can identify precise and useful details about the underlying cause for a regression, even in programs that use reflection, multithreading, or dynamic code generation, features that typically confound other analysis techniques.
efficiently and precisely locating memory leaks and bloat. inefficient use of memory, including leaks and bloat, remain a significant challenge for c and c++ developers. applications with these problems become slower over time as their working set grows and can become unresponsive. at the same time, memory leaks and bloat remain notoriously difficult to debug, and comprise a large number of reported bugs in mature applications. previous tools for diagnosing memory inefficiencies-based on garbage collection, binary rewriting, or code sampling-impose high overheads (up to 100x) or generate many false alarms. this paper presents hound, a runtime system that helps track down the sources of memory leaks and bloat in c and c++ applications. hound employs data sampling, a staleness-tracking approach based on a novel heap organization, to make it both precise and efficient. hound has no false positives, and its runtime and space overhead are low enough that it can be used in deployed applications. we demonstrate hound's efficacy across a suite of synthetic benchmarks and real applications.
snugglebug: a powerful approach to weakest preconditions. symbolic analysis shows promise as a foundation for bug-finding, specification inference, verification, and test generation. this paper addresses demand-driven symbolic analysis for object-oriented programs and frameworks. many such codes comprise large, partial programs with highly dynamic behaviors--polymorphism, reflection, and so on--posing significant scalability challenges for any static analysis. we present an approach based on interprocedural backwards propagation of weakest preconditions. we present several novel techniques to improve the efficiency of such analysis. first, we present directed call graph construction, where call graph construction and symbolic analysis are interleaved. with this technique, call graph construction is guided by constraints discovered during symbolic analysis, obviating the need for exhaustively exploring a large, conservative call graph. second, we describe generalization, a technique that greatly increases the reusability of procedure summaries computed during interprocedural analysis. instead of tabulating how a procedure transforms a symbolic state in its entirety, our technique tabulates how the procedure transforms only the pertinent portion of the symbolic state. additionally, we show how integrating an inexpensive, custom logic simplifier with weakest precondition computation dramatically improves performance. we have implemented the analysis in a tool called snugglebug and evaluated it as a bug-report feasibility checker. our results show that the algorithmic techniques were critical for successfully analyzing large java applications.
taj: effective taint analysis of web applications. taint analysis, a form of information-flow analysis, establishes whether values from untrusted methods and parameters may flow into security-sensitive operations. taint analysis can detect many common vulnerabilities in web applications, and so has attracted much attention from both the research community and industry. however, most static taint-analysis tools do not address critical requirements for an industrial-strength tool. specifically, an industrial-strength tool must scale to large industrial web applications, model essential web-application code artifacts, and generate consumable reports for a wide range of attack vectors. we have designed and implemented a static taint analysis for java (taj) that meets the requirements of industry-level applications. taj can analyze applications of virtually any size, as it employs a set of techniques designed to produce useful answers given limited time and space. taj addresses a wide variety of attack vectors, with techniques to handle reflective calls, flow through containers, nested taint, and issues in generating useful reports. this paper provides a description of the algorithms comprising taj, evaluates taj against production-level benchmarks, and compares it with alternative solutions.
dynamic software updates: a vm-centric approach. software evolves to fix bugs and add features. stopping and restarting programs to apply changes is inconvenient and often costly. dynamic software updating (dsu) addresses this problem by updating programs while they execute, but existing dsu systems for managed languages do not support many updates that occur in practice and are inefficient. this paper presents the design and implementation of jvolve, a dsu-enhanced java vm. updated programs may add, delete, and replace fields and methods anywhere within the class hierarchy. jvolve implements these updates by adding to and coordinating vm classloading, just-in-time compilation, scheduling, return barriers, on-stack replacement, and garbage collection. jvolve, is safe: its use of bytecode verification and vm thread synchronization ensures that an update will always produce type-correct executions. jvolve is flexible: it can support 20 of 22 updates to three open-source programs--jetty web server, javaemailserver, and crossftp server--based on actual releases occurring over 1 to 2 years. jvolve is efficient: performance experiments show that incurs no overhead during steady-state execution. these results demonstrate that this work is a significant step towards practical support for dynamic updates in virtual machines for managed languages.
programming model for a heterogeneous x86 platform. the client computing platform is moving towards a heterogeneous architecture consisting of a combination of cores focused on scalar performance, and a set of throughput-oriented cores. the throughput oriented cores (e.g. a gpu) may be connected over both coherent and non-coherent interconnects, and have different isas. this paper describes a programming model for such heterogeneous platforms. we discuss the language constructs, runtime implementation, and the memory model for such a programming environment. we implemented this programming environment in a x86 heterogeneous platform simulator. we ported a number of workloads to our programming environment, and present the performance of our programming environment on these workloads.
typed self-representation. self-representation -- the ability to represent programs in their own language -- has important applications in reflective languages and many other domains of programming language design. although approaches to designing typed program representations for sublanguages of some base language have become quite popular recently, the question whether a fully metacircular typed self-representation is possible is still open. this paper makes a big step towards this aim by defining the fω* calculus, an extension of the higher-order polymorphic lambda calculus fω that allows typed self-representations. while the usability of these representations for metaprogramming is still limited, we believe that our approach makes a significant step towards a new generation of reflective languages that are both safe and efficient.
towards a holistic approach to auto-parallelization: integrating profile-driven parallelism detection and machine-learning based mapping. compiler-based auto-parallelization is a much studied area, yet has still not found wide-spread application. this is largely due to the poor exploitation of application parallelism, subsequently resulting in performance levels far below those which a skilled expert programmer could achieve. we have identified two weaknesses in traditional parallelizing compilers and propose a novel, integrated approach, resulting in significant performance improvements of the generated parallel code. using profile-driven parallelism detection we overcome the limitations of static analysis, enabling us to identify more application parallelism and only rely on the user for final approval. in addition, we replace the traditional target-specific and inflexible mapping heuristics with a machine-learning based prediction mechanism, resulting in better mapping decisions while providing more scope for adaptation to different target architectures. we have evaluated our parallelization strategy against the nas and spec omp benchmarks and two different multi-core platforms (dual quad-core intel xeon smp and dual-socket qs20 cell blade). we demonstrate that our approach not only yields significant improvements when compared with state-of-the-art parallelizing compilers, but comes close to and sometimes exceeds the performance of manually parallelized codes. on average, our methodology achieves 96% of the performance of the hand-tuned openmp nas and spec parallel benchmarks on the intel xeon platform and gains a significant speedup for the ibm cell platform, demonstrating the potential of profile-guided and machine-learning based parallelization for complex multi-core platforms.
type-based data structure verification. we present a refinement type-based approach for the static verification of complex data structure invariants. our approach is based on the observation that complex data structures are typically fashioned from two elements: recursion (e.g., lists and trees), and maps (e.g., arrays and hash tables). we introduce two novel type-based mechanisms targeted towards these elements: recursive refinements and polymorphic refinements. these mechanisms automate the challenging work of generalizing and instantiating rich universal invariants by piggybacking simple refinement predicates on top of types, and carefully dividing the labor of analysis between the type system and an smt solver. further, the mechanisms permit the use of the abstract interpretation framework of liquid type inference to automatically synthesize complex invariants from simple logical qualifiers, thereby almost completely automating the verification. we have implemented our approach in dsolve, which uses liquid types to verify ocaml programs. we present experiments that show that our type-based approach reduces the manual annotation required to verify complex properties like sortedness, balancedness, binary-search-ordering, and acyclicity by more than an order of magnitude.
ceal: a c-based language for self-adjusting computation. self-adjusting computation offers a language-centric approach to writing programs that can automatically respond to modifications to their data (e.g., inputs). except for several domain-specific implementations, however, all previous implementations of self-adjusting computation assume mostly functional, higher-order languages such as standard ml. prior to this work, it was not known if self-adjusting computation can be made to work with low-level, imperative languages such as c without placing undue burden on the programmer. we describe the design and implementation of ceal: a c-based language for self-adjusting computation. the language is fully general and extends c with a small number of primitives to enable writing self-adjusting programs in a style similar to conventional c programs. we present efficient compilation techniques for translating ceal programs into c that can be compiled with existing c compilers using primitives supplied by a run-time library for self-adjusting computation. we implement the proposed compiler and evaluate its effectiveness. our experiments show that ceal is effective in practice: compiled self-adjusting programs respond to small modifications to their data by orders of magnitude faster than recomputing from scratch while slowing down a from-scratch run by a moderate constant factor. compared to previous work, we measure significant space and time improvements.
binary analysis for measurement and attribution of program performance. modern programs frequently employ sophisticated modular designs. as a result, performance problems cannot be identified from costs attributed to routines in isolation; understanding code performance requires information about a routine's calling context. existing performance tools fall short in this respect. prior strategies for attributing context-sensitive performance at the source level either compromise measurement accuracy, remain too close to the binary, or require custom compilers. to understand the performance of fully optimized modular code, we developed two novel binary analysis techniques: 1) on-the-fly analysis of optimized machine code to enable minimally intrusive and accurate attribution of costs to dynamic calling contexts; and 2) post-mortem analysis of optimized machine code and its debugging sections to recover its program structure and reconstruct a mapping back to its source code. by combining the recovered static program structure with dynamic calling context information, we can accurately attribute performance metrics to calling contexts, procedures, loops, and inlined instances of procedures. we demonstrate that the fusion of this information provides unique insight into the performance of complex modular codes. this work is implemented in the hpctoolkit performance tools (http://hpctoolkit.org).
error propagation analysis for file systems. unchecked errors are especially pernicious in operating system file management code. transient or permanent hardware failures are inevitable, and error-management bugs at the file system layer can cause silent, unrecoverable data corruption. we propose an interprocedural static analysis that tracks errors as they propagate through file system code. our implementation detects overwritten, out-of-scope, and unsaved unchecked errors. analysis of four widely-used linux file system implementations (cifs, ext3, ibm jfs and reiserfs), a relatively new file system implementation (ext4), and shared virtual file system (vfs) code uncovers 312 error propagation bugs. our flow- and context-sensitive approach produces more precise results than related techniques while providing better diagnostic information, including possible execution paths that demonstrate each bug found.
proving optimizations correct using parameterized program equivalence. translation validation is a technique for checking that, after an optimization has run, the input and output of the optimization are equivalent. traditionally, translation validation has been used to prove concrete, fully specified programs equivalent. in this paper we present parameterized equivalence checking (pec), a generalization of translation validation that can prove the equivalence of parameterized programs. a parameterized program is a partially specified program that can represent multiple concrete programs. for example, a parameterized program may contain a section of code whose only known property is that it does not modify certain variables. by proving parameterized programs equivalent, pec can prove the correctness of transformation rules that represent complex optimizations once and for all, before they are ever run. we implemented our pec technique in a tool that can establish the equivalence of two parameterized programs. to highlight the power of pec, we designed a language for implementing complex optimizations using many-to-many rewrite rules, and used this language to implement a variety of optimizations including software pipelining, loop unrolling, loop unswitching, loop interchange, and loop fusion. finally, to demonstrate the effectiveness of pec, we used our pec implementation to verify that all the optimizations we implemented in our language preserve program behavior.
progress guarantee for parallel programs via bounded lock-freedom. parallel platforms are becoming ubiquitous with modern computing systems. many parallel applications attempt to avoid locks in order to achieve high responsiveness, aid scalability, and avoid deadlocks and livelocks. however, avoiding the use of system locks does not guarantee that no locks are actually used, because progress inhibitors may occur in subtle ways through various program structures. notions of progress guarantee such as lock-freedom, wait-freedom, and obstruction-freedom have been proposed in the literature to provide various levels of progress guarantees. in this paper we formalize the notions of progress guarantees using linear temporal logic (ltl). we concentrate on lock-freedom and propose a variant of it denoted bounded lock-freedom, which is more suitable for guaranteeing progress in practical systems. we use this formal definition to build a tool that checks if a concurrent program is bounded lock-free for a given bound. we then study the interaction between programs with progress guarantees and the underlying system (e.g., compilers, runtimes, operating systems, and hardware platforms). we propose a means to argue that an underlying system supports lock-freedom. a composition theorem asserts that bounded lock-free algorithms running on bounded lock-free supporting systems retain bounded lock-freedom for the composed execution.
implementation of the memory-safe full ansi-c compiler. this paper describes a completely memory-safe compiler for c language programs that is fully compatible with the ansi c specification. programs written in c often suffer from nasty errors due to dangling pointers and buffer overflow. such errors in internet server programs are often exploited by malicious attackers to crack an entire system. the origin of these errors is usually corruption of in-memory data structures caused by out-of-bound array accesses. usual c compilers do not provide any protection against such out-of-bound access, although many other languages such as java and ml do provide such protection. there have been several proposals for preventing such memory corruption from various aspects: runtime buffer overrun detectors, designs for new c-like languages, and compilers for (subsets of) the c language. however, as far as we know, none of them have achieved full memory protection and full compatibility with the c language specification at the same time. we propose the most powerful solution to this problem ever presented. we have developed fail-safe c, a memory-safe implementation of the full ansi c language. it detects and disallows all unsafe operations, yet conforms to the full ansi c standard (including casts and unions). this paper introduces several techniques--both compile-time and runtime--to reduce the overhead of runtime checks, while still maintaining 100% memory safety. this compiler lets programmers easily make their programs safe without heavy rewriting or porting of their code. it also supports many of the "dirty tricks" commonly used in many existing c programs, which do not strictly conform to the standard specification. in this paper, we demonstrate several real-world server programs that can be processed by our compiler and present technical details and benchmark results for it.
go with the flow: profiling copies to find runtime bloat. many large-scale java applications suffer from runtime bloat. they execute large volumes of methods, and create many temporary objects, all to execute relatively simple operations. there are large opportunities for performance optimizations in these applications, but most are being missed by existing optimization and tooling technology. while jit optimizations struggle for a few percent, performance experts analyze deployed applications and regularly find gains of 2x or more. finding such big gains is difficult, for both humans and compilers, because of the diffuse nature of runtime bloat. time is spread thinly across calling contexts, making it difficult to judge how to improve performance. bloat results from a pile-up of seemingly harmless decisions. each adds temporary objects and method calls, and often copies values between those temporary objects. while data copies are not the entirety of bloat, we have observed that they are excellent indicators of regions of excessive activity. by optimizing copies, one is likely to remove the objects that carry copied values, and the method calls that allocate and populate them. we introduce copy profiling, a technique that summarizes runtime activity in terms of chains of data copies. a flat copy profile counts copies by method. we show how flat profiles alone can be helpful. in many cases, diagnosing a problem requires data flow context. tracking and making sense of raw copy chains does not scale, so we introduce a summarizing abstraction called the copy graph. we implement three clients analyses that, using the copy graph, expose common patterns of bloat, such as finding hot copy chains and discovering temporary data structures. we demonstrate, with examples from a large-scale commercial application and several benchmarks, that copy profiling can be used by a programmer to quickly find opportunities for large performance gains.
verifiable composition of deterministic grammars. there is an increasing interest in extensible languages, (domain-specific) language extensions, and mechanisms for their specification and implementation. one challenge is to develop tools that allow non-expert programmers to add an eclectic set of language extensions to a host language. we describe mechanisms for composing and analyzing concrete syntax specifications of a host language and extensions to it. these specifications consist of context-free grammars with each terminal symbol mapped to a regular expression, from which a slightly-modified lr parser and context-aware scanner are generated. traditionally, conflicts are detected when a parser is generated from the composed grammar, but this comes too late since it is the non-expert programmer directing the composition of independently developed extensions with the host language. the primary contribution of this paper is a modular analysis that is performed independently by each extension designer on her extension (composed alone with the host language). if each extension passes this modular analysis, then the language composed later by the programmer will compile with no conflicts or lexical ambiguities. thus, extension writers can verify that their extension will safely compose with others and, if not, fix the specification so that it will. this is possible due to the context-aware scanner's lexical disambiguation and a set of reasonable restrictions limiting the constructs that can be introduced by an extension. the restrictions ensure that the parse table states can be partitioned so that each state can be attributed to the host language or a single extension.
safe and timely updates to multi-threaded programs. many dynamic updating systems have been developed that enable a program to be patched while it runs, to fix bugs or add new features. this paper explores techniques for supporting dynamic updates to multi-threaded programs, focusing on the problem of applying an update in a timely fashion while still producing correct behavior. past work has shown that this tension of safety versus timeliness can be balanced for single-threaded programs. for multi-threaded programs, the task is more difficult because myriad thread interactions complicate understanding the possible program states to which a patch could be applied. our approach allows the programmer to specify a few program points (e.g., one per thread) at which a patch may be applied, which simplifies reasoning about safety. to improve timeliness, a combination of static analysis and run-time support automatically expands these few points to many more that produce behavior equivalent to the originals. experiments with thirteen realistic updates to three multi-threaded servers show that we can safely perform a dynamic update within milliseconds when more straightforward alternatives would delay some updates indefinitely.
fasttrack: efficient and precise dynamic race detection. \begin{abstract} multithreaded programs are notoriously prone to race conditions. prior work on dynamic race detectors includes fast but imprecise race detectors that report false alarms, as well as slow but precise race detectors that never report false alarms. the latter typically use expensive vector clock operations that require time linear in the number of program threads. this paper exploits the insight that the full generality of vector clocks is unnecessary in most cases. that is, we can replace heavyweight vector clocks with an adaptive lightweight representation that, for almost all operations of the target program, requires only constant space and supports constant-time operations. this representation change significantly improves time and space performance, with no loss in precision. experimental results on java benchmarks including the eclipse development environment show that our fasttrack race detector is an order of magnitude faster than a traditional vector-clock race detector, and roughly twice as fast as the high-performance djit+ algorithm. fasttrack is even comparable in speed to eraser on our java benchmarks, while never reporting false alarms.
control-flow refinement and progress invariants for bound analysis. symbolic complexity bounds help programmers understand the performance characteristics of their implementations. existing work provides techniques for statically determining bounds of procedures with simple control-flow. however, procedures with nested loops or multiple paths through a single loop are challenging. in this paper we describe two techniques, control-flow refinement and progress invariants, that together enable estimation of precise bounds for procedures with nested and multi-path loops. control-flow refinement transforms a multi-path loop into a semantically equivalent code fragment with simpler loops by making the structure of path interleaving explicit. we show that this enables non-disjunctive invariant generation tools to find a bound on many procedures for which previous techniques were unable to prove termination. progress invariants characterize relationships between consecutive states that can arise at a program location. we further present an algorithm that uses progress invariants to compute precise bounds for nested loops. the utility of these two techniques goes beyond our application to symbolic bound analysis. in particular, we discuss applications of control-flow refinement to proving safety properties that otherwise require disjunctive invariants. we have applied our methodology to over 670,000 lines of code of a significant microsoft product and were able to find symbolic bounds for 90% of the loops. we are not aware of any other published results that report experiences running a bound analysis on a real code-base.
trace-based just-in-time type specialization for dynamic languages. dynamic languages such as javascript are more difficult to compile than statically typed ones. since no concrete type information is available, traditional compilers need to emit generic code that can handle all possible type combinations at runtime. we present an alternative compilation technique for dynamically-typed languages that identifies frequently executed loop traces at run-time and then generates machine code on the fly that is specialized for the actual dynamic types occurring on each path through the loop. our method provides cheap inter-procedural type specialization, and an elegant and efficient way of incrementally compiling lazily discovered alternative paths through nested loops. we have implemented a dynamic compiler for javascript based on our technique and we have measured speedups of 10x and more for certain benchmark programs.
gc assertions: using the garbage collector to check heap properties. this paper introduces gc assertions, a system interface that programmers can use to check for errors, such as data structure invariant violations, and to diagnose performance problems, such as memory leaks. gc assertions are checked by the garbage collector, which is in a unique position to gather information and answer questions about the lifetime and connectivity of objects in the heap. by piggybacking on existing garbage collector computations, our system is able to check heap properties with very low overhead -- around 3% of total execution time -- low enough for use in a deployed setting. we introduce several kinds of gc assertions and describe how they are implemented in the collector. we also describe our reporting mechanism, which provides a complete path through the heap to the offending objects. we report results on both the performance of our system and the experience of using our assertions to find and repair errors in real-world programs.
laminar: practical fine-grained decentralized information flow control. decentralized information flow control (difc) is a promising model for writing programs with powerful, end-to-end security guarantees. current difc systems that run on commodity hardware can be broadly categorized into two types: language-level and operating system-level difc. language level solutions provide no guarantees against security violations on system resources, like files and sockets. operating system solutions can mediate accesses to system resources, but are inefficient at monitoring the flow of information through fine-grained program data structures. this paper describes laminar, the first system to implement decentralized information flow control using a single set of abstractions for os resources and heap-allocated objects. programmers express security policies by labeling data with secrecy and integrity labels, and then access the labeled data in lexically scoped security regions. laminar enforces the security policies specified by the labels at runtime. laminar is implemented using a modified java virtual machine and a new linux security module. this paper shows that security regions ease incremental deployment and limit dynamic security checks, allowing us to retrofit difc policies on four application case studies. replacing the applications' ad-hoc security policies changes less than 10% of the code, and incurs performance overheads from 1% to 56%. whereas prior difc systems only support limited types of multithreaded programs, laminar supports a more general class of multithreaded difc programs that can access heterogeneously labeled data.
verified validation of lazy code motion. translation validation establishes a posteriori the correctness of a run of a compilation pass or other program transformation. in this paper, we develop an efficient translation validation algorithm for the lazy code motion (lcm) optimization. lcm is an interesting challenge for validation because it is a global optimization that moves code across loops. consequently, care must be taken not to move computations that may fail before loops that may not terminate. our validator includes a specific check for anticipability to rule out such incorrect moves. we present a mechanically-checked proof of correctness of the validation algorithm, using the coq proof assistant. combining our validator with an unverified implementation of lcm, we obtain a lcm pass that is provably semantics-preserving and was integrated in the compcert formally verified compiler.
staged information flow for javascript. modern websites are powered by javascript, a flexible dynamic scripting language that executes in client browsers. a common paradigm in such websites is to include third-party javascript code in the form of libraries or advertisements. if this code were malicious, it could read sensitive information from the page or write to the location bar, thus redirecting the user to a malicious page, from which the entire machine could be compromised. we present an information-flow based approach for inferring the effects that a piece of javascript has on the website in order to ensure that key security properties are not violated. to handle dynamically loaded and generated javascript, we propose a framework for staging information flow properties. our framework propagates information flow through the currently known code in order to compute a minimal set of syntactic residual checks that are performed on the remaining code when it is dynamically loaded. we have implemented a prototype framework for staging information flow. we describe our techniques for handling some difficult features of javascript and evaluate our system's performance on a variety of large real-world websites. our experiments show that static information flow is feasible and efficient for javascript, and that our technique allows the enforcement of information-flow policies with almost no run-time overhead.
lightweight annotations for controlling sharing in concurrent data structures. sharc is a recently developed system for checking data-sharing in multithreaded programs. programmers specify sharing rules (read-only, protected by a lock, etc.) for individual objects, and the sharc compiler enforces these rules using static and dynamic checks. violations of these rules indicate unintended data sharing, which is the underlying cause of harmful data-races. additionally, sharc allows programmers to change the sharing rules for a specific object using a sharing cast, to capture the fact that sharing rules for an object often change during the object's lifetime. sharc was successfully applied to a number of multi-threaded c programs. however, many programs are not readily checkable using sharc because their sharing rules, and changes to sharing rules, effectively apply to whole data structures rather than to individual objects. we have developed a system called shoal to address this shortcoming. in addition to the sharing rules and sharing cast of sharc, our system includes a new concept that we call groups. a group is a collection of objects all having the same sharing mode. each group has a distinguished member called the group leader. when the sharing mode of the group leader changes by way of a sharing cast, the sharing mode of all members of the group also changes. this operation is made sound by maintaining the invariant that at the point of a sharing cast, the only external pointer into the group is the pointer to the group leader. the addition of groups allows checking safe concurrency at the level of data structures rather than at the level of individual objects. we demonstrate the necessity and practicality of groups by applying shoal to a wide range of concurrent c programs (the largest approaching a million lines of code). in all benchmarks groups entail low annotation burden and no significant additional performance overhead.
literace: effective sampling for lightweight data-race detection. data races are one of the most common and subtle causes of pernicious concurrency bugs. static techniques for preventing data races are overly conservative and do not scale well to large programs. past research has produced several dynamic data race detectors that can be applied to large programs. they are precise in the sense that they only report actual data races. however, dynamic data race detectors incur a high performance overhead, slowing down a program's execution by an order of magnitude. in this paper we present literace, a very lightweight data race detector that samples and analyzes only selected portions of a program's execution. we show that it is possible to sample a multithreaded program at a low frequency, and yet, find infrequently occurring data races. we implemented literace using microsoft's phoenix compiler. our experiments with several microsoft programs, apache, and firefox show that literace is able to find more than 70% of data races by sampling less than 2% of memory accesses in a given program execution.
a study of memory management for web-based applications on multicore processors. more and more server workloads are becoming web-based. in these web-based workloads, most of the memory objects are used only during one transaction. we study the effect of the memory management approaches on the performance of such web-based applications on two modern multicore processors. in particular, using six php applications, we compare a general-purpose allocator (the default allocator of the php runtime) and a region-based allocator, which can reduce the cost of memory management by not supporting per-object free. the region-based allocator achieves better performance for all workloads on one processor core due to its smaller memory management cost. however, when using eight cores, the region-based allocator suffers from hidden costs of increased bus traffics and the performance is reduced for many workloads by as much as 27.2% compared to the default allocator. this is because the memory bandwidth tends to become a bottleneck in systems with multicore processors. we propose a new memory management approach, defrag-dodging, to maximize the performance of the web-based workloads on multicore processors. in our approach, we reduce the memory management cost by avoiding defragmentation overhead in the malloc and free functions during a transaction. we found that the transactions in web-based applications are short enough to ignore heap fragmentation, and hence the costs of the defrag-mentation activities in existing general-purpose allocators outweigh their benefits. by comparing our approach against the region-based approach, we show that a per-object free capability can reduce bus traffic and achieve higher performance on multicore processors. we demonstrate that our defrag-dodging approach improves the performance of all the evaluated applications on both processors by up to 11.4% and 51.5% over the default allocator and the region-based allocator, respectively.
stretching transactional memory. transactional memory (tm) is an appealing abstraction for programming multi-core systems. potential target applications for tm, such as business software and video games, are likely to involve complex data structures and large transactions, requiring specific software solutions (stm). so far, however, stms have been mainly evaluated and optimized for smaller scale benchmarks. we revisit the main stm design choices from the perspective of complex workloads and propose a new stm, which we call swisstm. in short, swisstm is lock- and word-based and uses (1) optimistic (commit-time) conflict detection for read/write conflicts and pessimistic (encounter-time) conflict detection for write/write conflicts, as well as (2) a new two-phase contention manager that ensures the progress of long transactions while inducing no overhead on short ones. swisstm outperforms state-of-the-art stm implementations, namely rstm, tl2, and tinystm, in our experiments on stmbench7, stamp, lee-tm and red-black tree benchmarks. beyond swisstm, we present the most complete evaluation to date of the individual impact of various stm design choices on the ability to support the mixed workloads of large applications.
a randomized dynamic program analysis technique for detecting real deadlocks. we present a novel dynamic analysis technique that finds real deadlocks in multi-threaded programs. our technique runs in two stages. in the first stage, we use an imprecise dynamic analysis technique to find potential deadlocks in a multi-threaded program by observing an execution of the program. in the second stage, we control a random thread scheduler to create the potential deadlocks with high probability. unlike other dynamic analysis techniques, our approach has the advantage that it does not give any false warnings. we have implemented the technique in a prototype tool for java, and have experimented on a number of large multi-threaded java programs. we report a number of previously known and unknown real deadlocks that were found in these benchmarks.
merlin: specification inference for explicit information flow problems. the last several years have seen a proliferation of static and runtime analysis tools for finding security violations that are caused by explicit information flow in programs. much of this interest has been caused by the increase in the number of vulnerabilities such as cross-site scripting and sql injection. in fact, these explicit information flow vulnerabilities commonly found in web applications now outnumber vulnerabilities such as buffer overruns common in type-unsafe languages such as c and c++. tools checking for these vulnerabilities require a specification to operate. in most cases the task of providing such a specification is delegated to the user. moreover, the efficacy of these tools is only as good as the specification. unfortunately, writing a comprehensive specification presents a major challenge: parts of the specification are easy to miss, leading to missed vulnerabilities; similarly, incorrect specifications may lead to false positives. this paper proposes merlin, a new approach for automatically inferring explicit information flow specifications from program code. such specifications greatly reduce manual labor, and enhance the quality of results, while using tools that check for security violations caused by explicit information flow. beginning with a data propagation graph, which represents interprocedural flow of information in the program, merlin aims to automatically infer an information flow specification. merlin models information flow paths in the propagation graph using probabilistic constraints. a naive modeling requires an exponential number of constraints, one per path in the propagation graph. for scalability, we approximate these path constraints using constraints on chosen triples of nodes, resulting in a cubic number of constraints. we characterize this approximation as a probabilistic abstraction, using the theory of probabilistic refinement developed by mciver and morgan. we solve the resulting system of probabilistic constraints using factor graphs, which are a well-known structure for performing probabilistic inference. we experimentally validate the merlin approach by applying it to 10 large business-critical web applications that have been analyzed with cat.net, a state-of-the-art static analysis tool for .net. we find a total of 167 new confirmed specifications, which result in a total of 322 additional vulnerabilities across the 10 benchmarks. more accurate specifications also reduce the false positive rate: in our experiments, merlin-inferred specifications result in 13 false positives being removed; this constitutes a 15% reduction in the cat.net false positive rate on these 10 programs. the final false positive rate for cat.net after applying merlin in our experiments drops to under 1%.
petabricks: a language and compiler for algorithmic choice. it is often impossible to obtain a one-size-fits-all solution for high performance algorithms when considering different choices for data distributions, parallelism, transformations, and blocking. the best solution to these choices is often tightly coupled to different architectures, problem sizes, data, and available system resources. in some cases, completely different algorithms may provide the best performance. current compiler and programming language techniques are able to change some of these parameters, but today there is no simple way for the programmer to express or the compiler to choose different algorithms to handle different parts of the data. existing solutions normally can handle only coarse-grained, library level selections or hand coded cutoffs between base cases and recursive cases. we present petabricks, a new implicitly parallel language and compiler where having multiple implementations of multiple algorithms to solve a problem is the natural way of programming. we make algorithmic choice a first class construct of the language. choices are provided in a way that also allows our compiler to tune at a finer granularity. the petabricks compiler autotunes programs by making both fine-grained as well as algorithmic choices. choices also include different automatic parallelization techniques, data distributions, algorithmic parameters, transformations, and blocking. additionally, we introduce novel techniques to autotune algorithms for different convergence criteria. when choosing between various direct and iterative methods, the petabricks compiler is able to tune a program in such a way that delivers near-optimal efficiency for any desired level of accuracy. the compiler has the flexibility of utilizing different convergence criteria for the various components within a single algorithm, providing the user with accuracy choice alongside algorithmic choice.
a fast and efficient algorithm for low-rank approximation of a matrix. the low-rank matrix approximation problem involves finding of a rank k version of a m x n matrix a, labeled ak, such that ak is as "close" as possible to the best svd approximation version of a at the same rank level. previous approaches approximate matrix a by non-uniformly adaptive sampling some columns (or rows) of a, hoping that this subset of columns contain enough information about a. the sub-matrix is then used for the approximation process. however, these approaches are often computationally intensive due to the complexity in the adaptive sampling. in this paper, we propose a fast and efficient algorithm which at first pre-processes matrix a in order to spread out information (energy) of every columns (or rows) of a, then randomly selects some of its columns (or rows). finally, a rank-k approximation is generated from the row space of these selected sets. the preprocessing step is performed by uniformly randomizing signs of entries of a and transforming all columns of a by an orthonormal matrix f with existing fast implementation (e.g. hadamard, fft, dct...). our main contribution is summarized as follows. 1) we show that by uniformly selecting at random d rows of the preprocessed matrix with d = ( 1/η k max {log k, log 1/β} ), we guarantee the relative frobenius norm error approximation: (1 + η) norm{a - ak}f with probability at least 1 - 5β. 2) with d above, we establish a spectral norm error approximation: (2 + √2m/d) norm{a - ak}2 with probability at least 1 - 2β. 3) the algorithm requires 2 passes over the data and runs in time (mn log d + (m+n) d2) which, as far as the best of our knowledge, is the fastest algorithm when the matrix a is dense. 4) as a bonus, applying this framework to the well-known least square approximation problem min norm{a x - b} where a ∈ rm x r, we show that by randomly choosing d = (1/η γ r log m), the approximation solution is proportional to the optimal one with a factor of η and with extremely high probability, (1 - 6 m-γ), say.
on cryptography with auxiliary input. we study the question of designing cryptographic schemes which are secure even if an arbitrary function f(sk) of the secret key is leaked, as long as the secret key sk is still (exponentially) hard to compute from this auxiliary input. this setting of auxiliary input is more general than the more traditional setting, which assumes that some of information about the secret key sk may be leaked, but sk still has high min-entropy left. in particular, we deal with situations where f(sk) information-theoretically determines the entire secret key sk. as our main result, we construct cpa/cca secure symmetric encryption schemes that remain secure with exponentially hard-to-invert auxiliary input. we give several applications of such schemes. * we construct an average-case obfuscator for the class of point functions, which remains secure with exponentially hard-to-invert auxiliary input, and is reusable. * we construct a reusable and robust extractor that remains secure with exponentially hard-to-invert auxiliary input. our results rely on a new cryptographic assumption, learning subspace-with-noise (lsn), which is related to the well known learning parity-with-noise (lpn) assumption.
quantum algorithms using the curvelet transform. the curvelet transform is a directional wavelet transform over rn, which is used to analyze functions that have singularities along smooth surfaces (candes and donoho, 2002). i demonstrate how this can lead to new quantum algorithms. i give an efficient implementation of a quantum curvelet transform, together with two applications: a single-shot measurement procedure for approximately finding the center of a ball in rn, given a quantum-sample over the ball; and, a quantum algorithm for finding the center of a radial function over rn, given oracle access to the function. i conjecture that these algorithms succeed with constant probability, using one quantum-sample and o(1) oracle queries, respectively, independent of the dimension n -- this can be interpreted as a quantum speed-up. to support this conjecture, i prove rigorous bounds on the distribution of probability mass for the continuous curvelet transform. this shows that the above algorithms work in an idealized "continuous" model.
a constant-factor approximation for stochastic steiner forest. we consider the stochastic steiner forest problem: suppose we were given a collection of steiner forest instances, and were guaranteed that a random one of these instances would appear tomorrow; moreover, the cost of edges tomorrow will be λ times the cost of edges today. which edges should we buy today so that we can extend it to a solution for the instance arriving tomorrow, to minimize the expected total cost? while very general results have been developed for many problems in stochastic discrete optimization over the past years, the approximation status of the stochastic steiner forest problem has remained open, with previous works yielding constant-factor approximations only for special cases. we resolve the status of this problem by giving a constant-factor primal-dual based approximation algorithm.
how long does it take to catch a wild kangaroo? the discrete logarithm problem asks to solve for the exponent x, given the generator g of a cyclic group g and an element h∈ g such that gx=h. we give the first rigorous proof that pollard's kangaroo method finds the discrete logarithm in expected time (3+o(1))√{b-a} for the worst value of x∈[a,b], and (2+o(1))√b-a when x∈uar[a,b]. this matches the conjectured time complexity and, rare among the analysis of algorithms based on markov chains, even the lead constants 2 and 3 are correct.
hadwiger's conjecture is decidable. the famous hadwiger's conjecture asserts that every graph with no kt-minor is (t-1)-colorable. the case t=5 is known to be equivalent to the four color theorem by wagner, and the case t=6 is settled by robertson, seymour and thomas. so far the cases t ≥ 7 are wide open. in this paper, we prove the following two theorems: there is an o(n2) algorithm to decide whether or not a given graph g satisfies hadwiger's conjecture for the case t. every minimal counterexample to hadwiger's conjecture for the case t has at most f(t) vertices for some explicit bound f(t). the bound f(t) is at most pppt, where p=101010t. our proofs for both results use the well-known result by thomassen [46] for 5-list-coloring planar graphs, together with some results (but not the decomposition theorem) of graph minors in [36]. concerning the first result, we prove the following stronger theorem: for a given graph g and any fixed t, there is an o(n2) algorithm to output one of the following: a (t-1)-coloring of g, or a kt-minor of g, or a minor h of g of order at most f(t) such that h does not have a kt-minor nor is (t-1)-colorable. the last conclusion implies that h is a counterexample to hadwiger's conjecture with at most f(t) vertices for the case t. the time complexity of the algorithm matches the best known algorithms for 4-coloring planar graphs (the four color theorem), due to appel and hakken, and robertson, sanders, seymour and thomas, respectively. let us observe that when t=5, the algorithm gives rise to an algorithm for the four color theorem. the second theorem follows from our structure theorem, which has the following corollary: every minimal counterexample g to hadwiger's conjecture for the case t either has at most f(t) vertices, or has a vertex set z of order at most t-5 such that g-z is planar. it follows from the four color theorem that the second assertion does not happen to any minimal counterexample to hadwiger's conjecture for the case t. thus in constant time, we can decide hadwiger's conjecture for the case t.
multiple intents re-ranking. one of the most fundamental problems in web search is how to re-rank result web pages based on user logs. most traditional models for re-ranking assume each query has a single intent. that is, they assume all users formulating the same query have similar preferences over the result web pages. it is clear that this is not true for a large portion of queries as different users may have different preferences over the result web pages. accordingly, a more accurate model should assume that queries have multiple intents. in this paper, we introduce the multiple intents re-ranking problem. this problem captures scenarios in which some user makes a query, and there is no information about its real search intent. in such cases, one would like to re-rank the search results in a way that minimizes the efforts of all users in finding their relevant web pages. more formally, the setting of this problem consists of various types of users, each of which interested in some subset of the search results. moreover, each user type has a non-negative profile vector. consider some ordering of the search results. this order sets a position for each search result, and induces a position vector of the results relevant to each user type. the overhead of a user type is the dot product of its profile vector and its induced position vector. the goal is to order the search results as to minimize the average overhead of the users. our main result is an o(log r)-approximation algorithm for the problem, where r is the maximum number of search results that are relevant to any user type. the algorithm is based on a new technique, which we call harmonic interpolation. in addition, we consider two important special cases. the first case is when the profile vector of each user type is non-increasing. this case is a generalization of the well-known min-sum set cover problem. we extend the techniques of feige, lovasz and tetali (algorithmica '04), and present an algorithm achieving 4-approximation. the second case is when the profile vector of each user type is non-decreasing. this case generalizes the minimum latency set cover problem, introduced by hassin and levin (esa '05). we devise an lp-based algorithm that attains 2-approximation for it.
on the complexity of differentially private data release: efficient algorithms and hardness results. we consider private data analysis in the setting in which a trusted and trustworthy curator, having obtained a large data set containing private information, releases to the public a "sanitization" of the data set that simultaneously protects the privacy of the individual contributors of data and offers utility to the data analyst. the sanitization may be in the form of an arbitrary data structure, accompanied by a computational procedure for determining approximate answers to queries on the original data set, or it may be a "synthetic data set" consisting of data items drawn from the same universe as items in the original data set; queries are carried out as if the synthetic data set were the actual input. in either case the process is non-interactive; once the sanitization has been released the original data and the curator play no further role. for the task of sanitizing with a synthetic dataset output, we map the boundary between computational feasibility and infeasibility with respect to a variety of utility measures. for the (potentially easier) task of sanitizing with unrestricted output format, we show a tight qualitative and quantitative connection between hardness of sanitizing and the existence of traitor tracing schemes.
fault-tolerant spanners for general graphs. the paper concerns graph spanners that are resistant to vertex or edge failures. given a weighted undirected n-vertex graph g=(v,e) and an integer k ≥ 1, the subgraph h=(v,e'), e'⊆ e, is a spanner of stretch k (or, a k-spanner) of g if δh(u,v) ≤ k· δg(u,v) for every u,v ∈ v, where δg'(u,v) denotes the distance between u and v in g'. graph spanners were extensively studied since their introduction over two decades ago. it is known how to efficiently construct a (2k-1)-spanner of size o(n1+1/k), and this size-stretch tradeoff is conjectured to be tight. the notion of fault tolerant spanners was introduced a decade ago in the geometric setting [levcopoulos et al., stoc'98]. a subgraph h is an f-vertex fault tolerant k-spanner of the graph g if for any set f⊆ v of size at most f and any pair of vertices u,v ∈ v \ f, the distances in h satisfy δh \ f(u,v) ≤ k· δg \ f(u,v). levcopoulos et al. presented an efficient algorithm that given a set s of n points in rd, constructs an f-vertex fault tolerant geometric (1+ε)-spanner for s, that is, a sparse graph h such that for every set f⊆ s of size f and any pair of points u,v ∈ s \ f, δh \ f(u,v) ≤ (1+ε) |uv|, where |uv| is the euclidean distance between u and v. a fault tolerant geometric spanner with optimal maximum degree and total weight was presented in [czumaj &#; zhao, socg'03]. this paper also raised as an open problem the question whether it is possible to obtain a fault tolerant spanner for an arbitrary undirected weighted graph. the current paper answers this question in the affirmative, presenting an f-vertex fault tolerant (2k-1)-spanner of size o(f2 kf+1 · n1+1/klog1-1/kn). interestingly, the stretch of the spanner remains unchanged while the size of the spanner only increases by a factor that depends on the stretch k, on the number of potential faults f, and on logarithmic terms in n. in addition, we consider the simpler setting of f-edge fault tolerant spanners (defined analogously). we present an f-edge fault tolerant 2k-1 spanner with edge set of size o(f· n1+1/k) (only f times larger than standard spanners). for both edge and vertex faults, our results are shown to hold when the given graph g is weighted.
every planar graph is the intersection graph of segments in the plane: extended abstract. given a set s of segments in the plane, the intersection graph of s is the graph with vertex set s in which two vertices are adjacent if and only if the corresponding two segments intersect. we prove a conjecture of scheinerman (phd thesis, princeton university, 1984) that every planar graph is the intersection graph of some segments in the plane.
finding, minimizing, and counting weighted subgraphs. for a pattern graph h on k nodes, we consider the problems of finding and counting the number of (not necessarily induced) copies of h in a given large graph g on n nodes, as well as finding minimum weight copies in both node-weighted and edge-weighted graphs. our results include: the number of copies of an h with an independent set of size s can be computed exactly in o*(2s nk-s+3) time. a minimum weight copy of such an h (with arbitrary real weights on nodes and edges) can be found in o(4s+o(s) nk-s+3) time. (the o* notation omits (k) factors.) these algorithms rely on fast algorithms for computing the permanent of a k x n matrix, over rings and semirings. the number of copies of any h having minimum (or maximum) node-weight (with arbitrary real weights on nodes) can be found in o(nω k/3 + n2k/3+o(1)) time, where ω edge-weighted triangle of weight exactly 0 in general graphs requires ω(n2.5-ε) time for all ε > 0, unless the 3sum problem on n numbers can be solved in o(n2 - ε) time. this suggests that the edge-weighted problem is much harder than its node-weighted version.
public-key cryptosystems from the worst-case shortest vector problem: extended abstract. we construct public-key cryptosystems that are secure assuming theworst-case hardness of approximating the minimum distance on n-dimensional lattices to within small poly(n) factors. prior cryptosystems with worst-case connections were based either on the shortest vector problem for a special class of lattices (ajtai and dwork, stoc 1997; regev, j. acm 2004), or on the conjectured hardness of lattice problems for quantum algorithms (regev, stoc 2005). our main technical innovation is a reduction from variants of the shortest vector problem to corresponding versions of the "learning with errors" (lwe) problem; previously, only a quantum reduction of this kind was known. as an additional contribution, we construct a natural chosen ciphertext-secure cryptosystem having a much simpler description and tighter underlying worst-case approximation factor than prior schemes.
list decoding tensor products and interleaved codes. we design the first efficient algorithms and prove new combinatorial bounds for list decoding tensor products of codes and interleaved codes. (1) we show that for every code, the ratio of its list decoding radius to its minimum distance stays unchanged under the tensor product operation (rather than squaring, as one might expect). this gives the first efficient list decoders and new combinatorial bounds for some natural codes including multivariate polynomials where the degree in each variable is bounded. (2) we show that for every code, its list decoding radius remains unchanged under m-wise interleaving for an integer m. this generalizes a recent result of dinur.et.al, who proved such a result for interleaved hadamard codes (equivalently, linear transformations). (3)using the notion of generalized hamming weights, we give better list size bounds for both tensoring and interleaving of binary linear codes. by analyzing the weight distribution of these codes, we reduce the task of bounding the list size to bounding the number of close-by low-rank codewords. for decoding linear transformations, using rank-reduction together with other ideas, we obtain tight list size bounds for small fields. our results give better bounds on the list decoding radius than what is obtained from the johnson bound, and yield rather general families of codes decodable beyond the johnson bound.
on proximity oblivious testing. we initiate a systematic study of a special type of property testers. these testers consist of repeating a basic test for a number of times that depends on the proximity parameter, whereas the basic test is oblivious of the proximity parameter. we refer to such basic tests by the term proximity-oblivious testers. while proximity-oblivious testers were studied before - most notably in the algebraic setting - the current study seems to be the first one to focus on graph properties. we provide a mix of positive and negative results, and in particular characterizations of the graph properties that have constant-query proximity-oblivious testers in the two standard models (i.e., the adjacency matrix and the bounded-degree models). furthermore, we show that constant-query proximity-oblivious testers do not exist for many easily testable properties, and that even when proximity-oblivious testers exist, repeating them does not necessarily yield the best standard testers for the corresponding property.
private coresets. a coreset of a point set p is a small weighted set of points that captures some geometric properties of $p$. coresets have found use in a vast host of geometric settings. we forge a link between coresets, and differentially private sanitizations that can answer any number of queries without compromising privacy. we define the notion of private coresets, which are simultaneously both coresets and differentially private, and show how they may be constructed. we first show that the existence of a small coreset with low generalized sensitivity (i.e., replacing a single point in the original point set slightly affects the quality of the coreset) implies (in an inefficient manner) the existence of a private coreset for the same queries. this greatly extends the works of blum, ligett, and roth [stoc 2008] and mcsherry and talwar [focs 2007]. we also give an efficient algorithm to compute private coresets for k-median and k-mean queries in red, immediately implying efficient differentially private sanitizations for such queries. following mcsherry and talwar, this construction also gives efficient coalition proof (approximately dominant strategy) mechanisms for location problems. unlike coresets which only have a multiplicative approximation factor, we prove that private coresets must have an additive error. we present a new technique for showing lower bounds on this error.
differential privacy and robust statistics. we show by means of several examples that robust statistical estimators present an excellent starting point for differentially private estimators. our algorithms use a new paradigm for differentially private mechanisms, which we call propose-test-release (ptr), and for which we give a formal definition and general composition theorems.
multiplicative updates outperform generic no-regret learning in congestion games: extended abstract. we study the outcome of natural learning algorithms in atomic congestion games. atomic congestion games have a wide variety of equilibria often with vastly differing social costs. we show that in almost all such games, the well-known multiplicative-weights learning algorithm results in convergence to pure equilibria. our results show that natural learning behavior can avoid bad outcomes predicted by the price of anarchy in atomic congestion games such as the load-balancing game introduced by koutsoupias and papadimitriou, which has super-constant price of anarchy and has correlated equilibria that are exponentially worse than any mixed nash equilibrium. our results identify a set of mixed nash equilibria that we call weakly stable equilibria. our notion of weakly stable is defined game-theoretically, but we show that this property holds whenever a stability criterion from the theory of dynamical systems is satisfied. this allows us to show that in every congestion game, the distribution of play converges to the set of weakly stable equilibria. pure nash equilibria are weakly stable, and we show using techniques from algebraic geometry that the converse is true with probability 1 when congestion costs are selected at random independently on each edge (from any monotonically parametrized distribution). we further extend our results to show that players can use algorithms with different (sufficiently small) learning rates, i.e. they can trade off convergence speed and long term average regret differently.
intrinsic robustness of the price of anarchy. the price of anarchy (poa) is a worst-case measure of the inefficiency of selfish behavior, defined as the ratio of the objective function value of a worst nash equilibrium of a game and that of an optimal outcome. this measure implicitly assumes that players successfully reach some nash equilibrium. this drawback motivates the search for inefficiency bounds that apply more generally to weaker notions of equilibria, such as mixed nash and correlated equilibria; or to sequences of outcomes generated by natural experimentation strategies, such as successive best responses or simultaneous regret-minimization. we prove a general and fundamental connection between the price of anarchy and its seemingly stronger relatives in classes of games with a sum objective. first, we identify a "canonical sufficient condition" for an upper bound of the poa for pure nash equilibria, which we call a smoothness argument. second, we show that every bound derived via a smoothness argument extends automatically, with no quantitative degradation in the bound, to mixed nash equilibria, correlated equilibria, and the average objective function value of regret-minimizing players (or "price of total anarchy"). smoothness arguments also have automatic implications for the inefficiency of approximate and bayesian-nash equilibria and, under mild additional assumptions, for bicriteria bounds and for polynomial-length best-response sequences. we also identify classes of games --- most notably, congestion games with cost functions restricted to an arbitrary fixed set --- that are tight, in the sense that smoothness arguments are guaranteed to produce an optimal worst-case upper bound on the poa, even for the smallest set of interest (pure nash equilibria). byproducts of our proof of this result include the first tight bounds on the poa in congestion games with non-polynomial cost functions, and the first structural characterization of atomic congestion games that are universal worst-case examples for the poa.
3-query locally decodable codes of subexponential length. locally decodable codes (ldc) allow one to decode any particular symbol of the input message by making a constant number of queries to a codeword, even if a constant fraction of the codeword is damaged. in a recent work [yek08] yekhanin constructs a 3-query ldc with sub-exponential length of size exp(exp(o((log n)/(log log n)))). however, this construction requires a conjecture that there are infinitely many mersenne primes. in this paper we give the first unconditional constant query ldc construction with subexponantial codeword length. in addition our construction reduces codeword length. we give construction of 3-query ldc with codeword length exp(exp(o(√{log n log log n ))). our construction could also be extended to higher number of queries. we give a 2r-query ldc with length of exp(exp(o(☂[r] log n (log log n)r-1))).
exact learning of random dnf over the uniform distribution. we show that randomly generated c log(n)-dnf formula can be learned exactly in probabilistic polynomial time using randomly generated examples. our notion of randomly generated is with respect to a uniform distribution. to prove this we extend the concept of well behaved c log(n)-monotone dnf formulae to c log(n)-dnf formulae, and show that almost every dnf formula is well-behaved, and that there exists a probabilistic polynomial time algorithm that exactly learns all well behaved c log(n)-dnf formula. this is the first algorithm that properly learns (non-monotone) dnf with a polynomial number of terms from random examples alone.
reconstruction for the potts model. the reconstruction problem on the tree plays a key role in several important computational problems. deep conjectures in statistical physics link the reconstruction problem to properties of random constraint satisfaction problems including random k-sat and random colourings of random graphs. at this precise threshold the space of solutions is conjectured to undergo a phase transition from a single collected mass to exponentially many small clusters at which point local search algorithm must fail. in computational biology the reconstruction problem is central in phylogenetics. it has been shown [mossel 04] that solvability of the reconstruction problem is equivalent to phylogenetic reconstruction with short sequences for the binary symmetric model. rigorous reconstruction thresholds, however, have only been established in a small number of models. we confirm conjectures made by mezard and montanari for the potts models proving the first exact reconstruction threshold in a non-binary model establishing the so-called kesten-stigum bound for the 3-state potts model on regular trees of large degree. we further establish that the kesten-stigum bound is not tight for the $q$-state potts model when q ≥ 5. moreover, we determine asymptotics for these reconstruction thresholds.
polynomial-time theory of matrix groups. we consider matrix groups, specified by a list of generators, over finite fields. the two most basic questions about such groups are membership in and the order of the group. even in the case of abelian groups it is not known how to answer these questions without solving hard number theoretic problems (factoring and discrete log); in fact, constructive membership testing in the case of 1 × 1 matrices is precisely the discrete log problem. so the reasonable question is whether these problems are solvable in randomized polynomial time using number theory oracles. building on 25 years of work, including remarkable recent developments by several groups of authors, we are now able to determine the order of a matrix group over a finite field of odd characteristic, and to perform constructive membership testing in such groups, in randomized polynomial time, using oracles for factoring and discrete log. one of the new ingredients of this result is the following. a group is called semisimple if it has no abelian normal subgroups. for matrix groups over finite fields, we show that the order of the largest semisimple quotient can be determined in randomized polynomial time (no number theory oracles required and no restriction on parity). as a by-product, we obtain a natural problem that belongs to bpp and is not known to belong either to rp or to corp. no such problem outside the area of matrix groups appears to be known. the problem is the decision version of the above: given a list a of nonsingular d × d matrices over a finite field and an integer n, does the group generated by a have a semisimple quotient of order > n? we also make progress in the area of constructive recognition of simple groups, with the corollary that for a large class of matrix groups, our algorithms become las vegas.
new direct-product testers and 2-query pcps. the "direct product code" of a function f gives its values on all k-tuples (f(x1),...,f(xk)). this basic construct underlies "hardness amplification" in cryptography, circuit complexity and pcps. goldreich and safra [12] pioneered its local testing and its pcp application. a recent result by dinur and goldenberg [5] enabled for the first time testing proximity to this important code in the "list-decoding" regime. in particular, they give a 2-query test which works for polynomially small success probability 1/kα, and show that no such test works below success probability 1/k. our main result is a 3-query test which works for exponentially small success probability exp(-kα). our techniques (based on recent simplified decoding algorithms for the same code [15]) also allow us to considerably simplify the analysis of the 2-query test of [5]. we then show how to derandomize their test, achieving a code of polynomial rate, independent of k, and success probability 1/kα. finally we show the applicability of the new tests to pcps. starting with a 2-query pcp over an alphabet σ and with soundness error 1-δ, rao [19] (building on raz's (k-fold) parallel repetition theorem [20] and holenstein's proof [13]) obtains a new 2-query pcp over the alphabet σk with soundness error exp(-δ2 k). our techniques yield a 2-query pcp with soundness error exp(-δ √k). our pcp construction turns out to be essentially the same as the miss-match proof system defined and analyzed by feige and kilian [8], but with simpler analysis and exponentially better soundness error.
explicit construction of a small epsilon-net for linear threshold functions. we give explicit constructions of epsilon nets for linear threshold functions on the binary cube and on the unit sphere. the size of the constructed nets is polynomial in the dimension n and in 1/ε. to the best of our knowledge no such constructions were previously known. our results match, up to the exponent of the polynomial, the bounds that are achieved by probabilistic arguments. as a corollary we also construct subsets of the binary cube that have size polynomial in n and covering radius of n/2 - c√{n log n}, for any constant c. this improves upon the well known construction of dual bch codes that only guarantee covering radius of n/2 - c√n.
an improved constant-time approximation algorithm for maximum~matchings. this paper studies approximation algorithms for problems on degree-bounded graphs. let n and d be the number of vertices and the degree bound, respectively. this paper presents an algorithm to approximate the size of some maximal independent set with additive error ε n whose running time is o(d2). using this algorithm, it also shows that there are approximation algorithms for many other problems, e.g., the maximum matching problem, the minimum vertex cover problem, and the minimum set cover problem, that run exponentially faster than existing algorithms with respect to d and 1/ε. its approximation algorithm for the maximum matching problem can be transformed to a testing algorithm for the property of having a perfect matching with two-sided error. on the contrary, it also shows that every one-sided error tester for the property requires at least ω(n) queries.
a competitive algorithm for minimizing weighted flow time on unrelatedmachines with speed augmentation. we consider the online problem of scheduling jobs on unrelated machines so as to minimize the total weighted flow time. this problem has an unbounded competitive ratio even for very restricted settings. in this paper we show that if we allow the machines of the online algorithm to have ε more speed than those of the offline algorithm then we can get an o((1+ε-1)2)-competitive algorithm. our algorithm schedules jobs preemptively but without migration. however, we compare our solution to an offline algorithm which allows migration. our analysis uses a potential function argument which can also be extended to give a simpler and better proof of the randomized immediate dispatch algorithm of chekuri-goel-khanna-kumar for minimizing average flow time on parallel machines.
linear time approximation schemes for the gale-berlekamp game and related minimization problems. we design a linear time approximation scheme for the gale-berlekamp switching game and generalize it to a wider class of dense fragile minimization problems including the nearest codeword problem (ncp) and unique games problem. further applications include, among other things, finding a constrained form of matrix rigidity and maximum likelihood decoding of an error correcting code. as another application of our method we give the first linear time approximation schemes for correlation clustering with a fixed number of clusters and its hierarchical generalization. our results depend on a new technique for dealing with small objective function values of optimization problems and could be of independent interest.
artin automorphisms, cyclotomic function fields, and folded list-decodable codes. algebraic codes that achieve list decoding capacity were recently constructed by a careful "folding" of the reed-solomon code. the "low-degree" nature of this folding operation was crucial to the list decoding algorithm. we show how such folding schemes arise out of the artin-frobenius automorphism at primes in galois extensions. using this approach, we construct new folded algebraic-geometric codes for list decoding based on cyclotomic function fields with a cyclic galois group. such function fields are obtained by adjoining torsion points of the carlitz action of an irreducible m ∈ fq[t]. the reed-solomon case corresponds to the simplest such extension (corresponding to the case m=t). in the general case, we need to descend to the fixed field of a suitable galois subgroup in order to ensure the existence of many degree one places that can be used for encoding. our methods shed new light on algebraic codes and their list decoding, and lead to new codes achieving list decoding capacity. quantitatively, these codes provide list decoding (and list recovery/soft decoding) guarantees similar to folded reed-solomon codes but with an alphabet size that is only polylogarithmic in the block length. in comparison, for folded rs codes, the alphabet size is a large polynomial in the block length. this has applications to fully explicit (with no brute-force search) binary concatenated codes for list decoding up to the zyablov radius.
near-perfect load balancing by randomized rounding. we consider and analyze a new algorithm for balancing indivisible loads on a distributed network with n processors. the aim is minimizing the discrepancy between the maximum and minimum load. in every time-step paired processors balance their load as evenly as possible. the direction of the excess token is chosen according to a randomized rounding of the participating loads. we prove that in comparison to the corresponding model of rabani, sinclair, and wanka (1998) with arbitrary roundings, the randomization yields an improvement of roughly a square root of the achieved discrepancy in the same number of time-steps on all graphs. for the important case of expanders we can even achieve a constant discrepancy in o(log n (log log n)3) rounds. this is optimal up to loglog-factors while the best previous algorithms in this setting either require ©(log2 n) time or can only achieve a logarithmic discrepancy. our new result also demonstrates that with randomized rounding the difference between discrete and continuous load balancing vanishes almost completely.
a unified framework for concurrent security: universal composability from stand-alone non-malleability. we present a unified framework for obtaining universally composable (uc) protocols by relying on stand-alone secure non-malleable commitments. essentially all results on concurrent secure computation--both in relaxed models (e.g., quasi-polynomial time simulation), or with trusted set-up assumptions (e.g., the crs model, the imperfect crs model, or the timing model)--are obtained as special cases of our framework. this not only leads to conceptually simpler solutions, but also to improved set-up assumptions, round-complexity, and computational assumptions. additionally, this framework allows us to consider new relaxed models of security: we show that uc security where the adversary is a uniform ppt but the simulator is allowed to be a non-uniform ppt (i.e., essentially, traditional uc security, but with a non-uniform reduction) is possible without any trusted set-up. this gives the first results on concurrent secure computation without set-up, which can be used for securely computing "computationally-sensitive" functionalities (e.g., data-base queries, "proof of work"-protocols, or playing bridge on the internet).
message passing algorithms and improved lp decoding. linear programming decoding for low-density parity check codes (and related domains such as compressed sensing) has received increased attention over recent years because of its practical performance --coming close to that of iterative decoding algorithms--- and its amenability to finite-blocklength analysis. several works starting with the work of feldman et al. showed how to analyze lp decoding using properties of expander graphs. this line of analysis works for only low error rates, about a couple of orders of magnitude lower than the empirically observed performance. it is possible to do better for the case of random noise, as shown by daskalakis et al. and koetter and vontobel. building on work of koetter and vontobel, we obtain a novel understanding of lp decoding, which allows us to establish a 0.05-fraction of correctable errors for rate-1/2 codes; this comes very close to the performance of iterative decoders and is significantly higher than the best previously noted correctable bit error rate for lp decoding. unlike other techniques, our analysis directly works with the primal linear program and exploits an explicit connection between lp decoding and message passing algorithms. an interesting byproduct of our method is a notion of a "locally optimal" solution that we show to always be globally optimal (i.e., it is the nearest codeword). such a solution can in fact be found in near-linear time by a "re-weighted" version of the min-sum algorithm, obviating the need for linear programming. our analysis implies, in particular, that this re-weighted version of the min-sum decoder corrects up to a 0.05-fraction of errors.
randomly supported independence and resistance. we prove that for any positive integer k, there is a constant ck such that a randomly selected set of ck nk log n boolean vectors with high probability supports a balanced k-wise independent distribution. in the case of k ≤ 2 a more elaborate argument gives the stronger bound ck nk. using a recent result by austrin and mossel this shows that a predicate on t bits, chosen at random among predicates accepting c2 t2 input vectors, is, assuming the unique games conjecture, likely to be approximation resistant. these results are close to tight: we show that there are other constants, ck', such that a randomly selected set of cardinality ck' nk points is unlikely to support a balanced k-wise independent distribution and, for some c>0, a random predicate accepting ct2/log t input vectors is non-trivially approximable with high probability. in a different application of the result of austrin and mossel we prove that, again assuming the unique games conjecture, any predicate on t bits accepting at least (32/33) • 2t inputs is approximation resistant. the results extend from the boolean domain to larger finite domains.
an efficient algorithm for partial order production. we consider the problem of partial order production: arrange the elements of an unknown totally ordered set t into a target partially ordered set s, by comparing a minimum number of pairs in t. special cases of this problem include sorting by comparisons, selection, multiple selection, and heap construction. we give an algorithm performing itlb + o(itlb) + o(n) comparisons in the worst case. here, n denotes the size of the ground sets, and itlb denotes a natural information-theoretic lower bound on the number of comparisons needed to produce the target poset. the overall complexity of our algorithm is polynomial. this answers a question of yao (sicomp, 1989). our strategy is to extend the poset s to a weak order w whose corresponding information-theoretic lower bound is provably not much larger than that for s. taking w instead of s as a target poset, we then solve the problem by applying a multiple selection algorithm that performs not much more than itlb comparisons. we base our analysis on the entropy of the target poset s, a quantity that can be efficiently computed and provides a good estimate of itlb.
bit-probe lower bounds for succinct data structures. we prove lower bounds on the redundancy necessary to represent a set s of objects using a number of bits close to the information-theoretic minimum log2 |s|, while answering various queries by probing few bits. our main results are: to represent n ternary values t ∈ {0,1,2}n in terms of u bits b ∈ {0,1}u while accessing a single value ti ∈ {0,1,2} by probing q bits of b, one needs u ≥ (log2 3)n + n/2o(q). this matches an exciting representation by patrascu (focs 2008), later refined with thorup, where u ≤ (log_2 3)n + n/2ω(q). we also note that results on logarithmic forms imply the lower bound u ≥ (log2 3)n + n/logo(1) n if we access ti by probing one cell of log n bits. to represent sets of size n/3 from a universe of n elements in terms of u bits b ∈ {0,1}u while answering membership queries by probing q bits of b, one needs u ≥ log2 n/(n/3) + n/2o(q) - log n. both results above hold even if the probe locations are determined adaptively. ours are the first lower bounds for these fundamental problems; we obtain them drawing on ideas used in lower bounds for locally decodable codes.
finding sparse cuts locally using evolving sets. a local graph partitioning algorithm finds a set of vertices with small conductance (i.e.~a sparse cut) by adaptively exploring a large graph g, starting from a specified vertex. for the algorithm to be local, its complexity must be bounded in terms of the size of the set it outputs, with at most a weak dependence on n, the number of vertices in g. previous local partitioning algorithms find sparse cuts using random walks and personalized pagerank. in this paper, we introduce a randomized local partitioning algorithm that finds a sparse cut by simulating the volume-biased evolving set process, which is a markov chain on sets of vertices. we prove that for any set of vertices a that has conductance at most φ, and for at least half of the starting vertices in a, our algorithm will output (with probability at least half) a set of conductance o(φ1/2 log1/2 n). the complexity of a local partitioning algorithm is measured by its work/volume ratio, which is the ratio between the computational complexity of the algorithm on a given run, and the volume of the set output. we prove that for our algorithm, the expected value of the work/volume ratio is polylognoparen(φ-1/2). the best previous local partitioning algorithm, due to andersen, chung, and lang, has the same approximation guarantee but a larger work/volume ratio of polylognoparen(φ-1). as an application of our local partitioning algorithm, we construct a fast algorithm for finding balanced cuts. the resulting algorithm takes as input a graph and a fixed value of φ, has complexity polylog{m+nφ-1/2), and returns a cut with conductance o(φ1/2 log1/2 n) and volume at least vφ/2, where vφ is the volume of the largest set in the graph with conductance at most φ.
random graphs and the parity quantifier. the classical zero-one law for first-order logic on random graphs says that for every first-order property φ in the theory of graphs and every p ∈ (0,1), the probability that the random graph g(n, p) satisfies φ approaches either 0 or 1 as n approaches infinity. it is well known that this law fails to hold for any formalism that can express the parity quantifier: for certain properties, the probability that g(n,p) satisfies the property need not converge, and for others the limit may be strictly between 0 and 1. in this work, we capture the limiting behavior of properties definable in first order logic augmented with the parity quantifier, fop, over g(n,p), thus eluding the above hurdles. specifically, we establish the following "modular convergence law": for every fop sentence φ, there are two explicitly computable rational numbers a0, a1, such that for i ∈ {0,1}, as n approaches infinity, the probability that the random graph g(2n+i, p) satisfies φ approaches ai. our results also extend appropriately to fo equipped with modq quantifiers for prime q. in the process of deriving the above theorem, we explore a new question that may be of interest in its own right. specifically, we study the joint distribution of the subgraph statistics modulo 2 of g(n,p): namely, the number of copies, mod 2, of a fixed number of graphs f1, ..., fl of bounded size in g(n,p). we first show that every fop property φ is almost surely determined by subgraph statistics modulo 2 of the above type. next, we show that the limiting joint distribution of the subgraph statistics modulo 2 depends only on n mod 2, and we determine this limiting distribution completely. interestingly, both these steps are based on a common technique using multivariate polynomials over finite fields and, in particular, on a new generalization of the gowers norm that we introduce. the first step above is analogous to the razborov-smolensky method for lower bounds for ac0 with parity gates, yet stronger in certain ways. for instance, it allows us to obtain examples of simple graph properties that are exponentially uncorrelated with every fop sentence, which is something that is not known for ac.
an axiomatic approach to algebrization. non-relativization of complexity issues can be interpreted as giving some evidence that these issues cannot be resolved by "black-box" techniques. in the early 1990's, a sequence of important non-relativizing results was proved, mainly using algebraic techniques. two approaches have been proposed to understand the power and limitations of these algebraic techniques: (1) fortnow [for94] gives a construction of a class of oracles which have a similar algebraic and logical structure, although they are arbitrarily powerful. he shows that many of the non-relativizing results proved using algebraic techniques hold for all such oracles, but he does not show, e.g., that the outcome of the "p vs. np" question differs between different oracles in that class. (2) aaronson and wigderson [aw08] give definitions of algebrizing separations and collapses of complexity classes, by comparing classes relative to one oracle to classes relative to an algebraic extension of that oracle. using these definitions, they show both that the standard collapses and separations "algebrize" and that many of the open questions in complexity fail to "algebrize", suggesting that the arithmetization technique is close to its limits. however, it is unclear how to formalize algebrization of more complicated complexity statements than collapses or separations, and whether the algebrizing statements are, e.g., closed under modus ponens so it is conceivable that several algebrizing premises could imply (in a relativizing way) a non-algebrizing conclusion. in this paper, building on the work of arora, impagliazzo, and vazirani [aiv92], we propose an axiomatic approach to "algebrization", which complements and clarifies the approaches of [for94] and [aw08]. we present logical theories formalizing the notion of algebrizing techniques in the following sense: most known complexity results proved using arithmetization are provable within our theories, while many open questions are independent of the theories. so provability in the proposed theories can serve as a surrogate for provability using the arithmetization technique. our theories extend the [aiv92] theory with a new axiom, arithmetic checkability which intuitively says that all np languages have verifiers that are efficiently computable low-degree polynomials (over the integers). we show the following: (i) arithmetic checkability holds relative to arbitrarily powerful oracles (since fortnow's algebraic oracles from [for94] all satisfy the arithmetic checkability axiom). (ii) most of the algebrizing collapses and separations from [aw08], such as ip=pspace, np ⊂ zkip if one-way functions exist, ma-exp ⊄ p poly, etc., are provable from arithmetic checkability.(iii) many of the open complexity questions (including most of those shown to require non-algebrizing techniques in [aw08]), such as "p vs. np", "np vs. bpp", etc., cannot be proved from arithmetic checkability. (iv) arithmetic checkability is also insufficient to prove one known result, nexp=mip (although relative to an oracle satisfying arithmetic checkability, nexpo restricted to poly-length queries is contained in mipo, mirroring a similar result from [aw08]).
affiliation networks. in the last decade, structural properties of several naturally arising networks (the internet, social networks, the web graph, etc.) have been studied intensively with a view to understanding their evolution. in recent empirical work, leskovec, kleinberg, and faloutsos identify two new and surprising properties of the evolution of many real-world networks: densification (the ratio of edges to vertices grows over time), and shrinking diameter (the diameter reduces over time to a constant). these properties run counter to conventional wisdom, and are certainly inconsistent with graph models prior to their work. in this paper, we present the first model that provides a simple, realistic, and mathematically tractable generative model that intrinsically explains all the well-known properties of the social networks, as well as densification and shrinking diameter. our model is based on ideas studied empirically in the social sciences, primarily on the groundbreaking work of breiger (1973) on bipartite models of social networks that capture the affiliation of agents to societies. we also present algorithms that harness the structural consequences of our model. specifically, we show how to overcome the bottleneck of densification in computing shortest paths between vertices by producing sparse subgraphs that preserve or approximate shortest distances to all or a distinguished subset of vertices. this is a rare example of an algorithmic benefit derived from a realistic graph model. finally, our work also presents a modular approach to connecting random graph paradigms (preferential attachment, edge-copying, etc.) to structural consequences (heavy-tailed degree distributions, shrinking diameter, etc.).
on the geometry of graphs with a forbidden minor. we study the topological simplification of graphs via random embeddings, leading ultimately to a reduction of the gupta-newman-rabinovich-sinclair (gnrs) l1 embedding conjecture to a pair of manifestly simpler conjectures. the gnrs conjecture characterizes all graphs that have an o(1)-approximate multi-commodity max-flow/min-cut theorem. in particular, its resolution would imply a constant factor approximation for the general sparsest cut problem in every family of graphs which forbids some minor. in the course of our study, we prove a number of results of independent interest.
on the convergence of regret minimization dynamics in concave games. we study a general sub-class of concave games which we call socially concave games. we show that if each player follows any no-external regret minimization procedure then the dynamics will converge in the sense that both the average action vector will converge to a nash equilibrium and that the utility of each player will converge to her utility in that nash equilibrium. we show that many natural games are indeed socially concave games. specifically, we show that linear cournot competition and linear resource allocation games are socially-concave games, and therefore our convergence result applies to them. in addition, we show that a simple best response dynamics might diverge for linear resource allocation games, and is known to diverge for linear cournot competition. for the tcp congestion games we show that "near" the equilibrium the games are socially-concave, and using our general methodology we show the convergence of a specific regret minimization dynamics.
the work of leslie valiant. on saturday, may 30, one day before the start of the regular stoc 2009 program, a workshop was held in celebration of leslie valiant's 60th birthday. talks were given by jin-yi cai, stephen cook, vitaly feldman, mark jerrum, michael kearns, mike paterson, michael rabin, rocco servedio, paul valiant, vijay vazirani, and avi wigderson. the workshop was organized by michael kearns, rocco servedio, and salil vadhan, with support from the stoc local arrangements team and program committee. to accompany the workshop, here we briefly survey valiant's many fundamental contributions to the theory of computing.
integrality gaps for sherali-adams relaxations. we prove strong lower bounds on integrality gaps of sherali-adams relaxations for max cut, vertex cover, sparsest cut and other problems. our constructions show gaps for sherali-adams relaxations that survive nδ rounds of lift and project. for max cut and vertex cover, these show that even nδ rounds of sherali-adams do not yield a better than 2-ε approximation. the main combinatorial challenge in constructing these gap examples is the construction of a fractional solution that is far from an integer solution, but yet admits consistent distributions of local solutions for all small subsets of variables. satisfying this consistency requirement is one of the major hurdles to constructing sherali-adams gap examples. we present a modular recipe for achieving this, building on previous work on metrics with a local-global structure. we develop a conceptually simple geometric approach to constructing sherali-adams gap examples via constructions of consistent local sdp solutions. this geometric approach is surprisingly versatile. we construct sherali-adams gap examples for unique games based on our construction for max cut together with a parallel repetition like procedure. this in turn allows us to obtain sherali-adams gap examples for any problem that has a unique games based hardness result (with some additional conditions on the reduction from unique games). using this, we construct 2-ε gap examples for maximum acyclic subgraph that rules out any family of linear constraints with support at most nδ.
sherali-adams relaxations of the matching polytope. we study the sherali-adams lift-and-project hierarchy of linear programming relaxations of the matching polytope. our main result is an asymptotically tight expression 1+1/k for the integrality gap after k rounds of this hierarchy. the result is derived by a detailed analysis of the lp after k rounds applied to the complete graph k_{2d+1}. we give an explicit recurrence for the value of this lp, and hence show that its gap exhibits a "phase transition," dropping from close to its maximum value 1+1/2d to close to 1 around the threshold k=2d-θ(√d). we also show that the rank of the matching polytope (i.e., the number of sherali-adams rounds until the integer polytope is reached) is exactly 2d-1.
affine dispersers from subspace polynomials. an affine disperser over f2n for sources of dimension d is a function f: f2n → f2 such that for any affine space s ⊆ f2n of dimension at least d, we have {f(s) : s in s} = f2. affine dispersers have been considered in the context of deterministic extraction of randomness from structured sources of imperfect randomness. previously, explicit constructions of affine dispersers were known for every d = ω(n), due to barak et. al.[2] and bourgain[10] (the latter in fact gives stronger objects called affine extractors). in this work we give the first explicit affine dispersers for sublinear dimension. specifically, our dispersers work even when d = ω(n4/5). the main novelty in our construction lies in the method of proof, which relies on elementary properties of subspace polynomials. in contrast, the previous works mentioned above relied on sum-product theorems for finite fields.
max cut and the smallest eigenvalue. we describe a new approximation algorithm for max cut. our algorithm runs in ~o(n2) time, where n is the number of vertices, and achieves an approximation ratio of .531. on instances in which an optimal solution cuts a 1-ε fraction of edges, our algorithm finds a solution that cuts a 1-4√ε + 8ε-o(1) fraction of edges. our main result is a variant of spectral partitioning, which can be implemented in nearly linear time. given a graph in which the max cut optimum is a 1-ε fraction of edges, our spectral partitioning algorithm finds a set s of vertices and a bipartition l,r=s-l of s such that at least a 1-o(√ε) fraction of the edges incident on s have one endpoint in l and one endpoint in r. (this can be seen as an analog of cheeger's inequality for the smallest eigenvalue of the adjacency matrix of a graph.) iterating this procedure yields the approximation results stated above. a different, more complicated, variant of spectral partitioning leads to a polynomial time algorithm that cuts a 1/2 + e-ω(1/ε) fraction of edges in graphs in which the optimum is 1/2 + ε.
online and stochastic survivable network design. consider the edge-connectivity survivable network design problem: given a graph g = (v,e) with edge-costs, and edge-connectivity requirements rij for every pair of vertices i,j, find an (approximately) minimum-cost network that provides the required connectivity. while this problem is known to admit good approximation algorithms in the offline case, no algorithms were known for this problem in the online setting. in this paper, we give a randomized o(rmax log3 n) competitive online algorithm for this edge-connectivity network design problem, where rmax = maxij rij. our algorithms use the standard embeddings of graphs into random subtrees (i.e., into singly connected subgraphs) as an intermediate step to get algorithms for higher connectivity. our results for the online problem give us approximation algorithms that admit strict cost-shares with the same strictness value. this, in turn, implies approximation algorithms for (a) the rent-or-buy version and (b) the (two-stage) stochastic version of the edge-connected network design problem with independent arrivals. for these two problems, if we are in the case when the underlying graph is complete and the edge-costs are metric (i.e., satisfy the triangle inequality), we improve our results to give o(1)-strict cost shares, which gives constant-factor rent-or-buy and stochastic algorithms for these instances.
a new approach to auctions and resilient mechanism design. we put forward a new approach to mechanism design, and exemplify it via a new mechanism guaranteeing significant revenue in unrestricted combinatorial auctions. our mechanism (1) succeeds in a new and very adversarial collusion model; (2) works in a new, equilibrium-less, and very strong solution concept; (3) benchmarks its performance against the knowledge that the players have about each other; (4) is computationally efficient and preserves the players' privacy to an unusual extent.
numerical linear algebra in the streaming model. we give near-optimal space bounds in the streaming model for linear algebra problems that include estimation of matrix products, linear regression, low-rank approximation, and approximation of matrix rank. in the streaming model, sketches of input matrices are maintained under updates of matrix entries; we prove results for turnstile updates, given in an arbitrary order. we give the first lower bounds known for the space needed by the sketches, for a given estimation error ε. we sharpen prior upper bounds, with respect to combinations of space, failure probability, and number of passes. the sketch we use for matrix a is simply sta, where s is a sign matrix. our results include the following upper and lower bounds on the bits of space needed for 1-pass algorithms. here a is an n x d matrix, b is an n x d' matrix, and c := d+d'. these results are given for fixed failure probability; for failure probability δ>0, the upper bounds require a factor of log(1/δ) more space. we assume the inputs have integer entries specified by o(log(nc)) bits, or o(log(nd)) bits. (matrix product) output matrix c with f(atb-c) ≤ ε f(a) f(b). we show that θ(cε-2log(nc)) space is needed. (linear regression) for d'=1, so that b is a vector b, find x so that ax-b ≤ (1+ε) minx' ∈ reald ax'-b. we show that θ(d2ε-1 log(nd)) space is needed. (rank-k approximation) find matrix tak of rank no more than k, so that f(a-tak) ≤ (1+ε) f{a-ak}, where ak is the best rank-k approximation to a. our lower bound is ω(kε-1(n+d)log(nd)) space, and we give a one-pass algorithm matching this when a is given row-wise or column-wise. for general updates, we give a one-pass algorithm needing [o(kε-2(n + d/ε2)log(nd))] space. we also give upper and lower bounds for algorithms using multiple passes, and a sketching analog of the cur decomposition.
short seed extractors against quantum storage. in the classical privacy amplification problem alice and bob share information that is only partially secret towards an eavesdropper charlie. their goal is to distill this information to a shorter string that is completely secret. the classical privacy amplification problem can be solved almost optimally using extractors. an interesting variant of the problem, where the eavesdropper charlie is allowed to keep quantum information rather than just classical information, was introduced by konig, maurer and renner. in this setting, the eavesdropper charlie may entangle himself with the input (without changing it) and the only limitation charlie has is that it may keep at most b qubits of storage. a natural question is whether there are classical extractors that are good even against quantum storage. recent work has shown that some classical extractors miserably fail against quantum storage. at the same time, it was shown that some other classical extractors work well even against quantum storage, but all these extractors had a large seed length that was either as large as the extractor output, or as large as the quantum storage available to the eavesdropper. in this paper we show that a modified version of trevisan's extractor is good even against quantum storage, thereby giving the first such construction with logarithmic seed length. the technique we use is a combination of trevisan's approach of constructing an extractor from a black-box pseudorandom generator, together with locally list-decodable codes and previous work done on quantum random access codes.
the detectability lemma and quantum gap amplification. the quantum analogue of the constraint satisfaction problem is the fundamental physics question of finding the minimal energy state of a local hamiltonian --- each term of the hamiltonian specifies a local constraint whose violation contributes to the energy of the given quantum state. however, in general it is not meaningful to ask for the probability that a given quantum state violates at least one constraint; the difficulty being that the terms of the hamiltonian do not commute. we show how to make sense of this notion under mild restrictions on the form of the hamiltonian. we then provide two main results. we first prove the quantum detectability lemma, which states that the probability of detecting a violation of a constraint in a local hamiltonian system is bounded from below by some constant times the minimal energy of the system. the proof reveals some intrinsic structure of the hilbert space of local hamiltonians, which is captured in the "exponential decay" lemma, and formalized using a novel decomposition of the hilbert space called the xy decomposition. as an application of the detectability lemma, we prove our second main result: a quantum analogue of the classical gap amplification lemma using random walks over expander graphs, which was the seed for dinur's celebrated new proof of the pcp theorem [6]. we hope that these results will pave the way to better understandings of the computational properties of local hamiltonians systems, and to the evolving field of quantum hamiltonian complexity.
conditional hardness for satisfiable 3-csps. in this paper we study a fundamental open problem in the area of probabilistic checkable proofs: what is the smallest s such that np ⊆ napcp1,s[o(log n),3]? in the language of hardness of approximation, this problem is equivalent to determining the smallest s such that getting an s-approximation for satisfiable 3-bit constraint satisfaction problems ("3-csps") is np-hard. the previous best upper bound and lower bound for s are 20/27+µ by khot and saket [ks06], and 5/8 (assuming np subseteq bpp) by zwick [zwi98]. in this paper we close the gap assuming khot's d-to-1 conjecture. formally, we prove that if khot's d-to-1 conjecture holds for any finite constant integer d, then np napcp1,5/8+ µ[o(log n),3] for any constant µ > 0. our conditional result also solves hastad's open question [has01] on determining the inapproximability of satisfiable max-ntw ("not two") instances and confirms zwick's conjecture [zwi98] that the 5/8-approximation algorithm for satisfiable 3-csps is optimal.
random walks on polytopes and an affine interior point method for linear programming. let k be a polytope in rn defined by m linear inequalities. we give a new markov chain algorithm to draw a nearly uniform sample from k. the underlying markov chain is the first to have a mixing time that is strongly polynomial when started from a "central" point x0. if s is the supremum over all chords pq passing through x0 of (|p-x0|)/(|q-x0|) and ε is an upper bound on the desired total variation distance from the uniform, it is sufficient to take o(m n( n log (s m) + log 1/ε)) steps of the random walk. we use this result to design an affine interior point algorithm that does a single random walk to solve linear programs approximately. more precisely, suppose q = {z | bz ≤ 1} contains a point z such that ct z ≥ d and r := supz ∈ q |bz| + 1, where b is an m x n matrix. then, after τ = o(mn (n ln(mr/ε) + ln 1/δ)) steps, the random walk is at a point xτ for which ct xτ ≥ d(1-ε) with probability greater than 1-δ. the fact that this algorithm has a run-time that is provably polynomial is notable since the analogous deterministic affine algorithm analyzed by dikin has no known polynomial guarantees.
a deterministic reduction for the gap minimum distance problem: [extended abstract]. determining the minimum distance of a linear code is one of the most important problems in algorithmic coding theory. the exact version of the problem was shown to be np-complete in [14]. in [8], the gap version of the problem was shown to be np-hard for any constant factor under a randomized reduction. it was shown in the same paper that the minimum distance problem is not approximable in randomized polynomial time to the factor 2log1-ε n unless np ⊆ rtime(2polylog(n)). in this paper, we derandomize the reduction and thus prove that there is no deterministic polynomial time algorithm to approximate the minimum distance to any constant factor unless p=np. we also prove that the minimum distance is not approximable in deterministic polynomial time to the factor 2log1-εn unless np ⊆ dtime(2polylog(n)). as the main technical contribution, for any constant 2/3
testing juntas nearly optimally. a function on n variables is called a k-junta if it depends on at most k of its variables. in this article, we show that it is possible to test whether a function is a k-junta or is "far" from being a k-junta with o(kε + k log k ) queries, where epsilon is the approximation parameter. this result improves on the previous best upper bound of o (k3/2)ε queries and is asymptotically optimal, up to a logarithmic factor. we obtain the improved upper bound by introducing a new algorithm with one-sided error for testing juntas. notably, the algorithm is a valid junta tester under very general conditions: it holds for functions with arbitrary finite domains and ranges, and it holds under any product distribution over the domain. a key component of the analysis of the new algorithm is a new structural result on juntas: roughly, we show that if a function f is "far" from being a k-junta, then f is "far" from being determined by k parts in a random partition of the variables. the structural lemma is proved using the efron-stein decomposition method.
fully homomorphic encryption using ideal lattices. we propose a fully homomorphic encryption scheme -- i.e., a scheme that allows one to evaluate circuits over encrypted data without being able to decrypt. our solution comes in three steps. first, we provide a general result -- that, to construct an encryption scheme that permits evaluation of arbitrary circuits, it suffices to construct an encryption scheme that can evaluate (slightly augmented versions of) its own decryption circuit; we call a scheme that can evaluate its (augmented) decryption circuit bootstrappable. next, we describe a public key encryption scheme using ideal lattices that is almost bootstrappable. lattice-based cryptosystems typically have decryption algorithms with low circuit complexity, often dominated by an inner product computation that is in nc1. also, ideal lattices provide both additive and multiplicative homomorphisms (modulo a public-key ideal in a polynomial ring that is represented as a lattice), as needed to evaluate general circuits. unfortunately, our initial scheme is not quite bootstrappable -- i.e., the depth that the scheme can correctly evaluate can be logarithmic in the lattice dimension, just like the depth of the decryption circuit, but the latter is greater than the former. in the final step, we show how to modify the scheme to reduce the depth of the decryption circuit, and thereby obtain a bootstrappable encryption scheme, without reducing the depth that the scheme can evaluate. abstractly, we accomplish this by enabling the encrypter to start the decryption process, leaving less work for the decrypter, much like the server leaves less work for the decrypter in a server-aided cryptosystem.
the extended bg-simulation and the characterization of t-resiliency. a distributed task t on n processors is an input/output relation between a collection of processors' inputs and outputs. while all tasks are solvable if no processor may ever crash, the flp result revealed that the possibility of a failure of just a single processor precludes a solution to the task of consensus. that is consensus is not solvable 1-resiliently. yet, some nontrivial tasks are wait-free solvable, i.e. n-1-resiliently. what tasks are solvable if at most t processors may crash? i.e. what tasks are solvable t-resiliently? the herlihy-shavit condition characterizes wait-free solvability, i.e., when t=n-1. the borowsky-gafni (bg) simulation extends this characterization to the t-resilient case for the case "colorless" tasks - tasks like consensus in which one processor can adopt the output of any other processor. it does this by reducing questions about t-resilient solvability, to a question of wait-free solvability. the latter question has been characterized. in this paper, we amend the bg-simulation to result in the extended-bg-simulation, an extension that yields a full characterization of t-resilient solvability: a task t on n processors is solvable t-resiliently iff all tasks t' on t+1 simulators s0,..., st created as follows are wait-free solvable. simulator si is given an input of processor pi as well as the input to a set of processors of size n-(t+1) with ids higher than i. simulator si outputs for pi as well as for a (possibly different) set of processors of size n-(t+1) with ids higher than i. the input/output of the t+1 simulators have to be a projection of a single original input/output tuple-pair in t. we demonstrate the convenience that the characterization provides, in two ways. first, we prove a new equivalence result: we show that n processes can solve t-resiliently weak renaming with n+(t+1)-2 names, where n>1 and 0
on oblivious ptas's for nash equilibrium. if a class of games is known to have a nash equilibrium with probability values that are either zero or ω(1) -- and thus with support of bounded size -- then obviously this equilibrium can be found exhaustively in polynomial time. somewhat surprisingly, we show that there is a ptas for the class of games whose equilibria are guaranteed to have small --- o(1/n) -- values, and therefore large -- ω(n) -- supports. we also point out that there is a ptas for games with sparse payoff matrices, a family for which the exact problem is known to be ppad-complete [chen, deng, teng 2006]. both algorithms are of a special kind that we call oblivious: the algorithm just samples a fixed distribution on pairs of mixed strategies, and the game is only used to determine whether the sampled strategies comprise an ε-nash equilibrium; the answer is "yes" with inverse polynomial probability (in the second case, the algorithm is actually deterministic). these results bring about the question: is there an oblivious ptas for finding a nash equilibrium in general games? we answer this question in the negative; our lower bound comes close to the quasi-polynomial upper bound of [lipton, markakis, mehta 2003]. another recent ptas for anonymous games [daskalakis, papadimitriou 2007 and 2008, daskalakis 2008] is also oblivious in a weaker sense appropriate for this class of games (it samples from a fixed distribution on unordered collections of mixed strategies), but its running time is exponential in 1/ε. we prove that any oblivious ptas for anonymous games with two strategies and three player types must have 1/εα in the exponent of the running time for some α ≥ 1/3, rendering the algorithm in [daskalakis 2008] (which works with any bounded number of player types) essentially optimal within oblivious algorithms. in contrast, we devise a poly n • (1/ε)o(\log2(1/ε)) non-oblivious ptas for anonymous games with two strategies and any bounded number of player types. the key idea of our algorithm is to search not over unordered sets of mixed strategies, but over a carefully crafted set of collections of the first o(log 1/ε) moments of the distribution of the number of players playing strategy 1 at equilibrium. the algorithm works because of a probabilistic result of more general interest that we prove: the total variation distance between two sums of independent indicator random variables decreases exponentially with the number of moments of the two sums that are equal, independent of the number of indicators.
maxmin allocation via degree lower-bounded arborescences. we consider the problem of maxmin allocation of indivisible goods. there are m items to be distributed among n players. each player $i$ has a nonnegative valuation pij for an item j, and the goal is to allocate items to players so as to maximize the minimum total valuation received by each player. there is a large gap in our understanding of this problem. the best known positive result is an ~o(√ n)-approximation algorithm, while there is only a factor 2 hardness known. better algorithms are known for the restricted assignment case where each item has exactly one nonzero value for the players. we study the effect of bounded degree for items: each item has a nonzero value for at most d players. we show that essentially the case d = 3 is equivalent to the general case, and give a 4-approximation algorithm for d = 2. the current algorithmic results for maxmin allocation are based on a complicated lp relaxation called the configuration lp. we present a much simpler lp which is equivalent in power to the configuration lp. we focus on a special case of maxmin allocation-a family of instances on which this lp has a polynomially large gap. the technical core of our result for this case comes from an algorithm for an interesting new optimization problem on directed graphs, maxmindegree arborescence, where the goal is to produce an arborescence of large outdegree. we develop an nε-approximation for this problem that runs in no(1/ε) time and obtain a a polylogarithmic approximation that runs in quasipolynomial time, using a lift-and-project inspired lp formulation. in fact, we show that our results imply a rounding algorithm for the relaxations obtained by t rounds of the sherali-adams hierarchy applied to a natural lp relaxation of the problem. roughly speaking, the integrality gap of the relaxation obtained from t rounds of sherali-adams is at most n1/t. we are able to extend the latter result to a more general class of instances. along the way, we prove a result about the existence of a perfect matching in a probabilistically pruned graph which may be of independent interest.
mixing time for the solid-on-solid model. we analyze the mixing time of a natural local markov chain (the glauber dynamics) on configurations of the solid-on-solid model of statistical physics. this model has been proposed, among other things, as an idealization of the behavior of contours in the ising model at low temperatures. our main result is an upper bound on the mixing time of o~(n3.5), which is tight within a factor of o~(√n). the proof, which in addition gives insight into the actual evolution of the contours, requires the introduction of several novel analytical techniques that we conjecture will have other applications.
a nearly optimal oracle for avoiding failed vertices and edges. we present an improved oracle for the distance sensitivity problem. the goal is to preprocess a directed graph g = (v,e) with non-negative edge weights to answer queries of the form: what is the length of the shortest path from x to y that does not go through some failed vertex or edge f. the previous best algorithm produces an oracle of size ~o(n2) that has an o(1) query time, and an ~o(n2√m) construction time. it was a randomized monte carlo algorithm that worked with high probability. our oracle also has a constant query time and an ~o(n2) space requirement, but it has an improved construction time of ~o(mn), and it is deterministic. note that o(1) query, o(n2) space, and o(mn) construction time is also the best known bound (up to logarithmic factors) for the simpler problem of finding all pairs shortest paths in a weighted, directed graph. thus, barring improved solutions to the all pairs shortest path problem, our oracle is optimal up to logarithmic factors.
non-monotone submodular maximization under matroid and knapsack constraints. submodular function maximization is a central problem in combinatorial optimization, generalizing many important problems including max cut in directed/undirected graphs and in hypergraphs, certain constraint satisfaction problems, maximum entropy sampling, and maximum facility location problems. unlike submodular minimization, submodular maximization is np-hard. in this paper, we give the first constant-factor approximation algorithm for maximizing any non-negative submodular function subject to multiple matroid or knapsack constraints. we emphasize that our results are for non-monotone submodular functions. in particular, for any constant k, we present a (1/k+2+1/k+ε)-approximation for the submodular maximization problem under k matroid constraints, and a (1/5-ε)-approximation algorithm for this problem subject to k knapsack constraints (ε>0 is any constant). we improve the approximation guarantee of our algorithm to 1/k+1+{1/k-1}+ε for k≥2 partition matroid constraints. this idea also gives a ({1/k+ε)-approximation for maximizing a monotone submodular function subject to k≥2 partition matroids, which improves over the previously best known guarantee of 1/k+1.
twice-ramanujan sparsifiers. we prove that every graph has a spectral sparsifier with a number of edges linear in its number of vertices. as linear-sized spectral sparsifiers of complete graphs are expanders, our sparsifiers of arbitrary graphs can be viewed as generalizations of expander graphs. in particular, we prove that for every d > 1 and every undirected, weighted graph g = (v,e,w) on n vertices, there exists a weighted graph h=(v,f,~{w}) with at most ⌈d(n-1)⌉ edges such that for every x ∈ rv, [xt lg x ≤ xt lh x ≤ ((d+1+2√d)/(d+1-2√d)) • xt lg x] where lg and lh are the laplacian matrices of g and h, respectively. thus, h approximates g spectrally at least as well as a ramanujan expander with dn/2 edges approximates the complete graph. we give an elementary deterministic polynomial time algorithm for constructing h.
csp gaps and reductions in the lasserre hierarchy. we study integrality gaps for sdp relaxations of constraint satisfaction problems, in the hierarchy of sdps defined by lasserre. schoenebeck [23] recently showed the first integrality gaps for these problems, showing that for max k-xor, the ratio of the sdp optimum to the integer optimum may be as large as 2 even after ω(n) rounds of the lasserre hierarchy. we show that for the general max k-csp problem, this ratio can be as large as 2k/2k - ε when the alphabet is binary and qk/q(q-1)k - ε when the alphabet size a prime q, even after ω(n) rounds of the lasserre hierarchy. we also explore how to translate gaps for csp into integrality gaps for other problems using reductions, and establish sdp gaps for maximum independent set, approximate graph coloring, chromatic number and minimum vertex cover. for independent set and chromatic number, we show integrality gaps of n/2o(√(log n log log n)) even after 2ω(√(log n log log n)) rounds. in case of approximate graph coloring, for every constant l, we construct graphs with chromatic number ω(2l/2/l2), which admit a vector l-coloring for the sdp obtained by ω(n) rounds. for vertex cover, we show an integrality gap of 1.36 for ω(nδ) rounds, for a small constant δ. the results for csps provide the first examples of ω(n) round integrality gaps matching hardness results known only under the unique games conjecture. this and some additional properties of the integrality gap instance, allow for gaps for in case of independent set and chromatic number which are stronger than the np-hardness results known even under the unique games conjecture.
inaccessible entropy. we put forth a new computational notion of entropy, which measures the (in)feasibility of sampling high entropy strings that are consistent with a given protocol. specifically, we say that the i'th round of a protocol (a,b) has *accessible entropy* at most k, if no polynomial-time strategy a* can generate messages for a such that the entropy of its message in the i'th round has entropy greater than k when conditioned both on prior messages of the protocol and on prior coin tosses of a*. we say that the protocol has *inaccessible entropy* if the total accessible entropy (summed over the rounds) is noticeably smaller than the real entropy of a's messages, conditioned only on prior messages (but not the coin tosses of a). as applications of this notion, we -- give a much simpler and more efficient construction of statistically hiding commitment schemes from arbitrary one-way functions. -- prove that constant-round statistically hiding commitments are necessary for constructing constant-round zero-knowledge proof systems for np that remain secure under parallel composition (assuming the existence of one-way functions).
green's conjecture and testing linear-invariant properties. given a set of linear equations mx=b, we say that a set of integers s is (m,b)-free if it contains no solution to this system of equations. motivated by questions related to testing linear-invariant properties of boolean functions, as well as recent investigations in additive number theory, the following conjecture was raised (implicitly) by green and by bhattacharyya, chen, sudan and xie: we say that a set of integers s ⊆ [n], is ε-far from being (m,b)-free if one needs to remove at least ε n elements from s in order to make it (m,b)-free. the above conjecture states that for any system of homogenous linear equations mx=0 and for any ε >0 there is a constant time algorithm that can distinguish with high probability between sets of integers that are (m,0)-free from sets that are ε-far from being (m,0)-free. or in other words, that for any m there is an efficient testing algorithm for the property of being (m,0)-free. in this paper we confirm the above conjecture by showing that such a testing algorithm exists even for non-homogenous linear equations. as opposed to most results on testing boolean functions, which rely on algebraic and analytic arguments, our proof relies on results from extremal hypergraph theory, such as the recent removal lemmas of gowers, rodl et al. and austin and tao.
non-malleable extractors and symmetric key cryptography from weak secrets. we study the question of basing symmetric key cryptography on weak secrets. in this setting, alice and bob share an n-bit secret w, which might not be uniformly random, but the adversary has at least k bits of uncertainty about it (formalized using conditional min-entropy). since standard symmetric-key primitives require uniformly random secret keys, we would like to construct an authenticated key agreement protocol in which alice and bob use w to agree on a nearly uniform key r, by communicating over a public channel controlled by an active adversary eve. we study this question in the information theoretic setting where the attacker is computationally unbounded. we show that single-round (i.e. one message) protocols do not work when k ≤ n/2, and require poor parameters even when n/2 on the other hand, for arbitrary values of k, we design a communication efficient two-round (challenge-response) protocol extracting nearly k random bits. this dramatically improves the previous construction of renner and wolf [32], which requires θ(λ + log(n)) rounds where λ is the security parameter. our solution takes a new approach by studying and constructing "non-malleable" seeded randomness extractors -- if an attacker sees a random seed x and comes up with an arbitrarily related seed x', then we bound the relationship between r= ext(w;x) and r' = ext(w;x'). we also extend our two-round key agreement protocol to the "fuzzy" setting, where alice and bob share "close" (but not equal) secrets wa and wb, and to the bounded retrieval model (brm) where the size of the secret w is huge.
efficient discrete-time simulations of continuous-time quantum query algorithms. the continuous-time query model is a variant of the discrete query model in which queries can be interleaved with known operations (called "driving operations") continuously in time. we show that any quantum algorithm in this model whose total query time is t can be simulated by a quantum algorithm in the discrete-time query model that makes o(t log t / loglog t) subset o~(t) queries. this is the first such upper bound that is independent of the driving operations (i.e., it holds even if the norm of the driving hamiltonian is very large). a corollary is that any lower bound of t queries for a problem in the discrete-time query model immediately carries over to a lower bound of omega(t loglog t / log t) subset omega~(t) in the continuous-time query model.
non-malleability amplification. we show a technique for amplifying commitment schemes that are non-malleable with respect to identities of length t, into ones that are non-malleable with respect to identities of length ω(2t), while only incurring a constant overhead in round-complexity. as a result we obtain a construction of o(1)log* n-round (i.e., "essentially" constant-round) non-malleable commitments from any one-way function, and using a black-box proof of security.
approximating edit distance in near-linear time. we show how to compute the edit distance between two strings of length n up to a factor of 2(o-tilde(sqrt(log n))) in n(1+o(1)) time. this is the first sub-polynomial approximation algorithm for this problem that runs in near-linear time, improving on the state-of-the-art n(1/3+o(1)) approximation. previously, approximation of 2õ √log n) was known only for embedding edit distance into l1, and it is not known if that embedding can be computed in less than a quadratic time.
universally utility-maximizing privacy mechanisms. a mechanism for releasing information about a statistical database with sensitive data must resolve a trade-off between utility and privacy. publishing fully accurate information maximizes utility while minimizing privacy, while publishing random noise accomplishes the opposite. privacy can be rigorously quantified using the framework of differential privacy, which requires that a mechanism's output distribution is nearly the same whether or not a given database row is included or excluded. the goal of this paper is strong and general utility guarantees, subject to differential privacy. we pursue mechanisms that guarantee near-optimal utility to every potential user, independent of its side information (modeled as a prior distribution over query results) and preferences (modeled via a loss function). our main result is: for each fixed count query and differential privacy level, there is a geometric mechanism m* -- a discrete variant of the simple and well-studied laplace mechanism -- that is simultaneously expected loss-minimizing for every possible user, subject to the differential privacy constraint. this is an extremely strong utility guarantee: every potential user u, no matter what its side information and preferences, derives as much utility from m* as from interacting with a differentially private mechanism mu that is optimally tailored to u. more precisely, for every user u there is an optimal mechanism mu for it that factors into a user-independent part (the geometric mechanism m*) followed by user-specific post-processing that can be delegated to the user itself. the first part of our proof of this result characterizes the optimal differentially private mechanism for a fixed but arbitrary user in terms of a certain basic feasible solution to a linear program with constraints that encode differential privacy. the second part shows that all of the relevant vertices of this polytope (ranging over all possible users) are derivable from the geometric mechanism via suitable remappings of its range.
a new line of attack on the dichotomy conjecture. the well known dichotomy conjecture of feder and vardi states that for every finite family γ of constraints csp(γ) is either polynomially solvable or np-hard. bulatov and jeavons reformulated this conjecture in terms of the properties of the algebra pol(γ), where the latter is the collection of those n-ary operations (n= 1,2,...) that keep all constraints in γ invariant. we show that the algebraic condition boils down to whether there are arbitrarily resilient functions in pol(γ). using this characterization and a result of dinur, friedgut and regev, we give an entirely new and transparent proof to the hell-nesetril theorem, which states that for a simple, connected and undirected graph h, the problem csp(h) is np-hard if and only if h is non-bipartite. we also introduce another notion of resilience (we call it strong resilience), and we use it to characterize csp problems that 'do not have the ability to count.' very recently this class has been shown to be equivalent with the the class of bounded width problems, i.e. the class of csps that be described by existential k-pebble games. what emerges from our research, is that certain important algebraic conditions that are usually expressed via identities have equivalent definitions that rely on asymptotic properties of term operations. our new notions have a potential to show hardness of csps (as demonstrated on the hell-nesetril theorem), or to prove their tractability.
tight lower bounds for greedy routing in uniform small world rings. we consider augmented ring-based networks with vertices 0,...,n-1, where each vertex is connected to its left and right neighbor and possibly to some further vertices (called long range contacts). the outgoing edges of a vertex v are obtained by choosing a subset d of {1,2,...n-1}, with 1, n-1 in d, at random according to a probability distribution mu on all such d and then for each i in d connecting v to (v+i) mod n by a unidirectional link. the choices for different v are done independently and uniformly in the sense that the same distribution mu is used for all v. the expected number of long range contacts is l=e(|d|)-2. motivated by kleinberg's (2000) small world graph model and packet routing strategies for peer-to-peer networks, the greedy routing algorithm on augmented rings, where a packet sitting in a node v is routed to the neighbor of v closest to the destination of the package, has been investigated thoroughly, both for the "one-sided case", where packets can travel only in one direction, and the "two-sided case", where there is no such restriction. in this paper, for both the one-sided and the two-sided case and for an arbitrary distribution mu, we prove a lower bound of omega((log n)2/l) on the expected number of hops that are needed by the greedy strategy to route a package between two randomly chosen vertices on the ring. this bound is tight for omega(1)
homology flows, cohomology cuts. we describe the first algorithms to compute maximum flows in surface-embedded graphs in near-linear time. specifically, given an undirected graph embedded on an orientable surface of genus g, with two specified vertices s and t, we can compute a maximum (s,t)-flow in o(g7 n log2 n log2 c) time for integer capacities that sum to c, or in (g log n)o(g) n time for real capacities. except for the special case of planar graphs, for which an o(n log n)-time algorithm has been known for 20 years, the best previous time bounds for maximum flows in surface-embedded graphs follow from algorithms for general sparse graphs. our key insight is to optimize the relative homology class of the flow, rather than directly optimizing the flow itself. a dual formulation of our algorithm computes the minimum-cost cycle or circulation in a given (real or integer) homology class.
on the complexity of communication complexity. we consider the following question: given a two-argument boolean function f, represented as an n x n binary matrix, how hard is it to determine the (deterministic) communication complexity of f? we address two aspects of this question. on the computational side, we prove that, under appropriate cryptographic assumptions (such as the intractability of factoring), the deterministic communication complexity of f is hard to approximate to within some constant. under stronger (yet arguably reasonable) assumptions, we obtain even stronger hardness results that match the best known approximation. on the analytic side, we present a family of (two-argument) functions for which determining the deterministic communication complexity (or even obtaining non-trivial lower bounds on it) implies proving circuit lower bounds for some related functions. such connections between circuit complexity and communication complexity were known before (karchmer &#; wigderson, 1988) only in the more involved context of relations (search problems) but not in the context of functions (decision problems). this result, in particular, may explain the difficulty of analyzing the communication complexity of certain functions such as the "clique vs. independent-set" family of functions, introduced by yannakakis (1988).
holant problems and counting csp. we propose and explore a novel alternative framework to study the complexity of counting problems, called holant problems. compared to counting constrained satisfaction problems (csp), it is a refinement with a more explicit role for the function constraints. both graph homomorphism and csp can be viewed as special cases of holant problems. we prove complexity dichotomy theorems in this framework. because the framework is more stringent, previous dichotomy theorems for csp problems no longer apply. indeed, we discover surprising tractable subclasses of counting problems, which could not have been easily specified in the csp framework. the main technical tool we use and develop is holographic reductions. another technical tool used in combination with holographic reductions is polynomial interpolations. the study of holant problems led us to discover and prove a complexity dichotomy theorem for the most general form of boolean csp where every constraint function takes values in the complex number field {c}.
goal state optimization algorithm considering computational resource constraints and uncertainty in task execution time. a search methodology with goal state optimization considering computational resource constraints is proposed. the combination of ''an extended graph search methodology'' and ''parallelization of task execution and online planning'' makes it possible to solve the problem. the uncertainty of the task execution time is also considered. the problem can be solved by utilizing a random-based and/or a greedy-based graph-searching methodology. the proposed method is evaluated using a rearrangement problem of 20 movable objects with uncertainty in the task execution time, and the effectiveness is shown with simulation results.
location estimation for indoor autonomous vehicle navigation by omni-directional vision using circular landmarks on ceilings. a novel approach to location estimation by omni-directional vision for autonomous vehicle navigation in indoor environments using circular landmark information is proposed. a circular-shaped landmark is attached on a ceiling and an omni-directional camera is equipped on a vehicle to take upward-looking omni-directional images of the landmark. this way of image taking reduces possible landmark shape occlusion and image noise creation, which come from the existence of nearby objects or humans surrounding the vehicle. it is shown that the perspective shape of the circular landmark in the omni-directional image may be approximated by an ellipse by analytic formulas with good shape-fitting effect and fast computation speed. the parameters of the ellipse are then used for estimating the location of the vehicle with good precision for navigation guidance. both simulated and real images were tested and good experimental results confirm the feasibility of the proposed approach.
painting robot with multi-fingered hands and stereo vision. in this paper, we describe a painting robot with multi-fingered hands and stereo vision. the goal of this study is for the robot to reproduce the whole procedure involved in human painting. a painting action is divided into three phases: obtaining a 3d model, composing a picture model, and painting by a robot. in this system, various feedback techniques including computer vision and force sensors are used. as experiments, an apple and a human silhouette are painted on a canvas using this system.
mobile robot localization based on ultra-wide-band ranging: a particle filter approach. this article addresses the problem of mobile robot localization using ultra-wide-band (uwb) range measurements. uwb is a radio technology widely used for communications, that is recently receiving increasing attention for positioning applications. in these cases, the position of a mobile transceiver is determined from the distances to a set of fixed, well-localized beacons. though this is a well-known problem in the scientific literature (the trilateration problem), the peculiarities of uwb range measurements (basically, distance errors and multipath effects) demand a different treatment to other similar solutions, as for example, those based on laser. this work presents a thorough experimental characterization of uwb ranges within a variety of environments and situations. from these experiments, we derive a probabilistic model which is then used by a particle filter to combine different readings from uwb beacons as well as the vehicle odometry. to account for the possible offset error due to multipath effects, the state tracked by the particle filter includes the offset of each beacon in addition to the planar robot pose (x,y,@f), both estimated sequentially. we show navigation results for a robot moving in indoor scenarios covered by three uwb beacons that validate our proposal.
spiral: a novel biologically-inspired algorithm for gas/odor source localization in an indoor environment with no strong airflow. this work describes the design and experimental results of an algorithm, designed to localize a gas source in an indoor environment with no strong airflow by using an autonomous agent. this condition exacerbates the patchiness and intermittency of odor distribution, typical of turbulent flows in the presence of strong mean flows. furthermore, no information about the wind can be used to detect the position of the source. in the approach proposed here, the robot moves along spirals. a spiral can be reset and a new one started, based on the information acquired about gas distribution. this enables the robot to get close to the ejecting source, without relying on airflow measurements. results from experiments are also described and discussed, to assess the efficiency of the proposed method.
recognition of human grasps by time-clustering and fuzzy modeling. in this paper, we address the problem of recognition of human grasps for five-fingered robotic hands and industrial robots in the context of programming-by-demonstration. the robot is instructed by a human operator wearing a data glove capturing the hand poses. for a number of human grasps, the corresponding fingertip trajectories are modeled in time and space by fuzzy clustering and takagi-sugeno (ts) modeling. this so-called time-clustering leads to grasp models using time as an input parameter and fingertip positions as outputs. for a sequence of grasps, the control system of the robot hand identifies the grasp segments, classifies the grasps and generates the sequence of grasps shown before. for this purpose, each grasp is correlated with a training sequence. by means of a hybrid fuzzy model, the demonstrated grasp sequence can be reconstructed.
fusion of 2d and 3d sensor data for articulated body tracking. in this article, we present an approach for the fusion of 2d and 3d measurements for model-based person tracking, also known as human motion capture. the applied body model is defined geometrically with generalized cylinders, and is set up hierarchically with connecting joints of different types. the joint model can be parameterized to control the degrees of freedom, adhesion and stiffness. this results in an articulated body model with constrained kinematic degrees of freedom. the fusion approach incorporates this model knowledge together with the measurements, and tracks the target body iteratively with an extended iterative closest point (icp) approach. generally, the icp is based on the concept of correspondences between measurements and model, which is normally exploited to incorporate 3d point cloud measurements. the concept has been generalized to represent and incorporate also 2d image space features. together with the 3d point cloud from a 3d time-of-flight (tof) camera, arbitrary features, derived from 2d camera images, are used in the fusion algorithm for tracking of the body. this gives complementary information about the tracked body, enabling not only tracking of depth motions but also turning movements of the human body, which is normally a hard problem for markerless human motion capture systems. the resulting tracking system, named voodoo is used to track humans in a human-robot interaction (hri) context. we only rely on sensors on board the robot, i.e. the color camera, the tof camera and a laser range finder. the system runs in realtime (~20 hz) and is able to robustly track a human in the vicinity of the robot.
decentralised decision making in heterogeneous teams using anonymous optimisation. this paper considers the scenario where multiple autonomous agents must cooperate in making decisions to minimise a continuous and differentiable team cost function. a distributed and asynchronous optimisation algorithm is presented which allows each agent to incrementally refine their decisions while intermittently communicating with the rest of the team. a convergence analysis provides quantitative requirements on the frequency agents must communicate that is prescribed by the structure of the decision problem. in general the solution method will require every agent to communicate to and have a model of every other agent in the team. to overcome this, a specific subset of systems, called partially separable, is defined. these systems only require each agent to have a combined summary of the rest of the team and allows each agent to communicate locally over an acyclic communication network, greatly increasing the scalability of the system.
kick it with elasticity: safety and performance in human-robot soccer. the robocup community has one definite goal [h. kitano, m. asada, robocup humanoid challenge: that's one small step for a robot, one giant leap for mankind, in: ieee/rsj int. conf. on intelligent robots and systems, iros1998, victoria, pp. 419-424, 1998]: winning against the human world soccer champion team by the year 2050. this implies real tackles and fouls between humans and robots, rising safety concerns for the robots and even more important for the human players. nowadays, similar questions are discussed in the field of physical human-robot interaction (phri), but mainly in the context of industrial and service robotics applications. the first part of our paper is an attempt for a phri view on human-robot soccer. we take scenes from real soccer matches and discuss what could have happened if one of the teams consisted of robots instead of humans. the most important result is that elastic joints are needed to reduce the impact during collisions. the second and third part consider conversely, how the robot can handle the impact of kicking the ball and how it can reach the velocity of human-level soccer. again joint elasticity is the key point. overall, the paper analyzes a vision far ahead. however, all our conclusions are based on concrete simulations, experiments, derivations, or findings from sports science, forensics, and phri.
a variational approach to path planning for hyper-redundant manipulators. motion planning for hyper-redundant manipulators in a complicated and cluttered workspace is a challenging problem. many of the path planning algorithms, based on cell decomposition or potential field, fail due to the high dimensionality and complex nature of the c-space. probabilistic roadmap methods (prm) which have been proven to be successful in high dimensional c-spaces suffer from the drawback of generating paths which involve a lot of redundant motion. in this paper, we propose a path optimizing method to improve a given path in terms of path length and the safety against the collisions, using a variational approach. the capability of variational calculus to optimize a path is demonstrated on a variety of examples. the approach succeeds in providing a good quality path even in high dimensional c-spaces.
holonomy in mobile robots. the search for a simple and accurate odometry is a main concern when working with mobile robots. this article presents a general analysis of the problem and proposes a particular solution to improve the odometry. the three crucial kinematical aspects of mobile robots (mobility, control, and positioning) are reviewed in detail for vehicles based both in conventional and in omnidirectional wheels. the latter case is more suitable from a maneuvering point of view as it provides the robot frame with the three degrees of freedom (dof) of plane motion without singular configurations. moreover, a suitable design of the omnidirectional wheels leads to a strictly invariant jacobian matrix and thus to a linear control equation with constant coefficients. it is shown that such vehicles may have a holonomic behavior when moving under suitable kinematical restrictions without constraining their trajectory. in that case, the odometry is algebraic (instead of integrative) and thus more accurate. an application case is presented.
using probabilistic reasoning over time to self-recognize. using the probabilistic methods outlined in this paper, a robot can learn to recognize its own motor-controlled body parts, or their mirror reflections, without prior knowledge of their appearance. for each item in its visual field, the robot calculates the likelihoods of each of three dynamic bayesian models, corresponding to the categories of ''self'', ''animate other'', or ''inanimate''. each model fully incorporates the object's entire motion history and the robot's whole motor history in constant update time, via the forward algorithm. the parameters for each model are learned in an unsupervised fashion as the robot experiments with its arm over a period of four minutes. the robot demonstrated robust recognition of its mirror image, while classifying the nearby experimenter as ''animate other'', across 20 experiments. adversarial experiments, in which a subject mirrored the robot's motion showed that as long as the robot had seen the subject move for as little as 5 s before mirroring, the evidence was ''remembered'' across a full minute of mimicry.
pure reactive behavior learning using case based reasoning for a vision based 4-legged robot. a traditional problem in robotics is adaptation of developed algorithms to different platforms and sensors, as each of them has its specifics and associated errors. hierarchical control architectures deal with the problem through division of the system into layers, where deliberative processing is performed at high level and low level layers are in charge of dealing with reactive behaviors and adaptation to platform and sensor hardware. specifically, approaches based on the emergent behavior theory rely on building high level behaviors by combining simpler ones that provide intuitive reactive responses to sensory instance. this combination is controlled by higher layers in order to obtain more complex behaviors. unfortunately, low level behaviors might be difficult to develop, specially when dealing with legged robots and sensors like video cameras, where resulting motion is heavily influenced by the robot kinematics and dynamics and sensory input is affected by external conditions, transformations, distortions, noise and motion itself (e.g. the camera bouncing problem). in this paper, we propose a new learning based method to solve most of these problems. it basically consists of creating a reactive behavior by supervisedly driving a robot for a time. during that time, its visual input is reactively associated to commands sent to the robot through a case based reasoning (cbr) behavior builder. thus, the robot learns what the person would do in its situation to achieve a certain goal. this approach has two advantages. first, humans are particularly good at adapting and taking into account the specifics of a given mobile after some use. thus, kinematics and dynamics are absorbed into the casebase along with how the person thinks they should be dealt with by that particular robot. similarly, commands are associated to the input sensor as is, so systematic errors in sensors and motors are also implicitly learnt in the casebase (camera bouncing, distorsions, noise ...). also, different reactive strategies to reach a simple goal can be programmed into the robot by showing, rather than by coding. this is particularly useful because some reactive behaviors are ill-fitted to equations. naturally, cbr allows online adaptation to potential changes after supervised training, so the system is able to learn by itself when working autonomously too. the proposed system has been successfully tested in a 4-legged aibo robot in a controlled environment. to prove that it is adequate to create low level layers for hybrid architectures, two different cbr reactive behaviors have been tested and combined into an emergent one. a deliberative layer could be used to extent the system to more complex environments.
robust visual tracking control system of a mobile robot based on a dual-jacobian visual interaction model. this paper presents a novel design of a robust visual tracking control system, which consists of a visual tracking controller and a visual state estimator. this system facilitates human-robot interaction of a unicycle-modeled mobile robot equipped with a tilt camera. based on a novel dual-jacobian visual interaction model, a robust visual tracking controller is proposed to track a dynamic moving target. the proposed controller not only possesses some degree of robustness against the system model uncertainties, but also tracks the target without its 3d velocity information. the visual state estimator aims to estimate the optimal system state and target image velocity, which is used by the visual tracking controller. to achieve this, a self-tuning kalman filter is proposed to estimate interesting parameters and to overcome the temporary occlusion problem. furthermore, because the proposed method is fully working in the image space, the computational complexity and the sensor/camera modeling errors can be reduced. experimental results validate the effectiveness of the proposed method, in terms of tracking performance, system convergence, and robustness.
an experimental study of distributed robot coordination. coordinating the path of multiple robots along assigned paths is a computationally hard problem with great potential for applications. we here provide a detailed experimental study of a randomized algorithm for scheduling priorities that we have developed, and also compare it with exact and approximated solutions. it turns out that for problems of reasonable size our algorithm exhibits an appealing compromise between speed and quality.
learning to fall: designing low damage fall sequences for humanoid soccer robots. a methodology for the analysis and design of fall sequences of robots that minimize joint/articulation injuries, and the damage of valuable body parts is proposed. these fall sequences can be activated/triggered by the robot in case of a detected unintentional fall or an intentional fall, which are common events in humanoid soccer environments. the methodology is human-based and requires the use of a realistic simulator as development tool. the obtained results show that fall sequences designed using the proposed method produce less damage than standard, uncontrolled falls.
color learning and illumination invariance on mobile robots: a survey. recent developments in sensor technology have made it feasible to use mobile robots in several fields, but robots still lack the ability to accurately sense the environment. a major challenge to the widespread deployment of mobile robots is the ability to function autonomously, learning useful models of environmental features, recognizing environmental changes, and adapting the learned models in response to such changes. this article focuses on such learning and adaptation in the context of color segmentation on mobile robots in the presence of illumination changes. the main contribution of this article is a survey of vision algorithms that are potentially applicable to color-based mobile robot vision. we therefore look at algorithms for color segmentation, color learning and illumination invariance on mobile robot platforms, including approaches that tackle just the underlying vision problems. furthermore, we investigate how the inter-dependencies between these modules and high-level action planning can be exploited to achieve autonomous learning and adaptation. the goal is to determine the suitability of the state-of-the-art vision algorithms for mobile robot domains, and to identify the challenges that still need to be addressed to enable mobile robots to learn and adapt models for color, so as to operate autonomously in natural conditions.
sensor-based guidance control of a continuum robot for a semi-autonomous colonoscopy. due to their compliance and high dexterity, biologically-inspired continuum robots have attracted much interest for applications such as medical surgery, urban search and rescue, de-mining etc. in this paper, we will present an application to medical surgery-colonoscopy by designing a pneumatic-driven flexible robotic manipulator, called colobot. the focus of this paper lies in the sensor-based position control of the colobot for guiding the advancement in a tubular, compliant and slippery environment. the kinematic model related the position of the distal end of the colobot to the actuator inputs which is firstly developed and formulated to control the shape of the colobot through position control of the distal tip. to achieve safe guidance, the ideal position of the tip should be in the central axis of the colon. a method based on a circumscribed circle is proposed to approximate the central position in real-time based on three sensor readings. this position will be used as reference position for the tip to adjust its shape in real time to avoid the contact with tube wall. this proposed approach can be extended to the control of continuum robots in the conditions of a dynamically confined space. the simulation results and experimental results with a curved tube will be presented in order to validate the proposed control strategy.
behavioral control through evolutionary neurocontrollers for autonomous mobile robot navigation. this paper deals with the study of scaling up behaviors in evolutive robotics (er). complex behaviors were obtained from simple ones. each behavior is supported by an artificial neural network (ann)-based controller or neurocontroller. hence, a method for the generation of a hierarchy of neurocontrollers, resorting to the paradigm of layered evolution (le), is developed and verified experimentally through computer simulations and tests in a khepera^^^(r) micro-robot. several behavioral modules are initially evolved using specialized neurocontrollers based on different ann paradigms. the results show that simple behaviors coordination through le is a feasible strategy that gives rise to emergent complex behaviors. these complex behaviors can then solve real-world problems efficiently. from a pure evolutionary perspective, however, the methodology presented is too much dependent on user's prior knowledge about the problem to solve and also that evolution take place in a rigid, prescribed framework. mobile robot's navigation in an unknown environment is used as a test bed for the proposed scaling strategies.
a new paradigm of humanoid robot motion programming based on touch interpretation. most humanoid soccer robot teams design the basic movements of their robots, like walking and kicking, off-line and manually. once these motions are considered satisfactory, they are stored in the robot's memory and played according to a high level behavioral strategy. much time is spent in the development of the movements, and despite the significant progress made in humanoid soccer robots, the interfaces employed for the development of motions are still quite primitive. in order to accelerate development, an intuitive instruction method is desired. we propose the development of robot motions through physical interaction. in this paper we propose a ''teaching by touching'' approach; the human operator teaches a motion by directly touching the robot's body parts like a dance instructor. teaching by directly touching is intuitive for instructors. however, the robot needs to interpret the instructor's intention since tactile communication can be ambiguous. this paper presents a method to learn the interpretation of the touch meaning and investigates, through experiments, a general (shared among different users) and intuitive touch manner.
behavior transition between biped and quadruped walking by using bifurcation. in this research, we focus our discussion on the discontinuous dynamic behavior transition of a walking robot. for the transition, bifurcation of potential function is utilized. we demonstrate the behavior transition of the walking robot between biped and quadruped locomotion as an adaptation to the environment depending on the gradient of a slope. the behavior transition is carried out by using bifurcation of parameters used for control. we also show the effectiveness of hysteresis in the transition.
reference governor for constrained systems with time-varying references. this paper proposes constructing a reference governor for constrained linear systems with time-varying references. the main feature of the constructed reference governor is to simultaneously consider fulfillment of state and control constraints, as well as tracking performance by appropriately managing the reference to be inputted. to achieve constraint fulfillment and to evaluate tracking performance, the reference management is reduced into a convex quadratic programming problem using the concept of a maximal output admissible set. the reference governor is finally obtained in the form of a piecewise affine function of state and reference variables by means of a multi-parametric programming technique. in addition, the effectiveness of the reference governor is demonstrated by numerical and experimental examples of a practical dc position servomechanism with the control constraint.
development of adaptive modular active leg (amal) using bipedal robotics technology. the objective of the work presented here is to develop a low cost active above knee prosthetic device exploiting bipedal robotics technology which will work utilizing the available biological motor control circuit properly integrated with a central pattern generator (cpg) based control scheme. the approach is completely different from the existing active prosthetic devices, designed primarily as standalone systems utilizing multiple sensors and embedded rigid control schemes. in this research, first we designed a fuzzy logic based methodology for offering suitable gait pattern for an amputee, followed by formulating a suitable algorithm for designing a cpg, based on rayleigh's oscillator. an indigenous probe, humanoid gait oscillator detector (hgod) has been designed for capturing gait patterns from various individuals of different height, weight and age. these data are used to design a fuzzy inference system which generates most suitable gait pattern for an amputee. the output of the fuzzy inference system is used for designing a cpg best suitable for the amputee. we then developed a cpg based control scheme for calculating the damping profile in real time for maneuvering a prosthetic device called amal (adaptive modular active leg). also a number of simulation results are presented which show the stable behavior of knee and hip angles and determine the stable limit cycles of the network.
an appearance-based visual compass for mobile robots. localization is one of the most important basic skills of a mobile robot. most approaches, however, still rely either on special sensors or require artificial environments. in this article, a novel approach is presented that can provide compass information for localization, purely based on the visual appearance of a room. a robot using such a visual compass can quickly learn a cylindrical map of the environment, consisting of simple statistical features that can be computed very quickly. the visual compass algorithm is efficient, scalable and can therefore be used in real-time on almost any contemporary robotic platform. extensive experiments on a sony aibo robot have validated that the approach works in a vast variety of environments.
adequate motion simulation and collision detection for soccer playing humanoid robots. in this paper a humanoid robot simulator based on the multi-robot simulation framework (murosimf) is presented. among the unique features of this simulator is the scalability in the level of physical detail in both the robot's motion and sensing systems. it facilitates the development of control software for humanoid robots which is demonstrated for several scenarios from the robocup humanoid robot league. different requirements exist for a humanoid robot simulator. e.g., testing of algorithms for motion control and postural stability require high fidelity of physical motion properties whereas testing of behavior control and role distribution for a robot team requires only a moderate level of detail for real-time simulation of multiple robots. to meet such very different requirements often different simulators are used which makes it necessary to model a robot multiple times and to integrate different simulations with high-level robot control software. murosimf provides the capability of exchanging the simulation algorithms used for each robot transparently, thus allowing a trade-off between computational performance and fidelity of the simulation. it is therefore possible to choose different simulation algorithms which are adequate for the needs of a given simulation experiment, for example, motion simulation of humanoid robots based on kinematical, simplified dynamics or full multi-body system dynamics algorithms. in this paper also the sensor simulation capabilities of murosimf are revised. the methods for motion simulation and collision detection and handling are presented in detail including an algorithm which allows the real-time simulation of the full dynamics of a 21 dof humanoid robot. merits and drawbacks of the different algorithms are discussed in the light of different simulation purposes. the simulator performance is measured and illustrated in various examples, including comparison with experiments of a physical humanoid robot.
adaptive jacobian position/force tracking control of free-flying manipulators. this paper solves the problem of position/force tracking control of a free-flying space manipulator with uncertain kinematics and dynamics. a free-flying manipulator interacting with an uncertain compliant surface is considered. to cope with the uncertainties arising from free-flyer's kinematics, dynamics and surface stiffness and position, an adaptive jacobian controller is devised. the convergence of the force and position tracking errors is proved based on lyapunov stability analysis. numerical simulation is presented to show the performance of the controller.
repetitive motion of redundant robots planned by three kinds of recurrent neural networks and illustrated with a four-link planar manipulator's straight-line example. in this paper, a dual neural network, lvi (linear variational inequalities)-based primal-dual neural network and simplified lvi-based primal-dual neural network are presented for online repetitive motion planning (rmp) of redundant robot manipulators (with a four-link planar manipulator as an example). to do this, a drift-free criterion is exploited in the form of a quadratic performance index. in addition, the repetitive-motion-planning scheme could incorporate the joint physical limits such as joint limits and joint velocity limits simultaneously. such a scheme is finally reformulated as a quadratic program (qp). as qp real-time solvers, the aforementioned three kinds of neural networks all have piecewise-linear dynamics and could globally exponentially converge to the optimal solution of strictly-convex quadratic-programs. furthermore, the neural-network based rmp scheme is simulated based on a four-link planar robot manipulator. computer-simulation results substantiate the theoretical analysis and also show the effective remedy of the joint angle drift problem of robot manipulators.
collaborative coverage using a swarm of networked miniature robots. we study distributed coverage of environments with unknown extension using a team of networked miniature robots analytically and experimentally. algorithms are analyzed by incrementally raising the abstraction level starting from physical robots, to realistic and discrete event system (des) simulation. the realistic simulation is calibrated using sensor and actuator noise characteristics of the real platform and serves for calibration of the des microscopic model. the proposed algorithm is robust to positional noise and communication loss, and its performance gracefully degrades for communication and localization failures to a lower bound, which is given by the performance of a non-coordinated, randomized solution. results are validated by real robot experiments with miniature robots of a size smaller than 2 cmx2 cmx3 cm in a boundary coverage case study. trade-offs between the abilities of the individual platform, required communication, and algorithmic performance are discussed.
observer-based dynamic walking control for biped robots. this article presents a novel observer-based control system to achieve reactive motion generation for dynamic biped walking. the proposed approach combines a feedback controller with an online generated feet pattern to assure a stable gait. using the desired speed of the robot, a preview control system derives the dynamics of the robot's body, and thereby the trajectory of its center of mass, to ensure a zero moment point (zmp) movement, which results in a stable execution of the calculated step pattern. extending the control system by an observer, based on this knowledge and the measured sensor values, compensates for errors in the model parameters and disturbances encountering while walking.
toward a human-like biped robot with compliant legs. conventional models of bipedal walking generally assume rigid body structures, while elastic material properties seem to play an essential role in nature. on the basis of a novel theoretical model of bipedal walking, this paper investigates a model of biped robot which makes use of minimum control and elastic passive joints inspired from the structures of biological systems. the model is evaluated in simulation and a physical robotic platform by analyzing the kinematics and ground reaction force. the experimental results show that, with a proper leg design of passive dynamics and elasticity, an attractor state of human-like walking gait patterns can be achieved through extremely simple control without sensory feedback. the detailed analysis also explains how the dynamic human-like gait can contribute to adaptive biped walking.
conflict-free scheduling and routing of automated guided vehicles in mesh topologies. many storing and manufacturing systems tend to use automated guided vehicles (agv) for speed, quality and safety as transporting objects. in this paper an integrated algorithm for scheduling and routing of agvs in mesh-like systems is presented. the main characteristics of the scheduling algorithm are as follows: (1) prediction and prevention of conflicts, (2) arbitrary choice for agvs to traverse shortest path from source to destination, (3) effect of priority policies to the scheduling result, and (4) no theoretical limitation on the number of participated agvs. the proposed greedy algorithm for routing reduces the average number of conflicts and is closely related to the scheduling algorithm. we will also present mathematical and statistical models for the analysis of the algorithms.
optimization of grasping forces in handling of brittle objects. this paper deals with the optimization of grasping brittle objects with a multi-fingered robot hand under general constraints such as finger deformability and object positioning tolerances. first, a general formulation describing hyperstatic grasping is presented. then an optimization criterion based on the minimization of squeezing forces and torques is introduced. and finally results of numerical simulation for grasping with a special three-fingered gripper are presented.
timed trajectory generation using dynamical systems: application to a puma arm. we present an attractor based dynamics that autonomously generates trajectories with stable timing (limit cycle solutions), stably adapted to changing online sensory information. autonomous differential equations are used to formulate a dynamical layer with either stable fixed points or a stable limit cycle. a neural competitive dynamics switches between these two regimes according to sensorial context and logical conditions. the corresponding movement states are then converted by simple coordinate transformations and an inverse kinematics controller into spatial positions of a robot arm. movement initiation and termination is entirely sensor driven. in this article, the dynamic architecture was changed in order to cope with unreliable sensor information by including this information in the vector field. we apply this architecture to generate timed trajectories for a puma arm which must catch a moving ball before it falls over a table, and return to a reference position thereafter. sensory information is provided by a camera mounted on the ceiling over the robot. a flexible behavior is achieved. flexibility means that if the sensorial context changes such that the previously generated sequence is no longer adequate, a new sequence of behaviors, depending on the point at which the changed occurred and adequate to the current situation emerges. the evaluation results illustrate the stability and flexibility properties of the dynamical architecture as well as the robustness of the decision-making mechanism implemented.
singularity avoidance for acrobots based on fuzzy-control strategy. this paper presents a fuzzy-control method for the motion control of an acrobot. first, an explanation is given of the singularity that arises when a motion control law based on a lyapunov function has an integrated control objective for energy and posture. then, a fuzzy controller is designed that solves the singularity problem through regulation of a design parameter in the control law. finally, an additional fuzzy controller is designed that improves the control performance through regulation of another design parameter in the control law. simulation results demonstrate the effectiveness of this integrated fuzzy-control strategy.
robot motion description and real-time management with the harmonic motion description protocol. we describe the harmonic motion description protocol (hmdp), that can serve as a part in tools for rapid prototyping of behaviors in a hybrid simulation real robot environment. in particular, we are focusing on the robocup 3d soccer simulation league server that is currently evolving rapidly, and becomes a more and more useful open source, general purpose simulation environment for physical multiagent systems. hmdp uses harmonic functions to describe motions. it allows for superposition of motions and is therefore capable of describing parametric motions. thus, typical open loop motions (walking on spot, forward, turning, standing up) of small humanoid robots are readily available and can be optimized by hand. in conjunction with the hmdp some software tools and a small real-time motion generator (called motion machine) have been developed. the current implementation is very flexible to use and can easily be implemented in rather small embedded systems.
strategy of approach for seizure of an assistive mobile manipulator. in assistive robotics, a manipulator arm constitutes one possible solution for restoring some manipulation functions to victims of upper limb disabilities. the aim of this paper is to present a global strategy of approach of an assistive mobile manipulator (manipulator arm mounted on a mobile base). a manipulability criterion is defined to deal with the redundancy of the system. the aim is to keep the arm manipulable, i.e. capable of moving by itself. the strategy is based on human-like behaviour to help the disabled operator to understand the action of the robot. when the robot is far from its objective, only the mobile base moves, thus avoiding obstacles if necessary. when the objective is close to the robot, both mobile base and arm move and redundancy can be used to maximise a manipulability criterion. all the situations are tested separately and a global mission is realised in which all the previous situations are encountered. the partial results obtained with the real robot consolidate the results of simulation. this paper does not propose an autonomous path planning and navigation of the mobile arm but an assistance to the user for remote controlling it.
probabilistic instantaneous model-based signal processing applied to localization and tracking. in this paper, a probabilistic approach for estimating time and space-variant parameters of a system, based on sequentially received discrete-time signal values, is presented. the system description is the solution of a linear partial differential equation (pde). the pde describes for example the wave propagation of an acoustic wave in a localization system. the solution of the pde is given by a time-variant and space-variant impulse response. this impulse response is characterized by the time and space-variant parameters in order to track an object, which emits for example an acoustic signal. for estimating the position of the object in an instantaneous way a bayesian approach has to be used, which considers the dynamic behavior of the parameters in a system model and uncertainties in a stochastic manner by means of probability density functions. hence, the new approach provides a probabilistic instantaneous model-based signal processing, where the sequentially measured signal values are processed directly and known reference signal sequences are interpreted as part of a time-variant nonlinear measurement equation.
multi-robot task allocation through vacancy chain scheduling. modeling the effects of robot interaction in multi-robot systems, i.e., the group dynamics, is difficult due to the complexity of such interactions. this article formalizes the concept of group dynamics in the framework of scheduling and presents a proof that multi-robot task allocation (mrta), in systems with significant performance effects from group dynamics, is an np-complete problem. as a way of dealing with this complexity we have developed vacancy chain scheduling (vcs), a new formal model of mrta inspired by a resource distribution process commonly found in nature. vcs is also the foundation of a new mrta algorithm which relies on optimal allocation patterns to emerge from the stigmergic effects of robot interactions. we present experimental evidence of the validity of the vcs model from high-fidelity simulations. the experimental results validate the vcs model by reliably producing the predicted allocation patterns in both homogeneous and heterogeneous groups of robots. the evidence also supports our claim that vcs is a feasible solution for a restricted class of mrta problems.
coordinated pursuer control using particle filters for autonomous search-and-capture. in a real-world pursuit-evasion (pe) game, the pursuers often have a limited field-of-view of the evaders and thus are required to search for and detect the evaders before capturing them. this paper presents a unified framework and control algorithm using particle filters (pfs) for the coordination of multiple pursuers to search for and capture multiple evaders given the ability of pf to estimate highly non-gaussian densities prevalent in search problems. the pursuer control problem is formulated as a stochastic control problem where global objectives function of both searching and capturing are common. to take the evaders' actions into account, an action measure (am) is defined over the evaders' pds is used to represent the probability that the evader may transit each state in the pd. the global objective functions for search and capture are then decomposed into local objective functions for unification through objective priority weights. coordination between the pursuers takes place through the multi-sensor update where the observation likelihoods of all pursuers are used in the pf update stage. the control actions of each pursuer are then determined individually, based on the updated pds given the objective weights, action measures as well as evader importance weights in the case of multiple evaders. the proposed algorithm is tested in three scenarios for its effectiveness. in addition, a parametric study on the average capture time against the initial variances of the target state uncertainty is conducted to test for robustness. results show that the pursuers are able to capture all the evaders in each case with the capture time for the second and last scenario differing by only 2.9% implying firstly that under the proposed algorithm, the capture time is not proportional to the increase in the number of evaders and also suggested robustness and potential scalability of the proposed algorithm.
two-time scale control and observer design for trajectory tracking of two cooperating robot manipulators moving a flexible beam. in this paper, we present two-time scale control design for trajectory tracking of two cooperating planar rigid robots moving a flexible beam, which does not require vibration measurement for the beam. first, the kinematics and dynamics of the robots and the object are derived. then, using the relations between different forces acting on the object by the manipulators' end-effectors, dynamics equations of the robots and the object are combined. the resulting equations show that the coupled dynamics including beam vibration and the rigid motion take place in two different time domains. by applying two-time scale control theory on the combined dynamics, a composite control scheme is elaborated which makes the beam orientation and its center of mass position track a desired trajectory while suppressing the beam vibration. for the controller algorithm, first a slow controller is utilized for the slow (rigid) subsystem and then a fast stabilizing controller is considered for the fast (flexible) subsystem. to avoid requiring measurement of beam vibration for the fast control law, a linear observer is also designed. the simulation results show the efficiency of the proposed control scheme.
self-calibrated visual servoing with respect to axial-symmetric 3d objects. a self-calibrated approach to visual servoing with respect to non-planar targets modeled through a pair of coaxial circles plus one point is discussed. full calibration data (fixed internal parameters) are obtained from two views, and used to recover the euclidean structure of an auxiliary virtual plane associated to the target, together with the relative pose of the camera. pose disambiguation is achieved without requiring any real third view of the target. the approach benefits of an off-line planning strategy by which the camera follows a 3d helicoidal path around an arbitrarily chosen axis. a convenient choice for the helicoidal axis is found to be that of the target axis itself. simulation results demonstrate that the approach is robust with respect to noise both in the off-line and on-line control phases.
comparison of different gaits with rotation of the feet for a planar biped. fast human walking includes a phase where the stance heel rises from the ground and the stance foot rotates about the stance toe. this phase where the biped becomes under-actuated is not present during the walk of humanoid robots. the objective of this study is to determine if this phase is useful to reduce the energy consumed in the walking. in order to study the efficiency of this phase, six cyclic gaits are presented for a planar biped robot. the simplest cyclic motion is composed of successive single support phases with flat stance foot on the ground. the most complex cyclic motion is composed of single support phases that include a sub-phase of rotation of the stance foot about the toe and of finite time double support phase. for the synthesis of these walking gaits, optimal motions with respect to the torque cost, are defined by taking into account given performances of actuators. it is shown that for fast motions a foot rotation sub-phase is useful to reduce the criteria cost. in the optimization process, under-actuated phase (foot rotation phase), fully-actuated phase (flat foot phase) and over-actuated phase (double support phase) are considered.
autonomous collaborative environment for project-based learning. the importance of integrating different disciplines of information science and technology is growing for the realization of an information system which works robustly in the real world. such a system should be achieved by integrating different disciplines, since it is difficult to cover all areas in information science and technology by only one person or group. in order to support collaboration, the autonomous collaborative environment for project- based learning was developed. the environment comprises the workshop ''a hundred hour workshop'' and the community site ''ws100h.net''. novel interdisciplinary technology, fusion of recognition and parallel computation was successfully developed whose collaboration process was autonomous.
fitness functions in evolutionary robotics: a survey and analysis. this paper surveys fitness functions used in the field of evolutionary robotics (er). evolutionary robotics is a field of research that applies artificial evolution to generate control systems for autonomous robots. during evolution, robots attempt to perform a given task in a given environment. the controllers in the better performing robots are selected, altered and propagated to perform the task again in an iterative process that mimics some aspects of natural evolution. a key component of this process-one might argue, the key component-is the measurement of fitness in the evolving controllers. er is one of a host of machine learning methods that rely on interaction with, and feedback from, a complex dynamic environment to drive synthesis of controllers for autonomous agents. these methods have the potential to lead to the development of robots that can adapt to uncharacterized environments and which may be able to perform tasks that human designers do not completely understand. in order to achieve this, issues regarding fitness evaluation must be addressed. in this paper we survey current er research and focus on work that involved real robots. the surveyed research is organized according to the degree of a priori knowledge used to formulate the various fitness functions employed during evolution. the underlying motivation for this is to identify methods that allow the development of the greatest degree of novel control, while requiring the minimum amount of a priori task knowledge from the designer.
control and simulation of a tensegrity-based mobile robot. tensegrity structures can provide a new approach to the construction of mobile robots with different shapes and properties that usual robots, wheeled or legged, do not have. tensegrity are light, deformable structures that may be able to adapt their form to unconstrained environments. the main issue of this paper is twofold, first, to derive appropriate and general dynamic equations of motion to study the movement of such structures in the space; second to demonstrate, by means of simulation, that a tensegrity structure can execute any desired trajectory path by actuating some or all of its elements.
inverse dynamics of the 3-prr planar parallel robot. recursive modelling for the kinematics and dynamics of the known 3-prr planar parallel robot is established in this paper. three identical planar legs connecting to the moving platform are located in a vertical plane. knowing the motion of the platform, we develop first the inverse kinematics and determine the positions, velocities and accelerations of the robot. further, the principle of virtual work is used in the inverse dynamics problem. several matrix equations offer iterative expressions and graphs for the power requirement comparison of each of three actuators in two different actuation schemes: prismatic actuators and revolute actuators. for the same evolution of the moving platform in the vertical plane, the power distribution upon the three actuators depends on the actuating configuration, but the total power absorbed by the set of three actuators is the same, at any instant, for both driving systems. the study of the dynamics of the parallel mechanisms is done mainly to solve successfully the control of the motion of such robotic systems.
a local approach for bayesian fusion: mathematical analysis and agent based conception. an agent based architecture that is modelled on a successfully operating process of the real world-criminal investigation-circumvents high computational costs caused by bayesian fusion by realising a distributed local bayesian fusion approach. the idea underlying local bayesian fusion approaches is to perform bayesian fusion at least not in detail on the whole space that is spanned by the properties-of-interest. local bayesian fusion is mainly based on coarsening and restriction techniques. here, we focus on coarsening. we give an overview over the agent based conception and translate the proposed ideas in a formal mathematical framework.
analysis of skill acquisition process: a case study of arm reaching task. analysis of continuous process of motor learning gives a lot of useful knowledge for the recovery of human motion activities, and functional adaptability in new environment. this paper proposes a valuation index for degree of proficiency, and shows results of motor skill analysis for several arm reaching tasks. the motor skills were evaluated by using the reproducibility of muscle activation patterns, which were represented by using the variance value of the electromyographic (emg) signal patterns, and the motion accuracy. we confirm that the reproducibility is high when the motion accuracy is high, and the various skill acquisition processes exist due to individual difference. we conclude that, the reproducibility is one of the important indices for evaluating the degree of proficiency.
mutual adaptation among man and machine by using f-mri analysis. a prosthetic device for disabled people requires new and reliable robotics technology. this paper describes the interesting reaction of our brain to an adaptable prosthetic system. the adaptable prosthetic system is composed of an emg signal controlled robot hand with an emg pattern recognition learning function for transradial (below elbow) prostheses. the mutual adaptation between the system and the human body is analyzed using functional magnetic resonance imaging (f-mri) in order to clarify the plasticity of the motor and sensory cortex area according to the changes in the prosthetic system. the developed prosthetic hand has 13 dof: three motors on the thumb, two motors for each finger, and two motors for the wrist. the tactile feedback is applied by using surface electrical stimulus. the f-mri data shows the process of replacement from a phantom limb image to the prosthetic hand image.
hrp-2w: a humanoid platform for research on support behavior in daily life environments. we introduce a concept of a real-world-oriented humanoid robot that can support humans' activities in daily life. in such environments, robots have to watch humans, understand their behavior, and support their daily life tasks. in particular, these robots must be capable of such real-world behavior as handling tableware and delivering daily commodities by hand. we developed a humanoid robot, hrp-2w, which has an upper body of hrp-2 [k. kaneko, f. kanehiro, s. kajita, h. hirukawa, t. kawasaki, m. hirata, k. akachi, t. isozumi, humanoid robot hrp-2, in: proceedings of the 2004 ieee international conference on robotics & automation, 2004, pp. 1083-1090] and a wheel module instead of legs, as a research platform to fulfill this aim. we also developed basic software configuration in order to integrate our platform with other research groups. through experiments, we demonstrated the feasibility of the humanoid robot platform and the potential of the software architecture.
incremental reconstruction of generalized voronoi diagrams on grids. we present an incremental algorithm for constructing and reconstructing generalized voronoi diagrams (gvds) on grids. our algorithm, dynamic brushfire, uses techniques from the path planning community to efficiently update gvds when the underlying environment changes or when new information concerning the environment is received. dynamic brushfire is an order of magnitude more efficient than current approaches. in this paper we present the algorithm, compare it to current approaches on several experimental domains involving both simulated and real data, and demonstrate its usefulness for multirobot path planning.
optic flow-based vision system for autonomous 3d localization and control of small aerial vehicles. the problem considered in this paper involves the design of a vision-based autopilot for small and micro unmanned aerial vehicles (uavs). the proposed autopilot is based on an optic flow-based vision system for autonomous localization and scene mapping, and a nonlinear control system for flight control and guidance. this paper focusses on the development of a real-time 3d vision algorithm for estimating optic flow, aircraft self-motion and depth map, using a low-resolution onboard camera and a low-cost inertial measurement unit (imu). our implementation is based on 3 nested kalman filters (3nkf) and results in an efficient and robust estimation process. the vision and control algorithms have been implemented on a quadrotor uav, and demonstrated in real-time flight tests. experimental results show that the proposed vision-based autopilot enabled a small rotorcraft to achieve fully-autonomous flight using information extracted from optic flow.
policy gradient learning for a humanoid soccer robot. in humanoid robotic soccer, many factors, both at low-level (e.g., vision and motion control) and at high-level (e.g., behaviors and game strategies), determine the quality of the robot performance. in particular, the speed of individual robots, the precision of the trajectory, and the stability of the walking gaits, have a high impact on the success of a team. consequently, humanoid soccer robots require fine tuning, especially for the basic behaviors. in recent years, machine learning techniques have been used to find optimal parameter sets for various humanoid robot behaviors. however, a drawback of learning techniques is time consumption: a practical learning method for robotic applications must be effective with a small amount of data. in this article, we compare two learning methods for humanoid walking gaits based on the policy gradient algorithm. we demonstrate that an extension of the classic policy gradient algorithm that takes into account parameter relevance allows for better solutions when only a few experiments are available. the results of our experimental work show the effectiveness of the policy gradient learning method, as well as its higher convergence rate, when the relevance of parameters is taken into account during learning.
cheap joint probabilistic data association filters in an interacting multiple model design. this paper presents an approach to fuse multiple sensors in an interacting multiple model design. visual features like shadow and symmetry, treated as independent stand-alone virtual sensors, are employed for detection and tracking of vehicles for driver assistance tasks. cheap joint probabilistic data association is utilised to account for the large amount of clutter in the measurements provided by these sensors. special attention is devoted to the different noise characteristics of the measurements. the individual sensors are considered in a sequential manner, leading to a versatile fusion architecture that allows easy integration of further sensor modules.
self-modeling in humanoid soccer robots. in this paper we discuss the applicability, potential benefits, open problems and expected contributions that an emerging set of self-modeling techniques might bring on the development of humanoid soccer robots. the idea is that robots might continuously generate, validate and adjust physical models of their sensorimotor interaction with the world. these models are exploited for adapting behavior in simulation, enhancing the learning skills of a robot with the regular transference of controllers developed in simulation to reality. moreover, these simulations can be used to aid the execution of complex sensorimotor tasks, speed up adaptation and enhance task planning. we present experiments on the generation of behaviors for humanoid soccer robots using the back-to-reality algorithm. general motivations are presented, alternative algorithms are discussed and, most importantly, directions of research are proposed.
optimal pitch map generation for scanning pitch design in selective sampling. the reverse engineering process represents one of the best known methodologies for creating three-dimensional (3d) virtual models starting from physical ones. even if in the last few years its usage has significantly increased, the remarkable involvement of the operator has until now represented a significant constraint for its growth. having regard to the fact that this process, and in particular its first step (that is the acquisition phase), strongly depends on the operator's ability and expertise, this paper aims at proposing a strategy for automatically supporting an ''optimal'' acquisition phase. moreover, the acquisition phase represents the only moment in which there is a direct contact between the virtual model and the physical model. for this reason, designing an ''optimal'' acquisition phase will provide as output an efficient set of morphological data, which will turn out to be extremely useful for the following reverse engineering passages (pre-processing, segmentation, fitting, ...). this scenario drives the researcher to use a selective sampling plan, whose grid dimensions are correlated with the complexity of the local surface region analyzed, instead of a constant one. as a consequence, this work proposes a complete operative strategy which, starting from a first raw preliminary acquisition, will provide a new selective sampling plan during the acquisition phase, in order to allow a deeper and more efficient new scansion. the proposed solution does not require the creation of any intermediate model and relies exclusively on the analysis of the metrological performances of the 3d scanner device and of the morphological behaviour of the surface acquired.
differential evolution solution to the slam problem. a new solution to the simultaneous localization and modelling problem is presented in this paper. the algorithm is based on the stochastic search for solutions in the state space to the global localization problem by means of a differential evolution algorithm. this non linear evolutive filter, called evolutive localization filter (elf), searches stochastically along the state space for the best robot pose estimate. the set of pose solutions (the population) focuses on the most likely areas according to the perception and up to date motion information. the population evolves using the log-likelihood of each candidate pose according to the observation and the motion errors derived from the comparison between observed and predicted data obtained from the probabilistic perception and motion model. the proposed slam algorithm operates in two steps: in the first step the elf filter is used at local level to re-localize the robot based on the robot odometry, the laser scan at a given position and a local map where only a low number of the last scans have been integrated. in the second step, the aligned laser measures and the corrected robot poses are used to detect whether the robot is revisiting a previously crossed area (i.e., a cycle in the robot trajectory exists). once a cycle is detected, the evolutive localization filter is used again to estimate the accumulated residual drift in the detected loop and then to re-estimate the robot poses in order to integrate the sensor measures in the global map of the environment. the algorithm has been tested in different environments to demonstrate the effectiveness, robustness and computational efficiency of the proposed approach.
soccer playing humanoid robots: processing architecture, gait generation and vision system. research on humanoid robotics in mechatronics and automation (ma) laboratory, electrical and computer engineering (ece), national university of singapore (nus) was started at the beginning of this decade. various research prototypes for humanoid robots have been designed and are going through evolution over these years. these humanoids have been successfully participating in various robotic soccer competitions. in this paper, three major research and development aspects of the above humanoid research are discussed. the paper focuses on various practical and theoretical considerations involved in processing architecture, gait generation and vision systems.
a survey of robot learning from demonstration. we present a comprehensive survey of robot learning from demonstration (lfd), a technique that develops policies from example state to action mappings. we introduce the lfd design choices in terms of demonstrator, problem space, policy derivation and performance, and contribute the foundations for a structure in which to categorize lfd research. specifically, we analyze and categorize the multiple ways in which examples are gathered, ranging from teleoperation to imitation, as well as the various techniques for policy derivation, including matching functions, dynamics models and plans. to conclude we discuss lfd limitations and related promising areas for future research.
improving grasp quality evaluation. the capability to equilibrate external wrenches is crucial in optimal grasp planning. this paper presents a new method for evaluating this capability when the external wrench is unknown. two criteria are reformulated using the l"2 distance function, and further transformed into two nonlinear optimization problems. the differentiability of the objective functions and choice of initial conditions for global optimization are discussed. keeping all the merits, that the criteria are applicable to grasps of 3-d objects with any contact types, and that the friction cones are not linearized, this work endows them with several new virtues: (a) their formulation and computation are unified for both force-closure and non-force-closure grasps; (b) they are independent of the choice of coordinate frame and unit; (c) the object geometry is taken into account; (d) the computational efficiency is even higher than some methods by linearizing the friction cones.
a mixed analog-digital vision sensor for detecting objects approaching on a collision course. bio-inspired vision system is a particularly good candidate for navigation of mobile robots and vehicles because of its computational advantages, e.g., low power dissipation and compact hardware. previously, we had designed a mixed analog-digital integrated vision system for collision detection inspired by a locust neuronal circuit model. the response of the system was, however, susceptible to the luminance of approaching objects and the vibratory self-motion of a car when it was installed on a miniature mobile car. in the present study, we developed a new collision detection algorithm to overcome these problems based on robust image-motion detection and applied the algorithm to control a miniature mobile car.
feature fusion for basic behavior unit segmentation from video sequences. it has become increasingly popular to study animal behaviors with the assistance of video recordings. an automated video processing and behavior analysis system is desired to replace the traditional manual annotation. we propose a framework for automatic video based behavior analysis systems, which consists of four major modules: behavior modeling, feature extraction from video sequences, basic behavior unit (bbu) discovery and complex behavior recognition. bbu discovery is performed based on features extracted from video sequences, hence the fusion of multiple dimensional features is very important. in this paper, we explore the application of feature fusion techniques to bbu discovery with one and multiple cameras. we applied the vector fusion (sbp) method, a multi-variate vector visualization technique, in fusing the features obtained from a single camera. this technique reduces the multiple dimensional data into two dimensional (sbp) space, and the spatial and temporal analysis in sbp space can help discover the underlying data groups. then we present a simple feature fusion technique for bbu discovery from multiple cameras with the affinity graph method. finally, we present encouraging results on a physical system and a synthetic mouse-in-a-cage scenario from one, two, and three cameras. the feature fusion methods in this paper are simple yet effective.
hardware design and gait generation of humanoid soccer robot stepper-3d. this paper presents the hardware design and gait generation of humanoid soccer robot stepper-3d. virtual slope walking, inspired by passive dynamic walking, is introduced for gait generation. in virtual slope walking, by actively extending the stance leg and shortening the swing leg, the robot walks on level ground as it walks down a virtual slope. in practical, virtual slope walking is generated by connecting three key frames in the sagittal plane with sinusoids. aiming for improving the walking stability, the parallel double crank mechanism are adopted in the leg structure. experimental results show that stepper-3d achieves a fast forward walking speed of 0.5 m/s and accomplishes omnidirectional walking. stepper-3d performed fast and stable walking in the robocup 2008 humanoid competitions.
a bayesian approach to information fusion for evaluating the measurement uncertainty. the bayesian approach to uncertainty evaluation is a classical example of the fusion of information from different sources. basically, it is founded on both the knowledge about the measurement process and the influencing quantities and parameters. the knowledge about the measurement process is primarily represented by the so-called model equation, which forms the basic relationship for the fusion of all involved quantities. the knowledge about the influencing quantities and parameters is expressed by their degree of belief, i.e. appropriate probability density functions that usually are obtained by utilizing the principle of maximum information entropy and the bayes theorem. practically, the bayesian approach to uncertainty evaluation is put into effect by employing numerical integration techniques, preferably monte-carlo methods. compared to the iso-gum procedure, the bayesian approach does not have any restrictions with respect to nonlinearities and calculation of confidence intervals.
cluster tracking under kinematical constraints using random matrices. collectively moving object clusters are of particular interest in certain applications and have to be tracked as separate aggregated entities consisting of an unknown number of individuals. group targets often will not cause as many detections since there are individual targets in the group due to limited sensor resolution capabilities. in this case, tracking and data association under the 'one target, one detection' assumption are no longer applicable. in this paper, ellipsoidal object extensions are modeled by random matrices, which are treated as additional state variables to be estimated. an important aspect of gmti tracking is the incorporation of context information into the bayesian data processing formalism. here we consider kinematical constraints such as road maps and sensor specific characteristics such as doppler blindness.
characterization of zero tracking error references in the kinematic control of wheeled mobile robots. this work establishes the reference signal conditions for zero tracking error when controlling wheeled mobile robots under the kinematic framework, that is, when the low-level dynamics is neglected. the reference characterization is based on the classical decoupled robot control and the inverse kinematics of fixed, centered orientable, castor and swedish wheels. procedures to avoid tracking error when a particular condition is not satisfied are also indicated. simulations are shown to illustrate the reference conditions for each type of mobile robot and their implications. finally, an industrial forklift is considered in a real situation to validate the previous results and to highlight the limits of the kinematic framework assumption.
multisensor based security robot system for intelligent building. intelligent building can provide safety, convenience, efficiency and entertainment for life in the 21st century. the most importance role of the intelligent building is the security system. we develop a multi sensor-based intelligent security robot (isr) that is widely employed in intelligent buildings. the intelligent security robot can detect abnormal and dangerous situations and notify users. the robot has the shape of cylinder and its diameter, height, and weight are 50 cm, 130 cm and 100 kg respectively. the function of the isr contains six parts. there is the software development system; avoiding obstacle and motion planning system, image system, sensor system, remote supervise system and other systems. we develop a multi sensor-based sensor system in the isr. we use multiple multisensor fusion algorithms to get an exact decision in the detection subsystem of the sensor system. there is an adaptive fusion method, a rule based method, and a statistical signal method. we demonstrate the remote supervisory system to control the isr using a direct control mode and a behavior control mode. we think that the man-machine interface in a security robot system must have mobility and convenience. therefore, we use a touch screen to display the system state, and design a general user interface (gui) to service the user and visitors. the user can remotely control the appliance using a cell phone through a gsm modem, too. the appliance module can feedback reaction results to the user through a cell phone. finally, we implement the fire detection system in the intelligent security robot (chung-cheng-i). if a fire occurs, the intelligent security robot can find out the fire source using the fire detection system. in intruder detection, we program the same scenario to detect the intruder using the intelligent security robot. the intelligent security robot transmits the message of the detection result to the user using a gsm modem for a fire event or intruder, and transmits the detection result to a client computer through the internet.
cognitive agents - a procedural perspective relying on the predictability of object-action-complexes (oacs). embodied cognition suggests that complex cognitive traits can only arise when agents have a body situated in the world. the aspects of embodiment and situatedness are being discussed here from the perspective of linear systems theory. this perspective treats bodies as dynamic, temporally variable entities, which can be extended (or curtailed) at their boundaries. we show how acting agents can, for example, actively extend their body for some time by incorporating predictably behaving parts of the world and how this affects the transfer functions. we suggest that primates have mastered this to a large degree increasingly splitting their world into predictable and unpredictable entities. we argue that temporary body extension may have been instrumental in paving the way for the development of higher cognitive complexity as it is reliably widening the cause-effect horizon about the actions of the agent. a first robot experiment is sketched to support these ideas. we continue discussing the concept of object-action complexes (oacs) introduced by the european paco-plus consortium to emphasize the notion that, for a cognitive agent, objects and actions are inseparably intertwined. in another robot experiment we devise a semi-supervised procedure using the oac-concept to demonstrate how an agent can acquire knowledge about its world. here the notion of predicting changes fundamentally underlies the implemented procedure and we try to show how this concept can be used to improve the robot's inner model and behaviour. hence, in this article we have tried to show how predictability can be used to augment the agent's body and to acquire knowledge about the external world, possibly leading to more advanced cognitive traits.
generating human-like soccer primitives from human data. recently, interest in analysis and generation of human and human-like motion has increased in various areas. in robotics, in order to operate a humanoid robot, it is necessary to generate motions that have strictly dynamic consistency. furthermore, human-like motion for robots will bring advantages such as energy optimization. this paper presents a mechanism to generate two human-like motions, walking and kicking, for a biped robot using a simple model based on observation and analysis of human motion. our ultimate goal is to establish a design principle of a controller in order to achieve natural human-like motions. the approach presented here rests on the principle that in most biological motor learning scenarios some form of optimization with respect to a physical criterion is taking place. in a similar way, the equations of motion for the humanoid robot systems are formulated in such a way that the resulting optimization problems can be solved reliably and efficiently. the simulation results show that faster and more accurate searching can be achieved to generate an efficient human-like gait. comparison is made with methods that do not include observation of human gait. the gait has been successfully used to control robo-erectus, a soccer-playing humanoid robot, which is one of the foremost leading soccer-playing humanoid robots in the robocup humanoid league.
non-iterative nonlinear model predictive approach applied to the control of helicopters' group formation. two geometrical formation schemes that allow the definition of any desired three-dimensional formation mesh for a group of helicopters are presented. each formation scheme, which defines the leader-follower geometry of the formation mesh, has four parameters. these formation parameters are directly used as the output of decentralized controllers that independently control each helicopter in the group. the decentralized controllers are designed using a non-iterative nonlinear model predictive control (nmpc) method. the continuation method is used for solving, in real-time, for future control actions that minimize a nmpc cost function. it is shown by analyzing the number of floating point operations per calculation cycle that the calculation load of the nmpc method for this application is quite manageable for today's industrial embedded computers. simulations show that the formation schemes along with the nmpc controller can initialize and keep the formation of a group of helicopters even in the presence of bounded parameter uncertainty and environmental disturbance.
contour reconstruction using recursive smoothing splines - algorithms and experimental validation. in this paper, a recursive smoothing spline approach for contour reconstruction is studied and evaluated. periodic smoothing splines are used by a robot to approximate the contour of encountered obstacles in the environment. the splines are generated through minimizing a cost function subject to constraints imposed by a linear control system and accuracy is improved iteratively using a recursive spline algorithm. the filtering effect of the smoothing splines allows for usage of noisy sensor data and the method is robust to odometry drift. the algorithm is extensively evaluated in simulations for various contours and in experiments using a sick laser scanner mounted on a powerbot from activmedia robotics.
incremental pattern discovery on streams, graphs and tensors. incremental pattern discovery targets streaming applications where the data continuously arrive incrementally. the questions are how to find patterns (main trends) incrementally; or how to efficiently update the old patterns when new data arrive; or how to utilize the patterns to solve other problems such as anomaly detection? we first investigate a powerful data model, tensor stream (ts), where there is one tensor per timestamp. to capture diverse data formats, we have a zero-order ts for a single time-series (e.g., the stock price over time), a first-order ts for multiple time-series (sensor measurement streams), a second-order ts for matrices (graphs), and a high-order ts for multi-arrays (internet communication network, source-destination-port). second, we develop different online algorithms on ts: 1) the centralized and distributed spirit [7] for mining a 1st-order ts, as well as its extensions for local correlation function and privacy preservation; 2) the compact matrix decomposition (cmd) [5] and graphscope [4] for a 2nd-order ts; 3) the dynamic tensor analysis (dta) [2], streaming tensor analysis (sta) and window-based tensor analysis (wta) for a high-order ts. all the techniques are extensively evaluated for real applications such as network forensics, cluster monitoring.
mmis07, 08: mining multiple information sources workshop report. in this report, we summarize the research issues, contents, and outcomes of the two recent workshops on mining multiple information sources (mmis-07, 08) collocated with the 13th and the 14th acm sigkdd international conference on knowledge discovery and data mining (kdd-07 and kdd-08). we first summarize the research issues and topics which in workshop co-chairs' view are the major challenges for mining multiple information sources. then we briefiy introduce the content of the contributed papers in two years' program, along with the introduction to three keynote talks given by the invited speakers.
knowledge discovery from sensor data (sensorkdd). extracting knowledge and emerging patterns from sensor data is a nontrivial task. the challenges for the knowledge discovery community are expected to be immense. on one hand, dynamic data streams or events require real-time analysis methodologies and systems, while on the other hand centralized processing through high end computing is also required for generating offline predictive insights, which in turn can facilitate real-time analysis. in addition, emerging societal problems require knowledge discovery solutions that are designed to investigate anomalies, changes, extremes and nonlinear processes, and departures from the normal. keeping in view the requirements of the emerging field of knowledge discovery from sensor data, we took initiative to develop a community of researchers with common interests and scientific goals, which culminated into the organization of sensor-kdd series of workshops in conjunction with the prestigious acm sigkdd international conference of knowledge discovery and data mining. in this report, we summarize the events of the second acm-sigkdd international workshop on knowledge discovery form sensor data (sensor-kdd 2008).
learning preferences of new users in recommender systems: an information theoretic approach. recommender systems are an effective tool to help find items of interest from an overwhelming number of available items. collaborative filtering (cf), the best known technology for recommender systems, is based on the idea that a set of like-minded users can help each other find useful information. a new user poses a challenge to cf recommenders, since the system has no knowledge about the preferences of the new user, and therefore cannot provide personalized recommendations. a new user preference elicitation strategy needs to ensure that the user does not a) abandon a lengthy signup process, and b) lose interest in returning to the site due to the low quality of initial recommendations. we extend the work of [23] in this paper by incrementally developing a set of information theoretic strategies for the new user problem. we propose an offline simulation framework, and evaluate the strategies through extensive offline simulations and an online experiment with real users of a live recommender system.
kdd2008 workshop report dmmt'08: data mining using matrices and tensors. we provide a summary of theworkshop on data mining using matrices and tensors (dmmt'08) held in conjunction with acm sigkdd 2008, on august 24th in las vegas, usa. about 100 people attended the workshop. we report in detail about the research issues addressed in the talks at the workshop. more information about the workshop can be found at http://www.cs.fiu.edu/~taoli/kdd08-workshop.
report on the second kdd workshop on data mining for advertising. following the success of our first workshop, we organized adkdd 2008 1 - the second international workshop on data mining and audience intelligence for advertising, in conjunction with kdd 2008 at las vegas, nevada, usa. this report is a summary of the workshop, including brief descriptions of the accepted papers.
webkdd 2008: 10 years of knowledge discovery on the web post-workshop report. webkdd was held in conjunction with the 14th acm sigkdd international conference on knowledge discovery and data mining (kdd 2008), august 24, 2008, in henderson/las vegas, nevada. in 2008, webkdd was held for the tenth time. we report on the contents and outcomes of this anniversary workshop and include a small retrospection on 10 years of knowledge discovery on the web.
breast cancer identification: kdd cup winner's report. we describe the ideas and methodologies that we developed in addressing the kdd cup 2008 on early breast cancer detection, and discuss how they contributed to our success. the most important components of our solution were 1) the identification of predictive information in the patient identifier, 2) a linear svm on the 117 provided features, and 3) a heuristic post-processing approach to optimize the evaluation criteria.
kdd cup 2008 and the workshop on mining medical data. in this report we summarize the kdd cup 2008 task, which addressed a problem of early breast cancer detection. we describe the data and the challenges, the results and summarize the algorithms used by the winning teams. we also summarize the workshop on mining medical data held in conjunction with sigkdd on august 24, 2008 in las vegas, nv that brought together researchers working on various aspects of applying machine learning and data mining to challenging tasks in medical and health care domains.
on exploiting the power of time in data mining. we introduce the new paradigm of change mining as data mining over a volatile, evolving world with the objective of understanding change. while there is much work on incremental mining and stream mining, both focussing on the adaptation of patterns to a changing data distribution, change mining concentrates on understanding the changes themselves. this includes detecting when change occurs in the population under observation, describing the change, predicting change and pro-acting towards it. we identify the main tasks of change mining and discuss to what extent they are already present in related research areas. we elaborate on research results that can contribute to these tasks, giving a brief overview of the current state of the art and identifying open areas and challenges for the new research area.
snakdd 2008 social network mining and analysis postworkshop report. in this report, we summarize the contents and outcomes of the recent snakdd 2008 workshop on social network mining and analysis that was held in conjunction with the 14th acm sigkdd international conference on knowledge discovery and data mining (kdd 2008), august 24-27, 2008, in las vegas, nevada. the snakdd 2008 is the second in a successful series of workshops on social network mining and analysis. it solicited papers on broad overview subject "social network mining and analysis". the workshop drew a large number of participants from academia and industry. in this report we reflect on the results of the workshop, as captured in the regular paper session as well as the poster session.
learning to improve area-under-froc for imbalanced medical data classification using an ensemble method. this paper presents our solution for kdd cup 2008 competition that aims at optimizing the area under roc for breast cancer detection. we exploited weighted-based classification mechanism to improve the accuracy of patient classification (each patient is represented by a collection of data points). final predictions for challenge 1 are generated by combining outputs from weighted svm and adaboost; whereas we integrate svm, adaboost, and ga to produce the results for challenge 2. we have also tried location-based classification and model adaptation to add the testing data into training. our results outperform other participants given the same set of features, and was selected as the joint winner in kdd cup 2008.
pinkdd'08: privacy, security, and trust in kdd post workshop report. this report summarizes the events of the 2nd international workshop on privacy, security, and trust in kdd, at the 14th acm sigkdd international conference on knowledge discovery and data mining. the workshop was held on august 24, 2008 in las vegas, nevada and brought together computer scientists working on how data protection issues factor into the context of data mining.
retail sales prediction and item recommendations using customer demographics at store level. this paper outlines a retail sales prediction and product recommendation system that was implemented for a chain of retail stores. the relative importance of consumer demographic characteristics for accurately modeling the sales of each customer type are derived and implemented in the model. data consisted of daily sales information for 600 products at the store level, broken out over a set of non-overlapping customer types. a recommender system was built based on a fast online thin singular value decomposition. it is shown that modeling data at a finer level of detail by clustering across customer types and demographics yields improved performance compared to a single aggregate model built for the entire dataset. details of the system implementation are described and practical issues that arise in such real-world applications are discussed. preliminary results from test stores over a one-year period indicate that the system resulted in significantly increased sales and improved efficiencies. a brief overview of how the primary methods discussed here were extended to a much larger data set is given to confirm and illustrate the scalability of this approach.
algorithmic and statistical challenges in modern largescale data analysis are the focus of mmds 2008. we provide a report for the acm sigkdd community about the 2008 workshop on algorithms for modern massive data sets (mmds 2008), its origin in mmds 2006, and future directions for this interdisciplinary research area.
web data mining: exploring hyperlinks, contents, and usage data. this paper presents a review of the book "web data mining - exploring hyperlinks, contents, and usage data" by bing liu. the review concludes that the breadth and depth of this book makes it a required staple for every web mining researcher, student, or practitioner.
a brief survey on anonymization techniques for privacy preserving publishing of social network data. nowadays, partly driven by many web 2.0 applications, more and more social network data has been made publicly available and analyzed in one way or another. privacy preserving publishing of social network data becomes a more and more important concern. in this paper, we present a brief yet systematic review of the existing anonymization techniques for privacy preserving publishing of social network data. we identify the new challenges in privacy preserving publishing of social network data comparing to the extensively studied relational case, and examine the possible problem formulation in three important dimensions: privacy, background knowledge, and data utility. we survey the existing anonymization methods for privacy preservation in two categories: clustering-based approaches and graph modification approaches.
compacting cuts: a new linear formulation for minimum cut. for a graph (v,e), existing compact linear formulations for the minimum cut problem require &theta;(&verbar;v&verbar;&verbar;e&verbar;) variables and constraints and can be interpreted as a composition of &verbar;v&verbar; &minus; 1 polyhedra for minimum s-t cuts in much the same way as early approaches to finding globally minimum cuts relied on &verbar;v&verbar; &minus; 1 calls to a minimum s-t cut algorithm. we present the first formulation to beat this bound, one that uses o(&verbar;v&verbar;2) variables and o(&verbar;v&verbar;3) constraints. an immediate consequence of our result is a compact linear relaxation with o(&verbar;v&verbar;2) constraints and o(&verbar;v&verbar;3) variables for enforcing global connectivity constraints. this relaxation is as strong as standard cut-based relaxations and has applications in solving traveling salesman problems by integer programming as well as finding approximate solutions for survivable network design problems using jain's iterative rounding method. another application is a polynomial-time verifiable certificate of size n for for the np-complete problem of l1-embeddability of a rational metric on an n-set (as opposed to a certificate of size n2 known previously).
squarepants in a tree: sum of subtree clustering and hyperbolic pants decomposition. we provide efficient constant-factor approximation algorithms for the problems of finding a hierarchical clustering of a point set in any metric space, minimizing the sum of minimimum spanning tree lengths within each cluster, and in the hyperbolic or euclidean planes, minimizing the sum of cluster perimeters. our algorithms for the hyperbolic and euclidean planes can also be used to provide a pants decomposition, that is, a set of disjoint simple closed curves partitioning the plane minus the input points into subsets with exactly three boundary components, with approximately minimum total length. in the euclidean case, these curves are squares; in the hyperbolic case, they combine our euclidean square pants decomposition with our tree clustering method for general metric spaces.
an ( log ) approximation scheme for steiner tree in planar graphs. we give a polynomial-time approximation scheme (ptas) for the steiner tree problem in planar graphs. the running time is o(n log n).
instability of fifo in the permanent sessions model at arbitrarily small network loads. we show that for any r > 0, there is a network of first-in-first-out servers and a fixed set of sessions such that: &mdash;the network load is r with respect to the permanent sessions model with bounded arrivals. &mdash;the network can be made unstable.
optimal dynamic vertical ray shooting in rectilinear planar subdivisions. we consider the dynamic vertical ray shooting problem against horizontal disjoint segments, that is, the task of maintaining a dynamic set s of n nonintersecting horizontal line segments in the plane under a query that reports the first segment in s intersecting a vertical ray from a query point. we develop a linear-size structure that supports queries, insertions, and deletion in o(log n) worst-case time. our structure works in the comparison model on a random access machine.
near-optimal algorithms for maximum constraint satisfaction problems. in this article, we present two approximation algorithms for the maximum constraint satisfaction problem with k variables in each constraint (max k-csp). given a (1 &minus; &epsiv;) satisfiable 2csp our first algorithm finds an assignment of variables satisfying a 1 &minus; o(&sqrt;&epsiv;) fraction of all constraints. the best previously known result, due to zwick, was 1 &minus; o(&epsiv;1/3). the second algorithm finds a ck/2k approximation for the max k-csp problem (where c > 0.44 is an absolute constant). this result improves the previously best known algorithm by hast, which had an approximation guarantee of &omega;(k/(2k log k)). both results are optimal assuming the unique games conjecture and are based on rounding natural semidefinite programming relaxations. we also believe that our algorithms and their analysis are simpler than those previously known.
the impact of parametrization in memetic evolutionary algorithms. memetic (evolutionary) algorithms integrate local search into the search process of evolutionary algorithms. as computational resources have to be spread adequately among local and evolutionary search, one has to care about when to apply local search and how much computational effort to devote to local search. often local search is called with a fixed frequency and run for a fixed number of iterations, the local search depth. there is empirical evidence that these parameters have a significant impact on performance, but a theoretical understanding as well as concrete design guidelines are missing. we initiate the rigorous theoretical analysis of memetic algorithms. to this end, we consider a simple memetic algorithm for pseudo-boolean optimization that captures basic working principles of memetic algorithms-the interplay of genetic operators like mutation and selection with local search. we present function classes where even small changes of the parametrization have a strong impact on performance. for almost every reasonable parameter setting we construct a function that, with high probability, can be optimized in polynomial time. however, changing the local search depth by a small additive term in any direction yields a superpolynomial optimization time, with high probability. for another class of functions altering the local search frequency by a factor of 2 even yields exponential optimization times. our results show exemplarily that parametrizing memetic evolutionary algorithms can be extremely hard. moreover, this work yields insights into the dynamic behavior of memetic algorithms and contributes to a theoretical foundation of hybrid metaheuristics.
the parallel complexity of signed graphs: decidability results and an improved algorithm. we consider a graph-based model for the process of gene assembly in ciliates, as proposed in [a. ehrenfeucht, t. harju, i. petre, d. m. prescott, g. rozenberg, computation in living cells: gene assembly in ciliates, springer, 2003]. the model consists of three operations, each reducing the order of the signed graph. reducing the graph to the empty graph through a sequence of operations corresponds to assembling a gene. we investigate parallel reductions of a given signed graph, where the graph is reduced through a sequence of parallel steps. a parallel step consists of operations such that any of their sequential compositions are applicable to the current graph. we improve the basic exhaustive search algorithm reported in [a. alhazov, c. li, i. petre, computing the graph-based parallel complexity of gene assembly, theoretical computer science, 2008 (in press)] to compute the parallel complexity of signed graphs. on the one hand, we reduce the number of sets of operations which should be checked for parallel applicability. on the other hand, we speed up the parallel applicability check procedure. we prove also that deciding whether a given parallel composition of operations is applicable to a given signed graph is a conp problem. deciding whether the parallel complexity (the length of a shortest parallel reduction) of a signed graph is bounded by a given constant is in np^n^p.
binary sequences with optimal autocorrelation. sequences have important applications in ranging systems, spread spectrum communication systems, multi-terminal system identification, code-division multiple access communication systems, global positioning systems, software testing, circuit testing, computer simulation, and stream ciphers. sequences and error-correcting codes are also closely related. in this paper, we give a well rounded treatment of binary sequences with optimal autocorrelation. we survey known ones and construct new ones.
energy efficient randomised communication in unknown adhoc networks. this paper studies broadcasting and gossiping algorithms in random and general adhoc networks. our goal is not only to minimise the broadcasting and gossiping time, but also to minimise the energy consumption, which is measured in terms of the total number of messages (or transmissions) sent. we assume that the nodes of the network do not know the network, and that they can only send with a fixed power, meaning they can not adjust the area sizes that their messages cover. we believe that under these circumstances the number of transmissions is a very good measure for the overall energy consumption. for random networks, we present a broadcasting algorithm where every node transmits at most once. we show that our algorithm broadcasts in o(logn) steps, w.h.p., where n is the number of nodes. we then present a o(dlogn) (d is the expected degree) gossiping algorithm using o(logn) messages per node. for general networks with known diameter d, we present a randomised broadcasting algorithm with optimal broadcasting time o(dlog(n/d)+log^2n) that uses an expected number of o(log^2n/log(n/d)) transmissions per node. we also show a tradeoff result between the broadcasting time and the number of transmissions: we construct a network such that any oblivious algorithm using a time-invariant distribution requires @w(log^2n/log(n/d)) messages per node in order to finish broadcasting in optimal time. this demonstrates the tightness of our upper bound. we also show that no oblivious algorithm can complete broadcasting w.h.p. using o(logn) messages per node.
lattices of local two-dimensional languages. the aim of this paper is to study local two-dimensional languages from an algebraic point of view. we show that local two-dimensional languages over a finite alphabet, with the usual relation of set inclusion, form a lattice. the simplest case loc"1 of local languages defined over the alphabet consisting of one element yields a distributive lattice, which can be easily described. in the general case of the lattice loc"n of local languages over an alphabet of n>=2 symbols, we show that loc"n is not semimodular, and we exhibit sublattices isomorphic to m"5 and n"5. we characterize the meet-irreducible elements, the coatoms, and the join-irreducible elements of loc"n. we point out some undecidable problems which arise in studying the lattices loc"n, n>=2. we study in some detail atoms and chains of loc"2. finally we examine the lattice loc"2^h of local string languages, i.e. the local languages over the binary alphabet consisting of objects of only one row. loc"2^h is an ideal of loc"2. as a lattice, it is not semimodular but satisfies the jordan-dedekind condition.
a prolongation-projection algorithm for computing the finite real variety of an ideal. we provide a real algebraic symbolic-numeric algorithm for computing the real variety v"r(i) of an ideal i@?r[x], assuming v"r(i) is finite (while v"c(i) could be infinite). our approach uses sets of linear functionals on r[x], vanishing on a given set of polynomials generating i and their prolongations up to a given degree, as well as on polynomials of the real radical ideal ir obtained from the kernel of a suitably defined moment matrix assumed to be positive semidefinite and of maximum rank. we formulate a condition on the dimensions of projections of these sets of linear functionals, which serves as a stopping criterion for our algorithm; this new criterion is satisfied earlier than the previously used stopping criterion based on a rank condition for moment matrices. this algorithm is based on standard numerical linear algebra routines and semidefinite optimization and combines techniques from previous work of the authors together with an existing algorithm for the complex variety.
on the similarity metric and the distance metric. similarity and dissimilarity measures are widely used in many research areas and applications. when a dissimilarity measure is used, it is normally required to be a distance metric. however, when a similarity measure is used, there is no formal requirement. in this article, we have three contributions. first, we give a formal definition of similarity metric. second, we show the relationship between similarity metric and distance metric. third, we present general solutions to normalize a given similarity metric or distance metric.
parallelizing quantum circuits. we present a novel automated technique for parallelizing quantum circuits via the forward and backward translation to measurement-based quantum computing patterns, and analyze the trade off in terms of depth and space complexity. as a result we distinguish a class of polynomial depth circuits that can be parallelized to logarithmic depth while adding only a polynomial number of auxiliary qubits. in particular, we provide for the first time a full characterization of patterns with flow of arbitrary depth, based on the notion of influencing walks and a simple rewriting system on the angles of the measurement. our method provides new insight for constructing parallel circuits and as applications, we demonstrate several classes of circuits that can be parallelized to constant or logarithmic depth. furthermore, we prove a logarithmic separation in terms of quantum depth between the quantum circuit model and the measurement-based model.
on languages generated by asynchronous spiking neural p systems. in this paper, we investigate the languages generated by asynchronous spiking neural p systems. characterizations of finite languages and recursively enumerable languages are obtained by asynchronous spiking neural p systems with extended rules. the relationships of the languages generated by asynchronous spiking neural p systems with regular and non-semilinear languages are also investigated.
on the hopcroft's minimization technique for dfa and dfca. we show that the absolute worst case time complexity for hopcroft's minimization algorithm applied to unary languages is reached only for deterministic automata or cover automata following the structure of the de bruijn words. a previous paper by berstel and carton gave the example of de bruijn words as a language that requires o(nlogn) steps in the case of deterministic automata by carefully choosing the splitting sets and processing these sets in a fifo mode for the list of the splitting sets in the algorithm. we refine the previous result by showing that the berstel/carton example is actually the absolute worst case time complexity in the case of unary languages for deterministic automata. we show that the same result is valid also for the case of cover automata and an algorithm based on the hopcroft's method used for minimization of cover automata. we also show that a lifo implementation for the splitting list will not achieve the same absolute worst time complexity for the case of unary languages both in the case of regular deterministic finite automata or in the case of the deterministic finite cover automata as defined by s. yu.
twin-roots of words and their properties. in this paper we generalize the notion of an @i-symmetric word, from an antimorphic involution, to an arbitrary involution @i as follows: a nonempty word w is said to be @i-symmetric if w=@a@b=@i(@b@a) for some words @a,@b. we propose the notion of @i-twin-roots (x,y) of an @i-symmetric word w. we prove the existence and uniqueness of the @i-twin-roots of an @i-symmetric word, and show that the left factor @a and right factor @b of any factorization of w as w=@a@b=@i(@b@a), can be expressed in terms of the @i-twin-roots of w. in addition, we show that for any involution @i, the catenation of the @i-twin-roots of w equals the primitive root of w. we also provide several characterizations of the @i-twin-rots of a word, for @i being a morphic or antimorphic involution.
state complexity of unique rational operations. for each basic language operation we define its ''unique'' counterpart as being the operation that results in a language whose words can be obtained uniquely through the given operation. these unique operations can arguably be viewed as combined basic operations, placing this work in the popular area of state complexity of combined operations on regular languages. we study the state complexity of unique rational operations and we provide upper bounds and empirical results meant to cast light into this matter. equally important, we hope to have provided a generic methodology for estimating their state complexity.
one-shot learners using negative counterexamples and nearest positive examples. as some cognitive research suggests, in the process of learning languages, in addition to overt explicit negative evidence, a child often receives covert explicit evidence in form of corrected or rephrased sentences. in this paper, we suggest one approach to formalization of overt and covert evidence within the framework of one-shot learners via subset and membership queries to a teacher (oracle). we compare and explore general capabilities of our models, as well as complexity advantages of learnability models of one type over models of other types, where complexity is measured in terms of number of queries. in particular, we establish that ''correcting'' positive examples are sometimes more helpful to a learner than just negative (counter) examples and access to full positive data.
on minimal elements of upward-closed sets. upward-closed sets of integer vectors enjoy the merit of having a finite number of minimal elements, which is behind the decidability of a number of petri net related problems. in general, however, such a finite set of minimal elements may not be effectively computable. in this paper, we develop a unified strategy for computing the sizes of the minimal elements of certain upward-closed sets associated with petri nets. our approach can be regarded as a refinement of a previous work by valk and jantzen (in which a necessary and sufficient condition for effective computability of the set was given), in the sense that complexity bounds now become available provided that a bound can be placed on the size of a witness for a key query. the sizes of several upward-closed sets that arise in the theory of petri nets as well as in backward-reachability analysis in automated verification are derived in this paper, improving upon previous decidability results shown in the literature.
state complexity of basic operations on suffix-free regular languages. we investigate the state complexity of basic operations for suffix-free regular languages. the state complexity of an operation for regular languages is the number of states that are necessary and sufficient in the worst-case for the minimal deterministic finite-state automaton that accepts the language obtained from the operation. we establish the precise state complexity of catenation, kleene star, reversal and the boolean operations for suffix-free regular languages.
on two open problems of 2-interval patterns. the 2-interval pattern problem, introduced in [stephane vialette, on the computational complexity of 2-interval pattern matching problems theoret. comput. sci. 312 (2-3) (2004) 223-249], models general problems with biological structures such as protein contact maps and macroscopic describers of secondary structures of ribonucleic acids. given a set of 2-intervals d and a model r, the problem is to find a maximum cardinality subset d^' of d such that any two 2-intervals in d^' satisfy r, where r is a subset of relations on disjoint 2-intervals: precedence (
spreading messages. we model a network in which messages spread by a simple directed graph g=(v,e) and a function @a:v->n mapping each v@?v to a positive integer less than or equal to the indegree of v. the graph g represents the individuals in the network and the communication channels between them. an individual v@?v will be convinced of a message when at least @a(v) of its in-neighbors are convinced. suppose we are to convince a message to the individuals by first convincing a subset of individuals, called the seeds, and then let the message spread. we study the minimum number min-seed (g,@a) of seeds needed to convince all individuals at the end. in particular, we prove a lower bound on min-seed (g,@a) and the np-completeness of computing min-seed (g,@a). we also analyze the special case, called the strict-majority scenario, where each individual is convinced of a message when more than half of its in-neighbors are convinced. for the strict-majority scenario, we prove three results. first, we show that with high probability over the erdos-renyi random graphs g(n,p), @w(min{n,1/p}) seeds are needed to convince all individuals at the end. second, if g=(v,e) is undirected, then a set of s uniformly random samples from v convinces no more than an expected s(2|e|+2|v|)|v| individuals at the end. third, in a digraph g=(v,e) with a positive minimum indegree, one can find in polynomial (in |v|) time a set of at most (23/27)|v| seeds convincing all individuals.
new bounds on classical and quantum one-way communication complexity. in this paper we provide new bounds on classical and quantum distributional communication complexity in the two-party, one-way model of communication. in the classical one-way model, our bound extends the well known upper bound of kremer, nisan and ron [i. kremer, n. nisan, d. ron, on randomized one-round communication complexity, in: proceedings of the 27th acm symposium on theory of computing, stoc, 1995, pp. 596-605] to include non-product distributions. let @e@?(0,1/2) be a constant. we show that for a boolean function f:xxy->{0,1} and a non-product distribution @m on xxy, d"@e^1^,^@m(f)=o((i(x:y)+1)@?vc(f)), where d"@e^1^,^@m(f) represents the one-way distributional communication complexity of f with error at most @e under @m; vc(f) represents the vapnik-chervonenkis dimension of f and i(x:y) represents the mutual information, under @m, between the random inputs of the two parties. for a non-boolean function f:xxy->{1,...,k} (k>=2 an integer), we show a similar upper bound on d"@e^1^,^@m(f) in terms of k,i(x:y) and the pseudo-dimension of f^'=deffk, a generalization of the vc-dimension for non-boolean functions. in the quantum one-way model we provide a lower bound on the distributional communication complexity, under product distributions, of a function f, in terms of the well studied complexity measure of f referred to as the rectangle bound or the corruption bound of f. we show for a non-boolean total function f:xxy->z and a product distribution @m on xxy, q"@e"^"3"/"8^1^,^@m(f)=@w(rec"@e^1^,^@m(f)), where q"@e"^"3"/"8^1^,^@m(f) represents the quantum one-way distributional communication complexity of f with error at most @e^3/8 under @m and rec"@e^1^,^@m(f) represents the one-way rectangle bound of f with error at most @e under @m. similarly for a non-boolean partial function f:xxy->z@?{*} and a product distribution @m on xxy, we show, q"@e"^"6"/"("2"@?"1"5"^"4")^1^,^@m(f)=@w(rec"@e^1^,^@m(f)).
a ptas for parallel batch scheduling with rejection and dynamic job arrivals. in the parallel batch scheduling model, a group of jobs can be scheduled together as a batch while the processing time of this batch is the greatest processing time among its members; in the model of scheduling with rejection, any job can be rejected with a corresponding penalty cost added to the objective value. in this paper, we present a ptas for the combined model of the above two scheduling models where jobs arrive dynamically. the objective is to minimize the sum of the makespan of the accepted jobs and the total penalty of the rejected ones. our basic approaches are dynamic programming and roundings.
a new heuristic algorithm for the machine scheduling problem with job delivery coordination. in a rapidly changing environment, competition among enterprises has a tendency towards competing between supply chain systems instead of competing between individual companies. traditional scheduling models which only address the sequence of jobs to be processed at the production stage under some criteria are no longer suitable and should be extended to cope with the distribution stage after production. emphasizing on the coordination and integration among various members of a supply chain has become one of the vital strategies for the modern manufacturers to gain competitive advantages. this paper studies the np-hard problem of the two-stage scheduling in which jobs are processed by two parallel machines and delivered to a customer with the objective of minimizing the makespan (p2->d,k=1|v=1,c=z|c"m"a"x). the proposed heuristic algorithm is shown to have a worst-case ratio of 63/40, except for two particular cases.
linear connectivity problems in directed hypergraphs. we introduce a notion of hyperconnection (formally called l-hyperpath) between vertices in a directed hypergraph and relate this notion to existing notions of hyperpaths in directed hypergraphs. we show that some interesting questions in problem domains such as distributed secret sharing and routing in packet filtered networks are basically questions about the existence of l-hyperpaths in directed hypergraphs. we study the computational complexity of problems related to l-hyperpaths and the l-cyclomatic number of directed hypergraphs (the minimum number of hyperedges that need to be deleted to make a directed hypergraph free of l-hypercycles). we prove that the l-hyperpath existence problem, the l-cyclomatic number problem, the minimum l-cyclomatic set problem, and the minimal l-cyclomatic set problem are each complete for the complexity class np, @s"2^p, @p"2^p, and dp, respectively.
optimal tree structures for group key tree management considering insertion and deletion cost. we study the optimal structure for the group broadcast problem where the key tree model is extensively used. the objective is usually to find an optimal key tree to minimize the cost based on certain assumptions. under the assumption that n members arrive in the initial setup period and only member deletions are allowed after that period, previous works show that when only considering the deletion cost, the optimal tree can be computed in o(n^2) time. in this paper, we first prove a semi-balance property for the optimal tree and use it to reduce the running time from o(n^2) to o(loglogn) multiplications of o(logn)-bit integers. then we study the optimal tree structure when insertion cost is also considered. we show that the optimal tree is such a tree where any internal node has degree at most 7 and children of nodes with degree not equal to 2 or 3 are all leaves. based on this result we give a dynamic programming algorithm with o(n^2) time to compute the optimal tree.
cyclic renewal systems. we present three equivalent conditions for a generating set w of a renewal system to generate a maximal monoid in the language of the system. we show that if a code w generates a shift of finite type and satisfies those conditions, then it is cyclic. sufficient conditions are given when the converse holds.
conditional matching preclusion for hypercube-like interconnection networks. the conditional matching preclusion number of a graph with n vertices is the minimum number of edges whose deletion results in a graph without an isolated vertex that does not have a perfect matching if n is even, or an almost perfect matching if n is odd. we develop some general properties on conditional matching preclusion and then analyze the conditional matching preclusion numbers for some hl-graphs, hypercube-like interconnection networks.
parameterized computational complexity of control problems in voting systems. voting systems are common tools in a variety of areas. this paper studies parameterized computational complexity of control of plurality, condorcet and approval voting systems, respectively. the types of controls considered include adding or deleting candidates or voters, under constructive or destructive setting. we obtain the following results: (1) constructive control by adding candidates in plurality voting is w[2]-hard with respect to the parameter ''number of added candidates'', (2) destructive control by adding candidates in plurality voting is w[2]-hard with respect to the parameter ''number of added candidates'', (3) constructive control by adding voters in condorcet voting is w[1]-hard with respect to the parameter ''number of added voters'', (4) constructive control by deleting voters in condorcet voting is w[1]-hard with respect to the parameter ''number of deleted voters'', (5) constructive control by adding voters in approval voting is w[1]-hard with respect to the parameter ''number of added voters'', and (6) constructive control by deleting voters in approval voting is w[2]-hard with respect to the parameter ''number of deleted voters''.
exponential inapproximability and fptas for scheduling with availability constraints. we investigate the problems of scheduling n weighted jobs to one or more identical machines with the constraint that the machines may be unavailable in some specified time intervals. the objective is to find a schedule that minimizes the total weighted completion time. we consider both non-resumable and resumable schedules. our first contributions concern approximability. for both resumable problem and non-resumable problem, we show that they cannot be approximated within an exponential factor by any polynomial time algorithm for multiple machines where each of them has an unavailable interval, even if the weight of each job equals to its processing time. additionally, the non-resumable problem is also exponentially inapproximable for a single machine with two or more unavailable intervals. then we develop the first fptass for the problems with a single unavailable interval among all machines. the running time is o(cnlog^dn(1@elogw)^d) for the non-resumable problem, and o(cnlog^dn(1@elogw)^d^+^1) for the resumable problem, where w is the product of the total weight and the total processing time of all jobs, c is the number of machines that are always available and d=6c+12. thus our results give a clear boundary delineating the inapproximable cases and approximable cases. when there is a single machine and w=o(n^l^o^g^n^^^o^^^(^^^1^^^)), our algorithms greatly improve the current results. note that instead of conventional ways of sequentially processing the jobs, our fast schemes process jobs in a divide-and-conquer fashion, which greatly reduces the running time. this may give some insight for some other related problems.
decimations of languages and state complexity. let the words of a language l be arranged in increasing radix order: l={w"0,w"1,w"2,...}. we consider transformations that extract terms from l in an arithmetic progression. for example, two such transformations are even(l)={w"0,w"2,w"4...} and odd(l)={w"1,w"3,w"5,...}. lecomte and rigo observed that if l is regular, then so are even(l), odd(l), and analogous transformations of l. we find good upper and lower bounds on the state complexity of this transformation. we also give an example of a context-free language l such that even(l) is not context-free.
topology on words. we investigate properties of topologies on sets of finite and infinite words over a finite alphabet. the guiding example is the topology generated by the prefix relation on the set of finite words, considered as a partial order. this partial order extends naturally to the set of infinite words; hence it generates a topology on the union of the sets of finite and infinite words. we consider several partial orders which have similar properties and identify general principles according to which the transition from finite to infinite words is natural. we provide a uniform topological framework for the set of finite and infinite words to handle limits in a general fashion.
asynchronous spiking neural p systems. we consider here spiking neural p systems with a non-synchronized (i.e., asynchronous) use of rules: in any step, a neuron can apply or not apply its rules which are enabled by the number of spikes it contains (further spikes can come, thus changing the rules enabled in the next step). because the time between two firings of the output neuron is now irrelevant, the result of a computation is the number of spikes sent out by the system, not the distance between certain spikes leaving the system. the additional non-determinism introduced in the functioning of the system by the non-synchronization is proved not to decrease the computing power in the case of using extended rules (several spikes can be produced by a rule). that is, we obtain again the equivalence with turing machines (interpreted as generators of sets of (vectors of) numbers). however, this problem remains open for the case of standard spiking neural p systems, whose rules can only produce one spike. on the other hand we prove that asynchronous systems, with extended rules, and where each neuron is either bounded or unbounded, are not computationally complete. for these systems, the configuration reachability, membership (in terms of generated vectors), emptiness, infiniteness, and disjointness problems are shown to be decidable. however, containment and equivalence are undecidable.
comparison of simple diversity mechanisms on plateau functions. it is widely assumed and observed in experiments that the use of diversity mechanisms in evolutionary algorithms may have a great impact on its running time. up to now there is no rigorous analysis pointing out how different diversity mechanisms influence the runtime behavior. we consider evolutionary algorithms that differ from each other in the way they ensure diversity and point out situations where the right mechanism is crucial for the success of the algorithm. the considered evolutionary algorithms either diversify the population with respect to the search points or with respect to function values. investigating simple plateau functions, we show that using the ''right'' diversity strategy makes the difference between an exponential and a polynomial runtime. later on, we examine how the drawback of the ''wrong'' diversity mechanism can be compensated by increasing the population size.
state complexity of power. the number of states in a deterministic finite automaton (dfa) recognizing the language l^k, where l is regular language recognized by an n-state dfa, and k>=2 is a constant, is shown to be at most n2^(^k^-^1^)^n and at least (n-k)2^(^k^-^1^)^(^n^-^k^) in the worst case, for every n>k and for every alphabet of at least six letters. thus, the state complexity of l^k is @q(n2^(^k^-^1^)^n). in the case k=3 the corresponding state complexity function for l^3 is determined as 6n-384^n-(n-1)2^n-n with the lower bound witnessed by automata over a four-letter alphabet. the nondeterministic state complexity of l^k is demonstrated to be nk. this bound is shown to be tight over a two-letter alphabet.
on parameterized exponential time complexity. in this paper we study the notion of parameterized exponential time complexity. we show that a parameterized problem can be solved in parameterized 2^o^(^f^(^k^)^)p(n) time if and only if it is solvable in time o(2^@d^f^(^k^)q(n)) for any constant @d>0, where p and q are polynomials. we then illustrate how this equivalence can be used to show that special instances of parameterized np-hard problems are as difficult as the general instances. for example, we show that the planar dominating set problem on degree-3 graphs can be solved in 2^o^(^k^)p(n) parameterized time if and only if the general planar dominating set problem can. apart from their complexity theoretic implications, our results have some interesting algorithmic implications as well.
on the intersection of regex languages with regular languages. in this paper we revisit the semantics of extended regular expressions (regex), defined succinctly in the 90s [a.v. aho, algorithms for finding patterns in strings, in: jan van leeuwen (ed.), handbook of theoretical computer science, in: algorithms and complexity, vol. a, elsevier and mit press, 1990, pp. 255-300] and rigorously in 2003 by campeanu, salomaa and yu [c. campeanu, k. salomaa, s. yu, a formal study of practical regular expressions, ijfcs 14 (6) (2003) 1007-1018], when the authors reported an open problem, namely whether regex languages are closed under the intersection with regular languages. we give a positive answer; and for doing so, we propose a new class of machines - regex automata systems (ras) - which are equivalent to regex. among others, these machines provide a consistent and convenient method of implementing regex in practice. we also prove, as a consequence of this closure property, that several languages, such as the mirror language, the language of palindromes, and the language of balanced words are not regex languages.
conjugacy of finite biprefix codes. two languages x and y are called conjugates, if they satisfy the conjugacy equation xz=zy for some non-empty language z. we will compare solutions of this equation with those of the corresponding equation of words and study the case of finite biprefix codes x and y. we show that the maximal z in this case is rational. we will also characterize x and y in the case where they are both finite biprefix codes. this yields the decidability of the conjugacy of two finite biprefix codes.
a cache-friendly truncated fft. we describe a cache-friendly version of van der hoeven's truncated fft and inverse truncated fft, focusing on the case of 'large' coefficients, such as those arising in the schonhage-strassen algorithm for multiplication in z[x]. we describe two implementations and examine their performance.
identifying comparable entities on the web. web search engines are often presented with user queries that involve comparisons of real-world entities. thus far, this interaction has typically been captured by users submitting appropriately designed keyword queries for which they are presented a list of relevant documents. richer interactions that explicitly allow for a comparative analysis of entities represent a new potential direction to improve the search experience. with this in mind, we present an initial step of mining comparable entities from sources of information available to a large-scale web search engine, namely, search query logs and documents from a web crawl. our mining methods generate a diverse set of comparables consisting of entities from a broad class of categories, such as medicines, appliances, electronics, and vacation destinations.
mining tourist information from user-supplied collections. tourist photographs constitute a large part of the images uploaded to photo sharing platforms. but filtering methods are needed before one can extract useful knowledge from noisy user-supplied metadata. here we show how to extract clean trip related information (what people visit, for how long, panoramic spots) from flickr metadata. we illustrate our technique on a sample of metadata and images covering 183 cities of different size and from different parts of the world.
fast and effective histogram construction. histogram construction or sequence segmentation is a basic task with applications in database systems, information retrieval, and knowledge management. its aim is to approximate a sequence by line segments. unfortunately, the quadratic algorithm that derives an optimal histogram for euclidean error lacks the desired scalability. therefore, sophisticated approximation algorithms have been recently proposed, while several simple heuristics are used in practice. still, these solutions fail to resolve the efficiency-quality tradeoff in a satisfactory manner. in this paper we take a fresh view on the problem. we propose conceptually clear and scalable algorithms that efficiently derive high-quality histograms. we experimentally demonstrate that existing approximation schemes fail to deliver the desired efficiency and conventional heuristics do not fare well on the side of quality. on the other hand, our schemes match or exceed the quality of the former and the efficiency of the latter.
pseudo relevance feedback using semantic clustering in relevance language model. pseudo relevance feedback has demonstrated to be in general an effective technique for improving retrieval effectiveness, but the noise in the top retrieved documents still can cause topic drift problem that affects the performance of certain topics. by viewing a document as an interaction of a set of independent hidden topics, we propose a novel semantic clustering technique using independent component analysis. then within the language modeling framework, we apply the obtained semantic topic clusters into the query sampling process so that the sampling depends on the activated topics rather than on the individual document language model. therefore, we obtain a semantic cluster based relevance language model, which uses pseudo relevance feedback technique without requiring any relevance training information. we applied the model on five trec data sets. the experiments show that our model can significantly improve retrieval performance over traditional language models including relevance-based and clustering-based retrieval language models. the main contribution of the improvements comes from the estimation of the relevance model on the semantic clusters that are closely related to the query.
automatic link detection: a sequence labeling approach. the popularity of wikipedia and other online knowledge bases has recently produced an interest in the machine learning community for the problem of automatic linking. automatic hyperlinking can be viewed as two sub problems - link detection which determines the source of a link, and link disambiguation which determines the destination of a link. wikipedia is a rich corpus with hyperlink data provided by authors. it is possible to use this data to train classifiers to be able to mimic the authors in some capacity. in this paper, we introduce automatic link detection as a sequence labeling problem. conditional random fields (crfs) are a probabilistic framework for labeling sequential data. we show that training a crf with different types of features from the wikipedia dataset can be used to automatically detect links with almost perfect precision and high recall.
what's behind topic formation and development: a perspective of community core groups. over the past several years, there has been a great interest in topic detection and tracking (tdt). recently, analyzing general research trend from the huge amount of history documents also arouses considerable attention. however, existing work on tdt mainly focuses on overall trend analysis, and is unable to address questions such as "what determines the evolution of a topic?" and "when and how does a new topic get formed?". in this paper, we propose a core group model to explain the dynamics and further segment topic development. according to the division phase and interphase in the life cycle of a core group, a topic is separated into four states, i.e. birth state, extending state, saturation state and shrinkage state. experimental results on a real dataset show that the division of a core group brings on the generation of a new topic, and the progress of an entire topic is closely correlated to the growth of a core group during its interphase.
bridging the gap: complex networks meet information and knowledge management. in this article, we briefly summarize the motivation, content and structure of the cnikm'09 workshop.
exsearch: a novel vertical search engine for online barter business. e-commerce has shown its exponentially-growing business value in the past decade. however, in contrast to the successful examples in online sales, such as amazon1 and ebay2, the online barter business is still underexplored due to the lack of corresponding information aggregation service. in this paper, we design and implement a novel vertical search engine, called exsearch, to aggregate online barter information for developing the barter market. different from classical general purpose web search engines, exsearch adopts a focused crawler to gather related information from various websites. we propose to automatically extract the barter information from free-text web pages such that the unstructured information is represented in structured databases. in addition, we utilize the data mining techniques such as regression to fulfill the missing information, which cannot be extracted from the web pages. finally, we validate and rank the search results according to user queries. experimental results show that each component module in our proposed exsearch system is efficient and effective. the volunteer users are satisfied by and interested in this novel vertical search engine.
blog cascade affinity: analysis and prediction. information propagation within the blogosphere is of much importance in implementing policies, marketing research, launching new products, and other applications. in this paper, we take a microscopic view of the information propagation pattern in blogosphere by investigating blog cascade affinity. a blog cascade is a group of posts linked together discussing about the same topic, and cascade affnity refers to the phenomenon of a blog's inclination to join a specific cascade. we identify and analyze an array of features that may affect a blogger's cascade joining behavior and utilize these features to predict cascade affinity of blogs. evaluated on a real dataset consisting of 873,496 posts, our svm-based prediction achieved accuracy of 0.723 measured by f1. our experiments also showed that among all features identified, the number of friends was the most important factor affecting bloggers' inclination to join cascades.
a query model based on normalized log-likelihood. leveraging information from relevance assessments has been proposed as an effective means for improving retrieval. we introduce a novel language modeling method which uses information from each assessed document and their aggregate. while most previous approaches focus either on features of the entire set or on features of the individual relevant documents, our model exploits features of both the documents and the set as a whole. when evaluated, we show that our model is able to significantly improve over state-of-art feedback methods.
loop: local outlier probabilities. many outlier detection methods do not merely provide the decision for a single data object being or not being an outlier but give also an outlier score or "outlier factor" signaling "how much" the respective data object is an outlier. a major problem for any user not very acquainted with the outlier detection method in question is how to interpret this "factor" in order to decide for the numeric score again whether or not the data object indeed is an outlier. here, we formulate a local density based outlier detection method providing an outlier "score" in the range of [0, 1] that is directly interpretable as a probability of a data object for being an outlier.
predicting the conversion probability for items on c2c ecommerce sites. online ecommerce has been booming for a decade. for instance, as the largest online c2c marketplace (ebay), millions of new items are listed daily. due to the overwhelming number of items, the process of finding the right items to buy is sometimes daunting. in order to address this problem, this paper describes the idea of predicting the probability that a newly listed item will be sold successfully. and adjust the item exposure chances proportional according to their conversion possibility. hence, by ranking higher items that users are likely to buy, the chance that users make the purchases could be increased as well as their user satisfaction. for catalog products that have been listed repeatedly, this probability can be measured empirically. however, on c2c sites like ebay, lots of items are not product-based. they are unique, and from different sellers. therefore, in order to predict whether a new listing will be sold, we collect a large scale item set as the training data, and a set of features were used to model the average buyer shopping decision on c2c sites. experimental results verified our system's feasibility and effectiveness.
poka: identifying pareto-optimal k-anonymous nodes in a domain hierarchy lattice. data generalization is widely used to protect identities and prevent inference of sensitive information during the public release of microdata. the k-anonymity model has been extensively applied in this context. the model seeks a generalization scheme such that every individual becomes indistinguishable from at least k-1 other individuals and the loss in information while doing so is kept at a minimum. the search is performed on a domain hierarchy lattice where every node is a vector signifying the level of generalization for each attribute. an effort to understand privacy and data utility trade-offs will require knowing the minimum possible information losses of every possible value of k. however, this can easily lead to an exhaustive evaluation of all nodes in the hierarchy lattice. in this paper, we propose using the concept of pareto-optimality to obtain the desired trade-off information. a pareto-optimal generalization is one in which no other generalization can provide a higher value of k without increasing the information loss. we introduce the pareto-optimal k-anonymization (poka) algorithm to traverse the hierarchy lattice and show that the number of node evaluations required to find the pareto-optimal generalizations can be significantly reduced. results on a benchmark data set show that the algorithm is capable of identifying all pareto-optimal nodes by evaluating only 20% of nodes in the lattice.
opinion classification with tree kernel svm using linguistic modality analysis. we propose a method for classifying opinions which captures the role of linguistic modalities in the sentence. we use features than simple bag-of-words or opinion-holding predicates. the method is based on a machine learning and utilizes opinion-holding predicates and linguistic modalities as features. two different detectors help to classify the opinions: the opinion-holding predicate detector and the modality detector. an opinion in the target is first parsed into a dependency structure, and then the opinion-holding predicates and modalities stick onto the leaf nodes of the dependency tree. the whole tree is regarded as input features of the opinion, and it becomes the input of tree kernel support vector machines. we have applied method to opinions in japanese about television programs, and have confirmed the effectiveness of the method against conventional bag-of-words features, or against simple opinion-holding predicates features
inverted indexes vs. bitmap indexes in decision support systems. bitmap indexes are widely used in decision support systems (dsss) to improve query performance. in this paper, we evaluate the use of compressed inverted indexes with adapted query processing strategies from information retrieval as an alternative. in a thorough experimental evaluation on both synthetic data and data from the star schema benchmark, we show that inverted indexes are more compact than bitmap indexes in almost all cases. this compactness combined with efficient query processing strategies results in inverted indexes outperforming bitmap indexes for most queries, often significantly.
fragment-based clustering ensembles. clustering ensembles combine different clustering solutions into a single robust and stable one. most of existing methods become highly time-consuming when the data size turns to large. in this paper, we study the properties of the defined 'clustering fragment' and put forward a useful proposition. solid proofs are presented with two widely used goodness measures for clustering ensembles. finally, a new ensemble framework termed as fragment-based clustering ensembles is proposed. theoretically, most of existing methods can be improved by adopting this framework. to evaluate the proposed framework, three new methods are introduced by bring three popular clustering ensemble methods into our framework. the experimental results on several public data sets show that the three introduced methods are greatly improved in computational complexity and also achieved better or similar accurate results than the original methods.
characteristics of document similarity measures for compliance analysis. due to increased competition in the it services business, improving quality, reducing costs and shortening schedules has become extremely important. a key strategy being adopted for achieving these goals is the use of an asset-based approach to service delivery, where standard reusable components developed by domain experts are minimally modified for each customer instead of creating custom solutions. one example of this approach is the use of contract templates, one for each type of service offered. a compliance checking system that measures how well actual contracts adhere to standard templates is critical for ensuring the success of such an approach. this paper describes the use of document similarity measures - cosine similarity and latent semantic indexing - to identify the top candidate templates on which a more detailed (and expensive) compliance analysis can be performed. comparison of results of using the different methods are presented.
a co-classification framework for detecting web spam and spammers in social media web sites. social media are becoming increasingly popular and have attracted considerable attention from spammers. using a sample of more than ninety thousand known spam web sites, we found between 7% to 18% of their urls are posted on two popular social media web sites, digg.com and delicious.com. in this paper, we present a co-classification framework to detect web spam and the spammers who are responsible for posting them on the social media web sites. the rationale for our approach is that since both detection tasks are related, it would be advantageous to train them simultaneously to make use of the labeled examples in the web spam and spammer training data. we have evaluated the effectiveness of our algorithm on the delicious.com data set. our experimental results showed that the proposed co-classification algorithm significantly outperforms classifiers that learn each detection task independently.
retrieval constraints and word frequency distributions: a log-logistic model for ir. we first present in this paper an analytical view of heuristic retrieval constraints which yields simple tests to determine whether a retrieval function satisfies the constraints or not. we then review empirical findings on word frequency distributions and the central role played by burstiness in this context. this leads us to propose a formal definition of burstiness which can be used to characterize probability distributions wrt this phenomenon. we then introduce the family of information-based ir models which naturally captures heuristic retrieval constraints when the underlying probability distribution is bursty and propose a new ir model within this family, based on the log-logistic distribution. the experiments we conduct on three different collections illustrate the good behavior of the log-logistic ir model: it significantly outperforms the jelinek-mercer and dirichlet prior language models on all three collections, with both short and long queries and for both the map and the precision at 10 documents. it also outperforms the inl2 dfr model for the map, and yields results on a par with it for the precision at 10.
enhancing expertise retrieval using community-aware strategies. expertise retrieval has received increased interests in recent years, whose task is to suggest people with relevant expertise. motivated by the observation that communities could provide valuable insight and distinctive information, we investigate two community-aware strategies to enhance expertise retrieval. we first propose a new smoothing method using the community context instead of the whole collection for statistical language model in the document-based model. furthermore, a query-sensitive authorrank is proposed to model the authors' authorities according to the community co-authorship networks, and then an adaptive ranking refinement method is developed to further enhance expertise retrieval. experimental results demonstrate the effectiveness and robustness of both community-aware strategies.
exploiting bidirectional links: making spamming detection easier. previous anti-spamming algorithms based on link structure suffer from either the weakness of the page value metric or the vagueness of the seed selection. in this paper, we propose two page value metrics, avrank and hvrank. these two "values" of all the web pages can be well assessed by using the bidirectional links' information. moreover, with the help of bidirectional links, it becomes easier to enlarge the propagation coverage of seed sets. we further discuss the effectiveness of the combination of these two metrics, such as the quadratic mean of them. our experimental results show that with such two metrics, our method can filter out spam sites and identify reputable ones more effectively than previous algorithms such as trustrank.
cross-domain sentiment classification using a two-stage method. in this paper, we give out a two-stage approach for domain adaptation problem in sentiment classification. in the first stage, based on our observation that customers often use different words to comment on the similar topics in the different domains, we regard these common topics as the bridge to link the different domain-specific features. we propose a novel topic model named transfer-plsa to extract the topic knowledge between different domains. through these common topics, the features in the source domain are corresponded to the target features, so that those domain-specific knowledge can be transferred across different domains. in the second step, we use the classifier trained on the labeled examples in the source domain to pick up some informative examples in the target domain. then we retrain the classifier on these selected examples, so that the classifier is adapted for the target domain. experimental results on sentiment classification in four different domains indicate that our method outperforms other traditional methods.
predicting the volume of comments on online news stories. on-line news agents provide commenting facilities for readers to express their views with regard to news stories. the number of user supplied comments on a news article may be indicative of its importance or impact. we report on exploratory work that predicts the comment volume of news articles prior to publication using five feature sets. we address the prediction task as a two stage classification task: a binary classification identifies articles with the potential to receive comments, and a second binary classification receives the output from the first step to label articles "low" or "high" comment volume. the results show solid performance for the former task, while performance degrades for the latter.
topic and keyword re-ranking for lda-based topic modeling. topic-based text summaries promise to help average users quickly understand a text collection and derive insights. recent research has shown that the latent dirichlet allocation (lda) model is one of the most effective approaches to topic analysis. however, the lda-based results may not be ideal for human understanding and consumption. in this paper, we present several topic and keyword re-ranking approaches that can help users better understand and consume the lda-derived topics in their text analysis. our methods process the lda output based on a set of criteria that model a user's information needs. our evaluation demonstrates the usefulness of the methods in summarizing several large-scale, real world data sets.
a code generation approach to optimizing high-performance distributed data stream processing. we present a code-generation-based optimization approach to bringing performance and scalability to distributed stream processing applications. we express stream processing applications using an operator-based, stream-centric language called spade, which supports composing distributed data flow graphs out of toolkits of type-generic operators. a major challenge in building such applications is to find an effective and flexible way of mapping the logical graph of operators into a physical one that can be deployed on a set of distributed nodes. this involves finding how best operators map to processes and how best processes map to computing nodes. in this paper, we take a two-stage optimization approach, where an instrumented version of the application is first generated by the spade compiler to profile and collect statistics about the processing and communication characteristics of the operators within the application. in the second stage, the profiling information is fed to an optimizer to come up with a physical data flow graph that is deployable across nodes in a computing cluster. this approach not only creates highly optimized applications that are tailored to the underlying computing and networking infrastructure, but also makes it possible to re-target the application to a different hardware setup by simply repeating the optimization step and re-compiling the application to match the physical flow graph produced by the optimizer. using real-world applications, from diverse domains such as finance and radio-astronomy, we demonstrate the effectiveness of our approach on system s -- a large-scale, distributed stream processing platform.
consistent on-line classification of dbs workload events. an important goal of self-managing databases is the autonomic adaptation of the database configuration to evolving workloads. however, the diversity of sql statements in real-world workloads typically causes the required analysis overhead to be prohibitive for a continuous workload analysis. the workload classification presented in this paper reduces the workload analysis overhead by grouping similar workload events into classes. our approach employs clustering techniques based upon a general distance function for dbs workload events. to be applicable for a continuous workload analysis, our workload classification specifically addresses a stream-based, lightweight operation, a controllable loss of quality, and self-management.
efficient joins with compressed bitmap indexes. we present a new class of adaptive algorithms that use compressed bitmap indexes to speed up evaluation of the range join query in relational databases. we determine the best strategy to process a join query based on a fast sub-linear time computation of the join selectivity (the ratio of the number of tuples in the result to the total number of possible tuples). in addition, we use compressed bitmaps to represent the join output compactly: the space requirement for storing the tuples representing the join of two relations is asymptotically bounded by min(h; n.cb), where h is the number of tuple pairs in the result relation, n is the number of tuples in the smaller of the two relations, and cb is the cardinality of the larger column being joined. we present a theoretical analysis of our algorithms, as well as experimental results on large-scale synthetic and real data sets. our implementations are efficient, and consistently outperform well-known approaches for a range of join selectivity factors. for instance, our count-only algorithm is up to three orders of magnitude faster than the sort-merge approach, and our best bitmap index-based algorithm is 1.2x-80x faster than the sort-merge algorithm, for various query instances. we achieve these speedups by exploiting several inherent performance advantages of compressed bitmap indexes for join processing: an implicit partitioning of the attributes, space-efficiency, and tolerance of high-cardinality relations.
clustering object moving patterns for prediction-based object tracking sensor networks. prior works have shown that probabilistic suffix trees (pst) could predict accurately the moving behaviors of objects for prediction-based object tracking sensor networks. however, maintaining psts for objects incurs a considerable amount of storage spaces for resource-constrained sensor nodes. in this paper, we derive a distance function between two psts and propose an algorithm to determine the similarity between them. by the distance between psts, we propose a clustering algorithm to partition objects with similar moving behaviors into groups. furthermore, for each group, one pst is selected to predict movements of objects within one group. experimental results show that our proposed approaches not only effectively reduce the storage cost but also provide good prediction accuracy.
interpretable and reconfigurable clustering of document datasets by deriving word-based rules. clusters of text documents output by clustering algorithms are often hard to interpret. we describe motivating real-world scenarios that necessitate reconfigurability and high interpretability of clusters and outline the problem of generating clusterings with interpretable and reconfigurable cluster models. we develop a clustering algorithm toward the outlined goal of building interpretable and reconfigurable cluster models; it works by generating rules with disjunctions and conditions on the frequencies of words, to decide on the membership of a document to a cluster. each cluster is comprised of precisely the set of documents that satisfy the corresponding rule. we show that our approach outperforms the unsupervised decision tree approach by huge margins. we show that the purity and f-measure losses to achieve interpretability are as little as 5% and 3% respectively using our approach.
measuring system performance and topic discernment using generalized adaptive-weight mean. standard approaches to evaluating and comparing information retrieval systems compute simple averages of performance statistics across individual topics to measure the overall system performance. however, topics vary in their ability to differentiate among systems based on their retrieval performance. at the same time, systems that perform well on discriminative queries demonstrate notable qualities that should be reflected in the systems' evaluation and ranking. this motivated research on alternative performance measures that are sensitive to the discriminative value of topics and the performance consistency of systems. in this paper we provide a mathematical formulation of a performance measure that postulates the dependence between the system and topic characteristics. we propose the generalized adaptive-weight mean (gawm) measure and show how it can be computed as a fixed point of a function for which the brouwer fixed point theorem applies. this guarantees the existence of a scoring scheme that satisfies the starting axioms and can be used for ranking of both systems and topics. we apply our method to trec experiments and compare the gawm with the standard averages used in trec.
agglomerating local patterns hierarchically with alpha. to increase the relevancy of local patterns discovered from noisy relations, it makes sense to formalize error-tolerance. our starting point is to address the limitations of state-of-the-art methods for this purpose. some extractors perform an exhaustive search w.r.t. a declarative specification of error-tolerance. nevertheless, their computational complexity prevents the discovery of large relevant patterns. alpha is a 3-step method that (1) computes complete collections of closed patterns, possibly error-tolerant ones, from arbitrary n-ary relations, (2) enlarges them by hierarchical agglomeration, and (3) selects the relevant agglomerated patterns.
incremental query evaluation for support vector machines. support vector machines (svms) have been widely used in multimedia retrieval to learn a concept in order to find the best matches. in such a svm active learning environment, the system first processes k sampling queries and top-k uncertain queries to select the candidate data items for training. the user's top-k relevant queries are then evaluated to compute the answer. this approach has shown to be effective. however, it suffers from the scalability problem associated with larger database sizes. to address this limitation, we propose an incremental query evaluation technique for these three types of queries. based on the observation that most queries are not revised dramatically during the iterative evaluation, the proposed technique reuses the results of previous queries to reduce the computation cost. furthermore, this technique takes advantage of a tuned index structure to efficiently prune irrelevant data. as a result, only a small portion of the data set needs to be accessed for query processing. this index structure also provides an inexpensive means to process the set of candidates to evaluate the final query result. this technique can work with different kernel functions and kernel parameters. our experimental results indicate that the proposed technique significantly reduces the overall computation cost, and offers a promising solution to the scalability issue.
to divide and conquer search ranking by learning query difficulty. learning to rank plays an important role in information retrieval. in most of the existing solutions for learning to rank, all the queries with their returned search results are learnt and ranked with a single model. in this paper, we demonstrate that it is highly beneficial to divide queries into multiple groups and conquer search ranking based on query difficulty. to this end, we propose a method which first characterizes a query using a variety of features extracted from user search behavior, such as the click entropy, the query reformulation probability. next, a classification model is built on these extracted features to assign a score to represent how difficult a query is. based on this score, our method automatically divides queries into groups, and trains a specific ranking model for each group to conquer search ranking. experimental results on ranksvm and ranknet with a large-scale evaluation dataset show that the proposed method can achieve significant improvement in the task of web search ranking.
improving binary classification on text problems using differential word features. we describe an efficient technique to weigh word-based features in binary classification tasks and show that it significantly improves classification accuracy on a range of problems. the most common text classification approach uses a document's ngrams (words and short phrases) as its features and assigns feature values equal to their frequency or tfidf score relative to the training corpus. our approach uses values computed as the product of an ngram's document frequency and the difference of its inverse document frequencies in the positive and negative training sets. while this technique is remarkably easy to implement, it gives a statistically significant improvement over the standard bag-of-words approaches using support vector machines on a range of classification tasks. our results show that our technique is robust and broadly applicable. we provide an analysis of why the approach works and how it can generalize to other domains and problems.
using domain ontology for semantic web usage mining and next page prediction. this paper proposes the integration of semantic information drawn from a web application's domain knowledge into all phases of the web usage mining process (preprocessing, pattern discovery, and recommendation/prediction). the goal is to have an intelligent semantics-aware web usage mining framework. this is accomplished by using semantic information in the sequential pattern mining algorithm to prune the search space and partially relieve the algorithm from support counting. in addition, semantic information is used in the prediction phase with low order markov models, for less space complexity and accurate prediction, that will help ambiguous predictions problem. experimental results show that semantics-aware sequential pattern mining algorithms can perform 4 times faster than regular non-semantics-aware algorithms with only 26% of the memory requirement.
instance- and bag-level manifold regularization for aggregate outputs classification. aggregate outputs learning differs from the classical supervised learning setting in that, training samples are packed into bags with only the aggregate outputs (labels for classification or real values for regression) known. this setting of the problem is associated with several kinds of application background. we focus on the aggregate outputs classification problem in this paper, and set up a manifold regularization framework to deal with it. the framework can be of both instance level and bag level for different testing goals. we propose four concrete algorithms based on our framework, each of which can cope with both binary and multi-class scenarios. the experimental results on several datasets suggest that our algorithms outperform the state-of-art technique.
probabilistic models of ranking novel documents for faceted topic retrieval. traditional models of information retrieval assume documents are independently relevant. but when the goal is retrieving diverse or novel information about a topic, retrieval models need to capture dependencies between documents. such tasks require alternative evaluation and optimization methods that operate on different types of relevance judgments. we define faceted topic retrieval as a particular novelty-driven task with the goal of finding a set of documents that cover the different facets of an information need. a faceted topic retrieval system must be able to cover as many facets as possible with the smallest number of documents. we introduce two novel models for faceted topic retrieval, one based on pruning a set of retrieved documents and one based on retrieving sets of documents through direct optimization of evaluation measures. we compare the performance of our models to mmr and the probabilistic model due to zhai et al. on a set of 60 topics annotated with facets, showing that our models are competitive.
stereotrust: a group based personalized trust model. trust plays important roles in diverse decentralized environments, including our society at large. computational trust models help to, for instance, guide users' judgements in online auction sites about other users; or determine quality of contributions in web 2.0 sites. most of the existing trust models, however, require historical information about past behavior of a specific agent being evaluated - information that is not always available. in contrast, in real life interactions among users, in order to make the first guess about the trustworthiness of a stranger, we commonly use our "instinct" - essentially stereotypes developed from our past interactions with "similar" people. we propose stereotrust, a computational trust model inspired by real life stereotypes. a user forms stereotypes using her previous transactions with other agents. a stereotype contains certain features of agents and an expected outcome of the transaction. these features can be taken from agents' profile information, or agents' observed behavior in the system. when facing a stranger, the stereotypes matching stranger's profile are aggregated to derive his expected trust. additionally, when some information about stranger's previous transactions is available, stereotrust uses it to refine the stereotype matching. according to our experiments, stereotrust compares favorably with existing trust models that use different kind of information and more complete historical information. moreover, because evaluation is done according to user's personal stereotypes, the system is completely distributed and the result obtained is personalized. stereotrust can be used as a complimentary mechanism to provide the initial trust value for a stranger, especially when there is no trusted, common third parties.
ofcourse: web content discovery, classification and information extraction for online course materials. in this paper we present ofcourse, a vertical search engine for online course materials. these materials have the following characteristics: they are scattered very sparsely in the university web sites; and are generated by the teachers with totally different hmtl templates and layouts. these characteristics impose some challenges for web classification (to identify the course materials) and web information extraction (to extract course metadata, such as course title, time and id) from the identified course homepages. here, we describe our proposed method to tackle these challenges, and the features of this system. ofcourse, containing over 60,000 courses from the top 50 universities in the us, is currently available for public access at http://fusion.hpl.hp.com/ofcourse/.
automatic generation of topic pages using query-based aspect models. we investigate the automatic generation of topic pages as an alternative to the current web search paradigm. we describe a general framework, which combines query log analysis to build aspect models, sentence selection methods for identifying relevant and non-redundant web sentences, and a technique for sentence ordering. we evaluate our approach on biographical topics both automatically and manually, by using wikipedia as reference.
bitmap indexes for relational xml twig query processing. due to an increasing volume of xml data, it is considered prudent to store xml data on an industry-strength database system instead of relying on a domain specific application or a file system. for shredded xml data stored in the relational tables, however, it may not be straightforward to apply existing algorithms for twig query processing, because most of the algorithms require xml data to be accessed in a form of streams of elements grouped by their tags and sorted in a particular order. in order to support xml query processing within the common framework of relational database systems, we first propose several bitmap indexes for supporting holistic twig joins on xml data stored in the relational tables. since bitmap indexes are well supported in most of the commercial and open-source database systems, the proposed bitmap indexes and twig query processing algorithms can be incorporated into the relational query processing framework with more ease. the proposed query processing algorithms are efficient in terms of both time and space, since the compressed bitmap indexes stay compressed during query processing. in addition, we propose a hybrid index which computes twig query solutions with only bit-vectors, without accessing labeled xml elements stored in the relational tables.
effective, design-independent xml keyword search. keyword search techniques that take advantage of xml structure make it very easy for ordinary users to query xml databases, but current approaches to processing these queries rely on intuitively appealing heuristics that are ultimately ad hoc. these approaches often retrieve irrelevant answers, overlook relevant answers, and cannot rank answers appropriately. to address these problems for data-centric xml, we propose coherency ranking (cr), a domain- and database design-independent ranking method for xml keyword queries that is based on an extension of the concept of mutual information. with cr, the results of a keyword query are invariant under schema reorganization. we analyze how previous approaches to xml keyword search approximate cr, and present efficient algorithms to perform cr. our empirical evaluation with 65 user-supplied queries over two real-world xml data sets shows that cr has better precision and recall and provides better ranking than all previous approaches.
product query classification. web query classification is an effective way to understand web user intents, which can further improve web search and online advertising relevance. however, web queries are usually very short which cannot fully reflect their meanings. what is more, it is quite hard to obtain enough training data for training accurate classifiers. therefore, previous work on query classification has focused on two issues. one is how to represent web queries through query expansion. the other is how to increase the amount of training data. in this paper, we took product query classification as an example, which is to classify web queries into a predefined product taxonomy, and systematically studied the impact of query expansion and the size of training data. we proposed two methods of enriching web queries and three approaches of collecting training data. thereafter, we conducted a series of experiments to compare the classification performance of using different combinations of training data and query representations over a real data set. the data set consists of hundreds of thousands queries collected from a popular commercial search engine. from the experiments, we found some interesting observations, which were not discussed before. finally, we proposed an effective and efficient product query classification method based on our observations.
on the feasibility of multi-site web search engines. web search engines are often implemented as centralized systems. designing and implementing a web search engine in a distributed environment is a challenging engineering task that encompasses many interesting research questions. however, distributing a search engine across multiple sites has several advantages, such as utilizing less compute resources and exploiting data locality. in this paper we investigate the cost-effectiveness of building a distributed web search engine. we propose a model for assessing the total cost of a distributed web search engine that includes the computational costs and the communication cost among all distributed sites. we then present a query-processing algorithm that maximizes the amount of queries answered locally, without sacrificing the quality of the results compared to a centralized search engine. we simulate the algorithm on real document collections and query workloads to measure the actual parameters needed for our cost model, and we show that a distributed search engine can be competitive compared to a centralized architecture with respect to real cost.
incorporating robustness into web ranking evaluation. in many web search engines, a ranking function is selected for deployment mainly by comparing the relevance measurements over candidates. due to the dynamical nature of the web, the ranking features and the query and url distribution on which the ranking functions are built, may change dramatically over time. the actual relevance of the function may degrade, and thus the previous function selection conclusions become invalid. in this work we suggest to select web ranking functions according to both their relevance and robustness to the changes that may lead to relevance degradation over time. we argue that the ranking robustness can be effectively measured by taking into account the ranking score distribution across search results. we then propose two alternatives to the ndcg metric that both incorporate ranking robustness into ranking function evaluation and selection. a machine learning approach is developed to learn the parameters that control the metric sensitivity to score turbulence, from human-judged preference data.
framework for timely and accurate ads on mobile devices. we propose a framework for mobile advertising covering value-added services where an ad-database is maintained on the device and both selection and display are dictated by the device. advantages over existing mobile marketing are that ads are more timely, viable on a variety of use cases, can be both location-sensitive and personalized with minimal privacy concerns, and provide an obvious means for subsidizing users' service costs. we construct a suitable selection algorithm and evaluate its execution, accuracy and scalability. we show that ad-serving can be done under the processing constraints imposed by mobiles, which may lead to improvements in mobile marketing effectiveness.
helping editors choose better seed sets for entity set expansion. sets of named entities are used heavily at commercial search engines such as google, yahoo and bing. acquiring sets of entities typically consists of combining semi-supervised expansion algorithms with manual cleaning of the resulting expanded sets. in this paper, we study the effects of different seed sets in a state-of-the-art semi-supervised expansion system and show a tremendous variation in expansion performance depending on the choice of seeds. we further show that human editors, in general, provide very bad seed sets, which perform well-below the average random seed set. we identify three factors of seed set composition, namely prototypicality, ambiguity and coverage, and we investigate their effects on expansion performance. finally, we propose various automatic systems for improving editor-generated seed sets, which seek to remove ambiguous and other error-prone seed instances. an extensive experimental analysis shows that expansion quality, measured in r-precision, can be improved on average by a maximum of 46% by removing the right seeds from a seed set. our automatic methods outperform the human editors seed sets and on average improve expansion performance by up to 34% over the original seed sets.
semi-supervised learning of semantic classes for query understanding: from the web and for the web. understanding intents from search queries can improve a user's search experience and boost a site's advertising profits. query tagging via statistical sequential labeling models has been shown to perform well, but annotating the training set for supervised learning requires substantial human effort. domain-specific knowledge, such as semantic class lexicons, reduces the amount of needed manual annotations, but much human effort is still required to maintain these as search topics evolve over time. this paper investigates semi-supervised learning algorithms that leverage structured data (html lists) from the web to automatically generate semantic-class lexicons, which are used to improve query tagging performance - even with far less training data. we focus our study on understanding the correct objectives for the semi-supervised lexicon learning algorithms that are crucial for the success of query tagging. prior work on lexicon acquisition has largely focused on the precision of the lexicons, but we show that precision is not important if the lexicons are used for query tagging. a more adequate criterion should emphasize a trade-off between maximizing the recall of semantic class instances in the data, and minimizing the confusability. this ensures that the similar levels of precision and recall are observed on both training and test set, hence prevents over-fitting the lexicon features. experimental results on retail product queries show that enhancing a query tagger with lexicons learned with this objective reduces word level tagging errors by up to 25% compared to the baseline tagger that does not use any lexicon features. in contrast, lexicons obtained through a precision-centric learning algorithm even degrade the performance of a tagger compared to the baseline. furthermore, the proposed method outperforms one in which semantic class lexicons have been extracted from a database.
ossobook: database and knowledgemanagement techniques for archaeozoology. this demo describes the ossobook database system developed for archaeozoology applications providing data storage, data retrieval, and data mining facilities. it shows a case study of integrating state-of-the-art database concepts like intermittently synchronized database system as well as concepts of information retrieval and knowledge representation like similarity search and data mining in order to provide a comprehensive system for an interesting application domain.
smoothing dcg for learning to rank: a novel approach using smoothed hinge functions. discounted cumulative gain (dcg) is widely used for evaluating ranking functions. it is therefore natural to learn a ranking function that directly optimizes dcg. however, dcg is non-smooth, rendering gradient-based optimization algorithms inapplicable. to remedy this, smoothed versions of dcg have been proposed but with only partial success. in this paper, we first present analysis that shows it is ineffective using the gradient of the smoothed dcg to drive the optimization algorithm. we then propose a novel approach, shf-sdcg, for smoothing dcg by using smoothed hinge functions (shf). it has the advantage of seamlessly transition from driving the optimization mimicking pairwise learning when the ranking function does not fit the data well, to driving the optimization using dcg when the ranking function becomes more accurate. shf-sdcg is then extended to reg-shf-sdcg, an algorithm which gradually transits from pointwise and pairwise to listwise learning. finally experimental results are provided to validate the effectiveness of shf-sdcg and reg-shf-sdcg.
enhancing recommender systems under volatile userinterest drifts. this paper presents a systematic study of how to enhance recommender systems under volatile user interest drifts. a key development challenge along this line is how to track user interests dynamically. to this end, we first define four types of interest patterns to understand users' rating behaviors and analyze the properties of these patterns. we also propose a rating graph and rating chain based approach for detecting these interest patterns. for each users' rating series, a rating graph and a rating chain are constructed based on the similarities between rated items. the type of a given user's interest pattern is identified through the density of the corresponding rating graph and the continuity of the corresponding rating chain. in addition, we propose a general algorithm framework for improving recommender systems by exploiting these identified patterns. finally, experimental results on a real-world data set show that the proposed rating graph based approach is effective for detecting user interest patterns, which in turn help to improve the performance of recommender systems.
a social recommendation framework based on multi-scale continuous conditional random fields. this paper addresses the issue of social recommendation based on collaborative filtering (cf) algorithms. social recommendation emphasizes utilizing various attributes information and relations in social networks to assist recommender systems. although recommendation techniques have obtained distinct developments over the decades, traditional cf algorithms still have these following two limitations: (1) relational dependency within predictions, an important factor especially when the data is sparse, is not being utilized effectively; and (2) straightforward methods for combining features like linear integration suffer from high computing complexity in learning the weights by enumerating the whole value space, making it difficult to combine various information into an unified approach. in this paper, we propose a novel model, multi-scale continuous conditional random fields (mccrf), as a framework to solve above problems for social recommendations. in mccrf, relational dependency within predictions is modeled by the markov property, thus predictions are generated simultaneously and can help each other. this strategy has never been employed previously. besides, diverse information and relations in social network can be modeled by state and edge feature functions in mccrf, whose weights can be optimized globally. thus both problems can be solved under this framework. in addition, we propose to utilize markov chain monte carlo (mcmc) estimation methods to solve the difficulties in training and inference processes of mccrf. experimental results conducted on two real world data have demonstrated that our approach outperforms traditional cf algorithms. additional experiments also show the improvements from the two factors of relational dependency and feature combination, respectively.
aging effects on query flow graphs for query suggestion. world wide web content continuously grows in size and importance. furthermore, users ask web search engines to satisfy increasingly disparate information needs. new techniques and tools are constantly developed aimed at assisting users in the interaction with the web search engine. query recommender systems suggesting interesting queries to users are an example of such tools. most query recommendation techniques are based on the knowledge of the behaviors of past users of the search engine recorded in query logs. a recent query-log mining approach for query recommendation is based on query flow graphs (qfg). in this paper we propose an evaluation of the effects of time on this query recommendation model. as users interests change over time, the knowledge extracted from query logs may suffer an aging effect as new interesting topics appear. in order to validate experimentally this hypothesis, we build different query flow graphs from the queries belonging to a large query log of a real-world search engine. each query flow graph is built on distinct query log segments. then, we generate recommendations on different sets of queries. results are assessed both by means of human judgments and by using an automatic evaluator showing that the models inexorably age.
independent informative subgraph mining for graph information retrieval. in order to enable scalable querying of graph databases, intelligent selection of subgraphs to index is essential. an improved index can reduce response times for graph queries significantly. for a given subgraph query, graph candidates that may contain the subgraph are retrieved using the graph index and subgraph isomorphism tests are performed to prune out unsatisfied graphs. however, since the space of all possible subgraphs of the whole set of graphs is prohibitively large, feature selection is required to identify a good subset of subgraph features for indexing. thus, one of the key issues is: given the set of all possible subgraphs of the graph set, which subset of features is the optimal such that the algorithm retrieves the smallest set of candidate graphs and reduces the number of subgraph isomorphism tests? we introduce a graph search method for subgraph queries based on subgraph frequencies. then, we propose several novel feature selection criteria, max-precision, max-irredundant-information, and max-information-min-redundancy, based on mutual information. finally we show theoretically and empirically that our proposed methods retrieve a smaller candidate set than previous methods. for example, using the same number of features, our method improve the precision for the query candidate set by 4%-13% in comparison to previous methods. as a result the response time of subgraph queries also is improved correspondingly.
vetting the links of the web. many web links mislead human surfers and automated crawlers because they point to changed content, out-of-date information, or invalid urls. it is a particular problem for large, well-known directories such as the dmoz open directory project, which maintains links to representative and authoritative external web pages within their various topics. therefore, such sites involve many editors to manually revisit and revise links that have become out-of-date. to remedy this situation, we propose the novel web mining task of identifying outdated links on the web. we build a general classification model, primarily using local and global temporal features extracted from historical content, topic, link and time-focused changes over time. we evaluate our system via five-fold cross-validation on more than fifteen thousand odp external links selected from thirteen top-level categories. our system can predict the actions of odp editors more than 75% of the time. our models and predictions could be useful for various applications that depend on analysis of web links, including ranking and crawling.
refmed: relevance feedback retrieval system fo pubmed. finding related articles from the pubmed (a large biomedical literature repository) is challenging because it is hard to express the user's specific relevance in the given query interface and a keyword query typically retrieves many results. biomedical researchers spend a critical amount of time (e.g., often more than several days) in the literature search process. this paper proposes refmed, a novel search system for pubmed, which supports relevance ranking by enabling relevance feedback on pubmed. refmed first returns initial result documents for a user's keyword query as in pubmed. the user then makes relevance judgments on some of the resultant documents while browsing them. once the user "pushes the feedback", the system induces a relevance function using ranksvm and ranks the results according to the function. to realize the ad-hoc relevance retrieval on pubmed, refmed "tightly" integrates ranksvm within rdbms and runs the rank learning and process on the fly with a response time of a few minutes.our qualitative experiments with biomedical researchers show that refmed substantially reduces the amount of effort required to search related pubmed articles. refmed is accessible at "http://dm.postech.ac.kr/refmed".
characterizing commercial intent. understanding the intent underlying user's queries may help personalize search results and therefore improve user satisfaction. we develop a methodology for using the content of search engine result pages (serps) along with the information obtained from query strings to study characteristics of query intent, with a particular focus on sponsored search. this work represents an initial step towards the development and evaluation of an ontology for commercial search, considering queries that reference specific products, brands and retailers. the characteristics of query categories are studied with respect to aggregated user's clickthrough behavior on advertising links. we present a model for clickthrough behavior that considers the influence of such factors as the location of ads and the rank of ads, along with query category. we evaluate our work using a large corpus of clickthrough data obtained from a major commercial search engine. our findings suggest that query based features, along with the content of serps, are effective in detecting query intent. the clickthrough behavior is found to be consistent with the classification for the general categories of query intent, while for product, brand and retailer categories, all is true to a lesser extent.
acronym extraction and disambiguation in large-scale organizational web pages. in this paper, we focus on the automatic extraction and disambiguation of acronyms in large-scale organizational web pages, which is important but difficult due to the diversity of acronyms and the scale of organizational web pages. we propose two novel algorithms to address the key problems in acronym extraction and disambiguation: (1) an unsupervised ranking algorithm to automatically filter out the incorrect acronym-expansion pairs. different from the existing approaches, our method does not require any hand-crafted rules; (2) a graph-based algorithm to disambiguate ambiguous acronyms, which leverages the hyperlinks of pages to facilitate the acronym disambiguation. we evaluate the proposed approaches using two large-scale, real-world datasets in two different domains. our experimental results show that our approach is domain independent, and achieves higher precision and recall than the existing methods.
imecho: an associative memory based desktop search system. traditional desktop search engines only support keyword based search that needs exact keyword matching to find resources. however, users generally have a vague picture of what is stored but forget the exact location and keywords of the resource. according to observations of human associative memory, people tend to remember things from some memory fragments in their brains and these memory fragments are connected by memory cues of user activity context. we developed imecho (my memory echo), an associative memory based desktop search system, which exploits such associations and contexts to enhance traditional desktop search. desktop resources are connected with semantic links mined from explicit and implicit user activities according to specific access patterns. using these semantic links, associations among memory fragments can be built or rebuilt in a user's brain during a search. moreover, our personalized ranking scheme uses these links together with a user's personal preferences to rank results by both relevance and importance to the user. in addition, the system provides a faceted search feature and association graph navigation to help users refine and associate search results generated by full-text keyword search. our experiments investigating precision and recall quality of imecho prototype show that the association-based search system is superior to the traditional keyword search in personal search engines since it is closer to the way that human associative memory works.
nonlinear static-rank computation. mainstream link-based static-rank algorithms (e.g. pagerank and its variants) express the importance of a page as the linear combination of its in-links and compute page importance scores by solving a linear system in an iterative way. such linear algorithms, however, may give apparently unreasonable static-rank results for some link structures. in this paper, we examine the static-rank computation problem from the viewpoint of evidence combination and build a probabilistic model for it. based on the model, we argue that a nonlinear formula should be adopted, due to the correlation or dependence between links. we focus on examining some simple formulas which only consider the correlation between links in the same domain. experiments conducted on 100 million web pages (with multiple static-rank quality evaluation metrics) show that higher quality static-rank could be yielded by the new nonlinear algorithms. the convergence of the new algorithms is also proved in this paper by nonlinear functional analysis.
a machine learning approach for improved bm25 retrieval. despite the widespread use of bm25, there have been few studies examining its effectiveness on a document description over single and multiple field combinations. we determine the effectiveness of bm25 on various document fields. we find that bm25 models relevance on popularity fields such as anchor text and query click information no better than a linear function of the field attributes. we also find query click information to be the single most important field for retrieval. in response, we develop a machine learning approach to bm25-style retrieval that learns, using lambdarank, from the input attributes of bm25. our model significantly improves retrieval effectiveness over bm25 and bm25f. our data-driven approach is fast, effective, avoids the problem of parameter tuning, and can directly optimize for several common information retrieval measures. we demonstrate the advantages of our model on a very large real-world web data collection.
probabilistic moving range query over rfid spatio-temporal data streams. moving range query over rfid data streams is one of the most important spatio-temporal queries to support valuable information analysis. however, the location uncertainty challenges the query strategy. in this paper, we propose a probability evaluation model in the rfid-enabled monitoring environments and discuss the query optimization techniques under the scenarios of continuous moving range query, which can also be applied into more situations. the extensive experimental evaluation verifies the efficiency and effectiveness of our proposed model and methods.
similarity-aware indexing for real-time entity resolution. entity resolution, also known as data matching or record linkage, is the task of identifying and matching records from several databases that refer to the same entities. traditionally, entity resolution has been applied in batch-mode and on static databases. however, many organisations are increasingly faced with the challenge of having large databases containing entities that need to be matched in real-time with a stream of query records also containing entities, such that the best matching records are retrieved. example applications include online law enforcement and national security databases, public health surveillance and emergency response systems, financial verification systems, online retail stores, egovernment services, and digital libraries. a novel inverted index based approach for real-time entity resolution is presented in this paper. at build time, similarities between attribute values are computed and stored to support the fast matching of records at query time. the presented approach differs from other approaches to approximate query matching in that it allows any similarity comparison function, and any 'blocking' (encoding) function, both possibly domain specific, to be incorporated. experimental results on a real-world database indicate that the total size of all data structures of this novel index approach grows sub-linearly with the size of the database, and that it allows matching of query records in sub-second time, more than two orders of magnitude faster than a traditional entity resolution index approach. the interested reader is referred to the longer version of this paper [5].
walking in the crowd: anonymizing trajectory data for pattern analysis. recently, trajectory data mining has received a lot of attention in both the industry and the academic research. in this paper, we study the privacy threats in trajectory data publishing and show that traditional anonymization methods are not applicable for trajectory data due to its challenging properties: high-dimensional, sparse, and sequential. our primary contributions are (1) to propose a new privacy model called lkc-privacy that overcomes these challenges, and (2) to develop an efficient anonymization algorithm to achieve lkc-privacy while preserving the information utility for trajectory pattern mining.
on domain similarity and effectiveness of adapting-to-rank. adapting to rank address the problem of insufficient domain-specific labeled training data in learning to rank. however, the initial study shows that adaptation is not always effective. in this paper, we investigate the relationship between the domain similarity and the effectiveness of domain adaptation with the help of two domain similarity measure: relevance correlation and sample distribution correlation.
identifying interesting assertions from the web. how can we cull the facts we need from the overwhelming mass of information and misinformation that is the web? the textrunner extraction engine represents one approach, in which people pose keyword queries or simple questions and textrunner returns concise answers based on tuples extracted from web text. unfortunately, the results returned by engines such as textrunner include both informative facts (e.g., the fda banned ephedra) and less useful statements (e.g., the fda banned products). this paper therefore investigates filtering textrunner results to enable people to better focus on interesting assertions. we first develop three distinct models of what assertions are likely to be interesting in response to a query. we then fully operationalize each of these models as a filter over textrunner results. finally, we develop a more sophisticated filter that combines the different models using relevance feedback. in a study of human ratings of the interestingness of textrunner assertions, we show that our approach substantially enhances the quality of textrunner results. our best filter raises the fraction of interesting results in the top thirty from 41.6% to 64.1%.
matching person names through name transformation. matching person names plays an important role in many applications, including bibliographic databases and indexing systems. name variations and spelling errors make exact string matching problematic; therefore, it is useful to develop methodologies that can handle variant forms for the same named entity. in this paper, a novel person name matching model is presented. common name variations in the english speaking world are formalized, and the concept of name transformation paths is introduced; name similarity is measured after the best transformation path has been selected. supervised techniques are used to learn a similarity function and a decision rule. experiments with three datasets show the method to be effective.
a unified relevance model for opinion retrieval. representing the information need is the greatest challenge for opinion retrieval. typical queries for opinion retrieval are composed of either just content words, or content words with a small number of cue "opinion" words. both are inadequate for retrieving opinionated documents. in this paper, we develop a general formal framework--the opinion relevance model--to represent an information need for opinion retrieval. we explore a series of methods to automatically identify the most appropriate opinion words for query expansion, including using query independent sentiment resources. we also propose a relevance feedback-based approach to extract opinion words. both query-independent and query-dependent methods can also be integrated into a more effective mixture relevance model. finally, opinion retrieval experiments are presented for the blog06 and coae08 text collections. the results show that, significant improvements can always be obtained by this opinion relevance model whether sentiment resources are available or not.
privacy and anonymization for very large datasets. with the increase of available public data sources and the interest for analyzing them, privacy issues are becoming the eye of the storm in many applications. the vast amount of data collected on human beings and organizations as a result of cyberinfrastructure advances, or that collected by statistical agencies, for instance, has made traditional ways of protecting social science data obsolete. this has given rise to different techniques aimed at tackling this problem and at the analysis of limitations in such environments, such as the seminal study by aggarwal of anonymization techniques and their dependency on data dimensionality. the growing accessibility to high-capacity storage devices allows keeping more detailed information from many areas. while this enriches the information and conclusions extracted from this data, it poses a serious problem for most of the previous work presented up to now regarding privacy, focused on quality and paying little attention to performance aspects. in this workshop, we want to gather researchers in the areas of data privacy and anonymization together with researchers in the area of high performance and very large data volumes management. we seek to collect the most recent advances in data privacy and anonymization (i.e. anonymization techniques, statistic disclosure techniques, privacy in machine learning algorithms, privacy in graphs or social networks, etc) and those in high performance and data management (i.e. algorithms and structures for efficient data management, parallel or distributed systems, etc).
m-cope: a multiple continuous query processing engine. a data stream management system (dsms) should support an efficient evaluation scheme for long-running continuous queries over infinite data streams. this demonstration presents a scalable query processing engine, m-cope (multiple continuous query processing engine) developed to evaluate multiple continuous queries efficiently. a multiple query optimization scheme implemented in the system generates a single network of operations as an execution plan for registered queries in order to maximize the reuse of the intermediate results of common sub-expressions in the queries adaptively. in this paper, we describe the overall architecture of m-cope along with its special features. network traffic flow streams are used to demonstrate the main features of m-cope.
detection of orthogonal concepts in subspaces of high dimensional data. in the knowledge discovery process, clustering is an established technique for grouping objects based on mutual similarity. however, in today's applications for each object very many attributes are provided. as multiple concepts described by different attributes are mixed in the same data set, clusters do not appear in all dimensions. in these high dimensional data spaces, each object can be clustered in several projections of the data. however, recent clustering techniques do not succeed in detection of these orthogonal concepts hidden in the data. they either miss multiple concepts for each object by partitioning approaches or provide redundant clusters in very similar subspaces. in this work we propose a novel clustering method aiming only at orthogonal concept detection in subspaces of the data. unlike existing clustering approaches, osclu (orthogonal subspace clustering) detects for each object the orthogonal concepts described by differing attributes while pruning similar concepts. thus, each detected cluster in an orthogonal subspace provides novel information about the hidden structure of the data. thorough experiments on real and synthetic data show that osclu yields substantial quality improvements over existing clustering approaches.
minimal common container of tree patterns. tree patterns represent important fragments of xpath. in this paper, we show that some classes of tree patterns exhibit such a property that, given a finite number of tree patterns p1, ..., pn, there exists another pattern p (tree pattern or dag-pattern) such that p1, ..., pn, are all contained in p, and for any tree pattern q belonging to a given class c, p1, ..., pn, are contained in q implies p is contained in q.
incremental similarity joins with edit distance constraints. with the dynamic increase of string data and the need to integrate data from multiple data sources, a challenging issue is to perform similarity joins on dynamically-augmented string sets. existing methods only exploit domain-oriented filters to speed up join processing on static datasets, which are inefficient for incremental data-generation scenarios. in this paper, an efficient approach called isj-ed (abbr for incremental similarity joins with edit distance constraints) is proposed to tackle similarity join problem on ever-growing string sets. we first design a distance-based filtering technique which exploits an incrementally-built index to improve the filtering capability. then, for the existent filters, we study the impact of their executing orders on total filtering cost and suggest dynamically-optimized filtering orders. all these optimization strategies work jointly with the existing domain-oriented filters in isj-ed, that is, they are complementary to those filter-based methods with edit-distance thresholds. experimental results demonstrate that on dynamically augmented string sets, our method is more efficient than those only leverage domain-oriented filters with a fixed filtering order.
active learning in partially supervised classification. positive example based learners reduce human annotation effort significantly by removing the burden of labeling the negative examples. various methods have been proposed in literature for building classifiers using positive and unlabeled examples. however, we empirically observe that classification accuracy of the state of the art methods degrades significantly as the number of labeled positive examples decreases. in this paper, we propose an active learning based method to address this issue. the proposed method learns starting from a handful of positively labeled examples and a large number of unlabeled examples. experimental results on benchmark datasets show that the proposed method performs better than the state of the art methods when the percentage of labeled positive examples is small.
rank-aware clustering of structured datasets. in online applications such as yahoo! personals and yahoo! real estate users define structured profiles in order to find potentially interesting matches. typically, profiles are evaluated against large datasets and produce thousands of matches. in addition to filtering, users also specify ranking in their profile, and matches are returned in a ranked list. top results in a list are typically homogeneous, which hinders data exploration. for example, a user looking for 1- or 2-bedroom apartments sorted by price will see a large number of cheap 1-bedrooms in undesirable neighborhoods before seeing a different apartment. an alternative to ranking is to group matches on common attribute values, e.g., cheap 1-bedrooms in good neighborhoods, 2-bedrooms with 2 baths, and choose groups in relationship with ranking. in this paper, we present a novel paradigm of rank-aware clustering, and demonstrate its effectiveness on a large dataset from yahoo! personals, a leading online dating site.
information extraction meets relation databases. information extraction from unstructured text has much in common with querying in databases systems. despite some differences on how data is modeled or represented, the general goal remains the same, i.e. to retrieve data or tag elements that satisfy some user-specified constraints. in recent years, the two paradigms have become much closer thanks to the large volume of data on the world wide web and the need for more automated search tools for information extraction and often the need for relating the extracted pieces. several developments have contributed to the growth of the area including the work on named entity recognition (marked by muc-6 and subsequent conferences) and natural language processing, web information retrieval and mining, and web query languages inspired by the query languages in the relational world. this panel explores the areas where the two paradigms overlap, the impacts and contributions they have had on each other and the areas that may be open for further research. the panel will bring together researchers who have worked in some established areas that closely relate to extracting structured information from unstructured text. in the first (role-playing) round, each panelist will strongly take a side on where the intersection is heading, arguing that one area will subsume the other area in near future. in the second round, the panelists will counter one or two others, pointing out the challenges that one area would be facing in subsuming the other and implications for future research directions.
mashup-based information retrieval for domain experts. in this paper, we tackle the problem of helping domain experts to construct, parameterize and deploy mashups of data and code. we view a mashup as a data processing flow, that describes how data is obtained from one or more sources, processed by one or more components, and finally sent to one or more sinks. our approach allows specifying patterns of flows, in a language called cascade. the patterns cover different possible variations of the flows, including variations in the structure of the flow, the components in the flow and the possible parameterizations of these components. we present a tool that makes use of this knowledge of flow patterns and associated metadata to allow domain experts to explore the space of possible flows described in the pattern. the tool uses an ai planning approach to automatically build a flow, belonging to the flow pattern, from a high-level goal, specified as a set of tags. we describe examples from the financial services domain to show the use of flow patterns in allowing domain experts to construct a large variety of mashups rapidly.
exploring multimedia databases via optimization-based relevance feedback and the earth mover's distance. determining similar objects is a fundamental operation both in data mining tasks such as clustering and in query-driven object retrieval. by definition of similarity search, query objects can only be imprecise descriptions of what users are looking for in a database, and even high-quality similarity measures can only be approximations of the users' notion of similarity. to overcome these shortcomings, iterative query refinement systems have been proposed. they utilize user feedback regarding the relevance of intermediate results to adapt the query object and/or the similarity measure. we propose an optimization-based relevance feedback approach for adaptable distance measures - focusing on the earth mover's distance. our technique enables quicker iterative database exploration as shown by our experiments.
a comparative study of methods for estimating query language models with pseudo feedback. we systematically compare five representative state-of-the-art methods for estimating query language models with pseudo feedback in ad hoc information retrieval, including two variants of the relevance language model, two variants of the mixture feedback model, and the divergence minimization estimation method. our experiment results show that a variant of relevance model and a variant of the mixture model tend to outperform other methods. we further propose several heuristics that are intuitively related to the good retrieval performance of an estimation method, and show that the variations in how these heuristics are implemented in different methods provide a good explanation of many empirical observations.
as-index: a structure for string search using n-grams and algebraic signatures. as-index is a new index structure for exact string search in disk resident databases. it uses hashing, unlike known alternatives, whether baesd on trees or tries. it typically indexes every n-gram in the database, though non-dense indexing is also possible. the hash function uses the algebraic signatures of all n-grams. use of hashing provides for constant index access time for arbitrarily long patterns, unlike other structures whose search cost is at best logarithmic. the storage overhead of as-index is basically 500 - 600%, similar to that of alternatives or smaller. we show the index structure, our use of algebraic signatures and the search algorithm. we discuss the design trade-offs and present the theoretical and experimental performance analysis. we compare the as-index to main alternatives. we conclude that as-index is an attractive structure and we indicate directions for future work.
finding the topical anchors of a context using lexical cooccurrence data. lexical cooccurrence in textual data is not uniformly random. the statistics inferred from the term-cooccurrence data enable us to model dependencies between terms as graphs, somewhat resembling the way semantic memory is organised in human beings. in this paper we look at cooccurrence patterns to identify topical anchors of a given context. topical anchors are those terms whose semantics represent the topic of the whole context. this work is based on computing a stationary distribution in the cooccurrence graph. topical anchors were computed on a set of 100 contexts and were also evaluated by 86 volunteers and the results show that the algorithm correctly identifies the topical anchors around 62% of the time.
group-by skyline query processing in relational engines. the skyline operator was first proposed in 2001 for retrieving interesting tuples from a dataset. since then, 100+ skyline-related papers have been published; however, we discovered that one of the most intuitive and practical type of skyline queries, namely, group-by skyline queries remains unaddressed. group-by skyline queries find the skyline for each group of tuples. in this paper, we present a comprehensive study on processing group-by skyline queries in the context of relational engines. specifically, we examine the composition of a query plan for a group-by skyline query and develop the missing cost model for the bbs algorithm. experimental results show that our techniques are able to devise the best query plans for a variety of group-by skyline queries. our focus is on algorithms that can be directly implemented in today's commercial database systems without the addition of new access methods (which would require addressing the associated challenges of maintenance with updates, concurrency control, etc.).
an efficient clustering algorithm for large-scale topical web pages. the clustering of topic-related web pages has been recognized as a foundational work in exploiting large sets of web pages such as the cases in search engines and web archive systems, which collect and preserve billions of web pages. however, this task faces great challenges both in efficiency and accuracy. in this paper we present a novel clustering algorithm for large scale topical web pages which achieves high efficiency together with considerately high accuracy. in our algorithm, a two-phase divide and conquer framework is developed to solve the efficiency problem, in which both link analysis and content analysis are utilized in mining the topical similarity between pages to achieve a high accuracy. a comprehensive experiment was conducted to evaluate our method in terms of its effectiveness, efficiency, and quality of result.
evidence of quality of textual features on the web 2.0. the growth of popularity of web 2.0 applications greatly increased the amount of social media content available on the internet. however, the unsupervised, user-oriented nature of this source of information, and thus, its potential lack of quality, have posed a challenge to information retrieval (ir) services. previous work focuses mostly only on tags, although a consensus about its effectiveness as supporting information for ir services has not yet been reached. moreover, other textual features of the web 2.0 are generally overseen by previous research. in this context, this work aims at assessing the relative quality of distinct textual features available on the web 2.0. towards this goal, we analyzed four features (title, tags, description and comments) in four popular applications (citeulike, last.fm, yahoo! video, and youtube). firstly, we characterized data from these applications in order to extract evidence of quality of each feature with respect to usage, amount of content, descriptive and discriminative power as well as of content diversity across features. afterwards, a series of classification experiments were conducted as a case study for quality evaluation. characterization and classification results indicate that: 1) when considered separately, tags is the most promising feature, achieving the best classification results, although its absence in a non-negligible fraction of objects may affect its potential use; and 2) each feature may bring different pieces of information, and combining their contents can improve classification.
relying on topic subsets for system ranking estimation. ranking a number of retrieval systems according to their retrieval effectiveness without relying on costly relevance judgments was first explored by soboroff et al [6]. over the years, a number of alternative approaches have been proposed. we perform a comprehensive analysis of system ranking estimation approaches on a wide variety of trec test collections and topics sets. our analysis reveals that the performance of such approaches is highly dependent upon the topic or topic subset, used for estimation. we hypothesize that the performance of system ranking estimation approaches can be improved by selecting the "right" subset of topics and show that using topic subsets improves the performance by 32% on average, with a maximum improvement of up to 70% in some cases.
large margin transductive transfer learning. recently there has been increasing interest in the problem of transfer learning, in which the typical assumption that training and testing data are drawn from identical distributions is relaxed. we specifically address the problem of transductive transfer learning in which we have access to labeled training data and unlabeled testing data potentially drawn from different, yet related distributions, and the goal is to leverage the labeled training data to learn a classifier to correctly predict data from the testing distribution. we have derived efficient algorithms for transductive transfer learning based on a novel viewpoint and the support vector machine (svm) paradigm, of a large margin hyperplane classifier in a feature space. we show that our method can out-perform some recent state-of-the-art approaches for transfer learning on several data sets, with the added benefits of model and data separation and the potential to leverage existing work on support vector machines.
probabilistic skyline queries. the ability to deal with uncertain information is becoming increasingly important for modern database applications. whereas a conventional (certain) object is usually represented by a vector from a multidimensional feature space, an uncertain object is represented by a multivariate probability density function (pdf). this pdf can be defined either discretely (e.g. by a histogram) or continuously in parametric form (e.g. by a gaussian mixture model). for a database of uncertain objects, the users expect similar data analysis techniques as for a conventional database of certain objects. an important analysis technique for certain objects is the skyline operator which finds maximal or minimal vectors with respect to any possible attribute weighting. in this paper, we propose the concept of probabilistic skylines, an extension of the skyline operator for uncertain objects. in addition, we propose efficient and effective methods for determining the probabilistic skyline of uncertain objects which are defined by a pdf in parametric form (e.g. a gaussian function or a gaussian mixture model). to further accelerate the search, we elaborate how the computation of the probabilistic skyline can be supported by an index structure for uncertain objects. an extensive experimental evaluation demonstrates both the effectiveness and the efficiency of our technique.
easiest-first search: towards comprehension-based web search. although web search engines have become information gateways to the internet, for queries containing technical terms, search results often contain pages that are difficult to be understood by non-expert users. therefore, re-ranking search results in a descending order of their comprehensibility should be effective for non-expert users. in our approach, the comprehensibility of web pages is estimated considering both the document readability and the difficulty of technical terms in the domain of search queries. to extract technical terms, we exploit the domain knowledge extracted from wikipedia. our proposed method can be applied to general web search engines as wikipedia includes nearly every field of human knowledge. we demonstrate the usefulness of our approach by user experiments.
feature engineering on event-centric surrogate documents to improve search results. we investigate the task of re-ranking search results based on query log information. prior work has considered this problem as either the task of learning document rankings of using features based on user behavior, or as the task of enhancing documents and queries using log data. our contribution combines both. we distill log information into event-centric surrogate documents (esds), and extract features from these esds to be used in a learned ranking function. our experiments on a legal corpus demonstrate that features engineered on surrogate documents lead to improved rankings, in particular when the original ranking is of poor quality.
multi-task learning for learning to rank in web search. both the quality and quantity of training data have significant impact on the performance of ranking functions in the context of learning to rank for web search. due to resource constraints, training data for smaller search engine markets are scarce and we need to leverage existing training data from large markets to enhance the learning of ranking function for smaller markets. in this paper, we present a boosting framework for learning to rank in the multi-task learning context for this purpose. in particular, we propose to learn non-parametric common structures adaptively from multiple tasks in a stage-wise way. an algorithm is developed to iteratively discover super-features that are effective for all the tasks. the estimation of the functions for each task is then learned as a linear combination of those super-features. we evaluate the performance of this multi-task learning method for web search ranking using data from a search engine. our results demonstrate that multi-task learning methods bring significant relevance improvements over existing baseline methods.
cluster based rank query over multidimensional data streams. many data stream monitoring applications involve rank queries and hence a number of efficient evaluation algorithms are proposed recently. most of these techniques assume that rank queries are executed directly over the whole data space. however, we observe that many applications often require to perform clustering over the data streams before rank queries are run on each cluster. to address the problem, we propose a novel algorithm for integral clustering and ranking processing and we refer to such integrated queries as cluster-based rank queries. the algorithm includes two phases, namely the online phase which maintains the required data structures and statistics, and the query phase which uses these data structures to process queries. extensive experiments indicate that the proposed algorithm is efficient in both space consumption and query processing.
efficient multi-class unlabeled constrained semi-supervised svm. semi-supervised learning has been successfully applied to many fields such as knowledge management, information retrieval and data mining as it can utilize both labeled and unlabeled data. in this paper, we propose a general semi-supervised framework for multi-class categorization. many classical supervised and semi-supervised method dealing with binary classification or multi-class classification including the standard regularization and the manifold regularization can be viewed as special cases of this framework. based on this framework, we propose a novel method called multi-class unlabeled constrained svm(mcucsvm) and its special case: multi-class laplacian svm(mclapsvm). we then put forward a general kernel version semi-supervised dual coordinate descent algorithm to efficiently solve mcucsvm and makes it more applicable to problems with large number of classes and large scale labeled data. both rigorous theory and promising experimental results on four real datasets show the great performance and remarkable efficiency of mcucsvm and mclapsvm.
web search result summarization: title selection algorithms and user satisfaction. eye tracking experiments have shown that titles of web search results play a crucial role in guiding a user's search process. we present a machine-learned algorithm that trains a boosted tree to pick the most relevant title for a web search result. we compare two modeling approaches: i) using absolute editorial judgments and ii) using pairwise preference judgments. we find that the pairwise modeling approach gives better results in terms of three offline metrics. we present results of our models in four regions. we also describe a hybrid user satisfaction evaluation process -- search success -- that combines page relevance and user click behavior, and show that our machine-learned algorithm improves in search success.
a term dependency-based approach for query terms ranking. formulating appropriate and effective queries has been regarded as a challenging issue, since a large number of candidate words or phrases could be chosen as query terms to convey users' information needs. in this paper, we propose an approach to rank a set of given query terms according their effectiveness, wherein top ranked terms will be selected as an effective query. our ranking approach exploits and benefits from the underlying relationship between the query terms, and thereby the effective terms can be properly combined into the query. two regression models which capture a rich set of linguistic and statistical properties are used in our approach. experiments on ntcir-4 ad-hoc retrieval tasks demonstrate that the proposed approach can significantly improve retrieval performance, and can be well applied to other problems such as query expansion and querying by text segments.
scalable continuous range monitoring of moving objects in symbolic indoor space. indoor spaces accommodate large populations of individuals. the continuous range monitoring of such objects can be used as a foundation for a wide variety of applications, e.g., space planning, way finding, and security. indoor space differs from outdoor space in that symbolic locations, e.g., rooms, rather than euclidean positions or spatial network locations are important. in addition, positioning based on presence sensing devices, rather than, e.g., gps, is assumed. such devices report the objects in their activation ranges. we propose an incremental, query-aware continuous range query processing technique for objects moving in this setting. a set of critical devices is determined for each query, and only the observations from those devices are used to continuously maintain the query result. due to the limitations of the positioning devices, queries contain certain and uncertain results. a maximum-speed constraint on object movement is used to refine the latter results. a comprehensive experimental study with both synthetic and real data suggests that our proposal is efficient and scalable.
p-rank: a comprehensive structural similarity measure over information networks. with the ubiquity of information networks and their broad applications, the issue of similarity computation between entities of an information network arises and draws extensive research interests. however, to effectively and comprehensively measure "how similar two entities are within an information network" is nontrivial, and the problem becomes even more challenging when the information network to be examined is massive and diverse. in this paper, we propose a new similarity measure, p-rank (penetrating rank), toward effectively computing the structural similarities of entities in real information networks. p-rank enriches the well-known similarity measure, simrank, by jointly encoding both in- and out-link relationships into structural similarity computation. p-rank is proven to be a unified structural similarity framework, under which all state-of-the-art similarity measures, including cocitation, coupling, amsler and simrank, are just its special cases. based on its recursive nature of p-rank, we propose a fixed point algorithm to reinforce structural similarity of vertex pairs beyond the localized neighborhood scope toward the entire information network. our experimental studies demonstrate the power of p-rank as an effective similarity measure in different information networks. meanwhile, under the same time/space complexity, p-rank outperforms simrank as a comprehensive and more meaningful structural similarity measure, especially in large real information networks.
spider: a system for scalable, parallel / distributed evaluation of large-scale rdf data. rdf is a data model for representing labeled directed graphs, and it is used as an important building block of semantic web. due to its flexibility and applicability, rdf has been used in applications, such as semantic web, bioinformatics, and social networks. in these applications, large-scale graph datasets are very common. however, existing techniques are not effectively managing them. in this paper, we present a scalable, efficient query processing system for rdf data, named spider, based on the well-known parallel/distributed computing framework, hadoop. spider consists of two major modules (1) the graph data loader, (2) the graph query processor. the loader analyzes and dissects the rdf data and places parts of data over multiple servers. the query processor parses the user query and distributes sub queries to cluster nodes. also, the results of sub queries from multiple servers are gathered (and refined if necessary) and delivered to the user. both modules utilize the mapreduce framework of hadoop. in addition, our system supports some features of sparql query language. this prototype will be foundation to develop real applications with large-scale rdf graph data.
empirical justification of the gain and discount function for ndcg. the ndcg measure has proven to be a popular measure of retrieval effectiveness utilizing graded relevance judgments. however, a number of different instantiations of ndcg exist, depending on the arbitrary definition of the gain and discount functions used (1) to dictate the relative value of documents of different relevance grades and (2) to weight the importance of gain values at different ranks, respectively. in this work we discuss how to empirically derive a gain and discount function that optimizes the efficiency or stability of ndcg. first, we describe a variance decomposition analysis framework and an optimization procedure utilized to find the efficiency- or stability-optimal gain and discount functions. then we use trec data sets to compare the optimal gain and discount functions to the ones that have appeared in the ir literature with respect to (a) the efficiency of the evaluation, (b) the induced ranking of systems, and (c) the discriminative power of the resulting ndcg measure.
exploring relevance for clicks. mining feedback information from user click-through data is an important issue for modern web retrieval systems in terms of architecture analysis, performance evaluation and algorithm optimization. for commercial search engines, user click-through data contains useful information as well as large amount of inevitable noises. this paper proposes an approach to recognize reliable and meaningful user clicks (referred to as relevant clicks, rcs) in click-through data. by modeling user click-through behavior on search result lists, we propose several features to separate rcs from click noises. a learning algorithm is presented to estimate the quality of user clicks. experimental results on large scale dataset show that: 1) our model effectively identifies rcs in noisy click-through data; 2) different from previous click-through analysis efforts, our approach works well for both hot queries and long-tail queries.
text summarization model based on the budgeted median problem. we propose a multi-document generic summarization model based on the budgeted median problem. our model selects sentences to generate a summary so that every sentence in the document cluster can be assigned to and be represented by a sentence in the summary as much as possible. the advantage of this model is that it covers the entire relevant part of the document cluster through sentence assignment and can incorporate asymmetric relations between sentences such as textual entailment.
analyzing and evaluating query reformulation strategies in web search logs. users frequently modify a previous search query in hope of retrieving better results. these modifications are called query reformulations or query refinements. existing research has studied how web search engines can propose reformulations, but has given less attention to how people perform query reformulations. in this paper, we aim to better understand how web searchers refine queries and form a theoretical foundation for query reformulation. we study users' reformulation strategies in the context of the aol query logs. we create a taxonomy of query refinement strategies and build a high precision rule-based classifier to detect each type of reformulation. effectiveness of reformulations is measured using user click behavior. most reformulation strategies result in some benefit to the user. certain strategies like add/remove words, word substitution, acronym expansion, and spelling correction are more likely to cause clicks, especially on higher ranked results. in contrast, users often click the same result as their previous query or select no results when forming acronyms and reordering words. perhaps the most surprising finding is that some reformulations are better suited to helping users when the current results are already fruitful, while other reformulations are more effective when the results are lacking. our findings inform the design of applications that can assist searchers; examples are described in this paper.
message family propagation for ising mean field based on iteration tree. ising mean field is a basic variational inference method for ising model, which can provide an effective approximate solution for large-scale inference problem. the main idea is to transform a probabilistic inference problem into a functional extremum problem by variational calculus, and solve the functional extremum problem to obtain approximate marginal distributions. the process of solving the functional extremum is an important step and a computational core for variational inference. but the traditional full variational iteration methods make the variable information intercross with each other deeply. from the view of incomplete variational iterations, we propose a message family propagation method for ising mean field to compute a marginal distribution family of object variable. first we define the concepts of iteration tree and pruning iteration tree to describe the iteration computation process of ising mean field inference. then we design the message family propagation method based on the iteration trees. the method propagates mean field message families and belief message families from bottom to top of the iteration tree, and presents a marginal distribution family of variable in root node. finally we prove the marginal distribution bound theorem, which shows that the marginal distribution family computed by the method in the pruning iteration tree contains the exact marginal stribution. theoretical and experimental results illustrate that the message family propagation method is valid and the marginal distribution bounds are tight.
xqgen: an algebra-based xpath query generator for micro-benchmarking. we propose xqgen, a stand-alone, algebra-based xpath generator to aid engineers in testing and improving the design of xml query engines. xqgen takes an xml schema sketch and user configurations, such as number of queries, query types, duplication factors, and branching factors as input, and generates a set of queries that comform to the schema and configurations. in addition, given a set of label-paths as workload input, xqgen is capable of generating query sets that honor the workload.
graph-based transfer learning. transfer learning is the task of leveraging the information from labeled examples in some domains to predict the labels for examples in another domain. it finds abundant practical applications, such as sentiment prediction, image classification and network intrusion detection. in this paper, we propose a graph-based transfer learning framework. it propagates the label information from the source domain to the target domain via the example-feature-example tripartite graph, and puts more emphasis on the labeled examples from the target domain via the example-example bi-partite graph. our framework is semi-supervised and non-parametric in nature and thus more flexible. we also develop an iterative algorithm so that our framework is scalable to large-scale applications. it enjoys the theoretical property of convergence. compared with existing transfer learning methods, the proposed framework propagates the label information to both the features irrelevant to the source domain and the unlabeled examples in the target omain via the common features in a principled way. experimental results on 3 real data sets demonstrate the effectiveness of our algorithm.
navigational path privacy protection: navigational path privacy protection. navigational path query, one of the most popular location-based services (lbss), determines a route from a source to a destination on a road network. however, issuing path queries to some non-trustworthy service providers may pose privacy threats to the users. for instance, given a query requesting for a path from a residential address to a psychiatrist, some adversaries may deduce "who is related to what disease". in this paper, we present an obfuscator framework that reduces the likelihood of path queries being revealed, while supporting different user privacy protection needs and retaining query evaluation efficiency. the framework consists of two major components, namely, an obfuscator and an obfuscated path query processor. the former formulates obfuscated path queries by intermixing true and fake sources and destinations and the latter facilitates efficient evaluation of the obfuscated path queries in an lbs server. the framework supports three types of obfuscated path queries, namely, independent obfuscated path query, shared obfuscated path query, and anti-collusion obfuscated path query. our proposal strikes a balance between privacy protection strength and query processing overheads, while enhancing privacy protection against collusion attacks. finally, we validate the proposed ideas and evaluate the performance of our framework based on an extensive set of empirical experiments.
matching stream patterns of various lengths and tolerances. continuously identifying pre-defined patterns in a streaming time series has strong demand in various applications. while most existing works assume the patterns are in equal length and tolerance, this work focuses on the problem where the patterns have various lengths and tolerances, a common situation in the real world. the challenge of this problem roots on the strict space and time requirements of processing the arriving and expiring data in high-speed stream, combined with difficulty of coping with a large number of patterns with various lengths and tolerances. we introduce a novel concept of converging envelope which bounds the tolerance of a group of patterns in various tolerances and equal length and thus dramatically reduces the number of patterns for similarity computation. the basic idea of converging envelope has potential to more general index problems. to index patterns in various lengths and tolerances, we partition patterns into sub-patterns in equal length and an multi-tree index is developed in this paper.
exploiting term relationship to boost text classification. document classification provides an effective way to handle the explosive online textual data. however, in practical classification settings, we face the so-called feature sparsity problem caused by a lack of training documents or the shortness of text to be classified. in this paper, we solve the sparsity problem by exploiting term relationships along with naive bayes classifiers. the first method is to estimate term relationships based on the co-occurrence information of two terms in a certain context. the second method estimates the term relationships based on the distribution of terms over different hierarchical categories in a publicly available document taxonomy. thereafter, term relationship is used to augment naive bayes classifiers. we test our methods on two open-domain data sets to demonstrate its advantages. the experimental results show that our method can significantly improve the classification performance, especially when we do not have enough training data or the texts are web search queries.
effective anonymization of query logs. user search query logs have proven to be very useful, but have vast potential for misuse. several incidents have shown that simple removal of identifiers is insufficient to protect the identity of users. publishing such inadequately anonymized data can cause severe breach of privacy. while significant effort has been expended on coming up with anonymity models and techniques for microdata, there is little corresponding work for query log data. query logs are different in several important aspects, such as the diversity of queries and the causes of privacy breach. this necessitates the need to design privacy models and techniques specific to this environment. this paper takes a first cut at tackling this challenge. our main contribution is to define effective anonymization models for query log data along with proposing techniques to achieve such anonymization. we analyze the inherent utility and privacy tradeoff, and experimentally validate the performance of our techniques.
matchsim: a novel neighbor-based similarity measure with maximum neighborhood matching. the problem of measuring similarity between web pages arises in many important web applications, such as search engines and web directories. in this paper, we propose a novel neighbor-based similarity measure called matchsim, which uses only the neighborhood structure of web pages. technically, matchsim recursively defines similarity between web pages by the average similarity of the maximum matching between their neighbors. our method extends the traditional methods which simply count the numbers of common and/or different neighbors. it also successfully overcomes a severe counterintuitive loophole in simrank, due to its strict consistency with the intuitions of similarity. we give the computational complexity of matchsim iteration. the accuracy of matchsim is compared against others on two real datasets. the results show that our method performs best in most cases.
kernel latent semantic analysis using an information retrieval based kernel. hidden term relationships can be found within a document collection using latent semantic analysis (lsa) and can be used to assist in information retrieval. lsa uses the inner product as its similarity function, which unfortunately introduces bias due to document length and term rarity into the term relationships. in this article, we present the novel kernel based lsa method, which uses separate document and query kernel functions to compute document and query similarities, rather than the inner product. we show that by providing an appropriate kernel function, we are able to provide a better fit of our data and hence produce more effective term relationships.
an integrated discriminative probabilistic approach to information extraction. probabilistic graphical models for sequence data enable us to effectively deal with inherent uncertainty in many real-world domains. however, they operate on a mostly propositional level. logic approaches, on the other hand, can compactly represent a wide variety of knowledge, especially first-order ones, but treat uncertainty only in limited ways. therefore, combining probability and first-order logic is highly desirable for information extraction which requires uncertainty modeling as well as dependency and deeper knowledge representation. in this paper, we model both segmentations in observation sequence and relations of segments simultaneously in our proposed integrated discriminative probabilistic framework. we propose the metropolis-hastings, a markov chain monte carlo (mcmc) algorithm for approximate bayesian inference to find the maximum a posteriori assignment of all the variables of this model. this integrated model has several advantages over previous probabilistic graphical models, and it offers a great capability of extracting implicit relations and new relation discovery for relation extraction from encyclopedic documents, and capturing sub-structures in named entities for named entity recognition. we performed extensive experiments on the above two well-established information extraction tasks, illustrating the feasibility and promise of our approach.
voting in social networks. a voting system is a set of rules that a community adopts to take collective decisions. in this paper we study voting systems for a particular kind of community: electronically mediated social networks. in particular, we focus on delegative democracy (a.k.a. proxy voting) that has recently received increased interest for its ability to combine the benefits of direct and representative systems, and that seems also perfectly suited for electronically mediated social networks. in such a context, we consider a voting system in which users can only express their preference for one among the people they are explicitly connected with, and this preference can be propagated transitively, using an attenuation factor. we present this system and we study its properties. we also take into consideration the problem of missing votes, which is particularly relevant in online networks, as some recent case shows. our experiments on real-world networks provide interesting insight into the significance and stability of the results obtained with the suggested voting system.
a signal-to-noise approach to score normalization. score normalization is indispensable in distributed retrieval and fusion or meta-search where merging of result-lists is required. distributional approaches to score normalization with reference to relevance, such as binary mixture models like the normal-exponential, suffer from lack of universality and troublesome parameter estimation especially under sparse relevance. we develop a new approach which tackles both problems by using aggregate score distributions without reference to relevance, and is suitable for uncooperative engines. the method is based on the assumption that scores produced by engines consist of a signal and a noise component which can both be approximated by submitting well-defined sets of artificial queries to each engine. we evaluate in a standard distributed retrieval testbed and show that the signal-to-noise approach yields better results than other distributional methods. as a significant by-product, we investigate query-length distributions.
an analysis framework for search sequences. in this paper we present a general framework to study sequences of search activities performed by a user. our framework provides (i) a vocabulary to discuss types of features, models, and tasks, (ii) straightforward feature re-use across problems, (iii) realistic baselines for many sequence analysis tasks we study, and (iv) a simple mechanism to develop baselines for sequence analysis tasks beyond those studied in this paper. using this framework we study a set of fourteen sequence analysis tasks with a range of features and models. while we show that most tasks benefit from features based on recent history, we also identify two categories of "sequence-resistant" tasks for which simple classes of local features perform as well as richer features and models.
spatio-temporal association rule mining framework for real-time sensor network applications. in this paper, we present a data mining framework to estimate missing or corrupted data in sensor network applications - a frequently occurring phenomenon in this domain. the framework is naturally germane to the spatio-temporal analysis of relational data stream evolution. our method utilizes association rules to capture spatio-temporal correlations in multivariate, dynamically evolving, and unbounded sensor data streams. existing approaches that tackled this problem do not account for the multi-dimensionality of the node data and their relationship; furthermore they entail simplistic and/or premature assumptions on the temporal and spatial factors to overcome the complexity of the streaming environment. our technique, called mining autonomously spatio-temporal environmental rules (master), comprehensively formulates the problem of mining patterns in sensor data streams, and yet remains provably adaptive to bounded time and space costs while probabilistically assuring a bounded estimation error. simulation experiments show master's efficiency in terms of overhead as well as the quality of estimation.
structure-aware indexing for keyword search in databases. most of existing methods of keyword search over relational databases find the steiner trees composed of relevant tuples as the answers. they identify the steiner trees by discovering the rich structural relationships between tuples, and neglect the fact that such structural relationships can be pre-computed and indexed. tuple units that are composed of most relevant tuples are proposed to address this problem. tuple units can be precomputed and indexed. existing methods identify a single tuple unit to answer keyword queries. they, however, may involve false negatives as in many cases a single tuple unit cannot answer a keyword query. instead, multiple tuple units should be integrated to answer keyword queries. to address this problem, in this paper, we study how to integrate multiple related tuple units to effectively answer keyword queries. we devise novel indices and incorporate the structural relationships between different tuple units into the indices. we use the indices to efficiently and progressively identify the top-k relevant answers. we have implemented our method in real database systems, and the experimental results show that our approach achieves high search efficiency and accuracy, and outperforms state-of-the-art methods significantly.
experiments on pattern-based relation learning. relation extraction is the task of extracting semantic relations - such as synonymy or hypernymy - between word pairs from corpus data. past work in relation extraction has concentrated on manually creating templates to use in directly extracting word pairs for a given semantic relation from corpus text. recently, there has been a move towards using machine learning to automatically learn these patterns. we build on this research by running experiments investigating the impact of corpus type, corpus size and different parameter settings on learning a range of lexical relations.
xcfs: an xml documents clustering approach using both the structure and the content. this paper introduces a clustering approach, xml clustering using frequent substructures (xcfs) that considers both the structural and the content information of xml documents in clustering. xcfs uses frequent substructures in the form of a novel representation, closed frequent embedded (cfe) subtrees to constrain the content in the clustering process. the empirical analysis ascertains that xcfs can effectively cluster even very large xml datasets and outperforms other existing methods.
characterizing, constructing and managing resource usage profiles of system s applications: challenges and experience. we describe the challenges of characterizing, constructing and managing the usage profiles of system s applications. a running system s application is a directed graph with software processing elements(pes) as vertices and data streams as edges connecting the pes. the resource usage of each pe is a critical input to the runtime scheduler for proper resource allocation. we represent the resource usage of pes in terms of resource functions (rfs) that are used by the system s scheduler, with one rf per resource per pe. the first challenge is that it is difficult to build good rfs that can accurately predict the resource usage of a pe because the pes perform arbitrary computations. a second set of challenges arises in managing the rfs and performance data so that we can apply them for pes that are re-run or reused by the same or different applications or users. we report our experience in overcoming these challenges. specifically, we present an empirical characterization of pe rfs from several real streaming applications running in a system s testbed. this indicates that our simple models of resource usage that build on the data-flow nature of the underlying application can be effective, even for complex pes. to illustrate our methodology, we evaluate and analyze the performance of these applications as a function of the quality of our resource profile models. the system automatically learns the models from the raw metrics data collected from running pes. we describe our approach to managing the metrics and rf models, which allows us to construct generalizable rfs and eliminates the learning time for new pes by intelligently storing and reusing the metrics data.
dynamic hyperparameter optimization for bayesian topical trend analysis. this paper presents a new bayesian topical trend analysis. we regard the parameters of topic dirichlet priors in latent dirichlet allocation as a function of document timestamps and optimize the parameters by a gradient-based algorithm. since our method gives similar hyperparameters to the documents having similar timestamps, topic assignment in collapsed gibbs sampling is affected by timestamp similarities. we compute tfidf-based document similarities by using a result of collapsed gibbs sampling and evaluate our proposal by link detection task of topic detection and tracking.
to obtain orthogonal feature extraction using training data selection. feature extraction is an effective tool in data mining and machine learning. many feature extraction methods have been investigated recently. however, few methods can achieve orthogonal components. non-orthogonal components distort the metric structure of original data space and contain reductant information. in this paper, we propose a feature extraction method, named as incremental orthogonal basis analysis (ioba), to cope with the challenging endeavors. first, ioba learns orthogonal components for original data, not only theoretically but also numerically. second, an innovative way of training data selection is proposed. this selection scheme helps ioba pick up numerically orthogonal components from training patterns. third, by designing a self-adaptive threshold technique, no prior knowledge about the number of components is necessary to use ioba. moreover, without solving eigenvalue and eigenvector problems, ioba not only saves large computing loads, but also avoids ill-conditioned problems. results of experiments show the efficiency of the proposed ioba.
comprehenrank: estimating comprehension in classroom by absorbing random walks on a cognitive graph. this paper develops a graph-theoretic framework for estimating comprehension in classroom. to deal with imprecise data gathered in classroom, we propose multi-step comprehension propagation over a semantic graph. random walks on the graph measure students' comprehension with probabilities absorbed at student nodes.
a collaborative filtering approach to ad recommendation using the query-ad click graph. search engine logs contain a large amount of click-through data that can be leveraged as soft indicators of relevance. in this paper we address the sponsored search retrieval problem which is to find and rank relevant ads to a search query. we propose a new technique to determine the relevance of an ad document for a search query using click-through data. the method builds on a collaborative filtering approach to discover new ads related to a query using a click graph. it is implemented on a graph with several million edges and scales to larger sizes easily. the proposed method is compared to three different baselines that are state-of-the-art for a commercial search engine. evaluations on editorial data indicate that the model discovers many new ads not retrieved by the baseline methods. the ads from the new approach are on average of better quality than the baselines.
stochastic gradient boosted distributed decision trees. stochastic gradient boosted decision trees (gbdt) is one of the most widely used learning algorithms in machine learning today. it is adaptable, easy to interpret, and produces highly accurate models. however, most implementations today are computationally expensive and require all training data to be in main memory. as training data becomes ever larger, there is motivation for us to parallelize the gbdt algorithm. parallelizing decision tree training is intuitive and various approaches have been explored in existing literature. stochastic boosting on the other hand is inherently a sequential process and have not been applied to distributed decision trees. in this work, we present two different distributed methods that generates exact stochastic gbdt models, the first is a mapreduce implementation and the second utilizes mpi on the hadoop grid environment.
exploiting internal and external semantics for the clustering of short texts using world knowledge. clustering of short texts, such as snippets, presents great challenges in existing aggregated search techniques due to the problem of data sparseness and the complex semantics of natural language. as short texts do not provide sufficient term occurring information, traditional text representation methods, such as ``bag of words" model, have several limitations when directly applied to short texts tasks. in this paper, we propose a novel framework to improve the performance of short texts clustering by exploiting the internal semantics from original text and external concepts from world knowledge. the proposed method employs a hierarchical three-level structure to tackle the data sparsity problem of original short texts and reconstruct the corresponding feature space with the integration of multiple semantic knowledge bases -- wikipedia and wordnet. empirical evaluation with reuters and real web dataset demonstrates that our approach is able to achieve significant improvement as compared to the state-of-the-art methods.
efficient and reliable merging of xml documents. many knowledge-based processes rely on xml-based office documents. up to now, versioning and merging xml documents was a difficult and error-prone task, mostly done manually. the support by tools is still in its infancy. we have presented a novel approach to compare and merge xml documents in a reliable way using context fingerprints. in this demonstration, we show the application of our toolset to odf documents using a new, simple, and user-friendly graphical user-interface.
semantic queries in databases: problems and challenges. supporting semantic queries in relational databases is essential to many advanced applications. recently, with the increasing use of ontology in various applications, the need for querying relational data together with its related ontology has become more urgent. in this paper, we identify and discuss the problem of querying relational data with its ontologies. two fundamental challenges make the problem interesting. first, it is extremely difficult to express queries against graph structured ontology in the relational query language sql, and second, in many cases where data and its related ontology are complicated, queries are usually not precise, that is, users often have only a vague notion, rather than a clear understanding and definition, of what they query for. we outline a query-by-example approach that enables us to support semantic queries in relational databases with ease. instead of endeavoring to incorporate ontology into relational form and create new language constructs to express such queries, we ask the user to provide a small number of examples that satisfy the query she has in mind. using these examples as seeds, the system infers the exact query automatically, and the user is therefore shielded from the complexity of interfacing with the ontology.
hypersum: hypergraph based semi-supervised sentence ranking for query-oriented summarization. graph based sentence ranking algorithms such as pagerank and hits have been successfully used in query-oriented summarization. with these algorithms, the documents to be summarized are often modeled as a text graph where nodes represent sentences and edges represent pairwise similarity relationships between two sentences. a deficiency of conventional graph modeling is its incapability of naturally and effectively representing complex group relationships shared among multiple objects. simply squeezing complex relationships into pairwise ones will inevitably lead to loss of information which can be useful for ranking and learning. in this paper, we propose to take advantage of hypergraph, i.e. a generalization of graph, to remedy this defect. in a text hypergraph, nodes still represent sentences, yet hyperedges are allowed to connect more than two sentences. with a text hypergraph, we are thus able to integrate both group relationships formulated among multiple sentences and pairwise relationships formulated between two sentences in a unified framework. as essential work, it is first addressed in the paper that how a text hypergraph can be built for summarization by applying clustering techniques. then, a hypergraph based semi-supervised sentence ranking algorithm is developed for query-oriented extractive summarization, where the influence of query is propagated to sentences through the structure of the constructed text hypergraph. when evaluated on duc data sets, performance of the proposed approach is remarkable.
real-word spelling correction using google web 1tn-gram data set. we present a method for correcting real-word spelling errors using the google web 1t n-gram data set and a normalized and modified version of the longest common subsequence (lcs) string matching algorithm. our method is focused mainly on how to improve the correction recall (the fraction of errors corrected) while keeping the correction precision (the fraction of suggestions that are correct) as high as possible. evaluation results on a standard data set show that our method performs very well.
domain driven data mining to improve promotional campaign roi and select marketing channels. the trading activities of materials retail is concerned with an extremely competitive market. however, business people are not well informed about how to proceed and what to do during marketing activities. data mining methods could be interesting to generate substantial profits for decision makers and to optimize the choice of different marketing activities. in this paper, we propose an actionable knowledge discovery methodology, for one-to-one marketing, which allows to contact the right customer through the right communication channel. this methodology first requires a measurement of the tendency for the customers to purchase a given item, and second requires an optimization of the return on investment by selecting the most effective communication channels for attracting these customers. our methodology has been applied to the vm matériaux company. thanks to the collaboration between data miners and decision makers, we present a domain-driven view of knowledge discovery satisfying real business needs to improve the efficiency and outcome of several promotional marketing campaigns.
a fast and simple method for extracting relevant content from news webpages. we propose nce, an efficient algorithm to identify and extract relevant content from news webpages. we define relevant as the textual sections that more objectively describe the main event in the article. this includes the title and the main body section, and excludes comments about the story and presentation elements. our experiments suggest that nce is competitive, in terms of extraction quality, with the best methods available in the literature. it achieves f1 = 90.7% in our test corpus containing 324 news webpages from 22 sites. the main advantages of our method are its simplicity and its computational performance. it is at least an order of magnitude faster than methods that use visual features. this characteristic is very suitable for applications that process a large number of pages.
3se: a semi-structured search engine for heterogeneous data in graph model. as the ubiquitous interplay of structured, semi-structured and unstructured data from different sources, neither db-style structured query requiring knowledge of full schema and complex language, nor ir-style keyword search ignoring latent structures, can satisfy users. in this paper, we present a novel semi-structured search engine (3se) that provides easy, flexible, precise and rapid access to heterogeneous data represented by a semi-structured graph model. by using an intuitive 3se query language (3sql), users are able to pose queries on heterogeneous data in a varying degree of structural constraint according to their knowledge of schema. 3se evaluates 3sql queries as the top-k answers composed of "logical units" and relationship paths between them, and thus can extract meaningful information even if the query conditions are vague, ambiguous, and inaccurate.
maximal metric margin partitioning for similarity search indexes. we propose a partitioning scheme for similarity search indexes that is called maximal metric margin partitioning (mmmp). mmmp divides the data on the basis of its distribution pattern, especially for the boundaries of clusters. a partitioning surface created by mmmp is likely to be at maximum distances from the two cluster boundaries. mmmp is the first similarity search index approach to focus on partitioning surfaces and data distribution patterns. we also present an indexing scheme, named the mmmp-index, which uses mmmp and small ball partitioning. the mmmp-index prunes many objects that are not relevant to a query, and it reduces the query execution cost. our experimental results show that mmmp effectively indexes clustered data and reduces the search cost. for clustered vector data, the mmmp-index reduces the computational cost to less than two thirds that of comparable schemes.
data-driven compound splitting method for english compounds in domain names. significant amount of literature is available on compound splitting of long words albeit for non-english languages- especially european. not surprisingly, there has been not much work for english as it is not a compounding language like some of its european counterparts. however, internet domain names in general are compound english words, e.g. bankofamerica.com". compound splitting can be effectively employed to extract information from domain names. in this paper, an data-driven learning technique for splitting english compound words is described which among others uses features like normalized frequency, length of parts and n-gram. the splitting f-measure is higher than the published approaches. we applied this technique on a real life web search application where the queries are mistyped domain names routed through sources like isps and browsers. relevant and meaningful keywords were extracted out and shown to the user as a value added search option. results show a very high click-through rate and increased commercial value.
sdoc: exploring social wisdom for document enhancement in web mining. web document could be seen to be composed of textual content as well as social metadata of various forms (e.g., anchor text, search query and social annotation), both of which are valuable to indicate the semantic content of the document. however, due to the free nature of the web, the two streams of web data suffer from the serious problems of noise and sparseness, which have actually become the major challenges to the success of many web mining applications. previous work has shown that it could enhance the content of web document by integrating anchor text and search query. in this paper, we study the problem of exploring emergent social annotation for document enhancement and propose a novel reinforcement framework to generate "social representation" of document. distinguishing from prior work, textual content and social annotation are enhanced simultaneously in our framework, which is achieved by exploiting a kind of mutual reinforcement relationship behind them. two convergent models, social content model and social annotation model, are symmetrically derived from the framework to represent enhanced textual content and enhanced social annotation respectively. the enhanced document is referred to as social document or sdoc in that it could embed complementary viewpoints from many web authors and many web visitors. in this sense, the document semantics is enhanced exactly by exploring social wisdom. we build the framework on a large del.icio.us data and evaluate it through three typical web mining applications: annotation, classification and retrieval. experimental results demonstrate that social representation of web document could boost the performance of these applications significantly.
using opinion-based features to boost sentence retrieval. opinion mining has become recently a major research topic. a wide range of techniques have been proposed to enable opinion-oriented information seeking systems. however, little is known about the ability of opinion-related information to improve regular retrieval tasks. our hypothesis is that standard retrieval methods might benefit from the inclusion of opinion-based features. a sentence retrieval scenario is a natural choice to evaluate this claim. we propose here a formal method to incorporate some opinion-based features of the sentences as query-independent evidence. we show that this incorporation leads to retrieval methods whose performance is significantly better than the the performance of state of the art sentence retrieval models.
the gardener's problem for web information monitoring. we introduce and theoretically study the gardener's problem that well models many web information monitoring scenarios, where numerous dynamically changing web sources are monitored and local information needs to be periodically updated under communication and computation capacity constraints. typical such examples include maintenance of inverted indexes for search engines and maintenance of extracted structures for unstructured data management systems. we formulate a corresponding multicriteria optimization problem and propose heuristic solutions.
learning to rank graphs for online similar graph search. many applications in structure matching require the ability to search for graphs that are similar to a query graph, i.e., similarity graph queries. prior works, especially in chemoinformatics, have used the maximum common edge subgraph (mceg) to compute the graph similarity. this approach is prohibitively slow for real-time queries. in this work, we propose an algorithm that extracts and indexes subgraph features from a graph dataset. it computes the similarity of graphs using a linear graph kernel based on feature weights learned offline from a training set generated using mceg. we show empirically that our proposed algorithm of learning to rank graphs can achieve higher normalized discounted cumulative gain compared with existing optimal methods based on mceg. the running time of our algorithm is orders of magnitude faster than these existing methods.
compact full-text indexing of versioned document collections. we study the problem of creating highly compressed full-text index structures for versioned document collections, that is, collections that contain multiple versions of each document. important examples of such collections are wikipedia or the web page archive maintained by the internet archive. a straightforward indexing approach would simply treat each document version as a separate document, such that index size scales linearly with the number of versions. however, several authors have recently studied approaches that exploit the significant similarities between different versions of the same document to obtain much smaller index sizes. in this paper, we propose new techniques for organizing and compressing inverted index structures for such collections. we also perform a detailed experimental comparison of new techniques and the existing techniques in the literature. our results on an archive of the english version of wikipedia, and on a subset of the internet archive collection, show significant benefits over previous approaches.
answering xml queries using materialized views revisited. answering queries using views is a well-established technique in databases. in this context, two outstanding problems can be formulated. the first one consists in deciding whether a query can be answered exclusively using one or multiple materialized views. given the many alternative ways to compute the query from the materialized views, the second problem consists in finding the best way to compute the query from the materialized views. in the realm of xml, there is a restricted number of contributions in the direction of these problems due to the many limitations associated with the use of materialized views in traditional xml query evaluation models. in this paper, we adopt a recent evaluation model, called inverted lists model, and holistic algorithms which together have been established as the prominent technique for evaluating queries on large persistent xml data, and we address the previous two problems. this new context revises these problems since it requires new conditions for view usability and new techniques for computing queries from materialized views. we suggest an original approach for materializing views which stores for every view node only the list of xml nodes necessary for computing the answer of the view. we specify necessary and sufficient conditions for answering a tree-pattern query using one or multiple materialized views in terms of homomorphisms from the views to the query. in order to efficiently answer queries using materialized views, we design a stack-based algorithm which compactly encodes in polynomial time and space all the homomorphisms from a view to a query. we further propose space and time optimizations by using bitmaps to encode view materializations and by employing bitwise operations to minimize the evaluation cost of the queries. finally, we conducted an extensive experimentation which demonstrates that our approach yields impressive query hit rates in the view pool, achieves significant time and space savings and shows smooth scalability.
mining linguistic cues for query expansion: applications to drug interaction search. given a drug under development, what are other drugs or biochemical compounds that it might interact with? early answers to this question, by mining the literature, are valuable for pharmaceutical companies, both monetarily and in avoiding public relations nightmares. inferring drug-drug interactions is also important in designing combination therapies for complex diseases including cancers. we study this problem as one of mining linguistic cues for query expansion. by using (only) positive instances of drug interactions, we show how we can extract linguistic cues which can then be used to expand and reformulate queries to improve the effectiveness of drug interaction search. our approach integrates many learning paradigms: partially supervised classification, association measures for collocation mining, and feature selection in supervised learning. we demonstrate compelling results on using positive examples from the drugbank database to seed medline searches for drug interactions. in particular, we show that purely data-driven linguistic cues can be effectively mined and applied to realize a successful domain-specific query expansion framework.
ensembles in adversarial classification for spam. the standard method for combating spam, either in email or on the web, is to train a classifier on manually labeled instances. as the spammers change their tactics, the performance of such classifiers tends to decrease over time. gathering and labeling more data to periodically retrain the classifier is expensive. we present a method based on an ensemble of classifiers that can detect when its performance might be degrading and retrain itself, all without manual intervention. experiments with a real-world dataset from the blog domain show that our methods can significantly reduce the number of times classifiers are retrained when compared to a fixed retraining schedule, and they maintain classification accuracy even in the absence of manually labeled examples.
efficient algorithms for approximate member extraction using signature-based inverted lists. we study the problem of approximate membership extraction (ame), i.e., how to efficiently extract substrings in a text document that approximately match some strings in a given dictionary. this problem is important in a variety of applications such as named entity recognition and data cleaning. we solve this problem in two steps. in the first step, for each substring in the text, we filter away the strings in the dictionary that are very different from the substring. in the second step, each candidate string is verified to decide whether the substring should be extracted. we develop an incremental algorithm using signature-based inverted lists to minimize the duplicate list-scan operations of overlapping windows in the text. our experimental study of the proposed algorithms on real and synthetic datasets showed that our solutions significantly outperform existing methods in the literature.
yam: a schema matcher factory. in this paper, we present yam, a schema matcher factory. yam (yet another matcher) is not (yet) another schema matching system as it enables the generation of a la carte schema matchers according to user requirements. these requirements include a preference for recall or precision, a training data set (schemas already matched) and provided expert correspondences. yam uses a knowledge base that includes a (possibly large) set of similarity measures and classifiers. based on the user requirements, yam learns how to best apply these tools (similarity measures and classifiers) in concert to achieve the best matching quality. in our demonstration, we will let users apply yam to build the best schema matcher for different user requirements.
socializing or knowledge sharing?: characterizing social intent in community question answering. knowledge sharing communities, such as wikipedia or yahoo! answers, add greatly to the wealth of information available on the web. they represent complex social ecosystems that rely on user paricipation and the quality of users' contributions to prosper. however, quality is harder to achieve when knowledge sharing is facilitated through a high degree of personal interactions. the individuals' objectives may change from knowledge sharing to socializing, with a profound impact on the community and the value it delivers to the broader population of web users. in this paper we provide new insights into the types of content that is shared through community question answering (cqa) services. we demonstrate an approach that combines in-depth content analysis with social network analysis techniques. we adapted the undirected inductive coding method to analyze samples of user questions and arrive at a comprehensive typology of the user intent. in our analysis we focused on two types of intent, social vs. non-social, and define measures of social engagement to characterize the users' participation and content contributions. our approach is applicable to a broad class of online communities and can be used to monitor the dynamics of community ecosystems.
context sensitive synonym discovery for web search queries. we propose a simple yet effective approach to context sensitive synonym discovery for web search queries based on co-click analysis; i.e., analyzing queries leading to clicking same documents. in addition to deriving word based synonyms, we also derive concept based synonyms with the help of query segmentation. evaluation results show that this approach dramatically outperforms the thesaurus based synonym replacement method in keeping search intent, from accuracy of 40% to above 80%.
fuzzy semantic web ontology learning from fuzzy uml model. how to quickly and cheaply construct web ontologies has become a key technology to enable the semantic web. classical ontologies are not sufficient for handling imprecise and uncertain information that is commonly found in many application domains. in this paper, we propose an approach for constructing fuzzy ontologies from fuzzy uml models, in which the fuzzy ontology consists of fuzzy ontology structure and instances. firstly, the fuzzy uml model is investigated in detail, and a kind of formal definition of fuzzy uml models is proposed. then, a kind of fuzzy ontology called fuzzy owl dl ontology is introduced. furthermore, we consider the fuzzy uml model and the corresponding fuzzy uml instantiations (i.e., object diagrams) simultaneously, and translate them into the fuzzy ontology structure and the fuzzy ontology instances, respectively. in addition, since a fuzzy owl dl ontology is equivalent to a fuzzy description logic f-shoin(d) knowledge base, how the reasoning problems of fuzzy uml models (e.g., consistency, subsumption, equivalence, and redundancy) may be reasoned through reasoning mechanism of f-shoin(d) is investigated, which can help to construct fuzzy ontologies more exactly.
automatic query generation for patent search. patent search is the task of finding relevant existing patents, which is an important part of the patent's examiner's process of validating a patent application. in this paper, we studied how to transform a query patent (the application) into search queries. three types of search features are explored for automatic query generation for patent search. furthermore, different types of features are combined with a learning to rank method. experiments based on a uspto patent collection demonstrate that the single best search feature is the combination of words and noun-phrases from the summary field and the retrieval performance can be significantly improved by combining three types of search features.
user-induced links in collaborative tagging systems. collaborative tagging systems allow users to use tags to describe their favourite online documents. two documents that are maintained in the collection of the same user and/or assigned similar sets of tags can be considered as related from the perspective of the user, even though they may not be connected by hyperlinks. we call this kind of implicit relations user-induced links between documents. we consider two methods of identifying user-induced links in collaborative tagging, and compare these links with existing hyperlinks on the web. our analyses show that user-induced links have great potentials to enrich the existing link structure of the web. we also propose to use these links as a basis for predicting how documents would be tagged. our experiments show that they achieve much higher accuracy than existing hyperlinks. this study suggests that by studying the collective behaviour of users we are able to enhance navigation and organisation of web documents.
provenance query evaluation: what's so special about it? while provenance has been extensively studied in the literature, the efficient evaluation of provenance queries remains an open problem. traditional query optimization techniques, like the use of general-purpose indexes, or the materialization of provenance data, fail on different fronts to address the problem. therefore, the need to develop provenance-aware access methods becomes apparent. this paper starts by identifying some key requirements that are to a large extent specific to provenance queries and are necessary for their efficient evaluation. the first such property, called duality, requires that a single access method is used to evaluate both backward provenance queries (which input items of some analysis generate an output item) and forward provenance queries (which outputs of some analysis does an input item generate). the second property, called locality, guarantees that provenance query evaluation times should depend mainly on the size of the provenance query results and should be largely independent of the total size of provenance data. motivated by the above, we identify proper data structures with the aforementioned properties, we implement them, and through a detailed set of experiments, we illustrate their effectiveness on the evaluation of provenance queries.
online anonymity for personalized web services. to receive personalized web services, the user has to provide personal information and preferences, in addition to the query itself, to the web service. however, detailed personal information could identify the sender of sensitive queries, thus compromise user privacy. we propose the notion of online anonymity to enable users to issue personalized queries to an untrusted web service while with their anonymity preserved. the challenge for providing online anonymity is dealing with unknown and dynamic web users who can get online and offline at any time. we define this problem, discuss its implications and differences from the problems in the literature, and propose a solution.
url normalization for de-duplication of web pages. presence of duplicate documents in the world wide web adversely affects crawling, indexing and relevance, which are the core building blocks of web search. in this paper, we present a set of techniques to mine rules from urls and utilize these learnt rules for de-duplication using just url strings without fetching the content explicitly. our technique is composed of mining the crawl logs and utilizing clusters of similar pages to extract specific rules from urls belonging to each cluster. preserving each mined rules for de-duplication is not efficient due to the large number of specific rules. we present a machine learning technique to generalize the set of rules, which reduces the resource footprint to be usable at web-scale. the rule extraction techniques are robust against web-site specific url conventions. we demonstrate the effectiveness of our techniques through experimental evaluation.
heterogeneous cross domain ranking in latent space. traditional ranking mainly focuses on one type of data source, and effective modeling still relies on a sufficiently large number of labeled or supervised examples. however, in many real-world applications, in particular with the rapid growth of the web 2.0, ranking over multiple interrelated (heterogeneous) domains becomes a common situation, where in some domains we may have a large amount of training data while in some other domains we can only collect very little. one important question is: "if there is not sufficient supervision in the domain of interest, how could one borrow labeled information from a related but heterogenous domain to build an accurate model?". this paper explores such an approach by bridging two heterogeneous domains via the latent space. we propose a regularized framework to simultaneously minimize two loss functions corresponding to two related but different information sources, by mapping each domain onto a "shared latent space", capturing similar and transferable oncepts. we solve this problem by optimizing the convex upper bound of the non-continuous loss function and derive its generalization bound. experimental results on three different genres of data sets demonstrate the effectiveness of the proposed approach.
ranking model adaptation for domain-specific search. recently, various domain-specific search engines emerge, which are restricted to specific topicalities or document formats, and vertical to the broad-based search. simply applying the ranking model trained for the broad-based search to the verticals cannot achieve a sound performance due to the domain differences, while building different ranking models for each domain is both laborious for labeling sufficient training samples and time-consuming or the training process. in this paper, to address the above difficulties, we investigate two problems: (1) whether we can adapt the ranking model learned for existing web page search or verticals, to the new domain, so that the amount of labeled data and the training cost is reduced, while the performance requirement is still satisfied; and (2) how to adapt the ranking model from auxiliary domains to a new target domain. we address the second problem from the regularization framework and an algorithm called ranking adaptation svm is proposed. our algorithm is flexible enough, which needs only the prediction from the existing ranking model, rather than the internal representation of the model or the data from auxiliary domains. the first problem is addressed by the proposed ranking adaptability measurement, which quantitatively estimates if an existing ranking model can be adapted to the new domain. extensive experiments are performed over letor benchmark dataset and two large scale datasets crawled from different domains through a commercial internet search engine, where the ranking model learned for one domain will be adapted to the other. the results demonstrate the applicabilities of the proposed ranking model adaptation algorithm and the ranking adaptability measurement.
using multiple ontologies in information extraction. ontology-based information extraction (obie) has recently emerged as a subfield of information extraction (ie). here, ontologies - which provide formal and explicit specifications of conceptualizations - play a crucial role in the information extraction process. several obie systems have been implemented previously but all of them use a single ontology although multiple ontologies have been designed for many domains. we have studied the theoretical basis for using multiple ontologies in information extraction and have developed information extraction systems that use them. these systems investigate the two major scenarios for having multiple ontologies for the same domain: specializing in sub-domains and providing different perspectives. the domain of universities has been used for the former scenario through a corpus collected from university websites. for the latter, the domain of terrorist attacks and a corpus used by a previous message understanding conference (muc) have been used. the results from these two case studies indicate that using multiple ontologies in information extraction has led to a clear improvement in performance measures.
ming: mining informative entity relationship subgraphs. many modern applications are faced with the task of knowledge discovery in entity-relationship graphs, such as domain-specific knowledge bases or social networks. mining an "informative" subgraph that can explain the relations between k(>= 2) given entities of interest is a frequent knowledge discovery scenario on such graphs. we present ming, a principled method for extracting an informative subgraph for given query nodes. ming builds on a new notion of informativeness of nodes. this is used in a random-walk-with-restarts process to compute the informativeness of entire subgraphs.
who tags the tags?: a framework for bookmark weighting. in this work we propose a novel framework for bookmark weighting which allows us to estimate the effectiveness of each of the bookmarks individually. we show that by weighting bookmarks according to their estimated quality we can significantly improve search effectiveness. using empirical evaluation on real data gathered from two large bookmarking systems, we demonstrate the effectiveness of the new framework for search enhancement.
probabilistic latent preference analysis for collaborative filtering. a central goal of collaborative filtering (cf) is to rank items by their utilities with respect to individual users in order to make personalized recommendations. traditionally, this is often formulated as a rating prediction problem. however, it is more desirable for cf algorithms to address the ranking problem directly without going through an extra rating prediction step. in this paper, we propose the probabilistic latent preference analysis (plpa) model for ranking predictions by directly modeling user preferences with respect to a set of items rather than the rating scores on individual items. from a user's observed ratings, we extract his preferences in the form of pairwise comparisons of items which are modeled by a mixture distribution based on bradley-terry model. an em algorithm for fitting the corresponding latent class model as well as a method for predicting the optimal ranking are described. experimental results on real world data sets demonstrated the superiority of the proposed method over several existing cf algorithms based on rating predictions in terms of ranking performance measure ndcg.
post-rank reordering: resolving preference misalignments between search engines and end users. no search engine is perfect. a typical type of imperfection is the preference misalignment between search engines and end users, e.g., from time to time, web users skip higher-ranked documents and click on lower-ranked ones. although search engines have been aggressively incorporating clickthrough data in their ranking, it is hard to eliminate such misalignments across millions of queries. therefore, we, in this paper, propose to accompany a search engine with an "always-on" component that reorders documents on a per-query basis, based on user click patterns. because of positional bias and dependencies between clicks, we show that a simple sort based on click counts (and its variants), albeit intuitive and useful, is not precise enough. in this paper, we put forward a principled approach to reordering documents by leveraging existing click models. specifically, we compute the preference probability that a lower-ranked document is preferred to a higher-ranked one from the click chain model (ccm), and propose to swap the two documents if the probability is sufficiently high. because ccm models positional bias and dependencies between clicks, this method readily accounts for many twisted heuristics that have to be manually encoded in sort-based approaches. for this approach to be practical, we further devise two approximation schemes that make online computation of the preference probability feasible. we carried out a set of experiments based on real-world data from a major search engine, and the result clearly demonstrates the effectiveness of the proposed approach.
workload-aware trie indices for xml. well-designed indices can dramatically improve query performance. including query workload information can produce indices that yield better overall throughput while balancing the space and performance trade-off at the core of index design. in the context of xml, structural indices have proven to be particularly effective in supporting xpath queries by capturing the structural correlation between data components in an xml document. in this paper, we propose a family of novel workload-aware indices by taking advantage of the disk-based ρ[k]-trie index framework, which indexes node pairs of an xml document to facilitate index-only evaluation plans. our indices are designed to be optimal for answering frequent path queries in one index lookup and efficient for answering non-frequent path queries using an index-only plan. experimental results prove that our indices outperform the apex index in overall throughput and excel in answering non-frequent queries, queries with predicates, and queries that yield empty results.
usage based effectiveness measures: monitoring application performance in information retrieval. the aim of an information retrieval (ir) application is to support the user accessing relevant information effectively and efficiently. it is well known that system performance, in terms of finding relevant information is heavily dependent upon the ir application (i.e. the ir system exposed through the application's interface), as well as how the application is used by the user (i.e. how the user interacts with the system through the interface). thus, a very pragmatic evaluation question that arises at the application level is: what is the effectiveness experienced by the user during the usage of the application? to be able to answer this question, we represent the usage of an application by the stream of documents the user encounters while interacting with the application. this representation enables us to monitor and track the performance over time and usage. by taking a stream-based, time-centric view of the ir process, instead of a rank-list, topic/task centric view, the evaluation can be performed on any ir based application. to illustrate the difference and the utility of this approach, we demonstrate how a new suite of usage based effectiveness measures can be applied. this work provides the conceptual foundations for measuring, monitoring and modeling the performance of any ir application which needs to be evaluated over time and in context.
ds-cuber: an integrated olap environment for data streams. most of emerging applications deal with an infinite data stream in an incessant, immense and volatile manner. consequently, it is very important to analyze not only the varying characteristics of a source data stream in a short-term period but also those in a long-term period. for this purpose, this paper demonstrates an olap system, ds-cuber (data stream cuber) for the analysis of data streams. the proposed system consists of two analytic components: short-term and long-term, so that it can provide an integrated analysis environment for infinite data streams. furthermore, each of these two components supports diversified exception detection methods which can be used for the automatic identification of abnormality in the data elements of a data stream in order to guide the data cube navigation of a user effectively. network traffic flow streams are used to demonstrate the features of the ds-cube system.
(not) yet another matcher. discovering correspondences between schema elements is a crucial task for data integration. most schema matching tools are semi-automatic, e.g. an expert must tune some parameters (thresholds, weights, etc.). they mainly use several methods to combine and aggregate similarity measures. however, their quality results often decrease when one requires to integrate a new similarity measure or when matching particular domain schemas. this paper describes yam (yet another matcher), which is a schema matcher factory. indeed, it enables the generation of a dedicated matcher for a given schema matching scenario, according to user inputs. our approach is based on machine learning since schema matchers can be seen as classifiers. several bunches of experiments run against matchers generated by yam and traditional matching tools show how our approach is able to generate the best matcher for a given scenario.
efficient processing of group-oriented connection queries in a large graph. we study query processing in large graphs that are fundamental data model underpinning various social networks and web structures. given a set of query nodes, we aim to find the groups which the query nodes belong to, as well as the best connection among the groups. such a query is useful to many applications but the query processing is extremely costly. we define a new notion of correlation group (cg), which is a set of nodes that are strongly correlated in a large graph g. we then extract the subgraph from g that gives the best connection for the nodes in a cg. to facilitate query processing, we develop an efficient index built upon the cgs. our experiments show that the cgs are meaningful as groups and importantly, the meaningfulness of the query results are justifiable. we also demonstrate the high efficiency of cg computation, index construction and query processing.
an empirical study on using hidden markov model for search interface segmentation. this paper describes a hidden markov model (hmm) based approach to perform search interface segmentation. automatic processing of an interface is a must to access the invisible contents of deep web. this entails automatic segmentation, i.e., the task of grouping related components of an interface together. while it is easy for a human to discern the logical relationships among interface components, machine processing of an interface is difficult. in this paper, we propose an approach to segmentation that leverages the probabilistic nature of the interface design process. the design process involves choosing components based on the underlying database query requirements, and organizing them into suitable patterns. we simulate this process by creating an "artificial designer" in the form of a 2-layered hmm. the learned hmm acquires the implicit design knowledge required for segmentation. we empirically study the effectiveness of the approach across several representative domains of deep web. in terms of segmentation accuracy, the hmm-based approach outperforms an existing state-of-the-art approach by at least 10% in most cases. furthermore, our cross-domain investigation shows that a single hmm trained on data having varied and frequent design patterns can accurately segment interfaces from multiple domains.
constructing evolutionary taxonomy of collaborative tagging systems. collaborative tagging systems allow users to label online resources. the tags are generally correlated and evolving according to the change of web contents, and the popularity of tags represent evolution of social interests. tag taxonomy is a promising solution to organize the data in tagging systems. in this demonstration, we propose to construct the evolutionary taxonomy which incorporates the correlation and evolution of tags, as user generated tags grow and change temporally. we demonstrate that our approach is intuitive and efficient in tag organization which exploits the evolving characteristic of collaborative tagging systems.
pqc: personalized query classification. query classification (qc) is a task that aims to classify web queries into topical categories. since queries are usually short in length and ambiguous, the same query may need to be classified to different categories according to different people's perspectives. in this paper, we propose the personalized query classification (pqc) task and develop an algorithm based on user preference learning as a solution. users' preferences that are hidden in clickthrough logs are quite helpful for search engines to improve their understandings of users' queries. we propose to connect query classification with users' preference learning from clickthrough logs for pqc. to tackle the sparseness problem in clickthrough logs, we propose a collaborative ranking model to leverage similar users' information. experiments on a real world clickthrough log data show that our proposed pqc algorithm can gain significant improvement compared with general qc as well as natural baselines. our method can be applied to a wide range of applications including personalized search and online advertising.
automatic retrieval of similar content using search engine query interface. we consider the coverage testing problem where we are given a document and a corpus with a limited query interface and asked to find if the corpus contains a near-duplicate of the document. this problem has applications in search engines for competitive coverage testing. to solve this problem, we propose approaches that work in three main steps: generate a query signature from the document, query the corpus using the query signature and scrape the returned results, and validate the similarity between the input document and the returned results. we discuss techniques to control and bound the performance of these methods. we perform large-scale experimental validation and show that these methods perform well across different search engine corpora and documents in multiple languages. they also are robust against performance parameter variations.
improving retrievability of patents with cluster-based pseudo-relevance feedback documents selection. high findability of documents within a certain cut-off rank is considered an important factor in recall-oriented application domains such as patent or legal document retrieval. findability is hindered by two aspects, namely the inherent bias favoring some types of documents over others introduced by the retrieval model, and the failure to correctly capture and interpret the context of conventionally rather short queries. in this paper, we analyze the bias impact of different retrieval models and query expansion strategies. we furthermore propose a novel query expansion strategy based on document clustering to identify dominant relevant documents. this helps to overcome limitations of conventional query expansion strategies that suffer strongly from the noise introduced by imperfect initial query results for pseudo-relevance feedback documents selection. experiments with different collections of patent documents suggest that clustering based document selection for pseudo-relevance feedback is an effective approach for increasing the findability of individual documents and decreasing the bias of a retrieval system.
probabilistic models for topic learning from images and captions in online biomedical literatures. biomedical images and captions are one of the major sources of information in online biomedical publications. they often contain the most important results to be reported, and provide rich information about the main themes in published papers. in the data mining and information retrieval community, there has been much effort on using text mining and language modeling algorithms to extract knowledge from the text content of online biomedical publications; however, the problem of knowledge extraction from biomedical images and captions has not been fully studied yet. in this paper, a hierarchical probabilistic topic model with background distribution (hpb) is introduced to uncover the latent semantic topics from the co-occurrence patterns of caption words, visual words and biomedical concepts. with downloaded biomedical figures, restricted captions are extracted with regard to each individual image panel. during the indexing stage, the 'bag-of-words' representation of captions is supplemented by an ontology-based concept indexing to alleviate the synonym and polysemy problems. as the visual counterpart of text words, the visual words are extracted and indexed from corresponding image panels. the model is estimated via collapsed gibbs sampling algorithm. we compare the performance of our model with the extension of the correspondence lda (corr-lda) model under the same biomedical image annotation scenario using cross-validation. experimental results demonstrate that our model is able to accurately extract latent patterns from complicated biomedical image-caption pairs and facilitate knowledge organization and understanding in online biomedical literatures.
suffix trees for very large genomic sequences. a suffix tree is a fundamental data structure for string searching algorithms. unfortunately, when it comes to the use of suffix trees in real-life applications, the current methods for constructing suffix trees do not scale for large inputs. all the existing practical algorithms perform random access to the input string, thus requiring that the input be small enough to be kept in main memory. we are the first to present an algorithm which is able to construct suffix trees for input sequences significantly larger than the size of the available main memory. as a proof of concept, we show that our method allows to build the suffix tree for 12gb of real dna sequences in 26 hours on a single machine with 2gb of ram. this input is four times the size of the human genome, and the construction of suffix trees for inputs of such magnitude was never reported before.
translating relevance scores to probabilities for contextual advertising. information retrieval systems conventionally assess document relevance using the bag of words model. consequently, relevance scores of documents retrieved for different queries are often difficult to compare, as they are computed on different (or even disjoint) sets of textual features. many tasks, such as federation of search results or global thresholding of relevance scores, require that scores be globally comparable. to achieve this, in this paper we propose methods for non-monotonic transformation of relevance scores into probabilities for a contextual advertising selection engine that uses a vector space model. the calibration of the raw scores is based on historical click data.
clouddb workshop summary. this is the first workshop in cikm conference that addresses the challenge of large data management based on cloud computing infrastructure. this workshop will bring together researchers and practitioners in cloud computing and data-intensive system design, programming, parallel algorithms, data management, scientific applications, and information-based applications to maximize performance, minimize cost and improve the scale of their endeavors. totally this workshop attracted 11 submissions from asia, canada, europe, and the united states. the program committee accepted 8 papers, among which there are 5 full papers and 3 short papers. topics of accepted papers includes query processing & index, service in the cloud, platform availability, cloud system implementation, data replication and so on. these proceedings will serve as a valuable reference for cloud data management researchers and developers.
personalized social search based on the user's social network. this work investigates personalized social search based on the user's social relations -- search results are re-ranked according to their relations with individuals in the user's social network. we study the effectiveness of several social network types for personalization: (1) familiarity-based network of people related to the user through explicit familiarity connection; (2) similarity-based network of people "similar" to the user as reflected by their social activity; (3) overall network that provides both relationship types. for comparison we also experiment with topic-based personalization that is based on the user's related terms, aggregated from several social applications. we evaluate the contribution of the different personalization strategies by an off-line study and by a user survey within our organization. in the off-line study we apply bookmark-based evaluation, suggested recently, that exploits data gathered from a social bookmarking system to evaluate personalized retrieval. in the on-line study we analyze the feedback of 240 employees exposed to the alternative personalization approaches. our main results show that both in the off-line study and in the user survey social network based personalization significantly outperforms non-personalized social search. additionally, as reflected by the user survey, all three sn-based strategies significantly outperform the topic-based strategy.
rose: retail outlet site evaluation by learning with both sample and feature preference. it is critical for retail enterprises to select good sites or locations to open their stores, especially in current competitive retail market. however, evaluating the goodness of sites in real business applications is a complex problem. that is, how to judge whether the market around a store site is good? we don't know the exact mechanism of how a site can be good and it is hard to have correct site goodness values as supervised labels. the retail outlet site evaluation (rose) tool is designed to learn the site evaluation model by integrating city geographic & demographic data and two kinds of expert knowledge: sample preference and feature preference. the feature preference information can help greatly reduce the required number of sample preferences. it enables our application practicable because it is almost impossible to give such amount of sample preference pairs manually by experts when ranking hundreds of data points. in the experiment and case study part, we show that the rose tool can achieve good results and useful for users to do site evaluation work in real cases.
boosting knn text classification accuracy by using supervised term weighting schemes. the increasing availability of digital documents in the last decade has prompted the development of machine learning techniques to automatically classify and organize text documents. the majority of text classification systems rely on the vector space model, which represents the documents as vectors in the term space. each vector component is assigned a weight that reflects the importance of the term in the document. typically, these weights are assigned using an information retrieval (ir) approach, such as the famous tf-idf function. in this work, we study two weighting schemes based on information gain and chi-square statistics. these schemes take advantage of the category label information to weight the terms according to their distributions across the different categories. we show that using these supervised weights instead of conventional unsupervised weights can greatly improve the performance of the k-nearest neighbor (knn) classifier. experimental evaluations, carried out on multiple text classification tasks, demonstrate the benefits of this approach in creating accurate text classifiers.
towards non-directional xpath evaluation in a rdbms. xml query languages use directional path expressions to locate data in an xml data collection. they are tightly coupled to the structure of a data collection, and can fail when evaluated on the same data in a different structure. this paper extends path expressions with a new non-directional axis called the rank-distance axis. given a context node and two positive integers α and β, the rank-distance axis returns those nodes that are ranked between α and β in terms of closeness from the context node in any direction. this paper shows how to evaluate the rank-distance axis in a tree-unaware xml database. a tree-unaware implementation does not invade the database kernel to support xml queries, instead it uses an existing rdbms such as microsoft's sql server as a back-end and provides a front-end layer to translate xml queries to sql. this paper presents an overview of an algorithm that translates queries with a rank-distance axis to sql.
scalable learning of collective behavior based on sparse social dimensions. the study of collective behavior is to understand how individuals behave in a social network environment. oceans of data generated by social media like facebook, twitter, flickr and youtube present opportunities and challenges to studying collective behavior in a large scale. in this work, we aim to learn to predict collective behavior in social media. in particular, given information about some individuals, how can we infer the behavior of unobserved individuals in the same network? a social-dimension based approach is adopted to address the heterogeneity of connections presented in social media. however, the networks in social media are normally of colossal size, involving hundreds of thousands or even millions of actors. the scale of networks entails scalable learning of models for collective behavior prediction. to address the scalability issue, we propose an edge-centric clustering scheme to extract sparse social dimensions. with sparse social dimensions, the social-dimension based approach can efficiently handle networks of millions of actors while demonstrating comparable prediction performance as other non-scalable methods.
adaptive geospatially focused crawling. location information on the web is a precious asset for a multitude of applications and is becoming an increasingly important dimension in web search. even though more and more web pages carry location information, they form only a small share of all pages and are scattered over the web. to efficiently find and index location-related web content, we propose an efficient crawling strategy that retrieves precisely those pages that are geospatially relevant while minimizing the amount of the non-spatially-relevant pages within the crawled pages. we propose to address this challenge by expanding the technique of focused crawling to exploit location references on web pages to specifically retrieve geospatial topics on the web. in this paper, we describe the design and development of a focused crawler with an adaptive geospatial focus that efficiently retrieves and identifies location-relevant documents on the web. drawing from geospatial features of both web pages and the link graph, a crawl strategy based on bayesian classifiers prioritizes promising links and pages, leading to a faster coverage of the desired geospatial topic as a means for fast creation of precise geospatial web indexes. we present evaluations of the system's performance and share our findings on the geospatial web graph and the distribution of location references on the web.
efficient join processing on uncertain data streams. join processing in the streaming environment has many practical applications such as data cleaning and outlier detection. due to the inherent uncertainty in the real-world data, it has become an increasingly important problem to consider the join processing on uncertain data streams, where the incoming data at each timestamp are uncertain and imprecise. different from the static databases, processing uncertain data streams has its own requirements such as the limited memory, small response time, and so on. to tackle the challenges with respect to efficiency and effectiveness, in this paper, we formalize the problem of join on uncertain data streams (usj), which can guarantee the accuracy of usj answers over uncertain data, and propose effective pruning methods to filter out false alarms. we integrate the pruning methods into an efficient query procedure for incrementally maintaining usj answers. extensive experiments have been conducted to demonstrate the efficiency and effectiveness of our approaches.
the use of categorization information in language models for question retrieval. community question answering (cqa) has emerged as a popular type of service meeting a wide range of information needs. such services enable users to ask and answer questions and to access existing question-answer pairs. cqa archives contain very large volumes of valuable user-generated content and have become important information resources on the web. to make the body of knowledge accumulated in cqa archives accessible, effective and efficient question search is required. question search in a cqa archive aims to retrieve historical questions that are relevant to new questions posed by users. this paper proposes a category-based framework for search in cqa archives. the framework embodies several new techniques that use language models to exploit categories of questions for improving question-answer search. experiments conducted on real data from yahoo! answers demonstrate that the proposed techniques are effective and efficient and are capable of outperforming baseline methods significantly.
helping people to choose for whom to vote. a web information system for the 2009 european elections. we demonstrate a web information system created for the european elections in june 2009. based on their speeches in the eu parliament and their written questions, we created language models for each of the 736 members of the eu parliament. these language models were used to search for politicians responsible for a given topic, similar to expert search applications. users prefer to see some kind of evidence for returning a hit after a search. we created a profile of each eu parlementarian by comparing her personal language model to the language model created from all eu parlementarians. the top 50 words best separating the individual from the avarage were shown as a wordcloud. these top 50 words and their scores were derived from a parsimonious language model.
a study of selective collection enrichment for enterprise search. enterprise intranets are often sparse in nature, with limited use of alternative lexical representations between authors, making query expansion (qe) ineffective. hence, for some enterprise search queries, it can be advantageous to instead use the well-known collection enrichment (ce) method to gather higher quality pseudo-feedback documents from a more diverse external resource. however, it is not always clear for which queries the collection enrichment technique should be applied. in this paper, we study two different approaches, namely a predictor-based approach and a divergence-based approach, to decide on when to apply ce. we thoroughly evaluate both approaches on the trec enterprise track cerc test collection and its corresponding topic sets, in combination with three different external resources and nine different query performance predictors. our results show that both approaches are effective to selectively apply ce for enterprise search. in particular, the divergence-based approach leads to consistent and marked retrieval improvements over the systematic application of qe or ce on all external resources.
vrifa: a nonlinear svm visualization tool using nomogram and localized radial basis function (lrbf) kernels. prediction problems are prevalent in medical domains. for example, computer-aided diagnosis or prognosis is a key component in a cdss (clinical decision support system). svms, especially svms with nonlinear kernels such rbf kernels, have shown superior accuracy in prediction problems. however, they are not favorably used by physicians for medical prediction problems because nonlinear svms are difficult to visualize, thus it is hard to provide intuitive interpretation of prediction results to physicians. nomogram was proposed to visualize svm classification models. however, it cannot visualize nonlinear svm models. localized rbf (lrbf) kernel was proposed which shows comparable accuracy as the rbf kernel while the lrbf kernel is easier to interpret since it can be linearly decomposed. this paper presents a new tool named vrifa, which integrates the nomogram and lrbf kernel to provide users with an interactive visualization of nonlinear svm models. vrifa graphically exposes the internal structure of nonlinear svm models showing the effect of each feature, the magnitude of the effect, and the change at the prediction output. vrifa also performs nomogram-based feature selection while training a model in order to remove noise or redundant features and improve the prediction accuracy. the tool has been used by biomedical researchers for computer-aided diagnosis and risk factor analysis for diseases. vrifa is accessible at http://dm.postech.ac.kr/vrifa .
efficient information retrieval in mobile peer-to-peer networks. mobile devices have become indispensable in daily life, and hence how to take advantage of these portable and powerful facilities to share resources and information begins to emerge as an interesting problem. in this paper, we investigate the problem of information retrieval in a mobile peer-to-peer network. the prevailing approach to information retrieval is to apply flooding methods because of its quick response and easy maintenance. obviously, this kind of approach wastes a huge amount of communication bandwidth which greatly affects the availability of the network, and the battery power which significantly shortens the serving time of mobile devices in the network. to tackle this problem, we propose a novel approach by mimicking different human behaviors of social networks, which takes advantages of intelligence accuracy (ia) mechanism that evaluates the distance from a node to certain resources in the network. extensive experimental results show the efficiency and effectiveness of our approach as well as its scalability in a volatile environment.
clustering web queries. despite the wide applicability of clustering methods, their evaluation remains a problem. in this paper, we present a metric for the evaluation of clustering methods. the data set to be clustered is viewed as a sample from a larger population, with clustering quality measured in terms of our predicted ability to discriminate between members of this population. we measure this property by training a classifier to recognize each cluster and measuring the accuracy of this classifier, normalized by a notion of expected accuracy. to demonstrate the applicability of this metric we apply it to web queries. we investigated a commercially oriented data set of 1700 queries and a general data set of 4000 queries. both sets are taken from the logs of a commercial web search engine. clustering is based on the contents of search engine result pages generated by executing the queries on the search engine from which they were taken. multiple clustering algorithms are crossed with various weighting schemes to produce multiple clusterings of each query set. our metric is used evaluate these clusterings. the results on the commercially oriented data set are compared to two pre-existing manual labelings, and are also used in an ad clickthrough experiment.
pure spreading activation is pointless. almost every application of spreading activation is accompanied by its own set of often heuristic restrictions on the dynamics. we show that in constraint-free scenarios spreading activation would actually yield query-independent results, so that the specific choice of restrictions is not only a pragmatic computational issue, but crucially determines the outcome.
automatic web data extraction using tree alignment. this paper investigates the automatic extraction of data from forums, blogs and news web sites. web pages are increasingly dynamically generated using a common template populated with data from databases. this paper proposes a novel method that uses tree alignment to automatically extract data from these types of web pages. a new tree alignment algorithm is presented for determining the optimal matching structure of the input web pages. based on the alignment, the trees are merged into one union tree whose nodes record statistical information obtained from multiple web pages. a heuristic method is employed for determining the most probable content block and the alignment algorithm detects repeating patterns on the union tree. a wrapper built on the most probable content block and the repeating patterns extracts data from web pages. experimental results show that the method achieves high extraction accuracy and has steady performance.
frequent subgraph pattern mining on uncertain graph data. graph data are subject to uncertainties in many applications due to incompleteness and imprecision of data. mining uncertain graph data is semantically different from and computationally more challenging than mining exact graph data. this paper investigates the problem of mining frequent subgraph patterns from uncertain graph data. the frequent subgraph pattern mining problem is formalized by designing a new measure called expected support. an approximate mining algorithm is proposed to find an approximate set of frequent subgraph patterns by allowing an error tolerance on the expected supports of the discovered subgraph patterns. the algorithm uses an efficient approximation algorithm to determine whether a subgraph pattern can be output or not. the analytical and experimental results show that the algorithm is very efficient, accurate and scalable for large uncertain graph databases.
online community search using thread structure. online communities are valuable information sources where knowledge is accumulated by interactions between people. search services provided by online community sites such as forums are often, however, quite poor. to address this, we investigate retrieval techniques that exploit the hierarchical thread structures in community sites. since these structures are sometimes not explicit or accurately annotated, we use structure discovery techniques. we then make use of thread structures in retrieval experiments. our results show that using thread structures that have been accurately annotated can lead to significant improvements in retrieval performance compared to strong baselines.
selc: a self-supervised model for sentiment classification. this paper presents the selc model (self-supervised, (lexicon-based and (corpus-based model) for sentiment classification. the selc model includes two phases. the first phase is a lexicon-based iterative process. in this phase, some reviews are initially classified based on a sentiment dictionary. then more reviews are classified through an iterative process with a negative/positive ratio control. in the second phase, a supervised classifier is learned by taking some reviews classified in the first phase as training data. then the supervised classifier applies on other reviews to revise the results produced in the first phase. experiments show the effectiveness of the proposed model. selc totally achieves 6.63% f1-score improvement over the best result in previous studies on the same data (from 82.72% to 89.35%). the first phase of the selc model independently achieves 5.90% improvement (from 82.72% to 88.62%). moreover, the standard deviation of f1-scores is reduced, which shows that the selc model could be more suitable for domain-independent sentiment classification.
hddbrs middleware for implementing highly available distributed databases. our demo presents hddbrs, a middle tier offering to clients a highly available distributed database interface using reed solomon codes to compute parity data. parity data is stored in dedicated parity db backends, is synchronously updated and allows recovering from multiple db backend unavailability. hddbrs middle tier is implemented in java using standard technology, and is designed to be interoperable with any database engine that provides a jdbc driver and implements x/open xa protocol.
exploit the tripartite network of social tagging for web clustering. in this poster, we investigate how to enhance web clustering by leveraging the tripartite network of social tagging systems. we propose a clustering method, called "tripartite clustering", which cluster the three types of nodes (resources, users and tags) simultaneously based on the links in the social tagging network. the proposed method is experimented on a real-world social tagging dataset sampled from del.icio.us. we also compare the proposed clustering approach with k-means. all the clustering results are evaluated against a human-maintained web directory. the experimental results show that tripartite clustering significantly outperforms the content-based k-means approach and achieves performance close to that of social annotation-based k-means whereas generating much more useful information.
event detection from flickr data through wavelet-based spatial analysis. detecting events from web resources has attracted increasing research interests in recent years. our focus in this paper is to detect events from photos on flickr, an internet image community website. the results can be used to facilitate user searching and browsing photos by events. the problem is challenging considering: (1) flickr data is noisy, because there are photos unrelated to real-world events; (2) it is not easy to capture the content of photos. this paper presents our effort in detecting events from flickr photos by exploiting the tags supplied by users to annotate photos. in particular, the temporal and locational distributions of tag usage are analyzed in the first place, where a wavelet transform is employed to suppress noise. then, we identify tags related with events, and further distinguish between tags of aperiodic events and those of periodic events. afterwards, event-related tags are clustered such that each cluster, representing an event, consists of tags with similar temporal and locational distribution patterns as well as with similar associated photos. finally, for each tag cluster, photos corresponding to the represented event are extracted. we evaluate the performance of our approach using a set of real data collected from flickr. the experimental results demonstrate that our approach is effective in detecting events from the flickr photo collection.
l2 norm regularized feature kernel regression for graph data. features in many real world applications such as cheminformatics, bioinformatics and information retrieval have complex internal structure. for example, frequent patterns mined from graph data are graphs. such graph features have different number of nodes and edges and usually overlap with each other. in conventional data mining and machine learning applications, the internal structure of features are usually ignored. in this paper we consider a supervised learning problem where the features of the data set have intrinsic complexity, and we further assume that the feature intrinsic complexity may be measured by a kernel function. we hypothesize that by regularizing model parameters using the information of feature complexity, we can construct simple yet high quality model that captures the intrinsic structure of the data. towards the end of testing this hypothesis, we focus on a regression task and have designed an algorithm that incorporate the feature complexity in the learning process, using a kernel matrix weighted l2 norm for regularization, to obtain improved regression performance over conventional learning methods that does not consider the additional information of the feature. we have tested our algorithm using 5 different real-world data sets and have demonstrate the effectiveness of our method.
label correspondence learning for part-of-speech annotation transformation. the performance of machine learning methods heavily depends on the volume of used training data. for the purpose of dataset enlargement, it is of interest to study the problem of unifying multiple labeled datasets with different annotation standards. in this paper, we focus on the case of unifying datasets for sequence labeling problems with natural language part-of-speech (pos) tagging as an examplar application. to this end, we propose a probabilistic approach to transforming the annotations of one dataset to the standard specified by another dataset. the key component of the approach, named as label correspondence learning, serves as a bridge of annotations from the datasets. two methods designed from distinct perspectives are proposed to attack this sub-problem. experiments on two large-scale part-of-speech datasets demonstrate the efficacy of the transformation and label correspondence learning methods.
effective and efficient structured retrieval. search engines that support structured documents typically support structure created by the author (e.g., title, section), and may also support structure added by an annotation process (e.g., part of speech, named entity, semantic role). exploiting such structure can be difficult. query structure may fail to match structure in a relevant document for a variety of reasons, thus structured queries, although containing more information than keyword queries, are often less effective than unstructured queries. this paper studies retrieval of sentences with annotations for a question answering task. three problems of structured retrieval are identified and solutions proposed. structural mismatch is addressed by query structure expansion of predicted relevant structures. lack of presence of all key aspects of a question is solved by boolean filtering of result sentences. the score variations of the annotator generated fields with all the different lengths are accounted for by using field specific smoothing. experiments show that each solution incrementally improves structured retrieval, and a combination of boolean filtering, structural expansion, and keyword queries outperforms keyword and simple structured retrieval baselines.
a translation model for matching reviews to objects. we develop a generic method for the review matching problem, which is to match unstructured text reviews to a list of objects, where each object has a set of attributes. to this end, we propose a translation model for generating reviews from a structured description of objects. we develop an em-based method to estimate the model parameters and use this model to find, given a review, the object most likely to be the topic of the review. we conduct extensive experiments on two large-scale datasets: a collection of restaurant reviews from yelp and a collection of movie reviews from imdb. the experiments show that our translation model-based method is superior to traditional tf-idf based methods as well as a recent mixture model-based method for the review matching problem.
a scalable and effective full-text search in p2p networks. we consider the problem of full-text search involving multi-term queries in a network of self-organizing, autonomous peers. existing approaches do not scale well with respect to the number of peers, because they either require access to a large number of peers or incur a high communication cost in order to achieve good query results. in this paper, we present a novel algorithmic framework for processing multi-term queries in p2p networks that achieves high recall while using (per-query) a small number of peers and a low communication cost, thereby enabling high query throughput. our approach is based on per-query peer-selection strategy using two-dimensional histograms of score distributions. a full utilization of the histograms incurs a high communication cost. we show how to drastically reduce this cost by employing a two-phase peer-selection algorithm. we also describe an adaptive approach to peer selection that further increases the recall. experiments on a large real-world collection show that the recall is indeed high while the number of involved peers and the communication cost are low.
a word clustering approach for language model-based sentence retrieval in question answering systems. in this paper we propose a term clustering approach to improve the performance of sentence retrieval in question answering (qa) systems. as the search in question answering is conducted over smaller segments of data than in a document retrieval task, the problems of data sparsity and exact matching become more critical. in this paper we propose language modeling (lm) techniques to overcome such problems and improve the sentence retrieval performance. our proposed methods include building class-based models by term clustering, and then employing higher order n-grams with the new class-based model. we report our experiments on the trec 2007 questions from qa track. the results show that the methods investigated here enhanced the mean average precision of sentence retrieval from 23.62% to 29.91%.
compressing tags to find interesting media groups. on photo sharing websites like flickr and zooomr, users are offered the possibility to assign tags to their uploaded pictures. using these tags to find interesting groups of semantically related pictures in the result set of a given query is a problem with obvious applications. we analyse this problem from a minimum description length (mdl) perspective and develop an algorithm that finds the most interesting groups. the method is based on krimp, which finds small sets of patterns that characterise the data using compression. these patterns are sets of tags, often assignedtogether to photos. the better a database compresses, the more structure it contains and thus the more homogeneous it is. following this observation we devise a compression-based measure. our experiments on flickr data show that the most interesting and homogeneous groups are found. we show extensive examples and compare to clusterings on the flickr website.
towards real-time measurement of customer satisfaction using automatically generated call transcripts. customer satisfaction is a very important indicator of how successful a contact center is at providing services to the customers. contact centers typically conduct a manual survey with a randomly selected group of customers to measure customer satisfaction. manual customer satisfaction surveys, however, provide limited values due to high cost and the time lapse between the service and the survey. in this paper, we demonstrate that it is possible to automatically measure customer satisfaction by analyzing call transcripts enabling companies to measure customer satisfaction for every call in near real-time. we have identified various features from multiple knowledge sources indicating prosodic, linguistic and behavioral aspects of the speakers, and built machine learning models that predict the degree of customer satisfaction with high accuracy. the machine learning algorithms used in this work include decision tree, naive bayes, logistic regression and support vector machines (svms). experiments were conducted for a 5-point satisfaction measurement and a 2-point satisfaction measurement using customer calls to an automotive company. the experimental results show that customer satisfaction can be measured quite accurately both at the end of calls and in the middle of calls. the best performing 5-point satisfaction classification yields an accuracy of 66.09% outperforming the dominantclass baseline by 15.16%. the best performing 2-point classification shows an accuracy of 89.42% and outperforms both the dominantclass baseline and the csrjudgment baseline by 17.7% and 3.3% respectively. furthermore, decision tree and svms achieve higher f-measure than the csrjudgment baseline in identifying both satisfied customers and dissatisfied customers.
graph-based seed selection for web-scale crawlers. one of the most important steps in web crawling is determining the starting points, or seed selection. this paper identifies and explores the problem of seed selection in web-scale incremental crawlers. we argue that seed selection is not a trivial but very important problem. selecting proper seeds can increase the number of pages a crawler will discover, and can result in a repository with more "good" and less "bad" pages. we propose a graph-based framework for crawler seed selection, and present several algorithms within this framework. evaluation on real web data showed significant improvements over heuristic seed selection approaches.
context-sensitive document ranking. ranking is a main research issue in ir-styled keyword search over a set of documents. in this paper, we study a new keyword search problem, called context-sensitive document ranking, which is to rank documents with an additional context that provides additional information about the application domain where the documents are to be searched and ranked. the work is motivated by the fact that additional information associated with the documents can possibly assist users to find more relevant documents when they are unable to find the needed documents from the documents alone. in this paper, a context is a multi-attribute graph, which can represent any information maintained in a relational database. the context-sensitive ranking is related to several research issues, how to score documents, how to evaluate the additional information obtained in the context that may contribute the document ranking, how to rank the documents by combining the scores/costs from the documents and the context. more importantly, the relationships between documents and the information stored in a relational database may be uncertain, because they are from different data sources and the relationships are determined systematically using similarity match which causes uncertainty. in this paper, we concentrate ourselves on these research issues, and provide our solution on how to rank the documents in a context where there exist uncertainty between the documents and the context. we confirm the effectiveness of our approaches by conducting extensive experimental studies using real datasets.
supervised semantic indexing. in this article we propose supervised semantic indexing (ssi), an algorithm that is trained on (query, document) pairs of text documents to predict the quality of their match. like latent semantic indexing (lsi), our models take account of correlations between words (synonymy, polysemy). however, unlike lsi our models are trained with a supervised signal directly on the ranking task of interest, which we argue is the reason for our superior results. as the query and target texts are modeled separately, our approach is easily generalized to different retrieval tasks, such as online advertising placement. dealing with models on all pairs of words features is computationally challenging. we propose several improvements to our basic model for addressing this issue, including low rank (but diagonal preserving) representations, and correlated feature hashing (cfh). we provide an empirical study of all these methods on retrieval tasks based on wikipedia documents as well as an internet advertisement task. we obtain state-of-the-art performance while providing realistically scalable methods.
irank: an interactive ranking framework and its application in query-focused summarization. we address the problem of unsupervised ensemble ranking in this paper. traditional approaches either combine multiple ranking criteria into a unified representation to obtain an overall ranking score or to utilize certain rank fusion or aggregation techniques to combine the ranking results. beyond the aforementioned combine-then-rank and rank-then-combine approaches, we propose a novel rank-learn-combine ranking framework, called interactive ranking (irank), which allows two base rankers to "teach" each other before combination during the ranking process by providing their own ranking results as feedback to the others so as to boost the ranking performance. this mutual ranking refinement process continues until the two base rankers cannot learn from each other any more. the overall performance is improved by the enhancement of the base rankers through the mutual learning mechanism. we apply this framework to the sentence ranking problem in query-focused summarization and evaluate its effectiveness on the duc 2005 data set. the results are encouraging with consistent and promising improvements.
language-model-based ranking for queries on rdf-graphs. the success of knowledge-sharing communities like wikipedia and the advances in automatic information extraction from textual and web sources have made it possible to build large "knowledge repositories" such as dbpedia, freebase, and yago. these collections can be viewed as graphs of entities and relationships (er graphs) and can be represented as a set of subject-property-object (spo) triples in the semantic-web data model rdf. queries can be expressed in the w3c-endorsed sparql language or by similarly designed graph-pattern search. however, exact-match query semantics often fall short of satisfying the users' needs by returning too many or too few results. therefore, ir-style ranking models are crucially needed. in this paper, we propose a language-model-based approach to ranking the results of exact, relaxed and keyword-augmented graph pattern queries over rdf graphs such as er graphs. our method estimates a query model and a set of result-graph models and ranks results based on their kullback-leibler divergence with respect to the query model. we demonstrate the effectiveness of our ranking model by a comprehensive user study.
multi-aspect opinion polling from textual reviews. this paper presents an unsupervised approach to aspect-based opinion polling from raw textual reviews without explicit ratings. the key contribution of this paper is three-fold. first, a multi-aspect bootstrapping algorithm is proposed to learn from unlabeled data aspect-related terms of each aspect to be used for aspect identification. second, an unsupervised segmentation model is proposed to address the challenge of identifying multiple single-aspect units in a multi-aspect sentence. finally, an aspect-based opinion polling algorithm is presented. experiments on real chinese restaurant reviews show that our opinion polling method can achieve 75.5% precision performance.
rss watchdog: an instant event monitor on real online news streams. this paper introduces the rss watchdog system, which is capable of news clustering and instant event monitoring over multiple real and online rss news streams. we briefly mention software architecture design, technical implementation, and prototype demonstration. in addition, the results of real case studies are presented to notice the rss watchdog's functionality
a study of information retrieval on accumulative social descriptions using the generation features. this paper is concerned with the study of information retrieval (ir) on accumulative social descriptions (asds). asds refer to web texts that accumulated by many web users describing certain web resources, such as anchor texts, search logs and social annotations. there have been some studies working on leveraging asds for improving search performance in both internet and intranet. however, to the best of our knowledge, no prior study has concerned the specific generation features of asds, which are the focus point of this paper. specifically, we consider the generation features from two perspectives, the generation processes and the generated distributions. further, three probabilistic ir models are derived based on them. the three models are first demonstrated with one toy dataset and then empirically evaluated with two real datasets: an internet dataset consisting of 90,295 web pages, with 25,845,818 social annotations crawled from del.icio.us and 31,320,005 pieces of anchor texts crawled through yahoo! api, and an intranet dataset consisting of 179,835 web pages with 1,245,522 annotations dumped from the intranet tagging system in ibm, named as dogear. extensive experimental results show that the proposed methods, which fully leverage the generation features of asds, improve the performance of both internet and intranet search significantly.
privacy without noise. this paper presents several results on statistical database privacy. we first point out a serious vulnerability in a widely-accepted approach which perturbs query results with additive noise. we then show that for sum queries which aggregate across all records, when the dataset is sufficiently large, the inherent uncertainty associated with unknown quantities is enough to provide similar perturbation and the same privacy can be obtained without external noise. sum query is a surprisingly general primitive supporting a large number of data mining algorithms such as svd, pca, k-means, id3, svm, em, and all the algorithms in the statistical query model. we derive privacy conditions for sum queries and provide the first mathematical proof for the intuition that aggregates across a large number of individuals is private using a widely accepted notion of privacy. we also show how the results can be used to construct simulatable query auditing algorithms with stronger privacy.
efficient processing of twig pattern matching in fuzzy xml. in order to find all occurrences of a twig pattern in xml documents, a considerable amount of twig pattern matching algorithms have been proposed. at the same time, previous work mainly focuses on twig pattern query under the complete semantics. however, there is often a need to produce partial answers because xml data may have missing sub-elements. furthermore, the existed works fall short in their ability to support twig pattern query under different semantics in fuzzy xml. in this paper, we study the problem of twig matches in fuzzy xml. we begin by introducing the extended region scheme to accurately and effectively represent nodes information in fuzzy xml. we then discuss the fuzzy query semantics and compute the membership information by using einstein operator instead of zadeh's min-max technique. on the basis, we propose two efficient algorithms for querying twig under complete and incomplete semantics in fuzzy xml. the experimental results show that our proposed algorithms can perform on the fuzzy twig pattern matching efficiently.
mrm: an adaptive framework for xml searching. in order to deal with the diversified nature of xml documents as well as individual user preferences, we propose a novel multi-ranker model (mrm), which is able to abstract a spectrum of important xml properties and adapt the features to different xml search needs. the model consists of a novel three-level ranking structure and a training module called ranking support vector machine in a voting spy na¨1ve bayes framework (rssf). rssf is effective in learning search preference and then ranks the returned results adaptively. in this demonstration, we present our prototype developed from the model, which we call it the mrm xml search engine. the mrm engine employs only a list of simple xml tagged keywords as a user query for searching xml fragments from a collection of real xml documents. the demonstration presents an indepth analyses of the effectiveness of adaptive rankers, tailored xml rankers and a spectrum of low level ranking features.
query by analogical example: relational search using web search engine indices. we describe methods to search with a query by example in a known domain for information in an unknown domain by exploiting web search engines. relational search is an effective way to obtain information in an unknown field for users. for example, if an apple user searches for microsoft products, similar apple products are important clues for the search. even if the user does not know keywords to search for specific microsoft products, the relational search returns a product name by querying simply an example of apple products. more specifically, given a tuple containing three terms, such as (apple, ipod, microsoft), the term zune can be extracted from the web search results, where apple is to ipod what microsoft is to zune. as a previously proposed relational search requires a huge text corpus to be downloaded from the web, the results are not up-to-date and the corpus has a high construction cost. we introduce methods for relational search by using web search indices. we consider methods based on term co-occurrence, on lexico-syntactic patterns, and on combinations of the two approaches. our experimental results showed that the combination methods got the highest precision, and clarified the characteristics of the methods.
evaluating top-k queries over incomplete data streams. we study the problem of continuous monitoring of top-k queries over multiple non-synchronized streams. assuming a sliding window model, this general problem has been a well addressed research topic in recent years. most approaches, however, assume synchronized streams where all attributes of an object are known simultaneously to the query processing engine. in many streaming scenarios though, different attributes of an item are reported in separate non-synchronized streams which do not allow for exact score calculations. we present how the traditional notion of object dominance changes in this case such that the k dominance set still includes all and only those objects which have a chance of being among the top-k results in their life time. based on this, we propose an exact algorithm which builds on generating multiple instances of the same object in a way that enables efficient object pruning. we show that even with object pruning the necessary storage for exact evaluation of top-k queries is linear in the size of the sliding window. as data should reside in main memory to provide fast answers in an online fashion and cope with high stream rates, storing all this data may not be possible with limited resources. we present an approximate algorithm which leverages correlation statistics of pairs of streams to evict more objects while maintaining accuracy. we evaluate the efficiency of our proposed algorithms with extensive experiments.
a novel distributed p2p simulator architecture: d-p2p-sim. in this paper we introduce a novel distributed simulation environment with gui for p2p simulations (d-p2p-sim). the key aim is to provide the appropriate integrated set of tools in a single software solution to evaluate the performance of various protocols. the basic architecture of the distributed p2p simulator is based on a multi-threading, asynchronous, message passing and distributed environment with graphical user interface to facilitate ease of use by both researchers and programmers.
clustering queries for better document ranking. different queries require different ranking methods. it is however challenging to determine what queries are similar, and how to rank documents for them. in this paper, we propose a new method to cluster queries according to the similarity determined based on urls in their answers. we then train specific ranking models for each query cluster. in addition, a cluster-specific measure of authority is defined to favor documents from authoritative websites on the corresponding topics. the proposed approach is tested using data from a search engine. it turns out that our proposed topic-dependent models can significantly improve the search results of eight most popular categories of queries.
finding good feedback documents. pseudo-relevance feedback finds useful expansion terms from a set of top-ranked documents. it is often crucial to identify those good feedback documents from which useful expansion terms can be added to the query. in this paper, we propose to detect good feedback documents by classifying all feedback documents using a variety of features such as the distribution of query terms in the feedback document, the similarity between a single feedback document and all top-ranked documents, or the proximity between the expansion terms and the original query terms in the feedback document. by doing this, query expansion is only performed using a selected set of feedback documents, which are predicted to be good among all top-ranked documents. experimental results on standard trec test data show that query expansion on the selected feedback documents achieves statistically significant improvements over a strong pseudo-relevance feedback mechanism, which expands the query using all top-ranked documents.
collaborative resource discovery in social tagging systems. social tagging systems which allow users to create, edit and share collections of internet resources associated with tags in a collaborative fashion are growing in popularity in recent years. the rapidly growing amount of shared data in these folksonomies, i.e., taxonomies created by the folk, presents new technical challenges involved with discovering resources which are likely of interest to the user. social tags which reflect the meaning of resources from the user's points of view provide an opportunity to enhance the quality of retrieval. in this paper, we introduce a novel framework to search relevant resources to the user query by incorporating information obtained from folksonomies' underlying data structures consisting of a set of user/tag/resource triplets. in contrast to traditional retrieval and recommendation techniques which represent a collection by a matrix, we represent our data as a third-order tensor on which a novel cube latent semantic indexing (cubelsi) technique is proposed to capture latent semantic associations between tags. with the latent semantic representation we show how to rank relevant resources according to their relevance to user queries. the excellent performance of the method is demonstrated by an experimental evaluation on the deli.cio.us dataset.
fast shortest path distance estimation in large networks. in this paper we study approximate landmark-based methods for point-to-point distance estimation in very large networks. these methods involve selecting a subset of nodes as landmarks and computing offline the distances from each node in the graph to those landmarks. at runtime, when the distance between a pair of nodes is needed, it can be estimated quickly by combining the precomputed distances. we prove that selecting the optimal set of landmarks is an np-hard problem, and thus heuristic solutions need to be employed. we therefore explore theoretical insights to devise a variety of simple methods that scale well in very large networks. the efficiency of the suggested techniques is tested experimentally using five real-world graphs having millions of edges. while theoretical bounds support the claim that random landmarks work well in practice, our extensive experimentation shows that smart landmark selection can yield dramatically more accurate results: for a given target accuracy, our methods require as much as 250 times less space than selecting landmarks at random. in addition, we demonstrate that at a very small accuracy loss our techniques are several orders of magnitude faster than the state-of-the-art exact methods. finally, we study an application of our methods to the task of social search in large graphs.
evaluation of methods for relative comparison of retrieval systems based on clickthroughs. the cranfield evaluation method has some disadvantages, including its high cost in labor and inadequacy for evaluating interactive retrieval techniques. as a very promising alternative, automatic comparison of retrieval systems based on observed clicking behavior of users has recently been studied. several methods have been proposed, but there has so far been no systematic way to assess which strategy is better, making it difficult to choose a good method for real applications. in this paper, we propose a general way to evaluate these relative comparison methods with two measures: utility to users(utu) and effectiveness of differentiation(eod). we evaluate two state of the art methods by systematically simulating different retrieval scenarios. inspired by the weakness of these methods revealed through our evaluation, we further propose a novel method by considering the positions of clicked documents. experiment results show that our new method performs better than the existing methods.
learning to recommend questions based on user ratings. at community question answering services, users are usually encouraged to rate questions by votes. the questions with the most votes are then recommended and ranked on the top when users browse questions by category. as users are not obligated to rate questions, usually only a small proportion of questions eventually gets rating. thus, in this paper, we are concerned with learning to recommend questions from user ratings of a limited size. to overcome the data sparsity, we propose to utilize questions without users rating as well. further, as there exist certain noises within user ratings (the preference of some users expressed in their ratings diverges from that of the majority of users), we design a new algorithm called 'majority-based perceptron algorithm' which can avoid the influence of noisy instances by emphasizing its learning over data instances from the majority users. experimental results from a large collection of real questions confirm the effectiveness of our proposals.
beyond hyperlinks: organizing information footprints in search logs to support effective browsing. while current search engines serve known-item search such as homepage finding very well, they generally cannot support exploratory search effectively. in exploratory search, users do not know their information needs precisely and also often lack the needed knowledge to formulate effective queries, thus querying alone, as supported by the current search engines, is insufficient, and browsing into related information would be very useful. currently, browsing is mostly done by following hyperlinks embedded on web pages. in this paper, we propose to leverage search logs to allow a user to browse beyond hyperlinks with a multi-resolution topic map constructed based on search logs. specifically, we treat search logs as "footprints" left by previous users in the information space and build a multi-resolution topic map to semantically capture and organize them in multiple granularities. such a topic map can support a user to zoom in, zoom out, and navigate horizontally over the information space, and thus provide flexible and effective browsing capabilities for end users. to test the effectiveness of the proposed methods of supporting browsing, we rely on real search logs and a commercial search engine to implement our proposed methods. our experimental results show that the proposed topic map is effective to support browsing beyond hyperlinks.
what happens after an ad click?: quantifying the impact of landing pages in web advertising. unbeknownst to most users, when a query is submitted to a search engine two distinct searches are performed: the organic or algorithmic search that returns relevant web pages and related data (maps, images, etc.), and the sponsored search that returns paid advertisements. while an enormous amount of work has been invested in understanding the user interaction with organic search, surprisingly little research has been dedicated to what happens after an ad is clicked, a situation we aim to correct. to this end, we define and study the process of context transfer, that is, the user's transition from web search to the context of the landing page that follows an ad-click. we conclude that in the vast majority of cases the user is shown one of three types of pages, namely, homepage (the homepage of the advertiser), category browse (a browse-able sub-catalog related to the original query), and search transfer (the search results of the same query re-executed on the target site). we show that these three types of landing pages can be accurately distinguished using automatic text classification. finally, using such an automatic classifier, we correlate the landing page type with conversion data provided by advertisers, and show that the conversion rate (i.e., users' response rate to ads) varies considerably according to the type. we believe our findings will further the understanding of users' response to search advertising in general, and landing pages in particular, and thus help advertisers improve their web sites and help search engines select the most suitable ads.
scalable indexing of rdf graphs for efficient join processing. current approaches to rdf graph indexing suffer from weak data locality, i.e., information regarding a piece of data appears in multiple locations, spanning multiple data structures. weak data locality negatively impacts storage and query processing costs. towards stronger data locality, we propose a three-way triple tree (triplet) secondary memory indexing technique to facilitate flexible and efficient join evaluation on rdf data. the novelty of triplet is that the index is built over the atoms occurring in the data set, rather than at a coarser granularity, such as whole triples occurring in the data set; and, the atoms are indexed regardless of the roles (i.e., subjects, predicates, or objects) they play in the triples of the data set. we show through extensive empirical evaluation that triplet exhibits multiple orders of magnitude improvement over the state-of-the-art, in terms of both storage and query processing costs.
interactive relevance feedback with graded relevance and sentence extraction: simulated user experiments. research on relevance feedback (rfb) in information retrieval (ir) has given mixed results. success in rfb seems to depend on the searcher's willingness to provide feedback and ability to identify relevant documents or query keys. the paper is based on simulating many user scenarios regarding the amount and quality of rfb. in addition, we experiment with query-biased sentence extraction for query reformulation. the baselines are initial no-feedback queries and queries based on pseudo-relevance feedback. the core question is: under which conditions would rfb based on sentence extraction be successful? the answer depends on user's behavior, implementation of feedback query formulation, and the evaluation methods. a small amount of feedback from a short browsing window seems to improve the final ranking the most. longer browsing allows more feedback and better queries but also consumes the available relevant documents.
generating sql/xml query and update statements. the xml support in relational databases and the sql/xml language are still relatively new as compared to purely relational databases and traditional sql. today, most database users have a strong relational and sql background. sql/xml enables users to perform queries and updates across xml and relational data, but many struggle with writing sql/xml statements or xquery update expressions. one reason is the novelty of sql/xml and of the xquery expressions that must be included. another problem is that the tree structure of the xml data may be unknown or difficult to understand for the user. evolving xml schemas as well as hybrid xml/relational schemas make it even harder to write sql/xml statements. also, legacy applications use sql but may require access to xml data without costly code changes. motivated by these challenges, we developed a method to generate sql/xml query and update statements automatically. the input is either a gui or a regular sql statement that uses logical data item names irrespective of their actual location in relational or xml columns in the database. the output is a sql/xml statement that queries or updates relational and xml data as needed to carry out the original user statement. this relieves the user and simplifies schema evolution and integration. we have prototyped and tested the proposed method on top of db2 9.5.
classification-based resource selection. in some retrieval situations, a system must search across multiple collections. this task, referred to as federated search, occurs for example when searching a distributed index or aggregating content for web search. resource selection refers to the subtask of deciding, given a query, which collections to search. most existing resource selection methods rely on evidence found in collection content. we present an approach to resource selection that combines multiple sources of evidence to inform the selection decision. we derive evidence from three different sources: collection documents, the topic of the query, and query click-through data. we combine this evidence by treating resource selection as a multiclass machine learning problem. although machine learned approaches often require large amounts of manually generated training data, we present a method for using automatically generated training data. we make use of and compare against prior resource selection work and evaluate across three experimental testbeds.
tsa'09 workshop summary: topic-sentiment analysis. this workshop seeks to bring together researchers in both computer science and social sciences who are interested in developing and using topic-sentiment analysis methods to measure mass opinion, and to foster communications between the research community and industry practitioners as well.
clustering and exploring search results using timeline constructions. time is an important dimension of any information space and can be very useful in information retrieval and in particular clustering and exploration of search results. search result clustering is a feature integrated in some of today's search engines, allowing users to further explore search results. however, only little work has been done on exploiting temporal information embedded in documents for the presentation, clustering, and exploration of search results along well-defined timelines. in this paper, we present an add-on to traditional information retrieval applications in which we exploit various temporal information associated with documents to present and cluster documents along timelines. temporal information expressed in the form of, e.g., date and time tokens or temporal references, appear in documents as part of the textual context or metadata. using temporal entity extraction techniques, we show how temporal expressions are made explicit and used in the construction of multiple-granularity timelines. we discuss how hit-list based search results can be clustered according to temporal aspects, anchored in the constructed timelines, and how time-based document clusters can be used to explore search results that include temporal snippets. we also outline a prototypical implementation and evaluation that demonstrates the feasibility and functionality of our framework.
what makes categories difficult to classify?: a study on predicting classification performance for categories. in this paper, we try to predict which category will be less accurately classified compared with other categories in a classification task that involves multiple categories. the categories with poor predicted performance will be identified before any classifiers are trained and additional steps can be taken to address the predicted poor accuracies of these categories. inspired by the work on query performance prediction in ad-hoc retrieval, we propose to predict classification performance using two measures, namely, category size and category coherence. our experiments on 20-newsgroup and reuters-21578 datasets show that the spearman rank correlation coefficient between the predicted rank of classification performance and the expected classification accuracy is as high as 0.9.
luposdate: a semantic web database system. managing and querying semantic web are important issues for semantic web applications. therefore, we have developed a semantic web database system with logically and physically optimized sparql engines to manage and query rdf data, named luposdate. in order to present the functionalities of the luposdate system and engines, we have developed an online demonstration, which is available at http://www.ifis.uni-luebeck.de/index.php?id=luposdate-demo.
improvements that don't add up: ad-hoc retrieval results since 1998. the existence and use of standard test collections in information retrieval experimentation allows results to be compared between research groups and over time. such comparisons, however, are rarely made. most researchers only report results from their own experiments, a practice that allows lack of overall improvement to go unnoticed. in this paper, we analyze results achieved on the trec ad-hoc, web, terabyte, and robust collections as reported in sigir (1998--2008) and cikm (2004--2008). dozens of individual published experiments report effectiveness improvements, and often claim statistical significance. however, there is little evidence of improvement in ad-hoc retrieval technology over the past decade. baselines are generally weak, often being below the median original trec system. and in only a handful of experiments is the score of the best trec automatic run exceeded. given this finding, we question the value of achieving even a statistically significant result over a weak baseline. we propose that the community adopt a practice of regular longitudinal comparison to ensure measurable progress, or at least prevent the lack of it from going unnoticed. we describe an online database of retrieval runs that facilitates such a practice.
a framework for semantic link discovery over relational data. discovering links between different data items in a single data source or across different data sources is a challenging problem faced by many information systems today. in particular, the recent linking open data (lod) community project has highlighted the paramount importance of establishing semantic links among web data sources. currently, lod sources provide billions of rdf triples, but only millions of links between data sources. many of these data sources are published using tools that operate over relational data stored in a standard rdbms. in this paper, we present a framework for discovery of semantic links from relational data. our framework is based on declarative specification of linkage requirements by a user. we illustrate the use of our framework using several link discovery algorithms on a real world scenario. our framework allows data publishers to easily find and publish high-quality links to other data sources, and therefore could significantly enhance the value of the data in the next generation of web.
magiccube: choosing the best snippet for each aspect of an entity. wikis are currently used in business to provide knowledge management systems, especially for individual organizations. however, building wikis manually is a laborious and time-consuming work. to assist founding wikis, we propose a methodology in this paper to automatically select the best snippets for entities as their initial explanations. our method consists of two steps. first, we focus on extracting snippets from a given set of web pages for each entity. starting from a seed sentence, a snippet grows up by adding the most relevant neighboring sentences into itself. the sentences are chosen by the snippet growth model, which employs a distance function and an influence function to make decisions. secondly, we pick out the best snippet for each aspect of an entity. the combination of all the selected snippets serves as the primary description of the entity. we present three ever-increasing methods to handle selection process. experimental results based on a real data set show that our proposed method works effectively in producing primary descriptions for entities such as employee names.
location cache for web queries. this paper proposes a strategy to reduce the amount of hardware involved in the solution of search engine queries. it proposes using a secondary compact cache that keeps minimal information stored in the query receptionist machine to register the processors that must get involved in the solution of queries which are evicted from the standard result cache or are not admitted in it. this cache strategy produces exact answers by using very few processors.
linear inclusion for xml regular expression types. type inclusion is a fundamental operation in every type-checking compiler, but it is quite expensive for xml manipulation languages. we recently presented an inclusion checking algorithm for an expressive family of xml type languages which is polynomial, but runs in quadratic time both in the best and in the worst cases. we present here an algorithm that has a linear-time backbone, and resorts to the quadratic approach for some specific parts of the compared types. our experiments show that the new algorithm typically runs in linear time, hence can be used as a building block for a practical type-checking compiler.
answer typing for information retrieval. answer typing is commonly thought of as finding appropriate responses to given questions. we extend the notion of answer typing to information retrieval to ensure results contain plausible answers to queries. identification of a large class of applicable queries is performed using a discriminative classifier, and discriminative preference ranking methods are employed for the selection of type-appropriate terms. experimental results show that type-appropriate terms identified by the model are superior to terms most commonly associated with the query, providing strong evidence that answer typing techniques can find meaningful and appropriate terms. further experiments show that snippets containing correct answers are ranked higher by our model than by the baseline google search engine in those instances in which a query does indeed seek a short answer.
generating comparative summaries of contradictory opinions in text. this paper presents a study of a novel summarization problem called contrastive opinion summarization (cos). given two sets of positively and negatively opinionated sentences which are often the output of an existing opinion summarizer, cos aims to extract comparable sentences from each set of opinions and generate a comparative summary containing a set of contrastive sentence pairs. we formally formulate the problem as an optimization problem and propose two general methods for generating a comparative summary using the framework, both of which rely on measuring the content similarity and contrastive similarity of two sentences. we study several strategies to compute these two similarities. we also create a test data set for evaluating such a novel summarization problem. experiment results on this test set show that the proposed methods are effective for generating comparative summaries of contradictory opinions.
soire: a service-oriented ir evaluation architecture. we have developed a system that offers comprehensive analysis functionality for information retrieval experiments combined with a storage facility for persisting experiment data in a uniform fashion to facilitate repeatability and comparability of experiments. our service-oriented ir evaluation framework - soire offers a number of technological interfaces based on open networking standards and modeling languages to connect to other systems while regarding ease-of-use for researchers as the feature of utmost importance.
a proactive personalised retrieval system. we present a personalised retrieval system that captures explicit relevance feedback to build an evolving user profile with multiple aspects. the user profile is used to proactively retrieve results between search sessions to support multi-session search tasks. this approach to supporting users with their multi-session search tasks is evaluated in a between-subjects multiple time-series study with ten subjects performing two simulated work situation tasks over five sessions. system interaction data shows that subjects using the personalised retrieval system issue fewer queries and interact with fewer results than subjects using a baseline system. the interaction data also shows a trend of subjects interacting with the proactively retrieved results in the personalised retrieval system.
a general markov framework for page importance computation. we propose a general markov framework for computing page importance. under the framework, a markov skeleton process is used to model the random walk conducted by the web surfer on a given graph. page importance is then defined as the product of page reachability and page utility, which can be computed from the transition probability and the mean staying time of the pages in the markov skeleton process respectively. we show that this general framework can cover many existing algorithms as its special cases, and that the framework can help us define new algorithms to handle more complex problems. in particular, we demonstrate the use of the framework with the exploitation of a new process named mirror semi-markov process. the experimental results validate that the mirror semi-markov process model is more effective than previous models in several tasks.
effective xml content and structure retrieval with relevance ranking. xml documents can be retrieved by means of not only content-only (co) queries, but also content-and-structure (cas) queries. though promising better retrieval precision, cas queries introduce several new challenges. to address these challenges, we propose a novel approach for xml cas retrieval. the distinctive feature of the approach is that it adopts a content-oriented point of view. specifically, the approach first decomposes a cas query into several fragments, then retrieves results for each query fragment in a content-centric way, and finally scores each answer node. the approach is adaptive to versatile homogeneous and heterogeneous data environments. to assess the relevance of retrieval results to a query fragment, we present a scoring strategy that measures relevance from both content and structure perspectives. in addition, an effective approach is proposed to infer answer nodes based on the cas query and document structure. an efficient algorithm is also presented for cas retrieval. finally, we demonstrate the effectiveness of the proposed methods through comprehensive experimental studies.
iloc: a framework for incremental location-state acquisition and prediction based on mobile sensors. much research focuses on predicting a person's geo-spatial traversal patterns using a history of recorded geo-coordinates. in this paper, we focus on the problem of predicting location-state transitions. location-states for a user refer to a set of anchoring points/regions in space, and the prediction task produces a sequence of predicted location states for a given query time window. if this problem can be solved accurately and efficiently, it may lead to new location based services (lbs) that can smartly recommend information to a user based on his current and future location states. the proposed iloc (incremental (location-state acquisition and prediction) framework solves the prediction problem by utilizing the sensor information provided by a user's mobile device. it incrementally learns the location states by constantly monitoring the signal environment of the mobile device. further, the framework tightly integrates the learning and prediction modules, allowing iloc to update location-states continuously and predict future location-states at the same time. our extensive experiments show that the quality of the location-states learned by iloc are better than the state-of-the-art. we also show that when other learners failed to produce reasonable predictions, iloc provides good forecasts. as for the efficiency, iloc processes the data in a single pass, which fits well to many data stream processing models.
demonstration of an rfid middleware: lit ale manager. the sharp increase of rfid tags and readers require dedicated middleware solutions that manage readers and process event data. in this paper, we demonstrate a rfid middleware called lit ale manager system with key features and also illustrate overall functional components of the middleware system with implementation techniques.
learning document aboutness from implicit user feedback and document structure. capturing the "aboutness" of documents has been a key research focus throughout the history of automated textual information processing. in this work, we represent aboutness using words and phrases that best reflect the central topics of a document. we present a machine learning approach that learns to score and rank words and phrases in a document according to their relevance to the document. we use implicit user feedback available in search engine click logs to characterize the user-perceived notion of term relevance. using a small set of manually generated training data, we show that the surrogate training data from click logs correlates well with this data, thus eliminating the need to create data for training manually which is both expensive and fundamentally difficult to obtain for such a task. further, we use a diverse set of features in our learning model that capitalize heavily on the structural and visual properties of web documents. in our extensive experimentation, we pay particular attention to tail web pages and show that our approach trained on mainly head web pages generalizes and performs well on all kinds of documents. in several evaluation methods using manually generated summaries and term relevance judgments, our system shows 25% improvement over other aboutness solutions.
efficient feature weighting methods for ranking. feature weighting or selection is a crucial process to identify an important subset of features from a data set. removing irrelevant or redundant features can improve the generalization performance of ranking functions in information retrieval. due to fundamental differences between classification and ranking, feature weighting methods developed for classification cannot be readily applied to feature weighting for ranking. a state of the art feature selection method for ranking, called gas, has been recently proposed, which exploits importance of each feature and similarity between every pair of features. however, gas must compute the similarity scores of all pairs of features, thus it is not scalable for high-dimensional data and its performance degrades on nonlinear ranking functions. this paper proposes novel algorithms, rankwrapper and rankfilter, which is scalable for high-dimensional data and also performs reasonably well on nonlinear ranking functions. rankwrapper and rankfilter are designed based on the key idea of relief algorithm. relief is a feature selection algorithm for classification, which exploits the notions of hits (data points within the same class) and misses (data points from different classes) for classification. however, there is no such notion of hits or misses in ranking. the proposed algorithms instead utilize the ranking distances of nearest data points in order to identify the key features for ranking. our extensive experiments show that rankwrapper and rankfilter generate higher accuracy overall than the gas and traditional relief algorithms adapted for ranking, and run substantially faster than the gas on high dimensional data.
comparative document summarization via discriminative sentence selection. given a collection of document groups, a quick question is what are the differences in these groups. in this paper, we study a novel problem of summarizing the differences between document groups. a discriminative sentence selection method is proposed to extract the most discriminative sentences which represent the specific characteristics of each document group. experiments on real world data sets demonstrate the effectiveness of our proposed method.
a hybrid index structure for geo-textual searches. the efficient execution of multi-criteria queries has gained increasing interest over the last years. in the present paper we propose an r-tree based approach for queries addressing textual as well as geographic filter conditions. whereas most previous approaches use an index structure optimised for a single criterion adding special treatment for the other criterion at the leaf nodes or end points of this index structure, our approach uses a deeper integration. in short, r-trees are maintained for certain subsets of the whole term set. furthermore, in each of these r-trees bit sets are used within the nodes to indicate whether entries for the terms associated with the single bits can be found in the corresponding sub-tree. our index structure aims to be both, time and space efficient. the paper investigates the efficiency and applicability of the proposed index structure via practical experiments based on real-world and synthetic data.
learning to rank from bayesian decision inference. ranking is a key problem in many information retrieval (ir) applications, such as document retrieval and collaborative filtering. in this paper, we address the issue of learning to rank in document retrieval. learning-based methods, such as ranknet, ranksvm, and rankboost, try to create ranking functions automatically by using some training data. recently, several learning to rank methods have been proposed to directly optimize the performance of ir applications in terms of various evaluation measures. they undoubtedly provide statistically significant improvements over conventional methods; however, from the viewpoint of decision-making, most of them do not minimize the bayes risk of the ir system. in an attempt to fill this research gap, we propose a novel framework that directly optimizes the bayes risk related to the ranking accuracy in terms of the ir evaluation measures. the results of experiments on the letor collections demonstrate that the framework outperforms several existing methods in most cases.
discovering matching dependencies. matching dependencies (mds) are recently proposed for various data quality applications such as detecting the violation of integrity constraints and duplicate object identification. in this paper, we study the problem of discovering matching dependencies for a given database instance. first, we formally define the measures, support and confidence, for evaluating the utility of mds in the given database instance. then, we study the discovery of mds with certain utility requirements of support and confidence. exact algorithms are developed, together with pruning strategies to improve the time performance. finally, our experimental evaluation demonstrates the efficiency of the proposed methods.
towards a universal wordnet by learning from combined evidence. lexical databases are invaluable sources of knowledge about words and their meanings, with numerous applications in areas like nlp, ir, and ai. we propose a methodology for the automatic construction of a large-scale multilingual lexical database where words of many languages are hierarchically organized in terms of their meanings and their semantic relations to other words. this resource is bootstrapped from wordnet, a well-known english-language resource. our approach extends wordnet with around 1.5 million meaning links for 800,000 words in over 200 languages, drawing on evidence extracted from a variety of resources including existing (monolingual) wordnets, (mostly bilingual) translation dictionaries, and parallel corpora. graph-based scoring functions and statistical learning techniques are used to iteratively integrate this information and build an output graph. experiments show that this wordnet has a high level of precision and coverage, and that it can be useful in applied tasks such as cross-lingual text classification.
the effect of negation on sentiment analysis and retrieval effectiveness. we investigate the problem of determining the polarity of sentiments when one or more occurrences of a negation term such as "not" appear in a sentence. the concept of the scope of a negation term is introduced. by using a parse tree and typed dependencies generated by a parser and special rules proposed by us, we provide a procedure to identify the scope of each negation term. experimental results show that the identification of the scope of negation improves both the accuracy of sentiment analysis and the retrieval effectiveness of opinion retrieval.
a risk minimization framework for domain adaptation. supervised learning algorithms usually require high quality labeled training set of large volume. it is often expensive to obtain such labeled examples in every domain of an application. domain adaptation aims to help in such cases by utilizing data available in related domains. however transferring knowledge from one domain to another is often non trivial due to different data distributions among the domains. moreover, it is usually very hard to measure and formulate these distribution differences. hence we introduce a new concept of label-relation function to transfer knowledge among different domains without explicitly formulating the data distribution differences. a novel learning framework, domain transfer risk minimization (dtrm), is proposed based on this concept. dtrm simultaneously minimizes the empirical risk for the target and the regularized empirical risk for source domain. under this framework, we further derive a generic algorithm called domain adaptation by label relation (dalr) that is applicable to various applications in both classification and regression settings. dalr iteratively updates the target hypothesis function and outputs for the source domain until it converges. we provide an in-depth theoretical analysis of dtrm and establish fundamental error bounds. we also experimentally evaluate dalr on the task of ranking search results using real-world data. our experimental results show that the proposed algorithm effectively and robustly utilizes data from source domains under various conditions: different sizes for source domain data; different noise levels for source domain data, and different difficulty levels for target domain data.
confucius and "its" intelligent disciples. confucius is a great teacher in ancient china. his theories and principles were effectively spread throughout china by his disciples. confucius is the product code name of google knowledge search product, which is built at google beijing lab by my team. in this talk, i present knowledge search key disciples, which are machine learning subroutines that generates labels for questions, that matches existing answers to a question, that evaluates quality of answers, that ranks users based on their contributions, that distills high-quality answers for search engines to index, etc. i will also present the scalable machine learning services that we built to make these disciples effective and efficient. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
the impact of document structure on keyphrase extraction. keyphrases are short phrases that reflect the main topic of a document. because manually annotating documents with keyphrases is a time-consuming process, several automatic approaches have been developed. typically, candidate phrases are extracted using features such as position or frequency in the document text. document structure may contain useful information about which parts or phrases of a document are important, but has rarely been considered as a source of information for keyphrase extraction. we address this issue in the context of keyphrase extraction from scientific literature. we introduce a new, large corpus that consists of full-text journal articles, where the rich collection and document structure available at the publishing stage is explicitly annotated. we explore features based on the xml tags contained in the documents, and based on generic section types derived using position and cue words in section titles. for xml tags we find sections, abstract, and title to perform best, but many smaller elements may be beneficial in combination with other features. of the generic section types, the discussion section is found to be most useful for keyphrase extraction.
smoothing document language model with local word graph. smoothing document model with word graph is a new and effective method in information retrieval. word graph can naturally incorporate the dependency between the words; random walk algorithm based on the graph can be used to estimate the weight of each vertex. in this paper, we present a new way to construct a local word graph for smoothing document model, which exploits the document's k nearest neighbors: the vertices represent the words in the document and its k nearest neighbors, and the weights of the edges are estimated through word co-occurrence in the local document set. we argue that word graph is a key factor to the performance in graph-based smoothing method. by using the local document set, we can obtain a document specific word graph, and achieve better retrieval performance. experimental results on three trec collections show that our proposed approach is effective.
space-economical partial gram indices for exact substring matching. exact substring matching queries on large data collections can be answered using q-gram indices, that store for each occurring q-byte pattern an (ordered) posting list with the positions of all occurrences. such gram indices are known to provide fast query response time and to allow the index to be created quickly even on huge disk-based datasets. their main drawback is relatively large storage space, that is a constant multiple (typically >2) of the original data size, even when compression is used. in this work, we study methods to conserve the scalable creation time and efficient exact substring query properties of gram indices, while reducing storage space. to this end, we first propose a partial gram index based on a reduction from the problem of omitting indexed q-grams to the set cover problem. while this method is successful in reducing the size of the index, it generates false positives at query time, reducing efficiency. we then increase the accuracy of partial grams by splitting posting lists of frequent grams in a frequency-tuned set of signatures that take the bytes surrounding the grams into account. the resulting qs-gram scheme is tested on huge collections (up to 426gb) and is shown to achieve an almost 1:1 data:index size, and query performance even faster than normal gram methods, thanks to the reduced size and access cost.
data extraction from the web using wild card queries. this paper presents an overview of our work for searching and retrieving facts and relationships within natural language text sources. in this work, an extraction task over a text collection is expressed as a query that combines text fragments with wild cards, and the query result is a set of facts in the form of unary, binary and general n-ary tuples. despite being both simple and declarative, the framework can be applied to a wide range of extraction tasks. this paper presents an overview of the work and its various components. we also report some of our experiments and an evaluation of the proposed querying framework in extracting relevant information to a task.
learning from past queries for resource selection. federated text search provides a unified search interface for multiple search engines of distributed text information sources. resource selection is an important component for federated text search, which selects a small number of information sources that contain the largest number of relevant documents for a user query. most prior research of resource selection focused on selecting information sources by analyzing static information of available information sources that is sampled in the offline manner. on the other hand, most prior research ignored a large amount of valuable information like the results from past queries. this paper proposes a new resource selection technique (which is called qsim) that utilizes the search results of past queries for estimating the utilities of available information sources for a specific user query. experiment results demonstrate the effectiveness of the new resource selection algorithm.
density-based clustering using graphics processors. during the last few years, gpus have evolved from simple devices for the display signal preparation into powerful coprocessors that do not only support typical computer graphics tasks but can also be used for general numeric and symbolic computation tasks. as major advantage gpus provide extremely high parallelism combined with a high bandwidth in memory transfer at low cost. we want to exploit these dvantages in density-based clustering, an important paradigm in clustering since typical algorithms of this category are noise and outlier robust and search for clusters of an arbitrary shape in metric and vector spaces. moreover, with a time complexity ranging from o(n log n) to o(n2) these algorithms are scalable to large data sets in a database system. in this paper, we propose cuda-dclust, a massively parallel algorithm for density-based clustering for the use of a graphics processing unit (gpu). while the result of this algorithm is guaranteed to be equivalent to that of dbscan, we demonstrate a high speed-up, particularly in combination with a novel index structure for use in gpus.
graph classification based on pattern co-occurrence. subgraph patterns are widely used in graph classification, but their effectiveness is often hampered by large number of patterns or lack of discrimination power among individual patterns. we introduce a novel classification method based on pattern co-occurrence to derive graph classification rules. our method employs a pattern exploration order such that the complementary discriminative patterns are examined first. patterns are grouped into co-occurrence rules during the pattern exploration, leading to an integrated process of pattern mining and classifier learning. by taking advantage of co-occurrence information, our method can generate strong features by assembling weak features. unlike previous methods that invoke the pattern mining process repeatedly, our method only performs pattern mining once. in addition, our method produces a more interpretable classifier and shows better or competitive classification effectiveness in terms of accuracy and execution time.
an improved feedback approach using relevant local posts for blog feed retrieval. blog feed search aims to identify a blog feed with a recurring interest in a given topic. in this paper, we investigate the "pseudo-relevance feedback" for blog feed search task, where its unit of relevance judgment is not based on a blog post but a blog feed (the collection of all its constituent posts). this paper focuses on two characteristics of feed search task, blog feed's topical diversity and multifaceted property of query. we propose a novel feed-level selection of local posts which uses only highly relevant local posts in each top-ranked feed, in order to capture the correct and diverse relevant information to a given topic. experimental results show that the proposed approach outperforms traditional feedback approaches. especially, the proposed approach gives 2% further increase of ndcg over the best performing result of trec '08 blog distillation task.
user interests in social media sites: an exploration with micro-blogs. recent technological advances in mobile-based access to social networking platforms and facilities to update information in real{time (e.g. in facebook) have allowed an individual's online presence to be as ephemeral and dynamic in nature, as her very thoughts and interests. in this context, micro-blogging has been widely adopted by users as an effective means to capture and disseminate their thoughts and actions to a larger audience on a daily basis. interestingly, daily chatters of a user obtained from her micro-blogs offer a unique information source to analyze and interpret her context in real-time - i.e. interests, intentions,and activities. in this paper, we gather data from the public timeline of twitter spanning across ten worldwide cities over a period of four weeks. we use this dataset to (a) explore how users express interests in real-time through micro-blogs, and (b) understand how text mining techniques can be applied to interpret real-time context of a user based on her tweets. initial findings reported herein suggest that social media sites like twitter constitute a promising source for extracting user context that can be exploited by novel social networking applications.
improving search engines using human computation games. work on evaluating and improving the relevance of web search engines typically use human relevance judgments or clickthrough data. both these methods look at the problem of learning the mapping from queries to web pages. in this paper, we identify some issues with this approach, and suggest an alternative approach, namely, learning a mapping from web pages to queries. in particular, we use human computation games to elicit data about web pages from players that can be used to improve search. we describe three human computation games that we developed, with a focus on page hunt, a single-player game. we describe experiments we conducted with several hundred game players, highlight some interesting aspects of the data obtained and define the 'findability' metric. we also show how we automatically extract query alterations for use in query refinement using techniques from bitext matching. the data that we elicit from players has several other applications including providing metadata for pages and identifying ranking issues.
a query language for analyzing networks. with more and more large networks becoming available, mining and querying such networks are increasingly important tasks which are not being supported by database models and querying languages. this paper wants to alleviate this situation by proposing a data model and a query language for facilitating the analysis of networks. key features include support for executing external tools on the networks, flexible contexts on the network each resulting in a different graph, primitives for querying subgraphs (including paths) and transforming graphs. the data model provides for a closure property, in which the output of every query can be stored in the database and used for further querying.
semi-nonnegative matrix factorization with global statistical consistency for collaborative filtering. collaborative filtering, considered by many researchers as the most important technique for information filtering, has been extensively studied by both academic and industrial communities. one of the most popular approaches to collaborative filtering recommendation algorithms is based on low-dimensional factor models. the assumption behind such models is that a user's preferences can be modeled by linearly combining item factor vectors using user-specific coefficients. in this paper, aiming at several aspects ignored by previous work, we propose a semi-nonnegative matrix factorization method with global statistical consistency. the major contribution of our work is twofold: (1) we endow a new understanding on the generation or latent compositions of the user-item rating matrix. under the new interpretation, our work can be formulated as the semi-nonnegative matrix factorization problem. (2) moreover, we propose a novel method of imposing the consistency between the statistics given by the predicted values and the statistics given by the data. we further develop an optimization algorithm to determine the model complexity automatically. the complexity of our method is linear with the number of the observed ratings, hence it is scalable to very large datasets. finally, comparing with other state-of-the-art methods, the experimental analysis on the eachmovie dataset illustrates the effectiveness of our approach.
named entity disambiguation by leveraging wikipedia semantic knowledge. name ambiguity problem has raised an urgent demand for efficient, high-quality named entity disambiguation methods. the key problem of named entity disambiguation is to measure the similarity between occurrences of names. the traditional methods measure the similarity using the bag of words (bow) model. the bow, however, ignores all the semantic relations such as social relatedness between named entities, associative relatedness between concepts, polysemy and synonymy between key terms. so the bow cannot reflect the actual similarity. some research has investigated social networks as background knowledge for disambiguation. social networks, however, can only capture the social relatedness between named entities, and often suffer the limited coverage problem. to overcome the previous methods' deficiencies, this paper proposes to use wikipedia as the background knowledge for disambiguation, which surpasses other knowledge bases by the coverage of concepts, rich semantic information and up-to-date content. by leveraging wikipedia's semantic knowledge like social relatedness between named entities and associative relatedness between concepts, we can measure the similarity between occurrences of names more accurately. in particular, we construct a large-scale semantic network from wikipedia, in order that the semantic knowledge can be used efficiently and effectively. based on the constructed semantic network, a novel similarity measure is proposed to leverage wikipedia semantic knowledge for disambiguation. the proposed method has been tested on the standard weps data sets. empirical results show that the disambiguation performance of our method gets 10.7% improvement over the traditional bow based methods and 16.7% improvement over the traditional social network based methods.
caofes: an ontological framework for web service retrieval. semantic web search involves retrieval of user-specific web artifacts by utilizing their semantic descriptions. a very specific web artifact that has evolved in recent times is web services. web services can be semantically described in languages like owl-s. however, such languages are limited with respect to their expressivity of context. they also lack a formal ontological framework where efficient web service retrieval can be conducted. in this paper we model a service request scenario within the web as an event-driven system. services as well as user requests are modeled as events. we propose an ontological framework called context-aware ontology framework for events and services (caofes) where such event-driven web service retrieval can be efficiently executed by a novel reasoning technique.
product feature categorization with multilevel latent semantic association. in recent years, the number of freely available online reviews is increasing at a high speed. aspect-based opinion mining technique has been employed to find out reviewers' opinions toward different product aspects. such finer-grained opinion mining is valuable for the potential customers to make their purchase decisions. product-feature extraction and categorization is very important for better mining aspect-oriented opinions. since people usually use different words to describe the same aspect in the reviews, product-feature extraction and categorization becomes more challenging. manually product-feature extraction and categorization is tedious and time consuming, and practically infeasible for the massive amount of products. in this paper, we propose an unsupervised product-feature categorization method with multilevel latent semantic association. after extracting product-features from the semi-structured reviews, we construct the first latent semantic association (lasa) model to group words into a set of concepts according to their virtual context documents. it generates the latent semantic structure for each product-feature. the second lasa model is constructed to categorize the product-features according to their latent semantic structures and context snippets in the reviews. experimental results demonstrate that our method achieves better performance compared with the existing approaches. moreover, the proposed method is language- and domain-independent.
a general magnitude-preserving boosting algorithm for search ranking. traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like rankboost. however, such a pairwise approach ignores the information about the magnitude of preference in the learning process. in this paper, we present the directed distance function (ddf) as a substitute for binary labels in pairwise approach to preserve the magnitude of preference and propose a new boosting algorithm called mpboost, which applies gentleboost optimization and directly incorporates ddf into the exponential loss function. we give the boundedness property of mpboost through theoretic analysis. experimental results demonstrate that mpboost not only leads to better ndcg accuracy as compared to state-of-the-art ranking solutions in both public and commercial datasets, but also has good properties of avoiding the overfitting problem in the task of learning ranking functions.
constrained multi-aspect expertise matching for committee review assignment. automatic review assignment can significantly improve the productivity of many people such as conference organizers, journal editors and grant administrators. most previous works have set the problem up as using a paper as a query to independently "retrieve" a set of reviewers that should review the paper. a more appropriate formulation of the problem would be to simultaneously optimize the assignments of all the papers to an entire committee of reviewers under constraints such as the review quota. in this paper, we solve the problem of committee review assignment with multi-aspect expertise matching by casting it as an integer linear programming problem. the proposed algorithm can naturally accommodate any probabilistic or deterministic method for modeling multiple aspects to automate committee review assignments. evaluation using an existing data set shows that the proposed algorithm is effective for committee review assignments based on multi-aspect expertise matching.
detecting topic evolution in scientific literature: how can citations help? understanding how topics in scientific literature evolve is an interesting and important problem. previous work simply models each paper as a bag of words and also considers the impact of authors. however, the impact of one document on another as captured by citations, one important inherent element in scientific literature, has not been considered. in this paper, we address the problem of understanding topic evolution by leveraging citations, and develop citation-aware approaches. we propose an iterative topic evolution learning framework by adapting the latent dirichlet allocation model to the citation network and develop a novel inheritance topic model. we evaluate the effectiveness and efficiency of our approaches and compare with the state of the art approaches on a large collection of more than 650,000 research papers in the last 16 years and the citation network enabled by citeseerx. the results clearly show that citations can help to understand topic evolution better.
utilizing inter-passage and inter-document similarities for re-ranking search results. we present a novel language-model-based approach to re-ranking an initially retrieved list so as to improve precision at top ranks. our model integrates whole-document information with that induced from passages. specifically, inter-passage, inter-document, and query-based similarities are integrated in our model. empirical evaluation demonstrates the effectiveness of our approach.
robust record linkage blocking using suffix arrays. record linkage is an important data integration task that has many practical uses for matching, merging and duplicate removal in large and diverse databases. however, a quadratic scalability for the brute force approach necessitates the design of appropriate indexing or blocking techniques. we design and evaluate an efficient and highly scalable blocking approach based on suffix arrays. our suffix grouping technique exploits the ordering used by the index to merge similar blocks at marginal extra cost, resulting in a much higher accuracy while retaining the high scalability of the base suffix array method. efficiently grouping similar suffixes is carried out with the use of a sliding window technique. we carry out an in-depth analysis of our method and show results from experiments using real and synthetic data, which highlights the importance of using efficient indexing and blocking in real world applications where data sets contain millions of records.
adaptive relevance feedback in information retrieval. relevance feedback has proven very effective for improving retrieval accuracy. a difficult yet important problem in all relevance feedback methods is how to optimally balance the original query and feedback information. in the current feedback methods, the balance parameter is usually set to a fixed value across all the queries and collections. however, due to the difference in queries and feedback documents, this balance parameter should be optimized for each query and each set of feedback documents. in this paper, we present a learning approach to adaptively predict the optimal balance coefficient for each query and each collection. we propose three heuristics to characterize the balance between query and feedback information. taking these three heuristics as a road map, we explore a number of features and combine them using a regression approach to predict the balance coefficient. our experiments show that the proposed adaptive relevance feedback is more robust and effective than the regular fixed-coefficient feedback.
topic analysis for topic-focused multi-document summarization. topic-focused multi-document summarization has been a challenging task because the created summary is required to be biased to the given topic or query. existing methods consider the given topic as a single coarse unit and then directly incorporate the relevance between each sentence and the single topic into the sentence evaluation process. however, the given topic is usually not well-defined and it consists of a few explicit or implicit subtopics. in this study, the related subtopics are discovered from the topic's narrative text or document set through topic analysis techniques. then, the sentence relationships against each subtopic are considered as an individual modality and the multi-modality manifold-ranking method is proposed to evaluate and rank sentences by fusing the multiple modalities. experimental results on the duc benchmark datasets show the promising results of our proposed methods.
feature selection for ranking using boosted trees. modern search engines have to be fast to satisfy users, so there are hard back-end latency requirements. the set of features useful for search ranking functions, though, continues to grow, making feature computation a latency bottleneck. as a result, not all available features can be used for ranking, and in fact, much of the time, only a small percentage of these features can be used. thus, it is crucial to have a feature selection mechanism that can find a subset of features that both meets latency requirements and achieves high relevance. to this end, we explore different feature selection methods using boosted regression trees, including both greedy approaches (selecting the features with highest relative importance as computed by boosted trees; discounting importance by feature similarity and a randomized approach. we evaluate and compare these approaches using data from a commercial search engine. the experimental results show that the proposed randomized feature selection with feature-importance-based backward elimination outperforms greedy approaches and achieves a comparable relevance with 30 features to a full-feature model trained with 419 features and the same modeling parameters.
the influence of the document ranking in expert search. the retrieval effectiveness of the underlying document search component of an expert search engine can have an important impact on the effectiveness of the generated expert search results. in this large-scale study, we perform novel experiments in the context of the document search and expert search tasks of the trec enterprise track, to measure the influence that the performance of the document ranking has on the ranking of candidate experts. in particular, we show, using real and simulated document rankings, that while the expert search system performance is related to the relevance of the retrieved documents, surprisingly, it is not always the case that increasing document search effectiveness causes an increase in expert search performance.
incident threading for news passages. with an overwhelming volume of news reports currently available, there is an increasing need for automatic techniques to analyze and present news to a general reader in a meaningful and efficient manner. we explore incident threading as a possible solution to this problem. all text that describes the occurrence of a real-world happening is merged into a news incident, and incidents are organized in a network with dependencies of predefined types. earlier attempts at this problem have assumed that a news story covers a single topic. we move beyond that limitation to introduce passage threading, which processes news at the passage level. first we develop a new testbed for this research and extend the evaluation methods to address new granularity issues. then a three-stage algorithm is described that identifies on-subject passages, groups them into incidents, and establishes links between related incidents. finally, we observe significant improvement over earlier work when we optimize the harmonic mean of the appropriate evaluation measures. the resulting performance exceeds the level that a calibration study shows is necessary to support a reading comprehension task.
time sequence summarization to scale up chronology-dependent applications. in this paper, we present the concept of time sequence summarization to support chronology-dependent applications on massive data sources. time sequence summarization takes as input a time sequence of events that are chronologically ordered. each event is described by a set of descriptors. time sequence summarization produces a concise time sequence that can be substituted for the original time sequence in chronology-dependent applications. we propose an algorithm that achieves time sequence summarization based on a generalization, grouping and concept formation process. generalization expresses event descriptors at higher levels of abstraction using taxonomies while grouping gathers similar events. concept formation is responsible for reducing the size of the input time sequence of events by representing each group created by one concept. the process is performed in a way such that the overall chronology of events is preserved. the algorithm computes the summary incrementally and has reduced algorithmic complexity. the resulting output is a concise representation, yet, informative enough to directly support chronology-dependent applications. we validate our approach by summarizing one year of financial news provided by reuters.
building domain-oriented sentiment lexicon by improved information bottleneck. this paper describes an adapted information bottleneck approach for construction of domain-oriented sentiment lexicon. the basic idea is to use three kinds of relationships (wwinter, wdinter and wdintra,) to infer the semantic orientation of the out-of-domain words. the experimental results demonstrate that proposed method could dramatically improve the accuracy of the baseline approach on the construction of out-of-domain sentiment lexicon.
extraction of a latent blog community based on subject. in the blogosphere, there exist posts relevant to a particular subject and blogs that show interests in the subject. in this paper, we define a set of such posts and blogs as "blog community" and propose a method for extracting the blog community associated with a particular subject. the proposed method is based on the idea that the blogs who have performed actions to the posts of a particular subject are the ones that have interests in the subject, and that the posts which have received actions from such blogs are the ones that contain the subject. the proposed method selects a small number of seed posts that contain the subject. then, it selects the blogs that perform actions to the seed posts over some threshold and the posts that have received actions over some threshold. by repeating these two steps, it gradually expands the blog community. the experimental results show that the proposed method exhibits a higher level of accuracy than the methods proposed in prior research.
completing wikipedia's hyperlink structure through dimensionality reduction. wikipedia is the largest monolithic repository of human knowledge. in addition to its sheer size, it represents a new encyclopedic paradigm by interconnecting articles through hyperlinks. however, since these links are created by human authors, links one would expect to see are often missing. the goal of this work is to detect such gaps automatically. in this paper, we propose a novel method for augmenting the structure of hyperlinked document collections such as wikipedia. it does not require the extraction of any manually defined features from the article to be augmented. instead, it is based on principal component analysis, a well-founded mathematical generalization technique, and predicts new links purely based on the statistical structure of the graph formed by the existing links. our method does not rely on the textual content of articles; we are exploiting only hyperlinks. a user evaluation of our technique shows that it improves the quality of top link suggestions over the state of the art and that the best predicted links are significantly more valuable than the 'average' link already present in wikipedia. beyond link prediction, our algorithm can potentially be used to point out topics an article misses to cover and to cluster articles semantically.
multidimensional routing indices for efficient distributed query processing. traditional routing indices in peer-to-peer (p2p) networks are mainly designed for document retrieval applications and maintain aggregated one-dimensional values representing the number of documents that can be obtained in a certain direction in the network. in this paper, we introduce the concept of multidimensional routing indices (mris), which are suitable for handling multidimensional data represented by minimum bounding regions (mbrs). depending on data distribution on peers, the aggregation of the mbrs may lead to mris that exhibit extremely poor performance, which renders them ineffective. thus, focusing on a hybrid unstructured p2p network, we analyze the parameters for building mris of high selectivity. we present techniques that boost the query routing performance by detecting similar peers and grouping and reassigning these peers to other parts of the hybrid network in a distributed and scalable way. we demonstrate the advantages of our approach using large-scale simulations.
multidimensional political spectrum identification and analysis. in this work, we show the importance of multidimensional opinion representation in the political context combining domain knowledge and results from principal component analysis. we discuss the differences of feature selection between political spectrum analysis and normal opinion mining tasks. we build regression models on each opinion dimension for scoring and placing new opinion entities, e.g. personal blogs or politicians, onto the political opinion spectrum. we apply our methods on the floor statement records of the united states senate and evaluate it against the uni-dimensional representation of political opinion space. the experimental results show the effectiveness of the proposed model in explaining the voting records of the senate.
using negative voting to diversify answers in non-factoid question answering. we propose a ranking model to diversify answers of non-factoid questions based on an inverse notion of graph connectivity. by representing a collection of candidate answers as a graph, we posit that novelty, a measure of diversity, is inversely proportional to answer vertices' connectivity. hence, unlike the typical graph ranking models, which score vertices based on the degree of connectedness, our method assigns a penalty score for a candidate answer if it is strongly connected to other answers. that is, any redundant answers, indicated by a higher inter-sentence similarity, will be ranked lower than those with lower inter-sentence similarity. at the end of the ranking iterations, many redundant answers will be moved toward the bottom on the ranked list. the experimental results show that our method helps diversify answer coverage of non-factoid questions according to f-scores from nugget pyramid evaluation.
efficient itemset generator discovery over a stream sliding window. mining generator patterns has raised great research interest in recent years. the main purpose of mining itemset generators is that they can form equivalence classes together with closed itemsets, and can be used to generate simple classification rules according to the mdl principle. in this paper, we devise an efficient algorithm called streamgen to mine frequent itemset generators over a stream sliding window. we adopt a novel enumeration tree structure to help keep the information of mined generators and the border between generators and non-generators, and propose some optimization techniques to speed up the mining process. we further extend the algorithm to directly mine a set of high quality classification rules over stream sliding windows while keeping high performance. the extensive performance study shows that our algorithm outperforms other state-of-the-art algorithms which perform similar tasks in terms of both runtime and memory usage efficiency, and has high utility in terms of classification.
asic: algebra-based structural index comparison. structural indices play a significant role in improving the efficiency of xml query evaluation. being able to compare various structural indexing techniques is critical for a dbms to select which indices to support, for the query optimizer to choose an index to use in query evaluation, and for dbas to configure a database application. we present asic, an algebra-based structural index comparison framework that aids users in understanding the ability of different types of structural indices in answering xpath queries which have been characterized using the xpath algebra. asic allows users to select, configure and construct structural indices for comparison, guides users to compare the selected indices by evaluating queries of a particular xpath sub-algebra, and visually displays the index structures, query evaluation plans, and performance results for analysis and comparison.
blogger-centric contextual advertising. this paper addresses the concept of blogger-centric contextual advertising, which refers to the assignment of personal ads to any blog page, chosen in according to bloggers' interests. as blogs become a platform for expressing personal opinions, they naturally contain various kinds of statements, including facts, comments and statements about personal interests, of both a positive and negative nature. to extend the concept behind the long tail theory in contextual advertising, we argue that web bloggers, as the constant visitors of their own blog sites, could be potential consumers who will respond to ads on their own blogs. hence, in this paper, we propose using text mining techniques to discover bloggers' immediate personal interests in order to improve online contextual advertising. the proposed bcca (blogger-centric contextual advertising) framework aims to combine contextual advertising matching with text mining in order to select ads that are related to personal interests as revealed in a blog and rank them according to their relevance. we validate our approach experimentally using a set of data that includes both real ads and actual blog pages. the results indicate that our proposed method could effectively identify those ads that are positively-correlated with a blogger's personal interests.
retrieval experiments using pseudo-desktop collections. desktop search is an important part of personal information management (pim). however, research in this area has been limited by the lack of shareable test collections, making cumulative progress difficult. in this paper, we define desktop search as a semi-structured document retrieval problem and introduce a methodology to automatically build a reusable collection (the pseudo-desktop) that has many of the same properties as a real desktop collection. we then present a comprehensive evaluation of retrieval methods for semi-structured document retrieval on several pseudo-desktop collections and the trec enterprise collection. our results show that a probabilistic retrieval model using the mapping relation between a query term and a document field (prm-s) has the best performance in collections with more structure, such as email, and that the query-likelihood language model is better for other document types. we further analyze the observed differences using generated queries and suggest ways to improve prm-s, which makes the performance gains more significant and consistent.
injecting purpose and trust into data anonymisation. most existing works of data anonymisation target at the optimization of the anonymisation metrics to balance the data utility and privacy, whereas they ignore the effects of a requester's trust level and application purposes during the data anonymisation. our aim of this paper is to propose a much finer level anonymisation scheme with regard to the data requester's trust value and specific application purpose. we prioritize the attributes for anonymisation based on how important and critical they are related to the specified application purposes and propose a trust evaluation strategy to quantify the data requester's reliability, and further build the projection between the trust value and the degree of data anonymiztion, which intends to determine to what extent the data should be anonymized. the decomposition algorithm is developed to find the desired anonymous solution, which guarantees the uniqueness and correctness.
a graphical browser for xml schema documents. recently, tools for browsing xml schema documents have become popular, but they cannot support advanced browsing functionalities. we have implemented a new graphical schema browser which provides traversals not only along a composition hierarchy but also along a type hierarchy defined in the documents. in this demonstration, we show how users can quickly and easily understand the semantic structures by freely navigating to any datatypes or elements located at any position in the hierarchies.
efficient record-level wrapper induction. web information is often presented in the form of record, e.g., a product record on a shopping website or a personal profile on a social utility website. given a host webpage and related information needs, how to identify relevant records as well as their internal semantic structures is critical to many online information systems. wrapper induction is one of the most effective methods for such tasks. however, most traditional wrapper techniques have issues dealing with web records since they are designed to extract information from a page, not a record. we propose a record-level wrapper system. in our system, we use a novel ``broom'' structure to represent both records and generated wrappers. with such representation, our system is able to effectively extract records and identify their internal semantics at the same time. we test our system on 16 real-life websites from four different domains. experimental results demonstrate 99\% extraction accuracy in terms of f1-value.
olap with udfs in digital libraries. queries on digital libraries generally involve the retrieval of specific documents, but most techniques lack the ability to efficiently explore these collections. the integration of olap techniques with digital libraries allows users to navigate throughout these collections on multiple levels. in order to accomplish this, we propose the creation of olap networks, a complex data structure that contains summarized representations of the original collection of metadata to enrich traditional retrievals and allow the users to quickly explore the collection. we developed a system that enables olap-based exploration on the metadata of digital libraries through the use of a combination of efficient udfs and optimized sql queries. in addition, we also incorporated visualization methods into our system to allow fast navigation and exploration.
low-cost management of inverted files for online full-text search. in dynamic environments with frequent content updates, we require online full-text search that scales to large data collections and achieves low search latency. several recent methods that support fast incremental indexing of documents typically keep on disk multiple partial index structures that they continuously update as new documents are added. however, spreading indexing information across multiple locations on disk tends to considerably decrease the search responsiveness of the system. in the present paper, we take a fresh look at the problem of online full-text search with consideration of the architectural features of modern systems. selective range flush is a greedy method that we introduce to manage the index in the system by using fixed-size blocks to organize the data on disk and dynamically keep low the cost of data transfer between memory and disk. as we experimentally demonstrate with the proteus prototype implementation that we developed, we retrieve indexing information at latency that matches the lowest achieved by existing methods. additionally, we reduce the total building cost by 30% in comparison to methods with similar retrieval time.
generating synopses for document-element search. scientists often search for document-elements like tables, figures, or algorithm pseudo-codes. domain scientists and researchers report important data, results and algorithms using these document-elements; readers want to compare the reported results with their findings. some document-element search engines have been proposed (especially to search for tables and figures) to make this task easier. while searching for document-elements today, the end-user is presented with the caption of the document-element and a sentence in the document text that refers to the document-element. oftentimes, the caption and the reference text do not contain enough information to interpret the document-element. in this paper, we present the first set of methods to extract this useful information (synopsis) related to document-elements automatically. we also investigate the problem of choosing the optimum synopsis-size that strikes a balance between information content and size of the generated synopses.
reducing the risk of query expansion via robust constrained optimization. we introduce a new theoretical derivation, evaluation methods, and extensive empirical analysis for an automatic query expansion framework in which model estimation is cast as a robust constrained optimization problem. this framework provides a powerful method for modeling and solving complex expansion problems, by allowing multiple sources of domain knowledge or evidence to be encoded as simultaneous optimization constraints. our robust optimization approach provides a clean theoretical way to model not only expansion benefit, but also expansion risk, by optimizing over uncertainty sets for the data. in addition, we introduce risk-reward curves to visualize expansion algorithm performance and analyze parameter sensitivity. we show that a robust approach significantly reduces the number and magnitude of expansion failures for a strong baseline algorithm, with no loss in average gain. our approach is implemented as a highly efficient post-processing step that assumes little about the baseline expansion method used as input, making it easy to apply to existing expansion methods. we provide analysis showing that this approach is a natural and effective way to do selective expansion, automatically reducing or avoiding expansion in risky scenarios, and successfully attenuating noise in poor baseline methods.
dynamic in-page logging for flash-aware b-tree index. this paper presents dynamic ipl b+-tree (d-ipl in short) as a b+-tree index variant for flash-based storage systems. the d-ipl b+-tree adopts a dynamic in-page logging (ipl) scheme in order to address a few new problems that are caused by the unique characteristics of b+-tree indexes the d-ipl b+-tree avoids the frequent log overflow problem by allocating a log area in a flash block dynamically. it also addresses elegantly the problem of page evaporation, imposed by the contemporary nand flash chips, by introducing ghost nodes within the context of the dynamic ipl scheme. this simple but elegant design of the d-ipl b+-tree improves the performance significantly. for a random insertion workload, the d-ipl b+-tree index outperformed a b+-tree with a plain ipl scheme by more than a factor of two in terms of page write and block erase operations.
exploiting query views for static index pruning in web search engines. we propose incorporating query views in a number of static pruning strategies, namely term-centric, document-centric and access-based approaches. these query-view based strategies considerably outperform their counterparts for both disjunctive and conjunctive query processing in web search engines.
intention-focused active reranking for image object retrieval. we consider the problem of ranking refinement for image object retrieval, whose goal is to improve an existing ranking function by a small number of labeled instances. to retrieve the relevant image object, one state-of-the-art approach is to use the relevance feedback: it first ranks the images in database based on a given ranking function (i.e., base ranker), and then rerank the initial result by further introducing user's feedback information. the key challenge of combining the information from the base ranker and user's feedback comes from the fact that the base ranker tends to give an imperfect result and the information obtained from user's feedback tends to be very noisy. this paper describes an intention-focused active reranking, an approach for automatically finding the right information to re-estimate the query model. three novel strategies are proposed to boost the performance of the base ranker: (1) an active selection criterion, which obtains a small number of feedback images that are the most informative to the base ranker for user labeling; (2) the user intention verification, which captures the user's intention in object level to alleviate the query drift problem; (3) a discriminative query model re-estimation, which augments the generative approach with a model of the discriminative information conveyed by positive and negative feedback information. experiments on a real world data set demonstrate the effectiveness of the proposed approach and furthermore it significantly outperforms the baseline visual bag-of-words retrieval.
subspace maximum margin clustering. in text mining, we are often confronted with very high dimensional data. clustering with high dimensional data is a challenging problem due to the curse of dimensionality. in this paper, to address this problem, we propose an subspace maximum margin clustering (smmc) method, which performs dimensionality reduction and maximum margin clustering simultaneously within a unified framework. we aim to learn a subspace, in which we try to find a cluster assignment of the data points, together with a hyperplane classifier, such that the resultant margin is maximized among all possible cluster assignments and all possible subspaces. the original problem is transformed from learning the subspace to learning a positive semi-definite matrix, in order to avoid tuning the dimensionality of the subspace. the transformed problem can be solved efficiently via cutting plane technique and constrained concave-convex procedure (cccp). since the sub-problem in each iteration of cccp is joint convex, alternating minimization is adopted to obtain the global optimum. experiments on benchmark data sets illustrate that the proposed method outperforms the state of the art clustering methods as well as many dimensionality reduction based clustering approaches.
combining labeled and unlabeled data with word-class distribution learning. we describe a novel simple and highly scalable semi-supervised method called word-class distribution learning (wcdl), and apply it task of information extraction (ie) by utilizing unlabeled sentences to improve supervised classification methods. wcdl iteratively builds class label distributions for each word in the dictionary by averaging predicted labels over all cases in the unlabeled corpus, and re-training a base classifier adding these distributions as word features. in contrast, traditional self-training or co-training methods self-labeled examples (rather than features) which can degrade performance due to incestuous learning bias. wcdl exhibits robust behavior, and has no difficult parameters to tune. we applied our method on german and english name entity recognition (ner) tasks. wcdl shows improvements over self-training, multi-task semi-supervision or supervision alone, in particular yielding a state-of-the art 75.72 f1 score on the german ner task.
learning to rank with a novel kernel perceptron method. while conventional ranking algorithms, such as the pagerank, rely on the web structure to decide the relevancy of a web page, learning to rank seeks a function capable of ordering a set of instances using a supervised learning approach. learning to rank has gained increasing popularity in information retrieval and machine learning communities. in this paper, we propose a novel nonlinear perceptron method for rank learning. the proposed method is an online algorithm and simple to implement. it introduces a kernel function to map the original feature space into a nonlinear space and employs a perceptron method to minimize the ranking error by avoiding converging to a solution near the decision boundary and alleviating the effect of outliers in the training dataset. furthermore, unlike existing approaches such as ranksvm and rankboost, the proposed method is scalable to large datasets for online learning. experimental results on benchmark corpora show that our approach is more efficient and achieves higher or comparable accuracies in instance ranking than state of the art methods such as frank, ranksvm and rankboost.
supporting ranking pattern-based aggregate queries in sequence data cubes. sequence data processing has been studied extensively in the literature. in recent years, the warehousing and online-analytical processing (olap) of archived sequence data have received growing attentions. in particular, the concept of sequence olap is recently proposed with the objective of evaluating various kinds of so-called pattern-based aggregate (pba) queries so that various kinds of data analytical tasks on sequence data can be carried out efficiently. this paper studies the evaluation of ranking pba queries, which rank the results of pba queries and return only the top-ranked ones to users. we discuss how ranking pba queries drastically improve the usability of s-olap systems and present techniques that can evaluate various kinds of ranking pba queries efficiently.
exploring path query results through relevance feedback. feedback driven data exploration schemes have been implemented for non-structured data (such as text) and document-centric xml collections where formulating precise queries is often impossible. in this paper, we study the problem of enabling exploratory access, through ranking, to data-centric xml. given a path query and a set of results identified by the system to this query over the data, we consider feedback which captures the user's preference for some features over the others. the feedback can be "positive" or "negative". to deal with feedback, we develop a probabilistic feature significance measure and describe how to use this for ranking results in the presence of dependencies between the path features. we bring together these techniques in axp, a system for adaptive and exploratory path retrieval. the experimental results show the effectiveness of the proposed techniques.
modeling context-dependent information. object properties are often based on their contexts, and contexts can be nested to form complex context-dependent information. existing data models cannot naturally and directly represent such context-dependent information. in this paper, we propose a novel mechanism called context constructor in an object-oriented framework to solve this problem.
advanced metasearch engines. a metasearch engine is a system, which is connected to different search engines. in response to a user query, it invokes suitable search engines for the query, merges the information returned by these search engines and output the merged result. there are two types of metasearch engines: one type for unstructured data (mostly text) and the other for structured data. in comparison to a text search engine, a metasearch engine can have a higher coverage of the web and can have more timely information. a metasearch engine for structured data facilitates comparison shopping and services and is convenient to use. in this talk, we discuss the problems and their potential solutions. in addition, challenges and unsolved problems are sketched.
diverging patterns: discovering significant frequency change dissimilarities in large databases. in this paper, we present a framework for mining diverging patterns, a new type of contrast patterns whose frequency changes significantly differently in two data sets, e.g., it changes from a relatively low to a relatively high value in one dataset, but from high to low in the other. in this framework, a measure called diverging ratio is defined and used to discover diverging patterns. we use a four-dimensional vector to represent a pattern, and define the pattern's diverging ratio based on the angular difference between its vectors in two datasets. an algorithm is proposed to mine diverging patterns from a pair of datasets, which makes use of a standard frequent pattern mining algorithm to compute vector components efficiently. we demonstrate the effectiveness of our approach on real-world datasets, showing that the method can reveal novel knowledge from large databases.
a framework for safely publishing communication traces. a communication trace is a detailed record of the communication between two entities. communication traces are vital for research in computer networks and study of network protocols in various domains, but their release is severely constrained by privacy and security concerns. in this paper, we propose a framework in which a trace owner can match an anonymizing transformation with the requirements of analysts. the trace owner can release multiple transformed traces, each customized to an analyst's needs, or a single transformation satisfying all requirements. the framework enables formal reasoning about anonymization policies, for example to verify that a given trace has utility for the analyst, or to obtain the most secure anonymization for the desired level of utility. because communication traces are typically very large, we also provide techniques that allow efficient application of transformations using relational database systems.
practical lessons of data mining at yahoo! the usage of data in many commercial applications has been growing at an unprecedented pace in the last decade. while successful data mining efforts lead to major business advances, there were also numerous, less publicized efforts that for one or another reason failed. in this paper, we discuss practical lessons based on years of our data mining experiences at yahoo! and offer insights into how to drive the data mining effort to success in a business environment. we use two significant yahoo's applications as illustrative examples: shopping categorization and behavioral targeting; and reflect on four success factors: methodology, data, infrastructure, and people.
dissemination of heterogeneous xml data in publish/subscibe systems. the publish-subscribe paradigm is an effective approach for data publishers to asynchronously disseminate relevant data to a large number of data subscribers. a lot of recent research has focused on extending this paradigm to support content-based delivery of xml data using more expressive xml-based subscription specifications that allow constraints on both data contents as well as structure. however, due to the heterogeneous data schemas used by different data publishers even for data in the same domain, an important challenge is how to efficiently and effectively disseminate relevant data to subscribers whose subscriptions might be specified based on schemas that are different from those used by the data publishers. in this paper, we examine the options to resolve this schema heterogeneity problem in xml data dissemination, and propose a novel paradigm that is based on data rewriting. our experimental results demonstrate the effectiveness of the data rewriting paradigm and identifies the tradeoffs of the various approaches.
terminology mining in social media. the highly variable and dynamic word usage in social media presents serious challenges for both research and those commercial applications that are geared towards blogs or other user-generated non-editorial texts. this paper discusses and exemplifies a terminology mining approach for dealing with the productive character of the textual environment in social media. we explore the challenges of practically acquiring new terminology, and of modeling similarity and relatedness of terms from observing realistic amounts of data. we also discuss semantic evolution and density, and investigate novel measures for characterizing the preconditions for terminology mining.
progressive skyline query evaluation and maintenance in wireless sensor networks. skyline query has been received much attention due to its wide application backgrounds for multi-preference and decision making. in this paper we consider skyline query evaluation and maintenance in wireless sensor networks. we devise an evaluation algorithm for finding skyline points progressively and a maintenance algorithm for skyline maintenance incrementally. we also conduct extensive experiments by simulations to evaluate the performance of the proposed algorithms on various datasets. the experimental results show that the proposed algorithms significantly outperform existing algorithms in terms of network lifetime prolongation.
supporting context-based query in personal dataspace. many users need to refer to content in existing files (pictures, tables, emails, web pages and etc.) when they write documents(programs, presentations, proposals and etc.), and often need to revisit these referenced files for review, revision or reconfirmation. therefore it is meaningful to discover an approach to help users revisit these references effectively. traditional approaches (file explorer, desktop search, and etc.) fail to work in this case. in this paper, we propose an efficient solution for this problem. we firstly define a new personal data relationship: context-based reference (cr), which is generated by user behaviors. we also propose efficient methods to identify cr relationship and present a new type of query based on it: context-based query(c-query), which helps users efficiently revisit personal documents based on cr relationship. our experiments validate the effectiveness and efficiency of our methods.
ipog: fast interactive proximity querying on graphs. given an author-conference graph, how do we answer proximity queries (e.g., what are the most related conferences for john smith?); how can we tailor the search result if the user provides additional yes/no type of feedback (e.g., what are the most related conferences for john smith given that he does not like icml?)? given the potential computational complexity, we mainly devote ourselves to addressing the computational issues in this paper by proposing an efficient solution (referred to as ipog-b) for bipartite graphs. our experimental results show that the proposed fast solution (ipogb) achieves significant speedup, while leading to the same ranking result.
interactive, topic-based visual text summarization and analysis. we are building an interactive, visual text analysis tool that aids users in analyzing a large collection of text. unlike existing work in text analysis, which focuses either on developing sophisticated text analytic techniques or inventing novel visualization metaphors, ours is tightly integrating state-of-the-art text analytics with interactive visualization to maximize the value of both. in this paper, we focus on describing our work from two aspects. first, we present the design and development of a time-based, visual text summary that effectively conveys complex text summarization results produced by the latent dirichlet allocation (lda) model. second, we describe a set of rich interaction tools that allow users to work with a created visual text summary to further interpret the summarization results in context and examine the text collection from multiple perspectives. as a result, our work offers two unique contributions. first, we provide an effective visual metaphor that transforms complex and even imperfect text summarization results into a comprehensible visual summary of texts. second, we offer users a set of flexible visual interaction tools as the alternatives to compensate for the deficiencies of current text summarization techniques. we have applied our work to a number of text corpora and our evaluation shows the promise of the work, especially in support of complex text analyses.
learning to rank using evolutionary computation: immune programming or genetic programming? nowadays ranking function discovery approaches using evolutionary computation (ec), especially genetic programming (gp), have become an important branch in the learning to rank for information retrieval (lr4ir) field. inspired by the gp based learning to rank approaches, we provide a series of generalized definitions and a common framework for the application of ec in learning to rank research. besides, according to the introduced framework, we propose rankip, a ranking function discovery approach using immune programming (ip). experimental results demonstrate that rankip evidently outperforms the baselines. in addition, we study the differences between ip and gp in theory and experiments. results show that ip is more suitable for lr4ir due to its high diversity.
computational community interest for ranking. ranking documents with respect to users' information needs is a challenging task, due, in part, to the dynamic nature of users' interest with respect to a query, which can change over time. in this paper, we propose an innovative method for characterizing the interests of a community of users at a specific point in time and for using this characterization to alter the ranking of documents retrieved for a query. by generating a community interest vector (civ) for a given query, we measure the community interest by computing a score in a specific document or web page retrieved by the query. this score is based on a continuously updated set of recent (daily or past few hours) user-oriented text data. when applying our method in ranking yahoo! buzz results, the civ score improves relevant results by 16% as determined by real-world user evaluation.
expected reciprocal rank for graded relevance. while numerous metrics for information retrieval are available in the case of binary relevance, there is only one commonly used metric for graded relevance, namely the discounted cumulative gain (dcg). a drawback of dcg is its additive nature and the underlying independence assumption: a document in a given position has always the same gain and discount independently of the documents shown above it. inspired by the "cascade" user model, we present a new editorial metric for graded relevance which overcomes this difficulty and implicitly discounts documents which are shown below very relevant documents. more precisely, this new metric is defined as the expected reciprocal length of time that the user will take to find a relevant document. this can be seen as an extension of the classical reciprocal rank to the graded relevance case and we call this metric expected reciprocal rank (err). we conduct an extensive evaluation on the query logs of a commercial search engine and show that err correlates better with clicks metrics than other editorial metrics.
text segmentation via topic modeling: an analytical study. in this paper, the task of text segmentation is approached from a topic modeling perspective. we investigate the use of latent dirichlet allocation (lda) topic model to segment a text into semantically coherent segments. a major benefit of the proposed approach is that along with the segment boundaries, it outputs the topic distribution associated with each segment. this information is of potential use in applications like segment retrieval and discourse analysis. the new approach outperforms a standard baseline method and yields significantly better performance than most of the available unsupervised methods on a benchmark dataset.
mining data streams with periodically changing distributions. dynamic data streams are those whose underlying distribution changes over time. they occur in a number of application domains, and mining them is important for these applications. coupled with the unboundedness and high arrival rates of data streams, the dynamism of the underlying distribution makes data mining challenging. in this paper, we focus on a large class of dynamic streams that exhibit periodicity in distribution changes. we propose a framework, called dmm, for mining this class of streams that includes a new change detection technique and a novel match-and-reuse approach. once a distribution change is detected, we compare the new distribution with a set of historically observed distribution patterns and use the mining results from the past if a match is detected. since, for two highly similar distributions, their mining results should also present high similarity, by matching and reusing existing mining results, the overall stream mining efficiency is improved while the accuracy is maintained. our experimental results confirm this conjecture.
a flexible simulation environment for flash-aware algorithms. in this paper, we present a flexible simulation environment for the performance evaluation of flash-aware algorithms, which is called flash-dbsim. the main purpose of flash-dbsim is to provide a configurable virtual flash disk for upper systems, such as file system and dbms, so that the algorithms in those systems can be easily evaluated on different types of flash disks. moreover, it also offers a prototyping environment for those algorithms inside flash disk, e.g. the algorithms for garbage collection or wear-leveling. after an overview of the general features of flash-dbsim, we discuss the architecture of flash-dbsim. and finally, a case study of flash-dbsim's demonstration is presented.
learning better transliterations. we introduce a new probabilistic model for transliteration that performs significantly better than previous approaches, is language-agnostic, requiring no knowledge of the source or target languages, and is capable of both generation (creating the most likely transliteration of a source word) and discovery (selecting the most likely transliteration from a list of candidate words). our experimental results demonstrate improved accuracy over the existing state-of-the-art by more than 10% in chinese, hebrew and russian. while past work has commonly made use of fixed-size n-gram features along with more traditional models such as hmm or perceptron, we utilize an intuitive notion of "productions", where each source word can be segmented into a series of contiguous, non-overlapping substrings of any size, each of which independently transliterates to a substring in the target language with a given probability. to learn these parameters, we employ expectation-maximization (em), with the alignment between substrings in the source and target word training pairs as our latent data. despite the size of the parameter space and the 2(|w|-1) possible segmentations to consider for each word, by using dynamic programming each iteration of em takes o(m^6 * n) time, where m is the length of the longest word in the data and n is the number of word pairs, and is very fast in practice. furthermore, discovering transliterations takes only o(m^4 * w) time, where w is the number of candidate words to choose from, and generating a transliteration takes o(m2 * k2) time, where k is a pruning constant (we used a value of 100). additionally, we are able to obtain training examples in an unsupervised fashion from wikipedia by using a relatively simple algorithm to filter potential word pairs.
characterizing and predicting search engine switching behavior. search engine switching describes the voluntarily transition from one web search engine to another. in this paper we present a study of search engine switching behavior that combines large-scale log-based analysis and survey data. we characterize aspects of switching behavior, and develop and evaluate predictive models of switching behavior using features of the active query, the current session, and user search history. our findings provide insight into the decision-making processes of search engine users and demonstrate the relationship between switching and factors such as dissatisfaction with the quality of the results, the desire for broader topic coverage or verification of encountered information, and user preferences. the findings also reveal sufficient consistency in users' search behavior prior to engine switching to afford accurate prediction of switching events. predictive models may be useful for search engines who may want to modify the search experience if they can accurately anticipate a switch.
adaptive web mining of bilingual lexicons for cross language information retrieval. bilingual web pages contain abundant term translation knowledge which is crucial for query translation in cross language information retrieval systems. but it is a challenging task to extract term translations from bilingual web pages due to the variation in web page layouts and writing styles. in this paper, based on the observation that translation pairs on the same web page tend to appear following similar patterns, a new extraction model is proposed to adaptively learn extraction patterns and exploit them to facilitate term translation mining from bilingual web pages. experiments reflect that this model can significantly improve extraction coverage while maintaining high accuracy. it improves query translation in cross-language information retrieval, leading to significantly higher retrieval effectiveness on trec collections.
improving web page classification by label-propagation over click graphs. in this paper, we present a semi-supervised learning method for web page classification, leveraging click logs to augment training data by propagating class labels to unlabeled similar documents. current state-of-the-art classifiers are supervised and require large amounts of manually labeled data. we hypothesize that unlabeled documents similar to our positive and negative labeled documents tend to be clicked through by the same user queries. our proposed method leverages this hypothesis and augments our training set by modeling the similarity between documents in a click graph. we experiment with three different web page classifiers and show empirical evidence that our proposed approach outperforms state-of-the-art methods and reduces the amount of human effort to label training data.
an effective model of using negative relevance feedback for information filtering. over the years, people have often held the hypothesis that negative feedback should be very useful for largely improving the performance of information filtering systems; however, we have not obtained very effective models to support this hypothesis. this paper, proposes an effective model that use negative relevance feedback based on a pattern mining approach to improve extracted features. this study focuses on two main issues of using negative relevance feedback: the selection of constructive negative examples to reduce the space of negative examples; and the revision of existing features based on the selected negative examples. the former selects some offender documents, where offender documents are negative documents that are most likely to be classified in the positive group. the later groups the extracted features into three groups: the positive specific category, general category and negative specific category to easily update the weight. an iterative algorithm is also proposed to implement this approach on rcv1 data collections, and substantial experiments show that the proposed approach achieves encouraging performance.
db-ir integration and its application to a massively-parallel search engine. nowadays, as there is an increasing need to integrate the dbms (for structured data) with information retrieval (ir) features (for unstructured data), db-ir integration is becoming one of major challenges in the database area[1,2]. extensible architectures provided by commercial object-relational dbms(ordbms) vendors can be used for db-ir integration. here, extensions are implemented using a high-level (typically, sql-level) interface. we call this architecture loose-coupling. the advantage of loose-coupling is ease of implementation. but, loose-coupling is not preferable for implementing new data types and operations in large databases when high performance is required. in this talk, we present a new dbms architecture applicable to db-ir integration, which we call tight-coupling. in tight-coupling, new data types and operations are integrated into the core of the dbms engine in the extensible type layer. thus, they are incorporated as the "first-class citizens"[1] within the dbms architecture and are supported in a consistent manner with high performance. this tight-coupling architecture is being used to incorporate ir features and spatial database features into the odysseus ordbms that has been under development at kaist/aitrc for over 19 years. in this talk, we introduce odysseus and explain its tightly-coupled ir features (u.s. patented in 2002[2]). then, we demonstrate excellence in performance of tight-coupling by showing benchmark results. we have built a web search engine that is capable of managing 100 million web pages per node in a non-parallel configuration using odysseus. this engine has been successfully tested in many commercial environments. this work won the best demonstration award from the ieee icde conference held in tokyo, japan, in april 2005[3]. last, we present a design of a massively-parallel search engine using odysseus. recently, parallel search engines have been implemented based on scalable distributed file systems (e.g., gfs). nevertheless, building a massively-parallel search engine using a dbms can be an attractive alternative since it supports a higher-level (i.e., sql-level) interface than that of a distributed file system while providing scalability. the parallel search engine designed is capable of indexing 30 billion web pages with a performance comparable to or better than those of state-of-the-art search engines.
mining and ranking streams of news stories using cross-stream sequential patterns. we present a new method for mining and ranking streams of news stories using cross-stream sequential patterns and content similarity. in particular, we focus on stories reporting the same event across the streams within a given time window, where an event is defined as a specific thing that happens at a specific time and place. for every discovered cluster of stories reporting the same event we create an itemset-sequence consisting of stream identifiers of the stories in the cluster, where the sequence is ordered according to the timestamps of the stories. furthermore, we record exact timestamps and content similarities between the respective stories. given such a collection of itemset-sequences we use it for two tasks: (i) to discover recurrent temporal publishing patterns between the news streams in terms of frequent sequential patterns and content similarity and (ii) to rank the streams of news stories with respect to timeliness of reporting important events and content authority. we demonstrate the applicability of the presented method on a multi-stream of news stories was gathered from rss feeds of major world news agencies.
anchorwoman: top-k structured mobile web search engine. with advances in technology, mobile handheld devices-such as pdas-have become very popular. in many real-life situations, users want to find structuring information using these mobile devices, which are convenient to use but have relatively limited resources. in this paper, we present a top-k structured mobile web search engine. it uses a top-k adaptable search-tree method that utilizes hierarchical structure of hypermedia objects to effectively look for structuring information from the mobile web model. the engine, which is implemented in the mobile environment, provides users with top-k adaptive web search recommendations for mobile handheld devices.
a system for detecting xml similarity in content and structure using relational database. in this paper, we describe a system incorporating an improved technique that detects the similarity of two xml documents based on content and structure similarity using keys. the technique consists of three major components: a subtree generator and validator, a key generator, and similarity components that compare content and structure of the xml documents. first, an xml document is stored in a relational database and extracted into small subtrees using leaf-node parents. the leaf-node parents are considered as a root of a subtree which is then recursively traversed bottom-up for matching. second, a possible key(s) is identified in order to match xml subtrees from two documents efficiently. key matchings help in reducing the number of comparisons dramatically. in addition, the number of subtrees to be processed is reduced in the subtree validation phase using instance statistics and taxonomic analyzer. the subtrees are matched by the key(s) first and the remaining subtrees are matched by finding degrees of similarity in content and structure. to obtain improved similarity comparison results, xml element names are transformed according to their semantic similarity. the results show that the clustering points are selected appropriately and the overall execution time is reduced dramatically.
joint sentiment/topic model for sentiment analysis. sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. this paper proposes a novel probabilistic modeling framework based on latent dirichlet allocation (lda), called joint sentiment/topic model (jst), which detects sentiment and topic simultaneously from text. unlike other machine learning approaches to sentiment classification which often require labeled corpora for classifier training, the proposed jst model is fully unsupervised. the model has been evaluated on the movie review dataset to classify the review sentiment polarity and minimum prior information have also been explored to further improve the sentiment classification accuracy. preliminary experiments have shown promising results achieved by jst.
asymptotically good ideal linear secret sharing with strong multiplication over fixed finite field. this work deals with "mpc-friendly" linear secret sharing schemes (lsss), a mathematical primitive upon which secure multi-party computation (mpc) can be based and which was introduced by cramer, damgaard and maurer (eurocrypt 2000). chen and cramer proposed a special class of such schemes that is constructed from algebraic geometry and that enables efficient secure multi-party computation over fixed finite fields (crypto 2006). we extend this in four ways. first, we propose an abstract coding-theoretic framework in which this class of schemes and its (asymptotic) properties can be cast and analyzed. second, we show that for every finite field ${\mathbb f}_q$, there exists an infinite family of lsss over ${\mathbb f}_q$ that is asymptotically good in the following sense: the schemes are "ideal," i.e., each share consists of a single ${\mathbb f}_q$-element, and the schemes have t-strong multiplication on n players, where the corruption tolerance $\frac{3t}{n-1}$ tends to a constant ¿(q) with 0 < ¿(q) < 1 when n tends to infinity. moreover, when $|{\mathbb f}_q|$ tends to infinity, ¿(q) tends to 1, which is optimal. this leads to explicit lower bounds on $\widehat{\tau}(q)$, our measure of asymptotic optimal corruption tolerance. we achieve this by combining the results of chen and cramer with a dedicated field-descent method. in particular, in the ${\mathbb f}_2$-case there exists a family of binary t-strongly multiplicative ideal lsss with $\frac{3t}{n-1}\approx 2.86\%$ when n tends to infinity, a one-bit secret and just a one-bit share for every player. previously, such results were shown for ${\mathbb f}_q$ with q ¿ 49 a square. third, we present an infinite family of ideal schemes with t-strong multiplication that does not rely on algebraic geometry and that works over every finite field ${\mathbb f}_q$. its corruption tolerance vanishes, yet still $\frac{3t}{n-1}= \omega(1/(\log\log n)\log n)$. fourth and finally, we give an improved non-asymptotic upper bound on corruption tolerance.
abstraction in cryptography. abstraction means to eliminate irrelevant details from consideration, thereby focusing only on the relevant aspects of a problem or context. abstraction is of paramount importance in most scientific fields, especially in computer science and mathematics. the purpose of abstraction is to provide, at the same time, simpler definitions, higher generality of results, simpler proofs, improved elegance, and often better didactic suitability.abstraction can be a gradual process and need not be unique, but in many contexts, the highest achievable level of abstraction, once identified, appears natural and stable. for example, the abstract and natural concepts of a group or a field in algebra capture exactly what is required to prove many important results.in the spirit of algebraic abstraction, we advocate the definition and use of higher levels of abstraction in cryptography, with the goal of identifying the highest possible level at which a definition or theorem should be stated and proved. some questions one can ask are: what are abstractions of a system, a game, indistinguishability, a hybrid argument, a reduction, indifferentiability, or of (universal) composability? what are abstractions of efficient and negligible, and at which level of abstraction can computational and information-theoretic models be unified? and, of course: can the abstract viewpoint lead to new concepts and results that are perhaps otherwise missed?
the round complexity of verifiable secret sharing revisited. the round complexity of interactive protocols is one of their most important complexity measures. in this work we prove that existing lower bounds for the round complexity of vss can be circumvented by introducing a negligible probability of error in the reconstruction phase. previous results show matching lower and upper bounds of three rounds for vss, with n = 3t + 1, where the reconstruction of the secrets always succeeds, i.e. with probability 1. in contrast we show that with a negligible probability of error in the reconstruction phase: 1 there exists an efficient 2-round vss protocol for n = 3t + 1. if we assume that the adversary is non-rushing then we can achieve a 1-round reconstruction phase. 1 there exists an efficient 1-round vss for t = 1 and n > 3. 1 we prove that our results are optimal both in resilience and number of sharing rounds by showing: 1 there does not exist a 2-round wss (and hence vss) for n ≤ 3t. 1 there does not exist a 1-round vss protocol for t ¿ 2 and n ¿ 4.
smooth projective hashing for conditionally extractable commitments. the notion of smooth projective hash functions was proposed by cramer and shoup and can be seen as special type of zero-knowledge proof system for a language. though originally used as a means to build efficient chosen-ciphertext secure public-key encryption schemes, some variations of the cramer-shoup smooth projective hash functions also found applications in several other contexts, such as password-based authenticated key exchange and oblivious transfer. in this paper, we first address the problem of building smooth projective hash functions for more complex languages. more precisely, we show how to build such functions for languages that can be described in terms of disjunctions and conjunctions of simpler languages for which smooth projective hash functions are known to exist. next, we illustrate how the use of smooth projective hash functions with more complex languages can be efficiently associated to extractable commitment schemes and avoid the need for zero-knowledge proofs. finally, we explain how to apply these results to provide more efficient solutions to two well-known cryptographic problems: a public-key certification which guarantees the knowledge of the private key by the user without random oracles or zero-knowledge proofs and adaptive security for password-based authenticated key exchange protocols in the universal composability framework with erasures.
how to encipher messages on a small domain. we analyze the security of the thorp shuffle, or, equivalently, a maximally unbalanced feistel network. roughly said, the thorp shuffle on n cards mixes any n 1 ¿ 1/r of them in $o(r\lg n)$ steps. correspondingly, making o(r) passes of maximally unbalanced feistel over an n-bit string ensures cca-security to 2 n(1 ¿ 1/r) queries. our results, which employ markov-chain techniques, enable the construction of a practical and provably-secure blockcipher-based scheme for deterministically enciphering credit card numbers and the like using a conventional blockcipher.
leakage-resilient public-key cryptography in the bounded-retrieval model. we study the design of cryptographic primitives resilient to key-leakage attacks, where an attacker can repeatedly and adaptively learn information about the secret key, subject only to the constraint that the overall amount of such information is bounded by some parameter ¿. we construct a variety of leakage-resilient public-key systems including the first known identification schemes (id), signature schemes and authenticated key agreement protocols (aka). our main result is an efficient three-round aka in the random-oracle model, which is resilient to key-leakage attacks that can occur prior-to and after a protocol execution. our aka protocol can be used as an interactive encryption scheme with qualitatively stronger privacy guarantees than non-interactive encryption schemes (constructed in prior and concurrent works), which are inherently insecure if the adversary can perform leakage attacks after seing a ciphertext.moreover, our schemes can be flexibly extended to the bounded-retrieval model, allowing us to tolerate very large absolute amount of adversarial leakage ¿ (potentially many gigabytes of information), only by increasing the size of the secret key and without any other loss of efficiency in communication or computation. concretely, given any leakage parameter ¿, security parameter ¿, and any desired fraction 0 < ¿ ≤ 1, our schemes have the following properties: secret key size is ¿(1 + ¿) + o(¿). public key size is o(¿), and independent of ¿. communication complexity is o(¿/¿), and independent of ¿. computation reads o(¿/¿ 2) locations of the secret key, independent of ¿. lastly, we show that our schemes allow for repeated "invisible updates" of the secret key, allowing us to tolerate up to ¿ bits of leakage in between any two updates, and an unlimited amount of leakage overall. these updates require that the parties can securely store a short "master update key" (e.g. on a separate secure device protected against leakage), which is only used for updates and not during protocol execution. the updates are invisible in the sense that a party can update its secret key at any point in time, without modifying the public key or notifying the other users.
computational differential privacy. the definition of differential privacy has recently emerged as a leading standard of privacy guarantees for algorithms on statistical databases. we offer several relaxations of the definition which require privacy guarantees to hold only against efficient--i.e., computationally-bounded--adversaries. we establish various relationships among these notions, and in doing so, we observe their close connection with the theory of pseudodense sets by reingold et al.[1]. we extend the dense model theorem of reingold et al. to demonstrate equivalence between two definitions (indistinguishability- and simulatability-based) of computational differential privacy.our computational analogues of differential privacy seem to allow for more accurate constructions than the standard information-theoretic analogues. in particular, in the context of private approximation of the distance between two vectors, we present a differentially-private protocol for computing the approximation, and contrast it with a substantially more accurate protocol that is only computationally differentially private.
how risky is the random-oracle model? rsa-fdh and many other schemes secure in the random-oracle model (rom) require a hash function with output size larger than standard sizes. we show that the random-oracle instantiations proposed in the literature for such cases are weaker than a random oracle, including the proposals by bellare and rogaway from 1993 and 1996, and the ones implicit in ieee p1363 and pkcs standards: for instance, we obtain a 267 preimage attack on br93 for 1024-bit digests. next, we study the security impact of hash function defects for rom signatures. as an extreme case, we note that any hash collision would suffice to disclose the master key in the id-based cryptosystem by boneh et al. from focs '07, and the secret key in the rabin-williams signature for which bernstein proved tight security at eurocrypt '08. interestingly, for both of these schemes, a slight modification can prevent these attacks, while preserving the rom security result. we give evidence that in the case of rsa and rabin/rabin-williams, an appropriate pss padding is more robust than all other paddings known.
merkle puzzles are optimal - an ()-query attack on any key exchange from a random oracle. we prove that every key exchange protocol in the random oracle model in which the honest users make at most n queries to the oracle can be broken by an adversary making o(n 2) queries to the oracle. this improves on the previous $\tilde{\omega}(n^6)$ query attack given by impagliazzo and rudich (stoc '89), and answers an open question posed by them. our bound is optimal up to a constant factor since merkle (cacm '78) gave a key exchange protocol that can easily be implemented in this model with n queries and cannot be broken by an adversary making o(n 2) queries.
short and stateless signatures from the rsa assumption. we present the first signature scheme which is "short", stateless and secure under the rsa assumption in the standard model. prior short, standard model signatures in the rsa setting required either a strong complexity assumption such as strong rsa or (recently) that the signer maintain state. a signature in our scheme is comprised of one element in ${\mathcal {z}{^*}_{n}}$ and one integer. the public key is also short, requiring only the modulus n, one element of ${\mathcal {z}{^*}_{n}}$, one integer and one prf seed.to design our signature, we employ the known generic construction of fully-secure signatures from weakly-secure signatures and a chameleon hash. we then introduce a new proof technique for reasoning about weakly-secure signatures. this technique enables the simulator to predict a prefix of the message on which the adversary will forge and to use knowledge of this prefix to embed the challenge. this technique has wider applications beyond rsa.we use it to provide an entirely new analysis of the security of the waters signatures: the only short, stateless signatures known to be secure under the computational diffie-hellman assumption in the standard model.
reconstructing rsa private keys from random key bits. we show that an rsa private key with small public exponent can be efficiently recovered given a 0.27 fraction of its bits at random. an important application of this work is to the "cold boot" attacks of halderman et al. we make new observations about the structure of rsa keys that allow our algorithm to make use of the redundant information in the typical storage format of an rsa private key. our algorithm itself is elementary and does not make use of the lattice techniques used in other rsa key reconstruction problems. we give an analysis of the running time behavior of our algorithm that matches the threshold phenomenon observed in our experiments.
new birthday attacks on some macs based on block ciphers. this paper develops several new techniques of cryptanalyzing macs based on block ciphers, and is divided into two parts.the first part presents new distinguishers of the mac construction alred and its specific instance alpha-mac based on aes. for the alred construction, we first describe a general distinguishing attack which leads to a forgery attack directly with the complexity of the birthday attack. a 2-round collision differential path of alpha-mac is adopted to construct a new distinguisher with about 265.5 chosen messages and 265.5 queries. one of the most important results is to use this new distinguisher to recover the internal state, which is an equivalent subkey of alpha-mac. moreover, our distinguisher on alred construction can be applied to the macs based on cbc and cfb encryption modes.the second part describes the first impossible differential attack on macs-pelican, mt-mac-aes and pc-mac-aes. using the birthday attack, enough message pairs that produce the inner near-collision with some specific differences are detected, then the impossible differential attack on 4-round aes to the above mentioned macs is performed. for pelican, our attack recovers its internal state, which is an equivalent subkey. for mt-mac-aes, the attack turns out to be a subkey recovery attack directly. the complexity of the two attacks is 285.5 chosen messages and 285.5 queries. for pc-mac-aes, we recover its 256-bit key with 285.5 chosen messages and 2128 queries.
on bounded distance decoding, unique shortest vectors, and the minimum distance problem. we prove the equivalence, up to a small polynomial approximation factor $\sqrt{n/\log n}$, of the lattice problems usvp (unique shortest vector problem), bdd (bounded distance decoding) and gapsvp (the decision version of the shortest vector problem). this resolves a long-standing open problem about the relationship between usvp and the more standard gapsvp, as well the bdd problem commonly used in coding theory. the main cryptographic application of our work is the proof that the ajtai-dwork ([2]) and the regev ([33]) cryptosystems, which were previously only known to be based on the hardness of usvp, can be equivalently based on the hardness of worst-case gapsvp${_{o({n^{2.5}})}}$ and gapsvp${_{o(n^{2})}}$, respectively. also, in the case of usvp and bdd, our connection is very tight, establishing the equivalence (within a small constant approximation factor) between the two most central problems used in lattice based public key cryptography and coding theory.
batch binary edwards. this paper sets new software speed records for high-security diffie-hellman computations, specifically 251-bit elliptic-curve variable-base-point scalar multiplication. in one second of computation on a $200 core 2 quad q6600 cpu, this paper's software performs 30000 251-bit scalar multiplications on the binary edwards curve d(x + x 2 + y + y 2) = (x + x 2)(y + y 2) over the field ${\bf f}_2[t]/(t^{251}+t^7+t^4+t^2+1)$ where d = t 57 + t 54 + t 44 + 1. the paper's field-arithmetic techniques can be applied in much more generality but have a particularly efficient interaction with the completeness of addition formulas for binary edwards curves.
on the composition of public-coin zero-knowledge protocols. we show that only languages in bpp have public-coin, black-box zero-knowledge protocols that are secure under an unbounded (polynomial) number of parallel repetitions. this result holds both in the plain model (without any set-up) and in the bare public-key model (where the prover and the verifier have registered public keys). we complement this result by showing the existence of a public-coin black-box zero-knowledge proof that remains secure under any a-priori bounded number of concurrent executions.
randomizable proofs and delegatable anonymous credentials. we construct an efficient delegatable anonymous credentials system. users can anonymously and unlinkably obtain credentials from any authority, delegate their credentials to other users, and prove possession of a credential l levels away from a given authority. the size of the proof (and time to compute it) is o(lk), where k is the security parameter. the only other construction of delegatable anonymous credentials (chase and lysyanskaya, crypto 2006) relies on general non-interactive proofs for np-complete languages of size k ¿(2 l ). we revise the entire approach to constructing anonymous credentials and identify randomizable zero-knowledge proof of knowledge systems as the key building block. we formally define the notion of randomizable non-interactive zero-knowledge proofs, and give the first instance of controlled rerandomization of non-interactive zero-knowledge proofs by a third-party. our construction uses groth-sahai proofs (eurocrypt 2008).
improving the security of quantum protocols via commit-and-open. we consider two-party quantum protocols starting with a transmission of some random bb84 qubits followed by classical messages. we show a general "compiler" improving the security of such protocols: if the original protocol is secure against an "almost honest" adversary, then the compiled protocol is secure against an arbitrary computationally bounded (quantum) adversary. the compilation preserves the number of qubits sent and the number of rounds up to a constant factor. the compiler also preserves security in the bounded-quantum-storage model (bqsm), so if the original protocol was bqsm-secure, the compiled protocol can only be broken by an adversary who has large quantum memory and large computing power. this is in contrast to known bqsm-secure protocols, where security breaks down completely if the adversary has larger quantum memory than expected. we show how our technique can be applied to quantum identification and oblivious transfer protocols.
dual system encryption: realizing fully secure ibe and hibe under simple assumptions. we present a new methodology for proving security of encryption systems using what we call dual system encryption. our techniques result in fully secure identity-based encryption (ibe) and hierarchical identity-based encryption (hibe) systems under the simple and established decisional bilinear diffie-hellman and decisional linear assumptions. our ibe system has ciphertexts, private keys, and public parameters each consisting of a constant number of group elements. these results are the first hibe system and the first ibe system with short parameters under simple assumptions.in a dual system encryption system both ciphertexts and private keys can take on one of two indistinguishable forms. a private key or ciphertext will be normal if they are generated respectively from the system's key generation or encryption algorithm. these keys and ciphertexts will behave as one expects in an ibe system. in addition, we define semi-functional keys and ciphertexts. a semi-functional private key will be able to decrypt all normally generated ciphertexts; however, decryption will fail if one attempts to decrypt a semi-functional ciphertext with a semi-functional private key. analogously, semi-functional ciphertexts will be decryptable only by normal private keys.dual system encryption opens up a new way to prove security of ibe and related encryption systems. we define a sequence of games where we change first the challenge ciphertext and then the private keys one by one to be semi-functional. we finally end up in a game where the challenge ciphertext and all private keys are semi-functional at which point proving security is straightforward.
probabilistically checkable arguments. we give a general reduction that converts any public-coin interactive proof into a one-round (two-message) argument. the reduction relies on a method proposed by aiello et al. [1], of using a private-information-retrieval (pir) scheme to collapse rounds in interactive protocols. for example, the reduction implies that for any security parameter t, the membership in any language in pspace can be proved by a one-round (two-message) argument of size poly(n,t), which is sound for malicious provers of size 2 t . (note that the honest prover in this construction runs in exponential time, since she has to prove membership in pspace, but we can choose t such that 2 t is significantly larger than the running time of the honest prover).a probabilistically checkable argument (pca) is a relaxation of the notion of probabilistically checkable proof (pcp). it is defined analogously to pcp, except that the soundness property is required to hold only computationally. we consider the model where the argument is of one round (two-message), where the verifier's message depends only on his (private) randomness. we show that for membership in many np languages, there are pcas (with efficient honest provers) that are of size polynomial in the size of the witness. this compares to the best pcps that are of size polynomial in the size of the instance (that may be significantly larger). the number of queries to these pcas is poly-logarithmic.the soundness property, in all our results, relies on exponential hardness assumptions for pir schemes.
short chosen-prefix collisions for md5 and the creation of a rogue ca certificate. we present a refined chosen-prefix collision construction for md5 that allowed creation of a rogue certification authority (ca) certificate, based on a collision with a regular end-user website certificate provided by a commercial ca. compared to the previous construction from eurocrypt 2007, this paper describes a more flexible family of differential paths and a new variable birthdaying search space. combined with a time-memory trade-off, these improvements lead to just three pairs of near-collision blocks to generate the collision, enabling construction of rsa moduli that are sufficiently short to be accepted by current cas. the entire construction is fast enough to allow for adequate prediction of certificate serial number and validity period: it can be made to require about 249 md5 compression function calls. finally, we improve the complexity of identical-prefix collisions for md5 to about 216 md5 compression function calls and use it to derive a practical single-block chosen-prefix collision construction of which an example is given.
solving hidden number problem with one bit oracle and advice. in the hidden number problem (hnp), the goal is to find a hidden number s, when given p, g and access to an oracle that on query a returns the k most significant bits of $s\cdot g^a \bmod p$.we present an algorithm solving hnp, when given an advice depending only on p and g; the running time and advice length are polynomial in logp. this algorithm improves over prior hnp algorithms in achieving: (1) optimal number of bits k ¿ 1 (compared with k ¿ ¿(loglogp)); (2) robustness to random noise; and (3) handling a wide family of predicates on top of the most significant bit.as a central tool we present an algorithm that, given oracle access to a function f over ${\mathbb z}_n$, outputs all the significant fourier coefficients of f (i.e., those occupying, say, at least 1% of the energy). this algorithm improves over prior works in being: local. its running time is polynomial in logn and $l_1(\widehat f)$ (for $l_1(\widehat f)$ the sum of f's fourier coefficients, in absolute value). universal. for any n,t, the same oracle queries are asked for all functions f over ${\mathbb z}_n$ s.t. $l_1(\widehat f)\le t$. robust. the algorithm succeeds with high probability even if the oracle to f is corrupted by random noise. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
public-key cryptosystems resilient to key leakage. most of the work in the analysis of cryptographic schemes is concentrated in abstract adversarial models that do not capture side-channel attacks. such attacks exploit various forms of unintended information leakage, which is inherent to almost all physical implementations. inspired by recent side-channel attacks, especially the "cold boot attacks", akavia, goldwasser and vaikuntanathan (tcc '09) formalized a realistic framework for modeling the security of encryption schemes against a wide class of side-channel attacks in which adversarially chosen functions of the secret key are leaked. in the setting of public-key encryption, akavia et al. showed that regev's lattice-based scheme (stoc '05) is resilient to any leakage of l / polylog(l) bits, where l is the length of the secret key.in this paper we revisit the above-mentioned framework and our main results are as follows: we present a generic construction of a public-key encryption scheme that is resilient to key leakage from any universal hash proof system. the construction does not rely on additional computational assumptions, and the resulting scheme is as efficient as the underlying proof system. existing constructions of such proof systems imply that our construction can be based on a variety of number-theoretic assumptions, including the decisional diffie-hellman assumption (and its progressively weaker d-linear variants), the quadratic residuosity assumption, and paillier's composite residuosity assumption. we construct a new hash proof system based on the decisional diffie-hellman assumption (and its d-linear variants), and show that the resulting scheme is resilient to any leakage of l(1 ¿ o(1)) bits. in addition, we prove that the recent scheme of boneh et al. (crypto '08), constructed to be a "circular-secure" encryption scheme, is resilient to any leakage of l(1 ¿ o(1)) bits. these two proposed schemes complement each other in terms of efficiency. we extend the framework of key leakage to the setting of chosen-ciphertext attacks. on the theoretical side, we prove that the naor-yung paradigm is applicable in this setting as well, and obtain as a corollary encryption schemes that are cca2-secure with any leakage of l(1 ¿ o(1)) bits. on the practical side, we prove that variants of the cramer-shoup cryptosystem (along the lines of our generic construction) are cca1-secure with any leakage of l/4 bits, and cca2-secure with any leakage of l/6 bits.
computational indistinguishability amplification: tight product theorems for system composition. computational indistinguishability amplification is the problem of strengthening cryptographic primitives whose security is defined by bounding the distinguishing advantage of an efficient distinguisher. examples include pseudorandom generators (prgs), pseudorandom functions (prfs), and pseudorandom permutations (prps).the literature on computational indistinguishability amplification consists only of few isolated results. yao's xor-lemma implies, by a hybrid argument, that no efficient distinguisher has advantage better than (roughly) n2 m ¿ 1 ¿ m in distinguishing the xor of m independent n-bit prg outputs s 1,...,s m from uniform randomness if no efficient distinguisher has advantage more than ¿ in distinguishing s i from a uniform n-bit string. the factor 2 m ¿ 1 allows for security amplification only if $\delta: for the case of prfs, a random-offset xor-construction of myers was the first result to achieve strong security amplification, i.e., also for $\frac{1}{2} \le \delta .this paper proposes a systematic treatment of computational indistinguishability amplification. we generalize and improve the above product theorem for the xor of prgs along five axes. first, we prove the tight information-theoretic bound 2 m ¿ 1 ¿ m (without factor n) also for the computational setting. second, we prove results for interactive systems (e.g. prfs or prps). third, we consider the general class of neutralizing combination constructions, not just xor. as an application, this yields the first indistinguishability amplification results for the cascade of prps (i.e., block ciphers) converting a weak prp into an arbitrarily strong prp, both for single-sided and two-sided queries. fourth, strong security amplification is achieved for a subclass of neutralizing constructions which includes as a special case the construction of myers. as an application we obtain highly practical optimal security amplification for block ciphers, simply by adding random offsets at the input and output of the cascade. fifth, we show strong security amplification also for weakened assumptions like security against random-input (as opposed to chosen-input) attacks.a key technique is a generalization of yao's xor-lemma to (interactive) systems which is of independent interest.
distinguisher and related-key attack on the full aes-256. in this paper we construct a chosen-key distinguisher and a related-key attack on the full 256-bit key aes. we define a notion of differential q -multicollision and show that for aes-256 q-multicollisions can be constructed in time q·267 and with negligible memory, while we prove that the same task for an ideal cipher of the same block size would require at least $o(q\cdot 2^{\frac{q-1}{q+1}128})$ time. using similar approach and with the same complexity we can also construct q-pseudo collisions for aes-256 in davies-meyer mode, a scheme which is provably secure in the ideal-cipher model. we have also computed partial q-multicollisions in time q·237 on a pc to verify our results. these results show that aes-256 can not model an ideal cipher in theoretical constructions. finally we extend our results to find the first publicly known attack on the full 14-round aes-256: a related-key distinguisher which works for one out of every 235 keys with 2120 data and time complexity and negligible memory. this distinguisher is translated into a key-recovery attack with total complexity of 2131 time and 265 memory.
the group of signed quadratic residues and applications. we consider the cryptographic group of signed quadratic residues. this group is particularly useful for cryptography since it is a "gap-group," in which the computational problem (i.e., computing square roots) is as hard as factoring, while the corresponding decisional problem (i.e., recognizing signed quadratic residues) is easy. we are able to show that under the factoring assumption, the strong diffie-hellman assumption over the signed quadratic residues holds. that is, in this group the diffie-hellman problem is hard, even in the presence of a decisional diffie-hellman oracle.we demonstrate the usefulness of our results by applying them to the hybrid elgamal encryption scheme (aka diffie-hellman integrated encryption scheme - dhies). concretely, we consider the security of the scheme when instantiated over the group of signed quadratic residues. it is known that, in the random oracle model, the scheme is chosenciphertext (cca) secure under the strong diffie-hellman assumption and hence, by our results, under the standard factoring assumption. we show that furthermore, in the standard model, hybrid elgamal is cca secure under the higher residuosity assumption, given that the used hash function is four-wise independent. the latter result is obtained using the recent "randomness extraction framework" for hash proof systems.
cryptanalysis of c2. we present several attacks on the block cipher c2, which is used for encrypting dvd audio discs and secure digital cards. c2 has a 56 bit key and a secret 8 to 8 bit s-box. we show that if the attacker is allowed to choose the key, the s-box can be recovered in 224 c2 encryptions. attacking the 56 bit key for a known s-box can be done in complexity 248. finally, a c2 implementation with a 8 to 8 bit secret s-box (equivalent to 2048 secret bits) and a 56 bit secret key can be attacked in 253.5 c2 encryptions on average.
private mutual authentication and conditional oblivious transfer. a bi-directional private authentication, or unlinkable secret handshake, allows two parties to authenticate each other as certified by given certification authorities (i.e. affiliated with given groups), in a mutually private way, in the sense that the protocol leaks no information about either participant to a party which does not satisfy that participant's authentication policy. in particular, the protocol hides what group this participant belongs to, and protocol instances involving the same participant are unlinkable. we construct the first realization of such private authentication using o(1) exponentiations and bilinear maps, secure under strong diffie-hellman and decisional linear assumptions.our protocols rely on a novel technical tool, a family of efficient private conditional oblivious transfer (cot) protocols, secure under ddh, for languages defined by modular arithmetic constraints (e.g. equality, inequality, sums, products) on discrete-log representations of some group elements. (recall that (w 1,...,w n ) is a representation of c in bases (g 1,...,g n ) if $c=g_1^{w_1}...g_n^{w_n}$.) a cot protocol for language l allows sender s to encrypt message m "under" statement x so that receiver r gets m only if r holds a witness for membership of x in l, while s learns nothing. a private cot for l hides not only message m but also statement x from any r that does not know a witness for x in l.
practical cryptanalysis of iso/iec 9796-2 and emv signatures. in 1999, coron, naccache and stern discovered an existential signature forgery for two popular rsa signature standards, iso/iec 9796-1 and 2. following this attack iso/iec 9796-1 was withdrawn. iso/iec 9796-2 was amended by increasing the message digest to at least 160 bits. attacking this amended version required at least 261 operations.in this paper, we exhibit algorithmic refinements allowing to attack the amended (currently valid) version of iso/iec 9796-2 for all modulus sizes. a practical forgery was computed in only two days using 19 servers on the amazon ec2 grid for a total cost of $\simeq\mbox{{\sc us\$800}}$. the forgery was implemented for e = 2 but attacking odd exponents will not take longer. the forgery was computed for the rsa-2048 challenge modulus, whose factorization is still unknown.the new attack blends several theoretical tools. these do not change the asymptotic complexity of coron et al.'s technique but significantly accelerate it for parameter values previously considered beyond reach.while less efficient (us$45,000), the acceleration also extends to emv signatures. emv is an iso/iec 9796-2-compliant format with extra redundancy. luckily, this attack does not threaten any of the 730 million emv payment cards in circulation for operational reasons.costs are per modulus: after a first forgery for a given modulus, obtaining more forgeries is virtually immediate.
meet-in-the-middle preimage attacks against reduced sha-0 and sha-1. preimage resistance of several hash functions has already been broken by the meet-in-the-middle attacks and they utilize a property that their message schedules consist of only permutations of message words. it is unclear whether this type of attacks is applicable to a hash function whose message schedule does not consist of permutations of message words. this paper proposes new attacks against reduced sha-0 and sha-1 hash functions by analyzing a message schedule that does not consist of permutations but linear combinations of message words. the newly developed cryptanalytic techniques enable the meet-in-the-middle attack to be applied to reduced sha-0 and sha-1 hash functions. the attacks find preimages of sha-0 and sha-1 in 2156.6 and 2159.3 compression function computations up to 52 and 48 steps, respectively, compared to the brute-force attack, which requires 2160 compression function computations. the previous best attacks find preimages up to 49 and 44 steps, respectively.
linear algebra with sub-linear zero-knowledge arguments. we suggest practical sub-linear size zero-knowledge arguments for statements involving linear algebra. given commitments to matrices over a finite field, we give a sub-linear size zero-knowledge argument that one committed matrix is the product of two other committed matrices. we also offer a sub-linear size zero-knowledge argument for a committed matrix being equal to the hadamard product of two other committed matrices. armed with these tools we can give many other sub-linear size zero-knowledge arguments, for instance for a committed matrix being upper or lower triangular, a committed matrix being the inverse of another committed matrix, or a committed matrix being a permutation of another committed matrix.a special case of what can be proved using our techniques is the satisfiability of an arithmetic circuit with n gates. our arithmetic circuit zero-knowledge argument has a communication complexity of $o(\sqrt{n})$ group elements. we give both a constant round variant and an o(logn) round variant of our zero-knowledge argument; the latter has a computation complexity of o(n/logn) exponentiations for the prover and o(n) multiplications for the verifier making it efficient for the prover and very efficient for the verifier. in the case of a binary circuit consisting of nand-gates we give a zero-knowledge argument of circuit satisfiability with a communication complexity of $o(\sqrt{n})$ group elements and a computation complexity of o(n) multiplications for both the prover and the verifier.
privacy-enhancing auctions using rational cryptography. we consider enhancing with privacy concerns a large class of auctions, which include sealed-bid single-item auctions but also general multi-item multi-winner auctions, our assumption being that bidders primarily care about monetary payoff and secondarily worry about exposing information about their type to other players and learning information about other players' types, that is, bidders are greedy then paranoid. to treat privacy explicitly within the game theoretic context, we put forward a novel hybrid utility model that considers both monetary and privacy components in players' payoffs.we show how to use rational cryptography to approximately implement any given ex interim individually strictly rational equilibrium of such an auction without a trusted mediator through a cryptographic protocol that uses only point-to-point authenticated channels between the players. by "ex interim individually strictly rational" we mean that, given its type and before making its move, each player has a strictly positive expected utility. by "approximately implement" we mean that, under cryptographic assumptions, running the protocol is a computational nash equilibrium with a payoff profile negligibly close to the original equilibrium.
on the amortized complexity of zero-knowledge protocols. we propose a general technique that allows improving the complexity of zero-knowledge protocols for a large class of problems where previously the best known solution was a simple cut-and-choose style protocol, i.e., where the size of a proof for problem instance x and error probability 2¿ n was o(|x| n) bits. by using our technique to prove n instances simultaneously, we can bring down the proof size per instance to o(|x| + n) bits for the same error probability while using no computational assumptions. examples where our technique applies include proofs for quadratic residuosity, proofs of subgroup membership and knowledge of discrete logarithms in groups of unknown order, and proofs of plaintext knowledge for various types of homomorphic encryptions schemes. the generality of our method stems from a somewhat surprising application of black-box secret sharing schemes.
message authentication codes from unpredictable block ciphers. we design an efficient mode of operation on block ciphers, ss-nmac. our mode has the following properties, when instantiated with a block cipher f to yield a variable-length, keyed hash function h: (1) mac preservation. h is a secure message authentication code (mac) with birthday security, as long as f is unpredictable. (2) prf preservation. h is a secure pseudorandom function (prf) with birthday security, as long as f is pseudorandom. (3) security against side-channels. as long as the block cipher f does not leak side-channel information about its internals to the attacker, properties (1) and (2) hold even if the remaining implementation of h is completely leaky. in particular, if the attacker can learn the transcript of all block cipher calls and other auxiliary information needed to implement our mode of operation. our mode is the first to satisfy the mac preservation property (1) with birthday security, solving the main open problem of dodis et al. [7] from eurocrypt 2008. combined with the prf preservation (2), our mode provides a hedge against the case when the block cipher f is more secure as a mac than as a prf: if it is false, as we hope, we get a secure variable-length prf; however, even if true, we still "salvage" a secure mac, which might be enough for a given application.we also remark that no prior mode of operation offered birthday security against side channel attacks, even if the block cipher was assumed pseudorandom.although very efficient, our mode is three times slower than many of the prior modes, such as cbc, which do not enjoy properties (1) and (3). thus, our work motivates further research to understand the gap between unpredictability and pseudorandomness of the existing block ciphers, such as aes.
how to hash into elliptic curves. we describe a new explicit function that given an elliptic curve e defined over $\mathbb f_{p^n}$, maps elements of $\mathbb f_{p^n}$ into e in deterministic polynomial time and in a constant number of operations over $\mathbb f_{p^n}$. the function requires to compute a cube root. as an application we show how to hash deterministically into an elliptic curve.
position based cryptography. we consider what constitutes identities in cryptography. typical examples include your name and your social-security number, or your fingerprint/iris-scan, or your address, or your (non-revoked) public-key coming from some trusted public-key infrastructure. in many situations, however, where you are defines your identity. for example, we know the role of a bank-teller behind a bullet-proof bank window not because she shows us her credentials but by merely knowing her location. in this paper, we initiate the study of cryptographic protocols where the identity (or other credentials and inputs) of a party are derived from its geographic location.we start by considering the central task in this setting, i.e., securely verifying the position of a device. despite much work in this area, we show that in the vanilla (or standard) model, the above task (i.e., of secure positioning) is impossible to achieve. in light of the above impossibility result, we then turn to the bounded storage model and formalize and construct information theoretically secure protocols for two fundamental tasks: secure positioning; and position based key exchange. we then show that these tasks are in fact universal in this setting --- we show how we can use them to realize secure multi-party computation.our main contribution in this paper is threefold: to place the problem of secure positioning on a sound theoretical footing; to prove a strong impossibility result that simultaneously shows the insecurity of previous attempts at the problem; and to present positive results by showing that the bounded-storage framework is, in fact, one of the "right" frameworks (there may be others) to study the foundations of position-based cryptography.
fast cryptographic primitives and circular-secure encryption based on hard learning problems. the well-studied task of learning a linear function with errors is a seemingly hard problem and the basis for several cryptographic schemes. here we demonstrate additional applications that enjoy strong security properties and a high level of efficiency. namely, we construct: 1 public-key and symmetric-key cryptosystems that provide security for key-dependent messages and enjoy circular security. our schemes are highly efficient: in both cases the ciphertext is only a constant factor larger than the plaintext, and the cost of encryption and decryption is only n·polylog(n) bit operations per message symbol in the public-key case, and polylog(n) bit operations in the symmetric-case. 1 two efficient pseudorandom objects: a "weak randomized pseudorandom function" -- a relaxation of standard prf -- that can be computed obliviously via a simple protocol, and a length-doubling pseudorandom generator that can be computed by a circuit of n ·polylog(n) size. the complexity of our pseudorandom generator almost matches the complexity of the fastest known construction (applebaum et al., random 2006), which runs in linear time at the expense of relying on a nonstandard intractability assumption. our constructions and security proofs are simple and natural, and involve new techniques that may be of independent interest. in addition, by combining our constructions with prior ones, we get fast implementations of several other primitives and protocols.
collusion-free multiparty computation in the mediated model. collusion-free protocols prevent subliminal communication (i.e., covert channels) between parties running the protocol. in the standard communication model, if one-way functions exist, then protocols satisfying any reasonable degree of privacy cannot be collusion-free. to circumvent this impossibility, alwen, shelat and visconti (crypto 2008) recently suggested the mediated model where all communication passes through a mediator. the goal is to design protocols where collusion-freeness is guaranteed as long as the mediator is honest, while standard security guarantees hold if the mediator is dishonest. in this model, they gave constructions of collusion-free protocols for commitments and zero-knowledge proofs in the two-party setting.we strengthen the definition of alwen et al., and resolve the main open questions in this area by showing a collusion-free protocol (in the mediated model) for computing any multi-party functionality.
utility dependence in correct and fair rational secret sharing. the problem of carrying out cryptographic computations when the participating parties are rational in a game-theoretic sense has recently gained much attention. one problem that has been studied considerably is that of rational secret sharing. in this setting, the aim is to construct a mechanism (protocol) so that parties behaving rationally have incentive to cooperate and provide their shares in the reconstruction phase, even if each party prefers to be the only one to learn the secret.although this question was only recently asked by halpern and teague (stoc 2004), a number of works with beautiful ideas have been presented to solve this problem. however, they all have the property that the protocols constructed need to know the actual utility values of the parties (or at least a bound on them). this assumption is very problematic because the utilities of parties are not public knowledge. we ask whether this dependence on the actual utility values is really necessary and prove that in the basic setting, rational secret sharing cannot be achieved without it. on the positive side, we show that by somewhat relaxing the standard assumptions on the utility functions, it is possible to achieve utility independence. in addition to the above, observe that the known protocols for rational secret sharing that do not assume simultaneous channels all suffer from the problem that one of the parties can cause the others to output an incorrect value. (this problem arises when a party gains higher utility by having another output an incorrect value than by learning the secret itself; we argue that such a scenario is not at all unlikely.) we show that this problem is inherent in the non-simultaneous channels model, unless the actual values of the parties' utilities from this attack is known, in which case it is possible to prevent this from happening.
somewhat non-committing encryption and efficient adaptively secure oblivious transfer. designing efficient cryptographic protocols tolerating adaptive adversaries, who are able to corrupt parties on the fly as the computation proceeds, has been an elusive task. in this paper we make progress in this area. first, we introduce a new notion called semi-adaptive security which is slightly stronger than static security but significantly weaker than fully adaptive security. the main difference between adaptive and semi-adaptive security is that semi-adaptive security allows for the case where one party starts out corrupted and the other party becomes corrupted later on, but not the case where both parties start out honest and become corrupted later on. as such, semi-adaptive security is much easier to achieve than fully adaptive security. we then give a simple, generic protocol compiler which transforms any semi-adaptively secure protocol into a fully adaptively secure one. the compilation effectively decomposes the problem of adaptive security into two (simpler) problems which can be tackled separately: the problem of semi-adaptive security and the problem of realizing a weaker variant of secure channels.we solve the latter problem by means of a new primitive that we call somewhat non-committing encryption resulting in significant efficiency improvements over the standard method for realizing secure channels using (fully) non-committing encryption. somewhat non-committing encryption has two parameters: an equivocality parameter ¿ (measuring the number of ways that a ciphertext can be "opened") and the message sizes k. our implementation is very efficient for small values ¿, even when k is large. this translates into a very efficient compilation of semi-adaptively secure protocols for tasks with small input/output domains (such as bit-ot) into fully adaptively secure protocols.indeed, we showcase our methodology by applying it to the recent oblivious transfer protocol by peikert etal [crypto 2008], which is only secure against static corruptions, to obtain the first efficient, adaptively secure and composable ot protocol. in particular, to transfer an n-bit message, we use a constant number of rounds and o(n) public key operations.
nonrigid registration of myocardial perfusion mri using pseudo ground truth. in this paper we present a method for nonrigid registration of myocardial perfusion mr images. instead of registering pairs of images within the observed sequence, we register the observed sequence to a pseudo ground truth, which is a motion/noise-free sequence estimated from the observed one. as the corresponding images of the two sequences have almost identical intensity distributions, our method overcomes the challenges arising from rapidly varying image intensity and contrast. the pseudo ground truth and the deformation fields for the observed sequence are obtained simultaneously by minimizing an energy functional integrating both the registration error and the spatiotemporal constraints on the pseudo ground truth in an expectation-maximization fashion. we have tested the proposed nonrigid registration method on real cardiac mr perfusion scans, both qualitatively and quantitatively. experimental results show that the proposed method is able to successfully compensate for the heart motion during contrast enhancement.
multimodal image registration by information fusion at feature level. this paper proposes a novel multimodal image registration method which can fully utilize the multimodal information and result in a more accurate unified deformation field. different from the existing methods which fuse the information at the image/intensity level, the proposed method fuses the multimodal information at the feature level through gabor wavelets transformation. at this level, complementary and redundant information is distinguished reliably and efficiently, and then combined and removed respectively. experiments on both simulated and real t1+dti image sets illustrate that the proposed method can effectively incorporate better characterization for white matter (wm) from the dti and for gray matter (gm) from the t1 image and lead to a more accurate and efficient multimodal image registration which paves the way for the subsequent multimodal population-based studies.
graphical models and deformable diffeomorphic population registration using global and local metrics. in this paper we propose a novel framework to unite a population to an optimal (unknown) pose through their mutual deformation. the registration criterion comprises three terms, the first imposes compactness on appearance of the registered population at the pixel level, the second tries to minimize the individual distances between all possible pairs of images, while the last is a regularization one imposing smoothness on the deformation fields. the problem is reformulated as a graphical model that consists of hidden (deformation fields) and observed variables (intensities). a novel deformation grid-based scheme is proposed that guarantees the diffeomorphism of the deformation and is computationally favorably compared to standard deformation methods. towards addressing important deformations we propose a compositional approach where the deformations are recovered through the sub-optimal solutions of successive discrete mrfs by using efficient linear programming. promising experimental results using real 2d data demonstrate the potentials of our approach.
efficient large deformation registration via geodesics on a learned manifold of images. geodesic registration methods have been used to solve the large deformation registration problems, which are hard to solve with conventional registration methods. however, analytically defined geodesics may not coincide with anatomically optimal paths of registration. in this paper we propose a novel and efficient method for large deformation registration by learning the underlying structure of the data using a manifold learning technique. in this method a large deformation between two images is decomposed into a series of small deformations along the shortest path on the graph that approximates the metric structure of data. furthermore, the graph representation allows us to estimate the optimal group template by minimizing geodesic distances. we demonstrate the advantages of the proposed method with synthetic 2d images and real 3d mice brain volumes.
characterization of anatomic fiber bundles for diffusion tensor image analysis. in this paper we deal with the problem of quantification of diffusion tensor (dt) data sets. a set of measures and a 2d tract mapping technique are proposed to analyze the fiber structures in brain white matter and to allow for comparisons between different subjects, either patients or controls. features such as integrity, discontinuity and connectivity of the fiber bundles are proposed and analyzed, taking into account longitudinal and transverse information of the fiber bundle under study. the performance of the proposed characterization framework is shown analyzing the corticospinal tracts of control data sets and pathological cases, comparing the measures between controls and patients and also between the right and left hemispheres. a reproducibility study is also performed to show the robustness of the proposed measures.
hierarchical normalized cuts: unsupervised segmentation of vascular biomarkers from ovarian cancer tissue microarrays. research has shown that tumor vascular markers (tvms) may serve as potential oca biomarkers for prognosis prediction. one such tvm is esm-1, which can be visualized by staining ovarian tissue microarrays (tma) with an antibody to esm-1. the ability to quickly and quantitatively estimate vascular stained regions may yield an image based metric linked to disease survival and outcome. automated segmentation of the vascular stained regions on the tmas, however, is hindered by the presence of spuriously stained false positive regions. in this paper, we present a general, robust and efficient unsupervised segmentation algorithm, termed hierarchical normalized cuts (hncut), and show its application in precisely quantifying the presence and extent of a tvm on oca tmas. the strength of hncut is in the use of a hierarchically represented data structure that bridges the mean shift (ms) and the normalized cuts (ncut) algorithms. this allows hncut to efficiently traverse a pyramid of the input image at various color resolutions, efficiently and accurately segmenting the object class of interest (in this case esm-1 vascular stained regions) by simply annotating half a dozen pixels belonging to the target class. quantitative and qualitative analysis of our results, using 100 pathologist annotated samples across multiple studies, prove the superiority of our method (sensitivity 81%, positive predictive value (ppv), 80%) versus a popular supervised learning technique, probabilistic boosting trees (sensitivity, ppv of 76% and 66%).
estimating continuous 4d wall motion of cerebral aneurysms from 3d rotational angiography. this paper presents a technique to recover dynamic 3d vascular morphology from a single 3d rotational x-ray angiography acquisition. the dynamic morphology corresponding to a canonical cardiac cycle is represented via a 4d b-spline based spatiotemporal deformation. such deformation is estimated by simultaneously matching the forward projections of a sequence of the temporally deformed 3d reference volume to the entire 2d measured projection sequence. a joint use of two acceleration strategies is also proposed: semi-precomputation of forward projections and registration metric computation based on a narrow-band region-of-interest. digital and physical phantoms of pulsating cerebral aneurysms have been used for evaluation. accurate estimation has been obtained in recovering sub-voxel pulsation, even from images with substantial intensity inhomogeneity. results also demonstrate that the acceleration strategies can reduce memory consumption and computational time without degrading the performance.
toward real-time simulation of blood-coil interaction during aneurysm embolization. over the last decade, remarkable progress has been made in the field of endovascular treatment of aneurysms. technological advances continue to enable a growing number of patients with cerebral aneurysms to be treated with a variety of endovascular strategies, essentially using detachable platinum coils. yet, coil embolization remains a very complex medical procedure for which careful planning must be combined with advanced technical skills in order to be successful.in this paper we propose a method for computing the complex blood flow patterns that take place within the aneurysm, and for simulating the interaction of coils with this flow. this interaction is twofold, first involving the impact of the flow on the coil during the initial stages of its deployment, and second concerning the decrease of blood velocity within the aneurysm, as a consequence of coil packing. we also propose an approach to achieve real-time computation of coil-flow bilateral influence, necessary for interactive simulation. this in turns allows to dynamically plan coil embolization for two key steps of the procedure: choice and placement of the first coils, and assessment of the number of coils necessary to reduce aneurysmal blood velocity and wall pressure.
a meta registration framework for lesion matching. a variety of pixel and feature based methods have been proposed for registering multiple views of anatomy visible in studies obtained using diagnostic, minimally invasive imaging. a given registration method may outperform another depending on anatomical variations, imaging conditions, and imaging sensor performance, and it is often difficult a priori to determine the best registration method for a particular application. to address this problem, we propose a registration framework that pools the results of multiple registration methods using a decision function for validating registrations. we refer to this as meta registration. we demonstrate that our framework outperforms several individual registration methods on the task of registering multiple views of crohn's disease lesions sampled from a capsule endoscopy (ce) study database. we also report on preliminary work on assessing the quality of registrations obtained, and the possibility of using such assessment in the registration framework.
fast automatic segmentation of the esophagus from 3d ct data using a probabilistic model. automated segmentation of the esophagus in ct images is of high value to radiologists for oncological examinations of the mediastinum. it can serve as a guideline and prevent confusion with pathological tissue. however, segmentation is a challenging problem due to low contrast and versatile appearance of the esophagus. in this paper, a two step method is proposed which first finds the approximate shape using a "detect and connect" approach. a classifier is trained to find short segments of the esophagus which are approximated by an elliptical model. recently developed techniques in discriminative learning and pruning of the search space enable a rapid detection of possible esophagus segments. prior shape knowledge of the complete esophagus is modeled using a markov chain framework, which allows efficient inferrence of the approximate shape from the detected candidate segments. in a refinement step, the surface of the detected shape is non-rigidly deformed to better fit the organ boundaries. in contrast to previously proposed methods, no user interaction is required. it was evaluated on 117 datasets and achieves a mean segmentation error of 2.28mm with less than 9s computation time.
3d meshless prostate segmentation and registration in image guided radiotherapy. image guided radiation therapy (igrt) improves radiation therapy for prostate cancer by facilitating precise radiation dose coverage of the object of interest, and minimizing dose to adjacent normal organs. in an effort to optimize igrt, we developed a fast segmentation-registration-segmentation framework to accurately and efficiently delineate the clinically critical objects in cone beam ct images obtained during radiation treatment. the proposed framework started with deformable models automatically segmenting the prostate, bladder, and rectum in planning ct images. all models were built around seed points and involved in the ct image under the influence of image features using the level set formulation. the deformable models were then converted into meshless point sets and underwent a 3d non rigid registration from the planning ct to the treatment cbct. the motion of deformable models during the registration was constrained by the global shape prior on the target surface during the deformation. the meshless formulation provided a convenient interface between deformable models and the image feature based registration method. the final registered deformable models in the cbct domain were further refined using the interaction between objects and other available image features. the segmentation results for 15 data sets has been included in the validation study, compared with manual segmentations by a radiation oncologist. the automatic segmentation results achieved a satisfactory convergence with manual segmentations and met the speed requirement for on line igrt.
interventional 4-d motion estimation and reconstruction of cardiac vasculature without motion periodicity assumption. anatomical and functional information of cardiac vasculature is a key component of future developments in the field of interventional cardiology. with the technology of c-arm ct it is possible to reconstruct intraprocedural 3-d images from angiographic projection data. current approaches attempt to add the temporal dimension (4-d) by ecg-gating in order to distinct physical states of the heart. this model assumes that the heart motion is periodic. however, frequently arrhytmic heart signals are observed in a clinical environment. in addition breathing motion can still occur. we present a reconstruction method based on a 4-d time-continuous motion field which is parameterized by the acquisition time and not the quasi-periodic heart phase. the output of our method is twofold. it provides a motion compensated 3-d reconstruction (anatomic information) and a motion field (functional information). in a physical phantom experiment a vessel of size 3.08 mm undergoing a non-periodic motion was reconstructed. the resulting diameters were 3.42 mm and 1.85 mm assuming non-periodic and periodic motion, respectively. further, for two clinical cases (coronary arteries and coronary sinus) it is demonstrated that the presented algorithm outperforms periodic approaches and is able to handle realistic irregular heart motion.
toward video-based navigation for endoscopic endonasal skull base surgery. endoscopic endonasal skull base surgery (esbs) requires high accuracy to ensure safe navigation of the critical anatomy at the anterior skull base. current navigation systems provide approximately 2mm accuracy. this level of registration error is due in part from the indirect nature of tracking used. we propose a method to directly track the position of the endoscope using video data. our method first reconstructs image feature points from video in 3d, and then registers the reconstructed point cloud to pre-operative data (e.g. ct/mri). after the initial registration, the system tracks image features and maintains the 2d-3d correspondence of image features and 3d locations. these data are then used to update the current camera pose. we present registration results within 1mm, which matches the accuracy of our validation framework.
a dynamical shape prior for lv segmentation from rt3d echocardiography. real-time three-dimensional (rt3d) echocardiography is the newest generation of three-dimensional (3-d) echocardiography. segmentation of rt3d echocardiographic images is essential for determining many important diagnostic parameters. in cardiac imaging, since the heart is a moving organ, prior knowledge regarding its shape and motion patterns becomes an important component for the segmentation task. however, most previous cardiac models are either static models (sm), which neglect the temporal coherence of a cardiac sequence or generic dynamical models (gdm), which neglect the inter-subject variability of cardiac motion. in this paper, we present a subject-specific dynamical model (ssdm) which simultaneously handles inter-subject variability and cardiac dynamics (intra-subject variability). it can progressively predict the shape and motion patterns of a new sequence at the current frame based on the shapes observed in the past frames. the incorporation of this ssdm into the segmentation process is formulated in a recursive bayesian framework. this results in a segmentation of each frame based on the intensity information of the current frame, as well as on the prediction from the previous frames. quantitative results on 15 rt3d echocardiographic sequences show that automatic segmentation with ssdm is superior to that of either sm or gdm, and is comparable to manual segmentation.
dynamic active constraints for hyper-redundant flexible robots. in robot-assisted procedures, the surgeon's ability can be enhanced by navigation guidance through the use of virtual fixtures or active constraints. this paper presents a real-time modeling scheme for dynamic active constraints with fast and simple mesh adaptation under cardiac deformation and changes in anatomic structure. a smooth tubular pathway is constructed which provides assistance for a flexible hyper-redundant robot to circumnavigate the heart with the aim of undertaking bilateral pulmonary vein isolation as part of a modified maze procedure for the treatment of debilitating arrhythmia and atrial fibrillation. in contrast to existing approaches, the method incorporates detailed geometrical constraints with explicit manipulation margins of the forbidden region for an entire articulated surgical instrument, rather than just the end-effector itself. detailed experimental validation is conducted to demonstrate the speed and accuracy of the instrument navigation with and without the use of the proposed dynamic constraints.
targeting accuracy under model-to-subject misalignments in model-guided cardiac surgery. in image-guided interventions, anatomical models of organs are often generated from pre-operative images and further employed in planning and guiding therapeutic procedures. however, the accuracy of these models, along with their registration to the subject are crucial for successful therapy delivery. these factors are amplified when manipulating soft tissue undergoing large deformations, such as the heart. when used in guiding beating-heart procedures, pre-operative models may not be sufficient for guidance and they are often complemented with real-time, intra-operative cardiac imaging. here we demonstrate via in vitro endocardial "therapy" that ultrasound-enhanced model-guided navigation provides sufficient guidance to preserve a clinically-desired targeting accuracy of under 3 mm independently of the model-to-subject misregistrations. these results emphasize the direct benefit of integrating real-time imaging within intra-operative visualization environments considering that model-to-subject misalignments are often encountered clinically.
nonmagnetic rigid and flexible outer sheath with pneumatic interlocking mechanism for minimally invasive surgical approach. we developed a nonmagnetic rigid and flexible outer sheath with pneumatic interlocking mechanism using flexible toothed links and a wire-driven bending distal end. the outer sheath can be switched between rigid and flexible modes easily depending on surgical scenes, and the angle of its distal end can be controlled by three nylon wires. all components of flexible parts are made of mri-compatible nonmagnetic plastics. we manufactured the device with 300-mm long, 16-mm outer diameter, 7-mm inner diameter and 90-mm bending distal end. holding power of the device in rigid mode was maximum 3.6 n, which was sufficient for surgical tasks in body cavity. in vivo experiment using a swine, our device performed smooth insertion of a flexible endoscope and a biopsy forceps into reverse side of the liver, intestines and spleen with a curved path. in conclusion, our device shows availability of secure approach of surgical instruments into deep cavity.
methods for tractography-driven surface registration of brain structures. registration of brain structures should bring anatomically equivalent areas into correspondence which is usually done using information from structural mri modalities. correspondence can be improved by using other image modalities that provide complementary data. in this paper we propose and evaluate two novel surface registration algorithms which improve within-surface correspondence in brain structures. both approaches use a white-matter tract similarity function (derived from probabilistic tractography) to match areas of similar connectivity patterns. the two methods differ in the way the deformation field is calculated and in how the multi-scale registration framework is implemented. we validated both algorithms using artificial and real image examples, in both cases showing high registration consistency and the ability to find differences in thalamic sub-structures between alzheimer's disease and control subjects. the results suggest differences in thalamic connectivity predominantly in the medial dorsal parts of the left thalamus.
intra-operative multimodal non-rigid registration of the liver for navigated tumor ablation. ct guided tumor ablation of the liver often suffers from a lack of visualization of the target tumor and surrounding critical structures. this information is available on pre-operative contrast enhanced mr images and a non-rigid registration technique is desirable. however while registration methods have been successfully tested retrospectively on patient data, very few have been incorporated into clinical procedures. a non-rigid registration technique has been evaluated, optimized and validated to be able to perform registration of the liver between mr to ct images, and between intra-operative ct images. the method requires pre-processing and segmentation of the liver, and presents an accuracy of approximately 2mm. a clinical feasibility study has been conducted in 5 liver ablation cases. the method helps clinicians enhance interventional planning, confirm ablation probe location with respect to the tumor, and in the case of cryotherapy, evaluate tumor coverage by the ice ball.
optimal transseptal puncture location for robot-assisted left atrial catheter ablation. the preferred method of treatment for atrial fibrillation (af) is by catheter ablation wherein a catheter is guided into the left atrium through a transseptal puncture. however, the transseptal puncture constrains the catheter, thereby limiting its maneuverability and increasing the difficulty in reaching various locations in the left atrium. in this paper, we address the problem of choosing the optimal transseptal puncture location for performing cardiac ablation to obtain maximum maneuverability of the catheter. we have employed an optimization algorithm to maximize the global isotropy index (gii) to evaluate the optimal transseptal puncture location. as part of this algorithm, a novel kinematic model for the catheter has been developed based on a continuum robot model. preoperative mr/ct images of the heart are segmented using the open source image-guided therapy software, slicer 3, to obtain models of the left atrium and septal wall. these models are input to the optimization algorithm to evaluate the optimal transseptal puncture location. simulation results for the optimization algorithm are presented in this paper.
nonparametric intensity priors for level set segmentation of low contrast structures. segmentation of low contrast objects is an important task in clinical applications like lesion analysis and vascular wall remodeling analysis. several solutions to low contrast segmentation that exploit high-level information have been previously proposed, such as shape priors and generative models. in this work, we incorporate a priori distributions of intensity and low-level image information into a nonparametric dissimilarity measure that defines a local indicator function for the likelihood of belonging to a foreground object. we then integrate the indicator function into a level set formulation for segmenting low contrast structures. we apply the technique to the clinical problem of positive remodeling of the vessel wall in cardiac ct angiography images. we present results on a dataset of twenty five patient scans, showing improvement over conventional gradient-based level sets.
coronary tree extraction using motion layer separation. fluoroscopic images contain useful information that is difficult to comprehend due to the collapse of the 3d information into 2d space. extracting the informative layers and analyzing them separately could significantly improve the task of understanding the image content. traditional digital subtraction angiography (dsa) is not applicable for coronary angiography because of heart beat and breathing motion. in this work, we propose a layer extraction method for separating transparent motion layers in fluoroscopic image sequences, so that coronary tree can be better visualized.. the method is based on the fact that different anatomical structures possess different motion patterns, e.g., heart is beating fast, while lung is breathing slower. a multiscale implementation is used to further improve the efficiency and accuracy. the proposed approach helps to enhance the visibility of the vessel tree, both visually and quantitatively.
tractography-based parcellation of the cortex using a spatially-informed dimension reduction of the connectivity matrix. determining cortical functional areas is an important goal for neurosciences and clinical neurosurgery. this paper presents a method for connectivity-based parcellation of the entire human cortical surface, exploiting the idea that each cortex region has a specific connection profile. the connectivity matrix of the cortex is computed using analytical q-ball-based tractography. the parcellation is achieved independently for each subject and applied to the subset of the cortical surface endowed with enough connections to estimate safely a connectivity profile, namely the top of the cortical gyri. the key point of the method lies in a twofold reduction of the connectivity matrix dimension. first, parcellation amounts to iterating the clustering of voronoï patches of the cortical surface into parcels endowed with homogeneous profiles. the parcels without intersection with the patch boundaries are selected for the final parcellation. before clustering a patch, the complete profiles are collapsed into short profiles indicating connectivity with a set of putative cortical areas. these areas are supposed to correspond to the catchment basins of the watershed of the density of connection to the patch computed on the cortical surface. the results obtained for several brains are compared visually using a coordinate system.
a novel global tractography algorithm based on an adaptive spin glass model. this paper introduces a novel framework for global diffusion mri tractography inspired from a spin glass model. the entire white matter fascicle map is parameterized by pieces of fibers called spins. spins are encouraged to move and rotate to align with the main fiber directions, and to assemble into longer chains of low curvature. moreover, they have the ability to adapt their quantity in regions where the spin concentration is not sufficient to correctly model the data. the optimal spin glass configuration is retrieved by an iterative minimization procedure, where chains are finally assimilated to fibers. as a result, all brain fibers appear as growing simultaneously until they merge with other fibers or reach the domain boundaries. in case of an ambiguity within a region like a crossing, the contribution of all neighboring fibers is used determine the correct neural pathway. this framework is tested on a mr phantom representing a 45° crossing and a real brain dataset. notably, the framework was able to retrieve the triple crossing between the callosal fibers, the corticospinal tract and the arcuate fasciculus.
towards interactive planning of coil embolization in brain aneurysms. many vascular pathologies can now be treated in a minimally invasive way thanks to interventional radiology. instead of open surgery, it allows to reach the lesion of the arteries with therapeutic devices through a catheter. as a particular case, intracranial aneurysms are treated by filling the localized widening of the artery with a set of coils to prevent a rupture due to the weakened arterial wall. considering the location of the lesion, close to the brain, and its very small size, the procedure requires a combination of careful planning and excellent technical skills. an interactive and reliable simulation, adapted to the patient anatomy, would be an interesting tool for helping the interventional neuroradiologist plan and rehearse a coil embolization procedure. this paper describes an original method to perform interactive simulations of coil embolization and proposes a clinical metric to quantitatively measure how the first coil fills the aneurysm. the simulation relies on an accurate reconstruction of the aneurysm anatomy and a real-time model of the coil for which sliding and friction contacts are taken into account. simulation results are compared to real embolization procedure and exhibit good adequacy.
parallax-free long bone x-ray image stitching. in this paper, we present a novel method to create parallax-free panoramic x-ray images of long bones during surgery by making the c-arm rotate around its x-ray source, relative to the patient's table. in order to ensure that the c-arm motion is a relative pure rotation around its x-ray source, we move the table to compensate for the translational part of the motion based on c-arm pose estimation, for which we employed a camera augmented mobile c-arm system [1] and a visual planar marker pattern. thus, we are able to produce a parallax-free panoramic x-ray image that preserves the property of linear perspective projection. we additionally implement a method to reduce the error caused by varying intrinsic parameters of c-arm x-ray imaging. the results show that our proposed method can generate a parallax-free panoramic x-ray image, independent of the configuration of bone structures and without the requirement of a fronto-parallel setup or any overlap in the x-ray images. the resulting panoramic images have a negligible difference (below 2 pixels) in the overlap between two consecutive individual x-ray images and have a high visual quality, which promises suitability for intra-operative clinical applications in orthopedic and trauma surgery.
diffusion tensor field registration in the presence of uncertainty. we propose a novel method for deformable tensor---to---tensor registration of diffusion tensor imaging (dti) data. our registration method considers estimated diffusion tensors as normally distributed random variables whose covariance matrices describe uncertainties in the mean estimated tensor due to factors such as noise in diffusion weighted images (dwis), tissue diffusion properties, and experimental design. the dissimilarity between distributions of tensors in two different voxels is computed using the kullback-leibler divergence to drive a deformable registration process, which is not only affected by principal diffusivities and principal directions, but also the underlying dwi properties. we in general do not assume the positive definite nature of the tensor space given the pervasive influence of noise and other factors. results indicate that the proposed metric weights voxels more heavily whose diffusion tensors are estimated with greater certainty and exhibit anisotropic diffusion behavior thus, intrinsically favoring coherent white matter regions whose tensors are estimated with high confidence.
biomechanically constrained groupwise us to ct registration of the lumbar spine. registration of intraoperative ultrasound (us) with preoperative computed tomography (ct) data for interventional guidance is a subject of immense interest, particularly for percutaneous spinal injections. we propose a biomechanically constrained group-wise registration of us to ct images of the lumbar spine. each vertebra in ct is treated as a sub-volume and transformed individually. the sub-volumes are then reconstructed into a single volume. the algorithm simulates an us image from the ct data at each iteration of the registration. this simulated us image is used to calculate an intensity based similarity metric with the real us image. a biomechanical model is used to constrain the displacement of the vertebrae relative to one another. covariance matrix adaption - evolution strategy (cma-es) is utilized as the optimization strategy. validation is performed on ct and us images from a phantom designed to preserve realistic curvatures of the spine. the technique is able to register initial misalignments of up to 20mm with a success rate of 82%, and those of up to 10mm with a success rate of 98.6%.
temporal estimation of the 3d guide-wire position using 2d x-ray images. we present a method for realtime online 3d reconstruction of a guide-wire or catheter using 2d x-ray images, which do not have to be recorded from different viewpoints. no special catheters or sensors are needed. given a 3d patient data set and the projection parameters, we use recursive probability density propagation to estimate a probability distribution of the current positions of guide-wire parts. based on this distribution, we extract the optimal guide-wire position using regularization techniques. we describe the guide-wire position by a uniform cubic b-spline. experiments on simulated and phantom data demonstrate the high accuracy and robustness of our approach.
a robust solution to multi-modal image registration by combining mutual information with multi-scale derivatives. in this paper we present a novel method for performing image registration of different modalities. mutual information (mi) is an established method for performing such registration. however, it is recognised that standard mi is not without some problems, in particular it does not utilise spatial information within the images. various modifications have been proposed to resolve this, however these only offer slight improvement to the accuracy of registration. we present feature neighbourhood mutual information (fnmi) that combines both image structure and spatial neighbourhood information which is efficiently incorporated into mutual information by approximating the joint distribution with a covariance matrix (c.f. russakoff's regional mutual information). results show that our approach offers a very high level of accuracy that improves greatly on previous methods. in comparison to regional mi, our method also improves runtime for more demanding registration problems where a higher neighbourhood radius is required. we demonstrate our method using retinal fundus photographs and scanning laser ophthalmoscopy images, two modalities that have received little attention in registration literature. registration of these images would improve accuracy when performing demarcation of the optic nerve head for detecting such diseases as glaucoma.
groupwise registration and atlas construction of 4th-order tensor fields using the r riemannian metric. registration of diffusion-weighted mr images (dw-mri) can be achieved by registering the corresponding 2nd-order diffusion tensor images (dti). however, it has been shown that higher-order diffusion tensors (e.g. order-4) outperform the traditional dti in approximating complex fiber structures such as fiber crossings. in this paper we present a novel method for unbiased group-wise non-rigid registration and atlas construction of 4th-order diffusion tensor fields. to the best of our knowledge there is no other existing method to achieve this task. first we define a metric on the space of positive-valued functions based on the riemannian metric of real positive numbers (denoted by r + ). then, we use this metric in a novel functional minimization method for non-rigid 4th-order tensor field registration. we define a cost function that accounts for the 4th-order tensor re-orientation during the registration process and has analytic derivatives with respect to the transformation parameters. finally, the tensor field atlas is computed as the minimizer of the variance defined using the riemannian metric. we quantitatively compare the proposed method with other techniques that register scalar-valued or diffusion tensor (rank-2) representations of the dwmri.
time-of-flight 3-d endoscopy. this paper describes the first accomplishment of the time-of-flight (tof) measurement principle via endoscope optics. the applicability of the approach is verified by in-vitro experiments. off-the-shelf tof camera sensors enable the per-pixel, on-chip, real-time, marker-less acquisition of distance information. the transfer of the emerging tof measurement technique to endoscope optics is the basis for a new generation of tof rigid or flexible 3-d endoscopes. no modification of the endoscope optic itself is necessary as only an enhancement of illumination unit and image sensors is necessary. the major contribution of this paper is threefold: first, the accomplishment of the tof measurement principle via endoscope optics; second, the development and validation of a complete calibration and post-processing routine; third, accomplishment of extensive in-vitro experiments. currently, a depth measurement precision of 0.89 mm at 20 fps with 3072 3-d points is achieved.
prediction of the repair surface over cartilage defects: a comparison of three methods in a sheep model. defects in articular cartilage can be repaired through osteochondral transplantation (mosaic arthroplasty), where osteochondral plugs from non-weight-bearing areas of the joint are transferred to the defect site. incongruity between the plug surface and the adjacent cartilage results in increased contact pressures and poorer outcomes. we compare three methods to predict the desired repair surface for use in computer-assisted mosaic arthroplasty: manual estimation, a cubic spline surface, and a statistical shape atlas of the knee. the cubic spline was found to most accurately match the pre-impact cartilage surface; the atlas was found to match least accurately.
think global, act local; projectome estimation with bluematter. estimating the complete set of white matter fascicles (the projectome) from diffusion data requires evaluating an enormous number of potential pathways; consequently, most algorithms use computationally efficient greedy methods to search for pathways. the limitation of this approach is that critical global parameters - such as data prediction error and white matter volume conservation - are not taken into account. we describe bluematter, a parallel algorithm for global projectome evaluation, which uniquely accounts for global prediction error and volume conservation. leveraging the bluegene/l supercomputing architecture, bluematter explores a massive database of 180 billion candidate fascicles. the candidates are derived from several sources, including atlases and mutliple tractography algorithms. using bluematter we created the highest resolution, volume-conserved projectome of the human brain.
prostate biopsy assistance system with gland deformation estimation for enhanced precision. computer-assisted prostate biopsies became a very active research area during the last years. prostate tracking makes it possible to overcome several drawbacks of the current standard transrectal ultrasound (trus) biopsy procedure, namely the insufficient targeting accuracy which may lead to a biopsy distribution of poor quality, the very approximate knowledge about the actual location of the sampled tissues which makes it difficult to implement focal therapy strategies based on biopsy results, and finally the difficulty to precisely reach non-ultrasound (us) targets stemming from different modalities, statistical atlases or previous biopsy series. the prostate tracking systems presented so far are limited to rigid transformation tracking. however, the gland can get considerably deformed during the intervention because of us probe pressure and patient movements. we propose to use 3d us combined with image-based elastic registration to estimate these deformations. a fast elastic registration algorithm that copes with the frequently occurring us shadows is presented. a patient cohort study was performed, which yielded a statistically significant in-vivo accuracy of 0.83±0.54mm.
statistically deformable 2d/3d registration for accurate determination of post-operative cup orientation from single standard x-ray radiograph. the widely used procedure of evaluation of cup orientation following total hip arthroplasty using single standard anteroposterior (ap) radiograph is known inaccurate, largely due to the wide variability in individual pelvic orientation relative to x-ray plate. 2d/3d rigid image registration methods have been introduced for an accurate determination of the post-operative cup alignment with respect to an anatomical reference extracted from the ct data. although encouraging results have been reported, their extensive usage in clinical routine is still limited. this may be explained by their requirement of a cad model of the prosthesis, which is often difficult to be organized from the manufacturer due to the proprietary issue, and by their requirement of a pre-operative ct scan, which is not available for most retrospective studies. to address these issues, we developed and validated a statistically deformable 2d/3d registration approach for accurate determination of post-operative cup orientation. no cad model and pre-operative ct data is required any more. quantitative and qualitative results evaluated on cadaveric and clinical datasets are given, which indicate the validity of the approach.
multi-modal registration based ultrasound mosaicing. recent us systems allow the real-time acquisition of volume data, either by freehand 3d techniques or novel transducer hardware. however, the acquisition of large volumes is limited by the field of view of the us transducer and anatomical scanning windows into the patient. mosaicing of several 3d us scans has been proposed to generate large us volumes. still, us imaging specific characteristics and artifacts make it challenging to create high quality mosaics. for many clinical cases, especially interventions, additional high quality ct data is available. in this paper we present a novel multi-variate, multi-modal 3d us registration and mosaicing approach, which reduces the effects of ultrasound imaging artifacts on mosaic quality, by incorporating information from co-registered ct.
single fiber optical coherence tomography microsurgical instruments for computer and robot-assisted retinal surgery. we present initial prototype and preliminary experimental demonstration of a new class of microsurgical instruments that incorporate common path optical coherence tomography (cp-oct) capabilities. these instruments may be used freehand or with robotic assistance. we describe a prototype 25 gauge microsurgical pick incorporating a single 125 (m diameter optical fiber interfaced to a fourier domain cp-oct system developed in our laboratory. for initial experimentation, we have interfaced this instrument with an extremely precise, cooperatively controlled robot. we describe the tool, system design, and demonstration of three control methods on simple phantom models: 1) enforce ment of safety constraints preventing unintentional collisions of the instrument with the retinal surface; 2) the ability to scan the probe across a surface while maintaining a constant distance offset; and 3) the ability to place the pick over a subsurface target identified in a scan and then penetrate the surface to hit the target.
joint segmentation of image ensembles via latent atlases. spatial priors, such as probabilistic atlases, play an important role in mri segmentation. however, the availability of comprehensive, reliable and suitable manual segmentations for atlas construction is limited. we therefore propose a joint segmentation of corresponding, aligned structures in the entire population that does not require a probability atlas. instead, a latent atlas, initialized by a single manual segmentation, is inferred from the evolving segmentations of the ensemble. the proposed method is based on probabilistic principles but is solved using partial differential equations (pdes) and energy minimization criteria. we evaluate the method by segmenting 50 brain mr volumes. segmentation accuracy for cortical and subcortical structures approaches the quality of state-of-the-art atlas-based segmentation results, suggesting that the latent atlas method is a reasonable alternative when existing atlases are not compatible with the data to be processed.
endoscopic orientation correction. an open problem in endoscopic surgery (especially with flexible endoscopes) is the absence of a stable horizon in endoscopic images. with our "endorientation" approach image rotation correction, even in non-rigid endoscopic surgery (particularly notes), can be realized with a tiny mems tri-axial inertial sensor placed on the tip of an endoscope. it measures the impact of gravity on each of the three orthogonal accelerometer axes. after an initial calibration and filtering of these three values the rotation angle is estimated directly. achievable repetition rate is above the usual endoscopic video frame rate of 30hz; accuracy is about one degree. the image rotation is performed in real-time by digitally rotating the analog endoscopic video signal. improvements and benefits have been evaluated in animal studies: coordination of different instruments and estimation of tissue behavior regarding gravity related deformation and movement was rated to be much more intuitive with a stable horizon on endoscopic images.
asymmetric image-template registration. a natural requirement in pairwise image registration is that the resulting deformation is independent of the order of the images. this constraint is typically achieved via a symmetric cost function and has been shown to reduce the effects of local optima. consequently, symmetric registration has been successfully applied to pairwise image registration as well as the spatial alignment of individual images with a template. however, recent work has shown that the relationship between an image and a template is fundamentally asymmetric. in this paper, we develop a method that reconciles the practical advantages of symmetric registration with the asymmetric nature of image-template registration by adding a simple correction factor to the symmetric cost function. we instantiate our model within a log-domain diffeomorphic registration framework. our experiments show exploiting the asymmetry in image-template registration improves alignment in the image coordinates.
fast tensor image morphing for elastic registration. we propose a novel algorithm, called fast tensor image morphing for elastic registration or f-timer. f-timer leverages multiscale tensor regional distributions and local boundaries for hierarchically driving deformable matching of tensor image volumes. registration is achieved by aligning a set of automatically determined structural landmarks, via solving a soft correspondence problem. based on the estimated correspondences, thin-plate splines are employed to generate a smooth, topology preserving, and dense transformation, and to avoid arbitrary mapping of non-landmark voxels. to mitigate the problem of local minima, which is common in the estimation of high dimensional transformations, we employ a hierarchical strategy where a small subset of voxels with more distinctive attribute vectors are first deployed as landmarks to estimate a relatively robust low-degrees-of-freedom transformation. as the registration progresses, an increasing number of voxels are permitted to participate in refining the correspondence matching. a scheme as such allows less conservative progression of the correspondence matching towards the optimal solution, and hence results in a faster matching speed. results indicate that better accuracy can be achieved by f-timer, compared with other deformable registration algorithms [1, 2], with significantly reduced computation time cost of 4---14 folds.
estimating orientation distribution functions with probability density constraints and spatial regularity. high angular resolution diffusion imaging (hardi) has become an important magnetic resonance technique for in vivo imaging. current techniques for estimating the diffusion orientation distribution function (odf), i.e., the probability density function of water diffusion along any direction, do not enforce the estimated odf to be nonnegative or to sum up to one. very often this leads to an estimated odf which is not a proper probability density function. in addition, current methods do not enforce any spatial regularity of the data. in this paper, we propose an estimation method that naturally constrains the estimated odf to be a proper probability density function and regularizes this estimate using spatial information. by making use of the spherical harmonic representation, we pose the odf estimation problem as a convex optimization problem and propose a coordinate descent method that converges to the minimizer of the proposed cost function. we illustrate our approach with experiments on synthetic and real data.
bias of least squares approaches for diffusion tensor estimation from array coils in dt-mri. least squares (ls) and its weighted version are standard techniques to estimate the diffusion tensor (dt) from diffusion weighted images (dwi). they require to linearize the problem by computing the logarithm of the dwi. for the single-coil rician noise model it has been shown that this model does not introduce a significant bias, but for multiple array coils and parallel imaging, the noise cannot longer be modeled as rician. as a result the validity of ls approaches is not assured. an analytical study of noise statistics for a multiple coil system is carried out, together with the weighted ls formulation and noise analysis for this model. results show that the bias in the computation of the components of the dt may be comparable to their variance in many cases, stressing the importance of unbiased filtering previous to dt estimation.
closed-form jensen-renyi divergence for mixture of gaussians and applications to group-wise shape registration. in this paper, we propose a generalized group-wise non-rigid registration strategy for multiple unlabeled point-sets of unequal cardinality, with no bias toward any of the given point-sets. to quantify the divergence between the probability distributions --- specifically mixture of gaussians --- estimated from the given point sets, we use a recently developed information-theoretic measure called jensen-renyi (jr) divergence. we evaluate a closed-form jr divergence between multiple probabilistic representations for the general case where the mixture models differ in variance and the number of components. we derive the analytic gradient of the divergence measure with respect to the non-rigid registration parameters, and apply it to numerical optimization of the group-wise registration, leading to a computationally efficient and accurate algorithm. we validate our approach on synthetic data, and evaluate it on 3d cardiac shapes.
3-d respiratory motion compensation during ep procedures by image-based 3-d lasso catheter model generation and tracking. radio-frequency catheter ablation of the pulmonary veins attached to the left atrium is usually carried out under fluoroscopy guidance. two-dimensional x-ray navigation may involve overlay images derived from a static pre-operative 3-d volumetric data set to add anatomical details. however, respiratory motion may impair the utility of static overlay images for catheter navigation. we developed a system for image-based 3-d motion estimation and compensation as a solution to this problem for which no previous solution is yet known. it is based on 3-d catheter tracking involving 2-d/3-d registration. a biplane x-ray c-arm system is used to image a special circumferential (lasso) catheter from two directions. in the first step of the method, a 3-d model of the device is reconstructed. 3-d respiratory motion at the site of ablation is then estimated by tracking the reconstructed model in 3-d from biplane fluoroscopy. in our experiments, the circumferential catheter was tracked in 231 biplane fluoro frames (462 monoplane fluoro frames) with an average 2-d tracking error of 1.0 mm ± 0.5 mm.
cervical vertebrae tracking in video-fluoroscopy using the normalized gradient field. for patients with neck problems valuable functional and diagnostic information can be obtained from a fluoroscopy video of a flexion-extension movement of the cervical spine. in most cases physicians have to manually extract the vertebrae, making the analysis of these video sequences tedious and time consuming. in this paper we propose an automatic fast and precise method for tracking cervical vertebrae. our method relies only on a rough selection of template areas of each vertebra in a single frame of the video sequence. compared to existing automated methods, no contours need to be extracted and no vertebra segmentation is required. tracking is done with a normalized gradient field, using only the gradient orientations as features. experimental results show that the algorithm is robust and able to track the vertebrae accurately even if they are partially occluded or if a disc prosthesis is present.
improving pit-pattern classification of endoscopy images by a combination of experts. the diagnosis of colorectal cancer is usually supported by a staging system, such as the duke or tnm system. in this work we discuss computer---aided pit---pattern classification of surface structures observed during high---magnification colonoscopy in order to support dignity assessment of colonic polyps. this is considered a quite promising approach because it allows in vivo staging of colorectal lesions. since recent research work has shown that the characteristic surface structures of the colon mucosa exhibit texture characteristics, we employ a set of texture image features in the wavelet-domain and propose a novel classifier combination approach which is similar to a combination of experts. the experimental results of our work show superior classification performance compared to previous approaches on both a two-class (non-neoplastic vs. neoplastic) and a more complicated six-class (pit---pattern) classification problem.
wide-angle intraocular imaging and localization. vitreoretinal surgeries require accuracy and dexterity that is often beyond the capabilities of human surgeons. untethered robotic devices that can achieve the desired precision have been proposed, and localization information is required for their control. since the interior of the human eye is externally observable, vision can be used for their localization. in this paper we examine the effects of the human eye optics on imaging and localizing intraocular devices. we propose a method for wide-angle intraocular imaging and localization. we demonstrate accurate localization with experiments in a model eye.
in vivo oct coronary imaging augmented with stent reendothelialization score. the aim of this study is to automatically assess reendothelialization of stents at an accuracy of down to a few microns by analyzing endovascular optical coherence tomography (oct) sequences. vessel wall and struts are automatically detected and complete distance map is then computed from sparse distances measured between wall and struts by thin-plate spline (tps) interpolation. a reendothelialization score is mapped onto the geometry of the coronary artery segment. accuracy and robustness are increased by taking into account the inhomogeneity of datapoints and integrating in the same framework orthogonalized forward selection of support points, optimal selection of regularization parameters by generalized cross-validation (gcv) and rejection of detection outliers. the comparison against manual expert measurements for a phantom study and 12 in vivo stents demonstrates no significant discordance with variability of the order of the strut thickness.
non-rigid registration of high angular resolution diffusion images represented by gaussian mixture fields. in this paper, we present a novel algorithm for non-rigidly registering two high angular resolution diffusion weighted mris (hardi), each represented by a gaussian mixture field (gmf). we model the non-rigid warp by a thin-plate spline and formulate the registration problem as the minimization of the l2 distance between the two given gmfs. the key mathematical contributions of this work are, (i) a closed form expression for the derivatives of this objective function with respect to the parameters of the registration and (ii) a novel and simpler re-orientation scheme based on an extension to the "preservation of principle directions" technique. we present results of our algorithm's performance on several synthetic and real hardi data sets.
statistical regularization of deformation fields for atlas-based segmentation of bone scintigraphy images. the construction and application of statistical models of deformations based on non-rigid image registration methods have gained recent popularity. this paper presents the application of such a model to restricting a general-purpose registration algorithm to anatomically plausible solutions. specifically, the morphon registration method is used for atlas-based segmentation of bone scintigraphy images. from a training set of 734 images, a model of characteristic deformation fields is built and used for regularizing the registration of 113 test images. results show that around 300 training images and 30 principal modes are sufficient for building a useful model. the segmentation succeeded in 106 of 113 test images.
task-optimal registration cost functions. in this paper, we propose a framework for learning the parameters of registration cost functions --- such as the tradeoff between the regularization and image similiarity term --- with respect to a specific task. assuming the existence of labeled training data, we specialize the framework for the task of localizing hidden labels via image registration. we learn the parameters of the weighted sum of squared differences (wssd) image similarity term that are optimal for the localization of brodmann areas (bas) in a new subject based on cortical geometry. we demonstrate state-of-the-art localization of v1, v2, ba44 and ba45.
novel endoscope system with plasma flushing for off-pump cardiac surgery. the purpose of this study is to develop a new endoscope for performing simple surgical tasks inside a cardiac atrium/chamber filled with blood, i.e., for performing "off-pump" cardiac surgeries. in general, it is very difficult to observe the inner wall of the vessels containing circulating blood because the light from the endoscope is scattered by the red blood cells. "plasma flushing" performed using the separator system is developed to observe the inner side of the heart filled with blood and to remove blood cells from the front of the endoscope tip. the system was used in in vitro quantitative measurement of the device performance and in vivo experiments on a swine. in these experiments, we successfully obtained high-resolution images of the interior of the heart during off-pump surgery.
a non-rigid registration method for serial microct mouse hindlimb images. we present a new method for the non-rigid registration of serial mouse microct images which undergo potentially large changes in the positions of the legs due to articulation. while non-rigid registration methods have been extensively used in the evaluation of individual organs, application in whole body imaging has been limited, primarily because the scale of possible displacements and deformations is large resulting in poor convergence of most methods. our method is based on the extended demons algorithm that uses a level-set representation of the mouse skin and skeleton as an input, and composed of three steps reflecting the natural physical movements of bony structures. we applied our method to the registration of serial microct mouse images demonstrating encouraging performances as compared to competitive techniques.
a combined surface and volumetric registration (savor) framework to study cortical biomarkers and volumetric imaging data. constructing a one to one correspondence between whole brain mr image scans is a problem of critical importance in neuroimaging analyses. we present a framework to combine the strength of both surface-based and volumetric-based analyses for consistent, bijective data transfer between brain coordinate systems.
gyral folding pattern analysis via surface profiling. human cortical folding pattern has been studied for decades. this paper proposes a gyrus scale folding pattern analysis technique via cortical surface profiling. firstly, we sample the cortical surface into 2d profiles and model them using power function. this step provides both the flexibility of representing arbitrary shape by profiling and the compactness of representing shape by parametric modeling. secondly, based on the estimated model parameters, we extract affine-invariant features on the cortical surface and apply the affinity propagation clustering algorithm to parcellate the cortex into regions with different shape patterns. finally, a second-round surface profiling is performed on the parcellated cortical regions, and the number of hinges is detected to describe the gyral folding pattern. experiments demonstrate that our method could successfully classify human gyri into 2-hinge, 3-hinge and 4-hinge gyri. the proposed method has the potential to significantly contribute to automatic segmentation and recognition of cortical gyri.
robust medical images segmentation using learned shape and appearance models. we propose a novel parametric deformable model controlled by shape and visual appearance priors learned from a training subset of co-aligned medical images of goal objects. the shape prior is derived from a linear combination of vectors of distances between the training boundaries and their common centroid. the appearance prior considers gray levels within each training boundary as a sample of a markov-gibbs random field with pairwise interaction. spatially homogeneous interaction geometry and gibbs potentials are analytically estimated from the training data. to accurately separate a goal object from an arbitrary background, empirical marginal gray level distributions inside and outside of the boundary are modeled with adaptive linear combinations of discrete gaussians (lcdg). due to the analytical shape and appearance priors and a simple expectation-maximization procedure for getting the object and background lcdg, our segmentation is considerably faster than with most of the known geometric and parametric models. experiments with various goal images confirm the robustness, accuracy, and speed of our approach.
mr to ultrasound image registration for guiding prostate biopsy and interventions. a method is described for registering preoperative magnetic resonance (mr) to intraoperative transrectal ultrasound (trus) images of the prostate gland. a statistical motion model (smm) of the prostate is first built using training data provided by biomechanical simulations of the motion of a patient-specific finite element model, derived from a preoperative mr image. the smm is then registered to a 3d trus image by maximising the likelihood of the shape of an smm instance given a voxel-intensity-based feature, which represents an estimate of normal vector at the surface of the prostate gland. using data acquired from 7 patients, the accuracy of registering t2 mr to 3d trus images was evaluated using anatomical landmarks inside the gland. the results show that the proposed registration method has a root-mean-square target registration error of 2.66 mm.
image guidance for spinal facet injections using tracked ultrasound. anesthetic nerve blocks are a common therapy performed in hospitals around the world to alleviate acute and chronic pain. tracking systems have shown considerable promise in other forms of therapy, but little has been done to apply this technology in the field of anesthesia. we are developing a guidance system for combining tracked needles with non-invasive ultrasound (us) and patient-specific geometric models. in experiments with phantoms two augmented reality (ar) guidance systems were compared to the exclusive use of us for lumbar facet injection therapy. anesthetists and anesthesia residents were able to place needles within 0.57mm of the intended targets using our ar systems compared to 5.77 mm using us alone. a preliminary cadaver study demonstrated the system was able to accurately place radio opaque dye on targets. the combination of real time us with tracked tools and ar guidance has the potential to replace ct and fluoroscopic guidance, thus reducing radiation dose to patients and clinicians, as well as reducing health care costs.
tracked regularized ultrasound elastography for targeting breast radiotherapy. tracked ultrasound elastography can be used for guidance in partial breast radiotherapy by visualizing the hard scar tissue around the lumpectomy cavity. for clinical success, the elastography method needs to be robust to the sources of decorrelation between ultrasound images, specifically fluid motions inside the cavity, change of the appearance of speckles caused by compression or physiologic motions, and out-of-plane motion of the probe. in this paper, we present a novel elastography technique that is based on analytic minimization of a regularized cost function. the cost function incorporates similarity of rf data intensity and displacement continuity, making the method robust to small decorrelations present throughout the image. we also exploit techniques from robust statistics to make the method resistant to large decorrelations caused by sources such as fluid motion. the analytic displacement estimation works in real-time. moreover, the tracked data, used for targeting the radiotherapy, is exploited for discarding frames with excessive out-of-plane motion. simulation, phantom and patient results are presented.
a method to correct for brain shift when building electrophysiological atlases for deep brain stimulation (dbs) surgery. to help surgeons to pre-operatively select the target location for dbs electrodes, functional atlases based on intra-operatively acquired data have been created in the past. recently, many groups have reported on the occurrence of brain shift in stereotactic surgery and its impact on the procedure but not on the creation of such atlases. due to brain shift, the pre- and intra-operative coordinates of anatomic structures are different. when building large population atlases, which rely on pre-operative images for normalization purposes, it is thus necessary to correct for this difference. in this paper, we propose a method to achieve this. we show evidence that electrophysiological maps built using corrected and uncorrected data are different and that the maps created using shift-corrected data correlate better than those created using uncorrected data with the final position of the implant. these findings suggest that brain-shift correction of intra-operatively recorded data is feasible for the construction of accurate shift-corrected electrophysiological atlases.
expertise modeling for automated planning of acetabular cup in total hip arthroplasty using combined bone and implant statistical atlases. intraoperative robotic and computer-guided assistances are now commonly used in total hip arthroplasty (tha) for accurate execution of the preoperative plan. although the preoperative plan to be accurately executed is critical, it is still interactively prepared in a time-consuming and subjective manner. in this paper, atlas-based approach to automated surgical planning of the acetabular cup in tha is described to stabilize its quality as well as reduce its time-consuming nature. surgeon's expertise is embedded in two types of statistical atlases, which are constructed from training datasets of ct-based 3d plans prepared by experienced surgeons. one is a statistical shape model which encodes global spatial relationships between the patient anatomy and implant. the other is the statistical map of residual bone thickness on the implant surface, which encodes local spatial constraints of the anatomy and implant. given the 3d pelvis shape of the patient, we formulate a procedure to determine the best size and position of the acetabular cup which satisfy the constraints derived from the two statistical atlases. we validated the proposed planning method by retrospective study using the datasets which were actually used in the tha surgery.
a novel intensity similarity metric with soft spatial constraint for a deformable image registration problem in radiation therapy. in this paper we propose a novel similarity metric and a method for deformable registration of two images for a specific clinical application. the basic assumption in almost all deformable registration approaches is that there exist explicit correspondences between pixels across the two images. this principle is used to design image (dis)similarity metrics, such as sum of squared differences (ssd) or mutual information (mi). this assumption is strongly violated, for instance, within specific regions of images from abdominal or pelvic section of a patient taken at two different time points. nevertheless, in some clinical applications, it is required to compute a smooth deformation field for all the regions within the image including the boundaries of such regions. in this paper, we propose a deformable registration method, which utilizes a priori intensity distributions of the regions delineated on one of the images to devise a new similarity measure that varies across regions of the image to establish a smooth and robust deformation field. we present validation results of the proposed method in mapping bladder, prostate, and rectum contours of computer tomography (ct) volumes of 10 patients taken for prostate cancer radiotherapy treatment planning and verification.
parcellation of fmri datasets with ica and pls-a data driven approach. inter-subject parcellation of functional magnetic resonance imaging (fmri) data based on a standard general linear model (glm) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fmri. however, for all its appeal, a glm-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of hemodynamic response function (hrf) and task-related signal changes, or about the subject behaviour during the task.in this paper, we introduce a data-driven version of the spectral clustering parcellation, based on independent component analysis (ica) and partial least squares (pls) instead of the glm. first, a number of independent components are automatically selected. seed voxels are then obtained from the associated ica maps and we compute the pls latent variables between the fmri signal of the seed voxels (which covers regional variations of the hrf) and the principal components of the signal across all voxels. finally, we parcellate all subjects data with a spectral clustering of the pls latent variables.we present results of the application of the proposed method on both single-subject and multi-subject fmri datasets. preliminary experimental results, evaluated with intra-parcel variance of glm t-values and pls derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over glm based techniques.
correcting motion artifacts in retinal spectral domain optical coherence tomography via image registration. spectral domain optical coherence tomography (sd-oct) is an important tool for the diagnosis of various retinal diseases. the measurements available from sd-oct volumes can be used to detect structural changes in glaucoma patients before the resulting vision loss becomes noticeable. eye movement during the imaging process corrupts the data, making measurements unreliable. we propose a method to correct for transverse motion artifacts in sd-oct volumes after scan acquisition by registering the volume to an instantaneous, and therefore artifact-free, reference image. our procedure corrects for smooth deformations resulting from ocular tremor and drift as well as the abrupt discontinuities in vessels resulting from microsaccades. we test our performance on 48 scans of healthy eyes and 116 scans of glaucomatous eyes, improving scan quality in 96% of healthy and 73% of glaucomatous eyes.
a fast alternative to computational fluid dynamics for high quality imaging of blood flow. obtaining detailed, patient-specific blood flow information would be very useful in detecting and monitoring cardio-vascular diseases. current approaches rely on computational fluid dynamics to achieve this; however, these are hardly usable in the daily clinical routine due to the required technical supervision and long computing times. we propose a fast measurement enhancement method that requires neither supervision nor long computation and it is the objective of this paper to evaluate its performance as compared to the state-of-the-art. to this end a large set of abdominal aortic bifurcation geometries was used to test this technique and the results were compared to measurements and numerical simulations. we find that this method is able to dramatically improve the quality of the measurement information, in particular the flow-derived quantities such as wall shear stress. additionally, good estimation of unmeasurable quantities such as pressure can be provided. we demonstrate that this approach is a practical and clinically feasible alternative to fully-blown, time-consuming, patient-specific flow simulations.
modeling adaptation effects in fmri analysis. the standard general linear model (glm) for rapid event-related fmri design protocols typically ignores reduction in hemodynamic responses in successive stimuli in a train due to incomplete recovery from the preceding stimuli. to capture this adaptation effect, we incorporate a region-specific adaptation model into glm. the model quantifies the rate of adaptation across brain regions, which is of interest in neuroscience. empirical evaluation of the proposed model demonstrates its potential to improve detection sensitivity. in the fmri experiments using visual and auditory stimuli, we observed that the adaptation effect is significantly stronger in the visual area than in the auditory area, suggesting that we must account for this effect to avoid bias in fmri detection.
two-tensor tractography using a constrained filter. we describe a technique to simultaneously estimate a weighted, positive-definite multi-tensor fiber model and perform tractography. existing techniques estimate the local fiber orientation at each voxel independently so there is no running knowledge of confidence in the estimated fiber model. we formulate fiber tracking as recursive estimation: at each step of tracing the fiber, the current estimate is guided by the previous. to do this we model the signal as a weighted mixture of gaussian tensors and perform tractography within a filter framework. starting from a seed point, each fiber is traced to its termination using an unscented kalman filter to simultaneously fit the local model and propagate in the most consistent direction. further, we modify the kalman filter to enforce model constraints, i.e. positive eigenvalues and convex weights. despite the presence of noise and uncertainty, this provides a causal estimate of the local structure at each point along the fiber. synthetic experiments demonstrate that this approach significantly improves the angular resolution at crossings and branchings while consistently estimating the mixture weights. in vivo experiments confirm the ability to trace out fibers in areas known to contain such crossing and branching while providing inherent path regularization.
iterative co-linearity filtering and parameterization of fiber tracts in the entire cingulum. we present a method for the fully automated extraction of the cingulum using diffusion tensor imaging (dti) data. we perform whole-brain tractography and initialize tract selection in the cingulum with a registered dti atlas. tracts are parameterized from which tract co-linearity is derived. the tract set, filtered on the basis of co-linearity with the cingulum shape, yields an improved segmentation of the cingulum and is subsequently optimized in an iterative fashion to further improve the tract selection. we evaluate the method using a large dti database of 500 subjects from the general population and show robust extraction of tracts in the entire cingulate bundle in both hemispheres. we demonstrate the use of the extracted fiber-tracts to compare left and right cingulate bundles. our asymmetry analysis shows a higher fractional anisotropy in the left anterior part of the cingulum compared to the right side, and the opposite effect in the posterior part.
nibart: a new interval based algebraic reconstruction technique for error quantification of emission tomography images. this article presents a new algebraic method for reconstructing emission tomography images. this approach is mostly an interval extension of the conventional sirt algorithm. one of the main characteristic of our approach is that the reconstructed activity associated with each pixel of the reconstructed image is an interval whose length can be considered as an estimate of the impact of the random variation of the measured activity on the reconstructed image. this work aims at investigating a new methodological concept for a reliable and robust quantification of reconstructed activities in scintigraphic images.
dual tensor atlas generation based on a cohort of coregistered non-hardi datasets. we propose a method to create a dual tensor atlas from multiple coregistered non-hardi datasets. increased angular resolution is ensured by random variations of subject positioning in the scanner and different local rotations applied during coregistration resulting in dispersed gradient directions. simulations incorporating residual coregistration misalignments show that using 10 subjects should already double the angular resolution, even at a relatively low b-value of b = 1000 smm¿ 2. commisural corpus callosum fibers reconstructed by our method closely approximated those found in a hardi dataset.
system design of a hand-held mobile robot for craniotomy. this contribution reports the development and initial testing of a mobile robot system for surgical craniotomy, the craniostar. a kinematic system based on a unicycle robot is analysed to provide local positioning through two spiked wheels gripping directly onto a patients skull. a control system based on a shared control system between both the surgeon and robot is employed in a hand-held design that is tested initially on plastic phantom and swine skulls. results indicate that the system has substantially lower risk than present robotically assisted craniotomies, and despite being a hand-held mobile robot, the craniostar is still capable of sub-millimetre accuracy in tracking along a trajectory and thus achieving an accurate transfer of pre-surgical plan to the operating room procedure, without the large impact of current medical robots based on modified industrial robots.
-brush: a gaze-contingent virtual paintbrush for dense 3d reconstruction in robotic assisted surgery. with increasing demand on intra-operative navigation and motion compensation during robotic assisted minimally invasive surgery, real-time 3d deformation recovery remains a central problem. currently the majority of existing methods rely on salient features, where the inherent paucity of distinctive landmarks implies either a semi-dense reconstruction or the use of strong geometrical constraints. in this study, we propose a gaze-contingent depth reconstruction scheme by integrating human perception with semi-dense stereo and p-q based shading information. depth inference is carried out in real-time through a novel application of bayesian chains without smoothness priors. the practical value of the scheme is highlighted by detailed validation using a beating heart phantom model with known geometry to verify the performance of gaze-contingent 3d surface reconstruction and deformation recovery.
hybrid spline-based multimodal registration using local measures for joint entropy and mutual information. we introduce a new hybrid approach for spline-based elastic registration of multimodal medical images. the approach uses point landmarks as well as intensity information based on local analytic measures for joint entropy and mutual information. the information-theoretic similarity measures are computationally efficient and can be optimized independently for each voxel. we have applied our approach to synthetic images, brain phantom images, as well as clinically relevant multimodal medical images. we also compared our measures with previous measures.
biopsy site re-localisation based on the computation of epipolar lines from two previous endoscopic images. tracking biopsy sites in endoscopic images can be useful to provide a visual aid for the guidance of surgical tools, for example when endoscopic guided biopsy is required. a new method for re-localisation of these sites is presented in this paper. it makes use of epipolar geometry properties between three images of the same site observed from different viewpoints with an endoscope. two epipolar lines are derived from the two first images in the third image where the site needs to be re-localised. their intersection corresponds to the location of the biopsy site. this method was tested with gastroscopic data from 2 patients with 9 series of three images of the oesophagus. the re-localisation error was estimated at less than 1.5 millimetres by a clinical endoscopist, which is sufficient for most clinical endoscopic applications.
multivariate tensor-based brain anatomical surface morphometry via holomorphic one-forms. here we introduce multivariate tensor-based surface morphometry using holomorphic one-forms to study brain anatomy. we computed new statistics from the riemannian metric tensors that retain the full information in the deformation tensor fields. we introduce two different holomorphic one-forms that induce different surface conformal parameterizations. we applied this framework to 3d mri data to analyze hippocampal surface morphometry in alzheimer's disease (ad; 26 subjects), lateral ventricular surface morphometry in hiv/aids (19 subjects) and cortical surface morphometry in williams syndrome (ws; 80 subjects). experimental results demonstrated that our method powerfully detected brain surface abnormalities. multivariate statistics on the local tensors outperformed other tbm methods including analysis of the jacobian determinant, the largest eigenvalue, or the pair of eigenvalues, of the surface jacobian matrix.
attribute vector guided groupwise registration. groupwise registration has been recently introduced for simultaneous registration of a group of images with the goal of constructing an unbiased atlas. to this end, direct application of information-theoretic entropy measures on image intensity has achieved various successes. however, simplistic voxelwise utilization of image intensity often neglects important contextual information, which can be provided by more comprehensive geometric and statistical features. in this paper, we employ attribute vectors, instead of image intensities, to guide groupwise registration. in particular, for each voxel, the attribute vector is computed from its multiple-scale neighborhoods to capture geometric information at different scales. moreover, the probability density function (pdf) of each attribute in the vector is then estimated from the local neighborhood, providing a statistical summary of the underlying anatomical structure. for the purpose of registration, jensen-shannon (js) divergence is used to measure the pdf dissimilarity of each attribute at corresponding locations of different individual images. by minimizing the overall js divergence in the whole image space and estimating the deformation field of each image simultaneously, we can eventually register all images and build an unbiased atlas. experimental results indicate that our method yields better registration quality, compared with a popular groupwise registration method.
local white matter geometry indices from diffusion tensor gradients. we introduce a framework for computing geometrical properties of white matter fibres directly from diffusion tensor fields. the key idea is to isolate the portion of the gradient of the tensor field corresponding to local variation in tensor orientation, and to project it onto a coordinate frame of tensor eigenvectors. the resulting eigenframe-centered representation makes it possible to define scalar geometrical measures that describe the underlying white matter fibres, directly from the diffusion tensor field and its gradient, without requiring prior tractography. we define two new scalar measures of (1) fibre dispersion and (2) fibre curving, and we demonstrate them on synthetic and in-vivo datasets. finally, we illustrate their applicability in a group study on schizophrenia.
a general pde-framework for registration of contrast enhanced images. this paper presents a general pde-framework for registration of contrast enhanced images. the approach directly applies the idea of separating the contrast enhancement term from the images in the regularization terms. in our formulation, we stay consistent with existing non-parametric image registration techniques, however, we carry an additional contrast enhancement term throughout. a mathematically rigorous approach is pursued which can exploit various forms of regularization. in this paper, our experiments are built based on diffusion regularization for both contrast enhancement and the deformation field.
robust extrapolation scheme for fast estimation of 3d ising field partition functions: application to within-subject fmri data analysis. in this paper, we present a fast numerical scheme to estimate partition functions (pf) of 3d ising fields. our strategy is applied to the context of the joint detection-estimation of brain activity from functional magnetic resonance imaging (fmri) data, where the goal is to automatically recover activated regions and estimate region-dependent hemodynamic filters. for any region, a specific binary markov random field may embody spatial correlation over the hidden states of the voxels by modeling whether they are activated or not. to make this spatial regularization fully adaptive, our approach is first based upon a classical path-sampling method to approximate a small subset of reference pfs corresponding to prespecified regions. then, the proposed extrapolation method allows us to approximate the pfs associated with the ising fields defined over the remaining brain regions. in comparison with preexisting approaches, our method is robust to topological inhomogeneities in the definition of the reference regions. as a result, it strongly alleviates the computational burden and makes spatially adaptive regularization of whole brain fmri datasets feasible.
slipping objects in image registration: improved motion field estimation with direction-dependent regularization. the computation of accurate motion fields is a crucial aspect in 4d medical imaging. it is usually done using a non-linear registration without further modeling of physiological motion properties. however, a globally homogeneous smoothing (regularization) of the motion field during the registration process can contradict the characteristics of motion dynamics. this is particularly the case when two organs slip along each other which leads to discontinuities in the motion field. in this paper, we present a diffusion-based model for incorporating physiological knowledge in image registration. by decoupling normal- and tangential-directed smoothing, we are able to estimate slipping motion at the organ borders while ensuring smooth motion fields in the inside and preventing gaps to arise in the field. we evaluate our model focusing on the estimation of respiratory lung motion. by accounting for the discontinuous motion of visceral and parietal pleurae, we are able to show a significant increase of registration accuracy with respect to the target registration error (tre).
evaluation of 4d-ct lung registration. non-rigid registration accuracy assessment is typically performed by evaluating the target registration error at manually placed landmarks. for 4d-ct lung data, we compare two sets of landmark distributions: a smaller set primarily defined on vessel bifurcations as commonly described in the literature and a larger set being well-distributed throughout the lung volume. for six different registration schemes (three in-house schemes and three schemes frequently used by the community) the landmark error is evaluated and found to depend significantly on the distribution of the landmarks. in particular, lung regions near to the pleura show a target registration error three times larger than near-mediastinal regions. while the inter-method variability on the landmark positions is rather small, the methods show discriminating differences with respect to consistency and local volume change. in conclusion, both a well-distributed set of landmarks and a deformation vector field analysis are necessary for reliable non-rigid registration accuracy assessment.
bayesian maximal paths for coronary artery segmentation from 3d ct angiograms. we propose a recursive bayesian model for the delineation of coronary arteries from 3d ct angiograms (cardiac cta) and discuss the use of discrete minimal path techniques as an efficient optimization scheme for the propagation of model realizations on a discrete graph. design issues such as the definition of a suitable accumulative metric are analyzed in the context of our probabilistic formulation.our approach jointly optimizes the vascular centerline and associated radius on a 4d space+scale graph. it employs a simple heuristic scheme to dynamically limit scale-space exploration for increased computational performance. it incorporates prior knowledge on radius variations and derives the local data likelihood from a multiscale, oriented gradient flux-based feature. from minimal cost path techniques, it inherits practical properties such as computational efficiency and workflow versatility. we quantitatively evaluated a two-point interactive implementation on a large and varied cardiac cta database. additionally, results from the rotterdam coronary artery algorithm evaluation framework are provided for comparison with existing techniques. the scores obtained are excellent (97.5% average overlap with ground truth delineated by experts) and demonstrate the high potential of the method in terms of robustness to anomalies and poor image quality.
a spatio-temporal atlas of the human fetal brain with application to tissue segmentation. modeling and analysis of mr images of the early developing human brain is a challenge because of the transient nature of different tissue classes during brain growth. to address this issue, a statistical model that can capture the spatial variation of structures over time is needed. here, we present an approach to building a spatio-temporal model of tissue distribution in the developing brain which can incorporate both developed tissues as well as transient tissue classes such as the germinal matrix by using constrained higher order polynomial models. this spatio-temporal model is created from a set of manual segmentations through groupwise registration and voxelwise non-linear modeling of tissue class membership, that allows us to represent the appearance as well as disappearance of the transient brain structures over time. applying this model to atlas-based segmentation, we generate age-specific tissue probability maps and use them to initialize an em segmentation of the fetal brain tissues. the approach is evaluated using clinical mr images of young fetuses with gestational ages ranging from 20.57 to 24.71 weeks. results indicate improvement in performance of atlas-based em segmentation provided by higher order temporal models that capture the variation of tissue occurrence over time.
a novel measure of fractional anisotropy based on the tensor distribution function. fractional anisotropy (fa), a very widely used measure of fiber integrity based on diffusion tensor imaging (dti), is a problematic concept as it is influenced by several quantities including the number of dominant fiber directions within each voxel, each fiber's anisotropy, and partial volume effects from neighboring gray matter. with high-angular resolution diffusion imaging (hardi) and the tensor distribution function (tdf), one can reconstruct multiple underlying fibers per voxel and their individual anisotropy measures by representing the diffusion profile as a probabilistic mixture of tensors. we found that fa, when compared with tdf-derived anisotropy measures, correlates poorly with individual fiber anisotropy, and may sub-optimally detect disease processes that affect myelination. by contrast, mean diffusivity (md) as defined in standard dti appears to be more accurate. overall, we argue that novel measures derived from the tdf approach may yield more sensitive and accurate information than dti-derived measures.
a statistical model of right ventricle in tetralogy of fallot for prediction of remodelling and therapy planning. patients with repaired tetralogy of fallot commonly suffer from chronic pulmonary valve regurgitations and extremely dilated right ventricle (rv). to reduce risk factors, new pulmonary valves must be re-implanted. however, establishing the best timing for re-intervention is a clinical challenge because of the large variability in rv shape and in pathology evolution. this study aims at quantifying the regional impacts of growth and regurgitations upon the end-diastolic rv anatomy. the ultimate goal is to determine, among clinical variables, predictors for the shape in order to build a statistical model that predicts rv remodelling. the proposed approach relies on a forward model based on currents and lddmm algorithm to estimate an unbiased template of 18 patients and the deformations towards each individual shape. cross-sectional multivariate analyses are carried out to assess the effects of body surface area, tricuspid and transpulmonary valve regurgitations upon the rv shape. the statistically significant deformation modes were found clinically relevant. canonical correlation analysis yielded a generative model that was successfully tested on two new patients.
a log-euclidean polyaffine registration for articulated structures in medical images. in this paper we generalize the log-euclidean polyaffine registration framework of arsigny et al. [1] to deal with articulated structures. this framework has very useful properties as it guarantees the invertibility of smooth geometric transformations. in articulated registration a skeleton model is defined for rigid structures such as bones. the final transformation is affine for the bones and elastic for other tissues in the image. we extend the arsigny el al.'s method to deal with locally-affine registration of pairs of wires. this enables the possibility of using this registration framework to deal with articulated structures. in this context, the design of the weighting functions, which merge the affine transformations defined for each pair of wires, has a great impact not only on the final result of the registration algorithm, but also on the invertibility of the global elastic transformation. several experiments, using both synthetic images and hand radiographs, are also presented.
combining multiple true 3d ultrasound image volumes through re-registration and rasterization. we present an accurate and efficient technique to combine and rasterize multiple 3d ultrasound (3dus) image volumes originally presented in spherical coordinates into a single, 3d cartesian image that uniformly samples the total field of view. to ensure the consistency of merged image content in overlapping regions, image re-registration was performed by maximizing mutual information (mi). the technique was applied to 22 3dus image volumes obtained during five neurosurgical patient cases. the computational cost of the approach increases linearly with the number of images involved (average time to combine and rasterize one pair of 3dus images was 1.5 sec). interpolation was approximately 20% more accurate in overlapping regions when re-registration was performed before rasterization and minimized feature loss and/or blurring that was evident without re-registration. in addition, we report the average translational (35.2 mm) and rotational (38.5 o ) capture ranges for the mi re-registration of two volumetric 3dus images. the technique is applicable in any clinical application in which volumetric true 3dus is acquired.
automatic robust medical image registration using a new democratic vector optimization approach with multiple measures. the registration of various data is a challenging task in medical image processing and a highly frequented area of research. most of the published approaches tend to fail sporadically on different data sets. this happens due to two major problems. first, local optimization strategies induce a high risk when optimizing nonconvex functions. second, similarity measures might fail if they are not suitable for the data. thus, researchers began to combine multiple measures by weighted sums. in this paper, we show severe limitations of such summation approaches. we address both issues by a gradient-based vector optimization algorithm that uses multiple similarity measures. it gathers context information from the iteration process to detect and suppress failing measures. the new approach is evaluated by experiments from the field of 2d-3d registration. besides its generic character with respect to arbitrary data, the main benefit is a highly robust iteration behavior, where even very poor initial guesses of the transform result in good solutions.
spatiotemporal atlas estimation for developmental delay detection in longitudinal datasets. we propose a new methodology to analyze the anatomical variability of a set of longitudinal data (population scanned at several ages). this method accounts not only for the usual 3d anatomical variability (geometry of structures), but also for possible changes in the dynamics of evolution of the structures. it does not require that subjects are scanned the same number of times or at the same ages. first a regression model infers a continuous evolution of shapes from a set of observations of the same subject. second, spatiotemporal registrations deform jointly (1) the geometry of the evolving structure via 3d deformations and (2) the dynamics of evolution via time change functions. third, we infer from a population a prototype scenario of evolution and its 4d variability. our method is used to analyze the morphological evolution of 2d profiles of hominids skulls and to analyze brain growth from amygdala of autistics, developmental delay and control children.
accelerating feature based registration using the johnson-lindenstrauss lemma. we introduce an efficient search strategy to substantially accelerate feature based registration. previous feature based registration algorithms often use truncated search strategies in order to achieve small computation times. our new accelerated search strategy is based on the realization that the search for corresponding features can be dramatically accelerated by utilizing johnson-lindenstrauss dimension reduction. order of magnitude calculations for the search strategy we propose here indicate that the algorithm proposed is more than a million times faster than previously utilized naive search strategies, and this advantage in speed is directly translated into an advantage in accuracy as the fast speed enables more comparisons to be made in the same amount of time. we describe the accelerated scheme together with a full complexity analysis. the registration algorithm was applied to large transmission electron microscopy (tem) images of neural ultrastructure. our experiments demonstrate that our algorithm enables alignment of tem images with increased accuracy and efficiency compared to previous algorithms.
personalized pulmonary trunk modeling for intervention planning and valve assessment estimated from ct data. pulmonary valve disease affects a significant portion of the global population and often occurs in conjunction with other heart dysfunctions. emerging interventional methods enable percutaneous pulmonary valve implantation, which constitute an alternative to open heart surgery. as minimal invasive procedures become common practice, imaging and non-invasive assessment techniques turn into key clinical tools. in this paper, we propose a novel approach for intervention planning as well as morphological and functional quantification of the pulmonary trunk and valve. an abstraction of the anatomic structures is represented through a four-dimensional, physiological model able to capture large pathological variation. a hierarchical estimation, based on robust learning methods, is applied to identify the patient-specific model parameters from volumetric ct scans. the algorithm involves detection of piecewise affine parameters, fast centre-line computation and local surface delineation. the estimated personalized model enables for efficient and precise quantification of function and morphology. this ability may have impact on the assessment and surgical interventions of the pulmonary valve and trunk. experiments performed on 50 cardiac computer tomography sequences demonstrated the average speed of 202 seconds and accuracy of 2.2mm for the proposed approach. an initial clinical validation yielded a significant correlation between model-based and expert measurements. to the best of our knowledge this is the first dynamic model of the pulmonary trunk and right ventricle outflow track estimated from ct data.
statistical detection of longitudinal changes between apparent diffusion coefficient images: application to multiple sclerosis. the automatic analysis of longitudinal changes between diffusion tensor imaging (dti) acquisitions is a promising tool for monitoring disease evolution. however, few works address this issue and existing methods are generally limited to the detection of changes between scalar images characterizing diffusion properties, such as fractional anisotropy or mean diffusivity, while richer information can be exploited from the whole set of apparent diffusion coefficient (adc) images that can be derived from a dti acquisition. in this paper, we present a general framework for detecting changes between two sets of adc images and we investigate the performance of four statistical tests. results are presented on both simulated and real data in the context of the follow-up of multiple sclerosis lesion evolution.
design and construction of a realistic dwi phantom for filtering performance assessment. a methodology to build a realistic phantom for the assessment of filtering performance in diffusion weighted images (dwi) is presented. from a real dwi data---set, a regularization process is carried out taking into account the diffusion model. this process drives to a model which accurately preserves the structural characteristics of actual dwi volumes, being in addition regular enough to be considered as a noise---free data---set and therefore to be used as a ground---truth. we compare our phantom with a kind of simplified phantoms commonly used in the literature (those based on homogeneous cross sections), concluding that the latter may introduce important biases in common quality measures used in the filtering performance assessment, and even drive to erroneous conclusions in the comparison of different filtering techniques.
towards guidance of electrophysiological procedures with real-time 3d intracardiac echocardiography fusion to c-arm ct. this paper describes a novel method for improving the navigation and guidance of devices and catheters in electrophysiology and interventional cardiology procedures using volumetric data fusion. the clinical workflow includes the acquisition and reconstruction of ct data from a c-arm x-ray angiographic system and the real-time acquisition of volumetric ultrasound datasets with a new intracardiac real-time 3d ultrasound catheter. mono- and multi-modal volumetric registration methods, as well as visualization modes, that are suitable for real-time fusion are described, which are the key components of this work. evaluation on phantom and in-vivo animal data shows that it is feasible to register and track the motion of real-time 3d intracardiac ultrasound in c-arm ct.
tensor-based analysis of genetic influences on brain integrity using dti in 100 twins. information from the full diffusion tensor (dt) was used to compute voxel-wise genetic contributions to brain fiber microstructure. first, we designed a new multivariate intraclass correlation formula in the log-euclidean framework [1]. we then analyzed used the full multivariate structure of the tensor in a multivariate version of a voxel-wise maximum-likelihood structural equation model (sem) that computes the variance contributions in the dts from genetic (a), common environmental (c) and unique environmental (e) factors. our algorithm was tested on dt images from 25 identical and 25 fraternal twin pairs. after linear and fluid registration to a mean template, we computed the intraclass correlation and falconer's heritability statistic for several scalar dt-derived measures and for the full multivariate tensors. covariance matrices were found from the dts, and inputted into sem. analyzing the full dt enhanced the detection of a and c effects. this approach should empower imaging genetics studies that use dti.
development of the ultra-miniaturized inertial measurement unit wb3 for objective skill analysis and assessment in neurosurgery: preliminary results. in recent years there has been an ever increasing amount of research and development of technologies and methodologies aimed at improving the safety of advanced surgery. in this context, several training methods and metrics have been proposed, in particular for laparoscopy, both to improve the surgeon's abilities and also to assess her/his skills. for neurosurgery, however, the extremely small movements and sizes involved have prevented until now the development of similar methodologies and systems.in this paper we present the development of the ultra-miniaturized inertial measurement unit wb3 (at present the smallest, lightest, and best performing in the world) for practical application in neurosurgery as skill assessment tool. this paper presents the feasibility study for quantitative discrimination of movements of experienced surgeons and beginners in a simple pick and place scenario.
on the manifold structure of the space of brain images. this paper investigates an approach to model the space of brain images through a low-dimensional manifold. a data driven method to learn a manifold from a collections of brain images is proposed. we hypothesize that the space spanned by a set of brain images can be captured, to some approximation, by a low-dimensional manifold, i.e. a parametrization of the set of images. the approach builds on recent advances in manifold learning that allow to uncover nonlinear trends in data. we combine this manifold learning with distance measures between images that capture shape, in order to learn the underlying structure of a database of brain images. the proposed method is generative. new images can be created from the manifold parametrization and existing images can be projected onto the manifold. by measuring projection distance of a held out set of brain images we evaluate the fit of the proposed manifold model to the data and we can compute statistical properties of the data using this manifold structure. we demonstrate this technology on a database of 436 mr brain images.
patient specific 4d coronary models from ecg-gated cta data for intra-operative dynamic alignment of cta with x-ray images. we present an approach to derive patient specific coronary models from ecg-gated cta data and their application for the alignment of cta with mono-plane x-ray imaging during interventional cardiology. a 4d (3d+t) deformation model of the coronary arteries is derived by (i) extraction of a 3d coronary model at an appropriate cardiac phase and (ii) non-rigid registration of the cta images at different ecg phases to obtain a deformation model. the resulting 4d coronary model is aligned with the x-ray data using a novel 2d+t/3d+t registration approach. model consistency and accuracy is evaluated using manually annotated coronary centerlines at systole and diastole as reference. improvement of registration robustness by using the 2d+t/3d+t registration is successfully demonstrated by comparison of the actual x-ray cardiac phase with the automatically determined best matching phase in the 4d coronary model.
alignment of viewing-angle dependent ultrasound images. we address the problem of the viewing-angle dependency of ultrasound images for registration. the reflected signal from large scale tissue boundaries is dependent on the incident angle of the beam. this applies an implicit weighting on the ultrasound image, dependent on the viewing-angle, which negatively affects the registration process, especially when utilizing curved linear transducers. we show that a simple reweighting of the images, considering a common physical model for ultrasound imaging, is not feasible. we therefore introduce a new matching function, separating reflectivity and scattering regions, which are the results of two different types of physical interactions of the ultrasound beam with the tissue. we use the local phase for identifying regions of reflectivity, and consider it as one part of our matching function, combining feature- and intensity-based aspects. first experiments provide good results for this novel registration approach.
constrained data decomposition and regression for analyzing healthy aging from fiber tract diffusion properties. it has been shown that brain structures in normal aging undergo significant changes attributed to neurodevelopmental and neurodegeneration processes as a lifelong, dynamic process. modeling changes in healthy aging will be necessary to explain differences to neurodegenerative patterns observed in mental illness and neurological disease. driving application is the analysis of brain white matter properties as a function of age, given a database of diffusion tensor images (dti) of 86 subjects well-balanced across adulthood. we present a methodology based on constrained pca (cpca) for fitting age-related changes of white matter diffusion of fiber tracts. it is shown that cpca applied to tract functions of diffusion isolates population noise and retains age as a smooth change over time, well represented by the first principal mode. cpca is therefore applied to a functional data analysis (fda) problem. age regression on tract functions reveals a nonlinear trajectory but also age-related changes varying locally along tracts. four tracts with four different tensor-derived scalar diffusion measures were analyzed, and leave-one-out validation of data compression is shown.
data-derived models for segmentation with application to surgical assessment and training. this paper addresses automatic skill assessment in robotic minimally invasive surgery. hidden markov models (hmms) are developed for individual surgical gestures (or surgemes) that comprise a typical bench-top surgical training task. it is known that such hmms can be used to recognize and segment surgemes in previously unseen trials [1]. here, the topology of each surgeme hmm is designed in a data-driven manner, mixing trials from multiple surgeons with varying skill levels, resulting in hmm states that model skill-specific sub-gestures. the sequence of hmm states visited while performing a surgeme are therefore indicative of the surgeon's skill level. this expectation is confirmed by the average edit distance between the state-level "transcripts" of the same surgeme performed by two surgeons with different expertise levels. some surgemes are further shown to be more indicative of skill than others.
inverse c-arm positioning for interventional procedures using real-time body part detection. the automation and speedup of interventional therapy and diagnostic workflows is a crucial issue. one way to improve these workflows is to accelerate the image acquisition procedures by fully automating the patient setup. this paper describes a system that performs this task without the use of markers or other prior assumptions. it returns metric coordinates of the 3-d body shape in real-time for inverse positioning. this is achieved by the application of an emerging technology, called time-of-flight (tof) sensor. a tof sensor is a cost-efficient, off-the-shelf camera which provides more than 40,000 3-d points in real-time. the first contribution of this paper is the incorporation of this novel imaging technology (tof) in interventional imaging. the second contribution is the ability of a c-arm system to position itself with respect to the patient prior to the acquisition. we are using the 3-d surface information of the patient to partition the body into anatomical sections. this is achieved by a fast two-stage classification process. the system computes the iso-center for each detected region. to verify our system we performed several tests on the iso-center of the head. firstly, the reproducibility of the head iso-center computation was evaluated. we achieved an accuracy of (x: 1.73±1.11 mm/y: 1.87±1.31 mm/z: 2.91±2.62 mm). secondly, a c-arm head scan of a body phantom was setup. our system automatically aligned the iso-center of the head with the c-arm iso-center. here we achieved an accuracy of ± 1 cm, which is within the accuracy of the patient table control.
non-rigid reconstruction of the beating heart surface for minimally invasive cardiac surgery. this paper presents a new method to reconstruct the beating heart surface based on the non-rigid structure from motion technique using preprocessed endoscopic images. first the images captured at the same phase within each heart cycle are automatically extracted from the original image sequence to reduce the dimension of the deformation subspace. then the remaining residual non-rigid motion is restricted to lie within a low-dimensional subspace and a probabilistic model is used to recover the 3d structure and camera motion simultaneously. outliers are removed iteratively based on the reprojection error. missing data are also recovered with an expectation maximization algorithm. as a result the camera can move around the operation scene to build a 3d surface with a wide field-of-view for intra-operative procedures. the method has been evaluated with synthetic data, heart phantom data, and in vivo data from a da vinci surgical system.
optimal matching for prostate brachytherapy seed localization with dimension reduction. in prostate brachytherapy, x-ray fluoroscopy has been used for intra-operative dosimetry to provide qualitative assessment of implant quality. more recent developments have made possible 3d localization of the implanted radioactive seeds. this is usually modeled as an assignment problem and solved by resolving the correspondence of seeds. it is, however, np-hard, and the problem is even harder in practice due to the significant number of hidden seeds. in this paper, we propose an algorithm that can find an optimal solution from multiple projection images with hidden seeds. it solves an equivalent problem with reduced dimensional complexity, thus allowing us to find an optimal solution in polynomial time. simulation results show the robustness of the algorithm. it was validated on 5 phantom and 18 patient datasets, successfully localizing the seeds with detection rate of ¿ 97.6 % and reconstruction error of ≤ 1.2 mm. this is considered to be clinically excellent performance.
robotic force stabilization for beating heart intracardiac surgery. the manipulation of fast moving, delicate tissues in beating heart procedures presents a considerable challenge to surgeons. we present a new robotic force stabilization system that assists surgeons by maintaining a constant contact force with the beating heart. the system incorporates a novel, miniature uniaxial force sensor that is mounted to surgical instrumentation to measure contact forces during surgical manipulation. using this sensor in conjunction with real-time tissue motion information derived from 3d ultrasound, we show that a force controller with feed-forward motion terms can provide safe and accurate force stabilization in an in vivo contact task against the beating mitral valve annulus. this confers a 50% reduction in force fluctuations when compared to a standard force controller and a 75% reduction in fluctuations when compared to manual attempts to maintain the same force.
evaluation of lobar biomechanics during respiration using image registration. the human lungs are divided into five independent compartments called lobes. the lobar fissures separate the lung lobes. it is hypothesized that the lobar surfaces slide against each other during respiration. we propose a method to evaluate the sliding motion of the lobar surfaces during respiration using lobe-by-lobe mass-preserving non-rigid image registration. we measure lobar sliding by evaluating the relative displacement on both sides of the fissure. the results show a superior-inferior gradient in the magnitude of lobar sliding. we compare whole-lung-based registration accuracy to lobe-by-lobe registration accuracy using vessel bifurcation landmarks.
optical biopsy mapping for minimally invasive cancer screening. the quest for providing tissue characterization and functional mapping during minimally invasive surgery (mis) has motivated the development of new surgical tools that extend the current functional capabilities of mis. miniaturized optical probes can be inserted into the instrument channel of standard endoscopes to reveal tissue cellular and subcellular microstructures, allowing excision-free optical biopsy. one of the limitations of such a point based imaging and tissue characterization technique is the difficulty of tracking probed sites in vivo. this prohibits large area surveillance and integrated functional mapping. the purpose of this paper is to present an image-based tracking framework by combining a semi model-based instrument tracking method with vision-based simultaneous localization and mapping. this allows the mapping of all spatio-temporally tracked biopsy sites, which can then be re-projected back onto the endoscopic video to provide a live augmented view in vivo, thus facilitating re-targeting and serial examination of potential lesions. the proposed method has been validated on phantom data with known ground truth and the accuracy derived demonstrates the strength and clinical value of the technique. the method facilitates a move from the current point based optical biopsy towards large area multi-scale image integration in a routine clinical environment.
probabilistic region matching in narrow-band endoscopy for targeted optical biopsy. recent advances in biophotonics have enabled in-vivo, in-situ histopathology for routine clinical applications. the non-invasive nature of these optical `biopsy' techniques, however, entails the difficulty of identifying previously visited biopsy locations, particularly for surveillance examinations. this paper presents a novel region-matching approach for narrow-band endoscopy to facilitate retargeting the optical biopsy sites. the task of matching sparse affine covariant image regions is modelled in a markov random field (mrf) framework. the proposed model incorporates appearance based region similarities as well as spatial correlations of neighbouring regions. in particular, a geometric constraint that is robust to deviations in relative positioning of the detected regions is introduced. in the proposed model, the appearance and geometric constraints are evaluated in the same space (photometry), allowing for their seamless integration into the mrf objective function. the performance of the method as compared to the existing state-of-the-art is evaluated with both in-vivo and simulation datasets with varying levels of visual complexities.
adjusting the neuroimaging statistical inferences for nonstationarity. in neuroimaging cluster-based inference has generally been found to be more powerful than voxel-wise inference [1]. however standard cluster-based methods assume stationarity (constant smoothness), while under nonstationarity clusters are larger in smooth regions just by chance, making false positive risk spatially variant. hayasaka et al. [2] proposed a random field theory (rft) based nonstationarity adjustment for cluster inference and validated the method in terms of controlling the overall family-wise false positive rate. the rft-based methods, however, have never been directly assessed in terms of homogeneity of local false positive risk. in this work we propose a new cluster size adjustment that accounts for local smoothness, based on local empirical cluster size distributions and a two-pass permutation method. we also propose a new approach to measure homogeneity of local false positive risk, and use this method to compare the rft-based and our new empirical adjustment methods. we apply these techniques to both cluster-based and a related inference, threshold-free cluster enhancement (tfce). using simulated and real data we confirm the expected heterogeneity in false positive risk with unadjusted cluster inference but find that rft-based adjustment does not fully eliminate heterogeneity; we also observe that our proposed empirical adjustment dramatically increases the homogeneity and tfce inference is generally quite robust to nonstationarity.
non-rigid image registration with uniform gradient spherical patterns. in this paper, we propose a new feature based non-rigid image registration method for dealing with two important issues. first, in order to establish reliable anatomical correspondence between template and subject images, efficient and distinctive region descriptor is needed as intensity information alone maybe insufficient. second, since interference factors such as monotonic gray-level bias fields are commonly existed during the imaging process, the registration algorithm should be robust against such factors. there are two main contributions presented in this paper. (1) a new region descriptor, named uniform gradient spherical pattern (ugsp), is proposed to extract the geometric features from input images. ugsp encodes second order voxel interaction information. (2) the ugsp feature is rotation and monotonic gray-level bias field invariant. the proposed method is integrated with the markov random field (mrf) labeling framework to formulate the registration process. the ¿-expansion algorithm is used to optimize the corresponding mrf energy function. the proposed method is evaluated on both the simulated and real 3d databases obtained from brainweb and ibsr respectively and compared with other state-of-the-art registration methods. experimental results show that the proposed method gives the highest registration accuracy among all the compared methods on both databases.
automatic segmentation of the pulmonary lobes from fissures, airways, and lung borders: evaluation of robustness against missing data. automatic segmentation of structures with missing or invisible borders is a challenging task. since structures in the lungs are related, humans use contextual and shape information to infer the position of invisible borders. an example of a task in which the borders are often incomplete or invisible is the segmentation of the pulmonary lobes. in this paper, a fully automatic segmentation of the pulmonary lobes in chest ct scans is presented. the method is especially designed to be robust to incomplete fissures by incorporating contextual information from automatic lung, fissure, and bronchial tree segmentations, as well as shape information. since the method relies on the result of automatic segmentations, it is important that the method is robust against failure of one or more of these segmentation methods. in an extensive experiment on 10 chest ct scans with manual segmentations, the robustness of the method to incomplete fissures and missing input segmentations is shown. in a second experiment on 100 chest ct scans with incomplete fissures, the method is shown to perform well.
quantifying brain connectivity: a comparative tractography study. in this paper, we compare a representative selection of current state-of-the-art algorithms in diffusion-weighted magnetic resonance imaging (dwmri) tractography, and propose a novel way to quantitatively define the connectivity between brain regions. as criterion for the comparison, we quantify the connectivity computed with the different methods. we provide initial results using diffusion tensor, spherical deconvolution, ball-and-stick model, and persistent angular structure (pas) along with deterministic and probabilistic tractography algorithms on a human dwi dataset. the connectivity is presented for a representative selection of regions in the brain in matrices and connectograms.our results show that fiber crossing models are able to reveal connections between more brain areas than the simple tensor model. probabilistic approaches show in average more connected regions but lower connectivity values than deterministic methods.
a coaxial laser endoscope with arbitrary spots in endoscopic view for fetal surgery. in this paper, we describe a rigid endoscope that transmits a laser beam coaxially to arbitrary points in the endoscopic view, mainly for treatment of twin-to-twin transfusion syndrome. the endoscope consists of a hotmirror for coaxial transmission of visible light and a nd:yag laser beam, and galvanometers for controlling the beam irradiation angle. we evaluated the transmission efficiency of the laser power, the spot size through the endoscope and accuracy in positioning the beam. the maximum laser transmission efficiency was 39% and the spot diameter was 2.2---3.2 mm at a distance of 10---20 mm. the positioning accuracy was mostly within 1.0 mm in the endoscopic view at the distance. the average laser power density on the spot was estimated to be 170---370 w/cm2, and a chicken liver was successfully coagulated by changing the laser beam irradiation angle.
two-compartment models of the diffusion mr signal in brain white matter. this study aims to identify the minimum requirements for an accurate model of the diffusion mr signal in white matter of the brain. we construct a hierarchy of two-compartment models of white matter from combinations of simple models for the intra and extra-cellular spaces. we devise a new diffusion mri protocol that provides measurements with a wide range of parameters for diffusion sensitization both parallel and perpendicular to white matter fibres. we use the protocol to acquire data from a fixed rat brain, which allows us to fit, study and compare the different models. the results show that models which incorporate pore size describe the measurements most accurately. the best fit comes from combining a full diffusion tensor (dt) model of the extra-cellular space with a cylindrical intra-cellular component.
a novel method for registration of us/mr of the liver based on the analysis of us dynamics. radio frequency ablation of liver cancer is a minimally invasive alternative to open surgery. typically, the preoperative planning is done on an mr (or ct) scan, while the intervention relies on ultrasound (us) guidance. registration of intra-operative us and preoperative mr (or ct) would assist navigation and increase the confidence of rfa needle positioning. in this paper we present a novel method for registration of us and mr images of the liver. hepatic vessels are extracted from 2d us by an algorithm that models us dynamics. it generates 2d probability maps representing hepatic vessels which are then combined into probability volumes. a multi-resolution registration framework performs registration of the pre-processed mr with two 3d vessel probability images. the accuracy, robustness and speed of the method were assessed by registering eight us/mr datasets. high robustness (86%) and reasonable accuracy (1.98°, 4.10mm), acceptable for the rfa clinical application, suggest that the method has a good potential for intra-operative use.
disco: a coherent diffeomorphic framework for brain registration under exhaustive sulcal constraints. neuroimaging at the group level requires spatial normalization of individual structural data. we propose a geometric approach that consists in matching a series of cortical surfaces through diffeomorphic registration of their sulcal imprints. the resulting 3d transforms naturally extends to the entire mri volumes. the diffeomorphic sulcal-based cortical (disco) registration integrates two recent technical outcomes: 1) the automatic extraction, identification and simplification of numerous sulci from t1-weighted mri data series hereby revealing the sulcal imprint and 2) the measure-based diffeomorphic registration of those crucial anatomical landmarks. we show how the disco registration may be used to elaborate a sulcal template which optimizes the distribution of constraints over the entire cortical ribbon. disco was evaluated through a group of 20 individual brains. quantitative and qualitative indices attest how this approach may improve both alignment of sulcal folds and overlay of gray and white matter volumes at the group level.
using real-time fmri to control a dynamical system by brain activity classification. we present a method for controlling a dynamical system using real-time fmri. the objective for the subject in the mr scanner is to balance an inverted pendulum by activating the left or right hand or resting. the brain activity is classified each second by a neural network and the classification is sent to a pendulum simulator to change the force applied to the pendulum. the state of the inverted pendulum is shown to the subject in a pair of vr goggles. the subject was able to balance the inverted pendulum during several minutes, both with real activity and imagined activity. in each classification 9000 brain voxels were used and the response time for the system to detect a change of activity was on average 2-4 seconds. the developments here have a potential to aid people with communication disabilities, such as locked in people. another future potential application can be to serve as a tool for stroke and parkinson patients to be able to train the damaged brain area and get real-time feedback for more efficient training.
a computer model of soft tissue interaction with a surgical aspirator. surgical aspirators are one of the most frequently used neurosurgical tools. effective training on a neurosurgery simulator requires a visually and haptically realistic rendering of surgical aspiration. however, there is little published data on mechanical interaction between soft biological tissues and surgical aspirators. in this study an experimental setup for measuring tissue response is described and results on calf brain and a range of phantom materials are presented. local graphical and haptic models are proposed. they are simple enough for real-time application, and closely match the observed tissue response. tissue resection (cutting) with suction is simulated using a volume sculpting approach. a simulation of suction is presented as a demonstration of the effectiveness of the approach.
belief propagation based segmentation of white matter tracts in dti. this paper presents a belief propagation approach to the segmentation of the major white matter tracts in diffusion tensor images of the human brain. unlike tractography methods that sample multiple fibers to be bundled together, we define a markov field directly on the diffusion tensors to separate the main fiber tracts at the voxel level. a prior model of shape and direction guides a full segmentation of the brain into known fiber tracts; additional, unspecified fibers; and isotropic regions. the method is evaluated on various data sets from an atlasing project, healthy subjects, and multiple sclerosis patients.
a demons algorithm for image registration with locally adaptive regularization. thirion's demons [1] is a popular algorithm for nonrigid image registration because of its linear computational complexity and ease of implementation. it approximately solves the diffusion registration problem [2] by successively estimating force vectors that drive the deformation toward alignment and smoothing the force vectors by gaussian convolution. in this article, we show how the demons algorithm can be generalized to allow image-driven locally adaptive regularization [3,4] in a manner that preserves both the linear complexity and ease of implementation of the original demons algorithm. we show that the proposed algorithm exhibits lower target registration error and requires less computational effort than the original demons algorithm on the registration of serial chest ct scans of patients with lung nodules.
a riemannian framework for orientation distribution function computing. compared with diffusion tensor imaging (dti), high angular resolution imaging (hardi) can better explore the complex microstructure of white matter. orientation distribution function (odf) is used to describe the probability of the fiber direction. fisher information metric has been constructed for probability density family in information geometry theory and it has been successfully applied for tensor computing in dti. in this paper, we present a state of the art riemannian framework for odf computing based on information geometry and sparse representation of orthonormal bases. in this riemannian framework, the exponential map, logarithmic map and geodesic have closed forms. and the weighted frechet mean exists uniquely on this manifold. we also propose a novel scalar measurement, named geometric anisotropy (ga), which is the riemannian geodesic distance between the odf and the isotropic odf. the renyi entropy $h_{\frac{1}{2}}$ of the odf can be computed from the ga. moreover, we present an affine-euclidean framework and a log-euclidean framework so that we can work in an euclidean space. as an application, lagrange interpolation on odf field is proposed based on weighted frechet mean. we validate our methods on synthetic and real data experiments. compared with existing riemannian frameworks on odf, our framework is model-free. the estimation of the parameters, i.e. riemannian coordinates, is robust and linear. moreover it should be noted that our theoretical results can be used for any probability density function (pdf) under an orthonormal basis representation.
task versus subtask surgical skill evaluation of robotic minimally invasive surgery. evaluating surgical skill is a time consuming, subjective, and difficult process. this paper compares two methods of identifying the skill level of a subject given motion data from a benchtop surgical task. in the first method, we build discrete hidden markov models at the task level, and test against these models. in the second method, we build discrete hidden markov models of surgical gestures, called surgemes, and evaluate skill at this level. we apply these techniques to 57 data sets collected from the da vinci surgical system. our current techniques have achieved accuracy levels of 100% using task level models and known gesture segmentation, 95% with task level models and unknown gesture segmentation, and 100% with the surgeme level models in correctly identifying the skill level. we observe that, although less accurate, the second method requires less prior label information. also, the surgeme level classification provided more insights into what subjects did well, and what they did poorly.
a cluster overlap measure for comparison of activations in fmri studies. most fmri studies use voxel-wise statistics to carry out intra-subject as well as inter-subject analysis. we show that statistics derived from voxel-wise comparisons are likely to be noisy and error prone, especially for inter-subject comparisons. in this paper we propose a novel metric called weighted cluster coverage to compare two activation maps. this metric is based on the intersection of spatially contiguous clusters of activations. it is found to be more robust than voxel-wise comparisons and could potentially lead to more statistical power in fmri-based group studies.
spatio-temporal reconstruction of dpet data using complex wavelet regularisation. traditionally, dynamic pet studies reconstruct temporally contiguous pet images using algorithms which ignore the inherent consistency between frames. we present a method which imposes a regularisation constraint based on wavelet denoising. this is achieved efficiently using the dual tree --- complex wavelet transform (dt-cwt) of kingsbury, which has many important advantages over the traditional discrete wavelet transform: shift invariance, implicit measure of local phase, and directional selectivity. in this paper, we apply the decomposition to the full spatio-temporal volume and use it for the reconstruction of dynamic (spatio-temporal) pet data.instead of using traditional wavelet thresholding schemes we introduce a locally defined and empirically-determined cross scale regularisation technique. we show that wavelet based regularisation has the potential to produce superior reconstructions and examine the effect various levels of boundary enhancement have on the overall images.we demonstrate that wavelet-based spatio-temporally regularised reconstructions have superior performance over conventional gaussian smoothing in simulated and clinical experiments. we find that our method outperforms conventional methods in terms of signal-to-noise ratio (snr) and mean square error (mse), and removes the need to post-smooth the reconstruction.
improved maximum a posteriori cortical segmentation by iterative relaxation of priors. thickness measurements of the cerebral cortex can aid diagnosis and provide valuable information about the temporal evolution of several diseases such as alzheimer's, huntington's, schizophrenia, as well as normal ageing. the presence of deep sulci and `collapsed gyri' (caused by the loss of tissue in patients with neurodegenerative diseases) complicates the tissue segmentation due to partial volume (pv) effects and limited resolution of mri. we extend existing work to improve the segmentation and thickness estimation in a single framework. we model the pv effect using a maximum a posteriori approach with novel iterative modification of the prior information to enhance deep sulci and gyri delineation. we use a voxel based approach to estimate thickness using the laplace equation within a lagrangian-eulerian framework leading to sub-voxel accuracy. experiments performed on a new digital phantom and on clinical alzheimer's disease mr images show improvements in both accuracy and robustness of the thickness measurements, as well as a reduction of errors in deep sulci and collapsed gyri.
brain connectivity using geodesics in hardi. we develop an algorithm for brain connectivity assessment using geodesics in hardi (high angular resolution diffusion imaging). we propose to recast the problem of finding fibers bundles and connectivity maps to the calculation of shortest paths on a riemannian manifold defined from fiber odfs computed from hardi measurements. several experiments on real data show that our method is able to segment fibers bundles that are not easily recovered by other existing methods.
airway tree extraction with locally optimal paths. this paper proposes a method to extract the airway tree from ct images by continually extending the tree with locally optimal paths. this is in contrast to commonly used region growing based approaches that only search the space of the immediate neighbors. the result is a much more robust method for tree extraction that can overcome local occlusions. the cost function for obtaining the optimal paths takes into account of an airway probability map as well as measures of airway shape and orientation derived from multi-scale hessian eigen analysis on the airway probability. significant improvements were achieved compared to a region growing based method, with up to 36% longer trees at a slight increase of false positive rate.
a shape relationship descriptor for radiation therapy planning. in this paper we address the challenge of matching patient geometry to facilitate the design of patient treatment plans in radiotherapy. to this end we propose a novel shape descriptor, the overlap volume histogram, which provides a rotation and translation invariant representation of a patient's organs at risk relative to the tumor volume. using our descriptor, it is possible to accurately identify database patients with similar constellations of organ and tumor geometries, enabling the transfer of treatment plans between patients with similar geometries. we demonstrate the utility of our method for such tasks by outperforming state of the art shape descriptors in the retrieval of patients with similar treatment plans. we also preliminarily show its potential as a quality control tool by demonstrating how it is used to identify an organ at risk whose dose can be significantly reduced.
tumor invasion margin on the riemannian space of brain fibers. gliomas are one of the most challenging tumors to treat or control locally. one of the main challenges is determining which areas of the apparently normal brain contain glioma cells, as gliomas are known to infiltrate for several centimeters beyond the clinically apparent lesion visualized on standard ct or mri. to ensure that radiation treatment encompasses the whole tumour, including the cancerous cells not revealed by mri, doctors treat a volume of brain extending 2cm out from the margin of the visible tumour. this expanded volume often includes healthy, non-cancerous brain tissue.knowing that glioma cells preferentially spread along nerve fibers, we propose the use of a geodesic distance on the riemannian manifold of brain fibers to replace the euclidean distance used in clinical practice and to correctly identify the tumor invasion margin. to compute the geodesic distance we use actual dti data from patients with glioma and compare our predicted growth with follow-up mri scans. results show improvement in predicting the invasion margin when using the geodesic distance as opposed to the 2cm conventional euclidean distance.
subject-matched templates for spatial normalization. spatial normalization of images from multiple subjects is a common problem in group comparison studies, such as voxel-based and deformation-based morphometric analyses. use of a study-specific template for normalization may improve normalization accuracy over a study-independent standard template (good et al., neuroimage, 14(1):21-36, 2001). here, we develop this approach further by introducing the concept of subject-matched templates. rather than using a single template for the entire population, a different template is used for every subject, with the template matched to the subject in terms of age, sex, and potentially other parameters (e.g., disease). all subject-matched templates are created from a single generative regression model of atlas appearance, thus providing a priori template-to-template correspondence without registration. we demonstrate that such an approach is technically feasible and significantly improves spatial normalization accuracy over using a single template.
constructing a dictionary of human brain folding patterns. brain imaging provides a wealth of information that computers can explore at a massive scale. categorizing the patterns of the human cortex has been a challenging issue for neuroscience. in this paper, we propose a data mining approach leading to the construction of the first computerized dictionary of cortical folding patterns, from a database of 62 brains. the cortical folds are extracted using brainvisa open software. the standard sulci are manually identified among the folds. 32 sets of sulci covering the cortex are selected. clustering techniques are further applied to identify in each set the different patterns observed in the population. after affine global normalization, the geometric distance between sulci of two subjects is calculated using the iterative closest point (icp) algorithm. the dimension of the resulting distance matrix is reduced using isomap algorithm. finally, a dedicated hierarchical clustering algorithm is used to extract out the main patterns. this algorithm provides a score which evaluates the strengths of the patterns found. the score is used to rank the patterns for setting up a dictionary to characterize the variability of cortical anatomy.
mapping tissue optical attenuation to identify cancer using optical coherence tomography. the lymphatic system is a common route for the spread of cancer and the identification of lymph node metastases is a key task during cancer surgery. this paper demonstrates the use of optical coherence tomography to construct parametric images of lymph nodes. it describes a method to automatically estimate the optical attenuation coefficient of tissue. by mapping the optical attenuation coefficient at each location in the scan, it is possible to construct a parametric image indicating variations in tissue type. the algorithm is applied to ex vivo samples of human axillary lymph nodes and validated against a histological gold standard. results are shown illustrating the variation in optical properties between cancerous and healthy tissue.
topological characterization of signal in brain images using min-max diagrams. we present a novel computational framework for characterizing signal in brain images via nonlinear pairing of critical values of the signal. among the astronomically large number of different pairings possible, we show that representations derived from specific pairing schemes provide concise representations of the image. this procedure yields a "min-max diagram" of the image data. the representation turns out to be especially powerful in discriminating image scans obtained from different clinical populations, and directly opens the door to applications in a variety of learning and inference problems in biomedical imaging. it is noticed that this strategy significantly departs from the standard image analysis paradigm --- where the `mean' signal is used to characterize an ensemble of images. this offers robustness to noise in subsequent statistical analyses, for example; however, the attenuation of the signal content due to averaging makes it rather difficult to identify subtle variations. the proposed topologically oriented method seeks to address these limitations by characterizing and encoding topological features or attributes of the image. as an application, we have used this method to characterize cortical thickness measures along brain surfaces in classifying autistic subjects. our promising experimental results provide evidence of the power of this representation.
fast and robust 3-d mri brain structure segmentation. we present a novel method for the automatic detection and segmentation of (sub-)cortical gray matter structures in 3-d magnetic resonance images of the human brain. essentially, the method is a top-down segmentation approach based on the recently introduced concept of marginal space learning (msl). we show that msl naturally decomposes the parameter space of anatomy shapes along decreasing levels of geometrical abstraction into subspaces of increasing dimensionality by exploiting parameter invariance. at each level of abstraction, i.e., in each subspace, we build strong discriminative models from annotated training data, and use these models to narrow the range of possible solutions until a final shape can be inferred. contextual information is introduced into the system by representing candidate shape parameters with high-dimensional vectors of 3-d generalized haar features and steerable features derived from the observed volume intensities. our system allows us to detect and segment 8 (sub-)cortical gray matter structures in t1-weighted 3-d mr brain scans from a variety of different scanners in on average 13.9 sec., which is faster than most of the approaches in the literature. in order to ensure comparability of the achieved results and to validate robustness, we evaluate our method on two publicly available gold standard databases consisting of several t1-weighted 3-d brain mr scans from different scanners and sites. the proposed method achieves an accuracy better than most state-of-the-art approaches using standardized distance and overlap metrics.
weakly supervised group-wise model learning based on discrete optimization. in this paper we propose a method for the weakly supervised learning of sparse appearance models from medical image data based on markov random fields (mrf). the models are learnt from a single annotated example and additional training samples without annotations. the approach formulates the model learning as solving a set of mrfs. both the model training and the resulting model are able to cope with complex and repetitive structures. the weakly supervised model learning yields sparse mrf appearance models that perform equally well as those trained with manual annotations, thereby eliminating the need for tedious manual training supervision. evaluation results are reported for hand radiographs and cardiac mri slices.
graph-based pancreatic islet segmentation for early type 2 diabetes mellitus on histopathological tissue. it is estimated that in 2010 more than 220 million people will be affected by type 2 diabetes mellitus (t2dm). early evidence indicates that specific markers for alpha and beta cells in pancreatic islets of langerhans can be used for early t2dm diagnosis. currently, the analysis of such histological tissues is manually performed by trained pathologists using a light microscope. to objectify classification results and to reduce the processing time of histological tissues, an automated computational pathology framework for segmentation of pancreatic islets from histopathological fluorescence images is proposed. due to high variability in the staining intensities for alpha and beta cells, classical medical imaging approaches fail in this scenario.the main contribution of this paper consists of a novel graph-based segmentation approach based on cell nuclei detection with randomized tree ensembles. the algorithm is trained via a cross validation scheme on a ground truth set of islet images manually segmented by 4 expert pathologists. test errors obtained from the cross validation procedure demonstrate that the graph-based computational pathology analysis proposed is performing competitively to the expert pathologists while outperforming a baseline morphological approach.
ultrafast localization of the optic disc using dimensionality reduction of the search space. optic disc (od) localization is an important pre-processing step that significantly simplifies subsequent segmentation of the od and other retinal structures. current od localization techniques suffer from impractically-high computation times (few minutes/image). in this work, we present an ultrafast technique that requiresless than a second to localize the od. the technique is based on reducing the dimensionality of the search space by projecting the 2d image feature space onto two orthogonal (x- and y-) axes. this results in two 1d signals that can be used to determine the x- and y- coordinates of the od. image features such as retinal vessels orientation and the od brightness and shape are used in the current method. four publicly-available databases, including stare and drive, were used to evaluate the proposed technique. the od was successfully located in 330 images out of 340 images (97%) with an average computation time of 0.65 seconds.
a deformable surface model for vascular segmentation. inspired by the motion of a solid surface under liquid pressure, this paper proposes a novel deformable surface model to segment blood vessels in medical images. in the proposed model, the segmented region and the background region are respectively considered as liquid and an elastic solid. the surface of the elastic solid experiences various forces derived from the second order intensity statistics and the surface geometry. these forces cause the solid surface to deform in order to segment vascular structures in an image. the proposed model has been studied in the experiments on synthetic data and clinical data acquired by different imaging modalities. it is experimentally shown that the new model is robust to intensity contrast changes inside blood vessels and thus very suitable to perform vascular segmentation.
organ segmentation with level sets using local shape and appearance priors. organ segmentation is a challenging problem on which recent progress has been made by incorporation of local image statistics that model the heterogeneity of structures outside of an organ of interest. however, most of these methods rely on landmark based segmentation, which has certain drawbacks. we propose to perform organ segmentation with a novel level set algorithm that incorporates local statistics via a highly efficient point tracking mechanism. specifically, we compile statistics on these tracked points to allow for a local intensity profile outside of the contour and to allow for a local surface area penalty, which allows us to capture fine detail where it is expected. the local intensity and curvature models are learned through landmarks automatically embedded on the surface of the training shapes. we use parzen windows to model the internal organ intensities as one distribution since this is sufficient for most organs. in addition, since the method is based on level sets, we are able to naturally take advantage of recent work on global shape regularization. we show state-of-the-art results on the challenging problems of liver and kidney segmentation.
a conditional random field approach for coupling local registration with robust tissue and structure segmentation. we consider a general modelling strategy to handle in a unified way a number of tasks essential to mr brain scan analysis. our approach is based on the explicit definition of a conditional random field (crf) model decomposed into components to be specified according to the targeted tasks. for a specific illustration, we define a crf model that combines robust-to-noise and to nonuniformity markovian tissue and structure segmentations with local affine atlas registration. the evaluation performed on both phantoms and real 3t images shows good results and, in particular, points out the gain in introducing registration as a model component. besides, our modeling and estimation scheme provide general guidelines to deal with complex joint processes for medical image analysis.
spectral embedding based probabilistic boosting tree (sceptre): classifying high dimensional heterogeneous biomedical data. the major challenge with classifying high dimensional biomedical data is in identifying the appropriate feature representation to (a) overcome the curse of dimensionality, and (b) facilitate separation between the data classes. another challenge is to integrate information from two disparate modalities, possibly existing in different dimensional spaces, for improved classification. in this paper, we present a novel data representation, integration and classification scheme, spectral embedding based probabilistic boosting tree (sceptre), which incorporates spectral embedding (se) for data representation and integration and a probabilistic boosting tree classifier for data classification. se provides an alternate representation of the data by non-linearly transforming high dimensional data into a low dimensional embedding space such that the relative adjacencies between objects are preserved. we demonstrate the utility of sceptre to classify and integrate magnetic resonance (mr) spectroscopy (mrs) and imaging (mri) data for prostate cancer detection. area under the receiver operating curve (auc) obtained via randomized cross validation on 15 prostate mri-mrs studies suggests that (a) sceptre on mrs significantly outperforms a haar wavelets based classifier, (b) integration of mri-mrs via sceptre performs significantly better compared to using mri and mrs alone, and (c) data integration via sceptre yields superior classification results compared to combining decisions from individual classifiers (or modalities).
cross modality deformable segmentation using hierarchical clustering and learning. segmentation of anatomical objects is always a fundamental task for various clinical applications. although many automatic segmentation methods have been designed to segment specific anatomical objects in a given imaging modality, a more generic solution that is directly applicable to different imaging modalities and different deformable surfaces is desired, if attainable. in this paper, we propose such a framework, which learns from examples the spatially adaptive appearance and shape of a 3d surface (either open or closed). the application to a new object/surface in a new modality requires only the annotation of training examples. key contributions of our method include: (1) an automatic clustering and learning algorithm to capture the spatial distribution of appearance similarities/variations on the 3d surface. more specifically, the model vertices are hierarchically clustered into a set of anatomical primitives (sub-surfaces) using both geometric and appearance features. the appearance characteristics of each learned anatomical primitive are then captured through a cascaded boosting learning method. (2) to effectively incorporate non-gaussian shape priors, we cluster the training shapes in order to build multiple statistical shape models. (3) to our best knowledge, this is the first time the same segmentation algorithm has been directly employed in two very diverse applications: a. liver segmentation (closed surface) in pet-ct, in which ct has very low-resolution and low-contrast; b. distal femur (condyle) surface (open surface) segmentation in mri.
personalized modeling and assessment of the aortic-mitral coupling from 4d tee and ct. the anatomy, function and hemodynamics of the aortic and mitral valves are known to be strongly interconnected. an integrated quantitative and visual assessment of the aortic-mitral coupling may have an impact on patient evaluation, planning and guidance of minimal invasive procedures. in this paper, we propose a novel model-driven method for functional and morphological characterization of the entire aortic-mitral apparatus. a holistic physiological model is hierarchically defined to represent the anatomy and motion of the two left heart valves. robust learning-based algorithms are applied to estimate the patient-specific spatial-temporal parameters from four-dimensional tee and ct data. the piecewise affine location of the valves is initially determined over the whole cardiac cycle using an incremental search performed in marginal spaces. consequently, efficient spectrum detection in the trajectory space is applied to estimate the cyclic motion of the articulated model. finally, the full personalized surface model of the aortic-mitral coupling is constructed using statistical shape models and local spatial-temporal refinement. experiments performed on 65 4d tee and 69 4d ct sequences demonstrated an average accuracy of 1.45mm and speed of 60 seconds for the proposed approach. initial clinical validation on model-based and expert measurement showed the precision to be in the range of the inter-user variability. to the best of our knowledge this is the first time a complete model of the aortic-mitral coupling estimated from tee and ct data is proposed.
3d cardiac segmentation using temporal correlation of radio frequency ultrasound data. semi-automatic segmentation of the myocardium in 3d echographic images may substantially support clinical diagnosis of heart disease. particularly in children with congenital heart disease, segmentation should be based on the echo features solely since a priori knowledge on the shape of the heart cannot be used. segmentation of echocardiographic images is challenging because of the poor echogenicity contrast between blood and the myocardium in some regions and the inherent speckle noise from randomly backscattered echoes. phase information present in the radio frequency (rf) ultrasound data might yield useful, additional features in these regions. a semi-3d technique was used to determine maximum temporal cross-correlation values locally from the rf data. to segment the endocardial surface, maximum cross-correlation values were used as additional external force in a deformable model approach and were tested against and combined with adaptive filtered, demodulated rf data. the method was tested on full volume images (philips, ie33) of four healthy children and evaluated by comparison with contours obtained from manual segmentation.
automated segmentation of the femur and pelvis from 3d ct data of diseased hip using hierarchical statistical shape model of joint structure. segmentation of the femur and pelvis from 3d data is prerequisite of patient specific planning and simulation for hip surgery. separation of the femoral head and acetabulum is one of main difficulties in the diseased hip joint due to deformed shapes and extreme narrowness of the joint space. in this paper, we develop a hierarchical multi-object statistical shape model representing joint structure for automated segmentation of the diseased hip from 3d ct images. in order to represent shape variations as well as pose variations of the femur against the pelvis, both shape and pose variations are embedded in a combined pelvis and femur statistical shape model (ssm). further, the whole combined ssm is divided into individual pelvis and femur ssms and a partial combined ssm only including the acetabulum and proximal femur. the partial combined ssm maintains the consistency of the two bones by imposing the constraint that the shapes of the overlapped portions of the individual and partial combined ssms are identical. the experimental results show that segmentation and separation accuracy of the femur and pelvis was improved using the proposed method compared with independent use of the pelvis and femur ssms.
lung extraction, lobe segmentation and hierarchical region assessment for quantitative analysis on high resolution computed tomography images. regional assessment of lung disease (such as chronic obstructive pulmonary disease) is a critical component to accurate patient diagnosis. software tools than enable such analysis are also important for clinical research studies. in this work, we present an image segmentation and data representation framework that enables quantitative analysis specific to different lung regions on high resolution computed tomography (hrct) datasets. we present an offline, fully automatic image processing chain that generates airway, vessel, and lung mask segmentations in which the left and right lung are delineated. we describe a novel lung lobe segmentation tool that produces reproducible results with minimal user interaction. a usability study performed across twenty datasets (inspiratory and expiratory exams including a range of disease states) demonstrates the tool's ability to generate results within five to seven minutes on average. we also describe a data representation scheme that involves compact encoding of label maps such that both "regions" (such as lung lobes) and "types" (such as emphysematous parenchyma ) can be simultaneously represented at a given location in the hrct.
dynamic cone beam reconstruction using a new level set formulation. this paper addresses an approach toward tomographic reconstruction from rotational angiography data as it is generated by c-arms in cardiac imaging. since the rotational acquisition scheme forces a trade-off between consistency of the scene and reasonable baselines, most existing reconstruction techniques fail at recovering the 3d+t scene.we propose a new reconstruction framework based on variational level sets including a new data term for symbolic reconstruction as well as a novel incorporation of motion into the level set formalism. the resulting simultaneous estimation of shape and motion proves feasible in the presented experiments. since the proposed formulation offers a great flexibility in incorporating other data terms as well as hard or soft constraints, it allows an adaption to a wider range of problems and could be of interest to other reconstruction settings as well.
a new 3-d automated computational method to evaluate in-stent neointimal hyperplasia in in-vivo intravascular optical coherence tomography pullbacks. detection of stent struts imaged in vivo by optical coherence tomography (oct) after percutaneous coronary interventions (pci) and quantification of in-stent neointimal hyperplasia (nih) are important. in this paper, we present a new computational method to facilitate the physician in this endeavor to assess and compare new (drug-eluting) stents. we developed a new algorithm for stent strut detection and utilized splines to reconstruct the lumen and stent boundaries which provide automatic measurements of nih thickness, lumen and stent area. our original approach is based on the detection of stent struts unique characteristics: bright reflection and shadow behind. furthermore, we present for the first time to our knowledge a rotation correction method applied across oct cross-section images for 3d reconstruction and visualization of reconstructed lumen and stent boundaries for further analysis in the longitudinal dimension of the coronary artery. our experiments over oct cross-sections taken from 7 patients presenting varying degrees of nih after pci illustrate a good agreement between the computer method and expert evaluations: bland-altmann analysis revealed a mean difference for lumen cross-section area of 0.11±0.70mm 2 and for the stent cross-section area of 0.10±1.28mm 2.
real-time prediction of brain shift using nonlinear finite element algorithms. patient-specific biomechanical models implemented using specialized nonlinear (i.e. taking into account material and geometric nonlinearities) finite element procedures were applied to predict the deformation field within the brain for five cases of craniotomy-induced brain shift. the procedures utilize the total lagrangian formulation with explicit time stepping. the loading was defined by prescribing deformations on the brain surface under the craniotomy. application of the computed deformation fields to register the preoperative images with the intraoperative ones indicated that the models very accurately predict the intraoperative positions and deformations of the brain anatomical structures for limited information about the brain surface deformations. for each case, it took less than 40 s to compute the deformation field using a standard personal computer, and less than 4 s using a graphics processing unit (gpu). the results suggest that nonlinear biomechanical models can be regarded as one possible method of complementing medical image processing techniques when conducting non-rigid registration within the real-time constraints of neurosurgery.
surgical planning and patient-specific biomechanical simulation for tracheal endoprostheses interventions. we have developed a system for computer-assisted surgical planning of tracheal surgeries. the system allows to plan the intervention based on ct images of the patient, and includes a virtual database of commercially available prostheses. automatic segmentation of the trachea and apparent pathological structures is obtained using a modified region growing algorithm. a method for automatic adaptation of a finite element mesh allows to build a patient-specific biomechanical model for simulation of the expected performance of the implant under physiological movement (swallowing, sneezing). laboratory experiments were performed to characterise the tissues present in the trachea, and movement models were obtained from fluoroscopic images of a patient. results are reported on the planning and biomechanical simulation of two patients that underwent surgery at our hospital.
unsupervised inline analysis of cardiac perfusion mri. in this paper we first discuss the technical challenges preventing an automated analysis of cardiac perfusion mr images and subsequently present a fully unsupervised workflow to address the problems. the proposed solution consists of key-frame detection, consecutive motion compensation, surface coil inhomogeneity correction using proton density images and robust generation of pixel-wise perfusion parameter maps. the entire processing chain has been implemented on clinical mr systems to achieve unsupervised inline analysis of perfusion mri. validation results are reported for 260 perfusion time series, demonstrating feasibility of the approach.
tensor-based morphometry of fibrous structures with application to human brain white matter. tensor-based morphometry (tbm) is a powerful approach for examining shape changes in anatomy both across populations and in time. our work extends the standard tbm for quantifying local volumetric changes to establish both rich and intuitive descriptors of shape changes in fibrous structures. it leverages the data from diffusion tensor imaging to determine local spatial configuration of fibrous structures and combines this information with spatial transformations derived from image registration to quantify fibrous structure-specific changes, such as local changes in fiber length and in thickness of fiber bundles. in this paper, we describe the theoretical framework of our approach in detail and illustrate its application to study brain white matter. our results show that additional insights can be gained with the proposed analysis.
automatic extraction of mandibular nerve and bone from cone-beam ct data. the exact localization of the mandibular nerve with respect to the bone is important for applications in dental implantology and maxillofacial surgery. cone beam computed tomography (cbct), often also called digital volume tomography (dvt), is increasingly utilized in maxillofacial or dental imaging. compared to conventional ct, however, soft tissue discrimination is worse due to a reduced dose. thus, small structures like the alveolar nerves are even harder recognizable within the image data. we show that it is nonetheless possible to accurately reconstruct the 3d bone surface and the course of the nerve in a fully automatic fashion, with a method that is based on a combined statistical shape model of the nerve and the bone and a dijkstra-based optimization procedure. our method has been validated on 106 clinical datasets: the average reconstruction error for the bone is 0.5±0.1 mm, and the nerve can be detected with an average error of 1.0±0.6 mm.
shape modelling for tract selection. probabilistic tractography provides estimates of the probability of a structural connection between points or regions in a brain volume, based on information from diffusion mri. the ability to estimate the uncertainty associated with reconstructed pathways is valuable, but noise in the image data leads to premature termination or erroneous trajectories in sampled streamlines. in this work we describe automated methods, based on a probabilistic model of tract shape variability between individuals, which can be applied to select seed points in order to maximise consistency in tract segmentation; and to discard streamlines which are unlikely to belong to the tract of interest. our method is shown to ameliorate false positives and remove the widely observed falloff in connection probability with distance from the seed region due to noise, two important problems in the tractography literature. moreover, the need to apply an arbitrary threshold to connection probability maps is entirely obviated by our approach, thus removing a significant user-specified parameter from the tractography pipeline.
respiratory motion estimation from cone-beam projections using a prior model. respiratory motion introduces uncertainties when planning and delivering radiotherapy for lung cancer patients. cone-beam projections acquired in the treatment room could provide valuable information for building motion models, useful for gated treatment delivery or motion compensated reconstruction. we propose a method for estimating 3d+t respiratory motion from the 2d+t cone-beam projection sequence by including prior knowledge about the patient's breathing motion. motion estimation is accomplished by maximizing the similarity of the projected view of a patient specific model to observed projections of the cone-beam sequence. this is done semi-globally, considering entire breathing cycles. using realistic patient data, we show that the method is capable of good prediction of the internal patient motion from cone-beam data, even when confronted with interfractional changes in the breathing motion.
volumetric shape model for oriented tubular structure from dti data. in this paper, we describe methods for constructing shape priors using orientation information to model white matter tracts from magnetic resonance diffusion tensor images (dti). shape normalization is needed for the construction of a shape prior using statistical methods. moving beyond shape normalization using boundary-only or orientation-only information, our method combines the idea of sweeping and inverse-skeletonization to parameterize 3d volumetric shape, which provides point correspondence and orientations over the whole volume in a continuous fashion. tangents from this continuous model can be treated as a de-noised reconstruction of the original structural orientation inside a shape. we demonstrate the accuracy of this technique by reconstructing synthetic data and the 3d cingulum tract from brain dti data and manually drawn 2d contours for each tract. our output can also serve as the input for subsequent boundary finding or shape analysis.
multiple q-shell odf reconstruction in q-ball imaging. q-ball imaging (qbi) is a high angular resolution diffusion imaging (hardi) technique which has been proven very successful in resolving multiple intravoxel fiber orientations in mr images. the standard computation of the orientation distribution function (odf, the probability of diffusion in a given direction) from q-ball uses linear radial projection, neglecting the change in the volume element along the ray, thereby resulting in distributions different from the true odfs. a new technique has been recently proposed that, by considering the solid angle factor, uses the mathematically correct definition of the odf and results in a dimensionless and normalized odf expression from a single q-shell. in this paper, we extend this technique in order to exploit hardi data from multiple q-shells. we consider the more flexible multi-exponential model for the diffusion signal, and show how to efficiently compute the odfs in constant solid angle. we describe our method and demonstrate its improved performance on both artificial and real hardi data.
tissue tracking in thermo-physiological imagery through spatio-temporal smoothing. accurate tracking of facial tissue in thermal infrared imaging is challenging because it is affected not only by positional but also physiological (functional) changes. this article presents a particle filter tracker driven by a probabilistic template function with both spatial and temporal smoothing components, which is capable of adapting to abrupt positional and physiological changes. the method was tested on tracking facial regions of subjects under varying physiological and environmental conditions in 12 thermal clips. it demonstrated robustness and accuracy, outperforming other strategies. this new method promises improved performance in a host of biomedical applications that involve physiological measurements on the face, like unobtrusive sleep studies.
thermal vision for sleep apnea monitoring. the present paper proposes a novel methodology to monitor sleep apnea through thermal imaging. first, the nostril region is segmented and it is tracked over time via a network of cooperating probabilistic trackers. then, the mean thermal signal of the nostril region, carrying the breathing information, is analyzed through wavelet decomposition. the experimental set included 22 subjects (12 men and 10 women). the sleep-disordered incidents were detected by both thermal and standard polysomnographic methodologies. the high accuracy confirms the validity of the proposed approach, and brings non-obtrusive clinical monitoring of sleep disorders within reach.
modeling respiratory motion for cancer radiation therapy based on patient-specific 4dct data. prediction of respiratory motion has the potential to substantially improve cancer radiation therapy. a nonlinear finite element (fe) model of respiratory motion during full breathing cycle has been developed based on patient specific pressure-volume relationship and 4d computed tomography (ct) data. for geometric modeling of lungs and ribcage we have constructed intermediate cad surface which avoids multiple geometric smoothing procedures. for physiologically relevant respiratory motion modeling we have used pressure-volume (pv) relationship to apply pressure loading on the surface of the model. a hyperelastic soft tissue model, developed from experimental observations, has been used. additionally, pleural sliding has been considered which results in accurate deformations in the superior-inferior (si) direction. the finite element model has been validated using 51 landmarks from the ct data. the average differences in position is seen to be 0.07 cm (sd = 0.20 cm), 0.07 cm (0.15 cm), and 0.22 cm (0.18 cm) in the left-right, anterior-posterior, and superior-inferior directions, respectively.
extending genetic linkage analysis to diffusion tensor images to map single gene effects on brain fiber architecture. we extended genetic linkage analysis - an analysis widely used in quantitative genetics - to 3d images to analyze single gene effects on brain fiber architecture. we collected 4 tesla diffusion tensor images (dti) and genotype data from 258 healthy adult twins and their non-twin siblings. after high-dimensional fluid registration, at each voxel we estimated the genetic linkage between the single nucleotide polymorphism (snp), val66met (dbsnp number rs6265), of the bdnf gene (brain-derived neurotrophic factor) with fractional anisotropy (fa) derived from each subject's dti scan, by fitting structural equation models (sem) from quantitative genetics. we also examined how image filtering affects the effect sizes for genetic linkage by examining how the overall significance of voxelwise effects varied with respect to full width at half maximum (fwhm) of the gaussian smoothing applied to the fa images. raw fa maps with no smoothing yielded the greatest sensitivity to detect gene effects, when corrected for multiple comparisons using the false discovery rate (fdr) procedure. the bdnf polymorphism significantly contributed to the variation in fa in the posterior cingulate gyrus, where it accounted for around 90-95% of the total variance in fa. our study generated the first maps to visualize the effect of the bdnf gene on brain fiber integrity, suggesting that common genetic variants may strongly determine white matter integrity.
3d prostate segmentation in ultrasound images based on tapered and deformed ellipsoids. prostate segmentation from trans-rectal transverse b-mode ultrasound images is required for radiation treatment of prostate cancer. manual segmentation is a time-consuming task, the results of which are dependent on image quality and physicians' experience. this paper introduces a semi-automatic 3d method based on super-ellipsoidal shapes. it produces a 3d segmentation in less than 15 seconds using a warped, tapered ellipsoid fit to the prostate. a study of patient images shows good performance and repeatability. this method is currently in clinical use at the vancouver cancer center where it has become the standard segmentation procedure for low dose-rate brachytherapy treatment.
automatic image-based cardiac and respiratory cycle synchronization and gating of image sequences. we propose a novel method to detect the current state of the quasi-periodic system from image sequences which in turn will enable us to synchronize/gate the image sequences to obtain images of the organ system at similar configurations. the method uses the cumulated phase shift in the spectral domain of successive image frames as a measure of the net motion of objects in the scene. the proposed method is applicable to 2d and 3d time varying sequences and is not specific to the imaging modality. we demonstrate its effectiveness on x-ray angiographic and cardiac and liver ultrasound sequences. knowledge of the current (cardiac or respiratory) phase of the system, opens up the possibility for a purely image based cardiac and respiratory gating scheme for interventional and radiotherapy procedures.
predicting mgmt methylation status of glioblastomas from mri texture. in glioblastoma (gbm), promoter methylation of the dna repair gene mgmt is associated with benefit from chemotherapy. because mgmt promoter methylation status can not be determined in all cases, a surrogate for the methylation status would be a useful clinical tool. correlation between methylation status and magnetic resonance imaging features has been reported suggesting that non-invasive mgmt promoter methylation status detection is possible. in this work, a retrospective analysis of t2, flair and t1-post contrast mr images in patients with newly diagnosed gbm is performed using l1-regularized neural networks. tumor texture, assessed quantitatively was utilized for predicting the mgmt promoter methylation status of a gbm in 59 patients. the texture features were extracted using a space-frequency texture analysis based on the s-transform and utilized by a neural network to predict the methylation status of a gbm. blinded classification of mgmt promoter methylation status reached an average accuracy of 87.7%, indicating that the proposed technique is accurate enough for clinical use.
left ventricle segmentation using diffusion wavelets and boosting. we propose a method for the segmentation of medical images based on a novel parameterization of prior shape knowledge and a search scheme based on classifying local appearance. the method uses diffusion wavelets to capture arbitrary and continuous interdependencies in the training data and uses them for an efficient shape model. the lack of classic visual consistency in complex medical imaging data, is tackled by a manifold learning approach handling optimal high-dimensional local features by gentle boosting. appearance saliency is encoded in the model and segmentation is performed through the extraction and classification of the corresponding features in a new data set, as well as a diffusion wavelet based shape model constraint. our framework supports hierarchies both in the model and the search space, can encode complex geometric and photometric dependencies of the structure of interest, and can deal with arbitrary topologies. promising results are reported for heart ct data sets, proving the impact of the soft parameterization, and the efficiency of our approach.
automated anatomical labeling of bronchial branches extracted from ct datasets based on machine learning and combination optimization and its application to bronchoscope guidance. this paper presents a method for the automated anatomical labeling of bronchial branches extracted from 3d ct images based on machine learning and combination optimization. we also show applications of anatomical labeling on a bronchoscopy guidance system. this paper performs automated labeling by using machine learning and combination optimization. the actual procedure consists of four steps: (a) extraction of tree structures of the bronchus regions extracted from ct images, (b) construction of adaboost classifiers, (c) computation of candidate names for all branches by using the classifiers, (d) selection of best combination of anatomical names. we applied the proposed method to 90 cases of 3d ct datasets. the experimental results showed that the proposed method can assign correct anatomical names to 86.9% of the bronchial branches up to the sub-segmental lobe branches. also, we overlaid the anatomical names of bronchial branches on real bronchoscopic views to guide real bronchoscopy.
heart motion abnormality detection via an information measure and bayesian filtering. this study investigates heart wall motion abnormality detection with an information theoretic measure of heart motion based on the shannon's differential entropy (sde) and recursive bayesian filtering. heart wall motion is generally analyzed using functional images which are subject to noise and segmentation inaccuracies, and incorporation of prior knowledge is crucial in improving the accuracy. the kalman filter, a well known recursive bayesian filter, is used in this study to estimate the left ventricular (lv) cavity points given incomplete and noisy data, and given a dynamic model. however, due to similarities between the statistical information of normal and abnormal heart motions, detecting and classifying abnormality is a challenging problem which we proposed to investigate with a global measure based on the sde. we further derive two other possible information theoretic abnormality detection criteria, one is based on rényi entropy and the other on fisher information. the proposed method analyzes wall motion quantitatively by constructing distributions of the normalized radial distance estimates of the lv cavity. using 269×20 segmented lv cavities of short-axis magnetic resonance images obtained from 30 subjects, the experimental analysis demonstrates that the proposed sde criterion can lead to significant improvement over other features that are prevalent in the literature related to the lv cavity, namely, mean radial displacement and mean radial velocity.
evaluation of -space sampling strategies for the diffusion magnetic resonance imaging. we address the problem of efficient sampling of the diffusion space for the diffusion magnetic resonance imaging (dmri) modality. while recent scanner improvements enable the acquisition of more and more detailed images, it is still unclear which q-space sampling strategy gives the best performance. we evaluate several q-space sampling distributions by an approach based on the approximation of the mr signal by a series expansion of spherical harmonics and laguerre-gaussian functions. with the help of synthetic experiments, we identify a subset of sampling distributions which leads to the best reconstructed data.
vibro-elastography for visualization of the prostate region: method evaluation. we show that vibro-elastography, an ultrasound-based method that creates images of tissue viscoelasticity contrast, can be used for visualization and segmentation of the prostate. we use mri as the gold standard and show that ve images yield more accurate 3d volumes of the prostate gland than conventional b-mode imaging. furthermore, we propose two novel measures characterizing the strength and continuity of edges in noisy images. these measures, as well as contrast to noise ratio, demonstrate the utility of ve as a prostate imaging modality. the results of our study show that in addition to mapping the visco-elastic properties of tissue, ve can play a central role in improving the anatomic visualization of the prostate region and become an integral component of interventional procedures such as brachytherapy.
interactive simulation of flexible needle insertions based on constraint models. this paper presents a new modeling method for the insertion of needles and more generally thin and flexible medical devices into soft tissues. several medical procedures rely on the insertion of slender medical devices such as biopsy, brachytherapy, deep-brain stimulation. in this paper, the interactions between soft tissues and flexible instruments are reproduced using a set of dedicated complementarity constraints. each constraint is positionned and applied to the deformable models without requiring any remeshing. our method allows for the 3d simulation of different physical phenomena such as puncture, cutting, static and dynamic friction at interactive frame rate. to obtain realistic simulation, the model can be parametrized using experimental data. our method is validated through a series of typical simulation examples and new more complex scenarios.
multimodal prior appearance models based on regional clustering of intensity profiles. model-based image segmentation requires prior information about the appearance of a structure in the image. instead of relying on principal component analysis such as in statistical appearance models, we propose a method based on a regional clustering of intensity profiles that does not rely on an accurate pointwise registration. our method is built upon the expectation-maximization algorithm with regularized covariance matrices and includes spatial regularization. the number of appearance regions is determined by a novel model order selection criterion. the prior is described on a reference mesh where each vertex has a probability to belong to several intensity profile classes.
dynamic layer separation for coronary dsa and enhancement in fluoroscopic sequences. this paper presents a new technique of coronary digital subtraction angiography which separates layers of moving background structures from dynamic fluoroscopic sequences of the heart and obtains moving layers of coronary arteries. a bayeisan framework combines dense motion estimation, uncertainty propagation and statistical fusion to achieve reliable background layer estimation and motion compensation for coronary sequences. encouraging results have been achieved on clinically acquired coronary sequences, where the proposed method considerably improves the visibility and perceptibility of coronary arteries undergoing breathing and cardiac movements. perceptibility improvement is significant especially for very thin vessels. clinical benefit is expected in the context of obese patients and deep angulation, as well as in the reduction of contrast dose in normal size patients.
analysis of mr images of mice in preclinical treatment monitoring of polycystic kidney disease. a common cause of kidney failure is autosomal dominant polycystic kidney disease (adpkd). it is characterized by the growth of cysts in the kidneys and hence the growth of the entire kidneys with eventual failure in most cases by age 50. no preventive treatment for this condition is available. preclinical drug treatment studies use an in vivo mouse model of the condition. the analysis of mice imaging data for such studies typically requires extensive manual interaction, which is subjective and not reproducible. in this work both untreated and treated mice have been imaged with a high field, 9.4t, mri animal scanner and a reliable algorithm for the automated segmentation of the mouse kidneys has been developed. the algorithm first detects the region of interest (roi) in the image surrounding the kidneys. a parameterized geometric shape for a kidney is registered to the roi of each kidney. the registered shapes are incorporated as priors to the graph cuts algorithm used to extract the kidneys. the accuracy of the automated segmentation has been demonstrated by comparing it with a manual segmentation. the processing results are also consistent with the literature for previous techniques.
discriminative, semantic segmentation of brain tissue in mr images. a new algorithm is presented for the automatic segmentation and classification of brain tissue from 3d mr scans. it uses discriminative random decision forest classification and takes into account partial volume effects. this is combined with correction of intensities for the mr bias field, in conjunction with a learned model of spatial context, to achieve accurate voxel-wise classification. our quantitative validation, carried out on existing labelled datasets, demonstrates improved results over the state of the art, especially for the cerebro-spinal fluid class which is the most difficult to label accurately.
a computer-aided diagnosis system of nuclear cataract via ranking. a novel computer-aided diagnosis system of nuclear cataract via ranking is firstly proposed in this paper. the grade of nuclear cataract in a slit-lamp image is predicted based on its neighboring labeled images in a ranked images list, which is achieved using an optimal ranking function. a new ranking evaluation measure is proposed for learning the optimal ranking function via direct optimization. our system has been tested by a large dataset composed of 1000 slit-lamp images from 1000 different cases. both experimental results and comparison with several state-of-the-art methods indicate the superiority of our system.
septal flash assessment on crt candidates based on statistical atlases of motion. in this paper, we propose a complete framework for the automatic detection and quantification of abnormal heart motion patterns using statistical atlases of motion built from healthy populations. the method is illustrated on crt patients with identified cardiac dyssynchrony and abnormal septal motion on 2d ultrasound (us) sequences. the use of the 2d us modality guarantees that the temporal resolution of the image sequences is high enough to work under a small displacements hypothesis. under this assumption, the computed displacement fields can be directly considered as cardiac velocities. comparison of subjects acquired with different spatiotemporal resolutions implies the reorientation and temporal normalization of velocity fields in a common space of coordinates. statistics are then performed on the reoriented vector fields. results show the ability of the method to correctly detect abnormal motion patterns and quantify their distance to normality. the use of local p-values for quantifying abnormal motion patterns is believed to be a promising strategy for computing new markers of cardiac dyssynchrony for better characterizing crt candidates.
a fuzzy region-based hidden markov model for partial-volume classification in brain mri. we present a novel fuzzy region-based hidden markov model (frbhmm) for unsupervised partial-volume classification in brain magnetic resonance images (mris). the primary contribution is an efficient graphical representation of 3d image data in which irregularly-shaped image regions have memberships to a number of classes rather than one discrete class. our model groups voxels into regions for efficient processing, but also refines the region boundaries to the voxel level for optimal accuracy. this strategy is most effective in data where partial-volume effects due to resolution-limited image acquisition result in intensity ambiguities. our frbhmm employs a forward-backward scheme for parameter estimation through iterative computation of region class likelihoods. we validate our proposed method on simulated and clinical brain mris of both normal and multiple sclerosis subjects. quantitative results demonstrate the advantages of our fuzzy model over the discrete approach with significant improvements in classification accuracy (30% reduction in mean square error).
optimal graph search segmentation using arc-weighted graph for simultaneous surface detection of bladder and prostate. we present a novel method for globally optimal surface segmentation of multiple mutually interacting objects, incorporating both edge and shape knowledge in a 3-d graph-theoretic approach. hard surface interacting constraints are enforced in the interacting regions, preserving the geometric relationship of those partially interacting surfaces. the soft smoothness a priori shape compliance is introduced into the energy functional to provide shape guidance. the globally optimal surfaces can be simultaneously achieved by solving a maximum flow problem based on an arc-weighted graph representation. representing the segmentation problem in an arc-weighted graph, one can incorporate a wider spectrum of constraints into the formulation, thus increasing segmentation accuracy and robustness in volumetric image data. to the best of our knowledge, our method is the first attempt to introduce the arc-weighted graph representation into the graph-searching approach for simultaneous segmentation of multiple partially interacting objects, which admits a globally optimal solution in a low-order polynomial time. our new approach was applied to the simultaneous surface detection of bladder and prostate. the result was quite encouraging in spite of the low saliency of the bladder and prostate in ct images.
multiple sclerosis lesion segmentation using an automatic multimodal graph cuts. graph cuts have been shown as a powerful interactive segmentation technique in several medical domains. we propose to automate the graph cuts in order to automatically segment multiple sclerosis (ms) lesions in mri. we replace the manual interaction with a robust em-based approach in order to discriminate between ms lesions and the normal appearing brain tissues (nabt). evaluation is performed in synthetic and real images showing good agreement between the automatic segmentation and the target segmentation. we compare our algorithm with the state of the art techniques and with several manual segmentations. an advantage of our algorithm over previously published ones is the possibility to semi-automatically improve the segmentation due to the graph cuts interactive feature.
3d medical image segmentation by multiple-surface active volume models. in this paper, we propose multiple-surface active volume models (msavm) to extract 3d objects from volumetric medical images. being able to incorporate spatial constraints among multiple objects, msavm is more robust and accurate than the original active volume models [1]. the main novelty in msavm is that it has two surface-distance based functions to adaptively adjust the weights of contribution from the image-based region information and from spatial constraints among multiple interacting surfaces. these two functions help msavm not only overcome local minima but also avoid leakage. because of the implicit representation of avm, the spatial information can be calculated based on the model's signed distance transform map with very low extra computational cost. the msavm thus has the efficiency of the original 3d avm but produces more accurate results. 3d segmentation results, validation and comparison are presented for experiments on volumetric medical images.
mapping growth patterns and genetic influences on early brain development in twins. despite substantial progress in understanding the anatomical and functional development of the human brain, little is known on the spatial-temporal patterns and genetic influences on white matter maturation in twins. neuroimaging data acquired from longitudinal twin studies provide a unique platform for scientists to investigate such issues. however, the interpretation of neuroimaging data from longitudinal twin studies is hindered by the lacking of appropriate image processing and statistical tools. in this study, we developed a statistical framework for analyzing longitudinal twin neuroimaging data, which is consisted of generalized estimating equation (gee2) and a test procedure. the gee2 method can jointly model imaging measures with genetic effect, environmental effect, and behavioral and clinical variables. the score test statistic is used to test linear hypothesis such as the association between brain structure and function with the covariates of interest. a resampling method is used to control the family-wise error rate to adjust for multiple comparisons. with diffusion tensor imaging (dti), we demonstrate the application of our statistical methods in quantifying the spatiotemporal white matter maturation patterns and in detecting the genetic effects in a longitudinal neonatal twin study. the proposed approach can be easily applied to longitudinal twin data with multiple outcomes and accommodate incomplete and unbalanced data, i.e., subjects with different number of measurements.
combining registration and minimum surfaces for the segmentation of the left ventricle in cardiac cine mr images. this paper describes a system to automatically segment the left ventricle in all slices and all phases of cardiac cine magnetic resonance datasets. after localizing the left ventricle blood pool using motion, thresholding and clustering, slices are segmented sequentially. for each slice, deformable registration is used to align all the phases, candidates contours are recovered in the average image using shortest paths, and a minimal surface is built to generate the final contours. the advantage of our method is that the resulting contours follow the edges in each phase and are consistent over time. we demonstrate using 19 patient examples that the results are very good. the rms distance between ground truth and our segmentation is only 1.6 pixels (2.7 mm) and the dice coefficient is 0.89.
utero-fetal unit and pregnant woman modeling using a computer graphics approach for dosimetry studies. potential sanitary effects related to electromagnetic fields exposure raise public concerns, especially for fetuses during pregnancy. human fetus exposure can only be assessed through simulated dosimetry studies, performed on anthropomorphic models of pregnant women. in this paper, we propose a new methodology to generate a set of detailed utero-fetal unit (ufu) 3d models during the first and third trimesters of pregnancy, based on segmented 3d ultrasound and mri data. ufu models are built using recent geometry processing methods derived from mesh-based computer graphics techniques and embedded in a synthetic woman body. nine pregnant woman models have been generated using this approach and validated by obstetricians, for anatomical accuracy and representativeness.
statistical location model for abdominal organ localization. initial placement of the models is an essential pre-processing step for model-based organ segmentation. based on the observation that organs move along with the spine and their relative locations remain relatively stable, we built a statistical location model (slm) and applied it to abdominal organ localization. the model is a point distribution model which learns the pattern of variability of organ locations relative to the spinal column from a training set of normal individuals. the localization is achieved in three stages: spine alignment, model optimization and location refinement. the slm is optimized through maximum a posteriori estimation of a probabilistic density model constructed for each organ. our model includes five organs: liver, left kidney, right kidney, spleen and pancreas. we validated our method on 12 abdominal cts using leave-one-out experiments. the slm enabled reduction in the overall localization error from 62.0±28.5 mm to 5.8±1.5 mm. experiments showed that the slm was robust to the reference model selection.
functional segmentation of fmri data using adaptive non-negative sparse pca (anspca). we propose a novel method for functional segmentation of fmri data that incorporates multiple functional attributes such as activation effects and functional connectivity, under a single framework. similar to pca, our method exploits the structure of the correlation matrix but with neighborhood information adaptively integrated to encourage detection of spatially contiguous clusters yet without falsely pooling non-active voxels near the functional boundaries. in addition, our method adaptively combines pca and replicator dynamics, which we show to be equivalent to non-negative sparse pca, based on the sparsity of the activation pattern. we validate our method quantitatively on synthetic data and demonstrate that it outperforms methods including replicator dynamics, pca, gaussian mixture models, and general linear models. furthermore, when applied to real fmri data, our method successfully segmented the brodmann area 6 into its known functional sub-regions, whereas other conventional methods that we examined failed to attain such delineation.
a tract-specific framework for white matter morphometry combining macroscopic and microscopic tract features. diffusion tensor imaging plays a key role in our understanding of white matter (wm) both in normal populations and in populations with brain disorders. existing techniques focus primarily on using diffusivity-based quantities derived from diffusion tensor as surrogate measures of microstructural tissue properties of wm. in this paper, we describe a novel tract-specific framework that enables the examination of wm morphometry at both the macroscopic and microscopic scales. the framework leverages the skeleton-based modeling of sheet-like wm fasciculi using the continuous medial representation, which gives a natural definition of thickness and supports its comparison across subjects. the thickness measure provides a macroscopic characterization of wm fasciculi that complements existing analysis of microstructural features. the utility of the framework is demonstrated in quantifying wm atrophy in amyotrophic lateral sclerosis, a severe neurodegenerative disease of motor neurons. we show that, compared to using microscopic features alone, combining the macroscopic and microscopic features gives a more holistic characterization of the disease.
topological correction of brain surface meshes using spherical harmonics. a brain surface reconstruction allows advanced analysis of structural and functional brain data that is not possible using volumetric data alone. however, the generation of a brain surface mesh from mri data often introduces topological defects and artifacts that must be corrected. we show that it is possible to accurately correct these errors using spherical harmonics. our results clearly demonstrate that brain surface meshes reconstructed using spherical harmonics are free from topological defects and large artifacts that were present in the uncorrected brain surface. visual inspection reveals that the corrected surfaces are of very high quality. the spherical harmonic surfaces are also quantitatively validated by comparing the surfaces to an "ideal" brain based on a manually corrected average of twelve scans of the same subject. in conclusion, the spherical harmonics approach is a direct, computationally fast method to correct topological errors.
a two-level approach towards semantic colon segmentation: removing extra-colonic findings. computer aided detection (cad) of colonic polyps in computed tomographic colonography has tremendously impacted colorectal cancer diagnosis using 3d medical imaging. it is a prerequisite for all cad systems to extract the air-distended colon segments from 3d abdomen computed tomography scans. in this paper, we present a two-level statistical approach of first separating colon segments from small intestine, stomach and other extra-colonic parts by classification on a new geometric feature set; then evaluating the overall performance confidence using distance and geometry statistics over patients. the proposed method is fully automatic and validated using both the classification results in the first level and its numerical impacts on false positive reduction of extra-colonic findings in a cad system. it shows superior performance than the state-of-art knowledge or anatomy based colon segmentation algorithms [1,2,3].
an inverse scattering algorithm for the segmentation of the luminal border on intravascular ultrasound data. intravascular ultrasound (ivus) is a catheter-based medical imaging technique that produces cross-sectional images of blood vessels and is particularly useful for studying atherosclerosis. in this paper, we present a novel method for segmentation of the luminal border on ivus images using the radio frequency (rf) raw signal based on a scattering model and an inversion scheme. the scattering model is based on a random distribution of point scatterers in the vessel. the per-scatterer signal uses a differential backscatter cross-section coefficient (dbc) that depends on the tissue type. segmentation requires two inversions: a calibration inversion and a reconstruction inversion. in the calibration step, we use a single manually segmented frame and then solve an inverse problem to recover the dbc for the lumen and vessel wall (¿ l and ¿ w , respectively) and the width of the impulse signal ¿. in the reconstruction step, we use the parameters from the calibration step to solve a new inverse problem: for each angle ¿ i of the ivus data, we reconstruct the lumen-vessel wall interface. we evaluated our method using three 40mhz ivus sequences by comparing with manual segmentations. our preliminary results indicate that it is possible to segment the luminal border by solving an inverse problem using the ivus rf raw signal with the scatterer model.
a novel 3d joint markov-gibbs model for extracting blood vessels from pc-mra images. new techniques for more accurate segmentation of a 3d cerebrovascular system from phase contrast (pc) magnetic resonance angiography (mra) data are proposed. in this paper, we describe pc---mra images and desired maps of regions by a joint markov-gibbs random field model (mgrf) of independent image signals and interdependent region labels but focus on most accurate model identification. to better specify region borders, each empirical distribution of signals is precisely approximated by a linear combination of discrete gaussians (lcdg) with positive and negative components. we modified the conventional expectation-maximization (em) algorithm to deal with the lcdg. the initial segmentation based on the lcdg-models is then iteratively refined using a mgrf model with analytically estimated potentials. experiments with both the phantoms and real data sets confirm high accuracy of the proposed approach.
high-quality model generation for finite element simulation of tissue deformation. in finite element simulation, size, shape, and placement of the elements in a model are significant factors that affect the interpolation and numerical errors of a solution. in medical simulations, such models are desired to have higher accuracy near features such as anatomical boundaries (surfaces) and they are often required to have element faces lying along these surfaces. conventional modelling schemes consist of a segmentation step delineating the anatomy followed by a meshing step generating elements conforming to this segmentation. in this paper, a one-step energy-based model generation technique is proposed. an objective function is minimized when each element of a mesh covers similar image intensities while, at the same time, having desirable fem characteristics. such a mesh becomes essential for accurate models for deformation simulation, especially when the image intensities represent a mechanical feature of the tissue such as the elastic modulus. the use of the proposed mesh optimization is demonstrated on synthetic phantoms, 2d/3d brain mr images, and prostate ultrasound-elastography data.
shape analysis of human brain interhemispheric fissure bending in mri. this paper introduces a novel approach to analyze yakovlevian torque by quantifying the bending of human brain interhemispheric fissure in three-dimensional magnetic resonance imaging. it extracts the longitudinal medial surface between the cerebral hemispheres, which are segmented with an accurate and completely automatic technique, as the shape representation of the interhemispheric fissure. the extracted medial surface is modeled with a polynomial surface through least-square fitting. finally, curvature features, e.g. principal, gaussian and mean curvatures, are computed at each point of the fitted medial surface to describe the local bending of the interhemispheric fissure. this method was applied to clinical images of healthy controls (12 males, 7 females) and never-medicated schizophrenic subjects (11 males, 7 females). the hypothesis of the normal interhemispheric fissure bending (rightward in the occipital region) was quantitatively demonstrated. moreover, we found significant differences (p < 0.05) between the male schizophrenics and healthy controls with respect to the interhemispheric fissure bending in the frontal and occipital regions. these results show that our method is applicable for studying abnormal yakovlevian torque related to mental diseases.
particle based shape regression of open surfaces with applications to developmental neuroimaging. shape regression promises to be an important tool to study the relationship between anatomy and underlying clinical or biological parameters, such as age. in this paper we propose a new method to building shape models that incorporates regression analysis in the process of optimizing correspondences on a set of open surfaces. the statistical significance of the dependence is evaluated using permutation tests designed to estimate the likelihood of achieving the observed statistics under numerous rearrangements of the shape parameters with respect to the explanatory variable. we demonstrate the method on synthetic data and provide a new results on clinical mri data related to early development of the human head.
conditional variability of statistical shape models based on surrogate variables. we propose to increment a statistical shape model with surrogate variables such as anatomical measurements and patient-related information, allowing conditioning the shape distribution to follow prescribed anatomical constraints. the method is applied to a shape model of the human femur, modeling the joint density of shape and anatomical parameters as a kernel density. results show that it allows for a fast, intuitive and anatomically meaningful control on the shape deformations and an effective conditioning of the shape distribution, allowing the analysis of the remaining shape variability and relations between shape and anatomy. the approach can be further employed for initializing elastic registration methods such as active shape models, improving their regularization term and reducing the search space for the optimization.
an object-based method for rician noise estimation in mr images. the estimation of the noise level in mr images is used to assess the consistency of statistical analysis or as an input parameter in some image processing techniques. most of the existing rician noise estimation methods are based on background statistics, and as such are sensitive to ghosting artifacts. in this paper, a new object-based method is proposed. this method is based on the adaptation of the median absolute deviation (mad) estimator in the wavelet domain for rician noise. the adaptation for rician noise is performed by using only the wavelet coefficients corresponding to the object and by correcting the estimation with an iterative scheme based on the snr of the image. a quantitative validation on synthetic phantom with artefacts is presented and a new validation framework is proposed to perform quantitative validation on real data. the results show the accuracy and the robustness of the proposed method.
cortical shape analysis in the laplace-beltrami feature space. for the automated analysis of cortical morphometry, it is critical to develop robust descriptions of the position of anatomical structures on the convoluted cortex. using the eigenfunction of the laplace-beltrami operator, we propose in this paper a novel feature space to characterize the cortical geometry. derived from intrinsic geometry, this feature space is invariant to scale and pose variations, anatomically meaningful, and robust across population. a learning-based sulci detection algorithm is developed in this feature space to demonstrate its application in cortical shape analysis. automated sulci detection results with 10 training and 15 testing surfaces are presented.
depth data improves skin lesion segmentation. this paper shows that adding 3d depth information to rgb colour images improves segmentation of pigmented and non-pigmented skin lesion. a region-based active contour segmentation approach using a statistical model based on the level-set framework is presented. we consider what kinds of properties (e.g., colour, depth, texture) are most discriminative. the experiments show that our proposed method integrating chromatic and geometric information produces segmentation results for pigmented lesions close to dermatologists and more consistent and accurate results for non-pigmented lesions.
towards accurate, automatic segmentation of the hippocampus and amygdala from mri. we describe progress towards fully automatic segmentation of the hippocampus (hc) and amygdala (ag) in human subjects from mri data. three methods are described and tested with a set of mris from 80 young normal controls, using manual labeling of the hc and ag as a gold standard. the methods include: 1) our animal atlas-based method that uses non-linear registration to a pre-labeled non-linear average template (icbm152). hc and ag labels, defined on the template are mapped through the inverse transformation to segment these structures on the subject's mri; 2) template-based segmentation, where we select the most similar mri from the set of 80 labeled datasets to use as a template in the standard animal segmentation scheme; 3) label fusion methods where we combine segmentations from the `n' most similar templates. the label fusion technique yields the best results with median kappas of 0.886 and 0.826 for hc and ag, respectively.
gender differences in cerebral cortical folding: multivariate complexity-shape analysis with insights into handling brain-volume differences. this paper presents a study of gender differences in adult human cerebral cortical folding patterns. the study employs a new multivariate statistical descriptor for analyzing folding patterns in a region of interest (roi) and a rigorous nonparametric permutation-based scheme for hypothesis testing. unlike typical roi-based methods that summarize folding complexity or shape by single/few numbers, the proposed descriptor systematically constructs a unified description of complexity and shape in a high-dimensional space (thousands of numbers/dimensions). furthermore, this paper presents new mathematical insights into the relationship of intra-cranial volume (icv) with cortical complexity and shows that conventional complexity descriptors implicitly handle icv differences in different ways, thereby lending different meanings to "complexity". this paper describes two systematic methods for handling icv changes in folding studies using the proposed descriptor. the clinical study in this paper exploits these theoretical insights to demonstrate that (i) the answer to which gender has higher/lower "complexity" depends on how a folding measure handles icv differences and (ii) cortical folds in males and females differ significantly in shape as well.
intrinsic regression models for manifold-valued data. in medical imaging analysis and computer vision, there is a growing interest in analyzing various manifold-valued data including 3d rotations, planar shapes, oriented or directed directions, the grassmann manifold, deformation field, symmetric positive definite (spd) matrices and medial shape representations (m-rep) of subcortical structures. particularly, the scientific interests of most population studies focus on establishing the associations between a set of covariates (e.g., diagnostic status, age, and gender) and manifold-valued data for characterizing brain structure and shape differences, thus requiring a regression modeling framework for manifold-valued data. the aim of this paper is to develop an intrinsic regression model for the analysis of manifold-valued data as responses in a riemannian manifold and their association with a set of covariates, such as age and gender, in euclidean space. because manifold-valued data do not form a vector space, directly applying classical multivariate regression may be inadequate in establishing the relationship between manifold-valued data and covariates of interest, such as age and gender, in real applications. our intrinsic regression model, which is a semiparametric model, uses a link function to map from the euclidean space of covariates to the riemannian manifold of manifold data. we develop an estimation procedure to calculate an intrinsic least square estimator and establish its limiting distribution. we develop score statistics to test linear hypotheses on unknown parameters. we apply our methods to the detection of the difference in the morphological changes of the left and right hippocampi between schizophrenia patients and healthy controls using medial shape description.
mesh generation from 3d multi-material images. the problem of generating realistic computer models of objects represented by 3d segmented images is important in many biomedical applications. labelled 3d images impose particular challenges for meshing algorithms because multi-material junctions form features such as surface pacthes, edges and corners which need to be preserved into the output mesh. in this paper, we propose a feature preserving delaunay refinement algorithm which can be used to generate high-quality tetrahedral meshes from segmented images. the idea is to explicitly sample corners and edges from the input image and to constrain the delaunay refinement algorithm to preserve these features in addition to the surface patches. our experimental results on segmented medical images have shown that, within a few seconds, the algorithm outputs a tetrahedral mesh in which each material is represented as a consistent submesh without gaps and overlaps. the optimization property of the delaunay triangulation makes these meshes suitable for the purpose of realistic visualization or finite element simulations.
left ventricle segmentation via graph cut distribution matching. we present a discrete kernel density matching energy for segmenting the left ventricle cavity in cardiac magnetic resonance sequences. the energy and its graph cut optimization based on an original first-order approximation of the bhattacharyya measure have not been proposed previously, and yield competitive results in nearly real-time. the algorithm seeks a region within each frame by optimization of two priors, one geometric (distance-based) and the other photometric, each measuring a distribution similarity between the region and a model learned from the first frame. based on global rather than pixelwise information, the proposed algorithm does not require complex training and optimization with respect to geometric transformations. unlike related active contour methods, it does not compute iterative updates of computationally expensive kernel densities. furthermore, the proposed first-order analysis can be used for other intractable energies and, therefore, can lead to segmentation algorithms which share the flexibility of active contours and computational advantages of graph cuts. quantitative evaluations over 2280 images acquired from 20 subjects demonstrated that the results correlate well with independent manual segmentations by an expert.
surface/volume-based articulated 3d spine inference through markov random fields. this paper presents a method towards inferring personalized 3d spine models to intraoperative ct data acquired for corrective spinal surgery. an accurate 3d reconstruction from standard x-rays is obtained before surgery to provide the geometry of vertebrae. the outcome of this procedure is used as basis to derive an articulated spine model that is represented by consecutive sets of intervertebral articulations relative to rotation and translation parameters (6 degrees of freedom). inference with respect to the model parameters is then performed using an integrated and interconnected markov random field graph that involves singleton and pairwise costs. singleton potentials measure the support from the data (surface or image-based) with respect to the model parameters, while pairwise constraints encode geometrical dependencies between vertebrae. optimization of model parameters in a multi-modal context is achieved using efficient linear programming and duality. we show successful image registration results from simulated and real data experiments aimed for image-guidance fusion.
setting priors and enforcing constraints on matches for nonlinear registration of meshes. we show that a simple probabilistic modelling of the registration problem for surfaces allows to solve it by using standard clustering techniques. in this framework, point-to-point correspondences are hypothesized between the two free-form surfaces, and we show how to specify priors and to enforce global constraints on these matches with only minor changes to the optimisation algorithm. the purpose of these two modifications is to increase its capture range and to obtain more realistic geometrical transformations between the surfaces. we conclude with some validation experiments and results on synthetic and real data.
use of simulated atrophy for performance analysis of brain atrophy estimation approaches. in this paper, we study the performance of popular brain atrophy estimation algorithms using a simulated gold standard. the availability of a gold standard facilitates a sound evaluation of the measures of atrophy estimation, which is otherwise complicated. firstly, we propose an approach for the construction of a gold standard. it involves the simulation of a realistic brain tissue loss based on the estimation of a topology preserving b-spline based deformation fields. using this gold standard, we present an evaluation of three standard brain atrophy estimation methods (siena, sienax and bsi) in the presence of bias field inhomogeneity and noise. the effect of brain lesion load on the measured atrophy is also evaluated. our experiments demonstrate that siena, sienax and bsi show a deterioration in their performance in the presence of bias field inhomogeneity and noise. the observed mean absolute errors in the measured percentage of brain volume change (pbvc) are 0.35%±0.38, 2.03%±1.46 and 0.91%±0.80 for siena, sienax and bsi, respectively, for simulated whole brain atrophies in the range 0 ¿ 1%.
incompressible cardiac motion estimation of the left ventricle using tagged mr images. interpolation from sparse imaging data is typically required to achieve dense, three-dimensional quantification of left ventricular function. although the heart muscle is known to be incompressible, this fact is ignored by most previous approaches that address this problem. in this paper, we present a method to reconstruct a dense representation of the three-dimensional, incompressible deformation of the left ventricle from tagged mr images acquired in both short-axis and long axis orientations. the approach applies a smoothing, divergence-free, vector spline to interpolate velocity fields at intermediate discrete times such that the collection of velocity fields integrate over time to match the observed displacement components. through this process, the method yields a dense estimate of a displacement field that matches our observations and also corresponds to an incompressible motion.
3d multi-branch tubular surface and centerline extraction with 4d iterative key points. an innovative 3d multi-branch tubular structure and centerline extraction method is proposed in this paper. in contrast to classical minimal path techniques that can only detect a single curve between two pre-defined initial points, this method propagates outward from only one initial seed point to detect 3d multi-branch tubular surfaces and centerlines simultaneously. first, instead of only representing the trajectory of a tubular structure as a 3d curve, the surface of the entire structure is represented as a 4d curve along which every point represents a 3d sphere inside the tubular structure. then, from any given sphere inside the tubular structure, a novel 4d iterative key point searching scheme is applied, in which the minimal action map and the euclidean length map are calculated with a 4d freezing fast marching evolution. a set of 4d key points is obtained during the front propagation process. finally, by sliding back from each key point to the previous one via the minimal action map until all the key points are visited, we are able to fully obtain global minimizing multi-branch tubular surfaces. an additional immediate benefit of this method is a natural notion of a multi-branch tube's "central curve" by taking only the first three spatial coordinates of the detected 4d multi-branch curve. experimental results on 2d/3d medical vascular images illustrate the benefits of this method.
actin filament tracking based on particle filters and stretching open active contour models. we introduce a novel algorithm for actin filament tracking and elongation measurement. particle filters (pf) and stretching open active contours (soac) work cooperatively to simplify the modeling of pf in a one-dimensional state space while naturally integrating filament body constraints to tip estimation. our algorithm reduces the pf state spaces to one-dimensional spaces by tracking filament bodies using soac and probabilistically estimating tip locations along the curve length of soacs. experimental evaluation on tirfm image sequences with very low snrs demonstrates the accuracy and robustness of this approach.
atlas-based improved prediction of magnetic field inhomogeneity for distortion correction of epi data. we describe a method for atlas-based segmentation of structural mri for calculation of magnetic fieldmaps. ct data sets are used to construct a probabilistic atlas of the head and corresponding mr is used to train a classifier that segments soft tissue, air, and bone. subject-specific fieldmaps are computed from the segmentations using a perturbation field model. previous work has shown that distortion in echo-planar images can be corrected using predicted fieldmaps. we obtain results that agree well with acquired fieldmaps: 90% of voxel shifts from predicted fieldmaps show subvoxel disagreement with those computed from acquired fieldmaps. in addition, our fieldmap predictions show statistically significant improvement following inclusion of the atlas.
model-based estimation of ventricular deformation in the cat brain. the estimation of ventricular deformation has important clinical implications related to neuro-structural disorders such as hydrocephalus. in this paper, a poroelastic model was used to represent deformation effects resulting from the ventricular system and was studied in 5 feline experiments. chronic or acute hydrocephalus was induced by injection of kaolin into the cisterna magna or saline into the ventricles; a catheter was then inserted in the lateral ventricle to drain the fluid out of the brain. the measured displacement data which was extracted from pre-drainage and post-drainage mr images were incorporated into the model through the adjoint equations method. the results indicate that the computational model of the brain and ventricular system captured 33% of the ventricle deformation on average and the model-predicted intraventricular pressure was accurate to 90% of the recorded value during the chronic hydrocephalus experiments.
a hybrid 1d and 3d approach to hemodynamics modelling for a patient-specific cerebral vasculature and aneurysm. in this paper we present a hybrid 1d/3d approach to haemodynamics modelling in a patient-specific cerebral vasculature and aneurysm. the geometric model is constructed from a 3d cta image. a reduced form of the governing equations for blood flow is coupled with an empirical wall equation and applied to the arterial tree. the equation system is solved using a maccormack finite difference scheme and the results are used as the boundary conditions for a 3d flow solver. the computed wall shear stress (wss) agrees with published data.
ecoc random fields for lumen segmentation in radial artery ivus sequences. the measure of lumen volume on radial arteries can be used to evaluate the vessel response to different vasodilators. in this paper, we present a framework for automatic lumen segmentation in longitudinal cut images of radial artery from intravascular ultrasound sequences. the segmentation is tackled as a classification problem where the contextual information is exploited by means of conditional random fields (crfs). a multi-class classification framework is proposed, and inference is achieved by combining binary crfs according to the error-correcting-output-code technique. the results are validated against manually segmented sequences. finally, the method is compared with other state-of-the-art classifiers.
global and local multi-valued dissimilarity-based classification: application to computer-aided detection of tuberculosis. in many applications of computer-aided detection (cad) it is not possible to precisely localize lesions or affected areas in images that are known to be abnormal. in this paper a novel approach to computer-aided detection is presented that can deal effectively with such weakly labeled data. our approach is based on multi-valued dissimilarity measures that retain more information about underlying local image features than single-valued dissimilarities. we show how this approach can be extended by applying it locally as well as globally, and by merging the local and global classification results into an overall opinion about the image to be classified. the framework is applied to the detection of tuberculosis (tb) in chest radiographs. this is the first study to apply a cad system to a large database of digital chest radiographs obtained from a tb screening program, including normal cases, suspect cases and cases with proven tb. the global dissimilarity approach achieved an area under the roc curve of 0.81. the combination of local and global classifications increased this value to 0.83.
automatic correction of intensity nonuniformity from sparseness of gradient distribution in medical images. we propose to use the sparseness property of the gradient probability distribution to estimate the intensity nonuniformity in medical images, resulting in two novel automatic methods: a non-parametric method and a parametric method. our methods are easy to implement because they both solve an iteratively re-weighted least squares problem. they are remarkably accurate as shown by our experiments on images of different imaged objects and from different imaging modalities.
steerable features for statistical 3d dendrite detection. most state-of-the-art algorithms for filament detection in 3-d image-stacks rely on computing the hessian matrix around individual pixels and labeling these pixels according to its eigenvalues. this approach, while very effective for clean data in which linear structures are nearly cylindrical, loses its effectiveness in the presence of noisy data and irregular structures.in this paper, we show that using steerable filters to create rotationally invariant features that include higher-order derivatives and training a classifier based on these features lets us handle such irregular structures. this can be done reliably and at acceptable computational cost and yields better results than state-of-the-art methods.
feature-based morphometry. this paper presents feature-based morphometry (fbm), a new, fully data-driven technique for identifying group-related differences in volumetric imagery. in contrast to most morphometry methods which assume one-to-one correspondence between all subjects, fbm models images as a collage of distinct, localized image features which may not be present in all subjects. fbm thus explicitly accounts for the case where the same anatomical tissue cannot be reliably identified in all subjects due to disease or anatomical variability. a probabilistic model describes features in terms of their appearance, geometry, and relationship to sub-groups of a population, and is automatically learned from a set of subject images and group labels. features identified indicate group-related anatomical structure that can potentially be used as disease biomarkers or as a basis for computer-aided diagnosis. scale-invariant image features are used, which reflect generic, salient patterns in the image. experiments validate fbm clinically in the analysis of normal (nc) and alzheimer's (ad) brain images using the freely available oasis database. fbm automatically identifies known structural differences between nc and ad subjects in a fully data-driven fashion, and obtains an equal error classification rate of 0.78 on new subjects.
computer-aided assessment of anomalies in the scoliotic spine in 3-d mri images. the assessment of anomalies in the scoliotic spine using magnetic resonance imaging (mri) is an essential task during the planning phase of a patient's treatment and operations. due to the pathologic bending of the spine, this is an extremely time consuming process as an orthogonal view onto every vertebra is required. in this article we present a system for computer-aided assessment (caa) of anomalies in 3-d mri images of the spine relying on curved planar reformations (cpr). we introduce all necessary steps, from the pre-processing of the data to the visualization component. as the core part of the framework is based on a segmentation of the spinal cord we focus on this. the proposed segmentation method is an iterative process. in every iteration the segmentation is updated by an energy based scheme derived from markov random field (mrf) theory. we evaluate the segmentation results on public available clinical relevant 3-d mri data sets of scoliosis patients. in order to assess the quality of the segmentation we use the angle between automatically computed planes through the vertebra and planes estimated by medical experts. this results in a mean angle difference of less than six degrees.
model completion via deformation cloning based on an explicit global deformation model. our main focus is the registration and visualization of a pre-built 3d model from preoperative images to the camera view of a minimally invasive surgery (mis). accurate estimation of soft-tissue deformations is key to the success of such a registration. this paper proposes an explicit statistical model to represent global non-rigid deformations. the deformation model built from a reference object is cloned to a target object to guide the registration of the pre-built model, which completes the deformed target object when only a part of the object is naturally visible in the camera view. the registered target model is then used to estimate deformations of its substructures. our method requires a small number of landmarks to be reconstructed from the camera view. the registration is driven by a small set of parameters, making it suitable for real-time visualization.
detection of spatially correlated objects in 3 images using appearance models and coupled active contours. we consider the problem of segmenting 3d images that contain a dense collection of spatially correlated objects, such as fluorescent labeled cells in tissue. our approach involves an initial modeling phase followed by a data-fitting segmentation phase. in the first phase, cell shape (membrane bound) is modeled implicitly using a parametric distribution of correlation function estimates. the nucleus is modeled for its shape as well as image intensity distribution inspired from the physics of its image formation. in the second phase, we solve the segmentation problem using a variational level-set strategy with coupled active contours to minimize a novel energy functional. we demonstrate the utility of our approach on multispectral fluorescence microscopy images.
parametric representation of cortical surface folding based on polynomials. the development of folding descriptors as an effective approach for describing geometrical complexity and variation of the human cerebral cortex has been of great interests. this paper presents a parametric representation of cortical surface patches using polynomials, that is, the primitive cortical patch is compactly and effectively described by four parametric coefficients. by this parametric representation, the patterns of cortical patches can be classified by either model-driven approach or data-driven clustering approach. in the model-driven approach, any patch of the cortical surface is classified into one of eight primitive shape patterns including peak, pit, ridge, valley, saddle ridge, saddle valley, flat and inflection, corresponding to eight sub-spaces of the four parameters. the major advantage of this polynomial representation of cortical folding pattern is its compactness and effectiveness, while being rich in shape information. we have applied this parametric representation for segmentation of cortical surface and promising results are obtained.
a generic probabilistic active shape model for organ segmentation. probabilistic models are extensively used in medical image segmentation. most of them employ parametric representations of densities and make idealizing assumptions, e.g. normal distribution of data. often, such assumptions are inadequate and limit a broader application. we propose here a novel probabilistic active shape model for organ segmentation, which is entirely built upon non-parametric density estimates. in particular, a nearest neighbor boundary appearance model is complemented by a cascade of boosted classifiers for region information and combined with a shape model based on parzen density estimation. image and shape terms are integrated into a single level set equation. our approach has been evaluated for 3-d liver segmentation using a public data base originating from a competition (http://sliver07.org). with an average surface distance of 1.0 mm and an average volume overlap error of 6.5 %, it outperforms other automatic methods and provides accuracy close to interactive ones. since no adaptions specific to liver segmentation have been made, our probabilistic active shape model can be applied to other segmentation tasks easily.
cell segmentation using front vector flow guided active contours. phase-contrast microscopy is a common approach for studying the dynamics of cell behaviors, such as cell migration. cell segmentation is the basis of quantitative analysis of the immense cellular images. however, the complicated cell morphological appearance in phase-contrast microscopy images challenges the existing segmentation methods. this paper proposes a new cell segmentation method for cancer cell migration studies using phase-contrast images. instead of segmenting cells directly based on commonly used low-level features, e.g. intensity and gradient, we first identify the leading protrusions, a high level feature, of cancer cells. based on the identified cell leading protrusions, we introduce a front vector flow guided active contour, which guides the initial cell boundaries to the real boundaries. the experimental validation on a set of breast cancer cell images shows that the proposed method demonstrates fast, stable, and accurate segmentation for breast cancer cells with wide range of sizes and shapes.
image-driven cardiac left ventricle segmentation for the evaluation of multiview fused real-time 3-dimensional echocardiography images. real-time 3-dimensional echocardiography (rt3de) permits the acquisition and visualization of the beating heart in 3d. despite a number of efforts to automate the left ventricle (lv) delineation from rt3de images, this remains a challenging problem due to the poor nature of the acquired images usually containing missing anatomical information and high speckle noise. recently, there have been efforts to improve image quality and anatomical definition by acquiring multiple single-view rt3de images with small probe movements and fusing them together after alignment. in this work, we evaluate the quality of the multiview fused images using an image-driven semi-automatic lv segmentation method. the segmentation method is based on an edge-driven level set framework, where the edges are extracted using a local-phase inspired feature detector for low-contrast echocardiography boundaries. this totally image-driven segmentation method is applied for the evaluation of end-diastolic (ed) and end-systolic (es) single-view and multiview fused images. experiments were conducted on 17 cases and the results show that multiview fused images have better image segmentation quality, but large failures were observed on ed (88.2%) and es (58.8%) single-view images.
mkl for robust multi-modality ad classification. we study the problem of classifying mild alzheimer's disease (ad) subjects from healthy individuals (controls) using multi-modal image data, to facilitate early identification of ad related pathologies. several recent papers have demonstrated that such classification is possible with mr or pet images, using machine learning methods such as svm and boosting. these algorithms learn the classifier using one type of image data. however, ad is not well characterized by one imaging modality alone, and analysis is typically performed using several image types --- each measuring a different type of structural/functional characteristic. this paper explores the ad classification problem using multiple modalities simultaneously. the difficulty here is to assess the relevance of each modality (which cannot be assumed a priori), as well as to optimize the classifier. to tackle this problem, we utilize and adapt a recently developed idea called multi-kernel learning (mkl). briefly, each imaging modality spawns one (or more kernels) and we simultaneously solve for the kernel weights and a maximum margin classifier. to make the model robust, we propose strategies to suppress the influence of a small subset of outliers on the classifier --- this yields an alternative minimization based algorithm for robust mkl. we present promising multi-modal classification experiments on a large dataset of images from the adni project.
supervised nonparametric image parcellation. segmentation of medical images is commonly formulated as a supervised learning problem, where manually labeled training data are summarized using a parametric atlas. summarizing the data alleviates the computational burden at the expense of possibly losing valuable information on inter-subject variability. this paper presents a novel framework for supervised nonparametric image parcellation (snip). snip models the intensity and label images as samples of a joint distribution estimated from the training data in a non-parametric fashion. by capitalizing on recently developed fast and robust pairwise image alignment tools, snip employs the entire training data to segment a new image via expectation maximization. the use of multiple registrations increases robustness to occasional registration failures. we report experiments on 39 volumetric brain mri scans with manual labels for the white matter, cortex and subcortical structures. snip yields better segmentation than state-of-the-art algorithms in multiple regions of interest.
an interactive geometric technique for upper and lower teeth segmentation. due to the complexity of the dental models in semantics of both shape and form, a fully automated method for the separation of the lower and upper teeth is unsuitable while manual segmentation requires painstakingly user interventions. in this paper, we present a novel interactive method to segment the upper and lower teeth. the process is performed on 3d triangular mesh of the skull and consists of four main steps: reconstruction of 3d model from teeth ct images, curvature estimation, interactive segmentation path planning using the shortest path finding algorithm, and performing actual geometric cut on 3d models using a graph cut algorithm. the accuracy and efficiency of our method were experimentally validated via comparisons with ground truth (manual segmentation) as well as the state of art interactive mesh segmentation algorithms. we show the presented scheme can dramatically save manual effort for users while retaining an acceptable quality (with an averaged 0.29 mm discrepancy from the ideal segmentation).
a fully automatic random walker segmentation for skin lesions in a supervised setting. we present a method for automatically segmenting skin lesions by initializing the random walker algorithm with seed points whose properties, such as colour and texture, have been learnt via a training set. we leverage the speed and robustness of the random walker algorithm and augment it into a fully automatic method by using supervised statistical pattern recognition techniques. we validate our results by comparing the resulting segmentations to the manual segmentations of an expert over 120 cases, including 100 cases which are categorized as difficult (i.e.: low contrast, heavily occluded, etc.). we achieve an f-measure of 0.95 when segmenting easy cases, and an f-measure of 0.85 when segmenting difficult cases.
vascular territory image analysis using vessel encoded arterial spin labeling. arterial spin labeling (asl) permits the non-invasive assessment of cerebral perfusion, by magnetically labeling all the blood flowing into the brain. vessel encoded (ve) asl extends this concept by introducing spatial modulations of the labeling procedure, resulting in different patterns of label applied to the blood from different vessels. here a bayesian inference solution to the analysis of ve-asl is presented based on a description of the relative locations of labeled vessels and a probabilistic classification of brain tissue to vessel source. in simulation and on real data the method is shown to reliably determine vascular territories in the brain, including the case where the number of vessels exceeds the number of independent measurements.
toward early diagnosis of lung cancer. our long term research goal is to develop a fully automated, image-based diagnostic system for early diagnosis of pulmonary nodules that may lead to lung cancer. in this paper, we focus on generating new probabilistic models for the estimated growth rate of the detected lung nodules from low dose computed tomography (ldct). we propose a new methodology for 3d ldct data registration which is non-rigid and involves two steps: (i) global target-to-prototype alignment of one scan to another using the learned prior appearance model followed by (ii) local alignment in order to correct for intricate relative deformations. visual appearance of these chest images is described using a markov---gibbs random field (mgrf) model with multiple pairwise interaction. an affine transformation that globally registers a target to a prototype is estimated by the gradient ascent-based maximization of a special gibbs energy function. to handle local deformations, we displace each voxel of the target over evolving closed equi-spaced surfaces (iso-surfaces) to closely match the prototype. the evolution of the iso-surfaces is guided by a speed function in the directions that minimize distances between the corresponding voxel pairs on the iso-surfaces in both the data sets. preliminary results show that the proposed accurate registration could lead to precise diagnosis and identification of the development of the detected pulmonary nodules.
automated calibration for computerized analysis of prostate lesions using pharmacokinetic magnetic resonance images. the feasibility of an automated calibration method for estimating the arterial input function when calculating pharmacokinetic parameters from dynamic contrast enhanced mri is shown. in a previous study [1], it was demonstrated that the computer aided diagnoses (cadx) system performs optimal when per patient calibration was used, but required manual annotation of reference tissue. in this study we propose a fully automated segmentation method that tackles this limitation and tested the method with our cadx system when discriminating prostate cancer from benign areas in the peripheral zone.a method was developed to automatically segment normal peripheral zone tissue (pz). context based segmentation using the otsu histogram based threshold selection method and by hessian based blob detection, was developed to automatically select pz as reference tissue for the per patient calibration.in 38 consecutive patients carcinoma, benign and normal tissue were annotated on mr images by a radiologist and a researcher using whole mount step-section histopathology as standard of reference. a feature set comprising pharmacokinetic parameters was computed for each roi and used to train a support vector machine (svm) as classifier.in total 42 malignant, 29 benign and 37 normal regions were annotated. the diagnostic accuracy obtained for differentiating malignant from benign lesions using a conventional general patient plasma profile showed an accuracy of 0.65 (0.54-0.76). using the automated segmentation per patient calibration method the diagnostic value improved to 0.80 (0.71-0.88), whereas the manual segmentation per patient calibration showed a diagnostic performance of 0.80 (0.70-0.90).these results show that an automated per-patient calibration is feasible, a significant better discriminating performance compared to the conventional fixed calibration was obtained and the diagnostic accuracy is similar to using manual per-patient calibration.
a computational model of cerebral cortex folding. folding of the human cerebral cortex has intrigued many people for many years. quantitative description of cortical folding pattern and understanding of the underlying mechanisms have emerged as an important research goal. this paper presents a computational 3d geometric model of cerebral cortex folding that is initialized by mri data of human fetus brain and deformed under the governance of partial differential equations modeling the cortical growth. the simulations of this 3d geometric model provide computational experiment support to the following hypotheses: 1) mechanical constraints of the brain skull regulate the cortical folding process. 2) the cortical folding pattern is dependent on the global cell growth rate in the whole cortex. 3) the cortical folding pattern is dependent on relative degrees of tethering of different cortical areas and the initial geometry.
using frankenstein's creature paradigm to build a patient specific atlas. conformal radiotherapy planning needs accurate delineations of the critical structures. atlas-based segmentation has been shown to be very efficient to delineate brain structures. it would therefore be very interesting to develop an atlas for the head and neck region where 7 % of the cancers arise. however, the construction of an atlas in this region is very difficult due to the high variability of the anatomies. this can generate segmentation errors and over-segmented structures in the atlas. to overcome this drawback, we present an alternative method to build a template locally adapted to the patient's anatomy. this is done first by selecting in a database the images that are the most similar to the patient on predefined regions of interest, using on a distance between transformations. the first major contribution is that we do not compute every patient-to-image registration to find the most similar image, but only the registration of the patient towards an average image. this method is therefore computationally very efficient. the second major contribution is a novel method to use the selected images and the predefined regions to build a "frankenstein's creature" for segmentation. we present a qualitative and quantitative comparison between the proposed method and a classical atlas-based segmentation method. this evaluation is performed on a subset of 58 patients among a database of 105 head and neck ct images and shows a great improvement of the specificity of the results.
on the blurring of the funk-radon transform in q-ball imaging. one known issue in q---ball imaging is the blurring in the radial integral defining the orientation distribution function of fiber bundles, due to the computation of the funk---radon transform (frt). three novel techniques to overcome this problem are presented, all of them based upon different assumptions about the behavior of the attenuation signal outside the sphere densely sampled from hardi data sets. a systematic study with synthetic data has been carried out to show that the frt blurring is not as important as the error introduced by some unrealistic assumptions, and only one of the three techniques (the one with the less restrictive assumption) improves the accuracy of q---balls.
a new approach for creating customizable cytoarchitectonic probabilistic maps without a template. we present a novel technique for creating template-free probabilistic maps of the cytoarchitectonic areas using a groupwise registration. we use the technique to transform 10 human post-mortem structural mr data sets, together with their corresponding cytoarchitectonic information, to a common space. we have targeted the cytoarchitectonically defined subregions of the primary auditory cortex. thanks to the template-free groupwise registration, the created maps are not macroanatomically biased towards a specific geometry/topology. the advantage of the groupwise versus pairwise registration in avoiding such anatomical bias is better revealed in studies with small number of subjects and a high degree of variability among the individuals such as the post-mortem data. a leave-one-out cross-validation method was used to compare the sensitivity, specificity and positive predictive value of the proposed and published maps. we observe a significant improvement in localization of cytoarchitectonically defined subregions in primary auditory cortex using the proposed maps. the proposed maps can be tailored to any subject space by registering the subject image to the average of the groupwise-registered post-mortem images.
intra-retinal layer segmentation in optical coherence tomography using an active contour approach. optical coherence tomography (oct) is a non-invasive, depth resolved imaging modality that has become a prominent ophthalmic diagnostic technique. we present an automatic segmentation algorithm to detect intra-retinal layers in oct images acquired from rodent models of retinal degeneration. we adapt chan---vese's energy-minimizing active contours without edges for oct images, which suffer from low contrast and are highly corrupted by noise. we adopt a multi-phase framework with a circular shape prior in order to model the boundaries of retinal layers and estimate the shape parameters using least squares. we use a contextual scheme to balance the weight of different terms in the energy functional. the results from various synthetic experiments and segmentation results on 20 oct images from four rats are presented, demonstrating the strength of our method to detect the desired retinal layers with sufficient accuracy and average dice similarity coefficient of 0.85, specifically 0.94 for the the ganglion cell layer, which is the relevant layer for glaucoma diagnosis.
genetics of anisotropy asymmetry: registration and sample size effects. brain asymmetry has been a topic of interest for neuroscientists for many years. the advent of diffusion tensor imaging (dti) allows researchers to extend the study of asymmetry to a microscopic scale by examining fiber integrity differences across hemispheres rather than the macroscopic differences in shape or structure volumes. even so, the power to detect these microarchitectural differences depends on the sample size and how the brain images are registered and how many subjects are studied. we fluidly registered 4 tesla dti scans from 180 healthy adult twins (45 identical and fraternal pairs) to a geometrically-centered population mean template. we computed voxelwise maps of significant asymmetries (left/right hemisphere differences) for common fiber anisotropy indices (fa, ga). quantitative genetic models revealed that 47-62% of the variance in asymmetry was due to genetic differences in the population. we studied how these heritability estimates varied with the type of registration target (t1- or t2-weighted) and with sample size. all methods consistently found that genetic factors strongly determined the lateralization of fiber anisotropy, facilitating the quest for specific genes that might influence brain asymmetry and fiber integrity.
biomechanically-constrained 4d estimation of myocardial motion. we propose a method for the analysis of cardiac images with the goal of reconstructing the motion of the ventricular walls. the main feature of our method is that the inversion parameter field is the active contraction of the myocardial fibers. this is accomplished with a biophysically-constrained, four-dimensional (space plus time) formulation that aims to complement information that can be gathered from the images by a priori knowledge of cardiac mechanics. our main hypothesis is that by incorporating biophysical information, we can generate more informative priors and thus, more accurate predictions of the ventricular wall motion. in this paper, we outline the formulation, discuss the computational methodology for solving the inverse motion estimation, and present preliminary validation using synthetic and tagged mr images. the overall method uses patient-specific imaging and fiber information to reconstruct the motion. in these preliminary tests, we verify the implementation and conduct a parametric study to test the sensitivity of the model to material properties perturbations, model errors, and incomplete and noisy observations.
enforcing monotonic temporal evolution in dry eye images. we address the problem of identifying dry areas in the tear film as part of a diagnostic tool for dry-eye syndrome. the requirement is to identify and measure the growth of the dry regions to provide a time-evolving map of degrees of dryness. we segment dry regions using a multi-label graph-cut algorithm on the 3d spatio-temporal volume of frames from a video sequence. to capture the fact that dryness increases over the time of the sequence, we use a time-asymmetric cost function that enforces a constraint that the dryness of each pixel monotonically increases. we demonstrate how this increases our estimation's reliability and robustness. we tested the method on a set of videos and suggest further research using a similar approach.
improved modelling of ultrasound contrast agent diminution for blood perfusion analysis. ultrasound contrast imaging is increasingly used to analyze blood perfusion in cases of ischemic or cancerous diseases. among other imaging methods, the diminution harmonic imaging (dhi), which modells the diminution of contrast agent due to ultrasound pulses, is the most promising because of its speed. however, the current imaging quality of dhi is insufficient for reliable diagnoses.in this paper, we extend the mathematical dhi model to include the part of the intensity signal which is due to tissue reflections and other effects not based on the contrast agent and its concentration in the blood. we show in a phantom experiment with available perfusion ground truth the vast improvements in accuracy of the new model. our findings also strongly support the theory of a linear relationship between the perfusion speed and the determined perfusion coefficient, which is a large step towards quantitative perfusion measurements.
tensor-based morphometry with mappings parameterized by stationary velocity fields in alzheimer's disease neuroimaging initiative. tensor-based morphometry (tbm) is an analysis technique where anatomical information is characterized by means of the spatial transformations between a customized template and observed images. therefore, accurate inter-subject non-rigid registration is an essential prerrequisite. further statistical analysis of the spatial transformations is used to highlight some useful information, such as local statistical differences among populations. with the new advent of recent and powerful non-rigid registration algorithms based on the large deformation paradigm, tbm is being increasingly used. in this work we evaluate the statistical power of tbm using stationary velocity field diffeomorphic registration in a large population of subjects from alzheimer's disease neuroimaging initiative project. the proposed methodology provided atrophy maps with very detailed anatomical resolution and with a high significance compared with results published recently on the same data set.
a deformation tracking approach to 4d coronary artery tree reconstruction. this paper addresses reconstruction of a temporally deforming 3d coronary vessel tree, i.e., 4d reconstruction from a sequence of angiographic x-ray images acquired by a rotating c-arm. our algorithm starts from a 3d coronary tree that was reconstructed from images of one cardiac phase. driven by gradient vector flow (gvf) fields, the method then estimates deformation such that projections of deformed models align with x-ray images of corresponding cardiac phases. to allow robust tracking of the coronary tree, the deformation estimation is regularized by smoothness and cyclic deformation constraints. extensive qualitative and quantitative tests on clinical data sets suggest that our algorithm reconstructs accurate 4d coronary trees and regularized estimation significantly improves robustness. our experiments also suggest that a hierarchy of deformation models with increasing complexities are desirable when input data are noisy or when the quality of the 3d model is low.
contact studies between total knee replacement components developed using explicit finite elements analysis. a pneumatic simulator of the knee joint with five dof was developed to determine the correlation between the kinematics of the knee joint, and the wear of the polyethylene componenent of a tkr prosthesis. a physical model of the knee joint with total knee replacement (tkr) was built by rapid-prototyping based on ct images from a patient. a clinically-available prosthesis was mounted on the knee model. using a video analysis system, and two force and contact pressure plates, the kinematics and kinetics data were recorded during normal walking of the patient. the quadriceps muscle force during movement was computed using the anybody software. joint loadings were generated by the simulator based on recorded and computed data. using the video analysis system, the precise kinematics of the artificial joint from the simulator was recorded and used as input for an explicit dynamics fe analysis of the joint. the distribution of the contact stresses in the implant was computed during the walking cycle to analyze the prosthesis behavior. the results suggest that the combination of axial loading and anterior-posterior stress is responsible for the abrasive wear of the polyethylene component of the prosthesis.
atlas-based automated segmentation of spleen and liver using adaptive enhancement estimation. the paper presents the automated segmentation of spleen and liver from contrast-enhanced ct images of normal and hepato/splenomegaly populations. the method used 4 steps: (i) a mean organ model was registered to the patient ct; (ii) the first estimates of the organs were improved by a geodesic active contour; (iii) the contrast enhancements of liver and spleen were estimated to adjust to patient image characteristics, and an adaptive convolution refined the segmentations; (iv) lastly, a normalized probabilistic atlas corrected for shape and location for the precise computation of each organ's volume and height (mid-hepatic liver height and cephalocaudal spleen height). results from test data demonstrated the method's ability to accurately segment the spleen (rms error = 1.09mm; dice/tanimoto overlaps = 95.2/91) and liver (rms error = 2.3mm, and dice/tanimoto overlaps = 96.2/92.7). the correlations (r2) with clinical/manual height measurements were 0.97 and 0.93 for the spleen and liver respectively.
pattern recognition of abnormal left ventricle wall motion in cardiac mr. there are four main problems that limit application of pattern recognition techniques for recognition of abnormal cardiac left ventricle (lv) wall motion: 1) normalization of the lv's size, shape, intensity level and position; 2) defining a spatial correspondence between phases and subjects; 3) extracting features; 4) and discriminating abnormal from normal wall motion. solving these four problems is required for application of pattern recognition techniques to classify the normal and abnormal lv wall motion. in this work, we introduce a normalization scheme to solve the first and second problems. with this scheme, lvs are normalized to the same position, size, and intensity level. using the normalized images, we proposed an intra-segment classification criterion based on a correlation measure to solve the third and fourth problems. application of the method to recognition of abnormal cardiac mr lv wall motion showed promising results.
segmentation and classification of cell cycle phases in fluorescence imaging. current chemical biology methods for studying spatiotemporal correlation between biochemical networks and cell cycle phase progression in live-cells typically use fluorescence-based imaging of fusion proteins. stable cell lines expressing fluorescently tagged protein gfp-pcna produce rich, dynamically varying sub-cellular foci patterns characterizing the cell cycle phases, including the progress during the s-phase. variable fluorescence patterns, drastic changes in snr, shape and position changes and abundance of touching cells require sophisticated algorithms for reliable automatic segmentation and cell cycle classification. we extend the recently proposed graph partitioning active contours (gpac) for fluorescence-based nucleus segmentation using regional density functions and dramatically improve its efficiency, making it scalable for high content microscopy imaging. we utilize surface shape properties of gfp-pcna intensity field to obtain descriptors of foci patterns and perform automated cell cycle phase classification, and give quantitative performance by comparing our results to manually labeled data.
learning copd sensitive filters in pulmonary ct. the standard approaches to analyzing emphysema in computed tomography (ct) images are visual inspection and the relative area of voxels below a threshold (ra). the former approach is subjective and impractical in a large data set and the latter relies on a single threshold and independent voxel information, ignoring any spatial correlation in intensities. in recent years, supervised learning on texture features has been investigated as an alternative to these approaches, showing good results. however, supervised learning requires labeled samples, and these samples are often obtained via subjective and time consuming visual scoring done by human experts.in this work, we investigate the possibility of applying supervised learning using texture measures on random ct samples where the labels are based on external, non-ct measures. we are not targeting emphysema directly, instead we focus on learning textural differences that discriminate subjects with chronic obstructive pulmonary disease (copd) from healthy smokers, and it is expected that emphysema plays a major part in this. the proposed texture based approach achieves an 69% classification accuracy which is significantly better than ra's 55% accuracy.
building shape models from lousy data. statistical shape models have gained widespread use in medical image analysis. in order for such models to be statistically meaningful, a large number of data sets have to be included. the number of available data sets is usually limited and often the data is corrupted by imaging artifacts or missing information. we propose a method for building a statistical shape model from such "lousy" data sets. the method works by identifying the corrupted parts of a shape as statistical outliers and excluding these parts from the model. only the parts of a shape that were identified as outliers are discarded, while all the intact parts are included in the model. the model building is then performed using the em algorithm for probabilistic principal component analysis, which allows for a principled way to handle missing data. our experiments on 2d synthetic and real 3d medical data sets confirm the feasibility of the approach. we show that it yields superior models compared to approaches using robust statistics, which only downweight the influence of outliers.
segmentation of lumbar vertebrae using part-based graphs and active appearance models. the aim of the work is to provide a fully automatic method of segmenting vertebrae in spinal radiographs. this is of clinical relevance to the diagnosis of osteoporosis by vertebral fracture assessment, and to grading incident fractures in clinical trials. we use a parts based model of small vertebral patches (e.g. corners). many potential candidates are found in a global search using multi-resolution normalised correlation. the ambiguity in the possible solution is resolved by applying a graphical model of the connections between parts, and applying geometric constraints. the resulting graph optimisation problem is solved using loopy belief propagation.the minimum cost solution is used to initialise a second phase of active appearance model search. the method is applied to a clinical data set of computed radiography images of lumbar spines. the accuracy of this fully automatic method is assessed by comparing the results to a gold standard of manual annotation by expert radiologists.
predictive simulation of bidirectional glenn shunt using a hybrid blood vessel model. this paper proposes a method for performing predictive simulation of cardiac surgery. it applies a hybrid approach to model the deformation of blood vessels. the hybrid blood vessel model consists of a reference cosserat rod and a surface mesh. the reference cosserat rod models the blood vessel's global bending, stretching, twisting and shearing in a physically correct manner, and the surface mesh models the surface details of the blood vessel. in this way, the deformation of blood vessels can be computed efficiently and accurately. our predictive simulation system can produce complex surgical results given a small amount of user inputs. it allows the surgeon to easily explore various surgical options and evaluate them. tests of the system using bidirectional glenn shunt (bdg) as an application example show that the results produced by the system are similar to real surgical results.
robust atlas-based brain segmentation using multi-structure confidence-weighted registration. we present a robust and accurate atlas-based brain segmentation method which uses multiple initial structure segmentations to simultaneously drive the image registration and achieve anatomically constrained correspondence. we also derive segmentation confidence maps (scms) from a given manually segmented training set; these characterize the accuracy of a given set of segmentations as compared to manual segmentations. we incorporate these in our cost term to weight the influence of initial segmentations in the multi-structure registration, such that low confidence regions are given lower weight in the registration. to account for correspondence errors in the underlying registration, we use a supervised atlas correction technique and present a method for correcting the atlas segmentation to account for possible errors in the underlying registration. we applied our multi-structure atlas-based segmentation and supervised atlas correction to segment the amygdala in a set of 23 autistic patients and controls using leave-one-out cross validation, achieving a dice overlap score of 0.84. we also applied our method to eight subcortical structures in mri from the internet brain segmentation repository, with results better or comparable to competing methods.
anatomically informed bayesian model selection for fmri group data analysis. a new approach for fmri group data analysis is introduced to overcome the limitations of standard voxel-based testing methods, such as statistical parametric mapping (spm). using a bayesian model selection framework, the functional network associated with a certain cognitive task is selected according to the posterior probabilities of mean region activations, given a pre-defined anatomical parcellation of the brain. this approach enables us to control a bayesian risk that balances false positives and false negatives, unlike the spm-like approach, which only controls false positives. on data from a mental calculation experiment, it detected the functional network known to be involved in number processing, whereas the spm-like approach either swelled or missed the different activation regions.
multi-level ground glass nodule detection and segmentation in ct lung images. early detection of ground glass nodule (ggn) in lung computed tomography (ct) images is important for lung cancer prognosis. due to its indistinct boundaries, manual detection and segmentation of ggn is labor-intensive and problematic. in this paper, we propose a novel multi-level learning-based framework for automatic detection and segmentation of ggn in lung ct images. our main contributions are: firstly, a multi-level statistical learning-based approach that seamlessly integrates segmentation and detection to improve the overall accuracy for ggn detection (in a subvolume). the classification is done at two levels, both voxel-level and object-level. the algorithm starts with a three-phase voxel-level classification step, using volumetric features computed per voxel to generate a ggn class-conditional probability map. ggn candidates are then extracted from this probability map by integrating prior knowledge of shape and location, and the ggn object-level classifier is used to determine the occurrence of the ggn. secondly, an extensive set of volumetric features are used to capture the ggn appearance. finally, to our best knowledge, the ggn dataset used for experiments is an order of magnitude larger than previous work. the effectiveness of our method is demonstrated on a dataset of 1100 subvolumes (100 containing ggns) extracted from about 200 subjects.
lossless online ensemble learning (loel) and its application to subcortical segmentation. in this paper, we study the classification problem in the situation where large volumes of training data become available sequentially (online learning). in medical imaging, this is typical, e.g., a 3d brain mri dataset may be gradually collected from a patient population, and not all of the data is available when the analysis begins. first, we describe two common ensemble learning algorithms, adaboost and bagging, and their corresponding online learning versions. we then show why each is ineffective for segmenting a gradually increasing set of medical images. instead, we introduce a new ensemble learning algorithm, termed lossless online ensemble learning (loel). this algorithm is lossless in the online case, compared to its batch mode. loel outperformed online-adaboost and online-bagging when validated on a standardized dataset; it also performed better when used to segment the hippocampus from brain mri scans of patients with alzheimer's disease and matched healthy subjects. among those tested, loel largely outperformed the alternative online learning algorithms and gave excellent error metrics that were consistent between the online and offline case; it also accurately distinguished ad subjects from healthy controls based on automated measures of hippocampal volume.
noninvasive imaging of electrophysiological substrates in post myocardial infarction. the presence of injured tissues after myocardial infarction (mi) creates substrates responsible for fatal arrhythmia; understanding of its arrhythmogenic mechanism requires investigation of the correlation of local abnormality between phenomenal electrical functions and inherent electrophysiological properties during normal sinus rhythm. this paper presents a physiological-model-constrained framework for imaging post-mi electrophysiological substrates from noninvasive body surface potential measurements. using a priori knowledge of general cardiac electrical activity as constraints, it simultaneously reconstruct transmembrane potential dynamics and tissue excitability inside the 3d myocardium, with the central goal to localize and investigate the abnormality in these two different electrophysiological quantities. it is applied to four post-mi patients with quantitative validations by gold standards and notable improvements over existent results.
liver segmentation using automatically defined patient specific b-spline surface models. this paper presents a novel liver segmentation algorithm. this is a model-driven approach; however, unlike previous techniques which use a statistical model obtained from a training set, we initialize patient-specific models directly from their own pre-segmentation. as a result, the non-trivial problems such as landmark correspondences, model registration etc. can be avoided. moreover, by dividing the liver region into three sub-regions, we convert the problem of building one complex shape model into constructing three much simpler models, which can be fitted independently, greatly improving the computation efficiency. a robust graph-based narrow band optimal surface fitting scheme is also presented. the proposed approach is evaluated on 35 ct images. compared to contemporary approaches, our approach has no training requirement and requires significantly less processing time, with an rms error of 2.44±0.53mm against manual segmentation.
de-anonymizing social networks. operators of online social networks are increasingly sharing potentially sensitive information about users and their relationships with advertisers, application developers, and data-mining researchers.privacy is typically protected by anonymization, i.e., removing names, addresses, etc.we present a framework for analyzing privacy and anonymity in social networks and develop a new re-identification algorithm targeting anonymized social-network graphs.to demonstrate its effectiveness on real-world networks, we show that a third of the users who can be verified to have accounts on both twitter, a popular microblogging service, and flickr, an online photo-sharing site, can be re-identified in the anonymous twitter graph with only a 12% error rate.our de-anonymization algorithm is based purely on the network topology, does not require creation of a large number of dummy "sybil" nodes, is robust to noise and all existing defenses, and works even when the overlap between the target network and the adversary's auxiliary information is small.
practical mitigations for timing-based side-channel attacks on modern x86 processors. this paper studies and evaluates the extent to which automated compiler techniques can defend against timing-based side-channel attacks onmodern x86 processors. we study how modern x86 processors can leak timinginformation through side-channels that relate to control flow and data flow. toeliminate key-dependent control flow and key-dependent timing behavior relatedto control flow, we propose the use of if-conversion in a compiler backend, andevaluate a proof-of-concept prototype implementation. furthermore, we demonstratetwo ways in which programs that lack key-dependent control flow and key- dependent cache behavior can still leak timing information on modern x86implementations such as the intel core 2 duo, and propose defense mechanisms against them.
the mastermind attack on genomic data. in this paper, we study the degree to which a genomic string, $q$,leaks details about itself any time it engages in comparison protocolswith a genomic querier, bob, even if those protocols arecryptographically guaranteed to produce no additional information otherthan the scores that assess the degree to which $q$ matches stringsoffered by bob.we show that such scenarios allow bob to play variantsof the game of mastermind with $q$ so as to learn the complete identityof $q$.we show that there are a number of efficient implementationsfor bob to employ in these mastermind attacks, depending on knowledgehe has about the structure of $q$, which show how quickly he candetermine $q$.indeed, we show that bob can discover $q$ using anumber of rounds of test comparisons that is much smaller than thelength of $q$, under various assumptions regarding the types of scoresthat are returned by the cryptographic protocols and whether he can useknowledge about the distribution that $q$ comes from, e.g., usingpublic knowledge about the properties of human dna.we also providethe results of an experimental study we performed on a database ofmitochondrial dna, showing the vulnerability of existing real-world dnadata to the mastermind attack.
quantifying information leaks in outbound web traffic. as the internet grows and network bandwidth continues to increase, administrators are faced with the task of keeping confidential information from leaving their networks. today’s network traffic is so voluminous that manual inspection would be unreasonably expensive. in response, researchers have created data loss prevention systems that check outgoing traffic for known confidential information. these systems stop naïve adversaries from leaking data, but are fundamentally unable to identify encrypted or obfuscated information leaks. what remains is a high-capacity pipe for tunneling data to the internet. we present an approach for quantifying information leak capacity in network traffic. instead of trying to detect the presence of sensitive data—an impossible task in the general case--our goal is to measure and constrain its maximum volume. we take advantage of the insight that most network traffic is repeated or determined by external information, such as protocol specifications or messages sent by a server. by filtering this data, we can isolate and quantify true information flowing from a computer. in this paper, we present measurement algorithms for the hypertext transfer protocol (http), the main protocol for web browsing. when applied to real web browsing traffic, the algorithms were able to discount 98.5% of measured bytes and effectively isolate information leaks.
privacy weaknesses in biometric sketches. the increasing use of biometrics has given rise to new privacy concerns. biometric encryption systems have been proposed in order to alleviate such concerns: rather than comparing the biometric data directly, a key is derived from these data and subsequently knowledge of this key is proved. one specific application of biometric encryption is the use of biometric sketches: in this case biometric template data are protected with biometric encryption. we address the question whether one can undermine a user's privacy given access to biometrically encrypted documents, and more in particular, we examine if an attacker can determine whether two documents were encrypted using the same biometric. this is a particular concern for biometric sketches that are deployed in multiple locations: in one scenario the same biometric sketch is deployed everywhere; in a second scenario the same biometric data is protected with two different biometric sketches. we present attacks on template protection schemes that can be described as fuzzy sketches based on error-correcting codes. we demonstrate how to link and reverse protected templates produced by code-offset and bit-permutation sketches.
blueprint: robust prevention of cross-site scripting attacks for existing browsers. as social networking sites proliferate across the world wide web, complex user-created html content is rapidly becoming the norm rather than the exception.user-created web content is a notorious vector for cross-site scripting (xss) attacks that target websites and confidential user data.in this threat climate, mechanisms that render web applications immune to xss attacks have been of recent research interest.a challenge for these security mechanisms is enabling web applications to accept complex html input from users, while disallowing malicious script content.this challenge is made difficult by anomalous web browser behaviors, which are often used as vectors for successful xss attacks.motivated by this problem, we present a new xss defense strategy designed to be effective in widely deployed existing web browsers, despite anomalous browser behavior.our approach seeks to minimize trust placed on browsers for interpreting untrusted content.we implemented this approach in a tool called blueprint that was integrated with several popular web applications.we evaluated blueprint against a barrage of stress tests that demonstrate strong resistance to attacks, excellent compatibility with web browsers and reasonable performance overheads.
sphinx: a compact and provably secure mix format. sphinx is a cryptographic message format used to relay anonymized messages within a mix network. it is more compact than any comparable scheme, and supports a full set of security features: indistinguishable replies, hiding the path length and relay position, as well as providing unlinkability for each leg of the message's journey over the network. we prove the full cryptographic security of sphinx in the random oracle model, and we describe how it can be used as an efficient drop-in replacement in deployed remailer systems.
automatic discovery and quantification of information leaks. information-flow analysis is a powerful technique for reasoning about the sensitive information exposed by a program during its execution. we present the first automatic method for information-flow analysis that discovers what information is leaked and computes its comprehensive quantitative interpretation. the leaked information is characterized by an equivalence relation on secret artifacts, and is represented by a logical assertion over the corresponding program variables. our measurement procedure computes the number of discovered equivalence classes and their sizes. this provides a basis for computing a set of quantitative properties, which includes all established information-theoretic measures in quantitative information-flow. our method exploits an inherent connection between formal models of qualitative information-flow and program verification techniques.we provide an implementation of our method that builds upon existing tools for program verification and information-theoretic analysis. our experimental evaluation indicates the practical applicability of the presented method.
noninterference for a practical difc-based operating system. the flume system is an implementation of decentralized information flow control (difc) at the operating system level.prior work has shown flume can be implemented as a practical extension tothe linux operating system, allowing real web applications to achieve useful security guarantees.however, the question remains if the flume system is actually secure.this paper compares flume with other recent difc systems like asbestos, arguing that the latter is inherently susceptible to certain wide-bandwidth covert channels, and proving their absence in flume by means of a noninterference proof in the communicating sequential processes formalism.
prospex: protocol specification extraction. protocol reverse engineering is the process of extracting application-level specifications for network protocols. such specifications are very useful in a number of security-related contexts, for example, to perform deep packet inspection and black-box fuzzing, or to quickly understand custom botnet command and control (c\&c) channels.since manual reverse engineering is a time-consuming and tedious process, a number of systems have been proposed that aim to automate this task. these systems either analyze network traffic directly or monitor the execution of the application that receives the protocol messages. while previous systems show that precise message formats can be extracted automatically, they do not provide a protocol specification.the reason is that they do not reverse engineer the protocol state machine.in this paper, we focus on closing this gap by presenting a system that is capable of automatically inferring state machines. this greatly enhances the results of automatic protocol reverse engineering, while further reducing the need for human interaction. we extend previous work that focuses on behavior-based message format extraction,and introduce techniques for identifying and clustering different types of messages not only based on their structure, but also according to the impact of each message on server behavior.moreover, we present an algorithm for extracting the state machine.we have applied our techniques to a number of real-world protocols, including the command and control protocol used by a malicious bot. our results demonstrate that we are able to extract format specifications for different types of messages and meaningful protocol state machines. we use these protocol specifications to automatically generate input for a stateful fuzzer,allowing us to discover security vulnerabilities in real-world applications.
formally certifying the security of digital signature schemes. we present two machine-checked proofs of the existentialunforgeability under adaptive chosen-message attacks of the fulldomain hash signature scheme. these proofs formalize the originalargument of bellare and rogaway, and an optimal reduction by coronthat provides a tighter bound on the probability of a forgery. bothproofs are developed using certicrypt, a general framework toformalize exact security proofs of cryptographic systems in thecomputational model. since certicrypt is implemented on top of thecoq proof assistant, the proofs are highly trustworthy and can beverified independently and fully automatically.
native client: a sandbox for portable, untrusted x86 native code. this paper describes the design, implementation and evaluation of native client, a sandbox for untrusted x86 native code. native client aims to give browser-based applications the computational performance of native applications without compromising safety. native client uses software fault isolation and a secure runtime to direct system interaction and side effects through interfaces managed by native client. native client provides operating system portability for binary code while supporting performance-oriented features generally absent from web application programming environments, such as thread support, instruction set extensions such as sse, and use of compiler intrinsics and hand-coded assembler. we combine these properties in an open architecture that encourages community review and 3rd-party tools.
clamp: practical prevention of large-scale data leaks. providing online access to sensitive data makes web servers lucrative targets for attackers.a compromise of any of the web server's scripts, applications, or operating system can leak the sensitive data of millions of customers.unfortunately, many systems for stopping data leaks require considerable effort from application developers, hindering their adoption.in this work, we investigate how such leaks can be prevented with minimal developer effort.we propose clamp, an architecture for preventing data leaks even in the presence of web server compromises or sql injection attacks.clamp protects sensitive data by enforcing strong access control on user data and by isolating code running on behalf of different users.by focusing on minimizing developer effort, we arrive at an architecture that allows developers to use familiar operating systems, servers, and scripting languages, while making relatively few changes to application code -- less than 50 lines in our applications.
plaintext recovery attacks against ssh. this paper presents a variety of plaintext-recovering attacks against ssh. we implemented a proof of concept of our attacks against openssh, where we can verifiably recover 14 bits of plaintext from an arbitrary block of ciphertext with probability $2^{-14}$ and 32 bits of plaintext from an arbitrary block of ciphertext with probability $2^{-18}$. these attacks assume the default configuration of a 128-bit block cipher operating in cbc mode. the paper explains why a combination of flaws in the basic design of ssh leads implementations such as openssh to be open to our attacks, why current provable security results for ssh do not cover our attacks, and how the attacks can be prevented in practice.
an epistemic approach to coercion-resistance for electronic voting protocols. coercion resistance is an important and one of themost intricate security requirements of electronicvoting protocols. several definitions of coercionresistance have been proposed in the literature,including definitions based on symbolic models.however, existing definitions in such models arerather restricted in their scope and quite complex.in this paper, we therefore propose a new definitionof coercion resistance in a symbolic setting, basedon an epistemic approach. our definition isrelatively simple and intuitive. it allows for afine-grained formulation of coercion resistance andcan be stated independently of a specific, symbolicprotocol and adversary model. as a proof of concept,we apply our definition to three votingprotocols. in particular, we carry out the firstrigorous analysis of the recently proposed civitassystem.we precisely identify those conditions underwhich this system guarantees coercion resistance orfails to be coercion resistant. we also analyzeprotocols proposed by lee et al. and okamoto.
password cracking using probabilistic context-free grammars. choosing the most effective word-mangling rules to use when performing a dictionary-based password cracking attack can be a difficult task. in this paper we discuss a new method that generates password structures in highest probability order. we first automatically create a probabilistic context-free grammar based upon a training set of previously disclosed passwords. this grammar then allows us to generate word-mangling rules, and from them, password guesses to be used in password cracking. we will also show that this approach seems to provide a more effective way to crack passwords as compared to traditional methods by testing our tools and techniques on real password sets. in one series of experiments, training on a set of disclosed passwords, our approach was able to crack 28% to 129% more passwords than john the ripper, a publicly available standard password cracking program.
secure content sniffing for web browsers, or how to stop papers from reviewing themselves. cross-site scripting defenses often focus on html documents, neglecting attacks involving the browser's content-sniffing algorithm, which can treat non-html content as html.web applications, such as the one that manages this conference, must defend themselves against these attacks or risk authors uploading malicious papers that automatically submit stellar self-reviews.in this paper, we formulate content-sniffing xss attacks and defenses.we study content-sniffing xss attacks systematically by constructing high-fidelity models of the content-sniffing algorithms used by four major browsers.we compare these models with web site content filtering policies to construct attacks.to defend against these attacks, we propose and implement a principled content-sniffing algorithm that provides security while maintaining compatibility.our principles have been adopted, in part, by internet explorer 8 and, in full, by google chrome and the html 5 working group.
automatic reverse engineering of malware emulators. malware authors have recently begun using emulation technology to obfuscate their code. they convert native malware binaries into bytecode programs written in a randomly generated instruction set and paired with a native binary emulator that interprets the bytecode. no existing malware analysis can reliably reverse this obfuscation technique.in this paper, we present the first work in automatic reverse engineering of malware emulators. our algorithms are based on dynamic analysis. we execute the emulated malware in a protected environment and record the entire x86 instruction trace generated by the emulator. we then use dynamic data-flow and taint analysis over the trace to identify data buffers containing the bytecode program and extract the syntactic and semantic information about the bytecode instruction set. with these analysis outputs, we are able to generate data structures, such as control-flow graphs, that provide the foundation for subsequent malware analysis. we implemented a proof-of-concept system calledrotalume and evaluated it using both legitimate programs and malware emulated by vmprotect and code virtualizer. the results show that rotalume accurately reveals the syntax and semantics of emulated instruction sets and reconstructs execution paths of original programs from their bytecode representations.
a logic of secure systems and its application to trusted computing. we present a logic for reasoning about properties of securesystems.the logic is built around a concurrent programminglanguage with constructs for modeling machines with sharedmemory, a simple form of access control on memory, machineresets, cryptographic operations, network communication, anddynamically loading and executing unknown(and potentially untrusted) code.the adversary's capabilities are constrained by the system interface as defined in the programming model (leading to the name csi).we develop a sound proof system for reasoning about programs without explicitly reasoning about adversary actions. we use the logic to characterize trusted computing primitives and prove code integrity and execution integrity properties of two remote attestation protocols. the proofs make precise assumptions needed for the security of these protocols and reveal an insecure interaction between the two protocols.
dsybil: optimal sybil-resistance for recommendation systems. recommendation systems can be attacked in various ways, and the ultimate attack form is reached with a {\em sybil attack}, where the attacker creates a potentially unlimited number of {\em sybil identities} to vote. defending against sybil attacks is often quite challenging, and the nature of recommendation systems makes it even harder. this paper presents {\em dsybil}, a novel defense for diminishing the influence of sybil identities in recommendation systems. dsybil provides strong provable guarantees that hold even under the worst-case attack and are optimal. dsybil can defend against an unlimited number of sybil identities over time. dsybil achieves its strong guarantees by i) exploiting the heavy-tail distribution of the typical voting behavior of the honest identities, and ii) carefully identifying whether the system is already getting ``enough help'' from the (weighted) voters already taken into account or whether more ``help'' is needed. our evaluation shows that dsybil would continue to provide high-quality recommendations even when a million-node botnet uses an optimal strategy to launch a sybil attack.
tempest in a teapot: compromising reflections revisited. reflecting objects such as tea pots and glasses, but also diffusely reflecting objects such as a user's shirt, can be used to spy on confidential data displayed on a monitor. first, we show how reflections in the user's eye can be exploited for spying on confidential data. second, we investigate to what extent monitor images can be reconstructed from the diffuse reflections on a wall or the user's clothes, and provide information-theoretic bounds limiting this type of attack. third, we evaluate the effectiveness of several countermeasures. this substantially improves previous work (backes et al., ieee symposium on security & privacy, 2008).
fingerprinting blank paper using commodity scanners. we develop a novel technique for authenticating physical documentsby using random, naturally occurring imperfections in paper texture.to this end, we devised a new method for measuring thethree-dimensional surface of a paper without modifying the documentin any way, using only a commodity scanner.from this physicalfeature, we generate a concise fingerprint that uniquely identifiesthe document.our method is secure against counterfeiting, robustto harsh handling, and applicable even before any content is printedon a page.it has a wide range of applications, including detectingforged currency and tickets, authenticating passports, and haltingcounterfeit goods.on a more sinister note, document identificationcould be used to de-anonymize printed surveys and to compromise thesecrecy of paper ballots.
it's no secret. measuring the security and reliability of authentication via "secret" questions. all four of the most popular webmail providers -- aol, google, microsoft, and yahoo! -- rely on personal questions as the secondary authentication secrets used to reset account passwords. the security of these questions has received limited formal scrutiny, almost all of which predates webmail. we ran a user study to measure the reliability and security of the questions used by all four webmail providers. we asked participants to answer these questions and then asked their acquaintances to guess their answers. acquaintances with whom participants reported being unwilling to share their webmail passwords were able to guess 17% of their answers. participants forgot 20% of their own answers within six months. what's more, 13% of answers could be guessed within five attempts by guessing the most popular answers of other participants, though this weakness is partially attributable to the geographic homogeneity of our participant pool.
pretty-bad-proxy: an overlooked adversary in browsers' https deployments. https is designed to provide secure web communications over insecure networks. the protocol itself has been rigorously designed and evaluated by assuming the network as an adversary. this paper is motivated by our curiosity about whether such an adversary has been carefully examined when https is integrated into the browser/web systems. we focus on a specific adversary named “pretty-bad-proxy” (pbp). pbp is a malicious proxy targeting browsers’ rendering modules above the http/https layer. it attempts to break the end-to-end security guarantees of https without breaking any cryptographic scheme. we discovered a set of vulnerabilities exploitable by a pbp: in many realistic network environments where attackers can sniff the browser traffic, they can steal sensitive data from an https server, fake an https page and impersonate an authenticated user to access an https server. these vulnerabilities reflect the neglects in the design of modern browsers – they affect multiple major browsers and a large number of websites. we believe that the pbp adversary has not been rigorously examined in the browser/web industry. the vendors of the affected browsers have all confirmed the vulnerabilities reported in this paper. most of them have patched or planned on patching their browsers. we believe the attack scenarios described in this paper may only be a subset of the vulnerabilities under pbp. thus further (and more rigorous) evaluations of the https deployments in browsers appear to be necessary.
wirelessly pickpocketing a mifare classic card. the mifare classic is the most widely used contactless smartcard on the market.the stream cipher crypto1 used by the classic has recently been reverse engineered and serious attacks have been proposed. the most serious of them retrieves a secret key in under a second. in order to clone a card, previously proposed attacks require that the adversary either has access to an eavesdropped communication session or executes a message-by-message man-in-the-middle attack between the victim and a legitimate reader. although this is already disastrous from a cryptographic point of view, system integrators maintain that these attacks cannot be performed undetected.this paper proposes four attacks that can be executed by an adversary having only wireless access to just a card (and not to a legitimate reader). the most serious of them recovers a secret key in less than a second on ordinary hardware. besides the cryptographic weaknesses, we exploit other weaknesses in the protocol stack. a vulnerability in the computation of parity bits allows an adversary to establish a side channel. another vulnerability regarding nested authentications provides enough plaintext for a speedy known-plaintext attack.
exploiting unix file-system races via algorithmic complexity attacks. we defeat two proposed unix file-system race condition defense mechanisms. first, we attack the probabilistic defense mechanism of tsafrir, et al., published at usenix fast 2008. we then show that the same attack breaks the kernel-based dynamic race detector of tsyrklevich and yee, published at usenix security 2003. we then argue that all kernel-based dynamic race detectors must have a model of the programs they protect or provide imperfect protection. the techniques we develop for performing these attacks work on multiple unix operating systems, on uni- and multi-processors, and are useful for exploiting most unix file-system races. we conclude that programmers should use provably-secure methods for avoiding race conditions when accessing the file-system.
disappearing mobile devices. in this paper, we extrapolate the evolution of mobile devices in one specific direction, namely miniaturization. while we maintain the concept of a device that people are aware of and interact with intentionally, we envision that this concept can become small enough to allow invisible integration into arbitrary surfaces or human skin, and thus truly ubiquitous use. this outcome assumed, we investigate what technology would be most likely to provide the basis for these devices, what abilities such devices can be expected to have, and whether or not devices that size can still allow for meaningful interaction. we survey candidate technologies, drill down on gesture-based interaction, and demonstrate how it can be adapted to the desired form factors. while the resulting devices offer only the bare minimum in feedback and only the most basic interactions, we demonstrate that simple applications remain possible. we complete our exploration with two studies in which we investigate the affordance of these devices more concretely, namely marking and text entry using a gesture alphabet.
perceptual interpretation of ink annotations on line charts. asynchronous collaborators often use freeform ink annotations to point to visually salient perceptual features of line charts such as peaks or humps, valleys, rising slopes and declining slopes. we present a set of techniques for interpreting such annotations to algorithmically identify the corresponding perceptual parts. our approach is to first apply a parts-based segmentation algorithm that identifies the visually salient perceptual parts in the chart. our system then analyzes the freeform annotations to infer the corresponding peaks, valleys or sloping segments. once the system has identified the perceptual parts it can highlight them to draw further attention and reduce ambiguity of interpretation in asynchronous collaborative discussions.
integrated videos and maps for driving directions. while onboard navigation systems are gaining in importance, maps are still the medium of choice for laying out a route to a destination and for way finding. however, even with a map, one is almost always more comfortable navigating a route the second time due to the visual memory of the route. to make the first time navigating a route feel more familiar, we present a system that integrates a map with a video automatically constructed from panoramic imagery captured at close intervals along the route. the routing information is used to create a variable speed video depicting the route. during playback of the video, the frame and field of view are dynamically modulated to highlight salient features along the route and connect them back to the map. a user interface is demonstrated to allow exploration of the combined map, video, and textual driving directions. we discuss the construction of the hybrid map and video interface. finally, we report the results of a study that provides evidence of the effectiveness of such a system for route following.
relaxed selection techniques for querying time-series graphs. time-series graphs are often used to visualize phenomena that change over time. common tasks include comparing values at different points in time and searching for specified patterns, either exact or approximate. however, tools that support time-series graphs typically separate query specification from the actual search process, allowing users to adapt the level of similarity only after specifying the pattern. we introduce relaxed selection techniques, in which users implicitly define a level of similarity that can vary across the search pattern, while creating a search query with a single-gesture interaction. users sketch over part of the graph, establishing the level of similarity through either spatial deviations from the graph, or the speed at which they sketch (temporal deviations). in a user study, participants were significantly faster when using our temporally relaxed selection technique than when using traditional techniques. in addition, they achieved significantly higher precision and recall with our spatially relaxed selection technique compared to traditional techniques.
arc-pad: absolute+relative cursor positioning for large displays with a mobile touchscreen. we introduce arc-pad (absolute+relative cursor pad), a novel technique for interacting with large displays using a mobile phone's touchscreen. in arc-pad we combine ab-solute and relative cursor positioning. tapping with arc-pad causes the cursor to jump to the corresponding location on the screen, providing rapid movement across large distances. for fine position control, users can also clutch using relative mode. unlike prior hybrid cursor positioning techniques, arc-pad does not require an explicit switch between relative and absolute modes. we compared arc-pad with the relative positioning commonly found on touchpads. users were given a target acquisition task on a large display, and results showed that they were faster with arc-pad, without sacrificing accuracy. users welcomed the benefits associated with arc-pad.
ripples: utilizing per-contact visualizations to improve user interaction with touch displays. we present ripples, a system which enables visualizations around each contact point on a touch display and, through these visualizations, provides feedback to the user about successes and errors of their touch interactions. our visualization system is engineered to be overlaid on top of existing applications without requiring the applications to be modified in any way, and functions independently of the application's responses to user input. ripples reduces the fundamental problem of ambiguity of feedback when an action results in an unexpected behaviour. this ambiguity can be caused by a wide variety of sources. we describe the ambiguity problem, and identify those sources. we then define a set of visual states and transitions needed to resolve this ambiguity, of use to anyone designing touch applications or systems. we then present the ripples implementation of visualizations for those states, and the results of a user study demonstrating user preference for the system, and demonstrating its utility in reducing errors.
sikuli: using gui screenshots for search and automation. we present sikuli, a visual approach to search and automation of graphical user interfaces using screenshots. sikuli allows users to take a screenshot of a gui element (such as a toolbar button, icon, or dialog box) and query a help system using the screenshot instead of the element's name. sikuli also provides a visual scripting api for automating gui interactions, using screenshot patterns to direct mouse and keyboard events. we report a web-based user study showing that searching by screenshot is easy to learn and faster to specify than keywords. we also demonstrate several automation tasks suitable for visual scripting, such as map navigation and bus tracking, and show how visual scripting can improve interactive help systems previously proposed in the literature.
the rise of the expert amateur: diy culture and citizen science. we are at an important technological inflection point. most of our computing systems have been designed and built by professionally trained experts (i.e. us--computer scientists, engineers, and designers) for use in specific domains and to solve explicit problems. artifacts often called "user manuals" traditionally prescribed the appropriate usage of these tools and implied an acceptable etiquette for interaction and experience. a fringe group of individuals usually labeled "hackers" or "nerds" have challenged this producer-consumer model of technology by hacking novel hardware and software features to "improve" our research and products while a similar creative group of technicians called "artists" have re-directed the techniques, tools, and tenets of accepted technological usage away from their typical manifestations in practicality and product. over time the technological artifacts of these fringe groups and the support for their rhetoric have gained them a foothold into computing culture and eroded the established power discontinuities within the practice of computing research. we now expect our computing tools to be driven by an architecture of open participation and democracy that encourages users to add value to their tools and applications as they use them. similarly, the bar for enabling the design of novel, personal computing systems and "hardware remixes" has fallen to the point where many non-experts and novices are readily embracing and creating fascinating and ingenious computing artifacts outside of our official and traditionally sanctioned academic research communities. but how have we as "expert" practitioners been influencing this discussion? by constructing a practice around the design and development of technology for task based and problem solving applications, we have unintentionally established such work as the status quo for the human computing experience. we have failed in our duty to open up alternate forums for technology to express itself and touch our lives beyond productivity and efficiency. blinded by our quest for "smart technologies" we have forgotten to contemplate the design of technologies to inspire us to be smarter, more curious, and more inquisitive. we owe it to ourselves to rethink the impact we desire to have on this historic moment in computing culture. we must choose to participate in and perhaps lead a dialogue that heralds an expansive new acceptable practice of designing to enable participation by experts and non-experts alike. we are in the milieu of the rise of the "expert amateur". we must change our mantra: "not just usability but usefulness and relevancy to our world, its citizens, and our environment". we must design for the world and what matters. this means discussing our computing research alongside new keywords such as the economy, the environment, activism, poverty, healthcare, famine, homelessness, literacy, religion, and politics. this talk will explore the design territory and potential opportunities for all of us to collaborate and benefit as a society from this cultural movement.
optically sensing tongue gestures for computer input. many patients with paralyzing injuries or medical conditions retain the use of their cranial nerves, which control the eyes, jaw, and tongue. while researchers have explored eye-tracking and speech technologies for these patients, we believe there is potential for directly sensing explicit tongue movement for controlling computers. in this paper, we describe a novel approach of using infrared optical sensors embedded within a dental retainer to sense tongue gestures. we describe an experiment showing our system effectively discriminating between four simple gestures with over 90% accuracy. in this experiment, users were also able to play the popular game tetris with their tongues. finally, we present lessons learned and opportunities for future work.
virtual shelves: interactions with orientation aware devices. triggering shortcuts or actions on a mobile device often requires a long sequence of key presses. because the functions of buttons are highly dependent on the current application's context, users are required to look at the display during interaction, even in many mobile situations when eyes-free interactions may be preferable. we present virtual shelves, a technique to trigger programmable shortcuts that leverages the user's spatial awareness and kinesthetic memory. with virtual shelves, the user triggers shortcuts by orienting a spatially-aware mobile device within the circular hemisphere in front of her. this space is segmented into definable and selectable regions along the phi and theta planes. we show that users can accurately point to 7 regions on the theta and 4 regions on the phi plane using only their kinesthetic memory. building upon these results, we then evaluate a proof-of-concept prototype of the virtual shelves using a nokia n93. the results show that virtual shelves is faster than the n93's native interface for common mobile phone tasks.
interactions in the air: adding further depth to interactive tabletops. although interactive surfaces have many unique and compelling qualities, the interactions they support are by their very nature bound to the display surface. in this paper we present a technique for users to seamlessly switch between interacting on the tabletop surface to above it. our aim is to leverage the space above the surface in combination with the regular tabletop display to allow more intuitive manipulation of digital content in three-dimensions. our goal is to design a technique that closely resembles the ways we manipulate physical objects in the real-world; conceptually, allowing virtual objects to be 'picked up' off the tabletop surface in order to manipulate their three dimensional position or orientation. we chart the evolution of this technique, implemented on two rear projection-vision tabletops. both use special projection screen materials to allow sensing at significant depths beyond the display. existing and new computer vision techniques are used to sense hand gestures and postures above the tabletop, which can be used alongside more familiar multi-touch interactions. interacting above the surface in this way opens up many interesting challenges. in particular it breaks the direct interaction metaphor that most tabletops afford. we present a novel shadow-based technique to help alleviate this issue. we discuss the strengths and limitations of our technique based on our own observations and initial user feedback, and provide various insights from comparing, and contrasting, our tabletop implementations
a practical pressure sensitive computer keyboard. a pressure sensitive computer keyboard is presented that independently senses the force level on every depressed key. the design leverages existing membrane technologies and is suitable for low-cost, high-volume manufacturing. a number of representative applications are discussed.
a reconfigurable ferromagnetic input device. we present a novel hardware device based on ferromagnetic sensing, capable of detecting the presence, position and deformation of any ferrous object placed on or near its surface. these objects can include ball bearings, magnets, iron filings, and soft malleable bladders filled with ferrofluid. our technology can be used to build reconfigurable input devices -- where the physical form of the input device can be assembled using combinations of such ferrous objects. this allows users to rapidly construct new forms of input device, such as a trackball-style device based on a single large ball bearing, tangible mixers based on a collection of sliders and buttons with ferrous components, and multi-touch malleable surfaces using a ferrofluid bladder. we discuss the implementation of our technology, its strengths and limitations, and potential application scenarios.
user guided audio selection from complex sound mixtures. in this paper we present a novel interface for selecting sounds in audio mixtures. traditional interfaces in audio editors provide a graphical representation of sounds which is either a waveform, or some variation of a time/frequency transform. although with these representations a user might be able to visually identify elements of sounds in a mixture, they do not facilitate object-specific editing (e.g. selecting only the voice of a singer in a song). this interface uses audio guidance from a user in order to select a target sound within a mixture. the user is asked to vocalize (or otherwise sonically represent) the desired target sound, and an automatic process identifies and isolates the elements of the mixture that best relate to the user's input. this way of pointing to specific parts of an audio stream allows a user to perform audio selections which would have been infeasible otherwise.
abracadabra: wireless, high-precision, and unpowered finger input for very small mobile devices. we present abracadabra, a magnetically driven input technique that offers users wireless, unpowered, high fidelity finger input for mobile devices with very small screens. by extending the input area to many times the size of the device's screen, our approach is able to offer a high c-d gain, enabling fine motor control. additionally, screen occlusion can be reduced by moving interaction off of the display and into unused space around the device. we discuss several example applications as a proof of concept. finally, results from our user study indicate radial targets as small as 16 degrees can achieve greater than 92% selection accuracy, outperforming comparable radial, touch-based finger input.
mouse 2.0: multi-touch meets the mouse. in this paper we present novel input devices that combine the standard capabilities of a computer mouse with multi-touch sensing. our goal is to enrich traditional pointer-based desktop interactions with touch and gestures. to chart the design space, we present five different multi-touch mouse implementations. each explores a different touch sensing strategy, which leads to differing form-factors and hence interactive possibilities. in addition to the detailed description of hardware and software implementations of our prototypes, we discuss the relative strengths, limitations and affordances of these novel input devices as informed by the results of a preliminary user study.
enabling always-available input with muscle-computer interfaces. previous work has demonstrated the viability of applying offline analysis to interpret forearm electromyography (emg) and classify finger gestures on a physical surface. we extend those results to bring us closer to using muscle-computer interfaces for always-available input in real-world applications. we leverage existing taxonomies of natural human grips to develop a gesture set covering interaction in free space even when hands are busy with other objects. we present a system that classifies these gestures in real-time and we introduce a bi-manual paradigm that enables use in interactive systems. we report experimental results demonstrating four-finger classification accuracies averaging 79% for pinching, 85% while holding a travel mug, and 88% when carrying a weighted bag. we further show generalizability across different arm postures and explore the tradeoffs of providing real-time visual feedback.
using fnirs brain sensing in realistic hci settings: experiments and guidelines. because functional near-infrared spectroscopy (fnirs) eases many of the restrictions of other brain sensors, it has potential to open up new possibilities for hci research. from our experience using fnirs technology for hci, we identify several considerations and provide guidelines for using fnirs in realistic hci laboratory settings. we empirically examine whether typical human behavior (e.g. head and facial movement) or computer interaction (e.g. keyboard and mouse usage) interfere with brain measurement using fnirs. based on the results of our study, we establish which physical behaviors inherent in computer usage interfere with accurate fnirs sensing of cognitive state information, which can be corrected in data analysis, and which are acceptable. with these findings, we hope to facilitate further adoption of fnirs brain sensing technology in hci research.
activity analysis enabling real-time video communication on mobile phones for deaf users. we describe our system called mobileasl for real-time video communication on the current u.s. mobile phone network. the goal of mobileasl is to enable deaf people to communicate with sign language over mobile phones by compressing and transmitting sign language video in real-time on an off-the-shelf mobile phone, which has a weak processor, uses limited bandwidth, and has little battery capacity. we develop several h.264-compliant algorithms to save system resources while maintaining asl intelligibility by focusing on the important segments of the video. we employ a dynamic skin-based region-of-interest (roi) that encodes the skin at higher quality at the expense of the rest of the video. we also automatically recognize periods of signing versus not signing and raise and lower the frame rate accordingly, a technique we call variable frame rate (vfr). we show that our variable frame rate technique results in a 47% gain in battery life on the phone, corresponding to an extra 68 minutes of talk time. we also evaluate our system in a user study. participants fluent in asl engage in unconstrained conversations over mobile phones in a laboratory setting. we find that the roi increases intelligibility and decreases guessing. vfr increases the need for signs to be repeated and the number of conversational breakdowns, but does not affect the users' perception of adopting the technology. these results show that our sign language sensitive algorithms can save considerable resources without sacrificing intelligibility.
collabio: a game for annotating people within social networks. we present collabio, a social tagging game within an online social network that encourages friends to tag one another. collabio's approach of incentivizing members of the social network to generate information about each other produces personalizing information about its users. we report usage log analysis, survey data, and a rating exercise demonstrating that collabio tags are accurate and augment information that could have been scraped online.
interactive viscosity. your conscious experience is not a function of the world, it is a function of the neural networks of your brain. therefore, the biology of the brain and consciousness is as fundamental to understanding the universe, as we know it, as the high-energy physics of subatomic particles. this is especially true for the study of sensory and cognitive illusions, since they represent effects that clearly stand out as not representing the real world. that is, since illusions don't match reality we can know that by studying illusions we are studying exactly what the brain is actually doing, and not just what we think the brain should be doing. your brain does a staggering amount of pragmatic self-dealing guesswork and outright confabulation in order to construct the highly imperfect mental simulation of reality known as "consciousness." this is not to say that objective reality isn't "out there" in a very real sense--but no one lives there. no one's ever even been there for a visit. ironically, the fact that consciousness feels like a solid, robust, fact-rich transcript of reality is just one of the countless illusions your brain creates for itself. illusions are not errors of the brain. far from it. illusions arise from processes that are critical to our survival. our brains have developed illusory processes so that we may experience the world in a ready-to-consume manner. remove the machinery of illusion, and you unwind the entire tapestry of human awareness. illusions are those perceptual experiences that do not match the physical reality. they are therefore exquisite tools with which to analyze the neural correlates of human perception and consciousness. neuroscientists have long known that they can only be sure of where they stand, in terms of correlating neural responses to awareness, when they correlate the awareness of an illusion to the brain's response, specifically because of the illusions' mismatch with reality. the study of illusions is therefore of critical importance to the understanding of the basic mechanisms of sensory perception and conscious awareness. if you've ever seen a good magician perform, you know how thrilling it is to watch the impossible happening before your eyes. the laws of physics, probability, psychology and common sense--the four trusty compass points in your mental map of reality--are suddenly turned into liabilities. objects and people appear, vanish, levitate, transpose, transform, and with all your smarts you can't imagine how it's being done. magicians are the premier artists of attention and awareness, and they manipulate our cognition like clay on a potter's wheel. and the mechanisms underlying magic perception have implications for our daily lives. the magical arts work because humans have hardwired processes of attention and awareness that are hackable. by understanding how magicians hack our brains, we can better understand how we work.
detecting and leveraging finger orientation for interaction with direct-touch surfaces. current interactions on direct-touch interactive surfaces are often modeled based on properties of the input channel that are common in traditional graphical user interfaces (gui) such as x-y coordinate information. leveraging additional information available on the surfaces could potentially result in richer and novel interactions. in this paper we specifically explore the role of finger orientation. this property is typically ignored in touch-based interactions partly because of the ambiguity in determining it solely from the contact shape. we present a simple algorithm that unambiguously detects the directed finger orientation vector in real-time from contact information only, by considering the dynamics of the finger landing process. results of an experimental evaluation show that our algorithm is stable and accurate. we then demonstrate how finger orientation can be leveraged to enable novel interactions and to infer higher-level information such as hand occlusion or user position. we present a set of orientation-aware interaction techniques and widgets for direct-touch surfaces.
tapsongs: tapping rhythm-based passwords on a single binary sensor. tapsongs are presented, which enable user authentication on a single "binary" sensor (e.g., button) by matching the rhythm of tap down/up events to a jingle timing model created by the user. we describe our matching algorithm, which employs absolute match criteria and learns from successful logins. we also present a study of 10 subjects showing that after they created their own tapsong models from 12 examples (
everybodylovessketch: 3d sketching for a broader audience. we present everybodylovessketch, a gesture-based 3d curve sketching system for rapid ideation and visualization of 3d forms, aimed at a broad audience. we first analyze traditional perspective drawing in professional practice. we then design a system built upon the paradigm of ilovesketch, a 3d curve drawing system for design professionals. the new system incorporates many interaction aspects of perspective drawing with judicious automation to enable novices with no perspective training to proficiently create 3d curve sketches. everybodylovessketch supports a number of novel interactions: tick-based sketch plane selection, single view definition of arbitrary extrusion vectors, multiple extruded surface sketching, copy-and-project of 3d curves, freeform surface sketching, and an interactive perspective grid. finally, we present a study involving 49 high school students (with no formal artistic training) who each learned and used the system over 11 days, which provides detailed insights into the popularity, power and usability of the various techniques, and shows our system to be easily learnt and effectively used, with broad appeal.
contact area interaction with sliding widgets. we show how to design touchscreen widgets that respond to a finger's contact area. in standard touchscreen systems a finger often appears to touch several screen objects, but the system responds as though only a single pixel is touched. in contact area interaction all objects under the finger respond to the touch. users activate control widgets by sliding a movable element, as though flipping a switch. these sliding widgets resolve selection ambiguity and provide designers with a rich vocabulary of self-disclosing interaction mechanism. we showcase the design of several types of sliding widgets, and report study results showing that the simplest of these widgets, the sliding button, performs on-par with medium-sized pushbuttons and offers greater accuracy for small-sized buttons.
changing how people view changes on the web. the web is a dynamic information environment. web content changes regularly and people revisit web pages frequently. but the tools used to access the web, including browsers and search engines, do little to explicitly support these dynamics. in this paper we present diffie, a browser plug-in that makes content change explicit in a simple and lightweight manner. diffie caches the pages a person visits and highlights how those pages have changed when the person returns to them. we describe how we built a stable, reliable, and usable system, including how we created compact, privacy-preserving page representations to support fast difference detection. via a longitudinal user study, we explore how diffie changed the way people dealt with changing content. we find that much of its benefit came not from exposing expected change, but rather from drawing attention to unexpected change and helping people build a richer understanding of the web content they frequent.
augmenting interactive tables with mice & keyboards. this note examines the role traditional input devices can play in surface computing. mice and keyboards can enhance tabletop technologies since they support high fidelity input, facilitate interaction with distant objects, and serve as a proxy for user identity and position. interactive tabletops, in turn, can enhance the functionality of traditional input devices: they provide spatial sensing, augment devices with co-located visual content, and support connections among a plurality of devices. we introduce eight interaction techniques for a table with mice and keyboards, and we discuss the design space of such interactions.
the web page as a wysiwyg end-user customizable database-backed information management application. dido is an application (and application development environment) in a web page. it is a single web page containing rich structured data, an ajaxy interactive visualizer/editor for that data, and a "metaeditor" for wysiwyg editing of the visualizer/editor. historically, users have been limited to the data schemas, visualizations, and interactions offered by a small number of heavyweight applications. in contrast, dido encourages and enables the end user to edit (not code) in his or her web browser a distinct ephemeral interaction "wrapper" for each data collection that is specifically suited to its intended use. dido's active document metaphor has been explored before but we show how, given today's web infrastructure, it can be deployed in a small self-contained html document without touching a web client or server.
semfeel: a user interface with semantic tactile feedback for mobile touch-screen devices. one of the challenges with using mobile touch-screen devices is that they do not provide tactile feedback to the user. thus, the user is required to look at the screen to interact with these devices. in this paper, we present semfeel, a tactile feedback system which informs the user about the presence of an object where she touches on the screen and can offer additional semantic information about that item. through multiple vibration motors that we attached to the backside of a mobile touch-screen device, semfeel can generate different patterns of vibration, such as ones that flow from right to left or from top to bottom, to help the user interact with a mobile device. through two user studies, we show that users can distinguish ten different patterns, including linear patterns and a circular pattern, at approximately 90% accuracy, and that semfeel supports accurate eyes-free interactions.
photoelastictouch: transparent rubbery tangible interface using an lcd and photoelasticity. photoelastictouch is a novel tabletop system designed to intuitively facilitate touch-based interaction via real objects made from transparent elastic material. the system utilizes vision-based recognition techniques and the photoelastic properties of the transparent rubber to recognize deformed regions of the elastic material. our system works with elastic materials over a wide variety of shapes and does not require any explicit visual markers. compared to traditional interactive surfaces, our 2.5 dimensional interface system enables direct touch interaction and soft tactile feedback. in this paper we present our force sensing technique using photoelasticity and describe the implementation of our prototype system. we also present three practical applications of photoelastictouch, a force-sensitive touch panel, a tangible face application, and a paint application.
communitycommands: command recommendations for software applications. we explore the use of modern recommender system technology to address the problem of learning software applications. before describing our new command recommender system, we first define relevant design considerations. we then discuss a 3 month user study we conducted with professional users to evaluate our algorithms which generated customized recommendations for each user. analysis shows that our item-based collaborative filtering algorithm generates 2.1 times as many good suggestions as existing techniques. in addition we present a prototype user interface to ambiently present command recommendations to users, which has received promising initial user feedback.
a screen-space formulation for 2d and 3d direct manipulation. rotate-scale-translate (rst) interactions have become the de facto standard when interacting with two-dimensional (2d) contexts in single-touch and multi-touch environments. because the use of rst has thus far focused almost entirely on 2d, there are not yet standard techniques for extending these principles into three dimensions. in this paper we describe a screen-space method which fully captures the semantics of the traditional 2d rst multi-touch interaction, but also allows us to extend these same principles into three-dimensional (3d) interaction. just like rst allows users to directly manipulate 2d contexts with two or more points, our method allows the user to directly manipulate 3d objects with three or more points. we show some novel interactions, which take perspective into account and are thus not available in orthographic environments. furthermore, we identify key ambiguities and unexpected behaviors that arise when performing direct manipulation in 3d and offer solutions to mitigate the difficulties each presents. finally, we show how to extend our method to meet application-specific control objectives, as well as show our method working in some example environments.
bonfire: a nomadic system for hybrid laptop-tabletop interaction. we present bonfire, a self-contained mobile computing system that uses two laptop-mounted laser micro-projectors to project an interactive display space to either side of a laptop keyboard. coupled with each micro-projector is a camera to enable hand gesture tracking, object recognition, and information transfer within the projected space. thus, bonfire is neither a pure laptop system nor a pure tabletop system, but an integration of the two into one new nomadic computing platform. this integration (1) enables observing the periphery and responding appropriately, e.g., to the casual placement of objects within its field of view, (2) enables integration between physical and digital objects via computer vision, (3) provides a horizontal surface in tandem with the usual vertical laptop display, allowing direct pointing and gestures, and (4) enlarges the input/output space to enrich existing applications. we describe bonfire's architecture, and offer scenarios that highlight bonfire's advantages. we also include lessons learned and insights for further development and use.
mining web interactions to automatically create mash-ups. the deep web contains an order of magnitude more information than the surface web, but that information is hidden behind the web forms of a large number of web sites. metasearch engines can help users explore this information by aggregating results from multiple resources, but previously these could only be created and maintained by programmers. in this paper, we explore the automatic creation of metasearch mash-ups by mining the web interactions of multiple web users to find relations between query forms on different web sites. we also present an implemented system called tx2 that uses those connections to search multiple deep web resources simultaneously and integrate the results in context in a single results page. tx2 illustrates the promise of constructing mash-ups automatically and the potential of mining web interactions to explore deep web resources.
overview based example selection in end user interactive concept learning. interaction with large unstructured datasets is difficult because existing approaches, such as keyword search, are not always suited to describing concepts corresponding to the distinctions people want to make within datasets. one possible solution is to allow end users to train machine learning systems to identify desired concepts, a strategy known as interactive concept learning. a fundamental challenge is to design systems that preserve end user flexibility and control while also guiding them to provide examples that allow the machine learning system to effectively learn the desired concept. this paper presents our design and evaluation of four new overview based approaches to guiding example selection. we situate our explorations within cueflik, a system examining end user interactive concept learning in web image search. our evaluation shows our approaches not only guide end users to select better training examples than the best performing previous design for this application, but also reduce the impact of not knowing when to stop training the system. we discuss challenges for end user interactive concept learning systems and identify opportunities for future research on the effective design of such systems.
advanced narrow speech channeling algorithm for robot speech recognition. we propose a source extraction algorithm that provides robust speech recognition of intelligent service robots. this system consists of two stages. first, the target speech from a target direction is extracted from a mixture inputs using a binary time-frequency masking method. this stage can work alone. the next stage re-estimates the range of the target direction calculating the energy of the extracted speech by &delta; histogram. this algorithm was mounted on the speech recognition system of a service robot as a preprocessing step. in section 6, we show that our algorithm has excellent performances.
a study on enhanced algorithms for detecting defects of glasses. in this paper, we proposed image processing algorithms and developed the vision system for measuring blisters of flat glasses. the images captured by changing focus of camera because the depth of field of ccd camera is smaller than the depth of glasses and classified two types in blister as circle and ellipse types by the proposed criteria of measurement. we applied different methods to each type to improve the accuracy. in the pre-processing, it obtained binarized images to find blister. the information such as area, boundary, length, and position of blister has extracted from the binarized images by using chain code algorithm. for an illumination, the bright field illumination as back-light was applied. we tested the automatic measurement system, which we developed by using vision system, it successes 100% for detecting the blister at all glasses, and the error accuracy of information is about +/-10%.
context awareness inference engine for location based applications. in ubiquitous environments, location-based context awareness service provides additional services based on a user's location. in this paper, we design a context awareness inference engine model for working environment monitoring system of mobile object which is an issue in location-based application. we in the proposed a context awareness inference engine can use sensors, mobile communication network in order to achieve working environment information of mobile object. the proposed framework is consisted of data collector, context manager, knowledge base, inference engine, and context database. and it also has a structure that enables to serve users by embodying context awareness application interface for particular application.
fmm: fusion media middleware for actual feeling service. recently for media content from internet users, the increased interest in the web is huge and rich. between media content, especially in the eyes and ears of internet users attracted to the limelight of the media content is video content. additionally, in conjunction with web 2.0 internet users by their openness to each other and share content to create new forms of distribution of the flow. video media content for distribution on the web was created by a professional content to experts, but web 2.0 era, the ugc (user generated content) in the form of self-produced content is the most. made by the general internet users, but self-produced content to provide video information only and has limitations. to satisfy internet users as consumers, not just the images you add various effects are realized the need to provide the video. therefore, this paper used ontology concept for providing media that has actual feeling instead of simple information media. obtained knowledge of input media by using ontology concept stand in the basis of extracting actual feeling effects. on the basis of this methodology, this paper proposes fusion media middleware (fmm) that has function of offering fused media (music, sounds, images etc.). we describe the formatting guidelines for acm sig proceedings.
architecture of electronic surveillance of p2p based voip service. architectures of electronic surveillance of various types of p2p-based voip services are described in this paper. there are kinds of architectures of p2p based voip service according to the telecommunication networks used including pstn, mobile network, and voip network. in other words, appropriate architecture and points of electronic surveillance of p2p based voip services depend on the voip service architecture. hereupon, electronic surveillance architectures of p2p based voip service users whose counterpart uses pstn or voip service, and characteristics of each are described.
an application of host identity tags to dkim for identifying signers. the domainkeys identified mail (dkim) protocol gives a solution to guarantee the authentication and the integrity of e-mail messages. and in practice, to make dkim come from theory to engineering, a concept of adsp (author domain signing practice) has been put forth in an ietf draft. however, on the aspects of identifying a signer and delegating the signing ability, adsp fails to give a specification. yet the hits (host identity tags), put forth in rfc 5201, are born to identify signers featuring asymmetric key pairs and hits will offer extra functions for security of the keys involved and management of the identifiers. this paper proposes to apply hits to dkim for identifying signers.
design for supporting the multimedia emergency voip using pstn and ip network. internet is rapidly increased, and various services are deployed over internet. it is an important issue to support emergency service in voip, because many users want to use the emergency service similar to the service in pstn network. voip terminals which can create audio, video, and image data are able to send multimedia data to emergency agent. but the current voip service cannot provide multimedia data to emergency agent, because emergency calls have to flow through pstn network. if emergency agent has got some video as well as audio data for emergency call, it will be very helpful to rescue somebody in danger. in this paper, we will consider new network model to provide multimedia data to psap in emergency call.
huffman coding algorithm for compression of sensor data in wireless sensor networks. sensor data exhibit strong correlation in both space and time. many algorithms have been proposed to utilize these characteristics. however, each sensor just utilizes neighboring information, because its communication range is restrained. information that includes the distribution and characteristics of whole sensor data provides other opportunities to enhance the compression technique. in this paper, we propose an orthogonal approach for compressing sensor readings based on a novel feedback technique. that is, the base station or a super node generates huffman code for the compression of sensor data and broadcasts it into sensor networks as feedback information. all sensor nodes that have received the information compress their sensor data and transmit them to the base station. we call this approach as feedback-diffusion and this modified huffman coding as shuffman coding. in order to show the superiority of our approach, we compare it with the existing data compression algorithms in terms of the lifetime of the sensor network. as a result, our experimental results show that the whole network lifetime was prolonged by about 30%.
a novel genetic variable representation for dynamic optimization problems in evolutionary computation. this paper introduces a novel genetic variable representation for dynamic optimization problems in evolutionary computation. this variable representation allows static evolutionary optimization approaches to be extended to efficiently explore global and better local optimal areas in dynamic fitness landscapes. it represents a single individual as a pair of real-valued vector (x, r) &isin; rn x r2 in the evolutionary search population. the first vector x corresponds to a point in the n-dimensional search space (an object variable vector), while the second vector r represents the dynamic fitness value and the dynamic tendency of the individual x in the dynamic environment. r is the control variable (also called strategy variable), which allow self-adaptation. the object variable vector x is operated by different genetic strategies according to its corresponding r. as a case study, we have integrated the new variable representation into genetic algorithms (gas), yielding an dynamic optimization genetic algorithm (doga). doga is experimentally tested with 5 benchmark dynamic problems. the results all demonstrate that doga consistently outperforms other gas on dynamic optimization problems.
an efficient algorithm for as path inferring. discovering the as paths between two ases is invaluable for a wide area of network research and application activities. the traditional techniques for path discovery require direct access to the source node. recently, with more accurate as relationship inferring algorithm and publicly available as topology data, it is possible to infer as paths without accessing the source. this paper proposes an efficient algorithm for inferring all pair shortest as paths in a relationship annotated as graph. the running time of the algorithm is o(nm), where n is the number of nodes and m is the number of edges in as graph. the algorithm bases on the bread-first-search (bfs) algorithm, and experimental results show that it reduces running time dramatically compared with the existing algorithm whose running time is o(n3).
service discovery mechanism based on trustable dht in manet. service discovery mechanism is a core technique for getting a desired service in manet (mobile ad-hoc network) environment. however, as feature of manet, existing mechanisms have some problem that service requester search for trustable service. also it can not support scalability, in this paper, how to reliably support applications such as service discovery on top of manet. we are firstly finding a trustable service provider and configure dht (distributed hash table). p2p (peer-to-peer)'s dht can be adopted to service discovery mechanism because p2p and manet share certain similarities, primarily the fact that both are instances of self-organizing decentralized systems. especially, proposed dht systems used for p2p overlay network can be effective in reducing the communication overhead in service discovery. so proposed mechanism can support for reliably searching required service and scalability. simulation results show that our mechanism is scalable and outperforms existing service discovery mechanism.
efficient execution of application applets based on persistent object caching in java card system. atomic transactions involving persistent objects in java card system environment often creates performance bottleneck due to access speed gap between ram and flash memory. this paper proposes simple yet efficient way of handling persistent objects for atomic transactions by utilizing object caching and buffering. the proposed scheme significantly improves application execution performance.
middleware-based distributed systems software process. middleware facilitates the development of distributed systems by accommodating heterogeneity, hiding distribution details and providing a set of common and domain specific services. it plays a central and essential role for developing distributed systems. however, middleware is considered a mean rather than core elements of development process in the existing distributed systems software process. this paper explains the concept of middleware by categorizes middleware and analysis the problems of current middleware architectures. it also extracts three essential non-functional requirements of middleware and proposes a middleware-based distributed systems software process. the proposed software process consists in five phases: requirements analysis, design, validation, development and testing. the characteristics of middleware are considered in the entire software process.
application services based on location information in the sip phone. application service based on location information, 1588 representative number service such as flower delivery service, pizza delivery service and emergency call service such as 112, 113, 119, is a nationwide one. if internet phone subscriber calls to representative number, that call is transferred to the shortest service center based on the present location information of subscriber and service is supported to the caller. we describe the mechanism that sip phone, mounted basic sip protocol and presence protocol, can provide various application services based on location information. in order to support application service based on location information, we describe the system components of voip service provider and message flows among system components.
bridge transmission method of medical sensor node in u-healthcare services. when monitoring vital sign, cables between medical sensors and monitoring system make a patient uncomfortable. furthermore, it gets worse in case of a steady monitoring is needed. recently researches, therefore, are actively underway to integrate a wireless sensor network into vital sign monitoring devices. however, the measured data from the sensor can't be transmitted if a patient moves out of the transmission range since the receiving and transmitting range of the measured date is limited within a specific range. in order to clear out this sort of problem, this research suggests the bridge transmission method that can deliver data between nodes via other devices even if the medical sensor device went out of transmission range for a gateway. experiments have been carried out by materializing a bridge transmission module on sensor nodes to verify effectiveness of our suggesting transmission method, and ten experiments having transmitted 1,000 packets by case showed 98.4% of success in receiving
sampling scheme for better rbf network. neural networks have been developed for machine learning and data mining tasks, and because data mining problems contain a large amount of data, sampling is a necessity for the success of the task. for this reason, this paper suggests an effective sampling technique that is based on a generated decision tree, where the trees are generated based on a fast and dirty tree generation algorithm. experiments with several sample sizes and rbf network showed that the method is more effective with respect to accuracy than conventional random sampling method.
a detection model based on statistical against ddos attack. a development and research for distributed denial of service attack detection is underway. a statistical technique identified efficiently the normal packets and abnormal packets. in this paper several statistical techniques, using a mix of various offers a way to detect the attack. to verify the effectiveness of the proposed technique, it set packet filtering on router and the proposed ddos attacks detection method on a linux router. in result, the proposed technique detected various attacks, provided normal service mostly.
ecu configuration framework based on autosar ecu configuration metamodel. autosar (automotive open system architecture) is a partnership of automotive manufacturers and suppliers working together to develop and establish a de-facto open industry standard for automotive e/e architectures. autosar defines architecture, methodology, and application interfaces. the methodology describes ways to exchange formats or description templates to enable a seamless configuration process of the basic software stack and the integration of application software in ecus and it includes even the methodology how to use this framework. the configuration process is comprised of several steps such as system configurations and ecu configuration. in ecu configuration step, many ecu configuration parameters based on system configuration results are organized into xml files. this paper describes methodology how these ecu configuration parameters are described, classified, and stored in xml files.
vehicular client roaming and location-based handoff through multiple wlan aps in a container terminal. this paper reports on measurement results for the simultaneous use of multiple wlan aps in a large area. we describe some problems of applying legacy ieee 802.11 wlan technologies to a freight container terminal as a special application example. we begin by describing the characteristics of it infrastructures in a container terminal environment, and examine s/w application requirements and work processes in a container terminal. one of the key problems based on clients' complaints is frequent network disconnections. to find the cause of this problem, we observe the characteristics of service clients and collect the raw network data from actual measurements in a container terminal. we transform the collected raw data into meaningful secondary data and analyze the results. based on our analyses, we suggest several candidate solutions to mitigate the frequent network disconnections and enhance the network performance. we perform one of the suggestions location-based handoff, for evaluation.
apjava: an aspect-oriented parallel programming model in java. the paper introduces the apjava programming environment, called apjava. apjava is an aspect-oriented parallel dialect of java that imports hpjava-like arrays -- in particular the distributed arrays -- as new data structures. the main purpose of apjava is to provide an easy-to-use aspect-oriented parallel programming environment to engineers and scientists unfamiliar with parallel programming. the paper discusses an overview of apjava and pre-translation scheme and basic translation scheme adopted in a translator for the apjava language.
an improved camera identification method based on the texture complexity and the image restoration. the identification of source camera is useful to improve the capability of evidence in the digital image such as distinguish the photographer taking illegal images and adopting digital images as evidence of crime. luk&aacute;&scaron;, et al. showed the method for source camera identification based on the correlation of pnu (pixel nonuniformity) noise. however, the wavelet-based denoising filter for suppressing the random noise reduces the accuracy of camera identification. it is caused by the fact that the denoising filter diffuses the edge and makes the pnu noise less pronounced. moreover, it is difficult to extract pnu noise from the images taken by cameras which are equipped with the image improvement functions such as motion blur correction, contrast enhancement, and noise reduction. in this paper, we propose a method for improving the camera identification accuracy by selecting pixels based on the texture complexity. we also propose a-method for improving the identification accuracy by applying the image restoration method.
a study on intrusion protection techniques against linux kernel backdoor. as the existing backdoor worked at user mode, which is application mode, it was possible to check the existence of backdoor by the integrity check of system file. however, for the backdoor using kernel module, it is impossible to check its existence by the integrity check of system file. even various programs were presented to protect this lkm kernel backdoor, there is limitation in protection as they examine the changes on the system call table. this study, recognizing the danger of invasion through such lkm kernel backdoor, will provide alternative for the limitation which the existing integrity check couldn't prevent intrusion through kernel backdoor.
bio-inspired simulation tool for pert. this genetic programming based tool simulates activities and resource allocations in the program (project) evaluation and review technique method of project control. users constrain the optimization problem by means of a visual interface and genetic programming discovers a umber of acceptable solutions that satisfy the user constraints. it evolves computer programs that, when executed, produce a variable length vector of real numbers. this vector is then interpreted according to the grammar that abides by the user constraints. the tool has a wide application in the management of large and complex projects as it handles the a priori simulation of events that may delay or compromise the project, and enables the project owners and project managers to come up with robust and innovative contingency measures to decrease the likelihood of project failure before project start-up.
novel ofdm frame synchronization in multi-user environments. in this paper, we propose a novel frame synchronization algorithm for an orthogonal frequency division multiplexing (ofdm) system in multi-user environments. in order to enhance the synchronization performance, we add a repeated orthgonal gold sequence (rogs) directly to ofdm signals in the time domain. the power level of a rogs needs to be low engough in order not to affect a normal operation of the ofdm systems. frame synchronization can be achieved successfully over rayleigh fading channel interfereed by impulsive noise owing to good auto and cross-correlation properties of the rogs.
a study on the ber performance of turbo coded t-dmb system. the t-dmb system being able to transmit video service needs additional fec blocks which consist of rs code and convolutional interleaver along with the existing rcpc code. in this paper we propose a new turbo coded t-dmb system that replaces the existing rs code, convolutional interleaver and rcpc code by a turbo code without altering the puncturing procedure and puncturing vectors defined in the standard t-dmb system for compatibility. simulation results show that the new turbo coded system yields considerable performance gain after just 2 iterations.
a study of intelligent earth work using the process simulation. because it is a very repetitive and monotonous work and needs lots of construction equipment, the earth work operation for site development is a good field to apply automation technology. this study has analyzed input condition which has carried out in actual earth work. it has deduced simulation which would help to decide ideal combination of earthwork equipment through reflecting capacity of equipment and processing simulation according to input. in kind of construction which characterized specific process has repeated, simulation will have used to effectively as a reasonable decision to plan process of site planning process of u-construction.
design and implementation of a live-analysis digital forensic system. as the popularity of the internet continues growing, not only change our life, but also change the way of crime. number of crime by computer as tools, place or target, cases of such offenders increases these days, fact to the crime of computer case traditional investigators have been unable to complete the admissibility of evidence. to solve this problem, we must collect the evidence by digital forensics tools and analysis the digital data, or recover the damaged data. in this research, we use the open source digital forensics tools base on linux and want to make sure the stability of software then prove the evidence what we have. to avoid the data loss due to the shutdown of machines, we use the live-analysis to collect data and design the live dvd/usb to make image file and analysis the image. we use the md5 and sha-1 code to identity the file before the final report and ensure the reliability of forensic evidence on court.
a new stereo matching algorithm for binocular vision. the stereo matching algorithms for binocular vision are very popular and widely applied. however, the algorithms may have lower matching quality or higher time complexity. to improve that, a new stereo matching algorithm based on square and gradient for binocular vision is proposed in the paper. it divides an image line into a serious of ranges with comparing the gradients of the points in left and right image lines. the best matching in each range is found based on the summery of squared differences. the algorithm inherits the high quality of gradient algorithm and high performance of ssd algorithm and meanwhile avoids the additive noise.
combined ranking for multi-media web search engine. in this paper and we propose a new system structure for multi-media data search engine where the ranking for non-text data can be vastly improved. we first discuss why current search engines are not enough to search for multi-media data, and then introduce the new form of a database, called mixed database. then we explain how our ranking system will work and how it works on our search engine.
biomedical signal compression based on basis pursuit. this paper presents a discussion concerning eeg signals compression using the basis pursuit (bp) approach applied for several overcomplete wavelet dictionaries. the compression is based on an "optimal" superposition of dictionary elements, by minimizing the 11 norm of the error. the best results have been obtained with the daubechies10 dictionary.
a context-aware service model using a multi-level prediction algorithm in smart home environments. smart home is emerging as the future digital home environments that provide various ubiquitous home services like u-life, u-health, etc. it is composed of some home appliances and sensors which are connected through wired/wireless network. ubiquitous home services become aware of user's context with the information gathered from sensors and make home appliances adapt to the current home situation for maximizing user convenience. in these context-aware home environments, it is the one of significant research topics to predict user behaviors in order to proactively control the home environment. in this paper, we propose multi-level prediction algorithm for context-aware services in ubiquitous home environment. the algorithm has two phases, prediction and execution. in the first prediction phase, the next location of user is predicted using tree algorithm with information on users, time, location, devices. in the second execution phase, our table matching method decides home appliances to run according to the prediction, device's location, and user requirement. since usually home appliances operate together rather than separately, our approach introduces the concept of mode service, so that it is possible to control multiple devices as well as a single one. we also devised some scenarios for the conceptual verification and validated our algorithm through simulations.
implementation of ieee802.11a software defined receiver on chip multi-processor architecture using openmp. software radio (sr) is a promising technology for the next generation communication since it enables to implement various communication protocols in one platform. in general, software radio systems implemented in dsps or fpgas deliver satisfactory performance, but they do not provide enough flexibility which is a key merit of using soft radios. in this paper we implement a software radio system on a general purpose multiprocessor. running communication applications on an os-based general purpose processor has several merits. however, there are two big shortcomings. first, the system may not satisfy the required performance. second, it may be hard to meet the real time constraints. to achieve the required performance of signal processing, a chip multiprocessor is employed. typically, ample potential for parallelization is found in communication software. therefore by effectively utilizing task-level parallelism, chip multiprocessors can achieve the required performance. in this paper, we implement an ieee 802.11a baseband receiver in software, and parallelize the software by openmp. we also propose a new synchronization technique among threads. we evaluate the performance after running the software on an intel quad core workstation with the centos.
movement-aware alternative path routing protocol for vehicular multi-hop communications. vehicular ad-hoc networks (vanets) are now considered to be suitable for enhancing road safety and efficiency in vehicular environment. especially, due to the affluent spectrum resource, supports for non-safety relevant services, like inter-vehicle entertainments, are also under investigation. however, in the vehicular environments, the nodes can experience frequent link breakages due to the vehicle mobility characteristic. thus, a reliable multi-hop routing protocols is definitely needed to overcome the performance degradation caused by it. in this paper, we propose a novel scheme for non-safety applications, which is also referred as movement-aware alternative path routing protocol (marp), a reactive unicast routing protocol that considers two factors such as vehicle movement and multi-path to determine the optimum reliable routing paths. in addition, we devote special attention to the random characteristic of the radio propagation model to provide a simulation with the desired level of realism. after realistic simulation studies, the performance of proposed marp routing protocol outperforms the traditional vanets routing by reducing the routing overhead and enhancing the stability of routing path.
a study on intelligent cyber university. it is accepted that virtual university can easily study the lecture only press the mouse click or keyboard button anywhere and anytime, if you have a computer. in addition, many people believe that virtual university can save time and improve learning. in order to provide good lecture for them, it is needed that instructor should know how to understand their students related various course as well as find out their difficult problems. in this paper, we will propose new scheme to overcome the problem, which was originated from the cyber lecture. it is a studying method of full duplex direction. the method of traditional studying is one direction method. the computer simulation results confirms that full duplex virtual learning system has been proven to be much more efficient than one way direction which unfortunately does not consider to understanding problems.
capability and limitation of financial time-series data prediction using symbol string quantization. there are many methods for analyzing patterns in time-series data. although stock data represents a time series, there are few studies on pattern analysis and prediction stock price dynamics in the field of computer science. since people believe that stock price changes randomly we cannot predict stock prices using a scientific method. in this paper, we calculate randomness of stock price changes using kolmogorov complexity. it is related to the accuracy of stock prediction using semi-global alignments. we use stock price data of 690 firms listed on the korea stock exchange (krx) during 28 years for our experiments and to evaluate our methodology. when kolomogorov complexity is high we cannot predict accurately stock prices; while kolomogorov complexity is low, we can predict stock prices accurately. however, the prediction ratio of stock price changes of interest to investors, is 12% for short-term predictions and 54% for long-term predictions.
effective spelling correction in web queries and run-time db construction. studies on correcting errors in web search queries has some history over the past few years. there were novel ways in solving issues that occur when applying spelling correction techniques to query logs. this paper takes one more step forwards creating an effective and practical system out of what was learned so far, while also taking an intuitive approach to calculate a query's validity with the help of additional query information. this system consists of three phases that separates calculation from run-time database structure, which results in a faster program that can be used in real-time.
a threat-based privacy preservation system in untrusted environment. in an untrusted environment, it is hard to ensure that all the available technologies are being used to protect data privacy. once user's data is hosted outside of his/her local computer, a degree of control over his/her privacy information may be lost. consequently, a variety of threats may arise and result in hazards to the user. for that reason, users want to disclose privacy data in a minimum way so that the potential threats to their data can be also minimized. thus, the importance of privacy data elements must be verified by individual user. however, user may not be able to achieve this task if the threats are not obvious to the user. to address this problem, in this paper, we present a threat-based privacy preservation system that helps a user to evaluate the importance of privacy data and the risk of disclosing it. in our system, users can specify their privacy preferences by setting penalty values on potential threats. through a goal-oriented approach, our system can select proper services for users to restrict data disclosure by which the potential threats to users can be minimized.
privacy information protection in portable device. with the development of the information technology are increasing ever before, and the damage of it re-engineering is also rapidly increasing. particularly, overflow of critical information through the portable storage device is getting more important problems in these days. in this paper, we are making a suggestion of the pdsm (portable device security management) in order to solve these problems. the pdsm system is composed of 5 functions: 1) user identification/authentication, 2) specified data encryption and decryption, 3) copy prevention of stored data 4) deletion for data protection, 5) control management for major information. we also prototyped the pdsm which provides the privacy information protection for feasible approach in real system environments.
effective defect classification for flat display panel film images. in this paper, we propose an effective defect classification system for fdp (flat display panel) film images which are acquired in real production lines. a film image is segmented into a binary image with two non-overlapping regions: defect and non-defect regions. from the defect regions, various features are extracted such as brightness distribution, linearity, and morphologic characteristics. the film defects are classified through the analysis of those features extracted. empirical study shows our system classifies five types of film defects effectively.
optical wireless recharging model for wireless sensor nodes by using corner cube retroreflectors (ccrs). wireless sensor networks are included in today's important and evolving communication technologies. the size of sensors operating wirelessly decreases with the advent of advancement in device processing technologies like micro- and nano-electromechanical systems. this decrease in dimensions of sensors causes serious problem for battery storage capacity. we address this issue and propose a model of communication and recharging of wireless sensor network (wsn) nodes simultaneously using passive optical communication. we propose both line-of-sight and quasi-diffuse communication for this purpose. there are some situations where direct los is better option while at non-line-of-sight, the energy of a multi-spot quasi-diffuse beam can be utilized. in our model we have used modified corner cube retroreflector (ccr) and a newly proposed device thinfilm corner cube retroreflector (tccr) for passive communication and recharging sensor nodes. these devices have large angle of diversity due to which they can provide communication facility to large areas. our analysis shows that the proposed model could show better performance and significant increase in network life time.
research on load balancing mechanism based on handoff in heterogeneous network platform. modern service industry is a new kind of service industry based on information & communication technologies and modern management thinking, which is in accord with the concept "service science" by ibm. a heterogeneous network platform is founded to implement the applications of modern service industry. in this paper, an intelligent handoff algorithm is proposed to keep the service continuity in the heterogeneous network platform. and service class differentiation is considered to define the service priority according to service characters of real-time traffics and non-real-time traffics. a load balancing mechanism based handoff is proposed to balance the load of a network or cell by comparing the current load value with corresponding throughput thresholds. simulations illustrate that the load balancing algorithm can improve the blocking probability, call dropping probability and resource utilization to an extent.
a framework to support real-time features of intelligent service robots. in the ubiquitous environment, the real-time features for intelligent service robots are necessary to insure statistical and deterministic quality of service (qos) guarantees for latency. in this paper, we design and implement the real-time framework for intelligent service robots to support real-time features. the real-time framework with the priority-based real-time scheduling service will be operated on the general operating systems. it resolves a problem that the scheduler of general operating system can't support real-time features. it has been implemented on windows operating system for providing the qos guarantees for deterministic real-time robot applications. the performance measurements include both thread's response time and overhead to execute internal function of the real-time framework.
a statistical method for structure learning of bayesian networks from data. the bayesian network, a powerful tool for predicting and diagnosing uncertain phenomena, is used in various fields including artificial intelligence, business administration, and medical science. we use a statistical approach, and present a simple algorithm for learning bayesian network structure from data. first we obtain from data the original correlation graph and the correlation graphs when one or two variables are fixed. then we construct a bayesian network that would produce the most similar correlation graphs. simulation results are given to demonstrate that the algorithm determines the network structure with a high accuracy.
intelligent service reasoning model using data mining. this paper proposes an intelligent service reasoning (isr) model using data mining in smart home environments. this model creates a service tree used for service reasoning on the basis of the c4.5 algorithm, one of decision tree algorithms, and determines the services that will be provided to users through a quantitative weight estimation algorithm that uses a quantitative characteristic rule and a quantitative discrimination rule. the effectiveness in the performance of the developed model is validated through a smart home-network simulation.
a partition-based centralized leach algorithm for wireless sensor networks using solar energy. wireless sensor network (wsn) has been considered as a promising method for reliably monitoring both civil and military environments under hazardous conditions. due to such condition, the power supply for sensor in the network cannot be usually rechargeable or replaceable. thus, instead of battery replacement, we develop a solar energy recharging hardware to charge the battery of sensors to prolong the lifetime of each sensor recharging in the network. the proposed method, however, has a problem. each node cannot be charged with the same amount of power depending on its physical location. the classic leach protocol deploys the randomize rotation of cluster-heads to evenly distribute the energy load among sensors without considering the unbalanced residual energy of each node. so some enhanced solar aware leach protocols have been proposed, but it is not much efficient for prolonging the lifetime of network. this paper proposes an advanced leach algorithm which prioritizes each sensor for the cluster--head election according to its current energy and rate of energy harvesting. the simulation results and analysis show that our proposed algorithm could outperform existing methods in terms of the number of alive nodes.
analysis of rhythms of eeg signals using orthogonal polynomial approximation. we present a new method for analysis of the rhythms of the electroencephalogram (eeg) signal. the method is based on the multi-resolution analysis using the orthogonal polynomial approximation (opa). it is demonstrated that the proposed analysis technique employing the opa gives similar performance as the popular method based on the wavelet packet decomposition. however, the proposed technique is simpler in principle and can be implemented as a one-step process. some advantages of the proposed technique manifest in reduced computational complexity and feasibility of real-time implementation.
minimize the delay of parasitic capacitance and modeling in rlc circuit. this paper shows that how to minimize the delay. we changed several elements to minimize the delay in the circuit. simulation results show the best effect when the value of parasitic capacitance is changed. we found eligible point by simulating parasitic capacitance case by case based and proved it. types of case are elmore delay, interconnection delay, lowering parasitic capacitance's parameter entirely, raising parasitic capacitance's parameter in order of precedence, lowering parasitic capacitance's parameter in order of precedence, and changing inverter's w parameter. and it has been apparently proven that case of using parasitic capacitance is better than other methods.
a secure ubiquitous sensor network with dragon. the creation of wireless sensor networks provides a capable solution for a range of ubiquitous information services. its challenges like, data security and secrecy due to its hostile deployment nature of being flat to physical attacks with restricted source available. in order to competition the security pressure that sensor networks are exposed to, a cryptography algorithm is implemented at sensor nodes for node-to-node encryption, between nodes considering the data redundancy, energy constraint, and security requirement. in this paper, we analyze dragon stream cipher and propose a new d-mac secure data scheme which supports node-to-node encryption using dragon based-privacy [3] for sensor networks. our procedure regarded the entity verification and message authentication through the performance of authenticated encryption scheme in wireless sensor nodes.
optimal green time calculation using artificial intelligence. in order to reduce traffic accidents, many researchers studied a traffic accident model. the cause of traffic accidents is usually the miscalculation of traffic signals or bad traffic intersection design. therefore, it is necessary that calculating the optimal safe car speed based intersection conditions and weather. the conventional traffic light did not have the function of optimal cycle. thus, a conventional traffic cycle is not commensurate with the present traffic environment. in this paper, we proposed electro sensitive traffic light using fuzzy look up table method, which will reduce the average vehicle waiting time and improve average vehicle speed. in order to prove our propose scheme, computer simulation was used. as a result, our scheme is shown good result.
ubiquitous environmental infra systems for the green city. it is our objective to introduce a concept for the ubiquitous environmental infra system for controlling green house gas (ghg) emissions. the system suggested here was designed to collect data for ghgs generated from various point and non-point sources using various environmental, visible, and satellite sensors based upon graphic user interface and user-friendly controlling strategy for establishing an eco-friendly and low-carbon generating green city. given that major production of ghgs takes place in the cities, our system made up through technology fusion merging conventional and innovative environmental, nano, and information technologies is expected to allow the essential management of sources, generation, transport, and eventual removal of ghgs, and therefore, to contribute the mitigation of global warming problems. to this end, the new system introduced in this paper can be employed as a standardized concept for the green city in the future.
successive interference cancellation for cooperative communication systems. in this paper, we analyze and simulate a successive interference cancellation (sic) scheme for cooperative communication systems in wireless communication network. in the interference cancellation strategy, co-channel interference (cci) is mitigated by zero forcing (zf) or minimum mean square error (mmse) receivers. moreover, successive interference cancellation (sic) with optimal ordering algorithm is applied for rejecting cci efficiently. and we analyzed and simulated the proposed system performance in rayleigh fading channel. in order to justify the benefit of the proposed strategy, the overall system performance is illustrated in terms of bit error rate and compared with that of conventional interference cancellation receiver.
a 60hz interference reduction using slope trace waves. in this paper, a new method to remove 60hz power line interference from ecg (electrocardiogram) in time domain is introduced. the method uses two slope trace waves that are kind of delayed version of original signal with averaged slopes within a certain time interval. after the determination of the two slope trace waves, their arithmetic average is calculated. the result shows filtering effect removing the 60hz interference. in order to evaluate the effectiveness of the method, several ecgs from mit-bih arrhythmia database were chosen and 60hz sinusoidal waves with different amplitudes were added to them. the simulated ecg was then applied to the algorithm and the result showed its potential applicability to practical signal processing situation requiring effective 60hz interference removals with minimal waveform distortion.
an efficient design pattern algorithm for the environmental and hydrologic/hydraulic ubiquitous model developments. in this paper, we propose an efficient design pattern algorithm for the environmental and hydrologic/hydraulic ubiquitous model developments which specifies pattern names for retrieving, exploring the adapted patterns on the stage of design without pattern language that is redundant abstraction. by applying composite design pattern to the design of the recursive river and basin interface for total maximum daily load, we significantly improve the performance of polymorphism and especially of reusability than conventional basin models. thus, this study can contribute on the reducing iterations and repetitions of up-dating and committing after the spatial data changes that are frequently occurred in the process of the environmental gis model developments.
hybrid word sense disambiguation using language resources for transliteration of arabic numerals in korean. the high frequency of the use of arabic numerals in informative texts and their multiple senses and readings deteriorate the accuracy of tts systems. this paper presents a hybrid word sense disambiguation method exploiting a tagged corpus and a korean wordnet, korlex 1.0, for the correct and efficient conversion of arabic numerals into korean phonemes according to their senses. individual contextual features are extracted from the tagged corpus and are grouped in order to determine the sense of arabic numerals. least upper bound synsets among common hypernyms of contextual features were obtained from the korlex hierarchy, and they were used as semantic categories of the contextual features of arabic numerals. the semantic classes were trained to classify the meaning and the reading of arabic numerals using decision tree and to compose grapheme-to-phoneme rules for an automatic transliteration system for arabic numerals. the proposed system outperforms the customized tts systems by 3.9%--20.3%.
optimal rm scheduling for simply periodic tasks on uniform multiprocessors. the problem of scheduling simply periodic task systems upon a uniform multiprocessor is considered. each processor in a uniform multiprocessor is characterized by the speed or computing capacity, with the interpretation that a job executing on a processor with speed s for t time units completes (s x t) units of execution. in the partitioned approach to scheduling periodic tasks upon multiprocessors, each task is assigned to a specific processor and all jobs generated by a task are required to execute upon the same processor to which the task is assigned. however, the partitioning of periodic task systems requires solving the bin-packing problem, which is known to be intractable (np-hard in the strong sense). this paper presents a global scheduling algorithm which transforms a given simply periodic task system into another using a "task-splitting" technique. each transformed simply periodic task system is guaranteed to be successfully scheduled upon any uniform multiprocessor using a partitioned scheduling algorithm. the rate-monotonic (rm) algorithm is chosen for scheduling tasks on each processor. it is proven that the proposed algorithm achieves the theoretical maximum utilization bound upon any uniform multiprocessor platform. therefore, the proposed algorithm is optimal in the sense of maximizing achievable utilization for simply periodic task system on uniform multiprocessors.
session management of relay-based overlay multicast for managed group applications. in spite of the capability to provide efficient delivery of service, ip multicast has not been used widely because of technical limitations as well as management-related issues [1]. overlay multicast is introduced to overcome these problems which make it difficult to deploy various services requiring group communications. the multiple end-user hosts organize multicast delivery path forming a group. therefore, overlay multicast needs group management, a.k.a., session and membership management to provide robust and resilient group services. this paper proposes session and membership management method for overlay multicast. this paper describes the required session and membership management functions, and presents how those functions are processed. this paper will be helpful to service provider who needs to provide overlay multicast based service or for those who needs to enhance multicast-based service management.
creating an autonomous dancing robot. a robot with the ability to dance autonomously has many potential applications, such as serving as a prototype dancer for choreographers or as a participant in stage performances with human dancers. a robot that dances autonomously must be able to extract several features from audio in real time, including tempo, beat, and style. it must also be able to produce a continuous sequence of humanlike gestures. we chose the hitec robonova to use as a robot platform in our work on these problems. we have developed a beat identification algorithm that can extract the beat positions from audio in real time for multiple consecutive songs. our robonova can now produce sequences of smooth gestures that are synchronized with the predicted beats and match the tempo of the audio. our algorithm can also be easily moved to the hubo, a large humanoid robot that can move in a very humanlike manner.
a collective transaction processing scheme for mobile environment. technical advances in development of portable computers and wireless technology permit users to actively get advantage of mobile computing environment. better and faster communication mechanisms provided the needed flexibility which is demanded by variety of applications with stringent requirements. however, there are certain major issues that need to be taken seriously in this environment, such as reliability, concurrency control and data recovery, as there may exist more than one user in any one time to access or execute a transaction. a transaction is expressed in centralized or distributed environment as an atomic activity, while in a mobile environment a transaction is a long-lived process and this process may have to be split into sets of operations executed some on mobile host and others on stationary host. therefore, the task of ensuring consistency becomes more difficult in mobile environment. in this paper we study these issues and propose a reliable transaction model which combines the advantages of existing models to capture the data and mobility requirements in mobile environment.
hybrid analysis of advantage and efficiency of china agriculture. comparative advantage is the primary consideration during economy development. while to agriculture, this rule is often ignored and almost all countries or regions in one country support its development with finance, whether they have comparative advantage or not and no matter what the support efficiency is. this paper first gauges the efficiency value of agriculture fiscal support with the well-known panel-data model for the dataset of 25 provinces in china in recent 25 years. then we further analyze efficiency values combined with existed comparative advantage values by k-means clustering method, and 25 provinces are classified into 3 clusters. so according to hybrid information from the clustered results in consideration of both comparative advantage and comparative efficiency, the proposal for china agriculture development proposed by this paper will be more efficient and cost effective.
a study for semantics participation platform architecture using rdf/owl. in this paper, we describe platform to allow social participation. digital social is the technology for computer to estimate and reason the relation between human beings. with the relation being strengthened by digital social, you can encourage participation. especially emotion can change weak tie into strong tie by furthering participation. this study analyzes platform development to infer emotion and to anticipate various participation causes. therefore to express participation method and process, this paper described in rdf and owl, which are the essential languages for semantic web participation process, is realized in foal. this study can help develop participation platform architecture to be more relation-oriented.
study on service model for multimedia streaming and file hosting services using distributed overlay network. nowadays, since p2p technologies have been introduced, the amount of p2p traffic has been increased rapidly. the traffic is mainly composed of multimedia data such as video, music. as a matter of fact, much of such contents are illegal which violate copyrights. it should be also noted that legal video streaming or file distribution services are in rapid growth. such kind of services is legal but it does not use the p2p services that may contribute to the network performance. in this paper, we propose distributed services architecture for multimedia streaming and file sharing.
comparing two methods for acquiring 3d data of motion capture system by using psd camera and ccd camera. this paper presents a monocular psd-based motion capture system and ccd camera based system. the first system includes a psd (position sensitive detector) and active infrared (ir) led markers that are placed on the object to be tracked. the psd sensor is placed in the focal plane of a wide-angle lens. the microcontroller calculates the 3d position of the markers using only the measured intensity and the 2d position on the psd. the second system includes two ccd camera and led markers that are in hand and draw any motion trace. from the experimental results we see that the two kinds of methods for acquiring 3d data will be compare in accuracy, speed, process, methods, experimental circumstance.
automatic generation techniques of a resource monitor based on deployment diagram. the overall goal of this paper is to improve development environments of self-healing software to facilitate self-managing capabilities such as self-healing. this paper proposes using deployment diagram for self-healing approach to determine problems arising in external environments.
a parallel motion estimation engine for h.264 encoding using the umhexagons algorithm. we present a fast motion estimation engine for the unsymmetrical cross multi-hexagon-grid-search (umhexagons) algorithm used in h.264 video encoding. the architecture uses arrays of subtracting elements to maximize parallelism among search points on vertical or horizontal lines, and reduces sum of absolute differences (sad) calculations. performance is measured in terms of cycles required to encode common intermediate format (cif) video frames with 5 reference frames within a search range of 16. the number of cycles is reduced by around 99% compared with the jm 10.1 package running on a baseline pentium 4 processor. the architecture thus achieves real time motion estimation at a clock speed of only 200mhz.
a weighted-dissimilarity-based anomaly detection method for mobile networks. mobile wireless networks continue to be plagued by theft of identity and intrusion. both problems can be addressed in two different ways, either by misuse detection or anomaly-based detection. in this paper, we propose a weighted-dissimilarity-based anomaly detection method that can effectively identify abnormal behavior such as mobility patterns of mobile wireless networks. in the proposed algorithm, a normal profile is constructed from normal mobility patterns of mobile nodes in mobile wireless networks. from the constructed normal profile, the dissimilarity is computed by a weighted dissimilarity measure. if the computed dissimilarity value is greater than the dissimilarity threshold that is a system parameter, an alert message is occurred. the performance of the proposed method is evaluated through a simulation. from the result of the simulation, we know that the proposed method is superior to the performance of anomaly detection methods using other dissimilarity measures.
modeling rule for analysis and design of e-learning content. this paper classifies scorm model into individual modules and proposes the rule of object modeling to a uml class diagram. we verify the validity of the mapping technique proposed in this paper by analyzing and designing with reverse engineering after applying mapping technique to the contents developed with scorm-type e-learning writing tool. the proposed modeling technique can be applied to the analysis and design of standardized e-learning contents that can be developed in universities and corporations, and utilized as a communication means between developers and users.
a semantic drm contents in social-awareness using ontology. this paper proposes semantic drm (digital rights management) content to be developed by means of rdf (resource description framework) among ontology technology. the purpose of this paper is to implement drm utilizing semantic web technology for resolving the threat to copyright in ubiquitous network environment. this paper analyses research procedure and method to recognize environment and context socially through scenario. in other words, graph model and schema using rdf allows semantic features to conventional drm technology. proposed semantic drm can be applied to protect copyright of remix content with mash-up and syndication technology.
an energy-efficient skyline query processing method using priority-based bottom-up filtering. in sensor networks, many studies have been proposed to process in-network aggregation efficiently. unlike general aggregation queries, skyline query processing compares multi-dimensional data for the result. therefore, it is very difficult to process the skyline queries in sensor networks. it is important to filter unnecessary data for energy-efficient skyline query processing. existing approaches get rid of unnecessary data transmission by deploying filters to whole sensors. however, network lifetime is reduced due to energy consumption for transmitting filters. in this paper, we propose a lazy filtering-based in-network skyline query processing algorithm to reduce energy consumption by transmitting filters. our algorithm creates the skyline filter table (sft) in the data gathering process which sends data from sensor nodes to the base station and filters out unnecessary data transmissions using it. the experimental results show that our algorithm reduces false positive by 53% and improves network lifetime by 44% on average over the existing method.
hybrid file system. as density doubles with the rapidly dropping price each year for the past seven years (currently 32 gbits/chip), nand flash memory has virtually replaced hdds (hard disk drives) in battery-operated consumer devices such as cellular phones, pmps, and pdas. this trend has also enabled the introduction of so-called flash memory ssds (solid state disks) that has an interface identical to that of hdds but use nand flash memory inside as storage media. the ordinary filesystems designed for hdds are no longer suitable for ssds because ssds have many different features from hdds. we designed a hybrid filesystem, called hybridfs, that uses two kinds of storages - hdds and ssds. this is accomplished by distributing data into two partitions based on the data type. in hybridfs, data blocks of files are stored in a data partition in hdds, while metadata being stored in the metadata partition of ssds. separating data into the different storage type of disk partitions makes it possible to produce high i/o performance by taking appropriate i/o approach, according to the data characteristics.
an approach to enhancing reusabilities in service development. service-oriented computing is an emerging environment for business agility in the software industry. today, there is a focus on developing service-oriented software. in this environment, service is a key feature reflecting business concerns. however, there is still debate about how best to reflect business concerns in services and how to create more reusable services. therefore, in this paper, we propose an approach to enhancing the reusability of service development based on the concept of the product line.
development and verification of the drm standard protocol for media card. drm offers an efficient way to protect digital contents. however, existing general drm systems cannot be directly applied to low computation-power systems such as media cards. we propose an implementation of a drm system which is applicable to such limited environments by analyzing the main specifications and modifying key aspects of the cryptographic algorithms.
the study on the user authentication protocol in gsm. today's gsm platform is a successful wireless technology and an unprecedented story of global achievement. gsm platform evolved into 3rd generation mobile communication possibly not only voice call services but also the international roaming and a various kinds of the multimedia services. gsm requires an essential element techniques of a safe data transmission and a personal private protection. however, a crypto algorithm and a secure protocol for a safe data communication using gsm have various kind of problems.
on the design and implementation of a secure online password vault. many websites and web applications are secured using passwords. this requires internet users to keep track of many different strong passwords. since passwords are only used when users are online it appears that the most efficient and convenient way to store a users passwords would also be an online application. many users, however, are rightfully concerned about the security of such an approach. in particular they are worried that their online password account could be hacked or that password transmissions could be intercepted, potentially exposing all their accounts at the same time. in this paper we describe a new tool that we developed called "online safe vault" that allows users to securely store their passwords online. to secure the tool, passwords are always stored encrypted on our safe vault server and are also always transmitted over the network as encrypted passwords. en- and decryption is performed locally on the users machine. at the same time the passwords are never stored in plaintext on the users machine.
design and development of a distributed real-time tele-operation model: supporting u-gis integrated monitor system. in the real world it is very difficult to implement real-time models in uncontrolled distributed environments and to support well-defined interfaces from real-time systems to external systems. distributed real-time applications such as integrated monitor system to establish u-gis project environments require distributed real-time application integrated with tele-operation technology able to collect and process data (location information, image information and information about equipment in remote places) generated from remotely distributed construction sites in real time and operate equipment related to the sites from a long distance away. the main purpose of this paper is to study how to support real-time applications, to design tmo-based distributed real-time processing techniques for real industrial applications, to implement and develop a tmo-based drts model with less strict real-time constraints in ubiquitous environments.
terrain mapping and classification using neural networks. this paper describes a three-dimensional terrain mapping and classification technique to allow the operation of mobile robots in outdoor environments using laser range finders. we propose the use of a multi-layer perceptron neural network to classify the terrain into navigable, partially navigable, and non-navigable. the maps generated by our approach can be used for path planning, navigation, and local obstacle avoidance. experimental tests using an outdoor robot and a laser sensor demonstrate the accuracy of the presented methods.
smoke detection using boundary growing and moments. in this paper, we propose a smoke detection method using block based subtraction, boundary region growing and moments in outdoor video sequences. our proposed method is composed of three steps; the initial change area segmentation step, the boundary finding and expanding step, and the smoke classification step. in the first step, we use a background subtraction to detect changed areas in the current input frame against the background image. in the second step, we find boundaries of the changed areas using labeling algorithm and expand the boundaries to their neighbors using the boundary region growing algorithm. in the final step, ellipses of the boundaries are estimated using moments. we classify whether the boundary is smoke by using the temporal information.
inter-service revisit analysis of three user groups using intra-day behavior in the mobile clickstream. the mobile internet proliferates and penetrates all aspects of daily life. the 4 billion mobile users will increase their impacts on data services. the author came to a sense that the intra-day mobile behaviors are classified into three user groups: always-on, night, and infrequent users. the author proposes a two-phase method to identify these three user groups. the author shows the case study result from 2001 commercial service logs with two different mobile services. the derived user groups are evaluated by the revisit ratio in the following month. the results are discussed to highlight the three-segment model in intra-day mobile user behaviors. they show the clear revisit ratio difference among the three user groups in the four services in observation. the two services in the two case studies are significantly different, however, they still exhibit consistent patterns in the three group classification.
a molecular docking system using cuda. a molecular docking system enables biologists to check whether two molecular models can be combined at a specific position and remain in their stable states by simulation. it can be used in developing new materials and designing new drugs. since the docking simulation consists of several complicated computations at the level of atoms, it requires high computing capabilities such as super computers and parallel computing systems. we propose a molecular docking system using parallel gpus in this paper. in our proposed method, a gpu can process an equation as a single logical work unit. the computations can be executed through parallel gpus in real-time. the proposed system was evaluated in its performance by comparing with conventional cpu-based systems. a series of experiments for measuring performance of the system showed that our system is 33 to 287 times faster than the cpu-based systems.
context-aware robot navigation based on sensor association rules. within the mobile robotics research community, a great many approaches have been proposed for solving the navigation problem. the key difference between these various navigation architectures is the manner in which they decompose the problem into smaller subunits. in this paper, a data mining methodology developed for the retrieving significant frequent patterns is extended to allow robots to learn and navigate on unknown terrain in natural way. the method has two phases: context identification phase and validation phase. conjunction of those phases provides an easy and straightforward way for exploring new workings space for robots.
parallel implementation of mobile robotic self-localization. self-localization is a fundamental problem in mobile robotics. it consists of estimating the position of a robot given a map of the environment and information obtained by sensors. among the algorithms used to address this issue, the monte carlo technique has obtained a considerable attention by the scientific community due to its simplicity and precision. monte carlo localization is a sample-based technique that estimates robot's pose using a probability density function represented by samples (particles). the complexity of this algorithm scales proportionally to the number of particles used. the larger the environment, the more particles are required for robot localization. this fact limits the use of this algorithm to medium size environments. in order to improve the efficiency of the monte carlo technique and allow it to be used in large environments we propose a parallel implementation. our implementation is based on openmp and mpi message passing interface. experimental results are used to show the efficiency of our approach.
adaptive intra cluster routing for wireless sensor networks. scientists have listed down ten emerging technologies that will change the world's future and wireless sensor network (wsn) is one of them. a lot of work is in progress to make this technology more effective by having research in this field. this network is composed of sensing nodes which are energy limited so energy efficiency is one of the most critical design issues. to have energy efficient network, efficient routing plays very important role. in this paper, adaptive intra cluster routing (aicr) is proposed which is the best solution to the problem offered by traditional routing algorithms. comparative study of aicr is done with multihop router [1] by simulating. simulation results have revealed that aicr is 17% more energy efficient and has increased network lifetime up to 12%.
clarm routing: cross layer adhoc-routing based on reputation management in wireless multi-hop networks. this paper presents a framework of wireless multi-hop networks exploiting an ad hoc routing protocol working on the layer 2.5, called clarm (cross layer adhoc-routing based on reputation management) routing protocol. the framework of clarm routing protocol incorporates following three things: a new concept of wireless multi-hop network architecture, a new 2.5-layer routing technique with a reputation management scheme, high throughput network performance based on cross-layer approache between mac (medium access control) and clarm layers. we compare the performance of the clarm routing protocol with previous routing algorithms, dsr (dynamic source routing) and aodv (ad hoc on demand distance vector), previous reputation management scheme core (collaborative reputation) and confidant (cooperation of nodes fairness in dynamic ad hoc networks). a case study on practical experiments and simulations shows that the clarm routing protocol yields better performance in terms of low rate of packet loss and high throughput network performance.
mining quantitative association rule of earthquake data. earthquake is a natural disaster which causes extensive poverty damage as well as the death of thousands and thousands of people. in this study, we tried to find the unknown characteristics of earthquakes using association rule mining methods global earthquake data occurred since 1973. as a way for mining of quantitative association rule on the earthquake data which includes date, location, magnitude and depth of earthquake. we divided it into small sections and applied a method to find out association rule by repeating the process to merge nearby sections. as the result from study, we could derive associate relationship between time and magnitude, depth and magnitude, as well as location and frequency. this result could prove the relationship more efficiently when data mining technique was applied to earthquake data. it would serve as a reference for further study of relationship with other attributes such as geology, tectonic and so on.
distributed cluster head election algorithm using local energy estimation. in the wireless sensor network (wsn), selecting cluster head (ch) is important issue to increase the network lifetime and selection time of ch is critical. we propose improved ch selection method that the election time of ch does not be increased as the local energy level is decreased. the proposed method, distributed cluster head election algorithm using local energy estimation (dchea), uses energy levels of neighboring sensor nodes as well as local energy level to prevent the decrease of the ch probability of the sensor node. the simulation result shows that the life time of the wsn using the proposed scheme is extended.
enhanced next hop selection scheme for qos support in multi-hop wireless networks. when introduce real-time applications in wireless network environment, t is important to design how to guarantee several qos requirements of the applications. this paper proposes a novel selective forwarding scheme in order to satisfy qos requirements in the aspect of delay and reliability in multi-hop wireless networks. to achieve this purpose, we introduce the relay region by dividing the transmission range of each node into two regions: i) the region of the delay requirement, and ii) the region of the reliability requirement. this classification is determined by taking into account the traffic pattern arriving at each node. after realistic simulations using random way point mobility model, the simulation results show that the proposed scheme can maximize the network utilization while satisfying the qos requirements of real-time applications.
a color-based clustering approach for web image search results. in this paper, we propose an approach to cluster web image search results based on color (cbc). we index images into color histogram descriptors and improved-color distribution entropy descriptors (i-cde), and cluster them by the similarity of color descriptors. however, there are some problems in the similarity measurement of i-cde. in order to resolve the problems, we introduce a new method that measures similarity in vector space model (vsm). through experiment and comparison analysis, it is proved that the proposed cbc approach supplies a good experience for users, and the vsm method solves the problems existing in the similarity measuring method of i-cde and gives better performance.
ecg signal compression using 2d wavelet foveation. foveation principles suggested by natural vision systems enable the construction of a proper mask that may modulate the coefficients given by the discrete wavelet transform of an ecg record. the mask is spatially selective and provides maximum accuracy around specific regions of interest. subsequent denoising and coefficient quantization are further combined with efficient coding techniques such as spiht in order to provide high compression ratios at low reconstruction errors. experimental results reported on a number of mit-bih records show improved performances over existing solutions.
an implementation of the cqs supporting multimedia traffic. in this paper, we propose a cqs (calendar queue scheduler) architecture which was designed for processing multimedia and timing traffic in home network. with various characteristics of the increased traffic flowed in home such as voip, vod, iptv, and best-efforts traffic, the needs of managing qos (quality of service) are being discussed. making a group regarding application or service is effective to guarantee successful qos under the restricted circumstances. the proposed design is aimed for home gateway corresponding to the end points of receiver on end-to-end qos and eligible for supporting multimedia traffic within restricted network sources and optimizing queue sizes. we present a cqs (calendar queue scheduler) architecture implemented in synthesizable verilog form. we simulated the area for both each module and each memory. the area for each module is referenced by nand(2x1) gate(11.09) when synthesizing with magnachip 0.18 cmos libraries through the synopsys design compiler. we verified the portion of memory is 85.38% of the entire cqs. and each memory size is extracted through cacti 5.3(a unit in mm2). as the day size increases, the increment of the total area increases. according to the increase of the memory's entry, the increment of memory area gradually increases, and defining the day size for 1 year definitely affects the total cqs area. even though the cqs is eligible for rate control and delay control and it is in pursuit of home gateway corresponding to the end points of receiver on end-to-end qos, its biggest problem is the increased memory size. in this paper, we discussed design methodology and operation for each module when designing cqs by hardware. also, its biggest problem on designing cqs is the memory size. we surely know that it is important to define the number of priorities and the day size for 1 year.
design and implementation of page sharing scheme between guests in virtualization environments. according to the development of virtualization technology and enhancement of hardware performance, there will be more and more guests on a host in virtualization environments. these guests use many common files and each file should be duplicated on each guest filesystem and memory. in order to eliminate these duplications of resources, many corporations and laboratories proposed several resource sharing schemes. however, there are some problems such as overhead and complexity. in this paper, in order to reduce such duplications, we propose a page sharing scheme optimized for executable files and libraries using shadow paging. also, we validate our scheme with some evaluation results that show improvements in memory utilization and performance, through the implementation of the proposed scheme and experiments.
a hardware implementation of agc and synchronization for ofdm-based wlan. this paper presents a design and implementation on symbol synchronization and automatic gain control (agc) for ofdm-based wlan. synchronization in ofdm-based receiver is critical for performance and needs a great deal of hardware resources. based on the symmetries between real and imaginary values in short preamble of ieee 802.11, applying the symmetries of a short preamble can reduce the hardware complexities of a matched filter to 30% of multipliers and 80% of adders necessary for a cross-correlator. this paper, contrary to the existing methods which use lookup table or cordic for phase estimation, also presents the phase estimation that the phase of complex signal can be found through binary search to reduce the amount of memory. to maintain the amplitude of incoming signal within the allowable operating range, the method of agc in combination with receive signal strength indicator (rssi) is also presented.
adaptive psam in simo systems with imperfect csi in rayleigh fading channels. in this paper we provide an adaptive modulation approach that use adaptive pilot symbols in single input multiple output systems to maximize the spectral efficiency. the maximization is performed in the presence of imperfect channel state information at the transmitter. also for reduce the computational complexity we propose a new method based on the curve fitting to find optimum power allocation on symbols. numerical results show the accuracy of our new method and demonstrate that our adaptive system outperforms other traditional systems that use of non-adaptive pilot symbols with single antenna based on spectral efficiency performance measure.
automatic motion creating from the posture template for the robot physical training system. this paper presents the collaborated working model to provide service using robot. besides, we present the physical training system for prototype of the working model. at first in this system, to compare the posture, we define a human-like generic template with two angles, then, adjust the template to fit on each of the person to improve the recognition rate of system. moreover, we create robot motion that has used angle data of the created template. the angle data is transformed automatically to the most similar motion. this is achieved by the particular expressions that are up to robot specification. the expressions intend to differences of angle measurement on x, y, z planes and dof constraint. we also show the posture recognition and motion transformation are working well.
a modified-fcm segmentation algorithm for brain mr images. medical image segmentation is a complex and challenging task due to the intrinsic nature of the images. segmentation of magnetic resonance imaging (mri) is widely used in medical area. one of common clustering algorithms is fuzzy c-means (fcm) for segmentation of mr images. however mr images normally significant noise by the impact of principles of imaging, equipment and environment, which can lead to serious inaccuracies with segmentation. based on the fcm clustering algorithm, an improved segmentation technique is proposed in this paper. the sigma filter principle has been applied to change the neighbor pixels of targets. the efficacy of the proposed algorithm is demonstrated by comparison with fcm algorithm in visual evaluation and quantitative evaluation.
a high availability clustering and load balacing mechanism for information security infrastructure system. typically, the information security system is a sort of load balancing one, so server must handle all the communication traffics in intranet system. the server and system easily can be unstable because of increased volume overloaded by an internal connection. the delay and even the network failure of system can occurs server down. to solve these problems, the clustering resources must be distributed effectively to the internal infrastructure system. nowadays high availability clustering and load balacing (halb) is necessary for availability of clustering mechanism of information sysetm. halb is a system structure and functional hierarchy for interactive load euquality and load balancing system of each network area. if one server of some network domain fails, the other server of another domain migrates as a backup server under the multiplexing clustering mechanism through the load-balancing and high availability function. to achieve the best distributed computing, this mechanism is based on the value of critical path through dynamic load euquality policy and efficiency management of server resources. this paper provides a experimental test and recomands halb as a test result, because the test shows that the halb method is more effective in the load balancing between servers and packet filtering schedulings than that of traditional.
energy-efficient scheduling of a real-time task on dvfs-enabled multi-cores. we propose an energy-efficient scheduling of a long-lived real-time video task running on dvfs-enabled multi-core platforms. the proposed scheme reduces the energy consumption by executing the task in parallel on an appropriate number of cores with the other cores powered off, and assigning as lower frequency as possible while meeting the deadline. evaluation shows that the scheme saves a significant energy consumed when executing the task on a single core, up to 67%.
hardware-in-the-loop simulation of uav non-linear control system of mini-helicopter. this paper presents the design, simulation and real-time implementation of a control system for an autonomous mini-helicopter using qnx operating system with pc104 embedded board. the reliability of embedded computer systems can be difficult to analyze for several reason. in the development of unmanned vehicle initially it was much focused on military application to civilian application which has many issues in precise design and development cost. the rapid development in digital technology and real-time embedded control system has been widely applied in various industrial fields. this includes developing flight test prototype and test articles early in the system life cycle to gain real experience and determine the real function such that the ultimate design leads to the correct development of the product. the flight operation and guidance for navigation can be developed early in the program to support the testing without any human intervention. hardware in loop technique is a real time simulation where the input and output signals of the simulator show the same time dependent values as the real process. the gps data and sensor real-time data in the hils is fed into the closed loop of the control system which helps to tune and test the control system to directly fit into the uav on real-time.
design of sensor web condition using smsc. this paper designs wireless remote sensing device for a rapid warning and cut in the expenses of sensing and increase of sensing efficiency by detecting sensing data like a wood fire, gas, electricity, earthquake etc more easily.mthe wireless remote sensing condition of this paper consists of multiple sensors with zigbee communication module, multiple relay routers, and data coordinator. the composition of wireless sensor network is multiple wpan (wireless personal area networks) composed by cell-unit. wpan transfers sensing data to sensor web server using smsc (short message service center) method through more than one base station or remote network like internet. therefore, this paper shows the appropriateness of the application which connects wireless sensor network with sensor web service. also, this paper shows the possibility of expend on sensor network which is based on wpan, and the capability and reliance of the proposed system as usable sensor network.
performance evaluation of on-chip interconnect ip using cbr traffic generator model. the communication efficiency plays a crucial role in achieving high system performance in many multimedia socs (system-on-chips). increased requirements on high bandwidth on-chip communication have led to the emergence of complicated communication architectures and algorithms. however, without thorough analysis of bandwidth requirements of applications, we tend to over-provision resources to avoid potential performance degradation. in this paper, we present a cbr-based traffic modeling technique along with a performance evaluation framework. by using this evaluation technique, we can estimate the sustained performance of on-chip communication infrastructure used in multimedia socs. the traffic behaviors of a multimedia application have been captured and analyzed to characterize individual operations which are modeled using traffic generators to replace hardware ips in evaluation process. the simulation results show that this approach is also effective in discovering the peak performance of on-chip network and bandwidth allocation to ips.
a real-time hardware-software codesign technique of network protocols to provide qos. we present the inter-task communication technique incorporating the rhscc (real-time hardware-software communcation channel) that makes it possible to resolve the hardware-software co-design issue of implementing network protocols in the noc (network on chip) architecture developed in this paper. we address this issue as a partition problem of implementing any network protocol suite into real-time application-specific and reconfigurable hardware and software tasks. such a task decomposition technique can improve co-design productivity by supporting the modularity and reuse of complex network protocol cores. the rhscc guarantees the real-time performance of periodic packets and minimize the average response time of aperiodic packets in order to provide the qos support. a case study based on experiments is conducted to illustrate the application and efficiency of the proposed technique by implementing it in the noc architecture derived from the altera's excalibur epxa4 which is a commercial soc (system on chip) platform.
improved remote user authentication scheme using bilinear pairings. user authentication technologies that provide the anonymity of users have been proposed according to increase in the need for security of personal information and privacy protection in ubiquitous computing environments. studies on smart card-based authentication systems have been actively conducted. in 1993, chang and wu first proposed a smart card-based remote user authentication system. in 2005, das et al. proposed a remote user authentication scheme using bilinear pairings. in the das et al.'s scheme, it prevents many logged in users with the same login-id and provides a flexible password change option to the registered users without any help of the remote system. in this paper, it shows the weakness of the das et al.'s scheme for an impersonation attack using the euclidean algorithm in the login process. this paper proposes an improved scheme that shows more safe and effective figures than the scheme proposed by das et al.'s scheme.
deriving hierarchically combined queueing petri nets for performance prediction of distributed component system. in this paper we propose the performance analysis and improvement methodology based on hierarchically combined queueing petri nets (hqpns). to accomplish the goal, in this paper, we firstly propose architecture design and performance profiling methodology by using uml. secondly, we propose transformation algorithm from the uml based software architecture into hqpns model. lastly we offers performance analysis tool to identify potential bottleneck and critical component from the derived hqpns model. we validate the accuracy of performance prediction by applying real system development scenario. we compare the predicted performance results with the performance data of the real system. this approach reduces the time and the cost caused by developing the hqpns model at the software architecture design phase.
evolving fuzzy case-based reasoning in wholesaler's returning book forecasting. this paper proposes a hybrid system that is developed by evolving fuzzy case-based reasoning (fcbr) with genetic algorithm (ga), for reverse sales forecasting of returning books. fcbr systems have been successfully applied in several domains of artificial intelligence. however, in conventional fcbr method each factor has the same weight which means each one has the same influence on the output data that does not reflect the practical situation. in order to enhance the efficiency and capability of forecasting in fcbr systems, we connected the gas method to adjust the weights of factors in fcbr systems, gafcbr for short. the case base of this research is acquired from a book wholesaler in taiwan, and it is applied by the hybrid system to forecast returning books. the results of the prediction of the hybrid system were compared with the results of a back propagation neural network (bpnn), a conventional cbr, and a multiple-regression analysis method. the experimental results show that the gafcbr is more accurate and efficient when being applied to the forecast of the returning books than other methods.
a genetic algorithm approach for a constrained employee scheduling problem as applied to employees at mall type shops. in this application of artificial intelligence to a real-world problem, the constrained scheduling of employee resourcing for a mall type shop is solved by means of a genetic algorithm. chromosomes encode a one-week schedule and a constraint matrix handles all requirements for the population. the genetic operators are purposely designed to preserve all constraints and the objective function assures an imposed coverage, this is for people on both sections of the mall. the results demonstrate that the genetic algorithm approach can provide acceptable solutions to this type of employee scheduling problem with constrains.
design and implementation of a distributed early warning system combined with intrusion detection system and honeypot. network attack and defense is a never-ending war. along with the rapid development of the internet, network attacks have increased and diversified. use of traditional firewall and intrusion detection technologies cannot match to this rapid change. in response to this trend, we designed and implemented a distributed early warning system where several clients collected a wide range of network attack activities, such as malicious codes, sent attack activities back to a central server, and provided warning messages to the network administrator. the proposed system consists of snort intrusion detection system with nepenthes/sebek honeypot software. this combination comes with client and server architecture so that various aspects of attack-oriented records with analytical capabilities are provided. network administrators will receive warning notices when the entire network under monitoring was attacking. to reduce the burden on the deployment of distributed early warning system, we also implemented the system on the live usb and our system can be easily installed with high portability and plug-and-play features.
using w3af to achieve automated penetration testing by live dvd/live usb. as the popularity of the internet continues growing, there are more and more services appeared, security measures are expected to become all the most important on the internet. personal privacy and confidentiality of information also need to be protected and be resolved of vulnerabilities and weaknesses quickly. it is the user the most concerned about one of the topics on the internet now. in this research, we developed automated penetration testing tools based on an open source, we just enter the target url, and we can automate penetration testing with live dvd/live usb platform, which can be used any platform.
implicit relationship deduction in one/more judgment templates. the mamg distributed selection modeling system supports experts at different sites to judge the solutions with many relationships in the visualized modeling. the implicit relationships in judgment modeling templates are hard to find by directly surveying the templates. the paper deducts the implicit relationship based on the dimensions established by ahp. firstly, search for all the relationship-chains between any two objects; secondly, calculate the weight ratio of every relationship-chain by means of the weight of every object and every relationship. the detailed searching algorithm and calculation are given and an example with computing process in mamg is followed. the result indicates any implicit relationship between any two objects in one/more templates can be found out and evaluated.
a multi-level elaborate least frequently/recently used buffer cache for flash storage systems. this research is to design a new buffer cache for flash memory storage systems. specifically, flash memory based storage systems are compact and fast, compared with the traditional hard disks. eventually, flash memory based solid state disks (ssds) became another attractive storage unit, to be applied to general computing systems. however, flash memory based ssds show critical drawbacks that stem from the unique characteristics of the electronic storage units, incurring huge overhead. especially these drawbacks cause serious performance problem when the access pattern of overwrite operations is irregular. this is mainly because the irregular access pattern increases the frequency of overwrite operations and merge operations in the flash memory, which may cause serious overhead. in order to reduce such overhead, this paper proposes a new buffer cache, called the ml-elfru (multi-level elaborate least frequently/recently used buffer), for a flash translation layer (ftl) in flash memory storages or ssds. additionally, experiments are carried out to show that the ml-elfru can reduce the number of replacement operations in the buffer cache and the number of merge operations in the electronic storage unit compared with other existing buffer cache policies.
performability analysis method from reliability and availability. availability and reliability are important attributes of dependability. many dependability analysis methodologies measure and predict availability and reliability separately. however, those methodologies cannot reflect real system characteristics since availability and reliability are interdependent and occur simultaneously. we propose a performability analysis method which regards availability and reliability at the same time. the proposed performability analysis method contains discrete time markov chain modeling and its analysis.
coarse-grained reconfigurable architecture for multiple application domains: a case study. in this paper, we propose a coarse-grained reconfigurable architecture, which supports both integer type application domain and floating-point type application domain. our coarse-grained reconfigurable architecture has an 8x8 array of integer processing elements to execute 64 integer operations or 32 floating-point operations in parallel. in order to show the feasibility of the proposed architecture, we use mpeg4 decoder as an integer type application and physics engine for 3d graphics as a floating-point type application. we first analyze these applications and optimize their implementation on the proposed architecture at the system level. then we implement the proposed architecture on an fpga board, which decodes 12 frames per second of mpeg4 cif images and execute up to 160 million floating-point operations per second for the physics engine at 20mhz clock frequency.
evaluation of group communication quality over wibro for ship building environment. in the process of construction in the shipbuilding industry, the loading process requires intimate communication among workers and is very dangerous work. wireless sets with poor voice quality or trs with call connection delays are currently being used for the communication. an ip-based group communication system is proposed to replace the existing communication systems and measurements and quality evaluation of the new system are necessary. to obtain unified communication in the shipbuilding industry on the basis of a poc (pit over cellular) service, the first service in the ip multimedia system, this article reviews the quality measurements and evaluation of group communication, based on an enterprise poc service to overcome a very deteriorated nlos resulting from the extensive presence of steel in the work environment, and to provide efficient communication services. to verify that this service was theoretically applicable in this environment, analysis was performed and the results revealed a turnaround time of 1 second or less so that workers would experience no delay in communication with the wibro-based enterprise poc service.
a 3d coordinate estimation by using reformed two ir led markers and psd camera. we introduced a low-cost and compact motion capture system which enables to play motion games in play station 2[1]. the single-psd motion capture system that used the intensity light of a marker has a weak measurement at an intensity variation. it is so difficult to make markers having omni-direction equal intensity in single-psd. in this paper, we propose a new method that solves aforementioned problems. it can measure 3d coordination with the relation of the optical characteristics if the intensity of a pair of markers is same at forward direction. we made a system based on this proposed method and experimented for performance capability. as a result, we were able to make the motion capture system to the robust system for bad factors, such as variation intensity of markers, external light. the system is stable to obtain 3d positions and an adaptable motion games. the improved system is expected to be useful in animation, movies and games.
patient information display system in hospital using rfid. rfid technology is applied in many fields. this technology has the following advantage. if an object has a tag, reader can recognize the id of the object without contact. if this technology is used for identification of patient in hospital, it will be very useful. patients have different illness. when doctors operate patients or exanimate patients, if the doctor confuses the disease of patient, a fatal medical circumstance may occur. if rfid technology is used for this case, we can easily protect patients from fatal medical mistakes. in this paper, we introduced the developed rfid system for identification of patient in hospital. this system is displayed on the monitor with the information of name, photo, and illness of patient. rfid system uses general-purpose chip em4095. carrier frequency of em4095 is 125khz. operating process of this system is as follows. reader, which made with em4095, recognizes the patient's id. the recognized id is sent to the host computer. host computer search the same id in db of computer. the information of patient in db is shown on the monitor. the information is shown on pda for accompanied person or nurse. as the result, we explain the developed system and showed the photo of system and showed the table of performance.
zone-based fairness control in multi-channel multi-rate high-speed networks. sctp (stream control transmission protocol) is a general-purpose transport protocol for ip network data communications. due to its attractive features such as multi-streaming and multi-homing, sctp has received much attention from the various network communities. this paper introduces the main features of sctp, and presents a zone-based fairness control scheme that includes sctp multi-streaming to solve performance problems and evaluates its performance. the performance of the proposed scheme is evaluated using an opnet simulator. proposed zone-based fairness control scheme overcomes existing problems in the traditional sctp when a multi-streaming feature is used.
improved authentication algorithm for umts. authentication process of user in mobile networks is an important issue. previous standard of telecommunication global system for mobile communication (gsm) has many security weaknesses. under third generation partnership project(3gpp), new standard universal mobile telecommunication system is developed. which removes the security weaknesses of previous standards. however one security loop hole has been revealed in umts. it is the sending of international mobile subscriber identity (imsi) in plain text over the air interface. in this paper we introduce a security algorithm named as airam, whose name is derived from developers of this algorithm. it resolves the problem of sending imsi in plain text over the air interface by implementing asymmetric/symmetric cryptography techniques. we have presented simulation results of airam algorithm that show how effciently airam algorithm performs the user authentication process and its effectiveness against replay and imposition attacks.
a study on the digital watermarking technique for jpeg 2000. recently, according to the number of internet in widely use and the development of the related application, the distribution and use of multimedia contents, such as digital images, are very easy. since these can modify as easy as use, multimedia contents need newly compressed jpeg 2000 and digital watermarking technique because of its enormous amount of information. to protect the digital image in real-time, this paper proposes two methods that dual watermarking method (dwm) based jpeg 2000 and performing jpeg 2000 and watermarking synchronously. dwm consists of the robust and fragile watermarking. also, in dwm, watermarks are carefully embedded avoiding the areas of region of interest (roi) and the edge of the digital image to protect the integrity of it. in performing jpeg 2000 and watermarking, it takes considerably less time to do jpeg 2000 and watermarking than when they are done separately. based on the experimental results, it takes 0.72 second for jpeg 2000 and watermarking, and 1.11 second when they are done separately.
actuation architecture for emotional robotic applications. some robotic applications have been given emotional expression in an attempt to improve human-robot interaction. in this paper, we propose an actuation architecture of emotional robotic applications for faithful expression based on emotion information. it enables optimization of an interaction between a person and a robot based on an emotion, by expression of a natural emotion action suitable for change in autonomous emotion.
robust timing jitter control method for network synchronization. in this paper, a robust timing jitter control method is proposed and analyzed for network synchronization. in order to reduce timing jitter which exists in delays between a master and slave, following delay is estimated by using previous one. then, these estimated ones are not according to exact ones which do not include jitter. but timing jitter can be certainly reduced although remaining some jitters. the proposed method in this paper can be applied to the network synchronization procedure.
the integration of simulation modeling system for student experiment and modeling ability evaluation. this research aims at developing and evaluating the computer simulation software of pendulum, and exploring junior high students' scientific modeling ability. firstly, the researcher analyzed pendulum modeling software development. secondly, after considering the validity of the software, and the assessments of the whole system by the experts in the field, this researcher revised the software to make it more suitable for the purposes of junior high students' pendulum modeling with computer simulation. finally, purposes of this research are to contend the suggestions of application of the software for junior high science teacher, to synthetic development relevant software of pendulum modeling in this research, and to obtain the following conclusions: 1. there are six kinds of variables of simulation pendulum: mass, length, angle, force, air-force, and width of string. based on the modeling software systematic, the researcher needed to develop relevant software tools to help students' modeling, such as time-recorder, grid chart and the film of galileo's history of science. 2. the fuzzy synthetic evaluation was implemented for assessing modeling ability. five aspects, with totally 19 sub items together, are contained in the evaluation system, which can be regarded as the evaluation for student's modeling ability. 3. via the evaluation in discipline content, media interface and the user attitude, etc., this simulation software is suitable for the stage of junior high student pendulum modeling under the movement law, f = m a.
the structure of the sdp using enablers in the ims. nowadays in communication and network businesses, architectures and systems are independently constructed with existing service or new service deployment without considering common functions and services between them. consequently, the study of standardized service delivery platform (sdp) structure and its related interfaces is needed to provide the methodology of existing or new services in an efficient way. in this paper, we suggest the structure of common service enablers for the sdp and show the way of interaction between them. finally, we will describe an implementation of the components of the sdp using them.
nmf features for speech emotion recognition. there are numerous algorithms to detect emotion from speech signals. among the algorithms, we selected spectral analysis and fused non-negative matrix factorization (nmf) for obvios emotion classification. the algorithm has been tested in several different ways by varying nmf and the speech database. the experimental results show performance of 90% and classification success of 77% for speaker dependent and independent cases, respectively.
a mac protocol considering traffic load information for a cluster based wireless sensor network. power conservation is crucial in designing wireless sensor networks (wsns) with long network lifetime. an energy and delay efficient tdma scheduling algorithm for a cluster based wireless sensor network is proposed. the proposed energy efficient dynamic scheduling (eeds) algorithm in this paper uses the information about node traffic load, the number of member nodes and its qos (quality of service) requirement. our eeds algorithm could reduce energy consumption and transmission delay. through mathematical analysis we evaluate the performance of our algorithm and compare to the related works.
incentive mechanism for service differentiation in p2p networks. p2p (peer-to-peer) networks are self-organizing networks and rely on voluntary contribution from individual peers. peers can easily access information without contributing any information or service to p2p networks. this leads to the well known "free-riding" problem. in order to encourage the cooperation of peers, there needs to be an incentive mechanism that rewards cooperation and punishes free riding. in this paper, we propose an incentive mechanism, called p2pim (p2p incentive mechanism for service differentiation), which computes the contribution by monitoring the peer's behavior and provides the differentiated service according to the peer's contribution. our simulation results show the efficiency and stability of proposed incentive mechanism.
a study of metadata design for e-learning marketplace based on iptv. e-learning marketplace based on iptv is defined as the marketplace for e-learning service between contents supplier and demander through iptv environment. this e-learning marketplace is increasing the interest of e-learning service provider with its interactive media characteristics. to iptv, it can contribute to enhance its effectiveness by developing various contents and service model in the initial phase of broadcasting-communication convergence. this study designed metadata using e-learning marketplace based on iptv. especially the metadata designing include recommendation-tag for supply supplementary learning content. it can support self-directed learning. through basic metadata with weight value, it is designed to support supplementary learning content from customers to wants on the marketplace. recommendation-system can be built by many methods for recommending the learning content including explicit properties using collaborative filtering method that can solve limitations in existing learning recommendation.
parallel-machine scheduling of simple linear deteriorating jobs. we consider parallel-machine scheduling problems in which the processing time of a job is a simple linear increasing function of its starting time. the objectives are to minimize the makespan, total machine load, and total completion time. we show that all the problems are strongly np-hard with an arbitrary number of machines and np-hard in the ordinary sense with a fixed number of machines. for the former two problems, we prove that there exists no polynomial time approximation algorithm with a constant worst-case bound when the number of machines is arbitrary unless p=np. when the number of machines is fixed, we propose two similar fully polynomial-time approximation schemes for the former two problems.
on the descriptional complexity of watson-crick automata. watson-crick automata are finite state automata working on double-stranded tapes, introduced to investigate the potential of dna molecules for computing. in this paper, we continue the investigation of descriptional complexity of watson-crick automata initiated by paun et al. [a. paun, m. paun, state and transition complexity of watson-crick finite automata, in: g. ciobanu, g. paun (eds.), fundamentals of computation theory, fct'99, in: lncs, vol. 1684, 1999, pp. 409-420]. in particular, we show that any finite language, as well as any unary regular language, can be recognized by a watson-crick automaton with only two, and respectively three, states. also, we formally define the notion of determinism for these systems. contrary to the case of non-deterministic watson-crick automata, we show that, for deterministic ones, the complementarity relation plays a major role in the acceptance power of these systems.
sequential snp systems based on min/max spike number. we consider the properties of spiking neural p (snp) systems that work in a sequential manner. these snp systems are a class of computing devices recently introduced as a bridge between spiking neural nets and membrane computing. the general sequentiality of these systems was considered previously; now we focus on the sequentiality induced by the spike number: at each step, the neuron with the maximum (or minimum) number of spikes among the neurons that are active (can spike) will fire. this strategy corresponds to a global view of the whole network that makes the system sequential. we study the properties of this type of a restriction (i.e. considering the case of sequentiality induced by the function maximum defined on numbers of spikes as well as the case of the sequentiality induced by the function minimum similarly defined on numbers of spikes). several universality results are obtained for the cases of maximum and minimum induced sequentiality.
on determinism in modal transition systems. modal transition system (mts) is a formalism which extends the classical notion of labelled transition systems by introducing transitions of two types: must transitions that have to be present in any implementation of the mts and may transitions that are allowed but not required. the mts framework has proved to be useful as a specification formalism of component-based systems as it supports compositional verification and stepwise refinement. nevertheless, there are some limitations of the theory, namely that the naturally defined notions of modal refinement and modal composition are incomplete with respect to the semantic view based on the sets of the implementations of a given mts specification. recent work indicates that some of these limitations might be overcome by considering deterministic systems, which seem to be more manageable but still interesting for several application areas. in the present article, we provide a comprehensive account of the mts framework in the deterministic setting. we study a number of problems previously considered on mts and point out to what extend we can expect better results under the restriction of determinism.
dejean's conjecture holds for n>=30. we extend carpi's results by showing that dejean's conjecture holds for n>=30.
set multi-covering via inclusion-exclusion. set multi-covering is a generalization of the set covering problem where each element may need to be covered more than once and thus some subset in the given family of subsets may be picked several times for minimizing the number of sets to satisfy the coverage requirement. in this paper, we propose a family of exact algorithms for the set multi-covering problem based on the inclusion-exclusion principle. the presented esmc (exact set multi-covering) algorithm takes o^*((2t)^n) time and o^*((t+1)^n) space where t is the maximum value in the coverage requirement set (the o^*(f(n)) notation omits a polylog(f(n)) factor). we also propose the other three exact algorithms through different tradeoffs of the time and space complexities. to the best of our knowledge, this present paper is the first one to give exact algorithms for the set multi-covering problem with nontrivial time and space complexities. this paper can also be regarded as a generalization of the exact algorithm for the set covering problem given in [a. bjorklund, t. husfeldt, m. koivisto, set partitioning via inclusion-exclusion, siam journal on computing, in: focs 2006 (in press, special issue)].
defining syntax-directed translations by tree bimorphisms. we introduce a class of tree bimorphisms that define exactly the translations performed by syntax-directed translation schemata. we also show that these ''quasi-alphabetic'' tree bimorphisms preserve recognizability, and that their class is closed under composition and inverses.
separation numbers of trees. let g be a graph on n vertices. given a bijection f:v(g)->{1,2,...,n}, let |f|=min{|f(u)-f(v)|:uv@?e(g)}. the separation numbers(g) (also known as antibandwidth [t. calamoneri, a. massini, l. torok, i. vrt'o, antibandwidth of complete k-ary trees, electronic notes in discrete mathematics 24 (2006), 259-266; a. raspaud, h. schroder, o. sykora, l. torok, i. vrt'o, antibandwidth and cyclic antibandwidth of meshes and hypercubes, discrete mathematics 309 (2009) 3541-3552] of g is then max{|f|} over all such bijections f of g. we study the case when g is a forest, obtaining the following results. 1.let f be a forest in which each component is a star. then s(f)=n-@m2, where @m is the minimum value of @?x|-|y@? over all bipartitions (x,y) of f. 2.let d be the maximum degree of a tree t on n vertices. then (a)s(t)>=n2-c"1nd, and (b)s(t)>=n2-c"2d^2log"dn, where c"1 and c"2 are absolute constants. we give constructions showing that the bound (a) is asymptotically tight when d is in the range n^1^3=4 is an absolute constant. we also show that for h>=3 and odd d>=3, we have s(t"h^d)=n2-@q(d^2+dh), where t"h^d is the symmetric d-ary tree of height h, improving the estimates obtained in the first of the above-mentioned references.
pattern avoidance by palindromes. we show that every avoidable pattern can be avoided by an infinite sequence of palindromes over a fixed finite alphabet.
hard constraint satisfaction problems have hard gaps at location 1. an instance of the maximum constraint satisfaction problem (max csp) is a finite collection of constraints on a set of variables, and the goal is to assign values to the variables that maximises the number of satisfied constraints. max csp captures many well-known problems (such as maxk-sat and max cut) and is consequently np-hard. thus, it is natural to study how restrictions on the allowed constraint types (or constraint language) affect the complexity and approximability of max csp. the pcp theorem is equivalent to the existence of a constraint language for which max csp has a hard gap at location 1; i.e. it is np-hard to distinguish between satisfiable instances and instances where at most some constant fraction of the constraints are satisfiable. all constraint languages, for which the csp problem (i.e., the problem of deciding whether all constraints can be satisfied) is currently known to be np-hard, have a certain algebraic property. we prove that any constraint language with this algebraic property makes max csp have a hard gap at location 1 which, in particular, implies that such problems cannot have a ptas unless p=np. we then apply this result to max csp restricted to a single constraint type; this class of problems contains, for instance, max cut and max dicut. assuming p
a sturmian sequence related to the uniqueness conjecture for markoff numbers. sturmian sequences appear in the work of markoff on approximations of real numbers and minima of quadratic functions. in particular, christoffel words, or equivalently pairs of relatively prime nonnegative integers, parametrize the markoff numbers. it was asked by frobenius if this parametrization is injective. we answer this conjecture for a particular subclass of these numbers, and show that a special sturmian sequence of irrational slope determines the order of the markoff numbers in this subclass.
on the synchronized derivation depth of context-free grammars. we consider depth of derivations as a complexity measure for synchronized and ordinary context-free grammars. this measure differs from the earlier considered synchronization depth in that it counts the depth of the entire derivation tree. we consider (non-)existence of trade-offs when using synchronized grammars as opposed to non-synchronized grammars and establish lower bounds for certain classes of linear context-free languages.
from nerode's congruence to suffix automata with mismatches. in this paper we focus on the minimal deterministic finite automaton s"k that recognizes the set of suffixes of a word w up to k errors. as first result we give a characterization of the nerode's right-invariant congruence that is associated with s"k. this result generalizes the classical characterization described in [a. blumer, j. blumer, d. haussler, a. ehrenfeucht, m. chen, j. seiferas, the smallest automaton recognizing the subwords of a text, theoretical computer science, 40, 1985, 31-55]. as second result we present an algorithm that makes use of s"k to accept in an efficient way the language of all suffixes of w up to k errors in every window of size r of a text, where r is the repetition index of w. moreover, we give some experimental results on some well-known words, like prefixes of fibonacci and thue-morse words. finally, we state a conjecture and an open problem on the size and the construction of the suffix automaton with mismatches.
online parallel machines scheduling with two hierarchies. this paper investigates an online hierarchical scheduling problem on m parallel identical machines. each job, as well as each machine, has a hierarchy associated with it. a job can be scheduled on a machine only when its hierarchy is no higher than that of the machine. the objective is to minimize the makespan. in addition, we assume that there are only two hierarchies, and k machines have a higher hierarchy which can schedule all jobs. we present an online algorithm with a competitive ratio of 1+m^2-mm^2-km+k^2
a computational model for tiling recognizable two-dimensional languages. tiling systems are a well accepted model to define recognizable two-dimensional languages but they are not an effective device for recognition unless a scanning strategy for the pictures is fixed. we define a tiling automaton as a tiling system equipped with a scanning strategy and a suitable data structure. the class of languages accepted by tiling automata coincides with the rec family. in this framework it is possible to define determinism, non-determinism and unambiguity. then (deterministic) tiling automata are compared with the other known (deterministic) automata models for two-dimensional languages.
atomic routing games on maximum congestion. we study atomic routing games on networks in which players choose a path with the objective of minimizing the maximum congestion along the edges of their path. the social cost is the global maximum congestion over all edges in the network. we show that the price of stability is 1. the price of anarchy, poa, is determined by topological properties of the network. in particular, poa=o(@?+logn), where @? is the length of the longest path in the player strategy sets, and n is the size of the network. further, @k-1@?poa@?c(@k^2+log^2n), where @k is the length of the longest cycle in the network, and c is a constant.
a control flow analysis for beta-binders with and without static compartments. we introduce a control flow analysis, that statically approximates the dynamic behaviour of processes, expressed in the beta-binders calculus and in an extended version of the calculus modelling static compartments. our analysis of a system is able to describe the essential behaviour of each box, tracking all the possible bindings of variables, all the possible intra- and inter-boxes communications, and, finally, all the possible movements across compartments. the analysis offers a basis for establishing static checks of biological dynamic properties. we apply our analysis to an abstract specification of the interaction between a virus and cells of the immune system and to a model of the camp-signaling pathway in olfactory sensory neurons.
the "equal last letter" predicate for words on infinite alphabets and classes of multitape automata. we consider the first-order theory of the free infinitely generated monoid with the usual predicates ''prefix'' and ''equal length'' along with the predicate ''equal last letter''. the associated definable relations are related to the algebras of relations recognized by different types of multitape automata which are natural extensions of the famous rabin-scott multitape automata and the synchronous automata. we investigate these classes of automata and solve decision issues concerning them.
state-complexity hierarchies of uniform languages of alphabet-size length. we study the state complexity of certain simple languages. if a is an alphabet of k letters, then a k-language is a nonempty set of words of length k, that is, a uniform language of length k. we show that the minimal state complexity of a k-language is k+2, and the maximal, (k^k^-^1-1)/(k-1)+2^k+1. we prove constructively that, for every i between the minimal and maximal bounds, there is a language of state complexity i. we introduce a class of automata accepting sets of words that are permutations of a; these languages define a complete hierarchy of complexities between k^2-k+3 and 2^k+1. the languages of another class of automata, based on k-ary trees, define a complete hierarchy of complexities between 2^k+1 and (k^k^-^1-1)/(k-1)+2^k+1. this provides new examples of uniform languages of maximal complexity.
a process model of rho gtp-binding proteins. rho gtp-binding proteins play a key role as molecular switches in many cellular activities. in response to extracellular stimuli and with the help of regulators (gef, gap, effector, gdi), these proteins serve as switches that interact with their environment in a complex manner. based on the structure of a published ordinary differential equations (ode) model, we first present a generic process model for the rho gtp-binding proteins, and compare it with the ode model. we then extend the basic model to include the behaviour of the gdi regulators and explore the parameter space for the extended model with respect to biological data from the literature. we discuss the challenges this extension brings and the directions of further research. in particular, we present techniques for modular representation and refinement of process models, where, for example, different rho proteins with different rates for regulator interactions can be given as instances of the same parametric model.
synchronizing automata preserving a chain of partial orders. we present a new class of automata which strictly contains the class of aperiodic automata and shares with the latter certain synchronization properties. in particular, every strongly connected automaton in this new class is synchronizing and has a synchronizing word of length @?n(n+1)6@? where n is the number of states of the automaton.
on the runtime and robustness of randomized broadcasting. in this paper, we study the following randomized broadcasting protocol. at some time t an information r is placed at one of the nodes of a graph. in the succeeding steps, each informed node chooses one neighbor, independently and uniformly at random, and informs this neighbor by sending a copy of r to it. we begin by developing tight lower and upper bounds on the runtime of the algorithm described above. first, it is shown that on @d-regular graphs this algorithm requires at least log"2"-"1"@dn+log"("@d"@d"-"1")"^"@dn-o(logn)~1.69log"2n rounds to inform all n nodes. together with a result of pittel [b. pittel, on spreading a rumor, siam journal on applied mathematics, 47 (1) (1987) 213-223] this bound implies that the algorithm has the best performance on complete graphs among all regular graphs. for general graphs, we prove a slightly weaker lower bound of log"2"-"1"@dn+log"4n-o(logn)~1.5log"2n, where @d denotes the maximum degree of g. we also prove two general upper bounds, (1+o(1))nlnn and o(n@d@d), respectively, where @d denotes the minimum degree. the second part of this paper is devoted to the analysis of fault-tolerance. we show that if the informed nodes are allowed to fail in some step with probability 1-p, then the broadcasting time increases by at most a factor 6/p. as a by-product, we determine the performance of agent based broadcasting in certain graphs and obtain bounds for the runtime of randomized broadcasting on cartesian products of graphs.
reactive systems, (semi-)saturated semantics and coalgebras on presheaves. the semantics of process calculi has traditionally been specified by labelled transition systems (ltss), but, with the development of name calculi, it turned out that reaction rules (i.e., unlabelled transition rules) are often more natural. this leads to the question of how behavioral equivalences (bisimilarity, trace equivalence, etc.) defined for lts can be transferred to unlabelled transition systems. recently, in order to answer this question, several proposals have been made with the aim of automatically deriving an lts from reaction rules in such a way that the resulting equivalences are congruences. furthermore, these equivalences should agree with the standard semantics, whenever one exists. in this paper, we propose saturated semantics, based on a weaker notion of observation and orthogonal to all the previous proposals, and we demonstrate the appropriateness of our semantics by means of two examples: logic programming and open petri nets. we also show that saturated semantics can be efficiently characterized through the so called semi-saturated games. finally, we provide coalgebraic models relying on presheaves.
continuant polynomials and worst-case behavior of hopcroft's minimization algorithm. this paper is concerned with the analysis of the worst case behavior of hopcroft's algorithm for minimizing deterministic finite state automata. we extend a result of castiglione, restivo and sciortino. they show that hopcroft's algorithm has a worst case behavior for the automata recognizing fibonacci words. in a previous paper, we have proved that this holds for all standard sturmian words having an ultimately periodic directive sequence (the directive sequence for fibonacci words is (1,1,...)). we prove here that the same conclusion holds for all standard sturmian words having a directive sequence with bounded elements. more precisely, we obtain in fact a characterization of those directive sequences for which hopcroft's algorithm has worst case running time. these are the directive sequences (d"1,d"2,d"3,...) for which the sequence of geometric means (d"1d"2...d"n)^1^/^n is bounded. as a consequence, we easily show that there exist directive sequences for which the worst case for the running time is not attained.
the degree of word-expansion of lexicalized rrww-automata - a new measure for the degree of nondeterminism of (context-free) languages. restarting automata can be seen as analytical variants of classical automata as well as of regulated rewriting systems. we study a measure for the degree of nondeterminism of (context-free) languages in terms of deterministic restarting automata that are (strongly) lexicalized. this measure is based on the number of occurrences of auxiliary symbols (categories) used for recognizing a language as the projection of its characteristic language onto its input alphabet. this type of recognition is typical for analysis by reduction, a method used in linguistics for the creation and verification of formal descriptions of natural languages. our main results establish a hierarchy of classes of context-free languages and two hierarchies of classes of non-context-free languages that are based on the expansion factor of a language.
accelerating boyer-moore searches on binary texts. the boyer and moore (bm) pattern matching algorithm is considered as one of the best, but its performance is reduced on binary data. yet, searching in binary texts has important applications, such as compressed matching. the paper shows how, by means of some pre-computed tables, one may implement the bm algorithm also for the binary case without referring to bits, and processing only entire blocks such as bytes or words, thereby significantly reducing the number of comparisons. empirical comparisons show that the new variant performs better than regular binary bm and even than bdm.
determination of finite automata accepting subregular languages. we investigate the descriptional complexity of the nondeterministic finite automaton (nfa) to the deterministic finite automaton (dfa) conversion problem, for automata accepting subregular languages such as combinational languages, definite languages and variants thereof, (strictly) locally testable languages, star-free languages, ordered languages, prefix-, suffix-, and infix-closed languages, and prefix-, suffix-, and infix-free languages. most of the bounds for the conversion problem are shown to be tight in the exact number of states, that is, the number is sufficient and necessary in the worst case. otherwise tight bounds in order of magnitude are shown.
prime algebraicity. a prime algebraic lattice can be characterised as isomorphic to the downwards-closed subsets, ordered by inclusion, of its complete primes. it is easily seen that the downwards-closed subsets of a partial order form a completely distributive algebraic lattice when ordered by inclusion. the converse also holds; any completely distributive algebraic lattice is isomorphic to such a set of downwards-closed subsets of a partial order. the partial order can be recovered from the lattice as the order of the lattice restricted to its complete primes. consequently prime algebraic lattices are precisely the completely distributive algebraic lattices. the result extends to scott domains. several consequences are explored briefly: the representation of berry's di-domains by event structures; a simplified form of information systems for completely distributive scott domains; and a simple domain theory for concurrency.
finding compact structural motifs. protein structural motif detection has important applications in structural genomics. compared with sequence motifs, structural motifs are more sensitive in revealing the evolutionary relationships among proteins. a variety of algorithms have been proposed to attack this problem. however, they are either heuristic without theoretical performance guarantee, or inefficient due to employing exhaustive search strategies. this paper studies a reasonably restricted version of this problem: the compact structural motif problem. we prove that this restricted version is still np-hard, and we present a polynomial-time approximation scheme to solve it. this is the first approximation algorithm with a guaranteed ratio for the protein structural motif problem.
accelerating certain outputs of merging and sorting networks. this work studies comparator networks in which several of the outputs are accelerated. that is, they are generated much faster than the other outputs, and this without hindering the other outputs. we study this acceleration in the context of merging networks and sorting networks. the paper presents a new merging technique, the tri-section technique, that separates, using a depth 1 network, two sorted sequences into three sets, such that every key in one set is smaller than or equal to any key in the following set. after this separation, each of these sets can be sorted separately, causing the above acceleration of certain outputs. an additional contribution of this paper concerns the well-known 0-1 principle [d.e. knuth, the art of computer programming vol. 3: sorting and searching, second edition, addison-wesley, 1998]. this principle is a powerful tool that simplifies the construction and analysis of comparator networks. the paper demonstrates that, in some cases, there is a better tool for achieving the same goal. in the case at hand, this new tool simplifies one of our proofs by having fewer special cases than the classical 0-1 principle. a second additional contribution concerns batcher's merging techniques. it was shown in [t. levy, a. litman, on merging networks, technical report cs-2007-16, technion, department of computer science, 2007] that all published merging networks, whose width is a power of 2, are a natural generalization of batcher's odd-even merging network. all these published merging networks are of minimal depth and have no degenerate comparators. this raises the following question. is there a merging network, having the above properties, that is not a natural generalization of batcher's odd-even merging network? the tri-section technique provides a positive answer to this question.
on the size of computationally complete hybrid networks of evolutionary processors. a hybrid network of evolutionary processors (an hnep) is a graph where each node is associated with an evolutionary processor (a special rewriting system), a set of words, an input filter and an output filter. every evolutionary processor is given with a finite set of one type of point mutations (an insertion, a deletion or a substitution of a symbol) which can be applied to certain positions of a string over the domain of the set of these rewriting rules. the hnep functions by rewriting the words that can be found at the nodes and then re-distributing the resulting strings according to a communication protocol based on a filtering mechanism. the filters are defined by certain variants of random-context conditions. hneps can be considered as both language generating devices (ghneps) and language accepting devices (ahneps). in this paper, by improving the previous results, we prove that any recursively enumerable language can be determined by a ghnep and an ahnep with 7 nodes. we also show that the families of ghneps and ahneps with 2 nodes are not computationally complete.
predictable semiautomata. we introduce a new class of nondeterministic semiautomata: a nondeterministic semiautomaton s is predictable if there exists k>=0 such that, if s knows the current input a and the next k inputs, the transition under a can be made deterministically. nondeterminism may occur only when the length of the unread input is @?k. we develop a theory of predictable semiautomata. we show that, if a semiautomaton with n states is k-predictable, but not (k-1)-predictable, then k@?(n^2-n)/2, and this bound can be reached for a suitable input alphabet. we characterize k-predictable semiautomata, and introduce the predictor semiautomaton, based on a look-ahead semiautomaton. the predictor is essentially deterministic and simulates a nondeterministic semiautomaton by finding the set of states reachable by a word w, if it belongs to the language l of the semiautomaton (i.e., if it defines a path from an initial state to some state), or by stopping as soon as it infers that w@?l. membership in l can be decided deterministically.
burrows-wheeler transform and palindromic richness. the investigation of the extremal case of the burrows-wheeler transform leads to study the words w over an ordered alphabet a={a"1,a"2,...,a"k}, with a"1
two equivalence relations on digital lines with irrational slopes. a continued fraction approach to upper mechanical words. we examine the influence of the elements of the continued fraction (cf) expansion of irrational positive a less than 1 on the construction of runs in the digitization of the positive half line y=ax or, equivalently, on the run-hierarchical structure of the upper mechanical word with slope a and intercept 0. special attention is given to the cf elements equal to 1. we define two complementary equivalence relations on the set of slopes, based on their cf expansions. a new description of digital lines is presented; we show how to define a straight line or upper mechanical word by two sequences of positive integers fulfilling some extra conditions. these equivalence relations and this new description enable us to analyze the construction of digital lines and upper mechanical words. the analysis of suprema of equivalence classes under one of these relations leads to a result which involves fibonacci numbers.
two non-holonomic lattice walks in the quarter plane. we present two classes of random walks restricted to the quarter plane with non-holonomic generating functions. the non-holonomicity is established using the iterated kernel method, a variant of the kernel method. this adds evidence to a recent conjecture on combinatorial properties of walks with holonomic generating functions [m. mishna, classifying lattice walks in the quarter plane, j. combin. theory ser. a 116 (2009) 460-477]. the method also yields an asymptotic expression for the number of walks of length n.
on the joint subword complexity of automatic sequences. let the (subword) complexity of a sequence u=(u(n))"n"="0^~ over a finite set @s be the function m@?p"u(m), where p"u(m) denotes the number of distinct blocks u(n)...u(n+m-1) of size m in u. in this paper, we study the complexity of u->(n)=(u"1(n),...,u"r(n))"n"="0^~ when each u"i=(u"i(n))"n"="0^~, i=1,...,r, is a q"i-automatic sequence over a finite set @s"i and q"1,...,q"r>=2 are pairwise coprime integers. as an application, we answer a question of allouche and shallit regarding morphic real numbers.
operational state complexity of nested word automata. we introduce techniques to prove lower bounds for the number of states needed by finite automata operating on nested words. we study the state complexity of boolean operations and obtain lower bounds that are tight within an additive constant. the results for union and complementation differ from corresponding bounds for ordinary finite automata. for reversal and concatenation, we establish lower bounds that are of a different order than the worst-case bounds for ordinary finite automata.
fine and wilf words for any periods ii. given positive integers n, and p"1,...,p"r, we establish a fast word combinatorial algorithm for constructing a word w=w"1...w"n of length n, with periods p"1,...,p"r, and on the maximal number of distinct letters. moreover, we show that the constructed word, which is unique up to word isomorphism, is a pseudo-palindrome - i.e. it is a fixed point of an involutory antimorphism.
configuration structures, event structures and petri nets. in this paper the correspondence between safe petri nets and event structures, due to nielsen, plotkin and winskel, is extended to arbitrary nets without self-loops, under the collective token interpretation. to this end we propose a more general form of event structure, matching the expressive power of such nets. these new event structures and nets are connected by relating both notions with configuration structures, which can be regarded as representations of either event structures or nets that capture their behaviour in terms of action occurrences and the causal relationships between them, but abstract from any auxiliary structure. a configuration structure can also be considered logically, as a class of propositional models, or-equivalently-as a propositional theory in disjunctive normal from. converting this theory to conjunctive normal form is the key idea in the translation of such a structure into a net. for a variety of classes of event structures we characterise the associated classes of configuration structures in terms of their closure properties, as well as in terms of the axiomatisability of the associated propositional theories by formulae of simple prescribed forms, and in terms of structural properties of the associated petri nets.
nondeterministic functions and the existence of optimal proof systems. we provide new characterizations of two previously studied questions on nondeterministic function classes: q1: do nondeterministic functions admit efficient deterministic refinements? q2: do nondeterministic function classes contain complete functions? we show that q1 for the class npmv"t is equivalent to the question whether the standard proof system for sat is p-optimal, and to the assumption that every optimal proof system is p-optimal. assuming only the existence of a p-optimal proof system for sat, we show that every set with an optimal proof system has a p-optimal proof system. under the latter assumption, we also obtain a positive answer to q2 for the class npmv"t. an alternative view on nondeterministic functions is provided by disjoint sets and tuples. we pursue this approach for disjoint np-pairs and its generalizations to tuples of sets from np and conp with disjointness conditions of varying strength. in this way, we obtain new characterizations of q2 for the class npsv. question q1 for npsv is equivalent to the question of whether every disjoint np-pair is easy to separate. in addition, we characterize this problem by the question of whether every propositional proof system has the effective interpolation property. again, these interpolation properties are intimately connected to disjoint np-pairs, and we show how different interpolation properties can be modeled by np-pairs associated with the underlying proof system.
shortest synchronizing strings for huffman codes. most complete binary prefix codes have a synchronizing string, that is a string that resynchronizes the decoder regardless of its previous state. this work presents an upper bound on the length of the shortest synchronizing string for such codes. two classes of codes with a long shortest synchronizing string are presented. it is known that finding a synchronizing string for a code is equivalent to finding a synchronizing string of some finite automaton. the cerny conjecture for this class of automata is discussed.
overlap-free words and spectra of matrices. overlap-free words are words over the binary alphabet a={a,b} that do not contain factors of the form xvxvx, where x@?a and v@?a^*. we analyze the asymptotic growth of the number u"n of overlap-free words of length n as n->~. we obtain explicit formulas for the minimal and maximal rates of growth of u"n in terms of spectral characteristics (the joint spectral subradius and the joint spectral radius) of certain sets of matrices of dimension 20x20. using these descriptions we provide new estimates of the rates of growth that are within 0.4% and 0.03% of their exact values. the best previously known bounds were within 11% and 3%, respectively. we then prove that the value of u"n actually has the same rate of growth for ''almost all'' natural numbers n. this average growth is distinct from the maximal and minimal rates and can also be expressed in terms of a spectral quantity (the lyapunov exponent). we use this expression to estimate it. in order to obtain our estimates, we introduce new algorithms to compute the spectral characteristics of sets of matrices. these algorithms can be used in other contexts and are of independent interest.
modeling and simulation of cardiac tissue using hybrid i/o automata. we propose a new biological framework based on the lynch et al. theory of hybrid i/o automata (hioas) for modeling and simulating excitable tissue. within this framework, we view an excitable tissue as a composition of two main kinds of component: a diffusion medium and a collection of cells, both modeled as an hioa. this approach yields a notion of decomposition that allows us to describe a tissue as the parallel composition of several interacting tissues, a property that could be exploited to parallelize, and hence improve, the efficiency of the simulation process. we also demonstrate the feasibility of our hioa-based framework to capture and mimic different kinds of wave-propagation behavior in 2d isotropic cardiac tissue, including normal wave propagation along the tissue; the creation of spiral waves; the break-up of spiral waves into more complex patterns such as fibrillation; and the recovery of the tissue to the rest via electrical defibrillation.
a fast algorithm for finding the positions of all squares in a run-length encoded string. squares are strings of the form ww where w is any nonempty string. main and lorentz proposed an o(nlogn)-time algorithm for finding the positions of all squares in a string of length n. based on their result, we show how to find the positions of all squares in a run-length encoded string in time o(nlogn) where n is the number of runs in this string, provided that we do not explicitly compute at all ''trivial squares'' occurring within runs. the algorithm is optimal and its time complexity is independent of the length of the original uncompressed string.
a curtis-hedlund-lyndon theorem for besicovitch and weyl spaces. global functions of cellular automata on state spaces equipped with the cantor topology are well characterized by the curtis-hedlund-lyndon theorem. in this paper, we develop a characterization of global functions of cellular automata on z, if the state space is equipped by weyl and besicovitch topology. the necessary and sufficient condition for a function to be the global map of a cellular automaton is (1) a strong localization property, a condition that strengthen lipschitz continuity, (2) the set of (cantor) periodic states are positively invariant and (3) the function commutes (in the weyl/besicovitch sense) with the shift operator.
coordination mechanisms. we introduce the notion of coordination mechanisms to improve the performance in systems with independent selfish and non-colluding agents. the quality of a coordination mechanism is measured by its price of anarchy-the worst-case performance of a nash equilibrium over the (centrally controlled) social optimum. we give upper and lower bounds for the price of anarchy for selfish task allocation and congestion games.
deciding determinism of caterpillar expressions. caterpillar expressions have been introduced by bruggemann-klein and wood for applications in markup languages. caterpillar expressions provide a convenient formalism for specifying the operation of tree-walking automata on unranked trees. here we give a formal definition of determinism of caterpillar expressions that is based on the language of instruction sequences defined by the expression. we show that determinism of caterpillar expressions can be decided in polynomial time.
an analysis of the exponential decay principle in probabilistic trust models. research in models for experience-based trust management has either ignored the problem of modelling and reasoning about dynamically changing principal behaviour, or provided ad hoc solutions to it. probability theory provides a foundation for addressing this and many other issues in a rigorous and mathematically sound manner. using hidden markov models to represent principal behaviours, we focus on computational trust frameworks based on the 'beta' probability distribution and the principle of exponential decay, and derive a precise analytical formula for the estimation error they induce. this allows potential adopters of beta-based computational trust frameworks and algorithms to better understand the implications of their choice.
on the limits of the communication complexity technique for proving lower bounds on the size of minimal nfa's. in contrast to the minimization of deterministic finite automata (dfa's), the task of constructing a minimal nondeterministic finite automaton (nfa) for a given nfa is pspace-complete. moreover, there are no polynomial approximation algorithms with a constant approximation ratio for estimating the number of states of minimal nfa's. since one is unable to efficiently estimate the size of a minimal nfa in an efficient way, one should ask at least for developing mathematical proof methods that help to prove good lower bounds on the size of a minimal nfa for a given regular language. here we consider the robust and most successful lower bound proof technique that is based on communication complexity. in this paper it is proved that even a strong generalization of this method fails for some concrete regular languages. ''to fail'' is considered here in a very strong sense. there is an exponential gap between the size of a minimal nfa and the achievable lower bound for a specific sequence of regular languages. the generalization of the concept of communication protocols is also strong here. it is shown that cutting the input word into 2^o^(^n^^^1^^^/^^^4^) pieces for a size n of a minimal nondeterministic finite automaton and investigating the necessary communication transfer between these pieces as parties of a multiparty protocol does not suffice to get good lower bounds on the size of minimal nondeterministic automata. it seems that for some regular languages one cannot really abstract from the automata model that cuts the input words into particular symbols of the alphabet and reads them one by one using its input head.
on designing truthful mechanisms for online scheduling. we study the online version of the scheduling problem q@?c"m"a"x involving selfish agents, considered by archer and tardos in [a. archer, e. tardos, truthful mechanisms for one-parameter agents, in: proceedings of the 42nd ieee symposium on foundations of computer science (focs), 2001, pp. 482-491], where jobs must be scheduled on m related machines, each of them owned by a different selfish agent. we present a general technique for transforming competitive online algorithms for q@?c"m"a"x into truthful online mechanisms with a small loss of competitiveness. we also investigate the issue of designing new online algorithms from scratch so as to obtain efficient competitive mechanisms, and prove some lower bounds on a class of ''natural'' algorithms. a ''direct'' use of such natural algorithms to construct truthful mechanisms yields only trivial upper bounds for the case of two machines. finally, we consider mechanisms with verification, introduced by nisan and ronen [n. nisan, a. ronen, algorithmic mechanism design, in: proceedings of the 31st annual acm symposium on theory of computing, stoc, 1999, pp. 129-140], for offline scheduling problems. we present the first constant-competitive online truthful mechanism with verification for any number of machines.
on the satisfiability threshold of formulas with three literals per clause. in this paper we present a new upper bound for randomly chosen 3-cnf formulas. in particular we show that any random formula over n variables, with a clauses-to-variables ratio of at least 4.4898 is, as n grows large, asymptotically almost surely unsatisfiable. the previous best such bound, due to dubois in 1999, was 4.506. the first such bound, independently discovered by many groups of researchers since 1983, was 5.19. several decreasing values between 5.19 and 4.506 were published in the years between. we believe that the probabilistic techniques we use for the proof are of independent interest.
strip packing with precedence constraints and strip packing with release times. the strip packing problem seeks to tightly pack a set of n rectangles into a strip of fixed width and arbitrary height. the rectangles model tasks and the height models time. this paper examines two variants of strip packing: when the rectangles to be placed have precedence constraints and when the rectangles have release times. strip packing is used to model scheduling problems in which tasks require a contiguous subset of identical resources that are arranged in a linear topology. the variants studied here are motivated by scheduling tasks for dynamically reconfigurable field-programmable gate arrays (fpgas) comprised of a linear arrangement of k homogeneous computing resources, where k is a fixed positive integer, and each task occupies a contiguous subset of these resources. for the case in which tasks have precedence constraints, we give an o(logn) approximation algorithm. we then consider the special case in which all the rectangles have uniform height, and reduce it to the resource constrained scheduling studied by garey, graham, johnson and yao, thereby extending their asymptotic results to our special case problem. we also give an absolute 3-approximation for this special case problem. for strip packing with release times, we provide an asymptotic polynomial time approximation scheme. we make the standard assumption that the rectangles have height at most 1. in addition, we also require widths to be in [1k,1]. for the fpga application, this would imply that the rectangles are at least as wide as a column. our running time is polynomial in n and 1/@e, but exponential in k.
the complexity of weighted boolean #csp with mixed signs. we give a complexity dichotomy for the problem of computing the partition function of a weighted boolean constraint satisfaction problem. such a problem is parameterized by a set @c of rational-valued functions, which generalize constraints. each function assigns a weight to every assignment to a set of boolean variables. our dichotomy extends previous work in which the weight functions were restricted to being non-negative. we represent a weight function as a product of the form (-1)^sg, where the polynomial s determines the sign of the weight and the non-negative function g determines its magnitude. we show that the problem of computing the partition function (the sum of the weights of all possible variable assignments) is in polynomial time if either every function in @c can be defined by a ''pure affine'' magnitude with a quadratic sign polynomial or every function can be defined by a magnitude of ''product type'' with a linear sign polynomial. in all other cases, computing the partition function is fp^#^p-complete.
a powerful abelian square-free substitution over 4 letters. in 1961, paul erdos posed the question whether abelian squares can be avoided in arbitrarily long words over a finite alphabet. an abelian square is a non-empty word uv, where u and v are permutations (anagrams) of each other. the case of the four letter alphabet @s"4={a,b,c,d} turned out to be the most challenging and remained open until 1992 when the author presented an abelian square-free (a-2-free) endomorphism g"8"5 of @s"4^*. the size of this g"8"5, i.e., |g"8"5(abcd)|, is equal to 4x85 (uniform modulus). until recently, all known methods for constructing arbitrarily long a-2-free words on @s"4 have been based on the structure of g"8"5 and on the endomorphism g"9"8 of @s"4^* found in 2002. in this paper, a great many new a-2-free endomorphisms of @s"4^* are reported. the sizes of these endomorphisms range from 4x102 to 4x115. importantly, twelve of the new a-2-free endomorphisms, of modulus m=109, can be used to construct an a-2-free (commutatively functional) substitution @s"1"0"9 of @s"4^* with 12 image words for each letter. the properties of @s"1"0"9 lead to a considerable improvement for the lower bound of the exponential growth of c"n, i.e., of the number of a-2-free words over 4 letters of length n. it is obtained that c"n>@b^-^5^0@b^n with @b=12^1^/^m~1.02306. originally, in 1998, carpi established the exponential growth of c"n by showing that c"n>@b^-^t@b^n with @b=2^1^9^/^t=2^1^9^/^(^8^5^^^3^-^8^5^)~1.000021, where t=85^3-85 is the modulus of the substitution that he constructs starting from g"8"5.
isolation concepts for efficiently enumerating dense subgraphs. in an undirected graph g=(v,e), a set of k vertices is called c-isolated if it has less than c@?k outgoing edges. ito and iwama [h. ito, k. iwama, enumeration of isolated cliques and pseudo-cliques, acm transactions on algorithms (2008) (in press)] gave an algorithm to enumerate all c-isolated maximal cliques in o(4^c@?c^4@?|e|) time. we extend this to enumerating all maximal c-isolated cliques (which are a superset) and improve the running time bound to o(2.89^c@?c^2@?|e|), using modifications which also facilitate parallelizing the enumeration. moreover, we introduce a more restricted and a more general isolation concept and show that both lead to faster enumeration algorithms. finally, we extend our considerations to s-plexes (a relaxation of the clique notion), providing a w[1]-hardness result when the size of the s-plex is the parameter and a fixed-parameter algorithm for enumerating isolated s-plexes when the parameter describes the degree of isolation.
some operations preserving primitivity of words. we investigate some operations where essentially, from a given word w, the word ww^' is constructed where w^' is a modified copy of w or a modified mirror image of w. we study whether ww^' is a primitive word provided that w is primitive. for instance, we determine all cases with an edit distance of w and w^' at most 2 such that the primitivity of w implies the primitivity of ww^'. the operations are chosen in such a way that in the case of a two-letter alphabet, all primitive words of length @?11 can be obtained from single letters.
reoptimization of steiner trees: changing the terminal set. given an instance of the steiner tree problem together with an optimal solution, we consider the scenario where this instance is modified locally by adding one of the vertices to the terminal set or removing one vertex from it. in this paper, we investigate the problem of whether the knowledge of an optimal solution to the unaltered instance can help in solving the locally modified instance. our results are as follows: (i) we prove that these reoptimization variants of the steiner tree problem are np-hard, even if edge costs are restricted to values from {1,2}. (ii) we design 1.5-approximation algorithms for both variants of local modifications. this is an improvement over the currently best known approximation algorithm for the classical steiner tree problem which achieves an approximation ratio of 1+ln(3)/2~1.55. (iii) we present a ptas for the subproblem in which the edge costs are natural numbers {1,...,k} for some constant k.
online scheduling on two uniform machines subject to eligibility constraints. we consider the online scheduling of a set of jobs on two uniform machines with the makespan as objective. the jobs are presented in a list. we consider two different eligibility constraint set assumptions, namely (i) arbitrary eligibility constraints and (ii) grade of service (gos) eligibility constraints. in the first case, we prove that the high speed machine first (hsf) algorithm, which assigns jobs to the eligible machine that has the highest speed, is optimal. with regard to the second case, we point out an error in [m. liu et al., online scheduling on two uniform machines to minimize the makespan, theoretical computer science 410 (21-23) (2009) 2099-2109]; we then provide tighter lower bounds and present algorithms with worst-case analysis for various ranges of machine speeds.
on systems of word equations over three unknowns with at most six occurrences of one of the unknowns. in this paper, we investigate the open question, formulated in 1983 by culik ii and karhumaki, asking whether there exist independent systems of three word equations over three unknowns admitting non-periodic solutions. in particular, we answer negatively the above mentioned question for systems in which one of the unknowns occurs at most six times. that is, we show that such systems admit only periodic solutions or they are not independent.
online scheduling on m uniform machines to minimize total (weighted) completion time. we study two online problems on m uniform machines with speeds s"1@?...@?s"m. the problems are online in the sense that all jobs arrive over time. each job's characteristics, such as processing time and weight become known at its arrival time. for the first problem q|r"j,online|@?c"j, we prove that r-list algorithm is 4m-3+32-competitive. for the second problem q|r"j,online,pmtn|@?w"jc"j, we show that wspt-1 algorithm is 2-competitive if s"i/s"m>=@?"h"="1^is"h/@?"h"="1^ms"h for i=1,...,m-1. then we study a special case where s"1=s"2=...=s"m"-"1@?s"m. we obtain that algorithm wspt-1 is 2-competitive if s"m(m-2)@?s"1(m-1).
the structure and complexity of nash equilibria for a selfish routing game. in this work, we study the combinatorial structure and the computational complexity of nash equilibria for a certain game that models selfish routing over a network consisting of m parallel links. we assume a collection of n users, each employing a mixed strategy, which is a probability distribution over links, to control the routing of her own traffic. in a nash equilibrium, each user selfishly routes her traffic on those links that minimize her expected latency cost, given the network congestion caused by the other users. the social cost of a nash equilibrium is the expectation, over all random choices of the users, of the maximum, over all links, latency through a link. we embark on a systematic study of several algorithmic problems related to the computation of nash equilibria for the selfish routing game we consider. in a nutshell, these problems relate to deciding the existence of a pure nash equilibrium, constructing a nash equilibrium, constructing the pure nash equilibria of minimum and maximum social cost, and computing the social cost of a given mixed nash equilibrium. our work provides a comprehensive collection of efficient algorithms, hardness results, and structural results for these algorithmic problems. our results span and contrast a wide range of assumptions on the syntax of the nash equilibria and on the parameters of the system.
efficient construction of maximal and minimal representations of motifs of a string. two substrings of a given text string are called synchronous (occurrence-equivalent) if their sets of occurrence locations are translates of each other. linear time algorithms are given for the problems of finding a shortest and a longest substring that is synchronous with a given substring. we also introduce approximate variants of the motif discovery problem and give polynomial time algorithms for finding longest and shortest substrings whose suitably translated occurrence location set contains or, respectively, is contained in a given set of locations. the fft technique used here also leads to an o(nlogn) algorithm for finding the maximum-content gapped motif that is synchronous with a given set of locations; the previously known algorithm for this problem is only quadratic.
efficient enumeration of words in regular languages. the cross-section enumeration problem is to list all words of length n in a regular language l in lexicographical order. the enumeration problem is to list the first m words in l according to radix order. we present an algorithm for the cross-section enumeration problem that is linear in n+t, where t is the output size. we provide a detailed analysis of the asymptotic running time of our algorithm and that of known algorithms for both enumeration problems. we discuss some shortcomings of the enumeration algorithm found in the grail computation package. in the practical domain, we modify makinen's enumeration algorithm to get an algorithm that is usually the most efficient in practice. we performed an extensive performance analysis of the new and previously known enumeration and cross-section enumeration algorithms and found when each algorithm is preferable.
general suffix automaton construction algorithm and space bounds. suffix automata and factor automata are efficient data structures for representing the full index of a set of strings. they are minimal deterministic automata representing the set of all suffixes or substrings of a set of strings. this paper presents a novel analysis of the size of the suffix automaton or factor automaton of a set of strings. it shows that the suffix automaton or factor automaton of a set of strings u has at most 2q-2 states, where q is the number of nodes of a prefix-tree representing the strings in u. this bound significantly improves over 2@?u@?-1, the bound given by blumer et al. [a. blumer, j. blumer, d. haussler, r.m. mcconnell, a. ehrenfeucht, complete inverted files for efficient text retrieval and analysis, journal of the acm 34 (1987) 578-589], where @?u@? is the sum of the lengths of all strings in u. more generally, we give novel and general bounds for the size of the suffix or factor automaton of an automaton as a function of the size of the original automaton and the maximal length of a suffix shared by the strings it accepts. we also describe in detail a linear-time algorithm for constructing the suffix automaton s or factor automaton f of u in time o(|s|). our algorithm applies in fact to any input suffix-unique automaton and strictly generalizes the standard on-line construction of a suffix automaton for a single input string. our algorithm can also be used straightforwardly to generate the suffix oracle or factor oracle of a set of strings, which has been shown to have various useful properties in string-matching. our analysis suggests that the use of factor automata of automata can be practical for large-scale applications, a fact that is further supported by the results of our experiments applying factor automata to a music identification task with more than 15,000 songs.
simple equations on binary factorial languages. we consider equations on the monoid of factorial languages on the binary alphabet. we use the notion of a canonical decomposition of a factorial language and previous results by avgustinovich and the author to solve several simple equations on binary factorial languages including x^n=y^n, the commutation equation xy=yx and the conjugacy equation xz=zy. at the end of the paper, we discuss the difficulties hindering the reduction of equations on factorial languages to equations on words and the extension of the alphabet considered.
on post correspondence problem for letter monotonic languages. we prove that for given morphisms g,h:{a"1,a"2,...,a"n}->b^*, it is decidable whether or not there exists a word w in the regular language a"1^*a"2^*...a"n^* such that g(w)=h(w). in other words, we prove that the post correspondence problem is decidable if the solutions are restricted to be from this special language. this yields a nice example of an undecidable problem in integral matrices which cannot be directly proved undecidable using the traditional reduction from the post correspondence problem.
on a generalization of christoffel words: epichristoffel words. sturmian sequences are well-known as the ones having minimal complexity over a 2-letter alphabet. they are also the balanced sequences over a 2-letter alphabet and the sequences describing discrete lines. they are famous and have been extensively studied since the 18th century. one of the extensions of these sequences over a k-letter alphabet, with k>=3, is the episturmian sequences, which generalizes a construction of sturmian sequences using the palindromic closure operation. there exists a finite version of the sturmian sequences called the christoffel words. they have been known since the works of christoffel and have interested many mathematicians. in this paper, we introduce a generalization of christoffel words for an alphabet with 3 letters or more, using the episturmian morphisms. we call them the epichristoffel words. we define this new class of finite words and show how some of the properties of the christoffel words can be generalized naturally or not for this class.
sand automata as cellular automata. in this paper, we exhibit a strong relation between the sand automata configuration space and the cellular automata configuration space. this relation induces a compact topology for sand automata, and a new context in which sand automata are homeomorphic to cellular automata acting on a specific subshift. we show that the existing topological results for sand automata, including the hedlund-like representation theorem, still hold. in this context, we give a characterization of cellular automata which are sand automata, and study some dynamical behaviors such as equicontinuity. furthermore, we deal with simple sand automata. we show that the classical definition of nilpotency is not meaningful for sand automata. then, we introduce the suitable new notion of flattening sand automata. finally, we prove that this simple dynamical behavior is undecidable.
an o(n) algorithm for l(2, 1)-labeling of trees. an l(2,1)-labeling of a graph g is an assignment f from the vertex set v(g) to the set of nonnegative integers such that |f(x)-f(y)|>=2 if x and y are adjacent and |f(x)-f(y)|>=1 if x and y are at distance 2 for all x and y in v(g). a k-l(2,1)-labeling is an l(2,1)-labeling f:v(g)->{0,...,k}, and the l(2,1)-labeling problem asks the minimum k, which we denote by @l(g), among all possible l(2,1)-labelings. it is known that this problem is np-hard even for graphs of treewidth 2. tree is one of a few classes for which the problem is polynomially solvable, but still only an o(@d^4^.^5n) time algorithm for a tree t has been known so far, where @d is the maximum degree of t and n=|v(t)|. in this paper, we first show that an existent necessary condition for @l(t)=@d+1 is also sufficient for a tree t with @d=@w(n), which leads to a linear time algorithm for computing @l(t) under this condition. we then show that @l(t) can be computed in o(@d^1^.^5n) time for any tree t. combining these, we finally obtain an o(n^1^.^7^5) time algorithm, which substantially improves upon previously known results.
hierarchy and equivalence of multi-letter quantum finite automata. multi-letter quantum finite automata (qfas) are a new one-way qfa model proposed recently by belovs, rosmanis, and smotrovs [a. belovs, a. rosmanis, j. smotrovs, multi-letter reversible and quantum finite automata, in: proceedings of the 13th international conference on developments in language theory, dlt'2007, harrachov, czech republic, in: lecture notes in computer science, vol. 4588, springer, berlin, 2007, pp. 60-71], and they showed that multi-letter qfas can accept with no error some regular languages ((a+b)^*b) that are unacceptable by the one-way qfas. in this paper, we continue to study multi-letter qfas. we mainly focus on two issues: (1) we show that (k+1)-letter qfas are computationally more powerful than k-letter qfas, that is, (k+1)-letter qfas can accept some regular languages that are unacceptable by any k-letter qfa. a comparison with the one-way qfas is made by some examples; (2) we prove that a k"1-letter qfa a"1 and another k"2-letter qfa a"2 are equivalent, if and only if, they are (n"1+n"2)^4+k-1-equivalent, and the time complexity of determining the equivalence of two multi-letter qfas using this method is o(n^1^2+k^2n^4+kn^8), where n"1 and n"2 are the numbers of states of a"1 and a"2, respectively, and k=max(k"1,k"2). some other issues are addressed for further consideration.
complexity of counting the optimal solutions. following the approach of hemaspaandra and vollmer, we can define counting complexity classes #@?c for any complexity class c of decision problems. in particular, the classes #@?@p"kp with k>=1 corresponding to all levels of the polynomial hierarchy, have thus been studied. however, for a large variety of counting problems arising from optimization problems, a precise complexity classification turns out to be impossible with these classes. in order to remedy this unsatisfactory situation, we introduce a hierarchy of new counting complexity classes #@?opt"kp and #@?opt"kp[logn] with k>=1. we prove several important properties of these new classes, like closure properties and the relationship with the #@?@p"kp-classes. moreover, we establish the completeness of several natural counting complexity problems for these new classes.
nondeterministic state complexity of nested word automata. we study the nondeterministic state complexity of boolean operations on regular languages of nested words. for union and intersection we obtain matching upper and lower bounds. for complementation of a nondeterministic nested word automaton with n states we establish a lower bound @w(n!) that is significantly worse than the exponential lower bound for ordinary nondeterministic finite automata (nfa). we develop techniques to prove lower bounds for the size of nondeterministic nested word automata that extend the known techniques used for nfas.
periodicity, repetitions, and orbits of an automatic sequence. we revisit a technique of s. lehr on automata and use it to prove old and new results in a simple way. we give a very simple proof of the 1986 theorem of honkala that it is decidable whether a given k-automatic sequence is ultimately periodic. we prove that it is decidable whether a given k-automatic sequence is overlap-free (or squarefree, or cubefree, etc.). we prove that the lexicographically least sequence in the orbit closure of a k-automatic sequence is k-automatic, and use this last result to show that several related quantities, such as the critical exponent, irrationality measure, and recurrence quotient for sturmian words with slope @a, have automatic continued fraction expansions if @a does.
on the relative dominance of paging algorithms. in this paper, we give a finer separation of several known paging algorithms using a new technique called relative interval analysis. this technique compares the fault rate of two paging algorithms across the entire range of inputs of a given size, rather than in the worst case alone. using this technique, we characterize the relative performance of lru and lru-2, as well as lru and fwf, among others. we also show that look-ahead is beneficial for a paging algorithm, a fact that is well known in practice but it was, until recently, not verified by theory.
two collapsing hierarchies of subregularly tree controlled languages. tree controlled grammars are context-free grammars where the associated language only contains those terminal words which have a derivation where the word of any level of the corresponding derivation tree belongs to a given regular language. in this paper, we consider first as control sets such regular languages which can be represented by finite unions of monoids. we show that the corresponding hierarchy of tree controlled languages collapses already at the second level. second, we restrict the number of states allowed in the accepting automaton of the regular control language. we prove that the associated hierarchy has at most five levels.
finite state automata representing two-dimensional subshifts. a new type of two-dimensional automaton has been defined to recognize a class of two-dimensional shifts of finite type having the property that every admissible block found within the related local picture language can be extended to a point of the subshift. here it is shown that this automaton accurately represents the image of the represented two-dimensional shift of finite type under a block code. it is then shown that these automata can be used to check for a certain type of two-dimensional transitivity in the factor language of the corresponding shift space and how this relates to periodicity in the two-dimensional case. the paper closes with a notion of ''follower sets'' that are used to reduce the size of the automata representing two-dimensional sofic shifts.
weighted automata and weighted logics with discounting. we introduce a weighted logic with discounting and we establish the buchi-elgot theorem for weighted automata over finite words and arbitrary commutative semirings. then we investigate buchi and muller automata with discounting over the max-plus and the min-plus semiring. we show their expressive equivalence with weighted mso-sentences with discounting. in this case our logic has a purely syntactic definition. for the finite case, we obtain a purely syntactically defined weighted logic if the underlying semiring is additively locally finite.
optimally competitive list batching. batching has been studied extensively in the offline case, but applications such as manufacturing or tcp acknowledgment often require online solutions. we consider online batching problems, where the order of jobs to be batched is fixed and where we seek to minimize the sum of the completion times of the jobs. we present optimally competitive online algorithms for both s-batch and p-batch problems, and we also derive results for certain naturally occurring special cases, such as the case of unit processing times.
characteristic morphisms of generalized episturmian words. in a recent paper with l.q. zamboni, the authors introduced the class of @q-episturmian words. an infinite word over a is standard @q-episturmian, where @q is an involutory antimorphism of a^*, if its set of factors is closed under @q and its left special factors are prefixes. when @q is the reversal operator, one obtains the usual standard episturmian words. in this paper, we introduce and study @q-characteristic morphisms, that is, morphisms which map standard episturmian words into standard @q-episturmian words. they are a natural extension of standard episturmian morphisms. the main result of the paper is a characterization of these morphisms when they are injective. in order to prove this result, we also introduce and study a class of biprefix codes which are overlap-free, i.e., any two code words do not overlap properly, and normal, i.e., no proper suffix (prefix) of any code-word is left (right) special in the code. a further result is that any standard @q-episturmian word is a morphic image, by an injective @q-characteristic morphism, of a standard episturmian word.
probabilistic analysis of upper bounds for 2-connected distance k-dominating sets in graphs. a small virtual backbone which is modeled as the minimum connected dominating set (cds) problem has been proposed to alleviate the broadcasting storm for efficiency in wireless ad hoc networks. in this paper, we consider a general fault tolerant cds problem, called an h-connected distance k-dominating set (hckds) to balance high efficiency and fault tolerance, and study the upper bound for hckds with a probabilistic method for small h and improve the current best results.
new permutation coding and equidistribution of set-valued statistics. a new coding for permutations is explicitly constructed and its association with the classical lehmer coding provides a bijection of the symmetric group onto itself serving to show that six bivariable set-valued statistics are equidistributed on that group. this extends a recent result due to cori valid for integer-valued statistics.
language operations with regular expressions of polynomial size. this work deals with questions regarding to what extent regularity-preserving language operations affect the descriptional complexity of regular expressions. some language operations are identified which are feasible for regular expressions in the sense that the result of the operation can be represented as a regular expression of size polynomial in that of the operands. we prove that taking language quotients, in particular the prefix and suffix closures, of a regular set can incur at most a quadratic blow-up on the required expression size. the circular shift operation can cause only a cubic increase in size and at least a quadratic bloat can be necessary in the worst case.
optimal strategies for maintaining a chain of relays between an explorer and a base camp. we envision a scenario with robots moving on a terrain represented by a plane. a mobile robot, called explorer is connected by a communication chain to a stationary base camp. the chain is expected to pass communication messages between the explorer and the base camp. it is composed of simple, mobile robots, called relays. we are investigating strategies for organizing and maintaining the chain, so that the number of relays employed is minimized and nevertheless the distance between neighbored relays in the chain remains bounded. we are looking for local and distributed strategies employed by restricted relays that have to base their decision (''where should i go?'') solely on the relative positions of its neighbors in the chain. we present the manhattan-hopper and the hopper strategy which improve the performance of all known solutions to this problem significantly. they are the first such strategies that are optimal in this setting, i.e., that allow the explorer to move with constant speed, independent of the length of the chain, and keep this length minimum up to a constant factor.
regulated nondeterminism in pushdown automata. a generalization of pushdown automata towards regulated nondeterminism is studied. the nondeterminism is governed in such a way that the decision, whether or not a nondeterministic rule is applied, depends on the whole content of the stack. more precisely, the content of the stack is considered as a word over the stack alphabet, and the pushdown automaton is allowed to act nondeterministically, if this word belongs to some given set r of control words. otherwise its behavior is deterministic. it turns out that non-context-free languages can be accepted if r is a context-free and non-regular language. on the other hand, if the control sets r are regular languages, then the resulting devices are not more powerful than nondeterministic pushdown automata. this raises the natural question of the relations between the structure and complexity of regular sets r on one hand and the computational capacity of the corresponding r-pda on the other hand. the main result of the paper shows that an infinite proper hierarchy of regular control sets leads to an infinite proper hierarchy of the corresponding language classes. additionally, closure properties and decision problems of these language classes are investigated.
adaptive routing with stale information. we investigate the behaviour of load-adaptive rerouting policies in the wardrop model where decisions must be made on the basis of stale information. in this model, each one of an infinite number of agents controls an infinitesimal amount of flow, thus contributing to a network flow which induces latency. in our dynamic extension of this model, agents are activated in a concurrent and asynchronous fashion and may reroute their flow with the aim of reducing their sustained latency. it is a well-known problem that in settings where latency information is not always up-to-date, such behaviour may lead to oscillation effects which seriously harm network performance. two quantities determine the difficulty of avoiding oscillation: the steepness of the latency functions and the maximum possible age of the information t. in this work we ask for conditions that the rerouting policies must adhere to in order to converge to an equilibrium despite the information being stale. we consider simple policies which sample another path in a first step and then migrate from the current path to the new one with a probability that is a function of the anticipated latency gain. in fact we can show that our class of policies guarantees convergence if the latter migration probability function satisfies a certain smoothness condition that resembles lipschitz continuity. it turns out that for smooth adaptation policies where the migration probability is chosen small enough relative to the inverse of the steepness of the latency functions and t, the population actually converges to an equilibrium. in addition, we analyse the speed of convergence towards approximate equilibria of two specific variants of smooth adaptive routing policies, e.g., for a replication policy adopted from evolutionary game theory.
causal message sequence charts. scenario languages based on message sequence charts (mscs) have been widely studied in the last decade. the high expressive power of mscs renders many basic problems concerning these languages undecidable. however, several of these problems are decidable for languages that possess a behavioral property called ''existentially bounded''. unfortunately, collections of scenarios outside this class are frequently exhibited by systems such as sliding window protocols. we propose here an extension of mscs called causal message sequence charts and a natural mechanism for defining languages of causal mscs called causal hmscs (cahmscs). these languages preserve decidable properties without requiring existential bounds. further, they can model collections of scenarios generated by sliding window protocols. we establish here the basic theory of cahmscs as well as the expressive power and complexity of decision procedures for various subclasses of cahmscs. we also illustrate the modeling power of our formalism with the help of a realistic example based on the tcp sliding window feature.
on the uniqueness of shuffle on words and finite languages. we investigate a special variant of the shuffle decomposition problem for regular languages; namely, when the given regular language is the shuffle of finite languages. the shuffle decomposition into finite languages is, in general, not unique. that is, there are l"1,l"2,l"3,l"4 with but {l"1,l"2}
stochastic biological modelling in the presence of multiple compartments. the application of concurrent calculi to the formalisation of biological systems constitutes a promising approach to the analysis of biological phenomena in silico. the peculiar nature of such systems inspired the introduction of specific features in biologically-oriented calculi, such as compartments to model more faithfully their highly organised structure. in this paper we present s@p@, a conservative extension of the stochastic @p-calculus which allows an intuitive and concise formalisation of multi-compartment systems with dynamic structure, despite retaining the simplicity of the original @p-calculus. the possibility to encode into s@p@ several bio-inspired, compartmentalised languages demonstrates its expressive power and flexibility. the calculus is accompanied by an extended version of gillespie's stochastic simulation algorithm, able to handle multiple compartments with varying volumes. an enhanced formalisation of the algorithm is also presented, in order to provide efficient simulation in the presence of a high number of compartments and reactions.
a new characteristic property of rich words. originally introduced and studied by the third and fourth authors together with j. justin and s. widmer (2008), rich words constitute a new class of finite and infinite words characterized by containing the maximal number of distinct palindromes. several characterizations of rich words have already been established. a particularly nice characteristic property is that all 'complete returns' to palindromes are palindromes. in this note, we prove that rich words are also characterized by the property that each factor is uniquely determined by its longest palindromic prefix and its longest palindromic suffix.
compressed string-matching in standard sturmian words. we present a simple algorithm which for an explicitly given input string pat (a pattern) and a standard sturmian word x described by the recurrences of size n computes, in time o(|pat|+n), the set of all occurrences of pat in x as a single arithmetic progression (modulo the length of x). the algorithm can be extended to the case when some letters of the pattern are replaced by a don't care symbol. in this case the set of all occurrences does not need to be a single arithmetic progression and our algorithm produces linearly many (with respect to the size of pat) arithmetic progressions. it is an example of fast computations for the input given in a compressed form. in our special case the length of the standard sturmian word x is usually exponential with respect to the size of the input.
dynamic matrix rank. we consider maintaining information about the rank of a matrix under changes of the entries. for nxn matrices, we show an upper bound of o(n^1^.^5^7^5) arithmetic operations and a lower bound of @w(n) arithmetic operations per element change. the upper bound is valid when changing up to o(n^0^.^5^7^5) entries in a single column of the matrix. we also give an algorithm that maintains the rank using o(n^2) arithmetic operations per rank one update. these bounds appear to be the first nontrivial bounds for the problem. the upper bounds are valid for arbitrary fields, whereas the lower bound is valid for algebraically closed fields. the upper bound for element updates uses fast rectangular matrix multiplication, and the lower bound involves further development of an earlier technique for proving lower bounds for dynamic computation of rational functions.
probabilistic and nondeterministic aspects of anonymity. the concept of anonymity comes into play in a wide range of situations, varying from voting and anonymous donations to postings on bulletin boards and sending emails. the protocols for ensuring anonymity often use random mechanisms which can be described probabilistically, while the agents' behavior may be totally unpredictable, irregular, and hence expressible only nondeterministically. formal definitions of the concept of anonymity have been investigated in the past either in a totally nondeterministic framework, or in a purely probabilistic one. in this paper, we investigate a notion of anonymity which combines both probability and nondeterminism, and which is suitable for describing the most general situation in which the protocol and the users can have both probabilistic and nondeterministic behavior. we also investigate the properties of the definition for the particular cases of purely nondeterministic users and purely probabilistic users. we formulate the notions of anonymity in terms of probabilistic automata, and we describe protocols and users as processes in the probabilistic @p-calculus, whose semantics is again based on probabilistic automata. throughout the paper, we illustrate our ideas by using the example of the dining cryptographers.
conservation of some dynamical properties for operations on cellular automata. we consider the family of all the cellular automata (ca) sharing the same local rule but having different memories. this family contains also all ca with memory m@?0 (one-sided ca) which can act both on a^z and on a^n. we study several set theoretical and topological properties for these classes. in particular, we investigate whether the properties of a given ca are preserved when considering the ca obtained by changing the memory of the original one (shifting operation). furthermore, we focus our attention on the one-sided ca acting on a^z, starting from the one-sided ca acting on a^n and having the same local rule (lifting operation). as a particular consequence of these investigations, we prove that the long-standing conjecture [surjectivity @? dense periodic orbits (dpo)] can be restated in several different (but equivalent) ways. furthermore, we give some results on properties conserved under the iteration of the ca global map.
relation between powers of factors and the recurrence function characterizing sturmian words. in this paper we use the relation of the index of an infinite aperiodic word and its recurrence function to give another characterization of sturmian words. as a by-product, we give a new proof of the theorem describing the index of a sturmian word in terms of the continued fraction expansion of its slope. this theorem was independently proved in [a. carpi, a. de luca, special factors, periodicity, and an application to sturmian words, acta inform. 36 (2000) 983-1006] and [d. damanik, d. lenz, the index of sturmian sequences, european j. combin. 23 (2002) 23-29].
backward and forward bisimulation minimization of tree automata. we improve on an existing [p.a. abdulla, j. hogberg, l. kaati, bisimulation minimization of tree automata, international journal of foundations of computer science 18(4) (2007) 699-713] bisimulation minimization algorithm for finite-state tree automata by introducing backward and forward bisimulation and developing minimization algorithms for them. minimization via forward bisimulation is also effective on deterministic tree automata, faster than the previous algorithm, and yields the minimal equivalent deterministic tree automaton. minimization via backward bisimulation generalizes the previous algorithm and can yield smaller automata but is just as fast. we demonstrate implementations of these algorithms on a typical task in natural language processing.
some remarks about stabilizers. we continue our study of stabilizers of infinite words over finite alphabets, begun in [d. krieger, on stabilizers of infinite words, theoret. comput. sci. 400 (2008), 169-181]. let w be an aperiodic infinite word over a finite alphabet, and let stab(w) be its stabilizer. we show that stab(w) can be partitioned into the monoid of morphisms that stabilize w by finite fixed points and the ideal of morphisms that stabilize w by iteration. we also settle a conjecture given in the paper mentioned above, by showing that in some cases stab(w) is infinitely generated. if the aforementioned ideal is nonempty, then it contains either polynomially growing morphisms or exponentially growing morphisms, but not both. moreover, in the polynomial case, the degree of the polynomial is fixed. we also show how to compute the polynomial degree from the dependency graph of a polynomially growing morphism.
reconstruction of graphs based on random walks. the analysis of complex networks is of major interest in various fields of science. in many applications we face the challenge that the exact topology of a network is unknown but we are instead given information about distances within this network. the theoretical approaches to this problem have so far been focusing on the reconstruction of graphs from shortest path distance matrices. often, however, movements in networks do not follow shortest paths but occur in a random fashion. in these cases an appropriate distance measure can be defined as the mean length of a random walk between two nodes - a quantity known as the mean first hitting time. in this contribution we investigate whether a graph can be reconstructed from its mean first hitting time matrix and put forward an algorithm for solving this problem. a heuristic method to reduce the computational effort is described and analyzed. in the case of trees we can even give an algorithm for reconstructing graphs from incomplete random walk distance matrices.
bio-pepa: a framework for the modelling and analysis of biological systems. in this work we present bio-pepa, a process algebra for the modelling and the analysis of biochemical networks. it is a modification of pepa, originally defined for the performance analysis of computer systems, in order to handle some features of biological models, such as stoichiometry and the use of general kinetic laws. bio-pepa may be seen as an intermediate, formal, compositional representation of biological systems, on which different kinds of analyses can be carried out. bio-pepa is enriched with some notions of equivalence. specifically, the isomorphism and strong bisimulation for pepa have been considered and extended to our language. finally, we show the translation of a biological model into the new language and we report some analysis results.
hardness and approximation of traffic grooming. traffic grooming is a central problem in optical networks. it refers to packing low rate signals into higher speed streams, in order to improve bandwidth utilization and reduce network cost. in wdm networks, the most accepted criterion is to minimize the number of electronic terminations, namely the number of sonet add-drop multiplexers (adms). in this article we focus on ring and path topologies. on the one hand, we provide an inapproximability result for traffic grooming for fixed values of the grooming factor g, answering affirmatively the conjecture of chow and lin [t. chow, p. lin, the ring grooming problem, networks 44 (2004), 194-202]. more precisely, we prove that ring traffic grooming for fixed g>=1 and path traffic grooming for fixed g>=2 are apx-complete. that is, they do not accept a ptas unless p=np. both results rely on the fact that finding the maximum number of edge-disjoint triangles in a tripartite graph (and more generally cycles of length 2g+1 in a (2g+1)-partite graph of girth 2g+1) is apx-complete. on the other hand, we provide a polynomial-time approximation algorithm for ring and path traffic grooming, based on a greedy cover algorithm, with an approximation ratio independent of g. namely, the approximation guarantee is o(n^1^/^3log^2n) for any g>=1, n being the size of the network. this is useful in practical applications, since in backbone networks the grooming factor is usually greater than the network size. finally, we improve this approximation ratio under some extra assumptions about the request graph.
an intermediate language for the stochastic simulation of biological systems. we introduce stochastic string multiset rewriting (ssmsr), and propose this formalism as an intermediate language for the simulation of biomolecular systems. higher level formalisms for biological systems description can be translated into ssmsr, and the features of ssmsr allow the development of efficient simulators. in this paper, we show the encoding into ssmsr of two formalisms for the description of biological systems, namely stochastic cls and the stochastic @p-calculus. we prove soundness and completeness of both the encodings.
estimation of state complexity of combined operations. it appears that the state complexity of each combined operation has its own special features. thus, it is important and practical to obtain good estimates for some commonly used general cases. in this paper, we consider the state complexity of combined boolean operations and give an exact bound for all of them in the case when the alphabet is not fixed. moreover, we show that for any fixed alphabet, this bound can be reached in infinitely many cases. we also consider the state complexity of multiple catenations. the state complexities are obtained in the cases of the catenations of three and four languages. an estimate for the catenation of an arbitrary number of languages is given, which is very close to the state complexities in the three and four languages cases.
on the complexity of constrained nash equilibria in graphical games. a widely accepted rational behavior for non-cooperative players is based on the notion of nash equilibrium. although the existence of a nash equilibrium is guaranteed in the mixed framework (i.e., when players select their actions in a randomized manner) in many real-world applications the existence of ''any'' equilibrium is not enough. rather, it is often desirable to single out equilibria satisfying some additional requirements (in order, for instance, to guarantee a minimum payoff to certain players), which we call constrained nash equilibria. in this paper, a formal framework for specifying these kinds of requirement is introduced and investigated in the context of graphical games, where a player p may directly be interested in some of the other players only, called the neighbors of p. this setting is very useful for modeling large population games, where typically each player does not directly depend on all the players, and representing her utility function extensively is either inconvenient or infeasible. based on this framework, the complexity of deciding the existence and of computing constrained equilibria is then investigated, in the light of evidencing how the intrinsic difficulty of these tasks is affected by the requirements prescribed at the equilibrium and by the structure of players' interactions. the analysis is carried out for the setting of mixed strategies as well as for the setting of pure strategies, i.e., when players are forced to deterministically choose the action to perform. in particular, for this latter case, restrictions on players' interactions and on constraints are identified, that make the computation of nash equilibria an easy problem, for which polynomial and highly-parallelizable algorithms are presented.
an (18/11)n upper bound for sorting by prefix reversals. the pancake problem asks for the minimum number of prefix reversals sufficient for sorting any permutation of length n. we improve the upper bound for the pancake problem to (18/11)n+o(1)~(1.6363)n.
on algorithmic analysis of transcriptional regulation by ltl model checking. studies of cells in silico can greatly reduce the need for expensive and prolonged laboratory experimentation. the use of model checking for the analysis of biological networks has attracted much attention recently. the practical limitations are still the size of the model, and the time needed to generate the state space. this paper is focused on the model checking approach for analysis of piecewise-linear deterministic models of genetic regulatory networks. firstly, the qualitative simulation algorithm of de jong et al. that builds the heart of genetic network analyzer (gna) is revisited and its time complexity is studied in detail. secondly, a novel algorithm that reduces the state space generation time is introduced. the new algorithm is developed as an abstraction of the original gna algorithm. finally, a fragment of linear time temporal logic for which the provided abstraction is conservative is identified. efficiency of the new algorithm when implemented in the parallel model checking environment is demonstrated on a set of experiments performed on randomly modified biological models. in general, the achieved results bring a new insight into the field of qualitative simulation emerging in the context of systems biology.
integration of a prediction mechanism with a sensor model: an anticipatory bayes filter. in the task of robot localization, bayes filters use two processes: the prediction step and the measurement-update step. briefly, the state transition model is responsible for prediction, and the sensor model is responsible for measurement updates. this paper presents a new approach to the sensor model, called the predictive sensor model, which utilizes a prediction mechanism to improve the efficiency of measurement updates in bayes filters. by adding sensorial anticipation, we extend the original bayes filter to an anticipatory bayes filter. we also propose an entropy-based place-segmentation method for automatic segmentation of sequentially collected visionsensor data. our place segmentation technique is most useful for node clustering in the process of constructing topological maps. our work was verified by experiments using observed data.
energetically consistent collisions in simulation of multibody systems. this paper presents a methodology for treating energy consistency when considering multiple simultaneous impacts and contacts with friction in the simulation of systems of multiple interconnected bodies. hard impact and contact is considered where deformation of the impacting surfaces is negligible. the proposed approach uses a discrete algebraic model of impact in conjunction with moment and tangential coefficients of restitution (cors) to develop a general impact law for determining post-impact velocities. this process depends on impulse-momentum theory, complementarity conditions, a principle of maximum dissipation, and the determination of contact forces. the proposed methodology also uses an energy-modifying cor to directly control the system's energy. the approach is illustrated on a bicycle-like structure.
a global self-localization technique utilizing local anomalies of the ambient magnetic field. magnetic field fluctuations in modern buildings arise from both natural and man-made sources, such as steel and reinforced concrete structures, electric power systems, electric and electronic appliances, and industrial devices. if the anomalies of the magnetic field inside the building are nearly static and they have sufficient local variability, they provide a unique magnetic fingerprint that can be utilized in global self-localization. in this article, a monte carlo localization (mcl) technique based on this hypothesis is proposed. the feasibility of the technique is demonstrated by presenting a series of global localization experiments conducted in four arbitrarily selected buildings, including a hospital. the experiment setup consists of a mobile robot instrumented with a 3-axis magnetometer and a computer. in addition, successful human self-localization experiments were conducted by using a wireless wearable magnetometer. the reported experiments suggest that the ambient magnetic field may remain sufficiently stable for longer periods of time, giving support for self-localization techniques utilizing the local deviations of the field.
a study of cooperative control of self-assembling robots in space with experimental validation. modular self-assembling on-orbit robotic and satellite systems can be more reliable, have lower launch costs, and be more easily repaired and refueled. however, when individual modules assemble, many challenges and opportunities make the control of the assembled system complex. these issues include changes in inertial properties, and redundancy of actuators and sensors. optimal control methods may be used to coordinate the control of the modules after assembly, insure good performance, and best utilize the combined resources of the assembly of modules. simulation and experimental results compare this cooperative algorithm's performance to that of an approach in which the control of the individual modules is not coordinated. cooperative optimal control methods prove well-suited for controlling redundant, modular space systems.
energy-efficient target tracking with a sensorless robot and a network of unreliable one-bit proximity sensors. existing target tracking algorithms require the tracker to have access to information-rich sensors, and may have difficulty recovering when the target is out of the tracker's sensing range. in this paper, we present a target tracking algorithm that combines an extremely simple mobile robot with a networked collection of wireless sensor nodes, each of which is equipped with an unreliable, limited-range, boolean sensor for detecting the target. the tracker maintains close proximity to the target using only information sensed by the network, and can effectively recover from temporarily losing track of the target. our approach combines a protocol for the sensor network that conserves energy by dynamically adjusting the time-to-live for packets it transmits with a reactive strategy for the tracker based on its information state. we present an implementation along with experimental results. our experimental results show that our system achieves both good tracking precision and low energy consumption.
control of a four-steering, planar five-bar linkage-walker. this paper introduces and describes a new type of wheeled locomotor referred to as a "four-steering, planar fivebar linkage-walker." this wheeled locomotor is a nonholonomic mechanical system that consists of five links, five rotational joints, and four steering systems. the five links coupled by the five joints form a closed-loop. the four steering systems are attached to four of the five links. each of the four links has its own steering system at its middle point. the wheeled locomotor transforms the rotations of the five joints into movement by using the four steering systems. this means that the wheeled locomotor performs undulatory locomotion in which it transforms a change in its internal shape into the generation of its net displacement. in addition, a virtual joint is added to one of the ends of the first link. the virtual joint couples the first link and a virtual link which has a virtual axle at its middle point and a virtual steering system at its end. it is proven that, by assuming the presence of such virtual mechanical elements, it is possible to convert the kinematic equation of the wheeled locomotor into a five-chain, single-generator chained form in differential geometry. based on chained form, a path-following feedback control method that enables the wheeled locomotor to follow a straight line is derived. the validity of the mechanical design of the wheeled locomotor, the transformation of its kinematic equation into chained form, and the path-following feedback control method is verified by computer simulation.
fat-based adaptive visual servoing for robots with time varying uncertainties. most present adaptive control strategies for visual servoing of robots have assumed that the unknown camera parameters, kinematics and dynamics of visual servoing system should be linearly parameterized in the regressor matrix form. this is because the limitation of the traditional adaptive design in which the uncertainties should be time-invariant such that all time varying terms in the visual servoing system are collected inside the regressor matrix. however, derivation of the regressor matrix is tedious. in this paper, a fat (function approximation technique) based adaptive controller is designed for visual servo robots without the need for the regressor matrix. a lyapunov-like analysis is used to justify the closed-loop stability and boundedness of internal signals. moreover, the upper bounds of tracking errors in the transient state are also derived. computer simulation results are presented to demonstrate the usefulness of the proposed scheme.
model-based and model-free reinforcement learning for visual servoing. to address the difficulty of designing a controller for complex visual-servoing tasks, two learning-based uncalibrated approaches are introduced. the first method starts by building an estimated model for the visual-motor forward kinematic of the vision-robot system by a locally linear regression method. afterwards, it uses a reinforcement learning method named regularized fitted q-iteration to find a controller (i.e. policy) for the system (model-based rl). the second method directly uses samples coming from the robot without building any intermediate model (model-free rl). the simulation results show that both methods perform comparably well despite not having any a priori knowledge about the robot.
effect of time delay on telesurgical performance. in the area of surgical robotics no standard means of performance evaluation has been established. thousands of surgeons have gone through the sages fls program, and the psychomotor skill portion of the program is considered the gold standard in laparoscopic skills evaluation. this research describes the use of the fls block transfer task to evaluate the performance of both surgeons and non-surgeons teleoperating under different time delay conditions on the university of washington raven surgical robot. time delays of 0ms, 250ms, and 500ms were used and a statistically significant difference in mean block transfer time as well as mean tool tip path length were shown. for this task no significant difference was shown between the surgeon and non-surgeon groups. clearly surgeon input and feedback is key to surgical robotic system development, but this result implies that nonsurgeon subjects can be tested for simple usability evaluations.
modeling and optimization of quadriglide, a schönflies motion generator module for 5-axis milling machine-tools. this paper introduces the quadriglide, a schönflies motion generator module for 5-axis machine-tools. the targeted application is high speed milling of long aeronautic parts, in particular thin ones, instead of toxic and dangerous chemical milling. quadriglide is described and its kinematics derived. then, a preliminary optimization is done to achieve the best actuation stiffness in a prescribed workspace with large tilting angles (θ = ±π/4). workspace plots of the optimized module are shown at the end of the paper.
global transparency analysis of the lawrence teleoperator architecture. despite the frequent use of the lawrence architecture since its introduction in the early 90's, its global transparency characteristics have not yet been fully analyzed. that is the goal of this paper. we state and prove necessary and sufficient conditions for transparency, with special attention to the information sent across the communication layer. in particular, it is shown that transparency can be preserved even though one, and even two, communication channels are set to zero. the results may serve as a guideline for transparent teleoperator design.
synthesizing a desired trajectory and sensory feedback control laws for an origami-folding robot based on the statistical characteristics of direct teaching by a human. in this paper, a novel method to synthesize a desired trajectory and sensory feedback control laws for robots based on the statistical characteristics of direct teaching data by a human is proposed. this work was motivated by a poor performance of an origami-folding robot developed by the authors. since the robot simply replayed a given trajectory without sensory feedback control, it often failed in folding due to the fluctuation of origami paper behaviors. to model the statistical characteristics of the demonstrated motions by a human, a hidden markov model (hmm) is employed. a nominal desired trajectory is obtained by temporally normalizing and spatially averaging the demonstrated motions in a statistical manner. sensory feedback control laws are then synthesized based on the output probability density function parameters of the hmm. considering the velocity variance and the canonical correlation between velocity and force of the teaching data, important motion segments are extracted and the feedback control is applied only for those segments. the proposed method was applied to the origami-folding robot and experimental results showed that the success rate and the folding quality of "valley-fold" were improved. although the demonstrated task is very specific, the proposed method has generality to be applied to other tasks.
a visual odometry framework robust to motion blur. motion blur is a severe problem in images grabbed by legged robots and, in particular, by small humanoid robots. standard feature extraction and tracking approaches typically fail when applied to sequences of images strongly affected by motion blur. in this paper, we propose a new feature detection and tracking scheme that is robust even to non-uniform motion blur. furthermore, we developed a framework for visual odometry based on features extracted out of and matched in monocular image sequences. to reliably extract and track the features, we estimate the point spread function (psf) of the motion blur individually for image patches obtained via a clustering technique and only consider highly distinctive features during matching. we present experiments performed on standard datasets corrupted with motion blur and on images taken by a camera mounted on walking small humanoid robots to show the effectiveness of our approach. the experiments demonstrate that our technique is able to reliably extract and match features and that it is furthermore able to generate a correct visual odometry, even in presence of strong motion blur effects and without the aid of any inertial measurement sensor.
a model of muscle-tendon function in human walking. in this paper, we study the mechanical behavior of leg muscles and tendons during human walking in order to motivate the design of economical robotic legs. we hypothesize that quasi-passive, series-elastic clutch units spanning the knee joint in a musculoskeletal arrangement can capture the dominant mechanical behaviors of the human knee in level-ground walking. since the mechanical work done by the knee joint throughout a level-ground self-selected-speed walking cycle is negative, and since there is no element capable of dissipating mechanical energy in the musculoskeletal model, biarticular elements would necessarily need to transfer energy from the knee joint to hip and/or ankle joints. this mechanism would reduce the necessary actuator work and improve the mechanical economy of a human-like walking robot. as a preliminary evaluation of these hypotheses, we vary model parameters, or spring constants and clutch engagement times, using an optimization scheme that minimizes ankle and hip actuator positive work while still maintaining human-like knee mechanics. for model evaluation, kinetic and kinematic gait data were employed from one study participant walking across a level-ground surface at a self-selected gait speed. with this under-actuated leg model, we find good agreement between the model's quasi-passive knee torque and experimental knee values, suggesting that a knee actuator is not necessary for level-ground robotic ambulation at self-selected gait speeds.
novel design of a 3-axis optical fiber force sensor for applications in magnetic resonance environments. this paper describes a novel design of a 3-axis force sensor which can be applied in magnetic resonance (mr) workspaces such as that of a magnetic resonance imaging (mri) machine. the sensor operates based on an optical sensing principle to measure forces deforming a 3 degree-of-freedom (dof) flexible structure. by detecting minute deflection of such a structure using an optical sensing scheme, the magnitude and direction of an applied force can be determined. the sensor prototype described in this document demonstrates its capability of performing force measurement in both axial and radial directions with the calibrated working ranges of +/-3 n. because all the sensor's components are entirely fabricated from non-metallic and dielectric materials, the sensor is considered suitable for applications in mr environments.
extended nicosia-tomei observer-based tracking control of robot manipulators. this paper presents an observer-based control of robot manipulators for velocity estimation and trajectory tracking. the proposed scheme does not require the velocity feedback because velocity measurements may not be available due to cost and weight. we introduce parameters involving the tracking and estimation errors and their derivatives into the observer-controller. exploiting the structural properties, we propose the new combined form of observer-controller to ensure the closed loop stability of the tracking and estimation. moreover, we show that the proposed controller-observer scheme achieves semi-globally exponential stability results for tracking errors and estimation errors. the proposed observer-controller facilitates the stability analysis and explicitly extends nicosia-tomei observer-based tracking control. to validate the proposed scheme, we conduct numerical simulation of a two-link robot. the simulation results clearly indicate that the proposed scheme improves the error convergence for both trajectory tracking and velocity estimation.
real-time ultrasonic distance measurements for autonomous mobile robots using cross correlation by single-bit signal processing. distance measurement using an ultrasonic wave is suitable for environment recognition in autonomous mobile robots. ultrasonic distance measurement with the pulse-echo method is based on determining the time-of-flight (tof) of the reflected echoes. the pulse-echo method with pulse compression, the cross-correlation method, can improve the distance resolution and the signal-to-noise ratio (snr) of the reflected echo. however, cross correlation of the cross-correlation method requires the high-cost digital signal processing. a sensor signal processing method of cross correlation using a delta-sigma modulated single-bit digital signal has been proposed. cross correlation by single-bit signal processing reduces the calculation cost of cross correlation. furthermore, cross correlation by single-bit signal processing improves the time resolution of digital signal processing. in this paper, the distance resolution of cross correlation by single-bit signal processing is evaluated by computer simulations and experiments of ultrasonic distance measurement. distance measurement from the high-time-resolution cross-correlation function obtained by single-bit signal processing realized high distance resolution from experimental results, despite the low calculation costs.
adding millimeter-sized, rapidly prototyped robotic structures to microfluidic lab-on-a-chip devices. this paper describes a rapid prototyping method to add robotic functionality to microfluidic devices using existing equipment, materials, and methods already employed in photolithography. details on the fabrication as well as basic design and analyses methods are given. these techniques are then employed to fabricate an example structure that is subsequently integrated with a microfluidic channel. the eventual purpose of this example structure would be to serve as an interface between a microfluidic device and its environment, using a brush-like structure to sweep cells into the channel, which could then be delivered to another microfluidic system for analyses of the cells. the resulting brush-like structure fits within a 6mm × 4mm × 2mm volume and can be further miniaturized. the alteration of compressed air and vacuum modulated by pneumatic solenoid valves is used to push and pull a plunger/rod system that actuates the device. the delivery of the pressurized air and vacuum is accomplished through flexible 500µm-diameter tubing to the plunger/rod system but future work would involve completely containing the actuation on a chip-size device
3 axial force sensor for a semi-autonomous snake robot. now that mobile robots are getting tested more and more in challenging areas, difficulties in control, particularly when the robot cannot be seen, have appeared. in this research a mobile snake robot with actuated wheels is given the ability to sense its surroundings through its wheels by 3dof force sensors, so that semi-autonomous control can be realized. this will simplify necessary operator commands and improve situation awareness through information feedback. even with the many limitations of practical robot design, such as unwanted flexibilities, and measuring while actuating the wheels, the sensor's errors are confirmed to vary between just 1% and 3%. moreover, sensitivity is equal over the wheels, only a 3s calibration at startup is needed, and the sensor is shown to be resistant to aging and temperature change. the sensor is implemented directly into a new snake robot, one sensor in each segment. its central control will adjust the snake body according to the surroundings while automatically avoiding obstacles and crossing gaps.
analytic error variance predictions for planar vehicles. path planning algorithms that incorporate risk and uncertainty need to be able to predict the evolution of path-following error statistics for each candidate plan. we present an analytic method to predict the evolving error statistics of a holonomic vehicle following a reference trajectory in a planar environment. this method is faster than integrating the plant through time or performing a monte carlo simulation. it can be applied to systems with external gaussian disturbances, and it can be extended to handle plant uncertainty through numerical quadrature techniques.
range-only slam with a mobile robot and a wireless sensor networks. this paper presents the localization of a mobile robot while simultaneously mapping the position of the nodes of a wireless sensor network using only range measurements. the robot can estimate the distance to nearby nodes of the wireless sensor network by measuring the received signal strength indicator (rssi) of the received radio messages. the rssi measure is very noisy, especially in an indoor environment due to interference and reflections of the radio signals. we adopted an extended kalman filter slam algorithm to integrate rssi measurements from the different nodes over time, while the robot moves in the environment. a simple pre-processing filter helps in reducing the rssi variations due to interference and reflections. successful experiments are reported in which an average localization error less than 1 m is obtained when the slam algorithm has no a priori knowledge on the wireless node positions, while a localization error less than 0.5 m can be achieved when the position of the node is initialized close to the their actual position. these results are obtained using a generic path loss model for the trasmission channel. moreover, no internode communication is necessary in the wsn. this can save energy and enables to apply the proposed system also to fully disconnected networks.
piezoelectrically driven silicon microgrippers integrated with sidewall piezoresistive sensor. this paper presents the design, fabrication, and application of an piezoelectrically driven microgripper integrated sidewall piezoresistive force sensor for measuring the gripping force. surface and bulk micromachining technology is employed to fabricate end-effectors and sensor of the microgripper from a single crystal silicon wafer. vertical sidewall surface piezoresistor etching technique is used to form the side direction sensors. the end-effectors of the gripper are four-bar structures. two fixed cantilever beams integrated with piezoresistive sensor are designed to sense the gripping force, and a piezoelectrically driven microactuator is designed to provide the force to operate the other two movable bars. the piezoelectrically driver adhered with the silicon end-effectors generates a linear horizontal motion 9µm, which is amplified to 30µm at the bar tip of the microgripper. then the range of the operation is 25µm-140µm. testing results verify that the vertical sidewall surface piezoresistor etching technique is effective. the sensitivity of the piezoresistive sensors is better than 72v/n, and the resolution is better than 3µn.
radiation pattern correlation for mobile robot localization in low power wireless networks. we present a new method for localization using received signal strength indicator (rssi) in ordinary wireless communication networks such as specified by ieee 802.15.4. the method exploits the anisotropy of the antenna gain to determine the bearing of the robot relative to reference radio nodes. this method is not only more precise than the mapping of the rssi to distance only, it also allows to estimate the orientation of the robot and to monitor the integrity of the measurement. the integrity measure is also incorporated into the rssi to distance mapping and a thorough error analysis is presented. the paper describes the localization concept and presents experimental results for mobile robot localization in an outdoor environment. the achieved accuracy is significantly increased compared to previously developed rssi based localization methods.
overcoming adhesion forces: active release of micro objects in micromanipulation. due to force scaling laws, rapid, accurate release of micro objects has been a long-standing challenge for microrobotic manipulation. this paper presents an active release technique that for the first time, achieves 100% repeatability and a release accuracy of 0.70±0.46µm, experimentally quantified through the manipulation of 10µm glass spheres under an optical microscope. using a new mems (microelectromechanical systems) microgripper, this technique employs a controllable plunging mechanism for the micro object to gain sufficient momentum to overcome adhesion forces. experimental results also confirmed that this technique is not substrate dependent. theoretical analyses were conducted to understand the release principle. based on this preliminary study, the technique may also prove to be an effective solution to active release of submicron objects in robotic pick-place.
human daily activity recognition in robot-assisted living using multi-sensor fusion. in this paper, we propose a human daily activity recognition method by fusing the data from two wearable inertial sensors attached on one foot and the waist of the subject, respectively. we developed a multi-sensor fusion scheme for activity recognition. first, data from these two sensors are fused for coarse-grained classification in order to determine the type of the activity: zero displacement activity, transitional activity, and strong displacement activity. second, a fine-grained classification module based on heuristic discrimination or hidden markov models (hmms) is applied to further distinguish the activities. we conducted experiments using a prototype wearable sensor system and the obtained results prove the effectiveness and accuracy of our algorithm.
robust backstepping control of active vibration isolation using a stewart platform. this paper focuses on deriving a robust backstepping control approach to solve the active vibration isolation problem using a stewart platform. the dynamics of the stewart platform driven by the linear voice coil motors is developed with the newton-euler method. by fully considering the characteristics of vibration isolation, the properties of the dynamics of the stewart platform are applied to transform the coupled dynamics into six independent single-input single-output (siso) channels. furthermore, in the procedure of controller design, the influence factors of vibration isolation are taken into account, such as the parameter perturbation and the unmodeled dynamics, etc. meanwhile, high-gain design method is employed to deal with the problem introduced by input unmodeled dynamics of the system. it is demonstrated that a sufficiently small l2 gain from disturbance to output can be obtained in lyapunov synthesis. the simulation results show that the controller can effectively attenuate low frequency vibrations in six degrees of freedom (dofs) and a satisfactory vibration isolation performance can be achieved.
software framework for human neuromuscular behavior. in this paper we present our low-level software framework that allows human neuromuscular properties and behaviors to be programmed modularly onto biologically inspired prosthetic devices. specifically this software framework is used at the lowest level of the anatomically correct testbed (act) hand. it abstracts away from the robotic details and allows users including biologists to program individual muscle physiology, multiple muscle synergistic activities, neural commands, etc. independently. our system has been designed to be fault-tolerant with the idea of safe and continued operation of prostheses if a new prototype behavior were to perform incorrectly or outright fail. example coding of hills model is shown.
making networked robots connectivity-aware. maintaining the network connectivity in mobile multi-robot systems (mrss) is a key issue in many robotic applications. in our view, the solution to this problem consists of two main steps: (i) making robots aware of the network connectivity; and (ii), making use of this knowledge to plan robots tasks without compromising connectivity. in this paper, we view the ad-hoc network connectivity as an abstraction that is independent from application issues. we propose a new distributed algorithm executing on individual robots to build the connectivity-awareness. the correctness and theoretical analysis of the proposed algorithm are given. we also show how our solution allows checking network bi-connectivity more efficiently than existing work and can be used, for example, during distributed control motion.
anatomically correct testbed hand control: muscle and joint control strategies. human hands are capable of many dexterous grasping and manipulation tasks. to understand human levels of dexterity and to achieve it with robotic hands, we constructed an anatomically correct testbed (act) hand which allows for the investigation of the biomechanical features and neural control strategies of the human hand. this paper focuses on developing control strategies for the index finger motion of the act hand. a direct muscle position control and a force-optimized joint control are implemented as building blocks and tools for comparisons with future biological control approaches. we show how gaussian process regression techniques can be used to determine the relationships between the muscle and joint motions in both controllers. our experiments demonstrate that the direct muscle position controller allows for accurate and fast position tracking, while the force-optimized joint controller allows for exploitation of actuation redundancy in the finger critical for this redundant system. furthermore, a comparison between gaussian processes and least squares regression method shows that gaussian processes provide better parameter estimation and tracking performance. this first control investigation on the act hand opens doors to implement biological strategies observed in humans and achieve the ultimate human-level dexterity.
natural frequency based optimal design of a two-link flexible manipulator. modern industries, e.g., semiconductor packaging, imposes increasing stringent requirement on equipment with very high acceleration and high precision. traditionally, arm linkage and drive mechanism are first designed followed by control design. the integrated design method is proposed as a preferable technique of the traditional one. in this paper, a general framework of the integrated design method for a point-to-point control is presented. the dynamic model for a flexible planar two-link manipulator is derived by the finite element method. the pd control strategy is applied in the closed-loop system. the structural parameters and control parameters are optimized simultaneously by solving the integrated design problem. the differential evolution (de) technique, a global optimization technique, is used to solve the optimal design problem. a simulation shows the integrated design method gives improved system performance.
probabilistic search optimization and mission assignment for heterogeneous autonomous agents. this paper presents an algorithmic framework for conducting search and identification missions using multiple heterogeneous agents. dynamic objects of type "neutral" or "target" move through a discretized environment. probabilistic representation of the current level of situational awareness - knowledge or belief of object locations and identities - is updated with imperfect observations. optimization of search is formulated as a mixed-integer program to maximize the expected number of targets found and solved efficiently in a receding horizon approach. the search effort is conducted in tandem with object identification and target interception tasks, and a method for assignment of these missions among agents is developed. the proposed framework is demonstrated in simulation studies, and an implementation of its decision support capabilities in a recent field experiment is reported.
harnessing bacterial power in microscale actuation. this paper presents a systematic analysis of the motion of microscale structures actuated by flagellated bacteria. we perform the study both experimentally and theoretically. we use a blotting procedure to attach flagellated bacteria to a buoyancy-neutral plate called a microbarge. the motion of the plate depends on the distribution of the cells on the plate and the stimuli from the environment. we construct a stochastic mathematical model for the system, based on the assumption that the behavior of each bacterium is random and independent of that of its neighbors. the main finding of the paper is that the motion of the barge plus bacteria system is a function of a very small set of parameters. this reduced-dimensional model can be easily estimated using experimental data. we show that the simulation results obtained from the model show an excellent match with the experimentally-observed motion of the barge.
delayed-state information filter for cooperative decentralized tracking. this paper presents a decentralized data fusion approach to perform cooperative perception with data gathered from heterogeneous sensors, which can be static or carried by robots. particularly, a decentralized delayed-state extended information filter (ddseif) is described, where full state trajectories are considered to fuse the information. this permits to obtain an estimation equal to that obtained by a centralized system, and allows delays and latency in the communications. the sparseness of the information matrix maintains the communications overhead at a reasonable level. the method is applied to cooperative tracking and some results in disaster management scenarios are shown. in this kind of scenarios the target might move in both open field and indoor areas, so fusion of data provided by heterogeneous sensors is beneficial.
distributed sensor analysis for fault detection in tightly-coupled multi-robot team tasks. this paper presents a distributed version of our previous work, called safdetection, which is a sensor analysis-based fault detection approach that is used to monitor tightly-coupled multi-robot team tasks.while the centralized version of safdetection was shown to be successful, a shortcoming of the approach is that it does not scale well to large team sizes. the distributed safdetection approach addresses this problem by adapting and distributing the approach across team members. distributed safdetection has the same theoretic foundation as centralized safdetection, which maps selected robot sensor data to a robot state by using a clustering algorithm, and builds state transition diagrams to describe the normal behavior of the robot system. however, rather than processing multiple robots' sensor data centralized on a server, distributed safdetection performs feature selection and clustering on individual robots to build the normal behavior model of an individual robot and the entire robot team. fault detection is also accomplished in a distributed manner. we have implemented this distributed approach on a physical robot team and in simulation. this paper presents the results of these experiments, showing that distributed safdetection is an efficient approach to detect both local and interactive faults in tightly-coupled multi-robot team tasks. compared to the centralized version, this approach provides more scalability and reliability.
combining color-based invariant gradient detector with hog descriptors for robust image detection in scenes under cast shadows. in this work we present a robust detection method in outdoor scenes under cast shadows using color based invariant gradients in combination with hog local features. the method achieves good detection rates in urban scene classification and person detection outperforming traditional methods based on intensity gradient detectors which are sensible to illumination variations but not to cast shadows. the method uses color based invariant gradients that emphasize material changes and extract relevant and invariant features for detection while neglecting shadow contours. this method allows to train and detect objects and scenes independently of scene illumination, cast and self shadows. moreover, it allows to do training in one shot, that is, when the robot visits the scene for the first time.
generic slung load transportation system using small size helicopters. in this paper we present an overview of techniques and approaches used for a load transportation system based on small size unmanned helicopters. the focus is on the control approach and on the movement of the rope connecting helicopters and load. the proposed approach is based on two control loops: an outer loop to control the translation of each helicopter in compound and an inner loop to control the orientation of helicopters. the challenge here is that in both loops the dynamics of the whole system - all helicopters and load - should be accounted for. it is shown, that for designing the outer loop controller a complex model of the helicopters and load can be replaced by a simplified model based on interconnected mass points. for designing the inner loop controller, the complete dynamics of the whole system are considered. the usage of force sensors in the ropes is proposed in order to simplify the inner loop controller and to make it robust against variations of system parameters. the presented inner loop controller is independent of the number of coupled helicopters. the outer loop controller depends on the number of helicopters. the problem of oscillations in the flexible ropes due to external disturbancies (e.g. wind gusts) is discussed and a solution based on load state observer is presented. the performance of the presented system was verified in simulations and in real flight experiments with one and three helicopters transporting the load. the worldwide first demonstration of a slung load transportation using three helicopters was performed in december 2007.
regrasp planning for pivoting manipulation by a humanoid robot. a method of regrasp planning for humanoid robot manipulation is proposed. we adopt pivoting manipulation for the humanoid robot to move a bulky object without lifting in a stable and dexterous manner. in order to carry the object to a desired place, the humanoid should sometimes move through narrow areas surrounded by obstacles. we propose a roadmap multiplexing planning to allow the robot to leave the object near narrow places and to regrasp it from another position to continue carrying. we utilize visibility probabilistic roadmap (prm) method as a preprocessing to capture the critical configurations for regrasping. then a diffusion method is employed to plan the overall manipulation path including regrasping. the proposed method is verified through planning simulation including whole-body motions.
sbc for motion assist using neural oscillator. in this paper we propose a framework for synchronization based control (sbc) using neural oscillators for motion assist. a neural oscillator is used to accomplish synchronization and entrainment between periodic motions by the human and robot. the mutual joint torque between the human and robot is used as an external input signal for the neural oscillator, which generates the desired trajectory of a robot joint angle, so that the robot motion synchronizes with the external mutual joint torque. the validity and feasibility of the proposed method is examined from three points of view. the first is whether synchronization of action between human and robot can be realized. the second is whether the assist effect can be obtained, and the third is whether the proposed method has an acceptable level of usability for the user. we explored those three points of view by conducting computer simulations on a human-motion assist system and experiments with a joint torque sensing robot suit.
performance limitation analysis in visual servo systems: bounding the location error introduced by image points matching. visual servoing consists of positioning a robot end-effector based on the matching of some object features in the image. however, due to the presence of image noise, this matching can never be ensured, hence introducing an error on the final location of the robot. this paper addresses the problem of estimating the worst-case location error introduced by image points matching. in particular, we propose some strategies for computing upper bounds and lower bounds of such an error according to several possible measures for certain image noise intensity and camera-object configuration. these bounds provide an admissible region of the sought worst-case location error, and hence allow one to establish performance limitation of visual servo systems. some examples are reported to illustrate the proposed strategies and their results.
an explorative study of visual servo control with insect-inspired reichardt-model. in this paper, an insect-inspired motion detector (reichardt-model) is applied to visual servo control to ensure the stability of the system with high gain and time delay in its feedback. a reichardt-based control scheme is compared with a conventional visual servoing approach. as a consequence of the specific velocity dependence of the reichardt-model, the stability margin of the visual servo control is increased and high overall gains, thus, better performance are achievable. the response of the reichardt-model in the experiment and the control performance of velocity control approach with the reichardt-model in the closed loop are investigated. the velocity control model is tested on a 1-dof linear motor module with different feedback gain and different time delay in the loop. the results of simulation and realtime experiments demonstrate the stabilizing character of the reichardt-based approach.
dynamic modeling of mckibben pneumatic artificial muscles for antagonistic actuation. this paper presents the dynamic modeling of mckibben pneumatic artificial muscles. the air flow model of a valve orifice and the air volume model of a pneumatic muscle are incorporated into the proposed dynamic model to estimate precisely the pressure variance of a pneumatic muscle when mckibben muscles are in inflating and deflating. coefficient parameters of the proposed model are determined optimally through well-coordinated experiments. frequency response test is performed on an antagonistic structure consisting of mckibben muscles manufactured in our laboratory and a pneumatic circuit with fast pneumatic control valves. comparing with experimental results, simulations revealed that the proposed model gave good performance in estimating motions of the antagonistic actuation as well as the pressure variance of the mckibben muscles.
toward ischemia dynamics based medical diagnosis. for an arbitrary force impartment on tissue, the tissue color changes from red to white due to the decrease of arterial blood. the dynamics leading to (or recovering from) ischemia is a good index for evaluating the vitality of tissue. this paper discusses the ischemia dynamics by using a newly developed active sensing system composed of an air jet nozzle for imparting an air pulse to tissue and a high-speed camera for capturing the change of color of tissue with respect to time. through experiments, we found that the ischemia dynamics is particularly characterized by the recovery phase where the time constant changes depending upon the local physical condition of tissue. we also showed a map on color changing rate conveniently utilized for quickly understanding the location of ischemia area which is a candidate replaced by regenerated tissue.
development of insect thorax based flapping mechanism. design of a flapping mechanism for flapping wing micro air vehicles (fwmav) is presented based on a mathematical model of insect thorax. this model also includes an aerodynamic model of flapping wings. using experiments on dynamically scaled wings and numerical optimization, the mechanism is tuned for peak aerodynamic performance. the thorax model is used to understand the mechanics of the biological flapping mechanism and reveals the significance of rotational stiffness and inertia distribution in flapping wings. experiments conducted on the actual thorax based mechanism validate theoretical findings and also show significant lift generation capability.
effects of non-negligible cable mass on the static behavior of large workspace cable-driven parallel mechanisms. cable-driven robots are currently extensively studied. generally, for this type of manipulators, cables are considered to be massless and inextensible. but for large working volume applications, their mass cannot be neglected. based on a well-known model which describes the profile of a cable under the action of its own weight, the inverse and forward kinematics of minimally constrained cable-driven manipulators can be numerically computed. this paper studies the effects of taking cable mass into account by comparison to classical massless cable model. it highlights the real effects of such a model on cable lengths to reach a given position. the effects on cable tensions are also studied.
utilizing reflection properties of surfaces to improve mobile robot localization. a main difficulty that arises in the context of probabilistic localization is the design of an appropriate observation model, i.e., determining the likelihood of a sensor measurement given the pose of the robot and a map of the environment. many successful approaches to localization rely on data provided by range sensors, e.g., laser range scanners. when using such data one normally has to deal with erroneous maximum-range readings that occur due to poor-reflecting surfaces. in general, these readings cannot be distinguished from readings obtained when no obstacle is within the measurement range of the sensor. therefore, existing localization techniques treat these readings alike in the observation model. in this paper, we present a novel approach that explicitly considers the reflection properties of surfaces and thus the expectation of valid range measurements. in addition to the expected range measurement, we compute the probability of reflectance for a beam given the relative pose of the robot to the obstacle taking into account the angle of incidence of the beam. we estimate the reflection properties of surfaces using data collected with a mobile robot equipped with a laser range scanner. as we demonstrate in experiments carried out with a real robot, our technique leads to significantly improved localization results compared to a state-of-the-art observation model.
integration of impedance control and manipulability regulation for a finger-arm robot. motion control algorithms were proposed for a 9-dof finger-arm robot by using the finger manipulability obtained in a previous study. however, in the previous study, only methods for achieving unconstrained movement of the finger-arm robot were discussed. in this paper, the authors propose a novel method for having a finger-arm robot complete a constrained task by integrating impedance control with manipulability control of the finger. first, methods of applying the previous heuristic method to the passive impedance control and the active impedance control were developed; and experiments were performed to demonstrate the features. then, an impedance control combined with the steepest ascent method to modulate the manipulability of the finger was proposed. the proposed method demonstrates a strong performance even when a dynamic external force is applied to the finger. by using the proposed method, the arm actively moves along a direction to effectively maintain the moving potential of the finger during both the unconstrained and the constrained tasks.
concurrent synthesis of robot manipulators using hardware-in-the-loop simulation. this paper discusses a practical approach to the concurrent synthesis of robot manipulators, which is based on the alternative design methodology of linguistic mechatronics (lm) as well as the utilization of a modular robotic hardware-in-the-loop simulation (rhils) platform. the rhils platform involves physical joint modules and the control unit to reduce modeling complexities while taking into account various physical phenomena. the lm methodology simplifies the multi-objective constrained optimization problem into a single-objective unconstrained formulation and also brings subjective notions of design into the scope. the new approach is applied to redesigning kinematic, dynamic and control parameters of an industrial manipulator.
a minimum-order kalman filter for ambulatory real-time human body orientation tracking. in this paper, a computationally efficient orientation estimation algorithm using an inertial/magnetic sensor is presented for ambulatory real-time human motion tracking. based on a quaternion formulation, the proposed algorithm is designed to have two main steps that are connected in feedback relationship: a quaternion measurement step with a vector selector scheme and a kalman filter (kf) step. this allows us to choose only the quaternion as the state and measurement vectors in our kf design. thus, the kf has a minimum-order structure (i.e., 4th-order), which decreases the computational cost. the estimated orientation accuracy is validated experimentally by using an optical tracking system.
active localization of a robot on a lattice of rfid tags by using an entropy map. we have developed a novel way for robots to estimate their pose dynamically in an environment in which rfid tags have been arranged. we previously developed a method for localizing robots using a particle filter. testing in a room equipped with a lattice of rfid tags at 300-mm intervals revealed that the estimation fails when the robot's rfid readers are near the center of the robot's rotation because the reader could not detect enough tags by rotating movements when the robot's positions are not suitable. we have overcome this problem by developing an active localization algorithm that generates an entropy map from the rfid arrangement information, predicts the pose using a particle filter, and attracts the robot to the target using a dynamic model, the fundamental unit of which is rotation-based angular velocity. testing demonstrated that a robot using this algorithm and an entropy map can estimate its pose robustly without falling into a dead zone by moving only about 20 cm at most.
evaluation of pinching effort by a tendon-driven robot hand. in this paper, we focus on the hand posture when a human subject pinches an object, and the correlation between the results of sensory evaluation by the subject and the tendon force of the subject's fingers are investigated. surface electromyogram (surface emg) and pinching force are measured during the pinching motion of human subjects. experimental results show that subjects feel comfortable pinching a 60 [mm] cylinder. the surface emgs are lower in the vicinity of 60 [mm]. furthermore, a tendon-driven robot hand is developed as a sensing hand prototype. the surface emgs and the motor torque are compared in a pinching experiment using the tendon-driven robot hand. experimental results show that the tendon-driven robot hand is effective for quantitatively evaluating pinching effort. simulation of the pinching motion is conducted using a simple finger model. the simulation results show the importance of finger posture and the moment arm in estimating tendon force. taken together, these results demonstrate the possibility of conducting quantitative evaluation using the tendon-driven robot hand.
tuning the gains of haptic couplings to improve force feedback stability in nanorobotics. this paper deals with the problem of bilateral haptic control in nanorobotics. at this scale, a human operator cannot interact directly with objects. he needs special tools manipulated through robotic systems. therefore, force feedback devices are the only solution to provide him a sense of touch. however, the quality of the rendering strongly influences his ability to perform a given task. stability is the main requirement that the system must fulfil to be usable. as the choice of the controller and its tuning are critical issues, a general method to tune the parameters of two haptic controllers is presented. a theoretical study is carried out and the methodology is validated with an experiment composed of several phases with high dynamic phenomena. intrinsic limitations of the two controllers are also pointed out.
optimized passive dynamics improve transparency of haptic devices. for haptic devices, compensation of the robot's gravity is a frequent strategy with the aim to reduce interaction forces between robot and human in zero-impedance control. however, a closer look at the composition of these interaction forces may reveal that the net effect of uncompensated gravitational components of the robot actually reduces interaction forces during dynamic movements, because inertial and gravitational components at least partially compensate each other. this is the case in lower extremity exoskeletons, where less user force is necessary to swing the robot's leg when gravity helps. here, we go one step further by shaping optimal passive dynamics for arbitrary haptic devices. the proposed method of generalized elasticies uses conservative force fields to improve haptic transparency for certain movements types. in an example realization, these force fields are generated by elasticities spanning multiple joints. practical experiments with the lokomat lower extremity exoskeleton show the success of the proposed method in terms of reduced interaction torques and more physiological user motion compared to gravity compensation.
ground plane velocity estimation embedding rectification on a particle filter multi-target tracking. this paper presents an integrated solution for vehicle's velocity estimation and vehicle counting. the proposed restores the scene geometric properties, building a ground plane rectified image. moreover, multiple vehicles tracking is performed embedding the concept of region covariance descriptors in a particle filter framework. the results show the effectiveness of the approach here proposed in very clutter scenes.
perceptual factors for interaction modeling using haptic device. in this paper a perceptual model of the interaction with pliable surface is presented. the aim of this work is to evaluate those human factors most relevant to surface contact task in a bilateral teleoperation system characterized by a low stiffness environment. three psychophysical experiments are conducted using an high performance haptic device and a virtual environment. in the first experiment we measure the capability of the human hand in terms of absolute force detection. the second experiment takes into account the time required by the neuro-muscular-skeletal system to stabilize the hand displacement in the presence of an external force. in the third one, a task of surface detection is involved to measures the smallest penetration depth that can be used to reliably perceive the contact surface. these perceptual factors are evaluated to build a perceptual model of a surface detection task. results show the effectiveness of our model, which can be useful in applications where it is crucial to be aware of the interplay among perceptual factors.
an adaptive-scale robust estimator for motion estimation. although ransac is the most widely used robust estimator in computer vision, it has certain limitations making it ineffective in some situations, such as the motion estimation problem, in which uncertainty on the image features changes according to the capturing conditions. the greatest problem is that the threshold used by ransac to detect inliers cannot be changed adaptively; instead it is fixed by the user. an adaptive scale algorithm must therefore be applied in such cases. in this paper, we propose a new adaptive scale robust estimator that adaptively finds the best solution with the best scale to fit the inliers, without the need for predefined information. our new adaptive scale estimator matches the residual probability density from an estimate and the standard gaussian probability density function to find the best inlier scale. our algorithm is evaluated in several motion estimation experiments under varying conditions and the results are compared with several of the latest adaptive-scale robust estimators.
passive force analysis with elastic contacts for fixturing and grasping. unlike active force closure, which is a property for the multi-finger robotic hand grasping, passive force closure are involved in the grasping systems with constraining devices that cannot freely control the contact forces, such as the whole-arm grasping and manufacturing fixture. in passive grasping, the contact forces rely on the physical compliance of the system which is usually described by complex contact mechanics models. the purpose of this paper is to study the properties of a type of contact model, the linear elastic contact model, so that it is possible to determine the passive force closure condition and to understand the essential characteristics of the passive grasping. the formula to solve the passive grasping forces is derived. properties of the passive grasping is studied. the kinematic compatibility equation which describes the requirement of the coordination of contact forces is discovered, which is unique to the passive grasping. the algorithm to find the range of the preload to guarantee the passive force closure is deduced. the algorithm is demonstrated with two examples.
toward model free atmospheric sensing by aerial robot networks in strong wind fields. this paper presents a system for in situ atmospheric sensing using an aerial robot system in the presence of a strong wind field. the geostatistical concept of the variogram is used to characterize regions of the environment with high variability, which is assumed to correlate with scientific interest. after regions of interest are identified, ordered upwind methods are used to generate feasible trajectories in the face of strong background wind. the feasible trajectories are combined with the variogram characterization to select feasible paths that travel through the regions of highest interest. the system is tested in simulation using data from a simulated severe storm.
bending and kissing: computing self-contact configurations of planar loops with revolute joints. in recent work, we introduced the notion of a construction tree of simplices for a linkage l under distance constraints, and showed that the deformation space dspace(l) of such an l (i.e., its configuration space cspace(l) modulo rigid motions of ambient space respecting all system specifications) carries geometrically-defined simplex-based parameters that endow it with a "practically piecewise-convex" structure. here we present parametrizations of contact deformations of planar loops with revolute joints. we show that the bending and kissing loci, which include the self-contact subspace dscontact (generally as a strict subset) can be efficiently described by triangle-based parameters. these results further demonstrate the effectiveness of the simplex-based approach.
control of a class of thrust-propelled underactuated vehicles and application to a vtol drone. a control approach for a class of underactuated vehicles with the objective of stabilizing reference trajectories either in velocity or position is proposed. the basic modeling assumption is that the vehicle is propulsed via a thrust force along a single body-fixed direction and that it has full torque actuation for attitude control (i.e. a typical actuation structure for aircrafts, vertical take-off and landing (vtol) vehicles, submarines, etc.). additional assumptions on the external forces applied to the vehicle are also introduced for the sake of control design and stability analyses. they are best satisfied for vehicles whose shape induces lift forces with limited amplitude and which are subjected to an external force field (e.g. gravity), as in the case of vtol vehicles. the interactions of the vehicle with the surrounding fluid are often difficult to model precisely and they may significantly perturb its motion. some novel nonlinear feedback control laws are proposed to compensate for modeling errors and perform robustly against such perturbations. simulation results illustrating these properties on a realistic model of a vtol vehicle are reported.
an unsupervised adaptive strategy for constructing probabilistic roadmaps. since planning environments are complex and no single planner exists that is best for all problems, much work has been done to explore methods for selecting where and when to apply particular planners. however, these two questions have been difficult to answer, even when adaptive methods meant to facilitate a solution are applied. for example, adaptive solutions such as setting learning rates, hand-classifying spaces, and defining parameters for a library of planners have all been proposed. we demonstrate a strategy based on unsupervised learning methods that makes adaptive planning more practical. the unsupervised strategies require less user intervention, model the topology of the problem in a reasonable and efficient manner, can adapt the sampler depending on characteristics of the problem, and can easily accept new samplers as they become available. through a series of experiments, we demonstrate that in a wide variety of environments, the regions automatically identified by our technique represent the planning space well both in number and placement.we also show that our technique has little overhead and that it out-performs two existing adaptive methods in all complex cases studied.
planar catadioptric stereo: single and multi-view geometry for calibration and localization. planar catadioptric stereo vision sensors (pcs) combine a pinhole camera with two or more planar mirrors. pcs have recently received an increasing attention since a stereo view can be easily obtained without the need of exact multi-camera synchronization and calibration. in this paper we present a rigorous analytical treatment of the imaging geometry of pcs, propose new mirror calibration algorithms and introduce new multi-view properties that can be used for eye-in-hand camera localization. the effectiveness of the algorithms is shown via extensive simulation and real-data experiments on a robotic manipulator.
evidence grid-based methods for 3d map matching. registering multiple sets of 3d range data is a crucial capability for robots. the standard method for matching two sets of range data is to convert the ranges to a point cloud representation, and then use on of the many variants of iterative closest point (icp). we present a set of alternative methods for matching 3d range scans based on a different data representation: evidence grid maps. evidence grids are robust to noise and variations in point density, can incorporate an indefinite number of ranges, and explicitly encode empty as well as occupied space. while 3d evidence grids can be huge when naively implemented, we use an optimized octree data structure to efficiently store sparse volumetric maps. to register a series of range scans, we build an evidence grid map for each scan, and then register them together using a several different methods. the first two methods are based on a 3d extension of the classic 2d lucas-kanade template matching method, and differ only in whether we match a single large region, or multiple small regions that are selected heuristically. our third method involves extracting surfaces from the evidence grids, and then running icp to register the surfaces. we demonstrate our methods and compare them to icp using two datasets collected by two different subterranean robots.
dynamic programming and skyline extraction in catadioptric infrared images. unmanned aerial vehicles (uav) are the subject of an increasing interest in many applications and a key requirement for autonomous navigation is the attitude/position stabilization of the vehicle. some previous works have suggested using catadioptric vision, instead of traditional perspective cameras, in order to gather much more information from the environment and therefore improve the robustness of the uav attitude/position estimation. this paper belongs to a series of recent publications of our research group concerning catadioptric vision for uavs. currently, we focus on the extraction of skyline in catadioptric images since it provides important information about the attitude/position of the uav. for example, the dem-based methods can match the extracted skyline with a digital elevation map (dem) by process of registration, which permits to estimate the attitude and the position of the camera. like any standard cameras, catadioptric systems cannot work in low luminosity situations because they are based on visible light. to overcome this important limitation, in this paper, we propose using a catadioptric infrared camera and extending one of our methods of skyline detection towards catadioptric infrared images. the task of extracting the best skyline in images is usually converted in an energy minimization problem that can be solved by dynamic programming. the major contribution of this paper is the extension of dynamic programming for catadioptric images using an adapted neighborhood and an appropriate scanning direction. finally, we present some experimental results to demonstrate the validity of our approach.
topology design of surgical reconfigurable robots by interval analysis. an automated design generation algorithm for a serial kinematic chain is presented for the reconfigurable robot used in a novel endoluminal surgical procedure (european union project ares). the algorithm produces the possible topologies, given the design constraints, desired performance, and available modules, such that all constraints are satisfied for every point in the desired workspace. this is achieved through the use of interval analysis methods and branch-and-bound loop that searches through the end-effector pose and the design parameter spaces. the resulting algorithm is demonstrated through an example of a serial chain manipulator made of the reconfigurable modules of the surgical robot for the application. the results are presented and discussed.
design of a modular robotic system for archaeological exploration. this paper presents the design and field tests of an intelligent robotic system for archaeological exploration. the system is designed for recording the internal environment of the underground ancient tombs. the recorded data is used for the preservation of antiques inside the ancient tombs as well as for providing the valuable references to the archaeological research. the whole system is modular and minimized in size that can be adapted for two different archaeological situations during the exploration of the ancient tombs. the robotic system can enter the covered ancient tombs through the digging holes prepared by the regular archaeological exploration. one size of the vertical digging hole is less than 12 centimeter in diameter, and the other is 50 centimeter in diameter. the archaeologists can operate on the remote station to control the robotic system with wired communication. the field test results are finally presented for validation of this archaeological robotic system design.
rollover risk prediction of an instrumented heavy vehicle using high order sliding mode observer. in this paper, an original method about heavy vehicles rollover risk prediction is presented and validated experimentally. it is based on the calculation of the ltr (load transfer ratio) which depends on the estimated vertical forces using high order sliding mode observers. the validation tests were carried out on an instrumented truck rolling on the road at various speeds and lane-change manoeuvres. many scenarios have been experienced: driving on straight line, curve line and zigzag to emphasize the rollover phenomenon and its prediction to set off an alarm to the driver.
avoiding moving outliers in visual slam by tracking moving objects. to work at video rate, the maps that monocular slam builds are bound to be sparse, making them sensitive to the erroneous inclusion of moving points and to the deletion of valid points through temporary occlusion. this paper describes the parallel implementation of monoslam with a 3d object tracker, allowing reasoning about moving objects and occlusion. the slam process provides the object tracker with information to register objects to the map's frame, and the object tracker allows the marking of features, either those on objects, or those created by their occluding edges, or those occluded by objects. experiments are presented to verify the recovered geometry and to indicate the impact on camera pose in monoslam of including and avoiding moving features.
automated mouse embryo injection moves toward practical use. taking a different architecture than manual operation and existing microrobotic systems, this paper presents the first automated system that employs novel microfabricated cell holding devices and vision-position based control of multiple motion control devices to achieve easy sample immobilization, rapid cell orientation, and fast injection of mouse embryos. the system requires minimal human involvement through a maximum of three computer mouse clicking per mouse embryo, is human operator skill independent, and is immune from fatigue. while no robotic systems have provided performance close to manual operation, according to the preliminary experimental results (n = 90) from this study, this microrobotic system demonstrated: (i) an injection speed of 9 embryos/min vs. 2 embryos/min in typical manual operation, (ii) a success rate of 98.9%, a higher rate than the best success rate (90%) achieved by proficient injection technicians with over 10 years' experience, and (iii) a high survival rate of 82.1%, a rate comparable with the best survival rate (∼80%) achieved by proficient injection technicians. further improvement of the automated system will change the way of how mouse embryos are injected and promise its practical use in biology laboratories and mouse facilities.
development of a 2-dof electrostatic haptic joystick for mri/fmri applications. this paper describes the development of a 2-dof electrostatic haptic joystick designed for neuroscience studies in an mri/fmri. the joystick is fabricated using non-magnetic materials and actuated by two high-power electrostatic motor units which produce various force fields in the horizontal plane. the electrostatic motor is a synchronous drive and thus the positioning of the joystick is achieved in an open-loop control. as for force sensing, a 2-dof force sensor is developed using non-magnetic materials and optical fibers so as to measure interaction force with a user; hence, the haptic rendering is based on the admittance control scheme that respects the rule of force-in and position-out. the operation of both the actuators and force sensor respects non-magnetic principles. thus, the haptic joystick into which these components are integrated is expected to have high mr compatibility, although the evaluation of the mr compatibility is beyond the scope of this paper. in this paper, the device performance is evaluated in the normal environment, which verifies the operation of the unique electrostatic haptic device.
context assessment strategies for ubiquitous robots. this paper presents an architecture for context-aware ubiquitous robotics applications, where mobile robots cooperate with intelligent environments to fulfill their tasks. specifically, the work is focused on distributed knowledge representation issues and context assessment strategies, and introduces a technique for on-line context recognition in highly dynamic environments. experimental validation, performed in a civillian hospital building, is described and discussed.
differentiated layer design to modify the compliance of soft pads for robotic limbs. most of robotic soft pads studied so far were made with a thick layer of homogeneous material shaped around a rigid core; their behavior has been widely investigated in the literature, mainly under compressive contact load, showing typical non-linear relationship between contact deformation and applied load (the so called power law). this paper proposes differentiated layer design, that is the adoption of a single elastic material, dividing the overall thickness of the pad into layers with different structural design (e.g. a continuous skin layer coupled with an internal layer with voids). the purpose is to modify the actual pad compliance and the resulting power law; in particular, given the material and the allowable pad thickness, to increase the compliance with respect to a non structured pad. some possible internal layer structures are described, compatible with rapid prototyping manufacturing. their compressive behaviors are tested and comparatively evaluated showing that the concept can work and be exploited for useful application.
mri-compatible hands-on cooperative control of a pneumatically actuated robot. mri compatible robots are emerging as useful tools for image guided interventions. a shared control between a user and the mri compatible robot makes it more intuitive instrument especially during setup phases of interventions. we present a mri compatible, hands-on cooperative system using innomotion robotic arm. an economic mri compatible user input sensor was developed and its functionality was tested under typical application conditions. performance improvement in phantom tasks shows promise of adding hands-on interface in mri compatible robots.
nonlinear bilateral teleoperation: stability analysis. this paper aims to take a first step towards the unification of the stability analysis for teleoperators with time-delays. it proposes a general lyapunov-like function that, upon slight modification, allows to analyze the stability of different control schemes, ranging from constant to variable time delays, with or without the scattering transformation and with or without position tracking. it also presents design examples of the corresponding lyapunov-like function for some schemes based on pd controllers and on the scattering transformation for variable time-delays.
a snake robot joint mechanism with a contact force measurement system. a snake robot can traverse cluttered and irregular environments by using irregularities around its body as pushpoints to aid the propulsion. this is denoted obstacle-aided locomotion and requires the snake robot to have two features: 1) a smooth exterior surface combined with 2) a contact force sensing system. these two features are characteristic of biological snakes, but have received limited attention in snake robot designs so far. this paper presents a joint mechanism for a snake robot aimed at meeting both these requirements. the paper details the design and implementation of the joint mechanism and presents experimental results that validate the function of the contact force measurement system.
primitive static states for intelligent operated-work machines. advanced operated-work machines, which have been designed for complicated tasks and which have complicated operating systems, requires intelligent systems that can provide the quantitative work analysis needed to determine effective work procedures and that can provide operational and cognitive support for operators. construction work environments are extremely complicated, however, and this makes state identification, which is a key technology for an intelligent system, difficult. we therefore defined primitive static states (pss) that are determined using on-off information for the lever inputs and manipulator loads for each part of the grapple and front and that are completely independent of the various environmental conditions and variation in operator skill level that can cause an incorrect work state identification. to confirm the usefulness of pss, we performed experiments with a demolition task by using our virtual reality simulator. we confirmed that pss could robustly and accurately identify the work states and that untrained skills could be easily inferred from the results of pss-based work analysis. we also confirmed in skill-training experiments that advice information based on pss-based skill analysis greatly improved operator's work performance. we thus confirmed that pss can adequately identify work states and are useful for work analysis and skill improvement.
consensus for formation control of nonholonomic mobile robots. in this article we present novel formation control laws based on artificial potential fields and consensus algorithms for a group of unicycles enabling arbitrary formation patterns for these nonholonomic vehicles. given connected and balanced graphs we are able to prove stability of the rendezvous controller by applying the lasalle-krasovskii invariance principle. further, we introduce obstacle avoidance, enabling a reactive behavior of the robotic group in unknown environments. the effectiveness of the proposed controllers is shown using computer simulations and finally, a classification w.r.t. existing solutions is done.
uav target tracking using an adversarial iterative prediction. we present a control strategy that permits a fixed wing uav to visually track a ground target. a pursuit-evasion strategy aims at optimizing the visibility of the pursuer uav after having predicted the best action for the evading target. this is achieved by using two iterative methods that optimise various mission based criteria: obstacle avoidance and visibility maximisation for the uav and stealthy motions for the target.
analysis of sliding of a soft fingertip embedded with a novel micro force/moment sensor: simulation, experiment, and application. we have investigated the deformation of a soft fingertip when it slides. this process was first simulated using the non-linear finite element analysis (fea) method. based on the results of this simulation, we designed experiments to observe the sliding and object grasping of a soft fingertip, in which a 3-dof (degree of freedom) micro force/moment sensor was embedded. with this sensor, forces and moments acting in the fingertip are measured based on the piezoresistive effect. these measurements provide information on the status of contact and sliding of a soft fingertip on a surface. based on these results, incipient slip, which has an important role in object gripping by a robot manipulator, can be realized. textile's texture recognition experiments were also conducted to assess potentials of the fingertip in tactile and texture perception.
development of mörri, a high performance and modular outdoor robot. this paper describes the development of mörri, a multi purpose robot platform. the design of this robot includes mechanical, electrical and software development. key features of the robot are modularity for multi-purpose applications, affordable size for outdoor and indoor operation, low cost, high performance, and easy to use and repair in field conditions. the main focus on software architecture development has been on creating fully-functional real-time architecture, where several algorithms and methods can be easily integrated as part of the system. as a result, this robot took part on m-elrob outdoor robot competition in july 2008 and won "camp security" scenario.
multi-robot tree and graph exploration. in this paper we present an algorithm for the exploration of an unknown graph with k robots, which is guaranteed to succeed on any graph, and which on trees we prove to be near-optimal for two robots, having optimal dependence on the size of the tree but not on its radius. we believe that the algorithm performs well on any graph, and this is substantiated by simulations. for trees with n edges and radius r, the exploration time is 2n/k + o(rk-1), improving a recent method with o(n/log k + r) [1], and almost reaching the lower bound max(2n/k, 2r). the algorithm is meant to be used in indoor navigation or cave search scenarios where the environment can be modeled as a graph. in this scenario, communication is realized by the devices being dropped by the robots at explored vertices, and the states of which are read and changed by further visiting robots. simulations on player/stage platform have been performed in both tree and graph exploration which corroborate the mathematical results.
a probabilistic model for the performance analysis of a distributed task allocation algorithm. in this paper we extend our previous work where the mean of the global cost was used as a performance metric for distributed task allocation algorithms. in this case, we move a step forward and calculate the variance of the global cost. this second parameter gives us a better understanding of the distributed algorithm performance, i.e., we can estimate how much the algorithm behavior diverts from its mean. the normal distribution, computed from the theoretical mean and variance, is shown to be suitable for modeling the global cost. this approximation enables us to compare our algorithm theoretically in different cases.
qualitative robot localisation using information from cast shadows. recently, cognitive psychologists and others have turned their attention to the formerly neglected study of shadows, and the information they purvey. these studies show that the human perceptual system values information from shadows very highly, particularly in the perception of depth, even to the detriment of other cues. however with a few notable exceptions, computer vision systems have treated shadows not as signal but as noise. this paper makes a step towards redressing this imbalance by considering the formal representation of shadows. we take one particular aspect of reasoning about shadows, developing the idea that shadows carry information about a fragment of the viewpoint of the light source. we start from the observation that the region on which the shadow is cast is occluded by the caster with respect to the light source and build a qualitative theory about shadows using a region-based spatial formalism about occlusion. using this spatial formalism and a machine vision system we are able to draw simple conclusions about domain objects and egolocation for a mobile robot.
speed-accuracy optimization for skill learning. robot motor capability is crucial for skill learning because it determines how accurately and rapidly a robot can perform a skill to accomplish a task constrained by the spatial and temporal conditions. due to the capability of robot motor, a robot may not be able to perform skills to satisfy both task spatial and temporal constraints. to determine the robot motor capability, this paper formulates the skill for accomplishing a task as an optimization problem subject to the spatial and temporal conditions of the task, and proposes to develop a speed-accuracy constraint suitable for the optimization problem. the proposed speed-accuracy constraint is derived from the kinematics, dynamics, and control of a robot motor system. by solving the optimization problem, a robot can perform the skill to achieve a task by its fastest speed without violating the spatial and temporal conditions of the task. computer simulations were performed on a puma 560 robot to demonstrate a skill on a typical task to validate the proposed speed-accuracy optimization.
probabilistic situation recognition for vehicular traffic scenarios. to act intelligently in dynamic environments, a system must understand the current situation it is involved in at any given time. this requires dealing with temporal context, handling multiple and ambiguous interpretations, and accounting for various sources of uncertainty. in this paper we propose a probabilistic approach to modeling and recognizing situations. we define a situation as a distribution over sequences of states that have some meaningful interpretation. each situation is characterized by an individual hidden markov model that describes the corresponding distribution. in particular, we consider typical traffic scenarios and describe how our framework can be used to model and track different situations while they are evolving. the approach was evaluated experimentally in vehicular traffic scenarios using real and simulated data. the results show that our system is able to recognize and track multiple situation instances in parallel and make sensible decisions between competing hypotheses. additionally, we show that our models can be used for predicting the position of the tracked vehicles.
rough terrain walking for bipedal robot by using zmp criteria map. a new method for bipedal walking on rough terrain by using zmp criteria map is proposed. the rough terrain walking is classified to "step up" and "step down" by landing timing of a swing leg. the walking pattern is modified in real-time according to the difference between the ideal timing and the measured timing by a force sensor on the foot. in the case of "step up", the landing timing is faster than the ideal, and the swing leg trajectory should be change to follow the step so that the zmp based balance of the sudden caused double support phase is kept. in the case of "step down", the landing timing is later than the ideal, and the swing leg trajectory should be change to seek the ground so that the balance of the unknown future double support phase is kept. the modified walking pattern is decided based on the zmp criteria map. the zmp criteria map can indicate a safe landing timing and landing position of a swing leg. by referring the zmp criteria map, the robust walking pattern can be planned. the proposed method is implemented to hrp-2, and the effectiveness is confirmed through experiments.
ad-hoc wireless network coverage with networked robots that cannot localize. we study a fully distributed, reactive algorithm for deployment and maintenance of a mobile communication backbone that provides an area around a network gateway with wireless network access for higher-level agents. possible applications of such a network are distributed sensor networks as well as communication support for disaster or military operations. the algorithm has minimalist requirements on the individual robotic node and does not require any localization. this makes the proposed solution suitable for deployment of large numbers of comparably cheap mobile communication nodes and as a backup solution for more capable systems in gps-denied environments. robots keep exploring the configuration space by random walk and stop only if their current location satisfies user-specified constraints on connectivity (number of neighbors). resulting deployments are robust and convergence is analyzed using both kinematic simulation with a simplified collision and communication model as well as a probabilistic macroscopic model. the approach is validated on a team of 9 irobot create robots carrying wireless access points in an indoor environment.
randomized model predictive control for robot navigation. the paper suggests a new approach to navigation of mobile robots, based on nonlinear model predictive control and using a navigation function as a control lyapunov function. in this approach, the nonlinear optimal control problem is treated using randomized algorithms. the advantage of the proposed combination of navigation functions for robot motion planning with randomized algorithms within an mpc framework, is that the control design offers stability by design, is platform independent, and allows the designer to trade-off performance for (computation) speed, according to the application requirements.
survivability: measuring and ensuring path diversity. a novel criterion is introduced for assessing the diversity of a collection of paths or trajectories. the main idea is the notion of survivability, which measures the likelihood that numerous paths are obstructed by the same obstacle. this helps to improve robustness with respect to collision, which is an important challenge in the design of real-time planning algorithms. efficient algorithms are presented for computing the survivability criterion and for selecting a subset of paths that optimize survivability from a larger collection. the algorithms are implemented and solutions are illustrated for two different systems. chi-square tests are used to show uniform coverage obtained by using the computed paths in a simple breadth-first search. random obstacle placement is used to show superior robustness of these primitives compared to uniform sampling of the control space.
a variable stiffness joint using leaf springs for robot manipulators. safety of a manipulator designed to be used at home requires different approach than industrial robots, where safety is achieved mainly by decreasing the interaction with humans. robots for applications at home, however, require frequent interaction with humans. introducing compliant component gives the answer to the safety issue at the cost of performance degradation. in order to reduce the performance degradation, manipulators equipped with variable stiffness have been studied by many researchers. this paper presents a variable stiffness joint(vsj) designed for a robot manipulator. the stiffness is generated by leaf springs and two actuators are used to control the position and stiffness of the joint. changing the effective length of the spring results in change in stiffness. the position of the joint is controlled via rotating two actuators at the same speed in the same direction. the stiffness is controlled when the two actuators rotate in the different speed. experiments are conducted to show that the position and stiffness are controlled independent with each other and having less stiffness at the joint helps in making unexpected collision with object safer.
perception-centric force scaling function for stable bilateral interaction. in this paper a force scaling function for an haptic system is the output of the psychophysics experiments that have been carried out with the aim of better understanding the human perception capabilities. the experimental work consists in measuring the differential thresholds of force perception applied to the hand-arm system. these findings support our claim that the human perception of forces and torques depends on force intensity and works differently along different directions, thus suggesting that perception can be enhanced by suitable scaling. we have identified a scaling function for each direction and we have shown that this variable scalings can be safely embedded in a passivity based teleoperation system in order to improve the feeling perceived by the user during the interaction with remote environments.
revisiting uncertainty analysis for optimum planes extracted from 3d range sensor point-clouds. in this work, we utilize a recently studied more accurate range noise model for 3d sensors to derive from scratch the expressions for the optimum plane which best fits a point-cloud and for the combined covariance matrix of the plane's parameters. the parameters in question are the plane's normal and its distance to the origin. the range standard-deviation model used by us is a quadratic function of the true range and is a function of the incidence angle as well. we show that for this model, the maximum-likelihood plane is biased, whereas the least-squares plane is not. the plane-parameters' covariance matrix for the least-squares plane is shown to possess a number of desirable properties, e.g., the optimal solution forms its null-space and its components are functions of easily understood terms like the planar-patch's center and scatter. we verify our covariance expression with that obtained by the eigenvector perturbation method. we further compare our method to that of renormalization with respect to the theoretically best covariance matrix in simulation. the application of our approach to real-time range-image registration and plane fusion is shown by an example using a commercially available 3d range sensor. results show that our method has good accuracy, is fast to compute, and is easy to interpret intuitively.
deformation modeling of belt object with angles. a differential geometry based modeling to represent belt object deformation is proposed. deformation of a belt object such as film circuit boards or flexible circuit boards must be estimated for automatic manipulation and assembly. first, the fishbone model to describe deformation of a rectangular belt object is explained. in this model, the object shape is represented by the curved "spine line" and straight "rib lines". we can estimate deformation of the object by minimizing its potential energy under geometric constraints. next, this model is modified to represent deformation in which the rib line at an endpoint does not coincide with the transverse edge. moreover, the modified model is applied to a belt object with angles. the deformed shape of an angled object can be derived by separating it into rectangular parts and angled parts and by assuming that each angled part forms a part of a cylindrical surface. finally, the validity of our proposed model is verified by comparing the computed shape of an l-shaped belt object with its measured shape.
dynamics and control of a 4-dof wearable cable-driven upper arm exoskeleton. in this paper, we present the dynamics, control, and preliminary experiments on a wearable upper arm exoskeleton intended for human users with four degrees-of-freedom (dof), driven by six cables. the control of this cable-driven exoskeleton is complicated because the cables can transmit forces to the arm only under tension. the standard pd controllers or computed torque controllers perform only moderately since the cables need to be in tension. future efforts will seek to refine these control strategies and their implementations to improve functionality of a human user.
monte carlo simultaneous localization of multiple unknown transient radio sources using a mobile robot with a directional antenna. we report our system and algorithm developments that enable a single mobile robot equipped with a directional antenna to simultaneously localize multiple unknown transient radio sources. due to signal source anonymity, short transmission durations, and dynamic transmission patterns, the robot cannot treat the radio sources as continuous radio beacons. we model the radio source behaviors using a novel spatiotemporal probability occupancy grid (spog) that captures transient characteristics of radio transmissions and tracks the spatiotemporal posterior probability distribution of the radio transmissions. as a monte carlo method, we propose a ridge walking motion planning algorithm that enables the robot to efficiently traverse the high probability regions to accelerate the convergence of the posterior probability distribution. we have implemented the algorithms and the experiment results show that our method consistently outperforms methods such as a random walk or a fixed-route patrol mechanism.
development of backdrivable hydraulic joint mechanism for knee joint of humanoid robots. robots must have similar mechanical impedance characteristics to humans in order to make safe and efficient contact. this impedance requirement applies not only to the surface but also to the actuation mechanisms. the objective of this research is to develop inherently flexible actuator by realizing backdrivability. a class of hydraulic actuation called electro-hydrostatic actuator was applied to knee joint in humanoid robots to satisfy flexibility and large torque output simultaneously. this paper explains the methodology of performance evaluation of actuators and design concept of joint mechanism. mathematical model of electro-hydrostatic transmission is also presented. evaluation of backdrivability, inertia modification control, and compliance control of developed mechanism are performed.
hsm3d: feature-less global 6dof scan-matching in the hough/radon domain. this paper presents hsm3d, an algorithm for global rigid 6dof alignment of 3d point clouds. the algorithm works by projecting the two input sets into the radon/hough domain, whose properties allow to decompose the 6dof search into a series of fast one-dimensional cross-correlations. no planes or other particular features must be present in the input data, and the algorithm is provably complete in the case of noise-free input. the algorithm has been experimentally validated on publicly available data sets.
basic study of biarticular muscle's effect on muscular internal force control based on physiological hypotheses. in a musculoskeletal structure, the internal force among muscles plays an important role. changing the internal force enables to control not only joint angles but also impedance, so that vertebrate animals can produce a motion according to a situation. focusing on a musculoskeletal system with two links and six muscles, this paper investigate the effect of biarticular muscles when feedforward position control is inputted. this control gives the constant internal force balancing at desired posture as feedforward input, based on the ep hypothesis in physiology. from the result, we point out that the biarticular muscles can reduce the convergent time of the motion, and they also can stabilize the system.
milligram-scale high-voltage power electronics for piezoelectric microrobots. piezoelectric actuators can achieve high efficiency and power density in very small geometries, which shows promise for microrobotic applications, such as flapping-wing robotic insects. from the perspective of power electronics, such actuators present two challenges: high operating voltages, ranging from tens to thousands of volts, and a low electromechanical coupling factor, which necessitates the recovery of unused electrical energy. this paper explores the power electronics design problem by establishing the drive requirements of piezoelectric actuators, presenting circuit topologies and control methods suitable for driving different types of piezoelectric actuators in microrobotic applications, and demonstrating experimental realizations of sub-100mg power electronics circuits.
automatic deployment of autonomous cars in a robotic urban-like environment (rule). we present a computational framework and experimental setup for deployment of autonomous cars in a miniature robotic urban-like environment (rule). the specifications are given in rich, human-like language as temporal logic statements about roads, intersections, and parking spaces. we use transition systems to model the motion and sensing capabilities of the robots and the topology of the environment and use tools resembling model checking to generate robot control strategies and to verify the correctness of the solution. the experimental setup is based on khepera iii robots, which move autonomously on streets while observing traffic rules.
on achievable accuracy for pose tracking. this paper presents cramér-rao bound-like inequalities for pose tracking, which is defined as the problem of recovering the robot displacement given two successive readings of a relative sensor. computing the exact fisher information matrix (fim) for pose tracking is hard, because the state comprises the map, which is infinite-dimensional and unknown. this paper shows that the fim for pose tracking can be bounded by a function of the fim for localization on a known map, thereby reducing the analysis to a finite-dimensional problem. the resulting bounds are independent of the map prior and representation. the results are valid for any relative sensor; the experimental verification is done for the particular case of pose tracking using range-finders (scan matching).
search-based planning for a legged robot over rough terrain. we present a search-based planning approach for controlling a quadrupedal robot over rough terrain. given a start and goal position, we consider the problem of generating a complete joint trajectory that will result in the legged robot successfully moving from the start to the goal. we decompose the problem into two main phases: an initial global planning phase, which results in a footstep trajectory; and an execution phase, which dynamically generates a joint trajectory to best execute the footstep trajectory. we show how r* search can be employed to generate high-quality global plans in the high-dimensional space of footstep trajectories. results show that the global plans coupled with the joint controller result in a system robust enough to deal with a variety of terrains.
on autonomous detection of pressured air and gas leaks using passive ir-thermography for mobile robot application. today, pressured air and gas leaks are typically detected using in-situ sensor technology. in this contribution the application of passive ir-thermography is proposed to permit remote leak detection by assessing the resulting temperature profile disturbance due to expansion of pressured gas. remote measurements are advantageous as they are easier and safer to conduct. scanning high-rise objects can be achieved using a ground-bound system without requiring complex climbing. in the paper a novel method for automated leak detection by feature extraction and pattern recognition is presented. this enables autonomous mobile robots with remote leak detection capability.
range estimation from a moving camera: an immersion and invariance approach. the paper proposes an original solution to the range identification problem for perspective dynamical systems. the depth of a static point observed by a pinhole camera undergoing a predefined 3-d motion, is estimated from its 2-d projection on the image plane. the proposed nonlinear observer relies on the immersion and invariance (i&i) methodology and offers several advantages over the existing range estimators. the paper also provides an analytical study of nonlinear observability performed with the extended output jacobian. extensive simulation experiments illustrate the theory and show the effectiveness of the proposed design.
adaptive expert systems for indirect coverage control. herds of livestock, when left to their own devices, will forage for food in predictable patterns, and will often overgraze preferred areas while leaving other areas untouched. the field of grazing management looks to improve the efficiency of land use by moving the animals through different pastures at regular intervals, akin to coverage algorithms used in robotics but with non-uniform coverage and additional constraints due to the animals' natural behaviors. the knowledge of the field of grazing management is largely in the hands of ranchers and other domain experts, and as such has not been the subject of much computational study. in this work, we have created novel learning techniques for expert systems that use both off-line and on-line learning to generate efficient performance. the rules of the expert systems are initially developed using an evolutionary algorithm, and after deployment, an adaptive algorithm tracks the state of the system and updates rule weights to improve both coverage efficiency and animal stress levels. we present a series of results based on increasingly complex versions of simulated herd models that show improvements over unconstrained motion in each case, and suggest how the algorithm can apply to robotic coverage problems.
vision-based detection of finger touch for haptic device using transparent flexible sheet. a haptic device using transparent flexible sheet, which is an improvement of our previous one, presents visual and haptic sensations when a user pushes a virtual soft object. it consists of a transparent flexible sheet and a computer display; the display is placed behind the sheet. the user feels the softness of the object by pushing the sheet, and sees the stereoscopic cg image of the deformed object through the sheet. in the present study we propose a new method of detecting finger touch on the sheet and measuring the indentation of the contact point; the method is specialized for this haptic device. a camera is placed behind the sheet. a checkered pattern is reflected on the backside of the sheet like a two-way mirror. the camera monitors this reflected pattern. when the finger pushes the sheet, the sheet is deformed. then the reflected pattern near the fingertip, seen from the camera, is distorted. monitoring this distortion makes it possible to detect finger touch on the sheet. as the indentation of the contact point increases, the reflected pattern is more distorted. thus measuring the amount of the distortion allows the measurement of the indentation. the proposed method is ascertained by some experiments.
improved inverse-depth parameterization for monocular simultaneous localization and mapping. inverse-depth parameterization can successfully deal with the feature initialization problem in monocular simultaneous localization and mapping applications. however, it is redundant, and when multiple landmarks are initialized from the same image, it fails to enforce the "common origin" constraint. the authors propose two new variants that addresses both of these issues. the experimental results indicate that the proposed approach achieves a better performance at a lower computational cost.
whole body motion primitive segmentation from monocular video. this paper proposes a novel approach for motion primitive segmentation from continuous full body human motion captured on monocular video. the proposed approach does not require a kinematic model of the person, nor any markers on the body. instead, optical flow computed directly in the image plane is used to estimate the location of segment points. the approach is based on detecting tracking features in the image based on the shi and thomasi algorithm [1]. the optical flow at each feature point is then estimated using the lucas kanade pyramidal optical flow estimation algorithm [2]. the feature points are clustered and tracked on-line to find regions of the image with coherent movement. the appearance and disappearance of these coherent clusters indicates the start and end points of motion primitive segments. the algorithm performance is validated on full body motion video sequences, and compared to a joint-angle, motion capture based approach. the results show that the segmentation performance is comparable to the motion capture based approach, while using much simpler hardware and at a lower computational effort.
mimetic communication with impedance control for physical human-robot interaction. in this paper, mimetic communication is extended to human-robot interaction tasks, in which physical contact transitions must be handled. the mimetic communication consists of imitation learning for learning low level motion primitives and a higher level interaction learning stage in which also the information about the human-robot contacts is included. for the imitation learning, cartesian marker data from a motion capture system is used. a modification of the low level marker trajectory following algorithm is presented, which allows to reshape the trajectory of the motion primitive in accordance with the human hand motion in real-time. moreover, for performing safe contact motion, an appropriate impedance controller is integrated into the setting. all the presented concepts are evaluated in experiments with a humanoid robot.
a versatile wire robot concept as a haptic interface for sport simulation. this paper presents the design of a new user-cooperative rope robot. this robot serves as a large-scale haptic interface in a multi-modal cave environment used for sport simulation. in contrast to current rope robots, the configuration of the presented robot is adaptable to different simulation tasks what makes the robot more versatile. however, this adaptability and the high dynamics in sports lead to challenging requirements and specific design criteria of the hardware components. we present the requirements on the single robot components as well as the design of the entire setup optimized in terms of user-cooperativity and versatility. the setup includes sensors to measure the relevant parameters for user-cooperative control, i.e. position with a high resolution and the rope forces. furthermore, an algorithm is introduced, which calculates the distance between the single ropes and the user in order to avoid collisions between the ropes and the user. single points on the user's body are, therefore, tracked with a motion tracking system; the user's single body parts are then represented by geometrical objects whose distances to the ropes are calculated. the algorithm is programmed in such way that the collision detection runs in real-time. both, the hardware and the algorithm, were evaluated experimentally in two applications, a rowing simulator and a tennis application. the hardware concept combined with the distance calculation allows the use of new kinematic concepts and expands the spectrum of realizable movement tasks that can be implemented into the cave environment.
a wireless acoustic emitter for passive localization in liquids. for the localization of minimally invasive medical devices, such as capsule endoscopes in the human body, ultrasound combines good resolution, minimal adverse health effects, high speed, adequate frame rates, and low cost. in the case of capsule endoscopes, small onboard ultrasonic emitters with minimal power requirements have the potential to provide significantly enhanced localization. we demonstrate for the first time acoustic emission in the khz range using a wireless emitter based on the actuation principle of the wireless resonant magnetic microactuator developed recently in our institute. our experiments show good agreement with the theoretical model, and simulations show the potential for high resolution localization.
a numerical solution to the ray-shooting problem and its applications in robotic grasping. based on the distance algorithm by gilbert et al., this paper presents a numerical algorithm for computing the intersection of the boundary of a compact convex set with a ray emanating from an interior point of the set, which is known as the ray-shooting problem. affinely independent points on the boundary of the convex set are also determined such that the intersection point can be written as their convex combination. because of its high efficiency and other good qualities, this algorithm provides superior solutions to three fundamental problems in robotic grasping, i.e., force-closure test, contact force optimization, and grasp quality evaluation, which can be formulated as the ray-shooting problem.
standing stabilizability and stepping maneuver in planar bipedalism based on the best com-zmp regulator. the goal of this paper is to answer (i) how the stabilization performance of a biped controller can be evaluated on a certain invariant supporting region, (ii) how the standing stabilizer which performs the best on a given supporting region can be designed, (iii) how the system can be judged if it is stabilizable by the best standing stabilizer without deforming the current supporting region, and (iv) how the supporting region should be deformed if it is judged to be necessary. in order to answer these question, the stable standing region is defined. it gives a criterion to design the best standing stabilizer, to judge if the deformation of the supporting region is necessary to stabilize the system, and to maneuver the stepping motion in accordance with the standing stabilizability condition, which is also defined in the paper. it is found that the best standing stabilizer can be designed by a simple pole-assignment technique. this framework unifies the standing stability and the stepping stability of bipedalism, which have been separately considered in conventional studies. the discussion goes on an approximate planar com-zmp model, in which the total mass is concentrated at the center of mass, and the position of zmp is regarded as the input. though it is the simplest dynamical model of bipeds, it can conceal differences of body constitutions and represent the macroscopic dynamics. therefore, this paper contributes to not only the biped robot controller design but also the biomechanical analyses.
an optimization-based approach to control of robotic manipulators. this paper proposes a method to suboptimally tune the control parameters in a conventional lyapunov-based method which shares the same concept of control design with sliding mode approach as applied to the robot manipulators. optimal tuning of such parameters involves handling of non-linearities in system dynamics and cost functions, which makes the problem challenging. we propose a step-by-step numerical algorithm that select suboptimal parameters while ensuring system stability. the controller is, suboptimal due to the facts that (1) it is in the form of a slotine-type sliding mode control, (2) the numerical recursive algorithm might fall into a local minimum, and (3) the controller coefficients depend on the initial conditions of the system. the method is successfully applied to a two-link robot manipulator and the results are compared in simulation with those of a conventional controller.
mechanical design of a novel hand exoskeleton for accurate force displaying. this paper deals with the mechanical design of a novel haptic hand exoskeleton (he) that allows exerting controlled forces on the fingertip of the index and thumb of the operator. the proposed device includes several design solutions for optimizing the accuracy and mechanical performances. remote centers of motion mechanisms have been adopted for delocalizing the encumbrance of linkages of the structure away from the operator's fingers. an improved stiffness of the transmission and reduced requirements for the actuators have been achieved thanks to a novel patent pending principle for integrating speed reduction ratio with the transmission system.
realization of acrobatic turn via wheelie for a bicycle with a balancer. since unmanned bike robots have high mobility and do not require wide contact space to the ground, it is expected that they will be used as one kind of the robots working in disaster areas and/or in the mountains. we are developing one of the unmanned bike robot systems with a balancer and it can do a wheelie and move to track the path in the ground plane. in this paper, we propose a control strategy to perform an acrobatic turn with wheelie motion, which can be quick and require minimum contact space for a bicycle by using nonlinear control based on the output-zeroing controller. the dynamic models of the bicycle with the balancer are derived from lagrangian's equations and they are combined by lagrange's multiplier according to nonholonomic and holonomic constraints between subsystems. the effectiveness of the proposed method is shown by several numerical simulations using a detail model of a bicycle.
partial order techniques for vehicle collision avoidance: application to an autonomous roundabout test-bed. in this paper, we employ partial order techniques to develop linear complexity algorithms for guaranteed collision avoidance between vehicles at highway and roundabout mergings. these techniques can be employed by virtue of the rich structure offered by such traffic systems, which constrain vehicles to advance unidirectionally along a path. the algorithms are safe by construction while maintaining the liveness of the system. the proposed algorithms are on-line implemented in a decentralized fashion on an experimental testbed composed of two in-scale communicating vehicles continuously running on an autonomous roundabout system.
robot-assisted rapid prototyping for ice structures. ice has long been used by humankind for utilitarian purposes, and more recently for artistic and entertainment purposes. nowadays, the field of ice construction is becoming more commercially relevant, with increased interest in ice modeling at the small scale, and in ice tourism, specifically ice hotels at the large scale. as a result, there is a market for automating ice construction, and building detailed structures that would otherwise require a significant amount of manual work. to address this demand, the authors are currently developing experimental robotic systems for building ice structures: the fab@home, for building small-scale structures, and the adept cobra 600 robot, for building medium-scale structures. further software and hardware development is needed for the cobra, since it was not designed for rapid prototyping, and certainly not for rapid prototyping using ice as the working material. the authors have designed and built fluid delivery systems for each machine to permit the use of water as the building material. a signal-processing subsystem permits control of the water-delivery flow rate and synchronization with the robot motion. additionally, we have developed a slicing algorithm to generate toolpaths for the cobra using stereolithography (stl) files as the input. we also intend to develop a larger robotic system for producing ice sculptures and buildings at the architectural scale.
development of the ihmc mobility assist exoskeleton. the ihmc mobility assist exoskeleton is a robitic suit that a user can wear for strength augmentation or gait generation. this first generation exoskeleton prototype focuses on providing walking assistance to persons with lower extermity paralysis. the main goal is to successfully enable a person that cannot walk without assistance to walk in a straight line a distance of 15 feet. when in disable assist mode this prototype will rely on the user to provide balance control, and thus an external means for balancing will be required, such as crutches or a walker. power and control is off board and supplied to the exoskeleton by means of a tether. rotary series elastic actuators (rseas), which have high force fidelity and low impedance were designed to power the joints. this paper described the design, test results, future work and potential applications of the exoskeleton.
task oriented kinematic analysis for a legged robot with half-circular leg morphology. in this paper, we study the kinematics of a legged robot with half-circular leg morphology. in particular, our focus is on the rhex hexapod platform. a new kinematic model for rhex is developed considering the leg shape and its consequences, which was over simplified in the previous models seen in literature. the formulation is an accurate kinematic representation of the robot in the sagittal plane that is based on a four-link mechanism analogy. when only pure rolling motion of the legs are considered, it is found that when front and rear pairs of legs are in contact with the ground, the robot becomes a one degree-offreedom mechanism and position of the middle pair of legs are redundant. the problem is solved in two steps; the first one being the determination of the initial configuration of the leg angular positions which defines the initial value of the variable distance of the front and rear leg and ground contact ponts. after the initial configuration of the system is set, pitch angle of the robot body can be manipulated by controlling one of the leg angular positions and the results are presented on an example case; positioning a body fixed unactuated sensor by controlling robot body pitch angle through the actuation of one of the legs. the results are a good display of the multifunctional aspect of the legs in addition to their use for locomotion.
multi-vehicle path planning in dynamically changing environments. in this paper, we propose a path planning method for nonholonomic multi-vehicle system in presence of moving obstacles. the objective is to find multiple fixed length paths for multiple vehicles with the following properties: (i) bounded curvature (ii) obstacle avoidant (iii) collision free. our approach is based on polygonal approximation of a continuous curve. using this idea, we formulate an arbitrarily fine relaxation of the path planning problem as a nonconvex feasibility optimization problem. then, we propound a nonsmooth dynamical systems approach to find feasible solutions of this optimization problem. it is shown that the trajectories of the nonsmooth dynamical system always converge to some equilibria that correspond to the set of feasible solutions of the relaxed problem. the proposed framework can handle more complex mission scenarios for multi-vehicle systems such as rendezvous and area coverage.
task modeling approach to enhance man-machine collaboration in cell production. the objective of this work is to enhance man-machine collaboration in cell production by task modeling approach. task modeling provides a method to define and study the collaboration between man and machine. six requirements have been derived as basis of development. in this work, the task modeling has extended classical hta method to represent collaborative operation in a hierarchical structure with the classification of operation task levels and extended operation details as task properties. a modeling tool is developed to provide a development and data management platform. the man-machine collaboration is well defined in a structural format by the ability of task analysis method to address human task in a more flexible way. the collaboration modeling and operation resources information have significantly facilitated operation planning in both assembly and control levels. from the case study, the improvement in safety aspect has proven the ability of this approach in assisting safety design and development of production system. the integration with operation control system has shown the execution potential in real-time operation. the unique development of operation data management has expanded this work into operation information support. through the multimodal information support system, the human operator is well guided by the operation information corresponded to the task components. the operation information also can work as evaluation functions to measure the human working performance and system performance as a whole.
a coordinate-free approach to instantaneous kinematics of two rigid objects with rolling contact and its implications for trajectory planning. this paper adopts a coordinate-free approach to investigate the kinematics of rigid bodies with rolling contact. a new equation of angular velocity of the moving body is derived in terms of the magnitude of rolling velocity and two sets of geometric invariants belonging to the respective contact curves. this new formulation can be differentiated up to any order. furthermore, qualitative information about trajectory planning can be deduced from this equation if the characteristics of rolling objects and the motion are taken into consideration.
transfer of knowledge for a climbing virtual human: a reinforcement learning approach. in the reinforcement learning literature, transfer is the capability to reuse on a new problem what has been learnt from previous experiences on similar problems. adapting transfer properties for robotics is a useful challenge because it can reduce the time spent in the first exploration phase on a new problem. in this paper we present a transfer framework adapted to the case of a climbing virtual human (vh). we show that our vh learns faster to climb a wall after having learnt on a different previous wall.
coordinated motion control of multiple passive object handling robots based on environment information. in this paper, we introduce a passive mobile robot called prp (passive robot porter), which has passive dynamics with respect to an applied force and its appropriate motion is controlled based on the servo brakes. in this paper, we especially focus on a motion control algorithm of multiple passive mobile robots for handling a large object in cooperation with a human. by controlling each passive mobile robot in the decentralized way, we realize collision avoidance function and path following function of the object to improve the maneuverability for the human operator. the proposed algorithms applied to two prps actually, and experimental results illustrate the validity of the proposed algorithms.
probabilistic multi-component extended strong tracking filter for mobile robot global localization. this paper proposes a multi-component extended strong tracking filter (mester) for global localization. it is the first time strong tracking filter (stf) is introduced into robotics domain and is fundamentally extended to be suitable for fusing observations with arbitrary time-varying dimensionality, based on equivalent space transformation and extended orthogonality principle. the resulted extended strong tracking filter (estf) is then combined with a probabilistic multi-component evolving mechanism and finally forms the mester localization method. real robot experiments and comparisons with existing methods show that mester has high convergence speed, computational efficiency and definite robustness to sensor noises, kidnapped robot problem, system nonlinearities, and symmetric environments.
surface model reconstruction of 3d objects from multiple views. a points surface reconstruction algorithm of 3d object models from multiple silhouettes is proposed in this paper. some images of the target object are taken from a circular trajectory by a robot with a camera mounted in an eye-in-hand configuration. the silhouettes of the observed object are evaluated for each view using a blob analysis process, and from those a set of points that sample a reconstruction sphere surrounding the target object are estimated. the sphere sample points are attracted by the object center of mass using a variable step according to the distance from the silhouettes contours. for each point, the iterative process of constriction is stopped when all the back-projections of the point are within the corresponding silhouettes. moreover, a new method based on a rough estimation of object dimension is proposed to reduce the disturbances due to projection and shadow cones. simulations and experiments are presented to evaluate the performance of the proposed algorithm.
adaptive autonomous control using online value iteration with gaussian processes. in this paper, we present a novel approach to controlling a robotic system online from scratch based on the reinforcement learning principle. in contrast to other approaches, our method learns the system dynamics and the value function separately, which permits to identify the individual characteristics and is, therefore, easily adaptable to changing conditions. the major problem in the context of learning control policies lies in high-dimensional state and action spaces, that needs to be explored in order to identify the optimal policy. in this paper, we propose an approach that learns the system dynamics and the value function in an alternating fashion based on gaussian process models. additionally, to reduce computation time and to make the system applicable to online learning, we present an efficient sparsification method. in experiments carried out with a real miniature blimp we demonstrate that our approach can learn height control online. further results obtained with an inverted pendulum show that our method requires less data to achieve the same performance as an off-line learning approach.
development of inspection robot for under floor of house. we are developing robots for inspection of the under floor of houses. the developed robot system is reported in this paper. the mobile robot platform is based on a crawer type robot developed for rescue purposes. as sensors, a pan-tilt-zoom camera, top-view camera and sokuiki sensor are used. we constructed a test field and verified the performance of the robot.
detecting repeated motion patterns via dynamic programming using motion density. in this paper, we propose a method that detects repeated motion patterns in a long motion sequence efficiently. repeated motion patterns are the structured information that can be obtained without knowledge of the context of motions. they can be used as a seed to find causal relationships between motions or to obtain contextual information of human activity, which is useful for intelligent systems that support human activity in everyday environment. the major contribution of the proposed method is two-fold: (1) motion density is proposed as a repeatability measure and (2) the problem of finding consecutive time frames with large motion density is formulated as a combinatorial optimization problem which is solved via dynamic programming (dp) in polynomial time o(n log n) where n is the total amount of data. the proposed method was evaluated by detecting repeated interactions between objects in everyday manipulation tasks and outperformed the previous method in terms of both detectability and computational time.
tracking intraocular microdevices based on colorspace evaluation and statistical color/shape information. successful ophthalmic surgeries using intraocular untethered microrobots or tethered robotic microtools require methods to robustly track the microdevices in the posterior of the human eye. the dimensions and specularities of the microdevices are major obstacles for accurate tracking. in addition, the optical structure of the human eye makes it challenging to keep the objects of interest constantly in focus, resulting in blurred images. in this paper, the advantages of using different colorspacaes for intraocular tracking are examined. after selection of the appropriate colorspace, thresholds that ensure maximum separation of the device from the background are calculated. based on trained color histograms, level sets are used to track in real time, and the use of statistical shape information is incorporated in the existing tracking framework. the efficacy of the algorithm is demonstrated by tracking a microrobot in a model eye, using a custom made ophthalmoscope and off-the-shelf opthalmoscopy lenses. with the appropriate colorspace and threshold selection, tracking errors are minimized and are further diminished using shape information.
object handling tasks based on active tactile and slippage sensations in a multi-fingered humanoid robot arm. this paper presents a new algorithm for object handling tasks based on active tactile and slippage sensations using a humanoid robot multi-fingered arm for an object that exists at an arbitrary position. the idea is to enhance real-time object handling tasks based on tactile sensing in humanoid robotics, where grasp, move and release motions are involved. we developed a novel hemisphere-shaped optical three-axis tactile sensor to mount on fingertips of the robot arm. the tactile sensor is capable of defining normal and shearing forces simultaneously. for grasp and release motions, we designed the algorithm based on slippage direction analysis consisting of coordinate transformation of the sensing element for the arm global coordinate. the robot control system uses the analysis results to determine whether an object is in contact with the ground without needing to measure the height of the ground. the algorithm was evaluated in experiments with soft and hard objects, whereby results revealed good performance for the robot fingers in handling an object at an arbitrary position.
affordance based word-to-meaning association. this paper presents a method to associate meanings to words in manipulation tasks. we base our model on an affordance network, i.e., a mapping between robot actions, robot perceptions and the perceived effects of these actions upon objects. we extend the affordance model to incorporate words. using verbal descriptions of a task, the model uses temporal co-occurrence to create links between speech utterances and the involved objects, actions and effects. we show that the robot is able form useful word-to-meaning associations, even without considering grammatical structure in the learning process and in the presence of recognition errors. these word-to-meaning associations are embedded in the robot's own understanding of its actions. thus they can be directly used to instruct the robot to perform tasks and also allow to incorporate context in the speech recognition task.
modeling deformable shell-like objects grasped by a robot hand. this paper models (large) deformations of shell-like objects under the grasping of a robot hand. classical nonlinear theory of thin shells [21, pp. 186-194] is generalized to shells with arbitrary parametric middle surfaces, using a method introduced in our earlier work [13]. an experimental study demonstrates higher modeling accuracy using the nonlinear elasticity theory than its linear counterpart. given that many deformable objects undergo sizable shape changes when they are grasped, our result supports the application of nonlinear elasticity theory in the future design of grasp strategies for this type of objects.
development of high-sensitivity slip sensor using special characteristics of pressure conductive rubber. even with the eyes closed, humans are able to grip an object with minimal force without such information as the coefficient of friction or the weight. tactile sensors capable of detecting slippage are necessary for this gripping action to be realized in a robot hand. heretofore, many slip sensors were developed and produced, but there was not a slip sensor of simple structure practical for installation on fingertips of a robot hand. therefore, we propose a low-profile/lightweight slip sensor of simple structure. the special properties of pressure conductive rubber are utilized as a detection device in this sensor. in this paper, we discuss the results of trial manufacture and of slip detection property testing of this sensor. moreover, we will report the results of slip prevention experiments by this prototype slip sensor, and indicate that the pressure conductive rubber is promising as a material of slip sensor.
theoretical analysis of three bio-inspired plume tracking algorithms. we derive the theoretical performance of three bio-inspired odor source localization algorithms (casting, surgespiral and surge-cast) in laminar wind flow. based on the geometry of the trajectories and the wind direction sensor error, we calculate the distribution of the distance overhead and the mean success rate using bayes inference. our approach is related to particle filtering and produces smooth output distributions. the results are compared to existing real-robot and simulation results, and a good match is observed.
dynamic region following formation control for a swarm of robots. this paper presents a dynamic region following formation control method for a swarm of robots. in this control strategy, a swarm of robots shall move together as a group inside a dynamic region that can rotate or scale to enable the robots to adjust the formation. various desired shapes can be formed by choosing appropriate functions. unlike existing formation control methods, the proposed method do not need to have specific identities or orders in the group but yet dynamic formation can be formed for a large group of robots. this enables a swarm of robots to adjust the formation during the course of maneuver. the system is also scalable in the sense that any robot can move into the formation or leave the formation without affecting the other robots. lyapunov-like function is presented for convergence analysis of the multi-robot systems. simulation results are presented to illustrate the performance of the proposed controller.
high-speed position tracking for nanohandling inside scanning electron microscopes. this paper describes a new position tracking system that uses the scanning electron microscope as a fast, high-resolution sensor system. the position tracking system works similar to an optical encoder using a specially structured pattern as scale. thus, with low computational overhead, an accuracy below 10nm is achieved in a tungsten cathode-based microscope. the tracking system is virtually immune to changes in contrast, brightness, magnification and, to a certain extend, to defocusing. with a customized, external scan generator and scanning algorithm, the bottleneck of image acquisition can be bypassed and the position tracking system can reach update rates of more than 1 khz. furthermore, measurements can be conducted over long working ranges of up to 200 µm without losing precision.
new interval-based approach to determine the guaranteed singularity-free workspace of parallel robots. in the present paper we introduce an improved method to obtain the guaranteed singularity-free workspace of planar parallel kinematic machines. a geometric condition for the existence of singularities is extended to be used in interval analysis. therefore, we eliminate the need of calculating the inconvenient interval form of the jacobian's determinant. hence, an appropriate description of the singularity-free workspace is obtained and the computational effort is reduced significantly. with the interval-based approach error sources, like manufacturing tolerances, can be considered. consequently, regions that do not satisfy the proposed condition can be guaranteed not to have any type-two singularities. several analysis examples demonstrate the efficiency of the proposed geometrical-based solver in comparison to existing solvers, i.e. based on the jacobian's determinant.
fast needle insertion to minimize tissue deformation and damage. during needle-based procedures, transitions between tissue layers often involve puncture events that produce substantial deformation and tend to drive the needle off course. in this paper, we analyze the mechanics of these rupture events corresponding to unstable crack propagation during the insertion of a sharp needle in an inhomogeneous tissue. the force-deflection curve of the needle prior to a rupture event is modeled by a nonlinear viscoelastic kelvin model and a stress analysis is used to predict the relationship between rupture force and needle velocity. the model predicts that the force-deflection response of the needle is steeper and the tissue absorbs less energy when the needle moves faster. the force of rupture also decreases for faster insertion under certain conditions. the observed properties are sufficient to show that maximizing needle velocity minimizes tissue deformation and damage, and consequently, results in less needle insertion position error. the model predicts that tissue deformation and absorbed energy asymptotically approach lower bounds as velocity increases. experiments with porcine cardiac tissue confirm the analytical predictions.
efficient c-space and cost function updates in 3d for unmanned aerial vehicles. when operating in partially-known environments, autonomous vehicles must constantly update their maps and plans based on new sensor information. much focus has been placed on developing efficient incremental planning algorithms that are able to efficiently replan when the map and associated cost function changes. however, much less attention has been placed on efficiently updating the cost function used by these planners, which can represent a significant portion of the time spent replanning. in this paper, we present the limited incremental distance transform algorithm, which can be used to efficiently update the cost function used for planning when changes in the environment are observed. using this algorithm it is possible to plan paths in a completely incremental way starting from a list of changed obstacle classifications. we present results comparing the algorithm to the euclidean distance transform and a mask-based incremental distance transform algorithm. computation time is reduced by an order of magnitude for a uav application. we also provide example results from an autonomous micro aerial vehicle with on-board sensing and computing.
posture control of a dual-crawler-driven robot. this paper deals with a tracked robot that consists of the proposed crawler module, in which a planetary gear reducer is used as the power transmission device to give two different outputs with just one actuator. this underactuated system could perform posture control through the interaction between the front and rear modules. on occasion, the posture that the front module is lifted up can make the robot overcome obstacles actively and easily. to find out the controllable postures, the static analysis of the robot has been conducted. in this paper, we provide the control strategy for performing the posture control, and propose the control methods including direct, indirect, and cooperative control to conduct the posture control. experimental tests show the effectiveness of the control methods.
ability to hold grasped objects by underactuated hands: performance prediction and experiments. to evaluate and optimize the mechanical design of underactuated hands, a benchmark test is defined that quantifies the ability to hold grasped objects subject to force disturbances as occurs during for instance pick and place operations. the ability to hold is quantified by the magnitude of the maximum permitted static force on the center of a cylindrical object of known radius at which it can still be hold within the underactuated hand. a static grasp model is developed to efficiently calculate the effect of design parameters of the hand on this maximum force. this model is applied to a planar, underactuated hand with six degrees of freedom, calculating the maximum force while the rotational joint stiffnesses and distance between the fingers was varied. we demonstrated that the rotational joint stiffness has no effect on this force, while decreasing the distance between the fingers has a negative effect. these results were validated by measurements in an experimental setup. these preliminary results show that the developed benchmark test can be effective to evaluate and optimize the performance of underactuated hands to hold objects in pick and place operations.
torsional kinematic model for concentric tube robots. a recent approach to steerable needle design is based on combining pre-curved tubes concentrically. by rotating and extending the tubes with respect to each other, the position and orientation of the needle tip, as well as the shape of the inserted length, can be controlled. prior models neglected torsional twisting in the curved portions of the tubes. this paper presents a mechanics model that includes torsion, applies to any number of tubes and allows curvature and stiffness to vary with arc length. while the general model is comprised of differential equations, an analytic solution is given for two tubes of constant curvature. this solution enables analytic prediction of "snap through" instability based on a single dimensionless parameter. simulation and experiments are used to illustrate the results.
design of a semi-active knee prosthesis. current state-of-the-art prostheses for transfemoral amputees operate exclusively through controlled damping or through fully powered gait imitation. the passive devices cannot restore a natural gait, and the active devices are large and inefficient. this paper summarizes the design of a new semi-active prosthetic knee that combines the proven safety and power efficiency of a passively damped hydraulic device with the improved gait and advanced mobility of a fully active device.
step function based turning maneuvers in biomimetic robotic fish. this paper presents a new turning maneuver generation method for a multilink biomimetic robotic fish, in which smooth step functions are introduced to dynamically trigger directed offsets in active and asymmetric swimming. with the proposed method, three basic turning modes can be unified into a general framework by choosing appropriate step-function combinations and dynamic bias. furthermore, this method can be employed to maneuver the robotic fish agilely in the path planning, which promises more flexibility and steadiness in potential applications to bio-inspired autonomous underwater vehicles.
an optimized linear model predictive control solver for online walking motion generation. this article addresses the fast solution of a quadratic program underlying a linear model predictive control scheme that generates walking motions. we introduce an algorithm which is tailored to the particular requirements of this problem, and therefore able to solve it efficiently. different aspects of the algorithm are examined, its computational complexity is presented, and a numerical comparison with an existing state of the art solver is made. the approach presented here, extends to other general problems in a straightforward way.
design of human symbiotic robot twendy-one. in this paper, we propose a sophisticated design of human symbiotic robots that provide physical supports to the elderly such as attendant care with high-power and kitchen supports with dexterity while securing contact safety even if physical contact occurs with them. first of all, we made clear functional requirements for such a new generation robot, amounting to fifteen items to consolidate five significant functions such as "safety", "friendliness", "dexterity", "high-power" and "mobility". in addition, we set task scenes in daily life where support by robot is useful for old women living alone, in order to deduce specifications for the robot. based on them, we successfully developed a new generation of human symbiotic robot, twendy-one that has a head, trunk, dual arms with a compact passive mechanism, anthropomorphic dual hands with mechanical softness in joints and skins and an omni-wheeled vehicle. evaluation experiments focusing on attendant care and kitchen supports using twendy-one indicate that this new robot will be extremely useful to enhance quality of life for the elderly in the near future where human and robot co-exist.
pose estimation and adaptive robot behaviour for human-robot interaction. this paper introduces a new method to determine a person's pose based on laser range measurements. such estimates are typically a prerequisite for any human-aware robot navigation, which is the basis for effective and time-extended interaction between a mobile robot and a human. the robot uses observed information from a laser range finder to detect persons and their position relative to the robot. this information together with the motion of the robot itself is fed through a kalman filter, which utilizes a model of the human kinematic movement to produce an estimate of the person's pose. the resulting pose estimates are used to identify humans who wish to be approached and interacted with. the behaviour of the robot is based on adaptive potential functions adjusted accordingly such that the persons social spaces are respected. the method is tested in experiments that demonstrate the potential of the combined pose estimation and adaptive behaviour approach.
distributed coverage control for mobile sensors with location-dependent sensing models. this paper addresses the problem of coverage control of a network of mobile sensors. in the current literature, this is commonly formulated as a locational optimization problem under the assumption that sensing performance is independent of the locations of sensors. we extend this work to a more general framework where the sensor model is location-dependent. we propose a distributed control law and coordination algorithm. if the global sensing performance function is known a priori, we prove that the algorithm is guaranteed to converge. to validate this algorithm, we conduct experiments with indoor and outdoor deployments of cyclops cameras and model its sensing performance. this model is used to simulate deployments on 1d pathways and study the coverage obtained. we also examine the coverage in the case when the global sensing function is not known and is estimated in an online fashion.
person identification from human walking sequences using affine moment invariants. this paper proposes a new person identification method using physiological and behavioral biometrics. various person recognition systems have been proposed so far, and one of the recently introduced human characteristics for the person identification is gait. although the shape of one's body has not been considered much as a characteristic, it is closely related to gait and it is difficult to disassociate them. so, the proposed technique introduces a new hybrid biometric, combining body shape (physiological) and gait (behavioral). the new biometric is the full spatio-temporal volume carved by a person who walks. in addition to this biometric, we extract unique biometrics in individuals by the following way: creating the average image from the spatio-temporal volume and forming the new spatio-temporal volume from differential images which are created by subtracting an average image from original images. affine moment invariants are derived from these biometrics, and classified by a support vector machine. we used the leave-one-out cross validation technique to estimate the correct classification rate of 94%.
compact analysis of 3d bipedal gait using geometric dynamics of simplified models. the large number of degrees of freedom in legged robots give rise to complicated dynamics equations. analyzing these equations or using them for control can therefore be a difficult and non-intuitive task. a simplification of the complex multi-body dynamics can be achieved by instantaneously reducing it to an equivalent single inertial entity called the locked inertia or the composite rigid body inertia. in this paper, we adopt the methods of geometric dynamics to analyze the gait using the locked inertia of the robot. the analysis includes the rolling of a biped on a 3d rigid foot and 3d impacts. an example of numerical optimization of foot shape parameters is shown. our long-term objective is to develop the theoretical framework and to provide the necessary tools for systematic analysis, design, and control of efficient biped robots.
the curious robot - structuring interactive robot learning. if robots are to succeed in novel tasks, they must be able to learn from humans. to improve such human-robot interaction, a system is presented that provides dialog structure and engages the human in an exploratory teaching scenario. thereby, we specifically target untrained users, who are supported by mixed-initiative interaction using verbal and non-verbal modalities. we present the principles of dialog structuring based on an object learning and manipulation scenario. system development is following an interactive evaluation approach and we will present both an extensible, event-based interaction architecture to realize mixed-initiative and evaluation results based on a video-study of the system. we show that users benefit from the provided dialog structure to result in predictable and successful human-robot interaction.
a novel approach to path planning for multiple robots in bi-connected graphs. this paper addresses a problem of path planning for multiple robots. an abstraction where the environment for robots is modeled as an undirected graph with robots placed in its vertices is used (this abstraction is also known as the problem of pebble motion on graphs). a class of the problem with bi-connected graph and at least two unoccupied vertices is defined. a novel polynomial-time solution algorithm for this class of problem is proposed. it is shown in the paper that the new algorithm significantly outperforms the existing state-of-the-art techniques applicable to the problem. moreover, the performed experimental evaluation indicates that the new algorithm scales up well which make it suitable for practical problem solving.
human brain-teleoperated robot between remote places. this paper describes an eeg-based human brain-actuated robotic system, which allows performing navigation and visual exploration tasks between remote places via internet, using only brain activity. in operation, two teleoperation modes can be combined: robot navigation and camera exploration. in both modes, the user faces a real-time video captured by the robot camera merged with augmented reality items. in this representation, the user concentrates on a target area to navigate to or visually explore; then, a visual stimulation process elicits the neurological phenomenon that enables the brain-computer system to decode the intentions of the user. in the navigation mode, the target destination is transferred to the autonomous navigation system, which drives the robot to the desired place while avoiding collisions with the obstacles detected by the laser scanner. in the camera mode, the camera is aligned with the target area to perform an active visual exploration of the remote scenario. in june 2008, within the framework of the experimental methodology, five healthy subjects performed pre-established navigation and visual exploration tasks for one week between two cities separated by 260km. on the basis of the results, a technical evaluation of the device and its main functionalities is reported. the overall result is that all the subjects were able to successfully solve all the tasks reporting no failures, showing a high robustness of the system.
unified motion planning of passing under obstacles with humanoid robots. a motion planning method for humanoid robots to pass under obstacles is proposed. the proposed motion planner can calculate a goal configuration and connect it with an initial configuration in a collision-free dynamically stable motion. the method can generate not only a body motion but also the footstep sequence. the effectiveness of the proposed method was validated by experiments with the humanoid robot hrp- 2.
navigating by stigmergy: a realization on an rfid floor for minimalistic robots. stigmergy is a mechanism that allows the coordination of actions within the same agent or across different agents by means of traces left in the environment. we propose a stigmergetic approach to robot navigation in which a robot sets values in a hexagonal grid of rfid tags buried under the floor. this approach only requires minimal resources on the robot. the rfid floor will eventually contain a distance map that can guide the robot to a given goal (or set of goals) without the use of any localization system. the same map can be used or improved by other robots or by the same robot at later times. we define algorithms for building the rfid-floor map and for navigating on this map, we prove the convergence of the map building algorithm, and we show an empirical validation of our results using a small robot in a domestic environment.
a self-repairing structure for modules and its control by vibrating actuation mechanisms. in this study, we propose a self-repairing mechanism for modules. this mechanism has been developed by studying the self-repairing processes found in nature. proposed model is considered with the aid of energy given from the external environment. we investigate a self-repairing process using small modules actuated by vibration. we first describe the proposed self-repairing mechanism and its application to the control of a group of modules. we report the development of the vibrator used in this study and formulate the equation of translational and rotational motions of modules placed on this plate. the proposed mechanism is verified by carrying out numerical simulation and experiments. in addition, we introduce two simple structures based on the proposed mechanism.
evaluation of frequency band technique in estimating muscle fatigue during dynamic contraction task. long-time exposure to repetitive or monotonous work is associated with increased risk for musculoskeletal disorders that are due to muscle fatigue. previously, researchers reported that muscle fatigue can be estimated using a low-frequency band of an semg signal. however, these studies were performed exclusively during static contraction tasks. the objective of the present study was to evaluate and determine the frequency range for a low-frequency band. in addition, the performance during dynamic contraction tasks was analyzed. a group of healthy university students (8 males) was recruited, and endurance handgrip tasks were conducted. semg signals were captured from the forearm muscle. the frequency range for the low-frequency band was redefined as 5 - 40hz. the results from a dynamic contraction task indicated that a low-frequency band is a reliable method for indexing muscle fatigue from semg signals.
tracking groups of people with a multi-model hypothesis tracker. people in densely populated environments typically form groups that split and merge. in this paper we track groups of people so as to reflect this formation process and gain efficiency in situations where maintaining the state of individual people would be intractable. we pose the group tracking problem as a recursive multi-hypothesis model selection problem in which we hypothesize over both, the partitioning of tracks into groups (models) and the association of observations to tracks (assignments). model hypotheses that include split, merge, and continuation events are first generated in a data-driven manner and then validated by means of the assignment probabilities conditioned on the respective model. observations are found by clustering points from a laser range finder given a background model and associated to existing group tracks using the minimum average hausdorff distance. experiments with a stationary and a moving platform show that, in populated environments, tracking groups is clearly more efficient than tracking people separately. our system runs in real-time on a typical desktop computer.
motion control of impedance-type haptic devices. impedance type devices are frequently used in haptics due to their excellent rendition of free-space, low cost, and convenience. the spring drive, a recently proposed alternative to the traditional current motor driver for such devices, has been shown to improve their stiffness in rigid contact by moving the haptic coupling from the digital domain to analog circuitry. unlike the current drive, which operates the motor as a force source, the spring drive converts the motor to a motion source. in this paper we construct a motion-based virtual environment to fully leverage the benefits of operating an impedance device with motion control. this quasi-static environment is connected to a mid-level controller which interfaces with the analog motor drive. a full system analysis and experimental demonstration verify the anticipated performance.
development of a grip aid system using air cylinders. we have been developing a grip aid system using air cylinders to assist elderly who have weak grasping force to have daily living activities. the system is small and light weight. in this paper, mechanism to assist thumb, index, and middle fingers using one air cylinder for each finger, is proposed. and also control method of the device using a bending sensor to transfer their will to control the system is developed. finally much kind of objects are grasped with an assist of the system and the result shows a potential of the system.
the implementation of a novel, bio-inspired, robotic security system. the implementation of a robotic security solution generally requires one algorithm to route the robot around the environment and another algorithm to perform anomaly detection. solutions to the routing problem require the robot to have a good estimate of its own pose. we present a novel security system that uses metrics generated by the localisation algorithm to perform adaptive anomaly detection. the localisation algorithm is a vision-based slam solution called ratslam, based on mechanisms within the hippocampus. the anomaly detection algorithm is based on the mechanisms used by the immune system to identify threats to the body. the system is explored using data gathered within an unmodified office environment. it is shown that the algorithm successfully reacts to the presence of people and objects in areas where they are not usually present and is tolerised against the presence of people in environments that are usually dynamic.
using critical junctures and environmentally-dependent information for management of tightly-coupled cooperation in heterogeneous robot teams. this paper addresses the challenge of forming appropriate heterogeneous robot teams to solve tightly-coupled, potentially multi-robot tasks, in which the robot capabilities may vary over the environment in which the task is being performed. rather than making use of a permanent tightly-coupled robot team for performing the task, our approach aims to recognize when tight coupling is needed, and then only form tight cooperative teams at those times. this results in important cost savings, since coordination is only used when the independent operation of the team members would put mission success at risk. our approach is to define a new semantic information type, called environmentally dependent information, which allows us to capture certain environmentally-dependent perceptual constraints on vehicle capabilities. we define locations at which the robot team must transition between tight and weak cooperation as critical junctures. note that these critical juncture points are a function of the robot team capabilities and the environmental characteristics, and are not due to a change in the task itself. we calculate critical juncture points by making use of our prior asymtre approach, which can automatically configure heterogeneous robot team solutions to enable sharing of sensory capabilities across robots. we demonstrate these concepts in experiments involving a human-controlled blimp and an autonomous ground robot in a target localization task.
a robotic sentinel for benthic sampling along a transect. this paper presents the design of a novel robotic system capable of long-term benthic sampling along a transect. the robot is built to traverse back and forth along a mechanical guide-rail at the bottom of a water body. we present results from localization tests with the robot in a laboratory tank and a shallow swimming pool. a pilot deployment was made at a marina to accurately observe the rate and direction of water flow across a section of the marina inlet. results from the experiment demonstrate the potential of this platform for monitoring various aquatic phenomena of interest.
dynamic path planning with multi-agent data fusion - the parallel hierarchical replanner. the design of a hierarchical planning system in which each level operates in parallel and communicates asynchronously is presented. it is shown that this parallel hierarchical replanner is both reactive, and as close to optimal over all information in the state space as is possible given finite computational power. a comparison with three other hierarchical methods is presented, which demonstrates that for scenarios in which the time taken to achieve a mission goal is of greater importance than the cost incurred, this approach has better performance than related methods in the literature.
real-time face tracking and pose estimation with partitioned sampling and relevance vector machine. tracking the pose of human face has long been an important research topic which has many important applications, and it is particularly challenging with a monocular camera because the depth information is lost due to the perspective projection. this work adopts particle filter with partitioned sampling to decompose the state space of face pose tracking into two subspaces for increasing the sampling efficiency, thus achieving satisfactory performance with fewer particles. the parameters in the first subspace describe the target on image plane, and the parameter in the second subspace is used for the estimate of the face pose in yaw angle direction. for the evaluation of each hypothesis in the second subspace, a statistical learning algorithm called relevance vector machine (rvm) is used to map a face containing image to the pose of the face. the training of rvm is tailored to each detected frontal face, and it takes less than half second, which is suitable for a real-time application. the learning based regression model also presents the insensitive ability to expression variation and unmodeled degree of freedom. the experimental results verify that the combination of particle filter and rvm can efficiently reduce the processing time and add robustness to the performance of the system, thus making this algorithm applicable to human-machine interface with low-cost webcams.
learning 3-d object orientation from images. we propose a learning algorithm for estimating the 3-d orientation of objects. orientation learning is a difficult problem because the space of orientations is non-euclidean, and in some cases (such as quaternions) the representation is ambiguous, in that multiple representations exist for the same physical orientation. learning is further complicated by the fact that most man-made objects exhibit symmetry, so that there are multiple "correct" orientations. in this paper, we propose a new representation for orientations--and a class of learning and inference algorithms using this representation-- that allows us to learn orientations for symmetric or asymmetric objects as a function of a single image. we extensively evaluate our algorithm for learning orientations of objects from six categories.
3d tree reconstruction from laser range data. we present a method for reconstructing 3d models of tree branch structure from laser range data. our approach is probabilistic, and uses general knowledge of tree structure to guide an iterative reconstruction process. our goal is to recover parameters such as branch locations, angles, radii, and lengths, as well as connectivity information between branches. these parameters can then be fed into functional-structural plant models to study the relationships between the structure of a plant, its environment, and its internal biology. in this paper we present an algorithm for finding these parameters, and results on both simulated and real datasets.
environment adapted active multi-focal vision system for object detection. a biologically inspired foveated attention system in an object detection scenario is proposed. thereby, a high-performance active multi-focal camera system imitates visual behaviors such as scan, saccade and fixation. bottom-up attention uses wide-angle stereo data to select a sequence of fixation points in the peripheral field of view. successive saccade and fixation of high foveal resolution using a telephoto camera enables high accurate object recognition. once an object is recognized as target object, the bottom-up attention model is adapted to the current environment, using the top-down information extracted from this target object. the bottom-up attention model and the object recognition algorithm based on sift are implemented using cuda technology on graphics processing units (gpus), which highly accelerates image processing. in the experimental evaluation, all the target objects were detected in different backgrounds. evident improvements in accuracy, flexibility and efficiency are achieved.
transmission of tactile roughness through master-slave systems. in this study, a tactile-roughness transmission system applicable to master-slave systems with a communication time delay is developed. the master-side system constructs a local model of target objects placed in the slave-side environment. tactile feedbacks presented to an operator at the master side are produced by combining the physical properties of target objects in the local model and the kinetic information of the operator. the time delay between the operator's motion and the tactile feedback is cancelled because the stimuli are synchronized with the exploratory motions. the proposed system is applied to the transmission of tactile-roughness. the tactile stimuli presented to the operator are vibratory stimuli whose amplitude and frequency are controlled. these stimuli are locally synthesized by combining the surface wavelength of target objects and the operator's hand velocity. using the developed tactile-roughness transmission system, an experiment for transmitting the perceived roughness of grating scales was conducted. as a result, the roughness perceived by the operators was found to highly correlate with the roughness of the scales in the slave-side environment with a coefficient of 0.83.
a magnetic type tactile sensor using a two-dimensional array of inductors. a novel tactile sensor based on electromagnetic induction that can detect slippage in addition to three-axis force is proposed. the structure of this sensor is simple, and the sensor, which is essentially a displacement gauge, consists of a two-dimensional array of inductors and an elastic body containing a permanent magnet. formulas to transform the output voltage of the proposed sensor into a force vector are derived, and analyses of both deformation of the proposed structure and magnetic field generated by a cylindrical permanent magnet are carried out to extract transformation parameters. in addition, it is shown that the sensor sensitivity can be designed using the aspect ratio of the cylindrical magnet. a prototype unit-cell of a tactile sensor is developed with four chip inductors, silicon gel as an elastic body and a neodymium magnet, and experiments are undertaken with a six-axis force/torque sensor as a reference. the contributions of inductors to sensor output are observed experimentally to be in agreement with analytical prediction and the reference sensor. experimental results show that the proposed tactile sensor is useful for three-axis force measurement and slip detection.
distributed maximum a posteriori estimation for multi-robot cooperative localization. this paper presents a distributed maximum a posteriori (map) estimator for multi-robot cooperative localization (cl). as opposed to centralized map-based cl, the proposed algorithm reduces the memory and processing requirements by distributing data and computations amongst the robots. specifically, a distributed data-allocation scheme is presented that enables robots to simultaneously process and update their local data. additionally, a distributed conjugate gradient algorithm is employed that reduces the cost of computing the map estimates, while utilizing all available resources in the team and increasing robustness to single-point failures. finally, a computationally efficient distributed marginalization of past robot poses is introduced for limiting the size of the optimization problem. the communication and computational complexity of the proposed algorithm is described in detail, while extensive simulation studies are presented for validating the performance of the distributed map estimator and comparing its accuracy to that of existing approaches.
measurement of grasp position by human hands and grasp criterion for two soft-fingered robot hands. in this study, grasp positions of human hands are measured for planar objects for development of a reasonable grasp criterion for a two-soft-fingered robotic hand. we first propose a grasp criterion that yields the best grasping position for a robot hand with two soft fingers. to examine the properties of this criterion with respect to some weighting coefficients included in the criterion, a grasping experiment is performed by humans for planar objects with various sizes and shapes. results show that many observed grasping positions used by humans correspond to a set of weighting coefficients that equally weigh all the factors in the criterion. a grasping experiment using a robot has also been conducted using a set of coefficients corresponding to the equal weight; the effectiveness of the criterion was confirmed.
simultaneous task subdivision and allocation for teams of heterogeneous robots. in this paper, we present a negotiation protocol for simultaneous task subdivision and allocation for heterogeneous multi-robot systems. an abstraction of the concept of task is presented that allows to apply the protocol on a variety of tasks. the negotiation adopts rubinstein's alternate offers protocol, where offers are evaluated and generated using a heuristic search step. the protocol has been tested on computer simulations.
pdac-based underactuated 3d bipedal walking - stabilization of pdac constants and walking direction control -. this paper proposes a three-dimensional biped dynamic walking algorithm based on passive dynamic autonomous control (pdac) which is previously proposed. the robot dynamics is modeled as an autonomous system of a three-dimensional inverted pendulum by applying the pdac concept that is based on the assumption of point contact of the robot foot and the virtual constraint as to robot joints. due to autonomy, there are two conservative quantities named "pdac constant", that determine the velocity and direction of the biped walking. we also propose the convergence algorithm to make pdac constant converge to arbitrary value, so that walking velocity and direction is controllable. numerical simulation results validate proposed algorithm.
iclqg: combining local and global optimization for control in information space. when a mobile robot does not have perfect knowledge of its position, conventional controllers can experience failures such as collisions because the uncertainty of the position is not considered in choosing control actions. in this paper, we show how global planning and local feedback control can be combined to generate control laws in the space of distributions over position, that is, in information space. we give a novel algorithm for computing "information-constrained" linear quadratic gaussian (iclqg) policies for controlling a robot with imperfect state information. the iclqg algorithm uses the belief roadmap algorithm to efficiently search for a trajectory that approximates the globally-optimal motion plan in information space, and then iteratively computes a feedback control law to locally optimize the global approximation. the iclqg algorithm is not only robust to imperfect state information but also scalable to high-dimensional systems and environments. in addition, iclqg is capable of answering multiple queries efficiently. we demonstrate performance results for controlling a vehicle on the plane and a helicopter in three dimensions.
mobile robots with active ir-optical sensing for remote gas detection and source localization. while other robots use in-situ measurements for gas leak detection and localization, we propose to apply remote sensing. it is easier and safer to conduct, permits rapid scans and is applicable to leak sources high up. an ir-optical sensor is used, exploiting spectral absorption effects of gases. tailored leak detection and localization strategies are proposed. a simulation environment with a 3d model of the gas concentration field is used for developing and testing the detection and localization strategies. the system performance is demonstrated in a case study with a chemical plant.
optimal camera placement for total coverage. in this document, we study the problem of optimally placing a mixture of directional and omnidirectional cameras. in our solution, the workspace is represented by an occupancy grid map [1]. then, using surface-projected workspace and camera perception models, we develop a binary integer programming algorithm. the results of the algorithm are applied successfully to a variety of simulated scenarios.
performing aggressive maneuvers using iterative learning control. this paper presents an algorithm to iteratively drive a system quickly from one state to another. a simple model which captures the essential features of the system is used to compute the reference trajectory as the solution of an optimal control problem. based on a lifted domain description of that same model an iterative learning controller is synthesized by solving a linear least-squares problem. the non-causality of the approach makes it possible to anticipate recurring disturbances. computational requirements are modest, allowing controller update in real-time. the experience gained from successful maneuvers can be used to significantly reduce transients when performing similar motions. the algorithm is successfully applied to a real quadrotor unmanned aerial vehicle. the results are presented and discussed.
laser-based navigation enhanced with 3d time-of-flight data. navigation and obstacle avoidance in robotics using planar laser scans has matured over the last decades. they basically enable robots to penetrate highly dynamic and populated spaces, such as people's home, and move around smoothly. however, in an unconstrained environment the two-dimensional perceptual space of a fixed mounted laser is not sufficient to ensure safe navigation. in this paper, we present an approach that pools a fast and reliable motion generation approach with modern 3d capturing techniques using a time-of-flight camera. instead of attempting to implement full 3d motion control, which is computationally more expensive and simply not needed for the targeted scenario of a domestic robot, we introduce a "virtual laser". for the originally solely laserbased motion generation the technique of fusing real laser measurements and 3d point clouds into a continuous data stream is 100% compatible and transparent. the paper covers the general concept, the necessary extrinsic calibration of two very different types of sensors, and exemplarily illustrates the benefit which is to avoid obstacles not being perceivable in the original laser scan.
helios carrier: tail-like mechanism and control algorithm for stable motion in unknown environments. mobile platforms when negotiating steps and stairs should be able to control theirs posture in order to avoid sudden tilting or falls. in particular, when considering applications for search and rescue operations where users have a very limited time of operation, the motion on stairs should be automated as much as possible. in this way operators can concentrate on their tasks (i.e. search of survivors and/or exploration of dangerous environments) rather than having to focus on the stability of the vehicle. a simple but very effective mechanism called "tail" is introduced. the mechanical design and its control method is presented together with several tests and experiments carried out with a simple tracked vehicle in real environments.
hand & eye-vergence dual visual servoing to enhance observability and stability. in this paper, we propose a new two-way visual servoing method, named as hand & eye-vergence visual servoing. this idea stems from animal's evolution history, predator have evolved their eye positions to be at the front face and their eyes turn to gaze at the target prey to be suited to triangulation, enhancing the ability to measure precisely the distance to the prey for catching it. this animal's visual tracking includes motion control by visual servoing and triangular eye vergence. our proposed method includes two loops: an outer loop for conventional visual servoing that direct a manipulator toward a target object and an inner loop for active motion of binocular camera for accurate and broad observation of the target object. the effectiveness of the hand & eye-vergence visual servoing is evaluated through simulations incorporated with actual dynamics of 7-dof robot on the view points of how the new idea improved the stability in visual servoing dynamics and the accuracy of hand pose.
flocking control of a mobile sensor network to track and observe a moving target. this paper presents a new approach to flocking control of a mobile sensor network to track a moving target. in our approach, the center of mass (com) of positions and velocities of all mobile sensors in the network (single-com) or the center of mass of position and velocity of each sensor and its neighbors (multi-com) is controlled to track and observe a moving target. in addition, we prove that the com of position and velocity exponentially converges to the moving target in free space. based on this approach, the target is kept at the center of the sensor network. this is of great advantage for sensors to track and observe the target for recognition or identification purposes. in addition, collision-free and velocity matching among mobile sensors are guaranteed in the whole process of the target tracking. we also investigate the stability of our algorithms. the numerical simulations are performed to demonstrate the proposed approach.
a numerical method for choosing motions with optimal excitation properties for identification of biped dynamics - an application to human. identification results dramatically depend on the excitation properties of the motion used to sample the identification model. strategies to define persistent exciting trajectories have been developed for manipulator robots with few dof. however they can not easily be extended to humanoid systems and humans due to the important number of dof; and empirical knowledge is often used to generate and select persistent exciting motions. in this paper we propose a method to choose persistent exciting motions from an existing dataset in order to optimize both the identification results and the computation time. this method is based on the use of the identification model of legged systems obtained from the base-link equations. instead of using well-established consideration on the condition number of the regressor matrix, the method uses a decomposition of the regressor into elementary subregressors and the computation of the condition number for each. a selection rule is then proposed. the overall method is experimentally tested to identify the human body inertial parameters using a data-set of 40 motions. comparative results obtained from different combinations of motions are given.
mixed reality simulation for mobile robots. mobile robots are increasingly entering the real and complex world of humans in ways that necessitate a high degree of interaction and cooperation between human and robot. complex simulation models, expensive hardware setup, and a highly controlled environment are often required during various stages of robot development. there is a need for robot developers to have a more flexible approach for conducting experiments and to obtain a better understanding of how robots perceive the world. mixed reality (mr) presents a world where real and virtual elements co-exist. by merging the real and the virtual in the creation of an mr simulation environment, more insight into the robot behaviour can be gained, e.g. internal robot information can be visualised, and cheaper and safer testing scenarios can be created by making interactions between physical and virtual objects possible. robot developers are free to introduce virtual objects in an mr simulation environment for evaluating their systems and obtain a coherent display of visual feedback and realistic simulation results. we illustrate our ideas using an mr simulation tool constructed based on the 3d robot simulator gazebo.
experiments with a zigbee wireless communication system for self-reconfiguring modular robots. the problem of designing reliable low-cost communications systems to support decentralized algorithms is a major research challenge in self-reconfiguring modular robotics. in this paper we evaluate a communication system based on zigbee, a wireless ad-hoc mesh networking standard. we present a 15-node system prototype and results from an experiment of 300 trials that measures system performance on a benchmark task. the benchmark we chose is the connectivity problem - how to maintain connectivity in the module graph during the disconnections and reconnections that occur during reconfiguration. we also provide full implementation details in pseudocode for our connectivity algorithm. our results show that, despite its inherent scalability limitations, a zigbee wireless system is feasible as a simple, low-cost communication system for self-reconfiguring modular robots.
reachability-guided sampling for planning under differential constraints. rapidly-exploring random trees (rrts) are widely used to solve large planning problems where the scope prohibits the feasibility of deterministic solvers, but the efficiency of these algorithms can be severely compromised in the presence of certain kinodynamics constraints. obstacle fields with tunnels, or tubes are notoriously difficult, as are systems with differential constraints, because the tree grows inefficiently at the boundaries. here we present a new sampling strategy for the rrt algorithm, based on an estimated feasibility set, which affords a dramatic improvement in performance in these severely constrained systems. we demonstrate the algorithm with a detailed look at the expansion of an rrt in a swingup task, and on path planning for a nonholonomic car.
a riemannian-geometry approach for dynamics and control of object manipulation under constraints. a riemannian-geometry approach for control and stabilization of dynamics of object manipulation under holonomic or non-holonomic (but pfaffian) constraints is presented. first, position/force hybrid control of an endeffector of a multijoint redundant (or nonredundant) robot under a nonholonomic constraint is reinterpreted in terms of "submersion" in riemannian geometry. a force control signal constructed in the image space spanned from the constraint gradient can be regarded as a lifting in the direction orthogonal to the kernel space. by means of the riemannian distance on the constraint submanifold, stability on a manifold for a redundant system under holonomic constraints is discussed. second, control and stabilization of dynamics of two-dimensional object grasping and manipulation by using a pair of multi-joint robot fingers are tackled, when a rigid object is given with arbitrary shape. then, it is shown that rolling contact constraint induce the euler equation of motion in an implicit function form, in which constraint forces appear as wrench vectors affecting on the object. the riemannian metric can be introduced in a natural way on a constraint submanifold induced by rolling contacts. a control signal called "blind grasping" is defined and shown to be effective in stabilization of grasping without using the details of information of object shape and parameters or external sensing. the concept of stability of the closed-loop system under constraints is renewed in order to overcome the degrees-of-freedom redundancy problem. an extension of dirichlet-lagrange's stability theorem to a system of dof-redundancy under constraints is presented by using a morse-lyapunov function.
probabilistic action planning for active scene modeling in continuous high-dimensional domains. in active perception systems for scene recognition the utility of an observation is determined by the information gain in the probability distribution over the state space. the goal is to find a sequence of actions which maximizes the system knowledge at low resource costs. most current approaches focus either on optimizing the determination of the payoff neglecting the costs or develop sophisticated planning strategies for simple reward models. this paper presents a probabilistic framework which provides an approach for sequential decision making under model and state uncertainties in continuous and high-dimensional domains. the probabilistic planner, realized as a partially observable markov decision process (pomdp), reasons by considering both, information theoretic quality criteria of probability distributions and control action costs. in an experimental setting an autonomous service robot uses active perception techniques for efficient object recognition in complex multi-object scenarios, facing the difficulties of object occlusion. due to the high demand on real time applicability the probability distributions are represented by mixtures of gaussian to allow fast, parametric computation.
encoding molecular motions in voxel maps. understanding life at the atomic level requires the development of new methodologies, able to overcome the limitations of available experimental and computational techniques for the analysis of processes involving molecular motions. with this goal in mind, we develop new methods, combining robotic path planning algorithms and molecular modeling techniques, for computing large-amplitude motions. this paper builds on these new methods, and introduces voxel maps as a computational tool to encode and to represent such motions. voxel maps can be used to represent relative motions of two molecules, as well as conformational changes in macromolecules. we investigate several applications and show results that illustrate the interest of such representation. in particular, voxel maps are used to display channels into proteins, to analyze protein-ligand specificity, and to represents protein loop and domain motions.
mechatronic design of a fast and long range 4 degrees of freedom humanoid neck. this paper describes the mechatronic design of a humanoid neck. to research human machine interaction, the head and neck combination should be able to approach the human behavior as much as possible. we present a novel humanoid neck concept that is both fast, and has a long range of motion in 4 degrees of freedom (dofs). this enables the head to track fast objects, and the neck design is suitable for mimicking expressions. the humanoid neck features a differential drive design for the lower 2 dofs resulting in a low moving mass and the ability to use strong actuators. the performance of the neck has been optimized by minimizing backlash in the mechanisms, and by using gravity compensation. two cameras in the head are used for scanning and interaction with the environment.
safe longitudinal platoons of vehicles without communication. this paper deals with the platooning problem that can be defined as the automatic following of a manned driven vehicle by a convoy of automatic ones. different approaches have been proposed so far. some require the localisation of each vehicle and a communication infrastructure, others called near-to-near approach only needs vehicle on-board sensors. however, to our knowledge, they do not provide any proof of non collision. we propose a novel near-to-near longitudinal platooning building a collision-free platooning whatever the number of vehicles. the model is derived from the study of the most dangerous interaction between two vehicles, i.e. considering the maximum acceptable acceleration when the previous vehicles brakes at maximum capacity. collision avoidance of this model is proved. finally, we show that this model can be combined to existing ones, keeping this collision-free property while allowing more various behaviors.
nonlinear, large-strain pzt actuators using controlled structural buckling. buckling is a highly nonlinear and singular phenomenon in thin beams, and is usually an undesired characteristic that must be prevented from occurring in engineered systems. buckling, however, can be a useful mechanism for gaining extremely large displacement amplification, since a tiny displacement in the axial direction of the beam may lead to a large defection in the middle of the beam. this paper presents a novel large-strain piezoelectric actuator exploiting the buckling of a structure with imbedded pzt stacks. although the free displacement of a pzt stack is only 0.1% of the stack length, the buckling mechanism, controlled with an effective algorithm and strategically placed redirecting stiffness, can produce a large bi-polar displacement that is approximately 150 times larger than the original pzt displacement. furthermore, the structural buckling produces a pronounced nonlinearity in output impedance; the effective stiffness viewed from the output port varies as a function of output displacement, which can be a useful property for those applications where actuator stiffness needs to vary.
a stochastically stable solution to the problem of robocentric mapping. this paper provides a novel solution for robocentric mapping using an autonomous mobile robot. the robot dynamic model is the standard unicycle model and the robot is assumed to measure both the range and relative bearing to the landmarks. the algorithm introduced in this paper relies on a coordinate transformation and an extended kalman filter like algorithm. the coordinate transformation considered in this paper has not been previously considered for robocentric mapping applications. moreover, we provide a rigorous stochastic stability analysis of the filter employed and we examine the conditions under which the mean-square estimation error converges to a steady-state value.
motion planning for a golf swing robot based on reverse time symmetry and pgctc control. a new golf swing robot performing high-speed golf swings has been developed by the authors. this paper deals with the motion planning problem of the golf swing. at first, the reverse time symmetry and single pendulum inherences in manipulator dynamics are introduced. then, by utilizing the first inherence, the rest-to-point motion planning problem for the backswing and downswing is transformed into a reverse time symmetric point-to-rest motion planning problem. finally, based on the second inherence, a proportional plus gravity and coupling torque compensation (pgctc) control scheme is developed to solve both the reverse time symmetric point-to-rest motion planning problem for the backswing and downswing and the forward time point-to-rest problem for the follow-through. simulation shows the effect of the proposed method.
development of a prosthetic arm: experimental validation with the user and an adapted software. in the world of upper limb prostheses, few companies propose different kinds of hand, wrist and elbow prostheses but their control is often difficult to understand by the patients. we have decided to develop new myoelectric prosthetic arm (elbow, wrist and hand) by axing our development on the use of new technologies and user centered design methodology. in this paper, we are explaining the different kinds of prostheses currently manufactured their advantages and their drawbacks. then, we explain our designing choices of the prosthesis and the movements it can realize. we detail the control chosen to simplify the use and the instrument of the product by the patient. in the last part, an adapted software is developed and used to validate experimentally the practice by the patient.
mouth gesture and voice command based robot command interface. in this paper we present a voice command and mouth gesture based robot command interface which is capable of controlling three degrees of freedom. the gesture set was designed in order to avoid head rotation and translation, and thus relying solely in mouth movements. mouth segmentation is performed by using the normalized a* component, as in [1]. the gesture detection process is carried out by a gaussian mixture model (gmm) based classifier. after that, a state machine stabilizes the system response by restricting the number of possible movements depending on the initial state. voice commands are modeled using a hidden markov model (hmm) isolated word recognition scheme. the interface was designed taking into account the specific pose restrictions found in the davinci assisted surgery command console.
dynamic stability of variable stiffness running. humans and animals adapt their leg impedance during running for both internal (e.g. loading) and external (e.g. surface) changes. in this paper we examine the relationship between leg stiffness and the speed and stability of dynamic legged locomotion. we utilize a torque-driven reduced-order model of running based on a successful family of running robots to show how optimal clock-driven controllers can interact with variably compliant limbs to adapt to changing operating conditions. we show that the leg stiffness adaptation gives, in general, better results than simply optimizing the gait controller and nearly as good as the co-optimization of controller and leg stiffness.
collision avoidance in dynamic environments: an ics-based solution and its comparative evaluation. this paper presents ics-avoid, a collision avoidance scheme based upon the concept of inevitable collision state (ics), ie a state for which, no matter what the future trajectory of the robotic system is, a collision eventually occurs. by design, ics-avoid can handle dynamic environments since ics do take into account the future behaviour of moving objects. ics-avoid is designed to keep the system away from ics. by doing so, motion safety is guranteed (by definition a robotic system in a non-ics state has at least one collision-free trajectory that it can use). to demonstrate the efficiency of ics-avoid, it has been extensively compared with two state-of-the-art collision avoidance schemes: the first one is built upon the dynamic window approach and the second one on the velocity obstacle concept. the results obtained show that, when provided with the same amount of information about the future evolution of the environment, ics-avoid outperforms the other two schemes. the first reason for this has to do with the extent to which each collision avoidance scheme reasons about the future. the second reason has to do with the ability of each collision avoidance scheme to find a safe control if one exists. ics-avoid is the only one which is complete in this respect thanks to the concept of safe control kernel.
localization with multi-modal vision measurements in limited gps environments using gaussian sum filters. a gaussian sum filter (gsf) with component extended kalman filters (ekf) is proposed as an approach to localize an autonomous vehicle in an urban environment with limited gps availability. the gsf uses vehicle relative vision-based measurements of known map features coupled with inertial navigation solutions to accomplish localization in the absence of gps. the vision-based measurements are shown to have multi-modal measurement likelihood functions that are well represented as a weighted sum of gaussian densities and the gsf is ideally suited to accomplish recursive bayesian state estimation for this problem. a sequential merging technique is used for gaussian mixture condensation in the posterior density approximation after fusing multi-modal measurements in the gsf to maintain mixture size over time. the representation of the posterior density with the gsf is compared over a common dataset against a benchmark particle filter solution. the expectation-maximization (em) algorithm is used offline to determine the representational efficiency of the particle filter in terms of an effective number of gaussian densities. the gsf with vision-based vehicle relative measurements is shown to remain converged using 37 minutes of recorded data from the cornell university darpa urban challenge (duc) autonomous vehicle in an urban environment that includes a 32 minute gps blackout.
imitation learning with generalized task descriptions. in this paper, we present an approach that allows a robot to observe, generalize, and reproduce tasks observed from multiple demonstrations. motion capture data is recorded in which a human instructor manipulates a set of objects. in our approach, we learn relations between body parts of the demonstrator and objects in the scene. these relations result in a generalized task description. the problem of learning and reproducing human actions is formulated using a dynamic bayesian network (dbn). the posteriors corresponding to the nodes of the dbn are estimated by observing objects in the scene and body parts of the demonstrator. to reproduce a task, we seek for the maximum-likelihood action sequence according to the dbn. we additionally show how further constraints can be incorporated online, for example, to robustly deal with unforeseen obstacles. experiments carried out with a real 6-dof robotic manipulator as well as in simulation show that our approach enables a robot to reproduce a task carried out by a human demonstrator. our approach yields a high degree of generalization illustrated by performing a pick-and-place and a whiteboard cleaning task.
a two-steps next-best-view algorithm for autonomous 3d object modeling by a humanoid robot. a novel approach is presented which aims at building autonomously visual models of unknown objects, using a humanoid robot. previous methods have been proposed for the specific problem of the next-best-view during the modeling and the recognition process. however our approach differs as it takes advantage of humanoid specificities in terms of embedded vision sensor and redundant motion capabilities. in a previous work, another approach to this specific problem was presented which relies on a derivable formulation of the visual evaluation in order to integrate it with our posture generation method. however to get rid of some limitations we propose a new method, formulated using two steps: (i) an optimization algorithm without derivatives is used to find a camera pose which maximizes the amount of unknown data visible, and (ii) a whole robot posture is generated by using a different optimization method where the computed camera pose is set as a constraint on the robot head.
semi-supervised particle filter for visual tracking. in this paper, a semi-supervised particle filter approach is proposed for visual tracking. the combination of semi-supervised learning and particle filter is very natural since the unlabelled samples are generated by particle propagation. in addition, the proposed semi-supervised particle filter can online select different features for robust tracking. to the best knowledge of the authors, this is the first time for the semi-supervised learning technology to be incorporated into the framework of particle filter. finally, the performance of the proposed approach is evaluated using real visual tracking examples.
adaptive output feedback control of uncertain nonholonomic systems with strong nonlinear drifts. in this paper, an adaptive output feedback control strategy is presented to solve the stabilization problem of nonholonomic systems in chained form with strong nonlinear drifts and uncertain parameters using output signals only. the control law is developed using input-state scaling and backstepping techniques. the objective is to design adaptive nonlinear output feedback laws which can steer the closed-loop systems globally converge to the origin, while the estimated parameters remain bounded. an adaptive output feedback controller is proposed for a class of uncertain chained systems. simulation results demonstrate the effectiveness of the proposed controllers.
information retrieval system for human-robot communication - asking for directions. the creation of a robot capable of navigating in unknown urban environments without the use of gps data or prior map knowledge is envisioned in the autonomous city explorer (ace) project. the robot has to retrieve direction information solely by interacting with humans. this work presents a human-robot communication system that enables the robot to ask for directions and store the retrieved route information as internal knowledge. the system incorporates theories from linguistics in a mixed-modalities communication interface. it stores acquired information into a topological route graph which is used to give feedback to the human and to navigate in unknown environments.
evaluation of 3d registration reliability and speed - a comparison of icp and ndt. to advance robotic science it is important to perform experiments that can be replicated by other researchers to compare different methods. however, these comparisons tend to be biased, since re-implementations of reference methods often lack thoroughness and do not include the hands-on experience obtained during the original development process. this paper presents a thorough comparison of 3d scan registration algorithms based on a 3d mapping field experiment, carried out by two research groups that are leading in the field of 3d robotic mapping. the iterative closest points algorithm (icp) is compared to the normal distributions transform (ndt). we also present an improved version of ndt with a substantially larger valley of convergence than previously published versions.
combining planning and motion planning. robotic manipulation is important for real, physical world applications. general purpose manipulation with a robot (eg. delivering dishes, opening doors with a key, etc.) is demanding. it is hard because (1) objects are constrained in position and orientation, (2) many non-spatial constraints interact (or interfere) with each other, and (3) robots may have multi-degree of freedoms (dof). in this paper we solve the problem of general purpose robotic manipulation using a novel combination of planning and motion planning. our approach integrates motions of a robot with other (non-physical or external-to-robot) actions to achieve a goal while manipulating objects. it differs from previous, hierarchical approaches in that (a) it considers kinematic constraints in configuration space (c-space) together with constraints over object manipulations; (b) it automatically generates high-level (logical) actions from a c-space based motion planning algorithm; and (c) it decomposes a planning problem into small segments, thus reducing the complexity of planning.
parallel-distributed model in three-dimensional soft-fingered grasping and manipulation. this paper focuses on three-dimensional grasping and manipulation by robotic fingers with soft fingertips. the authors have proposed two-dimensional parallel-distributed model of a soft fingertip to describe the dependency of its potential energy to the relative orientation between the fingertip and the object. here we extend the previous two-dimensional model to three-dimensional model, incorporating the rotation in three-dimensional space. we formulate the elastic potential energy stored in a soft fingertip due to the contact with the planar surface in three-dimensional space. we sketch the lagrangian of the system consisting of a rigid prism grasped by three fingers with soft fingertips.
active exploration using scheme of autonomous distribution for landmarks. this paper investigates the on-line autonomous distribution for landmarks and the active exploration in environment without or lack of landmarks/features, such as disaster conditions and polar region. in such situation, the robot enters the environment carrying some landmarks and distributes them according to the rules given in this paper. the utility of the landmark distribution is analyzed. then, based on the extended kalman filter (ekf), the active exploration is converted into a problem of multi-objective optimization, in which the objective function includes three aspects, i.e. the accuracy of localization and mapping, the predictive area of the unknown environment that will be explored in next step and the information gain provided by the distributed landmarks respectively. the robot chooses the control input that optimizes the objective function such that accurate localization, high-quality mapping and complete exploration will be realized. and then, the supplementation and the redundancy elimination for landmarks are implemented. at last, a set of simulations is presented to show the effectiveness of our approach.
task-space setpoint control of robots with dual task-space information. in conventional task-space control problem of robots, a single task-space information is used for the entire task. when the task-space control problem is formulated in image space, this implies that visual feedback is used throughout the movement. while visual feedback is important to improve the endpoint accuracy in presence of uncertainty, the initial movement is primarily ballistic and hence visual feedback is not necessary. the relatively large delay in visual information would also make the visual feedback ineffective for fast initial movements. due to limited field of view of the camera, it is also difficult to easure that visual feedback can be used for the entire task. therefore, the task may fail if any of the features is out of view. in this paper, we present a new task-space control strategy that allows the use of dual task-space information in a single controller. we shall show that the proposed task-space controller can transit smoothly from cartesian-space feedback at the initial stage to vision-space feedback at the end stage when the target is near.
morphological design optimization of kinematically redundant manipulators using weighted isotropy measures. kinematically redundant manipulators are coveted for their ability to perform more complex and a greater variety of tasks than their non-redundant counterparts. this increased utility demands that manipulator designs be carefully optimized to achieve the kinematic dexterity required to perform their numerous intended tasks. the optimization of redundant manipulator designs to improve isotropy has been studied at great length, but a vast majority of the work done focuses on planar manipulation tasks and workspaces that, unlike many modern manufacturing environments, offer few or no physical impediments to motion. in this paper we investigate the incorporation of secondary manipulation goals, in particular obstacle avoidance, into the calculation of kinematic isotropy measures. we will use these weighted isotropy measures as a performance metric for redundant manipulators working in obstacle-laden workspaces, and employ the metric as part of an objective function for a global search design optimization problem. the effectiveness of the weighted isotropy design optimization will be demonstrated by increasing the global dexterity of a sub-optimal seven degree-of-freedom manipulator design used for pick-and-place tasks within a small, enclosed workspace.
intelligent power management: promoting power-consciousness in teams of mobile robots. effective robotic autonomy requires an accurate estimation of the remaining power that the robot is carrying. there are a number of methods to estimate the remaining capacity of the robot's batteries. the accuracy of these approaches varies depending upon the chemical composition of the batteries as well as the means by which the monitoring is conducted. in this paper, an overview of various battery capacity estimation methodologies will be presented as well as a discussion of a specific implementation utilized on robotic platforms developed at the center for distributed robotics at the university of minnesota. this approach involves the novel use of fuel-gauging electronics for mobile robotic platforms. experiments were conducted to show the accuracy of this method for both charge and discharge of the polymer lithium-ion batteries in use.
local voronoi decomposition for multi-agent task allocation. we propose a local voronoi decomposition (lvd) algorithm which is able to perform a robust and online task allocation for multiple agents based purely on local information. because only local information is required in determining each agent's voronoi region, each agent can then make its decision in a distributive fashion based on its allocated voronoi region. these voronoi regions eliminates the occurrence of agents executing instantaneous overlapping tasks. as our method does not require a pre-processing of the map, it is also able to work well in a dynamically changing map with changing number of agents. we will show our proof of concept in the problem of exploration in an unknown environment. in our experimental evaluation, we show that our method significantly outperforms the competing algorithms: ants algorithm and the brick&mortar algorithm. our results also show that our method is near the theoretical best solution.
optimal control of a space manipulator for detumbling of a target satellite. robotic capture of a tumbling target-satellite means that the space robot's hand and the target grapple point arrive at a rendezvous point with the same velocity and then the chase vehicle mechanically connects into the target using a grapple device. this paper is focused on optimal control of the space manipulator in the postcapture phase so as to bring the tumbling non-cooperative satellite to rest in minimum time while ensuring that the magnitude of the interaction torque between the manipulator and target remains below a prescribed value. first, we seek fast detumbling maneuvers of the target satellite subjected to the torque restriction. the theory of optimal control and pontryagin's principle are applied to obtain a closed-form solution for the optimal path planning problem, giving a great deal of insight: the vector of the interaction torque is aligned opposite to the direction of the instantaneous angular momentum vector. second, a coordination control for combined system of the space robot and the target satellite, which acts as the manipulator payload, is developed so that the robot tracks the optimal path while regulating the attitude of the chase vehicle to a desired value. a preliminary illustrative example is appended.
planning and control of a teleoperation system for research in minimally invasive robotic surgery. this paper introduces the planning and control software of a teleoperation system for research in minimally invasive robotic surgery. it addresses the problem of how to organize a complex system with 41 degrees of freedom as a flexible configurable platform. robot setup planning, force feedback control and nullspace handling with three robotic arms are considered. the planning software is separated into sequentially executed planning and registration procedures. an optimal setup is first planned in virtual reality and then adapted to variations in the operating room. the real time control system is structured in hierarchical layers. functions are arranged in the layers with respect to their domain and maximum response time. the design is flexible and expandable while performance is maintained. structure, functionality and implementation of planning and control are described. the prototypic robotic system provides intuitive bimanual bilateral teleoperation within the planned working space.
robust edge extraction for swissranger sr-3000 range images. this paper presents a new method for extracting object edges from range images obtained by a 3d range imaging sensor--the swissranger sr-3000. in range image preprocessing stage, the method enhances object edges by using surface normal information; and it employs the hough transform to detect straight line features in the normal-enhanced range image (neri). due to the noise in the sensor's range data, a neri contains corrupted object surfaces that may result in unwanted edges and greatly encumber the extraction of linear features. to alleviate this problem, a singular value decomposition (svd) filter is developed to smooth object surfaces. the efficacy of the edge extraction method is validated by experiments in various environments.
ca: controlled conservative advancement for continuous collision detection of polygonal models. we present a simple and fast algorithm to perform continuous collision detection between polygonal models undergoing rigid motion for interactive applications. our approach can handle all triangulated models and makes no assumption about the underlying geometry and topology. the algorithm uses the notion of conservative advancement (ca), originally developed for convex polytopes [1], [2]. we extend this formulation to general models using swept sphere volume hierarchy and present a compact formulation to compute the motion bounds along with a novel controlling scheme. we have implemented the algorithm and highlight its performance on various benchmarks. in practice, our algorithm can perform continuous collision queries in few milli-seconds on models composed of tens of thousands of triangles.
model-reference based wave-variable force control. internal friction, backlash and structural compliance within a robot makes force control a tricky noncolocated control problem. traditional force controllers are typically tuned for a specific environment and invariably have instability problems when contacting stiffer environments. this paper presents a new force controller designed to use control effort to compensate for energy losses due to friction without modifying the robots underlying passive dynamics. the controller uses a lossless model of the robot's inertia to predict the robot's motion in real time based on the wave-variables flowing between robot and environment. the model motion is used as a desired input for a wave-variable based controller. to calculate the wave variables the controller uses measurements of both the contact force and the acceleration at the end-effector. the resulting controller is compared analytically and experimentally to more traditional controllers.
development of robot hand aiming at nursing care services to humans. this paper describes a multi-joint robot finger with soft compliant mechanism for safe and comfortable nursing-care services. in proposed mechanism, we utilize 2 different types of elastic elements at fingertip and mp joint (metacarpa-phalangeal joint), respectively, so as to realize soft and stable contact with human body. at fingertip, a hemisphere shaped silicone gum cushion is mounted, while eight cylindrical cushions are placed between the motor and the link inside mp joint. these cushions deform easily and, as a result, absorb external forces exerted from multiple directions. furthermore the amplitudes and the directions of applied forces can be estimated with the information of changes in the pressure of each cushion.we examined the fundamental characteristics and performance of this finger module through several experiments.
optimum design and investigation on diffuser polymethylmethacrylate (pmma) peristaltic micropumps. utilizing micro-electro-mechanical-systems (mems) techniques and a solvent-assisted bonding process, a new generation of diffuser peristaltic polymethylmethacrylate (pmma) micropumps was optimized and fabricated. the main purpose of this study is to compare the performance of optimized and un-optimized micopump which have the same diffuser throat/inlet area (i.e. 16000 µm2). furthermore, an additional optimized design which has smaller diffuser inlet area was considered to validate and analyze the effect of diffuser inlet area to the micropump performance. the experimental results were validated by comparing with previous generation which had not been optimized the diffuser element. specifically, the experimental results showed that, with similar diffuser element inlet area (i.e. 160000 µm2), with and without optimized micropumps yield maximum flow rates of 246.4 µl/min and 194.8 µl/min, respectively. furthermore, it is shown that the back pressure in the optimized micropump is 6.9 kpa, while that in the un-optimized pump is 5.69 kpa. the effect of diffuser element throat/inlet area to pump flow rate and back pressure was investigated by comparing the experimental results of two optimized designs, one with 80 µm × 80 µm and the other with 127 µm × 127 µm cross-sectional area. the results indicated that, the design with larger inlet area gave higher flow rate. however, the rate of reduction in the maximum flow rate with increasing backpressure increases at the higher inlet area design, which is due to the greater pressure dissipation/loss associated with a larger channel cross-sectional area.
accurate 3d ground plane estimation from a single image. accurate localization of landmarks in the vicinity of a robot is a first step towards solving the slam problem. in this work, we propose algorithms to accurately estimate the 3d location of the landmarks from the robot only from a single image taken from its on board camera. our approach differs from previous efforts in this domain in that it first reconstructs accurately the 3d environment from a single image, then it defines a coordinate system over the environment, and later it performs the desired localization with respect to this coordinate system using the environment's features. the ground plane from the given image is accurately estimated and this precedes segmentation of the image into ground and vertical regions. a markov random field (mrf) based 3d reconstruction is performed to build an approximate depth map of the given image. this map is robust against texture variations due to shadows, terrain differences, etc. a texture segmentation algorithm is also applied to determine the ground plane accurately. once the ground plane is estimated, we use the respective camera's intrinsic and extrinsic calibration information to calculate accurate 3d information about the features in the scene.
where to go: interpreting natural directions using global inference. an important component of human-robot interaction is that people need to be able to instruct robots to move to other locations using naturally given directions. when giving directions, people often make mistakes such as labelling errors (e.g., left vs. right) and errors of omission (skipping important decision points in a sequence). furthermore, people often use multiple levels of granularity in specifying directions, referring to locations using single object landmarks, multiple landmarks in a given location, or identifying large regions as a single location. the challenge is to identify the correct path to a destination from a sequence of noisy, possibly erroneous directions. in our work we cast this problem as probabilistic inference: given a set of directions, an agent should automatically find the path with the geometry and physical appearance to maximize the likelihood of those directions. we use a specific variant of a markov random field (mrf) to represent our model, and gather multi-granularity representation information using existing large tagged datasets. on a dataset of route directions collected in a large third floor university building, we found that our algorithm correctly inferred the true final destination in 47 out of the 55 cases successfully followed by humans volunteers. these results suggest that our algorithm is performing well relative to human users. in the future this work will be included in a broader system for autonomously constructing environmental representations that support natural human-robot interaction for direction giving.
simultaneous local and global state estimation for robotic navigation. recent applications of robotics often demand two types of spatial awareness: 1) a fine-grained description of the robot's immediate surroundings for obstacle avoidance and planning, and 2) knowledge of the robot's position in a large-scale global coordinate frame such as that provided by gps. although managing information at both of these scales is often essential to the robot's purpose, each scale has different requirements in terms of state representation and handling of uncertainty. in such a scenario, it can be tempting to pick either a body-centric coordinate frame or a globally fixed coordinate frame for all state representation. although both choices have advantages, we show that neither is ideal for a system that must handle both global and local data. this paper describes an alternative design: a third coordinate frame that stays fixed to the local environment over short time-scales, but can vary with respect to the global frame. careful management of uncertainty in this local coordinate frame makes it well-suited for simultaneously representing both locally and globally derived data, greatly simplifying system design and improving robustness. we describe the implementation of this coordinate frame and its properties when measuring uncertainty, and show the results of applying this approach to our 2007 darpa urban challenge vehicle.
multi-robot routing with linear decreasing rewards over time. we study multi-robot routing problems (mr-ldr) where a team of robots has to visit a set of given targets with linear decreasing rewards over time, such as required for the delivery of goods to rescue sites after disasters. the objective of mr-ldr is to find an assignment of targets to robots and a path for each robot that maximizes the surplus, which is defined to be the total reward collected by the team minus its total travel cost. we develop a mixed integer program that solves mr-ldr optimally with a flow-type formulation and can be solved faster than the standard tsp-type formulations but also show that solving mr-ldr optimally is np-hard. we then develop an auction-based algorithm and demonstrate that it solves mr-ldr in seconds and with a surplus that is comparable to the surplus found by the mixed integer program with a 12 hour time limit.
manipulation at the nanonewton level: micrograpsing for mechanical characterization of biomaterials. this paper presents the use of a monolithic, force-feedback mems (microelectomechanical systems) microgripper for characterizing both elastic and viscoelastic properties of highly deformable hydrogel microcapsules (15-25µm) at wet state during micromanipulation. the single-chip microgripper integrates an electrothermal microactuator and two capacitive force sensors, one for contact detection (force resolution: 38.5nn) and the other for gripping force measurements (force resolution: 19.9nn). through nanonewton force measurements, closed-loop force control, and visual tracking, the system quantified young's modulus values and viscoelastic parameters of alginate microcapsules, demonstrating an easy-to-operate, accurate compression testing technique for characterizing soft, micrometer-sized biomaterials.
robotic rehabilitation treatments: realization of aquatic therapy effects in exoskeleton systems. exoskeletons are attracting a great attention as a new means of rehabilitation devices. in such applications, control algorithms of exoskeletons are often inspired by nature for natural and effective assistance for patients. in this paper, a control algorithm is inspired by aquatic therapy. aquatic therapy has various benefits for rehabilitation processes based on useful properties of water, e.g. buoyancy and drag. however, realization of such effects is challenged by limitations in hardware, such as mechanical impedance or impreciseness of actuator forces. therefore, the resistive forces generated by actuators, which cause serious discomfort to patients, are precisely modeled and compensated to realize the control algorithm inspired by aquatic therapy effectively. the proposed methods are implemented in subar developed by sogang university and verified by experiments.
a harmonic potential field approach for navigating a rigid, nonholonomic robot in a cluttered environment. this paper demonstrates the ability of the harmonic potential field (hpf) planning approach to generate a provably-correct, constrained, well-behaved trajectory for a rigid, nonholonomic robot (a tractor-trailer robot is not rigid) in a stationary, cluttered environment. this is accomplished using a closed loop control scheme that is inspired by model predictive control (mpc). the scheme is realized using a synchronizing signal derived from the hpf along with a procedure for inverting the process the robot is using for actuating motion. performance proofs as well as simulation results of the suggested planner are supplied.
efficient and safe on-line motion planning in dynamic environments. this paper presents a new on-line planner for dynamic environments that is based on the concept of velocity obstacles (vo). it addresses the issue of motion safety, i.e. avoiding states of inevitable collision, by selecting a proper time horizon for the velocity obstacle. the proper choice of the time horizon ensures that the boundary of the velocity obstacle coincides with the boundary of the set of inevitable collision states. this time horizon is determined by the minimum time it would take the robot to avoid collision, either by stopping or by passing the respective obstacle. the planner generates a near-time optimal trajectory to the goal by selecting at each time step the velocity that minimizes the time-to-go and is out of the velocity obstacle. the planner takes into account the shape, velocity, and path curvature of the obstacle's trajectory. it is demonstrated for on-line motion planning in very crowded static and dynamic environments.
a harmonic potential field approach with a probabilistic space descriptor for planning in non-divisible environments. this paper extends the capabilities of the harmonic potential field approach to planning to cover the situation where the workspace of a robot cannot be segmented into geometrical subregions each having an attribute of its own. instead the suggested planner accepts a holistic, task-centered, probabilistic descriptor of the workspace as an input. this descriptor is processed along with a goal point to yield the navigation policy used to direct motion. the extension is based on the physical analogy with an electric current flowing in a nonhomogeneous conducting medium. proofs of the ability of the modified approach to avoid zero-probability (definite threat) regions and converge to the goal are provided. the capabilities of the suggested planner are demonstrated using simulation.
1-dof dynamic pitching robot that independently controls velocity, angular velocity, and direction of a ball: contact models and motion planning. this paper demonstrates that a 1-dof planar ball-throwing robot has the capability of controlling three kinematic variables of a ball independently: translational velocity, angular velocity, and direction. the throwing motion is modeled using two underactuated contact dynamics, called a finger-link contact model and a fingertip contact model, with a unidirectional transition from one model to another. a combination of a preliminary global search method and a search algorithm based on a simulated annealing (sa) algorithm provides joint torque commands for this highly nonlinear system. an experimental system with a 1-dof planer manipulator has been developed that throws a disk (ball) in a frictionless plane. the experimental results confirm the validity of the contact models and the feasibility of independent control of the three kinematic variables.
guiding medical needles using single-point tissue manipulation. this paper addresses the use of robotic tissue manipulation in medical needle insertion procedures to improve targeting accuracy and to help avoid damaging sensitive tissues. to control these multiple, potentially competing objectives, we present a phased controller that operates one manipulator at a time using closed-loop imaging feedback. we present an automated procedure planning technique that uses tissue geometry to select the needle insertion location, manipulation locations, and controller parameters. the planner uses a stochastic optimization of a cost function that includes tissue stress and robustness to disturbances. we demonstrate the system on 2d tissues simulated with a mass-spring model, including a simulation of a prostate brachytherapy procedure. it can reduce targeting errors from more than 2cm to less than 1mm, and can also shift obstacles by over 1cm to clear them away from the needle path.
design and synthesis of wire-actuated universal-joint wrists for surgical applications. this paper presents synthesis methods and performance measures for wire-actuated wrists using a universal-joint constraining linkage. performance measures based on the isotropy of the wrench-closure workspace are derived and used in generating design atlases as a function of non-dimensional design parameters. the performance indices that are optimized include wrench-closure workspace, isotropy of the wrench-closure workspace, and kinematic conditioning index. stiffness is used to define a safety margin from singularities of wrench closure. a design example of a wire-actuated surgical wrist is presented and validated through simulation. the methods presented in this paper are useful for quick dimensional synthesis of wire-actuated wrists with predefined wrench-closure workspaces.
active-learning assisted self-reconfigurable activity recognition in a dynamic environment. it is desirable to know a resident's on-going activities before a robot or a smart system can provide attentive services to meet real human needs. this work addresses the problem of learning and recognizing human daily activities in a dynamic environment. most currently available approaches learn offline activity models and recognize activities of interest on a real time basis. however, the activity models become outdated when human behaviors or device deployment have changed. it is a tedious and error-prone job to recollect data for retraining the activity models. in such a case, it is important to adapt the learnt activity models to the changes without much human supervision. in this work, we present a self-reconfigurable approach for activity recognition which reconfigures previously learnt activity models and infers multiple activities under a dynamic environment meanwhile pursuing minimal human efforts in relabeling training data by utilizing active-learning assistance.
tactile sensing for an anthropomorphic robotic hand: hardware and signal processing. in this paper, a tactile sensing system for an anthropomorphic robot hand is presented. the tactile sensing system is designed as a construction kit making it very versatile. the sensor data preprocessing is embedded into the hand's hardware structure and is fully integrated. the sensor system is able to gather tactile pressure profiles and to measure vibrations in the sensor's cover. additionally to the introduction of the hardware, the signal processing and the classification of the acquired sensor data will be explained in detail. these algorithms make the tactile sensing system capable to detect contact points, to classify contact patterns and to detect slip conditions during object manipulation and grasping.
airborne smoothing and mapping using vision and inertial sensors. this paper presents a framework for integrating sensor information from an inertial measuring unit (imu), global positioning system (gps) receiver and monocular vision camera mounted to a low-flying unmanned aerial vehicle (uav) for building large-scale terrain reconstructions. our method seeks to integrate all of the sensor information using a statistically optimal non-linear least squares smoothing algorithm to estimate vehicle poses simultaneously to a dense point feature map of the terrain. a visualisation of the terrain structure is then created by building a textured mesh-surface from the estimated point features. the resulting terrain reconstruction can be used for a range of environmental monitoring missions such as invasive plant detection and biomass mapping.
design methodologies of a hybrid actuation approach for a human-friendly robot. determining design parameters is often a challenging procedure, especially in human-friendly robot design due to competition between robot safety and performance. presenting an analytical model of hybrid actuation for human-friendly robot development, this paper proposes design methodologies to improve performance factors such as range of motion, payload, and acceleration while maintaining the safety factor of effective inertia. the optimized parameters for various design requirements have been provided for 1dof and 2dof applications. comparison between current design parameters and the optimized parameters for a current platform shows the performance improvement. in future work this research will be extended to systems with higher degrees of freedom.
automatic weight learning for multiple data sources when learning from demonstration. traditional approaches to programming robots are generally inaccessible to non-robotics-experts. a promising exception is the learning from demonstration paradigm. here a policy mapping world observations to action selection is learned, by generalizing from task demonstrations by a teacher. most learning from demonstration work to date considers data from a single teacher. in this paper, we consider the incorporation of demonstrations from multiple teachers. in particular, we contribute an algorithm that handles multiple data sources, and additionally reasons about reliability differences between them. for example, multiple teachers could be inequally proficient at performing the demonstrated task. we introduce demonstration weight learning (dwl) as a learning from demonstration algorithm that explicitly represents multiple data sources and learns to select between them, based on their observed reliability and according to an adaptive expert learning inspired approach. we present a first implementation of dwl within a simulated robot domain. data sources are shown to differ in reliability, and weighting is found impact task execution success. furthermore, dwl is shown to produce appropriate data source weights that improve policy performance.
on connectivity maintenance in linear cyclic pursuit. the paper studies the cyclic pursuit problem in presence of connectivity constraints among single-integrator agents. the robots, each one pursuing its leading neighbor along the line of sight rotated by a common offset angle, are supposed to have a communication set described by a disk of constant radius. given the initial position of the agents, we determine the communication radii that preserve the connectivity of the robots while they rendezvous at a point or converge to an evenly spaced circle formation. the special case that the initial condition is a linear combination of the eigenvectors of the dynamic matrix of the system, is studied in detail. on the other hand, given the communication radii, we find the set of initial conditions that guarantee the robots remain always connected. as a final contribution, once assigned a "non-optimal" radius, we study the stability of the hybrid system describing the dynamics of the robotic network under variable connectivity levels.
model adaptation with least-squares svm for adaptive hand prosthetics. the state-of-the-art in control of hand prosthetics is far from optimal. the main control interface is represented by surface electromyography (emg): the activation potentials of the remnants of large muscles of the stump are used in a nonnatural way to control one or, at best, two degrees-of-freedom. this has two drawbacks: first, the dexterity of the prosthesis is limited, leading to poor interaction with the environment; second, the patient undergoes a long training time. as more dexterous hand prostheses are put on the market, the need for a finer and more natural control arises. machine learning can be employed to this end. a desired feature is that of providing a pre-trained model to the patient, so that a quicker and better interaction can be obtained. to this end we propose model adaptation with least-squares svms, a technique that allows the automatic tuning of the degree of adaptation. we test the effectiveness of the approach on a database of emg signals gathered from human subjects. we show that, when pre-trained models are used, the number of training samples needed to reach a certain performance is reduced, and the overall performance is increased, compared to what would be achieved by starting from scratch.
sparsing of information matrix for practical application of a robot's slam. mobile robot could navigate in unknown environment autonomously with the help of simultaneous localization and mapping (slam). recently, slam based on information matrix enjoys much popularity since it is naturally sparse. however, the computational burden related to information matrix balloons with respect to the increase of the mapped landmarks. in this paper, by considering the features of information matrix, we present a novel method which wipes off nearly half of the elements in information matrix. the errors that come from sparsification decrease apparently by loop-closure. furthermore, the relationship between sparsification and slam accuracy is analyzed theoretically. a large scale simulation and experiment conducted on a real robot suggest that the technique is effective for a robot's slam in real-world applications.
multi-beam laser micromanipulation of microtool by integrated optical tweezers. in noncontact cell manipulation with optical tweezers, we need to use microtools to avoid damages to the cells by direct laser irradiation. when we manipulate complex structures such as microtools, a multi-beam optical tweezers which can manipulate multiple objects is suitable; however manipulation speed or trapping number are not so good. therefore, we developed an integrated optical tweezers by using time-shared scanning method for high speed manipulation and generalized phase contrast method for a lot of trapping. then, we proposed cell manipulation method which suits for the integrated optical tweezers and then we designed the shape of microtools made of su-8. a new fabrication method of su-8 microtools was proposed to improve productivity. at last, we made the experiment system and the effectiveness of proposed methods was confirmed.
towards a navigation system for autonomous indoor flying. recently there has been increasing research on the development of autonomous flying vehicles. whereas most of the proposed approaches are suitable for outdoor operation, only a few techniques have been designed for indoor environments. in this paper we present a general system consisting of sensors and algorithms which enables a small sized flying vehicle to operate indoors. this is done by adapting techniques which have been successfully applied on ground robots. we released our system as open-source with the intention to provide the community with a new framework for building applications for indoor flying robots. we present a set of experiments to validate our system on an open source quadrotor.
inferring a probability distribution function for the pose of a sensor network using a mobile robot. in this paper we present an approach for localizing a sensor network augmented with a mobile robot which is capable of providing inter-sensor pose estimates through its odometry measurements. we present a stochastic algorithm that samples efficiently from the probability distribution for the pose of the sensor network by employing rao-blackwellization and a proposal scheme which exploits the sequential nature of odometry measurements. our algorithm automatically tunes itself to the problem instance and includes a principled stopping mechanism based on convergence analysis. we demonstrate the favourable performance of our approach compared to that of established methods via simulations and experiments on hardware.
power modeling of a skid steered wheeled robotic ground vehicle. analysis of the power consumption of a robotic ground vehicle (rgv) is important for planning since it enables motion plans that do not violate the power limitations of the motors, energy efficient path planning, prediction of the ability to complete a task based upon the vehicle's current energy supply, and estimation of when the vehicle will need to refuel or recharge. power modeling is particularly difficult for skid steered vehicles because of the complexities of properly taking into account the skidding that is used for vehicle turning. this paper begins with a 2-dimensional, second order differential equation of a skid steered, wheeled rgv and shows that the power model is terrain dependent and is a function of both the turning radius and linear velocity of the vehicle. this model was verified experimentally, and a comprehensive set of experiments was performed to describe the power consumption of a skid steered rgv on asphalt.
a modified newton-euler method for dynamic computations in robot fault detection and control. we present a modified recursive newton-euler method for computing some dynamic expressions that arise in two problems of fault detection and control of serial robot manipulators, and which cannot be evaluated numerically using the standard method. the two motivating problems are: i) the computation of the residual vector that allows accurate detection of actuator faults or unexpected collisions using only robot proprioceptive measurements, and ii) the evaluation of a passivity-based trajectory tracking control law. the modified newton-euler algorithm generates factorization matrices of the coriolis and centrifugal terms that satisfy the skew-symmetric property. the computational advantages with respect to numerical evaluation of symbolically obtained dynamic expressions is illustrated on a 7r dlr lightweight manipulator.
statistically integrated semiotics that enables mutual inference between linguistic and behavioral symbols for humanoid robots. this paper describes the linguistic model based on symbolization of motion patterns for humanoid robots. the model consists of two kinds of stochastic models: the motion language model and the natural language model. the motion language model stochastically connects the symbols of motion patterns to the morpheme words through the latent states which represent the underlying linguistic structure such as semantic contents. the natural language model represents the dynamics of the word classes. the motion language model and the natural language model correspond to semantics and syntax respectively. the integration of the motion language model and the natural language model allows robots not only to linguistically interpret the motion patterns as sentences but also to generate the motions from the sentences. the two kinds of linguistic processes of the interpretation and the generation can be obtained by solving search problems: search for a sequence of morpheme words and a symbol of motion pattern. the proposed approach to interpretation of motion patterns as sentences and generation of motion patterns from the sentences through integration of the motion language model and the natural language model is validated by the experiment on the human behavioral data.
dynamic compensating controller for passive haptic manipulators in teleoperation. haptic devices allow a human user to physically interact with the virtual or simulated world by generating real forces to represent interactions in the virtual world. by definition, haptic devices exist in the set of robotic systems whose workspaces must overlap with the workspace of the human. for that reason, safety of the human becomes a central concern when developing both the physical hardware and the control systems for new and novel interfaces. passive haptic devices, ones that display forces to the user by using passive actuators such as brakes, clutches of continuously variable transmissions, address the concerns of stability and safety by using actuators that physically guarantee a bounded output and the safety of the human user. however, a device using passive actuators can only produce a subset of the forces generated by a similar device built around active actuators. the work presented here will explore the use of a passive haptic device specifically with respect to teleoperation and will present a new algorithm for determining feedback that improves the transparency, a dynamic compensating controller. this controller will be implemented in labview on passive hardware and will be compared to two simpler control schemes in two typical teleoperation tasks, shape identification and point to point motion around an obstacle. the results will show that the passive device provides feedback that allows the user to recognize large surface features. furthermore, results will show that the dynamic compensating controller proves especially useful in dynamic situations represented by the motion task.
design and control of underactuated tendon-driven mechanisms. many robotic hands or prosthetic hands have been developed in the last several decades, and many use tendon-driven mechanisms for their transmissions. robotic hands are now built with underactuated mechanisms, which have fewer actuators than degrees of freedom, to reduce mechanical complexity or to realize a biomimetic motion such as flexion of an index finger. the design is heuristic and it is useful to develop design methods for the underactuated mechanisms. this paper classifies mechanisms driven by tendons into three classes, and proposes a design method for them. the two classes are related to underactuated tendon-driven mechanisms, and these have been used without distinction so far. an index finger robot, which has four active tendons and two passive tendons, is developed and controlled with the proposed method.
relative bearing estimation from commodity radios. relative bearing between robots is important in applications like pursuit-evasion [11] and slam [7]. this is also true in sensor networks, where the bearing of one sensor node relative to another has been used for localization [5], [18], [20] and topology control [14], [21], [6]. most systems use dedicated sensors like an ir array or a camera to obtain relative bearing. we study the use of radio signal strength (rss) in commodity radios for obtaining relative bearing. we show that by using the robot's mobility, commodity radios can be used to obtain coarse relative bearing. this measurement can be used for a suite of applications that do not require very precise bearing measurement. we analyze signal strength variations in simulation and experiment and also show an algorithm that uses this coarse bearing computation in a practical setting.
wearable motion capture suit with full-body tactile sensors. this paper presents a system for capturing human movement and tactile data and methods for analyzing this data. we cannot fully capture the essence of motion without tactile information, and sometimes the lack of such information causes critical problems. to achieve a better understanding of motion behavior, we developed a wearable motion capture suit with full-body tactile sensors. we also developed a motion sensor which can estimate its orientation with its inner cpu. we also built a tactile sensor module which can fit many kinds of body shapes. with this system, we can measure a user's movement and tactile information simultaneously. by integrating tactile data with motion data, we can achieve many kinds of meaningful insights. we demonstrate the effectiveness of this system with experiments. we captured two motions: stretching after sitting on a chair and laying down on a bed. by recognizing the contact point from the tactile data and fitting it into the environment, we were able to estimate the motion trajectories.
efficient off-road localization using visually corrected odometry. we describe an efficient, low-cost, low-overhead system for robot localization in complex visual environments. our system augments wheel odometry with visual orientation tracking to yield localization accuracy comparable with "pure" visual odometry at a fraction of the cost. such a system is well-suited to consumer-level robots, small form-factor robots, extraterrestrial rovers, and other platforms with limited computational resources. our system also benefits high-end multiprocessor robots by leaving ample processor time on all camera-computer pairs to perform other critical visual tasks, such as obstacle detection. experimental results are shown for outdoor, off-road loops on the order of 200 meters. comparisons are made with corresponding results from a state-of-the-art pure visual odometer.
a virtual machine-based approach for fast and flexible reprogramming of modular robots. modular robot programming spans a number of issues ranging from high-level coordination to controller distribution and update in individual modules. the latter issue has received little attention from the research community though in our experience it is one of the main factors hindering agile development and experimentation with physical robots: reprogramming tens or hundreds of modules can be a major overhead in the development process and cannot be done with traditional approaches without restarting the robot, which impedes updating a running system. we propose a solution based on a virtual machine design shaped around three core concepts: the context of a module and its role in the ensemble, the reactive nature of robot controllers, and control programs decomposable into subparts that can be dynamically and separately redefined. we show that by incorporating those concepts into the design we are able to both achieve program conciseness (thus providing fast and efficient code distribution) and program expressiveness (thus providing versatility to represent diverse control algorithms). the virtual machine is programmed in a high-level role-oriented language that allows the programmer to declaratively specify how programs are deployed in the modular robot. our approach enables fast and incremental on-line updates, allowing the programmer to interactively experiment with the physical robots. we show how this design lends itself to an efficient implementation targeting typical resource-constrained modular robotic hardware by illustrating our prototype implementation for the atron self-reconfigurable robot.
path following for an omnidirectional mobile robot based on model predictive control. in this paper, the path following problem of an omnidirectional mobile robot has been studied. given the error dynamic model derived from the robot state vector and the path state vector, model predictive control (mpc) is employed to design the control law, which can deal explicitly with the rate of progression of a virtual vehicle to be followed along the path. the distinct advantage over other control strategies is that input and system constraints are able to be handled straight forwardly in the optimization problem so that the robot can travel safely with a high velocity. unlike nonholonomic mobile robots, omnidirectional mobile robots, which we focus on in this paper, have simultaneously and independently controlled rotational and translational motion capabilities. then, our purposed mpc controller was validated by experiments with a real omnidirectional mobile robot.
geo-contextual priors for attentive urban object recognition. mobile vision services have recently been proposed for the support of urban nomadic users. while camera phones with image based recognition of urban objects provide intuitive interfaces for the exploration of urban space and mobile work, similar methodology can be applied to vision in mobile robots and autonomous aerial vehicles. a major issue for the performance of the service - involving indexing into a huge amount of reference images - is ambiguity in the visual information. we propose to exploit geo-information in association with visual features to restrict the search within a local context. in a mobile image retrieval task of urban object recognition, we determine object hypotheses from (i) mobile image based appearance and (ii) gps based positioning, and investigate the performance of bayesian information fusion with respect to benchmark geo-referenced image databases (tsg-20, tsg-40). this work specifically proposes to introduce position information as geo-contextual priors for geo-attention based object recognition to better prime the vision task. the results from geo-referenced image capture in an urban scenario prove a significant increase in recognition accuracy (> 10%) when using the geo-contextual information in contrast to omitting geo-information, the application of geo-attention is capable to improve accuracy by further > 5%.
object inherent dynamics based motion control in human-robot cooperative task system. in this paper we address a robot motion control scheme for a human-robot cooperative task. from the viewpoint of improving the operative efficiency of the cooperative task, we designed a novel robot control system, in which inherent dynamics of the target task and the object is conserved. the proposed control scheme differs widely from an ordinary impedance control scheme in that the inherent dynamics of the target task and the object is substituted by impedance characteristics. under the proposed control scheme, the dynamics of the target task and that of the robot motion are uncoupled and independent. the proposed control system enables the human operator to carry out the cooperative task intuitively by only considering the inherent dynamics of the target task and the object. to confirm the effectiveness of the proposed control system, an experiment base on a peg insertion task involving human-robot cooperation is carried out. the experimental results show that the proposed control scheme is effective for cooperative tasks requiring precision.
the autonomous city explorer (ace) project - mobile robot navigation in highly populated urban environments. one of the greatest challenges nowadays in robotics is the advancement of robots from industrial tools to companions and helpers of humans, operating in natural, populated environments. in this respect, the autonomous city explorer (ace) project aims to combine the research fields of autonomous mobile robot navigation and human robot interaction. a robot has been created that is capable of navigating in an unknown, highly populated, urban environment, based only on information extracted through interaction with passers-by and its local perception capabilities. this paper describes the algorithms and architecture that make up the navigation subsystem of ace. more specifically, the algorithms used for simultaneous localization and mapping (slam), path planning in dynamic environments and behavior selection are presented, as well as the system architecture that integrates them to a complete working system. results from an extended field experiment, where the robot navigated autonomously through the downtown city area of munich, are analyzed and show that the robot is capable of long-term, safe navigation in real-world settings.
roadmap-based stealth navigation for intercepting an invader. this paper deals with the stealth target-interception problem based on the active prediction planning execution (appe) strategy. in order to cope with the evasive feature of the invader, we make the robot move stealthily by hiding behind obstacles. we adopt a roadmap-based decoupled approach, which plans the path and the trajectory separately by developing new concept; the detection map. simulation results demonstrate the efficiency of the proposed algorithm. it has an enough practical running time to be applied to the real-time situation.
design and implementation of a 9-axis inertial measurement unit. we report on a 9-axis inertial measurement unit (imu) which utilizes 3-axis angular velocity measurements from rate gyros and 6-axis linear acceleration measurements from three 2-axis accelerometers. this system is capable of deriving linear acceleration, angular acceleration and angular velocity via simple matrix operations, and it also releases the requirement of accelerometer installation at the center of mass as in the traditional imu. an optimal configuration of the system is proposed based on the analysis of rigid body dynamics and matrix theory. we performed error analyses, including position, orientation, and sensor noise, and we also report the results of experimental evaluation. we believe the analysis presented in this paper would benefit the practical design of imus in the future.
fir position profiles using an infinitely continuous kernel. large and fragile systems may require motion trajectories with the highest attainable degree of smoothness. this paper introduces a method to create infinitely continuous motion profiles based on convolving an infinitely continuous fir kernel with an underlying rate-limited position profile. conventional motion profiling is limited to blending polynomial between linear segments. due to the issues of controlling unwanted inflections and the computing of the polynomial coefficient, blending polynomials are usually limited to third order with special cases up to seventh order. beyond third order, closed form equations do not exists for the coefficients, requiring a set of equations to be solved for each blend. with third order polynomials the highest derivative that can be controlled is jerk. while maximum jerk can be controlled, change in jerk is instantaneous. this inherent instantaneous change in jerk can send shock waves though a system with the possibility of causing damage. the infinitely continuous profiles introduced in this paper overcomes all the shortcomings of polynomial blending. with fir smoothing of an underlying rate-limited position profile, only a single kernel is needed to be computed off-line before motion starts. the entire process of motion generation consists of rate-limiting desired position updates and then filtering them with an infinitely continuous fir kernel. the output is an infinitely continuous profile that allows real-time updates of velocity. two methods are introduced to create the kernels. in the first method the duration of the kernel is minimized for a given maximum value of any derivative. in the second method the maximum value of any derivative is minimized for a given kernel duration. the use of the convolution instead of polynomial fitting to create profiles is simpler, eliminates special cases, and allows real-time updates of velocity while producing maximally smooth profiles.
synchronous eeg brain-actuated wheelchair with automated navigation. this paper describes a new non-invasive brain-actuated wheelchair that relies on a p300 neurophysiological protocol and automated navigation. in operation, the subject faces a screen with a real-time virtual reconstruction of the scenario, and concentrates on the area of the space to reach. a visual stimulation process elicits the neurological phenomenon and the eeg signal processing detects the target area. this target area represents a location that is given to the autonomous navigation system, which drives the wheelchair to the desired place while avoiding collisions with the obstacles detected by the laser scanner. the accuracy of the brain-computer interface is above 94% and the flexibility of the sensor-based motion system allows for navigation in non-prepared and populated scenarios. the prototype has been validated with five healthy subjects in three experimental sessions: screening (an analysis of three different interfaces and its implications on the performance of the users), virtual environment driving (training and instruction of the users) and driving sessions with the wheelchair (driving tests along pre-established circuits). on the basis of the results, this paper reports a technical evaluation of the device and a variability study. all the users were able to successfully use the device with relative ease showing a great adaptation.
generic nonlinear model of reduced scale uavs. this paper proposes, through a survey of models of several uav-structures, a generic nonlinear model for reduced scale aerial robotic vehicles (6 dof). dynamics of an aircraft and some vtol uav (quadricopter, ducted fan and classical helicopter) are illustrated. this generic model focuses only on the key physical efforts acting on the dynamics in order to be sufficiently simple to design a controller. the small body forces expression which can introduce a zero dynamics is then discussed.
dynamic modeling and analysis of pitch motion of a basilisk lizard inspired quadruped robot running on water. a quadrupedal robot inspired by the basilisk lizard was developed and modeled with a 3-d real time simulation. due to the robot's geometry, leg motion, and water interactions, the net pitch moment at the center of mass is not zero making pitch motion unstable. this paper introduces two types of tails, passive and active, to stabilize pitch motion and analyzes the advantages and disadvantages of each. it is shown in simulation that a purely passive tail can stabilize pitch motion and lead to a steady state robot pitch angle in the absence of disturbances. it is further shown that an active tail can compensate for disturbances and correct any drift in the robot body pitch angle due to changes in robot running speed.
crawling by body deformation of tensegrity structure robots. in this paper, we describe the design of a deformable robot with a tensegrity structure that can crawl and we show the results of experiments showing the ability of these robots to crawl. we first describe a tensegrity structure, composed of struts and cables, and its characteristics. we next explain the principle of crawling by robot body deformation, followed by a classification of the methods by which a body can be deformed and the contact conditions of the robot through the cable-graph of the tensegrity structure. we also describe topological transition graphs that can visualize crawling from each initial contact condition. we then discuss the characteristics of the proposed robot in terms of design freedom. finally, we show experimentally that the prototype of a tensegrity robot can crawl.
attractiveeye: augmented gaze representation for "what is the robot looking at?". this paper describes a novel approach that can be used to determine the focal object that a robot is looking at and introduces the unique robotic eye, attractiveeye. humans have the visual input mechanism but do not have the output mechanism concerning the visual signal except gestures. attractiveeye can communicate information regarding the color of an object by changing its color to match that of the object. thus, from the color of this robot, we can determine the focal object that it is looking at. we carry out a human-robot interaction experiment to show that human-robot interaction can be made easier by using attractiveeye.
experimental validation of model-based thruster fault detection for underwater vehicles. this paper describes a model-based thruster fault detection scheme for an autonomous underwater vehicle. for a vehicle equipped with servo motor based marine thrusters, the velocity and current feedback from the motor controllers can be used to derive two independent thrust approximations. the difference between the two models reveals the presence of fault conditions, and quantifies the error of the output thrust relative to the desired reference. the method is proven effective through experimental validation.
design of man-machine cooperative nonholonomic two-wheeled vehicle based on impedance control and time-state control. this paper presents a new control methodology for a nonholonomic electric two-wheeled vehicle wherein the autonomous and man-machine cooperative controls are synthesized. in the proposed control scheme, the 'autonomous control' and the 'man-machine cooperative control' are designed by synthesizing time-state control and impedance control. the time-state controller tries to reduce the machine's deviation from the guideline, the impedance controller, on the other hand, generates power to assist the operator's maneuver. furthermore, experimental results are shown to demonstrate the usefulness of the proposed strategy.
muscle tension database for contact-free estimation of human somatosensory information. contact-free estimation of the human somatosensory information is an essential skill for robots working in daily environments. the main objective of this paper is to develop a method for estimating muscle tensions without any sensors attached to the body. muscle tension is an important information for evaluating physical load during motions. existing approaches utilizing optimization techniques and/or electromyography (emg) signals are not appropriate due to lack of physiological validity or usage of electrodes. in this paper, we propose to use a database of muscle tension distribution for obtaining physiologically realistic muscle tensions only from motion data. using such database instead of direct emg measurement is justified by the fact that muscle tension distribution is relatively highly correlated even among different subjects. for each new motion frame, we search for a similar entry in the database and use the corresponding muscle tension distribution to estimate the current muscle tensions. we demonstrate that the muscle tensions obtained by this approach is much closer to the result using the emg data than that using pure numerical optimization, even when the database is constructed from other person's data.
autonomous map construction using three-dimensional feature descriptors. autonomous robotic mapping has been an open research topic for more than twenty years. the primary objective of the robotic mapping problem is to design methods that can guide a robot around an environment and allow it to create a map of what has been sensed. most automatic mapping algorithms rely on robot pose estimation to fuse map data together. this paper demonstrates that through feature extraction using spin-histograms, the pose of the robot can be estimated accurately enough for an iterative closest point (icp) algorithm to register overlapping data sets. by eliminating consideration for points according to curvature and saliency, the spin-histogram matching process can improve in both accuracy and computation time. in combination with a global registration algorithm known as simultaneous matching, this process can obtain a fully autonomous registration process.
a parametric study of flapping wing performance using a robotic flapping wing. flapping wings have the potential to revolutionize the field of micro aerial vehicles (mavs), however the effect of flapping motion on the performance of such wings has not been studied in detail. this paper presents a parametric study of flapping wing propulsion, using two types of passive flapping wings and three flapping motions. each combination of wing type and flapping motion was tested over a range of amplitudes and frequencies ranging from 1.4-36° and 5-50 hz respectively. wing performance was evaluated by measuring lift force and mechanical efficiency for all tests. the performance of wing a was found to be significantly higher than wing b, with up to twice the maximum lift and efficiency. overall, wing a with the triangular flapping motion was found to be the most suitable for mavs. this research has the potential to significantly improve the performance of flapping wing propulsion, resulting in new capabilities and applications for mavs.
real-time correlative scan matching. scan matching, the problem of registering two laser scans in order to determine the relative positions from which the scans were obtained, is one of the most heavily relied-upon tools for mobile robots. current algorithms, in a trade-off for computational performance, employ heuristics in order to quickly compute an answer. of course, these heuristics are imperfect: existing methods can produce poor results, particularly when the prior is weak. the computational power available to modern robots warrants a re-examination of these quality vs. complexity trade-offs. in this paper, we advocate a probabilistically-motivated scan-matching algorithm that produces higher quality and more robust results at the cost of additional computation time. we describe several novel implementations of this approach that achieve real-time performance on modern hardware, including a multiresolution approach for conventional cpus, and a parallel approach for graphics processing units (gpus). we also provide an empirical evaluation of our methods and several contemporary methods, illustrating the benefits of our approach. the robustness of the methods make them especially useful for global loop-closing.
integration of active and passive compliance control for safe human-robot coexistence. in this paper we discuss the integration of active and passive approaches to robotic safety in an overall scheme for real-time manipulator control. the active control approach is based on the use of a supervisory visual system, which detects the presence and position of humans in the vicinity of the robot arm, and generates motion references. the passive control approach uses variable joint impedance which combines with velocity control to guarantee safety in worst-case conditions, i.e. unforeseen impacts. the implementation of these techniques in a 3-dof, variable impedance arm is described, and the effectiveness of their functional integration is demonstrated through experiments.
on efficiency and optimality of asymmetric dynamic bipedal gait. period-doubling bifurcation and chaotic behavior are interesting phenomena in limit cycle walking. their mechanisms are very complicated and their roles in dynamic biped locomotion are still unclear. this paper then investigates how the gait efficiency changes with the asymmetrization through analysis of a simple rimless wheel model. we mathematically show that the symmetric configuration gives the optimal solution when the mean value of the inter-leg angles is constant in terms of kinetic energy. this is derived from two magnitude relations of the energy-loss coefficient and restored mechanical energy. we also show that the symmetric gait is not always optimal from another viewpoint.
impedance control of redundant drive joints with double actuation. this paper proposes impedance control of redundant drive joints with double actuation (rdj-da) to produce compliant motions with the future goal of higher bandwidth. first, to reduce joint inertia, a double-input-single-output mechanism with one internal degree of freedom (dof) is presented as part of the basic structure of the rdj-da. next, the basic structure of rdj-da is further explained and its dynamics and statics are derived. then, the impedance control scheme of rdj-da to produce compliant motions is proposed and the validity of the proposed controller is investigated using numerical examples.
design of a rehabilitation device based on a mechanical link system. realizing an ideal impedance control system in lower extremity rehabilitation systems is challenged by mechanical impedance of robot hardware. although some studies in the field of control systems have been helpful in reducing the mechanical impedance of actuators, they have not been able to remove the inertia of robot hardware. this paper introduces an alternative design in which mechanical links are utilized. the mechanical links are driven by one actuator without any complicated servo systems. the design parameters are optimized for the link system to generate the normal walking motion. the simulation data shows that the normal gait patterns are realized successfully. the device is connected to a patient using elastic components, and therefore the inertia of the robot is not directly imposed on the patient. the patient's legs are guided to follow the motion of the robot with the forces generated by the elastic components.
multi-vehicle path coordination in support of communication. this paper presents a framework for generating time-optimal velocity profiles for a group of path-constrained vehicle robots that have fixed and known initial and goal locations and are required to maintain communication connectivity. each robot must follow a fixed and known path, arrive at its goal as quickly as possible (or at least not increase the time for the last robot to arrive at its goal) and stay in communication with other robots in the arena throughout its journey. the main contribution of this paper is the formulation of the problem as a discrete time nonlinear programming problem (nlp) with constraints on robot kinematics, dynamics, collision avoidance, and communication connectivity. we develop partition elimination constraints that assist in ensuring that the communication network is fully connected (no network partitions). these constraints are enforced only when network partitions would otherwise occur, an approach which significantly reduces the problem size and the required computational effort. in addition, we introduce path-constrained jammer robots with known paths and velocity profiles into the scenario. these jammer robots have an effective jamming range and disrupt all communications within this range. except for the jammers, all robots must remain outside this jamming range at all times. we investigate the scalability of the proposed approach by testing scenarios involving up to fifty (50) robots. solutions demonstrate (i) the trade off between the arrival time and the communication connectivity requirements in scenarios with and without jamming; and (ii) the dependence of computation time on the number of robots.
adaptive bayesian filtering for vibration-based terrain classification. outdoor robots are faced with a variety of terrain types each possessing different characteristics. to ensure a safe traversal a robot has to infer the current ground surface from sensor readings. recent techniques generate a model which predicts the terrain class from single vibration signals disregarding the temporal coherence between consecutive measurements. in this paper, we present a novel approach in which the final classification relies on the analysis of not only one, but several recent observations. therefore, the probabilistic framework of the bayes filter is adopted to the problem of terrain classification. we propose an adaptive approach which automatically adjusts its parameters according to the history of observations. to demonstrate the performance of our method we further describe and compare another technique based on temporal coherence. the evaluation using data collected from our rwi atrv-jr robot shows that our approach is both reactive and stable enough to detect fast terrain transitions and selective misclassifications.
automated 2-d nanoparticle manipulation with an atomic force microscope. atomic force microscope (afm) based nanomanipulation systems are generally slow, not repeatable and imprecise due to a lack of control on the success of limited attempts in the literature. to improve the amount of control, reliability and precision of such systems, this work proposes an automated nanomanipulation method. spherical gold nanoparticles with 100 nm diameter are positioned mechanically on a flat mica substrate by contact manipulation by the afm probe tip to a desired position autonomously. the most significant issue of the manipulation operation is the lack of real-time visual feedback. this issue is solved by developing a robust algorithm for particle center detection and using the afm cantilever deflection (force) signals to detect contact losses in real-time and to repeat the manipulation again until the target location is reached. using these solutions, an automated afm manipulation system is developed and a statistical study is made, where gold nanoparticles are positioned for 50 times to random target positions in different directions and pushing distances. 86% of all the particles could be successfully positioned to the target positions with an accuracy less than 100 nm. unsuccessful positioning operations are due to the particle sticking to either the tip (8%) or the substrate (6%). additionally, performance of the successful manipulations are investigated on 60 manipulation operations in 12 different directions and 5 different distances. the metrics used to quantify performance are the final particle position error and the average manipulation speed.
bayesian surprise and landmark detection. automatic detection of landmarks, usually special places in the environment such as gateways, for topological mapping has proven to be a difficult task. we present the use of bayesian surprise, introduced in computer vision, for landmark detection. further, we provide a novel hierarchical, graphical model for the appearance of a place and use this model to perform surprise-based landmark detection. our scheme is agnostic to the sensor type, and we demonstrate this by implementing a simple laser model for computing surprise. we evaluate our landmark detector using appearance and laser measurements in the context of a topological mapping algorithm, thus demonstrating the practical applicability of the detector.
humanoid robot lola. this paper presents our new 25-dof humanoid walking robot lola. the goal of our research is to realize a fast, human-like walking motion (target speed: 5 km/h). furthermore, we want to increase the robot's autonomous, vision-guided walking capabilities. the robot has 25 degrees of freedom, including 7-dof legs with actively driven toe joints. it is characterized by its lightweight construction, a modular, multi-sensory joint design with brushless motors and an electronics architecture using decentralized joint controllers. special emphasis was put on an improved mass distribution of the leg apparatus to achieve good dynamic performance. the sensor system comprises absolute angular sensors in all links, two custom-made force/torque sensors in the feet and a high-precision inertial sensor in the upper body. trajectory generation and control system aim at faster, more flexible, and more robust walking patterns.
exploiting angular momentum to enhance bipedal center-of-mass control. recent humanoid control investigations have emphasized the importance of controlling whole-body angular momentum throughout a movement task. for typical movement tasks, such as normal walking, such controllers minimize fluctuations in angular momentum about the center of mass (cm). this minimization is consistent with observed behavior of humans for such tasks. however, there are cases where such minimization is not desirable. in this study, we investigate movement tasks where bipedal balance control requires a relaxation of the goal of minimizing whole-body angular moment. we construct a humanoid model having a humanlike mass distribution, and a moment-exploiting control algorithm that modulates whole-body angular momentum to enhance cm control. the model only requires reference trajectories for cm position and torso orientation. joint reference trajectories are not required. while balancing on one leg, we show that the controller is capable of correcting errors in cm state by sacrificing angular postural goals for the swing leg, trunk and head. this prioritization capability provides robustness to significant disturbances, without the need to plan new reference trajectories. we compare the dynamic behavior of our humanoid model to that of human test participants. while standing on one leg, the model, like the human, is shown to reposition its cm just above the stance foot from an initial body state where cm velocity is zero, and the ground cm projection falls outside the foot envelope.
centralized fusion for fast people detection in dense environment. human beings do not have well defined shapes neither well defined behaviors. in dense outdoor environments, they are as a consequence hard to detect and algorithms based on a single sensor tend to produce lot of wrong detections. moreover, many applications require algorithms that work very fast on cpu limited mobile architectures while remaining able to detect, track and classify objects as people with a very high precision. we present an algorithm based on the contribution of a range finder and a vision based algorithm that addresses these three constraints: efficiency, velocity and robustness and that we believe is scalable to a large variety of applications.
an active anti-rollover device based on predictive functional control: application to an all-terrain vehicle. the active devices dedicated to on-road vehicle stability cannot be applied satisfactorily in an off-road context, since the variability and the non-linear features of grip conditions can no longer be neglected. specific solutions have then to be investigated. in this paper, the prevention of light all-terrain vehicle (atv) rollover is addressed. first, a backstepping observer is designed in order to estimate online a rollover indicator accounting for sliding phenomena, from a low-cost perception system. next, the maximum vehicle velocity, compatible with a safe motion over some horizon of prediction, is computed via predictive functional control (pfc), and can then be applied, if needed, to the vehicle actuator to prevent from rollover. the capabilities of the proposed device are demonstrated and discussed thanks to an advanced simulation testbed that has proved to supply results very close to experimental ones.
clothes state recognition using 3d observed data. in this paper, we propose a deformable-model-driven method to recognize the state of hanging clothes using three-dimensional (3d) observed data. for the task to pick up a specific part of the clothes, it is indispensable to obtain the 3d position and posture of the part. in order to robustly obtain such information from 3d observed data of the clothes, we take a deformable-model-driven approach[4], that recognizes the clothes state by comparing the observed data with candidate shapes which are predicted in advance. to carry out this approach despite large shape variation of the clothes, we propose a two-staged method. first, small number of representative 3d shapes are calculated through physical simulations of hanging the clothes. then, after observing clothes, each representative shape is deformed so as to fit the observed 3d data better. the consistency between the adjusted shapes and the observed data is checked to select the correct state. experimental results using actual observations have shown the good prospect of the proposed method.
contextual occupancy maps using gaussian processes. in this paper we introduce a new statistical modeling technique for building occupancy maps. the problem of mapping is addressed as a classification task where the robot's environment is classified into regions of occupancy and unoccupancy. our model provides both a continuous representation of the robot's surroundings and an associated predictive variance. this is obtained by employing a gaussian process as a non-parametric bayesian learning technique to exploit the fact that real-world environments inherently possess structure. this structure introduces a correlation between points on the map which is not accounted for by many common mapping techniques such as occupancy grids. using a trained neural network covariance function to model the highly non-stationary datasets, it is possible to generate accurate representations of large environments at resolutions which suit the desired applications while also providing inferences into occluded regions, between beams, and beyond the range of the sensor, even with relatively few sensor readings. we demonstrate the benefits of our approach in a simulated data set with known ground-truth, and in an outdoor urban environment covering an area of 120,000 m2.
controlling a robotically steered needle in the presence of torsional friction. a flexible needle can be accurately steered by robotically controlling the orientation of the bevel tip as the needle is inserted into tissue. here, we demonstrate the significant effect of friction between the long, flexible needle shaft and the tissue, which can cause a significant discrepancy between the orientation of the needle tip and the orientation of the base where the needle is controlled. our experiments show that several common phantom tissues used in needle steering experiments impart substantial frictional forces to the needle shaft, resulting in a lag of over 45° for a 10 cm insertion depth in some phantoms; clinical studies have reported torques large enough to could cause similar errors during needle insertions. such angle discrepancies will result in poor performance or failure of path planners and image-guided controllers, since the needles used in percutaneous procedures are too small for state-of-the-art imaging to accurately measure the tip angle. to compensate for the angle discrepancy, we develop a model for the rotational dynamics of a needle being continuously inserted into tissue and show how a pd controller is sufficient to compensate for the rotational dynamics.
a high performance 2-dof over-actuated parallel mechanism for ankle rehabilitation. this paper presents the mechanical design of an ankle rehabilitation robotic device based on a 2-dof, redundantly actuated parallel mechanism. the parallel mechanism introduced in this paper has the advantage of mechanical and kinematic simplicity when compared to existing platforms while at the same time it is fully capable of carrying out all the exercises required by ankle rehabilitation protocols. the proposed device makes use of actuation redundancy to eliminate singularity and greatly improve the workspace dexterity. in addition, the requirements for high torque capacity and back-drivability are satisfied with the employment of a custom made cable driven linear electric actuator that combines the high force capacity with excellent back-drivability. the analysis undergoes the optimal design towards the maximization of manipulator workspace, dexterity, torque output and compactness of the device. finally, the performance of the custom linear actuator and the prototype of the rehabilitation device are shown.
periosim: haptic virtual reality simulator for sensorimotor skill acquisition in dentistry. this paper describes a haptic simulator that has been developed as an aid for the sensorimotor skill acquisition in dentistry. an important feature of the simulator is the ability to generate templates of position and force trajectories for the students to follow. furthermore, the simulator has a mechanism, haptic playback, to help the students follow and learn these templates. using this feature, the teacher can perform a procedure in the haptic simulator and record her actions. the trainee is then able to observe the recorded procedure and follow the correct trajectory in the position and force. several haptic playback techniques are reviewed and the procedure implemented in the simulator is described in detail. we also describe hardware and software components of the simulator and their functionality.we conclude by describing the results of a preliminary classroom evaluation of the simulator.
practical visual odometry for car-like vehicles. a method for calculating visual odometry for ground vehicles with car-like kinematic motion constraints similar to ackerman's steering model is presented. by taking advantage of this non-holonomic driving constraint we show a simple and practical solution to the odometry calculation by clever placement of a single camera. the method has been implemented successfully on a large industrial forklift and a toyota prado suv. results from our industrial test site is presented demonstrating the applicability of this method as a replacement for wheel encoder-based odometry for these vehicles.
traversable path identification in unstructured terrains: a markov random walk approach. many terrains in outdoor robot navigation problems have paths that are distinct and continuous compared to the non-traversable regions. in image space these paths correspond to continuous segments that can be thought of as clusters embedded in image feature space. these segments very often translate directly to traversable ground plane. in this paper we build the intuition for semi-supervised methods in path identification and present a markov random walk based approach that requires very few labeled points. the method creates a nearest neighbor graph representation of the current image frame using features deemed suitable for the task and propagates labels based on the concept of absorbing markov chains. we extend this formalism to the task of dynamically identifying traversable and non-traversable regions in the incoming image frames. we present results on actual terrains corresponding to test courses used by the lagr test team. the results demonstrate that with minimal initial supervision the robot can navigate to the goal. we also conduct comparisons of our path labeling technique against other machine learning techniques including non-linear support vector machines on hand labeled data. the results demonstrate that our semi-supervised approach is proficient in the domain of path traversal in unstructured domains.
integration of the control electronics for a mm-sized autonomous microrobot into a single chip. microrobots were proposed more than 20 years ago but it has proven challenging to integrate a power system and actuators into some few mm3. there have been some attempts to create an autonomous mobile microrobot but any has been successful. moreover, the proposed microrobots were simply mobile platforms incapable of sensing its environment and taking decisions. i-swarm has been designed to be a real autonomous microrobot. it is powered by solar cells and provided with a locomotion unit for moving, an ir module for communicating and a contact tip for detecting near objects. those modules are managed by an asic designed specifically for i-swarm. all the electronics (power electronics, buffers, adcs, dacs, control unit, analog transducers and an oscillator) have been embedded in the asic due to the limited area, 3 × 3 mm2. the asic is a complete system on chip (soc) that has several features not reported before in any circuit for microrobots: communicate and act cooperatively with other i-swarm microrobots, detect near objects, measure distance to an object, light trailing and reprogramability. this paper gives some guidelines to design integrated circuits for microrobots.
automatic stimulation of experiments and learning based on prediction failure recognition. in this paper we focus on the task of automatically and autonomously initiating experimentation and learning based on the recognition of prediction failure. we present a mechanism that utilizes conceptual knowledge to predict the outcome of robot actions, observes their execution and indicates when discrepancies occur. we show how this mechanism was applied to a robot that learns using the paradigm of learning by experimentation, and present first results obtained from this implementation.
bilateral teleoperation with time delay using modified wave variable based controller. force-reflecting teleoperators in which the remote environment is kinesthetically coupled to the operator can considerably increase task performance. wave-variable-based controllers can support the stable operation of force-reflecting teleoperators under arbitrary communication delays. transparency in such systems is compromised in order to maintain stability. we had previously proposed a modified wave variable controller that implemented additional wave impedance in the wave variable transformations in order to focus more closely on force tracking. in this paper, we present a new controller for bilateral teleoperators based on the modified wave variable control method which provides superior position and force tracking performance compared to the traditional wave-variable-based method. moreover, the method has high stability. theoretical investigation and experimental results confirm the performance of this new controller.
vertical line matching for omnidirectional stereovision images. we are investigating the mobile robot indoor localization and environment mapping using an omnidirectional stereovision sensor. it uses four parabolic mirrors and an orthographic camera, giving four images of the same scene. at least, only two mirrors are needed. using four mirrors gives redundancy. we propose to exploit the images of vertical lines. this paper presents a new method in order to match these lines in the four images. contrary to existing approaches, we took into account the four sub-images existence in the design of this method, in order to exploit redundancy. this brought an original algorithm combining matching and pose estimation of vertical lines from the 3d environment. experimental results will be presented to validate this approach.
simultaneous localization of mobile robot and multiple sound sources using microphone array. sound source localization is an important function in robot audition. the existing works perform sound source localization using static microphone arrays. this work proposes a framework that simultaneously localizes the mobile robot and multiple sound sources using a microphone array on the robot. first, an eigenstructure-based generalized cross correlation method for estimating time delays between microphones under multi-source environments is described. a method to compute the far field source directions as well as the speed of sound using the estimated time delays is proposed. in addition, the correctness of the sound speed estimate is utilized to eliminate spurious sources, which greatly enhances the robustness of sound source detection. the arrival angles of the detected sound sources are used as observations in a bearings-only slam procedure. as the source signals are not persistent and there is no identification of the signal content, data association is unknown which is solved using fastslam. the experimental results demonstrate the effectiveness of the proposed approaches.
characterization of bacterial actuation of micro-objects. in recent years, flagellar motors of bacteria have not only inspired design of an entirely new category of microrobots, they have also been interfaced with synthetic components and used for controlled actuation of microscale objects. the ultimate goal of these efforts is to develop bio-hybrid swimming micro-robots which use bacteria for actuation, control, and sensing. as bacteria begin to become an integral part of microscale engineered systems, there is a great need for characterizing their performance and understanding the forces involved in interfacing them with synthetic components. in this work repeatability and endurance (performance as a function of time) of an ensemble of bacteria used for actuation of 10 µm polystyrene micro-beads are characterized. moreover, a series of adhesion assay methods are introduced and used to determine the strength and timeline of adhesion of serratia marcescens (s. marcescens) bacteria to hydrophobic and hydrophilic polystyrene surfaces.
on-chip detection and separation of micro-particles using magnetized microtools driven by focused magnetic field. we succeeded in powerful noncontact actuation of magnetically driven microtool (mmt) by magnetizing it and focusing magnetic field in a microfluidic chip. novelty of this paper is summarized as follows. (1) we employed neodium powder as the main component of mmt. the density of magnetic flux was improved about 100 times larger after magnetization. (2) we fabricated a pair of magnetic sharp needles in the chip by electroplating. mmt was placed between the needles and the density of magnetic flux was improved about 3 times larger. as a result, we succeeded in powerful actuation of mmt in a chip. drive frequency was improved about 10 times faster (up to 180 hz). we applied it for sorting of copolymer beads in a chip. mmt is put in the microchannel. the size of the bead was measured by image processing (15 hz). moving frequency of the mmt was made higher than the sampling frequency of measurement and secure sorting was achieved.
real-time positioning and tracking technique for endovascular untethered microrobots propelled by mri gradients. a real-time positioning and tracking technique for untethered devices or robots magnetically propelled by a clinical magnetic resonance imaging (mri) system is described. the local magnetic field induced by the device, composed of a ferromagnetic material, is used as a signature to localize the device on three one-dimensional projections. a high-precision 3d circular-motion system was used to assess the precision and accuracy of this method. the integration of this technique inside propulsion and imaging mri sequences was also achieved to demonstrate the feasibility of this tracking scheme in a closed-loop control scheme. finally, in vivo tracking during automatic navigation of an untethered device in the carotid artery of a living animal is demonstrated.
generating robot/agent backchannels during a storytelling experiment. this work presents the development of a real-time framework for the research of multimodal feedback of robots/talking agents in the context of human robot interaction (hri) and human computer interaction (hci). for evaluating the framework, a multimodal corpus is built (enterface stead), and a study on the important multimodal features was done for building an active robot/agent listener of a storytelling experience with humans. the experiments show that even when building the same reactive behavior models for robot and talking agents, the interpretation and the realization of the behavior communicated is different due to the different communicative channels robots/agents offer be it physical but less human-like in robots, and virtual but more expressive and human-like in talking agents.
fabrication and feedback control of an articulated microarm. as cancer becomes the no.1 cause of the death in japan, endoscopic surgery is gaining attentions. in this paper, endoscopical tool to grip and lift the targeted tumor in esd (endoscopic submucosal dissection) surgery is proposed. this articulated microarm is part of new esd surgery concept in which two wire-driven microarms (1 × 1 × 25 mm) from the tip of the endoscope help lift the tumor to cut. this research needs to emphasize a new fabrication method of arm which is fabricated by photolithography and electroplating. the microarm is composed of five layers. individual layers are fabricated separately and assembled together in the end. the microarm uses the elastic deformation of metal to bend (cu or phosphor bronze). it is feedback control with pid using a strain gauge attached to the articulated joint. this technique enabled the further miniaturization of the microarm, but it also comes with a downside. it is difficult to build a 3-dimensional structure. we overcame this problem by proposing an assembly method (stamp: stacked microassembly process). electroplated layers are assembled by stacking up on top of each other. this assembly process is feasible to produce multiple microarms at one assembly, thus mass-production with low cost is possible. a strain gauge is attached to the elastic joint as an angle sensor.
development of a climbing robot for grit blasting operations in shipyards. this paper deals with the design and construction of a climbing robot for performing grit blasting operations in shipyards. the robot is based on a double sliding platform that uses permanent magnets for attachment. it is lightweight and compact and can move up and along the shipside with any inclination while grit blasting the surface to pre-specified surface quality levels. it can also rotate to compensate for hull curvature and to avoid obstacles while performing its task. the blasting operation is modulated by a vision based quality control system that is used by the mission control system to adapt the blasting parameters in order to attain the desired quality levels while maximizing the surface area the robot strips per unit time.
dynamic estimation of homography transformations on the special linear group for visual servo control. in the last decade, many vision-based robot controllers have been designed using cartesian information encoded in the homography transformation that links two images of a planar object. for any approach, the performance of the closed-loop system depends on the quality of the homography estimates obtained. in this paper, we exploit the special linear lie-group structure of the set of all homographies to develop a dynamic observer to estimate homographies on-line. the resulting estimates are effective and can be used to improve closed-loop response of several visual servoing algorithms.
consistent cooperative localization. in cooperative navigation, teams of mobile robots obtain range and/or angle measurements to each other and dead-reckoning information to help each other navigate more accurately. one typical approach is moving baseline navigation, in which multiple autonomous underwater vehicles (auvs) exchange range measurements using acoustic modems to perform mobile trilateration. while the sharing of information between vehicles can be highly beneficial, exchanging measurements and state estimates can also be dangerous because of the risk of measurements being used by a vehicle more than once; such data re-use leads to inconsistent (overconfident) estimates, making data association and outlier rejection more difficult and divergence more likely. in this paper, we present a technique for the consistent cooperative localization of multiple auvs performing mobile trilateration. each auv establishes a bank of filters, performing careful bookkeeping to track the origins of measurements and prevent the use any of the measurements more than once. the multiple estimates are combined in a consistent manner, yielding conservative covariance estimates. the technique is illustrated using simulation results. the new method is compared side-by-side with a naive approach that does not keep track of the origins of measurements, illustrating that the new method keeps conservative covariance bounds whereas state estimates obtained with the naive approach become overconfident and diverge.
a dynamic programming approach to multi-level supervision. using dynamic programming (dp), this paper presents a multi-level supervisory control implementation in the standard hierarchical discrete-event control framework. for a class of hierarchically consistent discrete-event systems, the dp algorithm developed implements a multi-level nonblocking controller with reduced off-line complexity of control synthesis and increased on-line transparency of control operations. an example illustrates the on-line control operations of the algorithm.
tracking of facial features to support human-robot interaction. in this paper we present a novel methodology for detection and tracking of facial features like eyes, nose and mouth in image sequences. the proposed methodology is intended to support natural interaction with autonomously navigating robots that guide visitors in museums and exhibition centers and, more specifically, to provide input for the analysis of facial expressions that humans utilize while engaged in various conversational states. for face and facial feature region detection and tracking, we propose a methodology that combines appearance-based and feature-based methods for recognition and tracking, respectively. for the stage of face tracking the introduced method is based on least squares matching (lsm), a matching technique able to model effectively radiometric and geometric differences between image patches in different images. thus, compared with previous research, the lsm approach can overcome the problems of variable scene illumination and head in-plane rotation. another significant characteristic of the proposed approach is that tracking is performed on the image plane only wherever laser range information suggests so. the increased computational efficiency meets the real time demands of human-robot interaction applications and hence facilitates the development of relevant systems.
comparison of local image descriptors for full 6 degree-of-freedom pose estimation. recent years have seen advances in the estimation of full 6 degree-of-freedom object pose from a single 2d image. these advances have often been presented as a result of, or together with, a new local image descriptor. this paper examines how the performance for such a system varies with choice of local descriptor. this is done by comparing the performance of a full 6 degree-of-freedom pose estimation system for fourteen types of local descriptors. the evaluation is done on a database with photos of complex objects with simple and complex backgrounds and varying lighting conditions. from the experiments we can conclude that duplet features, that use pairs of interest points, improve pose estimation accuracy, and that affine covariant features do not work well in current pose estimation frameworks. the data sets and their ground truth is available on the web to allow future comparison with novel algorithms.
aerodynamics and control of autonomous quadrotor helicopters in aggressive maneuvering. quadrotor helicopters have become increasingly important in recent years as platforms for both research and commercial unmanned aerial vehicle applications. this paper extends previous work on several important aerodynamic effects impacting quadrotor flight in regimes beyond nominal hover conditions. the implications of these effects on quadrotor performance are investigated and control techniques are presented that compensate for them accordingly. the analysis and control systems are validated on the stanford testbed of autonomous rotorcraft for multi-agent control quadrotor helicopter testbed by performing the quadrotor equivalent of the stall turn aerobatic maneuver. flight results demonstrate the accuracy of the aerodynamic models and improved control performance with the proposed control schemes.
mobility reconfiguration for terrain exploration using passive perception. the ability of robotic units to autonomously navigate various terrains is critical to the advancement of robotic operation in natural environments. next generation robots will need to adapt to their environment in order to accomplish tasks that are either too hazardous, too time consuming, or physically impossible for human-beings. such tasks may include accurate and rapid explorations of various planets or potentially dangerous areas on earth. furthermore, because terrain variability typically increases as the distance that a rover traverses increases, it will be beneficial for robotic units to adapt to their surroundings. as a result, this research investigates a navigation control methodology for a multi-modal locomotive robot based upon passive perception. surface estimation for robot reconfigurability is implemented using a region growing method, which characterizes the traversability of the terrain, in conjunction with passive perception regarding motion. a mathematical approach is then implemented that inherits human psychological aspects to direct necessary navigation behavior to control robot mobility. physical experimentations in a simulated mars yard are presented to validate the methodology.
leader-follower formation control of underactuated auvs with leader position measurement. in this paper, we investigate the leader-follower formation control of underactuated autonomous underwater vehicles (auvs). by using position measurements from the leader, we design a virtual vehicle such that the trajectory of the virtual vehicle converges to the reference trajectory of the follower. a position tracking control is designed for the follower to track the virtual vehicle using lyapunov and backstepping synthesis. simulation results demonstrated the effectiveness of the proposed scheme.
design and development of a low-cost flexure-based hand-held mechanism for micromanipulation. this paper presents a 3-dof low-cost hand-held micromanipulator driven by 3 piezoelectric actuators and built using rapid prototyping. traditional pin and ball joints have been commonly replaced by flexure-based methods in the field of micromanipulation. utilization of flexure-based joints have several advantages like the non-existence of backlash and assembly errors. however, most of the present flexure-based mechanisms are bulky and not suitable for hand-held applications. it is difficult and expensive to make such compact mechanism using traditional machining methods. in additional, traditional machining methods are limited to simple design. to reduce the cost of fabrication and also to allow more complex designs, objet (a rapid prototyping machine) is proposed to be used to build the mechanism. with regards to hand-held applications, the size of the mechanism is a constraint. hence, a parallel manipulator design is the preferred choice as compared to a serial mechanism because of its rigidity, compactness, and simplicity in design. for the illustration of an application, the mechanism is designed with an intraocular needle attached to it. possible applications of this design include enhancement of performance in microsurgery and cell micromanipulation. experiments are also conducted to evaluate the manipulator's tracking performance of the needle tip at a frequency of 10hz.
quantitative assessment of the surgical training methods with the suture/ligature training system wks-2rii. the emerging field of medical robotics is aiming in introducing intelligent tools to perform medical procedures. in particular, robotic researchers have been proposed advanced medical training systems to enhance motor dexterities of trainees. an efficient medical training system should be designed to simulate real-world conditions and to assure their effectiveness as the representation of the motor skills often differs among trainees. up to now, several training simulators have been developed by medical companies designed to reproduce with high fidelity the human body. however, such devices are not designed to provide any information to trainees. therefore, we have proposed the development of a patient robot which embeds sensors and actuators into a conventional human model. due to its complexity, as a first approach; we are presenting the development of a suture training system designed to simulate the real-world task conditions as well as providing quantitative assessments. in particular; the waseda-kyotokagaku suture no.2 refined ii is presented, which includes a new evaluation function to provide more detailed information of the task. a set of experiments were proposed to analyze the performance of trainees. from the experimental results, we could confirm its effectiveness to detect differences of the performance of trainees.
a nonlinear observer for 6 dof pose estimation from inertial and bearing measurements. this paper considers the problem of estimating pose from inertial and bearing-only vision measurements. we present a non-linear observer that evolves directly on the special euclidean group se(3) from inertial measurements and bearing measurements, such as provided by a visual system tracking known landmarks. local asymptotic convergence of the observer is proved. the observer is computationally simple and its gains are easy to tune. simulation results demonstrate robustness to measurement noise and initial conditions.
the role of small redundant actuators in precise manipulation. with the goal of developing humanlike dextrous manipulation, we investigate how the central nervous system uses the redundant control space of the human hand to perform tasks with force-stiffness requirements. specifically, while the human hand is actuated by several muscles with varying mechanical advantage (called the moment arm), it is unclear how each muscle is used. using the anatomically correct testbed (act) robotic hand to compute the control solution space and human-subject experiments with surface electromyography to measure biological control strategy, we identified that there is significant redundancy in the control spaces of both muscles with large moment arms and muscles with small moment arms. however, the central nervous system was selective about the solution for muscles with large moment arms, while it chose to span large regions of the available control space for muscles with small moment arms. furthermore, the biological solution used low-moment-arm muscles at relatively high actuation levels. we summarize by making inferences on why the central nervous system chooses such a strategy and how this can help robotic manipulation.
global vector field computation for feedback motion planning. we present a global vector field computation algorithm in configuration spaces for smooth feedback motion planning. our algorithm performs approximate cell decomposition in the configuration space and approximates the free space using rectanguloid cells. we compute a smooth local vector field for each cell in the free space and address the issue of the smooth composition of the local vector fields between the non-uniform adjacent cells. we show that the integral curve over the computed vector field is guaranteed to converge to the goal configuration, be collision-free, and maintain c∞ smoothness. as compared to prior approaches, our algorithm works well on non-convex robots and obstacles. we demonstrate its performance on planar robots with 2 or 3 dofs, articulated robots composed of 3 serial links and multi-robot systems with 6 dofs.
safe robot arm with safe joint mechanism using nonlinear spring system for collision safety. collision safety between humans and robots has drawn much attention since service robots are increasingly being used in human environments. a safe robot arm based on passive compliance can usually provide faster and more reliable responses for dynamic collision than an active one involving sensors and actuators. since both positioning accuracy and collision safety of the robot arm are equally important, a robot arm should have very low stiffness when subjected to a collision force greater than the injury tolerance, but should otherwise maintain very high stiffness. to implement these requirements, a novel safe joint mechanism (sjm-ii) which has much smaller size and lighter weight than the previous model, is proposed in this research. the sjm-ii has the advantage of nonlinear spring which is achieved using only passive mechanical elements such as linear springs and a double-slider mechanism. various analyses and experiments on static and dynamic collisions show that stiffness of the sjm-ii is kept very high against an external torque less than the predetermined threshold torque, but abruptly drops when the input torque exceeds this threshold, thereby guaranteeing positioning accuracy and collision safety. furthermore, a robot arm with two sjm-iis is verified to achieve collision safety in 2d space.
learning sound location from a single microphone. we consider the problem of estimating the incident angle of a sound, using only a single microphone. the ability to perform monaural (single-ear) localization is important to many animals; indeed, monaural cues are also the primary method by which humans decide if a sound comes from the front or back, as well as estimate its elevation. such monaural localization is made possible by the structure of the pinna (outer ear), which modifies sound in a way that is dependent on its incident angle. in this paper, we propose a machine learning approach to monaural localization, using only a single microphone and an "artificial pinna" (that distorts sound in a direction-dependent way). our approach models the typical distribution of natural and artificial sounds, as well as the direction-dependent changes to sounds induced by the pinna. our experimental results also show that the algorithm is able to fairly accurately localize a wide range of sounds, such as human speech, dog barking, waterfall, thunder, and so on. in contrast to microphone arrays, this approach also offers the potential of significantly more compact, as well as lower cost and power, devices for sounds localization.
design and calibration of a microfabricated 6-axis force-torque sensor for microrobotic applications. this work describes the design of a capacitive multi-axis force-torque sensor for the monitoring of forces in the sub-milli-newton and sub-micro-newtonmeter range. this force range makes it a valuable tool for microrobotic applications. the sensor is experimentally investigated and calibrated. this is the first microfabricated 6-axis force-torque sensor that has been successfully developed.
safe motion planning computation for databasing balanced movement of humanoid robots. motion databasing is an important topic in robotics research. humanoid robots have a large number of degrees of freedom and their motions have to satisfy a set of constraints (balance, maximal joint torque velocity and angle values). thus motion planning cannot efficiently be done online. the computation of optimal motions is performed off-line to create databases that transform the problem of large computation time into a problem of large memory space. motion planning can be seen as a semi-infinite programming problem (sip) since it involves a finite number of variables over an infinite set of constraints. most methods solve the sip problem by transforming it into a finite programming one using a discretization over a prescribed grid. we show that this approach is risky because it can lead to motions which may violate one or several constraints. then we introduce our new method for planning safe motions. it uses interval analysis techniques in order to achieve a safe discretization of the constraints. we show how to implement this method and use it with state-of-the-art constrained optimization packages. then, we illustrate its capabilities for planning safe motions dedicated to the hoap-3 humanoid robot.
traction force distribution on omni-directional four wheel independent drive electric vehicle. this paper proposes an optimal traction force distribution for omni-directional four wheel independent steering (4wis) and four wheel independent drive (4wid) vehicle. the proposed force distribution algorithm is aimed to enhance the vehicle stability with minimum cost. the algorithm avoids the use of any feedback information of vehicle motion such as linear velocity as this information is difficult to measure accurately and the price of the measuring equipment is very high. as a result, the implementation cost can be reduced and at the same time avoid improper force distribution due to the inaccurate measured information. moreover, the proposed algorithm does not involve any parameter tuning. it makes the algorithm easy to implement. the proposed algorithm can also be applied to any steering types of 4wid vehicle such as typical two wheel steering (2ws) as 4wis is the general case of any steering configuration. simulation results reveal that the performance of the proposed force distribution is superior to the uniform force distribution which is commonly used in 4wid vehicle.
tendon-based transmission systems for robotic devices: models and control algorithms. tendon-based transmission systems present many positive aspects and greatly simplify the mechanical design of small robotic devices, such as robotic fingers. on the other hand, they introduce several nonlinear effects that must be properly considered by the control algorithms to achieve a suitable performance level in the regulation of the finger joint torques. in this paper, the model of the tendons-based driving system and of the nonlinear effects arising from the use of sliding paths instead of pulleys for the tendon routing are discussed, and control algorithms aiming at compensating these nonlinearities are presented. both models and control algorithms have been validated by experiments. in particular, in order to gain a better insight on the force distribution along the tendon, an experimental setup for the measurement of the tension in some intermediate points has been developed. after the identification of the tendon characteristics, a suitable control law for the compensation of the nonlinear effects due to the friction acting on the transmission system has been applied. the proposed compensation scheme is based on a sliding-mode controller with boundary layer, where the boundary threshold is modulated as a function of the desired tendon tension.
real-time trajectory generation for car-like vehicles navigating dynamic environments. this paper presents tiji, a trajectory generation scheme, ie an algorithm that computes a feasible trajectory between a start and a goal state, for a given robotic system. tiji is geared towards complex dynamic systems subject to differential constraints, such as wheeled vehicles, and its efficiency warrants it can be used in real-time. above all, tiji is able to compute a trajectory that reaches the goal state at a prescribed final time in order to avoid collision with the moving objects of the environment. the method proposed, which relies upon a parametric trajectory representation, is variational in nature. the trajectory parameters are incrementally updated in order to optimize of a cost function involving the distance between the end of the trajectory computed and the (goal state, final time) pair. should the goal state be unreachable (if the final time is ill-chosen), the method returns a trajectory that ends as close as possible to the (goal state, final time) pair, which can be useful in certain applications.
thermally constrained motor operation for a climbing robot. climbing robots are especially susceptible to thermal overload during normal operation, due to the need to oppose gravity and to frequently apply internal forces for clinging. as an alternative to setting conservative limits on the motor peak and average current, we investigate methods for measuring motor temperatures, predicting motor thermal conditions and generating thermally constrained behavior. a thermal model, verified using empirical data, predicts the motor's winding temperature based on measured case temperature and input current. we also present a control strategy that maximizes robot velocity while satisfying a constraint on the maximum permissible motor winding temperature.
delay-dependent stability analysis of teleoperation systems with unsymmetric time-varying delays. this paper investigates the stability analysis problem of teleoperation system. compared with previous work, the communication delays are assumed to be both time-varying and unsymmetric. the stability analysis is performed on two classes of controllers: delayed position error feedback and delayed force feedback. by choosing lyapunov krasovskii functional, we show that the master-slave teleoperation system is asymptotically stable under specific lmi conditions. with the given controller design parameters, the proposed stability criteria can be used to compute the allowable maximum delay values. finally, the simulations are performed to show the effectiveness of the proposed method.
i-bug: an intensity-based bug algorithm. this paper introduces a sensor-based planning algorithm that uses less sensing information than any others within the family of bug algorithms. the robot is unable to access precise information regarding position coordinates, angular coordinates, time, or odometry, but is nevertheless able to navigate itself to a goal among unknown piecewise-analytic obstacles in the plane. the only sensor providing real values is an intensity sensor, which measures the signal strength emanating from the goal. the signal intensity function may or may not be symmetric; the main requirement is that the level sets are concentric images of simple closed curves, i.e. topological circles. convergence analysis and distance bounds are established for the presented approach.
dynamic effects of arc feet on the leg motion of passive walker. the passive walker with knees can naturally execute the leg motion by the dynamics of legs under the gravity only. circular arc foot is very important for the leg motion. in this paper, the dynamical effects of the arc foot, which can keep the knee joint of stance leg straight only by the stopper and can enhance the flexion of knee joint of swing leg, are discussed. also, its geometrical negative effect is examined. finally, the desired arc foot is designed and the actual effects are confirmed by a walking experiment.
static anti-windup controller design for planar 2dof robot manipulators with actuator saturation. a static anti-integrator-windup controller design method is proposed for zero-gravity planar robot manipulators. the asymptotic stability is achieved using a simple static anti-windup gain matrix for pi or pid controllers. the control performance is verified by numerical simulations and experiments on a two-link planar 2dof robot arm.
mixed-initiative in human augmented mapping. in scenarios that require a close collaboration and knowledge transfer between inexperienced users and robots, the "learning by interacting" paradigm goes hand in hand with appropriate representations and learning methods. in this paper we discuss a mixed initiative strategy for robotic learning by interacting with a user in a joint map acquisition process. we propose the integration of an environment representation approach into our interactive learning framework. the environment representation and mapping system supports both user driven and data driven strategies for the acquisition of spatial information, so that a mixed initiative strategy for the learning process is realised. we evaluate our system with test runs according to the scenario of a guided tour, extending the area of operation from structured laboratory environment to less predictable domestic settings.
vision-based guidance and control of a hovering vehicle in unknown, gps-denied environments. this paper describes the system architecture and core algorithms for a quadrotor helicopter that uses vision data to navigate an unknown, indoor, gps-denied environment. without external sensing, an estimation system that relies only on integrating inertial data will have rapidly drifting position estimates. micro aerial vehicles (mavs) are stringently weight-constrained, leaving little margin for additional sensors beyond the mission payload. the approach taken in this paper is to introduce an architecture that exploits a common mission payload, namely a video camera, as a dual-use sensor to aid in navigation. several core algorithms, including a fast environment mapper and a novel heuristic for obstacle avoidance, are also presented. finally, drift-free hover and obstacle avoidance flight tests in a controlled environment are presented and analyzed.
probabilistic estimation of multi-level terrain maps. recent research has shown that robots can model their world with multi-level (ml) surface maps, which utilize 'patches' in a 2d grid space to represent various environment elevations within a given grid cell. though these maps are able to produce 3d models of the environment while exploiting the computational feasibility of single elevation maps, they do not take into account in-plane uncertainty when matching measurements to grid cells or when grouping those measurements into 'patches.' to respond to these drawbacks, this paper proposes to extend these ml surface maps into probabilistic multi-level (pml) surface maps, which uses formal probability theory to incorporate estimation and modeling errors due to uncertainty. measurements are probabilistically associated to cells near the nominal location, and are categorized through hypothesis testing into 'patches' via classification methods that incorporate uncertainty. experimental results comparing the performances of the pml and ml surface mapping algorithms on representative objects found in both indoor and outdoor environments show that the pml algorithm outperforms the ml algorithm in most cases including in the presence of noisy and sparse measurements. the experimental results support the claim that the pml algorithm produces more densely populated, conservative representations of its environment with fewer measurements than the ml algorithm.
nanolab: a nanorobotic system for automated pick-and-place handling and characterization of cnts. carbon nanotubes (cnts) are one of the most promising materials for nanoelectronic applications. before bringing cnts into large-scale production, a reliable nanorobotic system for automated handling and characterization as well as prototyping of cnt-based components is essential. this paper presents the nanolab setup, a nanorobotic system that combines specially developed key components such as electrothermal microgrippers and mobile microrobots inside a scanning electron microscope. the working principle and fabrication of mobile microrobots and electrothermal microgripper as well as their interaction and integration is described. furthermore, the nanolab is used to explore novel key strategies such as automated locating of cnts for pick-and-place handling and methods for electrical characterization of cnts. the results have been achieved within the framework of a european research project where the scientific knowledge will be transfered into an industrial system that will be commercially available for potential customers.
flow separation for fast and robust stereo odometry. separating sparse flow provides fast and robust stereo visual odometry that deals with nearly degenerate situations that often arise in practical applications. we make use of the fact that in outdoor situations different constraints are provided by close and far structure, where the notion of close depends on the vehicle speed. the motion of distant features determines the rotational component that we recover with a robust two-point algorithm. once the rotation is known, we recover the transiational component from close features using a robust one-point algorithm. the overall algorithm is faster than estimating the motion in one step by a standard ransac-based three-point algorithm. and in contrast to other visual odometry work, we avoid the problem of nearly degenerate data, under which ransac is known to return inconsistent results. we confirm our claims on data from an outdoor robot equipped with a stereo rig.
state estimation with delayed measurements considering uncertainty of time delay. state estimation problem with time delayed measurements is addressed. in dynamic system with noise, after taking measurements, it often requires some time until that is available in a filter. a filter not considering this time delay cannot be used since a current measurement is related with a past state. these delayed measurements problem is solved with augmented state kalman filter, and uncertainty of the delayed time is also resolved based on the probability distribution of the delay. the proposed method is analyzed by a simple example, and its consistency is verified.
continuous vocal imitation with self-organized vowel spaces in recurrent neural network. a continuous vocal imitation system was developed using a computational model that explains the process of phoneme acquisition by infants. human infants perceive speech sounds not as discrete phoneme sequences but as continuous acoustic signals. one of critical problems in phoneme acquisition is the design for segmenting these continuous speech sounds. the key idea to solve this problem is that articulatory mechanisms such as the vocal tract help human beings to perceive speech sound units corresponding to phonemes. to segment acoustic signal with articulatory movement, we apply the segmenting method to our system by recurrent neural network with parametric bias (rnnpb). this method determines the multiple segmentation boundaries in a temporal sequence using the prediction error of the rnnpb model, and the pb values obtained by the method can be encoded as kind of phonemes. our system was implemented by using a physical vocal tract model, called the maeda model. experimental results demonstrated that our system can self-organize the same phonemes in different continuous sounds, and can imitate vocal sound involving arbitrary numbers of vowels using the vowel space in the rnnpb. this suggests that our model reflects the process of phoneme acquisition.
control uncertainty in image-based visual servoing. it has recently been demonstrated that the effect of visual measurement errors on the open-loop control in visual servoing can be estimated using linear propagation of errors. the uncertainty estimation offers a tool to build and analyze hybrid control systems such as switching or partitioning control. in earlier works, position-based and 2.5d servoing have been analysed. this work extends the approach to the analysis of closed loop uncertainty, showing how the path uncertainty can be approximated. the uncertainty is analyzed in cartesian reference to make the approach general over different hardware. in addition, we show how image-based visual servoing can be analysed using the same approach.
effect of energy feedbacks on virtual slope walking: i. complementary energy feedback. this paper presents our study over the effect of complementary energy feedback on virtual slope walking, while virtual slope walking is our new biped gait generation method inspired by passive dynamic walking. the energy feedback strength is defined and the walking is modeled as a step-to-step function. the jacobi matrix eigenvalues of the function are calculated together with the basin of attraction. from the analysis, we find the characteristic of complementary energy feedback is being effective on a fast gait but weak on a slow one. by making use of the complementary energy feedback in walking experiment, our robot achieves speed change from 1.5leg/s to 4.1leg/s.
maccepa 2.0: adjustable compliant actuator with stiffening characteristic for energy efficient hopping. the maccepa (mechanically adjustable compliance and controllable equilibrium position actuator) is an electric actuator of which the compliance and equilibrium position are fully independently controllable and both are set by a dedicated servomotor. in this paper an improvement of the actuator is proposed where the torque-angle curve and consequently the stiffness-angle curve can be modified by choosing an appropriate shape of a profile disk, which replaces the lever arm of the former design. the actuator has a large joint angle, torque and stiffness range and these properties can be made beneficial for safe human robot interaction and the construction of energy efficient walking, hopping and running robots. the ability to store and release energy is shown by simulations on a 1dof hopping robot. its hopping height is much higher compared to a configuration in which the same motor is used in a traditional stiff setup. the stiffness of the actuator has a stiffening characteristic so the leg stiffness resembles more a linear stiffness as found in humans.
robust servo-control for underwater robots using banks of visual filters. we present an application of machine learning to the semi-automatic synthesis of robust servo-trackers for underwater robotics. in particular, we investigate an approach based on the use of boosting for robust visual tracking of color objects in an underwater environment. to this end, we use adaboost, the most common variant of the boosting algorithm, to select a number of low-complexity but moderately accurate color feature trackers and we combine their outputs. the novelty of our approach lies in the design of this family of weak trackers, which enhances a straightforward color segmentation tracker in multiple ways. from a large and diverse family of possible filters, we select a small subset that optimizes the performance of our trackers. the tracking process applies these trackers on the input video frames, and the final tracker output is chosen based on the weights of the final array of trackers. by using computationally inexpensive, but somewhat accurate trackers as members of the ensemble, the system is able to run at quasi real-time, and thus, is deployable on-board our underwater robot. we present quantitative cross-validation results of our spatio-chromatic visual tracker, and conclude by pointing out some difficulties faced and subsequent shortcomings in the experiments we performed, along with directions of future research in the area of ensemble tracking in real-time.
above 40g acceleration for pick-and-place with a new 2-dof pkm. this paper introduces a new two-degree-of-freedom parallel manipulator producing two translations in the vertical plane. one drawback of existing robots built to realize those dof is their lack of rigidity along the transversal axis, another one being their limited ability to provide very high acceleration. indeed, these architectures cannot be lightweight and stiff at the same time. the proposed architecture is a spatial mechanism which guarantees a good stiffness along the transversal axis. this parallel architecture is composed by two actuated kinematic chains, and two passive chains built in the transversal plane. the key feature of this robot comes from the passive chains which are coupled for creating a kinematic constraint: the platform stays in one plane. a stiffness analysis shows that the robot can be lighter and stiffer than a classical 2 dof mechanism. a prototype of this robot is presented and preliminary tests show that accelerations above 40 g can be achieved while keeping a low tracking error.
on-line planning of nonholonomic trajectories in crowded and geometrically unknown environments. navigation of a car-like robot in environments with unknowns requires effective on-line planning of nonholonomic trajectories. we propose a set of basic maneuver patterns based on bezier curves that allow either forward or backward motion as building blocks to create nonholonomic trajectories quickly, given a sequence of knot positions/points (e.g., from some gps navigator). these maneuver patterns are particularly useful for generating feasible trajectories in crowded environments with many narrow passages. we embed the above techniques in a new planner suitable for on-line planning of nonholonomic and collision-free trajectories, called the on planner. our on planner enables that, given a sequence of rough knot points, a car-like robot can simultaneously plan and move in a geometrically unknown, crowded environment with local sensing towards a goal. simulation results demonstrate the planner's nice capabilities.
time-bounded lattice for efficient planning in dynamic environments. for vehicles navigating initially unknown cluttered environments, current state-of-the-art planning algorithms are able to plan and re-plan dynamically-feasible paths efficiently and robustly. it is still a challenge, however, to deal well with the surroundings that are both cluttered and highly dynamic. planning under these conditions is more difficult for two reasons. first, tracking and predicting the trajectories of moving objects (i.e., cars, humans) is very noisy. second, the planning process is computationally more expensive because of the increased dimensionality of the state-space, with time as an additional variable. moreover, re-planning needs to be invoked more often since the trajectories of moving obstacles need to be constantly re-estimated. in this paper, we develop a path planning algorithm that addresses these challenges. first, we choose a representation of dynamic obstacles that efficiently models their predicted trajectories and the uncertainty associated with the predictions. second, to provide real-time guarantees on the performance of planning with dynamic obstacles, we propose to utilize a novel data structure for planning - a time-bounded lattice - that merges together short-term planning in time with long-term planning without time. we demonstrate the effectiveness of the approach in both simulations with up to 30 dynamic obstacles and on real robots.
autonomous planetary exploration using lidar data. in this paper we present the approach for autonomous planetary exploration developed at the canadian space agency. the goal of this work is to autonomously navigate to remote locations, well beyond the sensing horizon of the rover, with minimal interaction with a human operator. we employ lidar range sensors due to their accuracy, long range and robustness in the harsh lighting conditions of space. irregular triangular meshes (itms) are used for representing the environment providing an accurate yet compact spatial representation. in this paper a novel path-planning technique through the itm is introduced, which guides the rover through flatter terrain and safely away from obstacles. experiments performed in csa's mars emulation terrain that validate our approach are also presented.
a novel control algorithm for wearable robotics using phase plane invariants. with microprocessing power greatly increasing, hardware is no longer a hurdle in the development of controllers for wearable robotic systems, specifically lower limb robots. the challenge remains in developing smart algorithms that are able to detect which task a person is about to perform and then determine the correct desired movements for the robotic system. this paper reflects on four existing control algorithms for the task of level ground walking, and then presents theory and test results of a novel control algorithm based on phase plane invariants. the goal of this paper is to produce the correct motor reference command in a continuous fashion rather than based on determining distinct states for a given task.
spectral clustering for feature-based metric maps partitioning in a hybrid mapping framework. hybrid maps combine metric and topological information for efficiently managing large-scale environments. in a feature-based mapping framework, this paper describes the application of a spectral clustering approach for automatically detecting the transitions between subsequently traversed local maps. contrary to recently proposed approaches, this algorithm considers each individual map feature as a node of a graph whose edges link two nodes if they are simultaneously observed. thus, given a sequence of observations, an auxiliary graph is incrementally built whose edges carry non-negative weights according to the locality of the features. given a feature, its locality defines the set of features that has been observed simultaneously with it at least once. at each execution of the mapping approach, the feature-based graph is split into two subgraphs using a normalized spectral clustering algorithm. if the graph partition is validated, the algorithm determines that the robot is moving into a new area and a new local map is generated. we have tested the proposed approach in real environments where features are obtained using 2d laser sensors or vision. experimental results demonstrate the performance of the proposal.
linescout technology: from inspection to robotic maintenance on live transmission power lines. power line inspection and maintenance practices are evolving as changing market regulations, significantly increased line loading and system availability requirements put pressure on grid owners to innovate. robotics is thus making its debut in that field. described in previous papers as an inspection tool, hydro-québec linescout technology is evolving into a teleoperated mobile robot capable of performing basic maintenance tasks. programmable pan-and-tilt camera (pptc) units were designed and implemented as the first step towards enhanced teleoperation control. linearm, a dual end effector robotic arm, was specifically designed for work on bundled conductors. design specifications and kinematics of these two subsystems are presented. implemented application modules to be mounted on linearm are also presented and their utilization is reported as a milestone in power line live maintenance. lastly, future work and challenges in applying robotics to transmission line maintenance are briefly discussed.
synchronized control in a large-scale networked distributed printing system. as engineered systems that have traditionally been controlled centrally become more modular, distributed, and autonomous, techniques are needed to maintain control coordination among independent elements, often across a network with delays and bandwidth limitations. in particular, manufacturing systems may require tight coordination, or synchronization, among components acting on the same physical object. this paper addresses the problem of controller synchronization in such a system. we present an implementation of exact controller synchronization for independent controllers in a highly modular printing domain. our approach, which allows networked controllers to join and leave a task dynamically, has produced excellent results on a high-speed printer prototype.
multi-robot plan adaptation by constrained minimal distortion feature mapping. we propose a novel method for multi-robot plan adaptation which can be used for adapting existing spatial plans of robotic teams to new environments or imitating collaborative spatial teamwork of robots in novel situations. the algorithm selects correspondences between previous and current spatial features by the application of pairwise constraints, and generates the transformation function with a fast regular grid approximation which minimizes distortion. the algorithm requires minimal domain knowledge, is capable of transforming the spatial aspects of collaborative team behavior and performs better in noisy problems with large displacements than the most generally used quadratic differences method. the algorithm can be utilized for rapid plan adaptation, plan generalization or team behavior imitation. methods are demonstrated on a multi-robot control problem in a random environment.
miniature soft hand with curling rubber pneumatic actuators. in medical and biotechnology fields, soft devices are required because of their high safety from low mechanical impedance. fma (flexible microactuator) is one of the typical soft actuators. it consists of fiber-reinforced rubber structure with multi air chambers and realizes bending motion pneumatically. it has been applied to robot hands, robot legs and so on. high potential of fma has been confirmed by many experiments reported in several papers. however in fabrication process of the actuator, it is difficult to embed the reinforced fiber in the rubber structure. in this study, we aim at development of a fiber less fma realizing quite large motion, which can be said curling motion, and a soft hand using the actuators. we design the actuator without fiber using nonlinear fem (finite element method) and derived efficient shape. the actuator is fabricated through micro rubber casting process including micro machining process for molds, micro vacuum rubber molding process and rubber bonding process with surface improvement by excimer light. basic driving experiments of the actuator showed that it realized curling motion which agreed well with fem results. and the actuator could grasp a fish egg without breaking. additionally, we made a soft hand consisting of three curling actuators. this hand also could be manufactured by simple casting process. the developed hand works opening and closing motions well.
kinematics and dynamics of a hybrid serial-parallel mobile robot. in this study, kinematics design, dynamics modeling and verification of a compounded serial-parallel wheeled mobile robot is elaborated. the proposed novel kinematic structure is best suited to fulfill stable motion of the robotic system when handling heavy objects by manipulators mounted on mobile platforms. the proposed system is made of a differentially-driven wheeled platform, a planar parallel manipulator, which is called here as star-triangle (st) mechanism, and a serial puma-type manipulator arm. the suggested structure adopts the advantages of both serial and parallel robots, to move the base point of the serial robot with respect to the mobile platform to fulfill the system stability after grasping heavy objects. in order to investigate the comprehensive kinematics model of the robot, after introducing its novel structure it is divided into three modules, i.e. a mobile platform, a parallel st mechanism, and a serial robot. next, a closed-form dynamics model is derived for the whole hybrid system based on a combined newton-euler and lagrange formulation. the proposed method presents the mutual dynamic interaction wrenches between the integrated platform and the serial manipulator which can be exploited for the tip-over stability analysis of the mobile robotic system. then, to verify the obtained mathematical model, several benchmark actuating inputs are applied to the model and the system responses are analyzed.
directionality control and flight stability of takeoff. flight initiation is an area that remains unexplored amongst today's nano-scaled, flapping-wing, robotic insects. to understand mechanical principles of ground-to-air transitions at this particular scale, we investigate the biomechanics of the fruit fly drosophila melanogaster during takeoff. building upon a prior framework [1], we analyze the insect's pre-flight motion, and its impact in directionality control. using a rigid multibody system comprised by one central body and six legs, we are able to estimate forces from joint kinematics. the approach provides a mathematical framework for studying tradeoffs between directionality control [1] and dynamic stability during flight initiation.
aerodynamics of dragonfly flight and robotic design. a pair of dynamically scaled robotic dragonfly model wings was developed to investigate the aerodynamic effect of wing-wing interaction in dragonfly flight. instantaneous aerodynamic forces were measured while forewing-hindwing phase difference (γ) was systematically varied. experimental results showed that, i) for hovering flight, γ=0° enhanced the lift force on both forewing and hindwing; γ=180° reduced the total lift force, but was beneficial for vibration suppression and body posture stabilization. in nature, 0° is employed by dragonflies in acceleration mode while 180° is usually in hovering mode. ii) for forward flight, wing-wing interaction enhances forewing lift while reduced hindwing lift at all phase differences. furthermore, the total lift was slightly reduced for γ= 0° to 90° and significantly reduced by 18% when γ=270°. the results consist well with the fact that, dragonflies usually employ 50° to 100° for forward flight, but seldom employ 270°. piv results are shown for wing-wing interaction analysis.
rollin' justin - design considerations and realization of a mobile platform for a humanoid upper body. research on humanoid robots for use in servicing tasks, e.g. fetching and delivery, attracts steadily more interest. with rollin' justin a mobile robotic system and research platform is presented that allows the implementation and demonstration of sophisticated control algorithms and dexterous manipulation. important problems of service robotics such as mobile manipulation and strategies for using the increased workspace and redundancy in manipulation task can be studied in detail. this paper gives an overview of the design considerations for a mobile platform and their realizations to transform the formerly table-mounted humanoid upper body system justin into rollin' justin, a fully self-sustaining mobile research platform.
a temptative to reach a visual singular configuration using halley's method. image-based visual servoing has been found to give satisfactory accurate and robust results. however, singularity and local minima may appear causing stability and convergence problems. in this paper, we present new control schemes based on halley's method as a temptative to obtain a robust system even when the desired configuration is singular. the new control scheme use the first and the second order derivatives of the error to be regulated to zero. hessian matrices of an image point are thus determined to be used in the control schemes. preliminary experimental results obtained on a 6 dof eye-in-hand system shows that a more accurate positioning can be obtained compared with classical methods.
the winch-bot: a cable-suspended, under-actuated robot utilizing parametric self-excitation. a simple, compact, yet powerful robotic winch, called "winch-bot," is presented in this paper. the winch-bot is an underactuated robot having only one controllable axis. although hanging a load with merely one cable, it is capable of moving it in a large workspace by swinging the load dynamically based on parametric self-excitation. the generated trajectories can be used for a variety of tasks, from moving material to cyclic inspection of surfaces. the basic principle and design concept of the winch-bot are first described, followed by dynamic modeling and analysis. two trajectory generation problems are solved. one is point-to-point transfer of a load, and the other is the tracking of a continuous path. it will be shown that the system can track a given geometric trajectory, although the tracking velocity cannot be determined arbitrarily due to the underactuated nature of dynamics. a prototype winch-bot is designed and built, and point-to-point, continuous path, and parametric excitation control are implemented.
robot force/position tracking with guaranteed prescribed performance. a control law is proposed that achieves predefined performance indices regarding the speed of response, the steady state and the allowed overshoot of the robot force/position tracking errors, ensuring no loss of contact of the robot end effector. the controller incorporates a transformed error, which includes the performance indices. the control objective is satisfied under parametric uncertainties in the robot dynamics and the elasticity model constant. simulation results confirm the theoretical findings and compare the proposed controller with a conventional one.
precise and robust large-shape reproduction using uncalibrated vision. the paper presents an alternative to cnc machining, based on a proposed method for creating very large and precise replicas of prototype shapes using material-removal and/or material-adding mechanisms that need not be calibrated. the method is based upon the creation of a "virtual mold", which is created in the two-dimensional image planes of two or more stationary, uncalibrated cameras. the cameras are placed so as to view portions of the prototype surface and remain stationary while multiple-beam laser pointers cast their light toward the prototype shape and the resulting laser-spot reflections are registered and matched among the cameras. large numbers of images can be acquired with slightly offset pan and tilt angles of laser-pointer-bearing units, resulting in collected laser-spot-centroid indications that may number in the thousands. the spot-centroid coordinates in camera space are matched in such a way that individual, physical spot-centroid indications are registered in memory in accordance with correspondence among those cameras able to view any one particular spot. this forms the basis of the "virtual mold". subsequent reproduction of the shape, as with a cnc machine, relies upon action of a robot to remove material from a blank. this blank is placed so as to occupy the region where the prototype had been during laser spot casting. camera-space manipulation is used to guide the robot in consecutive passes of material removal, with laser spots cast upon each newly revealed intermediate surface and reflected up into the original cameras. the paper presents the use of a fanuc m16-ib industrial robot, in order to obtain experimental evidence on how the original surface regions can be replicated with extremely high precision despite no need for calibration either of the cameras or the manipulator.
auxiliary models based multi-innovation gradient identification with colored measurement noises. for pseudo-linear regression identification models corresponding output error systems with colored measurement noises, a difficulty of identification is that there exist unknown inner variables and unmeasurable noise terms in the information vector. this paper presents an auxiliary model based multiinnovation stochastic gradient algorithm by using the auxiliary model technique and by expanding the scalar innovation to an innovation vector. compared with single-innovation stochastic gradient algorithm, the proposed approach can generate highly accurate parameter estimates. the simulation results confirm theoretical findings.
temporal stabilization of discrete movement in variable environments: an attractor dynamics approach. the ability to generate discrete movement with distinct and stable time courses is important for interaction scenarios both between different robots and with human partners, for catching and interception tasks, and for timed action sequences. in dynamic environments, where trajectories are evolving on-line, this is not a trivial task. the dynamical systems approach to robotics provides a framework for robust incorporation of fluctuating sensor information, but control of movement time is usually restricted to rhythmic motion and realized through stable limit cycles. the present work uses a hopf oscillator to produce discrete motion and formulates an on-line adaptation rule to stabilize total movement time against a wide range of disturbances. this is integrated into a dynamical systems framework for the sequencing of movement phases and for directional navigation, using 2d-planar motion as an example. the approach is demonstrated on a khepera mobile unit in order to show its reliability even when depending on low-level sensor information.
designing image trajectories in the presence of uncertain data for robust visual servoing path-planning. path-planning allows one to steer a camera to a desired location while taking into account the presence of constraints such as visibility, workspace, and joint limits. unfortunately, the planned path can be significantly different from the real path due to the presence of uncertainty on the available data, with the consequence that some constraints may be not fulfilled by the real path even if they are satisfied by the planned path. in this paper we address the problem of performing robust path-planning, i.e. computing a path that satisfies the required constraints not only for the nominal model as in traditional path-planning but rather for a family of admissible models. specifically, we consider an uncertain model where the point correspondences between the initial and desired views and the camera intrinsic parameters are affected by unknown random uncertainties with known bounds. the difficulty we have to face is that traditional path-planning schemes applied to different models lead to different paths rather than to a common and robust path. to solve this problem we propose a technique based on polynomial optimization where the required constraints are imposed on a number of trajectories corresponding to admissible camera poses and parameterized by a common design variable. the planned image trajectory is then followed by using an ibvs controller. simulations carried out with all typical uncertainties that characterize a real experiment illustrate the proposed strategy and provide promising results.
dynamically running quadrupeds self-stable region expansion by mechanical design. dynamic stability allows running animals to maintain preferred speed during locomotion over rough terrain. it appears that rapid disturbance rejection is an emergent property of the mechanical system. in running robots, simple motor control seems to be effective in the negotiation of rough terrain when used in concert with a mechanical system that stabilizes passively. in this paper, we show that a quadruped robot could be able to perform self-stable running behavior in significantly broader ranges of forward speed and pitch rate with suitable mechanical design. the results presented here are derived by studying the stability of passive dynamics of a quadruped robot running in the sagittal plane in a dimensionless context and can be summarized as: (a) the self-stabilized behavior of a quadruped robot for a particular gait is related to the magnitude of its dimensionless inertia, (b) the values of hip separation, normalized to rest leg length, and the leg relative stiffness of a quadruped robot affect the stability and should be in inverse proportion to its dimensionless inertia, and (c) the self-stable regime of quadruped running robots is enlarged at relatively high forward speeds.
mapping opaque and confined environments using proprioception. mapping opaque and confined environments such as caves and pipes is a challenging problem for mobile robots because sensor information is severely limited to the immediate proximity of the robot due to the extreme environmental conditions. the robot must also be flexible and agile in unstructured environments while still providing accurate pose estimation. this paper presents a solution to mapping a 2-dimensional tube by using only a snake robot's proprioceptive joint angle sensors. we assume that the tube is sufficiently smooth and that we know the tube width. we propose techniques for (1) pose estimation of a snake robot by using a self-posture motion model, (2) correcting error in pose estimation using only the snake's internal configuration over time, and (3) building environmental features using only self-occupancy and contact detection. our goal is to use the minimal amount of sensor information possible to build an accurate spatial map of the environment. we have tested the proposed techniques in simulated environments and experimental results show that they are both effective and efficient for mapping tube environments. we plan to extend these techniques to deal with more complex confined environments beyond single-path tubes.
autonomous driving in a multi-level parking structure. recently, the problem of autonomous navigation of automobiles has gained substantial interest in the robotics community. especially during the two recent darpa grand challenges, autonomous cars have been shown to robustly navigate over extended periods of time through complex desert courses or through dynamic urban traffic environments. in these tasks, the robots typically relied on gps traces to follow pre-defined trajectories so that only local planners were required. in this paper, we present an approach for autonomous navigation of cars in indoor structures such as parking garages. our approach utilizes multi-level surface maps of the corresponding environments to calculate the path of the vehicle and to localize it based on laser data in the absence of sufficiently accurate gps information. it furthermore utilizes a local path planner for controlling the vehicle. in a practical experiment carried out with an autonomous car in a real parking garage we demonstrate that our approach allows the car to autonomously park itself in a large-scale multi-level structure.
task space robot control using an inner pd loop. this paper presents a task-space robot controller composed of two nested loops. the inner loop corresponds to a proportional-derivative joint-position controller and the outer loop consists of a proportional-integral controller fed by task space measurements. the lyapunov method allows concluding closed loop stability and a visual servoing application permits assessing the performance of the proposed controller.
magnetic dipoles for electromagnetic multi-dof actuator design. this paper presents a new method for solving the magnetic forces/torques of a multi-dof spherical actuator that has more controlling inputs than its mechanical dof. unlike methods that based on the lorentz force equation or the maxwell stress tensor, which require computing the volume or surface integrals to derive the forces, the dipole force method presented here offers the magnetic force solution in closed form. we validate the dipole force model against published experimental data, and demonstrate its application in solving the inverse torque model of a multi-dof spherical motor, which computes the required set of maximum current inputs for a given design specifications.
formations on two-layer pursuit systems. the paper studies hierarchical pursuit strategies for groups of mobile agents in the plane. it is shown that fascinating global patterns emerge from simple two-layer pursuit schemes, including rendezvous, uniform circular motion, complex circular motion, concentric circular motion, and concentric logarithmic spiral motion. both rigorous analysis and simulations are provided.
omni-directional steer-by-wire interface for four wheel independent steering vehicle. in this paper, an omni-directional steer-by-wire interface for four wheel independent steering vehicle is presented. the proposed steering interface is an extension of a traditional steering interface that provides three steering inputs. by combination of which, driver can control the vehicle in traditional way or omni-directionally without any mode switching operation. the reservation of the conventional steering behavior makes driver easy to adapt the novel steering interface. the force feedback controller is designed to synchronize the extended steering interface and the orientations of wheels so as to improve vehicle handling. hardware-in-the-loop simulations are conducted to verify the hardware prototype and examine the proposed algorithms.
surveillance of a polygonal area by a mobile searcher from the boundary: searchability testing. we study the surveillance of a polygonal area by a robot, which is equipped with a flashlight and moves along the polygon boundary. its aim is to illuminate any intruder who can move faster than the moving flashlight beam, trying to avoid detection. we propose an o(n)-time algorithm for testing if it is possible for such a robot to always detect any intruder in a given polygon, where n is the number of vertices of the given polygon. this improves upon the best previous time complexity of o(n log n).
asymptotic stability of teleoperators with variable time-delays. this paper extends the previous results on position tracking for bilateral teleoperators with constant time-delays, reported in nuño et al. ieee trans. robot., vol. 24, no. 3, pp. 753-758, june 2008, to the case of variable time-delays in the teleoperator's communications. the key part is the extension of a previous lemma that is used to prove that p+d or pd+d controllers can stabilize the teleoperator under variable time-delays, and moreover, they provide position tracking. the paper outlines the conditions under which velocities and position errors, of the nonlinear teleoperator, are bounded, and using barbalat's lemma, it is proved asymptotic converge to zero if the local manipulator stands still and the remote manipulator does not interact with the environment. simulations and real experiments validate the proposed schemes. the experiments have been performed using the internet as communication channel between urbana-champaign, usa and barcelona, spain.
identification of robots dynamics with the instrumental variable method. the identification of the dynamic parameters of robot is based on the use of the inverse dynamic model which is linear with respect to the parameters. this model is sampled while the robot is tracking "exciting" trajectories, in order to get an over determined linear system. the linear least squares solution of this system calculates the estimated parameters. the efficiency of this method has been proved through the experimental identification of a lot of prototypes and industrial robots. however, this method needs joint torque and position measurements and the estimation of the joint velocities and accelerations through the pass band filtering of the joint position at high sample rate. so, the observation matrix is noisy. moreover identification process takes place when the robot is controlled by feedback. these violations of assumption imply that the ls solution is biased. the simple refined instrumental variable (sriv) approach deals with this problem of noisy observation matrix and can be statistically optimal. this paper focuses on this technique which will be applied to a 2 degrees of freedom (dof) prototype developed by the irccyn robotic team.
mmm-classification of 3d range data. this paper presents a method for accurately segmenting and classifying 3d range data into particular object classes. object classification of input images is necessary for applications including robot navigation and automation, in particular with respect to path planning. to achieve robust object classification, we propose the idea of an object feature which represents a distribution of neighboring points around a target point. in addition, rather than processing raw points, we reconstruct polygons from the point data, introducing connectivity to the points. with these ideas, we can refine the markov random field (mrf) calculation with more relevant information with regards to determining "related points". the algorithm was tested against five outdoor scenes and provided accurate classification even in the presence of many classes of interest.
open e-puck range & bearing miniaturized board for local communication in swarm robotics. we have designed and built a new open hardware/ software board that lets miniaturized robots communicate and at the same time obtain the range and bearing of the source of emission. the open e-puck range & bearing board improves an existing infrared relative localization/communication software library (libircom) developed for the e-puck robot and based on its on-board infrared sensors. the board allows the robots to have an embodied, decentralized and scalable communication system. its use and capabilities are demonstrated via an alignment experiment.
resonance-based motion control method for multi-joint robot through combining stiffness adaptation and iterative learning control. this paper proposes a new trajectory tracking control method for multi-joint robots by combining stiffness adaptation and iterative learning control. the proposed controller achieves trajectory tracking while optimizing stiffness of elastic elements installed in each joint of the robots. even though the multi-joint robots have nonlinear dynamics and multi degree-of-freedom, the stiffness optimization realizes high energy efficiency as if we utilized resonance. an advantage of the proposed control is to work well without using exact parameter values of the robots. since it seems that adaptive control and iterative learning control have not been used simultaneously, this paper newly proposes a methodology to appropriately combine stiffness adaptation and iterative learning control. this combination enables trajectory tracking and convergence of the stiffness to the optimal one. these properties can not be achieved by our previous controllers.
bayesian network-based behavior control for skilligent robots. a skilligent robot must be able to learn skills autonomously to accomplish a task. "skilligence" is the capacity of the robot to control behaviors reasonably, based on the skills acquired during run-time. behavior control based on bayesian networks is used to control reasonable behaviors. to accomplish this, subgoals are first discovered by clustering similar features of state transition tuples, which are composed of current states, actions, and next states. here, features used in clustering are produced using changes of the states in the state transition tuples. parameters of bayesian networks and utility functions are learned separately using state transition tuples belonging to each subgoal. to select the best action while executing a task, the expected utility of each subgoal is calculated by the expected utility function and the robot chooses the action that maximizes expected utility calculated by the maximum expected utility (meu) function. the meu function is based on the conditional probabilistic distributions of bayesian networks and utility functions. we also propose a method for reconstructing learned networks and increasing subgoals by incremental learning. to show the validities of our proposed methods, a task using dribbling-box-into-a-goal (dbig) and obstacle-avoidance-while-dribbling-box (oawdb) skills is simulated and experimented.
analysis of crohn's disease lesions in capsule endoscopy images. capsule endoscopy (ce) is aimed at diagnosing disease in areas of the gastrointestinal (gi) tract beyond the reach of conventional endoscopy. recent work has addressed various methods for reducing the complexity of ce diagnosis and the time needed for analyzing the data. this includes detection of lumen and its contractions, fluids such as blood and intestinal juices, as well as extraneous matter such as food and bubbles. this paper outlines our ongoing work to segment lesions (in particular crohn's disease) and other abnormalities in ce images. in particular, here we describe the data collection and clinical analysis for our project and preliminary results for segmenting abnormal and extraneous images from a set of 10 ce studies.
multiple hypothesis tracking using clustered measurements. this paper introduces an algorithm for tracking targets whose locations are inferred from clusters of observations. this method, which we call mhtc, expands the traditional multiple hypothesis tracking (mht) hypothesis tree to include model hypotheses--possible ways the data can be clustered in each time step--as well as ways the measurements can be associated with existing targets across time steps. we present this new hypothesis framework and its probability expressions and demonstrate mhtc's operation in a robotic solution to tracking neural signal sources.
topological modeling and classification in home environment using sonar gridmap. this paper presents a method of topological representation and classification in home environment using only low-cost sonar sensors. approximate cell decomposition and normalized graph cut are applied to sonar gridmap to extract graphical model of the environment. the extracted model represents spatial relation of the environment appropriately by segmenting several subregions. moreover, node classification is achieved by applying template matching method to a local gridmap. rotational invariant matching is used to obtain candidate location for each node and the true node can be classified by considering detail distance information. the proposed method extracts well-structured topological model of the environment and classification also results in reliable matching even under the uncertain and sparse sonar data. experimental results verify the performance of proposed environmental modeling and classification in real home environment.
singo: a single-end-operative and genderless connector for self-reconfiguration, self-assembly and self-healing. flexible and reliable connection is critical for self-reconfiguration, self-assembly, or self-healing. however, most existing connection mechanisms suffer from a deficiency that a connection would seize itself if one end malfunctions or is out of service. to mitigate this limitation on self-healing, this paper presents a new singo connector that can establish or disengage a connection even if one end of the connection is not operational. we describe the design and the prototype of the connector and demonstrate its performance by both theoretical analysis and physical experimentations.
unsupervised learning of 3d object models from partial views. we present an algorithm for learning 3d object models from partial object observations. the input to our algorithm is a sequence of 3d laser range scans. models learned from the objects are represented as point clouds. our approach can deal with partial views and it can robustly learn accurate models from complex scenes. it is based on an iterative matching procedure which attempts to recursively merge similar models. the alignment between models is determined using a novel scan registration procedure based on range images. the decision about which models to merge is performed by spectral clustering of a similarity matrix whose entries represent the consistency between different models.
rapid pole climbing with a quadrupedal robot. this paper describes the development of a legged robot designed for general locomotion of complex terrain but specialized for dynamical, high-speed climbing of a uniformly convex cylindrical structure, such as an outdoor telephone pole. this robot, the rise v3 climbing machine--mass 5.4 kg, length 70 cm, excluding a 28 cm tail appendage--includes several novel mechanical features, including novel linkage designs for its legs and a non-backdrivable, energy-dense power transmission to enable high-speed climbing. we summarize the robot's design and document a climbing behavior that achieves rapid ascent of a wooden telephone pole at 21 cm/s, a speed previously unachieved--and, we believe, heretofore impossible--with a robot of this scale. the behavioral gait of the robot employs the mechanical design to propel the body forward while passively maintaining yaw, pitch, and roll stability during climbing locomotion. the robot's general-purpose legged design coupled with its specialized ability to quickly gain elevation and park at a vertical station silently with minimal energy consumption suggest potential applications including search and surveillance operations as well as ad hoc networking.
a compact rotational manipulator using shape memory alloy wire actuated flexures. this paper presents the design, fabrication, and control of a rotational manipulator using shape memory alloy (sma) wire actuated flexures. monolithic flexure mechanisms have no friction/backlash and are capable of miniaturization. they are well-suited for tasks that required high precision and packed space. to explore flexure shapes beyond traditional notch hinges and leaf springs, we present a general two-step design method to find the optimal flexure shapes for maximal rotation without yield. the advantages gained from shape variations are shown through a simulation example. we further use a sma wire to drive the flexure. sma exhibits large stroke with high power density and requires low driving voltage. by using versatile sma wire, the rotational range of the manipulator can be significantly increased while the overall size can be kept compact. a feedback pid control algorithm with fuzzy-tuned gains is implemented to precisely control the response of the manipulator. we illustrate its performance by tracking and step response experiments. with the merits shown, we expect this type of manipulator can be utilized in meso to micro scale applications.
dam wall detection and tracking using a mechanically scanned imaging sonar. in dam inspection tasks, an underwater robot has to grab images while surveying the wall meanwhile maintaining a certain distance and relative orientation. this paper proposes the use of an msis (mechanically scanned imaging sonar) for relative positioning of a robot with respect to the wall. an imaging sonar gathers polar image scans from which depth images (range & bearing) are generated. depth scans are first processed to extract a line corresponding to the wall (with the hough transform), which is then tracked by means of an ekf (extended kalman filter) using a static motion model and an implicit measurement equation associating the sensed points to the candidate line. the line estimate is referenced to the robot fixed frame and represented in polar coordinates (ρ&θ) which directly corresponds to the actual distance and relative orientation of the robot with respect to the wall. the proposed system has been tested in simulation as well as in water tank conditions.
a relative frame representation for fixed-time bundle adjustment in sfm. a successful approach in the recovery of video-rate structure from motion is to allow the camera to keep track of its position in every frame assuming the recovered set of scene landmarks is fixed in 3d, and then to use the poses in a subset of separated frames, or keyframes, to initialise further landmark structure. the landmark structure and keyframe poses are optimised in a bundle adjustment. unfortunately this monolithic bundle adjustment has cubic complexity. this paper shows how representing landmarks and camera poses in relative frames, and by temporarily removing certain measurements, introduces a conditional indepedence which allows the bundle adjustment to be split into two parts. one "local" part involves the most recent keyframes and associated landmarks, and runs in constant time. the other "global" part deals with older keyframes and structure, and runs, as ever, in cubic time. three important outcomes are: (i) the fixed-time local adjustment allows exploratory map-building to keep pace with camera pose tracking; (ii) it produces statistically consistent results; and (iii) referencing to relative frames means that any update in positions from the global adjustment are immediately incorporated in the local fixed-time adjustment. the relative frame approach is applied to the parallel tracking and mapping method for structure from motion, and its results shown to be identical, and the exploratory map building phase shown to maintain fixed time performance.
on the complexity and consistency of ukf-based slam. this paper addresses two key limitations of the unscented kalman filter (ukf) when applied to the simultaneous localization and mapping (slam) problem: the cubic, in the number of states, computational complexity, and the inconsistency of the state estimates. in particular, we introduce a new sampling strategy that minimizes the linearization error and whose computational complexity is constant (i.e., independent of the size of the state vector). as a result, the overall computational complexity of ukf-based slam becomes of the same order as that of the extended kalman filter (ekf) when applied to slam. furthermore, we investigate the observability properties of the linear-regression-based model employed by the ukf, and propose a new algorithm, termed the observability-constrained (oc)-ukf, that improves the consistency of the state estimates. the superior performance of the oc-ukf compared to the standard ukf and its robustness to large linearization errors are validated by extensive simulations.
modeling and motion stability analysis of skid-steered mobile robots. skid-steered mobile robots are widely used because of the simplicity of mechanism and high reliability. however, understanding of the kinematics and dynamics of such a robotic platform is challenging due to the complex wheel/ground interactions and kinematic constraints. in this paper, we attempt to develop a kinematic and dynamic modeling scheme to analyze the skid-steered mobile robot. we model wheel/ground interaction and analyze the robot motion stability. as an application example, we present how to utilize the kinematic and dynamic modeling and analysis for robot localization and slip estimation using only low-cost strapdown inertial measurement units (imu). the extended kalman filter (ekf)-based localization scheme incorporates the kinematic constraints. the performance of the ekf-based localization and slip estimation scheme are presented. the estimation methodology is tested and validated on a robotic testbed.
insect powered micro air vehicles. in this paper we present successful navigation of a mechanically linked insect moth-pair, using light-weight and low-power actuators, demonstrating insect powered micro air vehicles (mavs). these mavs can fly for long periods of time, consuming only a small fraction(1%) of power compared to purely mechanical mavs. we demonstrate strategies for harnessing the high energy-density biofuel and high efficiency muscle actuators of insects using tissue-embedded and externally attached miniature insect generated momentum redirectors. commercial off-the-shelf tail motor, a rudder that exploits flow behind the insect wings, and a steering mechanism that misaligns the thrust directions of two insects were all separately used to control yaw of the hawkmoth, manduca sexta, in tethered flight. untethered flight control of two hawkmoths over 60 m was achieved using a 6 gm backpack, including a 3 gram helium balloon to keep the backpack airborne, for over 5 to 30 minutes of flight time.
force control with safety constraints via iterative feedback tuning. this paper presents a new design method for force control, which aims to control the interaction force between a robot and a human by satisfying certain safety requirements. in this method, an optimization-based control algorithm, called iterative feedback tuning (ift), is used to employ safety requirements as constraints of an optimization problem, which is then solved using sequential quadratic programming (sqp). therefore, this control method is applicable for safety-critical systems such as personal service robots. these robots are developed to provide assistance to patients or disabled people in their daily life by performing human-robot contact tasks such as wiping the face with a towel, scratching, etc. in addition, in ift, a newton search direction to update the controller parameters at each iteration is obtained on the basis of the closed-loop experimental data. hence, ift does not require explicit modeling of environment, in particular, human dynamics, otherwise in model-based approach it will be hard task to obtain a useful model. in the simulation and experiment, the effectiveness of the proposed method is examined by applying it to 1-dof contact system.
modeling and control of hydraulic rotary actuators used in forestry cranes. the steps for modeling and control of a hydraulic rotary actuator are discussed. our aim is to present experimental results working with a particular sensing device for angular position as a complement to pressure sensing devices. we provide the steps in experimental system identification used for modeling the system dynamics. the cascade controller designed contains an inner loop for an accurate tracking of torque while stabilizing position reference trajectories. the performance of this design is experimentally verified.
mining gps data for extracting significant places. this paper addresses the problem of safety in mining applications. it presents new metrics that can be used to determine dangerous situations during mine operation in real time. it also presents a fast and robust algorithm for extracting significant places from information logged by a state-of-the-art collision avoidance system. determining significant places provides valuable context information in a variety of applications such as map building, vehicle tracking and user assistance. in our case, we are interested in obtaining context information as a preliminary step towards improving mining safety. the algorithm presented here is validated with experimental data obtained from a fleet of haulage vehicles operating in various open pit mines.
randomised mpc-based motion-planning for mobile robot obstacle avoidance. this paper presents an algorithm for real-time sensor-based motion planning under kinodynamic constraints, in unknown environments. the objective of the trajectory-generation algorithm is to optimise a cost function out to a limited time horizon. the space of control trajectories is searched by expanding a tree using randomised sampling, in a manner similar to an rrt. the algorithm is improved by seeding the tree using the best control trajectory from the previous iteration, and by pruning branches based on a bound to the cost function and the best trajectory found so far. performance of the algorithm is analysed in simulation. in addition, the algorithm has been implemented on two kinds of vehicles: the segway rmp and a four-wheel-drive. the algorithm has been used to drive autonomously for a combined total on the order of hundreds of hours.
the effect of chord-wise flexibility on the aerodynamic force generation of flapping wings: experimental studies. wings of insects are flexible structures. although there has been much recent progress in the area of insect flight aerodynamics, very little is known about how wing flexibility influences aerodynamic forces during flapping flight. we investigated this question using a dynamically scaled mechanical model of insect wings. using a suite of wings with varying flexural stiffness (ei) values, we generated aerodynamic polar plots to characterize the force coefficients of flexible wings. these polar plots showed that the aerodynamic performance of the wings varied with wing flexibility. in general, aerodynamic force production decreased with increasing flexibility. both lift and drag coefficients of wings are greater when wings are more rigid. however, at very high angles of attack, flexible wings generated greater lift than a rigid wing. in addition, the ratio of lift-to-drag also decreased with increasing flexibility. these data show that flexible wings offer no aerodynamic advantage over a rigid wing under steady state circumstances. because wing material in insects is usually flexible but reinforced by wing veins, we tested the hypothesis that wing veins enhance the aerodynamic performance of wings by increasing their effective stiffness. our data suggests that even a very basic framework of appropriately placed wing veins can substantially increase the functional rigidity of the wings thereby enhancing its aerodynamic performance.
a variable stiffness pzt cellular actuator with tunable resonance for cyclic motion tasks. a simple and efficient approach for varying the inherent stiffness and impedance of a muscle-like actuator is presented. the basic architecture of pzt cellular actuators has already achieved a large effective strain (10-20%). this architecture is modified and extended so that each cellular unit can be switched between a zero compliance state and constant compliance state. the effective stiffness of the cellular actuator is varied by changing the distribution of cellular units in the rigid versus compliant state. furthermore, by placing a multitude of these cellular units in series or parallel, the stiffness can vary within a large set of discrete values. this paper also demonstrates the viability of the variable stiffness cellular actuator for cyclic tasks such as running and flapping. the basic principle and design concept for the actuator is described, followed by force-displacement analysis. a dynamic model is then constructed to demonstrate the variable resonance properties of the actuator under load.
a stereoscopic fibroscope for camera motion and 3d depth recovery during minimally invasive surgery. this paper introduces a stereoscopic fibroscope imaging system for minimally invasive surgery (mis) and examines the feasibility of utilizing images transmitted from the distal fibroscope tip to a proximally mounted ccd camera to recover both camera motion and 3d scene information. fibre image guides facilitate instrument miniaturization and have the advantage of being more easily integrated with articulated robotic instruments. in this paper, twin 10,000 pixel coherent fibre bundles (590µm diameter) have been integrated into a bespoke laparoscopic imaging instrument. images captured by the system have been used to build a 3d map of the environment and reconstruct the laparoscope's 3d pose and motion using a slam algorithm. detailed phantom validation of the system demonstrates its practical value and potential for flexible mis instrument integration due to the small footprint and flexible nature of the fibre image guides.
sliding motion control of active flexible cable using simple shape information. we propose a new framework for a self-propelled flexible cable in which the freedom of lateral motion with sliding movements is increased on the basis of simple shape information. we developed a large-scale prototype of the flexible cable that has a ciliary drive mechanism and precise shape sensors to investigate our concept. we developed a kinetic model for the prototype by employing the nonlinear driving force model and the lateral friction model for representing slippages. further, we proposed a sliding motion control method that focus on the shape and length of the straight element. we applied the method to control the running direction. the experimental results and dynamic simulations demonstrated the effectiveness of sliding motion for controlling the running direction.
representing sets of orientations as convex cones. in a wide range of applications the orientation of a rigid body does not need to be restricted to one given orientation, but can be given as a continuous set of frames. we address the problem of defining such sets and to find simple tests to verify if an orientation lies within a given set. the unit quaternion is used to represent the orientation of the rigid body and we develop three different sets of orientations that can easily be described by simple constraints in quaternion space. the three sets discussed can also be described as convex cones in r3 defined by different norms. by describing the sets as convex cones and using certain properties of dual cones, we are able find simpler representations for the set of orientations and computationally faster and more accurate tests to verify if a quaternion lies within the given set.
trajectory generation of robotic fingers based on tri-axial tactile data for cap screwing task. in a previous paper, we developed a robotic finger equipped with optical three-axis tactile sensors, of which the sensing cell can separately detect normal and shearing forces. with appropriate precision, the robotic finger was able to perform three tasks: scanning flat specimens to obtain the friction coefficient, following the contour of objects, and manipulating a parallelepiped case put on a table by sliding it on the table. in the present study, designed as a follow-up to the above study, a robotic hand is composed of two robotic fingers. not only tri-axial force distribution directly obtained from the tactile sensor but also the time derivative of the shearing force distribution are used for the hand control algorithm: if grasping force measured from normal force distribution is lower than a threshold, grasping force is increased; the time derivative is defined as slippage; if slippage arises, grasping force is enhanced to prevent fatal slippage between the finger and an object. in the verification test, the robotic hand screws a bottle cap to close it. although input finger trajectories were a rectangular roughly decided to touch and screw the cap, a segment of the rectangular was changed from a straight line to a curved line to fit the cap contour. we concluded that higher order tactile information such as tri-axial tactile data can reduce the complexity of the control algorithm.
climbing rough vertical surfaces with hierarchical directional adhesion. prior research in biology and mechanics has shown the importance of hierarchy to the performance of dry adhesive systems on rough surfaces. the gecko utilizes several levels of hierarchy that operate on length scales from millimeters to 100s of nanometers in order to maneuver on smooth and rough vertical surfaces ranging from glass to rock. the gecko's hierarchical system serves two main purposes: it permits conformation to the surface for a large effective area of contact, and it distributes the load evenly among contacting elements. we present a new two-tiered directional adhesive system that provides these capabilities for a gecko-inspired climbing robot. the distal features consist of wedge-shaped structures with a base width of 50 µm and a height of approximately 180 µm. the wedges are mounted atop angled cylindrical features, 380 µm in diameter by approximately 1 mm long. together, the proximal and distal features bend preferentially in the direction of inclination when loaded with a tangential force, achieving a combination of directional adhesion and conformation to rough surfaces. using this system, a four legged robot that was previously restricted to climbing smooth surfaces is able to climb vertical surfaces such as a wood panels, painted metals, and plastics. on rougher surfaces, the two-tiered system improves adhesion by a factor of five compared to the wedge features alone. the hierarchical system also improved alignment and performance for large patch sizes.
path planning in 1000+ dimensions using a task-space voronoi bias. the reduction of the kinematics and/or dynamics of a high-dof robotic manipulator to a low-dimension "task space" has proven to be an invaluable tool for designing feedback controllers. when obstacles or other kinodynamic constraints complicate the feedback design process, motion planning techniques can often still find feasible paths, but these techniques are typically implemented in the high-dimensional configuration (or state) space. here we argue that providing a voronoi bias in the task space can dramatically improve the performance of randomized motion planners, while still avoiding non-trivial constraints in the configuration (or state) space. we demonstrate the potential of task-space search by planning collision-free trajectories for a 1500 link arm through obstacles to reach a desired end-effector position.
using a pocket-filling strategy for distributed reconfiguration of a system of hexagonal metamorphic robots in an obstacle-cluttered environment. we address the problem of reconfiguration planning for a metamorphic robotic system composed of a large number of hexagonal mobile robots. our objective is to develop an algorithm to plan the concurrent movement of individual robots over a lattice composed of identical robots, from an initial configuration i to a goal configuration g, when g contains one or more obstacles. the contribution of this paper is a deterministic motion planning algorithm to envelop multiple obstacles in an admissible set of goal configurations while eliminating the risk of module collision or deadlock. we developed a discrete event simulator to test our algorithms, and every admissible g tested was filled successfully. we include a full proof of correctness and analysis of our algorithm.
comparison of surface normal estimation methods for range sensing applications. as mobile robotics is gradually moving towards a level of semantic environment understanding, robust 3d object recognition plays an increasingly important role. one of the most crucial prerequisites for object recognition is a set of fast algorithms for geometry segmentation and extraction, which in turn rely on surface normal vectors as a fundamental feature. although there exists a plethora of different approaches for estimating normal vectors from 3d point clouds, it is largely unclear which methods are preferable for online processing on a mobile robot. this paper presents a detailed analysis and comparison of existing methods for surface normal estimation with a special emphasis on the trade-off between quality and speed. the study sheds light on the computational complexity as well as the qualitative differences between methods and provides guidelines on choosing the 'right' algorithm for the robotics practitioner. the robustness of the methods with respect to noise and neighborhood size is analyzed. all algorithms are benchmarked with simulated as well as real 3d laser data obtained from a mobile robot.
statistics for sparse, high-dimensional, and nonparametric system identification. local linearization techniques are an important class of nonparametric system identification. identifying local linearizations in practice involves solving a linear regression problem that is ill-posed. the problem can be ill-posed either if the dynamics of the system lie on a manifold of lower dimension than the ambient space or if there are not enough measurements of all the modes of the dynamics of the system. we describe a set of linear regression estimators that can handle data lying on a lower-dimension manifold. these estimators differ from previous estimators, because these estimators are able to improve estimator performance by exploiting the sparsity of the system - the existence of direct interconnections between only some of the states - and can work in the "large p, small n" setting in which the number of states is comparable to the number of data points. we describe our system identification procedure, which consists of a presmoothing step and a regression step, and then we apply this procedure to data taken from a quadrotor helicopter. we use this data set to compare our procedure with existing procedures.
interactive learning of the acoustic properties of household objects. human beings can perceive object properties such as size, weight, and material type based solely on the sounds that the objects make when an action is performed on them. in order to be successful, the household robots of the near future must also be capable of learning and reasoning about the acoustic properties of everyday objects. such an ability would allow a robot to detect and classify various interactions with objects that occur outside of the robot's field of view. this paper presents a framework that allows a robot to infer the object and the type of behavioral interaction performed with it from the sounds generated by the object during the interaction. the framework is evaluated on a 7-d.o.f. barrett wam robot which performs grasping, shaking, dropping, pushing and tapping behaviors on 36 different household objects. the results show that the robot can learn models that can be used to recognize objects (and behaviors performed on objects) from the sounds generated during the interaction. in addition, the robot can use the learned models to estimate the similarity between two objects in terms of their acoustic properties.
probabilistic graph-clear. this paper introduces a probabilistic model for multirobot surveillance applications with limited range and possibly faulty sensors. sensors are described with a footprint and a false negative probability, i.e. the probability of failing to report a target within their sensing range. the model implements a probabilistic extension to our formerly developed deterministic approach for modeling surveillance tasks in large environments with large robot teams known as graph-clear. this extension leads to a new algorithm that allows to answer new design and performance questions, namely 1) how many robots are needed to obtain a certain confidence that the environment is free from intruders, and 2) given a certain number of robots, how should they coordinate their actions to minimize their failure rate.
study on adhesion force reduction and state estimation by piezo-transducer. our previous paper presented a method for reducing adhesion forces by oscillation and showed the adhesion state can be checked by analyzing the data obtained by laser displacement meter. however, there are several problems in this method. 1)the end-effector must be located at the specific point where laser displacement meter can measure oscillation. 2)the adhesion state can not be checked if something blocks the light/laser or the target leaves the measuring point. 3)the total system becomes very large. to resolve these problems, this paper firstly presents a method for checking the adhesion state by piezo-transducer. next, to achieve more precise manipulation, we propose a method to deform the end-effector by adding dc input to the piezo actuator which is also oscillated simultaneously to reduce adhesion forces. furthermore, we find that the first mode resonance frequency shifts with the increase of the pushing force applied to the object by the end-effector. using the shift amount, we develop a method for checking the adhesion state.
a high-speed multi-gpu implementation of bottom-up attention using cuda. in this paper a novel implementation of the saliency map model on a multi-gpu platform using cuda technology is presented. the saliency map model is a well-known computational model for bottom-up attention selection and serves as a basis of many attention control strategies of cognitive vision systems. a real-time implementation is the prerequisite of an application of bottom-up attention on mobile robots and vehicles. parallel computation on graphics processing unit (gpu) provides an excellent solution for this kind of compute-intensive image processing. running on 1 to 4 nvidia geforce 8800 (gtx) graphics cards a frame rate of 313 fps at resolution of 640 × 480 is achieved, which is approximately 8.5 times faster than the standard implementations on cpus. the implementation is also evaluated using a high-speed camera at 200 hz. using two gpus only 2 ms extra computational time for the saliency map generation in addition to the camera capture time is required for images of 640 × 480 pixels.
visual homing and surprise detection for cognitive mobile robots using image-based environment representations. one important feature of a cognitive system is to perceive and understand its environment and to adapt its actions to changes and unforeseen situations. in this paper, we propose a scheme for visual surprise detection in cognitive mobile robots. with the robot's observation and a set of reference images previously acquired near its current viewpoint, a pixel-wise surprise trigger is computed using bayesian probabilistic inference techniques. with appropriate mathematical approximations this algorithm can be implemented on modern graphics hardware which nearly allows for real-time surprise detection. in order to refer to prior observations, a mobile robot has to be able to re-localize itself with respect to its environment. thus, we also present two online image-based homing algorithms which both facilitate the computation of location-independent surprise triggers. experiments show acceptable results in terms of robust and fast detection of unexpected changes in the environment.
bayesian plan recognition for brain-computer interfaces. for people with very severe motor dysfunctions, brain-computer interfaces (bcis) may provide the solution to regain mobility and manipulation capabilities. unfortunately, bcis are characterized by a limited bandwidth and uncertainty on the bci output. in the past, we have developed a bayesian plan recognition framework that estimates from uncertain human-robot interface signals the task a robot should execute. this paper extends our plan recognition framework to incorporate uncertain bci signals. a benchmark test is proposed and adopted to evaluate both the plan recognition framework and the performance of the bci user, for the concrete application of wheelchair driving.
combining area patrol, perimeter surveillance, and target tracking using ordered upwind methods. the problems of area patrol, perimeter surveillance, and target tracking are combined into a single reconnaissance framework. this integration is based on application of ordered upwind methods to track the propagation of the target position boundary. the ordered upwind methods provide a computationally efficient method for computing the target track boundary over a discretized nonuniform mesh of the environment. planning methods based on the target track boundary are discussed. simulation results demonstrate the use of ordered upwind methods for reconnaissance tasks.
achieving efficient and stable comanipulation through adaptation to changes in human arm impedance. we focus on comanipulation, i.e. manipulation of an object simultaneously held by a robot and a human operator. in this domain, a major difficulty is raised by significant variations of human dynamics, which depend not only on the arm posture, but also on the muscular activity (muscular co-contraction) and more generally on the type of task being performed: fine positioning, gross and rapid movements, repeated movements, etc. an ideal comanipulation system should be able of adapting its behavior to the operator's functional intention, resulting in an intuitive assisting device. toward this goal, we present in this paper first results of our research aimed at developing an instrumented handle mounted on a robot end-effector and held by an operator, that can be used for estimating the grasping force and for adapting the robot controller accordingly. we show first experimental evidences that changes in the grasping force drastically affect the robot controller performances. we thus propose a handle design and a gain scheduling strategy that result in a robot behavior adequate for any kind of grasps. this solution is successfully experimented with a 1 degree of freedom robot under largely variable comanipulation conditions, exhibiting a stable and efficiently adaptive behavior.
the "dlr crash report": towards a standard crash-testing protocol for robot safety - part ii: discussions. after giving a rich data basis of our impact tests with standardized crash-test dummies in part i of this work we address in part ii various aspects related to these tests in a case based discussion. the presented facts, the knowledge gained from our previous work, and the data from part i lead us to recommendations for standardized crash-testing procedures in robotics. the proposed impact procedures will help to compare blunt robot-human impacts on a common basis. we will discuss additional requirements which will enhance the completeness of testing procedures.
3d voxel based online human pose estimation via robust and efficient hashing. in this paper, we present a novel framework to recover human body pose on multi camera systems. our framework leverages 3d voxel data, which are reconstructed from multi-camera systems. the use of voxel data leads to viewpoint-free estimation, which benefits in that reconstruction of a training model is needless in different multicamera arrangements. other notable aspects of our approach are real-time ensuring speed (up to 30 fps), flexibility towards various complex motions and environments. we treat the pose estimation problem as estimating human pose label from the voxel features and tackle this by example based approach. to ensure the real-time speed and to improve precision of pose estimation, a newly fast and robust near-neighbor search metric is installed prior to the evaluation process, what we call csi-psh. we demonstrate the effectiveness of our approach with experiments on both synthetic and real image sequences.
on the switching control of multiple mobile robots formation. this paper considers the formation control of multiple skid-steered mobile robots with nonholonomic constraint in each robot dynamics. we propose a switching control method based on local sensor-based information for the group of robots. if the distance between leader and follower robots is larger than the switching thershold, a nonlinear control law is employed to make the followers move effectively toward the leader robot; otherwise, finite-time control based on feedback linearization is used to quickly stabilize the relative distance and orientation of the follower robots. both stability analysis and simulations are provided and moreover, the formation control of pioneer 3-at mobile robots by the proposed method is shown.
image-based path following control of mobile robots with central catadioptric cameras. the research of image-based control for nonholonomic mobile robots is a recent topic of mobile robots. there are few researches about image-based control of mobile robots with central catadioptric cameras. a central catadioptric camera is very effective to keep target objects in the camera field of view because of its wide area view. in this paper, a new image-based path following control method for a nonholonomic mobile robot with a central catadioptric camera is proposed in the image parameter space. it is confirmed by several simulation, indoor and outdoor experiments that the designed system has high performance and robustness in real world.
vision-aided inertial navigation on an uncertain map using a particle filter. this paper presents a vision-based navigation solution for unmanned aircraft operations on airfield surfaces in gps-denied environments. the unmanned aircraft system ground operations management system (ugoms) described here combines measurements from a computer vision system and inertial sensors with an airport layout database to provide real-time position determination on the airfield surface. ugoms provides both absolute position of the aircraft as well as relative position to airport surface elements such as runway hold lines and taxiway edges. the key technical components of ugoms are computer vision algorithms that classify image regions, markov localization using particle filters, and a navigation architecture which incorporates the localization information. an overview of the overall ugoms architecture is presented as well as preliminary test results using an uncertain airfield map to highlight the performance capabilities of the system.
estimation of the camera pose from image point correspondences through the essential matrix and convex optimization. estimating the camera pose in stereo vision systems is an important issue in computer vision and robotics. one popular way to handle this problem consists of determining the essential matrix which minimizes the algebraic error obtained from image point correspondences. unfortunately, this search amounts to solving a nonconvex optimization, and the existing methods either rely on some approximations in order to get rid of the non-convexity or provide a solution that may be affected by the presence of local minima. this paper proposes a new approach to address this search without presenting such problems. in particular, we show that the sought essential matrix can be obtained by solving a convex optimization built through a suitable reformulation of the considered minimization via appropriate techniques for representing polynomials. numerical results show the proposed approach compares favorably with some standard methods in both cases of synthetic data and real data.
reliable control during current loop failure using etf for position servo system including disturbance observer. a reliable control method is proposed for multiple loop control systems. if a feedback loop fails (e.g., as a result of a sensor breakdown), the control system develops an unstable fluctuation. to cope with this problem, the proposed method uses an equivalent transfer function (etf) for active redundancy compensation after loop failure. the etf is used to maintain the transfer function of the entire system the same before and after loop failure. in this study, the characteristics of a reliable control system that uses an etf were examined experimentally. a position servo system including a disturbance observer is used in the experiment. in case of feedback loop failure, the control system could not be stabilized using the disturbance observer alone; however, the etf stabilized the control system after feedback loop failure.
control of mobile manipulator using the dynamical systems approach. the combination of a mobile platform and a manipulator, known as a mobile manipulator, provides a highly flexible system, which can be used in a wide range of applications, especially within the field of service robotics. one of the challenges with mobile manipulators is the construction of control systems, enabling the robot to operate safely in potentially dynamic environments. in this paper we will present work in which a mobile manipulator is controlled using the dynamical systems approach. the method presented is a two level approach in which competitive dynamics are used both for the overall coordination of the mobile platform and the manipulator as well as the lower level fusion of obstacle avoidance and target acquisition behaviors.
coordination of multiple non-holonomic agents with input constraints. in this paper we present a multi-agent coordination algorithm suitable for systems with aircraft-like kinematic constraints. a model of a system of input-constrained nonholonomic agents is constructed, suitable for use with formal verification tools. the agents considered are uniform and have bounded velocities and limited turning capabilities. we demonstrate how a model checker can be used to generate a counterexample trace for such a system, usable as a trajectory that satisfies our safety and liveness requirements.
prediction and imitation of other's motions by reusing own forward-inverse model in robots. this paper proposes a model that enables a robot to predict and imitate the motions of another by reusing its body forward-inverse model. our model includes three approaches: (i) projection of a self-forward model for predicting phenomena in the external environment (other individuals), (ii) "triadic relation" that is mediation by a physical object between self and others, (iii) introduction of infant imitation by a parent. the recurrent neural network with parametric bias (rnnpb) model is used as the robot's self forward-inverse model. a group of hierarchical neural networks are attached to the rnnpb model as "conversion modules". experiments demonstrated that a robot with our model could imitate a human's motions by translating the viewpoint. it could also discriminate known/unknown motions appropriately, and associate whole motion dynamics from only one motion snap image.
learning to detect loop closure from range data. despite significant developments in the simultaneous localisation and mapping (slam) problem, loop closure detection is still challenging in large scale unstructured environments. current solutions rely on heuristics that lack generalisation properties, in particular when range sensors are the only source of information about the robot's surrounding environment. this paper presents a machine learning approach for the loop closure detection problem using range sensors. a binary classifier based on boosting is used to detect loop closures. the algorithm performs robustly, even under potential occlusions and significant changes in rotation and translation. we developed a number of features, extracted from range data, that are invariant to rotation. additionally, we present a general framework for scan-matching slam in outdoor environments. experimental results in large scale urban environments show the robustness of the approach, with a detection rate of 85% and a false alarm rate of only 1%. the proposed algorithm can be computed in real-time and achieves competitive performance with no manual specification of thresholds given the features.
cardiolock2: parallel singularities for the design of an active heart stabilizer. in this paper, the design of a new active cardiac stabilizer, cardiolock2, is presented. following the proof of concept cardiolock [7], this device allows an active stabilization of the surface of a beating heart in two directions, which is considered sufficient for a complete stabilization. piezoelectric actuation is combined with a compliant architecture to obtain high dynamics and accuracy. a remote center of motion is obtained with a serial architecture, and parallel mechanisms in configurations close to singularity are used to increase the workspace. a kinematic analysis is first presented, before detailing the main properties of the device and the current development of the prototype.
stable dynamic walking of a quadruped via phase modulations against small disturbances. it is generally accepted that locomotion in animals is based on a trade-off between energy consumption and stability. however, this trade-off is the result of the interaction between complex mechanical and control systems. to gain insight into that issue, a step-by-step approach is needed. in this study, as a first step to investigate three dimensional quadrupedal walking, we aim at establishing a control system as "minimal" as possible, able to realize stable dynamic walk. using a simple mechanical structure, we realized dynamic walk with a distributed control system, made of four independent leg controllers whose swing and stance phases durations are modulated based on leg loading information. phase modulations contribute to stabilize the posture in the frontal plane via automatic duty ratios adjustments that tend to compensate perturbations of the body rolling motion. by applying lateral perturbations, we found that the control system withstands well perturbations increasing the rolling motion amplitude, but is sensible to perturbations that suddenly decrease it, as the foreleg on the more loaded side is prevented to swing. hence, we implemented an ascending coordination mechanism where the transition to swing in a hind leg promotes the same event in the foreleg. the duration of the subsequent foreleg swing phase is reduced to prevent excessive increase of the rolling motion amplitude. the resultant control system, although extremely simple, was able to realize dynamic walk resistant to small disturbances (lateral perturbations and terrain irregularities).
battery state estimation using unscented kalman filter. online evaluation of battery state of function (sof) is crucial for battery management systems of autonomous mobile robots. battery state of charge (soc) represents its remaining energy available, whereas internal resistance and capacity reflect its state of health (soh). in this paper, an improved equivalent circuit model is proposed to estimate soc, internal resistance and capacity using an unscented kalman filter (ukf). the proposed method not only estimates soc, but also evaluates soh and sof. experimental results have shown the effectiveness of the proposed method using resistive loads and a robot prototype for inspecting power transmission line.
effects of compliant ankles on bipedal locomotion. the influence of ankle compliance on bipedal robot locomotion is investigated in this paper. the focus is on reduction of energy consumption. the concept of hybrid zero dynamics is adapted to design walking gaits with three phases: underactuated heel roll, full actuation and underactuated toe roll. ankle springs work in parallel with the ankle actuators. stiffness and offset of the linear torsional springs at the ankle and gait parameters are optimized simultaneously. it is shown that simultaneous optimization of spring properties and gait is superior to optimizing the spring after the gait. optimal spring stiffness and offset lead to a major reduction in energy consumption. furthermore, a more human-like gait is observed for simultaneous optimization of gait and spring parameters compared to gait optimization with zero stiffness.
visual servoing and characterization of resonant magnetic actuators for decoupled locomotion of multiple untethered mobile microrobots. wireless resonant magnetic micro-actuators have been previously described as highly effective propulsion mechanisms for untethered mobile microrobots. the discussion thus far has been primarily relegated to a characterization of stationary devices and the de facto observation of their mobility. before applications of microrobots can be more fully explored, devices are required that can operate reliably and repeatably in a host of operating environments. in this paper, we analyze the in situ performance of resonant magnetic actuators for microrobotic locomotion to better understand their durability, substrate requirements, and driving characteristics.
natural self motion of a robotic limb with single degree-of-redundancy. the self motion of a kinematically redundant robotic limb with single degree of redundancy is analyzed, focusing thereby on the nonlinear self-motion component. the role of this component has been completely ignored in past studies on self motion. it is shown that jacobian pseudoinverse-based resolution -- the usual resolution method for nonlinear self-motion -- yields poor dynamic performance. a special type of self motion is identified based on the natural metric on the self-motion manifold and the energy conservation principle. this type of self motion is shown to have superior dynamics in terms of torque requirement and to avoid abrupt fluctuations in acceleration in the vicinity of singular points.
modular weight-balanced mechanical tracker for portable haptics. this paper describes the design, the development and the tests of an innovative 6 degrees of freedom (dofs) mechanical tracker. the new device has a modular structure that exploits three mechanical units each composed of two rotational joints and allows to scale the usable workspace by substituting the connecting links. the sensing principle for the joint angles measurement is based on an innovative hall-effect angle sensor with high resolution, developed and conceived for low cost applications. the system that has been realized and tested is conceived for the tracking of portable haptic devices. furthermore, the system includes a weight balancing system that allows to exploit the mechanical structure of the tracker for balancing a given weight located at the end-effector of the device.
orbital stabilization of a pre-planned periodic motion to swing up the furuta pendulum: theory and experiments. the problem of swinging up inverted pendulums has often been solved by stabilization of a particular class of homoclinic structures present in the dynamics of the standard pendulum. in this article new arguments are suggested to show how different homoclinic curves can be preplanned for dynamics of the passive-link of the robot. this is done by reparameterizing the motion according to geometrical relations among the generalized coordinates. it is also shown that under certain conditions there exist periodic solutions surrounding such homoclinic orbits. these trajectories admit designing feedback controllers to ensure exponential orbital stabilization. the method is illustrated by simulations and supported by experimental studies.
an efficient parallel approach to random sample matching (pransam). this paper introduces a parallelized variant of the random sample matching (ransam) approach, which is a very time and memory efficient enhancement of the common random sample consensus (ransac). ransam exploits the theory of the birthday attack whose mathematical background is known from cryptography. the ransam technique can be applied to various fields of application such as mobile robotics, computer vision, and medical robotics. since standard computers feature multi-core processors nowadays, a considerable speedup can be obtained by distributing selected subtasks of ransam among the available cores. first of all this paper addresses the parallelization of the ransam approach. several important characteristics are derived from a probabilistic point of view. moreover, we apply a fuzzy criterion to compute the matching quality, which is an important step towards real-time capability. the algorithm has been implemented for windows and for the qnx rtos. in an experimental section the performance of both implementations is compared and our theoretical results are validated.
generic decoupled image-based visual servoing for cameras obeying the unified projection model. in this paper a generic decoupled imaged-based control scheme for calibrated cameras obeying the unified projection model is proposed. the proposed decoupled scheme is based on the surface of object projections onto the unit sphere. such features are invariant to rotational motions. this allows the control of translational motion independently from the rotational motion. finally, the proposed results are validated with experiments using a classical perspective camera as well as a fisheye camera mounted on a 6 dofs robot platform.
singularity avoidance for over-actuated, pseudo-omnidirectional, wheeled mobile robots. for mobile platforms with steerable standard wheels it is necessary to precisely coordinate rotation and steering angle of their wheels. an established approach to ensure this is to represent the current state of motion in form of the instantaneous centre of motion (icm) and to derive a trajectory within this space. however, while control in the icm space does guarantee adherence to the system's nonholonomic constraints, it does not avoid the system's singular configurations. within this work we address the problem of singularity avoidance within the icm space. singularities related to the mathematical representation of the icm are reduced by a reformulation of this representation. furthermore, a controller based on artificial potential fields avoiding singular configurations of the robot by representing them as obstacles in the derived icm space is designed. the resulting controller is particularized and analyzed w.r.t. the care-o-bot 3 demonstrator.
oriented bounding surfaces with at most six common normals. we present a new type of oriented bounding surfaces, which is particularly well suited for shortest distance computations. the bounding surfaces are obtained by considering surfaces whose support functions are restrictions of quadratic polynomials to the unit sphere. we show that the common normals of two surfaces of this type - and hence their shortest distance - can be computed by solving a polynomial of degree six. this compares favorably with other existing bounding surfaces, such as quadric surfaces, where the computation of the common normals is known to lead to a polynomial of degree 24.
task-space trajectories via cubic spline optimization. we consider the task of planning smooth trajectories for robot motion. in this paper we make two contributions. first we present a method for cubic spline optimization; this technique lets us simultaneously plan optimal task-space trajectories and fit cubic splines to the trajectories, while obeying many of the same constraints imposed by a typical motion planning algorithm. the method uses convex optimization techniques, and is therefore very fast and suitable for real-time re-planning and control. second, we apply this approach to the tasks of planning foot and body trajectory for a quadruped robot, the "littledog," and show that the proposed approach improves over previous work on this robot.
navigation through urban environments by visual perception and interaction. in the autonomous city explorer (ace) project a mobile robot is developed, which is capable of finding its way to a given destination in an unknown urban environment. an exemplary mission is to find the way from our institute to the marienplatz, a public place in the center of munich, without any prior knowledge or gps information. inspired by the behavior of humans in unknown environments, ace must find its way by asking pedestrians. the route is about 1.5 kilometers far and includes heavily traveled roads and crowded public places. in order to navigate safely in an unknown urban environment, some challenges arise for the vision system. robust human detection, tracking and the estimation of human body poses is essential for natural interaction with pedestrians. furthermore, the robot needs to be able to detect sidewalk and crossroads. a visual odometry system is used to support the conventional navigation. outdoor experiments were conducted twice successfully. after about 5 hours and interacting with 25 and 38 persons respectively, ace arrived the marienplatz. this paper describes both, an architecture of the vision system used for ace and the algorithms used to deal with the described challenges.
graph-based planning using local information for unknown outdoor environments. one of the common applications for outdoor robots is to follow a path in large scale unknown environments. this task is challenging due to the intensive memory requirements to represent the map, uncertainties in the location estimate of the robot and unknown terrain type and obstacles on the way to the goal. we develop a novel graph-based path planner that is based on only local perceptual information to plan a path in such environments. in order to extend the capabilities of the graph representation, we introduce exploration bias, which is a node attribute that can implicitly encode obstacle features at immediate surrounding of a node in the graph, the uncertainty of the planner about a node location and also the frequency of visiting a location. through simulation experiments, we demonstrate that the resulting path cost and distance that the robot traverses to reach the goal location is not significantly different from those of the previous approaches.
finding the optimal strategies for robotic patrolling with adversaries in topologically-represented environments. using autonomous mobile robots to patrol environments for detecting intruders is a topic of increasing relevance for its possible applications. a large part of strategies for mobile patrolling robots proposed so far adopt some kind of random movements. although these strategies are unpredictable for an intruder, they are not always efficient in getting the patroller a large expected utility. in this paper we propose an approach that considers a model of the adversary in a game theoretic framework to find optimally-efficient patrolling strategies. we show that our approach extends those proposed in literature and we experimentally analyze some of its features.
a framework for modeling steady turning of robotic fish. in this paper we present a novel framework for computing the steady turning motion of a robotic fish undergoing periodic body and/or tail deformation. taking the turning radius and the angular velocity as unknowns, we obtain the absolute motion trajectories of points on the "spinal column" of robotic fish by superimposing relative body/tail motions on the rigid body circular motion. the hydrodynamic reactive force and the resulting moment are then computed from the motion trajectories, using lighthill's large-amplitude elongated-body theory, in terms of the two turning parameters. by integrating the dynamics of rigid body motion and averaging out oscillations, implicit equations involving the turning parameters can be established and solved. we also discuss the plan of applying the proposed framework to the modeling of steady turning maneuvers of biomimetic robotic propelled by an ionic polymer-metal composite (ipmc) caudal fin.
onboard contextual classification of 3-d point clouds with learned high-order markov random fields. contextual reasoning through graphical models such as markov random fields often show superior performance against local classifiers in many domains. unfortunately, this performance increase is often at the cost of time consuming, memory intensive learning and slow inference at testing time. structured prediction for 3-d point cloud classification is one example of such an application. in this paper we present two contributions. first we show how efficient learning of a random field with higher-order cliques can be achieved using subgradient optimization. second, we present a context approximation using random fields with high-order cliques designed to make this model usable online, onboard a mobile vehicle for environment modeling. we obtained results with the mobile vehicle on a variety of terrains, at 1/3 hz for a map 25 × 50 meters and a vehicle speed of 1-2 m/s.
force estimation in a piezoelectric cantilever using the inverse-dynamics-based uio technique. this paper presents the estimation of the force applied by a piezocantilever dedicated to micromanipulation/microassembly. relative to previous works, the presented method avoids the reliance on the force dynamics on the characteristics of the micro-objects. furthermore, the estimation is a closed-loop kind technique so that convergency can be ensured efficiently. to perform these, we consider the force at the tip of a piezocantilever as an unknown input and we use an unknown input observation technique. we especially use the inverse-dynamics-based uio technique because it is well suited for a piezocantilever model. the experiments show that the performances of the observer are convenient for micromanipulation/microassembly tasks.
a geometric approach for the design of singularity-free parallel robots. while a number of researchers have published results in the area of parallel robot singularity determination and the a posteriori elimination of these singularities, far less work has been published in the area of singularity free workspace design. several researchers have committed substantial funds to design hardware prototypes that have proven worthless because of unavoidable singularities. this trend, if carried over to industrial applications, could prove especially detrimental to the future of applied parallel robotics. a comprehensive and straightforward design strategy that guarantees a singularity free workspace is presented in this paper. the design problem is mathematically modeled, and relaxations are suggested for finding solutions. the translational 3-upu parallel robot is studied to verify the efficacy of the design approach.
passive event-based extrapolation for lossy haptic data compression in bilateral presence systems. a new lossy compression method is proposed for haptic (force, velocity) data as exchanged in bilateral telepresence systems. the method is based on the passive extrapolative compression strategy proposed in [1]. the innovation is that the extrapolations do not have a stiff horizon, but are triggered by considerable changes (events) in the target environment. this enables longer average extrapolation horizons and thus, higher compression. experiments are conducted using two dlr light weight robots. the results indicate that the method outperforms older implementations.
observations and models for needle-tissue interactions. the asymmetry of a bevel-tip needle results in the needle naturally bending when it is inserted into soft tissue. in this study we present a mechanics-based model that calculates the deflection of the needle embedded in an elastic medium. microscopic observations for several needle-gel interactions were used to characterize the interactions at the bevel tip and along the needle shaft. the model design was guided by microscopic observations of several needle-gel interactions. the energy-based model formulation incorporates tissue-specific parameters such as rupture toughness, nonlinear material elasticity, and interaction stiffness, and needle geometric and material properties. simulation results follow similar trends (deflection and radius of curvature) to those observed in macroscopic experimental studies of a robot-driven needle interacting with different kinds of gels. these results contribute to a mechanics-based model of robotic needle steering, extending previous work on kinematic models.
a simple nonlinear pid control for finite-time regulation of robot manipulators. a simple nonlinear proportional-integral-derivative (pid) controller is proposed to solve the finite-time regulation of uncertain robot manipulators. the semiglobal finite-time stabilization is shown by using lyapunov theory and finite-time stability theory. the proposed control algorithm does not involve the modeling information in the control law formulation and the control gains can be explicitly determined based on some well-known bounds extracted from the robot dynamics, and thus permits easy implementation. simulations preformed on a two degrees-of-freedom (dof) manipulator demonstrate the expected properties of the proposed approach.
mechanics of bending, torsion, and variable precurvature in multi-tube active cannulas. active cannulas are a relatively new continuum robot subclass characterized by their use of preshaped tubes that transmit bending moments as they slide within one another and are axially rotated. previous (experimentally vetted) mechanics-based models of active cannula shape assume piece-wise constant precurvature of component tubes, and neglect torsion in curved sections of the device. recently a general, coordinate-free, energy-based framework for active cannula shape has been formulated that relaxes these requirements and includes all prior models as special cases. however, only the 2-tube, constant-precurvature case has thus far been explored in detail using the framework. in this paper we consider the general case of an arbitrary number of component tubes and precurvatures that vary with arc length, deriving a set of differential equations that capture both bending and torsional effects continuously along the active cannula backbone. we then show how to solve these differential equations numerically to describe active cannula shape.
autonomous robot cameraman - observation pose optimization for a mobile service robot in indoor living space. this paper presents a model based system for a mobile robot to find an optimal pose for the observation of a person in indoor living environments. we define the observation pose as a combination of the camera position and view direction as well as further parameters like the aperture angle. the optimal placement of a camera is not trivial because of the high dynamic range of the scenes near windows or other bright light sources, which often results in poor image quality due to glare or hard shadows. the proposed method tries to minimize these negative effects by determining an optimal camera pose based on two major models: a spatial free space model and a representation of the lighting. in particular, a task-dependent optimization takes into account the intended purpose of the camera images, e.g. different inputs are needed for video communication with other people or for an image-processing based passive observation of the person's activities. to prove the validity of our approach, we present first experimental results comparing the chosen observation pose and resulting image with and without respect to lighting in different observation tasks.
a force control based cell injection approach in a bio-robotics system. robotic cell injection is a technique that employs automated device to insert substances into a single living cell with a fine needle. most existing microinjection methods are based on position control without explicit regulation of the injection force. the injection force, if not controlled properly, may destroy the cell and lead to death of the cells. in this paper, we propose a force control based cell injection technology to explicitly regulate the injection force to follow the desired force trajectory during the injection. any desired force trajectory that is twice continuously differentiable can be realized by the proposed approach. the convergence of the force tracking algorithm is provably guaranteed. experiments performed on a laboratorial robotic cell injection system demonstrate the effectiveness of the proposed approach.
potential field guide for humanoid multicontacts acyclic motion planning. we present a motion planning algorithm that computes rough trajectories used by a contact-points planner as a guide to grow its search graph. we adapt collision-free motion planning algorithms to plan a path within the guide space, a submanifold of the configuration space included in the free space in which the configurations are subject to static stability constraint. we first discuss the definition of the guide space. then we detail the different techniques and ideas involved: relevant c-space sampling for humanoid robot, task-driven projection process, static stability test based on polyhedral convex cones theory's double description method. we finally present results from our implementation of the algorithm.
trajectory planning and control of an underactuated dynamically stable single spherical wheeled mobile robot. the ballbot is a dynamically stable mobile robot that moves on a single spherical wheel and is capable of omnidirectional movement. the ballbot is an underactuated system with nonholonomic dynamic constraints. the authors propose an offline trajectory planning algorithm that provides a class of parametric trajectories to the unactuated joint in order to reach desired static configuration of the system with regard to the dynamic constraint. the parameters of the trajectories are obtained using optimization techniques. a feedback controller is proposed that ensures accurate trajectory tracking. the trajectory planning algorithm and tracking controller are validated experimentally. the authors also extend the offline trajectory planning algorithm to a generalized case of motion between non-static configurations.
motion control of multi-limbed robots for asteroid exploration missions. the interest on the study of asteroids has increased due to the recent missions that have been sent to explore such low gravity bodies. due to its complexity, little attention has been given to close surface analysis by a mobile robotic system. in this paper, the authors present a study on the locomotion of limbed robotic systems based on the detection of friction force in an emulated microgravity environment. the issues rose by the microgravity environment and its effect on the dynamics of such robotic system during motion are addressed, and an algorithm to generate compliant motion gaits is presented. experimental results show that the control system is capable of maintaining balanced contacts during motions.
robot kinematics based model to predict compensatory motion of transradial prosthesis while performing bilateral tasks. in order to perform activities of daily living (adl), a person with an amputation(s) must use a greater than normal range of movement from other anatomical body joints to compensate for the loss of movement caused by the amputation, this is called compensatory motion. by studying the compensatory motion of prosthetic users the mechanics of how they adapt to the loss of range of motion in a given limb for can be analyzed for select tasks. the purpose of this study is to create a robotic based kinematic model that can simulate the compensatory motion of a given task using given subject data. this paper reviews the use of the model to simulate compensatory motion of a transradial amputee performing two bilateral tasks: turning a steering wheel, and lifting a box. the simulation operates by changing a set of prosthetic configurations that are represented by parameters that consist of the joint degrees of freedom (dof) provided by each prosthesis in the set. the task information is inputted into the model by defining a trajectory which the hand or prosthesis must follow to perform the task. the inclusion of the ability to model bilateral tasks is accomplished by giving control of the proximal joints to the prosthetic side. analysis of tasks is completed by running the simulation with prosthetic and anatomical constraints attached to the left arm of the model, the right arm maintains an anatomical configuration. by running the model through this simulation the compensatory motions can be determined. results obtained from the model can be used to select the best prosthesis for a given user, design prostheses that are more effective at selected tasks, further analyze previous studies, or to determine areas of interest for further human study.
visual topological slam and global localization. visual localization and mapping for mobile robots has been achieved with a large variety of methods. among them, topological navigation using vision has the advantage of offering a scalable representation, and of relying on a common and affordable sensor. in previous work, we developed such an incremental and real-time topological mapping and localization solution, without using any metrical information, and by relying on a bayesian visual loop-closure detection algorithm. in this paper, we propose an extension of this work by integrating metrical information from robot odometry in the topological map, so as to obtain a globally consistent environment model. also, we demonstrate the performance of our system on the global localization task, where the robot has to determine its position in a map acquired beforehand.
a genericity condition for general serial manipulators. generic manipulators possess the desireable properties that their set of singulartities is a smooth manifold, and that the drop of rank of the manipulator jacobian is bounded. a sufficient condition for genericity is the transverse-regularity of its jacobian mapping in any configuration. in this paper a necessary and sufficient condition for transverse-regularity is presented. the condition is based on the manipulator's joint screws and their screw products. it is also shown that a manipulator is non-generic if it can attain a pose where the rank of the manipulator's screw system together with the screw products is not the maximal rank of the jacobian.
gaussian process modeling of large scale terrain. this paper addresses the problem of large scale terrain modeling for a mobile robot. building a model of large scale terrain data that can adequately handle uncertainty and incompleteness in a statistically sound way is a very challenging problem. this work proposes the use of gaussian processes as models of large scale terrain. the proposed model naturally provides a multi-resolution representation of space, incorporates and handles uncertainties aptly and copes with incompleteness of sensory information. gaussian process regression techniques are applied to estimate and interpolate (to fill gaps in unknown areas) elevation information across the field. the estimates obtained are the best linear unbiased estimates for the data under consideration. a single non-stationary (neural network) gaussian process is shown to be powerful enough to model large and complex terrain, handling issues relating to discontinuous data effectively. a local approximation methodology based on kd-trees is also proposed in order to ensure local smoothness and yet preserve the characteristic features of rich and complex terrain data. the use of the local approximation technique based on kd-trees further addresses concerns relating to the scalability of the proposed approach for large data sets. experiments performed on sparse gps based survey data as well as dense laser scanner data taken at different mine-sites are reported in support of these claims.
utilizing object-object and object-scene context when planning to find things. in this paper, our goal is to search for a novel object, where we have a prior map of the environment and knowledge of some of the objects in it, but no information about the location of the specific novel object. we develop a probabilistic model over possible object locations that utilizes object-object and object-scene context. this model can be queried for any of over 25,000 naturally occurring objects in the world and is trained from labeled data acquired from the captions of photos on the flickr website. we show that these simple models based on object co-occurrences perform surprisingly well at localizing arbitrary objects in an office setting. in addition, we show how to compute paths that minimize the expected distance to the query object and show that this approach performs better than a greedy approach. finally, we give preliminary results for grounding our approach in object classifiers.
modelling and control of obstacle-aided snake robot locomotion based on jam resolution. a snake robot can traverse cluttered and irregular environments by using irregularities around its body as pushpoints to aid the propulsion. this characteristic feature of snake locomotion, denoted obstacle-aided locomotion, has received limited focus in previous literature. this paper presents a model of this phenomenon and a control strategy employing measured contact forces to maintain propulsion while simultaneously preventing the snake robot from being jammed between obstacles in its path. the simulation results validate the contact modelling approach and the effectiveness of the proposed control strategy.
physical parameter identification of rheological object based on measurement of deformation and force. there are many kinds of deformable objects in our living life. some of them exhibit rheological behaviors when they are subject to external force, such as human tissues, human organs, and food. if we want to simulate or control such behaviors, we have to know the physical parameters of the object in advance. in this paper, we propose an approach to identify these parameters based on 2d finite element (fe) simulation and measurement of deformation and force. at first, 2d fe model used to simulate rheological deformation was described. then, identification method was presented according to the analysis of simulation results. identification results for simulation were also given. finally, this method was applied to a object made of clay. deformation and force were measured by camera and tactile sensor respectively. the identification results show the validity and effectiveness of this method.
semi-closed microchip for probe manipulation and the target cell harvesting. in this paper, we propose a semi-closed microchip which can realize the probe type manipulation in the microchip with the internal environment sealed off from the external environment. long-term experiments can be conducted for in-situ culture and analysis of cells by the semi-closed microchip. the semi-closed microchip has a bath in the middle of microchannel to allow the insertion of micropipettes into the microchip. the bath is sealed off by thin oil film to prevent the evaporation of the solution in the bath. the seal by the oil film can maintain even if micropipettes are inserted into the bath and pulled out from the bath because the oil film can fill the hole by its surface tension. the seal by the oil film was evaluated by measuring the weight of the bath after 12/24 hours. to use the semi-closed microchip for cell culture and cell analysis, the exchange of the solution in the bath was demonstrated. it was also demonstrated that the cell fixation with the thermo sensitive gel in the proposed semi-closed microchip by fabricating the ito electrodes as heaters in the bath. cell culture and the target cell harvesting were conducted by the semi-closed microchip. the proposed semi-closed microchip can be used for cell culture, cell analysis and cell harvesting under a microscope as the biological applications for single cell analysis.
playing with toys: towards autonomous robot manipulation for therapeutic play. when young children play, they often manipulate toys that have been specifically designed to accommodate and stimulate their perceptual-motor skills. robotic playmates capable of physically manipulating toys have the potential to engage children in therapeutic play and augment the beneficial interactions provided by overtaxed care givers and costly therapists. to date, assistive robots for children have almost exclusively focused on social interactions and teleoperative control. within this paper we present progress towards the creation of robots that can engage children in manipulative play. first, we present results from a survey of popular toys for children under the age of 2 which indicates that these toys share simplified appearance properties and are designed to support a relatively small set of coarse manipulation behaviors. we then present a robotic control system that autonomously manipulates several toys by taking advantage of this consistent structure. finally, we show results from an integrated robotic system that imitates visually observed toy playing activities and is suggestive of opportunities for robots that play with toys.
what to do and how to do it: translating natural language directives into temporal and dynamic logic representation for goal management and action execution. robots that can be given instructions in spoken language need to be able to parse a natural language utterance quickly, determine its meaning, generate a goal representation from it, check whether the new goal conflicts with existing goals, and if acceptable, produce an action sequence to achieve the new goal (ideally being sensitive to the existing goals). in this paper, we describe an integrated robotic architecture that can achieve the above steps by translating natural language instructions incrementally and simultaneously into formal logical goal description and action languages, which can be used both to reason about the achievability of a goal as well as to generate new action scripts to pursue the goal. we demonstrate the implementation of our approach on a robot taking spoken natural language instructions in an office environment.
robust velocity sliding mode control of mobile wheeled inverted pendulum systems. there has been an increasing interest in a kind of underactuated mechanical systems, mobile wheeled inverted pendulum (mwip) models, which are widely used in the field of autonomous robotics and intelligent vehicles. robust velocity tracking problem of mwip systems is investigated in this study. in the velocity control problem, model uncertainties accompany uncertain equilibriums, which make the controller design become more difficult. a sliding mode control (smc) method based on a novel sliding surface is proposed for the systems, which are capable of handling both parameter uncertainties and external disturbances. by assuming the specially designed sliding surface, the proposed smc controller is capable of eliminating the steady velocity tracking error. the asymptotical stability of the closed-loop system is achieved through selecting sliding surface parameters in terms of some rules. the effectiveness of the proposed methods is finally confirmed by numerical simulations.
effects of geometric imperfections to the control of redundantly actuated parallel manipulators. the model-based control of robotic manipulators relies on an exact model of the manipulator. redundantly actuated pkm posses the ability to exhibit internal prestress that does not affect its environment. this allows for a purposeful distribution of control forces, taking into account secondary tasks, such optimal force distribution, active stiffness, and backlash avoiding control. in the presence of kinematic uncertainties this feature can become a serious problem since then the control forces may be annihilated or even some of the intentional prestress components may interfere with the environment. the effect of such kinematic uncertainties and the application of standard model-based control schemes is analyzed in this paper. it is shown that, in the presence of model uncertainties, it leads to parasitic perturbation forces that can not be compensated by the controls. an amended version of the augmented pd and computed torque control scheme is proposed that removes the parasitic feedback forces.
1000 trials: an empirically validated end effector that robustly grasps objects from the floor. unstructured, human environments present great challenges and opportunities for robotic manipulation and grasping. robots that reliably grasp household objects with unknown or uncertain properties would be especially useful, since these robots could better generalize their capabilities across the wide variety of objects found within domestic environments. within this paper, we address the problem of picking up an object sitting on a plane in isolation, as can occur when someone drops an object on the floor - a common problem for motor-impaired individuals. we assume that the robot has the ability to coarsely position itself in front of the object, but otherwise grasps the object with an open-loop strategy that does not vary from object to object. we present a novel end effector that is capable of robustly picking up a diverse array of everyday handheld objects given these conditions. this straight-forward, inexpensive, nonprehensile end effector combines a compliant finger with a thin planar component with a leading wedge that slides underneath the object. we empirically validated the efficacy of this design through a set of 1096 trials over which we systematically varied the object location, object type, object configuration, and floor characteristics. our implementation, which we mounted on a irobot create, had a success rate of 94.71% on 680 trials, which used 4 floor types with 34 objects of particular relevance to assistive applications in 5 different poses each (4×34×5=680). the robot also had strong performance with objects that would be difficult to grasp using a traditional end effector, such as a dollar bill, a pill, a cloth, a credit card, a coin, keys, and a watch. prior to this test, we performed 416 trials in order to assess the performance of the end effector with respect to variations in object position.
on the generation of feasible paths for aerial robots with limited climb angle. this paper presents a methodology based on a variation of the quintic pythagorean hodographs curves for generating smooth feasible paths for autonomous vehicles in three-dimensional space under the restriction of limited climb angles. a given path is considered feasible if the main kinematic constraints of the vehicle are not violated. the generated paths satisfy three main angular constraints: (i) maximum curvature, (ii) maximum torsion and (iii) maximum climb (or dive). the smoothness the vehicle acceleration profile is indirectly guaranteed between two consecutive points of the profile. the proposed methodology is applicable to vehicles that move in three-dimensional environments, and that can be modelled under the constraints assumed. we apply our methodology and show the results for a small autonomous aerial vehicle.
t-hive : vibrotactile interface presenting spatial information on handle surface. many recent studies have explored the use of tactile cues, however they were confined to the unilateral display device. although lots of bilateral haptic devices have been developed to provide a guiding force on an input handle, however, a vibrotactile stimuli has not been tried to present directional information on the handle. this research introduces an attempt to combine a tactile display with an input device. a new 6dof bilateral haptic device, which provides a spatial sensation on the handle using vibrotactile display, is proposed in this research. the sphere-shape handle is specially designed to be covered with several pieces of vibrating panels. when a specific panel is activated, the user perceives the spatial location of the vibrotactile stimulus during an input operation. this paper introduces the design of the proposed device, including the selection guide of the dimension, location, and number of vibrotactile panels. the method for combination of vibrotactile stimulus and the way to achieve fine resolution with small number of tactors are discussed. experimental results show that the users can reliably perceive the directional information using the proposed device. an application for teleoperation of a robot proves the effectiveness and the usefulness of the proposed bilateral device.
physiological motion rejection in flexible endoscopy using visual servoing and repetitive control : improvements on non-periodic reference tracking and non-periodic disturbance rejection. flexible endoscopes are used in many surgical procedures and diagnostic exams. they have also been used recently for new surgical procedures using natural orifices called notes. while these procedures are really promising for the patients, they are really awkward for the surgeons. in order to assist the surgeon, physiological motion cancellation has been successfully applied on a robotized endoscope in [8] by using a prototype repetitive controller (prc) and a repetitive generalized predictive controller (r-gpc). both controllers showed to be powerful tools to cancel periodic disturbances but with poor transient response to non-periodic disturbances. contrary to the r-gpc, the prc is unsuitable for handling non-periodic reference changes. we propose in this paper, as a first improvement, a model-based control scheme using the prc which allows to decouple the reference tracking from the periodic output disturbance rejection. the response to nonperiodic disturbance is also improved by this technique but a repetition appears caused by the repetitive controller. as a second improvement, a switching control scheme is proposed to avoid the repetition.
realization of cylinder climbing locomotion with helical form by a snake robot with passive wheels. recently, multiple locomotion gaits of snake have been realized by snake robots. however, previous locomotion gaits are mainly limited on two-dimensional plane. in this study, we make a snake robot that can move in three-dimensional space by connecting several units serially. the each unit is composed by assembling one pitch axis and one yaw axis, and it can have two passive wheels. we realize previously achieved basic locomotion gaits and simple cylinder climbing locomotion. in addition, we also realize cylinder climbing locomotion with helical form by the snake robot using mathematical continuum model.
time-minimal path planning in dynamic current fields. numerous approaches have been proposed for path planning in dynamic current fields, for a fixed departure time. however, in many applications, the departure time is not necessarily known in advance, but can vary in a time window. in this context, the choice of a good departure time is a critical issue. that is why we introduce in this paper a new approach, called symbolic wavefront expansion, determining both the path and the departure time minimizing the travel time of the vehicle. the key idea of this approach is to propagate and compose functions instead of numerical values, with appropriate operators.
active multi-view object search on a humanoid head. visual search is a common daily human activity and a prerequisite to the interaction with objects encountered in cluttered environments. humanoid robots that are supposed to take part in human daily life should possess similar capabilities in terms of representing, attending to and recalling objects of interest in order to ensure robust perception in human-centered environments. in this paper, we present necessary processes, memories and representations which allow to identify and store locations of objects, encountered from different angles of view, in a visual search task. in particular, we introduce the so-called feature ego-sphere (fes) as the scene memory for a humanoid robot. experiments comprising different visual search tasks have been carried out on an active humanoid head equipped with perspective and foveal stereo camera systems. the scene is analyzed actively using both camera systems in order to find instances of searched objects in a consistent and persistent manner.
3d model-based 6-dof head tracking by a single camera for human-robot interaction. in human-robot interaction, it is important for the robot to know the head movement, gaze direction and expression of the conversation partner, since such information are deeply related with the attention, intention and emotion. recently, many types of real-time measurement systems for head pose and gaze direction have been proposed and utilized for human interfaces and ergonomics applications. we have proposed a face measurement system which is non-contact and passive by utilizing a stereo camera pair. however the necessity of the use of stereo camera has several drawbacks. to cope with this problem, this paper proposes a method to measure the 6 dof motions of the head by utilizing a single camera. the use of 3d face model enables us to predict six 2d motion vector fields of facial features which correspond to six unit motions in translation and rotation. an actual 2d motion vector field obtained by tracking facial features is then resolved into a linear combination of the predicted six motion vector fields. the estimated 6 dof motions can be obtained as the six coefficients of the linear combination. through the evaluation of the implemented motion estimation method, it was shown that the accuracy of the proposed estimation method using a single camera was comparable with that of the conventional method using a stereo camera pair. finally developed face tracking system is demonstrated by a humanoid robot interacting with two persons, which takes advantage of the wide field of view of the camera system due to the unnecessity of the stereoscopy.
developing a product quality fault detection scheme. in current semiconductor and tft-lcd factories, periodic sampling is commonly adopted to monitor the stability of manufacturing processes and the quality of products (or workpieces). as for those non-sampled workpieces, their quality is usually monitored by such as a fault-detection-and-classification (fdc) server. however, this method may fail to detect defected products. for example, a workpiece with all the individual manufacturing process parameters being in-spec may still result in out-of-spec product quality. under this circumstance, unless this certain defected workpiece is selected for sampling by chance, it cannot be detected by simply monitoring the manufacturing process parameters collected from the production equipment. to solve the abovementioned problem, this research proposes a product quality fault detection scheme (fds), which utilizes the classification and regression tree to implement a model for identifying the relationship between process parameters and out-of-spec products. through this model, each set of normal manufacturing process parameters can be real-time and on-line examined to detect failure or defected products.
adaptive triangular mesh generation of self-configuring robot swarms. we address the problem of dispersing a large number of autonomous mobile robots toward building wireless ad hoc sensor networks performing environmental monitoring and control. for the purpose, we propose the adaptive triangular mesh generation algorithm that enables robots to generate triangular meshes of various sizes adapting to changing environmental conditions. a locally interacting, geometric technique allows robots to generate each triangular mesh with their two neighbor robots. specifically, we have assumed that robots are not allowed to have the identifier, any pre-determined leaders or common coordinate systems, and any explicit communication. under such minimal conditions, the positions of the robots were shown to converge to the desired distribution, which was mathematically proven and also verified through extensive simulations. our preliminary results indicate that the proposed algorithm can be applied to the problem regarding the coverage of an area of interest by a swarm of mobile sensors.
equitable partitioning policies for robotic networks. the most widely applied resource allocation strategy is to balance, or equalize, the total workload assigned to each resource. in mobile multi-agent systems, this principle directly leads to equitable partitioning policies in which (i) the workspace is divided into subregions of equal measure, (ii) there is a bijective correspondence between agents and subregions, and (iii) each agent is responsible for service requests originating within its own subregion. in this paper, we provide the first distributed algorithm that provably allows m agents to converge to an equitable partition of the workspace, from any initial configuration, i.e., globally. our approach is related to the classic lloyd algorithm, and provides novel insights into the properties of power diagrams. simulation results are presented and discussed.
rational systems and matrix inequalities to the multicriteria analysis of visual servos. this paper outlines a generic method to the analysis of eye-in-hand position-based or image-based visual servos. a side from convergence, the fulfillment of additional important criteria can be assessed, e.g. the target visibility, the avoidance of actuators' saturations, and the guarantee of 3d constraints. the field of nonlinear "rational" systems is first shown to constitute a sound and versatile framework to the problem. the fundamentals of a solution based on lyapunov theory are overviewed next, together with the noteworthy difficulties raised by robotics. constructive results are finally sketched out, in terms of a feasibility/optimization program subject to matrix inequalities. a case study illustrates the approach.
learning sequential visual attention control through dynamic state space discretization. similar to humans and primates, artificial creatures like robots are limited in terms of allocation of their resources to huge sensory and perceptual information. serial processing mechanisms used in the design of such creatures demands engineering attentional control mechanisms. in this paper, we present a new algorithm for learning top-down sequential visual attention control for agents acting in interactive environments. our method is based on the key idea, that attention can be learned best in concert with visual representations through automatic construction and discretization of the visual state space. the tree representing the top-down attention is incrementally refined whenever aliasing occurs by selecting the most appropriate saccadic direction. the proposed approach is evaluated on action-based object recognition and urban navigation tasks, where obtained results support applicability and usefulness of developed saccade movement method for robotics.
regulation control of underactuated mechanical systems based on a new matching equation of port-controlled hamiltonian systems. we consider the control of port-controlled hamiltonian (pch) systems, which are a generalization of euler-lagrange systems. a new matching equation for pch systems is developed so that interconnection damping assignment passivity-based control (ida-pbc) can be extended to the regulation of some underactuated pch systems whose kinetic energy must be modified. a simple underactuated mechanical system (the inertial wheel pendulum) is used to demonstrate the effectiveness of the proposed method.
robobuntu: a linux distribution for mobile robotics. during last years linux started to climb the market of operating systems (oss), and ubuntu, derived by debian os, has become a good alternative to common oss like windows xp or vista. the mobile robotics scientific community makes use of linux based oss to avoid the lack of stability that affects microsoft oss, especially when real time conditions must be satisfied. in this paper we present the linux distribution robobuntu, acronym formed by the union of robot and ubuntu, to overcome the almost totally independent robotic software platforms existing today. the key idea behind robobuntu is the integration of different tools for mobile robotics into an embedded ubuntu distribution. another important characteristics of robobuntu is that every "hard step", like installation and configuration of os and tools, is hidden to common users. in particular, robobuntu can be used either by students or researchers, as livecd, permanent installation on standard hard drive or, more interesting, on a usb storage flash disk.
motion compensation for robotic-assisted surgery with force feedback. the paper presents a control architecture for robotic-assisted surgery in the presence of physiological motions. dynamic and kinematic models, operational space, computed torque, discrete state space and stochastic design are addressed in the control. inner loops are based on position and velocity signals and outer loops have force measurements. two active observers (aobs) are introduced for force control and motion compensation. the first aob is responsible for model-reference adaptive control to guarantee a desired closed loop dynamics for the force. the second aob performs control actions to compensate physiological motions. such motions are described by a second-order stochastic equation, without apriori knowledge of signal characteristics. simulation results are presented for sinusoidal and non-sinusoidal motions, highlighting merits of the approach.
specialization as an optimal strategy under varying external conditions. we present an investigation of specialization when considering the execution of collaborative tasks by a robot swarm. specifically, we consider the stick-pulling problem first proposed by martinoli et al. [1], [2] and develop a macroscopic analytical model for the swarm executing a set of tasks that require the collaboration of two robots. we show, for constant external conditions, maximum productivity can be achieved by a single species swarm with carefully chosen operational parameters. while the same applies for a two species swarm, we show how specialization is a strategy best employed for changing external conditions.
on computing robust n-finger force-closure grasps of 3d objects. the paper deals with computing frictional force-closure grasps of 3d objects problem. the key idea of the presented work is the demonstration that wrenches associated to any three non-aligned contact points of 3d objects form a basis of their corresponding wrench space. this result permits the formulation of a new sufficient force-closure test. our approach works with general objects, modelled with a set of points, and with any number n of contacts (n ≥ 4). a quality criterion is also introduced. a corresponding algorithm for computing robust force-closure grasps has been developed. its efficiency is confirmed by comparing it to the classical convexhull method [26].
appearance-based loop detection from 3d laser data using the normal distributions transform. we propose a new approach to appearance based loop detection from metric 3d maps, exploiting the ndt surface representation. locations are described with feature histograms based on surface orientation and smoothness, and loop closure can be detected by matching feature histograms. we also present a quantitative performance evaluation using two real-world data sets, showing that the proposed method works well in different environments.
combined yaw and roll control of an autonomous boat. in this paper we try to develop a host-based system and study actual sea trials via rudder based roll control method. to authors' best knowledge, the boat we investigated is the smallest among those reported in the literature. an autonomous boat model is obtained by a system identification approach. the identified system is designed with frequency-shaped sliding mode control. the control scheme is composed of a sliding mode observer and a sliding mode controller. the stability and reachability of the switching function are proved by lyapunov theory. computer simulations and experiment show that successful course keeping and roll reduction results are achieved.
extending itasc to support inequality constraints and non-instantaneous task specification. in [1], we presented our constraint-based programming approach, itasc, that formulates instantaneous sensor-based robot tasks as constraint sets, and subsequently solves a corresponding least-squares problem to obtain control set points, such as desired joint velocities or joint torques. this paper further extends this approach, (i) by explicitly supporting the inclusion of inequality constraints in the task and (ii) by supporting a broader class of objective functions for translating the task constraints into robot motion. these extensions are made while retaining a tractable mathematical problem structure (a convex program). furthermore, first results on extending the approach to non-instantaneous tasks are presented. as illustrated in the paper, the power of the approach lies (i) at its versatility to specify a wide range of robot behaviors and the ease of making task adjustments, and (ii) at its generic nature, that permits using systematic procedures to derive the underlying control equations.
actuation and position estimation of a passive mobile end effector from across a thin wall for heavy-duty aircraft manufacturing. a passive mobile robot carrying a heavy manufacturing tool is activated from across a thin wall. the mobile robot placed within a confined space has no tether and no local battery, but is powered from an outside robot through magnetic coupling. a pair of magnetic feet allows the passive inside robot to hang from a ceiling and walk across a wall. a heavy manufacturing tool held in the middle of the passive inside robot is activated with a lorentz force actuator - this is also activated from the outside robot. a set of hall effect sensors on the outside robot detect the magnetic field created by the passive robot in order to estimate the position of the inside robot. first, the task conditions and functional requirements are described, and the design concept of the passive mobile robot is presented. an electro-magnetic model for predicting magnetic field strength and load bearing capacity is used to facilitate design as well as to estimate and control the position of the passive inside robot. a proof-of-concept prototype system is designed and built for application to aircraft manufacturing.
body torque modulation for a microrobotic fly. the harvard microrobotics lab has previously demonstrated the world's first at-scale robotic insect capable of vertical takeoff with external power. both of the robot's wings were driven by a single power actuator and 1-dof mechanical transmission - making independent control of both wings, and therefore asymmetric flapping and the generation of a net body torque, impossible. this paper presents a method to modulate body torques by altering the kinematics of each wing transmission independently, via the introduction of two additional control actuators. theoretical kinematic and dynamic predictions based on a pseudo-rigid body model are compared to the observed wing trajectories. controllable body torques are necessary for the development of control algorithms for eventual stable hovering and free flight.
lsh-ransac: an incremental scheme for scalable localization. this paper addresses the problem of feature-based robot localization in large-size environments. with recent progress in slam techniques, it has become crucial for a robot to estimate the self-position in real-time with respect to a large-size map that can be incrementally build by other mapper robots. self-localization using large-size maps have been studied in litelature, but most of them assume that a complete map is given prior to the self-localization task. in this paper, we present a novel scheme for robot localization as well as map representation that can successfully work with large-size and incremental maps. this work combines our two previous works on incremental methods, ilsh and iransac, for appearance-based and position-based localization.
assigning cameras to subjects in video surveillance systems. we consider the problem of tracking multiple agents moving amongst obstacles, using multiple cameras. given an environment with obstacles, and many people moving through it, we construct a separate narrow field of view video for as many people as possible, by stitching together video segments from multiple cameras over time. we employ a novel approach to assign cameras to people as a function of time, with camera switches when needed. the problem is modeled as a bipartite graph and the solution corresponds to a maximum matching. as people move, the solution is efficiently updated by computing an augmenting path rather than by solving for a new matching. this reduces computation time by an order of magnitude. in addition, solving for the shortest augmenting path minimizes the number of camera switches at each update. when not all people can be covered by the available cameras, we cluster as many people as possible into small groups, then assign cameras to groups using a minimum cost matching algorithm. we test our method using numerous runs from different simulators.
finding good cycle constraints for large scale multi-robot slam. in this paper we describe an algorithm to compute cycle constraints that can be used in many graph-based slam algorithms; we exemplify it in hierarchical slam. our algorithm incrementally computes the minimum cycle basis of constraints from which any other cycle can be derived. cycles in this basis are local and of minimum length, so that the associated cycle constraints have less linearization problems. this also permits to construct regional maps, that is, it makes possible efficient and accurate intermediate mapping levels between local maps and the whole global map. we have extended our algorithm to the multi-robot case. we have tested our methodology using the victoria park data set with satisfactory results.
characterization of the compact hokuyo urg-04lx 2d laser range scanner. this paper presents a detailed characterization of the hokuyo urg-04lx 2d laser range finder. while the sensor specifications only provide a rough estimation of the sensor accuracy, the present work analyzes issues such as time drift effects and dependencies on distance, target properties (color, brightness and material) as well as incidence angle. since the sensor is intended to be used for measurements of a tubelike environment on an inspection robot, the characterization is extended by investigating the influence of the sensor orientation and dependency on lighting conditions. the sensor characteristics are compared to those of the sick lms 200 which is commonly used in robotic applications when size and weight are not critical constraints. the results show that the sensor accuracy is strongly depending on the target properties (color, brightness, material) and that it is consequently difficult to establish a calibration model. the paper also identifies cases for which the sensor returns faulty measurements, mainly when the surface has low reflectivity (dark surfaces, foam) or for high incidence angles on shiny surfaces. on the other hand, the repeatability of the sensor seems to be competitive with the lms 200.
tissue identification using inverse finite element analysis of rolling indentation. the authors have recently proposed the method of rolling indentation over soft tissue to rapidly identify soft tissue properties for localization and detection of tissue abnormalities, with the aim of compensating for the loss of haptics information experienced during robotic-assisted minimally invasive surgery (rmis). this paper investigates the concept of rolling indentation using finite element modeling. to obtain ground truth data, rolling indentation experiments are conducted on a silicone phantom which contains three simulated tumours. the tissue phantom is modeled as hyperelastic material using abaqus™. the identification of tumours includes two parts: firstly, when the spatial location of tumour is known, identify the tumour's mechanical properties (initial shear modulus); secondly if the mechanical properties of tumour are known, identify the tumour's spatial location. the results show that the proposed method can identify information of tumours accurately and robustly. the identified tumour mechanical properties and tumour locations are in good agreement with experimental measurements.
surveying noctural cuttlefish camouflage behaviour using an auv. this paper describes a recent study in which an autonomous underwater vehicle (auv) with a high resolution stereo-imaging system was used to document nocturnal camouflage behaviour in cuttlefish at a well known spawning site in whyalla, south australia. the auv's ability to fly at low altitude during day and night while closely following a desired survey pattern provided improved data collection compared to divers and previous work with a small rov. over the course of the week long expedition, the auv sirius was deployed on 38 dives at three sites in the survey area and collected tens of thousands of stereo images. of these, nearly a thousand were seen to contain cuttlefish during post cruise analysis, with a large proportion showing evidence of camouflage. the distribution of images containing cuttlefish suggest that the animal concentrations were substantially higher closer in to shore in shallow waters, where the flat rocky substrate occurs; females lay their eggs on the underside of these rocks. results demonstrate the strengths of using an auv for surveying near-shore benthic habitats of ecological interest, with a particular emphasis on the ability to operate during both day and night time operations.
stochastic strategies for a swarm robotic assembly system. we present a decentralized, scalable approach to assembling a group of heterogeneous parts into different products using a swarm of robots. while the assembly plans are predetermined, the exact sequence of assembly of parts and the allocation of subassembly tasks to robots are determined by the interactions between robots in a decentralized fashion in real time. our approach is based on developing a continuous abstraction of the system derived from models of chemical reactions and formulating the strategy as a problem of selecting rates of assembly and disassembly. these rates are mapped onto probabilities that determine stochastic control policies for individual robots, which then produce the desired aggregate behavior. this top-down approach to determining robot controllers also allows us to optimize the rates at the abstract level to achieve fast convergence to the specified target numbers of products. because the method incorporates programs for assembly and disassembly, changes in demand can lead to reconfiguration in a seamless fashion. we illustrate the methodology using a physics-based simulator with examples involving 15 robots and two types of final products.
active mechanical compensation to obtain gravity-free robots: modeling, control, design and preliminary experimental results. in this paper, a new hybrid active mechanical technique is proposed, which nullifies the torque coming from gravitational acceleration by means of controlled displacements of the center of mass of each link. modeling, design and control issues are presented as well as some preliminary experimental results illustrate this principle.
development and preliminary data of novel integrated optical micro-force sensing tools for retinal microsurgery. this paper reports the development of novel micro-force sensing tools for retinal microsurgery. retinal microsurgery requires extremely delicate manipulation of retinal tissue, and tool-to-tissue interaction forces are frequently below human perceptual thresholds. further, the interaction between the tool shaft and sclera makes accurate sensing of forces exerted on the retina very difficult with previously developed force sensing schemes, in which the sensor is located outside the eye. in the work reported here, we incorporate 160 µm fiber bragg grating (fbg) strain sensors into the tool shaft to sense forces distal to the sclera. the sensor is applicable both with robotically manipulated and freehand tools. preliminary results with a 1 degree-of-freedom (dof) sensor have demonstrated 0.25 mn resolution, and work is underway to develop 2 and 3 dof tools. the design and analysis of the force sensing tool is presented with preliminary testing data and some initial experiments using the tool with both freehand and robotic manipulation.
bounded attitude control of a flapping wing micro aerial vehicle using direct sensors measurements. this paper presents two bounded attitude control laws of a high frequency flapping micro aerial vehicle (fmav) based on sensors measurements feedback. first, a simplified model of a fmav is proposed using only the steady aerodynamic efforts. since solely the averaged forces and torques affect the body's movement, the control laws are computed using the averaged model and applied to the time varying model at the beginning of each wingbeat period. a first control law is developed using a rate gyro (measuring the body's angular velocity), and some reference sensors used to compute the attitude error. a second control law is proposed omitting the rate gyro in order to reduce fmav's size and weight. the control laws are highly simple and bounded in order to prevent the saturation of the actuators and to increase their efficiency. the control strategies are compared and tested with respect to external disturbances.
the columbia grasp database. collecting grasp data for learning and benchmarking purposes is very expensive. it would be helpful to have a standard database of graspable objects, along with a set of stable grasps for each object, but no such database exists. in this work we show how to automate the construction of a database consisting of several hands, thousands of objects, and hundreds of thousands of grasps. using this database, we demonstrate a novel grasp planning algorithm that exploits geometric similarity between a 3d model and the objects in the database to synthesize form closure grasps. our contributions are this algorithm, and the database itself, which we are releasing to the community as a tool for both grasp planning and benchmarking.
node localization during power adjustment in wireless sensor networks. node localization is a challenging problem in wireless sensor networks, especially in the scenarios of tuning multiple transmit-powers. in this article, we utilized particle filter to infer static node position from the correlations between radio frequency (rf) received signal strength indication (rssi) and distance under multiple power settings. the rssi based stochastic measurement model was analyzed and followed by the particle filter design. the simulation results verified the performance of proposed algorithm for localization. the proposed method is contributive in terms of making advantages of multiple transmit power for localization.
wiping motion for deformable object handling. this paper presents wiping motion as a task during which the movement and deformation of a deformable object occur simultaneously. during the wiping motion of a deformable object, there is contact, but no relative movement, between the manipulator and the object, while there is both contact and relative movement between the object and the floor during the displacement of the object. we first describe wiping motion and distinguish wiping slide from wiping deformation by displacement of the internal points of an object. in addition, we show that a wiping motion is an extended system of pushing and sliding of rigid objects. as an example of wiping motion, we utilize grasping of a fabric, and we demonstrate the grasping motion of a fabric using a single-armed gripper.
laser-based detection and tracking moving objects using data-driven markov chain monte carlo. we present a method of simultaneous detection and tracking moving objects from a moving vehicle equipped with a single layer laser scanner. a model-based approach is introduced to interpret the laser measurement sequence by hypotheses of moving object trajectories over a sliding window of time. knowledge of various aspects including object model, measurement model, motion model are integrated in one theoretically sound bayesian framework. the data-driven markov chain monte carlo (ddmcmc) technique is used to sample the solution space effectively to find the optimal solution. experiments and results on real-life data of urban traffic show promising results.
novel parameter estimation schemes in microsystems. this paper presents two novel estimation methods that are designed to enhance our ability of observing, positioning, and physically transforming the objects and/or biological structures in micromanipulation tasks. in order to effectively monitor and position the microobjects, an online calibration method with submicron precision via a recursive least square solution is presented. to provide the adequate information to manipulate the biological structures without damaging the cell or tissue during an injection, a nonlinear spring-mass-damper model is introduced and mechanical properties of a zebrafish embryo are obtained. these two methods are validated on a microassembly workstation and the results are evaluated quantitatively.
design of a robotic system for mri-guided deep brain stimulation electrode placement. deep brain stimulation (dbs) is a technique for influencing brain function though the use of implanted electrodes. direct magnetic resonance (mr) image guidance during dbs insertion would provide many benefits; most significantly, interventional mri can be used for planning, monitoring of tissue deformation, real-time visualization of insertion, and confirmation of placement. the accuracy of standard stereotactic insertion is limited by registration errors and brain movement during surgery. with real-time acquisition of high-resolution mr images during insertion, probe placement can be confirmed intra-operatively. direct mr guidance has not yet taken hold because it is often confounded by a number of issues including: mr-compatibility of existing stereotactic surgery equipment and patient access in the scanner bore. the high resolution images required for neurosurgical planning and guidance require high-field mr (1.5-3t); thus, any system must be capable of working within the constraints of a closed, long-bore diagnostic magnet. currently, no technological solution exists to assist mri guided neurosurgical interventions in an accurate, simple, and economical manner. we present the design of a robotic assistant system that overcomes these difficulties and promises safe and reliable electrode placement in the brain inside closed high-field mri scanners. the robot performs the insertion under real-time 3t mr image guidance. this paper described analysis of the workspace requirements, mr compatibility evaluation, and mechanism design.
turning dynamics and passive damping in flapping flight. we investigated whether flapping flight has an inherent stability by analyzing the inertial and aerodynamic effects of flapping wings on body dynamics. based on wing and body kinematics of free flying fruit flies during rapid maneuvers, we found a passive counter torque due to body rotation. it is indentified both in simulation through quasi-steady state aerodynamic model and through experiments on a dynamically scaled robotic wing. an analytical form is derived correspondingly. in the turning yaw axis, the estimated damping coefficient of flapping wings is significantly higher than body frictional damping; this indicates a passive deceleration during turning. by simulating insect to rotate about each principal axis of inertial and body frames, we calculated the corresponding damping coefficients, and further analyzed the attitude stability. the result reveals that, passive damping of flapping flight, while does not necessarily lead to a stable full body dynamics, provides a considerable passive restoring torque that could be critical for flight stabilization and control in the design of micro aerial vehicles. preliminary analysis on the scaling parameters of passive damping was also performed.
identification of accelerometer orientation errors and compensation for acceleration estimation errors. inertial measurement units (imu) consist of accelerometers. estimation accuracy of acceleration in a particular direction depends on how accurately accelerometers are placed at desired or ideal orientations. the estimation inaccuracy which results from inaccurate orientation of an accelerometer can be eliminated if the orientation error or the angle between the actual and the ideal orientations is known. this paper presents a method of identification of the accelerometer orientation errors without requiring any rotational motion of the imu in which accelerometers are placed. it also presents a method of compensation for the inaccuracy of acceleration estimation due to the accelerometer orientation errors using angular motion information.
'teleportation'-based motion planner for design error analysis. probabilistic path planning techniques have proven to be vital for finding and validating solutions for difficult industrial assembly tasks. nevertheless, the failure of a path planner to find a solution to a task does not suggest how to correct the error. we suggest a methodology to identify possible bottlenecks and present an algorithm to analyze the extent to which the design must be modified in order for the task to complete successfully. we validate our algorithm on two industrial problems involving design errors, and explain how to interpret the results in order to improve the design.
realtime segmentation of range data using continuous nearest neighbors. in mobile robotics, the segmentation of range data is an important prerequisite to object recognition and environment understanding. this paper presents an algorithm for realtime segmentation of a continuous stream of incoming range data. the method is an extension of the previously developed rbnn algorithm and proceeds in two phases: firstly, the normal vector of each incoming point is estimated from its neighborhood, which is continuously monitored. secondly, new points are clustered according to their euclidean and angular distance to previously clustered points. an outline of the algorithm complexity as well as the parameters that influence the segmentation performance is provided. three benchmark scenarios in which the algorithm is deployed on a mobile robot with a laser range finder confirm that the method can robustly segment incoming data at high rates.
analysis and improvement of image-based insertion point estimation for robot-assisted minimally invasive surgery. estimating insertion points of surgical instruments for minimally invasive surgery is a necessary step to be able to control surgical instruments using endoscopic images. in this paper, we propose an analysis of possible methods which use image information only. mathematical properties are detailed together with statistical properties obtained by simulations. then a specific method is chosen to estimate the insertion point for bi-modal surgery (laparoscopy and flexible endoscopy). in vitro experiments show the accuracy of the approach and how it is possible to track the motion of the insertion point in the case of physiological motions.
learning to stabilize the head of a quadrupedal robot with an artificial vestibular system. during quadrupedal robot locomotion, there is pitch, yaw, and roll of the head and body due to the stepping. the head motion adversely affects visual sensors embedded in the robot's head. mammals stabilize the head using a vestibulocollic reflex that detects linear and rotational acceleration. in this paper we describe the use of a machine learning algorithm that utilizes signals from an artificial vestibular system that has been embedded in the robot's head. our approach can rapidly learn to compensate for the head movements that appear when no stabilization mechanism is present. the stabilization using a sony aibo robot occurs in only a few gait cycles.
design principles of large quadrotors for practical applications. virtually all quadrotors used in research weigh less than 2 kg, and carry payload measured in hundreds of grams. to be useful platforms for expanded operations, these vehicles must be capable of carrying greater weight. several obstacles in aerodynamics, design and control must be overcome to enable the construction of larger craft with payloads in excess of 1 kg. we report the key design considerations essential for the construction of heavy quadrotor mavs and demonstrate a 4 kg quadrotor with 1 kg payload.
cooperative multi-robot localization under communication constraints. this paper addresses the problem of cooperative localization (cl) under severe communication constraints. specifically, we present minimum mean square error (mmse) and maximum a posteriori (map) estimators that can process measurements quantized with as little as one bit per measurement. during cl, each robot quantizes and broadcasts its measurements and receives the quantized observations of its teammates. the quantization process is based on the appropriate selection of thresholds, computed using the current state estimates, that minimize the estimation error metric considered. extensive simulations demonstrate that the proposed iteratively-quantized extended kalman filter (iqekf) and the iteratively quantized map (iqmap) estimator achieve performance indistinguishable of that of their real-valued counterparts (ekf and map, respectively) when using as few as 4 bits for quantizing each robot measurement.
learning to recognize familiar faces in the real world. we present an incremental and unsupervised face recognition system and evaluate it offline using data which were automatically collected by mertz, a robotic platform embedded in real human environment. in an eight-day-long experiment, the robot autonomously detects, tracks, and segments face images during spontaneous interactions with over 500 passersby in public spaces and automatically generates a data set of over 100,000 face images. we describe and evaluate a novel face clustering algorithm using these data (without any manual processing) and also on an existing face recognition database. the face clustering algorithm yields good and robust performance despite the extremely noisy data segmented from the realistic and difficult public environment. in an incremental recognition scheme evaluation, the system is correct 74% of the time when it declares "i don't know this person" and 75.1% of the time when it declares" i know this person, he/she is ..." the latter accuracy improves to 83.8% if the system is allowed some learning curve delay in the beginning.
local decomposition and observability properties for automatic calibration in mobile robotics. this paper considers the problem of sensor self-calibration in mobile robotics by only using a single point feature (e.g. a source of light). in particular, the problem of determining the extrinsic parameters of a bearing sensor mounted on a mobile platform (e.g. a camera) and simultaneously estimating the parameters describing the systematic error in the odometry system is discussed. special attention is devoted to investigate the dependence of the observability properties of these parameters on the chosen robot trajectory. the main contribution provided by this paper is the introduction of a new method to deal with estimation problems in the framework of mobile robotics. specifically, a calibration problem has been considered. however, the same method can be adopted to solve other fundamental estimation problems. the method is based on the theory of distributions which exploits all the system lie symmetries. regarding the considered calibration problem this method allows analytically detecting the combinations of the calibration parameters which are observable for a given robot trajectory. experiments are provided to validate the results.
execution anomaly detection in distributed systems through unstructured log analysis. detection of execution anomalies is very important for the maintenance, development, and performance refinement of large scale distributed systems. execution anomalies include both work flow errors and low performance problems. people often use system logs produced by distributed systems for troubleshooting and problem diagnosis. however, manually inspecting system logs to detect anomalies is unfeasible due to the increasing scale and complexity of distributed systems. therefore, there is a great demand for automatic anomalies detection techniques based on log analysis. in this paper, we propose an unstructured log analysis technique for anomalies detection. in the technique, we propose a novel algorithm to convert free form text messages in log files to log keys without heavily relying on application specific knowledge. the log keys correspond to the log-print statements in the source code which can provide cues of system execution behavior. after converting log messages to log keys, we learn a finite state automaton (fsa) from training log sequences to present the normal work flow for each system component. at the same time, a performance measurement model is learned to characterize the normal execution performance based on the log mes-sages’ timing information. with these learned models, we can automatically detect anomalies in newly input log files. experiments on hadoop and silk show that the technique can effectively detect running anomalies.
combining super-structuring and abstraction on sequence classification. we present an approach to adapting the data representation used by a learner on sequence classification tasks. our approach that exploits the complementary strengths of super-structuring (constructing complex features by combining existing features) and abstraction (grouping of similar features to generate more abstract features), yields smaller and, at the same time, accurate models. super-structuring provides a way to increase the predictive accuracy of the learned models by enriching the data representation (and hence, increases the complexity of the learned models) whereas abstraction helps reduce the number of model parameters by simplifying the data representation. the results of our experiments on two data sets drawn from macromolecular sequence classification applications show that adapting data representation by combining super-structuring and abstraction, makes it possible to construct predictive models that use significantly smaller number of features (by one to three orders of magnitude) than those that are obtained using super-structuring alone, without sacrificing predictive accuracy. our experiments also show that simplifying data representation using abstraction yields better performing models than those obtained using feature selection.
discovering organizational structure in dynamic social network. applying the concept of organizational structure to social network analysis may well represent the power of members and the scope of their power in a social network. in this paper, we propose a data structure, called community tree, to represent the organizational structure in the social network. we combine the pagerank algorithm and random walks on graph to derive the community tree from the social network. in the real world, a social network is constantly changing. hence, the organizational structure in the social network is also constantly changing. in order to present the organizational structure in a dynamic social network, we propose a tree learning algorithm to derive an evolving community tree. the evolving community tree enables a smooth transition between the two community trees and well represents the evolution of organizational structure in the dynamic social network. experiments conducted on real data show our methods are effective at discovering the organizational structure and representing the evolution of organizational structure in a dynamic social network.
topic modeling for sequences of temporal activities. temporally-ordered activity sequences are popular in many real-world domains. this paper presents an lda-style topic model for sequences of temporal activities that captures three features of such sequences: 1) the counts of unique activities, 2) the markov transition dependence and 3) the absolute or relative timestamp on each activity. in modeling the first two features we propose the concept of global transition probability and distinguish it with local transition probability used in previous work. in modeling the third feature, we employ a continuous time distribution to depict the time range of latent topics. the combination of the global transition probability and the temporal information helps to refine the mixture distribution over topics for temporal sequence analysis. we present results on the data of system call traces, showing better next activity prediction and sequence clustering.
vague one-class learning for data streams. in this paper, we formulate a new research problem of learning from vaguely labeled one-class data streams, where the main objective is to allow users to label instance groups, instead of single instances, as positive samples for learning. the batch-labeling, however, raises serious issues because labeled groups may contain non-positive samples, and users may change their labeling interests at any time. to solve this problem, we propose a vague one-class learning (vocl) framework which employs a double weighting approach, at both instance and classifier levels, to build an ensembling framework for learning. at instance level, both local and global filterings are considered for instance weight adjustment. two solutions are proposed to take instance weight values into the classifier training process. at classifier level, a weight value is assigned to each classifier of the ensemble to ensure that learning can quickly adapt to users’ interests. experimental results on synthetic and real-world data streams demonstrate that the proposed vocl framework significantly outperforms other methods for vaguely labeled one-class data streams.
vif regression: a fast regression algorithm for large data. we propose a fast regression algorithm that can substantially reduce the computational complexity of searching, yet retain good accuracy. it also guarantees to discover correlated features that are collectively predictive, and avoid model over-fitting. its capability of controlling mfdr (marginal false discovery rate) statistically enables the one-pass search of the fast algorithm and guarantees the accuracy of the sparse model chosen by the algorithm without cross validation. numerical results show that our algorithm is much faster than any other algorithm and is competitively as accurate as the best but slower algorithms.
accelerated gradient method for multi-task sparse learning problem. many real world learning problems can be recast as multi-task learning problems which utilize correlations among different tasks to obtain better generalization performance than learning each task individually. the feature selection problem in multi-task setting has many applications in fields of computer vision, text classification and bio-informatics. generally, it can be realized by solving a l-1-infinity regularized optimization problem. and the solution automatically yields the joint sparsity among different tasks. however, due to the nonsmooth nature of the l-1-infinity norm, there lacks an efficient training algorithm for solving such problem with general convex loss functions. in this paper, we propose an accelerated gradient method based on an ``optimal'' first order black-box method named after nesterov and provide the convergence rate for smooth convex loss functions. for nonsmooth convex loss functions, such as hinge loss, our method still has fast convergence rate empirically. moreover, by exploiting the structure of the l-1-infinity ball, we solve the black-box oracle in nesterov's method by a simple sorting scheme. our method is suitable for large-scale multi-task learning problem since it only utilizes the first order information and is very easy to implement. experimental results show that our method significantly outperforms the most state-of-the-art methods in both convergence speed and learning accuracy.
p-packsvm: parallel primal gradient descent kernel svm. it is an extreme challenge to produce a nonlinear svm classifier on very large scale data. in this paper we describe a novel p-packsvm algorithm that can solve the support vector machine (svm) optimization problem with an arbitrary kernel. this algorithm embraces the best known stochastic gradient descent method to optimize the primal objective, and has 1/ϵ dependency in complexity to obtain a solution of optimization error ϵ. the algorithm can be highly parallelized with a special packing strategy, and experiences sub-linear speed-up with hundreds of processors. we demonstrate that p-packsvm achieves accuracy sufficiently close to that of svm-light, and overwhelms the state-of-the-art parallel svm trainer psvm in both accuracy and efficiency. as an illustration, our algorithm trains ccat dataset with 800k samples in 13 minutes and 95% accuracy, while psvm needs 5 hours but only has 92% accuracy. we at last demonstrate the capability of p-packsvm on 8 million training samples.
modeling syntactic structures of topics with a nested hmm-lda. latent dirichlet allocation (lda) is a commonly used topic modeling method for text analysis and mining. standard lda treats documents as bags of words, ignoring the syntactic structures of sentences. in this paper, we propose a hybrid model that embeds hidden markov models (hmms) within lda topics to jointly model both the topics and the syntactic structures within each topic. our model is general and subsumes standard lda and hmm as special cases. compared with standard lda and hmm, our model can simultaneously discover both topic-specific content words and background functional words shared among topics. our model can also automatically separate content words that play different roles within a topic. using perplexity as evaluation metric, our model returns lower perplexity for unseen test documents compared with standard lda, which shows its better generalization power than lda. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
analysis of subsequence time-series clustering based on moving average. subsequence time-series clustering (stsc), which consists of subsequence cutout with a sliding window and k-means clustering, had been commonly used in time-series data mining. however, a problem was pointed out that stsc always generates moderate sinusoidal patterns independently of the input. to address this problem, we theoretically explain and empirically confirm the similarity between stsc and moving average. the present analysis is consistent with, and simpler than, one of the most important analyses of stsc. we also question the pattern extraction in the time domain and discuss another solution.
finding maximal fully-correlated itemsets in large databases. finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. much previous research focuses on finding correlated pairs instead of correlated itemsets in which all items are correlated with each other. when designing gift sets, store shelf arrangements, or website product categories, we are more interested in correlated itemsets than correlated pairs. we solve this problem by finding maximal fully-correlated itemsets (mfcis), in which all subsets are closely related to all other subsets. putting the items in an mfci together can promote sales within this itemset. though some exsiting methods find high-correlation itemsets, they suffer from both efficiency and effectiveness problems in large datasets. in this paper, we explore high-dimensional correlation in two ways. first, we expand the set of desirable properties for correlation measures and study the advantages and disadvantages of various measures. second, we propose an mfci framework to decouple the correlation measure from the need for efficient search. by wrapping the best measure in our mfci framework, we take advantage of likelihood ratio’s superiority in evaluating itemsets, make use of the properties of mfci to eliminate itemsets with irrelevant items, and still achieve good computational performance.
to trust or not to trust? predicting online trusts using trust antecedent framework. this paper analyzes the trustor and trustee factors that lead to inter-personal trust using a well studied trust antecedent framework in management science \cite{mayer}. to apply these factors to trust ranking problem in online rating systems, we derive features that correspond to each factor and develop different trust ranking models. the advantage of this approach is that features relevant to trust can be systematically derived so as to achieve good prediction accuracy. through a series of experiments on real data from epinions, we show that even a simple model using the derived features yields good accuracy and outperforms moletrust, a trust propagation based model. svm classifiers using these features also show improvements.
active learning with adaptive heterogeneous ensembles. one common approach to active learning is to iteratively train a single classifier by choosing data points based on its uncertainty, but it is nontrivial to design uncertainty measures unbiased by the choice of classifier. query by committee suggests that given an ensemble of diverse but accurate classifiers, the most informative data points are those that cause maximal disagreement among the predictions of the ensemble members. however the method for finding ensembles appropriate to a given data set remains an open question. in this paper, the random subspace method is combined with active learning to create multiple instances of different classifier types, and an algorithm is introduced that adapts the ratio of different classifier types in the ensemble towards better overall accuracy. here we show that the proposed algorithm outperforms c4.5 with uncertainty sampling, naive bayes with uncertainty sampling, bagging, boosting and the random subspace method with random sampling. to the best of our knowledge, our work is the first to adapt the ratio of classifiers in a heterogeneous ensemble for active learning.
cocost: a computational cost efficient classifier. computational cost of classification is as important as accuracy in on-line classification systems. the computational cost is usually dominated by the cost of computing implicit features of the raw input data. very few efforts have been made to design classifiers which perform effectively with limited computational power; instead, feature selection is usually employed as a pre-processing step to reduce the cost of running traditional classifiers. we present cocost, a novel and effective approach for building classifiers which achieve state-of-the-art classification accuracy, while keeping the expected computational cost of classification low, even without feature selection. cocost employs a wide range of novel cost-aware decision trees, each of which is tuned to specialize in classifying instances from a subset of the input space, and judiciously consults them depending on the input instance in accordance with a cost-aware meta-classifier. experimental results on a network flow detection application show that, our approach can achieve better accuracy than classifiers such as svm and random forests, while achieving 75%-90% reduction in the computational costs.
promoting total efficiency in text clustering via iterative and interactive metric learning. in this paper, we propose a framework to make the text clustering process, as a whole, efficient. in a real text clustering task, an analyst usually has some expectation on the results in mind. however, a single run of a clustering algorithm on the preprocessed data would not satisfy the expectation. then the analyst faces labor-intensive trials for improving the results that involve repetitive feature refinement and parameter tuning. we develop the iterative and interactive metric learning system (iimls) for addressing the challenge. specifically, iimls allows analysts to input feedback on a current clustering result. given the feedback, iimls optimizes metric in the feature space so that the clustering algorithm applied with the refined metric would reflect the feedback. as a byproduct, learned metric may be used for a similar dataset. illustrative examples on a real-world dataset show iimls can dramatically improve efficiency of a text clustering task. the learned “knowledge”, or the metric, is visualized for gaining insights of the optimized feature metric.
aspect guided text categorization with unobserved labels. this paper proposes a novel multiclass classification method and exhibits its advantage in the domain of text categorization with a large label space and, most importantly, when some of the labels were not observed in the training data. the key insight is the introduction of intermediate aspect variables that encode properties of the labels. aspect variables serve as a joint representation for observed and unobserved labels. this way the classification problem can be viewed as a structure learning problem with natural constraints on assignments to the aspect variables. we solve the problem as a constrained optimization problem over multiple learners and show significant improvement in classifying short sentences into a large label space of categories, including previously unobserved categories.
clustering trajectories of moving objects in an uncertain world. mining trajectory databases (td) has recently gained great interest due to the popularity of tracking devices. on the other hand, the inherent presence of uncertainty in td (e.g., due to gps errors) has not been taken yet into account during the mining process. in this paper, we study the effect of uncertainty in td clustering and introduce a three-step approach to deal with it. first, we propose an intuitionistic point vector representation of trajectories that encompasses the underlying uncertainty and introduce an effective distance metric to cope with uncertainty. second, we devise centra, a novel algorithm which tackles the problem of discovering the centroid trajectory of a group of movements. third, we propose a variant of the fuzzy c-means (fcm) clustering algorithm, which embodies centra at its update procedure. the experimental evaluation over real world td demonstrates the efficiency and effectiveness of our approach.
audio classification of bird species: a statistical manifold approach. our goal is to automatically identify which species of bird is present in an audio recording using supervised learning. devising effective algorithms for bird species classification is a preliminary step toward extracting useful ecological data from recordings collected in the field. we propose a probabilistic model for audio features within a short interval of time, then derive its bayes risk-minimizing classifier, and show that it is closely approximated by a nearest-neighbor classifier using kullback-leibler divergence to compare histograms of features. we note that feature histograms can be viewed as points on a statistical manifold, and kl divergence approximates geodesic distances defined by the fisher information metric on such manifolds. motivated by this fact, we propose the use of another approximation to the fisher information metric, namely the hellinger metric. the proposed classifiers achieve over 90% accuracy on a data set containing six species of bird, and outperform support vector machines.
multirelational topic models. in this paper we propose the multirelational topic model (mrtm) for multiple types of link modeling such as citation and coauthor links in document networks. in the citation network, the mrtm models the citation link between each pair of documents as a binary variable conditioned on their topic distributions. in the coauthor network, the mrtm models the coauthor link between each pair of authors as a binary variable conditioned on their expertise distributions. the topic discovery is collectively regularized by multiple relations in both citation and coauthor networks. this model can summarize topics from the document network, predict citation links between documents and coauthor links between authors. efficient inference and learning algorithms are derived based on gibbs sampling. experiments demonstrate that the mrtm significantly outperforms other state-of-the-art single-relational link modeling methods for large scientific document networks.
a sparsification approach for temporal graphical model decomposition. temporal causal modeling can be used to recover the causal structure among a group of relevant time series variables. several methods have been developed to explicitly construct temporal causal graphical models. however, how to best understand and conceptualize these complicated causal relationships is still an open problem. in this paper, we propose a decomposition approach to simplify the temporal graphical model. our method clusters time series variables into groups such that strong interactions appear among the variables within each group and weak (or no) interactions exist for cross-group variable pairs. specifically, we formulate the clustering problem for temporal graphical models as a regression-coefficient sparsification problem and define an interesting objective function which balances the model prediction power and its cluster structure. we introduce an iterative optimization approach utilizing the quasi-newton method and generalized ridge regression to minimize the objective function and to produce a clustered temporal graphical model. we also present a novel optimization procedure utilizing a graph theoretical tool based on the maximum weight independent set problem to speed up the quasi-newton method for a large number of variables. finally, our detailed experimental study on both synthetic and real datasets demonstrates the effectiveness of our methods.
uncoverning groups via heterogeneous interaction analysis. with the pervasive availability of web 2.0 and social networking sites, people can interact with each other easily through various social media. for instance, popular sites like del.icio.us, flickr, and youtube allow users to comment shared content (bookmark, photos, videos), and users can tag their own favorite content. users can also connect to each other, and subscribe to or become a fan or a follower of others. these diverse individual activities result in a multi-dimensional network among actors, forming cross-dimension group structures with group members sharing certain similarities. it is challenging to effectively integrate the network information of multiple dimensions in order to discover cross-dimension group structures. in this work, we propose a two-phase strategy to identify the hidden structures shared across dimensions in multi-dimensional networks. we extract structural features from each dimension of the network via modularity analysis, and then integrate them all to find out a robust community structure among actors. experiments on synthetic and real-world data validate the superiority of our strategy, enabling the analysis of collective behavior underneath diverse individual activities in a large scale.
peculiarity analysis for classifications. peculiarity-oriented mining (pom) is a new data mining method consisting of peculiar data identification and peculiar data analysis. peculiarity factor (pf) and local peculiarity factor (lpf) are important concepts employed to describe the peculiarity of points in the identification step. one can study the notions at both attribute and record levels. in this paper, a new record lpf called distance based record lpf (d-record lpf) is proposed, which is defined as the sum of distances between a point and its nearest neighbors. it is proved mathematically that d-record lpf can characterize accurately the probability density function of a continuous m-dimensional distribution. this provides a theoretical basis for some existing distance based anomaly detection techniques. more important, it also provides an effective method for describing the class conditional probabilities in the bayesian classifier. the result enables us to apply peculiarity analysis for classification problems. a novel algorithm called lpf-bayes classifier and its kernelized implementation are presented, which have some connection to the bayesian classifier. experimental results on several benchmark data sets demonstrate that the proposed classifiers are effective.
extending semi-supervised learning methods for inductive transfer learning. inductive transfer learning and semi-supervised learning are two different branches of machine learning. the former tries to reuse knowledge in labeled out-of-domain instances while the later attempts to exploit the usefulness of unlabeled in-domain instances. in this paper, we bridge the two branches by pointing out that many semi-supervised learning methods can be extended for inductive transfer learning, if the step of labeling an unlabeled instance is replaced by re-weighting a diff-distribution instance. based on this recognition, we develop a new transfer learning method, namely coitl, by extending the co-training method in semi-supervised learning. experimental results reveal that coitl can achieve significantly higher generalization and robustness, compared with two state-of-the-art methods in inductive transfer learning.
a new kernel-based classification algorithm. a new kernel-based learning algorithm called kernel affine subspace nearest point (kasnp) approach is proposed in this paper. inspired by the geometrical explanation of support vector machines (svms) and its nearest point problem in convex hulls, we extend the convex hull of each class to its corresponding affine subspace in high dimensional space induced by kernel. in two class affine subspaces, kasnp finds the nearest points and then constructs a separating hyperplane, which bisects the line segment joining them. the nearest point problem of kasnp is only an unconstrained optimal problem whose solution can be directly computed. compared with svm, kasnp avoids solving convex quadratic programming. experiments on two-spiral dataset, two uci credit datasets, and face recognition datasets show that our proposed kasnp is effective for data classification.
argumentation based constraint acquisition. efficient acquisition of constraint networks is a key factor for the applicability of constraint problem solving methods. current techniques learn constraint networks from sets of training examples, where each example is classified as either a solution or non-solution of a target network. however, in addition to this classification, an expert can usually provide arguments as to why examples should be rejected or accepted. generally speaking domain specialists have partial knowledge about the theory to be acquired which can be exploited for knowledge acquisition. based on this observation, we discuss the various types of arguments an expert can formulate and develop a knowledge acquisition algorithm for processing these types of arguments which gives the expert the possibility to input arguments in addition to the learning examples. the result of this approach is a significant reduction in the number of examples which must be provided to the learner in order to learn the target constraint network.
fine-grain perturbation for privacy preserving data publishing. recent work [12] shows that conventional privacy preserving publishing techniques based on anonymity-groups are susceptible to corruption attacks. in a corruption attack, if the sensitive information of any anonymity-group member is uncovered, then the remaining group members are at risk. in this study, we abandon anonymity-groups and hide sensitive information through perturbation on the sensitive attribute. with each record being perturbed independently, corruption attacks cannot be effectively carried out. previous anti-corruption work did not minimize information loss. this paper proposes to address this issue by allowing fine-grain privacy specification. we demonstrate the power of our approach through experiments on real medical and synthetic datasets.
outlier detection using inductive logic programming. we present a novel definition of outlier in the context of inductive logic programming. given a set of positive and negative examples, the definition aims at singling out the examples showing anomalous behavior. we note that the task here pursued is different from noise removal, and, in fact, the anomalous observations we discover are different in nature from noisy ones. we discuss pecularities of the novel approach, present an algorithm for detecting outliers, discuss some examples of knowledge mined, and compare it with alternative approaches.
improving svm classification on imbalanced data sets in distance spaces. imbalanced data sets present a particular challenge to the data mining community. often, it is the rare event that is of interest and the cost of misclassifying the rare event is higher than misclassifying the usual event. when the data is highly skewed toward the usual, it can be very difficult for a learning system to accurately detect the rare event. there have been many approaches in recent years for handling imbalanced data sets, from under-sampling the majority class to adding synthetic points to the minority class in feature space. distances between time series are known to be non-euclidean and nonmetric, since comparing time series requires warping in time. this fact makes it impossible to apply standard methods like smote to insert synthetic data points in feature spaces. we present an innovative approach that augments the minority class by adding synthetic points in distance spaces. we then use support vector machines for classification. our experimental results on standard time series show that our synthetic points significantly improve the classification rate of the rare events, and in many cases also improves the overall accuracy of svm.
maximum margin clustering with multivariate loss function. this paper presents a simple but powerful extension of the maximum margin clustering (mmc) algorithm that optimizes multivariate performance measure specifically defined for clustering, including normalized mutual in- formation, rand index and f-measure. different from previous mmc algorithms that always employ the error rate as the loss function, our formulation involves a multivariate loss function that is a non-linear combination of the individual clustering results. computationally, we propose a cutting plane algorithm to approximately solve the resulting optimization problem with a guaranteed accuracy. experimental evaluations show clear improvements in clustering performance of our method over previous maximum margin clustering algorithms.
hierarchical bayesian models for collaborative tagging systems. collaborative tagging systems with user generated content have become a fundamental element of websites such as delicious, flickr or citeulike. by sharing common knowledge, massively linked semantic data sets are generated that provide new challenges for data mining. in this paper, we reduce the data complexity in these systems by finding meaningful topics that serve to group similar users and serve to recommend tags or resources to users. we propose a well-founded probabilistic approach that can model every aspect of a collaborative tagging system. by integrating both user information and tag information into the well-known latent dirichlet allocation framework, the developed models can be used to solve a number of important information extraction and retrieval tasks.
cross-guided clustering: transfer of relevant supervision across domains for improved clustering. lack of supervision in clustering algorithms often leads to clusters that are not useful or interesting to human reviewers. we investigate if supervision can be automatically transferred to a clustering task in a target domain, by providing a relevant supervised partitioning of a dataset from a different source domain. the target clustering is made more meaningful for the human user by trading off intrinsic clustering goodness on the target dataset for alignment with relevant supervised partitions in the source dataset, wherever possible. we propose a cross-guided clustering algorithm that builds on traditional k-means by aligning the target clusters with source partitions. the alignment process makes use of a cross-domain similarity measure that discovers hidden relationships across domains with potentially different vocabularies. using multiple real-world datasets, we show that our approach improves clustering accuracy significantly over traditional k-means.
mining peculiarity groups in day-by-day behavioral datasets. behavior mining is one of the most important issues in data mining. the growing interest in the study of behavior mining has been credited to the availability of a large amount of individual behavioral data. some objects containing common behavioral patterns in the dataset are dramatically different from other individual objects and show their peculiarities. it is very important for behavior analysis to mine these peculiar objects' groups as this has great potential in practice. however, to the best of our knowledge, it has not been explored before. in this paper, we identify this interesting and practical problem of behavior mining: mining peculiarity groups and defining a measurement of the degree of peculiarity. as the first attempt to tackle the problem, we present a set-value-oriented day-by-day behavioral data expression mode considering that daily behaviors with respect to an object should be recorded as a set of behaviors, and devise a peculiarity group mining algorithm in view of the set-value-oriented data expression which cannot be very well handled by existing methods. furthermore, we show that our method is practical and efficient using real datasets.
beyond banditron: a conservative and efficient reduction for online multiclass prediction with bandit setting model. in this paper, we consider a recently proposed supervised learning problem, called online multiclass prediction with bandit setting model. aiming at learning from partial feedback of online classification results, i.e. “true” when the predicting label is right or “false” when the predicting label is wrong, this new kind of problems arouses much of researchers’ interest due to its close relations to real world internet applications and human cognitive procedure. while some algorithms have been brought forward, we propose a novel algorithm to deal with such problems. first, we reduce the multiclass prediction problem to binary based on conservative one-versus-all others reduction scheme; then online passive-aggressive algorithm is embedded as binary learning algorithm to solve the reduced problem. also we derive a pleasing cumulative mistake bound for our algorithm and a time complexity bound linear to the sample size. further experimental evaluation on several real world multiclass datasets including rcv1, mnist, 20 newsgroups and usps shows that our method outperforms the existing algorithms with a great improvement.
multi-document summarization by information distance. fast changing knowledge on the internet can be acquired more efficiently with the help of automatic document summarization and updating techniques. this paper described a novel approach for multi-document update summarization. the best summary is defined to be the one which has the minimum information distance to the entire document set. the best update summary has the minimum conditional information distance to a document cluster given that a prior document cluster has already been read. experiments on the duc 2007 dataset and the tac 2008 dataset have proved that our method closely correlates with the human summaries and outperforms other programs such as lexrank in many categories under the rouge evaluation criterion.
knowledge discovery from citation networks. knowledge discovery from scientific articles has received increasing attentions recently since huge repositories are made available by the development of the internet and digital databases. in a corpus of scientific articles such as a digital library, documents are connected by citations and one document plays two different roles in the corpus: \emph{document itself} and \emph{a citation of other documents}. in the existing topic models, little effort is made to differentiate these two roles. we believe that the topic distributions of these two roles are different and related in a certain way. in this paper we propose a \emph{bernoulli process topic}~(bpt) model which models the corpus at two levels: \emph{document level} and \emph{citation level}. in the bpt model, each document has two different representations in the latent topic space associated with its roles. moreover, the multi-level hierarchical structure of the citation network is captured by a generative process involving a bernoulli process. the distribution parameters of the bpt model are estimated by a variational approximation approach. in addition to conducting the experimental evaluations on the document modeling task, we also apply the bpt model to a well known scientific corpus to discover the latent topics. the comparisons against state-of-the-art methods demonstrate a very promising performance.
scalable classification in large scale spatiotemporal domains applied to voltage-sensitive dye imaging. we present an approach for learning models that obtain accurate classification of large scale data objects, collected in spatiotemporal domains. the model generation is structured in three phases: pixel selection (spatial dimension reduction), spatiotemporal features extraction and feature selection. novel techniques for the first two phases are presented, with two alternatives for the middle phase. model generation based on the combinations of techniques from each phase is explored. the introduced methodology is applied on datasets from the voltage-sensitive dye imaging (vsdi) domain, where the generated classification models successfully decode neuronal population responses in the visual cortex of behaving animals. vsdi currently is the best technique enabling simultaneous high spatial (10,000 points) and temporal (10 ms or less) resolution imaging from neuronal population in the cortex. we demonstrate that not only our approach is scalable enough to handle computationally challenging data, but it also contributes to the neuroimaging field of study with its decoding abilities.
significance of episodes based on minimal windows. discovering episodes, frequent sets of events from a sequence has been an active field in pattern mining. traditionally, a level-wise approach is used to discover all frequent episodes. while this technique is computationally feasible it may result in a vast number of patterns, especially when low thresholds are used. in this paper we propose a new quality measure for episodes. we say that an episode is significant if the average length of its minimal windows deviates greatly when compared to the expected length according to the independence model. we can apply this measure as a post-pruning step to test whether the discovered frequent episodes are truly interesting and consequently to reduce the number of output. as a main contribution we introduce a technique that allows us to compute the distribution of lengths of minimal windows using the independence model. such a computation task is surpisingly complex and in order to solve it we compute the distribution iteratively starting from simple episodes and progressively moving towards the more complex ones. in our experiments we discover candidate episodes that have a sufficient amount of minimal windows and test each candidate for significance. the experimental results demonstrate that our approach finds significant episodes while ignoring uninteresting ones.
naive bayes classification of uncertain data. traditional machine learning algorithms assume that data are exact or precise. however, this assumption may not hold in some situations because of data uncertainty arising from measurement errors, data staleness, and repeated measurements, etc. with uncertainty, the value of each data item is represented by a probability distribution function (pdf). in this paper, we propose a novel naive bayes classification algorithm for uncertain data with a pdf. our key solution is to extend the class conditional probability estimation in the bayes model to handle pdf’s. extensive experiments on uci datasets show that the accuracy of naive bayes model can be improved by taking into account the uncertainty information.
dirichlet mixture allocation for multiclass document collections modeling. topic model, latent dirichlet allocation (lda), is an effective tool for statistical analysis of large collections of documents. in lda, each document is modeled as a mixture of topics and the topic proportions are generated from the unimodal dirichlet distribution prior. when a collection of documents are drawn from multiple classes, this unimodal prior is insufficient for data fitting. to solve this problem, we exploit the multimodal dirichlet mixture prior, and propose the dirichlet mixture allocation (dma). we report experiments on the popular tdt2 corpus demonstrating that dma models a collection of documents more precisely than lda when the documents are obtained from multiple classes.
semi-markov kmeans clustering and activity recognition from body-worn sensors. subsequence clustering aims to find patterns that appear repeatedly in time series data. we introduce a novel subsequence clustering technique that we call semi-markov kmeans clustering. the clustering results in ideal examples of the repeating patterns and in labeled segmentations that can be used as training data for sophisticated discriminative methods like max-margin semi-markov models. we are applying the new clustering technique to activity recognition from body-worn sensors by showing how it can enable a system to learn from data that is only annotated by an ordered list of activity types that have been undertaken. this kind of annotation, unlike a detailed segmentation of the sensor data, is easily provided by a non-expert user. we show that we can achieve equally good results using only an ordered list of activity types for training as when using a full detailed labeled segmentation.
discovering excitatory networks from discrete event streams with applications to neuronal spike train analysis. mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-computer interaction modeling. we focus in this paper on temporal models representable as excitatory networks where all connections are stimulative, rather than inhibitory. through this emphasis on excitatory networks, we show how they can be learned by creating bridges to frequent episode mining. specifically, we show that frequent episodes help identify nodes with high mutual information relationships and which can be summarized into a dynamic bayesian network (dbn). to demonstrate the practical feasibility of our approach, we show how excitatory networks can be inferred from both mathematical models of spiking neurons as well as real neuroscience datasets.
a bootstrap approach to eigenvalue correction. eigenvalue analysis is an important aspect in many data modeling methods. unfortunately, the eigenvalues of the sample covariance matrix (sample eigenvalues) are biased estimates of the eigenvalues of the covariance matrix of the data generating process (population eigenvalues). we present a new method based on bootstrapping to reduce the bias in the sample eigenvalues: the eigenvalue estimates are updated in several iterations, where in each iteration synthetic data is generated to determine how to update the population eigenvalue estimates. comparison of the bootstrap eigenvalue correction with a state of the art correction method by karoui shows that depending on the type of population eigenvalue distribution, sometimes the karoui method performs better and sometimes our bootstrap method.
gsml: a unified framework for sparse metric learning. there has been significant recent interest in sparse metric learning (sml) in which we simultaneously learn both a good distance metric and a low-dimensional representation. unfortunately, the performance of existing sparse metric learning approaches is usually limited because the authors assumed certain problem relaxations or they target the sml objective indirectly. in this paper, we propose a generalized sparse metric learning method (gsml). this novel framework offers a unified view for understanding many of the popular sparse metric learning algorithms including the sparse metric learning framework proposed, the large margin nearest neighbor (lmnn), and the d-ranking vector machine (d-ranking vm). moreover, gsml also establishes a close relationship with the pairwise support vector machine. furthermore, the proposed framework is capable of extending many current non-sparse metric learning models such as relevant vector machine (rca) and a state-of-the-art method proposed into their sparse versions. we present the detailed framework, provide theoretical justifications, build various connections with other models, and propose a practical iterative optimization method, making the framework both theoretically important and practically scalable for medium or large datasets. a series of experiments show that the proposed approach can outperform previous methods in terms of both test accuracy and dimension reduction, on six real-world benchmark datasets.
a framework for computing the privacy scores of users in online social networks. a large body of work has been devoted to address corporate-scale privacy concerns related to social networks. the main focus was on how to share social networks owned by organizations without revealing the identities or sensitive relationships of the users involved. not much attention has been given to the privacy risk of users posed by their information sharing activities. in this paper, we approach the privacy concerns arising in online social networks from the individual users’ viewpoint: we propose a framework to compute a privacy score of a user, which indicates the potential privacy risk caused by his participation in the network. our definition of privacy score satisfies the following intuitive properties: the more sensitive the information revealed by a user, the higher his privacy risk. also, the more visible the disclosed information becomes in the network, the higher the privacy risk. we develop mathematical models to estimate both sensitivity and visibility of the information. we apply our methods to synthetic and real-world data and demonstrate their efficacy and practical utility.
accurate estimation of the degree distribution of private networks. we describe an efficient algorithm for releasing a provably private estimate of the degree distribution of a network. the algorithm satisfies a rigorous property of differential privacy, and is also extremely efficient, running on networks of 100 million nodes in a few seconds. theoretical analysis shows that the error scales linearly with the number of unique degrees, whereas the error of conventional techniques scales linearly with the number of nodes. we complement the theoretical analysis with a thorough empirical analysis on real and synthetic graphs, showing that the algorithm's variance and bias is low, that the error diminishes as the size of the input graph increases, and that common analyses like fitting a power-law can be carried out very accurately.
regression learning vector quantization. learning vector quantization (lvq) is a popular class of nearest prototype classifiers for multiclass classification. learning algorithms from this family are widely used because of their intuitively clear learning process and ease of implementation. in this paper we propose an extension of the lvq algorithm to regression. just like the lvq algorithm, the proposed modification uses a supervised learning procedure to learn the best prototype positions, but unlike lvq algorithm for classification, it also learns the best prototype target values. this results in the effective partition of the feature space, similar to the one the k-means algorithm would make. experimental results on benchmark datasets showed that the proposed regression lvq algorithm performs better than the nearest prototype competitors that choose prototypes randomly or through k-means clustering, classification lvq on quantized target values, and similarly to the memory-based parzen window and nearest neighbor algorithms.
joint emotion-topic modeling for social affective text mining. this paper is concerned with the problem of social affective text mining, which aims to discover the connections between social emotions and affective terms based on user-generated emotion labels. we propose a joint emotion-topic model by augmenting latent dirichlet allocation with an additional layer for emotion modeling. it first generates a set of latent topics from emotions, followed by generating affective terms from each topic. experimental results on an online news collection show that the proposed model can effectively identify meaningful latent topics for each emotion. evaluation on emotion prediction further verifies the effectiveness of the proposed model.
scalable algorithms for distribution search. distribution data naturally arise in countless domains, such as meteorology, biology, geology, industry and economics. however, relatively little attention has been paid to data mining for large distribution sets. given n distributions of multiple categories and a query distribution q, we want to find similar clouds (i.e., distributions), to discover patterns, rules and outlier clouds. for example, consider the numerical case of sales of items, where, for each item sold, we record the unit price and quantity; then, each customer is represented as a distribution of 2-d points (one for each item he/she bought). we want to find similar users, e.g., for market segmentation, anomaly/fraud detection. we propose to address this problem and present d-search, which includes fast and effective algorithms for similarity search in large distribution datasets. our main contributions are (1) approximate kl divergence, which can speed up cloud-similarity computations, (2) multi-step sequential scan, which efficiently prunes a significant number of search candidates and leads to a direct reduction in the search cost. we also introduce an extended version of d-search: (3) time-series distribution mining, which finds similar subsequences in time-series distribution datasets. extensive experiments on real multi-dimensional datasets show that our solution achieves up to 2,300 faster wall-clock time over the naive implementation while it does not sacrifice accuracy.
a local scalable distributed expectation maximization algorithm for large peer-to-peer networks. this paper describes a local and distributed expectation maximization algorithm for learning parameters of gaussian mixture models (gmm) in large peer-to-peer (p2p) environments. the algorithm can be used for a variety of well-known data mining tasks in distributed environments such as clustering, anomaly detection, target tracking, and density estimation to name a few, necessary for many emerging p2p applications in bioinformatics, webmining and sensor networks. centralizing all or some of the data to build global models is impractical in such p2p environments because of the large number of data sources, the asynchronous nature of the p2p networks, and dynamic nature of the data/network. the proposed algorithm takes a two-step approach. in the monitoring phase, the algorithm checks if the model ‘quality’ is acceptable by using an efficient local algorithm. this is then used as a feedback loop to sample data from the network and rebuild the gmm when it is outdated. we present thorough experimental results to verify our theoretical claims.
on the (in)security and (im)practicality of outsourcing precise association rule mining. the recent interest in outsourcing it services onto the cloud raises two main concerns: security and cost. one task that could be outsourced is data mining. in vldb 2007, wong et al. propose an approach for outsourcing association rule mining. their approach maps a set of real items into a set of pseudo items, then maps each transaction non-deterministically. this paper, analyzes both the security and costs associated with outsourcing association rule mining. we show how to break the encoding scheme from wong et al. without using context specific information and reduce the security to a one-to-one mapping. we present a stricter notion of security than used by wong et al., and then consider the practicality of outsourcing association rule mining. our results indicate that outsourcing association rule mining may not be practical, if the data owner is concerned with data confidentiality.
mining data streams with labeled and unlabeled training examples. in this paper, we propose a framework to build prediction models from data streams which contain both labeled and unlabeled examples. we argue that due to the increasing data collection ability but limited resources for labeling, stream data collected at hand may only have a small number of labeled examples, whereas a large portion of data remain unlabeled but can be beneficial for learning. unleashing the full potential of the unlabeled instances for stream data mining is, however, a significant challenge, consider that even fully labeled data streams may suffer from the concept drifting, and inappropriate uses of the unlabeled samples may only make the problem even worse. to build prediction models, we first categorize the stream data into four different categories, each of which corresponds to the situation where concept drifting may or may not exist in the labeled and unlabeled data. after that, we propose a relational k-means based transfer semi-supervised svm learning framework (rk-ts3vm), which intends to leverage labeled and unlabeled samples to build prediction models. experimental results and comparisons on both synthetic and real-world data streams demonstrate that the proposed framework is able to help build prediction models more accurate than other simple approaches can offer.
a global-model naive bayes approach to the hierarchical prediction of protein functions. in this paper we propose a new global--model approach for hierarchical classification, where a single global classification model is built by considering all the classes in the hierarchy -- rather than building a number of local classification models as it is more usual in hierarchical classification. the method is an extension of the flat classification algorithm naive bayes. we present the extension made to the original algorithm as well as its evaluation on eight protein function hierarchical classification datasets. the achieved results are positive and show that the proposed global model is better than using a local model approach.
?-anomica: a fast support vector based novelty detection technique. in this paper we propose ν-anomica, a novel anomaly detection technique that can be trained on huge data sets with much reduced running time compared to the benchmark one-class support vector machines algorithm. in ν-anomica, the idea is to train the machine such that it can provide a close approximation to the exact decision plane using fewer training points and without losing much of the generalization performance of the classical approach. we have tested the proposed algorithm on a variety of continuous data sets under different conditions. we show that under all test conditions the developed procedure closely preserves the accuracy of standard one- class support vector machines while reducing both the training time and the test time by 5 − 20 times.
active learning with generalized queries. active learning can actively select or construct examples to label to reduce the number of labeled examples needed for building accurate classifiers. however, previous works of active learning can only ask specific queries. for example, to predict osteoarthritis from a patient dataset with 30 attributes, specific queries always contain values of all these 30 attributes, many of which may be irrelevant. a more natural way is to ask "generalized queries" with don't-care attributes, such as "are people over 50 with knee pain likely to have osteoarthritis?" (with only two attributes: age and type of pain). we assume that the oracle (and human experts) can readily answer those generalized queries by returning probabilistic labels. the power of such generalized queries is that one generalized query may be equivalent to many specific ones. however, overly general queries may receive highly uncertain labels from the oracle, and this makes learning difficult. in this paper, we propose a novel active learning algorithm that asks generalized queries. we demonstrate experimentally that our new method asks significantly fewer queries compared with the previous works of active learning. our method can be readily deployed in real-world tasks where obtaining labeled examples is costly.
a new clustering algorithm based on regions of influence with self-detection of the best number of clusters. clustering methods usually require to know the best number of clusters, or another parameter, e.g. a threshold, which is not ever easy to provide. this paper proposes a new graph-based clustering method called gbc which detects automatically the best number of clusters, without requiring any other parameter. in this method based on regions of influence, a graph is constructed and the edges of the graph having the higher values are cut according to a hierarchical divisive procedure. an index is calculated from the size average of the cut edges which self-detects the more appropriate number of clusters. the results of gbc for 3 quality indices (dunn, silhouette and davies-bouldin) are compared with those of k-means, ward's hierarchical clustering method and dbscan on 8 benchmarks. the experiments show the good performance of gbc in the case of well separated clusters, even if the data are unbalanced, non-convex or with presence of outliers, whatever the shape of the clusters.
conditional models for non-smooth ranking loss functions. learning to rank is an important area at the interface of machine learning, information retrieval and web search. the central challenge in optimizing various measures of ranking loss is that the objectives tend to be non-convex and discontinuous. to make such functions amenable to gradient based optimization procedures one needs to design clever bounds. in recent years, boosting, neural networks, support vector machines, and many other techniques have been applied. however, there is little work on directly modeling a conditional probability pr(y|x_q) where y is a permutation of the documents to be ranked and x_q represents their feature vectors with respect to a query q. a major reason is that the space of y is huge: n! if n documents must be ranked. we first propose an intuitive and appealing expected loss minimization objective, and give an efficient shortcut to evaluate it despite the huge space of ys. unfortunately, the optimization is non-convex, so we propose a convex approximation. we give a new, efficient monte carlo sampling method to compute the objective and gradient of this approximation, which can then be used in a quasi-newton optimizer like lbfgs. extensive experiments with the widely-used letor dataset show large ranking accuracy improvements beyond recent and competitive algorithms.
automatically extracting dialog models from conversation transcripts. there is a growing need for task-oriented natural language dialog systems that can interact with a user to accomplish a given objective. recent work on building task-oriented dialog systems have emphasized the need for acquiring task-specific knowledge from un-annotated conversational data. in our work we acquire task-specific knowledge by defining \textit{sub-task} as the key unit of a task-oriented conversation. we propose an unsupervised, apriori like algorithm that extracts the sub-tasks and their valid orderings from un-annotated human-human conversations. modeling dialogues as a combination of sub-tasks and their valid orderings easily captures the variability in conversations. it also provides us the ability to map our dialogue model to aiml constructs and therefore use off-the-shelf aiml interpreters to build task-oriented chat-bots. we conduct experiments on real world data sets to establish the effectiveness of the sub-task extraction process. we codify the extracted sub-tasks in an aiml knowledge base and build a chatbot using this knowledge base. we also show the usefulness of the chatbot in automatically handling customer requests by performing a user evaluation study.
sparse norm-regularized reconstructive coefficients learning. inspired by the fact that the final decision rule is mainly affected by a small subset of the training samples, i.e., support vector machine(svm) shows that the decision function relies on the few samples that are on or over the margin. we propose a new framework that explicitly strengthen this intuitive fact by adding an $l_1$-norm regularizer. we give different formulations for our framework in different scenarios, and the experiments show that our framework can not only lead to high sparse solutions but also better performance than traditional methods.
unsupervised relation extraction by massive clustering. the goal of information extraction is to automatically generate structured pieces of information from the relevant information contained in text documents. machine learning techniques have been applied to reduce the cost of information extraction system adaptation. however, elements of human supervision strongly bias the learning process. unsupervised learning approaches can avoid these biases. in this paper, we propose an unsupervised approach to learning for relation detection, based on the use of massive clustering ensembles. the results obtained on the ace relation mention detection task outperform in terms of f1 score by 5 points the state of the art of unsupervised techniques for this evaluation framework, in addition to being simpler and more flexible.
projective clustering ensembles. recent advances in data clustering concern clustering ensembles and projective clustering methods, each addressing different issues in clustering problems. in this paper, we consider for the first time the projective clustering ensemble (pce) problem, whose main goal is to derive a proper projective consensus partition from an ensemble of projective clustering solutions. we formalize pce as an optimization problem which does not rely on any particular clustering ensemble algorithm, and which has the ability to handle hard as well as soft data clustering, and different feature weightings. we provide two formulations for pce, namely a two-objective and a single-objective problem, in which the object-based and feature-based representations of the ensemble solutions are taken into account differently. experiments have demonstrated that the proposed methods for pce show clear improvements in terms of accuracy of the output consensus partition.
self-adaptive anytime stream clustering. clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. as data is constantly arriving, time for processing is limited. clustering has to be performed in a single pass over the incoming data and within the possibly varying inter-arrival times of the stream. likewise, memory is limited, making it impossible to store all data. for clustering, we are faced with the challenge of maintaining a current result that can be presented to the user at any given time. in this work, we propose a parameter free algorithm that automatically adapts to the speed of the data stream. it makes best use of the time available under the current constraints to provide a clustering of the objects seen up to that point. our approach incorporates the age of the objects to reflect the greater importance of more recent data. moreover, we are capable of detecting concept drift, novelty and outliers in the stream. for efficient and effective handling, we introduce the clustree, a compact and self-adaptive index structure for maintaining stream summaries. our experiments show that our approach is capable of handling a multitude of different stream characteristics for accurate and scalable anytime stream clustering.
unsupervised class separation of multivariate data through cumulative variance-based ranking. this paper introduces a new extension of outlier detection approaches and a new concept, class separation through variance. we show that accumulating information about the outlierness of points in multiple subspaces leads to a ranking in which classes with differing variance naturally tend to separate. exploiting this leads to a highly effective and efficient unsupervised class separation approach, especially useful in the difficult case of heavily overlapping distributions. unlike typical outlier detection algorithms, this method can be applied beyond the `rare classes' case with great success. two novel algorithms that implement this approach are provided. additionally, experiments show that the novel methods typically outperform other state-of-the-art outlier detection methods on high dimensional data such as feature bagging, soe1, lof, orca and robust mahalanobis distance and competes even with the leading supervised classification methods.
efficient discovery of confounders in large data sets. given a large transaction database, association analysis is concerned with efficiently finding strongly related objects. unlike traditional associate analysis, where relationships among variables are searched at a global level, we examine confounding factors at a local level. indeed, many real-world phenomena are localized to specific regions and times. these relationships may not be visible when the entire data set is analyzed. specially, confounding effects that change the direction of correlation is the most significant. along this line, we propose to efficiently find confounding effects attributable to local associations. specifically, we derive an upper bound by a necessary condition of confounders, which can help us prune the search space and efficiently identify confounders. experimental results show that the proposed confound algorithm can effectively identify confounders and the computational performance is an order of magnitude faster than benchmark methods.
a deep non-linear feature mapping for large-margin knn classification. knn is one of the most popular data mining methods for classification, but it often fails to work well with inappropriate choice of distance metric or due to the presence of numerous class-irrelevant features. linear feature transformation methods have been widely applied to extract class-relevant information to improve knn classification, which is very limited in many applications. kernels have also been used to learn powerful non-linear feature transformations, but these methods fail to scale to large datasets. in this paper, we present a scalable non-linear feature mapping method based on a deep neural network pretrained with restricted boltzmann machines for improving knn classification in a large-margin framework, which we call dnet-knn. dnet-knn can be used for both classification and for supervised dimensionality reduction. the experimental results on two benchmark handwritten digit datasets and one newsgroup text dataset show that dnet-knn has much better performance than large-margin knn using a linear mapping and knn based on a deep autoencoder pretrained with restricted boltzmann machines.
algorithms for large, sparse network alignment problems. we propose a new distributed algorithm for sparse variants of the network alignment problem, which occurs in a variety of data mining areas including systems biology, database matching, and computer vision. our algorithm uses a belief propagation heuristic and provides near optimal solutions for this np-hard combinatorial optimization problem. we show that our algorithm is faster and outperforms or ties existing algorithms on synthetic problems, a problem in bioinformatics, and a problem in ontology matching. we also provide a unified framework for studying and comparing all network alignment solvers.
a linear-time graph kernel. the design of a good kernel is fundamental for knowledge discovery from graph-structured data. existing graph kernels exploit only limited information about the graph structures but are still computationally expensive. we propose a novel graph kernel based on the structural characteristics of graphs. the key is to represent node labels as binary arrays and characterize each node using logical operations on the label set of the connected nodes. our kernel has a linear time complexity with respect to the number of nodes times the average number of neighboring nodes in the given graphs. the experimental result shows that the proposed kernel performs comparable and much faster than a state-of-the-art graph kernel for benchmark data sets and shows high scalability for new applications with large graphs.
efficient algorithm for computing link-based similarity in real world networks. similarity calculation has many applications, such as information retrieval, and collaborative filtering, among many others. it has been shown that link-based similarity measure, such as simrank, is very effective in characterizing the object similarities in networks, such as the web, by exploiting the object-to-object relationship. unfortunately, it is prohibitively expensive to compute the link-based similarity in a relatively large graph. in this paper, based on the observation that link-based similarity scores of real world graphs follow the power-law distribution, we propose a new approximate algorithm, namely power-simrank, with guaranteed error bound to efficiently compute link-based similarity measure. we also prove the convergence of the proposed algorithm. extensive experiments conducted on real world datasets and synthetic datasets show that the proposed algorithm outperforms simrank by four-five times in terms of efficiency while the error generated by the approximation is small.
a cost-effective lsh filter for fast pairwise mining. the pairwise mining problem is to discover pairwise objects having measures greater than the user-specified minimum threshold from a collection of objects. it is essential in a large variety of database and data-mining applications. of late, there has been increasing interest in applying a locality-sensitive hashing (lsh) scheme for pairwise mining. lsh-type methods have shown themselves to be simply implementable and capable of achieving significant performance gain in running time over most exact methods. however, the present lsh-type methods still suffer from some bottlenecks, such as ”the curse of threshold”. in this paper, we proposed a novel lshbased method, namely cost-effective lsh filter (ce-lsh for short), for pairwise mining. compared with previous lsh-type methods, it uses a lower fixed number of lsh functions and is thus more cost-effective. substantial experiments evidence that our method gives significant improvement in running time over existing lsh-type methods and some recently reported method based on upper-bound. experimental results also indicate that it scales well even for a relatively low minimum threshold and for a fairly small miss ratio.
spatio-temporal energy based gait recognition. recently there has been lot of interest in using the gait energy image (gei) of human walk sequence for individual recognition. researchers have reported very good recognition rates using both unsupervised and supervised methods for normal walk sequences. however, the performance degrades when there is a variant like change in clothing or carrying a bag. this paper shows that the performance for the variant situations can be improved by constructing the gei with sway alignment instead of upper body alignment, and dynamically selecting just the required number of rows from the bottom of the silhouette as inputs for an unsupervised feature selection approach. the improvement in recognition rates are established with performance testing on a large gait dataset.
active selection of sensor sites in remote sensing applications. in a data-mining approach, a model for estimation of aerosol optical depth (aod) from satellite observations is learned using collocated satellite and ground-based observations. for accurate learning of such a spatio-temporal model, it is important to collect ground-based data from a large number of sites. the objective of this project is to determine appropriate locations for the next set of ground-based data collection sites to maximize accuracy of aod estimation. ideally, a new site should capture the most significant unseen aerosol patterns and should be the least correlated with the previously observed patterns. we propose achieving this aim by selecting the locations on which the existing prediction model is the most uncertain. several criteria were considered for site selection, including uncertainty, spatial diversity, similarity in temporal pattern, and their combination. extensive experiments on globally distributed data over 90 aeronet sites from the years 2005 and 2006 provide strong evidence that sites selected using the proposed algorithms improve the overall aod prediction accuracy at a faster rate than those selected randomly or based on spatial diversity among sites.
finding associations and computing similarity via biased pair sampling. sampling-based methods have previously been proposed for the problem of finding interesting associations in data, even for low-support items. while these methods do not guarantee precise results, they can be vastly more efficient than approaches that rely on exact counting. however, for many similarity measures no such methods have been known. in this paper we show how a wide variety of measures can be supported by a simple biased sampling method. the method also extends to find high-confidence association rules. we demonstrate theoretically that our method is superior to exact methods when the threshold for "interesting similarity/confidence" is above the average pairwise similarity/confidence, and the average support is not too low. our method is particularly good when transactions contain many items. we confirm in experiments on standard association mining benchmarks that this gives a significant speedup on real data sets (sometimes much larger than the theoretical guarantees). reductions in computation time of over an order of magnitude, and significant savings in space, are observed.
filtering and refinement: a two-stage approach for efficient and effective anomaly detection. anomaly detection is an important data mining task. most existing methods treat anomalies as inconsistencies and spend the majority amount of time on modeling normal instances. a recently proposed, sampling-based approach may substantially boost the efficiency in anomaly detection but may also lead to weaker accuracy and robustness. in this study, we propose a two-stage approach to find anomalies in complex datasets with high accuracy as well as low time complexity and space cost. instead of analyzing normal instances, our algorithm first employs an efficient deterministic space partition algorithm to eliminate obvious normal instances and generates a small set of anomaly candidates with a single scan of the dataset. it then checks each candidate with density-based multiple criteria to determine the final results. this two-stage framework also detects anomalies of different notions. our experiments show that this new approach finds anomalies successfully in different conditions and ensures a good balance of efficiency, accuracy, and robustness.
online system problem detection by mining patterns of console logs. we describe a novel application of using data mining and statistical learning methods to automatically monitor and detect abnormal execution traces from console logs in an online setting. different from existing solutions, we use a two stage detection system. the first stage uses frequent pattern mining and distribution estimation techniques to capture the dominant patterns (both frequent sequences and time duration). the second stage use principal component analysis based anomaly detection technique to identify actual problems. using real system data from a 203-node hadoop [1] cluster, we show that we can not only achieve highly accurate and fast problem detection, but also help operators better understand execution patterns in their system.
hierarchical probabilistic segmentation of discrete events. segmentation, the task of splitting a long sequence of discrete symbols into chunks, can provide important information about the nature of the sequence that is understandable to humans. algorithms for segmenting mostly belong to the supervised learning family, where a labeled corpus is available to the algorithm in the learning phase. we are interested, however, in the unsupervised scenario, where the algorithm never sees examples of successful segmentation, but still needs to discover meaningful segments. in this paper we present an unsupervised learning algorithm for segmenting sequences of symbols or categorical events. our algorithm, hierarchical multigram, hierarchically builds a lexicon of segments and computes a maximum likelihood segmentation given the current lexicon. thus, our algorithm is most appropriate to hierarchical sequences, where smaller segments are grouped into larger segments. our probabilistic approach also allows us to suggest conditional entropy as a measurement of the quality of a segmentation in the absence of labeled data. we compare our algorithm to two previous approaches from the unsupervised segmentation literature, showing it to provide superior segmentation over a number of benchmarks. we also compare our algorithm to previous approaches over a segmentation of the unlabeled interactions of a web service and its client.
unified solution to nonnegative data factorization problems. in this paper, we restudy the non-convex data factorization problems (regularized or not, unsupervised or supervised), where the optimization is confined in the \emph{nonnegative} orthant, and provide a \emph{unified} convergency provable solution based on multiplicative nonnegative update rules. this solution is general for optimization problems with block-wisely quadratic objective functions, and thus direct update rules can be derived by skipping over the tedious specific procedure deduction process and algorithmic convergence proof. by taking this unified solution as a general template, we i) re-explain several existing nonnegative data factorization algorithms, ii) develop a variant of nonnegative matrix factorization formulation for handling out-of-sample data, and iii) propose a new nonnegative data factorization algorithm, called correlated co-decomposition (ccd), to simultaneously factorize two feature spaces by exploring the inter-correlated information. experiments on both face recognition and multi-label image annotation tasks demonstrate the wide applicability of the unified solution as well as the effectiveness of two proposed new algorithms.
grape: a graph-based framework for disambiguating people appearances in web search. finding information about people using search engines is one of the most common activities on the web. however, search engines usually return a long list of web pages, which may be relevant to many namesakes, especially given the explosive growth of web data. to address the challenge caused by name ambiguity in web people search, this paper proposes a novel graph-based framework, grape (abbr. a graph-based framework for disambiguating people appearances in web search). in grape, people tag information (e.g., people name, organization, and email address) surrounding the queried people name is extracted from the search results, a graph-based unsupervised algorithm is then developed to cluster the extracted tags, where a new method, cohesion, is introduced to measure the importance of a tag for clustering, and each final cluster of tags represents a unique people entity. experimental results show that our proposed framework outperforms the state-of-the-art web people name disambiguation approaches.
inverse time dependency in convex regularized learning. in the conventional regularized learning, training time increases as the training set expands. recent work on l2 linear svm challenges this common sense by proposing the inverse time dependency on the training set size. in this paper, we first put forward a primal gradient solver (pgs) to effectively solve the convex regularized learning problem. this solver is based on the stochastic gradient descent method and the fenchel conjugate adjustment, employing the well-known online strongly convex optimization algorithm with logarithmic regret. we then theoretically prove the inverse dependency property of our pgs, embracing the previous work of the l2 linear svm as a special case and enable the l_p-norm optimization to run within a bounded sphere, which qualifies more convex loss functions in pgs. we further illustrate this solver in three examples: svm, logistic regression and regularized least square. experimental results substantiate the property of the inverse dependency on training data size.
learning local components to understand large bayesian networks. bayesian networks are known for providing an intuitive and compact representation of probabilistic information and allowing the creation of models over a large and complex domain. bayesian learning and reasoning are nontrivial for a large bayesian network. in parallel, it is a tough job for users (domain experts) to extract accurate information from a large bayesian network due to dimensional difficulty. we define a formulation of local components and propose a clustering algorithm to learn such local components given complete data. the algorithm groups together most inter-relevant attributes in a domain. we evaluate its performance on three benchmark bayesian networks and provide results in support. we further show that the learned components may represent local knowledge more precisely in comparison to the full bayesian networks when working with a small amount of data.
least square incremental linear discriminant analysis. linear discriminant analysis (lda) is a well-known dimension reduction approach, which projects high-dimensional data into a low-dimensional space with the best separation of different classes. in many tasks, the data accumulates over time, and thus incremental lda is more desirable than batch lda. several incremental lda algorithms have been developed and achieved success; however, the eigen-problem involved requires a large computation cost, which hampers the efficiency of these algorithms. in this paper, we propose a new incremental lda algorithm, ls-ilda, based on the least square solution of lda. when new samples are received, ls-ilda incrementally updates the least square solution of lda. our analysis discloses that this algorithm produces the exact least square solution of batch lda, while its computational cost is o(min(n; d) £ d) for one update on dataset containing n instances in d-dimensional space. experimental results show that comparing with state-of-the-art incremental lda algorithms, our proposed ls-ilda achieves high accuracy with low time cost.
resolving identity uncertainty with learned random walks. a pervasive problem in large relational databases is identity uncertainty which occurs when multiple entries in a database refer to the same underlying entity in the world. relational databases exhibit rich graphical structure and are naturally modeled as graphs whose nodes represent entities and whose typed-edges represent relations between them. we propose using random walk models for resolving identity uncertainty since they have proven effective for finding points which are proximately located in a network. because not all types of relations are equally helpful in alleviating identity uncertainty, we develop a supervised approach to learning the usefulness of different database relations from a training set of database entries whose true identities are known. when tested on the task of resolving uncertainty of ambiguously named authors in bibliographical data, the learned random walk models yield performance superior to support vector machines, and to a related spectral clustering method.
binomial matrix factorization for discrete collaborative filtering. matrix factorization (mf) models have proved efficient and well scalable for collaborative filtering (cf) problems. many researchers also present the probabilistic interpretation of mf. they usually assume that the factor vectors of users and items are from normal distributions, and so are the ratings when the user and item factors are given. then they can derive the exact mf algorithm by finding a map estimate of the model parameters. in this paper we suggest a new probabilistic perspective on mf for discrete cf problems. we assume that all ratings are from binomial distributions with different preference parameters instead of the original normal distributions. the new interpretation is more reasonable for discrete cf problems since they only allow several legal discrete rating values. we also present two effective algorithms to learn the new model and make predictions. they are applied to the netflix prize data set and acquire considerably better accuracy than those of mf.
an l-infinity norm visual classifier. we introduce a mathematical framework, based on the l-infinity norm distance metric, to describe human interactions in a visual data mining environment. we use the framework to build a classifier that involves an algebra on hyper-rectangles. our classifier, called visclassifier, generates set-wise rules from simple gestures in an exploratory visual gui. logging these rules allows us to apply our analysis to a new sample or batch of data so that we can assess the predictive power of our visual-processing motivated classifier. the accuracy of this classifier on widely-used benchmark datasets rivals the accuracy of competitive classifiers.
relevant subspace clustering: mining the most interesting non-redundant concepts in high dimensional data. subspace clustering aims at detecting clusters in any subspace projection of a high dimensional space. as the number of possible subspace projections is exponential in the number of dimensions, the result is often tremendously large. recent approaches fail to reduce results to relevant subspace clusters. their results are typically highly redundant, i.e. many clusters are detected multiple times in several projections. in this work, we propose a novel model for relevant subspace clustering (rescu). we present a global optimization which detects the most interesting non-redundant subspace clusters. we prove that computation of this model is np-hard. for rescu, we propose an approximative solution that shows high accuracy with respect to our relevance model. thorough experiments on synthetic and real world data show that rescu successfully reduces the result to manageable sizes. it reliably achieves top clustering quality while competing approaches show greatly varying performance.
parallel pathfinder algorithms for mining structures from graphs. pathfinder networks are increasingly used in data mining for different purposes, like network visualization or knowledge extraction. this novel way of representing graphical data has been proven to give better results than other link reduction algorithms, like minimum spanning networks however, this increase in quality comes with a high computation cost, typically of the order of n^3 or higher, where n is the number of nodes in the graph. while this problem has previously been tackled by using mathematical properties to speed up the algorithm, in this paper, we propose two new algorithms to speed up pathfinder computation based on parallelization techniques to take advantage of the increasingly available multi-core hardware platform. experiments show that both new algorithms are more efficient than the state of the art algorithms; one of them can achieve speed-ups of up to x127 with an average of x23 on recent hardware (2007).
two heads better than one: metric+active learning and its applications for it service classification. large it service providers track service requests and their execution through problem/change tickets. it is important to classify the tickets based on the problem/change description in order to understand service quality and to optimize service processes. however, two challenges exist in solving this classification problem: 1) ticket descriptions from different classes are of highly diverse characteristics, which invalidates most standard distance metrics; 2) it is very expensive to obtain high-quality labeled data. to address these challenges, we develop two seemingly independent methods 1) discriminative neighborhood metric learning (dnml) and 2) active learning with median selection (alms), both of which are, however, based on the same core technique: iterated representative selection. a case study on real it service classification application is presented to demonstrate the effectiveness and efficiency of our proposed methods.
probabilistic similarity query on dimension incomplete data. retrieving similar data has drawn many research efforts in the literature due to its importance in data mining, database and information retrieval. this problem is challenging when the data is incomplete. in previous research, data incompleteness refers to the fact that data values for some dimensions are unknown. however, in many practical applications (e.g., data collection by sensor network under bad environment), not only data values but even data dimension information may also be missing, which will make most similarity query algorithms infeasible. in this work, we propose the novel similarity query problem on dimension incomplete data and adopt a probabilistic framework to model this problem. for this problem, users can give a distance threshold and a probability threshold to specify their retrieval requirements. the distance threshold is used to specify the allowed distance between query and data objects and the probability threshold is used to require that the retrieval results satisfy the distance condition at least with the given probability. instead of enumerating all possible cases to recover the missed dimensions, we propose an efficient approach to speed up the retrieval process by leveraging the inherent relations between query and dimension incomplete data objects. during the query process, we estimate the lower/upper bounds of the probability that the query is satisfied by a given data object, and utilize these bounds to filter irrelevant data objects efficiently. furthermore, a probability triangle inequality is proposed to further speed up query processing. according to our experiments on real data sets, the proposed similarity query method is verified to be effective and efficient on dimension incomplete data.
constraint-based pattern mining in dynamic graphs. dynamic graphs are used to represent relationships between entities that evolve over time. meaningful patterns in such structured data must capture strong interactions and their evolution over time. in social networks, such patterns can be seen as dynamic community structures, i.e., sets of individuals who strongly and repeatedly interact. in this paper, we propose a constraint-based mining approach to uncover evolving patterns. we propose to mine dense and isolated subgraphs defined by two user-parameterized constraints. the temporal evolution of such patterns is captured by associating a temporal event type to each identified subgraph. we consider five basic temporal events: the formation, dissolution, growth, diminution and stability of subgraphs from one time stamp to the next. we propose an algorithm that finds such subgraphs in a time series of graphs processed incrementally. the extraction is feasible due to efficient patterns and data pruning strategies. we demonstrate the applicability of our method on several real-world dynamic graphs and extract meaningful evolving communities.
rule ensembles for multi-target regression. methods for learning decision rules are being successfully applied to many problem domains, especially where understanding and interpretation of the learned model is necessary. in many real life problems, we would like to predict multiple related (nominal or numeric) target attributes simultaneously. methods for learning rules that predict multiple targets at once already exist, but are unfortunately based on the covering algorithm, which is not very well suited for regression problems. a better solution for regression problems may be a rule ensemble approach that transcribes an ensemble of decision trees into a large collection of rules. an optimization procedure is then used for selecting the best (and much smaller) subset of these rules, and to determine their weights. using the rule ensembles approach we have developed a new system for learning rule ensembles for multi-target regression problems. the newly developed method was extensively evaluated and the results show that the accuracy of multi-target regression rule ensembles is better than the accuracy of multi-target regression trees, but somewhat worse than the accuracy of multi-target random forests. the rules are significantly more concise than random forests, and it is also possible to create very small rule sets that are still comparable in accuracy to single regression trees.
semi-naive exploitation of one-dependence estimators. it is well known that the key of bayesian classifier learning is to balance the two important issues, that is, the exploration of attribute dependencies in high orders for ensuring a sufficient flexibility in approximating the ground-truth dependencies, and the exploration of low orders for ensuring a stable probability estimate from limited training samples. by allowing one-order attribute dependencies, one-dependence estimators (odes) have been shown to be able to approximate the ground-truth attribute dependencies whilst keeping the effectiveness of probability estimation, and therefore leading to excellent performance. in previous studies, however, odes were exploited in simple ways, such as by averaging, for classification. in this paper, we propose a semi-naive exploitation of odes that fits a function of odes to pursue higher-order attribute dependencies. extensive experiments show that the proposed snode approach can achieve better performance than many state-of-the-art bayesian classifiers.
trbagg: a simple transfer learning method and its application to personalization in collaborative tagging. the aim of transfer learning is to improve prediction accuracy on a target task by exploiting the training examples for tasks that are related to the target one. transfer learning has received more attention in recent years, because this technique is considered to be helpful in reducing the cost of labeling. in this paper, we propose a very simple approach to transfer learning: trbagg, which is the extension of bagging. trbagg is composed of two stages: many weak classifiers are first generated as in standard bagging, and these classifiers are then filtered based on their usefulness for the target task. this simplicity makes it easy to work reasonably well without severe tuning of learning parameters. further, our algorithm equips an algorithmic scheme to avoid negative transfer. we applied trbagg to personalized tag prediction tasks for social bookmarks our approach has several convenient characteristics for this task such as adaptation to multiple tasks with low computational cost.
an effective approach to inverse frequent set mining. the inverse frequent set mining problem is the problem of computing a database on which a given collection of itemsets must emerge to be frequent. earlier studies focused on investigating computational and approximability properties of this problem. in this paper, we face it under the pragmatic perspective of defining heuristic solution approaches that are effective and scalable in real scenarios. in particular, a general formulation of the problem is considered where minimum and maximum support constraints can be defined on each itemset, and where no bound is given beforehand on the size of the resulting output database. within this setting, an algorithm is proposed that always satisfies the maximum support constraints, but which treats minimum support constraints as soft ones that are enforced as long as possible. a thorough experimentation evidences that minimum support constraints are hardly violated in practice, and that such negligible degradation in accuracy (which is unavoidable due to the theoretical intractability of the problem) is compensated by very good scaling performances.
explore/exploit schemes for web content optimization. we propose novel multi-armed bandit (explore/exploit) schemes to maximize total clicks on a content module published regularly on yahoo! intuitively, one can ``explore'' each candidate item by displaying it to a small fraction of user visits to estimate the item's click-through rate (ctr), and then ``exploit'' high ctr items in order to maximize clicks. while bandit methods that seek to find the optimal trade-off between explore and exploit have been studied for decades, existing solutions are not satisfactory for web content publishing applications where dynamic set of items with short lifetimes, delayed feedback and non-stationary reward (ctr) distributions are typical. in this paper, we develop a bayesian solution and extend several existing schemes to our setting. through extensive evaluation with nine bandit schemes, we show that our bayesian solution is uniformly better in several scenarios. we also study the empirical characteristics of our schemes and provide useful insights on the strengths and weaknesses of each. finally, we validate our results with a ``side-by-side'' comparison of schemes through live experiments conducted on a random sample of real user visits to yahoo!
a tree-based framework for difference summarization. understanding the differences between two datasets is a fundamental data mining question and is also ubiquitously important across many real world scientific applications. in this paper, we propose a tree-based framework to provide a parsimonious explanation of the difference between two distributions based on rigorous two-sample statistical test. we develop two efficient approaches. the first one is a dynamic programming approach that finds a minimal number of data subsets that describe the difference between two data sets. the second one is a greedy approach that approximates the dynamic programming approach. we employ the well-known friedman's mst (minimal spanning tree) statistics for two-sample statistical tests in our summarization tree construction, and develop novel techniques to speedup its computational procedure. we performed a detailed experimental evaluation on both real and synthetic datasets and demonstrated the effectiveness of our tree-summarization approach.
effective criterion functions for efficient agglomerative clustering on very large networks. as the agglomerative clustering algorithm is widely used in data mining, image processing, bioinformatics and pattern recognition. it has attracted great interests from both academical and industrial communities. however, existing studies neglect the decisive factor of the efficiency of the agglomerative clustering algorithm for large complex networks and usually use criterion functions which lead to inefficiency. in this paper, we propose three effective criterion functions for improving performance of agglomerative clustering algorithm. we note that clustering efficiency is determined by two factors: a) the number of neighbors of two merged clusters in each merge step; b) the number of neighbors shared by the two clusters. based on these observations, we propose a framework for designing criterion functions in order to efficiently find clusters in very large networks. we devise three criterion functions that can effectively control the number of neighbors of clusters, and they can efficiently produce high-quality clusters. we have implemented our method and compared with existing studies on real networks, and our method outperforms state-of-the-art approaches significantly on large networks.
itopicmodel: information network-integrated topic modeling. document networks, i.e., networks associated with text information, are becoming increasingly popular due to the ubiquity of web documents, blogs, and various kinds of online data. in this paper, we propose a novel topic modeling framework for document networks, which builds a unified generative topic model that is able to consider both text and structure information for documents. a graphical model is proposed to describe the generative model. on the top layer of this graphical model, we define a novel multivariate markov random field for topic distribution random variables for each document, to model the dependency relationships among documents over the network structure. on the bottom layer, we follow the traditional topic model to model the generation of text for each document. a joint distribution function for both the text and structure of the documents is thus provided. a solution to estimate this topic model is given, by maximizing the log-likelihood of the joint probability. some important practical issues in real applications are also discussed, including how to decide the topic number and how to choose a good network structure. we apply the model on two real datasets, dblp and cora, and the experiments show that this model is more effective in comparison with the state-of-the-art topic modeling algorithms.
feature selection in the tensor product feature space. classifying objects that are sampled jointly from two or more domains has many applications. the tensor product feature space is useful for modeling interactions between feature sets in different domains but feature selection in the tensor product feature space is challenging. conventional feature selection methods ignore the structure of the feature space and may not provide the optimal results. in this paper we propose methods for selecting features in the original feature spaces of different domains. we obtained sparsity through two approaches, one using integer quadratic programming and another using l1-norm regularization. experimental studies on biological data sets validate our approach.
topic distributions over links on web. it is well known that web users create links with different intentions. however, a key question, which is not well studied, is how to categorize the links and how to quantify the strength of the influence of a web page on another if there is a link between the two linked web pages. in this paper, we focus on the problem of link semantics analysis, and propose a novel supervised learning approach to build a model, based on a training link-labeled and link-weighted graph where a link-label represents the category of a link and a link-weight represents the influence of one web page on the other in a link. based on the model built, we categorize links and quantify the influence of web pages on the others in a large graph in the same application domain. we discuss our proposed approach, namely pairwise restricted boltzmann machines (prbms), and conduct extensive experimental studies to demonstrate the effectiveness of our approach using large real datasets.
semi-supervised sequence labeling with self-learned features. typical information extraction (ie) systems can be seen as tasks assigning labels to words in a natural language sequence. the performance is restricted by the availability of labeled words. to tackle this issue, we propose a semi-supervised approach to improve the sequence labeling procedure in ie through a class of algorithms with {\em self-learned features} (slf). a supervised classifier can be trained with annotated text sequences and used to classify each word in a large set of unannotated sentences. by averaging predicted labels over all cases in the unlabeled corpus, slf training builds class label distribution patterns for each word (or word attribute) in the dictionary and re-trains the current model iteratively adding these distributions as extra word {\em features}. basic slf models how likely a word could be assigned to target class types. several extensions are proposed, such as learning words' class boundary distributions. slf exhibits robust and scalable behaviour and is easy to tune. we applied this approach on four classical ie tasks: named entity recognition (german and english), part-of-speech tagging (english) and one gene name recognition corpus. experimental results show effective improvements over the supervised baselines on all tasks. in addition, when compared with the closely related self-training idea, this approach shows favorable advantages.
evaluating statistical tests for within-network classifiers of relational data. recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and identically distributed (i.i.d.). these methods specifically exploit the statistical dependencies among instances in order to improve classification accuracy. however, there has been little focus on how these same dependencies affect our ability to draw accurate conclusions about the performance of the models. more specifically, the complex link structure and attribute dependencies in network data violate the assumptions of many conventional statistical tests and make it difficult to use these tests to assess the models in an unbiased manner. in this work, we examine the task of within-network classification and the question of whether two algorithms will learn models which will result in significantly different levels of performance. we show that the commonly-used form of evaluation (paired t-test on overlapping network samples) can result in an unacceptable level of type i error. furthermore we show that type i error increases as (1) the correlation among instances increases and (2) the size of the evaluation set increases (i.e., the proportion of labeled nodes in the network decreases). we propose a method for network cross-validation that combined with paired t-tests produces more acceptable levels of type i error while still providing reasonable levels of statistical power (i.e., type ii error).
cofkm: a centralized method for multiple-view clustering. this paper deals with clustering for multi-view data, i.e. objects described by several sets of variables or proximity matrices. many important domains or applications such as information retrieval, biology, chemistry and marketing are concerned by this problematic. the aim of this data mining research field is to search for clustering patterns that perform a consensus between the patterns from different views. this requires to merge information from each view by performing a fusion process that identifies the agreement between the views and solves the conflicts. various fusion strategies can be applied, occurring either before, after or during the clustering process. we draw our inspiration from the existing algorithms based on a centralized strategy. we propose a fuzzy clustering approach that generalizes the three fusion strategies and outperforms the main existing multi-view clustering algorithm both on synthetic and real datasets.
interaction-based clustering of multivariate time series. in this paper, we present a novel approach to clustering multivariate time series. in contrast to previous approaches, we base our cluster notion on the interactions between the univariate time series within a data object. our objective is to assign objects with a similar intrinsic interaction pattern to a common cluster. to formalize this idea, we define a cluster by a set of mathematical models describing the cluster-specific interaction pattern. in addition, we propose interaction k-means (ikm), an efficient algorithm for partitioning clustering of multivariate time series. the cluster-specific interaction patterns detected by ikm provide valuable information for interpretation of the cluster content. an extensive experimental evaluation on synthetic and real world data demonstrates the effectiveness and efficiency of our approach.
convex non-negative matrix factorization in the wild. non-negative matrix factorization (nmf) has recently received a lot of attention in data mining, information retrieval, and computer vision. it factorizes a non-negative input matrix v into two non-negative matrix factors v = wh such that w describes "clusters" of the datasets. analyzing genotypes, social networks, or images, it can be beneficial to ensure v to contain meaningful ``cluster centroids'', i.e., to restrict w to be convex combinations of data points. but how can we run this convex nmf in the wild, i.e., given millions of data points? triggered by the simple observation that each data point is a convex combination of vertices of the data convex hull, we propose to restrict w further to be vertices of the convex hull. the benefits of this convex-hull nmf approach are twofold. first, the expected size of the convex hull of the candidate set typically grows much slower than the data set. second, distance preserving low-dimensional embeddings allow one to compute candidate vertices efficiently. our extensive experimental evaluation shows that convex-hull nmf compares favorably to convex nmf for large data sets both in terms of speed and reconstruction quality. moreover, we show that our method can easily be applied to large-scale, real-world data sets, in our case consisting of 1.6 million images respectively 160 million votes on world of warcraft guilds.
a walk from 2-norm svm to 1-norm svm. this paper studies how useful the standard 2-norm regularized svm is in approximating the 1-norm svm problem. to this end, we examine a general method that is based on iteratively re-weighting the features and solving a 2-norm optimization problem. the convergence rate of this method is unknown. previous work indicates that it might require an excessive number of iterations. we study how well we can do with just a small number of iterations. in theory the convergence rate is fast, except for coordinates of the current solution that are close to zero. our empirical experiments confirm this. in many problems with irrelevant features, already one iteration is often enough to produce accuracy as good as or better than that of the 1-norm svm. hence, it seems that in these problems we do not need to converge to the 1-norm svm solution near zero values. the benefit of this approach is that we can build something similar to the 1-norm regularized solver based on any 2-norm regularized solver. this is quick to implement and the solution inherits the good qualities of the solver such as scalability and stability.
flownet: flow-based approach for efficient analysis of complex biological networks. biological networks having complex connectivity have been widely studied recently. by characterizing their inherent and structural behaviors in a topological perspective, these studies have attempted to discover hidden knowledge in the systems. however, even though various algorithms with graph-theoretical modeling have provided fundamentals in the network analysis, the availability of practical approaches to efficiently handle the complexity has been limited. in this paper, we present a novel flow-based approach, called flownet, to efficiently analyze large-sized, complex networks. our approach is based on the functional influence model that quantifies the influence of a biological component on another. we introduce a dynamic flow simulation algorithm to generate a flow pattern which is a unique characteristic for each component. the set of patterns can be used in identifying functional modules (i.e., clustering). the proposed flow simulation algorithm runs very efficiently in sparse networks. since our approach uses a weighted network as an input, we also discuss supervised and unsupervised weighting schemes for unweighted biological networks. as experimental results in real applications to the yeast protein interaction network, we demonstrate that our approach outperforms previous graph clustering methods with respect to accuracy.
discriminative mixed-membership models. although mixed-membership models have achieved great success in unsupervised learning, they have not been widely applied to classification problems. in this paper, we propose a family of discriminative mixed-membership models for classification by combining unsupervised mixed-membership models with multi-class logistic regression. in particular, we propose two variants respectively applicable to text classification based on latent dirichlet allocation and usual feature vector classification based on mixed-membership naive bayes models. the proposed models allow the number of components in the mixed membership to be different from the number of classes. we propose two variational inference based algorithms for learning the models, including a fast variational inference which is substantially more efficient than mean-field variational approximation. through extensive experiments on uci and text classification benchmark datasets, we show that the models are competitive with the state of the art, and can discover components not explicitly captured by the class labels.
bayesian overlapping subspace clustering. given a data matrix, the problem of finding dense/uniform sub-blocks in the matrix is becoming important in several applications. the problem is inherently combinatorial since the uniform sub-blocks may involve arbitrary subsets of rows and columns and may even be overlapping. while there are a few existing methods based on co-clustering or subspace clustering, they typically rely on local search heuristics and in general do not have a systematic model for such data. we present a bayesian overlapping subspace clustering (bosc) model which is a hierarchical generative model for matrices with potentially overlapping uniform sub-block structures. the bosc model can also handle matrices with missing entries. we propose an em-style algorithm based on approximate inference using gibbs sampling and parameter estimation using coordinate descent for the bosc model. through experiments on both simulated and real datasets, we demonstrate that the proposed algorithm outperforms the state-of-the-art.
slider: mining correlated motifs in protein-protein interaction networks. correlated motif mining (cmm) is the problem to find overrepresented pairs of patterns, called motif pairs, in interacting protein sequences. algorithmic solutions for cmm thereby provide a computational method for predicting binding sites for protein interaction. in this paper, we adopt a motif-driven approach where the support of candidate motif pairs is evaluated in the network. we experimentally establish the superiority of the chi-square-based support measure over other support measures. furthermore, we obtain that cmm is an np-hard problem for a large class of support measures (including chi-square) and reformulate the search for correlated motifs as a combinatorial optimization problem. we then present the method slider which uses local search with a neighborhood function based on sliding motifs and employs the chi-square-based support measure. we show that slider outperforms existing motif-driven cmm methods and scales to large protein-protein interaction networks.
ring: an integrated method for frequent representative subgraph mining. we propose a novel representative based subgraph mining model. a series of standards and methods are proposed to select invariants. patterns are mapped into invariant vectors in a multidimensional space. to find qualified patterns, only a subset of frequent patterns is generated as representatives, such that every frequent pattern is close to one of the representative patterns while representative patterns are distant from each other. we devise the ring algorithm, integrating the representative selection into the pattern mining process. meanwhile, we use r-trees to assist this mining process. last but not least, a large number of real and synthetic datasets are employed for the empirical study, which show the benefits of the representative model and the efficiency of the ring algorithm.
extended boolean matrix decomposition. with the vast increase in collection and storage of data, the problem of data summarization is most critical for effective data management. since much of this data is categorical in nature, it can be viewed in terms of a boolean matrix. boolean matrix decomposition (bmd) has been used to provide concise and interpretable representations of boolean data sets. a boolean matrix can be expressed as a product of two boolean matrices, where the first matrix represents a set of meaningful concepts, and the second describes how the observed data can be expressed as combinations of those concepts. typically, the combination is only in terms of the set union. in other words, a successful boolean matrix decomposition gives a set of concepts and shows how every column of the input data can be expressed as a union of some subset of those concepts. however, this way of modeling only incompletely represents real data semantics. essentially, it ignores a critical component -- the set difference operation: a column can be expressed as the combination of union of certain concepts as well as the exclusion of other concepts. this has two significant benefits. first, the total number of concepts required to describe the data may itself be reduced. second, a more succinct summarization may be found for every column. in this paper, we propose the extended boolean matrix decomposition (ebmd) problem, which aims to factor boolean matrices using both the set union and set difference operations. we study several variants of the problem, show that they are np-hard, and propose efficient heuristics to solve them. extensive experimental results demonstrate the power of ebmd.
stacked gaussian process learning. triggered by a market relevant application that involves making joint predictions of pedestrian and public transit flows in urban areas, we address the question of how to utilize hidden common cause relations among variables of interest in order to improve performance in the two related regression tasks. specifically, we propose stacked gaussian process learning, a meta-learning scheme in which a base gaussian process is enhanced by adding the posterior covariance functions of other related tasks to its covariance function in a stage-wise optimization. the idea is that the stacked posterior covariances encode the hidden common causes among variables of interest that are shared across the related regression tasks. stacked gaussian process learning is efficient, capable of capturing shared common causes, and can be implemented with any kind of standard gaussian process regression model such as sparse approximations and relational variants. our experimental results on real-world data from the market relevant application show that stacked gaussian processes learning can significantly improve prediction performance of a standard gaussian process.
permutation tests for studying classifier performance. we explore the framework of permutation-based p-values for assessing the behavior of the classification error. in this paper we study two simple permutation tests. the first test estimates the null distribution by permuting the labels in the data; this has been used extensively in classification problems in computational biology. the second test produces permutations of the features within classes, inspired by restricted randomization techniques traditionally used in statistics. we study the properties of these tests and present an extensive empirical evaluation on real and synthetic data. our analysis shows that studying the classification error via permutation tests is effective; in particular, the restricted permutation test clearly reveals whether the classifier exploits the interdependency between the features in the data.
on k-means cluster preservation using quantization schemes. this work examines under what conditions compression methodologies can retain the outcome of clustering operations. we focus on the popular k-means clustering algorithm and we demonstrate how a properly constructed compression scheme based on post-clustering quantization is capable of maintaining the global cluster structure. our analytical derivations indicate that a 1-bit moment preserving quantizer per cluster is sufficient to retain the original data clusters. merits of the proposed compression technique include: a) reduced storage requirements with clustering guarantees, b) data privacy on the original values, and c) shape preservation for data visualization purposes. we evaluate quantization scheme on various high-dimensional datasets, including 1-dimensional and 2-dimensional time-series (shape datasets) and demonstrate the cluster preservation property. we also compare with previously proposed simplification techniques in the time-series area and show significant improvements both on the clustering and shape preservation of the compressed datasets.
redistricting using heuristic-based polygonal clustering. redistricting is the process of dividing a geographic area into districts or zones. this process has been considered in the past as a problem that is computationally too complex for an automated system to be developed that can produce unbiased plans. in this paper we present a novel method for redistricting a geographic area using a heuristic-based approach for polygonal spatial clustering. while clustering geospatial polygons several complex issues need to be addressed – such as: removing order dependency, clustering all polygons assuming no outliers, and strategically utilizing domain knowledge to guide the clustering process. in order to address these special needs, we have developed the constrained polygonal spatial clustering (cpsc) algorithm that holistically integrates do-main knowledge in the form of cluster-level and instance-level constraints and uses heuristic functions to grow clusters. in order to illustrate the usefulness of our algorithm we have applied it to the problem of formation of unbiased congressional districts. furthermore, we compare and contrast our algorithm with two other approaches proposed in the literature for redistricting, namely – graph partitioning and simulated annealing.
non-sparse multiple kernel learning for fisher discriminant analysis. we consider the problem of learning a linear combination of pre-specified kernel matrices in the fisher discriminant analysis setting. existing methods for such a task impose an $\ell_1$ norm regularisation on the kernel weights, which produces sparse solution but may lead to loss of information. in this paper, we propose to use $\ell_2$ norm regularisation instead. the resulting learning problem is formulated as a semi-infinite program and can be solved efficiently. through experiments on both synthetic data and a very challenging object recognition benchmark, the relative advantages of the proposed method and its $\ell_1$ counterpart are demonstrated, and insights are gained as to how the choice of regularisation norm should be made.
learning the shared subspace for multi-task clustering and transductive transfer classification. there are many clustering tasks which are closely related in the real world, e.g. clustering the web pages of different universities. however, existing clustering approaches neglect the underlying relation and treat these clustering tasks either individually or simply together. in this paper, we will study a novel clustering paradigm, namely multi-task clustering, which performs multiple related clustering tasks together and utilizes the relation of these tasks to enhance the clustering performance. we aim to learn a subspace shared by all the tasks, through which the knowledge of the tasks can be transferred to each other. the objective of our approach consists of two parts: (1) within-task clustering: clustering the data of each task in its input space individually; and (2) cross-task clustering: simultaneous learning the shared subspace and clustering the data of all the tasks together. we will show that it can be solved by alternating minimization, and its convergence is theoretically guaranteed. furthermore, we will show that given the labels of one task, our multi-task clustering method can be extended to transductive transfer classification (a.k.a. cross-domain classification, domain adaption). experiments on several cross-domain text data sets demonstrate that the proposed multi-task clustering outperforms traditional single-task clustering methods greatly. and the transductive transfer classification method is comparable to or even better than several existing transductive transfer classification approaches.
large scale relation acquisition using class dependent patterns. this paper proposes a minimally supervised method for acquiring high-level semantic relations such as causality and prevention from the web. our method learns linguistic patterns that express causality such as “x gave rise to y”, and uses them to extract causal noun pairs like (global warming, malaria epidemic) from sentences like “global warming gave rise to a new malaria epidemic”. the novelty of our method lies in the use of semantic word classes acquired by large scale clustering for learning class dependent patterns. we demonstrate the effectiveness of this class based approach on three large-scale relation mining tasks from 50 million japanese web pages. in two of these tasks we obtained more than 30,000 relation instances with over 80% precision, outperforming a state-of-the-art system by a large margin.
global slope change synopses for measurement maps. quality control using scalar quality measures is standard practice in manufacturing. however, there are also quality measures that are determined at a large number of positions on a product, since the spatial distribution is important. we denote such a mapping of local coordinates on the product to values of a measure as a measurement map. in this paper, we examine how measurement maps can be clustered according to a novel notion of similarity—mapscape similarity—that considers the overall course of the measure on the map. we present a class of synopses called global slope change that uses the profile of the measure along several lines from a reference point to different points on the borders to represent a measurement map. we conduct an evaluation of global slope change using a real-world data set from manufacturing and demonstrate its superiority over other synopses.
maximum margin clustering on data manifolds. clustering is one of the most fundamental and important problems in computer vision and pattern recognition communities. maximum margin clustering(mmc) is a recently proposed clustering technique which has shown promising experimental results. the main theme behind mmc is to extend the standard maximum margin principle in support vector machine (svm) to the unsupervised scenario. this paper will consider the problem of maximum margin clustering on data manifolds. specifically, we propose an approach called manifold regularized maximum margin clustering (mrmmc) which combines both the maximum margin data discrimination and data manifold information in a unified clustering objective and propose an efficient algorithm to solve it. finally the experimental results on several real world data sets are presented to show the effectiveness of our method.
clustering with multiple graphs. in graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. in many real-world applications, however, entities are often associated with relations of different types and/or from different sources, which can be well captured by multiple undirected graphs over the same set of vertices. how to exploit such multiple sources of information to make better inferences on entities remains an interesting open problem. in this paper, we focus on the problem of clustering the vertices based on multiple graphs in both unsupervised and semi-supervised settings. as one of our contributions, we propose linked matrix factorization (lmf) as a novel way of fusing information from multiple graph sources. in lmf, each graph is approximated by matrix factorization with a graph-specific factor and a factor common to all graphs, where the common factor provides features for all vertices. experiments on siam journal data show that (1) we can improve the clustering accuracy through fusing multiple sources of information with several models, and (2) lmf yields superior or competitive results compared to other graph-based clustering methods.
fast online training of ramp loss support vector machines. a fast online algorithm onlinesvmr for training ramp-loss support vector machines (svmrs) is proposed. it finds the optimal svmr for t+1 training examples using svmr built on t previous examples. the algorithm retains the karush–kuhn–tucker conditions on all previously observed examples. this is achieved by an smo-style incremental learning and decremental unlearning under the concave-convex procedure framework. further speedup of training time could be achieved by dropping the requirement of optimality. a variant, called onlineasvmr, is a greedy approach that approximately optimizes the svmr objective function and is suitable for online active learning. the proposed algorithms were comprehensively evaluated on 9 large benchmark data sets. the results demonstrate that onlinesvmr (1) has the similar computational cost as its offline counterpart; (2) outperforms idsvm, its competing online algorithm that uses hinge-loss, in terms of accuracy, model sparsity and training time. the experiments on online active learning show that for a fixed number of label queries onlineasvmr (1) achieves consistently better accuracy than queryall and competitive accuracy to greedy approach; (2) outperforms the active learning version of idsvm.
finding time series motifs in disk-resident data. time series motifs are sets of very similar subsequences of a long time series. they are of interest in their own right, and are also used as inputs in several higher-level data mining algorithms including classification, clustering, rule-discovery and summarization. in spite of extensive research in recent years, finding exact time series motifs in massive databases is an open problem. previous efforts either found approximate motifs or considered relatively small datasets residing in main memory. in this work, we describe for the first time a disk-aware algorithm to find exact time series motifs in multi-gigabyte databases which contain on the order of tens of millions of time series. we have evaluated our algorithm on datasets from diverse areas including medicine, anthropology, computer networking and image processing and show that we can find interesting and meaningful motifs in datasets that are many orders of magnitude larger than anything considered before.
a fully automated method for discovering community structures in high dimensional data. identifying modules, or natural communities, in large complex networks is fundamental in many fields, including social sciences, biological sciences and engineering. recently several methods have been developed to automatically identify communities from complex networks by optimizing the modularity function. the advantage of this type of approaches is that the algorithm does not require any parameter to be tuned. however, the modularity-based methods for community discovery assume that the network structure is given explicitly and is correct. in addition, these methods work best if the network is unweighted and/or sparse. in reality, networks are often not directly defined, or may be given as an affinity matrix. in the first case, each node of the network is defined as a point in a high dimensional space and different networks can be obtained with different network construction methods, resulting in different community structures. in the second case, an affinity matrix may define a dense weighted graph, for which modularity-based methods do not perform well. in this work, we propose a very simple algorithm to automatically identify community structures from these two types of data. our approach utilizes a k-nearest-neighbor network construction method to capture the topology embedded in high dimensional data, and applies a modularity-based algorithm to identify the optimal community structure. a key to our approach is that the network construction is incorporated with the community identification process and is totally parameter-free. furthermore, our method can suggest appropriate pre-processing / normalization of the data to improve the results of community identification. we tested our methods on several synthetic and real data sets, and evaluated its performance by internal or external accuracy indices. compared with several existing approaches, our method is not only fully automatic, but also has the best accuracy overall.
a contrast pattern based clustering quality index for categorical data. since clustering is unsupervised and highly explorative, clustering validation (i.e. assessing the quality of clustering solutions) has been an important and long standing research problem. existing validity measures have significant shortcomings. this paper proposes a novel contrast pattern based clustering quality index (cpcq) for categorical data, by utilizing the quality and diversity of the contrast patterns (cps) which contrast the clusters in clusterings. high quality cps can characterize clusters and discriminate them against each other. experiments show that the cpcq index (1) can recognize that expert-determined classes are the best clusters for many datasets from the uci repository; (2) does not give inappropriate preference to larger number of clusters; (3) does not require a user to provide a distance function.
discovering contexts and contextual outliers using random walks in graphs. the identifying of contextual outliers allows the discovery of anomalous behavior that other forms of outlier detection cannot find. what may appear to be normal behavior with respect to the entire data set can be shown to be anomalous by subsetting the data according to specific spatial or temporal context. however, in many real-world applications, we may not have sufficient a priori contextual information to discover these contextual outliers. this paper addresses the problem by proposing a probabilistic approach based on random walks, which can simultaneously explore meaningful contexts and score contextual outliers therein. our approach has several advantages including producing outlier scores which can be interpreted as stationary expectations and their calculation in closed form in polynomial time. in addition, we show that point outlier detection using the stationary distribution is a special case of our approach. it allows us to find both global and contextual outliers simultaneously and to create a meaningful ranked list consisting of both types of outliers. this is a major departure from existing work where an algorithm typically identifies one type of outlier. the effectiveness of our method is justified by empirical results on real data sets, with comparison to related work.
extracting output metadata from scientific deep web data sources. increasingly, many data sources appear as online databases, hidden behind query forms, thus forming the deep web. the popularity of this new medium for data dissemination is leading to new problems in data integration. particularly, to enable data integration from multiple deep web data sources, one needs to obtain the metadata for each of the data sources. obtaining the metadata, particularly, the output schema, can be very challenging. this is because, given an input query, many deep web data sources only return a subset of the output schema attributes, i.e, the ones that have a non-null value for the corresponding input. in this paper, we propose two approaches, which are the sampling model approach and the mixture model approach, respectively, to efficiently obtain an approximately complete set of output schema attributes from a deep web data source. our experiments show while each of the above two approaches has limitations, a hybrid strategy, where we combine the two approaches, achieves high recall with good precision for most data sources.
connecting sparsely distributed similar bloggers. the nature of the blogosphere determines that the majority of bloggers are only connected with a small number of fellow bloggers, and similar bloggers can be largely disconnected from each other. aggregating them allows for cost-effective personalized services, targeted marketing, and exploration of new business opportunities. as most bloggers have only a small number of adjacent bloggers, the problem of aggregating similar bloggers presents challenges that demand novel algorithms of connecting the non-adjacent due to the fragmented distributions of bloggers. in this work, we define the problem, delineate its challenges, and present an approach that uses innovative ways to employ contextual information and collective wisdom to aggregate similar bloggers. a real-world blog directory is used for experiments. we demonstrate the efficacy of our approach, report findings, and discuss related issues and future work.
semi-supervised density-based clustering. most of the effort in the semi-supervised clustering literature was devoted to variations of the k-means algorithm. in this paper we show how background knowledge can be used to bias a partitional density-based clustering algorithm. our work describes how labeled objects can be used to help the algorithm detecting suitable density parameters for the algorithm to extract density-based clusters in specific parts of the feature space. considering the set of constraints estabilished by the labeled dataset we show that our algorithm, called ssdbscan, automatically finds density parameters for each natural cluster in a dataset. four of the most interesting characteristics of ssdbscan are that (1) it only requires a single, robust input parameter, (2) it does not need any user intervention, (3) it automaticaly finds the noise objects according to the density of the natural clusters and (4) it is able to find the natural cluster structure even when the density among clusters vary widely. the algorithm presented in this paper is evaluated with artificial and real-world datasets, demonstrating better results when compared to other unsupervised and semi-supervised density-based approaches.
a new mca-based divisive hierarchical algorithm for clustering categorical data. clustering categorical data faces two challenges, one is lacking of inherent similarity measure, and the other is that the clusters are prone to being embedded in different subspace. in this paper, we propose the first divisive hierarchical clustering algorithm for categorical data. the algorithm, which is based on multiple correspondence analysis (mca), is systematic, efficient and effective. in our algorithm, mca plays an important role in analyzing the data globally. the proposed algorithm has five merits. first, our algorithm yields a dendrogram representing nested groupings of patterns and similarity levels at different granularities. second, it is parameter-free, fully automatic and, most importantly, requires no assumption regarding the number of clusters. third, it is independent of the order in which the data are processed. forth, it is scalable to large data sets; and finally, using the novel data representation and chi-square distance measures makes our algorithm capable of seamlessly discovering the clusters embedded in the subspaces. experiments on both synthetic and real data demonstrate the superior performance of our algorithm.
semi-supervised multi-task learning with task regularizations. multi-task learning refers to the learning problem of performing inference by jointly considering multiple related tasks. there have already been many research efforts on supervised multi-task learning. however, collecting sufficient labeled data for each task is usually time consuming and expensive. in this paper, we consider the semi-supervised multitask learning (ssmtl) problem, where we are given a small portion of labeled points together with a large pool of unlabeled data within each task. we assume that the different tasks can form some task clusters and the task in the same cluster share similar classifier parameters. the final learning problem is relaxed to a convex one and an efficient gradient descent strategy is proposed. finally the experimental results on both synthetic and real world data sets are presented to show the effectiveness of our method.
efficient discovery of frequent correlated subgraph pairs. the recent proliferation of graph data in a wide spectrum of applications has led to an increasing demand for advanced data analysis techniques. in view of this, many graph mining techniques, such as frequent subgraph mining and correlated subgraph mining, have been proposed. in many applications, both frequency and correlation play an important role. thus, this paper studies a new problem of mining the set of frequent correlated subgraph pairs. a simple algorithm that combines existing algorithms for mining frequent subgraphs and correlated subgraphs results in a multiplication of the mining operations, the majority of which are redundant. we discover that most of the graphs correlated to a common graph are also highly correlated. we establish theoretical foundations for this finding and derive a tight lower bound on the correlation of any two graphs that are correlated to a common graph. this theoretical result leads to the design of a very effective skipping mechanism, by which we skip the processing of a majority of graphs in the mining process. our algorithm, fcp-miner, is a fast approximate algorithm, but we show that the missing pairs are only a small set of marginally correlated pairs. extensive experiments verify both the efficiency and effectiveness of fcp-miner.
temporal neighborhood discovery using markov models. temporal data, which is a sequence of data tuples measured at successive time instances, is typically very large. hence instead of mining the entire data, we are interested in dividing the huge data into several smaller intervals of interest which we call temporal neighborhoods. in this paper we propose an approach to generate temporal neighborhoods through unequal depth discretization. we describe two novel algorithms (a) similarity based merging (smerg) and, (b) stationary distribution based merging (stmerg). these algorithms are based on the robust framework of markov models and the markov stationary distribution respectively. we identify temporal neighborhoods with distinct demarcations based on unequal depth discretization of the data. we discuss detailed experimental results in both synthetic and real world data. specifically we show (i) the efficacy of our approach through precision and recall of labeled bins, (ii) the ground truth validation in real world datasets and, (iii) knowledge discovery in the temporal neighborhoods such as global anomalies. our results indicate that we are able to identify valuable knowledge based on our ground truth validation from real world traffic data.
bi-relational network analysis using a fast random walk with restart. identification of nodes relevant to a given node in a relational network is a basic problem in network analysis with great practical importance. most existing network analysis algorithms utilize one single relation to define relevancy among nodes. however, in real world applications multiple relationships exist between nodes in a network. therefore, network analysis algorithms that can make use of more than one relation to identify the relevance set for a node are needed. in this paper, we show how the random walk with restart (rwr) approach can be used to study relevancy in a bi-relational network from the bibliographic domain, and show that making use of two relations results in better results as compared to approaches that use a single relation. as relational networks can be very large, we also propose a fast implementation for rwr by adapting an existing iterative aggregation and disaggregation (iad) approach. the iad-based rwr exploits the block-wise structure of real world networks. experimental results show significant increase in running time for the iad-based rwr compared to the traditional power method based rwr.
pub: a class description technique based on partial coverage of subspace. a good description of a class should be accurate and interpretable. previous works describe classes either by analyzing the correlation of each attribute with the class, or by producing rules as in building a classifier. these solutions suffer from issues in accuracy and interpretability. a description naturally consists of sentences, where each sentence consists of a set of terms. normally, a sentence is defined as a disjunction or conjunction of several terms, each of which specifies a constraint (range/set of values) on an attribute. from the data analysis point of view, a sentence specifies a subspace in the database. in this paper, we create a richer yet interpretable form of a sentence, i.e., a sentence describes an object if any $k$ attributes of that object satisfy the specified constraints. to that end, we design \textsc{pub}, an algorithm that produces descriptions with our form of sentences. while constructing a sentence (within the description), \textsc{pub} finds the optimal range/set of values for each attribute in linear time. we also empirically show that \textsc{pub} is efficient, and able to produce more accurate, concise and interpretable descriptions than current approaches on various real datasets.
non-negative laplacian embedding. laplacian embedding provides a low dimensional representation for a matrix of pairwise similarity data using the eigenvectors of the laplacian matrix. the true power of laplacian embedding is that it provides an approximation of the ratio cut clustering. however, ratio cut clustering requires the solution to be {\it nonnegative}. in this paper, we propose a new approach, nonnegative laplacian embedding, which approximates ratio cut clustering in a more direct way than traditional approaches. from the solution of our approach, clustering structures can be read off directly. we also propose an efficient algorithm to optimize the objective function utilized in our approach. empirical studies on many real world datasets show that our approach leads to more accurate ratio cut solution and improves clustering accuracy at the same time.
synthesizing novel dimension reduction algorithms in matrix trace oriented optimization framework. dimension reduction (dr) algorithms are generally categorized into feature extraction and feature selection algorithms. in the past, few works have been done to contrast and unify the two algorithm categories. in this work, we introduce a matrix trace oriented optimization framework to provide a unifying view for both feature extraction and selection algorithms. we show that the unified view of dr algorithms allows us to discover some essential relationships among many state-of- the-art dr algorithms. inspired by these essential insights, we propose to synthesize unlimited number of novel dr algorithms by combining, mapping and integrating the state- of-the-art algorithms. we present examples of newly synthesized dr algorithms with experimental results to show the effectiveness of our automatically synthesized algorithms.
kernel conditional quantile estimation via reduction revisited. quantile regression refers to the process of estimating the quantiles of a conditional distribution and has many important applications within econometrics and data mining, among other domains. in this paper, we show how to estimate these conditional quantile functions within a bayes risk minimization framework using a gaussian process prior. the resulting non-parametric probabilistic model is easy to implement and allows non-crossing quantile functions to be enforced. moreover, it can directly be used in combination with tools and extensions of standard gaussian processes such as principled hyperparameter estimation, sparsification, and quantile regression with input-dependent noise rates. no existing approach enjoys all of these desirable properties. experiments on benchmark datasets show that our method is competitive with state-of-the-art approaches."
automatic formation deployment of decentralized heterogeneous multi-robot networks with limited sensing capabilities. heterogeneous multi-robot networks require novel tools for applications that require achieving and maintaining formations. this is the case for distributing sensing devices with heterogeneous mobile sensor networks. here, we consider a heterogeneous multi-robot network of mobile robots. the robots have a limited range in which they can estimate the relative position of other network members. the network is also heterogeneous in that only a subset of robots have localization ability. we develop a method for automatically configuring the heterogeneous network to deploy a desired formation at a desired location. this method guarantees that network members without localization are deployed to the correct location in the environment for the sensor placement.
tracked vehicle with circular cross-section to realize sideways motion. in this video, a novel tracked mechanism for sideways motion is presented. the tracked mechanism is of circular cross-section and has active rolling axes at the center of the circles. conventional tracked mechanisms can support massive loads, but cannot produce sideways motion. additionally, previous crawler edges sink undesirably on soft ground, particularly when the vehicle body is subject to a sideways tilt. the proposed design solves these drawbacks by adopting a circular cross-section crawler. a prototype has been developed to illustrate the concept. motion experiments confirm the novel properties of this mechanism: sideways motion and robustness against edge-sink. motion experiments, with a test vehicle are also presented.
rollin' justin - mobile platform with variable base. research on humanoid robots for use in servicing tasks, e.g. fetching and delivery, attracts steadily more interest. with "rollin' justin" a mobile robotic system and research platform is presented that allows sophisticated control algorithms and dexterous manipulation. this video gives an overview of the mobile humanoid robotic system "rollin' justin" with special emphasis on mechanical design features, control issues and high-level system capabilities such as human robot interaction.
three dimensional hybrid microassembly combining robotic microhandling and self-assembly. hybrid microassembly combining robotic microhandling and self-assembly aims at having the best of the both: good efficiency, reliability, accuracy and capability in creating complex structures. in this paper, a microassembly technique combining robotic tweezer-type microgripper and droplet self-alignment is discussed. the assembly method is evaluated by applying it in different 3d assembly cases, which would pose problems to a solution based on robotics or self-assembly alone. in the first, part rotation is realized by capillary forces. in the second, hierarchical structures are realized. finally, cantilever structures are created using the method.
development of leg-robot for simulation of spastic movement with compact mr fluid clutch. in this study, we propose a leg-robot with a compact mr fluid clutch (cmrfc) to realize haptic control of abnormal spastic movements of brain-injured patients. this system can be used in the practical training for trainees of physical therapy. additionally, we will study to figure out the physiological mechanism of spastic movements of human with the process to simulate patient-like spastic motion by this robot. in this paper, basic structure and mechanism of the leg-robot with cmrfc are explained. finally, experimental results of some kinds of haptic control for spastic movements are described.
a flexible robot skin for safe physical human robot interaction. providing contact sensing on the whole body of a robot is a key feature to increase the safety level of physical human-robot interaction. in this paper, a new robot skin capable of sensing multiple contact locations is presented. the motivation behind the proposed design is to produce a relatively inexpensive skin having the capability to provide the spatial location of collisions and also to add compliance to the robot's external cover. the resulting device is a thin flexible sensor sheet made of polyimide films with electrically conductive ink and a pressure sensitive conductive rubber sheet. the problem of internal wire routing is circumvented by the use of conductive ink and a circuit is proposed to minimize the number of output wires. to provide collision absorption and mechanical robustness, the sensor is embedded in different layers of polyurethane using shape deposition manufacturing (sdm). the paper presents the design and the fabrication process of the skin but also some experimental results on the determination of the mechanical properties of the resulting sensor as well as its potential for increasing human safety during human robot interaction.
bouncing an unconstrained ball in three dimensions with a blind juggling robot. we describe the design of a juggling robot that is able to vertically bounce a completely unconstrained ball without any sensing. the robot consists of a linear motor actuating a machined aluminum paddle. the curvature of this paddle keeps the ball from falling off while the apex height of the ball is stabilized by decelerating the paddle at impact. we analyze the mapping of perturbations of the nominal trajectory over a single bounce to determine the design parameters that stabilize the system. the first robot prototype confirms the results from the stability analysis and exhibits substantial robustness to perturbations in the horizontal degree of freedoms. we then measure the performance of the robot and characterize the noise introduced into the system as white noise. this allows us to refine the design parameters by minimizing the h2 norm of an input-output representation of the system. finally, we design an h2 optimal controller for the apex height using impact time measurements as feedback and show that the closed-loop performance is only marginally better than what is achieved with open-loop control.
a novel method for learning policies from constrained motion. many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. constraints are usually unobservable and frequently change between contexts. in this paper, we present a novel approach for learning (unconstrained) control policies from movement data, where observations come from movements under different constraints. as a key ingredient, we introduce a small but highly effective modification to the standard risk functional, allowing us to make a meaningful comparison between the estimated policy and constrained observations. we demonstrate our approach on systems of varying complexity, including kinematic data from the asimo humanoid robot with 27 degrees of freedom.
a real-time helicopter testbed for insect-inspired visual flight control. the paper describes an indoor helicopter testbed that allows implementing and testing of bio-inspired control algorithms developed from scientific studies on insects. the helicopter receives and is controlled by simulated sensory inputs (e.g. visual stimuli) generated in a virtual 3d environment, where the connection between the physical world and the virtual world is provided by a video camera tracking system. the virtual environment is specified by a 3d computer model and is relatively simple to modify compared to realistic scenes. this enables rapid examinations of whether a certain control law is robust under various environments, an important feature of insect behavior. as a first attempt, flight stabilization and yaw rate control near hover are demonstrated, utilizing biologically realistic visual stimuli as in the fruit fly drosophila melanogaster.
behavioral control for multi-robot perimeter patrol: a finite state automata approach. this paper proposes a multiple robot control algorithm to approach the problem of patrolling an open or closed line. the algorithm is fully decentralized, i.e., no communication occurs between robots or with a central station. robots behave according only to their sensing and computing capabilities to ensure high scalability and robustness towards robots' fault. the patrolling algorithm is designed in the framework of behavioral control and it is based on the concept of action: an higher level of abstraction with respect to the behaviors. each action is obtained by combining more elementary behaviors in the null-space-behavioral framework. a finite-state-automata is designed as supervisor in charge of selecting the appropriate action. the approach has been validated in simulation as well as experimentally with a patrol of 3 pioneer robots available at the distributed intelligence laboratory of the university of tennessee.
development of underwater robots using piezoelectric fiber composite. underwater robot using piezoelectric fiber composite with the merits of being soft and capable of large displacement, is proposed in this paper. by pasting the thin and flexible composite on to a structure, meandering motion observed in underwater creatures such as fish can be realized by generating propagation wave for propulsive force. hence, a compact, effective and powerful robot capable of underwater movement can be realized. this paper describes the mechanism design and control method of the robot using piezoelectric fiber composite based on the principle of underwater creatures and shows the feasibility of the proposal by the experimental results of two developed prototypes.
on-line time-optimal path tracking for robots. this paper focuses on time-optimal path tracking, which involves planning of robot motions along prescribed geometric paths. starting from a discretized convex reformulation of time-optimal path tracking problems, a log-barrier based batch solution method is presented which allows to rapidly obtain an approximate solution with smooth actuator torques. based on this batch method, a recursive variant is derived for on-line path tracking. by means of an experimental test case in which the path data is generated on-line by human demonstration, the results and trade-offs in calculation time, delay and path duration are compared for the batch and recursive variant of the log-barrier method as well as for an exact solution method.
chomp: gradient optimization techniques for efficient motion planning. existing high-dimensional motion planning algorithms are simultaneously overpowered and underpowered. in domains sparsely populated by obstacles, the heuristics used by sampling-based planners to navigate "narrow passages" can be needlessly complex; furthermore, additional post-processing is required to remove the jerky or extraneous motions from the paths that such planners generate. in this paper, we present chomp, a novel method for continuous path refinement that uses covariant gradient techniques to improve the quality of sampled trajectories. our optimization technique both optimizes higher-order dynamics and is able to converge over a wider range of input paths relative to previous path optimization strategies. in particular, we relax the collision-free feasibility prerequisite on input paths required by those strategies. as a result, chomp can be used as a standalone motion planner in many real-world planning queries. we demonstrate the effectiveness of our proposed method in manipulation planning for a 6-dof robotic arm as well as in trajectory generation for a walking quadruped robot.
multimodal telepresent control of dlr's rollin' justin. this video presents a telepresence system which enables a human operator to explore a remote environment by means of a multimodal man machine interface and rollin' justin as teleoperator. the man machine interface allows for bimanual, dexterous manipulation and, through two different operating modi of the man machine interface, wide area movement as well. a bimanual assembly task, consisting of grasping a connector, opening and closing it again, is shown in this video.
articulated object tracking by rendering consistent appearance parts. we describe a general methodology for tracking 3-dimensional objects in monocular and stereo video that makes use of gpu-accelerated filtering and rendering in combination with machine learning techniques. the method operates on targets consisting of kinematic chains with known geometry. the tracked target is divided into one or more areas of consistent appearance. the appearance of each area is represented by a classifier trained to assign a class-conditional probability to image feature vectors. a search is then performed on the configuration space of the target to find the maximum likelihood configuration. in the search, candidate hypotheses are evaluated by rendering a 3d model of the target object and measuring its consistency with the class probability map. the method is demonstrated for tool tracking on videos from two surgical domains, as well as in a human hand-tracking task.
leaving flatland: toward real-time 3d navigation. we report our first experiences with leaving flatland, an exploratory project that studies the key challenges of closing the loop between autonomous perception and action on challenging terrain. we propose a comprehensive system for localization, mapping, and planning for the rhex mobile robot in fully 3d indoor and outdoor environments. this system integrates visual odometry-based localization with new techniques in real-time 3d mapping from stereo data. the motion planner uses a new decomposition approach to adapt existing 2d planning techniques to operate in 3d terrain. we test the map-building and motion-planning subsystems on real and synthetic data, and show that they have favorable computational performance for use in high-speed autonomous navigation.
development of pressure-driven micro active catheter using membrane micro emboss following excimer laser ablation (meme-x) process. the world's smallest micro active catheter of φ∼300µm was successfully fabricated using membrane micro emboss following excimer laser ablation (meme-x) process. the catheter has a one-sided hollow bellows at the tip made of thin polymer membrane. the bellows is composed of a series of folded micro-chambers and microchannels connecting the micro-chambers. the folded-chambers expand on one side by increasing inner water pressure using a syringe, thus the whole bellows bends toward one direction within 0 to 180 degree. this micro active catheter should be useful for safe intravascular surgery in narrow and complicated blood vessels. moreover, the nonelectrical actuation mechanism of this catheter can be widely applied to micro-actuators and micro-robots which need high safety.
roombots-mechanical design of self-reconfiguring modular robots for adaptive furniture. we aim at merging technologies from information technology, roomware, and robotics in order to design adaptive and intelligent furniture. this paper presents design principles for our modular robots, called roombots, as future building blocks for furniture that moves and self-reconfigures. the reconfiguration is done using dynamic connection and disconnection of modules and rotations of the degrees of freedom. we are furthermore interested in applying roombots towards adaptive behaviour, such as online learning of locomotion patterns. to create coordinated and efficient gait patterns, we use a central pattern generator (cpg) approach, which can easily be optimized by any gradient-free optimization algorithm. to provide a hardware framework we present the mechanical design of the roombots modules and an active connection mechanism based on physical latches. further we discuss the application of our roombots modules as pieces of a homogenic or heterogenic mix of building blocks for static structures.
development of a robot balanced on a ball - application of passive motion to transport -. this paper proposes a robot balanced on a ball. in contrast to an inverted pendulum with two wheels, such as the segway human transporter, an inverted pendulum using a ball can traverse in any direction without changing its orientation, thereby enabling stable motion. such robots can be used in place of the two-wheeled robots. the robot proposed in this paper is equipped with three omnidirectional wheels with stepping motors that drive the ball and two sets of rate gyroscopes and accelerometers as attitude sensors. the robot has a simple design; it is controlled with a 16-bit microcontroller and runs on ni-mh batteries. it can not only stand still but also traverse on floor and pivot around its vertical axis. inverted pendulum control is applied in two axes for attitude control, and commanded motions are converted into velocity commands for the three wheels. the mechanism, control method, and experimental results including application to transport are described in this paper.
remote haptic feedback from a dynamic running machine. in this paper we present our efforts to design a system for feeding back useful haptic information from a highly dynamic running robot to a remote operator using a haptic device. without adding additional sensors, the legs of the robot are used as feelers to give the operator the capability to both explore and manipulate the robot's environment and to gather meaningful information about properties not captured by visual feedback like weight, movability and structure of an encountered object. we show the capabilities of the system in a user study with both trained and untrained operators.
the kinematic modeling and optimal paramerization of an omni-directional pipeline robot. there is no prior work on exact kinematic modeling for a pipeline robot having three powered chains. this work presents the closed-form kinematic model of the pipeline inspection robot driven by three caterpillar wheel chains. next, optimal kinematic parameters are analyzed by using isotropic index and force transmission ratio. lastly, the feasibility of the kinematic model is verified through motion simulation for a virtual pipeline equipped with elbows and t-branches.
noiseless and vibration-free ionic propulsion technology for indoor surveillance blimps. we present in this paper a novel indoor blimp that is propelled by a propulsion technology that uses no moving mechanical parts and thus is noiseless and vibration free. in our prior work reported at ieee/asme aim 2007, we demonstrated several prototype propulsive units (with asymmetric capacitor configurations) that lift themselves into air. using these basic propulsive units ("ionic flyers"), we have recently developed an indoor flying blimp that has a propulsion system with no moving mechanical parts and thus generates no noise or vibration -- the ionic propulsion blimp. the key to successfully create this novel indoor flying system is the development of a power generation system that includes an 11.1v battery which is capable of generating ∼20kv dc voltage continuously over time for a load in the mω range. the architecture of this ionic power system will be presented. a detailed parametric analysis and an optimal design methodology of the ionic flyer are also discussed. initial experimental results of the ionic propulsion blimp are also summarized in this paper.
6dof haptic cooperation over large latency network with wave variables for virtual prototyping. this paper describes a 6 dofs haptic cooperative platform dedicated to cad objects simulation and virtual prototyping tasks. this system is based on several distributed physical engines linked together by a network subject to time delay. to deal with the destabilizing effect of time delay, a wave variable transformation is used. the wave variable formalism is adapted to the platform, therefore the behavior of each physical engine is similar. several prototyping tasks have been tested on this system. a case is presented where two users are manipulating two distinct objects and interacting with each other.
automatic high-precision self-calibration of camera-robot systems. in this article a new method is presented to obtain a full and precise calibration of camera-robot systems with eyein-hand cameras. it achieves a simultaneous and numerically stable calibration of intrinsic and extrinsic camera parameters by analysing the image coordinates of a single point marker placed in the environment of the robot. the method works by first determining a rough initial estimate of the camera pose in the tool coordinate frame. this estimate is then used to generate a set of uniformly distributed calibration poses from which the object is visible. the measurements obtained in these poses are then used to obtain the exact parameters with cma-es (covariance matrix adaptation evolution strategy), a derandomised variant of an evolution strategy optimiser. minimal claims on the surrounding area and flexible handling of environmental and kinematical limitations make this method applicable to a range of robot setups and camera models. the algorithm runs autonomously without supervision and does not need manual adjustments. our problem formulation is directly in the 3d space which helps in minimising the resulting calibration errors in the robot's task space. both simulations and experimental results with a real robot show a very good convergence and high repeatability of calibration results without requiring user-supplied initial estimates of the calibration parameters.
eye-in-hand stereo visual servoing of an assistive robot arm in unstructured environments. we document the progress in the design and implementation of a motion control strategy that exploits visual feedback from a narrow baseline stereo head mounted in the hand of a wheelchair mounted robot arm (wmra) to recognize and grasp textured adl objects for which one or more templates exist in a large image database. the problem is made challenging by kinematic uncertainty in the robot, imperfect camera and stereo calibration, as well as the fact that we work in unstructured environments. the approach relies on separating the overall motion into gross and fine motion components. during the gross motion phase, local structure on an object around a user selected point of interest (poi) is extracted using sparse stereo information which is then utilized to converge on and roughly align the object with the image plane in order to be able to pursue object recognition and fine motion with strong likelihood of success. fine motion is utilized to grasp the target object by relying on feature correspondences between the live object view and its template image. while features are detected using a robust real-time keypoint tracker, a hybrid visual servoing technique is exploited in which tracked pixel space features are utilized to generate translational motion commands while a euclidean homography decomposition scheme is utilized for generation of orientation setpoints for the robot gripper. experimental results are presented to demonstrate the efficacy of the proposed algorithm.
dynamically diverse legged locomotion for rough terrain. in this video, we demonstrate the effectiveness of a kinodynamic planning strategy that allows a high-impedance quadruped to operate across a variety of rough terrain. at one extreme, the robot can achieve precise foothold selection on intermittent terrain. more surprisingly, the same inherently-stiff robot can also execute highly dynamic and underactuated motions with high repeatability. this range of dynamic motion is possible through careful reasoning about the coupled dynamics during underactuated phases of motion. our results demonstrate visceral progress toward realization of one of the central theoretically claims giving legged locomotion a "leg-up" over wheeled robotics: that appropriate design of control can produce a set of capabilities which span a dynamic range from deliberate foothold selection through acrobatic-style motion on a single, particular robot.
inertial aided sift for time to collision estimation. visual time to collision estimation for small or micro air vehicles is challenging due to aggressive 6-dof motion, real time performance requirements and significant size, weight and power constraints of the platform. recent work in collision detection using insect inspired optical flow based methods have been demonstrated in low power hardware implementations [1][2][3][4], but have not achieved the obstacle detection and false alarm rate performance necessary for practical deployment. this performance is sensitive to correspondence errors in the optical flow field, so one approach to improving performance is to use a richer feature set for correspondence, along with calibrated inertial information from the platform to aid correspondence. in this video, we show proof of concept results for such an approach. estimation results are noisy, but encouraging, and given that sift feature correspondence has been demonstrated in real time on low power gpus, it has the potential for future small uav integration.
fast point feature histograms (fpfh) for 3d registration. in our recent work [1], [2], we proposed point feature histograms (pfh) as robust multi-dimensional features which describe the local geometry around a point p for 3d point cloud datasets. in this paper, we modify their mathematical expressions and perform a rigorous analysis on their robustness and complexity for the problem of 3d registration for overlapping point cloud views. more concretely, we present several optimizations that reduce their computation times drastically by either caching previously computed values or by revising their theoretical formulations. the latter results in a new type of local features, called fast point feature histograms (fpfh), which retain most of the discriminative power of the pfh. moreover, we propose an algorithm for the online computation of fpfh features for realtime applications. to validate our results we demonstrate their efficiency for 3d registration and propose a new sample consensus based method for bringing two datasets into the convergence basin of a local non-linear optimizer: sac-ia (sample consensus initial alignment).
control of hopping speed and height over unknown rough terrain using a single actuator. we present a method for controlling the forward speed and the apex height of a one-legged hopping robot over rough terrain, using a single actuator located at the robot hip. the control algorithm is comprised of two elements, the forward speed control and the height control. the only input to the system is the torque applied by the hip actuator. the control is demonstrated to perform tracking of desired forward speed trajectories and desired apex height trajectories. simulation and experimental results on the sahr (single actuator hopping robot) experimental setup are presented and compared. it is shown that the robot follows both trajectories closely in simulation as well as in experiment. also the robot is tested successfully on a rough terrain course, which includes inclined ground and an abrupt drop in height of over 25% the length of the robot leg. the robot has no knowledge of its environment. further, the robot is made to run over the course a number of times, to demonstrate the control robustness.
gatmo: a generalized approach to tracking movable objects. we present gatmo (generalized approach to tracking movable objects), a system for localization and mapping that incorporates the dynamic nature of the environment while maintaining semantic labels. objects in the environment are broken down into multiple mobility levels, from static (walls) to highly mobile (people), by maintaining a history of object movement. object classification is accomplished through a multi-layer, multi-hypothesis approach that does not rely on any static features such as shape or size. maps are stored in an efficient manner that incorporates a history of previous orientations of each object. gatmo is initialized with a static map; it subsequently changes the map over time as objects in the map change position.
monocular stereo image processing using viewpoint switching iris. in the recent years, intensive studies have been carried out on the measurement of distance by using stereo camera systems. however, image systems with multiple image sensors are usually very complex and are inconvenient to use. in this paper, we present a new method that is based on the fact that the viewpoint depends on the position of aperture. we show images from different viewpoints can be obtained by using a monocular system. in the proposed method, stereo image analysis is carried out by using a viewpoint switching iris. a prototype of the viewpoint switching iris has be developed, which can be used along with a monocular camera for distance measurement. furthermore, we have verified that this system can be used to a moving object by using a compensation method.
voice coil based hopping mechanism for microrobot. hopping is a very efficient locomotion method for a robot in an unconstructed environment or a complicated terrain. small hopping robots have many interesting properties in comparison to the larger ones. however, relatively little research has been reported on hopping microrobot, while most of existing designs of hopping robots are not suitable to scale down. in this paper we propose a novel hopping mechanism that is based on the working principle of voice coil actuator. this mechanism is relatively easy to miniaturize and the hopping performance improves in a smaller scale. two prototypes are developed based on electromagnetic simulation and an analytic model of hopping process. the first prototype has a dimension of φ30 mm × 10 mm and a mass of 41.59 g, with a hopping height of about 45 mm. the second one has a dimension of φ14 mm × 6 mm and a mass of 4.94 g, and achieves a hopping height of about 65 mm.
real-world robot navigation amongst deformable obstacles. in this paper, we consider the problem of mobile robots navigating in environments with non-rigid objects. whereas robots can plan their paths more effectively when they utilize the information about the deformability of objects, they also need to consider the influence of the interaction with the deformable objects on their measurements during the execution of their navigation task. in this paper, we present a probabilistic approach to identify the measurements influenced by the deformable objects. based on a learned statistics about the influence of the deformable objects on the measurements, the robot is able to perform a sensor-based collision avoidance of unforeseen objects. we present experiments carried out with a real robot that illustrate the practicability of our approach.
ci-graph: an efficient approach for large scale slam. when solving the simultaneous localization and mapping (slam) problem, submapping and graphical methods have shown to be valuable approaches that provide significant advantages over the standard ekf solution: they are faster and can produce more consistent estimates when using local coordinates. in this paper we present ci-graph, a submapping method for slam that uses a graph structure to efficiently solve complex trajectories reducing the computational cost. unlike other submapping slam approaches, we are able to transmit and share information through maps in the graph in a consistent manner by using conditionally independent submaps. in addition, the current submap always summarizes, without further computations, all information available making ci-graph be an intrinsically "up to date" algorithm. moreover, the technique is also efficient in memory requirements since it does not need to recover the full covariance matrix. to evaluate ci-graph performance, the method has been tested using a synthetic manhattan world and victoria park data set.
combining search and action for mobile robots. we explore the interconnection between search and action in the context of mobile robotics. the task of searching for an object and then performing some action with that object is important in many applications. of particular interest to us is the idea of a robot assistant capable of performing worthwhile tasks around the home and office (e.g., fetching coffee, washing dirty dishes, etc.). we prove that some tasks allow for search and action to be completely decoupled and solved separately, while other tasks require the problems to be analyzed together. we complement our theoretical results with the design of a combined search/action approximation algorithm that draws on prior work in search. we show the effectiveness of our algorithm by comparing it to state-of-the-art solvers, and we give empirical evidence showing that search and action can be decoupled for some useful tasks. finally, we demonstrate our algorithm on an autonomous mobile robot performing object search and delivery in an office environment.
safe, stable and intuitive control for physical human-robot interaction. for physical human-robot interaction, safety and dependability are of utmost importance due to the potential risk a relatively powerful robot poses for human beings. from the control standpoint, it is possible to increase this level of safety by guaranteeing that the robot will never exhibit any unstable behaviour. however, stability is not the only concern in the design of a controller for such a robot. during human-robot interaction, the resulting cooperative motion should be truly intuitive and should not restrict in any way the human performance. for this purpose, we have designed a new variable admittance control law that guarantees the stability of the robot during constrained motion and also provides a very intuitive human interaction. the first characteristic is provided by the design of a stability observer while the other is based on a variable admittance control scheme that uses the force derivative as a way to predict human intention. the stability observer is based on a previous stability investigation of cooperative motion which implies the knowledge of the interaction stiffness. a method to accurately estimate this stiffness online using the data coming from the encoder and from a multi-axis force sensor at the end effector is also provided. the stability and intuitivity of the control law were verified in a user study during a cooperative drawing task with a 3 degree-of-freedom (dof) parallel robot.
high dynamic range stereo vision for outdoor mobile robotics. we present a technique for high-dynamic range stereo for outdoor mobile robot applications. stereo pairs are captured at a number of different exposures (exposure bracketing), and combined by projecting the 3d points into a common coordinate frame, and building a 3d occupancy map. we present experimental results for static scenes with constant and dynamic lighting as well as outdoor operation with variable and high contrast lighting conditions.
real-time monocular visual odometry for on-road vehicles with 1-point ransac. this paper presents a system capable of recovering the trajectory of a vehicle from the video input of a single camera at a very high frame-rate. the overall frame-rate is limited only by the feature extraction process, as the outlier removal and the motion estimation steps take less than 1 millisecond with a normal laptop computer. the algorithm relies on a novel way of removing the outliers of the feature matching process. we show that by exploiting the nonholonomic constraints of wheeled vehicles it is possible to use a restrictive motion model which allows us to parameterize the motion with only 1 feature correspondence. using a single feature correspondence for motion estimation is the lowest model parameterization possible and results in the most efficient algorithms for removing outliers. here we present two methods for outlier removal. one based on ransac and the other one based on histogram voting. we demonstrate the approach using an omnidirectional camera placed on a vehicle during a peak time tour in the city of zurich. we show that the proposed algorithm is able to cope with the large amount of clutter of the city (other moving cars, buses, trams, pedestrians, sudden stops of the vehicle, etc.). using the proposed approach, we cover one of the longest trajectories ever reported in real-time from a single omnidirectional camera and in cluttered urban scenes, up to 3 kilometers.
least absolute policy iteration for robust value function approximation. least-squares policy iteration is a useful reinforcement learning method in robotics due to its computational efficiency. however, it tends to be sensitive to outliers in observed rewards. in this paper, we propose an alternative method that employs the absolute loss for enhancing robustness and reliability. the proposed method is formulated as a linear programming problem which can be solved efficiently by standard optimization software, so the computational advantage is not sacrificed for gaining robustness and reliability. we demonstrate the usefulness of the proposed approach through simulated robot-control tasks.
kinematic analysis and optimal design of a 3t1r type parallel mechanism. in previous studies on 4-dof parallel mechanisms with four sub-chains, only symmetric arrangement of those four chains connected to the top plate was considered. such symmetric shape sometimes falls into a sort of architetural singularity. this work demonstrates that an asymmetric placement of the four chains on the top platform is desired to minimize the effect of such architectural singularity. a new 4-dof parallel mechanism exhibiting 4-dof motion (3-dof translational motion and one rotational motion) is examined as an exemplary device. this device consists of a base plate, an upper plate, and four hybrid subchains connecting those two plates together. the position analysis and kinematic modeling for this mechanism are performed, and an optimal design with respect to the workspace size and the kinematic isotropic characteristic is conducted. a set of offset angles on the top platform is found, which significantly minimizes the architectural singularity problem within the valid workspace of the mechanism. then, through the analysis of the workspace and kinematic isotropic property for the optimized mechanism, its high potential for real applications is confirmed. finally, the mechanism was developed to verify the motion capability.
backbone-based connectivity control for mobile networks. while a network of autonomous mobile agents is capable of performing spatially distributed tasks, communication between agents imposes a class of constraints over the corresponding task. this paper proposes a distributed paradigm to deal with a critical communication constraint, connectedness constraint, where a group of mobile agents are required to remain connected while performing a task (e.g., formation control, consensus, etc.). the proposed method adaptively extracts communication backbone of the group, which is formed by a subset of agents, and thus partitions the group into backbone agents and non-backbone agents. the connectedness of the system is maintained at two levels: motion of backbone agents is controlled to maintain existing connections in the backbone; motion of non-backbone agents is determined via a leader-follower formation control method with backbone agents as the leaders. key advantages of the proposed approach are that it can deal with arbitrary system topologies, it is a distributed method, it uses only two-hop neighbor information, and has low communication cost.
robot basketball: a comparison of ball dribbling with visual and force/torque feedback. ball dribbling is a central element of basketball and a main challenge for creating basketball robots is to achieve stability of the periodic dribbling task. in this paper two control designs for ball dribbling with an industrial robot are compared. for the two strategies, the ball position is determined either through force/torque or visual sensor feedback and the ball trajectory is predicted with a recursive least squares algorithm. the end effector trajectory for each dribbling cycle is generated based on the predicted ball position/velocity at the dribbling height and the estimated coefficient of restitution. for both tracking approaches, dribbling for multiple cycles is achieved. the vision-based approach performs better as compared to the force/torque-based approach, in particular for imprecise estimates of the coefficient of restitution.
hybrid design for multiple-goal task realization of robot arm with rotating table. the minimization of task completion time of robot arms has been an extensively studied area in robotics. previous researches mostly focused on optimization methods for the motion planning and collision avoidance, which did not involve any modifications in the hardware design of a robot arm. some researches, on the other hand, fully design a specialized robot arm for a given task. in this study, we propose a hybrid design composed of a hardware design and an optimization method. the hardware design is a tool attachment, which is a fixed linkage attached between the end-effector of a robot arm and a tool. in the optimization method, we incorporate base placement design, goal rearrangement and collision avoidance through motion coordination in order to minimize the task completion time of a robot arm. our proposed design is tested using a 6-dof robot arm and a 1-dof rotating table. the method is evaluated over a single task and a set of tasks showing its effectiveness and applicability for practical applications.
on fast surface reconstruction methods for large and noisy point clouds. in this paper we present a method for fast surface reconstruction from large noisy datasets. given an unorganized 3d point cloud, our algorithm recreates the underlying surface's geometrical properties using data resampling and a robust triangulation algorithm in near realtime. for resulting smooth surfaces, the data is resampled with variable densities according to previously estimated surface curvatures. incremental scans are easily incorporated into an existing surface mesh, by determining the respective overlapping area and reconstructing only the updated part of the surface mesh. the proposed framework is flexible enough to be integrated with additional point label information, where groups of points sharing the same label are clustered together and can be reconstructed separately, thus allowing fast updates via triangular mesh decoupling. to validate our approach, we present results obtained from laser scans acquired in both indoor and outdoor environments.
impass: intelligent mobility platform with active spoke system. impass (intelligent mobility platform with active spoke system) is a novel mobile robot driven by two rimless spoke wheels. each of the spokes can be individually actuated with intelligent motion planning to walk over uneven terrain with high mobility. this form of novel locomotion has the potential to combine the efficiency of a wheeled robot and the mobility of a legged robot. a highly mobile robot such as impass could prove very valuable in applications where the terrain is complex and dangerous, such as search and rescue, reconnaissance, or anti-terror response. this video presents an overview of the system concept with examples and demonstrations of its unique mobility. beginning with an overview of the system concept and hardware, the video then demonstrates the different mobility advantages. these include rough terrain locomotion, dynamic surface locomotion, and large step climbing.
modeling and control of a pair of robot fingers with saddle joint under orderless actuations. a new robot hand dynamics model with rolling constraints and with a saddle joint at one finger is proposed, where two saddle-joint actuations are considered to be orderless. spinning motion around the opposition axis connecting two center points of each finger-tip contact area with an object is faithfully treated, and a viscosity model for damping rotational motion of the object is proposed. a class of control signals without referring to object kinematics or using external sensing is proposed. finally, numerical simulation results show the stability of motion of the overall closed-loop dynamics supplied with the proposed control input.
on the potential of physics-based animation for task programming in virtual reality. physics-based animation is becoming an essential feature for any advanced simulation software. in this paper we explore potential benefits of physics-based modeling for task programming in virtual reality. firstly, we show how realistic animation of manipulation tasks can be exploited for learning sequential constraints from user demonstrations. in particular, we propose a method where information about physical interaction is used to discover task precedences and to reason about task similarities at the goal level. a second contribution of the paper is the application of physics-based modeling to the problem of disassembly sequence planning. experiments have been performed in a desktop virtual reality environment with dataglove and motion tracker.
a study on sinus-lifting motion of a snake robot with switching constraints. in this paper, we consider "sinus-lifting motion" which is the effective motion of a snake for rapid movement consisting of lifting some parts of its body off the ground, and switching the lifted and grounded parts dynamically. this motion is analyzed based on control theory. we focus on the constraint force of passive wheels and switching of grounded parts of the snake robot to minimize the constraint force. simulations show that the motion that minimizes the constraint force of the snake robot is similar to the sinus-lifting motion in appropriate amplitudes and periods of the body shape.
producing rigid contacts in cable-driven haptic interfaces using impact generating reels. this paper presents a design for a cable reel that allows a cable-driven haptic interface to produce rigid impacts with virtual objects in a virtual reality settings. the haptic interface studied in this article has three degrees of freedom (3 dof) and acts as a sword-fighting simulator. in order to obtain sharp impacts with this interface, an impact generating reel is proposed to transmit forces across the cables to a user holding the end-effector (sword). a prototype is presented in order to demonstrate the concept. as a method of quantifying the credibility of these impacts, an accelerometer was mounted on the end-effector, where the cables are attached in order to measure the vibrations caused by these impacts. these vibrations are compared with the vibrations caused by an impact with a rigid material such as steel in order to classify the stiffness of the impacts generated by the mechanism
learning and generalization of motor skills by learning from demonstration. we provide a general approach for learning robotic motor skills from human demonstration. to represent an observed movement, a non-linear differential equation is learned such that it reproduces this movement. based on this representation, we build a library of movements by labeling each recorded movement according to task and context (e.g., grasping, placing, and releasing). our differential equation is formulated such that generalization can be achieved simply by adapting a start and a goal parameter in the equation to the desired position values of a movement. for object manipulation, we present how our framework extends to the control of gripper orientation and finger position. the feasibility of our approach is demonstrated in simulation as well as on the sarcos dextrous robot arm. the robot learned a pick-and-place operation and a water-serving task and could generalize these tasks to novel situations.
moving obstacle detection in highly dynamic scenes. we address the problem of vision-based multiperson tracking in busy pedestrian zones using a stereo rig mounted on a mobile platform. specifically, we are interested in the application of such a system for supporting path planning algorithms in the avoidance of dynamic obstacles. the complexity of the problem calls for an integrated solution, which extracts as much visual information as possible and combines it through cognitive feedback. we propose such an approach, which jointly estimates camera position, stereo depth, object detections, and trajectories based only on visual information. the interplay between these components is represented in a graphical model. for each frame, we first estimate the ground surface together with a set of object detections. based on these results, we then address object interactions and estimate trajectories. finally, we employ the tracking results to predict future motion for dynamic objects and fuse this information with a static occupancy map estimated from dense stereo. the approach is experimentally evaluated on several long and challenging video sequences from busy inner-city locations recorded with different mobile setups. the results show that the proposed integration makes stable tracking and motion prediction possible, and thereby enables path planning in complex and highly dynamic scenes.
a protocol for decentralized multi-vehicle mapping with limited communication connectivity. this paper addresses the problem of communication range limitations for decentralized multi-vehicle mapping. we present a novel integrated communication and planning protocol that enables all vehicles to form a common global map. the fusion of mapping information is facilitated through the information filter and performed over a connected acyclic wireless communication network with limited communication range. the formation of the acyclic connected communication network is achieved by partitioning the landmark graph using graph theoretic tools during the planning phase. we provide results that illustrate the effectiveness of our approach over different distributions of landmarks.
the null-space based behavioral control for non-holonomic mobile robots with actuators velocity saturation. this paper presents the application of the null-space based behavioral (nsb) approach to the motion control of a non-holonomic mobile robot with velocity saturated actuators. in particular, the proposed solution aims at managing actuator velocity saturations by dynamically scaling task velocity commands so that the hierarchy of task priorities is preserved in spite of actuator velocity saturations. the approach is tested on a specific case study where the nsb approach elaborates the motion directives for a mobile robot that has to reach a target while avoiding a punctual obstacle. the approach is validated by numerical simulations and by experimental results with a non-holonomic mobile robot.
decentralized localization for dynamic and sparse robot networks. finite-range sensing and communication are factors in the connectivity of a dynamic mobile robot network. state estimation becomes a difficult problem when communication connections for information exchange between all robots are not guaranteed. this paper presents a decentralized state estimation algorithm guaranteed to work in dynamic networks without connectivity requirements. we show that a robot only needs to consider its own knowledge of network topology in order to produce an estimate equivalent to the centralized state estimate whenever possible, while ensuring the same can be performed by all other robots in the network. our technique is validated through simulations.
tokyo-tech 100 n hand : three-fingered eight-dof hand with a force-magnification mechanism. this paper presents tokyo-tech 100 n hand, a three-fingered eight-degree of freedom hand that can generate a large grasp force of 100n. all fingers are 90 mm in length and the weight of the hand is 941 g. the hand can generate a large grasp force with a force-magnification mechanism whereas all joints can perform a high speed motion of over 200 deg/s with a high-speed driving mechanism. the high-speed driving mechanism consists of a feed screw and nut with a low reduction ratio. we propose a simple and small three-dimensional toggle mechanism for the force-magnification mechanism. the toggle mechanism thrusts the feed screw and nut of the high-speed driving mechanism when the finger is in contact with an object. it can maintain a large grasp force without energy consumption. we experimentally verify the force and speed performances.
moving object classification using horizontal laser scan data. motivated by two potential applications, i.e. enhancing driving safety and traffic data collection, a system has been developed using a single-layer horizontal laser scanner as the major sensor for both localization and perception of the surroundings in a large dynamic urban environment. this research focuses on a classification method, that given a stream of laser measurements, classify the moving object into either a person, a group of people, a bicycle or a car. in this research, a number of features are defined after examining the property of data appearance. a classification method is proposed after examining the likelihood measures between each pair of feature and class. experimental results are presented, demonstrating that the algorithm has efficiency with respect to both driving safety and traffic data collection in highly dynamic environment.
plc-based control of a robot manipulator with closed kinematic chain. the paper describes the design and implementation of a robot control system on a hardware platform based on a programmable logic controller (plc). the controlled robot is a 4 degrees of freedom (dof) manipulator with a closed kinematic chain, designed for high-performance pick and place applications in a packaging workcell. the control software is fully developed on a commercial plc system, using its standard programming tools and the multi-tasking features of its operating system. in particular, the paper analyse in detail the drawbacks and the advantages related to the choice of standard plcs in this kind of applications, compared to the much common choice of specialized hardware or industrial personal computers, with particular emphasis on the computational performances obtained with the proposed control architecture.
markerless human motion tracking with a flexible model and appearance learning. a new approach to the 3d human motion tracking problem is proposed, which combines several particle filters with a physical simulation of a flexible body model. the flexible body model allows the partitioning of the state space of the human model into much smaller subsets, while finding a solution considering all the partial results of the particle filters. the flexible model also creates the necessary interaction between the different particle filters and allows effective semi-hierarchical tracking of the human body. the physical simulation does not require inverse kinematics calculations and is hence fast and easy to implement. furthermore the system also builds an appearance model on-the-fly which allows it to work without a foreground segmentation. the system is able to start tracking automatically with a convenient initialization procedure. the implementation runs with 10 hz on a regular pc using a stereo camera and is hence suitable for human-robot interaction applications.
smoothed sarsa: reinforcement learning for robot delivery tasks. our goal in this work is to make high level decisions for mobile robots. in particular, given a queue of prioritized object delivery tasks, we wish to find a sequence of actions in real time to accomplish these tasks efficiently. we introduce a novel reinforcement learning algorithm called smoothed sarsa that learns a good policy for these delivery tasks by delaying the backup reinforcement step until the uncertainty in the state estimate improves. the state space is modeled by a dynamic bayesian network and updated using a region-based particle filter. we take advantage of the fact that only discrete (topological) representations of entity locations are needed for decision-making, to make the tracking and decision making more efficient. our experiments show that policy search leads to faster task completion times as well as higher total reward compared to a manually crafted policy. smoothed sarsa learns a policy orders of magnitude faster than previous policy search algorithms. we demonstrate our results on the player/stage simulator and on the pioneer robot.
a nonlinear terrain-following controller for a vtol unmanned aerial vehicle using translational optical flow. this paper presents a nonlinear controller for terrain following of a vertical take-off and landing vehicle (vtol). the vtol vehicle is assumed to be a rigid body, equipped with a minimum sensor suite (camera and imu) along with a measure of the forward speed from another sensor such as global positioning system, maneuvering over a textured terrain made of planar surfaces. assuming that the forward velocity is separately set to a desired value, the proposed control approach ensures terrain following and guaranties the vehicle does not collide with the ground during the task. the proposed control acquires an optical flow from three spatially separate observation points, typically obtained via three cameras or three non collinear directions in a unique camera. the proposed control algorithm has been tested extensively in simulation and then implemented on a quadrotor uav to demonstrate the performance of the closed loop system.
vision-based leader-follower formations with limited information. this paper presents a new vision-based leader-follower formation algorithm where the leader's trajectory is unknown to the robots which are following. formation schemes in straight lines and diagonal formations are introduced which are both stable and observable in the presence of limited views. the algorithms are novel since they only use local image measurements through a pinhole camera to estimate the leader's position. this approach does not require specialized markings nor extensive robot communications. the algorithms are also decentralized. we apply an input-output feedback linearization for system stability and utilize an extended kalman filter (ekf) for estimation. simulations illustrate how the proposed formation controls work. real experiments utilizing multiple miniature robots are also presented and illustrate the challenges associated with noisy images in real-world applications.
high performance anthropomorphic robot hand with grasp force magnification mechanism. this paper presents a lightweight 328 g anthropomorphic robot hand that can exert a large grasp force. we propose a combination mechanism of a flexion-drive and a force-magnification-drive for a cable driven multifingered robot hand. the flexion-drive consisting of a feed screw enables quick motion of its fingers and the force-magnification-drive consisting of an eccentric cam, a bearing and a pulley enables a firm grasp. this paper also proposes a three-dimensional linkage for the thumb. this linkage consists of four links and is driven by a feed screw. it can oppose to a large force exerted by the other fingers with the force-magnification-drive. these mechanisms are compact enough to be installed in the developed lightweight hand. we experimentally verify that the maximum fingertip force of the hand exceeds 20 n and that the thumb can hold a large force of 100 n. the time to fully close the hand by using the flexion-drives is 0.47 s. after the fingers make contact with an object, the time to achieve a firm grasp by using the grasp-magnification-drive is approximately 1 s.
multiple-model ransac for ego-motion estimation in highly dynamic environments. robust ego-motion estimation in urban environments is a key prerequisite for making a robot truly autonomous, but is not easily achievable as there are two motions involved: the motions of moving objects and the motion of the robot itself. we proposed a random sample consensus (ransac) based ego-motion estimator to deal with highly dynamic environments using one planar laser scanner. instead of directly sampling on individual measurements, the ransac process is performed at a higher level abstraction for systematic sampling and computational efficiency. we proposed a multiple-model approach to solve the problems of ego-motion estimation and moving object detection jointly in a ransac paradigm. to accommodate ransac to multiple models - a static environment model for ego-motion estimation and a moving object model for moving object detection, a compact representation models moving object information implicitly is proposed. moving objects are successfully detected without incorporating any grid maps, that are inherently time and space consuming. the experimental results show that accurate identification of static environments can help classification of moving objects, whereas discrimination of moving objects also yields better ego-motion estimation, particularly in environments containing a significant percentage of moving objects.
prioritizing linear equality and inequality systems: application to local motion planning for redundant robots. we present a novel method for prioritizing both linear equality and inequality systems and provide one algorithm for its resolution. this algorithm can be summarized as a sequence of optimal resolutions for each linear system following their priority order. we propose an optimality criterion that is adapted to linear inequality systems and characterize the resulting optimal sets at every priority level. we have successfully applied our method to plan local motions for the humanoid robot hpr-2. we will demonstrate the validity of the method using an original scenario where linear inequality constraints are solved at lower priority than equality constraints.
conflict-evaluated maximum approximated likelihood approach for building grid maps using sonar sensors. in this paper, we address the problem of building a grid map using cheap sonar sensors, that is, the problem of using erroneous sensors when seeking to model an environment as accurately as possible. we rely on the inconsistency of information among sonar measurements and the sound pressure of the waves from the sonar sensors to develop a new method of detecting incorrect sonar readings, called the conflict evaluation with sound pressure (cesp). to fuse the correct measurements into a map, we start with the maximum likelihood approach due to its ability to manage the angular uncertainty of sonar sensors. however, since this approach suffers from heavy computational complexity, we convert it to a light logic problem called the maximum approximated likelihood (mal) approach. integrating the mal approach with the cesp method results in the conflict-evaluated maximum approximated likelihood (cemal) approach. the cemal approach generates a very accurate map that is close to the map that would be built by accurate laser sensors, and does not require adjustment of parameters for various environments.
from pixels to objects: enabling a spatial model for humanoid social robots. this work adds the concept of object to an existent low-level attention system of the humanoid robot icub. the objects are defined as clusters of sift visual features. when the robot first encounters an unknown object, found to be within a certain (small) distance from its eyes, it stores a cluster of the features present within an interval about that distance, using depth perception. whenever a previously stored object crosses the robot's field of view again, it is recognized, mapped into an egocentrical frame of reference, and gazed at. this mapping is persistent, in the sense that its identification and position are kept even if not visible by the robot. features are stored and recognized in a bottom-up way. experimental results on the humanoid robot icub validate this approach. this work creates the foundation for a way of linking the bottom-up attention system with top-down, object-oriented information provided by humans.
constructing action set from basis functions for reinforcement learning of robot control. continuous action sets are used in many reinforcement learning (rl) applications in robot control since the control input is continuous. however, discrete action sets also have the advantages of ease of implementation and compatibility with some sophisticated rl methods, such as the dyna [1]. however, one of the problem is the absence of general principles on designing a discrete action set for robot control in higher dimensional input space. in this paper, we propose to construct a discrete action set given a set of basis functions (bfs). we designed the action set so that the size of the set is proportional to the number of the bfs. this method can exploit the function approximator's nature, that is, in practical rl applications, the number of bfs does not increase exponentially with the dimension of the state space (e.g. [2]). thus, the size of the proposed action set does not increase exponentially with the dimension of the input space. we apply an rl with the proposed action set to a robot navigation task and a crawling and a jumping tasks. the simulation results demonstrate that the proposed action set has the advantages of improved learning speed, and better ability to acquire performance, compared to a conventional discrete action set.
tissue property estimation and graphical display for teleoperated robot-assisted surgery. manual palpation of tissue and organs during a surgical procedure provides clinicians with valuable information for diagnosis and surgical planning. in present-day robot-assisted minimally invasive surgery systems, lack of perceptible haptic feedback makes it challenging to detect a tumor in an organ or a calcified artery in heart tissue. this study presents an automated tissue property estimation method and a real-time graphical overlay that allow an operator to discriminate hard and soft tissues. we first evaluate experimentally the properties of an artificial tissue and compare seven possible mathematical tissue models. self-validation as well as cross-validation confirm that the hunt-crossley model best describes the experimentally observed phantom tissue properties and is suitable for our purpose. second, we present the development of a system in which the phantom tissue is palpated using a teleoperated surgical robot, and the stiffness of the hunt-crossly model is estimated in real time by recursive least squares. a real-time visual overlay representing tissue stiffness is created using a hue-saturation-luminance representation on a semitransparent disc at the tissue surface. hue depicts the stiffness at a palpated point and saturation is calculated based on distance from the point. a simple interpolation technique creates a continuous stiffness color map. in an experiment, the graphical overlay successfully shows the location of an artificial calcified artery hidden in phantom tissue.
constraint based world modeling in mobile robotics. in this paper we present a novel approach using constraint based techniques for world modeling, i.e. self localization and object modeling. within the last years, we have seen a reduction of landmarks such as beacons or colored goals within the robocup domain. using other features as line information becomes more important. using such sensor data is tricky, especially when the resulting position belief is stretched over a larger area. constraints can overcome this limitations, as they have several advantages: they can represent large distributions and are easy to store and to communicate to other robots. propagation of several constraints can be computationally cheap. even high dimensional belief functions can be used. we will describe a sample implementation and show experimental results.
a novel 1d trifocal tensor-based control for differential-drive robots. this paper presents an image-based approach to perform visual control for differential-drive robots. we use for the first time the elements of the 1d trifocal tensor directly in the control law. the visual control utilizes the usual teach-by showing strategy without requiring any a prior knowledge of the scene and does not need any auxiliary image. the main contribution of the paper is that the proposed two-steps control law ensures total correction of both position and orientation without switching to any other visual constraint rather than the 1d trifocal tensor. the paper exploits the sliding mode control technique in a square system, ensuring stability and robustness for the closed loop. the good performance of the control system is proven via simulations.
the dlr mirosurge - a robotic system for surgery. this video presents the in-house developed dlr mirosurge robotic system for surgery. as shown, the system is suitable for both minimally invasive and open surgery. essential part of the system is the miro robot: the soft robotics feature enables intuitive interaction with the robot. in the presented minimally invasive robotic setup three miros guide an endoscopic stereo camera and two endoscopic instruments with force feedback sensors. the master console for teleoperation consists of an autostereoscopic monitor and force reflecting input devices for both hands. versatility is shown with two additional applications: for assistance in manual minimally invasive surgery a miro robot automatically guides the endoscope such that the surgical instrument is always in view. in a biopsy application the miro robot is positioning the needle with navigation system support.
kinematic reconfigurability of mobile robots on irregular terrains. this paper considers the active control problem of reconfigurable mobile robots on irregular terrain. a kinematic control strategy to improve robot mobility (stability and traction) is proposed. the proposed control is validated through numerical simulations and experimental tests using an amphibious wheel-legged robot, named environmental hybrid robot, recently developed by petrobras s.a. (brazilian petroleum company) for environmental monitoring in the amazon rain forest.
autonomous driving in semi-structured environments: mapping and planning. we consider the problem of autonomous driving in semi-structured environments (e.g., parking lots). such environments have strong topological structure (graphs of drivable lanes), but maneuvers with significant deviations from those graphs are valid and frequent. we address two main challenges of operating in such environments: i) detection of topological structure from sensor data, and ii) using that structure to guide path planning. we present experimental results on both of these topics, demonstrating robust estimation of lane networks in parking lots and the benefits of using these topological networks to guide path planning.
most salient region tracking. in this paper, we introduce a cognitive approach for object tracking from a mobile platform. the approach is based on a biologically motivated attention system which is able to detect regions of interest in images based on concepts of the human visual system. a top-down guided visual search module of the system enables to especially favor features which fit to a previously learned target object. here, the appearance of an object is learned online within the first image in which it is detected. in subsequent images, the attention system searches for the target features and builds a top-down, target-related saliency map. this enables to focus on the most relevant features of especially this object in especially this scene without knowing anything about a particular object model or scene in advance. the system is able to operate in real-time and to cope with the requirements of real-world tasks such as illumination variations and other moving objects.
active guidance of a handheld micromanipulator using visual servoing. in microsurgery, a surgeon often deals with anatomical structures of sizes that are close to the limit of the human hand accuracy. robotic assistants can help to push beyond the current state of practice by integrating imaging and robot-assisted tools. this paper demonstrates control of a handheld tremor reduction micromanipulator with visual servo techniques, aiding the operator by providing three behaviors: snap-to, motion-scaling, and standoff-regulation. a stereo camera setup viewing the workspace under high magnification tracks the tip of the micromanipulator and the desired target object being manipulated. individual behaviors activate in task-specific situations when the micromanipulator tip is in the vicinity of the target. we show that the snap-to behavior can reach and maintain a position at a target with an accuracy of 17.5 ± 0.4µm root mean squared error (rmse) distance between the tip and target. scaling the operator's motions and preventing unwanted contact with non-target objects also provides a larger margin of safety.
minimalistic control of a compass gait robot in rough terrain. although there has been an increasing interest in dynamic bipedal locomotion for significant improvement of energy efficiency and dexterity of mobile robots in the real world, their locomotion capabilities are still mostly restricted on flat surfaces. the difficulty of dynamic locomotion in rough terrain is mainly originated in the stability and controllability of gait patterns while exploiting the natural mechanical dynamics of the robots. for a systematic investigation of the challenging problem, this paper presents the simplest control architecture for the compass gait model which can be used for locomotion in rough terrain. locomotion of the model is mainly achieved by an open-loop oscillator which induces self-stabilizing gait patterns, and we test the proposed control architecture in a real-world robotic platform. in addition, we also found that this controller is capable of varying stride length with a minimum change of control parameters, which enables locomotion in rough terrains. by using these basic principles of self-stability and gait variability, we extended the proposed controller with a simple sensory feedback about the location in the environment, which makes the robot possible to control gait patterns autonomously for traversing a rough terrain. we describe a set of experimental results and discuss how the proposed minimalistic control architecture can be enhanced for dynamic locomotion control in more complex environment.
modeling and control of the monopedal robot thumper. a hybrid controller that induces stable running gaits on a monopedal robot is developed. the robot features a rigid leg with a revolute knee and a heavy torso with center of mass located far from the hip. the torso houses a novel powertrain that provides series compliance in the compression direction of the leg. the proposed control law is developed within the hybrid zero dynamics framework and it acts on two levels. on the first level, continuous within-stride control asymptotically imposes (virtual) holonomic constraints reducing the dynamics of the robot to a lower-dimensional hybrid subsystem. on the second level, event-based control stabilizes the resulting hybrid subsystem. the controller achieves the dual objectives of working harmoniously with the system's natural dynamics and inducing provably exponentially stable running motions, while all relevant physical constraints are respected.
wireless reconfigurable modules for robotic endoluminal surgery. in this paper, a reconfigurable modular robotic system is proposed to augment the dexterity of endoluminal interventions in the gastrointestinal tract. in the proposed system, miniaturized robotic modules are ingested and assembled in the stomach cavity. the assembled robot can change its configuration according to the target location, thus enabling complicated surgical tasks. the robotic assembly, the robotic configuration and the surgical tasks are controlled via wireless bidirectional communication. based on this concept, early prototypes of the robotic modules were designed and fabricated. the developed module has 2dof (±90° of bending and 360° of rotation), measures 15.4 mm in diameter and 36.5 mm in length. it weighs 5.6 g and contains a li-po battery, two brushless dc motors, and a custom-made control board capable of wireless communication. the performance of the bending and rotational motion was evaluated and the future work has been discussed.
dynamic distributed intrusion detection for secure multi-robot systems. a general technique to build a dynamic and distributed intrusion detector for a class of multi-agent systems is proposed in this paper, by which misbehavior in the motion of one or more agents can be discovered. previous work from the authors has focused on how to distinguish the behavior of a misbehaving agent in a completely distributed way, by developing a solution where agents act as local monitors of their neighbors and use locally sensed information as well as data received from other monitors at a particular time. in this work, we improve the system detection capability by allowing monitors to use information collected at different instants and thus realizing a dynamic state observer that is valid for any system in the considered class. finally, we show through simulations the effectiveness of the proposed solution for a case study.
safe fall: humanoid robot fall direction change through intelligent stepping and inertia shaping. although fall is a rare event in the life of a humanoid robot, we must be prepared for it because its consequences are serious. in this paper we present a fall strategy which rapidly modifies the robot's fall direction in order to avoid hitting a person or an object in the vicinity. our approach is based on the key observation that during "toppling" the rotational motion of a robot necessarily occurs at the leading edge or the leading corner of its support base polygon. to modify the fall direction the robot needs to change the position and orientation of this edge or corner vis-a-vis the prohibited direction. we achieve it through intelligent stepping as soon as a fall is detected. we compute the optimal stepping location which results in the safest fall. additional improvement to the fall controller is achieved through inertia shaping techniques aimed at controlling the centroidal inertia of the robot. we demonstrate our results through the simulation of an asimo-like humanoid robot. to our knowledge, this is the first implementation of a controller that attempts to change the fall direction of a humanoid robot.
controller decomposition and combination design of body / motion elements based on orbit attractor. robot control systems consist of a feedback controller and reference motion pattern. they are designed based on the robot dynamics and coupled with each other, and it requires lots of calculation to obtain them. so far, we have proposed controller design method based on orbit attractor of nonlinear dynamics. because the controller yields one motion for one robot, we can assume that the controller includes information of motion and body elements. if those elements can be decomposed from the controller, a new controller can be easily designed by the combination of these elements. so in this paper, we propose the motion and body elements design method with lagrange's method of undetermined multipliers based on robot dynamics, and combination design method of a new controller using these elements. the effectiveness of the proposed method is evaluated by experiments with tapping dance robots.
developing a planning method for straight needle insertion using probability-based condition where a puncture occurs. needle insertion treatments require accurate placement of the needle tip into the target cancer. however, it is difficult to insert the needle accurately because of cancer displacement caused by organ deformation. therefore, a path planning using numerical simulation to analyze the deformation of the organ is important for accurate needle insertion. the problem in developing a planning method is that puncture conditions, such as the force applied to the needle, is difficult to be decided deterministically, because the experimental data of puncture conditions have variations. therefore, the purpose of this research was to develop a novel planning method to decide the robust paths of straight needle insertion for various puncture points. the basic idea of this planning method is to consider the puncture condition probabilistic and to evaluate the expected value of needle placement accuracy. first, a probability-based puncture condition was introduced, and then the expected value of needle placement accuracy was defined. next, the optimization method was developed to search the insertion path in a way that minimizes the expected values of needle placement accuracy. then, a numerical simulation and evaluation of the planning method was conducted, using a liver-shaped 2d model. furthermore, an in-vitro experiment was carried out to measure needle placement accuracy from the optimized path. experimental results show that the planning method realizes needle insertion with a mean accuracy of 1.5 mm.
robust hitting with dynamics shaping. the present paper proposes the motion planning based on "the dynamics shaping" for a robotic arm to hit the target robustly toward the desired direction, of which the concept is to shape the robot dynamics appropriately in order to accomplish the desired motion. according to the linear system theory, the positional error of the end-point converges onto near the singular vector corresponding to its maximum singular value of the output controllability matrix of the robotic arm. therefore, if we can control the direction of the singular vector by applying the dynamics shaping, we will be able to control the direction of the positional error of the end-effector caused by the disturbance. we propose a novel motion planning based on the dynamics shaping and verify numerically and experimentally that the robotic arm can robustly hit the target toward the desired direction with a simple open-loop control system even though the disturbance is applied.
inverse kinematics with closed form solutions for highly redundant robotic systems. this paper presents inverse position kinematics algorithms with real time capability for justin, a robotic system with high redundancy and many degrees of freedom. the combination of closed form solutions for parts of the kinematic chain embedded in a nonlinear equation solver is shown to be advantageous. the algorithms are evaluated with dlr's robot justin both in simulation and reality. calculation times of 1 ms are achieved, including various optimization criteria for redundancy resolution. in case only a single arm with 7 dof is considered, a fast calculation time of 250 µs is reached. with inclusion of an iterative step, reachability can be shown in more than 99% of the calculations regardless of the initial guess. the problem of weighting in multi-criteria optimization problems remains, though in the chosen approach the tool tip position is never compromised by other criteria due to the partially closed form solution. the presented algorithm can be applied to inverse position kinematics for all manipulators with serial or tree structure and redundant joints in case closed form solutions are available for parts of the kinematic chain.
on the use of inverse scaling in monocular slam. recent works have shown that it is possible to solve the simultaneous localization and mapping problem using an extended kalman filter and a single perspective camera. the principal drawback of these works is an inaccurate modeling of measurement uncertainties, which therefore causes inconsistencies in the filter estimations. a possible solution to proper uncertainty modeling is the unified inverse depth parametrization. in this paper we propose the inverse scaling parametrization that still allows an un-delayed initialization of features, while reducing the number of needed parameters and simplifying the measurement model. this novel approach allows a better uncertainty modeling of both low and high parallax features and reduces the likelihood of inconsistencies. experiments in simulation demonstrate that the use of the inverse scaling solution improves the performance of the monocular ekf slam filter when compared with the unified inverse depth approach; experiment on real data confirm the applicability of the idea.
equipping robot control programs with first-order probabilistic reasoning capabilities. an autonomous robot system that is to act in a real-world environment is faced with the problem of having to deal with a high degree of both complexity as well as uncertainty. therefore, robots should be equipped with a knowledge representation system that is able to soundly handle both aspects. in this paper, we thus introduce an architecture that provides a coupling between plan-based robot controllers and a probabilistic knowledge representation system based on recent developments in statistical relational learning, which possesses the required level of expressiveness and generality. we outline possible applications of the corresponding models in the context of robot control, discussing suitable representation formalisms, inference and learning methods as well as transparent extensions of a robot planning language that allow robot control programs to soundly integrate the results of probabilistic inference into their plan generation process.
motion planning for high dof anthropomorphic hands. the paper deals with the problem of motion planning of anthropomorphic mechanical hands avoiding collisions. the proposed approach tries to mimic the real human hand motions, but reducing the dimension of the search space in order to obtain results as a compromise between motion optimality and planning complexity (time) by means of the concept of principal motion directions. basically, the work includes the following phases: capturing the human hand workspace using a sensorized glove and mapping it to the mechanical hand workspace, reducing the space dimension by looking for the most relevant principal motion directions, and planning the hand movements using a sampling-based roadmap planner. the approach has been implemented for a four finger anthropomorphic mechanical hand, and some examples are included to illustrate its validity.
in-pipe robot navigation based on the landmark recognition system using shadow images. in this paper, we present an autonomous in-pipe robot navigating system using vision-based landmark recognition. we propose to use special features of the pipelines (such as elbows or branches) as landmarks by recognizing the shadows of the elbows and branches. to obtain consistent shadow images, the in-pipe robot equips with specially designed illuminator. by analyzing the shadow, the robot can easily identify these landmarks, detect the direction of the passage, and adaptively traverse through while continuously updating the map. the effectiveness of the proposed method is verified by real experiments using the in-pipe robot mrinspect v for inspecting inside of the miniature urban 8-inch gas pipeline structure.
fast running experiments involving a humanoid robot. the present paper describes an implementation of fast running motions involving a humanoid robot. two important technologies are described: a motion generation and a balance control. the motion generation is a unified way to design both walking and running and can generate the trajectory with the vertical conditions of the center of mass (com) in short calculation time. the balance control enables a robot to maintain balance by changing the positions of the contact foot dynamically when the robot is disturbed. this control consists of 1) compliance control without force sensors, in which the joints are made compliant by feed-forward torques and adjustment of gains of position control, and 2) feedback control, which uses the measured orientation of the robot's torso used in the motion generation as an initial condition to decide the foot positions. finally, a human-sized humanoid robot that can run forward at 7.0 [km/h] is presented.
manipulation planning on constraint manifolds. we present the constrained bi-directional rapidly-exploring random tree (cbirrt) algorithm for planning paths in configuration spaces with multiple constraints. this algorithm provides a general framework for handling a variety of constraints in manipulation planning including torque limits, constraints on the pose of an object held by a robot, and constraints for following workspace surfaces. cbirrt extends the bi-directional rrt (birrt) algorithm by using projection techniques to explore the configuration space manifolds that correspond to constraints and to find bridges between them. consequently, cbirrt can solve many problems that the birrt cannot, and only requires one additional parameter: the allowable error for meeting a constraint. we demonstrate the cbirrt on a 7dof wam arm with a 4dof barrett hand on a mobile base. the planner allows this robot to perform household tasks, solve puzzles, and lift heavy objects.
tankbot: a miniature, peeling based climber on rough and smooth surfaces. tankbot is a miniature, energy efficient, lightweight (60 g), and robust climbing robot. it uses the continuous detachment force (peeling) of the flat, bulk tacky elastomer tread to climb. an optimum peeling angle with a preliminary analysis of the pretension effect, and the tread force distributions are presented. a passive tail transfers the peeling force from the rear wheel to the front and ensures intimate continuous contact with the surface. tankbot works in any orientation on smooth surfaces, such as glass and acrylic, of all slope angles (0 - 360 degrees). however, the robot can only work vertically on relatively rough surfaces in any direction, such as wood, metal, painted wall, and painted brick. tankbot can carry a payload of up to 40 g and 100 g on inverted and vertical surfaces, respectively. in addition, the robot can go over obstacles up to 15 mm tall on smooth vertical surfaces. internal transitioning from horizontal to vertical and vertical to horizontal and external transitioning from vertical to the horizontal are also achieved. the potential applications of this robot include inspection, exploration, maintenance, cleaning, repair, and search and rescue.
sampling-based path planning for geometrically-constrained objects. one of the key factors that affect the success and efficiency of sampling-based path planners is the obtention of samples in the more relevant regions of the workspace. this is known as importance sampling, and different approaches have already been proposed in this direction. this paper proposes a novel method to bias sampling by means of geometric constraints that reduces the sampling space to sets of lower dimensional submanifolds. these constraints may be imposed by the kinematic structure of the actuation system, by the task specification, or provided by a human user as an intuitive way to include problem knowledge to the planner. the method has been implemented and tested on a probabilistic roadmap planner giving promising results. a variant using a deterministic sampling source is also reported.
a switching active sensing strategy to maintain observability for vision-based formation control. vision-based control of a robot formation is challenging because the on-board sensor (camera) only provides the view-angle to the other moving robots, but not the distance that must be estimated. in order to guarantee a consistent estimate of the distance by knowing the control inputs and the sensor outputs in a given interval, the nonlinear multi-robot system must preserve its observability. recent theoretical studies on leader-follower robot formation exploit the interesting influence that the control actions have on observability. based on these results, in this paper we present a switching active control strategy for formation control. our control strategy is active in the sense that, while asymptotically achieving the formation control tasks, it also guarantees the system observability in those cases in which all the robots tend to move along nonobservable paths. as a result, both estimation and formation performances are improved. extensive simulation results show the effectiveness of the proposed design.
task-level imitation learning using variance-based movement optimization. recent advances in the field of humanoid robotics increase the complexity of the tasks that such robots can perform. this makes it increasingly difficult and inconvenient to program these tasks manually. furthermore, humanoid robots, in contrast to industrial robots, should in the distant future behave within a social environment. therefore, it must be possible to extend the robot's abilities in an easy and natural way. to address these requirements, this work investigates the topic of imitation learning of motor skills. the focus lies on providing a humanoid robot with the ability to learn new bimanual tasks through the observation of object trajectories. for this, an imitation learning framework is presented, which allows the robot to learn the important elements of an observed movement task by application of probabilistic encoding with gaussian mixture models. the learned information is used to initialize an attractor-based movement generation algorithm that optimizes the reproduced movement towards the fulfillment of additional criteria, such as collision avoidance. experiments performed with the humanoid robot asimo show that the proposed system is suitable for transferring information from a human demonstrator to the robot. these results provide a good starting point for more complex and interactive learning tasks.
graph-based robust shape matching for robotic application. shape is one of the useful information for object detection. the human visual system can often recognize objects based on the 2-d outline shape alone. in this paper, we address the challenging problem of shape matching in the presence of complex background clutter and occlusion. to this end, we propose a graph-based approach for shape matching. unlike prior methods which measure the shape similarity without considering the relation among edge pixels, our approach uses the connectivity of edge pixels by generating a graph. a group of connected edge pixels, which is represented by an "edge" of the graph, is considered together and their similarity cost is defined for the "edge" weight by explicit comparison with the corresponding template part. this approach provides the key advantage of reducing ambiguity even in the presence of background clutter and occlusion. the optimization is performed by means of a graph-based dynamic algorithm. the robustness of our method is demonstrated for several examples including long video sequences. finally, we applied our algorithm to our grasping robot system by providing the object information in the form of prompt hand-drawn templates.
optimal coverage for multiple hovering robots with downward facing cameras. this paper presents a distributed control strategy for deploying hovering robots with multiple downward facing cameras to collectively monitor an environment. information per pixel is proposed as an optimization criterion for multicamera placement problems. this metric is used to derive a specific cost function for multiple downward facing cameras mounted on hovering robot platforms. the cost function leads to a gradient-based distributed controller for positioning the robots. a convergence proof using lasalle's invariance principle is given to show that the robots converge to locally optimal positions. the controller is demonstrated in experiments with three flying quad-rotor robots.
posture control of redundant manipulators on the norm of task space stiffness optimization. this paper investigates the posture of the manipulator that has redundant dof similar to human upper extremity. the human arm naturally takes a posture with no wandering although it has one or two dof redundancy. the authors consider that the posture will be determined in task-oriented, which means that human unconsciously takes a posture of his/her upper extremities, which is suitable for he task that the endpoint is about to do. this study also assumes that all joints are capable to adjust the joint stiffness so that the stiffness of the endpoint in the space is also adjustable. hence our study aims to establish the theoretical method to make the manipulator take a posture that provides a stiffness of the endpoint suitable for the task. the new formula for shaping the manipulator's posture to provide a desired stiffness of the endpoint is presented followed by the similation study to verify it.
multi-robot coordination using generalized social potential fields. we present a novel approach to compute collision-free paths for multiple robots subject to local coordination constraints. more specifically, given a set of robots, their initial and final configurations, and possibly some additional coordination constraints, our goal is to compute a collision-free path between the initial and final configuration that maintains the constraints. to solve this problem, our approach generalizes the social potential field method to be applicable to both convex and nonconvex polyhedra. social potential fields are then integrated into a "physics-based motion planning" framework which uses constrained dynamics to solve the motion planning problem. our approach is able to plan for over 200 robots while averaging about 110 ms per step in a variety of environments.
biologically-inspired dynamical systems for movement generation: automatic real-time goal adaptation and obstacle avoidance. dynamical systems can generate movement trajectories that are robust against perturbations. this article presents an improved modification of the original dynamic movement primitive (dmp) framework by ijspeert et al [1], [2]. the new equations can generalize movements to new targets without singularities and large accelerations. furthermore, the new equations can represent a movement in 3d task space without depending on the choice of coordinate system (invariance under invertible affine transformations). our modified dmp is motivated from biological data (spinal-cord stimulation in frogs) and human behavioral experiments. we further extend the formalism to obstacle avoidance by exploiting the robustness against perturbations: an additional term is added to the differential equations to make the robot steer around an obstacle. this additional term empirically describes human obstacle avoidance. we demonstrate the feasibility of our approach using the sarcos slave robot arm: after learning a single placing movement, the robot placed a cup between two arbitrarily given positions and avoided approaching obstacles.
global path planning for robust visual servoing in complex environments. we incorporate sampling-based global path planning with visual servoing (vs) for a robotic arm equipped with an in-hand camera. the path planning accounts for a number of constraints: 1) maintaining continuous visibility of the target within the camera's field of view, 2) avoiding visual occlusion of target features caused by the workspace obstacles, robot's body, or the target itself, 3) avoiding collision with physical obstacles or self collision, and 4) joint limits. incorporating these constraints enhances the applicability of vs to significantly more complex environments/tasks, thereby making the resulting vs much more robust. the proposed planner explores the camera space, i.e. 3d cartesian space, for permissible camera paths satisfying the aforementioned constraints by iteratively extending a search tree in camera space and simultaneously tracking these paths in the robot's joint space using a local planner. the planned camera path is then projected into the image space and tracked using an image-based visual servoing scheme. the validity and effectiveness of the proposed approach in accomplishing vs tasks in complex environments are demonstrated through a number of simulations on a 6-dof robot arm moving among obstacles.
interactive segmentation for manipulation in unstructured environments. to perform successful manipulation, robots depend on information about objects in their environment. in unstructured environments, such information cannot be given to the robot a priori. it is thus critical for the robot to be able to continuously acquire task-specific information about objects. towards this goal, we present a robust perceptual skill for identifying, tracking, and segmenting objects in a cluttered environment. we increase the robot's perceptual capabilities by closely coupling them with the robot's manipulation skills. the robot's interaction with objects in the environment creates a perceptual signal, i.e. motion, that renders segmentation and tracking robust and reliable. in addition, the resulting perceptual signal reveals the type of segmentation most relevant to manipulation, namely a segmentation of rigidly connected physical bodies. we demonstrate our approach with experiments on a real world mobile manipulation platform with multiple objects in a cluttered scene.
development of a haptic device "delta-4" using parallel link mechanism. nowadays, several haptic devices are commercialized and becoming common not only in research fields but also in consumer use. in this paper, a new parallel link mechanism "delta-4" is proposed for a new haptic device within high quality force display capability and operability. delta-4 consists of 3 dof of translational motions. the key features of delta-4 comparing with conventional parallel link mechanisms are: a redundant actuation, a wide working area and a small footprint. the prototype is equipped with a 3 dof of rotation mechanism, which its center of motions is located on the wrist position of an operator. an evaluation test of force display was conducted on a prototype of delta-4 mechanism.
object recognition and full pose registration from a single image for robotic manipulation. robust perception is a vital capability for robotic manipulation in unstructured scenes. in this context, full pose estimation of relevant objects in a scene is a critical step towards the introduction of robots into household environments. in this paper, we present an approach for building metric 3d models of objects using local descriptors from several images. each model is optimized to fit a set of calibrated training images, thus obtaining the best possible alignment between the 3d model and the real object. given a new test image, we match the local descriptors to our stored models online, using a novel combination of the ransac and mean shift algorithms to register multiple instances of each object. a robust initialization step allows for arbitrary rotation, translation and scaling of objects in the test images. the resulting system provides markerless 6-dof pose estimation for complex objects in cluttered scenes. we provide experimental results demonstrating orientation and translation accuracy, as well a physical implementation of the pose output being used by an autonomous robot to perform grasping in highly cluttered scenes.
integration of multi-level postural balancing on humanoid robots. this paper discusses an integration issue of multi-level postural balancing on humanoid robot. we give a unified viewpoint of postural balancing, which covers ankle strategy to hip strategy. two kinds of distributor of desired ground reaction force to whole-body joint torque are presented. the one distributor leads to a dynamic balancer which covers hip strategy, with the under-actuated situation. a simple angular momentum regulator is also proposed to stabilize the internal motions due to the joint redundancy. the other distributor leads to a static balancer which lies between ankle and hip strategy. furthermore, this paper demonstrates that replacement of the center of mass feedback with the local joint stiffness makes the robot much stabler for some fast motions. motivated by the practicability of the static balancer and the strong push-recovery performance of the dynamic balancer, this paper presents a simple integration by superposition of the both balancers on a compliant human-sized biped robot. the simulation and experimental videos are supplemented.
a combination of particle filtering and deterministic approaches for multiple kernel tracking. color-based tracking methods have proved to be efficient for their robustness qualities. the drawback of such global representation of an object is the lack of information on its spatial configuration, making difficult the tracking of more complex motions. this issue can be overcome by using several kernels weighting pixels locations. in this paper a multiple kernels configuration is proposed and developed in both probabilistic and deterministic frameworks. the advantages of both approaches are combined to design a robust tracker allowing to track location, size and orientation of the object. a target tracking scheme using visual servoing considering measurements provided by the presented approach validates the proposed method.
on the kinematic modeling and control of a mobile platform equipped with steering wheels and movable legs. mobile platforms equipped with several steering wheels are known to be omnidirectional, i.e., able to independently translate and rotate on the plane. as an improvement to this design, the justin mobile platform also possesses the ability to vary its footprint over time by extending/retracting the wheel legs during motion. in this paper, we discuss the kinematic modeling and control issues for such a platform. the goal is to obtain a tracking controller which is able to realize an arbitrary linear/angular platform motion while, at the same time, independently expanding/retracting each leg. experimental results support the proposed approach.
visual homing for undulatory robotic locomotion. this paper addresses the problem of vision-based closed-loop control for undulatory robots. we present an image-based visual servoing scheme, which drives the robot to a desired location specified by a target image, without explicitly estimating its pose. instead, the control relies on the computation of the epipolar geometry between the current and target images. we analyze controllability and stability of the proposed control scheme, which is validated by simulation studies using the simuun computational tools. preliminary experiments, involving the nereisbot undulatory robotic prototype, are also presented.
a guidance and control strategy for dynamic soaring with a gliding uav. soaring is the process of gaining energy from the atmosphere in-flight using an aerodynamic free-flying platform. dynamic soaring utilizes the energy available in vertical wind gradients and is commonly used by soaring birds. this research aims to develop a guidance and control strategy to utilize dynamic soaring for a fixed-wing gliding uav. the basic strategies for dynamic soaring in vertical wind shear are explored and a simple piecewise trajectory based controller is developed to identify regions suitable for soaring and attempt traveling energy-neutral trajectories.
gel-type sticky mobile inspector to traverse on the rugged wall and ceiling. an epoch-making handy sized sticky mobile robot has been developed, aiming to search and rescue survivors inside the half collapsed buildings caused by big earthquakes. after the robot is tossed through small spaces, it moves around the rugged or bumpy wall and ceiling to overlook the floor by the installed camera. to generate large enough adhesive force even on the rugged wall, a gel mat made of urethane is introduced, whose force can be recovered by the washing function. developed sticky robot based on the above method could realize the 3d mobile performance on the rugged wall and ceiling with the function of washing of the gel mat and monitoring the scene of the inside of the building. the validity of the application to the rescue inspector is also verified.
cad-based recognition of 3d objects in monocular images. this paper provides a method for recognizing 3d objects in a single camera image and for determining their 3d poses. a model is trained solely based on the geometry information of a 3d cad model of the object. we do not rely on texture or reflectance information of the object's surface, making this approach useful for a wide range of industrial and robot applications and complementary to descriptor-based approaches. a view-based approach that does not show the drawbacks of previous methods is applied: it is robust to noise, occlusions, clutter, and contrast changes. furthermore, the 3d pose is determined with high accuracy. the high robustness of an exhaustive search is combined with an efficient hierarchical search, a high percentage of which can be computed offline, making our method suitable even for time-critical applications. the method is especially suited for, but not limited to, the recognition of untextured objects like metal parts, which are often used in industrial environments. it allows, for example, 3d pin picking in robot applications. tracking approaches can use it for initialization.
the adelopod tumbling robot. the desire for a high mobility-to-size ratio in mobile robots has led to the exploration of many new methods of locomotion, one of which is tumbling. we believe that tumbling has a great potential to produce high mobility-to-size ratios in miniature mobile robots. in this paper we discuss tumbling locomotion and introduce the adelopod, a small two-armed tumbling robot recently developed at the university of minnesota center for distributed robotics. the adelopod achieves high mobility with low hardware complexity, making it a desirable addition to any heterogeneous team of robots.
kinematic design of an ejection-free underactuated anthropomorphic finger. this paper presents preliminary results on the design of a novel architecture of a three-phalanx underactuated finger. an ejection-free underactuated anthropomorphic hand is of the greatest interest for the field of humanoid robots. so far, all underactuated fingers lead to ejection for certain configurations. by using a second system of actuation in a three-phalanx finger, the zone of instability of this finger is reduced and the ejection problem is prevented. hence, the mathematical model of this finger is first introduced, followed by the choice of transmission ratios to be taken for the two pulley systems. finally, the zone of instability of this new architecture is presented where it is proved that ejection is avoided.
a search and rescue robot. in order to increase the effectiveness of robotic systems, the robots must be able to negotiate a variety of terrains. in urban environments this task becomes challenging as environments built for humans often have impediments such as stairs and thresholds which may be difficult or impossible for wheeled or tracked vehicles to go over. this is further complicated in search and rescue scenarios where debris and rubble from collapsed structures may further complicate the environment. in order to address these limitations a novel robotic platform, the loper, has been developed. the loper utilizes a trilobe wheel and a compliant chassis in order to traverse difficult terrain. in addition, multiple gait configurations of the trilobe wheel enable the loper to overcome a variety of obstacles, both indoors and out.
control for throwing manipulation by one joint robot. this paper proposes a throwing manipulation strategy for a robot with one revolute joint. the throwing manipulation enables the robot not only to manipulate the object to outside of the movable range of the robot, but also to control the position of the object arbitrarily in the vertical plane even though the robot has only one degree of freedom. in the throwing manipulation, the robot motion is dynamic and quick, and the contact state between the robot and the object changes. these make it difficult to obtain the exact model and solve its inverse problem. in addition, since the throwing manipulation requires more powerful actuators than the static manipulation, we should set the control input by taking consideration of the performance limits of the actuators. the present paper proposes the control strategy based on the iteration optimization learning to overcome the above problems and verifies its effectiveness experimentally.
manipulation planning with workspace goal regions. we present an approach to path planning for manipulators that uses workspace goal regions (wgrs) to specify goal end-effector poses. instead of specifying a discrete set of goals in the manipulator's configuration space, we specify goals more intuitively as volumes in the manipulator's workspace. we show that wgrs provide a common framework for describing goal regions that are useful for grasping and manipulation. we also describe two randomized planning algorithms capable of planning with wgrs. the first is an extension of rrt-jt that interleaves exploration using a rapidly-exploring random tree (rrt) with exploitation using jacobian-based gradient descent toward wgr samples. the second is the ikbirrt algorithm, which uses a forward-searching tree rooted at the start and a backward-searching tree that is seeded by wgr samples. we demonstrate both simulation and experimental results for a 7dof wam arm with a mobile base performing reaching and pick-and-place tasks. our results show that planning with wgrs provides an intuitive and powerful method of specifying goals for a variety of tasks without sacrificing efficiency or desirable completeness properties.
a miniature ceiling walking robot with flat tacky elastomeric footpads. in this paper, the design, analysis, and development of a sixteen-legged palm-sized climbing robot using flat bulk tacky elastomer adhesives as an attachment method is presented. a legged robot with four-bar based kinematics is designed and fabricated with elastomeric footpads. the proposed robot has a passive peeling mechanism for energy efficient and vibration free detachment. a rocker-type mechanism in the leg and compliant foam under the footpads are utilized for passive alignment on concave and convex surfaces. adhesion experimental data is used to estimate the adhesion and preload saturation on the footpads on different angled acrylic surface. it is showed that although the initial preload does not affect the adhesion and preload saturation point, the orientation and the weight of the robot, roughness of the surface, and waiting time between consecutive steps greatly effect the climbing performance. experimental results revealed that the robot can climb in any direction in 3d space on smooth surfaces, such as acrylic and glass. it can carry a payload of up to 2 n, which is almost twice as its own weight, on a smooth inverted surface. the robot can robustly climb vertically on relatively rough surfaces such as a painted wall or a wooden door. potential applications of this robot include inspection, exploration, maintenance, cleaning, repair, and search and rescue.
the twente humanoid head. this video shows the results of the project on the mechatronic development of the twente humanoid head. the mechanical structure consists of a neck with four degrees of freedom (dofs) and two eyes (a stereo pair system) which tilt on a common axis and rotate sideways freely providing a three more dofs. the motion control algorithm is designed to receive, as an input, the output of a biological-inspired vision processing algorithm and to exploit the redundancy of the joints for the realization of the movements. the expressions of the humanoid head are implemented by projecting light from the internal part of the translucent plastic cover.
surface identification using simple contact dynamics for mobile robots. this paper describes an approach to surface identification in the context of mobile robotics, applicable to supervised and unsupervised learning. the identification is based on analyzing the tip acceleration patterns induced in a metallic rod, dragged along a surface that is to be identified. eight features in time and frequency domains are used for classification. results show that for ten type of indoor and outdoor surfaces, reliable identification can be achieved (90.0 and 94.6 percent for a 1 and 4 seconds time-window, respectively), using a non-sophisticated classifier (artificial neural network). demonstration is done on how such a sensor and a simple control strategy can be used to guide a blind robot, using a simulation and a real differential drive robot.
laser-based geometric modeling using cooperative multiple mobile robots. in order to construct three-dimensional shape models of large-scale architectural structures using a laser range finder, a number of range images are taken from various viewpoints. these images are aligned using post-processing procedures such as the icp algorithm. however, in general, before applying the icp algorithm, these range images must be aligned roughly by a human operator in order to converge to precise positions. the present paper proposes a new modeling system using a group of multiple robots and an on-board laser range finder. each measurement position is identified by a highly precise positioning technique called cooperative positioning system (cps), which utilizes the characteristics of the multiple-robot system. thus, the proposed system can construct 3d shapes of large-scale architectural structures without any post-processing procedure or manual registration. icp is applied optionally for a subsequent refinement of the model. measurement experiments in unknown and large indoor/outdoor environments are carried out successfully using the newly developed measurement system consisting of three mobile robots named cps-v. generating a model of dazaifu tenmangu, a famous cultural heritage, for its digital archive completes the paper.
single-trocar assemblable retractor-hand for laparoscopic surgery. in laparoscopic surgery large instruments cannot be used because they cannot pass through trocars which are typically smaller than 12mm in diameter. for example, retracting an internal organ with a slender instrument is often a difficult task. to remove this limitation, we have proposed "assemblable instruments", that is, parts are inserted through trocars and assembled inside the abdominal cavity to become a large instrument and we have developed assemblable hands. however they use two trocars for assembling, which require positioning and alignment of two assembled parts. this paper presents a simple three fingered hand whose function is limited to retracting. we propose a much simpler assembling method "single trocar assembling" for the hand. experimental results verify that the hand can be assembled easily and that it can withstand a force of 25n enough to rectract a pancreas.
state transition, balancing, station keeping, and yaw control for a dynamically stable single spherical wheel mobile robot. unlike statically stable wheeled mobile robots, dynamically stable mobile robots can have higher centers of gravity, smaller bases of support and can be tall and thin resembling the shape of an adult human. this paper concerns the ballbot mobile robot, which balances dynamically on a single spherical wheel. the ballbot is omni-directional and can also rotate about its vertical axis (yaw motion). it uses a triad of legs to remain statically stable when powered off. this paper presents the evolved design with a four-motor inverse mouse-ball drive, yaw drive, leg drive, control system, and results including dynamic balancing, station keeping, yaw motion while balancing, and automatic transition between statically stable and dynamically stable states.
towards swarms of communication-enabled and intelligent sensotaxis-based bacterial microrobots capable of collective tasks in an aqueous medium. experimental data and proofs of concepts are used to show the feasibility of providing the basic components and functionalities required for the implementation of intelligent untethered 150 × 300µm bacterial microrobots capable of sophisticated collective tasks under computer supervision and coordination. more specifically, we show that it is possible to embed within such microrobots, photovoltaic cells supplying ∼4µw necessary to power an internal microelectronic circuit providing embedded intelligence with the capability to communicate commands and data wirelessly to an external computer. we also show that such data or commands transmitted wirelessly could be used to instruct an external computer to send a swarm of flagellated bacteria to move such microrobots towards a specific target based on various sensory information acquired with specific sensors embedded in each microrobots. similar to chemotaxis used by several species of flagellated bacteria, the algorithms used to move such microrobots could be governed by a larger range of sensory means, leading to what we refer to here as sensotaxisbased hybrid microrobots. the possibility of transmitting a request to a central computer to send a swarm of flagellated magnetotactic bacteria to provide propulsion and steering in order to move accurately to desired locations would allow such microrobots to perform collective tasks. a simple example suggesting the possibility of implementing accurate collective tasks by such hybrid microrobots is demonstrated experimentally where a microstructure emulating a v-shaped microrobot is moved and rotated autonomously using a swarm of approximately 3000 flagellated bacteria towards another similar v-shaped microstructure to form the character 'm' as in microrobot.
camera self-calibration for sequential bayesian structure from motion. computer vision researchers have proved the feasibility of camera self-calibration -the estimation of a camera's internal parameters from an image sequence without any known scene structure. various self-calibration algorithms have been published. nevertheless, all of the recent sequential approaches to 3d structure and motion estimation from image sequences which have arisen in robotics and aim at real-time operation (often classed as visual slam or visual odometry) have relied on pre-calibrated cameras and have not attempted online calibration. in this paper, we present a sequential filtering algorithm for simultaneous estimation of 3d scene estimation, camera trajectory and full camera calibration from a sequence of fixed but unknown calibration. this calibration comprises the standard projective parameters of focal length and principal point along with two radial distortion coefficients. to deal with the large non-linearities introduced by the unknown calibration parameters, we use a sum of gaussians (sog) filter rather than the simpler extended kalman filter (ekf). to our knowledge, this is the first sequential bayesian autocalibration algorithm which achieves complete fixed camera calibration using as input only a sequence of uncalibrated monocular images. the approach is validated with experimental results using natural images, including a demonstration of loop closing for a sequence with unknown camera calibration.
control of locomotion with shape-changing wheels. we present a novel approach to controlling the locomotion of a wheel by changing its shape, leading to applications to the synthesis and closed-loop control of gaits for modular robots. a dynamic model of a planar, continuous deformable ellipse in contact with a ground surface is derived. we present two alternative approaches to controlling this system and a method for mapping the gaits to a discrete rolling polygon. mathematical models and dynamic simulation of the continuous approximation and the discrete n-body system, and experimental results obtained from a physical modular robot system illustrate the accuracy of the dynamic models and the validity of the approach.
which landmark is useful? learning selection policies for navigation in unknown environments. in general, a mobile robot that operates in unknown environments has to maintain a map and has to determine its own location given the map. this introduces significant computational and memory constraints for most autonomous systems, especially for lightweight robots such as humanoids or flying vehicles. in this paper, we present a novel approach for learning a landmark selection policy that allows a robot to discard landmarks that are not valuable for its current navigation task. this enables the robot to reduce the computational burden and to carry out its task more efficiently by maintaining only the important landmarks. our approach applies an unscented kalman filter for addressing the simultaneous localization and mapping problems and uses monte-carlo reinforcement learning to obtain the selection policy. based on real world and simulation experiments, we show that the learned policies allow for efficient robot navigation and outperform handcrafted strategies. we furthermore demonstrate that the learned policies are not only usable in a specific scenario but can also be generalized towards environments with varying properties.
effects of haptic and graphical force feedback on teleoperated palpation. direct haptic feedback and graphical force feed-back have both been hypothesized to improve the performance of robot-assisted surgery. in this study we evaluate the benefits of haptic and graphical force feedback on surgeon performance and tissue exploration behavior during a teleoperated palpation task of artificial tissues. seven surgeon subjects (four experienced in robot-assisted surgery) used a 7-degree-of-freedom teleoperated surgical robot to identify a comparatively rigid rigid target object (representing a calcified artery) in phantom heart models using the following feedback conditions: (1) direct haptic and graphical feedback, (2) direct haptic only, (3) graphical feedback only, and (4) no feedback. to avoid the problems of force sensing in a minimally invasive surgical environment, we use a position-exchange controller with dynamics compensation for direct haptic feedback and a force estimator displayed via tool-tip tracking bar graph for graphical force feedback. although the transparency of the system is limited with this approach, results show that direct haptic force feedback minimizes applied forces to the tissue, while coupled haptic and graphical force feedback minimizes subject task error. for experienced surgeons, haptic force feedback substantially reduced task error independent of graphical feedback.
3d model selection from an internet database for robotic vision. we propose a new method for automatically accessing an internet database of 3d models that are searchable only by their user-annotated labels, for using them for vision and robotic manipulation purposes. instead of having only a local database containing already seen objects, we want to use shared databases available over the internet. this approach while having the potential to dramatically increase the visual recognition capability of robots, also poses certain problems, like wrong annotation due to the open nature of the database, or overwhelming amounts of data (many 3d models) or the lack of relevant data (no models matching a specified label). to solve those problems we propose the following: first, we present an outlier/inlier classification method for reducing the number of results and discarding invalid 3d models that do not match our query. second, we utilize an approach from computer graphics, the so called 'morphing', to this application to specialize the models, in order to describe more objects. third, we search for 3d models using a restricted search space, as obtained from our knowledge of the environment. we show our classification and matching results and finally show how we can recover the correct scaling with the stereo setup of our robot.
vision-tactile-force integration and robot physical interaction. this paper presents an approach for integrating vision, tactile and force sensors in a robotic manipulation framework. having an initial estimation of the object pose in the environment, a position-based visual servoing loop controls the hand for task execution, based on the input received from a model-based articular pose estimator following the virtual visual servoing approach. the visual control is combined with another control signal obtained from tactile feedback, through a set of selection matrices that can be modified at runtime in order to select the best modality for a given cartesian degree of freedom. the result of the preliminary integration is modified by an impedance force controller, in charge of performing the task motion along the task direction, at the same time that forces are regulated on the rest of directions. the design of the controller allows to perform the task even if a sensor is not available or provides inaccurate data. several experiments are performed, first by considering only force feedback, and then adding vision and, finally, tactile information. errors in the estimation of the object initial position are manually introduced in the experiments, and results show how the vision-tactile-force combination is able to deal with them, performing much better than the vision-force and force-alone approaches.
a new framework for force feedback teleoperation of robotic vehicles based on optical flow. this paper proposes the use of optical flow from a moving robot to provide force feedback to an operator's joystick to facilitate collision free teleoperation. optic flow is measured by wide angle cameras on board the vehicle and used to generate a virtual environmental force that is reflected to the user through the joystick, as well as feeding back into the control of the vehicle. the coupling between optical flow (velocity) and force is modelled as an impedance - in this case an optical impedance. we show that the proposed control is dissipative and prevents the vehicle colliding with the environment as well as providing the operator with a natural feel for the remote environment. the paper focuses on applications to aerial robotics vehicles, however, the ideas apply directly to other force actuated vehicles such as submersibles or space vehicles, and the authors believe the approach has potential for control of terrestrial vehicles and even teleoperation of manipulators. experimental results are provided for a simulated aerial robot in a virtual environment controlled by a haptic joystick.
lightweight high performance integrated actuator for humanoid robotic applications: modeling, design & realization. actuation of robotic systems is still an open question and represents a big challenge. demanding performances including high power to mass ratio, capability of producing high power at low speed within a small-occupied volume are some of the key issues that required careful consideration. these criteria aimed to increase autonomy of humanoid robots. in this paper, a novel hydrostatic transmission actuator is proposed. the proposed actuator is controlled by displacement and has capacities for energy storage. this leads to an optimal solution in terms of power consumption. first, the proposed hydrostatic actuation principle is explained. a simplified hydraulic scheme to illustrate the energy storage capability is then provided. a mathematical model of the proposed solution is detailed showing our ability to access to the payload "jerk". the built prototype is presented and its properties are outlined. finally, a prototype of the actuator and the preliminary results of the actuator performance are presented, demonstrating the novelty of our solution.
skillful manipulation based on high-speed sensory-motor fusion. this video introduces the demonstration of skillful manipulation using a high-speed robot system. the system consists of visual and tactile sensors at a rate of 1 khz and a high-speed hand-arm manipulator. the high-speed sensory-motor fusion improves not just the speed of existing robot manipulations, but robotic skills by introducing the features peculiar to high-speed motion. based on such a concept, new variations of skillful manipulation were achieved.
planning the reconfiguration of grounded truss structures with truss climbing robots that carry truss elements. in this paper we describe an optimal reconfiguration planning algorithm that morphs a grounded truss structure of known geometry into a new geometry. the plan consists of a sequence of paths to move truss elements to their new locations that generate the new truss geometry. the trusses are grounded and remain connected at all time. intuitively, the algorithm grows gradually the new truss structure from the old one. the truss elements are rigid bars joined with 18-way connectors. the paper also introduces the design of a truss-climbing robot that can execute the plan.
self-adapting modular robotics: a generalized distributed consensus framework. biological systems achieve amazing adaptive behavior with local agents performing simple sensing and actions. modular robots with similar properties can potentially achieve self-adaptation tasks robustly. inspired by this principle, we present a generalized distributed consensus framework for self-adaptation tasks in modular robotics. we demonstrate that a variety of modular robotic systems and tasks can be formulated within such a framework, including (1) an adaptive column that can adapt to external force, (2) a modular gripper that can manipulate fragile objects, and (3) a modular tetrahedral robot that can locomote towards a light source. we also show that control algorithms derived from this framework are provably correct. in real robot experiments, we demonstrate that such a control scheme is robust towards real world sensing and actuation noise. this framework can potentially be applied to a wide range of distributed robotics applications.
multi-jointed robot finger driven by artificial muscle actuator. in this paper we present a robotic actuation system by artificial muscle actuator based on dielectric elastomer. a novel linear actuator called "multi-stacked actuator" is presented, which can be embedded in the phalanges of the finger and ensures a compact design of the overall system. as an exemplary work, a two degree-of-freedom robot finger is developed and its performance is experimentally demonstrated. the proposed system can be extended to the multifingered robot hand easily, and applied even for articulated mechanisms such as legged robots etc.
development of the airway management training system wka-2 designed to reproduce different cases of difficult airway. the emerging field of medical robotics aims to introduce intelligent tools to assist a physician. the main challenges for developing efficient medical robotic training systems are simulating real-world conditions of the task and assuring training effectiveness. high anatomic fidelity has been achieved in current systems. however, those training systems are designed to reproduce specific conditions of the task (passive training). in this research, we are focusing in developing an airway management training systems designed to reproduce various cases of difficult airway. such difficulties (i.e. restricted mouth opening, various shapes of oral cavity including tongue swallowing, etc) may provoke traumas on different organs of the patient during an emergency situation. for this purpose, the authors have proposed the development of more advanced training tools. for this purpose, we have focused in embedding sensors and actuators to a conventional patient model towards the development of a patient robot (in previous research, authors have presented the evaluation model which embeds sensors). in this paper, we present an airway training system which embeds actuators into a mannequin. in particular, the mechanism design of the waseda kyotokagaku airway no.2 (wka-2) is detailed. the wka-2 is composed of twelve active and one passive degrees of freedom; which are designed to reproduce the various cases of difficult airway. for this purpose, the wka-2 reproduces the human muscles around the upper airway based on a wire driving mechanisms (a total of sixteen wires are used). in particular, the head of the model is composed of a tongue and mandible with translational and rotational movements around kinematic axis. in addition, we present the details of the kinematic model of wka-2 which enable the robot to reproduce the airway difficulties. finally, we presented the design of a tension sensor designed to measure the applied tension on each of the wire driving mechanism of wka-2. as preliminary experiments, we reproduce several cases of difficult airways using wka-2.
automatically and efficiently inferring the hierarchical structure of visual maps. in simultaneous localisation and mapping (slam), it is well known that probabilistic filtering approaches which aim to estimate the robot and map state sequentially suffer from poor computational scaling to large map sizes. various authors have demonstrated that this problem can be mitigated by approximations which treat estimates of features in different parts of a map as conditionally independent, allowing them to be processed separately. when it comes to the choice of how to divide a large map into such 'submaps', straightforward heuristics may be sufficient in maps built using sensors such as laser range-finders with limited range, where a regular grid of submap boundaries performs well. with visual sensing, however, the ideal division of submaps is less clear, since a camera has potentially unlimited range and will often observe spatially distant parts of a scene simultaneously. in this paper we present an efficient and generic method for automatically determining a suitable submap division for slam maps, and apply this to visual maps built with a single agile camera. we use the mutual information between predicted measurements of features as an absolute measure of correlation, and cluster highly correlated features into groups. via tree factorisation, we are able to determine not just a single level submap division but a powerful fully hierarchical correlation and clustering structure. our analysis and experiments reveal particularly interesting structure in visual maps and give pointers to more efficient approximate visual slam algorithms.
a four degree of freedom microrobot with large work volume. this paper presents a unique four-axis articulated mems robot, constructed by microassembly, targeting micro and nano scale manipulation and probing applications. the first version of this microrobot has a 2p2r (prismatic prismatic revolute revolute) kinematic configuration, occupies a total volume of 3mm × 2mm × 1mm, and operates within a workspace envelope of 50µm × 50µm × 75µm. this is by far the largest operating envelope of any independent micropositioner with non-planar dexterity. as a result, it can be classified as a new type of 3 dimensional miniaturized top-down assembly robot with dimensions smaller than 1 cm. the robot incorporates a combination of miniature flexures and cables to drive its joints from high force mems actuators. actuation is accomplished via two banks of in-plane electrothermal actuators, one coupled through an out of plane compliant socket, and the other one coupled remotely via a 30 µm diameter cu wire. in this paper, we decouple the motion of the robot joints by identifying the robot jacobian, and we offer preliminary experimental characterization of the microrobot repeatability. results show that the robot is repeatable to under 0.5 µm along xy and 0.015 degrees along pitch and yaw degrees of freedom.
the latency model for viscoelastic contact interface in robotics: theory and experiments. viscoelasticity is the phenomenon of time-dependent strain and/or stress in elastic solids. various contact interfaces with anthropomorphic end-effectors and polymeric solids found in robots and manipulators are intrinsically viscoelastic. it is therefore important to model such behavior and to study the effects of such time-dependent strain and stress on the stability and sustainability of grasping and manipulation. various models have been proposed over the years to describe such behavior of time-dependent strain and stress. furthermore, viscoelastic solids also display typically nonlinear elastic response. built upon a variety of literature, a new and practical latency model is proposed in this paper for the application of contact interface involving viscoelasticity in robotics. latency model can describe various features of viscoelastic materials, such as stress relaxation, creep, and material clock. the theoretical modeling was supported by experiments in which we found two types of relaxation, depending on the loading and unloading of grasping or contact. one type is well documented in existing literature; but the other type has not been, to our best knowledge, presented before. the proposed theory can unify both types of time-dependent relaxation responses.
an interactive tool for designing complex robot motion patterns. low-cost robots with a large number of degrees of freedom are becoming increasingly popular, nevertheless their programming is still a domain for experts. this paper introduces the kouretes motion editor (kme), a freely-available interactive software tool for designing complex motion patterns on robots with many degrees of freedom using intuitive means. kme allows for a tcp/ip connection to a real or simulated robot, over which various robot poses can be communicated to or from the robot and manipulated locally using the kme graphical user interface. this portability and flexibility enables the user to work under different modes, with different robots, using different host machines. kme is originally designed for the aldebaran nao humanoid robot which features a total of 21 degrees of freedom, but can be easily customized for other robots. kme has been employed successfully by kouretes, the robocup team of the technical university of crete, for designing various special actions at the robocup 2008 competition (standard platform league).
high-accuracy 3d sensing for mobile manipulation: improving object detection and door opening. high-resolution 3d scanning can improve the performance of object detection and door opening, two tasks critical to the operation of mobile manipulators in cluttered homes and workplaces. we discuss how high-resolution depth information can be combined with visual imagery to improve the performance of object detection beyond what is (currently) achievable with 2d images alone, and we present door-opening and inventory-taking experiments.
development of the anthropomorphic saxophonist robot was-1: mechanical design of the lip, tonguing, fingers and air pump mechanisms. the research on the development of musical performance robots has been particularly intensified on the last decades. in fact, the development of anthropomorphic robots able of playing musical instruments have been served as a mean for understanding the human motor control from an engineering point of view as well as understanding how to enable the communication between human and robots from an emotional point of view. in particular, our research aims in the development of an anthropomorphic saxophonist robot which is able not only of performing a musical score; but also to interact with other musical performance robots (i.e. waseda flutist robot) at the emotional level of perception. in this year, we have focused on the mechanical design of an anthropomorphic robot waseda saxophonist robot no. 1 (was-1); which has been designed for playing an alto saxophone. was-1 has a total of 15-dofs which mechanically reproduces the following organs involved during the saxophone playing: lips (1-dof), tongue (1-dof), oral cavity, lungs (air pump: 1-dof and air valve: 1-dof) and fingers (11-dofs). in order to verify the effectiveness of the production of sound, a set of experiments have been proposed. in particular, the characteristics of air flow-pressure, level of mechanical noise, and the ripple effect ratio are presented. finally, a qualitative evaluation of the sound produced by was-1 is presented and discussed. from the experimental results, we have confirmed the effectiveness of the proposed mechanisms to produce the saxophone sound.
smooth path planning in constrained environments. in this paper we describe a novel path planning approach for mobile robots operating in indoor environments. in such scenarios, robots must be able to maneuver in crowded spaces, partially filled with static and dynamic obstacles (such as people). our approach produces smooth, complex maneuvers over large distances through the use of an anytime graph search algorithm applied to a novel multi-resolution state lattice, where the resolution is adapted based on both environmental characteristics and task characteristics. in addition, we present a novel approach for generating fast globally optimal trajectories in constrained spaces (i.e. rooms connected via doors and hallways). this approach exploits offline precomputation to provide extremely efficient online performance and is applicable to a wide range of both indoor and outdoor navigation scenarios. by combining an anytime, multi-resolution lattice-based search algorithm with our precomputation technique, globally optimal trajectories in up to four dimensions (2d position, heading and velocity) are obtained in real-time.
modeling and 3d local estimation for in-plane and out-of-plane motion guidance by 2d ultrasound-based visual servoing. this paper presents a new model-free visual servoing that is able to servo a robotized 2d ultrasound probe that interacts with a soft tissue object. it makes direct use of the b-mode ultrasound images in order to reach a desired one. this approach does not require the 3d model of the object nor its location in the 3d space. the visual features are based on image moments. the exact analytical form of the interaction matrix relating the image moments variation to the probe velocity is modelled. to perform model-free servoing, the approach combines the image points coordinates with the probe pose to estimate efficiently 3d parameters required in the control law. the approach is validated with simulation and experimental results showing its robustness to different errors and perturbations.
robust 3d slam with a stereo camera based on an edge-point icp algorithm. most vision-based slam systems utilize corner-like features, and may be unstable in non-textured environments where only a few corner features can be extracted. to cope with this problem, we employ edge points to perform slam with a stereo camera. the edge-point based slam is applicable to non-textured environments since plenty of edge points can be obtained even from a small number of lines. the proposed method estimates camera poses and builds detailed 3d maps robustly by aligning edge points between frames using the icp algorithm. in indoor experiments, the method successfully built detailed 3d maps even under noisy condition.
design considerations and human-machine performance of moving virtual fixtures. haptic virtual fixtures have been shown to improve user performance and increase the safety of robot-assisted tasks, particularly for surgical applications. however, little research has studied virtual fixtures that provide moving force constraints based on motion of the environment, e.g., organ movement due to heartbeat or respiration. this work discusses design considerations of moving forbidden-region virtual fixtures and presents two methods of implementation: predicted-position and current-position virtual fixtures. human subject experiments were performed to determine the effectiveness of moving virtual fixtures when interacting with an object in motion using a teleoperator. results show that moving virtual fixtures can help improve user precision and decrease the amount of force applied.
design and simulation of a joint-coupled orthosis for regulating fes-aided gait. a hybrid functional electrical stimulation (fes)/orthosis system is being developed which combines two channels of (surface-electrode-based) electrical stimulation with a computer-controlled orthosis for the purpose of restoring gait to spinal cord injured (sci) individuals (albeit with a stability aid, such as a walker). the orthosis is an energetically passive, controllable device which 1) unidirectionally couples hip to knee flexion; 2) aids hip and knee flexion with a spring assist; and 3) incorporates sensors and modulated friction brakes, which are used in conjunction with electrical stimulation for the feedback control of joint (and therefore limb) trajectories. this paper describes the hybrid fes approach and the design of the joint coupled orthosis. a dynamic simulation of an sci individual using the hybrid approach is described, and results from the simulation are presented that indicate the promise of the jco approach.
the autonomous city explorer project. this video presents the autonomous city explorer (ace) project. its goal was to create a robot capable of navigating unknown urban environments without the use of gps data or prior map knowledge. the robot had to find its way solely by interacting with pedestrians and building a topological representation of its surroundings. this video outlines the necessary ingredients for successful low-level navigation on sidewalks, information retrieval from pedestrians as well as the construction of a semantic representation of an urban environment. a system architecture for outdoor localization, traversability assessment, path planning, behavior selection and topological abstraction in urban environments is presented.
fluorescent monitoring using microfluidics chip and development of syringe pump for automation of enucleation to automate cloning. we have developed a novel technique for fluorescent monitoring of a bovine oocyte nucleus for an automatic cloning device. animal cells that have been chemically softened by cytochalasin and stained with hoechst dye are aspirated into a thin microchannel of a microfluidic chip and stretched thin, allowing the nucleus of the expanded oocyte to be monitored. half the volume of the oocyte is aspirated into the thin microchannel and a high-velocity fluid flow is generated in the wide microchannel to bisect the oocyte. then, the half-oocytes are monitored to determine which contains the nucleus. to control flow velocity with high accuracy and rapid response, we also developed a syringe pump that is small, has no backlash, and has highly-accurate volume control and a good response for automatic cutting. in this report, we describe the monitoring method and construction of the syringe pump.
the "dlr crash report": towards a standard crash-testing protocol for robot safety - part i: results. after analyzing fundamental impact characteristics of robot-human collisions in our previous work, the intention in the present paper is to augment existing knowledge in this field, verify previously given statements with standardized equipment of the german automobile club (adac), and provide a crash-test report for robots in general. various new insights are achieved and a systematic and extensive set of data is provided. the presented work is divided into two papers. the main purpose of part i is to give, similarly to reports known from the automobile world1, a fact based and result oriented view on our newest robot crash-test experiments. in part ii detailed discussions of the results listed in the present paper and recommendations towards a standard crash-test protocol for robot safety are carried out.
2 dof cartesian force limiting device for safe physical human-robot interaction. this paper presents a device that significantly increases the safety level of suspended robots whose end-effector orientation remains constant with respect to the vertical direction (e.g. scara-type suspended robots). the device is a two-degree-of-freedom (dof) parallel mechanism with a parallepipedic architecture on which two revolute joints have been replaced with commercially available torque limiters. the device is implemented as a mechanical connection between the robot and the effector. it is rigid unless excessive horizontal forces are applied on the end-effector, for example during a collision. the level of force that activates the mechanism is set by properly adjusting the threshold of the torque limiters. furthermore, a collision can be rapidly detected with a limit switch placed on one of the links of the mechanism and a signal can be sent directly to brakes that will stop the robot, without passing through a controller and thus improving the reliability and reaction-time of the safety system. by mechanically disconnecting the robot from its end-effector, the device ensures that the person involved in the collision is only subjected to the inertia of the end-effector and thus potential injuries are greatly reduced. a prototype of the proposed device has been built to validate the concept and to study its behaviour for collisions with different velocities and orientations.
expansion segmentation for visual collision detection and estimation. collision detection and estimation from a monocular visual sensor is an important enabling technology for safe navigation of small or micro air vehicles in near earth flight. in this paper, we introduce a new approach called expansion segmentation, which simultaneously detects "collision danger regions" of significant positive divergence in inertial aided video, and estimates maximum likelihood time to collision (ttc) in a correspondenceless framework within the danger regions. this approach was motivated from a literature review which showed that existing approaches make strong assumptions about scene structure or camera motion, or pose collision detection without determining obstacle boundaries, both of which limit the operational envelope of a deployable system. expansion segmentation is based on a new formulation of 6- dof inertial aided ttc estimation, and a new derivation of a first order ttc uncertainty model due to subpixel quantization error and epipolar geometry uncertainty. proof of concept results are shown in a custom designed urban flight simulator and on operational flight data from a small air vehicle.
continuous 3d scan-matching with a spinning 2d laser. scan-matching is a technique that can be used for building accurate maps and estimating vehicle motion by comparing a sequence of point cloud measurements of the environment taken from a moving sensor. one challenge that arises in mapping applications where the sensor motion is fast relative to the measurement time is that scans become locally distorted and difficult to align. this problem is common when using 3d laser range sensors, which typically require more scanning time than their 2d counterparts. existing 3d mapping solutions either eliminate sensor motion by taking a "stop-and-scan" approach, or attempt to correct the motion in an open-loop fashion using odometric or inertial sensors. we propose a solution to 3d scan-matching in which a continuous 6dof sensor trajectory is recovered to correct the point cloud alignments, producing locally accurate maps and allowing for a reliable estimate of the vehicle motion. our method is applied to data collected from a 3d spinning lidar sensor mounted on a skid-steer loader vehicle to produce quality maps of outdoor scenes and estimates of the vehicle trajectory during the mapping sequences.
reactive grasping using optical proximity sensors. we propose a system for improving grasping using fingertip optical proximity sensors that allows us to perform online grasp adjustments to an initial grasp point without requiring premature object contact or regrasping strategies. we present novel optical proximity sensors that fit inside the fingertips of a barrett hand, and demonstrate their use alongside a probabilistic model for robustly combining sensor readings and a hierarchical reactive controller for improving grasps online. this system can be used to complement existing grasp planning algorithms, or be used in more interactive settings where a human indicates the location of objects. finally, we perform a series of experiments using a barrett hand equipped with our sensors to grasp a variety of common objects with mixed geometries and surface textures.
development of grip-type master hand "meistergrip". we propose a novel grip-type master hand called meistergrip that measures grip force in terms of a force vector distribution. this device is expected to allow intuitive robot manipulation using vision-based haptic-sensing technology. furthermore, it can be used for general-purpose manipulation and is tolerant to individual differences in hand size and grasping posture. we constructed meistergrip and evaluated the accuracy of the measured grip force. furthermore, we constructed and exhibited a complete robot manipulation system using meistergrip to demonstrate the possibility of using meistergrip as a general-purpose master hand.
three-dimensional measurement of objects in water by using space encoding method. in this paper, a new method for 3-d measurement of objects in water is proposed. when observing objects in water through a camera contained in a waterproof housing or observing objects in an aquarium tank filled with preserving liquid, we should solve a problem of light refraction at the boundary surfaces of refractive index discontinuity which gives image distortion. the proposed method uses a space encoding method which does not have a problem of corresponding point detection as a stereo vision system has, and is faster than spot light projection or slit light projection methods. a ray tracing technique solves the problem of image distortion caused by refractive index discontinuity. it should be noted that monochromatic light projection onto objects gives more accurate measurement than white light projection because the refractive index depends on the wavelength of the light. then, in order to measure colored objects, we should project red, green and blue light patterns onto them separately. experimental results show the validity of the proposed method.
undulatory and pedundulatory robotic locomotion via direct and retrograde body waves. the present paper explores the effect of the mechanism-substrate frictional interface on the locomotion characteristics of robotic mechanisms employing traveling waves for propulsion. for these investigations, an extended class of undulatory robotic locomotors is considered, termed pedundulatory, which augment lateral body undulations by coordinated dorso-ventral oscillations of multiple pairs of lateral paddle-shaped appendages (parapodia). we examine how, the same robotic prototype, allows the implementation of four distinct bio-inspired undulatory and pedundulatory modes of locomotion, by modifying the motion control strategy depending on the mechanism-substrate frictional interface. these modes employ retrograde or direct body waves, either standalone (giving rise to eel-like and ochromonas-like undulatory locomotion modes, respectively), or combined with appropriately coordinated substrate contact by the parapodial appendages (giving rise to centipede-like and polychaete-like pedundulatory modes, respectively). these four modes are investigated and comparatively assessed, both in simulation and via extensive experiments on granular substrates with the nereisbot prototype. our results validate the identified locomotion principles and also highlight the enhanced performance and gait repertoire of pedundulatory systems, compared to purely undulatory ones.
a probabilistic sonar sensor model for robust localization of a small-size blimp in indoor environments using a particle filter. in recent years, autonomous miniature airships have gained increased interest in the robotics community. this is due to their ability to move safely and hover for extended periods of time. the major constraints of miniature airships come from their limited payload which introduces substantial constraints on their perceptional capabilities. in this paper, we consider the problem of localizing a miniature blimp with lightweight ultrasound sensors. since the opening angle of the sound cone emitted by a sonar sensor depends on the diameter of the membrane, small-size sonar devices introduce the problem of high uncertainty about which object has been perceived. we present a novel sensor model for ultrasound sensors with large opening angles that allows an autonomous blimp to robustly localize itself in a known environment using monte carlo localization. as we demonstrate in experiments with a real blimp, our novel sensor model outperforms a popular sensor model that has in the past been shown to work reliably on wheeled platforms.
modeling rfid signal strength and tag detection for localization and mapping. in recent years, there has been an increasing interest within the robotics community in investigating whether radio frequency identification (rfid) technology can be utilized to solve localization and mapping problems in the context of mobile robots. we present a novel sensor model which can be utilized for localizing rfid tags and for tracking a mobile agent moving through an rfid-equipped environment. the proposed probabilistic sensor model characterizes the received signal strength indication (rssi) information as well as the tag detection events to achieve a higher modeling accuracy compared to state-of-the-art models which deal with one of these aspects only. we furthermore propose a method that is able to bootstrap such a sensor model in a fully unsupervised fashion. real-world experiments demonstrate the effectiveness of our approach also in comparison to existing techniques.
optimized projection pattern supplementing stereo systems. stereo camera systems are widely used in many real applications including indoor and outdoor robotics. they are very easy to use and provide accurate depth estimates on well-textured scenes, but often fail when the scene does not have enough texture. it is possible to help the system work better in this situation by actively projecting certain light patterns to the scene to create artificial texture on the scene surface. the question we try to answer in ths paper is what would be the best pattern(s) to project. this paper introduces optimized projection patterns based on a novel concept of (symmetric) non-recurring de bruijn sequences, and describes algorithms to generate such sequences. a projected pattern creates an artificial texture which does not contain any duplicate patterns over epipolar lines within certain range, thus it makes the correspondence match simple and unique. the proposed patterns are compatible with most existing stereo algorithms, meaning that they can be used without any changes in the stereo algorithm and one can immediately get much denser depth estimates without any additional computational cost. it is also argued that the proposed patterns are optimal binary patterns, and finally a few experimental result using stereo and space-time stereo algorithms are presented.
movement primitives for three-legged locomotion over uneven terrain. we propose a framework for online generation of efficient gaits on uneven terrain. a set of dynamically optimal leg swing motion primitives for irregular terrains is first constructed offline-this is done by generating minimum torque motions for various starting and ending ground configurations, extracting dominant principal components, and forming basis functions. gaits are then generated online via linear interpolation of the principal component basis functions, using a distance metric on so(3) to select the components. the algorithm is verified via dynamic simulations involving the strider, a three legged passive-walking robot. our results show that gaits using only knee-actuated leg swings are able to traverse uneven terrain of bounded variation.
interference estimated time of arrival on a 6-dof cable-driven haptic foot platform. a cable-driven locomotion interface employs two independent cable-driven haptic foot platforms constrained in six degrees of freedom (6-dof). its control system and its geometry are designed for performing a wide range of trajectories that could generate cable interferences. this paper presents and analyzes computational methods for determining which cable can be released from an active actuation state while allowing control in a minimal tension state, thereby ensuring that both platforms stay in a controllable workspace. one challaging task is to develop light and fast computational algorithms for hard real time processes included in haptic display applications. seeing that releasing a cable from an active actuation state might generate discontinuities in tension values in the other cables, this paper proposes collision prediction schemes named interference estimated time of arrival in order to reduce or completely eliminate such discontinuities.
learning motor primitives for robotics. the acquisition and self-improvement of novel motor skills is among the most important problems in robotics. motor primitives offer one of the most promising frameworks for the application of machine learning techniques in this context. employing an improved form of the dynamic systems motor primitives originally introduced by ijspeert et al. [2], we show how both discrete and rhythmic tasks can be learned using a concerted approach of both imitation and reinforcement learning. for doing so, we present both learning algorithms and representations targeted for the practical application in robotics. furthermore, we show that it is possible to include a start-up phase in rhythmic primitives. we show that two new motor skills, i.e., ball-in-a-cup and ball-paddling, can be learned on a real barrett wam robot arm at a pace similar to human learning while achieving a significantly more reliable final performance.
vibration control of a multi-link flexible robot arm with fiber-bragg-grating sensors. flexible, lightweight manipulators offer some advantages in contrast to rigid arms, such as compact and lighter drives, energy efficiency, reduced masses and costs. this paper presents a novel approach for vibration damping of a multilink flexible arm. the strain of the elastic arms is measured with fiber-bragg-grating (fbg) sensors and provides the feedback signal to dampen their flexural dynamics. a dynamic model of a three link arm is derived that accounts for the rigid and flexural dynamics including gravity. the arm vibrations are damped by nonlinear strain feedback. the controller is general and robust and its design does not require a model of the flexural dynamics. in the context of closed loop vibration control fbg sensors offer a better signal to noise ratio compared to strain gauges, which allows a higher static gain in the feedback loop with more efficient dissipation of vibrational energy. the feasibility and effectiveness of the proposed vibration control scheme in conjunction with fbg sensors is verified and analyzed in simulations and confirmed in experiments with a flexible three link robot arm.
stereo vision and terrain modeling for quadruped robots. legged robots offer the potential to navigate highly challenging terrain, and there has recently been much progress in this area. however, a great deal of this recent work has operated under the assumption that either the robot has complete knowledge of its environment or that its environment is suitably regular so as to be navigated with only minimal perception, an unrealistic assumption in many real-world domains. in this paper we present an integrated perception and control system for a quadruped robot that allows it to perceive and traverse previously unseen, rugged terrain that includes large, irregular obstacles. a key element of the system is a novel terrain modeling algorithm, used for filling in the occluded models resulting from on-board vision systems. we apply our approach to the littledog robot, and show that it allows the robot to walk over challenging terrain using only on-board perception.
waalbot: agile climbing with synthetic fibrillar dry adhesives. this video presents a palm-size climbing robot which uses synthetic fibrillar dry adhesives inspired by geckos. with fibrillar footpads, the robot is shown to climb smooth surfaces such as glass and acrylic, and surfaces with micron-scale roughness such as wood. in particular, the agility of the robot is highlighted by demonstrations of climbing, steering, and plane-to-plane transitions.
reusable electronics and adaptable communication as implemented in the odin modular robot. this paper describes the electronics and communication system of odin, a novel heterogeneous modular robot made of links and joints. the electronics is divided into two printed circuit boards: a general board with reusable components and a specific board with non-reusable components. while the general board is common to the design of every type of module, such as power, actuator, sensor and structure, the specific board is unique to each type of module. the communication system, one of the most important reusable components of odin, is based on local buses that can be extended by bridging electrical signals. the implementations of actuator and power links show that splitting the electronics into general and specific boards allows rapid development of different types of modules, and an analysis of performance indicates that the communication system is simple, fast and flexible. as the electronic design reuses approx. 50% of components between two different types of modules, we find it convenient for heterogeneous modular robots where production costs demand a small set of parts. in addition, as the features of the communication system are desirable in modular robots, we think it is suitable for such systems as well as useful for future research into flexible network topologies.
parking with the essential matrix without short baseline degeneracies. this paper addresses the problem of visual control of a mobile robot. the system consists of a calibrated camera fixed onboard a robot with nonholonomic motion constraints. the parking task is defined by a reference image taken at the target location. the proposed control law is based on the essential matrix, but unlike traditional methods, it is not used to compute pose parameters. instead, the control law is defined directly in terms of individual entries of the essential matrix by means of the input-output linearization of the system. here we solve the problem of degeneracies due to short baseline by taking advantage of the planar motion constraint of the robot. thus, a virtual target is defined providing a stable estimation of the essential matrix without degeneracies despite short baseline.
capsular microrobot using directional friction spiral. most researches on internal mobile robot are going on based on the invasive clamping functions which generate the propulsion through a direct contact with organic tubes. this paper proposes a novel locomotion mechanism, which moves fundamentally based on a spiral profile and generates the additional force by transferring the rotational movement to the linear movement. the essence of proposed mobile microrobot is development of a rotation-linear movement interface mechanism and a non-invasive clamping function. this paper introduces the working principle and analyzes the behavior of mobile robot. finally we validate the performance of robot as non-invasive locomotion mechanism by experiments.
large motion range magnet levitation using a planar array of coils. we have formulated a method and implemented a device for magnetic levitation with a translation range which is at least twice as large as the dimensions of the levitated body in all directions. the motion range can be extended to any distance in the horizontal plane by adding more coils to the actuator array, and the rotation is potentially unlimited in all directions.
head motion stabilization during quadruped robot locomotion: combining dynamical systems and a genetic algorithm. the head shaking that results from robot locomotion is important because it difficults stable image acquisition and the possibility to rely on that information to act accordingly, for instance, to achieve visually-guided locomotion. in this article, we focus on the development of a head controller able to minimize the head motion induced by locomotion itself. specifically, we propose a combined approach to generate head movement stabilization on a quadruped robot, using central pattern generators (cpgs) and a genetic algorithm. head movement is generated by cpgs which are modelled as autonomous differential equations. this approach allows to explicitly specify parameters such as amplitude, offset and frequency of movement and to smoothly modulate the generated trajectories according to changes in these parameters. it is therefore easy to combine the cpg with an optimization method. a genetic algorithm determines the best set of parameters that generates the head movement that reduces the head shaking caused by locomotion. experimental results on a simulated aibo robot demonstrate that the proposed approach generates head movement that does not eliminate but reduces the one induced by locomotion.
stability / precision improvement of 6-dof visual servoing by motion feedforward compensation and experimental evaluation. this paper deals with position-based 6-dof visual servoing. with a common sense of feedback control, we stress that improvement of the dynamics of the sensing unit is important for a stable visual servoing. we propose a method to improve dynamics in visual recognition, with compensating the fictional motion of the target in the camera images based on kinematics of the manipulator, by extracting the real motion of the target. we named it as hand-eye motion feedforword (mff) method. the enhanced dynamics of recognition gave further stability and precision to the total visual servoing system, evaluated by full 6-dof servoing experiment using 7- link manipulator. the convergence time in step response was about 10[s] and precise visual servoing to a moving target object has been achieved.
non-grasp manipulation of deformable object by using pizza handling mechanism. this paper discusses the non-grasp dynamic manipulation of a deformable object inspired by the handling mechanism of pizza master. the master handles a tool where a plate is attached at the tip of a bar, and he remotely manipulates a pizza on the plate. we found that he aggressively utilizes two dofs (degrees of freedom), such that the linear motion along the bar and the rotational one around the bar, in order to produce quick plate motions for dynamically manipulating the object. applying this handling mechanism to the robot system, we first show how to rotate an object by using the two dofs of plate motion. we then reveal that the deformation of the object generated by dynamic effects can drastically contribute to high-speed and stable rotation, just like human steps for turn on the floor. by both simulation and experiment, we show that there exists the optimum plate motion leading to the maximum rotational speed of the object.
the airwand: design and characterization of a large-workspace haptic device. almost all commercially available haptic interfaces share a common pitfall, a small shoebox-sized workspace; these devices typically rely on rigid-link manipulator design concepts. in this paper we outline our design for a new kinesthetic haptic system that drastically increases the usable haptic workspace. we present a proof-of-concept prototype, along with our analysis of its capabilities. our design uses optical tracking to sense the position of the device, and air jet actuation to generate forces. by combining these two technologies, we are able to detach our device from the ground, thus sidestepping many problems that have plagued traditional haptic devices including workspace size, friction, and inertia. we show that optical tracking and air jet actuation successfully enable kinesthetic haptic interaction with virtual environments. given an appropriately large volume high-pressure air source, and a reasonably high speed tracking system, this design paradigm has many desirable qualities when compared to traditional haptic design schemes.
a compact soft actuator unit for small scale human friendly robots. this paper presents the development of a new compact soft actuation unit intended to be used in multi degree of freedom and small scale robotic systems such as the child humanoid robot "icub" [1]. compared to the other existing series elastic linear or rotary implementations the proposed design shows high integration density and wider passive deflection. the miniaturization of the newly developed high performance unit was achieved with a use of a new rotary spring module based on a novel arrangement of linear springs. the model and the control scheme of the actuator are analysed. the proposed control scheme is a velocity based controller that generates command signals based on the desired simulated stiffness using the spring deflection state. the overall system is evaluated with experimental trials performed using a prototype unit. preliminary results are presented to show that the unit and the proposed control scheme are capable of replicating virtual impedances within a wide range and with good fidelity.
model and parameter identification of friction during robotic insertion of cochlear-implant electrode arrays. robot-assisted cochlear implant surgery was proposed and proved to be efficient in reducing insertion forces on acrylic scala tympani models. during experiments, the authors discovered that the insertion force not only depends on the shape discrepancy between the scala tympani and the inserted electrode array, but also on the insertion speed. this paper presents a friction model that describes the whole insertion process and investigates the relationship between the insertion speed and the insertion force. experimental and statistical results show the effectiveness of the model. applying the friction model generates safety insertion force boundaries for future insertions and gives the optimal insertion speed. it also provides predictive force information for insertion speed feedback control law design which may be applied to robot-assisted cochlear implant surgeries.
object classification based on a geometric grammar with a range camera. this paper proposes an object classification framework based on a geometric grammar aimed for mobile robotic applications. the paper first discusses the geometric grammar as a compact representation form for object categories with primitive parts as its constituent elements. the paper then discusses the object classification implemented as parsing of primitive parts. in particular, two approaches are discussed that constrain the search space in order to render the parsing of the primitive parts practical. the two approaches are experimentally verified, first, for a generic object category of chair applied to real range images acquired with a range camera mounted on a mobile robot and, second, for multiple generic object categories applied to synthetic range images. the experimental results show the practicability of the framework.
study of a 2-dof joint for the small active cord mechanism. the active cord mechanism (acm) such as a snake-like robot is suitable for tasks in a narrow environment because of its slender body, but mechanical models developed in prior research were somewhat large for practical usage. in this paper, we propose a new 2-dof joint mechanism for the small acm. a usual joint mechanism has the same number of rotational axes as that of the actuators, but the proposed mechanism has 4 rotation axes against 2 actuators. this joint mechanism has relatively large range of motion and it can improve the capability of acm in a narrow environment. we verified the specification of the proposed mechanism and the result showed that it is suitable for the small acm. in addition, we developed the acm with the proposed joint mechanism, and it realized a sidewinding motion, which is a kind of snakes' locomotion style. we think this result shows that the proposed mechanism will contribute to the study of the small acm.
mechatronic design of nao humanoid. this article presents the mechatronic design of the autonomous humanoid robot called nao that is built by the french company aldebaran-robotics. with its height of 0:57m and its weight about 4:5 kg, this innovative robot is lightweight and compact. it distinguishes itself from existing humanoids thanks to its pelvis kinematics design, its proprietary actuation system based on brush dc motors, its electronic, computer and distributed software architectures. this robot has been designed to be affordable without sacrificing quality and performance. it is an open and easy-to-handle platform. the comprehensive and functional design is one of the reasons that helped select nao to replace the aibo quadrupeds in the 2008 robocup standard league.
distributed beamforming in relay-assisted multiuser communications. this paper considers a communication network with multiple pairs of source and destination, assisted by multiple relays. it is assumed that perfect channel state information (csi) is available at the relays. in a two-stage af protocol, all the sources broadcast their signals to all the relays in the first stage. the received signal at each relay is processed by a beamforming weight and then re-broadcasted to all the destinations at the same time with other relays in the second stage. the focus is to find the optimal beamforming weights to meet a given set of target signal-to-interference-and-noise ratio (sinr) at the destinations, while minimizing the total transmitted power at the relays. we show that this problem can be formulated as a nonconvex quadratically constrained quadratic program (qcqp). through relaxations, the problem can be solved efficiently by convex programming.
compact dfa structure for multiple regular expressions matching. new applications such as real-time deep packet inspection require high-speed regular expression (regex) matcher, and the number of regexes in pattern store is increasing to several thousands, which requires a memory efficient solution. in this paper, a kind of hardware based compact dfa structure for multiple regexes matching called cpdfa is presented. according to statistics of regexes in snort and l7-filter rules, transitions from each state to its next states are not evenly distributed. the summation of transitions from each state to its top three most popular next states takes about 90% of all the transitions. therefore, cpdfa employs an indirect index table to represent transitions to top three most popular next states more efficiently. the remaining transitions which take about 10% of all the transitions are stored in direct transition table or k parallel srams according to the number of remaining transitions from the same state is more than k or not. simulation shows that cpdfa structure can save about 90% of memory storage comparing with the original dfa structure. by using pipelined architecture in fpga, cpdfa can advance one character in one memory access cycle.
detection of jamming attacks in wireless ad hoc networks using error distribution. mobile ad hoc networks are a new wireless networking paradigm for mobile hosts. unlike traditional mobile wireless networks, ad hoc networks do not rely on any fixed infrastructure. instead, hosts rely on each other to keep the network connected. the military tactical and other security-sensitive operations are still the main applications of ad hoc networks. one main challenge in design of these networks is their vulnerability to denial-of-service (dos) attacks. in this paper, we consider a particular class of dos attacks called jamming. the objective of a jammer is to interfere with legitimate wireless communications. a jammer can achieve this goal by either preventing a real traffic source from sending out a packet, or by preventing the reception of legitimate packets. we propose in this study a new method of detection of such attack by the measurement of error distribution.
subband adaptive array with reduced pilot signal using maximal ratio combining scheme. this paper presents a subband adaptive array (sbaa) with reduced pilot signal based on maximal ratio combining (mrc) scheme. by the subband processing, mrc design based on eigenfiltering which is widely used in frequency flat environments could be applied to frequency selective channels, but the efficient synthesis of output signal through the inverse dft (discrete fourier transform) is disturbed by the nonuniqueness of eigenvectors. in the proposed method, a two-step approach is adopted to solve this problem: in the first step, we use simple compensation of weight uncertainty with short (or possibly no) pilot signal and derive a hard-decision temporary output. then in the second step, the output data is used as a training sequence to determine optimum compensation. it is shown through computer simulations that the proposed scheme improves the transmission rate of sbaa scheme keeping good performance, and some fundamental features are also investigated.
self-actuation of camera sensors for redundant data elimination in wireless multimedia sensor networks. with the increasing interest in the deployment of wireless multimedia sensor networks (wmsns), new challenges arouse with effective use of camera sensors to provide maximized event coverage with the least amount of redundancy in the collected multimedia data. given that the processing and transmission of multimedia data are costly in terms of energy, camera sensors should only be actuated when an event is detected within their vicinity. while achieving maximum coverage with such actuation is desirable, multiple camera sensors' field-of-view (fov) can be covering the same spots and thus redundant multimedia data can unnecessarily be sent to the base-station. in this paper, assuming camera sensors with fixed orientation, we propose a low-cost distributed actuation scheme which strives to turn on the least number of camera sensors to avoid possible redundancy in the multimedia data while still providing the necessary event coverage. the basic idea of this distributed scheme is the collaboration of camera sensors that have heard from scalar sensors about an occurring event in order to minimize the possible coverage overlaps among their fovs. the scheme requires only 1-hop information for camera sensors and its messaging overhead is negligible. through simulation, we show how the distributed scheme performs with respect to the cases when all the cameras within the vicinity or the region are actuated and assess the performance under various conditions.
spectrum sensing design framework based on cross-layer optimization of detection efficiency. cross-layer optimization of the spectrum sensing (ss) sub-system in a cognitive radio (cr) is essential for achieving the best spectrum utilization because the three ss layers - sensing radio, sensing phy and sensing mac - jointly determine the overall performance of the ss sub-system. in this paper we introduce a function called detection efficiency that measures how much of the idle primary user spectra is actually utilized by the cr users as a function of regulatory constraints, network specifications and the parameters of the sensing radio, mac and phy. by optimizing these parameters to maximize detection efficiency of the ss system, the designer can compare and select the best ss design for a given wireless network requirement. by applying this design method to evaluate several design options for the ss layers, we show that cross-layer optimization can in some cases improve the detection efficiency (and therefore spectrum utilization) from 35% to as much as 99%.
distributed multi-source transmission in wireless mobile peer-to-peer networks: a restless bandit approach. in wireless mobile peer-to-peer (p2p) networks, multiple sources can provide multimedia file sharing at the same time. the selection of multiple sources is one of the key issues in the design of a multi-source transmission system in wireless mobile p2p networks. in this paper, we propose a distributed multi-source sender selection scheme to maximize the receiving data rate and minimize the energy consumption. our scheme is based on recent advances in restless bandit algorithms. the proposed sender selection scheme has an indexability property that dramatically simplifies the computation and implementation of the policy. in addition, there is no need for a centralized control point, and senders can join and leave from the wireless mobile p2p network freely. simulation results show that the proposed scheme improves the receiving data rate and energy consumption performance significantly compared to the existing scheme.
acns: adaptive complementary neighbor selection in bittorrent-like applications. bittorrent, one of the most popular peer-to-peer file sharing applications, accounts for a large proportion of the total internet traffic. while its appearance benefits the content distributors and users, the traffic injected into the network backbone has become a great challenge for the isps. in this paper, we study traffic shaping in bittorrent-like applications to improve traffic locality and enable fast data delivery. to this end, a piece complementary index is introduced based on the piece demand between peer nodes. then, we propose an efficient and adaptive neighbor selection scheme (acns). according to acns, each node self-adaptively chooses the most complementary peers to connect with and download file pieces, rather than having a fixed number of outside neighbors. our scheme can be integrated with the bittorrent protocol by slight modifications, and requires no additional infrastructure provided by isps. experimental results based on extensive simulations have shown the effectiveness of acns. compared with the fixed biased neighbor selection scheme, ancs cuts down the cross-isp traffic by more than 31% and improves the download rate by about 15%.
analysis of duopoly price competition between wlan providers. with the rapid development of wireless internet services, several wlan service providers may coexist in one public hotspot to compete for the same group of customers, leading to an inevitable price competition. the charged price and the provisioned packet loss at each provider are major factors in determining users' demands and behaviors, which in turn will affect providers' revenue and social welfare. in this paper, we set up a novel game model to analyze a duopoly price competition. we first show the users' demands are distributed between providers according to a wardrop equilibrium and then prove the existence of a nash equilibrium on providers' charged prices. through analysis, we further find that in nash equilibrium state the social welfare is very close to its maximal value in cooperative situation. furthermore, the providers' aggregate revenues also do not decrease when the users have high sensitivity about the charged prices. thus the competitive duopoly wlan market can still run in an efficient way even in the absence of complex regulation schemes.
short-length raptor codes for mobile free-space optical channels. free-space optical (fso) links are competitive wireless links offering high data rate, security and low system complexity. for mobile applications, e.g., from a ground base station to an unmanned aerial vehicle (uav), the fso channel can suffer from severe instantaneous misalignment. this time varying misalignment is unknown to the transmitter and causes data packet corruption and erasure. as a result, the application of traditional fixed-rate erasure coding techniques is difficult. in this paper, we consider the application of rateless raptor codes for such mobile fso channels. due to the high data rates required, short-length (16-1024) raptor codes are designed and simulated on a severe jitter fso channel. a key advantage of raptor codes is their independence on channel state, no matter how large the misalignment. with a 1 gbps transmitter, the designed raptor code with k = 64 message packets offers 560 mbps data rate and decoding cost of 4.14 operations per packet when transmitting power is 20 dbm. in contrast, a traditional automatic repeat-request (arq) algorithm technique on the same fso jitter channel achieves a rate of 60 mbps.
localized sensor self-deployment for guaranteed coverage radius maximization. focused coverage is defined as the coverage of a wireless sensor network surrounding a point of interest (poi), and is measured by coverage radius, i.e., minimum distance from poi to uncovered areas. sensor self-deployment algorithm grg is designed for autonomous focused coverage formation. it however does not always produce optimal (i.e., maximized) coverage radius. in this paper, we propose optimized grg, referred to as ogrg, for guaranteed coverage radius maximization, and evaluate its performance in comparison with grg.
a semidefinite relaxation approach to efficient soft demodulation of mimo 16-qam. three computationally-efficient list-based soft mimo demodulators are developed, each of which generates its list using the randomization procedure associated with the semidefinite relaxation (sdr) of a particular hard demodulation problem. the structure of this sdr depends on the signaling scheme, and we will focus on 16-qam signaling. the key step in the development of the first two demodulators is the derivation of polynomial expressions for the extrinsic information provided by the decoder. these expressions enable this information to be incorporated into the sdr framework. the resulting "list-sdr" demodulators require one semidefinite program (sdp) to be solved at each demodulation-decoding iteration. in the proposed "single-sdr" demodulator this requirement is reduced to one sdp per channel use by deriving an approximation of the randomization procedure used by the list-sdr demodulator and showing that this approximation enables the decoupling of the processing of the channel measurement from that of the extrinsic information from the decoder. simulation results show that the proposed demodulators provide considerable reductions in computational cost over several existing soft demodulators, and that these reductions are obtained without incurring a substantial degradation in performance.
cycle synchronizing approach for sleep mode operation in wimax system. based on the "green concepts", lots of research has been performed to efficiently reduce the power consumption of mobile communication systems. correspondingly, ieee 802.16e has specified sleep mode operations depending on different types of power saving class for the purpose of energy saving. to solve the inefficient problem of multiple power saving classes over the same ms, this paper proposes a cycle synchronizing method to minimize the energy consumption of the ms while keeping the qos requirements satisfied. the analytical models are derived for performance evaluation of the parallel power saving classes in sleep mode operation. furthermore, performance improvement of the proposed method has been validated in a developed wimax simulation platform based on ns-2 network simulator.
merging spanning trees in tomographic network topology discovery. tomographic techniques allow the reconstruction of network topologies with no need for cooperation from internal routers. however, most of such mechanisms adopt a method of node clustering producing trees that reveal only a partial structure of the network. therefore, we have proposed a novel approach to topology discovery based on packet sandwich probes and decision theory allowing to retrieve a complete picture of the network, which includes the detection of all the internal nodes along with the values of capacities of the interconnecting links. such an approach, as well as all the standard techniques of topology discovery, reconstructs the spanning tree of the probe sender only. hence, in this paper a specific technique is presented for merging the spanning trees associated to all different roots, in order to provide a complete representation of the network. such a method does not require further probing traffic and is specifically designed to merge topology reconstructions where all the nodes of the network (not only the branching nodes) are revealed, along with link capacities. our algorithm performs quite well on a wide set of both synthetic and realistic topologies, and in many cases provides a picture of the network which is exactly equivalent to the original one.
on the effect of power amplifier nonlinearity on mimo transmit diversity systems. nonlinearity of high-power amplifier (hpa) plays a crucial role in the performance of multiple-input multiple-output (mimo) systems. in this paper, we investigate the performance of mimo orthogonal space-time block coding (stbc) systems in the presence of nonlinear hpa. specifically, we assess the impact of hpa nonlinearity on the average symbol error probability (sep), total degradation (td), and system capacity of orthogonal stbc in uncorrelated nakagami-m fading channels. numerical results are provided and show the effects of several system parameters, such as the output back-off (obo) of nonlinear hpa, numbers of transmit and receive antennas, and modulation order of quadrature amplitude modulation (qam), on performance.
enabling differentiated qos based on cross-layer optimization in wireless ad hoc networks. many optimization theoretic based bandwidth allocation strategies have been developed for guaranteeing some levels of quality of service (qos) for some classes of competing real-time users in wireless ad hoc networks. by considering different objective functions (such as congestion level, constrained delay and so on), the researchers propose some optimization frameworks by which the problem can be solved. the rapid increase in the development of different real-time applications with stringent maximum packet loss requirements in such environments and the existence of difficulties in satisfying the pre-specified qos limits, is a great motivation for designing some type of differentiated qos guaranteeing mechanisms that can satisfy the demands of this class of the real-time traffics. in the current work, a cross-layer technique is being introduced in which, based on the packet loss information from the lower layers, some optimal bandwidth is assigned to the real-time applications which need some levels of the maximum packet loss guaranties. as, each real-time application needs a different level of maximum packet loss guarantee, a weighted aggregate packet loss objective function is being introduced. the weights are proportional with the importance of the packet loss mitigation for a specific application. the simulation results verify the claims.
modeling and analysis for proactive-decision spectrum handoff in cognitive radio networks. spectrum handoff occurs when the primary users appear in the licensed band occupied by the secondary users. spectrum handoff procedures aim to help the secondary users to vacate the occupied licensed spectrum and find suitable target channel to resume the unfinished transmission. in this paper, we discuss how to select the target channels to minimize the total service time with multiple spectrum handoffs. we propose a preemptive resume priority (prp) m/g/1 queueing network model to evaluate total service time for various target channels selections. then, we suggest a low-complexity greedy algorithm to select target channels. numerical results show that a spectrum handoff scheme based on greedy selection strategy can reduce total service time compared to the randomly selection scheme.
graph matching based side information generation for distributed multi-view video coding. in this paper, we adopt constrained relaxation for distributed multi-view video coding (dmvc). the novel framework integrates the graph-based segmentation and matching to generate inter-view correlated side information without knowing the camera parameters. moreover, graph-based representations of multi-view images are incorporated to form more distinctive feature constraints. the sparse data as a good hypothesis space aim for a best matching optimization of inter-view side information with compact syndromes, from inferred relaxed coset. the plausible filling-in from a priori feature constraints between neighboring views could reinforce a promising compensation to inter-view side information generation for joint multi-view decoding. in order to find distinctive feature matching with a more stable approximation, pca-sift and tps (thin plate spline) are adopted to reduce the dimension of sift descriptors and construct a more accurate inter-view motion model. the experimental results validate the high estimation precision and the rate-distortion improvements.
asymptotic analysis and design of multiuser cooperative ds-cdma systems. the performance of a cooperative multiuser direct-sequence code-division multiple-access (ds-cdma) system is analyzed in the asymptotic regime where both the spreading codes and the number of users grow large with the same ratio. a simple signal-to-interference-plus-noise ratio (sinr) expression is derived that is independent from the spreading codes and explicitly accounts for the effects of the multiple-access interference (mai) and the relay noise. the so-obtained sinr expression is then computed based entirely on the available local information. the results obtained above are then used to optimally design the cooperative system. in particular, it is shown how the amount of cooperation between each collaborating pair can be adjusted to simultaneously achieve a preassigned target sinr for both users. based on the local information, the globally optimal amount of the relay power is also obtained that maximizes the achieved sinr at the access point.
information theoretic approach for characterizing spam botnets based on traffic properties. in this paper, we present several novel identifying characteristics of spam-sending bots (or spambots) based on traffic statistics. we use the entropy to measure the distribution skewness for a number of traffic features including packet inter-departure time, email per recipients, rate of change in recipient list and destination domains, and inconsistency in email header information of the outgoing email traffic. we also show how we can measure the deviation in these features from benign emails traffic to decisively detect spambots. our tool is developed to sit anonymously behind the mail server in a network, capturing smtp data packets and analyzing the traffic while keeping all of the personal email data private and unrecoverable. unlike content filtering, our technique is hard to evade and used to detect spam email close to the source. in addition, our technique uses on-line light weight calculations and can be efficiently deployed in the end-user or isp devices as well. we evaluated our technique using about 6 million email records of real spambot traffic collected during june 2007 - june 2008. our evaluation results show that our tool can detect spambots accurately and efficiently even with high traffic volume.
active queue management for mac client implementation of resilient packet rings. the ieee 802.17 is a standardized ring topology network architecture, called the resilient packet ring (rpr), to be used mainly in metropolitan and wide area networks. this paper focuses on the rpr mac client implementation of the ieee 802.17 rpr mac in the aggressive mode of operation and introduces a new active queue management scheme for ring networks that achieves higher overall utilization of the ring bandwidth with simpler and less expensive implementation than the generic implementation provided in the standard. the scheme introduced in this paper provides performance comparable to the per destination queuing implementation, the best achievable performance.
robust amc scheme against feedback delay in vehicular environment. adaptive modulation and coding (amc) scheme suffers performance degradation with the signaling feedback delay, as channel state information (csi) is outdated with time variant channel. in this paper, we propose a robust amc scheme to mitigate the effect of signaling feedback delay, especially in vehicular environments. channel information estimated in current time interval is utilized to obtain the distribution of channel fading in upcoming time interval. average block error rate (bler) for given modulation and coding scheme (mcs) is derived. simulation results indicate that the proposed scheme guarantees reliable performance even in a vehicular environment with maximum doppler frequency shift of 300hz.
radar sensor network using a new triphase coded waveform: theory and application. in radar sensor network (rsn), interference with each radar can be effectively reduced when waveforms are properly designed. in this paper, we firstly perform some theoretical studies on co-existence of phase coded waveforms in rsn. then we give the definition of a new set of triphase coded waveforms called optimized punctured zero correlation zone sequence-pair set (optimized punctured zczps) and analyze their properties especially their optimized cross correlation property of any two sequence-pairs in the set. furthermore, we apply our newly provided triphase coded waveforms and equal gain combination technique to the system simulation, and study the performances versus different number of radars in rsn, with doppler shift or not. simulation results show that detection performances of multiradars (utilizing our optimized punctured zczps and equal gain combination), either under the doppler shift condition or not, are superior to those of singler radar.
a chaotic maps-based key agreement protocol that preserves user anonymity. a key agreement protocol is a protocol whereby two or more communicating parties can agree on a key or exchange information over an open communication network in such a way that both of them agree on the established session keys for use in subsequent communications. recently, several key agreement protocols based on chaotic maps are proposed. these protocols require a verification table to verify the legitimacy of a user. since this approach clearly incurs the risk of tampering and the cost of managing the table and suffers from the stolen-verifier attack, we propose a novel key agreement protocol based on chaotic maps to enhance the security. the proposed protocol not only achieves mutual authentication without verification tables, but also allows users to anonymously interact with the server. moreover, security of the proposed protocol is modelled and analyzed with petri nets. our analysis shows that the proposed protocol can successfully defend replay attacks, forgery attacks, and stolen-verifier attacks.
joint optimization of placement and bandwidth reservation for relays in ieee 802.16j mobile multihop networks. mobile multihop relay (mmr) networks based on the ieee 802.16j standard are able to extend the service area as well as improve the performance of mobile wimax networks. we present an optimization framework for jointly optimizing the placement and bandwidth reservation for a relay station in an mmr network. the objective of this framework is to maximize utility of the mmr network service provider. the decision on the placement of the relay corresponds to finding the best location for the relay station under uncertainty about the number of active users in the extended service area of the mmr network. this uncertainty could be due to random connection initiation and termination by the users or due to the random arrivals and departures of the mobile subscriber stations in the extended service area. however, this decision on relay placement may not achieve the highest utility when the users dynamically adapt their decisions on whether to transmit directly to the base station or transmit through the relay station. in this scenario, optimal decision on bandwidth reservation by the relay station needs to be made (over a relatively shorter period of time) which takes the dynamics of users' decision into account. the placement of the relay station (over a relatively longer period of time) can then be optimized based on the optimal bandwidth reservation. a stochastic programming formulation and a markov decision process formulation are used to obtain the long-term and short-term optimization solutions, respectively.
optimal channel sensing in wireless communication networks with cognitive radio. in this paper, designing channel sensing policies for cognitive radio networks is discussed. a discrete-time semi-markov channel model is first introduced, which facilitates the analysis on more general channel occupancy behaviors and possible asynchronism among primary and secondary users. based on the characteristics of the channels at the stationary state, multiple channel sensing policies have been proposed for different network scenarios with homogeneous channels, heterogeneous channels, and sequential channel sensing. both analytical and simulation results are given to demonstrate the effectiveness of the proposed channel sensing policies.
energy-aware utility regions: multiple access pareto boundary. power management and energy-awareness has become popular in mobile computing as well as mobile communications. in future wireless communication systems, the energy efficiency of terminals and base stations has to be improved. therefore, we propose a new utility function which is the difference of the capacity and a weighted power cost term. next, the utility region for single-antenna and multi-antenna multiple access channels is characterized. we show that the siso mac utility region is convex and provide a closed form expression for the pareto boundary. we need the pareto boundary to compute efficient operating points. furthermore, an iterative algorithm is developed for weighted sum utility maximization in miso and mimo mac. all results are illustrated in discussed by numerical simulations.
message origin authentication and integrity protection in chaos-based optical communication. the construction of quantum computers forms the major threat against the security of modern communication systems, as anyone who can build a large quantum computer can break today's most popular cryptosystems. given the central role of information security in the deployment of modern systems, the preparation of the cryptographic world for a future of quantum computers is imperative. in this context, several alternatives have been proposed, mainly basing their security on the laws of physics. one of the most promising technologies is the optically generated chaos-based cryptography. one of its main advantages is that it can be combined with the technology of optical communication networks in a natural way. in this paper, we propose a message authentication and integrity protection scheme based on optically generated chaos. the new scheme is coming to complete a recently introduced solution, for data confidentiality based on optical chaos.
system spectral efficiency and stability of 3g networks: a comparative study. cdma2000, wcdma and wimax are three widely used 3g technologies. since they share the same goal, which is to provide broader coverage and higher throughput in 3g networks, an impartial comparison of their performance is indispensable. however, they are based on different design principles and methodologies, which make the comparison challenging. this paper presents a comparative study of these technologies, with focus on system spectral efficiency and stability in 3g networks. specifically, the paper presents a framework for the comparison based on the common set of configurations adopted by these technologies, which include channel models, system parameters and key algorithms. through extensive simulations, the system spectral efficiency and stability of cdma2000 1x evdo rev.a, wcdma hsdpa/hsupa and mobile wimax are compared. it is found that while wimax can provide highest throughput, the two cdma-based technologies achieve higher system spectral efficiency, especially on the downlink. regarding system stability, it is observed that cdma2000 1x ev-do rev.a can operate under higher interference levels than wcdma hsdpa/hsupa and mobile wimax. in addition, the comparison on system spectral efficiency between cdma2000, wcdma and wimax is also conducted when relevant enhanced technologies, i.e., mimo and interference cancelation, are adopted. we believe that our work will serve as a cornerstone for a fair comparison between the various technologies for prospective 3g networks.
fpga design of box-constrained mimo detector. in this paper, a box-constrained mimo detector is considered that allows simple fpga implementation and provides improvement in the detection performance compared to the mmse detector. the box-constrained detector is implemented using dichotomous coordinate descent iterations. we investigate the design throughput against the ber performance and the design complexity in terms of the number of logic slices. the proposed design requires as few as 637, 658, and 667 slices for 4 × 4, 8 × 8, and 16 × 16 mimo systems, respectively, which is significantly less than that required by known designs of the mmse detector.
spatial multiplexing with mrc and zf receivers in ad hoc networks. this paper investigates the performance of point-to-point spatial multiplexing with stream control and slotted aloha in ad hoc networks. in particular, we derive new closed-form outage probability, network throughput and transmission capacity expressions for spatial multiplexing with maximum-ratio-combining (mrc) and zero forcing (zf) receivers. from these expressions, we show that the relative throughput of mrc and zf receivers is dependent on node intensity and sinr threshold levels. in addition, we present a new transmission capacity scaling law for zf receivers, which shows that increasing the number of transmitted data streams can either increase or decrease the transmission capacity depending on the path loss exponent and number of receive antennas. we also present conditions such that the transmission capacity using spatial multiplexing with zf receivers is greater than orthogonal space time block codes.
crystallized rates region of the interference channel via correlated equilibrium with interference as noise. treating the interference as noise in the n-user interference channel, the paper describes a novel approach to the rates region, composed by the time-sharing convex hull of 2n -1 corner points achieved through on/off binary power control. the resulting rates region is denoted crystallized rates region. by treating the interference as noise, the n-user rates region frontiers has been found in the literature to be the convex hull of n hyper-surfaces. the rates region bounded by these hypersurfaces is not necessarily convex, and thereby a convex hull operation is imposed through the strategy of time-sharing. this paper simplifies this rates region in the n-dimensional space by having only an on/off binary power control. this consequently leads to 2n - 1 corner points situated within the rates region. a time-sharing convex hull is imposed onto those corner points, forming the crystallized rates region. the paper focuses on game theoretic concepts to achieve that crystallized convex hull via correlated equilibrium. in game theory, the correlated equilibrium set is convex, and it consists of the time-sharing mixed strategies of the nash equilibriums. in addition, the paper considers a mechanism design approach to carefully design a utility function, particularly the vickrey-clarke-groves auction utility, where the solution point is situated on the correlated equilibrium set. finally, the paper proposes a self learning algorithm, namely the regret-matching algorithm, that converges to the solution point on the correlated equilibrium set in a distributed fashion.
dynamic pre-allocation harq (dp-harq) in ieee 802.16j mobile multihop relay (mmr). ieee 802.16 is defining standards for mobile multihop relay (mmr). the major purpose of mmr is to efficiently extend the coverage of a bs and to enhance the system throughput. relay station (rs) has been introduced to fulfill this goal. however, packets in mmr would have a large probability of failure transmission because not all links over the multihop path are in good channel condition. therefore, hybrid automatic repeat request (harq) has been designed to increase the reliability in multihop transmission. however, the retransmission mechanism proposed in 802.16j is not efficient. it will result in high packet delay. in this paper, we propose dynamic pre-allocation harq (dp-harq) which pre-allocates bandwidth for harq. therefore, the packet delay is reduced significantly. the pre-allocated bandwidth is dynamically adjusted so the channel utilization will not be degraded much. we also propose mathematical models to analyze the proposed dp-harq. the analysis is validated by extensive simulations. results show that the proposed dp-harq can reduce packet delay and jitter significantly.
adaptive exponential beacon period protocol for power saving in delay tolerant networks. in this paper, a new power saving mechanism in delay/disruption tolerant networks is designed. by exploiting the intermittent connection characteristic of delay/disruption tolerant network in synchronized clock based scenario, an adaptive exponential beacon protocol is proposed where the beacon periods of nodes are independently adjusted depending on the trend of contact availability. the proposed protocol is optimized for different network environments using distribution of contact durations. simulation results show that power savings up to 35 percent are achieved compared with existing power saving protocols, while maintaining similar average packet delays and packet delivery ratios to that without a power management.
block detection of multiple symbol dpsk in a statistically unknown time-varying channel. we present a detection scheme for multiple-symbol dpsk for use in a statistically unknown time-varying channel. the scheme relies on a parametric representation of the time-varying channel, resulting in a reduction in the number of parameters required to be determined by optimizing a maximum likelihood sequence estimation (mlse) type cost function. we also present a reduced-complexity version of the detection scheme based on sphere decoding. analysis and simulations show good performance in rayleigh fading over varying degrees of channel time-variation for an appropriately selected channel parameterization.
on achieving cost-sensitive anomaly detection and response in mobile ad hoc networks. in mobile ad hoc networks (manet), anomaly detection and response system (adrs) plays a paramount role in diagnosing anomalous events, which are resulted by both accidental system errors and intentional attacks. while a variety of adrs is ready for deployment, there lacks a sound and formal way to examine their operational characteristics for selecting the most appropriate ones with particular concerns. to that end, this paper develops a decision-theoretical framework to identify the fundamental tradeoffs between the key evaluation metrics of adrs in manet, along with a formal method to optimize the overall performance of adrs in terms of those metrics of concern. in particular, each adrs sensor is treated as an autonomous agent, making its decision as the local operational environment and a global signal that estimates the performance of adrs as a whole, in terms of detection performance (detection accuracy and false positive rate) and operational cost (detection cost and response cost). the theoretical framework then serves as a basis for developing policy gradient algorithms for practically and automatically inferring the optimal behavior of adrs sensors. a set of simulations is conducted for validating the feasibility and evaluating the performance of our proposed framework.
joint flow control, routing and medium access control in random access multi-hop wireless networks. in wireless multi-hop networks, the allocation of resources is influenced by mechanisms for medium access control (mac), routing, congestion control, and flow control. designing these mechanisms jointly can increase the capacity of wireless networks. we attempt to introduce routing into an existing framework for the joint design of flow control and mac on random access multi-hop wireless networks. the problem of joint flow control, routing and mac in random access multi-hop wireless network is formulated as an optimization problem. however, a direct formulation yields a non-convex optimization problem. to overcome the difficulty in solving a nonconvex problem, we introduce a harmonic rate function to convexify the formulation. the joint optimization mechanism is presented as an iterative process to compute a solution. the resultant distributed algorithm is proved to yield a global optimal solution when it converges. numerical results are provided to show the convergence of the proposed algorithm and properties of the harmonic rate function.
characterising the behaviour of ieee 802.11 broadcast transmissions in ad hoc wireless lans. this paper evaluates the performance of the ieee 802.11 broadcast traffic under both saturation and nonsaturation conditions. the evaluation highlights some important characteristics of ieee 802.11 broadcast traffic as compared to corresponding unicast traffic. moreover, it underlines the inaccuracy of the broadcast saturation model proposed by ma and chen due to the absence of backoff counter freeze process when channel is busy. computer simulations are used to validate the accuracy of the new model and demonstrate the importance of capturing the freezing of backoff counter in the analytical study of ieee 802.11 broadcast.
routing-aware channel selection in multi-radio mesh networks. efficient channel selection is essential in 802.11 mesh deployments, for minimizing contention and interference among co-channel devices and thereby supporting a plurality of qos-sensitive applications. in this paper, we propose arachne, a routing-aware channel selection protocol for wireless mesh networks. arachne is distributed in nature, and motivated by our measurements on a wireless testbed. the main novelty of our protocol comes from adopting a metric that captures the end-to-end link loads across different routes in the network. arachne prioritizes the assignment of low-interference channels to links that (a) need to serve high-load aggregate traffic and/or (b) already suffer significant levels of contention and interference. our protocol takes into account the number of potential interfaces (radios) per device, and allocates these interfaces in a manner that efficiently utilizes the available channel capacity. we evaluate arachne through extensive, trace-driven simulations. we observe that our protocol improves the total network throughput, as compared to three other channel allocation strategies.
rewritable channels with data-dependent noise. we present some recent results on rewritable channels, that is, storage channels that admit optional reading and rewriting of the content at a given cost. this is a general class of channels that models many nonvolatile memories. we focus on the storage capacity of rewritable channels affected by data-dependent noise. we prove tight upper and lower bounds on the storage capacity of a simple yet significant channel model and suggest some simple capacity-achieving coding techniques. lower bounds on the storage capacity of gaussian rewritable channels with data-dependent noise are also shown.
end-to-end delay approximation in cascades of generalized processor sharing schedulers. this paper proposes an analytical method to evaluate the delay violation probability of traffic flows with statistic al quality-of-service (qos) guarantees in a generalized processor sharing scheduler. the statistical qos targets, for each service class, are expressed in terms of a delay threshold and delay violation probability. we study both the single node and the end-to-end paths comprising multiple schedulers. moreover, we assume that traffic admits a linear variance envelope, therefore, we account for leaky-bucket-regulated traffic, for general markov-modulated poisson process sources and markov-modulated fluid process sources and, more in general, to the wide class of sources for which the variance of the cumulative generated traffic can be upper bounded by a linear function of time. under these assumptions, we are able to derive an approximation on delay distributions for each class of the gps scheduler. moreover, by exploiting a novel framework for the calculation of statistical end-to-end delay bounds (the bounded variance network calculus) we iterate our formulas, derived for the isolated node, to multi-node paths and, in turn, we provide analytical forms for the end-to-end delay. numerical investigation shows that our approximations are very close to the simulated values.
sb-rawvec - a semi-blind watermarking method for vector maps. rawvec [1] is a private watermarking method for vector maps that uses a raster image as watermark. visually recognizable watermarks can add extra information like integrity and authentication, while blind watermarks do not need the original data to be published for the detection. this work presents a semi-blind version of rawvec, i.e. a method that uses the original vector map during the detection without revealing it, but maintains the watermark as a raster image.
optical techniques for up-conversion of mb-ofdm signals in 60 ghz band using fiber bragg grating. we have demonstrated two techniques for all optical frequency up-conversion of multi-band orthogonal frequency division multiplexing (mb-ofdm) signal with 400mbps bit rate in the 60 ghz band. the first technique is based on direct modulation of laser diode (ld) associated with an electro-optic modulator (eom) and the second one is based on two cascaded eoms. for both techniques, a fiber bragg grating (fbg) is inserted to suppress undesired signal around 60 ghz band. direct modulation of ld with an eom is cost effective compared to two cascaded eoms, and exhibits a gain of 5 db in the received optical power. a minimum error vector magnitude (evm) of 18% and 20% are measured for direct modulation of ld with an eom and two cascaded eoms techniques, respectively which complies with mb-ofdm standard.
power-saving geographic routing in the presence of location errors. existing power efficient geographic routing algorithms have been shown to be able to reduce power consumption and hence prolong the lifetime of multi-hop wireless networks. however, in practical deployment scenarios where location errors inevitably exist, these algorithms are vulnerable to a substantial performance degradation in terms of energy consumption. since location errors always exist no matter which localization technique is used, there is the need of a geographic routing protocol which can tolerate location errors and achieve reduced energy consumption. in this paper, we study the optimal distance of existing power-saving geographic routing algorithms. through incorporating location errors into an objective function, we propose a novel geographic routing algorithm. extensive performance evaluations show that our proposal is robust to location errors, thus statistically minimizing consumed transmit power as a packet is relayed from source to destination.
lattice reduction aided multi-user mimo successive interference cancellation combined with linear pre-equalization. we present a lattice reduction (lr) aided successive interference cancellation (sic) scheme combined with linear pre-equalization in the correlated multi-user mimo system. the lr-aided sic schemes have been extensively studied to detect multiple users' symbols due to the nearly optimal performance. however, the lr algorithm and the sequential detecting method inherently incur considerable computational complexity overhead although it is of a polynomial order. to reduce their computational complexities, we decouple the entire system into multiple lower dimensional subsystems using linear pre-equalization based on the correlation among the users. we then utilize the lr-aided sic parallel in each subsystem. furthermore, to combine the lr-aided sic with pre-equalization optimally, we modify the lr-aided sic scheme, handling the residual interferences after pre-equalization.
an improved split-row threshold decoding algorithm for ldpc codes. we present an improved thresholding ldpc decoding algorithm which outperforms the split-row and original split-row threshold decoders with a small increase in hard-ware. simulation results show that the algorithm provides 0.27- 0.50 db coding gain over split-row, 0.10-0.20 db over split-row threshold, and is within 0.08-0.13 db of spa. compared with the original threshold algorithm the check node processor's gate count is increased by 3% while total chip area is kept the same.
on the security performance of physical-layer network coding. physical-layer network coding (plnc) is a novel wireless communication technology, in which multiple transmitters can send signals on the same channel to the same receiver at the same time. our previous studies have revealed that plnc can substantially improve the throughput performance of the whole network. in this paper, we address the security performance of plnc. in particular, we investigate the symbol error performance of a potential eavesdropper in the plnc system. extensive simulation studies show that plnc can provide security means against passive eavesdroppers.
the spatial effect of mobility on the mean number of handoffs: a new theoretical result. the mean number of handoffs is a fundamental performance measure in any mobile system, as it directly relates to the signaling load in the network as well as to the delivered qos. as the mobile services are evolving from simple cellular voice calls towards media and data sessions, and as cellular providers are reinventing their businesses by incorporating third party services, the handoff rate will even play a more pivotal role. this is because future sessions are expected to last longer than voice calls and users are more likely to roam into other networks. existing results provide an estimate of the mean number of handoffs in networks composed of an infinite number of access gateways and hence consider neither the topological arrangement of the gateways nor the mobility patterns between them. in this paper, we obtain a closed form solution for the mean number of handoffs under generic assumptions of two-dimensional markovian mobility patterns, spatial arrangement of the access gateways, as well as generic session times and gateway residence times. our solution unveils a new insight into mobility foundations as it shows that the consideration of the mobility pattern and the access gateways' layout simply transforms the known equation for the mean number of handoffs of an infinite network size from scalar to vector representation. we demonstrate that the mean number of handoffs is a non-linear function of the gateway spatial arrangement and user mobility.
a multicost approach to online impairment-aware rwa. we design and implement a multicost impairment-aware routing and wavelength assignment algorithm for online traffic. in transparent optical networks the quality of a transmission degrades due to physical layer impairments. to serve a connection, the proposed algorithm finds a path and a free wavelength (a lightpath) that has acceptable signal quality performance by estimating a quality of transmission measure, called the q factor. we take into account channel utilization in the network, which changes as new connections are established or released, in order to calculate the noise variances that correspond to physical impairments on the links. these, along with the time invariant eye impairment penalties of all candidate network paths, form the inputs to the algorithm. the multicost algorithm finds a set of so called non-dominated q paths from the given source to the given destination. various objective functions are then evaluated in order to choose the optimal lightpath to serve the connection. the proposed algorithm combines the strength of multicost optimization with low execution time, making it appropriate for serving online connections.
performance-aware security of unicast communication in hybrid satellite networks. in this work, we address the performance problems that arise when unicast security protocols ipsec and ssl are applied for securing the end-to-end communication in hybrid satellite networks. satellite networks use tcp and http performance-enhancing proxy servers to overcome the adverse effect of the large delay-bandwidth product of the satellite channel. however, the proxy servers cannot function when ipsec and ssl are used for secure unicast communication in hybrid satellite networks. we therefore propose the use of the layered ipsec (les) protocol as an alternative to ipsec for network-layer security. we describe a modification to the internet key exchange protocol if dynamic key establishment is needed for layered ipsec. for application-level security of web browsing with acceptable end-to-end delay, we propose the dual-mode ssl protocol (dssl) to be used instead of ssl. we describe how les and dssl protocols achieve the desired end-to-end communication security while allowing the tcp and http proxy servers to function correctly. through simulation studies, we quantify the improvement in performance that is achieved using our proposed protocols, compared to traditional ipsec and ssl.
capacity of optical intensity channels with peak and average power constraints. the design and analysis of capacity-approaching input signalling for optical intensity channels are presented. both peak and average optical power constraints are considered in the analysis. the capacity-achieving distribution for this channel is discrete with a finite number of mass points. in practice, finding this distribution requires solving a complex non-linear optimization at every snr. in this work, we present a closed form discrete capacity-approaching distribution derived via source entropy maximization. the computation of this distribution is substantially less complex than previous optimization approaches and can be easily computed for different snrs. the information rates using the derived maxentropic distribution are shown to be negligibly far away from the channel capacity found by non-linear optimization in the snr range -6 to 6 db.
bandwidth-guaranteed multicast in multi-channel multi-interface wireless mesh networks. we consider multi-channel multi-interface wireless mesh networks with a schedule-based mac protocol, where conflict-free transmission is ensured by requiring links assigned with the same channel and within the mutual interference range of each other to be active at different time slots. when a (point-to-multipoint) multicast call arrives, the call is accepted if a multicast distribution tree can be established for connecting the source node with all the receiving nodes, and with sufficient bandwidth reserved on each link. otherwise, the call is rejected. to maximize the call acceptance rate, the multicast tree must be constructed judiciously upon each call arrival. aiming at minimizing the carried load on the most-heavily loaded channel, and maximizing the residual capacity of the most heavily loaded node, an integer linear program (ilp) is formulated for multicast tree construction. since solving ilp can be time-consuming, an efficient heuristic algorithm is then proposed. we compare the two tree construction algorithms by simulations. we found that both algorithms give comparable call acceptance rate, but the heuristic algorithm requires much shorter running time.
measurement-based modeling of vehicle-to-vehicle mimo channels. vehicle-to-vehicle (vtv) communications are of interest for applications within traffic safety and congestion avoidance, but the development of suitable communications systems requires accurate models for vtv propagation channels. this paper presents a new wideband mimo (multiple-input-multiple-output) channel model for vtv channels based on extensive mimo channel measurements performed at 5.2 ghz in rural environments in lund, sweden. the measured channel characteristics, in particular the non-stationarity of the channel statistics, motivate the use of a geometry-based stochastic channel model (gscm) instead of the classical tapped-delay line model. we introduce generalizations of the generic gscm approach and find it suitable to distinguish between diffuse and discrete scattering contributions. the time-variant contributions from discrete scatterers are tracked over time and delay using a high resolution algorithm, and our observations motivate their power being modeled as a combination of a deterministic part and a stochastic part. the paper gives a full model parameterization and the model is verified by comparison of mimo antenna correlations derived from the channel model to those obtained directly from measurements.
tri-message: a lightweight time synchronization protocol for high latency and resource-constrained networks. existing terrestrial synchronization protocols including rbs, ftsp, tpsn, lts and tshl have already achieved high precision in radio networks, but none of them perform well in high latency networks like acoustic sensor networks. in this paper, we present tri-message: a lightweight time synchronization protocol for high latency and resource-constrained networks. as its name suggests, only three message exchanges are required in one synchronization process. meanwhile, tri-message utilizes very simple mathematical operations to calculate the clock skew and offset. specially, tri-message is feasible for many extremely long latency applications such as space exploration because it has an increasing synchronization precision with the increasement of distance.
an upper bound on the performance of non-repetitive flooding over csma in wireless ad-hoc networks. although flooding and its variants are widely deployed for broadcasting by different applications, there are limited results on a complete and comprehensive analytical framework describing their behavior in general cases. we have previously published results which provide an upper bound for the performance of flooding when flooded packets have the highest serving priority. in this paper, using a different and simpler approach, we develop an analytical framework for analysis of flooding in general cases where flooding packets do not receive any special priority treatment in the network. the analysis is performed for a static multi-hop ad hoc wireless network using csma as its mac layer. the framework provides an upper bound on the network coverage and energy consumption of flooding and its popular variant, probabilistic flooding for any service time and queuing delay that flooded packets experience. the analytical upper bound is verified by extensive simulations which give evidence of its tightness in real scenarios.
on contextcast: a context-aware communication mechanism. the dissemination of messages according to clients' contexts (i.e., location and other attributes) opens up new possibilities in context-aware systems. while geocast or content-based publish/subscribe forward messages according to client location or attributes, respectively, neither uses a combination of the two. in this paper, we present this new communication paradigm and the challenges it poses. we also extend concepts from publish/subscribe networks to efficiently deal with highly dynamic user location to lower update rates by approximating the user's location. this reduces update rates by between 25% and 90%, depending on the granularity of the approximation.
information hiding with optimal detector for highly correlated signals. in this paper, a novel scaling based information hiding approach robust against noise and gain attack is presented. the host signal is assumed to be stationary gaussian modeled with a first-order autoregressive process. for data embedding, the host signal is divided into two parts. one part is manipulated while the other part is kept unchanged for parameter estimation. the decoding scheme using the ratio of samples is suitable for highly correlated signals in which the decoding process is difficult. by calculating the distribution of the ratio, the performance of the maximum likelihood decoder is analytically studied. the proposed algorithm is applied to several artificial gaussian autoregressive signals to verify the validity of our results.
joint path and wavelength selection using q-learning in optical burst switching networks. contention losses which usually do not indicate congestion is a major issue that hinders the deployment of optical burst switching (obs) networks. development of efficient path and wavelength selection algorithms is crucial to minimize the burst loss probability (blp) in obs networks. in this paper, we handle path selection and wavelength selection in a joint fashion. we formulate the problem of selecting a pair of path and wavelength jointly as a multi-armed bandit problem (mabp) and discuss the difficulties in solving mabp directly. we then rewrite the q-learning formalism to solve the mabp without explicit model in an online fashion and propose an algorithm to solve the problem near-optimally. the proposed algorithm selects a pair of path and wavelength at each ingress node to minimize the blp on the long run. simulation results demonstrate the effectiveness of our algorithm in minimizing the blp with better link utilization compared to the other proposals in the literature.
channel access throttling for overlapping bss management. multiple co-channel wlan bsses (i.e., wlan cells) overlapping in coverage are generally considered undesirable because members of the obsses compete for channel access, which typically increases the contention level of wireless medium access and reduces overall system performance. in this paper, we propose to use channel access throttling (cat) for managing wireless lan radio resources for overlapping bsses (obsses). cat provides an access point (ap) of each bss with a mechanism to control channel access parameters of its member stations on the fly. by coordinating the cat operations of the obss aps, we can enable privileged channel access to an individual bss at a particular time, for example, by assigning high priority access parameters to member stations associated with the bss. by controlling how much each bss may be given the privileged channel access, we can also achieve a proportional partitioning of channel capacity among obsses. we present evaluation results obtained from both simulations and experiments using testbed built with commercial off-the-shelf (cots) wlan hardware and open-source device driver. our results show that with cat, not only can we proportionally partition channel capacity among the obsses, but also improve channel utilization efficiency and increase overall capacity.
efficient adaptive routing in delay tolerant networks. conventional routing algorithms in mobile ad hoc networks (manets), i.e., multi-hop forwarding, assume the existence of contemporaneous source-destination paths and are not scalable to large networks. on the other hand, in delay tolerant networks (dtns), routing protocols use the mobility-assisted, store-carry-forward paradigm which allows delivery among disconnected network components. adaptive routing, which combines multi-hop and mobility-assisted routing protocols, is of practical value: it allows efficient multi-hop forwarding while providing the flexibility to deliver messages among disconnected network components. however, existing adaptive routing protocols use mobility-assisted routing protocols as an alternative only when the former fails. in this paper, we propose to improve the performance of adaptive routing from a resource allocation point of view, in situations where bandwidth is a critical and limited resource affecting routing performance. we propose an adaptive routing protocol, named efficient adaptive routing (ear), which allocates bandwidth (or forwarding opportunities) between its multi-hop forwarding component and its mobility-assisted routing component dynamically to improve bandwidth utility. simulations are conducted to evaluate the routing performance of ear under different network parameters.
optimal transmission for dying channels. in this paper, we investigate the optimal transmission schemes for dying channels, which were introduced in [1]. the dying channels are resulted in wireless networks subject to random fatal impacts, e.g., sensor networks under sudden physical attacks or cognitive radio networks with unpredictable primary user occupancy. due to the non-ergodic and delay-limited nature of a dying channel, the outage capacity is adopted as the performance metric. firstly, we show that the optimal power allocation profile is non-increasing when fading gains are independently and identically distributed (i.i.d.). secondly, when the fading gains over the blocks are the same, we prove that the optimal number of blocks over which a codeword should be spanned is k = 1. at last, we consider the case where uniform power allocation is utilized and fading gains are i.i.d. in this case, we derive the upper and lower bounds for the outage probability. moreover, for the high signal-to-noise ratio (snr) case with rayleigh fading , we derive analytical results on the optimal number of coding blocks k. for the low snr case, we show that repetition transmissions are approximately optimal.
fast power control for cross-layer optimal resource allocation in ds-cdma wireless networks. this paper presents a novel cross-layer design for joint power and end-to-end rate control optimization in ds-cdma wireless networks, along with a detailed implementation and evaluation in the network simulator ns-2. starting with a network utility maximization formulation of the problem, we derive distributed power control, transport rate and queue management schemes that jointly achieve the optimal network operation. our solution has several attractive features compared to alternatives: it adheres to the natural time-scale separation between rapid power control updates and slower end-to-end rate adjustments, and uses simplified power control mechanisms with reduced signalling requirements. we argue that these features are critical for a successful real-world implementation. to validate these claims, we present a detailed implementation of a cross-layer adapted networking stack for ds-csma ad-hoc networks in ns-2. we describe several critical issues that arise in the implementation, but are typically neglected in the theoretical protocol design, and evaluate the alternatives in extensive simulations.
link adaptation in linearly precoded closed-loop mimo-ofdm systems with linear receivers. upcoming multi antenna systems such as 3gpp- lte employ code book based multi-mode precoding in order to adapt to a wide range of channel conditions. link adaptation, which includes the selection of precoding matrices, the number of spatially multiplexed layers as well as modulation coding schemes is a crucial task, carried out by the receiver. in this contribution we propose link adaption based on the measure of mutual information between the channel input and the linear detector output and evaluate the behavior of the proposed algorithm in spatially correlated and uncorrelated propagation scenarios. the results highlight the importance of proper link adaption in order to mitigate the impact of spatial correlation.
statistical learning for automated rrm: application to eutran mobility. self organizing network (son) functionalities are currently developed to improve network performance and management tasks. son functionalities require efficient utilization of data extracted from the network. in this context, the paper has two objectives. first it is shown that one can use simple statistical learning techniques such as regression to extract a model from data. the model comprises closed form expressions that approximate the functional relations between measured key performance indicators (kpis) and radio resource management (rrm) parameters. second, it is shown how the model can be integrated in a monitoring process and be used to devise an efficient auto-tuning algorithm. to this end, two case studies of handover monitoring and handover auto-tuning in a lte network are described and illustrate the application of the proposed approach.
dual hop mimo relaying with orthogonal space-time block codes. this paper considers orthogonal space-time block coded (ostbc) transmission for non-regenerative multiple-input multiple-output dual-hop channels. we focus on scenarios where the relay does not have access to instantaneous channel state information, and as such operates according to a non-coherent amplify-and-forward protocol based on a long-term power constraint.we investigate the performance of the proposed ostbc approach by employing tools from finite-dimensional random matrix theory. in particular, we derive exact closed-form expressions for the moment generating function, high order cumulants, and first and second moments of the signal-to-noise ratio at the destination. based on these results, we also derive analytical expressions for the symbol error rate with m-ary phase-shift keying, and the amount of fading.
error-tolerant searchable encryption. in this paper, we describe a new primitive for error-tolerant searchable encryption and a security model for it. this generic scheme permits to make searches on encrypted data with only an approximation of some keyword. it enables to efficiently query secure databases in order to get the exact data with a close estimation of it. an application to biometric identification arises from this construction. this is the first construction both for error-tolerant searchable encryption and for a biometric identification protocol over encrypted personal data.
optimal output back-off in ofdm systems with nonlinear power amplifiers. a well-known problem of ofdm signals is their high peak-to-average power ratio, which can cause the clipping of peaks in the transmitted signal due to the limited linear range of high power amplifiers. operating the amplifier solely in the linear region, i.e., with a large output back-off, results in an undistorted transmitted signal, but at the expense of a low snr at the receiver. driving the amplifier into saturation, on the other hand, maximizes the received snr, but causes severe nonlinear signal distortions. in this paper we study the resulting trade-off. we show both theoretically and by simulations that, despite the distortions, it is optimal to operate the amplifier close to saturation. furthermore, we analytically derive a modification of the bussgang noise cancellation algorithm which was recently shown in the literature to improve the exit characteristic of the algorithm.
hmm-web: a framework for the detection of attacks against web applications. nowadays, the web-based architecture is the most frequently used for a wide range of internet services, as it allows to easily access and manage information and software on remote machines. the input of web applications is made up of queries, i.e. sequences of pairs attribute←value. a wide range of attacks exploits web application vulnerabilities, typically derived from input validation flaws. in this work we propose a new formulation of query analysis through hidden markov models (hmm) and show that hmm are effective in detecting a wide range of either known or unknown attacks on web applications. in addition, despite previous works, we explicitly address the problem related to the presence of noise (i.e., attacks) in the training set. finally, we show that performance can be increased when a sequence of symbols is modelled by an ensemble of hmm. experimental results on real world data, show the effectiveness of the proposed system in terms of very high detection rates and low false alarm rates.
dynamic resiliency analysis of key predistribution in wireless sensor networks. wireless sensor networks have been analyzed for more than a decade from operational and security points of view. several key predistribution schemes have been proposed in the literature. although valuable and state-of-the-art proposals have been made, their corresponding security analyses have not been performed by considering the dynamic nature of networking behavior and the time dimension. the sole metric used for resiliency analysis of key predistribution schemes is "fraction of links compromised" which is roughly defined as the ratio of secure communication links that the adversary can compromise over all secure links. however, this metric does not consider the dynamic nature of the network; it just analyzes a snapshot of the network without considering the time dimension. for example, possible dead nodes may cause change of routes and some captured links become useless for the attacker as time goes by. moreover, an attacker cannot perform sensor node capturing at once, but performs over time. that is why a methodology for dynamic security analysis is needed in order to analyze the change of resiliency in time a more realistic way. in this paper, we propose such a dynamic approach to measure the resiliency of key predistribution schemes in sensor networks. we take the time dimension into account with a new performance metric, "captured message fraction". this metric is defined as the percentage of the messages generated within the network to be forwarded to the base station (sink) that are captured and read by the attacker. our results show that for the cases where the static fraction of links compromised metric indicates approximately 40% of the links are compromised, our proposed captured message fraction metric shows 80% of the messages are captured by the attacker. this clearly proves the limitations of the static resiliency analysis in the literature.
two phase spectrum sharing for frequency-agile radio networks. modern frequency-agile radios are capable of dynamically changing the spectrum width and central frequency of its channels. existing spectrum sharing algorithms often fail to exploit this characteristic to realize efficient spectrum utilization. in this paper, we present a theoretical framework that capitalize on the frequency agility of modern radios. we solve a joint spectrum sharing and end-to-end rate control problems for general wireless networks to achieve optimal spectrum efficiency with regard to network utility. analytical and simulation results show the effectiveness of our design.
bandwidth and computing resources provisioning for grid applications and services. applications using grid computing infrastructure usually require resources allocation to satisfy their quality of service (qos) requirements. given that the grid infrastructure is a set of computing resources geographically distributed, the support of grid applications requires the allocation of computing resources and bandwidth to enable communication among these resources. the objective is to accommodate as many applications as possible while still satisfying their requirements. ideally, we would like to accommodate a given grid application using a set of computing resources (e.g., one server) that are not geographically distributed (e.g., in the same lan); however, this is not always possible. indeed, to increase the probability of accommodating grid applications, we may need to use computing resources scattered all over the network; in this case, bandwidth allocation is required to enable communication among these resources. in this paper, we propose an optimization model that enables the "simultaneous" allocation of computing resources and bandwidth for grid application while maximizing the number of grid applications being accommodated. a heuristic is proposed to solve the model with an acceptable response time; simulations show that the proposed approach outperforms existing classical approaches.
optimizing access radio in multi-radio mesh network. this paper discusses a hierarchical multi-radio mesh network, where the normal clients associate with the mesh ap through the access radio and then the mesh aps communicate with each other via the mesh radio. while most of the existing studies focus on the performance issue for the mesh nodes communication with the mesh radio, in this paper, we argue that the channel assignment for the access radio will affect the overall system significantly. in this paper, we try to exploit the information exchange among the mesh nodes to help the access radio channel selection. a new metric, effective channel air time (ecat), is proposed for channel assignment under this multi-radio mesh network. ecat can work well when there are traffics in the overlapping channels. a real testbed has been developed to demonstrate the effectiveness of the proposed metric and scheme.
adaptive hybrid call admission control policy for umts with underlying tunnel-wlans heterogeneous networks. in this paper we evaluate the handoff performance of an umts network with underlying tunnel-wlans at the cell periphery while developing an adaptive qos oriented cac function, proposed to limit the occurrence of hard ieee 802.11 wlan-umts handovers to mobiles using real time applications. the proposed protocol is hybrid and based on the service class differentiation, the location in the heterogeneous infrastructure and a vertical handoff decision function as well. the results show that our policy achieves significant performance and gains. it maximizes the utilization of the resources available at the wlan cells, and meets as much as possible the qos requirement of higher priority users.
a generalized two-way relay channel with private information for the relay. in the conventional two-way relay channel, two sources exchange information with help from a relay. we introduce a generalized two-way relay channel where each source additionally sends private information to the relay. for this channel, we consider a protocol that consists of a multiple-access (ma) phase and a broadcast (bc) phase and obtain achievable rate regions for both phases. the ma phase is related to computation over the multiple-access channel (mac).we show that our scheme achieves rates that always lie within half bit of the capacity region for computation over mac, and is capacity achieving in the bc phase. this near optimality in the ma phase can be achieved by time sharing a capacity-achieving code for the mac and a superposition code that uses a lattice code as its component code.
performance analysis of verification-based decoding for packet-based ldpc codes over binary symmetric channel. in this paper, we propose a statistical model to analyze the performance of verification-based algorithm (va) for packet-based low-density parity-check (ldpc) codes over binary symmetric channel (bsc). in contrast to the analysis of va in the literature, we propose to take the false verification into consideration. for a given ensemble of ldpc codes and channel parameters, the proposed analysis model gives an efficient way to find the average performance of packet-based ldpc codes with verification-based decoding. through numerical results, we find that the proposed method can provide a close estimation of frame error rate (fer) for packet-based ldpc codes with verification-based decoding over bsc for all crossover probabilities of practical interests.
capacity with probabilistic delay constraint for voice traffic in a rayleigh channel. the capacity with probabilistic delay constraint cdt,ɛ expresses the maximum source rate that may be supported in a wireless system with a probability ɛ of exceeding certain delay bound dt. in [1], cdt,ɛ was calculated for a rayleigh channel carrying a constant rate flow. in this work, the potential of the effective bandwidth theory is shown by evaluating this constrained capacity for a variable rate source modeled as an on-off process. cross relations among on-off process parameters, fading channel statistics, qos constraints and maximum allowable mean source rate are displayed by the obtained closed-form expressions. cdt,ɛ is measured in different scenarios to exhibit to which extent higher time-correlation of the channel response or longer on-off periods are harmful to the delay behaviour, getting a lower value of the capacity cdt,ɛ.
adaptive sensor activation for target tracking in wireless sensor networks. this paper presents an adaptive sensor activation for target tracking in wireless sensor networks by dynamically adjusting the range of sensor selective activation instead of fixed one. a closed-loop control algorithm for the range of adaptive sensor activation is designed according to the online feedback of the tracking quality. the failed tracking case can also be handled by the proposed algorithm. extensive simulation results show that the adaptive sensor activation achieves higher performance in terms of tracking effect and energy efficiency.
design and deployment of a network-aware grid for e-science applications. in the last years, grid computing has emerged as a valuable service to solve complex computational problems in many scientific and industrial domains. quality of service (qos) provision for these applications is therefore a key challenge for high speed next generation networks and cross-layer mechanisms, enabling the development of network-aware grids, should be introduced. this paper takes into account, as a case study, an application for the simulation of particles coagulation phenomena. a parallel direct simulation monte carlo algorithm has been implemented and extensive computations have been performed in a cluster of computing nodes to evaluate the execution time of the application in different operating conditions. then, data collected from these experiments, have been used as input for the design and deployment of a network-aware grid infrastructure. since this application is characterized by frequent data exchanges, the impact of the allocated bandwidth on the overall application's performance has been investigated.
design of a codebook structure for a progressively linear pre-coded closed-loop mimo hybrid arq system. the paper considers a hybrid arq (harq) scheme for a linear pre-coding-based closed-loop multiple-input multiple-output (mimo) system, in which a pre-coding matrix is dynamically selected for every retransmission by taking into account a symbol-level combining gain obtained from the previous receptions. a new retransmission structure with a sequence of multiple codebooks is proposed that are optimized for combining gain, rather than using a single identical codebook for every retransmission. furthermore, a criterion for selecting a pre-coding matrix for each retransmission can be provided so as to minimize the retransmission error probability. under the proposed multiple codebook structure for mimo-harq systems, a sequence of optimum codebooks is constructed for the subsequent retransmissions. simulation results are presented for showing that the proposed scheme achieves significant error performance advantages over conventional schemes with a single codebook and furthermore, a near-optimal performance is achieved as the codebook size chosen is large enough.
improved fast recursive algorithms for v-blast and g-stbc with novel efficient matrix inversion. in this paper, we propose a novel matrix inversion algorithm, which speeds up the corresponding step in the existing fast recursive algorithm for vertical bell laboratories layered space-time architecture (v-blast) by 1.67. totally our improved recursive algorithm for v-blast speeds up the existing recursive algorithm for v-blast by 1.3. furthermore, we develop an efficient recursive algorithm to implement the minimum mean-square error (mmse) successive interference cancellation (sic) detector with optimal ordering for groupwise space-time block coded system (g-stbc), by exploiting the properties of the alamouti structure in the equivalent channel matrix for gstbc. our recursive algorithm for g-stbc speeds up the low-complexity mmse sic algorithm with sub-optimal ordering for g-stbc by 2.57 approximately.
on accurate and scalable anomaly detection in next generation mobile network. this paper proposes an adaptive sampling strategy to address the accuracy and scalability issues of anomaly detection at high-speed backbone side of next generation mobile network (ngmn). the proposed sampling strategy is formulated based on the network traffic condition. it is constituted by two important functions namely the traffic identification and the sampling decision. while the former utilizes spectral analysis to identify the severity status of the traffic flows, the latter exploits both the flow status and flow size to compute the optimal sampling rate. in addition, a renormalization process is proposed to address the scalability issue in the network. our analysis demonstrates that the proposed technique is efficient in providing adequate statistics for detecting anomaly traffic and scales well to the high speed traffic of ngmn.
a directional mac protocol with deafness avoidance for uwb wireless sensor networks. ultra-wideband (uwb) is a key solution for wireless connectivity, characterized by ultralow power consumption and a good degree of robustness to interference. evidence of its importance, is its recent use in the ieee 802.15.4a standard. uwb technology with joint consideration of directional antennas can benefit when compared to classical omnidirectional antennas from the energy conservation viewpoint, which is of fundamental concern when it comes to wireless sensor networks (wsns). however, exploiting directionality requires new approach in the design of a medium access control (mac) protocol to be applied. in this work, idle nodes continuously rotate their receiving beams over 360 degrees until a predefined preamble trailer is detected. the resulting scheme is a directional ultra-wideband mac protocol, named du-mac, which deals effectively with the problem of deafness and the problem of determination of neighbors' location. simulation based studies would demonstrate the effectiveness of our protocol in many critical parameters.
security in advanced optical communication networks. the increased demand of data services within the last few years has prompted a commensurate explosion in transportable bandwidth, most of which contain sensitive information, personal data, bank accounts, credit card numbers, proprietary documents, and more. as a result, there are two types of security in communications, securing user data and securing the physical network. the first is addressed with encryption algorithms, the unbreakability of which does not depends so much on the sophistication of the algorithm but on the difficulty to break it using a sequential computer; that is, it capitalizes on the inability of the attacker to use a fast supercomputer. the second is not a well addressed topic, particularly in modern fiber-optic networks. one attempt to create an unbreakable cipher-text is quantum cryptography that emanated from quantum mechanics; this method capitalizes on the no-cloning principle of particular characteristics of photons, such as polarization. in this paper, we examine the security of advanced optical networks, fiber-optic and free space optical (fso). we describe quantum cryptography and the quantum key distribution, including the principle of teleportation, we identify vulnerabilities and we discuss detection mechanisms and countermeasure strategies against attacks on the physical network.
composite hypothesis testing for cooperative spectrum sensing in cognitive radio. in this paper, we present a composite hypothesis testing approach for cooperative spectrum sensing. we derive the optimal likelihood ratio test (lrt) statistic based on the neyman-pearson (np) criterion at the fusion center for both hard (one-bit) and quantized (multi-bit) local decisions. we show that the lrt statistic depends on the modulation type and second-and fourth- order statistics of the primary signal. however, such side information is not commonly available to the secondary network. therefore, we propose to apply composite hypothesis testing methods, such as the rao test, which do not require any prior knowledge about the primary signal, in a cooperative sensing scenario. we derive a modified rao test statistic for decision making at the fusion center for both cases of hard and quantized local decisions. we also apply the locally most powerful (lmp) detector at the fusion center for weak primary signals and derive its corresponding test statistic. these methods are much simpler than the optimal np-based method and do not require estimation of the primary signal statistics while having a very close performance to the optimal method.
joint precoding for mimo-relay systems with partial channel state information. in this paper, we propose a joint precoding scheme for both the base station (bs) and relay station (rs) to increase the ergodic capacity of downlink non-regenerative multiple-input multiple-output(mimo)-relay systems. different from previous work, we assume only the mean and the covariance matrix are known for the channel state information (csi) of the rs-mobile station(ms) link. since the exact solution of this problem is difficult to be found because the rs-ms channel is only partially known, we employ precoding matrices that maximize the upper bound on the ergodic capacity. based on this approach, the proposed scheme uses an iterative method to determine both bs and rs precoding matrices simultaneously. in numerical results, the proposed joint precoding scheme is shown to outperform the water-filling and amplify-and-forward (wf-af) scheme in high signal-to-noise ratio (snr) regions. it is also shown to outperform the spatial multiplexing and rs precoding (sm-rp) scheme in low snr regions.
diversity analysis of a randomized distributed space-time coding in an amplify and forward relay channel. this paper considers a cooperative communications system where a single relay aids a point-to-point transmission using an amplify and forward configuration. the relay linearly encodes the k received symbols into n new ones by means of a matrix multiplication, and the destination employs a lmmse filter to estimate the information originally transmitted. a large-snr approximation of the outage probability pout is derived for this system. the analysis of pout shows that the diversity order of the system depends on the ratio k/n: if such a ratio is too high (the relay excessively compresses the information), no diversity is added by introducing the relay. conversely, if this ratio is smaller than a certain quantity, diversity order 2 is ensured. the derived expressions are finally used to establish the diversity-multiplexing tradeoff of the system.
co-opetition strategy for collaborative multiuser multimedia resource allocation. this paper focuses on using the mindset of co-opetition for collaborative multimedia resource allocation. the co-opetition suggests a judicious mixture of competition and cooperation. we present a novel co-opetition strategy based on the kalai-smorodinsky bargaining solution (ksbs), and apply it to video rate allocation. the proposed strategy makes satisfied users stop competing for resources such that qos of unsatisfied users can be improved. our strategy is evaluated through comparing to existing competition-based strategies. numerical results indicate that, the co-opetition strategy can result in an improved number of satisfied users. algorithm with low complexity is also presented.
revisiting relative location estimation in wireless sensor networks. relative location estimation plays an important role of localization in wireless sensor networks (wsns). in wsns with planned deployment of anchor nodes, some prior information may be available. existing work on relative location estimation rarely takes into account the lognormal fading effect of wireless channel and the prior probability of the link distance to each reachable anchor node. as a result, when applied to such environments, they may not work effectively. in this paper, we propose a new model called probability-based maximum likelihood (pml) for relative location estimation. with some prior information, the estimation accuracy can be improved significantly. we also discuss the impact of over-estimation and under-estimation of the distance to each reachable anchor node on the accuracy of relative location estimation, and introduce the concept of the compensation factor to combat such effects. the simulation results show that the proposed pml outperforms existing solutions in terms of estimation accuracy for wsns with planned deployment of anchor nodes.
performance evaluation of contention-based access in ieee 802.16 networks with subchannelization. ieee 802.16 wireless networks, known as wimax, employ a mechanism for guaranteed time allocation to mobile stations in order to meet the different quality of service requirements for service flows. the base station allocates contention-based time slots for the stations to transmit their requests for additional bandwidth. each contention time slot can accommodate a single transmission if there is no subchannelization or multiple concurrent transmissions if the base station enables subchannelization during the contention period. for transmission during this period, each station employs a contention-resolution mechanism. in this paper, we develop an analytical model for the bandwidth request and resolution mechanism during this contention period when subchannelization is employed. the model is shown to accurately model the contention period when subchannelization is enabled. performance metrics, such as throughput and capacity, show that adding more subchannels to the contention time slots increases both the throughput and the capacity of the contention period carrying more successful bandwidth requests. simulations with different parameter sets are carried out to validate the proposed model.
low complexity resource allocation algorithm for ieee 802.16 ofdma system. adaptive resource allocation including the allocation of subcarrier, bit and power in orthogonal frequency division multiple access (ofdma) system, can significantly improve spectral efficiency, increase capacity, and reduce power consumption. the resource allocation in an ofdma system is normally modeled as a combinatorial optimization problem involving a nonlinear objective with nonlinear constraints. this leads to high computation complexity that is only solvable online. in this paper we first develop a nonlinear optimization model of ofdma resource allocation that incorporates not only the throughput constraint but also the delay constraint. we then find an equivalent linear formulation to this optimization problem to facilitate analysis. moreover, we develop a heuristic approximation algorithm to provide a close solution to the equivalent linear programming problem. the heuristic algorithm is efficient enough for on-line adaptive resource allocation. simulation results show that the heuristic solution can achieve almost same capacity but with less computation complexity.
intelligent service monitoring and support. intelligent service management techniques play an important role in the continuously and rapidly evolving area of technologically advanced services. high tech companies are looking for better ways to deliver and preserve services to their customers in a competitive way. this paper introduces a new architecture for a scalable service monitoring and support system called call home analysis and response system (chars). the proposed system utilizes data de-noising and filtering techniques to meet the service management requirements of large-scale service deployments. the system utilizes intra and inter-element correlation of events to enhance the services delivered to end-users. our results demonstrate that the proposed system is effective in covering the performance and fault management aspects for large-scale deployments of advanced services.
joint computing and network resource scheduling in a lambda grid network. data-intensive grid applications require huge data transfers between grid computing nodes. these computing nodes, where computing jobs are executed, are usually geographically separated. a grid network that employs optical wavelength division multiplexing (wdm) technology and optical switches to interconnect computing resources with dynamically provisioned multigigabit rate bandwidth lightpath is called a lambda grid network. a computing task may be executed on any one of several computing nodes which possesses the necessary resources. in order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. however, few scheduling methods consider the communication contention on lambda grids. in this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a lambda grid network. the objective of our work is to maximize the total number of jobs that can be scheduled in a lambda grid network. an adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. four heuristics (fifo, estf, ljf, rs) are implemented for job scheduling of the computational tasks. simulation results prove the feasibility and efficiency of the proposed solution.
sdma for 60ghz gigabit wireless networks. with the opening of the 60 ghz spectrum for wlans, there has been a great deal of interest in academia and industry on how best to exploit the more than 5 ghz of available bandwidth. one goal in the wireless community has been delivering gigabit data rates to end users. for this, a variety of approaches have been studied in the past. in this paper, we present two sdma (spatial division multiple access) algorithms that exploit the peculiar propagation properties of this part of the frequency. we show that in typical indoor environments, one access point can deliver over 8 gbps total throughput while using only 640 mhz of the bandwidth. we generalize the algorithms to the case when multiple channels are available and show that with seven channels, we get aggregate throughput of over 31 gbps.
performance analysis of slotted aloha with multi-access-point diversity. slotted aloha is an effective random access protocol and can also be an important element of more advanced media access protocols. this paper investigates slotted aloha in a radio environment with multiple access points. specifically, we examine the impact of multi-access-point (multi-ap) diversity on the performance of slotted aloha. the paper considers both omni-directional (om) and beamforming (bf) antennas at transmission nodes. this leads to the investigation and comparison of four different network scenarios, i.e., om with multi-ap diversity, om without multi-ap diversity, bf with multi-ap diversity and bf without multi-ap diversity. performance evaluations and comparisons are presented in terms of throughput.
resources allocation for the transmission of scalable images on ofdm systems. in a frequency selective channel for wireless applications, we provide a new resources allocation procedure that enables the transmission of scalable images in accordance with end-to-end quality of service (qos) constraints. this scheme is based on an unequal error protection (uep) policy with the possible truncation of the source data layers (after the source coding stage) and an optimal use of the available resources for each layer (with local flattening over the channel portion). the proposed algorithm is applied to the transmission of jpeg- 2000 scalable images over an ofdm channel. we analyze the performance of our method in term of perceived quality and speed, and show better results than state-of-the-art uep schemes.
on construction of moderate-length ldpc codes over correlated erasure channels. the design of moderate-length erasure correcting low-density parity-check (ldpc) codes over correlated erasure channels is considered. although the asymptotic ldpc code design remains the same as for a memoryless erasure channel, robustness to the channel correlation shall be guaranteed for the finite length ldpc code. this further requirement is of great importance in several wireless communication scenarios where packet erasure correcting codes represent a simple countermeasure for correlated fade events (e.g., in mobile wireless broadcasting services) and where the channel coherence time is often comparable with the code length. in this paper, the maximum tolerable erasure burst length (mtbl) is adopted as a simple metric for measuring the code robustness to the channel correlation. correspondingly, a further step in the code construction is suggested, consisting of improving the ldpc code mtbl. numerical results conducted over a gilbert erasure channel, under both iterative and maximum likelihood decoding, highlight both the importance of the mtbl improvement in the finite-length code construction and the possibility to tightly approach the performance of maximum distance separable codes.
routing and spectral efficiency in fading with alamouti coding at two parallel relays. this paper compares direct and relayed transmission in a simple four node configuration with a source, a destination and two parallel relays. the channel model assumes additive white gaussian noise, attenuation from path loss, and slow rayleigh fading. the two parallel relays use the alamouti code to relay data to the destination. using outage probability as a metric, we investigate the relative advantage of relaying as a function of relay placement and the required end-to-end spectral efficiency. we first quantify the benefit derived from adding a second relay to a one-relay network; we then calculate the "critical" rate, above which direct transmission always yields a lower outage probability. it is seen that the critical rate for a two-relay system (with diversity combining) is only modestly higher than that of a one-relay system - suggesting that the addition of more parallel relays is not an effective means of increasing the range of end-to-end rates over which relaying provides an advantage over direct transmission.
a self-organized spectrum assignment strategy in next generation ofdma networks providing secondary spectrum access. this paper proposes a self-organized spectrum assignment strategy in the context of next generation multicell orthogonal frequency division multiple access networks. the proposed strategy is able to dynamically find spectrum assignments per cell depending on the spatial distribution of the users over the scenario, opening new spectrum access opportunities for secondary spectrum usage. reinforcement learning methodology has been employed to implement the strategy, which compared with other fixed and dynamic spectrum assignment strategies shows the best tradeoff between spectral efficiency and quality-of-service while releases spectrum in large geographical areas.
resource allocation for frequency-selective fading, multi-carrier systems with fairness constraints. we consider the problem of fair resource allocation for multi-carrier systems. opportunistic scheduling exploits the time-varying, location-dependent channel conditions to achieve multi-user diversity. previous work in this area has focused on the single-user scheduling in single-carrier systems over a narrowband flat-fading channel, where only one node is scheduled at a time. in wideband multi-carrier systems, multiple nodes can be scheduled concurrently over multiple narrowband channels. in this paper, we analyze proportional fair scheduling (pfs) in multi-carrier systems over a wideband frequency-selective channel. in particular, we first derive analytical expressions for the throughput of opportunistic scheduling under proportional fairness constraints in a frequency-selective channel, for both single-user and multi-user systems. furthermore, we provide closed-form expression to quantify the throughput benefit of the multi-user pfs over the single-user pfs in frequency-selective systems. this research is an extension of our previous theoretical work on opportunistic scheduling over flat-fading channel in narrowband single-carrier systems.
slow adaptive ofdma via stochastic programming. fueled by the promises of high spectral efficiency, adaptive ofdma has attracted enormous research interests over the last decade. the significant capacity gain of adaptive ofdma comes from fast adaptation of resource allocation in response to instantaneous channel conditions. despite years of efforts to improve the practicality of adaptive ofdma, such promising technique is still far from real implementation due to the prohibitively high computational complexity and excessive control overhead. this paper is an endeavor to address the problem by proposing a slow adaptation scheme, where resource allocation is adapted on a much slower time scale than the fluctuation of wireless channel fading. specifically, the slow adaptive ofdma is formulated into a stochastic programming problem, which adapts resource allocation according to the channel statistics within an adaptation window rather than according to instantaneous channel conditions. by tuning the length of the adaptation window, we could engineer a desirable tradeoff between spectral efficiency and computational complexity. furthermore, the proposed scheme can be modified to accommodate inelastic traffics. the modification, referred to as "safe" slow adaptation, ensures worst-case data rates to all users. in this work, safe slow adaptation is formulated into a conic linear program, which is efficiently solved via interior-point methods. through extensive simulations, we show that the proposed schemes drastically reduce the computational complexity and control overheads, while achieving satisfactorily high spectral efficiency and qos provisioning as their fast-adaptation counterpart does with a much higher cost.
level biased random walk for information discovery in wireless sensor networks. in this paper, we consider the problem of information discovery in wireless sensor networks (wsns), where the search initiator is unaware of any of the γ locations of target information. one of the fundamental techniques which is used for this purpose is random walk since it has several advantages like low cost (number of bytes transmitted) compared to flooding, load balancing among nodes, and minimal state maintenance. even though random walk reduces cost, it is still high enough for energy constrained networks like wsns. furthermore, random walk incurs high latencies making it infeasible for delay sensitive applications. to alleviate the above mentioned problems in random walk, we propose a variant of random walk called level biased random walk (lbrw). in lbrw, the search packet traverses from the sink node (search initiator) to the circumference nodes (nodes without children) of the network and vice versa via random paths. the idea is to improve the node coverage of lbrw compared to that of random walk by forcing it to move in some particular directions. we show by extensive simulations that the cost and latency of lbrw are only 56-69% of that by random walk, when γ = 3 and at reasonable densities.
a graph approach to dynamic fractional frequency reuse (ffr) in multi-cell ofdma networks. a graph-based framework for dynamic fractional frequency reuse (ffr) in multi-cell ofdma networks is proposed in this work. ffr is a promising resource allocation technique that can effectively mitigate inter-cell interference (ici) in ofdma networks. the proposed scheme enhances the conventional ffr by enabling adaptive spectral sharing per cell load conditions. such adaptation has significant benefits in a practical environment where traffic load in different cells may be asymmetric and time-varying. the dynamic feature is accomplished via a graph approach in which the resource allocation problem is translated to a graph coloring problem. specifically, in order to incorporate various versions of ffr in our framework, we construct a graph that matches the specific version of ffr and then color the graph using the corresponding graph algorithm. the performance improvement enabled by the proposed dynamic ffr scheme is further demonstrated by computer simulation for a 19-cell network with asymmetric cell load. for instance, the proposed dynamic ffr scheme can achieve a 12% and 33% gain in cell throughput and service rate over conventional ffr, and render a 70% and 107% gain in cell throughput and service rate with respect to the reuse-3 system.
a modified exclusion mechanism and optimal routing algorithm in uwb networks. ultra-wide band (uwb) is a radio technology that uses a very large bandwidth. a two-dimensional exclusion mechanism and routing strategy are mentioned in [1]. we extend the exclusion region to three-dimension and modify the interference from other nodes as gaussian noise. the conclusion is also correct under mobility. we also present a new model combining exclusion mechanism and interference mitigation. then we propose an optimal routing algorithm described as mti. we raise a geometrical method unlike the simulation in [1] to demonstrate that the mer routing minimize the total interference and is the optimal routing.
wireless sensor networks localization with isomap. this paper studies the problem of determining the sensors' locations in wireless sensor networks. to alleviate the influence of the noise and the inaccurate measurement in the complicated environment, rather than estimating the pairwise euclidean distance between sensors, we use the geodesic distance to measure the dissimilarity between sensors, and employ the isomap algorithm to determine the relative locations of sensors. given sufficient anchors, the relative locations can be aligned to absolute locations by using coordinate transformation. the coordinate transformation matrix can be obtained by minimizing the sum of squares of the errors between the true locations of the anchors and their transformed locations. since isomap is parameter-sensitive, we also present an adaptive parameter selection procedure based on the locations of anchors. simulation results show that the isomap algorithm achieves smaller average location error with little quantity of anchors.
a directional broadcast protocol for emergency message exchange in inter-vehicle communications. broadcast is an effective approach for safety-related information exchange to achieve cooperative driving in vehicular ad hoc network (vanet). however, it suffers from several fundamental challenges such as message redundancy, link unreliability, hidden terminal and broadcast storm, etc., which degrade the efficiency of the network greatly. to address these issues, this paper proposes a position based multi-hop broadcast protocol (pmbp) for emergency message dissemination in inter-vehicle communications. by adopting a cross-layer approach considering both the mac and network layers in the proposed scheme, the candidate vehicle for forwarding an emergency message is selected according to its distance from the source vehicle in the message propagation direction. analysis and simulation results show that pmbp can not only quickly deliver emergency messages, but also reduce broadcast message redundancy significantly.
dynamic policy based model for trust based access control in p2p applications. dynamic self-organizing groups like wikipedia, and f/oss have special security requirements not addressed by typical access control mechanisms. an example is the ability to collaboratively modify access control policies based on the evolution of the group and trust and behavior levels. in this paper we propose a new framework for dynamic multi-level access control policies based on trust and reputation. the framework has interesting features wherein the group can switch between policies over time, influenced by the system's state or environment. based on the behavior and trust level of peers in the group and the current group composition, it is possible for peers to collaboratively modify policies such as join, update and job allocation. we have modeled the framework using the declarative language prolog. we also performed some simulations to illustrate the features of our framework.
authentication tests based on test type matrix. the theory of authentication tests is a powerful tool for analyzing and designing cryptographic protocols. however, it is difficult to apply the theory directly to prove the security goals of the protocols because determining the type of the test (e.g. outgoing, incoming and unsolicited test) is a little complex for computer and deriving the security properties of a test needs more intelligence. therefore, automatic security protocol analyzer cannot be implemented efficiently based on this theory. to solve this problem, in this paper we propose an authentication test type matrix (attm), which makes the identification of the test type very simple and straightforward. furthermore, we propose and prove a set of security properties associated with each case indicated by the elements in the attm, which can be used directly in protocol analysis and design. using the example of needham-schroeder protocol, we demonstrate that attm makes automatic security protocol verification and design much easier and more straightforward.
picocells with mimo and cell bonding for wlan systems. we consider a picocell system that implements multiple input multiple output (mimo) using cell bonding with one antenna per node. we show that this picocell system can initially have 1/2 or fewer access points (aps) with similar voice over ip coverage as a conventional system, yet can gracefully grow to the capacity of conventional systems with the same number of aps. although the coverage is somewhat lower for mimo (both 2×2 and 4×4), we show that through the use of dynamic antenna/node selection the picocell system with cell bonding can have similar coverage to conventional systems.
spectogram reconstruction from random sampling: application to the gsm band sensing. in the context of cognitive radios, we present a method to sense wideband radio spectra from randomly distributed samples with an average sampling rate smaller than the nyquist sampling rate. the method finds its roots in the compressed sensing paradigm. the gabor time-frequency is employed as a sparsifying transform to represent the radio signals generated in the framework of tdma/fdma based radio access technologies. indeed, many white spaces are observable in these wideband spectrograms. in addition, noisy measurements are modeled through the basis pursuit denoise formulation, which enables to reconstruct the time-frequency representation with some errors or information losses. the method is experimented on measured baseband radio signals sampled at 51.2mhz and acquired in the gsm 900 downlink band. finally, results about the effects of the algorithm parameters and about the algorithm complexity are provided and discussed.
an adaptive peer selection scheme with dynamic network condition awareness. locality-based peer selection paradigms have been proposed recently based on cooperation between peer-to-peer (p2p) service providers, internet service providers (isps) and end users in order to achieve efficient resource utilization by p2p traffic. based on this cooperation between different stakeholders, we introduce a more advanced paradigm with adaptive peer selection that takes into account traffic dynamics in the operational network. specifically, peers associated with low path utilization as measured by the isp are selected in order to reduce the probability of network congestion. this approach not only improves real-time p2p service assurance but also optimizes the overall use of network resources. our simulations based on the geant network topology and real traffic traces show that the proposed adaptive peer selection scheme achieves significant improvement in utilizing bandwidth resources as compared to static locality-based approaches.
towards a taxonomy of wired and wireless anonymous networks. with the aim to preserve privacy over a communications network, a plethora of anonymous protocols have been proposed along with many empirical investigations into specific adversary attacks over those networks. however, no known taxonomies exist that address anonymity in the diverse set of both wired and wireless anonymous communications networks. this paper proposes such a novel cubic taxonomy which explores the three key components of anonymity property, adversary capability, and network type. this taxonomy expands the definition of anonymity and aids in the advancement of state-of-the-art technological privacy-preserving mechanisms in anonymous networks against any adversary.
achieving exponential diversity in wireless multihop systems with regenerative relays. we present and analyze two different power allocation strategies for considerably improving the average bit error rate (ber) performance of wireless multihop systems with an arbitrary number of regenerative relay stations. in both cases, the power allocation is done based on instantaneous channel state information subject to an overall sum power constraint as well as possible additional per-node power constraints and it is optimal in terms of minimizing an upper bound on the average end-to-end ber. it is shown that for a general class of fading distributions with both schemes exponential diversity can be achieved and we express the corresponding upper bounds on the average ber in closed-form for the important case of nakagami-m fading on all hops. finally, the performance of our approach is illustrated and evaluated by means of both numerical and simulation results.
a novel graph model for dynamic multicast flow aggregation in optical networks. in this paper, we address the dynamic multicast flow aggregation problem and propose a novel graph model with different aggregation policies. we first give the network model with an auxiliary graph for the aggregation. we then discuss an aggregation algorithm using the auxiliary graph and propose three policies for aggregating multicast flows. numerical results show that aggregation can tremendously reduce the total trees in the network while the three policies can achieve good performance for various scenarios.
service cluster: a new framework for sla-oriented provisioning in wdm mesh networks. a service level agreement (sla) typically specifies the availability a service provider (sp) promises to a customer. current schemes usually employ backup resources to achieve high sla satisfaction. we propose a new provisioning framework, called service cluster (sc), which uses no explicit backup resources. by grouping several services with (typically) different availability specifications, an sc can dynamically reallocate resources to avoid sla violations. services that can tolerate additional down time lend resources to services that need to be kept running. we first analyze a condition for admission control. we then propose a dynamic resource allocation scheme (adt1 balancing scheme, sc-abs) and apply it to the sc framework. the dynamic management of sc-abs is realized by novel sla-violation estimation in an event-driven manner without continuous monitoring. we compare sc-abs with shared-path protection, and numerically show its various advantages in terms of: 1) higher sla satisfaction (up to 30% more); 2) lower service blocking ratio; 3) higher tolerance of failures; 4) more balanced sla satisfaction; and 5) consuming no explicit backup (or standby) resources. our scheme can meet the sla of significantly more services than protection-based schemes, thus providing more profit for the sp and lower cost for the customer.
designing demand-wise shared protection networks with specified minimum dual-failure restorability. we develop a new integer linear programming model to optimally design demand-wise shared protection (dsp) networks to achieve specified minimum levels of dual-failure restorability at minimum cost. findings suggest that dual-failure restorability levels of up to 40% can be achieved with minimal additional capacity relative to single-failure restorable designs. network designs approaching full dual-failure restorability require substantially greater amounts of spare capacity.
backbone construction for heterogeneous wireless ad hoc networks. in this paper, we propose a backbone construction scheme over heterogeneous ad hoc networks, where the network nodes have different characteristics such as communication capacity, processing power and energy resource. most of the wireless backbone construction techniques focus on minimizing the number of backbone nodes. in our proposed scheme, we not only minimize the backbone size, but also take the characteristics of nodes into account when building a backbone. in the scheme, the more capable nodes have higher probability to serve as backbone nodes and provide a wireless highway over which end-to-end communication can take place. the proposed scheme includes two major steps, which can be solved by formulating as a dominating set (ds) problem and a steiner tree problem with minimum number of steiner points (stp-msp) respectively. we focus on the two subproblems and present a number of polynomial time approximation algorithms. simulation results show that the proposed scheme achieves higher average backbone node performance, while has approximately the same backbone size comparing with other schemes.
model-tree-based rate adaptation scheme for vehicular networks. rate adaptation techniques have been extensively studied for traditional wireless lans as way to adjust the data transmission bandwidth as a function of the channel quality. however, existing solutions which are mostly based on statistics collection inherently experience a large delay in response to the wireless channel fluctuations, which is unsuitable for the rapid changing of the channel conditions in vehicular networks. in this paper, we propose an efficient self-adaptive model-tree-based rate adaptation scheme termed mtra that can predict the packet error rate (per) and adapt the data rate in real time. we also present a detailed methodology for the per model tree building and update. we have performed comprehensive experimentations using ns-2 simulations which demonstrate that mtra can achieve much better performance than the traditional rate adaptation approaches under various scenarios in vehicular networks.
an iterative list-based multiuser detector for overloaded receivers in a rayleigh fading channel. we consider a wireless communication system where multiple co-channel users transmit data via a synchronous, frequency-flat rayleigh fading channel. the receiver employs an antenna array. the paper develops an iterative list multiuser detector for overloaded applications where the number of transmitted signals exceeds the number of receive antennas. the receiver uses a linear preprocessor to reduce co-channel interference followed by a multiuser detector with an iterative groupwise symbol detection algorithm that extracts a list of the most likely user symbols. simulation results show that the proposed detector provides good complexity-performance trade offs.
on the performance improvements of max-sinr equalizers in wireless communications. in this work, we derive a blind equalizer that pursues the maximization of an objective function, consisting of the ratio between the square of the mean signal power and the variance of the signal power. the performance of the addressed equalizers is then investigated by focusing on ds/cdma communication environments in a downlink scenario. in particular, we have evidenced the effectiveness of the presented equalizer in the numerical examples, in terms of robustness against the effect of interference, as well as in terms of convergence rate, in spite of a small amount of extra processing
symbol based search space constraining for complexity/performance scalable near ml detection in spatial multiplexing mimo ofdm systems. for both outdoor and indoor wireless systems there is an increasing demand of high spectral efficiency at a very low cost and power consumption. in this context, mimo wireless system adopting spatial multiplexing offer a way of increasing the spectral efficiency of the system. in order to fully exploit this capacity non linear mimo detectors such as maximum likelihood detectors are required. however, when high order modulation schemes are applied, the complexity of this kind of detector becomes prohibitive for a practical implementation. as a solution to this problem, low complexity maximum likelihood detectors such as sphere detectors are appealing as a low complexity solution for high spectral efficiency transmission. although sphere decoding provides a lower complexity solution than a classical ml detector, its complexity still remains unpredictable and exponentially dependent on channel propagation conditions. this variability in complexity makes the implementation of sphere decoders not practical. in this paper, a new approach for constraining the ml search space is proposed which provides a predictable upper bound for complexity, hence facilitating its implementation. moreover, the new approach for computing the constrained search space significantly reduces the complexity of the detection while offering scalability in terms of performance and complexity. simulation results in a cellular system demonstrate the scalability of our detector and the performance/complexity trade-off that it enables.
joint effect of multiple correlated cameras in wireless multimedia sensor networks. wireless multimedia sensor networks (wmsns) are interconnected devices that allow retrieving video and audio streams, still images, and scalar data from the environment. in a densely deployed wmsn, there exists correlation among the visual information observed by cameras with overlapped field of views. in this paper, the correlation characteristics of visual information are used to address two issues: 1) how to measure the amount of visual information provided by multiple cameras in the network, and 2) how to select a group of cameras to report their information to the sink under distortion constraints. an entropy-based analytical framework is developed to measure the amount of visual information provided by multiple correlated cameras first. based on this framework, a correlation-based camera selection scheme is introduced. simulation results show that, given a distortion bound at the sink, the correlation-based selection scheme requires fewer cameras to report to the sink than the random selection scheme.
approximation algorithm for qos routing with multiple additive constraints. in this paper, we study the problem of computing the supported qos from a source to a destination with multiple additive constraints. the problem has been shown to be np-complete and many approximation algorithms have been developed. we propose a new approximation algorithm called multi-dimensional relaxation algorithm. we formally prove that our algorithm produces smaller approximation error than the existing algorithms. we further verify the performance by extensive simulations.
design and implementation of physical layer private key setting for wireless networks. due to the enormous spreading of applied wireless networks, security is actually one of the most important issues for telecommunications. one of the main issue in the field of securing wireless information exchanging is the initial common knowledge between source and destination. a shared secret is normally mandatory in order to decide the encryption (algorithm or code or key) of the information stream. it is usual to exchange this common a priori knowledge by using a "secure" channel. now a days a secure wireless channel is not possible. in fact normally the common a priori knowledge is already established (but this is not secure) or by using a non-radio channel (that implies a waste of time and resource). this contribution deals with the proposal of a new modulation technique ensuring secure communication in a full wireless environment. the information is modulated, at physical layer, by the thermal noise experienced by the link between two terminals. a loop scheme is designed for unique recovering of mutual information. the probability of error/detection is analytically derived for the legal users and for the third unwanted listener. the proposed scheme has also been implemented in a xilinx virtex ii fpga. all the results show that the performance of the proposed scheme yields the advantage of intrinsic security, i.e., the mutual information cannot be physically demodulated (passive attack) or denied (active attack) by a third terminal, leading us to conclude that the proposed technique is really useful for private key distribution in every wireless network.
distributed communication control mechanisms for ad hoc networks. we considered a single hop ad-hoc network consisting of n source-destination pairs. each transmitter is endowed with a finite buffer and accepts packets from a poisson distributed arrival process. the channel is described by a markov chain. we investigate distributed algorithms for joint admission control, rate and power allocation aiming at maximizing the individual or the global throughput defined as the average information rate successfully received. the decisions are based on the statistical knowledge of the channel and buffer states of the other communication pairs and on the exact knowledge of their own channel and buffer states. the problems are formulated as a cooperative and noncooperative games and reduced to the mathematical framework of the variational inequalities problems. the proposed algorithms provide sizable improvements with respect to straightforward extension of decentralized algorithms for multiple access channels to ad hoc networks.
optimal weighted antenna selection for imperfect channel knowledge from training. receive antenna selection (as) reduces the hardware complexity of multi-antenna receivers by dynamically connecting an instantaneously best antenna element to the available radio frequency (rf) chain. due to the hardware constraints, the channels at various antenna elements have to be sounded sequentially to obtain estimates that are required for selecting the "best" antenna and for coherently demodulating data. consequently, the channel state information at different antennas is outdated by different amounts. we show that, for this reason, simply selecting the antenna with the highest estimated channel gain is not optimum. rather, the channel estimates of different antennas should be weighted differently, depending on the training scheme. we derive closed-form expressions for the symbol error probability (sep) of as for mpsk and mqam in time-varying rayleigh fading channels for arbitrary selection weights, and validate them with simulations. we then derive an explicit formula for the optimal selection weights that minimize the sep. we find that when selection weights are not used, the sep need not improve as the number of antenna elements increases, which is in contrast to the ideal channel estimation case. however, the optimal selection weights remedy this situation and significantly improve performance.
joint reduction of peak to average power ratio and symbol loss rate in multicarrier systems. peak to average power ratio (papr) and symbol loss rate (slr) are two challenges of multicarrier based communications that have recently drawn much attention. high slr renders the system unreliable and high papr is associated with power inefficiency and nonlinearity of the system. there are rich literatures studying these two issues separately but, unfortunately, only a few works have studied simultaneous reductions of papr and slr. this paper studies the problem of reducing the papr while keeping the slr at minimum. in [1], we derived the conditions for the minimum slr in on-off channels. the algorithm proposed in this paper simultaneously satisfies the conditions derived in [1] and reduces the papr substantially. this paper differs from previous techniques in the sense that none of the previously proposed techniques are capable of reducing papr substantially while achieving the minimum symbol loss rate. we compare our algorithm with the optimum selected mapping papr reduction method, which is well known in the literature for having a strong reduction capability. the comparison is done in terms of complementary cumulative distribution function (ccdf) of the papr of the multicarrier signal. the simulation results show that our algorithm can achieve a stronger papr reduction while maintaining the minimum slr.
rate and power adaptation for increasing spectrum efficiency in cognitive radio networks. we propose rate and power adaptation strategies to optimize data transmission over fading channels in a spectrum sharing system operating under average received-interference constraint at the licensed user (primary user). specifically, considering availability of the channel state information (csi) pertaining to the secondary link and spectrum-sensing information about the activity state of the primary user, we investigate two adaptation policies at the secondary user's transmitter, namely, variable power and variable rate and power, over rayleigh fading channels. the adaptation policies are obtained by maximizing the achievable capacity under said constraint and bit error rate (ber) requirements in multilevel quadrature amplitude modulation (m-qam). we asses the benefits of using soft-sensing information about the primary user's activity on rate and power adaptation in spectrum sharing systems, and provide numerical results and comparisons illustrating performance for different operating scenarios.
low complexity antenna selection scheme for multiuser mimo broadcast systems. in this paper, a low complexity antenna selection scheme for multi-antenna broadcast systems is developed. using sum-rate capacity maximisation as the selection criteria, the proposed scheme exploits the duality principle of broadcast and multiple access channel in order to reduce the computational complexity. the performance of the proposed scheme under i.i.d. rayleigh fading channel is then evaluated via monte carlo simulation under different system parameters, and its performance is compared to the full complexity brute force scheme. it is demonstrated that the scheme is able to achieve most of the gain available in the system with a considerably lower complexity.
secure signaling in next generation networks with nsis. the ietf working group next steps in signaling (nsis) develops signaling protocols for quality-of-service (qos) reservations or dynamic nat and firewall (nat/fw) configuration. qos signaling allows for on-demand resource reservations in order to provide guaranteed quality-of-service for real-time oriented services in ip-based next generation networks whereas nat/fw signaling allows for establishing pinholes in firewalls or bindings in nat devices. qos signaling must be secured to allow for a reliable accounting and nat/fw configuration is a sensitive operation per se. this paper presents an approach that provides an integrity protection of nslp signaling messages by extending an nslp session authorization object. a worked example for secure qos signaling in a kerberos-secured domain is given.
a scalable block cipher design using filter banks and lifting over finite fields. a scalable block cipher based on a filter bank structure over gf(28) is proposed. the filter bank structure is used to introduce the diffusion during the circular convolution process between the filters coefficients (which are generated from the key) and the plaintext. the confusion is achieved by the mixing between the analysis filter bank and a novel lifting scheme. the proposed cipher is scalable in both block and key lengths. the cipher is shown to be secure against differential and linear cryptanalysis and of comparable complexity to the aes.
an energy-efficient integrated mac and routing protocol for wireless sensor networks. in recent integrated mac/routing solutions for wireless sensor networks (wsns), hop-count is exploited to build a coarse-grained logical coordinates to help forward packets towards the direction of sink. this method can retain the merits of geographic routing at the absence of exact location knowledge. however, these solutions may present low energy-efficiency and unacceptable delays in real networks since they seldom consider the impacts of low duty-cycling and link unreliability on routing. furthermore, geographic advancement of forwarding in hop-count based coordinates is very unreliable and even towards the reverse direction. in this work, average power cost to the sink of each node is considered together with hop-count to build a fine-grained logical coordinates, which can help forward packets towards the direction of sink more accurately. then we propose an energy-efficient integrated mac/routing (eemr) protocol for event-driven and time-critical applications based on new logical coordinates. the optimal relay is elected in each hop dynamically, where the objective is to optimize forwarding energy-efficiency on the premise that end-to-end delay is restricted under the predefined upper bound. analysis and extensive simulations are given to demonstrate the superiority of eemr by comparing its performance against existing solutions.
analysis, insights and generalization of a fast decentralized relay selection mechanism. relay selection for cooperative communications has attracted considerable research interest recently. while several criteria have been proposed for selecting one or more relays and analyzed, mechanisms that perform the selection in a distributed manner have received relatively less attention. in this paper, we analyze a splitting algorithm for selecting the single best relay amongst a known number of active nodes in a cooperative network. we develop new and exact asymptotic analysis for computing the average number of slots required to resolve the best relay. we then propose and analyze a new algorithm that addresses the general problem of selecting the best q ≥ 1 relays. regardless of the number of relays, the algorithm selects the best two relays within 4.406 slots and the best three within 6.491 slots, on average. our analysis also brings out an intimate relationship between multiple access selection and multiple access control algorithms.
loop-free forwarding table updates with minimal link overflow. the forwarding paths in an ip network may change due to a link failure, network equipment maintenance, or reconfiguration of link weights. the forwarding tables in the routers need then to be updated. these updates may cause transient loops and link overflow, if they are not performed in an appropriate order. while existing proposals achieve loop-free updates, transient link overflow is still a problem during the updating process. in this paper, we present a method that compares the initial and final forwarding paths, and obtains the updatable nodes that do not cause any transient loop or link overflow. however, this goal is not always achievable, therefore, we propose an algorithm to update the forwarding tables that will refrain the link overflows to a minimal level. the performance study on a real topology with two setups confirms that our approach achieves smaller link overflow than by using a previously proposed approach.
cognitive radio policy languages. this paper characterizes key issues in establishing a policy language for ieee standards activity p1900.5 to shape radio behavior that realizes social contracts and business logic via cognitive radio policy languages (crpl). this paper shows the current lack of consensus on the scope and needs of policy languages, tracing roots to differences among regulatory, financial, business, and technical domains. cognitive linguistics, an emerging theory of human language acquisition and use shows why this is the case and may assist in formulating a crpl that addresses the diverse policy needs of the regulatory and business communities as well as the narrower issues of dynamic spectrum.
performance analysis of double-channel 802.11n contending with single-channel 802.11. due to their ease of deployment, 802.11 networks are widely used. to cope with increasing throughput requirements, and to take advantage of improvements in hardware performance, 802.11n has been introduced. one of the extra features is the 20/40 functionality, which allows 802.11n devices to operate using one or two 802.11 channels. in this paper, we study the contention rules for such 20/40 operation on top of the 802.11 distributed coordination function (dcf). we then study the performance of double-channel users in presence of single-channel 802.11 users. similar to the 802.11 model introduced by bianchi, we introduce a markov model for both the legacy 802.11 and double-channel 802.11n users. to couple the markov models of both types of users, we have to understand how to relate virtual time slots of both types. next, we introduce collision rules that capture traditional in-channel 802.11 collisions as well as collisions between the different types of users. this allows us to complete the analytical throughput model for 802.11 and double-channel 802.11n users when they coexist. the conclusions are important for understanding 802.11 networks in particular, but also for contention of heterogeneous devices in general.
on reliable transmission by adaptive network coding in wireless sensor networks. in wireless sensor networks (wsns), due to scarce resources like energy, computational capability and storage space as well as rapid change in wireless link characteristics such as signal strength, interference, and multi-path propagation, how to provide a reliable data transmission in wsns while prolonging the network lifetime as long as possible is an important and challenging issue. in general, there are several approaches, e.g., automatic repeat request, multi-path routing and source coding, used for providing reliable data transfer in wsns. we note that the overhead and performance of such end-to-end single-path approaches are often dominated by some poor-quality links or nodes on the path. that is, these traditional approaches are not able to quickly and properly react in this multi-hop wireless environment. to cope with the above issues, in this work we would like to propose an efficient reliable data transfer scheme with network coding for wsns. to guarantee expected reliability with appropriate overhead, we not only derive an analytic model to estimate the proper amount of redundancy, but also propose the cluster-based and distributed scheme to dynamically adjust the redundancy at each hop. through simulations in ns2, our results show that, compared with existing reliable data transfer schemes, our approach can achieve the required reliability with significantly fewer transmissions.
co-channel interference mitigation for 3g lte mimo-ofdm systems. we propose an algorithm to reject co-channel interference in 3gpp long term evolution (lte) multiple input multiple output orthogonal frequency division multiplexing (mimo-ofdm) systems. an improved channel estimation method and interference rejection algorithm are discussed. the interference information is measured on the pilot sub-carriers which are sent regularly in time and frequency. an improved model averaged interference mitigation method parameterizes the interference and noise spatial-covariance-matrix on each carrier as a combination of several low-rank models, each associated with probability soft information. a reduced complexity a posteriori receiver is derived based on the low-rank spatial covariance model. parameterizing the interference and noise covariance matrix helps in adapting receiver for different interference scenarios. simulation results are provided to demonstrate the efficacy of the model averaged interference rejection method applied to mimo-ofdm system.
preprocessing dns log data for effective data mining. the domain name service (dns) provides a critical function in directing internet traffic. defending dns servers from bandwidth attacks is assisted by the ability to effectively mine dns log data for statistical patterns. processing dns log data can be classified as a data-intensive problem, and as such presents challenges unique to this class of problem. when problems occur in capturing log data, or when the dns server experiences an outage (scheduled or unscheduled), the normal pattern of traffic for that server becomes clouded. simple linear interpolation of the holes in the data does not preserve features such as peaks in traffic (which can occur during an attack, making them of particular interest). we demonstrate a method for estimating values for missing portions of time sensitive dns log data. this method would be suitable for use with a variety of datasets containing time series values where certain portions are missing.
coverage prediction in urban environments for inter-system mobility simulations. next-generation mobile networks will offer wireless coverage through heterogeneous radio accesses. the possibility of realistically simulating advanced mobility scenarios in such networks, with the users roaming across different radio technologies, depends on the availability of light models capable of predicting the users' mobility and the wireless coverage offered by the heterogeneous infrastructure. the article proposes an analysis of the criteria to identify proper wireless coverage models and shows how to use the uniform geometrical theory of diffraction and a ray-tracing approach to build up a low complexity model capable of fulfilling such criteria.
an efficient regularized semi-blind estimator. this paper addresses the issue of the optimization of the regularization constant in semi-blind channel estimation techniques, in which the training sequence-based criterion is combined linearly with the blind subspace criterion. in such semi-blind estimation techniques, the optimization of the regularizing constant with respect to the channel estimation error is mandatory, otherwise, the expected improvement in performance could not be achieved. in this context, recent works proposed numerical methods for the setting of the regularization constant. however, these methods are often sub-optimum and involve high computational complexities. in this paper, we propose to optimize with respect to a regularizing matrix instead of a regularizing scalar. we prove that interestingly in this case, a closed-form expression for the optimum regularizing matrix exists, thereby avoiding iterative algorithms as for the conventional techniques. we also prove that the obtained scheme has slightly better performance in terms of mean square error and bit error rate while ensuring lower complexity.
time and frequency synchronization for power line ofdm systems with colored noise. a pilot aided joint symbol timing and frequency offset estimator for ofdm systems over power line channel (plc) with colored noise is proposed in this paper. in the proposed estimator, the received time domain ofdm samples are first divided into groups where noise samples are approximately independent. initial maximum likelihood (ml) based symbol timing and frequency offset estimates are obtained based on each group and final estimate is then derived by combining the initial estimates. we further simplify the proposed estimator to a practical one which does not require the knowledge of plc fading profile, noise profile and signal-to-noise-ratio (snr). the simulation results show that, under the presence of colored noise, the proposed practical symbol timing estimator achieves performance gain in terms of correct synchronization probability, around 2db at snr=15db, and with improved mean square error (mse) performance, compared to the widely adopted estimator in [6], .with the knowledge of the statistics of colored noise, another algorithm is also proposed to further improve the estimation performance.
reducing power consumption in backbone networks. according to several studies, the power consumption of the internet accounts for up to 10% of the worldwide energy consumption, and several initiatives are being put into place to reduce the power consumption of the ict sector in general. to this goal, we propose a novel approach to switch off network nodes and links while still guaranteeing full connectivity and maximum link utilization. after showing that the problem falls in the class of capacitated multi-commodity flow problems, and therefore it is np-complete, we propose some heuristic algorithms to solve it. simulation results in a realistic scenario show that it is possible to reduce the number of links and nodes currently used by up to 30% and 50% respectively during off-peak hours, while offering the same service quality.
architecture of run-time reconfigurable channel decoder. modern wireline and wireless communication devices are multimode and multifunctional communication devices. in order to support multiple standards on a single platform, it is necessary to develop a reconfigurable architecture that can provide the required flexibility and performance. the channel decoder is one of the most compute intensive and essential elements of any communication system. most of the standards require a reconfigurable channel decoder that is capable of performing viterbi decoding and turbo decoding. furthermore, the channel decoder needs to support different configurations of viterbi and turbo decoders. in this paper, we propose a reconfigurable channel decoder that can be reconfigured for standards such as wcdma, cdma2000, ieee802.11, dab, dvb and gsm. different parameters like code rate, constraint length, polynomials and truncation length can be configured to map any of the above mentioned standards. a multiprocessor approach has been followed to provide higher throughput and scalable power consumption in various configurations of the reconfigurable viterbi decoder and turbo decoder. we have proposed a hybrid register exchange approach for multiprocessor architecture to minimize power consumption.
ber performance of multibeam satellite systems with tomlinson-harashima precoding. a multibeam satellite system can be modelled as a multiple-input multiple-output (mimo) system with an inter-beam interference matrix that is derived from the positions of the users in the different beams. this way it is possible to apply precoding techniques, such as tomlinson-harashima precoding (thp), to mitigate the interference. this paper presents an analytical framework to model the interference by a simple and effective parameter, which enables to assess the uncoded bit error rate (ber) of thp in such a scenario, and to derive useful hints on the optimization of the overall system capacity.
effects of user behavior on mmorpg traffic. game traffic depends on two main factors, the game protocol and the gamers' behavior. based on a few popular real-time multiplayer games, this paper investigates the latter factor showing how a set of typical game phases-e.g., player movement, changes in environment-impacts traffic. by understanding the nature of this impact an algorithm is introduced to grab specific events and states from passive traffic measurements. further, a measurement example including a detailed analysis is shown from an operational broadband network. the collected data of player behavior in the gaming environment was analyzed and it was also shown that the long range dependence (lrd) property of gaming traffic is not due to the popular explanation based on the heavy-tailed periods of player activities.
optimal network selection in heterogeneous wireless multimedia networks. the complementary characteristics of different wireless networks make it attractive to integrate a wide range of radio access technologies. most of previous work on integrating heterogeneous wireless networks concentrates on network layer quality of service (qos), such as blocking probability and utilization, as design criteria. however, from a user's point of view, application layer qos, such as multimedia distortion, is an important issue. in this paper, we propose an optimal distributed network selection scheme in heterogeneous wireless networks considering multimedia application layer qos. specifically, we formulate the integrated network as a restless bandit system. with this stochastic optimization formulation, the optimal network selection policy is indexable, meaning that the network with the lowest index should be selected. the proposed scheme can be applicable to both tight coupling and loose coupling scenarios in the integration of heterogeneous wireless networks. simulation results are presented to illustrate the performance of the proposed scheme.
multiuser mac protocols for 802.11n wireless networks. the emerging 802.11n standard establishes the integration of mimo technology in wlans with the goal of achieving high data rates. however there are still many open issues regarding mac protocol design for mimo based systems, especially in order to exploit the multiuser capabilities of the mimo channel. in this paper we investigate practical solutions to implement multiuser downlink transmission in infrastructure 802.11n based wlans. a low-complexity beamforming transmission technique is employed at the physical layer and four mac schemes that vary in complexity and efficiency are presented and evaluated through computer simulations.
the two-way mimo wire-tap channel. we introduce the two-way mimo wire-tap channel and convey its potential to provide information-theoretic secure communications. we mainly address two challenges, namely the channel estimation and the single-user decodability issues. for the former, as the channel estimation becomes trickier owing to self-interference, we propose that users project their training signals on orthogonal subspaces to ensure their separability upon reception. for the latter, we suggest that each user uses, among the available antennas only the antenna subset that ensures both peers are not single-user decodable while maximizing their achievable secrecy sum-rate. thus, unlike the result reported in literature about the two-way single-antenna wire-tap channel, we demonstrate that it is possible to achieve a positive secrecy rate even when a user is single-user decodable, provided that a sufficient number of transmit antennas be available. finally, we observe that the proposed scheme, unlike secrecy schemes based on wyner's degraded wire-tap channel, provides positive secrecy sum-rate even when the eavesdropper's channels incur as little noise as the legitimate users', and maintains the secrecy rate's growth in the high snr regime, a fact we demonstrate by computer simulations. this makes the proposed scheme a better candidate for high-throughput secrecy applications.
privacy-enhanced user-centric identity management. user-centric identity management approaches have received significant attention for managing private and critical identity attributes from the user's perspective. user-centric identity management allows users to control their own digital identities. users are allowed to select their credentials when responding to an authentication or attribute requester and it gives users more rights and responsibility over their identity information. however, current user-centric approaches mainly focus on interoperable architectures between existing identity management systems and privacy issues have not been considered in depth. in this paper, we propose a category-based privacy preference approach to enhance the privacy of user-centric identity management systems. in addition, we present our proof-of-concept prototype of our approach in the identity metasystem.
bayesian potential games to model cooperation for cognitive radios with incomplete information. this paper presents a bayesian potential game to model distributed joint power and channel allocation for cognitive radios with incomplete information. we propose a cooperative approach where secondary users (sus) devote part of their transmission power in licensed channels to relaying primary users' (pus) messages. in addition, we consider incomplete information in the decision making process, so as to avoid the need for a common control channel (ccc), where users share information. this hypothesis improves the robustness and feasibility of the cognitive radio network supported by the proposed approach. simulation results show that cooperation benefits both pus and sus and that the lack of complete information in the decision process slightly reduces performances in terms of signal to interference and noise ratio (sinr) and outage probability.
improved joint source-channel decoding of jpeg2000 images and reed-solomon codes. in this paper we present improvements to the recently-proposed joint decoding of jpeg2000 bitstreams and reed-solomon codes in the context of unequal loss protection. using error resilience features of jpeg2000 bitstreams, the joint decoder helps to restore the erased symbols when the reed-solomon decoder fails to retrieve them on its own. we make use of the ability of the jpeg2000 decoder to provide rough error localization within a coding pass to speed up the search for erased symbol values. in addition, we show how transmitting a relatively small amount of side information with high reliability may help the joint decoder by reducing the size of the search space and bypassing some of the jpeg2000 decoding iterations needed to verify the correctness of the restored source information. the improved joint decoder is up to 20 times faster compared to the previous one.
energy saving ad-hoc on-demand distance vector routing for mobile ad-hoc networks. a mobile ad-hoc network (manet) is usually power constrained due to the limited battery energy on each node. for manets, energy efficiency is crucial for the design of new routing protocols. in this paper, a new energy-aware routing algorithm, called energy saving ad-hoc on-demand distance vector (esaodv) routing, is proposed. in the route discovery process of esaodv, intermediate nodes estimate the current average energy of the network (caen) as a comparison threshold to determine how to respond to the received route request (rreq) packets. after that, the effects of esaodv on network performance are addressed. analytical and simulation results show that the proposed esaodv can effectively protect the energy-overused nodes and can greatly prolong the network lifetime.
service engineering for inter-domain overlay networks. in recent years application-level networking (e.g. overlay networks, p2p networks) has become key enabling architecture for supporting distributed services on the internet. we consider overlays to have delay and cost requirements and thus there exists an optimal distribution of the overlay traffic (the service engineering problem) across multi-domain underlay networks such that these requirements can be satisfied while achieving fairness among the overlays. to this end, we formulate the problem as a convex optimization problem and propose a distributed solution. we show the efficiency and effectiveness of our approach through simulation studies.
compressed sensing maximum likelihood channel estimation for ultra-wideband impulse radio. one of the most attractive features of ultra-wideband impulse radio is the collection of rich multipath with the transmission of ultra-short pulses. exploiting the rich multi-path diversity with channel estimating rake receivers enables significant energy capture, higher performance and flexibility than suboptimal receivers. although data-aided (da) maximum likelihood (ml) channel estimator shows a promising performance, its implementation is restricted by the nyquist sampling criterion. the emerging theory of compressed sensing (cs) describes a novel framework to jointly compress and detect a sparse signal with fewer samples than the traditional nyquist criterion. in this paper, we propose a cs-ml channel estimator which combines the compression framework of cs for sampling rate reduction while retaining the noise statistics formulation of ml to achieve a reliable performance. simulation assessment indicates that, with far fewer measurements, the performance of our proposed scheme supersedes that of the l1-norm minimization estimator of cs and can be as close as the ml, but with a reduction in complexity.
three-stage concatenated ultra-wide bandwidth time-hopping spread-spectrum impulse radio using iterative detection. the powerful tool of extrinsic information transfer (exit) charts is used to design a new serially concatenated irregular variable length coded (irvlc) and unity-rate precoded time-hopping (th) pulse position modulation (ppm) aided ultra-wide bandwidth (uwb) spread-spectrum (ss) impulse radio for near-capacity operation in nakagami-m fading channels contaminated by partial band noise jamming (pbnj). the benefits of the 3-stage concatenation of the th-uwb detector, the unity-rate decoder and the outer irvlc decoder are quantified. a number of novel variable length coding (vlc) codebooks having different coding rates are utilized by the irvlc scheme for encoding specific fractions of the input source symbol stream. more explicitly, exit charts are employed to appropriately select these input stream fractions to shape the inverted exit curve of the irvlc in order to match that of the inner decoder and hence to achieve an infinitesimally low bit error ratio (ber) at near-capacity snr values.
on quantizer design for soft values in the multiple-access relay channel. a network with two sources, one relay, and one destination is considered. under the assumption of noisy source-relay links causing the relay to be unable to decode without error, we propose a quantizer design framework where the quantizer jointly compresses the soft information available for both sources at the relay. the quantizer design is based on the information bottleneck method using the notion of relevant information as an optimization criterion.
antenna diversity schemes for uplink frequency-domain multiuser detection in cp-assisted ds-cdma systems. in this paper, antenna diversity (ad) schemes are presented for frequency-domain (fd) multi-user detection (mud) in the up-link (ul) of cellular systems which apply cp (cyclic prefix) assisted ds-cdma (direct sequence code division multiple access). alamouti-based space-time-code (stc) was applied to exploit transmitter (tx) diversity. the mud and the diversity combining in the receiver (rx) are mmse (minimum mean square error) based. simulation results show that with moderate computational complexity, the simo and mimo schemes have achieved better performance than the iterative block decision feedback equalization (ib-dfe) based scheme in [1]. it was also shown that simo is superior to miso in terms of diversity exploitation and achieves the best tradeoff between complexity and performance.
joint synchronization and channel estimation for ofdm transmissions over doubly selective channels. this paper proposes a pilot-aided joint channel estimation and synchronization scheme for burst-mode orthogonal frequency division multiplexing (ofdm) systems over time- and frequency-selective (doubly selective) channels. based on the basis expansion model (bem) for representing doubly-selective channels, a least-square (ls) cost function of carrier frequency offset (cfo) and bem coefficients is formulated for the joint estimation problem. by applying the first-order taylor series expansion, an approximately linearized estimation error is obtained to facilitate a recursive least-square (rls)-based joint cfo and bem estimation with the aid of pilot ofdm symbols. simulation results demonstrate that, over a wide range of doppler spreads, the proposed estimation scheme offers a high robustness against the time variation of fast fading channels and outperforms the linear minimum mean-square (lmmse) algorithm [6] using cfo estimates provided by the cfo estimation technique in [11].
tap: an adjustable planar structure for adaptive topology control in wireless ad hoc networks. in wireless ad hoc networks, a planar topology enables nodes to deliver packets without a routing table. pervious planar structures are fixed for the whole network. however, environmental or network dynamics such as channel status, interference or energy will prevent such structures from providing the best service to the network. in this paper, we present a t-adjustable planar structure (tap) which enables nodes to adjust the topology independently and allows nodes to have different path loss exponent. we show by proof or simulation properties of tap: (1) it preserves connectivity; (2) it is planar, sparse and symmetric; (3) it preserves all minimum energy path when t = 1 for all nodes; (4) the average transmission power, interference and node degree decrease as t increases and the maximum node degree is bounded by 6 when t = 3 for all nodes.
coverage-aware connectivity restoration in mobile sensor networks. mobile sensor networks rely heavily on inter-sensor connectivity for collection of data. nodes in these networks monitor different regions of an area of interest and collectively present a global overview of some monitored activities or phenomena. a failure of a sensor leads to loss of connectivity and may cause partitioning of the network into disjoint segments. a number of approaches have been recently proposed that pursue node relocation in order to restore connectivity. however, these approaches tend to ignore the possible loss of coverage in some areas, either due to the failure itself or due to the connectivity-limited focus of the recovery. this paper fills this gap by addressing the connectivity and coverage concerns in an integrated manner. a novel coverage conscious connectivity restoration (c^3r) algorithm is presented. c^3r involves one or multiple neighbors of the failed node to recover from the failure. each neighbor temporarily relocates to substitute the failed node, one at a time, and then returns back to its original location. this leads to intermittent connectivity and monitoring of all the originally covered spots. this paper also presents energy-centric optimized recovery algorithm (ecr), an optimized version of c^3r that is geared for energy efficiency. both c^3r and ecr are validated through simulation. the simulation results confirm the effectiveness of these approaches.
a mathematical view of network-based suppressions of worm epidemics. when worms self replicate, their probe traffic increases the network load. it is known that some "bandwidth-limited" worms such as slammer spread so rapidly that they impede their own progress by congesting the network. existing worm epidemic models do not take into consideration the phenomenon of network congestion acting naturally to slow down the epidemic rate. in this paper, we present a new epidemic model, the community of households with limited inter-household bandwidths (coh-lihb), which we believe is the first model to account for limited network capacity and its impact on the spreading rate of a random scanning worm. in addition to explaining the natural dampening effect of network congestion, we use the new model to study the effectiveness of active defenses, namely dynamic quarantine and rate limiting, which artificially restrict the bandwidth available to worm traffic. the cohlihb model is applied to the specific example of a slammer-like worm to show how the combination of quarantine and rate throttling hypothetically could have been effective in suppressing the slammer outbreak.
fragmentation and aes encryption overhead in very high-speed wireless lans. in this paper, we study the overhead introduced by the advanced encryption standard cipher in the context of wireless lans, specifically at the medium access control layer, as described in the 802.11 standard developed by the 802.11n task group. we compute the maximum throughput, optimal frame, and fragment sizes which can be achieved in this context and compare them to the optimal values when encryption is not used.
an efficient software radio framework for wimax physical layer on cell multicore platform. wireless baseband processing, which is characterized by high computation complexity and high data throughput, is regarded as the most challenging issue for software radio (sr) systems. to relieve this implementation difficulty in sr systems, the multicore architecture is proposed. however, due to the lack of the universal parallel programming framework for sr systems, it is difficult to take full advantage of the multicore architecture. to fill this gap, in this paper, an efficient parallel sr framework is proposed under the cell multicore architecture for wimax base station (bs). with the proposed framework, one cell blade server (including two cell processors) can support up to three sectors, and each sector can support 20mbps data rate for both uplink and downlink. the system performance results verify the effectiveness of the proposed sr multicore framework.
on the performance of harq with hybrid relaying schemes. in this paper, we consider a three-node relay system with a hybrid relaying scheme, where the relay, based on its decoding status, switches between decode-and-forward (df) and compress-and-forward (cf) adaptively. we propose according harq strategy and analyze its throughput performance. then, we consider practical implementation issues by enhancing the ability of the feedback channel from the destination to the relay to convey a few extra bits (only 2 bits in this paper) and propose a modified harq scheme accordingly. the combined technique exhibits superior performance over direct transmission and conventional df.
a multi-agent reinforcement learning approach to path selection in optical burst switching networks. an important issue of research in optical burst switching (obs) networks is to minimize the loss of bursts due to contention at the intermediate nodes. these contention losses can be minimized with the design of efficient path selection algorithms at the ingress node. path selection algorithms that learn the optimal path dynamically with the changing traffic conditions outperform the deterministic path selection algorithms. usually in the single agent path selection algorithms, a path is selected by the agent based on the feedback received at the ingress node which does not capture the effect of the paths selected by the other nodes in the network. we develop a multi-agent approach for path selection that includes the effect of the selection made by all the other nodes in the network. the proposed path selection algorithm uses agents at different source nodes to collectively learn the network dynamics and select the best outgoing path for each burst. we present simulation results to demonstrate the effectiveness of the proposed algorithm over the other similar algorithms in the literature.
optimal sleep-wake policies for an energy harvesting sensor node. we study a sensor node with an energy harvesting source. in any slot, the sensor node is in one of two modes: wake or sleep. the generated energy is stored in a buffer. the sensor node senses a random field and generates a packet when it is awake. these packets are stored in a queue and transmitted in the wake mode using the energy available in the energy buffer. we obtain energy management policies which minimize a linear combination of the mean queue length and the mean data loss rate. then, we obtain two easily implementable suboptimal policies and compare their performance to that of the optimal policy. next, we extend the throughput optimal policy developed in our previous work to sensors with two modes. via this policy, we can increase the throughput substantially and stabilize the data queue by allowing the node to sleep in some slots and to drop some generated packets. this policy requires minimal statistical knowledge of the system. we also modify this policy to decrease the switching costs.
differentiated static resource allocation in wdm networks. we present a study on the static resource allocation in lightpath routed wdm networks, where each request is associated with a service grade. the goal is to maintain certain acceptance ratios for the requests of all grades, as well as to minimize the resource consumption. we propose a model of static grade-of-service (gos) differentiation as minimizing the total rejection and cost penalty. then, we use the lagrangian relaxation and subgradient methods to solve the problem. the results of using static gos differentiation are presented.
on the capacity of bidirectional broadcast channels under channel uncertainty. we consider the broadcast phase of a spectrally efficient two-phase decode-and-forward protocol which is used by a relay node to establish a bidirectional communication between two nodes. in the first phase the two nodes transmit their message to the relay node which decodes the messages. in the succeeding phase the relay node broadcasts a re-encoded composition of them. we consider imperfect channel knowledge and assume that all nodes merely know that the channel used for the transmission belongs to a set of channels. this is called compound bidirectional broadcast channel. we derive a universal strategy which achieves capacity and show that perfect channel state information (csi) at the receivers does not lead to an increased capacity region. otherwise, perfect csi at the transmitter can advantageously be used to enlarge the capacity region. finally, we give a game-theoretic interpretation as a game against nature.
design, implementation, and performance evaluation of an advanced sip-based call control for voip services. the growing interest in developing value-added services based on internet telephony brings into sharp focus several issues related to service creation. it becomes compelling for developers to take advantage of a platform that could offer high-level apis and standard interfaces, in order to reduce the time-to-market and extend the service portability over multiple networks and devices. the java community is tackling those issues within the java apis for integrated networks (jain) activity, utilizing java enterprise edition technologies in order to ease the development process of telecommunication services. this paper describes a sip-based call control service for internet telephony, designed for an ip-pstn converged scenario. the service has a back-to-back user agent (b2bua) architecture and is deployed into a service logic execution environment (slee). our slee is based on mobicents, an open-source platform for telecom applications, which offers an implementation of the jain slee specifications. we present the design and a comparative performance evaluation of different architectural implementations of the service, carried out with sipp, an open-source sip traffic generation tool.
sensitivity analysis of burst detection and rf fingerprinting classification performance. there has been a recent shift toward improving wireless access security within the osi phy layer by exploiting rf features that are inherently device specific and difficult to replicate by an unintended party. this work addresses the extraction and exploitation of rf "fingerprints" to classify emissions and provide device-specific identification. burst transient detection precedes rf fingerprint extraction and is generally the most critical step in the overall process. this work provides a much needed sensitivity analysis of burst detection capability. the analysis is conducted using instantaneous amplitude responses with both fractal-bayesian step change detection (fractal-bscd) and variance trajectory (vt) processes. the performance of each method is evaluated under varying snr conditions using experimentally collected 802.11a ofdm signals. the impact of transient detection error on signal classification performance is then demonstrated using rf fingerprints and multiple discriminant analysis (mda) with maximum likelihood (ml) classification. the vt technique emerges as the better alternative for all snrs considered and yields mda-ml classification accuracy that is consistent with "perfect" transient estimation performance.
a novel ray tracing based multipath modeling approach for site-specific wlan simulations. current propagation models used in network simulations neglect obstacles of a propagation environment and employ over-simplified assumptions that the received signal strength is a simple function of distance and the transmission area of a node is circular. these assumptions are in contradiction with the actual tests and the measurement results. to run reasonable simulations for evaluating the performance of a specific outdoor wireless testbed, a novel multipath propagation framework is proposed in this paper, which is based on the ray tracing technique and uses site-specific geographic data of the analyzed area. it provides accurate propagation predictions, and it does not significantly prolong the simulation duration.
minimum-latency gossiping in multi-hop wireless mesh networks. wireless mesh networks (wmns) is an emerging communication paradigm to enable resilient, cost-efficient and reliable services for the future-generation wireless networks. we study the minimum-latency communication primitive of gossiping (all-to-all communication) in multi-hop ad-hoc wmns. each mesh node in the wmn is initially given a message and the objective is to design a minimum-latency schedule such that each mesh node distributes its message to all other mesh nodes. minimum-latency gossiping problem is known to be np-hard even for the scenario in which the topology of the wmn is known to all mesh nodes in advance. we show an approximation scheme that can complete gossiping task in o(n log3/2n) time units with high probability at least 1-1/n in any ad-hoc wmn of size n. our algorithm allows the labels (identifiers) of the mesh nodes to be polynomially large in n. to the best of our knowledge, this is the first time that randomized algorithm has been considered in ad-hoc wmns with large labels. moreover, our gossiping scheme also significantly improved all current gossiping algorithms in terms of approximation ratio. our work has approximation ratio at most o(log32n) which is a great improvement of the current best known state-of-the-art algorithm with approximation ratio o(log3/2 n) but for linearly large node labels by czumaj and rytter[11].
effects of imperfect channel state information on achievable rates of precoded multi-user mimo broadcast channels with limited feedback. we consider multi-user mimo broadcast channels with limited feedback. a recently proposed linear precoding technique, regularized block diagonalization (rbd), is used to mitigate multi-user interference. we assume that each receiver has estimated channel state information (csi) via downlink training and independently quantizes its channel by using an efficient channel quantization scheme that we propose in this paper. the transmitter acquires the quantized csi from each receiver through a noiseless and delayed feedback channel. the achievable rates are studied under these assumptions. we derive an upper bound for the rate loss compared to the case that the transmitter has perfect csi and quantify the impact of channel estimation errors, quantization errors, and outdated quantized csi on the rate loss. furthermore, we provide an expression of the number of feedback bits needed per user to maitain that bound. it is found that the delay of the feedback is the predominant cause of performance degradation in the case of rapidly changing channel impluse response.
reduced complexity intrusion detection in sensor networks using genetic algorithm. we propose a reduced-complexity genetic algorithm for intrusion detection of resource constrained multi-hop mobile sensor networks. traditional intrusion detection mechanisms have limited applicability to the sensor networks due to scarce battery and processing resources. therefore, an effective scheme would require a power efficient and lightweight approach to identify malicious attacks. the goal of this paper is to evaluate sensor node attributes by measuring the perceived threat and its suitability to host local monitoring node (lmn) that acts as trusted proxy agent for the sink and capable of securely monitoring its neighbors. security attributes in conjunction with genetic algorithm jointly optimizes the placement of monitoring nodes (i.e, lmn) by dynamically evaluating node fitness by profiling workloads patterns, packet statistics, utilization data, battery status, and quality-of-service compliance.
optimum internet gateway selection in ad hoc networks. wireless ad hoc networks are connected to the fixed internet by means of internet gateways. whenever a node within the ad hoc network wishes to communicate with a host in the internet, it selects a default internet gateway to relay its traffic from the ad hoc network to the internet. in this paper, we formulate the problem of selecting the best internet gateway as a mixed integer linear program minimizing the maximum node utilization in the wireless network. by simulations, we show that the performance that can be achieved by solving this optimization problem is significantly higher than what is achieved by standard gateway selection algorithms based on hop count or gateway load. in particular, these heuristic algorithms fail to adapt to the offered traffic and available capacity in the network.
analysis of network coding in slotted aloha with two-hop bidirectional traffic. this paper deals with two representative bidirectional traffic cases in two-hop wireless relay access systems employing network coding and a slotted aloha protocol. network coding is a recent and highly regarded technology for capacity enhancement of multiple unicast and multisource multicast networks. the relay nodes are generally involved with unbalanced multidirectional traffic, but the impact of the unbalanced traffic on network coding has not been analyzed. this paper provides closed-form expressions for the throughput and packet delay for two-hop bidirectional traffic cases both with and without network coding even if the buffers on nodes are unsaturated. the analytical results are mainly derived by solving queueing systems for the buffer behavior at the relay node. the results show that the transmission probability of the relay node is a design parameter that is crucial for maximizing the achievable throughput of slotted aloha systems with network coding in two-hop bidirectional traffic cases.
achievable rates for the gaussian relay interferer channel with a cognitive source. a relay interferer channel consists of the classic relay channel with an additional source of interference. a three-terminal full-duplex gaussian relay interferer channel with a cognitive source is analyzed. each of the relay node and the destination node experiences on its link an additive gaussian outside interference, in addition to additive noise. only the source node, referred to as being the cognitive encoder, knows the interferences, in a non-causal manner. we first focus on the case in which the links to the relay and to the destination are corrupted by the same interference; and then we focus on the case of independent interferences. for each of these two models, we establish a lower bound on the channel capacity. the coding schemes for the lower bounds use techniques of dirty paper coding or carbon copying onto dirty paper, interference reduction at the source and decode-and-forward relaying. the results reveal that, by opposition to carbon copying onto dirty paper and its root costa's initial dirty paper coding (dpc), it may be beneficial in our setup that the informed source uses a part of its power to partially cancel the effect of the interference so that the uninformed relay benefits from this cancellation, and so the source benefits in turn.
fast spanning tree reconnection for resilient metro ethernet networks. ethernet is becoming a preferred technology to be deployed in metro domain due to its low cost, simplicity and ubiquity. however, spanning tree based ethernet protocol does not meet the requirement for metro area networks in terms of network resilience, despite the advancement of ethernet standardization and commercialization. in this paper, we propose a fast spanning tree reconnection (fstr) mechanism for metro ethernet networks to handle any single link failure, which has features of fast recovery, backup capacity guarantees and ease of implementation. upon failure of a link on a spanning tree, a distributed failure recovery protocol is activated to reconnect the broken spanning tree using a reconnect-link not on the spanning tree. we present the details of the protocol, including failure notification and forwarding table reconfiguration procedures. the pre-configuration of the reconnect-links to reconnect each spanning tree is formulated as an integer linear programming (ilp) problem. the optimization results show that with lower implementation cost, fast spanning tree reconnection mechanism can achieve comparative or considerably better performance than other resilient mechanisms for metro ethernet networks.
mechanism for maximizing area-centric coding gains in wireless multihop networks. localized network coding is a promising technique to improve the throughput of wireless multihop networks with multiple concurrent unicast sessions. however, most existing mechanisms in this field perform network coding without considering the maximization of joint coding gain among neighboring nodes. in this paper, we study how to improve network performance by maximizing the area-centric coding gains in wireless networks. to achieve this goal, we design an efficient coding-aware transmission scheduling mechanism. simulation results show that our mechanism can remarkably improve the network throughput as compared with existing mechanisms.
markov chain minimum bit error rate detection for multi-functional mimo uplink. in this paper, we introduce a novel markov chain (mc) representation aided minimum bit error rate (mber) detection method that is applicable to an m-qam modulated sdm/sdma uplink system. compared to the conventional mber scheme, the proposed mc-mber scheme is capable of reducing the complexity imposed with the aid of its efficient detection candidate set generation assisted by the markov chain process. our performance results demonstrate that the mc-mber multi-user detection (mud) is capable of reducing the computational complexity by a factor of eight in comparison to the conventional mber mud in a rank-deficient system transmitting four 4-qam uplink substreams with the aid of two receive antennas at the base station (bs), while achieving a ber performance comparable to that of the mber mud.
efficient fpga implementation of mimo decoder for mobile wimax system. in this paper, we present a fpga prototyping of the mimo decoder for the ieee 802.16e wimax mobile systems. the ieee 802.16e standard supports three types of mimo space time codes (stc), referred to in the standard by matrix a, b, and c, that achieve different levels of throughput and diversity depending on the quality of the mimo channels. in particular, the stc matrix a achieves full diversity by employing the alomuti coding, while the stc matrix b achieves full rate by employing spatial multiplexing and the stc matrix c achieves full rate and diversity by employing the golden code. in this paper, we present a fpga architecture of mimo decoder based on the fixed sphere decoder (fsd) algorithm that achieves close-to ml ber performance with a reduced computational complexity and fixed throughput. we show how a single fsd can be used to decode the different stc by adaptively processing the received signal according to the stc type prior to be fed to the fsd. the fpga design is incorporated with a qr decomposition of the channel matrix. the proposed fsd achieves fixed and high throughput required for the wimax systems. the fpga implementation is incorporated with a matlab simulation model of an fusc ofdma-based wimax 2x2 mimo system to validate the hardware design.
base station pilot management for user-deployed cellular networks. in this paper we review a 4g vision of deploying a cellular network whose infrastructure topology can be autonomously determined by cellular users. intelligent spectrum management is required for cellular interference control and mobile handoff management etc. we study an optimization method that maximizes the cell size coverage for user-deployed base stations, e.g. femtocells. the algorithm periodically updates the pilot power configuration based on each femtocell's channel pass loss and the global traffic distribution in the network. performance results are studied by simulation based on the wcdma cellular standard.
on pareto-efficiency between revenue and utility in resource allocation. in the broadband mobile service market, it is reasonable that the carrier (service provider) should choose a pareto-efficient resource allocation policy so that both the revenue of the carrier and the utility of users can be maximized. in this paper, we investigate the fundamental problem of the existence of resource allocation policies that are pareto-efficient between the revenue and the utility. we show that the revenue-maximizing policy is not always equal to the utility-maximizing policy and that the two distinct policies, if any, generate a set of pareto-efficient resource allocation policies. to make a pareto-efficient resource allocation schedule, we develop a mathematical framework, where we study the existence of the pareto-efficient policies, a necessary and sufficient condition for pareto-efficiency, which can be used for finding the set of all the pareto-efficient policies, and an efficient and exact solution method to find a pareto-efficient resource allocation schedule.
joint linear filter design in multi-user non-regenerative mimo-relay systems. this paper addresses the filter-design issues for multi-user non-regenerative mimo-relay systems. based on the perfect channel state information (csi), optimal joint linear filter schemes at the base station and the relay are derived, aiming to minimize the mean squared error (mse). we first propose the joint optimal filter scheme in the downlink scenario along with a more practical suboptimal scheme, and then a closed-form optimal solution in the uplink scenario is exploited. numerical results show that the proposed joint schemes can reduce the bit error rate (ber) significantly, especially for the high snr case.
fpga implementation of trellis shaping to control peak power for psk signals. single-carrier (sc) transmission is considered as a promising candidate for the uplink of the next generation cellular systems due to its relatively low peak-to-average power ratio (par) compared to multi-carrier systems such as orthogonal frequency division multiplexing (ofdm). in sc systems, bandwidth efficiency can be effectively enhanced by the use of waveform shaping filter with low roll-off factor. however, as a price, nonnegligible increase of par is incurred in pulse-shaped signals even for phase shift keying (psk) modulation. to balance both low par and high bandwidth efficiency, the authors have recently proposed a novel par reduction technique for sc-psk based on trellis shaping (ts). in this paper, we evaluate its effectiveness and feasibility through implementation with field programmable gate array (fpga) and testbed experiments with a sample rf power amplifier (pa).
an energy-efficient cooperative simo transmission scheme for wireless sensor networks. this paper presents a cooperative single-input multiple-output (simo) transmission scheme for wireless sensor networks (wsns), where the number of antennas and the constellation size of modulation are jointly optimized for different transmission distances such that the energy consumption is minimized. as compared to previous cooperative mimo schemes for wsns, the proposed one achieves higher energy efficiency and has a smaller critical distance above which cooperative mimo/simo outperforms single-input single-output (siso). the proposed optimization method is further extended to a clustered multi-hop wsn scenario. through joint optimization of the number of transmitter antennas, the number of receiver antennas, the constellation size, and the hop length, we derive an energy-efficient clustered cooperative simo multi-hop scheme. numerical results show that the proposed scheme not only reduces the overall energy consumption but also balances the energy consumption among clusters.
virtual time-slot allocation scheme for throughput enhancement in a millimeter-wave gbps wpan cross layer design. this paper proposes the virtual time-slot allocation (vtsa) scheme for throughput enhancement to realize a gbps-order time division multiple access (tdma) wireless personal area network (wpan) system in a realistic millimeter-wave residential multipath environment. conventional tdma system allocates each time-slot to only one communication link, which is insufficient to achieve gbps-order throughput, particularly in severe channel conditions of multipath environment. in this paper, the proposed vtsa scheme enables a single time-slot to be reused for multiple communication links simultaneously (hence the name virtual), thus significantly increases system throughput. however, this generates co-channel interference (cci) among the communication links occupying the same time-slot. the proposed cross layer vtsa scheme is therefore designed to be able to schedule the sharing of time-slots among multiple communication links, and at the same time monitor to minimize performance degradation due to cci. two time-slot reuse methods are proposed and compared in this paper, namely the minimum-cci slotting method and the random slotting method. as a result, it is found that the vtsa scheme is capable of increasing the system throughput as much as approximately 30% in the additive white gaussian noise (awgn), line-of-sight (los) and the nonline-of-sight (nlos) multipath channel. it is also found that the minimum-cci slotting method has 10% better performance as compared to the random slotting method.
a dynamic frame partitioning scheme for ieee 802.16 mesh and multihop relay networks. the ieee 802.16 standard, also known as wimax, defines flexible frame structures to support applications classified into different wimax traffic classes. the standard defines two types of scheduling to guarantee the quality of service (qos) requirements of these applications - centralized and distributed. however, the standard does not specify how the frame can be dynamically partitioned among its centralized and distributed schedulers or uplink and downlink schedulers. through efficient partitioning that dynamically adapts the partitioning based on demand, network can support more user applications with different qos requirements, and hence increase the revenues of service providers. in this paper, we propose a novel and general dynamic frame partitioning scheme for ieee 802.16 mesh and ieee 802.16j multi-hop relay networks. the scheme uses a dynamic markov model that studies the frame utilization over current frames to predict efficient partitions for future frames. simulation results show that the proposed scheme improves average frame utilization and decreases packet dropping.
non disruptive data services towards real-time traffic in wireless ad hoc networks. mobile wireless ad hoc networks (manets) naturally support a traffic mix of elastic and real-time flows but the shared nature and lossy properties of the radio medium make their coexistence challenging. we argue in this paper for a new kind of elastic data transport service which would preserve the quality of real-time priority flows while guaranteeing an acceptaple (tunable) end-to-end delivery time of elastic data. we propose to use mechanisms from delay tolerant networking (dtn) to support hop-by-hop data transfer from source to destination and an adaptation of tcp which monitors its agressiveness towards local voip traffic on each hop. the scheme is evaluated in simulation on a simple 4-node scenario and in a more realistic case where doubling data transfer time allows for the support of seven voip flows of medium quality against none for standard tcp.
joint transmitter-receiver beamforming in downlink cyclic prefix-free spatio-temporal mc-cdma. the problem of jointly optimizing the transmitter and receiver beamforming weights in the downlink of a cyclic prefix-free mc-cdma system over multipath fading channels is addressed in this paper. both the base station and user terminals are equipped with antenna arrays to leverage on the spatial information provided by the antenna arrays. the precoding and equalization matrices are designed with the aim of minimizing the overall mean-squared-error (mse) of the system subject to a power constraint for each transmitter antenna, which has the additional benefit of reducing the probability of clipping of the transmitted signals from the transmitter. this is highly favorable for a mc-cdma system due to the multi-carrier modulation involved. the performance of the optimization process is supported by simulation results.
adaptive coherent lp-norm combining. in this paper, we introduce an adaptive lp-norm metric for robust coherent diversity combining in non-gaussian noise and interference. we derive a general closed-form expression for the asymptotic bit error rate (ber) for lp-norm combining in independent non-identically distributed ricean fading and non-gaussian noise and interference with finite moments. based on this asymptotic ber expression, the metric parameters can be adapted to the underlying type of noise and interference using a finite difference stochastic approximation (fdsa) algorithm. simulation results confirm the validity of the derived asymptotic ber expression and the excellent performance of the proposed adaptive lp-norm metric.
performance evaluation of qam-based bicm: an analytical approach. we present an analytical approach to determine the performance of bit-interleaved coded modulation (bicm) transmission over unfaded gaussian channels. in particular, we derive expressions for bit-error rate and cutoff rate assuming general quadrature amplitude modulation (qam) constellations. different from previously proposed methods, our analysis is valid for arbitrary labeling rules and results in simple closed-form expressions. the key idea is to utilize a simplification to estimate the probability density function of reliability metrics, which is tight for signal-to-noise ratio regions of interest for bicm systems with moderate coding complexity such as, e.g., convolutional coded bicm systems. the usefulness of the proposed analytical approach is validated through numerical and simulation results for a number of bicm transmission examples.
symmetric-key homomorphic encryption for encrypted data processing. the difficulty of processing data in encrypted form has long been the barrier to the widespread use of encryption in data storage applications; improved security or privacy would always imply a sacrifice of functionality. many applications, such as asp, requiring a significant amount of processing at the data storage servers are hence precluded from using encryption to protect data privacy. to address this problem, this paper works on privacy homomorphism which allows encrypted data to be operated on. two additive homomorphic schemes, namely iterated hill cipher (ihc) and modified rivest scheme (mrs), are given. they are secure to ciphertext-only attacks and have the nice property that the same data may have different representations in the encrypted domain.
a novel high data rate prerake uwb system using orthogonal codes and chip-interleaving. a novel signal structure is designed for a high data rate (hdr) prerake uwb system, which uses orthogonal codes and chip-interleaving to suppress the inter-chip interference (ici). on one hand, high data rate is achieved via superposition of symbols. on the other hand, the symbols are coded using the walsh-hadamard codes and interleaved on the chip level, which largely eliminates the ici. the ber performance of the system is analyzed under imperfect channel estimation. numerical results show that the hdr prerake uwb system using the walsh-hadamard codes and chip-interleaving outperforms the conventional hdr prerake uwb system using the random ds codes without ici suppression under both perfect and imperfect channel estimation. effect of the length of walsh-hadamard codes on the system performance is also discussed in detail.
the effect of fading correlation on average source mmse distortion. this paper considers the end-to-end mean-square distortion in reconstructing a memoryless proper-complex gaussian source transmitted over parallel block-fading rayleigh awgn channels. we characterize the distortion exponent of several source and channel coding strategies; that is, we characterize how fast the distortion decays to zero as the snr increases. unlike previous works, we consider networks with different received snr's and with correlated fading. we generalize the definition of distortion exponent to snr-asymmetric channels. we show that fading correlation degrades the achievable mean-square distortion but does not affect the distortion exponent. the performance degradation is measured in terms of power-offset; that is, the power increment needed to achieve the same performance as the uncorrelated case. we show that the power-offset is proportional to the determinant of the fading correlation matrix. our proposed methodology allows us to study any number of parallel channels and we are no longer restricted to two channels (as was commonly done in the previous literature). finally, we show that determining the distortion exponent of multiple description coding (mdc) schemes in high snr reduces to solving a linear programming problem.
buffer schemes for vbr video streaming over heterogeneous wireless networks. with the co-existence of different wireless networks, which exhibit largely different bandwidth and coverage characteristics, much interest has been involved in integrating these networks to support smooth and efficient multimedia services. in this paper, we present an analytical framework for variable-bit-rate (vbr) video streaming in a two-tier wireless network with vbr channels. we derive the expected number of jitters and average buffering delay during video playback as measures of system performance. our objective is to discover heterogeneous networking attributes that may influence the streaming performance, in terms of the tradeoff between jitter frequency and buffering delay. through experimenting with a wide range of fixed, separate, and jointly optimal jitter-recovery buffering schemes, based on buffering delay, buffered data, and buffered playback duration, we quantify the benefit of incorporating user location information in streaming over heterogeneous wireless networks.
multiuser mimo downlink beamforming based on group maximum sinr filtering with per stream power allocation. we propose an algorithm which iteratively computes the transmit-receive beamforming filters and the power allocation matrix to solve the multiuser multi-input multi-output (mimo) downlink beamforming problem under signal-to-interference-plus-noise-ratio (sinr) constraints. the transmitter is a multi-antenna base-station broadcasting to users. each user has multiple antennas at the receiver. the beamforming filter is a group maximum sinr filter which exploits intra-group cooperation, and the power allocated to each data stream is adjusted to enhance performance. simulation results verify the superiority of the proposed algorithm over previous works.
performance evaluation of multiple-relay cooperative arq strategies for mobile networks. in cooperative automatic repeat request (c-arq) protocols, one or more nodes can act as relays, collaborating in the frame retransmission process between a sender and a destination node. in the framework of a broadband mobile access network, we consider a relay enhanced cell where the sender represents the base station, and an undefined number of relays can cooperate with a single user (destination). in this paper we present a markov model complemented with a reward model to analyze the throughput performance and the efficiency in the bandwidth utilization at the base station, highlighting a clear tradeoff between them. both performance metrics are balanced by means of a multi-objective optimization algorithm resulting in a retransmission strategy for the access node that notably improves the bandwidth efficiency while maintaining the throughput very close to its maximum. the benefits of the proposed approach are evaluated in two scenarios. in the first one, the relays are part of the network infrastructure. in the second one, the relays are cooperative users.
denoising strategy for convolutionally-coded bidirectional relaying. in this paper, we present a forwarding strategy for two-stage bidirectional relaying in which trellis-coded modulation (tcm) is employed. we reveal that adaptive network coding cannot resolve distance shortening occurred at specific channel conditions when a certain tcm is used. to overcome this issue, we introduce an improved amplify-and-forward (af) scheme termed pseudo af (paf). the proposed strategy adaptively switches network coding and paf according to the channel information. computer simulations demonstrate that the proposed approach can improve throughput performance.
a set of topological graphs for 2-d sensor ad hoc networks. recently, different types of sensors have been developed to detect environmental changes (e.g., instability of the earth's crust) and to reduce the associated damage. for an efficient usage of the sensor technology, several design factors (e.g., topology and sensing coverage) should be taken into account. in this paper, we focus on the underlying topology of sensor networks in two-dimensional environments and propose a new set of graphs referred to as the derived circles (dcα) graphs. we show that dcα graphs are locally constructed, connected, power efficient, and orientation-invariant. we also show that dcα graphs have a minimum degree of one and an euclidean dilation of one. furthermore, via simulations, we demonstrate that dcα graphs outperform the half space proximal (hsp) graph in terms of the network dilation, euclidean dilation, and power dilation. this, in turn, reduces the energy consumption of nodes and accordingly prolongs the network lifetime.
supporting dynamic inter-domain network composition: domain discovery. when two administratively independent domains need to engage in cooperation of some kind, some initial common known point of contact must exist, both in terms of the application topological position (i.e., ip address, transport protocol and port) and in terms of the interface technology (e.g., the protocol suite of the interaction). in a world of many domains of many types (not necessarily autonomous systems in the sense of interdomain routing), manual or single-directory-based operations are not practical (or even feasible); hence, some form of autonomic discovery and handshaking of domains is needed. we propose and evaluate several strategies to allow autonomic bootstrapping of inter-domain operations, all fit to be deployed as bgp extensions. we show the time/message overhead tradeoff: it's possible to obtain the absolute minimum message complexity of o(n) but at the cost of central administrative burden or, for fully distributed schemes, a tradeoff (message/time complexity) of o(n2)/o(n) or o(n2)/o(log2n).
on the use of compression algorithms for network anomaly detection. in the last few years, the number and impact of security attacks over the internet have been continuously increasing. since it seems impossible to guarantee complete protection to a system by means of the "classical" prevention mechanisms, the use of intrusion detection systems has emerged as a key element in network security. in this paper we address the problem considering some techniques for detecting network anomalies. our approach is based on the use of different compression algorithms for detecting anomalies in the network traffic running over tcp. in more detail we take into account the use of three different compression algorithms, based on distinct approaches, namely: huffman coding, dynamic markov coding, and lempel-ziv-welch algorithm. the proposed methods are based on the consideration that the entropy represents a lower bound to the compression rate that we can obtain, and that the more redundant the data are and the better we can compress them. the performance analysis, presented in this paper, demonstrates the effectiveness of the proposed methods.
interference cancellation and detection using precoders. we consider interference cancellation for a system with two users when users know each other channels. the goal is to utilize channel information to cancel the interference without sacrificing the diversity or the complexity of the system. before, in the literature, it was shown how a receiver with 2 receive antennas can completely cancel the interference of two users and provide a diversity of 2 for users with 2 transmit antennas. we propose a system to achieve the maximum possible diversity of 4 with low complexity. our main idea is to design precoders, using the channel information, to make it possible for different users to transmit over orthogonal spaces. then, using the orthogonality of the transmitted signals, the receiver can separate them and decode the signals independently. we analytically prove that the system provides full diversity to both users. in addition, we provide simulation results that confirm our analytical proof.
verification of secret key generation from uwb channel observations. theoretical models of ultrawideband (uwb) radio channels indicate that pairs of uwb radio transceivers measure their common radio channel with a high degree of agreement and third parties are not be able to accurately estimate the state of the common channels. these properties allow generation of secret keys to support secure communications from uwb channels measurements. in this paper, the results of uwb propagation studies are presented that validate the required properties to support secret key generation in a typical indoor environment. key generation algorithms are employed on the measured data and key lengths on the order of thousands of bits are obtained capable of supporting most popular cryptographic systems. the paper also reports measurements of the spatial and temporal correlation of the uwb channel from which the relative privacy of the secret keys can be determined as well as the rate new secret keys may be generated.
diversity analysis of smart relaying with equal gain combining. cooperative relaying has been proposed as a way to create a virtual antenna array, hence providing spatial diversity in slow fading wireless environment. from the practical implementation perspective, one needs to design a relaying system that can achieve the maximum diversity order with a low system complexity. one promising candidate is to incorporate equal gain combining (egc) technique into relaying systems and it is the main focus of this paper. in particular, the techniques of egc and smart relaying are combined in the decode-and-forward (df) relay processing method. it is shown that for a system with one relay and m phase-shift-keying (m-psk) modulation, a maximum diversity order of 2m is achieved in nakagami-m fading environment. with k relays, numerical results suggest that the diversity order is m(k + 1).
how can network coding help p2p content distribution? it is well known that network coding can enhance the performance of peer-to-peer (p2p) content distribution systems since it benefits block scheduling. in this paper, we introduce our p2p content distribution system "smartcode" with sparse network coding on planetlab. smartcode uses prechecking to avoid linearly dependent blocks being transmitted. under the same system architecture, we also implement two systems "ecode" and "lrf". ecode is also based on sparse network coding, but without pre-checking. lrf is bittorrent-like, using local-rarest-first for block scheduling. we conduct extensive experiments to compare the performances among the three systems. experimental results show that the distributing time of smartcode is reduced by 11% on average and up to 19% compared with lrf, and by 7% on average and up to 16% compared with ecode. we also conduct experiments to analyze robustness among the three systems under the assumption that peers join in and leave a content distribution session dynamically and the seed leave the session after it has transmitted a fixed percentage of blocks over the total blocks of the content. in dynamical cases, smartcode outperforms evidently than ecode and lrf in downloading time and the times of peers completing the downloading.
a unified framework for interference modeling for multi-user wireless networks. the paper addresses the problem of interference modeling for wireless networks. two axiomatic frameworks are known from the literature: (1) standard interference functions introduced by yates in [jsac 1995], and (2) general interference functions proposed by the authors in their previous work. in this paper, both frameworks are analyzed and compared. it is shown that (1) is contained in the more general framework (2). this means that certain structure results, which were recently derived for (2) can also be applied to (1). a focus of this paper is on convexity and concavity properties, which are important because they often lead to interesting algorithmic opportunities. the results provide a bridge between both frameworks, which have been studied separately in the past.
on the multi-rate division with limited feedback for one source multiple destinations wireless transmission systems. multiuser diversity is inherent in wireless networks due to independent channel variations of different users. it requires that the transmitter has the knowledge of the channel state information (csi) of each user in the downlink. too much feedback will bring a heavy load to the system in some cases. this paper investigates the problem of exploiting multiuser diversity in a one source multiple destinations wireless transmission system with limited feedback. a strategy for obtaining the optimal multiple rate level and the maximum achievable sum rate is proposed in this paper. moreover, the scheduling outage probability, the probability that rates of all users are below a threshold, is also analyzed. for one-bit feedback, a tight bound of the achievable rate is obtained. it is shown that the achievable rate nearly capture the order of the double-logarithmical of the number of users in full csi systems. numerical results are also presented. the achievable sum rate is close to the full csi capacity via limited feedback as the number of users is large enough.
channel spectral flattening in time domain equalizer design for ofdm systems. time domain equalization (teq) methods based on the maximum shortening signal-to-noise ratio (mssnr) criterion is one of the most commonly used criterion for shortening impulse responses as it is computationally efficient and simple. however, the mssnr method tends to design a teq with a bandpass-like frequency response, resulting in a spectrally uneven effective channel response. as as result, bit-loading have to be performed to improve the bit rate of the system. additionally, when residual intersymbol interference (isi) is low compared to noise power, the spectral shape of the effective channel does not have much impact on the bit rate. however, the negative effect of the channel spectral unevenness on achievable bit rate increases as the noise power decreases. in this paper, a design method is proposed to maximize effective channel spectral flatness to increase the bit rate of the system.
low complexity coordinated beamforming in 2-user mimo systems. in this paper, we propose a new noniterative coordinated beamforming scheme to obtain full multiplexing gain in 2-user mimo systems. in order to find the beamforming and combining matrices, we solve a generalized eigenvector problem and describe how to find generalized eigenvectors according to the gaussian broadcast channels. selected simulation results show that the proposed method yields the same sum-rate performance as the iterative coordinated beamforming method with a lower complexity non-iterative computation of the beamforming and combining matrices. we also show that the proposed method can easily exploit selective gain by choosing the best combination of generalized eigenvectors.
spatial and temporal packet recovery schemes for dvb-h systems through ip-relay wireless networks. the dvb-h standard has been defined to provide digital video broadcast to mobile handheld devices. however, without a request channel, a handheld device may encounter data loss and thus it requires an additional recovery architecture to relieve this problem. in this paper, we follow the dvb-ipdc standard and propose combining a dvb-h system with an ip-relay wireless network. a handheld device losing dvb-h data can thus request the relay network for retransmission. under this architecture, we identify two critical issues, group packet loss (gpl) and broadcast data handover (bdh). the gpl problem occurs when there are bursty requests for retransmissions of the same data with high spatial and temporal locality, causing network congestion. the bdh problem occurs when these requesting devices move out of their current serving cells. in this paper, we propose a bulk request recovery (brr) scheme to solve these problems by exploiting spatial and temporal locality of recovery requests. our scheme can efficiently reduce duplicate requests and schedule retransmissions of lost packets, so both gpl and bdh problems are relieved. simulations results are also presented to verify the effectiveness of our result.
performance analysis of cooperative communication systems with imperfect channel estimation. this paper investigates the effects of channel estimation errors on the symbol-error-rate (ser) performance of a cooperative communication system operating in an amplify-and-forward (af) mode. a pilot symbol assisted modulation scheme with linear minimum mean square estimation (lmmse) is used for the channel estimation. an accurate and easy-to-evaluate ser expression is presented for uncoded cooperative communication systems with quadrature amplitude modulation (qam) and phase-shift keying (psk) constellations. numerical simulations are conducted to verify the correctness of the proposed analytical formulation. it is shown that the performance loss caused by channel estimation errors increases mainly with the normalized maximum doppler frequency.
detecting low-power primary signals via distributed sensing to support opportunistic spectrum access. cognitive radio operation with opportunistic spectrum access has been proposed to utilize spectrum holes left unused by a primary system owning the spectrum license. the key of cognitive radio operation is the ability to detect weak primary signals and to control the transmission of cognitive users in a way that interference between the two systems is minimized. in this paper we evaluate how a sensor network deployed to provide distributed spectrum sensing can assist cognitive operation. specifically, we consider sensor networks with regular topology, where a high level of cooperation also means that sensors far from the source of the primary signal are involved in the sensing process. assuming energy detection and hard-decision combining we derive worst case probabilities of missed detection and false alarm, determine the necessary level of cooperation among the sensors and evaluate how the sensor density and the sensing time affect the performance of distributed sensing.
peer-to-peer application recognition based on signaling activity. because of the enormous growth in the number of peer-to-peer (p2p) applications in recent years, p2p traffic now constitutes a substantial proportion of internet traffic. the ability to accurately identify different p2p applications from the network traffic is essential for managing a number of network traffic issues, such as service differentiation and capacity planning. however, modern p2p applications often use proprietary protocols, dynamic port numbers, and packet encryptions, which make traditional identification approaches like port-based or signature-based identification less effective. in this paper, we propose an approach for accurately recognizing p2p applications running on monitored hosts based on signaling behavior, which is regulated by the underlying p2p protocol; therefore, each application possesses a distinguishing characteristic. we consider that the signaling behavior of each p2p application can serve as a unique signature for application identification. our approach is particularly useful for three reasons: 1) it does not need to access the packet payload; 2) it recognizes applications based purely on their signaling behavior; and 3) it can identify particular p2p applications. the performance evaluation shows that 92% of a real-life traffic trace can be correctly recognized within a 5-minute monitoring period.
reducing average power in wireless sensor networks through data rate adaptation. the use of variable data rate can reduce network latency and average power consumption, and automatic rate selection is critical for improving scalability and minimizing network overhead. in the ieee 802.15.4 standard the snr can be inferred through the radio reported link quality or received signal strength, and an extension to the standard leads to highly dynamic and accurate rate selection. using data from an experimental study of 44 ieee 802.15.4 nodes in an industrial mesh network, snr is extracted to show sufficient margin exists for higher data rate communication. a variable rate signaling scheme with automatic rate selection is proposed to provide links at the standard 250kb/s as well as 500kb/s, 1000kb/s and 2000kb/s with a minimum of hardware changes. using the experimental data to generate a model of the real world system, total network energy is compared using legacy and variable rate signaling showing over 40% savings.
zero forcing processing in two hop networks with multiple source, relay and destination nodes. in this paper, we consider two hop networks with multiple source, relay and destination nodes. in particular, we investigate systems with different processing capabilities at the relay and destination nodes. we derive new closed-form outage probability expressions when zero forcing processing is used at the i) relay, ii) relay and destination and iii) destination nodes only. our results indicate significant decreases in outage probability for certain node configurations. we confirm our results through comparison with monte carlo simulations.
demonstration of ipv6 network mobility in aeronautical communications network. this paper presents the development of a laboratory demonstrator within newsky, a project co-funded by the european commission within its 6th research framework programme (fp6). host and network mobility are some of the essential network functionalities required for efficient operation of a network-centric aeronautical communication system. this paper deals with the feasibility demonstration of mobile ipv6 (mipv6) and network mobility (nemo) protocols to suitable provide mobility support for the future air traffic management (atm) network.
controlling error propagation in network-coded cooperative wireless systems. in cooperative communications, error propagation at relays degrades the diversity order of the system. to combat that effect, it has been suggested to implement a reliability threshold at the relay to control error propagation. the relay calculates log-likelihood ratio (llr) values for the bits sent from the source. these values are subjected to a threshold to selectively forward bits that are most reliable and discard bits that are less so, resulting in less errors propagating to the destination. we investigate the application of this technique to a network-coded two-way relay channel, where the relay is assisting two sources simultaneously. we investigate two modes of thresholding at the relay: at the individual-bit level and at the combined-bit level. we analyze the bit-error rates of both thresholding modes and optimize the threshold for both. we show significant gains using thresholding over an unthresholded network-coded system. based on system simulations, we conclude that utilizing separate thresholds yields better results than utilizing a combined threshold scheme.
pick your layers wisely - a quality assessment of h.264 scalable video coding for mobile devices. multi-dimensional video scalability as defined in h.264/svc is a promising concept to efficiently adapt encoded streams to individual device capabilities and network conditions. however, we still lack a thorough understanding of how to automate scaling procedure in order to achieve an optimal quality of experience (qoe) for end uses. in this paper we present and discuss the results of a subjective quality assessment we performed on mobile devices to investigate the effects of multi-dimensional scalability on human quality perception. our study reveals that qoe degrades nonmonotonically with bitrate and that scaling order preferences are content-dependent. we confirm previous studies which found common objective metrics to fail for scalable content, but we also show that even scalability-aware models perform poor. our results are supposed to help improving the design of quality metrics and adaptive network services for scalable streaming applications.
optimal relay assignment and power allocation in selection based cooperative cellular networks. we consider a system with a single base station communicating with multiple users over orthogonal channels while being assisted by multiple relays. several recent works have suggested that selection, i.e., a single relay helping the source, is the best option in terms of the resulting complexity and overhead. however, in a multiuser setting, optimal relay assignment is a combinatorial problem. in this paper, using the sum rate as our design metric, we develop a convex optimization problem that provides an extremely tight upper bound on performance. we also provide a heuristic to find a close-to-optimal relay assignment. simulation results using realistic channel models demonstrate the efficacy of the proposed scheme.
a study on collaborative beamforming with protocol defects in wireless ad hoc networks. to conduct collaborative beamforming in wireless ad hoc or sensor networks, several protocols must be executed, including the localization protocol, time synchronization protocol, and data dissemination protocol. in practice, however, these protocols are often limited by their complexities for achieving the ideal perfect performance. therefore, protocol defects such as location errors, time synchronization errors, and message losses often appear in collaborative beamforming with distributed operations. in this paper, we introduce an analytical framework to analyze the impact of protocol defects on the performance of collaborative beamforming. we show numerical results of the proposed model, and explain how the proposed model can be used to mitigate the impact of protocol defects for collaborative beamforming in wireless networks.
reduced-rank adaptive least bit error-rate detection in hybrid direct-sequence time-hopping ultrawide bandwidth systems. in this paper we consider the low-complexity detection in hybrid direct-sequence time-hopping ultrawide bandwidth (ds-th uwb) systems. a reduced-rank adaptive lber detector is proposed, which is operated in the least bit error-rate (lber) principles within a detection subspace obtained with the aid of the principal component analysis (pca)- assisted reduced-rank technique. our reduced-rank adaptive lber detector is free from channel estimation and does not require the knowledge about the number of resolvable multipaths as well as that about the multipaths' strength. in this paper the bit error-rate (ber) performance of the hybrid ds-th uwb system is investigated, when communicating over the uwb channels modelled by the saleh-valenzuela (s-v) channel model. our study and simulation results show that this reduced-rank adaptive lber detector constitutes a feasible detection scheme for deployment in practical pulse-based uwb systems.
bluebat: towards practical bluetooth honeypots. it is still difficult to assess the real danger posed by bluetooth-propagated malware. bluebat is an effort to build and deploy a practical honeypot for capturing in-the-wild samples and empirically study malware prevalence. this paper describes the design and implementation of a first prototype, focusing on bluetooth worms propagating over the obex push service. we develop and perform initial field testing of different types of sensors, in order to achieve an optimal collection capability. we analyze the results of the field tests, and demonstrate various design constraints. also, from these preliminary tests, we cast some doubts on the prevalence of in-the-wild bluetooth worms, and hint at some reasons why such threat could be more limited than previously thought.
rate allocation for the multi-source downlink channel with minimax optimization. we consider the downlink transmission with multiple sources. each source transmits over an orthogonal channel by using cooperative broadcasting. each destination is required to receive and decode a given amount of information. a destination can receive different partitions of information from multiple sources. the sources cooperate and allocate the flow rates along each link to minimize the maximum individual transmit power of each source. to simplify the computations involved in the optimization process, we suggest a sub-optimal algorithm. simulation results indicate that our optimal scheme gives improvements between 4.2db and 5.6db over the single-source scheme, where a destination selects only one source for transmission, in our considered networks and rate requirements. our sub-optimal algorithm suffers a loss of below 0.4db compared with the optimal one. the expressions involved in the sub-optimal algorithm are less complicated and it requires m iterations, where m is the number of destinations, and a bisection search in each iteration.
dynamic coexistence of frequency hopping networks using parallel and gaussian allocations. this paper studies the coexistence of several independent and dynamic wireless networks using the frequency hopping technique in the unlicensed radio band. we propose a new hopping scheme that allows more networks to collocate effectively, but does not violate federal restrictions regarding frequency constraint (related to the minimum number of frequencies in a hopping set) and time constraint (related to the maximum duration of using a particular frequency). the coexisting networks follow the gaussian distribution in choosing transmission frequencies from parallel hopping spaces without the overhead of extra message exchange. simulation results include comparison with other contemporary approaches and establish the viability of the proposed scheme.
information combining for relay networks. analyzing the capacity of relay networks is often based on the max-flow min-cut theorem providing an upper bound on the true capacity which is generally still unknown. this paper analyzes the achievable rates of a simple relay network by a semi-analytical approach considering ideal capacity achieving codes of appropriate rates and optimum symbol-by-symbol soft-output decoding at the relay. applying the information combining technique, regions are illustrated where the upper bound provided by the max-flow min-cut theorem can be reached. moreover, the results show that the lower bound obtained by the constraint of error-free decoding at the relay can be exceeded in many scenarios. simulations with a nearly capacity achieving half-rate repeat accumulate code confirm the semi-analytic results.
ofdma-tdd networks with busy burst enabled grid-of-beam selection. interference aware user scheduling in fixed grid-of-beam (gob) transmission is envisaged to significantly benefit from the receiver initiated busy burst (bb) protocol. fixed gob scheduling relies on the knowledge of the location of the intended users as well as the vulnerable users which effectively is provided by the bb protocol via exploitation of channel reciprocity. this paper studies the hybrid bb and gob (bb+gob) approach in a manhattan environment. the new proposed hybrid interference avoidance scheme with an underlying score based scheduler is evaluated by means of system level simulations, and is compared against a pure gob approach with the same scheduler as well as the bb based interference avoidance techniques applied to omnidirectional antennas. the results show an improvement in both system throughput and fairness (defined as cell edge user throughput). in particular, system throughput of up to 238.5 mbps/cell or user throughput of up to 8.88 mbps/user for the lower 10%-ile of users are shown to be feasible. in particular, the hybrid bb+gob scheme exhibits a 16-fold improvement at the lower 10%-ile compared to pure gob technique.
improving throughput in high bandwidth-delay product networks with random packet losses. it is well known that the standard tcp has become a performance bottleneck in the networks with large bandwidth-delay products. the situation gets worse if high-speed wireless links are part of the networks, due to the frequent random losses over the wireless links. this is because the standard tcp increments its congestion window too slowly in the absence of packet losses and decrements it too drastically in response to packet losses. a natural solution is to make tcp more aggressive. this approach has been exercised in the recent tcp development such as hstcp and multcp which have the capability of using a single logical connection to emulate the behaviour of a set of multiple standard tcp connections. in the meantime, tcp parallelisation uses a set of parallel tcp connections to transfer data for an application process. then, a question arises - can the single-connection based approach achieve the similar performance as tcp parallelisation in the environments where random packet losses prevail. our analysis shows that tcp parallelisation has the better performance and is more efficient for performance improvement.
improved vector perturbation with modulo loss reduction for multiuser downlink systems. in this paper, we present an improved precoding technique which reduces a modulo loss in vector perturbation (vp) with low complexity for the downlink of a multiuser multiple-input multiple-output (mimo) system. at low snr regime, the vp suffers from the modulo loss due to the increased number of nearest neighbors. for the original vp, the sphere encoder searches perturbation vectors in the infinite lattice. in contrast, the proposed scheme restricts the search range utilizing the distribution of the perturbation vector depending on transmitted data. as a result, we can achieve significant complexity savings at the transmitter and the receiver while providing better performance compared to the conventional sphere encoder. simulation results show that the proposed scheme provides a 0.2 db gain over the conventional vp at a bit error rate (ber) of 10-3 for the case of four transmit antennas and four users with 4qam. also, the proposed scheme reduces the maximum number of candidate search by 95% in comparison to the original vp.
distributed interference pricing for the mimo interference channel. we study distributed algorithms for updating transmit precoding matrices for a two-user multi-input/multi-output (mimo) interference channel. our objective is to maximize the sum rate with linear minimum mean squared error (mmse) receivers, treating the interference as additive gaussian noise. an iterative approach is considered in which given a set of precoding matrices and powers, each receiver announces an interference price (marginal decrease in rate due to an increase in interference) for each received beam, corresponding to a column of the precoding matrix. given the interference prices from the neighboring receiver, and also knowledge of the appropriate cross-channel matrices, the transmitter can then update the beams and powers to maximize the rate minus the interference cost. variations on this approach are presented in which beams are added sequentially (and then fixed), and in which all beams and associated powers are adjusted at each iteration. numerical results are presented, which compare these algorithms with iterative water-filling (which requires no information exchange), and a centralized optimization algorithm, which finds locally optimal solutions. our results show that the distributed algorithms perform close to the centralized algorithm, and by adapting the rank of the precoder matrices, achieve the optimal high-snr slope.
battle management language (bml) as an enabler. according to its definition, a battle management language (bml) is an unambiguous language used to command and control forces and equipment conducting military operations and to provide for situational awareness and a shared, common operational picture. in this paper, we will argue that the use of a bml enables military units to utilize state-of-the-art it techniques for today's operations. in particular, we will discuss the benefits of using bml for military communications in multinational endeavors, for the use of simulation systems in staff training, for decision support, and for automatic information fusion.
maximum a posteriori bit-unstuffing. bit-stuffing is the procedure of introducing an extra bit in the transmitted stream after a fixed number of consecutive ones or zeros. this paper demonstrates that, for conventional unstuffing, the ber experienced by individual bits within a stuffed frame dramatically and monotonically degrades with its positional-index. we also show that when knowledge of the number of stuffed bits is applied to maximum a posteriori (map) bit-unstuffing (mapbu) (through a bcjr algorithm), this trend is significantly mitigated.
experimental triple-play service delivery using commodity wireless lan hardware. in this paper we study the feasibility of utilizing wireless local area network (wlan) technology to deliver the triple-play services (video, voice and data) over a specific system model. existing protocols are shown to not efficiently manage the wireless channel therefore we propose a new triple-play time division multiple access (tp-tdma) media access control (mac) protocol to provide quality of service (qos) for these triple-play services in a point-to-multipoint network over an existing 802.11a physical layer. through extensive simulation analysis, the protocol is shown to offer better performance than the 802.11e enhanced distributed coordination function (edcf). moreover, this protocol is implemented in hardware using the madwifi driver to verify the real-world performance. both results of the simulation study and hardware implementation are provided.
on channel estimation for ofdm based two-way relay networks. we consider the channel estimation issues for two-way relay network (twrn) that employs orthogonal frequency division multiplexing (ofdm) modulation. we propose a two-phase training protocol for channel estimation, which is compatible with two-phase data transmission scheme associated with twrn. it will be seen that channel estimation in twrn is quite different from that in the traditional point-to-point system or even that in the one-way relay network (owrn). the identifiability issue of the channel estimation, which particularly exists for twrn, is studied. simulation results corroborate the effectiveness of the proposed method.
approximated matching-based spectrum access algorithm for heterogenous cognitive networks. we present a novel spectrum access scheme for open spectrum networks. different from existing works, this work considers the scenario that contending secondary users have heterogeneous channel availability. it is proved to be np hard to find the optimal spectrum assignment in this scenario. to solve this problem, a novel approximation algorithm is proposed which is based on the maximum weighted matching technique. the performance of the algorithm is evaluated through extensive simulations. compared with the general optimal spectrum allocation scheme without considering the difference of spectrum availability, the experiments' results demonstrate that the new matching based algorithm improves the network throughput significantly, generally by 20% to 60%. the algorithm's computation complexity is also at a low level of o(m*n2*m).
using limited feedback in power allocation design for a two-hop relay ofdm system. in this paper, we study power allocation (pa) in a single-relay ofdm system with limited feedback. we propose a pa scheme that uses a codebook of quantized pa vectors designed offline and known to the source, relay, and destination. the destination, which has full knowledge of channel side information (csi), chooses one of the codebook vectors and conveys back to the source and relay. with the limited amount of available feedback, the design of an appropriate codebook is central to pa, which varies depending on the destination's strategy to choose the optimal pa vector. assuming high received snr on either link in the relay path, we first derive the optimal pa solutions as the function of channel realizations with two design criteria, maximizing capacity and minimizing error rate. it is found that when there is high received snr in either the relay path or the direct path, the optimal solutions for both criteria reduce to simple forms. for maximizing capacity, the available power should be equally allocated to each ofdm subcarrier shared by the source and relay; while for minimum error rate, the available power should be allocated such that the received snrs for all subcarriers at the destination are the same. the findings lead us to the sub-optimal solutions with great complexity reduction. we then present an adaptation of lloyd's algorithm to construct a codebook to quantize the optimal pa vectors subject to the amount of feedback. simulations show that a mild to negligible performance loss can be achieved with only a few bits of feedback at different snr values.
towards a denial-of-service resilient design of complex ipsec overlays. by monitoring the exchanged ipsec traffic an adversary can usually easily discover the layout of virtual private networks (vpns). of even worse extend is the disclosure if compromised ipsec gateways are considered, for example in remote environments. this revelation enables attackers to identify vital components and may allow him to compromise the availability of the overall infrastructure by launching well-targeted denial-of-service (dos) attacks against them. in this article we present a formal model to analyze the resilience of vpn infrastructures against dos attacks, to estimate the impact of compromised gateways, and to formalize the planning process of more resilient infrastructures.
recipient maximization routing scheme for multicast over ieee 802.16j relay networks. in this paper, we consider the resource allocation problem for multicast over ieee 802.16j wimax networks, which use relay stations to transmit data between the base station and subscriber stations to improve the transmission quality. our objective is to maximize the total number of recipients by allocating resource among the base station and relay stations subject to the resource budget and the channel quality. we prove that the problem is np-hard, and design a polynomial-time algorithm to solve it. the algorithm can be integrated with the multicast mechanism defined in the wimax standards, and can also be applied to any kind of wireless networks that support adaptive modulation and coding schemes. the performance of the algorithm is evaluated through simulations. we show that the typical routing approach is inefficient, whereas our scheme can always utilize relay stations to achieve a superior performance under different channel qualities and resource budgets.
a stochastic mimo model for far-end crosstalk in vdsl cable binders. future digital subscriber line (dsl) systems are supposed to achieve higher data rates by using interference cancellation techniques. since far-end crosstalk (fext) is the major impairment in dsl systems based on frequency division duplexing, mitigation of this interference can increase the signal-to- interference-and-noise ratio, and therefore significantly boost the data rate. for simulation and evaluation of fext cancellation algorithms, more accurate modelling of the multiple-input-multiple-output (mimo) crosstalk channels is needed. until now, dsl standards usually rely on the 99% worst case modelling of crosstalk power-sum for the lines in a binder. this paper proposes a parametric stochastic fext model based on the sum-of-sinusoids approach for the pair-to-pair crosstalk among multiple lines in a binder, which shows a more realistic behaviour than the worst case models.
spectrum sensing using hidden markov modeling. cognitive radio technologies are being developed which allow heterogeneous systems to share spectrum access while minimizing interference to improve the overall efficiency of spectrum usage. interference minimization requires cognitive radio receivers to be able to detect the presence of all other systems competing for spectrum usage, a process often termed "spectrum sensing". this paper focuses on the kernel function of spectrum sensing: blind interference detection from a single, strictly time-limited, received data vector. recent research has identified shortcomings in the operation of classical blind interference detection techniques such as energy detection and radiometry. this paper demonstrates that implicit interference characteristics can be exploited in a formal framework using hidden markov modeling to produce a spectrum sensor with a receiver operating characteristic which is improved on that of energy detection and several other previously reported methods.
latency and capacity optimal broadcasting in wireless multihop networks. in this paper, we study the fundamental properties of broadcasting in multi-hop wireless networks. previous studies have shown that, as long as broadcast capacity is concerned, asymptotically optimal broadcasting is possible in wireless multi-hop networks under very general conditions. however, none of the existing work on broadcast capacity has considered latency in message delivery, which is simply assumed to be finite (but not explicitly bounded). in this paper, we address the issue of investigating the fundamental properties of broadcast communications for what concerns both capacity and latency using a realistic, sinr-based interference model. in particular, we introduce a novel topological notion of network connectivity, and show that, if the network satisfies this property, asymptotically optimal broadcast capacity and latency can be achieved simultaneously. this is in sharp contrast to similar results obtained for the case of unicast transmissions, where strictly bounded latency in message delivery can be achieved only at the expense of asymptotically reducing network capacity. thus, the results presented in this paper show that scalable broadcasting in multi-hop wireless networks is, in principle, possible.
crbs for uwb multipath channel estimation: impact of the overlapping between the mpcs on mpc gain and toa estimation. in this paper we study the impact of the overlapping between neighboring mpcs (multipath component) on the performance of channel estimation. we consider ir-uwb (impulse radio) signals, and the ieee802.15.3a and ieee802.15.4a uwb channel models. we show that for a pulse width (pw) sufficiently smaller than the average mpc rate of arrival (roa) the probability to have more than three overlapping mpcs is relatively small. we derive the crbs (cramer rao bound) for the joint estimation of the mpc gain and toa (time of arrival) in the case of up to three overlapping mpcs. we compute also the average crbs. we show that the crbs obtained by averaging more than 80% of possible cases of the channel, are very close to the bounds obtained under the non-overlapping assumption (nola).
monitoring abnormal traffic flows based on independent component analysis. the randomness of the network behaviors poses serious challenges for discovering the abnormal patterns in network traffic flows. this paper presents a method based on blind source separation approach for detecting abnormal traffic flows. it decomposes the network traffic into two components: the routine pattern and the abnormal pattern. the scale-space filter with adaptive scale is applied to filter the noise without affecting the main behavior patterns which can be used to form the abnormal traffic metrics and profiles. the zero-crossing method is applied to extract the stochastic behavior pulse widths and the largest width is selected as the scale space factor. in this way, the influence of the inherent randomness could be removed or greatly reduced. the extracted patterns of the routine behaviors imply the user's habit and the abnormal patterns are useful for discovering anomalous behaviors such as scanning, flooding and content distribution attacks. a salient feature of the method is that no supervised learning process is needed. this is a very important advantage since obtaining labeled samples in traffic monitoring is extremely difficult. experimental results based on the datasets of an actual network show that this method is effective for monitoring anomaly traffic flows in the gigabytes traffic environment and the identification accuracy is above 95%.
variable-width channel allocation in wireless lan: a game-theoretic perspective. the fixed channelization structure used by ieee 802.11-based wlans constrains the total capacity and leads to unfairness. the concept of variable-width channels is recently proposed to overcome these drawbacks. to investigate the problem of the non-overlapping variable-width channel allocation for selfish access points (aps) in a wlan, we model it as a non-cooperative game. we aim to investigate two fundamental issues on it in this paper: 1) are there some fair and system-optimal nash equilibrium (ne) allocations? 2) how to achieve one of these desirable allocations if they exist? at first, the existence of fair and system-optimal nash equilibria in this game is proved. then, a simple protocol to achieve one of these desirable ne allocations is proposed. considering the implementation issues, a punishment-based method and a transfer-based self-enforcing truth-telling method are proposed for single-stage and multi-stage game scenarios respectively. the numerical results show the effectiveness of our approaches.
underground wireless communication using magnetic induction. underground is a challenging environment for wireless communication since the propagation medium is no longer air but soil, rock and water. the well established wireless communication techniques using electromagnetic (em) waves do not work well in this environment due to three problems: high path loss, dynamic channel condition and large antenna size. new techniques using magnetic induction (mi) can solve two of the three problems (dynamic channel condition and large antenna size), but may still cause even higher path loss. in this paper, a complete characterization of the underground mi communication channel is provided. based on the channel model, the mi waveguide technique for communication is developed in order to reduce the mi path loss. the performance of the traditional em wave systems, the current mi systems and our improved mi waveguide system are quantitatively compared. the results reveal that our mi waveguide system has much lower path loss than the other two cases for any channel conditions.
sampler: an optimal mac algorithm for wireless instrumentation systems. wireless devices provide flexible solutions for industrial instrumentation applications, such as quality control of manufacture of jet engines. in this context, the dominant issues are providing high-throughput, and reliability in the sense of not losing samples due to buffer overflow at the wireless devices. a random medium access control (mac) scheme, such as the ieee 802.15.4, is unlikely to perform well along those metrics. csma/ca, the foundation of ieee 802.15.4, is inefficient at the high-throughput regime. the polling mode of ieee 802.15.4, on the other hand, ignores the buffer constraints, thereby increasing the risk of buffer overflow. in this paper, we propose sampler, a scheduled mac protocol that is optimal, in the sense of minimizing sample losses while maximizing throughput, in the typical scenario where a sophisticated access point forms a star topology with the wireless sensors. we describe sampler, its properties and demonstrate its superior performance compared to random-access mac through simulations.
end-to-end qos provisioning for real-time video streaming over sp-driven p2p networks using admission control. enabling end-to-end quality of service (qos) for real-time video content delivery across heterogeneous p2p networks is challenging but vital for the efficient service provision. in this paper, we present a p2p based admission control mechanism for real-time video streaming driven by service provider (sp). sp-driven p2p network is a network where service provider has a comprehensive control over contracted resource utilization. sp assures the coordination and the creation of overlay p2p network and it is responsible for admission control and resource allocation among others. our proposed qos provision mechanism employs video traffic descriptor (i.e. traffic specification) for performing admission control. before accepting a particular p2p video streaming session, the sp controls the access to the network resources by performing policy and admission control. after retrieving the service availability from its traffic repository, sp decides whether to accept or to reject the request. the proposed sp-driven p2p admission control mechanism is evaluated using ns2 simulator and the results show that our proposed mechanism allows the provisioning of end-to-end qos for delivered video content over p2p network.
a study of network throughput gain in optical-wireless (fiwi) networks subject to peer-to-peer communications. optical-wireless (fiwi) access network is a newly emerged access network architecture which integrates passive optical networks (pons) with wireless mesh networks (wmns) to provide the ubiquitous, low cost, high bandwidth last mile internet access. though the pon subnetwork of fiwi network can provide high bandwidth, the interference in the wireless subnetwork still limits the throughput of fiwi network if all traffic goes online to the internet. however, when peer-to-peer communication from one wireless client to another wireless client is introduced, the proposed integration of pons and wmns can significantly improve the network throughput. in traditional wmns, peer-to-peer communication from one wireless client to another wireless client is carried in the wireless network, which is subject to interferences in wireless communications. in fiwi network, peer-to-peer communication can be carried through the wireless-optical-wireless mode in which the traffic is sent from the source wireless client to its nearest onu, which is then sent to the onu close to the destination wireless client through the pon subnetwork and then delivered to the destination wireless client. such wireless-optical-wireless communication mode introduced by fiwi networks can sustain the interference in wireless subnetwork, thus improving the network throughput. this paper aims to study the network throughput gain in fiwi network subject to peer-to-peer communications and parameters which can affect the network throughput gain. we first have a fair modeling of fiwi networks and traditional wmns. we then present an lp based routing algorithm for fiwi networks. extensive simulations have been carried to study the network throughput gain in fiwi networks subject to peer-to-peer communications compared with traditional wmns. the work provides insightful observations for fully utilizing advantages brought by the integration of pons and wmns in fiwi networks.
an efficient mac layer handoff scheme for wifi-based multichannel wireless mesh networks. compared to traditional wireless networks, wireless mesh networks (wmns) are more efficient in terms of deployment, configuration, and maintenance. however, connecting all routers through wireless connection in wmns results in remarkably lower bandwidth of the network backbone. multichannel technology, where non-interfering channels are used to enable mesh routers to send and receive packets simultaneously, has been extensively adopted to improve the throughput of wmns, and providing seamless roaming in multichannel wmns has become an important topic in wmn research. in this paper, a novel mac layer handoff scheme is proposed as a means of minimizing handoff latency in wifi-based multichannel wmns for seamless communication in real-time applications. by designing a dynamic grouping algorithm for channel selection and allowing mesh routers to switch channels for probe message reply, this new scheme can shorten the waiting time for the detection of available access routers, decrease loss ratio of data packets during handoff, and consequently achieve smooth handoff in the mac layer.
multihomed sip-based network mobility using ieee 802.21 media independent handover. when a group of users or devices move together, network mobility resolves how to manage the location transition of the whole members. two kinds of solutions have been proposed at different layers. network mobility (nemo) basic support protocol (bsp) is the extension of mobile ipv6 at the network layer. on the other hand, session initiation protocol (sip) based network mobility (sip-nemo) is defined at the application layer. however, on the perspective of ubiquitous network environment, a mobile router requires to possess several egress paths to the internet for providing uninterrupted services and aggregating good enough bandwidth. multihoming in network mobility support becomes one urgent and nessceary issue. since mobile ipv6 based nemo bsp, called mipv6-nemo hereafter for convenience, uses a bi-directional tunnel between home agent and mobile router, multihomed mipv6-nemo would suffer and deepen header overhead and suboptimal routing. in the past, we have proposed sip-nemo to achieve route optimization. in this paper, we investigate and analyze how to extend the current sip-nemo to support multihoming further. the proposed multihomed sipnemo is simulated in different cases and integrated with the ieee 802.21 media independent handover (mih) standard. according to the simulation result, the sip-nemo can keep route optimization no matter which multihomed case is configured.
blind spectrum sensing for cognitive radio based on signal space dimension estimation. based on information theoretic tools, a new spectrum sensing method is proposed in this paper to detect vacant sub-bands in the radio spectrum1. specifically, based on the subspace analysis of the received signal, we present a new method to detect the signal presence in a blind way. we have shown that the analysis of signal dimension can assist blind spectrum sensing procedure. indeed, we have shown that the slope change, from positive to negative trend, of the signal space dimension curve is representative of the transition from a vacant band to an occupied band (and vice versa). in fact, the number of significant eigenvalues is determined by the value that minimizes the akaike's information criterion (aic) and is directly related to the presence/absance of data in the signal. the validation of this new method is based on experimental measurements captured by eurécom rf agile platform operating from 200 mhz to 7.5 ghz. simulations show good results in terms of spectrum holes detection.
spatial interference cancellation and pairwise error probability analysis. future wireless communication systems being characterized by tight frequency reuse, adaptive modulation and coding schemes and diversified data services will be interference limited by interfering signals of diverse rates and strengths. keeping in view such a scenario, we propose in this paper the application of a recently proposed low complexity match filter (mf) based detector for spatial interference cancellation in the presence of one strong interferer. we derive an analytical upper bound for the coded pair wise error probability (pep) for the proposed mf based detector using the moment generating function (mgf) based method and prove that this detector not only recuperates the diversity order lost by mmse but also exhibits a coding gain as the interference gets stronger. we also study in this paper the effect of non gaussian interference on coded pep of mmse linear detection and demonstrate the deficit of one order of diversity and a coding loss as the interference gets stronger. our analysis provides insights to explain the relative performance of mmse and proposed mf based detectors as a function of the strength of interference. finally we demonstrate the strength of our new analytical pep upper bounds by simulations.
cfo estimation schemes for differential ofdm systems. this paper proposes two blind carrier frequency offset (cfo) estimation schemes for differentially modulated orthogonal frequency division multiplexing (ofdm) systems. the proposed schemes estimate the fractional part of the cfo with only two consecutive ofdm blocks, and they exploit two implicit properties associated with differentially modulated ofdm (dofdm) systems, i.e., the channel keeps constant over two consecutive ofdm blocks, and the dofdm systems employ an m-ary phase-shift keying constellation. one of the schemes is based on the finite alphabet (fa) constraint and the other one is based on the constant modulus (cm) constraint. they provide a trade-off between the performance and computational complexity. the constrained cramer-rao lower bound is also derived. several numerical examples are presented to validate the efficacy of the proposed schemes.
crbs for the joint estimation of toa and aoa in wideband miso and mimo systems: comparison with siso and simo systems. we derive the crbs (cramer rao bound) for the joint estimation of the toa (time of arrival) and the aoa (angle of arrival) in wideband (wb) miso (multiple input single output) and mimo (multiple input multiple output) systems.we consider both cases of orthogonal and non-orthogonal transmitted signals. we compare the crbs obtained in siso (single input single output), simo (single input multiple output), miso and mimo systems under the assumption that the total transmitted energy is the same for all systems. we show that simo and mimo are equivalent for toa estimation, and miso and siso as well when the transmitted signals are orthogonal. for non-orthogonal signals, mimo is better than simo, and miso is better than siso when the received signals are constructive. for aoa estimation, we show that mimo is better than simo and simo is better than miso when the transmitted signals are orthogonal. for non-orthogonal signals, mimo is much better when the received signals are constructive. the crbs obtained for non-orthogonal signals are very sensitive to the angle. numerical results obtained in a typical scenario are provided.
code book based cl-mimo for dl wimax rel. 1.5: system level performance analysis. in this paper, gains of the codebook based cl-mimo for down link wimax system has been studied using system level simulations. the system level simulation is based on the ieee 802.16m evaluation methodology. the 2×2 and 4×2 antenna configurations, and 3 bits and 6 bits preferred matrix index (pmi) feedback codebooks are considered. both the sub-band and wide band pmi feedback are studied. the results show that the cl-mimo provides substantial gains in cell edge and average sector throughput over ol-mimo system.
dynamic resource allocation for downlink multi-user mimo-ofdma/sdma systems. in this paper, new dynamic resource allocation algorithms are presented for the downlink of multi-user mimo-ofdma/sdma systems. since it is difficult to obtain the optimal solution to the joint optimization problem, the whole procedure is divided into two steps, namely, the subcarrier-user scheduling and the resource allocation. in the first step, a new metric is proposed to measure the spatial compatibility of multiple users each with multiple receive antennas, based on which a new subcarrier-user scheduling algorithm is designed. in the second step, two dynamic resource allocation algorithms are developed to assign radio resources to the scheduled users accordingly. simulation results demonstrate the superiority of the proposed algorithms in terms of the system throughput.
tale in the multi-core era: is java still competitive to host sip applications? multi-core platforms are becoming prevailing in telecom infrastructures, and many sip(session initiation protocol) enabled applications are using java as the development language and runtime environment. it is important to understand the workload characteristics and performance issues of java based sip stack over multi-core platforms. in this paper, two rfc 3261 compliant java based sip stacks, the jain-sip and a proprietary sip stack are studied in depth. especially we focused on the typical performance issues caused by either java language features or the workload of sip protocol, including scalability of sip stack, resource contention issue and gc impact with sip memory usage pattern. some optimization techniques and their drawbacks are also discussed along with the performance evaluation. it turns out that due to the complex combination of sip protocol semantics and java language features, the performance of java based sip stack tends to be far from competitive on multicore platforms. extensive optimization and certain improvements of program structure and object management policy may help, however, may, on the other hand, sacrifice some key values of the java language, e.g. easy development.
extending the inter-domain pce framework for authentication and authorization in gmpls networks. ietf is working on the design of new architectures and signaling solutions to support inter-as (autonomous system) gmpls-te (generalized multi protocol label switching with traffic engineering) for multi-domain, multi-carrier connection setup with guaranteed quality of service (qos). in addition, the path computation element (pce) working group is developing the framework for inter-domain path computation. however, many issues are still open regarding the joint path computation and path setup signaling solutions for inter-carrier authentication and authorization (aa). in this paper, we propose the first security solution which integrates inter-domain aa features in the pce path computation framework. specifically, we define a new architecture for inter-domain qos path provisioning based on an extension of the pce framework to include features that allow domains interested in inter-domain resources to get aa for end-to-end path provisioning over multiple domains belonging to different carriers. in addition, we introduce a mechanism to tie policies controlling path setup with the aa mechanisms introduced in the pce framework. while at present provisioning of inter-domain paths is based on rather static settlements between neighboring domains that make end-to-end qos provisioning a challenge, we propose an aa framework that allows domains interested in setting an inter-domain qos path to have guarantees about resource provided by each domain along the path from source to destination. simulation results show the performance of the model proposed in networks having different size and connectivity.
optimization of split-and-combine relaying. relays play an important role for increasing rate and reducing energy consumption of wireless networks. in this paper we consider a three-node network (source, relay, destination) in which we want to minimize total energy consumption for a given transmission rate. we analyze and optimize the split-combine-relaying (scr) protocol that for many typical parameter settings performs better than traditional decode-and-forward. scr splits a data packet into two fragments, which are then transmitted in two phases. in the first phase of transmission, the source sends the first fragment to the relay. in the second phase of the transmission, the source sends the second fragment to the destination, while, at the same time, the relay forwards the first fragment to the destination. we provide an optimization framework to decide the amount of data in each fragment, the amount of time spent in each of the phases, and the corresponding transmission powers. we also show that an extension of scr that employs slepian-wolf coding of the fragments leads to further reduction of energy consumption.
power optimal signaling for fading multi-access channel in presence of coding gap. in a multi-access fading channel, dynamic allocation of bandwidth, transmission power and rates is an important aspect to counter the detrimental effect of time-varying nature of the channel. most of the existing work on dynamic resource allocation assumes capacity achieving codes for various signaling schemes like tdma, fdma, cdma and successive decoding. for the capacity achieving codes, the rate achievable by the user is log(1 + snr), where snr denotes the signal to noise ratio of the user at the receiver side. however, codes that are used in practice have a finite gap to capacity, i.e., the achievable rate is log(1 + snr/γ) γ > 1. the exact value of γ depends on the coding strategy and the desired bit error rate. many existing resource allocation techniques that are optimal for capacity achieving codes perform sub-optimally in presence of the coding gap. for example, successive decoding does not always minimize the sum power required for providing the desired rate to each of the users for γ > 1. the problem of minimizing the sum power while guaranteeing the required rate to each of the users is important for both real-time and non real-time applications, and is addressed here. we obtain the resource allocation that is optimal for the above problem in presence of the coding gap.
dtia: an architecture for inter-domain routing. this paper proposes an architecture for inter-domain routing, called dtia - dynamic topological information architecture. dtia separates the issues of reachability and routing, and this paper addresses the first one. one major requirement has been not to change ip packets and the commercial relations in the internet. dtia is based on the knowledge of a static network formed by the autonomous systems (as) and an algorithm to manage link failures. we use the concept of a region as a mechanism to sustain scale. dtia supports the most important functionalities of bgp: some of them are built in and others can be implemented on top of the reachability level or the routing level. the main concerns we aim to solve are taking advantage of multihoming, increase the robustness in terms of convergence, reduce the churn rate and range of routing events, and due to forwarding packets by as identifiers and topologic links (as opposed to prefix policy defined) reduce the growth of the routing table.
on the capacity region of the gaussian multiple access channel with noisy feedback. we provide a new outer bound on the capacity region of the two-user gaussian multiple access channel (mac) with awgn-corrupted feedback. our outer bound is based on the idea of dependence balance due to hekstra and willems [1]. evaluating our outer bound is non-trivial as it involves taking a union over joint densities of three random variables, one of which is an auxiliary random variable. we resolve this difficulty by proving that it is sufficient to consider jointly gaussian random variables when evaluating our outer bound. as the feedback noise variances become large, our outer bound collapses to the capacity region of the gaussian mac without feedback, thereby yielding the first non-trivial result for a gaussian mac with noisy feedback. furthermore, as the feedback noise variances tend to zero, our outer bound collapses to the capacity region of the gaussian mac with noiseless feedback, which was established by ozarow [2]. for all non-zero, finite values of the feedback noise variances, our outer bound strictly improves upon the cut-set outer bound.
low bound of energy-latency trade-off of opportunistic routing in multi-hop networks. during the last decade, many works were devoted to improving the performance of relaying techniques in ad hoc networks. one promising approach consists in allowing the relay nodes to cooperate, thus using spatial diversity to increase the capacity of the system. however, this approach introduces an overhead in terms of information exchange, increasing the complexity of the receivers. a simpler way of exploiting spatial diversity is referred to as opportunistic routing. in this scheme, a cluster of nodes still serves as relay candidates but only a single node in the cluster forwards the packet. this paper proposes a thorough analysis of opportunistic routing efficiency under different realistic radio channel conditions. the study aims at finding the best trade-off between two objectives: energy and latency minimizations, under a hard reliability constraint. we derive an optimal bound, namely, the pareto front of the related optimization problem, which offers a good insight into the benefits of opportunistic routing compared with classical multi-hop routing.
distributed flooding-based storage algorithms for large-scale wireless sensor networks. in this paper we propose distributed storage algorithms for large-scale wireless sensor networks. assume a wireless sensor network with n nodes that have limited power, memory, and bandwidth. each node is capable of both sensing and storing data. such sensor nodes might disappear from the network due to failures or battery depletion. hence it is desired to design efficient schemes to collect data from these n nodes. we propose two distributed storage algorithms (dsa's) that utilize network flooding to solve this problem. in the first algorithm, dsa-i, we assume that the total number of sensors is known to each sensor in the network. we show that this algorithm is efficient in terms of the encoding and decoding operations. furthermore, every node utilizes network flooding to disseminate its data throughout the network using a mixing time of approximately o(n). in the second algorithm, dsa-ii, we assume that the total number of nodes is not known to every sensor; hence dissemination of the data does not depend on n. the encoding operations in this case take o(cµ2), where µ is the mean degree of the network graph and c is a system parameter. we evaluate the performance of the proposed algorithms through analysis and simulation. we show that the performance of the proposed algorithms matches the derived theoretical results.
a mutual information approach for comparing llr metrics for iterative decoders. we develop an approach to compare different log-likelihood ratio (llr) metrics for iterative soft decoding. we show that an llr metric for a function of the received signals is a sufficient statistic to this function about the binary channel input. we also prove that when the function belongs to a set of specific mappings, the corresponding llr metric can feed the maximal mutual information to the decoder. for decoding low density parity check codes with the belief-propagation decoder, we develop a method to estimate the minimal average number of iterations. the results are applied to compare the gaussian metric in [1] and the two-symbol-observation-interval llr metric in [2]. the latter is shown to be superior.
dimensioning of a multi-rate network transporting variable bit rate tv channels. we consider a centralised (client-server) digital tv network with heterogeneous receiver devices of different resolutions, requiring a multi-rate transport system. there exist two main ways to store and transport (streamed) tv channels in such a system: either by providing different single-layer versions of a channel (simulcast transport mode) or by keeping one multi-layered version (encoded e.g. in svc) with extractable substreams. we propose one approximate analytical and two simulation methods to estimate the capacity demand in such a network with variable bit rate channels and we consider two behaviour models. in some tv distribution networks, the video is delivered in constant bit rate. however, this implies that the video quality is varying. in order to provide better quality of service (qos), a network operator must deliver the channels in non-constant bit rate aiming in this way at constant video quality. our models take into account also the correlations between the different resolutions of a channel. starting from real experimental data, we obtain the necessary input to our models and explore two realistic tv network scenarios - with bouquets of 50 and 300 channels, respectively. the results by the three approaches correspond well (relative error of 0.5% at most). in the case of 50 channels, svc outperforms simulcast in terms of required bandwidth, while in the case of 300 channels, svc is outperformed by simulcast. therefore, we conclude that it depends on the system parameters which of both transport strategies will be more beneficial to save network resources.
low-complexity energy-efficient ofdma. energy efficient communications in wireless communications is very important as mobile devices are battery-constrained. for mobile devices in a cellular system, uplink power consumption dominates the wireless power budget, due to the rf power requirements for reliable communications over long distances. our previous work in this area demonstrated significant energy savings in uplink cellular ofdma transmissions, with iterative approaches maximizing the instantaneous bits-per-joule energy efficiency. in this paper, we use a time-averaged bits-per-joule metric to develop low-complexity schemes. specifically, we obtain closed-form solutions for energy-efficient link adaptation in frequency-selective channels. we also derive closed-form approaches for the maximum arithmetic and geometric mean energy-efficient schedulers. simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions.
channel estimation and tracking schemes for the pulse-shaping ofdm systems. robust channel estimation scheme is essential for pulse-shaping ofdm systems in the multipath mobile environment. this paper proposes three types of channel estimation schemes for the general class of pulse-shaping ofdm systems. the first two types are suboptimal low-complexity maximum likelihood estimators. the last type is adaptive kalman filter channel estimator. we numerically evaluate the performance of each estimator using computer simulation.
statistical analysis of ip delay measurements as a basis for network alert systems. measuring packet delay and packet loss through dedicated test packet streams in computer networks allows for the assessment of quality of service on the path the probes traverse. for this reason, active ip performance measurements have been carried out in x-win, germany's national research and educational network, and géant2, its european counterpart, by the win-labor group of the university of erlangen-nuremberg for many years. this paper provides an overview of how network measurements can be interpreted using a variety of statistical concepts in order to gain insight into the state of monitored connections. the focus here is set on the analysis of one-way delay (owd); the approach demonstrates how owd can be used for the identification of network congestions and can serve as a basis for network alert systems by statistically categorizing changes in the performance metric.
spectrally efficient fdm signals: bandwidth gain at the expense of receiver complexity. this paper investigates the transmission of frequency division multiplexed (fdm) signals, where carrier orthogonality is intentionally violated in order to increase bandwidth efficiency. in analogy to conventional ofdm, signal generation relies on an inverse fractional fourier transform (ifrft) that can be implemented with o(n log2 n) algorithmic complexity. optimal maximum likelihood (ml) detection is overly complex due to the presence of substantial intercarrier interference (ici). consequently, we investigate an alternative detection mechanism based on the generalized sphere decoding (gsd) algorithm. we examine the bandwidth efficiency and the error performance in additive white gaussian noise (awgn), for various fdm signal parameters. in particular, we show that it is possible to detect optimally and efficiently fdm signals, with 25% bandwidth gain with respect to analogous ofdm signals. this indicates that the transmission of spectrally efficient non orthogonal fdm signals is tangible.
a design of space-time codes for cpfsk modulation over multipath fading channels. in this paper, we derive space-time code design criteria for continuous phase frequency-shift keying (cpfsk) over multipath fast fading channels, aiming at maximizing the overall space-time diversity. we also propose a space-time coding scheme to meet the dominated design criterion, the rank criterion. our encoding scheme consists of a ring convolutional encoder and a spatial encoder with an extender in it. both the theoretical and simulation results show that with the effective code length ecl of the convolutional encoder, lt transmit antennas, lr receive antennas, and l+1 paths in the fading channel, a maximal overall diversity ecl lt lr (l+1) is achievable.
a user grouping method for maximum weighted sum capacity gain. achieving the capacity region in the mimo broadcast channel requires the use of dirty paper coding (dpc). when it cannot be afforded to satisfy the requirements of all users by dpc based approaches, it is necessary to identify the users which exhibit the highest performance gain compared to simpler approaches. in this paper we present a user grouping method that aims to identify those users with highest weighted sum rate gain. first some users are excluded by a simple criterion leading to a reduced user set, from which the final user group is selected by a more sophisticated criterion.
a cross layer fast handover scheme in vanet. this study presents a cross-layer fast handover scheme for vanet, called vehicular fast handover scheme (vfhs), where the physical layer information is shared with the mac layer, to reduce the handover delay. the key idea of vfhs is to utilize oncoming side vehicles (osvs) to collect physical and mac layers information of passing through rvs and broadcast the information to vehicles that are temporarily disconnected, referred to as broken vehicles (bvs). a bv can thus perform a rapid handover when it enters the transmission range of the approaching rvs. the effectiveness of vfhs is verified using ns2 simulations. simulation results indicate that vfhs significantly decreases handover latency and packet loss.
optimal utility-energy tradeoff in delay constrained random access networks. rate, energy and delay are three main parameters of interest in ad-hoc networks. in this paper, we discuss the problem of maximizing network utility and minimizing energy consumption while satisfying a given transmission delay constraint for each packet. we formulate this problem in the standard convex optimization form and subsequently discuss the tradeoff between utility, energy and delay in such framework. also, in order to adapt for the distributed nature of the network, a distributed algorithm where nodes decide on choosing transmission rates and probabilities based on their local information is introduced.
replica arrangement scheme for location dependent information on sensor networks with unpredictable query frequency. storing data on sensor nodes at a specified location is a useful technique for data-centric storage and management of location dependent data on wireless sensor networks. to decrease the cost of accessing these data, arranging replicas of data so that the distance between the consumer nodes and replica holder nodes decreases is desirable. conventional schemes, however, are costly for updating the replicas even if they are not often used or do not support functions for ensuring their consistency. we propose a novel replica arrangement scheme, which adaptively arranges replicas at positions close to nodes for frequent sending of queries. instead of arranging many replicas on sensor nodes, our scheme consists of nodes with pointers that point to the replica holder nodes in order to save storage for replicas. the pointers, which are smaller than replicas, are arranged so that nodes are in circular arcs surrounding the location where the original data item is associated. simulation results show that our scheme outperforms conventional replica arrangement schemes in terms of the cost required for sending queries and replies with sufficiently low replica update cost.
a new efficient mechanism for establishing ip connectivity between ambient networks. the changes in the communication paradigm envisioned for future networks, with peer-to-peer/symmetric attachments gaining momentum and two ip (internet protocol) versions coexisting, will pose new challenges to mobile communication networks. traditional ip autoconfiguration mechanisms will not work properly, since they were designed mostly having in mind a client-server/asymmetric attachment model, they assume a single ip version paradigm, and they target the auto-configuration of devices only. the ist ambient networks project has introduced a new concept - the ambient network - that enables handling every communication entity, either a single device or an entire network, as an ambient network (an). this paper describes a new efficient mechanism, named basic connectivity (bc) mechanism, for autoconfiguring ip connectivity between attaching ans. a proof-of-concept prototype, experimental results, and theoretical analysis show that bc suites the future networking paradigm and represents a solution more efficient than the current trial-and-error mechanism for auto-configuring ip connectivity.
an approach for increasing base-station anonymity in sensor networks. wireless sensor networks (wsn) are becoming an attractive choice for many critical applications, such as border protection and combat field reconnaissance. in these applications, sensors probe their surroundings and send their findings to a base-station (bs) over multi-hop paths. given the important role of the bs, an adversary who likes to disrupt the network operation would eagerly look for where the bs could be and target it with attacks in order to inflict maximum damage. the continuous flow of traffic towards the bs creates a pronounced pattern of wireless links that may expose the bs position and thus make the network more vulnerable. this paper investigates means for boosting the anonymity of the bs. first, we adapt three models -entropy based model, gsat test and evidence theory model, to quantify anonymity in the context of wsn. we further customize models that conventionally measure anonymity of the entire network, to suit the bs. then, a novel approach for boosting the anonymity of the bs is proposed. the idea is for the bs to disguise itself by transmitting some of the data packets it receives with varying intensity. the goal is to create a perception that the bs node is just another sensor node sending data and thus confuse the adversary. the approach is validated through simulation.
modeling of a public safety communication system for emergency response. this paper describes simulation work in modeling a city-wide trunked radio system and evaluating its performance under stress. specifically, traffic models are developed to simulate both routine background traffic and the traffic load associated with an emergency scenario of a high-rise apartment fire. an analysis of a one-month radio data log provided insights on the traffic distribution among different talkgroups, as well as building individual traffic loading profiles for the talkgroups directly involved in the emergency response. the performance of the radio system is evaluated under different traffic loading intensity levels. initial simulation results show that this emergency response communication system provides adequate capacity even under intense traffic loading. however, one area of concern is the build-up of waiting calls within some heavily loaded talkgroup, which results in long waiting time to access the channel.
nash bargaining over mimo interference systems. in this paper, the source covariance matrices of multiple-input multiple-output (mimo) interference channels (ifcs) are investigated from a game-theoretic perspective. it is proved that the requirement of sufficiently small interference-to-noise ratio (inr) is the sufficient condition for the uniqueness of the nash bargaining (nb) solution. the structure of the source covariance matrices, which constitute the feasible set of nb solution, is analyzed by comparing them with the covariance matrices leading to the nash equilibrium (ne). the existence of the nb solution and concavity of the rate product for mimo ifcs are also studied.
constellation rotated vector ofdm and its performance over rayleigh fading channels. although the single antenna vector ofdm (vofdm) proposed by xia is robust to channel spectral nulls, it does not necessarily attain full diversity for multi-path fading channels. in this paper, we propose a novel constellation-rotated v-ofdm (crv-ofdm) system based on modified v-ofdm, and analyze its performance over rayleigh fading channels. in crv-ofdm, we design rotation angles for each symbol to minimize upper bounds on bit error rate (ber) with full diversity order. our simulation results show that, compared with v-ofdm, proposed crv-ofdm always attains the maximum diversity order determined by the vector length m. as a result, for ber 10-4, crv-ofdm improves the performance of v-ofdm by 2db for both bpsk and qpsk modulation for m = 2, and, for m = 4, the improvement is about 1.3db. to verify optimality of the derived angles, we also test, in therms of ber, some other angles including the angles derived from minimum product distance (mpd) criterion and compare with the theoretical union bounds and show that the bers take the smallest values at our derived optimal angles.
a distributed protocol for virtual device composition in mobile ad hoc networks. the dynamic composition of systems of networked appliances, or virtual devices, in manets, enables users to generate, on-the-fly, complex strong specific systems. current work in the development of service composition architectures in manets has yet to address qos metrics for enhanced composition from a virtual device perspective. in this paper, we present an extension to a prominent dynamic broker-based distributed service composition protocol, embedding in a distributed manner, a qos model providing compositions that form the best possible virtual device at the time of need. simulation results show that our protocol extension provides a high increase in qos at a low cost in terms of increased amounts of messages and composition time.
identifying the use of data/voice/video-based p2p traffic by dns-query behavior. there are more and more p2p applications in the internet, with or without encrypted content. the p2p applications can be classified into three categories: file sharing (bt, emule), voip (skype, msn), and video streaming (ppstream, pplive). by observing the common communication nature among the peers, this paper proposes a simple but efficient way to identify the p2p traffic by the dns query behavior. experimental results illustrate that the proposed mechanism is able to accurately identify if a host is using data/voice/video-based p2p traffic, even the packet content is encrypted. the proposed mechanism is also capable of detecting future unknown p2p applications as long as they perform the common p2p behaviors.
joint message-passing symbol-decoding of ldpc coded signals over partial-response channels. we consider the problem of joint detection and decoding of low-density parity-check (ldpc) coded signals over partial response (pr) channels. a method to graphically represent the constraints imposed by the channel and the code on the channel output sequence is introduced. this enables the design of a detector and decoder that estimates a posteriori probabilities of noiseless channel output symbols rather than binary channel inputs. by running the sum-product algorithm (spa) on this graph, a joint decoder is obtained that is shown to perform significantly better than the turbo-equalizer, at the cost of increased computational complexity.
throughput enhancement in multi-carrier systems employing overlapping weyl-heisenberg frames. a methodology for doubling the throughput of multi-carrier systems is proposed. throughput enhancement method is introduced by using pulse shaping in multi-carrier systems. by employing more than one weyl- heisenberg frames that are orthonormal both within the frame and in between the frames, the throughput of multi-carrier systems is increased. different lattice density scenarios are investigated for throughput enhancement. it is shown that by employing the proposed methodology, throughput of a multi-carrier system can be doubled. theoretical analysis quantifying throughput enhancements are presented and results are supported by simulation studies. a system level comparison is presented for ieee 802.16 standards. the effects of various impairments are investigated.
efficient sample rate conversion in software radio employing folding number system. in an ideal software radio, digitization of the received signal occurs immediately after receive antenna to enable channelization to be performed in the discrete time domain. however, this vision is still far from reality due to limitations of current analog to digital converter performance. in this paper, a novel number system called the folding number system (fns) is proposed for use in software radio. we implement sample rate conversion immediately after the receive antenna using this number system thus providing an efficient solution to the above problem. by decomposing the input analog signal into separate channels in parallel, symmetrical residues are obtained with reduced number of comparators. these residues together with the folding information are processed in parallel in the fns domain. the fns has the same computational complexity as that in residue number system but the need for the intermediate steps such conversion of the analog data into binary and subsequently into residues is absent.
fpga implementation of rls adaptive filter using dichotomous coordinate descent iterations. in this paper, we present an fpga implementation of a recursive least squares adaptive filtering algorithm based on dichotomous coordinate descent iterations. the algorithm is simple for finite precision implementation, requires small chip resources, and exhibits numerical stability. for arbitrary regressors (as in antenna array beamforming), the proposed implementation allows significant increase in the weight update rate compared to implementations based on qr decomposition; for 9 and 32-element arrays, the update rates are as high as 162 khz and 31 khz, respectively. for 16-tap and 64-tap transversal filters, the proposed implementation provides the weight update rate 207 khz and 76 khz, respectively.
a performance analysis on route optimization for proxy mobile ipv6. proxy mobile ipv6 has been developed from the concept of network-based mobility support protocol in the ietf. the recently published specification of proxy mobile ipv6 only focuses on the mobility support. then, route optimization issues are left in the basket for further works. in this paper, we provide the performance analysis in where the recently proposed route optimization is evaluated in terms of signaling cost and packet delivery cost. through the provided analysis results, we demonstrate that route optimization solves the ineffective routing path problem during the mobile host communicates with its corresponding host and argue that the scalability of proxy mobile ipv6 architecture is improved due to the distributed routing path. in addition, the cost model developed in this paper would be a reference model in order to facilitate decision-making for further route optimization design.
detecting greedy behaviors by linear regression in wireless ad hoc networks. the csma/ca protocol is well known to handle the channel access to various users in wireless ad hoc networks using ieee 802.11 technology. this protocol requires nodes to wait for some time before initiating a transmission to avoid collisions. as a result, the greedy behavior of some misbehaving nodes can try to lower their waiting time in order to access the channel earlier and penalize the other nodes. in order to avoid this misbehavior, we propose in this paper a model based on measuring the linear regression of nodes' access time to the channel. we have demonstrated that this model exhibits a linear regression between the different nodes' access time. this result has been also confirmed by simulations. in this model, each deviation from the estimated slope is considered as a source of cheating from a corresponding node. by using this detection model, we were able to detect most of the misbehaving nodes in wireless ad hoc networks without requiring modifications to the ieee 802.11 mac protocol.
a handover scheme based on moving extended cells for 60 ghz radio-over-fiber networks. we demonstrate a handover scheme for supporting high end-user mobility in a 60 ghz broadband picocellular radio-over-fiber network. the proposed scheme relies on a novel moving extended cell (mec) concept which is based on user-centric virtual groups of adjacent cells that transmit the same data content to the user. the mec concept utilizes a mechanism for restructuring the virtual multi-cell area according to the user's mobility pattern, so that a virtual antenna group moves together with the mobile user. a mathematical model is developed and performance evaluation is also conducted and presented, demonstrating zero packet loss and call dropping probability values in high-rate wireless services for a broad range of mobile speeds up to 40m/sec and independently of the fiber link distances.
epson: enhanced physical security in ofdm networks. secure wireless communications is a challenging problem due to the shared nature of the wireless medium. most existing security mechanisms focus on traditional cryptographic schemes. in recent years, features of the multi-path channel (such as randomness and reciprocity), have driven researchers to exploit its potential to enhance the security of wireless networks. as ofdm occupies wide bandwidth, it will experience a prolific source of multi-path components. in this paper, we comprehensively exploit the inherent physical parameters of the multi-path fading channel to achieve continuous two way authentication between wireless terminals. in our scheme, pilot information is randomly spread in a wideband channel, leading to low probability of detection (lpd). unlike other channel-based approaches, the information of both amplitude and phase in the channel signature is fully utilized to enhance the security of the ofdm communication network. more specially, the receiver will detect the channel response continuously according to the randomly inserted pilots and identify the valid user based on the statistical channel signature information. simulation results indicate the high efficiency of the proposed method.
a case study for evaluating ieee 802.15.4 wireless sensor network formation with mobile sinks. wireless sensor networks are traditionally composed of a multiplicity of sensor nodes that sense given phenomena and deliver the sensed data to specific sink nodes. in the most of the application scenarios, sensor nodes have been considered motionless. on the contrary, interesting possibilities arise if some sensors are embedded in devices carried by mobile agents as people, cars, animals, etc. if sinks move within the considered sensor field, they are able to provide both sparse sensing and collecting of data measured by static sensors placed at fixed locations. the main goal of this work is to evaluate, through simulations, the impact of sinks' mobility in a wireless sensor network created by using the topology formation mechanism provided by the ieee 802.15.4 standard. to this aim, as a practical case study, we consider a wireless sensor network deployed in a museum used to monitor the presence, the localization and other parameters of artworks exposed in it. in this context, we analyze how sinks' mobility affects connectivity and energy consumption for network formation and re-configuration.
novel preamble-based channel estimation for ofdm/oqam systems. ofdm/oqam has been considered as an attractive alternative to classic ofdm with cyclic prefix (cp) over doubly dispersive channels. by utilising well designed pulse shapes and removing cp, ofdm/oqam has the advantage of reduced out-of-band energy and a theoretically higher spectral efficiency. however, channel estimation over doubly dispersive channels has been a big problem for ofdm/oqam due to the nonorthogonality between the real and imaginary parts of its modulated signals. therefore conventional channel estimation (ce) methods used for ofdm cannot be directly applied to ofdm/oqam. recently a preamble-based ce method - interference approximation method (iam) - has been proposed to ease this task. by treating the intrinsic interference from neighbour symbols as known information, two heuristic preamble sequences have been constructed based on tentative observations, which turn out to be suboptimal. in this paper, we present a general theoretical framework for iam preamble design and apply it to identify the optimal iam preamble sequence which results in a higher gain. numerical results have verified the effectiveness of the theoretical framework and a gain of 2.4 db against cp-ofdm has been demonstrated with the new preamble in various doubly dispersive channels with a qpsk modulation.
distributed turbo coding with information transfer via timing of the half-duplex relay-phases. we consider a wireless half-duplex relay communication from a source to a destination with a distributed turbo code. the source broadcasts code-bits to relay and destination during the relay-receive phases, the relay decodes and transmits additional code-bits to the destination during the relay-transmit phases. we propose to use the timing of the relay-receive and relay-transmit phases to transfer more additional code-bits to the destination at the cost of stricter synchronization requirements. moreover, it is required that the relay is able to switch its state rapidly between receiving and transmitting from symbol to symbol. the destination does not know the timing of the relay-receive and relay-transmit phases a priori and has to distinguish the transmissions of source and relay due to the received amplitude. the received amplitude at the destination is higher for transmissions of the relay because the relay-destination link is stronger than the source-destination link. a constant-weight code is used to determine the timing of the relay-receive and relay-transmit phases. simulation results for an example show a substantial gain of the proposed extension.
on the use of multi-objective optimization algorithms for solving the impairment aware-rwa problem. in future transparent optical networks, it is important to consider the impact of physical impairments in the routing and wavelengths assignment process, to achieve efficient connection provisioning. in this paper, we use classical multi-objective optimization (moo) strategies and particularly genetic algorithms to jointly solve the impairment aware rwa (iarwa) problem. fiber impairments are indirectly considered through the insertion of the path length and the number of common hops in the optimization process. it is shown that blocking is greatly improved, while the obtained solutions truly converge towards the pareto front that constitutes the set of global optimum solutions. we have evaluated our findings, using an q estimator tool, that calculates the signal quality of each path analytically.
crosstalk cancellation in upstream coordinated dsl using an iterative mmse receiver. in this paper, we address the problem of the presence of spatial correlated noise in upstream coordinated dsl systems. the performance of a minimum mean-squared-error (mmse) iterative receiver structure without whitening the noise is evaluated. a simplified mmse receiver based on the approximation of matrix inversion in the iterative process is presented. the convergence of the iterative scheme in this scenario is predicted using exit charts under realistic transmission conditions.
space-time block codes with symbol-by-symbol maximum likelihood detections. this paper presents a new set of quasi-orthogonal space-time block codes (qostbcs) with symbol-by-symbol maximum likelihood (ml) detections for four transmit antennas over quasi-static rayleigh fading channels. each of them is analytically proved to achieve full diversity and the same coding gains as the coordinate-interleaved orthogonal design by individually using their optimal constellation rotations over arbitrary qam or 4m-psk constellations. previous designs are included in our systematic formulation as well. together with the simulation results, the coding loss paying for simplifying the optimal decoders from complex symbol pairwise to symbol-by-symbol ml detections is found asymptotically equal to 0.21 db, for the qostbcs achieving full diversity and the optimal coding gains over general qam constellations.
reflected simplex codebooks for limited feedback mimo beamforming. this paper proposes reflected simplex codebooks for limited feedback beamforming in multiple-input multiple-output (mimo) wireless systems. the codebooks are a geometric construction based on simplices and the an lattice. we propose a fast codebook search and indexing algorithm. we show that such codebooks perform superior or comparable to other codebooks, with much lower implementation complexity.
a secure solution for ubiquitous multimedia broadcasting. ubiquitous multimedia applications are becoming more and more popular. however, the solutions that confirm content and interaction security in these applications are still open issues because of various network convergences and device interconnections. this paper investigates a ubiquitous multimedia scheme and proposes a secure service solution. in the ubiquitous scheme, the multimedia content is encoded with scalable video coding and broadcasted via digital video broadcasting for handheld terminals (dvb-h) to mobile terminals, the access right is transmitted by global system for mobile (gsm) channel, and the media content and access right can also be transmitted from mobile terminals to home tv through wifi based wireless local area network. the proposed secure solution supports three kinds of business models by using various content encryption modes and secure interaction protocols. the solution's security is evaluated and discussed. since few works have been done to solve this problem, this paper is expected to attract more researchers.
proposal of the architecture of a qos assured network by cooperating between ip flow control and mpls diffserv-te. this paper proposes a network architecture to achieve a qos assured network, which is composed of two qos control technologies such as ip flow control and mpls diffserv-te. ip flow control technology is utilized to treat ip packets as an ip flow distinguished by source and destination ip addresses, ports, protocol and priority and to apply the cac function on the per-flow basis. mpls diffserv-te is also used to accommodate multiple ip flows along the lsp via a bandwidth guarantee with certain service classes. by using the network testbed, we confirmed some of functions in our proposed architecture of the qos assured network worked properly following the cac capability of flow state routing and lsp-based bandwidth guarantee of mpls diffserv-te. multiple ip flows can be appropriately conveyed over the assigned lsp. moreover, we verified the operation of the prototype nms to monitor ip flows, lsps and the inclusion relationship between them. and we also derived a policy to set the bandwidth for cac at the edge router for effective utilization of bandwidth.
channel-assignment and scheduling in wireless mesh networks considering switching overhead. this paper considers the channel-assignment and scheduling in wireless mesh networks that employ multiple radios and multiple channels. in contrast to the various algorithms available in the literature, we explicitly model the delay overhead that is incurred during channel switching, and use that delay in the design of algorithms. we prove that the well known greedy maximal scheduling (gms) algorithm does not have any provable efficiency ratio when the switching overhead is considered. we present a centralized algorithm (cgsso), and a dynamic algorithm (dmsso), both of which consider switching overhead. simulation results show that the proposed algorithms significantly outperform other algorithms in packet throughput and average packet delay metrics. results also show that the improvements in performance become more pronounced as the switching delay increases.
a low ml-decoding complexity, high coding gain, full-rate, full-diversity stbc for 4 × 2 mimo system. this paper proposes a full-rate, full-diversity space-time block code (stbc) with low maximum likelihood (ml) decoding complexity and high coding gain for the 4 transmit antenna, 2 receive antenna (4×2) multiple-input multiple-output (mimo) system that employs 4/16-qam. for such a system, the best code known is the djabba code and recently, biglieri, hong and viterbo have proposed another stbc (bhv code) for 4-qam which has lower ml-decoding complexity than the djabba code but does not have full-diversity like the djabba code. the code proposed in this paper has the same ml-decoding complexity as the bhv code for any square m-qam but has full-diversity for 4- and 16-qam. compared with the djabba code, the proposed code has lower ml-decoding complexity for square m-qam constellation, higher coding gain for 4- and 16-qam, and hence a better codeword error rate (cer) performance. simulation results confirming this are presented.
dynamic resource allocation with limited feedback for ofdm based cooperative networks. we propose a dynamic resource allocation scheme for a wireless cooperative network based on orthogonal frequency division multiplexing (ofdm) modulations with limited feed-back. the amount of the feedback information required from the relay to the source in the proposed scheme is independent of the number of subchannels, which results in a dramatic reduced overhead over conventional resource allocation schemes. furthermore, the transmission durations at the source and the relay are designed to be asymmetric, which enhances the degree of freedom for transmission. simulation results show that the proposed resource allocation scheme achieves a higher system capacity, and has less sensitivity to channel estimation errors than the previously proposed schemes based on subchannel paring and power allocation. it also has a fast convergence speed. an intensive performance analysis is provided for the proposed resource allocation scheme.
probabilistic diagnosis of link loss using end-to-end path measurements and maximum likelihood estimation. internet fault diagnosis has attracted much attention in recent years. in this paper, we focus on the problem of finding the link pass ratios (lprs) when the path pass ratios (pprs) of a set of paths are given. usually, given the pprs of the paths, the lprs of a significant percentage of the links cannot be uniquely determined because the system is under-constrained. we consider the maximum likelihood estimation of the lprs of such links. we prove that the problem of finding the maximum likelihood estimation is np-hard, then propose a simple algorithm based on divide-and-conquer. we first estimate the number of faulty links on a path, then use the global information to assign lprs to the links. we conduct simulations on networks of various sizes and the results show that our algorithm performs very well in terms of identifying faulty links.
energy efficient error correction in mobile tv. the current error correction layer of digital mobile tv is designed for worst case scenarios, which often do not apply. in this paper, we propose a new opportunistic error correction layer based on fountain codes and a resolution adaptive adc, which has been integrated into the ofdm-based physical layer. the key element in the new proposed system is that only packets are processed by the receiver which have encountered high-energy channels. others are discarded. with this new approach, around 84% of the energy consumption in adcs can be saved compared with the conventional mobile tv system under the same channel conditions.
detecting primary user emulation attacks in dynamic spectrum access networks. in this paper, we present an analytical model as well as a practical mechanism to detect denial of service (dos) attacks on secondary users in dynamic spectrum access (dsa) networks. in particular, we analyze primary user emulation attacks (puea) in cognitive radio networks without using any location information and therefore can do away with dedicated sensor networks. we present an analysis using fenton's approximation and wald's sequential probability ratio test (wsprt) to detect puea. simulation results demonstrate that it is possible to keep the probability of success of puea low, while still keeping the probability of missing the return of the primary low as well.
steady-state kalman filtering for channel estimation in ofdm systems utilizing snr. kalman filters are effective channel estimators but they have the drawback of having heavy calculations when filtering needs to be done in each sample. in our paper we obtain the steady-state kalman gain to estimate the channel state thus eliminating a larger portion of the calculation burden. steady-state value is calculated by transforming the vector kalman filtering in to scalar domain by exploiting the filter characteristics when pilot subcarriers are used for channel estimation. kalman filters operate optimally in the steady-state condition. therefore by avoiding the convergence period of the kalman gain, the proposed scheme is able to perform better than the conventional method. also, driving noise variance of the channel is difficult to obtain practical situations and accurate knowledge is important for the proper operation of the kalman filter. thus we extend our scheme to operate in the absence of the knowledge of driving noise variance by utilizing received signal-to-noise ratio (snr). simulation results show considerable estimator performance gain can be obtained compared to the conventional kalman filter.
superior nda ml delay and gain estimators for uwb channels. novel non-data-aided maximum likelihood estimators for the delays and the attenuations in an ultra-wide bandwidth channel are proposed. numerical results show that these new estimators outperform the previous non-data-aided maximum likelihood channel estimators derived in the literature. moreover, in some cases, the performances of the new non-data-aided estimators approach those of the data-aided estimators, enabling us to reduce the overhead expense of pilot symbols.
fsa: a fast coordination scheme for opportunistic routing. opportunistic routing (or) has been considered as one promising technique to overcome the unreliability of the wireless medium by collaborating multiple neighboring receivers/candidates for packet forwarding. a key challenge in or is how to efficiently coordinate the multiple candidates and ensure only one of them to forward the packet. in this paper, we investigate the existing candidate coordination schemes and propose a "fast slotted acknowledgment" (fsa) to further improve the performance of or by using single ack with the help of channel sensing technique. the simulation results show that fsa can reduce the average end-to-end time delay of or protocols by up to 50% compared with state-of-the-art coordination schemes in light traffic scenarios and can increase the average end-to-end throughput by up to 20% in heavy traffic scenarios.
towards secure spectrum decision. the key idea of dynamic spectrum access (dsa) networks is to allow the secondary, unlicensed users to detect and use unused portions of the spectrum (white spaces) opportunistically. the two main constraints in the design of dsa networks is to make sure that this opportunistic access is done without any disruption of service to the primary users and without any modifications to the primaries themselves. most architectures and protocols for dsa networks in the literature assume that all parties are honest and that there are no attackers. recently (ieee icc, cognet 2008) we demonstrated the failure of this approach by showing that an attacker can manipulate messages to convince the parties involved in the protocol to make incorrect spectrum decisions. in this paper, we consider spectrum decision protocols in clustered infrastructure-based dynamic spectrum access networks where the spectrum decision in each cluster is coordinated by some central authority. we propose an efficient and provably secure protocol that can be used to protect the spectrum decision process against a malicious adversary.
opportunities, constraints, and benefits of relaying in the presence of interference. in this paper the interference channel is extended by additional relay nodes in order to investigate the influence of interference on the design and performance of relaying protocols. we introduce a framework in which the relay interference channel is decomposed into a cascade of individual interference channels with finite conference links at the transmitters. each of these stages is able to implement interference cancellation and mitigation schemes such as dirty-paper and han-kobayashi coding. we discuss the dependencies between individual stages and propose specific approaches with reasonable complexity. finally, we compare the performance of these protocols using a simplified model for the channel and network geometry of a mobile communications system. the results show that a reasonable choice is to coordinate the base-station to relay links using distributed dirty-paper coding and to mitigate interference on the relay to user link using han-kobayashi coding.
a user-decided service model and resource management in a cooperative wimax/hsdpa network. employing multiple radio access technologies such as wimax, hsdpa and wi-fi in a mobile network to provide users with more cost-effective communication services has long been a vision of many service network providers. in this paper, we propose a novel user-decided service model for a cooperative wireless network in which the radio resources of multiple wireless networks are collectively managed. under the model, users are provided with multiple service options with different levels of service quality and charges. it is up to users to choose the most suitable service option (and access network) based on their personal preference and the amount of money they are willing to pay. we use a video streaming service in a wimax/hsdpa network as an example to illustrate the key concepts and resource management of our approach. the results of simulation show that, under the model, the service network can accommodate more users and provide higher user satisfaction than the traditional network-decided service model. it can also achieve higher resource utilization and revenues. this demonstrates the importance of defining the concept of user-decided service model in a cooperative heterogeneous networking environment.
system design and resource allocation in 802.16j multi-hop relay systems under the user rate fairness constraint. ieee 802.16j multi-hop relay task standard includes two mutually exclusive options: transparent relay stations (t-rs) and non-transparent relay stations (nt-rs). in this work, a system design approach is proposed to compare different relay systems in term of their capacity with rate fairness constraint among the mobile stations (ms). single-input single-output (siso) and multi-input multi-output (mimo) antenna systems are considered in the links between the base station (bs) and relay stations (rs). 1 and 3 rss per sector are considered. our simulation results show that for any case, the highest capacity is achieved by nt-rs with 3 rss per sector in distributed scheduling mode. in addition, the effect of the ms association rule, which determines the access station (bs or rs) for each ms, is also investigated. two rules: highest mcs scheme with the highest modulation and coding rate, and highest (mod) ese scheme with the highest (modified) effective spectrum efficiency, are studied along with the optimal rule that maximizes system capacity with rate fairness constraint. it is demonstrated that highest (mod) ese scheme performs closely to the optimal rule in term of capacity.
vb-rescheduling: an efficient data channel rescheduling algorithm based on virtual burst for obs networks. in optical burst switching (obs) networks, the data channel scheduling algorithm is one of the most important issues, which have a great impact on network performances. currently, there are various data channel scheduling algorithms. among them, the rescheduling algorithm is more attractive because it could adaptively reallocate the data channels even when they have been occupied by some data bursts (db), and release some channel resource for the latter db in most situations. however when the traffic load is heavy, it is not effective any more, and would worsen network performance. therefore, this paper proposes a new rescheduling algorithm, namely vb-rescheduling algorithm. according to the state of the data channels, it reschedules data blocks on demand by three granularities (i.e., virtual burst, child-burst cluster and normal burst). compared with other rescheduling algorithms, it has some advantages as follows. firstly, it could keep the same sequence of the arriving data bursts at a node as the corresponding control packets. secondly, it is more flexible to reschedule data blocks. finally, simulation results show that it can greatly improve obs network performance in terms of the overall packet loss probability and the link utilization, compared with traditional obs rescheduling algorithm (whose rescheduling granularity is normal burst) and the native virtual burst scheduling scheme.
routing games for traffic engineering. current data network scenario makes traffic engineering (te) a very challenging task. the ever growing access rates and new applications running on end-hosts result in more variable and unpredictable traffic patterns. by providing origin-destination pairs with several possible paths, load-balancing has proved itself an excellent tool to face this uncertainty. in particular, mechanisms where routers greedily minimize a path cost function (thus requiring minimum coordination) have been studied from a game-theoretic perspective in what is known as a routing game (rg). the contribution of this paper is twofold. we first propose a new rg specifically designed for elastic traffic, where we maximize the total utility through load-balancing only. secondly, we consider several important rgs from a te perspective and, using several real topologies and traffic demands, present a thorough comparison of their performance. this paper brings insight into several rgs, which will help one in choosing an adequate dynamic load-balancing mechanism. the comparison shows that the performance gain of the proposed game can be important.
capacity of hierarchical wifi/wimax networks. in this paper, we assess the capacity of hierarchical wifi/wimax networks, where end users are connected to the internet via wifi access points while wimax plays the part of backhaul. at the packet level, we model both wifi and wimax throughputs, taking into account inter-cell interference and radio conditions heterogeneity over the network. at the flow level, we provide a markovian analysis that calculates the performance metrics like the blocking rate and the user-perceived throughput. the interaction between the different cells in the network, at the access and backhaul layers, is solved by a fixed point approach. our numerical results illustrate the capacity of the network and the impact of replacing the wired backhaul by a wimax one.
a service-transparent and self-organized optical network architecture. in this paper, a new service oriented networking paradigm is presented, where network nodes (peers) are self-organized into individual service entities. the key idea relies on the overlay approach, where there exists a virtual service plane, fragmented into self-organized and self-managed entities called islands of service transparency. the islands are formed in an upstream, ad-hoc mode from the non-networking resources (i.e vod, grid server, etc) towards all ingress routers of the network, using link state advertisements and multi-cost path selection algorithms (i.e residual bandwidth, server capacity, storage, etc). organization and re-organization of nodes around nonnetwork resources is transparent to end-users, and thus any request within a specific service island is transparently routed to the island's resource for execution. a service proxy is commissioned to resolve service addresses and service attributes to qos metrics. in this paper, we present the main notations and metrics of the proposed architecture as well as node behavior and potential gmpls extensions for implementation issues.
an insider-resistant group key exchange protocol without signatures. the well-known method for a group key exchange (gke) protocol to be against insider attack is to make use of signatures. however, using signatures considerably degrades the performance of the gke protocol. in this paper, we propose a new method to resist insider attack. the underlying tool of our method is a two-party authenticated key exchange (ake) protocol, which can be used to authenticate all other participants' session identifiers instead of using signatures. based on the two-party ake protocol, we propose an efficient insider-resistant gke protocol without signatures. we show that our proposal is provably secure against insider attack if the underlying two-party ake protocol is secure.
resource management in stargate-based ethernet passive optical networks (sg-epons). at present there is a strong worldwide push towards bringing fiber closer to individual homes and businesses. another evolutionary step is the cost-effective all-optical integration of fiber-based access and metro networks. stargate [1] is an all-optical access-metro architecture which does not rely on costly active devices and makes use of an overlay island of transparency with optical bypassing capabilities. in this paper we propose onu architectures, and discuss several technical challenges, which allow stargate epons (sg-epons) to evolve in a pay-as-you grow manner while providing backward compatibility with legacy infrastructure and protecting previous investment. using a simple bandwidth and wavelength allocation, we study the capacity and delay performance of sg-epon through simulations
arbitrarily tight upper and lower bounds on the gaussian q-function and related functions. we present a new family of tight lower and upper bounds on the gaussian q-function q(x). it is first shown that, for any x, the integrand ϕ(θ x) of the craig representation of q(x) can be partitioned into a pair of complementary convex and concave segments. as a consequence of this property, integrals of ϕ(θ x) over arbitrary intervals within its convex region can be lower-bounded by jensen's inequality and upper-bounded by cotes' quadrature rule, with the opposite occurring for the concave region ϕ(θ x). the combination of these complementary bounds yield a complete family of both lower and upper bounds on q(x), which are expressed in terms of elementary transcendental functions and can be made arbitrarily tight by finer segmentation. a by-product of the method is that various other functions, such as the squared gaussian q-function q2(x), the 2d joint gaussian q-function q(x, y, ρ), and the generalized marcum q-function qm(x, y), can also be both upper and lower bounded with arbitrarily tightness, which to the best of our knowledge finds no precedence in the literature. explicit examples of the latter applications are given.
impact of alliances on end-to-end qos satisfaction in an interdomain network. this paper focuses on qos guarantees in an interdomain selfish network where each domain may sell qos guarantees for its transit traffic. the main objective of the paper is to evaluate the benefit for some of these domains to develop together a privileged partnership in terms of economic alliance. this alliance permits the members to share their local knowledge of the network and to exchange some traffic network services. after defining the alliance model and the way each domain may use it to obtain better qos guarantees, we analyse by simulation on realistic generated topologies the impact of such alliances on the qos requests satisfaction.
linear mmse mimo channel estimation with imperfect channel covariance information. in this paper, we investigate the effects of imperfect knowledge of the channel covariance matrix on the performance of a linear minimum mean-square-error (mmse) estimator for multiple-input multiple-output (mimo) channels. the estimation mean-square-error (mse) is analytically analyzed by providing both a very tight lower bound and an upper bound. the proposed analysis is useful for the understanding of how estimation accuracy of the channel covariance matrix impacts on system performance, depending on the average signal-to-noise ratio (snr) and specific propagation conditions. conclusions are fully supported by numerical results.
receive antenna gain of uniform linear arrays of isotrops. the receive antenna gain of an antenna array critically depends on the receiver noise covariance. receiver noise essentially originates from two sources: the receive low-noise amplifiers (lna), and background radiation that is received by the array. in case that the lnas are the sole origin of noise, it is state of the art to argue that the receiver noise is spatially uncorrelated, for noise originates in components of physically separate lnas. however, this argument ignores coupling between antennas due to their spatial proximity, and moreover the coupling introduced by the impedance matching network which is located between the antenna outputs and the lna inputs. because of these coupling effects, the receiver noise is usually spatially correlated even when independent lnas are the sole source of noise in the system. the noise covariance, depends on the following four factors: 1) antenna spacing of the array, 2) properties of the impedance matching network, 3) noise-resistance of the lnas, 4) intensity of received background noise with respect to noise generated by the lnas. taking these issues into account, we derive, in this paper, the receive antenna gain of a uniform linear antenna array of isotrops in closed form. it turns out that the receive antenna gain can become much larger than the number of antennas. for the case of low noise-resistance, and low relative intensity of received background noise, we show that the receive antenna gain can even grow exponentially with the number of antennas. these results are exciting, because they imply that the performance of communication systems which use multiple receive antennas can be much better than previously reported.
a compressed sensing based ultra-wideband communication system. sampling is the bottleneck for ultra-wideband (uwb) communication. our major contribution is to exploit the channel itself as part of compressed sensing, through waveform-based pre-coding at the transmitter. we also have demonstrated a uwb system baseband bandwidth (5 ghz) that would, if with the conventional sampling technology, take decades for the industry to reach. the concept has been demonstrated, through simulations, using real-world measurements. realistic channel estimation is also considered.
on the performance of amplify-and-forward cooperative diversity with the nth best-relay selection scheme. cooperative-diversity networks have recently been proposed as a way to form virtual antenna arrays without using collocated multiple antennas. in this paper, we consider the amplify-and-forward cooperative-diversity system with the nth best-relay selection scheme. in the best-relay selection scheme, the best relay only forwards the source signal to the destination. however, the best relay might be unavailable; hence we might resort to the second, third or generally the nth best relay. we derive closed-form expressions for the symbol error probability, outage probability and channel capacity. in particular, we derive a closed-form expression for the probability density function of the signal-to-noise ratio of the relayed signal at the destination node. then, we find a closed-form expression for the moment generating function of the total snr at the destination. this mgf is used to derive the closed-form expressions of the performance metrics. results show that with the nth best relay the diversity order is equal to (m - n +2) where m is the number of relays. simulation results are also given to verify the analytical results.
multi-hop capacity of mimo-multiplexing relaying in wimax mesh networks. one of the main challenges for metro-scale wimax mesh network deployments is related to capacity scaling. in a full mesh mode, a wimax node acts as a mesh router as well as a client access node. to improve latency and speed performance, typical dual- and multi-radio mesh solutions use different radio channels to create separate links for access and mesh relaying services. the available spectrum is therefore split between mesh and client access services. network operators operating the wimax system over the licensed spectrum are not keen to provide separate radio channels for access and mesh relay services, as this reduces the total number of users serviced per spectrum allocation. mimo-multiplexing relaying approach however provides separate links for access and mesh relaying services on the same radio channel. in this paper, we discuss the multi-hop capacity of ofdm-based mimo-multiplexing relaying in wimax networks. for an n×n mimo-multiplexing relaying with amplification factor α at relay nodes, r-hops relaying degrade the capacity by at most -nlog2(α2r/(1+σrr=1 α2r nr)) +rnlog2(n) bits/sec/hz. therefore, greater capacity loss is experienced in networks employing high-order mimo-multiplexing relaying. we also show that the capacity loss is independent of the ofdm configurations employed; thus network operators could employ higher ofdm configurations to compensate data rate loss in access services when some of the mimo-multiplexing links are dedicated to mesh relay. this analysis provides useful guidelines for operators planning mimo-multiplexing option for mesh support in wimax network.
help: // hypertext in-emergency leveraging protocol. this paper proposes help://, a simple light-weight protocol that runs over http and is used to disseminate information from a server(s) to its clients during the time of a crisis. help runs on an architecture that is a hybrid mix between a pure client/server architecture and a peer-to-peer architecture. its resemblance to one versus the other is dynamically decided based on load. in particular, under light load, help operates in a client/server mode, where all clients are served directly from the server. under high load, however, help picks one client in every n clients to help the server in serving its content. the value of n is chosen dynamically to optimize the performance of help and to ensure that clients receive their requested content with a very high probability, even in the presence of uncooperative clients. we assess the performance of help through analysis, simulation experiments and real implementation in linux. we envision help to be installed as a plug-in in common browsers.
multiuser extensions for closed loop transmit diversity in hsdpa. closed loop transmit diversity has already been adopted by 3gpp for mimo hsdpa in the form of txaa and its dual stream counterpart, d-txaa. while both these transmission techniques provide performance gains for single user (su) scenarios, they both introduce multi-user interference in the downlink in multi-user(mu) scenarios. in this paper, we study the extension of these transmission techniques to the multi-user case which entail minimal changes to the existing standard. to this end, we consider the classical mmse chip equalizer receivers that feed back beamforming weights so as to maximize the receive sinr at each user equipment (ue). given that the base station (bs) has to use these weights to transmit data to the ues, we compare practical and realistic strategies that bs can employ in order to maximize downlink capacity. we derive the sinr expression for mmse chip equalizer receivers for the general case of mu-txaa which is used at the receivers to select optimum feedback weights. we investigate different multiuser schemes for hsdpa in the downlink (dl), compare their performance and suggest optimal strategies for single and dual stream transmission for both single and multi-antenna receivers and corroborate our arguments with simulation results. we show that for the case of single antenna receivers, scheduling users with same beamforming weights maximizes downlink capacity in txaa. for the d-txaa with multiple antennas at receivers (mimo) we show that sdma outperforms spatial multiplexing in terms of maximizing dl capacity.
a simple near-capacity bandwidth-efficient coded modulation scheme in rayleigh fading. this paper proposes a near-capacity yet simple bit-interleaved coded modulation with iterative decoding (bicm-id) scheme by employing a multi-dimensional (multi-d) mapping technique in a multi-d constellation carved from a rotated lattice. using extrinsic information transfer (exit) charts, it is shown that the proposed technique fits well with simple convolutional codes in terms of the area property, for which turbo pinch-off can happen at a low eb/no value. in particular, both exit chart analysis and simulation results indicate that by using just a simple convolutional code together with a 4-d mapping, a turbo pinch-off and a bit error rate (ber) close to 10-6 happen at a signal-to-noise ratio (snr) that is even lower than the bicm constraint capacity limit with a uniform input. the proposed bicm-id scheme can be considered as an attractive alternative to other bandwidth-efficient coded modulation techniques using powerful turbo-like codes such as turbo or low-density parity-check (ldpc) codes over a rayleigh fading channel.
multi-user joint subchannel and power resource-allocation for powerline relay networks. this paper investigates orthogonal frequency-division multiple-access (ofdma) resource-allocation schemes for two-hop relays in a home powerline communication (plc) network. unlike wireless channels, which can have noticeable path loss and shadow effects to bring a substantial relay gain, the powerline channel usually observes a quality of the relay channel on par with the direct link so that simple fixed relay configurations often lose performance instead of gaining any. besides, the quasi-cyclostationary powerline channel benefits little from diversity combining, a scheme often found in cooperative wireless relay protocols to obtain performance improvements on fast fading channels. to address these special and challenging features of the powerline channel, home-plc relay protocols that jointly allocate subchannels and power to the source and relay nodes are proposed. simulation results show that significant improvements of data rates can be achieved by jointly optimizing the subchannel and power allocation of home-plc relay networks.
achieving and maintaining cost-optimal operation of a hierarchical dht system. although hierarchical p2p systems have been found to outperform flat systems in many respects, current p2p research does not focus on strategies to build and maintain such systems. available solutions assume either no or little coordination between peers, that could lead the system toward satisfying a globally defined goal (e.g., minimizing traffic). in this paper we focus on hierarchical dhts and provide a full set of algorithms to build and maintain such systems, that mitigate this problem. in particular, given the goal state of minimizing the total traffic without overloading any peer, our algorithms dynamically adjust the system state as to keep the goal met at any time. the algorithms are fully decentralized and probabilistic, all decisions taken by the peers are based on their partial view on a set of system wide parameters. thus, they demonstrate the main principle of self-organization - the system behavior emerges from local interactions. our simulations, run in a range of realistic settings, confirm a good performance of the algorithms.
simulation of spit filtering: quantitative evaluation of parameter tuning. a future where internet telephony will constitute a target valuable to attack is not so unrealistic. e-mail spam botnets software can be updated to send voice spam (commonly referred to as spit, spam over internet telephony) constituting a huge threat to voip-based applications and business. this paper tries to learn from one of the biggest lessons learnt from the e-mail world, i.e. "do not wait until is too late", and proposes a quantitative study, based on a simulation campaign, of spit filtering based on the analysis of the call setup protocols. after discussing attack scenarios based on dichotomic choices by the attacker, it presents how the spit filtering system can be optimized in order to self-tune parameters achieving high spit detection ratio and low false rates at the same time.
joint transmission with significant csi in the downlink of distributed antenna systems. interference management is required for improving the performance of future mobile radio communication systems. in the downlink (dl) of cellular systems with base stations (bss) located in the cell centers and equipped with omnidirectional antennas, transmission strategies such as matched filtering (mf) can't achieve good system performance, and zero forcing (zf) with full channel state information (csi) of the whole system imposes a high computational cost and requires a substantial amount of feedback. in this paper, an intelligent signal processing technique with moderate complexity, i.e., zf joint transmission (jt) with significant csi, based on distributed antenna systems (dass) with bss located at three vertices of each cell and equipped with sector antennas is proposed. from numerical results, it is shown that our proposal is a good combination of bs antenna layout and signal processing technique for interference management. the proposed intelligent signal processing technique can significantly benefit from the proposed smart bs antenna layout.
linear precoding for multiuser mimo systems with multiple base stations. linear precoding for multiuser multiple input multiple output (mimo) cellular systems has generally focused on a single isolated cell. a crucial tool in algorithm development has been a downlink/uplink duality. here we investigate downlink multiuser communications across multiple cells. previous work identified the resulting asynchronous interference as a key issue. we prove the existence of a downlink/uplink duality requiring time reversal. this duality is used to develop an effective linear precoding algorithm for multiuser, multi-cell, mimo systems. simulation results illustrate the importance of accounting for, and to quantify the loss due to, asynchronous interference.
two-tx precoding codebooks for variable spatial correlation. we design precoding codebooks for the situation when the spatial correlation is not known at the transmitter, but its distribution is. the optimum codebooks combine features of grassmannian precoding, optimum in the limit of spatially i.i.d. channels, and equatorial precoding, where all antennas transmit the same power. parametrizable families of codebooks interpolating between these two are considered. the optimum choice of parameter depends on the distribution of spatial correlations. in the case of two transmit antennas, the interpolation is between sphere packings in 2d and sphere packings in 1d, and the codebooks can be understood as the vertices of deformed platonic solids.
a novel relay placement mechanism for capacity enhancement in ieee 802.16j wimax networks. the ieee 802.16j draft proposes a multi-hop relay network architecture that introduces the new network element of relay station aimed at increasing the network throughput or coverage. the deployment of the relay stations is one of the most important issues that determines the network throughput. given a base station, k relay stations, and a deployed region that can be fully covered by the bs, this paper proposes a relay deployment mechanism that determines the deployed locations of rss so that the bandwidth requirement of mss can be satisfied while the network throughput can be significantly improved. experimental study reveals that the proposed mechanism can efficiently determine the locations for relay deployment and improve the network throughput.
bidirectional packet aggregation and coding for voip transmission in wireless multi-hop networks. this paper proposes bidirectional packet aggregation and coding (bipac), a packet mixing technique which jointly applies packet aggregation and network coding in order to increase the number of supportable voip sessions in wireless multi-hop networks. bipac applies network coding for aggregated voip packets by exploiting bidirectional nature of voip sessions, and largely reduces the required protocol overhead for transmitting short voip packets. we design bipac and related protocols so that the operations of aggregation and coding are well-integrated while satisfying the required quality of service by voip transmission, such as delay and packet loss rate. our computer simulation results show that bipac can increase the number of supportable voip sessions maximum by around 70% as compared with the case when the packet aggregation alone is used, and 450% in comparison to the transmission without aggregation/coding. we also implement bipac in a wireless testbed, and run experiments in an actual indoor environment. our experimental results show that bipac is a practical and efficient forwarding method, which can be implemented into the current mesh hardware and network stack.
mapping techniques for uwb positioning. this paper deals with a wireless indoor positioning problem in which the location of a tag is estimated from range measurements taken by fixed beacons. the measurements may be affected by non-line-of-sight (nlos) errors that must be mitigated. we discuss a maximum likelihood (ml) positioning technique that assumes a realistic model for the range errors and a signature database providing information on the propagation conditions at every hypothesized tag spot. the database can be gathered from knowledge of the service area infrastructure and through pre-measurements. it is given in the form of a map indicating, at any node of a close-mesh grid, the nature (los/nlos) of the link between that node and each beacon. the performance of the positioning algorithm is assessed by simulation and is compared with other methods available in literature. the results show that the proposed technique provides significant improvements and is robust against mismatches between true and assumed values of the parameters in the range error model. comparisons with the cramer-rao bound are made.
robust multiplicative audio and speech watermarking using statistical modeling. in this paper, a semi-blind multiplicative watermarking approach for audio and speech signals has been presented. at the receiver end, the optimal maximum likelihood (ml) detector aided by the channel side information for gaussian and laplacian signals in noisy environment is designed and implemented. the performance of the proposed scheme is analytically calculated and verified by simulation. then, we adapt the proposed scheme to speech and audio signals. to improve robustness, the algorithm is applied to low frequency components of the host signal. besides, the power of the watermark is controlled elegantly to have inaudibility using perceptual evaluation of audio quality (peaq) and perceptual evaluation of speech quality (pesq) algorithms. experimental results over several audio and speech signals show the higher robustness of the proposed technique in comparison with a recent watermarking scheme.
using gmm and svm-based techniques for the classification of ssh-encrypted traffic. when employing cryptographic tunnels such as the ones provided by secure shell (ssh) to protect their privacy on the internet, users expect two forms of protection. first, they aim at preserving the privacy of their data. second, they expect that their behavior, e.g., the type of applications they use, also remains private. in this paper we report on two statistical traffic analysis techniques that can be used to break the second type of protection when applied to ssh tunnels, at least under some restricting hypothesis. experimental results show how current implementations of ssh can be susceptible to this type of analysis, and illustrate the effectiveness of our two classifiers both in terms of their capabilities in analyzing encrypted traffic and in terms of their relative computational complexity.
improved estimation of clock offset in sensor networks. clock synchronization is an important issue for the design of a network composed of small sensor nodes. based on the two-way timing message exchange mechanism and assuming an exponential network delay distribution, many analytical results have been presented in the literature by applying the techniques from statistical signal processing. this paper derives the minimum variance unbiased estimator for the clock offset for both symmetric and asymmetric exponential delay cases. for the asymmetric delays, it is shown to be a function of both the minimum and the mean link delays. this result is a very significant contribution since only the minimum link delay observations have been used to estimate the clock offset in the past. for the symmetric case, it is shown to coincide with the maximum likelihood estimator. in addition, the result is also applicable to clock synchronization problem in general computer networks.
starburst ssd: an efficient protocol for selective dissemination. we present starburst, a routing-based protocol designed to efficiently disseminate data items to small subsets within a sensor network. starburst constructs a routing hierarchy to enable fast, efficient and reliable dissemination to nodes in a sensor network that satisfy data-specific predicates. the protocol is based on the idea that when only a few nodes need an update, it is more efficient and much faster to route to those nodes directly. when every node needs an update, algorithms such as trickle are more efficient. starburst therefore dynamically determines what portion of nodes need an update and locally adapts its delivery policy accordingly. we also present dynamic beacon selection algorithms which enable scalability and fault tolerance in starburst. we have implemented and evaluated starburst on top of both the bvr and s4 routing protocols with promising results. our simulations show that starburst reduces both the transmission cost and latency of existing dissemination protocols by at least 50% for small subsets of nodes, and performs no worse than them for larger sets. finally, tests on the motelab testbed validate our simulation results.
on concurrent multipath transfer in sctp-based handover scenarios. handling mobility at the transport layer is a promising approach to achieve seamless handover in the context of heterogeneous wireless access networks. in particular, features such as multihoming and dynamic address reconfiguration provided by mobile sctp (msctp) protocol are among the key enablers for handover support at the transport layer. this paper investigates the applicability of concurrent multipath transfer (cmt) to distribute data among two end-to-end paths of an msctp association during the handover transition process. to that end, the principles of the msctp-cmt design are given, emphasizing the consequences of a sender-introduced reordering and its effect on congestion control. the proposed msctpcmt handover scheme is benchmarked with two other handover schemes, namely msctp and sctp failover-based. provided analysis indicates the possible application area of msctp-cmt, taking into account not only handover scenario parameters (dwelling time, available bandwidth ratio and round-trip time), but also an important design constraint: receiver buffer (rbuf) size. rbuf size proves to be a major limiting factor shrinking significantly, yet not excluding msctp-cmt's application scope.
design and evaluation of a multilevel decoder for satellite communications. in this paper, we propose a multilevel coding (mlc) scheme suitable for satellite communications, where different qos levels are required. we introduce a novel characterization of schemes based on mutual information, called multi-stage decoder (msd) charts, to aid in the design and evaluation of multilevel coding systems. this characterization method finds the optimal set of code rates for the mlc scheme for a set of required snr operation points. on the other hand, fixing the code rates to find out the operation points of snr is also possible. performance of common mapping strategies used in mlc schemes, as block labeling and ungerböck labeling, are evaluated using msd charts. an established transmission scheme for satellite broadcasting, european satellite digital radio (esdr) standard, is compared with the proposed mlc scheme, showing that the mlc scheme is able to work in lower snr regions and provides more flexibility in designing the levels.
adaptive intra-symbol smse waveform design amidst coexistent primary users. an analytic approach is presented for optimizing spectrally modulated, spectrally encoded (smse) waveforms using independent selection of intra-symbol (within a symbol) subcarrier power and modulation order. the smse framework is well-suited for cognition-based, software defined radio (sdr) applications. by exploiting statistical knowledge about the spectral and temporal behavior of interfering signals, the inherent smse framework flexibility is leveraged to substantially increase system throughput while limiting coexistent interference. results for a coexistent scenario are provided in which the analytic optimization of the smse waveform is demonstrated in the presence of multiple direct sequence spread spectrum (dsss) signals. the results reveal significant performance benefits that demonstrate the potential of the smse framework to dynamically adapt to changing environmental conditions-key functionality required for future sdr implementations.
2nd order cyclostationarity of ofdm signals: impact of pilot tones and cyclic prefix. this paper deals with 2nd order cyclostationarity of orthogonal frequency division multiplex (ofdm) signals. a new generalized formula for the spectral correlation density (scd) function is derived. compared to related work in the literature, our derivation is not restricted to the case that all sub-carriers of an ofdm signal carry statistically independent data. the reason for that is that correlated data in terms of pilot tones are typically introduced on different carriers for channel estimation and synchronization purposes. the new formula allows us to analyze the impact of such pilot tones on the scd. in addition, it gives extra information about the impact of the cyclic prefix.
on the efficiency of dynamic routing of connections with known duration. in this paper we devise an highly-efficient load balancing algorithm, called lb-hta, for the dynamic provisioning of connections with known duration in wdm networks. we introduce a time-dependent link-weight assignment that captures future congestion of links, leveraging the knowledge of connection durations. by means of an extensive set of simulative experiments, we compare our approach to other traditional, yet holding-time agnostic, dynamic routing algorithms. for a typical us nationwide network, lb-hta obtains significant saving in blocking probability for practical scenarios. moreover, we address two key-questions regarding holding-time-aware dynamic routing. three main traffic models are considered here, namely i) dynamic traffic, ii) dynamic traffic with known durations and iii) scheduled traffic: how much the knowledge of connection durations improves the performance with respect of a holding-time- agnostic solution? is the obtained solution close to the most effective solution provided by scheduled traffic? in order to exhaustively evaluate the performance of lb-hta, we consider as benchmark the solution obtained under the well-known scheduled traffic model (ti-st) and also under an approximated, but more effective, approach for traffic scheduling, called time-variant scheduled traffic (tv-st). for both ti-st and tv-st, integer linear program (ilp) formulations are proposed and results compared with dynamic routing algorithms.
non-coherent receiver with fractional sampling for impulsive uwb systems. we propose a low complexity noncoherent receiver operating at twice the symbol-rate for systems where each data symbol consists of multiple frames/chips. the receiver does not require explicit timing and channel estimation. it implements simple delayed-autocorrelation, followed by sampling at twice the symbol-rate. simulation results show the receiver achieves performance close to a conventional one with perfect timing.
robust cyclic space-frequency filtering for bicm-ofdm with outdated csit. in this paper, we introduce robust cyclic space-frequency (csf) filtering for systems combining bit-interleaved coded modulation (bicm) and orthogonal frequency division multiplexing (ofdm). the proposed robust csf filtering scheme exploits outdated channel state information at the transmitter (csit) and takes into account the reliability of the csit via a bayesian model. based on an upper bound on the worst-case pairwise error probability we formulate the optimization problem for the robust csf filters which can be solved exactly for certain special cases. for the general case, we obtain an approximate solution by solving a related problem with additional constraints. this approximate solution can be further improved with a gradient algorithm for the original problem. simulation results confirm the excellent performance of bicm-ofdm with robust csf filtering.
an economic model for pricing tiered network services. we consider networks offering tiered services and corresponding price structures, a model that has become prevalent in practice.we develop an economic model for such networks and make contributions in two important areas. first, we formulate the problem of selecting the service tiers and present an approximate yet accurate and efficient solution approach for tackling this nonlinear programming problem. given the set of (near-) optimal service tiers, we then employ game-theoretic techniques to find an optimal price for each service tier that strikes a balance between the conflicting objectives of users and service provider. this work provides a theoretical framework for reasoning about and pricing internet tiered services. our results also indicate that tiering solutions currently adopted by isps do not perform well.
capacity evaluation of a land mobile satellite system utilizing multiple element antennas. land mobile satellite (lms) systems can exploit multiple-input-multiple-output (mimo) techniques in order to achieve high transmission rates. this paper evaluates theoretically the capacity of single-input-multiple-output (simo) system utilizing uniform linear arrays at the receiver terminal for satellite applications. the theoretical study is performed at three different frequency bands. sufficient capacities are achieved varying between 5 and 6.2 b/s/hz at l and s bands being almost independent from the elevation angle. in ku band the capacity is highly variable with the elevation angle, taking values between 2 and 5.9 b/s/hz, whereas the maximum capacity values are observed in a blocked environment. at l and s bands the capacity is uncorrelated with distance for element spacing up to 1.5 cm and varies between 5.5 and 6 b/s/hz. in ku band the capacity is highly variable with the element spacing and maximizes for distances between 1 and 1.5 cm.
discernibility analysis and accuracy improvement of machine learning algorithms for network intrusion detection. network intrusion detection based on machine learning algorithms has demonstrated high performance in execution time and overall classification accuracy. however, very poor identification skill is showed for certain specific attack types, especially for the unknown attack types appeared in the test data only. we use the parallel coordinates plot (pcp), one kind of visualization technique for multi-dimension data analysis, to comparatively analyze the data distribution characteristic for both training and test datasets. on the other hand, we make use of rough sets theory to investigate the discernibility in respect of whole training dataset, randomly sampled dataset and reduct attributes set. furthermore, based on the higher classification accuracy for data with unknown attack types by using rough sets method, the decision rules extracted from both c4.5 and rough sets method are combined to improve the detection capability of classification model.
bit-interleaved coded modulation for hybrid rf/fso systems. in this paper, we propose a novel architecture for hybrid radio frequency (rf)/free-space optics (fso) wireless systems. in particular, we show that a hybrid system robust to all weather conditions is obtained by joint bit-interleaved coded modulation (bicm) of the bit steams transmitted over the rf and fso sub-channels. an asymptotic performance analysis reveals that a properly designed convolutional code can exploit the diversity offered by the independent sub-channels. furthermore, we develop a code design criterion and provide an efficient code search procedure. simulation results show that hybrid rf/fso systems with bicm outperform previously proposed hybrid systems employing a simple repetition code and selection diversity.
performance evaluation of optical ofdm systems with nonlinear clipping distortion. this paper investigates the effects of nonlinear biasing and clipping (bac) on a random optical orthogonal frequency-division multiplexing (ofdm) signal with direct detection. we look at the problem of theoretical performance evaluation of such a system. specifically, we derive an approximation for the symbol error rate (ser). the nonlinear bac process is modeled as a linear deterministic gain plus a random additive clipping noise. the total effective snr is presented as a function of biasing power, modulation constellation and receiver snr. analytical results are in good agreement with simulations in various cases.
sub-noise primary user detection by cross-correlation. an ideal cognitive radio must be able to detect primary user signals under unfavorable conditions. especially when the hidden node problem occurs, a cognitive radio is required to detect the presence of signals under the noise floor. this paper addresses the question to what extent sub-noise detection is practically usable in a cognitive radio. three methods based on cross-correlation are analyzed and compared.
low complexity markov chain monte carlo detector for channels with intersymbol interference. in this paper, we propose a novel low complexity soft-in soft-out (siso) equalizer using the markov chain monte carlo (mcmc) technique. direct application of mcmc to siso equalization (reported in a previous work) results in a sequential processing algorithm that leads to a long processing delay in the communication link. using the tool of factor graph, we propose a novel parallel processing algorithm that reduces the processing delay by orders of magnitude. numerical results show that, both the sequential and parallel processing siso equalizers perform similarly well and achieve a performance that is only slightly worse than the optimum siso equalizer. the optimum siso equalizer, on the other hand, has a complexity that grows exponentially with the size of the memory of the channel, while the complexity of the proposed siso equalizers grows linearly.
multiple-ring based modeling and simulation of wideband space-time-frequency mimo channels. in this paper, based on the concept of the tapped delay line (tdl) structure, we first propose a new wideband multiple-ring multiple input multiple output (mimo) channel reference model for macro-cell scenarios. it is shown that the proposed model can easily match any given or measured power delay profile (pdp) and has the ability to jointly consider the angle of arrival (aoa), angle of departure (aod), and time of arrival (toa). from the proposed model, we derive the closed-form expression of the 3-dimensional (3-d) space-time-frequency (stf) correlation function (cf) for each tap, considering the interaction of the temporal, spatial, and frequency correlations. finally, based on the proposed reference model, a deterministic simulation model is then proposed.
green dsl: energy-efficient dsm. dynamic spectrum management (dsm) has been recognized as a key technology for tackling multi-user crosstalk interference for dsl broadband access. up to now, dsm design has mainly been focusing on maximization of data rates. however, recently, reducing the total power has become a main target, as it power consumption has been identified as a significant contributor to global warming. in this paper we extend traditional dsm design towards a much wider energy-efficient scope and show how to tackle the corresponding optimization problems. the impact of this 'green dsl' approach is evaluated for practice with some surprisingly good numerical results. furthermore bounds are provided on the trade-off between data rate performance and power saving.
carrier-sense arq: squeezing out bluetooth performance while preserving standard compliancy. in this paper, we propose a simple and standard compliant retransmission mechanism, called carrier-sense automatic repeat request (cs-arq), which aims at improving system performance, both in terms of throughput and energy efficiency, by avoiding useless data packet retransmissions. more specifically, in case of missed acknowledgment (ack), the source makes use of its carrier-sensing capabilities to decide whether retransmitting the data packet or soliciting the ack retransmission from the destination. the scheme is modeled by means of a two-state markov chain that permits to determine closed-form expressions for the throughput and energy efficiency figures. the analysis reveals that the cs-arq mechanism is actually capable of significantly enhancing the system performance, in particular in some critical scenarios, while preserving standard compliancy.
adaptive puncturing for coded ofdma systems. a scheme is proposed for adaptively changing the code rate of coded ofdma systems via changing the puncturing rate within a single codeword (scw). in the proposed structure, the data is encoded with the lowest available code rate then it is divided among different resource blocks (tiles) where it is punctured adaptively based on some measure of the channel quality for each tile. the proposed scheme is compared against using multiple codewords (mcws) where the transmitter divides the data over tiles and encodes them separately. we investigate two different adaptive modulation and coding (amc) selection methods. the first is a recursive scheme that operates directly on the snr whereas the second operates on the effective snr value that is obtained using mutual information effective snr mapping (miesm). we then compare our scheme to per-frame adaptation (pfa) where we fix the modulation and coding scheme (mcs) over a given frame. we show via simulations that when using the recursive rate selection method the scw scheme significantly outperforms the mcws and the pfa. it is also shown that applying the miesm rate selection method, the pfa improves significantly, yet the scw scheme is the best performer. we also introduce a novel interleaving method prior to puncturing that improves the performance for certain restricted adaptation mechanisms.
end-host authentication and authorization for middleboxes based on a cryptographic namespace. today, middleboxes such as firewalls and network address translators have advanced beyond simple packet forwarding and address mapping. they also inspect and filter traffic, detect network intrusion, control access to network resources, and enforce different levels of quality of service. the cornerstones for these security-related network services are end-host authentication and authorization. using a cryptographic namespace for end-hosts simplifies these tasks since it gives them an explicit and verifiable identity. the host identity protocol (hip) is a key-exchange protocol that introduces such a cryptographic namespace for secure end-to-end communication. although hip was designed with middleboxes in mind, these cannot securely use its namespace because the on-path identity verification is susceptible to replay attacks. moreover, the binding between hip as an authentication protocol and ipsec as payload transport is insufficient because on-path middleboxes cannot securely map payload packets to a hip association. in this paper, we propose to prevent replay attacks by allowing packet-forwarding middleboxes to directly interact with end-hosts. also we propose a method for strengthening the binding between the hip authentication process and its payload channel with hash-chain-based authorization tokens for ipsec. our solution allows on-path middleboxes to efficiently leverage cryptographic end-host identities and integrates cleanly into existing standards.
speeding up homomorpic hashing using gpus. homomorphic hash functions (hhfs) have been applied into peer-to-peer networks with erasure coding or network coding to defend against pollution attacks. unfortunately hhfs are computationally expensive for contemporary cpus. this paper proposes to exploit the computing power of graphic processing units (gpus) for homomorphic hashing. specifically, we demonstrate how to use nvidia gpus and the computer unified device architecture (cuda) programming model to achieve 38 times of speedup over the cpu counterpart. we also develop a multi-precision modular arithmetic library on cuda platform, which is not only key to our specific application, but also very useful for a large number of cryptographic applications.
throughput optimization in high speed downlink packet access (hsdpa). in this paper, we investigate throughput optimization in high speed downlink packet access (hsdpa). specifically, we propose offline and online algorithms for adjusting the channel quality indicator (cqi) used by the network to schedule data transmission. in the offline algorithm, a given target bler is achieved by adjusting cqi based on ack/nak history. by sweeping through different target blers, we can find the throughput optimal bler offline. this algorithm could be used not only to optimize throughput but also to enable fair resource allocation among mobile users in hsdpa. in the online algorithm, the cqi offset is adapted using an estimated short term throughput gradient without specifying a target bler. an adaptive stepsize mechanism is proposed to track temporal variation of the environment. we investigate convergence behavior of both algorithms. simulation results show that the proposed offline algorithm can achieve the given target bler with good accuracy. both algorithms yield up to 30% hsdpa throughput improvement over that with 10% target bler.
an evolutionary approach to end-to-end addressing and routing in all-ethernet wide-area networks. while the introduction of new ethernet-based wide-area solutions, such as provider-backbone bridging traffic engineering-pbb-te, paves a way for ethernet to become a carrier class service, it is restricted to the metro area and hence unable to provision global end-to-end communication. in this paper, we propose a new scheme for all-ethernet wide area networking that involves a unique addressing and routing mechanism, and leads to a scalable, hierarchical and service-oriented transport network architecture. the scalability is achieved by means of abstraction of any irregular physical topology into a regular logical topology, based on the concept of binary trees. the regular logical topology is represented with logical 1x2 ethernet switches as the fundamental building blocks which allow switching using a unique binary addresses in a simple and automated fashion. we propose an evolutionary architecture to provide end-to-end ethernet routes using binary addresses embedded in stacked vlan tags on native ethernet frames, in line with the emerging standards. the results show that a significant simplification of wide-area inter-networking can be achieved, while supporting carrier-grade network performance with all-ethernet features.
supporting vcr-like operations in derivative tree-based p2p streaming systems. supporting user interactivity in peer-to-peer streaming systems is challenging. vcr-like operations, such as random seek, pause, fast forward and rewind, require timely p2p overlay topology adjustment and appropriate bandwidth resource re-allocation. if not handled properly, the dynamics caused by user interactivity may severely deteriorate users' perceived video quality, e.g., longer start-up delay, frequent playback freezing, or blackout altogether. in this paper, we propose a derivative tree-based overlay management scheme to support user interactivity in p2p streaming system. derivative tree takes advantage of well organized buffer overlapping to support asynchronous user requests while brings high resilience to the impact of vcr-like operations. a session discovery service is introduced to quickly locate parent peer. we show that the overhead of vcr-like operations in derivative-tree based scheme is o(log(n)), where n is the number of sessions. simulation experiments further demonstrate the efficiency of the proposed scheme.
caching video contents in iptv systems with hierarchical architecture. in this paper we consider iptv systems with an hierarchical architecture. the lowest elements of the architecture are set-top boxes (stbs) at the user homes; a stb is connected to a central office (co) which is in charge of delivering the video content to the end user. since cos have limited storage capabilities, they may need to retrieve a particular video content that is requested by a user but temporary not stored in the local memory. thus, cos exchange video contents with similar cos in a peer-to-peer fashion. at a higher hierarchical level, video source offices (vsos) offer the video contents that cannot be retrieved at the co level. video content caching strategies at the cos and vsos influence the system performance in terms of traffic exchanged between the network nodes. in this paper we propose two simple strategies that aim at reducing both the intra-and inter-level traffic. the strategies are studied by means of an analytical model that is validated against simulation results. our results show that the hierarchical architecture allow good system performance even with limited overall storage capacity. the proposed strategies, in particular, can be helpful in improving system performance.
implementation of a chaotically encrypted wireless communication system. implementing the synchronization of chaotic systems presents new challenges that are difficult to handle by using currently adopted schemes. the paper proposes an implementation of a synchronization method for a pseudo-true random bit generator (ptrbg) based on chaotic systems. synchronization of the chaotic binary sequences is achieved by using the backward iteration approach. the implementation test bed for the complete wireless communication system is based on a chipcon wireless development kit. assessment of the pseudo- true random bits (ptrb) generated is performed using the nist statistical test suite.
adaptive power allocation in two-way amplify-and-forward relay networks. two-way amplify-and-forward relaying is considered in this paper. we propose adaptive power allocation (pa) algorithms to maximize the instantaneous achievable rate and minimize the system outage probability, respectively. both single-and multi-relay systems are considered. it is shown that the proposed adaptive pa algorithms significantly outperform the uniform pa algorithms. furthermore, exploiting multiple relays obtains higher diversity order and lower outage probability than using only one relay, at the price of a lower achievable information rate. the relay locations and relay selection are also taken into account to further improve the system performance.
optimal cross-layer bandwidth adaptation for maximum-throughput vbr media wireless content delivery. emerging media overlay networks for wireless applications aim at delivering variable-bit-rate (vbr) encoded media contents to nomadic end-users by exploiting the (fading-impaired and time-varying) access capacity offered by the "last-hop" wireless channel. in this application scenario, a still open question concerns the design of control policies maximizing the average throughput over the wireless last-hop, under constraints on the maximum connection bandwidth allowed at the application (app) layer, the queue-capacity available at the data-link (dl) layer, and the average and peak transmit energies sustained by the physical (phy) layer. the main feature of the approach we follow relies on the maximization (on a per-slot basis) of the throughput averaged over the fading statistics and conditioned on the queue-state. the resulting optimal controller is rate-based and operates in a cross-layer fashion that involves the app, dl and phy layers of the underlying protocol stack. this means that the proposed controller dynamically allocates connection bandwidth at the app layer, throughput at the dl layer and transmit energy at the phy layer by basing on both current queue and channel states. the carried out numerical tests give insights about the connection bandwidth-vs.-queue delay tradeoff attained by optimal controller.
content clustering based video quality prediction model for mpeg4 video streaming over wireless networks. the aim of this paper is quality prediction for streaming mpeg4 video sequences over wireless networks for all video content types. video content has an impact on video quality under same network conditions. this feature has not been widely explored when developing reference-free video quality prediction model for streaming video over wireless or mobile communications. in this paper, we present a two step approach to video quality prediction. first, video sequences are classified into groups representing different content types using cluster analysis. the classification of contents is based on the temporal (movement) and spatial (edges, brightness) feature extraction. second, based on the content type, video quality (in terms of mean opinion score) is predicted from network level parameter (packet error rate) and application level (i.e. send bitrate, frame rate) parameters using principal component analysis (pca). the performance of the developed model is evaluated with unseen datasets and good prediction accuracy is obtained for all content types. the work can help in the development of reference-free video prediction model and priority control for content delivery networks.
comparative performance evaluation of tcp variants on satellite environments. satellite communications are essential to provide internet access to wide areas, helping bridge the "digital divide". however, long rtts and the possible presence of losses due to satellite channel errors, severely impair standard tcp performance. to overcome this problem several approaches are possible, including the adoption of enhanced versions of tcp. this paper focuses on these, by presenting the results of a comparative performance evaluation carried out in a satellite environment through a linux testbed. the interest of the analysis lies in the wide variety of tcp variants considered and in the different aspects analyzed, such as performance at start-up, level of rtt unfairness and robustness against link losses. the results are analyzed at length in the paper and give interesting indications about the performance achievable on satellite channels by the most promising tcp variants proposed in recent years.
tracing stateful pirate decoders. most traitor tracing schemes in the literature assume that pirate decoders are stateless. this stateless assumption, however, is unrealistic especially in case of hardware decoders. any tracing algorithm based on the above assumption may draw a wrong detecting conclusion. the present approach converts a tracing algorithm for stateless decoder into a tracing algorithm for stateful decoder. by employing a robust watermarking scheme, the proposed approach ensures that tracing processes and normal broadcast processes are indistinguishable for pirate decoders. this in turn allows a tracer to incriminate at least one traitor from a pirate decoder. since the communication overhead for conversion is merely linear to the number of traitors and independent of the number of users, our approach is more efficient than the techniques in [1].
efficient recovery algorithms for wireless mesh networks with cognitive radios. cognitive radios allow unlicensed wireless users to access channels that are in the licensed spectrum bands. however, in a wireless network with cognitive radios, when a licensed user becomes active on a channel in a certain area, nodes and links that were using that channel must release it, which will cause traffic failures. simple and effective recovery schemes are needed to re-allocate available resources for the failed traffic. in this paper, we study the failure recovery in wireless mesh networks with cognitive radios. we formally formulate the corresponding problems as integer linear programming problems. by solving them, we can obtain optimal solutions. moreover, an efficient distributed heuristic algorithm is presented for fast recovery. simulation results show that the performance given by our distributed algorithm is close to that of the optimal solutions.
differential space-time-frequency codes for mb-ofdm uwb with dual carrier modulation. in a multiple-input multiple-output (mimo) multi-band orthogonal frequency division multiplexing (mb-ofdm) ultra-wideband (uwb) system, coherent detection where the channel state information (csi) is assumed to be exactly known at the receiver requires the transmission of a large number of symbols for channel estimation, thus reducing the bandwidth efficiency. this paper examines the use of unitary differential space-time frequency codes (dstfcs) in mb-ofdm uwb, which increases the system bandwidth efficiency due to the fact that no csi is required for differential detection. the proposed dstfc mb-ofdm system would be useful when the transmission of multiple channel estimation symbols is impractical or uneconomical. simulation results show that the application of dstfcs associated with dual carrier modulation (dcm) can significantly improve the bit error performance of conventional differential mb-ofdm system (without mimo), and even provide better bit error performance than the dstfc mb-ofdm system associated with constant envelope modulation schemes.
joint scheduling and relay selection in one- and two-way relay networks with buffering. in most wireless relay networks, the source and relay nodes transmit successively via fixed time division (ftd) and each relay forwards a packet immediately upon receiving. in this paper we enable the buffering capability of relay nodes and propose a framework for joint scheduling and relay selection. the goal is to maximize the system long-term throughput by fully exploiting multi-user diversity in the network. we develop two joint scheduling and relay selection (jsrs) algorithms for unidirectional and bidirectional traffic, respectively. the novel cross-layer relay selection metrics which our algorithms are based upon take into account both instantaneous channel conditions and the queuing status. we also demonstrate that the proposed jsrs can be realized in a distributed way without explicit coordination among the network nodes. extensive simulation is carried out to evaluate the performance of the proposed jsrs with buffering in comparison with traditional ftd without buffering. typical throughput enhancements up to 101% and 110% are observed in one-way and two-way relay networks respectively, at low signal-to-noise ratio (0 db).
performance of cooperative diversity networks: analysis of amplify-and-forward relaying under equal-gain and maximal-ratio combining. by enhancing diversity, cooperation in wireless networks allows increasing the transmission reliability and extending the radio coverage, without the need of implementing multiple antennas at the terminals. in this context, this paper proposes a general approach for analyzing the performance of dual-hop cooperative diversity networks with nonregenerative variable-gain relays. such a strategy allows for the use of both equal-gain combining (egc) and maximal-ratio combining (mrc) techniques at the destination. in our analysis, closed-form approximations for the outage probability (op) and average symbol error rate (ser) of linear modulations are presented. these expressions yield results instantaneously, regardless the number of relays used, in contrast with exact solutions which are rather intricate and difficult to evaluate, especially when the number of relays increases. the inherent simplicity of our methodology makes it attractive to serve as a benchmark in the design and performance evaluation of cooperative networks with variable-gain relays and employing either egc or mrc. numerical results are provided and compared with monte carlo simulations to illustrate the accuracy of the proposed expressions.
netcluster: a clustering-based framework for internet tomography. in this paper, internet data collected via passive measurement are analyzed to obtain localization information on nodes by clustering (i.e., grouping together) nodes that exhibit similar network path properties. since traditional clustering algorithms fail to correctly identify clusters of homogeneous nodes, we propose a novel framework, named "netcluster", suited to analyze internet measurement datasets. we show that the proposed framework correctly analyzes synthetically generated traces. finally, we apply it to real traces collected at the access link of our campus lan and discuss the network characteristics as seen at the vantage point.
multi-point ethernet over next-generation sonet/sdh. advances in sonet/sdh technologies have introduced novel features for improved services mapping and provisioning, enabling many new avenues for new carrier ethernet support. however ethernet-over-sonet studies have mostly focused on provisioning point-to-point ethernet private line offerings. this paper considers the more challenging case of provisioning multi-point-to-multi-point ethernet lan services over advanced sonet/sdh networks and presents novel strategies based upon connection group overlays. detailed simulation results are also presented along with directions for future work.
cooperative precoding and beamforming for co-existing multi-user mimo systems. interference among multiple base stations that co-exist in the same location limits the capacity of wireless networks. in this paper, we propose a nonlinear multi-user mimo cooperative downlink transmission scheme. the algorithm eliminates the interference and achieves symbol error rate (ser) fairness among different users. to eliminate the interference, tomlinson harashima precoding (thp) is used to cancel part of the interference while the transmit-receive antenna weights cancel the remaining part. the uplink-downlink duality principle is used to calculate transmit-receive antenna weights. the proposed scheme is then extended to work when the receiver does not have complete channel state informations (csis). the simulation results show that the proposed schemes considerably outperform existing cooperative transmission schemes in terms of ser performance and approach an interference free performance under the same configuration.
initial synchronization for multi-cell ofdma systems. in this paper, a complete solution to the initial synchronization for multi-cell ofdma (orthogonal frequency division multiple access) systems is proposed. the proposed method consists of the following operations: timing synchronization, fractional carrier frequency offset (cfo) estimation, fractional cfo compensation, and joint integer cfo and preamble index estimation. to estimate multiple fractional cfos with pseudoperiodic preamble, we suggest an over-sampling approach. an ill-condition detection and noise suppression algorithm is also presented. for joint integer cfo and preamble index estimation, we use a differential detection based cross-correlation method. simulation results have shown that the proposed method gives satisfactory performance for a wide snr range even when the mobile station (ms) is on the cell boundaries.
optimal rate allocation for loss sensitive applications in wireless ad hoc networks. some real-time applications (such as video on demand) are sensitive to the perceived packet loss when using the network resources. due to time-varying topological changes in a wireless ad hoc network, it is a challenging issue to provide this stringent qos requirement of real-time applications. each real-time application requires a specific level of packet loss guarantee. as multi-path routing has the potential of reducing the congestion and increasing the throughput of the user traffic in multi-hop wireless networks, it is assumed that multiple paths are available in advance between each source-destination pair. in the current work, using a constrained optimization framework and trying to minimize the packet loss, an optimal rate is allocated to each source-destination path of those subsets of real-time applications which requires minimized packet loss and a lower bound on the delivered bandwidth. simulation results verify the enhanced performance of the proposed method in terms of the packet error rate.
optimum tcm codes design for gaussian channels by considering both euclidean and hamming distances. trellis-coded modulation (tcm) is an attractive coded modulation technique which yields significant coding gain without bandwidth expansion. so far, researches concerning the optimization of tcm codes under gaussian channels have concentrated on minimizing the error-event probability (eep). the criterion is to maximize the free euclidean distance of tcm coded sequences. however, for bitwise communication systems, minimizing the bit error rate (ber) is particularly important. this paper illustrates that the conventional tcm coding criterion is not sufficient in terms of minimizing ber. the reason is that the ber depends on not only euclidean but also hamming distances. we then propose a new criterion for tcm codes design, which considers both euclidean and hamming distances. based on the proposed criterion, a general design method is given. a number of optimum tcm codes are designed by using this method. simulation results verify that, compared with the conventional best-performed tcm codes, our codes not only yield the minimum eep but also achieve better ber performance.
subcarrier allocation for ofdma relay networks with proportional fair constraint. this paper considers subcarrier allocation for the multihop orthogonal frequency division multiple-access (ofdma) broadcast networks consisting of one source, multiple destinations, and one amplify-and-forward (af) relay. in this paper, proportional fair (pf) based subcarrier allocation is discussed to get a tradeoff between the system transmission rate and fairness. first, the problem is formulated as an optimization problem with prohibitive complexity. second, by analyzing the optimal solution for the subcarrier allocation problem without pf constraint, two suboptimal schemes are proposed. the simulation results indicate that with the same fairness performance, the proposed schemes achieve considerable capacity gain compared with the conventional pf scheduling method which is extended simply from the single-hop system.
a spatial learning algorithm for ieee 802.11 networks. the success of dynamic spectrum access through simple listen-before-talk etiquettes has paved the way for opening up the spectrum. however, many problems still remain in these networks. due to the complex nature of ieee 802.11 networks, for instance, optimizing these networks regarding power, rate and carrier sense threshold remains a very tough challenge. in this paper, we introduce spatial learning. this new optimization algorithm for ieee 802.11 networks employs learning to find an optimal combination of power, rate and carrier sense threshold. it is assumed that nodes behave selfishly and are only interested in optimizing their own throughput. extensive network simulations show that spatial learning performs better than the state-of-the-art solution, spatial backoff, on all axes of interest: network-wide throughput, fairness and power consumption.
feature analysis of mouse dynamics in identity authentication and monitoring. mouse dynamics has recently become an interesting new topic in the area of behavioral biometrics due to its non-intrusiveness and convenience. some promising results have been shown by previous researches on identity authentication and monitoring using characteristics in users' mouse actions. this paper explores mouse dynamics further by focusing on an important issue not addressed previously: behavioral variability. with an empirical study of long term behaviors of 10 computer users, we show variations are obvious in mouse activities and can have a serious impact if not considered carefully. to tackle the problem of variability, we propose a dimensionality reduction based approach which is demonstrated to be effective in our experiments. more specifically, the classification results after preprocessing by pca and isomap are shown to be much better than direct classification. moreover, the results of a false acceptance rate (far) 0.55% and false rejection rate (frr) 3.00% by the nonlinear method isomap are comparable to the best result reported in literature while being subject to more behavioral variability.
practical packet pacing in small-buffer networks. the demand for more bandwidth has lead to proposals for an all-optical network core. due to inherent constraints of optical technology, only routers with small packet buffers are feasible to be implemented. in order to ensure efficient operation of such small-buffer networks, it is necessary to ensure that traffic is less bursty than in conventional networks. we propose a novel packet pacing mechanism that can smooth traffic bursts. our theoretical analysis shows that our pacing scheme can guarantee that queue length of routers is bibo stable. experimental results from our prototype implementation show the effectiveness of our pacer on in terms of reduced network congestion and improving network throughput.
downlink power distribution in a wireless cdma network with cooperative relaying. this paper studies power distribution in the downlink of a wireless cdma network, where mobile stations (mss) cooperatively relay traffic for their peer stations, and the destination station (ds) combines signals received from both the base station (bs) and the relay station (rs). both the ds and the rss transmit at the same frequency band. we consider both decode-and-forward (df) and amplify-and-forward (af). an optimization problem is first formulated for distributing the transmission power of the bs and the rss. the objective is to minimize the transmission power of the bs and the total transmission power of the rss, subject to the average transmission rate and signal-to-interference-plus-noise ratio (sinr) requirement of the user traffic. the optimum power distribution requires link gains among different mss, which are usually not available at the bs. we then propose a practical power distribution scheme based on link gains of the rs and ds to the bs. our results show that i) the proposed link-gain based power distribution scheme achieves close-to-optimum performance, ii) by appropriately selecting the rs and forwarding techniques, cooperative relaying in the downlink of a cdma network can reduce the communication outage probability and significantly save the bs transmission power in the downlink transmissions, and iii) cooperatively relaying requires very low transmission power from the rss.
a modular reference application for ieee 802.11n wireless lan macs. designing efficient yet flexible medium access controllers (mac) for wireless protocols is a challenge. not only are these protocols still evolving, they are also increasingly demanding in terms of throughput and real-time requirements. in order to support a careful application-driven architecture development, reference applications are required that expose the full system and enable the quantitative evaluation of performance-flexibility tradeoffs. for this purpose, we have captured the 802.11n mac protocol in an executable reference application which comprises the system function and its environment including traffic scenarios. we model the reference in click, a packet processing framework. the functionally-correct model captures performance-relevant aspects such as the wireless protocol timing exactly. leveraging extensions to click we can use the model for the development and deployment of embedded architectures. our 802.11n mac model comprises between 118 and 1238 functional elements and can be simulated in real time depending on the scenario. due to ts modularity, additional scenarios can be added productively.
application of phase shift in coherent multi-relay mimo communications. in this paper we propose a new low feedback and low complexity scheme that adjusts the phases at the relays, thus allowing for the coherent combining of signals from multiple relays in a cooperative multi-input-multi-output (mimo) system using space division multiple access (sdma). it is assumed that the channel state information (csi) is not fed back to the source and the relays and the case of imperfect csi at the destination is also taken into consideration. in determining the parameters, conventional convex optimization schemes cannot be applied due to the non-convex nature of the function. a low complexity method is used to optimize the system that utilizes bisection search. numerical calculations and ber simulations demonstrate a significant performance gain over conventional af.
a k-best version of the turbo-lord mimo detector in realistic settings. in this paper we introduce an improved version of the turbo layered orthogonal lattice detector (t-lord), recently presented. this implementation, namely k-best t-lord, misses the performance of the turbo map detector by only few tenths of db in various configurations, like the fully enhanced t-lord. however, its complexity is quadratic in the number of transmitting antennas instead of exponential. moreover, we show that the k-best t-lord is robust also over realistic channels, with correlation between tones and antennas, and with imperfect channel state information at the receiver. this behavior is shown not only via monte carlo simulations, but also with exit chart analysis.
coding-aware scheduling for reliable many-to-one flows. we revisit the problem of scheduling the sources transmissions in a many-to-one flow to provide reliable communication between n sources and a single destination. the performance of coding-aware scheduling is studied based on both digital network coding (dnc) and analog network coding (anc). we discuss some special cases in which an optimal anc-based schedule can be constructed efficiently. finally, we show that the maximum gain from using anc is theoretically bounded by n, where n is the number of sources.
hybrid resource allocation in wireless ad hoc networks. inefficient resource management may cause problems of reliability of service in shared medium wireless networks. resources include bandwidth, processor cycles and buffers. excessive competition for these resources can cause severe packet collision rates, compound network congestion, or even result in starvation of some nodes. in such a situation, data transmission is subject to very long delays and significant packet losses. although transport layer protocols can help improve end-to-end performance, these approaches are slow in responding to network changes and incur additional overhead. this paper aims to reduce transmission delay and increase packet delivery ratio. a hybrid resource allocation problem is formulated by the primal algorithm and a controller is derived to decrease congestion globally and to reduce collisions locally. our simulation results show that this hybrid controller can achieve packet loss rates close to 1% and significantly shorten end-to-end delay even in a high interference environment with heavy system load. in addition, we also compare the performance of the hybrid controller with the impact of multipath routing. the accuracy of our simulation is improved by adding a probabilistic preamble detection model and sinr collision model based on frame error rate.
a recursive distributed topology discovery service for network-aware grid clients. distributed application (e.g., grid-enabled application) performance is highly dependent on the information available when computational resources are chosen. a resource selection based on computational resource information complemented with network performance information has the potential to be optimal from the application performance viewpoint. this is particularly true for network-intensive distributed applications. this study proposes a recursive distributed topology discovery service (rd-tds) that allows grid clients to retrieve network performance information (i.e., ip-level topology and link capacity) without the need of specific administrative privileges. the rd-tds exploits a selected set of distributed beacons (i.e., measurement points) that recursively probe newly discovered nodes until no undiscovered nodes are found during an exploration step. the rd-tds simulative and experimental evaluation confirms its expected qualities: a rapid and complete discovery of the network performance information with the utilization of a limited number of active beacons. in addition, the proposed method rationale can be easily applied to many current network exploration tools.
adaptive compress-and-forward relaying in fading environments with or without wyner-ziv coding. compress-and-forward is a protocol for transmission over relay networks in which the relay forwards a compressed version of the signal it observes. the compression method used by the relay is source coding with side information, i.e. wyner-ziv coding, since the destination can use the signal it receives directly from the source as side information. this paper addresses the case of a wireless relay network with orthogonal transmissions from the source and the relay terminals; we show that when the transmitters have no instantaneous channel state information the optimal compression parameters often make wyner-ziv coding reduce to conventional source compression, i.e. compression that does not take into account the side information available at the destination. this result simplifies the implementation of the cf protocol in the case we consider, since it shows that in several situations one can use more convenient compression methods without significant performance loss.
four-antenna based structure for cellular networks with frequency reuse factor of one. in this paper, a new four-antenna based structure (fas) is introduced for capacity improvement in future cellular networks with frequency reuse factor of 1. in fas, each cell consists of one omni-directional antenna located at the cell center and three 120-degree directional antennas located at the cell edge. in order to achieve effective system bandwidth allocation among four antennas, novel spectrum planning schemes for both downlink (dl) and uplink (ul) are proposed. theoretical analysis and simulation demonstrate that the proposed cellular structure can significantly improve the system capacity in both dl and ul, especially at the cell edge.
resource allocation in an lte cellular communication system. the problem of allocating resources for user transmissions on the downlink of a long term evolution (lte) cellular communication system is studied. a novel optimal multiuser scheduler is proposed and its performance is evaluated. numerical results show that the system performance improves with increasing correlation among ofdma sub-carriers. it is found that a limited amount of feedback information can provide a relatively good performance. a sub-optimal scheduler with a lower computational complexity is also proposed, and shown to provide good performance. the sub-optimal scheme is especially attractive when the number of users is large, as the complexity of the optimal scheme may be unacceptably high in many practical situations.
a fuzzy logic based scheme to detect adaptive cheaters in wireless lan. the most commonly used medium access mechanism in wlan is based on the csma/ca protocol. this protocol schedules properly the access to the medium among all competing nodes. however, in a hostile environment, such as wireless local area networks (wlans), selfish or greedy behaving nodes may prefer to decline the proper use of the protocol's rules in order to increase their bandwidth shares at the expense of well behaving nodes. in this paper, we focus on one such misbehavior and in particular on the adaptive greedy misbehavior of a node in the context of wireless local area network environment. in such environment, wireless nodes compete to gain access to the medium and communicate directly with an access point (ap). in this case, a greedy node may violate the common rules in order to earn extra bandwidth upon its neighbors. in order to avoid its detection, this node may adopt intelligently different techniques and switch dynamically between each of them. to counter such a misbehavior, we propose the use of a fuzzy logic technique in a new detection scheme. this scheme, implemented in the access point, monitors the behavior of associated wireless nodes and reports any deviation from the proper use of the csma/ca protocol. the simulation results of the proposed scheme show its robustness and ability to detect and identify quickly most of the deviations of an adaptive cheater.
low-complexity equalization based on least squares support vector classifiers for ds-uwb systems. we propose the least squares support vector classifier (ls-svc) based equalization schemes for direct sequence ultra wideband (ds-uwb) systems, where a bank of independent ls-svcs are employed to detect each block of signals. the ls-svc based equalizers provide a close bit error rate (ber) performance in the line-of-sight (los) scenario to the case with additive white gaussian noise (awgn). simulation results show that the ls-svc based equalizers have almost identical ber performance to that of typical support vector classifiers (svcs) with a reduced training complexity. furthermore, the sparse lssvcs are employed to reduce the detection complexity, with little performance loss compared to ls-svcs.
managing distributed feature interactions in enterprise sip application servers. several trends in sip application server deployments in large scale telephony environments exacerbate the classic problem of feature interaction : use of distributed feature servers, mixing of legacy and green-field feature servers, and the co-existence of multiple third-party feature implementations provisioned in the same environment. next-generation sip application servers will include an application router (ar) to provide more application control over feature sequencing. as we discuss here, the ar can be augmented to incorporate feature interaction detection and resolution logic. we describe a novel design for run-time feature interaction detection and resolution in an environment of distributed feature servers using a sip application server with application routing function, such as that defined in jsr 289. the approach is based on the algorithm of the kolberg-magill (k-m) method for feature interaction detection. here we extend the notation of the algorithm to cover advanced call control services, enable the algorithm to work in topologies involving b2buas (back-to-back user agents) and sbcs (session border controllers), and test the approach with a substantial feature set of 32 features found in large enterprise solutions.
on opportunistic beamforming in fast fading scenarios. we comment on the famous work «opportunistic beamforming using dumb antennas» by p. viswanath, d.n.c. tse, and r. laroia, from 2002. in that paper, it is argued that in an independent and fast fading environment, the opportunistic beamforming technique provides no performance gain. this assessment is based on the argument that the fading distribution of the equivalent channel, which is obtained through opportunistic beamforming, does not depend on the number of transmit antennas in independent and fast fading scenarios. in this paper, we show that this argument of the original work is based on a non-physical model of rayleigh fading, and as a consequence, results in a wrong conclusion. in contrast, we show that there is beamforming gain to be obtained by the opportunistic beamforming technique even for independent and fast fading environments. for the case of uncoupled antennas, the amount of obtainable beamforming gain approaches-with probability one-the number of transmit antennas from below as the number of users approaches infinity.
a resource-efficient traffic localization scheme for multiple bittorrents. the emergence of peer-to-peer (p2p) applications has posed a threat to the operating cost of internet service providers (isps) due to the large amount of inter-isp traffic generated. the problem stems from the mismatch between the p2p overlay network formed randomly and the underlying physical network. recently, bittorrent has attracted enormous users by its convenience of large-scale content distribution and has also become a major challenge for isps. therefore, in this paper we proposed an effective b-proxy scheme to evaluate through realistic simulation on planetlab, where hundreds of bittorrent clients were executed during the experiment. simulation results show that more than thirty percent of inter-isp traffic could be saved in a torrent with a relatively small cache size consumed which is only eighth times that of the original file.
a partial-protection approach using multipath provisioning. we study the problem of reliably provisioning traffic using multipath routing in a mesh network. traditional approaches handled reliability requirements using full-protection schemes. although full-protection approaches offer high assurance, this assurance can be costly. we take a less expensive approach to maintain reliability by offering partial-protection. specifically, our approach guarantees part of the requested bandwidth, rather than the full amount, in the event of a link failure. we first show that the amount of partial-protection that can be guaranteed is limited by the topology of the network and the bandwidth requirement of a connection request. we then propose an effective multipath algorithm that attempts to provision bandwidth requests while guaranteeing the maximum partial-protection possible. results show that by effectively selecting paths that limit edge overuse, our algorithm achieves very low bandwidth blocking probability. our algorithm also serves significantly more requested bandwidth than the protection approach.
iterative detection and decoding for hard-decision forwarding aided cooperative spatial multiplexing. in this paper, the optimal decoding strategy for cooperative spatial multiplexing (csm) aided systems is derived. in csm systems, the multiple relay stations (rss), which compose a virtual antenna array (vaa), independently decode the packets received from the mobile stations (ms) and forward them to the base station (bs). when the bs decodes the signal forwarded from the rss, the potential decoding errors encountered at the rss will result in erroneous forwarding, but their effects are mitigated by the proposed solution. our simulation results show that when the direct link has a significantly higher signal-to-noise ratio than the relay link, the proposed decoding algorithm achieves an approximately 3 db better performance than conventional csm, which does not consider the deleterious effects of erroneous forwarding from the rss.
distributed reallocation scheme for virtual network resources. network virtualization is an emerging technology for cost-effective sharing of network resources. the key strategy in network virtualization is of slicing physical resources (links, cpu, memory, and storage) to create virtual networks that are assigned to different operators. one important challenge on network virtualization is the efficient use of the physical resources. to accomplish such efficient use the management of the physical resources should be transparent to the applications running within the virtual networks, and should be executed at runtime in order to deal with the variation on the load requests of different virtual networks. traditional resource allocation schemes use offline, centralized, and global view strategies to manage the use of physical resources. in contrast to these strategies, we propose a runtime, distributed, local view approach to manage physical resources. in this paper we introduce a virtual network architecture and an associated self-organizing algorithm to reallocate virtual network resources along different physical nodes in order to equalize the bandwidth, and storage consumption on the physical nodes. we developed a virtual network model based on omnet++ to simulate the designed self-organizing algorithm. an iptv testbed scenario is presented and initial experiments, about the interruption time of the application inside the iptv virtual network, are described.
multipurpose image watermarking based on the wavelet tree contrast level transformation. multipurpose image watermarking algorithms can achieve the goal of content authentication and copyright protection simultaneously. in this paper, we propose a wavelet tree based blind watermarking algorithm using contrast level transformation. the wavelet coefficients of the host image are grouped into trees. the robust watermark and the semifragile watermark are embedded by quantizing one tree and resetting the other. with level change compensation, the watermarked image has high fidelity to the original one since the difference is minimized. both of the watermarks can be independently extracted without the original image. the simulation results have demonstrated the effectiveness of the proposed algorithm in terms of robustness compared with other wavelet tree based technique.
security games with incomplete information. we study two-player security games which can be viewed as sequences of nonzero-sum matrix games played by an attacker and a defender. at each stage of the game iterations, the players make imperfect observations of each other's previous actions. the underlying decision process can be viewed as a fictitious play (fp) game, but what differentiates this class from the standard one is that the communication channels that carry action information from one player to the other, or the sensor systems, are error prone. two possible scenarios are addressed in the paper: (i) if the error probabilities associated with the sensor systems are known to the players, then our analysis provides guidelines for each player to reach a nash equilibrium (ne), which is related to the ne of the underlying static game; (ii) if the error probabilities are not known to the players, then we study the effect of observation errors on the convergence to the ne and the final outcome of the game. we discuss both the classical fp and the stochastic fp, where for the latter the payoff function of each player includes an entropy term to randomize its own strategy, which can be interpreted as a way of concealing its true strategy.
blind detection of interleaver parameters for non-binary coded data streams. interleaving, which is commonly used to combat bursts of errors, is an important technique in digital communications systems. the blind detection of interleaving parameters has been studied by many researchers for forward-error-correction (fec) encoded binary data streams. in this paper, we use finite field gauss elimination with pivoting to blindly estimate interleaving period of non-binary data streams. to be specific, the data streams are encoded by reed solomon codes. suppose the percentage of zeros in each column of the analytical matrix block is denoted as φ0. numerical results show that both the variance and the mean of φ0 can be used as the evaluation parameter to detect the interleaving parameters. however, the former approach provides a 1-db gain over the latter.
do next generation networks need path diversity? we have currently reached a phase where big shifts in the network traffic might impose to rethink the design of current architectures, and where new technologies, being pushed into market, will act as enabler of such changes. taking into account the current scenario and its likely evolution as well, in this paper we examine the case for multi-path routing within the metropolitan access network. through an optimization framework, we undertake the analysis of several interesting aspects of the problem, such as i) the user access technology, ii) the topology of the access network and iii) the traffic locality ratio within the access. by numerical solution of the problem we quantify the potential gain given by path-diversity: our results confirm the appeal of multi-path routing strategies both from the user and the network perspectives.
qos of video delivered over 802.11e wlans. many home networks now use 802.ll wireless local area networks (wlan)s. the 802.11e amendment has been designed to improve quality of service (qos) over these networks allowing for multimedia applications such as iptv to be better supported. the h.264 video compression standard is suitable for iptv due to its high compression and error resilience. video packets of different slice types are of varying importance to the decoded video quality so can be mapped into different priority queues using 802.11e enhanced distributed channel access (edca). we investigate several mapping schemes for a variety of video content to see how the quality of the decoded video is affected as the number of concurrent video connections is increased. the different mapping schemes exhibit different loss patterns in the video sequences and their impact on the video quality is content dependent. subjective tests were therefore carried out which allow us to perform an accurate and valid assessment of the video quality. packet loss rate is also reported. our results show that as the number of concurrent videos approaches the network capacity some mapping schemes show a cliff-edge drop in quality while others offer a more acceptable gradual quality degradation. these schemes cause b-frames to be dropped and in effect reduce the video frame rate. these schemes are more successful for videos that have low or medium temporal activity.
subset selection in type-ii hybrid arq/fec for video multicast. this paper proposes an error control scheme that minimizes the total distortion experienced by the receivers using a new version of type-ii hybrid arq/fec. based on the feedback information about the losses in the previous group of pictures (gop), the server sends parity packets for a subset of the frames from that gop with the aim of minimizing the total distortion experienced by the receivers. the subset selection problem is np-hard, so we propose a suboptimal method to solve it based on simulated annealing. experimental results for the case when a single parity packet is used per group of 16 packets show that the proposed subset selection improves the plain type-ii hybrid arq/fec by over 4 db in decoded video psnr, and achieves a 1-1.5 db gain compared to a state-of-the-art error control method based on rate-distortion optimized frame retransmission.
on the cache-and-forward network architecture. in order to meet the increasing demands of content dissemination in internet, we propose a novel architecture for the future internet called cache-and-forward (cnf), which transports content as "packages" in a hop-by-hop manner towards the destination, instead of transporting a stream of fragmented packets along an established tcp/ip connection. in this paper, we discuss how the cnf network architecture can be designed for efficient content retrieval. we first introduce several specific services provided in cnf network which are centered around content handling and mobile access. we then give an overview of the cnf protocol stack, which is built on top of ip, and consists of a data plane and a control plane. we provide detailed descriptions of each protocol within both planes. then we present two caching algorithms, where one involves each cnf router making independent decisions on content caching while the other coordinates node caching within an autonomous system (as) through hashing. finally, we gave the initial simulation results to show the performance benefits of hop-by-hop transport and content caching.
using session identifiers as authentication tokens. as authentication provides crucial online identity, it is the basis of data security. in this paper, a session based authentication is proposed and the long unique un-guessable session identifier is used as a parameter of an authentication token. it has the advantages of one-timeness, short-lived and no prior knowledge requirement. the session model is established with detailed implementation of communication protocol. the security of this protocol is then analyzed formally and the results show that the protocol can resist various attacks, e.g. session hijacking, message replay and pharming attacks etc. finally, a case is studied and the performance of the application is evaluated, which indicates that the proposed scheme is simpler and more efficient than the existing schemes.
low complexity variational bayes iterative receiver for mimo-ofdm systems. a low complexity iterative receiver is proposed in this paper for mimo-ofdm systems in time-varying multi-path channel based on the variational bayes (vb) method. according to the vb method, the estimation algorithms of the signal distribution and the channel distribution are derived for the receiver.with the aid of the soft-output qrd-m algorithm, whose complexity is fixed and relatively low, the signal distribution can be obtained conveniently. in particular, a sequential channel estimation algorithm, which completely avoids the computation of matrix inversion and multiplication, is introduced for the channel distribution estimation. moreover, the distribution estimations of the signals and the channels are performed in a cyclical iteration way. the simulation results show that the performance loss of the proposed receiver is only 1db for fast varying channels and less than 0.5db for slow varying channels at the bit error rate of 10-4after 3 iterations, compared with the optimum receiver with perfect channel state information.
a phy-mac cross-layer protocol for ad hoc networks with multiple-antenna nodes. in this paper, we propose a physical (phy) - medium access control (mac) cross-layer protocol for ad hoc networks with antenna-array-equipped nodes that employ single-antenna transmission and multiple-antenna reception. our protocol extends the progressive back-off algorithm (pboa), proposed by toumpis and goldsmith, by integrating medium access and power control with optimum receive beamforming (orb); hence it is named pboa-orb. the protocol performance is evaluated via simulations over a single-hop ad hoc network that is subject to a uniform traffic load. it is shown that pboa-orb significantly enhances both the aggregate throughput and the energy efficiency of pboa by harnessing the interference suppression and array gains of receive beamforming. specifically, for a small number of antennas compared to the number of nodes, the aggregate throughput increases linearly with the number of antennas while the average energy consumption per data packet decreases.
fairness-aware joint routing and scheduling in ofdma-based cellular fixed relay networks. relaying and orthogonal frequency division multiple access (ofdma) are the accepted technologies for emerging wireless communications standards. the activities in many wireless standardization bodies and forums, for example ieee 802.16 j/m and lte-advanced, attest to this fact. the availability or lack thereof of efficient radio resource management (rrm) could make or mar the opportunities in these networks. this paper therefore provides a comprehensive rrm algorithm for ofdma-based multi-cellular fixed relay networks in a way to ensure fairness among users with minimal impact on the network throughput (in contrast, pure opportunistic rrm techniques always favor users with good channel conditions). unlike the majority of works in the literature, our proposed scheme is queue-aware and jointly performs routing, fair scheduling, and load balancing among cell nodes. the routing strategy has inherent learning ability and it dynamically converges to better routes.
sum rates and user scheduling for multi-user mimo vector perturbation precoding. this paper considers the multiuser multiple-input multiple-output (mimo) rayleigh fading broadcast channel. we consider the case where the multiple transmit antennas are used to deliver independent data streams to multiple users via a multi-user technique known as vector perturbation. we derive expressions for the capacity in terms of the average energy of the precoded vector, and use this to derive a closed-form high-snr upper bound, which we show to be tight via simulation. we then turn to the practical issue of user selection. we propose a low-complexity user selection algorithm that attempts to maximize the high-snr sum rate upper bound. simulations show that the algorithm outperforms other user selection algorithms of similar complexity.
distributed space-time code for asynchronous two-way wireless relay networks under frequency-selective channels. in this paper, we consider asynchronous two-way wireless relay networks with amplify-and-forward protocol (aftwrn), where the distributed space-time code (dstc) is utilized without synchronization among relays to assist the communication between two terminals. we analyze the pairwise error probability (pep) behavior of dstc for af-twrn under frequency-selective channels. from our analysis, it is seen that of the paths from one terminal to relays and from relays to another terminal, those with smaller diversity order result in an overall system performance bottleneck. considering both the timing errors among relays and the multipath fading, we then propose a family of distributed convolutional space-time codes (dcstc) for af-twrn such that the full diversity order can be achieved. finally, various numerical examples are provided to corroborate the analytical studies.
loop-free link stability metrics for proactive routing in wireless ad hoc networks. to improve communication quality in wireless ad hoc networks, it is definitely important to select stable links as communication paths. to this end, various mobility metrics are presented in the literature. however, the routing loop problem, which is inevitably involved in link-state proactive routing scheme, has not been discussed well. in this paper, we propose a simple dynamic metrics in respect of link stability, which is loop-free throughout dynamic metric transition. through a theoretical analysis of loop-freeness, we present our new strategy to achieve loop-freeness with sufficiently low cost for ad hoc networks.
a game-based self-organizing uplink tree for voip services in ieee 802.16j networks. in this paper, we propose a game theoretical approach to tackle the problem of the distributed formation of the uplink tree structure among the relay stations (rss) and their serving base station (bs) in an ieee 802.16j wimax network. unlike existing literature, which focused on the performance assessment of the network in the presence of the rss, we investigate the topology and dynamics of the tree structure in the uplink of an 802.16j network. we model the problem as a network formation game, where each rs aims to maximize its utility that accounts for the gains from cooperation in terms of bit error rate (ber) and the delay costs resulting from multi-hop transmission. the proposed utility model is based on the concept of the r-factor which is a parameter suitable for assessing the performance of voip services. for forming the tree structure, we propose a distributed myopic best response dynamics in which each rs can autonomously choose the path that connects it to the bs through other relays while optimizing its utility. using the proposed dynamics, the rss can self-organize into the tree structure, and adapt this topology to environmental changes such as mobility while converging to a nash tree network. simulation results show that the proposed algorithm presents significant gains in terms of average achieved ms utility reaching up to 42.57% compared to the star topology where all rss are directly connected to the bs, and up to 44.78% compared to the case with no rss.
an adaptive resource/performance trade-off for resolving complex queries in p2p networks. structured peer-to-peer (p2p) systems are increasingly important for scalable data dissemination and search. current distributed approaches for resolving complex search queries, like multi-attribute and range queries, typically require multiple query messages to resolve a single search request. to reduce the message overhead and the search latency, some approaches like the multi-attribute addressable network (maan) use static replication. however, this results in high main memory requirements and large data transfers each time a device joins the p2p network. those drawbacks can be tolerated for p2p networks that mainly consist of fixed, powerful nodes like pcs but are intolerable for resource-constrained nodes with high churn, like mobile devices. as mobile devices will play a significant role in accessing and distributing data in the future, we propose and evaluate an improved search mechanism for such a scenario. compared to maan, our approach significantly reduces the memory footprint and bandwidth requirements (up to a factor of five in our sample scenario). at the same time, the good latency properties of maan are remained on average. this is achieved via a dynamic replication scheme which introduces an adjustable trade-off between memory footprint and search latency. thereby, our approach makes efficient, distributed resolution of complex queries in resource-constrained p2p networks feasible.
a mathematical optimization approach for radio network planning of gsm/umts co-siting. 3g umts networks are being widely deployed by several cellular operators worldwide that already have existing gsm networks. in this paper, we model the problem of gsm/umts co-siting as a nested mixed integer optimization problem which takes as input an area of interest with existing gsm sites and obtains as output the optimal number and locations of umts sites to be deployed (new and co-sited with gsm sites) in order to optimize target objectives. the goal is to minimize the cost of umts network deployment by reusing as many existing gsm sites as possible while guaranteeing that every cell is covering a target capacity load which is a percentage of the downlink pole capacity. we propose an algorithm taking into account both integer and continuous variables to solve the formulated optimization problem as a function of the user distribution and the existing fixed gsm site locations. results for different scenarios show that it is optimal to reuse a subset of the existing gsm sites in addition to deploying new umts sites.
novel shaping and complexity-reduction techniques for approaching capacity over queuing timing channels. this paper discusses practical codes for communication via packet timings across network queuing systems - an instantiation of the "bits through queues" result for timing channels. it has recently been shown that sparse-graph linear codes followed by shaping techniques, combined with message-passing decoding, can enable practical timing channel codes with low symbol error rates near the capacity. the previous work had two main drawbacks. first, the shaping technique was only effective for very large finite field sizes. secondly, the complexity of the message-passing decoder was quadratic in the block length. in this work, 1) we develop an alternative shaping technique using random dithers with provably good statistical guarantees; 2) we exploit little's law from queuing theory along with a large deviations argument to reduce the message-passing decoder's complexity from quadratic to linear in block length. we illustrate the effectiveness of this approach on simulated queuing systems with low symbol error rates near the capacity.
reconfigurable peer-to-peer connectivity overlays for information assurance applications. the paper offers tree-structured connectivity between the peer entities over an infrastructure network as an abstraction to embody the application-oriented processing functions on peer-to-peer information flows. tree reconfigurations are triggered when failures or security violations occur in the connectivity path between the peer nodes (e.g., increase in path delays, dos attack on a node). reconfigurations are also initiated when the application-level properties of information flows change (e.g., lower data accuracy for non-important contents). for information assurance settings, a tree structure elegantly supports the desired properties of separation and non-inference between the low-level network entities and the application entities. a connectivity management algorithm reconfigures a tree satisfying the desired topological properties (e.g., low geographic spread, low peer-to-peer distances). the algorithm provides redundancy in the connectivity paths along the temporal dimension (on top of a rich connectivity in the physical infrastructure -- as in overlay networks). application case studies of tree-structured connectivity with qos and security goals are also described.
on sensor placement for directional wireless sensor networks. a directional sensor network is formed by directional sensors which may be oriented toward different directions. the sensing region of a directional sensor can be viewed as a sector in a two-dimensional plane. therefore, a directional sensor can only choose one sector (or direction) at any time instant. planning of directional sensor networks has received very little attention in the literature. in this paper, we discuss directional sensor placement which is a critical task in the planning of directional sensor networks. we also present an integer linear programming model whose goal is to minimize the number of directional sensors that need to be deployed to monitor a set of discrete targets in a sensor field. numerical results demonstrate the viability and effectiveness of the model.
analysis of selective retransmission techniques for differentially encoded data. this paper presents an analytical framework for the study of hybrid arq techniques aimed at the transmission of multimedia content with differential encoding. we propose a markov model of a selective repeat hybrid arq transmission scheme, where we assume that packets have different properties in terms of size, information content, and retransmission limit, so as to capture the differential encoding which characterizes such multimedia data.we consider a non-zero round-trip time channel modeled through a discrete-time markov chain. we provide an analytical tool for the evaluation of two main performance metrics, namely, throughput and goodput. the model is extremely flexible and allows evaluation of several channel conditions and comparison of different types of arq (plain arq, type i and ii hybrid arq). our results can be used as an effective tool to define design guidelines of multimedia transmission systems and to understand their performance trends.
pilot design of mimo-ofdm with beamforming. reference symbols (pilots) support coherent detection, but add overhead and consume transmit power. a sophisticated pilot design needs to trade-off the attainable channel estimation accuracy with the induced losses in bandwidth & power efficiency. mimo transmission, transmit beamforming, and spatial multiplexing further complicate pilot design. in this paper a unified analytical framework is developed to evaluate the attainable spectral efficiency of different pilot types for mimo-ofdm employing fixed transmit beamforming.
a load-balanced route selection for network coding in wireless mesh networks. cope [1] appears as the first wireless network coding approach which can improve the throughput of wireless mesh networks (wmns). but the established routes in cope may result in fairly limited coding opportunities and low throughput gain. although excessive intersections of flows can bring forth more coding opportunities, they may make some nodes overloaded, and decrease the throughput. furthermore, detecting coding opportunities may induce the high routing delay. to solve these problems, we propose hlcr, a heuristic load-balanced coding-aware routing mechanism, and its novel path metric called heuristic path metric for coding and load-balancing (hpmcl) in wmns. hpmcl evaluates a path considering network load, expected number of transmissions and potential coding opportunities. thus hlcr can efficiently find high throughput paths having coding opportunities and achieve good load balance with low cost by the hpmcl metric and other effective measures. our simulation results in ns-2 show that hlcr scheme can gain higher network throughput compared with cope.
blind frame synchronization of product codes based on the adaptation of the parity check matrix. we present in this paper a blind frame synchronization method based on the adaptation of the parity check matrix of the code. the blind synchronizer is initially based on the calculation of the log-likelihood ratios (llr) of the syndrome elements, obtained using the parity check matrix of the code. before applying our synchronization procedure, we propose in this paper to rearrange the parity check matrix of the code according to the reliability of the received symbols as previously introduced for decoding linear block codes with high density parity check matrix. simulation results show that the frame error rate (fer) curves obtained after applying the proposed synchronization method to product codes are very close to the ones with perfect synchronization. in addition to its powerful synchronization properties, the main advantage of the proposed synchronization algorithm is its capability of being introduced as a part of the decoder so that no additional material is required for the synchronization step.
a novel interactive streaming protocol for image-based 3d virtual environment navigation. image-based rendering (ibr) has attracted recent attention mainly due to its low requirements for generating new scenes based on a sequence of reference images. ibr has paved the way for a new class of application, the free viewpoint television (ftv), which allows the viewer to interactively control the camera and move freely within a scene. ibr can also be used to render complex 3d virtual environments on graphics-constrained devices, such as cellphones and pdas. in this paper, we propose a new protocol that offers the user a richer virtual experience by pre-streaming the necessary imagery data to generate new views as the user wanders within a 3d environment. we introduce the idea of key partial panoramas, i.e., panorama segments that cover movements in any direction by simply strafing from an appropriate key partial panorama and streaming the amount of lost pixels. we have implemented our protocols and evaluated them against two well-known approaches. experimental results show that our solution outperforms the selected approaches, by minimizing the delay between image updates and by allowing for a more complex navigation scheme.
lightweight static analysis to detect polymorphic exploit code with static analysis resistant technique. the general method in which attackers obtain the control authority of the remote host is through the exploit code. as network security systems have mounted the desired signatures about exploits, they have reduced damage due to the spreading and reoccurrence of the exploits. however, to avoid signature-based detection techniques, exploits employing techniques such as polymorphism and metamorphism have become more prevalent. especially in the case of polymorphism, because there are many automation engines even if there is no special knowledge in order to make various exploits easily, the polymorphism researches need to be more actively studied. we present a new static analysis method for detecting the decryption routine of polymorphic exploit code. most of decryption routines store the program counter value of remote host on a stack and use the value as the address for accessing the memory that the encrypted original code is positioned. the proposed method traces the processing steps of decryption routine as using the static analysis method. in the results of experiment, the proposed method can detect polymorphic exploit codes that the static analysis resistant techniques are used, and shows more efficient than the emulation-based method in the processing performance.
a linear time synchronization algorithm for underwater wireless sensor networks. large propagation delay and node movement are considered to be two significant attributes that differentiate an underwater wireless sensor network (uwsn) from a ground wireless sensor network (wsn). considering the effects of both propagation delay and movement, we propose a time synchronization algorithm suitable for a uwsn. an underwater node can move out of and into another node's range frequently. with the proposed algorithm, no time synchronization is necessary if the time stamps of the received data packets are within the tolerance. in this fashion, the network underwater does not need to perform global time synchronizations periodically, which reduces the time used to synchronize clocks among sensor nodes. the simulation results show the time cost for synchronization is linear to the data packets exchanged.
cross-layer design for mimo spatial multiplexing in correlated ricean fading. in this paper, we investigate a cross-layer transmit antenna selection (t-as) approach for multiple-input multiple-output spatial multiplexing (mimo-sm) systems employing decision-feedback detector (dfd), over spatially correlated ricean channels. the selected transmit antennas are those that maximize the link layer throughput of mimo channels. a closed-form expression for the system throughput with perfect channel state information (csi) is derived. extensive simulation results are provided for the system performance assessment, showing that the cross-layer t-as scheme always assigns the transmission to the antenna combination which sees better channel conditions, resulting in a substantial improvement over the optimal capacity-based t-as approach.
bicmb-ofdm link resource adaptation. an efficient and flexible air interface is the necessary condition for enabling high data rates next generation wireless systems. a practical answer to this need consists in exploiting channel state information at the transmitter for an adaptive and efficient use of the available radio link resources. this paper contributes with a novel strategy for the allocation of the sub-carrier transmit power in the case of a wireless system featuring: i) bit-interleaved coded modulation (bicm); ii) orthogonal frequency division multiplexing (ofdm); iii) multiple antenna profile (mimo). the proposed power-allocation algorithm aims at maximizing the so-called goodput performance metric for packet transmissions employing automatic repeat request (arq) schemes. in addition, it is also proven to be near-optimum in maximizing the input/output mutual information of the mimo-ofdm subchannels. numerical simulations over typical wireless indoor scenarios confirm the effectiveness of the procedure when applied in the context of mimo-bicm-ofdm systems.
effective capacity of superposition coding based mobile multicast in wireless networks. effective capacity is a useful technique to characterize the system throughput with statistical delay-constrained quality of service (qos) guarantees. in this paper, we integrate effective capacity theory into superposition-coding (spc) based multicast transmission to devise the efficient channel-aware multicasting scheme in wireless networks. specifically, we propose to optimize the effective capacity for multicast transmissions subject to the specified loss-rate constraint and the statistical delay qos requirement in terms of the qos exponent. we use superposition coding in wireless multicast to handle heterogeneous channel fading across multicast receivers, and apply the pre-drop strategy to gain more flexible rate control. under our proposed framework, we derive the optimal pre-drop strategy and the optimal power/rate allocation for each layer of superposition coding. simulation analyses present insightful observations on tradeoff between effective capacity and the qos requirements, and demonstrate the superiority of the spc-based scheme over the existing time-sharing (ts) based multicast scheme.
integration of ims and dvb-rcs for interactive content delivery. this paper describes issues related to the integration of ims and dvb-rcs satellite networks. dvb-rcs is studied as an access network variant for ims in addition to the already known cellular, wireless and cable access networks. although combining ims and dvb-rcs seems a practical solution for communication and content delivery several issues must be addressed in order to make the integration effective. the main areas of research are quality of service integration and multicast integration. specifically, integration of the ims qos architecture (pcc) and the control protocol (c2p) of satellite communication is studied, and also how ip multicast can be integrated with the satellite content distribution mechanism.
adaptive time synchronization for wireless sensor networks with self-calibration. time synchronization is important for wireless sensor networks because it facilitates cooperation among nodes and helps raise power efficiency. time synchronization protocols like tpsn, rbs and ftsp have provided great schemes to fulfill fast synchronization with efficiency. in some applications, nodes might hope to sleep for a long time without timestamp exchanges with other nodes. in that case, accurate time drift prediction is quite necessary. for that purpose, firstly, we propose a time synchronization scheme, which fully utilizes the broadcast nature. the scheme achieves time synchronization with fewer timestamps compared with rbs and tpsn. secondly, we introduce a method to find relative time drift rate on the fly. thirdly, we introduce a scheme to predict time drift rates of the next few hours. we also analyze a few factors that deteriorate frequency drift or time drift rate. the diurnal periodical environment trend, instead of mathematical extrapolation, is used for time drift rates prediction of the next few hours.
probability-based combination for cooperative spectrum sensing in cognitive radio networks. to take advantage of time-varying spectrum opportunities, a cognitive radio (cr) network monitors the dynamic usage of the licensed band through cooperative spectrum sensing. in this paper, we propose a probability-based scheme for combination of spectrum sensing information collected from several cr users. different from conventional cooperative spectrum sensing schemes that assume synchronous local sensing information, our scheme enables combination of both synchronous and asynchronous sensing information by utilizing the statistics of licensed band occupancy. in our scheme, the amount of information from each cr user is flexible and a simplified implementation is also feasible under a symmetrical case. simulation results demonstrate that our scheme is robust and superior in terms of detection performance.
measuring indoor mobile wireless link quality. this paper investigates methods for link quality measurement of an indoor, time-varying wireless link. link quality estimates are used for a number of higher-layer functions, including rate adaptation, routing, and topology control. the objective is to rapidly and efficiently estimate the current reliability of an rf link in terms of its packet success probability in the presence of a time-varying channel. we compare various approaches to estimating the current packet success rate (psr), including packet counting and several methods employing physical layer signal-to-noise ratio (snr) measurements. among the snr-based estimators, we consider those using a simple moving average, an exponential moving average, and a yule-walker predictor of the current snr. the analysis shows that the snr-based estimators are more efficient than packet counting methods in terms of the number of measurements needed, are more accurate when link quality variability increases, and are more flexible in terms of predicting the psr for various bit rates and packet sizes. an important requirement, however, of the snr-based estimators is a priori knowledge of the snr-psr relationship, which is environment- and radio-dependent. an efficient methodology for obtaining this mapping is presented.
decomposition for low-complexity near-optimal routing in multi-hop wireless networks. network flow models serve as a popular mathematical framework for the analysis and optimization of multi-hop wireless networks. they also serve to provide the understanding necessary to derive effective distributed protocols. however, the high computational complexity of realistic models restrict the translation of theoretical insights into distributed protocols. in this paper, we consider an np-hard, mixed integer linear programming based routing model that computes single-path routes in a wireless network. we propose an efficient, polynomial time algorithm that applies domain specific heuristics to reduce the complexity. we employ a decomposition based approach to break the monolithic problem into several sub-problems that cooperate to find near-optimal routes. the sub-problem structure is chosen such that it captures the optimal route discovery process between a source and destination; this is a design principle that can be directly used in distributed routing protocols. we show that the resulting formulation achieves orders of magnitude improvement in the run-time. simulation results show that the routes derived from the model are effective even in practical wireless networks with commonly used protocol stack.
joint bandwidth reservation and admission control in ieee 802.16e based networks. the ieee 802.16e is a compatible and reasonable technology to solve the last mile access problem. since the multiple services in the system are connection-oriented, it is crucial to provide effective admission control and resource allocation mechanisms to guarantee the quality of service (qos) of the system. in this paper, we investigate the joint bandwidth reservation and admission control in the ieee 802.16e networks. foremost, we consider two system models: model without buffer and model with buffer. then two optimization problems are formulated for the two models separately. to solve the two min-max optimization problems, we propose a bandwidth reservation algorithm. in addition, the bandwidth reservation thus obtained can be used with admission control jointly. our aim is to enhance fairness while satisfying qos requirement. numerical results are presented to demonstrate the performance of the proposed scheme in terms of maximal call blocking probability and fairness.
a blind channel estimation algorithm for space-time coded mc-cdma receivers. in this paper we proposed a linearly constrained minimum variance receiver for a space-time coded multicarrier (mc) cdma system in frequency selective fading channels. it is shown that in the proposed receiver the channel can be blindly estimated as the eigenvector that corresponds to the maximum eigenvalue of an autocorrelation matrix, and then, efficient algorithms for subspace tracking can be used. computer simulations shows that the proposed channel estimation algorithm achieves performance comparable to traditional algorithms with less computational cost.
power allocations for adaptive distributed mimo multi-hop networks. distributed mimo multi-hop relaying is one of the most promising technologies that permits cost-effective improvement of coverage, data rate and end-to-end (e2e) user experience by utilizing distributed low-complexity space-time codes to overcome path losses and deep fades of wireless channels. however, an efficient transmission scheme and resource management are required to exploit these advantages. specifically, low-complexity adaptive schemes and power control strategies should be designed, thereby achieving robust and cost-efficient e2e communications. in this paper an adaptive transmission scheme is presented, where one relay stops forwarding the message if it is in outage and other nodes adapt to a new space-time code. for this adaptive scheme, optimal as well as sub-optimal closed-form power allocation solutions are derived which minimize the total transmission power while satisfying a given e2e outage probability. the significant power savings due to the proposed approaches in comparison to a non-adaptive scheme is demonstrated by numerical results.
signal detection in distributed cooperative cellular systems without perfect synchronisation. in this paper, an asynchronous cooperative cellular system is investigated on the uplink. we propose a signal detector which involves successive interference cancellation (sic) and parallel interference cancellation (pic) to suppress the impact of interference caused by co-channel users and imperfect synchronisation. simulation results show that the proposed scheme provides significant performance improvement with low computational complexity.
weighted size-aware packet distribution for multipath live streaming. we focus on the problem of packet distribution for live media streaming over multipath networks. after proposing multipath live streaming model and an in-depth analysis of it, we suggest that traffic load should be allocated to paths in proportion to the paths' available bandwidths, considering complicated network status changing as well as burst of media sending rate, that can minimize the bandwidth overload probability. moreover, weighted size-aware packet distribution algorithm is proposed to avoid the actual traffic deviation from expected due to variance of packet sizes. simulation results show that the proposed algorithm outperforms other traditional algorithms, especially on reducing late packets, which has negative impact on real-time requirement.
relay-assisted routing in cognitive radio networks. cognitive radio has been proposed in recent years to promote spectrum efficiency by exploiting the existence of spectrum holes. the heterogeneity of both spectrum availability and traffic demand among secondary users has brought significant challenge for efficient spectrum allocation in cognitive radio networks. observing that spectrum resource can be better matched to traffic demand of secondary users with the help of relay nodes, in this paper we propose to utilize cooperative relays to assist the transmission and improve spectrum efficiency. different from traditional cooperative communication within a single channel, in our scheme a relay node may be selected for a link to bridge the link's source and destination using its different common channels with those two nodes. with these new logical links composed of both direct link and relay link, new routing protocols are needed so that end-to-end performance can be better improved. therefore, we define a new link cost, relay-aware link cost, which considers several aspects including channel availability, channel condition, channel utilization and potential relays. based on this link cost, a relay-assisted routing (rar) protocol is proposed which includes routing discovery and local adjustment. simulation results demonstrate the effectiveness of the proposed routing scheme.
performance analysis of optimal joint beamforming in multi-keyhole mimo channels. this paper presents an analytical performance analysis for a multi-keyhole multiple-input multiple-output (mimo) fading channel. our main contribution is a set of new statistical results for the maximum eigenvalue of the random multikeyhole channel matrix, which includes closed-form expressions for the cumulative distribution function and probability density function, as well as asymptotic expansions. based on the results, we analyze the outage performance of the optimal joint beamforming system in multi-keyhole mimo channels. our results illustrate that the outage performance of the multi-keyhole channels is generally worse than that of rich-scattering mimo rayleigh channels.
the interference-multiple-access channel. we introduce the interference-multiple-access channel, which is a discrete memoryless channel with two transmitters and two receivers, similar to the interference channel. one receiver is required to decode the information encoded at one transmitter, the other receiver is required to decode the messages from both transmitters. we provide an inner bound on the capacity region of this channel, as well as an outer bound for a special class of such channels. for this class, we also quantify the gap between inner and outer bound and show that the bounds match for a semi-deterministic channel, providing a complete characterization. for the gaussian case, we show that the gap is at most 1 bit, yielding an approximate characterization.
throughput-gain analysis of network coding in multi-channel multi-radio wireless networks. wireless network coding (nc) has emerged as a promising technology that improves network throughput and spectrum efficiency. how large can the coding gain be? in this paper, we study the network throughput gains of two types of wireless nc schemes, the conventional wireless nc and the analog nc, respectively, over the traditional non-nc scheme in multi-hop, multi-channel, and multi-radio wireless networks. in particular, we propose an analytical framework, which can exploit the best coding opportunities among all the possible realistic ones, for deriving the network throughput gains of the wireless nc schemes. by solving the problem of maximizing the network throughput subject to the fairness requirements under our proposed framework, we quantitatively analyze the network throughput gains of these two types of wireless nc schemes under various wireless network topologies.
cooperative content dissemination in intermittently connected networks. over the last few years, the popularity of multimedia content sharing among the internet users has promoted a new kind of networking where the content dissemination is determined by the interests of users rather than pre-specified destinations. development of wireless mobile devices has further enhanced the trend of content exchange among the mobile users. however, such mobile nodes based content dissemination may suffer the underlying intermittent connectivity due to the inherent limitations such as short radio transmission range, sporadic node densities and constrained power. to this effect, some solutions have been proposed in the literature that exploit the mobility and storage space of the nodes to distribute contents even if a route never exists. in all these mechanisms, whenever two mobile nodes encounter each other, each node only focuses on making independent disseminating decisions to improve the overall performance. however, even though each node can get its own optimized decisions, it may not be an optimized decision between the two encountering nodes. with this in mind, this paper presents a cooperative content dissemination framework (ccdf) with an analytical model to select and store the contents that maximizes the overall content delivery probability in the future. simulation results demonstrate the enhanced delivery performance offered by the proposed ccdf over existing schemes.
distributed usage control architecture for business coalitions. the dynamic environment of business coalition (bc) requires a flexible access control approach to deal with user management and policy writing. however, the traditional approach applied to bc assigns to access control a burden, mainly to the service provider, thus requiring ad hoc schemes to mitigate the lack of controls developed to bc needs. we present a brokered access control architecture, based on uconabc, to obtain an integrated usage control management for bc. the broker intermediates contract establishment between service provider and consumer, and derives from it the policies to regulate the usage at service-level. the consumer defines user-level policies to control the usage of the contracted services. we developed a web services based prototype to evaluate the feasibility of our proposal. the proposed architecture enables distribution of duties and integration of usage control management in a loosely coupled fashion, providing the flexibility desired in bc environments.
a body surface coordinator for implanted biosensor networks. biomedical sensors can be implanted and networked in the human body for health monitor, diagnosis, treatment or as a prosthetic device. life time and heat generated by implant due to communication and circuitry power consumption are big concerns. this paper presents a new network architecture for long range communications in the implanted sensor networks. we measured the on-body propagation around body surface and in-body propagation through tissue in the frequency ranges of 403mhz and 2.45ghz. we have found that the in-body path loss is more than that of on-body. to exploit the path loss difference, we propose to introduce a body surface coordinator which has more resources to the implanted sensor networks. instead of only routing data among implants, the coordinator on the body surface can forward data from one implant to another over long distance more safely and efficiently.
improving performance of tcp-based applications over dvb-rcs links. dvb-rcs links, as well as most of vsat systems, to improve tcp performance usually consider a pep solution. the satlabs group of the european space agency issued i-pep, selecting scps-tp as transport protocol, which supports two congestion control schemes: tcp vegas (default) and van jacobson's slow start and congestion avoidance. in both cases the most popular tcp-based applications, i.e. web browsing and e-mail, achieve very poor performance especially when dama schemes run at the mac layer. in this frame, tcp noordwijk has been specifically designed to optimize performance of short tcp-based data transfers over dvb-rcs dama links, meeting the requirement to be compatible with i-pep specifications. this paper presents an overview of tcp-based application criticalities over dvb-rcs links and shows how tcp noordwijk improves performance.
evaluate reliability of wireless sensor networks with obdd. reliability evaluation of wireless sensor networks (wsn) is a critical step in wsn design. to evaluate the reliability of wsn, an algorithm named cobdd is presented in this paper. cobdd executes recursive construction of the ordered binary decision diagram (obdd) only once, and therefore save much running time when wsn is subject to large number of common causes. furthermore, it constructs obdd with node expansion and decrease redundant computations from isomorphic subnetworks. experiments show that cobdd is an efficient algorithm for the reliability evaluation of wsn.
distributed multi-user scheduling for improving throughput of wireless lan. carrier sense multi-access (csma) is a typical method to share the common channel in a wireless lan (wlan). it works fairly well in times of light traffic. however as the number of nodes in a wlan increases quickly, severe collision greatly degrades network performance. in this paper we propose a distributed multi-user scheduling (dmus) scheme to solve this problem, taking time-variant link quality and rate adaptation into account. instead of all nodes, only nodes with high instantaneous link quality are allowed to contend for the channel. by setting a suitable snr threshold, at any instance only a small percentage of nodes join the contention. as a result, collision is mitigated, fairness is retained by independent fading, and the total throughput is increased since transmissions are finished at higher rates. simulation results show when there are 40 nodes in a wlan, the dmus scheme improves total throughput by up to 49.6% compared with the contention-free scheme, and by up to 194.6% compared with the csma/ca scheme.
selection cooperation with transparent amplify-and-forward relaying in mimo relay channels. in this paper, we consider a single-relay cooperative scenario, where the source, relay, and destination terminals are equipped with multiple transmit and receive antennas. we focus on the so-called transparent amplify-and-forward (t-aaf) for mimo relay channels, in which the relay requires neither channel state information (csi) nor synchronization of symbols or carrier. specifically, we propose and analyze new selection schemes where the relay, based on the received signal energies, select the "best" received signals on the s → r hop and retransmits them to the destination terminal with either repetitive or selective transmission. through the derivation of pairwise error probability (pep) expressions and asymptotic order of diversity (aod) analysis, we demonstrate that the proposed selection schemes maintain full diversity order. furthermore, we show that selective transmission on r → d hop has better performance, better throughput, and significantly better energy efficiency than repetitive transmission.
highly integrated fractional-n synthesizer for locatable wireless sensor nodes. local positioning systems significantly enhance the value of wireless sensor networks (wsn). this paper presents an integrated synthesizer for localization using frequency modulated continuous wave (fmcw) radar. the synthesizer is based on a fractional-n phase-locked loop (pll) architecture. all components of the pll are carefully designed with respect to their power consumption, and the digital parts are implemented in current-mode logic (cml). the complete synthesizer was manufactured in a 0.18µm sige bicmos process from ibm, and it consumes only 100mw, achieves a phase noise better than -117 dbc/hz and has a silicon area of 1.15mm2. due to its high integration level and its optimized design, the synthesizer achieves low power consumption and low phase noise that make it suitable for precise localization in mobile sensor nodes. localization measurements in indoor environments with multi-path propagation showed mean distance errors about 10 cm.
deterministic combining for fading channels. for a communication system employing receive diversity in flat rician fading, we consider linear combining receivers with deterministic weights. two receiver structures are proposed: (1) a modified maximum likelihood receiver in which detection is performed by maximizing the likelihood function of the combined received signal, (2) a deterministic maximal-ratio combining (mrc) receiver which uses the same structure as that of an mrc receiver with deterministic weights. the deterministic weight vector is chosen such that it minimizes the union bound on the symbol error probability. the error performance of the receivers is compared with that of the square-law combining and the equal-gain combining receivers.
transmission capacity of two-way communication in wireless ad hoc networks. wireless ad hoc networks require bidirectional data transmission to support two-way traffic and control functions like packet acknowledgement. most prior work on the capacity of wireless ad hoc networks, however, has focused only on one-way communication. in this paper we develop the concept of transmission capacity of two-way communication in wireless ad hoc networks. the transmission capacity has been used extensively to analyze one-way ad hoc networks - in this paper we provide a generalization that incorporates the concept of a two-way outage. we derive an upper bound and an approximation for the two-way transmission capacity, which are shown to be relatively tight for small outage probability constraints. we also quantify how the two-way success requirement reduces network capacity. our numerical and simulation results show that for certain two-way networks the capacity loss is considerable.
implementing secure p2p-ons. name services for the internet of things (specifically, the epcglobal network) are distributed systems that serve the following fundamental lookup function: given an identifier for a real-world object, e.g., an electronic product code (epc), they return a list of internet addresses of services, which offer additional information about this object. without name services acting as a broker between items and their information sources, the internet of things could not achieve the flexibility and global scalability necessary to live up to its vision. the currently specified object naming service (ons) for the epcglobal network has severe security drawbacks in its architecture and design. in this paper, we present the implementation of a peer-to-peer name service architecture based on distributed hash tables (dht) on the research platform planetlab. this alternative ons architecture named oida, if deployed as an infrastructure network, offers enhanced overall multilateral security compared to ons, combined with potentially better functionality, scalability, and roughly equivalent performance.
analytical and experimental comparison of packet loss recovery methods based on amr-wb for voip. forward error control (fec) and multiple description coding (mdc) are two classical techniques to resist packet loss for voice over ip (voip). amr-wb codec has been standardized for wideband speech conversational applications and has widely potential applications in the migration of wireless or wired networks toward a single converged ip network. however, how to choose the optimal fec or mdc for amr-wb in different loss rate conditions is an unexplored option. in this paper, we compare the performance of different fec and mdc techniques for amr-wb codec both analytically and experimentally. based on the comparison results, some practical configurations of fec and mdc for amr-wb codec are obtained.
bit loading for mimo with statistical channel information at the transmitter and zf receivers. for single-user mimo communication with uncoded and coded qam signals, we propose bit and power loading schemes that rely only on channel distribution information at the transmitter. to that end, we develop the relationship between the average bit error probability at the output of a zf linear receiver and the bit rates and powers allocated at the transmitter. this relationship, and the fact that a zf receiver decouples the mimo parallel channels, allow leveraging bit loading algorithms already existing in the literature. we solve dual bit rate maximization and power minimization problems and present performance results that illustrate the gains of the proposed scheme with respect to a non-optimized transmission.
distributed scalable multi-target tracking with a wireless sensor network. we propose a novel technique for tracking multiple co-dependently maneuvering targets using a wireless sensor network. we consider the scenario where the targets carry radio frequency identification (rfid) tags and the sensors in the network measure some metric of the radio transmissions from these tags, like the received signal strength, the time of arrival or the angle of arrival. these measurements are then processed by a sampling importance re-sampling particle filter for tracking. while such a set-up is now fairly standard in literature, the novel aspect of our algorithm is that it exploits the co-dependencies in the motion of the targets via a fully distributed and tractable particle filter bank. we thereby extract a significant "diversity gain", while allowing the network to scale seamlessly to a large tracking region. in particular, we avoid the pitfalls of network congestion and severely shortened battery lifetimes that plague currently used procedures that implement the filter on the joint multi-target probability density.
performance evaluation of interactive data services under sharing and preemptive scheduling disciplines. as specified by the third-generation (3g) wireless networks such as the universal mobile telecommunication system (umts), interactive data services, such as web browsing, voice messaging, and file transfer, represent a major service class in operation nowadays. in this paper, we develop an analytical approach to evaluate the performance of interactive data services under sharing and preemptive scheduling. specifically, we take into account user interactions in data sessions and the heavy-tailed data file size. both the mean and the standard deviation of data transfer delay are investigated for the two representative scheduling disciplines. numerical results are given to show the validity of the evaluation approach and the impact of the on-off user behavior under the scheduling disciplines.
stateful scheduling with network coding for roadside-to-vehicle communication. in urban areas such as street blocks, media-rich services are delivering to moving vehicles through access points (aps) deployed on the roadside. to increase the capacity of wireless links for these services, a roadside-to-vehicle communication system based on a novel stateful scheduling with network coding (ssnc) strategy is proposed. a major innovation of ssnc is that it enables the scheduling on the roadside ap to fully utilize the states of received data from vehicles for an enhanced performance. furthermore, a set of mechanisms are proposed to ensure reliable transmission in such highly dynamic and error-prone wireless channels. extensive simulations show that ssnc achieves an increased throughput gain between 1.2 and 2.0 at various conditions.
energy saving mac for mimo systems. over the last decade multiple-input and multiple-output (mimo) systems have been actively researched and started to be deployed in wireless communications owing to the significant increase in channel capacity. in this paper, we propose an energy saving mac protocol in mimo (esmacm) systems by focusing on energy efficiency instead of capacity maximization. esmacm considers the energy consumption together with the tradeoff between reliability (i.e., diversity) and throughput (i.e., multiplexing gain), and dynamically chooses an appropriate number of antennas for transmission. in computing the total energy consumption, esmacm counts circuit energy as well as transmission energy. naturally the circuit energy consumption is directly proportional to the number of active antennas. through numerical analysis, we confirm that our esmacm considerably saves energy consumption compared to conventional capacity maximization schemes that use a fixed number of mimo channels, for a given outage constraint. our finding is that the capacity maximizing communication which possibly can be regarded best in terms of energy efficiency gives a different solution from the energy minimizing communication.
constructions on 2d wavelength-time codes for cdma fiber-optic systems. in this paper, we study a new class of two-dimensional codes, here called multi-level prime codes, with expanded code cardinality by relaxing the maximum cross-correlation function to any arbitrary positive integer n. besides having asymptotically optimal cardinality and zero autocorrelation sidelobes, these multi-level prime codes can be partitioned into n levels, such that the cross-correlation function between any two code matrices in level l is at most l, where l ∈ [1, n]. the performance of the new codes in an optical code-division multiple-access system with hard-limiting detection is analyzed. our results show that the unique partition property of the multi-level prime codes allows the trade-off between code cardinality and performance for meeting different system requirements, such as capacity and throughput.
atomic distributed semaphores for accessing networked data. distributed hash tables (dhts), based on consistent hashing, offer efficient lookup services for decentralized distributed systems. dhts operate efficiently to handle large number of network nodes with continual node arrivals, departures, and failures. upon addressing the crucial issues of communication efficiency and offering load balancing in dynamic networking environments, dhts are the essential components for building structured peer-to-peer (p2p) overlay networks. although structured overlays improve data availability and consistency, they do not provide strong semantics on distributed data mutual exclusion operations. for a robust network operating system, it is essential to provide atomic data access semantic services. in this paper, a distributed semaphore (disem) mechanism is proposed, and it is designed on top of a dynamic structured overlay. the proposed design circumvents the availability and consistency issues. independent of any underlying overlay algorithms, disem provides a tunable level of data availability and consistency, while offering fault tolerance and reliable delivery services. a testbed prototype has been implemented to validate the mutual exclusiveness of networked replicas under different traffic loadings. the measured results indicate that disem offers high mutual exclusive access rates under different networking conditions.
comparison of analog and digital relay methods with network coding for wireless multicast. we study wireless multicasting from two sources to two destinations with the assistance of a single half-duplex relay. the objective is to evaluate the throughput and error performance of different analog and digital relay schemes with linear network coding at the relay. the analog relay node forwards either a scaled version of the received signal to the destinations, or alternatively, first filters the received signals to generate a linear minimum mean squared error (mmse) estimate, which is subsequently forwarded. the digital relay scheme first detects the source transmissions, combines the packets with a network code, and forwards the resulting symbols to the destinations. for all schemes the destinations recover the source and relay signals by first applying linear mmse filters, followed by decoding of the source bits. the performance of the schemes are compared in terms of normalized throughput (bits per channel use accounting for the delay due to the relay) and uncoded error probability, given a normalized power constraint. both narrowband and wide-band transmission schemes are considered. our results show that the analog relay schemes outperform the digital network coding scheme with respect to both throughput and error probability because of error propagation through the relay. numerical results are presented, which illustrate throughput-reliability trade-offs for all schemes considered.
efficient load-balanced ip routing scheme based on shortest paths in hose model. this paper proposes a simple shortest-path-based load-balanced ip routing scheme for the hose model. the proposed scheme is an extension of the smart-ospf scheme. the proposed scheme, the same as s-ospf, splits traffic demand only at source edge nodes and transmits the traffic along the shortest path routes. in s-ospf, the split ratios are determined for each source-destination edge node pair by assuming that the traffic demand between all source-destination edge node pairs are known, in other words, the exact traffic matrix is completely given. on the other hand, in the proposed scheme, we assume the use of the hose model; in this model, only the total amount of traffic that a node injects into the network and the total amount of traffic it receives from the network are known. any extension of the linear programming (lp) formulation to suit the hose model cannot be solved as a simple lp problem, because the traffic matrix is not known. by introducing a duality theorem, we successfully formulate our problem as an lp formulation that can be easily solved yielding the desired split ratios. numerical results show that the proposed scheme dramatically reduces the network congestion ratio compared to the classical shortest path routing scheme and it provides performance close to that provided by the sophisticated traffic-engineering (te) scheme of multi-protocol label switching (mpls)-te.
mean time to loss of lock and average switching rate of an automatic frequency control loop with an interferer and noise in a fading channel. the performance of an automatic frequency control (afc) loop in a noisy fading channel when an interference signal is present at the input of the afc is studied. independent non-identically distributed (i.n.d.) channels with rayleigh and rician fading are considered. the received signals are assumed to be narrowband and linearly modulated while the analysis is applicable to the unmodulated scenario as well. closed-form expressions and integral form formulas are derived for the mean time to loss of lock (mtll) and the average switching rate (asr) of an afc. numerical examples are provided to illustrate the effects of noise and slow fading on the performance of an afc in the presence of an interferer. it is shown that in some scenarios, an afc has a better performance if the desired signal is corrupted by more noise.
cooperative cognitive radio with priority queueing analysis. in this paper, we model the hierarchical structures inherent in cognitive radio networks as the priority queueing system in which primary users interact with the highest priority and secondary users belong to the lowest priority class. in a m/g/1 system containing one primary user and multiple secondary users, we obtain analytical forms of delay and throughput for different users with the function of traffic and channel conditions. based on the analysis, the secondary user is considered to act as a relaying terminal to assist the primary communication by adopting an amplify-and-forward tdma protocol. cooperative diversity gains are examined next and the benefits of the secondary: improvement of throughput, is discussed with respect of the primary traffic.
a flexible antenna selection scheme for 60 ghz multi-antenna systems using interleaved adcs. we present a new scheme for maximizing the signal-to-noise ratio (snr) in wideband multi-antenna receivers that employ time-interleaved analog-to-digital converters (adcs). current wideband receivers interleave a fixed number of slower adcs into one fast adc and assign this latter to one antenna according to an antenna selection algorithm. however, this does not always guarantee an optimal trade-off between thermal noise and quantization noise. this results in an overall snr that is lower than what could be obtained with the same number of adcs, assigned in a more optimal way. therefore, we propose to adjust the number of slower adcs assigned to a certain fast, interleaved adc dynamically, according to the snr of every individual antenna. our proposed algorithm can be implemented at the expense of a very limited hardware complexity increase. the snr gain of our new scheme can exceed 7 db, depending on channel conditions and adc specifications.
on the use of an adsl2+ testbed for video quality assessment. in this paper we share our experience in building an adsl video delivery test-bed. as a result, we are able to measure the impact of important parameters such as the loop length, the presence of background traffic and line protection against transmission errors on video quality. we show that although these access technologies promise a broadband pipe and low delay communication, a careful configuration of line parameters is paramount to achieve optimal access and is needed for the success of multimedia triple play (3p) services. we particularly analyze the delay, jitter, packet loss and bitrate consumption obtained from real adsl measurements. these results are an important step towards understanding the adequate deployment of such services. as a special case, we study the effect of repetitive noise on sdtv.
effective capacity maximization in multi-antenna channels with covariance feedback. the optimal transmit strategies of single-user multi-antenna systems with respect to average capacity maximization are well understood. however, the performance measure does neglect delay aspects which are important for higher layer design. therefore, we consider the maximization of the effective capacity in a single-user multi-antenna system with covariance knowledge. the optimal transmit strategy is derived and the properties as a function of the decay-rate requirement of the buffer occupancy are analyzed. in particular, we show that the larger the decay-rate requirement, the smaller the beamforming optimality range, i.e., the more spatial eigenmodes are activated. this behavior is illustrated by numerical simulations and explained by the channel hardening effect.
quality of service in 802.11 networks: modeling and experimental evaluation. this paper compares the theoretical and the experimental throughput of an 802.11 adhoc network implementing quality of service (qos) mechanisms. the theoretical model provides the throughput of each access category (ac) of each node in saturated and non-saturated traffic conditions. the experimental setup is described in detail to enable the reproduction of the presented measurements. this setup adopts the widely used multiband atheros driver forwireless fidelity (madwifi), which, however, provides the qos option for centralized operations only. hence, this study describes the adjustments to the madwifi source code that guarantee the control of the qos parameters in adhoc mode.
performance analysis of maximum likelihood decode and forward cooperative systems in rayleigh fading. the bit error rate (ber) performance analysis of maximum-likelihood (ml) based decode and forward (df) cooperative diversity systems has been a subject of considerable interest. exact analysis of ml-df transmission has been considered a challenging problem due to the nonlinear characteristic of the ml detector. in this paper, we provide exact expressions for the ber of ml-df cooperative systems employing a single relay. we extend these results to the case of multiple relays for the piecewise linear (pl) combiner, that is known to be a close approximation of the ml detector. this is done by using a novel theory of conditionally gaussian random variables. by expressing the ml decision variable in terms of functions of conditionally gaussian variables, exact expressions for the ber of the ml-df system are obtained. through simulation results, we verify the validity of the derived analytical expressions.
idc: an energy efficient communication scheme for connected mobile platforms. mobile platforms (e.g. laptops) offer ubiquitous network connectivity through its wireless communication interfaces, with most of usage models driven by always-on communication activities. however this in turn creates significant power challenges as the battery life is a critical resource for all mobile platforms. while the communication device itself consumes a relatively small portion of the total power, the impact of communication on the overall platform power is significant, due to the non-deterministic nature of the network traffic, which tends to keep the platform busy more than necessary. in this paper, we extensively investigate characteristics of various real-world network-centric workloads, e.g., voip, web browsing, etc., and their impact on the mobile platform in terms of power consumption and energy. based on the understandings, we propose, implement and evaluate an interrupt /dma (direct memory access) coalescing (idc) scheme at the wireless network interface card (nic). this scheme effectively reduces platform wakeups due to incoming network traffic, another advantage of the scheme is that it requires only nic modification at the receiving node, and is transparent to the user and the network. using a commercial nic with a laptop testing platform, we evaluate the power savings and performance impact of our proposed scheme. the measurements show that our scheme achieves significant platform power saving, around 25% of platform components, without impacting user experience.
a progressive chaotic mpeg-4 video encryption scheme for wireless networks. the intrinsic vulnerabilities of wireless networks place a great demand on efficient encryption techniques.with the proliferation of video streaming applications, the need for multimedia encryption techniques is becoming of utmost importance. this paper presents a scalable coding scheme for multimedia transmission over wireless networks. the proposed approach unifies the compression and encryption functionalities using the wavelet transform and chaotic functions to build up random permutations. the major advantage of our chaotic multimedia encryption process is that a client can access to multiple resolutions of the streamed video. these resolutions vary according to the security level of the client as well as the networking and processing capabilities. a set of simulations have also been carried out to assess the performance of the proposed coding scheme in terms of security, compression ratio, and error resilience.
an analytical model for the contention access period of the slotted ieee 802.15.4 with service differentiation. the ieee 802.15.4 standard is poised to become the global standard for low data rate, low energy consumption wireless sensor networks (wsn). by assigning the same sets of contention access parameters for all data frames and nodes, the contention access period (cap) of the slotted ieee 802.15.4 medium access control (mac) currently provides a priorityindependent channel access functionality and no service diiterentiation. several recent wsn applications such as wireless body sensor networks, however, may require service dilterentiation and traf6e prioritization support to accommodate potential highpriority traffic (e.g., alarms or emergency alerts). by allowing dilterent sets of access parameters and data frame lengths for differentpriority classes, this paper develops a markov-chain-based analytical model of the cap of the ieee 802.15.4 mac with service dilterentiatlon, under unsaturated traffic conditions. in particular, given two priority classes, our analytical model is used to evaluate the performance of a simple, yet eitective, contentionwindow-based service dilterentiation strategy, in terms of the resulting throughput, average frame service time and access priority for each priority class. the accuracy of the analytical model is validated by extensive ns-2 simulation.
degrees of freedom and sum rate maximization for two mutually interfering broadcast channels. in this paper, we derive a precise expression of spatial degrees of freedom (dof) for two mutually interfering broadcast channels (ifbc) as a function of arbitrary numbers of transmit antennas and users. the lower bound on the dof is obtained by showing that the zero-forcing solution suffices to achieve all the dof. also, the upper bound which coincides with the lower bound is shown using jafar's earlier work. from the derived result, we observe that disabling receive cooperation of the mimo interference channel causes the dof loss. additionally, we propose a linear precoding scheme for the ifbc by extending one designed for broadcast channels with an aim of maximizing the sum rate performance. we utilize the fact that the precoding matrices in stationary point always satisfy the zero-gradient condition. our result is confirmed through numerical simulations on the sum rate performance of the proposed precoding technique.
authentication in 802.11 lans using a covert side channel. we present a covert side channel technique that uses the 802.11 mac rate switching protocol as cover for covert authentication messages. covert authentication prevents an attacker from knowing when a user is authenticating and protects user credentials from malicious software attacks. similar to port knocking, a remote client sends authentication messages to an access point in order to access a protected service. the technique uses a one-time password algorithm to protect against replay attacks. we investigate how the covert side channel affects node throughput in mobile and non-mobile scenarios. we also investigate the covertness of the covert side channel using standardized entropy. the results show that the performance impact is minimal and increases slightly as the authentication frequency increases. we further show that we can authenticate with 100% accuracy with minimal impact on rate switching entropy.
fast connected dominating set construction in mobile ad hoc networks. the connected dominating set (cds) has been commonly used for routing and broadcast in mobile ad hoc networks (manets). considering the applications of manets, it is generally preferred that the cds protocol not only creates cds of small size, incurs less communication and computational overheads, adapts to the nodal mobility, but also generates cds as quickly as possible. unfortunately, none of the existing cds protocols possesses all of these desirable properties. in this paper, we propose an algorithm to rapidly grow a cds tree from an initiator. by incorporating this algorithm with the multi-initiator cds protocol, we have created the cds protocol for manets which enjoys all the aforementioned desirable properties. the simulation results validate that our proposed protocol achieves its design goals. in addition, an analytical model is provided that can accurately estimate the convergence time required by our proposed cds protocol.
positioning in multibeam geostationary satellite networks. the problem of local positioning for geostatic satellite networks operating at frequencies above 10ghz is studied in the present paper. based on angle of arrival (aoa) and received signal strength (rss) techniques, a simple yet effective algorithm is provided to estimate the position of a satellite terminal (st). since the accuracy of rss techniques can be affected by the propagation model, two operational conditions are examined, namely the clear sky and the raining one. this distinction becomes critical since modern satellite networks operate at frequencies above 10ghz, where rain attenuation constitutes the dominant factor impairing link performance and therefore causing uncertainty in the localization of a satellite station. both cases are studied and useful conclusions, concerning the probability of inaccurate location estimation due to rain, are drawn. moreover, the effect of various factors on the accuracy of localization is investigated through extended numerical results. finally, an algorithm that is able to identify the position of a st independently of the climatic conditions is provided.
a comprehensive analytical model for weighted fair queuing under multi-class self-similar traffic. weighted fair queueing (wfq) is a practical scheduling discipline for supporting differentiated quality-of-service (qos) in computer networks and communication systems. analytical models are important tools for system performance evaluation and resource optimization. however, there is not any comprehensive model reported in the open literature for analytically investigating the performance behaviors of wfq subject to multiple self-similar traffic flows. to fill this gap, this paper develops such a model and derives the upper bounds for the distributions of several important qos performance metrics including queue length, packet delay and loss of traffic flows in the wfq system. the comparison between analytical and simulation results using the traffic parameters obtained from real-world mpeg frame traces validates the accuracy of the developed model which can be used for investigating the performance behavior of wfq systems with multi-class self-similar traffic under realistic working conditions.
delay-tolerant distributed linear convolutional space-time code under frequency-selective channels. in cooperative communication networks, the performance of the distributed space-time code (dstc) will be severely degraded if the timing synchronization among relay nodes are not perfect. in this paper, we propose a systematic construction of the so called distributed linear convolutional space-time code (dlcstc) for multipath fading channels that does not require the synchronization assumption. we derive sufficient conditions on the code design such that the full cooperative and multipath diversities can be achieved under the minimum memory length constraint. then we design dlcstcs that both have the trace-orthonormality property and achieve the full diversity. we also study the diversity property of the dlcstc with suboptimal receivers. we show that the proposed codes can also achieve the full diversity for asynchronous cooperative communications with zf, mmse and mmse-dfe receivers under frequency-selective channels. finally, various numerical examples are provided to corroborate the analytical studies.
a lightweight skeleton construction algorithm for self-organizing sensor networks. although, current technology enables an inexpensive massive production of sensors, it raises numerous challenges on the protocols needed to interact with these sensors efficiently. several techniques have been proposed to address each of these challenges individually (i.e. localization, clustering, routing, aggregation ... etc). instead of solving each of these problems individually facing the same common challenges with each problem, we propose to construct what we call a network skeleton that is constructed immediately after network deployment and provides a topology that makes the network more tractable. the skeleton provides sensors with coarse localization information that enables them to associate their sensory data with the geographic location in which the data was measured. moreover, it promotes a geographic routing scheme that simplifies data communication across the network through skeleton sensors. by hypothetically tiling the deployment area using identical hexagons, the construction algorithm clusters sensors based on their locations into hexagons. skeleton sensors are chosen to be the closest sensors to the centers of these hexagons. simulation results show that the accuracy of the proposed protocol to establish the skeleton is sufficient to make the approach applicable for most wsn applications.
iteratively detected generalised mc ds-cdma using layered steeered space-time spreading. we present a novel tri-functional multiple-input multiple-output (mimo) scheme that intrinsically amalgamates space-time spreading (sts), the vertical bell labs layered space-time (v-blast) scheme and beamforming with generalised multicarrier direct sequence code division multiple access (mc ds-cdma). further system performance improvements can be attained by employing channel coding, where the source bits are serial-to-parallel converted to two layers, each constituted by a serial concatenation of an outer code amalgamated with a unity-rate code for the sake of improving the convergence behaviour of the proposed system. additionally, the convergence behaviour of the iteratively detected scheme is evaluated with the aid of extrinsic information transfer (exit) charts. we also propose a novel logarithmic likelihood ratio (llr) postprocessing technique for improving the iteratively detected system's performance. explicitly, after i=10 decoding iterations and employing an interleaver depth of dint=160, 000 bits, the proposed system supporting k=4 users attains a ber below 10-5 for eb/no values in excess of -2.8 db.
cooperation or not in mobile ad hoc networks: a mac perspective. in this paper, we investigate benefits of cooperative communication in mobile ad hoc networks (manets). cooperative communication as an effective way to mitigate channel impairments has attracted much attention, especially on the physical layer. however, without properly designed higher-layer protocols, the cooperation gain can decrease and even disappear, due to factors such as limited payload and nonnegligible overhead. a two-hop interference model from a medium access control (mac) point of view is proposed to study the performance of a cooperative network. analysis based on the model demonstrates that cooperation may not be beneficial when the number of blocked nodes increases. further, a busy-tone based cooperative mac scheme is presented to investigate the gain from cooperative communication and the relationship among influential factors. simulation results demonstrate that the node density and traffic load greatly impact the effectiveness of cooperative communication.
performance analysis of coherent free space optical communication systems with k-distributed turbulence. error performance of a coherent free space optical system with k-distributed turbulence is studied. a closed-form expression of the moment generating function for k-distributed turbulence is derived, and the moment generating function is used to obtain the exact error rates for binary phase shift keying (bpsk), bpsk with spatial diversity, as well as differential phase-shift keying. based on our analytical moment generating function expression, asymptotic error rates in large signal-to-noise ratio regions are obtained.
power allocation for improved df relayed ofdm transmission: the individual power constraint case. we consider an ofdm (orthogonal frequency division multiplexing) point to point transmission scheme improved by a relay. for each carrier, symbols sent by the source may be retransmitted during a second time slot by the relay, which is assumed to be of the decode-and-forward (df) type. for each relayed carrier the destination implements maximum ratio combining. assuming perfect csi (channel state information) knowledge the paper investigates the power allocation problem in order to maximize the rate offered by the scheme. compared to [1], the second time slot is better used. the source is allowed to transmit a new symbol during this second time slot when the relay is inactive. for this improved protocol, the optimization has been conducted for a sum power constraint and reported in [2]. the present paper is devoted to the case of individual power constraints at the source and at the relay. the theoretical analysis is illustrated by numerical results.
a system level algorithmic approach toward energy-aware sdr baseband implementations. wireless communication standards are continuously evolving and getting more diverse.this requires a wide variety of baseband implementations within a short time-to-market. besides, deepsub-micron technology significantly increases the design complexity andassociated cost. these yield a growing need forreconfigurable/programmable baseband solutions. implementing the wholebaseband functionality on programmable architectures, as foreseen in the tier-2 sdr, will become a must. however, the energy efficiency of sdr baseband platforms is unavoidably worse than the asic counterparts. this brings a challenging gap to bridge, which iseven broadening further in emerging high rate standards. with a holistic view, we advocate a system level algorithmic approach to bridge this gap. specifically, we propose to leverage the advantages(programmability) of sdr platforms to compensate for its disadvantages(energy efficiency). highly flexible baseband algorithms are designed to exploitthe abundant dynamics in the environment and the user requirements.in this way, the baseband can utilize the dynamics and substantially reduce the average energy consumption. in this paper, wepresent a design methodology and principles, illustrated with 3 representative case studies in hsdpa, wimax, and 3gpp lte.
multiple description coding based video multicast over heterogeneous wireless ad hoc networks. in this paper, we investigate how multiple description coding (mdc) can improve the user's satisfaction for a group of heterogeneous destinations for video multicast over wireless ad hoc networks. specifically, we explore the independent-description property of mdc with multiple paths to improve the user's satisfaction. in our approach, the assignment of multiple description (md) video is randomly done by a multicast source node. based on the assignment of md video, the multicast source constructs multiple multicast trees accordingly. simulation results demonstrate that our approach can achieve higher user's satisfaction regardless of the multicast group size.
low snr capacity of double-scattering mimo channels with transmitter channel knowledge. this paper investigates the capacity of double-scattering multiple-input multiple-output (mimo) channels in the low signal to noise ratio (snr) regime. we first derive analytical expressions for the two key low snr parameters; namely, the minimum required eb/n0 and wideband slope, assuming statistical channel state information (csi) at the transmitter. based on these results, we investigate the effect of transmit, scatter, and receive correlation. for the case of the double-scattering mimo keyhole channel, we then analyze the low snr capacity for different levels of transmit csi. we show that increased transmit csi leads to a reduced minimum required eb/n0.
deadline-guarantee-enhanced co-allocation for parameter sweep application in grid. in grid computing, deadline-guarantee is one of the most mentioned qos requirements for applications. however, the resource heterogeneity and the unpredictable workloads make it difficult for grid system to provide deadline-guarantee. in this paper, a novel approach is proposed to evaluate the deadline-guarantee of various co-allocation policies. by this approach, a hybrid-policy co-allocation model is also proposed to address the issue of deadline-constrained resource co-allocation in grid environments. the proposed model integrates multiple co-allocation policies to generate different co-allocation schemes, and selects the optimal deadline-guarantee scheme for grid applications. by this way, the hybrid-policy model combines the merits of different co-allocation policies, and overcomes the shortcomings of those policies. extensive simulations are conducted to verify the effectiveness and the performance of the proposed model in terms of deadline-miss rate. experimental results show that it can provide co-allocation scheme with enhanced deadline-guarantee as well as lower deadline-miss rate.
link-layer handover in earth-fixed leo satellite systems. using virtual node (vn) approach, network layer handover can be eliminated in earth-fixed leo satellite systems. however, handover in lower layers could result in significant data loss. in this work we propose a link-layer handover algorithm for vn-based satellite systems: virtual node handover algorithm (vn-ho). further, we propose to increment number of satellites per orbit in order to enable soft handover. on the modified system, which can be represented by multi-state virtual network (msvn) topology, we propose a soft handover algorithm (msvn-sho). relying on test results, msvn-sho is faster and smoother than vn-ho, despite a marginal increase in the cost.
on the performance of "compensation-based" and "greedy" scheduling policies in ieee 802.16 networks. the provision of quality of service (qos) is one of the primary requirements for ieee 802.16/wimax to become a reference technology for multimedia service delivery. this paper reports on the design and analysis of some channel-aware scheduling algorithms for downlink traffic delivery in a fixed point-to-multipoint wimax network. in particular, compensation-based and greedy approaches are compared according to their ability to provide qos and fairness to traffic flows when not working in ideal channel conditions. simulations highlight that the greedy philosophy fails to provide service differentiation, especially when users perceive heterogeneous channel conditions.
fast rfid counting under unreliable radio channels. a fast rfid counting algorithm with performance guarantee can be used as a fundamental building block for other more sophisticated rfid query protocols and operations. recently, kodialam et. al. propose various low-latency rfid counting schemes with accuracy guarantees [1], [2] based on a probabilistic counting approach which does not require explicit identification of individual tags. however, the proposed schemes all assume a perfect communication channel between the reader and the tags which is unlikely to be true in practice. on the contrary, as demonstrated by recent empirical measurement studies, the radio communications between an rfid reader and a set of seemingly "in-range" tags are rather non-deterministic and can even be unreliable at times due to varying radio conditions. in this paper, we extend the algorithms in [2] by taking into account the effects of radio channel unreliability. by modeling the spatial distribution of tags and the corresponding channel fading effects, we analyze the new requirements on the algorithm parameters used in [2] (e.g. number of reader polling cycles, frame-size and persistent probability) in order to achieve a desired level of estimation accuracy. another key observation is that, unlike the perfect channel case where one can indefinitely reduce the estimation error by increasing the number of reader polling cycles, with an unreliable radio channel, there is a lower-bound on the estimation error due to the inherent variation in the spatial distribution of the tags and the radio channel conditions. towards this end, we have derived an expression for this lower-bound. we also demonstrate the efficacy of our analytical results and their corresponding guarantees in estimation accuracy via an simulation study.
a provider-level reputation system for assessing the quality of spit mitigation algorithms. the prevention of spam over ip telephony (spit) is one of the greatest challenges for future large-scale deployments of voip telephony solutions. some useful information for detecting spit calls is only available at the caller's voip provider. recent approaches therefore suggest the signalling of such information among providers. however, there is currently no way for a receiving provider to assess the trustwortiness or the semantics of spit-related information received. our approach tackles this problem by applying a provider-level reputation system, based on spit tags assigned to outgoing sip messages by the caller's provider. the system provides an incentive to tag outgoing calls correctly, and it translates tags with arbitrary semantics into meaningful spit probabilities. we show analytically that our system significantly improves the receiving provider's assessment of spit tags.
a game theory approach to selection diversity in wireless ad-hoc networks. in this paper game theory is exploited to derive an optimal solution to the problem of cooperative data transmission based on distributed selection diversity in an ad hoc wireless network consisting of selfish nodes. first, a credit-based micro-economical model is proposed to manage node interaction; then, a transmission strategy maximizing node utility is derived. in the proposed strategy each node decides, in an autonomous fashion, whether and when transmitting data packets over a shared wireless channel. numerical results evidence that this approach can ensure both fairness in the access to a shared medium and excellent network efficiency. in particular, it offers an higher throughput level than other communication protocols implementing selection diversity in distributed multi-antenna systems.
optical broadcast-and-select network architecture with centralized multi-carrier light source. this paper proposes an optical broadcast-and-select network architecture with centralized multi-carrier light source (c-mcls). a large number of optical carriers/wavelengths generated by c-mcls are distributed to all edge nodes (ens), which select and modulate wavelengths to realize transmission. to utilize wavelength resources efficiently, we introduce a framework of wavelength allocation and selection (was). wavelength allocation is performed at a wavelength control server, while wavelength selection is done at each en according to wavelength allocation results. both static and dynamic schemes are adopted for was and their implementations are shown. by using fixed or tunable band pass filter and periodical arrayed waveguide grating demultiplexer, wavelengths are selected and utilized by ens in a static or dynamic manner. we evaluate network cost and performance of the proposed network. cost analysis and numerical results show that it offers greatly reduced cost compared to the conventional one when the number of required access wavelengths at en becomes large. we delineate its applicable areas through cost comparisons. blocking probabilities of static and dynamic schemes are analyzed to evaluate network performance. numerical results show that by choosing appropriate design parameters, the dynamic scheme offers about 25% increase in admissible offered load under the specified blocking probability, compared to the static scheme. this indicates that the dynamic scheme makes the proposed network more robust against traffic fluctuations.
coded pulse-position modulation for free-space optical communications. multilevel (q-ary, q >2) pulse-position modulation (q-ppm) with direct detection is a very popular transmission method for power-efficient free-space optical communication systems. the combination of q-ppm with error-control coding is an effective means to further improve power efficiency. in this paper, we study the application of the multilevel coding (mlc) paradigm to q-ppm transmission. in particular, we devise a powerful coded q-ppm scheme which is a simplified version of mlc and which we refer to as reduced-level mlc (rl-mlc). we show how to design and optimize rl-mlc for q-ppm when using constellation-constrained capacity as the pertinent figure of merit. furthermore, we provide simulative evidence that rlmlc with off-the-shelf low-density parity-check codes (ldpc) closely approaches its corresponding capacity limit. for 64-ppm, rl-mlc with only two levels achieves practically the same performance as that of bit-interleaved coded modulation with iterative decoding (bicm-id), which involves a more difficult design procedure.
a stochastic analysis of secure joint decision processes in peer-to-peer systems. central trusted instances as well as predefined security policies are not available in spontaneously established peer-to-peer environments. the former can be addressed by joint decision processes based on threshold cryptography. to compensate the latter, users can be involved directly in security-relevant decisions. in this case, minimizing the number of users involved is a necessary optimization goal to keep user-based joint decisions feasible for real-world deployment. still, a certain redundancy has to be introduced when taking into account users that do not provide their decision in a reasonable amount of time. in this paper we scrutinize different interaction schemes for joint decision processes. we develop stochastic models that describe the outcome subject to the number of users requested and the probability with which one user provides his decision in time. the derived closed-form representation of the models serves as a tool for governing the decision process, allowing for a real-time minimization of the number of users involved.
throughput/reliability tradeoffs in spread spectrum multi-hop ad-hoc wireless networks with multi-packet detection. wireless ad hoc networks with nodes capable of simultaneous multiple packet reception are considered. we focus on spread spectrum networks and address the relationship between the packet detection success, probability of the packet success over multiple hops, and asymptotic throughput capacity of the network in terms of power and bandwidth resources as well as the multi-packet detection capability of the nodes. in the second part of the paper we consider network with nodes employing partitioned code division multiple access (cdma) transmission and joint iterative reception. we study local communication in the network and derive a relationship between the probability of detection success and a fraction of the multiple access channel capacity that can be achieved at any communicating node.we use this result to demonstrate that near optimum throughput and reliable end-to-end communication can be achieved in the network with use of a practical detection method. finally, we present simulation results which demonstrate the advantage of partitioned cdma with iterative receivers over cdma with linear receivers in a network setting.
efficient resource discovery in mobile ad hoc networks. the highly dynamic nature of infrastructureless adhoc networks poses new challenges during resource discovery. in this paper, we propose a novel algorithm for resource discovery in mobile ad hoc networks called efficient resource-discovery (erd). when proposing this novel algorithm, our primary goal is to spread the most relevant resources and queries to the nodes in the network. the proposed algorithm erd is very efficient in dynamically ranking resources and queries based on their priority, selecting the transmission time, and determining how many resources and queries are to be transmitted. erd utilizes the network bandwidth in an optimal manner avoiding the spread of redundant data in the network, which otherwise can significantly overload the network with duplicate copies. we compare erd with periodic flooding and rank based broadcast (rbb) algorithms for mobile ad hoc networks. results show that erd outperforms both these algorithms significantly.
efficient algorithms for non-realtime video multicasting in wireless networks. this paper considers the problem of multiuser resource allocation for multicasting stream video traffic over a wireless time-division multiplexing system. most of previous work attempts to guarantee the reliability of data transmission for every user by limiting the multicast rate to the lowest instant sustainable rate of the worst user. such rate allocation schemes may seriously penalize users with better channel conditions. our proposed approaches attempt to exploit the multiuser diversity by dynamically selecting the rate which is not necessarily the lowest sustainable rate in order to maximize the total goodput. simulation results conclusively demonstrate that the proposed approaches can improve the wireless channel efficiency, especially when there are more users in the multicast group.
an automated signature generation approach for polymorphic worm based on color coding. in order to prevent worms from propagating rapidly, it is essential to generate worm signatures quickly and accurately. however, most of recent approaches can not generate accurate signatures for polymorphic worms in environments with noise. in this paper, we present a signature generation algorithm, namely ccsf (color coding signature finding), for polymorphic worms based on color coding. ccsf divides n sequences into m groups and each group contains 20 sequences. firstly, ccsf generates signatures for each group by adopting color coding and filters them. then all reserved signatures are clustered to get rid of redundant substrings. in this approach, signature can be generated without any fragment in environments with noise, and it can be used in ids (intrusion detection system) to detect polymorphic worm. we perform extensive experiments to demonstrate the effectiveness of our approach. experiment results show distinct advantages in generating accurate signatures over other existed approaches.
restless watchdog: monitoring multiple bands with blind period in cognitive radio systems. spectrum sensing, which monitors the spectrum activity, is studied for cognitive radio systems using multiple frequency bands with non-negligible band switching time (blind period). due to hardware limitation, it is assumed that only a subset of frequency bands can be monitored simultaneously. the problem of controlling the monitoring procedure is studied in the frameworks of dynamic programming (dp). system states and cost functions are defined. cost-to-go functions for dp are derived, simplified and approximated, based on which control policies are derived. numerical results are provided to demonstrate the proposed algorithms.
optimal fdl design for time-wavelength crossconnects and optical packet switches. time-wavelength-switched networks (twsns) provide a finer bandwidth granularity than traditional wavelength routing networks. in twsns, time on every wavelength is slotted and the crossconnects are configured to switch slots within a frame, and connections are assigned one or more slots per frame. fiber delay line (fdl) banks within the crossconnects can reduce the probability of connection blocking due to output slot contention. in this paper, we consider the optimal construction of an fdl bank with a limited number of recirculations through the fdls. specifically, given a frame consisting of m slots, an fdl bank of d fdls per output link, we develop a method to find a set of delay values d = {d1, d2, . . . dd} such that the set of achievable delays using no more than k recirculations through the bank is maximized. maximizing the number of achievable delays provides more flexibility in slot provisioning for connections, and is expected to decrease the blocking probability. we investigate the impact of the fdl configuration on a crossconnect's performance. our results show that the optimal fdl bank construction presented here achieves better blocking than previously considered fdl bank configurations. we also present a solution to the fdl bank design problem for an optical packet switch, and show through simulations that packet drop probability is considerably reduced for the optimal configuration.
degrees of freedom of cooperative mimo in cellular networks. in cellular networks, relays and/or mobiles can cooperate to improve the overall system performance. for example, once the transmission from a base station with multiple antennas is received by multiple nodes (relays and/or mobiles), they can exchange information to enhance the quality of intended signals while suppressing interference. such virtual multiple-input multiple-output (mimo) transmission is a key ingredient in hierarchical cooperation by özgür et al., which was shown to improve the throughput scaling of ad hoc networks greatly. in this paper, we analyze the achievable rate of such a cooperative mimo between a base station with multiple antennas and a node group. an antenna array with a fixed area has a limited number of degrees of freedom. we use a realistic channel model that can capture the effect of geometry of antenna arrays on the number of degrees of freedom. our achievable rate is limited by the product of the aperture of the antenna array in the base station and the angular spread, which is consistent with some known results on the limit of the degrees of antenna arrays.
security analysis of enterprise network based on stochastic game nets model. in this paper, we propose a novel modeling method, stochastic game nets (sgn), and use it to model and analyze the security issues in enterprise networks. firstly, the definition and modeling algorithm of stochastic game nets are given. and then we apply the stochastic game nets method to describe the attack and defense course in the enterprise networks successfully, and find a nash equilibrium. finally we analyze the confidentiality and integrity of the enterprise network quantificationally based on the model. the method can also be applied to other areas with respect to a game.
cross-layer design for energy conservation in wireless sensor networks. wireless sensor networks (wsns) require energy-efficient protocols to improve the network lifetime. in this work, we adopt a cross-layer strategy that considers routing and mac layers jointly. at the routing layer, we propose balancing the traffic through the wsn. we show that sending the traffic generated by each sensor node through multiple paths instead of using a single path allows significant energy conservation. on the other hand, at the mac layer, we propose to control the retry limit of retransmissions over each wireless link. we show that by efficiently adjusting the retry limit for each link, further energy conservation can be achieved, improving thus the network lifetime. a new analytical model for the joint optimization system is complemented by simulations in order to quantitatively evaluate the benefits of our proposal.
selective channel inversion precoding for the downlink of mimo wireless systems. in this paper a novel channel inversion (ci) precoding scheme is introduced for the downlink of multiple input multiple output (mimo) systems. the proposed technique outperforms conventional ci by exploiting some of the consequential inter-channel interference (ici). it achieves this by applying partial channel inversion such that the constructive part of ici is preserved and exploited while the destructive part is eliminated by means of ci precoding. by doing so, the effective signal to interference-plus-noise ratio (sinr) delivered to the mobile unit (mu) receivers is enhanced, without the need to invest in additional transmitted signal power at the mimo base station (bs). the trade-off to this achievement is a minor increase in the complexity of the bs processing. the presented theoretical analysis and simulations show that due to the sinr enhancement, significant performance gains are offered by the proposed mimo precoding technique compared to its conventional counterpart.
adaptive mixture-based neural network approach for higher-level fusion and automated behavior monitoring. a novel adaptive mixture-based neural network is presented for exploiting track data to learn normal patterns of motion behavior and detect deviations from normalcy. we have extended our prior approach by introducing multidimensional probability density components to represent class density using an adaptive mixture of such components. the number of components in the adaptive mixture algorithm, as well as the values of the parameters of the density components, is estimated from the data. the network utilizes a recursive version of the expectation maximization (em) algorithm to minimize the kullback-leibler information metric by means of stochastic approximation combined with a rule for creation of new components. learning occurs incrementally in order to allow the system to take advantage of increasing amounts of data without having to take the system offline periodically to update models. continuous incremental learning enables the models of normal behavior to adapt well to evolving situations while maintaining high levels of performance. in addition, the adaptive mixtures neural network classifies streaming track data as normal or deviant. these capabilities contribute to higher-level fusion situational awareness and assessment objectives by enabling a shift of operator focus from sensor monitoring and activity detection to assessment and response. our overall motion pattern learning approach learns behavioral patterns at a variety of conceptual, spatial, and temporal levels to reduce massive amounts of track data to a rich set of information regarding operator field of regard that supports rapid decision-making and timely response initiation.
the multicell processing capacity of the cellular mimo uplink channel under correlated fading. in the information-theoretic literature, it has been widely shown that multicell processing is able to provide high capacity gains in the context of cellular systems and that the per-cell sum-rate capacity of multicell processing systems grows linearly with the number of base station (bs) receive antennas. however, the majority of results in this area has been produced assuming that the fading coefficients of the mimo subchannels are totally uncorrelated. in this direction, this paper investigates the ergodic per-cell sum-rate capacity of the mimo cellular multiple-access channel under correlated fading and multicell processing. more specifically, the current channel model considers rayleigh fading, uniformly distributed user terminals (uts) over a planar cellular system and power-law path loss. furthermore, both bss and uts are equipped with correlated multiple antennas, which are modelled according to the kronecker model. the per-cell sum-rate capacity closed form is derived using a free probability approach and numerical results are produced by varying the cell density of the system, as well as the level of correlation.
rate distortion optimization for mesh-based p2p video streaming. this paper addresses the problem of optimal rate allocation for video streaming in a multi-path peer-to-peer mesh network. we present a distributed rate allocation algorithm that minimizes the total rate distortion among receiving peers. the scheme assumes that video streams can be transcoded/requantized at intermediate peers. we deploy a double pricing solution that simultaneously incorporates both the network and the relay constraints. we compare it with a single pricing solution where the relay constraint is applied only after all the communicating peers have converged. our simulation shows that the double pricing solution consistently achieves a smaller aggregate distortion for all peers in comparison to the single pricing solution and thus achieves higher video quality.
efficient utilization of error protection techniques for transmission of data-partitioned h.264 video in a capacity constrained network. we propose an efficient error protection technique for data-partitioned h.264 video in a capacity constrained network. our scheme maximizes video quality by choosing the optimal point in the application layer and medium access control (mac) layer redundancy. we have shown that, in a capacity constrained network and highly lossy environment, neither forward error correction (fec) nor retransmissions alone can result in optimum performance. instead, it is the combination of these two techniques that effectively reduces the overall loss.
application layer signaling for proactive handoff management in all-ip wireless networks. recently, all-ip wireless systems have been standardized under the ip multimedia subsystem (ims) framework to support next generation value added mobile services. in all-ip networks, multiple base stations connect to ims policy servers through ip-based access gateways. as users move from one access gateway area into another, the corresponding access gateways initiate signaling flows for qos authorization toward the ims policy server. depending on the service, the policy function may contact one or more application servers resulting in variable and prolonged signaling delays upon each handoff. such delays can be of the order of seconds, depending on the specific system design and whether the user is roaming, which maybe critical to the quality of real time services. in this paper, we propose a novel proactive signaling method in the application layer that conveys authorization delay constraints from the ims to the radio layer and thus mitigates the effects of variable signaling delay. our method is practically relevant as it uses the already established mechanisms of authentication and authorization signaling via standardized interfaces and protocols. using the opnet simulator, we demonstrate that our scheme is also scalable, as its corresponding signaling overhead is upper bounded to approximately double the handoff rate.
markov modeling for data block transmission of ofdm systems over fading channels. orthogonal frequency-division multiplexing (ofdm) is a promising technique for high data rate wireless access networks. modeling ofdm systems for the analysis of network performance is very challenging, because of the complexity of the modulation/coding schemes and the wideband wireless channel fading in both the time and frequency domains. in this paper, a novel packet-level model based on a two-dimensional markov chain is proposed for ofdm systems over time-varying (nakagami-m fading), frequency-selective channels. first, the level cross rate (lcr) of the amplitude of channel frequency response is derived. then, we develop a methodology to map the received signal-to-noise ratio (snr) of the subcarriers into a finite number of channel states with different packet error rate (per). the proposed model presents directly the performance of the ofdm systems and incorporates the time- and frequency-domain correlations of the fading channels. channel coding is also considered in evaluating per. simulations have verified that the statistics of the ber presented by our model are consistent with those of waveform simulations. the proposed markov model can be an effective tool to study and optimize upper-layer protocols of ofdm-based wireless networks, via both analysis and simulation.
revealing social networks of spammers through spectral clustering. to date, most studies on spam have focused only on the spamming phase of the spam cycle and have ignored the harvesting phase, which consists of the mass acquisition of email addresses. it has been observed that spammers conceal their identity to a lesser degree in the harvesting phase, so it may be possible to gain new insights into spammers' behavior by studying the behavior of harvesters, which are individuals or bots that collect email addresses. in this paper, we reveal social networks of spammers by identifying communities of harvesters with high behavioral similarity using spectral clustering. the data analyzed was collected through project honey pot, a distributed system for monitoring harvesting and spamming. our main findings are (1) that most spammers either send only phishing emails or no phishing emails at all, (2) that most communities of spammers also send only phishing emails or no phishing emails at all, and (3) that several groups of spammers within communities exhibit coherent temporal behavior and have similar ip addresses. our findings reveal some previously unknown behavior of spammers and suggest that there is indeed social structure between spammers to be discovered.
detecting malicious packet dropping in the presence of collisions and channel errors in wireless ad hoc networks. detecting malicious packet dropping is important in ad hoc networks to combat a variety of security attacks such as blackhole, greyhole, and wormhole attacks. we consider the detection of malicious packet drops in the presence of collisions and channel errors and describe a method to distinguish between these types. we present a simple analytical model for packet loss that helps a monitoring node to detect malicious packet dropping attacks. the model is analyzed and evaluated using simulations. the results show that it is possible to detect malicious packet drops in the presence of collisions and channel errors.
performance of voip with dccp for satellite links. we present experimental results for the performance of selected voice codecs using the datagram congestion control protocol (dccp) with tcp-friendly rate control (tfrc) congestion control mechanism over a satellite link. we evaluate the performance of both constant and variable data rate speech codecs (g.729, g.711 and speex) for a number of simultaneous calls, using the itu e-model and identify problem areas and potential for improvement. our experiments are done on a commercial satellite service using a data stream generated by a voip application, configured with selected voice codecs and using the dccp/ccid4 linux implementation. we analyse the sources of packet losses which are a main contributor to reduced voice quality when using ccid4 and additionally analyse the effect of jitter which is one of the crucial parameters contributing to voip quality and has, to the best of our knowledge, not been considered previously in the published dccp performance results. we propose modifications to the ccid4 algorithm and demonstrate how these improve the voip performance, without the need for additional link information other than what is already monitored by ccid4 (which is the case for quick-start). we also demonstrate the fairness of the proposed modifications to other flows. we identify the additional benefit of dccp when used in voip admission control mechanisms and draw conclusions about the advantages and disadvantages of the proposed dccp/ ccid4 congestion control mechanism for use with voip applications.
upper bounding the deletion channel capacity by auxiliary memoryless channels. we present two upper bounds on the capacity of the binary deletion channel. both bounds are obtained by providing the transmitter and the receiver with genie-aided information on suitably-defined random processes. since the closed-form expressions of the proposed bounds involve infinite series, we also introduce provable inequalities that lead to more manageable results. for most values of the deletion probability, these bounds improve the existing ones and significantly narrow the gap with the available lower bounds.
enhanced milsa architecture for naming, addressing, routing and security issues in the next generation internet. milsa (mobility and multihoming supporting identifier locator split architecture) [1] has been proposed to address the naming and addressing challenges for ngi (next generation internet). we present several design enhancements for milsa which include a hybrid architectural design that combines "core-edge separation approach" and "split approach", a security-enabled and logically oriented hierarchical identifier system, a three-level identifier resolution system, a new hierarchical code based design for locator structure, cooperative mechanisms among the three planes in milsa model to assist mapping and routing, and an integrated milsa service model. the underlying design rationale is also discussed along with the design descriptions. further analysis addressing the irtf (internet research task force) rrg (routing research group) design goals [9] shows that the enhanced milsa provides comprehensive benefits in routing scalability, traffic engineering, mobility and multihoming, renumbering, security, and deployability.
low energy and low latency in wireless sensor networks. it is widely known that in wireless sensor networks (wsn), energy efficiency is of utmost importance. as a result, a common protocol design guideline has been to trade off some performance metrics such as throughput and delay for energy. this has also gone well in line with many applications for wsn. however, there are other applications with real-time constraints, such as those involved in surveillance or control loops, for which wsn still need to be energy efficient but also need to provide better performance, particularly latency. this paper presents a wsn cross-layer design approach involving the physical, mac, and network layers that not only preserves the energy efficiency of current alternatives but also coordinates the transfer of packets from source to destination in such a way that latency and jitter are improved considerably. our simulations show how lemr (latency, energy, mac and routing), the proposed protocol, outperforms the well-known tmac and s-mac protocols in both performance metrics.
tailoring elb for multi-layered satellite networks. owing to the diverse geographical distributions of users, multi-layered satellite networks tend to exhibit high variances causing traffic concentrations at particular satellites to increase drastically. this results in high packet drop rates and severe degradation of quality of service (qos). the explicit load balancing (elb) scheme was developed to address these issues in low earth orbit (leo) satellite networks by having the satellites, which experience heavy traffic, redirect a portion of the traffic via alternative paths. to cope with network congestion (over a single layer) and for better traffic distribution, multi layer satellites were proposed. in this paper, we propose an efficient traffic distribution scheme for multi-layered satellite networks based on elb in which we extend the range for exchanging the traffic-load information for achieving further reductions in packet drop rates. we also present an enhanced technique for efficiently computing the detouring ratio. the effectiveness of the envisioned approach is validated via simulations.
interference-aware location estimation in cellular ofdm communications systems. in this paper, we consider location estimation algorithms using cellular orthogonal frequency division multiplexing (ofdm) communications systems. in the classical approach the mobile station (ms) determines time difference of arrival (tdoa) information from the received signals of at least three bases stations (bss). with these tdoas the location of the ms is estimated. however, only at the cell edge a good reception of several bss is ensured. especially for future systems targeting a frequency re-use of one, interference is a limiting factor. hence, in the inner cell it is difficult to detect out-of-cell bss with sufficient quality. therefore, we propose an interference cancellation scheme to improve the performance in these critical situations for tdoa positioning. simulation results for a 3gpp- lte system show the ability of this approach to increase the accuracy and to extend the coverage of the overall location estimation.
multi-dimensional nested lattice quantization for wyner-ziv coding. in this paper, we consider the coding of an independent and identically distributed (i.i.d.) gaussian source with side information available only at the decoder in the form of a noisy version of the source to be encoded. this problem is known as wyner-ziv coding in literature. in this paper, we propose concrete implementation by using the strategy of multi-dimensional nested lattice quantization (nlq). by investigating various lattices in the dimensions considered, we give some analysis on how lattice properties affect performance. we also propose a method on choosing good coarse lattices in multiple dimensions. by introducing scale factors, we examine the relationship between distortion and scale factor for various rates. as dimension increases to eight and twenty-four, we obtain distortion performance close to the wyner-ziv limit. meanwhile, our scheme is simple without causing long delay and large storage, which is suitable for sensor networks.
prototyping of a pass-band chaos-based cdma system in fpga technology. this paper presents the theoretical analysis, design and fpga implementation of a pass-band chaos-based cdma system. the system uses a digital modulation technique called chaos-phase-shift-keying (cpsk) in a complex form, where chaotic sequences are used for spreading digital messages. conventional multi-rate signal processing techniques are employed for carrier modulation and demodulation, which changed the structure of the theoretical model of the analysed system. the model of a pass-band additive white gaussian noise channel is also constructed. the system is implemented in altera stratix ii ep2s180 dsp development board. the fpga design flow is carried out using alter dsp builder integrated into mathworks simulink algorithm development environment. the ber characteristics obtained on the prototype and simulation confirmed the theoretical findings.
trust-based data disclosure in sensor networks. in sensor networks, privacy can be addressed in different levels of the network stack and at different points of the information flow. this paper presents an application level scheme for controlling information disclosure at the points of data capture. the scheme includes a trust model for facilitating in-network privacy decisions. the trust model exploits the pre-deployment knowledge on the network topology and the information flows, and combines aspects from alternative approaches on trust establishment on common evaluation metrics, in order to allow for flexibility in the trust establishment process. the trust assigned to each data requestor is used to determine if the data or only a sample of it will be disclosed, or if the request will be rejected. the scheme allows the use of various mechanisms, including negative surveys, for publishing samples of data to partially trusted requestors. the proposed scheme has been validated through simulation. the results and analysis demonstrate its effectiveness in managing trust relationships and data disclosure operations.
algebraic reduction for the golden code. in this paper we introduce a new right preprocessing method for the decoding of 2×2 algebraic space-time codes, called algebraic reduction, which exploits the multiplicative structure of the code. the principle of the new reduction is to absorb part of the channel into the code, by approximating the channel matrix with an element of the maximal order of the code algebra. we prove that algebraic reduction attains the receive diversity when followed by a simple zero-forcing (zf) detection. simulation results for the golden code show that using minimum mean squared error generalized decision feedback equalization (mmse-gdfe left preprocessing), algebraic reduction with simple zf detection has a loss of only 3db with respect to optimal decoding.
joint power allocation and scheduling of multi-antenna ofdm system in broadcast channel. this paper considers the general multiuser down-link scheduling problem and power minimization with multiuser rate constraints. we present joint user selection algorithms for dpc, zf-dpc, zfbf and tdma for multi-antenna ofdm system in broadcast channels, and we also present a practical waterfilling solution in this paper. by the selected users with the consideration of fairness, we derive the power optimization algorithm with multiuser rate constraints. simulation results show that the presented user scheduling algorithms and power minimization algorithms can achieve good power performance. meanwhile, simulation results also show that the scheduling algorithm can guarantee fairness.
matched spectral-null code with run-length limitation for optical recording channels. high track-density recording and multi-layer recording have been investigated for large capacity optical recording discs. in this case, the recorded data will be reproduced under the low signal-to-noise ratio (snr) condition due to crosstalk from the adjacent tracks or the other layers, and robust data detection will be required. in this paper, a novel matched spectral-null (msn) code providing the property of run-length limitation (rll) was described considering the optical recording channels. trellis coded partial response maximum likelihood (tcprml) employing the msn code with rll was also proposed for the data detection method enhancing the minimum euclidian distance. the detection performance was estimated through the simulation model, which emulates the optical recording channels based on the blu-ray disc (bd) specification.
successive par reduction in (mimo) ofdm. a successive scheme for par reduction in (mimo/ siso) ofdm is presented, where k (parallel/consecutive) ofdm frames are treated jointly. employing reed-solomon codes further candidate ofdm frames are generated and assessed successively; the currently best k are selected for possible transmission. the procedure stops if (i) all k best frames stay below a given tolerable par limit, or (ii) the maximally allowed number of candidates is exhausted. thereby complexity compared to other par reduction schemes can be reduced significantly. analytical derivations show that for par limits in the region of the "critical par" value ξcrit = log(d), with d being the number of carriers, the average number candidates is close to euler's number e = 2.71828..., which is particularly low.
cross-layer optimized routing for wireless sensor networks using dynamic programming. in this paper, we study the joint optimization problem on channel coding, power allocation, and route planning in wireless sensor networks (wsn) using dynamic programming (dp). each sensor node has multiple antennas and applies orthogonal space time block codes (ostbc) in order to improve the transmission reliability. a decode-and-forward protocol is adopted to relay the signals. the objective function is to determine the packet forwarding route that has the maximum successful transmission rate (str) subject to the source-to-destination (s-d) energy consumption constraint. specifically, we cast this energy and quality-of-service (qos) aware packet forwarding problem into the framework of dp, such that adaptive power allocation can be jointly realized at each sensor node. state space partition techniques and state aggregation approximation architecture are introduced to derive the value function. simulation results show that the proposed protocols significantly outperform classical routing algorithms, especially when the energy constraint becomes stringent.
a dynamic ultrapeers selection policy for collaborative virtual environments over mobile ad hoc networks. with the rapid developments in technology, mobile collaborative virtual environments (mcves) have become an unavoidable application in area such as military training, health, and education. unfortunately, as 1the number of users grows, nodes may easily become overloaded as they process messages from other nodes. most of the existing ultrapeer systems are confined to wired network environments and thus preclude collaboration while users are mobile. in this paper, a gnutella ultrapeer system gus to improve the performance of mcves is proposed. in manets, a reconfiguration process is frequently required in the ultrapeer system due to node mobility. in addition, the number of ultrapeers must be well dispersed throughout the overlay network. to address these problems, we adopt a novel selection approach in which we create a hierarchical overlay network based on the cve profile in order to reflect the user's interest in the virtual environment. we then perform a dynamic ultrapeer election based on a score measurement that combines the network behaviors and the user behaviors in the ve. thus, not every change in the network topology will entail an immediate ultrapeer system reconfiguration. simulation results indicate that the proposed gus is more efficient than popular ultrapeer topologies in several important scenarios.
a multihoming support scheme with localized shim protocol in proxy mobile ipv6. this paper proposes an enhanced multihoming support scheme based on combining ideas from both the shim and proxy mobile ipv6 (pmipv6) protocols. the proposed scheme not only resolves the multihoming support problems with the current pmipv6, but also provides mobility support to the shim protocol. in the proposed scheme, the shim protocol is locally used between a multihomed mobile node (mn) and the local mobility anchor (lma) in the pmipv6 domain. a flow distribution scheme with the shim locator preferences is proposed to provide flexible multihoming. simulation results show that the pmipv6 combined with the localized shim protocol can support both mobility and multihoming efficiently.
salsa: super-peer assisted live streaming architecture. in p2p live streaming, free-riders which do not upload data but only download them are still present. since a greater number of viewers can generate more profit, the streaming server wants to serve the free-riders also. in this paper, we have proposed a novel p2p live streaming system, called super-peer assisted live streaming architecture (salsa). in salsa, super-peers, which have high upload bandwidth and serve many free-riders, are eligible to receive an incentive reward that is the ability to watch high quality videos. the server places high-quality-view-tickets at auction to make the super-peers serve free-riders more efficiently. we have proposed novel auction mechanisms and a heuristic algorithm. the simulation results showed that the proposed scheme has comparable performance to the optimal form and are able to differentiate the super-peers' video quality commensurate with their contribution level.
energy savings for wireless terminals through smart vertical handover. this paper optimizes handover decisions between wlan (802.11) and wimax (802.16e) standards, for both uplink and downlink data transmission. the handover becomes part of a cross-layer approach controlling several knobs (air interface parameters or platform settings) in order to reduce the terminal power consumption. the first step is to derive detailed power and performance models for both standards, in order to correctly evaluate the opportunity of a handover. this includes channel fading fluctuations, extraction of mac-level behavior and packet error rates, and overall power consumption from the wireless platform. such models enable first optimal single-standard power-throughput trade-offs, that will be used as reference points before adding the handover possibility in order to assess its specific gain. the second step is the design of a handover controller that selects the network with the lowest expected power for the required rate. the proposed mechanism is based on regular scanning of both networks. it computes the expected energy in order to send a given amount of data over each network, taking handover cost into account, and selects the most appropriate one. based on a software-defined radio platform and a typical channel coherence time of one second, simulations demonstrate a power saving factor up to 2.5 as a function of the scenario, compared to a single-standard system that is already cross-layer optimized. this illustrates the large gain that is available, besides the handover advantage in terms of improved connectivity.
differential (de)modulation for orthogonal bi-pulse noncoherent uwb. in this paper, we propose a novel noncoherent uwb (de)modulation system, which uses a pair of orthogonal pulses to convey information symbols. same as the original noncoherent uwb [1], our approach remains operational even without timing and channel estimation. moreover, due to the orthogonality between the received waveforms of the pulse pair, our approach results in a differential demodulator. this means that our approach does not need viterbi decoding which is required by [1], even in the presence of timing error. simulations are also carried out to corroborate our theoretical analysis.
maximizing the sum rate in symmetric networks of interfering links. we consider the power optimization problem of maximizing the sum rate of a symmetric network of interfering links in gaussian noise. all transmitters have an average transmit power constraint, the same for all transmitters. this problem has application to dsl, as well as wireless networks. we solve this nonconvex problem by indentifying some underlying convex structure. in particular, we characterize the maximum sum rate of the network, and show that there are essentially two possible states at the optimal solution depending on the cross-gain (√ε) between the links, and/or the average power constraint: the first is a wideband (wb) state, in which all links interfere with each other, and the second is a frequency division multiplexing (fdm) state, in which all links operate in orthogonal frequency bands. the fdm state is optimal if the cross-gain between the links is above 1/√2. if √ε < 1/√2, then fdm is still optimal provided the snr of the links is sufficiently high. with √ε < 1/√2, the wb state occurs when the snr is low, but as we increase the snr from low to high, there is a smooth transition from the wb state to the fdm state: for intermediate snr values, the optimal configuration is a mixture, with some fraction of the bandwidth in the wb state, and the other fraction in the fdm state. we also consider an alternative formulation in which the power is mandated to be frequency flat. in this formulation, the optimal configuration is either all links at full power, or just one link at full power. in this setting, there is an abrupt phase transition between these two states.
an m-sequence based steganography model for voice over ip. differing from applying steganography on storage cover media, steganography on voice over ip (voip) must often delicately balance between providing adequate security and maintaining low latency for real-time services. this paper presents a novel real-time steganography model for voip that aims at providing good security for secret messages without sacrificing real-time performance. we achieve this goal by employing the well-known least-significant-bits (lsb) substitution approach to provide a reasonable tradeoff between the adequate information hiding requirement (good security and sufficient capacity) and the low latency requirement for voip. further, we incorporate the m-sequence technique to eliminate the correlation among secret messages to resist the statistical detection based on the fact that the distribution of the lsbs in the stego-speech is not uniform and to provide a short-term security protection of secret messages. to accurately recover secret messages at the receiver side, we design a synchronization mechanism based on the rsa key agreement and the synchronized sequence transmission using techniques of the protocol steganography, which can effectively enhance the flexibility of the covert communication system and be extended to other steganography schemes based on real-time systems. we evaluate the effectiveness of our model with itu-t g.729a as the codec of the cover speech in stegtalk, a covert communication system based on voip. the experimental results demonstrate that our technique provides good security and transparency for transmitting secret messages while adequately meeting the real-time requirement of voip.
evaluation of the extremely low block error rate of irregular ldpc codes. in this paper, we attempt to evaluate irregular ldpc code performance at the high snr region using the importance sampling (is) approach in conjunction with primary-trapping-set identification. results have indicated that our proposed is scheme can produce speed-up gains up to 3.9 × 109 times compared with monte carlo simulations.
reduced feedback designs for sdma-ofdma systems. in sdma-ofdma wireless communication systems, the feedback load increases with the number of users, subcarriers and antennas in the cell. in this paper, we propose two efficient reduced feedback algorithms by selecting the clusters at the user side. for each cluster, we select the users according to their norm and their orthogonality. we evaluate the performance of the user selection algorithms considering the quantization effect. we also design a specific codebook design to quantize csi for the proposed criterion.
energy-efficient itinerary planning for mobile agents in wireless sensor networks. compared to conventional wireless sensor networks (wsns) that are operated based on the client-server computing model, mobile agent (ma) systems provide new capabilities for energy-efficient data dissemination by flexibly planning its itinerary for facilitating agent based data collection and aggregation. it has been known that finding the optimal itinerary is np-hard and is still an open area of research. in this paper, we consider the impact of both data aggregation and energy-efficiency in sensor networks itinerary selection, we propose an itinerary energy minimum for first-source-selection (iemf) algorithm, as well as the itinerary energy minimum algorithm (iema), the iterative version of iemf. our simulation experiments show that iemf provides higher energy efficiency and lower delay compared to existing solutions, and iema outperforms iemf with some moderate increase in computation complexity.
complexity reduced soft-in soft-out sphere detection based on search tuples. depth-first tree search algorithms provide a promising approach to solve the detection problems in mimo systems. realizations like the list sphere detector (lsd) or the single tree search (sts) enable near max-log detection at reduced but still high complexity. in this paper we show how the complexity of list sphere detection can be significantly reduced by mmse preprocessing in combination with a novel unbiased and separated candidate handling. therefor, we propose an extension of the lsd by search tuples. without any performance loss, the resulting tuple search (ts) algorithm enables major reduction of sphere sizes and enables moreover a detection with flexible performance respectively complexity. avoiding loss of useful status information, caused by unbiased mmse preprocessing or small candidate storage, is provided by a novel matched candidate determination, leading also to reduced hardware complexity. the combination of these methods enable high-performance soft-out detection at very low complexity. more specifically, this enables a performance improvement up to 1 db at half the complexity of common lsd or sts algorithms.
speech quality while roaming in next generation networks. in ngns, handovers between different wireless access technologies provide seamless roaming during voice calls. the resulting speech quality depends on the audio bandwidth of the speech codecs used in the respective networks, as well as on degradations resulting from the handover, coding, and packet loss. we present the results of four listening experiments where speech quality is quantified as a function of network and codec characteristics, and compare them to estimations obtained from instrumental models. the results show when and under which circumstances a network handover and/or codec changeover should be scheduled in order to obtain better speech quality. this is important for the development of high-quality roaming strategies.
idle channel time estimation in multi-hop wireless networks. this paper presents a theoretical estimation for idle channel time in a multi-hop environment. idle channel time is the time proportion of a node during which the channel state is idle. thus, it can be used to evaluate the available bandwidth. major related work considers a cross-layer model, where the idle channel time measure is available at the mac layer, but it is rarely implemented. furthermore, this measure is not very flexible: it cannot differentiate the traffic's priorities and it works under the hypothesis that flows are strictly policed. estimating instead of measuring the idle channel time prevents these drawbacks. this estimation is computed in three steps by (1) calculating the idle channel time bounds, (2) evaluating the probability of a given idle channel time value, (3) computing the expected value of this distribution and deducing the average idle channel time. we show by simulation that our estimation is accurate.
combining hidden markov models for improved anomaly detection. in host-based intrusion detection systems (hids), anomaly detection involves monitoring for significant deviations from normal system behavior. hidden markov models (hmms) have been shown to provide a high level performance for detecting anomalies in sequences of system calls to the operating system kernel. although the number of hidden states is a critical parameter for hmm performance, it is often chosen heuristically or empirically, by selecting the single value that provides the best performance on training data. however, this single best hmm does not typically provide a high level of performance over the entire detection space. this paper presents a multiple-hmms approach, where each hmm is trained using a different number of hidden states, and where hmm responses are combined in the receiver operating characteristics (roc) space according to the maximum realizable roc (mrroc) technique. the performance of this approach is compared favorably to that of a single best hmm and to a traditional sequence matching technique called stide, using different synthetic hids data sets. results indicate that this approach provides a higher level of performance over a wide range of training set sizes with various alphabet sizes and irregularity indices, and different anomaly sizes, without a significant computational and storage overhead.
interferer classification, channel selection and transmission adaptation for wireless sensor networks. wireless sensor networks (wsns) are being increasingly deployed in office blocks or residential areas for commercial applications, such as home automation, meter reading, surveillance, among others. at these locations, the wsns experience interference in the 2.4ghz unlicensed band due to wireless lans (wlans) and commercial microwave devices, leading up to 92% packet losses. in this paper, an algorithmic framework is proposed, that allows the sensor nodes to identify the type of the interferer and its operational channel, so that the former may adapt their own transmission to reduce packet losses in the network. our proposed interference classification approach comprises of an (i) offline measurement of the spectral characteristics of the wlan and microwave devices to obtain a reference spectrum shape, and (ii) matching the observed spectral pattern during network operation with the stored reference shape the knowledge of the interferer characteristics is then leveraged by the sensor nodes to decide their transmission channel, packet scheduling times and sleep-awake cycles. results reveal that our approach incurs up to 50-70% energy savings in the wsn, by reducing interference related packet losses.
a fluid background traffic model. background traffic has a significant impact on the behavior of network services and protocols. however, a detailed model of the background traffic can be extremely time consuming in simulation. in this paper, we extend our previous hybrid model that combines fluid and packet-oriented characterization of network traffic for a realistic representation of the background traffic on internet. in particular, we get rid of some unrealistic assumptions in the hybrid model, by adding an acknowledgment scheme to correctly capture the mutual influence of fluid tcp flows on network queues, and by applying the poisson pareto burst process (ppbp) model to describe the long-range dependencies of the internet traffic. experiments show that our fluid background traffic model can capture similar level of realism as the traditional packet-oriented approach.
problem-specific encoding and genetic operation for a multi-objective deployment and power assignment problem in wireless sensor networks. wireless sensor networks deployment and power assignment problems (dpaps) for maximizing the network coverage and lifetime respectively, have received increasing attention recently. classical approaches optimize these two objectives individually, or by combining them together in a single objective, or by constraining one and optimizing the other. in this paper, the two problems are formulated as a multi-objective dpap and tackled simultaneously. problem-specific encoding representation and genetic operators are designed for the dpap and a multi-objective evolutionary algorithm based on decomposition (moea/d) is specialized. the multi-objective dpap is decomposed into many scalar subproblems which are solved simultaneously by using neighborhood information and network knowledge. simulation results have shown the effectiveness of the proposed evolutionary components by providing a high quality set of alternative solutions without any prior knowledge on the objectives preference, and the superiority of our problem-specific moea/d approach against a state of the art moea.
spectrum balancing algorithms for power minimization in dsl networks. spectrum balancing (sb) techniques optimize transmission and can significantly improve digital subscriber lines (dsl) services. in the literature, the dsl system optimization is typically formulated as a rate maximization problem. however, there is an increasing interest in minimizing the considerable amount of power consumed by telecommunication networks. few works in the sb literature have explored algorithms for power minimization. it is known that some existing solutions for rate maximization can be converted into power minimization algorithms. this relation has not been fully explored and, consequently, the area lacks results regarding what can be achieved with power minimization sb algorithms. this work aims to diminish this gap. first, the equivalence between rate maximization and power minimization problems is formalized. second, extended versions of some rate maximization sb algorithms are proposed for power minimization purposes and evaluated through simulations. in addition, the power-usage capabilities and convergence characteristics of each extended sb algorithms is discussed.
uwb radar sensor networks detection of targets in foliage using short-time fourier transform. in this paper, we study target detection in foliage environment. when radar echoes are in good quality, the detection of target can be achieved by applying short time fourier transform (stft) to the received uwb radar waveform. we compare our approach in case of no target as well as with target against the scheme in which 2-d image was created via adding voltages with the appropriate time offset. results show that our approach can detect target more easily. when radar echoes are in poor condition and single radar is unable to carry out the detection, we employ both radar sensor networks (rsn) and rake structure to combine the echoes from different radar members and finally detect the target.
performance of host identity protocol on symbian os. the host identity protocol (hip) has been specified by the ietf as a new solution for secure host mobility and multihoming in the internet. hip uses self-certifying public-private key pairs in combination with ipsec to authenticate hosts and protect user data. while there are three open-source hip implementations, little experience is available with running hip on lightweight hardware such as a mobile phone. limited computational power and battery lifetime of lightweight devices raise concerns if hip can be used there at all. this paper describes the porting process of hip on linux (hipl) and openhip implementations to symbian os, as well as performance measurements of hip over wlan using nokia e51 and n80 smartphones. we found that with 1024-bit keys, the hip base exchange with a server varies from 1.68 to 3.31 seconds depending on whether the mobile phone is in standby or active state respectively. after analyzing hip performance in different scenarios we make conclusions and recommendations on using ip security on lightweight hardware clients.
minimum energy strong bidirectional topology for ad hoc wireless sensor networks. a node in a wireless sensor network typically consists of a micro-controller, a communication device or transceiver, and a battery unit for powering the transceiver and other devices. an important feature of wireless sensor networks is the low power consumption requirement, since these sensor nodes carry generally irreplaceable power sources or batteries. we consider the problem of assigning a power to each node in the network such that the induced connectivity graph is strongly connected with only bidirectional links, and the sum total of powers assigned to all sensor nodes is minimized. this will allow the nodes to communicate with each other, while conserving battery power as much as possible. this problem has been shown to be strongly np-complete and heuristic approaches for solving this problem have been reported in the literature. in this paper, we establish a lower bound on the optimal power value, and provide a sufficient condition for a minimal spanning tree (mst) based approach to be an optimal solution to the problem. based on this condition, we propose a novel heuristic approach which computationally outperforms previously reported heuristics.
quantum coin-flipping-based authentication. quantum cryptographic key distribution (qkd) is a promising candidate for achieving unconditional security, making the renowned one-time pad encryption technically feasible for building computer networks. however, although well-developed theoretical foundations perfectly ensure protection against eavesdropping, no natural mechanism is yet able to successfully repel an adversary sitting between alice and bob, performing qkd with both and re-encrypting each message after heaving read it in plain text. authentication is hence of crucial importance, and normally applied to all messages that are related to the public discussion part of the qkd protocol. we present an analysis of a scenario, in which authentication is postponed until the end of the qkd protocol. this yields to reduced computational effort, as well as simple and tight bounds on the amount of preshared key material. our solution relies on a combination of quantum key distribution and quantum coin-flipping, which ensures noncontrollability of the qkd key. based on this assumption, we can apply a standard fingerprint comparison for authentication, to guard the protocol against a person-in-the-middle attack.
space-time coding and processing with differential chaos shift keying scheme. this paper investigates the feasibility to use chaotic communications in mimo channel. differential chaos shift keying modulation is chosen as a benchmark and alamouti space-time code scheme is used for the 2 transmit and 2 receiver antennas wireless system. based on the evaluation of system performance, improvements are also discussed.
minimizing energy consumption in ir-uwb based wireless sensor networks. impulse radio ultra-wideband (ir-uwb) communication has proven an important technique for supporting high-rate, short-range, low-power communication. these are necessary criteria for emerging sensor networks, which oftentimes have very short distance communication requirements, necessitate low power operation and may require high data rates (e.g., for supporting the transmission of images or video). in this paper, using detailed models of typical ir-uwb transmitter/receiver structures, we minimize the energy consumption per information bit in a single link of an ir-uwb system, considering packet retransmissions and overhead. this minimization is realized by finding the optimum packet length and the optimum number of rake fingers at the receiver for different transmission distances, using differential bpsk (dbpsk) and ook with coherent and non-coherent detection. our results show that at very short distances, it is optimum to use ook with non-coherent detection and large packets, and at longer distances, it is optimum to use dbpsk with coherent detection and small packets.
a simplified suboptimal algorithm for tone reservation ofdm. a gradient algorithm has been used in the tone reservation technique for peak to average power ratio (papr) reduction. this provides a good approximation to the optimal solution with lower complexity. this technique requires that a kernel signal be computed and iteratively shifted in the time-domain to the peak locations to reduce the papr. the kernel signal should be updated dynamically for the best performance in time varying channels, which increases the computational complexity. in this paper, we propose a low complexity gradient algorithm for computing the peak reduction kernels. this approach is more efficient than the previous algorithm, and provides better papr performance.
performance comparison among conventional selection combining, optimum selection combining and maximal ratio combining. reference [1] introduced optimum selection combining (osc) for binary phase shift keyed signals which selects the diversity branch having the maximum a posteriori probability. it performs much closer to maximal ratio combining (mrc) than the conventional selection combining (csc) which selects the diversity branch having the maximal instantaneous signal power [2]. it is known that these combining techniques have the same diversity order (do), i.e., the same performance slope (log error probability versus signal-to-noise ratio (snr) in db) - the performance variation is the snr difference (gap) between any two techniques to achieve the same bit error rate (ber). this paper derives closed-form expressions for the snr gaps among these three combining schemes. the paper also analyzes the asymptotic ber for these three combining schemes as a function of do for a fixed snr.
dsc: cooperation incentive mechanism for multi-hop cellular networks. muli-hop cellular network is a promising network architecture which incorporates the ad hoc characteristic into the cellular system aiming to improve current cellular network performance. unlike single hop cellular network, due to involving autonomous devices in packet forwarding, routing process suffers from new security challenges which endanger the practical implementation of the network. one security challenge is that selfish devices do not relay other nodes' packets because cooperation consumes their resources and does not provide any immediate advantages. selfish nodes degrade the network throughput, connectivity and power consumption. in order to stimulate the nodes' cooperation, we propose a micro-payment mechanism to reward the forwarding nodes and charge the communicating ones. the security analysis shows that the proposed mechanism is robust against rational attacks, and it can thwart some irrational ones. to evaluate the cost of applying our mechanism, an implementation model is proposed. the performance analysis based on the implementation model demonstrates that the overhead is acceptable.
matched rotation precoding: a new paradigm in space-frequency coding. this paper proposes an efficient rate one space-frequency block code (sfbc) for multiple-input multiple-output orthogonal frequency division multiplexing (mimo-ofdm) systems. the proposed sfbc incorporates concept of matched rotation precoding (mrp) to achieve full transmit diversity and optimal system performance for arbitrary number of transmit antennas, subcarrier interval and subcarrier grouping. the mrp exploits the inherent rotation property of sfbc and has relaxed restrictions on subcarrier interval and subcarrier grouping, making it ideal for adaptive/time varying systems. the lowerbound of the coding gain for mrp is derived and shown that it is useful when designing a sfbc for practical scenarios, e.g. when transmitters have only partial knowledge of power delay profile or when the power delay profile has only a few dominant delayed paths. simulation results show that themrp can achieve a similar or better performance than existing sfbcs.
downlink resource allocation for ofdma-based multiservice networks with imperfect csi. this paper addresses practical implementation issues of resource allocation in ofdma networks: inaccuracy of channel state information (csi) available to the resource allocation unit (rau) and diversity of subscribers' quality of service (qos) requirements. the resource allocation problem in the considered point-to-multipoint (pmp) network is modeled as a network utility maximization (num) problem that allocates subcarriers, rate and power while satisfying orthogonal frequency division multiple access (ofdma) constraints and qos constraints defined in the service level agreement. performance evaluation findings support our theoretical claims: a substantial data rate gain is achieved by considering the csi imperfection and multiservice classes are supported with qos guarantees by coordinating with a call admission control (cac) scheme.
performance evaluation of harq schemes for cooperative regenerative relaying. two hybrid arq (harq) schemes based on selective decode and forward are considered for a cooperative half-duplex relay channel. two time slot types: t1 slot for relay listening and t2 slot for relay forwarding are assumed to accommodate half duplex relaying. the considered harq schemes differ in the frequency of the arq feedback: one is frame and the other is slot based where each frame is composed of one t1 followed by one t2 slot. two types of encodings: repetition coding (rc) and unconstrained coding (uc) (also known as incremental redundancy) are assumed. outage performance analysis is carried out for both rc and uc. the state transition models of the considered protocols are presented and are used to analytically calculate the harq throughput and latency performance; thus avoiding time consuming monte carlo based evaluations. the provided analysis enables us to predict the system performance and tune its transmission parameters (transmission rate and frame structure) for any combination of the signal to noise ratio (snr) of the constituent links.
spectrum handoff in cognitive radio networks: opportunistic and negotiated situations. spectrum handoff is an indispensable component in cognitive radio networks to provide resilient service for the secondary users. in this paper, we explore the spectrum handoff procedure and then propose four metrics to characterize both short-term and long-term spectrum handoff performance: link maintenance probability, the number of spectrum handoff, switching delay, and non-completion probability. in particular, the probability mass function (pmf) and the average number of spectrum handoff are developed. the tele-traffic parameters are relaxed to follow a general distribution function, which will enable a wide applicability and theoretical significance of the derived formulae. both opportunistic and negotiated spectrum access strategies are investigated. results show that these two mechanisms will generate significantly different performance. numerical examples are presented to demonstrate the performance trade-off and the interaction between the primary users and the secondary users. the impact of key parameters on spectrum handoff is also discussed. the techniques as well as the results are important for evaluating the primary and second users co-existence, and hence helpful for design and optimization of cognitive radio networks.
em-based maximum-likelihood sequence detection for mimo optical wireless systems. a major performance-limiting factor in terrestrial optical wireless (ow) systems is turbulence-induced fading. exploiting the additional degrees of freedom in the spatial dimension, multiple laser transmitters combined with multiple receiver apertures provide an effective solution for fading mitigation. although mimo (multiple-input multiple-output) ow systems have been extensively studied in recent years, most of these works are mainly limited to symbol-by-symbol decoding. maximum likelihood sequence detection (mlsd) exploits the temporal correlation of turbulence-induced fading and promises further performance gains. in this paper, we investigate mlsd for im/dd (intensity-modulation/direct-detection) mimo ow systems over log-normal atmospheric turbulence channels. even with a low-order modulation scheme such as on-off keying which is typically used in ow systems, the complexity of mlsd might be prohibitive. we therefore present an iterative sequence detector based on the expectation-maximization (em) algorithm. the complexity of the proposed algorithm is much smaller than a direct evaluation of the log-likelihood function. the monte-carlo simulation results demonstrate that the em-based algorithm outperforms the symbol-by-symbol decoder and achieves a performance which lies within 0.5 db of that of the optimal mlsd.
design of a delay-based routing protocol for multi-rate multi-hop mobile ad hoc networks. the temporal fluctuations in quality exhibited by the wireless links act as a major challenge in the design of efficient routing protocols in real-world mobile ad hoc networks (manets). none of the existing link metrics fully account for the characteristics of data loss and delay on the links of a manet. this paper provides the design of a novel delay-based link quality metric that uses real-time statistics from the wireless driver to take into account wireless contention, congestion, channel loss and mobility. the proposed delay metric is additive, does not introduce much additional overhead and is reflective of the varying wireless link quality. we design an efficient link delay-aware routing (ldar) protocol based on the proposed link metric. the proposed protocol has been implemented on a manet test bed consisting of 5 laptop nodes. the evaluation of our protocol performed through extensive experimentation on the 5-node multi-hop manet testbed and network simulator ns-2 demonstrate the superior benefits of the new protocol.
delay-based congestion avoidance for qos provisioning in wired/wireless networks. with the emergence of high bandwidth-delay product and heterogeneous wired / wireless networks, the standard tcp appears to be too conservative to offer reasonable performance. the use of parallel tcp connections has been suggested in such environments. we have demonstrated that, with the same level of aggressiveness, this approach can outperform the single-connection based approach. however, this approach also introduces new problems: the complexity of managing multiple connections and its performance sensitive to the number of the connections in use. this paper presents a few methods to overcome these problems. in particular, we propose a novel method using a delay-based congestion avoidance (ca) algorithm with multiple connections. this method is not sensitive to the number of the connections in use. we also suggest using a smaller number of connections to emulate the behaviours of a number of standard tcp connections, in order to reduce the complexity of connection management.
shedding new light on sequence design criteria for multipath channels. the merit factor (mf) introduced by golay has long been accepted as the standard criterion to evaluate and design binary sequences with good anti-multipath property in sonar, radar, and communication systems for its theoretical tightness and practical simplicity. in this paper, we first show that the mf is a biased anti-multipath performance evaluation metric in theory and, more importantly, is not a pertinent sequence design criterion in practice for most binary sequences of practical interest. then we propose the weighted merit factor (wmf) based on a non-uniform weighting of the out-of-phase aperiodic autocorrelation function (acf) that provides accurate measurement of self-generated interference for the constant amplitude complex-valued sequences and the nonconstant modulus ones. based on the wmf, a list of "bad" (of low mfs) binary sequences (lengths 33-95) with better anti-multipath performance than the "best" (known) ones have been designed to verify its greater pertinence over the mf as a sequence design criterion for sonar, radar, and communication systems. moreover, we extend the weighted correlation model of the wmf to the code-division multiple-access (cdma) systems and propose the weighted cross-correlation factor (wcf) to evaluate the sequence set's multiple-access interference (mai) rejection property in the context of multipath propagation. theoretical analysis corroborated by simulations confirms that the wcf provides greater practical pertinence and analytical tractability over the current standard criterion.
transmission control with imperfect csi in channel-aware slotted aloha networks. the impact of imperfect channel state information (csi) on the transmission control of channel-aware slotted aloha networks is studied in this work. by taking into consideration the statistics of the channel estimation error to maximize the achievable stable throughput, we obtain the optimal transmission control policy that determines the transmission probability, rate, and power that should be adopted under different channel states. specifically, with imperfect csi, we find that high transmission probabilities should be assigned to channel states that allow for high probability of successful transmission (which may be affected by the estimation errors), but rate allocation must be performed more conservatively (compared to the case with perfect csi) in order to avoid transmission errors due to imprecise channel estimates. the policies are first developed for single carrier systems and then extended to multi-carrier systems with maximum per-user power constraints. the asymptotic maximal stable throughput is analyzed for both the single and multiple carrier systems as the number of users goes to infinity. we observe that, with error in the channel estimate, the proposed transmission control policy that takes into consideration the error statistics may significantly increase the throughput compared to strategies that are derived under the perfect csi assumption.
dynamic resource modeling for heterogeneous wireless networks. high variability of access resources in heterogenous wireless networks and limited computing power and battery life of mobile computing devices such as smartphones call for novel approaches to satisfy the quality-of-service requirements of emerging wireless services and applications. towards this end, we first investigate a markov-based stochastic scheme for modeling and estimation of bandwidth and delay on heterogenous wireless networks. borrowing clustering techniques from machine learning literature for intelligent state quantization, we demonstrate that the performance of the markov model is enhanced significantly. we implement a measurement tool zeus on smartphones and collect real-world data on 802.11g, 2.5g, and 3g wireless networks. the accuracy of the developed model is evaluated through simulation studies based on the collected data. furthermore, a distributed rate-control scheme leveraging the predictions of our model is developed and observed to be much more efficient than a baseline additive-increase multiplicative-decrease scheme.
local information busy burst thresholding. this paper presents a novel approach for setting the thresholds for busy burst (bb) enabled interference avoidance in tdd (time division duplex) systems. one of the key issues in the bb concept is the appropriate choice of the threshold, which determines whether a user is allowed to transmit on a specific time-frequency resource unit. for a two-link network we derive the optimum threshold value that maximises the sum rate. furthermore, for multiple links, a new heuristic threshold that only relies on locally available information is derived. it is demonstrated via simulations that the heuristic threshold provides superior sum rate than a fixed system-wide threshold.
partial multiuser detection for cs-cdma/cp over multipath channels and its comparison with ds-cdma. convolutional spreading cdma with cyclic prefix (cs-cdma/cp) enables multiuser interference-free (mui-free) transmission over multipath downlink channels with the use of zero correlation zone (zcz) codes. however, mui-free transmission is guaranteed only when the data length d, channel delay l, and zcz length z satisfy z + 1 ≥ d + l, and the user population is constraint to be k ≤ ⌊n/z+1⌋, where n is the code length. in this paper, for the purpose of allowing higher bandwidth efficiency for more active users, we propose an iterative partial multiuser detector for cs-cdma/cp with m-zcz code to allow z + 1 < d + l. because the detector is implemented in the symbol-level (after despreading) and only a partion of users are jointly considered, its receiver complexity is expected to be acceptable for a mobile terminal. comparison with the ds-cdma system employing chip-equalization receiver shows that the cs-cdma/cp system employing the proposed receiver offers a better tradeoff between the performance and receiver complexity, which indicates its potential application in future wireless communications.
destination-driven on-demand multicast routing protocol for wireless ad hoc networks. abstract-in this paper, we design a destination-driven on-demand multicast routing protocol for wireless ad hoc networks. the design objective is to improve the multicast forwarding efficiency. to achieve this goal, the path to reach a multicast destination is biased towards those paths passing through another multicast destination. if multiple such choices are available, the one leading to the least extra cost is selected. our protocol embeds this destination-driven feature into the on-demand multicast structure building process of an existing multicast protocol odmrp. detailed protocol design descriptions are provided. simulation results show that our protocol can greatly improve the forwarding efficiency as compared with odmrp. moreover, our destination-driven design can also work well with other existing multicast routing protocols for wireless ad hoc networks.
correcting suboptimal metrics in iterative decoders. in this paper the issue of improving the performance of iterative decoders based on sub-optimal calculation of the messages exchanged during iterations (l-values) is addressed. it is well known in the literature that a simple-yet very effective-- way to improve the performance of suboptimal iterative decoders is based on applying a scaling factor to the l-values. in this paper, starting with a theoretical model based on the so-called consistency condition of a random variable, we propose a methodology for correcting the l-values that relies only on the distribution of the soft information exchanged in the iterative process. this methodology gives a clear explanation of why the well-known linear scaling factor provides a very good performance. additionally, the proposed methodology allows us to avoid the exhaustive search required otherwise. numerical simulations show that for turbo codes the scaling factors found closely follow the optimum values, which translates to a close-to-optimal ber performance. moreover, for ldpc codes, the proposed methodology produces a better ber performance compared with the known method in the literature.
theoretical performance of multi-weight spreading codes for multimedia optical access network. the optical code division multiple access (ocdma) technique is a potential solution to provide access on the optical channel to different users but also to different services applying performance differentiation. for this purpose, we focus here on an ocdma system using 2 dimensional (2d) multiweight spreading codes. at the reception, a hard limiter (hl) device in front of the conventional correlation receiver (ccr) is used to reduce the multiple access interference. to evaluate the performance of this scheme in a noisy optical channel, we develop an approximated calculation which provides a theoretical upper bound of the multi-weight code performances. in addition, for any noise amount, the optimal ccr threshold can be exactly determined. we use the theoretical results to design the multiweight codes adapted to the transmission of three services with respectively low, medium and high bit error rates (ber). thanks to our theoretical approach, the noise impact is analyzed and shown being very significant for each service. it is possible to take the noise power into account in the code design, but at the cost of the increase of the spreading code length. to overcome these drawbacks, we investigate the ber gain provided by low density parity check (ldpc) codes. the results obtained show that forward error correction (fec) is a good way to improve the multimedia access network potentialities.
particle swarm optimisation aided minimum bit error rate multiuser transmission. we consider the downlink of multiuser system from a transmitter equipped with multiple antennas to multiple non-cooperative single-antenna mobile receivers. particle swarm optimisation (pso) algorithm is invoked to solve the constrained nonlinear optimisation problem for the minimum bit error rate (mber) multiuser transmission (mut). the proposed pso aided mber-mut scheme provides much better performance over the conventional minimum mean-square-error mut scheme, and it achieves a much lower complexity compared to the state-of-the-art sequential quadratic programming based mber mut.
design of two-dimensional wavelength-time codes for fiber-optic cdma systems. in this paper, a new family of two-dimensional (2d) wavelength-time codes, which uses one-dimensional (1d) optical orthogonal codes (oocs) with the maximum cross-correlation value of two as the time-spreading codes is proposed and analyzed. by relaxing the cross-correlation functions to at most two, the new 2d codes can provide larger code cardinality to accommodate more subscribers. they also have better performance than 1d optical codes because they can support heavier code weight, for a given code length. moreover, our numerical examples show that the heavier code weight supported by our new 2d codes results in better performance than some of our previously proposed 2d codes, which have the maximum cross-correlation value of one.
selecting concurrent network architectures at runtime. the current internet architecture nicely structures functionality into layers of protocols. while this reduces complexity, many tweaks have emerged because of the architecture's limited flexibility. cross layer functionality corrodes the layer boundaries, intermediate layers had to be introduced for protocols like mpls and ipsec, and middleboxes - like in case of nat - further complicate the interaction of protocols. to overcome these problems, many publications have proposed modular solutions or protocol composition, allowing software engineering ideas to improve protocol design. other publications state that instead of choosing a single common network architecture for the future internet, it might be advantageous to run multiple different architectures in parallel. we combine both approaches and make it possible to rapidly create and run different network architectures in parallel. while this allows for simplified future internet development, it requires the network architecture to be dynamically chosen. this paper not only presents a node architecture enabling the parallel operation of different network architectures but also introduces algorithms for their selection at runtime.
on-line dynamic traffic grooming algorithms for wdm mesh networks. traffic grooming in wavelength division multiplexing networks merges low-speed flows into large capacity pipes so that the bandwidth discrepancy between them will not lead to underutilization of resources. on-line solutions for dynamic grooming typically involve the construction of an auxiliary graph for deciding on the routing and wavelength assignment. an auxiliary graph can represent the network partially leading to scalable solutions. previous algorithms based on such type of auxiliary graph produce unfair distribution of resources. this paper introduces a novel algorithm and two of its variants, which are scalable and produce low blocking and fair distribution of resources.
rf in the jungle: effect of environment assumptions on wireless experiment repeatability. most researchers conduct wireless networking experiments in their laboratory or similar indoor environments. such environments are veritable rf jungles, especially when we consider the ism bands. in this paper we examine and test several common explicit and implicit assumptions that researchers tend to make about the wireless environment. although these assumptions are acknowledged by most researchers, the extent of their impact is often underestimated. we find that because the environment is always in flux, it is almost impossible to reproduce the results of an experiment. hence, there is a high risk of misinterpreting the data obtained from such experiments. through this paper we try to caution experimenters against such risky assumptions when they venture into the rf jungle. after a successful proof-of-concept experiment, we advocate the use of wireless networking testbeds that provide experimenters better control over the rf environment by using coaxial cables, programmable attenuators and power dividers/combiners.
a transmission scheme for continuous arq protocols over underwater acoustic channels. due to the half-duplex property of the underwater acoustic channels, the classic stop-and-wait arq (sw-arq) and its variants are generally thought to be the only class of arq protocols that can be applied in underwater. when combined with the large propagation delay property of the underwater acoustic channels, the use of sw-arq and its variants makes the throughput performance of underwater acoustic communication systems very inefficient. in this paper, we propose a transmission scheme that takes advantage of the long propagation delay in underwater to enable the use of continuous arq protocols over underwater acoustic channels. simulation results show that our proposed transmission scheme allows much higher throughput to be achieved than both the classic sw-arq and its variants, even when simple continuous arq protocols are used.
push popular segments in p2p vod system: possibility and design. video-on-demand (vod) services have attracted a lot of attentions in recent years. measurement studies show that vcr (video cassette recorder) operations, such as pause, rewind, and fast forward/backward, influence the pattern of the access to video segments and viewer(session) sojourn time. moreover, some vcr features (e.g., bookmarking [1]) newly proposed can further magnify such effects. this work analyzes the possibility to discern popular segments (highlights) from normal non-popular segments (normal-content) and how to reduce playback jitter in p2p streaming by leveraging this difference in segment popularity. our contributions are two folds. first, a user playback model is presented, based on which we come to an affirmative conclusion on the possibility aforementioned. besides, we also examine a real workload trace to validate the model and conclusions. second, we propose a hybrid system, namely pitapat, which pro-actively pushes out highlights and pulls in normal-content on demand. in order to reduce the playback jitter, the overlay topology is designed to provide a pull demand as many desired sessions as possible. the performance of pitapat is evaluated by using a queuing model and simulations, whose results show that pitapat outperforms the traditional mesh-pull based p2p system in terms of playback continuity.
a greedy cophasing scheme for mimo beamforming systems using quantized feedback. we propose the hadamard matrix as a codebook for multiple-input multiple-output (mimo) beamforming systems, and show that a quantized equal gain transmission (qegt) scheme using the hadamard codebook has the same symbol error probability performance as a receiver selection diversity combining scheme operating in independent generalized rayleigh fading channels. also, we propose a greedy cophasing scheme for mimo beamforming systems using quantized feedback. the greedy cophasing scheme provides 3.2 db power gain over an orthogonal space-time block code when the number of transmit antennas is four, the number of receive antennas is one, and the number of feedback bits is three.
mobility-based generic infrastructure for large scale sensor network architecture. building efficient general purpose sensor network infrastructure that could be leveraged by upper layer protocols is still an open research problem. in this paper, mobility is exploited to organize sensor nodes into generic efficient infrastructure. we propose layered infrastructure protocol (lip) that allows mobile robots to organize the network nodes into co centric circular layers. once the network is organized, the mobile robots are assigned layers to serve called home service layers where they act as moving probes to access the data and monitor the layers. access positions are selected dynamically at each layer to provide anchors for the probes to visit in their home service layers. probes cooperate to perform the application requests by executing a communication plan that is provided by the upper layer applications. the protocol is greatly able to cope with failures and requires only local updates for maintenance. we show that the proposed protocol provides a flexible infrastructure that keeps the nodes proximity and could be leveraged by upper layer protocols. to evaluate the performance of the proposed infrastructure some upper layer applications are implemented and built over the proposed infrastructure. simulation-based results show the robustness and efficiency of the implemented applications.
asymptotic analysis of multiuser diversity and selection diversity in multiple-relay networks. selection cooperation has been proposed as a promising way of realizing cooperative diversity for its simplicity and good performance. in this paper, a framework to analyze the multiuser diversity and selection diversity in multiple-relay networks is presented. based on this framework, we derive closed-form asymptotic expressions of outage probability and symbol error rate (ser) for both amplify-and-forward (af) and decode-and-forward (df) based multiple-relay networks. both the theoretical analysis and simulations show that a multiuser diversity order of k and a selection diversity order of m + 1 can be achieved simultaneously for both af and df protocols (where k is the number of accessing users and m is the number of available relays). these show that the multiuser diversity can be readily combined with the selection diversity in multiple-relay networks.
integration of handover in a cross-layer mechanism for mobile multimedia systems. a cross-layer mechanism for the performance improvement of real-time applications over ieee 802.16e networks is proposed. the mechanism coordinates i) adaptation capabilities at different layers of the protocol stack, and ii) the handover initiation procedure. it uses information from the physical (phy) and medium access control (mac) layers to determine the appropriate burst profile, transmission power level and media encoding rate for a connection, or initialize a handover. the main contribution of this mechanism is the integration of the handover initiation into an existing cross-layer logic mechanism to improve the overall system performance. extensive simulation results show that the proposed design achieves significantly improved performance in terms of packet loss rate, power consumption, and throughput, as well as an increased system capacity.
uplink capacity of multi-class ieee 802.16j relay networks with adaptive modulation and coding. the emerging ieee 802.16j mobile multi-hop relay (mmr) network is currently being developed to increase the user throughput and extend the service coverage as an enhancement of existing 802.16e standard. in 802.16j, the intermediate relay stations (rss) help the base station (bs) communicate with those mobile stations (mss) that are either too far away from the bs or placed in an area where direct communication with bs experiences unsatisfactory level of service. in this paper, we investigate the uplink erlang capacity of a two-hop 802.16j relay system supporting both voice and data traffics with adaptive modulation and coding (amc) scheme applied in the physical layer. we first develop analytical models to calculate the blocking probability in the access zone and the outage probability in the relay zone, respectively. then a joint algorithm is proposed to determine the bandwidth distribution between the access zone and the relay zone, and to derive the erlang capacity region of the system. the numerical examples show that some capacity gains can be obtained with a relay-enhanced 802.16j system compared to the conventional single-hop 802.16e system.
a game-theoretic analysis of inter-session network coding. a common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. however, this assumption can be violated in practice. in this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. we prove the existence of nash equilibria for a wide range of utility functions. the number of nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. we then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (poa), compared to an optimal and cooperative network design. we show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve poa in comparison with the case where a single pricing scheme is being used. however, poa is still worse than the case when network coding is not applied. this implies that intersession network coding is more sensitive to strategic behavior. for example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain nash equilibria can be as low as 48%. these results generalize the well-known result of guaranteed 67% efficiency bounds shown by johari and tsitsiklis for traditional packet forwarding networks.
a mathematical perspective of self-optimizing wireless networks. we present a mathematical framework for quantitative investigations of self-optimizing wireless networks (son) with focus on the 3gpp long-term evaluation (lte) system. basic target functions, such as the signal-to-noise ratio distribution, the number of satisfied users, or energy efficiency are derived as a figure of merit, including the impact of adaptation of downlink transmit power adaptation, antenna tilt, and the handover parameter. the framework is exemplified by basic investigations on load balancing.
channel estimation for amplify-and-forward two-way relay network with power allocation. in this work, we consider channel estimation for an amplify-and-forward (af) two way relay network (twrn), where two terminal nodes exchange information via a single relay node in between. a new concept of channel estimation by performing the power allocation at the relay node is introduced. as an example, we consider the maximum likelihood (ml) channel estimation at relay node and derive the power allocation factor such that the average effective signal-to-noise ratio (aesnr) at the terminal nodes is maximized. nonetheless, the idea of using power allocation at relay node can be straightforwardly extended to more general scenarios. the simulation results show the advantages of the proposed method over the existing techniques.
optimal diversity-multiplexing tradeoff in ofdma systems. ofdma technology can significant improve the transmission reliability in multi-user communication systems because of its inherent frequency diversity. in a recent work, we have derived a surprising result which demonstrates that ofdma systems can achieve a frequency diversity gain which is equal to the total number of independent subcarriers. in this paper, we shall show that the frequency diversity and the frequency multiplexing can be simultaneously achieved in ofdma systems with a fundamental tradeoff between them. the random bipartite graph theory is used to model and analyze this diversity-multiplexing tradeoff problem. in particular, the maximum proper f-matching is introduced as a subcarrier allocation method which can minimize the user outage probability with fairness assurance given some multiplexing requirements. similar to the zheng-tse tradeoff in mimo systems [1], the optimal diversity-multiplexing tradeoff in multi-user ofdma systems and it will be shown that its curve can be characterized by a piecewise linear function, despite of the user conflicts in the subcarrier allocation.
network coding for bit error recovery in ieee 802.11 mesh networks. opportunistic routing (or) relies on links of intermediate quality, i.e. packet losses are common. however, the reasons for packet losses are manifold, e.g. a received packet may contain corrupted bits. according to traditional approaches, the receiver discards the whole frame in such a case. in this paper, we present measurements from an indoor ieee 802.11 wireless mesh network (wmn), which indicate that corrupted frames still contain a significant amount of correct data, which can be utilized. in particular, corrupted frames are common for intermediate quality links. bit errors tend to occur in proximity, i.e. they are bursty. furthermore, bit errors are uncorrelated across different receivers in most cases. based on our observations, we propose a harq scheme for or called hybrid arq with limited fragmentation (half). it operates on a hop-by-hop manner and requires only local knowledge. due to the bursty nature of bit errors, we are dividing frames into fragments with additional error detection. using random linear network codes, the sender transmits incremental redundancy until one of its receivers is able to decode all fragments and therefore sends an acknowledgement packet. however, the partial information at all other receivers is not lost. instead, to increase the throughput further, it is also used in subsequent forwarding rounds along the multi-hop route. we implemented a prototype of our protocol to evaluate its performance. with the help of detailed simulations, we analyzed the reasons why half significantly outperforms traditional approaches like dsr.
utility maximization in the multi-user miso downlink with linear precoding. the maximization of an increasing function over the set of achievable rates in a multi-user, multi-antenna downlink is addressed. in general, the set of rates achievable by linear precoding and treating interference as noise is nonconvex. as a result, the corresponding utility maximization problem is nonconvex. the rate region can be convexified by time sharing, and the utility maximization over the convexified region can be solved via lagrange duality. still, subproblems in the dual problem remain nonconvex. it is shown how all the aforementioned nonconvex problems can be solved to global optimality in the framework of monotonic optimization. moreover, it is investigated to what extent utility is increased by time sharing. while all problems can be solved to global optimality, the resulting computational complexity is rather high, thus the proposed solution strategies mainly provide a benchmark for locally optimum, less complex methods. numerical results demonstrate that a method which finds stationary points on the boundary of the rate region can provide close-to-optimum performance.
energy efficient routing in ad hoc networks with nakagami-m fading channels. this paper considers minimum-energy routing problem in poisson random ad-hoc networks with nakagami-m fading channels. we first formulate an analytical model for the transmission power, subject to a certain packet reception probability, under the assumption that the users employ proper power control and slotted aloha protocol. based on this, we consider five routing strategies and compare their energy performances. our results show that, long-hop routing in nakagami-m networks can be more energy efficient than short-hop routing in certain scenarios, especially under light traffic and significant channel fading. when the interference can not be neglected, short-hop routing is typically better. it is also observed that when the path loss exponent is small, intelligent mac mechanisms are critical for the energy efficiencies of routing strategies.
application of analytic wavelet transform for signal detection in nyquist folding analog-to-information receiver. one of the challenges in cognitive radio (cr) is efficiently monitoring a wideband radio frequency (rf) spectrum in order to identify unoccupied bands. compressive sensing (cs) has recently been proposed to address this problem. typical cs techniques, however, involve random projections followed by a computationally intensive signal reconstruction process. since spectral monitoring does require full signal reconstruction - only identification of occupied regions to avoid - we propose a novel spectrum monitoring approach based on the nyquist folding receiver (nyfr) in conjunction with the analytic wavelet transform. the nyfr performs analog compression via a non-uniform sampling process that induces a chirp-like modulation on each received signal. this induced modulation can be measured using time-frequency analysis techniques to determine the original rf band of origin without full signal reconstruction. this paper investigates the feasibility of using the analytic wavelet transform to perform nyfr information recovery in support of cr wideband spectrum sensing.
subcarrier sensing for distributed ofdma in powerline communication. powerline communication (plc) is a preferred choice for smart home network. in this paper, a new system structure is proposed for plc, which is based on distributed orthogonal frequency division multiple access (dofdma). sub-carrier sensing, i.e., sensing every ofdm subcarrier to see if it is occupied or not, is proposed to replace the conventional carrier sensing multiple access (csma) for multi-user contention of a channel. this structure, borrowed from cognitive radio, allows multiple users to opportunistically share the same channel on different subcarriers and therefore increases the channel capacity. two subcarrier sensing methods are proposed: one is based on information theory and the other is based on successive energy comparison. simulations are provided to verify the methods.
density-varying high-end sensor placement in heterogeneous wireless sensor networks. to achieve better performance, we adopt a heterogeneous sensor network (hsn) model. in many applications, the locations of some sensor nodes are controllable. in this paper, first we propose a novel density-varying deployment scheme for high-end sensors (h-sensors) in an hsn. the scheme solves the bottleneck problem in typical many-to-one sensor networks. we then study the optimal placement of h-sensors whose locations are controllable. the goal is to use the minimum number of h-sensors for ensuring successful data delivery, coverage and connectivity in a network for a given lifetime. we present an effective h-sensor placement scheme that can simultaneously achieve coverage, connectivity and data relay requirements while uses a small number of h-sensors. both theoretical proofs and simulation results demonstrate that the proposed h-sensor placement scheme achieves very good performance.
adaptive bitrate and resource allocation for relay-assisted arq transmissions. automatic repeat request (arq) protocols deal with the situations where the selected data rate is not supported by the current channel realization. the inappropriate selection is motivated by the limited channel state information at the transmitter (csit). this work looks into how the arq protocols are applied to the half-duplex relay-assisted transmission with decode-and-forward relays by exploiting the ack feedback channel of the terminals. two implementations are tackled: 1) only the source or 2) source and relay manage the retransmissions under the pure-arq protocol. this work presents an analytical framework for the comparison of both options. the study allows the optimization of the bitrate and amount of resource allocated for the relay transmission phases.
routing to a mobile data collector on a predefined trajectory. in this paper, we propose a distributed scheme for data gathering using a mobile data collector in wireless sensor networks (wsns). in our scheme, a mobile data collector moves along a predefined track over the sensing field and data are forwarded to nodes whose transmission disks overlap with the trajectory of the data collector; these nodes are called relaying nodes. data are classified into two categories: delay-sensitive data and delay-tolerant data. while delay-sensitive data are sent to the data collector directly, delay-tolerant data may be sent to a nearby relaying node, where they wait for the data collector to come and pick them up. we give a theoretical analysis to quantify the impact of data collector mobility on the lifetime of the network as compared to a wsn with a stationary data collector. moreover, we use simulations to evaluate our scheme in practice. simulation results show that our scheme has the potential to prolong the lifetime of the network significantly.
a study of the percolation threshold for k-collaborative wireless networks. how to efficiently use the air interface is a crucial issue in wireless networks. in order to improve the performance, mechanisms have been proposed to improve the reach and the connectivity of nodes in a wireless network. one such mechanism is to use joint, synchronized transmission from a cluster of several nodes to reach nodes outside of the transmission range of any of the transmitting nodes in the cluster. we adopt a simplified model of collaboration where the power at the receiver is the sum of the transmitted power at the sender, and study the performance of such system with clusters of arbitrary size k. we compute theoretical bounds on the gain achieved using collaboration as a function of the cluster size. our key result is to show that, in a percolation framework, the critical node density for the infinite connectedness of the network is significantly reduced by the use of k-cooperation: for large k, it is reduced by a factor which we show to converge towards α√ξ(α)2, where ξ(.) is the riemann zeta function. the previously known best bound on the gain of cooperation was 5/4 = 1.25 for α = 2 and pairwise cooperation, while our results yield a provable gain of at least π2/6 = 1.64. we provide some simulations to display the gain of cooperation in a finite size network as well.
probabilistic data detection for probe-based storage channels in the presence of jitter. probe-storage devices employ large arrays of probes to write/read data in parallel in some storage medium. because of their inherent parallelism and the independence of data retrieved from different probes, these devices lend themselves naturally to low-density parity-check (ldpc) codes and associated soft/iterative decoding techniques. in this paper, a concatenated coding scheme for a particular probe-storage channel is presented that comprises an inner (d, k)-constrained code and an outer ldpc code, and the problem of probabilistic data retrieval for this channel is addressed. in particular, soft information is generated by explicitly accounting for the channel output statistics in the presence of jitter and additive noise, based on derived analytical expressions.
a combined approach for receiver-based mac and network layers in wireless sensor networks. data communication represents the greatest energy cost of wireless sensor networks. both mac and network layers of the protocol stack are responsible for data communication in these networks. this work proposes the receiverbased medium access control (rb-mac) protocol to be used in a combined solution with a receiver-based routing scheme. the main advantage of combining receiver-based mac and routing protocols is that this solution does not use neighbor tables and, consequently, it saves energy when compared with mac and routing protocols that use these tables. simulation results reveal that receiver-based data communication has a great data delivery ratio, and reduces energy consumption, number of transmissions, and collisions wben compared with a senderbased data communication. moreover, we use a model checking techdique to perform the formal verification of rb-mac.
theoretical analysis of selective relaying, cooperative multi-hop networks with fairness constraints. we consider the problem of selective relaying in multi-hop networks. at each slot, a relay and a node along the optimal non-cooperative path are opportunistically selected to transmit to the next-hop node in a cooperative manner. being a promising scheme for fair resource allocation, the proportional fair scheduling (pfs) algorithm provides excellent balance between throughput and fairness via multi-user diversity and game-theoretic equilibrium. to maximize the overall utility along a cooperative multi-hop path, we apply the proportional fair (pf) criterion in selecting nodes and relays for cooperative transmission. furthermore, we analyze and provide an analytical expression for end-to-end throughput of an opportunistic relaying, cooperative multi-hop path with proportional fairness constraints over a rayleigh flat-fading channel. to our knowledge, it is the first time that a closed-form expression is obtained for the throughput of a proportional fair relaying, cooperative multi-hop path. this research is an extension of previous theoretical work on pf for cellular networks.
a novel power allocation scheme for distributed space-time coding. this paper derives an optimal power allocation (pa) to maximize the effective average signal-to-noise ratio (snr) of distributed space-time coding (dstc) in wireless relay networks, where the locations of the relays can be anywhere between the source and destination. it is first shown that in maximizing the average snr, not all the relays might be active, and hence the code performance might be compromised. the amount of fading is then introduced for the relay networks and used as a constraint to derive a novel pa scheme. this new pa is shown to obtain the maximum diversity order of both noncoherent and coherent dstc systems at high snr.
improved topology control method for maximizing traffic delivery ratio in wireless mesh networks with directional antennas. in this paper we proposed a topology control algorithm for the single channel wireless mesh network with m directional antennas equipped on each node. the objective of our algorithm is to maximize the traffic delivery ratio from each nongateway node to gateway nodes, by adjusting the orientations of the directional antennas appropriately. by allowing each antenna connecting to multiple nodes, our proposed algorithm improves traffic delivery ratio by 40%-280%, compared to previous work.
distributed uplink signal processing of cooperating base stations based on iq sample exchange. cellular systems in general suffer from co-channel interference, when simultaneous transmissions in other cells use the same physical resources. in order to mitigate such co-channel interference cooperating base stations (bss) can perform joint multi-antenna signal processing across cell borders. this paper describes a concept of distributed cooperation, where bss communicate directly via a bs-bs interface without central control. a serving bs can serve its terminals on its own or it can request cooperation from one or more supporting bss. by collecting iq samples from the supporting bss' antenna elements, the serving bs can virtually increase its number of receive antennas. exchanging additional parameters allows applying advanced receiver algorithms, e.g., interference rejection or cancelation. performance evaluations by means of simulation show the capability of bs cooperation applied to 3gpp lte in terms of cell and user throughput but it also shows the trade-off in terms of increased backhaul requirement due to bs-bs communication.
support for dynamic adaptation in next generation packet processing systems. designs of next-generation internet architectures propose a diverse and changing set of features in the data path of routers. these routers require high-performance programmable packet processing platforms to allow for dynamic feature deployment and adaptation. in this paper, we present programming abstractions that quantifies processing and storage of network services. we further devise a runtime environment that provides the ability of adaptation to dynamically deployed network services and varying network traffic.
distributed turbo trellis coded modulation for cooperative communications. in this contribution, we propose a distributed turbo trellis coded modulation (dttcm) scheme for cooperative communications. the dttcm scheme is designed based on its decoding convergence with the aid of non-binary extrinsic information transfer (exit) charts. the source node transmits ttcm symbols to both the relay and the destination nodes during the first transmission period. the relay performs ttcm decoding and re-encodes the information bits using a recursive systematic convolutional (rsc) code regardless whether the relay can decode correctly or not. only the parity bits are transmitted from the relay node to the destination node during the second transmission period. the resultant symbols transmitted from the source and relay nodes can be viewed as the coded symbols of a three-component parallel-concatenated ttcm scheme. at the destination node, a novel three-component ttcm decoding is performed. it is shown that the performance of the dttcm matches exactly the exit chart analysis. it also performs very closely to its idealised counterpart that assumes perfect decoding at the relay.
context-aware receiver-driven retransmission control in wireless local area networks. automatic repeat request (arq) techniques employed by leading wireless technologies aim at compensating the high error rates due to radio impairments, but do not offer any differentiated levels of protection. in this work, we propose to enable per-packet differentiation of link layer arq protection (in terms of no. of retransmissions) driven by requirements of the end applications as well as of communication protocols implemented on the mobile terminal. experimental results demonstrate the potential benefits deriving from the proposed strategy, both on tcp data flows and mpeg-4 video streams.
resource criticality analysis of static resource allocations in wdm networks. various static resource allocation algorithms have been used in wdm networks to allocate resources such as wavelength channels, transmitters, receivers, and wavelength converters to a given set of static lightpath demands, based on certain design objectives. however, although optimized resource allocations can be obtained, it remains an open issue how to determine which resources are bottlenecks to achieve better performance. existing static resource allocation algorithms do not explicitly measure the impact of a given resource on the design objective. in this paper, we propose such a measurement based on the lagrangian relaxation (lr) framework. we use the optimized values of lagrange multipliers as a direct measurement of the criticality of resources. such a quantitative measurement can be naturally acquired along with the optimization process to obtain the optimal solution (or a near optimal solution) to the static routing and wavelength assignment (rwa) problem. such a measurement helps to identify critical resources, and thus to decide the best way to add or reallocate resources.
voice service support over cognitive radio networks. in this paper, quality of service (qos) provisioning for voice service over cognitive radio networks is considered. as voice traffic is sensitive to delay, the presence of primary users and the requirement that secondary users should not interfere with them pose many challenges for qos support for secondary voice users. two cognitive medium access schemes are proposed in this paper for the secondary voice users to access the available channel. an analytical model is developed to obtain the voice service capacity (i.e., the maximum number of voice users that can be supported with qos guarantee) for the secondary users, taking the impact of primary users' activities into consideration. the analytical model is validated by the simulation. the analytical results will be useful to support voice service in cognitive radio networks.
pcn-based flow termination with multiple bottleneck links. pre-congestion notification (pcn) is a new packet marking scheme based on which simple measurement-based admission control (ac) and flow termination (ft) are implemented. ft is useful for traffic management in unexpected events, e.g., when admitted flows lead to overload on a link after rerouting which may be due to a link or node failure. while ac is a classic flow control function, ft is new and only little understood so far. the limited literature on ft focuses mainly on a single overloaded link. however, when a link or node fails, redirected traffic is likely to cause overload on multiple backup links (bottlenecks) at the same time. as the packet marking probability for flows traversing multiple bottlenecks is larger than for flows traversing only the most severe bottleneck, more traffic is possibly terminated than needed, i.e. overtermination occurs. this paper quantifies potential overtermination in case of multiple bottlenecks for different ft mechanisms which are currently discussed by the ietf.
downlink ofdma resource allocation under partial channel state information. the problem of resource allocation (ra) in a down-link ofdma system is examined under the realistic assumption of imperfect channel state information (csi) at the base station. in this case, there is a nonzero outage probability that the assigned rate at a particular subcarrier/user pair will not be supported by the true channel realization, which may lead to a significant waste of the system's available resources. it is therefore necessary to obtain ra algorithms that take into account the effect of imperfect csi. by exploiting the statistical description of the imperfect csi, various algorithms are proposed that tradeoff complexity versus performance, aiming at maximizing the system's successfully transmitted rate.
maximizing throughput with multiple power levels in a random access infrastructure-less radio system. we propose and analyse a new random access protocol with multiple power levels selection schemes for infrastructureless wireless networks. in these networks, mobile nodes may communicate with each other without a central entity (base station), where each mobile node will be either in a transmitting mode or in a receiving mode or in an idle mode. throughput with random power levels selection scheme is derived in terms of the transmission probability of each mobile node, receiving probability of each mobile node and the number of power levels. throughput with optimum power levels selection scheme is also derived and compared with the previous one. results show that the optimum transmission probability of each mobile node to achieve the maximum throughput depends only on the number of power levels. the maximum throughput region is devised in terms of transmission probability of each mobile node and the number of power levels. the proposed new random access protocol is truly distributive in nature and can be easily implemented in infrastructure-less wireless access systems without requiring any centralized control.
connectivity optimization for wireless sensor networks applied to forest monitoring. device deployment plays a key role in the performance of any large-scale wireless sensor network (wsn) application. wsn device deployment (i.e. the numbers and positions of the devices) must consider several design factors, viz. coverage, connectivity, lifetime, etc. however, connectivity remains the most fundamental factor especially in a large scale harsh environment. in this paper, we explore the problem of relay node (rn) placement in 3d forestry space. we formulate a generalized rn deployment optimization problem aimed at maximizing the network connectivity with constraints on rns count. we investigate how the number of rns can affect the connectivity of a wsn in a harsh environment. based on quantitative analysis of such effects, the paper sets a threshold on the minimum number of required rns.
scalable video-on-demand streaming in mobile wireless hybrid networks. video-on-demand service in wireless networks is one important step to achieving the goal of providing video services anywhere anytime. typically, carrier mobile networks are used to deliver videos wirelessly. since every video stream comes from the base station, regardless of what bandwidth sharing techniques are being utilized, the media stream system is still limited by the network capacity of the base station. the key to overcome the scalability issue is to exploit resources available to mobile clients in a peer-to-peer setting. we observe that it is common to have a carrier mobile network and a mobile peer-to-peer network co-existing in a wireless environment. a feature of such hybrid environment is that the former offers high availability assurance, while the latter presents an opportunistic use of resources available at mobile clients. our proposed videoon-demand technique, patchpeer, leverages this network characteristic to allow the video-on-demand system to scale beyond the bandwidth capacity of the server. mobile clients in patchpeer are no longer passive receivers, but also active senders of video streams to other mobile clients. our extensive performance study shows that patchpeer can accept more clients than the current state-of-the-art technique, while maintaining the same quality-of-service to clients.
improving ieee 802.11 performance in chain topologies through distributed polling and network coding. wireless multi-hop networks often rely on the use of ieee 802.11 technology. despite of the robustness of the ieee 802.11 distributed coordination function (dcf) for working in various network scenarios, it has been proven that critical inefficiencies can arise in the case of multi-hop packet forwarding. in this paper, we propose a mac scheme, based on the virtualization of the point coordination function, optimized for working on chain topologies with bidirectional traffic flows. our scheme is based on a token-like access mechanism coupled with network coding. the basic idea is the use of multiple point coordinators (pcs) along the node chain, which are elected by passing special token frames. since traffic sources are located at the edge of the chain and intermediate nodes act as relays, we also exploit network coding for merging uplink and downlink traffic. analytical and simulation results prove that our scheme can provide an aggregated uplink and downlink throughput comparable with bidirectional point-to-point transmissions.
a fast converging adaptive pre-distorter for multi-carrier transmitters. digital pre-distortion is a powerful technique for combating nonlinearity in power amplifiers. nonlinear response identification of the amplifier is one of the primary objectives in all pre-distortion schemes. if the estimation performance of the adaptive algorithm is not fast and accurate enough, the system will not be able to satisfy the stringent timing and spectral requirements of modern standards. this problem is exacerbated in modern communication systems which are rapidly converging towards a multi-carrier scheme. in such schemes, due to high peak to average power ratios, the convergence of pre-distorters worsens significantly. this paper highlights the problem of slow convergence in multi-carrier systems, and proposes a novel solution, which consists of implementing a twin feedback loop, one including the power amplifier and the other including the pre-distortion system itself. the goal is to leverage the learning curve of the pre-distorter itself and build on what is already known from the partially converged characteristics. simulations with standard multi-carrier schemes indicate that such a method can deliver vastly improved performance over conventional systems.
modeling and evaluation of homing-pigeon based delay tolerant networks with periodic scheduling. in this paper, we analyze a new type of delay tolerant networks (dtn) where each node owns multiple dedicated messengers, called pigeons. the only form of internode communication is for a pigeon to periodically carry a batch of messages originated at the home node, deliver to the corresponding destination nodes and return home. we name this as homing-pigeon (hop) based routing mechanism, which is an effective way to overcome end-to-end disconnection in dtn. in this work, we model the hop mechanism analytically with a periodic pigeon scheduling algorithm. our analysis focuses on understanding the pigeon departure frequency from the home node while keeping the message delivery ratio above a given threshold. simulation results are given to validate our analysis.
new approaches for lowering path expansion complexity of k-best mimo detection algorithms. the present paper proposes two original approaches to reduce computational resources necessary for expanding survivor paths while searching in a k-best manner the mimo detection tree. the first approach involves precomputing some products that are so far recomputed for each path expansion. the second technique is a new method to compute the path metrics. in all k-best detection techniques proposed so far, the complexity necessary to expand a path grows with the path depth in the tree. the originality of our approach stems from the fact that the path expansion complexity decreases with the path depth. since the number of expanded paths increases with their depth, our approach better balances the path expansion complexity and the number of expanded paths at a given depth, which can yield a significant complexity reduction. we then present a new k-best hard-output lattice decoding (k-hold) algorithm that combines both proposed techniques. a complexity analysis shows that k-hold can reduce by up to 70% the overall path expansion complexity as compared to the less-complex known algorithms [1]. this advantage comes about at no cost in terms of performance degradation.
experimental investigations on mimo radio channel characteristics on uhf band. pan-european project b21c (broadcasting for the 21st century) aims to develop technology for dvb-t2 (digital video broadcasting, terrestrial), which is a spectrum efficient broadcasting system for future. the evaluated technologies include mimo, which has been widely studied in perspective of b3g (beyond 3rd generation) systems, but never for any uhf band systems. in addition, the latest decision of wrc (world radiocommunication conference) highlights that the b3g systems can be deployed in uhf bands. this paper introduces a measurement campaign performed in uhf frequency and presents the most important results with regard to channel modeling and mimo.
a distributed approach for location lookup in vehicular ad hoc networks. efficient location management is one of the major challenges in vehicular ad hoc networks (vanets). due to the high mobility of vehicles and the increase in their number, the location information updating and querying messages will consume the limited bandwidth of vanets. this involves the development of a scalable and locality-aware location service management protocol. in this paper, we propose a promising solution called the modified region-based location service management protocol (mrlsmp), which utilizes the existing infrastructure on the road as a location management service entity. to evaluate the efficiency of our proposal, we compare our scheme with existing solutions using both analytical and simulation approaches. specifically, we develop analytical models to evaluate the total control overhead. numerical and simulation results show that our protocol scales better than existing schemes, when increasing the size of vanets which enhances the feasibility of such large scale ad hoc networks.
using partially overlapped channels for end-to-end flow allocation and channel assignment in wireless mesh networks. the performance of multi-channel multi-radio (mc-mr) wireless mesh networks (wmns) can be improved significantly with the increase in number of channels and radios. despite the availability of multiple channels in several of the current wireless standards, only a few of them are non-overlapping and many channels are partially overlapped. in this paper, we formulate the joint channel assignment and flow allocation problem for mc-mr wmns as a mixed integer linear program (milp). unlike most of the previous studies, we consider the case of using both non-overlapped and partially overlapped channels. we consider an objective of maximizing aggregate end-to-end throughput and minimizing queueing delay in the network, instead of the sum of link capacities, since the traffic characteristics of a multihop wmn are quite different from a single hop wireless network. our formulation takes into consideration several important network parameters such as the transmission power of each node, path loss information, signal to interference plus noise ratio at a node, and frequency response of the filters used in the transmitter and receiver. we show by simulations that our milp formulation makes efficient use of the spectrum, by providing superior channel assignments and flow allocations with the addition of partially overlapped channels, without the use of any additional spectrum.
frame: an innovative incentive scheme in vehicular networks. vehicular ad hoc networks (vanets) are envisioned to provide promising applications and services. one critical deployment issue in vanets is to motivate vehicles and their drivers to cooperate and contribute to packet forwarding in vehicle-to-vehicle or vehicle-to-roadside communication. in this paper, we examine this problem, analyze the drawbacks of two straightforward schemes, and present a secure incentive scheme to stimulate cooperation in vanets. we define the measurement of contribution according to the unique characteristics of vanet communication. our scheme uses the weighted rewarding component to ensure fairness. extensive simulation results are presented to support the effectiveness of our scheme.
evaluation of prefix delegation-based route optimization schemes for nemo. among the schemes, proposed in the literature to solve the route optimization problem in network mobility (nemo), the prefix delegation-based schemes perform better than other schemes. depending on the way the prefix are delegated, the prefix delegation-based schemes result in difference in performance under different speed at various distance from the home network (network to which mobile network usually belongs). therefore, there is a need to evaluate the performance of individual prefix delegation-based scheme to find an appropriate scheme based on speed and distance from home network. in this paper, we identify the differences of the refix delegation-based schemes using simulation. results reveal that performance of the schemes depends on speed of the network and distance from home network.
a behaviour study of network-aware stealthy worms. this paper examines the general behaviour of stealthy worms. in particular, we focus on worms that are designed based on network awareness. we study the case where a worm, instead of aiming to spread as fast as possible and penetrate intrustion detection systems (ids), aims to avoid ids and spread with the minimum number of detections. we compare different scanning strategies for this worm, including different combinations of hitlist and random scanning, and how they affect the number of infections and the rate of detected infection attempts. we compare the network-aware worm's behavior to that of the code red ii worm. simulations show that scanning worms can generate many fewer detections using localized scanning while maintaining its capability to infect.
constrained ergodic rates maximization for mobile wimax with statistical channel information. in some fading environments, there may not be a feedback link sufficiently fast to convey the full channel state information (csi) to the transmitter. this paper considers resource allocation strategies for downlink multiuser mobile wimax systems, where the base station knows only the channel distribution information (cdi), but has no knowledge of the instantaneous channel realization. the base station uses cdi to assign subchannels and allocate power to users with the objective to maximize the ergodic weighted sum rate while satisfying minimum rate, long-term fairness and power constraints. we solve the underlying constrained optimization problem using the lagrange dual decomposition framework. the proposed method has a complexity of o(km) for k users and m subchannels. simulation results are provided to compare the performance of this method with other allocation schemes and to illustrate the trade-off between maximized weighted sum rate and the constraints.
null space-based precoding scheme for secondary transmission in a cognitive radio mimo system using second-order statistics. in this paper, we propose a null space-based precoding scheme for secondary transmission in a cognitive radio multiple-input multiple-output (cr-mimo) network under the assumption that time-division-duplex is employed by the primary transmission. first, the secondary transmitter periodically senses the transmitted signals from the primary users and estimates the corresponding covariance matrix. then, subspace techniques are utilized to estimate the noise subspace of this covariance matrix, and the dimension of the noise subspace is estimated using information theory criteria (aic or mdl). finally, the obtained null space is used as the precoding matrix for the secondary transmission, which effectively avoids the interference induced by the secondary transmission at the primary users. moreover, the achievable capacity of the secondary mimo channel by the proposed scheme is derived. simulations are performed to show the efficacy of the proposed scheme.
a data-aided symbol timing estimation algorithm for ofdm/oqam systems. in this paper we deal with the problem of data-aided symbol timing estimation for orthogonal frequency division multiplexing systems based on offset-qam modulation (ofdm/oqam). specifically, a data-aided joint phase offset and symbol timing estimator, based on the least squares (ls) approach, exploiting the conjugate-symmetry property of a properly designed training symbol, is derived. since the phase estimate is in closed form, the symbol timing estimate requires only an one-dimensional maximization procedure. the derived ls estimator does not require the knowledge of the prototype filter and, moreover, its performance, is independent of the carrier frequency offset.
a low complexity iterative technique for soft decision decoding of reed-solomon codes. a new iterative soft decision decoding method for reed-solomon (rs) codes is proposed. this method is based on bit level belief propagation (bp) decoding. in order to make bp decoding effective for rs codes, we use an extended binary parity check matrix with a lower density and reduced number of 4-cycles compared to the original binary parity check matrix of the code. in our proposed method, we take advantage of the cyclic structure of rs codes. based on this property, we can apply the belief propagation algorithm on any cyclically shifted version of the received symbols with the same binary parity check matrix. for each shifted version of received symbols, the geometry of the factor graph will change and deterministic errors can be avoided. our method results in considerable performance improvement of rs codes compared to hard decision decoding. the performance is also superior to some popular soft decision decoding methods.
network coding does not change the multicast throughput order of wireless ad hoc networks. we demonstrate that the gain attained by network coding (nc) on the multicast capacity of random wireless ad hoc networks is bounded by a constant factor. we consider a network with n nodes distributed uniformly in a unit square, with each node acting as a source for independent information to be sent to a multicast group consisting of m randomly chosen destinations. we show that, under the protocol model, the persession capacity in the presence of arbitrary nc has a tight bound of θ (1/√mnlog(n)) when m = o(n/log(n)) and θ(1/n) when m = ω(n/log(n). our result follows from the fact that prior work has shown that the same order bounds are achievable with pure routing based only on traditional store-and-forward methods.
waveguide-grating-routers-based realization of time-spreading and wavelength-group-hopping over fiber-to-the-home networks. exploiting the inherent cyclic and periodic free-spectral- range (fsr) properties of arrayed-waveguide grating (awg) routers, the time-spreading and free-spectral-range (fsr) group hopping code, which is embedded by maximum length sequences (called ts/gh embedded m-sequence code) is configured over a fiber-to-the-home (ftth) network. for constructing the proposed code, we use the same prime code for generating the time code (time-spreading code) and the spectral domain code (group hopping code). therefore it is referred to as a two-dimensional (2-d) optical code. importantly, for the proposed broadband light source (bls), the total number of available wavelengths is partitioned into g different groups according to the length of the m-sequence code. every group is referred to as a hopping pattern and characterized by the fsr interval of the awg router. improving the prime-hop code (phc) and the modified prime-hop code (mphc) with cascading one additional awg router, the cardinality of the proposed scheme is significantly increased by a factor of 15 under the optimum arrangement for a group hopping number of g=7. moreover, the correlation property and bit error rate (ber) of proposed scheme is evaluated and the result reveals an improvement of the ber compared to mphc and phc.
dynamic decode-and-forward and amplify-and-forward cooperative strategy using distributed space-time code in uplink mimo systems with multiple relays. we extend the idea of hybrid decode-and-forward (df)/amplify-and-forward (af) relaying scheme for single relay to the multiple relays scenario and refer to it as dynamic df/af scheme. in this dynamic scheme, each relay in the system chooses, packet by packet, between df and af dynamically and independently by examining the cyclic redundancy check (crc) result of the packet. the relays encode the mixed df/af signals into a distributed linear dispersion code (dldc), and then transmit the coded signals to the destination. we show that our proposed dynamic df/af scheme outperforms the df and af schemes over a wide signal-to-noise ratio (snr) range. we also propose a more general and flexible form of dldc, which treats the source-relay link and relay-destination link separately and allows their packet durations to be different. in particular, we assume that the destination has multiple antennas and uses a general two-stage linear mmse receiver to detect the possibly mixed df/af signals, without knowing the forwarding types adopted at the relays. a channel estimator is embedded in the receiver to estimate the source-relay link channel state information (csi). with this receiver, only partial csi (the csi of the combined source-relay and relay-destination link) is required at the destination. the simulation results show that the degradation due to this two-stage receiver is minimal when compared to the optimal, but more complex, ml receiver with full csi and knowledge of relay forwarding types.
adaptive antenna array interference mitigation diversity for decentralized dynamic spectrum allocation in license-exempt spectrum. decentralized dynamic spectrum allocation (dsa) that exploit adaptive antenna array interference mitigation (im) diversity at the receiver, is proposed for interference-limited environments with high level of frequency reuse. the system consists of base stations (bss) that may belong to different providers in license-exempt spectrum, who can optimize uplink frequency allocation to their subscriber stations (sss) to achieve the least impact of im on the useful signal, assuming no control over band allocation of other bss sharing the same bands. the im-based dsa algorithms based on a "good neighbor" decentralized dsa strategies are proposed. the new strategy introduces controllable behavior of decentralized networks, which promises a practical perspective for im-based dsa algorithms even without guarantee of the network convergence to stationary points.
decision directed channel estimation for ofdm systems employing fast data projection method algorithm. in this paper we propose a fast data projection method (fdpm)-based channel impulse response (cir) estimator of a decision directed channel estimation (ddce) scheme for ofdm system. the proposed algorithm is employed in the context of a more realistic channel condition, the fractionally spaced (fs)-cir based channel model. the performance of the proposed algorithm is compared with an earlier proposed deflated projection approximation subspace tracking (pastd) algorithm. it is found from the simulation results that the fdpm-based ddce outperformed the pastd-based ddce.
sip network design to prevent congestion caused by disaster. we present a session initiation protocol (sip) network design for a voice-over-ip (voip) network to prevent congestion caused by people calling friends and family after a disaster. the design increases the capacity of sip servers in a network by using all the sip servers equally. the design uses a property that sip network elements do not carry voice data packets but signaling packets instead. furthermore, the design achieves simple routing based on telephone numbers. we evaluate the performance of preventing congestion through simulation. we show that the proposed design has roughly 20 times more capacity, which is 57 times of the normal load, than the conventional design if a disaster were to occur in niigata prefecture.
stochastic decoding of ldpc codes over gf(q). nonbinary ldpc codes have been shown to outperform currently used codes for magnetic recording and several other channels. currently proposed nonbinary decoder architectures have very high complexity for high-throughput implementations and sacrifice error-correction performance to maintain realizable complexity. in this paper, we present an alternative decoding algorithm based on stochastic computation that has a very simple implementation and minimal performance loss when compared to the sum-product algorithm. we demonstrate the performance of the algorithm when applied to a gf(16) code and provide details of the hardware resources required for an implementation.
on the minimum k-connectivity repair in wireless sensor networks. repairing connectivity and achieving a certain level of fault tolerance are two important research challenges in wireless sensor networks that have, in many papers in the literature, been jointly studied. most of the proposals that aim at restoring network connectivity deal with the network as a general graph of n nodes with the edge cost being the number of nodes needed to establish connectivity between the two ends of the edge. this assumption ignores the topological properties of the network, especially the overlap between sensors' communication ranges, and the node-failure pattern that caused the disconnection. in this paper, we try to exploit these properties to minimize the number of additional nodes needed to repair the connectivity.
distributed gradient based gain allocation for coherent multiuser af relaying networks. a set of distributed non-cooperating relay antennas is known to be capable of orthogonalizing multiple source-destination pairs in space by coherent amplify-and-forward (af) relaying techniques. known relay gain allocation schemes for this setup require either global knowledge of the channel coefficients between all participating nodes or an excess number of relays. the required dissemination of the channel state information (csi) introduces a major overhead, which in practice may well diminish the spatial multiplexing gain. we introduce a new distributed gradient based gain allocation scheme, which minimizes this overhead. key to this is the proof, that the gradient of the destination signal-to-interference-plus-noise ratio (sinr) can be calculated in a distributed manner based on local csi at the relays and very limited feedback from the destinations. in order to minimize the number of iterations in the distributed gradient algorithm we propose two distributed approaches to determine the optimal step size for each iteration. finally we provide simulation results on the sum rate performance and identify the sequential opening of the spatial channels as a key factor that impacts speed of convergence.
an effective sip security solution for heterogeneous mobile networks. with the evolution and penetration of the ip-based core network and the mobile access networks, more and more legacy services are being transferred to the converged and unified ip-based platform. for realizing this transfer, sip (session initiation protocol) has been adopted by standards bodies for creating, modifying, and terminating multimedia sessions. sip with application-level mobility support can replace mip (mobile ip) to provide a fmc (fixed mobile convergence) solution. taking the important role of sip into account, it is critical to fully resolve the sip security issues including service authentication, confidentiality, and integrity protection on both signaling and data transmission. ipsec (ip security) and the combination of tls (transport layer security) and srtp (secure real-time transport protocol) are two typical sip security solutions that can protect signaling and data transmission from various security attacks. however, these security solutions don't consider the issue of mobility support during the handover of mobile nodes among different access networks. this paper, therefore, proposes an effective sip security solution that realizes sip security with seamless mobility support across heterogeneous mobile networks. we compare the proposal to existing approaches and show that it better satisfies the sip security requirements in terms of security, mobility support, and performance.
interference aware subcarrier assignment for throughput maximization in ofdma wireless relay mesh networks. the wireless relay mesh network (wrmn) is designed to provide robust and fault tolerant communications between relay and user nodes in broadband wireless networks. in this paper, we study interference aware resource allocation in ofdma based wrmns and the effects of spatial reuse on throughput. we propose an interference aware subcarrier assignment (iasa) algorithm to allocate subcarriers to links in the network such that interference is mitigated and throughput is maximized. the protocol interference model and spatial reuse are exploited to achieve the subcarrier assignment. we show that our iasa algorithm improves throughput compared to when subcarriers are used only once. however, overuse of a single subcarrier can have detrimental effects on network performance, therefore a balance must be achieved. in addition, using a maximum concurrent flow (mcf) approach, we show that under the iasa scheme of spatial reuse, throughput can be enhanced. we formulate the mcf as a linear program and solve it using dual optimization techniques. we compare our proposed algorithm with that of a graph coloring approach using a conflict graph and column generation to show that our throughput results are better than those obtained by the link coloring strategy.
power allocation for wireless communications using variable time-fraction collaboration. in order to increase spatial diversity, collaborative protocols have recently been investigated. this allows nodes not equipped with multiple transmit antennas the ability to achieve high levels of diversity. in previous works, the authors proposed and analyzed a collaborative protocol using variable time-fraction. in this paper, the scheme is further expanded to include the case where the transmitting nodes have access to the channel state information (csit). the outage probability of such a scenario is obtained. in order to exploit the csit, an optimal power allocation algorithm (opaa) is proposed. furthermore, we present a simpler, more robust suboptimal paa. an upper bound on the frame error rate is obtained and the different paas are analyzed. the opaa shows a gain of 3 db compared to a non csit scheme. the results also show the advantages of using paa with a variable time-fraction for any relay location.
understanding the roles of servers in large-scale peer-assisted online storage systems. online storage systems that provide versatile and convenient platforms for content distribution have attracted significant attention over the internet. to guarantee adequate levels of service quality and to minimize server cost, such systems typically deploy dedicated servers while effectively utilizing peer bandwidth in a complementary fashion. it is essential to understand the role of servers and critical factors that influence the server contributions. in this paper, with full knowledge of internal mechanisms of a large-scale peer-assisted online storage system, namely fs2you, and large set of real-world traces, we examine the role of servers in such a system. specifically, through analyzing server traffic volumes versus various critical factors including file popularity, time period (both "cold" and "hot" periods), and peer types, we not only reveal empirical observations that are contrary to general belief with in-depth rationales, but also exploit potential flaws of current design and strategy, which further draw practical implications on future design.
utility-based user grouping and bandwidth allocation for wireless multicast systems. with the proliferation of wireless multimedia applications, multicast/broadcast has been recognized as an efficient technique to transmit a large volume of data to multiple mobile stations at the same time. in most multicast systems, the transmitter (e.g. base station) adapts its data rate to the furthest located users, so as to guarantee service quality to as many users as possible. predictably, the more users in a multicast group, the lower data rate the base station can transmit. on the other hand, grouping more users together leads to a more efficient utilization of spectrum bandwidth, as these users are served simultaneously. this bring the interesting problem that presses for solution: how to group users in a cell into multicast groups and how to allocate a fixed amount of bandwidth resource to the groups, to achieve a good balance between throughput and fairness in multicast systems. in this paper, we formulate the united user grouping and bandwidth allocation strategy into a utility-based optimization problem. one method of signomial programming is used to solve the non-convex optimization problem. numerical results will show that this suboptimal algorithm performs well even compared to the optimal one. moreover, through theoretical analysis, we prove that the best user grouping and bandwidth allocation scheme of throughput maximization is to allocate the entire bandwidth to the unique group containing the users located within a ring-shaped region with an optimal outer radius r*.
load balancing vs. distributed rate limiting: an unifying framework for cloud control. with the expansion of cloud-based services, the question as to how to control usage of such large distributed systems has become increasingly important. load balancing (lb), and recently proposed distributed rate limiting (drl) have been used independently to reduce costs and to fairly allocate distributed resources. in this paper we propose a new mechanism for cloud control that unifies the use of lb and drl: lb is used to minimize the associated costs and drl makes sure that the resource allocation is fair. from an analytical standpoint, modelling the dynamics of drl in dynamic workloads (resulting from lb cost-minimization scheme) is a challenging problem. our theoretical analysis yields a condition that ensures convergence to the desired working regime. analytical results are then validated empirically through several illustrative simulations. the closed-form nature of our result also allows simple design rules which, together with extremely low computational and communication overhead, makes the presented algorithm practical and easy to deploy.
distributed beamforming and rate allocation in multi-antenna cognitive radio networks. we consider decentralized multi-antenna cognitive radio networks where secondary (cognitive) users are granted simultaneous spectrum access along with license-holding (primary) users. we investigate the problem of designing beamformers for the secondary users by maximizing the minimum rate, subject to a limited sum-power budget and constraints on the interference level imposed on each primary receiver. we consider two scenarios: the first one allows only single-user decoding at each secondary receiver whereas in the second case each secondary receiver is allowed to employ advanced multi-user decoding and is free to decode any subset of secondary users. we provide an optimal distributed algorithm for the first scenario and an explicit formulation of the optimization problem corresponding to the second scenario. this problem however is non-convex and hence cannot be efficiently solved even in a centralized setup. as a remedy, we suggest a two-step approach. in particular, the beamformers are first designed assuming single user decoding at each secondary receiver. an optimal distributed low-complexity algorithm is then proposed to allocate excess rates to the secondary users, which are made possible due to the use of advanced decoders at the secondary receivers. simulation results demonstrate the gains yielded by the optimal beamformers as well as the rate allocation algorithms.
voip malware: attack tool & attack scenarios. with the appearance of new internet services like voice over ip and ip television, malwares are in the way to update and extend their targets. in this paper, we discuss the emergence of a new generation of malwares attacking voip infrastructures and services. such malwares constitute a real threat to the currently deployed voip architectures without strong security measures in place. we present one implemented environment that can be used to evaluate such attacks. our "voip bots" support a wide set of attacks ranging from spit to ddos and are tested against several voip platforms.
approximate flow-aware networking. a new variation of the flow-aware networking (fan) concept is presented in the paper. the proposed solution is based on the approximate fair dropping algorithm and called by us approximate flow-aware networking (afan). the simplicity of the new proposal is assured as a result of using only two fifo queues for the scheduled packets. the impact of congestion control mechanisms proposed for flow-aware networks on packet transmission in the overloaded network for the afan is also presented. the analysis shows how to choose the values of the parameters which decide of proper transmission characteristics of the network. the results of the research are compared with those obtained for the other two fan architectures, with the pfq (priority fair queuing) and with the pdrr (priority deficit round robin) scheduling algorithms. the advantages and weaknesses of the new proposal are described and analyzed.
service coalitions for future internet services. this paper proposes an algorithm that enables the support for a service market place in which service providers can negotiate and form coalitions in a self-centred approach. we present the main features of the algorithm and evaluate the proposed solution under different technical aspects including social network topology, scalability and convergence to optimal results.
bandwidth efficiency of practical mimo-ofdm systems with adaptive mimo schemes. this paper considers the practical multiple-input multiple-output systems with orthogonal frequency division multiplexing (mimo-ofdm) and bit-interleaved coded modulation (bicm) in spatially correlated broadband channels. using link adaption techniques, the mimo scheme that better exploits the space and frequency characteristics of the encountered channel condition is selected. it is shown that the bandwidth efficiency is increased compared to systems with fixed mimo schemes in all propagation scenarios, while maintaining a predefined link quality. furthermore, the adaptive transmission in channels with low spatial correlation can attain the complete multiplexing gain, whereas the finite set of modulation and coding schemes restricts the multiplexing gain that can be extracted when the spatial correlation is large.
weighted sum-rate maximization scheduling for mimo ad hoc networks. in this paper, we propose a duality-optimization based framework to maximize the weighted sum throughput for a multiple-input multiple-output (mimo) ad hoc network. the new schemes include an approximate global optimization approach and an iterative search approach based on the duality framework. transmitter adaptive precoding and receiver minimum mean-square-error (mmse) detection for interference suppression are considered. simulation results show that a significantly higher throughput is achieved for the dual optimization schemes than for the fixed mode precoding schemes and the transmit iterative waterfilling (iwf) scheme. the negative effects of transmit and receive antenna correlations are also studied. results show that the proposed schemes are more robust against both transmit and receive correlations than the fixed-mode and iwf schemes.
performance analysis of the edca medium access mechanism over the control channel of an ieee 802.11p wave vehicular network. the fcc has set apart a frequency band with the specific goal of improving safety and efficiency of the transportation system. its purpose is to provide wireless communications between stations on the roadside and mobile radio units located on board of vehicles. the resulting technology is known as wave and is currently under development as draft standard ieee 802.11p. the most time-critical messages, carrying urgent safety-related information, are transmitted over the so-called control channel (cch). wave devices use the edca mac protocol, defined in the 2007 version of the ieee 802.11 standard, to compete for the transmission medium. this work analyzes the performance of edca under the specific conditions of the cch of a wave environment. the protocol is modeled using markov chains and results related to throughput, frame-error rate, buffer occupancy and delay are obtained under different traffic-load conditions.
exploiting cooperative diversity and spatial reuse in multihop cellular networks. multihop cellular networks employ relay stations to enhance end-to-end link quality in terms of capacity, coverage and reliability. techniques like cooperative relaying and spatial reuse can further improve the network performance. efficient resource allocation algorithms are required to exploit the potential advantages. in this paper we first introduce three relaying schemes, and show that there is a trade-off between cooperative diversity and spatial reuse. then we propose an efficient resource allocation algorithm to fairly allocate the resource among users in multihop cellular networks. the algorithm exploits both spatial reuse and cooperative diversity. simulations show that the proposed algorithm outperforms the algorithms with only cooperative diversity or only spatial reuse.
flexible single sign-on for sip: bridging the identity chasm. identity federation is a key requirement for today's distributed services. this technology allows managed sharing of users' identity information between identity providers (idp), and subsequently, the use of federated identities to access service providers (sp). single sign-on (sso) is a core feature provided by these systems. the session initiation protocol (sip) is a signaling framework for session call control. it is becoming a widely accepted layer for applications and services, especially in the telecommunications and multimedia domain. in this paper, we explore solutions to incorporate sso process into the sip framework in order to simplify the services and resources access. our design leverages the liberty alliance specifications and extends the existing sip standards to support sso functionality. we also present a prototype implementation at the end of this paper.
reliability and efficiency analysis of distributed source coding in wireless sensor networks. we propose a comprehensive theoretical framework to evaluate reliability and energy consumption of distributed source coding (dsc) in wireless sensor networks (wsns) applications. energy efficiency and the amount of measurements that can be successfully decoded in tree-based wsns employing dsc in the presence of different coding topologies and packet aggregation schemes (pa) are accurately characterized. the system model includes a realistic network architecture with multi-hop communication, automatic repeat request protocol (arq), packet losses due to channel impairments and collisions, and correlation properties of the sensed phenomena. four dsc topologies and three alternatives of pa are considered. the analysis is carried out by evaluating the expressions of reliability of dsc in terms of probability of measurements that cannot be decoded (loss factor), and the efficiency in terms of average energy consumption of the network. numerical results show that the best choice of dsc topology and packet aggregation depends highly on the network parameters and source characteristics. therefore, the analysis developed in this paper can be used as an effective mean to optimize network operations.
contention-aware cooperative routing in wireless mesh networks. cooperative communication is a new physical layer technique which improves link capacity by exploiting broadcast nature and spatial diversity of wireless channel. the introduction of cooperative communication in wireless networks changes the traditional definition of link and the contention relationship among links. in this paper, we focus on cooperative communication aware routing protocol design in wireless mesh networks, targeting at maximizing the overall end-to-end throughput of the whole network and meanwhile taking contention relationship among multiple links into consideration. we propose a routing metric called contention-aware cooperative metric (ccm) and prove that ccm has the isotonic property. therefore, efficient algorithms such as dijkstra or bellman-ford can be used to find ccm-based minimum cost paths. based on ccm, we propose a routing protocol called contention-aware cooperative routing (ccr) which can be implemented in both link-state and distance-vector routing protocols. extensive simulations are conducted on ns-2 to evaluate the performance of our novel routing metric and routing protocol. the results show that ccr achieves significant throughput gain compared with hopcount-based routing and ett-based routing. the end-to-end delay is also dramatically reduced under ccr routing.
efficient and adaptively secure append-only signature. most of digital signatures require the secret key when signing a message, however, there does exists a kind of signature scheme which is able to sign by appending new message only, so-called append-only signature (aos) [9]. motivated by its numerous useful applications in network security such as secure routing, etc., in this paper, we propose new efficient aos scheme with shorter public key (parameters) using id-based cryptographic techniques. to our surprise, it is the first time to achieve a practical, adaptively secure aos via id-based encryption approach. the proposed signature enjoys the merit of security against adaptive attack, while the previously presented aos is only secure in a weak sense of selective unforgeability. finally, we also present a new restricted aos (raos) signature, which may be of independent interest in practice.
connectivity of finite wireless networks with random communication range nodes. one of the most important topological characteristics of a network is its connectivity. this work analyzes the connectivity of one-dimensional wireless networks considering finite number of randomly deployed nodes with random communication ranges. in particular, it focuses on the probability of being able to convey a message from the source to the sink given certain number of nodes. the method to address the problem is by mapping it to the problem of covering a circle with arcs of random sizes. this paper provides an analytical solution when the communication ranges of the nodes are distributed uniformly over the field of interest. in addition, and of practical relevance, it shows how the random communication radii model can represent certain kind of randomness in the communication channel. specifically there is a comparison between our model and the log-normal shadowing statistical model. stochastic simulations validate the derived formula as well as its approximation to the standard shadowing model. in agreement to previous results for wireless networks, this work verifies that the requirements on the number of nodes to have a connected network may be relaxed when the nodes have random communication radii.
parallel detection algorithm with selective interference cancellation for v-blast systems. maximum-likelihood detection (mld) is the optimal scheme for vertical bell laboratories layered space-time (vblast) systems. however, due to its exponentially high complexity, many alternative algorithms, including some parallel detection (pd) ones with low complexity and high stability, have been proposed instead for practical applications. nevertheless, the existing pd algorithms are unable to exploit sufficiently the diversity order increment for low-complexity algorithms via exhaustive interference cancellation (eic) and the complexity of the sub-detectors is still undesirably high. in this paper, a novel pd algorithm with relative low-complexity sub-detectors, i.e., the selective-interference-cancellation sub-detectors, has been developed. the algorithm is abbreviated as pdsic algorithm. numerical analysis indicates that the pdsic algorithm can achieve the near-optimal performance with much lower complexity in comparison with the existing pd algorithms. thus, the pdsic algorithm makes the parallel detection more feasible in practical systems with limited parallel processing elements.
gmpls network reliability enhancement by using the dominating nodes approach. the impact of the control plane architecture on reliability of the gmpls network is studied. to improve this reliability, a method based on the graph-theoretical dominating set problem is proposed. several algorithms to select dominating nodes are presented and evaluated for four different network topologies by using simulation methods. it is shown that the service recovery time can be shortened by using the presented approach.
error resilient non-asymmetric slepian-wolf coding. we consider non-asymmetric distributed source coding (dsc) that achieves any point in the slepian-wolf (sw) region. we study the error propagation phenomena and propose a decoding algorithm which limits this phenomena. for the case of turbo-codes, design rules are derived in order for the decoder to recover the sources.
transmission capacity of wireless ad hoc networks: successive interference cancellation vs. joint detection. the performance benefits of two interference cancellation methods, successive interference cancellation (sic) and joint detection (jd), in wireless ad hoc networks are compared within the transmission capacity framework. sic involves successively decoding and subtracting out strong interfering signals until the desired signal can be decoded, while higher-complexity jd refers to simultaneously decoding the desired signal and the signals of a few strong interferers. tools from stochastic geometry are used to develop bounds on the outage probability as a function of the spatial density of interferers. these bounds show that sic performs nearly as well as jd when the signal-to-interference ratio (sir) threshold is less than one, but that sic is essentially useless for sir thresholds larger than one whereas jd provides a significant outage benefit regardless of the sir threshold.
optimising radio access in a heterogeneous wireless network environment. a variety of wireless network technologies have been developed and deployed, including gsm, umts, wifi and wimax. the advantages of having an integrated heterogeneous wireless network environment include seamless communications, joint resource management and adaptive quality of service. in such environment, operators would not need to reject the service requests, but redirect them to appropriate networks. however, the sought aims of a heterogeneous network system still have many pending issues. one of them is the selection of the most appropriate radio access network (ran) according to the requested service and the context information about the user and the networks. we aim to develop efficient ran selection algorithms to facilitate radio access optimisation for future heterogeneous network system. the simulation results show that our ran selection algorithm can improve the network performance.
near-optimal relaying strategy for cooperative broadcast channels. we propose a near-optimal relaying strategy for cooperative broadcast channels (cbc), cbc-ssaf, based on the class of sequential slotted amplify and forward (ssaf) strategies. our strategy allows each destination to act in turn as a relay and forward its previously received signal to other destinations. while cbc-ssaf is not a full multiplexing gain strategy, the loss is negligible when the number of destinations is large. moreover, cbc-ssaf allows each destination to be protected by the maximum number of extra paths in order to achieve the near-optimal diversity gain in the high multiplexing gain regime. a diversity and multiplexing tradeoff (dmt) lower bound for cbc-ssaf is derived which suggests that our proposed relaying strategy approaches the multiple-input multiple-output (mimo) dmt upper bound and is therefore asymptotically optimal.
distributed ecn-based congestion control. following the design philosophy of xcp, vcp is a router-assisted congestion protocol that intends to balance the efficiency and the fairness control in high bandwidth-delay product networks. while both vcp and xcp achieve comparable performance, vcp represents a more practical alternative of deployment as it only requires the use of two ecn bits in the ip header. however, the use of two ecn bits only allows for establishing three levels of congestion notification signaling. our previous work reveals that vcp suffers from relatively low speed of convergence and exhibits a biased fairness behavior in moderate bandwidth high delay networks due to utilizing an insufficient amount of congestion feedback. in this paper, we propose a distributed ecn-based congestion control protocol to which we refer as double-packet congestion control protocol (dpcp). dpcp is capable of relaying a more precise congestion feedback compared to earlier proposed variable-structure congestion-control protocol (vcp) yet preserving the utilization of the two ecn bits. by distributing (extracting) congestion related information into (from) a series of packets, dpcp is able to circumvent the limitations of vcp related to the use of three congestion levels encoded into two ecn bits. we implement dpcp in linux and demonstrate its performance improvements compared to vcp through experimental studies.
second order statistics of non-isotropic mobile-to-mobile ricean fading channels. this paper develops a generic geometry-based stochastic model for mobile-to-mobile (m2m) ricean fading channels. from the generic model, the level crossing rate (lcr) and average fade duration (afd) are derived. based on the derived expressions, we for the first time investigate the lcr and afd for m2m channels with different vehicular traffic densities (vtds). excellent agreement is achieved between the theoretical results and measured data, demonstrating the utility of the proposed model.
optimization of cooperative sensing in cognitive radio networks: a sensing-throughput tradeoff view. in cognitive radio networks, protection to primary users can be quantified by the probability of detection. on the other hand, the probability of false alarm affects the achievable throughput of secondary users. performances of these two probabilities depend heavily on the fusion scheme used when cooperative sensing is performed. in this paper, we consider the case where n secondary users sense the channel cooperatively using k-out-of-nfusion rule. a sensing-throughput tradeoff under cooperative sensing scenario is formulated to find a pair of sensing time and k value that maximize the secondary users' throughput subject to sufficient protection provided to the primary user. an iterative algorithm is proposed to obtain the optimal values of these two parameters. computer simulations show that significant improvement of the secondary users' throughput can be achieved when the parameters from the fusion scheme and sensing time are jointly optimized.
signal classification using a peak-to-average power ratio statistic. this paper addresses signal classification based on an average power statistic for peak-to-average-power ratio (par) reduced signals. specifically, it is assumed that either a qam or a complex gaussian finite-length symbol is transmitted in a noisy, peak-limited channel with known peak power. the goal is determine the whether an uninformed receiver can distinguish between these signal types using an average power statistic. several methods for transmitting through peak-power channels are examined including optimal clipping and piecewise linear scaling (pwls) with selected mapping (slm) par reduction. for the analysis, it is necessary to derive the mean power for each of the transmission methods. accordingly, we show how the harmonic mean par, e[1/par], is related to the mean power and derive e[1/par] in closed form. we find that average power is a accurate discriminator for low-order qam and gaussian symbols. for high-order qam, accurate discrimination is also possible when the noise level is sufficiently low or when enough signal samples are available.
error probability of energy detected multilevel pam signals in lognormal multipath fading channels. noncoherent multilevel systems have been typically analyzed with spectrally inefficient orthogonal modulation methods. in this paper, we present a novel error probability analysis of energy detected (ed) signals with spectrally efficient multilevel pulse amplitude modulation (pam). one of the main challenges in the analysis of ed systems with the multilevel pam is to find analytical methods to evaluate and optimize the performance of ed systems with respect to arbitrary system parameters, e.g., decision thresholds for chi-squared-distributed decision variables, integration time, bandwidth, and number of modulation levels. we propose analytically tractable methods that can be efficiently used to design spectrally efficient ed systems for short-range, wideband, and high data rate wireless communications in lognormal multipath fading channels with uncorrelated diversity paths.
generalized differential vector signaling. binary nrz signaling over single ended or fully differential parallel wired channels is commonly used for chip-to-chip communications. this paper presents differential vector signaling as a generalized new class of signaling for parallel wired links. differential vector signaling has many of the benefits inherent to differential signaling while maintaining high pin efficiency of single ended parallel links and offers an alternative solution for high speed chip-to-chip interconnections. the signaling is viewed as a multi-wire coded communication system. the encoding method and the maximum likelihood decoding algorithm are presented. also a variant of this signaling which requires a reduced complexity receiver is proposed.
marking conversion for pre-congestion notification. pre-congestion notification (pcn) defines admissible rates (ar) and supportable rates (sr) per link and marks the pcn traffic rate above these thresholds as ar- or sr-overload. the ietf standardizes simple mechanisms for admission control (ac) and flow termination (ft) based on this pcn-feedback for high-priority diffserv traffic. while admission control (ac) has been extensively discussed in the literature, flow termination (ft) is a new control function. in this paper we propose an algorithm that converts marked ar-overload into marked sr-overload by unmarking appropriate packets. classic marked flow termination (mft) is based on marked sr-overload and works well even with a small number of pcn flows per ingress-egress aggregate and in case of multipath routing. thanks to the new marking converter mft also works with marked ar-overload so that a single marking scheme suffices to support ac and ft. we investigate whether mft with marking conversion based on ar-overload retains the benefits classic mft.
a fault-tolerant backbone network architecture targeting time-critical communication for avionic wdm lans. in this paper, we focus on the design and analysis of a torus-based backbone architecture which targets to meet both the low delay and high reliability requirements of avionic time-critical communications. reliable optical connection between arbitrary source-destination pairs is proposed by enabling four non-overlapping lightpaths between the source and destination, which makes the network tolerant to at least three arbitrary link failures without losing connectivity. a greedy algorithm is introduced to set up the four non-overlapping lightpaths with the aim of maximizing two-terminal reliability (ttr), as well as minimizing signal attenuation and propagation delay. a wavelength assignment and reuse (war) method is used to reduce by half the wavelength requirement for all-to-all communication in a case study of 4×4 torus. both probabilistic analysis and a packet-level simulation reveal that the proposed architecture can provide efficient communication with a 3-fault reliability guarantee.
interference-aware energy-efficient power optimization. while the demand for battery capacity on mobile devices has grown with the increase in high-bandwidth multi-media rich applications, battery technology has not kept up with this demand. therefore power optimization techniques are becoming increasingly important in wireless system design. power optimization schemes are also important for interference management in wireless systems as interference resulting from aggressive spectral reuse and high power transmission severely limits system performance. although power optimization plays a pivotal role in both interference management and energy utilization, little research addresses their joint interaction. in this paper, we develop energy-efficient power optimization schemes for interference-limited communications. both circuit and transmit powers are considered and energy efficiency is emphasized over throughput. we note that the general power optimization problem in the presence of interference is intractable even when ideal user cooperation is assumed. we first study this problem for a simple two-user network with ideal user cooperation and then develop a practical non-cooperative power optimization scheme. simulation results show that the proposed scheme improves not only energy efficiency but also spectral efficiency in an interference-limited cellular network.
an automatic and dynamic parameter tuning of a statistics-based anomaly detection algorithm. the detection of anomalies in network traffic is a crucial issue affecting the security of internet users. a statistical network anomaly detection algorithm is a promising way of detecting such anomalies, however, it has to be given appropriate parameters for accurate detection and identification. in general, it is very difficult to obtain appropriate parameter settings a priori, because network traffic is not stable in time or space. thus, although many anomaly detection methods have been proposed, there has been little discussion about their parameter tunings. in this paper, we investigate an automatic and dynamic parameter tuning of a statistical network traffic anomaly detection method. in particular, we clarify whether one can consistently use the best parameter fixed for a certain instance; this choice clearly depends on the macroscopic and dynamic behavior of internet traffic anomalies. we ascertain the appropriate learning period for setting a parameter of an anomaly detection algorithm based on a sketch and multi-scale gamma-function model by using real network traces measured in a trans-pacific link over a period of six months. the main results of our study are as follows: (1) without learning, the best parameter varies day by day. (2) with a longer learning period, the best parameter setting is affected by significant data during the learning period. (3) the appropriate period of the learning is about 3 days. (4) the performance degradation from introducing dynamic parameter tuning is 17% in the best case.
mean waiting delay for web object transfer in wireless sctp environment. most current web application use http (hyper text transfer protocol) and tcp (transmission control protocol) to retrieve objects from the internet. sctp (stream control transmission protocol) is recently proposed transport protocol with congestion control mechanism similar to that of tcp. waiting delay is an important performance criterion for when transferring web object over the internet. in this paper, we present an analytical model of mean waiting delay for object transfers over the internet in a wireless using the sctp as the transport protocol and compare with the mean waiting in using tcp. validation of the model using experimental results show that the mean waiting delay for http over sctp is less than that for http over tcp. this is caused by the small slow-start time of sctp.
a polite cross-layer protocol for contention-based home power-line communications. in typical home power-line communication (plc) networks using contention-based access methods, providing quality-of-service (qos) to high-priority users often comes at the expense of reducing the throughput of low-priority users. this paper proposes a cross-layer protocol which involves interaction between the physical (phy) and the medium-access-control (mac) layers, for ensuring politeness of the high-priority users toward the low-priority users for uplink transmission in home plc networks. this protocol modifies the contention-based csma protocol of the mac layer to exploit the cyclostationarity of the noise in home plc networks. the plc noise spectrum has been shown in literature to be periodic with the period of ac line cycle. using this periodicity, the proposed protocol allows longer medium-access times for low-priority users in every ac line cycle, while meeting the high throughput requirements of the high-priority users. the proposed cross-layer protocol, termed opportunistic csma, improves the throughput of the low-priority users by as much as 300% compared to the current csma protocols in home plc networks.
distributed intrusion detection with intelligent network interfaces for future networks. intrusion detection remains an important and challenging task in current and next generation networks (ngn). emerging technologies such as multi-core processors and virtualization have changed the architecture of the building elements of ngn significantly, thus call for rethinking of how network processing is done. in this paper, we propose distributed intrusion detection using intelligent network interfaces where additional processing capabilities are available. we design and implement a prototype to perform pattern matching using network processors since pattern matching is one of the important workloads in intrusion detection. through the experimental results, we show the feasibility and performance of distributed intrusion detection in next generation networks.
real-time traffic in ad-hoc sensor networks. the usage of sensors is emerging in the nowadays scenario where safety related applications are more and more used. these applications have timing constraints that need to be met by the control system. thus, guaranteeing timeliness properties is considered a key challenge for research on wireless sensor networks. among the different components that need to address this problem, we focus on the communication sub-system and, in particular, on the mac protocols that handles transmissions. to provide timeliness behavior, the employed mac protocol has to provide a time-bounded service. the contribution of this paper is to investigate the performance of two wireless mac protocols that can be employed in wireless sensor networks: ieee 802.11e and wrt-ring. the former is part of the well know ieee 802.11 standard, whereas the latter has characteristics that well fit the requirements of wireless sensor networks. results show that two protocols have similar performances for networks with limited devices and/or traffic, whereas when devices and/or traffic increases, wrt-ring has to be preferred.
routing-based source-location privacy in wireless sensor networks. wireless sensor networks (wsn) have the potential to be widely used in many areas for unattended event monitoring. mainly due to lack of a protected physical boundary, wireless communications are vulnerable to unauthorized interception and detection. privacy is becoming one of the major issues that jeopardize the successful deployment of wireless sensor networks. while confidentiality of the message can be ensured through content encryption, it is much more difficult to adequately address the source-location privacy. for wsn, source-location privacy service is further complicated by the fact that the sensor nodes consist of low-cost and low-power radio devices, computationally intensive cryptographic algorithms (such as public-key cryptosystems) and large scale broadcasting-based protocols are not suitable for wsn. in this paper, we propose a scheme to provide both content confidentiality and source-location privacy through routing to a randomly selected intermediate node (rrin). while being able to provide source-location privacy for wsn, our simulation results also demonstrate that the proposed scheme is very efficient and can be used for practical applications.
protocols and resource allocation for the two-way relay channel with half-duplex terminals. the two-way relay channel (twrc) describes the communication between two terminals sharing a common relay. in this work we compare different protocols for the twrc with a half-duplex relay (forwarding and protocol i) and transmission schemes (network coding relaying with random binning and xor precoding), when the relay works in decode-and-forward and without channel state information at the transmitters. we provide the optimal resource allocation (in terms of phase duration, data rate and power allocation) when there is an individual or sum-average power constraint over the terminals. closed-form solutions are derived whenever it is possible, while for others cases we show that the resource allocation can be formulated as a convex problem, which means that the solution can be obtained by low-complexity interior point methods.
three layered hidden markov models for binary digital wireless channels. generative models are created to be used in the design and performance assessment of high layer wireless communication protocols and some error control strategies. generative models can replace real digital wireless channels to significantly reduce the time and complexity of system simulation. the errors occurring in digital wireless channels are not independent but form clusters or bursts. generative models have to produce error sequences having similar burst error statistics to those of original error sequences obtained from real digital systems. in this paper, we propose a generative hidden markov model (hmm) with three layers. it is shown that the proposed three layered hmm can generate error sequences that have statistics compatible with those of original error sequences derived from an enhanced general packet radio service (egprs) transmission system.
performance improvement of error-prone multi-rate wlans through adjustment of access/frame parameters. the ieee 802.11 standard supports multiple phy rates. however, the ieee 802.11 dcf in a multiple-rate environment may cause a performance anomaly. there have been many studies about the performance analysis and improvement of single- and multi-rate wlan systems. however, there were a few studies about a generalized analysis on throughput and channel utilization for successful transmissions in multi-rate wlan systems with different frame parameters and channel errors. in particular, the performance anomaly problem of the multi-rate wlans still needs to be solved. we propose a more generalized mathematical model for each station with a different data transmission time and mathematically analyze the throughput and channel utilization for successful transmission in error-prone multi-rate wlans. moreover, we propose a contention window size adjustment scheme and a payload adjustment scheme to resolve the well-known performance anomaly problem in multi-rate wlans by achieving temporal fairness. numerical results show that the proposed scheme is very effective in achieving temporal fairness.
target identification and distributed cooperative control of sensor networks. with the advances in communication and embedded systems, the monitoring and/or controlling of physical phenomena that span over wide spatial area have been attempted with deployment of a network of inexpensive and miniature sensors. in this paper, we focus on the automated sensor management for target identification at the application layer. the sensor management is formulated using graph grammar that reactively control the states of the sensors based on their proximity to the target and the states of their neighboring sensors. target identification, on the other hand, concerns the estimation of the target's kinematics and attributes. the current practice is often formulated as finding the conditional probability of the target type on features derived from the sensor measurements with statistical pattern recognition. however, due to lack of training data, we demonstrate that the use of semantic latent indexing and stochastic approximation techniques, borrowed from the computer science community, is a more powerful method for sensor management and target identification.
minimum sum expected distortion in cooperative networks. in this paper, we consider a wireless cooperative multimedia decode-and-forward network wherein one relay may assist multiple source-destination pairs. by exploiting the global channel state information at the relay, we propose a power allocation, a time allocation and an iterative joint power-time allocation algorithm to minimize the sum expected distortion. firstly, we separately optimize the relay's transmission power and the system transmission time allocated to each source-destination pair such that the sum expected distortion can be minimized. then, we propose an iterative joint power-time allocation algorithm subject to the relay's total power constraint to further improve the distortion performance. the proposed iterative algorithm is guaranteed to converge to an optimal, despite not necessarily globally optimal, point and can achieve the minimum sum expected distortion among all the schemes.
on low-density mimo codes. multiple antenna systems are promising approaches to increase the data rate of wireless communication systems. there, modulated symbols are multiplexed on multiple transmission antennas. typically an outer error correcting code is used additionally to ensure a desired quality of service for a given data rate. an appropriate communications performance can be achieved by iterative decoding, where probabilistic information are exchanged between outer decoder and the mimo demodulator. however, in this case the mimo demodulator has to calculate probabilistic soft-output values for each bit which can be very complex. in this paper we present a new class of linear block codes named low-density mimo codes which reduces the complexity of the mimo soft-demodulator and the outer channel decoder inherently by code design without decreasing the data rate of the overall system. these ldmc codes can have a better communications performance then state of the art solutions with a order of magnitude smaller decoding complexity.
noise-aware wavelength assignment for wavelength switched optical networks. in transparent wson (wavelength switched optical networks), signals are switched optically and propagate thousands of kilometers without electrical regeneration. over such distances, physical impairments, such as crosstalk, ase noise and so on, can accumulate along the path and lead to signal quality degradation. if the admission of a lightpath will either cause its ber to be too high, or sufficiently degrade the performance of the already established lightpaths, it must be blocked. most of recent research only consider the first case, but ignore the second case, which will lead to service interruption. in this paper, a new noise-aware wavelength assignment scheme called nawa has been proposed, which use iies (impairments impact evaluation scheme) to solve both problems mentioned above in a distributed way. simulations have been conducted and numerical results show that: compared with normal impairment-aware solutions, nawa can eliminate the occurrence of service interruption, and achieve better performance in total blocking.
near successive refinement of gaussian vectors in grassmannian space. in this paperwe look at the problem of successively refining the description of a gaussian i.i.d. source in a grassmannian space. this problem is relevant, for example, in the encoding of channel state information for the limited feedback mimo broadcast channel. we show how it is possible to achieve an isotropic distribution of the error vector by applying unitary transformations, which simplifies the problem of finding optimal codebooks for the error quantisation. reconstruction error analysis and numerical tests show how the proposed technique can, in practice, perform very close to the distortion-rate bound and suggest that, in some cases, these successive error descriptions can be optimal refinements of one another.
an optimal sensor network for intrusion detection. wireless sensor networks have been widely used in environment and habitat monitoring, as well as in military applications such as battlefield surveillance. in this paper, we focus on detecting intruders in such surveillance systems. our goal is to optimize the network coverage when the network is deployed to detect an intrusion object with the shape of a disc or a rectangle. we study how the size and shape of the intrusion object influence the configuration of the sensor network. we prove many mathematical results related to detection probability and intrusion coverage intensity and study the asymptotic properties of these detection metrics. we also study the problem of maximizing network lifetime under some qos constraints. we prove the existence of the solution and derive the explicit form of the solution under certain conditions.
to sort or not to sort: optimal sensor scheduling for successive compress-and-estimate encoding. in this paper, we address the problem of energy-efficient decentralized parameter estimation with wireless sensor networks (wsn). more precisely, we adopt the so-called compress & estimate successive encoding scheme and we analyze the impact of the ordering in which the sensor transmissions are scheduled on the resulting estimation accuracy. we consider two scenarios of interest: (i) sensors experiencing different channel gains to the fc (e.g. due to rayleigh fading); and (ii) sensors with different observation qualities. for each scenario, we determine the optimal and worst-case scheduling orders for an arbitrary number of sensors. besides, we propose a suboptimal yet efficient scheduling rule suitable for the case in which sensors experience both different channel gains and observation qualities. performance assessment is carried out by means of computer simulations where we check how sensitive performance can be to the ordering for a varying number of sensors, transmit power and correlation among observations.
performance analysis of the dd ml mimo channel tracking algorithm. in this paper, performance analysis of the decision directed (dd) maximum likelihood (ml) multiple-input multiple-output (mimo) channel tracking algorithm is presented. the ml channel tracking algorithm presents efficient performance especially in the dd mode of the operation. because of the nonlinear decision device, analysis of the dd based algorithms is very difficult. in this paper, first the decision error rate is computed for the known channel tracking error and then the channel tracking error is evaluated for the known decision error rate. the presented analysis is compared with the simulation results for different doppler frequency shifts and snrs, and it is shown that the analysis and simulation results are in a good match even for high rank mimo channels and high doppler shifts.
cross-layer design of networked control systems. the wireless connection of spatially separated sensors, controllers and actuators poses challenging problems to the control system, due to packet drops, delays and measurements quantization, as well as to the wireless network resource allocator. this pushes for a cross-layer design of communication and estimation/control systems. assuming a tcp-like protocol between controller and actuator, we solve the problem of optimum control around a target state for a stable system in case of both packet drops and signal quantization. generalization for unstable systems is also given for large bandwidth transmissions. next, we derive the limiting behavior of the system in the infinite horizon and propose a general framework for cross-layer optimization of signal quantization and network resource allocation. as an example of application, we consider a simple scalar, stable system and compare network resource allocation in the presence of i) low-cost sensors using a fix modulation and ii) long-term future sensors capable of rate adaptation. interestingly, almost optimal control is achievable by small bandwidth transmissions using a simple bpsk, supporting the use of low-cost sensors in applications dealing with state control in stable systems.
an effective cross-layer packet scheduling and routing algorithm for delay-sensitive media transmission over manet. this work presents a tightly-coupled packet scheduling and routing algorithm to effectively transmit delay-sensitive media over mobile ad hoc network. first, packet urgency, node urgency, and route urgency are defined based on the end-to-end delay requirement of each packet and the number of hops over a route. packet scheduling algorithm and packet drop policy are designed to maximize the number of packets delivered in the tolerable delay bound and minimize their node urgency at each node simultaneously. finally, the routing algorithm is implemented to search for a route with the minimum route urgency.
dynamic lightpath allocation in translucent wdm optical networks. the optical reach (the distance an optical signal can travel before the signal quality degrades to a level that necessitates regeneration) ranges from 500 to 2000 miles. to establish a lightpath of length greater than the optical reach, it is necessary to regenerate optical signals. in a translucent optical network, there are regeneration points, where the signal undergoes optical-electronic-optical (o-e-o) conversion. in this paper we have proposed routing algorithms for translucent networks in a dynamic lightpath allocation environment in which requests for communication arrive continuously. in response to each request for communication, the objective is to establish, if possible, a path, from the source to the destination of the request for communication, so that a lightpath may be established, using the path that requires the fewest stages of regeneration. in practical transparent networks, a lightpath must satisfy the wavelength continuity constraint. however, in a translucent network, this constraint can be relaxed at the regeneration points. we have proposed an integer linear program, to give the optimum results for small networks, as well as an efficient heuristic for this problem that works for larger networks. we have evaluated the heuristic through extensive simulations to establish that the heuristic produces close-to-optimal solutions in a fraction of the time needed for the optimal solutions. our extensive evaluations demonstrate the relative impact of a set of network resources, such as (i) the number of regenerators, (ii) the optical reach of the regenerators and (iii) the number of wavelengths, on the network performance, measured in terms of the call blocking probability. to the best of our knowledge this is the first study that undertakes such an evaluation for translucent networks.
component based performance modelling of wireless routing protocols. we propose a component based methodology for modelling and design of wireless routing protocols. componen-tization is a standard methodology for analysis and synthesis of complex systems, or software. the feasibility of the component based design relies heavily on the compositionality property (i.e. system-level properties can be computed from properties of components). to provide a component based design methodology and to test compositionality for routing protocols, we have to develop a component based model of the wireless network. we present the main components of the routing protocol that should be modelled and focus on three main components: neighborhood discovery, selector of topology information to disseminate, and the path selection components. for each component, we identify the inputs, outputs, and a generic methodology for modelling. throughout the paper, we use the optimized link state routing (olsr) protocol as a case study to demonstrate the effectiveness of our approach. using the neighborhood discovery component, we present our design methodology and design a modified enhanced version of this component, and compare its performance to the original olsr design.
on capacity region of two-way multi-antenna relay channel with analogue network coding. this paper studies the wireless two-way relay channel (twrc), where two source nodes, s1 and s2, exchange information through an assisting relay node, r. it is assumed that r receives the sum signal from s1 and s2 in one time-slot, and then amplifies and forwards the received signal to both s1 and s2 in the next time-slot. by applying the principle of analogue network coding (anc), each of s1 and s2 cancels the so-called "self-interference" in the received signal from r and then decodes the desired message. assuming that s1 and s2 are each equipped with a single antenna and r with multi-antennas, this paper analyzes the capacity region of an anc-based twrc with linear processing (beamforming) at r. the capacity region contains all the achievable bidirectional rate-pairs of s1 and s2 under the given transmit power constraints at s1, s2, and r. we present the optimal relay beamforming structure as well as an efficient algorithm to compute the optimal beamforming matrix based on convex optimization techniques.
pollution resilience for dns resolvers. the dns is a cornerstone of the internet. unfortunately, no matter how securely an organization provisions and guards its own dns infrastructure, it is at the mercy of others' provisioning when it comes to resolutions its resolvers perform on behalf of its clients - even one compromised dns server in the internet can mislead an organization's clients to fake look-alike phishing web sites or malware-serving sites, among other things. in this paper, we propose a self-defense mechanism where the dns resolvers collect a small amount of additional information for the dns responses they receive and maintain a history of previous responses to guard their clients against misleading information from compromised dns servers in the internet. any organization can choose to enhance its resolvers with our mechanism unilaterally, unlike dnssec, which can ensure correctness of information only if the remote dns server deploys it.
a first order logic security verification model for sip. it is well known that no security mechanism can provide full protection against a potential attack. there is always a possibility that a security incident may happen, mainly as a result of a new or modified attack that the employed countermeasures cannot handle or identify. it is therefore useful to perform a deferred analysis of logged network data, in an attempt to identify abnormal behavior/traffic that flags some type of security incident that has not been detected by the security countermeasures. such an analysis of logged data for critical real time applications, like voip services, is certainly a valuable tool for enhancing the security level of the provided service. in this paper we introduce a practical tool that can be employed for the analysis of logged voip data and thus validate the effectiveness of the security mechanisms and the conformance with the corresponding security policy rules. for the analysis of the data we capitalize on our security model for voip services [25] that is based on first order logic concepts, while the protégé api and the semantic web rule language (swrl) are also exploited. the proposed tool has been evaluated in terms of an experimental environment, while the results obtained confirm the validity of its operation and demonstrate its effectiveness.
virtual calibration for rssi-based indoor localization with ieee 802.15.4. localization systems based on received signal strength indicator (rssi) exploit fingerprinting (based on extensive signal strength measurements) to calibrate the system parameters. this procedure is very expensive in terms of time as it relies on human operators. in this paper we propose a virtual calibration procedure which only exploits the measurements of the rssi between pairs of anchors. in particular, we propose two procedures for virtual calibration and we evaluate their performance with respect to an ad-hoc calibration campaign by performing measures in an indoor environment with an ieee 802.15.4 sensor network.
general order selection allocation for decentralized multiple access networks. decentralized multiple access networks require dynamic spectrum allocation to efficiently and fairly allocate resources among multiple users. in this paper, we consider the problem of spectrum allocation from the standpoint of diversity combining, and in particular as an explicit case of selection combining (sc). general order selection allocation (gosa) was previously proposed by the authors as a low-complexity spectrum allocation scheme for decentralized multiple access networks. in this paper, noting that previous analytical results on the error performance of gosa are for independent identically distributed (i.i.d.) rayleigh fading, we carry out a thorough and exact analysis of gosa for the i.i.d. nakagami-m fading scenario. in particular, based on new results on the exact and asymptotic average error probability of the γ-th order statistic, we obtain exact and asymptotic closed-form expressions for the error performance of gosa. numerical results show that the performance of the algorithm is close to that of the highly complex optimal search method.
a new ns2 module for the simulation of mpls networks with point-to-multipoint lsp support. nowadays, many ip backbone networks adopt separate control and forwarding planes for unicast and multicast traffic flows. indeed, while mpls (multiprotocol label switching) is widely deployed for unicast traffic, ip multicast is the only available solution for the delivery of "one-to-many" traffic flows. with p2mp lsps (point-to-multipoint label switched paths) support, a unified control and forwarding plane may be devised. such a reduction in the number of protocols used in the core of the network as well as in the number of encapsulations in the data plane, results in simplified network operations. the paper discusses the design and the development of the control and data planes extensions needed to provide p2mp lsp support in an mpls node. in particular, such extensions, concerning the p2mp lsps path computation, the rsvp-te signalling protocol, and the forwarding mechanism, have been implemented as new software modules for an ad-hoc developed simulator, based on ns2. finally, tests have been performed to assess the behaviour of the new functionalities introduced in the simulator.
optimization for fractional cooperation in multiple-source multiple-relay systems. in fractional cooperation, many relays simultaneously assist the source, and each relay is responsible to relay only a fraction of the source transmission. in this paper, the problem of fractional cooperation is considered in the presence of multiple sources and multiple relays. in particular, optimization problems are formulated that can be used to allocate the relay resources between multiple sources to either minimize the energy consumed to achieve a given probability of error threshold, or minimize the maximum probability of error experienced by each source node.
throughput improvement through precoding in ofdma systems with limited feedback. in this paper, we study the possibility of throughput improvement through precoding in ofdma based wireless systems with limited channel feedback. precoding can increase the overall system throughput by selecting the use of higher modulation and coding schemes (if there are any) in each physical resource unit (pru) under a maximum bit error rate constraint. for a specific form of precoding that we proposed in [1], we analytically derive a formula for the maximum pru throughput. sufficient conditions guaranteeing that our proposed technique outperforms the conventional technique are derived. finally, numerical results show the amount of throughput gain achieved by our proposed technique.
protecting primary users in cognitive radio networks: peak or average interference power constraint? this paper considers spectrum sharing between a cognitive radio (cr) and a primary radio (pr) where the cr protects the pr transmission by regulating the resultant interference power level at the pr receiver to be below some predefined threshold. the interference-power constraint at the pr receiver is usually one of the following two types: average interference power (aip) constraint that regulates the average power level over different fading states and peak interference power (pip) constraint that limits the peak power level at each fading state. from cr's perspective, aip constraint is more favorable than pip constraint because of its more flexibility for dynamic power allocations. on the contrary, from the perspective of protecting the pr, the more restrictive pip constraint appears at a first glance to be a better option. some surprisingly, this paper shows that in terms of various forms of capacity limits achievable for the pr fading channel, namely, ergodic and outage capacities, aip constraint is also superior over pip constraint. this result is based upon an interesting interference diversity phenomenon, i.e., variable interference power levels at the pr receiver in the aip case are more advantageous over constant ones in the pip case for minimizing the resulted pr capacity losses. therefore, aip constraint leads to larger fading channel capacities over pip constraint for both cr and pr transmissions.
power optimization of device-to-device communication underlaying cellular communication. we address resource sharing of the cellular network and a device-to-device (d2d) underlay communication assuming that the cellular network has control over the transmit power and the radio resources of d2d links. we show that by proper power control, the interference between two services can be coordinated to benefit the overall performance. in addition, we consider a scenario with prioritized cellular communication and an upper limit on the maximum transmission rate of all links. we derive the optimum power allocation for the considered resource sharing modes. the results show that cellular service can be effectively guaranteed while having a comparable sum rate with a none power control case in most of the cell area.
blind multipath mimo channel parameter estimation using the parafac decomposition. in this paper, we consider the problem of estimating the physical parameters that describe a multipath mimo communication channel model characterized by specular reflections due to remote scatterers. using the impulse response channel coefficients, we introduce a channel model based on a 3rd- order tensor structure that admits a parafac decomposition with rank equal to the number of propagation paths. the alternating least squares (als) algorithm is used to estimate the channel spatial and temporal signatures and the multipath parameters are then extracted by means of music-like subspace algorithms, enabling us to recover the transmit and receive angles as well as the path propagation delays of the mimo channel, without ambiguities. computer simulation results are shown to illustrate the performance of the proposed als-music estimation algorithm.
improving the performance of lp decoders for cyclic codes. recently, a linear programming (lp) decoder has been introduced for binary linear codes. although the performance of an lp decoder has a close relationship with the form of the parity check matrix (or equivalently with the tanner graph) of the code, there is no clear approach to choosing a suitable form for lp decoding. in this paper, we focus on the class of cyclic codes, and show that the cyclic structure of the code can be used to expand the parity check matrix and obtain a low redundancy form which is suitable for lp decoding. performance results are given which demonstrate the effectiveness of the proposed algorithm.
cyclostationary signatures in ofdm-based cognitive radios with cyclic delay diversity. the man-induced cyclostationary signatures can provide a robust mechanism for the self-coordination of cognitive radio networks. however, such artificial signatures incur signaling overhead and come at the bandwidth cost. in this paper, we show intrinsic cyclostaionary signatures in the orthogonal frequency division multilplexing (ofdm) system with cyclic delay diversity (cdd). the standard conformable cdd technique is initially motivated by the objective for exploiting spatial diversity. significantly, the underlying periodicity of cdd can simultaneously induce advantageous cyclostationary signatures without any signaling overhead. the lag-indices of the cdd-induced signatures are uniquely determined by the assigned amount of cyclic delay. consequently each cdd-ofdm system can be identified by a pre-assigned cyclic delay. the signed system can be easily and robustly recognized through cyclostationary detection. furthermore, the cdd-ofdm systems still preserve the cyclic-prefix induced cyclostationarity as primitive ofdm. by exploiting the overall cyclostationarity, we present a desirable cyclostionarity detector with asymptotical constant false alarm rate for spectrum sensing. comprehensive simulations are also given to show the performance improvement.
qos-aware relay node placement in a segmented wireless sensor network. in some applications of wireless sensor networks (wsns) it may be necessary to federate a number of disjoint segments. linking these segments may be subject to varying inter-segment quality of service (qos) requirements. this paper presents an effective approach for federating these segments. the main idea is to place relay nodes (rns) in order to establish inter-segment connectivity with the least number of rns while meeting the desired qos requirements. finding the optimal number and position of rns is shown to be np-hard and heuristics are thus pursued. the deployment area is modeled as a grid with equal-sized cells. each cell is evaluated based on the residual capabilities of rns populated in the cell. the optimization problem is then mapped to finding the cell-based least cost paths that collectively meet the qos requirements. the performance of the proposed approach is validated through simulation
modeling of user-perceived web-browsing performance over a wlan/3g inter-working environment. the wide deployment of wireless local area networks (wlan) and the advent of third generation (3g) networks have provided users with the flexibility of switching between dissimilar networks while running different applications. a mobile terminal (mt) can be equipped with multimodal functionalities, and can select the wireless interface that best suits its needs. this paper specifically focuses on the web-browsing application, and models the user-perceived performance for an mt operating over a wlan/3g environment. a system model is proposed that facilitates performance evaluation of web-browsing sessions in terms of different network metrics. the effect of user mobility and that of variations in network characteristics are incorporated. a simulation framework has been developed and the results generated are presented to demonstrate the utility of the data-session modeling and handover algorithms proposed in this paper.
channel modeling and performance evaluation on uwb-based wireless body area networks. this paper provides channel models for wireless body area network (wban) in uwb frequency band, and also presents performance evaluation using the derived channel models. the channel model is given by a statistical model in which parameters are derived from actually measured channel transfer function in a hospital room environment. these models enable us to evaluate performance of uwb-based wban. in this paper, bit error ratio (ber) and packet error ratio (per) are shown for uwb-based wban which employs a signaling scheme among ook, bppm, bpsk, and dpsk. the results show that both ook and bppm which generally uses a non-coherent receiver provide severe performance when the target per is set to 10-2 under the packet size of 128 bytes. the other signaling schemes achieve the required performance from the viewpoint of such error ratio.
extracting attack sessions from real traffic with intrusion prevention systems. false positive (fp) and false negative (fn) happen to every intrusion prevention system (ips). no one could do better judgment than others all the time. this work proposes a system of attack session extraction (ase) to create a pool of suspicious traffic traces which cause potential fns (abbreviated as p-fns) and potential fps (abbreviated as p-fps) to ipses. developers of ipses can use these suspicious traffic traces to improve the accuracy of their products. traffic traces are called suspicious since what they cause are p-fns and p-fps which need to be confirmed by the developers of ipses whether p-fns are fns and p-fps are fps. first, the ase captures real traffic and replays captured traffic traces to multiple ipses. by comparing the logs of ipses, we can find that some attack logs are logged or not logged only at certain ips. the former is p-fps, while the latter is p-fns to that ips. the ase then starts to extract this suspicious traffic from replayed traffic traces. the extracted traffic traces can then be used for further analysis by ips developers. some of the traces may prove to be guilty, i.e. confirmed to be fns and fps. to completely extract a suspicious session, the ase uses an association mechanism based on anchor packets, five-tuple and time, and similarity for the first packet, first connection, and whole session, respectively. it calculates the degree of similarity among packets to extract a suspicious session containing multiple connections. we define variation and completeness/purity as the performance indexes to evaluate ase. the experiments demonstrate that 95% of extracted sessions have low variation, and the average completeness/purity is around 80%
a laplace transform-based method to stochastic path finding. finding the most likely path satisfying a requested additive quality-of-service (qos) value, such as delay, when link metrics are defined as random variables by known probability distributions is np-hard [1]. we transform the probability distributions into the laplace domain, find the laplace transform of their convolutions and numerically inverse to find the distribution function in the time domain. picard's iterative method of successive approximations is used to find the solution. to the best of our knowledge, ours is the first to propose a transform-based approach for the qos routing problem of finding the most likely path. simulations show that our stochastic approach (1) selects correct paths more frequently, (2) incurs less overhead with respect to the dissemination and processing of state information, and (3) reduces the churn by selecting more stable paths.
adaptive modulation in spectrum-sharing systems with delay constraints. in this paper, we consider variable-rate variable-power mqam modulation employed under delay quality-of-service (qos) constraints over spectrum-sharing channels. in particular, we assume two users sharing the spectrum with one of them having a primary access to the band, and the other, known as secondary user, constrained by interference limitations imposed by the former. we study the performance of the secondary user's link employing adaptive mqam modulation scheme when, on top of the above-mentioned interference constraint, the secondary user is also required to satisfy a statistical delay qos constraint. considering two modulation schemes, namely, continuous mqam and discrete mqam with restricted constellations, we obtain the effective capacity of the secondary user's link, and derive the optimum power allocation scheme that maximizes the effective capacity in each case. numerical simulations are conducted to corroborate our theoretical results.
qos swarm state dependent routing for irregular traffic in telecommunication networks. this paper introduces a polynomial time approximation quality of service (qos) routing algorithm and constructs dynamic state-dependent routing policies. the proposed algorithm uses an inductive approach based on trial/error paradigm combined with swarm adaptive approaches to optimize the end-to-end delay packet transmission. the algorithm presented here is based on our earlier adaptive routing system and uses a model combining both a stochastic planned pre-navigation for the exploration phase and a deterministic approach for the backward phase. numerical results obtained with opnet simulator for different levels of traffic's load show good performances of our approach compared the classical non adaptive algorithms in a high dynamic environment.
game theory as a tool for modeling cross-layer interactions. modeling computer networks is a complex task, as their behavior depends from several variables. focusing on a single communication device, iso/osi and tcp/ip layered protocol stacks provide interoperability and fast deployment of networking solutions, but they limit the control on the interaction among protocols operating at different layers. as a consequence, the need is emerging to develop appropriate models to capture and evaluate the interaction of protocols within a single communication device in order to underline such forms of "indirect" interaction - since they may lead to unforeseen performance degradations. the proposed work aims at using the game theory for capturing the interactions within the protocol stack of a single node, with the goal of allowing to determine the "steady state" or the operating point of the system in a given scenario. as a result, a scalable and modular framework is presented, that enables characterization and analysis of cross-layer interactions starting from the protocols' specifications. finally, as an example of application, the model is applied to a single-hop ieee 802.11 wireless network.
evaluating algorithms for composable service placement in computer networks. novel network architectures with distributed service components on both routers and end-systems have been proposed to provide the necessary flexibility in the next-generation internet. such architectures allow services to be composed along the data path to satisfy different communication requirements. a major operational challenge in such systems is to determine where to perform the required services along the data path. this problem, which we call as the "service placement problem" is proven to be np-complete when considering resource (e.g., link and processing capacity) constraints. in this paper, we present an evaluation of several existing and newly developed heuristic algorithms for solving the problem. we explore the quality of the achieved placement in terms of effective use of system resources, end-to-end delay, connection drop rate, and load balancing. our results show the design trade-offs of these different algorithms.
dvd based moving event localization in multihop cellular sensor networks. in this paper, we consider moving event localization using data collected from a multihop cellular sensor network (mcsn). the main contribution of the paper is a novel structure-free distributed velocity dependent (dvd) waiting time based protocol. we compare the performance of the proposed dvd protocol with that of a centralized approach and the existing randomized waiting time (rw) protocol. simulation results show that dvd exhibits a performance superior to rw with respect to center of event localization error and end-to-end delay. we also present simulation results on the the sensitivity analysis based comparison between dvd, rw and the centralized scheme.
on the stability of ad hoc group mobility models. group mobility has been modeled for simulators to evaluate protocols in wireless ad hoc networks. these mobility models have to be verified in terms of their instant and long-run behaviors. this paper discusses importance and challenges of the stability evaluation for ad hoc group mobility models; proposes analytical technique for the stability of group mobility model and evaluation of the same via simulation. as a case study, we evaluate the personal network group mobility model (pnmm). the evaluation method presented in this paper can be applied to all generic ad hoc group mobility models in terms of stability analysis and simulations.
programmable and scalable per-flow traffic management scheme using a control server. we propose a programmable and scalable traffic management scheme. programmable traffic management at high-speed routers is difficult because programmability and high-speed packet processing have involved a serious tradeoff. to attain both, the new scheme combines control programs at a control server and simple packet handling functions, such as sampling packet headers and discarding packets, at routers. therefore, by installing appropriate control programs into the server, a variety of active queue management schemes, per-flow bandwidth management schemes, dos mitigation schemes, and so on, are achieved. one of the main contributions of this paper is its proposal of a statistical scheme for handling flows. as only a fraction of complete flow information stored at the conterol server is loaded into the router's flow table and it is replaced cyclically, the proposed scheme scales more than the routerfs flow table capacity. our simulation results indicate that the scheme provides efficient traffic management, per-flow wfq emulation in our example, even with very small flow tables compared to the number of concurrently active flows. furthermore, we discuss implementation issues with the proposed scheme and reveal that the processing cost at the server and router is sufficiently small for use with 10 gbps links.
fundamental power-allocation for cooperative relay networks. this paper develops a optimal power-allocation strategy for the general multi-hop cooperative relay systems. the systems allow a different number of hops for different paths and different destinations for different paths. when the orthogonality of channels is guaranteed for each hop, and when the systems want to minimize the total system power to transmit the data to the destinations, it is shown that the optimal power-allocation satisfies the following condition: the summation of all water-levels of a path should be the same as those of others.
the importance of being really random: methodological aspects of ip-layer 2g and 3g network delay assessment. the accurateness of round-trip- and one way delay measurements for 2g and 3g networks rely to a much larger extent on employing a sound methodological framework than this is the case for other types of networks. typical mobile access networks differ significantly from core networks, most prominently with respect to delay. in this paper we present payload-dependent delay measurement results for public 2g and 3g networks which illustrate that accurate ip-layer delay measurements in mobile networks must use high sample counts and randomness in start times for uplink and for downlink. most notably this concerns icmp round-trip delay measurements which, due to the synchronization of icmp requests with the network clock when leaving the mobile network's uplink, fail to meet the random start time criterion for icmp replies in the downlink (or vice-versa). this synchronization effect leads to significant clustering of one-way delay values for the reply leg and causes minor delay differences in the core network to have potential significant impact on icmp round-trip delays. therefore, highly accurate simulations and emulations must model uplink and downlink of time-slotted networks as two interrelated links based on a common timebase.
parafac2 receivers for orthogonal space-time block codes. space-time block codes can be represented by tensors, like for example the kathri-rao space time codes introduced by sidiropoulos. in this paper, we introduce a paraallel factor analysis 2 (parafac2) model for orthogonal space-time block codes (ostbc). this model, along with a small modification at the transmitter and the use of tensor diagonalisation designed for orthogonal tensors at the receiver, leads us to develop a generic parallel factor analysis (parafac) blind receiver for ostbc. unlike most tensor based blind receivers, our channel estimator is based on a data tensor rather than on a cumulant tensor.
an enhanced multiple-feedback algorithm for rfid mac protocols. this paper introduces two new tree-based anti-collision schemes using multiple feedback symbols for uplink tag random access of emerging radio frequency identification (rfid) networks. to this end a uplink(ul) time slot requires an extra time portion called voting field in addition to the packet payload to obtain a slot based estimate for the number of contending tags. as a function of the voting field length we examine mac efficiency improvements in terms of ul throughput, and compare it with the conventional binary tree based rfid mac in iso 18000-6 type b standard.
parametric construction of improved nyquist filters based on inner and outer functions. in this paper, we explore the concept of inner and outer functions to come up with two novel parametric families of nyquist pulses. aside from requiring only two design parameters, the proposed pulses yield an enhanced performance compared to the sophisticated flipped-inverse hyperbolic secant (asech) pulse, that was recently presented in the literature. while the construction of parametric families originates from the work of beaulieu and damen, the usage of inner and outer functions guarantees a higher flexibility in the choice of the composite family members. the proposed pulses may have a slower decay rate than the well-known raised-cosine (rc) pulse, but exhibit a more pronounced decrease in the amplitudes of the two largest sidelobes and this accounts for their improved robustness to error probabilities. in the following, it is clearly demonstrated that a lower bit error rate (ber), compared to the existing pulses, can be achieved for different values of the roll-off factor and timing jitter. moreover, a smaller maximum distortion along with a more open eye diagram are attained as well.
self-protecting networking using dynamic p-cycle construction within link capacity constraint. the p-cycle design problem has been extensively studied because it can provide both ring-like fast self-protection speed and spare capacity efficiency of path protection scheme. however, p-cycle provisioning for dynamic traffic has not been fully addressed. most related works have not considered link capacity in the construction of p-cycles, which may cause problems in practice because the protection paths may not have enough backup bandwidth. in this paper, with the consideration of link capacity, we present a sufficient and necessary condition that guarantees p-cycles for providing enough protection bandwidth. based on this condition, we propose an effective solution to provide connections for dynamic requests with the property that each link used for a connection is protected by a p-cycle. simulation results show that our dynamic p-cycle provisioning solution outperforms the traditional path protection scheme.
throughput analysis of a randomized sensing scheme in cell-based ad-hoc cognitive networks. cognitive radios have a great potential to improve spectrum utilization by enabling secondary (unlicensed) users to opportunistically access the spectrum without disturbing the primary (licensed) users' communication. however, to assure acceptable qos for secondary users without interfering with primary users several challenges must be overcome under physical constraints. because of hardware constraints, secondary users can only sense a limited number of spectrum channels. therefore a secondary user must wisely select the channels to be sensed to increase it's likelihood for successful data transmission. however if a secondary user takes up a greedy approach and disregards other secondary users in its channel selection, the whole secondary network would suffer in terms of aggregate throughput. also because of the autonomous nature of secondary users, the search policy must be as decentralized as possible, i.e. secondary users should need almost no information of one another to operate. in this work we propose a search policy for secondary users in a cell based ad-hoc network and evaluate its performance (total primary and secondary throughput) as a function of different system parameters.
novel switched interleaving techniques with limited feedback for ds-cdma systems. in this paper we propose a novel switched interleaving algorithm based on limited feedback for downlink ds-cdma systems. the proposed switched chip-interleaving ds-cdma scheme requires the cooperation among the transmitter, the receiver and a feedback channel sending the index of the interleaver to be used. the transmit chip-interleaver is chosen by the receiver from a codebook of interleaving matrices known to both the receiver and the transmitter and we send back the codebook index using a limited number of bits. in order to design the codebook, we consider patterns such as the block interleavers, and a selection function is designed to maximize the received signal to interference plus noise ratio (sinr).we present block-based and symbol-based linear minimum mean squared error (mmse) receivers for interference suppression. simulation results show that our proposed algorithm achieves significantly better performance than the conventional cdma systems and the existing chip-interleaving schemes.
large snr analysis of diversity schemes on rayleigh channels with arbitrary correlation. asymptotic error rate expressions are derived for multi-branch equal gain combining and selection combining operating on arbitrarily correlated rayleigh fading channels. these closed-form solutions are used to provide rapid and accurate estimation of the error rates in large signal-to-noise ratio regions. more importantly, it is shown that the asymptotic error rates over correlated branches can be obtained by scaling the asymptotic error rates over independent branches with a factor, det(m), where det(m) is the determinant of the normalized channel correlation matrix.
reservation-based directional medium access control (rdmac) protocol for multi-hop wireless networks with directional antennas. in this paper, we study the issues of medium access control (mac) mechanisms for multi-hop wireless networks with directional antennas. specifically, we explore the location-dependent carrier sensing problem and the interference problem caused by the minor lobes of antennas. existing solutions to directional antenna mac problems rarely account for the impact of minor lobes and typically assume that the neighboring nodes' locations are known a priori. as a result, they are not applicable to practical systems or to mobile nodes. in this paper, we propose a reservation-based directional mac (rdmac) protocol for multi-hop wireless networks with directional antenna. this mechanism operates in sessions. each session comprises two periods, namely, a reservation period and a transmission period. the reservation period is further composed of a set of two phases, namely, a probing phase and a beam-indication phase. the mechanism is designed to reduce the interference among neighboring nodes and to increase the network throughput. the performance of the proposed mechanism is evaluated analytically and via the ns2 simulator. the results show that our mechanism outperforms existing solutions in terms of higher throughput and lower delay.
qos enhancement and performance evaluation of ad-hoc routing protocols for rural public safety. in this paper, we explore the feasibility of using mobile ad-hoc networks (manets) for rural public safety. first, we discuss a qos enhancement to a standard routing protocol, dynamic source routing (dsr). by incorporating a new routing metric and the available bandwidth and delay estimation algorithms with dsr, we design a new routing protocol, qos-aware source routing (qasr), to meet the qos requirements specified by statement of requirements (sor) for public safety communications. we then evaluate the performance of qasr and the well-known standard routing protocols including ad-hoc on-demand distance vector (aodv) and dsr based on real public safety scenarios using the opnet modeler at the 4.9ghz public safety spectrum band. simulation results show that qasr significantly outperforms dsr and aodv in terms of various performance metrics.
vls: a map-based vehicle location service for city environments. location based routing protocols are often used to deliver packets in vanet for the sake of scalability and lower overhead. before exchanging information between moving vehicles, the location of destination node should be discovered. however, the existing location service employed in manet is not very suitable for vehicular ad hoc network. in this paper, a vehicle location service protocol (vls) is proposed to support inter-vehicle communication (ivc) in cities. the information in digital maps is utilized to help realize location service. we present a method of partitioning the network and constructing distributed location servers, which can avoid selecting servers in void areas and decrease the average location discovery delay. in order to reduce the location update cost, forwarding trees and adaptive update policies are used to send messages. in addition, the cost of location update and discovery delay can be balanced through different parameters setting for a given network. different scenarios are simulated to compare the performance of gls, ghls and vls. the experiment results show that vls outperforms others in urban environments.
a new joint timing and channel estimation method for block transmission uwb systems. in this paper, a new joint timing and channel estimation scheme is proposed for orthogonal frequency division multiplexing and single carrier block transmission ultra-wideband (uwb) systems. in particular, a new preamble pattern is used for both coarse timing and channel estimation. despite of the presence of coarse timing error, the estimated channel impulse response (cir) is simply the cyclic shifted version of the real cir, thanks to the unique structure of the preamble. then a new method is proposed to search for the first channel tap in the cir vector, which can be employed to fine tune the timing position and adjust the channel estimation for later data block detection. the proposed scheme has low complexity, saves preamble overhead by performing joint synchronization and channel estimation, and outperforms existing timing acquisition methods in the literature by a large margin in dense multipath uwb channels. moreover, this paper presents an analysis of the effect of residual timing error on the performance of single carrier systems with frequency domain equalization.
performance measure analysis of amplify-and-forward relaying over non-identical nakagami-m fading channel. this paper analyzes the performance measures of amplify-and-forward (af) relaying over non-identical nakagamim fading channel. the exact probability density functions (pdfs) of total signal-to-noise ratio (snr) for variable gain relaying and fixed gain relaying are deduced, and the theoretical formulas of moment generating function (mgf) and moments for fixed gain relaying are presented. since the exact pdf of total snr for variable gain relaying is not tractable, its approximation is used to derive the formulas of mgf and moments. using these statistic characteristics, the average symbol error rate (aser) and amount of fading (aof) for fixed gain relaying are derived, and the tight approximate aser for variable gain relaying are given. these proposed mathematics results are verified by simulation.
cooperative amplify-and-forward beamforming for ofdm systems with multiple relays. in this paper, we propose frequency-domain (fd) and time-domain (td) beamforming (bf) schemes for co-operative orthogonal frequency division multiplexing (ofdm) networks with multiple amplify-and-forward relays. whereas for fd-bf the bf weights are applied in the fd, for td-bf cyclic bf filters (c-bffs) are used on the td signal avoiding discrete-time fourier transform operations at the relays and drastically reducing the required amount of feedback from the receiver to the relays. adopting the average mutual information (ami) per sub-carrier as optimality criterion, we show that the direction of the optimal fd-bf weights can be obtained in closed-form and that the optimal sub-carrier power allocation (pa) problem is convex. for solution of the pa problem an interior point method and a bisectional search dual method are provide. furthermore, for solution of the c-bff optimization problem an efficient gradient algorithm is proposed. simulation results for ieee 802.11n channels show that td-bf with short c-bffs closely approaches the performance of fd-bf and outperforms direct transmission without relaying.
performance evaluation of moip applications over satellite: an experimental study. in the last years, broadband satellite networks have emerged as a flexible technology offering high-speed internet access to large communities of users at relatively low-cost. at the same time, the large widespread of voip and multimedia over ip (moip) applications, has pointed out the need of investigating their performance over heterogeneous networks and, more specifically, on wireless and satellite systems not offering quality of service (qos) guarantee. the paper presents the results of an experimental study aimed at analyzing the behaviour of moip applications over a two-way satellite system. starting from the most relevant performance metrics of a satellite network, the paper is focused on the evaluation of the perceived quality of service (pqos) when voip and moip applications are deployed over a satellite network. control and data plane issues that may deteriorate the performance of such applications are highlighted.
on the performance of selection cooperation arq. we extend current automatic repeat request (arq) protocols by proposing a cross-layer communication system, which relies on selection cooperation at the physical layer. we argue that selection cooperation is a better alternative to distributed space-time block coding (dtsbc) when coupled with non-cooperative arq protocols. the selection cooperation arq (scarq) system proposed in this paper performs better than competing alternatives, such as the dstbc arq or the non-cooperative arq schemes, and has the added benefit of being simple to implement. to facilitate comparisons with cooperative and non-cooperative approaches, we develop a formula to calculate the throughput of the scarq system. the accuracy of the throughput formula is verified through monte carlo simulations. using the proposed formula, we determine that a significant improvement in the performance of the retransmission process is achieved by using selection cooperation only among a small number of nodes.
precoded spatial multiplexing systems in the presence of feedback delay using kalman filter. precoded spatial multiplexing multiple-input multiple-output (mimo) systems using limited feedback are mainly based on the notion of delay-free feedback channels. in this paper, we take into account the time varying nature of the channel, and consider the feedback delay problem. in order to reduce performance degradation of spatial multiplexing systems in the presence of feedback delay, we propose the use of a kalman filter linear predictor at the receiver to provide the transmitter with the predicted channel state information, and hence, mitigate the effect of feedback delay. the performance of this method is assessed using computer simulation, and the obtained results for the proposed channel prediction scheme demonstrate improved bit error rate performance for time varying rayleigh fading channels.
hybrid arq with rate adaptation in multiband ofdm uwb systems. in this paper, we propose a cross-layer design (cld) scheme combining rate adaptation and four types of hybrid automatic repeat request (harq) for multiband orthogonal frequency division multiplexing (mb-ofdm) ultra wideband (uwb) systems following the ecma-368 standard. the time varying property is incorporated into standard uwb channel models for the purpose of investigating rate adaptation. to accurately accommodate fast time-varying channel conditions, we propose to embed the selected rate information into the acknowledgement (ack) frames. it is shown that the proposed cld scheme combining rate adaptation and harq can provide higher throughput than the harq-only schemes. among the four types of harq schemes, harq type-iii has the best throughput performance while type i has the worst.
a cross-layer perspective on rateless coding for wireless channels. rateless coding ensures reliability by providing ever-increasing redundancy, traditionally at the packet level (i.e. the application layer) through erasure coding. this paper explores whether additional redundancy for wireless channels is most helpful at the packet level through erasure coding or at the physical layer through lower-rate channel coding. this cross-layer trade-off is explored in a traditional wireless setting where the communication of a message consisting of a fixed number of packets takes place over a rayleigh fading channel. the examined scenarios include both a single receiver and multiple cooperating receivers allowing the results to be extended to situations where selection diversity is available in the system. for several interesting scenarios, this paper determines the optimal trade-off between the amount of packet-level erasure coding and physical-layer channel coding required to provide reliable communication over the widest range of operating snr's. our results indicate that packet-level erasure coding can provide a significant benefit when no other form of diversity is available. in many cases, the amount of redundancy that should be allocated to such erasure coding is nearly constant, and further redundancy (i.e. any rateless coding) should be applied to the physical layer.
improving sensor network lifetime through hierarchical multihop clustering. in this project, we developed an adaptive multihop clustering algorithm maxlife for sensor networks. maxlife significantly improves sensor network lifetime by balancing energy dissipation and minimizing energy consumption at the same time. the algorithm is compared to random and minenergy algorithms and shows great performance gain. random is extended from its original design of single hop clustering in [1] to multihop clustering, which elects cluster heads with absolute fairness. however, the idea of rotating the role of cluster heads does not work well in a multihop environment, because relay nodes can also drain out energy quickly. minenergy chooses cluster heads to minimize total energy consumption, which leads to large energy disparity and hurts long-term performance. maxlife on the other hand, uses global optimization techniques and directly maximizes network lifetime. simulation results verified that maxlife achieves the best tradeoff between fairness and energy efficiency, and the clustering topology computed from it has significantly longer lifetime than those from the other two algorithms.
localization of a swarm of mobile agents via unscented kalman filtering. this paper deals with the application of kalman filtering (kf) techniques to the localization of a swarm of mobile agents in awireless sensor network (wsn). in particular, both extended (ekf) and unscented (ukf) kalman filters have been investigated referring to a typical urban scenario with energetic and resource constraints. a cooperation strategy among sensor nodes, based on a virtual diversity scheme, has been introduced allowing the swarm tracking under severe propagation conditions. the effectiveness of the proposed solution has been assessed by means of simulations concerning a squad of robots moving in realistic scenarios. it has been shown that ukf achieves a higher accuracy and reliability than ekf in localizing the barycenter of the robot squad. further, the proposed solution provides advantages in terms of measurement update frequency and, hence, of energy saving.
experimental and simulation study of a wimax system in the sea port scenario. the paper presents a measurement campaign carried out on a 2.5 ghz mobile wimax test-bed in a sea port scenario, aimed at evaluating the system performance. the analysis of acquired data suggested the definition of a 2-ray pathloss model, which is able to fit the actual behavior of the observed marine channel. in order to evaluate the effects of the proposed pathloss model on system performance the paper presents a simulation study carried out by means of opnet simulator. in particular, the simulation study is aimed at comparing the throughput at ip level obtained using different pathloss models implemented in opnet, with that obtained when the proposed 2-ray model is considered. further, the throughput at ip level obtained by simulation is compared with the one measured in the actual test-bed. this comparison points out that the wimax opnet model is able to reproduce in most cases the system performance observed during the measurement campaign, when the proposed 2-ray pathloss model is used. however, the simulator is not able to predict the behavior of actual system in all situations. indeed, in the areas where the pathloss presents peaks, the breakdown of system performance, mainly caused by synchronization problems, is not predicted by the simulator.
biometric mobile template protection: a composite feature based fingerprint fuzzy vault. biometric authentication is emerging as the promising solution to conventional cryptography based authentication technologies. however, protecting users' biometric templates stored in a mobile device in a secure way is a challenge issue and has attracted many attentions. as one of the possible solutions, the fuzzy vault construct binds a secret key and biometric information to provide template protection. most existing fingerprint fuzzy vault algorithms use pre-aligned fingerprint impressions and rely strongly on image registration, a process that is well known to be nontrivial and unreliable. moreover, it is inherently insecure to store raw fingerprint images for the alignment. in this paper, we propose a fingerprint fuzzy vault based on composite features which are reliable, distortion tolerant and registration-free. experimental results on public database show that our scheme can improve verification performance significantly.
capacity analysis for mimo two-hop amplify-and-forward relaying systems with the source to destination link. this paper presents an ergodic capacity analysis of an amplify-and-forward multiple-input, multiple-output two-hop system including the source to destination (direct) link. we first derive an expression for the probability density function of an unordered eigenvalue of the system. then, using this result, a closed form expression for the ergodic capacity of the system is derived. the ergodic capacity expression has one integral that needs to be evaluated numerically. the results produced are valid for all snr values and for arbitrary numbers of antennas at the source, relay and destination. we also present simulation results to validate our analysis. the results show that the analysis exactly matches the simulations and quantifies the improvements in capacity due to the diversity offered by the direct link.
qos-aware optimal power allocation with channel inversion regularization precoding in mu-mimo. in multiuser mimo systems, the channel inversion regularization (cir) precoding outperforms zero-forcing (zf) in the case of a small number of users and low snr. however, unlike the zero-interference zf,the optimal power allocation issue using cir is a nonconvex optimization problem which will become more intractable with nonconvex qos constraints. in this paper we focus on the challenging qos-aware optimal power allocation problem, aiming to maximize the system sum rate and guarantee the users' minimum data rates. as a result, an "iterative geometric programming" (igp) strategy is proposed which transforms the underlying problem to a series of tractable geometric programming (gp) problems through an iterative convex approximation. extensive simulations have been conducted and the results indicate that igp is quite suitable to tackle the problem, which can achieve a good balance between the system sum rate and the individual qos requirements.
decentralized fair resource allocation for relay-assisted cognitive cellular downlink systems. in this paper, we consider a relay-assisted cognitive cellular downlink system dynamically accessing a spectrum licensed to a primary network, thereby improving the efficiency of spectrum usage. a cluster-based relay-assisted architecture is proposed, where relay stations are employed for minimizing the interference to users in the primary network and achieving fairness for cell-edge users. based on this architecture, an optimal solution is derived for jointly controlling data rate, transmission power, and subband allocation to optimize the weighted sum goodput where proportional fair scheduling (pfs) is included as a special case. as shown by simulations, the proposed solution achieves significant throughput gains and better user fairness compared with existing designs.
limited-feedback modified block diagonalization for multiuser mimo downlink with time-varying channels. block diagonalization (bd) is a low-complexity linear precoding scheme for multiuser mimo (mu-mimo) down-link, which can completely eliminate multi-user interference with perfect channel state information (csi) at the transmitter. under the assumption of block fading channels, bd with fixed amount of feedback is interference-limited. in this paper, we first introduce a low-complexity csi feedback scheme, by exploiting the temporal correlation of practical channels, to improve the efficiency of feedback. then, a modified bd algorithm is proposed to further utilize the channel correlation in time domain. combined with the csi feedback scheme, the modified bd algorithm handles the interference-limiting problem in a wide range of snr with a fixed, small number of feedback bits.
anonymous and authenticated routing in multi-hop cellular networks. multi-hop cellular network is a promising architecture aiming to improve the performance of current cellular network. however, there are many security challenges due to the participation of the mobile nodes in the routing process. in this paper, we address two challenges: route anonymity, aiming to prevent attackers from tracking a packet flow to its source or destination; and location privacy, aiming to prevent attackers from detecting the nodes' locations. most of the existing solutions require much computational power and energy. we propose a routing protocol that provides anonymous communication by protecting the user's anonymity and location privacy. the user's anonymity is preserved for a large number of compromised nodes. simulations results show that the proposed protocol is efficient and can be implemented with an acceptable overhead.
characterization of the dynamic narrowband on-body to off-body area channel. a characterization of the dynamic narrowband on-body to off-body area channel is presented based on real-time measurements of the time domain channel response at carrier frequencies near the 900mhz and 2400mhz industrial, scientific and medical (ism) bands. a statistical characterization is presented of received signal amplitude when the subject's body is standing and walking, transmitted from the body to a receiver, rx, off the body, with various orientations of the subject's body with respect to the receiver, and various distances from the receiver. two locations of the transmitter, tx, on the human body are considered. the lognormal distribution provides a good fitting model with and without movement. further, the stability is characterized based on a measure of channel response variance, which is called here the channel variation factor and can characterize the channel coherence time. the on-body to off-body area channel is determined to be generally stable over a period of 25ms, but the amount of stability is found to be dependent both on movement, tx location on-body, and carrier frequency.
channel estimation based on divergence minimization for ofdm systems with co-channel interference. in this paper, we present a novel approach for pilot-aided channel estimation in ofdm systems with synchronous co-channel interference. the estimator is derived based on the kullback-leibler divergence minimization framework. the obtained solution iteratively updates both the desired user's and the interferer's channels, using a combination of linear minimum mean squared-error (lmmse) filtering and interference cancellation, avoiding the complex matrix inversions involved in the full lmmse channel estimation approach. estimation of the noise variance is also included in the iterative algorithm, accounting for gaussian noise and residual interference after each iteration. the estimates of both channels are used at the equalizer to reject the interfering signal, thus mitigating the degradation due to co-channel interference. simulation results show that the receiver using the proposed estimator performs as good as the one employing the full lmmse estimator and very closely to a receiver having perfect knowledge of the channel coefficients.
a resilient transparent optical network design with a pre-configured extended-tree scheme. we propose a new design scheme of resilient wavelength division multiplexing (wdm) networks by extending and reshaping pre-configured protection tree (p-tree) structures. the resulting protection scheme relies on optimized pre-cross connected structures that span all previously proposed protection patterns. p-tree-based protection schemes offer the advantages of scalability, local restoration capabilities, and failure impact restriction, but at the same time suffer from capacity inefficiency. while keeping these advantages, we propose an extension (reshaping) of the p-tree protection pattern that imposes no restriction on the shapes of the protection building blocks. not only the resulting protection scheme remains scalable and highly flexible, but it also leads to pre-configured protection structures that improve much further on capacity efficiency and recovery delay. we establish some new integer linear programming models, and use a large scale optimization tool, named column generation (cg) to solve them. our cg-based solution method is highly scalable as it does not require an a priori explicit enumeration of the protection structures, but an efficient dynamic enumeration of only the most promising ones. comparison are made with three other protection schemes, i.e, simple and non-simple p-cycles (fully pre-cross connected structures) as well as p-trees. results show a clear advantage of the proposed extended-tree scheme with respect to flexibility, capacity efficiency, and restoration delay.
a unified approach to network traffic and network security visualisation. in this paper we present an architecture which enables data-sharing between computer security and network traffic visualisation tools. at its core is a middleware which manages all interactions. this enables one application to determine the acceptable input for another, and send compatible data. the middleware sits atop a unified database which provides data in a generic form to the applications. interesting traffic patterns or attack trends seen in one tool can be sent directly to another for further examination and analysis. all communication in the middleware is performed using xml as a data transport mechanism.
coordinated transmission in distributed ad hoc peer-to-peer (p2p) communications. the centralized transmission (tx) coordination is presented for p2p networks to mitigate the strong near-far interference (nfi) by aligning the transmissions of nearby p2p pairs. with the concern of signaling overhead, all nodes measure and feedback the sum co-channel interference (cci) exclusively to the central node. with the same principle, the more practical distributed tx coordination is proposed, where every p2p pair exchanges the cci measurements and coordinates the tx order locally. simulations illustrate that the distributed tx coordination provides the similar performance to the heuristic centralized method and outperforms the prior art dramatically. in addition, the latency is quite low in the distributed coordination.
mitigating channel estimation error via cooperative communications. channel estimation error problem is among the main causes of performance degradation in wireless networks. in this paper, we investigate the impact of cooperative communications on mitigating the effect of channel estimation error. two main performance criteria, namely, the traditional outage probability and the proposed signal-to-noise ratio (snr) gap ratio, are utilized to characterize such impact. the snr gap ratio measures the reduction in the snr due to channel estimation error. taking into consideration the channel estimation error, we show that the outage probability is reduced by utilizing cooperative transmission. we also show that cooperative transmission results in lower snr gap ratio compared to that of the direct transmission. thus, cooperative transmission is less susceptible to the effect of channel estimation error compared to direct transmission. finally, we illustrate that increasing the number of cooperating relays reduces the effect of the channel estimation error more.
iq imbalance correction for ofdma uplink systems. direct conversion receivers are attractive for low cost systems as they avoid intermediate frequency (if) filters. however, the direct conversion from radio frequencies (rf) to complex inphase (i) and quadrature (q) baseband signals in one mixing step introduces additional front-end distortions. these iq distortions lead to a degradation in the system performance. the problem becomes more significant in orthogonal frequency division multiple access (ofdma) systems where multiple user signals with different iq impairments are combined in the uplink (ul) signal. in this paper, detection methods for ofdma-ul signals corrupted by iq distortions are investigated. the received signal as a function of transmitted signals, iq parameters, and communication channels is mathematically formulated. we designed a novel pilot pattern that is used by two proposed estimation and compensation methods of iq impairments to the signal. proposed methods were shown to significantly improve the system performance.
a new reduced complexity ml detection scheme for mimo systems. for multiple-input multiple-output (mimo) systems, the optimum maximum likelihood (ml) detection requires tremendous complexity as the number of antennas or modulation level increases. this paper proposes a new algorithm which attains the ml performance with significantly reduced complexity. based on the minimum mean square error (mmse) criterion, the proposed scheme reduces the search space by excluding unreliable candidate symbols in data streams. utilizing the probability metric which evaluates the reliability with the normalized likelihood functions of each symbol candidate, near optimal ml detection is made possible. a threshold parameter is introduced to balance a tradeoff between complexity and performance. besides, we propose an efficient way of generating the log likelihood ratio (llr) values which can be used for coded systems.
adoption of cognitive radio scheme to class-based call admission control. by using cognitive radio technology, opportunistic spectrum access has the potential to solve the underused spectrum problem. in this paper, by first introducing a specific cognitive radio scheme, we analyze the secondary user's capacity and the collision probability. employing this scheme, we build two call admission control models for three classes of service, namely, handoff voice calls, new voice calls and data calls. we show that they achieve improved blocking probability and throughput by exploiting the cognitive radio scheme. further, we show a tradeoff between collision probability and blocking/throughput in the call admission control.
design and analysis of a hierarchical ip traceback system. in this paper, we present the detailed design and analysis of our solution to the ip traceback problem. we adopt (at the as level) a path signature generation method which was proposed at the router level to primarily provide a means of filtering attack traffic. our solution assumes a secure routing infrastructure to exchange authenticated messages in order to learn path signatures. we envision the local adoption of a separate, yet complementary, traditional traceback system at each as. this solution is hierarchical in the sense that it works at the autonomous system (as) level first then once a small list of possible source ases is identified, those ases are queried and traceback is performed within each as to prune the list down to the actual source. using simulation results we demonstrate that our solution is practical since it reduces - as a first step - the search space from the entire router space of the internet to an as-list that is only a very small fraction of all possible ases. this combination is more scalable than doing a flat ip traceback on the entire router space of the internet. we go on to propose a means of using more than 16 bits of the ip fragmentation fields which are traditionally used by various ip traceback systems. we present results based on using various sizes for the marking field, as well as varying number of total marks and different sizes for each mark.
lifetime optimization for wireless sensor networks using the nonlinear battery current effect. one of the design challenges of wireless sensor networks is the tradeoff between network operation time and network coverage. recent studies reveal that the useable battery capacity drops faster at a higher discharge current in a nonlinear fashion. to take advantage of this battery current effect, in this paper we explore a new sensor node deployment scheme to prolong the entire sensor network lifetime as well as each individual sensor node. the key idea of the proposed scheme is to assign a sensor node having higher traffic load to adopt lower transmission power level. in this way, batteries of all nodes in a given area are discharged at the same current, thus they are depleted at the same time. extensive simulations have conducted to evaluate the performance of the proposed sensor node deployment scheme. compared with peer work on heterogeneous deployment, the useable battery capacity by using the proposed scheme can be improved by 26.67%, and the operating time per sensor node can be enhanced by 20.95%. furthermore, the proposed deployment scheme can reduce the number of sensor nodes required to cover the given area, leading to a significant reduction of deployment cost.
performance analysis of optical flow switching. in our previous work [1], [2], we presented optical flow switching (ofs) as a key enabler of scalable future optical networks. in the present work, we propose a practical scheduling algorithm and conduct an approximate throughput-delay analysis for ofs networks.
user profiling: a method for limited feedback in ofdma systems. in the ofdma downlink, obtaining channel state information (csi) from users is necessary for the base station (bs) to optimize network performance by intelligently allocating resources and scheduling mobile stations (ms). however, the overhead of obtaining csi is a large burden and therefore, schemes to reduce csi are necessary for a realizable system. by considering a ms's coherence time δtcoh and coherence bandwidth bcoh, and exploiting this redundancy in the ms's csi, the amount of feedback can be tailored to the specific user's profile and greatly decreased. typically, reducing feedback results in more uncertainty in csit and performance degradation. however, in the proposed scheme, the csit's deviation from the true channel state is bounded, and thus can provide robust scheduling. specifically, two bs schemes are suggested that either fix the average ber or the average outage probability regardless of user mobility or delay spread.
approximating maximum directed flow in a large wireless network. we study the maximum forwarding capacity for the relay traffic that can be transmitted through a wireless multihop network in a single direction. the problem appears as the microscopic level problem in a dense multihop network where the routing and forwarding tasks can be considered independently (separation of scales). ultimately, the problem of finding the maximum forwarding capacity involves solving a maxflow problem in an infinite plane with an infinite dimensional scheduling vector as an additional parameter to be optimized. in this paper, we approximate the infinite network by a finite but large network consisting of nodes distributed as a spatial poisson process, and give the problem an lp formulation assuming a boolean interference model. the computational complexity is further reduced by relaxing the necessary and sufficient constraints and solving the lp problem with a reduced set of necessary clique constraints. this gives a new significantly tighter upper bound on the achievable forwarding capacity compared with our previous (non-achievable) upper bound corresponding to the maximum capacity in one time slot.
on average packet delay bounds and loss rates of network-coded multicasts over wireless downlinks. latency is a critical concern in interactive or delay-sensitive services such as interactive iptv and voip. this is especially so when using network coding as a means to conserve bandwidth in these bandwidth-hungry services. in practical network coding, packets are coded in batches and thus suffer a large average delay per packet when packets get decoded after the whole batch is received. a larger batch size, however, also gives the highest bandwidth savings. in this paper, we analyze the achievable upper and lower bounds of the average delay per packet as well as packet loss rates due to finite-sized queue in a multicast downlink transmission from the system and client perspectives. we validate our analysis with simulation results and characterize the queueing and transmission delays, and packet loss performance with respect to (i) the maximum size of a batch and (ii) packet arrival rates. we find that random linear coding is an upper bound in delay performance and other hybrid network coding method might achieve better delay gains.
iterative receiver design for mimo systems with improper signal constellations. in this paper, we propose a novel iterative receiver strategy for uncoded multiple-input, multiple-output (mimo) systems employing improper signal constellations. the proposed scheme is shown to achieve superior performance and faster convergence without the loss of spectrum efficiency compared to the conventional iterative receivers. the superiority of this novel approach over conventional solutions is verified by both simulation and analytical results.
a new architecture for data collection in vehicular networks. vehicular sensor networks (vsns) are an emerging paradigm in vehicular networks. this new technology uses different kind of sensing devices available in new vehicles, to gather information about the driver's environment (speed, acceleration, temperature, seats occupations, etc.) in order to provide a safer, more efficient and more comfortable driving experience. in this paper, we focus on a particular vsn architecture, where the ad hoc network is operated by a telecommunication/service provider (wimax access point, 2.5/3g base station) to combine non-valuable individual sensed data and extract from them effective feedbacks about the situation of the road in a geographical area (traffic density, unusual traffic behavior, etc.). in operated vsns, providers tend to reduce the traffic load on their network, using unlicensed spectrum communication medium (ieee 802.11p, for example). to do so, we propose cgp (clustered gathering protocol), a cross layer protocol based on hierarchical and geographical data collection, aggregation and dissemination mechanisms. we analyze the performances of cgp using a simulation environment and realistic mobility models. we demonstrate the feasibility of such solution and show that cgp offers the operator precious information without overloading his network.
inadequacy of the queue-based max-weight optimal scheduler on wireless links with tcp sources. the interaction between wireless optimized scheduling algorithms and tcp congestion control mechanisms can have adverse effects on the performance of the system. we focus on the queue based max-weight (qbmw) scheduler, a scheduling strategy which is known to be throughput-optimal under unregulated traffic sources. we use fluid modeling to describe the time evolution of the congestion window size and of the wireless buffer, and show by numerical results that under tcp traffic sources the qbmw scheduling policy leads to a very unfair outcome, in which some users may be completely shut off. we also evaluate and discuss the performance achieved by other scheduling policies: the proportional fair (pf) scheduler, and the queue age (qa) scheduler, which takes account of the age of the packets stored in the wireless buffers.
contrasting open-loop and closed-loop power control performance in utran lte uplink by ue trace analysis. uplink power control in utran long term evolution consists of an open-loop scheme handled by the user equipment and closed-loop power corrections determined and signaled by the network. in this study the difference in performance between pure open-loop and combined open and closed-loop power control has been analyzed and the different behavior of fractional vs. full path-loss compensation has been evaluated. a comprehensive system level simulation model has been used with a facility to trace a particular test user during its motion from enodeb towards the cell border and back to its initial position. this study demonstrates the effect of distance path-loss of a test user on several physical layer performance metrics including throughput, resource allocation as well as modulation and coding scheme utilization. simulation results in a fully loaded network show high throughput for open-loop fractional power control for the user located in the vicinity of the serving enodeb, however, steep performance degradation has been observed when the user is moving towards the cell edge. the user throughput at the cell border can be increased by the closed-loop component. the benefit of closed-loop power control is the higher homogeneity in terms of throughput across the entire network area and the ability to automatically stabilize the network performance under different conditions like cell load and traffic distribution.
an ultra-wideband radar system for through-the-wall imaging using a mobile robot. high-resolution imaging through walls and other materials using microwave signals serves amongst other applications in the rapid detection of human maneuvering, rescue missions in collapsed buildings, and target feature extraction. while narrowband doppler radar in the millimeter-wave or infrared spectrum can provide good resolution through clothing and packaging, penetration through denser sheetrock, plaster, and brick requires operation below 10 ghz; this band however yields poor resolution. as an alternative, ultra-wideband radar operating in this band boosts the bandwidth which translates into fine range resolution; still it requires an aperture length of several meters for comparable cross-range resolution. the associated cost and portability in realizing such an aperture through antenna arrays or fixed-length scanners have limited their lengths to the order of 1 meter in prototype systems to date. in this work, we propose a novel aperture taking form as a variable-length scanner or mobile robot. the wide dynamic range of our system coupled with its unrestricted aperture length allows us to generate high-resolution images up to a range of 8 meters or more.
a group based service triggering algorithm for ims network. to determine the potential signaling traffic reductions, the session establishment procedures are investigated. the investigation shows that, the s-cscf (serving call session control function) is the major bottleneck in ims (ip multimedia subsystem) and the existing 3gpp (the 3rd generation partnership project) service triggering algorithm (3gpp sta) increases largely the end to end session setup delay. to reduce the session setup delay and improve the system performance, a new group based service triggering algorithm (gsta) is proposed. and then the modeling of 3gpp sta and gsta are presented. theoretical analysis and simulation results show that, gsta can efficiently reduce the signaling traffic load of the s-cscf, increase the throughput of the system and considerably reduce the session setup delay, improve ims network quality of service.
low-complexity list-based frame synchronization for ldpc coded transmission. in this paper, we propose a simple and efficient two-stage list synchronizer for frame synchronization of low-density parity-check (ldpc) coded data transmitted over the additive white gaussian noise (awgn) channel. the proposed method uses both synchronization sequence and code constraints for frame synchronization. in the first stage, a list of the most likely frame starting positions is made using synchro-sequence, while in the second stage the code constraints are used to select the most likely position from the list. we analytically relate the synchro-sequence length, the frame length and the list length in order to keep the synchronization frame error rate (fer) lower than the error-correcting fer of the ldpc code, and we investigate the trade-off between the sequence length and the list length. we demonstrate that the proposed scheme outperforms both the frame synchronization methods based on synchro-sequence only and the recently proposed blind synchronization methods based on ldpc code constraints, the former in terms of the synchronization fer for the same sequence lengths and the latter in terms of complexity.
a new mechanism to detect selfish behavior in ieee 802.11 ad hoc networks. selfish behavior at the mac (medium access control) layer can have devastating side effects on the performance of wireless ad hoc networks. in this work, we consider the problem of detecting selfish behavior at the mac layer in ieee 802.11 wireless networks when a selfish node can manipulate the backoff operation. we propose a simple and robust mechanism based on cusum (cumulative sum) test by tracing the statistics characteristic in real time to detect the selfish behavior. this method can be used with any random access mac protocols and it does not require any modification on the existing protocols. the efficacy of this detection mechanism has been validated by a qualnet simulator. our simulation results show that the detection mechanism has short detection time and high detection accuracy.
on the use of admission control for better quality of security. we propose an admission control policy that admits users into a public access network as soon as possible while limiting the overall security impact on the network and other users. in our model, each user has a particular reputation level when first requesting network access. before admitting a user into the network, the initial risk of a user is assessed by the admission control system using past history and a scanning of the user's device which delays the user's admission into the network and updates the user's reputation level accordingly. we formulate the trade-off between the admission delay and security risk as a convex optimization problem, which can be solved for an admission control policy. the evaluation suggests that our approach can substantially increase the system security for public access networks while minimizing admission delay, in contrast to current approaches widely used in enterprise networks. the proposed framework extends the traditional quality of service-based admission control mechanisms with a well-defined notion of quality of security.
on the impact of correlation on distributed detection in wireless sensor networks with relays deployment. in this paper, a binary hypothesis distributed detection problem in correlated wireless sensor networks with cooperative relays deployment is considered. in particular, the effect of correlation between sensor nodes is modeled and analyzed in rayleigh flat fading channels in order to explore the natural tradeoffs between the number of sensor/relay nodes and the detection error performance in the network. specifically, two communication protocols are utilized; in protocol i, each sensor node communicates its observation directly to the fusion center while in protocol ii, amplify-and-forward (af) cooperative relays are deployed and a fewer number of sensors is used. based on the theoretical analysis and simulations, it is revealed that employing less sensor nodes and instead deploying relay nodes results in significant performance gains under strict network power constraint. it is concluded that with cooperative distributed detection and exploitation of spatial diversity, better detection error performance is achieved as well as reduction in the required number of sensor nodes.
minimum distance based precoder for mimo-ofdm systems using a 16-qam modulation. a precoder based on the exact optimization of the minimum euclidean distance dmin between signal points at the receiver side is proposed for mimo-ofdm systems using a 16-qam modulation. assuming that channel state information (csi) can be made available at the transmitter, the channel is diagonalized and a precoder can be derived. a numerical approach shows that the precoder design depends on the channel characteristics, leading to 8 different precoder expressions. comparisons with maximum signal-to-noise ratio (snr) strategy and other precoders based on criteria, such as water-filling (wf), minimum mean square error (mmse), and maximization of the minimum singular value of the global channel matrix, are performed to illustrate the significant bit-error-rate (ber) improvement of the proposed precoder. in order to make its implementation easier, it is shown that it can be expressed by only two ways without significant performance degradation.
impact of imperfect channel state information on arq schemes over rayleigh fading channels. with imperfect channel state information (csi) acquired by channel estimation at the receiver, the performances of automatic-repeat-request (arq) systems are evaluated as a function of the accuracy of channel estimation. a link between network-layer performances and physical-layer parameters is therefore established. we study in particular the goodput and the accepted packet error rate as a function of the channel estimation mean square error (mse) and the factors which affect the mse. the results enable us to analyze the optimum allocation of energy for data transmission and energy for pilot channel estimation so as to maximize the goodput.
multiple backhaul mobile access router striping. the multiple backhaul mobile access router (mar) can provide high capacity and high performance internet access for emerging mobile wireless applications. in this paper we improve the mar with the capability to stripe traffic from clients over multiple available network devices. the mar allows different backhauls to be used simultaneously and accommodates diverse policies.we present experimental results to validate the per user striping performance of our mar and explore trade-offs when integrating switching policies. with the above enhancements, the mar is able to provide aggregated communication channels to the users, and enhance reliability by switching wireless interfaces when it is necessary.
location based sleep scheduling for target tracking applications in smart space environments. this paper describes locmac, a new location aware power saving mac layer for target tracking applications in smart space environments. target tracking applications focus on providing proximity based local services to mobile users within a fixed deployment of wireless nodes. conventional wireless sensor mac layers increase the lifespans of battery powered wireless nodes by scheduling sleep periods for the entire network, which are either of fixed length, or vary based upon current network metrics. locmac bases its sleep schedule on the relative physical location of network nodes and allows target tracking service to be guaranteed. it propagates user location updates, and uses this knowledge to perform 'location based sleep scheduling' (lbss). lbss describes the use of wireless node and network target positions to maximise the potential sleep periods. adding knowledge of user mobility allows those nodes which will not be required by the network application to sleep for longer periods of time, waking up just in time to service network user requirements. the paper describes the operation of locmac and compares its performance against existing sleep scheduling mac protocols through analysis and simulations of typical application scenarios. the results show that locmac performs significantly better for target tracking applications and is particularly appropriate for use in future smart spaces.
fair and flexible budget-based clustering. an efficient way to bound the size of clusters in large-scale self-organizing wireless networks is to rely on a budget-based strategy. the side effect of conventional budget-based clustering approaches is that they generate a potentially large number of small, even single-node, clusters. the consequence is that while clusters are bounded, their average size may be far from the expected value (the budget), which negatively impacts the performance of the communication systems running on top of it. in contrast, we propose fair and flexible budget-based clustering (ffbc) to form size-controlled clusters in large-scale self-organizing networks. for a given target cluster size, our approach outperforms previous budget-based algorithms by creating clusters of average size closer to the requested value and avoiding isolated nodes.
transmit precoding for mimo systems with partial csi and discrete-constellation inputs. in this paper, we consider the transmit linear precoding problem for mimo systems with discrete-constellation inputs. we assume that the receiver has perfect channel state information (csi) and the transmitter only has partial csi, namely, the channel covariance information. we first consider mimo systems over frequency-flat fading channels. we design the optimal linear precoder based on direct maximization of mutual information over the mimo channels with discrete-constellation inputs. it turns out that the optimal linear precoder is a non-diagonal non-unitary matrix. then, we consider mimo systems over frequency selective fading channels via extending our method to mimo-ofdm systems. to keep reasonable computational complexity of solving the linear precoding matrix, we propose a sub-optimal approach to restrict the precoding matrix as a block-diagonal matrix. this approach has near-optimal performance when we integrate it with a properly chosen interleaver. numerical examples show that for mimo systems over frequency flat fading channels, our proposed optimal linear precoder enjoys 6-9 db gain compared to the same system without linear precoder. for mimo-ofdm systems, our reduced-complexity sub-optimal linear precoder captures 3-6 db gain compared to the same system with no precoding. moreover, for those mimo systems employing a linear precoder designed based on gaussian inputs with gap approximation technique for discrete-constellation inputs, significant loss may occur when the signal-to-noise ratio is larger than 0 db.
a study on cross-layer multi-constraint path computation for ip-over-optical networks. a powerful path computation element is a must for the next-generation ip-over-optical networks to support on-demand service provisioning crossing layers. the main purpose of path computation in multi-layer networks (mln) is to enable traffic engineering (te) under a multitude of constraints. a common objective of such traffic engineering is to minimize resource utilization while satisfying all the applicable constraints. in this study, we investigate a variety of mln path computation methods based on real-world control plane implementations and network settings. we present some techniques for handling the specific te constraints that concern the ip-over-optical networks. experimental results are presented for performance evaluation and comparison of the investigated multiconstraint path computation methods and techniques.
situation understanding based on heterogeneous sensor networks and human-inspired favor weak fuzzy logic system. humans use multiple sources of sensory information to estimate environmental properties and has innate ability to integrate information from heterogeneous data sources. how the multi-sensory and multimodal information are integrated in human brain? there is consensus that it depends on the prefrontal cortex (pfc). the pfc has top-down control (favor weak) and rule-based mechanisms, and we incorporate the favor weak mechanism into rule-based fuzzy logic systems (fls) via using upper and lower membership functions. the inference engine of favor weak fuzzzy logic system is proposed under three different categories based on fuzzifiers. we apply the favor weak fls to situation understanding based on heterogeneous sensor network, and it shows that our favor weak fuzzy logic system has clear advantage comparing to the type-1 fls. the favor weak fls can increase the probability of threat detection, and provides timely indication & warning (i&w).
proactive detection of spectrum holes in cognitive radio. most of existing works on spectrum sensing detect primary transmitters while the purpose of spectrum sensing is to avoid interfering with primary receivers (prs). therefore, it is more important to detect prs. in this paper, we propose a proactive spectrum sensing method that detects whether a pr is within the coverage or the interference range of a cr transmitter by exploiting the close-loop power control policy in primary systems. with the proposed scheme, the cr user may still access the spectrum band even though a primary signal is present as long as its transmission does not interfere with the pr. simulation results show the advantages of the proposed method.
preserving privacy for location-based services with continuous queries. location-based service (lbs) is gaining momentum as gps-equipped mobile devices become increasingly affordable and popular. one of the potential obstacles faced by lbs is that users may raise concerns about their personal privacy when location data are sent to a distrusted lbs provider. a well-known solution is to render the location data less accurate through spatial or temporal cloaking. in this paper, we show that by combining consecutive location data including speed, heading direction, and cloaked locations, an adversary can obtain more accurate estimation of the actual location. we propose a solution to prevent such inferences by cloaking speed and direction. since the cloaking is based on estimated future locations, we devise methods for tolerating errors caused by the estimation process. we report simulation results on the tradeoff between the capability of tolerating errors and the degree of cloaking.
approximation algorithms for traffic grooming in wdm rings. this paper addresses the problem of traffic grooming in wdm rings in which all traffic emanates from a single node and all other nodes are destination nodes. this "one-to-many" scenario arises in metropolitan access networks in which one node serves as a "hub" connecting the ring to a larger network as well as in video-on-demand and other multimedia services where a single source node serves a collection of subscriber nodes. the ring comprises a given number of wavelengths of uniform capacity and a variable number of tunable add-drop multiplexers (adms) at each node. given a set of requests at the destination nodes, where each request comprises a bandwidth demand and a profit for fulfilling the request, our objective is to select a subset of the requests and pack ("groom") them onto the wavelengths such that no wavelength's capacity is exceeded and the total profit of the selected requests is maximized. although this problem is np-complete, we give polynomial time approximation algorithms with excellent theoretical performance validated with experimental results.
an advanced method for watermarking digital signals in bit-plane structure. inverting signal bits is a basic operation for data hiding such as digital watermarking. in the previous papers the level transformation that performs both inverting a specified bit and minimizing the resultant level change has been proposed. because the transformation maps signal levels sparsely within the dynamic range, some variation of the transformed levels is necessary to conceal the fact that the signals are transformed. this paper proposes a method for varying the transformed levels randomly so that those bits that present the randomness can be distinguished. then, these bits can represent a message to recover. accordingly, a capacity of embedding additional bits increases. the performance of the proposed method is analyzed in a stochastic manner in terms of the resultant level distortion and an embedding capacity. a simulation result is also shown to demonstrate the actual performance in the application to digital images.
cooperative communication techniques for wireless ofdma-based ad-hoc networks. this paper proposes a new architecture for cooperative communication in wireless ad-hoc networks particularly suitable to emergency and safety applications. the proposed solution is characterized by the following relevant features: a) a wireless connection between each couple of network nodes is established via multiple relays; b) each source-to-destination link is characterized by a double string topology allowing the use of specific transmit diversity techniques for reliable communications; c) a novel utility-based and distributed routing algorithm providing a fair exploitation of the available resources is employed. simulation results evidence that our solution offers substantial energy savings with respect to traditional ad-hoc architectures.
an interior point penalty method for utility maximization problems in ofdma networks. this paper investigates the non-convexity of utility-based resource allocation problems in orthogonal frequency division multiple access (ofdma) networks with heterogeneous traffic classes. efficient transmission in ofdma networks requires optimal resource allocation to users based on their current channel states. also, utility-based resource allocation improves the network resource utilization and application level quality of service (qos) provisioning. however, a major difficulty in using utility-based ofdma resource allocation schemes is the nonconvexity of corresponding optimization problem. in this paper, a continuous optimization technique is proposed to treat the nonconvexity. the approach is based on a combination of penalty function methods and interior point methods. numerical results demonstrate that the proposed approach solves the problem within limited time, and the solutions are close to near optimal solutions obtained by the search algorithm.
unequal error protection in bicm with qam constellations: interleaver and code design. in this paper we present a general methodology for the interleaver and code design for qam-based bicm transmissions. we develop analytical bounds on the bit error rate and we use them to predict the performance of bicm when unequal error protection (uep) is introduced by the constellation labeling. based on these bounds, the optimum design of interleaver and code is presented. the improvements obtained reached 2 db for the analyzed cases, and are obtained without complexity increase. although previous works noted the influence of the interleaver design and the uep, to the best of our knowledge, this paper is the first to analyze formally this problem for bicm transmissions.
energy efficiency of fixed-rate wireless transmissions under qos constraints. transmission over wireless fading channels under quality of service (qos) constraints is studied when only the receiver has perfect channel side information. being unaware of the channel conditions, transmitter is assumed to send the information at a fixed rate. under these assumptions, a two-state (on-off) transmission model is adopted, where information is transmitted reliably at a fixed rate in the on state while no reliable transmission occurs in the off state. qos limitations are imposed as constraints on buffer violation probabilities, and effective capacity formulation is used to identify the maximum arrival rate that a wireless channel can sustain while satisfying statistical qos constraints. energy efficiency is investigated by obtaining the minimum bit energy and wideband slope expressions in both low-power and wideband regimes. the increased energy requirements due to the presence of qos constraints are quantified. comparisons with variable-rate/fixed-power and variable-rate/variable-power cases are given. overall, an energy-delay tradeoff for fixed-rate transmission systems is provided.
complexity measure of fh/ss sequences using approximate entropy. high complexity of frequency-hopping (fh)/spread-spectrum (ss) sequence is of great importance to high-security multiple-access communication systems, for it makes fh/ss sequence difficult to be analyzed. with the growing development in the design of fh/ss sequence in much wider fields, the well-known complexity measures-the linear complexity (lc), the linear complexity profile (lcp) and the k-error linear complexity (k-error lc)-are widely used but not sufficient to evaluate the complexities of the sequences available, such as the cryptographical sequence and the chaotic sequence families. in this paper, a new complexity metric to evaluate the unpredictability of fh/ss sequence based on the approximate entropy (apen) is proposed in the view of the maximal randomness of the sequences with arbitrary length. and the theoretical bounds of the apen are derived from a probabilistic point of view. simulations and analysis results show that, the proposed apen works effectively to discern the changing complexities of the fh/ss sequences with small number of samples, which provide superior performance over its candidates.
optimal transmitters for hypothesis testing over a rayleigh fading mac. we consider the case when k sensors have strongly correlated measurements - they all observe a 0 or they all observe a 1. the two possibilities are to be tested at the output of a multiple access channel with rayleigh fading coefficients, which are not known to the transmitter and the receiver. we study the problem of optimal transmitters for this case using the notion of generalized snr (gsnr). under certain symmetry and orthogonality restrictions on the transmitter, we find optimal and near-optimal transmission schemes. in particular, for low snr, type-based multiple access is optimal, while for high snr, the optimal strategy assigns orthogonal codewords across sensors. in between these two extremes, we identify optimal/near-optimal schemes for any fixed snr. simulation results for the probability of error are also given, which demonstrate the relevance of gsnr optimization.
bivariate nakagami-q (hoyt) distribution. new, exact expressions for the bivariate nakagami-q (hoyt) processes with arbitrary correlation in a nonstationary environment are derived. more specifically, the following are obtained: joint probability density function, joint cumulative distribution function, power correlation coefficient, and some statistics related to the signal-to-noise ratio at the output of the selection combiner, namely, outage probability and probability density function. the expressions are mathematically tractable and flexible enough to accommodate a myriad of correlation scenarios, useful in the analysis of a more general fading environment.
a novel cooperative diversity based on multilevel coded modulation. we propose a novel cooperative diversity using multilevel coded modulation which can perform with arbitrary number of cooperative nodes. the proposed multilevel coded cooperation makes use of a signal superposition, which is one form of analog network coding techniques. due to the ability and flexibility of a multilevel coded modulation, the proposed multilevel coded cooperation can outperform not only a time-division cooperative diversity but also a signal superposition cooperative diversity in the case where the number of cooperating nodes is more than two. moreover, achievable outage probability and channel capacity are analyzed and two design criteria based on the analysis are proposed.
adaptive spreading code assignment for up-link mc-cdma. multi-carrier (mc) code division multiple access (cdma) is able to take the advantages of ofdm and cdma and is a potential technique for future wireless communications. for an uplink mc-cdma system, the symbols of different users are spread in the frequency domain. however, the frequency-selective fading of wireless channels destroys the othogonality of the spreading codes for different users and causes multiple access interference (mai), especially for a network with full load. to reduce the impact of mai, we adaptively assign spreading codes according to channel state information and mai environments. since it requires high computational complexity to find an optimal set of spreading codes for all active users, we develop several simplified approaches to search the suboptimal spreading code sets. it is demonstrated by the computer simulation that the adaptive spreading code assignment, even though suboptimal, can significantly improve the performance of mc-cdma systems.
on uplink network mimo under a constrained backhaul and imperfect channel knowledge. it is known that next generation mobile communications systems will most likely employ multi-cell signal processing - often referred to as network mimo - in order to improve spectral efficiency and fairness. many publications exist that predict strong achievable rate improvements, but usually neglecting various practical issues connected to network mimo. in this paper, we analyse the impact of a constrained backhaul infrastructure and imperfect channel knowledge on uplink network mimo from an information theoretical point of view. especially the latter aspect leads to the fact that the channel conditions for which network mimo is reasonably beneficial are strongly constrained. we observe different base station cooperation schemes in scenarios of maximal 3 base stations and 3 terminals, provide simulation results, and discuss the practicability of the discussed schemes and the implications of our results.
igcp: a platform for interactive communication in groupware applications. this paper presents the interactive group communication platform (igcp), a high-level framework designed to provide groupware application developers with an efficient tool for realization of interactive, multipoint collaboration across a heterogeneous network environment. the concept of the platform has been depicted, one of its most important elements is a scalable data stream whose volume can be progressively adjusted along the path between a sender and a group of receivers. the strong temporal requirements have been met by using a number of advanced mechanisms, such as application-level congestion detection and specialized message compressors installed on end nodes or on intermediate, infrastructural nodes. igcp also offers typical groupware services such as session state management and floor control. the presented discussion on the usefulness of various transport protocols and other network mechanisms shows that the contemporary internet infrastructure does not offer sufficient support for this class of applications. igcp has been implemented in the microsoft. net framework using ice middleware and its usefulness has been proved in a real application - the teledicom 2.0 teleconsultation tool.
a new cooperative detection technique with malicious user suppression. spectrum detection for vacant bands is one of the key techniques in cognitive radio (cr) systems. cooperative detection outperforms single user detection in many aspects. the existence of malicious user could severely degrade the performance of cooperative cr systems. in this paper, a new cooperative detection scheme with malicious user suppression is proposed, which has lower complexity and better performance compared with the existing one. simulation results show that when 25% users in the system are malicious, our proposed method can introduce more improvement of missed detection probability by nearly 20%.
an analytical approach for throughput evaluation of wireless network coding. in this paper, we propose a new analytical model for stable throughput evaluation of wireless network coding. in this new approach we consider the arrival and departure rates in and from the wireless nodes, respectively, in steady state. our analytical model is founded on a multi-class open queueing network. in this model, we include two basic processes of network coding, i.e., packets combination and packets multicasting, in a suitable manner considering the constraints of the queueing networks. in this respect, we consider the coded packets as new classes of customers. by solving the related traffic equations and applying the stability condition, we compute the maximum stable throughput, i.e., the maximum packet generation rate at which the packets reach their destinations with finite delays. we apply our approach to a symmetric wlan with unicast flows and a slotted random access mac scheme, and compute the maximum stable throughputs for the cases of simple routing and network coding, distinctly. finally, we confirm our analytical results by simulation.
impact of gateways placement on clustering algorithms in wireless mesh networks. in wireless mesh networks, designing algorithms that efficiently balance the traffic loads among a given set of network gateways is a challenging problem. links interfere, transfer capacity is limited, and traffic demands vary overtime. the position of the gateways also affects the overall network performance as a result of its direct impact on the way routers are associated to gateways. in this paper, we investigate the performance of several routers-to-gateways association heuristics in relation with different gateway placement algorithms.we show that if bounds on the number of hops between routers and gateways exist, load-based heuristics perform the best. in general cases however, interference-based approaches provide better load balancing.
cost and target-based scheduling for switch power control. in this paper we propose two advanced algorithms which allow for both differentiated quality-of-service (qos) and power conservation in input-queued packet switches. these algorithms are based on two core ideas: first, we assume that the switch can operate in a number of operational speed modes; a higher speed mode serves more packets per time slot at the cost of higher power consumption. second, each virtual output queue may tolerate a certain low backlog which is called a target in this setting. thus, one can control power by adjusting the speed mode and qos by setting the targets appropriately. we first survey previous work to provide the necessary background behind our approach. we then describe our algorithms and evaluate their performance experimentally through simulation. our preliminary results show that these new procedures offer significant performance gains compared to existing approaches.
evaluation of sip signaling and qos for voip over satellite networks. in satellite networks, voice over ip performance is degraded by long delays and low bandwidth. both call setup time and quality of service (qos) for voice calls are affected. separate studies have been undertaken for these performance metrics. in this paper, we have carried out experiments using different voice codecs to evaluate sip call setup time and qos parameters together. the experiments are performed on the satellite network testbed at centre for communication systems research (ccsr) at university of surrey. the results present a comparison of different codecs, highlighting their performance.
polynomial eigen-beamformer in time domain for mimo-ofdm systems. co-space interference (csi) mitigation is one of the main challenging issues in multiple input multiple output (mimo) systems. using beamformer in both transmit and receive sides is an approach to mitigate the csi. in the mimo systems employing orthogonal frequency division multiplexing (ofdm) technique, frequency domain or time domain beamforming can be used. in this paper, we propose a new time domain broadband beamforming (tbbf) for mimo-ofdm systems based on a svd type of block circular channel matrix. tbbf is attained by polynomial eigen-beamformer when the right and the left polynomial eigenvectors are utilized at the transmitter and the receiver sides, respectively. the new proposed tbbf is able to completely mitigate the csi due to shaping the multiple beams in orthogonal directions. performance of the proposed polynomial eigen-based tbbf is evaluated by computer simulations and compared with the previously proposed tbbf scheme based on the sbr2 algorithm. the results show that the proposed time domain beamforming method outperforms the sbr2-based scheme.
pilot matrix design for interim channel estimation in two-hop mimo af relay systems. in this paper, we are concerned with a two-hop multi-input-multi-output (mimo) amplify-and-forward (af) relay system consisting of a source node (sn), a relay node (rn), and a destination node (dn). since the simple rn in this system is unaware of the structure of its received signal and incapable of performing complicated signal processing, the interim channels over the sn-rn and the rn-dn hops can not be estimated directly. therefore, we develop a novel interim channel estimation approach in this paper. furthermore, we find necessary and sufficient conditions for the pilot amplifying matrix sequence at the rn to ensure successful interim channel estimation at the dn, and present rules to design low-complexity pilot amplifying matrices meeting these conditions.
interference-aware channel assignments with seamless multi-channel monitoring in wireless mesh networks. the wireless mesh networks (wmns) are statically deployed on heterogeneous areas and are operating in open wireless media, and thus it coexists with other networks operating on the same frequency with the same or different radio access technology (rat). the wmns experience two types of interferences according to the source of interference. coexisted networks with wmn induce the interference called external interference and nodes in wmn experience interference each other, which is called internal interference. most of existing protocols strive for dealing with internal interference. but the increased external interferences can degrade the performance of wmn significantly. to resolve this coexistence problem, we propose three channel assignment schemes for hybrid multi-channel protocol (hmcp) by capturing the states of each channel and selecting its operating channel. we also devise a seamless multi-channel monitoring method to recognize channel states without performance degradation. intensive simulation results demonstrate that our proposed channel assignment schemes outperform existing hmcp's channel assignment scheme in terms of aggregate throughput, delay, and fairness.
prioritized flow optimization with generalized routing for scalable multirate multicasting. this paper addresses the performance optimization for scalable video coding and multicast over networks. multi-path video streaming, network coding based routing, and network flow control are jointly optimized to maximize a network utility function defined over heterogeneous receivers. importantly, contextual priors of scalable video layers are imposed on the flow routing optimization problem, seeking to guarantee the transmission cost for each layer in an incremental order and find jointly optimal multicast paths and associated rates. through a primal decomposition and the primal-dual approach, a decentralized algorithm with two-level optimization update is developed to solve the target convex optimization problem. numerical and simulation results validate the convergence and network performance of the proposed algorithm.
evaluation of link protection schemes in physically impaired optical networks. link protection schemes for wdm-based optical networks have been extensively researched. most work to date has ignored the physical layer impairments (plis) that could be dominant in transparent optical networks with long links. in this paper, we first evaluate the performance of two link protection schemes - namely, p-cycles and generalized loopback - when plis are considered. our evaluation shows that a choice of p-cycles that merely tries to optimize the wavelength usage can be more susceptible to failures in a realistic environment. in particular, we show that the hamiltonian p-cycle is not the optimal choice for p-cycle selection in all-optical networks. this is mainly due to the interference caused by the long lightpaths that appear in the network after a failure occurs. we show that although a selection of smaller p-cycles can cause higher blocking probability, it is less vulnerable to failures. we also compare the performance of p-cycles to the generalized loopback link cover approach in these environments. finally, we apply a cross-layer routing and wavelength assignment algorithm to these schemes that significantly enhances performance in physically impaired optical networks.
exploiting the operating point in sensing-based opportunistic spectrum access scenarios. spectrum sensing is one key enabler towards opportunistic spectrum access in cognitive radio networks. such scenarios allow cognitive users (a.k.a. secondary users) to access some licensed spectrum band as long as they do not interfere with the licensed (or primary) users. the main goal is to achieve an efficient and utmost access to the otherwise underutilized spectrum resources while still guaranteeing primary users a non-harmful operation. spectrum sensing can be then used by secondary users to detect spectrum holes that may be accessed in a non-interfering manner. however, spectrum sensing may be subject to errors in the form of false-alarm and misdetection. false-alarm causes spectrum under-use while misdetection leads to spectrum interference between primary and secondary users. unfortunately, these two magnitudes pose a trade-off on the sensing mechanism: low misdetection is achieved at the expense of high false alarm and vice versa. consequently, an adequate operating point of the sensing mechanism should be determined. in this work we evaluate the impact of false-alarm and misdetection errors on the performance of a spectrum sensing scenario.we use a discrete time markov chain (dtmc) model and we determine the suitable operating point for the sensing mechanism under different traffic load conditions such that some quality of service is attained by both primary and secondary users. performance results reveal that by effectively choosing the operation point bearing in mind the traffic load levels will lead to enhanced perceived quality of service of both primary and secondary users.
capacity analysis and experimental study with multiple interfaces and multiple channels in 802.11 mesh networks. a key challenge in multihop wireless network is to provision for sufficient network capacity to meet user requirements. the contributions of this paper are two-fold: (a) we analyses wireless bandwidth, the ratio between the number of channels and the number of interfaces, the ratio between the number of gateways and the number of mesh routers, and the impact on the capacity of mesh backbone, and present the asymptotic upper bound of the average throughput of mesh routers (b) based on insights from capacity analysis, we built tju meshnet testbed and develop a multi-interface routing protocol (mirp). we implement the proposed protocol in our testbed to demonstrate the feasibility in practice.
repeater-assisted capacity enhancement (race) for mimo links in a line-of-sight environment. a single on-frequency, full duplex wireless repeater is considered for enhancing the capacity of a long-distance 2×2 multiple-input multiple-output (mimo) wireless link with a dominant line-of-sight (los) component. such links might be used for high-speed communication between buildings or towers. for practical reasons, the aperture sizes of the transmit (tx) and receive (rx) arrays may be limited, which tends to make the rank of the long-distance mimo channel matrix close to unity. the paper shows that the addition of just one repeater can bring the channel to full rank, approximately doubling the capacity of the link. typical values of repeater isolation are assumed. for small tx and rx array element spacings, there is considerable robustness in optimal repeater location. even with some multipath, most of the capacity improvement is retained.
adaptive bandwidth control to handle long-duration large flows. we describe a method of adaptively controlling bandwidth allocation to flows for reducing the file transfer time of short flows without decreasing throughput of long-duration large flows. according to the rapid increase in internet traffic volume, effective traffic engineering is increasingly required. specifically, the traffic of long-duration large flows due to the use of peer-to-peer applications, for example, is a problem. most conventional qos controls allocate a fair-share bandwidth to each flow regardless of its duration. thus, a long-duration large flow (such as a p2p flow) is allocated the same bandwidth as a short-duration flow (such as data from a web page) in which the user is more sensitive to response time, i.e., file transfer time. as a result, long-duration large flows consume bandwidth over a long period and increase response times of short-duration flows, and conventional qos methods do nothing to prevent this. in this paper, we therefore investigate a different approach, that is, a new form of bandwidth control that enables us to achieve better performance when handling short-duration flows while maintaining performance when handling long-duration flows. the basic idea is to tag packets of long-duration large flows according to traffic conditions and to give temporarily higher priority to nontagged packets during network congestion. we also show the effectiveness of our method through simulation.
design of survivable hybrid wireless-optical broadband-access network. the hybrid wireless-optical broadband-access network (woban) is a promising architecture for access networks. although the front-end wireless mesh networks in a woban are self-healing, the back-end passive optical networks (pons) do not have survivability due to their tree topology. we propose a costeffective protection method for woban that deals with network element failures in the optical part of woban. we define the maximum protection with minimum cost (mpmc) problem and show that the problem can be converted to the minimum cost maximum flow (mcmf) problem. we also present an ilp model for the mcmf problem. numerical results are reported for applying our algorithm to obtain the optimal solutions for different instances of the mpmc problem.
spatial-temporal event correlation. temporal event correlation deals with removing temporally redundant events to produce synthesized events, simplifying downstream processing. in situation management applications and location-based services, it is necessary to incorporate spatial constraints into the correlation process. this requirement is difficult to meet because the traditional algorithms for spatial processing are not well-suited to spatial dynamics occurring in these applications. in this paper we formalize spatial-temporal event correlation compared to the functionality of temporal correlation, present an architecture for efficient implementation, analytically analyze the architecture's performance relative to two other designs, and describe a system design for efficiently supporting situation management applications and location-based services.
hybridcast: a hybrid probabilistic/deterministic approach for adjustable broadcast reliability in mobile wireless ad hoc networks. broadcast is a crucial yet expensive building block for many applications in bandwidth-scarce mobile wireless ad hoc networks. we propose a hybrid deterministic/probabilistic, decentralized broadcast protocol with adjustable broadcast reliability and overhead. the paper first proposes a purely probabilistic, topology-aware broadcast algorithm. the probabilistic broadcast adjusts each node's broadcast forwarding probability locally such that the average broadcast reliability requirement is met. an extension of the probabilistic broadcast to tolerate node mobility and packet loss is then presented. furthermore, the paper augments the proposed probabilistic broadcast scheme with an existing deterministic broadcast protocol in order to reduce excessive broadcast overhead. the proposed hybrid protocol, called hybridcast, combines good characteristics of probabilistic broadcasts, such as adjustable reliability and resilience to mobility, with good characteristics of deterministic broadcasts, such as few retransmissions and low packet collisions. the simulation results show that the proposed protocol can achieve the system's reliability requirement with good tolerance to mobility and packet losses while incurring low broadcast overhead.
interference cancellation in distributed space-time coded wireless relay networks. this paper considers the interference cancellation (ic) problem in multi-user wireless relay networks. first, it is shown that using distributed space-time coding (dstc), the multiple antenna ic scheme previously proposed for systems with direct transmissions can be applied to relay networks. the ml decoding after full ic can be performed symbol by symbol. then, by allowing ic at relays, a new degree of freedom in relay network design is discovered. with this new idea, the required number of antennas at the receiver for full ic can be reduced and a balance between diversity and delay can be obtained.
robust pim-sm multicasting using anycast rp in wireless ad hoc networks. due to its bandwidth efficiency, multicast makes a group-centric communication more viable in wireless ad hoc networks with limited radio resources. pim-sm, a de facto standard multicast protocol known for its high scalability, is a good fit for a large-scale ad hoc network. however, it does not provide a robust multicast communication under rp outage and host mobility. in this paper, we propose a robust way of configuring pim-sm using anycast rp in wireless ad hoc networks. we analyze the impact of cardinality and locations of anycast rps on the network performance under node mobility. based on these observations, we find metrics for near-optimal cardinality of anycast rps and propose a novel rp selection scheme. the proposed scheme is proven to make pim-sm robust against mobility while satisfying qos requirements and maintaining the scalability of pim-sm.
evidences behind skype outage. skype is one of the most successful voip application in the current internet spectrum. one of the most peculiar characteristics of skype is that it relies on a p2p infrastructure for the exchange of signaling information amongst active peers. during august 2007, an unexpected outage hit the skype overlay, yielding to a service blackout that lasted for more than two days: this paper aims at throwing light to this event. leveraging on the use of an accurate skype classification engine, we carry on an experimental study of skype signaling during the outage. in particular, we focus on the signaling traffic before, during and after the outage, in the attempt to quantify interesting properties of the event. while it is very difficult to gather clear insights concerning the root causes of the breakdown itself, the collected measurement allow nevertheless to quantify several interesting aspects of the outage: for instance, measurements show that the outage caused, on average, a 3-fold increase of signaling traffic and a 10-fold increase of number of contacted peers, topping to more than 11 million connections for the most active node in our network - which immediately gives the feeling of the extent of the phenomenon.
capex-aware design of survivable dwdm mesh networks. this paper reviews the basic architecture and component costs of opaque, transparent, and semitransparent dwdm networks and looks at the network design problem from a capital expenditure (capex) point of view. given are a fiber topology and a demand matrix with different bit rates. required is the least-cost optical equipment for that topology together with the routing and potential muxponder-based aggregation of all demands such that they can be supported by the newly designed network. we look at the problem for networks without resilience requirements and for survivable networks using 1+1 protection against single fiber cuts. we model this problem for the three types of optical networks by integer linear programs (ilps) in a canonical way.
deference mechanisms significantly increase the mac delay of slotted csma/ca. slotted csma/ca is an algorithm proposed by ieee 802.15.4 in order to deal with the contention of energy constrained nodes. slotted csma/ca is used during a limited time interval, included in a superframe. two specific mechanisms defer the transmissions that would occur towards the end of the contention period. multiple models of the average delay or throughput of slotted csma/ca have been proposed recently, but they do not take into account the deference mechanisms. in this paper, we show that the deference mechanisms occurring at the end of the superframe have a significant impact on the performance of slotted csma/ca. we prove this by giving the distribution of the delay in a simple scenario, obtained by simulation. then, we compute the average delay tmac of traversing the mac layer, as the mac parameters or the frame size vary. we show that for either reactive wpans and energy-efficient wpans, the impact of the deference mechanisms is important.
sphere packing optimization and exit chart analysis for multi-dimensional qam signaling. we investigate on multi-dimensional qam constellations optimized by sphere packing with the known densest lattices. we propose a greedy design method assisted by the sphere detection. it is demonstrated that the optimized constellations can significantly increase the squared minimum distance in comparison to the conventional qam constellations. in addition, we analyze the optimized qams through the use of an extrinsic information transfer (exit) chart for iterative decoding.
femtocell coverage optimization using switched multi-element antennas. femtocells are low-cost, low-power cellular base stations that are deployed by the end user to supplement macrocellular coverage and provide high data rates in the customer's premises. in femtocell deployments, leakage of the pilot signal to the outside of a house can result in a highly increased signalling load to the core network as a result of the higher number of mobility events caused by passing users. in this paper, a low cost multi-element antenna solution is proposed to reduce the core network mobility signalling over previously published results using a single antenna only. antenna gain pattern measurements of a prototype with two patches and two inverted f antennas are presented and a corresponding feeder network is discussed. self-optimization methods are proposed that jointly select an appropriate antenna pattern and optimize the pilot power. this allows to better match the femtocell coverage to the shape of each individual house and results in an improvement of both indoor coverage and core network signalling resulting from mobility events.
statistical analysis of multiple access interference in asynchronous uwb impulse radio. optimal component and system design requires knowledge of the statistics underlying the system. to date, the determination of the probability distributions characterizing the multiple access interference in ultra-wide bandwidth wireless systems is an unsolved problem. the statistical characteristics of the multiple access interference in ultra-wide bandwidth wireless systems are studied. expressions for the probability density functions of the distribution due to asynchronous multiple access interference and additive white gaussian noise are derived for both additive white gaussian noise and multipath fading ultra-wide bandwidth environments. the accuracies of the derived expressions for the probability density functions are assessed and confirmed by simulation results.
on the performance of ofdm in zero-if receivers impaired by tx leakage. transmitter leakage has a significant impact on the system performance in mobile devices using zero-if receivers. in this contribution, the statistical properties of the tx leakage impact in zero-if receivers are derived, in the context of uplink and downlink ofdm transmission. in order to design suitable algorithms for the digital compensation of tx leakage in ofdm communication systems, an accurate modeling of the corresponding performance loss is required.we therefore provide a statistical description of tx leakage effects on ofdm signals, which is used to compute bit error rates and mutual information.
on the log-normal fading networks: power control and spatial reuse. in this paper, we consider two fundamental problems in log-normal fading networks. one is the energy efficiency. the other is the characterization of the internode interferences and spacial reuse. we first introduce a power efficiency factor as a new parameter to measure the transmit efficiency and obtain an optimal transmit power allocation of the concurrent transmitters in such fading environment. the internode interference caused by the simultaneous transmissions within a local area is then analyzed. the analysis will also be extended to the whole network within unlimited region where the interference accumulative impact is taken into account. by doing so, we set up a direct link between the interference double disc model with the statistical accumulative interference model and derive the optimal spatial reuse distance to guarantee the network efficiency. finally, we propose a concurrent access strategy, ocmac (opportunistic concurrent mac), which can efficiently mitigate the internode interference through the node coordination before the simultaneous transmissions while keeping a relatively low transmit power and high spatial reuse efficiency.
iptv quality of service management in home networks. in the progressive development of iptv technology, special attention is being paid at the assurance of an appropriate service quality to the end user. several research and standardization activities are studying how to provide qos for iptv streams along the delivery path from the head end office/video server to the end user. the customer's premise is the last part of this path, and the one that is typically not under control of an operator. at the same time, the home network is becoming a complex environment, including a variety of devices and different network technologies. this paper presents an architecture for iptv quality of service management focused on the home network. a key point of this solution is the introduction of service assurance functions in the home gateway. a prototype of the proposed solution proves the applicability of this approach.
fast distributed multi-cell scheduling with delayed limited-capacity backhaul links. both fast scheduling and spatial signal processing have proven to be capacity-increasing methods in wireless communication systems. however, when applied in the downlink of a cellular network, the combination of both leads to non-stationary intercell interference. if the base stations do not cooperate, either they have to encode the data very conservatively to gain robustness or the non-stationary fluctuations of the interference powers lead to frequent outages, both of which strongly impair the average achievable throughput. on the other hand, base station cooperation increases complexity and delays, contradicting the desire for fast scheduling algorithms. in this paper, we propose a scheme that makes average channel state information available to all base stations via low-rate backhaul communication, whereas high-rate inter-base-station communication is limited to b ⌈log2 k⌉-bit integers, k being the number of users in each of the b cells. simulations show that for slow fading channels, the proposed algorithm preserves most of the per cell sum-rate of other beamforming and dirty-paper coding approaches that have unlimited-capacity backhaul links. furthermore, when out-of-cell information is outdated the proposed algorithm even outperforms those.
centralized and distributed power allocation in multi-user wireless relay networks. optimal power allocation for multi-user amplify-and-forward wireless relay networks in which multiple source-destination pairs are assisted by a set of relays is investigated. two relay power allocation strategies based on maximization of either i) the minimum rate among all users or ii) the weighted sum of rates are developed. a distributed implementation of the maximum weighted-sum-rate power allocation strategy is also studied. numerical results demonstrate the efficiency of the proposed strategies and reveal their interesting throughput-fairness tradeoff in resource allocation.
random access protocols for wlans based on mechanism design. in wireless local area networks (wlans), quality of service (qos) can be provided by mapping applications with different requirements (e.g., delay and throughput) into one of the available access categories (acs), as is done in the ieee 802.11e standard. with the increasing programmability of network adapters, a malicious user can strategically declare a higher ac for its application to gain an unfair share of resources. this can drastically degrade the network performance and avoid adequate service distinction among different acs. in this paper, we use the technique of mechanism design in game theory to tackle this problem in wlans with random access. we propose to use the vickrey-clarke-groves (vcg) mechanism in order to motivate each station to inform the access point (ap) truthfully, about the required ac of its application. the ap will then inform each station about its persistent probability and the price it needs to pay for the offered service. the result of the allocation of the persistent probabilities can be used for admission control. simulation results show that the use of mechanism design can lead to a higher aggregate utility and prevents malicious users from gaining an unfair share of the network bandwidth.
analysis of probabilistic flooding: how do we choose the right coin? this paper studies probabilistic information dissemination in random networks. consider the following scenario: a node intends to deliver a message to all other nodes in the network ("flooding"). it first transmits the message to all its neighboring nodes. each node forwards a received message with some network-wide probability pf. a natural question arises: which forwarding probability pf should each node use such that a flooded message is obtained by all nodes with high probability? in other words, what is the minimum pf to achieve a high global outreach probability? we first present a generic approach to estimate the probability for achieving global outreach. this approach is then employed in erdös rényi random graphs, where we derive an upper and a lower bound for the global outreach probability for given random network and flooding parameters. the analysis is complemented with simulation results showing the tightness of both bounds. as a final result, we take a system design perspective to show a number of parameter vectors leading to global outreach.
controller design for rate assignment in wireless networks. in this paper, data-rate assignment in is-856 uplink (reverse link) is studied. the problem is first formulated in an interference model framework, and then a dynamic control strategy is developed for efficient rate assignment. in the first step, the controller is designed for the special case when the number of users in the network is fixed. then, the minimum time required for a dynamic network (where the number of users is subject to change) to achieve a desired performance is obtained. the simulation results are presented to elucidate the effectiveness of the proposed approach.
protecting location privacy in large-scale wireless sensor networks. in a wireless sensor network, an adversary equipped monitoring antenna can easily overhear packets, which may facilitate identifying the directions of packet flows and trace to the sink or source nodes. in order to defend the location privacy of the sink and source nodes, we propose a location privacy support scheme (lpss). we prove that, with the increase in distance between sink and source node, the protection strength of the lpss increases exponentially. theoretical and simulation results show that lpss can provide strong location privacy protection for both the sink and source nodes under different attacks. under the similar delivery delay (or energy consumption), the safe time provided by lpss is much longer than other approaches. facilitated by the study on lpss, we further investigate that the correlation between sink and source nodes. we find that if one source node is exposed to a sophisticated adversary, conventional fake packet injection mechanisms for protecting sink node tend to be useless.
3g/hspa performance in live networks from the end user perspective. operators around the world are improving their 3g/umts networks by introducing hspa (high speed packet access) that includes both, enhanced uplink and downlink. the hspa is expected to finally provide the mobile broadband access that is able to compete with the fixed connections in performance regarding popular applications such as web browsing, voip, and video. however, it has remained unclear how well the live networks fulfill the promises of performance. we contribute in filling this void by providing measurements in live 3g/hspa networks. we compare tcp and udp goodput performance in basic wcdma, hsdpa-only, and hspa. moreover, one-way delay and jitter measurement results are presented in a stationary as well as in a mobile scenario. the results show that the enhanced network outperforms clearly its predecessor by offering considerably higher data rates, lower delay, and lower jitter. also, because of the harq (hybrid automatic repeat request), there are notably less delay spikes observed with hspa than with wcdma. however, the drive tests show that handovers result in high jitter and interruptions to the communications, which causes, e.g., decreased voip call quality. the uplink enhancement (hsupa) improves the tcp performance beyond the hsdpa-only access, but it is still behind that of the fixed connections. in addition, the properties of the channel allocation mechanism still considerably deteriorate the data rates seen by the user. nevertheless, the hspa is an enabler for true mobile broadband internet access.
downlink scheduling for qos-guaranteed services in multi-user mimo systems with limited feedback. significant throughput gains and system fairness can be obtained by employing scheduling schemes based on precoding techniques. however, qos guarantee requirements are seldom taken into account. in this paper, we propose a downlink scheduling algorithm for qos-guaranteed services in multi-user multiple-input multiple-output (mimo) systems with limited feedback. the proposed algorithm combines stream selection with multi-user packet scheduling. to maximize the overall capacity and reduce co-channel interference, streams are selected in accordance with precoding matrices. in multi-user packet scheduling, the base station first determines the sdma region size for the primary streams. in addition, packet scheduling for the secondary streams is performed to completely exploit spatial multiplexing gains. numerical results show that, at the cost of slightly lower system fairness, the proposed algorithm can achieve higher spectrum efficiency, and have a noticeable improvement in guaranteeing qos requirements in terms of data rates and delay.
sleeping schedule-aware minimum latency broadcast in wireless ad hoc networks. broadcast is a fundamental operation of wireless ad hoc networks (wanet) and has been widely studied in the last decade. however, very few existing broadcasting strategies has considered the scenarios with sleeping schedule, which is a prevalent power-saving method in wireless networks. in this paper we study the sleeping schedule-aware minimum latency broadcast (mlb-sa) problem in wanets and prove its np-hardness. by constructing a shortest path tree (spt) defined with the latency function on the network, we derive a lower bound on the broadcast latency theoretically. following the top-down layered approach and using the d2-coloring solution, we proposed two progressively improved algorithms: the simple layered coloring algorithm (slac) and the enhanced layered coloring algorithm (elac) for the mlb-sa problem. the slac has an approximation ratio of o(δ2 + 1) where δ is maximum degree of the network, while the elac has constant approximation ratio of 24|t|+1 where |t| is the number of time-slotsin a scheduling period. the two algorithms have o(n2) and o(n3) time complexities respectively. the performance of the proposed algorithms are evaluated by simulations.
performance analysis of trust-based node evaluation schemes in wireless and mobile ad hoc networks. as the use of mobile ad hoc networks spreads beyond personal networks to practical military and commercial applications, addressing security issues becomes extremely important in this area. however, mobile networks are more susceptible to malicious behavior; thus, an effective node evaluation mechanism can prevent malicious nodes from initiating attacks and tampering the data communications process in these networks. in this article, we formalize the node evaluation problem, discuss its challenges, and present possible solutions. moreover, we propose a novel node evaluation solution with the assistance of trustworthy neighboring nodes, which allows a mobile node to more effectively evaluate its neighbors based on the additional trust information from selected neighboring nodes. our schemes can thus enhance the security of a network and improve the effectiveness of node evaluation. finally, we evaluate our node evaluation strategies and analyze their advantages when compared to existing node evaluation mechanisms used in wireless communications.
rate and end-to-end delay control for multicast and unicast flows. there is growing evidence that a new generation of potentially high-revenue applications are emerging that can benefit from widespread multicast support in large ip networks. these applications, such as streaming video and interactive games, have inherent quality of service (qos) requirements. current methods of qos provisioning have either scalability concerns or cannot guarantee end-to-end delay with acceptable packet loss unless bandwidth is over-provisioned. while low jitter guarantee is sufficient for streaming applications, maximum end-to-end delay is also required for interactive games. previously, we presented a new holistic architecture for end-to-end qos guarantee for unicast flows only in the core network based on several novel combined rate and end-to-end delay control algorithms. we also demonstrated the viability of this architecture and its advantage over differentiated services by implementing it in edge and core routers and monitoring the rate, end-to-end delay and packet loss of all flows in a six-node core network with long delay links. here, we extend the architecture to include multicast flows and demonstrate that network operators can tune the architectural configuration parameters so as to fairly share the excess bandwidth between multicast and unicast flows.
ergodic secrecy capacity region of the fading broadcast channel. we consider the fading broadcast channel from a secrecy point of view. in this channel, each user views the other user as an eavesdropper, and wants to keep its information as secret from the other user as possible. first, we consider a more general channel model which consists of l independent sub-channels, where in each sub-channel, one of the users' channel is less noisy with respect to the other user. since the user which has the less noisy observation can be different in each sub-channel, the overall channel is not less noisy for any one of the users. we establish the secrecy capacity region of this channel for the case where the transmitter sends a common message to both users and an individual confidential message to each user. this channel model encompasses the sub-class of channels, where in each sub-channel, one of the users' observation is degraded with respect to the other user. the parallel gaussian broadcast channel belongs to this sub-class. in the gaussian case, we identify the optimum input distribution, which is gaussian, and the optimum power allocation corresponding to each point on the boundary of the secrecy capacity region. finally, noting that the fading gaussian broadcast channel is equivalent to a parallel gaussian broadcast channel from an ergodic capacity perspective, we explicitly evaluate the ergodic secrecy capacity region of the fading broadcast channel.
performance analysis of the signal-to-noise ratio assisted crosstalk channel estimation for dsl systems. in this paper we investigate the tracking performance of the downstream (ds) crosstalk (xt) channel estimation based on the reported signal to noise ratio (snr), in particular for digital subscriber line (dsl) systems. aiming to its simplicity, the snr-assisted xt estimation, has been recognized in itu as a backward compatible method that does not require any change in the very high speed digital subscriber line 2 (vdsl2) standard. this low complex algorithm can be used for xt channel estimation in dynamic spectrum management (dsm) techniques today. the algorithm as proposed recently, relies on sending perturbing signals on the victim lines (vls) and reporting the snrs by those lines to acquire the crosstalk channel from some disturber line (dl) to the vls. we generalize this concept to include full startup, tracking and joining scenarios as well as the impact of different perturbation signal choices. simulation results reveal that starting from no crosstalk precompensation, and updating a precoder matrix based on the ds crosstalk channel estimates, the far-end crosstalk (fext) free snr can be reached in few iterations (36 snr measurements for the four lines case).
lightpath establishment in wdm networks with best effort shared path protection in impaired-transmissions. in wavelength division multiplexing (wdm) networks, failures can imply in great loss of data due to high transmission rates, leading to the need of employment of protection mechanisms. transparency and switching in all-optical networks causes physical impairments, which can significantly degrade the signal quality. if the signal quality in a path is below acceptable values, this path cannot be used by incoming requests for lighpath establishment. therefore, quality needs to be checked by the routing and wavelength assignment algorithm. this paper introduces two novel algorithms for shared path protection in wdm networks that take into account the pmd, ase and homowavelength crosstalk physical impairments in path selection. the efficacy of these algorithms are compared to those of their impairment unaware counterpart.
beamforming in dual-hop fixed gain relaying systems. the performance of beamforming in dual-hop co-operative networks with fixed-gain relays is investigated. these kinds of relays offer low complexity and ease of deployment when compared with variable-gain relays. in our analysis, the source and destination nodes are equipped with multiple antennas, whereas the relay is assumed to be a single-antenna device. closed-form expressions for the outage probability (op), probability density function (pdf), moment generating function (mgf), and generalized moments of the end-to-end signal-to-noise ratio (snr) are obtained. it is shown that when the same antenna configurations are considered at the source and destination sides, the power imbalance between the hops may be either beneficial or detrimental for the overall system performance. in addition, depending on whether the average snr of the second hop is equal, lower, or higher than that of the first hop, an increase of the number of antennas may not necessarily result in a substantial improvement in performance.
practical scalability of wavelength routing switches. packet switches with optical fabrics can potentially scale to higher capacities. it is also potentially possible to improve their reliability, and reduce both their footprint and power consumption. a well-known alternative for implementing hardwired switches is arrayed waveguide grating (awg). ideally, awg insertion losses do not depend on the number of input-output ports, meaning that scalability is theoretically infinite. however, accurate second-order assessment has demonstrated that in-band crosstalk exponentially increases the power penalty, limiting the realistic useful size of awg commercial devices to about 10-15 ports (13-18 db) [1]. on the other hand, the in-band crosstalk at awg outputs depends on the connection pattern set by the scheduling algorithm and this port count limitation is calculated for worst-case scenarios. in this paper, we show that distributed schedulers with predetermined connection patterns can be used to avoid these harmful arrangements. we also show that the probability of worst-case patterns is very low, allowing us to set a more realistic port limit for general centralized schedulers and very small losses. with these results, we calculate more realistic port count limits for both scheduler types.
low complexity decision directed channel tracking for high mobility ofdm systems. pilot assisted channel tracking (pact) has been very popular for channel estimation in ofdm systems. however, as the mobility in the system increases and one has to maintain a high accuracy in channel estimation, the pilot overhead typically has to be increased. emerging cellular ofdm standards are expected to use about 6 - 12% pilot overhead per stream, and any possible reduction in pilot overhead would be useful. decision directed channel tracking (ddct) can help reduce pilot overhead, but is known to suffer from error propagation at high fade rates. in emerging broadband wireless systems promising peak bit rates of 50 mbps or more, saving on pilot overhead by using ddct schemes would be highly attractive provided: (a) such a ddct approach does not suffer from error propagation and has an error rate performance comparable to (or better than) pact schemes even at high fade rates; (b) the computational complexity of such a ddct approach is not significantly more than that of the mmse based pact scheme. in this work, we propose a low complexity ddct method which exploits the structure of the regression matrix in conjunction with robust statistics to mitigate the effect of error propagation. it has a much lower computational complexity and a better error rate performance than the decision directed em-kalman and other existing robust statistics based ddct schemes. the proposed method also outperforms a 12.5% pilot overhead based pact scheme with only a modest increase in computational complexity.
chip-level modulated bppm fiber-optic code division multiple access. chip-level modulated binary pulse position modulation (clm-bppm) is proposed as a modulation scheme for fiber-optic code division multiple access (fo-cdma) systems using optical orthogonal code (ooc) for time domain signal spreading. the proposed scheme provides better synchronization and source activity detection at the receiver side as compared to on-off keying (ook). a mathematical expression is derived for the ber of clm-bppm using a combinatorial interference pattern analysis approach. the mathematical model is verified using simulation. numerical results demonstrate that clmbppm has a ber that is very close to ook. moreover, increasing the average source activity causes the performance of the clmbppm to approach that of the ook system with an asymptotic ber equal to the ber of ook at full user activity.
efficient implementation of binary sequence generator for wimax and wran on programmable digital signal processor. in this paper, an efficient design for implementing binary sequence generator on 32-bit instruction execution mode ti tms320c6416 dsp is presented. the main goal is to achieve high-speed channel coding sequence generator that can support ieee802.16 wimax and ieee 802.22 wireless regional area network (wran). the paper focuses on exploiting the binary property of data value and the finite bit-string organization of data on the dsp systems. the impact on parametric variables of the sequence generator on the computational clock-cycles is analyzed. computational results of sequence generation on ti 'c64x dsp show that the proposed design achieves significant speed improvement over the conventional sequential implementation. with this improvement, more functionalities can be included in a single dsp or lower power consumptions can be expected.
on the optimal transmission for the mimo bidirectional broadcast channel. in this work the transmit covariance matrix optimization problem for the mimo gaussian bidirectional broadcast channel is studied. a half-duplex relay node establishes bidirectional communication between two nodes using a decode-and-forward protocol. in the initial multiple access phase both nodes transmit their messages to the relay node. in the succeeding phase the relay broadcasts an optimal re-encoded message so that both nodes can decode the other's message using their own message as side information. we show that if the channels are orthogonal then there exist equivalent transmit strategies with different ranks. the study of special cases reveals some of the difficult structure of the optimal solution. in particular a closed form procedure for the case of full rank transmission for invertible channels is derived. moreover, for parallel channels the optimal solution is completely characterized and discussed.
adaptive 2.5 gbit/s optical wireless systems employing a two dimensional beam clustering method and imaging diversity receivers. in this paper, we propose and evaluate a novel optical wireless (ow) configuration that employs a two dimensional adaptive beam clustering method (2dabcm) in conjunction with imaging diversity receivers. our goal is to reduce the effect of intersymbol interference and to improve the signal-to-noise ratio (snr) when the system operates under the constraints of background noise (bn) and multipath dispersion. in the conventional diffuse system, an snr improvement of 22 db and an increase in the bandwidth from 38 mhz to 200 mhz approximately, is achieved when an imaging receiver is implemented. furthermore, the new methods introduced (transmit power adaptation, beam clustering, and diversity imaging) increase the bandwidth from 38 mhz to 5.56 ghz. previous optical wireless systems operated typically at 30 to 100 mbit/s and here we report a system that operates at 2.5 gbit/s. our results indicate that the new 2.5 gbit/s 2dabcm transmitter with a new imaging diversity receiver (with select best (sb)) demonstrates an snr improvement of 16 db over the non-imaging cds system operating at 30 mbit/s. the results also show that the proposed system (imaging 2dabcm at a bit rate of 2.5 gbit/s) produces an snr improvement of 10 db when maximum ratio combining (mrc) replaces sb.
comparing effects of carrier frequency offset on generalized multi-carrier and ofdm systems. the carrier frequency offset (cfo) could destroy the orthogonality of ofdm subcarriers and induce the inter-carrier interference (ici) spread. however, the generalized multi-carrier (gmc) system reflects different interference characters in the presence of cfo. in this paper, we exactly analyze the cfo effect on gmc, which multiplexes several single band single carrier based frequency division multiple access (sc-fdma) streams in frequency domain, under the scenario of additive white gaussian noise (awgn) channels. a closed-form expression of signal to interference plus noise ratio (sinr) is derived for the gmc systems in the presence of cfo. furthermore, the bit error rate (ber) performance analysis is also performed in comparison with the traditional ofdm system for both uncoded and coded environments. analysis and simulation results show that the feature procedure of discrete fourier transform (dft) spread may condense the cfo-induced interference in the first symbol of each subband, resulting in less interference in other symbols. such condensing procedure can provide robustness against the cfo effect, which also lies on the subband bandwidth for gmc systems. in contrast to the conventional ofdm system, gmc exhibits more robustness when each subband width is designed for 4 times larger than the subcarrier spacing.
how much multiuser diversity gain is required over large-scale fading? in multiuser diversity systems, the impact of large-scale fading on the total system performance such as link quality and system power has not been widely addressed. considering large-scale fading, we propose an adaptive multiuser scheduling to minimize the total system power while reducing the effect of large-scale fading on the system bit error rate. the number of active users is adapted to every shadow variation, which varies slower than small-scale fading. we consider the two widely used multiuser systems (i.e., delay-tolerant, and delay-sensitive multiuser systems). closed-form expressions for the bit error rate are derived. the selection procedure for the minimum number of users is introduced for guaranteed performance of the above multiuser systems. the impact of adaptive multiuser diversity gain on the system power and bit error rate is illustrated over large-scale fading channels by numerical results.
energy efficient cooperative broadcasting in wireless networks. minimizing the total transmission power is one of the main objectives of efficient broadcast algorithms in wireless networks, where all nodes are powered by battery with limited energy supply. cooperative transmission is an important way to make full use of the space diversity and can save the transmission power significantly, especially in the wireless broadcast transmission, where the nodes can accumulate the overheard information. in this paper, firstly a centralized cooperative broadcast algorithm, which permits multiple nodes to cooperate in transmitting the broadcast message, is proposed to save the total transmission power. considering that the centralized algorithm requiring a global knowledge of the networks is impractical in large wireless networks, the distributed version of the centralized algorithm requiring only 1-hop neighborhood information is proposed under the assumption that limited frequency band is available. the distributed algorithm combines the physical (phy) and medium-access-control (mac) layer mechanisms to reach all the nodes in a cooperative way. though the proposed distributed algorithm is inferior to the centralized algorithm in terms of total transmission power, it takes less resource to broadcast than the centralized algorithms. simulation results show that both the centralized algorithm and distributed algorithm can get a better performance than the existing broadcast algorithms. furthermore, the distributed algorithm can achieve the total transmission power close to the centralized algorithm.
markov chain monte carlo detection methods for high snr regimes. statistical detectors that are based on markov chain monte carlo (mcmc) simulators have emerged as promising low-complexity solutions to both multiple-input multiple-output (mimo) and code division multiple access (cdma) communication systems. while these types of detectors achieve unprecedented near capacity performance, i.e., when operated in low signal-to-noise ratio (snr) regime, they exhibit a serious problem at medium to high snr regimes, referred to as the "stalling" problem. in this paper, we investigate the sources of this degradation and propose a new search strategy called constrained mcmc to remedy the issue of stalling.
a high throughput load balance algorithm for multichannel wireless sensor networks. achieving efficient bandwidth utilization in multi-channel sensor networks is a challenging research problem. in this paper, we present a cognitive load balance algorithm for single-hop multi-channel sensor networks. based on the load distribution of all base stations, our algorithm dynamically alternates the communication channels. as a result, the extra load from over-loaded channels is directed to under-loaded channels with a computed switch probability. in this paper, we also prove that a high throughput can be achieved if the load is balanced. the performance of the load balance algorithm is evaluated through both theoretical analysis and simulation study.
static analysis of executables for collaborative malware detection on android. smartphones are getting increasingly popular and several malwares appeared targeting these devices. general countermeasures to smartphone malwares are currently limited to signature-based antivirus scanners which efficiently detect known malwares, but they have serious shortcomings with new and unknown malwares creating a window of opportunity for attackers. as smartphones become host for sensitive data and applications, extended malware detection mechanisms are necessary complying with the corresponding resource constraints. the contribution of this paper is twofold. first, we perform static analysis on the executables to extract their function calls in android environment using the command readelf. function call lists are compared with malware executables for classifying them with part, prism and nearest neighbor algorithms. second, we present a collaborative malware detection approach to extend these results. corresponding simulation results are presented.
capex costs of lightly loaded restorable networks under a consistent wdm layer cost model. shared protection promises the benefits of lower network capacity utilization without sacrificing the availability level of dedicated protection. shared protection is often evaluated in terms of its spare capacity efficiency, but seldom in terms of real-world capex (capital expenditure) costs. in this paper, we investigate the design of several shared protection architectures under a standardized cost model for the wdm layer, developed recently within the european nobel project. this paper presents a comparative study of the implementations and costs of these architectures under this model. findings show a counterintuitive relationship between network capacity utilization and design cost when the network is lightly loaded.
investigating multiple alternating cooperative broadcasts to enhance network longevity. we propose a broadcast protocol that is based on a form of cooperative transmission called the opportunistic large array (ola). multiple snr (or transmission) thresholds are used to define mutually exclusive sets of olas, such that the union of the sets includes all the nodes in the network. the new protocol, termed alternating ola with transmission threshold (a-ola-t), exercises a different set of olas on each consecutive broadcast from the same sink until all sets have transmitted once. then the sequence repeats. thus, broadcasts consume energy efficiently and uniformly over the network, and a-ola-t is especially well suited for static networks. the transmission thresholds are optimized to maximize the network life if broadcasts were the only transmissions. in this paper, we first optimize triples of broadcasts, and then extend the optimization for a higher number of broadcasts.
a new joint estimation scheme for carrier frequency offset and i/q imbalance. this paper introduces a novel algorithm for jointly estimating carrier frequency offset and i/q imbalance for ofdm systems. the new algorithm is a closed form solution to obtain the frequency offset and i/q imbalance parameters in the absence of noise. in the presence of noise, the proposed algorithm uses the least squares algorithm to accurately estimate the parameters. the proposed algorithm is thus very scalable in terms of complexity. while the target system is ofdm, the proposed algorithm applies to any system as long as two identical data blocks are received in the receiver. simulation results show that given a suitable amount of cfo, the high estimation accuracy of the proposed algorithm makes its ber performance comparable to a system without cfo and i/q imbalance.
secure browser-based access to web services. access to web services via web front-ends provides all the advantages related to browser-based thin clients and is therefore a common setting. however, providing end-to-end security between web browsers and web services is currently not feasible due to the inadequate support for web service security in web browsers. moreover, the current soap apis offered by the major browsers are incompatible with one another making the task of providing a uniform solution to address this problem difficult. this paper describes a method by which the web service communication between a web browser and a web service is protected end-to-end using web service security thereby providing a means to overcome this limitation.
rate-per-link adaptation in cooperative wireless networks with multi-rate combining. rate adaptation based on signal-to-noise ratio (snr) measurements is a common channel adaptation scheme to increase throughput in wireless communication systems. to use rate adaptation efficiently in cooperative wireless networks, an adaptation algorithm must consider multiple channels (source-destination, source-relays, and relays-destination) to select modulation and code rates that maximize throughput. in this paper we analyze the potential gains that combining cooperation with rate adaptation brings in three steps: (1) we derive the theoretical capacity bounds for ideal rate adaptation schemes for typical topologies. (2) we propose an offline heuristic for computing snr thresholds aimed at reaching the derived bounds. (3) using this heuristic, we compare rate adaptation for maximal ratio combining (mrc), where links are equally adapted, with soft-bit mrc (sbmrc), where links are individually adapted. we find that adapting the rate per link is superior in terms of throughput.
spectrally efficient anti-jamming system design using message-driven frequency hopping. this paper considers spectrally efficient anti-jamming system design based on message-driven frequency hopping (mdfh). we first analyze the performance of the mdfh system under different jamming scenarios. it is observed that mdfh is particularly robust under strong jamming. however, it experiences a performance bottleneck under disguised jamming, for which the jamming power is close to the signal power. to overcome this drawback, we propose an anti-jamming mdfh (aj-mdfh) system. the main idea is to transmit an id sequence along with the information stream. the id sequence is generated through a cryptographic algorithm using the shared secret between the transmitter and the receiver. it is then exploited by the receiver for effective signal detection and extraction. it was shown that aj-mdfh is robust under strong jamming, and can effectively reduce the performance degradation caused by disguised jamming. simulation examples are provided to demonstrate the performance of the proposed approaches.
multihop light-trails (mlt) - a solution to extended metro networks. a light-trail is a generalization of a lightpath such that multiple nodes can take part in communication along the path. a light-trail exhibits properties of dynamic provisioning, optical multicasting and sub-wavelength grooming and architecturally is analogous to a shared wavelength optical bus with an out-of-band (oob) control channel. the bus feature results in a node that has a large pass-through loss, and hence restricts the size of a light-trail to metro environments. within a bus the oob control channel allows for dynamic real-time arbitration. due to this limitation, it is difficult to extend the light-trail concept to regional and core networks. in this paper we propose a method to provide multihop communication in light-trails thereby relaxing the limitation in hop count, as well as enhancing reach of communications. we propose node architecture and protocol requirements for creating multi-hop light-trails (mlts). we then discuss design issues for mlts in regional area networks through problem formulation. a simulations study validates mlts.
solution of a 200-node p-cycle network design problem with ga-based pre-selection of candidate structures. as a research challenge we have sought to create and solve p-cycle network design problems involving 200 or more nodes. at such problems sizes, the space of all simple cycle structures on the network graph cannot even be known in practice, let alone put into a conventional ilp problem instance. the approach being taken is a combination of ga methods with ilp; ga is guided by a subsidiary ilp surrogate problem to preselect a set of collectively high merit candidate cycles to populate a size-reduced final fully detailed ilp. feasible solutions of high quality have been obtained for an initial 200- node test case. comparison of the result by other workers is invited.
space-frequency-coded mimo ofdm receivers based on gaussian message passing. forney-style factor graphs are used for modeling space-frequency-coded mimo ofdm systems over frequency-selective fading channels. we analyze the gaussian message passing mechanism for the alamouti scheme and linear transformation of the factor graph. a new decision rule is derived in terms of the mean vector and covariance matrix of modulation symbols. we employ the k-best algorithm with reduced complexity to justify the effectiveness of our receiver.
analysis of delay statistics for the queued-code. quality of service (qos) guarantees in mobile wireless networks are typically provided through queuing analysis, which uses an idealized model for the physical layer, leading to optimistic guarantees. a queued-code combines ideas from queuing theory and information/coding theory, to allow rate adaptation, while enabling accurate modeling of the physical layer. previous work showed the benefit of using a queued-code, in achieving lower error probabilities while satisfying a fixed delay bound. this paper analyzes the queued-code when some function of delay statistics must be optimized while guaranteeing a fixed error probability. a practical implementation of queued-codes based on low density parity check (ldpc) convolutional codes is also presented. numerical and simulation results demonstrate the benefit of using the queued-code in obtaining a better qos.
a novel scheme for spatial localization of passive rfid tags; communication range recognition (crr) scheme. the rfid (radio frequency identification) tag is expected to be used as a tool of localization. with the localization of rfid tags, a mobile robot with an installed rfid reader can recognize the surrounding environment. in addition, it can be applied to a navigation system for walkers. in this paper, we propose a new scheme named communication range recognition (crr) in order to localize rfid tags effectively. in this scheme, the rfid reader finds the edges of the communication range when its position is moved appropriately by the robot. we evaluate the performance of the estimated position error through numerous experiments. we show that our proposed scheme can reduce the moving distance of the rfid reader without degrading the accuracy of localization in comparison with the conventional schemes.
carrier frequency dependent downlink spectral efficiency of cellular lte deployments. this paper explains a system level evaluation framework which allows performance assessment of cellular ofdm-based systems at different carrier frequencies. in the numerical examples we model the downlink transmission of an 3gpp lte deployment.
a distributed linear convolutive space-frequency coding for cooperative communication systems with multiple frequency offsets. multiple frequency offsets (cfo) in cooperative communications are difficult, if not impossible, to compensate completely at the destination node. the multiple cfo make the channel time-varying, and thus the conventional space-time codes to collect diversity gain for co-located multi-input multi-output (mimo) systems may not be applied directly. in a previous paper, we proposed a distributed space-frequency code (sfc), called frequency-reversal sfc (fr-sfc), for cooperative transmissions with multiple cfos and flat fading channels. we have shown that this code can achieve the full cooperative diversity with only linear receivers, such as zero-forcing (zf) and minimum mean square error (mmse) receivers. however, the code is not bandwidth efficient when the relay nodes are more than 3. to have a higher bandwidth efficiency, in this paper we propose a new distributed sfc called frequency-domain linear convolutive sfc(flc-sfc). the symbol rates of the new codes approach 1 when code block length is sufficiently larger than the number of relay nodes. furthermore. it achieves the full cooperative diversity with linear receivers.
a novel interface selection scheme for multi-interface wireless mesh networks. wireless mesh networks suffer of scalability problems when the number of nodes grows. to solve this issue, multi-interface wireless mesh networks were introduced. in such networks it is possible to use multiple channels to implement spatial reuse of frequencies. however, channel assignment schemes make this kind of networks complex to manage and limit their applicability in presence of mobile nodes. in this paper a novel technique is introduced for the optimization of resources allocation in a multi-interface wireless mesh network where channel assignment is fixed. with this technique the scalability of the network is improved and the support for mobility is easily granted.
a hybrid mc-cdma precoding scheme employing code hopping and partial beamforming. this paper proposes a hybrid transmission technique based on code optimization and partial linear precoding for interference exploitation on the downlink of phase shift keying (psk) based mulitcarrier code division multiple access (mc-cdma) systems. the first stage of the technique is to dynamically allocate codes to the users so that the combination of instantaneous data and user crosscorrelations yield a favourable constructive to destructive multiple access interference (mai) ratio. to further optimize the received signal to interference plus noise ratio (sinr), the second stage is to employ a dynamic, partial transmitter based pre-decorrelation scheme specifically designed for the exploitation of constructive mai. the decorrelation processing is targeted to the destructive interferers, while users that interfere constructively are let correlated. this results in a significant sinr enhancement without the need for additional power-per-user investment. mathematical analysis and simulations show that significant bit error rate (ber) performance benefits can be achieved with this technique.
general-rank beamforming for multi-antenna relaying schemes. we consider a wireless network consisting of a single-antenna transmitter, a single-antenna receiver, and a multi-antenna relay node. for such a network, we introduce the novel approach of general rank beamforming. in this approach, the relay multiplies the vector of its received signals by a general-rank complex matrix to obtain a new vector. each entry of this new vector is then transmitted on one of the antennas available at the relay. we show that maximizing the receiver snr subject to total relay power constraint yields a closed-form solution for the beamforming matrix. we also prove that if the channel coefficients from the transmitter to the relay antennas and those from the relay antennas to the receiver are statistically independent, the general rank beamforming approach results in a rank-one solution for the beamforming matrix.
potential field approach to ensure connectivity and differentiated detection in wsn deployment. this paper addresses the issue of wireless sensor network (wsn) deployment. we investigate this problem in the case where the monitored area is characterized by a geographical irregularity of the sensed events. precisely, we consider that each point of the deployment area requires a minimum threshold guarantee on the event detection probability. our proposed scalable deployment method, named potential field-based deployment algorithm (pfda), is based on the potential field and the virtual force approaches. our proposal is able to (1) satisfy the required event detection probability threshold for each point, in a large-scale area, while minimizing the number of deployed sensors and (2) to ensure the network connectivity. the results and evaluation analysis show that pfda outperforms the other strategies proposed in literature.
performance of sequential probability ratio test for gps acquisition. acquisition of signals in noise, in particular cdma signals like the global positioning system (gps) l1 c/a signal, can be carried out using fixed or variable dwell times. in this work, a sequential multiple dwell procedure for verifying acquisition is examined and compared to a fixed time single dwell strategy. the procedure under analysis is the sequential probability ratio test (sprt) which has not been widely used for gps applications, possibly due to its sensitivity to attenuation of the received signal relative to the design point. in this paper, it is shown that for the received signal to noise ratios (snr) typically encountered in gps, the sprt can outperform the single dwell detector strategy in terms of mean acquisition time. in addition, it is shown that the single dwell (sd) detector's fixed dwell time approaches the worst case dwell time for the sprt, as design point carrier to noise ratio decreases. thus, for very weak signals, the sprt can be a better choice of verification algorithm than the sd strategy, under certain constraints.
seas: a secure and efficient anonymity scheme for low-cost rfid tags. in this paper, we propose seas, a novel privacy preserving, anonymous authentication scheme for rfid tags, which allows the tags to use pseudonyms instead of their true identity for authentication. using seas, a tag generates random numbers and uses them to create a pseudonym as its identity for authentication. the pseudonym does not reveal the identity of the tag and the pseudonyms of multiple authentications appear random and uncorrelated to the adversary. a pseudonym can only be deciphered by the back-end authentication authority to identify the tag. no other entity in the network can link the pseudonym to the identity of the tag. our scheme is efficient, with a tag needing to perform only simple operations such as xor, bits shifting, bits concatenation, and random number generation. we perform security analysis of our scheme to show its effectiveness against different forms of attacks. we also perform comparison of our scheme with existing schemes in terms of efficiency in the use of resources. our scheme performs effectively, while at the same time being better than the other popular schemes in the literature in terms of cost and computation efficiency.
concurrent heap-based network sort engine - toward enabling massive and high speed per-flow queuing. a network sort engine (nse) that rapidly identifies the highest priority from numerous priorities is indispensable to enable per-flow queuing that supports massive queues in high-speed communications lines. this is because the bottleneck in per-flow queuing is the process to select a single queue to emit a frame from queues that are ready to emit frames; this process leads to sorting issues in identifying the highest priority. thus, a concurrent heap that parallelizes each layer of a binary tree has been developed as a method of implementing a massive and high speed nse. since it does not essentially modify conventional heap algorithms, it can work at high speed due to its lightweight memory management and it also ensures the worst-case runtime. as the fpga results from implementing the concurrent heap indicate that the required resources are very small, it could be implemented, in practice, in a small fpga, and the warranted runtime speed indicates that over 8,000 per-flow queues for a 10gbe lan-phy could work at the wire rate with successive minimum-length frames.
energy efficient collision aware multipath routing for wireless sensor networks. multipath routing can reduce the need for route updates, balance the traffic load and increase the data transfer rate in a wireless sensor network, improving the utilization of the limited energy of sensor nodes. however, previous multiple path routing methods use flooding for route discovery and transmit data with maximum power regardless of need, which results in waste of energy. moreover, often a serious problem of collisions among multiple paths arises. in this paper, we propose an energy efficient and collision aware (eeca) node-disjoint multipath routing algorithm for wireless sensor networks. with the aid of node position information, the eeca algorithm attempts to find two collision-free routes using constrained and power adjusted flooding and then transmits the data with minimum power needed through power control component of the protocol. our preliminary simulation results show that ecca algorithm results in good overall performance, saving energy and transferring data efficiently.
approximate expressions for cramer-rao bounds of code aided qam dynamical phase estimation. in this paper, we study bayesian and hybrid cramer-rao bounds (bcrb and hcrb) for the code-aided (ca) dynamical phase estimation of qam modulated signals. in order to avoid the calculus of the inverse of the bayesian information matrix and of the hybrid information matrix, we present some analytical expressions for the various crbs, which greatly reduce the computation complexity.
stereo image transmission over fading channels with multiterminal source coding. this paper addresses the problem of wireless delivery of a captured scene from two cameras, which do not communicate with each other, to a central point for joint decoding. we exploit correlation among two camera views using distributed source coding and use complete complementary (cc) data spreading to combat multiple access interference and noise even when the transmitters are de-synchronized. our distributed source coding scheme is based on uniform scalar quantization in the dct domain and non-asymmetric slepian-wolf coding via turbo codes. the non-asymmetric slepian-wolf scheme enables efficient trade-off between the transmission rates of the two cameras. simulation results indicate that the proposed system outperforms significantly two independently jpeg-encoded streams at low transmission rates.
green support for pc-based software router: performance evaluation and modeling. we consider a new generation of cots software routers (srs), able to effectively exploit multi-core/cpu hw platforms. our main objective is to evaluate and to model the impact of power saving mechanisms, generally included in today's cots processors, on the sr networking performance and behavior. to this purpose, we separately characterized the roles of both hw and sw layers through a large set of internal and external experimental measurements, obtained with a heterogeneous set of hw platforms and sr setups. starting from this detailed measure analysis, we propose a simple model, able to represent the sr performance with a high accuracy level in terms of packet throughput and related power consumption. the proposed model can be effectively applied inside "green optimization" mechanisms in order to minimize power consumption, while maintaining a certain sr performance target.
towards a gnu/linux ieee 802.21 implementation. multiaccess mobile devices and overlapping wireless network deployments have emerged as a next generation network fixture. to make the most of all available networks, mobile devices should be capable of handing over between heterogeneous networks seamlessly and automatically. at the same time, operators should be able to steer network attachment based on their criteria. although several cross layer mechanisms have been proposed in recent years, only the media independent handover (mih) services framework has advanced in any of the established standardization bodies. this paper presents a blueprint for a gnu/linux implementation of ieee 802.21. we review the salient points of the standard, introduce our software implementation architecture, detail information gathering in gnu/linux, and show how our prototype implementation can be used in practice. in contrast with prior published work, this paper presents a real ieee 802.21 implementation, not an abstracted or reduced mih-like framework, tested and empirically evaluated over real heterogeneous networks.
a decision theoretic approach to gaussian sensor networks. we consider the acquisition of measurements from a source, representing a physical phenomenon, by means of sensors deployed at different distances, and measuring random variables that are correlated with the source output. the acquired values are transmitted to a sink, where an estimation of the source has to be constructed, according to a given distortion criterion. in the presence of gaussian random variables and a gaussian vector channel, we are seeking optimum real-time joint source-channel encoder-decoder pairs that achieve a distortion sufficiently close to the theoretically optimal one, under a global power constraint, by activating only a subset of the sensors. the problem is posed in a team decision theoretic framework, and the optimal strategies are approximated by means of neural networks. we compare the solution with the results obtained by heuristically choosing a subset of the sensors on the basis of successive simulations under a fixed topology.
ofdma based multiparty medium access control in wireless ad hoc networks. we present the concurrent transmission or reception multiple access (ctrma) protocol as an example of embracing interference in wireless ad hoc networks, even when each node is endowed with a single half-duplex radio and a single antenna. ctrma uses ofdma to enable each node to either send or receive multiple concurrent transmissions over orthogonal subchannels (groupings of subcarriers). with ctrma, a node transmits multiple transmissions at the same time by negotiating the subchannels over which transmissions take place by using information attained with a channel priority assignment algorithm. ctrma supports dynamic bandwidth selection and enhances channel reuse. we prove the correctness of ctrma and use simulation experiments to illustrate the major performance advantages of ctrma over prior channel access protocols proposed for single-radio single-channel, single-radio multi-channel and multi-radio multi-channel wireless ad hoc networks.
traffic-matching revenue-rate maximization scheduling for downlink ofdma. in this paper, we study the weighted sum rate (w- rate) maximization algorithms with proportional rate fairness (prf) and delay constraints for the downlink orthogonal frequency division multiple access (ofdma) system. first, based on the lagrangian duality optimization tool, we design a weighted sum rate maximization scheme based on instantaneous transmit power and bit error rate (ber) constraints. second, to meet the rate fairness constraint imposed by different users' diverse traffic demands, we design a fast algorithm to search for the optimal weight factors, and implement the traffic-matching duality scheme to achieve the long-term target prf and enhanced revenue rate. third, we provide analytical channel throughput formulas for equal power allocation (epa) and waterfilling (wf) power allocations schemes, and also evaluate the actual throughput taking into account the traffic random arrival process, limited buffer size, and transmission delay deadline. simulation results show that the proposed traffic-matching duality scheme can achieve a significantly higher revenue rate than the fixed weight duality scheme which only tries to maximize the revenue rate but does not match the incoming traffic.
load aware broadcast in mobile ad hoc networks. in a wireless ad hoc network, the main issue of a good broadcast protocol is to attain maximum reachability with minimal packet forwarding. existing protocols address this issue by utilizing the knowledge of up to 2-hop neighbors to approximate an mcds (minimum connected dominating set) via heuristics derived from techniques known as self pruning and dominant pruning. our experiments show that, using these greedy choice heuristics result in a biased load distribution throughout the network. some nodes become heavily loaded and consequently packets through those nodes, whether unicast or broadcast, experience significantly larger delay. contention and collision also increase at some regions, while they are relatively low at other regions. in this paper we address these issues, and propose various methods to evenly distribute the load caused by broadcast packets. our algorithms take various reactive measures to dynamically include less loaded nodes in the forward list, while maintaining total number of packet forwards low. detailed simulation using ns-2 shows fair scheduling of resources and significant improvement in distribution of packet forwarding load, packet delay, latency and overall performance.
on hashing with tweakable ciphers. cryptographic hash functions are often built on block ciphers in order to reduce the security analysis of the hash to that of the cipher, and to minimize the hardware size. well known hash constructs are used in international standards like md5 and sha-1. recently, researchers proposed new modes of operations for hash functions to protect against generic attacks, and it remains open how to base such functions on block ciphers. an attracting and intuitive choice is to combine previous constructions with tweakable block ciphers. we investigate such constructions, and show the surprising result that combining a provably secure mode of operation with a provably secure tweak-able cipher does not guarantee the security of the constructed hash function. in fact, simple attacks can be possible when the interaction between secure components leaves some additional "freedom" to an adversary. our techniques are derived from the principle of slide attacks, which were introduced for attacking block ciphers.
exposure-path prevention in directional sensor networks using sector model based percolation. in wireless sensor networks, most existing works on region coverage mainly concentrate on the omnidirectional sensor based full coverage, which ensures that all points in the sensor-deployed region are covered. in contrast, this paper studies the problem of exposure-path prevention for the region coverage in directional sensor networks. because the exposure paths are prevented as long as no moving objects or phenomena can go through a sensor-deployed region without being detected, exposure-path prevention does not require full coverage, and instead it only needs the partial coverage. towards this end, we apply the percolation theory to solve the exposure path problem for directional sensor networks. in particular, we map the exposure path problem into a sector based percolation model, and then derive the bounds of critical density where directional sensors are deployed according to a 2-dimensional poisson process. also conducted is a set of extensive simulations to validate and evaluate our developed models and schemes.
iris recognition using combination of dual tree rotated complex wavelet and dual tree complex wavelet. the increasing requirement of security due to advances in information technologies, especially e-commerce have led to rapid development of personnel identification /recognition systems based on biometric. a remarkable and important characteristic of the iris is the randomly distributed irregular texture details in all directions. in this paper, the authors have proposed a novel approach of feature extraction of iris image using 2d redundant rotated complex wavelet transform (rcwt) in combination with 2d dual trace complex wavelet transform(dt-cwt) to obtains the features in 12 different directions as against 3 and 6 directions in discrete wavelet transform (dwt) and complex wavelet transform (cwt) respectively. iris features are obtained by computing energies and standard deviation of detailed coefficients in 12 directions. the sub-bands f rcwt are derived from sub-bands of cwt by using the suitable mapping rules. canbera distance is used for matching. the results are obtained using dwt, cwt and combination of cwt and rcwt on ubiris database of 2400 images. the performance measure, zerofar is reduced from 6.3 using dwt to 2.9 using the proposed method. the method is also computationally efficient as compared to gabor filters.
ipsec-based anonymous networking: a working implementation. protecting users' privacy is becoming one of the rising issues for the success of future communications. the internet in particular, with its open architecture, presents several threats to the right of protecting personal and sensitive data. one fundamental building block of privacy-respectful communications is protecting the communication parties identities, or, as it is commonly called within the research community anonymous networks (ans). an an prevents external observers as well as the network to have access to communicating partners identities and addresses. in this paper we propose a novel architecture to realize ans, as an extension to ipsec. after explaining the rationale and discussing possible alternatives, we present a working prototype implementation and its experimental performance comparison with application level solutions.
coopmax: a cooperative mac with randomized distributed space-time coding for an ieee 802.16 network. cooperative communication is a technique that can be employed to meet the increased throughput needs of next-generation wimax systems. in a cooperative scenario, multiple stations can jointly emulate the antenna elements of a multi-input multi-output (mimo) system in a distributed fashion. although distributed space-time coding (dstc) is being considered by the ieee 802.16j/16m standards for spatial diversity gain, it has several inherent drawbacks. these are addressed in the recently invented randomized distributed space-time coding, called r-dstc. in this paper, we present the framework for the r-dstc technique in the emerging relay-assisted wimax network, and develop a cooperative medium access control (mac) layer protocol, called coopmax, for r-dstc deployment in an ieee 802.16 system. our scheme couples the mac layer with the physical (phy) layer for performance optimization. the phy layer yields significant diversity gain, while the mac layer achieves a substantial end-to-end throughput gain. through extensive simulations, we evaluate the performance of coopmax and show that it can generate capacity gains of up to about 77% for an ieee 802.16 network.
efficient gsvd based multi-user mimo linear precoding and antenna selection scheme. we present a multi-user multiple-input multiple-output (mu-mimo) precoding scheme utilizing generalized singular value decomposition (gsvd). our work is motivated by the precoding scheme developed by sadek, tarighat, and sayed that maximizes the signal to leakage and noise ratio (slnr), in which the precoding weight is obtained by the generalized eigenvalue decomposition (gevd). however, the covariance matrix utilized in gevd becomes close to be singular as the signal to noise ratio goes high. to improve the numerical accuracy, a gsvd based algorithm is exploited in this paper and a novel method is derived to compute the precoding weights for multiple users by removing redundant computational loads rather than repeating the gsvd algorithm for each user. in addition, we propose a technique to speed up the gsvd based precoding algorithm by preprocessing using the qr decomposition. finally, to improve the system performance, the antenna selection scheme using gsvd is also proposed which does not require the exhaustive search to choose the active antennas.
distributed power control for interference-limited cooperative relay networks. in this paper, a distributed power control algorithm is proposed for wireless relay networks in interference-limited environments. the objective is to minimize the total transmission power while satisfying the signal-to-interference-plus-noise ratio (sinr) requirements. two forwarding techniques, i.e., decode-and-forward (df) and amplify-and-forward (af), are considered. the proposed algorithm only requires locally measured sinr on the relay nodes (rns) and the destination nodes (dns), based on which each cooperation unit (defined as one source node (sn) and dn pair with the rn associated to it) iteratively updates the transmission power of the sn and the rn by solving a local optimization problem. we prove that the convergence is guaranteed when the parameters adopted in the algorithm are sufficiently large, and then a parameter adjusting method is also designed. simulation results indicate that the proposed algorithm converges fast and leads to only 7% more power consumption than the optimal power allocation in the considered scenarios. it is also shown that even in interference-limited environments, relaying can still improve system performance substantially in terms of outage and power consumption.
performance gain of space-time-frequency concatenated ldpc codes. this paper introduces a stfc-ldpc (space-time-frequency code low density parity check) concatenated coding scheme for high performance mimo (multiple input, multiple output) systems. the coding design and performance evaluation are illustrated for various frequency-selective block fading conditions and compared with a stc-ldpc (space-time code ldpc) concatenated scheme over quasi-static fading conditions. the codes were analyzed and compared in space-selective conditions using various pdps (power-delay profiles) to illustrate the performance gain of this newly proposed coding technique. the proposed stfc-ldpc showed a performance increase compared to the stc-ldpc scheme due to the inherent higher diversity of the stfc and is a suitable coding technique for high performance mimo systems.
joint detection and estimation for cooperative communications in cluster-based networks. this paper considers the joint symbol detection and channel estimation problem for cooperative communications in cluster-based networks. the proposed joint detection and estimation scheme is derived by using the expectation maximization (em) algorithm. in addition, the cooperative communication between the relays and the destination is based on the concept of compress-and-forward (cf) scheme. most importantly, the distribution detection theory is incorporated in developing the joint detection and estimation rules. specifically, each relay makes its decision based on its joint detection and estimation rule and then forwards it to the destination node. the destination node makes a decision by fusing the decisions sent from the relays using its joint detection and estimation rule. in our considered structure, the feedback channels are also allowed from the destination node to all the relays to further improves the performance of cooperative communications. the simulation results show that the performance of cooperative communication can improve significantly by using the fusion technique and the feedback channels.
policy-based security configuration management, application to intrusion detection and prevention. intrusion detection and/or prevention systems (idps) represent an important line of defense against the variety of attacks that can compromise the security and well functioning of an enterprise information system. idpses can be network or host-based and can collaborate in order to provide better detections of malicious traffic. although several idps systems have been proposed, their appropriate configuration and control for effective detection and prevention of attacks has always been far from trivial. another concern is related to the slowing down of system performance when maximum security is applied, hence the need to trade off between security enforcement levels and the performance and usability of an enterprise information system. in this paper we motivate the need for and present a policy-based framework for the configuration and control of the security enforcement mechanisms of an enterprise information system. the approach is based on dynamic adaptation of security measures based on the assessment of system vulnerability and threat prediction and provides several levels of attack containment. as an application, we have implemented a dynamic policy-based adaptation mechanism between the snort signature-based idps and the light weight anomaly-based firecollaborator ids. experiments conducted over the darpa 2000 and 1999 intrusion detection evaluation datasets show the viability of our framework.
mmse-based non-regenerative multicarrier mimo wireless relay communications with direct source-destination link. in this paper we propose non-regenerative multi-carrier multiple-input multiple-output (mimo) relay techniques that minimize the mean-squared error (mse) of the signal wave-form estimation. in particular, we consider the practical scenario where the direct source-destination link can not be neglected and develop an alternating technique to minimize the signal mse. in order to reduce the computational complexity of the alternating algorithm, a suboptimal non-alternating precoding approach is proposed. numerical examples illustrate a significant performance improvement of the proposed algorithms compared with the existing techniques.
interference subtraction with supplementary cooperation in wireless cooperative networks. in wireless networks, the broadcast nature of wireless transmission enables cooperation by sharing the same transmissions with nearby receivers and thus can help improve spatial reuse and boost network throughput along a multi-hop routing. the performance of wireless networks can be further improved if prior information available at the receivers can be utilized to achieve perfect interference subtraction. in this paper, we investigate performance gain on network throughput for wireless cooperative networks by using a simple mud scheme, called overlapped transmission, in which multiple transmissions are allowed only when the information in the interfering signal is known at the receiver. it is shown that the scheme of cooperative transmission with overlapping increases network throughput by 24% compared to that of direct transmission with overlapping. we then propose a new cooperation scheme called supplementary cooperation, which improves the performance gain of direct transmission with overlapping by 42%. analytical results are developed to show that in a general network scenario, supplementary cooperation achieves bit error rate (ber) reduction of 34.87%, compared with the conventional cooperative transmission. furthermore, we proposed a criterion for finding the best cooperative route to achieve maximum network throughput in a general network.
a discrete channel model for capturing memory and soft-decision information: a capacity study. a discrete (binary-input 2q-ary output) communication channel with memory is introduced with the objective to judiciously capture both the statistical memory and the soft-decision information of time-correlated fading channels modulated via binary phase-shift keying and coherently demodulated with an output quantizer of resolution q. it is shown that the discrete channel can be explicitly described in terms of its binary input process and a 2q-ary noise process. it is also shown that the channel is symmetric and admits a simple expression for its capacity when its noise is stationary ergodic. the 2q-ary noise process is next modeled via a generalized version of the recently studied binary queue-based channel (2007) to produce a mathematically tractable stationary ergodic m'th order markovian noise source with 2q + 2 parameters. numerical results indicate that the capacity of the discrete channel with q = 2, 3 is substantially improved over the cases of perfect channel interleaving (which yields an equivalent memoryless channel) and of hard-decision demodulation (q = 1). these results point to potentially large performance gains achievable by designing coding schemes for this discrete channel that exploit both its memory and soft-decision information, as opposed to ignoring either of them.
burst erasure correction capabilities of (n, n-1) convolutional codes. for (n, k, m) systematic polynomial convolutional encoders, there exists an upperbound on the length of a correctable burst of erasures in terms of code parameters. in this paper, we restrict ourselves to the case k = n-1 and provide a necessary and sufficient condition to achieve the upperbound in terms of the encoder coefficients. in addition, for selected values of m, we present explicit (n, n-1, m) systematic polynomial convolutional encoders that achieve the upperbound.
efficiently constructing candidate set for network topology design. network topology seriously affects network cost, path length, distribution of link load, and reliability, for example, so we need to consider these multiple criteria with different units simultaneously when designing network topology. the analytic hierarchy process (ahp) is a way to make a rational decision considering multiple criteria. using ahp, we can reflect the relative importance of each criterion on the evaluation result, so we have applied it to network topology evaluation. when evaluating network topologies using ahp, we need to construct the set of topology candidates prior to the evaluation. however, the time required to construct this set greatly increases as the network size grows. in this paper, we propose to apply a binary partition approach for constructing a topology candidate set with dramatically reduced calculation time. to reduce the calculation time, we introduce an upper limit for the total link length. although the results of ahp are affected by introducing the upper limit of total link length, we show that desirable topologies are still selected in ahp.
intercell interference measured in urban areas. we report on measurements at 2.53 ghz with 20 mhz bandwidth in two triple-sectored urban macro-cell deployments in berlin and dresden, germany. these measurements assist the design of multiuser and cooperative transmission and detection techniques promising to reduce the interference in future cellular systems. we study the geometry factor and the top-n power statistics in the non-cooperative case and compare the results with a commonly used spatial channel model. furthermore we observe that the median delay parameters in a coherent single frequency network deployment are roughly 1.5 times higher than in an isolated cell while the maximum excess delays are similar in both cases. finally we study the correlation of the channel response for different antenna spacings at the base station. when the sector antennas are close together, the correlation is generally high which is also predicted by the channel model, but with spacings of about 20 m the correlation significantly decreases.
per-tone equalizer design and analysis of filtered multitone communication systems over time-varying frequency-selective channels. although orthogonal frequency division multiplexing (ofdm) communication systems that use inverse discrete fourier (idft) for multicarrier modulation and discrete fourier transform (dft) for demodulation are dominantly adopted in the current broadband standards, there have been some reports in recent years that discuss the shortcomings of ofdm in highly mobile and/or multiple access environments. to resolve these problem, a number of authors have proposed a shift from ofdm to filterbank-based multicarrier techniques. this paper is also along the same line. we present a thorough study of filtered multitone (fmt)in time-varying frequency selective channels. we derive close-form equations for the optimum parameters of per tone fractionally spaced equalizers and also signal to interference plus noise ratio (sinr) and use these to evaluate fmt in typical wireless mobile environments.
distributed quality-lifetime maximization in wireless video sensor networks. owing to the availability of low-cost and low-power cmos cameras, wireless video sensor networks (wvsn) has recently become a reality. however video encoding is still a costly process for energy and capacity constrained sensor nodes and its optimal joint control with the communication protocols has a direct impact on the network lifetime. in this paper we propose a distributed quality-lifetime control algorithm where quality is simply measured by the visual signal quality. in order to formulate the quality-lifetime problem, we consider the power-rate-distortion (p-r-d) model of the video encoder together with the rate control, medium access and routing functions of the underlying communication protocol and formulate the problem as a generalized network utility maximization (gnum) problem. then we construct a distributed solution based on duality and proximal point methods with necessary convergence analysis. simulation results support that optimal quality-lifetime control is possible through the proposed distributed algorithm, where the desired point of operation is simply adjusted by the sink via a configuration parameter.
wireless location privacy protection in vehicular ad-hoc networks. advances in mobile networks and positioning technologies have made location information a valuable asset in vehicular ad-hoc networks (vanets). however, the availability of such information must be weighted against the potential for abuse. in this paper, we investigate the problem of alleviating unauthorized tracking of target vehicles by adversaries in vanets. we propose a vehicle density-based location privacy (dlp) scheme which can provide location privacy by utilizing the neighboring vehicle density as a threshold to change the pseudonyms. we derive the delay distribution and the average total delay of a vehicle within a density zone. given the delay information, an adversary may still be available to track the target vehicle by some selection rules. we investigate the effectiveness of dlp based on extensive simulation study. simulation results show that the probability of successful location tracking of a target vehicle by an adversary is inversely proportional to both the traffic arrival rate and the variance of vehicles' speed. our proposed dlp scheme also has a better performance than both mix-zone scheme and amoeba with random silent period.
vertex packing decoding. in this work, we present a new framework for developing decoding algorithms for linear block codes. we define a new graphical model, called configuration graph and show that maximum likelihood (ml) sequence decoding can be performed by finding a maximum vertex packing on a configuration graph. we present examples of low-cost decoding algorithms developed using this graphical model and show that remarkable performance improvements can be achieved especially by combining these algorithms with belief propagation (bp) decoding for low density parity check (ldpc) codes.
improved decision-directed recursive least squares mimo channel tracking. this paper presents a comparative study of different recursive least squares algorithms to track a rayleigh flat fading mimo channel. we investigate the effect of the initialization and training of these algorithms on their performance. we propose a new training scheme which can deliver a lower mean squared estimation error without loss of bandwidth efficiency.
on the interaction between channel coding and hierarchical modulation. classical systems using hierarchical modulation (such as dvb-sh) involve a "high-priority" (hp) and a "low-priority" (lp) bit stream that are separately and independently encoded before being mapped on non-uniformly spaced constellation points, leading to different levels of error protection. however, an inherent drawback of this scheme is the severe performance degradation of the less protected lp stream. in this paper, we propose a concatenated encoding scheme that mixes the two streams in order to make the encoding of the lp stream dependent on the well protected hp stream. consequently, at the receiver side, the reliable information on hp bits provided by the hp decoder is naturally involved in the decoding process of the lp stream and acts as "soft pilots". we have exploited this feature inside a soft decoding mechanism in order to improve the lp decoding performance while keeping the hp decoding performance unchanged. numerical results presented in the case of the dvb-sh standard show that the proposed system outperforms the classical approach in terms of lp bit error rate without a considerable increase in the receiver complexity.
joint transmit and receive analog beamforming in 60 ghz mimo multipath channels. analog beamforming (abf) with one scalar weight per antenna is an attractive technique for low-cost, low-power 60 ghz multi-antenna wireless communication systems. however, the design of the corresponding joint transmit and receive (tx/rx) abf optimization algorithms is still challenging in the case of multipath channels due to the constraint of having only one scalar weight per antenna. in this paper, we aim at maximizing the average signal to noise ratio (snr) at the input of the equalizer and analytically derive close-to-optimal tx/rx scalar weights. we show that the required channel state information (csi) for joint tx/rx abf weights computation is the inner product between all tx/rx channel impulse response pairs. taking the channel length into account, a training-based estimation strategy of this csi is proposed. simulation results carried out in a typical 60 ghz multipath environment show that the proposed scheme outperforms the existing abf schemes in term of ber performances.
a generalised multi-receiver radio network and its decomposition into independent transmitter-receiver pairs: simple feasibility condition and power levels in closed form. we consider a generalised multi-receiver radio network under a quality-of-service (qos) constraint that involves generalised carrier-to-interference ratios. this model includes as special cases many well-known schemes, such as those discussed by yates (jsac, 13(7):1341-1348, 1995). a simple feasibility condition for the qos targets, and a power-vector that yields those targets are given in closed form for the case in which additive noise is negligible and the key functions are homogeneous of degree one. the condition has the simple form, k_i <= q_i, where "i" identifies a terminal, "k_i" its desired qos level, and "q_i" its quality of service when all power levels equal unity. if the feasibility condition is satisfied, the power levels p_i = k_i / q_i yield or exceed the desired levels of quality. the generalised multi-receiver network can be conservatively represented by an equivalent set of independent transmitter-receiver pairs, with q_i equal to the channel gain of the pair that represents "i". macro-diversity and multiple-connection reception are some of the specific models discussed as examples.
distributed and power efficient routing in wireless cooperative networks. most ad hoc mobile devices in wireless networks operate on batteries and power consumption is therefore an important issue for wireless network design. in this paper, we propose and investigate a new distributed cooperative routing algorithm that realizes minimum power transmission for each composed cooperative link, given the link ber (bit error rate) constrained at a certain target level. the key contribution of the proposed scheme is to bring the performance gain of cooperative diversity from the physical layer up to the networking layer. specifically, the proposed algorithm selects the best relays with minimum power consumption in distributed manner, and then forms cooperative links for establishing a route with appropriate error performance from a source to a destination node. analytical results are developed to show that our cooperative transmission strategy (mpsdf) achieves average energy saving of 82.43% compared to direct transmission, and of 21.22% compared to the existing minimum power cooperation strategy. furthermore, the proposed power efficient routing algorithm can also reduce the total power consumption by a couple db compared to existing cooperative routing algorithms. monte-carlo simulation results are also provided for performance evaluation.
using area hierarchy for multi-resolution storage and search in large wireless sensor networks. we consider multi-resolution storage, a technique for providing scalable adaptive data fidelity, necessary for many applications of large wireless sensor networks (wsns). although the previously proposed design of multi-resolution storage, based on quad trees and geographic routing, is conceptually simple, it exhibits inherent problems if applied to real-world wsns. to address these problems, we revisit some of the networking assumptions and propose an alternative design that employs an overlay combining area and landmark hierarchies. simulations and initial experiments with a prototype embedded implementation indicate that our solution can be scalable and can work on real hardware, which motivates further research.
de-registration based s-cscf load balancing in ims core network. ip multimedia subsystem (ims) provides a common control layer over which the services can be easily accessed by fixed and mobile users. in order to guarantee performance to both service providers and end service subscribers, careful management and maintenance within the control layer must be fulfilled. in this paper, we propose a solution that utilizes a controlling entity to track the utilization of hotspot session initiation protocol (sip) server (i.e., s-cscf) and to initiate de-registration procedure so that a sufficient number of subscribers at the overloaded s-cscf are re-associated with the other s-cscf(s) for subsequent session services. the proposed solution redistributes and smoothes the future traffic load over individual s-cscf in an automatic manner. the goodness of the proposal is assessed through simulations using opnet.
a 3-d markov chain queueing model of ieee 802.11 dcf with finite buffer and load. we introduce a 3-dimensional markov chain that integrates the ieee 802.11 dcf contention resolution and queueing processes into one model. important qos measures, delay and loss, plus throughput and queue length, can be obtained for a realistic systems with finite buffer under finite load. we present an efficient method for solving the steady state probabilities of the markov chain. simulations confirm the accuracy of our model, and demonstrate that the model provides new insights into the 802.11 dcf protocol.
performance of dual-hop transmissions with fixed gain relays over generalized-k fading channels. we present the end-to-end performance of dual-hop wireless communication systems with non-regenerative fixed gain relays operating over independent not necessarily identically generalized-k (kg) fading channels. new closed-form expressions are derived for the moments of the end-to-end signal-to-noise ratio (snr), while the corresponding moment-generating function (mgf) is accurately approximated with the aid of padé approximants theory. useful performance criteria are studied; the average end-to-end snr and the amount of fading, which are expressed in closed form, the average bit-error probability for several coherent, noncoherent, and multilevel modulation schemes, and the outage probability, which are both accurately approximated using the well-known mgf approach. furthermore, novel closed-form expression is obtained for the gain of semi-blind relays over kg fading channels. the proposed mathematical analysis is complemented by various performance evaluation results, which demonstrate the accuracy of the theoretical approach.
smoothing plls for qam dynamical phase estimation. this paper presents a near-optimum, low-complexity, fixed-interval smoothing algorithm that approaches the performance of an optimal smoother for the price of two low-complexity sequential estimators (two plls). the proposed smoothing pll (s-pll) algorithm is easy to implement and fits the cramer-rao bounds over a wide range of signal-to-noise ratios. moreover we show that, compared to the conventional forward loop, the proposed scheme allows to have a large gain of several dbs and is able to track frequency offsets.
investigation of h.264 video streaming over an ieee 802.11e edca wireless testbed. although a number of investigations have been conducted using ieee 802.11e enabled networks to stream class differentiated video, very few reports are available based on a real testbed. in our work, we set up a wireless testbed for h.264 video streaming through assigning the partitioned video packets onto the dcf mac layer and different access classes of the edca mac layer. we investigate three assignment schemes: 1) dcf is used and all the traffic is treated equally; 2) video traffic is assigned to each of the access classes in turn; and 3) the packets are assigned according to their importance and the class priority. in addition to the video stream we introduce tcp traffic from three clients in the best effort class. we show that video quality can be improved through properly assigning packets to wireless access classes compared to the standard best effort scheme. importantly, we show, based on our testbed results, that the single class assignment can achieve better performance than the multi-class assignment suggested by other researchers. finally we show that virtual contention between traffic classes at the access point is an important issue to address.
a testbed development framework for cognitive radio networks. cognitive radio networking is a promising approach to fulfill the future's need for intelligent, high-performance communication and improve the efficiency of overall spectrum utilization. testbed evaluation of protocols and algorithms is a must for the development of cognitive radio networks. in this paper, we present an integrated testbed framework for cognitive radio networks. the framework includes necessary components for cognitive radio operations: flexible rf front end, software define signal processing, adaptive mac layer and network layer as well as a cross layer management interface. such a design eases the cross layer configuration and performance optimization of cognitive protocol stack, while retaining the advantage of modularity. we design a testbed for ad-hoc cognitive radio network.
exploiting connections between mimo mmse achievable rate and mimo mutual information. we present an interesting and powerful new framework connecting the achievable sum rate of multiple-input multiple-output (mimo) wireless systems employing linear minimum mean-squared error (mmse) receivers, and the ergodic mimo mutual information. this allows the vast literature on ergodic mimo mutual information to be directly applied to the analysis of mmse receivers. as an example, the framework is particularized to spatially-correlated rayleigh fading to yield new exact closed-form expressions for the achievable sum rate, as well as simplified expressions for high and low signal to noise ratios.
low complexity encoder for generalized quasi-cyclic codes coming from finite geometries. we define generalized quasi-cyclic (gqc) codes as linear codes with nontrivial automorphism groups. therefore, gqc codes, unlike quasi-cyclic codes, can include many important codes such as hermitian and projective geometry (pg) codes; this capability is important in practical applications. further, we propose the echelon canonical form algorithm for computing gröbner bases from their parity check matrices. consequently, by applying gröbner base theory, gqc codes can be systematically encoded and implemented with simple feedback shift registers. our algorithm is based on gaussian elimination and requires a sufficiently small number of finite-field operations, which is related to the third power of code-length. in order to demonstrate our encoder's efficiency, we prove that the number of circuit elements in the encoder architecture is proportional to the code-length for finite geometry (fg) ldpc codes (a class of gqc codes). we show that the hardware complexity of a serial-in-serial-out encoder architecture for fg-ldpc codes is related to the linear order of the code-length; less than 2n adder and 2n memory elements are required to encode a binary codeword of length n.
cryptanalysis of substitution cipher chaining mode (scc). in this paper, we cryptanalyze the substitution cipher chaining mode (scc-128) [3], which uses three keys. the first key is the encryption key, which we were able to recover with about 240 cipher executions and 5 × 28 chosen plaintexts. the second key is responsible of generation two layers of masks, we recovered the first layer with 213 chosen plaintext and 221 cipher executions and our attack to recover the second layer costs only one known sector plaintext and 64 cipher executions. the third key is used to generate the encrypted sector id, we were able to recover the encrypted sector id of a sector with 1 known plaintext and 2 cipher executions for each sector.
a cooperative scheme for dynamic window resizing in p2p live streaming. due to their widespread popularity, peer-to-peer (p2p) live streaming systems have become a great challenge for internet service providers (isps) as they consume huge amount of internet bandwidth. by observing that different users may watch a channel with different window sizes, we propose a cooperative scheme called partial participation scheme (pps) in which different peers request a video stream at different rates based on their window sizes, and a subset of peers viewing the video stream using a small window work as helpers to forward extra data to help other peers using a large window. by reducing streaming rate received by small-window peers, the total amount of consumed bandwidth decreases without sacrificing users' satisfaction. pps includes peer cooperative bandwidth allocation algorithms and neighbor maintenance mechanisms to achieve short resizing delay when a peer changes its window between different sizes. we evaluate the performance of pps via a comprehensive set of metrics generated from extensive simulations. our simulation results show that pps greatly reduces the bandwidth consumption, achieves short resizing delay, and maintains high and stable streaming quality.
radio resource allocation schemes in hybrid mode wireless communication systems. scheduling schemes achieving multiuser diversity gain are suitable to support high rate bursty data services, while orthogonal resource hopping schemes achieving statistical multiplexing gain are suitable to accommodate low/medium rate applications and real-time traffic. hence, a hybrid mode system has been proposed to support both the scheduling and hopping schemes. we propose a distributed radio resource allocation scheme for the hybrid mode system and compare the system performance of the proposed distributed allocation scheme with that of a localized resource allocation scheme for varying the number of users. in addition, scheduling criterion threshold values for the proposed distributed allocation scheme are derived to maintain the proportion of scheduling to hopping modes. the proposed scheme allocates radio resources adaptively according to users' channel states between scheduling and hopping modes and, thus, it significantly increases system capacity as the scheduling criterion threshold value increases.
practical dirty paper coding with nested binary ldgm-ldpc codes. the superior shaping performance of low-density generation matrix (ldgm) codes makes them important in the design of capacity-approaching dirty paper coding (dpc) schemes. one possible ldgm-based dpc scheme is the nested ldgm-ldpc code proposed by wainwright and martinian, which has been shown to be capacity-achieving under optimal encoding and decoding. in this paper, considering the gaussian dpc problem limited to a binary alphabet, we propose practical encoding and decoding algorithms for the nested ldgm-ldpc code utilizing ideas from the fast ldpc encoding algorithm to satisfy the parity constraints, and optimize the degree distributions of the code through density evolution. simulation results show that the proposed scheme can indeed closely approach the alphabet-constrained dpc capacity.
scalable alternatives to virtual output queuing. to avoid head of line blocking in switches, virtual output queues (voqs) are commonly used. however, the number of voqs grows quadratically with the number of ports, making this approach impractical for large switches. in this paper, we propose dynamic switch buffer management (dsbm) to tackle this problem. similar to dbbm [3], it saves memory by reducing the number of buffers. our scheme significantly improves the performance by dynamically assigning the incoming cells to the least occupied buffers.
how scalable could p2p live media streaming system be with the stringent time constraint? the peer-to-peer (p2p) live video streaming system has been demonstrated to have great potential in the public internet; the large-scale deployment of such systems, however, critically relies on how effective they can deal with the high dynamics encountered, in particular during flash crowd. the rationale behind is that the scaling in p2p live video streaming systems is heavily determined by the timing requirement that streaming applications demand. in this paper, we present an analytical and experimental study on the inherent relationship between the time constraint and the system scale. we develop a generic model for p2p live video streaming that focuses on the peer joining process during flash crowd. we first illustrate that the simple notion of "demand vs. supply" model is insufficient in describing the system scale. by computing the peer start-up time distribution, we demonstrate that the scale is affected by several key factors, especially the peer uploading capacity and the initial system size. we further show the scale is essentially bounded by the timing requirement and the system's capability to accommodate flash crowd is subject to a maximum limit.
multi-hop aggregate information efficiency in wireless ad hoc networks. we introduce multi-hop aggregate information efficiency (miea), a comprehensive metric that captures several performance-affecting factors of wireless ad hoc networks in a unified formulation. this metric is then employed to analyze such networks with respect to their spectral efficiencies, network loads, and hopping strategies. the analysis reveals that the hopping strategy that achieves maximum information efficiency is that of multiple short hops with no more than a single packet retransmission allowed at each hop, as opposed to the alternative of fewer long-haul hops with multiple packet retransmissions. the implementation of that preferred strategy withstanding, it is found furthermore that the most efficient networks typically exhibit about 65% of link outage probability, which corroborates similar findings obtained in different network settings and using different metrics. bearing in mind that link outage is a function not only of deterministic parameters such as node density, but also of design parameters such as modulation, our analysis also shows that the modulation scheme that optimizes the aggregate information efficiency is in fact a function of node density. in that respect, our metric and method is shown to be useful to determining the modulation scheme that optimizes the performance of a network with a certain node density.
an snr-assisted crosstalk channel estimation technique. in this paper, we present a new method to estimate the crosstalk channels in vdsl systems, allowing to implement well-known pre-compensation schemes. as opposed to previously presented methods, this estimation only requires minimal changes to the current standard and equipments. it is based on the concept of adding small, controlled, perturbations to the transmitted signal and observing the related changes to the snr at the receiver. it is shown in this paper that, based on a limited amount of snr measurements from the receivers, it is possible to accurately estimate the crosstalk channels, both in amplitude and phase.
analysis of turbo codes over hybrid optical/rf channels. an analysis on the bit error rate performance of turbo codes for hybrid optical/rf channels is presented using the transfer function bounding technique. the optical channel includes the effects of atmospheric turbulence, which is represented using the gamma-gamma model. the effects of various turbulence conditions on the performance of the hybrid link is investigated. the role of the rf link in the hybrid channel is analyzed using the trade-offs between the rf and the optical signal-to-noise ratios.
performance analysis of multi-branch decode-and-forward cooperative diversity networks over nakagami-m fading channels. in this paper, the performances analysis of cooperative-diversity networks using adaptive decode-and-forward (df) relaying over independent non-identical flat nakagami-m fading channels is investigated. we derive closed-form expressions for the error probability, outage probability and average channel capacity, and analyze their dependence on the channel parameters. in adaptive df relaying, among m relays that can participate, only c relays (c ≤ m), with good channels to the source, decode and forward (retransmit) the source information to the destination. then, the destination combines the direct and the indirect signals using maximum ratio combining (mrc) technique. we derive a closed-form expression for the the moment generating function (mgf) of the total signal-to-noise ratio (snr) at the destination node. then, we find a closed-form expression for the probability density function (pdf) of the total snr at the destination. this pdf is used to derive the closed-form expressions of the performance metrics. computer simulations are used to validate our analytical results. results show the significant performance improvement due to the use of the adaptive df cooperative diversity. also, results indicate that increasing the number of relays will not always decrease the outage probability.
reduced-delay interference-aware opportunistic relaying. in this work, we extend low-complexity, slow-fading opportunistic relaying in both noise and interference-limited setups in order to harvest cooperation benefits without sacrificing overall delay. in particular, we show that information can be reliably relayed without delay, at the presence of interference, while harvesting benefits of cooperative diversity due to the opportunistic protocol nature. under interference-aware opportunistic relaying, relays become useful provided that they offer strong paths towards source and destination, while at the same time they are as "isolated" as possible from each other (e.g. when directive antennas are utilized). this work could potentially assist reduced-delay, cooperative relaying applications (e.g. wireless access) with low-complexity receivers.
a tcp-driven mac resource allocation scheme in a wimax network. the paradigm of a traditional wired network protocol stack is a hierarchy of services provided by each individual layer, but the ability of such paradigm to handle an error-prone physical medium is severely compromised in wireless networks. several approaches, including cross-layer techniques, have been developed to address this problem. while much cross-layer research endeavour focused on interactions of the lower layers, in this paper, we present a cross-layer technique that involves the transport and mac layers. in particular, our approach allows the mac layer of a wimax network to be made aware of the network congestion condition perceived by tcp at the transport layer. this cross-layer technique allows the scarce radio resource to be distributed in a more intelligent fashion among the stations in the network. more specifically, our resource allocation scheme at the mac layer adapts to the congestion window sizes passed down from tcp. we have developed analytical and simulation models to understand the dynamics of the proposed technique and quantify the resulting performance gains. our results show that our proposed algorithm delivers a better performance in average end-to-end delay, file download time, and throughput when the traffic intensity of the network is moderate to high.
decentralized control and optimization of networks with qos-constrained services. we consider data networks in which real-time/near real-time applications require not only successful transmission of packets from source to destination, but also specific end-to-end delay bounds, such as voice over ip. although there is a well-developed general theory for control of best-effort packet traffic in data networks (elastic traffic), little is known about decentralized control mechanisms that ensure end-to-end performance bounds (inelastic traffic). in this paper we propose and analyze a simple, distributed and self-stabilizing rate control scheme that uses only end-to-end delay feedback to ensure qos while using the network resources efficiently. in particular, we show that while for short paths (up to two hops long) the proposed scheme guarantees end-to-end delay budgets for all node pairs and also maximizes the total network throughput, when there are long paths in the network the resulting solution, even though still self-stabilizing and qos-compliant, can deviate from the global network throughput. we present numerical results and conclude with a discussion of possible implementations of the proposed scheme in multi-service networks involving a mixture of best-effort and qos-constrained services.
fairness-aware resource allocation in ofdma cooperative relaying network. this paper investigates the resource allocation problem in the downlink of ofdma cooperative relaying networks with one source (base station) and multiple relay and destination nodes. assuming that the base station knows all the instantaneous channel gains of all links, we propose a dynamic joint subchannel and power allocation (spa) scheme whose objective is to maximize the worst user's data rate with the constraint of total transmission power. since the optimal solution to this combinatorial problem is extremely computationally complex, we propose a low-complexity suboptimal algorithm that allocates subchannel and power separately. in the proposed algorithm, subchannels are firstly paired by relay nodes according to their equivalent channel gains and then assigned to a specific user. subsequently, an optimal power distribution algorithm is designed for the proposed subchannel allocation (sa) scheme. the simulation results show that the performance of the proposed algorithm approaches asymptotically to that of the optimal one, and maximal fairness is guaranteed for all users.
power allocation for broadcasting in multiuser ofdm systems with sublinear complexity. it has been shown that adaptive power and rate allocation for multiuser orthogonal frequency multiplexing (ofdm) improves the system performance significantly. in this paper, the resource allocation that aims at minimizing the total transmission power under certain data transmission constraints is considered. first, the power variation for single-user water-filling while changing the subcarrier assignment is derived. based on this, a class of methods for multiuser resource allocation is proposed. the presented methods, consisting of tactical processes, can achieve a good balance of computational complexity and performance. compared to previous works, simulations show that our methods have comparable or better performance and that the computing time for the proposed methods is approximately sublinearly increasing in the number of users k and the number of subcarriers n.
spatial statistics of spectrum usage: from measurements to spectrum models. several measurement studies have found a large amount of underutilized radio spectrum. more flexible regulation employing dynamic spectrum access (dsa) has been proposed as solution to this problem. the analysis of several aspects of dsa systems, e.g., cooperative sensing, requires good spatial models of spectrum usage. however, only very focused models such as propagation or shadowing correlation models exist. in this paper we apply techniques developed by the spatial statistics community to the modelling of spectrum. in more detail, we use random fields and the semivariogram to describe the spatial correlation of spectrum usage.we extract parameters from extensive real-life measurements for multiple wireless technologies. these parameter sets enable other researchers to use the model for different tasks ranging from theoretical to simulation-based studies.
analyzing selfish topology control in multi-radio multi-channel multi-hop wireless networks. typically, topology control is perceived as a per-node transmit power control process that achieves certain network-level objectives. we take an alternative approach of controlling the topology of a network purely by assigning channels to multiple radio interfaces on nodes. specifically, we exploit the synergy between topology control and channel allocation to reduce the overall interference in multi-radio multi-channel wireless ad hoc networks. we formulate channel assignment as a non-cooperative game, with nodes selecting low interference channels while maintaining some degree of network connectivity. this game is shown to be a potential game, which ensures the existence of, and convergence to, a nash equilibrium (ne). next, we evaluate the performance of ne topologies with respect to interference and connectivity objectives. by quantifying the impact of channel availability on interference performance, we illuminate the tradeoff between interference reduction that can be achieved by distributing interference over multiple channels and the cost of having additional channels. finally, we study the spectral occupancy of steady state topologies, and show that despite the non-cooperative behavior, the ne topologies achieve load balancing.
a cooperative vehicular network framework. vehicular ad hoc networks are networks characterized by intermittent connectivity and rapid changes in their topology. this paper addresses car-to-road communications in which vehicles use access points (ap) in a delay tolerant network architecture. results show how the combination of a delay-cooperative arq mechanism reduces packet losses and in conjunction with a carry-and-forward cooperative mechanism improves performance parameters in terms of total file transfer delay and number of ap needed to download files.
the effects of multi-layer traffic on the survivability of ip-over-wdm networks. the survivability of backbone networks to failures is an on-going concern. this paper investigates survivability strategies for ip-over-wdm networks in a multi-layer framework where traffic originates at each layer.we present an optimization-based formulation of performing recovery mechanisms at the bottom layer for both layers of traffic in two cases: with capacity sharing between backup paths of the traffic in two layers and without. we then study and compare spare capacity requirements under multi-layer traffic ratios and the impact of network connectivity. numerical results indicate that, in such a wavelength-based optical network, implementing survivability of all traffic at the bottom layer can be a viable solution with significant advantages.
energy detection spectrum sensing with discontinuous primary user signal. this paper addresses the problem of spectrum sensing for cognitive radio, in the case of a primary signal characterized by a discontinuous channel occupation within the considered sensing window. under such conditions, the performance of two different energy detectors is investigated. the first one (energy average detector) decides whether the channel is free or busy on the basis of the energy sample average; the second one (energy threshold detector) performs a soft estimation of the channel occupation probability by comparing the energy samples with a proper threshold. for both the detectors, an analytical model is derived and validated through simulation, and the optimal decision threshold is found as a function of the primary signal parameters.
secure physical layer key generation schemes: performance and information theoretic limits. there is growing interest in wireless security methods that provide strong or even perfect secrecy by taking advantage of features of the physical propagation channel. in advantage-based methods, high channel quality in an average or opportunistic sense is exploited between two legitimate nodes, such that nonzero secrecy capacity can be achieved. since such methods require bounds on the quality of the eavesdropper channel, they are somewhat impractical. secret key generation based on tracking channel evolution in time division duplex systems is a more attractive option, where two nodes generate secret key bits based on a mutually known random channel. since the eavesdropper channel is typically independent of the legitimate channel, the key can only be broken by brute force attacks, which are difficult when new keys are continuously generated. in this paper, the information theoretic limits of key generation schemes are investigated, based on the level of estimation error, temporal correlation, and dependence of the eavesdropper and legitimate channels. three practical candidate key generation schemes are also considered: channel quantization and channel quantization with guardband.
power allocation for multi-access two-way relaying. we consider a multi-access two-way relay network where multiple pairs of users exchange information with their pre-assigned partners with the assistance of an intermediate relay node. each pair is assumed to have a shared channel which is orthogonal to the channels used by the remaining pairs. we investigate the relay power allocation problem for two-way relaying protocols that allow a variety of forwarding mechanisms, such as decode-and-superposition-forward (dsf), decode-and-xor-forward (dxf), amplify-and-forward (af) and compress-and-forward (cf). different from one-way communications, in two-way relaying, the rates of the two communication directions between a pair of partners constrain each other, and the relay power allocated to one user pair simultaneously affects the rates of both directions. for each relaying scheme, we solve the problem of optimally allocating relay's power among the user pairs such that an arbitrary weighted sum rate of all users is maximized. simulation results are presented to demonstrate performance of optimum relay power allocation, as well as the comparison among different two-way relaying schemes.
analog antenna combining for maximum capacity under ofdm transmissions. in this paper, we study beamforming schemes for a novel mimo transceiver, which performs adaptive signal combining in the radio-frequency domain. assuming perfect channel knowledge at both the transmit and receive sides, we consider the problem of selecting the transmit and receive rf beamformers that maximize the capacity (maxcap criterion) of the system under orthogonal frequency division multiplexing (ofdm) transmissions. this problem is non-convex and has no closed-form solution, therefore the maximum capacity beamformers are found using a gradient search algorithm. furthermore, it is shown in the paper that, for low signal-to-noise ratios (snr), the maxcap criterion is equivalent to maximizing the received snr (maxsnr criterion). however, for moderate and high snrs, the maximum capacity beamformers sacrifice part of the received snr in order to improve the worst subcarriers and, in this way, they increase the overall capacity of the multicarrier channel. finally, by means of numerical examples we show that the maxcap criterion significantly outperforms the maxsnr criterion in terms of bit error rate and outage probability.
deterministic qos provisioning with network calculus based admission control in wdm epon networks. passive optical network (pon) is viewed by many as an attractive solution to the first mile problem. with the rapidly increasing number of users and bandwidth intensive applications, upgrading current pon architecture with the wavelength division multiplexing (wdm) technology has become a natural choice. multiple wdm pon architectures have been proposed, yet to the best of our knowledge none could support deterministic quality of service (qos) so far. in this paper we propose a two-level wdm epon solution which provides two main functions: efficient network scaling with bandwidth sharing at the wavelength level, and deterministic qos provisioning at the epon level. to guarantee deterministic qos for multiple classes, an efficient admission control scheme based on network calculus has been developed in conjunction with the scheduling discipline. we evaluate the performance of our scheme by means of extensive simulations, and show that it could not only provide deterministic qos to bursty traffic but also achieve high utilization of resources.
tfrc-based rate control for real-time video streaming over wireless multi-hop mesh networks. as a tcp-friendly rate control protocol on the basis of tcp reno's throughput equation, tfrc is designed to provide optimal service for unicast multimedia delivery over the wired internet networks. however, when used in wireless environment, it suffers significant performance degradation. most of the current research on this issue only focuses on the tfrc protocol itself, ignoring tightly-coupled relation between the transport layer and other network layers. in this paper, we propose a new approach to address this problem, integrating tfrc with application layer and physical layer to form a holistic design for real-time video streaming over wireless multi-hop mesh networks. the goal of the proposed approach is to achieve the best user-perceived video quality by jointly optimizing system parameters residing in different network layers, including the real-time video coding parameters at the application layer, the packet sending rate at the transport layer, and the modulation and coding scheme at the physical layer. the problem is formulated and solved as to find the optimal combination of parameters to minimize the end-to-end expected video distortion constrained by a given video playback delay. experimental results have validated 2-4db psnr gain achieved by the proposed approach in wireless multi-hop mesh networks.
a training-based iterative detection/channel estimation scheme for large non-orthogonal stbc mimo systems. in this paper, we propose a training-based channel estimation scheme for large non-orthogonal space-time block coded (stbc) mimo systems. the proposed scheme employs a block transmission strategy where an nt×nt pilot matrix is sent (for training purposes) followed by several nt × nt square data stbc matrices, where nt is the number of transmit antennas. at the receiver, we iterate between channel estimation (using an mmse estimator) and detection (using a low-complexity likelihood ascent search (las) detector) till convergence or for a fixed number of iterations. our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed scheme at low complexities. the fact that we could show such good results for large stbcs (e.g., 16×16 stbc from cyclic division algebras) operating at spectral efficiencies in excess of 20 bps/hz (even after accounting for the overheads meant for pilot-based channel estimation and turbo coding) establishes the effectiveness of the proposed scheme.
a robust approach to carrier sense for mimo ad hoc networks. this paper proposes a method to improve the robustness of the carrier sense system for opportunistic mac (omac). this carrier sense method is specific for mimo and the new version here illustrated is robust to noise and interference. network simulations prove that this modified mimo carrier sense correctly estimates whether a new communication would harm other ongoing transmissions for a wide range of system parameters.
channel estimation and performance of mismatched decoding in wireless relay networks. this paper proposes a novel power allocation among the source and relays of wireless relay networks to minimize the mean-square error of the channel estimation when distributed space-time coding (dstc) is applied. both the maximum likelihood (ml) and minimum mean-square error (mmse) estimations are considered. the impact of imperfect channel estimation on the error performance of dstc is also analyzed, where it is proved that the mismatched decoding of dstc is able to achieve the same diversity order as the coherent decoding of dstc. furthermore, when the optimal power allocation obtained in the training phase is applied to the transmission phase, the mismatched decoding is able to achieve the maximum diversity order as the coherent decoding.
an energy-aware routing protocol for ad-hoc networks based on the foraging behavior in ant swarms. routing in ad-hoc networks can consume considerable amount of battery power. however, as the nodes in these networks have limited power, routing is very much energy-constrained. continuous drainage of energy degrades battery performance as well. if a battery is allowed to intermittently remain in an idle state, it recovers some of its lost charge due to the charge recovery effect, which, in turn, results in prolonged battery life. in this paper, we use the ideas of naturally occurring ants' foraging behavior [1] and based on those ideas we design an energy-aware routing protocol, which not only incorporates the effect of power consumption in routing a packet, but also exploits the multi-path transmission properties of ant swarms and, hence, increases the battery life of a node. the efficiency of the protocol with respect to some of the existing ones has been established through simulations.
impact of topology and shadowing on the outage probability of cellular networks. this paper proposes an analytical study of the shadowing impact on the outage probability in cellular radio networks. we establish that the downlink other-cell interference factor, f, which is defined here as the ratio of outer cell received power to the inner cell received power, plays a fundamental role in the outage probability. from f, we are able to derive the outage probability of a mobile station (ms) initiating a new call. taking into account the shadowing, f is expressed as a lognormal random variable. analytical expressions of the interference factor's mean mf and standard deviation sf are provided in this paper. these expressions depend on the topology of the network characterized by a g factor. we show that shadowing increases the outage probability, and using our analytical method, we are able to quantify this impact. however, we establish that the network topology, or correlated received powers, may limit this increase.
capacity allocation for long tailed traffic in packet switching networks. the packet switching techniques are under evolution. the conventional "best effort" approach will no longer be the dominant service. the next generation of ip networks must provide the qos to customers. inadequacy is obvious when the conventional capacity allocation (ca) models are applied to the new ip architecture. in this paper, we propose a ca model that characterizes (1) the service priority scheme, (2) the service preemption scheme, and (3) the non-poisson traffic in which the packets follow long tailed distributions.
a lightweight fast handover authentication scheme in mobile networks. when a mobile node roams in the mobile networks, its access router and routing path keeps changing. hence the mobile node needs to authenticate the new access router and establish a new key for secure communication. to this motivation, this paper proposes a lightweight, efficient and scalable protocol to establish and update the authentication key in the mobile ipv6 networks.
modeling random walk search algorithms in unstructured p2p networks with social information. random walk (rw) has been widely used as a strategy for searching in peer-to-peer networks. the boom of social network applications introduces new impact to the classical algorithms on the internet. in this paper, we model the random walk algorithm in peer-to-peer networks when social information is available. we define the social relationship between two nodes as the knowledge about the resources the other node possesses. we mathematically show that the social information can benefit the searching by extending the existing random walk search model.
multipath distributed data reliability for wireless sensor networks. in this work, we explore and evaluate data reliability in wireless sensor networks (wsns) using a novel approach that promises to increase the net network throughput with greater energy efficiency than prevalent schemes. our results suggest that, under investigated scenarios, proposed approach can achieve reliable communication without fast depleting energy resources of individual sensor nodes. in particular, we propose a framework in which nodes collaborate, in a distributed fashion, to provide robustness against channel induced errors as data traverses the multi-hop network. our scheme builds on two core concepts: partial decoding of incoming packets at intermediate nodes & directed diffusion of interest over the network for selective event based reliable path reinforcement. in addition, we use path diversity with selective budgeting of network energy resources to achieve data reliability. we show that the proposed scheme outperforms conventional error robustness approaches by considerable margin for a given network energy budget. we further discuss energy-distortion tradeoffs that may lead to greater network lifetime along-with maintaining a desired level of throughput. we use iteratively decodable ldpc codes to illustrate efficiency of our scheme.
automated real-time recommendations for iptv. nowadays iptv offers a very wide range of multimedia content. on one side the increasing number of channels improves the chances of each viewer finding relevant content; on the other side it poses serious challenges in the navigation through the program grid. typically, once a program has been selected, the only way to know what is being broadcasted on another one is by switching the channel. this paper proposes, discusses, and shows a prototype implementation of an innovative iptv feature called real-time meta-data (rtmd) for automated recommendations. it provides iptv systems with simple user-specific live event notification based on user profiles and only for subscribed channels. event notifications can be automatically associated in the iptv client with specific class of event reactions (e.g. channel switch) to enhance the iptv user experience. furthermore, rather than merely delivering channel-related information (e.g. a goal in a soccer match), this technology is also designed to provide additional services such as user-to-user or community notifications. in order to assess the feasibility of the approach, a small scale proof-of-concept prototype has been implemented. subsequently, a validation in terms of both integration with existing standards and technical performance has been realized, fulfilling the initial expectations.
avoiding eclipse attacks on kad/kademlia: an identity based approach. kademlia is a distributed hash table widely used in p2p networks that has been applied to commercial and non commercial distribution of files. in this paper the authors review some security issues connected with kademlia and a technique to leverage its security using an external certification service.
introduction of measurement-based estimation of handover attempts for automatic planning of mobile radio networks. the complexity of current mobile radio networks (geran, utran) has raised a demand for automatic planning procedures and a call for self-planning in future systems (lte second phase). however, for any kind of automatism, reliable input data is necessary and, among other things, derivable from measurements of statistical counters collected by the operation and maintenance centre (omc). mobility information is required by planning procedures concerning registration areas, handover (ho) parameters, etc., in particular, and can mainly be derived from ho statistics. for a new network plan, this information has to be estimated. in this paper, an estimation method for ho attempts based on corresponding ho measurements from the network in operation is proposed. the associated model is based on graphs representing the interdependency of cells. the order of neighbourhood is introduced as a weight function for the edges. for appropriate weighting during estimation a general pareto probability density function is determined from ho measurements. the analysis of the estimation performance is carried out by comparing the estimation values with corresponding omc measurement data. both the required network data and the omc measurement data are provided by a real network.
svd-based receiver for downlink mimo mc-cdma systems. in this paper, a new receiver for downlink multicarrier code-division multiple-access (mc-cdma) system is proposed when the channel between the transmitter and each user is multiple-input multiple-output (mimo). the structure of the proposed receiver is based on the singular value decomposition (svd) method. the conventional svd method is able to eliminate the co-space interference (csi) in single user scenario, however, due to multi-channel environment, it is not able to eliminate the co-space interferences caused by the transmitted signals to the other users that is called multiuser interference (mui). by combining the svd and space frequency spreading code, a receiver called total interference cancellation (tic) is developed that completely eliminates both the csi and the mui. the performance of the tic suffers from small singular values of the subchannel matrices. to improve the performance, a symbol-chip level mmse receiver is developed in which joint equalization and beamforming is utilized at chip level when the mmse criterion is employed at symbol level (after despreading). the performance of the proposed receiver is evaluated and compared under different scenarios by computer simulations. the results show that there is no error floor in the bit error rate (ber) performances of the svd based receiver under both criteria in the multiuser environment. compared with the tic criterion, the receiver designed based on the symbol-chip level mmse criterion significantly improves the ber performance.
a link-reliability-based approach to providing qos support for vanets. vehicular ad hoc networks are a promising technology that provides several interesting new functionalities to drivers and passengers. these services are spread through a wide variety of applications, each with specific requirements in terms of latency, jitter and bandwidth, among other metrics. for this reason, it is crucial to provide mechanisms that can be used to offer different levels of communication quality in order to achieve reasonable performance in all services. in this paper, we demonstrate how link reliability may be used to support quality of service policies for any protocol based on unicast packets relay. this article is divided into two parts, the first of which describes how we estimate link reliability and evaluates how these estimations can be used to classify links into different groups with distinct quality. in the second part, this link reliability estimation model is used to group links into queues with different levels of expected transmission success ratios, which can be used to provide different quality levels depending on the requirements of each individual service. we show that the proposed mechanism adds little-to-none overhead to the overall network and provides an effective mean of supporting qos in vanets.
power allocation in wireless relay networks with partial channel state information. amplify-and-forward (af) wireless relay networks in which the source communicates with the relays and destination in the first phase and the relays forward signals to the destination in the second phase over orthogonal and uncorrelated rayleigh fading channels are considered. convex programming is used to obtain optimal and approximately optimal power allocation (opa) schemes to maximize the average signal-to-noise ratios (snrs) at the output of the receiver filters under two different assumptions of partial channel state information (csi). analysis and simulation results demonstrate the superiority of the proposed power allocation schemes over the equal-power allocation scheme. performance comparison to the extreme cases of (i) direct transmission between the source and destination and (ii) having full csi is made to illustrate the gain and loss, respectively, of the proposed schemes. the impact of power allocation between the source and the relays is also investigated by computer simulation.
adaptive resource allocation for multi-destination relay systems based on ofdm modulation. we propose the optimal resource allocation for wireless multi-destination relay systems with orthogonal frequency division multiplexing (ofdm) modulation, which includes sub-channel allocation (sa), subchannel pairing (sp), and joint source-relay power allocation (pa). our work is different in that we consider a practical downlink ofdm based coperative network, where the relay is used to help the source (base station) to communicate with multiple destinations (users) rather than a single destination as assumed in the previous work. simulation results demonstrate that the proposed optimal resource allocation outperforms other resource allocation schemes in terms of the system capacity. this work can be extended to multi-relay multidestination uplink/downlink ofdm relay systems.
public key-based rendezvous infrastructure for secure and flexible private networking. secure private networking over the internet is difficult especially when trying to form a new network with private servers and hosts that belong to different administrative domains. although such form of private network is useful as a closed group communication environment, simply applying existing vpn technologies is not sufficient. not to mention common problems such as nat and firewall traversal, potential collision of private ip addresses among networks makes their interconnection extremely difficult. in addition, access control inside the private network is required in order to prevent inappropriate access to other users' network resources. in this paper, we propose a public key-based rendezvous infrastructure and user-side vpn agents that can instantly interconnect multiple private networks while automatically mediating address collision and enforcing appropriate access control on cross domain communication by utilizing zeroconf technologies. we built the rendezvous infrastructure using dht technologies in order to achieve good scalability and implemented the vpn agent for linux-based embedded devices so that users can run it on their residential gateway or wireless router.
extended kalman filter for oversampled dynamical phase offset estimation. in this paper, we present an application of the extended kalman filter for the on-line estimation of a dynamical carrier phase offset. the novel approach implies deriving the filter in an oversampled scenario in a digital receiver. we consider a brownian phase evolution in a data aided scenario. our numerical results using a boc shaping pulse show that using the oversampled signal for estimating the phase offset we can obtain better performances than using a classical synchronizer.
performance analysis of generalized selection combining for amplify-and-forward cooperative-diversity networks. we consider an amplify-and-forward (af) cooperative-diversity system where a source node communicates with a destination node directly and indirectly (through multiple relays). in this paper, we analyze the system where n multiple relays that have the strongest signal strength at the destination are selected out of m relays and forward their received data from the source node to the destination node. we derive closed-form expressions for the average symbol error probability, the outage probability, the average channel capacity, the average signal-to-noise ratio (snr), the amount of fading, and the snr moments. in particular, closed-form expression for the moment generating function of the snr at the destination node is determined. then, we find a closed-form expression for the probability density function (pdf) of the total snr at the destination. this pdf is used to derive the closed-form expressions of the performance metrics. simulation results are also given to verify the analytical results. results show that increasing n will slightly improves the error performance and degrade the outage probability and average channel capacity. in particular, n = m gives the best performance in terms of error performance and n = 1 (the best relay) gives the best performance in terms of outage probability and average channel capacity.
a new mac protocol with collision resolution for ofdma wireless mesh networks. wireless mesh networks (wmns) are envisaged to be a key enabling technology for next generation wireless networks. the mesh nodes form the backbone connectivity, performing the dual tasks of packet forwarding as well as providing network access to the mesh clients. in this paper we present a new mac protocol based on a star-mesh topology, which is compatible with the ieee 802.16e-2005 orthogonal frequency division multiple access (ofdma) air interface. in this protocol, the same radio resource can be shared by neighboring cells in the wmn and collisions can be reduced in the overlapping areas. in addition, a markov chain model is developed for analyzing this protocol operating in two overlapping cells. with this model, we analyze the performance of the uplink operating in the ofdma mode. this new scheme resolves collisions using subcarrier allocation, thereby eliminating the need for random backoff intervals that increase latency and delay variability. as such, the scheme may be more suited for real-time traffic such as voice and video. the analytical results match very well with the simulation results. we then extend our model to a star-mesh topology with multiple overlapped regions. simulation results show that the capacity can be improved due to the superior ability of our proposed protocol to deal with collisions in the overlapped regions.
modeling human behavior for defense against flash-crowd attacks. flash-crowd attacks are the most vicious form of distributed denial of service (ddos). they flood the victim with service requests generated from numerous bots. attack requests are identical in content to those generated by legitimate, human users, and bots send at a low rate to appear non-aggressive -- these features defeat many existing ddos defenses. we propose defenses against flash-crowd attacks via human behavior modeling, which differentiate ddos bots from human users. current approaches to human-vs-bot differentiation, such as graphical puzzles, are insufficient and annoying to humans, whereas our defenses are highly transparent. we model three aspects of human behavior: a) request dynamics, by learning several chosen features of human interaction dynamics, and detecting bots that exhibit higher aggressiveness in one or more of these features, b) request semantics, by learning transitional probabilities of user requests, and detecting bots that generate valid but low-probability sequences, and c) ability to process visual cues, by embedding into server replies human-invisible objects, which cannot be detected by automated analysis, and flagging users that visit them as bots. we evaluate our defenses' performance on a series of web traffic logs, interlaced with synthetically generated attacks, and conclude that they raise the bar for a successful, sustained attack to botnets whose size is larger than the size observed in 1-5% of ddos attacks today.
trmsim-wsn, trust and reputation models simulator for wireless sensor networks. trust and reputation models research and development for distributed systems such as p2p networks, wireless sensor networks (wsns) or multi-agent systems has arisen and taken importance in the last recent years among the international research community. however it is not always easy to check the correctness and accuracy of a model and even more, to compare it against other trust and reputation models. this paper presents trmsim-wsn, a java-based trust and reputation models simulator aimed to provide an easy way to test a trust and/or reputation model over wsns and to compare it against other models. it allows the user to adjust several parameters such as the percentage of malicious nodes or the possibility of forming a collusion, among many others.
joint synchronization using cyclic property. it is well known that the cyclic property of transmitted signal can be used to achieve joint frame and carrier frequency synchronization, while the uncompensated sampling frequency offset (sfo) would still be a problem. based on the observation that the impact of sfo on the received cyclic block and its replica is equivalent to a relative time shift, a joint synchronization scheme solely based on cyclic property is proposed to achieve frame, sampling frequency and carrier frequency synchronization simultaneously. a two-dimensional sliding-window auto-correlator (2d-swac) is presented to implement the joint synchronization with low complexity. the proposed scheme is suitable for any transmission system with similar cyclic property. meanwhile, it is robust to large sampling and carrier frequency offset and strong channel frequency selectivity, as demonstrated by the analysis and simulations.
estimating statistical eigen-beamforming gains using spatial channel correlation. statistical eigen-beamforming (ebf) is a widely used multiple antenna transmission technique in which one antenna weight is used over potentially a large bandwidth (e.g., all subcarriers in ofdm). with n transmit antennas, the maximum gain for ebf at a receiver is 20 log n decibels over a single antenna transmission (assuming a power unfair comparison where each transmit antenna has a fixed power so the addition of new antennas brings a beamforming gain as well as a total transmit power increase). based on statistical analysis of field data and observations, this gain is nearly achievable with line-of-sight transmissions. while useful for characterizing the benefits of ebf, the statistical analysis does not indicate the realizable gain for a particular location. this paper presents a relationship between the ebf gain, spatial correlation of the channel, and the number of transmit antennas. the conjectured gain is compared to the expected gain based on an analysis of field data. the results of this comparison show that the spatial correlation as defined in this paper can be used to predict the ebf gain accurately for a variety of antenna spacings and polarizations.
efficient detection of bots in subscribers' computers. we investigate how an isp can efficiently detect bots in its subscribers' computers, possibly as a value-added service or to prevent collateral damage to its infrastructure. by causing an isp's email servers and network links to get clogged or blacklisted, bots reduce the quality of service the isp provides to its subscribers. we describe dns flagger, a novel device for isp bot detection, and evaluate its efficiency. dns flagger matches subscribers' dns traffic against ip and dns signatures. in real-time experiments, we found that, on average, major antivirus programs (avs) detected only 59% of freshly caught bots, while dns flagger detected 73.1% or 91% of those bots, respectively on hosts that do not or do also have a major av. there were no false alarms. because its processing involves only a small fraction of all network traffic and can be performed at very high speed, a single dns flagger can handle hundreds of thousands of subscribers.
a performance comparison of recent network simulators. a widespread methodology for performance analysis in the field of communication systems engineering is network simulation. while ns-2 has established itself as virtually the standard network simulation tool, other network simulators have gained more and more attention during the last years. in this paper, we briefly survey new developments in the field of network simulation and conduct a performance comparison study by implementing an identical simulation set-up in five simulators, namely ns-2, omnet++, ns-3, simpy and jist/swans. our results reveal large differences according to both run-time performance and memory usage.
sensitive data requests: do sites ask correctly? to ensure the security of sensitive web content, an organization must use tls and do so correctly. however, little is known about how tls is actually used on the web. in this work, we perform large-scale internet-wide measurements to determine if web sites use tls when needed and when they do, if they use it correctly. we find hundreds of thousands of pages where tls is either not used when it should be or is used improperly, putting sensitive data at risk.
non-regenerative multicarrier mimo relay communications based on minimization of mean-squared error. in this paper we propose non-regenerative multi-carrier multiple-input multiple-output (mimo) relay techniques that minimize the mean-squared error (mse) of the signal wave-form estimation. we establish the closed-form optimal precoding matrices at the source and relay nodes in the absence of the direct source-destination link. interestingly, we show that the proposed precoding matrices jointly convert the multicarrier mimo relay channel into parallel single-input single-output (siso) relay channels. in order to reduce the computational complexity of the optimal algorithm, a suboptimal precoding approach based on an upper-bound of the mse expression is developed. numerical examples illustrate a significant performance improvement of the proposed algorithms over the existing techniques.
clack: a network covert channel based on partial acknowledgment encoding. the ability of setting up a covert channel, which allows any two nodes with internet connections to engage in secretive communication, clearly causes a very serious security concern. a number of recent studies have indeed shown that setting up such covert channels is possible by exploiting the protocol fields in the ip, tcp, or application layer. however, the quality of these covert channels is susceptible to unpredictable network condition and active wardens. in this paper, we propose clack, a new covert channel which encodes covert messages into the tcp acknowledgments (acks). since the message encoding is performed in a tcp data channel, clack is reliable and resilience to adverse network conditions. moreover, clack is very difficult to detect in practice, because the tck acks encoded by clack cannot be easily distinguished from the normal acks. we have implemented and tested clack in a test-bed to validate its correctness.
dynamic channel feedback control for limited-feedback multi-user mimo systems. efficient channel feedback methods are becoming more important in limited-feedback multi-user multiple input multiple output (mu-mimo) systems. we propose a new dynamic channel feedback control (defcon) scheme, which efficiently allocates the limited system resources for channel feedback to appropriate users. the main features of the proposed defcon scheme are as follows. firstly, the channel feedback procedure is composed of two stages: rough channel feedback of all users and additional precise channel feedback of the selected users only. secondly, each selected user is allocated with different amount of resources for additional channel feedback according to its channel status. we mathematically solve the resource allocation problem by proposing a suboptimal method, which utilizes convex optimization technique combined with iterative steepest decent direction search algorithm. numerical results show that zero-forcing beamforming (zfbf) with the proposed defcon scheme considerably outperforms previous limited-feedback mu-mimo schemes such as zfbf with conventional static feedback method and per user unitary beamforming rate control (pu2rc).
low-complexity multisampling multiuser detector for time-hopping uwb systems. multiple access interference (mai) in time hopping (th) ultra-wideband (uwb) systems is known to be non-gaussian. much previous research in th-uwb receiver design has attempted to propose better single-user uwb detectors by introducing more accurate models for the distribution of the mai. recently, it was shown that some of the single-user receivers track closely the optimum achievable single-user performance. although, these receivers are simple, all suffer from error rate floors, and hence limited user capacity. multiuser detection (mud) is considered for offering high performance at the cost of complexity that grows exponentially with the number of users. thought to be too complex for low-cost uwb receivers, mud applied in th-uwb systems benefits from the low duty cycle implying that the number of effective interfering users is small compared to the number of active users. a novel low-complexity multisampling multiuser detector inspired by the inferiority of single-user receivers and the small number of effective interfering users in th-uwb systems is proposed. simulation results show that this detector achieves the performance of the conventional matched filter receiver operating in a single-user system.
new constructions of low-complexity convolutional codes. in this paper new constructions of low trellis complexity convolutional codes are presented. new codes are found by searching into a specific class of time varying convolutional codes, which is shaped by some basic properties and search restrictions. an efficient technique for obtaining minimal trellis modules for the proposed codes is provided. finally, new low complexity convolutional codes of various code rates and memory sizes are tabulated.
prmac: pipelined routing enhanced mac protocol for wireless sensor networks. we describe a novel pipelined routing enhanced mac protocol (prmac) for wireless sensor networks that employs cross layer optimization to realize efficient channel access over multiple hops. the main goal of the protocol is to schedule multi hop transmissions of data packets in a single cycle to reduce end-to-end delay. when nodes are awake, a multi-hop flow is constructed using the information from the routing layer, and data packet transmission is scheduled in the subsequent sleep period. when compared with existing solutions such as rmac, our ns-2 based simulation results show an average 62.2% reduction in end to end packet delivery time for unicast traffic on random networks and up to 200% improvement in delivery ratio on multi-hop chains.
on increasing information availability in gnutella-like peer-to-peer networks. in this paper, we address some of the problems such as dead searches, complexity in the study of network topology and network overloading that are associated with gnutella and gnutella-like peer-to-peer (p2p) networks. we use advanced heuristic parameters with information shuffling as a solution for them. we propose an advancement of gnutella using the above-mentioned schemes. at a panoramic level, our work is founded on the following concepts: (a) crawling the p2p networks to shuffle information, so that the knowledge is distributed over the whole network, and (b) bringing the information within searchable hops of each network. these have been verified on a self-built p2p simulator, named peerns, which works on actual p2p network statistics and is, hence, very close to the actual scenario. the results obtained through simulation affirm that the nodes with extremely large number of dead searches benefit the most and are observed to have a sharp decrease in their dead search count after crawling a small part of the overall network.
on the convergence of ica algorithms with symmetric orthogonalization. independent component analysis (ica) problem is often posed as the maximization/minimization of an objective/ cost function under a unitary constraint, which presumes the prewhitening of the observed mixtures. the parallel adaptive algorithms corresponding to this optimization setting, where all the separators are jointly trained, are typically implemented by a gradient-based update of the separation matrix followed by the so-called symmetrical orthogonalization procedure to impose the unitary constraint. this article addresses the convergence analysis of such algorithms, which has been considered as a difficult task due to the complication caused by the minimum-(frobenius or induced 2-norm) distance mapping step. we first provide a general characterization of the stationary points corresponding to these algorithms. furthermore, we show that fixed point algorithms employing symmetrical orthogonalization are monotonically convergent for convex objective functions. we later generalize this convergence result for nonconvex objective functions. at the last part of the article, we concentrate on the kurtosis objective function as a special case. we provide a new set of critical points based on householder reflection and we also provide the analysis for the minima/maxima/saddle-point classification of these critical points.
nested support vector machines. one-class and cost-sensitive support vector machines (svms) are state-of-the-art machine learning methods for estimating density level sets and solving weighted classification problems, respectively. however, the solutions of these svms do not necessarily produce set estimates that are nested as the parameters controlling the density level or cost-asymmetry are continuously varied. such nesting not only reflects the true sets being estimated, but is also desirable for applications requiring the simultaneous estimation of multiple sets, including clustering, anomaly detection, and ranking. we propose new quadratic programs whose solutions give rise to nested versions of one-class and cost-sensitive svms. furthermore, like conventional svms, the solution paths in our construction are piecewise linear in the control parameters, although here the number of breakpoints is directly controlled by the user. we also describe decomposition algorithms to solve the quadratic programs. these methods are compared to conventional (non-nested) svms on synthetic and benchmark data sets, and are shown to exhibit more stable rankings and decreased sensitivity to parameter settings.
sparse reconstruction by separable approximation. finding sparse approximate solutions to large under-determined linear systems of equations is a common problem in signal/image processing and statistics. basis pursuit, the least absolute shrinkage and selection operator (lasso), wavelet-based deconvolution and reconstruction, and compressed sensing (cs) are a few well-known areas in which problems of this type appear. one standard approach is to minimize an objective function that includes a quadratic (l2) error term added to a sparsity-inducing (usually l1) regularizater. we present an algorithmic framework for the more general problem of minimizing the sum of a smooth convex function and a nonsmooth, possibly nonconvex regularizer. we propose iterative methods in which each step is obtained by solving an optimization subproblem involving a quadratic term with diagonal hessian (i.e., separable in the unknowns) plus the original sparsity-inducing regularizer; our approach is suitable for cases in which this subproblem can be solved much more rapidly than the original problem. under mild conditions (namely convexity of the regularizer), we prove convergence of the proposed iterative algorithm to a minimum of the objective function. in addition to solving the standard l2 -- l1 case, our framework yields efficient solution techniques for other regularizers, such as an l∞ norm and group-separable regularizers. it also generalizes immediately to the case in which the data is complex rather than real. experiments with cs problems show that our approach is competitive with the fastest known methods for the standard l2 -- l1 problem, as well as being efficient on problems with other separable regularization terms.
distributed detection in uwb wireless sensor networks. in this paper, we study distributed detection in ultra-wideband (uwb) wireless sensor networks (wsns) over frequency selective channels. several schemes with different requirements on channel state information (csi) are proposed, analyzed, and compared. we study the error exponent and asymptotic optimality for these schemes under different energy, and time-bandwidth product requirements. our study shows that to achieve a nonzero error exponent, the no-feedback scheme requires large energy and time-bandwidth product but has advantages of no synchronization requirement and no feedback overhead. on the other hand, schemes requiring feedback are suitable for energy and bandwidth limited settings but require quasi-synchronization.
a low-complexity universal scheme for rate-constrained distributed regression using a wireless sensor network. we propose a scheme for rate-constrained distributed nonparametric regression using a wireless sensor network. the scheme is universal across a wide range of sensor noise models, including unbounded and nonadditive noise; it has low complexity, requiring simple operations such as uniform scalar quantization with dither and message passing between neighboring nodes in the network, and attains minimax optimality for regression functions in common smoothness classes. we present theoretical results on the tradeoff between the compression rate, communication complexity of encoding, and the mse and demonstrate empirical performance of the scheme using simulations.
efficient computation of the binary vector that maximizes a rank-deficient quadratic form. the maximization of a full-rank quadratic form over the binary alphabet can be performed through exponential-complexity exhaustive search. however, if the rank of the form is not a function of the problem size, then it can be maximized in polynomial time. by introducing auxiliary spherical coordinates, we show that the rank-deficient quadratic-form maximization problem is converted into a double maximization of a linear form over a multidimensional continuous set, the multidimensional set is partitioned into a polynomial-size set of regions which are associated with distinct candidate binary vectors, and the optimal binary vector belongs to the polynomial-size set of candidate vectors. thus, the size of the candidate set is reduced from exponential to polynomial. we also develop an algorithm that constructs the polynomial-size candidate set in polynomial time and show that it is fully parallelizable and rank-scalable. finally, we demonstrate the efficiency of the proposed algorithm in the context of adaptive spreading code design.
a sub goal seeking approach for reactive navigation in complex unknown environments. reactive-based approaches are widely used in autonomous navigation. however, in complex unknown environments, pure reactive-based navigation still poses a few challenges since it can be easily trapped by a local minimum and may produce some extra manoeuvres. this paper presents the design of a reactive-based approach for navigation in complex and unknown environments called sub goal seeking, in which depth point maps of the environment are analysed to extract free spaces around the robot. these spaces are then evaluated the one that is most likely to lead to the final goal is chosen as a sub goal. the robot then drives towards these sub goals, instead of the final goal until it is visible. by analysing the environmental structure, dead-ends within robot sensory range are able to be detected thus reducing the chance of being trapped and also reducing unnecessary manoeuvres. this paper also evaluates the performance of the sub goal seeking approach using three criteria, goal achievable ability, safety and maneuvering through extensive simulation and real mobile robot experiments.
collision free path-planning for cable-driven parallel robots. in this study, a path-planning method that has been developed for serial manipulators is adapted to cable-driven robots. the proposed method has two modes. the first one is active when the robot is far from an obstacle. in this mode, the robot moves toward the goal on a straight line. the second mode is active when the robot is near an obstacle. during this mode, the robot finds the best way to avoid the obstacle. moreover, an algorithm is presented to detect the collision between the robot and the obstacle. a similar algorithm is also presented to avoid the collision of the cables with an obstacle. some simulation results are shown, which are then validated experimentally using a built 4-cable-driven parallel manipulator. although the path obtained between the initial and final poses may not be the shortest possible one, it guarantees finding a path, when it exists, no matter how cluttered the environment is.
covariance recovery from a square root information matrix for data association. data association is one of the core problems of simultaneous localization and mapping (slam), and it requires knowledge about the uncertainties of the estimation problem in the form of marginal covariances. however, it is often difficult to access these quantities without calculating the full and dense covariance matrix, which is prohibitively expensive. we present a dynamic programming algorithm for efficient recovery of the marginal covariances needed for data association. as input we use a square root information matrix as maintained by our incremental smoothing and mapping (isam) algorithm. the contributions beyond our previous work are an improved algorithm for recovering the marginal covariances and a more thorough treatment of data association, now including the joint compatibility branch and bound (jcbb) algorithm. we further show how to make information theoretic decisions about measurements before actually taking the measurement, therefore allowing a reduction in estimation complexity by omitting uninformative measurements. we evaluate our work on simulated and real-world data.
consistent triangulation for mobile robot localization using discontinuous angular measurements. localization is a fundamental operation for the navigation of mobile robots. the standard localization algorithms fuse external measurements of the environment with the odometric evolution of the robot pose to obtain its optimal estimation. in this work, we present a different approach to determine the pose using angular measurements discontinuously obtained in time. the presented method is based on an extended kalman filter (ekf) with a state-vector composed of the external angular measurements. this algorithm keeps track of the angles between actual measurements from robot odometric information. this continuous angular estimation allows the consistent use of the triangulation methods to determine the robot pose at any time during its motion. the article reports experimental results that show the localization accuracy obtained by means of the presented approach. these results are compared to the ones obtained applying the ekf algorithm with the standard pose state-vector. for the experiments, an omnidirectional robotic platform with omnidirectional wheels is used.
efference copies in neural control of dynamic biped walking. in the early 1950s, von holst and mittelstaedt proposed that motor commands copied within the central nervous system (efference copy) help to distinguish 'reafference' activity (afference activity due to self-generated motion) from 'exafference' activity (afference activity due to external stimulus). in addition, an efference copy can be also used to compare it with the actual sensory feedback in order to suppress self-generated sensations. based on these biological findings, we conduct here two experimental studies on our biped ''runbot'' where such principles together with neural forward models are applied to runbot's dynamic locomotion control. the main purpose of this article is to present the modular design of runbot's control architecture and discuss how the inherent dynamic properties of the different modules lead to the required signal processing. we believe that the experimental studies pursued here will sharpen our understanding of how the efference copies influence dynamic locomotion control to the benefit of modern neural control strategies in robots.
motion planning for cooperative unicycle-type mobile robots with limited sensing ranges: a distributed receding horizon approach. this paper presents a decentralized motion planner for a team of nonholonomic mobile robots subject to constraints imposed by sensors and the communication network. the motion planning scheme consists of decentralized receding horizon planners that reside on each vehicle to achieve coordination among flocking agents. the advantage of the proposed algorithm is that each vehicle only requires local knowledge of its neighboring vehicles. the main requirement for designing an optimal conflict-free trajectory in a decentralized way is that each robot does not deviate too far from its presumed trajectory designed without taking the coupling constraints into account. a comparative study between the proposed algorithm and other existing algorithms is provided in order to show the advantages, especially in terms of computing time. finally, experiments are performed on a team of three mobile robots to demonstrate the validity of the proposed approach.
modeling of tracked mobile manipulators with consideration of track-terrain and vehicle-manipulator interactions. this paper presents a systematic method to establish the kinematics model for a tracked mobile manipulator on firm grounds, with consideration of the interactive motions between the tracks and the terrain, as well as those between the tracked vehicle and the onboard manipulator. kinematics analysis is essential for real-time pose estimation and online autonomous navigation of tracked mobile manipulators. furthermore, to improve the effectiveness of motion planning, and to simulate or control tracked mobile manipulators, a reliable kinematics model is required. however, kinematics modeling for a tracked mobile manipulator is complicated by the fact that there are infinite number of contact points between the tracks and the terrain, which makes slippage unavoidable. the track-terrain and vehicle-manipulator interactions make the problem even more complicated as the motion of the onboard manipulator and the centrifugal forces during moderate or high speed motion give rise to transfer of the load distribution, which will affect the longitudinal and lateral tractive forces and the resistance. also, the motion of the mobile platform contributes to the inertial forces of the manipulator, and the track-terrain interactive forces help balance the gravity as well as the manipulation forces. the developed kinematics modeling approach is presented on the basis of a tracked mobile manipulator in our laboratory, but the forward kinematics analysis method, and the track-terrain and vehicle-manipulator interaction analysis algorithm are general, and can be used for any tracked mobile manipulators with little modification. this work lays a solid foundation for autonomous control, online slippage estimation, real-time traction optimization as well as tip-over prediction and prevention of tracked mobile manipulators.
two different approaches to a macroscopic model of a bio-inspired robotic swarm. by compiling macroscopic models we analyze the adaptive behavior in a swarm of autonomous robots generated by a bio-inspired, distributed control algorithm. we developed two macroscopic models by taking two different perspectives: a stock & flow model, which is simple to implement and fast to simulate, and a spatially resolved model based on diffusion processes. these two models were compared concerning their prediction quality and their analytical power: one model allowed easy identification of the major feedback loops governing the swarm behavior. the other model allowed analysis of the expected shapes and positions of observable robot clusters. we found a high correlation in the challenges posed by both modeling techniques and we highlighted the inherent problems of inferring emergent macroscopic rules from a microscopic description of swarm behavior.
recognizing places using spectrally clustered local matches. place recognition is a fundamental perceptual problem at the heart of many basic robot operations, most notably mapping. failures can result from ambiguous sensor readings and environments with similar appearances. in this paper, we describe a robust place recognition algorithm that fuses a number of uncertain local matches into a high-confidence global match. we describe the theoretical basis of the approach and present extensive experimental results from a variety of sensor modalities and environments.
effect of global position information in unknown world exploration - a case study using the teleworkbench. this paper presents empirical results of the effect of the global position information on the performance of the modified local navigation algorithm (mlna) for unknown world exploration. the results show that global position information enables the algorithm to maintain 100% success rate irrespective of initial robot position, movement speed, and environment complexity. most mobile robot systems accrue an odometry error while moving, and hence need to use external sensors to recalibrate their position on an ongoing basis. we deal with position calibration to compensate the odometry error using the global position information provided by the teleworkbench, which is a teleoperated platform and test bed for managing experiments using mini-robots. in this paper we demonstrate how we incorporate the global position information during and after the experiments.
robot learning language - integrating programming and learning for cognitive systems. one central property of cognitive systems is the ability to learn and to improve continually. we present a robot control language that combines programming and learning in order to make learning executable in the normal robot program. the language constructs of our learning language roll rely on the concept of hierarchical hybrid automata to enable a declarative, explicit specification of learning problems. using the example of an autonomous household robot, we point out some instances where learning-and especially continued learning-makes the robot control program more cognitive.
keypoint design and evaluation for place recognition in 2d lidar maps. we address the place recognition problem, which we define as the problem of establishing whether an observed location has been previously seen, and if so, determining the transformation aligning the current observations to an existing map. in the contexts of robot navigation and mapping, place recognition amounts to globally localizing a robot or map segment without being given any prior estimate. an efficient method of solving this problem involves first selecting a set of keypoints in the scene which store an encoding of their local region, and then utilizing a sublinear-time search into a database of keypoints previously generated from the global map to identify places with common features. we present an algorithm to embed arbitrary keypoint descriptors in a reduced-dimension metric space, in order to frame the problem as an efficient nearest neighbor search. given that there are a multitude of possibilities for keypoint design, we propose a general methodology for comparing keypoint location selection heuristics and descriptor models that describe the region around the keypoint. with respect to selecting keypoint locations, we introduce a metric that encodes how likely it is that the keypoint will be found in the presence of noise and occlusions during mapping passes. metrics for keypoint descriptors are used to assess the distinguishability between the distributions of matches and non-matches and the probability the correct match will be found in an approximate k-nearest neighbors search. verification of the test outcomes is done by comparing the various keypoint designs on a kilometers-scale place recognition problem. we apply our design evaluation methodology to three keypoint selection heuristics and six keypoint descriptor models. a full place recognition system is presented, including a series of match verification algorithms which effectively filter out false positives. results from city-scale and long-term mapping problems illustrate our approach for both offline and online slam, map merging, and global localization and demonstrate that our algorithm is able to produce accurate maps over trajectories of hundreds of kilometers.
kinematic design optimization of a parallel ankle rehabilitation robot using modified genetic algorithm. rehabilitation robotics is an evolving area of active research and recently novel mechanisms have been proposed to reinstate complex human movements. parallel robots are of particular interest to researchers since they are rigid and can provide enough load capacity for human joint movements. this paper proposes a soft parallel robot (spr) for ankle joint rehabilitation. kinematic workspace analysis is carried out and the singularity criterion of the spr's jacobian matrix is used to define the feasible workspace. a global conditioning number (gcn) is defined using the jacobian matrix as a performance index for the evaluation of the robot design. an optimization problem is formulated to minimize the gcn using modified genetic algorithm (ga). results from simple ga and modified ga are compared and discussed. as a result of the optimization, an optimal robot design is obtained which has a near unity gcn with almost uniform distribution in the entire feasible workspace of the robot.
tackling the premature convergence problem in monte-carlo localization. monte-carlo localization uses particle filtering to estimate the position of the robot. the method is known to suffer from the loss of potential positions when there is ambiguity present in the environment. since many indoor environments are highly symmetric, this problem of premature convergence is problematic for indoor robot navigation. it is, however, rarely studied in particle filters. we introduce a number of so-called niching methods used in genetic algorithms, and implement them on a particle filter for monte-carlo localization. the experiments show a significant improvement in the diversity maintaining performance of the particle filter.
shared potential fields and their place in a multi-robot co-ordination taxonomy. previously our novel shared potential field (spf) method has been introduced and compared against a non-sharing control in both simulation and laboratory settings. in this paper, extended from a paper presented at the ciras 2008 conference, we compare the spf against an existing type of robot architecture, a hybrid robotic system. the spf method is compared to the traditional potential field method, and it is shown that the spf is less susceptible to the traditional limitations of potential fields. the spf method's position in farinelli's multi-robot taxonomy is also discussed, and it is shown that rather than being placed in one category it encompasses two, corresponding to the two levels of control within the architecture. in experiments, the multi-robot systems are given the task of traversing an unknown environment, in an attempt to locate a target. the metric of performance for this task was the time taken to find the target. experiments show that the hybrid system showed similar performance to the non-sharing control. in contrast, our pessimistic variant of the spf outperformed the hybrid system in the cluttered environment, and the optimistic spf variant outperformed the hybrid system in the sparse environment. we conclude that the spf method reacts more robustly to the dynamic nature of the real world, and so performed significantly better throughout the experimentation.
collision-free control of an omni-directional vehicle. this study addresses the problem of controlling an omni-directional vehicle with both state and control dependent constraints. the task of the vehicle is to attain its desired final position given in the task space. the control constraints resulting from the physical abilities of actuators driving the vehicle wheels are also taken into account during the robot movement. the problem of collision avoidance is solved here based on an exterior penalty function approach which results in smooth vehicle velocities near obstacles. provided that, a solution to the aforementioned vehicle task exists, the lyapunov stability theory is used to derive the control scheme. the numerical simulation results carried out for the omni-directional vehicle operating in both a constraint-free task space and task space including obstacles, illustrate the performance of the proposed controllers.
efficient data association for view based slam using connected dominating sets. loop closing in vision based slam applications is a difficult task. comparing new image data with all previously acquired image data is practically impossible because of the high computational costs. most approaches therefore compare new data with only a subset of the old data, for example by sampling the data over time or over space by using a position estimate. in this paper, we propose a more natural approach, which dynamically determines a subset of images that best describes the complete image data in the space of all previously seen images. the actual problem of finding such a subset is called the ''connected dominating set'' (cds) problem, which is well studied in the field of graph theory. application on large indoor datasets results in approximately the same map using only 13% of the computational resources with respect to comparing with all previous images. also, it outperforms other sampling approaches. the proposed method is particularly beneficial for realistic mapping scenarios including moving objects and persons, motion blur and changing light conditions.
metric-topological maps from laser scans adjusted with incremental tree network optimizer. several adaptations of maximum likelihood approaches to incremental map learning have been proposed recently. in particular, an incremental network optimizer based on stochastic gradient descent provides a fast and easy-to-implement solution to the problem. in this paper, we illustrate two map builders that process laser scans in order to extract the constraint network for the optimization algorithm. the first algorithm builds a map in the form of a collection of scans corresponding to a subset of the poses of a robot moving in the environment. even though such a solution has the advantage of simplicity, it requires careful processing of data associations. after a preliminary selection of pose constraints candidates, a relative pose is computed through standard scan matching techniques. the second map builder stores a hybrid metric-topological representation: the map consists of a graph whose nodes contain local occupancy grid maps and whose edges are labeled with the relative pose between pairs of nodes. each patch map summarizes the information of consecutive raw scans and such a richer representation better solves loop closure. association between pairs of local maps is then performed and tested using correlation-based techniques. our aim is to illustrate the effectiveness of a tree network optimizer integrated with simple methods for data association. experiments reported in the paper show that a compact system integrating the optimizer and one of two versions of the map builder works reasonably well with commonly used benchmarks.
contributions to non-identifier based adaptive control in mechatronics. funnel-control (fc)-an adaptive (time-varying) mimo/siso control strategy-is re-introduced and its applicability introductory for position control of nonlinear, coupled (rigid) robotic systems and for speed control of nonlinear two-mass flexible servo systems is shown. additionally error reference control (erc)-a direct derivative of fc-is established. erc is specially designed with asymmetric boundaries and auxiliary reference, ensuring that the control error evolves within a prespecified tube (a shrinked funnel region, achieving even better tracking performance). fc and hence erc are based on the high-gain stabilizability of minimum-phase systems with relative degree one and known sign of the high-frequency gain. although the plant only needs to be known in structure, both concepts assure prescribed transient behavior without identification and/or parameter estimation. as most industrial applications, also the considered robotic and two-mass flexible servo systems, exhibit relative degrees greater than one, fc and erc cannot directly be applied. therefore a special state feedback is introduced, reducing the relative degree and retaining the minimum-phase property. the additional implementation of a nominal pi-like extension guarantees good disturbance rejection and asymptotic tracking of (constant) velocity and position reference trajectories. simulation results for a 6-dof manutec r3 robot underpin and compare the achievable position control performance of one overall mimo funnel controller for all joints and one siso funnel controller for each joint (6 controllers). for nonlinear two-mass flexible servo systems, measurement results demonstrate the achievable load speed control performance of fc and erc in comparison to optimal lq state feedback.
complementing visual tracking of moving targets by fusion of tactile sensing. robot control in uncertain and dynamic environments can be greatly improved using sensor-based control. vision is a versatile low-cost sensory modality, but low sample rate, high sensor delay and uncertain measurements limit its usability, especially in strongly dynamic environments. vision can be used to estimate a 6-dof pose of an object by model-based pose-estimation methods, but the estimate is typically not accurate along all degrees of freedom. force is a complementary sensory modality allowing accurate measurements of local object shape when a tooltip is in contact with the object. in multimodal sensor fusion, several sensors measuring different modalities are combined together to give a more accurate estimate of the environment. as force and vision are fundamentally different sensory modalities not sharing a common representation, combining the information from these sensors is not straightforward. we show that the fusion of tactile and visual measurements enables to estimate the pose of a moving target at high rate and accuracy. making assumptions of the object shape and carefully modeling the uncertainties of the sensors, the measurements can be fused together in an extended kalman filter. experimental results show greatly improved pose estimates with the proposed sensor fusion.
a comparison of loop closing techniques in monocular slam. loop closure detection systems for monocular slam come in three broad categories: (i) map-to-map, (ii) image-to-image and (iii) image-to-map. in this paper, we have chosen an implementation of each and performed experiments allowing the three approaches to be compared. the sequences used include both indoor and outdoor environments and single and multiple loop trajectories.
energy based control of a hydromechanical system. this contribution deals with an energy based controller design for an under-actuated mechanical system with a hydraulic piston actuator. in particular, the example consists of a single acting piston actuator and a rigid mass between two springs. for the resulting system a static feedback control is designed based on energy consideration. since the control algorithm requires the velocities, which are not measurable in this application, it is extended by a reduced observer. in addition, the stability of the desired equilibrium of the closed loop system is proven and the results are illustrated by simulation.
global indoor self-localization based on the ambient magnetic field. there is evidence that animals utilize local anomalities of earth's magnetic field not just for orientation detection but also for true navigation, i.e., some animals are not only able to detect the direction of earth's magnetic field (compass heading), they are able to derive positional information from local cues arising from the local anomalities of earth's magnetic field. similarly to earth's non-constant magnetic field, the magnetic field inside buildings can be highly non-uniform. the magnetic field fluctuations inside buildings arise from both natural and man-made sources, such as steel and reinforced concrete structures, electric power systems, electric and electronic appliances, and industrial devices. assuming that the anomalities of the magnetic field inside a building are nearly static and they have sufficient local variability, the anomalies provide a unique magnetic fingerprint that can be utilized in global self-localization. based on the evidence presented in this article it can be argued that this hypothesis is valid. in this article, a monte carlo localization (mcl) technique based on the above hypothesis is proposed. the feasibility of the technique is demonstrated by presenting a series of global self-localization experiments conducted in four arbitrarily selected buildings, including a hospital. the experiment setup consists of a mobile robot instrumented with a 3-axis magnetometer and a computer. in addition to global robot self-localization experiments, successful person self-localization experiments were also conducted by using a wireless, wearable magnetometer. the reported experiments suggest that the ambient magnetic field may remain sufficiently stable for longer periods of time giving support for self-localization techniques utilizing the local deviations of the magnetic field.
auto-organized visual perception using distributed camera network. camera networks are complex vision systems difficult to control if the number of sensors is getting higher. with classic approaches, each camera has to be calibrated and synchronized individually. these tasks are often troublesome because of spatial constraints, and mostly due to the amount of information that need to be processed. cameras generally observe overlapping areas, leading to redundant information that are then acquired, transmitted, stored and then processed. we propose in this paper a method to segment, cluster and codify images acquired by cameras of a network. the images are decomposed sequentially into layers where redundant information are discarded. without the need of any calibration operation, each sensor contributes to build a global representation of the entire network environment. the information sent by the network is then represented by a reduced and compact amount of data using a codification process. this framework allows structures to be retrieved and also the topology of the network. it can also provide the localization and trajectories of mobile objects. experiments will present practical results in the case of a network containing 20 cameras observing a common scene.
dynamics analysis of the star parallel manipulator. matrix relations in kinematics and dynamics of the star parallel manipulator are established in this paper. the prototype of the manipulator is a three-degree-of-freedom mechanism, which consists of a system of parallel kinematical chains connecting to a moving platform. knowing the translation motion of the platform, we develop first the inverse kinematics problem and determine the position, velocity and acceleration of each robot's link. further, the inverse dynamics problem is solved using an approach based on the principle of virtual work, but it has been verified the results in the framework of the lagrange equations with their multipliers. recursive formulae offer expressions and graphs for the power requirement comparison of each of three actuators in two computational complexities: complete dynamic model and simplified dynamic model.
active matching for visual tracking. in the feature matching tasks which form an integral part of visual tracking or slam (simultaneous localisation and mapping), there are invariably priors available on the absolute and/or relative image locations of features of interest. usually, these priors are used post-hoc in the process of resolving feature matches and obtaining final scene estimates, via 'first get candidate matches, then resolve' consensus algorithms such as ransac or jcbb. in this paper we show that the dramatically different approach of using priors dynamically to guide a feature by feature matching search can achieve global matching with far fewer image processing operations and lower overall computational cost. essentially, we put image processing into the loop of the search for global consensus. in particular, our approach is able to cope with significant image ambiguity thanks to a dynamic mixture of gaussians treatment. in our fully bayesian algorithm denoted active matching, the choice of the most efficient search action at each step is guided intuitively and rigorously by expected shannon information gain. we demonstrate the algorithm in feature matching as part of a sequential slam system for 3d camera tracking with a range of settings, and give a detailed analysis of performance which leads to performance-enhancing approximations to the full algorithm.
applications of energy based control methods for the inverted pendulum on a cart. this contribution deals with the application of energy based control methods for the inverted pendulum on a cart model. we will present a swing up controller as well as a nonlinear balancing controller with the focus on the implementation on a laboratory model. therefore we recapitulate well-known control concepts from the literature which will be adapted such that they work on a concrete experiment with all the undesirable effects like friction and quantisation.
recent progress and development of the humanoid robot hansaram. this paper presents an overview of the recent progress and development of the humanoid robot, hansaram series, which have been developed in the robot intelligence technology (rit) laboratory, kaist since 2000. the hansaram series have been designed and developed as a small-sized robot for researching walking gate generation, navigation, task planning and hurocup of fira. in particular, the performance of the 7th and 8th versions have been remarkably improved in the aspect of walking pattern generation and task planning. this paper describes the overall design and architecture of recently developed two versions of hansaram along with a developed vision simulator tool and the real-time walking gate generation scheme, modifiable walking pattern generator.
adaptive supervision of moving objects for mobile robotics applications. one of the main tasks of mobile robotics is vision. lighting independence, adaptivity and automated learning are still the main issues when it comes to applications. in this article, we present an image understanding system and its methods targeting automatic, lighting-independent and reliable color-based object recognition under real time conditions. its application test bed is global vision robot soccer (i.e. fira mirosot und robocup small size leagues) but it has many other applications in color-based supervision of moving objects. under typical conditions, it learns the objects of recognition automatically, has zero setup time and tolerates environmental changes during run-time.
workspace analysis of fully restrained cable-driven manipulators. for cable-driven parallel manipulators (cdpms), employing redundant driving cables is necessary to obtain the full manipulation of the moving platform because of the unilateral driving property of the cables. unlike rigid-link manipulators, the workspace of cdpms is always determined and characterized by positive tension status of driving cables. in addition, it has been realized that the tension factor (tf) reflecting the relative tension distribution among the driving cables is an appropriate measure to evaluate the quality of tension restraint for cdpms. however, since redundant cables are employed to drive the moving platform, the tf values are not unique for a particular moving platform pose. therefore, how to determine the workspace and obtain the optimal tf value so as to generate a workspace with optimized performance become the major subjects of this paper. it is shown that the workspace can be generally formed from tension conditions verified by a recursive dimension-reduction approach and that the optimal tf value at every pose can be efficiently determined through a linear optimization approach, although it is essentially a nonlinear optimization problem. computational examples are provided to demonstrate the effectiveness of the proposed algorithms.
automatic abstraction in reinforcement learning using data mining techniques. in this paper, we used data mining techniques for the automatic discovering of useful temporal abstraction in reinforcement learning. this idea was motivated by the ability of data mining algorithms in automatic discovering of structures and patterns, when applied to large data sets. the state transitions and action trajectories of the learning agent are stored as the data sets for data mining techniques. the proposed state clustering algorithms partition the state space to different regions. policies for reaching different parts of the space are separately learned and added to the model in a form of options (macro-actions). the main idea of the proposed action sequence mining is to search for patterns that occur frequently within an agent's accumulated experience. the mined action sequences are also added to the model in a form of options. our experiments with different data sets indicate a significant speedup of the q-learning algorithm using the options discovered by the state clustering and action sequence mining algorithms.
development of complex robotic systems using the behavior-based control architecture ib2c. this paper presents a development methodology for complex robotic systems using the behavior-based control architecture ib2c (integrated behavior-based control). it is shown how architectural principles support several behavior-based mechanisms, e.g. coordination mechanisms, behavior interaction, and hierarchical abstraction. furthermore, design guidelines and structural patterns are presented which support the design and implementation process. the provided analysis tools and visualization techniques help to manage the complexity of large behavior-based networks. finally, application examples are presented and a step by step description of constructing a behavior-based control structure for the outdoor robot ravon is given.
calibration for mobile robots with an invariant jacobian. the kinematics of some mobile robots is described through a strictly invariant jacobian matrix [j]. this is the case for robots with three degrees of freedom and suitable omnidirectional wheels, and that for robots with conventional wheels and differential kinematics. this article proposes a calibration technique for the matrix [j] of such robots. it is based on four accurate configuration measurements associated with particular nominal motions where the generalized velocities maintain a constant proportional relationship. as a consequence, the nominal trajectories are arcs of circumference and may be part of the actual trajectories of the robot. an application example is presented.
optimized obstacle avoidance trajectory generation for a reconfigurable staircase climbing wheelchair. this paper describes the mechanical devices, the control scheme and the trajectory generation of which a new wheelchair prototype capable of climbing staircases is formed. the key feature of the mechanical design is the use of two decoupled mechanisms in each axle, one to negotiate steps, and the other to position the axle with regard to the chair in order to accommodate the overall slope. this design simplifies the control task substantially. kinematic models are necessary to describe the behavior of the system and to control the actuated degrees of freedom of the wheelchair in order to ensure the passenger's comfort. the choice of a good control scheme based on a local and a global trajectory planner simplifies control, decreases power consumption, reduces the time invested in traversing the obstacles and maintains passenger comfort throughout all movements. the paper presented here is the natural continuation of a previous work presented in [r. morales, a. gonzalez, v. feliu, p. pintado, environment adaptation of a new staircase climbing wheelchair, autonomous robots 23 (2007) 275-292]. after studying the time outs in the staircase climbing/descent process due to configuration changes, we started to increase the capabilities of the trajectory planner in order to reduce the time invested in traversing obstacles. the optimization algorithm is only used in the period of time in which configuration changes are being produced. more specifically, we have used the special properties of the mechanical configuration, the kinematic model and the trajectory planner to develop an improvement in the trajectory planning based on complex notation. the new optimized algorithm solves a nonlinear problem in order to discover an auxiliar center of mass route which is free of obstacles, through the work environment of the wheelchair prototype. additional properties of the new optimization algorithm are: (a) the resulting analytical expressions are closed (iterative calculation is not necessary); (b) it is easy to implement in the real prototype and (c) it can be executed in real time. experimental results are reported which show the behavior of the prototype as it climbs a staircase both when using the original trajectory planner and when using the new obstacle avoidance optimization algorithm explained in this paper. the results obtained illustrate a high percentage of time reduction and the maintenance of comfort levels. however, the control prototype becomes more complicated, the power consumption is increased and the comfort level is slightly lower.
multi-robot visual slam using a rao-blackwellized particle filter. this paper describes an approach to solve the simultaneous localization and mapping (slam) problem with a team of cooperative autonomous vehicles. we consider that each robot is equipped with a stereo camera and is able to observe visual landmarks in the environment. the slam approach presented here is feature-based, thus the map is represented by a set of 3d landmarks each one defined by a global position in space and a visual descriptor. the robots move independently along different trajectories and make relative measurements to landmarks in the environment in order to jointly build a common map using a rao-blackwellized particle filter. we show results obtained in a simulated environment that validate the slam approach. the process of observing a visual landmark is simulated in the following way: first, the relative measurement obtained by the robot is corrupted with gaussian noise, using a noise model for a standard stereo camera. second, the visual description of the landmark is altered by noise, simulating the changes in the descriptor which may occur when the robot observes the same landmark under different scales and viewpoints. in addition, the noise in the odometry of the robots also takes values obtained from real robots. we propose an approach to manage data associations in the context of visual features. different experiments have been performed, with variations in the path followed by the robots and the parameters in the particle filter. finally, the results obtained in simulation demonstrate that the approach is suitable for small robot teams.
a realistic benchmark for visual indoor place recognition. an important competence for a mobile robot system is the ability to localize and perform context interpretation. this is required to perform basic navigation and to facilitate local specific services. recent advances in vision have made this modality a viable alternative to the traditional range sensors, and visual place recognition algorithms emerged as a useful and widely applied tool for obtaining information about robot's position. several place recognition methods have been proposed using vision alone or combined with sonar and/or laser. this research calls for standard benchmark datasets for development, evaluation and comparison of solutions. to this end, this paper presents two carefully designed and annotated image databases augmented with an experimental procedure and extensive baseline evaluation. the databases were gathered in an uncontrolled indoor office environment using two mobile robots and a standard camera. the acquisition spanned across a time range of several months and different illumination and weather conditions. thus, the databases are very well suited for evaluating the robustness of algorithms with respect to a broad range of variations, often occurring in real-world settings. we thoroughly assessed the databases with a purely appearance-based place recognition method based on support vector machines and two types of rich visual features (global and local).
classification and characterization of inverse kinematics solutions for anthropomorphic manipulators. topological properties of the kinematics map are exploited to develop a novel method for redundancy parameterization and extremely fast inverse kinematics solutions for 7-dof anthropomorphic manipulators and animation characters. the method consists of generating joint angles vectors (configurations) and determining their associated hand position/orientation (pose) via the known forward kinematics. the generated data are classified into various inverse kinematics solutions manifolds. these manifolds are subsequently segmented so that the redundancy can be parameterized and the solutions can be represented by simple equations whose parameters are stored for rapid online computation. during the online phase, given the desired hand pose, the appropriate stored parameters are retrieved and various inverse kinematics solutions are computed. the online time to provide various solutions is of the order of several microseconds, which allow real-time inverse kinematics evaluations for fast moving animation characters or manipulators.
vision guided manipulation for planetary robotics - position control. manipulation systems for planetary exploration operate under severe restrictions. they need to integrate vision and manipulation to achieve the reliability, safety, and predictability required of expensive systems operating on remote planets. they also must operate on very modest hardware that is shared with many other systems, and must operate without human intervention. typically such systems employ calibrated stereo cameras and calibrated manipulators to achieve precision of the order of one centimeter with respect to instrument placement activities. this paper presents three complementary approaches to vision guided manipulation designed to robustly achieve high precision in manipulation. these approaches are described and compared, both in simulation and on hardware. in situ estimation and adaptation of the manipulator and/or camera models in these methods account for changes in the system configuration, thus ensuring consistent precision for the life of the mission. all the three methods provide several-fold increases in accuracy of manipulator positioning over the standard flight approach.
an adaptive fuzzy sliding mode controller for remotely operated underwater vehicles. sliding mode control is a very attractive control scheme because of its robustness against both structured and unstructured uncertainties as well as external disturbances. in this way, it has been widely employed for the dynamic positioning of remotely operated underwater vehicles. nevertheless, in such situations the discontinuities in the control law must be smoothed out to avoid the undesirable chattering effects. the adoption of properly designed boundary layers has proven effective in completely eliminating chattering, however, leading to an inferior tracking performance. this work describes the development of a dynamic positioning system for remotely operated underwater vehicles. the adopted approach is primarily based on the sliding mode control strategy and enhanced by an adaptive fuzzy algorithm for uncertainty/disturbance compensation. using the lyapunov stability theory and barbalat's lemma, the boundedness and convergence properties of the closed-loop signals are analytically proven. the performance of the proposed control scheme is also evaluated by means of numerical simulations.
a solution to the path planning problem using angle preprocessing. the path planning problem is a common topic for robotics and computational geometry. many important results have been found to this classic problem, some of them based on plane or space tessellation. the new approach we propose in this paper computes a partition of the plane called the polar diagram, using angle properties as criterion of construction. compared to some other plane partitions as voronoi diagrams, this tessellation can be computed much more efficiently for different geometric objects. the polar diagram used as preprocessing can be applied to many geometric problems where the solution can be given by angle processing, such as visibility or path planning problems.
stereo vision specific models for particle filter-based slam. this work addresses the slam problem for stereo vision systems under the unified formulation of particle filter methods. in contrast to most existing approaches to visual slam, the present method does not rely on restrictive smooth camera motion models, but on computing incremental 6-dof pose differences from the image flow through a probabilistic visual odometry method. moreover, our observation model, which considers both the 3d positions and the sift descriptors of the landmarks, avoids explicit data association between the observations and the map by marginalizing the observation likelihood over all the possible associations. we have experimentally validated our research with two experiments in indoor scenarios.
geographical information systems for map based navigation in urban environments. in order to solve most of the existing mobile robotics applications, the robot needs some information about its spatial environment encoded in what it has been commonly called a map. the knowledge contained in such a map, whatever approach is used to obtain it, will mainly be used by the robot to gain the ability to navigate in a given environment. we are describing in this paper, a method that allows a robot or team of robots to navigate in large urban areas for which an existing map in a standard human understandable fashion is available. as detailed maps of most urban areas already exist, it will be assumed that a map of the zone where the robot is supposed to work is given, which has not been constructed using the robot's own sensors. we propose in this paper, the use of an existing geographical information system based map of an urban zone so that a robot or a team of robots can connect to this map and use it for navigation purposes. details of the implemented system architecture as well as a position tracking experiment in a real outdoor environment, a university campus, are provided.
modeling floor-cleaning coverage performances of some domestic mobile robots in a reduced scenario. in this paper, floor-cleaning coverage performances of some domestic mobile robots are measured, analyzed and modeled. results obtained in a reduced scenario show that floor-cleaning coverage is complete in all cases if the path-planning exploration algorithm has some random dependence. additionally, the evolution of the area cleaned by the mobile robot expressed in a distance domain has an exponential shape that can be modeled with a single exponential where the amplitude defines the maximum cleaning-coverage achieved and the time-constant defines the dynamic evolution of the coverage. both parameters are robot dependent and can be estimated if the area of the room is known and then floor-cleaning coverage can be predicted and over-cleaning minimized.
hardness of edge-modification problems. for a graph property p consider the following computational problem. given an input graph g, what is the minimum number of edge modifications (additions and/or deletions) that one has to apply to g in order to turn it into a graph that satisfies p? namely, what is the edit distance @d(g,p) of a graph g from satisfying p? clearly, the computational complexity of such a problem strongly depends on p. for over 30 years this family of computational problems has been studied in several contexts and various algorithms, as well as hardness results, were obtained for specific graph properties. alon, shapira and sudakov studied in [n. alon, a. shapira, b. sudakov, additive approximation for edge-deletion problems, in: proc. of the 46th ieee focs, 2005, 419-428. also: annals of mathematics (in press)] the approximability of the computational problem for the family of monotone graph properties, namely properties that are closed under removal of edges and vertices. they describe an efficient algorithm that achieves an o(n^2) additive approximation to @d(g,p) for any monotone property p, where g is an n-vertex input graph, and show that the problem of achieving an o(n^2^-^@e) additive approximation is np-hard for most monotone properties. the methods in [n. alon, a. shapira, b. sudakov, additive approximation for edge-deletion problems, in: proc. of the 46th ieee focs, 2005, 419-428. also: annals of mathematics (in press)] also provide a polynomial time approximation algorithm which computes @d(g,p)+/-o(n^2) for the broader family of hereditary graph properties (which are closed under removal of vertices). in this work we introduce two approaches for showing that improving upon the additive approximation achieved by this algorithm is np-hard for several sub-families of hereditary properties. in addition, we state a conjecture on the hardness of computing the edit distance from being induced h-free for any forbidden graph h.
a direct proof of the confluence of combinatory strong reduction. i give a proof of the confluence of combinatory strong reduction that does not use the one of @l-calculus. i also give simple and direct proofs of a standardization theorem for this reduction and the strong normalization of simply typed terms.
rank/select on dynamic compressed sequences and applications. operations rank and select over a sequence of symbols have many applications to the design of succinct and compressed data structures managing text collections, structured text, binary relations, trees, graphs, and so on. we are interested in the case where the collections can be updated via insertions and deletions of symbols. two current solutions stand out as the best in the tradeoff of space versus time (when considering all the operations). one solution, by makinen and navarro, achieves compressed space (i.e., nh"0+o(nlog@s) bits) and o(lognlog@s) worst-case time for all the operations, where n is the sequence length, @s is the alphabet size, and h"0 is the zero-order entropy of the sequence. the other solution, by lee and park, achieves o(logn(1+log@sloglogn)) amortized time and uncompressed space, i.e. nlog"2@s+o(n)+o(nlog@s) bits. in this paper we show that the best of both worlds can be achieved. we combine the solutions to obtain nh"0+o(nlog@s) bits of space and o(logn(1+log@sloglogn)) worst-case time for all the operations. apart from the best current solution to the problem, we obtain several byproducts of independent interest applicable to partial sums, text indexes, suffix arrays, the burrows-wheeler transform, and others.
dynamic rank/select structures with applications to run-length encoded texts. given an n-length text over a @s-size alphabet, we propose a framework for dynamic rank/select structures on the text and some of its applications. for a small alphabet with @s@?logn, we propose a two-level structure consisting of a counting scheme and a storing scheme that supports o(logn) worst-case time rank/select operations and o(logn) amortized time insert/delete operations. for a large alphabet with logn
semi-online machine covering for two uniform machines. the machine covering problem deals with partitioning a sequence of jobs among a set of machines, so as to maximize the completion time of the least loaded machine. we study a semi-online variant, where jobs arrive one by one, sorted by non-increasing size. the jobs are to be processed by two uniformly related machines, with a speed ratio of q>=1. each job has to be processed continuously, in a time slot assigned to it on one of the machines. this assignment needs to be performed upon the arrival of the job. the length of the time slot, which is required for a specific job to run on a given machine, is equal to the size of the job divided by the speed of the machine. we give a complete competitive analysis of this problem by providing an algorithm of the best possible competitive ratio for every q>=1. we first give a tight analysis of the performance of a natural greedy algorithm lpt for the problem. to achieve the best possible performance for the semi-online problem, we use a combination of lpt, together with two alternative algorithms which we design. the new algorithms attain the best possible competitive ratios in the two intervals q@?(1,1.5) and q@?(2.4856,1+3), respectively, whereas the greedy algorithm has the best possible competitive ratio for any other q>=1.
on the minimum hitting set of bundles problem. we consider a natural generalization of the classical minimum hitting set problem, the minimum hitting set of bundles problem (mhsb) which is defined as follows. we are given a set e={e"1,e"2,...,e"n} of n elements. each element e"i (i=1,...,n) has a positive cost c"i. a bundleb is a subset of e. we are also given a collection s={s"1,s"2,...,s"m} of m sets of bundles. more precisely, each set s"j (j=1,...,m) is composed of g(j) distinct bundles b"j^1,b"j^2,...,b"j^g^(^j^). a solution to mhsb is a subset e^'@?e such that for every s"j@?s at least one bundle is covered, i.e. b"j^l@?e^' for some l@?{1,2,...,g(j)}. the total cost of the solution, denoted by c(e^'), is @?"{"i"|"e"""i"@?"e"^"'"}c"i. the goal is to find a solution with a minimum total cost. we give a deterministic n(1-(1-1n)^m)-approximation algorithm, where n is the maximum number of bundles per set and m is the maximum number of sets in which an element can appear. this is roughly speaking the best approximation ratio that we can obtain, since by reducing mhsb to the vertex cover problem, it implies that mhsb cannot be approximated within 1.36 when n=2 and n-1-@e when n>=3. it has to be noticed that the application of our algorithm in the case of the mink-sat problem matches the best known approximation ratio.
computational study on planar dominating set problem. recently, there has been significant theoretical progress towards fixed-parameter algorithms for the dominating set problem of planar graphs. it is known that the problem on a planar graph with n vertices and dominating number k can be solved in o(2^o^(^k^)n) time using tree/branch-decomposition based algorithms. in this paper, we report computational results of fomin and thilikos algorithm which uses the branch-decomposition based approach. the computational results show that the algorithm can solve the dominating set problem of large planar graphs in a practical time and memory space for the class of graphs with small branchwidth. for the class of graphs with large branchwidth, the size of instances that can be solved by the algorithm in practice is limited to about one thousand edges due to a memory space bottleneck. the practical performances of the algorithm coincide with the theoretical analysis of the algorithm. the results of this paper suggest that the branch-decomposition based algorithms can be practical for some applications on planar graphs.
the complete inclusion structure of leaf power classes. let k>=2 be an integer and g=(v,e) be a finite simple graph. a tree t is a k-leaf root of g, if v is the set of leaves of t and, for any two distinct x,y@?v, the distance between x and y in t is at most k if and only if xy@?e. we say that g is a k-leaf power if there is a k-leaf root of g. the main result of this paper is that, for all 2@?k
suffix tree characterization of maximal motifs in biological sequences. finding motifs in biological sequences is one of the most intriguing problems for string algorithm designers due to, on the one hand, the numerous applications of this problem in molecular biology and, on the other hand, the challenging aspects of the computational problem. indeed, when dealing with biological sequences it is necessary to work with approximations (that is, to identify fragments that are not necessarily identical, but just similar, according to a given similarity notion), and this complicates the problem. existing algorithms run in time linear with respect to the input size. nevertheless, the output size can be very large due to the approximation (namely exponential in the approximation degree). this often makes the output unreadable, as well as slowing down the inference itself. a high degree of redundancy has been detected in the set of motifs that satisfy traditional requirements, even for exact motifs. moreover, it has been observed many times that only a subset of these motifs, namely the maximal motifs, could be enough to provide the information of all of them. in this paper, we aim at removing such redundancy. we extend some notions of maximality already defined for exact motifs to the case of approximate motifs with hamming distance, and we give a characterization of maximal motifs on the suffix tree. given that this data structure is used by a whole class of motif extraction tools, we show how these tools can be modified to include the maximality requirement without changing the asymptotical complexity.
why greed works for shortest common superstring problem. the shortest common superstring problem (scs) has been extensively studied for its applications in string compression and dna sequence assembly. although the problem is known to be max-snp hard, the simple greedy algorithm performs extremely well in practice. to explain the good performance, previous researchers proved that the greedy algorithm is asymptotically optimal on random instances. unfortunately, the practical instances in dna sequence assembly are very different from the random instances. in this paper we explain the good performance of the greedy algorithm by using the smoothed analysis. we show that, for any given instance i of scs, the average approximation ratio of the greedy algorithm on a small random perturbation of i is 1+o(1). the perturbation defined in the paper is small and naturally represents the mutations of the dna sequence during evolution. due to the existence of the uncertain nucleotides in the output of a dna sequencing machine, we also proposed the shortest common superstring with wildcards problem (scsw). we prove that in the worst case scsw cannot be approximated within the ratio n^1^/^7^-^@e, while the greedy algorithm still has 1+o(1) smoothed approximation ratio.
on the surface area of the (n, k)-star graph. we present an explicit formula for the surface area of the (n,k)-star graph, i.e., the number of nodes at a certain distance from the identity node in the graph, by identifying the unique cycle structures associated with the nodes in the graph, deriving a distance expression in terms of such structures between the identity node of the graph and any other node, and enumerating those cycle structures satisfying the distance restriction. the above surface area derivation process can also be applied to some of the other node symmetric interconnection structures defined on the symmetric group, when the aforementioned distance expression is available.
(r, p)-centroid problems on paths and trees. an instance of the (r,p)-centroid problem is given by an edge and node weighted graph. two competitors, the leader and the follower, are allowed to place p and r facilities, respectively, into the graph. users at the nodes connect to the closest facility. a solution of the (r,p)-centroid problem is a leader placement such that the maximum total weight of the users connecting to any follower placement is as small as possible. we show that the absolute (r,p)-centroid problem is np-hard even on a path which answers a long-standing open question of the complexity of the problem on trees (hakimi, 1990 [10]). moreover, we provide polynomial time algorithms for the discrete (r,p)-centroid on paths and the (1,p)-centroid on trees, and complementary hardness results for more complex graph classes.
meet continuity properties of posets. in this paper we consider a number of properties of posets that are not directed complete: in particular, meet continuous posets, locally meet continuous posets and pi-meet continuous posets are introduced. characterizations of (locally) meet continuous posets are presented. the main results are: (1) a poset is meet continuous iff its lattice of scott closed subsets is a complete heyting algebra; (2) a poset is a meet continuous poset with a lower hereditary scott topology iff its upper topology is contained in its local scott topology and the lattice of all local scott closed sets is a complete heyting algebra; and (3) a poset with a lower hereditary scott topology is meet continuous iff it is locally meet continuous, iff it is pi-meet continuous.
a 3.4713-approximation algorithm for the capacitated multicast tree routing problem. given an underlying communication network represented as an edge-weighted graph g=(v,e), a source node s@?v, a set of destination nodes d@?v, and a capacity k which is a positive integer, the capacitated multicast tree routing problem asks for a minimum cost routing scheme for source s to send data to all destination nodes, under the constraint that in each routing tree at most k destination nodes are allowed to receive the data copies. the cost of the routing scheme is the sum of the costs of all individual routing trees therein. improving on our previous approximation algorithm for the problem, we present a new algorithm which achieves a worst case performance ratio of 2089+7780+54@r, where @r denotes the best known approximation ratio for the steiner minimum tree problem. since @r is about 1.55 at the writing of the paper, the ratio achieved by our new algorithm is less than 3.4713. in comparison, the previously best ratio was 85+54@r~3.5375.
on nfas where all states are final, initial, or both. we examine questions involving nondeterministic finite automata where all states are final, initial, or both initial and final. first, we prove hardness results for the nonuniversality and inequivalence problems for these nfas. next, we characterize the languages accepted. finally, we discuss some state complexity problems involving such automata.
approximate string matching with address bit errors. a string s@?@s^m can be viewed as a set of pairs s={(@s"i,i):i@?{0,...,m-1}}. we consider approximate pattern matching problems arising from the setting where errors are introduced to the location component (i), rather than the more traditional setting, where errors are introduced into the content itself (@s"i). in this paper, we consider the case where bits of i may be erroneously flipped, either in a consistent or transient manner. we formally define the corresponding approximate pattern matching problems, and provide efficient algorithms for their resolution, while introducing some novel techniques.
on locally reversible languages. there exist several works that study the class of reversible languages defined as the union closure of 0-reversible languages, their properties and suitable representations. in this work we define and study the class of locally reversible languages, defined as the union closure of k-reversible languages. we characterize the class and prove that it is a local (positive) variety of formal languages. we also extend the definition of quasi-reversible automata to deal with locally reversible languages and propose a polynomial algorithm to obtain, for any given locally k-reversible language, a quasi-k-reversible automaton.
the complexity of c-words of the form w×w. let p"n(~) denote the number of c^b^@w-words of the form w@?xw with gap n and p"n(k) denote the number of c^~-words of the form w@?xw with length 2k+n and gap n, where n is the length of the word x. [s. brlek, a. ladouceur, a note on differentiable palindromes, theoret. comput. sci. 302 (2003) 167-178] proved that c^~-palindromes are characterized by the left palindromic closure of the prefixes of the well-known kolakoski sequences and revealed an interesting perspective for understanding some of the conjectures. in fact, they found all infinite c^~-palindromes and established p"0(k)=p"1(k)=2 for all k@?n, where n is the set of positive integers. [y.b. huang, about the number of c^~-words of form w@?xw, theoret. comput. sci. 393 (2008) 280-286] obtained p"n(k)=6 for all k@?n and n=2,3,4, and gave all c^b^@w-words of the form w@?xw with gap less than 5, which imply p"n(~)=2 for n=0,1, and p"n(~)=6 for n=2,3,4. in this paper, we prove the following intriguing results: (1) if w@?xw@?c^b^@w and |x|>=7 then the first and last letters of the word x are the same; (2) p"n(~)=14 for n>=5; (3) for every positive integer n, there exists a positive integer h(n) such that for all k@?n, if k>h(n) then p"n(k)=p"5(k) if k is odd and p"n(k)=p"6(k) if k is even, which would help us understand better the complexity of finite c^~-words of the form w@?xw. moreover, we provide all twenty eight c^b^@w-words of the form w@?xw.
optimal movement of mobile sensors for barrier coverage of a planar region. intrusion detection, area coverage and border surveillance are important applications of wireless sensor networks today. they can be (and are being) used to monitor large unprotected areas so as to detect intruders as they cross a border or as they penetrate a protected area. we consider the problem of how to optimally move mobile sensors to the fence (perimeter) of a region delimited by a simple polygon in order to detect intruders from either entering its interior or exiting from it. we discuss several related issues and problems, propose two models, provide algorithms and analyze their optimal mobility behavior.
isolation concepts for clique enumeration: comparison and computational experiments. we do computational studies concerning the enumeration of isolated cliques in graphs. isolation, as recently introduced, measures the degree of connectedness of the cliques to the rest of the graph. isolation helps both in getting faster algorithms for the enumeration of maximal general cliques and in filtering out cliques with special semantics. we compare three isolation concepts and their combination with two enumeration modi for maximal cliques (''isolated maximal'' vs ''maximal isolated''). all studied concepts exhibit the fixed-parameter tractability of the enumeration task with respect to the parameter ''degree of isolation''. we provide a first systematic experimental study of the corresponding enumeration algorithms, using synthetic graphs (in the g"n","m","p model), financial networks, and a music artist similarity network, proposing the enumeration of isolated cliques as a useful instrument in analyzing financial and social networks.
on the longest common parameterized subsequence. the well-known problem of the longest common subsequence (lcs), of two strings of lengths n and m respectively, is o(nm)-time solvable and is a classical distance measure for strings. another well-studied string comparison measure is that of parameterized matching, where two equal-length strings are a parameterized match if there exists a bijection on the alphabets such that one string matches the other under the bijection. all works associated with parameterized pattern matching present polynomial time algorithms. there have been several attempts to accommodate parameterized matching along with other distance measures, as these turn out to be natural problems, e.g., hamming distance, and a bounded version of edit-distance. several algorithms have been proposed for these problems. in this paper we consider the longest common parameterized subsequence problem which combines the lcs measure with parameterized matching. we prove that the problem is np-hard, and then show a couple of approximation algorithms for the problem.
approximation algorithms for orthogonal packing problems for hypercubes. orthogonal packing problems are natural multidimensional generalizations of the classical bin packing problem and knapsack problem and occur in many different settings. the input consists of a set i={r"1,...,r"n} of d-dimensional rectangular items r"i=(a"i","1,...,a"i","d) and a space q. the task is to pack the items in an orthogonal and non-overlapping manner without using rotations into the given space. in the strip packing setting the space q is given by a strip of bounded basis and unlimited height. the objective is to pack all items into a strip of minimal height. in the knapsack packing setting the given space q is a single, usually unit sized bin and the items have associated profits p"i. the goal is to maximize the profit of a selection of items that can be packed into the bin. we mainly focus on orthogonal knapsack packing restricted to hypercubes and our main results are a (5/4+@e)-approximation algorithm for two-dimensional hypercube knapsack packing, also known as square packing, and a (1+1/2^d+@e)-approximation algorithm for d-dimensional hypercube knapsack packing. in addition we consider d-dimensional hypercube strip packing in the case of a bounded ratio between the shortest and longest side of the basis of the strip. we derive an asymptotic polynomial time approximation scheme (aptas) for this problem. finally, we present an algorithm that packs hypercubes with a total profit of at least (1-@e)opt into a large bin (the size of the bin depends on @e). this problem is known as hypercube knapsack packing with large resources. a preliminary version was published in harren [rolf harren, approximating the orthogonal knapsack problem for hypercubes, in: icalp: proc. 33rd international colloquium on automata, languages and programming, 2006, pp. 238-249] but especially for the latter two approximation schemes no details were given due to page limitations.
partitioning graphs into connected parts. the 2-disjoint connected subgraphs problem asks if a given graph has two vertex-disjoint connected subgraphs containing pre-specified sets of vertices. we show that this problem is np-complete even if one of the sets has cardinality 2. the longest path contractibility problem asks for the largest integer ¿ for which an input graph can be contracted to the path p ¿ on ¿ vertices. we show that the computational complexity of the longest path contractibility problem restricted to p ¿-free graphs jumps from being polynomially solvable to being np-hard at ¿= 6, while this jump occurs at ¿= 5 for the 2-disjoint connected subgraphs problem. we also present an exact algorithm that solves the 2-disjoint connected subgraphs problem faster than ${\cal o}^*(2^n)$ for any n-vertex p ¿-free graph. for ¿= 6, its running time is ${\cal o}^*(1.5790^n)$. we modify this algorithm to solve the longest path contractibility problem for p 6-free graphs in ${\cal o}^*(1.5790^n)$ time.
on selecting a maximum volume sub-matrix of a matrix and related problems. given a matrix a@?r^m^x^n (n vectors in m dimensions), we consider the problem of selecting a subset of its columns such that its elements are as linearly independent as possible. this notion turned out to be important in low-rank approximations to matrices and rank revealing qr factorizations which have been investigated in the linear algebra community and can be quantified in a few different ways. in this paper, from a complexity theoretic point of view, we propose four related problems in which we try to find a sub-matrix c@?r^m^x^k of a given matrix a@?r^m^x^n such that (i) @s"m"a"x(c) (the largest singular value of c) is minimum, (ii) @s"m"i"n(c) (the smallest singular value of c) is maximum, (iii) @k(c)=@s"m"a"x(c)/@s"m"i"n(c) (the condition number of c) is minimum, and (iv) the volume of the parallelepiped defined by the column vectors of c is maximum. we establish the np-hardness of these problems and further show that they do not admit ptas. we then study a natural greedy heuristic for the maximum volume problem and show that it has approximation ratio 2^-^o^(^k^l^o^g^k^). our analysis of the greedy heuristic is tight to within a logarithmic factor in the exponent, which we show by explicitly constructing an instance for which the greedy heuristic is 2^-^@w^(^k^) from optimal. when a has unit norm columns, a related problem is to select the maximum number of vectors with a given volume. we show that if the optimal solution selects k columns, then greedy will select @w(k/logk) columns, providing a logk approximation.
protean graphs with a variety of ranking schemes. we introduce a new class of random graph models for complex real-world networks, based on the protean graph model by luczak and pralat. our generalized protean graph models have two distinguishing features. first, they are not growth models, but instead are based on the assumption that a ''steady state'' of large but finite size has been reached. second, the models assume that the vertices are ranked according to a given ranking scheme, and the rank of a vertex determines the probability that that vertex receives a link in a given time step. precisely, the link probability is proportional to the rank raised to the power -@a, where the attachment strength @a is a tunable parameter. we show that the model leads to a power law degree distribution with exponent 1+1/@a for ranking schemes based on a given prestige label, or on the degree of a vertex. we also study a scheme where each vertex receives an initial rank chosen randomly according to a biased distribution. in this case, the degree distribution depends on the distribution of the initial rank. for one particular choice of parameters we obtain a power law with an exponent that depends both on @a and on a parameter determining the initial rank distribution.
automaton semigroups. the concept of an automaton group generalizes easily to semigroups, and the systematic study of this area is beginning. this paper aims to contribute to that study. the basic theory of automaton semigroups is briefly reviewed. various natural semigroups are shown to arise as automaton semigroups. the interaction of certain semigroup constructions with the class of automaton semigroups is studied. semigroups arising from cayley automata are investigated. various open problems and areas for further research are suggested.
a randomized algorithm for determining dominating sets in graphs of maximum degree five. the paper is devoted to demonstrating a randomized algorithm for determining a dominating set in a given graph having a maximum degree of five. the algorithm follows the las vegas technique. furthermore, the concept of a 2-separated collection of subsets of vertices in graphs is used. the suggested algorithm is based on a condition of the upper bound of the cardinality of a local dominating set. if the condition is not satisfied, then the algorithm halts with an appropriate message. otherwise, the algorithm determines the dominating set. the given algorithm is considered a polynomial-time approximation one.
non-strict independence-based program parallelization using sharing and freeness information. the current ubiquity of multi-core processors has brought renewed interest in program parallelization. logic programs allow studying the parallelization of programs with complex, dynamic data structures with (declarative) pointers in a comparatively simple semantic setting. in this context, automatic parallelizers which exploit and-parallelism rely on notions of independence in order to ensure certain efficiency properties. ''non-strict'' independence is a more relaxed notion than the traditional notion of ''strict'' independence which still ensures the relevant efficiency properties and can allow considerable more parallelism. non-strict independence cannot be determined solely at run-time (''a priori'') and thus global analysis is a requirement. however, extracting non-strict independence information from available analyses and domains is non-trivial. this paper provides on one hand an extended presentation of our classic techniques for compile-time detection of non-strict independence based on extracting information from (abstract interpretation-based) analyses using the now well understood and popular sharing+freeness domain. this includes algorithms for combined compile-time/run-time detection which involve special run-time checks for this type of parallelism. in addition, we propose herein novel annotation (parallelization) algorithms, urlp and crlp, which are specially suited to non-strict independence. we also propose new ways of using the sharing+freeness information to optimize how the run-time environments of goals are kept apart during parallel execution. finally, we also describe the implementation of these techniques in our parallelizing compiler and recall some early performance results. we provide as well an extended description of our pictorial representation of sharing and freeness information.
approximating the maximum internal spanning tree problem. given an undirected connected graph g we consider the problem of finding a spanning tree of g which has a maximum number of internal (non-leaf) vertices among all spanning trees of g. this problem, called maximum internal spanning tree problem, is clearly np-hard since it is a generalization of the hamiltonian path problem. from the optimization point of view the maximum internal spanning tree problem is equivalent to the minimum leaf spanning tree problem. however, the two problems have different approximability properties. lu and ravi proved that the latter has no constant factor approximation-unless p = np-, while salamon and wiener gave a linear-time 2-approximation algorithm for the maximum internal spanning tree problem. in this paper, we improve this approximation ratio by giving an o(|v(g)|^4)-time7/4-approximation algorithm for graphs without pendant vertices. our approach is based on the successive execution of local improvement steps. we use a linear programming formulation and a primal-dual technique to prove the approximation ratio. we also investigate the vertex-weighted case, that is to find a spanning tree of a vertex-weighted graph g in which the weight sum of internal vertices is maximal among all spanning trees of g. for this problem we present a (2@d(g)-3)-approximation algorithm, where @d(g) is the maximum vertex-degree of g. a slight modification of this algorithm ensures a 2-approximation whenever the input graph is claw-free. both algorithms run in o(|v(g)|^4) time for graphs with no pendant vertices.
necessary and sufficient conditions for learning with correction queries. we investigate the newly introduced model of learning with correction queries in the context of query learning. we present necessary and sufficient conditions for a class of languages to be inferable within this setting. we also offer a complete picture of how is the model of learning with corrections related with other well-established learning models, like the model of learning in the limit from positive data, or the one of learning with membership queries. as an application, we show that the class of k-reversible languages is learnable with correction queries.
searching for gapped palindromes. we study the problem of finding, in a given word, all maximal gapped palindromes verifying two types of constraints, that we call long-armed and length-constrained palindromes. for each of the two classes, we propose an algorithm that runs in time o(n+s) for a constant-size alphabet, where s is the number of output palindromes. both algorithms can be extended to compute biological gapped palindromes within the same time bound.
parameterized learnability of juntas. we study the parameterized complexity of learning k-juntas and some variations of juntas. we show the hardness of learning k-juntas and subclasses of k-juntas in the pac model by reductions from a w[2]-complete problem. on the other hand, as a consequence of a more general result, we show that k-juntas are exactly learnable with improper equivalence queries and access to a w[p] oracle.
a four-stage algorithm for updating a burrows-wheeler transform. we present a four-stage algorithm that updates the burrows-wheeler transform of a text t, when this text is modified. the burrows-wheeler transform is used by many text compression applications and some self-index data structures. it operates by reordering the letters of a text t to obtain a new text bwt(t) which can be better compressed. even though recent advances are offering this structure new applications, a major bottleneck still exists: bwt(t) has to be entirely reconstructed from scratch whenever t is modified. we study how standard edit operations (insertion, deletion, substitution of a letter or a factor) that transform a text t into t^' impact bwt(t). then we present an algorithm that directly converts bwt(t) into bwt(t^'). based on this algorithm, we also sketch a method for converting the suffix array of t into the suffix array of t^'. we finally show, based on the experiments we conducted, that this algorithm, whose worst-case time complexity is o(|t|log|t|(1+log@s/loglog|t|)), performs really well in practice and replaces advantageously the traditional approach.
the subsequence composition of a string. words that appear as constrained subsequences in a text-string are considered as possible indicators of the host string structure, hence also as a possible means of sequence comparison and classification. the constraint consists of imposing a bound on the number @w of positions in the text that may intervene between any two consecutive characters of a subsequence. a subset of such @w-sequences is then characterized that consists, in intuitive terms, of sequences that could not be enriched with more characters without losing some occurrence in the text. a compact spatial representation is then proposed for these representative sequences, within which a number of parameters can be defined and measured. in the final part of the paper, such parameters are empirically analyzed on a small collection of text-strings endowed with various degrees of structure.
approximating maximum edge 2-coloring in simple graphs via local improvement. we present a polynomial-time approximation algorithm for legally coloring as many edges of a given simple graph as possible using two colors. it achieves an approximation ratio of 2429~0.828.
a combinatorial geometrical approach to two-dimensional robust pattern matching with scaling and rotation. the problem of two-dimensional pattern matching invariant under a given class of admissible transformations f is to find matches of transformed versions f(p) of a pattern p in a given text t, for all f in f. in this paper, pattern matching invariant under compositions of real valued scaling and rotation are investigated. we give a new discretization technique for this class of transformations and prove sharp lower and upper bounds on the number of different possibilities to transform a pattern in this way. subsequently, we present the first efficient pattern matching algorithm invariant under compositions of scaling and rotation. the algorithm works in time o(m^2n^6) for patterns of size m^2 and texts of size n^2. we conclude with an experimental section to support the practical use of our results.
completing codes in a sofic shift. we define a code in a sofic shift as a set of blocks of symbols of the shift such that any block of the shift has at most one decomposition into code words. it is maximal if it is not strictly included in another one. such a code is complete in the sofic shift if any block of the shift occurs within some concatenation of code words. we prove that a maximal code in an irreducible sofic shift is complete in this shift. we give an explicit construction of a regular completion of a regular code in a sofic shift. this extends the well known result of ehrenfeucht and rozenberg to the case of codes in sofic systems. we also give a combinatorial proof of a result concerning the polynomial of a code in a sofic shift.
fixed-parameter algorithms for kemeny rankings. the computation of kemeny rankings is central to many applications in the context of rank aggregation. given a set of permutations (votes) over a set of candidates, one searches for a ''consensus permutation'' that is ''closest'' to the given set of permutations. unfortunately, the problem is np-hard. we provide a broad study of the parameterized complexity for computing optimal kemeny rankings. besides the three obvious parameters ''number of votes'', ''number of candidates'', and solution size (called kemeny score), we consider further structural parameterizations. more specifically, we show that the kemeny score (and a corresponding kemeny ranking) of an election can be computed efficiently whenever the average pairwise distance between two input votes is not too large. in other words, kemeny score is fixed-parameter tractable with respect to the parameter ''average pairwise kendall-tau distance d"a''. we describe a fixed-parameter algorithm with running time 16^@?^d^"^a^@?@?poly. moreover, we extend our studies to the parameters ''maximum range'' and ''average range'' of positions a candidate takes in the input votes. whereas kemeny score remains fixed-parameter tractable with respect to the parameter ''maximum range'', it becomes np-complete in the case of an average range of two. this excludes fixed-parameter tractability with respect to the parameter ''average range'' unless p=np. finally, we extend some of our results to votes with ties and incomplete votes, where in both cases one no longer has permutations as input.
faster entropy-bounded compressed suffix trees. suffix trees are among the most important data structures in stringology, with a number of applications in flourishing areas like bioinformatics. their main problem is space usage, which has triggered much research striving for compressed representations that are still functional. a smaller suffix tree representation could fit in a faster memory, outweighing by far the theoretical slowdown brought by the space reduction. we present a novel compressed suffix tree, which is the first achieving at the same time sublogarithmic complexity for the operations, and space usage that asymptotically goes to zero as the entropy of the text does. the main ideas in our development are compressing the longest common prefix information, totally getting rid of the suffix tree topology, and expressing all the suffix tree operations using range minimum queries and a novel primitive called next/previous smaller value in a sequence. our solutions to those operations are of independent interest.
on the algebraic structure of declarative programming languages. we develop an algebraic framework, logic programming doctrines, for the syntax, proof theory, operational semantics and model theory of horn clause logic programming based on indexed premonoidal categories. our aim is to provide a uniform framework for logic programming and its extensions capable of incorporating constraints, abstract data types, features imported from other programming language paradigms and a mathematical description of the state space in a declarative manner. we define a new way to embed information about data into logic programming derivations by building a sketch-like description of data structures directly into an indexed category of proofs. we give an algebraic axiomatization of bottom-up semantics in this general setting, describing categorical models as fixed points of a continuous operator.
expander properties and the cover time of random intersection graphs. we investigate important combinatorial and algorithmic properties of g"n","m","p random intersection graphs. in particular, we prove that with high probability (a) random intersection graphs are expanders, (b) random walks on such graphs are ''rapidly mixing'' (in particular they mix in logarithmic time) and (c) the cover time of random walks on such graphs is optimal (i.e. it is @q(nlogn)). all results are proved for p very close to the connectivity threshold and for the interesting, non-trivial range where random intersection graphs differ from classical g"n","p random graphs.
masking patterns in sequences: a new class of motif discovery with don't cares. we introduce a new notion of motifs, called masks, that succinctly represents the repeated patterns for an input sequence t of n symbols drawn from an alphabet @s. we show how to build the set of all frequent maximal masks of length l in o(2^ln) time and space in the worst case, using the karp-miller-rosenberg approach. we analytically show that our algorithm performs better than the method based on constant-time enumerating and checking all the potential (|@s|+1)^l candidate patterns in t, after a polynomial-time preprocessing of t. our algorithm is also cache-friendly, attaining o(2^lsort(n)) block transfers, where sort(n) is the cache complexity of sorting n items.
vpspace and a transfer theorem over the complex field. we extend the transfer theorem of [14] to the complex field. that is, we investigate the links between the class vpspace of families of polynomials and the blum-shub-smale model of computation over c. roughly speaking, a family of polynomials is in vpspace if its coefficients can be computed in polynomial space. our main result is that if (uniform, constant-free) vpspace families can be evaluated efficiently, then the class par"c of decision problems that can be solved in parallel polynomial time over the complex field collapses to p"c. as a result, one must first be able to show that there are vpspace families which are hard to evaluate in order to separate p"c from np"c, or even from par"c.
circular sturmian words and hopcroft's algorithm. in order to analyze some extremal cases of hopcroft's algorithm, we investigate the relationships between the combinatorial properties of a circular sturmian word (x) and the run of the algorithm on the cyclic automaton a"x associated to (x). the combinatorial properties of words taken into account make use of sturmian morphisms and give rise to the notion of reduction tree of a circular sturmian word. we prove that the shape of this tree uniquely characterizes the word itself. the properties of the run of hopcroft's algorithm are expressed in terms of the derivation tree of the automaton, which is a tree that represents the refinement process that, in the execution of hopcroft's algorithm, leads to the coarsest congruence of the automaton. we prove that the shape of the reduction tree of a circular sturmian word (x) coincides with that of the derivation tree t(a"x) of the automaton a"x. from this we derive a recursive formula to compute the running time of hopcroft's algorithm on the automaton a"x, expressed in terms of parameters of the reduction tree of (x). as a special application, we obtain the time complexity @q(nlogn) of the algorithm in the case of automata associated to fibonacci words.
on the computational complexity of the languages of general symbolic dynamical systems and beta-shifts. we consider the computational complexity of languages of symbolic dynamical systems. in particular, we study complexity hierarchies and membership of the non-uniform class p/poly. we prove: 1.for every time-constructible, non-decreasing function t(n)=@w(n), there is a symbolic dynamical system with language decidable in deterministic time o(n^2t(n)), but not in deterministic time o(t(n)). 2.for every space-constructible, non-decreasing function s(n)=@w(n), there is a symbolic dynamical system with language decidable in deterministic space o(s(n)), but not in deterministic space o(s(n)). 3.there are symbolic dynamical systems having hard and complete languages under @?"m^l^o^g^s- and @?"m^p-reduction for every complexity class above logspace in the backbone hierarchy (hence, p-complete, np-complete, conp-complete, pspace-complete, and exptime-complete sets). 4.there are decidable languages of symbolic dynamical systems in p/poly for every alphabet of size |@s|>=1. 5.there are decidable languages of symbolic dynamical systems not in p/poly iff the alphabet size is >1. for the particular class of symbolic dynamical systems known as @b-shifts, we prove that: 1.for all real numbers @b>1, the language of the @b-shift is in p/poly. 2.if there exists a real number @b>1 such that the language of the @b-shift is np-hard under @?"t^p-reduction, then the polynomial hierarchy collapses to the second level. as np-hardness under @?"m^p-reduction implies hardness under @?"t^p-reduction, this result implies that it is unlikely that a proof of existence of an np-hard language of a @b-shift will be forthcoming. 3.for every time-constructible, non-decreasing function t(n)>=n, there is a real number 1
interchange rearrangement: the element-cost model. given an input string s and a target string t when s is a permutation of t, the interchange rearrangement problem is to apply on s a sequence of interchanges, such that s is transformed into t. the interchange operation exchanges the position of the two elements on which it is applied. the goal is to transform s into t at the minimum cost possible, referred to as the distance between s and t. the distance can be defined by several cost models that determine the cost of every operation. there are two known models: the unit-cost model and the length-cost model. in this paper, we suggest a natural cost model: the element-cost model. in this model, the cost of an operation is determined by the elements that participate in it. though this model has been studied in other fields, it has never been considered in the context of rearrangement problems. we consider both the special case where all elements in s and t are distinct, referred to as a permutation string, and the general case, referred to as a general string. an efficient optimal algorithm for the permutation string case and efficient approximation algorithms for the general string case, which is np-hard, are presented. the study is broadened to include the transposition rearrangement problem under the element-cost model and under the other known models, in order to provide additional perspective on the new model.
applications of polyhedral computations to the analysis and verification of hardware and software systems. convex polyhedra are the basis for several abstractions used in static analysis and computer-aided verification of complex and sometimes mission-critical systems. for such applications, the identification of an appropriate complexity-precision trade-off is a particularly acute problem, so that the availability of a wide spectrum of alternative solutions is mandatory. we survey the range of applications of polyhedral computations in this area; give an overview of the different classes of polyhedra that may be adopted; outline the main polyhedral operations required by automatic analyzers and verifiers; and look at some possible combinations of polyhedra with other numerical abstractions that have the potential to improve the precision of the analysis. areas where further theoretical investigations can result in important contributions are highlighted.
a push-relabel approximation algorithm for approximating the minimum-degree mst problem and its generalization to matroids. in the minimum-degree minimum spanning tree (mdmst) problem, we are given a graph g, and the goal is to find a minimum spanning tree (mst) t, such that the maximum degree of t is as small as possible. this problem is np-hard and generalizes the hamiltonian path problem. we give an algorithm that outputs an mst of degree at most 2@d"o"p"t" (g)+o(@d"o"p"t" (g)), where @d"o"p"t" (g) denotes the degree of the optimal tree. this result improves on a previous result of fischer [t. fischer, optimizing the degree of minimum weight spanning trees. technical report 14853, dept. of computer science, cornell university, ithaca, ny, 1993] that finds an mst of degree at most b@d"o"p"t" (g)+log"bn, for any b>1. the mdmst problem is a special case of the following problem: given a k-ary hypergraph g=(v,e) and weighted matroid m with e as its ground set, find a minimum-cost basis (mcb) t of m such that the degree of t in g is as small as possible. our algorithm immediately generalizes to this problem, finding an mcb of degree at most k^2@d"o"p"t" (g,m)+o(kk@d"o"p"t" (g,m)). we use the push-relabel framework developed by goldberg [a. v. goldberg, a new max-flow algorithm, technical report mit/lcs/tm-291, massachusetts institute of technology, 1985 (technical report)] for the maximum-flow problem. to our knowledge, this is the first use of the push-relabel technique in an approximation algorithm for an np-hard problem. the mdmst problem is closely connected to the bounded-degree minimum spanning tree (bdmst) problem. given a graph g and degree bound b on its nodes, the bdmst problem is to find a minimum cost spanning tree among the spanning trees with maximum degree b. previous algorithms for this problem by konemann and ravi [j. konemann, r. ravi, a matter of degree: improved approximation algorithms for degree-bounded minimum spanning trees, siam journal on computing 31(6) (2002) 1783-1793; j. konemann, r. ravi, primal-dual meets local search: approximating mst's with nonuniform degree bounds, in: proceedings of the thirty-fifth acm symposium on theory of computing, 2003, pp. 389-395] and by chaudhuri et al. [k. chaudhuri, s. rao, s. riesenfeld, k. talwar, what would edmonds do? augmenting paths and witnesses for bounded degree msts, in: proceedings of approx/random, 2005, pp. 26-39] incur a near-logarithmic additive error in the degree. we give the first bdmst algorithm that approximates both the degree and the cost to within a constant factor of the optimum. these results generalize to the case of nonuniform degree bounds.
scheduling with families of jobs and delivery coordination under job availability. we consider in this paper the scheduling of families of jobs in which both processing and delivery are coordinated together. only one vehicle is available to deliver the jobs to specified customers. the jobs can be processed together to form processing batches on the machine and setups of batches are required when the machine is changing from one family to another. jobs from different families cannot be transported together by the vehicle. the objective is to minimize the time when the vehicle finishes delivering the last delivery batch to its customer and returns to the machine. we propose an o(nlogn)-time optimal algorithm for the scheduling problem under the group technology assumption. for the scheduling problem without the group technology assumption, we show that the problem is np-hard and give an o(f^2n^f)-time dynamic programming algorithm, where n is the number of jobs, and f is the number of families; we also provide a heuristic algorithm with a performance ratio of 3/2.
probe threshold and probe trivially perfect graphs. an undirected graph g=(v,e) is a probec graph if its vertex set can be partitioned into two sets, n (nonprobes) and p (probes) where n is independent and there exists e^'@?nxn such that g^'=(v,e@?e^') is a c graph. in this article we investigate probe threshold and probe trivially perfect graphs and characterise them in terms of certain 2-sat formulas and in other ways. for the case when the partition into probes and nonprobes is given, we give characterisations by forbidden induced subgraphs, linear recognition algorithms (in the case of probe threshold graphs it is based on the degree sequence of the graph), and linear algorithms to find a set e^' of minimum size. furthermore, we give linear time recognition algorithms for both classes and a characterisation by forbidden subgraphs for probe threshold graphs when the partition (p,n) is not given.
ptas for connected vertex cover in unit disk graphs. this paper gives the first polynomial time approximation scheme for the connected vertex cover problem in unit disk graphs.
scale free interval graphs. scale free graphs have attracted attention by their non-uniform structure that can be used as a model for various social and physical networks. in this paper, we propose a natural and simple random model for generating scale free interval graphs. the model generates a set of intervals randomly under a certain distribution, which defines a random interval graph. the main advantage of the model is its simpleness. the structure/properties of generated graphs are analyzable by relatively simple probabilistic and/or combinatorial arguments, which is different from many other models. based on such arguments, we show for our random interval graph that its degree distribution follows a power law, and that it has a large average clustering coefficient.
periodic scheduling with obligatory vacations. we consider a problem of repeatedly scheduling n jobs on m parallel machines. each job is associated with a profit that is gained each time the job is completed, and the goal is to maximize the average profit per time unit. once the processing of a job is completed, it goes on vacation and returns to the system, ready to be processed again, only after its vacation is over. this problem has many applications: in production planning, machine maintenance, video-on-demand and database query processing, among others. we show that the problem is np-hard already for jobs with unit processing times and unit profits, and develop approximation algorithms as well as optimal algorithms for certain subclasses of instances. we first show that a 5/3-approximation algorithm can be obtained for instances with unit processing times, using known results for windows scheduling. we then present a preemptive greedy algorithm, which yields a ratio of e/(e-1) to the optimal for general instances, with arbitrary processing times and arbitrary profits. for the special case where all jobs have the same (unit) processing times and the same (unit) profits, we present a 1.39-approximation algorithm. for this case we also show that, when the load generated by an instance is sufficiently large (in terms of n and m), any algorithm which uses no intended idle times yields an optimal schedule.
finding paths between graph colourings: pspace-completeness and superpolynomial distances. suppose we are given a graph g together with two proper vertex k-colourings of g, @a and @b. how easily can we decide whether it is possible to transform @a into @b by recolouring vertices of g one at a time, making sure we always have a proper k-colouring of g? this decision problem is trivial for k=2, and decidable in polynomial time for k=3. here we prove it is pspace-complete for all k>=4. in particular, we prove that the problem remains pspace-complete for bipartite graphs, as well as for: (i) planar graphs and 4@?k@?6, and (ii) bipartite planar graphs and k=4. moreover, the values of k in (i) and (ii) are tight, in the sense that for larger values of k, it is always possible to recolour @a to @b. we also exhibit, for every k>=4, a class of graphs {g"n","k:n@?n^*}, together with two k-colourings for each g"n","k, such that the minimum number of recolouring steps required to transform the first colouring into the second is superpolynomial in the size of the graph: the minimum number of steps is @w(2^n), whereas the size of g"n is o(n^2). this is in stark contrast to the k=3 case, where it is known that the minimum number of recolouring steps is at most quadratic in the number of vertices. we also show that a class of bipartite graphs can be constructed with this property, and that: (i) for 4@?k@?6 planar graphs and (ii) for k=4 bipartite planar graphs can be constructed with this property. this provides a remarkable correspondence between the tractability of the problem and its underlying structure.
robustness of temporal logic specifications for continuous-time signals. in this paper, we consider the robust interpretation of metric temporal logic (mtl) formulas over signals that take values in metric spaces. for such signals, which are generated by systems whose states are equipped with non-trivial metrics, for example continuous or hybrid, robustness is not only natural, but also a critical measure of system performance. thus, we propose multi-valued semantics for mtl formulas, which capture not only the usual boolean satisfiability of the formula, but also topological information regarding the distance, @e, from unsatisfiability. we prove that any other signal that remains @e-close to the initial one also satisfies the same mtl specification under the usual boolean semantics. finally, our framework is applied to the problem of testing formulas of two fragments of mtl, namely metric interval temporal logic (mitl) and closed metric temporal logic (clmtl), over continuous-time signals using only discrete-time analysis. the motivating idea behind our approach is that if the continuous-time signal fulfills certain conditions and the discrete-time signal robustly satisfies the temporal logic specification, then the corresponding continuous-time signal should also satisfy the same temporal logic specification.
a parameterized view on matroid optimization problems. matroid theory gives us powerful techniques for understanding combinatorial optimization problems and for designing polynomial-time algorithms. however, several natural matroid problems, such as 3-matroid intersection, are np-hard. here we investigate these problems from the parameterized complexity point of view: instead of the trivial n^o^(^k^) time brute force algorithm for finding a k-element solution, we try to give algorithms with uniformly polynomial (i.e., f(k)@?n^o^(^1^)) running time. the main result is that if the ground set of a represented linear matroid is partitioned into blocks of size @?, then we can determine in randomized time f(k,@?)@?n^o^(^1^) whether there is an independent set that is the union of k blocks. as a consequence, algorithms with similar running time are obtained for other problems such as finding a k-element set in the intersection of @? matroids, or finding k terminals in a network such that each of them can be connected simultaneously to the source by @? disjoint paths.
a new approach to the periodicity lemma on strings with holes. we first give an elementary proof of the periodicity lemma for strings containing one hole (variously called a ''wild card'', a ''don't-care'' or an ''indeterminate letter'' in the literature). the proof is modelled on euclid's algorithm for the greatest common divisor and is simpler than the original proof given in [j. berstel, l. boasson, partial words and a theorem of fine and wilf, theoret. comput. sci. 218 (1999) 135-141]. we then study the two-hole case, where our result agrees with the one given in [f. blanchet-sadri, robert a. hegstrom, partial words and a theorem of fine and wilf revisited, theoret. comput. sci. 270 (1-2) (2002) 401-419] but is more easily proved and enables us to identify a maximum-length prefix or suffix of the string to which the periodicity lemma does apply. finally, we extend our result to three or more holes using elementary methods, and state a version of the periodicity lemma that applies to all strings with or without holes. we describe an algorithm that, given the locations of the holes in a string, computes maximum-length substrings to which the periodicity lemma applies, in time proportional to the number of holes. our approach is quite different from that used by blanchet-sadri and hegstrom, and also simpler.
semisimple algebras of almost minimal rank over the reals. a famous lower bound for the bilinear complexity of the multiplication in associative algebras is the alder-strassen bound. algebras for which this bound is tight are called algebras of minimal rank. after 25 years of research, these algebras are now well understood. here we start the investigation of the algebras for which the alder-strassen bound is off by one. as a first result, we completely characterize the semisimple algebras over r whose bilinear complexity is by one larger than the alder-strassen bound. furthermore, we characterize all algebras a (with radical) of minimal rank plus one over r for which a/rada has minimal rank plus one. the other possibility is that a/rada has minimal rank. for this case, we only present a partial result.
claw finding algorithms using quantum walk. the claw finding problem has been studied in terms of query complexity as one of the problems closely connected to cryptography. given two functions, f and g, with domain sizes n and m(n@?m), respectively, and the same range, the goal of the problem is to find x and y such that f(x)=g(y). this problem has been considered in both quantum and classical settings in terms of query complexity. this paper describes an optimal algorithm that uses quantum walk to solve this problem. our algorithm can be slightly modified to solve the more general problem of finding a tuple consisting of elements in the two function domains that has a prespecified property. it can also be generalized to find a claw of k functions for any constant integer k>1, where the domain sizes of the functions may be different.
the parikh counting functions of sparse context-free languages are quasi-polynomials. let l be a sparse context-free language over an alphabet of t letters and let f"l:n^t->n be its parikh counting function. we prove the following two results: 1.there exists a partition of n^t into a finite family of polyhedra such that the function f"l is a quasi-polynomial on each polyhedron of the partition. 2.there exists a partition of n^t into a finite family of rational subsets such that the function f"l is a polynomial on each set of the partition.
the isolation game: a game of distances. we introduce a new multi-player geometric game, which we will refer to as the isolation game, and study its nash equilibria and best or better response dynamics. the isolation game is inspired by the voronoi game, competitive facility location, and geometric sampling. in the voronoi game studied by durr and thang, each player's objective is to maximize the area of her voronoi region. in contrast, in the isolation game, each player's objective is to position herself as far away from other players as possible in a bounded space. even though this game has a simple definition, we show that its game-theoretic behaviors are quite rich and complex. we consider various measures of farness from one player to a group of players and analyze their impacts to the existence of nash equilibria and to the convergence of the best or better response dynamics: we prove that it is np-hard to decide whether a nash equilibrium exists, using either a very simple farness measure in an asymmetric space or a slightly more sophisticated farness measure in a symmetric space. complementing these hardness results, we establish existence theorems for several special families of farness measures in symmetric spaces: we prove that, for isolation games where each player wants to maximize her distance to her mth nearest neighbor, for any m, equilibria always exist. moreover, there is always a better response sequence starting from any configuration that leads to a nash equilibrium. we show that when m=1 the game is a potential game, no better response sequence has a cycle, but when m>1 the games are not potential. more generally, we study farness functions that give different weights to a player's distances to others based on the distance rankings, and obtain both existence and hardness results when the weights are monotonically increasing or decreasing. finally, we present results on the hardness of computing best responses when the space has a compact representation as a hypercube.
distance paired-domination problems on subclasses of chordal graphs. let g=(v,e) be a graph without isolated vertices. for a positive integer k, a set s@?v is a k-distance paired-dominating set if each vertex in v-s is within distance k of a vertex in s and the subgraph induced by s contains a perfect matching. in this paper, we present two linear time algorithms to find a minimum cardinality k-distance paired-dominating set in interval graphs and block graphs, which are two subclasses of chordal graphs. in addition, we present a characterization of trees with unique minimum k-distance paired-dominating set.
repetitions in strings: algorithms and combinatorics. the article is an overview of basic issues related to repetitions in strings, concentrating on algorithmic and combinatorial aspects. this area is important both from theoretical and practical points of view. repetitions are highly periodic factors (substrings) in strings and are related to periodicities, regularities, and compression. the repetitive structure of strings leads to higher compression rates, and conversely, some compression techniques are at the core of fast algorithms for detecting repetitions. there are several types of repetitions in strings: squares, cubes, and maximal repetitions also called runs. for these repetitions, we distinguish between the factors (sometimes qualified as distinct) and their occurrences (also called positioned factors). the combinatorics of repetitions is a very intricate area, full of open problems. for example we know that the number of (distinct) primitively-rooted squares in a string of length n is no more than 2n-@q(logn), conjecture to be n, and that their number of occurrences can be @q(nlogn). similarly we know that there are at most 1.029n and at least 0.944n maximal repetitions and the conjecture is again that the exact bound is n. we know almost everything about the repetitions in sturmian words, but despite the simplicity of these words, the results are nontrivial. one of the main motivations for writing this text is the development during the last couple of years of new techniques and results about repetitions. we report both the progress which has been achieved and which we expect to happen.
minimum leaf out-branching and related problems. given a digraph d, the minimum leaf out-branching problem (minlob) is the problem of finding in d an out-branching with the minimum possible number of leaves, i.e., vertices of out-degree 0. we prove that minlob is polynomial-time solvable for acyclic digraphs. in general, minlob is np-hard and we consider three parameterizations of minlob. we prove that two of them are np-complete for every value of the parameter, but the third one is fixed-parameter tractable (fpt). the fpt parameterization is as follows: given a digraph d of order n and a positive integral parameter k, check whether d contains an out-branching with at most n-k leaves (and find such an out-branching if it exists). we find a problem kernel of order o(k^2) and construct an algorithm of running time o(2^o^(^k^l^o^g^k^)+n^6), which is an 'additive' fpt algorithm. we also consider transformations from two related problems, the minimum path covering and the maximum internal out-tree problems into minlob, which imply that some parameterizations of the two problems are fpt as well.
on the directional dynamics of additive cellular automata. we continue the study of cellular automata (ca) directional dynamics, i.e. , the behavior of the joint action of ca and shift maps. this notion has been investigated for general ca in the case of expansive dynamics by boyle and lind; and by sablik for sensitivity and equicontinuity. in this paper we give a detailed classification for the class of additive ca providing non-trivial examples for some classes of sablik's classification. moreover, we extend the directional dynamics studies by considering also factor languages and attractors.
simplicial powers of graphs. in a graph, a vertex is simplicial if its neighborhood is a clique. for an integer k>=1, a graph g=(v"g,e"g) is the k-simplicial power of a graph h=(v"h,e"h) (h a root graph of g) if v"g is the set of all simplicial vertices of h, and for all distinct vertices x and y in v"g, xy@?e"g if and only if the distance in h between x and y is at most k. this concept generalizes k-leaf powers introduced by nishimura, ragde and thilikos which were motivated by the search for underlying phylogenetic trees; k-leaf powers are the k-simplicial powers of trees. recently, a lot of work has been done on k-leaf powers and their roots as well as on their variants phylogenetic roots and steiner roots. for k@?5, k-leaf powers can be recognized in linear time, and for k@?4, structural characterizations are known. for k>=6, the recognition and characterization problems of k-leaf powers are still open. since trees and block graphs (i.e., connected graphs whose blocks are cliques) have very similar metric properties, it is natural to study k-simplicial powers of block graphs. we show that leaf powers of trees and simplicial powers of block graphs are closely related, and we study simplicial powers of other graph classes containing all trees such as ptolemaic graphs and strongly chordal graphs.
large independent sets in random regular graphs. we present algorithmic lower bounds on the size s"d of the largest independent sets of vertices in random d-regular graphs, for each fixed d>=3. for instance, for d=3 we prove that, for graphs on n vertices, s"d>=0.43475n with probability approaching one as n tends to infinity.
parameterized complexity of candidate control in elections and related digraph problems. there are different ways for an external agent to influence the outcome of an election. we concentrate on ''control'' by adding or deleting candidates. our main focus is to investigate the parameterized complexity of various control problems for different voting systems. to this end, we introduce natural digraph problems that may be of independent interest. they help in determining the parameterized complexity of control for different voting systems including llull, copeland, and plurality voting. devising several parameterized reductions, we provide an overview of the parameterized complexity of the digraph and control problems with respect to natural parameters such as adding/deleting only a bounded number of candidates or having only few voters.
scheduling multiprocessor uet tasks of two sizes. in this paper we study task scheduling problems on m identical parallel processors, where each task has unit execution time, and needs either a single processor, or q processors concurrently, and it has a release date and a due date. under the assumption that the release dates and due dates of the q-processor tasks are agreeable, we describe a polynomial time algorithm for minimising the number of tardy tasks. in addition, we apply this result for minimising the maximum lateness, and the maximum tardiness. we also discuss the combinatorial background of the polynomial time solvability of all these problems under the 'agreeable' assumption.
a characterization of regular circular languages generated by marked splicing systems. splicing systems are generative devices of formal languages, introduced by head in 1987 to model biological phenomena on linear and circular dna molecules. a splicing system is defined by giving an initial set i and a set r of rules. some unanswered questions are related to the computational power of circular splicing systems. in particular, a still open question is to find a characterization of circular languages generated by finite circular splicing systems (i.e., circular splicing systems with both i and r finite sets). in this paper we introduce a special class of the latter systems named marked systems. we prove that a marked system s generates a regular circular language if and only if s satisfies a special (decidable) property. as a consequence, we are able to characterize the structure of these regular circular languages.
disjoint directed and undirected paths and cycles in digraphs. we show that the following problem is np-complete: given a digraph d and distinct vertices s,t of d, decide whether the underlying graph of d contains two internally disjoint (s,t)-paths p and q such that p is a directed (s,t)-path in d. using this result we characterize those mixed linkage problems which are polynomially solvable (assuming p
direct chosen-ciphertext secure identity-based key encapsulation without random oracles. we describe a practical identity-based encryption scheme that is secure in the standard model against chosen-ciphertext attacks. our construction applies ''direct chosen-ciphertext techniques'' to waters' chosen-plaintext secure scheme and is not based on hierarchical identity-based encryption. furthermore, we give an improved concrete security analysis for waters' scheme. as a result, one can instantiate the scheme in smaller groups, resulting in efficiency improvements.
maximum weight bipartite matching in matrix multiplication time. in this paper we consider the problem of finding maximum weight matchings in bipartite graphs with nonnegative integer weights. the presented algorithm for this problem works in o@?(wn^@w) time, where @w is the matrix multiplication exponent, and w is the highest edge weight in the graph. as a consequence of this result we obtain o@?(wn^@w) time algorithms for computing: minimum weight bipartite vertex cover, single source shortest paths and minimum weight vertex disjoint s-t paths. all of the presented algorithms are randomized and with small probability can return suboptimal solutions.
termination of narrowing revisited. this paper describes several classes of term rewriting systems (trs's), where narrowing has a finite search space and is still (strongly) complete as a mechanism for solving reachability goals. these classes do not assume confluence of the trs. we also ascertain purely syntactic criteria that suffice to ensure the termination of narrowing, and include several subclasses of popular trs's such as right-linear trs's, almost orthogonal trs's, topmost trs's, and left-flat trs's. our results improve and/or generalize previous criteria in the literature regarding narrowing termination.
maximal and minimal representations of gapped and non-gapped motifs of a string. the problems of finding maximal and minimal equivalent representations for gapped and non-gapped motifs as well as finding motifs that characterize a fixed set of occurrence locations for a given string are studied. we apply two equivalence relations on representations. the first one is the well-known occurrence-equivalence of motifs. the second equivalence is introduced for patterns of occurrence locations, to characterize such patterns by motifs. for both equivalences, quadratic-time algorithms are given for finding a maximal representative of an equivalence class. finding a minimal representative is shown to be np-complete in both cases. for non-gapped motifs suffix-tree-based linear-time algorithms are given for finding maximal and minimal representatives. maximal (minimal) gapped motifs are composed of blocks that are maximal (minimal) non-gapped motifs, maximal and minimal non-gapped motifs thus making up a small basis for all motifs. the implied bound on the number of gapped motifs that have a fixed number of non-gapped blocks is also given.
speed scaling with a solar cell. we consider the setting of a device that obtains its energy from a battery and some regenerative source such as a solar cell. we consider the speed scaling problem of scheduling a collection of tasks with release times, deadlines, and sizes, so as to minimize the energy recharge rate of the regenerative source. this is the first theoretical investigation of speed scaling for devices with a regenerative energy source. we show that the problem can be expressed as a polynomial sized convex program. we show that, using the kkt conditions, one can obtain an efficient algorithm to verify the optimality of a schedule. we show that the energy optimal yds schedule is 2-approximate with respect to the recharge rate. we show that the online algorithm bkp is o(1)-competitive with respect to recharge rate.
lmntal as a hierarchical logic programming language. lmntal (pronounced ''elemental'') is a simple language model based on hierarchical graph rewriting that uses logical variables to represent connectivity and membranes to represent hierarchy. lmntal is an outcome of the attempt to unify constraint-based concurrency and constraint handling rules (chr), the two notable extensions to concurrent logic programming. lmntal is intended to be a substrate language of various computational models, especially those addressing concurrency, mobility and multiset rewriting. although the principal objective of lmntal was to provide a unifying computational model, it is of interest to equip the formalism with a precise logical interpretation. in this paper, we show that it is possible to give lmntal a simple logical interpretation based on intuitionistic linear logic and a flattening technique. this enables us to call lmntal a hierarchical, concurrent linear logic language.
how hard is it to find extreme nash equilibria in network congestion games? we study the complexity of finding extreme pure nash equilibria in symmetric (unweighted) network congestion games. in our context best and worst equilibria are those with minimum respectively maximum makespan. on series-parallel graphs a worst nash equilibrium can be found by a greedy approach while finding a best equilibrium is np-hard. for a fixed number of users we give a pseudo-polynomial algorithm to find the best equilibrium in series-parallel networks. for general network topologies also finding a worst equilibrium is np-hard.
deciding branching time properties for asynchronous programs. asynchronous programming is a paradigm that supports asynchronous function calls in addition to synchronous function calls. programs in such a setting can be modeled by automata with counters that keep track of the number of pending asynchronous calls for each function, as well as a call stack for synchronous recursive computation. these programs have the restriction that an asynchronous call is processed only when the call stack is empty. the decidability of the control state reachability problem for such systems was recently established. in this paper, we consider the problems of checking other branching time properties for such systems. specifically we consider the following problems - termination, which asks if there is an infinite (non-terminating) computation exhibited by the system; control state maintainability, which asks if there is a maximal execution of the system, where all the state visited lie in some ''good'' set; whether the system can be simulated by a given finite state system; and whether the system can simulate a given finite state system. we present decision algorithms for all these problems.
efficient model checking for ltl with partial order snapshots. certain behavioral properties of distributed systems are difficult to express in interleaving semantics, whereas they are naturally expressed in terms of partial orders of events or, equivalently, mazurkiewicz traces. two examples of such properties are serializability of a database and global snapshots of concurrent systems. recently, a modest extension for ltl by an operator that expresses snapshots, has been proposed. it combines the ease of linear (interleaving) specification with this useful partial order concept. the new construct allows one to assert that a global snapshot appeared in the past, perhaps not in the observed execution sequence, but possibly in an equivalent one. originally, a model checking algorithm for this logic that is exponential space in the size of the system was suggested. in this paper, we provide a model checking algorithm that is in polynomial space in the size of the system. our construction can also serve as an efficient (polynomial) algorithm for detecting conjunctive properties (i.e., conjunction of local process properties) in a concurrent history of execution.
hardness results and approximation algorithms for (weighted) paired-domination in graphs. let g=(v,e) be a simple graph without isolated vertices. a vertex set s@?v is a paired-dominating set if every vertex in v-s has a neighbor in s and the induced subgraph g[s] has a perfect matching. in this paper, we investigate the approximation hardness of paired-domination in graphs. for weighted paired-domination, an approximation algorithm in general graphs and an exact dynamic programming style algorithm in trees are also given.
fast algorithms for computing tree lcs. the lcs of two rooted, ordered, and labeled trees f and g is the largest forest that can be obtained from both trees by deleting nodes. we present algorithms for computing tree lcs which exploit the sparsity inherent to the tree lcs problem. assuming g is smaller than f, our first algorithm runs in time o(r@?height(f)@?height(g)@?lglg|g|), where r is the number of pairs (v@?f,w@?g) such that v and w have the same label. our second algorithm runs in time o(lrlgr@?lglg|g|), where l is the size of the lcs of f and g. for this algorithm we present a novel three-dimensional alignment graph. our third algorithm is intended for the constrained variant of the problem in which only nodes with zero or one children can be deleted. for this case we obtain an o(rhlglg|g|) time algorithm, where h=height(f)+height(g).
going weighted: parameterized algorithms for cluster editing. the goal of the cluster editing problem is to make the fewest changes to the edge set of an input graph such that the resulting graph is a disjoint union of cliques. this problem is np-complete but recently, several parameterized algorithms have been proposed. in this paper, we present a number of surprisingly simple search tree algorithms for weighted cluster editing assuming that edge insertion and deletion costs are positive integers. we show that the smallest search tree has size o(1.82^k) for edit cost k, resulting in the currently fastest parameterized algorithm, both for this problem and its unweighted counterpart. we have implemented and compared our algorithms, and achieved promising results.
on the size of boyer-moore automata. in this work we study the size of boyer-moore automata introduced in knuth, morris & pratt's famous paper on pattern matching. we experimentally show that a finite class of binary patterns produce very large boyer-moore automata, and find one particular case which we conjecture, generates automata of size @w(m^6). further experimental results suggest that the maximal size could be a polynomial of o(m^7), or even an exponential o(2^0^.^4^m), where m is the length of the pattern.
online scheduling to minimize modified total tardiness with an availability constraint. we consider online scheduling problems to minimize modified total tardiness. the problems are online in the sense that jobs arrive over time. for each job j"j, its processing time p"j, due date d"j and weight w"j become known at its arrival time (or release time) r"j. preemption is not allowed. we first show that there is no finite competitive ratio for problem 1|online,r"j,d"j|@?w"jt"j. so we focus on problem 1|online,r"j,d"j|@?w"j(t"j+d"j) and show that d-swpt (delayed shortest weighted processing time) algorithm is 3-competitive. we further study two problems 1|online,r"j,d"j,h(1),res|@?w"j(t"j+d"j) and 1|online,r"j,d"j,h(1),n-res|@?w"j(t"j+d"j), where res and n-res denote resumable and non-resumable models respectively, and h(1) denotes a non-available time interval [s,@as] with s>0 and @a>=1. we give a lower bound of 1+@a for both problems and prove that m-d-swpt (modified d-swpt) is 3@a and 6@a-competitive in the resumable and non-resumable models, respectively. moreover, we extend the upper bounds to the scenario of parallel machine scheduling with uniform job weight and an assumption that all machines have the same non-available time interval [s,@as]. a lower bound of min{@a,1+@am} is given as well for the scenario.
abstract interpretation of resolution-based semantics. we extend the abstract interpretation point of view on context-free grammars by cousot and cousot to resolution-based logic programs and proof systems. starting from a transition-based small-step operational semantics of prolog programs (akin to the warren machine), we consider maximal finite derivations for the transition system from most general goals. this semantics is abstracted by instantiation to terms and furthermore to ground terms, following the so-called c- and s-semantics approach. orthogonally, these sets of derivations can be abstracted to sld-trees, call patterns and models, as well as interpreters providing effective implementations (such as prolog). these semantics can be presented in bottom-up fixpoint form. this abstract interpretation-based construction leads to classical bottom-up semantics (such as the s-semantics of computed answers, the c-semantics of correct answers of keith clark, and the minimal-model semantics of logical consequences of maarten van emden and robert kowalski). the approach is general and can be applied to infinite and top-down semantics in a straightforward way.
navigable small-world networks with few random bits. we study small-world graphs in the perspective of their use in the development of efficient as well as easy to implement network infrastructures. our analysis starts from the small-world model proposed by kleinberg: a grid network augmented with directed long-range random links. the choices of the long-range links are independent from one node to another. in this setting greedy routing and some of its variants have been analyzed and shown to produce paths of polylogarithmic expected length. we start from asking whether all the randomness, used in kleinberg's model for establishing the long-range contacts of the nodes, is indeed necessary to assure the existence of short paths. in order to deal with the above question, we impose (stringent) restrictions on the choice of long-range links and we show that such restrictions do not increase the average path length of greedy routing and its variations. we are able to decrease the number of random bits, required to establish each node's long-range link, from @w(logn) to o(loglogn) on a network of size n. diminishing the randomness in the choice of random links has several benefits; in particular, it implies an increase in the clustering of the graph, thus increasing the resilience of the network.
frame rule for mutually recursive procedures manipulating pointers. using a predicate transformer semantics of programs, we introduce statements for heap operations and separation logic operators for specifying programs that manipulate pointers. we prove a powerful hoare total correctness rule for mutually recursive procedures manipulating pointers. the rule combines earlier proof rules for (mutually) recursive procedures with the frame rule for pointer programs. the theory, including the proofs, is implemented in the theorem prover pvs. in this implementation program variables and addresses can store values of almost any type of the theorem prover.
covering arrays avoiding forbidden edges. covering arrays (cas) can be used to detect the existence of faulty pairwise interactions between parameters or components in a software system. the generalization considered here applies to the situation in which some input combinations are invalid, a requirement quite common in software testing. in this paper, we study covering arrays avoiding forbidden edges (cafes), where certain pairwise interactions are forbidden while all others must be covered, and we aim to minimize the number of tests. we establish a theoretical framework for this problem, by providing connections to the edge clique covering problem, lower and upper bounds, complexity results and a recursive construction. we also give an algorithm for the case of binary alphabets.
a new linear time algorithm to compute the genomic distance via the double cut and join distance. the genomic distance problem in the hannenhalli-pevzner (hp) theory is the following: given two genomes whose chromosomes are linear, calculate the minimum number of translocations, fusions, fissions and inversions that transform one genome into the other. this paper presents a new distance formula based on a simple tree structure that captures all the delicate features of this problem in a unifying way, and a linear time algorithm for computing this distance.
the complexity of solitaire. klondike is the well-known 52-card solitaire game available on almost every computer. the problem of determining whether an n-card klondike initial configuration can lead to a win is shown np-complete. the problem remains np-complete when only three suits are allowed instead of the usual four. when only two suits of opposite color are available, the problem is shown nl-hard. when the only two suits have the same color, two restrictions are shown in ac^0 and in nl respectively. when a single suit is allowed, the problem drops in complexity down to ac^0[3], that is, the problem is solvable by a family of constant-depth unbounded-fan-in {and, or, mod"3 }-circuits. other cases are studied: for example, ''no king'' variant with an arbitrary number of suits of the same color and with an empty ''pile'' is nl-complete.
local consistency for extended csps. we extend the framework of constraint satisfaction problems to make it more suitable for/applicable to modern constraint programming languages where both constraint satisfaction and constraint solving have a role. some rough principles for local consistency conditions in the extended framework are developed, appropriate notions of local consistency are formulated, and relationships between the various consistency conditions are established.
on the complexity of 2d discrete fixed point problem. we study a computational complexity version of the 2d sperner problem, which states that any three coloring of vertices of a triangulated triangle, satisfying some boundary conditions, will have a trichromatic triangle. in introducing a complexity class ppad, papadimitriou [c.h. papadimitriou, on graph-theoretic lemmata and complexity classes, in: proceedings of the 31st annual symposium on foundations of computer science, 1990, 794-801] proved that its 3d analogue is ppad-complete about fifteen years ago. the complexity of 2d-sperner itself has remained open since then. we settle this open problem with a ppad-completeness proof. the result also allows us to derive the computational complexity characterization of a discrete version of the 2d brouwer fixed point problem, improving a recent result of daskalakis, goldberg and papadimitriou [c. daskalakis, p.w. goldberg, c.h. papadimitriou, the complexity of computing a nash equilibrium, in: proceedings of the 38th annual acm symposium on theory of computing (stoc), 2006]. those hardness results for the simplest version of those problems provide very useful tools to the study of other important problems in the ppad class.
optimal resilient sorting and searching in the presence of memory faults. we investigate the problem of reliable computation in the presence of faults that may arbitrarily corrupt memory locations. in this framework, we consider the problems of sorting and searching in optimal time while tolerating the largest possible number of memory faults. in particular, we design an o(nlogn) time sorting algorithm that can optimally tolerate up to o(nlogn) memory faults. in the special case of integer sorting, we present an algorithm with linear expected running time that can tolerate o(n) faults. we also present a randomized searching algorithm that can optimally tolerate up to o(logn) memory faults in o(logn) expected time, and an almost optimal deterministic searching algorithm that can tolerate o((logn)^1^-^@e) faults, for any small positive constant @e, in o(logn) worst-case time. all these results improve over previous bounds.
focusing and polarization in linear, intuitionistic, and classical logics. a focused proof system provides a normal form to cut-free proofs in which the application of invertible and non-invertible inference rules is structured. within linear logic, the focused proof system of andreoli provides an elegant and comprehensive normal form for cut-free proofs. within intuitionistic and classical logics, there are various different proof systems in the literature that exhibit focusing behavior. these focused proof systems have been applied to both the proof search and the proof normalization approaches to computation. we present a new, focused proof system for intuitionistic logic, called ljf, and show how other intuitionistic proof systems can be mapped into the new system by inserting logical connectives that prematurely stop focusing. we also use ljf to design a focused proof system lkf for classical logic. our approach to the design and analysis of these systems is based on the completeness of focusing in linear logic and on the notion of polarity that appears in girard's lc and lu proof systems.
s-semantics for logic programming: a retrospective look. the paper provides an overview of the s-semantic approach to the semantics of logic programs which had been developed about twenty years ago. the aim of such an approach was that of providing a suitable base for program analysis by means of a semantics which really captures the operational behavior of logic programs, and thus offers useful notions of observable program equivalences. the semantics is given in terms of extended interpretations, which are more expressive than herbrand interpretations, extends the standard herbrand semantics, and can be obtained as a result of both top-down and bottom-up constructions. the approach has been applied to several extensions of positive logic programs and used to develop semantic-based techniques for program analysis, verification and transformation.
on the shyr-yu theorem. an alternative proof of shyr-yu theorem is given. some generalizations are also considered using fractional root decompositions and fractional exponents of words.
on-the-fly tctl model checking for time petri nets. in this paper, we show how to efficiently model check a subset of tctl properties for the time petri net model (tpn model), using the state class method. the verification proceeds by augmenting the tpn model under analysis with a special tpn, called alarm-clock, to allow the capture of relevant time events. a forward on-the-fly exploration is then applied on the resulting tpn state class space to verify a timed property. a relaxation operation on state classes is also introduced to further improve performances. alarm-clock is the same for all properties, whereas the exploration technique is not. three exploration techniques are presented to cover most interesting tctl properties. we prove the decidability of our verification technique for bounded tpn models and compare it with the reachability algorithm implemented in the tool uppaal [g. behrmann, j. bengtsson, a. david, k.g. larsen, p. pettersson, w. yi, uppaal implementation secrets, in: proc. of the 7th international symposium on formal techniques in real-time and fault-tolerant systems, 2002]. finally, we give some experimental results to show the efficiency of our verification technique.
a sublinear-time approximation scheme for bin packing. the bin packing problem is defined as follows: given a set of n items with sizes 00, we present an algorithm a"@e that has sampling access to the input instance and outputs a value k such that c"o"p"t@?k@?(1+@e)@?c"o"p"t+1, where c"o"p"t is the cost of an optimal solution. it is clear that uniform sampling by itself will not allow a sublinear-time algorithm in this setting; a small number of items might constitute most of the total weight and uniform samples will not hit them. in this work we use weighted samples, where item i is sampled with probability proportional to its weight: that is, with probability w"i/@?"iw"i. in the presence of weighted samples, the approximation algorithm runs in o@?(n@?poly(1/@e))+g(1/@e) time, where g(x) is an exponential function of x. when both weighted sampling and uniform sampling are allowed, o@?(n^1^/^3@?poly(1/@e))+g(1/@e) time suffices. in addition to an approximate value to c"o"p"t, our algorithm can also output a constant-size ''template'' of a packing that can later be used to find a near-optimal packing in linear time.
when ignorance helps: graphical multicast cost sharing games. in non-cooperative games played on highly decentralized networks the assumption that each player knows the strategy adopted by any other player may be too optimistic or even infeasible. in such situations, the set of players of which each player knows the chosen strategy can be modeled by means of a social knowledge graph in which nodes represent players and there is an edge from i to j if i knows j. following the framework introduced in [7], we study the impact of social knowledge graphs on the fundamental multicast cost sharing game in which all the players want to receive the same communication from a given source in an undirected network. in the classical complete information case, such a game is known to be highly inefficient, since its price of anarchy can be as high as the total number of players @r. we first show that, under our incomplete information setting, pure nash equilibria always exist only if the social knowledge graph is directed acyclic (dag). we then prove that the price of stability of any dag is at least 12log@r and provide a dag lowering the classical price of anarchy to a value between 12log@r and log^2@r. if specific instances of the game are concerned, that is if the social knowledge graph can be selected as a function of the instance, we show that the price of stability is at least 4@r@r+3, and that the same bound holds also for the price of anarchy of any social knowledge graph (not only dags). moreover, we provide a nearly matching upper bound by proving that, for any fixed instance, there always exists a dag yielding a price of anarchy less than 4. our results open a new window on how the performances of non-cooperative systems may benefit from the lack of total knowledge among players.
the relevant prefixes of coloured motzkin walks: an average case analysis. in this paper we study some relevant prefixes of coloured motzkin walks (otherwise called coloured motzkin words). in these walks, the three kinds of step can have @a,@b and @c colours, respectively. in particular, when @a=@b=@c=1 we have the classical motzkin walks while for @a=@c=1 and @b=0 we find the well-known dyck walks. by using the concept of riordan arrays and probability generating functions we find the average length of the relevant prefix in a walk of length n and the corresponding variance in terms of @a,@b and @c. this result is interesting from a combinatorial point of view and also provides an average case analysis of algorithms related to the problem of ranking and generating uniformly at random the coloured motzkin words.
stationary algorithmic probability. kolmogorov complexity and algorithmic probability are defined only up to an additive resp. multiplicative constant, since their actual values depend on the choice of the universal reference computer. in this paper, we analyze a natural approach to eliminate this machine-dependence. our method is to assign algorithmic probabilities to the different computers themselves, based on the idea that ''unnatural'' computers should be hard to emulate. therefore, we study the markov process of universal computers randomly emulating each other. the corresponding stationary distribution, if it existed, would give a natural and machine-independent probability measure on the computers, and also on the binary strings. unfortunately, we show that no stationary distribution exists on the set of all computers; thus, this method cannot eliminate machine-dependence. moreover, we show that the reason for failure has a clear and interesting physical interpretation, suggesting that every other conceivable attempt to get rid of those additive constants must fail in principle, too. however, we show that restricting to some subclass of computers might help to get rid of some amount of machine-dependence in some situations, and the resulting stationary computer and string probabilities have beautiful properties.
three results on frequency assignment in linear cellular networks. in the frequency assignment problem we are given a graph representing a wireless network and a sequence of requests, where each request is associated with a vertex. each request has two more attributes: its arrival and departure times, and it is considered active from the time of arrival to the time of departure. we want to assign frequencies to all requests so that at each time step any two active requests associated with the same or adjacent vertices use different frequencies. the objective is to minimize the number of frequencies used. we focus exclusively on the special case of the problem when the underlying graph is a linear network (path). for this case, we consider both the offline and online versions of the problem, and we present three results. first, in the incremental online case, where the requests arrive over time, but never depart, we give an algorithm with an optimal (asymptotic) competitive ratio 43. second, in the general online case, where the requests arrive and depart over time, we improve the current lower bound on the (asymptotic) competitive ratio to 117. third, we prove that the offline version of this problem is np-complete.
definable transductions and weighted logics for texts. a text is a word together with an additional linear order on it. we study quantitative models for texts, i.e. text series which assign to texts elements of a semiring. we introduce an algebraic notion of recognizability following reutenauer and bozapalidis as well as weighted automata for texts combining an automaton model of lodaya and weil with a model of esik and nemeth. after that we show that both formalisms describe the text series definable in a certain fragment of weighted logics as introduced by droste and gastin. in order to do so, we study certain definable transductions and show that they are compatible with weighted logics.
linear logic by levels and bounded time complexity. we give a new characterization of elementary and deterministic polynomial time computation in linear logic through the proofs-as-programs correspondence. girard's seminal results, concerning elementary and light linear logic, achieve this characterization by enforcing a stratification principle on proofs, using the notion of depth in proof nets. here, we propose a more general form of stratification, based on inducing levels in proof nets by means of indices, which allows us to extend girard's systems while keeping the same complexity properties. in particular, it turns out that girard's systems can be recovered by forcing depth and level to coincide. a consequence of the higher flexibility of levels with respect to depth is the absence of boxes for handling the paragraph modality. we use this fact to propose a variant of our polytime system in which the paragraph modality is only allowed on atoms, and which may thus serve as a basis for developing lambda-calculus type assignment systems with more efficient typing algorithms than existing ones.
new algorithms for approximate nash equilibria in bimatrix games. we consider the problem of computing additively approximate nash equilibria in non-cooperative two-player games. we provide a new polynomial time algorithm that achieves an approximation guarantee of 0.36392. we first provide a simpler algorithm, that achieves a 0.38197-approximation, which is exactly the same factor as the algorithm of daskalakis, mehta and papadimitriou. this algorithm is then tuned, improving the approximation error to 0.36392. our method is relatively fast and simple, as it requires solving only one linear program and it is based on using the solution of an auxiliary zero-sum game as a starting point. finally we also exhibit a simple reduction that allows us to compute approximate equilibria for multi-player games by using algorithms for two-player games.
itineraries of rigid rotations and diffeomorphisms of the circle. we examine the itinerary of 0@?s^1=r/z under the rotation by @a@?r@?q. the motivating question is: if we are given only the itinerary of 0 relative to i@?s^1, a finite union of closed intervals, can we recover @a and i? we prove that the itineraries do determine @a and i up to certain equivalences. then we present elementary methods for finding @a and i. moreover, if g:s^1->s^1 is a c^2, orientation preserving diffeomorphism with an irrational rotation number, then we can use the orbit itinerary to recover the rotation number up to certain equivalences.
priority algorithms for graph optimization problems. we continue the study of priority or ''greedy-like'' algorithms as initiated in borodin et al. (2003) [10] and as extended to graph theoretic problems in davis and impagliazzo (2009) [12]. graph theoretic problems pose some modeling problems that did not exist in the original applications of borodin et al. and angelopoulos and borodin (2002) [3]. following the work of davis and impagliazzo, we further clarify these concepts. in the graph theoretic setting, there are several natural input formulations for a given problem and we show that priority algorithm bounds in general depend on the input formulation. we study a variety of graph problems in the context of arbitrary and restricted priority models corresponding to known ''greedy algorithms''.
simulation of one-way cellular automata by boolean circuits. we present a relationship between two major models of parallel computation: the one-way cellular automata and the boolean circuits. the starting point is the boolean circuit of small depth designed by ladner and fischer to simulate any rational transducer. we extend this construction to simulate one-way cellular automata by boolean circuits.
variations on a theme by akl and taylor: security and tradeoffs. in 1983, akl and taylor [cryptographic solution to a problem of access control in a hierarchy, acm transactions on computer systems 1 (3) (1983) 239-248] first suggested the use of cryptographic techniques to enforce access control in hierarchical structures. due to its simplicity and versatility, the scheme has been used, for more than twenty years, to implement access control in several different domains, including mobile agent environments and xml documents. however, despite its use over time, the scheme has never been fully analyzed with respect to security and efficiency requirements. in this paper we provide new results on the akl-taylor scheme and its variants. more precisely: *we provide a rigorous analysis of the akl-taylor scheme. we consider different key assignment strategies and prove that the corresponding schemes are secure against key recovery. *we show how to obtain different tradeoffs between the amount of public information and the number of steps required to perform key derivation in the proposed schemes. *we also look at the mackinnon et al. and harn and lin schemes and prove they are secure against key recovery. *we describe an akl-taylor based key assignment scheme with time-dependent constraints and prove the scheme efficient, flexible and secure. *we propose a general construction, which is of independent interest, yielding a key assignment scheme offering security w.r.t. key indistinguishability, given any key assignment scheme which guarantees security against key recovery. *finally, we show how to use our construction, along with our assignment strategies and tradeoffs, to obtain an akl-taylor scheme, secure w.r.t. key indistinguishability, requiring a constant amount of public information.
strong normalization property for second order linear logic. the paper contains the first complete proof of strong normalization (sn) for full second order linear logic (ll): girard's original proof uses a standardization theorem which is not proven. we introduce sliced pure structures (sps), a very general version of girard's proof-nets, and we apply to sps gandy's method to infer sn from weak normalization (wn). we prove a standardization theorem for sps: if wn without erasing steps holds for an sps, then it enjoys sn. a key step in our proof of standardization is a confluence theorem for sps obtained by using only a very weak form of correctness, namely acyclicity slice by slice. we conclude by showing how standardization for sps allows to prove sn of ll, using as usual girard's reducibility candidates.
an axiom system for sequence-based specification. this paper establishes an axiomatic foundation and a representation theorem for the rigorous, constructive process, called sequence-based specification, of deriving precise specifications from ordinary (informal) statements of functional requirements. the representation theorem targets a special class of mealy state machines, and algorithms are presented for converting from the set of sequences that define the specification to the equivalent mealy machine, and vice versa. since its inception, sequence-based specification has been effectively used in a variety of real applications, with gains reported in quality and productivity. this paper establishes the mathematical foundation independently of the process itself.
energy optimal schedules for jobs with multiple active intervals. in this paper, we study the scheduling problem of jobs with multiple active intervals. each job in the problem instance has n(n>=1) disjoint active time intervals where it can be executed and a workload characterized by the required number of cpu cycles. previously, people studied multiple interval job scheduling problem where each job must be assigned enough cpu cycles in one of its active intervals. we study a different practical version where the partial work done by the end of an interval remains valid and each job is considered finished if total cpu cycles assigned to it in all its active intervals reach the requirement. the goal is to find a feasible schedule that minimizes energy consumption. by adapting the algorithm for single interval jobs proposed in yao, demers and shenker (1995) [1], one can still obtain an optimal schedule. however, the two phases in that algorithm (critical interval finding and scheduling the critical interval) can no longer be carried out directly. we present polynomial time algorithms to solve the two phases for jobs with multiple active intervals and therefore can still compute the optimal schedule in polynomial time.
quantum implicit computational complexity. we introduce a quantum lambda calculus inspired by lafont's soft linear logic and capturing the polynomial quantum complexity classes eqp, bqp and zqp. the calculus is based on the ''classical control and quantum data'' paradigm. this is the first example of a formal system capturing quantum complexity classes in the spirit of implicit computational complexity - it is machine-free and no explicit bound (e.g., polynomials) appears in its syntax.
on stateless multihead automata: hierarchies and the emptiness problem. we look at stateless multihead finite automata in their two-way and one-way, deterministic and nondeterministic variations. the transition of a k-head automaton depends solely on the symbols currently scanned by its k heads, and every such transition moves each head one cell left or right, or instructs it to stay. we show that stateless (k+4)-head two-way automata are more powerful than stateless k-head two-way automata. in the one-way case, we prove a tighter result: stateless (k+1)-head one-way automata are more powerful than stateless k-head one-way automata. finally, we show that the emptiness problem for stateless 2-head two-way automata is undecidable.
on lazy bin covering and packing problems. in this paper, we study two interesting variants of the classical bin packing problem, called lazy bin covering (lbc) and cardinality constrained maximum resource bin packing (ccmrbp) problems. for the offline lbc problem, we first prove the approximation ratio of the first-fit-decreasing and first-fit-increasing algorithms, then present an aptas. for the online lbc problem, we give a competitive analysis for the algorithms of next-fit, worst-fit, first-fit, and a modified harmonic"m algorithm. the ccmrbp problem is a generalization of the maximum resource bin packing (mrbp) problem boyar et al. (2006) [1]. for this problem, we prove that its offline version is no harder to approximate than the offline mrbp problem.
on graphs of central episturmian words. episturmian sequences are a natural extension of sturmian sequences to the case of finite alphabets of arbitrary cardinality. in this paper, we are interested in central episturmian words, or simply, epicentral words, i.e., the palindromic prefixes of standard episturmian sequences. an epicentral word admits a variety of faithful representations including as a directive word, as a certain type of period vector, as a parikh vector, as a certain type of fine and wilf extremal word, as a suitable modular matrix, and as a labeled graph. various interconnections between the different representations of an epicentral word are analyzed. in particular, we investigate the structure of the graphs of epicentral words proving some curious and surprising properties.
narrowing power vs efficiency in synchronous set agreement: relationship, algorithms and lower bound. the k-set agreement problem is a generalization of the uniform consensus problem: each process proposes a value, and each non-faulty process has to decide a value such that a decided value is a proposed value, and at most k different values are decided. it has been shown that any algorithm that solves the k-set agreement problem in synchronous systems that can suffer up to t crash failures requires @?tk@?+1 rounds in the worst case. it has also been shown that it is possible to design early deciding algorithms where no process decides and halts after min(@?fk@?+2,@?tk@?+1) rounds, where f is the number of actual crashes in a run (0@?f@?t). this paper explores a new direction to solve the k-set agreement problem in a synchronous system. it considers that the system is enriched with base objects (denoted has [m,@?]_sa objects) that allow solving the @?-set agreement problem in a set of m processes (m
on the complexities of consistency checking for restricted uml class diagrams. automatic debugging of uml class diagrams helps in the visual specification of software systems because users cannot detect errors in logical consistency easily. this study focuses on the tractable consistency checking of uml class diagrams. we accurately identify inconsistencies in these diagrams by translating them into first-order predicate logic that is generalized by counting quantifiers and classify their expressivities by eliminating certain components. we introduce optimized algorithms that compute the respective consistencies of class diagrams of different expressive powers in p, np, pspace, or exptime with respect to the size of the class diagrams. in particular, owing to the restrictions imposed on attribute value types, the complexities of consistency checking of class diagrams decrease from exptime to p and pspace in two cases: (i) when the class diagrams contain disjointness constraints and overwriting/multiple inheritances and (ii) when the class diagrams contain both these components along with completeness constraints. additionally, we confirm the existence of a restriction of class diagrams that prevents any logical inconsistency.
maximal width learning of binary functions. this paper concerns learning binary-valued functions defined on r, and investigates how a particular type of 'regularity' of hypotheses can be used to obtain better generalization error bounds. we derive error bounds that depend on the sample width (a notion analogous to that of sample margin for real-valued functions). this motivates learning algorithms that seek to maximize sample width.
on-demand strategy annotations revisited: an improved on-demand evaluation strategy. in functional languages such as obj*, cafeobj, and maude, symbols are given strategy annotations that specify (the order in) which subterms are evaluated. syntactically, strategy annotations are given either as lists of natural numbers or as lists of integers associated to function symbols whose (absolute) values refer to the arguments of the corresponding symbol. a positive index prescribes the evaluation of an argument whereas a negative index means ''evaluation on-demand''. these on-demand indices have been proposed to support laziness in obj-like languages. while strategy annotations containing only natural numbers have been implemented and investigated to some extent (regarding, for example, termination, confluence, and completeness), fully general annotations (including positive and negative indices) have been disappointingly under-explored to date. in this paper, we first point out a number of problems of current proposals for handling on-demand strategy annotations. then, we propose a solution to these problems by keeping an accurate track of annotations along the evaluation sequences. we formalize this solution as a suitable extension of the evaluation strategy of obj-like languages (which only consider annotations given as natural numbers) to on-demand strategy annotations. our on-demand evaluation strategy (ode) overcomes the drawbacks of previous proposals and also has better computational properties. for instance, we show how to use this strategy for computing (head-)normal forms. we also introduce a transformation which allows us to prove the termination of the new evaluation strategy by using standard rewriting techniques. finally, we present two interpreters of the new strategy together with some encouraging experiments which demonstrate the usefulness of our approach.
np-hard and linear variants of hypergraph partitioning. this article presents an infinite family of combinatorial problems that shows abrupt changes of complexity between neighbour problems. we define problem p"k^l as a purely constraint-driven variant of hypergraph partitioning with parameters k and l as follows. given a hypergraph on n vertices and k sizes of colours t"1,...,t"k of sum n, can we colour the vertices with k colours of given size such that each hyperedge intersects at most l colours? we show that, for fixed parameters k and l, p"k^l is: polynomial when l=1, and np-complete when l1 on the class of hypergraphs with pairwise disjoint hyperedges. this inversion of complexity is possible since hypergraphs with disjoint hyperedges can be encoded in a more compact way, namely @q(mlog(n)) instead of @q(mn) bits (n and m are the number of vertices and edges of the hypergraph).
canonical finite state machines for distributed systems. there has been much interest in testing from finite state machines (fsms) as a result of their suitability for modelling or specifying state-based systems. where there are multiple ports/interfaces a multi-port fsm is used and in testing, a tester is placed at each port. if the testers cannot communicate with one another directly and there is no global clock then we are testing in the distributed test architecture. it is known that the use of the distributed test architecture can affect the power of testing and recent work has characterised this in terms of local s-equivalence: in the distributed test architecture we can distinguish two fsms, such as an implementation and a specification, if and only if they are not locally s-equivalent. however, there may be many fsms that are locally s-equivalent to a given fsm and the nature of these fsms has not been explored. this paper examines the set of fsms that are locally s-equivalent to a given fsm m. it shows that there is a unique smallest fsm @g"m"i"n(m) and a unique largest fsm @g"m"a"x(m) that are locally s-equivalent to m. here smallest and largest refer to the set of traces defined by an fsm and thus to its semantics. we also show that for a given fsm m the set of fsms that are locally s-equivalent to m defines a bounded lattice. finally, we define an fsm that, amongst all fsms locally s-equivalent to m, has fewest states. we thus give three alternative canonical fsms that are locally s-equivalent to an fsm m: one that defines the smallest set of traces, one that defines the largest set of traces, and one with fewest states. all three provide valuable information and the first two can be produced in time that is polynomial in terms of the number of states of m. we prove that the problem of finding an s-equivalent fsm with fewest states is np-hard in general but can be solved in polynomial time for the special case where there are two ports.
mechanism design for set cover games with selfish element agents. in this article, we study the set cover games when the elements are selfish agents, each of which has a privately known valuation of receiving the service from the sets, i.e., being covered by some set. each set is assumed to have a fixed cost. we develop several approximately efficient strategyproof mechanisms that decide, after soliciting the declared bids by all elements, which elements will be covered, which sets will provide the coverage to these selected elements, and how much each element will be charged. for single-cover set cover games, we present a mechanism that is at least 1d"m"a"x-efficient, i.e., the total valuation of all selected elements is at least 1d"m"a"x fraction of the total valuation produced by any mechanism. here, d"m"a"x is the maximum size of the sets. for multi-cover set cover games, we present a budget-balanced strategyproof mechanism that is 1d"m"a"xh"d"""m"""a"""x-efficient under reasonable assumptions. here, h"n is the harmonic function. for the set cover games when both sets and elements are selfish agents, we show that a cross-monotonic payment-sharing scheme does not necessarily induce a strategyproof mechanism.
maximum likelihood analysis of algorithms and data structures. we present a new approach for an average-case analysis of algorithms and data structures that supports a non-uniform distribution of the inputs and is based on the maximum likelihood training of stochastic grammars. the approach is exemplified by an analysis of the expected size of binary tries as well as by three sorting algorithms and it is compared to the known results that were obtained by traditional techniques. investigating traditional settings like the random permutation model, we rediscover well-known results formerly derived by pure analytic methods; changing to biased data yields original results. all but one step of our analysis can be automated on top of a computer-algebra system. thus our new approach can reduce the effort required for an average-case analysis, allowing for the consideration of realistic input distributions with unknown distribution functions at the same time. as a by-product, our approach yields an easy way to generate random combinatorial objects according to various probability distributions.
comparing notions of randomness. it is an open problem in the area of effective (algorithmic) randomness whether kolmogorov-loveland randomness coincides with martin-lof randomness. joe miller and andre nies suggested some variations of kolmogorov-loveland randomness to approach this problem and to provide a partial solution. we show that their proposed notion of injective randomness is still weaker than martin-lof randomness. since in this proof some of the ideas we use are clearer, we also show the weaker theorem that permutation randomness is weaker than martin-lof randomness.
a graph theoretic approach to general euler diagram drawing. euler diagrams are used in a wide variety of areas for representing information about relationships between collections of objects. recently, several techniques for automated euler diagram drawing have been proposed, contributing to the euler diagram generation problem: given an abstract description, draw an euler diagram with that description and which possesses certain properties, sometimes called well-formedness conditions. we present the first fully formalized, general framework that permits the embedding of euler diagrams that possess any collection of the six typically considered well-formedness conditions. our method first converts the abstract description into a vertex-labelled graph. an euler diagram can then be formed, essentially by finding a dual graph of such a graph. however, we cannot use an arbitrary plane embedding of the vertex-labelled graph for this purpose. we identify specific embeddings that allow the construction of appropriate duals. from these embeddings, we can also identify precisely which properties the drawn euler diagram will possess and 'measure' the number of times that each well-formedness condition is broken. we prove that every abstract description can be embedded using our method. moreover, we identify exactly which (large) class of euler diagrams can be generated.
theory of one-tape linear-time turing machines. a theory of one-tape two-way one-head off-line linear-time turing machines is essentially different from its polynomial-time counterpart since these machines are closely related to finite state automata. this paper discusses structural-complexity issues of one-tape turing machines of various types (deterministic, nondeterministic, reversible, alternating, probabilistic, counting, and quantum turing machines) that halt in linear time, where the running time of a machine is defined as the length of any longest computation path. we explore structural properties of one-tape linear-time turing machines and clarify how the machines' resources affect their computational patterns and power.
maximizing the minimum load for selfish agents. we consider the problem of maximizing the minimum load (completion time) for machines that are controlled by selfish agents, who are only interested in maximizing their own profit. unlike the classical load balancing problem, this problem has not been considered for selfish agents until now. the goal is to design a truthful mechanism, i.e., one in which all users have an incentive to tell the truth about the speeds of their machines. this then allows us to find good job assignments. it is known that this requires monotone approximation algorithms, in which the amount of work assigned to an agent does not increase if its bid (claimed cost per unit work) increases. for a constant number of machines, m, we show a monotone polynomial-time approximation scheme (ptas) with running time that is linear in the number of jobs. it uses a new technique for reducing the number of jobs while remaining close to the optimal solution. we use an fptas for the classical problem, i.e., where no selfish agents are involved, to give a monotone fptas. additionally, we give a monotone approximation algorithm with approximation ratio min(m,(2+@e)s"1/s"m) where @e>0 can be chosen arbitrarily small and s"i is the (real) speed of machine i. finally we give improved results for two machines.
compositions of maximal codes. the proposition ''for composable thin codes y and z, the composition y@?z is maximal if and only if y and z are maximal'' put forward by j. berstel and d. perrin in their book ''theory of codes'' is well known. is the proposition also true without the assumption that y and z are thin? we give an example showing that the answer is negative. furthermore, several generalizations of the above proposition are also given.
on a special class of primitive words. when representing dna molecules as words, it is necessary to take into account the fact that a word u encodes basically the same information as its watson-crick complement @q(u), where @q denotes the watson-crick complementarity function. thus, an expression which involves only a word u and its complement can be still considered as a repeating sequence. in this context, we define and investigate the properties of a special class of primitive words, called pseudo-primitive words relative to @q or simply @q-primitive words, which cannot be expressed as such repeating sequences. for instance, we prove the existence of a unique @q-primitive root of a given word, and we give some constraints forcing two distinct words to share their @q-primitive root. also, we present an extension of the well-known fine and wilf theorem, for which we give an optimal bound.
cps-translation as adjoint. we show that there exist translations between polymorphic @l-calculus and a subsystem of minimal logic with existential types, which form a galois insertion (embedding). the translation from polymorphic @l-calculus into the existential type system is the so-called call-by-name cps-translation that can be expounded as an adjoint from the neat connection. the construction of an inverse translation is investigated from a viewpoint of residuated mappings. the duality appears not only in the reduction relations but also in the proof structures, such as paths between the source and the target calculi. from a programming point of view, this result means that abstract data types can interpret polymorphic functions under the cps-translation. we may regard abstract data types as a dual notion of polymorphic functions.
a mezei-wright theorem for categorical algebras. the main result of this paper is a generalization of the mezei-wright theorem, a result on solutions of a system of fixed point equations. in the typical setting, one solves a system of fixed point equations in an algebra equipped with a suitable partial order; there is a least element, suprema of @w-chains exist, the operations preserve the ordering and least upper bounds of @w-chains. in this setting, one solution of this kind of system is provided by least fixed points. the mezei-wright theorem asserts that such a solution is preserved by a continuous, order preserving algebra homomorphism. in several settings such as (countable) words or synchronization trees there is no well-defined partial order but one can naturally introduce a category by considering morphisms between the elements. the generalization of this paper consists in replacing ordered algebras by ''categorical algebras''; the least element is replaced by an initial element, and suprema of @w-chains are replaced by colimits of @w-diagrams. then the mezei-wright theorem for categorical algebras is that initial solutions are preserved by continuous morphisms. we establish this result for initial solutions of parametric fixed point equations. one use of the theorem is to characterize an ''algebraic'' element as one that can arise as a solution of some system of fixed point equations. in familiar examples, an algebraic element is one that is context-free, regular or rational. then, if h:a->b is a continuous morphism of categorical algebras, the algebraic objects in b are those isomorphic to h-images of algebraic objects in a.
on the computational power of blenx. we present some decidability and undecidability results for subsets of the blenx language, a process-calculi-based programming language developed for modelling biological processes. we show that for a core subset of the language (which considers only communication primitives) termination is decidable. moreover, we prove that by adding either global priorities or events to this core language, we obtain turing equivalent languages. the proof is through encodings of random access machines (rams), a well-known turing equivalent formalism, into our subsets of blenx. all the encodings are shown to be correct.
peek arc consistency. this paper studies peek arc consistency, a reasoning technique that extends the well-known arc consistency technique for constraint satisfaction. in contrast to other more costly extensions of arc consistency that have been studied in the literature, peek arc consistency requires only linear space and quadratic time and can be parallelized in a straightforward way such that it runs in linear time with a linear number of processors. we demonstrate that for various constraint languages, peek arc consistency gives a polynomial-time decision procedure for the constraint satisfaction problem. we also present an algebraic characterization of those constraint languages that can be solved by peek arc consistency, and study the robustness of the algorithm.
complexity and succinctness issues for linear-time hybrid logics. full linear-time hybrid logic (hl) is a non-elementary and equally expressive extension of standard ltl + past obtained by adding the well-known binder operators @7 and @?. we investigate complexity and succinctness issues for hl in terms of the number of variables and nesting depth of binder modalities. first, we present direct automata-theoretic decision procedures for satisfiability and model-checking of hl, which require space of exponential height equal to the nesting depth of the binder modalities. the proposed algorithms are proved to be asymptotically optimal by providing matching lower bounds. second, we show that, for the one-variable fragment of hl, the considered problems are elementary and, precisely, expspace-complete. finally, we show that, for all 0@?h
factorization forests for infinite words and applications to countable scattered linear orderings. the theorem of factorization forests of imre simon shows the existence of nested factorizations-a la ramsey-for finite words. this theorem has important applications in semigroup theory, and beyond. we provide two improvements to the standard result. first we improve on all previously known bounds. second, we extend it to 'every linear ordering'. we use this last variant in a simplified proof of the translation of recognizable languages over countable scattered linear orderings to languages accepted by automata.
complexity issues in color-preserving graph embeddings. in the context of comparative analysis of protein-protein interaction graphs, we use a graph-based formalism to detect the preservation of a given protein complex (pattern graph) in the protein-protein interaction graph (target graph) of another species with respect to (w.r.t.) orthologous proteins. we give an efficient exponential-time randomized algorithm in case the occurrence of the pattern graph in the target graph is required to be exact. for approximate occurrences, we prove a tight inapproximability result and give four approximation algorithms that deal with bounded degree graphs, small ortholog numbers, linear forests and very simple yet hard instances, respectively.
some complexity results for prefix gröbner bases in free monoid rings. we establish the following complexity results for prefix grobner bases in free monoid rings: 1. |r|@?size(p) reduction steps are sufficient to normalize a given polynomial p w.r.t. a given right-normalized system r of prefix rules compatible with some total admissible well-founded ordering >. 2. o(|r|@?size(r)) basic steps are sufficient to transform a given terminating system r of prefix rules into an equivalent right-normalized system. 3. o(|r|^2@?size(r)) basic steps are sufficient to decide whether or not a given terminating system r of prefix rules is a prefix grobner basis. the latter result answers an open question posed by zeckzer (2000) [9].
extended strings and graphs for simple gene assembly. the simple intramolecular model for gene assembly in ciliates is particularly interesting because it can predict the correct assembly of all available experimental data, although it is not universal. the simple model also has a confluence property that is not shared by the general model. a previous formalization of the simple model through sorting of signed permutations is unsatisfactory because it effectively ignores one operation of the model and thus, it cannot be used to answer questions about parallelism in the model, or about measures of complexity. we propose in this paper a string-based model in which a gene is represented through its sequence of pointers and markers and its assembly is represented as a string rewriting process. we prove that this string-based model is equivalent to the permutation-based model as far as gene assembly is concerned, while it tracks all operations of the simple model. we also consider overlap graphs for these strings and prove the results with respect to the overlap of markers.
on notions of regularity for data languages. with motivation from considerations in xml database theory and model checking, data strings have been introduced as an extension of finite alphabet strings which carry, at each position, a symbol and a data value from an infinite domain. previous work has shown that it is difficult to come up with an expressive yet decidable automaton model for data languages. recently, such a model, data automata, was introduced. this paper introduces a simpler but equivalent model and investigates its expressive power, algorithmic and closure properties, and some extensions.
on blockwise symmetric signatures for matchgates. we give a classification of blockwise symmetric signatures in the theory of matchgate computations. the main proof technique uses matchgate identities, also known as useful grassmann-plucker identities.
real-time reversible iterative arrays. iterative arrays are one-dimensional arrays of interconnected interacting finite automata. the cell at the origin is equipped with a one-way read-only input tape. we investigate iterative arrays as acceptors for formal languages. in particular, we consider real-time devices which are reversible on the core of computation, i.e., from initial configuration to the configuration given by the time complexity. this property is called real-time reversibility. it is shown that real-time reversible iterative arrays can simulate restricted variants of stacks and queues. it turns out that real-time reversible iterative arrays are strictly weaker than real-time reversible cellular automata. on the other hand, a non-semilinear language is accepted. we show that real-time reversibility itself is not even semidecidable, which extends the undecidability for cellular automata and contrasts with the general case, where reversibility is decidable for one-dimensional devices. moreover, we prove the non-semidecidability of several other properties. several closure properties are also derived.
productivity of stream definitions. we give an algorithm for deciding productivity of a large and natural class of recursive stream definitions. a stream definition is called 'productive' if it can be evaluated continually in such a way that a uniquely determined stream in constructor normal form is obtained as the limit. whereas productivity is undecidable for stream definitions in general, we show that it can be decided for 'pure' stream definitions. for every pure stream definition the process of its evaluation can be modelled by the dataflow of abstract stream elements, called 'pebbles', in a finite 'pebbleflow net(work)'. and the production of a pebbleflow net associated with a pure stream definition, that is, the amount of pebbles the net is able to produce at its output port, can be calculated by reducing nets to trivial nets.
on the complexity of kings. a king in a directed graph is a vertex from which each vertex in the graph can be reached through paths of length at most two. there is a broad literature on tournaments (completely oriented digraphs), and it has been known for more than half a century that all tournaments have at least one king. recently, kings have proven useful in theoretical computer science, in particular in the study of the complexity of reachability problems and semifeasible sets. in this article, we study the complexity of recognizing kings. for each succinctly specified family of tournaments, the king problem is already known to belong to @p"2^p. we prove that the complexity of kingship problems is a rich enough vocabulary to pinpoint every nontrivial many-one degree in @p"2^p. that is, we show that every set in @p"2^p other than 0@? and @s^* is equivalent to a king problem under @?"m^p-reductions. indeed, we show that the equivalence can even be realized by relatively simple padding, and holds even if the notion of kings is redefined to refer to k-kings (for any fixed k>=2)-vertices from which all vertices can be reached through paths of length at most k. in contrast, we prove that for each succinctly specified family of tournaments the source problem (the problem of deciding whether a given vertex v has the property that there exists a k such that v is a k-king) also falls within @p"2^p, yet cannot be @p"2^p-complete-or even np-hard-unless p=np. using these and related techniques, we obtain a broad range of additional results about the complexity of king problems, diameter problems, and radius problems. it follows easily from our proof approach that the problem of testing kingship in succinctly specified graphs (which need not be tournaments) is @p"2^p-complete. we show that the radius problem for arbitrary succinctly represented graphs is @s"3^p-complete, but that in contrast the diameter problem for arbitrary succinctly represented graphs (or even tournaments) is @p"2^p-complete.
notions of hyperbolicity in monoids. we introduce a notion of hyperbolicity in monoids which is a restriction of that suggested by duncan and gilman. one advantage is that the notion gives rise to efficient algorithms for dealing with certain questions; for example, the word problem can be solved in time o(nlogn). we also introduce a new way of defining automatic monoids which provides a uniform framework for the discussion of these concepts. hyperbolic monoids (in the sense introduced here) turn out to be biautomatic.
recent developments in computer vision, second asian conference on computer vision, accv '95, singapore, december 5-8, 1995, invited session papers in this paper, we propose a new edge-based text verification approach for video. based on the investigation of the relation between candidate blocks and their neighbor areas, the proposed approach first detects background edges in candidate blocks, then erases them by an edge tracking technique, and finally the candidate blocks containing too few remaining edges are eliminated as false alarms. three measures for text detection evaluation in video were used to assess the performance of the proposed text verification approach. experimental results on 50 broadcast news video clips demonstrate the validity of our approach.
computer vision - accv'98, third asian conference on computer vision, hong kong, china, january 8-10, 1998, proceedings, volume i in this paper, we analyze the problem of network disconnection in the context of large-scale p2p networks and understand how both static and dynamic patterns of node failure affect the resilience of such graphs. we start by applying classical results from random graph theory to show that a large variety of deterministic and random p2p graphs almost surely (i.e., with probability 1-o(1)) remain connected under random failure if and only if they have no isolated nodes. this simple, yet powerful, result subsequently allows us to derive in closed-form the probability that a p2p network develops isolated nodes, and therefore partitions, under both types of node failure. we finish the paper by demonstrating that our models match simulations very well and that dynamic p2p systems are extremely resilient under node churn as long as the neighbor replacement delay is much smaller than the average user lifetime.
computer vision - accv'98, third asian conference on computer vision, hong kong, china, january 8-10, 1998, proceedings, volume ii this paper proposes an enhanced rvlc coder, context-adaptive reversible variable length coder (crvlc), for dct coefficients by using the techniques of data sub-partitioning and context modeling. the data sub-partitioning means that the data part of dct coefficients is split into several small sub-partitions. as each sub-partition can be reversibly decoded by rvlc, more data as well as higher error resilience can be obtained. the context modeling exploits the correlation of dct coefficients for further compression. this modeling defines the contexts by hierarchical-dependent information. the information is also available in the backward decoding, so that it supports the reversible decoding. and with it the data outputted by crvlc can be naturally placed into multiple sub-partitions.
computer vision - accv 2006, 7th asian conference on computer vision, hyderabad, india, january 13-16, 2006, proceedings, part i in this paper, a low-complexity 8times8/4times4 adaptive block-size transform (abt) scheme is tentatively proposed for the chinese audio and video coding standard (avs). in the proposed abt scheme, an integer 8times8 transform is derived from the integer 4times4 transform used in avs according to a transform extension principle. the 8times8 transform not only has high energy compacted property but also can be merely implemented within several additions and shifts, and all intermediate results are limited with 16-bit. the 8times8 transform and 4times4 transform can be merged together and share the same scale matrix so that the hardware units and storage resources are efficiently saved for both encoder and decoder. the experimental results on numerous sequences show that the proposed abt scheme can achieve significant performance improvement for avs
computer vision - accv 2006, 7th asian conference on computer vision, hyderabad, india, january 13-16, 2006, proceedings, part ii in this paper, a new threshold correction method for document image binarization that is forcused on ruled-line extraction is presented. this method enhances the binary image of a ruled line, which is often adversely influenced by adjacent text pixels or background noise. the threshold correction method consists of two submethods. one is a noise reduction method that is based on background determination, and the other is a threshold surface conversion method. both these methods use the aspect of local straightness feature to distinguish ruled-line pixels from background pixels.
computer vision - accv 2007, 8th asian conference on computer vision, tokyo, japan, november 18-22, 2007, proceedings, part i visual tracking could be formulated as a state estimation problem of target representation based on observations in image sequences. approaching visual tracking problem in the bayesian filter framework, how to sample the state evolution model to generate hypothesis of high confidence level is a critical factor. in this paper, we introduce an interacting multiple model estimation (imme) framework for adaptive visual tracking. the essence of the imme framework is that the state is estimated by integrating several different models in parallel and by interacting among those models' estimates probabilistically. based on the imme framework, we propose a new variation of particle filter named interacting multiple model particle filter (immpf), in which the hypotheses can be sampled from several different state evolution models adaptively. experiments show that, when compared with the standard particle filter, the immpf generates better hypotheses resulting in better tracking results, especially when the target behaves along several motion modes randomly.
computer vision - accv 2007, 8th asian conference on computer vision, tokyo, japan, november 18-22, 2007, proceedings, part ii we address the problem of bandwidth selection in mls surfaces. while the problem has received relatively little attention in the literature, we show that appropriate selection plays a critical role in the quality of reconstructed surfaces. we formulate the mls polynomial fitting step as a kernel regression problem for both noiseless and noisy data. based on this framework, we develop fast algorithms to find optimal bandwidths for a large class of weight functions. we show experimental comparisons of our method, which outperforms heuristically chosen functions and weights previously proposed. we conclude with a discussion of the implications of the levin's two-step mls projection for bandwidth selection.
robust 3d face recognition based on rejection and adaptive region selection. in this paper, we propose an effective fingerprint matching algorithm based on ridge count matching and minutiae subset combination. in the algorithm, the orientation-based ridge patterns are first utilized to remove the spuriously matched minutiae pairs. then the reliable ridge counts between every two minutiae are estimated to improve the minutiae relationship, and finally the matched minutiae subsets corresponding to different alignments are selectively combined to reduce the influence caused by distortions in fingerprints. experimental results on nist-4 show that our method achieves a much better matching performance
gradient vector flow over manifold for active contours. in this paper, we propose a moving object extraction technique for mpeg coded data directly. it is a change-based motion object extraction approach, which discriminates background and moving objects by means of the higher-order statistics (hos) performed on the interframe differences of dc image. the dc image is partly decoded picture from the compressed video for the rapid reconstruction of image data. in order to employ an optimal threshold in moving object detection stage, the background is detected by the moment-preserving thresholding technique for each frame. based on the background statistic, the proportion of background variance is employed to extract the final object mask by comparison with the fourth moment measure and the variance. experimental results have demonstrated that the proposed approach worked efficiently and showed a robust result for object extraction in compressed video.
learning logic rules for scene interpretation based on markov logic networks. artificial intelligence technique namely artificial neural network (ann) was used to describe the enzymatic kinetics of cellulose hydrolysis in a heterogeneous system, and compared with response surface methodology (rsm). three hydrolysis conditions (activity of added cellulase, substrate concentration and time) served as the input of the neural network model, and the glucose content served as the output. the experimental data from box-behnken design were used to train the neural network using the back propagation algorithm. the others of 33 design were used to check the performance of the trained network. the ann modelled and predicted values showed better agreement with the experimentally reported ones than rsm. ann could mimic the heterogeneous enzymatic hydrolysis of cellulose.
a statistical-structural constraint model for cartoon face wrinkle representation and generation. canetti, goldreich, goldwasser, and micali (stoc 2000) introduced the notion of resettable zero-knowledge proofs, where the protocol must be zero-knowledge even if a cheating verifier can reset the prover and have several interactions in which the prover uses the same random tape. soon afterwards, barak, goldreich, goldwasser, and lindell (focs 2001) studied the closely related notion of resettable soundness, where the soundness condition of the protocol must hold even if the cheating prover can reset the verifier to have multiple interactions with the same verifier's random tape. the main problem left open by this work was whether it is possible to have a single protocol that is simultaneously resettable zero knowledge and resettably sound. we resolve this question by constructing such a protocol. at the heart of our construction is a new non-black-box simulation strategy, which we believe to be of independent interest. this new strategy allows for simulators which "marry'' recursive rewinding techniques (common in the context of concurrent simulation) with non-black-box simulation. previous non-black-box strategies led to exponential blowups in computational complexity in such circumstances, which our new strategy is able to avoid.
human action recognition using pyramid vocabulary tree. a new block detection receiver is presented for noncoherent orthogonal cdma (such as the cdma is-95a reverse link). this new receiver uses multiple hadamard (or walsh) codes for joint detection instead of using a single walsh code as conventional receivers do. the simulation results show that the new block detection receiver is significantly better than the conventional non-block detection receivers in both additive white gaussian noise and flat rayleigh fading channels. a reduced-complexity algorithm for the block detection is also presented with significant complexity reduction and negligible performance degradation
perception-based lighting adjustment of image sequences. one of the main problems that arises when using gene expression programming (gep) conditions in learning classifier systems is the increasing number of symbols present as the problem size grows. when doing model-building lcs, this issue limits the scalability of such a technique, due to the cost required. this paper proposes a binary representation of gep chromosomes to palliate the computation requirements needed. a theoretical reasoning behind the proposed representation is provided, along with empirical validation.
scalable image retrieval based on feature forest. raid storage systems using scsi and traditional disk drives cannot meet the growing demand of new i/o intensive applications. new technologies such as smart disks and ssa are being proposed to improve the performance, scalability, and reliability of raid systems. the objective of this work is to investigate the impact of smart disks and ssa's spatial reuse property on the performance of raid-5 storage systems. in order to perform this work, we have enhanced cmu's raidframe simulator so that it accurately models the overhead of current scsi and ssa protocols, and we have created smart disk models which include on-drive xor logic and on-drive caches. we observe that neither smart disks alone nor spatial reuse property alone has much impact on raid system performance. however, if smart disks and spatial reuse property are properly used in combination, raid-5 system performance and scalability can be further enhanced. in particular, we propose a parity caching approach to improve the performance of small writes
an effective segmentation for noise-based image verification using gamma mixture models. with the wide adoption of open grid services architecture (ogsa) and web services resource framework (wsrf), the grid is emerging as a service-oriented computing infrastructure for engineers and scientists to solve data and computationally intensive problems. it is envisioned that computing resources in a future grid environment will be exposed as services. service discovery becomes an issue of vital importance for a wider uptake of the grid. this paper presents rssm, a rough sets based service matchmaking algorithm for service discovery with an aim to tolerate uncertainty in identifying service properties. the evaluation results show that the rssm algorithm is more effective in service discovery compared with other mechanisms such as uddi and owls.
color correction and compression for multi-view video using h.264 features. the metal implants have been widely used for the human skeleton in dental, maxillofacial and orthopedic treatments for many years. the main function of the implant is to reinforce the fractured bone or provide a direct attachment for a prosthetic limb. the mechanical based orthopedic fixation normally uses a self-tapping implant to provide connectivity between fractured bones. in such a system, the integration between bone and implant is normally based on a biology process called osseointegration. however, the implantation process courses temperature elevation at the bone-implant interface. clinically the high interfacial temperature affects regeneration of bone tissue and ultimately the osseointegration between implant and bone. in order to investigate the temperature elevation at the bone-implant interface, the authors developed a designated instrument system and special self-tapping implant with k type thermocouples placed close to the outer surface inside the implant. the experiments were carried out using re-hydrated human femurs while the implant was screwed into the femur. in this study, the temperature elevation was investigated using different implant diameters, insertion distances and speeds. the experiments were performed at the operation room temperature 21degc and the recorded peak temperature was 47.2degc. the result showed that there was a considerable temperature increase at the bone-implant interface while a self-tapping implant was inserted.
refined exponential filter with applications to image restoration and interpolation. today's communication-based applications are mostly crafted in a stovepipe development paradigm, which is inflexible to be used by various domain-specific applications and costly in the development phase. in a previous paper, we proposed a new design called cvm (communication virtual machine) to overcome these problems by having a high-level api which can be reused and extended easily for user-centric applications in any domain. within cvm framework, we came across a practical issue, which is actually the case for any end- to-end multimedia communication, namely the nat-traversal (network address translation) problem that limits the reliability and availability of cvm and variants of cvm. in this paper, we explain about the necessity of self-configuration for the nat-traversal problem in end-to-end communications, and propose a solution within the core cvm framework.
a scalable algorithm for learning a mahalanobis distance metric. the results of simulating past and future mass balances suggest that the bering glacier will lose significant ice mass and that the hubbard glacier will grow more slowly in the near future than in the recent past
co-occurrence random forests for object localization and classification. proposed for mpcs, rdt has already been proved to support better performances than most of the direct network, such as smaller diameter based on its vector routing algorithm, smaller degree, embedded mesh/torus topology, etc. it gives a network form method to form groups of networks with recursively structured torus/torus-like networks. a rdt structure can be formed with the method and its related parameters. after analyzing its performance by the average distance, the descending vector routing reducing redundant computations and the fault-tolerant routing algorithm are proposed. a simpler structure named rdt(2,2,1)/a are proposed for the parallel systems with no more than 5000 nodes and given its performance evaluation. considering the structure features of the practical rdts, they are suitable for the interconnection network of an noc design. the design of laying out rdt(2,2, 1)/a is proposed and proved to be available
beyond pairwise shape similarity analysis. it is known that the execution of programs exhibits repetitive phases; in other words, the execution of programs can be partitioned into segments of execution, during which the application exhibits unique architectural properties. this property has been used for various optimization goals. in addition, phase information is utilized to reduce the run time of the architectural simulation. conventionally, an application is examined in an architecture-independent manner (such as the number of times a basic block is executed) to extract information about the phases and then only the representative execution intervals are executed to analyze architectural choices. we claim that such approaches are becoming inadequate in the many-core era as application execution is not dominated by the instructions only, but instead the communication structure of the application is becoming as important as the instruction behavior. hence, we propose to utilize communication behavior to determine the phases of an application. our results reveal that the inclusion of the communication information can increase the accuracy of the phase detection significantly. specifically, for splash2 and mine-bench applications, the average (geometric mean) cpi error rate with the instruction-based phase detection is 11.01%, while our phase detection scheme has an average error rate of 3.41% when compared to the simulations that run the applications to completion.
computer vision - accv 2009, 9th asian conference on computer vision, xi'an, china, september 23-27, 2009, revised selected papers, part i in this paper we propose an individualized 3d facial model constructed from the anatomical perspective for realistic facial expression synthesis. our model incorporates a physically-based approximation to facial skin tissue, a set of anatomically-motivated facial muscle actuators and underlying skull structure. the skin is modeled as a multi-layer mass-spring lattice by taking into account the nonlinear stress-strain relationship of the real skin. the 3d face model incorporates a skull structure which extends the scope of facial motion and facilitates facial muscle definition. the automatic facial muscle construction is achieved by using an efficient muscle mapping approach that ensures different muscles to be located at the anatomically correct positions between the skin and skull layers. for computational efficiency, we devise a semi-implicit integration method to numerically solve the governing dynamics. the dynamic facial animation algorithm runs at an interactive rate with realistic facial expressions to be synthesized.
an improved template matching method for object detection. digital documents are easily copied and distributed ille- gally. document copy detection is a powerful tool to pro- tect the author's intellectual property and to improve the efficiency of information retrieval. it is difficult for the ex- isting copy detection systems to identify the sentence struc- ture changed copies. to address the problem, we research the semantic level of natural language processing and pro- pose a document copy detection method based on chinese semantic knowledge. we introduce the realization mecha- nisms of chinese language analysis, which contains syn- tactic parsing and semantic analyzing. we also report on the experimental comparison the proposed method with the representative document copy detection systems. the result is satisfying.
gait recognition using procrustes shape analysis and shape context. wireless sensor networks (wsns) deployed for mission-critical applications face the fundamental challenge of meeting stringent spatiotemporal performance requirements using nodes with limited sensing capacity. although advance network planning and dense node deployment may initially achieve the required performance, they often fail to adapt to the unpredictability of physical reality. this paper explores efficient use of mobile sensors to address the limitations of static wsns in target detection. we propose a data fusion model that enables static and mobile sensors to effectively collaborate in target detection. an optimal sensor movement scheduling algorithm is developed to minimize the total moving distance of sensors while achieving a set of spatiotemporal performance requirements including high detection probability, low system false alarm rate and bounded detection delay. the effectiveness of our approach is validated by extensive simulations based on real data traces collected by 23 sensor nodes.
computer vision - accv 2009, 9th asian conference on computer vision, xi'an, china, september 23-27, 2009, revised selected papers, part ii the transmission delays in the networked control systems are inevitable and can degrade the system's performance or stability. this paper has proposed an r-suboptimal hinfin controller for networked control systems with model uncertainty and network induced delay which is longer than one sampling period. the closed-loop system with structured uncertainties and long transmission delay is asymptotically stable. simulation is applied to numerical examples with networked control show that the proposed method works well.
finger-vein recognition based on a bank of gabor filters. although fuzzy logic has been successfully applied in many different problem domains, fuzzy solutions typically structure the problem task as one of static categorisation. this may not be appropriate for dynamic systems, especially where higher-order information is unavailable. the paper proposes an approach to reasoning about dynamic systems drawing upon the first-order approach to temporal logic. a brief overview of the classical theory is provided and extended to a fuzzy theory modelling the inherent vagueness of linguistic terms such as "recently". the notion of a temporal qualification is developed as a domain independent method for augmenting base domains and term set of a linguistic variable. such extended variables are termed temporal linguistic variables. the technique is then applied to a simple dynamic system highlighting its advantage over traditional approaches. since temporal linguistic variables are a special case of linguistic variable they are immediately applicable in fuzzy knowledge based system and machine learning contexts
a novel visual organization based on topological perception. with 3d (3-dimensional) movement's ability and rhythmic locomotion mode, a nature snake makes itself survive in rugged terrains. the rhythmic activities of most creatures are generated by the cpg (central pattern generator). based on this fact, the sustained-type neuron has been adopted to construct a cyclic inhibitory cpg model for a snake-like robot whose joints are perpendicularly connected in series. having compared with the sustained-type neuron and the mutual inhibitory cpg, the cyclic inhibitory cpg was proven to generate capably rhythmic output with the least number of differential equations. in this paper, we introduce the neuron network organized by the cyclic inhibitory cpgs connected in line with unilateral excitation to control the 3d locomotion of a snake-like robot, and present the necessary condition for the cpg neuron network to sustain a rhythmic output. by implementing this control architecture to a simulator with consideration of mechanical dynamics of a real snake-like robot "perambulator", preliminary parameter setting of the cpg neuron network for its 3d locomotion is obtained. moreover, it is shown that "perambulator" can successfully exhibit 3d locomotion by using the output of the proposed cpg network. the obtained results have also provided a bran new approach to understand the unknown neuron network of nature snakes
head pose estimation based on manifold embedding and distance metric learning. this paper proposes a visual cognitive neural network for automatic object searching and locating. the model consists of two sub-networks. one is a visual perceiving network, which simulates human eyes to input image signals and recognize an object's direction and distance in terms of a high-level perceiving neuron's maximum response. the other one is an eyeball-motion controlling network, which simulates that human brain's high-level perceiving neurons transfer their responses to eyeball-motion controlling muscle cells to change eye's gaze to the position of the object that the perceiving system is attentive to or interested in. the system is applied to human face features searching and experiments show a promising result.
an online framework for learning novel concepts over multiple cues. in this paper, a discriminative manifold learning method for face recognition is proposed which achieved the discriminative embedding the high dimensional face data into a low dimensional hidden manifold. unlike the recently proposed lle, isomap and eigenmap algorithms, which are based on reconstruction purpose, our method uses the rca algorithm to achieve nonlinear embedding and data discrimination at the same time. also, the lle and isomap algorithms are crucially depends on the appropriateness of the neighborhood construction rule, in this paper, a ck-nearest neighborhood rule is proposed to achieve better neighborhood construction. experimental results indicate the promising performance of the proposed method.
evolving mean shift with adaptive bandwidth: a fast and noise robust approach. subspace clustering is one of the best approaches for discovering meaningful clusters in high dimensional space. one cluster in high dimensional space may be transcribed into multiple distinct maximal clusters by projecting onto different subspaces. a direct consequence of clustering independently in each subspace is an overwhelmingly large set of overlapping clusters which may be significantly similar. to reveal the true underlying clusters, we propose a similarity measurement of the overlapping clusters. we adopt the model of gaussian tailed hyper-rectangles to capture the distribution of any subspace cluster. a set of experiments on a synthetic dataset demonstrates the effectiveness of our approach. application to real gene expression data also reveals impressive meta-clusters expected by biologists.
visual saliency based on conditional entropy. this paper analyses the defect of the designing model of load balancing in hybrid p2p network, and proposes a new strategy of scheduling for load balancing, which based on culture algorithm of multilayer belief spaces. according to the current load status of each super-node in the system, it can calculate its load weight of the next time section by using the cultural algorithm, and assign the current requests of login with weighted round-robin. the extracted knowledge which is got by selecting the best belief space from the multilayer belief space is used to optimize the constrains of the evolutionary, in order to accelerate the optimization process of the calculation of load weight. simulation experiments show that the allocation of login request to each node is to be balance much faster through using of cultural algorithm based on multilayer belief spaces.
image-set based face recognition using boosted global and local principal angles. semantics-preserving dimensionality reduction refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encountered in many areas such as machine learning, pattern recognition, and signal processing. this has found successful application in tasks that involve data sets containing huge numbers of features (in the order of tens of thousands), which would be impossible to process further. recent examples include text processing and web content classification. one of the many successful applications of rough set theory has been to this feature selection area. this paper reviews those techniques that preserve the underlying semantics of the data, using crisp and fuzzy rough set-based methodologies. several approaches to feature selection based on rough set theory are experimentally compared. additionally, a new area in feature selection, feature grouping, is highlighted and a rough set-based feature grouping technique is detailed.
estimating human pose from occluded images. computed prediction represents a major shift in learning classifier system research. xcs with computed prediction, based on linear approximates, has been applied so far to function approximation, to single step problems involving continuous payoff functions, and to multi step problems. in this paper we take this new approach in a different direction and apply it to the learning of boolean functions - a domain characterized by highly discontinuous 0/1000 payoff functions. we also extend it to the case of computed prediction based on functions, borrowed from neural networks, that may be more suitable for 0/1000 payoff problems: the perceptron and the sigmoid. the results we present show that xcsf with linear prediction performs optimally in typical boolean domains and it allows more compact solutions evolving classifiers that are more general compared with xcs. in addition, perceptron based and sigmoid based prediction can converge slightly faster than linear prediction while producing slightly more compact solutions
temporal-spatial local gaussian process experts for human pose estimation. in this paper, we analyze the system and channel characteristic based on multi-band orthogonal frequency division multiplexing (mb-ofdm) ultra wide-band (uwb), and propose the corresponding improved channel estimation and tracking algorithms. the proposed channel estimation algorithm which is based on the improved dft algorithm is quite suitable for the low snr environment. it conditionally cuts the paths with little energy within the window, then decreases the infection caused by noise. the proposed channel tracking algorithm aimed at the considerable performance damage coursed by frequency offset conquers the sparseness of pilots, tracks and corrects the amplitude attenuation and phase rotation coursed by frequency offset. the simulation between improved and traditional algorithms is carried out and the results show that better performance can be achieved.
robust focal length estimation by voting in multi-view scene reconstruction. collaborative design and application integration emphasize the demand for database security. database encryption is widely adopted to ensure data privacy, which can prevent attacks from both outside intruders and inside malicious users. current researches on this area are mainly focusing on encryption algorithms, key management and encryption efficiency. however, data sharing nature of database system is usually neglected. in this paper, we propose an access control model, 3s-rbac, which enables data sharing while guaranteeing privacy. the model has many features: the novel concept of strong permission and weak permission; the hierarchy of database objects and keys; the permission and key inheritance; the binding of keys and permissions. implementation in oscar secure dbms shows that the model is flexible, secure, practical, and can be integrated easily into existing enterprise applications
manifold estimation in view-based feature space for face synthesis across poses. in this paper, we propose a novel spatial autocorrelation model of the shadow fading process in urban macro environments. the proposed model is based on the empirical results obtained from extensive wideband radio channel measurement campaigns at 2.35 ghz in an urban area of a typical medium-sized chinese city. the shadow fading component was extracted assuming a single-slope log-distance path loss model. the consistency with the level crossing theory of gaussian processes is achieved by an implicit constraint on the parameters of the model. the proposed model gives a better fit to the empirical results in individual measurement routes than the widely reported exponential and double exponential models. an heuristic explanation of the proposed autocorrelation property is also presented.
learning group activity in soccer videos from local motion. hybrid wireless-optical access network (woan) is a newly emerged network which integrates passive optical networks (pons) and wireless mesh neworks(wmns) to provide the ubiquitous, high bandwidth last mile internet access. in woan, transmission delay for traffic up to the internet consists of wireless path delay in wmns and waiting delay at onus due to the tdma schedule. the onu from which transmission delay is minimal is chosen to be the destination for traffic and the minimal transmission delay is defined as delay bound. in the paper, we intend to find the wireless path to the destinated onu with path delay no more than delay bound and meanwhile with the minimal maximal link delay, which is defined as interference aware and delay bounded routing (iadbr) problem. we propose both centralized and distributed algorithms to solve iadbr. simulation results show that the distributed algorithm performs quite closely to the optimal centralized algorithm and performs much better than the shortest path algorithm.
clustering-based descriptors for fingerprint indexing and fast retrieval. a high fault detection coverage is very critical for systems with ultra-safe requirements and fault injection is an effective technique for estimating the coverage. one difficulty of fault injection lies in the huge number of injections that need to be carried out in order to obtain statistically significant results. fault expansion has been proposed as a means of reducing the number of injections by dividing faults into equivalence classes. we show that this intuitively appealing approach is only effective when each fault equivalence class is a significant portion of the fault population
level set segmentation based on local gaussian distribution fitting. we present an algebraic approach to multibody motion segmentation from line correspondences. given three perspective views containing multiple linearly moving objects, we demonstrate that after applying a polynomial embedding to the line correspondences, they became related by the so-called multibody line constraint of translational motions. we show how to linearly estimate the multibody trifocal epipole from line-line-line correspondences. the individual trifocal epipoles are then obtained from the derivatives of the multibody line constraint (up to an unknown factor). given normalized trifocal epipoles, we can use any special clustering technique to obtain the clustering of the motions and the correspondences. the limitations of the proposed algorithm are also discussed. experimental results on synthetic and real dynamic scenes are presented.
natural image segmentation with adaptive texture and boundary encoding. this paper proposes the ssoa (semantic service-oriented architecture) based on formal and distributed ontologies, and the knowledge base framed by ontology and the fuzzy reasoning system oriented to agent cognition are considered to prescribe and treat the uncertainty of agent cognizing. the ssoa includes two essential components: knowledge base supported by formal ontology and agent-oriented fuzzy reasoning system. first, knowledge base framed by formal ontology builds a concept hierarchy organized by inclusion relation, and uses those concepts to describe specific objects to form assertions of an application domain. agent-oriented fuzzy reasoning system then incorporates plausibility degree into assertions of certain agent, and the alphabet of symbols, well-formed formulas, axioms and inferences rules are constructed respectively. the ssoa architecture constructs a fundamental for services interaction and composition automatically under open environment.
human action recognition under log-euclidean riemannian metric. location information should be verifiable in order to support new computing and information services. in this paper, we adapt the classical challenge-response method for authentication to the task of verifying an entity's location. our scheme utilizes a collection of transmitters, and adapts their power allocations to verify a user's claimed location. this strategy, which we call power-modulated challenge response, is able to be used with existing wireless sensor networks, and we present three variations. first, we propose a direct method, where some transmitters are selected to send "challenges" that the claimant node should be able to witness based on its claimed location, and for which the claimant node must correctly respond in order to prove its location. second, we reverse the strategy by presenting an indirect method, where some transmitters send challenges that the claimant node should not be able to witness. finally, we present a signal strength based method, where the node responds with its received signal strength and thereby provides improved location verification. to evaluate our schemes, we examine different adversarial models for the claimant, and characterize the performance of our power-modulated challenge response schemes under these adversarial models.
a novel hierarchical model of attention: maximizing information acquisition. in this paper, we proposed an automatic method to segment text from complex background for recognition task. first, a rule-based sampling method is proposed to get portion of the text pixels. then, the sampled pixels are used for training gaussian mixture models of intensity and hue components in hsi color space. finally, the trained gmms together with the spatial connectivity information are used for segment all of text pixels form their background. we used the word recognition rate to evaluate the segmentation result. experiments results show that the proposed algorithm can work fully automatically and performs much better than the traditional methods.
categorization of multiple objects in a scene without semantic segmentation. compositional modelling (cm) has been applied to synthesize automatically plausible scenarios in many problem domains with promising results. however, it is assumed that the generic and reusable model fragments within the knowledge base can all be expressed by precise and crisp information. this paper presents an initial attempt to extend the existing cm work to allow the generation of scenario spaces which are capable of representing, storing and supporting inference about imprecise or ill-defined data, by the use of fuzzy sets. a knowledge representation formalism for both fuzzy parameters and fuzzy constraints is incorporated into the representation of conventional model fragments. the applicability of the proposed method is illustrated by means of a simple worked example for supporting crime investigation.
image enhancement of low-light scenes with near-infrared flash images. we propose a practical and secure electronic voting protocol for large-scale online elections. our protocol satisfies a large set of important criteria that has never been put together in a single protocol before. among all electronic voting schemes in the literature, sensus, a security-conscious electronic voting protocol proposed by cranor and cytron (1997), satisfies most of our criteria. sensus has been implemented and used in mock elections. however, sensus suffers from several major drawbacks. for instance, we show that even if all voters follow the sensus protocol honestly, some voters' votes may still be replaced with different votes without being detected. our protocol overcomes these drawbacks
efficient partial shape matching of outer contours. we present netspy, a tool to automatically generate network-level signatures for spyware. netspy determines whether an untrusted program is spyware by correlating user input with network traffic generated by the untrusted program. if classified as spyware, netspy also generates a signature characterizing the malicious substrate of the spyware's network behavior. such a signature can be used by network intrusion detection systems to detect spyware installations in large networks. in our experiments, netspy precisely identified each of the 7 spyware programs that we considered and generated network-level signatures for them. of the 9 supposedly-benign programs that we considered, netspy correctly characterized 6 of them as benign. the remaining 3 programs showed network behavior that was highly suggestive of spying activity
3d motion segmentation using intensity trajectory. in this paper, we carry out a study on the rns (residue number system) application in digital image processing and propose a rns image coding scheme that offers high-speed and low-power vlsi implementation for secure image processing. the proposed scheme is more efficient than the rns image coding scheme of ammar et al. (2001) in that the proposed method encrypts the entire image and does not require any additional component other than a standard rns system. further, the proposed scheme is based on the modified crt and its associated residue-to-binary conversion and moduli selection methods and is more efficient than the scheme by ammar et al. (2001) in terms of vlsi implementation. the design of an encoder and decoder pair for the greyscale image is carried out using matlab tool and some vlsi tools. the preliminary results of the matlab simulation demonstrate the security ability of the proposed image coding scheme.
mean-shift object tracking with a novel back-projection calculation method. multicore architectures, which have multiple processing units on a single chip, are widely viewed as a way to achieve higher processor performance, given that thermal and power problems impose limits on the performance of single-core designs. accordingly, several chip manufacturers have already released, or will soon release, chips with dual cores, and it is predicted that chips with up to 32 cores will be available within a decade. to effectively use the available processing resources on multicore platforms, software designs should avoid co-executing applications or threads that can worsen the performance of shared caches, if not thrash them. while cache-aware scheduling techniques for such platforms have been proposed for throughput-oriented applications, to the best of our knowledge, no such work has targeted real-time applications. in this paper, we propose and evaluate a cache-aware pfair-based scheduling scheme for real-time tasks on multicore platforms
combining discriminative and descriptive models for tracking. we introduce a social network analysis method as a new approach to build an intrusion detection system (sn-ids) in ad hoc networks. the sn-ids utilizes social relations as metrics-of-interest for anomaly detections, which is different from most traditional ids approaches. to construct proper social networks, we first investigate ad hoc mac and network layer data attributes and select relevant social feature sets; then we build up a set of socio-matrices based on these features. social analysis methods are applied to these matrices to detect suspicious behaviors of mobile nodes. ns-2 simulation results show that this sn-ids system can effectively detect common attacks with high detection rates and low false positive alarm rates. furthermore, it has clear advantages over the conventional association rule based data mining ids in terms of computation and system complexity.
3d reconstruction of human motion and skeleton from uncalibrated monocular video. soft-decision decoding of a linear block code using the most reliable basis corresponding to each received word is investigated. based either on probabilistic properties or on the structure of the code considered, three improvements to the algorithm devised by fossorier and lin (see ibid., vol.41, no.9, p.1379-1396, 1995) are presented. these modifications allow large computation savings or significant decoding speedup with little error performance degradation. first, a reduced probabilistic list of codeword candidates is associated with order-i reprocessing of a given code. it results in a large reduction of the maximum number of computations with a very small degradation in performance. then, a probabilistic stopping criterion is introduced for order-0 reprocessing. this new test significantly decreases the average number of computations when appropriately implemented. finally, the application of the algorithm to coset decoding is considered for |u|u+v| constructed codes. in addition to the conventional coset decoding, a new adaptive practically optimum coset decoding method is presented where at each reprocessing stage, the number of surviving cosets decreases. suboptimum closest coset decoding is also investigated. it is shown that two-stage decoding with the algorithm of fossorier and lin offers a large variety of choices, since the reprocessing order of each stage can be determined independently
multiple view reconstruction of a quadric of revolution from its occluding contours. support vector machine (svm) is a new sort of machine learning method based on structure risk minimization (srm) principle, which has high generalization capability. many problems with small samples, nonlinearity or high dimension in pattern recognition could be solved by the method. in this paper, the traffic data on freeway were taken as research objects and an information fusion algorithm based on svm about freeway incident detection was proposed. a svm was trained and tested using the data obtained from the simulation under the condition of incident and non-incident. compared with the multi-layer feed forward neural network (mlf) algorithm trained with the same data, the simulation results showed that the svm offers a lower misclassification rate, higher correct detection rate and lower false alarm, and it can improve the detection performance
interactive shadow removal from a single image using hierarchical graph cut. we examine the coding problem of base layer (bl) in fine granularity scalable videos and rate adaptation of enhancement layer (el) during streaming in order to support constant quality streaming. the problem arises from the facts that different frames of bl often exhibit significant quality variation in the usual fgs bl encoding methods, and consequently the actual el rate-distortion (r-d) curves of different frames present significant difference. under this condition it would be computationally exhaustive to scale the el to flatten out the fluctuating bl quality and to attain constant quality. we propose, in this paper, an accurate constant quality encoding method of bl, under which we investigate the similarity of actual el r-d curves, and then a simple but effective weight-based el rate allocation algorithm is introduced. experiments show, compared with default methods, our fast and simple methods not only provide constant-quality streaming, but also decrease the average mse of videos.
a shape derivative based approach for crowd flow segmentation. more and more softwares based on web service technologies are developed. before their releases on the internet, it is necessary to evaluate these systems' performance, especially their response time under different workload pressures. however, existing performance testing benchmarks and tools for web service applications are difficult to adapt to various user-specific testing purposes. this paper proposes a configurable web service performance testing framework which contains client module, application server module and database module. client module, by using the network cooperation method that one central client drives several other clients, adapts to a great number of concurrent customers to request web services. application server module contains web services under testing and external supporting web services, each of which is configured as a plug-in. the process to realize mixed ratio of web service interactions is similar to dealing cards and adapts to different commercial application characteristics. in database module, the data model including table and attribute dependence can be customized, and the data scale initialization can be resized according to the topology of above dependence. as such, this framework allows testers to dynamically define their data model, customize their scale of database, configure their transaction characteristics, deploy their application strategies and confirm their performance metrics..
incorporating spatial correlogram into bag-of-features model for scene categorization. a reconfigurable modular snake robot has been developed, which can not only move on a plane but also achieve some 3-dimensional motions while reconfigured. control equations of 3-dimensional locomotion were established by the composition of two bending motions in mutual orthogonal plane. three types of lateral rolling locomotion, flapping, linear rolling and curved rolling, were achieved by controlling the amplitudes and the number of two waves in the two bending motions. using the three types of locomotion the snake robot can realize net lateral translation, alternation of its contact base and rolling over some obstacles. the lateral rolling locomotion obtains its driving force through the interaction with the environment the rolling shape and its direction depend on the transferring direction and phase difference of the two waves respectively.
towards robust object detection: integrated background modeling based on spatio-temporal features. we present a new algorithm for the automatic recovery of tag grid-line intersections in tagged mr images of the left ventricle of the heart. our method uses an active spring mesh to capture local properties of the motion and a global motion model to capture the global coherence of the motion. we recover the global component of the motion using robust estimation. different motion models have been developed for short and long axis views of the heart. the algorithm has been tested on healthy and pathological data
vehicle headlights detection using markov random fields. sign language is the primary modality of communication among deaf and mute society all over the world. this paper proposes a viewpoint independent method for sign recognition. considering that two sequences of the same sign can be roughly considered as the input of a stereo vision system after time-warping, and the fundamental matrix associated with two views should be unique, we can convert the temporal-spatial recognition task as a verification task within a stereo vision framework. after time-warping of the input sequences, the proposed framework can reach both temporal and viewpoint invariance. we demonstrate the efficiency of the proposed framework by recognizing a vocabulary of 100 words of chinese sign language. the recognition rate is up to 97% at rank 3. furthermore, the proposed framework can be easily extended to other recognition tasks, such as gait recognition and lip-reading recognition.
multilevel algebraic invariants extraction by incremental fitting scheme. this paper give the applications of safety audit and monitor technology in power management system. this paper first introduce the audit technology and its working environment and then introduce the elopements of the system which including the design of monitoring module in proxy and network capability, etc. and it also proposes the implement flow of these function models including the implement flow of security audit model and network monitoring model, it also gives the design and realization of ip address peculate model and monitoring module in proxy.
support aggregation via non-linear diffusion with disparity-dependent support-weights for stereo matching. in this paper we put forward a method to animate an arbitrary topology facial model (atfm) based on the mpeg-4 standard. this paper deals mainly with the problem of building the facedeftables, which play a very important role in the mpeg-4 based facial animation system. the facedeftables for our predefined standard facial model (sfm) are built using the interpolation method. since the facedeftables depend on facial models, the facedeftables for the sfm can be applied only to those facial models having the same topology as the sfm. for those facial models that have different topology, we have to build the facedeftables accordingly. to acquire the facedeftables for atfm, we first select feature points on atfm, then transform the sfm according to those feature points. finally, we project each vertex on the atfm to the transformed sfm and build the facedeftables for the atfm according to the projection position. with the facedeftables we built, realistic animation results have been acquired.
distance-based multiple paths quantization of vocabulary tree for object and scene retrieval. many media access control (mac) protocols for wireless sensor networks (wsns) such as sensor mac (s-mac) and carrier sense multiple access with minimum preamble sampling (csma-mps) exploit listen/sleep cycles to conserve energy. the cycles of nodes influence the network performances such as energy efficiency, packet latency and throughput in wsns. in this paper, an adaptive schedule medium access control (as-mac) for wsns is presented. as-mac introduces the adaptation of the cycles in mac layer to the data traffic. the effect of the protocol is that it can decrease the latency, improve the throughput and energy efficiency when traffic is dynamic. we also compare as-mac with s-mac and csma-mps through simulations and the results show it has better performances than the former protocols.
from ramp discontinuities to segmentation tree. this study was designed to elucidate the problem-solving skills used by frequent and infrequent chinese video game players to negotiate impasses encountered while playing video game. all participants were instructed to think aloud while playing a video game for 20 consecutive minutes. comments were made with thinking aloud. findings showed that frequent players made significantly greater reference to insight and game strategies than infrequent players. after reaching an impasse, all players also were most likely to comment on their game progress and potential game strategies to use. over the course of game play, there are some cross cultural differences were founded.
fabric defect detection and classification using gabor filters and gaussian mixture model. radar signal sorting is picking-up pulse serial of same radar emitter from dense complex pulse signal flow. the tolerance of radar signal sorting is analyzed in modern electronic warfare. the complex and dense pulses environment makes it become a vital factor to restrict the efficiency of sorting of the conventional multi-parameters signal sorting system. a segment clustering radar signal sorting method is presented based on support vector clustering (svc) according to the idea of statistics learning theory. it prevents tolerance from affecting radar sorting. the accuracy of sorting and the sensitivity of algorithm on parameter variation is analyzed. the experimental results show that the sorting method presented is effective to overcome the tolerance of radar signal sorting.
spectral graph partitioning based on a random walk diffusion similarity measure. fine-grained access controls for xml define access privileges at the granularity of individual xml nodes. in this paper, we present a fine-grained access control mechanism for xml data. this mechanism exploits the structural locality of access rights as well as correlations among the access rights of different users to produce a compact physical encoding of the access control data. this encoding can be constructed using a single pass over a labeled xml database. it is block-oriented and suitable for use in secondary storage. we show how this access control mechanism can be integrated with a next-of-kin (nok) xml query processor to provide efficient, secure query evaluation. the key idea is that the structural information of the nodes and their encoded access controls are stored together so the access privileges can be checked efficiently. our evaluation shows that the access control mechanism introduces little overhead into the query evaluation process.
human action recognition using hdp by integrating motion and location information. this paper presents a rate control scheme for h.264 by introducing the concept of basic unit and a linear prediction model. the basic unit can be a macroblock (mb), a slice, or a frame. it can be used to obtain a trade-off between the overall coding efficiency and the bits fluctuation. the linear model is used to solve the chicken and egg dilemma existing in the rate control of h.264. both constant bit rate (cbr) and variable bit rate (vbr) cases are studied. our scheme has been adopted by h.264.
automated center of radial distortion estimation, using active targets. a new reconfigurable planetary robot system (rprs) is introduced in this paper. the locomotion mechanism, especially the static force analysis and the climbing ability for different configurations of the multiple child-robots are presented in detail. the basic configurations of two child-robots systems were given in three modes: connecting in series with arm in front or back and combining to a loop with grasper. the simulation results of these three configurations based on static analysis demonstrate that the climbing ability is closely correlated to their configurations. compared the results, the conclusion can be obtained that the loop configuration has the best effect than others on slope climbing. the actual experiments of the child-robots system have illustrated the simulating results, and an exciting phenomenon has emerged, which shows that all the configurations can climb bigger gradient than the simulating results. the phenomenon rightly discloses the characteristic of the novel architecture of the child-robot.
an accelerated human motion tracking system based on voxel reconstruction under complex environments. load balancing is a key technique in parallel computer supported collaborative work (cscw) systems, parallel database system and p2p system for instance, to boost performance and improve scalability. in order to reduce total cost of ownership (tco), adaptive/self-tuning administration techniques are gradually and extensively expected in the cyberspace. in parallel database systems, adaptive load balancing techniques are proposed to face the change in data storage patterns and access patterns in a dynamic real environment. the techniques utilized in both shared-nothing and shared-disk parallel database systems are discussed, and a general flexible framework based on collaborative agents is studied to support these techniques in both architectures. the framework supports two kinds of load balancing - one is passively executing query statements balancedly, and the other one is proactively adjusting data placement and task execution scheme, by means of data and task migration, whenever load unbalance is detected. three categories of agents, scheduling agents, monitoring agents and task agents, are identified in the framework. the collaboration protocols and scheduling algorithms to support adaptive load balancing are described. the framework also applies to other parallel systems such as p2p systems and shared file processing systems due to their underlying commonness.
confidence-based color modeling for online video segmentation. an efficient and flexible coding technique is proposed in this paper inspired by the sp frame in the h.26l standard, which can achieve a drift-free bitstream switching at the predicted frame. the proposed scheme improves the coding efficiency of the sp frames in the h.26l standard by limiting the mismatch between the references for the prediction and reconstruction with two dct coefficient coding modes and the rate-distortion optimization. furthermore, the proposed scheme allows independent quantization parameters for up-switching and down-switching bitstreams. it further reduces the switching bitstream size while keeping the coding efficiency of the normal bitstreams. more rapid and frequent down-switching than up-switching and much smaller size of down-switching bitstream can be achieved with the proposed sp technique. these are very desirable features for any tcp-friendly protocols. compared with the original sp method for h.26l, the proposed sp method improves the coding efficiency up to 1.0 db. this sp technique has been officially accepted by the jvt standard.
single-camera multi-baseline stereo using fish-eye lens and mirrors. in this paper, we present a new speaker diarization system that improves the accuracy of traditional hierarchical clustering-based methods with little increase in computational cost. our contributions are mainly two fold. first, we include a preprocessing called "local clustering" before the hierarchical clustering algorithm to merge very similar adjacent speech segments. this local clustering aims to reduce the number of segments to be clustered by the hierarchical clustering, so as to dramatically increase the processing speed. second, we perform a postprocessing called "cross em refinement" to purify the clusters generated by the hierarchical clustering. this algorithm is based on the idea of cross validation and em algorithm. our experimental evaluations show that the proposed cross em refinement approach reduces the speaker diarization error by up to 56%, with an average reduction of 22% compared to the traditional hierarchical clustering method
moving object segmentation in the h.264 compressed domain. we have described the architecture of system r, including the relational data system and the research storage system. the rds supports a flexible spectrum of binding times, ranging from precompilmion of &#x201c;canned transactions&#x201d; to on-line execution of ad hoc queries. the advantages of this approach may be summarized as follows: 1. for repetitive transactions, all the work of parsing, name binding, and access path selection is done once at precompilation time and need not be repeated. 2. ad hoc queries are compiled on line into small machine-language routines that execute more efficiently than an interpreter. 3. users are given a single language, sql, for use in ad hoc queries as well as in writing pl/i and cobol transaction programs. 4. the sql parser, access path selection routines, and machine language code generator are used in common between query processing and precompilation of transaction programs. 5. when an index used by a transaction program is dropped, a new access path is automatically selected for the transaction without user intervention.
semi-supervised feature selection for gender classification. this paper proposes a new survivable algorithm named sub-path protection based on auxiliary virtual topology (spavt) to tolerate the single-link failure in wdm optical networks. according to the protection-switching time constraint, spavt constructs the virtual topology. then, it only needs to run one time of routing algorithm to find the feasible virtual route in virtual topology. simulation results show that spavt has smaller blocking probability and lower time complexity than conventional algorithms.
detecting spatiotemporal structure boundaries: beyond motion discontinuities. this paper proposes a method for matching road vehicles between two non-overlapping cameras. the matching problem is formulated as a same-different classification problem: probability of two observations from two distinct cameras being from the same vehicle or from different vehicles. we employ a measurement vector consists of three independent edge-based measures and their associated robust measures computed from a pair of aligned vehicle edge maps. the weight of each match measure in the final decision is determined by a unsupervised learning process so that the same-different classification can be optimally separated in the combined measurement space. the robustness of the match measures and the use of discriminant analysis in the classification ensure that the proposed method performs better than existing edge-based approaches, especially in the presence of missing/false edges caused by shadows and different illumination conditions, and systematic misalignment caused by different camera configurations. extensive experiments based on real data of over 200 vehicles at different times of day demonstrate promising results.
improved uncalibrated view synthesis by extended positioning of virtual cameras and image quality optimization. in this paper, a model and algorithm of optimum layout is proposed for blank layout of single pattern on single rectangular sheet. the approach arranges the cutting patterns on rectangular sheet in the typical style of double opposite layout (dol). the remains of the sheet, which has been left in one direction after arranging patterns, called as "step leavings" (sl) is considered while the optimum layout is discussed we make full use of material of the sheet, including the a in x-direction and y-direction, and set up a reasonable mathematical model for the two-dimensional optimum layout. a corresponding algorithm is also provided to work out the optimum layout quickly and automatically. in this way, we can get the best layout scheme to arrange the maximum shapes on the sheet.
tracking eye gaze under coordinated head rotations with an ordinary camera. in this paper, we treat multi-core processor design space exploration as an application-driven machine learning problem. we develop two machine learning-based techniques for efficiently exploring the processor design space. we observe that these techniques result in multi-core processors whose performance is comparable (within 1%) to a processor design that requires an exhaustive exploration of the design space. these techniques often take orders of magnitude (a factor of 3800 at the minimum) less time for coming up with these processors. the benefits are up to 13% over intelligent search techniques that have been adapted to do multi-core design space exploration. we leverage the knowledge gained in this research to develop magellan - a framework for accelerating multi-core design space exploration and optimization. magellan can be used to find the highest throughput processors of a given type for a given area, power, or time budget. it can be used to aid even experienced processor designers that prefer to rely on intuition by allowing fast refinements to an input design.
monocular template-based tracking of inextensible deformable surfaces under -norm. we propose a physically-based approach based on anatomical knowledge for real-time facial expression animation. the facial model incorporates a physically-based approximation to facial skin and a set of anatomically-motivated facial muscles. the skin is modeled by a mass-spring system with nonlinear springs which have a biphasic stress-strain relationship to simulate the elastic dynamics of real facial skin. facial muscles are modeled as forces deforming the spring mesh. based on the action units (aus) of the facial action coding system (facs), various expressions can be generated by a combination of contractions of a set of facial muscles. lagrangian mechanics governs the dynamics, dictating the deformation of the facial surface in response to muscle forces. simulation results show real-time facial deformation as well as realistic expression animation
a novel self-created tree structure based multi-view face detection. in this paper, we present an active volumetric model (avm) for 3d reconstruction from multiple calibrated images of a scene. the avm is a physically motivated 3d deformable model which shrinks actively under the influence of multiple simulated forces towards the real scene by throwing away some of its voxels. it provides a computational framework to integrate several constraints in an intelligible way. in the current work, we use three forces derived respectively from the smooth constraint, the compulsory silhouette constraint, and the color consistency constraint. based on the composition of the 3 forces, our algorithm can significantly restrain holes and floating voxels, which plague voxel coloring algorithms, and produce precise and smooth models. we test our algorithm by experiments based on both synthetic and real data.
heavy-tailed model for visual tracking via robust subspace learning. presented in this paper is the thread-associative memory microarchitecture for multicore and multithreaded processor design. memory contention among concurrent threads in chip multithreaded processing has become a limiting factor for performance improvement. the proposed thread-associative memory addresses this challenge by incorporating thread-specific information explicitly into on-chip memory hardware. the proposed technique can be utilized at different levels of memory hierarchy. furthermore, it is not just a technique for performance enhancement but also a solution for energy efficiency. trace-driven simulations on a 32kb l1 data cache demonstrate 36.6% maximum performance improvement and up to 15.1% total energy reduction, with 20.3% dynamic energy reduction and 9.9% leakage energy reduction
crease detection on noisy meshes via probabilistic scale selection. in light of advances in processor and networking technology, especially the emergence of network attached disks, the traditional client-server architecture of file systems has become suboptimal for many computation/data intensive applications. we introduce a revised architecture for file management employing network attached storage: the dynamic file server environment (dynamo). dynamo introduces two main architectural innovations: to provide high scalability, the file management functions are mainly performed cooperatively by the clients in the system. furthermore, data is transferred directly to the client's cache from network-attached disks, thus avoiding copies from a disk to the server buffer and then over the network to the client. secondly, dynamo uses a cooperative cache management which employs a decentralized lottery-based page replacement strategy. we show via performance benchmarks run on the dynamo system and simulation results how this architecture increases the system's adaptability, scalability and cost performance
two-view geometry and reconstruction under quasi-perspective projection. hitherto, the major challenge to sign language recognition is how to develop approaches that scale well with increasing vocabulary size. we present an approach to large vocabulary, continuous chinese sign language (csl) recognition that uses phonemes instead of whole signs as the basic units. since the number of phonemes is limited, hmm-based training and recognition of the csl signal becomes more tractable and has the potential to recognize enlarged vocabularies. furthermore, the proposed method facilitates the csl recognition when the finger-alphabet is blended with gestures. about 2400 phonemes are defined for csl. one hmm is built for each phoneme, and then the signs are encoded based on these phonemes. a decoder that uses a tree-structured network is presented. clustering of the gaussians on the states, the language model and n-best-pass is used to improve the performance of the system. experiments on a 5119 sign vocabulary are carried out, and the result is exciting.
fast depth map compression and meshing with compressed tritree. in this paper, facet analyses are made about the population sizing and sampling of the factorization based on gaussian probability density function in the real- coded ecga (recga) on the univariate and multivariate real-valued deceptive functions (urdf and mrdfi). the dynamics of the recga with single gaussian pdf and mixture gaussian pdf are described statistically. experimental results illustrate that the recga with mixture gaussian pdf has a scalability of sub-quadratic polynomial on the mrdfi, which indicates that it is applicable to large-scale decomposable optimization problems.
scene gist: a holistic generative model of natural image. embedded systems with heterogeneous processors extend the energy/timing trade-off flexibility and provide the opportunity to fine tune resource utilization for particular applications. in this paper, we present a resource model that considers the time and energy costs of run-time mode switching, which considerably improves the accuracy of existing models. given an application, the software partitioning problem then becomes an optimization over energy cost given deadline constraints, which can be formulate as an integer linear programming (ilp) problem. we apply the resource modeling and software partitioning techniques to a multi- module embedded sensing device, the mplatform, and present a case study of configuring the platform for a real-time sound source localization application on a stack of msp430 and arm7 processor based sensing and processing boards.
pedestrian recognition using second-order hog feature. in this report, we first point out and analyse an error in the implementation of the pre-encoding logic in the lop module proposed in [1], and then present a modification method.
transductive segmentation of textured meshes. in this paper, we propose a new model for coherent clustering of gene expression data called reg-cluster. the proposed model allows (1) the expression profiles of genes in a cluster to follow any shifting-and-scaling patterns in subspace, where the scaling can be either positive or negative, and (2) the expression value changes across any two conditions of the cluster to be significant. no previous work measures up to the task that we have set: the density-based subspace clustering algorithms require genes to have similar expression levels to each other in subspace; the pattern-based biclustering algorithms only allow pure shifting or pure scaling patterns; and the tendency-based biclustering algorithms have no coherence guarantees. we also develop a novel patternbased biclustering algorithm for identifying shifting-andscaling co-regulation patterns, satisfying both coherence constraint and regulation constraint. our experimental results show that the reg-cluster algorithm is able to detect a significant amount of clusters missed by previous models, and these clusters are potentially of high biological significance.
multilinear nonparametric feature analysis. this paper proposes a fast close-loop video transcoder with limited drifting error. firstly, similar to the traditional close-loop transcoder, the proposed transcoder still accumulates the re-quantization error of each i or p picture. however, the accumulated errors are not always introduced into the transcoding loop in every block. a triple-threshold algorithm is proposed to adaptively utilize the accumulated errors at block level so as to control drifting error under an acceptable level. secondly, when the accumulated errors are not introduced into the transcoding loop, additional dct transform in the proposed transcoder can be removed. furthermore, the re-quantization process can be simply implemented by looking up table, which significantly reduces the complexity of the re-quantization process. the experimental results show that picture quality of the proposed transcoder is closed to that of the traditional closed-loop one while about 40% blocks are not updated with the accumulated errors. in this case, the transcoding process can be speeded up to 30%.
region based color image retrieval using curvelet transform. in this paper, a region-based spatio-temporal markov random field (stmrf) model is proposed to segment moving objects semantically. the stmrf model combines segmentation results of four successive frames and integrates the temporal continuity in the uniform energy function. the segmentation procedure is composed of two stages: one is the short-term's classification and the other is temporal integration. at the first stage, moving objects are extracted by a region-based mrf model between two frames in a frame group of four successive frames. at the second stage, the ultimate semantic object is labeled by minimization the energy function of the stmrf model. such phased segmentation process is corresponding to a multi-level simulated anneal strategy. experimental results show that the proposed algorithm can efficiently capture the motion semantic meaning of objects and accurately extract moving objects.
multicue graph mincut for image segmentation. ensemble learning algorithms train multiple component learners and then combine their predictions. in order to generate a strong ensemble, the component learners should be with high accuracy as well as high diversity. a popularly used scheme in generating accurate but diverse component learners is to perturb the training data with resampling methods, such as the bootstrap sampling used in bagging. however, such a scheme is not very effective on local learners such as nearest-neighbor classifiers because a slight change in training data can hardly result in local learners with big differences. in this paper, a new ensemble algorithm named filtered attribute subspace based bagging with injected randomness (fasbir) is proposed for building ensembles of local learners, which utilizes multimodal perturbation to help generate accurate but diverse component learners. in detail, fasbir employs the perturbation on the training data with bootstrap sampling, the perturbation on the input attributes with attribute filtering and attribute subspace selection, and the perturbation on the learning parameters with randomly configured distance metrics. a large empirical study shows that fasbir is effective in building ensembles of nearest-neighbor classifiers, whose performance is better than that of many other ensemble algorithms.
mift: a mirror reflection invariant feature descriptor. this paper presents a superposition method for constructing low-density parity-check (ldpc) codes. several classes of structured ldpc codes are constructed. codes in these classes perform well with iterative decoding, and their tanner graphs have girth at least six.
similarity scores based on background samples. harvesting the benefits of a sensor-rich world presents many data management challenges. recent advances in research and industry aim to address these challenges. with the rapidly increasing number of large-scale sensor network deployments, the vision of a worldwide sensor web is close to becoming a reality.
a robust algorithm for color correction between two stereo images. the next generation resource monitoring system in distributed computing environments should not only accurately monitor the environment but also automatically reconfigure the environment. in this paper, we present inapmon, a robust and scalable policy-based resource monitoring system in a multi- server network computer environment. it monitors the resource usage with sensors and aggregates the data in servers for reconfiguring the environment, which aims to guarantee load balance between servers and impartiality between users. this policy-based approach indeed provides a novel perspective for the design of future resource monitoring system.
semantic classification in aerial imagery by integrating appearance and height information. haussler, littlestone and warmuth (1994) described a general-purpose algorithm for learning according to the prediction model, and proved an upper bound on the probability that their algorithm makes a mistake in terms of the number of examples seen and the vapnik-chervonenkis (vc) dimension of the concept class being learned. we show that their bound is within a factor of 1+o(1) of the best possible such bound for any algorithm
extracting spatio-temporal local features considering consecutiveness of motions. for communication between the cluster head node (chn) and the distant data fusion center (dfc) with the cooperation of intra-cluster nodes in wireless sensor networks (wsns), reliable handling of packets by the cooperative node (cn) is difficult to ensure. in this paper, we propose a novel cn selection scheme based on trust for wsns. this scheme can choose one of high trust nodes to assist in the transmission of chn, which aims to improve the transmission performance over cooperative communication in the presence of potential malicious nodes. first, we establish a trust model to improve the reliability of transmission by cn in wsns, which is based on both the direct trust and the indirect trust of nodes. then the chn selects a node based on the proposed trust model to aid the chn in transmission. simulation results show that the proposed scheme can mitigate the impact of the potential malicious nodes on transmission performance and the simulation results also demonstrate the efficiency of the proposed scheme.
dense and accurate spatio-temporal multi-view stereovision. this paper proposes an integrated approach for personal name recognition (pnr) in chinese by utilizing both statistical language models and categorized linguistic knowledge. various formulas are proposed for calculating personal name credibility and context credibility for different types of personal names. experiment is conducted on large-scale corpus to evaluate the approach and the f-1 scores has reached 98.85% and 92.73% respectively in close and open test.
efficient human action detection using a transferable distance function. utilizing the ability simple in application and quick in convergence of quantum delta-potential-well-based particle swarm optimization (qdpso) algorithm and the high generalization ability of support vector machine (svm), selecting the appropriate state variables, a dynamic time-varying model has been built. using the model and algorithm to per-estimate some biochemical state variables which can not be measured on-line, and to optimise some operational variables. it is proved that the method is efficiency through the practical application of penicillin fermentation process.
a harris-like scale invariant feature detector. in this paper, we present an algorithm for computing the bounds on energy-efficiency of digital very large scale integration (vlsi) systems in the presence of deep submicron noise. the proposed algorithm is based on a soft-decision channel model of noisy vlsi systems and employs information-theoretic arguments. bounds on energy-efficiency are computed for multimodule systems, static gates, dynamic circuits and noise-tolerant dynamic circuits in 0.25-&mu;m cmos technology. as the complexity of the proposed algorithm grows linearly with the size of the system, it is suitable for computing the bounds on energy-efficiency for complex vlsi systems. a key result presented is that noise-tolerant dynamic circuits offer the best trade off between energy-efficiency and noise-immunity when compared to static and domino circuits. furthermore, employing a 16-bit noise-tolerant manchester adder in a cdma receiver, we demonstrate a 31.2%-51.4% energy reduction over conventional systems when operating in the presence of noise. in addition, we compute the lower bounds on energy dissipation for this cdma receiver and show that these lower bounds are 2.8&times; below the actual energy consumed, and that noise-tolerance reduces the gap between the lower bounds and actual energy dissipation by a factor of 1.9&times;.
accurate and efficient cost aggregation strategy for stereo correspondence based on approximated joint bilateral filtering. we investigate the problem of memory reuse in order to reduce the memory needed to store an array variable. we develop techniques that can lead to smaller memory requirements in the synthesis of dedicated processors or to more effective use by compiled code of software-controlled scratchpad memory. memory reuse is well-understood for allocating registers to hold scalar variables. its extension to arrays has been studied recently for multimedia applications, for loop parallelization, and for circuit synthesis from recurrence equations. in all such studies, the introduction of modulo operations to an otherwise affine mapping (of loop or array indices to memory locations) achieves the desired reuse. we develop here a new mathematical framework, based on critical lattices, that subsumes the previous approaches and provides new insight. we first consider the set of indices that conflict, those that cannot be mapped to the same memory cell. next, we construct the set of differences of conflicting indices. we establish a correspondence between a valid modular mapping and a strictly-admissible integer lattice-one having no nonzero element in common with the set of conflicting index differences. the memory required by an optimal modular mapping is equal to the determinant of the corresponding lattice. the memory reuse problem is thus reduced to the (still interesting and nontrivial) problem of finding a strictly admissible integer lattice-of least determinant. we then propose and analyze several practical strategies for finding strictly admissible integer lattices, either optimal or optimal up to a multiplicative factor, and, hence, memory-saving modular mappings. we explain and analyze previous approaches in terms of our new framework.
generation of an omnidirectional video without invisible areas using image inpainting. optical burst switching (obs) has been considered the most promising optical switching technology. to the best of authors' knowledge, this is the first paper that identifies the out- of-sequence delivery problem in obs networks. to minimize the impact of the out-of-sequence delivery on buffer space and resequencing latency, we propose a novel virtual burst assembly scheme to eliminate the problem. in addition to simulation results obtained from the obs-ns2 simulator, we implemented the proposed virtual burst assembly scheme in altera stratix ii fpga hardware using verilog hdl, and tested experimentally using real video. both simulation and experimental results confirm the effectiveness of the proposed scheme.
hierarchical model for joint detection and tracking of multi-target. power is a valuable resource in embedded systems as the lifetime of many such systems is constrained by their battery capacity. recent advances in processor design have added support for dynamic frequency/voltage scaling (dvs) for saving power. recent work on real-time scheduling focuses on saving power in static as well as dynamic scheduling environments by exploiting idle and slack due to early task completion for dvs of subsequent tasks. these scheduling algorithms rely on a priori knowledge of worst-case execution times (wcet) for each task. they assume that dvs has no effect on the worst-case execution cycles (wcec) of a task and scale the wcet according to the processor frequency. however, for systems with memory hierarchies, the wcec typically does not change under dvs due to frequency modulation. hence, current assumptions used by dvs schemes result in a highly exaggerated wcet. this paper contributes novel techniques for tight and flexible static timing analysis particularly well-suited for dynamic scheduling schemes. the technical contributions are as follows: (1) we assess the problem of changing execution cycles due to scaling techniques. (2) we propose a parametric approach towards bounding the wcet statically with respect to the frequency. using a parametric model, we can capture the effect of changes in frequency on the wcec and thus, accurately model the wcet over any frequency range. (3) we discuss design and implementation of the frequency-aware static timing analysis (fast) tool based on our prior experience with static timing analysis. (4) we demonstrate in experiments that our fast tool provides safe upper bounds on the wcet, which are tight. the fast tool allows us to capture the wcet of six benchmarks using equations that overestimate the wcet by less than 1%. fast equations can also be used to improve existing dvs scheduling schemes to ensure that the effect of frequency scaling on wcet is considered and that the wcet used is not exaggerated. (5) we leverage three dvs scheduling schemes by incorporating fast into them and by showing that the power consumption further decreases. to the best of our knowledge, this study of dvs effects on timing analysis is unprecedented.
a novel system for robust text location and recognition of book covers. congestion in interconnection networks due to the presence of hot spots is an important and difficult problem that occurs in parallel machines. this problem has been studied in depth and different solutions for the case of multiprocessors with shared memory have been proposed. current trends point towards the implementation of systems with physically distributed memory, either based on, message passing (multicomputers) or on a single shared memory address space (multiprocessors). our paper is developed in this context. up to now, proposals to improve the throughput of networks with hot-spots have focused on using virtual channels or adaptive algorithms. we present a novel solution based on reconfigurable networks. a reconfigurable network is one in which nodes can change their position depending on the communication pattern in order to diminish the congestion produced in the network and, therefore, increase its throughput. we studied this problem in two-dimensional k-ary n-cube networks using a deterministic routing algorithm and wormhole routing. in this paper the main features of a reconfigurable network are presented and the results obtained by simulation are shown. these results confirm that this technique is a very interesting one for systems with distributed memory, with applications to a great variety of problems
face alignment using boosting and evolutionary search. though the popular ieee 802.11 dcf is designed primarily for wireless lan (wlan) environments, today it is being widely used for wide area wireless mesh networking. the protocol parameters of ieee 802.11 such as timeout values, interframe spaces, and slot durations, which are sufficient for a general wlan environment need to be modified in order to efficiently operate in wide area wireless mesh networks. the current wide area wireless mesh network deployments use manual configuration of these parameters to the upper limit which essentially makes the networks operate at lower system efficiency. in this paper, we propose d802.11 (dynamic 802.11) which dynamically adapts the protocol parameters in order to operate at varying link distances. we present three strategies, (i) multiplicative timer back-off (mtb), (ii) additive timer back-off (atb), and (iii) link rtt memorization (lrm), to adapt the ack_timeout in d802.11 in order to provide better adaptation for varying link dimensions. through extensive simulation experiments we observed significant performance improvement for the proposed strategies. we also theoretically modeled the maximum throughput as a function of the link dimension for the proposed system. our results show that the lrm technique provides the best adaptation compared to all other schemes.
orientation and scale invariant kernel-based object tracking with probabilistic emphasizing. while there is currently great interest in the problem of providing real time services in general purpose operating systems, the issue of real time scheduling of internal operating system activities has received relatively little attention. without such real time scheduling, the system is susceptible to conditions such as receive livelock-a situation in which an operating system spends all its time processing arriving network packets, and application processes, even if scheduled with a real time scheduler, are starved. we investigate the problem of scheduling operating system activities such as network protocol processing in a proportional share manner. we describe a proportional share implementation of the freebsd operating system and demonstrate that it solves the receive livelock problem. packets are processed within the operating system only at the cumulative rate at which the destination applications are prepared to receive them. if packets arrive at a faster rate then they are discarded after consuming minimal system resources. in this manner the performance of &ldquo;well behaved&rdquo; applications is unaffected by &ldquo;misbehaving&rdquo; applications. we demonstrate this effect by running a set of multimedia applications under a variety of network conditions on a set of increasingly sophisticated proportional share implementations of freebsd and comparing their performance. this work contributes to our knowledge of the engineering of proportional share real time systems
incremental multi-view face tracking based on general view manifold. face representations based on gabor features have achieved great success in face recognition, such as elastic graph matching, gabor fisher classifier (gfc), and adaboosted gabor fisher classifier (agfc). in gfc and agfc, either down-sampled or selected gabor features are analyzed in holistic mode by a single classifier. in this paper, we propose a novel patch-based gfc (pgfc) method, in which gabor features are spatially partitioned into a number of patches, and on each patch one gfc is constructed as component classifier to form the final ensemble classifier using sum rule. the positions and sizes of the patches are learned from a training data using adaboost. experiments on two large-scale face databases (feret and cas-peal-r1) show that the proposed pgfc with only tens of patches outperforms the gfc and agfc impressively
probabilistic cascade random fields for man-made structure detection. spectrum sensing for the china digital television terrestrial broadcasting system is considered in this paper. the spectrum sensing algorithms utilize pn sequences embedded in the frame headers to perform spectrum sensing. a theoretical lower bound on the misdetection probability for each spectrum sensor presented in this paper is derived. the performances of the proposed spectrum sensing algorithms are demonstrated by computer simulation for the multipath rayleigh fading and steady state multipath rayleigh fading channels. simulation results show that the misdetection probability evaluated by computer simulations is close to the lower bound on the misdetection probability for a steady state multipath rayleigh channel. when the probability of false alarm is 0.01 and a 50 ms of sensing time is used, a misdetection probability equal to 0.1 is achieved when the signal to noise power ratio is -16 db, -18.8 db, and -18 db for modes 1, 2, and 3 in the multipath rayleigh fading channel, respectively.
people tracking and segmentation using efficient shape sequences matching. a secure image transmission mechanism is necessary when malicious intruders intend to access and modify content delivery over wireless networks. to assure data integrity, authentication is required for multimedia data delivered over wireless image sensor networks. watermarking technique is an effective vehicle to assert and assure the image data authentications. there have been recent works reported on watermarking, but few with the consideration of energy cost in terms of the data communication and processing, which is a key constraint to many embedded systems and wireless sensor networks. most watermarking systems only target at minimizing watermarked image distortion and increasing robustness at the source coding site for lossy image processing. the watermarked image distortion caused by error-prone wireless environments during transmission has not been fully considered. in this paper, an innovative energy-aware adaptive watermarking scheme for realtime image delivery is proposed in wireless multimedia sensor networks. this new scheme allocates network resource to protect the watermarked image transmission while embedding watermark coding redundancies into the images. dynamic watermark thresholds are applied to be adaptive to the network condition (packet loss ratio) and the inter-frame correlation is exploited to reduce processing delay. the simulation results show that the proposed adaptive watermark system can achieve considerable energy efficiency and assure the data integrity.
twisted cubic: degeneracy degree and relationship with general degeneracy. this paper presents an adaptive timing method for analysis of deskew signaling in high-performance integrated systems. the proposed approach models the practical deskew schemes as an adaptive system to study the performance limit of deskew signaling. we investigate the statistical properties of optimal deskew, which can be considered as the theoretical limit of deskew signaling. this approach also allows us to study the related energy efficiency issues in deskew schemes. we determine the bound on energy efficiency subject to the performance constraint on deskew signaling. simulation results show that the performance of practical deskew schemes in a 90-nm process is 23.2% away from the optimal deskew scheme, and the gap of energy efficiency is 51% above the bound.
video segmentation using iterated graph cuts based on spatio-temporal volumes. in this paper, we present a new method for texture classification which we call the regularized simultaneous autoregressive method (rsar). the regularization technique is introduced. with the technique, the new algorithm rsar outperforms the traditional algorithm in texture classification. particularly, our new algorithm is useful for extracting texture from the image which is coarse or contains too much noise.
robust real-time multiple target tracking. feature selection method based on text study is a mainstream method currently, whose research key lies in finding out one suitable feature assessment method, which can reduce the numbers of the words to be processed as less as possible in the situation of not decreasing classification precision, to improve the speed and the efficiency of classification. a new feature assessment method entropy ratio is proposed in this paper on the base of researching the classical feature assessment methods in the existing literature. this method not only considered feature classification ability, but also the feature generalization ability. it is a new and better choice to apply the centroid-based classifier to improve the effect of classification. experimental results show that the effect obtained by using this method to select features is obviously superior to the one obtained by other methods, especially when the feature selected is less.
a multi-scale bilateral structure tensor based corner detector. biological snakes' diverse locomotion modes and physiology make them supremely adapted for environment. to realize these snakes' noticeable features, we have developed a snake-like robot that has no any forward direction driving force. to enlarge the environment-adaptable ability of our robot, in this study we discuss the creeping locomotion of our snake-like robot on a slope. a computer simulator is presented for analysis of the creeping locomotion of our snake-like robot on a slope, and the environment-adaptable body shape for the creeping locomotion of the snake-like robot on slope is also derived through this simulator.
part-based object detection using cascades of boosted classifiers. skyline computation has many applications including multi-criteria decision making. in this paper, we study the problem of efficient processing of continuous skyline queries over sliding windows on uncertain data elements regarding given probability thresholds. we first characterize what kind of elements we need to keep in our query computation. then we show the size of dynamically maintained candidate set and the size of skyline. we develop novel, efficient techniques to process a continuous, probabilistic skyline query. finally, we extend our techniques to the applications where multiple probability thresholds are given or we want to retrieve "top-k" skyline data objects. our extensive experiments demonstrate that the proposed techniques are very efficient and handle a high-speed data stream in real time.
bayesian 3d human body pose tracking from depth image sequences. when trying to discover knowledge on a collection of data, one of the first arising tasks is to identify groups of similar objects, that is, to carry out cluster analysis for obtaining data partitions. thus, a decision must be taken for choosing the clustering result that produces the best data partition for a given data collection. in order to support such a decision, indexes for measuring the quality of a data partitioning must be constructed. so far, several cluster validity indexes have been formulated in the literatures. each of those indexes has strengths and drawbacks when compared with the others. in the present study, an alternative cluster validity index is formulated. the proposed validity index not only takes the contribution of each pattern into consideration, but also relies on information of intra-cluster and inter-cluster distance. the main advantage of the presented index is that is insensitive to noise by introducing the gaussian kernel into the proposed validity index. an experimental design was devised in order to determine the comparative performance of the proposed cluster validity index against db index previously formulated in the literature. experimental results show that the proposed index is insensitive to noise and adaptive to produce good clustering solution.
detecting critical configurations for dividing long image sequences for factorization-based 3-d scene reconstruction. clustering is an old research topic in data mining and machine learning. most of the traditional clustering methods can be categorized as local or global ones. in this paper, a novel clustering method that can explore both the local and global information in the data set is proposed. the method, clustering with local and global regularization (clgr), aims to minimize a cost function that properly trades off the local and global costs. we show that such an optimization problem can be solved by the eigenvalue decomposition of a sparse symmetric matrix, which can be done efficiently using iterative methods. finally, the experimental results on several data sets are presented to show the effectiveness of our method.
a dynamic programming approach to maximizing tracks for structure from motion. reconfigurable robots consist of many modules which are able to change the way they are connected. as a result, the robots have the capability of adopting different configurations to match various tasks and suit complex environments. this paper presents a novel field robot named jl-i which consists of three uniform modules. with the docking mechanisms, the modules can connect or disconnect flexibly and automatically. furthermore the active joints formed by serial and parallel mechanisms endow the robot with the ability of changing shape in three dimensions. consequently useful locomotion capabilities, such as crossing high vertical obstacles, getting self-recovery when the robot is upside-down are achieved. after describing the structural principle of the robot, the related kinematics analysis follows. in the end, the successful on-site tests confirm the principles described above and the robot's ability
efficient scale-space spatiotemporal saliency tracking for distortion-free video retargeting. this letter considers the problem of resource sharing between two selfish nodes in cooperative relay networks. in our system, each node can act as a source as well as a potential relay, and both nodes are willing to achieve an optimal signal-to-noise ratio (snr) increase by adjusting their power levels for cooperative relaying. we formulate this problem as a two-person bargaining game, and use the nash bargaining solution (nbs) to achieve a win-win strategy for both nodes. simulation results indicate the nbs resource sharing is fair in that the degree of cooperation of a node only depends on how much contribution its partner can make to its snr increase.
human action recognition using spatio-temporal classification. we present a case study of the use of a software process improvement method which is based on the analysis of defect data. the first step of the method is the classification of software defects using attributes which relate defects to specific process activities. such classification captures the semantics of the defects in a fashion which is useful for process correction. the second step utilizes a machine-assisted approach to data exploration which allows a project team to discover such knowledge from defect data as is useful for process correction. we show that such analysis of defect data can readily lead a project team to improve their process during development
a graph-based feature combination approach to object tracking. this paper proposes an improved immunological surveillance for network danger evaluation model, focusing on intrusion detection and countermeasures with respect to widely-used networks. an improved intrusion detection mechanism based on self-tolerance, clone selection, and immune surveillance is established. a new network security evaluation method using antibody concentration to quantitatively analyze the degree of intrusion danger level is presented. additionally, this new hierarchical management framework of the proposed model adopt to improve the detection efficiency and to overcome the shortcoming of the local optimum. the experimental results show that the proposed model is a good solution for network security evaluation.
iterated graph cuts for image segmentation. future ip networks need to support different quality of service (qos) sensitive services with distinct end-to-end qos requirement. an attractive solution is to use adaptive bandwidth provisioning to provide guaranteed distinctive qos and maintain high network efficiency at the same time. but, previous research on adaptive provisioning assumes dedicated bandwidth and is limited to the single-link case. this paper studies adaptive bandwidth provisioning to provide guaranteed statistical end-to-end qos. the novelty of this study is that our adaptive bandwidth provisioning is performed on multiple links along the end-to-end path to satisfy the end-to-end statistical qos requirement, and it is done in bandwidth sharing generalized processor sharing (gps) networks, in which the received qos of one flow can be interfered by other competing flows. the analysis and simulation results show that by utilizing adaptive bandwidth provisioning, guaranteed end-to-end statistical qos can be achieved, and between the two possible schemes to carry out this multiple-link adaptive bandwidth provisioning, the end-to-end bandwidth provisioning scheme is more efficient than performing local adaptive bandwidth provisioning on each individual link
contour extraction based on surround inhibition and contour grouping. the change in meaning of data over time poses significant challenges for the use of that data. these challenges exist in the use of an individual data source and are further compounded with the integration of multiple sources. in this paper, we identify three types of temporal semantic heterogeneities. we propose a solution based on extensions to the context interchange framework, which has mechanisms for capturing semantics using ontology and temporal context. it also provides a mediation service that automatically resolves semantic conflicts. we show the feasibility of this approach with a prototype that implements a subset of the proposed extensions.
rotation averaging with application to camera-rig calibration. this paper reports on the design, implementation and performance evaluation of a suite of gridrpc programming middleware called ninf-g version 2 (ninf-g2). ninf-g2 is a reference implementation of the gridrpc api, a proposed ggf standard. ninf-g2 has been designed so that it provides 1) high performance in a large-scale computational grid, 2) the rich functionalities which are required to adapt to compensate for the heterogeneity and unreliability of a grid environment, and 3) an api which supports easy development and execution of grid applications. ninf-g2 is implemented to work with basic grid services, such as gsi, gram, and mds in the globus toolkit version 2. the performance ofninf-g2 was evaluated using a weather forecasting system which was developed using ninf-g2. the experimental results indicate that high performance can be attained even in relatively fine-grained task-parallel applications on hundreds of processors in a grid environment.
real-time video matting based on bilayer segmentation. many real-life networks, such as the www, biological realms, and social networks are small-world networks. most previous researches on small-world networks have been based on probabilistic methods. in this paper, we present a general method by using cayley graph to build deterministic small-world networks. we also analyze the cluster topology of the cayley graph with small world properties by constructing its left coset graph. this method has great value in constructing interconnection networks model and analyzing many other real network models.
dynamic kernel-based progressive particle filter for 3d human motion tracking. soldiers possessing of network attack-defense ability are the key factor for future information war. aiming at the problem of lacking daily training and drilling environment, a method of building network attack-defense simulation training system (nadsts) based on hla is put forward. with the method, attack and defense training are designed as different federation member. the system is divided to presentation, application and adapter layer clearly. key technologies involves network attack-defense, network simulation and simulation driving are also presented. software is developed based on plug-in framework. its simulation examples show greatest traits on building similar large-scale simulation system.
multi-view texturing of imprecise mesh. this paper presents an eco-friendly daemon that reduces power and energy consumption while better maintaining high performance via an accurate workload characterization that infers ldquoprocessor stall cycles due to off-chip activities.rdquo the eco-friendly daemon is an interval-based, run-time algorithm that uses the workload characterization to dynamically adjust a processorpsilas frequency and voltage to reduce power and energy consumption with little impact on application performance. using the nas parallel benchmarks as our workload, we then evaluate our eco-friendly daemon on a cluster computer. the results indicate that our workload characterization allows the power-aware daemon to more tightly control performance (5% loss instead of 11%) while delivering substantial energy savings (11% instead of 8%).
visual saliency based object tracking. the security of web services has become one of the important research topics about the application of web services. in this paper, we propose an agent-based policy aware framework for web services security. in this framework, a policy language called reit which is a declarative language based on the rules and ontologies is introduced. the non-structural knowledge is represented by rules and the structural temporal knowledge is represented by ontology. moreover, we propose a mixed reasoning mechanism to evaluate the reit policy. the access control policy including the context of the user and web services is evaluated by the reasoner. in addition, we present a policy aware boid agent to authorize the access control of the web services. and we implement the policy aware boid agent by extending the jade platform.
combining edge and color features for tracking partially occluded humans. based on the amino acid sequence of bhlh-zip motif in srebp-1 and srebp-2 in landes goose obtained by gene cloning, the sequences of hlh family members in poultry genome were screened in the protein databases of ncbi. the classification and evolution of hlh protein family in poultry genome were analyzed. hlh protein family in poultry genome are divided into five groups (a, b, c, d and e) according to the sequence features of bhlh domain. the result of phylogenetic development indicates the sequences of hlh family members in poultry genome also gather into five groups, and this grouping is generally consistent with the classification by sequence features. group b diverges from other groups firstly, and the divergent time of group a is the latest. groups a and d have closer genetic relationship, and groups c and e have closer phylogenetic relationship.
a blind robust watermarking scheme based on ica and image dividing blocks. the interconnection network plays an important role in the performance and energy consumption of a network-on-chip (noc) system. in this paper, we propose a rdt(2,2,1)/&alpha;-based interconnection network for noc designs. rdt(2,2,1)/&alpha; is constructed by recursively overlaying 2d diagonal meshes (torus). the number of layers needed for routing the links in rdt(2,2,1)/&alpha; is shown to be bounded at 6, which is feasible to be implemented with current and future vlsi technologies. with the innovative diagonal structure and its simple rank assignment, rdt(2,2,1)/&alpha; possesses the following features: recursive structure, smaller diameter and average distance, embedded mesh/torus topology, a constant node degree of 8, and robust routing schemes. these features make rdt(2,2,1)/&alpha; a promising solution for the interconnection network of noc designs satisfying the requirements for scalability, energy-efficiency, customizability, and fault-tolerance.
planar scene modeling from quasiconvex subproblems. in multi-site distributed education (msde), video streams from multiple sites are available. to best utilize the limited screen space at each site, we develop a customizable, automated display management system in this paper, i.e., only user-preferred streams will be shown as triggered by events and timers. the configuration of such user preference, however, is challenging because it has to be both human-friendly and machine-friendly. to address this challenge, we propose a three-layer virtual director model. in the user layer, we identify three categories of parameters that can represent a wide range of user preferences yet are easy to use. these preferences are then automatically translated into a machine-friendly timed automaton in the execution layer. the automaton is simulated dynamically, which selects a subset of streams to show on the screen through a display layer. evaluation results demonstrate the correctness and efficiency of the proposed framework
a three-phase approach to photometric calibration for multi-projector display using lcd projectors. negotiation strategy is an important research branch of agent-based automatic negotiation. under the background of bilateral multi-issues negotiation, a novel negotiation skill algorithm by interactive micro-adjustment and multi-rounds approximation is proposed, which classifies both partiespsila proposal issues into two divisions --- interest point set and disinterest point set, and combined with the historical experience data conducts in-depth negotiation process according to the composite relationship of both interest level of consistency proposal issues and difference of issue values. at the same time concern degree of opponent about proposal issues is given and updated by a fuzzy theory-based prediction function, which can realize the purpose of learning negotiation opponent. finally, the application and analysis of the proposed negotiation skill algorithm are demonstrated by a numerical experiment.
crowd flow characterization with optimal control theory. this paper is concerned with cellular systems with rate constraints in fading environments. we consider a simple but asymptotically optimal matched filtering/successive interference cancellation (mf-sic) scheme. we derive several concise and closed-form bounds for the power and spectral efficiencies of various base station cooperation strategies, which provide some useful insights into cellular systems.
levels of details for gaussian mixture models. as the first dht implemented in real applications and involving millions of simultaneous users, all aspects of kad must be analyzed and measured carefully. this paper focuses on measuring the routing table of kad in emule/amule. we present and analyze the availability and stability of routing table by crawling actively. we find the phenomenon of id repetition in kad that many peers use a same id simultaneously, which will decrease the performance of routing and then reduce the availability of routing table. the connection availability of global routing table is relatively low, the average of which is about 64.9%. connection availability influences the efficiency of searching and routing in kad network directly.
detection of vehicle manufacture logos using contextual information. in this paper, an improved spatial scalable wavelet domain distributed video coding (dvc) scheme is proposed. in this scheme, we adaptively apply differential pulse code modulation (dpcm) wyner-ziv (wz) coding and discrete cosine transform (dct) based intra block coding to reduced-resolution layer. due to the low energy nature of high-pass subbands, wz coding can be directly used. at decoder, in full-resolution layer wz frame decoding, an efficient side information (si) generation technique for low-pass subband is proposed, in which motion compensated interpolation (mci) is performed on full-resolution signal. on the other hand, a refined technique is also employed to generate the si for high-pass subbands by taking advantage of inter-band correlation. experimental results show that the proposed scheme provides an efficient wavelet domain dvc coding paradigm.
auto-scaled incremental tensor subspace learning for region based rate control application. fuzzy c-means (fcm) clustering algorithm is a popular model widely used in segmentation of magnetic imaging (mri) data. the conventional fcm does not take into account the spatial information of image and get the unexpected results of segmentation when dealing with some mri contaminated by noise. considering the intensities of ideal mri are piecewise constant, we present an improved model to fuzzy c-means algorithm using membership smoothing constraint. the proposed algorithm can reasonably use the spatial information of image and improve the accuracy of segmentation. simulation mr brain image with different noise levels and real mr brain image are presented in the experiments. the results of experiments show better robustness of our algorithms to noise than other segmentation algorithms.
local spatial co-occurrence for background subtraction via adaptive binned kernel estimation. this paper addresses several questions related to the control of timed continuous petri nets under infinite server semantics. first, some results regarding equilibrium states and control actions are given. in particular, it is shown that the considered systems are piecewise linear, and for every linear subsystem the possible steady states are characterized. second, optimal steady-state control is studied, a problem that surprisingly can be computed in polynomial time, when all transitions are controllable and the objective function is linear. third, an interpretation of some controllability aspects in the framework of linear dynamic systems is presented. an interesting finding is that noncontrollable poles are zero valued.
visual focus of attention recognition in the ambient kitchen. we present a new adaptive and energy-efficient broadcast dissemination model that supports flexible responses to client requests. in current broadcast dissemination models, clients must specify precisely what documents they require, and servers disseminate exactly those documents. this approach can be impractical, since in practice, clients may know the characteristics of the documents, but not the document names or ids. in our model, clients specify the required document using attributes, and servers broadcast documents that match client requests at a prespecified level of similarity. a single document may satisfy several clients, so the server broadcasts a minimal set of documents that achieves a desired level of satisfaction in the client population. we introduce a mechanism for the server to obtain randomized feedback from clients to adapt its broadcast program to client needs. finally, the server integrates a selective tune-in scheme based on approximate index matching to allow clients to conserve energy. our simulation results show that our model captures client interest patterns efficiently and accurately and scales very well with the number of clients, while reducing overall client average waiting times. the selective tune-in scheme can considerably reduce the consumption of client energy with moderate waiting time overhead.
computer vision - accv 2009, 9th asian conference on computer vision, xi'an, china, september 23-27, 2009, revised selected papers, part iii in this paper, two scanning paradigms are presented and compared that may be used for robotic scanning of a harsh environment such as a celestial body or earth poles. the first paradigm, tight scanning, includes three algorithms, which may be used to find small objects or gasses confined to small regions such as the methane gas given off by bacteria in buried hot springs in the canadian arctic. the second paradigm, relaxed scanning, includes four algorithms which may be used to find large objects such as large ice deposits that may be buried just below the surface of mars. the algorithms are compared against their peer algorithms by their quality of performance. such performance quality is determined by the ratio of scanned area to the traveled distance by the two robots
a probabilistic model for correspondence problems using random walks with restart. technology trends are driving parallel on-chip architectures in the form of multi-processor systems-on-a-chip (mpsocs) and chip multi-processors (cmps). in these systems the increasing on-chip communication demand among the computation elements necessitates the use of scalable, nigh-bandwidth network-on-chip (noc) fabrics. as transistor feature sizes are further miniaturized leading to rapidly increasing amounts of on-chip resources, more complicated and powerful noc architectures become feasible that can support more sophisticated and demanding applications. given the myriad emerging software-hardware combinations, for cost-effectiveness, a system designer critically needs to prune this widening noc design space to identify the architecture(s) that best balance(s) cost/performance, before the actual design process begins. this prompted us to develop polaris 1, a system-level roadmap for on-chip interconnection networks that guides designers towards the most suitable network design(s) tailored to their performance needs and power/silicon area constraints with respect to a range of applications that will run over this network(s). polaris explores the plethora of noc designs based on projections of network traffic, architectures, and process characteristics. while the polaris roadmapping toolchain is extensible so new traffic, network designs, and processes can be added, the current version of the roadmap already incorporates 7,872 noc design points. polaris is rapid and iterates over all these noc architectures within a tractable run time of 125 hours on a typical desktop machine, while maintaining high relative and absolute accuracies when validated against detailed noc synthesis results.
fingerspelling recognition through classification of letter-to-letter transitions. currently, most governments experience severe problems managing the large n tier, networked environment. while new it technologies aiming at automating the deployment and maintenance of it infrastructure are emerging, as manifested in the autonomic computing paradigm where the it infrastructure and its components are self-managing, the technology alone still cannot solve the complex information system manageability problems for e-government infrastructure. this paper proposes an information and knowledge management model that combines the benefit of autonomic computing system paradigm for self-managed infrastructure systems and an event-based awareness collaboration knowledge management approach for coordinating the infrastructure management processes. we hope it provides a more comprehensive guideline for managing e-government information systems.
adapting svm image classifiers to changes in imaging conditions using incremental svm: an application to car detection. with the fast development of the technology in database and internet, excessive information has become a problem that decision makers engage in electronic commerce have to affront. this paper firstly establishes the decision table for excessive data, then reduces knowledge of the decision table, and obtains the best rules. this can reduce the redundancy of the data, and improve the efficiency of knowledge obtaining. because of the high time complexity and spatial complexity the general algorithm has, this paper proposed a new algorithm based on analogical matrix, and carried out the algorithm. the practice proves that the algorithm can improve the efficiency of knowledge obtaining, and the rules is tidy and best.
fingerprint orientation field estimation: model of primary ridge for global structure and model of secondary ridge for correction. watermarks can be embedded into the host contents by multiplicative spread spectrum (mss) methods. however, the interference from the host contents hinders the successful detection of the embedded watermark. this interference can be compensated at the embedder, or be exploited at the detector to improve the detection rate. in this paper, we first derive the optimum decision rule for watermarking in the discrete cosine transform domain, and then proceed to present an enhanced mss scheme that compensates the host interference at the embedder. in our scheme, the host interference to be compensated is a generalized correlation tailored to the optimum decision rule. its effectiveness is validated through both theoretical analyses and experiments
super-resolution of multiple moving 3d objects with pixel-based registration. with the growing popularity of xml technology, developing effective and efficient query techniques of xml data becomes an important problem. in this paper, we introduce a query recommendation technique, which is able to provide both result recommendation and query input recommendation for xml queries, to help users to find useful information more efficiently. ln our approach, we mine association rules from xml documents to discover related xml fragments and recommend to the user the possibly interesting results, which are however not included in the original query results. in order to restrict the number of discovered rules and to discard uninteresting rules, our system allows users to specify constraints on the generated association rules. in addition to the recommendation of results, our system also provides potentially relevant xml queries to help users to find the desired content rapidly. our experimental results show that our methods can provide recommendations for both query results and query input effectively.
face relighting based on multi-spectral quotient image and illumination tensorfaces. this paper introduces compositional time petri net (ctpn) models. a ctpn is a modularized time petri net (tpn), which is composed of components and connectors. the paper also proposes a set of component-level reduction rules for tpns. each of these reduction rules transforms a tpn component to a very simple one while maintaining the net's external observable timing properties. consequently, the proposed method works at a coarse level rather than at an individual transition level. therefore, one requires significantly fewer applications to reduce the size of the tpn under analysis than those existing ones for tpns. the use and benefits of ctpns and reduction rules are illustrated by modeling and analyzing the response time of a command and control system to its external arriving messages
weighted map for reflectance and shading separation using a single image. this paper explores thread scheduling on an increasingly popular architecture: chip multiprocessors with simultaneous multithreading cores. conventional multiprocessor scheduling, applied to this architecture, will attempt to balance the thread load across cores. this research demonstrates that such an approach eliminates one of the big advantages of this architecture - the ability to use unbalanced schedules to allocate the right amount of execution resources to each thread. however, accommodating unbalanced schedules creates several difficulties, the biggest being the fact that the search space of all schedules (both balanced and unbalanced) is much greater than that of the balanced schedules alone. this work proposes and evaluates scheduling policies that allow the system to identify and migrate toward good thread schedules, whether the best schedules are balanced or unbalanced
spatially varying regularization of image sequences super-resolution. in this paper, we propose and evaluate a new protocol that provides topology change- and fault-tolerant real-time communication services on now and clusters. this protocol overcomes the main drawback of our previously proposed protocol, called dynamically re-established real-time channels (drrtc), which is physically limited by the number of virtual channels per port. the new protocol allows different real-time channels to share the same virtual channel. in this way, the new protocol allows us to establish a greater number of real-time channels than the previous one. moreover, its only limitation is the bandwidth devoted to real-time traffic. however, this introduces two new problems that are successfully managed by the new protocol: the existence of cyclic dependencies among different real-time channels and the increased complexity of deadline requirements. we present and analyze the performance evaluation results when a single switch or a single link is deactivated/activated for different topologies and workloads. the new protocol overwhelms the drrtc protocol while guaranteeing deadline requirements and channel recovery.
training support vector machines on large sets of image data. reduced resolution update (rru) video coding provides a better compression performance than h.264/avc does. it is implemented by encoding the predicted residuals after down-sampling at the encoder and at the decoder, is up-sampled to the full-resolution size while motion compensation prediction signal are still yielded in the full-resolution spatial domain. in this paper, the authors first extend the frame-level rru to the macroblock-level to obtain better coding performance than the frame-level rru. furthermore, a novel macroblock-level reduced resolution coding scheme was proposed which adaptively selects the part of dct coefficients in the zigzag scan order to obtain better coding efficiency in terms of rate distortion performance. experimental results exhibit that the proposed methods can achieve obvious improvements in both compression efficiency and decoding complexity compared with the frame-level rru and h.264/avc.
gable roof description by self-avoiding polygon. in this paper an analytic model for ge/si core/shell nanowire mosfets (nwfets) is developed. first, the electrostatic potential and charge model are derived out from classical device physics. then the drift-diffusion drain current model is obtained and verified by comparisons with the numerical simulation. the ballistic current model is obtained with the approximately described quantum-mechanical effect through modifying the intrinsic carrier concentration under 2-dimensional confinement. with the proposed model, the performances of ge/si core/shell nwfets are analyzed and significant characteristics are demonstrated in details. the analytic model in this paper provides a framework for further developing compact models of the nwfets with ge/si core/shell heterostructure for circuit design and simulation.
efficient classification of images with taxonomies. one important issue the designer of a scalable shared-memory multiprocessor must deal with is the amount of extra memory required to store the directory information. it is desirable that the directory memory overhead be kept as low as possible, and that it scales very slowly with the size of the machine. unfortunately, current directory architectures provide scalability at the expense of performance. this work presents a scalable directory architecture that significantly reduces the size of the directory for large-scale configurations of a multiprocessor without degrading performance. first, we propose multilayer clustering as an effective approach to reduce the width of directory entries. based on this concept, we derive three new compressed sharing codes, some of them with a space complexity of o(log2(log2(n))) for an n-node system. then, we present a novel two-level directory architecture to eliminate the penalty caused by compressed directories in general. the proposed organization consists of a small full-map first-level directory (which provides precise information for the most recently referenced lines) and a compressed second-level directory (which provides in-excess information for all the lines). the proposals are evaluated based on extensive execution-driven simulations (using rsim) of a 64-node cc-numa multiprocessor. results demonstrate that a system with a two-level directory architecture achieves the same performance as a multiprocessor with a big and nonscalable full-map directory, with a very significant reduction of the memory overhead.
a 7-round parallel hardware-saving accelerator for gaussian and dog pyramid construction part of sift. this paper examines the area, power, performance, and design issues for the on-chip interconnects on a chip multiprocessor, attempting to present a comprehensive view of a class of interconnect architectures. it shows that the design choices for the interconnect have significant effect on the rest of the chip, potentially consuming a significant fraction of the real estate and power budget. this research shows that designs that treat interconnect as an entity that can be independently architected and optimized would not arrive at the best multi-core design. several examples are presented showing the need for careful co-design. for instance, increasing interconnect bandwidth requires area that then constrains the number of cores or cache sizes, and does not necessarily increase performance. also, shared level-2 caches become significantly less attractive when the overhead of the resulting crossbar is accounted for. a hierarchical bus structure is examined which negates some of the performance costs of the assumed base-line architecture.
polygonal light source estimation. this paper focuses on the problem of reasoning about concurrent assembly code with reentrant locks. our verification technique is based on concurrent separation logic (csl). in csl, locks are treated as non-reentrant locks and each lock is associated with a resource invariant, the lock-protected resources are obtained and released through acquiring and releasing the lock respectively. in order to accommodate for reentrancy, we introduce some additional notions into our specification language to describe reentrant level for each acquiring and releasing lock operation. keeping track of the reentrant level for each lock in the pre- and post- conditions enables the program logic to ensure that resources are not reacquired upon reentrancy, thus resources owned by a thread are prevented from reintroducing in the postcondition. our framework is fully mechanized. its soundness has been verified using the coq proof assistant. we demonstrate the usage of our framework through giving a safety proof of a simple program.
incrementally discovering object classes using similarity propagation and graph clustering. for improving the usability of the anonymous result, it is important to comply with the hierarchical structure when generalizing quasi-identifying attributes with hierarchical characteristics. we propose an unrestricted multi-dimensional anonymization model which combines global recoding and local recoding methods. the bottom-up anonymization algorithm with the minimal coverage subgraph constraint and the anonymization metric are proposed. the experiment results justify the effectiveness and scalability of this model.
skeleton graph matching based on critical points using path similarity. a fuzzy logic expert system for diagnosis and security assessment of power transformers (fdsapt) is presented. a prototype of this expert-system has been accomplished with the ai-language turbo-prolog on a microcomputer and satisfactory application results were obtained. in building a sophisticated expert system for fd-sapt, the main difficulties arise from the inexactness or impreciseness of the fault information, the uncertainty of the inference rules, the complexity of representing experts' knowledge, and the inference process. to solve these problems, the test information was represented by fuzzy sets obtained by the operation of predicate rules. a production rule with a certainty factor was adopted to represent the knowledge of experts, and a fuzzy inference approach based on fuzzy synthetic judgment theory was introduced into the inexact reasoning of the expert system. a complex inference mechanism with depth-first search strategy was successfully used in this system. the fdsapt system has been applied to beijing electric power system and satisfactory results were obtained
highly-automatic mi based multiple 2d/3d image registration using self-initialized geodesic feature correspondences. given a user keyword query, current web search engines return a list of individual web pages ranked by their "goodness" with respect to the query. thus, the basic unit for search and retrieval is an individual page, even though information on a topic is often spread across multiple pages. this degrades the quality of search results, especially for long or uncorrelated (multitopic) queries (in which individual keywords rarely occur together in the same document), where a single page is unlikely to satisfy the user's information need. we propose a technique that, given a keyword query, on the fly generates new pages, called composed pages, which contain all query keywords. the composed pages are generated by extracting and stitching together relevant pieces from hyperlinked web pages and retaining links to the original web pages. to rank the composed pages, we consider both the hyperlink structure of the original pages and the associations between the keywords within each page. furthermore, we present and experimentally evaluate heuristic algorithms to efficiently generate the top composed pages. the quality of our method is compared to current approaches by using user surveys. finally, we also show how our techniques can be used to perform query-specific summarization of web pages.
a variant of the trace quotient formulation for dimensionality reduction. the paper describes an algorithm for combining color and texture information for the segmentation of color images. the algorithm uses maximum likelihood classification combined with a certainty based fusion criterion. the algorithm was validated using mosaics of real color textures. it was also tested on real outdoor color scenes and aerial images. this algorithm is part of a more complex system which is currently being designed to assist an operator in updating an old map of an area using aerial images
background estimation based on device pixel structures for silhouette extraction. current trends in computing indicate that there is a great potential for service oriented computing and similar technologies, such as cisco's application oriented networks, where services provide a higher-level of abstraction to traditional applications. in such cases, providing and consuming services and establishing a relationship between consumers (users of services) and producers (providers of services) are still challenging and vastly researched aspects. we define a service location planning problem (slp) that is novel in the approach it takes to match consumers to producers, such that the cost of providing services is minimized while taking into account quality of service constraints of throughput and delay. in previous work, we presented an integer linear programming (ilp) model to formulate the service location planning problem. in this paper, we present lagrangean relaxation of the model for large-scale networks. we use the approach of trick [3] to decrease computational overheads.
a chromosome image recognition method based on subregions. biochips based on digital microfluidics offer a powerful platform for massively parallel biochemical analysis such as clinical diagnosis and dna sequencing. current full-custom design techniques for digital microfluidic biochips do not scale well for increasing levels of system integration. analogous to classical vlsi synthesis, a top-down system-level design automation approach can shorten the biochip design cycle and reduce human effort. we present here an overview of a system-level design methodology that includes architectural synthesis and physical design. the proposed design automation approach is expected to relieve biochip users from the burden of manual optimization of bioassays, time-consuming hardware design, and costly testing and maintenance procedures.
tracking endocardial boundary and motion via graph cut distribution matching and multiple model filtering. the sloan digital sky survey (sdss) science database describes over 230 million objects and is over 1.6 tb in size. the sdss catalog archive server (cas) provides several levels of query interface to the sdss data via the skyserver website. most queries execute in seconds or minutes. however, some queries can take hours or days, either because they require non-index scans of the largest tables, or because they request very large result sets, or because they represent very complex aggregations of the data. these "monster queries" not only take a long time, they also affect response times for everyone else - one or more of them can clog the entire system. to ameliorate this problem, we developed a multiserver multiqueue batch job submission, execution, and tracking system for the cas called casjobs. the transfer of very large result sets from queries over the network is another serious problem. statistics suggested that much of this data transfer is unnecessary; users would prefer to store results locally in order to allow further joins and filtering. to allow local analysis, a system was developed that gives users their own personal databases (mydb) at the server side. users may transfer data to their mydb, and then perform further analysis before extracting it to their own machine. mydb tables also provide a convenient way to share results of queries with collaborators without downloading them. casjobs is built using soap xml web services and has been in operation since may 2004.
image classification using probability higher-order local auto-correlations. color as a distinct feature is widely used for object representation and tracking. however, color-based tracking is often influenced by clutter background and illumination variation. this paper presents a robust color-based tracking method, in which robust color feature is extracted for constructing the observation model under the modified particle filter tracking framework. the object is represented by its dominant color, and the weighted histogram with spatial information of the dominant color is used to optimize object models. in the particle filter framework, an extended iterated likelihood weighting scheme is employed to utilize more valuable particles. the experimental results show it is a real-time robust tracker, and it can obtain more than 30 fps with 2.4 g cpu and 512 mram.
learning bundle manifold by double neighborhood graphs. with the rapid development of the field of industrial process control and the fast popularization of embedded arm processor, it has been a trend that arm processor can substitute the single-chip to realize data acquisition and control. a new kind of remote i/o data acquisition system based on embedded arm platform has been researched and developed in this paper, whose hardware platform use 32-bit embedded arm microprocessor, and software platform use the uc/os-ii core of real-time multitask operating system which is open-source and can be grafted, cut out and solidified. this system can measure all kinds of electrical and thermal parameters such as voltage, current, thermocouple, rtd, and so on. the measured data can be displayed on lcd of the system, and at the same time can be transmitted through rs485 or ethernet network to remote das or dcs monitoring system by using modbus/rtu or modbus/tcp protocol. the system has the dual redundant network and long-distance communication function, which can ensure the disturb rejection capability and reliability of the communication network.
face recognition by estimating facial distinctive information distribution. the analysis shows that the conventional codebook construction of grassmannian subspace packing can not control the performance loss caused by a linear receiver, while a proper unitary perturbation to the codebook is capable of compensating for this performance loss. this paper therefore proposes a novel hierarchical codebook to exploit the gain of unitary perturbation. the hierarchical codebook consists of a grassmannian subcodebook and a proposed perturbation subcodebook. to implement precoding, this paper also presents a successive codeword selection scheme, thus the receiver would successively selects two preferred codewords from grassmannian and perturbation subcodebooks. with the feedback binary indices of these selections, the transmitter uses the product of two preferred codewords as the precoder. the theoretical analysis of the proposed precoding technique shows that the usage of the perturbation subcodebook can improve to a certain degree the system performance in terms of throughput as well as ber, with a small additional feedback overhead, and the proposed codebook would reduce the computational and storage requirements in contrast to the conventional codebook. it is also shown via computer simulations that the proposed technique gives a better ber performance than the single grassmannian codebook based precoding technique does, even if the feedback overhead remains the same.
image content based curve matching using hmcd descriptor. a proportion factor is constructed though the maximum aposteriori probability of examples in test data to select the training examples in incremental learning process. instead of complex normal classify loss expression, the proportion factor lambda is used to estimate the classify loss to improve classification efficiency. the final experiment shows that this algorithm is feasible, and more accurate than simple bayesian classifier. the computing time is highly reduced on the optimal selection of examples in incremental learning process.
non-rigid shape matching using geometry and photometry. zhou wang proposed the structural similarity theory (mssim), guan-hao chen proposed a marginal texture distorts theory on it. jian-xin pang proposed a method of image quality assessment based on the energy of structural distortion (esd). because the theory isn't applied directly on the video field and it don't think over hvs. so we propose a method of video quality assessment based on the sensitive region. first of all, we get the energy of structural distortion (esd)based on the block. then, we get the weighted factor according to the structure information and the movement information. finally, we get the final results according to the hvs. from the last results, we know that the weighting method base on the esd (wesd) is better than the psnr, mssim and essim on the compression loss, smooth loss and noise loss.
model-based 3d object localization using occluding contours. chinese remainder theorem based rsa (crt-rsa) digital signature has important applications in smart cards. previous crt-rsa algorithms such as crt-2 and bos are susceptible to practical hardware fault attacks. in this paper, a new crt-rsa algorithm with countermeasures to hardware fault attacks is proposed. to our knowledge, the proposed algorithm is the first that can resist what we call the single-fault adversarial attacks. the proposed algorithm first computes the signature using crt in a secret algebraic setting, then a set of fault-detection variables are computed to detect possible faults. lastly, the signature is mapped from the secret algebraic setting to the intended setting. by using a random number and the fault detection variables, every step of the algorithm is protected from hardware faults. the output of the algorithm will be fully randomized in case of faults. the crt's speed advantages are also maintained. the proposed algorithm is approximately two times as fast as the direct form rsa for the two-prime case, and about four times as fast for the three-prime case
convolutional virtual electric field external force for active contours. in this paper, a novel approach is proposed for estimating traffic matrices. our method, called pamtram for partial measurement of traffic matrices, couples lightweight origin-destination (od) flow measurements along with a computationally lightweight algorithm for producing od estimates. the first key aspect of our method is to actively select a small number of informative od flows to measure in each estimation interval. to avoid the heavy computation of optimal selection, we use intuition from game theory to develop randomized selection rules, with the goals of reducing errors and adapting to traffic changes. we show that it is sufficient to measure only one flow per measurement period to drastically reduce errors-thus rendering our method lightweight in terms of measurement overhead. the second key aspect is an explanation and proof that an iterative proportional fitting algorithm approximates traffic matrix estimates when the goal is a minimum mean-squared error; this makes our method lightweight in terms of computation overhead. a one-step error bound is provided for pamtram that bounds the average error for the worst scenario. we validate our method using data from sprint's european tier-1 ip backbone network and demonstrate its consistent improvement over previous methods.
solving multilabel mrfs using incremental -expansion on the gpus. video comprises multiple types of textual, audio and visual information, and each of them contains abundant semantic information. therefore multimodal features query and fusion are necessary in video retrieval. in this paper, we propose a new video retrieval model, which adopts multi-model including text, image, semantic concept and camera motion to query video. then relation algebra expression is advanced to fuse multimodal information instead of traditional linear fusion method. in semantic concept detection model, bayesian network based ontology is proposed to extract concepts. the experiments on trecvid 2005 corpus have demonstrated a superior performance compared with exiting key approaches of video retrieval by multimodal information fusion.
image search result summarization with informative priors. this paper is motivated to improve the performance of individual ensembles using a hybrid mechanism in the regression setting. based on an error-ambiguity decomposition, we formally analyze the optimal linear combination of two base ensembles, which is then extended to multiple individual ensembles via pairwise combinations. the cocktail ensemble approach is proposed based on this analysis. experiments over a broad range of data sets show that the proposed approach outperforms the individual ensembles, two other methods of ensemble combination, and two state-of-the-art regression approaches.
globally optimal spatio-temporal reconstruction from cluttered videos. offshore outsourcing has become popular because of cost or skill advantage. china is considered as one of major global software and information service offshore destinations, but it cannot compete with india right now. based on literature review, this paper first presents an overview of the industry. then 38 service providers in china are investigated to give a firm-level analysis of the industry. a framework of factors influencing the industry is presented. influence factors are classified into macro factors, middle factors, and micro factors, each of which is analyzed in detail. it is concluded that china software and information service offshore outsourcing industry is of great potential, but needs marketing and advertising.
exploiting intensity inhomogeneity to extract textured objects from natural scenes. in large scale mobile gaming environments, efficient mechanisms for state update is crucial to allow graceful real-time interaction of a large number of players, under limited wireless network bandwidth. by using the state updating threshold as a key parameter that bridges the resulting state inconsistency (or distortion) and the network traffic, we are able to model the fundamental traffic-distortion tradeoffs. given the tradeoffs for all users, an optimal bandwidth allocation can be derived using well-known convex programming techniques. by exploring the temporal locality of gaming behavior, we also propose a prediction method to realize on-line bandwidth adaptation. using real data trace from a multi-player driving game, the proposed network aware bandwidth allocation method, naba, is able to achieve significant reduction in state distortion compared to two baselines: uniform and proportional policies. naba is also adaptable to variations in system parameters, including bandwidth constraint and network delay.
object detection with multiple motion models. presents a method of generating test sequences for concurrent programs and communication protocols that are modeled as communicating nondeterministic finite-state machines (cnfsms). a conformance relation, called trace-equivalence, is defined within this model, serving as a guide to test generation. a test generation method for a single nondeterministic finite-state machine (nfsm) is developed, which is an improved and generalized version of the wp-method that generates test sequences only for deterministic finite-state machines. it is applicable to both nondeterministic and deterministic finite-state machines. when applied to deterministic finite-state machines, it yields usually smaller test suites with full fault coverage than the existing methods that also provide full fault coverage, provided that the number of states in implementation nfsms are bounded by a known integer. for a system of cnfsms, the test sequences are generated in the following manner: a system of cnfsms is first reduced into a single nfsm by reachability analysis; then the test sequences are generated from the resulting nfsm using the generalized wp-method
unfolding a face: from singular to manifold. static timing analysis safely bounds worst-case execution times to determine if tasks can meet their deadlines in hard real-time systems. however, conventional timing analysis requires that the upper bound of loops be known statically, which limits its applicability. parametric timing analysis methods remove this constraint by providing the wcet as a formula parameterized on loop bounds. this paper contributes a novel technique to allow parametric timing analysis to interact with dynamic real-time schedulers. by dynamically detecting actual loop bounds, a lower wcet bound can be calculated, on-the-fly, for the remaining execution of a task. we analyze the benefits from parametric analysis in terms of dynamically discovered slack in a schedule. we then assess the potential for dynamic power conservation by exploiting parametric loop bounds for parascale, our intra-task dynamic voltage scaling (dvs) approach. our results demonstrate that the parametric approach to timing analysis provides 66%-80% additional savings in power consumption. we further show that using this approach combined with online intra-task dvs to exploit parametric execution times results in much lower power consumption. hence, even in the absence of dynamic scheduling, significant savings in power can be obtained, e.g., in the case of cyclic executives
gender from body: a biologically-inspired approach with manifold learning. a new feature-based method for the correspondence problem is proposed. the used feature is the boundary of a parameter-dependent connected component ((ε,&delta;)-component, wang and bhattacharya, 1996) of an image. we prove that under certain conditions, there is a one-to-one relationship between the sets of the boundary points in a pair of stereo images. this correspondence may be identified through epipolar geometry. furthermore, since such connected components may represent some meaningful objects (wang and bhattacharya, 1996) in images, we may obtain the corresponding objects directly, instead of only the corresponding points or lines as in some other methods which need the process of feature grouping to conduct further analysis. also, a hierarchy of the connected components provides us with a coarse-to-fine matching method to recover the surface corresponding to a connected component
lorentzian discriminant projection and its applications. with the steady development of wimax based broadband wireless access networks, complete and accurate simulation studies become crucial. in an effort to further improve our ns-2 simulation model for mobile wimax, we have implemented a selective repeat automatic retransmission request (sr-arq) mechanism into our model and evaluated its performance and accuracy. in this paper, we present the design and implementation methodology of the wimax sr-arq simulation model in ns-2 and discuss its accuracy via extensive simulation studies. our evaluation clearly shows that sr-arq achieves increased successful packet delivery ratio and goodput, which is true for both non-saturated channels and saturated channels. in each case a cost of increased bandwidth consumption and latency overhead for received packets is also quantitatively analyzed. we believe the implementation of sr-arq in the ns-2 simulation model and its evaluation studies will provide profound empirical values to wimax field test studies.
gender recognition via locality preserving tensor analysis on face images. mithos (micro-kernel threads operating system) is an experimental operating system for embedded systems. the system kernel is a first implementation of the posix minimal real-time system profile. it is based on prior work of a library implementation of pthreads (posix threads). the system is fully preemptive. it supports multi-threading within a single process environment with shared kernel and user space, i.e. real-time tasks are mapped onto posix threads. it exhibits remarkable timing predictability intended for hard real-time requirements. this is achieved by a careful design of only few device drivers. the system has been implemented and tested on the sparc vme architecture. the system includes a fast context switching algorithm for the sparc which outperforms the context switch under sunos and matches the performance under solaris. it supports selective enabling and disabling of hardware components (mmu, caches, etc.) since its sources are available. furthermore, an implementation-defined extension of posix threads for deadline scheduling is presented. overall, the system exhibits slightly faster performance than sunos 4.x and is considerably more predictable in its timing behavior. applications of the kernel range from evaluating the overhead of new language features in ada 95 and its runtime system, verifying static timing predictions on a bare machine, to providing the operating system for small embedded system that require a high timing predictability
interactive super-resolution through neighbor embedding. this paper proposes a distributed video coding scheme based on the zero tree entropy (zte) coding. wyner-ziv theory on source coding with side information is taken as the basic coding principle, which makes independent encoding and joint decoding possible. in this scheme, wavelet transform is used to exploit the spatial correlation of a wyner-ziv frame. the quantized wavelet coefficients are reorganized in terms of the zero tree structure so as to identify the significant and insignificant coefficients. the significance map is intra-codec and transmitted. in particular, the significant coefficients are independently encoded with turbo coder, and only the parity bits are transmitted. at the decoder, a predictive frame generated through motion-compensated prediction is used as the side information, with which the wyner-ziv frame can be conditionally decoded. experimental results show that, compared to the traditional intra-frame coding and pixel-domain wnyer-ziv video coding, the proposed scheme can achieve a better coding performance, especially at low bit rates
a subjective method for image segmentation evaluation. peer-to-peer media streaming has been an important service on the internet in recent years. the data-driven (or mesh-based) structure is adopted by most working systems,in which data scheduling is one of the important problems.however, those frequently used scheduling algorithms are often faced with such a case: a neighbor peer takes up its bandwidth to deliver the packets that other neighbors can also supply, but some packets only held by it are not delivered.these packets can not be delivered in the current scheduling cycle, even though that the other neighbors have surplus bandwidth. this is a kind of waste of bandwidth and decreases the throughput of transmission. in this paper we propose anew scheduling algorithm aiming at the optimal throughput:bipartite-matching based block scheduling algorithm(bbs).we convert the original data scheduling problem to a problem of finding a maximum match on the correspond bipartite graph, then assign data packets to neighbors according to the maximum match. we evaluate the performance of bbs with extensive experiments and the results show that bbs throughput and provides better streaming quality than those frequently used scheduling algorithms.
polymorphous facial trait code. real-time multicast video distribution is an important component of many multimedia applications. our work addresses the fairness problem in feedback-controlled multicast video distribution systems over best effort networks (such as the internet). we have proposed, implemented and experimented with a scheme called destination set grouping (dsg), where a source maintains a small number of video streams, all carrying the same video but each targeted at receivers with different capabilities. each stream is feedback-controlled within prescribed limits by its group of receivers. receivers may move among groups as their capabilities or the capabilities of the network paths leading to them change. in this paper, we focus on the potential for network overloading caused by the transmission of multiple replicated streams. we propose a number of mechanisms to be implemented at the source and the receivers that can help avert this problem. we also describe an evaluation of these schemes using simulation, and discuss a comparison of replicated-stream versus layered-encoding approaches
adaptive-scale robust estimator using distribution model fitting. in this paper, a method of chinese question classification based on ensemble learning is proposed. words and bi-gram are extracted from question as classic features and feature classifiers are constructed. the classifiers are kinds of simple classifier and their generalization ability are not strong enough, but they are a qualified base learner for ensemble because of their low computational cost, and the generalization feasibility improved with the help of ensemble learning. we translate and modify the uiuc question set and trec2001 question set as chinese question set. experimental results on the corpus show that the proposed method can achieve good performance, the classification precision reaches 87.6%, under the fine grained question types.
human action recognition using non-separable oriented 3d dual-tree complex wavelets. this letter deals with the global exponential synchronization of a class of chaotic networks with time delays. based on the halanay inequality technique and the lyapunov stability theory, the global synchronization of a network about its all variables is derived by only considering the global synchronization of its partial variables, and a delay-independent criteria and decentralized control law is derived to ensure the adaptive exponential synchronization of the model and these results are proved to be able to guarantee different exponential convergence rates for the controlled states and the uncontrolled states of the error systems, respectively, and the simpler, less conservative and more efficient results are easy to be verified in engineering applications. finally, an illustrative example is presented to verify the effectiveness of the presented synchronization scheme.
better correspondence by registration. classification is a major task in the gene sequence analysis. based on the general principle of artificial immune system, this paper first constructed a classifier which inducted antibody-antigen identification, immune colonel reproduction, hypermutation, affinity mature and the network suppression, by simulating how the antigens stimulate the immune network and how the immune network responds. then, a "leave-one-out" method was adopted to test the classifier's performance, applying 1-20th dna sequences of art-model-data with class attribute. its accuracy was up to 90%. at last, a well-pleasing result was got on the prediction of 21-40th dna sequences of art-model-data.
person de-identification in videos. design on the web raises challenging questions concerning how users interact with objects, applications, and other users. in this work, we propose a collaborative and interactive client-server design framework and implement a room design system for our study. we have integrated technologies used in distributed computation (java and corba) and computer graphics (vrml). it divides the design process into three tiers. first, collaborative and interactive design, viewing, and publishing. second, scene generation. third, scene database management. our system can be applied in electronic commerce to improve the existing systems by allowing customers to select furniture and to visualize the whole furnished room in 3d
real-time object detection with adaptive background model and margined sign correlation. as an extensible signaling protocol, sip (session initiation protocol) can be applied in developing video conference system. traditionally, for sip-based centralized video conference system, conferencing scale is limited by both the capability of conference server and the availability of bandwidth. the paper focuses on how to keep conferencing when the number of conference users increases. based on the study of the sip protocol, we analyze the drawback of the existing video conference model, and propose a dynamic scalable service model for sip-based video conference. by this model, the extra service requests can be transferred and served in the cooperated conference servers. the paper presents the conferencing control policy of the model in detail. we developed a prototype of video conference system based on the above model. experimental results show this service model works well.
face recognition via aam and multi-features fusion on riemannian manifolds. rissanen's (1978, 1986, 1989, 1996) minimum description length (mdl) principle is a statistical modeling principle motivated by coding theory. for exponential families we obtain pathwise expansions, to the constant order, of the predictive and mixture codelengths used in mdl. the results are useful for understanding different mdl forms
ultrasound speckle reduction via super resolution and nonlinear diffusion. the digital television (dtv) technology becomes widely available and the need for a good interlace-to-progressive conversion (ipc) algorithm becomes more inevitable. in this paper, a new ipc scheme is proposed, which combines several existing techniques and is suitable for hardware implementation. the proposed scheme consists of three components: a spatial linear pre-filter, a motion estimator, and a three stage adaptive recursive (3sar) filter. the proposed adaptive filter improves the performance of the system without requiring complex hardware design. the computer simulations and real-time fpga/asic implementation demonstrate the efficiency and effectiveness of the proposed scheme in hardware applications
better alignments = better translations? we present a new modeling method to evaluate the performance indices of traffic control systems where each intersection has two or four phases. the method is based on the stochastic timed petri net models of isolated intersections. it considers one direction of traffic along a street each time, and the interactions between traffic of different directions are partially approximated by statistical models. by so doing, it dramatically reduces the computing complexity that other petri net-based methods suffer due to the consideration of detailed interactions among all directions of traffic. an example is presented to show the potential application of the new method
mining wiki resources for multilingual named entity recognition. in this paper, a novel passive reduced-order macro-modeling algorithm is proposed for structure dynamics in mems systems that are described by discrete models through the use of finite element methods (fem). in the proposed scheme, the system of equations given by the fem formulation are converted to state-space form such that the state-space equations are compatible with passive krylov subspace methods based on congruent transformations. as an example, modeling, simulation, and experimental studies are presented for a butterfly gyro developed at the imego institute. our simulation results for this example are in very good agreement with previous publications using traditional modeling techniques
a joint model of text and aspect ratings for sentiment summarization. for a signal distributed in rd with an arbitrary density we find the limit distribution as the cell size goes to zero of the quantization noise in the case of a redundant system and the pulse-code modulation scheme. the dimension the support of the limiting distribution equals the largest number of non-comeasurable vectors in the frame and the limit distribution is uniform over its support. this gives the necessary and sufficient conditions for the asymptotic form of the white noise hypothesis.
credibility improves topical blog post retrieval. we present a new global approach to the variable-ordering problem in pseudo-symmetric binary decision diagrams (psbdds). it is based on analyzing symmetric relations between functions' variables. we group all function's variables into symmetry chains and then order the chains based on symmetries. to further reduce the size and the number of levels in psbdds, we introduce a hierarchical decomposition method, based on multiple symmetries. comparing to the previously published results, we substantially reduced the numbers of levels (delay) in psbdds, and for many non-symmetric benchmark functions we did not have to use any repeated variables. results for mcnc benchmark functions are presented
resolving personal names in email using context expansion. we show that even if every node or edge in an n-node butterfly network fails independently with some constant probability, p, it is still possible to identify a set of &theta;(n) nodes between which packets can be routed in any permutation in o(logn) steps, with high probability. although the analysis as complicated, the routing algorithm itself is relatively simple
which are the best features for automatic verb classification. in large-deformation diffeomorphic metric mapping (lddmm), the diffeomorphic matching of images are modeled as evolution in time, or a flow, of an associated smooth velocity vector field v controlling the evolution. the initial momentum parameterizes the whole geodesic and encodes the shape and form of the target image. thus, methods such as principal component analysis (pca) of the initial momentum leads to analysis of anatomical shape and form in target images without being restricted to small-deformation assumption in the analysis of linear displacements. we apply this approach to a study of dementia of the alzheimer type (dat). the left hippocampus in the dat group shows significant shape abnormality while the right hippocampus shows similar pattern of abnormality. further, pca of the initial momentum leads to correct classification of 12 out of 18 dat subjects and 22 out of 26 control subjects
you talking to me? a corpus and algorithm for conversation disentanglement. this paper presents a frequency-estimation algorithm for the adpll designs instead of traditional binary frequency-search algorithm. with the proposed adpll architecture and synchronization process, the lock time can be optimized to two cycles. as the reference clock varies or frequency multiplication switches, lock time holds in two reference clock cycles. an implementation of proposed adpll design is realized in umc 0.18 mum 1p6m cmos technology with core area of 520times530 mum2. the pll has the frequency range of 140 mhz to 1030 mhz with 22ps dco resolution
a single generative model for joint morphological segmentation and syntactic parsing. this paper presents a method for recovering 3d facial shape from single image via learning the relationship between the 2d intensity images and the 3d facial shapes. with a coupled training set, the intensity images and their corresponding facial shapes make up two vector spaces respectively. but only the correlated components in both spaces are useful for inference, so there must be embedded hidden subspaces in each space which preserve the inter-space correlation information. thus by learning the projection onto hidden subspaces based on maximum correlation criteria and optimizing the linear transform between the hidden spaces, 3d facial shape is inferred from the intensity image. the effectiveness of the method is demonstrated on both synthesized and real world data.
which words are hard to recognize? prosodic, lexical, and disfluency factors that increase asr error rates. measurement of visual quality is of fundamental importance for numerous video processing applications. in this paper, we proposed a full-reference color video quality assessment based on quaternion singular value decomposition(qsvd), which takes into account the luminance, chrominance and gradient information of each pixel and treats them as a whole. the algorithm is tested on the video quality experts group (vqeg) phase i fr-tv test dataset. experiments show that it has good correlation with perceived video quality.
classification of semantic relationships between nominals using pattern clusters. we study the application of rissanen's (1989) principle of minimum description length (mdl) to the problem of wavelet denoising and compression for natural images. after making a connection between thresholding and model selection, we derive an mdl criterion based on a laplacian model for noiseless wavelet coefficients. we find that this approach leads to an adaptive thresholding rule. while achieving mean-squared-error performance comparable with other popular thresholding schemes, the mdl procedure tends to keep far fewer coefficients. from this property, we demonstrate that our method is an excellent tool for simultaneous denoising and compression. we make this claim precise by analyzing mdl thresholding in two optimality frameworks; one in which we measure rate and distortion based on quantized coefficients and one in which we do not quantize, but instead record rate simply as the number of nonzero coefficients
an unsupervised approach to biography production using wikipedia. in this paper, we propose a set of human perceptual cues used jointly to automatically detect image orientation. the cues used are: orientation of faces, position of the sky, brighter regions, and textured objects, and symmetry. we combine these cues in a bayesian framework, and the photo acquiring model has been considered carefully as the prior knowledge of the image orientation. results on more than a thousand different images provide a compelling argument that our approach is a viable one.
unsupervised learning of narrative event chains. we have developed a software system, phi-psi, on the connection machine that uses a parallel algorithm to retrieve and use information from a database of 112 known protein structures (selected from the brookhaven protein databank) to predict the structures of other proteins. the &#x03c6; and angles of each amino acid (the angles each amino acid forms with its immediate neighbors) in a protein are used to represent its 3-d structure. phi-psi's algorithm is based on the idea of memory-based reasoning (mbr) [10] and extends it to include a recursive procedure to refine its initial prediction and a &#x0201c;window&#x0201d; of varying sizes to look at different contexts of an input. phi-psi has been tested with all the available data. initial results show that it performs better than distribution-based guesses for most of the &#x03c6; and angle values.
chinese-english backward transliteration assisted with mining monolingual web pages. facial expression animation considering wrinkle formation is an aspiring goal and a challenging task. this paper presents a new geometric wrinkle model that is defined according to facial muscle anatomy for efficient simulation of dynamic wrinkles within expressions. our method is applied to an anatomy-based face model with a multi-layer structure of skin, muscles, and skull. the location and orientation of the wrinkles are automatically determined based on muscle contraction and its influence on the skin. corresponding to two types of facial muscles, the geometric wrinkle model governs evolution of wrinkle amplitude in the local deformed face regions. it provides intuitive parameters for easy control over wrinkle characteristics by taking into account the properties of real wrinkles. results show that this method enables realistic wrinkles synchronized with facial movements to be dynamically simulated and rendered at an interactive rate.
simple semi-supervised dependency parsing. we propose xseed, a synopsis of path queries for cardinality estimation that is accurate, robust, efficient, and adaptive to memory budgets. xseed starts from a very small kernel, and then incrementally updates information of the synopsis. with such an incremental construction, a synopsis structure can be dynamically configured to accommodate different memory budgets. cardinality estimation based on xseed can be performed very efficiently and accurately. extensive experiments on both synthetic and real data sets show that even with less memory, xseed could achieve accuracy that is an order of magnitude better than that of other synopsis structures. the cardinality estimation time is under 2% of the actual querying time for a wide range of queries in all test cases.
generating impact-based summaries for scientific literature. the essence of counter inference is intelligence competition and critical decision making that will result in chained reactions in an open system environment. intelligent agents are capable not only of carrying out negotiations but also playing games. a negotiation could have win-win (or lose-lose) outcomes while a game may result in win-lose situations. the paper proposes counter inference as a unified reasoning paradigm to allow intelligent agents to execute reasoning tasks in either cooperative or non-cooperative ways. based on logic theory, we discuss a framework of counter inference. some examples of counter inference are also given to illustrate its reasoning scenario
learning to rank answers on large online qa collections. in a typical manufacturing system, jobs are released from a production planning stage to a shop floor, where they are allocated to resources like machines. an optimal or near optimal schedule is generally found for those jobs. in reality, the execution of this schedule is often interrupted by dynamic events like unexpected incoming new jobs, machine breakdowns, etc. a rapid recovery or a self-organized feature of the interrupted schedule is desirable for manufacturing resource management. this paper proposes an ant-colony inspired approach to recover the interrupted schedule through a self-organization mechanism. the experiments show that this mechanism significantly improves the quality of the recovered schedules.
forest reranking: discriminative parsing with non-local features. this paper proposes a novel approach for multi-view multi-pose object detection using discriminative shapebased exemplars. the key idea underlying this method is motivated by numerous previous observations that manually clustering multi-view multi-pose training data into different categories and then combining the separately trained two-class classifiers greatly improved the detection performance. a novel computational framework is proposed to unify different processes of categorization, training individual classifier for each intra-class category, and training a strong classifier combining the individual classifiers. the individual processes employ a single objective function that is optimized using two nested adaboost loops. the outer adaboost loop is used to select discriminative exemplars and the inner adaboost is used to select discriminative features on the selected exemplars. the proposed approach replaces the manual time-consuming process of exemplar selection as well as addresses the problem of labeling ambiguity inherent in this process. also, our approach fully complies with the standard adaboost-based object detection framework in terms of real-time implementation. experiments on multi-view multi-pose people and vehicle data demonstrate the efficacy of the proposed approach.
task-oriented evaluation of syntactic parsers and their representations. the pervasiveness of computer networks in our economic system has increased our vulnerability to systems-based attacks. these attacks are addressed in this minitrack, which covers issues related to anticipating, detecting, mitigating and preventing them. in particular, the minitrack focuses on (1) cyber-threats and information security, which includes assaults on computer systems themselves as well as fraud or other actions taken through the use of computers, (2) emergent risks in operations, which comprise heretofore-underestimated risks from the introduction of technology and technology-based infrastructure, (3) compliance and prevention, (4) information sharing (public regulation or private, confidential information pooling of risks and disclosure might be an interesting option), and (5) modeling and theory building of security topics.
evaluating roget's thesauri. majority-logic decoding is attractive for three reasons: (1) it can be simply implemented; (2) the decoding delay is short; and (3) its performance, while suboptimal, is always superior to bounded distance decoding. for these reasons, majority-logic decodable cyclic codes are very suitable for error control in high speed digital data transmission systems. among the majority-logic decodable codes, the one-step decodable codes can be most easily implemented; they employ a single majority-logic gate. in this paper we study a class of one-step majority-logic decodable cyclic codes. first, we describe these codes in a simple manner. second, a way of finding the orthogonal polynomials for decoding these codes is presented. third, we show that for a given error correction capability, the ratio of the number of parity digits to the code length goes to zero as the code length increases. for error correction capabilities of the form 2k-1 or 2k, we determine the dimensions of the codes exactly.
automatic editing in a back-end speech-to-text system. in this paper, we propose an approach for body detection and tracking with a hierarchical and salient-half-body-prior scheme and apply it in real dynamic scenes. the human region is firstly located by an svm classifier with histogram of oriented gradients (hog). two image observations, motion foreground and edge distance map, are then applied for body detection. in detail, the torso part is first roughly initialized, and then parts are localized in a salient-prior half-body sampling scheme by maximizing body configuration probability with both parts likelihood and body geometry constraints. for body tracking, the color-texture appearance templates of parts extracted in detection phase are further used in tracking process. the approach has been tested on soccer and skating videos and got good results.
generalized expectation criteria for semi-supervised learning of conditional random fields. service oriented architecture (soa), web services, asynchronous javascript and xml (ajax), and other new web technologies have revolutionized the use of geospatial web applications. the geobrain project has built a powerful online extensible and scalable geospatial analysis system based on soa. this system utilizes web services and ajax to increase the interactive capabilities of user interfaces and improve the user experience. it provides geosciences community a highly interoperable way of accessing open geospatial consortium (ogc) web services for geospatial data discovery, retrieval, visualization and analysis. it also leverages web service standards to enable geospatial services discovery, selection, negotiation and invocation to be used in making more informed decisions.
unsupervised discovery of generic relationships using pattern clusters and its evaluation by automatically generated sat analogy questions. in this paper, the generalized gaussian distribution is employed first to model the dct coefficients of image data from mpeg-4 fine-granularity scalability (fgs) frame. then, according to the quantization theory, the distortion-rate function of the generalized gaussian model is analyzed and it is concluded that the derivative of the distortion-rate function first decreases, and then increases up to the boundary of 6.02 as the bit rate increases. for actual fgs coding, the derivative of actual distortion-rate function usually decreases as the rate increases, and then begins to increase slowly at a comparatively high bit rate. finally, based on above observations, a rate-distortion (r-d) model is proposed to approximate the actual distortion-rate function. experiments show that the proposed r-d model is accurate and flexible.
gestural cohesion for topic segmentation. this paper presents middleware enabling mutual and equal transfer of computing power between individuals, as in the original idea behind p2p, while also supporting large-scale distributed computation utilizing heterogeneous pcs. this goal is strongly supported by a network overlay over which peers can communicate with each other directly and bidirectionally. we made use of a general-purpose p2p library, jxta, supporting the common requirements of p2p software, including network overlay. other features of the p2p library, such as ad-hoc self-organization, discovery and grouping of peers, also support our middleware efficiently. in this paper, we propose and evaluate an application of those p2p concepts to virtual resource transfer and parallel computation with aggregated resources. however, such a p2p library imposes a certain amount of overhead on the middleware in terms of communication performance. measured communication performance and throughput of an application program shows the feasibility of the application of p2p concepts. the middleware achieves 100 &times; 106 bps communication performance and over a 20 fold increase in speed with 32 computers, even though the granularity of workunits is as fine as less than a second.
generalizing word lattice translation. the authors study the performance of online algorithms in environments where no value is obtained for the partial execution of a request. they prove that no online scheduling algorithm can have a competitive factor greater than 0.25 times the optimal. they further refine this bound by considering the effect of the loading factor. other models of task systems (for example, tasks systems consisting of many types of task requests), are considered. similar upper bounds on the competitive factor that can be made by online scheduling algorithms in these environments are proved. it is shown that the performance bound of 0.25 is tight by means of a simple online uniprocessor scheduling algorithm has a competitive factor of 1/4. the authors extend the discussion to systems with dual processors. they show that the upper bound for the dual-processor online scheduling problem is 1/2 if all tasks have the same value density. this bound is tight if the tasks all also have zero laxity
unsupervised multilingual learning for morphological segmentation. modeling background and segmenting moving objects are significant techniques for video surveillance and other video processing applications. most existing methods of modeling background and segmenting moving objects mainly operate in the spatial domain at pixel level. in this paper, we present three new algorithms (running average, median, mixture of gaussians) modeling background directly from compressed video, and a two-stage segmentation approach based on the proposed background models. the proposed methods utilize discrete cosine transform (dct) coefficients (including ac coefficients) at block level to represent background, and adapt the background by updating dct coefficients. the proposed segmentation approach can extract foreground objects with pixel accuracy through a two-stage process. first a new background subtraction technique in the dct domain is exploited to identify the block regions fully or partially occupied by foreground objects, and then pixels from these foreground blocks are further classified in the spatial domain. the experimental results show the proposed background modeling algorithms can achieve comparable accuracy to their counterparts in the spatial domain, and the associated segmentation scheme can visually generate good segmentation results with efficient computation. for instance, the computational cost of the proposed median and mog algorithms are only 40.4% and 20.6% of their counterparts in the spatial domain for background construction.
assessing dialog system user simulation evaluation measures using human judges. the existing network security assessment models have the problems of inadequate capacity of quantitative analysis and lacking for vulnerabilities correlation. to address these problems, a hierarchical network security evaluation model is proposed. the network is divided into vulnerability level, service level, equipment level and network level. the model uses attack graph to correlate the network vulnerabilities, and then calculates the probabilities of successfully exploiting the vulnerabilities. on this basis, the quantitative risks of each level are calculated. since this model much more accords with the features of network structure, it is an effectively guidance for the network administrators to develop and improve the network security policies.
searching questions by identifying question topic and question focus. the two fundamental advantages of video over still imagery are: (i) the ability capture temporal information, and (ii) the ability to acquire a continuously varying set of views of a scene. these advantages are obtained, however, at the cost of vastly increased amount of data. this paper describes an approach to video representation that is based on frame-to-frame alignment, mosaic construction, and 3d parallax recovery. the basic motivation behind our approach is to enable rapid access to the contents, while maintaining the data in a form as close to the source as possible. this representation supports a wide variety of applications that involve transmission, storage, visualization, retrieval, analysis, and manipulation of video sequences
the tradeoffs between open and traditional relation extraction. an effective method for fuzzy image enhancement was presented by russo, which was controlled by tuning of one parameter. the fixed parameter was used for the entire image resulting in over blurring or sharpening of image features in some parts of the image. on the basis of these, in this paper, we applied russo's algorithm on different kinds of noise and proposed an efficient method to obtain the parameter values adaptively. firstly, each pixel went through a phase of smoothing and then followed by a phase of combining smoothing and sharpening; secondly, to effectively enhance image, each pixel local feature was adaptively assigned different parameter values by evaluating pixel local features through a fuzzy membership function; finally, compared with russopsilas method and other methods, experimental results indicated that the proposed method could achieve better performance than traditional methods for the enhancement of images corrupted with impulse and gaussian noise.
learning bigrams from unigrams. clustering web search result is a promising way to help alleviate the information overload for web users. in this paper, we focus on clustering snippets returned by google scholar. we propose a novel similarity function based on mining domain knowledge and an outlier-conscious clustering algorithm. experimental results showed improved effectiveness of the proposed approach compared with existing methods.
word clustering and word selection based feature reduction for maxent based hindi ner. a robot, which is composed of adaptive mobile mechanism, is developed for the purpose of performing the internal inspection tasks of pipelines. adaptability and efficiency are the basic considerations for this robot. based on these concepts, a prototype is designed and fabricated. the proposed adaptive mobile mechanism equipped with one actuator can perform two working modes, a normal working mode and an assistant enhanced mode. robot under the normal working mode is used for moving in pipe or monitoring the inner surface of the pipe. on the other hand, robot under the assistant enhanced mode will produce a larger torque to help itself surmount an obstacle in the pipe without any other driving actuator. this special feature is achieved by applying a power transmission mechanism. the rotation problem of the stator is solved according to the calculation results of the robot kinematics. basic experiments have been conducted to testify the adaptability and efficiency of the robot.
maxsim: a maximum similarity metric for machine translation evaluation. this paper presents our study over the effect of complementary energy feedback on virtual slope walking, while virtual slope walking is our new biped gait generation method inspired by passive dynamic walking. the energy feedback strength is defined and the walking is modeled as a step-to-step function. the jacobi matrix eigenvalues of the function are calculated together with the basin of attraction. from the analysis, we find the characteristic of complementary energy feedback is being effective on a fast gait but weak on a slow one. by making use of the complementary energy feedback in walking experiment, our robot achieves speed change from 1.5 leg/s to 4.1 leg/s.
soft syntactic constraints for hierarchical phrased-based translation. distributed and heterogeneous environments present significant challenges to complex software systems, which must operate in the context of continuously changing loads, with partial or out-of-date information on resource capabilities. a distributed query processor (dqp) can be used to access and integrate data from distributed sources, as well as for combining data access with data analysis. however in heterogeneous environments, statically constructed query plans may commit a query evaluator to following significantly suboptimal strategies. as such, there is considerable interest in using adaptive query processors (aqps) in such settings to provide self-optimizing behaviour. however, with many possible adaptive strategies available, it is important that aqps can be constructed in a systematic and efficient manner. this paper outlines an approach to the development of aqps in which adaptive behaviour is implemented using cooperating monitoring, assessment and response components. it is shown how this decomposition has been applied in the development of an adaptive dqp system for service-based grids, which reallocates load at query runtime, thereby supporting self-optimization.
regular tree grammars as a formalism for scope underspecification. copyright protection of digital contents, as one of the most important application of digital watermarks, works by watermark verification. in traditional watermark authentication schemes, a prover exposed a watermark to be present in a digital data to the possible dishonest verifier. however, a potential attacker is able to spoil or remove the watermark entirely once classified information like the watermark or the embedding key is known. some of previous schemes proposed as solutions have not really achieved desirable results. their lack of security and validity is the most serious problem. in this paper, we propose a secure watermark verification scheme based on zero knowledge protocols and public-key encryption scheme in order to solve this problem. there is no secret information that can be used for removing watermark disclosed during the verification process. it has considerable advantages over previously proposed schemes in terms of security and validity
sentence simplification for semantic role labeling. video encoding now is being implemented in various computing platforms with different computing capability, the requirement on the encoding complexity is also different according to different applications. as the most computation-intensive part of video encoding, the me (motion estimation) should have a scalable complexity. this paper proposes a me algorithm with fine-granular scalable complexity, a more important feature of the proposed algorithm is that it seeks for the complexity-distortion optimization. the given computation budget will be allocated to each mb (macroblock) in one frame. each mb will consume its allocated computation by a hybrid search pattern. experimental results show that the proposed algorithm can get a better computation-distortion performance than the existing me algorithms
multi-task active learning for linguistic annotations. collaborative filtering is a key technique in recommender system and applied widely in e-commerce. in reality, due to data sparseness, similarity of users is computed wrongly, which results that really similar users maybe filtered out while false similar users are exploited to produce recommendation. in this paper, two pre-filling methods based on community, respectively simple pre-filling based on community (pfci) and pre-filling based on community association (pfcii) are presented to overcome the sparsity. if user-item pair is null, its rating is pre-filling by using our method before traditional collaborative filtering is executed. the experiment shows better performance of our methods.
semantic class learning from the web with hyponym pattern linkage graphs. given two sets da and db of multidimensional objects, a spatial region r, and a critical distance dc, an optimal-nearest- neighbor (onn) query retrieves outside r, the object in db with maximum optimality. let car (sp,p) be the cardinality of the subset sp of objects in da which locate within r and are enclosed by the vicinity circle centered at p with radius dc. then, an object o is said to be better than another one o' if (i) car (so,o) = car (so,o'), or (ii) when car (so,o) = car (so',o') the sum of the weighted distance from each object in so to o is smaller than the sum of the weighted distance between every object in so' and o'. this type of queries is quite useful in many decision making applications. in this paper, we formalize the onn query, develop the optimality metric, and propose several algorithms for finding optimal nearest neighbors efficiently. our techniques assume that both da and db are indexed by r-trees. extensive experiments demonstrate the efficiency and scalability of our proposed algorithms using both real and synthetic datasets.
a discriminative latent variable model for statistical machine translation. existing algorithms for learning bayesian network require a lot of computation on high dimensional itemsets which affects accuracy especially on limited datasets and takes up a large amount of time. to address the above problem, we propose a novel bayesian network learning algorithm mrmrg, max relevance-min redundancy greedy. mrmrg algorithm is a variant of k2 which is a well- known bn learning algorithm. we also analyze the time complexity of mrmrg. the experimental results show that mrmrg algorithm has much better efficiency and accuracy than most of existing algorithms on limited datasets.
semi-supervised convex training for dependency parsing. future cmp designs that will integrate tens of processor cores on-chip will be constrained by area and power. area constraints make impractical the use of a bus or a crossbar as the on-chip interconnection network, and tiled cmps organized around a direct interconnection network will probably be the architecture of choice. power constraints make impractical to rely on broadcasts (as token-cmp does) or any other brute-force method for keeping cache coherence, and directory-based cache coherence protocols are currently being employed. unfortunately, directory protocols introduce indirection to access directory information, which negatively impacts performance. in this work, we present dico-cmp, a novel cache coherence protocol especially suited to future tiled cmp architectures. in dico- cmp the role of storing up-to-date sharing information and ensuring totally ordered accesses for every memory block is assigned to the cache that must provide the block on a miss. therefore, dico-cmp reduces the miss latency compared to a directory protocol by sending coherence messages directly from the requesting caches to those that must observe them (as it would be done in brute-force protocols), and reduces the network traffic compared to token-cmp (and consequently, power consumption in the interconnection network) by sending just one request message for each miss. using an extended version of gems simulator we show that dico-cmp achieves improvements in execution time of up to 8% on average over a directory protocol, and reductions in terms of network traffic of up to 42% on average compared to token-cmp.
learning document-level semantic properties from free-text annotations. today, the scale of high performance computing (hpc) systems is much larger than ever. some hpc systems consist of thousands or even tens of thousands of processors. the larger scale leads to a challenge that how to deal with process failures. the most important programming tool for hpc is mpi (message passing interface). there are some existing methods to deal with fault-tolerance, such as mpich-v, starfish, mpi/ft and so on, using the mpi context. most of them do the checkpoint on disk. in this paper, some erasure codes, which used in raid systems usually, are applied to deal with the fault-tolerance in-memory. based on fault-tolerance-mpi (ft-mpi) platform, raid4, raid5, rdp and x-code are implanted to do the checkpoint in-memory. the experimental results show that rdp is feasible for double-fault-tolerance in-memory.
efficient, feature-based, conditional random field parsing. this paper proposes a mobile, intelligent agent-based framework that allows buyers and sellers to perform business at remote locations. a business participant can generate a mobile, intelligent agent via a mobile device and dispatch the agent to the internet to do business. the proposed framework brings in several advantages: first, it provides great convenience for traders as business can be conducted anytime and anywhere. secondly, the user is freed from the time-consuming task of finding and negotiating with appropriate traders. thirdly, it addresses the problem of limited and expensive connection time for mobile users: a trader can disconnect her mobile device from its server after launching a mobile agent. later on, she can reconnect and call back the agent for results, therefore minimizing the connection time. finally, by complying with the standardization body of fipa, this flexible framework increases the interoperability between agent systems and provides high design scalability.
optimal $k$-arization of synchronous tree-adjoining grammar. location service provides position of mobile destination to source node so that position based routing can be applied. several quorum-based location services have been proposed. these location service protocols suffer from complex structure with high overhead, or host location foreknowledge, and difficulty in quorum construction. to overcome those deficiencies, we propose a novel quorum-based location service. in the proposed scheme, location databases are stored in the network nodes themselves, which form a self-organizing virtual backbone network. quorum system is constructed on the virtual backbone network in conformity to irregular grid rule. every mobile node will notify its location update information to irregular grid quorum system so that other hosts can obtain the mobile node location through irregular grid quorum system. the simulation results show that our proposed location service leads to high success rate, appropriate quorum size and good load.
multilingual harvesting of cross-cultural stereotypes. we present a framework for acquiring and restoring images of warped documents to their original planar shapes. image capturing of warped documents often results in warped images. most digital restoration approaches make use of 2d image processing methods which are dependent on the content of the images. some recent work attempts to remove this constraint by working directly on the 3d shape of the warped documents. in our framework, we improve on this recent approach to make it more efficient and stable. first we capture the warped surface representation through a set of active lighting from a laser range scanner onto the document surface. this gives us an accurate 3d representation of the document shape. next by using a stick constraint and a stable numerical integrator, we can digitally flatten the 3d model to a planar shape. this simple approach avoids potential instability problem and is fast. restoration results for a few types of warped documents are demonstrated and a significant improvement over the original images can be observed.
applying a grammar-based language model to a simplified broadcast-news transcription task. in this paper, we present the approach and architecture of target: two-way web service router gateway, for two-way web service interaction crossing enterprise domain and firewall. it provides a full support for asynchronous outbound operation and event notification in communication services. target addresses an acute issue for internet applications that today's enterprise nats and firewalls only allow outbound http request from the inside to the outside and block any request from the outside to the inside, which is a serious problem for two-way web services. target is a generic solution to allow two-way web service interaction to traverse legitimately through nats and strictly configured firewalls; and it is based on two-way soap message tunneling, service local registry, and service routing to bridge two-way web service interaction. a research target system has been implemented and applied to real time communication services, e.g. conferencing. extensive experiments on target are performed, and its performance with various sizes of soap messages is studied. the applicability and feasibility of target for two-way web service interaction is verified
correcting misuse of verb forms. designing effective image priors is of great interest to image super-resolution (sr), which is a severely under-determined problem. an edge smoothness prior is favored since it is able to suppress the jagged edge artifact effectively. however, for soft image edges with gradual intensity transitions, it is generally difficult to obtain analytical forms for evaluating their smoothness. this paper characterizes soft edge smoothness based on a novel softcuts metric by generalizing the geocuts method . the proposed soft edge smoothness measure can approximate the average length of all level lines in an intensity image. thus, the total length of all level lines can be minimized effectively by integrating this new form of prior. in addition, this paper presents a novel combination of this soft edge smoothness prior and the alpha matting technique for color image sr, by adaptively normalizing image edges according to their alpha-channel description. this leads to the adaptive softcuts algorithm, which represents a unified treatment of edges with different contrasts and scales. experimental results are presented which demonstrate the effectiveness of the proposed method.
collecting a why-question corpus for development and evaluation of an automatic qa-system. new electronic technologies for signal analysis raise the possibility of sampling very rapidly, with a time-varying density, and determining empirically both the sampling rate and the window width as the signal evolves in time. these opportunities also point to the possibility of sequentially sampling in a time-varying way in more traditional problems. motivated by these ideas, we establish a sampling formula, valid in cases where both sampling rate and window width may be varied. the formula states that, in terms of the ways in which these quantities should alter with time, optimal performance is achieved when the window width is inversely proportional to squared sampling rate, and sampling rate is directly proportional to squared bias.
mining parenthetical translations from the web by word alignment. wide-area distribution raises significant performance problems for traditional query processing techniques as data access becomes less predictable due to link congestion, load imbalances, and temporary outages. non-blocking joining query execution is a promising approach to coping with unpredictability in such environments because of reactively scheduling background processing. classical non-blocking two-way joining technique based on hash-merge (hmj), however, fail to deliver acceptable performance in such a scenario where relatively short intermittent delay exists in the gross. we have developed a fairly fine-grained hash-merge join, called hmj-fg, which has employed a replacement selection tree, allowing many disparted segments to be active in parallel. using the optimization implementation along with simulation obtained by tao, we show that hmj-fg is an effective solution for providing fast query responses to users even in the presence of the longer-term of data sources appeared as unavailability. theory and experimental results show that our technique delivers results significantly fast under unreliable network.
a probabilistic model for fine-grained expert search. peer-to-peer, or p2p sharing has gone through fast growth in recent years and drawn the interests of information systems (is) researchers. however, there is a lack of empirical study on the individual's behavior of using p2p sharing software. given the current existence of various uncertainties in p2p sharing, it is crucial to understand the factors that affect individual's usage of p2p sharing software. in this paper, we develop and empirically test a usage intention model which includes trust in the vendor of p2p sharing software and perceived risk as two major antecedent beliefs to the usage intention. several trust antecedents are also identified in the model. our preliminary results show the support for the model, and offer some important implications for software vendors in p2p sharing industry and regulatory bodies.
automatic syllabification with structured svms for letter-to-phoneme conversion. sign language recognition is to provide an efficient and accurate mechanism to transcribe sign language into text or speech. state-of-the-art sign language recognition should be able to solve the signer-independent continuous problem for practical applications. a divide-and-conquer approach, which takes the problem of continuous chinese sign language (csl) recognition as subproblems of isolated csl recognition, is presented for signer-independent continuous csl recognition. in the proposed approach, the improved simple recurrent network (srn) is used to segment the continuous csl. the outputs of srn are regarded as the states of hidden markov models (hmm) in which the lattice viterbi algorithm is employed for searching for the best word sequence. experimental results show that the srn/hmm approach has a better performance than the standard hmm.
unsupervised translation induction for chinese abbreviations using monolingual corpora. in today's information society, privacy protection has become a very important concern. in this paper we research the inference problems due to functional dependencies (fd) and multi-valued dependencies (mvd) in multilevel secure database (mls) with element classification instances. to deal with the secure problem brought by inference channels we present our fd and mvd based inference control algorithms working on the finest-grained data level which greatly improve the availability of data and minimize the information loss
distributional identification of non-referential pronouns. the computational grid is rapidly evolving into a service-oriented computing infrastructure that facilitates resource sharing and large-scale problem solving over the internet. service discovery becomes an issue of vital importance in utilizing grid facilities. this paper presents rosse, a rough sets-based search engine for grid service discovery. building on the rough sets theory, rosse is novel in its capability to deal with the uncertainty of properties when matching services. in this way, rosse can discover the services that are most relevant to a service query from a functional point of view. since functionally matched services may have distinct nonfunctional properties related to the quality of service (qos), rosse introduces a qos model to further filter matched services with their qos values to maximize user satisfaction in service discovery. rosse is evaluated from the aspects of accuracy and efficiency in discovery of computing services.
robustness and generalization of role sets: propbank vs. verbnet. the advent of dna microarray technologies has revolutionized the experimental study of gene expression. clustering is the most popular approach of analyzing gene expression data and has indeed proven to be successful in many applications. our work focuses on discovering a subset of genes which exhibit similar expression patterns along a subset of conditions in the gene expression matrix. specifically, we are looking for the order preserving clusters (op-cluster), in each of which a subset of genes induce a similar linear ordering along a subset of conditions. the pioneering work of the opsm model, which enforces the strict order shared by the genes in a cluster, is included in our model as a special case. our model is more robust than opsm because similarly expressed conditions are allowed to form order equivalent groups and no restriction is placed on the order within a group. guided by our model, we design and implement a deterministic algorithm, namely opc-tree, to discover op-clusters. experimental study on two real datasets demonstrates the effectiveness of the algorithm in the application of tissue classification and cell cycle identification. in addition, a large percentage of op-clusters exhibit significant enrichment of one or more function categories, which implies that op-clusters indeed carry significant biological relevance.
combining speech retrieval results with generalized additive models. efficient and intelligent music information retrieval is a very important topic of the 21st century. with the ultimate goal of building personal music information retrieval systems, this paper studies the problem of identifying "similar" artists using both lyrics and acoustic data. in this paper, we present a clustering algorithm that integrates features from both sources to perform bimodal learning. the algorithm is tested on a data set consisting of 570 songs from 53 albums of 41 artists using artist similarity provided by all music guide. experimental results show that the accuracy of artist similarity classifiers can be significantly improved and that artist similarity can be efficiently identified.
distributed word clustering for large scale class-based language modeling in machine translation. for group-oriented applications, designing secure and efficient group key management schemes is a major problem. we present a group key management scheme for dynamic peer networks, which supports join, leave, merge and partition events. in the scheme, the numbers of rounds and messages are close to the lower bounds of those for dynamic group key management, and the length of messages and computation costs are less than those of the existing schemes. furthermore, this scheme provides forward secrecy, backward secrecy and key independence
extraction of entailed semantic relations through syntax-based comma resolution. aimed at the overvoltage trouble of electric equipments in 500 kv gis substation caused by lightning strikes to overhead line, four protection solutions were proposed. through atp simulation, the protection margins and economy of the protective devices such as transformer, reactor, cvt and gis-inlet were estimated. it is concluded that installation of a set of outdoor type surge arrester at line inlet and a set of indoor type one at main transformers may effectively reduce the lightning overvoltage based on chaos fractal theory, fractal dimension and kolmogorov entropy of voltage wave at transformer were calculated and compared, and the positive correlation between the protection margin and kolmogorov entropy was proved. it is proposed that protection solution may be determined using chaos characteristics of voltage wave, it is satisfactory when potection point p is not less than the reference point pi, namely, pgespi.
evaluating a crosslinguistic grammar resource: a case study of wambaya. this paper presents a method for evaluating an upper bound of simultaneous switching gates in combinational circuits. in this method, the original circuit is partitioned into subcircuits, and the upper bound is approximately computed as the sum of maximum switching gates for all subcircuits. in order to increase the accuracy, we adopted an evaluation function that takes account of both the interconnections among subcircuits and the number of generated subcircuits. experimental results for iscas circuits show that the method efficiently evaluates the upper bounds of switching gates
applying morphology generation models to machine translation. most tracking algorithms are based on the maximum a posteriori (map) solution of a probabilistic framework called hidden markov model, where the distribution of the object state at current time instance is estimated based on current and previous observations. however this approach is prone to errors caused by temporal distractions such as occlusion, background clutter and multi-object confusion. in this paper we propose a multiple object tracking algorithm that seeks the optimal state sequence which maximizes the joint state-observation probability. we name this algorithm trajectory tracking since it estimates the state sequence or "trajectory" instead of the current state. the algorithm is capable of tracking multiple objects whose number is unknown and varies during tracking. we introduce an observation model which is composed of the original image, the foreground mask given by background subtraction and the object detection map generated by an object detector the image provides the object appearance information. the foreground mask enables the likelihood computation to consider the multi-object configuration in its entirety. the detection map consists of pixel-wise object detection scores, which drives the tracking algorithm to perform joint inference on both the number of objects and their configurations efficiently.
combining multiple resources to improve smt-based paraphrasing model. we examine a knowledge representation architecture to support context interchange mediation. for autonomous receivers and sources sharing a common subject domain, the mediator's reasoning engine can devise query plans integrating multiple sources and resolving semantic heterogeneity. receiver applications obtain the data they need in the form they need it without imposing changes on sources. the kr architecture includes: 1) data models for each source and receiver, 2) subject domain ontologies, containing abstract subject matter conceptualizations that would be known to experienced practitioners in the industry, and 3) context models for each source and receiver that explain how each source or receiver data model implements the abstract concepts from a subject domain ontology. examples drawn from the fixed income securities industry illustrate problems and solutions enabled by the proposed architecture.
hedge classification in biomedical texts with a weakly supervised selection of keywords. route flap damping is a mechanism generally used in network routing protocols. its goal is to limit the global impact of unstable routes by temporarily suppressing routes with rapid changes over short time periods. although route damping is a clearly defined and simple procedure at each router, its effect in a large network setting is not well understood. we show that the current damping design leads to the intended behavior only under persistent route flapping. when the number of flaps is small, the global routing dynamics deviates significantly from the expected behavior with a longer convergence delay. previous work observed that a single route flap can falsely trigger route suppression due to path exploration. however our simulations show that this false suppression only accounts for 30% of the convergence delay after a single route flap. our study reveals previously unknown interactions between reuse timers at different routers. route suppression and reuse at different routers are triggered at different times and thus affect the number of updates received by other routers. in turn, this impacts other routers' damping behavior. we propose to use root cause notification to eliminate both false suppression and undesirable timer interaction
exploiting feature hierarchy for transfer learning in named entity recognition. summary form only given. facola (face coder based on location and attention) is proposed for potential applications such as compression of face pictures used in ic and id cards. the face locator locates a face in an image using template matching and eigenface techniques. the attention detector detects high attention and low attention in the located face according to their different frequency characteristics. for high attention, usually high quality or lossless coding is required. the dct is not suitable for such a case because it will not lead to an efficient compaction of the image energy and variable length coding (vlc) cannot be done efficiently. so a dpcm coder with three directional predictors is presented instead of the dct. the prediction difference is quantized and the entropy coded dpcm coder supports lossless and lossy compression. the dct coder is adopted for low attention and non-face area compression using different quantization factors
name translation in statistical machine translation - learning when to transliterate. soft-core microprocessors mapped onto field-programmable gate arrays (fpgas) represent an increasingly common embedded software implementation option. modern fpga soft-cores are parameterized to support application-specific customization, wherein pre-defined units, such as a multiplication unit or floating-point unit, may be included in the microprocessor architecture to speed up software execution at the expense of increased size. we introduce a methodology for fast application-specific customization of a parameterized fpga soft core, using synthesis and execution to obtain size and performance data in order to create a tool that can be used across a variety of tool platforms and fpga devices. as synthesizing a soft core takes tens of minutes, developing heuristics that execute in an acceptable time of an hour or two, yet find near-optimal results, is a challenge. we consider two approaches, one using a traditional cad approach that does an initial characterization using synthesis to create an abstract problem model and then explores the solution space using a knapsack algorithm, and the other using a synthesis-in-the-loop exploration approach. we compare approaches for a variety of design constraints, on 11 eembc benchmarks, using an actual xilinx soft-core processor, and for two different commercial xilinx fpga devices. our results show that the approaches can generate a customized configuration exhibiting roughly 2x speedups over a base soft core, reaching within 4% of optimal in about 1.5 hours, including complete synthesis of the soft-core onto the fpga, compared to over 11 hours for exhaustive search. our results also show that including synthesis-in-the-loop, compared to a traditional cad approach, improved speedups by an average of 20% when size constraints were tight. the approaches may also be applicable to soft-core processors targeted to asics in addition to fpgas
refining event extraction through cross-document inference. "the marauder's map" is a magical map in j. k. rowling's fantasy series, "harry potter and the prisoner of azkaban". it shows all moving objects within the boundary of the "hogwarts school of witchcraft and wizardry". in this paper, we introduce a similar attack to location privacy in wireless networks. our system, namely the digital marauder's map, can reveal the locations of wifi-enabled mobile devices within the coverage area of a single high-gain antenna. the digital marauder's map is built solely with off-the-shelf wireless equipments, and features a mobile design that can be quickly deployed to a new location and instantly used without training. we present a comprehensive set of theoretical analysis and experimental results which demonstrate the coverage and localization accuracy of the digital marauder's map.
learning effective multimodal dialogue strategies from wizard-of-oz data: bootstrapping and evaluation. this paper summarizes a methodology for reliability prediction of new products where field data are sparse, and the allowed number & length of experiments are limited. the methodology relies on estimating a set where the unknown parameters are most likely to be found, calculation of an upper bound for the reliability metric of interest conditioned that the parameters reside in the estimated set, and tightening the bounds via design of experiments. models of failure propagation, failure acceleration, system operations, and time/cycle to failure at various levels of fidelity & expert elicited information may be incorporated to enhance the accuracy of the predictions. the application of the model is illustrated through numerical studies.
pdt 2.0 requirements on a query language. the v-detector generation algorithm is a kind of negative selection algorithm (nsa) inspired by biological immune system (bis). in this paper, v-detector generation algorithm is simply introduced. the problem that v-detector generation algorithm can not meet the change of parameters in significant level is also pointed out. this problem will cause instable algorithm performance. in the meantime, it will cause the algorithm failed under the circumstance of some parameter values. this paper analyzed the reason that caused the problem theoretically and the relevant solution is proposed. the experiment results showed that the proposed solution solved the problem existed in original algorithm successfully and make the performance more stable and reliable. the improved algorithm can really adapt to different values of significant level and obtain better detection performance.
forest-based translation. this paper describes a new approach to invariant object recognition. in this approach, an object is represented by a set of key points called landmarks. all possible translation, scaling, and rotation of the object are placed into an equivalent class and associated to a single point in a complex projective space called the shape space. object recognition is then achieved by distance calculations in this shape space. this approach is invariant to object translation, scaling, and rotation, and is computationally simple. our experimental results also indicate that it is insensitive to noise and moderate occlusions
randomized language models via perfect hash functions. data management in very large distributed systems (vlds) is considered. a replication strategy that can offer a tradeoff between cost and quality of service is discussed. imperfect replicated data, called quasi-copies, are considered in conjunction with the notion of file stashing. stashing a file means placing copies of that file in several nodes of a computer network to augment the availability of the file, i.e. to be able to access the file when the file server that holds it is no longer reachable. the stash propagation problem of how to efficiently propagate updates to the stashed copies throughout the system is studied
selecting query term alternations for web search by exploiting query contexts. we propose a client-server graphics design framework and implement a room design system using corba. we have integrated technologies used in distributed computation (java and corba) and computer graphics (vrml). to support multiuser collaborative design, we propose a supplier-consumer communication approach and implement it using the event service in corba. our system can be applied in electronic commerce to improve the existing systems by allowing customers to select furniture and to visualize the whole furnished room in 3d
improving parsing and pp attachment performance with sense information. with the advance of hardware and software technology, modern phased array radars are now built with commercial off-the-shelf (cots) components, and it opens up a new era in real-time resource scheduling of digital signal processing. this paper targets the essential issues in building a component-oriented signal processor (sp), which is one of the two major modules in modern phased array radars. we propose a simple but effective task allocation policy and a real-time scheduling algorithm to address the design objectives of sps. we are able to bound the number of processing units needed for a component-oriented sp in the design time, while everything was done empirically in the past. a series of experiments were done to demonstrate the strength of our methodology
a logical basis for the d combinator and normal form in ccg. how to manage trust is regarded as a main problem of security issues in p2p overlay networks. reputation-based trust management is regarded as a promising way to solve the problem. however, in p2p systems, obtaining reputation evidence for building trust relationships is not an easy job. we tackle this problem by employing a scheme for the distribution of reputation evidence, which is based on the swarm intelligence paradigm. our simulations show that it performs very well in p2p environment. we hope that this method will help move the reputation based trust management closer to fulfilling its promise in p2p networks
finding contradictions in text. accuracy of statistical face recognition is determined by face's distributed feature. applying statistical recognition to faces without obvious distributed feature is meaningless. but such faces can be classified by subtle differences between local features. so local feature based face recognition by obtaining local feature and its dimension is proposed in this paper. experiments show that, the algorithm is satisfactory
pivot approach for extracting paraphrase patterns from bilingual corpora. as an important part of requirement management, managing requirement change plays a key role in controlling project schedule and costs at early stage. effective requirement impact analysis would give proper assessment on the effect of certain requirement changes on the whole system, and provide useful information for making trade-off decisions on future system design and implementation. in this paper a quantitative approach to concern impact analysis at requirement level has been proposed with the application of pagerank algorithm, which is a successful link based web page sorting algorithm. at first, separation of concerns is applied during deriving formal requirement specification from textual requirement statements. next, concerns are specified and concern relationship graph is established. finally, pagerank algorithm is utilized on concern relationship graph for assessing the impact of concern changes. our approach has been applied to hallway section in light control system and validation of analysis result has been stated.
enriching morphologically poor languages for statistical machine translation. microarray image technology is a powerful tool for monitoring the expression of thousands of genes simultaneously. each microarray experiment produces immense amounts of image data, and efficient storage and transmission requires compression that utilizes the microarray image's structure and unique analysis goals. we have developed a progressive compression scheme for microarray images which can be either lossy or lossless. our scheme has a coded data structure that allows fast decoding and reprocessing of image subsets, and includes summary statistics and image segmentation information. since visual fidelity is not the end goal for microarray images, we introduce a new measure of distortion for lossy compression: the sensitivity of microarray information extraction to compression loss. we find that a lossy compression ratio of 8:1 for cdna microarrays minimally affects downstream processing. the average lossless compression ratio is 1.83:1 for cdna images and 2.43:1 for inkjet images, comparable to state-of-the-art lossless schemas, yet with added flexibility and information.
trainable generation of big-five personality styles through data-driven parameter estimation. h.264/avc is a new international standard for the compression of natural video images, in which a deblocking filter has been adopted to remove blocking artifacts. we propose an efficient processing order for the deblocking filter, and present the vlsi architecture according to the order. making good use of data dependence between neighboring 4&times;4 blocks, our design reduces the requirement of on-chip sram bandwidth and increases the throughput of the filter processing. the architecture has been described in verilog hdl, simulated with vcs and synthesized using 0.25 &mu;m cmos cells library by synopsys design compiler. the circuit costs about 24k logic gates (not including a 32&times;64 sram and two 32&times;96 srams) when the working frequency is set to 100 mhz. this design can support real-time deblocking of hdtv (1280&times;720, 60 fps) h.264/avc video. this architecture is valuable for the hardware design of an h.264/avc codec.
when specialists and generalists work together: overcoming domain dependence in sentiment tagging. this paper presents an efficient survivability hierarchy analysis method for networked information system. in the hierarchical model, the top level is the survivability of system; the second is the survivability of essential service; the third is the survivability of atomic module; the lowest one is vulnerability. with the help of attack graph, the survivability (3r+a) is quantified according the records of the qos before and after attack. key words: survivability, hierarchical model
a tree sequence alignment-based tree-to-tree translation model. validation is one of the most complex and expensive tasks in current application specific instruction set processors (asip) design process. many existing approaches employ a multiple-level approach to efficiently design and verify asip design. this paper presents a novel extended timed petri net model called hdpn-hardware design based-on petri net to model systems at multiple levels, and introduces a verification scheme based on hdpn to satisfy the requirement of design space exploration (dse). this paper focuses on formal modeling and verification asip architecture. and a dlx pipelined processor is presented to demonstrate the validity and usage of this method.
joint word segmentation and pos tagging using a single perceptron. in open multi-agent systems (mas), interaction between agents is uncertain. trust plays an important role in deciding with whom to interact and how to interact with it. current trust models have solved the problem of how to quantify, deduce and evaluate trust, but there are still challenges. this paper presents fire+ trust model using utility loss of issue to evaluate trust values. with the representation of matrix, it efficiently increases the rating information. also by introducing d-s theory and wma, it can handle uncertain information and dishonest witness finely. meanwhile, our approach introduces the concept of information-amount to derive each issue 's weight so as to gain the whole trust value of the target agent. it also takes witness reliability into account. experiments show that fire+ is more effective than others.
an entity-mention model for coreference resolution with inductive logic programming. dynamic random access memory (dram) has been used in main memory design for decades. however, dram consumes an increasing power budget and faces difficulties in scaling down for small feature size cmos processing technologies. compared to conventional dram, emerging phase change random access memory (pram) demonstrates superior power efficiency and processing scalability as vlsi technologies and integration density continue to advance. nevertheless, using nano-scale fabrication technologies will unavoidably introduce design parameter variability in the manufacturing stage. in the past, the impact of process variation (pv) on conventional transistor-based storage cells and combinational logic has been studied extensively. however, the implication of pv on non-volatile memory design using emerging phase change techniques has not been well understood. in this paper, we take the first step toward characterizing the effect of process variation on pram and explore pv-aware design techniques. we show that process variation increases the pram programming power by 96% and degrades pram endurance by 50x. our proposed circuit and two microarchtiecture techniques with system-level support reduce pram power by 44%, 59% and 57% and improve pram endurance by 27x, 277x and 268x, relative to pv-affected pram design. moreover, we show that the synergy of the proposed cross-layer approaches, which achieve an average 63% power savings and 13050x endurance improvement over the conventional case, provide an attractive design solution to mitigate the deleterious impact of pv for non-volatile memory in the upcoming nano-scale processing technology era.
parsing noun phrase structure with ccg. this paper describes a new method for image smoothing. we view the image features as residing on a differential manifold, and we work with a representation based on the exponential map for this manifold (i.e. the map from the manifold to a plane that preserves geodesic distances). on the exponential map we characterise the features using a riemannian weighted mean. we show how both gradient descent and newton's method can be used to find the mean. based on this weighted mean, we develop an edge-preserving filter that combines gaussian and median filters of gray-scale images. we demonstrate our algorithm both on direction fields from shape-from-shading and tensor-valued images
cohesive phrase-based decoding for statistical machine translation. probabilistic risk assessment is a technique to assess the probability of failure or success of a mission. results provided by the risk assessment methodology are used to make decisions concerning choice of upgrades, scheduling of maintenance, decision to launch, etc. however, current pra neglects the contribution of software to the risk of failure of the mission. this paper presents a framework for "integrating software into pra", a methodology for systematic integration of the software contribution to risk in system failure analysis. in particular, we established a software-related failure mode taxonomy and a three-level pra sub-model to account for the impact of software to the classical pra structure. application and validation of the taxonomy are discussed in this paper. future research is also summarized.
a critical reassessment of evaluation baselines for speech summarization. medical systems require the end-to-end high availability and scalability. there are many components in a medical system, and each individual component contributes to the overall system availability and scalability. we present the formulas to assess the overall system availability and capacity planning, and we architect approaches and technologies to make all components highly available in all tiers by clustering, workload management, and replication. we discuss how to unify all medical systems and design the uniform framework for different kinds of medical systems to hook up with this framework so that we can maintain a highly available and highly scalable system with ease. we use the n-tier distributed component based architecture and j2ee technologies as well as web services to interact with .net and others. we discuss how to program in the framework for high availability and scalability and how to upgrade application software without service interruption to achieve continuous availability. we show how to add or reduce hardware capacity in each tier and how to maintain hardware and software without service interruption as well as how to balance the capacity and availability among tiers.
learning bilingual lexicons from monolingual corpora. this paper examines graph-theoretic properties of existing peer-to-peer networks and proposes a new infrastructure based on optimal-diameter de bruijn graphs. since generalized de bruijn graphs exhibit very short average distances and high resilience to node failure, they are well suited for distributed hash tables (dhts). using the example of chord, can, and de bruijn, we study the routing performance, graph expansion, clustering properties, and bisection width of each graph. having confirmed that de bruijn graphs offer the best diameter and highest connectivity among the existing peer-to-peer structures, we offer a very simple incremental building process that preserves optimal properties of de bruijn graphs under uniform user joins/departures. we call the combined peer-to-peer architecture optimal diameter routing infrastructure.
semi-supervised sequential labeling and segmentation using giga-word scale unlabeled data. in many computer vision algorithms, the well known euclidean or ssd (sum of the squared differences) metric is prevalent and justified from a maximum likelihood perspective when the additive noise is gaussian. however, gaussian noise distribution assumption is often invalid. previous research has found that other metrics such as double exponential metric or cauchy metric provide better results, in accordance with the maximum likelihood approach. in this paper, we examine different error metrics and provide a theoretical approach to derive a rich set of nonlinear estimations. our results on image databases show more robust results are obtained for noise estimation based on the proposed error metric analysis.
phrase table training for precision and recall: what makes a good phrase and a good phrase pair? survivability is a key concern in modern network design in order to achieve fast service restorability against network failures. this paper investigates the problem of survivable dynamic connection provisioning in general telecom backbone networks, which are mesh structured. these networks employ optical fibers, which may fail due to network outages such as fiber cuts, etc. our study applies to survivability of optical wavelength-division multiplexing (wdm) as well as multi-protocol label switching (mpls) networks. for survivability study, we assume differentiated services where connections may have different availability requirements, so they may be provisioned differently with protection (if needed) based on their availability requirements and current network state. therefore, it may be possible that connections with the same source, destination, and availability requirement are provisioned differently (unprotected, shared-path protected, or dedicated-path protected) at different times based on current network state. such differentiated provisioning can provide diverse levels of service performance and achieve network resource optimization flexibly. our main contributions are as follows. first, we develop an analytical model to quantify the availabilities of connections with various protection modes, i.e., unprotected, dedicated-path protected, and shared-path protected. particular emphasis is placed on computing a connection's availability with shared-path protection by employing the link-vector technique, because this technique can maximally explore the sharing potential among backup paths and achieve bandwidth-assignment flexibility. based on the mathematical model, we then present a novel provisioning strategy for dynamic connection requests in which multiple levels of services are provided and different protection schemes may be applied to different connections. the strategy jointly considers both connection availability satisfaction and resource optimizatio- - n. numerical results show very good accuracy of our model and high effectiveness of our provisioning strategy
inducing gazetteers for named entity recognition by large-scale clustering of dependency relations. it is a key problem to approximate data of complex surface in many graphics and image processing applications. it is difficult to compute the control parameters of nurbs (non uniform rational b-spline) effecting the result of fitted shape. an evolutionary programming algorithm is used to optimize the weight and knot by minimizing the sum square error between the fitted and target curve and surface. the results obtained from curves and surfaces shows that comparing to knot optimization, the weight optimization is a better option because knot optimization requires a good initial location of knot vector.
joint processing and discriminative training for letter-to-phoneme conversion. as gene order evolves through a variety of chromosomal rearrangements, conserved segments provide important insight into evolutionary relationships and functional roles of genes. however, gene loss within otherwise conserved segments, as typically occurs following large-scale genome duplication, has received limited algorithmic study. this has been a major impediment to comparative genomics in certain taxa, such as plants and fish. we propose a heuristic algorithm/or the inference of ancestral gene order in a set of related genomes that have undergone large-scale duplication and gene loss. first, approximately conserved (i.e. homologous) segments are identified using pairwise local genome alignment. second, homologous segments are iteratively clustered under the control of two parameters, (1) the minimal required number of shared genes between two clusters and (2) the maximal allowed number of rearrangement breakpoints along the lineage leading to each descendant segment. finally, we compute an estimated ancestral gene order for each cluster that is optimal in some sense. we evaluate the performance of this algorithm on simulated data that models a genome evolving by large-scale duplication, duplicate gene loss, transposition, translocation, and inversion. the results suggest that long segments of ancestral gene order may be reconstructed following moderate levels of rearrangement with only minor loss of accuracy.
measure word generation for english-chinese smt systems. when a data-parallel language like fortran 90 is compiled for a distributed-memory machine, aggregate data objects (such as arrays) are distributed across the processor memories. the mapping determines the amount of residual communication needed to bring operands of parallel operations into alignment with each other. a common approach is to break the mapping into two stages: first, an alignment that maps all the objects to an abstract template, and then a distribution that maps the template to the processors. the authors solve two facets of the problem of finding alignments that reduce residual communication, i.e., determining both the alignments that vary in loops, and the objects that should have replicated alignments. they show that loop-dependent mobile alignment is sometimes necessary for optimum performance, and they provide algorithms with which a compiler can determine good mobile alignments for objects within do loops. they also identify situations in which replicated alignment is either required by the program itself (via spread operations) or can be used to improve performance. an algorithm based on network flow that determines which objects to replicate so as to minimize the total amount of broadcast communication in replication is proposed.
vector-based models of semantic composition. this paper addresses the joint design of multiuser precoding and scheduling for downlink multiuser (mu-) multiple-input-multiple-output (mimo) systems with imperfect channel state information at the transmitter (csit). the major issue is to control the increased co-channel-interference (cci) caused by csit error among users sharing the same time-frequency resource. we propose an advanced joint multiuser precoding and scheduling technique, which uses the statistical information of the csit error to predict the relationship among cci, precoding matrixes and scheduling results, and utilizes such information to improve the precoding and scheduling algorithms for better cci control. simulation results have shown that considerable capacity improvement can be achieved by the proposed technique in the case of imperfect csit.
using adaptor grammars to identify synergies in the unsupervised acquisition of linguistic structure. program phase analysis has many applications in computer architecture design and optimization. recently, there has been a growing interest in employing wavelets as a tool for phase analysis. nevertheless, the examined scope of workload characteristics and the explored benefits due to wavelet-based analysis are quite limited. this work further extends prior research by applying wavelets analysis to abundant types of program execution statistics and quantifying the benefits of wavelet analysis in terms of accuracy, scalability and robustness in phase classification. experimental results on spec cpu 2000 benchmarks show that compared with methods that work in the time domain, wavelet domain phase analysis achieves higher accuracy and exhibits superior scalability and robustness. we examine and contrast the effectiveness of applying wavelets to a wide range of runtime workload execution characteristics. we find that wavelet transform significantly reduces temporal dependence in the sampled workload statistics and therefore simple models which are insufficient in the time domain become quite accurate in the wavelet domain. more attractively, we show that different types of workload execution characteristics in wavelet domain can be assembled together to further improve phase classification accuracy. for long-running, complex and real-world workloads, a scalable phase analysis technique is essential to capture the manifested large-scale program behavior. in this study, we show that such scalability can be achieved by applying wavelet analysis of high dimension sampled workload statistics to alleviate the counter overflow problem which can negatively affect phase classification accuracy. by exploiting the wavelet denoising capability, we show in this paper that phase classification can be performed robustly under program execution variability. to our knowledge, this work presents the first effort on using wavelets to improve scalability and robustness in phase analysis
a new string-to-dependency machine translation algorithm with a target dependency language model. there are almost more than 4,000 sorts of algae which could result in the red tide in the world, but only two or three, named the dominant species, place a premium on red tide at a time. this paper presents a method which uses the hyper-spectral images of different familiar dominant species to train the different networks respectively, then synthesizes the outputs of the networks with the same weight to recognize the red tide. it not only conquers the difficulties that are the selection of the training data and the network's training method, but also improves the generalization ability of the network system effectively. on the other hand, based on the neural network ensembles, the red tide recognition model could be extended easily and need not remodel the other networks. a mass of comparison experiments prove that the method recognizes the red tide and the dominant species effectively
intensional summaries as cooperative responses in dialogue: automation and evaluation. the cdna microarray image technology is a powerful tool for monitoring the expressions of thousands of genes simultaneously. an experiment is comprised of hundreds of images, each image easily over 30mb. since image processing and statistical analysis tools are still under development, the images are always kept. current focus on the development of standards makes efficient data transmission an important problem. though the cost of disk space for storage is decreasing, efficient transmission requires compression. we have developed a partially progressive compression scheme for microarray images, allowing for fast decoding and reprocessing of image subsets. the scheme also permits locally varying image distortion or loss. the degree of loss can be chosen on-line, or be based on local parameters such as the spot intensities, or signal-to-noise ratios. the minimum decodable bitrate depends on the initial choice of parameters. we find that a bitrate of 4.1 bpp (cmp 32 bpp uncompressed) is sufficient for most tasks, such as image segmentation, and gene expression level extraction with a variety of existing methods. the lossless bitrate is about 17.5 bpp, comparable to the state-of-the-art lossless schemes, yet with the added flexibility of a progressive scheme. our scheme has been tested on microarray images from different labs, and on images of varying quality.
combining em training and the mdl principle for an automatic verb classification incorporating selectional preferences. in this paper, we propose an effective coarse-to-fine algorithm to detect text in video. firstly, in coarse-detection section, stroke filter is employed to detect all candidate stroke pixels, and then a fast region growing method is developed to connect these pixels into regions which are further separated into candidate text lines by projection operation. secondly, in fine-detection section, correct text regions are selected from candidate ones by support vector machine (svm) model and stroke features, and text regions in multi-resolution are integrated. finally, the result is optimized significantly according to temporal correlation information. experimental results show that our algorithm achieves real-time performance and is robust for the variation of language, font, size, color and noise of text caused by low frame resolution in video.
contextual preferences. the wireless link with fixed parameters is subject to time-varying channel, and the battery energy is limited in mobile terminals. thus we consider the co-existence of 20 mstti and 5 ms tti in e-dch of td-scdma hsupa. in this paper, based on the comparative study on the link performances with different tti and the analysis on the link simulation results, we discuss the different tti's influence on the terminal power consumption. furthermore, the system level performances of semi-static tti and traditional single tti configurations are compared. finally the conclusions are drawn: 20 ms and 5 mstti should co-exist in td-scdma hsupa, and be adopted respectively in different channel condition to save the terminal power. the data throughput of semi-static tti configuration is greater than those of both single tti configurations, and the semi-static tti selection between 20 ms and 5 ms is implemented according to the moving speed of a specific ue.
robust dialog management with n-best hypotheses using dialog examples and agenda. modelling the immune system plays an important role in the understanding of the computational aspects of the immune system, because most of existing artificial immune system models are designed for a specific application problem and have their advantages and disadvantages. in this paper, an ais model based on ontology is presented which can integrate several ais models and algorithms. secondly, this model has accurate semantic, shared knowledge and understood by computer. with the guidance of ais ontolgy, more and more effectual ais models can be created and implement evolution dynamicly.
a re-examination of query expansion using lexical resources. fluidification constitutes a relaxation technique to study discrete event systems through a continuous approximated model, thus avoiding the state explosion problem. in this paper, the approximation by timed continuous petri nets under infinite server semantics is studied. the main contribution of this work is the addition of gaussian noise in order to obtain a better (but stochastic) approximation when synchronizations are important.
linguistically motivated features for enhanced back-of-the-book indexing. a new second-order bandpass sigma-delta modulator employing a micro-mechanical resonator is presented. the micro-mechanical resonator is used to replace its electronic counterpart for its high q value. the design is based on the pulse-invariant transform and multi-feedback technique. a compensation circuit is proposed to cancel the anti-resonance in the micro-mechanical resonator in order to obtain the desired transfer function. the modulator is implemented in a 0.6 &mu;m cmos process with an external clamped-clamped beam micro-mechanical resonator. simulations show that a 47 db dynamic range can be achieved in a 200 khz bandwidth centered at 8 mhz when sampled at 32 mhz.
analyzing the errors of unsupervised learning. establishing structure-function relationships on the proteomic scale is a unique challenge faced by bioinformatics and molecular biosciences. large protein families represent natural libraries of analogues of a given catalytic or protein function, thus making them ideal targets for the investigation of structure-function relationships in proteins. to this end, we have developed a new technique for analyzing large amounts of detailed molecular structure information focusing on the functional centers of homologous proteins. our approach uses unsupervised machine learning, in particular, self-organizing maps. the information captured by a self-organizing map and stored in its reference models highlights the essential structure of the proteins under investigation and can be effectively used to study detailed structural differences and similarities among homologous proteins. our preliminary results obtained with a prototype based on these techniques demonstrate that we can classify proteins and identify common and unique structures within a family and, more importantly, identify common and unique structural features of different conformations of the same protein. the approach developed here outperforms many of today’s structure analysis tools. these tools are usually either limited by the number of proteins they can process at the same time or they are limited by the structural resolution they can accommodate, that is, many of the structural analysis tools that can handle multiple proteins at the same time limit themselves to secondary structure analysis and therefore miss fine structural nuances within proteins.
integrating graph-based and transition-based dependency parsers. the earliest-deadline-first (edf) scheduling of a sporadic real-time task system on a multiprocessor may require that the total utilization of the task system, usum, not exceed (m + 1)/2 on m processors if every deadline needs to be met. in recent work, we considered the alleviation of this under-utilization for task systems that can tolerate deadline misses by bounded amounts (i.e., bounded tardiness). we showed that if usum &le; m and tasks are not pinned to processors, then the tardiness of each task is bounded under both preemptive and non-preemptive edf. however, the tardiness bounds derived are applicable to every task in the task system, i.e., any task may incur maximum tardiness. in this paper, we consider supporting tasks whose tolerances to tardiness are less than that known to be possible under edf. we propose a new scheduling policy, called edf-hl, which is a variant of edf, and show that under edf-hl, any tardiness, including zero tardiness, can be ensured for a limited number of privileged tasks, and that bounded tardiness can be guaranteed to the remaining tasks if their utilizations are restricted. edf-hl reduces to edf in the absence of privileged tasks. the tardiness bound that we derive is a function of usum, in addition to individual task parameters. hence, tardiness for all tasks can be lowered by lowering usum. a simulation-based evaluation of the tardiness bounds that are possible is provided.
automatic image annotation using auxiliary text information. a novel circuit employing p-type low-temperature poly-si thin-film transistors is introduced for active matrix-organic light-emitting diode (am-oled) circuits to automatically detect short defects and switch to a spare oled. this design maintains the luminance of the oled pixel without changing the driving current in the event of defects. experimental results show that not only is fault tolerance capability obtained during operation, but also a significant amount (around 90%) of power consumption is saved compared with the standard driving circuits.
semantic role labeling systems for arabic using kernel methods. the design and evaluation of microprocessor architectures is a difficult and time-consuming task. although small, hand-coded microbenchmarks can be used to accelerate performance evaluation, these programs lack the complexity to stress increasingly complex architecture designs. larger and more complex real-world workloads should be employed to measure the performance of a given design or to evaluate the efficiency of various design alternatives. these applications can take days or weeks if run to completion on a detailed architecture simulator. in the past, researchers have applied machine learning and statistical sampling methods to reduce the average number of instructions required for detailed simulation. others have proposed statistical simulation and workload synthesis techniques, which can produce programs that emulate the execution characteristics of the application from which they are derived but have a much shorter execution period than the original. however, these existing methods are difficult to apply to multi-threaded programs and can result in simplifications that miss the complex interactions between multiple, concurrently running threads. this study focuses on developing new techniques for accurate and effective multi-threaded workload synthesis, which can significantly accelerate architecture design evaluation of multi-core processors. we propose to construct synchronized statistical flow graphs that incorporate inter-thread synchronization and sharing behavior to capture the complex characteristics and interactions of multiple threads. moreover, we develop thread-aware data reference models and wavelet-based branching models to generate accurate memory access and dynamic branch statistics. experimental results show that a framework integrated with the aforementioned models can automatically generate synthetic programs that maintain characteristics of original workloads but have significantly reduced runtime.
contradictions and justifications: extensions to the textual entailment task. an extensive simulation study of various combinations of resistive bridges and crosstalk has been performed and several notable properties that have significant implications for test development have been discovered. scenarios have been identified where a combination of a bridge at one site and a crosstalk at a separate site in its transitive fanout (or vice versa) can cause slowdown/speed-up whose magnitude significantly exceeds the sum of the slow-down/speed-up, caused by each effect in isolation. it has also been identified that a test vector generated for crosstalk may in fact be invalidated due to the presence of a weak bridge at the crosstalk site. the properties discovered, provide the motivation for a more analytical study that will eventually lead to the proposed framework for test development.
can you summarize this? identifying correlates of input difficulty for multi-document summarization. a novel adaptive smoothing approach is proposed for noise removal and feature preservation where two distinct measures are simultaneously adopted to detect discontinuities in an image. inhomogeneity underlying an image is employed as a multiscale measure to detect contextual discontinuities for feature preservation and control of the smoothing speed, while local spatial gradient is used for detection of variable local discontinuities during smoothing. unlike previous adaptive smoothing approaches, two discontinuity measures are combined in our algorithm for synergy in preserving nontrivial features, which leads to a constrained anisotropic diffusion process that inhomogeneity offers intrinsic constraints for selective smoothing. thanks to the use of intrinsic constraints, our smoothing scheme is insensitive to termination times and the resultant images in a wide range of iterations are applicable to achieve nearly identical results for various early vision tasks. our algorithm is formally analyzed and related to anisotropic diffusion. comparative results indicate that our algorithm yields favorable smoothing results, and its application in extraction of hydrographic objects demonstrates its usefulness as a tool for early vision.
solving relational similarity problems using the web as a corpus. many asset tracking applications demand long-lived, low-cost, and continuous monitoring of a large number of items, which has posed a significant challenge to today's rfid design. in order to satisfy these requirements, we propose to adopt transmit-only tags without a receiver, which can offer both low power and low cost. in spite of their great potential, such a platform faces many challenges since it cannot sense the channel, causing the collisions among tag transmissions to be high. it is thus crucial to employ effective multi-user detection schemes at the tag reader to extract valid information from collided signals. traditional detection schemes, such as successive cancellation, cannot be directly applied to the targeted system. firstly, due to the simplicity of receiver-less transmit-only tags, there is no mechanism for feedback to the tags that is traditionally needed for accurate multi-user detection. more importantly, these schemes impose serious processing and memory requirements on the underlying system, which makes real-time tracking impossible. in this study, we address these challenges by performing a statistical estimation of the signal amplitude, and by dividing the received signal sequence (from all the tags) and assigning each block to one reader. we also adopt an online learning mechanism so that readers can anticipate the tags that belong to them. we show that the proposed detection algorithm can achieve low detection error under realistic system conditions.
a cascaded linear model for joint chinese word segmentation and part-of-speech tagging. traditional reversible cellular automata (rca) is fit for cryptography for its rules being an affine function, i.e. one reversible ca's rule can be applied in encryption process while another counterpart rule can be applied in decryption process. however, there is few number of traditional rca; for example, there are only six reversible rules in elementary ca. this property caused it cannot meet large key-space of cryptography. in this paper, an extended rca is proposed aimed to be applied in cryptography. analysis indicates that the extended rca can be obtained by a pair of complementary traditional rule. furthermore, in order to improve the complexity of ca's dynamics, which is a crux in cryptography, traditional ca model is replaced by multi-granularity cellular automata (mgca). in mgca, different granularity cells have their own rules. based on mgca and rca a cryptography algorithm that is proposed which called mgrca. in mgrca, cells have different granularity and can adjust their granularity dynamically by "split-recombination" behavior during the process of encryption and decryption. unlike des, the length of block in mgrca can be adjusted by user. the analysis results show that the cryptosystem can resist brute attack and differential attack, and also has high security. the hardware that shared by encryption and decryption caused the cryptosystem has a strong practicability.
ad hoc treebank structures. in this paper, we propose a robust approach for recognition of text embedded in natural scenes. instead of using binary information as most other ocr systems do, we extract features from intensity of an image directly. we utilize a local intensity normalization method to effectively handle lighting variations. we then employ gabor transform to obtain local features, and use the linear discriminant analysis (lda) for selection and classification of features. the proposed method has been applied to a chinese sign recognition task. the system can recognize a vocabulary of 3755 level i chinese characters in the chinese national standard character set gb2312-80 with various print fonts. we tested the system on 1630 test characters in sign images captured from the natural scenes, and the recognition accuracy was 92.46%. we have integrated the system into our automatic chinese sign translation system.
large scale acquisition of paraphrases for learning surface patterns. in recent years, inspired by the emerging web services standard and peer-to-peer technology, a new federated service providing (fsp) system paradigm has attracted increasing research interests. many existing systems have either explicitly or implicitly followed this paradigm. instead of exchanging files, peers in fsp systems share their computation resources in order to offer domain-specific services. in this paper, we focused on the coordination problem of how to self-organize the service group structures in response to the varying service demand. we presented our solution in the form of a coordination mechanism, which includes a labor-market model, a recruiting protocol, and a policy-driven decision architecture. peers make their service providing decisions based on their local policies, which can be added, removed, or modified by users. a general methodology is introduced in this paper to facilitate policy design. specifically, a heuristic inspired by the extremal optimization technique is utilized to handle potential inconsistencies among policies. a stimulus-response mechanism was further applied to make the decision process adjustable. experiments under five application scenarios verified our ideas and demonstrated the effectiveness of our coordination mechanism.
efficient multi-pass decoding for synchronous context free grammars. there has been ongoing debate regarding the use of voltage overscaling along with error resilience techniques for ultra low power operation of scaled cmos logic. the issue is whether to build enough design margin into future electronic systems so that errors do not impact the quality of service of the end application or to allow errors to occur and correct them using error tolerance mechanisms. specific signal processing algorithms have been shown to be inherently tolerant to errors. however, large general purpose processors experience virtually zero errors under supply voltage scaling up to a certain scaling level and then exhibit &#x201c;massive errors&#x201d; or &#x201c;complete breakdown&#x201d;. the problem is made worse by the fact that low power design methodologies force devices to be sized in such a way as to make a large number of circuit paths &#x201c;critical&#x201d;. under all of the above constraints, what is the best way to build low power systems of the future using deeply scaled cmos technologies? is the use of voltage overscaling along with error resilience techniques realistic? can we allow errors to occur and compensate for them with high confidence? under what conditions will design guardbanding be absolutely necessary? if we do let errors occur periodically, will customers buy the associated products and is there a marketplace for such error-resilient ics?
weakly-supervised acquisition of open-domain classes and class attributes from web documents and query logs. the classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases such as cancer. in gene expression data, the number of genes is usually very high (in the thousands) compared to the number of data samples (in the tens or low hundreds); that is, the data dimension is large compared to the number of data points (such data is said to be undersampled). to cope with performance and accuracy problems associated with high dimensionality, it is commonplace to apply a preprocessing step that transforms the data to a space of significantly lower dimension with limited loss of the information present in the original data. linear discriminant analysis (lda) is a well-known technique for dimension reduction and feature extraction, but it is not applicable for undersampled data due to singularity problems associated with the matrices in the underlying representation. this paper presents a dimension reduction and feature extraction scheme, called uncorrelated linear discriminant analysis (ulda), for undersampled problems and illustrates its utility on gene expression data. ulda employs the generalized singular value decomposition method to handle undersampled data and the features that it produces in the transformed space are uncorrelated, which makes it attractive for gene expression data. the properties of ulda are established rigorously and extensive experimental results on gene expression data are presented to illustrate its effectiveness in classifying tissue samples. these results provide a comparative study of various state-of-the-art classification methods on well-known gene expression data sets
using conditional random fields to extract contexts and answers of questions from online forums. middleware components are becoming increasingly important as applications share computational resources in distributed environments. one of the main challenges in such environments is to achieve scalability of concurrency control. existing concurrency protocols lack scalability. scalability enables resource sharing and computing with distributed objects in systems with a large number of nodes. we have designed and implemented a novel, scalable and filly decentralized middleware concurrency control protocol. our experiments on a linux cluster indicate that an average number of three messages is required per lock request on a system with as many as 120, which is a logarithmic asymptote. at the same time, the response time for the requests scales linearly with the increase in concurrency level. a comparison to another scalable concurrency protocol shows that our protocol results in significantly superior asymptotic savings in message overhead and response time for large number of nodes. while our approach follows the specification of general corba concurrency services for large-scale data and object repositories, the principles are applicable to any distributed concurrency services and transaction models. the results of this work impact scalability for distributed computing facilities ranging from embedded computing with distributed objects over peer-to-peer computing environments to arbitrating accesses in very large database environments.
enhancing performance of lexicalised grammars. genetic algorithms (gas) are increasingly being applied to large scale problems. the traditional mpi-based parallel gas require detailed knowledge about machine architecture. on the other hand, mapreduce is a powerful abstraction proposed by google for making scalable and fault tolerant applications. in this paper, we show how genetic algorithms can be modeled into the mapreduce model. we describe the algorithm design and implementation of gas on hadoop, an open source implementation of mapreduce. our experiments demonstrate the convergence and scalability up to 105 variable problems. adding more resources would enable us to solve even larger problems without any changes in the algorithms and implementation since we do not introduce any performance bottlenecks.
lexicalized phonotactic word segmentation. in this paper an area signal control model based on temporal planning is presented. every activity of area signal control is modeled using planning domain definition language, and then the domain model of area signal control is established. aiming at the representation problem of resource and time in the area signal control model, we extended the basic activity model by adding resource constraint and temporal constraint, and temporal planning based domain model for area signal control is established finally.
phrase chunking using entropy guided transformation learning. this paper presents a quick group search optimizer with passive congregation (qgsopc) for optimum design of pin connected structure. the algorithm is based on the quick group search optimizer (qgso). the qgsopc algorithm is verified and compared with the hpso, gso and qgso algorithm used for the designs of two planar and spatial truss structures. the results show that the qgsopc algorithm not only has preferable convergence rate and accuracy, but also it has the best stability of convergence rate and accuracy. it is desired for qgsopc to be used more effectively for practical structural optimal design problems.
summarizing emails with conversational cohesion and subjectivity. chip-multiprocessors (cmps) have been revealed as the most promising way of making efficient use of current improvements in integration scale. nowadays, commercial cmp releases integrate at most 8 processor cores onto the chip. however, 16 or more processor cores are expected to be offered in near future dense-cmp (d-cmp) systems. in this way, these architectures impose new design restrictions, and some topics, such as the cache-coherence problem, must be reviewed. in this paper we present an exhaustive performance evaluation of two recently proposed d-cmp architectures, making special emphasis on the solution to the cache-coherence problem that each one of them introduces. the shared bus fabric architecture (sbf) features a snoop cache-coherence protocol and is based on a high-performance bus fabric interconnection network. the second architecture follows a directory-based approach and integrates a bi-dimensional mesh as the interconnection network. our results show that the performance achieved by the sbf architecture is hard-limited by the bandwidth restrictions of the bus fabric. on the other hand, the directory-based architecture outperforms the sbf one, but presents some performance inefficiencies due to the additional indirection that the directory structure stored in the l2 cache level introduces
em can find pretty good hmm pos-taggers (when given a good start). choosing a cotton variety involves making comparisons over many trials and across an increasingly large number of available varieties. to aid in this process, a computerized tool has been developed at the texas tech university. this tool, called cotwiz, based on the cotton variety selection model, allows multiple comparisons of varieties across a number of trial locations. cotwiz based on the cotton variety selection model and uses cotton ovt data to make comparisons that are imported by the user.
grounded language modeling for automatic speech recognition of sports video. this paper investigates effective human team cooperation and incorporated the findings into multi-agent teamwork. we describe how to give agents the same cooperative capabilities, observability and proactivity, that humans use. we show how agents can use observation of the environment and of teammates' actions to estimate the teammates' beliefs without generating unnecessary messages; we also show how agents can anticipate information needs among the team members and proactively communicate the information. finally, we present two experiments that explore the effectiveness and the scalability of the use of observability and proactivity.
hypertagging: supertagging for surface realization with ccg. in inter-picture coding, block-based frequency transform is usually carried out on the predicted errors for each interblock to remove the spatial correlation among them. however, it can not always do well since the predicted errors in some inter-blocks have marginal or diagonal correlation. a good solution is to omit transform operations for the predicted errors of those inter-blocks with low correlation before quantization operation. the same phenomenon also can be observed in fine grain scalability (fgs) layer coding. in this paper, an adaptive prediction error coding method in spatial and frequency domain with lower complexity is considered for fgs layer coding. transform operation is only needed when there are non-zero reconstructed coefficients in spatially co-located block in base layer. the experimental results show that compared with fgs coding in jsvm, higher coding efficiency can be achieved with lower computational complexity at decoder since inverse transform is no longer needed for those predicted errors coded in spatial domain at encoder.
a generic sentence trimmer with crfs. in an optical wdm mesh network, different protection schemes (such as dedicated or shared protection) can be used to improve the service availability against network failures. however, in order to satisfy a connections service-availability requirement in a cost-effective and resource-efficient manner, we need a systematic mechanism to select a proper protection scheme for each connection request while provisioning the connection. in this paper, we propose to use connection availability as a metric to provide differentiated protection services in a wavelength-convertible wdm mesh network. we develop a mathematical model to analyze the availabilities of connections with different protection modes (i.e., unprotected, dedicated protected, or shared protected). in the shared-protection case, we investigate how a connection's availability is affected by backup resource sharing. the sharing might cause backup resource contention between several connections when multiple simultaneous (or overlapping) failures occur in the network. using a continuous-time markov model, we derive the conditional probability for a connection to acquire backup resources in the presence of backup resource contention. through this model, we show how the availability of a shared-protected connection can be quantitatively computed. based on the analytical model, we develop provisioning strategies for a given set of connection demands in which an appropriate, possibly different, level of protection is provided to each connection according to its predefined availability requirement, e.g., 0.999, 0.997. we propose integer linear programming (ilp) and heuristic approaches to provision the connections cost effectively while satisfying the connections' availability requirements. the effectiveness of our provisioning approaches is demonstrated through numerical examples. the proposed provisioning strategies inherently facilitate the service differentiation in optical wdm mesh networks.
bayesian learning of non-compositional phrases with synchronous parsing. with the efforts to understand protein structure, many computational approaches have been made recently. among them, the support vector machine (svm) methods have been recently applied and showed successful performance compared with other machine learning schemes. however, despite the high performance, the svm approaches suffer from the problem of understandability since it is a black-box model. to overcome this limitation, this study attempted to combine the svm with the association rule based classifier which can present the meaningful explanation about the prediction. to perform this task, a new association rule based classifier (pcpar) was devised based on the existing classifier, cpar, to handle the sequential data. pcpar creates the patterns by merging the generated rules and then classifies the sequential data based on the pattern match. the experimental result presents the following: with sequential data, the pcpar scheme shows better performance with respect to the accuracy and the number of generated patterns than cpar method whether applied alone or combined with svm. the combined scheme of svmpcpar generates more compact patterns than the combined scheme of svm with decision tree, svm dt, with similar performance. these patterns are easily understandable and biologically meaningful
adaptive language modeling for word prediction. we present the development and tuning of a topic-adapted language model for word prediction, which improves keystroke savings over a comparable baseline. we outline our plans to develop and integrate style adaptations, building on our experience in topic modeling to dynamically tune the model to both topically and stylistically relevant texts.
a subcategorization acquisition system for french verbs. this paper presents a system capable of automatically acquiring subcategorization frames (scfs) for french verbs from the analysis of large corpora. we applied the system to a large newspaper corpus (consisting of 10 years of the french newspaper 'le monde') and acquired subcategorization information for 3267 verbs. the system learned 286 scf types for these verbs. from the analysis of 25 representative verbs, we obtained 0.82 precision, 0.59 recall and 0.69 f-measure. these results are comparable with those reported in recent related work.
inferring activity time in news through event modeling. many applications in nlp, such as question-answering and summarization, either require or would greatly benefit from the knowledge of when an event occurred. creating an effective algorithm for identifying the activity time of an event in news is difficult in part because of the sparsity of explicit temporal expressions. this paper describes a domain-independent machine-learning based approach to assign activity times to events in news. we demonstrate that by applying topic models to text, we are able to cluster sentences that describe the same event, and utilize the temporal information within these event clusters to infer activity times for all sentences. experimental evidence suggests that this is a promising approach, given evaluations performed on three distinct news article sets against the baseline of assigning the publication date. our approach achieves 90%, 88.7%, and 68.7% accuracy, respectively, outperforming the baseline twice.
arabic language modeling with finite state transducers. in morphologically rich languages such as arabic, the abundance of word forms resulting from increased morpheme combinations is significantly greater than for languages with fewer inflected forms (kirchhoff et al., 2006). this exacerbates the out-of-vocabulary (oov) problem. test set words are more likely to be unknown, limiting the effectiveness of the model. the goal of this study is to use the regularities of arabic inflectional morphology to reduce the oov problem in that language. we hope that success in this task will result in a decrease in word error rate in arabic automatic speech recognition.
an integraged architecture for generating parenthetical constructions. the aim of this research is to provide a principled account of the generation of embedded constructions (called parentheticals) and to implement the results in a natural language generation system. parenthetical constructions are frequently used in texts written in a good writing style and have an important role in text understanding. we propose a framework to model the rhetorical properties of parentheticals based on a corpus study and develop a unified natural language generation architecture which integrates syntax, semantics, rhetorical and document structure into a complex representation, which can be easily extended to handle parentheticals.
impact of initiative on collaborative problem solving. even though collaboration in peer learning has been shown to have a positive impact for students, there has been little research into collaborative peer learning dialogues. we analyze such dialogues in order to derive a model of knowledge co-construction that incorporates initiative and the balance of initiative. this model will be embedded in an artificial agent that will collaborate with students.
a supervised learning approach to automatic synonym identification based on distributional features. distributional similarity has been widely used to capture the semantic relatedness of words in many nlp tasks. however, various parameters such as similarity measures must be hand-tuned to make it work effectively. instead, we propose a novel approach to synonym identification based on supervised learning and distributional features, which correspond to the commonality of individual context types shared by word pairs. considering the integration with pattern-based features, we have built and compared five synonym classifiers. the evaluation experiment has shown a dramatic performance increase of over 120% on the f-1 measure basis, compared to the conventional similarity-based classification. on the other hand, the pattern-based features have appeared almost redundant.
an unsupervised vector approach to biomedical term disambiguation: integrating umls and medline. this paper introduces an unsupervised vector approach to disambiguate words in biomedical text that can be applied to all-word disambiguation. we explore using contextual information from the unified medical language system (umls) to describe the possible senses of a word. we experiment with automatically creating individualized stoplists to help reduce the noise in our dataset. we compare our results to senseclusters and humphrey et al. (2006) using the nlm-wsd dataset and with senseclusters using conflated data from the 2005 medline baseline.
combining source and target language information for name tagging of machine translation output. a named entity recognizer (ner) generally has worse performance on machine translated text, because of the poor syntax of the mt output and other errors in the translation. as some tagging distinctions are clearer in the source, and some in the target, we tried to integrate the tag information from both source and target to improve target language tagging performance, especially recall. in our experiments with chinese-to-english mt output, we first used a simple merge of the outputs from an et (entity translation) system and an english ner system, getting an absolute gain of 7.15% in f-measure, from 73.53% to 80.68%. we then trained an memm module to integrate them more discriminatively, and got a further average gain of 2.74% in f-measure, from 80.68% to 83.42%.
the role of positive feedback in intelligent tutoring systems. the focus of this study is positive feedback in one-on-one tutoring, its computational modeling, and its application to the design of more effective intelligent tutoring systems. a data collection of tutoring sessions in the domain of basic computer science data structures has been carried out. a methodology based on multiple regression is proposed, and some preliminary results are presented. a prototype intelligent tutoring system on linked lists has been developed and deployed in a collegelevel computer science class.
a re-examination on features in regression based approach to automatic mt evaluation. machine learning methods have been extensively employed in developing mt evaluation metrics and several studies show that it can help to achieve a better correlation with human assessments. adopting the regression svm framework, this paper discusses the linguistic motivated feature formulation strategy. we argue that "blind" combination of available features does not yield a general metrics with high correlation rate with human assessments. instead, certain simple intuitive features serve better in establishing the regression svm evaluation model. with six features selected, we show evidences to support our view through a few experiments in this paper.
a hierarchical approach to encoding medical concepts for clinical notes. this paper proposes a hierarchical text categorization (tc) approach to encoding free-text clinical notes with icd-9-cm codes. preliminary experimental result on the 2007 computational medicine challenge data shows a hierarchical tc system has achieved a micro-averaged f1 value of 86.6, which is comparable to the performance of state-of-the-art flat classification systems.
high frequency word entrainment in spoken dialogue. cognitive theories of dialogue hold that entrainment, the automatic alignment between dialogue partners at many levels of linguistic representation, is key to facilitating both production and comprehension in dialogue. in this paper we examine novel types of entrainment in two corpora---switchboard and the columbia games corpus. we examine entrainment in use of high-frequency words (the most common words in the corpus), and its association with dialogue naturalness and flow, as well as with task success. our results show that such entrainment is predictive of the perceived naturalness of dialogues and is significantly correlated with task success; in overall interaction flow, higher degrees of entrainment are associated with more overlaps and fewer interruptions.
coreference-inspired coherence modeling. research on coreference resolution and summarization has modeled the way entities are realized as concrete phrases in discourse. in particular there exist models of the noun phrase syntax used for discourse-new versus discourse-old referents, and models describing the likely distance between a pronoun and its antecedent. however, models of discourse coherence, as applied to information ordering tasks, have ignored these kinds of information. we apply a discourse-new classifier and pronoun coreference algorithm to the information ordering task, and show significant improvements in performance over the entity grid, a popular model of local coherence.
dialect classification for online podcasts fusing acoustic and language based structural and semantic information. the variation in speech due to dialect is a factor which significantly impacts speech system performance. in this study, we investigate effective methods of combining acoustic and language information to take advantage of (i) speaker based acoustic traits as well as (ii) content based word selection across the text sequence. for acoustics, a gmm based system is employed and for text based dialect classification, we proposed n-gram language models combined with latent semantic analysis (lsa) based dialect classifiers. the performance of the individual classifiers is established for the three dialect family case (dc rates vary from 69.1%--72.4%). the final combined system achieved a dc accuracy of 79.5% and significantly outperforms the baseline acoustic classifier with a relative improvement of 30%, confirming that an integrated dialect classification system is effective for american, british and australian dialects.
a linguistically annotated reordering model for btg-based statistical machine translation. in this paper, we propose a linguistically annotated reordering model for btg-based statistical machine translation. the model incorporates linguistic knowledge to predict orders for both syntactic and non-syntactic phrases. the linguistic knowledge is automatically learned from source-side parse trees through an annotation algorithm. we empirically demonstrate that the proposed model leads to a significant improvement of 1.55% in the bleu score over the baseline reordering model on the nist mt-05 chinese-to-english translation task.
novel semantic features for verb sense disambiguation. we propose a novel method for extracting semantic information about a verb's arguments and apply it to verb sense disambiguation (vsd). we contrast this method with two popular approaches to retrieving this information and show that it improves the performance of our vsd system and outperforms the other two approaches
correlation between rouge and human evaluation of extractive meeting summaries. automatic summarization evaluation is critical to the development of summarization systems. while rouge has been shown to correlate well with human evaluation for content match in text summarization, there are many characteristics in multiparty meeting domain, which may pose potential problems to rouge. in this paper, we carefully examine how well the rouge scores correlate with human evaluation for extractive meeting summarization. our experiments show that generally the correlation is rather low, but a significantly better correlation can be obtained by accounting for several unique meeting characteristics, such as disfluencies and speaker information, especially when evaluating system-generated summaries.
a unified syntactic model for parsing fluent and disfluent speech. this paper describes a syntactic representation for modeling speech repairs. this representation makes use of a right corner transform of syntax trees to produce a tree representation in which speech repairs require very few special syntax rules, making better use of training data. pcfgs trained on syntax trees using this model achieve high accuracy on the standard switchboard parsing task.
assessing the costs of sampling methods in active learning for annotation. traditional active learning (al) techniques assume that the annotation of each datum costs the same. this is not the case when annotating sequences; some sequences will take longer than others. we show that the al technique which performs best depends on how cost is measured. applying an hourly cost model based on the results of an annotation user study, we approximate the amount of time necessary to annotate a given sentence. this model allows us to evaluate the effectiveness of al sampling methods in terms of time spent in annotation. we acheive a 77% reduction in hours from a random baseline to achieve 96.5% tag accuracy on the penn treebank. more significantly, we make the case for measuring cost in assessing al methods.
recent improvements in the cmu large scale chinese-english smt system. in this paper we describe recent improvements to components and methods used in our statistical machine translation system for chinese-english used in the january 2008 gale evaluation. main improvements are results of consistent data processing, larger statistical models and a pos-based word reordering approach.
a novel feature-based approach to chinese entity relation extraction. relation extraction is the task of finding semantic relations between two entities from text. in this paper, we propose a novel feature-based chinese relation extraction approach that explicitly defines and explores nine positional structures between two entities. we also suggest some correction and inference mechanisms based on relation hierarchy and co-reference information etc. the approach is effective when evaluated on the ace 2005 chinese data set.
evaluating word prediction: framing keystroke savings. researchers typically evaluate word prediction using keystroke savings, however, this measure is not straightforward. we present several complications in computing keystroke savings which may affect interpretation and comparison of results. we address this problem by developing two gold standards as a frame for interpretation. these gold standards measure the maximum keystroke savings under two different approximations of an ideal language model. the gold standards additionally narrow the scope of deficiencies in a word prediction system.
computing confidence scores for all sub parse trees. computing confidence scores for applications, such as dialogue system, information retrieving and extraction, is an active research area. however, its focus has been primarily on computing word-, concept-, or utterance-level confidences. motivated by the need from sophisticated dialogue systems for more effective dialogs, we generalize the confidence annotation to all the subtrees, the first effort in this line of research. the other contribution of this work is that we incorporated novel long distance features to address challenges in computing multi-level confidence scores. using conditional maximum entropy (cme) classifier with all the selected features, we reached an annotation error rate of 26.0% in the swbd corpus, compared with a subtree error rate of 41.91%, a closely related benchmark with the charniak parser from (kahn et al., 2005).
beyond log-linear models: boosted minimum error rate training for n-best re-ranking. current re-ranking algorithms for machine translation rely on log-linear models, which have the potential problem of underfitting the training data. we present boostedmert, a novel boosting algorithm that uses minimum error rate training (mert) as a weak learner and builds a re-ranker far more expressive than log-linear models. boostedmert is easy to implement, inherits the efficient optimization properties of mert, and can quickly boost the bleu score on n-best re-ranking tasks. in this paper, we describe the general algorithm and present preliminary results on the iwslt 2007 arabic-english task.
choosing sense distinctions for wsd: psycholinguistic evidence. supervised word sense disambiguation requires training corpora that have been tagged with word senses, which begs the question of which word senses to tag with. the default choice has been wordnet, with its broad coverage and easy accessibility. however, concerns have been raised about the appropriateness of its fine-grained word senses for wsd. wsd systems have been far more successful in distinguishing coarsegrained senses than fine-grained ones (navigli, 2006), but does that approach neglect necessary meaning differences? recent psycholinguistic evidence seems to indicate that closely related word senses may be represented in the mental lexicon much like a single sense, whereas distantly related senses may be represented more like discrete entities. these results suggest that, for the purposes of wsd, closely related word senses can be clustered together into a more general sense with little meaning loss. the current paper will describe this psycholinguistic research and its implications for automatic word sense disambiguation.
the complexity of phrase alignment problems. many phrase alignment models operate over the combinatorial space of bijective phrase alignments. we prove that finding an optimal alignment in this space is np-hard, while computing alignment expectations is #p-hard. on the other hand, we show that the problem of finding an optimal alignment can be cast as an integer linear program, which provides a simple, declarative approach to viterbi inference for phrase alignment models that is empirically quite efficient.
four techniques for online handling of out-of-vocabulary words in arabic-english statistical machine translation. we present four techniques for online handling of out-of-vocabulary words in phrase-based statistical machine translation. the techniques use spelling expansion, morphological expansion, dictionary term expansion and proper name transliteration to reuse or extend a phrase table. we compare the performance of these techniques and combine them. our results show a consistent improvement over a state-of-the-art baseline in terms of bleu and a manual error analysis.
active learning with confidence. active learning is a machine learning approach to achieving high-accuracy with a small amount of labels by letting the learning algorithm choose instances to be labeled. most of previous approaches based on discriminative learning use the margin for choosing instances. we present a method for incorporating confidence into the margin by using a newly introduced online learning algorithm and show empirically that confidence improves active learning.
simulating the behaviour of older versus younger users when interacting with spoken dialogue systems. in this paper we build user simulations of older and younger adults using a corpus of interactions with a wizard-of-oz appointment scheduling system. we measure the quality of these models with standard metrics proposed in the literature. our results agree with predictions based on statistical analysis of the corpus and previous findings about the diversity of older people's behaviour. furthermore, our results show that these metrics can be a good predictor of the behaviour of different types of users, which provides evidence for the validity of current user simulation evaluation metrics.
mixture model pomdps for efficient handling of uncertainty in dialogue management. in spoken dialogue systems, partially observable markov decision processes (pomdps) provide a formal framework for making dialogue management decisions under uncertainty, but efficiency and interpretability considerations mean that most current statistical dialogue managers are only mdps. these mdp systems encode uncertainty explicitly in a single state representation. we formalise such mdp states in terms of distributions over pomdp states, and propose a new dialogue system architecture (mixture model pomdps) which uses mixtures of these distributions to efficiently represent uncertainty. we also provide initial evaluation results (with real users) for this architecture.
partial matching strategy for phrase-based statistical machine translation. this paper presents a partial matching strategy for phrase-based statistical machine translation (pbsmt). source phrases which do not appear in the training corpus can be translated by word substitution according to partially matched phrases. the advantage of this method is that it can alleviate the data sparseness problem if the amount of bilingual corpus is limited. we incorporate our approach into the state-of-the-art pbsmt system moses and achieve statistically significant improvements on both small and large corpora.
enforcing transitivity in coreference resolution. a desirable quality of a coreference resolution system is the ability to handle transitivity constraints, such that even if it places high likelihood on a particular mention being coreferent with each of two other mentions, it will also consider the likelihood of those two mentions being coreferent when making a final assignment. this is exactly the kind of constraint that integer linear programming (ilp) is ideal for, but, surprisingly, previous work applying ilp to coreference resolution has not encoded this type of constraint. we train a coreference classifier over pairs of mentions, and show how to encode this type of constraint on top of the probabilities output from our pairwise classifier to extract the most probable legal entity assignments. we present results on two commonly used datasets which show that enforcement of transitive closure consistently improves performance, including improvements of up to 3.6% using the b3 scorer, and up to 16.5% using cluster f-measure.
event matching using the transitive closure of dependency relations. this paper describes a novel event-matching strategy using features obtained from the transitive closure of dependency relations. the method yields a model capable of matching events with an f-measure of 66.5%.
extracting a representation from text for semantic analysis. we present a novel fine-grained semantic representation of text and an approach to constructing it. this representation is largely extractable by today's technologies and facilitates more detailed semantic analysis. we discuss the requirements driving the representation, suggest how it might be of value in the automated tutoring domain, and provide evidence of its validity.
speakers' intention prediction using statistics of multi-level features in a schedule management domain. speaker's intention prediction modules can be widely used as a pre-processor for reducing the search space of an automatic speech recognizer. they also can be used as a preprocessor for generating a proper sentence in a dialogue system. we propose a statistical model to predict speakers' intentions by using multi-level features. using the multi-level features (morpheme-level features, discourse-level features, and domain knowledge-level features), the proposed model predicts speakers' intentions that may be implicated in next utterances. in the experiments, the proposed model showed better performances (about 29% higher accuracies) than the previous model. based on the experiments, we found that the proposed multi-level features are very effective in speaker's intention prediction.
exploiting n-best hypotheses for smt self-enhancement. word and n-gram posterior probabilities estimated on n-best hypotheses have been used to improve the performance of statistical machine translation (smt) in a rescoring framework. in this paper, we extend the idea to estimate the posterior probabilities on n-best hypotheses for translation phrase-pairs, target language n-grams, and source word reorderings. the smt system is self-enhanced with the posterior knowledge learned from n-best hypotheses in a re-decoding framework. experiments on nist chinese-to-english task show performance improvements for all the strategies. moreover, the combination of the three strategies achieves further improvements and outperforms the baseline by 0.67 bleu score on nist-2003 set, and 0.64 on nist-2005 set, respectively.
robust extraction of named entity including unfamiliar word. this paper proposes a novel method to extract named entities including unfamiliar words which do not occur or occur few times in a training corpus using a large unannotated corpus. the proposed method consists of two steps. the first step is to assign the most similar and familiar word to each unfamiliar word based on their context vectors calculated from a large unannotated corpus. after that, traditional machine learning approaches are employed as the second step. the experiments of extracting japanese named entities from irex corpus and nhk corpus show the effectiveness of the proposed method.
intrinsic vs. extrinsic evaluation measures for referring expression generation. in this paper we present research in which we apply (i) the kind of intrinsic evaluation metrics that are characteristic of current comparative hlt evaluation, and (ii) extrinsic, human task-performance evaluations more in keeping with nlg traditions, to 15 systems implementing a language generation task. we analyse the evaluation results and find that there are no significant correlations between intrinsic and extrinsic evaluation measures for this task.
mining wikipedia revision histories for improving sentence compression. a well-recognized limitation of research on supervised sentence compression is the dearth of available training data. we propose a new and bountiful resource for such training data, which we obtain by mining the revision history of wikipedia for sentence compressions and expansions. using only a fraction of the available wikipedia data, we have collected a training corpus of over 380,000 sentence pairs, two orders of magnitude larger than the standardly used ziff-davis corpus. using this new-found data, we propose a novel lexicalized noisy channel model for sentence compression, achieving improved results in grammaticality and compression rate criteria with a slight decrease in importance.
lyric-based song sentiment classification with sentiment vector space model. due to the internet's sheer size, complexity, and various routing policies, it is difficult if not impossible to locate the causes of large volumes of bgp update messages that occur from time to time. to provide dependable global data delivery we need diagnostic tools that can pinpoint the exact connectivity changes. we describe an algorithm, called mvschange that can pin down the origin of routing changes due to any single link failure or link restoration. using a simplified model of bgp, called simple path vector protocol (spvp), and a graph model of the internet, mvschange takes as input the spvp update messages collected from multiple vantage points and accurately locates the link that initiated the routing changes. we provide theoretical proof for the correctness of the design.
using automatically transcribed dialogs to learn user models in a spoken dialog system. we use an em algorithm to learn user models in a spoken dialog system. our method requires automatically transcribed (with asr) dialog corpora, plus a model of transcription errors, but does not otherwise need any manual transcription effort. we tested our method on a voice-controlled telephone directory application, and show that our learned models better replicate the true distribution of user actions than those trained by simpler methods and are very similar to user models estimated from manually transcribed dialogs.
extractive summaries for educational science content. this paper describes an extractive summarizer for educational science content called cogent. cogent extends mead based on strategies elicited from an empirical study with domain and instructional experts. cogent implements a hybrid approach integrating both domain independent sentence scoring features and domain-aware features. initial evaluation results indicate that cogent outperforms existing summarizers and generates summaries that closely resemble those generated by human experts.
learning semantic links from a corpus of parallel temporal and causal relations. finding temporal and causal relations is crucial to understanding the semantic structure of a text. since existing corpora provide no parallel temporal and causal annotations, we annotated 1000 conjoined event pairs, achieving inter-annotator agreement of 81.2% on temporal relations and 77.8% on causal relations. we trained machine learning models using features derived from wordnet and the google n-gram corpus, and they outperformed a variety of baselines, achieving an f-measure of 49.0 for temporals and 52.4 for causals. analysis of these models suggests that additional data will improve performance, and that temporal information is crucial to causal relation identification.
language dynamics and capitalization using maximum entropy. this paper studies the impact of written language variations and the way it affects the capitalization task over time. a discriminative approach, based on maximum entropy models, is proposed to perform capitalization, taking the language changes into consideration. the proposed method makes it possible to use large corpora for training. the evaluation is performed over newspaper corpora using different testing periods. the achieved results reveal a strong relation between the capitalization performance and the elapsed time between the training and testing data periods.
smoothing a tera-word language model. frequency counts from very large corpora, such as the web 1t dataset, have recently become available for language modeling. omission of low frequency n-gram counts is a practical necessity for datasets of this size. naive implementations of standard smoothing methods do not realize the full potential of such large datasets with missing counts. in this paper i present a new smoothing algorithm that combines the dirichlet prior form of (mackay and peto, 1995) with the modified back-off estimates of (kneser and ney, 1995) that leads to a 31% perplexity reduction on the brown corpus compared to a baseline implementation of kneser-ney discounting.
construct state modification in the arabic treebank. earlier work in parsing arabic has speculated that attachment to construct state constructions decreases parsing performance. we make this speculation precise and define the problem of attachment to construct state constructions in the arabic treebank. we present the first statistics that quantify the problem. we provide a baseline and the results from a first attempt at a discriminative learning procedure for this task, achieving 80% accuracy.
the good, the bad, and the unknown: morphosyllabic sentiment tagging of unseen words. the omnipresence of unknown words is a problem that any nlp component needs to address in some form. while there exist many established techniques for dealing with unknown words in the realm of pos-tagging, for example, guessing unknown words' semantic properties is a less-explored area with greater challenges. in this paper, we study the semantic field of sentiment and propose five methods for assigning prior sentiment polarities to unknown words based on known sentiment carriers. tested on 2000 cases, the methods mirror human judgements closely in three- and two-way polarity classification tasks, and reach accuracies above 63% and 81%, respectively.
enriching spoken language translation with dialog acts. we first present the tele-immersive environments developed jointly by university of illinois at urbana-champaign and university of california at berkeley. the environment features 3d full and real body capturing, wide field of view, multi-display 3d rendering, and attachment free participant. we then describe a study of collaborative dancing between remotely located dancers in the shared virtual space. two professional dancers are invited to the tele-immersive site of each university. as a preliminary experiment, we let the dancers perform elementary body movements and coordinate their dancing. the coordination requires one dancer to take the lead while the other follows her by appropriate movements. during the experiment, the dancers are dancing at various motion rates to evaluate how well the collaborative dancing is supported with the current technical boundary. our important findings indicate that 1) tele-immersive environments have strong potential impact on the concept of choreography and communication of live dance performance, 2) the presence of multi-display system, real body 3d rendering, audio channel, and less intrusive-ness greatly enhances the immersive and dancing experience, and 3) the level of synchronization achieved by the dancers is higher than that expected from the video rate
query-based sentence fusion is better defined and leads to more preferred results than generic sentence fusion. we show that question-based sentence fusion is a better defined task than generic sentence fusion (q-based fusions are shorter, display less variety in length, yield more identical results and have higher normalized rouge scores). moreover, we show that in a qa setting, participants strongly prefer q-based fusions over generic ones, and have a preference for union over intersection fusions.
blog categorization exploiting domain dictionary and dynamically estimated domains of unknown words. this paper presents an approach to text categorization that i) uses no machine learning and ii) reacts on-the-fly to unknown words. these features are important for categorizing blog articles, which are updated on a daily basis and filled with newly coined words. we categorize 600 blog articles into 12 domains. as a result, our categorization method achieved an accuracy of 94.0% (564/600).
unlexicalised hidden variable models of split dependency grammars. this paper investigates transforms of split dependency grammars into unlexicalised context-free grammars annotated with hidden symbols. our best unlexicalised grammar achieves an accuracy of 88% on the penn treebank data set, that represents a 50% reduction in error over previously published results on unlexicalised dependency parsing.
dictionary definitions based homograph identification using a generative hierarchical model. a solution to the problem of homograph (words with multiple distinct meanings) identification is proposed and evaluated in this paper. it is demonstrated that a mixture model based framework is better suited for this task than the standard classification algorithms - relative improvement of 7% in f1 measure and 14% in cohen's kappa score is observed.
surprising parser actions and reading difficulty. an incremental dependency parser's probability model is entered as a predictor in a linear mixed-effects model of german readers' eye-fixation durations. this dependency-based predictor improves a baseline that takes into account word length, n-gram probability, and cloze predictability that are typically applied in models of human reading. this improvement obtains even when the dependency parser explores a tiny fraction of its search space, as suggested by narrow-beam accounts of human sentence processing such as garden path theory.
icelandic data driven part of speech tagging. data driven pos tagging has achieved good performance for english, but can still lag behind linguistic rule based taggers for morphologically complex languages, such as icelandic. we extend a statistical tagger to handle fine grained tagsets and improve over the best icelandic pos tagger. additionally, we develop a case tagger for non-local case and gender decisions. an error analysis of our system suggests future directions.
you've got answers: towards personalized models for predicting success in community question answering. question answering communities such as yahoo! answers have emerged as a popular alternative to general-purpose web search. by directly interacting with other participants, information seekers can obtain specific answers to their questions. however, user success in obtaining satisfactory answers varies greatly. we hypothesize that satisfaction with the contributed answers is largely determined by the asker's prior experience, expectations, and personal preferences. hence, we begin to develop personalized models of asker satisfaction to predict whether a particular question author will be satisfied with the answers contributed by the community participants. we formalize this problem, and explore a variety of content, structure, and interaction features for this task using standard machine learning techniques. our experimental evaluation over thousands of real questions indicates that indeed it is beneficial to personalize satisfaction predictions when sufficient prior user history exists, significantly improving accuracy over a "one-size-fits-all" prediction model.
self-training for biomedical parsing. parser self-training is the technique of taking an existing parser, parsing extra data and then creating a second parser by treating the extra data as further training data. here we apply this technique to parser adaptation. in particular, we self-train the standard charniak/johnson penn-treebank parser using unlabeled biomedical abstracts. this achieves an f-score of 84.3% on a standard test set of biomedical abstracts from the genia corpus. this is a 20% error reduction over the best previous result on biomedical data (80.2% on the same test set).
distributed listening: a parallel processing approach to automatic speech recognition. while speech recognition systems have come a long way in the last thirty years, there is still room for improvement. although readily available, these systems are sometimes inaccurate and insufficient. the research presented here outlines a technique called distributed listening which demonstrates noticeable improvements to existing speech recognition methods. the distributed listening architecture introduces the idea of multiple, parallel, yet physically separate automatic speech recognizers called listeners. distributed listening also uses a piece of middleware called an interpreter. the interpreter resolves multiple interpretations using the phrase resolution algorithm (pra). these efforts work together to increase the accuracy of the transcription of spoken utterances.
semantic types of some generic relation arguments: detection and evaluation. this paper presents an approach to detection of the semantic types of relation arguments employing the wordnet hierarchy. using the semeval-2007 data, we show that the method allows to generalize relation arguments with high precision for such generic relations as origin-entity, content-container, instrument-agency and some other.
adapting a wsj-trained parser to grammatically noisy text. we present a robust parser which is trained on a treebank of ungrammatical sentences. the treebank is created automatically by modifying penn treebank sentences so that they contain one or more syntactic errors. we evaluate an existing penn-treebank-trained parser on the ungrammatical treebank to see how it reacts to noise in the form of grammatical errors. we re-train this parser on the training section of the ungrammatical treebank, leading to an significantly improved performance on the ungrammatical test sets. we show how a classifier can be used to prevent performance degradation on the original grammatical data.
segmentation for english-to-arabic statistical machine translation. in this paper, we report on a set of initial results for english-to-arabic statistical machine translation (smt). we show that morphological decomposition of the arabic source is beneficial, especially for smaller-size corpora, and investigate different recombination techniques. we also report on the use of factored translation models for english-to-arabic translation.
decompounding query keywords from compounding languages. splitting compound words has proved to be useful in areas such as machine translation, speech recognition or information retrieval (ir). furthermore, real-time ir systems (such as search engines) need to cope with noisy data, as user queries are sometimes written quickly and submitted without review. in this paper we apply a state-of-the-art procedure for german decompounding to other compounding languages, and we show that it is possible to have a single decompounding model that is applicable across languages.
active sample selection for named entity transliteration. this paper introduces a new method for identifying named-entity (ne) transliterations within bilingual corpora. current state-of-the-art approaches usually require annotated data and relevant linguistic knowledge which may not be available for all languages. we show how to effectively train an accurate transliteration classifier using very little data, obtained automatically. to perform this task, we introduce a new active sampling paradigm for guiding and adapting the sample selection process. we also investigate how to improve the classifier by identifying repeated patterns in the training data. we evaluated our approach using english, russian and hebrew corpora.
arabic morphological tagging, diacritization, and lemmatization using lexeme models and feature ranking. we investigate the tasks of general morphological tagging, diacritization, and lemmatization for arabic. we show that for all tasks we consider, both modeling the lexeme explicitly, and retuning the weights of individual classifiers for the specific task, improve the performance.
in-browser summarisation: generating elaborative summaries biased towards the reading context. we investigate elaborative summarisation, where the aim is to identify supplementary information that expands upon a key fact. we envisage such summaries being useful when browsing certain kinds of (hyper-)linked document sets, such as wikipedia articles or repositories of publications linked by citations. for these collections, an elaborative summary is intended to provide additional information on the linking anchor text. our contribution in this paper focuses on identifying and exploring a real task in which summarisation is situated, realised as an in-browser tool. we also introduce a neighbourhood scoring heuristic as a means of scoring matches to relevant passages of the document. in a preliminary evaluation using this method, our summarisation system scores above our baselines and achieves a recall of 57% annotated gold standard sentences.
efficient processing of underspecified discourse representations. underspecification-based algorithms for processing partially disambiguated discourse structure must cope with extremely high numbers of readings. based on previous work on dominance graphs and weighted tree grammars, we provide the first possibility for computing an underspecified discourse description and a best discourse representation efficiently enough to process even the longest discourses in the rst discourse treebank.
splitsvm: fast, space-efficient, non-heuristic, polynomial kernel computation for nlp applications. we present a fast, space efficient and non-heuristic method for calculating the decision function of polynomial kernel classifiers for nlp applications. we apply the method to the maltparser system, resulting in a java parser that parses over 50 sentences per second on modest hardware without loss of accuracy (a 30 time speedup over existing methods). the method implementation is available as the open-source splitsvm java library.
kernels on linguistic structures for answer extraction. natural language processing (nlp) for information retrieval has always been an interesting and challenging research area. despite the high expectations, most of the results indicate that successfully using nlp is very complex. in this paper, we show how support vector machines along with kernel functions can effectively represent syntax and semantics. our experiments on question/answer classification show that the above models highly improve on bag-of-words on a trec dataset.
machine translation system combination using itg-based alignments. given several systems' automatic translations of the same sentence, we show how to combine them into a confusion network, whose various paths represent composite translations that could be considered in a subsequent rescoring step. we build our confusion networks using the method of rosti et al. (2007), but, instead of forming alignments using the tercom script (snover et al., 2006), we create alignments that minimize invwer (leusch et al., 2003), a form of edit distance that permits properly nested block movements of substrings. oracle experiments with chinese newswire and weblog translations show that our confusion networks contain paths which are significantly better (in terms of bleu and ter) than those in tercom-based confusion networks.
combined one sense disambiguation of abbreviations. a process that attempts to solve abbreviation ambiguity is presented. various context-related features and statistical features have been explored. almost all features are domain independent and language independent. the application domain is jewish law documents written in hebrew. such documents are known to be rich in ambiguous abbreviations. various implementations of the one sense per discourse hypothesis are used, improving the features with new variants. an accuracy of 96.09% has been achieved by svm.
using structural information for identifying similar chinese characters. chinese characters that are similar in their pronunciations or in their internal structures are useful for computer-assisted language learning and for psycholinguistic studies. although it is possible for us to employ image-based methods to identify visually similar characters, the resulting computational costs can be very high. we propose methods for identifying visually similar chinese characters by adopting and extending the basic concepts of a proven chinese input method--cangjie. we present the methods, illustrate how they work, and discuss their weakness in this paper.
dimensions of subjectivity in natural language. current research in automatic subjectivity analysis deals with various kinds of subjective statements involving human attitudes and emotions. while all of them are related to subjectivity, these statements usually touch on multiple dimensions such as non-objectivity, uncertainty, vagueness, non-objective measurability, imprecision, and ambiguity, which are inherently different. this paper discusses the differences and relations of six dimensions of subjectivity. conceptual and linguistic characteristics of each dimension will be demonstrated under different contexts.
evolving new lexical association measures using genetic programming. automatic extraction of collocations from large corpora has been the focus of many research efforts. most approaches concentrate on improving and combining known lexical association measures. in this paper, we describe a genetic programming approach for evolving new association measures, which is not limited to any specific language, corpus, or type of collocation. our preliminary experimental results show that the evolved measures outperform three known association measures.
unsupervised learning of acoustic sub-word units. accurate unsupervised learning of phonemes of a language directly from speech is demonstrated via an algorithm for joint unsupervised learning of the topology and parameters of a hidden markov model (hmm); states and short state-sequences through this hmm correspond to the learnt sub-word units. the algorithm, originally proposed for unsupervised learning of allophonic variations within a given phoneme set, has been adapted to learn without any knowledge of the phonemes. an evaluation methodology is also proposed, whereby the state-sequence that aligns to a test utterance is transduced in an automatic manner to a phoneme-sequence and compared to its manual transcription. over 85% phoneme recognition accuracy is demonstrated for speaker-dependent learning from fluent, large-vocabulary speech.
text segmentation with lda-based fisher kernel. in this paper we propose a domain-independent text segmentation method, which consists of three components. latent dirichlet allocation (lda) is employed to compute words semantic distribution, and we measure semantic similarity by the fisher kernel. finally global best segmentation is achieved by dynamic programming. experiments on chinese data sets with the technique show it can be effective. introducing latent semantic information, our algorithm is robust on irregular-sized segments.
multi-domain sentiment classification. this paper addresses a new task in sentiment classification, called multi-domain sentiment classification, that aims to improve performance through fusing training data from multiple domains. to achieve this, we propose two approaches of fusion, feature-level and classifier-level, to use training data from multiple domains simultaneously. experimental studies show that multi-domain sentiment classification using the classifier-level approach performs much better than single domain classification (using the training data individually).
pairwise document similarity in large collections with mapreduce. this paper presents a mapreduce algorithm for computing pairwise document similarity in large document collections. mapreduce is an attractive framework because it allows us to decompose the inner products involved in computing document similarity into separate multiplication and summation stages in a way that is well matched to efficient disk access patterns across several machines. on a collection consisting of approximately 900,000 newswire articles, our algorithm exhibits linear growth in running time and space in terms of the number of documents.
fastsum: fast and accurate query-based multi-document summarization. we present a fast query-based multi-document summarizer called fastsum based solely on word-frequency features of clusters, documents and topics. summary sentences are ranked by a regression svm. the summarizer does not use any expensive nlp techniques such as parsing, tagging of names or even part of speech information. still, the achieved accuracy is comparable to the best systems presented in recent academic competitions (i.e., document understanding conference (duc)). because of a detailed feature analysis using least angle regression (lars), fastsum can rely on a minimal set of features leading to fast processing times: 1250 news documents in 60 seconds.
an adaptive approach to collecting multimodal input. multimodal dialogue systems allow users to input information in multiple modalities. these systems can handle simultaneous or sequential composite multimodal input. different coordination schemes require such systems to capture, collect and integrate user input in different modalities, and then respond to a joint interpretation. we performed a study to understand the variability of input in multimodal dialogue systems and to evaluate methods to perform the collection of input information. an enhancement in the form of incorporation of a dynamic time window to a multimodal input fusion module was proposed in the study. we found that the enhanced module provides superior temporal characteristics and robustness when compared to previous methods.
extraction and verification of ko-ou expressions from large corpora. in the japanese language, as a predicate is placed at the end of a sentence, the content of a sentence cannot be inferred until reaching the end. however, when the content is complicated and the sentence is long, people want to know at an earlier stage in the sentence whether the content is negative, affirmative, or interrogative. in japanese, the grammatical form called the ko-ou relation exists. the ko-ou relation is a kind of concord. if a ko element appears, then an ou element appears in the latter part of a sentence. it is being pointed out that the ko-ou relation gives advance notice to the element that appears in the latter part of a sentence. in this paper, we present the method of extracting automatically the ko-ou expression data from large-scale electronic corpus and verify the usefulness of the ko-ou expression data.
a speech interface for open-domain question-answering. speech interfaces to question-answering systems offer significant potential for finding information with phones and mobile networked devices. we describe a demonstration of spoken question answering using a commercial dictation engine whose language models we have customized to questions, a web-based text-prediction interface allowing quick correction of errors, and an open-domain question-answering system, answerbus, which is freely available on the web. we describe a small evaluation of the effect of recognition errors on the precision of the answers returned and make some concrete recommendations for modifying a question-answering system for improving robustness to spoken input.
high-precision identification of discourse new and unique noun phrases. coreference resolution systems usually attempt to find a suitable antecedent for (almost) every noun phrase. recent studies, however, show that many definite nps are not anaphoric. the same claim, obviously, holds for the indefinites as well.in this study we try to learn automatically two classifications, &plusmn;discourse_new and &plusmn;unique, relevant for this problem. we use a small training corpus (muc-7), but also acquire some data from the internet. combining our classifiers sequentially, we achieve 88.9% precision and 84.6% recall for discourse new entities.we expect our classifiers to provide a good prefiltering for coreference resolution systems, improving both their speed and performance.
learning non-isomorphic tree mappings for machine translation. often one may wish to learn a tree-to-tree mapping, training it on unaligned pairs of trees, or on a mixture of trees and strings. unlike previous statistical formalisms (limited to isomorphic trees), synchronous tsg allows local distortion of the tree topology. we reformulate it to permit dependency trees, and sketch em/viterbi algorithms for alignment, training, and decoding.
bilingual terminology acquisition from comparable corpora and phrasal translation to cross-language information retrieval. the present paper will seek to present an approach to bilingual lexicon extraction from non-aligned comparable corpora, phrasal translation as well as evaluations on cross-language information retrieval. a two-stages translation model is proposed for the acquisition of bilingual terminology from comparable corpora, disambiguation and selection of best translation alternatives according to their linguistics-based knowledge. different rescoring techniques are proposed and evaluated in order to select best phrasal translation alternatives. results demonstrate that the proposed translation model yields better translations and retrieval effectiveness could be achieved across japanese-english language pair.
discourse chunking: a tool in dialogue act tagging. discourse chunking is a simple way to segment dialogues according to how dialogue participants raise topics and negotiate them. this paper explains a method for arranging dialogues into chunks, and also shows how discourse chunking can be used to improve performance for a dialogue act tagger that uses a case-based reasoning approach.
finding non-local dependencies: beyond pattern matching. we describe an algorithm for recovering non-local dependencies in syntactic dependency structures. the pattern-matching approach proposed by johnson (2002) for a similar task for phrase structure trees is extended with machine learning techniques. the algorithm is essentially a classifier that predicts a non-local dependency given a connected fragment of a dependency structure and a set of structural features for this fragment. evaluating the algorithm on the penn treebank shows an improvement of both precision and recall, compared to the results presented in (johnson, 2002).
an ontology-based semantic tagger for ie system. in this paper, we present a method for the semantic tagging of word chunks extracted from a written transcription of conversations. this work is part of an ongoing project for an information extraction system in the field of maritime search and rescue (sar). our purpose is to automatically annotate parts of texts with concepts from a sar ontology. our approach combines two knowledge sources a sar ontology and the wordsmyth dictionary-thesaurus, and it uses a similarity measure for the classification. evaluation is carried out by comparing the output of the system with key answers of predefined extraction templates.
classifying recognition results for spoken dialog systems. this paper investigates the correlation between acoustic confidence scores as returned by speech recognizers with recognition quality. we report the results of two machine learning experiments that predict the word error rate of recognition hypotheses and the confidence error rate for individual words within them.
a computational treatment of korean temporal markers, oe and dongan. in this paper, we elucidate how korean temporal markers, oe and dongan contribute to specifying the event time and formalize it in terms of typed lambda calculus. we also present a computational method for constructing temporal representation of korean sentences on the basis of g grammar proposed by [renaud, 1992;1996].
dialog navigator : a spoken dialog q-a system based on large text knowledge base. this paper describes a spoken dialog q-a system as a substitution for call centers. the system is capable of making dialogs for both fixing speech recognition errors and for clarifying vague questions, based on only large text knowledge base. we introduce two measures to make dialogs for fixing recognition errors. an experimental evaluation shows the advantages of these measures.
the framenet data and software. the framenet project has developed a lexical knowledge base providing a unique level of detail as to the the possible syntactic realizations of the specific semantic roles evoked by each predicator, for roughly 7,000 lexical units, on the basis of annotating more than 100,000 example sentences extracted from corpora. an interim version of the framenet data was released in october, 2002 and is being widely used. a new, more portable version of the framenet software is also being made available to researchers elsewhere, including the spanish framenet project.this demo and poster will briefly explain the principles of frame semantics and demonstrate the new unified tools for lexicon building and annotation and also framesql, a search tool for finding patterns in annotated sentences. we will discuss the content and format of the data releases and how the software and data can be used by other nlp researchers.
an evaluation method of words tendency using decision tree. in every text, some words have frequency appearance and are considered as keywords because they have strong relationship with the subjects of their texts, these words frequencies change with time-series variation in a given period. however, in traditional text dealing methods and text search techniques, the importance of frequency change with time-series variation is not considered. therefore, traditional methods could not correctly determine index of word's popularity in a given period. in this paper, a new method is proposed to estimate automatically the stability classes (increasing, relatively constant, and decreasing) that indicate word's popularity with time-series variation based on the frequency change in past texts data. at first, learning data was produced by defining four attributes to measure frequency change of word quantitatively, these four attributes were extracted automatically from electronic texts.according to the comparison between the evaluation of the decision tree results and manually (human) results, f-measures of increasing, relatively constant and decreasing classes were 0.847, 0.851, and 0.768 respectively, and the effectiveness of this method is achieved.
spoken interactive odqa system: spiqa. we have been investigating an interactive approach for open-domain qa (odqa) and have constructed a spoken interactive odqa system, spiqa. the system derives disambiguating queries (dqs) that draw out additional information. to test the efficiency of additional information requested by the dqs, the system reconstructs the user's initial question by combining the addition information with question. the combination is then used for answer extraction. experimental results revealed the potential of the generated dqs.
a speech translation system with mobile wireless clients. we describe a new approach for elucidating the nonlinear degrees of freedom in a distribution of shapes depicted in digital images. by combining a deformation-based method for measuring distances between two shape configurations together with multidimensional scaling, a method for determining the number of degrees of freedom in a shape distribution is described. in addition, a method for visualizing the most representative modes of variation (underlying shape parameterization) in a nuclei shape distribution is also presented. the novel approach takes into account the nonlinear nature of shape manifolds and is related to the isomap algorithm. we apply the method to the task of analyzing the shape distribution of hela cell nuclei and conclude that approximately three parameters are responsible for their shape variation. excluding differences in size, translation, and orientation, these are: elongation, bending (concavity), and shifts in mass distribution. in addition, results show that, contrary to common intuition, the most likely nuclear shape configuration is not symmetric.
word sense disambiguation using pairwise alignment. in this paper, we proposed a new supervised word sense disambiguation (wsd) method based on a pairwise alignment technique, which is used generally to measure a similarity between dna sequences. the new method obtained 2.8%-14.2% improvements of the accuracy in our experiment for wsd.
on the applicability of global index grammars. we investigate global index grammars (gigs), a grammar formalism that uses a stack of indices associated with productions and has restricted context-sensitive power. we discuss some of the structural descriptions that gigs can generate compared with those generated by ligs. we show also how gigs can represent structural descriptions corresponding to hpsgs (pollard and sag, 1994) schemas.
deverbal compound noun analysis based on lexical conceptual structure. this paper proposes a principled approach for analysis of semantic relations between constituents in compound nouns based on lexical semantic structure. one of the difficulties of compound noun analysis is that the mechanisms governing the decision system of semantic relations and the representation method of semantic relations associated with lexical and contextual meaning are not obvious. the aim of our research is to clarify how lexical semantics contribute to the relations in compound nouns since such nouns are very productive and are supposed to be governed by systematic mechanisms. the results of applying our approach to the analysis of noun-deverbal compounds in japanese and english show that lexical conceptual structure contributes to the restrictional rules in compounds.
automatic collection of related terms from the web. this paper proposes a method of collecting a dozen terms that are closely related to a given seed term. the proposed method consists of three steps. the first step, compiling corpus step, collects texts that contain the given seed term by using search engines. the second step, automatic term recognition, extracts important terms from the corpus by using nakagawa's method. these extracted terms become the candidates for the final step. the final step, filtering step, removes inappropriate terms from the candidates based on search engine hits. an evaluation result shows that the precision of the method is 85%.
a novel approach to semantic indexing based on concept. this paper suggests the efficient indexing method based on a concept vector space that is capable of representing the semantic content of a document. the two information measure, namely the information quantity and the information ratio, are defined to represent the degree of the semantic importance within a document. the proposed method is expected to compensate the limitations of term frequency based methods by exploiting related lexical items. furthermore, with information ratio, this approach is independent of document length.
a limited-domain english to japanese medical speech translator built using regulus 2. we argue that verbal patient diagnosis is a promising application for limited-domain speech translation, and describe an architecture designed for this type of task which represents a compromise between principled linguistics-based processing on the one hand and efficient phrasal translation on the other. we propose to demonstrate a prototype system instantiating this architecture, which has been built on top of the open source regulus 2 platform. the prototype translates spoken yes-no questions about headache symptoms from english to japanese, using a vocabulary of about 200 words.
automatic error detection in the japanese learners' english spoken data. this paper describes a method of detecting grammatical and lexical errors made by japanese learners of english and other techniques that improve the accuracy of error detection with a limited amount of training data. in this paper, we demonstrate to what extent the proposed methods hold promise by conducting experiments using our learner corpus, which contains information on learners' errors.
automatic acquisition of named entity tagged corpus from world wide web. in this paper, we present a method that automatically constructs a named entity (ne) tagged corpus from the web to be used for learning of named entity recognition systems. we use an ne list and an web search engine to collect web documents which contain the ne instances. the documents are refined through sentence separation and text refinement procedures and ne instances are finally tagged with the appropriate ne categories. our experiments demonstrates that the suggested method can acquire enough ne tagged corpus equally useful to the manually tagged one without any human intervention.
a ranking model of proximal and structural text retrieval based on region algebra. this paper investigates an application of the ranked region algebra to information retrieval from large scale but unannotated documents. we automatically annotated documents with document structure and semantic tags by using taggers, and retrieve information by specifying structure represented by tags and words using ranked region algebra. we report in detail what kind of data can be retrieved in the experiments by this approach.
semantic classification of chinese unknown words. this paper describes a classifier that assigns semantic thesaurus categories to unknown chinese words (words not already in the cilin thesaurus and the chinese electronic dictionary, but in the sinica corpus). the focus of the paper differs in two ways from previous research in this particular area.prior research in chinese unknown words mostly focused on proper nouns (lee 1993, lee, lee and chen 1994, huang, hong and chen 1994, chen and chen 2000). this paper does not address proper nouns, focusing rather on common nouns, adjectives, and verbs. my analysis of the sinica corpus shows that contrary to expectation, most of unknown words in chinese are common nouns, adjectives, and verbs rather than proper nouns. other previous research has focused on features related to unknown word contexts (caraballo 1999; roark and charniak 1998). while context is clearly an important feature, this paper focuses on non-contextual features, which may play a key role for unknown words that occur only once and hence have limited context. the feature i focus on, following ciaramita (2002), is morphological similarity to words whose semantic category is known. my nearest neighbor approach to lexical acquisition computes the distance between an unknown word and examples from the cilin thesaurus based upon its morphological structure. the classifier improves on baseline semantic categorization performance for adjectives and verbs, but not for nouns.
a spoken dialogue interface for tv operations based on data collected by using woz method. the development of multi-channel digital broadcasting has generated a demand not only for new services but also for smart and highly functional capabilities in all broadcast-related devices. this is especially true of the television receivers on the viewer's side. with the aim of achieving a friendly interface that anybody can use with ease, we built a prototype interface system that operates a television through voice interactions using natural language. at the current stage of our research, we are using this system to investigate the usefulness and problem areas of the spoken dialogue interface for television operations.
integrating information extraction and automatic hyperlinking. this paper presents a novel information system integrating advanced information extraction technology and automatic hyper-linking. extracted entities are mapped into a domain ontology that relates concepts to a selection of hyperlinks. for information extraction, we use sprout, a generic platform for the development and use of multilingual text processing components. by combining finite-state and unification-based formalisms, the grammar formalism used in sprout offers both processing efficiency and a high degree of decalrativeness. the extralink demo system show-cases the extraction of relevant concepts from german texts in the tourism domain, offering the direct connection to associated web documents on demand.
totalrecall: a bilingual concordance for computer assisted translation and language learning. this paper describes a web-based english-chinese concordance system, total-recall, developed to promote translation reuse and encourage authentic and idiomatic use in second language writing. we exploited and structured existing high-quality translations from the bilingual sinorama magazine to build the concordance of authentic text and translation. novel approaches were taken to provide high-precision bilingual alignment on the sentence, phrase and word levels. a browser-based user interface (ui) is also developed for ease of access over the internet. users can search for word, phrase or expression in english or chinese. the web-based user interface facilitates the recording of the user actions to provide data for further research.
an intelligent procedure assistant built using regulus 2 and alterf. we will demonstrate the latest version of an ongoing project to create an intelligent procedure assistant for use by astronauts on the international space station (iss). the system functionality includes spoken dialogue control of navigation, coordinated display of the procedure text, display of related pictures, alarms, and recording and playback of voice notes. the demo also exemplifies several interesting component technologies. speech recognition and language understanding have been developed using the open source regulus 2 toolkit. this implements an approach to portable grammar-based language modelling in which all models are derived from a single linguistically motivated unification grammar. domain-specific cfg language models are produced by first specialising the grammar using an automatic corpus-based method, and then compiling the resulting specialised grammars into cfg form. translation between language centered and domain centered semantic representations is carried out by alterf, another open source toolkit, which combines rule-based and corpus-based processing in a transparent way.
towards interactive text understanding. this position paper argues for an interactive approach to text understanding. the proposed model extends an existing semantics-based text authoring system by using the input text as a source of information to assist the user in re-authoring its content. the approach permits a reliable deep semantic analysis by combining automatic information extraction with a minimal amount of human intervention.
a prototype text to british sign language (bsl) translation system. we demonstrate a text to sign language translation system for investigating sign language (sl) structure and assisting in production of sign narratives and informative presentations. the system is demonstrable on a conventional pc laptop computer.
kiwi: a multilingual usage consultation tool based on internet searching. we present a usage consultation tool based on internet searching. when a user enters a string of words that he wants to find the usage for, the system sends a query to the search engine to obtain a corpus about the string. the corpus is statistically analyzed and results are displayed. as the system uses neither language-dependent analysis nor initial data, queries can be made in any language, even languages for which there are no well-established analytical methods. also, since the corpus is dynamically obtained from the search engines, the usages provided to the user are always up to date. kiwi can fill in the missing parts of the collocations frequently used by native speakers.
ineats: interactive multi-document summarization. we describe ineats -- an interactive multi-document summarization system that integrates a state-of-the-art summarization engine with an advanced user interface. three main goals of the system are: (1) provide a user with control over the summarization process, (2) support exploration of the document set with the summary as the staring point, and (3) combine text summaries with alternative presentations such as a map-based visualization of documents.
a debug tool for practical grammar development. we have developed willex, a tool that helps grammar developers to work efficiently by using annotated corpora and recording parsing errors. willex has two major new functions. first, it decreases ambiguity of the parsing results by comparing them to an annotated corpus and removing wrong partial results both automatically and manually. second, willex accumulates parsing errors as data for the developers to clarify the defects of the grammar statistically. we applied willex to a large-scale hpsg-style grammar as an example.
approaches to zero adnominal recognition. this paper describes our preliminary attempt to automatically recognize zero adnominals, a subgroup of zero pronouns, in japanese discourse. based on the corpus study, we define and classify what we call "argument-taking nouns (atns)," i.e., nouns that can appear with zero adnominals. we propose an atn recognition algorithm that consists of lexicon-based heuristics, drawn from the observations of our analysis. we finally present the result of the algorithm evaluation and discuss future directions.
automatic detection of grammar elements that decrease readability. this paper proposes an automatic method of detecting grammar elements that decrease readability in a japanese sentence. the method consists of two components: (1) the check list of the grammar elements that should be detected; and (2) the detector, which is a search program of the grammar elements from a sentence. by defining a readability level for every grammar element, we can find which part of the sentence is difficult to read.
chinese unknown word identification using character-based tagging and chunking. lossless compression of color mosaic images poses a unique and interesting problem of spectral decorrelation of spatially interleaved r, g, b samples. we investigate reversible lossless spectral-spatial transforms that can remove statistical redundancies in both spectral and spatial domains and discover that a particular wavelet decomposition scheme, called mallat wavelet packet transform, is ideally suited to the task of decorrelating color mosaic data. we also propose a low-complexity adaptive context-based golomb-rice coding technique to compress the coefficients of mallat wavelet packet transform. the lossless compression performance of the proposed method on color mosaic images is apparently the best so far among the existing lossless image codecs.
improving the performance of the random walk model for answering complex questions. we consider the problem of answering complex questions that require inferencing and synthesizing information from multiple documents and can be seen as a kind of topic-oriented, informative multi-document summarization. the stochastic, graph-based method for computing the relative importance of textual units (i.e. sentences) is very successful in generic summarization. in this method, a sentence is encoded as a vector in which each component represents the occurrence frequency (tf*idf) of a word. however, the major limitation of the tf*idf approach is that it only retains the frequency of the words and does not take into account the sequence, syntactic and semantic information. in this paper, we study the impact of syntactic and shallow semantic information in the graph-based method for answering complex questions.
comparison between cfg filtering techniques for ltag and hpsg. an empirical comparison of cfg filtering techniques for ltag and hpsg is presented. we demonstrate that an approximation of hpsg produces a more effective cfg filter than that of ltag. we also investigate the reason for that difference.
mapping between compositional semantic representations and lexical semantic resources: towards accurate deep semantic parsing. this paper introduces a machine learning method based on bayesian networks which is applied to the mapping between deep semantic representations and lexical semantic resources. a probabilistic model comprising minimal recursion semantics (mrs) structures and lexicalist oriented semantic features is acquired. lexical semantic roles enriching the mrs structures are inferred, which are useful to improve the accuracy of deep semantic parsing. verb classes inference was also investigated, which, together with lexical semantic information provided by verbnet and propbank resources, can be substantially beneficial to the parse disambiguation task.
artificial intelligence medicine, 5th conference on artificial intelligence in medicine in europe, aime'95, pavia, italy, june 25-28, 1995, proceedings although researchers have made great progresses on music genre classification in recent years, the need for more accurate system is still not satisfied. in this paper, we propose a method for further reducing the classification error rate based on multiple classifier fusion. first of all, mfccs and four features from mpeg-7 audio descriptor are extracted in every short time frame, and then a group of frames are gathered into a longer segment, in which mean and variance of these short time frames features are calculated. the segment is considered as the basic unit for training and testing module. then random forest (rf) and multilayer perceptron neural network (mlp) are executed on such segment independently. finally, a weighted voting fusion strategy is employed to fusion the result of the two classifiers on each segment, and the whole file decision is made by selecting the most frequently labeled genre over all the segments. experiments showed that the approach is effective. the fusion result gets 12.4% relative reduction in error rate compared to our baseline system.
artificial intelligence medicine, 6th conference on artificial intelligence in medicine in europe, aime'97, grenoble, france, march 23-26, 1997, proceedings feature selection (fs) is a technique for dimensionality reduction. its aims are to select a subset of the original features of a dataset which are rich in the most useful information. the benefits include improved data visualisation, transparency, a reduction in training and utilisation times and potentially, improved prediction performance. many approaches based on rough set theory have employed the dependency function which is based on the information contained in the lower approximation as an evaluation step in the fs process with much success. this paper presents a novel rough set fs technique which uses the information of both the lower approximation dependency value and a distance metric for the consideration of objects in the boundary region. the use of this measure in rough set feature selection can result in smaller subset sizes than those obtained using the dependency function alone.
artificial intelligence medicine, 8th conference on ai in medicine in europe, aime 2001, cascais, portugal, july 1-4, 2001, proceedings since multisensor image fusion is becoming a promising technique, many image fusion techniques based on the multiresolution wavelet decomposition have been developed. however, wavelets have been proved to have disappointing behaviors in higher dimensions. so, we proposed a novel multisensor image fusion scheme based on contourlet transform, which can capture the intrinsic geometrical structure that is key in visual information. we have estimated the validity of the fusion method by analyzing, visually and quantitatively, and the approaches proposed in this paper result in fused images with improved quality with respect to those obtained by wavelet-based fusion methods.
artificial intelligence in medicine, 9th conference on artificial intelligence in medicine in europe, aime 2003, protaras, cyprus, october 18-22, 2003, proceedings scene matching measures the similarity of scenes in photos and is of central importance in applications where we have to properly organize large amount of digital photos by scene categories. in this paper, we present a novel scene matching method using local features representatives. for a given image, its scene is compactly represented as a set of cluster centers, called local feature representatives, where the clusters are obtained using the affinity propagation (ap) algorithm to aggregate local features according to their spatial closeness and appearance similarity. the similarity of scenes in two images is then measured by a modified earth mover distance (emd) between their corresponding sets of local feature representatives. empirical experiments on real world photos shows that our method is comparable to the state-of-the-arts.
artificial intelligence in medicine, 10th conference on artificial intelligence in medicine, aime 2005, aberdeen, uk, july 23-27, 2005, proceedings minutiae pattern remains a widely used representation of a fingerprint. the research on minutiae matching never stops due to its complexity and intractability. in this paper, an efficient fingerprint minutiae matching algorithm is proposed. to obtain reliable reference minutiae pairs, the bank of coordinate systems is introduced. the coordinate systems bank is derived from the original minutiae features and applied to get more useful information about the minutiae. to improve the accuracy of minutiae matching, a global optimum alignment approach is developed, which is targeted on the alignment of the set of reference minutiae pairs. experimental results show that this algorithm achieves excellent performance with high matching speed and high matching reliability
artificial intelligence in medicine, 11th conference on artificial intelligence in medicine, aime 2007, amsterdam, the netherlands, july 7-11, 2007, proceedings as networks grow in size and complexity, both the probability and the impact of failures increase. the pre-allocated backup bandwidth, which has been widely investigated in the literature, may not be able to provide full protection guarantee when multiple failures occur in a network. in this study, we consider multiple concurrent failures where concurrent means that a new failure occurs before a previous failure is repaired. to combat the effect of multiple concurrent failures, new backups can be reprovisioned after one failure such that the next potential failure can be handled effectively and efficiently. we consider dynamic traffic where a pair of link-disjoint primary and backup paths is provisioned when a new connection request arrives. after a failure occurs, the affected connections switch traffic from their primary paths to backup paths. to protect against next potential failure, we reprovision new backups for connections that become unprotected or vulnerable because of losing their primary or their backup due to the previous failure or due to backup resource sharing. this approach is called minimal backup reprovisioning (mbr). an alternative approach is to globally rearrange backups for all connections after one failure occurs, which is called global backup reprovisioning (gbr). backup reprovisioning can be performed whenever the network's state changes, e.g., (1) when a new request arrives, (2) when an existing connection terminates, (3) when a network failure occurs, (4) when a failed link/node is repaired, etc., to utilize the available resources more efficiently or to recover quickly from the next failure. in this study, we perform mbr or gbr after one network failure occurs to protect against the next potential failure in a wavelength-convertible wdm mesh network. the link-vector network model which can maximally explore the backup-sharing potential is assumed in this study. we then analyze the complexity of mbr and gbr under such a network model. a r- - eprovisioning algorithm is proposed for mbr which can significantly reduce the connection vulnerability without the knowledge of the location of the next failure. in gbr, both integer linear program (ilp) and heuristic-based approaches are proposed. we compare capacity requirement and computational complexity of mbr to that of gbr through numerical examples. mbr demonstrates a good tradeoff between complexity and capacity efficiency to handle multiple concurrent failures
artificial intelligence in medicine, 12th conference on artificial intelligence in medicine, aime 2009, verona, italy, july 18-22, 2009. proceedings that ensuring the electronic documents security is the key to the protection of internal information. with the extent of file sharing enlarged, it is hard to keep balance between the security and sharing. to achieve this goal, file tracing and audit, dynamic adjustment of right must be solved better. in this paper, a electronic document security system based on lineage mechanism is proposed,it support dynamic adjust right in mutable environment. it implement the file trace through recording the access logs and path of transmission. in fact, it implement one of the ucon models: pre-authorization with post update.
sherlog: error diagnosis by connecting clues from run-time logs. computer systems often fail due to many factors such as software bugs or administrator errors. diagnosing such production run failures is an important but challenging task since it is difficult to reproduce them in house due to various reasons: (1) unavailability of users' inputs and file content due to privacy concerns; (2) difficulty in building the exact same execution environment; and (3) non-determinism of concurrent executions on multi-processors. therefore, programmers often have to diagnose a production run failure based on logs collected back from customers and the corresponding source code. such diagnosis requires expert knowledge and is also too time-consuming, tedious to narrow down root causes. to address this problem, we propose a tool, called sherlog, that analyzes source code by leveraging information provided by run-time logs to infer what must or may have happened during the failed production run. it requires neither re-execution of the program nor knowledge on the log's semantics. it infers both control and data value information regarding to the failed execution. we evaluate sherlog with 8 representative real world software failures (6 software bugs and 2 configuration errors) from 7 applications including 3 servers. information inferred by sherlog are very useful for programmers to diagnose these evaluated failures. our results also show that sherlog can analyze large server applications such as apache with thousands of logging messages within only 40 minutes.
probabilistic job symbiosis modeling for smt processor scheduling. symbiotic job scheduling boosts simultaneous multithreading (smt) processor performance by co-scheduling jobs that have `compatible' demands on the processor's shared resources. existing approaches however require a sampling phase, evaluate a limited number of possible co-schedules, use heuristics to gauge symbiosis, are rigid in their optimization target, and do not preserve system-level priorities/shares. this paper proposes probabilistic job symbiosis modeling, which predicts whether jobs will create positive or negative symbiosis when co-scheduled without requiring the co-schedule to be evaluated. the model, which uses per-thread cycle stacks computed through a previously proposed cycle accounting architecture, is simple enough to be used in system software. probabilistic job symbiosis modeling provides six key innovations over prior work in symbiotic job scheduling: (i) it does not require a sampling phase, (ii) it readjusts the job co-schedule continuously, (iii) it evaluates a large number of possible co-schedules at very low overhead, (iv) it is not driven by heuristics, (v) it can optimize a performance target of interest (e.g., system throughput or job turnaround time), and (vi) it preserves system-level priorities/shares. these innovations make symbiotic job scheduling both practical and effective. our experimental evaluation, which assumes a realistic scenario in which jobs come and go, reports an average 16% (and up to 35%) reduction in job turnaround time compared to the previously proposed sos (sample, optimize, symbios) approach for a two-thread smt processor, and an average 19% (and up to 45%) reduction in job turnaround time for a four-thread smt processor.
a real system evaluation of hardware atomicity for software speculation. in this paper we evaluate the atomic region compiler abstraction by incorporating it into a commercial system. we find that atomic regions are simple and intuitive to integrate into an x86 binary-translation system. furthermore, doing so trivially enables additional optimization opportunities beyond that achievable by a high-performance dynamic optimizer, which already implements superblocks. we show that atomic regions can suffer from severe performance penalties if misspeculations are left uncontrolled, but that a simple software control mechanism is sufficient to reign in all detrimental side-effects. we evaluate using full reference runs of the spec cpu2000 integer benchmarks and find that atomic regions enable up to a 9% (3% on average) improvement beyond the performance of a tuned product. these performance improvements are achieved without any negative side effects. performance side effects such as code bloat are absent with atomic regions; in fact, static code size is reduced. the hardware necessary is synergistic with other needs and was already available on the commercial product used in our evaluation. finally, the software complexity is minimal as a single developer was able to incorporate atomic regions into a sophisticated 300,000 line code base in three months, despite never having seen the translator source code beforehand.
power routing: dynamic power provisioning in the data center. data center power infrastructure incurs massive capital costs, which typically exceed energy costs over the life of the facility. to squeeze maximum value from the infrastructure, researchers have proposed over-subscribing power circuits, relying on the observation that peak loads are rare. to ensure availability, these proposals employ power capping, which throttles server performance during utilization spikes to enforce safe power budgets. however, because budgets must be enforced locally -- at each power distribution unit (pdu) -- local utilization spikes may force throttling even when power delivery capacity is available elsewhere. moreover, the need to maintain reserve capacity for fault tolerance on power delivery paths magnifies the impact of utilization spikes. in this paper, we develop mechanisms to better utilize installed power infrastructure, reducing reserve capacity margins and avoiding performance throttling. unlike conventional high-availability data centers, where collocated servers share identical primary and secondary power feeds, we reorganize power feeds to create shuffled power distribution topologies. shuffled topologies spread secondary power feeds over numerous pdus, reducing reserve capacity requirements to tolerate a single pdu failure. second, we propose power routing, which schedules it load dynamically across redundant power feeds to: (1) shift slack to servers with growing power demands, and (2) balance power draw across ac phases to reduce heating and improve electrical stability. we describe efficient heuristics for scheduling servers to pdus (an np-complete problem). using data collected from nearly 1000 servers in three production facilities, we demonstrate that these mechanisms can reduce the required power infrastructure capacity relative to conventional high-availability data centers by 32% without performance degradation.
technology for developing regions: moore's law is not enough. the historic focus of development has rightfully been on macroeconomics and good governance, but technology has an increasingly large role to play. in this talk, i review several novel technologies that we have deployed in india and africa, and discuss the challenges and opportunities of this new subfield of eecs research. working with the aravind eye hospital, we are currently supporting doctor / patient videoconferencing in 30+ rural villages; more than 25,000 people have had their blindness cured due to these exams. although moore's law has led to great cost reductions and thus enabled new technologies, we have reached essentially the low point for cost: the computing is essentially free compared to the rest of the system. the premium is thus on a combination of 1) deeper integration (fewer compo-nents), 2) shared usage models (even phones are shared), and 3) lower operating costs in terms of power and connectivity.
addressing shared resource contention in multicore processors via scheduling. contention for shared resources on multicore processors remains an unsolved problem in existing systems despite significant research efforts dedicated to this problem in the past. previous solutions focused primarily on hardware techniques and software page coloring to mitigate this problem. our goal is to investigate how and to what extent contention for shared resource can be mitigated via thread scheduling. scheduling is an attractive tool, because it does not require extra hardware and is relatively easy to integrate into the system. our study is the first to provide a comprehensive analysis of contention-mitigating techniques that use only scheduling. the most difficult part of the problem is to find a classification scheme for threads, which would determine how they affect each other when competing for shared resources. we provide a comprehensive analysis of such classification schemes using a newly proposed methodology that enables to evaluate these schemes separately from the scheduling algorithm itself and to compare them to the optimal. as a result of this analysis we discovered a classification scheme that addresses not only contention for cache space, but contention for other shared resources, such as the memory controller, memory bus and prefetching hardware. to show the applicability of our analysis we design a new scheduling algorithm, which we prototype at user level, and demonstrate that it performs within 2\% of the optimal. we also conclude that the highest impact of contention-aware scheduling techniques is not in improving performance of a workload as a whole but in improving quality of service or performance isolation for individual applications.
paralog: enabling and accelerating online parallel monitoring of multithreaded applications. instruction-grain lifeguards monitor the events of a running application at the level of individual instructions in order to identify and help mitigate application bugs and security exploits. because such lifeguards impose a 10-100x slowdown on existing platforms, previous studies have proposed hardware designs to accelerate lifeguard processing. however, these accelerators are either tailored to a specific class of lifeguards or suitable only for monitoring singlethreaded programs. we present paralog, the first design of a system enabling fast online parallel monitoring of multithreaded parallel applications. paralog supports a broad class of software-defined lifeguards. we show how three existing accelerators can be enhanced to support online multithreaded monitoring, dramatically reducing lifeguard overheads. we identify and solve several challenges in monitoring parallel applications and/or parallelizing these accelerators, including (i) enforcing inter-thread data dependences, (ii) dealing with inter-thread effects that are not reflected in coherence traffic, (iii) dealing with unmonitored operating system activity, and (iv) ensuring lifeguards can access shared metadata with negligible synchronization overheads. we present our system design for both sequentially consistent and total store ordering processors. we implement and evaluate our design on a 16 core simulated cmp, using benchmarks from splash-2 and parsec and two lifeguards: a data-flow tracking lifeguard and a memory-access checker lifeguard. our results show that (i) our parallel accelerators improve performance by 2-9x and 1.13-3.4x for our two lifeguards, respectively, (ii) we are 5-126x faster than the time-slicing approach required by existing techniques, and (iii) our average overheads for applications with eight threads are 51% and 28% for the two lifeguards, respectively.
characterizing processor thermal behavior. temperature is a dominant factor in the performance, reliability, and leakage power consumption of modern processors. as a result, increasing numbers of researchers evaluate thermal characteristics in their proposals. in this paper, we measure a real processor focusing on its thermal characterization executing diverse workloads. our results show that in real designs, thermal transients operate at larger scales than their performance and power counterparts. conventional thermal simulation methodologies based on profile-based simulation or statistical sampling, such as simpoint, tend to explore very limited execution spans. short simulation times can lead to reduced matchings between performance and thermal phases. to illustrate these issues we characterize and classify from a thermal standpoint spec00 and spec06 applications, which are traditionally used in the evaluation of architectural proposals. this paper concludes with a list of recommendations regarding thermal modeling considerations based on our experimental insights.
orthrus: efficient software integrity protection on multi-cores. this paper proposes an efficient hardware/software system that significantly enhances software security through diversified replication on multi-cores. recent studies show that a large class of software attacks can be detected by running multiple versions of a program simultaneously and checking the consistency of their behaviors. however, execution of multiple replicas incurs significant overheads on today's computing platforms, especially with fine-grained comparisons necessary for high security. orthrus exploits similarities in automatically generated replicas to enable simultaneous execution of those replicas with minimal overheads; the architecture reduces memory and bandwidth overheads by compressing multiple memory spaces together, and additional power consumption and silicon area by eliminating redundant computations. utilizing the hardware architecture, orthrus implements a fine-grained memory layout diversification with the llvm compiler and can detect corruptions in both pointers and critical data. experiments indicate that the orthrus architecture incurs minimal overheads and provides a protection against a broad range of attacks.
dynamically replicated memory: building reliable systems from nanoscale resistive memories. dram is facing severe scalability challenges in sub-45nm tech- nology nodes due to precise charge placement and sensing hur- dles in deep-submicron geometries. resistive memories, such as phase-change memory (pcm), already scale well beyond dram and are a promising dram replacement. unfortunately, pcm is write-limited, and current approaches to managing writes must de- commission pages of pcm when the first bit fails. this paper presents dynamically replicated memory (drm), the first hardware and operating system interface designed for pcm that allows continued operation through graceful degradation when hard faults occur. drm reuses memory pages that con- tain hard faults by dynamically forming pairs of complementary pages that act as a single page of storage. no changes are required to the processor cores, the cache hierarchy, or the operating sys- tem's page tables. by changing the memory controller, the tlbs, and the operating system to be drm-aware, we can improve the lifetime of pcm by up to 40x over conventional error-detection techniques.
micro-pages: increasing dram efficiency with locality-aware data placement. power consumption and dram latencies are serious concerns in modern chip-multiprocessor (cmp or multi-core) based compute systems. the management of the dram row buffer can significantly impact both power consumption and latency. modern dram systems read data from cell arrays and populate a row buffer as large as 8 kb on a memory request. but only a small fraction of these bits are ever returned back to the cpu. this ends up wasting energy and time to read (and subsequently write back) bits which are used rarely. traditionally, an open-page policy has been used for uni-processor systems and it has worked well because of spatial and temporal locality in the access stream. in future multi-core processors, the possibly independent access streams of each core are interleaved, thus destroying the available locality and significantly under-utilizing the contents of the row buffer. in this work, we attempt to improve row-buffer utilization for future multi-core systems. the schemes presented here are motivated by our observations that a large number of accesses within heavily accessed os pages are to small, contiguous "chunks" of cache blocks. thus, the co-location of chunks (from different os pages) in a row-buffer will improve the overall utilization of the row buffer contents, and consequently reduce memory energy consumption and access time. such co-location can be achieved in many ways, notably involving a reduction in os page size and software or hardware assisted migration of data within dram. we explore these mechanisms and discuss the trade-offs involved along with energy and performance improvements from each scheme. on average, for applications with room for improvement, our best performing scheme increases performance by 9% (max. 18%) and reduces memory energy consumption by 15% (max. 70%).
conmem: detecting severe concurrency bugs through an effect-oriented approach. multicore technology is making concurrent programs increasingly pervasive. unfortunately, it is difficult to deliver reliable concurrent programs, because of the huge and non-deterministic interleaving space. in reality, without the resources to thoroughly check the interleaving space, critical concurrency bugs can slip into production runs and cause failures in the field. approaches to making the best use of the limited resources and exposing severe concurrency bugs before software release would be desirable. unlike previous work that focuses on bugs caused by specific interleavings (e.g., races and atomicity-violations), this paper targets concurrency bugs that result in one type of severe effects: program crashes. our study of the error-propagation process of realworld concurrency bugs reveals a common pattern (50% in our non-deadlock concurrency bug set) that is highly correlated with program crashes. we call this pattern concurrency-memory bugs: buggy interleavings directly cause memory bugs (null-pointer-dereference, dangling-pointer, buffer-overflow, uninitialized-read) on shared memory objects. guided by this study, we built conmem to monitor program execution, analyze memory accesses and synchronizations, and predicatively detect these common and severe concurrency-memory bugs. we also built a validator conmem-v to automatically prune false positives by enforcing potential bug-triggering interleavings. we evaluated conmem using 7 open-source programs with 9 real-world severe concurrency bugs. conmem detects more tested bugs (8 out of 9 bugs) than a lock-set-based race detector and an unserializable-interleaving detector that detect 4 and 5 bugs respectively, with a false positive rate about one tenth of the compared tools. conmem-v further prunes out all the false positives. conmem has reasonable overhead suitable for development usage.
coredet: a compiler and runtime system for deterministic multithreaded execution. the behavior of a multithreaded program does not depend only on its inputs. scheduling, memory reordering, timing, and low-level hardware effects all introduce nondeterminism in the execution of multithreaded programs. this severely complicates many tasks, including debugging, testing, and automatic replication. in this work, we avoid these complications by eliminating their root cause: we develop a compiler and runtime system that runs arbitrary multithreaded c/c++ posix threads programs deterministically. a trivial non-performant approach to providing determinism is simply deterministically serializing execution. instead, we present a compiler and runtime infrastructure that ensures determinism but resorts to serialization rarely, for handling interthread communication and synchronization. we develop two basic approaches, both of which are largely dynamic with performance improved by some static compiler optimizations. first, an ownership-based approach detects interthread communication via an evolving table that tracks ownership of memory regions by threads. second, a buffering approach uses versioned memory and employs a deterministic commit protocol to make changes visible to other threads. while buffering has larger single-threaded overhead than ownership, it tends to scale better (serializing less often). a hybrid system sometimes performs and scales better than either approach individually. our implementation is based on the llvm compiler infrastructure. it needs neither programmer annotations nor special hardware. our empirical evaluation uses the parsec and splash2 benchmarks and shows that our approach scales comparably to nondeterministic execution.
a power-efficient all-optical on-chip interconnect using wavelength-based oblivious routing. we present an all-optical approach to constructing data networks on chip that combines the following key features: (1) wavelength-based routing, where the route followed by a packet depends solely on the wavelength of its carrier signal, and not on information either contained in the packet or traveling along with it. (2) oblivious routing, by which the wavelength (and thus the route) employed to connect a source-destination pair is invariant for that pair, and does not depend on ongoing transmissions by other nodes, thereby simplifying design and operation. and (3) passive optical wavelength routers, whose routing pattern is set at design time, which allows for area and power optimizations not generally available to solutions that use dynamic routing. compared to prior proposals, our evaluation shows that our solution is significantly more power efficient at a similar level of performance.
specifying and dynamically verifying address translation-aware memory consistency. computer systems with virtual memory are susceptible to design bugs and runtime faults in their address translation (at) systems. detecting bugs and faults requires a clear specification of correct behavior. to address this need, we develop a framework for at-aware memory consistency models. we expand and divide memory consistency into the physical address memory consistency (pamc) model that defines the behavior of operations on physical addresses and the virtual address memory consistency (vamc) model that defines the behavior of operations on virtual addresses. as part of this expansion, we show what at features are required to bridge the gap between pamc and vamc. based on our at-aware memory consistency specifications, we design efficient dynamic verification hardware that can detect violations of vamc and thus detect the effects of design bugs and runtime faults, including most at related bugs in published errata.
fairness via source throttling: a configurable and high-performance fairness substrate for multi-core memory systems. cores in a chip-multiprocessor (cmp) system share multiple hardware resources in the memory subsystem. if resource sharing is unfair, some applications can be delayed significantly while others are unfairly prioritized. previous research proposed separate fairness mechanisms in each individual resource. such resource-based fairness mechanisms implemented independently in each resource can make contradictory decisions, leading to low fairness and loss of performance. therefore, a coordinated mechanism that provides fairness in the entire shared memory system is desirable. this paper proposes a new approach that provides fairness in the entire shared memory system, thereby eliminating the need for and complexity of developing fairness mechanisms for each individual resource. our technique, fairness via source throttling (fst), estimates the unfairness in the entire shared memory system. if the estimated unfairness is above a threshold set by system software, fst throttles down cores causing unfairness by limiting the number of requests they can inject into the system and the frequency at which they do. as such, our source-based fairness control ensures fairness decisions are made in tandem in the entire memory system. fst also enforces thread priorities/weights, and enables system software to enforce different fairness objectives and fairness-performance tradeoffs in the memory system. our evaluations show that fst provides the best system fairness and performance compared to four systems with no fairness control and with state-of-the-art fairness mechanisms implemented in both shared caches and memory controllers.
butterfly analysis: adapting dataflow analysis to dynamic parallel monitoring. online program monitoring is an effective technique for detecting bugs and security attacks in running applications. extending these tools to monitor parallel programs is challenging because the tools must account for inter-thread dependences and relaxed memory consistency models. existing tools assume sequential consistency and often slow down the monitored program by orders of magnitude. in this paper, we present a novel approach that avoids these pitfalls by not relying on strong consistency models or detailed inter-thread dependence tracking. instead, we only assume that events in the distant past on all threads have become visible; we make no assumptions on (and avoid the overheads of tracking) the relative ordering of more recent events on other threads. to overcome the potential state explosion of considering all the possible orderings among recent events, we adapt two techniques from static dataflow analysis, reaching definitions and reaching expressions, to this new domain of dynamic parallel monitoring. significant modifications to these techniques are proposed to ensure the correctness and efficiency of our approach. we show how our adapted analysis can be used in two popular memory and security tools. we prove that our approach does not miss errors, and sacrifices precision only due to the lack of a relative ordering among recent events. moreover, our simulation study on a collection of splash-2 and parsec 2.0 benchmarks running a memory-checking tool on a hardware-assisted logging platform demonstrates the potential benefits in trading off a very low false positive rate for (i) reduced overhead and (ii) the ability to run on relaxed consistency models.
shoestring: probabilistic soft error reliability on the cheap. aggressive technology scaling provides designers with an ever increasing budget of cheaper and faster transistors. unfortunately, this trend is accompanied by a decline in individual device reliability as transistors become increasingly susceptible to soft errors. we are quickly approaching a new era where resilience to soft errors is no longer a luxury that can be reserved for just processors in high-reliability, mission-critical domains. even processors used in mainstream computing will soon require protection. however, due to tighter profit margins, reliable operation for these devices must come at little or no cost. this paper presents shoestring, a minimally invasive software solution that provides high soft error coverage with very little overhead, enabling its deployment even in commodity processors with "shoestring" reliability budgets. leveraging intelligent analysis at compile time, and exploiting low-cost, symptom-based error detection, shoestring is able to focus its efforts on protecting statistically-vulnerable portions of program code. shoestring effectively applies instruction duplication to protect only those segments of code that, when subjected to a soft error, are likely to result in user-visible faults without first exhibiting symptomatic behavior. shoestring is able to recover from an additional 33.9% of soft errors that are undetected by a symptom-only approach, achieving an overall user-visible failure rate of 1.6%. this reliability improvement comes at a modest performance overhead of 15.8%.
dynamic filtering: multi-purpose architecture support for language runtime systems. this paper introduces a new abstraction to accelerate the read-barriers and write-barriers used by language runtime systems. we exploit the fact that, dynamically, many barrier executions perform checks but no real work -- e.g., in generational garbage collection (gc), frequent checks are needed to detect the creation of inter-generational references, even though such references occur rarely in many workloads. we introduce a form of dynamic filtering that identifies redundant checks by (i) recording checks that have recently been executed, and (ii) detecting when a barrier is repeating one of these checks. we show how this technique can be applied to a variety of algorithms for gc, transactional memory, and language-based security. by supporting dynamic filtering in the instruction set, we show that the fast-paths of these barriers can be streamlined, reducing the impact on the quality of surrounding code. we show how we accelerate the barriers used for generational gc and transactional memory in the bartok research compiler. with a 2048-entry filter, dynamic filtering eliminates almost all the overhead of the gc write-barriers. dynamic filtering eliminates around half the overhead of stm over a non-synchronized baseline -- even when used with an stm that is already designed for low overhead, and which employs static analyses to avoid redundant operations.
flexible architectural support for fine-grain scheduling. to make efficient use of cmps with tens to hundreds of cores, it is often necessary to exploit fine-grain parallelism. however, managing tasks of a few thousand instructions is particularly challenging, as the runtime must ensure load balance without compromising locality and introducing small overheads. software-only schedulers can implement various scheduling algorithms that match the characteristics of different applications and programming models, but suffer significant overheads as they synchronize and communicate task information over the deep cache hierarchy of a large-scale cmp. to reduce these costs, hardware-only schedulers like carbon, which implement task queuing and scheduling in hardware, have been proposed. however, a hardware-only solution fixes the scheduling algorithm and leaves no room for other uses of the custom hardware. this paper presents a combined hardware-software approach to build fine-grain schedulers that retain the flexibility of software schedulers while being as fast and scalable as hardware ones. we propose asynchronous direct messages (adm), a simple architectural extension that provides direct exchange of asynchronous, short messages between threads in the cmp without going through the memory hierarchy. adm is sufficient to implement a family of novel, software-mostly schedulers that rely on low-overhead messaging to efficiently coordinate scheduling and transfer task information. these schedulers match and often exceed the performance and scalability of carbon when using the same scheduling algorithm. when the adm runtime tailors its scheduling algorithm to application characteristics, it outperforms carbon by up to 70%.
inter-core cooperative tlb for chip multiprocessors. translation lookaside buffers (tlbs) are commonly employed in modern processor designs and have considerable impact on overall system performance. a number of past works have studied tlb designs to lower access times and miss rates, specifically for uniprocessors. with the growing dominance of chip multiprocessors (cmps), it is necessary to examine tlb performance in the context of parallel workloads. this work is the first to present tlb prefetchers that exploit commonality in tlb miss patterns across cores in cmps. we propose and evaluate two inter-core cooperative (icc) tlb prefetching mechanisms, assessing their effectiveness at eliminating tlb misses both individually and together. our results show these approaches require at most modest hardware and can collectively eliminate 19% to 90% of data tlb (d-tlb) misses across the surveyed parallel workloads. we also compare performance improvements across a range of hardware and software implementation possibilities. we find that while a fully-hardware implementation results in average performance improvements of 8-46% for a range of tlb sizes, a hardware/software approach yields improvements of 4-32%. overall, our work shows that tlb prefetchers exploiting inter-core correlations can effectively eliminate tlb misses.
virtualized and flexible ecc for main memory. we present a general scheme for virtualizing main memory error-correction mechanisms, which map redundant information needed to correct errors into the memory namespace itself. we rely on this basic idea, which increases flexibility to increase error protection capabilities, improve power efficiency, and reduce system cost; with only small performance overheads. we augment the virtual memory system architecture to detach the physical mapping of data from the physical mapping of its associated ecc information. we then use this mechanism to develop two-tiered error protection techniques that separate the process of detecting errors from the rare need to also correct errors, and thus save energy. we describe how to provide strong chipkill and double-chip kill protection using existing dram and packaging technology. we show how to maintain access granularity and redundancy overheads, even when using ×8 dram chips. we also evaluate error correction for systems that do not use ecc dimms. overall, analysis of demanding spec cpu 2006 and parsec benchmarks indicates that performance overhead is only 1% with ecc dimms and less than 10% using standard non-ecc dimm configurations, that dram power savings can be as high as 27%, and that the system energy-delay product is improved by 12% on average.
decoupling contention management from scheduling. many parallel applications exhibit unpredictable communication between threads, leading to contention for shared objects. the choice of contention management strategy impacts strongly the performance and scalability of these applications: spinning provides maximum performance but wastes significant processor resources, while blocking-based approaches conserve processor resources but introduce high overheads on the critical path of computation. under situations of high or changing load, the operating system complicates matters further with arbitrary scheduling decisions which often preempt lock holders, leading to long serialization delays until the preempted thread resumes execution. we observe that contention management is orthogonal to the problems of scheduling and load management and propose to decouple them so each may be solved independently and effectively. to this end, we propose a load control mechanism which manages the number of active threads in the system separately from any contention which may exist. by isolating contention management from damaging interactions with the os scheduler, we combine the efficiency of spinning with the robustness of blocking. the proposed load control mechanism results in stable, high performance for both lightly and heavily loaded systems, requires no special privileges or modifications at the os level, and can be implemented as a library which benefits existing code.
analyzing multicore dumps to facilitate concurrency bug reproduction. debugging concurrent programs is difficult. this is primarily because the inherent non-determinism that arises because of scheduler interleavings makes it hard to easily reproduce bugs that may manifest only under certain interleavings. the problem is exacerbated in multi-core environments where there are multiple schedulers, one for each core. in this paper, we propose a reproduction technique for concurrent programs that execute on multi-core platforms. our technique performs a lightweight analysis of a failing execution that occurs in a multi-core environment, and uses the result of the analysis to enable reproduction of the bug in a single-core system, under the control of a deterministic scheduler. more specifically, our approach automatically identifies the execution point in the re-execution that corresponds to the failure point. it does so by analyzing the failure core dump and leveraging a technique called execution indexing that identifies a related point in the re-execution. by generating a core dump at this point, and comparing the differences betwen the two dumps, we are able to guide a search algorithm to efficiently generate a failure inducing schedule. our experiments show that our technique is highly effective and has reasonable overhead.
conservation cores: reducing the energy of mature computations. growing transistor counts, limited power budgets, and the breakdown of voltage scaling are currently conspiring to create a utilization wall that limits the fraction of a chip that can run at full speed at one time. in this regime, specialized, energy-efficient processors can increase parallelism by reducing the per-computation power requirements and allowing more computations to execute under the same power budget. to pursue this goal, this paper introduces conservation cores. conservation cores, or c-cores, are specialized processors that focus on reducing energy and energy-delay instead of increasing performance. this focus on energy makes c-cores an excellent match for many applications that would be poor candidates for hardware acceleration (e.g., irregular integer codes). we present a toolchain for automatically synthesizing c-cores from application source code and demonstrate that they can significantly reduce energy and energy-delay for a wide range of applications. the c-cores support patching, a form of targeted reconfigurability, that allows them to adapt to new versions of the software they target. our results show that conservation cores can reduce energy consumption by up to 16.0x for functions and by up to 2.1x for whole applications, while patching can extend the useful lifetime of individual c-cores to match that of conventional processors.
request behavior variations. a large number of user requests execute (often concurrently) within a server system. a single request may exhibit fluctuating hardware characteristics (such as instruction completion rate and on-chip resource usage) over the course of its execution, due to inherent variations in application execution semantics as well as dynamic resource competition on resource-sharing processors like multicores. understanding such behavior variations can assist fine-grained request modeling and adaptive resource management. this paper presents operating system management to track request behavior variations online. in addition to metric sample collection during periodic interrupts, we exploit the frequent system calls in server applications to perform low-cost in-kernel sampling. we utilize identified behavior variations to support or enhance request modeling in request classification, anomaly analysis, and online request signature construction. a foundation of our request modeling is the ability to quantify the difference between two requests' time series behaviors. we evaluate several differencing measures and enhance the classic dynamic time warping technique with additional penalties for asynchronous warp steps. finally, motivated by fluctuating request resource usage and the resulting contention, we implement contention-easing cpu scheduling on multicore platforms and demonstrate its effectiveness in improving the worst-case request performance. experiments in this paper are based on five server applications -- apache web server, tpcc, tpch, rubis online auction benchmark, and a user-content-driven online teaching application called webwork.
respec: efficient online multiprocessor replayvia speculation and external determinism. deterministic replay systems record and reproduce the execution of a hardware or software system. while it is well known how to replay uniprocessor systems, replaying shared memory multiprocessor systems at low overhead on commodity hardware is still an open problem. this paper presents respec, a new way to support deterministic replay of shared memory multithreaded programs on commodity multiprocessor hardware. respec targets online replay in which the recorded and replayed processes execute concurrently. respec uses two strategies to reduce overhead while still ensuring correctness: speculative logging and externally deterministic replay. speculative logging optimistically logs less information about shared memory dependencies than is needed to guarantee deterministic replay, then recovers and retries if the replayed process diverges from the recorded process. externally deterministic replay relaxes the degree to which the two executions must match by requiring only their system output and final program states match. we show that the combination of these two techniques results in low recording and replay overhead for the common case of data-race-free execution intervals and still ensures correct replay for execution intervals that have data races. we modified the linux kernel to implement our techniques. our software system adds on average about 18% overhead to the execution time for recording and replaying programs with two threads and 55% overhead for programs with four threads.
joint optimization of idle and cooling power in data centers while maintaining response time. server power and cooling power amount to a significant fraction of modern data centers' recurring costs. while data centers provision enough servers to guarantee response times under the maximum loading, data centers operate under much less loading most of the times (e.g., 30-70% of the maximum loading). previous server-power proposals exploit this under-utilization to reduce the server idle power by keeping active only as many servers as necessary and putting the rest into low-power standby modes. however, these proposals incur higher cooling power due to hot spots created by concentrating the data center loading on fewer active servers, or degrade response times due to standby-to-active transition delays, or both. other proposals optimize the cooling power but incur considerable idle power. to address the first issue of power, we propose powertrade, which trades-off idle power and cooling power for each other, thereby reducing the total power. to address the second issue of response time, we propose surgeguard to overprovision the number of active servers beyond that needed by the current loading so as to absorb future increases in the loading. surgeguard is a two-tier scheme which uses well-known over-provisioning at coarse time granularities (e.g., one hour) to absorb the common, smooth increases in the loading, and a novel fine-grain replenishment of the over-provisioned reserves at fine time granularities (e.g., five minutes) to handle the uncommon, abrupt loading surges. using real-world traces, we show that combining powertrade and surgeguard reduces total power by 30% compared to previous low-power schemes while maintaining response times within 1.7%.
compass: a programmable data prefetcher using idle gpu shaders. a traditional fixed-function graphics accelerator has evolved into a programmable general-purpose graphics processing unit over the last few years. these powerful computing cores are mainly used for accelerating graphics applications or enabling low-cost scientific computing. to further reduce the cost and form factor, an emerging trend is to integrate gpu along with the memory controllers onto the same die with the processor cores. however, given such a system-on-chip, the gpu, while occupying a substantial part of the silicon, will sit idle and contribute nothing to the overall system performance when running non-graphics workloads or applications lack of data-level parallelism. in this paper, we propose compass, a compute shader-assisted data prefetching scheme, to leverage the gpu resource for improving single-threaded performance on an integrated system. by harnessing the gpu shader cores with very lightweight architectural support, compass can emulate the functionality of a hardware-based prefetcher using the idle gpu and successfully improve the memory performance of single-thread applications. moreover, thanks to its flexibility and programmability, one can implement the best performing prefetch scheme to improve each specific application as demonstrated in this paper. with compass, we envision that a future application vendor can provide a custom-designed compass shader bundled with its software to be loaded at runtime to optimize the performance. our simulation results show that compass can improve the single-thread performance of memory-intensive applications by 68% on average.
speculative parallelization using software multi-threaded transactions. with the right techniques, multicore architectures may be able to continue the exponential performance trend that elevated the performance of applications of all types for decades. while many scientific programs can be parallelized without speculative techniques, speculative parallelism appears to be the key to continuing this trend for general-purpose applications. recently-proposed code parallelization techniques, such as those by bridges et al. and by thies et al., demonstrate scalable performance on multiple cores by using speculation to divide code into atomic units (transactions) that span multiple threads in order to expose data parallelism. unfortunately, most software and hardware thread-level speculation (tls) memory systems and transactional memories are not sufficient because they only support single-threaded atomic units. multi-threaded transactions (mtxs) address this problem, but they require expensive hardware support as currently proposed in the literature. this paper proposes a software mtx (smtx) system that captures the applicability and performance of hardware mtx, but on existing multicore machines. the smtx system yields a harmonic mean speedup of 13.36x on native hardware with four 6-core processors (24 cores in total) running speculatively parallelized applications.
a randomized scheduler with probabilistic guarantees of finding bugs. this paper presents a randomized scheduler for finding concurrency bugs. like current stress-testing methods, it repeatedly runs a given test program with supplied inputs. however, it improves on stress-testing by finding buggy schedules more effectively and by quantifying the probability of missing concurrency bugs. key to its design is the characterization of the depth of a concurrency bug as the minimum number of scheduling constraints required to find it. in a single run of a program with n threads and k steps, our scheduler detects a concurrency bug of depth d with probability at least 1/nkd-1. we hypothesize that in practice, many concurrency bugs (including well-known types such as ordering errors, atomicity violations, and deadlocks) have small bug-depths, and we confirm the efficiency of our schedule randomization by detecting previously unknown and known concurrency bugs in several production-scale concurrent programs.
macross: macro-simdization of streaming applications. simd (single instruction, multiple data) engines are an essential part of the processors in various computing markets, from servers to the embedded domain. although simd-enabled architectures have the capability of boosting the performance of many application domains by exploiting data-level parallelism, it is very challenging for compilers and also programmers to identify and transform parts of a program that will benefit from a particular simd engine. the focus of this paper is on the problem of simdization for the growing application domain of streaming. streaming applications are an ideal solution for targeting multi-core architectures, such as shared/distributed memory systems, tiled architectures, and single-core systems. since these architectures, in most cases, provide simd acceleration units as well, it is highly beneficial to generate simd code from streaming programs. specifically, we introduce macross, which is capable of performing macro-simdization on high-level streaming graphs. macro-simdization uses high-level information such as execution rates of actors and communication patterns between them to transform the graph structure, vectorize actors of a streaming program, and generate intermediate code. we also propose low-overhead architectural modifications that accelerate shuffling of data elements between the scalar and vectorized parts of a streaming program. our experiments show that macross is capable of generating code that, on average, outperforms scalar code compiled with the current state-of-art auto-vectorizing compilers by 54%. using the low-overhead data shuffling hardware, performance is improved by an additional 8% with less than 1% area overhead.
shimon: an interactive improvisational robotic marimba player. shimon is an autonomous marimba-playing robot designed to create interactions with human players that lead to novel musical outcomes. the robot combines music perception, interaction, and improvisation with the capacity to produce melodic and harmonic acoustic responses through choreographic gestures. we developed an anticipatory action framework, and a gesture-based behavior system, allowing the robot to play improvised jazz with humans in synchrony, fluently, and without delay. in addition, we built an expressive non-humanoid head for musical social communication. this paper describes our system, used in a performance and demonstration at the chi 2010 media showcase.
interactive diagram layout. we examine an approach for defining layout algorithms for diagrams. such an algorithm is specified on an abstract level and may be applied to many kinds of visual languages. it mainly allows for incremental diagram drawing and attaches great importance on mental map preservation. with the approach, it is possible to combine graph drawing algorithms and other layout algorithms. it is capable of defining layout behavior for non-graph-like visual languages like nassi-shneiderman diagrams or gui forms as well as graph-like visual languages such as class diagrams, mindmaps, or business process models. in this paper, we demonstrate that the combination of graph drawing algorithms and other layout algorithms is meaningful by presenting three visual language editors that have been created by students.
location aware applications to support mobile food vendors in the developing world. this paper describes an ongoing research project to explore the potential of location aware mobile phone-based applications to support mobile food vendors in the developing world. these vendors are a ubiquitous phenomenon in the developing world and can be seen hawking their wares in carts, bicycles or motorcycles. we report preliminary findings from nine interviews conducted with various mobile food vendors in indonesia. based on these findings, we present our initial system design for a mobile phone-based application that allows these vendors to advertize their current location, accept orders from customers, and have customers recommend particular vendors.
managing user experience: managing change. as managers of user experience and design teams we often find ourselves in environments where it is difficult to position the work of our team members. their roles are often misunderstood and our adjacent disciplines such as product management and development see their work as unnecessary or in some cases are threatened by them. we find that the culture of the company we are trying to deploy ux resources into isn't ready to accept them and we find that our role becomes more that of a change manager than a user experience manager. we have a vision for what the future processes of the company can look like but we find it hard to communicate that vision and engage our adjacent disciplines. what are effective strategies user experience leaders can use to impact change? how can we leverage current business and engineering trends to move corporate cultures in a direction that support our work? what are the potential traps and pitfalls? what does a culture of design thinking really mean in this context? what is a realistic expectation for an end state?
there's a monster in my kitchen: using aversive feedback to motivate behaviour change. in this paper we argue that "persuasive technologies," developed to motivate behaviour change in users, have so far failed to exploit the established body of empirical research within behavioural science. we propose that persuasive technologies may benefit from both adapting to individual preferences, and a constructive use of aversive, in addition to appetitive, feedback. we detail an example application that demonstrates how this approach can be incorporated into an application designed to train users to adopt more environmentally friendly behaviours in their domestic kitchens.
a classification scheme for user intentions in image search. searching for images on the web is still an open problem. while multiple approaches have been presented, there has been surprisingly little work on the actual goals and intentions of users. in this poster we present our classification scheme for user goals in image search and describe our ongoing work focusing on identification and classification of user intentions during image search tasks.
model-driven development of advanced user interfaces. the workshop on model-driven development of advanced user interfaces will be a forum of multi-disciplinary discussion on how to integrate model-driven development with the often more informal methodologies used in user-centered design. starting point of the discussion will be the tools, models, methods and experiences of the workshop participants.
empowering products: personal identity through the act of appropriation. this paper explores the relationship between personal identity and the act of appropriating digital objects in the home--specifically do-it-yourself--to inform the design of empowering products. it reports ongoing research and provides a preliminary analysis of the steampunk movement as a case study for personal appropriation. appropriation-identity design guidelines are provided as a result of the data analysis.
lightweight selective availability in instant messaging. selective availability in instant messaging systems can improve connectiveness while at the same time keeping disruption low. in this paper we report on a four-week experience sampling study of selective availability in instant messaging to inform the design of lightweight mechanisms with little user effort.
robotany: breeze. this paper describes breeze, a live roboticized tree. visitor interaction with breeze is interpreted through a series of narratives. these narratives yield results with implications for human-computer interaction research.
natural interaction enhanced remote camera control for teleoperation. in teleoperation, operators usually have to control multiple devices simultaneously, which requires frequent hand switches between different controllers. we designed and implemented two prototypes, one by applying head motion and the other by integrating eye gaze as intrinsic elements of teleoperation for remote camera control in a multi-control setting. we report a user study of a modeled multi-control experiment that compares the performance of head tracking control, eye tracking control and traditional joystick control. the results provide clear evidence that eye tracking control significantly outperforms joystick and head tracking control in both objective measures and subjective measures.
making friends by killing them: using location-based urban gaming to expand personal networks. cultural problems exist with current online systems for meeting new people, such as dating sites, which encourage unnatural meetings with strangers. an sms-based murder mystery game was designed to facilitate the natural progression of growing one's personal network by meeting friends of friends. considerations on how a location-based mobile system could further facilitate personal network expansion are discussed.
metagora: a meta-community approach to guide users through the diversity of web communities. online communities have become an essential instrument for obtaining valuable information on the web. with today's community jungle, however, users find it increasingly difficult to find and decide on appropriate online communities. therefore, we propose the concept of a meta-community conceived as being a social gateway to guide users through a vast number of different online communities within a certain domain. we present a proof-of-concept study of our meta-community prototype and discuss implications for the community landscape as well as for the satisfaction of user needs.
toward modeling auditory information seeking strategies on the web. human performance models based on information foraging theory have proved capable of predicting navigation behavior on the web. they can therefore provide a useful tool for web site design. they may also be effective for modeling auditory navigation within a single web page. designers often struggle to accommodate this sort of access, different as it is from their own experience. as a step toward realistic simulations based on models of auditory web access, we describe information seeking strategies observed in people with visual impairment using screen reading software for web navigation tasks. we outline one example strategy for approaching a new web page that, guided by information foraging theory, may expose access barriers that current design tools miss.
himawari: shape memory alloy motion display for robotic representation. we propose the concept of shape memory alloy motion display (smd), a new type of physical display, and introduce a plant-shaped robot "himawari" based on this technology. smd is a display apparatus taking advantage of existence of an actual object, and gives visual expressions by movement and change in shape of actuators, which are components of this device. visual expressions resembling tentacles of sea anemone and foliage of grasses and trees are possible by designing the actuators, making way for new expressions by physical display. we built the plant-shaped robot himawari as a piece of art applying smd technology. we discuss the possibilities of smd through fabrication of the completed piece of art, himawari.
tavr: temporal-aural-visual representation to convey imperceptible spatial information. this paper describes a study that investigated the use of time as a form of representation for imperceptible sizes by incorporating it in a multimodal representation that is designed to extend students' learning experience of the sizes of the objects beyond human sense (called submacroscopic objects). in this paper we introduce the research we conducted to explore how middle school students interpret and conceptualize the temporal representation.
everybody to the power of one, for soprano t-stick. we present a live solo concert performance of an original piece of music - everybody to the power of one - written for the soprano t-stick digital musical instrument. like other digital musical instruments, the t-stick enables the reincorporation of performer gesture as the main source of control in computer-based music making. a brief description of the instrument development, gesture-sound mapping and performance practice is given, followed by an introduction to the compositional motivation and materials of the piece. everybody to the power of one is the fourth musical composition created for the t-stick by composer and performer d. andrew stewart.
one-press control: a tactile input method for pressure-sensitive computer keyboards. this work presents one-press control, a tactile input method for pressure-sensitive keyboards based on the detection and classification of pressing movements on the already held-down key. to seamlessly integrate the added control input with existing practices for ordinary computer keyboards, the redefined notion of virtual modifier keys is introduced. a number of application examples are given, especially to point out a potential for simplifying existing interactions by replacing modifier key combinations with single key presses. also, a new class of interaction scenarios employing the technique is proposed, based on an interaction model named "what you touch is what you get (wytiwyg)". here, the proposed tactile input method is used to navigate interaction options, get full previews of potential outcomes, and then either commit to one or abort altogether -- all in the space of one key depress / release cycle. the results of user testing indicate some remaining implementation issues, as well as that the technique can be learned within about a quarter of an hour of hands-on operating practice time.
sig: branding the changing enterprise - impact of mergers & acquisitions on user experience organizations. mergers and acquisitions are becoming increasingly common in the enterprise software world. for example, sap acquired business objects, oracle acquired peoplesoft and ca acquired cassatt in recent times. while this is a business expansion strategy for the acquiring company, it presents a challenge for ux professionals in both the acquiring and acquired companies, who are responsible for branding the look and feel of the newly combined business entity. this sig examines the design, technical and cultural challenges facing a ux practitioner from the acquiring as well as acquired company's perspectives. we will explore possible best practice solutions that can help other ux professionals facing similar challenges.
cross currents: water scarcity and sustainable chi. growing awareness of the threats posed by global freshwater shortages coupled with increased interest in environmental sustainability among chi researchers make water management a ripe area for new chi applications. this paper presents a qualitative study of practices and attitudes in a water-stressed region of the united states. we describe water conservation as a culturally-situated activity influenced by a variety of social factors, and show "sustainability" to be a complicated concept rife with competing, often incompatible interpretations and prescriptions. we discuss implications for designing interfaces that encourage personal conservation, and identify environmental policy making as an area ripe for new chi activity. finally, we suggest that sustainability has the potential to move from the periphery of chi research and become a galvanizing force for the community at large.
public issues on projected user interface. what will happen when pocket projectors become mainstream personal display channels? what will be affected when numerous projections intrude our living space without proper control? today's technology in projection has promised a big screen viewing experience from mobile devices, pushing us toward a truly ubiquitous display environment. but, is our society prepared for the next projection-generation? we argue that the projected user interface (pui) will introduce new problems both in environmental and social aspects which are seldom been explored. this paper explores our rights to project and be projected in public space. can we project on human body without asking for permission? can we refuse to be projected? can projection pollute the environment and influence the people therein? this paper proposes several issues about people's rights on projection, and provide discussions on possible solutions.
how do users interact with a pet-robot and a humanoid. in this paper, we compare users' interaction with the humanoid robot asimo and the dog-shaped robot aibo. we conducted a user study in which the participants had to teach object names and simple commands and give feedback to either aibo or asimo. we did not find significant differences in the users' evaluation of both robots and in the way commands were given to the two different robots. however, the way of giving positive and negative feedback differed significantly: we found that for the pet-robot aibo users tend to give reward in a similar way as giving reward to a real dog by touching it and commenting on its performance by uttering feedback like "well done" or "that was right". for the humanoid asimo, users did not use touch as a reward and rather used personal expressions like "thank you" to give positive feedback to the robot.
sxratch for metasaxophone. sxratch (2006) is a musical composition and interactive performance work created for the metasaxophone, an augmented instrument invented and built by the author in 1999. the metasaxophone is one of the earliest augmented instruments still in regular use today. the piece uses the instrument interface to control interactive computer sound software and robots.
trouble-spotting photoshows: capturing everyday hci experiences. trouble-spotting is a newly-invented video method for capturing everyday hci experiences. the method borrows qualities from scenarios and photo elicitation, allowing images and narration to be captured, appropriated, and post-processed into a narrated sequence of photographs, called a photoshow. in a pilot project which focused on four participants' problematic experiences with business processes, participants created four trouble-spotting photoshows, varying in length from 33 seconds to 13:16 minutes, containing useful and actionable firsthand accounts. in this paper, trouble-spotting is introduced along with insights gained from the pilot project and directions for future work.
vote-o-graph: a dishonest touchscreen voting system. we present vote-o-graph, an experimental touchscreen voting system designed to simulate reported interface issues in existing electronic voting systems. touchscreen miscalibration and the application of relative touch coordinates in anonymity-preserving user interface event logs are discussed.
personal, public: using diy to explore citizen-led efforts in urban computing. as communities develop technological literacy and explore how technology can impact their lives, the future of urban computing will come from grass-roots initiatives in addition to traditional top-down urban planning. to this end, we aim to engage the do-it- yourself (diy) community in exploring how individuals can add technology to their communities. as design probes into this space, we have built prototype devices around off-the-shelf technology, open-ended interactions and simple engineering techniques familiar to the diy community. through evolving these devices with both the technical diy community and pittsburgh's local communities, we hope to spark citizen-led efforts in bringing novel applications of computing to our communities.
wellness informatics: towards a definition and grand challenges. the last decade has seen a large explosion of health-related human centered computing research and practice focused on wellness (e.g., good nutrition and exercise promotion) with the intention of helping people avoid needing medical care. and while health informatics may appear to be the obvious home for these activities, it is a discipline that has focused on the design, development, and evaluation of systems to process healthcare data and through that aid in patient treatment. given the ubiquity of wellness systems we think its time to create a wellness informatics community. the goal of the workshop is to identify the themes and grand challenges for designing and evaluating information and communications technologies (icts) that help people stay well.
contextual user experience: how to reflect it in interaction designs? user experience is highly influenced and even changed by the context in which it occurs. in this sig session we want to discuss how specific contexts influence various aspects of user experience. so far, both concepts "user experience" and "context" have been discussed a lot to various extent and in different dimensions. with this sig, we aim to bring both concepts together, highlighting the differences arising from the consideration of different specific contexts and their relevant user experience factors. thus, we reach a more comprehensive understanding of "contextual user experience", which opens up different roads for research and challenges the hci community in all design and development phases. we will discuss user experience as focal point of user interface and interaction design bound to specific situational cases.
case study: designing an advanced visualization system for geological core drilling expeditions. we present the design and process of an interactive high-resolution visualization system for diverse and distributed real-world geological core drilling expeditions. the high domain knowledge barrier makes it difficult for a person who is outside this field to imagine the user experience, and the globally distributed core drilling community imposes more design constraints in space and time. in addition to activities proposed in prior literatures, we used the "immersive empathic design" approach of having a computer scientist trained as a junior core technician. through in-situ observation and interview evaluations from on-going expeditions, we present the system and the lesson learned in the process. it makes the best use of precious co-located opportunities. it allows the developer to build up domain knowledge efficiently. it establishes a trust relationship between the developer and scientists. the system designed through this approach formed a sustainable foundation that was adapted in the following design iterations. this process allows the software developer to experience authentic user activities. the designed system is innovative and helps scientists solving real-world problems. this approach can be a useful example to hci practitioners who work with potential users or communities that share similar properties.
cogknow day navigator: the system in daily life. in this project people with dementia and their carers were asked to describe their problems in daily life. with their input integrated solutions for people with dementia were developed. the aim was to develop solutions that help ageing people with early dementia to experience greater autonomy and feelings of empowerment, and to enjoy an enhanced quality of life. this movie shows the solutions that were developed during the project.
does underlining links help or hurt? two types of link treatments, underlined or non-underlined, were investigated in the context of three web pages. over 1,000 participants completed tasks for which the answers were found either on the pages or by clicking a link. task accuracy, speed, and ratings were collected in an online study. conflicting findings suggest that primarily navigational pages should use underlined links, while informational pages should not.
laugh enhancer using laugh track synchronized with the user's laugh motion. in television shows, we are familiar with the sound of artificial laughter, the so called "canned laughter" or "laugh track". it generally has an enhancing effect on the viewer's desire to laugh. however, if the sound is played when the user dislikes the content, it works negatively. to cope with this problem, we propose a system that produces the laugh track synchronized with the user's desire to laugh. we use a use a myoelectric signal from the diaphragmatic muscle to detect an initial laugh, and dolls around the user to produce the laugh sound. we speculated that although the initial laugh trigger from the user is necessary, the system can still effectively enhance the laugh activity, and even affect the subjective quality of the contents.
interaction design in the university: designing disciplinary interactions. interaction design (id) as a field emerged in the late 1990s with roots in both the hci and design communities. we ask whether the 'interdisciplinary' agenda of the 3rd paradigm of hci can be accommodated in the traditional disciplined university. an alternate model of 'interdisciplinarity' offers one way forward, but calls for clarity on the question of what interaction design aspires to be. we offer the notion of 'disciplined transdisciplinarity' as an exciting and perhaps necessary way of solving the complex problems that id researchers face, and illustrate this with examples drawn from the area of emotional design and assessment. our bridge between 3rd paradigm, knowledge production and what we are calling 'disciplined transdisciplinary' yields insights into the path toward institutionalizing and legitimating research on id and academic careers in this field in the university.
using metaphors to create a natural user interface for microsoft surface. creating a new model of human computer interaction is not straightforward. only a handful of such models have been commercially successful. those that have, such as the graphical user interface (gui), can provide valuable lessons. when we were challenged to develop a new natural user interface design for microsoft surface, we drew from these lessons and from modern user research techniques. a prominent starting point resulting from this was using metaphors to develop the new user interface. we used metaphors for two reasons: to create a user interface world that was understandable and predictable for our users, and to guide the design team in creating the detailed user interface design. we continued this practice in the user research: we focused on which metaphors worked best in the studies, and learned if users understood the metaphors we were using and which metaphor they preferred. this case study describes the process we followed, and the lessons we learned from this.
exploring reactive access control. as users store and share more digital content at home, effective access control becomes increasingly important. one promising mechanism for helping non-expert users create accurate access policies is reactive policy creation, in which users can update their policy dynamically in response to access requests that cannot otherwise succeed. an earlier study suggested that reactive policy creation may be a good fit for file access control at home. to test this theory, we designed and piloted an experience sampling study in which participants used a simulated reactive access control system for a week. preliminary results suggest a neutral to positive response to using this kind of system and indicate that reactive policy creation may help meet users' need for dynamic, contextual policy decisions.
hands free mouse: comparative study on mouse clicks controlled by humming. in this paper we present a novel method of simulating mouse clicks while the cursor is navigated by head movements tracked by webcam. our method is based on simple hummed voice commands. it is fast, language independent and provides full control of common mouse buttons. our method was compared with other three different methods in an experiment that proved its efficiency by means of task duration.
mobile questionnaires for user experience evaluation. as user experience studies move from laboratories to mobile context, we need tools for collecting data in natural settings. based on the results from a pilot study, we present early guidelines for designing mobile questionnaires to be filled in on handheld, palm-sized mobile devices. we found that special attention needs to be paid to the clarity and simplicity of the structure, layout and questionnaire content, including questions, visual icons, items and scales. in addition to the requirements set by the screen size, also data entry method, interaction style and mobile context related issues need to be taken into account when designing questionnaires for mobile devices.
maintaining levels of activity using a haptic personal training application. this paper describes the development of a novel mobile phone-based application designed to monitor the walking habits of older adults. haptic cues integrated within the prototype, are designed to inform an individual of changes which should be made to maintain a prescribed level of activity. a pilot study was conducted with fifteen older adults walking at varying speeds, both with and without the presence of assistive haptic feedback from the prototype. the results confirm that more steps were taken when haptic feedback was provided while walking at normal and fast paces. however, results also indicate that further refinements would be needed to improve the identification of haptic cues while individuals are in motion.
'steps': walking on the music, moving with light breathing. recently calm technology has been widely applied. many cases help to enhance social intimacy among close people. particularly, the area of family members has opportunities to support feeling of connectedness. we aim to investigate of implication through case study of calm technology to support social interaction. we suggested a mutual communication system; steps, it supports emotional communion in short time separation. it consists of an attachable device for parents and shoes for children. it helps remote and non-verbal communication in a shopping context. we achieved to solve the worry of safety and fear, curiosity issues by sharing their steps. it is also sublimated from daily activities to pleasurable interaction. it suggested a possibility to extend the application of calm technology.
effects of cognitive aging on credibility assessment of online health information. results from a study comparing how different web contents and features influence younger and older adults' credibility assessment are reported. results were in general consistent with the elaboration likelihood model (elm) of persuasive communication. it was found that cognitive aging differentially influences the processing of central arguments and peripheral cues (web features such as layouts, third-party endorsement). specifically, older adults were in general worse at distinguishing between strong and weak arguments, and this effect was moderated by cognitive abilities and motivation for cognition. results will be useful for informing designs that facilitate credibility assessment of health information for older adults.
opportunities for computing to support healthy sleep behavior. getting the right amount of quality sleep is one of the key aspects of good health, along with a healthy diet and regular exercise. we conducted a literature review and formative study aimed at uncovering the opportunities for technology to support healthy sleep behaviors. we present the results of interviews with sleep experts, a large survey, and interviews with potential users that indicate what people would find practical and useful for sleep. we identified a number of functional and non-functional requirements for technology for sleep. we explored three possible technology ideas for healthy sleep behaviors: a sleep tracking tool, game to promote sleep, and sleep condition assessment tool.
buddy bearings: a person-to-person navigation system. this paper proposes a mobile application to facilitate the meeting of people in unmarked spaces. we report on the concept, aspects of the work-in-progress implementation and future steps.
constant connectivity, selective participation: mobile-social interaction of students and faculty. beyond voice and textual communication, by enabling ubiquitous online connectivity and changing mediated social interaction. we report the results of a study of the mobile-social practices of students who use such devices, and the ways in which hierarchical relationships between students and professors were affected by the use of smart-mobile devices. the common premise is that because such devices enable continuous interaction, students are constantly using social networking and communication applications on the go, across different types of relationships. our study shows that in hierarchy-based interaction mobile-social communication is more limited than could be expected. social norms and usability issues both played a part in shaping students' mobile-social practices, resulting in "selective participation" - as students carefully crafted their mobile interaction to maintain hierarchical distance.
scaffolding science inquiry in museums with zydeco. one of the educational goals in science is to not only learn content but also to learn the scientific process. while there is a range of settings for this, such as classrooms and museums, they are not always well connected in educationally viable ways. we are designing zydeco to bridge the classroom and museum environment and address the following goals: (1) to scaffold science inquiry in a mobile context and (2) to facilitate collaboration among peers. in this paper we will be focusing on the mobile design of zydeco, which will scaffold structured investigation, data collection and analysis while students are in the museum.
zoozbeat: mobile music recreation. zoozbeat is a gesture-based music recreation studio. it is designed to provide users with expressive and creative access to music making on the go. zoozbeat users can compose user-generated songs based on generic beats in different styles or remix and modify commercially licensed songs. to play notes or trigger musical loops, players can shake the phone or tap the screen. users can also record voice or other audio input into their songs and utilize tilt and shake movements to manipulate and share the music in a group. design goals of the project focused on creating intuitive metaphors for mobile music making and maintaining a balance between control and ease-of-use.
world-wide access to geospatial data by pointing through the earth. traditional augmented reality ui views are restricted to the visible surroundings around the user. in this paper we present a concept that enables viewing and accessing geospatial data from all around the earth, by pointing with the device towards a physical location. we describe a prototype of the concept and share the results of the first user experience study conducted with the prototype. we also discuss our future research directions.
next generation of hci and education: workshop on ui technologies and educational pedagogy. given the exponential growth of interactive whiteboards in classrooms around the world, and the recent emergence of multi-touch tables, tangible computing devices and mobile devices, there has been a need to explore how next generation hci will impact education in the future. educators are depending on the interaction communities to deliver technologies that will improve/adapt learning to an ever-changing world. in addition to novel ui concepts, the hci community needs to examine how these concepts can be matched to contemporary paradigms in educational pedagogy. the classroom is a challenging environment for evaluation, thus new interaction techniques need to be established to prove the value of new hci interactions in the educational space. this workshop provides a forum to discuss key hci issues facing next generation education ranging from whole class interactive whiteboards, small group interactive multi-touch tables, and individual personal response systems in the classroom.
sensing human activities with resonant tuning. designing new interactive experiences requires effective methods for sensing human activities. in this paper, we propose new sensor architecture based on tracking changes in the resonant frequency of objects with which users interact.
emotions experienced by families living at a distance. this paper describes some of the results of a probe study where members of three-generational families, where at least one person is geographically separated from the others, talk about their emotional experiences. the method for eliciting this information is briefly described along with some of the themes identified in a grounded theory analysis. these include: sharing the moment with pride; reassurance with regard to intergenerational obligations; comfort and consolation from yearning; and little time to give comfort to one another.
social and spatial interactions: shared co-located mobile phone use. this paper outlines the design of the social and spatial interactions platform. the design of the platform was inspired by observing people's pervasive use of mobile technologies. the platform extends the current individual use of these devices to support shared co-located interactions with mobile phones. people are able to engage in playful social interactions on any flat surface by using devices fitted with wireless sensors that detect their current location with respect to each other.
fit and finish using a bug tracking system: challenges and recommendations. this article shares practical lessons for using a bug management tool to manage user interface fit and finish process for a software product. it describes common challenges and provides recommendations for processes that will lead to enhanced product quality.
examining appropriation, re-use, and maintenance for sustainability. within the past few years, the field of hci has increasingly addressed the issue of environmental sustainability, primarily identifying the challenges and developing an agenda for designing for sustainability. yet, the most difficult task remains, how do we develop realistic solutions when the digital ethos is based upon short-lived computing products that come and go at rapid pace. by examining appropriation, re-use, and maintenance practices, this workshop aims to identify sustainable interaction design challenges and directions in re-utilizing used or obsolete computing products for prolonged use.
special interest group for the chi 2010 management community. this sig will provide an opportunity for those interested in the relationship between management and hci to explore this subject and the ongoing development of the management community at chi conferences and beyond.
selective function of speaker gaze before and during questions: towards developing museum guide robots. this paper presents a method of selecting the answerer from audiences for a museum guide robot. first, we observed and videotaped scenes when a human guide asks visitors questions in a gallery talk to engage visitors. based on the interaction analysis, we have found that the human guide selects the appropriate answerer by distributing his/her gaze towards visitors and observing visitors' gaze responses during the pre-question phase. then, we performed the experiments that a robot distributed its gaze towards visitors to select an answerer and analyzed visitors' responses. from the experiments, we have found that the visitors who are asked questions by the robot feel embarrassed when they have no prior knowledge about the questions and the visitor's gaze before and during the question play an important role to avoid being asked questions. based on these findings we have developed a function for a guide robot to select the answerer by observing visitors' gaze responses.
event maps: a collaborative calendaring system for navigating large-scale events. event maps is a novel, rich and interactive web-based system targeted at improving the experience of attending and organizing large, multi-track conferences. through its zoomable tabular timeline, users can navigate the conference schedule, seamlessly moving between global and local views. through a compact decoration widget named active corners, event maps enables contextual asynchronous collaboration before, during, and after the conference. organizers can easily create or import conference schedules via a backend interface, and also use the provided analytic toolkits to get insights from visiting patterns and statistics.
edits & credits: exploring integration and attribution in online creative collaboration. attribution allows online reputations to be formed and motivates many contributions to online creative collaboration. yet, we know little about attribution practices in online creative collaboration and the technologies that shape them. this paper describes a study of online collaborative animation projects, focused on the practices surrounding integration and attribution. we found that both tasks are closely related and often completed by a single person, a process we call "cr-editing." we also identify frustrations with existing practices and systems and propose design considerations for alleviating them. our findings offer insights into the growing space of online remixing, mashups, and creativity.
computational objects and expressive forms: a design exploration. we suggest the concept of expressive forms as a rising design theme to explore aesthetics of computational objects. the theme, exemplified in our design exploration, attempts to synthesize a concept-driven design process and exploratory engagement with new forms and materials available to computational objects. we report the detailed process of designing the soft-spiky mouse including prototyping and a pilot user study, leading to a discussion about the experiential qualities and design implications of expressive forms for research on aesthetic interaction.
towards predicting web searcher gaze position from mouse movements. a key problem in information retrieval is inferring the searcher's interest in the results, which can be used for implicit feedback, query suggestion, and result ranking and summarization. one important indicator of searcher interest is gaze position - that is, the results or the terms in a result listing where a searcher concentrates her attention. capturing this information normally requires eye tracking equipment, which until now has limited the use of gaze-based feedback to the laboratory. while previous research has reported a correlation between mouse movement and gaze position, we are not aware of previous work on automatically inferring searcher's gaze position from mouse movement or similar interface interactions. in this paper, we report the first results on automatically inferring whether the searcher's gaze position is coordinated with the mouse position - a crucial step towards predicting the searcher gaze position from the computer mouse movements.
service users' views of a mainstream telecare product: the personal trigger. telecare is a term that covers a range of products and services that use new technology to enable people to live with greater independence and safety in their own homes. this paper considers the need for design development of a mainstream telecare product called a personal trigger, which provides a means of summoning assistance when help is needed. it is provided as part of a community alarm service and should be worn at all times for continuous protection. the discussion is based on key findings from a survey of 1,324 service users in north east scotland with a 60% response rate. telecare technology is often unattractive because the emphasis is on producing a functional, rather than a desirable product. we argue that the telecare industry needs to consider the social and emotional aspects of design as well as function, even though many of today's service users find the current design acceptable. the survey findings can be incorporated into future product designs.
first-person cooking: a dual-perspective interactive kitchen counter. hobby chefs have various ways to learn cooking-paper recipes or cooking shows, for example. however, information in paper recipes may require prior experience to be understood and a television show cannot adapt to a viewer's individual speed. based on our findings on cooking habits, we are developing personalchef to unravel the complexity of recipes in order to increase users' confidence and fun when preparing an unknown recipe. personalchef is a multi-display, dual-perspective, interactive kitchen counter to support users in-situ while cooking and to teach them about food preparation. in addition to an interactive "personal chef" on a screen behind the stove, the user can retrieve as much or as little information as needed/wanted using a display embedded in the kitchen counter.
evaluating the social acceptability of multimodal mobile interactions. multimodal mobile interfaces require users to adopt new and possibly strange behaviors in public places. it is important to design these interfaces to account for the social restrictions of public settings. however, past research in multimodal interaction has primarily focused on issues of sensing and recognition rather than the investigation of user opinions and social factors that influence the acceptance of multimodal interfaces. this research examines the factors affecting social acceptability of multimodal interactions, beginning with gesture-based interfaces. this work includes a survey and an on-the-street user study that examine how users determined which gestures were acceptable. future work seeks to examine other modalities, in order to create guidelines for socially acceptable designs and a methodology for investigating social acceptability.
is a friend a friend?: investigating the structure of friendship networks in virtual worlds. in this paper, we examine online friendships at a network level. we focus on three structural signatures: network size, balance (triangles), and age homophily in the friendship ego-networks of 30 users of the virtual world second life. in relation to previous findings from studies of offline friendship networks, our results reveal that online networks are similar in age-homophily, but significantly different in size and balance.
comparing awareness and distraction between desktop and peripheral-vision displays. we tested a peripheral-vision display to provide users with awareness of others and their level of interest in interaction in an experiment where participants had to be aware of a simulated workgroup during a visually-demanding primary task. participants gathered more information from the peripheral-vision display although they attended to it significantly less often (less than half the number of glances, and less than a third of the total time spent looking). our results suggest that the peripheral-vision space around the user is a valuable resource for awareness and communication systems.
remote interaction for 3d manipulation. in this paper, we present a two-handed 3d interaction approach for immersive virtual reality applications on a large vertical display. the proposed interaction scheme is based on hybrid motion sensing technology that tracks the 3d position and orientation of multiple handheld devices. more specifically, the devices have embedded ultrasonic and inertial sensors to accurately identify their position and attitude in the air. the interaction architecture is designed for pointing and object manipulation tasks. since the sensor system guarantees 3d spatial information only, we develop an algorithm to exactly track the position of interest produced by the pointing task. for the object manipulation, we have carefully assigned one-handed and two-handed interaction schemes for each task. one-handed interaction includes selection and translation while rotation and scaling are assigned for the two-handed interaction. by combining one-handed and two-handed interactions, we believe that the presented system provide users with more intuitive and natural interaction for 3d object manipulation. the feasibility and validity of the proposed method are validated through user tests.
layered surveillance. artist annabel manning explores the world of immigration and identity, and explores imagery related to border crossings and surveillance. computer scientist celine latulipe explores embodied, collaborative interaction. the intersection of these two worlds leads to research in embodied collaborative interaction and an interactive art exhibit in which participants can explore both static images through interactive layers, and moving video through interactive surveillance lenses. participants can explore alone or with others, using gyroscopic mice to control different aspects of the artwork. the participants are led, through interaction, to contemplate the (in)visibility of the immigrant and the agency of surveillance.
snag: social networking games to facilitate interaction. because professional relationships and a sense of community are so important for career mobility and satisfaction, it is important to foster and support these relationships early. however, research has shown that women and underrepresented minorities approach these relationships differently and may need help to develop networking skills. to combat both of these problems, we present snag, (social networking and games), a suite of mobile and internet games to facilitate social networking within a professional community. we present snag'em, a game that helps conference attendees build meet one another and track their new contacts.
end user software engineering: chi 2010 special interest group meeting. end users create software whenever they create, for instance, interactive web pages, games, educational simulations, or spreadsheets. researchers are working to bring the benefits of rigorous software engineering methodologies to these end users to try to make their software more reliable. unfortunately, errors are pervasive in end-user software, and the resulting impact is sometimes enormous. this special interest group meeting will bring together the community of researchers who are addressing this topic with the companies that are creating and using end-user programming tools.
critical dialogue: interaction, experience and cultural theory. although topics such as fun, enjoyment, aesthetics, and experience are relatively new in hci, long traditions of scholarship in the humanities and social sciences have examined them. some have already been expressed in the appropriation of conceptualizations of experience in hci research and practice. there is also a small but fast growing body of work in hci seeking to approach these topics from the perspective of cultural and critical theory. in the history of ideas, experience and critical theory have not always made good bedfellows, sometimes complementing each other, sometimes resisting each other. this workshop will explore the ways in which hci can benefit from a constructive dialogue between critical theory and experience in questions of design and evaluation.
behind the scenes of google maps navigation: enabling actionable user feedback at scale. this case study describes an android-based feedback mechanism, created to gain structured input on prototypes of google maps navigation, a mobile gps navigation system, during real-world usage. we note the challenges faced, common to many mobile projects, and how we addressed them. we describe the user flow for submitting feedback; the resulting feedback report from the team's perspective; our triaging process for the high volume of incoming data; and the results & benefits gleaned from using this system. learnings and recommendations are provided, to aid mobile teams who may be interested in developing a similar system for their working prototype, particularly if real-world testing is required.
cookie confusion: do browser interfaces undermine understanding? we performed a series of in-depth qualitative interviews with 14 subjects recruited to discuss internet advertising. participants held a wide range of views ranging from enthusiasm about ads that inform them of new products, to resignation that ads are "a fact of life," to resentment of ads that they find "insulting." we discovered that many participants have a poor understanding of how internet advertising works, do not understand cookies, and mistakenly believe there are legal protections barring companies from sharing information they collect online. we found that participants have substantial confusion about the results of the actions they take within their browsers, and do not understand the technology they work with now. the user interface for cookie management in popular browsers may be contributing to confusion.
exploring iterative and parallel human computation processes. mechanical turk (mturk) is an increasingly popular web service for paying people small rewards to do human computation tasks. current uses of mturk typically post independent parallel tasks. this research explores an alternative iterative paradigm, in which workers build on each other's work. we run a couple of experiments comparing the efficacy of this paradigm in two different problem domains: image description writing, and brainstorming company names.
designing for children: a fear therapy tool. software for young children requires specific attention to a variety of details that range from the used metaphors, interaction modalities and even used language. these aspects gain further relevance when creating software for critical activities such as fear therapy, requiring specific approaches during the design process right from the start. this paper describes the design process of a set of software solutions for young children's fear therapy using mobile devices. we address the used techniques, procedures and describe the resulting prototypes. initial evaluation results and future work plans are also presented.
adaptive mouse: a deformable computer mouse achieving form-function synchronization. in this paper, we implement a computer mouse for demonstrating the idea of form-function synchronization by embedding deformation sensing modules consisting of deformable foam and hall-effect sensors. due to its automatic sensing, recognizing and actuating mechanisms actively responding to users' diverse gestures, we have chosen to name it adaptive mouse. working with adaptive mouse, all users have to do is to hold it with preferred hand gestures, then through the use of their fore and middle fingers the correct button functions will intuitively be triggered. users can also freely move the mouse and always get accurate cursor feedbacks. this "intuitive holds then clicks" action creates sense of "magic", and the mouse shape with minimum visual clues not only lowers mental loads but also achieves the goal of simplicity design.
building common ground and reciprocity through social network games. social network games (sng) are an extremely popular and rapidly growing application of social network sites (sns). but are sngs really social? a survey based on a social cognitive theory approach to uses and gratifications revealed that people are motivated to play the game to create common ground, reciprocate, cope, and pass time. people play sngs to create common ground for future social interaction rather than seeking direct social interaction in the game. customization was strongly correlated with social motivations; in particular, use of avatar customization was different from use of space customization. reciprocity was facilitated more by the design of the game than social motives.
auditory menus are not just spoken visual menus: a case study of "unavailable" menu items. auditory menus can supplement or replace visual menus to enhance usability and accessibility. despite the rapid increase of research on auditory displays, more is still needed to optimize the auditory-specific aspects of these implementations. in particular, there are several menu attributes and features that are often displayed visually, but that are not or poorly conveyed in the auditory version of the menu. here, we report on two studies aimed at determining how best to render the important concept of an unavailable menu item. in study 1, 23 undergraduates navigated a microsoft word-like auditory menu with a mix of available and unavailable items. for unavailable items, using whisper was favored over attenuated voice or saying "unavailable". in study 2, 26 undergraduates navigated a novel auditory menu. with practice, whispering unavailable items was more effective than skipping unavailable items. results are discussed in terms of acoustic theory and cognitive menu selection theory.
building interpretable discussions: for effective public engagement. shifts in the culture of civic engagement, technologies and practices surrounding social media, and pressure from political leaders have ignited a movement amongst gov't agencies to extend their efforts for obtaining input on public issues. these projects face serious challenges related to scale of participation and political capture, though collaborative efforts elsewhere suggest we may be able to support interactions amongst large numbers of people. instead of emphasizing the exchange of individual messages and voting, i propose that systems should be designed to support the cooperative production of discussions.
modeling the effect of habituation on banner blindness as a function of repetition and search type: gap analysis for future work. this paper provides a theoretical foundation to guide future work in online marketing research. specifically, we target the phenomenon of banner blindness that prevents users from noticing online advertisements; thus, leading to a steady decline in revenues for online publishers and service providers. while habituation was identified as the main cause of banner blindness, there are competing behavioral models that predict different orienting response patterns as a function of repetition. this work bridges the theoretical gap between models in the marketing and ergonomics domains while illuminating an additional factor that has yet to be studied in this context -- search type. finally, we outline future research steps to validate the user's response to online advertisements with an emphasis on a battery of physiological measurements.
investigating user account control practices. non-administrator user accounts and the user account control (uac) approach of windows vista are two practical solutions to limit the damage of malware infection. uac in windows vista supports usage of lower privilege accounts; a uac prompt allows users to raise their privileges when required. we conducted a user study and contextual interviews to understand the motives and challenges participants face when using different user accounts and the uac approach. most participants were not aware of or motivated to employ low-privileged accounts. moreover, most did not understand or carefully consider the prompts.
hci at the end of life: understanding death, dying, and the digital. death and our experience of it is a fundamental aspect of life and consequently every human culture has developed practices associated with responding to, signifying, and dealing with its implications. as our technology pervades our cultures, we find that the digital is increasingly intersecting with these practices. this raises issues which have rarely been conceptualized or articulated in the hci and cscw communities. it is increasingly important to design "thanatosensitive" technologies which support death-centric practices such as collaborative acts of remembrance, bequeathing of digital data, or group reflection on the digital residua of a life. this workshop will bring together participants interested in such technologies and their implications. potential topics include, but are not limited to: devices for reflection and meaning-making across multiple lifespans; interdisciplinary practices surrounding mortality, dying, and death; technology heirlooms; digital rights management; and methodological approaches to researching end-of-life technology issues.
improved window switching interfaces. in this research, we explore ways of improving window switching interfaces. empirical studies reveal how people currently organise and switch between windows. these characteristics inform our new design: spatially consistent thumbnails zones (scotz).
ontology models for interaction design: case study of online support. we report a case study for online self-support, which illustrates an advanced form of work modeling based on ontology technology. this new method enables a much earlier understanding of the design problem and promotes interdisciplinary design collaboration. a functional prototype was implemented for user testing and showed significant improvement in content discovery.
recognizing shapes and gestures using sound as feedback. the main goal of this research work is to show the possibility of using sound feedback techniques to recognize shapes and gestures. the system is based on the idea of relating spatial representations to sound. the shapes are predefined and the user has no access to any visual information. the user interacts with the system using a universal pointer device, as a mouse or a pen tablet, or the touch screen of a mobile device. while exploring the space using the pointer device, sound is generated, which pitch and intensity vary according to a strategy. sounds are related to spatial representation, so the user has a sound perception of shapes and gestures. they can be easily followed with the pointer device, using the sound as only reference.
exploring mobile technologies for the urban homeless. my research examines the practical and social impact of technology on the urban homeless. to accomplish this, i have conducted interviews with the homeless to understand how technology-from mobile phones to bus passes-affects their lives. i have also conducted ethnographic fieldwork at care providers to understand how technology figures into the provision of care for the homeless. these formative studies have motivated the design of a set of information sharing services that aggregate information available in the community and provide it to the homeless via mobile phones. i will deploy this system to diverse set of homeless individuals to better understand how such technologies fit within the social and economic constraints of the homeless community. i expect my research to result in theoretical contributions and guidelines for designing for uncommon users, like the homeless.
biotisch: the interactive molecular biology lab bench. in a molecular biology lab, scientists often need to execute strictly defined sequences of operations, typically mixing specific amounts of reagents. the exact steps require information from various sources, like manuals, websites and own notes. direct access to a computer at the bench would be highly desirable but is rarely implemented, as computers do not fit well into a wet lab environment. in this paper, we present biotisch, an interactive workbench for molecular biology laboratories. we show a prototypical setup of an interactive table which provides a sterile user interface for access to existing documentation and for common tasks such as unit conversions. the example illustrates that interactive tables blend very well into a modern biological laboratory and could improve access and exchange of information in this environment.
measuring user experience of websites: think aloud protocols and an emotion word prompt list. to develop simple yet effective methods for eliciting user experience of websites and other interactive technologies, we explored the use of two techniques: an emotional think aloud protocol and an emotion word prompt list (ewpl). a study of four websites with 16 participants found that a retrospective emotional think aloud protocol produced significantly more emotion words than an equivalent concurrent protocol; plus, with on average 40 emotion words per website, it appears an effective technique for eliciting users emotional reactions to websites. surprisingly, the use of the ewpl did not produce more emotion words per website, but may still help users overcome their difficulties in expressing emotional reactions to websites when unprompted. further research will explore the use of these methods with other interactive technologies.
pinch-the-sky dome: freehand multi-point interactions with immersive omni-directional data. pinch-the-sky dome is a large immersive installation where several users can interact simultaneously with omni-directional data inside of a tilted geodesic dome. our system consists of an omni-directional projector-camera unit in the center of the dome. the projector is able to project an image spanning the entire 360 degrees and a camera is used to track freehand gestures for navigation of the content. the interactive demos include: 1) the exploration of the astronomical data provided by world wide telescope, 2) social networking 3d graph visualizations, 3) immersive panoramic images, and 4) 360 degree video conferencing. we combine speech commands with freehand pinch gestures to provide a highly immersive and interactive experience to several users inside the dome, with a very wide field of view for each user.
open columns: a carbon dioxide (co2) responsive architecture. this paper describes the use of composite urethane elastomers for constructing responsive structures at an architectural scale. it explains the underlying material research and design criteria for constructing deployable columns that are responsive to carbon dioxide (co2) emissions and are used to reconfigure and pattern the space of inhabitation.
the generative visual renku project: integrating multimedia semantics, animation, and interface design. this paper presents generative visual renku (gvr), a new genre of visual interactive/generative art form inspired by japanese renku poetry and generative contemporary art. griot, a system for composing generative and interactive multimedia discourse, is used to semantically constrain generated output both visually and conceptually. gvr utilizes griot to implement constraints for visual composition, revealing new technical and aesthetic challenges. since modular animated graphical systems are ubiquitous in computing culture, ranging from avatars to guis, gvr works pose a contribution to a breadth of hci research and to the development of new theory and technology for integrating ai and the arts.
enhancing distributed corporate meetings with lightweight avatars. the difficulties remote participants of distributed meetings face are widely recognized. in this paper we describe the design of an avatar-based e-meeting support tool named olympus, which aims to ameliorate some of the challenges remote participants face in distributed meetings. olympus provides a customizable peripheral display on the bottom of existing e-meeting solutions. an initial observational study was conducted of the use of olympus in 6 meetings, three each of a status meeting and a presentation meeting. avatars fostered team bonding through social play during status meetings, while minimalist dots allowed focused attention during presentation meetings.
touch2annotate: generating better annotations with less human effort on multi-touch interfaces. annotation is essential for effective visual sense making. for multidimensional data, most existing annotation approaches require users to manually type notes to record the semantic meaning of their findings. they require high effort from multi-touch interface users since these users often experience low typing speeds and high typing errors. to lower the typing effort and improve the quality of the generated annotations, we propose a new approach that semi-automatically generates annotations with rich semantic meanings on multidimensional visualizations. a working prototype of this approach, named touch2annotate, has been implemented and used on a tabletop. we present a scenario of using touch2annotate to demonstrate its effectiveness.
improving the form factor of a wrist-based mobile gesture interface. we present the form factor design iteration process of the gesture watch, a wearable gesture interface that utilizes non-contact hand gestures to control mobile devices while non-visual feedback is provided from its tactile display. based on limitations discovered from a previous prototype, we identified three design challenges: wearability, mobility, and tactile perception. in addressing these challenges, we focus on three main parts affecting the form factor: the sensor housing, the strap, and the motor housing.
the effect of eco-driving system towards sustainable driving behavior. in this paper, we explore the use of an eco-driving system to see how the system promotes greener driving behavior. we conducted both an online survey (n=60) and a user test (n=14) to study the eco-driving system. based on participant responses, we found that the current eco-driving system shows minor benefits in gas mileage due to different driving behaviors and also increased task loads for our participants. therefore, we suggest a new research direction for the eco-driving system for further study.
who said what when?: capturing the important moments of a meeting. meeting information capturing paradigms such as pen and paper has been found to be tedious and distractive. this paper presents meeting essence ii, a mobile phone based, one screen meeting information capture system to address these issues. we also introduce a new social interaction centric recording paradigm, where events in the meeting are identified by meeting participants and are recorded, classified by time and person with a single screen touch. results from our pilot experiment shows that our system positively contributes to the quality of meeting reconstruction, while being minimally distractive to the meeting participants.
mediated crafts: digital practices around creative handwork. in this submission, i discuss my design research and fieldwork investigating mediated crafts' - digital practices around creative handwork. specifically, i study how creating and sharing digital information around knitting or crochet activity affects the social and material relationships enacted through craft. here i review my qualitative research on the role of digital resources in creative handwork and the iterative design of spyn, mobile phone software that associates digital records of the creative process' - captured through audio/visual media, text, and geographic data' - with physical locations on handmade fabric.
locked-out: investigating the effectiveness of system lockouts to reduce errors in routine tasks. while frustrating and innocuous in many settings, errors can have disastrous consequences for the use of safety critical systems and medical devices. this work-in-progress investigates the effectiveness of an enforced lockout period for reducing errors in a routine task. during the lockout period the user can look at, but not interact with the device interface for a period of 10 seconds before they resume the task after an interruption. results show that this lockout period can reduce sequence errors by up to 64%. identifying ways to reduce the disruptiveness of interruptions is important for hci research given that many devices are now used in settings where interruptions are commonplace.
facilitating meetings with playful feedback. effective group meetings are important for the productivity of corporations. various types of meeting facilitators have been developed over the past couple of years. we present a prototype that is unique because it captures both individual and group behaviors and provides real time playful feedback. the portable prototype includes a set of table-top microphones with an audio interface to a laptop pc, where audio data are processed and an avatar-based ui displays the shared state of individual and group behaviors during a meeting. the interface reveals not only level of participation, but also several other meaningful but harder to detect behaviors such as turn taking, interruptions, and group laughter. the presentation's design is deliberately playful to keep participants monitor, self-estimate and improve their meeting behavior.
tagliatelle: social tagging to encourage healthier eating. this paper describes the design and initial evaluation of tag-liatelle, a collaborative tagging application for encouraging healthier eating. users photograph their own meals and upload these photos to a website, where fellow users anonymously tag them for content. initial results suggest that tagging of food content is a popular activity. however, further work must be done to automate the extraction of valid nutritional information from the tags generated.
the mystique of numbers: belief in quantitative approaches to segmentation and persona development. quantitative market research and qualitative user-centered design research have long had an uneasy and complex relationship. a trend toward increasingly complex statistical segmentations and associated personas will once again increase the urgency of addressing paradigm differences to allow the two disciplines to collaborate effectively. we present an instructive case in which qualitative field research helped contribute to abandoning a "state of the art" quantitative user segmentation that was used in an attempt to unify both marketing and user experience planning around a shared model of users. this case exposes risks in quantitative segmentation research, common fallacies in the evolving practice of segmentation and use of personas, and the dangers of excessive deference to quantitative research generally.
beliv'10: beyond time and errors novel evaluation methods for information visualization. information visualization systems allow users to produce insights, innovations, and discoveries. evaluating such tools is a challenging task. current evaluation methods exhibit noticeable limitations and researchers in the area experience frustration with evaluation processes that are time consuming but often lead to unsatisfactory results. the goal of beliv'10 is to provide a venue for researchers to report and discuss the latest innovations in this area.
the elocuter: i must remind you we live in dada times. the elocuter is a sonification device that attaches via suction cup to a computer screen. it translates newspaper headlines about the global economic crisis into spoken words, composed of impossible sequences of allophones similar to a dada poem. the project references poetic experiments of the dada movement of the 1910/20s, specifically the play with language as a way to respond to a seemingly irrational political and cultural context. finally, this project can be placed in the history of combining human and machinic components into instruments for performance.
exploring cultural differences in information behavior applying psychophysiological methods. this ongoing exploratory study has two main goals: to compare information seeking behavior (1) across two cultures and (2) across the users' native and foreign languages. a secondary goal is the evaluation of the capability of psychophysiological data collection methods in the study of human-computer interaction (and especially the information interaction) experience. the applied physiological channels are heart period variability (hpv), skin conductance (sc), pupil size, and eye-tracking data. the first part of the series of experiments has been completed with us participants with a significant (non-heritage) knowledge of spanish. the second part will be performed in hungary, with hungarian participants with knowledge of english.
concept mapping in agile usability: a case study. in this paper we report on the experience of using our concept mapping approach on an agile software project to assess its fitness. participants used our novel concept mapping approach over a four week period during the development of a software tool for a local nonprofit agency. results indicate that our concept mapping approach has value as a visual tool in agile usability environments.
video microblogging: your 12 seconds of fame. microblogging is a recently popular phenomenon and with the increasing trend for video cameras to be built into mobile phones, a new type of microblogging has entered the arena of electronic communication: video microblogging. in this study we examine video microblogging, which is the broadcasting of short videos. a series of semi-structured interviews offers an understanding of why and how video microblogging is used and what the users post and broadcast.
connect 2 congress: visual analytics for civic oversight. strong representative democracies rely on educated, informed, and active citizenry to provide oversight of the government. we present connect 2 congress (c2c), a novel, high temporal-resolution and interactive visualization of legislative behavior. we present the results of focus group and domain expert interviews that demonstrate how different stakeholders use c2c for a variety of investigative activities. the evaluation provided evidence that users are able to support or reject claims made by candidates and conduct free-form, low-cost, exploratory analysis into the legislative behavior of representatives across time periods.
thermo-message: exploring the potential of heat as a modality of peripheral expression. peripheral expressions using various modalities are considered as possible alternative ways of delivering information in our communication. in this research, we aimed to explore how the thermal expression can be used in the interpersonal communication. based on the result of the focus group interview, we developed a pair of devices with which the users can exchange a "thermal message" each other. experience prototyping was conducted with the devices in the real daily life context of the users. we identifed the charateristics of thermal expression, and confirmed the potential of the thermal expression in interpersonal communication.
'castling rays' a decision support tool for uav-switching tasks. this project is a collaborative research effort of the israeli air force (iaf), synergy integration ltd. and ben-gurion university. it is directed to design and develop tools and display layouts to facilitate task switching and coordination among operators in multi-operator multi-uav (unmanned aerial vehicle) environments. all for the benefit of improving overall mission performance. in this paper we focus on one of the main tools that were developed - 'castling rays'. the 'castling rays' tool is a uav-switching decision aid, enabling operators to visually view which uav has the best view of 'their' target at any given moment. structured interviews with experienced operators strengthened the necessity and importance of this tool in reducing operators' workload and improving their situation awareness.
making policy decisions disappear into the user's workflow. complaints of security interfering with getting work done often arise when users are distracted from their tasks to make policy decisions. we have identified what is missing from earlier security interaction designs that leads to these interruptions. explicitly representing policy decisions in the user interface as items relevant to the application and providing application-specific controls for changing those policies has allowed us to reliably infer users' desired policy decisions from actions they take as they work. this paper describes the underlying principles and how they resulted in an interaction design that does not interfere with the user's work.
gbook: an e-book reader with physical document navigation techniques. in this paper, we present gbook, a prototype for a new style of e-book reader that uses flexible inputs and page orientation to simulate the properties of reading a bound printed book. this project takes into account some of the known methods that people use when reading books, to make page navigation correspond more to that of paper-based books. the underlying assumption is that doing so will improve the learnability of navigation, as well as the usability by allowing more casual methods of page navigation.
exploring surround haptics displays. in this paper we present the design and evaluation of a two dimensional haptics display intended to be used for enhancing experience for movies and rides. the display, haptics surface, utilizes an array of vibrators contacting the skin at discrete locations and creates static and dynamic haptic sensations derived from scenes and situations. for this regard, a set of haptic morphs are introduced that can be used as building blocks to create new sensations on the skin. a novel haptic sensation, haptic blur, is also introduced that gives an illusion of continuous motion across the skin using discrete vibrating points. a pilot study investigating the reliability of haptic blur along a two dimensional skin surface is presented along with conceptual discussion on future haptic feelings rendered through the haptics surface.
toward a computationally-enhanced acoustic grand piano. although the capabilities of electronic musical instruments have grown exponentially over the past decades, many performers continue to prefer acoustic instruments, perceiving them to be more expressive than their electronic counterparts. we seek to create a new application for computer music interfaces by augmenting, rather than replacing, acoustic instruments. starting with an acoustic grand piano, an optical keyboard scanner measures the continuous position of every key while electromagnetic actuators directly induce the strings to vibration. unlike the traditional piano, the performer is given the ability to continuously modulate the sound of each note, resulting in a new creative vocabulary. ongoing work explores the creation of intelligent mappings from sensed user input to acoustic control parameters which build on the existing musical intuition of trained pianists, creating a hybrid acoustic-electronic instrument that offers new expressive dimensions for human performers.
artex: artificial textures from every-day surfaces for touchscreens. the lack of tactile feedback available on touchscreen devices adversely affects their usability and forces the user to rely heavily on visual feedback. here we pro-pose texturing a touchscreen with virtual vibrotactile textures to support the user when browsing an interface non-visually. we demonstrate how convincing pre-recorded textures can be delivered using processed audio files generated through recorded audio from a contact microphone being dragged over everyday sur-faces. these textures are displayed through a vibrotactile device attached to the back of an htc hero phone varying the rate and amplitude of the texture with the user's finger speed on the screen. we then discuss our future work exploring the potential of this idea to allow browsing of information and widgets non-visually.
learning basic dance choreographies with different augmented feedback modalities. we plan to evaluate different kinds of augmented feedback (tactile, video, sound) for learning basic dance choreographies. therefore we develop a dance training system based on motion capturing technology. in this work we describe and put up for discussion its capabilities and our methodological approach.
how to bring hci research and practice closer together. this special interest group probes potential problems between hci researchers and the practitioners who are consumers of research, to explore the extent of the problems and propose possible solutions. it will start with the results of the chi 2010 workshop on the same topic, articulating factors that may render some of the research literature inaccessible or irrelevant to practitioners. when should hci researchers be concerned about the relevance of their work to practitioners? how should practitioners communicate their needs for research? participants will discuss these topics and others that both groups can use to help bridge the gap between research and practice in hci.
experience in social affective applications: methodologies and case study. new forms of social affective applications are emerging, bringing with them challenges in design and evaluation. we report on one such application, conveying well-being for both personal and group benefit, and consider why existing methodologies may not be suitable, before explaining and analyzing our proposed approach. we discuss our experience of using and writing about the methodology, in order to invite discussion about its suitability in particular, as well as the more general need for methodologies to examine experience and affect in social, connected situations. as these fields continue to interact, we hope that these discussions serve to aid in studying and learning from these types of application.
design to read: designing for people who do not read easily. many people do not read easily. they may have an impairment such as a visual problem. they may be reading in stressful conditions or poor light, or perhaps they are reading in a second language. is it possible to provide one consistent set of guidelines or approaches that will allow designers of electronic materials to meet all the apparently diverse needs of these people? or are there compromises to be made? if so, what are those compromises?
a method to get rich feedbacks from users in an interview for design concept decision. although participatory design methods such as co-creation and cultural probes are used in many forms of design practice, user involvement in the design concept decision phase is more difficult and rather rare. the aim of this research is to investigate a method that helps designers get rich feedbacks from users to help in making decisions on design concept directions. we present a method, called 'fuzzy & clear', which uses a level of clarity and concreteness when the concept directions are shown to users in group interviews or workshops. we also report on a design project case study to show how the method can be used and how the method impacts user feedback on a design project case study. the results show that the method helped develop diverse viewpoints and make a positive impact on getting more valuable user feedback. with this approach, designers and users can maintain a comple-mentary cooperation as co-creators.
whole body large wall display interfaces. this video demonstrates an application that uses a body-centric approach to support interaction with very large wall displays. the design is centered on a virtual body model that represents the users in the context of the workspace, relative to one another as well as to the display(s). this concept of body-centric interaction serves both as a design philosophy and an implementation approach and is both general and powerful. our approach is general because if the model is detailed enough, a broad range of interaction techniques can be implemented. it is powerful because it opens up an entire class of new interaction techniques: those that depend on properties of a users' body, such as arm or hand pointing direction, head direction, or body location or orientation. the video highlights some of the body-centric interaction techniques that we believe are of value based on how people use their bodies in the everyday world.
designing graphical interfaces for design rationale search & retrieval. design rationale (dr) explains why an artifact is designed the way it is, which is well recognized as critical information for designers in design reuse. the existing dr systems largely rely on human effort to capture dr which cannot discover dr from a large amount of archived design documents. therefore those systems have limited features in helping designers to explore dr information from a holistic view. our dr system focuses on discovering dr from archived documents (i.e. patent documents) and providing dr search and retrieval based on the proposed isal model. in this paper, we report our effort in designing graphical interfaces for our dr search and retrieval system, which provides interactive visualization of holistic view of drs from a large amount of patents and it enables search & navigation of dr from multiple aspects.
iphone as a physical activity measurement platform. iphone is emerging as a ubiquitous physical activity measurement platform due to its incorporated accelerometer sensor. the iphone's capacity to accurately measure physical activity has not been put to scrutiny up to now, despite claims from an increasing number of applications. this study examines ways to perform accurate physical activity measurements with the iphone, at various positions on the user's body. the study focuses on walking and running - the two most prevalent aerobic activities. for walking, a methodology has been developed that translates accelerometer values from peripheral body locations to equivalent readings on the waist and from there to metabolic units. for running, the limitation of iphone to perform accurate metabolic measurements is documented. the formulas and results in this paper can readily be used by developers to increase the accuracy of fitness applications and improve user experience.
usability and strength in click-based graphical passwords. click-based graphical passwords have attractive usability properties, such as cueing and good memorability. however, parameters such as image size and number of click-points in each password significantly affect their security. we investigated the usability of such a graphical password system when its parameters were adjusted to provide security equivalent to (or better than) that of text passwords. we found that manipulating different parameters resulted in similar usability. this suggests that the preferred method for adjusting security can be dictated by the constraints of devices and preferences of users. for example, mobile devices might use smaller image sizes and more click-points.
a multi-touch enabled steering wheel: exploring the design space. cars offer an increasing number of infotainment systems as well as comfort functions that can be controlled by the driver. with our research we investigate new interaction techniques that aim to make it easier to interact with these systems while driving. in contrast to the standard approach of combining all functions into hierarchical menus controlled by a multifunctional controller or a touch screen we suggest to utilize the space on the steering wheel as additional interaction surface. in this paper we show the design challenges that arise for multi-touch interaction on a steering wheel. in particular we investigate how to deal with input and output while driving and hence rotating the wheel. we describe the details of a functional prototype of a multi-touch steering wheel that is based on ftir and a projector, which was built to explore experimentally the user experience created. in an initial study with 12 participants we show that the approach has a general utility and that people can use gestures for controlling applications intuitively but have difficulties to imagine gestures to select applications.
real time eye movement identification protocol. this paper introduces a real time eye movement identification (remi) protocol designed to address challenges related to the implementation of the eye-gaze guided computer interfaces. the remi protocol provides the framework for 1) eye position data processing such as noise removal, smoothing, prediction and handling of invalid positional samples 2) real time eye movement identification into the basic eye movement types 3) mapping of the classified eye movement data to interface actions such as object selection.
mobile product customization. many companies are using the web to enable customers to individually customize their products that range from automobiles and bicycles to cds, cosmetics and shirts. in this paper we present a mobile application for product customization and production within a smart factory. this allows the ad hoc configuration of products at the point of sale (pos). we investigate human factors when customizing products while interacting with them. we focus on the concept of the mobile client that enables this ad hoc modification, but also present the production chain behind our product. we believe that this particular 3d interaction with a product and a mobile device help to improve the customer satisfaction as it allows for customizing a product in an easy and intuitive way. from a chi perspective an important aspect is that our mobile augmented reality interface can help to match the costumer's expectations with the final modified product and allows the most natural and intuitive interaction. as a use case of the system, we present the modification of a soap dispenser.
microblogging: what and how can we learn from it? microblogging, the act of broadcasting short, real-time messages, is a relatively new communication practice allowing people to share information they are less likely to express using existing technologies (e.g. email, phone, im or weblogs). we use microblogging as an umbrella term to include the posting of status updates to social network sites such as facebook, and message-exchange services like twitter, jaiku, and yammer. microblogging has become popular quickly, catching researchers' interests as both a means of public, social information exchange, and a medium for collaboration and communication in the work context. the goal of this workshop is to provide a forum for researchers and practitioners from academia and industry to exchange insights into microblogging as a communication practice in enterprises, academic and social settings. we aim to develop an agenda for what and how we can learn from and better study this phenomenon.
studying and tackling temporal challenges in mobile hci. in this paper, i present the idea of receptivity as a broader concept than interruptibility alongside empirical studies of receptivity to interruptions on mobile devices in naturalistic settings, and a methodology based around experience-sampling in order to inform and motivate the development of concepts and models for system design that respond to issues of receptivity in general and temporal challenges such as timing and episodic engagement in particular.
heartbeats: a methodology to convey interpersonal distance through touch. individuals who are blind are at a disadvantage when interacting with sighted peers given that nearly 65% of interaction cues are non-verbal in nature [3]. previously, we proposed an assistive device in the form of a vibrotactile belt capable of communicating interpersonal positions (direction and distance between users who are blind and the other participants involved in a social interaction). in this paper, we extend our work through use of novel tactile rhythms to provide access to the non-verbal cue of interpersonal distance, referred to as proxemics in popular literature. experimental results reveal that subjects found the proposed approach to be intuitive, and they could accurately recognize the rhythms, and hence, the interpersonal distances.
needs analysis: the case of flexible constraints and mutable boundaries. needs analysis is a prerequisite to effective design, but typically is difficult and time consuming. we applied and extended our methods and tools in a case study helping a mission control group for the international space station. this domain illustrates the challenges of information-system domains that lack rigid, immutable, physical constraints and boundaries. we report the successes & challenges of our approach and characterize the situations where it should prove useful.
context-adaptive interaction for collaborative work. context plays an increasingly important role to adapt systems to users' needs and to make access to large information spaces more efficient. yet, in the area of collaborative work the potential of context-based adaptation of it systems has so far not been investigated and exploited. there is a lack of methods that take into account the manifold aspects of context such as physical, activity-based, thematic or social context in an integrated fashion. this workshop will discuss models, methods and system design approaches for context-adaptive collaboration support and will outline research directions leading towards comprehensive understanding of context.
modality is the message: interactivity effects on perception and engagement. new media interfaces offer a wide variety of modalities for interacting with systems. while typing and clicking remain the staple of most interfaces, several other modalities have emerged in recent years, enabling users to perform a range of other actions, such as dragging, sliding, zooming-in/out, mousing-over and flipping through a revolving carousel of images (as in cover flow). while each modality offers a unique way of interacting with information, it is not clear whether it brings unique psychological advantages. does a drag engender greater user engagement? is the mouse-over likely to enhance user's perceptual bandwidth? a scientific assessment of such effects is impossible with existing interfaces given the confounded nature of modality combinations and information provided by them. therefore, we designed six web interface prototypes with identical content, differing only in modality, for experimentally isolating the effects of each, using a between-subjects design. ongoing data collection involves both physiological and psychological measures of perceptual bandwidth and engagement.
pot à musique: tangible interaction with digital media. we describe the conceptualisation, design and prototype development of a tangible gesture-based interface for the control of a music player. the device takes the form of a pot, augmented with inertial sensing and model-based vibrotactile feedback, which it is envisioned will encourage a more playful form of interaction for a richer interactive experience with our increasingly dematerialised digital media.
tongue music: the sound of a kiss. in this paper we examine the tongue music project: a performance-instrumental that makes use of the human tongue to yield amorous sounds, either by solo using a primary tongue controller or as a duet (the sound of a kiss) pairing a tongue controller and a receiver. we describe the design of the system and how the participants use the technology in a creative way to produce music.
using "rapid experimentation" to inform customer service experience design. this case study describes how cisco followed a "rapid experimentation" methodology in conducting iterative, high velocity pilot studies to inform a large global customer service experience design project. the research findings described in this case study informed the design of a better mechanism for customers to select their expected outcomes, so cisco can provide a personalized service experience. this improved accuracy moves us closer to our goal of eliminating at least 5% of all re-routing of service requests. in addition, customer satisfaction improves as we approach our target of reducing average time-to-resolution by at least 5%, which also saves on the cost-per-call for cisco. the case study explains how these studies improved the direction of the design concept and narrowed the research focus to answer more specific design questions. it summarizes how this approach was successfully applied in the customer service experience design situation to achieve the same experience design goal in 8 weeks, 4 weeks ahead of the 12 week schedule. we also describe lessons learned in applying the "rapid experimentation" methodology.
lowering the barrier to applying machine learning. researchers have used machine learning algorithms to solve hard problems in a variety of domains, enabling exciting, new applications of computing. however, research results have not transferred to software solutions. in part, this is because developing software with machine learning algorithms is itself difficult. my dissertation work aims to understand why using machine learning is difficult and to create tools that lower the bar so that more developers can effectively use machine learning.
radio healer. in this paper we discuss our performance titled radio healer. this performance reflects upon the indigenous cultural implications of consumer technologies such as the internet, mobile handheld devices, and personal computers, and how this relates to the effects of these technologies upon the lived experiences of all people. radio healer achieves this through the tactical appropriation and adaptive reuse of consumer technologies by indigenous peoples, along with the expression of indigenous media through sustainable cross-cultural partnerships between peoples of diverse backgrounds. the motivation of our collaborative work is to appropriate and express electronic technology in order to recognize the sovereign rights of indigenous peoples.
free-space pointing with constrained hand movements. research on pointing devices has shown that rate control is appropriate for isometric and elastic devices but not effective when input control is purely isotonic. human hand has been generally considered as an isotonic device. therefore, pointing devices that are directly controlled by hand movements (e.g., the mouse) are based on position rather than rate control. in this work, we study the relevance of rate control in low-resolution input. taking into account elastic properties of the human wrist, this work explores designs that mix position and rate control when input is handled by constrained hand movements.
brain, body and bytes: psychophysiological user interaction. the human brain and body are prolific signal generators. recent technologies and computing techniques allow us to measure, process and interpret these signals. we can now infer such things as cognitive and emotional states to create adaptive interactive systems and to gain an understanding of user experience. this workshop brings together researchers from the formerly separated communities of physiological computing (pc), and brain-computer interfaces (bci) to discuss psychophysiological computing. we set out to identify key research challenges, potential global synergies, and emerging technological contributions.
improving remote collaboration through side-by-side telepresence. virtually all teleconferencing solutions are designed to facilitate face-to-face interactions. while face-to-face is suitable for meetings or conversations, we see many real-world situations where people choose to sit in other configurations. face-to-face telepresence inaccurately simulates these alternate interaction styles. in this paper we describe a side-by-side telepresence concept, which is more appropriate for side-by-side style interactions, such as collaborative writing or training. we explore the differences between face-to-face and side-by-side telepresence, and discuss our prototype side-by-side telepresence workstation.
heads-up engagement with the real world: multimodal techniques for bridging the physical-digital divide. the vast and ever-increasing collection of geo-tagged digital content about the physical world around us has prompted the development of interaction methods for various different scenarios. however, the map-based views common on desktop computers are not always appropriate when considering mobile usage. the aim of this research is to provide suitable methods that can encourage user interaction with geo-located digital content, avoiding unnecessary interference with the user's immersion in the physical world around them. this extended abstract outlines the work published to date, suggests future areas of research, and highlights the key contributions brought to the hci community.
enabling cross-device interaction with web history. internet-enabled personal devices are growing in number. as people own and use more devices, sharing information between devices becomes increasingly important. web browsing is one of the most common tasks, thus sharing web history is a first step in supporting cross-device interaction. current methods of sharing web history involve manual, cumbersome methods. this paper explores a system to automatically synchronize web information among a user's personal devices, and optimize the interface to support mobile users. we describe a system that enables users to quickly find directions on their mobile phone based on past web searches, and seamlessly share favorite web pages between their personal devices.
creating salient summaries of home activity lifelog data. keeping track of the fluctuations in functional abilities that elders experience is important for early detection of cognitive decline and maintaining independence. in this proposal, i describe my research in understanding how to design ubiquitous home sensor systems that can monitor how well individuals carry out everyday activities important for independence. these systems collect an overwhelmingly large amount of data and thus only the most salient details need to be presented. i will identify the information needs of stakeholders to inform the design of salient summaries of the data for elders, their family caregivers, their doctors, and their therapists to become more aware of changes functional abilities. i also describe the technical, hci, and clinical contributions of this work.
computing technology in international development: who, what, where, when, why and how? building on the successes of prior workshops at chi and other hci conferences on computing in international development, we propose a panel to engage with the broader chi community. topics to be discussed include why international development is important to hci as a discipline, and how chi researchers and practitioners who are not already involved in international development can contribute.
mirrored message wall: sharing between real and virtual space. in this paper, we describe the mirrored message wall as a public display to promote social communication and user participation. it exists in both physical and virtual space and is a bridge to connect users between the real and virtual worlds.
behavior assessment and visualization tool. this paper introduces our work on a new tablet pc-based tool that allows near-real-time coding (a technique of classification) of video-recorded or live behavior. the tool also allows the user to create and manipulate simple interactive visualizations of the coding results. this tool has been designed both to advance behavioral research and to support applied uses, for instance in professional coaching. we envision that this tool will be extremely versatile as users will be able to classify in near-real-time individual and team-behavior occurring in many research domains including hci. this paper describes the salient design and interaction aspects of this tool, and the improvements it has over existing systems.
social network games: exploring audience traits. the audience of social network games is an as of yet unexplored group. given the growing number of users and people spending time playing social network games, a better understanding of the audience, and how they are using social network games is important to crafting better social networking tools in the future. respondents of this survey reported personality factors, demographics, habit strength, self-efficacy of social network games, and types of use by different features.
sawtooth: interactive clarity and aesthetic complexity. sawtooth (2009) is an artwork integrating performance, sound, and animation. this paper describes the design of sawtooth, with particular reference to the balances it strikes between control, clarity, and complexity.
eyebrowse: real-time web activity sharing and visualization. in this paper, we explore the potential for letting users automatically track and selectively publish their web browsing activities in real time on the web. we developed a system, eyebrowse, with three goals: first, to provide a means for individuals to better understand how they spend time on the web through visualizations and statistics; secondly, to foster social discovery and awareness through real-time web activity sharing; and finally, to build a large public corpus of web browsing trails using this method. we gathered user impressions of eyebrowse, including perceived usefulness, feelings of self-exposure, and privacy concerns, for ascertaining ways to improve the system.
mudpad: fluid haptics for multitouch surfaces. in this paper, we present an active haptic multitouch input device. its touch surface is a malleable pouch filled with a smart fluid. the viscosity of this fluid can be controlled to provide localized active haptic feedback. magnetic fields can stiffen the liquid locally, thus creating an invisible "labyrinth that can be felt when a user tries to displace the liquid at an activated location. the user feels this labyrinth as a relief when running her fingers over the surface. we believe there are promising applications for this kind of haptic feedback. hence, we intend to further investigate them in comparison to traditional vibrotactile feedback techniques.
the effect of preference elicitation methods on the user experience of a recommender system. to increase the user experience, preference elicitation methods used by recommender systems can be adapted to individual differences such as the level of expertise. however, we will show that the satisfaction and perceived usefulness of a recommender system also depends strongly on subtle variations of the implementation of these methods.
integrated model based on the psychology of active/non-active computer users: activating technology holdouts. although many internet-based social services exist that can raise our quality of life, there are still many non-active users who cannot fully enjoy the convenience of the computer and its functionality even though they have computers in the home. in order to analyze how to enhance computer usage, we conducted a field study and arrived at an integrated model that enables us to deeply understand the psychology of active/non-active computer users. initial design guidelines for activating the non-active users are derived from our model.
there's methodology in the madness: toward critical hci ethnography. we examine the expansion of topic areas for qualitative research in hci publications, focusing on representations of users and field sites. we examine further developments in anthropological methodologies during a critical period of the late 1980s and 90s. we identify concerns shared by both research communities, in particular, the relationships between researcher and informant, and the construction of bounded settings for field work. we then argue that ethnographic approaches and theoretical commitments which came to the fore after anthropology's critical turn can be usefully applied, in ways that can inspire design, to investigations of social practice and technology appropriation.
factors impeding wiki use in the enterprise: a case study. our research explored factors that impacted the use of wikis as a tool to support the dissemination of knowledge within an enterprise. although we primarily talked to a population of wiki contributors and readers, we discovered two major factors which contributed to staff's unwillingness to share information on a wiki under certain circumstances. first, we uncovered a reluctance to share specific information due to a perceived extra cost, the nature of the information, the desire to share only "finished" content, and sensitivities to the openness of the sharing environment. second, we discovered a heavy reliance on other, non-wiki tools based on a variety of factors including work practice, lack of guidelines, and cultural sensitivities. our findings have several implications for how an enterprise may more fully reap the benefits of wiki technology. these include implementation of incentive structures, support for dynamic access control, documenting clear guidelines and policies, and making wikis more usable.
video play: playful interactions in video conferencing for long-distance families with young children. long-distance families are increasingly staying connected with free video conferencing tools. however research has highlighted a need for shared activities for long-distance family communication. while video technology is reportedly superior to audio-only tools for children under age 7, the tools themselves are not designed to accommodate children's or families needs. this paper introduces games for intergenerational families to play with young children during a video chat. we build on research in cscw and child development to create opportunities for silliness and open-ended play between adults and young children. our goal is to create a space for shared activities that scaffold interaction across distance and generations.
game-y information graphics. in this paper we explore the application of formal elements of games such as goals and scores to information graphics?so called "game-y" information graphics. in order to study how game-y aspects could engender exploration of a dataset, we built two versions of an information graphic, one without game elements and the other incorporating aspects of trivia games. preliminary results based on a real world deployment of the graphics on a newspaper website suggest that the trivia game information graphic engendered increased exploration of the data space by users as compared to the regular version of the graphic.
designing a cd augmentation for mobile phones. interacting with physical cds can be a very tangible and explorative experience. however, physical objects can't provide access to the digital services we are used to when using with digital music collections. in this paper we develop user interfaces for mobile phones that augment physical cds to provide access to digital services. the most important functionalities of the music player are derived from a user study. design sketches for the augmentation shown on the phone's display are collected from 10 participants. participants' ideas are subsumed by four concepts that are implemented as prototypes for the android platform.
guidelines for a costume designer's workbench. costume design presents an opportunity to study image search, selection, and use within the context of visual communication. interaction with images is fundamental to supporting many collaborative design practices. this paper presents emergent guidelines for a costume designer's workbench based on three case studies of costume-related image use during the design and production of three plays. future work will implement such a workbench and then test it with a wide variety of costume designers.
manual deskterity: an exploration of simultaneous pen + touch direct input. manual deskterity is a prototype digital drafting table that supports both pen and touch input. we explore a division of labor between pen and touch that flows from natural human skill and differentiation of roles of the hands. we also explore the simultaneous use of pen and touch to support novel compound gestures.
asthmon: empowering asthmatic children's self-management with a virtual pet. asthma is a common chronic childhood disease. children spend a majority of their time in schools, and barriers to on-site asthma management have been reported. previous forms of clinical intervention have regarded patients as passive subjects. however, self-management plays a significant role in caring for asthmatics. we consider asthmatic children and their parents, primary caregivers, as active participants in their treatment and care. to achieve this, we created asthmon, a portable virtual pet that measures the lung capacity, and instructs appropriate actions to take.
exploring interfaces to botanical species classification. we have developed several prototype user interfaces for botanical species identification and data collection across a diversity of platforms including tablet pc, ultra mobile pc (umpc), apple iphone, augmented reality, and microsoft surface. in our demonstration, we show umpc and iphone user interfaces, discuss the commonalities and distinctions across the different interfaces, and invite visitors to explore these differences. our prototypes address several issues of interest to the chi community including mobile interfaces, interfaces to object recognition, and visualization.
hci, communities and politics. working with communities around social change presents a challenge to common hci methods, as politics often comes to the fore. in some cases, the politics of a community are explicit, for example, when working with activists or advocacy groups. in other cases, political aspects are less explicit but surface in considering the allocation of resources or in groups wherein issues of race, gender or class are of major importance. to address these dynamics, hci researchers have to go beyond traditional hci tools and metrics, which too often bracket out the political in an effort to focus on the instrumental issues and uses of technology. this panel juxtaposes several community-based hci research projects in which politics have been a significant factor and asks "how do we address the
extended klm for mobile phone interaction: a user study result. facing with the fast development of mobile phones, the designers need to evaluate user performance for early responding to the potential interaction problems. previous studies show that the original keystroke-level model (klm) has been successfully used in conventional computer-based interaction design. however, with the emphasizing of the next-generation design and new interactions in mobile phones, the existing klm cannot fulfill all range of mobile-based tasks. this research aims to present discussions on extending klm for mobile phone interaction. in addition to the basic operators in conventional klm, another fourteen new operators and a new concept - operator block were proposed. this extended klm will help designers to reach a full-fledged user performance model for mobile phone interaction.
hard-to-use interfaces considered beneficial (some of the time). researchers in hci share a common understanding that 'easy-to-use', 'easy-to-learn' and 'intuitive' interfaces are beneficial to users. designing such interfaces raises challenges and often requires multiple iterations. while we are generally prompt to discard more hard-to-use interfaces and smooth out usability issues, we want to raise here the issue of their potential benefits. we de-scribe two cases in which we observed potential bene-fits from introducing barriers for collaborating and communicating with others. we attempt to shed a new light on interfaces with usability "problems" and how these problems may benefit system efficiency and user experience. we end with a discussion of the pros and cons of making systems harder for people to use, and how to integrate this perspective in the design process.
bridging the gap: moving from contextual analysis to design. a typical product development lifecycle for interactive systems starts with contextual analysis to guide system design. the challenge however is in transitioning from findings about users, their activities, and needs, into design requirements, constraints and implications that are directly applicable to design. in this workshop, we seek to bring together researchers, designers, and practitioners who regularly face the challenge of transitioning from contextual analysis to design implications and design practices. our goal is to foster a community in this space, understand the techniques that are being employed to move from contextual analysis to design, the challenges that still exist, and solutions to overcome them.
design situations and methodological innovation in interaction design. this juried alt.chi paper argues that philosophy can seed hci innovations. recent developments in ontology open up novel methodological opportunities. alain badiou's situational ontology breaks an apparent impasse between essentialism and relationalism. for badiou, the essence of any entity is a multiplicity formed from what is counted-as-one, but its parts bring potentials for change. these can exploited through the concept of design situations that contain infinite opportunities for designing as connecting. far from being a barren abstraction, this opens up new spaces for demonstrable practical methodological innovation in interaction design.
the reactable: tangible and tabletop music performance. in this paper we present the reactable, a new electronic musical instrument with a simple and intuitive tabletop interface that turns music into a tangible and visual experience, enabling musicians to experiment with sound, change its structure, control its parameters and be creative in a direct, refreshing and unseen way.
digestmanga: interactive movie summarizing through comic visualization. digestmanga is a system for interactively integrating movies with comics. several systems already exist for visualizing input movies as comic books to allow users to see several frames of a movie at the same time through a comic visualization. however, their intention is mainly to represent a movie with visual summaries. although users can edit the visualized comic book to arrange the summaries, the manipulations are not reflected in the input movie.
new media and folk music in rural india. this paper presents the results of a preliminary ethnographic study of folk music practices in rural malwa, madhya pradesh (india), specifically on the impact of new media on the production and dissemination of this music. our findings show that new media can lead to increased listening and appreciation of folk music, but that better mechanisms are required for remunerating and recognizing folk artists themselves.
shape-changing mobiles: tapering in two-dimensional deformational displays in mobile phones. this paper presents a novel haptic actuation system for mobile phones: two-dimensional tapering through an actuated back plate. it proposes this type of shape-change for various applications, e.g. for ergonomically actuating the shape itself, displaying internal contents, and pointing to entities located outside the device. the paper reports a user study in which the accuracy of perceiving the two-dimensional tilt of the phone's back plate is measured, as well as results from a questionnaire and a user interview. the results indicate that two-dimensional shape change may be a suitable addition to existing mobile phone technology.
grassroots heritage in the crisis context: a social media probes approach to studying heritage in a participatory age. social media technologies are rapidly changing the way people create, share, and experience memories especially around crises. when collective memory is generated on a societal scale and shared across generations over time, this practice assumes social and cultural significance and becomes a heritage matter. emerging uses of social media are generating new kinds of heritage practices from the bottom-up, what i call "grassroots heritage." this interdisciplinary design study works at the intersection of social media and cultural heritage in the crisis context using a variant method called "social media probes." i present a grassroots heritage framework with design ideas for facilitating "socially-distributed curation" to guide future hci research in the heritage domain.
real-time interaction with supervised learning. my work concerns the design of interfaces for effective interaction with machine learning algorithms in real-time application domains. i am interested in supporting human interaction throughout the entire supervised learning process, including the generation of training examples. in my dissertation research, i seek to better understand how new machine learning interfaces might improve accessibility and usefulness to non-technical users, to further explore how differences between machine learning in practice and machine learning in theory can inform both interface and algorithm design, and to employ new machine learning interfaces for novel applications in real-time music composition and performance.
comlex: visualizing communication for research and saving lives. one of the major causes of patient harm in hospital is poor communication. we are developing a video review and visualization platform to research and improve medics' communication skills. it intended for use by experimenters, as a deployable training tool for medics, and also for forensic review of communication. it supports pluggable analysis modules and visualizations for research teams, and configurable workflow for educators and hospital administrators.
gest: exploring gestural interactions. in this paper we describe the use of gesture based 'device interlinking' to achieve an enhanced user experience and optimize hardware utilization.
a novel method to monitor driver's distractions. many attempts were made in the past to monitor a driver's visual and cognitive distractions. yet, most of the techniques did not become a practical application due to their contact-based nature of monitoring. in this paper, we describe research that aims to monitor the driver's distractions from a distance. the proposed method is based on the thermal signature of the face. the method measures human physiology in a contact-free manner and therefore, is suitable for continuous monitoring. we conducted two experiments to analyze the validity of our method. experiment-1 focused on driver's cognitive distraction by allowing cell phone talking while driving. experiment-2 focused on driver's visual distraction by allowing texting while driving. the experimental results from 11 participants illustrate that the facial physiology alters in a measurable amount in both kinds of distraction. the proposed method quantifies this physiological change and detects periods of distractions. ultimately, this information can be utilized to alert the drivers in real time. participants' performance analysis confirms validity of the proposed method.
making food, producing sustainability. many contemporary approaches to environmental sustainability focus on the end-consumer. in this panel, we explore lessons from small food producers for future development of hci as an agency of sustainable ways of being. we argue that attention to the relationship small producers have to the environment and their experiences of interrelations between environmental, economic, and social sustainability suggest new foundational issues for sustainable hci research.
designing for collaboration: improving usability of complex software systems. designing for collaboration approaches systems and users as a team and focuses on the cooperation between the two. this work in progress aims to delineate how designing for collaboration is also inherently designing for usability. it is proposed that designing for collaboration is theoretically more appropriate for building complex problem-solving applications, where the user and system are by definition co-information-processors.
bodies, boards, clubs and bugs: a study of bodily engaging artifacts. popular practices with non-digital artifacts were explored in order to reveal qualities for design of interaction that allow for full body experiences, and engagement of a rich array of our senses and bodily capabilities for being-in and moving-in the world. for successful design of movement-based and bodily interactive artifacts, we have to include qualities that allow users to connect their actions with the artifact to the surrounding physical and social world.
rehabilitation centred design. stroke is a significant cause of disability, and is predicted to become a greater burden as population demographics shift. research suggests that the completion of rehabilitation exercises can considerably improve function in damaged limbs, yet these exercises can be both boring and frustrating for patients to complete at home. new technologies create possibilities to support rehabilitation in motivating and entertaining ways, and, in this paper, we present a case study that illustrates the work of designing such technologies for a single user. participation in this case study has highlighted some interesting tensions between designing for rehabilitation and designing for the user.
video games as research instruments. the workshop aims to help researchers share experience and expertise on the use of video games as research instruments in hci and related disciplines. it will focus on existing uses, methodologies, results and issues with using video games, and is expected to lead to a better shared understanding of their current and future use across a variety of disciplines.
understanding "cool". design practitioners know that part of their job is to create products and services with usability in mind. making products and services learnable, efficient and pleasant to use are certainly goals, but every designer dreams of creating something more - something so great that people crave it, long for it, must have it. marketers call it "a must have", "compelling", or "insanely great". but most of the rest of us just call it cool. over the past several decades, cool has evolved into a marketing imperative. and so cool has become like an overarching requirement for many designs, especially in the consumer product space. but cool is hard to pin down - there's no accepted way to define it, measure it, or design for it. like glamour, it is an ineffable yet powerful quality that depends on a host of subtle factors. this sig creates a forum to go beyond "you know cool when you see it", collecting and collating a number of concrete examples of cool and identifying patterns and design principles underlying cool.
opportunities and challenges for mobile-based financial services in rural uganda. this paper outlines key research findings on the use of mobile-based financial services in rural uganda. it also includes insights into behaviors and attitudes towards finances that may impact the widespread uptake of mobile financial services in rural uganda. this paper provides actionable insight into the opportunities and challenges for these services as well recommendations for future research.
thanatosensitively designed technologies for bereavement support. computing supports a number of activities across the lifespan, from interactive games for children to smart homes for seniors. however, one part of the lifespan which is often overlooked by application designers is the end of life - a period marked by issues of mortality, dying, and death. my thesis takes up this area as its object of study, and does so specifically by examining the bereaved as a target population. i argue that most modern technologies are not designed with proper acknowledgement of the eventual death of their users, and that this oversight results in a series of circumstances which complicate affairs for bereaved family members. based on evidence from a survey and interview study, i identify opportunities for technology designers to support bereavement activities through a process called "thanatosensitive design." my thesis seeks to contribute methodological insights for designing for the end of the lifespan, a novel system which connects bereaved individuals together, and account of how this system mediates social support.
the future of floss in chi research and practice. in the past 10 years, free/libre/open source software (floss) has become a potent enabler in all areas of computing. despite its rise in importance, the chi community has been slow to study and partner with the floss community. this workshop will join researchers and practitioners from the chi and floss communities to establish an agenda for future research and collaboration between the two communities.
who are the crowdworkers?: shifting demographics in mechanical turk. amazon mechanical turk (mturk) is a crowdsourcing system in which tasks are distributed to a population of thousands of anonymous workers for completion. this system is increasingly popular with researchers and developers. here we extend previous studies of the demographics and usage behaviors of mturk workers. we describe how the worker population has changed over time, shifting from a primarily moderate-income, u.s.-based workforce towards an increasingly international group with a significant population of young, well-educated indian workers. this change in population points to how workers may treat turking as a full-time job, which they rely on to make ends meet.
squishy circuits: a tangible medium for electronics education. this paper reports on the design of a circuit building activity intended for children, which replaces wires with malleable conductive and non-conductive dough. by eliminating the need for soldering or breadboards, it becomes possible to very quickly incorporate movement and light into sculptures, and to introduce simple circuit concepts to children at a younger age. future applications in both structured and unstructured learning environments, based on results from a preliminary pilot study, are presented.
enhancing navigation skills through audio gaming. we present the design, development and initial cognitive evaluation of an audio-based environment simulator (abes). this software allows a blind user to navigate through a virtual representation of a real space for the purposes of training orientation and mobility skills. our findings indicate that users feel satisfied and self-confident when interacting with the audio-based interface, and the embedded sounds allow them to correctly orient themselves and navigate within the virtual world. furthermore, users are able to transfer spatial information acquired through virtual interactions into real world navigation and problem solving tasks.
socially cued mental models. we investigate how initial mental models of a photo sharing website are shaped by observing the behavior of existing users. we manipulate experimentally whether content with critical or popular appeal is highlighted as the best content on the website. despite interacting with uniform site content and interface design, user's mental models are significantly influenced by social cues embedded in content highlighting behavior, manifesting differential behavioral explanations, audience perceptions, and predictions of unseen features. results are interpreted within a specific theory of socialized mental models.
topaoko: interactive construction kit. if you have a laser cutter, you can build your own topaoko. we describe work in progress on topaoko, an interactive construction kit that encourages experimentation and play with pieces of a hardboard based, embedded circuit, kit. we describe each component of the kit and examples of constructions built with it.
remote web browsing via the phone with teleweb. teleweb is an assistive voice-enabled application empowering users to remotely access the web through the most ubiquitous device - the phone. the uniqueness of the technology is that it enables users to gain access to information from almost anywhere via a plain, old-fashioned telephone. teleweb users will be able to call their own personal numbers, authenticate themselves, and then use speech and phone key-pad to remotely browse the web on their own pcs. teleweb may especially appeal to people with vision loss, as well as older adults who may find the phone interface to be more familiar and easier to use. in this paper, i describe the teleweb approach and the interface.
rolling and shooting: two augmented reality games. we present two fast-paced augmented reality games. one is a single-player game experienced through a head-worn display. the player manipulates a tracked board to guide a virtual ball through a dynamic maze of obstacles. combining the 3dof absolute orientation tracker on the head-worn display with 6dof optical marker tracking allows the system to always account for the correct direction of gravity. the second game is a networked, two-player, first-person-shooter, in which tracked hand-held umpcs are used to blast virtual dominoes off a table. players' virtual locations are warped to keep them from physically interfering with each other.
interfaces beyond the surface: a structural approach to embodiment. this work aims to contribute to the theory and practice of embodied interaction. it criticizes that its underlying term of embodiment has not been defined sufficiently, and is, consequently, used inconsistently. it also argues that this circumstance is a problematic one. it presents an attempt to provide more clarity to the theory of embodiment, as a basis for the practice of designing embodied interaction in tangible user interfaces (tuis). it proposes a purely structural approach, derived from heidegger's works around 'being and time' [3]. aspects and criteria of embodiment (as which heideggerian dinglichkeit is interpreted) in the literature are reviewed in this work, and applied to the design practice of embodied interaction.
design by physical composition for complex tangible user interfaces. in this paper, we present a novel approach to create devices with tangible user interfaces by physical com-position. while the separation of the user interface from the application logic has a long tradition in software engineering, for products with tangible user interfaces there is no equivalent approach that realizes a true separation and flexible combination of interface components, underlying technology, and software parts. we propose a novel concept that is based on an inner core for the basic technical and software platform of a product and an outer shell that builds a flexible and ex-changeable tangible user interface from passive components. using vision-based tracking, we can realize a clear separation between the components. no wiring is necessary. this paper introduces our novel approach and presents a first working prototype as well as initial results from its application in a design workshop.
beyond: collapsible tools and gestures for computational design. since the invention of the personal computer, digital media has remained separate from the physical world, blocked by a rigid screen. in this paper, we present beyond, an interface for 3-d design where users can directly manipulate digital media with physically retractable tools and hand gestures. when pushed onto the screen, these tools physically collapse and project themselves onto the screen, letting users perceive as if they were inserting the tools into the digital space beyond the screen. the aim of beyond is to make the digital 3-d design process straightforward, and more accessible to general users by extending physical affordances to the digital space beyond the computer screen.
socialcrc: a social- and context-aware rendezvous coordination system. we present a new mobile application socialcrc to simplify the process of coordinating an impromptu rendezvous. by considering contextual information and the social relationships between the attendants of a rendezvous, socialcrc can identify a more satisfactory rendezvous point. in this study, we deploy socialcrc in the context of a dinner rendezvous. a preliminary user evaluation indicates that socialcrc can offer satisfactory results for the most influential person involved in the coordination process. it also provides an acceptable solution for the whole group, without diminishing the satisfaction of the least influential person in the group.
mobidev: a mobile development kit for combined paper-based and in-situ programming on the mobile phone. in this paper we present mobidev, a development kit that allows the creation of applications for mobile devices by developing directly on a mobile phone and by using paper-based sketches as a starting point for creating the user interface (ui). although programming mobile applications on a computer has a well defined development structure, developing a mobile application on the mobile phone instead offers some advantages: (1) it allows people without access to a computer but to a mobile phone to create mobile applications and (2) it supports the development of applications which employ enhanced mobile phone features that are not fully supported by current desktop development environments. users draw ui sketches on paper (similar to a paper prototype) as the initial step in an evolutionary ui development process to speed up the development of the application and to minimize the text input effort.
let users tell the story: evaluating user experience with experience reports. user experience (ux) has been under extensive research in recent years. one of the key questions has been how to evaluate user experience. several methods such as diaries, experience sampling and questionnaires have been used for collecting data on user experience with a product. although these methods provide valuable data, they may lack obtaining rich descriptions of ux in users' everyday lives. we have approached the question of ux evaluation by experience reports which are open-ended experience stories written by the users after using their products in real contexts of use. in this paper, we describe a field study in which 21 participants wrote 116 experience reports about ux with their personal products such as smart phones and mp3 players. the reports were analyzed with predefined context and experience categorizations to identify core experiences. we discuss our initial findings on the applicability of the method to evaluate ux.
the fulfillment of user needs and the course of time in field investigation. business contexts represent a big challenge for software development, specifically in terms of finding a balance between business goals and users' goals. this context determines the utility of an application, but good user experience (ux) with business applications is only achieved if the software supports the fulfillment of users' goals and needs. this article presents the efforts realized in a call-center of a german telephone company aimed at enhancing ux and hence creating a positive influence on the emotional state of the users/employees. it describes a method applied for the elicitation of user needs as well as ideas for improving ux. beyond that, the results indicate that software properties can influence the emotional state of the user if they support the fulfillment of human needs and thus positively affect the achievement of business goals.
graaasp: a web 2.0 research platform for contextual recommendation with aggregated data. in this paper we describe graaasp, a social software currently under development to support the creation of a real usage database of social artifacts. our goals are twofold: first to offer a generic aggregation service and user interface to people and communities. second, to experiment with recommendation and reputation models and algorithms in e-learning.
the complexity of perception of image distortion: an initial study. image retargeting methods adapt an image for displays with different sizes and aspect ratios. methods are based on the assumption that some kinds of distortions are preferable to others. while a rich variety of literature exists on retargeting methods, there is little codified understanding of how these distortions are perceived. this paper shows that people's perception of image distortions is complex. we report an initial study exploring the phenomenon that shows that even in a simple form of distortion, perception depends on a myriad of factors including amount of distortion, image content, and the viewer's cultural background. these initial findings have ramifications for the design and evaluation of image retargeting, and suggest that a more thorough study is necessary.
tangible video bubbles. we introduce the tangible video bubbles, a new video-based drawing space for children to create expressive video art. a tangible video bubble acts both as a container for children's expressions, as well as an instrument with which children can perform with their recorded video by squeezing and stretching the physical bubble. we present our iterative design process and evaluation of the play space with children, and discuss a new approach to making video creation more concrete and playful for children.
weight-shifting mobiles: two-dimensional gravitational displays in mobile phones. in this paper, we present a novel type of haptic display for usage in mobile phones. it changes the gravitational properties of the device by shifting an internal weight along two axes. its utility is explored in a performance study, in which users were estimating positions of the device's actuated center of gravity. the users also participated in qualitative studies: a questionnaire that assessed the perceived quality of interacting with the device, and an interview in which they described their experiences with the weight-shifting mobile. furthermore, this paper suggests three domains of application in which the system may be of benefit: augmenting digital content with physical mass, ambient displays, and haptically augmented wayfinding.
human social response toward humanoid robot's head and facial features. this study explores how people's social response toward a humanoid robot can change when we vary the number of the active degrees of freedom in the robot's head and face area. we investigate this problem by conducting two wizard-of-oz user studies that situate an elder person in a self-disclosure dialogue with a remotely operated robot. in our first study, we investigated the effect of expressive head gestures with a four-degree-of-freedom neck. in the second study we focused on the face where we investigated the effect of expressive eyebrow movement versus active gaze and eyelid movement. in the first study, we found that participants are willing to disclose more to the robot when the robot moved its neck in an expressive manner. in the second study, our data suggests a trend where gaze and expressive eyelid movement results in more disclosure over eyebrow movement
the problem of defining values for design: a lack of common ground between industry and academia? the hci community recognizes the importance of value-centric design methodologies as reflected in the number of publications on the topic in recent years. however, the adoption of these methodologies by industry has been slower than desirable. this paper seeks to uncover potential reasons behind this slow adoption by investigating the concept of "values" among individuals working as designers in various industries. based on a survey of these design industry professionals, this paper reports that design professionals believe they do consider values in their design and hence may not see a need for a specific value-sensitive methodology. while design professionals clearly consider personal, social, and economic values in their work, there may be a lack of consideration of moral values. implications and further findings are discussed.
wow pod. wow pod is an immersive architectural solution for the advanced massive online role-playing gamer that provides and anticipates all life needs. inside, the player finds him/herself comfortably seated in front of the computer screen with easy-to-reach water, pre-packaged food, and a toilet conveniently placed underneath a built-in throne.
real time search user behavior. real time search is an increasingly important area of information seeking on the web. in this research, we analyze 1,005,296 user interactions with a real time search engine over a 190 day period. we investigate aggregate usage of the search engine, such as number of users, queries, and terms. we also investigate the structure of queries and terms submitted by these users. the results are compared to web searching on traditional search engines. results show that 60% of the traffic comes from the engine's application program interface, indicating that real time search is heavily leveraged by other applications. of the queries, 30% were unique (used only once in the entire dataset). the most frequent query accounted for 0.003% of the query set. less than 8% of the terms were unique. the most frequently used terms accounted for only 0.03% of the total terms. concerning search topics, the most used terms dealt with technology, entertainment, and politics, reflecting both the temporal nature of the queries and, perhaps, an early adopter user-based. sexual queries were quite low, relative to traditional web search. searchers of real time content often repeat queries overtime, perhaps indicating long term interest in a topic. we discuss the implications for search engines and information providers as real time content increasingly enters the main stream.
designing a touch-screen sensecam browser to support an aging population. in this paper, we describe the hci challenges associated with the novel domain of lifelogging for older users. the sensecam is a passively capturing wearable camera, worn via a lanyard around the neck and used to create a personal lifelog or visual recording of the wearer's life, which generates information that may be very helpful as a human memory aid. indeed, given that memory defects are more marked in the elderly, we believe that lifelogging browsing techniques which are considerate of the elderly are imperative. thus, the challenge tackled in this work was to design and integrate the lifelogging activity supported by new technologies in such a way that can easily be learned and used by older people, enabling them to enhance and enrich their lives with the new technologies. this work provides design practitioners of future lifelogging interfaces early sight of the lessons we have learned in making lifelogging technologies accessible to elderly non-computing literate participants.
chi 2010 special interest group: creating prosocial media for children. children are introduced to social networking at younger and younger ages through commercially-centered virtual worlds and social gaming sites like club penguin, neopets, and webkinz. a small and growing subset of these web 2.0 sites use social media to address prosocial values in children. this special interest group focuses on "prosocial media for children", which we define as social media that strive to increase children's awareness of the lives and needs of others and promote caring about the welfare and well-being of others. participants in this sig are invited to join the growing discussion regarding the design and development of children's prosocial media. participants will review 3 - 6 short examples, and then break into small groups that will host facilitated discussions about the issues and challenges surrounding design and development of children's prosocial media. a primary goal of this sig is to foster the development of a community of researchers and practitioners who are focused on designing and developing prosocial media for children.
on presenting audio-tactile maps to visually impaired users for getting directions. recent years have witnessed significant efforts on developing computer-based technologies for making maps accessible to people who are blind. existing work has largely focused on the technological aspects of the problem without adequate attention to the humancomputer interaction issues. using an audio-tactile system as the platform, we present a focused study on such hci issues for supporting a blind user's effective navigation of a map in getting directions. the ultimate goal of the research is to establish comprehensive design guidelines for building technologies that truly serve the needs of the users in the application of accessible maps. the results of our current study suggest that the proposed designs are effective for supporting a blind user in obtaining directions from online maps.
blowtooth: pervasive gaming in unique and challenging environments. this paper describes blowtooth, a bluetooth-implemented pervasive game where players smuggle virtual drugs through real airport security with the help of unknowing bystanders. the game explores the nature of pervasive game playing in environments that are not generally regarded as playful or "fun," and where people are subject to particularly high levels of intrusive surveillance and monitoring. six participants who were travelling internationally within a two-week period were recruited to evaluate the game. findings suggest that creating pervasive games that incorporate the unique features of their context as part of the game may provide enjoyable, novel and thought-provoking experiences for players.
using concept maps to evaluate the usability of apis. application programming interfaces (apis) are the interfaces to existing code structures, such as widgets, frameworks, or toolkits. therefore, they very much do have an impact on the quality of the resulting system. so ensuring that developers can make the most out of them is an important challenge. however standard usability evaluation methods as known from hci have limitations in grasping the interaction between developer and api -- the gui, which makes this interaction obvious, is missing. in this paper we present a longitudinal approach using concept maps and a question diary to make this interaction visible and study the usability of an api over time.
tangible interfaces for download: initial observations from users' everyday environments. tangible user interfaces (tuis) have been promoted and discussed in the hci community for 15 years. most reported tuis are research prototypes, available in laboratories or museums. this paper reports an attempt to understand the impact of tuis in users' everyday environments through a low-cost, simple set-up tangible interface for music that can be freely downloaded from a website. the system requires only a regular computer, a webcam and a printer - the physical parts of the interface can be folded out of ordinary paper. logging interaction with the interfaces and analyzing content posted by users on the web we observed that the tuis were accepted as normal: just interfaces to make music rather than esoteric systems.
interactive robot task learning. in this paper we provide a brief overview of our research agenda in human-robot interaction and interactive learning. we highlight key components to be demonstrated as part of the chi 2010 media showcase.
exploring social dimensions of personal information management with adults with ad/hd. studies in personal information management (pim) have primarily examined pim behavior as an individual activity. in this paper, we discuss social dimensions of pim, more specifically, socially derived pim activities. the biggest challenge adults with attention deficit / hyperactivity disorder (ad/hd) face is managing information and tasks. accordingly, online forums for sharing pim strategies is a wide spread practice among many individuals with ad/hd. those that are not engaged in online forums are also found to often rely on social resources in forming pim strategies. we discuss social dimensions of pim emerged from our 16 interviews with adults with ad/hd and coaches of ad/hd. our findings provide a good starting point towards understanding the social, adaptive and evolutionary nature of pim practices, which would later inform design implications.
current issues in assessing and improving information usability. the usability of information is vital to successful websites, products, and services. managers and developers often recognize the role of information or content in overall product usability, but miss opportunities to improve information usability as part of the product-development effort. this meeting is an annual forum on human factors of information design, in which we discuss issues selected by the group from the facilitators' list of topics, augmented by attendees' suggestions.
investigation of cultural dependency in mobile technology and older adults. studies using different methods have been carried out of older adults' use of mobile technology in malaysia and the uk. preliminary results suggest that there are significant differences in the results which are culturally dependent.
ubiquitous drums: a tangible, wearable musical interface. drummers and non-drummers alike can often be seen making percussive gestures on their chests, knees and feet. ubiquitous drums enhances this experience by providing musical feedback for these and other gestures. this paper describes the implementation and evolution of this tangible, wearable musical instrument.
get the picture?: evaluating interfaces through children's drawings. we conducted a study to determine whether it was possible to evaluate the usability of a children's interface just by looking at their drawings, uncovering indicators that would reveal the degree of success of the interaction. two groups of children aged between four and five years old were exposed to two versions of a computer game. in the regular version the game worked as expected, in the other version the mouse would stop functioning during random periods of the game play. the drawings made by the children after the game were analyzed by three evaluators to determine if they corresponded to the interaction with the regular or the broken game. the results show that in this specific study the decoding of children's drawings made after their interaction was clearly insufficient to assess the usability of the interface, and that further research is needed in this area.
exploring information spaces by using tangible magic lenses in a tabletop environment. to solve the challenge of exploring large information spaces on interactive surfaces such as tabletops, we developed an optically tracked, lightweight, passive display (magic lens) that provides elegant three-dimensional exploration of rich datasets. this can either be volumetric, layered, zoomable, or temporal information spaces, which are mapped onto the physical volume above a tabletop. by moving the magic lens through the volume, corresponding data is displayed, thus serving as a window into virtuality. hereby, various interaction techniques are introduced, which especially utilize the lens' height above a tabletop in a novel way, e.g. for zooming or displaying information layers.
tangible spin cube for 3d ring menu in real space. in this paper, we introduce a novel interface, the tangible spin cube, for experiencing a 3d ring menu in real space. it enables a tangible object-referenced 3d ring menu and its items' placement by using multi-marker tracking. also, it supports spin interaction using hall sensor-based spin detection for natural menu browsing. finally, we evaluate the performance of the current prototype's spin detection and show an example of a 3d ring menu application.
vibroglove: an assistive technology aid for conveying facial expressions. in this paper, a novel interface is described for enhancing human-human interpersonal interactions. specifically, the device is targeted as an assistive aid to deliver the facial expressions of an interaction partner to people who are blind or visually impaired. vibro-tactors, mounted on the back of a glove, provide a means for conveying haptic emoticons that represent the six basic human emotions and the neutral expression of the user's interaction partner. the detailed design of the haptic interface and haptic icons of expressions are presented, along with a user study involving a subject who is blind, as well as sighted, blind-folded participants. results reveal the potential for enriching social communication for people with visual disabilities.
more than a feeling: understanding the desirability factor in user experience. interest in understanding the "desirability" factor in user experience continues to grow while the use of post-test questionnaires to measure desirability continues to be problematic. microsoft created a toolkit to address desirability in studies, and their use of the product reaction cards from that kit was presented at conferences in 2002 and 2004. since then, however, little has been published about how others have used the cards to measure desirability. we began using the product reaction cards in 2006, and we report on the results in case studies from the past several years. we find that the cards prompt users to tell a rich and revealing story of their experience. triangulating these findings with post-test questionnaire data and direct observation strengthens the understanding of the desirability factor.
dragonfly: spatial navigation for lecture videos. dragonfly is an application designed for reviewing lecture recordings of mind map-structured presentations. instead of using a timeline slider, the lecture recording is controlled by selecting elements located at different positions on the map. hence, video time is controlled by navigating in space. a controlled experiment revealed that dragonfly reviewers performed 1.5 times faster in finding a specific scene of a lecture recording compared to reviewers that worked with quicktime player and a mind map printout.
critical point, a composition for cello and computer. critical point is written for solo cello and interactive computer music system with two to four channel sound system and computer animation. the cellist plays from a score, and the computer records and transforms the cello sounds in various ways. graphics and video are also projected. the computer-generated graphics are affected by audio from the live cellist. critical point is written in memory of the artist rob fisher.
the haptic wheel: design & evaluation of a tactile password system. authentication through passwords in public spaces (such as in atms) is susceptible to simple observation attacks, such as shoulder surfing, which can result in the password being compromised and ultimately the exposure of users to fraud and theft. haptic technology, which can present information non-visually to users, offers a potential solution to this problem through the creation of tactile passwords. situated in this space, this paper presents the design and initial evaluation of a novel haptic device, the haptic wheel, which displays tactons, or structured tactile messages, to enable password entry. it describes this device and the tactile passwords it supports in detail before presenting two short user studies. the results of these reveal that the chosen tactons are easily identifiable and that password entry times are significantly improved compared to previous systems based on haptic authentication.
touch your way: haptic sight for visually impaired people to walk with independence. haptic sight is a new interface idea providing immediate spatial information to visually impaired people in order to assist independent walking. the interface idea stems from a thorough investigation in which we studied visually impaired people's indoor walking behavior, decision making process, their unique concept of space, and information needs. the aim of this study is to identify an interface design and investigate an appropriate means of spatial information delivery.
cleanly: trashducation urban system. half the world's population is expected to live in urban areas by 2020. the high human density and changes in peoples' consumption habits result in an ever-increasing amount of trash that must be handled by governing bodies. problems created by inefficient or dysfunctional cleaning services are exacerbated by a poor personal trash management culture. in this paper we present cleanly, an urban trashducation system aimed at creating awareness of garbage production and management, which may serve as an educational plat-form in the urban environment. we report on data collected from an online survey, which not only motivates our research but also provides useful information on reasons and possible solutions for trash problems.
liquidtext: active reading through multitouch document manipulation. active reading, involving acts such as highlighting, writing notes, etc., is an important part of knowledge workers' activities. most computer based active reading support has sought to better replicate the affordances of paper. instead, this dissertation seeks to go past paper by proposing a more flexible, fluid document representation, controlled through gesture and multitouch input. formative evaluations revealed details about modern active reading behavior and early reactions to the prototype system. i discuss how these will inform the next design iteration, and current plans for a comparative study against other media.
the tiresias effect: feedforward using light versus temperature in a tangible user interface. in this paper we discuss how light and temperature information can be designed to affect feedforward in a tangible user interface (tui). in particular we focus on temperature, which has not been widely considered as a mode of information representation in feedback or feedforward. we describe a prototype that implements both information modes in a tui. finally, we outline a user study in which these modes are explored as feedforward coaching devices for a decision-making task. the expected outcomes are an understanding of the role of temperature as information for feedforward in tuis and a set of design guidelines for designers of tangibles working with these physical characteristics.
playwrite: end-user adaptable games to support adolescent mental health. adaptability to the needs of end-users has been identified as a key requirement for technologies designed to support mental health interventions. the playwrite system allows end users - mental healthcare professionals - to create and adapt therapeutic 3d computer games, which can then be used to support adolescent interventions. playwrite has enabled the creation of games that implement a range of theoretical approaches to mental health interventions and target a broad range of disorders. here we discuss the initial findings regarding the design, clinical evaluations and adaptation strategies used in playwrite.
a cross-device spatial workspace supporting artifact-mediated collaboration in interaction design. in this paper we present our approach to support artifact-mediated collaboration in interaction design. we argue that the extensive number and the diversity of artifacts created and reflected upon during collaborative design activities as well as transitions between physical and digital representations impose both a challenge and opportunity for supporting interaction design practice. the design principles for our experimental tool that we introduce within this paper are based on a cross-device spatial workspace synchronized by a shared design artifact repository within a computation-augmented design studio setting.
automating ui guidelines verification by leveraging pattern based ui and model based development. in large enterprises different teams work on different parts of a big software application. therefore, retaining user interaction paradigms and concepts becomes important. however, during the development of a large software product, these principles and paradigms get progressively diluted, due to trade-offs, differences in interpretation, communication errors and many other reasons. in order to remain true to design rationale and communicating them to a wider audience/consumers, often user interface (ui) style guide are created. the style guide attempts to sensitize and educate its consumers about design principles and document some of these design rationales for references. however, the usability, usage and adoption of these ui guidelines within an organization are topics frequently discussed and debated in several forums for years. post the 'design and definition phase' of software development lifecycle, ui designers are often required to do 'quality checks' as the uis get developed. despite painstakingly defining every interaction to its finest level of granularity, in practice the guidelines are often not followed or interpreted incorrectly. the method of manually inspecting the 'implemented' user interface for compliance to ui guidelines has the following pitfalls: highly effort and time consuming; outcome is often inaccurate, unreliable and sub-optimal in quality; findings are too late in the process to be fixed.; not an efficient process for tracking issues to resolution this case study talks about the challenges we faced with our ui style guide and how we tackled them. based on internal user research and design thinking we defined an approach of better integrating ui style guide into the software design and development process. we leveraged the benefits of pattern based ui approach and a model based development environment to achieve compliance to our ui guidelines by: providing tools to automate verification of ui guidelines in the model based development environment; redefining the development process to support ui verification early-on during the design and development process
know thyself: monitoring and reflecting on facets of one's life. people strive to gain better knowledge of themselves by collecting information about their behaviors, habits, and thoughts. personal informatics systems can help by facilitating the collection of personal information and the reflection on that information. these systems satisfy people's innate curiosity about themselves and encourage holistic engagement with one's life. development of such systems poses new challenges in human-computer interaction and opens opportunities for new applications and collaborations between diverse disciplines, such as design, life-logging, ubiquitous computing, persuasive technologies, and information visualization.
gcoll: enhancing trust in flexible group-to-group videoconferencing. in this paper we describe a quantitative study of a group-to-group videoconferencing environment called gcoll that provides a compromise between the need for preserving non-verbal cues and the requirements of low-cost and flexibility. we have compared the task process and outcome of participants interacting over an environment analogous to common commodity solutions, those using face-to-face communication, and groups communicating over gcoll. our results demonstrate that it is possible to design a group-to-group collaboration environment with modest technical requirements and low overall cost that still shows measurable advantages over the common environment in its ability to support trust in social dilemma games.
sequential art for science and chi. this paper illustrates our preliminary studies of new interactive tools that support the generation of sequential art for entertainment, learning and scientific discourse. in the first of two examples, primary school students document a practical science session through the creation of a photostory. in the second, participants in a study on the biological nature of thrill create a souvenir photostory by selecting images from a dvd. the paper is written in a comic-book format to further explore and highlight the communicative capabilities of the medium, one that can be visually attractive and facilitate rapid dissemination to a wide audience.
investigating an appropriate design for personal firewalls. personal firewalls are an important aspect of security for home computer users, but little attention has been given to their usability. we conducted semi-structured interviews to understand participants' knowledge, requirements, expectations, and misconceptions for personal firewalls. analysis of 10 interviews shows that different design decisions (i.e., level of automation, multiple profile settings) are appropriate for users with different levels of security knowledge and experience.
text 2.0. we discuss the idea of text responsive to reading and argue that the combination of eye tracking, text and real time interaction offers various possibilities to en- hance the reading experience. we present a number of prototypes and applications facilitating the user's gaze in order to assist comprehension difficulties and show their benefit in a preliminary evaluation.
challenges of software recontextualization: lessons learned. this paper describes the case of a complex and problem-ridden software development and deployment process: the implementation of a campus management system at a large university. based on an understanding of software development as recontextualization process on the technical, organizational, human, and task level, critical factors for success or failure are analyzed. results show that deficits in change management and organizational support account for a considerable amount of difficulties in the implementation process. furthermore, individual characteristics and commitment of the users involved play a major role. lessons learned for software introduction processes are discussed.
navigation for the blind through audio-based virtual environments. we present the design, development and an initial study changes and adaptations related to navigation that take place in the brain, by incorporating an audio-based environments simulator (abes) within a neuroimaging environment. this virtual environment enables a blind user to navigate through a virtual representation of a real space in order to train his/her orientation and mobility skills. our initial results suggest that this kind of virtual environment could be highly efficient as a testing, training and rehabilitation platform for learning and navigation.
contacts 3.0: bringing together research and design teams to reinvent the phonebook. we present a narrative of the design of contacts 3.0, a service and updated phonebook application on a mobile device that combines on-device communication with communication from online social networks to create a central hub for communication on the device. we discuss how research and design teams worked together to create design assets, technical architectures, and business cases around this concept.
gen x and ys attitudes on using social media platforms for opinion sharing. in this paper, we investigate opinion sharing attitudes and behaviors of 13 - 24 year olds on social media platforms. this research utilizes data from 34,514 survey respondents from users of the social media site, myyearbook. results show that those more engaged with multiple social media platforms are more willing to share opinions, seek opinions, and act on these opinions. however, there were statistically significant differences among users of myyearbook, myspace, facebook, and twitter. findings show that the reported demographic differences and social network service chosen have an effect on behaviors. these results have implications for businesses and others interested in advertising on these platforms, and researchers interested in investigating these populations.
design of a web-based therapist tool to promote emotional closeness. we describe progress using a user-centered design process to migrate a family therapy game to a web-based therapist tool, called familysense, that supports therapists creating part of the therapeutic game. using cards with questions about players' daily life and alternative answers considering their cultural context, the game gives parent and child awareness of each other. online design of different elements for the board, cards and communication provide an effective online therapy tool. four user-centered design process stages are presented including: design strategies, design questions, stakeholders, prototype and evaluation for each stage. the process has been successful for the migration, achieving an online game environment that shows strong potential for a family therapy tool.
cloudroom: a conceptual model for managing data in space and time. cheap broadband access and hosting infrastructure on the web have enabled many services that traditionally would have been deployed as local desktop applications to be hosted and accessed via the internet - in the cloud - from any network-connected device. this trend is referred to as cloud computing. the movement towards a network-based environment implies novel conceptual models for storing, searching and sharing digital information on the web and across devices. in this paper we describe our concept design for management and visualization of resources in the cloud computing paradigm. based on our insights from qualitative user studies, we design an environment which reflects the way people use spatial and temporal memory to organize and navigate through artifacts. we then discuss how our concept builds upon existing work and its implications for future work.
human performance modeling for all: importing ui prototypes into cogtool. ui designers use a variety of prototyping tools, from paper and pencil sketching, to drag-and-drop mock-up tools (e.g., balsamiq mockups), to sophisticated suites of modeling tools and toolkits (e.g., irise or dijit, the dojo gui toolkit ). many projects would benefit from quickly analyzing prototypes at an early stage without the effort of bringing in users for empirical tests. most analysis tools, however (e.g., autocww [1], bloodhound [2], and cogtool [4]), require prototypes to be in their own format, which forces the designer to re-do the prototypes in order to analyze them. our work is a step toward allowing the cogtool analysis tools to import from many different prototyping tools, so designers will have a path to quick usability analysis without changing the way they currently express their preliminary designs.
hci methods for including adults with disabilities in the design of champion. the demand for software, suitable for users with complex communication needs and other disabilities, is increasing. however, traditional hci design methods are not always suitable for these users. to address this, the champion project is piloting adapted methods in the development of a patient hospital profile for this user group. initial results show that users with cognitive and communication disabilities can be involved in participatory design. the challenge is now to develop meaningful evaluation methods for this group.
ben neill and bill jones: posthorn. this paper describes the interactive computer system used in posthorn, a multimedia composition which is performed on neill's self-designed instrument, the mutantrumpet. the technology and aesthetics of the system and the merging of acoustic instrument performance with software-based improvisation are explored in detail.
graphemes: self-organizing shape-based clustered structures for network visualisations. network visualisations use clustering approaches to simplify the presentation of complex graph structures. we present a novel application of clustering algorithms, which controls the visual arrangement of the vertices in a cluster to explicitly encode information about that cluster. our technique arranges parts of the graph into symbolic shapes, depending on the relative size of each cluster. early results suggest that this layout augmentation helps viewers make sense of a graph's scale and number of elements, while facilitating recall of graph features, and increasing stability in dynamic graph scenarios.
pim-mail: consolidating task and email management. traditional email clients are built with a "one-touch" model in mind that assumes an immediate action is performed once an email is read. however, some emails require a follow-up action or users decide to read them later, so they cannot be discharged immediately. we present a prototype to keep track of these email-associated tasks that works as a plug-in inside a traditional email client. besides providing flexible task management features, such as linking more than one message to a task to follow conversations, our system also supports exchanging tasks for collaborative work.
visualizing language use in team conversations: designing through theory, experiments, and iterations. one way to potentially help people develop effective teamwork skills is to visualize elements of their language use during team conversations. there are several challenges in designing such visualizations, such as how to balance attention between the conversation and the visualization and how much guidance to offer about appropriate behaviors. we discuss the design space around these questions in the context of groupmeter, a chatroom augmented with visualizations of language use. we generate and critique potential answers to these questions using prior theoretical and empirical work, then describe how the interface evolved and how our answers changed over a series of prototypes we deployed in experimental studies. we conclude with the lessons from our experience that could be used by designers of collaboration-enhancing systems.
gridorbit public display: providing grid awareness in a biology laboratory. we introduce gridorbit, a public awareness display that visualizes the activity of a community grid used in a biology laboratory. this community grid executes bioin-formatics algorithms and relies on users to donate cpu cycles to the grid. the goal of gridorbit is to create a shared awareness about the research taking place in the biology laboratory. this should promote contribu-tions to the grid, and thereby mediate the appropriation of the grid technology. gridorbit visualizes the activity in the grid, shows information about the different active projects, and supports a messaging functionality where people comment on projects. our work explores the usage of interactive technologies as enablers for the appropriation of an otherwise invisible infrastructure.
best of both worlds: improving gmail labels with the affordances of folders. gmail's filing system for email conversations is based around labels, which are more flexible and powerful than folders. with its original user interface, many users did not discover labels, and wondered why gmail had no folders. the gmail team redesigned the user interface for labeling to make it more discoverable and understandable, and to add the most useful functionality of folders. the new design works for the simple use case (a conversation with only one label), while still making the more complex use case (multiple labels) easily available. it has been launched to millions of users worldwide and has resulted in much higher adoption of labels, especially by new users of gmail.
astrojumper: motivating children with autism to exercise using a vr game. children with autism have shown substantial benefits from rigorous physical activity, however, it is often difficult to motivate these children to exercise due to their usually sedentary lifestyles. to address the problem of motivation, we have developed astrojumper, a stereoscopic virtual reality exergame which was designed to fit the needs of children with autism. we use electromagnetic trackers and a 3-sided cave to present virtual space-themed stimuli to the user, who must use physical movements to avoid collisions and gain points. we can use astrojumper not only to motivate exercise, but to evaluate the different ways people with and without autism interact with an exercise tool. preliminary playtesting of astrojumper has been positive, and we plan to run an extensive evaluation assessing the effectiveness of this system on children with and without autism.
snap and match: a case study of virtual color cosmetics consultation. in this paper we describe an imaging based virtual color consultation system that automatically recommends cosmetics appropriate for users' skin tone based on user's photograph. this system is intended for commercial use to address the problem of color selection of cosmetic foundation. based on surveys and semi-structured interviews we have verified that visual selection of color foundation cosmetics by consumers is error prone, and the results of our study indicate that both mobile and kiosk touch points are essential to cover the entire target population (women of all ages) since we identified technical vs. social comfort, accuracy vs. convenience and social vs. individual parameters that play a huge role in the usage and adoption of such personal services for women.
ifeel_im: innovative real-time communication system with rich emotional and haptic channels. the paper focuses on a novel system ifeel_im! that integrates 3d virtual world, intelligent component for automatic emotion recognition from text, and innovative affective haptic interfaces providing additional nonverbal communication channels through simulation of emotional feedback and social touch. the motivation behind our work is to enrich social interaction and emotional involvement of the users of communication media. ifeel_im! users can not only exchange messages but also emotionally and physically feel the presence of the communication partner.
skchi: designing sketch recognition interfaces. sketch recognition user interfaces currently treat the pen in the same manner as a mouse and keyboard. the aim of this workshop is to promote thought and discussion about how to move beyond this to create natural and intuitive pen-based interfaces. to this end, the workshop will include panel discussions, group discussions, and even an instructional session on drawing sketches.
supporting medical communication with a multimodal surface computer. this research explores the utility of a multimodal surface computer for supporting medical communication between older adults and health care providers. research involves a field study of health care communication practices, the design of a multimodal surface computer application, and an in-context evaluation of the technology at a local retirement community.
e-government: services for everyone, everywhere, eventually. online provision of government services has great potential for reducing costs, improving service, and increasing citizen participation in government, but it has not yet achieved this potential. a panel of e-government experts from the u.s. and u.k. will assess the status of e-government, discuss obstacles that keep it from being ubiquitous and accessible, offer solutions, and answer audience questions. some of the panelists work in government, some work in consultancies that assist government agencies, and some are ict public policy experts.
grip sensing in smart toys: a formative design method for user categorization. modern toys are interactive, motivate play, and can be used to aid detection and analysis of play behavior. our research has investigated the use of wireless sensors embedded in toys to aid in the automatic detection and analysis of children's playtime activities. in order to guide age appropriate interaction style and facilitate data collection (adult vs. child), we need to identify who is playing with the toy. this becomes especially challenging when these smart toys are deployed into everyday play areas. in this paper we describe a formative design methodology to inform the creation of a smart toy that could allow differentiation between a child and adult. we also describe an evaluation of our prototype design from a pilot study that shows promise for future research.
arranging touch screen software keyboard split-keys based on contact surface. touch screen devices, which have become ubiquitous in our daily lives, offer users flexible input and output operations. typical operation methods for touch screen devices include the use of a stylus or a finger. a touch screen user can select a stylus or finger depending on the user's situation and preference. in this paper, we propose a dynamic method of assigning symbols to keys for a software keyboard on a touch screen device. this method provides flexible adjustment to both the stylus operation and finger operation.
designing and evaluating voice-based virtual communities. voice-based virtual communities offer new possibilities for information dissemination and sharing for billions of users who lack access to internet-connected pcs. as interaction is only through voice, these systems are subject to different design constraints than web-based social software. through lab experiments and fieldwork, we have identified three key design challenges for voice-based virtual communities: supporting threaded conversations; indexing and searching content; and managing identity. we discuss each of these issues and propose approaches to address them. we also present plans to evaluate the impact of voice-based virtual communities on knowledge access and sharing in rural india.
generating default privacy policies for online social networks. default privacy policies have a significant impact on the overall dynamics and success of online social networks, as users tend to keep their initial privacy policies. in this work-in-progress, we present a new method for suggesting privacy policies for new users by exploring knowledge of existing policies. the defaults generation process performs a collaborative analysis of the policies, finding personalized and representative suggestions. we show how the process can be extended to a wide range of domains, and present results based on 543 privacy policies obtained from a live location-based social network. finally, we present a user interaction model that lets the user retain control over the default policies, allowing the user to make knowledgeable decisions regarding which default policy to take.
pico-ing into the future of mobile projector phones. ten years ago we were on the verge of having cameras built into our mobile phones, but knew very little about what to expect or how they would be used. now we are faced with the same unknowns with mobile projector phones. this research-in-progress seeks to explore how people will want to use such technology, how they will feel when using it, and what social effects we can expect to see. this paper describes our two-phase field investigation, with results and design recommendations from its first, experience-sampling phase.
on the retrospective assessment of users' experiences over time: memory or actuality? an alternative paradigm to longitudinal studies of user experience is proposed. we illustrate this paradigm through a number of recent tool-based methods. we conclude by raising a number of challenges that we need to address in order to establish this paradigm as a fruitful alternative to longitudinal studies.
the emoti-chair: an interactive tactile music exhibit. in this abstract, we present the emoti-chair, a sensory substitution system that brings a high resolution audio-tactile version of music to the body. the system can be used to improve music accessibility for deaf or hard of hearing people, while offering everyone the chance to experience sounds as tactile sensations. the model human cochlea (mhc) is the sensory substitution system that drives the emoti-chair. music can be experienced as a tactile modality, revealing vibrations that originate from different instruments and sounds spanning the audio frequency spectrum along multiple points of the body. the system uses eight separate audio-tactile channels to deliver sound to the body, and provides an opportunity to experience a broad range of musical elements as physical vibrations.
toward an ecological sensibility: tools for evaluating sustainable hci. we are developing evaluation tools that help sustainable hci researchers to contribute to the overall project of achieving sustainability. in this paper we argue for the importance of broadening sustainable hci evaluation beyond traditional hci evaluation. we note the widespread phenomenon of unintended environmental consequences, largely overlooked thus far in sustainable hci evaluation. we discuss three categories of tools - principles, heuristics, and indices - that could facilitate evaluation of sustainable hci projects, mainly by operationalizing definitions of sustainability. we suggest that sustainable hci research could become more relevant by developing evaluations that link to understandings of sustainability beyond hci, and more 'scientific' by developing more systematic evaluations, while acknowledging that many ways of knowing play important roles in both sustainability and hci. our next steps include developing these tools for sustainable hci evaluation and applying them to published research.
the effect of avatar realism of virtual humans on self-disclosure in anonymous social interactions. in this paper, we illustrate progress in research designed to investigate interactants' self-disclosure when they communicate with virtual humans or real humans in computer-mediated interactions. we explored the effect of the combination of avatar realism and interactants' anticipated future interaction (afi) on self-disclosure in emotionally engaged and synchronous interaction. we primarily aimed at exploring ways to promote interactants' self-disclosure while securing their visual anonymity, timely nonverbal feedback of virtual humans, when interactants anticipate future interaction. the research examined interactants' self-disclosure through measuring their verbal behaviors. the preliminary findings indicated that interactants revealed greater intimate information about themselves in interactions with virtual humans than with real humans. however, interactants' afi did not affect their self-disclosure, which does not correspond to the results of previous studies using text based interfaces.
communication and computing in health facilities of southwest uganda. mobile phones are often pitched as the solution for africa's development. this study examines the social changes entailed by the introduction of new technologies into a health subsidy program, and compares mobile phones and netbooks side by side in southwest uganda as potential health information management devices for private health facilities.
leveraging gesture and voice data to improve group brainstorming. we seek to investigate how co-located group brainstorming could be enhanced through computational tools that leverage gestures and voice cues. to pursue this goal we are developing a computer mediated brainstorming environment that utilizes reality-based interaction techniques and sensor-driven hidden markov models (hmms) tracking group engagement to computationally augment existing brainstorming practices. in this paper, we report the results of a preliminary user study of brainstorming practices that indicate that gesture and voice data can serve as signals for group brainstorming success.
communicating software agreement content using narrative pictograms. we present narrative pictograms, illustrative diagrams designed to convey the abstract concepts of software agreements. narrative pictograms arose out of a need to create software agreements that are comprehensible without written language. we first present example diagrams designed to describe the data collection policies of research software, and the composition rules used to create them. we then present our design process and lessons learned during design. finally, we present results from an evaluation based on the iso 9186-1 test for graphical symbols.
wearable-object-based interaction for a mobile audio device. in this paper, we explore the possibilities of providing miniaturized audio players with gesture control capabilities that are based on wearable objects. we selected thirteen wearable objects and used them as interaction surfaces. we used user-centered design methods to collect interaction gestures suited for play, stop, volume up, volume down, previous song, and next song functions. the characteristics and possibility of these interaction gestures are also discussed.
photosense: emergent semantics based approach to image annotation. tagging of images using descriptive keywords (tags), contributed by ordinary users, is a powerful way of organizing them. however, due to the richness of the image content, it is often difficult to choose tags that best describe the content of the image to the viewing audience and ensure access to the image. in this paper, we present a novel tagging framework based on the theory of emergent semantics to assist the user in the tag selection process. our idea is to enrich the current "looking at" experience of tagging with the "looking for" experience of searching. we describe the design of our approach along with a preliminary user study conducted with a prototype flickr application.
hci on the move: methods, culture, values. as hci is taken up across different cultures, its methods have typically been presumed to be culturally universal. though evidence suggests that they are not, dimensions of cultural specificities of hci methods are not understood. through detailed fieldwork with design practitioners in delhi, india, i propose to develop a framework for understanding tacit material, cultural, and value commitments in hci design methods, opening up possibilities for alternate conceptions of design.
interaction techniques for hybrid piles of documents on interactive tabletops. piling is a highly common activity for the casual organization of documents. today's tabletops do not offer sufficient support for piling, particularly in hybrid set-tings where both digital documents and paper documents are used on the same surface. we contribute several techniques for interacting with hybrid piles of printed and digital documents on tabletops. by employing a soap bubble metaphor and by using paper as a tangible control for the hybrid pile, these allow easy creating and rearranging piles while maintaining the flexibility of traditional paper piles.
contravision: presenting contrasting visions of future technology. how can we best explore the range of users' reactions when developing future technologies that may be controversial, such as personal healthcare systems? our approach - contravision - uses futuristic videos, or other narrative forms, that convey both negative and positive aspects of the proposed technology for the same scenarios.
synthesizing meaningful feedback for exploring virtual worlds using a screen reader. users who are visually impaired can access virtual worlds, such as second life, with a screen reader by extracting a meaningful textual representation of the environment their avatar is in. since virtual worlds are densely populated with large amounts of user-generated content, users must iteratively query their environment as to not to be overwhelmed with audio feedback. on the other hand, iteratively interacting with virtual worlds is inherently slower. this paper describes our current work on developing a mechanism that can synthesize a more usable and efficient form of feedback using a taxonomy of virtual world objects.
chi 2010 engineering community sig: the role of engineering work in chi. the engineering community faces a number of serious challenges around its role in the larger chi community and its contribution to chi-sponsored conferences. this sig is its forum to identify key issues and begin developing positions to address them.
re-connect: designing accessible email communication support for persons with aphasia. in this paper we present some preliminary outcomes concerning the design of an email communication tool for persons with expressive aphasia. the purpose of our design is to make email accessible for aphasics. it is based on interviews with persons with aphasia and their partners and has been verified with a speech therapist. our user studies confirm that aphasics find current email communication systems too challenging to use. the most obvious barrier is the lack of writing support. based on these findings we designed an email application that should be simpler to use than existing solutions and that moreover supplies language support.
designing and evaluating affective aspects of sociable media to support social connectedness. the use of sociable media for supporting social connectedness has been a serious subject of study for researchers and designers in recent years. social connectedness is considered to be the momentary experience of belongingness and relatedness with others. particular user groups may benefit from support in social connectedness, such as elderly or divorced parents and their children. several research projects have made efforts to support social connectedness. however, there have been few formal studies into the factors affecting connectedness. also, the way in which social connectedness has been measured in studies to date is diverse and often not grounded in psychological theory. this shows a need for more elaborate investigation in how social connectedness can be measured, what types of content could be shared between users, and which interactions should be provided by a system, when aiming for social connectedness. this should lead to guidelines and an ontology of elements to help and inspire designers of social connectedness systems.
gender and role differences in family-based healthy living networks. we have recently witnessed a tremendous increase in popularity and growth of online social networks. social support and family involvement can play an important supportive role in health management. an increasing number of family members are establishing online social networking relationships with their families. this trend poses new research questions on effectively accommodating family members in online social networks. family members themselves often have very different requirements based on their gender and family role. there is little research on the design of family-oriented social networking applications. in order to fill this research gap and investigate the impact of social and family relationships in online social networks, we are developing a healthy living online social application to support families in adopting healthy lifestyles. this paper reports the findings of a user study aimed at understanding gender- and role-based characteristics and differences in family-based healthy living social networks. the study shows that female users play a major role in leading the usage of the social technology; parents remain conscious of and concerned about their family's health as they interact with the social technology; and the social technology should support fun, especially for children.
natural user interfaces: the prospect and challenge of touch and gestural computing. natural user interfaces show great promise to define new and potentially large niches of interactive computing. the promise of natural computing interfaces (touch and gesture) stems from at least two sources -- the prospect of touch and gestural computing becoming as ubiquitous as currently dominant paradigms (e.g. gui.) and technical breakthroughs. however, this new field of research and commercial development faces significant challenges. for example the challenge of developing a common terminology and framework while fostering innovation and creativity. the workshop will begin the process of addressing some of the challenges by (1) enumerating them, (2) listing potential ways to address them. as such our aim is to foster the evolution of nui community of researchers and practitioners.
senior-friendly technologies: interaction design for senior users. the elderly represent a valid group of users who can potentially benefit greatly from engaging with technology, such as healthcare systems or playing digital games. yet, less attention has been given to the significance of senior citizens as technology users, as compared to the common younger population. in an effort to fill in the gap, this workshop aims to investigate the design of technology for senior citizens. to provide for more focused, thus more productive discussion, we will use elderly mobile phone games as a case in point here. the overarching objective is to understand what can help to make for better and more meaningful use of interactive applications and technology by the elderly, for instance, games on the mobile phone.
green tracker: a tool for estimating the energy consumption of software. the energy consumption of computers has become an important environmental issue. this paper describes the development of green tracker, a tool that estimates the energy consumption of software in order to help concerned users make informed decisions about the software they use. we present preliminary results gathered from this system's initial usage. ultimately the information gathered from this tool will be used to raise awareness and help make the energy consumption of software a more central concern among software developers.
what makes a good design critic?: food design vs. product design criticism. this panel will bring together leading food design and product design critics. the panelists will include: a leading atlanta-based food critic and writer, a food stylist, a restaurant architect & designer, and a well-known product design critic familiar with the field of user experience. together, the panel will compare and contrast how design experts from these two disciplines provide design criticism, and whether there are any novel learning points from each perspective.
triggerhunter: designing an educational game for families with asthmatic children. in this paper, we propose a collaborative and educational game for families with asthmatic children to improve their health. this paper describes design approaches and specifications of a game called triggerhunter that enables asthmatic children to see asthma triggers in their home environment through an augmented reality technology. the goal of designing a game for tracking asthma triggers in the real world is to educate asthmatic children and their parents about triggers that may cause asthma attacks or worsen symptoms. by providing tailored learning experience that is enjoyable, this interactive game aims to increase awareness of asthma triggers and changes behaviors as to improve pediatric asthma management.
a task-focused approach to support sharing and interruption recovery in web browsers. over the last two decades a vast number of services have moved online, and many new services have been created. previous work shows that many users are overloaded by the number of webpages they use simultaneously. we introduce tabfour, a prototype web browser which integrates three features that address the design requirements identified in an initial design study. webpages can be grouped into tasks, providing a unified target for resumption after an interruption. tasks and pages can be annotated, supporting resumption after longer intervals. finally, tasks can be shared through a simple yet novel web-service, allowing users to share groups of webpages more easily than with existing tools.
artifacts in design: representation, ideation, and process. artifacts-representations that express properties or captured information-can serve to inspire, represent, and manage the decisions made throughout the design process. this workshop will explore how these artifacts are created, used, and reused during design projects, toward understanding the overall impact on the larger discipline of design. through active engagement with novel design artifacts and methods, workshop participants will examine, categorize, and evaluate various design artifacts.
docblocks: communication-minded visualization of topics in u.s. congressional bills. us federal legislation is a hot topic for discussion and advocacy on the web. yet legislative bills present a significant challenge for both experts and average citizens to navigate and understand. to explore solutions to this problem, we have created docblocks: a prototype visualization and website that enables users to explore the content of congressional bills and communicate their findings to others. our technique enables us to take any document from a categorized corpus, classify its sections, and visualize its topic structure. with the launch of this service, we hope to provide a valuable tool for open governance and learn from our users at this critical intersection of visualization, advocacy, social software, and civil society.
sequencebook: interactive paper book capable of changing the storylines by shuffling pages. in this paper, the author proposes sequencebook, an interactive picture book system, which consists of a paper book with very thin ic tags embedded in each page and an rfid antenna. this system uses a traditional paper book as an interface and realizes natural interface that keeps the affordance of traditional book and thus smoothly prompts users to experience its contents by just flipping pages in the same way as they read an ordinary book. another important feature of the system is that users can change its storyline as they like. the system is designed just as like a bookbinder so that users can easily shuffle pages and make several patterns of stories.
a novel way to conduct human studies and do some good. in this paper the authors describe a novel way to conduct large-scale human studies achieving the maximum outreach and impact with the minimum cost. an iphone health application, 'walk n' play', was developed and released for free in the app store. the application measures calories spent due to walking activities through the iphone's accelerometer. it is a real-time awareness tool that helps people to keep their sedentariness in check. furthermore, it uses motivational mechanisms based on buddy support/competition and social networking to increase daily physical activity. the anonymous data gathered from thousands of users around the world, reveal patterns of human behavior at a resolution and scale not feasible before.
interface-to-face: sharing information with customers in service encounters. customers are often deprived of valuable information during face-to-face service encounters. we discuss such situations in the context of the "incidental user" and highlight the associated problems. a theoretical framework is proposed, according to which sharing information with customers would significantly enhance the service experience both by inspiring trust and by contributing to the effectiveness of the service encounter. we discuss possible hci-related solutions to this challenge, including the use of a double screen approach as a means for presenting information to customers and enhancing collaboration between service providers and their customers.
cultural similarities and differences in user-defined gestures for touchscreen user interfaces. as the first phase of a two-phase project, the international usability partners (iup; http://www.international-usability-partners.com/) conducted a study in nine different countries to identify cultural similarities and differences in the use of gestures on small, handheld, touchscreen user interfaces. a total of 340 participants in the study were asked to define their own gestures for 28 common actions like "zoom" and "copy" on a custom-constructed gesture recorder that simulated a handheld touchscreen device. actions were described pictorially by showing participants a "before" screen and an "after" screen to clarify the exact context for each action. initial analysis suggests four primary findings. the first is that there is generally a high level of agreement across cultures. one exception, however, is the use of symbolic gestures; chinese participants created significantly (p phase two of this research effort will be to present the most common three to five user-defined gestures for each action to a large number of participants and ask them to select the gesture that they believe to be the most intuitive gesture for that action.
rumu editor: a non-wysiwyg web editor for non-technical users. this paper discusses rumu editor, a prototype of a non-wysiwyg web editor for non-technical users. users often struggle with wysiwyg web editors, and the code produced is notoriously bad. rumu aims to improve the user experience and the resulting websites by providing a simple semantic markup language for the user, changing how styles are applied, simplifying and automating complex aspects of web design, and enabling users to make responsible choices. i conducted usability studies to compare rumu to iweb, a wysiwyg editor, the results of which suggest that users are more satisfied and successful with rumu. in a case study, two users created real personal websites using iweb or rumu. in a blind survey, web designers preferred the websites and source generated by rumu.
designing a pen-based flashcard application to support classroom learning environment. pen-based flash cards application ("application") offers the flexibility of handwritten input while benefiting a wide set of users to increase their memory retention. it is particularly useful in learning mathematics where typing the material using a keyboard can be difficult. in this study, we describe the observations and major findings in a two-year case study in an eighth-grade geometry class. we found that this application may enhance teacher-student interaction, increase autonomy in students for self-guided learning, and encourage collaborative learning.
visible and controllable rfid tags. radio frequency identification (rfid) tags containing privacy-sensitive information are increasingly embedded into personal documents (e.g., passports and driver's licenses). the problem is that people are often unaware of the security and privacy risks associated with rfid, likely because the technology remains largely invisible and uncontrollable for the individual. to mitigate this problem, we developed a collection of novel yet simple and inexpensive alternative tag designs to make rfid visible and controllable. this video and demonstration illustrates these designs. for awareness, our tags provide visual, audible, or tactile feedback when in the range of an rfid reader. for control, people can allow or disallow access to the information on the tag by how they touch, orient, move, press, or illuminate the tag (for example, figure 1 shows a tilt-sensitive rfid tag).
early explorations of cat: canine amusement and training. cross-species computer applications have a history of blended science and humor, despite the real potential for improving the canine-human bond. new activities available to humans in the electronic age can be used to improve this bond. by using a serious games approach, this project motivates the human to spend time with their canine in healthy and informative ways. an iterative design process, with a canine behavior expert, has produced a prototype focused on calm, healthy and enjoyable games for both canine and human. formative results and guidelines are reported, as are current and future directions.
cultural versioning of mobile user experience. most current user interfaces and services are based on psychological and social models drawn from european and american research traditions. after identifying preferences and value orientations in different cultures from a series of user studies, this research tries to form a theoretical base for understanding local cultures and designing different user experiences for people from different cultures. the goal of this research is to explore cost-effective strategies for developing multiple versions of user interfaces and services for different cultures, perhaps through cultural templates or through special versioning tools.
the proximity toolkit and viconface: the video. proximity toolkit is a toolkit that simplifies the exploration of interaction techniques based on proximity and orientations of people, tools, and large digital surfaces. viconface is a playful demonstration application built atop of this toolkit. a cartoon face on a large display tracks a person moving around it, where it visually and verbally responds to that person's proximity, orientation and wand use. the accompanying video illustrates all this in action.
kairos chat: a novel text-based chat system that has multiple streams of time. in this paper we propose a novel chat system named "kairos chat" that has multiple streams of time whose velocities are different. a pilot study shows that users spontaneously use the different streams for different types of messages without any concrete instructions on how to use the streams.
classifying web queries by topic and user intent. in this research, we investigate a methodology to classify automatically web queries by topic and user intent. taking a 20,000 plus web query data set sectioned by topic, we manually classified each query using a three-level hierarchy of user intent. we note that significant differences in user intent across topics. results show that user intent (informational, navigational, and transactional) varies by topic (15 to 24 percent depending on the category). we then use this manually classified data set to classify searches in a web search engine query stream automatically, using an exact match followed by n-gram approach. these approaches have the advantage of being implementable in real time for query classification of web searches. the implications are that a search engine can improve retrieval performance by more effectively identifying the intent underlying user queries.
evaluating realistic visualizations for safety-related in-car information systems. this paper reflects on the currently observable evolution of in-vehicle information systems towards realistic visualization. as compared to common schematic maps, hi-fidelity visualizations might support an easier recognition of the outside world and therefore better contribute to driving safety. on the other hand, too much visual detail might distract from the primary driving task. we present an experimental car-simulator study with 28 users, in which the in-car hmi was systematically manipulated with regard to representation of the outside world. the results show that perceived safety is significantly higher with 1:1 realistic views than with conventional schematic styles, despite higher visual complexity. furthermore, we found that the more demanding the safety recommendation on the hmi, the more realistic visualization are perceived as a valuable support.
using word spotting to evaluate roila: a speech recognition friendly artificial language. in our research we argue for the benefits that an artificial language could provide to improve the accuracy of speech recognition. we briefly present the design and implementation of a vocabulary of our intended artificial language (roila), the latter by means of a genetic algorithm that attempted to generate words which would have low likelihood of being confused by a speech recognizer. lastly we discuss the methodology and results of two word spotting experiments that were carried out to evaluate if indeed the vocabulary of roila achieved better recognition than english. our results reveal that our initial vocabulary was not significantly better than english but when the vocabulary was modified to include cv-type words only, the vocabulary nearly significantly outperformed english.
only one fitts' law formula please! the hci community uses at least four different formulas for fitts' law. each of them is derived from shannon's information theory. this raises the question which formula is wrong and which is right. while the hci community on the one hand gives free choice for the formula, it demands good statistical values for the evaluation on the other hand. from a scientific point of view this situation is not satisfying.
hybrid groups of printed and digital documents on tabletops: a study. this paper presents an exploratory study investigating how physical and digital documents are used in combination on tabletops. our results identify hybrid piles as the most common grouping concept and show that users willingly occlude digital documents with physical paper. these findings have considerable impact on the design of novel hybrid interaction techniques, which we sketch at the end of this paper.
counterlines: a duet for piano and pen display. this paper describes three introductory studies for an intermedia performance counterlines - a duet for disklavier and wacom cintiq, in which both performers generate audiovisual materials that relate to each other contrapuntally. in the described studies the pianist generates graphic lines while playing music and the graphic performer generates piano lines by drawing. to reinforce the clarity of relationships between visual contours all graphic elements are projected on a single screen. the paper discusses our approach to audio-visual interfacing and intermedia composition.
tavr: temporal-aural-visual representation for representing imperceptible spatial information. designing a technology tool to support learners better conceptualize the imperceptible scale has been a challenging research topic for learning technology researchers. because of the limits in human visual sense and cognitive capacity, visual representations have not been successful in representing such scales. to address this issue, i designed a computer-based simulation that incorporates a multimodal (temporal-aural-visual) representation (tavr). in my dissertation i assess the successfulness of tavr and potential design options.
exploring the design space in technology-augmented dance. in this paper we describe the process and technology behind a dance performance, "bodies/antibodies," that will be presented at chi 2010. this performance is part of an ongoing dance.draw project at the university of north carolina at charlotte, which investigates lightweight methods for integrating dance motion with interactive visualizations and enhancing audience interaction with dance.
an utterance attitude model in human-agent communication: from good turn-taking to better human-agent understanding. in this study, we discuss a novel expression and comprehension model of the utterance attitude of speaking/hearing during conversations. humans who participate in conversation display these implicit and explicit attitudes, and use them to understand the other participants in advance of turn-taking. we design abstract animated agents that mimic human turntaking in conversations to confirm the validity of our model. the subjective evaluation tests show that the expressions of the agents are understandable. the model may facilitate turn-taking in human-agent interaction.
multi-lifespan information system design in post-conflict societies: an evolving project in rwanda. in this paper we report on our early-stage research and design efforts to provide rwandans with access to and reuse of video interviews from the international criminal tribunal for rwanda. more generally, we investigate methods and designs that can be deployed successfully within a post-conflict political climate concerned about recurring violence. this work: (1) directly supports the rwandan people in their efforts to achieve justice, healing and reconciliation; (2) provides the hci community with methods and approaches for undertaking design in post-conflict situations; and (3) describes the first empirical exploration of multi-lifespan information system design.
gestalt theory, engagement and interaction. this paper presents a design exploration research project in which principles derived from gestalt theory were applied as a framework for guiding human-computer interaction (hci). the analysis contained within examines how a gestalt approach to hci can be used to enhance engagement and promote user interaction. the concepts discussed in this analysis are supported by a series of informal user observations.
automotive user interfaces: human computer interaction in the car. cars have become complex interactive systems. mechanical controls and electrical systems are transformed to the digital realm. it is common that drivers operate a vehicle and, at the same time, interact with a variety of devices and applications. texting while driving, looking up an address for the navigation system, and taking a phone call are just some common examples that add value for the driver, but also increase the risk of driving. novel interaction technologies create many opportunities for designing useful and attractive in-car user interfaces. with technologies that assist the user in driving, such as assistive cruise control and lane keeping, the user interface is essential to the way people perceive the driving experience. new means for user interface development and interaction design are required as the number of factors influencing the design space for automotive user interfaces is increasing. in comparison to other domains, a trial and error approach while the product is already in the market is not acceptable as the cost of failure may be fatal. user interface design in the automotive domain is relevant across many areas ranging from primary driving control, to assisted functions, to navigation, information services, entertainment and games.
the role of tangible technologies for special education. the physicality and multisensory aspect of tangibles make them particularly suitable for children with special needs. to date, however, there is little empirical research on tangibles for supporting cognition and learning difficulties. this research aims to investigate the role of tangibles in supporting attention, verbal memory and abstract thinking of children with learning needs, particularly when collaborating with peers.
musicjacket: the efficacy of real-time vibrotactile feedback for learning to play the violin. this research investigates the potential for vibrotactile feedback to enhance motor learning in the context of playing the violin. a prototype has been built which delivers vibrotactile feedback to the arms to indicate to a novice player how to correctly hold the violin and how to bow in a straight manner. this prototype was tested in a pilot user study with four complete beginners. observations showed improvements in three of the four players whilst receiving the feedback. we also discuss the pros and cons of using negative feedback to enhance learning.
whole body interaction 2010. in this workshop we explore the notation of whole body interaction. we bring together different disciplines to create a new research direction for study of this emerging form of interaction.
researcher-practitioner interaction. this workshop explores whether problems exist between hci researchers and the practitioners who are consumers of research - and, if so, will endeavor to identify the dimensions of the problems and propose possible solutions. on the one hand, the workshop aims to articulate factors that may render the research literature inaccessible or irrelevant to practitioners and to suggest potential improvements. on the other hand, the workshop also aims to learn from researchers how their research could benefit from practitioner input.
3d user interface combining gaze and hand gestures for large-scale display. in this paper, we present a novel attentive and immersive user interface based on gaze and hand gestures for interactive large-scale displays. the combination of gaze and hand gestures provide more interesting and immersive ways to manipulate 3d information.
ilight: information flashlight on objects using handheld projector. handheld projectors are novel display devices developed recently. in this paper we present ilight, information flashlight, which is based on the ongoing research project guiding light [9] using a handheld projector. by using a handheld projector with a tiny camera attached on it, system can recognize objects and augment information directly on them. ilight also present a interaction methodology on handheld projector and a novel real-time interactive experiences among users.
bridging the digital divide one tweet at a time: twitter-enabled devices for family communication. we present two devices designed to facilitate information transfer and communication between family members, particularly older adults and their younger relatives. central to both devices is their use of twitter to send updates and messages to relatives and friends. in this paper, we report on the design of the system and share results from preliminary focus groups.
health shelf: interactive nutritional labels. "healthy shelf" is an interactive nutritional label system. user-centered design process was used to create the labels with html and javascript for deployment on kiosks attached to supermarket shelves. users change the serving size on the nutritional labels and the labels then calculate nutritional values. the interactive labels also display comparisons of nutritional values. we evaluated a prototype of the system and found that participants liked the idea of using interactive nutritional labels while shopping and they make more accurate serving size.
using obstructed theatre with child designers to convey requirements. this paper describes the use of obstructed theatre as a novel design method for the elicitation of ideas from children for the design of a new mobile product. obstructed theatre has previously been used, in this same context with adults, but this is the first paper that outlines its use with children. the paper describes the initial ideas for the script for the theatre and evaluates its use. it is shown that the method can be useful and it specifically conveyed the idea of portability and mobility but was less effective at conveying the more complex interactive ideas. specifically the paper outlines the origins of the method, presents some reflection on the usefulness of the method and suggests how it can be used with other contexts.
augmented reality, surface style: extending displays through fiber optics. most displays can show information only on a planar surface. in some cases it is advantageous to extend the display into the third dimension or inside objects on the surface. for instance, a person on one side of an interactive table might want to read a message displayed privately to themselves. this paper describes a novel use of fiber optics to take the light from a planar surface and extend it to display into the third dimension, both vertically and in any direction that the fiber optic is bent.
cognitive models of user behavior in social information systems. the widespread popularity and adoption of social information systems ranging from social networking systems to social book marking systems has resulted in an increased research focus on studying user interactions in such systems. recent research literature has reported on analysis of large datasets of logs of social interactions as a way to describe the structure of these systems and to characterize individual behavior. there is significantly limited research on cognitive behavior of individual users in social information systems. research on individual behavior can help us develop nuanced perspectives of social information use and can provide insights for developing more effective systems for users.
the biomuse trio. the biomuse trio is computer chamber music for violin, computer and biomuse. the violinist performs conventionally; the only sensor used is a microphone to capture its sound. the computer produces all of its sound through processing of violin sounds captured during performance. the performance of the computer sound is controlled by the gestures of the biomusician, measured with on-body sensors. the musical composition consists of precisely sequenced events for violinist and biomusician, as well as performance environments that are explored through improvisation.
motionbeam: designing for movement with handheld projectors. in this paper we present a novel interaction metaphor for handheld projectors we label motionbeam. we detail a number of interaction techniques that utilize the physical movement of a handheld projector to better express the motion and physicality of projected objects. finally we present the first iteration of a projected character design that uses the motionbeam metaphor for user interaction.
input precision for gaze-based graphical passwords. click-based graphical passwords have been proposed as alternatives to text-based passwords, despite being potentially vulnerable to shoulder-surfing, where an attacker can learn passwords by watching or recording users as they log in. cued gaze-points (cgp) is a graphical password system which defends against such attacks by using eye-gaze password input, instead of mouse-clicks. a first user study revealed that cgp's unique use of eye tracking required special techniques to improve gaze precision. in this paper, we present two enhancements that we developed and tested: a nearest-neighbour gaze-point aggregation algorithm and a 1-point calibration before each password entry. we found that these enhancements made a substantial improvement to users' gaze accuracy and system usability.
best practices in longitudinal research. this sig will help to identify best practices for longitudinal research through a collaborative discussion of methods and metrics for collecting and analyzing user data over time. this is the fifth event in an ongoing effort by the facilitators to enhance our current body of knowledge about longitudinal research.
indian cultural effects on user research methodologies. modern user research techniques such as think aloud usability testing were mainly designed and refined in europe and north america. these techniques perform substantially differently in traditional indian culture due to the participants' perception of social status differences between them and the moderator(s). understanding and controlling these effects can make the difference between a successful research project and one that gains little reliable data. examples are cited from india-based user testing and open-ended field research by kern communications for nokia's ovi mail and nokia life tools services in january 2009.
on improving application utility prediction. when using the computer, each user has some notion that "these applications are important" at a given point in time. we term this subset of applications that the user values as high-utility applications. identifying these high-utility applications is critical to the fields of task analysis, user interruptions, workflow analysis, and goal prediction. yet, existing techniques to identify high-utility applications are based upon task identification, conglomeration of related windows, limited qualitative observation, or common sense. our work directly associates measurable computer interaction (cpu consumption, window area, etc.) with the user's perceived application utility. in this paper, we present an objective utility function that accurately predicts the user's subjective impressions of application importance. our work is based upon 321 hours of real-world data from 22 users (both professional and academic) improving existing techniques by over 53%.
real-time eye gaze tracking with an unmodified commodity webcam employing a neural network. an eye-gaze-guided computer interface could enable computer use by the seriously disabled but existing systems cost tens of thousands of dollars or have cumbersome setups. this paper presents a methodology for real-time eye gaze tracking using a standard webcam without the need for hardware modification or special placement. an artificial neural network was employed to estimate the location of the user's gaze based on an image of the user's eye, mimicking the way that humans determine where another person is looking. accuracy measurements and usability experiments were performed using a laptop computer with a webcam built into the screen. the results show this approach to be promising for the development of usable eye tracking systems using standard webcams, particularly those built into many laptop computers.
weight-shifting mobiles: automatic balancing in mobile phones. this paper presents a new type of interaction support for mobile phones: automatic balancing through weight-shift. it proposes that weight-shift in mobile phones could be used as to change the device's balancing behavior. the question that this technology can help us to explore is how our interaction with mobile phones in everyday life could change, once devices were able to actively change the way we hold them in our hands. various levels of interaction are proposed: balancing based on angular tilt and counter-balancing of button-clicks, and, for a future implementation, balancing, supported through grasp recognition. we report a user study that assessed in how much such a system may help users to balance the a device equipped with the proposed system. it concludes that actuated balancing may be helpful in mobile interactions, but that it needs to be designed carefully.
mobile interaction techniques for interrelated videos. with the advent of increasingly powerful mobile devices like apple's iphone, videos can be used virtually anywhere and anytime. however, state of the art mobile video browsers do not efficiently support users in browsing within individual, semantically segmented videos and between the large amounts of related videos, e.g. available on the web. we contribute a novel user interface for the mobile navigation of large video collections comprising two novel spatial interaction techniques for the mobile, nonlinear interaction with multiple videos. evaluation results show that our solution leads to significantly higher efficiency and user satisfaction.
understanding information sharing from a cross-cultural perspective. we are examining how chinese and americans share positive and negative information online and offline in different types of relationships. in this paper, we present results of a pilot study used to refine our methods and get some insight into this question. the pilot study, as hoped, confirmed that a scenario-based study of cross-cultural differences may be a viable way to understand potential technology use. we also found preliminary evidence that chinese and americans had different perspectives on how and when information should be shared. in the next phase of our work, we will deploy a scenario-based survey to a large sample of employees at a single company in china and the us.
participatory design for sustainable campus living. participatory design methods have the potential to produce ethical and useful persuasive technologies, particularly in support of environmental sustainability. i present the use and results of ethnographically-inspired methods, cultural probes, and the inspiration card workshop to generate concepts for new persuasive technologies for use by a college ecohouse.
designing user interfaces for multi-touch and surface-gesture devices. initially designers only had a keyboard and lines of text to design. then, the mouse enabled a richer design ecosystem with two dimensional plains of ui. now the design and research communities have access to multi-touch and gestural interfaces which have been released on a mass market scale. this allows them to design and develop new, unique, and richer design patterns and approaches. these methods are no longer confined to research projects or innovation labs, but are now offered on a large scale to millions of consumers. with these new interface behaviors, in combination with multiple types of hardware devices that can affect the interface, there are new problems and patterns that have increased the complexity of designing interfaces. the aim of this sig is to provide a forum for designers, researchers, and usability professionals to discuss this new and emerging technology trends for multi-touch and gesture interfaces, as well as discuss current design patterns within these interfaces. our goal is to cross pollinate ideas and current solutions from practitioners and researchers across communities to help drive awareness of this new field for those interested in, just starting in, or currently involved in the design of these systems.
embedding robotics in civic monuments for an information world. the monument is our first computer: a complex, physical entity that stores and brings to consciousness facts, ideas and aspirations - information. in this paper, we introduce transdisciplinary research aiming to overcome, in the information world, the static, petrified character of monuments which has longpresented collective memories about human events in immutable spatial forms. our concept is, instead, the monument-as-robot. embedded with sensing and actuating technologies, our concept affords multiconfigurations representing the multivalent character of collective" memory more so than the single conventional monuments. we reflect on the crisis of the monument today, describe our three novel prototypes responding to this crisis, and discuss the import for hci.
a sketch recognition interface that recognizes hundreds of shapes in course-of-action diagrams. sketch recognition is the automated recognition of hand drawn diagrams. military course-of-action (coa) diagrams are used to depict battle scenarios. the domain of military course of action diagrams is particularly interesting because it includes tens of thousands of different geometric shapes, complete with many additional textual and designator modifiers. existing sketch recognition systems recognize on the order of at most 20 different shapes. our sketch recognition interface recognizes 485 different freely drawn military course-of-action diagram symbols in real time, with each shape containing its own elaborate set of text labels and other variations. we are able to do this by combining multiple recognition techniques in a single system. when the variations (not allowable by other systems) are factored in, our system is several orders of magnitude larger than the next biggest system. on 5,900 hand-drawn symbols drawn by 8 researchers, the system achieves an accuracy of 90% when considering the top 3 interpretations and requiring every aspect of the shape (variations, text, symbol, location, orientation) to be correct.
the coffee lab: developing a public usability space. introducing the coffee lab: a novel concept for conducting usability studies in a public space where anyone can experience and evaluate research novel interactive systems. the coffee lab serves as a model for the public usability lab, which extends the methods common to laboratory-based usability experiments by adapting prototypes, usability methods, and task interactions to suit different scenarios. details on the design and implementation of public evaluation methods are discussed, along with a description of the coffee lab, and two ongoing public usability tests.
reuse: promoting repurposing through an online diy community. with the large volumes of waste going to landfills and the increase in popularity with online do-it-yourself communities, there is an opportunity to support renewal and reuse with the content generated from these communities that has yet to be explored. although do-it-yourself (diy) sites offer support for repurposing, projects are often presented top-down, potentially requiring users to acquire additional items to complete a project. the reuse application leverages content from existing diy websites but employs a bottom-up search mechanism that allows of users to search based on the items that she wants to repurpose. this application is intended to encourage and motivate people to reuse, renew, and remanufacture what they own to extend the lifecycle and utility of objects.
eye tracking analysis of preferred reading regions on the screen. we report on an exploratory study analyzing preferred reading regions on a monitor using eye tracking. we show that users have individually preferred reading regions, varying in location on the screen and in size. furthermore, we explore how scrolling interactions and mouse movements are correlated with position and size of the individually preferred reading regions.
planz to put our digital information in its place. planz provides a single, integrative document-like overlay to a folder hierarchy through the dynamic, on-demand assembly of xml fragments. this overlay provides a context in which to create or reference not only files but also email messages, web pages and informal notes. this paper describes an evaluation of planz over a period of several days during which participants compared their experiences on two projects - one involving "status quo" methods, a second project involving planz. also discussed is an architecture that extends on the front-end to provide additional overlays and on the back-end in support of additional information stores. work on planz is guided by a vision of "structural integrity": many tools, many modes of interaction applied to a common structure for the organization of and access to personal information.
competitive carbon counting: can social networking sites make saving energy more enjoyable? this paper reports on the design, deployment and initial evaluation of "wattsup", an innovative facebook application which displays live data from a commercial off-the-shelf energy monitor. the wattsup application was deployed and trialled in eight homes over an eighteen day period in two conditions - personal energy data viewable and friend's energy data viewable. a significant reduction in energy was observed in the socially enabled condition. the paper argues that socially-mediated discussion and competition made for a more enjoyable user experience.
stimulating everyday creativity: harnessing the potential of customizable uis. customizability makes an interactive interface an ideal venue for users to participate in the content creation and consumption process, thereby offering possibilities for creative pursuits. in this paper i describe research that has been designed to investigate the creativity enhancing potential of such customizable user interfaces (uis).
digitizer auditory graph: making graphs accessible to the visually impaired. this paper describes the design goal, design approach, and user testing of an assistive technology called digitizer auditory graphfia sonification software tool that allows users to upload or take an image of a line graph with an optical input device (e.g., webcam, digital camera, cell phone camera) and then hear an auditory graph of the digitized graph image. this technique enables visually impaired students to have a multimodal display of the information in a graph. preliminary evaluation results indicate that both visually impaired and sighted people can understand the patterns of graphs by listening to auditory graph, and optical input allows them to have simple and fast output results.
sharing awareness information improves interruption timing and social attraction. in distant collaborations, interruptions increase significantly due to the limited awareness of colleagues' availability. in this paper we evaluate openmessenger, an instant messaging prototype that provides awareness information. results suggest that the use of om benefits group task performance and the social attraction developed between group members. experiment observation also suggests that people use om both to predict their partner's availability and to explain the causes of their partner's late response.
cobra: flexible displays for mobilegaming scenarios. we discuss cobra, a handheld peripheral for computer games that applies flexible display design principles to provide a highly intuitive, mobile gaming experience. cobra is a flexible plastic board interface that uses bends as input to the gaming device. the display is provided by a shoulder-mounted pico projector. in this paper, we will present our prototype, the motives behind it, and its immediate applications.
ucom: spatial displays for visual awareness of remote locations. ucom enables remote users to be visually aware of each other using "spatial displays"' live views of a remote space assembled according to an estimate of the remote space's layout. remote video views from multiple viewpoints are shown individually or in a 3d collage representation that is faithful to the scene geometry. a multi-display setup integrates always-on visual connections of a remote site into the local space. this work applies an innovative spatial context to visual awareness between remote locations.
cheektouch: an affective interaction technique while speaking on the mobile phone. we present a new affective interaction technique, called cheektouch, by combining tactile feedback, delivered through the cheek, and multi-finger input, while speaking on the mobile phone. we designed a prototype by using a multi-touch mobile device and a 4x3 vibrotactile display device. we identified six affective touch behaviors (pinching, stroking, patting, slapping, kissing and tickling) that can be exchanged through one another's cheeks while speaking on the phone. we mapped the affective touch behaviors on tactile feedback expressions of the vibrotactile display. results of a preliminary user study suggest that our technique is positively evaluated by the participants and applicable to intimate and emotional communication.
can we all stand under our umbrella: the arts and design research in hci. the arts (i.e., all liberal, cultural, literary, visual and performing arts disciplines) are becoming more prominent at chi. this sig will take stock of what they can contribute, and how and why, and what the chi community needs to do to more fully embrace the arts to advance the leading edge of design research.
pixsmix: visual ambiguity as a means of designing interpersonal connection. strategies for meeting people online are often based on appearance or demographics, criteria that do not guarantee quality connections or long-lasting relationships. drawing from prior work in ambiguity and affective interaction, pixsmix is a conceptual design to facilitate human connection through visual expression and interpretation. participants create mosaics formed from a dozen public images, co-creating meaning with those who view and interact with the social artifact. to explore the validity and dynamics of this process, we gathered feedback using a paper prototype and a task-oriented focus group. the early outcomes support the notion of ambiguous design as an engaging creative activity and, through sharing of new social artifacts, as rewarding reflective experience.
supporting effective user navigation in digital documents. electronic documents such as pdfs are becoming increasingly popular as we move further towards the notion of the paperless office. the harsh truth however is that e-documents differ greatly from their physical paper counterparts, with many users opting to print them before reading. this paper describes several novel implementations that utilize a technique known as 'lightweight interaction'; a term that describes activities that can be performed without excessive cognitive attention. incorporating tools into digital document readers to aid users in day-to-day tasks will enhance their performance and hopefully increase user uptake of digital reading. my research on this topic centers on several areas of document navigation, focusing specifically on current physical (paper) practices, in order to enhance their digital equivalents.
a survey to assess the potential of mobile phones as a learning platform for panama. education is a major concern in developing countries. we believe that new and emerging technologies offer hope in improving their educational systems. while the use of personal computers in developing countries is still very low, they have seen a widespread adoption of mobile phones in recent years. since mobile phones have become small computing platforms, this inspired us to investigate their potential as educational tools. in this paper we report on a large survey (300 school children, 85 teachers) that was carried out in panama to assess the status quo of technology use, as well as the initial ideas of the potential of using mobile phones in the context of school education. results show that there is a high proliferation of mobile phones among school children, and that teachers and pupils were all able to envision using mobile phones for learning purposes. the results indicate that mobile devices have the potential to integrate into existing learning contexts, as well as enable new learning contexts.
critical gameplay: software studies in computer gameplay. the computer game software with which we interact on a daily basis not only entertains us, it trains us into specific patterns. critical gameplay is a design practice which endeavors to expose and redesign the patterns to which standard gameplay subscribes. the ongoing project seeks to identify the dominant values, philosophies and problem solving models reinforced by computer games and provides prototypical alternates to those standards.
remote skincare advice system using life logs. many women find it difficult to maintain beautiful skin since different skincare approaches require different amounts of effort, time, and special knowledge. women often ask experts in cosmetic stores for skincare advice. however, this approach has the limitations of time, place, and personal information. to solve these problems, we propose a remote skincare advice system that uses life logs. this system helps users to automatically log information related to their skin condition and share these data with skincare experts in order to obtain appropriate advice.
models, theories and methods of studying online behaviour. while there is a growing body of work that documents online behavior in its different forms, there has been little research that develops holistic models and theories of online behavior. this workshop will draw together internet researchers to develop new understandings of online behavior across a diversity of activities and applications. the emphasis is on new theories and models that can be used to understand and predict social behavior as underlying technologies change. this workshop will work as a valuable bridge across individual disciplines and empirical studies supporting the generalization of understandings and approaches.
mobigaze: development of a gaze interface for handheld mobile devices. handheld mobile devices that have a touch screen are widely used but are awkward to use with one hand. to solve this problem, we propose mobigaze, which is a user interface that uses one's gaze (gaze interface) to operate a handheld mobile device. by using stereo cameras, the user's line of sight is detected in 3d, enabling the user to interact with a mobile device by means of his/her gaze. we have constructed a prototype system of mobigaze that consists of two cameras with ir-led, a windows-based notebook pc, and ipod touch. moreover, we have developed several applications for mobigaze.
measuring environments for public displays: a space syntax approach. this paper reports on an on-going project, which is investigating the role that location plays in the visibility of information presented on a public display. spatial measures are presented, derived from the architectural theory of space syntax. these are shown to relate to the memorability of words and images presented on different displays. results show a complex pattern of interactions between the size and shape of spaces in which displays are situated and the memorability of different types of representations depicted. this approach offers a new way to consider the role of space in guiding and constraining interaction in real settings: a growing concern within hci and ubicomp.
addressing challenges in doing international field research. this panel will discuss some of the key challenges in doing international field research including issues with planning, conducting, interpreting, and reporting on such research. panelists will also share potential solutions and approaches they have used to try to deal with these challenges, and will discuss with the audience additional challenges that audience members have encountered, offering ideas on how to address these as appropriate.
encouraging awareness of peers' learning activities using large displays in the periphery. learners benefit from creating personally meaningful artifacts for an audience, especially when those artifacts embody concepts the learners aim to understand. in this pilot study, we explored ways to expand opportunities for sharing mathematical artifacts with a larger audience (beyond learners seated next to each other) by incorporating structured ways to share work on a large display. we changed the functionality of the large display throughout the experiment to explore different content management schemas. early results suggest children's awareness of their peers' work increases with the use of the large display, but that they tend to share only finished work.
an integrated probabilistic and logic approach to encyclopedia relation extraction with multiple features. we propose a new integrated approach based on markov logic networks (mlns), an effective combination of probabilistic graphical models and first-order logic for statistical relational learning, to extracting relations between entities in encyclopedic articles from wikipedia. the mlns model entity relations in a unified undirected graph collectively using multiple features, including contextual, morphological, syntactic, semantic as well as wikipedia characteristic features which can capture the essential characteristics of relation extraction task. this model makes simultaneous statistical judgments about the relations for a set of related entities. more importantly, implicit relations can also be identified easily. our experimental results showed that, this integrated probabilistic and logic model significantly outperforms the current state-of-the-art probabilistic model, conditional random fields (crfs), for relation extraction from encyclopedic articles.
linguistically annotated btg for statistical machine translation. bracketing transduction grammar (btg) is a natural choice for effective integration of desired linguistic knowledge into statistical machine translation (smt). in this paper, we propose a linguistically annotated btg (labtg) for smt. it conveys linguistic knowledge of source-side syntax structures to btg hierarchical structures through linguistic annotation. from the linguistically annotated data, we learn annotated btg rules and train linguistically motivated phrase translation model and reordering model. we also present an annotation algorithm that captures syntactic information for btg nodes. the experiments show that the labtg approach significantly outperforms a baseline btg-based system and a state-of-the-art phrase-based system on the nist mt-05 chinese-to-english translation task. moreover, we empirically demonstrate that the proposed method achieves better translation selection and phrase reordering.
from words to senses: a case study of subjectivity recognition. we determine the subjectivity of word senses. to avoid costly annotation, we evaluate how useful existing resources established in opinion mining are for this task. we show that results achieved with existing resources that are not tailored towards word sense subjectivity classification can rival results achieved with supervision on a manually annotated training set. however, results with different resources vary substantially and are dependent on the different definitions of subjectivity used in the establishment of the resources.
tracking the dynamic evolution of participants salience in a discussion. we introduce a technique for analyzing the temporal evolution of the salience of participants in a discussion. our method can dynamically track how the relative importance of speakers evolve over time using graph based techniques. speaker salience is computed based on the eigenvector centrality in a graph representation of participants in a discussion. two participants in a discussion are linked with an edge if they use similar rhetoric. the method is dynamic in the sense that the graph evolves over time to capture the evolution inherent to the participants salience. we used our method to track the salience of members of the us senate using data from the us congressional record. our analysis investigated how the salience of speakers changes over time. our results show that the scores can capture speaker centrality in topics as well as events that result in change of salience or influence among different participants.
using three way data for word sense discrimination. in this paper, an extension of a dimensionality reduction algorithm called non-negative matrix factorization is presented that combines both 'bag of words' data and syntactic data, in order to find semantic dimensions according to which both words and syntactic relations can be classified. the use of three way data allows one to determine which dimension(s) are responsible for a certain sense of a word, and adapt the corresponding feature vector accordingly, 'subtracting' one sense to discover another one. the intuition in this is that the syntactic features of the syntax-based approach can be disambiguated by the semantic dimensions found by the bag of words approach. the novel approach is embedded into clustering algorithms, to make it fully automatic. the approach is carried out for dutch, and evaluated against eurowordnet.
when is self-training effective for parsing? self-training has been shown capable of improving on state-of-the-art parser performance (mcclosky et al., 2006) despite the conventional wisdom on the matter and several studies to the contrary (charniak, 1997; steedman et al., 2003). however, it has remained unclear when and why self-training is helpful. in this paper, we test four hypotheses (namely, presence of a phase transition, impact of search errors, value of non-generative reranker features, and effects of unknown words). from these experiments, we gain a better understanding of why self-training works for parsing. since improvements from self-training are correlated with unknown bigrams and biheads but not unknown words, the benefit of self-training appears most influenced by seeing known words in new combinations.
extractive summarization using supervised and semi-supervised learning. it is difficult to identify sentence importance from a single point of view. in this paper, we propose a learning-based approach to combine various sentence features. they are categorized as surface, content, relevance and event features. surface features are related to extrinsic aspects of a sentence. content features measure a sentence based on content-conveying words. event features represent sentences by events they contained. relevance features evaluate a sentence from its relatedness with other sentences. experiments show that the combined features improved summarization performance significantly. although the evaluation results are encouraging, supervised learning approach requires much labeled data. therefore we investigate co-training by combining labeled and unlabeled data. experiments show that this semi-supervised learning approach achieves comparable performance to its supervised counterpart and saves about half of the labeling time cost.
a systematic comparison of phrase-based, hierarchical and syntax-augmented statistical mt. probabilistic synchronous context-free grammar (pscfg) translation models define weighted transduction rules that represent translation and reordering operations via nonterminal symbols. in this work, we investigate the source of the improvements in translation quality reported when using two pscfg translation models (hierarchical and syntax-augmented), when extending a state-of-the-art phrase-based baseline that serves as the lexical support for both pscfg models. we isolate the impact on translation quality for several important design decisions in each model. we perform this comparison on three nist language translation tasks; chinese-to-english, arabic-to-english and urdu-to-english, each representing unique challenges.
shift-reduce dependency dag parsing. most data-driven dependency parsing approaches assume that sentence structure is represented as trees. although trees have several desirable properties from both computational and linguistic perspectives, the structure of linguistic phenomena that goes beyond shallow syntax often cannot be fully captured by tree representations. we present a parsing approach that is nearly as simple as current data-driven transition-based dependency parsing frameworks, but outputs directed acyclic graphs (dags). we demonstrate the benefits of dag parsing in two experiments where its advantages over dependency tree parsing can be clearly observed: predicate-argument analysis of english and syntactic analysis of danish with a representation that includes long-distance dependencies and anaphoric reference links.
mind the gap: dangers of divorcing evaluations of summary content from linguistic quality. in this paper, we analyze the state of current human and automatic evaluation of topic-focused summarization in the document understanding conference main task for 2005--2007. the analyses show that while rouge has very strong correlation with responsiveness for both human and automatic summaries, there is a significant gap in responsiveness between humans and systems which is not accounted for by the rouge metrics. in addition to teasing out gaps in the current automatic evaluation, we propose a method to maximize the strength of current automatic evaluations by using the method of canonical correlation. we apply this new evaluation method, which we call rose (rouge optimal summarization evaluation), to find the optimal linear combination of rouge scores to maximize correlation with human responsiveness.
diagnostic evaluation of machine translation systems using automatically constructed linguistic check-points. we present a diagnostic evaluation platform which provides multi-factored evaluation based on automatically constructed check-points. a check-point is a linguistically motivated unit (e.g. an ambiguous word, a noun phrase, a verb~obj collocation, a prepositional phrase etc.), which are pre-defined in a linguistic taxonomy. we present a method that automatically extracts check-points from parallel sentences. by means of checkpoints, our method can monitor a mt system in translating important linguistic phenomena to provide diagnostic evaluation. the effectiveness of our approach for diagnostic evaluation is verified through experiments on various types of mt systems.
emotion classification using massive examples extracted from the web. in this paper, we propose a data-oriented method for inferring the emotion of a speaker conversing with a dialog system from the semantic content of an utterance. we first fully automatically obtain a huge collection of emotion-provoking event instances from the web. with japanese chosen as a target language, about 1.3 million emotion provoking event instances are extracted using an emotion lexicon and lexical patterns. we then decompose the emotion classification task into two sub-steps: sentiment polarity classification (coarsegrained emotion classification), and emotion classification (fine-grained emotion classification). for each subtask, the collection of emotion-proviking event instances is used as labelled examples to train a classifier. the results of our experiments indicate that our method significantly outperforms the baseline method. we also find that compared with the single-step model, which applies the emotion classifier directly to inputs, our two-step model significantly reduces sentiment polarity errors, which are considered fatal errors in real dialog applications.
on robustness and domain adaptation using svd for word sense disambiguation. in this paper we explore robustness and domain adaptation issues for word sense disambiguation (wsd) using singular value decomposition (svd) and unlabeled data. we focus on the semi-supervised domain adaptation scenario, where we train on the source corpus and test on the target corpus, and try to improve results using unlabeled data. our method yields up to 16.3% error reduction compared to state-of-the-art systems, being the first to report successful semi-supervised domain adaptation. surprisingly the improvement comes from the use of unlabeled data from the source corpus, and not from the target corpora, meaning that we get robustness rather than domain adaptation. in addition, we study the behavior of our system on the target domain.
authorship attribution and verification with many authors and limited data. most studies in statistical or machine learning based authorship attribution focus on two or a few authors. this leads to an overestimation of the importance of the features extracted from the training data and found to be discriminating for these small sets of authors. most studies also use sizes of training data that are unrealistic for situations in which stylometry is applied (e.g., forensics), and thereby overestimate the accuracy of their approach in these situations. a more realistic interpretation of the task is as an authorship verification problem that we approximate by pooling data from many different authors as negative examples. in this paper, we show, on the basis of a new corpus with 145 authors, what the effect is of many authors on feature selection and learning, and show robustness of a memory-based learning approach in doing authorship attribution and verification with many authors and limited training data when compared to eager learning methods such as svms and maximum entropy learning.
are morpho-syntactic features more predictive for the resolution of noun phrase coordination ambiguity than lexico-semantic similarity scores? coordinations in noun phrases often pose the problem that elliptified parts have to be reconstructed for proper semantic interpretation. unfortunately, the detection of coordinated heads and identification of elliptified elements notoriously lead to ambiguous reconstruction alternatives. while linguistic intuition suggests that semantic criteria might play an important, if not superior, role in disambiguating resolution alternatives, our experiments on the reannotated wsj part of the penn treebank indicate that solely morpho-syntactic criteria are more predictive than solely lexico-semantic ones. we also found that the combination of both criteria does not yield any substantial improvement.
a method for automatic pos guessing of chinese unknown words. this paper proposes a method for automatic pos (part-of-speech) guessing of chinese unknown words. it contains two models. the first model uses a machine-learning method to predict the pos of unknown words based on their internal component features. the credibility of the results of the first model is then measured. for low-credibility words, the second model is used to revise the first model's results based on the global context information of those words. the experiments show that the first model achieves 93.40% precision for all words and 86.60% for disyllabic words, which is a significant improvement over the best results reported in previous studies, which were 89% precision for all words and 74% for disyllabic words. further, the second model improves the results by 0.80% precision for all words and 1.30% for disyllabic words.
dependency-based n-gram models for general purpose sentence realisation. we present dependency-based n-gram models for general-purpose, wide-coverage, probabilistic sentence realisation. our method linearises unordered dependencies in input representations directly rather than via the application of grammar rules, as in traditional chart-based generators. the method is simple, efficient, and achieves competitive accuracy and complete coverage on standard english (penn-ii, 0.7440 bleu, 0.05 sec/sent) and chinese (ctb6, 0.7123 bleu, 0.14 sec/sent) test data.
bayesian semi-supervised chinese word segmentation for statistical machine translation. words in chinese text are not naturally separated by delimiters, which poses a challenge to standard machine translation (mt) systems. in mt, the widely used approach is to apply a chinese word segmenter trained from manually annotated data, using a fixed lexicon. such word segmentation is not necessarily optimal for translation. we propose a bayesian semi-supervised chinese word segmentation model which uses both monolingual and bilingual information to derive a segmentation suitable for mt. experiments show that our method improves a state-of-the-art mt system in a small and a large data environment.
exploiting constituent dependencies for tree kernel-based semantic relation extraction. this paper proposes a new approach to dynamically determine the tree span for tree kernel-based semantic relation extraction. it exploits constituent dependencies to keep the nodes and their head children along the path connecting the two entities, while removing the noisy information from the syntactic parse tree, eventually leading to a dynamic syntactic parse tree. this paper also explores entity features and their combined features in a unified parse and semantic tree, which integrates both structured syntactic parse information and entity-related semantic information. evaluation on the ace rdc 2004 corpus shows that our dynamic syntactic parse tree outperforms all previous tree spans, and the composite kernel combining this tree kernel with a linear state-of-the-art feature-based kernel, achieves the so far best performance.
normalizing sms: are two metaphors better than one ? electronic written texts used in computermediated interactions (e-mails, blogs, chats, etc) present major deviations from the norm of the language. this paper presents an comparative study of systems aiming at normalizing the orthography of french sms messages: after discussing the linguistic peculiarities of these messages, and possible approaches to their automatic normalization, we present, evaluate and contrast two systems, one drawing inspiration from the machine translation task; the other using techniques that are commonly used in automatic speech recognition devices. combining both approaches, our best normalization system achieves about 11% word error rate on a test set of about 3000 unseen messages.
parsing the syntagrus treebank of russian. we present the first results on parsing the syntagrus treebank of russian with a data-driven dependency parser, achieving a labeled attachment score of over 82% and an unlabeled attachment score of 89%. a feature analysis shows that high parsing accuracy is crucially dependent on the use of both lexical and morphological features. we conjecture that the latter result can be generalized to richly inflected languages in general, provided that sufficient amounts of training data are available.
an improved hierarchical bayesian model of language for document classification. this paper addresses the fundamental problem of document classification, and we focus attention on classification problems where the classes are mutually exclusive. in the course of the paper we advocate an approximate sampling distribution for word counts in documents, and demonstrate the model's capacity to outperform both the simple multinomial and more recently proposed extensions on the classification task. we also compare the classifiers to a linear svm, and show that provided certain conditions are met, the new model allows performance which exceeds that of the svm and attains amongst the very best published results on the newsgroups classification task.
a supervised algorithm for verb disambiguation into verbnet classes. verbnet (vn) is a major large-scale english verb lexicon. mapping verb instances to their vn classes has been proven useful for several nlp tasks. however, verbs are polysemous with respect to their vn classes. we introduce a novel supervised learning model for mapping verb instances to vn classes, using rich syntactic features and class membership constraints. we evaluate the algorithm in both in-domain and corpus adaptation scenarios. in both cases, we use the manually tagged semlink wsj corpus as training data. for indomain (testing on semlink wsj data), we achieve 95.9% accuracy, 35.1% error reduction (er) over a strong baseline. for adaptation, we test on the genia corpus and achieve 72.4% accuracy with 10.7% er. this is the first large-scale experimentation with automatic algorithms for this task.
textual demand analysis: detection of users' wants and needs from opinions. this paper tackles textual demand analysis, the task of capturing what people want or need, rather than identifying what they like or dislike, on which much conventional work has focused. it exploits syntactic patterns as clues to detect previously unknown demands, and requires domaindependent knowledge to get high recall. to build such patterns we created an unsupervised pattern induction method relying on the hypothesis that there are commonly desired aspects throughout a domain corpus. experimental results show that the proposed method detects twice to four times as many demand expressions in japanese discussion forums compared to a baseline method.
regenerating hypotheses for statistical machine translation. this paper studies three techniques that improve the quality of n-best hypotheses through additional regeneration process. unlike the multi-system consensus approach where multiple translation systems are used, our improvement is achieved through the expansion of the n-best hypotheses from a single system. we explore three different methods to implement the regeneration process: redecoding, n-gram expansion, and confusion network-based regeneration. experiments on chinese-to-english nist and iwslt tasks show that all three methods obtain consistent improvements. moreover, the combination of the three strategies achieves further improvements and outperforms the baseline by 0.81 bleu-score on iwslt'06, 0.57 on nist'03, 0.61 on nist'05 test set respectively.
latent morpho-semantic analysis: multilingual information retrieval with character n-grams and mutual information. we describe an entirely statistics-based, unsupervised, and language-independent approach to multilingual information retrieval, which we call latent morpho-semantic analysis (lmsa). lmsa overcomes some of the shortcomings of related previous approaches such as latent semantic analysis (lsa). lmsa has an important theoretical advantage over lsa: it combines well-known techniques in a novel way to break the terms of lsa down into units which correspond more closely to morphemes. thus, it has a particular appeal for use with morphologically complex languages such as arabic. we show through empirical results that the theoretical advantages of lmsa can translate into significant gains in precision in multilingual information retrieval tests. these gains are not matched either when a standard stemmer is used with lsa, or when terms are indiscriminately broken down into n-grams.
investigating the portability of corpus-derived cue phrases for dialogue act classification. we present recent work in the area of cross-domain dialogue act tagging. our experiments investigate the use of a simple dialogue act classifier based on purely intra-utterance features - principally involving word n-gram cue phrases. we apply automatically extracted cues from one corpus to a new annotated data set, to determine the portability and generality of the cues we learn. we show that our automatically acquired cues are general enough to serve as a cross-domain classification mechanism.
the choice of features for classification of verbs in biomedical texts. we conduct large-scale experiments to investigate optimal features for classification of verbs in biomedical texts. we introduce a range of feature sets and associated extraction techniques, and evaluate them thoroughly using a robust method new to the task: cost-based framework for pairwise clustering. our best results compare favourably with earlier ones. interestingly, they are obtained with sophisticated feature sets which include lexical and semantic information about selectional preferences of verbs. the latter are acquired automatically from corpus data using a fully unsupervised method.
almost flat functional semantics for speech translation. we introduce a novel semantic representation formalism, almost flat functional semantics (aff), which is designed as an intelligent compromise between linguistically motivated predicate/argument semantics and ad hoc engineering solutions based on flat feature/value lists; the central idea is to tag each semantic element with the functional marking which most closely surrounds it. we argue that aff is well-suited for medium-vocabulary speech translation applications, and describe simple and general algorithms for parsing, generating and performing transfer using aff representations. the formalism has been fully implemented within a medium-vocabulary interlingua-based open source speech translation system which translates between english, french, japanese and arabic.
contents modelling of neo-sumerian ur iii economic text corpus. this paper describes a system for processing economic documents written in the ancient sumerian language. the system is application-oriented and takes advantage of the simplicity of ancient economy. we have developed an ontology for a selected branch of economic activities. we translate the documents into a meaning representation language by means of a semantic grammar. the meaning representation language is constructed in a way that allows us to handle massive ambiguity caused by: the specifics of the sumerian writing system (signs' polyvalence, lack of mid-word signs), our incomplete knowledge of the sumerian language and frequent damages of documents. the system is augmented with the capability of processing documents whose parts describe concepts not included in the ontology and grammar. as an effect we obtain a structural description of the documents contents in the meaning representation language, ready to use in historical research.
two-phased event relation acquisition: coupling the relation-oriented and argument-oriented approaches. addressing the task of acquiring semantic relations between events from a large corpus, we first argue the complementarity between the pattern-based relation-oriented approach and the anchor-based argument-oriented approach. we then propose a two-phased approach, which first uses lexico-syntactic patterns to acquire predicate pairs and then uses two types of anchors to identify shared arguments. the present results of our empirical evaluation on a large-scale japanese web corpus have shown that (a) the anchor-based filtering extensively improves the accuracy of predicate pair acquisition, (b) the two types of anchors are almost equally contributive and combining them improves recall without losing accuracy, and (c) the anchor-based method also achieves high accuracy in shared argument identification.
grammar comparison study for translational equivalence modeling and statistical machine translation. this paper presents a general platform, namely synchronous tree sequence substitution grammar (stssg), for the grammar comparison study in translational equivalence modeling (tem) and statistical machine translation (smt). under the stssg platform, we compare the expressive abilities of various grammars through synchronous parsing and a real translation platform on a variety of chinese-english bilingual corpora. experimental results show that the stssg is able to better explain the data in parallel corpora than other grammars. our study further finds that the complexity of structure divergence is much higher than suggested in literature, which imposes a big challenge to syntactic transformation-based smt.
pedagogically useful extractive summaries for science education. this paper describes the design and evaluation of an extractive summarizer for educational science content called cogent. cogent extends mead based on strategies elicited from an empirical study with science domain and instructional design experts. cogent identifies sentences containing pedagogically relevant concepts for a specific science domain. the algorithms pursue a hybrid approach integrating both domain independent bottom-up sentence scoring features and domain-aware top-down features. evaluation results indicate that cogent outperforms existing summarizers and generates summaries that closely resemble those generated by human experts. cogent concept inventories appear to also support the computational identification of student misconceptions about earthquakes and plate tectonics.
comparative parser performance analysis across grammar frameworks through automatic tree conversion using synchronous grammars. this paper presents a methodology for the comparative performance analysis of the parsers developed for different grammar frameworks. for such a comparison, we need a common representation format of the parsing results since the representation of the parsing results depends on the grammar frameworks; hence they are not directly comparable to each other. we first convert the parsing result to a shallow cfg analysis by using an automatic tree converter based on synchronous grammars. the use of such a shallow representation as a common format has the advantage of reduced noise introduced by the conversion in comparison with the noise produced by the conversion to deeper representations. we compared an hpsg parser with several cfg parsers in our experiment and found that meaningful differences among the parsers' performance can still be observed by such a shallow representation.
an algorithm for adverbial aspect shift. the paper offers a new type of approach to the semantic phenomenon of adverbial aspect shift within the framework of finite-state temporal semantics. the heart of the proposal is a supervaluational concept of underspecification, and the idea of treating the meanings of temporal prepositions as dynamic presuppositions. the simple shifting algorithm used in the present approach derives the correct set of possible readings on the basis of lexical semantic input only, and, furthermore, may claim cognitive plausibility.
sentence type based reordering model for statistical machine translation. many reordering approaches have been proposed for the statistical machine translation (smt) system. however, the information about the type of source sentence is ignored in the previous works. in this paper, we propose a group of novel reordering models based on the source sentence type for chinese-to-english translation. in our approach, an svm-based classifier is employed to classify the given chinese sentences into three types: special interrogative sentences, other interrogative sentences, and non-question sentences. the different reordering models are developed oriented to the different sentence types. our experiments show that the novel reordering models have obtained an improvement of more than 2.65% in bleu for a phrase-based spoken language translation system.
a framework for identifying textual redundancy. the task of identifying redundant information in documents that are generated from multiple sources provides a significant challenge for summarization and qa systems. traditional clustering techniques detect redundancy at the sentential level and do not guarantee the preservation of all information within the document. we discuss an algorithm that generates a novel graph-based representation for a document and then utilizes a set cover approximation algorithm to remove redundant text from it. our experiments show that this approach offers a significant performance advantage over clustering when evaluated over an annotated dataset.
acquiring sense tagged examples using relevance feedback. supervised approaches to word sense disambiguation (wsd) have been shown to outperform other approaches but are hampered by reliance on labeled training examples (the data acquisition bottleneck). this paper presents a novel approach to the automatic acquisition of labeled examples for wsd which makes use of the information retrieval technique of relevance feedback. this semi-supervised method generates additional labeled examples based on existing annotated data. our approach is applied to a set of ambiguous terms from biomedical journal articles and found to significantly improve the performance of a state-of-the-art wsd system.
weakly supervised supertagging with grammar-informed initialization. much previous work has investigated weak supervision with hmms and tag dictionaries for part-of-speech tagging, but there have been no similar investigations for the harder problem of supertagging. here, i show that weak supervision for supertagging does work, but that it is subject to severe performance degradation when the tag dictionary is highly ambiguous. i show that lexical category complexity and information about how supertags may combine syntactically can be used to initialize the transition distributions of a first-order hidden markov model for weakly supervised learning. this initialization proves more effective than starting with uniform transitions, especially when the tag dictionary is highly ambiguous.
a fluid knowledge representation for understanding and generating creative metaphors. creative metaphor is a phenomenon that stretches and bends the conventions of semantic description, often to humorous and poetic extremes. the computational modeling of metaphor thus requires a knowledge representation that is just as stretchable and semantically accommodating. we present here a flexible knowledge representation for metaphor interpretation and generation, called talking points, and describe how talking points can be acquired on a large scale from wordnet (fellbaum, 1998) and from the web. we show how talking points can be fluidly connected to form a slipnet, and demonstrate that talking points provide an especially concise representation for concepts in general.
estimation of conditional probabilities with decision trees and an application to fine-grained pos tagging. we present a hmm part-of-speech tagging method which is particularly suited for pos tagsets with a large number of fine-grained tags. it is based on three ideas: (1) splitting of the pos tags into attribute vectors and decomposition of the contextual pos probabilities of the hmm into a product of attribute probabilities, (2) estimation of the contextual probabilities with decision trees, and (3) use of high-order hmms. in experiments on german and czech data, our tagger outperformed state-of-the-art pos taggers.
understanding and summarizing answers in community-based question answering services. community-based question answering (cqa) services have accumulated millions of questions and their answers over time. in the process of accumulation, cqa services assume that questions always have unique best answers. however, with an in-depth analysis of questions and answers on cqa services, we find that the assumption cannot be true. according to the analysis, at least 78% of the cqa best answers are reusable when similar questions are asked again, but no more than 48% of them are indeed the unique best answers. we conduct the analysis by proposing taxonomies for cqa questions and answers. to better reuse the cqa content, we also propose applying automatic summarization techniques to summarize answers. our results show that question-type oriented summarization techniques can improve cqa answer quality significantly.
modeling chinese documents with topical word-character models. as chinese text is written without word boundaries, effectively recognizing chinese words is like recognizing collocations in english, substituting characters for words and words for collocations. however, existing topical models that involve collocations have a common limitation. instead of directly assigning a topic to a collocation, they take the topic of a word within the collocation as the topic of the whole collocation. this is unsatisfactory for topical modeling of chinese documents. thus, we propose a topical word-character model (twc), which allows two distinct types of topics: word topic and character topic. we evaluated twc both qualitatively and quantitatively to show that it is a powerful and a promising topic model.
ontonotes: corpus cleanup of mistaken agreement using word sense disambiguation. annotated corpora are only useful if their annotations are consistent. most large-scale annotation efforts take special measures to reconcile inter-annotator disagreement. to date, however, no-one has investigated how to automatically determine exemplars in which the annotators agree but are wrong. in this paper, we use ontonotes, a large-scale corpus of semantic annotations, including word senses, predicate-argument structure, ontology linking, and coreference. to determine the mistaken agreements in word sense annotation, we employ word sense disambiguation (wsd) to select a set of suspicious candidates for human evaluation. experiments are conducted from three aspects (precision, cost-effectiveness ratio, and entropy) to examine the performance of wsd. the experimental results show that wsd is most effective on identifying erroneous annotations for highly-ambiguous words, while a baseline is better for other cases. the two methods can be combined to improve the cleanup process. this procedure allows us to find approximately 2% remaining erroneous agreements in the ontonotes corpus. a similar procedure can be easily defined to check other annotated corpora.
integrating a unification-based semantics in a large scale lexicalised tree adjoining grammar for french. in contrast to lfg and hpsg, there is to date no large scale tree adjoining grammar (tag) equiped with a compositional semantics. in this paper, we report on the integration of a unification-based semantics into a feature-based lexicalised tag for french consisting of around 6 000 trees. we focus on verb semantics and show how factorisation can be used to support a compact and principled encoding of the semantic information that needs to be associated with each of the verbal elementary trees. the factorisation is made possible by the use of xmg, a high-level linguistic formalism designed to specify and compile computational grammars and in particular, grammars based on non-local trees or tree descriptions.
generation of referring expressions: managing structural ambiguities. existing algorithms for the generation of referring expressions tend to generate distinguishing descriptions at the semantic level, disregarding the ways in which surface issues can affect their quality. this paper considers how these algorithms should deal with surface ambiguity, focussing on structural ambiguity. we propose that not all ambiguity is worth avoiding, and suggest some ways forward that attempt to avoid unwanted interpretations. we sketch the design of an algorithm motivated by our experimental findings.
a joint information model for n-best ranking. in this paper, we present a method for modeling joint information when generating n-best lists. we apply the method to a novel task of characterizing the similarity of a group of terms where only a small set of many possible semantic properties may be displayed to a user. we demonstrate that considering the results jointly, by accounting for the information overlap between results, generates better n-best lists than considering them independently. we propose an information theoretic objective function for modeling the joint information in an n-best list and show empirical evidence that humans prefer the result sets produced by our joint model. our results show with 95% confidence that the n-best lists generated by our joint ranking model are significantly different from a baseline independent model 50.0% &plusmn; 3.1% of the time, out of which they are preferred 76.6% &plusmn; 5.2% of the time.
efficiently parsing with the product-free lambek calculus. this paper provides a parsing algorithm for the lambek calculus which is polynomial time for a more general fragment of the lambek calculus than any previously known algorithm. the algorithm runs in worst-case time o(n5) when restricted to a certain fragment of the lambek calculus which is motivated by empirical analysis. in addition, a set of parameterized inputs are given, showing why the algorithm has exponential worst-case running time for the lambek calculus in general.
enhancing multilingual latent semantic analysis with term alignment information. latent semantic analysis (lsa) is based on the singular value decomposition (svd) of a term-by-document matrix for identifying relationships among terms and documents from cooccurrence patterns. among the multiple ways of computing the svd of a rectangular matrix x, one approach is to compute the eigenvalue decomposition (evd) of a square 2 x 2 composite matrix consisting of four blocks with x and xt in the off-diagonal blocks and zero matrices in the diagonal blocks. we point out that significant value can be added to lsa by filling in some of the values in the diagonal blocks (corresponding to explicit term-to-term or document-to-document associations) and computing a term-by-concept matrix from the evd. for the case of multilingual lsa, we incorporate information on cross-language term alignments of the same sort used in statistical machine translation (smt). since all elements of the proposed evd-based approach can rely entirely on lexical statistics, hardly any price is paid for the improved empirical results. in particular, the approach, like lsa or smt, can still be generalized to virtually any language(s); computation of the evd takes similar resources to that of the svd since all the blocks are sparse; and the results of evd are just as economical as those of svd.
a probabilistic model for measuring grammaticality and similarity of automatically generated paraphrases of predicate phrases. the most critical issue in generating and recognizing paraphrases is development of wide-coverage paraphrase knowledge. previous work on paraphrase acquisition has collected lexicalized pairs of expressions; however, the results do not ensure full coverage of the various paraphrase phenomena. this paper focuses on productive paraphrases realized by general transformation patterns, and addresses the issues in generating instances of phrasal paraphrases with those patterns. our probabilistic model computes how two phrases are likely to be correct paraphrases. the model consists of two components: (i) a structured n-gram language model that ensures grammaticality and (ii) a distributional similarity measure for estimating semantic equivalence and substitutability.
translating queries into snippets for improved query expansion. user logs of search engines have recently been applied successfully to improve various aspects of web search quality. in this paper, we will apply pairs of user queries and snippets of clicked results to train a machine translation model to bridge the "lexical gap" between query and document space. we show that the combination of a query-to-snippet translation model with a large n-gram language model trained on queries achieves improved contextual query expansion compared to a system based on term correlations.
coordination disambiguation without any similarities. the use of similarities has been one of the main approaches to resolve the ambiguities of coordinate structures. in this paper, we present an alternative method for coordination disambiguation, which does not use similarities. our hypothesis is that coordinate structures are supported by surrounding dependency relations, and that such dependency relations rather yield similarity between conjuncts, which humans feel. based on this hypothesis, we built a japanese fully-lexicalized generative parser that includes coordination disambiguation. experimental results on web sentences indicated the effectiveness of our approach, and endorsed our hypothesis.
switching to real-time tasks in multi-tasking dialogue. in this paper we describe an empirical study of human-human multi-tasking dialogues (mtd), where people perform multiple verbal tasks overlapped in time. we examined how conversants switch from the ongoing task to a real-time task. we found that 1) conversants use discourse markers and prosodic cues to signal task switching, similar to how they signal topic shifts in single-tasking speech; 2) conversants strive to switch tasks at a less disruptive place; and 3) where they cannot, they exert additional effort (even higher pitch) to signal the task switching. our machine learning experiment also shows that task switching can be reliably recognized using discourse context and normalized pitch. these findings will provide guidelines for building future speech interfaces to support multi-tasking dialogue.
domain adaptation for statistical machine translation with domain dictionary and monolingual corpora. statistical machine translation systems are usually trained on large amounts of bilingual text and monolingual text. in this paper, we propose a method to perform domain adaptation for statistical machine translation, where in-domain bilingual corpora do not exist. this method first uses out-of-domain corpora to train a baseline system and then uses in-domain translation dictionaries and in-domain monolingual corpora to improve the in-domain performance. we propose an algorithm to combine these different resources in a unified framework. experimental results indicate that our method achieves absolute improvements of 8.16 and 3.36 bleu scores on chinese to english translation and english to french translation respectively, as compared with the baselines using only out-of-domain corpora.
prediction of maximal projection for semantic role labeling. in semantic role labeling (srl), arguments are usually limited in a syntax subtree. it is reasonable to label arguments locally in such a sub-tree rather than a whole tree. to identify active region of arguments, this paper models maximal projection (mp), which is a concept in d-structure from the projection principle of the principle and parameters theory. this paper makes a new definition of mp in s-structure and proposes two methods to predict it: the anchor group approach and the single anchor approach. the anchor group approach achieves an accuracy of 87.75% and the single anchor approach achieves 83.63%. experimental results also indicate that the prediction of mp improves semantic role labeling.
parametric: an automatic evaluation metric for paraphrasing. we present parametric, an automatic evaluation metric for data-driven approaches to paraphrasing. parametric provides an objective measure of quality using a collection of multiple translations whose paraphrases have been manually annotated. parametric calculates precision and recall scores by comparing the paraphrases discovered by automatic paraphrasing techniques against gold standard alignments of words and phrases within equivalent sentences. we report scores for several established paraphrasing techniques.
word lattice reranking for chinese word segmentation and part-of-speech tagging. in this paper, we describe a new reranking strategy named word lattice reranking, for the task of joint chinese word segmentation and part-of-speech (pos) tagging. as a derivation of the forest reranking for parsing (huang, 2008), this strategy reranks on the pruned word lattice, which potentially contains much more candidates while using less storage, compared with the traditional n-best list reranking. with a perceptron classifier trained with local features as the baseline, word lattice reranking performs reranking with non-local features that can't be easily incorporated into the perceptron baseline. experimental results show that, this strategy achieves improvement on both segmentation and pos tagging, above the perceptron baseline and the n-best list reranking.
a fully-lexicalized probabilistic model for japanese zero anaphora resolution. this paper presents a probabilistic model for japanese zero anaphora resolution. first, this model recognizes discourse entities and links all mentions to them. zero pronouns are then detected by case structure analysis based on automatically constructed case frames. their appropriate antecedents are selected from the entities with high salience scores, based on the case frames and several preferences on the relation between a zero pronoun and an antecedent. case structure and zero anaphora relation are simultaneously determined based on probabilistic evaluation metrics.
a discriminative alignment model for abbreviation recognition. this paper presents a discriminative alignment model for extracting abbreviations and their full forms appearing in actual text. the task of abbreviation recognition is formalized as a sequential alignment problem, which finds the optimal alignment (origins of abbreviation letters) between two strings (abbreviation and full form). we design a large amount of finegrained features that directly express the events where letters produce or do not produce abbreviations. we obtain the optimal combination of features on an aligned abbreviation corpus by using the maximum entropy framework. the experimental results show the usefulness of the alignment model and corpus for improving abbreviation recognition.
semantic role assignment for event nominalisations by leveraging verbal data. this paper presents a novel approach to the task of semantic role labelling for event nominalisations, which make up a considerable fraction of predicates in running text, but are underrepresented in terms of training data and difficult to model. we propose to address this situation by data expansion. we construct a model for nominal role labelling solely from verbal training data. the best quality results from salvaging grammatical features where applicable, and generalising over lexical heads otherwise.
representations for category disambiguation. as it serves as a basis for pos tagging, category induction, and human category acquisition, we investigate the information needed to disambiguate a word in a local context, when using corpus categories. specifically, we increase the recall of an error detection method by abstracting the word to be disambiguated to a representation containing information about some of its inherent properties, namely the set of categories it can potentially have. this work thus provides insights into the relation of corpus categories to categories derived from local contexts.
extracting synchronous grammar rules from word-level alignments in linear time. we generalize uno and yagiura's algorithm for finding all common intervals of two permutations to the setting of two sequences with many-to-many alignment links across the two sides. we show how to maximally decompose a word-aligned sentence pair in linear time, which can be used to generate all possible phrase pairs or a synchronous context-free grammar (scfg) with the simplest rules possible. we also use the algorithm to precisely analyze the maximum scfg rule length needed to cover hand-aligned data from various language pairs.
knownet: building a large net of knowledge from the web. this paper presents a new fully automatic method for building highly dense and accurate knowledge bases from existing semantic resources. basically, the method uses a wide-coverage and accurate knowledge-based word sense disambiguation algorithm to assign the most appropriate senses to large sets of topically related words acquired from the web. knownet, the resulting knowledge-base which connects large sets of semantically-related concepts is a major step towards the autonomous acquisition of knowledge from raw corpora. in fact, knownet is several times larger than any available knowledge resource encoding relations between synsets, and the knowledge knownet contains outperform any other resource when is empirically evaluated in a common framework.
robust similarity measures for named entities matching. matching coreferent named entities without prior knowledge requires good similarity measures. soft-tfidf is a fine-grained measure which performs well in this task. we propose to enhance this kind of metrics, through a generic model in which measures may be mixed, and show experimentally the relevance of this approach.
what's the date? high accuracy interpretation of weekday names. in this paper we present a study on the interpretation of weekday names in texts. our algorithm for assigning a date to a weekday name achieves 95.91% accuracy on a test data set based on the ace 2005 training corpus, outperforming previously reported techniques run against this same data. we also provide the first detailed comparison of various approaches to the problem using this test data set, employing re-implementations of key techniques from the literature and a range of additional heuristic-based approaches.
retrieving bilingual verb-noun collocations by integrating cross-language category hierarchies. this paper presents a method of retrieving bilingual collocations of a verb and its objective noun from cross-lingual documents with similar contents. relevant documents are obtained by integrating cross-language hierarchies. the results showed a 15.1% improvement over the baseline non-hierarchy model, and a 6.0% improvement over use of relevant documents retrieved from a single hierarchy. moreover, we found that some of the retrieved collocations were domain-specific.
mining opinions in comparative sentences. this paper studies sentiment analysis from the user-generated content on the web. in particular, it focuses on mining opinions from comparative sentences, i.e., to determine which entities in a comparison are preferred by its author. a typical comparative sentence compares two or more entities. for example, the sentence, "the picture quality of camera x is better than that of camera y", compares two entities "camera x" and "camera y" with regard to their picture quality. clearly, "camera x" is the preferred entity. existing research has studied the problem of extracting some key elements in a comparative sentence. however, there is still no study of mining opinions from comparative sentences, i.e., identifying preferred entities of the author. this paper studies this problem, and proposes a technique to solve the problem. our experiments using comparative sentences from product reviews and forum posts show that the approach is effective.
extending a thesaurus with words from pan-chinese sources. in this paper, we work on extending a chinese thesaurus with words distinctly used in various chinese communities. the acquisition and classification of such region-specific lexical items is an important step toward the larger goal of constructing a pan-chinese lexical resource. in particular, we extend a previous study in three respects: (1) to improve automatic classification by removing duplicated words from the thesaurus, (2) to experiment with classifying words at the subclass level and semantic head level, and (3) to further investigate the possible effects of data heterogeneity between the region-specific words and words in the thesaurus on classification performance. automatic classification was based on the similarity between a target word and individual categories of words in the thesaurus, measured by the cosine function. experiments were done on 120 target words from four regions. the automatic classification results were evaluated against a gold standard obtained from human judgements. in general accuracy reached 80% or more with the top 10 (out of 80+) and top 100 (out of 1,300+) candidates considered at the subclass level and semantic head level respectively, provided that the appropriate data sources were used.
relational-realizational parsing. state-of-the-art statistical parsing models applied to free word-order languages tend to underperform compared to, e.g., parsing english. constituency-based models often fail to capture generalizations that cannot be stated in structural terms, and dependency-based models employ a 'single-head' assumption that often breaks in the face of multiple exponence. in this paper we suggest that the position of a constituent is a form manifestation of its grammatical function, one among various possible means of realization. we develop the relational-realizational approach to parsing in which we untangle the projection of grammatical functions and their means of realization to allow for phrase-structure variability and morphological-syntactic interaction. we empirically demonstrate the application of our approach to parsing modern hebrew, obtaining 7% error reduction from previously reported results.
japanese dependency parsing using a tournament model. in japanese dependency parsing, kudo's relative preference-based method (kudo and matsumoto, 2005) outperforms both deterministic and probabilistic cky-based parsing methods. in kudo's method, for each dependent word (or chunk) a log-linear model estimates relative preference of all other candidate words (or chunks) for being as its head. this cannot be considered in the deterministic parsing methods. we propose an algorithm based on a tournament model, in which the relative preferences are directly modeled by one-on-one games in a step-ladder tournament. in an evaluation experiment with kyoto text corpus version 4.0, the proposed method outperforms previous approaches, including the relative preference-based method.
semantic classification with distributional kernels. distributional measures of lexical similarity and kernel methods for classification are well-known tools in natural language processing. we bring these two methods together by introducing distributional kernels that compare co-occurrence probability distributions. we demonstrate the effectiveness of these kernels by presenting state-of-the-art results on datasets for three semantic classification: compound noun interpretation, identification of semantic relations between nominals and semantic classification of verbs. finally, we consider explanations for the impressive performance of distributional kernels and sketch some promising generalisations.
verification and implementation of language-based deception indicators in civil and criminal narratives. our goal is to use natural language processing to identify deceptive and non-deceptive passages in transcribed narratives. we begin by motivating an analysis of language-based deception that relies on specific linguistic indicators to discover deceptive statements. the indicator tags are assigned to a document using a mix of automated and manual methods. once the tags are assigned, an interpreter automatically discriminates between deceptive and truthful statements based on tag densities. the texts used in our study come entirely from "real world" sources---criminal statements, police interrogations and legal testimony. the corpus was hand-tagged for the truth value of all propositions that could be externally verified as true or false. classification and regression tree techniques suggest that the approach is feasible, with the model able to identify 74.9% of the t/f propositions correctly. implementation of an automatic tagger with a large subset of tags performed well on test data, producing an average score of 68.6% recall and 85.3% precision when compared to the performance of human taggers on the same subset.
a syntactic time-series model for parsing fluent and disfluent speech. this paper describes an incremental approach to parsing transcribed spontaneous speech containing disfluencies with a hierarchical hidden markov model (hhmm). this model makes use of the right-corner transform, which has been shown to increase non-incremental parsing accuracy on transcribed spontaneous speech (miller and schuler, 2008), using trees transformed in this manner to train the hhmm parser. not only do the representations used in this model align with structure in speech repairs, but as an hmm-like time-series model, it can be directly integrated into conventional speech recognition systems run on continuous streams of audio. a system implementing this model is evaluated on the standard task of parsing the switchboard corpus, and achieves an improvement over the standard baseline probabilistic cyk parser.
hybrid processing for grammar and style checking. this paper presents an implemented hybrid approach to grammar and style checking, combining an industrial pattern-based grammar and style checker with bidirectional, large-scale hpsg grammars for german and english. under this approach, deep processing is applied selectively based on the error hypotheses of a shallow system. we have conducted a comparative evaluation of the two components, supporting an integration scenario where the shallow system is best used for error detection, whereas the hpsg grammars add error correction for both grammar and controlled language style errors.
reading the markets: forecasting public opinion of political candidates by news analysis. media reporting shapes public opinion which can in turn influence events, particularly in political elections, in which candidates both respond to and shape public perception of their campaigns. we use computational linguistics to automatically predict the impact of news on public perception of political candidates. our system uses daily newspaper articles to predict shifts in public opinion as reflected in prediction markets. we discuss various types of features designed for this problem. the news system improves market prediction over baseline market systems.
measuring and predicting orthographic associations: modelling the similarity of japanese kanji. as human beings, our mental processes for recognising linguistic symbols generate perceptual neighbourhoods around such symbols where confusion errors occur. such neighbourhoods also provide us with conscious mental associations between symbols. this paper formalises orthographic models for similarity of japanese kanji, and provides a proof-of-concept dictionary extension leveraging the mental associations provided by orthographic proximity.
random restarts in minimum error rate training for statistical machine translation. och's (2003) minimum error rate training (mert) procedure is the most commonly used method for training feature weights in statistical machine translation (smt) models. the use of multiple randomized starting points in mert is a well-established practice, although there seems to be no published systematic study of its benefits. we compare several ways of performing random restarts with mert. we find that all of our random restart methods outperform mert without random restarts, and we develop some refinements of random restarts that are superior to the most common approach with regard to resulting model quality and training time.
unsupervised induction of labeled parse trees by clustering with syntactic features. we present an algorithm for unsupervised induction of labeled parse trees. the algorithm has three stages: bracketing, initial labeling, and label clustering. bracketing is done from raw text using an unsupervised incremental parser. initial labeling is done using a merging model that aims at minimizing the grammar description length. finally, labels are clustered to a desired number of labels using syntactic features extracted from the initially labeled trees. the algorithm obtains 59% labeled f-score on the wsj10 corpus, as compared to 35% in previous work, and substantial error reduction over a random baseline. we report results for english, german and chinese corpora, using two label mapping methods and two label set sizes.
choosing the right translation: a syntactically informed classification approach. one style of multi-engine machine translation architecture involves choosing the best of a set of outputs from different systems. choosing the best translation from an arbitrary set, even in the presence of human references, is a difficult problem; it may prove better to look at mechanisms for making such choices in more restricted contexts. in this paper we take a classification-based approach to choosing between candidates from syntactically informed translations. the idea is that using multiple parsers as part of a classifier could help detect syntactic problems in this context that lead to bad translations; these problems could be detected on either the source side---perhaps sentences with difficult or incorrect parses could lead to bad translations---or on the target side---perhaps the output quality could be measured in a more syntactically informed way, looking for syntactic abnormalities. we show that there is no evidence that the source side information is useful. however, a target-side classifier, when used to identify particularly bad translation candidates, can lead to significant improvements in bleu score. improvements are even greater when combined with existing language and alignment model approaches.
hindi urdu machine transliteration using finite-state transducers. finite-state transducers (fst) can be very efficient to implement inter-dialectal transliteration. we illustrate this on the hindi and urdu language pair. fsts can also be used for translation between surface-close languages. we introduce uit (universal intermediate transcription) for the same pair on the basis of their common phonetic repository in such a way that it can be extended to other languages like arabic, chinese, english, french, etc. we describe a transliteration model based on fst and uit, and evaluate it on hindi and urdu corpora.
tera-scale translation models via pattern matching. translation model size is growing at a pace that outstrips improvements in computing power, and this hinders research on many interesting models. we show how an algorithmic scaling technique can be used to easily handle very large models. using this technique, we explore several large model variants and show an improvement 1.4 bleu on the nist 2006 chinese-english task. this opens the door for work on a variety of models that are much less constrained by computational limitations.
class-driven attribute extraction. we report on the large-scale acquisition of class attributes with and without the use of lists of representative instances, as well as the discovery of unary attributes, such as typically expressed in english through prenominal adjectival modification. our method employs a system based on compositional language processing, as applied to the british national corpus. experimental results suggest that document-based, open class attribute extraction can produce results of comparable quality as those obtained using web query logs, indicating the utility of exploiting explicit occurrences of class labels in text.
metric learning for synonym acquisition. the distance or similarity metric plays an important role in many natural language processing (nlp) tasks. previous studies have demonstrated the effectiveness of a number of metrics such as the jaccard coefficient, especially in synonym acquisition. while the existing metrics perform quite well, to further improve performance, we propose the use of a supervised machine learning algorithm that fine-tunes them. given the known instances of similar or dissimilar words, we estimated the parameters of the mahalanobis distance. we compared a number of metrics in our experiments, and the results show that the proposed metric has a higher mean average precision than other metrics.
a classifier-based approach to preposition and determiner error correction in l2 english. in this paper, we present an approach to the automatic identification and correction of preposition and determiner errors in non-native (l2) english writing. we show that models of use for these parts of speech can be learned with an accuracy of 70.06% and 92.15% respectively on l1 text, and present first results in an error detection task for l2 writing.
event frame extraction based on a gene regulation corpus. this paper describes the supervised acquisition of semantic event frames based on a corpus of biomedical abstracts, in which the biological process of e. coli gene regulation has been linguistically annotated by a group of biologists in the ec research project "bootstrep". gene regulation is one of the rapidly advancing areas for which information extraction could boost research. event frames are an essential linguistic resource for extraction of information from biological literature. this paper presents a specification for linguistic-level annotation of gene regulation events, followed by novel methods of automatic event frame extraction from text. the event frame extraction performance has been evaluated with 10-fold cross validation. the experimental results show that a precision of nearly 50% and a recall of around 20% are achieved. since the goal of this paper is event frame extraction, rather than event instance extraction, the issue of low recall could be solved by applying the methods to a larger-scale corpus.
the ups and downs of preposition error detection in esl writing. in this paper we describe a methodology for detecting preposition errors in the writing of non-native english speakers. our system performs at 84% precision and close to 19% recall on a large set of student essays. in addition, we address the problem of annotation and evaluation in this domain by showing how current approaches of using only one rater can skew system evaluation. we present a sampling approach to circumvent some of the issues that complicate evaluation of error detection systems.
learning reliable information for dependency parsing adaptation. in this paper, we focus on the adaptation problem that has a large labeled data in the source domain and a large but unlabeled data in the target domain. our aim is to learn reliable information from unlabeled target domain data for dependency parsing adaptation. current state-of-the-art statistical parsers perform much better for shorter dependencies than for longer ones. thus we propose an adaptation approach by learning reliable information on shorter dependencies in an unlabeled target data to help parse longer distance words. the unlabeled data is parsed by a dependency parser trained on labeled source domain data. the experimental results indicate that our proposed approach outperforms the baseline system, and is better than current state-of-the-art adaptation techniques.
measuring topic homogeneity and its application to dictionary-based word sense disambiguation. the use of topical features is abundant in natural language processing (nlp), a major example being in dictionary-based word sense disambiguation (wsd). yet previous research does not attempt to measure the level of topic cohesion in documents, despite assertions of its effects. this paper introduces a quantitative measure of topic homogeneity using a range of nlp resources and not requiring prior knowledge of correct senses. evaluation is performed firstly by using the wordnet::domains package to create word-sets with varying levels of homogeneity and comparing our results with those expected. additionally, to evaluate each measure's potential value, the homogeneity results are correlated against those of 3 co-occurrence/dictionary-based wsd techniques, tested on 1040 semcor and senseval sub-documents. many low-moderate correlations are found to exist with several in the moderate range (above .40). these correlations surpass polysemy and senseentropy, the 2 most cited factors affecting wsd. finally, a combined homogeneity measure achieves correlations of up to .52.
automatic generation of parallel treebanks. the need for syntactically annotated data for use in natural language processing has increased dramatically in recent years. this is true especially for parallel treebanks, of which very few exist. the ones that exist are mainly hand-crafted and too small for reliable use in data-oriented applications. in this paper we introduce a novel platform for fast and robust automatic generation of parallel treebanks. the software we have developed based on this platform has been shown to handle large data sets. we also present evaluation results demonstrating the quality of the derived treebanks and discuss some possible modifications and improvements that can lead to even better results. we expect the presented platform to help boost research in the field of data-oriented machine translation and lead to advancements in other fields where parallel treebanks can be employed.
improving statistical machine translation using lexicalized rule selection. this paper proposes a novel lexicalized approach for rule selection for syntax-based statistical machine translation (smt). we build maximum entropy (maxent) models which combine rich context information for selecting translation rules during decoding. we successfully integrate the maxent-based rule selection models into the state-of-the-art syntax-based smt model. experiments show that our lexicalized approach for rule selection achieves statistically significant improvements over the state-of-the-art smt system.
generating chinese couplets using a statistical mt approach. part of the unique cultural heritage of china is the game of chinese couplets (du&igrave;li&aacute;n). one person challenges the other person with a sentence (first sentence). the other person then replies with a sentence (second sentence) equal in length and word segmentation, in a way that corresponding words in the two sentences match each other by obeying certain constraints on semantic, syntactic, and lexical relatedness. this task is viewed as a difficult problem in ai and has not been explored in the research community. in this paper, we regard this task as a kind of machine translation process. we present a phrase-based smt approach to generate the second sentence. first, the system takes as input the first sentence, and generates as output an n-best list of proposed second sentences, using a phrase-based smt decoder. then, a set of filters is used to remove candidates violating linguistic constraints. finally, a ranking svm is applied to rerank the candidates. a comprehensive evaluation, using both human judgments and bleu scores, has been conducted, and the results demonstrate that this approach is very successful.
detecting multiple facets of an event using graph-based unsupervised methods. we propose a new unsupervised method for topic detection that automatically identifies the different facets of an event. we use pointwise kullback-leibler divergence along with the jaccard coefficient to build a topic graph which represents the community structure of the different facets. the problem is formulated as a weighted set cover problem with dynamically varying weights. the algorithm is domain-independent and generates a representative set of informative and discriminative phrases that cover the entire event. we evaluate this algorithm on a large collection of blog postings about different news events and report promising results.
collabrank: towards a collaborative approach to single-document keyphrase extraction. previous methods usually conduct the keyphrase extraction task for single documents separately without interactions for each document, under the assumption that the documents are considered independent of each other. this paper proposes a novel approach named collabrank to collaborative single-document keyphrase extraction by making use of mutual influences of multiple documents within a cluster context. collabrank is implemented by first employing the clustering algorithm to obtain appropriate document clusters, and then using the graph-based ranking algorithm for collaborative single-document keyphrase extraction within each cluster. experimental results demonstrate the encouraging performance of the proposed approach. different clustering algorithms have been investigated and we find that the system performance relies positively on the quality of document clusters.
exploiting graph structure for accelerating the calculation of shortest paths in wordnets. this paper presents an approach for substantially reducing the time needed to calculate the shortest paths between all concepts in a wordnet. the algorithm exploits the unique "star-like" topology of wordnets to cut down on time-expensive calculations performed by algorithms to solve the all-pairs shortest path problem in general graphs. the algorithm was applied to two wordnets of two different languages: princeton wordnet (fellbaum, 1998) for english, and germanet (kunze and lemnitzer, 2002), the german language wordnet. for both wordnets, the time needed for finding all shortest paths was brought down from several days to a matter of minutes.
chinese dependency parsing with large scale automatically constructed case structures. this paper proposes an approach using large scale case structures, which are automatically constructed from both a small tagged corpus and a large raw corpus, to improve chinese dependency parsing. the case structure proposed in this paper has two characteristics: (1) it relaxes the predicate of a case structure to be all types of words which behaves as a head; (2) it is not categorized by semantic roles but marked by the neighboring modifiers attached to a head. experimental results based on penn chinese treebank show the proposed approach achieved 87.26% on unlabeled attachment score, which significantly outperformed the baseline parser without using case structures.
statistical anaphora resolution in biomedical texts. this paper presents a probabilistic model for resolution of non-pronominal anaphora in biomedical texts. the model seeks to find the antecedents of anaphoric expressions, both coreferent and associative ones, and also to identify discourse-new expressions. we consider only the noun phrases referring to biomedical entities. the model reaches state-of-the art performance: 56--69% precision and 54--67% recall on coreferent cases, and reasonable performance on different classes of associative cases.
a classification of dialogue actions in tutorial dialogue. in this paper we present a taxonomy of dialogue moves which describe the actions that students and tutors perform in tutorial dialogue. we are motivated by the need for a categorisation of such actions in order to develop computational models for tutorial dialogue. as such, we build both on existing work on dialogue move categorisation for tutorial dialogue as well as dialogue taxonomies for general dialogue. our taxonomy has been prepared by analysing a corpus of tutorial dialogues on mathematical theorem proving. we also detail an annotation experiment in which we apply the taxonomy and discuss idiosyncrasies in the data which influence the decisions in the dialogue move classification.
source language markers in europarl translations. this paper shows that it is very often possible to identify the source language of medium-length speeches in the europarl corpus on the basis of frequency counts of word n-grams (87.2%--96.7% accuracy depending on classification method). the paper also examines in detail which positive markers are most powerful and identifies a number of linguistic aspects as well as culture- and domain-related ones.
linguistically-based sub-sentential alignment for terminology extraction from a bilingual automotive corpus. we present a sub-sentential alignment system that links linguistically motivated phrases in parallel texts based on lexical correspondences and syntactic similarity. we compare the performance of our sub-sentential alignment system with different symmetrization heuristics that combine the giza++ alignments of both translation directions. we demonstrate that the aligned linguistically motivated phrases are a useful means to extract bilingual terminology and more specifically complex multiword terms.
learning entailment rules for unary templates. most work on unsupervised entailment rule acquisition focused on rules between templates with two variables, ignoring unary rules - entailment rules between templates with a single variable. in this paper we investigate two approaches for unsupervised learning of such rules and compare the proposed methods with a binary rule learning method. the results show that the learned unary rule-sets outperform the binary rule-set. in addition, a novel directional similarity measure for learning entailment, termed balanced-inclusion, is the best performing measure.
improving alignments for better confusion networks for combining machine translation systems. the state-of-the-art system combination method for machine translation (mt) is the word-based combination using confusion networks. one of the crucial steps in confusion network decoding is the alignment of different hypotheses to each other when building a network. in this paper, we present new methods to improve alignment of hypotheses using word synonyms and a two-pass alignment strategy. we demonstrate that combination with the new alignment technique yields up to 2.9 bleu point improvement over the best input system and up to 1.3 bleu point improvement over a state-of-the-art combination method on two different language pairs.
the effect of syntactic representation on semantic role labeling. almost all automatic semantic role labeling (srl) systems rely on a preliminary parsing step that derives a syntactic structure from the sentence being analyzed. this makes the choice of syntactic representation an essential design decision. in this paper, we study the influence of syntactic representation on the performance of srl systems. specifically, we compare constituent-based and dependency-based representations for srl of english in the framenet paradigm. contrary to previous claims, our results demonstrate that the systems based on dependencies perform roughly as well as those based on constituents: for the argument classification task, dependency-based systems perform slightly higher on average, while the opposite holds for the argument identification task. this is remarkable because dependency parsers are still in their infancy while constituent parsing is more mature. furthermore, the results show that dependency-based semantic role classifiers rely less on lexicalized features, which makes them more robust to domain changes and makes them learn more efficiently with respect to the amount of training data.
classifying what-type questions by head noun tagging. classifying what-type questions into proper semantic categories is found more challenging than classifying other types in question answering systems. in this paper, we propose to classify what-type questions by head noun tagging. the approach highlights the role of head nouns as the category discriminator of what-type questions. to reduce the semantic ambiguities of head noun, we integrate local syntactic feature, semantic feature and category dependency among adjacent nouns with conditional random fields (crfs). experiments on standard question classification data set show that the approach achieves state-of-the-art performances.
modeling the structure and dynamics of the consonant inventories: a complex network approach. we study the self-organization of the consonant inventories through a complex network approach. we observe that the distribution of occurrence as well as co-occurrence of the consonants across languages follow a power-law behavior. the co-occurrence network of consonants exhibits a high clustering coefficient. we propose four novel synthesis models for these networks (each of which is a refinement of the earlier) so as to successively match with higher accuracy (a) the above mentioned topological properties as well as (b) the linguistic property of feature economy exhibited by the consonant inventories. we conclude by arguing that a possible interpretation of this mechanism of network growth is the process of child language acquisition. such models essentially increase our understanding of the structure of languages that is influenced by their evolutionary dynamics and this, in turn, can be extremely useful for building future nlp applications.
good neighbors make good senses: exploiting distributional similarity for unsupervised wsd. we present an automatic method for senselabeling of text in an unsupervised manner. the method makes use of distributionally similar words to derive an automatically labeled training set, which is then used to train a standard supervised classifier for distinguishing word senses. experimental results on the senseval-2 and senseval-3 datasets show that our approach yields significant improvements over state-of-the-art unsupervised methods, and is competitive with supervised ones, while eliminating the annotation cost.
a concept-centered approach to noun-compound interpretation. a noun-compound is a compressed proposition that requires an audience to recover the implicit relationship between two concepts that are expressed as nouns. listeners recover this relationship by considering the most typical relations afforded by each concept. these relational possibilities are evident at a linguistic level in the syntagmatic patterns that connect nouns to the verbal actions that act upon, or are facilitated by, these nouns. we present a model of noun-compound interpretation that first learns the relational possibilities for individual nouns from corpora, and which then uses these to hypothesize about the most likely relationship that underpins a noun compound.
instance-based ontology population exploiting named-entity substitution. we present an approach to ontology population based on a lexical substitution technique. it consists in estimating the plausibility of sentences where the named entity to be classified is substituted with the ones contained in the training data, in our case, a partially populated ontology. plausibility is estimated by using web data, while the classification algorithm is instance-based. we evaluated our method on two different ontology population tasks. experiments show that our solution is effective, outperforming existing methods, and it can be applied to practical ontology population problems.
classifying chart cells for quadratic complexity context-free inference. in this paper, we consider classifying word positions by whether or not they can either start or end multi-word constituents. this provides a mechanism for "closing" chart cells during context-free inference, which is demonstrated to improve efficiency and accuracy when used to constrain the well-known charniak parser. additionally, we present a method for "closing" a sufficient number of chart cells to ensure quadratic worst-case complexity of context-free inference. empirical results show that this o(n2) bound can be achieved without impacting parsing accuracy.
sentence compression beyond word deletion. in this paper we generalise the sentence compression task. rather than simply shorten a sentence by deleting words or constituents, as in previous work, we rewrite it using additional operations such as substitution, reordering, and insertion. we present a new corpus that is suited to our task and a discriminative tree-to-tree transduction model that can naturally account for structural and lexical mismatches. the model incorporates a novel grammar extraction method, uses a language model for coherent output, and can be easily tuned to a wide range of compression specific loss functions.
experiments with reasoning for temporal relations between events. few attempts have been made to investigate the utility of temporal reasoning within machine learning frameworks for temporal relation classification between events in news articles. this paper presents three settings where temporal reasoning aids machine learned classifiers of temporal relations: (1) expansion of the dataset used for learning; (2) detection of inconsistencies among the automatically identified relations; and (3) selection among multiple temporal relations. feature engineering is another effort in our work to improve classification accuracy.
looking for trouble. this paper presents a method for mining potential troubles or obstacles related to the use of a given object. some example instances of this relation are (medicine, side effect) and (amusement park, height restriction). our acquisition method consists of three steps. first, we use an un-supervised method to collect training samples from web documents. second, a set of expressions generally referring to troubles is acquired by a supervised learning method. finally, the acquired troubles are associated with objects so that each of the resulting pairs consists of an object and a trouble or obstacle in using that object. to show the effectiveness of our method we conducted experiments using a large collection of japanese web documents for acquisition. experimental results show an 85.5% precision for the top 10,000 acquired troubles, and a 74% precision for the top 10% of over 60,000 acquired object-trouble pairs.
anomalies in the wordnet verb hierarchy. the wordnet verb hierarchy is tested, with a view to improving the performance of its applications, revealing topological anomalies and casting doubt on its semantic categories. encoded troponyms frequently misrepresent other kinds of entailment. approaches are proposed for correcting these anomalies including a new top ontology.
tighter integration of rule-based and statistical mt in serial system combination. recent papers have described machine translation (mt) based on an automatic post-editing or serial combination strategy whereby the input language is first translated into the target language by a rule-based mt (rbmt) system, then the target language output is automatically post-edited by a phrase-based statistical machine translation (smt) system. this approach has been shown to improve mt quality over rbmt or smt alone. in this previous work, there was a very loose coupling between the two systems: the smt system only had access to the final 1-best translations from rbmt. furthermore, the previous work involved european language pairs and relatively small training corpora. in this paper, we describe a more tightly integrated serial combination for the chinese-to-english mt task. we will present experimental evaluation results on the 2008 nist constrained data track where a significant gain in terms of both automatic and subjective metrics is achieved through the tighter coupling of the two systems.
computer aided correction and extension of a syntactic wide-coverage lexicon. the effectiveness of parsers based on manually created resources, namely a grammar and a lexicon, rely mostly on the quality of these resources. thus, increasing the parser coverage and precision usually implies improving these two resources. their manual improvement is a time consuming and complex task: identifying which resource is the true culprit for a given mistake is not always obvious, as well as finding the mistake and correcting it. some techniques, like van noord (2004) or sagot and villemonte de la clergerie (2006), bring a convenient way to automatically identify forms having potentially erroneous entries in a lexicon. we have integrated and extended such techniques in a wider process which, thanks to the grammar ability to tell how these forms could be used as part of correct parses, is able to propose lexical corrections for the identified entries. we present in this paper an implementation of this process and discuss the main results we have obtained on a syntactic wide-coverage french lexicon.
non-compositional language model and pattern dictionary development for japanese compound and complex sentences. to realize high quality machine translation, we proposed a non-compositional language model, and developed a sentence pattern dictionary of 226,800 pattern pairs for japanese compound and complex sentences consisting of 2 or 3 clauses. in pattern generation from a parallel corpus, compositional constituents that could be generalized were 74% of independent words, 24% of phrases and only 15% of clauses. this means that in japanese-to-english mt, most of the translation results as shown in the parallel corpus could not be obtained by methods based on compositional semantics. this dictionary achieved a syntactic coverage of 98% and a semantic coverage of 78%. it will substantially improve translation quality.
using discourse commitments to recognize textual entailment. in this paper, we introduce a new framework for recognizing textual entailment (rte) which depends on extraction of the set of publicly-held beliefs -- known as discourse commitments -- that can be ascribed to the author of a text (t) or a hypothesis (h). we show that once a set of commitments have been extracted from a t-h pair, the task of recognizing textual entailment is reduced to the identification of the commitments from a t which support the inference of the h. our system correctly identified entailment relationships in more than 80% of t-h pairs taken from all three of the previous pascal rte challenges, without the need for additional sources of training data.
a local alignment kernel in the context of nlp. this paper discusses local alignment kernels in the context of the relation extraction task. we define a local alignment kernel based on the smith-waterman measure as a sequence similarity metric and proceed with a range of possibilities for computing a similarity between elements of sequences. we propose to use distributional similarity measures on elements and by doing so we are able to incorporate extra information from the unlabeled data into a learning task. our experiments suggest that a la kernel provides promising results on some biomedical corpora largely outperforming a baseline.
syntactic reordering integrated with phrase-based smt. we present a novel approach to word reordering which successfully integrates syntactic structural knowledge with phrase-based smt. this is done by constructing a lattice of alternatives based on automatically learned probabilistic syntactic rules. in decoding, the alternatives are scored based on the output word order, not the order of the input. unlike previous approaches, this makes it possible to successfully integrate syntactic reordering with phrase-based smt. on an english- danish task, we achieve an absolute improvement in translation quality of 1.1 % bleu. manual evaluation supports the claim that the present approach is significantly superior to previous approaches.
discourse level opinion interpretation. this work proposes opinion frames as a representation of discourse-level associations which arise from related opinion topics. we illustrate how opinion frames help gather more information and also assist disambiguation. finally we present the results of our experiments to detect these associations.
investigating statistical techniques for sentence-level event classification. the ability to correctly classify sentences that describe events is an important task for many natural language applications such as question answering (qa) and summarisation. in this paper, we treat event detection as a sentence level text classification problem. we compare the performance of two approaches to this task: a support vector machine (svm) classifier and a language modeling (lm) approach. we also investigate a rule based method that uses hand crafted lists of terms derived from wordnet. these terms are strongly associated with a given event type, and can be used to identify sentences describing instances of that type. we use two datasets in our experiments, and evaluate each technique on six distinct event types. our results indicate that the svm consistently outperform the lm technique for this task. more interestingly, we discover that the manual rule based classification system is a very powerful baseline that outperforms the svm on three of the six event types.
active learning with sampling by uncertainty and density for word sense disambiguation and text classification. this paper addresses two issues of active learning. firstly, to solve a problem of uncertainty sampling that it often fails by selecting outliers, this paper presents a new selective sampling technique, sampling by uncertainty and density (sud), in which a k-nearest-neighbor-based density measure is adopted to determine whether an unlabeled example is an outlier. secondly, a technique of sampling by clustering (sbc) is applied to build a representative initial training data set for active learning. finally, we implement a new algorithm of active learning with sud and sbc techniques. the experimental results from three real-world data sets show that our method outperforms competing methods, particularly at the early stages of active learning.
using web-search results to measure word-group similarity. semantic relatedness between words is important to many nlp tasks, and numerous measures exist which use a variety of resources. thus far, such work is confined to measuring similarity between two words (or two texts), and only a handful utilize the web as a corpus. this paper introduces a distributional similarity measure which uses internet search counts and also extends to calculating the similarity within word-groups. the evaluation results are encouraging: for word-pairs, the correlations with human judgments are comparable with state-of-the-art web-search page-count heuristics. when used to measure similarities within sets of 10 words, the results correlate highly (up to 0.8) with those expected. relatively little comparison has been made between the results of different search-engines. here, we compare experimental results from google, windows live search and yahoo and find noticeable differences.
applying discourse analysis and data mining methods to spoken osce assessments. this paper looks at the transcribed data of patient-doctor consultations in an examination setting. the doctors are internationally qualified and enrolled in a bridging course as preparation for their australian medical council examination. in this study, we attempt to ascertain if there are measurable linguistic features of the consultations, and to investigate whether there is any relevant information about the communicative styles of the qualifying doctors that may predict satisfactory or non-satisfactory examination outcomes. we have taken a discourse analysis approach in this study, where the core unit of analysis is a 'turn'. we approach this problem as a binary classification task and employ data mining methods to see whether the application of which to richly annotated dialogues can produce a system with an adequate predictive capacity.
re-estimation of lexical parameters for treebank pcfgs. we present procedures which pool lexical information estimated from unlabeled data via the inside-outside algorithm, with lexical information from a treebank pcfg. the procedures produce substantial improvements (up to 31.6% error reduction) on the task of determining subcategorization frames of novel verbs, relative to a smoothed penn treebank-trained pcfg. even with relatively small quantities of unlabeled training data, the re-estimated models show promising improvements in labeled bracketing f-scores on wall street journal parsing, and substantial benefit in acquiring the subcategorization preferences of low-frequency verbs.
using hidden markov random fields to combine distributional and pattern-based word clustering. word clustering is a conventional and important nlp task, and the literature has suggested two kinds of approaches to this problem. one is based on the distributional similarity and the other relies on the co-occurrence of two words in lexicosyntactic patterns. although the two methods have been discussed separately, it is promising to combine them since they are complementary with each other. this paper proposes to integrate them using hidden markov random fields and demonstrates its effectiveness through experiments.
topic identification for fine-grained opinion analysis. within the area of general-purpose fine-grained subjectivity analysis, opinion topic identification has, to date, received little attention due to both the difficulty of the task and the lack of appropriately annotated resources. in this paper, we provide an operational definition of opinion topic and present an algorithm for opinion topic identification that, following our new definition, treats the task as a problem in topic coreference resolution. we develop a methodology for the manual annotation of opinion topics and use it to annotate topic information for a portion of an existing general-purpose opinion corpus. in experiments using the corpus, our topic identification approach statistically significantly outperforms several non-trivial baselines according to three evaluation measures.
using syntactic information for improving why-question answering. in this paper, we extend an existing paragraph retrieval approach to why-question answering. the starting-point is a system that retrieves a relevant answer for 73% of the test questions. however, in 41% of these cases, the highest ranked relevant answer is not ranked in the top-10. we aim to improve the ranking by adding a re-ranking module. for re-ranking we consider 31 features pertaining to the syntactic structure of the question and the candidate answer. we find a significant improvement over the baseline for both success@10 and mrr@150. the most important features for re-ranking are the baseline score, the presence of cue words, the question's main verb, and the relation between question focus and document title.
coreference systems based on kernels methods. various types of structural information - e.g., about the type of constructions in which binding constraints apply, or about the structure of names - play a central role in coreference resolution, often in combination with lexical information (as in expletive detection). kernel functions appear to be a promising candidate to capture structure-sensitive similarities and complex feature combinations, but care is required to ensure they are exploited in the best possible fashion. in this paper we propose kernel functions for three subtasks of coreference resolution - binding constraint detection, expletive identification, and aliasing - together with an architecture to integrate them within the standard framework for coreference resolution.
chinese term extraction using minimal resources. this paper presents a new approach for term extraction using minimal resources. a term candidate extraction algorithm is proposed to identify features of the relatively stable and domain independent term delimiters rather than that of the terms. for term verification, a link analysis based method is proposed to calculate the relevance between term candidates and the sentences in the domain specific corpus from which the candidates are extracted. the proposed approach requires no prior domain knowledge, no general corpora, no full segmentation and minimal adaptation for new domains. consequently, the method can be used in any domain corpus and it is especially useful for resource-limited domains. evaluations conducted on two different domains for chinese term extraction show quite significant improvements over existing techniques and also verify the efficiency and relative domain independent nature of the approach. experiments on new term extraction also indicate that the approach is quite effective for identifying new terms in a domain making it useful for domain knowledge update.
homotopy-based semi-supervised hidden markov models for sequence labeling. this paper explores the use of the homotopy method for training a semi-supervised hidden markov model (hmm) used for sequence labeling. we provide a novel polynomial-time algorithm to trace the local maximum of the likelihood function for hmms from full weight on the labeled data to full weight on the unlabeled data. we present an experimental analysis of different techniques for choosing the best balance between labeled and unlabeled data based on the characteristics observed along this path. furthermore, experimental results on the field segmentation task in information extraction show that the homotopy-based method significantly outperforms em-based semi-supervised learning, and provides a more accurate alternative to the use of held-out data to pick the best balance for combining labeled and unlabeled data.
automatic seed word selection for unsupervised sentiment classification of chinese text. we describe and evaluate a new method of automatic seed word selection for un-supervised sentiment classification of product reviews in chinese. the whole method is unsupervised and does not require any annotated training data; it only requires information about commonly occurring negations and adverbials. unsupervised techniques are promising for this task since they avoid problems of domain-dependency typically associated with supervised methods. the results obtained are close to those of supervised classifiers and sometimes better, up to an f1 of 92%.
stopping criteria for active learning of named entity recognition. active learning is a proven method for reducing the cost of creating the training sets that are necessary for statistical nlp. however, there has been little work on stopping criteria for active learning. an operational stopping criterion is necessary to be able to use active learning in nlp applications. we investigate three different stopping criteria for active learning of named entity recognition (ner) and show that one of them, gradient-based stopping, (i) reliably stops active learning, (ii) achieves nearoptimal ner performance, (iii) and needs only about 20% as much training data as exhaustive labeling.
modeling semantic containment and exclusion in natural language inference. we propose an approach to natural language inference based on a model of natural logic, which identifies valid inferences by their lexical and syntactic features, without full semantic interpretation. we greatly extend past work in natural logic, which has focused solely on semantic containment and monotonicity, to incorporate both semantic exclusion and implicativity. our system decomposes an inference problem into a sequence of atomic edits linking premise to hypothesis; predicts a lexical entailment relation for each edit using a statistical classifier; propagates these relations upward through a syntax tree according to semantic properties of intermediate nodes; and composes the resulting entailment relations across the edit sequence. we evaluate our system on the fracas test suite, and achieve a 27% reduction in error from previous work. we also show that hybridizing an existing rte system with our natural logic system yields significant gains on the rte3 test suite.
evaluating unsupervised part-of-speech tagging for grammar induction. this paper explores the relationship between various measures of unsupervised part-of-speech tag induction and the performance of both supervised and unsupervised parsing models trained on induced tags. we find that no standard tagging metrics correlate well with unsupervised parsing performance, and several metrics grounded in information theory have no strong relationship with even supervised parsing performance.
multi-criteria-based strategy to stop active learning for data annotation. in this paper, we address the issue of deciding when to stop active learning for building a labeled training corpus. firstly, this paper presents a new stopping criterion, classification-change, which considers the potential ability of each unlabeled example on changing decision boundaries. secondly, a multi-criteria-based combination strategy is proposed to solve the problem of predefining an appropriate threshold for each confidence-based stopping criterion, such as max-confidence, min-error, and overall-uncertainty. finally, we examine the effectiveness of these stopping criteria on uncertainty sampling and heterogeneous uncertainty sampling for active learning. experimental results show that these stopping criteria work well on evaluation data sets, and the combination strategies outperform individual criteria.
a hybrid generative/discriminative framework to train a semantic parser from an un-annotated corpus. we propose a hybrid generative/discriminative framework for semantic parsing which combines the hidden vector state (hvs) model and the hidden markov support vector machines (hm-svms). the hvs model is an extension of the basic discrete markov model in which context is encoded as a stack-oriented state vector. the hm-svms combine the advantages of the hidden markov models and the support vector machines. by employing a modified k-means clustering method, a small set of most representative sentences can be automatically selected from an un-annotated corpus. these sentences together with their abstract annotations are used to train an hvs model which could be subsequently applied on the whole corpus to generate semantic parsing results. the most confident semantic parsing results are selected to generate a fully-annotated corpus which is used to train the hm-svms. the proposed framework has been tested on the darpa communicator data. experimental results show that an improvement over the baseline hvs parser has been observed using the hybrid framework. when compared with the hm-svms trained from the fully-annotated corpus, the hybrid framework gave a comparable performance with only a small set of lightly annotated sentences.
binning optimization based on ssta for transparently-latched circuits. with increasing process variation, binning has become an important technique to improve the values of fabricated chips, especially in high performance microprocessors where transparent latches are widely used. in this paper, we formulate and solve the binning optimization problem that decides the bin boundaries and their testing order to maximize the benefit (considering the test cost) for a transparently-latched circuit. the problem is decomposed into three sub-problems which are solved sequentially. first, to compute the clock period distribution of the transparently-latched circuit, a sample-based ssta approach is developed which is based on the generalized stochastic collocation method (gscm) with sparse grid technique. the minimal clock period on each sample point is found by solving a minimal cycle ratio problem in the constraint graph. second, a greedy algorithm is proposed to maximize the sales profit by iteratively assigning each boundary to its optimal position. then, an optimal algorithm of o(n log n) runtime is used to generate the optimal testing order of bin boundaries to minimize the test cost, based on alphabetic tree. experiments on all the iscas'89 sequential benchmarks with 65-nm technology show 6.69% profit improvement and 14.00% cost reduction in average. the results also demonstrate that the proposed ssta method achieves an error of 0.70% and speedup of 110x in average compared with the monte carlo simulation.
first steps towards sat-based formal analog verification. boolean satisfiability (sat) based methods have traditionally been popular for formally verifying properties for digital circuits. we present a novel methodology for formulating a spice-type circuit simulation problem as a satisfiability problem. we start with a circuit level netlist, capture the non-linear behavior of the circuits at the transistor level via conservative approximations and transform the simulation problem into a search problem that can be exhaustively explored via a sat solver. thus, for dc as well as fixed time-step based transient and periodic steady state (pss) simulation formulations, the solutions produced by the solver are formal in nature. we also present algorithms for abstraction refinement and smart interval generation to improve the computational efficiency of our proposed solution scheme. we have implemented our ideas into a tool called fspice which is the first attempt at building a formal spice engine. we demonstrate the applicability of our ideas by showing experimental results using pruned versions of real designs that faced challenges during chip tape-out.
thermal modeling for 3d-ics with integrated microchannel cooling. integrated microchannel liquid-cooling technology is envisioned as a viable solution to alleviate an increasing thermal stress imposed by 3d stacked ics. thermal modeling for microchannel cooling is challenging due to its complicated thermal-wake effect, a localized temperature wake phenomenon downstream of a heated source in the flow. this paper presents a fast and accurate thermal-wake aware thermal model for integrated microchannel 3d ics. validation results show the proposed thermal model achieves more than 400x speed up and only 2.0% error in comparison with a commercial numerical simulation tool. we also demonstrate the use of the proposed thermal model for thermal optimization during the ic placement stage. we find that due to the thermal-wake effect, tiles are placed in the descending order of power magnitude along the flow direction. we also find that modeling thermal-wakes is critical for generating a thermal-aware placement for integrated microchannel-cooled 3d ic. it could result in up to 25&deg;c peak temperature difference according to our experiments.
a framework for early and systematic evaluation of design rules. design rules have been the primary contract between technology and design and are likely to remain so to preserve abstractions and productivity. while current approaches for defining design rules are largely unsystematic and empirical in nature, this paper offers a novel framework for early and systematic evaluation of design rules and layout styles in terms of major layout characteristics of area, manufacturability, and variability. due to the focus on co-exploration in early stages of technology development, we use first order models of variability and manufacturability (instead of relying on accurate simulation) and layout topology/congestion-based area estimates (instead of explicit and slow layout generation). the framework is used to efficiently co-evaluate several debatable rules (evaluation for a 104-cell library takes 20 minutes). results show that: a) diffusion-rounding mainly from diffusion power-straps is a dominant source of variability, b) cell-area overhead of fixed gate-pitch implementation compared to 1d-poly implementation is tolerable (5%) given the improvement in variability, and c) 1d-poly restriction, which improves manufacturability and variability, has almost no area overhead compared to 2d-poly. in addition, we explore gate-spacing rules using our evaluation framework. this exploration yields almost identical values as those of a commercial 65nm process, which serves as a validation for our approach.
ipr: in-place reconfiguration for fpga fault tolerance. we describe in-place reconfiguration (ipr) for lut-based fpgas, an algorithm that maximizes identical configuration bits for complementary inputs of a lut thereby reducing the propagation of faults seen at a pair of complementary inputs. based on ipr, we develop a fault-tolerant logic resynthesis algorithm which decreases the circuit fault rate while preserving functionality and topology of the lut-based logic network. since the topology is preserved, the resynthesis algorithm can be applied post-layout and without changes in physical design. compared to the state-of-the-art academic technology mapper berkeley abc, ipr reduces the relative fault rate by 48% and increases mttf by 1.94x with the same area and performance, and ipr combined with a previous fault-tolerant logic resynthesis algorithm (rose) reduces the relative fault rate by 49% and increases mttf by 2.40x with 19% less area but same performance. the above improvement assumes a stochastic single fault and more improvement is expected for multi-fault models.
how to consider shorts and guarantee yield rate improvement for redundant wire insertion. this paper accurately considers wire short defects and proposes an algorithm to guarantee ic chip yield rate improvement for redundant wire insertion. without considering yield rate degradation caused by shorts, traditional methods may even lead to yield rate loss. however, shorts are more complicated to analyze than opens. moreover, since any two points of a routed net can be connected by a redundant wire, the number of possible insertion patterns for a chip is un-tractable. to maximize yield rate improvement and to make the problem tractable, we identify a key insight, tolerance-ratio, as an effective guide for choosing insertion patterns and insertion order. finally, to guarantee yield rate improvement, only positive gain redundant wires are committed. experimental results show that, compared with unprocessed cases, all yield rate improvements in the proposed algorithm are positive, and the defect rates are reduced by up to 65% and by 24% on average. on the other hand, without considering shorts, the defect rate can increase as much as 7%.
voltage binning under process variation. process variation is recognized as a major source of parametric yield loss, which occurs because a fraction of manufactured chips do not satisfy timing or power constraints. on the other hand, both chip performance and chip leakage power depend on supply voltage. this dependence can be used for converting the fraction of too slow or too leaky chips into good ones by adjusting their supply voltage. this technique is called voltage binning [4]. all the manufactured chips are divided into groups (bins) and each group is assigned its individual supply voltage. this paper proposes a statistical technique of yield computation for different voltage binning schemes using results of statistical timing and variational power analysis. the paper formulates and solves the problem of computing optimal supply voltages for a given binning scheme.
an efficient pre-assignment routing algorithm for flip-chip designs. the flip-chip package is introduced for modern ic designs with higher integration density and larger i/o counts. in this paper, we consider the pre-assignment flip-chip routing problem with predefined connections between driver pads and bump pads. this problem has been shown to be much more difficult than the free-assignment one, but is more popular in real-world designs because the connections between driver pads and bump pads are typically pre-determined by ic or packaging designers. based on the concept of routing sequence exchange, we propose a very efficient global routing algorithm by computing the weighted longest common subsequence (wlcs) and the maximum planar subset of chords (mpsc) for pre-assignment flip-chips. we observe that the existing work over constrains the capacity of a routing tile, which might miss some critical solution space with a better routing solution (e.g., smaller wirelength), and provide a remedy for this insufficiency to identify a better solution in a more complete solution space. we also develop a constant-time routability analyzer to check if a given set of wires can pass through a tile. experimental results show that our router can achieve a 122x speedup with even better solution quality (same routability with slightly smaller wire-length), compared with a state-of-the-art flip-chip router based on integer linear programming (ilp).
intrinsic nbti-variability aware statistical pipeline performance assessment and tuning. random process variation and variability intrinsic to pmos negative bias temperature instability (nbti-induced statistical variation) are two major reliability concerns as transistor dimensions scales with technology. previous works have studied these two sources of variation separately at device and circuit level. we study the impact of the interaction between intrinsic pmos nbti variability and time0 process variability on circuit delay spread. a statistical pipeline timing error model is proposed including both the variability sources to predict its impact on pipeline stage count. it is shown that a wide difference in statistical timing response to intrinsic nbti variability exists among different circuits. traditional design time nbti-aware delay guard-banding is proved to be statistically insufficient in pipelines and an excess of 2x guard-band needs to be incorporated at the end of 10 years. however, the guard-band is shown to be reduced by 30% when the dynamic cycle time stealing technique is employed.
an efficient algorithm for modeling spatially-correlated process variation in statistical full-chip leakage analysis. statistical full-chip leakage analysis considering spatial correlation is highly expensive due to its o(n2) complexity for logic circuits with n gates. although efforts have been made to reduce the cost at the loss of accuracy, existing methods are still unsuitable for large-scale problems. in this paper we resolve the problem by re-formulating the computation to one that can be done efficiently using a well-developed technique that has been widely used in fast em simulation and machine learning areas. the resulting algorithm is provably of o(n) or o(n log n) complexity with well-defined and easily-controlled error bounds. experiments show that using the proposed method it is feasible to handle milliongate circuits within only a few minutes on a regular desktop pc. the corresponding error is less than 0.5% compared to exhausted computation that takes more than 3 days. the proposed method is about 300x faster and 10x more accurate compared to existing grid-approximation method.
psta-based branch and bound approach to the silicon speedpath isolation problem. the lack of good "correlation" between pre-silicon simulated delays and measured delays on silicon (silicon data) has spurred efforts on so-called silicon debug. the identification of speed-limiting paths, or simply speedpaths, in silicon debug is a crucial step, required for both "fixing" failing paths and for accurate learning from silicon data. we propose using characterized, pre-silicon, variational timing models to identify speedpaths that can best explain the observed delays from silicon measurements. delays of all logic paths are written as affine functions of process parameters, called hyperplanes, and a branch and bound approach is then applied to find the "best" path combinations. our method has been tested on a set of iscas-89 circuits and the results show that it accurately identifies the speedpaths in most cases, and that this is achieved in a very efficient manner.
genetic design automation. electronic design automation (eda) tools have facilitated the design of ever more complex integrated circuits each year. synthetic biology would also benefit from the development of genetic design automation (gda) tools. existing gda tools require biologists to design genetic circuits at the molecular level, roughly equivalent to designing electronic circuits at the layout level. analysis of these circuits is also performed at this very low level. this paper presents the background and issues involved in the development of such a gda tool for modeling, analysis, and design.
adaptive power management using reinforcement learning. system level power management must consider the uncertainty and variability that comes from the environment, the application and the hardware. a robust power management technique must be able to learn the optimal decision from past history and improve itself as the environment changes. this paper presents a novel online power management technique based on model-free constrained reinforcement learning (rl). it learns the best power management policy that gives the minimum power consumption for a given performance constraint without any prior information of workload. compared with existing machine learning based power management techniques, the rl based learning is capable of exploring the trade-off in the power-performance design space and converging to a better power management policy. experimental results show that the proposed rl based power management achieves 24% and 3% reduction in power and latency respectively comparing to the existing expert based power management.
an accurate and efficient performance analysis approach based on queuing model for network on chip. an accurate and highly-efficient performance analysis approach is extremely important for the early-stage designs of network-on-chip. in this paper, the novel m/g/i/n queuing models for generic routers are proposed to analyze various packet blockings and then the performance analysis algorithm is presented to estimate some key metrics in terms of packet latency, buffer utilization, etc. for single-channel and multi-channel routers, the comparisons between analysis and observed results validate that the proposed approach with mean errors of 6.9% and 7.8% achieve the speed-ups of 240 and 210 times respectively. in our design methodology, this approach can not only effectively direct noc synthesis process but also be conveniently applied to multi-objective optimizations to find the best mapping solutions.
enhanced reliability-aware power management through shared recovery technique. while dynamic voltage scaling (dvs) remains as a popular energy management technique for real-time embedded applications, recent research has identified significant and negative impact of voltage scaling on system reliability. for this reason, a number of reliability-aware power management (ra-pm) schemes were recently proposed to preserve the system reliability when dvs is used. in this paper, we propose a new approach, called the shared recovery (shr) technique, to minimize the system-level energy consumption while still preserving the system's original reliability. the main idea of the shr technique is to avoid the offline allocation of separate recovery tasks to the scaled tasks by assigning a global/shared recovery block that can be used by any task at run-time. our simulation results show that, compared to the existing ra-pm schemes, our scheme can achieve up to 35% energy savings. further, this performance is shown to be comparable to the maximum energy savings that can be achieved by any algorithm. interestingly, our extensive evaluation indicates that shr offers also non-trivial gains over the previous algorithms on the reliability side. further, a dynamic extension is proposed to improve energy and reliability management at run-time by reducing the size of the recovery block and re-using the slack that arises from early completions.
multi-level clustering for clock skew optimization. clock skew scheduling has been effectively used to reduce the clock period of sequential circuits. however, this technique may become impractical if a different skew must be applied for each memory element. this paper presents a new technique for clock skew scheduling constrained by the number of skew domains. the technique is based on a multi-level clustering approach that progressively groups flip-flops with skew affinity. this new technique has been compared with previous work, showing the efficiency in the obtained performance and computational cost. as an example, the skews for an opensparc with almost 16k flip-flops and 500k paths have been calculated in less than 5 minutes when using only 2 to 5 skew domains.
qlmor: a new projection-based approach for nonlinear model order reduction. we present a new projection-based nonlinear model order reduction method, named qlmor (mor via quadratic-linear systems). qlmor employs two novel ideas: (1) we show that daes (differential-algebraic equations) with many commonly-encountered nonlinear kernels can be re-written equivalently into a special format, qldaes (quadratic-linear differential algebraic equations, i.e., daes that are quadratic in their state variables and linear in their inputs); (2) we adapt the moment-matching reduction technique of norm[1] to reduce these qldaes into qldaes of much smaller size. because of the generality of the qldae form, qlmor has significantly broader applicability than taylor-expansion based methods [2, 3, 1]. importantly, qlmor, unlike norm, totally avoids explicit moment calculations (aib terms), hence it has improved numerical stability properties as well. because the reduced model has only quadratic nonlinearities (i.e., no cubic and higher-order terms), its computational complexity is less than that of similar prior methods[2, 3, 1]. we also prove that qlmor-reduced models preserve local passivity, and provide an upper bound on the size of the qldaes derived from a polynomial system. we compare qlmor against prior methods [2, 3, 1] on a circuit and a biochemical reaction-like system, and demonstrate that qlmor-reduced models retain accuracy over a significantly wider range of excitation than taylor-expansion based methods [2, 3, 1]. indeed, qlmor is able to reduce systems that taylor-expansion based methods fail to reduce due to passivity loss and impractically high computational costs. qlmor therefore demonstrates that volterra-kernel based nonlinear mor techniques can in fact have far broader applicability than previously suspected, possibly being competitive with trajectory-based methods (e.g., tpwl [4]) and nonlinear-projection based methods (e.g., manimor [5]).
energy reduction for stt-ram using early write termination. the emerging spin torque transfer memory (stt-ram) is a promising candidate for future on-chip caches due to stt-ram's high density, low leakage, long endurance and high access speed. however, one of the major challenges of stt-ram is its high write current, which is disadvantageous when used as an on-chip cache since the dynamic power generated is too high. in this paper, we propose early write termination (ewt), a novel technique to significantly reduce write energy with no performance penalty. ewt can be implemented with low complexity and low energy overhead. our evaluation shows that up to 80% of write energy reduction can be achieved through ewt, resulting 33% less total energy consumption, and 34% reduction in ed2. these results indicate that ewt is an effective and practical scheme to improve the energy efficiency of a stt-ram cache.
scan power reduction in linear test data compression scheme. xor network-based on-chip test compression schemes have been widely employed in large industrial scan designs due to their high compression ratio and efficient decompression mechanism. nevertheless, such a scheme necessitates high unspecified bit ratios in the original test cubes, resulting in quite significant difficulties in preprocessing test cubes for scan power reduction. the linear mapping from the original cubes to the compressed seeds typically provides extra degrees of flexibility as multiple seeds may reconstruct the test cube. appreciable power reductions in the decompressed test data can be attained through the pinpointing of the power-optimal seeds during the compression phase. the proposed work explores the aforementioned flexibility in the seed space, and proposes the mathematical and algorithmic framework for a power-aware linear test compression scheme. the proposed technique incurs no hardware overhead over the traditional linear compression scheme; it can be easily embedded furthermore into the industrial test compaction/compression flow. experimental results confirm that the proposed technique delivers significant scan power reduction with negligible impact on the compression ratio.
voltage-drop aware analytical placement by global power spreading for mixed-size circuit designs. excessive supply voltage drops in a circuit may lead to significant circuit performance degradation and even malfunction. to handle this problem, existing power delivery aware placement algorithms model voltage drops as an optimization objective. we observe that directly minimizing voltage drops in an objective function might not resolve voltage-drop violations and might even cause problems in power-integrity convergence. to remedy this deficiency, in this paper, we propose new techniques to incorporate device power spreading forces into a mixed-size analytical placement framework. unlike the state-of-the-art previous work that handles the worst voltage-drop spots one by one, our approach simultaneously and globally spreads all the blocks with voltage-drop violations to desired locations directly to minimize the violations. to apply the power force, we model macro current density and power rails for our placement framework to derive desired macro/cell locations. to further improve the solution quality, we propose an efficient mathematical transformation to adjust the power force direction and magnitude. experimental results show that our approach can substantially improve the voltage drops, wirelength, and runtime over the previous work.
grplacer: improving routability and wire-length of global routing with circuit replacement. placement profoundly impacts physical design owing to its role in determining the lower bound of a circuit wirelength, as well as the circuit routability. to close the gap between placement and routing, this study integrates global routing and placement to improve the wirelength estimation accuracy of placement. two methods, called wirelength-reduced cell shifting and cell rearrangement by bipartite matching, are applied to minimize wirelength. cell sorting based congestion reduction and pattern-prerouting based congestion-avoided cell shifting are proposed to reduce congestion. experimental results demonstrate that the proposed placer improves total routed wirelength by 2% to rooster on ibmv2 benchmarks. moreover, the proposed grplacer resolves the original congested regions of the placements generated by rooster. compare with the detailed placer in rooster, our work can reduce more routed wire length and remove more overflows.
an efficient wakeup scheduling considering resource constraint for sensor-based power gating designs. power gating has been a very effective way to reduce leakage power. one important design issue for a power gating design is to limit the surge current during the wakeup process. normally, a wakeup scheduling is required to control turn-on times of sleep transistors. in this paper, we adopt a voltage sensor to compare pre-designed reference voltages with the virtual ground voltage and use the comparison result to determine turn-on times of sleep transistors. special properties and optimizations of using voltage sensors are discussed. since a wakeup scheduling with fast wakeup time may require significant hardware resources, we propose a new wakeup scheduling formulation which considers the trade-off between wakeup times and hardware resources. our experimental results show that with small increases on wakeup times, we can reduce significant hardware resources for a power gating design.
resilience in computer systems and networks. the term resilience is used differently by different communities. in general engineering systems, fast recovery from a degraded system state is often termed as resilience. computer networking community defines it as the combination of trustworthiness (dependability, security, performability) and tolerance (survivability, disruption tolerance, and traffic tolerance). dependable computing community defined resilience as the persistence of service delivery that can justifiably be trusted, when facing changes. in this paper, resilience definitions of systems and networks will be presented. metrics for resilience will be compared with dependability metrics such as availability, performance, performability. simple examples will be used to show quantification of resilience via probabilistic analytic models.
grema: graph reduction based efficient mask assignment for double patterning technology. double patterning technology (dpt) has emerged as the most hopeful candidate for the next technology node of the itrs roadmap [1]. the goal of a dpt decomposer is to decompose the entire layout on each layer onto two masks. it assigns two features to different masks if their spacing is less than a predefined threshold. besides, some features must be sliced and put onto two masks so that there would be a feasible solution for mask assignment. such slicing will cause stitches that affect yield. so decomposer needs to minimize their number. in this paper, we formulate the dpt decomposition problem as a maximum cut problem. we propose an extremely efficient two-stage decomposition algorithm called grema. the first stage of grema generates a set of candidate stitches to ensure that feasible solutions exist for dpt decomposition. the second stage uses maximum cut to find the minimal set of stitches. our decomposer is able to solve much larger realistic design problems. experiments demonstrated that grema achieved great performance on resolving conflicts with greatly reduced runtime.
characterizing within-die variation from multiple supply port iddq measurements. the importance of within-die process variation and its impact on product yield has increased significantly with scaling. within-die variation is typically monitored by embedding characterization circuits in product chips. in this work, we propose a minimally-invasive, low-overhead technique for characterizing within-die variation. the proposed technique monitors within-die variation by measuring quiescent (iddq) currents at multiple power supply ports during wafer-probe test. we show that the spatially distributed nature of power ports enables spatial observation of process variation. we demonstrate our methodology on an experimental test-chip fabricated in 65-nm technology. the measurement results show that the iddq currents drawn by multiple power supply ports correlate very well with the variation trends introduced by state-dependent leakage patterns.
retiming and time borrowing: optimizing high-performance pulsed-latch-based circuits. pulsed-latches take advantage of both latches in their high performance and flip-flops in their convenience of timing analysis. to minimize the clock period of pulsed-latch-based circuits for a higher performance, a problem of combined retiming and time borrowing is formulated, where the latter is enabled by using a handful of different pulse widths. the problem is first approached by formulating it as an integer linear programming to lay a theoretical foundation. a heuristic approach is proposed, which solves the problem by performing clock skew scheduling for the minimum clock period and gradually converting skew into a combination of retiming and time borrowing. experiments with 45-nm technology demonstrate that the clock period close to the minimum can be achieved for all benchmark circuits with an average of 1.03x with less use of extra latches compared to the conventional retiming.
pre-bond testable low-power clock tree design for 3d stacked ics. pre-bond testing of 3d stacked ics involves testing individual dies before bonding. the overall yield of 3d ics improves with prebond testability because designers can avoid stacking defective dies with good ones. however, pre-bond testability presents unique challenges to 3d clock tree design. first, each die needs a complete 2d clock tree for the pre-bond testing. in addition, the entire 3d stack needs a complete 3d clock tree for post-bond testing and normal operations. in the case of two-die stack, a straightforward solution is to have two complete 2d clock trees connected with a single through-silicon-via (tsv). we show that this solution suffers from long wirelength and high clock power consumption. instead, our algorithm minimizes the overall wirelength and clock power consumption while providing the pre-bond testability and post-bond operability under given skew and slew constraints. compared with the single-tsv solution, spice simulation results show that our multi-tsv approach significantly reduces the clock power by up to 15.9% for two-die and 29.7% for four-die stack. in addition, the wirelength reduction is up to 24.4% and 42.0%.
yield estimation of sram circuits using "virtual sram fab". static random access memories (srams) are key components of modern vlsi designs and a major bottleneck to technology scaling as they use the smallest size devices with high sensitivity to manufacturing details. analysis performed at the "schematic" level can be deceiving as it ignores the interdependence between the implementation layout and the resulting electrical performance. we present a computational framework, referred to as "virtual sram fab", for analyzing and estimating pre-si sram array manufacturing yield considering both lithographic and electrical variations. the framework is being demonstrated for sram design/optimization in 45nm nodes and currently being used for both 32nm and 22nm technology nodes. the application and merit of the framework are illustrated using two different sram cells in a 45nm pd/soi technology, which have been designed for similar stability/performance, but exhibit different parametric yields due to layout/lithographic variations. we also demonstrate the application of virtual sram fab for prediction of layout-induced imbalance in an 8t cell, which is a popular candidate for sram implementation in 32-22nm technology nodes.
gene-regulatory memories: electrical-equivalent modeling, simulation and parameter identification. the development of gene-regulatory memory circuits provides key understandings of biological information storage and enables new biological applications. computer models and simulations can provide quantitative analysis and prediction of the behaviors and functions of genetic networks, thereby providing valuable verification and design guidance. in this paper, we model the nonlinear dynamics associated with various chemical reactions in gene-regulatory memory networks using chemical reaction equations. these reaction equations are mapped into a set of electrical-equivalent models and the network is simulated by an extended spice-like circuit simulation environment. furthermore, we address the practical difficulty in direct characterization of network model parameters by developing a simulation-driven bayesian framework for parameter identification. to ensure the reliable identification of key system properties, we propose a two-step structure-preserving parameter identification approach. the first step infers bistability, the most critical characteristics of a memory device; and the second step is geared towards identifying dynamical properties of the network while maintaining the identified bistability. we demonstrate the proposed approaches through extensive simulations that well agree with established biological understandings and identified networks that recreate measured circuit responses in a statistical sense.
a parallel preconditioning strategy for efficient transistor-level circuit simulation. we describe a parallel computing approach for large-scale spice-accurate circuit simulation, which is based on a new strategy for the parallel preconditioned iterative solution of circuit matrices. this strategy consists of several steps, including singleton removal, block triangular form (btf) reordering, hypergraph partitioning, and a block jacobi pre-conditioner. our parallel implementation makes use of a mixed load balance, employing a different parallel partition for the matrix load and solve. based on message-passing, our circuit simulation code was originally designed for large parallel computers, but for the purposes of this paper we demonstrate that it also gives good parallel speedup in modern multi-core environments. we show that our new parallel solver outperforms a serial direct solver, a parallel direct solver and an alternative iterative solver on a set of circuit test problems.
generation of optimal obstacle-avoiding rectilinear steiner minimum tree. in this paper, we present an efficient method to solve the obstacle-avoiding rectilinear steiner tree problem optimally. our work is developed based on the geosteiner approach, modified and extended to allow rectilinear blockages in the routing region. we extended the proofs on the possible topologies of full steiner tree (fst) in [4] to allow blockages, where fst is the basic concept used in geosteiner. we can now handle hundreds of pins with multiple blockages, generating an optimal solution in a reasonable amount of time. this work serves as a pioneer in providing an optimal solution to this difficult problem.
nanoelectromechanical (nem) relays integrated with cmos sram for improved stability and low leakage. we present a hybrid nanoelectromechanical (nem)/cmos static random access memory (sram) cell, in which the two pull-down transistors of a conventional cmos six transistor (6t) sram cell are replaced with nem relays. this sram cell utilizes the infinite subthreshold slope and hysteretic properties of nem relays to dramatically increase the cell stability compared to the conventional cmos 6t sram cells. it also utilizes the zero off-state leakage of nem relays to significantly decrease static power dissipation. the structure is designed so that the relatively long mechanical delay of the nem relays does not result in performance degradation. circuit simulations are performed using a veriloga model of a nem relay. compared to a 65nm cmos 6t sram cell, when 10nm-gap nem relays (pull-in voltage = 0.8v, pull-out voltage = 0.2v, on resistance = 1k&omega;) are integrated, hold and read static noise margin (snm) improve by ~110% and ~250%, respectively. in addition, static power dissipation decreases by ~85%. the write delay decreases by ~60%, while read delay decreases by ~10%. the advantages in snm and static power dissipation are expected to increase with scaling.
interpolant generation without constructing resolution graph. in this paper, we proposed a novel interpolant generation algorithm without constructing the resolution graph of the unsatisfiability proof. our algorithm generates the interpolant by building sub-interpolants from conflict analyses and then merges them based on the last decision conflict. the experimental results show that our algorithm has the advantages over the prior interpolant generation techniques in both memory usage and interpolation circuit size.
an electrical-level superposed-edge approach to statistical serial link simulation. brute-force simulation approaches to estimating serial-link bit-error rates (bers) become computationally intractable for the case when bers are low and the interconnect electrical response is slow enough to generate intersymbol interference that spans dozens of bit periods. electrical-level statistical simulation approaches based on superposing pulse responses were developed to address this problem, but such pulse-based methods have difficulty analyzing jitter and rise/fall asymmetry. in this paper we present a superposing-edge approach for statistical simulation, as edge-based methods handle rise/fall asymmetry and jitter in straightforward way. we also resolve a key problem in using edge-based approaches, that edges are always correlated, by deriving an efficient inductive approach for propagating the edge correlations. examples are presented demonstrating the edge-based method's accuracy and effectiveness in analyzing combinations of uniform, gaussian, and periodic distributed random jitter.
memory organization and data layout for instruction set extensions with architecturally visible storage. present application specific embedded systems tend to choose instruction set extensions (ises) based on limitations imposed by the available data bandwidth to custom functional units (cfus). adoption of the optimal ise for an application would, in many cases, impose formidable cost increase in order to achieve the required data bandwidth. in this paper we propose a novel methodology for laying out data in memories, generating high-bandwidth memory systems by making use of existing low-bandwidth low-cost ones and designing custom functional units all with the desirable data bandwidth for only a fraction of the additional cost required by traditional techniques.
a study of through-silicon-via impact on the 3d stacked ic layout. through-silicon-via (tsv) is the enabling technology for the fine-grained 3d integration of multiple dies into a single stack. these tsvs occupy non-negligible silicon area because of their sheer size. this significant silicon area occupied by the tsvs and the interconnections made to the tsvs greatly affect area, power, performance, and reliability of 3d ic layouts. well-managed tsvs alleviate congestion, reduce wirelength, and improve performance, whereas excessive tsvs not only increase the die area, but also have negative impact on many design objectives. in this paper, we study the impact of tsv on various aspects of 3d layouts. we use gdsii layouts of 2d and 3d designs, and thoroughly compare the pros and cons of tsv usage. we propose a new force-directed 3d gate-level placement that efficiently handles tsvs. in addition, we present an algorithm that assigns tsvs to nets to complete routing that involves tsvs. this algorithm, together with our 3d placer, is integrated into a commercial p&r tool to generate fully validated gdsii layouts. our experiments based on synthesized benchmarks indicate that our algorithms help generate gdsii layouts of 3d designs that are optimized in terms of area, wirelength, and metal layer count.
exact route matching algorithms for analog and mixed signal integrated circuits. as soc designs are getting more popular, the importance of design automation for analog and mixed-signal ics is increasing. in this paper, we study the problem of exact route matching, which is an important physical design constraint commonly imposed on specific analog signals for the purpose of correct analog functionality. for this, we first propose a mathematical formulation that models the route matching problem exactly. based on this formulation, we derive important theoretical conclusions, and propose dynamic-programming algorithms to solve the problem. we also discuss how to use heuristic search techniques to enable faster computations. our experimental results show the effectiveness of our algorithms.
improved heuristics for finite word-length polynomial datapath optimization. conventional high-level synthesis techniques are not able to manipulate polynomial expressions efficiently due to the lack of suitable optimization techniques for redundancy elimination over z2n. this paper, in comparison with [1], presents 1) an improved partitioning heuristic based on single-variable monomials instead of checking all sub-polynomials, 2) an improved compensation heuristic which is able to compensate monomials as well as coefficients, and 3) a combined area-delay-optimized factorization approach to extract the most frequently used sub-expressions from multi-output polynomials over z2n. experimental results have shown an average saving of 32% and 27.2% in the number of logic gates and critical path delay respectively compared to the state-of-the-art techniques. regarding the comparison with [1], the number of gates and delay are improved by 14.3% and 13.9% respectively. furthermore, the results show that the combined area-delay optimization can reduce the average delay by 26.4%.
adaptive sampling for efficient failure probability analysis of sram cells. in this paper, an adaptive sampling method is proposed for the statistical sram cell analysis. the method is composed of two components. one part is the adaptive sampler that manipulates an alternative sampling distribution iteratively to minimize the estimated yield error. the drifts of the sampling distribution are re-configured in each iteration toward further minimization of the estimation variance by using the data obtained from the previous circuit simulations and applying a high-order householder's method. secondly, an analytical framework is developed and integrated with the adaptive sampler to further boost the efficiency of the method. this is achieved by the optimal initialization of the alternative multi-variate gaussian distribution via setting its drift vector and covariance matrix. the required number of simulation iterations to obtain the yield with a certain accuracy is several orders of magnitude lower than that of the crude-monte carlo method with the same confidence interval.
fast detection of node mergers using logic implications. in this paper, we propose a new node merging algorithm using logic implications. the proposed algorithm only requires two logic implications to find the substitute nodes for a given target node, and thus can efficiently detect node mergers. furthermore, we also apply the node merger identification algorithm for area optimization in vlsi circuits. we conduct experiments on a set of iwls 2005 benchmarks. the experimental results show that our algorithm has a competitive capability on area optimization compared to a global observability don't care (odc)-based node merging algorithm which is highly time-consuming. our speedup is approximately 86 times for overall benchmarks.
timing model extraction for sequential circuits considering process variations. as semiconductor devices continue to scale down, process variations become more relevant for circuit design. facing such variations, statistical static timing analysis is introduced to model variations more accurately so that the pessimism in traditional worst case timing analysis is reduced. because all delays are modeled using correlated random variables, most statistical timing methods are much slower than corner based timing analysis. to speed up statistical timing analysis, we propose a method to extract timing models for flip-flop and latch based sequential circuits respectively. when such a circuit is used as a module in a hierarchical design, the timing model instead of the original circuit is used for timing analysis. the extracted timing models are much smaller than the original circuits. experiments show that using extracted timing models accelerates timing verification by orders of magnitude compared to previous approaches using flat netlists directly. accuracy is maintained, however, with the mean and standard deviation of the clock period both showing usually less than 1% error compared to monte carlo simulation on a number of benchmark circuits.
operating system scheduling for efficient online self-test in robust systems. very thorough online self-test is essential for overcoming major reliability challenges such as early-life failures and transistor aging in advanced technologies. this paper demonstrates the need for operating system (os) support to efficiently orchestrate online self-test in future robust systems. experimental data from an actual dual quad-core system demonstrate that, without software support, online self-test can significantly degrade performance of soft real-time and computation-intensive applications (by up to 190%), and can result in perceptible delays for interactive applications. to mitigate these problems, we develop os scheduling techniques that are aware of online self-test, and schedule/migrate tasks in multi-core systems by taking into account the unavailability of one or more cores undergoing online self-test. these techniques eliminate any performance degradation and perceptible delays in soft real-time and interactive applications (otherwise introduced by online self-test), and significantly reduce the impact of online self-test on the performance of computation-intensive applications. our techniques require minor modifications to existing os schedulers, thereby enabling practical and efficient online self-test in real systems.
a novel post-atpg ir-drop reduction scheme for at-speed scan testing in broadcast-scan-based test compression environment. reducing ir-drop in the test cycle during at-speed scan testing has become mandatory for avoiding test-induced yield loss. an efficient approach for this purpose is post-atpg test modification based on x-identification and x-filling since it causes no circuit/clock design change and no test vector count inflation. however, applying this approach to test compression has been considered challenging due to the limited availability of x-bits. this paper solves this serious problem by proposing a novel and practical ca (compression-aware) test modification scheme for reducing ir-drop in the widely-used broadcast-scan based test compression environment. this unique scheme features (1) ca circuit remodeling for minimizing the effort of applying test modification to broadcast-scan-based test compression, (2) ca x-identification for increasing x-bits for risky test vectors, and (3) ca x-filling for effectively using limited x-bits in reducing ir-drop. as a result, the ca test modification scheme can achieve significant ir-drop reduction even when a test cube only has a small number of x-bits. this advantage is clearly demonstrated by experimental results on three compression configurations created from an industrial circuit.
a scalable decision procedure for fixed-width bit-vectors. efficient decision procedures for bit-vectors are essential for modern verification frameworks. this paper describes a new decision procedure for the core theory of bit-vectors that exploits a reduction to equality reasoning. the procedure is embedded in a congruence closure algorithm, whose data structures are extended in order to efficiently manage the relations between bit-vector slicings, modulo equivalence classes. the resulting procedure is incremental, backtrackable, and proof producing: it can be used as a theory-solver for a lazy smt schema. experiments show that our approach is comparable and often superior to bit-blasting on the core fragment, and that it also helps as a theory layer when applied over the full bit-vector theory.
security against hardware trojan through a novel application of design obfuscation. malicious hardware trojan circuitry inserted in safety-critical applications is a major threat to national security. in this work, we propose a novel application of a key-based obfuscation technique to achieve security against hardware trojans. the obfuscation scheme is based on modifying the state transition function of a given circuit by expanding its reachable state space and enabling it to operate in two distinct modes -- the normal mode and the obfuscated mode. such a modification obfuscates the rareness of the internal circuit nodes, thus making it difficult for an adversary to insert hard-to-detect trojans. it also makes some inserted trojans benign by making them activate only in the obfuscated mode. the combined effect leads to higher trojan detectability and higher level of protection against such attack. simulation results for a set of benchmark circuits show that the scheme is capable of achieving high levels of security at modest design overhead.
interpolating functions from large boolean relations. boolean relations are an important tool in system synthesis and verification to characterize solutions to a set of boolean constraints. for physical realization as hardware, a deterministic function often has to be extracted from a relation. prior methods however are unlikely to handle large problem instances. from the scalability standpoint this paper demonstrates how interpolation can be exploited to extend deter-minization capacity. a comparative study is performed on several proposed computation techniques. experimental results show that boolean relations with thousands of variables can be effectively determinized and the extracted functional implementations are of reasonable quality.
simultaneous layout migration and decomposition for double patterning technology. double patterning technology (dpt) and layout migration are two closely related problems on design for manufacturability in the nanometer era. dpt decomposes a layout into two masks and applies double exposure patterning to increase the pitch size and thus printability. in this paper, we present the first algorithm in the literature for the simultaneous layout migration and decomposition (smd) problem. our algorithm first constructs a conflict graph and dpt-aware constraint graphs, and then applies integer linear programming (ilp) corresponding to the graphs to obtain a decomposed and migrated layout. we further present an effective graph-based reduction technique to prune the ilp solution space, which maintains the same dpt conflicts. we also present a new dpt-aware objective for the smd problem to minimize the difference between the original and migrated layouts while considering the dpt effects. in addition, we present an approach to generate dpt-aware standard cells by considering the dpt effects on the cell boundaries; this technique improves the layout printability and facilitates eda tools to consider dpt. experimental results show that our algorithms can effectively generate conflict-free migrated layouts with 14% smaller layout areas and 28% smaller layout changes, compared with the traditional method of layout decomposition followed by layout migration. in particular, our reduction technique can reduce the runtimes for the test cases from more than one day for the basic ilp formulation to only seconds. can reduce the runtimes for the test cases from more than one day to only seconds.
final-value odes: stable numerical integration and its application to parallel circuit analysis. while solving initial-value odes is the de facto approach to time-domain circuit simulation, the opposite act, solving final-value odes, has been neglected for a long time. stable numerical integration of initial-value odes involves significant complications; the application of standard integration methods simply leads to instability. we show that not only practically meaningful applications of final-value ode problems exist, but also the inherent stability challenges may be addressed by recently proposed numerical methods. furthermore, we demonstrate an elegant bi-directional parallel circuit simulation scheme, where one time-domain simulation task is sped up by simultaneously solving initial and final-value odes, one from each end of the time axis. the proposed approach has unique and favorable properties: the solutions of the two ode problems are completely data independent with built-in automatic load balancing. as a specific application study, we demonstrate the proposed technique under the contexts of parallel digital timing simulation and the shooting-newton based steady-state analysis.
a method for calculating hard qos guarantees for networks-on-chip. many networks-on-chip (noc) applications exhibit one or more critical traffic flows that require hard quality of service (qos). guaranteeing bandwidth and latency for such real time flows is crucial. in this paper, we present novel methods to efficiently calculate worst-case bandwidth and latency bounds and thereby provide hard qos guarantees. importantly, the proposed methods apply even to best-effort noc architectures, with no extra hardware dedicated to qos support. by applying our methods to several realistic noc designs, we show substantial improvements (on average, more than 30% in bandwidth and 50% in latency) in bound tightness with respect to existing approaches.
taming irregular eda applications on gpus. recently general purpose computing on graphic processing units (gpus) is rising as an exciting new trend in high-performance computing. thus it is appealing to study the potential of gpu for electronic design automation (eda) applications. however, eda generally involves irregular data structures such as sparse matrix and graph operations, which pose significant challenges for efficient gpu implementations. in this paper, we propose highperformance gpu implementations for two important irregular eda computing patterns, sparse-matrix vector product (smvp) and graph traversal. on a wide range of eda problem instances, our smvp implementations outperform all published work and achieve a speedup of one order of magnitude over the cpu baseline. upon such a basis, both timing analysis and linear system solution can be considerably accelerated. we also introduce a smvp based formulation for breadth-first search and observe considerable speedup on gpu implementations. our results suggest that the power of gpu computing can be successfully unleashed through designing gpu-friendly algorithms and/or re-organizing computing structures of current algorithms.
pad assignment for die-stacking system-in-package design. wire bonding is the most popular method to connect signals between dies in system-in-package (sip) design nowadays. pad assignment, which assigns inter-die signals to die pads so as to facilitate wire bonding, is an important physical design problem for sip design because the quality of a pad assignment solution affects both the cost and performance of a sip design. in this paper, we study a pad assignment problem, which prohibits the generation of illegal crossings and aims to minimize the total signal wirelength, for die-stacking sip design. we first consider a variety of special cases and present a minimum-cost maximum-flow based approach to optimally solve them in polynomial time. we then describe an approach, which uses a modified left edge algorithm and an integer linear programming technique, to solve the general case. encouraging experimental results are shown to support our approaches.
dynatune: circuit-level optimization for timing speculation considering dynamic path behavior. traditional circuit design focuses on optimizing the static critical paths no matter how infrequently these paths are exercised dynamically. circuit optimization is then tuned to the worst-case conditions to guarantee error-free computation but may also lead to very inefficient designs. recently, there are processor works that over-clock the chip to achieve higher performance to the point where timing errors occur, and then error correction is performed either through circuit-level or microarchitecture-level techniques. this approach in general is referred to as timing speculation. in this paper, we propose a new circuit optimization technique "dynatune" for timing speculation based on the dynamic behavior of a circuit. dynatune optimizes the most dynamically critical gates of a circuit and improves the circuit's throughput under a fixed power budget. we test this proposed technique with two timing speculation schemes - telescopic unit (tu) and razor logic (rz). experimental results show that applying dynatune on the leon3 processor can increase the throughput of critical modules by up to 13% and 20% compared to the timing-speculative and non-timing-speculative results optimized by synopsys design compiler, respectively. for mcnc benchmark circuits, dynatune combined with tu can provide 9% and 20% throughput gains on average compared to timing-speculative and non-timing-speculative results optimized by design compiler. when combined with rz, dynatune can achieve 8% and 15% throughput gains on average for above experiments.
scheduling with soft constraints. in a behavioral synthesis system, a typical approach used to guide the scheduler is to impose hard constraints on the relative timing between operations considering performance, area, power, etc., so that the resulting rtl design is favorable in these aspects. the mechanism is often flawed in practice because many such constraints are actually soft constraints which are not necessary, and the constraint system may become inconsistent when many hard constraints are added for different purposes. this paper describes a scheduler that distinguishes soft constraints from hard constraints when exploring the design space. we propose a special class of soft constraints called integer-difference soft constraints, which lead to a totally unimodular constraint matrix in an integer linear programming formulation. by exploiting the total unimodularity, the problem can be solved optimally and efficiently using a linear programming relaxation without expensive branch and bound procedures. we also show how the proposed method can be used to support a variety of design considerations. as an example application, we apply the method to the problem of low-power synthesis with operation gating. in a set of experiments on real-world designs, our method achieves an average of 33.9% reduction in total power; it outperforms a previous method by 17.1% on average and gives close-to-optimal solutions on several designs.
decoupling capacitance efficient placement for reducing transient power supply noise. decoupling capacitance (decap) is an efficient way to reduce transient noise in on-chip power supply networks. however, excessive decap may cause more leakage power, chip resource waste, and even lead to more design iterations. in this paper, we present a novel decap-efficient placement algorithm for transient power supply noise reduction. in contrast to traditional design flow, our approach considers decap impacts at the placement stage to seek the placement minimizing decap requirements while still satisfying the traditional placement objectives. in the new method, we first devise a fast procedure to assess the decap requirement for the force-based placement framework, in which the required decap is modeled as a density function over the chip. then, we build a corresponding supply and demand system to adjust the placement in favor of minimizing decap. finally, we develop a decap efficient placement algorithm with a new force induced by imbalance between power supply and power demands. experimental results show that the new combined placement and decap optimization flow could reduce the minimum decap area by 35% with a wire length increase of only 0.5% at nearly the same computational cost, which is efficient for practical problems.
minimizing expected energy consumption through optimal integration of dvs and dpm. while dynamic voltage scaling (dvs) and dynamic power management (dpm) techniques are widely used in real-time embedded applications, their complex interaction is not fully understood. in this research effort, we consider the problem of minimizing the expected energy consumption on settings where the workload is known only probabilistically. by adopting a system-level power model, we formally show how the optimal processing frequency can be computed efficiently for a real-time embedded application that can use multiple devices during its execution, while still meeting the timing constraints. our evaluations indicate that the new technique provides clear (up to 35%) energy gains over the existing solutions that are proposed for deterministic workloads. moreover, in a non-negligible part of the parameter spectrum, the algorithm's performance is shown to be close to that of a clairvoyant algorithm that can minimize the energy consumption with the advance knowledge about the exact workload.
layout-driven test-architecture design and optimization for 3d socs under pre-bond test-pin-count constraint. we propose a layout-driven test-architecture design and optimization technique for core-based system-on-chips (socs) that are fabricated using three-dimensional (3d) integration. in contrast to prior work, we consider the pre-bond test-pin-count constraint during optimization since these pins occupy large silicon area that cannot be used in functional mode. in addition, the proposed test-architecture design takes the soc layout into consideration and facilitates the sharing of test wires between pre-bond tests and post-bond test, which significantly reduces the routing cost for a test-access mechanism in 3d technology. experimental results for the itc'02 soc benchmarks circuits demonstrate the effectiveness of the proposed solution.
modeling of layout-dependent stress effect in cmos design. strain technology has been successfully integrated into cmos fabrication to improve carrier transport properties since 90nm node. due to the non-uniform stress distribution in the channel, the enhancement in carrier mobility, velocity, and threshold voltage shift strongly depend on circuit layout, leading to systematic performance variations among transistors. a compact stress model that physically captures this behavior is essential to bridge the process technology with design optimization. in this paper, starting from the first principle, a new layout-dependent stress model is proposed as a function of layout, temperature, and other device parameters. furthermore, a method of layout decomposition is developed to partition the layout into a set of simple patterns for efficient model extraction. these solutions significantly reduce the complexity in stress modeling and simulation. they are comprehensively validated by tcad simulation and published si-data, including the state-of-the-art strain technologies and the sti stress effect. by embedding them into circuit analysis, the interaction between layout and circuit performance is well benchmarked at 45nm node.
ghm: a generalized hamiltonian method for passivity test of impedance/admittance descriptor systems. a generalized hamiltonian method (ghm) is proposed for passivity test of descriptor systems (dss) which describe impedance or admittance input-output responses. ghm can test passivity of dss with any system index without minimal realization. this frequency-independent method can avoid the time-consuming system decomposition as required in many existing ds passivity test approaches. furthermore, ghm can test systems with singular d + dt where traditional hamiltonian method fails, and enjoys a more accurate passivity violation identification compared to frequency sweeping techniques. numerical results have verified the effectiveness of ghm. the proposed method constitutes a versatile tool to speed up passivity check and enforcement of dss and subsequently ensures globally stable simulations of electrical circuits and components.
active-passive co-synthesis of multi-gigahertz radio frequency circuits with broadband parametric macromodels of on-chip passives. synthesis of multi-gigahertz radio frequency circuits brings together difficult challenges related to simulation, extraction and multidimensional space search. the standard approach of mapping all electromagnetic parasitics into parametric rlc models prior to synthesis is extremely restrictive especially when broadband and full-wave models with high accuracy are needed. in the presented approach, a two-stage macromodel that creates broadband, accurate parametric representations of passives, in particular spiral inductors, is developed. the broadband nature is captured through the vector fitting algorithm. the macromodels are implemented via efficient nonlinear, multidimensional regression using relevance vector machine, and are coupled into circuit simulators through admittance parameters. subsequently, optimization on both active and passive parameters are carried out simultaneously, thereby bypassing the ad hoc nature of two stage (actives and passives) approximate optimization. two standard low-noise amplifier topologies are synthesized with tight performance constraints at center frequencies 5, 10 and 12 gigahertz in order to demonstrate the frequency scalability of the methodology.
temporal and spatial idleness exploitation for optimal-grained leakage control. runtime leakage control techniques, such as power gating (pg) and body biasing (bb), have been applied in a coarse-grained manner traditionally. in order to enable more aggressive leakage reduction, researchers are seeking ways to control leakage with finer granularity. our research proposes two novel methods, namely circuit clustering for temporal and spatial idleness exploitation, to systematically reduce the granularity of leakage control and improve leakage reduction. another strength of this paper is the quantitative study of leakage saving and control cost by leakage control with different granularity. with our quantitative study, designers can make the trade-off between leakage saving and control cost, and decide the optimum granularity for leakage control. a heuristic algorithm has been developed to automate the two circuit clustering methods and determine the optimum granularity for any given circuit. the analysis and experiments of this paper is mainly based on rbb. they are also applicable to pg by modifying the cost function.
a hierarchical floating random walk algorithm for fabric-aware 3d capacitance extraction. with the adoption of ultra regular fabric paradigms for controlling design printability at the 22nm node and beyond, there is an emerging need for a layout-driven, pattern-based parasitic extraction of alternative fabric layouts. in this paper, we propose a hierarchical floating random walk (hfrw) algorithm for computing the 3d capacitances of a large number of topologically different layout configurations that are all composed of the same layout motifs. our algorithm is not a standard hierarchical domain decomposition extension of the well established floating random walk technique, but rather a novel algorithm that employs markov transition matrices. specifically, unlike the fast-multipole boundary element method and hierarchical domain decomposition (which use a far-field approximation to gain computational efficiency), our proposed algorithm is exact and does not rely on any tradeoff between accuracy and computational efficiency. instead, it relies on a tradeoff between memory and computational efficiency. since floating random walk type of algorithms have generally minimal memory requirements, such a tradeoff does not result in any practical limitations. the main practical advantage of the proposed algorithm is its ability to handle a set of layout configurations in a complexity that is basically independent of the set size. for instance, in a large 3d layout example, the capacitance calculation of 120 different configurations made of similar motifs is accomplished in the time required to solve independently just 2 configurations, i.e. a 60x speedup.
timing arc based logic analysis for false noise reduction. the problem of calculating accurate impact of crosstalk on a circuit considering its inherent logic and timing properties is very complex. although it has been widely studied, it still lacks an efficient solution. as a result, state-of-the-art crosstalk calculators use simplistic and overly pessimistic models resulting in the over-estimation of crosstalk effects. such pessimism in crosstalk analysis often leads to the triggering of false violations and consequently an inefficient use of design resources. the main contribution of this paper is a novel technique called timing arc based logic analysis (tabla) that serves as an efficient means to calculate realistic crosstalk bounds. tabla uses timing arcs as basic elements to perform an efficient temporal logic analysis employing the min-max timing model using dedicated solvers for logic and timing. additionally, a procedure to generate powerful conflict clauses is proposed to improve the run time of the overall analysis. the proposed technique has been tested in an industrial environment on benchmark circuits as well as on an industrial design, and results are provided.
iterative layering: optimizing arithmetic circuits by structuring the information flow. current logic synthesis techniques are ineffective for arithmetic circuits. they perform poorly for xor-dominated circuits, and those with a high fan-in dependency between inputs and outputs. many optimizers, therefore employ libraries of hand-optimized arithmetic components, but cannot optimize across component boundaries. to remedy this situation, we introduce a new logic synthesis algorithm which analyzes the input circuit based on its behavior on a set of random assignments of input variables, and outputs a structural implementation of the input circuit. the method presented here is similar to the covering algorithm used in multi-level optimizations [4]; however, it is not based on sum-of-product form, or any specific input representation. our experiments show that our approach is not only capable of automatically reproducing some known architectural implementations without any prior knowledge about the functionality of the circuit, but also, in some cases, it is able to discover completely new designs which we have not seen described in literature.
the epsilon-approximation to discrete vt assignment for leakage power minimization. as vlsi technology reaches 45nm technology node, leakage power optimization has become a major design challenge. threshold voltage (vt) assignment has been extensively studied, due to its effectiveness in leakage power reduction. in contrast to the efficiently solvable continuous vt assignment problem, the discrete vt assignment problem is known to be np-hard. all of the existing techniques are heuristics without performance guarantee due to the np-hardness nature of the problem. it is still not known whether there is any rigorous approximation algorithm for the discrete vt assignment problem. in this paper, the first &epsilon;-approximation algorithm is designed for the discrete vt assignment problem. the algorithm can &epsilon;-approximate the optimal vt assignment solution in o([equation]) time, where n is the size of the combinational circuit and m is the number of available threshold voltages per gate. it is based on an advanced potential function technique and an efficient dual decision core query technique. our experiments on iscas'85 benchmark circuits demonstrate that the new algorithm always returns a solution with error bounded by &epsilon; even compared to the lower bound of the optimal solution. on average, it can approximate the optimal solution with 2.8% additional leakage power running in 51.3 seconds, while the integer linear programming technique is computationally prohibitive. our algorithm also significantly outperforms the heuristic in [1] by 16.5% leakage power saving with similar runtime. this clearly demonstrates the practicality of the proposed &epsilon;-approximation algorithm for the vt assignment problem.
the synthesis of combinational logic to generate probabilities. as cmos devices are scaled down into the nanometer regime, concerns about reliability are mounting. instead of viewing nano-scale characteristics as an impediment, technologies such as pcmos exploit them as a source of randomness. the technology generates random numbers that are used in probabilistic algorithms. with the pcmos approach, different voltage levels are used to generate different probability values. if many different probability values are required, this approach becomes prohibitively expensive. in this work, we demonstrate a novel technique for synthesizing logic that generates new probabilities from a given set of probabilities. three different scenarios are considered in terms of whether the given probabilities can be duplicated and whether there is freedom to choose them. in the case that the given probabilities cannot be duplicated and are predetermined, we provide a solution that is fpga-mappable. in the case that the given probabilities cannot be duplicated but can be freely chosen, we provide an optimal choice. in the case that the given probabilities can be duplicated and can be freely chosen, we demonstrate how to generate arbitrary decimal probabilities from small sets -- a single probability or a pair of probabilities -- through combinational logic.
leveraging efficient parallel pattern search for clock mesh optimization. mesh-based clock distribution network has been employed in many high-performance microprocessor designs due to its favorable properties such as low clock skew and robustness. such clock distributions are usually highly complex. while the simulation of clock meshes is already time consuming, tuning such networks under tight performance constraints is a more daunting task. in this paper, we address the challenging task of driver size optimization with a goal of skew minimization. the expensive objective function evaluations and difficulty in getting explicit sensitivity information make this problem intractable to standard optimization methods. we propose to explore the recently developed asynchronous parallel pattern search (apps) method for efficient driver size tuning. while being a search-based method, apps not only provides the desirable derivative-free optimization capability, but is also amenable to parallelization and possesses appealing theoretically rigorous convergence properties. we show how such a method can lead to powerful parallel sizing optimization of large clock meshes with significant runtime and quality advantages over the traditional sequential quadratic programming (sqp) method. we also show how design-specific properties and speeding-up techniques can be exploited to make the optimization even more efficient while maintaining the convergence of apps in a practical sense.
a performance analytical model for network-on-chip with constant service time routers. performance models for network-on-chip (noc) are essential for design, optimization and quality of service (qos) assurance. classical queueing theory has been often used to provide fast analytical models to estimate average performance. this paper presents a new analytical model that focuses on qos assurance. it assumes that the noc has an underlying synchronous behavior with constant service time routers. the comparisons with simulation results show a tangible improvement with regard to the classical m/d/1 models when estimating the worst-case latencies and queue delays. the model can be applied to any network modeled as a queueing system with constant-time routers.
battery allocation for wireless sensor network lifetime maximization under cost constraints. wireless sensor networks hold the potential to open new domains to distributed data acquisition. however, such networks are prone to premature failure because some nodes deplete their batteries more rapidly than others due to workload variations, non-uniform communication, and heterogenous hardware. many-to-one traffic patterns are common in sensor networks, further increasing node power consumption heterogeneity. most previous sensor network lifetime enhancement techniques focused on balancing power distribution, based on the assumption of uniform battery capacity allocation among homogeneous nodes. this paper gives a formulation and solution to the cost-constrained lifetime-aware battery allocation problem for sensor networks with arbitrary topologies and heterogeneous power distributions. an integer nonlinear programming formulation is given. based on an energy-cost battery pack model and optimal node partitioning algorithm, a rapid battery pack selection heuristic is developed and its deviation from optimality is quantified. experimental results indicate that the proposed technique achieves network lifetime improvements ranging from 3--11x compared to uniform battery allocation, with no more than 10 battery pack energy levels. the proposed technique achieves 2--5 orders of magnitude speedup compared to a general-purpose commercial nonlinear program solver, solution quality improves, and little approximation error is observed.
joint design-time and post-silicon optimization for digitally tuned analog circuits. joint design time and post-silicon optimization for analog circuits has been an open problem in literature because of the complex nature of analog circuit modeling and optimization. in this paper we formulate the co-optimization problem for digitally tuned analog circuits to optimize the parametric yield, subject to power and area constraints. a general optimization framework combing the branch-and-bound algorithm and gradient ascent method is proposed. we demonstrate our framework with two examples in high-speed serial link, the transmitter design and the phase-locked-loop (pll) design. simulation results show that compared with the design heuristic from analog designers' perspective, joint design-time and post-silicon optimization can improve the yield by up to 47% for transmitter design and up to 56% for pll design under the same area and power constraints. to the best of the authors' knowledge, this is the first in-depth study on yield-driven analog circuit design technique that optimizes post-silicon tuning together with the design-time optimization.
layout-dependent sti stress analysis and stress-aware rf/analog circuit design optimization. with the continuous shrinking of feature size, various effects due to shallow-trench-isolation (sti) stress are becoming more and more significant. the resulting nonuniform distribution of stress affects the mosfet characteristics and hence changes the circuit behavior. this paper proposes a complete flow to characterize the influence of sti stress on performance of rf/analog circuits based on layout design and process information. an accurate and efficient fem-based stress simulator has been developed to handle the layout dependence. a comprehensive mosfet model is also proposed to capture the effects of sti stress on mobility, threshold voltage, and leakage current. the influence of layout-dependent sti stress on the circuit performance is further studied, and the corresponding optimization strategies to circuit design are discussed. a realistic pll design realized using 90nm cmos technology is used as a test case for the proposed approach.
optimal layer assignment for escape routing of buses. escape routing is a critical problem in pcb design. in ic-cad'07, a layer assignment algorithm was proposed for escape routing of buses. the algorithm is optimal for single layer design in the sense that it determines if a set of buses can all be escaped on one layer. if they cannot, the algorithm is able to select a maximum subset of the buses that can be escaped on one layer. this, in turn, leads to a heuristic for the layer assignment problem with multiple layers, which is to repeatedly assign a maximum subset of the unassigned buses to a new layer. in this work, we present an algorithm that solves the multi-layer layer assignment problem optimally. our algorithm guarantees to produce a layer assignment with minimum number of layers. we applied our algorithm on industrial data and obtained encouraging results.
automatic memory partitioning and scheduling for throughput and power optimization. hardware acceleration is crucial in modern embedded system design to meet the explosive demands on performance and cost. selected computation kernels for acceleration are usually captured by nest loops, which are optimized by state-of-the-art techniques like loop tiling and loop pipelining. however, memory bandwidth bottlenecks prevent designs to reach optimal throughput with respect to available parallelism. in this paper we present an automatic memory partitioning technique which can efficiently improve throughput and reduce energy consumption of pipelined loop kernels for given throughput constraints and platform requirement. our partition scheme consists of two steps, the first step considers cycle accurate scheduling information to meet the hard constraints on memory bandwidth requirements specifically for synchronized hardware designs. experimental results show an average 6x throughput improvement on a set of real world designs with moderate area increase (about 45% on average), given that less resource sharing opportunities exist with higher throughput in optimized designs. the second step further partitions the memory banks for reducing the dynamic power consumption of the final design. in contrast with previous approaches, our technique can statically compute memory access frequencies in polynomial time with little to none profiling. experimental results show about 30% power reduction on the same set of benchmarks.
energy-optimal dynamic thermal management for green computing. existing thermal management systems for microprocessors assume that the thermal resistance of the heat-sink is constant and that the objective of the cooling system is simply to avoid thermal emergencies. but in fact the thermal resistance of the usual forced-convection heat-sink is inversely proportional to the fan speed, and a more rational objective is to minimize the total power consumption of both processor and cooling system. our new method of dynamic thermal management uses both the fan speed and the voltage/frequency of the microprocessor as control variables. experiments show that tracking the energy-optimal steady-state temperature can saves up to 17.6% of the overall energy, when compared with a conventional approach that merely avoids over-heating.
mitigation of intra-array sram variability using adaptive voltage architecture. sram cell design is driven by the need to satisfy static noise margin, write margin and read current margin (rcm) over all cells in the array in an energy-efficient manner. these constraints determine both the minimum cell size and supply voltage. rcm is set by the maximum read access time over the array. the randomness of transistor threshold voltages, and thus read times, makes maximum read time follow extreme order statistics, specifically, the gumbel distribution which is characterized by long tails. thus, the margin specification needs to be met at the high sigma corners in order to reach acceptable yield, resulting in oversizing and increased vdd. in this work, we demonstrate that a reduced-area bitcell design is achievable by reducing the impact of intra-array randomness through a new architecture that employs an adaptive voltage scheme in a partitioned sram array. the key idea is to be able to shift empirical distributions (realizations) of read time in a set of rows that form a single partition to meet the target. because the partition is smaller than the whole array, the tail of the gumbel distribution is significantly reduced. the adaptive voltage tuning policy is driven by the worst partition access time. for the blocks whose delay violates access time constraints, a higher voltage is selected out of the available set to gain yield, otherwise voltage is reduced for power saving. this permits smaller cell area and lower vdd at identical yield. the cost of adaptivity is in generation and routing of a small number (in our experiments, four) voltage levels and the area of one-per-partition set of pmos switches. we demonstrate that through the voltage tuning architecture we propose, it is possible to obtain mean power consumption reduction on average by 21% iso-area. alternatively, bitcell area can be reduced on average by 7% iso-power compared to the existing design strategy.
maximizing performance of thermally constrained multi-core processors by dynamic voltage and frequency control. in this paper a precise formulation of the problem of minimizing the maximum completion time of tasks on a multi-core processor, subject to thermal constraints is presented. the power model used in this work, accounts for the leakage dependence on temperature, while the thermal model is based on the hotspot model. the general problem is shown to be a non-linear optimization problem that includes cyclic constraints between temperature and power. the derived policy of dynamic frequency and voltage control results in a performance improvement of 19.6% over an optimal policy which performs speed-only control.
value assignment of adjustable delay buffers for clock skew minimization in multi-voltage mode designs. in synchronous circuit designs, clock skew is difficult to minimize because a single physical layout of a clock tree must satisfy multiple constraints in a complicated power mode environment where certain modules may operate with different voltages. in this paper, we use adjustable delay buffers (adb) whose delays can be tuned or adjusted to minimize clock skew under different power modes. assuming that the positions of k adbs are already determined, we propose a linear-time optimal algorithm which assigns the values of adbs so that the skew is optimal among all possible adb assignments. we also propose an efficient heuristic to determine good positions for adbs. our results show significant improvement when compared to cases without adbs.
global routing revisited. recent progress in the area of global routing has been remarkable; yet, in many ways, the classical formulation has yet to catch up with the demands imposed by modern physical synthesis flows. in this work, we visit (and revisit) the topic of global routing. we provide a brief review of global routing's history, and touch on recent work that has contributed to the state-of-the-art in the field. while we cover in depth the basic principles behind leading approaches, we also emphasize open challenges and problems that remain unresolved. we argue that not only does the current academic formulation lack key components of the true routing problem - such as scenic control, layer directives, and capabilities for integration with physical synthesis - but also that present methods are likely to fail when extended toward the more generalized formulation. finally, we offer a revised incarnation of the ispd benchmarks to encourage continued progress in the research community.
a variation-aware preferential design approach for memory based reconfigurable computing. static random access memory (sram) arrays designed in sub-90nm technologies are highly vulnerable to process variation induced read/write/access failures. in memory based reconfigurable computing frameworks, which use large high density memory array, such failures lead to incorrect execution of mapped applications. it causes loss in quality of service (qos) for digital signal processing (dsp) applications. we propose a "preferential design" approach at both application mapping and circuit level, which can significantly improve qos and yield under large parameter variations. such a architecture/circuit co-design approach can also tolerate increased failure rate at low operating voltage, thus facilitating low-power operation. simulation results for a common dsp application show 45% improvement in power at iso--qos and 47% in yield for a target peak signal to noise ratio (psnr) at 45nm technology.
a rigorous framework for convergent net weighting schemes in timing-driven placement. we present a rigorous framework that defines a class of net weighting schemes in which unconstrained minimization is successively performed on a weighted objective. we show that, provided certain goals are met in the unconstrained minimization, these net weighting schemes are guaranteed to converge to the optimal solution of the original timing-constrained placement problem. these are the first results that provide conditions under which a net weighting scheme will converge to a timing optimal placement. we then identify several weighting schemes that satisfy the given convergence properties and implement them, with promising results: a modification of the weighting scheme given in [11]results in consistently improved delay over the original, 4% on average, without increase in computation time.
fast trade-off evaluation for digital signal processing systems during wordlength optimization. this paper presents a novel precision analysis approach, which optimizes the fractional wordlengths of signals in digital signal processing systems. quantization-operation-error model is proposed to formulate the quantization error bound propagations through modules. based on that, explicit relationship between output accuracy and hardware cost is built up, and a greedy search algorithm is proposed to find the minimum implementation cost while meeting output error constraint. moreover, the greedy search steps can form a near pareto-optimal front, which can be used for a fast trade-off evaluation between output accuracy and implementation cost, such as area, power and latency. experimental results and comparisons with existing state-of-the-art methods demonstrate the efficiency of proposed approach.
from 2d to 3d nocs: a case study on worst-case communication performance. advanced integration technologies enable the construction of network-on-chip (noc) from two dimensions to three dimensions. studies have shown that 3d nocs can improve average communication performance because of the possibility of using the additional dimension to shorten communication distance. in this paper, we present a detailed case study on worst-case communication performance in regular k-ary-2-mesh networks. through both analysis and simulation, we show that, while 3d networks achieve better average performance, this may not be the case for worst-case performance mainly due to constraints on vertical channels. our analysis is based on network calculus, which allows to calculate theoretical delay bounds for constrained flows traversing network elements.
remis: run-time energy minimization scheme in a reconfigurable processor with dynamic power-gated instruction set. reconfigurable processors provide a means to flexible and energy-aware computing. in this paper, we present a new scheme for runtime energy minimization (remis) as part of a dynamically reconfigurable processor that is exposed to run-time varying constraints like performance and footprint (i.e. amount of reconfigurable fabric). the scheme chooses an energy-minimizing set of so-called special instructions (considering leakage, dynamic, and reconfiguration energy) and then 'power-gates' a temporarily unused subset of the special instruction set. we provide a comprehensive evaluation for different technologies (ranging from 65 nm to 150 nm) and thereby show that our scheme is technology independent, i.e. it is beneficial for various technologies alike. by means of an h.264 video encoder we demonstrate that for certain performance constraints our scheme (applied to our in-house reconfigurable processor) achieves an allover energy saving of up to 40.8% (avg. 24.8%) compared to a performance-maximizing scheme. we also demonstrate that our scheme is equally beneficial to various other state-of-the-art reconfigurable processor architectures like molen [9] where it achieves energy savings of up to 48.7% (avg. 28.93%) at 65 nm. we have employed an h.264 encoder within this paper as an application in order to demonstrate the strengths of our scheme, since the h.264's complexity and run-time unpredictability present a challenging scenario for state-of-the-art architectures.
synthesizing complementary circuits automatically. one of the most difficult jobs in designing communication and multimedia chips, is to design and verify complex complementary circuit pair (e, e-1), in which circuit e transforms information into a format that is suitable for transmission and storage, while e's complementary circuit e-1 recovers this information. in order to ease this job, we propose a novel two-step approach to synthesize complementary circuit e-1 from e fully automatically. first, we assume that the circuit e satisfies parameterized complementary assumption, which means its input can be recovered from its output under some parameter setting. we check this assumption with sat solver and find out proper values of these parameters. second, with parameter values and the sat instance obtained in the first step, we build the complementary circuit e-1 with an efficient satisfying assignments enumeration technique that is specially designed for circuits with lots of xor gates. to illustrate its usefulness and efficiency, we run our algorithm on several complex encoders from industrial projects, including pcie and 10g ethernet, and successfully generate correct complementary circuits for them.
nonvolatile memristor memory: device characteristics and design implications. the search for new nonvolatile universal memories is propelled by the need for pushing power-efficient nanocomputing to the next higher level. as a potential contender for the next-generation memory technology of choice, the recently found "the missing fourth circuit element", memristor, has drawn a great deal of research interests. in this paper, we characterize the fundamental electrical properties of memristor devices by encapsulating them into a set of compact closed-form expressions. our derivations provide valuable design insights and allow a deeper understanding of key design implications of memristor-based memories. in particular, we investigate the design of read and write circuits and analyze data integrity and noise-tolerance issues.
compacting test vector sets via strategic use of implications. as the complexity of integrated circuits has increased, so has the need for improving testing efficiency. unfortunately, the types of defects are also becoming more complex, which in turn makes simple approaches for testing inadequate. using n-detect testing can improve detect coverage; however, this approach can greatly increase the test set size. in this proof-of-concept paper we investigate the use of logic implication checkers, inserted in hardware, as an aid in compacting n-detect test sets. we show that checker hardware with minimal area overhead can reduce test set size by up to 25%. in addition, this implication checker can serve a dual purpose for online error detection.
a methodology for robust, energy efficient design of spin-torque-transfer ram arrays at scaled technologies. in this paper we propose a methodology for energy efficient spin-torque-transfer random access memory (sttram) array design at scaled technology nodes. we present a model to estimate and analyze the energy dissipation of an sttram array. the presented model shows the strong dependence of the array energy on the silicon transistor width, word line voltage and row/column organization. using the array energy model we propose a design methodology for sttram arrays which minimizes the energy dissipation while maintaining the required robustness in read and write operations at scaled technologies.
power-switch routing for coarse-grain mtcmos technologies. multi-threshold cmos (mtcmos) is an effective power-gating technique to reduce ic's leakage power consumption by turning off idle devices with mtcmos switches. however, few existing literatures have discussed the algorithms required in mtcmos's back-end tools. in this paper, we propose a switch-routing framework which serially connects the mtcmos switches without violating the manhattan-distance constraint. the proposed switch-routing framework can simultaneously maximize the number of mtcmos switches covered by its trunk path and minimize the total path length. the experimental result based on four industrial mtcmos designs demonstrates the effectiveness and efficiency of the proposed framework compared to a solution provided by an eda vendor and an advanced tsp solver.
parallel multi-level analytical global placement on graphics processing units. gpu platforms are becoming increasingly attractive for implementing accelerators because they feature a larger number of cores with improved programmability. in this paper, we describe our implementation of a state-of-the-art academic multi-level analytical placer mpl [8] on nvidia's massively parallel gt200 series platforms. we detail our efforts on performance tuning and optimizations. when compared to software implementation on intel's recent generation xeon cpu, the speed of the global placement part of mpl is 15x faster on average using a tesla c1060 card, with comparable wl. (less than 1% wl degradation on average)
on soft error rate analysis of scaled cmos designs - a statistical perspective. this paper re-examines the soft error effect caused by cosmic radiation in sub 90nm technologies. considering the impact of process variation, a number of statistical natures of transient faults are found more sophisticated than their static ones. we apply the state-of-the-art statistical learning algorithm to tackle the complexity of these natures and build compact yet accurate generation and propagation models for transient fault distributions. a statistical analysis framework for soft error rate (ser) is also proposed on the basis of these models. experimental results show that the proposed framework can obtain improved ser estimation compared to the static approaches.
consistency-based characterization for ic trojan detection. a trojan attack maliciously modifies, alters, or embeds unplanned components inside the exploited chips. given the original chip specifications, and process and simulation models, the goal of trojan detection is to identify the malicious components. this paper introduces a new trojan detection method based on nonintrusive external ic quiescent current measurements. we define a new metric called consistency. based on the consistency metric and properties of the objective function, we present a robust estimation method that estimates the gate properties while simultaneously detecting the trojans. experimental evaluations on standard benchmark designs show the validity of the metric, and demonstrate the effectiveness of the new trojan detection.
deltasyn: an efficient logic difference optimizer for eco synthesis. during the ic design process, functional specifications are often modified late in the design cycle, after placement and routing are completed. however, designers are left either to manually process such modifications by hand or to restart the design process from scratch---a very costly option. in order to address this issue, we present deltasyn, a method for generating a highly optimized logic difference between a modified high-level specification and an implemented design. deltasyn has the ability to locate boundaries in implemented logic within which changes can be confined. deltasyn demarcates the boundary in two phases. the first phase employs fast functional and structural analysis techniques to identify equivalent signals forming the input-side boundary of the changes. the second phase locates the outputside boundary of the changes through a novel dynamic algorithm that detects matching logic downstream from the changes required by the eco. experiments on industrial designs show that together these techniques successfully implement ecos while preserving an average of 97% of the existing logic. unlike previous approaches, the use of bitparallel logic simulation and fast sat solvers enables high performance and scalability. deltasyn can process and verify a typical eco for a design of around 10k gates in about 200 seconds or less.
an elegant hardware-corroborated statistical repair and test methodology for conquering aging effects. we propose a new and efficient statistical-simulation-based test methodology for optimally selecting repair elements at beginning-of-life (bol) to improve the end-of-life (eol) functionality of memory designs. this is achieved by identifying the best bol test/repair corner that maximizes eol yield, thereby exploiting redundancy to optimize eol operability with minimal bol yield loss. the statistical approach makes it possible to identify such corners with tremendous savings in terms of test time and hardware. to estimate yields and search for the best repair corner the approach relies on fast conditional importance sampling statistical simulations. the methodology is versatile and can handle complex aging effects with asymmetrical distributions. results are demonstrated on state-of-the-art dual-supply memory designs subject to statistical negative bias temperature instability (nbti) effects, and hardware results are shown to match predicted model trends.
fast and reliable passivity assessment and enforcement with extended hamiltonian pencil. passivity is an important property for a macro-model generated from measured or simulated data. existence of purely imaginary eigenvalues of a hamiltonian matrix provides useful information in assessing and correcting the passivity of a system. since direct computation of eigenvalues is very expensive for large-scale systems, several authors have proposed to solve iteratively for a subset of the eigenvalues based on heuristic sampling along the imaginary axis. however, completeness is not guaranteed in such methods and thus potential risk of missing important eigenvalues is difficult to avoid. in this paper we are aiming at finding all eigenvalues efficiently to avoid both the high cost and the potential risk of missing important eigenvalues. the idea of the proposed method is to convert the hamiltonian matrix to an equivalent sparse form, termed the "extended hamiltonian pencil", and solve for its eigenvalues efficiently using a special eigensolver. experiments on several realistic systems demonstrate an 80x speed-up compared with standard direct eigensolvers.
timing yield-aware color reassignment and detailed placement perturbation for double patterning lithography. double patterning lithography (dpl) is a likely resolution enhancement technique for ic production in 32nm and below technology nodes. however, dpl gives rise to two independent, uncorrelated distributions of linewidth on a chip, resulting in a 'bimodal' linewidth distribution and an increase in performance variation. [13] suggested that new physical design mechanisms could reduce harmful covariance terms that contribute to this performance variation. in this paper, we propose new bimodal-aware timing analysis and optimization methods to improve timing yield of standard-cell based designs that are manufactured using dpl. our first contribution is a dpl-aware approach to timing modeling, based on detailed analysis of cell layouts. our second contribution is an ilp-based maximization of 'alternate' mask coloring of instances in timing-critical paths, to minimize harmful covariance and performance variation. third, we propose a dynamic programming-based detailed placement algorithm that solves mask coloring conflicts and can be used to ensure "double patterning correctness" after placement or even after detailed routing, while minimizing the displacement of timing-critical cells with manageable eco impact. with a 45nm library and open-source design testcases, our timing-aware recoloring and placement optimizations together achieve up to 232ps (resp. 36.22ns) reduction in worst (resp. total) negative slack, and 78% (resp. 65%) reduction in worst (resp. total) negative slack variation.
post-fabrication measurement-driven oxide breakdown reliability prediction and management. oxide breakdown has become an increasingly pressing reliability issue in modern vlsi design with ultra-thin oxides. the conventional guard-band methodology assumes uniformly thin oxide thickness and results in overly pessimistic reliability estimation that severely degrades the system performance. in this study we present the use of limited post-fabrication measurements of oxide thicknesses from on-chip sensors to aid in the chip-level oxide breakdown reliability prediction and quantify the trade-off between reliability margin and system performance. given the post-fabrication measurements, chip oxide breakdown reliability can be formulated as a conditional distribution that allows us to achieve a significantly more accurate chip lifetime estimation. the estimation is then used to individually tune the supply voltage of each chip for performance maximization while maintaining or improving the reliability. experimental results show that the proposed method can achieve performance improvement of 19% on average and 27% at maximum for a design with up to 50 million devices, using merely 25 measurements per chip, while analysis time is only 0.4 second.
bist design optimization for large-scale embedded memory cores. built-in self test (bist) is a crucial technique for testing embedded memory cores in a system-on-chip (soc). however, there is not much published work on bist design optimization for multiple memory cores in the soc designs. in this paper, we present a method for the bist design optimization problem for large-scale soc embedded memory cores, considering various real-world constraints such as peak current, ir drop, etc. our method is based on a three-stage technique: (1) assignment, (2) legalization, and (3) refinement. the first stage adopts an integer linear programming (ilp) formulation for each memory partition to find a desired assignment of memory cores to controllers. the second stage then legalizes the assignment to meet user-specified assignment constraints. the last stage refines the solution to further reduce its cost. experimental results show that our method can reduce the test time by 26.6%, the routing length by 8.9%, and the area by 24.1%, compared with a heuristic method currently used in industry.
quantifying robustness metrics in parameterized static timing analysis. process and environmental variations continue to present significant challenges to designers of high-performance integrated circuits. in the past few years, while much research has been aimed at handling parameter variations as part of timing analysis, few proposals have actually included ways to interpret the results of this parameterized static timing analysis (psta) step. in this paper, we propose a new post-variational analysis metric that can be used to quantify the (timing) robustness of designs to parameter variations. in addition to helping designers diagnose if and when different nodes can fail, this metric can guide optimization and can give insights on what to fix, by identifying nodes with small robustness values and proceeding to fix those nodes first. inspired by the rich literature on design centering, tolerancing, and tuning (dctt), we use distance as a measure for robustness. our analysis thus determines the minimum distance from the nominal point in the parameter space to any timing violation, and works under the assumption that parameters are specified as ranges rather than statistical distributions. we demonstrate the usefulness of this distance-based robustness metric on circuit blocks extracted from a commercial 45nm microprocessor.
crop: fast and effective congestion refinement of placement. modern circuits become harder to route with the ever decreasing design features. previous routability-driven placement techniques are usually tightly coupled with the underlying placers. so usually they cannot be easily integrated into various placement tools. in this paper, we propose a tool called crop (congestion refinement of placement) for mixed-size placement solutions. crop is independent of any placer. it takes a legalized placement solution and then relocates the modules to improve routability without significantly disturbing the original placement solution. crop interleaves a congestion-driven module shifting technique and a congestion-driven detailed placement technique. basically the shifting technique targets at better allocating the routing resources. shifting in each direction can be formulated as a linear program (lp) for resizing each g-cell. instead of solving the computationally expensive lp, we discover that the lp formulation could be relaxed and solved by a very efficient longest-path computation. then the congestion-driven detailed placement technique is proposed to better distribute the routing demands. congestion reduction is realized by weighting the hpwl with congestion coefficient during detailed placement. the experimental results show that crop is capable of effectively alleviating the congestion for unroutable placement solutions. we apply it to placement solutions generated by four different placers on the ispd05/06 placement benchmarks [1][2]. within a very short runtime, crop greatly improves the routability and saves execution time for the routing stage after refinement.
a circuit-software co-design approach for improving edp in reconfigurable frameworks. use of two-dimensional memory array for lookup table (lut) based reconfigurable computing frameworks has been proposed earlier for improvement in performance and energy-delay product (edp). in this paper, we propose an integrated solution for achieving significantly higher edp in these frameworks by leveraging on the read-dominant memory access pattern. first, we propose to employ an asymmetric memory cell design, which provides higher read performance (~2x) and lower read power (~1.6x) in order to improve the overall edp during operation. exploiting the fact that the proposed memory cell provides better read power/performance for cells storing logic '0', next we propose a content-aware application mapping approach, which tries to maximize the logic '0' content in the luts. we show that the joint circuit and application mapping level optimization approach provides significant improvement in system edp for a set of benchmark circuits.
pcramsim: system-level performance, energy, and area modeling for phase-change ram. phase-change random access memory (pcram) is an emerging memory technology with attractive features, such as fast read access, high density, and non-volatility. because of these attractive properties, pcram is regarded as a promising candidate for future universal memories, and system-level designers could open up new design opportunities by leveraging this new memory technology. however, the majority of the pcram research has been at the device level, and system-level design space exploration using pcram is still in its infancy due to the lack of high-level modeling tools for pcram-based caches and memories. in this paper, we present a pcram model, called pcramsim, to bridge the gap between the device-level and system-level research on pcram technology. the model is validated against industrial pcram prototypes. this new pcramsim tool is expected to help boost pcram-related studies such as next-generation memory subsystems.
moles: malicious off-chip leakage enabled by side-channels. economic incentives have driven the semiconductor industry to separate design from fabrication in recent years. this trend leads to potential vulnerabilities from untrusted circuit foundries to covertly implant malicious hardware trojans into a genuine design. hardware trojans provide back doors for on-chip manipulation, or leak secret information off-chip once the compromised ic is deployed in the field. this paper explores the design space of hardware trojans and proposes a novel technique, "malicious off-chip leakage enabled by side-channels" (moles), which employs power side-channels to convey secret information off-chip. an experimental moles circuit is designed with fewer than 50 gates and is embedded into an advanced encryption standard (aes) cryptographic circuit in a predictive 45nm cmos technology model. engineered by a spread-spectrum technique, the moles technique is capable of leaking multi-bit information below the noise power level of the host ic to evade evaluators' detections. in addition, a generalized methodology for a class of moles circuits and design verification by statistical correlation analysis are presented. the goal of this work is to demonstrate the potential threats of moles on embedded system security. nevertheless, moles could be constructively used for hardware authentication, fingerprinting and ip protection.
variability analysis of finfet-based devices and circuits considering electrical confinement and width quantization. finfet is considered as the most likely candidate to substitute bulk cmos technology. finfet-based design, however, requires special attention due to its exclusive properties such as width quantization and electrical confinement (quantum-mechanical effect) even in subthreshold regime. considering these exclusive properties of finfets, the sources of process variations and their effects on finfet-based circuit characteristics can be significantly different from that in bulk cmos devices. this paper identifies a new source of random process variation due to the gate work-function variation and resulting electrical confinement in emerging high-k/metal-gate finfet devices. in order to capture the effect of the variations on the characteristics of multifin finfets (considering their width quantization property), this paper also presents a new statistical framework to accurately predict the effective threshold voltage of multifin finfet devices. this framework is subsequently used to predict the leakage profile of finfet-based sram cells. since finfets are optimal for ultra-low-voltage operations due to near-ideal subthreshold swing (60 mv/dec), we focus on finfet-based sram (including subthreshold sram) design. contrary to the low sensitivity of the static noise margin (snm) to the width of the pull-down devices in bulk-cmos subthreshold srams, our analysis shows, for the first time, the significant impact of employing multifin pull-down devices on the snm of subthreshold finfet srams.
virtual probe: a statistically optimal framework for minimum-cost silicon characterization of nanoscale integrated circuits. in this paper, we propose a new technique, referred to as virtual probe (vp), to efficiently measure, characterize and monitor both inter-die and spatially-correlated intra-die variations in nanoscale manufacturing process. vp exploits recent breakthroughs in compressed sensing [15]--[17] to accurately predict spatial variations from an exceptionally small set of measurement data, thereby reducing the cost of silicon characterization. by exploring the underlying sparse structure in (spatial) frequency domain, vp achieves substantially lower sampling frequency than the well-known (spatial) nyquist rate. in addition, vp is formulated as a linear programming problem and, therefore, can be solved both robustly and efficiently. our industrial measurement data demonstrate that by testing the delay of just 50 chips on a wafer, vp accurately predicts the delay of the other 219 chips on the same wafer. in this example, vp reduces the estimation error by up to 10x compared to other traditional methods.
pre-atpg path selection for near optimal post-atpg process space coverage. path delay testing is becoming increasingly important for high-performance chip testing in the presence of process variation. to guarantee full process space coverage, the ensemble of critical paths of all chips irrespective of their manufacturing process conditions needs to be tested, as different chips may have different critical paths. existing coverage-based path selection techniques, however, suffer from the loss of coverage after atpg (automatic test pattern generation), i.e., although the pre-atpg path selection achieves good coverage, after atpg, the coverage can be severely reduced as many paths turn out to be unsensitizable. this paper presents a novel path selection algorithm that, without running atpg, selects a set of n paths to achieve near optimal post-atpg coverage. details of the algorithm and its optimality conditions are discussed. experimental results show that, compared to the state-of-the-art, the proposed algorithm achieves not only superior post-atpg coverage, but also significant runtime speedup.
multi-functional interconnect co-optimization for fast and reliable 3d stacked ics. heat removal and power delivery have become two major reliability concerns in 3d stacked ic technology. for thermal problem, two possible solutions exist: thermal-through-silicon-vias (t-tsvs) and micro-fluidic channel (mfc) based liquid cooling. in case of power delivery, a highly complex power distribution network is required to deliver currents reliably to all parts of the 3d stacked ic while suppressing the power supply noise to an acceptable level. however, these thermal and power networks pose major challenges in signal routability and congestion. this is because the signal, power, and thermal interconnects are all competing for routing space. in this paper, we present a co-optimization methodology for the signal, power, and thermal interconnects for 3d stacked ics based on design of experiments (doe) and response surface method (rsm). the goal is to improve performance, thermal, noise, and congestion metrics with our holistic approach. we also provide in-depth comparison between t-tsv and mfc based cooling method and discuss how to employ doe and rsm to best co-optimize the multi-functional interconnects simultaneously.
task management in mpsocs: an asip approach. scheduling, mapping and synchronization have an essential impact on the performance of multi-processor system-on-chips (mpsocs), especially in heterogeneous systems with many cores and small tasks. this paper presents a technique to efficiently accelerate these operations. key contribution is an application-specific instruction-set processor (asip) called osip which is especially tailored to achieve this. in contrast to pure hw solutions, osip is programmable and hence features higher flexibility and better scalability. osip comes with a compiler and a firmware that ease its usability, and an abstract formal model that allows analytical evaluation and integration into fast system level simulators. together with osip, a thin software layer is proposed that leverages high level multi-task programming by abstracting osip's low level details away. in an extensive case study based on a synthetic benchmark and a benchmark from the multimedia domain (h.264), osip highlights its potential when compared against a standard risc and an arm926-ejs processor.
a hybrid local-global approach for multi-core thermal management. multi-core processors have become an integral part of mainstream high performance computer systems. in parallel, exponentially increasing power density and packaging costs have necessitated system level thermal management solutions for multi-core systems. dynamic thermal management (dtm) techniques monitor on-chip temperature continuously and typically employs dynamic voltage and frequency scaling (dvfs) to lower the temperature when it exceeds a pre-defined threshold. state-of-the-art dtm solutions for multi-core systems include distributed dvfs (where each core can scale the voltage/frequency individually) and global dvfs (where all cores scale voltage/frequency simultaneously). distributed dvfs generally offers higher performance than global dvfs, but it is hard to implement and has major scalability issues. we propose a hybrid local-global thermal management approach for multi-core systems that offers better performance than distributed dvfs, while maintaining the simplicity of global dvfs. we employ global dvfs across all the cores but locally tune the performance of each core individually through architectural adaptations. we exploit easily reconfigurable micro-architecture parameters such as instruction window size, issue width, and fetch throttling in per-core thermal management. our hybrid solution is easy to implement and highly effective towards temperature management. the key challenge is appropriate choice of configurations at runtime to provide optimal performance under thermal constraints. we formulate it as a configuration search problem and design an efficient software-based solution that selects the appropriate configuration. our hybrid method, though simpler to implement, achieves 5% better throughput compared to distributed dvfs.
a hierarchy of subgraphs underlying a timing graph and its use in capturing topological correlation in ssta. this paper shows that a timing graph has a hierarchy of specially defined subgraphs, based on which we present a technique that captures topological correlation in arbitrary block-based statistical static timing analysis (ssta). we interpret a timing graph as an algebraic expression made up of addition and maximum operators. we define the division operation on the expression and propose algorithms that modify factors in the expression without expansion. as a result, they produce an expression to derive the latest arrival time with better accuracy in ssta. existing techniques handling reconvergent fanouts usually use dependency lists, requiring quadratic space complexity. instead, the proposed technique has linear space complexity by using a new directed acyclic graph search algorithm. our results show that it outperforms an existing technique in speed and memory usage with comparable accuracy.
power7 - verification challenge of a multi-core processor. over the years functional hardware verification has made significant progress in the areas of traditional simulation techniques, hardware accelerator usage and last but not least formal verification approaches. this has been sufficient to deal with the additional design content and complexity increase that has been happening at the same time. for power7, ibm's first high end 8-core microprocessor, these incremental improvements in verification have been deemed not to be enough by themselves, because the chip was not just a remap of an existing design with more cores. the infrastructure on the chip had to be changed significantly, while at the same time the business side requested a shorter development cycle with perfect quality but without growing the team. looking at these constraints a two phase approach seemed to be the only solution. this paper commences with the highlights of the first phase, where improvements to the existing process have been identified. this includes topics ranging from enhanced test case generation, over advancements in structural checking to the extensions of the formal verification scope both in property checking and sequential equivalence checking. at the same time, the paper describes the second phase which has targeted the exploitation of synergy across the various verification activities. the active interlock between simulation, formal verification and the design has helped to reduce workload and improved the project schedule. and the usage of coverage in holistic way from unit level simulation to acceleration has led to new innovations and new insight, which improved the overall verification process. finally, an outlook on future challenges and future trends is given.
obstacle-avoiding rectilinear steiner tree construction based on steiner point selection. for the obstacle-avoiding rectilinear steiner minimal tree (oarsmt) problem, this paper presents a steiner-point based algorithm to achieve the best practical performance in wirelength and run time. unlike many previous works, the steiner-based framework is more focused on the usage of steiner points instead of the handling of obstacles. this paper also proposes a new concept of steiner point locations to provide an effective as well as efficient way to generate desirable steiner point candidates. experimental results show that this algorithm achieves the best solution quality in &theta; (n log n) empirical time, which was originally generated by applying the maze routing on an &omega;(n2)-space graph. the steiner-point based framework and the new concept of steiner point locations can be applied to future research on the oarsmt problem and its generations, such as the multi-layer oarsmt problem.
crisp: congestion reduction by iterated spreading during placement. dramatic progress has been made in algorithms for placement and routing over the last 5 years, with improvements in both speed and quality. combining placement and routing into a joint optimization has also been proposed. however, it remains unclear if the benefits would be significant enough to justify major changes in commercial tools. crisp addresses this challenge and is the first tool to demonstrate tangible benefits of combined place-and-route optimization including fewer global routing detours, reduced detailed routing violations and runtime, and even shrinking the floorplan of a commercial design. we employ fast global routing to choose standard cells to temporarily inflate and iteratively spread for congestion reduction. spreading only in congested regions, we enable die area reduction by facilitating routing with high area utilization.
resilient circuits - enabling energy-efficient performance and reliability. voltage and frequency margins necessary to ensure correct processor operation under dynamic voltage, temperature, and aging variations result in performance and power overheads. resilient circuit techniques, including embedded error-detection sequentials and tunable replica circuits, allow these margins to be reduced or eliminated, resulting in reliable, energy-efficient operation.
a study of routability estimation and clustering in placement. this paper studies the effects of clustering as a pre-processing step and routability estimation in the placement flow. the study shows that when clustering and routability estimation are considered, the placer effectively improves the routed wirelength for the circuits of ibm-place 2.0 standard-cell benchmark suite [1] and results in the best average routed wirelength when compared against state-of-the-art academic placers.
fast 3-d thermal analysis of complex interconnect structures using electrical modeling and simulation methodologies. accurate and fast estimation of vlsi interconnect thermal profiles has become critically important to estimate their impact on circuit/system performance and reliability, which is necessary for reducing product development time and achieving first-pass silicon success. present commercial thermal analysis tools are incapable of simulating complex structures, particularly in the 3-d domain and are also difficult to integrate with existing design tools. existing analytical thermal models are not perfect either: they are either not accurate enough or oversimplified. this paper uses a methodology, which exploits existing electrical resistance solvers for thermal simulation, to allow fast acquisition of thermal profiles of complex interconnect structures with good accuracy and reasonable computation cost. moreover, for the first time, an accurate closed-form thermal model is developed. the model allows for an equivalent medium with effective thermal conductivity (isotropic or anisotropic) to replace the detailed material information in non-critical regions so that complex interconnect structures can be simulated. using these techniques, this paper demonstrates the simulation of a very complex interconnect structure (~9000 objects or 15 million meshed unknowns after first order isotropic equivalent medium replacement), which is a first time achievement in the area of interconnect thermal analysis. on the other hand, it is shown that an anisotropic equivalent medium is a much better approximation of real interconnect structures from the point of view of accuracy and computation.
constraint solving techniques for software testing and analysis. software testing and analysis are very important research topics in software engineering. we are interested in improving the accuracy of analysis, as well as automation of test generation. in particular, we have been working on the automatic generation of small orthogonal arrays which can be used for combinatorial testing, and the computation of path execution frequency for a program path. the basic idea is to reduce the original problems to constraint satisfaction problems and develop effective constraint solving techniques for solving the problems.
using symbolic evaluation to understand behavior in configurable software systems. many modern software systems are designed to be highly configurable, which increases flexibility but can make programs hard to test, analyze, and understand. we present an initial empirical study of how configuration options affect program behavior. we conjecture that, at certain levels of abstraction, configuration spaces are far smaller than the worst case, in which every configuration is distinct. we evaluated our conjecture by studying three configurable software systems: vsftpd, ngircd, and grep. we used symbolic evaluation to discover how the settings of run-time configuration options affect line, basic block, edge, and condition coverage for our subjects under a given test suite. our results strongly suggest that for these subject programs, test suites, and configuration options, when abstracted in terms of the four coverage criteria above, configuration spaces are in fact much smaller than combinatorics would suggest and are effectively the composition of many small, self-contained groupings of options.
from behaviour preservation to behaviour modification: constraint-based mutant generation. the efficacy of mutation analysis depends heavily on its capability to mutate programs in such a way that they remain executable and exhibit deviating behaviour. whereas the former requires knowledge about the syntax and static semantics of the programming language, the latter requires some least understanding of its dynamic semantics, i.e., how expressions are evaluated. we present an approach that is knowledgeable enough to generate only mutants that are both syntactically and semantically correct and likely exhibit non-equivalent behaviour. our approach builds on our own prior work on constraint-based refactoring tools, and works by negating behaviour-preserving constraints. as a proof of concept we present an enhanced implementation of the access modifier change operator for java programs whose naive implementations create huge numbers of mutants that do not compile or leave behaviour unaltered. while we cannot guarantee that our generated mutants are non-equivalent, we can demonstrate a considerable reduction in the number of vain mutant generations, leading to substantial temporal savings.
advanced hands-on training for distributed and outsourced software engineering. today's software projects are often distributed across multiple locations. this distribution poses new challenges produced by the cooperation across different countries, times zones, and cultures. software engineering courses have to prepare students accordingly. this paper reports an experience on teaching a distributed software engineering course. in this course, students develop software in collaboration with five universities located in italy, hungary, russia, switzerland, and ukraine. the projects allow students to face the difficulties of developing software in a globalized context, and provide a practical experience on distributed software engineering. we describe the major obstacles on organizing such a course, and we suggest best practices to achieve successful outcome.
linking e-mails and source code artifacts. e-mails concerning the development issues of a system constitute an important source of information about high-level design decisions, low-level implementation concerns, and the social structure of developers. establishing links between e-mails and the software artifacts they discuss is a non-trivial problem, due to the inherently informal nature of human communication. different approaches can be brought into play to tackle this trace-ability issue, but the question of how they can be evaluated remains unaddressed, as there is no recognized benchmark against which they can be compared. in this article we present such a benchmark, which we created through the manual inspection of a statistically significant number of e-mails pertaining to six unrelated software systems. we then use our benchmark to measure the effectiveness of a number of approaches, ranging from lightweight approaches based on regular expressions to full-fledged information retrieval approaches.
a discriminative model approach for accurate duplicate bug report retrieval. bug repositories are usually maintained in software projects. testers or users submit bug reports to identify various issues with systems. sometimes two or more bug reports correspond to the same defect. to address the problem with duplicate bug reports, a person called a triager needs to manually label these bug reports as duplicates, and link them to their "master" reports for subsequent maintenance work. however, in practice there are considerable duplicate bug reports sent daily; requesting triagers to manually label these bugs could be highly time consuming. to address this issue, recently, several techniques have be proposed using various similarity based metrics to detect candidate duplicate bug reports for manual verification. automating triaging has been proved challenging as two reports of the same bug could be written in various ways. there is still much room for improvement in terms of accuracy of duplicate detection process. in this paper, we leverage recent advances on using discriminative models for information retrieval to detect duplicate bug reports more accurately. we have validated our approach on three large software bug repositories from firefox, eclipse, and openoffice. we show that our technique could result in 17--31%, 22--26%, and 35--43% relative improvement over state-of-the-art techniques in openoffice, firefox, and eclipse datasets respectively using commonly available natural language information only.
codebook: discovering and exploiting relationships in software repositories. large-scale software engineering requires communication and collaboration to successfully build and ship products. we conducted a survey with microsoft engineers on inter-team coordination and found that the most impactful problems concerned finding and keeping track of other engineers. since engineers are connected by their shared work, a tool that discovers connections in their work-related repositories can help. here we describe the codebook framework for mining software repositories. it is flexible enough to address all of the problems identified by our survey with a single data structure (graph of people and artifacts) and a single algorithm (regular language reachability). codebook handles a larger variety of problems than prior work, analyzes more kinds of work artifacts, and can be customized by and for end-users. to evaluate our framework's flexibility, we built two applications, hoozizat and deep intellisense. we evaluated these applications with engineers to show effectiveness in addressing multiple inter-team coordination problems.
dynamic service quality and resource negotiation for high-availability service-oriented systems. the principle goal of our research project is to improve the availability of service-oriented systems. this is especially important in systems that cross organizational boundaries. in this paper we outline the main research questions, our approach, which is based on appropriate redundancy strategies, and the progress achieved to date.
precise calling context encoding. calling contexts are very important for a wide range of applications such as profiling, debugging, and event logging. most applications perform expensive stack walking to recover contexts. the resulting contexts are often explicitly represented as a sequence of call sites and hence bulky. we propose a technique to encode the current calling context of any point during an execution. in particular, an acyclic call path is encoded into one number through only integer additions. recursive call paths are divided into acyclic subsequences and encoded independently. we leverage stack depth in a safe way to optimize encoding: if a calling context can be safely and uniquely identified by its stack depth, we do not perform encoding. we propose an algorithm to seamlessly fuse encoding and stack depth based identification. the algorithm is safe because different contexts are guaranteed to have different ids. it also ensures contexts can be faithfully decoded. our experiments show that our technique incurs negligible overhead (1.89% on average). for most medium-sized programs, it can encode all contexts with just one number. for large programs, we are able to encode most calling contexts to a few numbers.
towards end-user enabled web service consumption for mashups. services oriented architecture (soa) and web 2.0 are two complementary trends towards a programmable web. in this respect, the ws-* stack became pervasive for enterprise application integration and mashups attracted interest as novel web 2.0 applications combining heterogeneous web sources. while most mashup tools focus on the integration of lightweight web services (i.e. rss/atom, rest), evolving enterprise mashups particularly need to integrate ws-* for enterprise-class data and logic. hence, it requires experienced developers to prepare rather complex ws-* (e.g. as widgets) to enable casual developers and business users to create mashups. therefore, we postulate the hypothesis that this requires an a-priori simplification and cognitive support. in this abstract, we propose a research agenda on how to address such a simplification approach for enterprise services to ultimately empower business users to create real enterprise-class mashups.
characterizing and predicting which bugs get fixed: an empirical study of microsoft windows. we performed an empirical study to characterize factors that affect which bugs get fixed in windows vista and windows 7, focusing on factors related to bug report edits and relationships between people involved in handling the bug. we found that bugs reported by people with better reputations were more likely to get fixed, as were bugs handled by people on the same team and working in geographical proximity. we reinforce these quantitative results with survey feedback from 358 microsoft employees who were involved in windows bugs. survey respondents also mentioned additional qualitative influences on bug fixing, such as the importance of seniority and interpersonal skills of the bug reporter. informed by these findings, we built a statistical model to predict the probability that a new bug will be fixed (the first known one, to the best of our knowledge). we trained it on windows vista bugs and got a precision of 68% and recall of 64% when predicting windows 7 bug fixes. engineers could use such a model to prioritize bugs during triage, to estimate developer workloads, and to decide which bugs should be closed or migrated to future product versions.
an exploratory study of the evolution of software licensing. free and open source software systems (foss) are distributed and made available to users under different software licenses, mentioned in foss code by means of licensing statements. various factors, such as changes in the legal landscape, commercial code licensed as foss, or code reused from other foss systems, lead to evolution of licensing, which may affect the way a system or part thereof can be subsequently used. therefore, it is crucial to monitor licensing evolution. however, manually tracking the licensing evolution of thousands of files is a daunting task. after presenting several cases of the effects of licensing evolution, we propose an approach to automatically track changes occurring in the licensing terms of a system. then, we report an empirical study of the licensing evolution of six different foss systems. results show that licensing underwent frequent and substantial changes.
using information fragments to answer the questions developers ask. each day, a software developer needs to answer a variety of questions that require the integration of different kinds of project information. currently, answering these questions, such as "what have my co-workers been doing?", is tedious, and sometimes impossible, because the only support available requires the developer to manually link and traverse the information step-by-step. through interviews with eleven professional developers, we identified 78 questions developers want to ask, but for which support is lacking. we introduce an information fragment model (and prototype tool) that automates the composition of different kinds of information and that allows developers to easily choose how to display the composed information. in a study, 18 professional developers used the prototype tool to answer eight of the 78 questions. all developers were able to easily use the prototype to successfully answer 94% of questions in a mean time of 2.3 minutes per question.
south africa and the world beyond 2010: the latest scenarios. the talk will address the following issues: &bull; what does it take to be a futurist in today's fast-changing world particularly in it? &bull; is the world economy in a u-shaped recession which could last another 5 years or has the recovery begun. what are the flags to suggest which scenario is in play? &bull; what is the profile of a winning nation and does south africa fit the bill? &bull; are you a fox or a hedgehog? the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
a large-scale empirical study of practitioners' use of object-oriented concepts. we present the first results from a survey carried out over the second quarter of 2009 examining how theories in object-oriented design are understood and used by software developers. we collected 3785 responses from software developers world-wide, which we believe is the largest survey of its kind. we targeted the use of encapsulation, class size as measured by number of methods, and depth of a class in the inheritance hierarchy. we found that, while overall practitioners followed advice on encapsulation, there was some variation of adherence to it. for class size and depth there was substantially less agreement with expert advice. in addition, inconsistencies were found within the use and perception of object-oriented concepts within the investigated group of developers. the results of this survey has deep reaching consequences for both practitioners and researchers as they highlight and confirm central issues.
an empirical study of the effects of conscientiousness in pair programming using the five-factor personality model. this paper describes a formal experiment carried out to investigate the effect of the personality factor conscientiousness on the effectiveness of pair programming as a pedagogical tool in higher education. this experiment took place at the university of auckland, using as subjects undergraduate students attending an introductory programming course. conscientiousness was chosen because it has been shown to be the most consistent predictor of academic achievement. our findings showed that differences in conscientiousness level did not significantly affect the academic performance of students who pair programmed, which could have been due to the short duration of the tasks used throughout the experiment. however, results revealed that another personality factor - openness to experience - presented a significant correlation with paired students' academic performance.
has the bug really been fixed? software has bugs, and fixing those bugs pervades the software engineering process. it is folklore that bug fixes are often buggy themselves, resulting in bad fixes, either failing to fix a bug or creating new bugs. to confirm this folklore, we explored bug databases of the ant, aspectj, and rhino projects, and found that bad fixes comprise as much as 9% of all bugs. thus, detecting and correcting bad fixes is important for improving the quality and reliability of software. however, no prior work has systematically considered this bad fix problem, which this paper introduces and formalizes. in particular, the paper formalizes two criteria to determine whether a fix resolves a bug: coverage and disruption. the coverage of a fix measures the extent to which the fix correctly handles all inputs that may trigger a bug, while disruption measures the deviations from the program's intended behavior after the application of a fix. this paper also introduces a novel notion of distance-bounded weakest precondition as the basis for the developed practical techniques to compute the coverage and disruption of a fix. to validate our approach, we implemented fixation, a prototype that automatically detects bad fixes for java programs. when it detects a bad fix, fixation returns an input that still triggers the bug or reports a newly introduced bug. programmers can then use that bug-triggering input to refine or reformulate their fix. we manually extracted fixes drawn from real-world projects and evaluated fixation against them: fixation successfully detected the extracted bad fixes.
measuring complexity, effectiveness and efficiency in software course projects. this paper discusses results achieved in measuring complexity, effectiveness and efficiency, in a series of related software course projects, spanning a period of seven years. we focus on how the complexity of those projects was measured, and how the success of the students in effectively and efficiently taming that complexity was assessed. this required defining, collecting, validating and analyzing several indicators of size, effort and quality; their rationales, advantages and limitations are discussed. the resulting findings helped to improve the process itself.
test generation through programming in udita. we present an approach for describing tests using non-deterministic test generation programs. to write such programs, we introduce udita, a java-based language with non-deterministic choice operators and an interface for generating linked structures. we also describe new algorithms that generate concrete tests by efficiently exploring the space of all executions of non-deterministic udita programs. we implemented our approach and incorporated it into the official, publicly available repository of java pathfinder (jpf), a popular tool for verifying java programs. we evaluate our technique by generating tests for data structures, refactoring engines, and jpf itself. our experiments show that test generation using udita is faster and leads to test descriptions that are easier to write than in previous frameworks. moreover, the novel execution mechanism of udita is essential for making test generation feasible. using udita, we have discovered a number of bugs in eclipse, netbeans, sun javac, and jpf.
archface: a contract place where architectural design and code meet together. this paper proposes archface, an interface mechanism for bridging the gap between architectural design and its implementation. archface, which encapsulates design essence based on the component-and-connector architecture, is not only an adl (architecture description language) but also a programming-level interface. archface is effective for software evolution because traceability between design and its implementation can be realized by enforcing architectural constraints on program implementation, and this traceability is bidirectional. in archface, a component exposes program points such as method call/execution and a connector defines how to coordinate exposed program points. a collaborative architecture consisting of components can be encapsulated into a group of interfaces and separated from implementation, because dynamic program points representing control flow can be specified in the interfaces. we can characterize the notion of archface with the phrase "predicate coordination," in which program points are exposed by a predicate and coordinated by a trait-based connector.
leakpoint: pinpointing the causes of memory leaks. most existing leak detection techniques for c and c++ applications only detect the existence of memory leaks. they do not provide any help for fixing the underlying memory management errors. in this paper, we present a new technique that not only detects leaks, but also points developers to the locations where the underlying errors may be fixed. our technique tracks pointers to dynamically-allocated areas of memory and, for each memory area, records several pieces of relevant information. this information is used to identify the locations in an execution where memory leaks occur. to investigate our technique's feasibility and usefulness, we developed a prototype tool called leakpoint and used it to perform an empirical evaluation. the results of this evaluation show that leakpoint detects at least as many leaks as existing tools, reports zero false positives, and, most importantly, can be effective at helping developers fix the underlying memory management errors.
an empirical study of optimizations in yogi. though verification tools are finding industrial use, the utility of engineering optimizations that make them scalable and usable is not widely known. despite the fact that several optimizations are part of folklore in the communities that develop these tools, no rigorous evaluation of these optimizations has been done before. we describe and evaluate several engineering optimizations implemented in the yogi property checking tool, including techniques to pick an initial abstraction, heuristics to pick predicates for refinement, optimizations for interprocedural analysis, and optimizations for testing. we believe that our empirical evaluation gives the verification community useful information about which optimizations they could implement in their tools, and what gains they can realistically expect from these optimizations.
developers ask reachability questions. a reachability question is a search across feasible paths through a program for target statements matching search criteria. in three separate studies, we found that reachability questions are common and often time consuming to answer. in the first study, we observed 13 developers in the lab and found that half of the bugs developers inserted were associated with reachability questions. in the second study, 460 professional software developers reported asking questions that may be answered using reachability questions more than 9 times a day, and 82% rated one or more as at least somewhat hard to answer. in the third study, we observed 17 developers in the field and found that 9 of the 10 longest activities were associated with reachability questions. these findings suggest that answering reachability questions is an important source of difficulty understanding large, complex codebases.
a degree-of-knowledge model to capture source code familiarity. the size and high rate of change of source code comprising a software system make it difficult for software developers to keep up with who on the team knows about particular parts of the code. existing approaches to this problem are based solely on authorship of code. in this paper, we present data from two professional software development teams to show that both authorship and interaction information about how a developer interacts with the code are important in characterizing a developer's knowledge of code. we introduce the degree-of-knowledge model that computes automatically a real value for each source code element based on both authorship and interaction information. we show that the degree-of-knowledge model can provide better results than an existing expertise finding approach and also report on case studies of the use of the model to support knowledge transfer and to identify changes of interest.
developing next generation adls through mde techniques. despite the flourishing of languages to describe software architectures, existing architecture description languages (adls) are still far away from what it is actually needed. in fact, while they support a traditional perception of a software architecture (sa) as a set of constituting elements (such as components, connectors and interfaces), they mostly fail to capture multiple stakeholders concerns and their design decisions that represent a broader view of sa being accepted today. next generation adls must cope with various and ever evolving stakeholder concerns by employing semantic extension mechanisms. in this paper we present a framework, called byadl - build your adl, for developing a new generation of adls. byadl exploits model-driven techniques that provide the needed technologies to allow a software architect, starting from existing adls, to define its own new generation adl by: i) adding domain specificities, new architectural views, or analysis aspects, ii) integrating adls with development processes and methodologies, and iii) customizing adls by fine tuning them. the framework is put in practice in different scenarios showing the incremental extension and customization of the darwin adl.
a machine learning approach for tracing regulatory codes to product specific requirements. regulatory standards, designed to protect the safety, security, and privacy of the public, govern numerous areas of software intensive systems. project personnel must therefore demonstrate that an as-built system meets all relevant regulatory codes. current methods for demonstrating compliance rely either on after-the-fact audits, which can lead to significant refactoring when regulations are not met, or else require analysts to construct and use traceability matrices to demonstrate compliance. manual tracing can be prohibitively time-consuming; however automated trace retrieval methods are not very effective due to the vocabulary mismatches that often occur between regulatory codes and product level requirements. this paper introduces and evaluates two machine-learning methods, designed to improve the quality of traces generated between regulatory codes and product level requirements. the first approach uses manually created traceability matrices to train a trace classifier, while the second approach uses web-mining techniques to reconstruct the original trace query. the techniques were evaluated against security regulations from the usa government's health insurance privacy and portability act (hipaa) traced against ten healthcare related requirements specifications. results demonstrated improvements for the subset of hipaa regulations that exhibited high fan-out behavior across the requirements datasets.
code bubbles: rethinking the user interface paradigm of integrated development environments. today's integrated development environments (ides) are hampered by their dependence on files and file-based editing. we propose a novel user interface that is based on collections of lightweight editable fragments, called bubbles, which when grouped together form concurrently visible working sets. in this paper we describe the design of a prototype ide user interface for java based on working sets. a quantitative evaluation shows that developers could expect to view a sizeable number of functions concurrently with relatively few ui operations. a qualitative user evaluation with 23 professional developers indicates a high level of excitement, interest, and potential benefits and uses.
adaptive bug isolation. statistical debugging uses lightweight instrumentation and statistical models to identify program behaviors that are strongly predictive of failure. however, most software is mostly correct; nearly all monitored behaviors are poor predictors of failure. we propose an adaptive monitoring strategy that mitigates the overhead associated with monitoring poor failure predictors. we begin by monitoring a small portion of the program, then automatically refine instrumentation over time to zero in on bugs. we formulate this approach as a search on the control-dependence graph of the program. we present and evaluate various heuristics that can be used for this search. we also discuss the construction of a binary instrumentor for incorporating the feedback loop into post-deployment monitoring. performance measurements show that adaptive bug isolation yields an average performance overhead of 1% for a class of large applications, as opposed to 87% for realistic sampling-based instrumentation and 300% for complete binary instrumentation.
views: object-inspired concurrency control. we present views, a new approach to controlling concurrency. fine-grained locking is often necessary to increase concurrency. correctly implementing fine-grained locking with today's concurrency primitives can be challenging---race conditions often plague programs with sophisticated locking schemes. views ease the task of implementing sophisticated locking schemes and provide static checks to automatically detect many data races. views consist of view declarations that describe which views of an object may be simultaneously held by different threads, which object fields may be accessed through a given view, and which methods can be called through a given view. a set of view annotations specify which code regions hold a view of an object. our view compiler performs simple static checks which eliminate many data races. we have ported three benchmark applications to use views: portions of vuze, a bittorrent client; mailpuccino, a graphical e-mail client; and tuplesoup, a database. our experience indicates that views are easy to use, make implementing sophisticated locking schemes simple, and can help eliminate concurrency bugs.
an empirical analysis of team review approaches for teaching quality software development. reviews are an integral part of the software development process. they are one of the key methodologies that undergraduates study in order to develop quality software. despite their importance, reviews are rarely used in software engineering projects at the baccalaureate level. this paper demonstrates results from a study conducted on students at baccalaureate level enrolled in a one-semester software engineering course at the national university of computer and emerging sciences -- foundation for advancement of science and technology (nuces-fast) in pakistan. the objectives of the study are: to determine how the various team review techniques help to educate students about the importance of the review process and find which technique is more suitable for teaching reviews to undergraduates. two variations on team review are proposed: similar domain review (sdr) and cross-domain review (cdr) without author. the paper presents a comparison of the proposed and existing team review techniques and measures their effectiveness in terms of defect detection. the results show that the proposed variation sdr is more effective in defect detection than cdr (with/without author). another interesting result is that the proposed cdr-without author is better than cdr with author (the existing team review approach). also, early defect detection enabled students to incorporate changes and improve the software quality.
online inference and enforcement of temporal properties. the interfaces of software components are often paired with specifications or protocols that prescribe correct and safe usage. an important class of these specifications consists of temporal safety properties over function or method call sequences. because violations of these properties can lead to program crashes or subtly inconsistent program state, these properties are frequently the target of runtime monitoring techniques. however, the properties must be specified in advance, a time-consuming process. recognizing this problem, researchers have proposed various specification inference techniques, but they suffer from imprecision and require a significant investment in developer time. this work presents the first fully automatic dynamic technique for simultaneously learning and enforcing general temporal properties over method call sequences. our technique is an online algorithm that operates over a short, finite execution history. this limited view works well in practice due to the inherent temporal locality in sequential method calls on java objects, a property we validate empirically. we have implemented our algorithm in a practical tool for java, ocd, that operates with a high degree of precision and finds new defects and code smells in well-tested applications.
mining api mapping for language migration. to address business requirements and to survive in competing markets, companies or open source organizations often have to release different versions of their projects in different languages. manually migrating projects from one language to another (such as from java to c#) is a tedious and error-prone task. to reduce manual effort or human errors, tools can be developed for automatic migration of projects from one language to another. however, these tools require the knowledge of how application programming interfaces (apis) of one language are mapped to apis of the other language, referred to as api mapping relations. in this paper, we propose a novel approach, called mam (mining api mapping), that mines api mapping relations from one language to another using api client code. mam accepts a set of projects each with two versions in two languages and mines api mapping relations between those two languages based on how apis are used by the two versions. these mined api mapping relations assist in migration of projects from one language to another. we implemented a tool and conducted two evaluations to show the effectiveness of mam. the results show that our tool mines 25,805 unique mapping relations of apis between java and c# with more than 80% accuracy. the results also show that mined api mapping relations help reduce 54.4% compilation errors and 43.0% defects during migration of projects with an existing migration tool, called java2csharp. the reduction in compilation errors and defects is due to our new mined mapping relations that are not available with the existing migration tool.
summarizing software artifacts: a case study of bug reports. many software artifacts are created, maintained and evolved as part of a software development project. as software developers work on a project, they interact with existing project artifacts, performing such activities as reading previously filed bug reports in search of duplicate reports. these activities often require a developer to peruse a substantial amount of text. in this paper, we investigate whether it is possible to summarize software artifacts automatically and effectively so that developers could consult smaller summaries instead of entire artifacts. to provide focus to our investigation, we consider the generation of summaries for bug reports. we found that existing conversation-based generators can produce better results than random generators and that a generator trained specifically on bug reports can perform statistically better than existing conversation-based generators. we demonstrate that humans also find these generated summaries reasonable indicating that summaries might be used effectively for many tasks.
panel on master's degree programs in software engineering. as software engineering advances, new software engineering programs continue to emerge in universities around the world and existing ones are continually being updated. these programs face myriad challenges such as incorporating new software engineering technologies, recruiting and retaining qualified faculty, attracting students, leveraging new technologies for remote teaching, integrating related disciplines such as systems engineering, and, of course, deciding what basic content to include in their courses. the recently published graduate software engineeing 2009 "gswe2009" (http://www.gswe2009.org) presents a model and guidelines to help faculty address those challenges. both acm and ieee approved and endorsed gswe2009 in 2009. the panel will debate approaches to developing master's programs in software engineering in general and gswe2009 in particular. it will consider experiences, challenges, and criticisms of gswe2009.
effective interprocedural resource leak detection. garbage collection relieves programmers from the burden of explicit memory management. however, explicit management is still required for finite system resources, such as i/o streams, fonts, and database connections. failure to release unneeded system resources results in resource leaks, which can lead to performance degradation and system crashes. in this paper, we present a new tool, tracker, that performs static analysis to find resource leaks in java programs. tracker is an industrial-strength tool that is usable in an interactive setting: it works on millions of lines of code in a matter of minutes and it has a low false positive rate. we describe the design, implementation and evaluation of tracker, focusing on the features that make the tool scalable and its output actionable by the user.
is operator-based mutant selection superior to random mutant selection? due to the expensiveness of compiling and executing a large number of mutants, it is usually necessary to select a subset of mutants to substitute the whole set of generated mutants in mutation testing and analysis. most existing research on mutant selection focused on operator-based mutant selection, i.e., determining a set of sufficient mutation operators and selecting mutants generated with only this set of mutation operators. recently, researchers began to leverage statistical analysis to determine sufficient mutation operators using execution information of mutants. however, whether mutants selected with these sophisticated techniques are superior to randomly selected mutants remains an open question. in this paper, we empirically investigate this open question by comparing three representative operator-based mutant-selection techniques with two random techniques. our empirical results show that operator-based mutant selection is not superior to random mutant selection. these results also indicate that random mutant selection can be a better choice and mutant selection on the basis of individual mutants is worthy of further investigation.
collaborative reliability prediction of service-oriented systems. service-oriented architecture (soa) is becoming a major software framework for building complex distributed systems. reliability of the service-oriented systems heavily depends on the remote web services as well as the unpredictable internet. designing effective and accurate reliability prediction approaches for the service-oriented systems has become an important research issue. in this paper, we propose a collaborative reliability prediction approach, which employs the past failure data of other similar users to predict the web service reliability for the current user, without requiring real-world web service invocations. we also present a user-collaborative failure data sharing mechanism and a reliability composition model for the service-oriented systems. large-scale real-world experiments are conducted and the experimental results show that our collaborative reliability prediction approach obtains better reliability prediction accuracy than other approaches.
beyond hacking: an sos! cyber-security today is focused largely on defending against known attacks. we learn about the latest attack and find a hack to defend against it. so our defenses improve only after they have been successfully penetrated. this is a recipe to ensure some attackers succeed---not a recipe for achieving system trustworthiness. we must move beyond reacting to yesterday's attacks and instead start building systems whose trustworthiness derives from first principles. yet today we lack the understanding to adopt that proactive approach; it's not only a matter of engineering, but we lack a science of security (sos). the sos landscape would includes attacks, defense mechanisms, and security properties; the science would characterize how these relate. what security properties can be preserved by a given defense mechanism? what attacks are resisted by a given mechanism? how can enforcement mechanisms be viewed as "trust relocators"? some challenges are reminiscent of problems that software engineering researchers confront; others resemble problems addressed in the fault-tolerance community. in fact, there are significant technical differences for an sos, deriving from the very different assumptions about requirements and the environment. this talk will attempt clarify the differences. we will also survey recent and promising avenues toward building a sos and creating a principled basis for the engineering of trustworthy systems.
software traceability with topic modeling. software traceability is a fundamentally important task in software engineering. the need for automated traceability increases as projects become more complex and as the number of artifacts increases. we propose an automated technique that combines traceability with a machine learning technique known as topic modeling. our approach automatically records traceability links during the software development process and learns a probabilistic topic model over artifacts. the learned model allows for the semantic categorization of artifacts and the topical visualization of the software system. to test our approach, we have implemented several tools: an artifact search tool combining keyword-based search and topic modeling, a recording tool that performs prospective traceability, and a visualization tool that allows one to navigate the software architecture and view semantic topics associated with relevant artifacts and architectural components. we apply our approach to several data sets and discuss how topic modeling enhances software traceability, and vice versa.
using twinning to adapt programs to alternative apis. we describe twinning and its applications to adapting programs to alternative apis. twinning is a simple technique that allows programmers to specify a class of program changes, in the form of a mapping, without modifying the target program directly. using twinning, programmers can specify changes that transition a program from using one api to using an alternative api. we describe two related mapping-based source-to-source transformations. the first applies the mapping to a program, producing a copy with the changes applied. the second generates a new api that abstracts the changes specified in the mapping. using this api, programmers can invoke either the old (replaced) code or the new (replacement) code through a single interface. managing program variants usually involves heavyweight tasks that can prevent the program from compiling for extended periods of time, as well as simultaneous maintenance of multiple implementations, which can make it easy to forget to add features or to fix bugs symmetrically. our main contribution is to show that, at least in some common cases, the heavyweight work can be reduced and symmetric maintenance can be at least encouraged, and often enforced.
a search engine for finding highly relevant applications. a fundamental problem of finding applications that are highly relevant to development tasks is the mismatch between the high-level intent reflected in the descriptions of these tasks and low-level implementation details of applications. to reduce this mismatch we created an approach called exemplar (executable examples archive) for finding highly relevant software projects from large archives of applications. after a programmer enters a natural-language query that contains high-level concepts (e.g., mime, data sets), exemplar uses information retrieval and program analysis techniques to retrieve applications that implement these concepts. our case study with 39 professional java programmers shows that exemplar is more effective than sourceforge in helping programmers to quickly find highly relevant applications.
an empirical study of reported bugs in server software with implications for automated bug diagnosis. reproducing bug symptoms is a prerequisite for performing automatic bug diagnosis. do bugs have characteristics that ease or hinder automatic bug diagnosis? in this paper, we conduct a thorough empirical study of several key characteristics of bugs that affect reproducibility at the production site. we examine randomly selected bug reports of six server applications and consider their implications on automatic bug diagnosis tools. our results are promising. from the study, we find that nearly 82% of bug symptoms can be reproduced deterministically by re-running with the same set of inputs at the production site. we further find that very few input requests are needed to reproduce most failures; in fact, just one input request after session establishment suffices to reproduce the failure in nearly 77% of the cases. we describe the implications of the results on reproducing software failures and designing automated diagnosis tools for production runs.
a cut-off approach for bounded verification of parameterized systems. the features in multi-threaded programs, such as recursion, dynamic creation and communication, pose a great challenge to formal verification. a widely adopted strategy is to verify tentatively a system with a smaller size, by limiting the depth of recursion or the number of replicated processes, to find errors without ensuring the full correctness. the model checking of parameterized systems, a parametric infinite family of systems, is to decide if a property holds in every size instance. there has been a quest for finding cut-offs for the verification of parameterized systems. the basic idea is to find a cut-off on the number of replicated processes or on the maximum length of paths needed to prove a property, standing a chance of improving verification efficiency substantially if one can come up with small or modest cut-offs. in this paper, a novel approach, called forward bounded reachability analysis (fbra), based upon the cut-off on the maximum lengths of paths is proposed for the verification of parameterized systems. experimental results show that verification efficiency has been significantly improved as a result of the introduction of our new cut-offs.
aura: a hybrid approach to identify framework evolution. software frameworks and libraries are indispensable to today's software systems. as they evolve, it is often time-consuming for developers to keep their code up-to-date, so approaches have been proposed to facilitate this. usually, these approaches cannot automatically identify change rules for one-replaced-by-many and many-replaced-by-one methods, and they trade off recall for higher precision using one or more experimentally-evaluated thresholds. we introduce aura, a novel hybrid approach that combines call dependency and text similarity analyses to overcome these limitations. we implement it in a java system and compare it on five frameworks with three previous approaches by dagenais and robillard, m. kim et al., and sch&auml;fer et al. the comparison shows that, on average, the recall of aura is 53.07% higher while its precision is similar, e.g., 0.10% lower.
engineering parallel applications with tunable architectures. current multicore computers differ in many hardware characteristics. software developers thus hand-tune their parallel programs for a specific platform to achieve the best performance; this is tedious and leads to non-portable code. although the software architecture also requires adaptation to achieve best performance, it is rarely modified because of the additional implementation effort. the tunable architectures approach proposed in this paper automates the architecture adaptation of parallel programs and uses an auto-tuner to find the best-performing software architecture for a particular machine. we introduce a new architecture description language based on parallel patterns and a framework to express architecture variants in a generic way. several case studies demonstrate significant performance improvements due to architecture tuning and show the applicability of our approach to industrial applications. software developers are exposed to less parallel programming complexity, thus making the approach attractive for experts as well as inexperienced parallel programmers.
identifying crosscutting concerns using historical code changes. detailed knowledge about implemented concerns in the source code is crucial for the cost-effective maintenance and successful evolution of large systems. concern mining techniques can automatically suggest sets of related code fragments that likely contribute to the implementation of a concern. however, developers must then spend considerable time understanding and expanding these concern seeds to obtain the full concern implementation. we propose a new mining technique (commit) that reduces this manual effort. commit addresses three major shortcomings of current concern mining techniques: 1) their inability to merge seeds with small variations, 2) their tendency to ignore important facets of concerns, and 3) their lack of information about the relations between seeds. a comparative case study on two large open source c systems (post-gresql and netbsd) shows that commit recovers up to 87.5% more unique concerns than two leading concern mining techniques, and that the three techniques complement each other.
an exploratory study of fault-proneness in evolving aspect-oriented programs. this paper presents the results of an exploratory study on the fault-proneness of aspect-oriented programs. we analysed the faults collected from three evolving aspect-oriented systems, all from different application domains. the analysis develops from two different angles. firstly, we measured the impact of the obliviousness property on the fault-proneness of the evaluated systems. the results show that 40% of reported faults were due to the lack of awareness among base code and aspects. the second analysis regarded the fault-proneness of the main aspect-oriented programming (aop) mechanisms, namely pointcuts, advices and intertype declarations. the results indicate that these mechanisms present similar fault-proneness when we consider both the overall system and concern-specific implementations. our findings are reinforced by means of statistical tests. in general, this result contradicts the common intuition stating that the use of pointcut languages is the main source of faults in aop.
a hot --- human, organizational and technological --- framework for a software engineering course. in this paper, we present a hot --- human, organizational and technological --- framework for software engineering and describe its application in a full one-semester software engineering course on agile software development. we suggest and illustrate how this framework has the potential to widen and deepen the students' understanding of software engineering processes.
quality of service profiling. many computations exhibit a trade off between execution time and quality of service. a video encoder, for example, can often encode frames more quickly if it is given the freedom to produce slightly lower quality video. a developer attempting to optimize such computations must navigate a complex trade-off space to find optimizations that appropriately balance quality of service and performance. we present a new quality of service profiler that is designed to help developers identify promising optimization opportunities in such computations. in contrast to standard profilers, which simply identify time-consuming parts of the computation, a quality of service profiler is designed to identify subcomputations that can be replaced with new (and potentially less accurate) subcomputations that deliver significantly increased performance in return for acceptably small quality of service losses. our quality of service profiler uses loop perforation (which transforms loops to perform fewer iterations than the original loop) to obtain implementations that occupy different points in the performance/quality of service trade-off space. the rationale is that optimizable computations often contain loops that perform extra iterations, and that removing iterations, then observing the resulting effect on the quality of service, is an effective way to identify such optimizable subcomputations. our experimental results from applying our implemented quality of service profiler to a challenging set of benchmark applications show that it can enable developers to identify promising optimization opportunities and deliver successful optimizations that substantially increase the performance with only small quality of service losses.
awareness 2.0: staying aware of projects, developers and tasks using dashboards and feeds. software development teams need to maintain awareness of various different aspects ranging from overall project status and process bottlenecks to current tasks and incoming artifacts. currently, there is a lack of theoretical foundations to guide tool selection and tool design to best support awareness tasks. in this paper, we explore how the combination of highly configurable project, team and contributor dashboards along with individual event feeds is used to accomplish extensive awareness. our results stem from an empirical study of several large development teams, with a detailed study of a team of 150 developers and additional data from another four project teams. we present how dashboards become pivotal to task prioritization in critical project phases and how they stir competition while feeds are used for short term planning. our findings indicate that the distinction between high-level and low-level awareness is often unclear and that integrated tooling could improve development practices.
moving into a new software project landscape. when developers join a software development project, they find themselves in a project landscape, and they must become familiar with the various landscape features. to better understand the nature of project landscapes and the integration process, with a view to improving the experience of both newcomers and the people responsible for orienting them, we performed a grounded theory study with 18 newcomers across 18 projects. we identified the main features that characterize a project landscape, together with key orientation aids and obstacles, and we theorize that there are three primary factors that impact the integration experience of newcomers: early experimentation, internalizing structures and cultures, and progress validation.
recurring bug fixes in object-oriented programs. previous research confirms the existence of recurring bug fixes in software systems. analyzing such fixes manually, we found that a large percentage of them occurs in code peers, the classes/methods having the similar roles in the systems, such as providing similar functions and/or participating in similar object interactions. based on graph-based representation of object usages, we have developed several techniques to identify code peers, recognize recurring bug fixes, and recommend changes for code units from the bug fixes of their peers. the empirical evaluation on several open-source projects shows that our prototype, fixwizard, is able to identify recurring bug fixes and provide fixing recommendations with acceptable accuracy.
falcon: fault localization in concurrent programs. concurrency fault are difficult to find because they usually occur under specific thread interleavings. fault-detection tools in this area find data-access patterns among thread interleavings, but they report benign patterns as well as actual faulty patterns. traditional fault-localization techniques have been successful in identifying faults in sequential, deterministic programs, but they cannot detect faulty data-access patterns among threads. this paper presents a new dynamic fault-localization technique that can pinpoint faulty data-access patterns in multi-threaded concurrent programs. the technique monitors memory-access sequences among threads, detects data-access patterns associated with a program's pass/fail results, and reports dataaccess patterns with suspiciousness scores. the paper also presents the description of a prototype implementation of the technique in java, and the results of an empirical study we performed with the prototype on several java benchmarks. the empirical study shows that the technique can effectively and efficiently localize the faults for our subjects.
towards contextualised software engineering education: an african perspective. the discipline of software engineering is continuously adapting to new challenges while gaining more and more insights. the age of globalisation has brought about a new movement of internationalisation and localisation. while practitioners fully embrace the efforts, educators only marginally consider the implications for the teaching and learning of software engineering. while the relevance of the software deployment context has been widely recognised, the intrinsic values of the development context are less evident. besides western cultural indicators being omnipresent in software applications, they are deeply rooted in software engineering concepts and methods. standards and models have been established in the absence of possible deviations from other -- e.g. african -- contexts. educators and authors of common and internationally used textbooks present software engineering concepts and methods as universally valid. thus software engineering graduates all over the world continue to be ill-equipped for specific software development contexts. moreover the necessity to localise software engineering education is illustrated by our vast amount of challenges, experiences and best-practices of teaching software engineering in a sub-saharan country. in this paper, we introduce a generic framework leading towards a contextualised software engineering education (cse2).
stakenet: using social networks to analyse the stakeholders of large-scale software projects. many software projects fail because they overlook stakeholders or involve the wrong representatives of significant groups. unfortunately, existing methods in stakeholder analysis are likely to omit stakeholders, and consider all stakeholders as equally influential. to identify and prioritise stakeholders, we have developed stakenet, which consists of three main steps: identify stakeholders and ask them to recommend other stakeholders and stakeholder roles, build a social network whose nodes are stakeholders and links are recommendations, and prioritise stakeholders using a variety of social network measures. to evaluate stakenet, we conducted one of the first empirical studies of requirements stakeholders on a software project for a 30,000-user system. using the data collected from surveying and interviewing 68 stakeholders, we show that stakenet identifies stakeholders and their roles with high recall, and accurately prioritises them. stakenet uncovers a critical stakeholder role overlooked in the project, whose omission significantly impacted project success.
determin: inferring likely deterministic specifications of multithreaded programs. the trend towards multicore processors and graphic processing units is increasing the need for software that can take advantage of parallelism. writing correct parallel programs using threads, however, has proven to be quite challenging due to nondeterminism. the threads of a parallel application may be interleaved nondeterministically during execution, which can lead to nondeterministic results---some interleavings may produce the correct result while others may not. we have previously proposed an assertion framework for specifying that regions of a parallel program behave deterministically despite nondeterministic thread interleaving. the framework allows programmers to write assertions involving pairs of program states arising from different parallel schedules. we propose an algorithm to dynamically infer likely deterministic specifications for parallel programs given a set of inputs and schedules. we have implemented our specification inference algorithm for java and have applied it to a number of previously examined java benchmarks. we were able to automatically infer specifications largely equivalent to or stronger than our manual assertions from our previous work. we believe that the inference of deterministic specifications can aid in understanding and documenting the deterministic behavior of parallel programs. moreover, an unexpected deterministic specification can indicate to a programmer the presence of erroneous or unintended behavior.
liability in software engineering: overview of the lise approach and illustration on a case study. lise is a multidisciplinary project involving lawyers and computer scientists with the aim to put forward a set of methods and tools to (1) define software liability in a precise and unambiguous way and (2) establish such liability in case of incident. this paper provides an overview of the overall approach taken in the project based on a case study. the case study illustrates a situation where, in order to reduce legal uncertainties, the parties to a contract wish to include in the agreement specific clauses to define as precisely as possible the share of liabilities between them for the main types of failures of the system.
practical fault localization for dynamic web applications. we leverage combined concrete and symbolic execution and several fault-localization techniques to create a uniquely powerful tool for localizing faults in php applications. the tool automatically generates tests that expose failures, and then automatically localizes the faults responsible for those failures, thus overcoming the limitation of previous fault-localization techniques that a test suite be available upfront. the fault-localization techniques we employ combine variations on the tarantula algorithm with a technique based on maintaining a mapping between statements and the fragments of output they produce. we implemented these techniques in a tool called apollo, and evaluated them by localizing 75 randomly selected faults that were exposed by automatically generated tests in four php applications. our findings indicate that, using our best technique, 87.7% of the faults under consideration are localized to within 1% of all executed statements, which constitutes an almost five-fold improvement over the tarantula algorithm.
an analysis of the variability in forty preprocessor-based software product lines. over 30 years ago, the preprocessor cpp was developed to extend the programming language c by lightweight metaprogramming capabilities. despite its error-proneness and low abstraction level, the preprocessor is still widely used in present-day software projects to implement variable software. however, not much is known about how cpp is employed to implement variability. to address this issue, we have analyzed forty open-source software projects written in c. specifically, we answer the following questions: how does program size influence variability? how complex are extensions made via cpp's variability mechanisms? at which level of granularity are extensions applied? which types of extension occur? these questions revive earlier discussions on program comprehension and refactoring in the context of the preprocessor. to provide answers, we introduce several metrics measuring the variability, complexity, granularity, and types of extension applied by preprocessor directives. based on the collected data, we suggest alternative implementation techniques. our data set is a rich source for rethinking language design and tool support.
the educational value of mapping studies of software engineering literature. we identify three challenges related to the provenance of the material we use in teaching software engineering. we suggest that these challenges can be addressed by using evidence-based software engineering (ebse) and its primary tool of systematic literature reviews (slrs). this paper aims to assess the educational and scientific value of undergraduate and postgraduate students undertaking a specific form of slr called a mapping study. using a case study methodology, we asked three postgraduate students and three undergraduates and their supervisor to complete a questionnaire concerning the educational value of mapping studies and any problems they experienced. students found undertaking a mapping study to be a valuable experience providing both reusable research skills and a good overview of a research topic. postgraduates found it useful as a starting point for their studies. undergraduates reported problems undertaking the study in the required timescales. searching and classifying the literature was difficult.
oracle-guided component-based program synthesis. we present a novel approach to automatic synthesis of loop-free programs. the approach is based on a combination of oracle-guided learning from examples, and constraint-based synthesis from components using satisfiability modulo theories (smt) solvers. our approach is suitable for many applications, including as an aid to program understanding tasks such as deobfuscating malware. we demonstrate the efficiency and effectiveness of our approach by synthesizing bit-manipulating programs and by deobfuscating programs.
customized awareness: recommending relevant external change events. it is often assumed that developers' view of their system and its environment is always consistent with everyone else's; in practice, this assumption can be false, as the developer has little practical control over changes to the environments in which their code will be deployed. to proactively respond to such situations, developers must constantly monitor a flood of information involving changes to the deployment environments; unfortunately, the vast majority of this information is irrelevant to the individual developer, and its sheer volume makes it likely that infrequent change events of relevance are overlooked. as a result, errors may arise at deployment time that the developer does not immediately detect. this paper presents a recommendation approach for filtering the flood of change events on deployment dependencies to those that are most likely to cause problems for the individual developer. the approach is evaluated for its ability to drastically filter irrelevant details, while being unlikely to filter important ones. the relevance of the results is assessed on the basis of deployment problems that would have historically occurred within a set of industrial systems.
supporting developers with natural language queries. the feature list of modern ides is steadily growing and mastering these tools becomes more and more demanding, especially for novice programmers. despite their remarkable capabilities, ides often still cannot directly answer the questions that arise during program comprehension tasks. instead developers have to map their questions to multiple concrete queries that can be answered only by combining several tools and examining the output of each of them manually to distill an appropriate answer. existing approaches have in common that they are either limited to a set of predefined, hardcoded questions, or that they require to learn a specific query language only suitable for that limited purpose. we present a framework to query for information about a software system using guided-input natural language resembling plain english. for that, we model data extracted by classical software analysis tools with an owl ontology and use knowledge processing technologies from the semantic web to query it. we use a case study to demonstrate how our framework can be used to answer queries about static source code information for program comprehension purposes.
detecting atomic-set serializability violations in multithreaded programs through active randomized testing. concurrency bugs are notoriously difficult to detect because there can be vast combinations of interleavings among concurrent threads, yet only a small fraction can reveal them. atomic-set serializability characterizes a wide range of concurrency bugs, including data races and atomicity violations. in this paper, we propose a two-phase testing technique that can effectively detect atomic-set serializability violations. in phase i, our technique infers potential violations that do not appear in a concrete execution and prunes those interleavings that are violation-free. in phase ii, our technique actively controls a thread scheduler to enumerate these potential scenarios identified in phase i to look for real violations. we have implemented our technique as a prototype system assetfuzzer and applied it to a number of subject programs for evaluating concurrency defect analysis techniques. the experimental results show that assetfuzzer can identify more concurrency bugs than two recent testing tools racefuzzer and atomfuzzer.
efficient hybrid typestate analysis by determining continuation-equivalent states. typestate analysis determines whether a program violates a set of finite-state properties. because the typestate-analysis problem is statically undecidable, researchers have proposed a hybrid approach that uses residual monitors to signal property violations at runtime. we present an efficient novel static typestate analysis that is flow-sensitive, partially context-sensitive, and that generates residual runtime monitors. to gain efficiency, our analysis uses precise, flow-sensitive information on an intra-procedural level only, and models the remainder of the program using a flow-insensitive pointer abstraction. unlike previous flow-sensitive analyses, our analysis uses an additional backward analysis to partition states into equivalence classes. code locations that transition between equivalent states are irrelevant and require no monitoring. as we show in this work, this notion of equivalent states is crucial to obtaining sound runtime monitors. we proved our analysis correct, implemented the analysis in the clara framework for typestate analysis, and applied it to the dacapo benchmark suite. in half of the cases, our analysis determined exactly the property-violating program points. in many other cases, the analysis reduced the number of instrumentation points by large amounts, yielding significant speed-ups during runtime monitoring.
from scripts to specifications: the evolution of a flight software testing effort. this paper describes the evolution of a software testing effort during a critical period for the flagship mars science laboratory rover project at the jet propulsion laboratory. formal specification for post-run analysis of log files, using a domain-specific language, logscope, replaced scripted real-time analysis. log analysis addresses the key problems of on-the-fly approaches and cleanly separates specification and execution. mining the test repository suggested the inadequacy of the scripted approach, and encouraged a partly engineer-driven development. logscope development should hold insights for others facing the tight deadlines and reactionary nature of testing for critical projects. logscope received a jpl mariner award for "improving productivity and quality of the msl flight software" and has been discussed as an approach for other flight missions. we note logscope features that most contributed to ease of adoption and effectiveness. logscope is general and can be applied to any software producing logs.
jdf: detecting duplicate bug reports in jazz. both developers and users submit bug reports to a bug repository. these reports can help reveal defects and improve software quality. as the number of bug reports in a bug repository increases, the number of the potential duplicate bug reports increases. detecting duplicate bug reports helps reduce development efforts in fixing defects. however, it is challenging to manually detect all potential duplicates because of the large number of existing bug reports. this paper presents jdf (representing jazz duplicate finder), a tool that helps users to find potential duplicates of bug reports on jazz, which is a team collaboration platform for software development and process management. jdf finds potential duplicates for a given bug report using natural language and execution information.
fourth international workshop on software clones (iwsc). software clones are identical or similar pieces of code. they are often the result of copy--and--paste activities as ad-hoc code reuse by programmers. software clones research is of high relevance for the industry. many researchers have reported high rates of code cloning in both industrial and open-source systems. in this workshop we will explore lines of research that evaluate code clone detection methods, reason about ways to remove clones, assess the effect of clones on maintainablity, track clones' evolution, and investigate the root causes of clones.
design science methodology: principles and practice. design scientists have to balance the demands of methodological rigor that they share with purely curiosity-driven scientists, with the demands of practical utility that they share with utility-driven engineers. balancing these conflicting demands can be conceptually complex and may lead to methodological mistakes. for example, treating a design question as an empirical research question may lead to researcher to omit the identification of the practical problem to solve, to omit the identification of stakeholder-motivated evaluation criteria, or to omit trade-off and sensitivity analysis. this tutorial aims to clear up this methodological mist in the case of software engineering (se) research.
exemplar: executable examples archive. searching for applications that are highly relevant to development tasks is challenging because the high-level intent reflected in the descriptions of these tasks doesn't usually match the low-level implementation details of applications. in this demo we show a novel code search engine called exemplar (executable examples archive) to bridge this mismatch. exemplar takes natural-language query that contains high-level concepts (e.g., mime, data sets) as input, then uses information retrieval and program analysis techniques to retrieve applications that implement these concepts.
feature-oriented requirements modelling. our goal is to develop a method for creating models of functional software requirements in which features are explicit, with a focus on the automotive software domain. in the current state of our proposed method, feature requirements are modelled using state machines that describe changes to a shared domain model.
compose & conquer: modularity for end-users. users have vast amounts of information at their disposal and access to many tools that can compute on that data. often, no particular program can fulfill a user's needs; or, when such a program exists, it may be too obscure for the user to find. when users encounter this problem, they resort to ad-hoc approaches, such as importing and exporting data to different file formats, as a way to piece together disparate features from several different programs. as a result, users end up manually entering and manipulating data, defeating the purpose of automatic computing machines. in this paper, we introduce the concept of a creativity engine, which is like a search engine over the possible links between software libraries. a creativity engine can be used to bring together libraries that were never intended to work together, in way that can bring within users' reach the almost infinite flexibility their machines have to transform data.
failure preventing recommendations. software becomes more and more integral to our lives thus software failures affect more people than ever. failures are not only responsible for billions of dollars lost to industry but can cause lethal accidents. although there has been much research into predicting such failures, those predictions usually concentrate either on the technical or the social level of software development. with the ever growing size of software teams we think that coordination among developers is becoming increasingly more important. therefore, we propose to leverage the combination of both social and technical dimensions to create recommendation upon which developers can act to prevent software failures.
an eclectic approach for change impact analysis. change impact analysis aims at identifying software artifacts being affected by a change. in the past, this problem has been addressed by approaches relying on static, dynamic, and textual analysis. recently, techniques based on historical analysis and association rules have been explored. this paper proposes a novel change impact analysis method based on the idea that the mutual relationships between software objects can be inferred with a statistical learning approach. we use the bivariate granger causality test, a multivariate time series forecasting approach used to verify whether past values of a time series are useful for predicting future values of another time series. results of a preliminary study performed on the samba daemon show that change impact relationships inferred with the granger causality test are complementary to those inferred with association rules. this opens the road towards the development of an eclectic impact analysis approach conceived by combining different techniques.
bpgen: an automated breakpoint generator for debugging. during debugging processes, breakpoints are frequently used to inspect and understand runtime behaviors of programs. although most development environments offer convenient breakpoint facilities, the use of these environments usually requires considerable human efforts in order to generate useful breakpoints. before setting breakpoints or typing breakpoint conditions, developers usually have to make some judgements and hypotheses on the basis of their observations and experience. to reduce this kind of efforts we present a tool, named bpgen, to automatically generate breakpoints for debugging. bpgen uses three well-known dynamic fault localization techniques in tandem to identify suspicious program statements and states, through which both conditional and unconditional breakpoints are generated. bpgen is implemented as an eclipse plugin for supplementing the existing eclipse jdt debugger.
a modeling language's evolution driven by tight interaction between academia and industry. domain specific languages play an important role in model-driven engineering of software-intensive industrial systems. a rich body of knowledge exists on the development of languages, modeling environments, and transformation systems. the understanding of architectural choices for combining these parts into a feasible solution, however, is not particularly deep. we report on an endeavor in the realm of a technology transfer process from academia to industry, where we encountered unexpected influences of the architecture on the modeling language. by examining the evolution of our language and its programming interface, we show that these influences mainly stemmed from practical considerations; for identifying these early on, tight interaction between our research lab and the industrial partner was key. in addition, we share insights into the practice of cooperating with industry by presenting essential lessons we learned.
web2se: first workshop on web 2.0 for software engineering. social software is built around an "architecture of participation" where user data is aggregated as a side-effect of using web 2.0 applications. web 2.0 implies that processes and tools are socially open, and that content can be used in several different contexts. web 2.0 tools and technologies support interactive information sharing, data interoperability and user centered design. for instance, wikis, blogs, tags and feeds help us organize, manage and categorize content in an informal and collaborative way. one goal of this workshop is to investigate how these technologies can improve software development practices. some of these technologies have made their way into collaborative software development processes such as agile and scrum, and in development platforms such as rational team concert which draw their inspiration from web 2.0. these processes and environments are just scratching the surface of what can be done by incorporating web 2.0 approaches and technologies into collaborative software development. this workshop aims to improve our understanding of how web 2.0, manifested in technologies such as mashups or dashboards, can change the culture of collaborative software development.
bayesian methods for data analysis in software engineering. software engineering researchers analyze programs by applying a range of test cases, measuring relevant statistics and reasoning about the observed phenomena. though the traditional statistical methods provide a rigorous analysis of the data obtained during program analysis, they lack the flexibility to build a unique representation for each program. bayesian methods for data analysis, on the other hand, allow for flexible updates of the knowledge acquired through observations. despite their strong mathematical basis and obvious suitability to software analysis, bayesian methods are still largely under-utilized in the software engineering community, primarily because many software engineers are unfamiliar with the use of bayesian methods to formulate their research problems. this tutorial will provide a broad introduction of bayesian methods for data analysis, with a specific focus on problems of interest to software engineering researchers. in addition, the tutorial will provide an in-depth understanding of a subset of popular topics such as bayesian inference, probabilistic prediction techniques, markov models, information theory and sampling. the core concepts will be explained using case studies and the application of prominent statistical tools on examples drawn from software engineering research. at the end of the tutorial, the participants will acquire the necessary skills and background knowledge to formulate their research problems using bayesian methods, and analyze their formulation using appropriate software tools.
emfstore: a model repository for emf models. models need to be put under version control to facilitate collaboration and to control change. emfstore is a software configuration management system tailored to the specific requirements for versioning models. it employs operation-based change tracking, conflict detection and merging.
raw: runtime automatic workarounds. faults in web apis may escape the testing process, and therefore affect thousands of web applications. as a consequence, users of these applications might suffer from related failures for a long time until proper fixes are released by the web api developers. in this paper we present raw, a tool that tries to find workarounds automatically and at runtime, thereby reducing the negative impact of faults in web applications. runtime and automatically deployed workarounds serve as a temporary relief for application users while proper fixes are developed and released.
cuta4uml: bridging the gap between informal and formal requirements for dynamic system aspects. in this paper, we describe our integrated approach to improve requirements elicitation and system specification by supporting a strong and direct involvement of all stakeholders, including non technical personnel, in the early phases of a project. this so-called cuta4uml approach comprises a framework of methods, tools and feedback cycles that is based on the concept of participatory design (pd) and instantiated via an extended version of a user-driven "card game" (cuta). this card game can be executed on paper or via electronic means. our focus will be on the system's dynamic aspects which are, always, especially tricky to cover. we will also take a closer look at the inherently involved problem to match the rather informal results of such an card-based approach to a quite formal (uml -- activity diagrams) modeling technique -- a step necessary to make the results useful in a structured development process and, so far, one of the weak points in all of these approaches. all our concepts and conclusions are based on a sound experimental basis and have been evaluated and discussed with industrial partners, mostly in a context of small and medium sized companies.
the "physics" of notations: a scientific approach to designing visual notations in software engineering. visual notations form an integral part of the language of software engineering (se). yet historically, se researchers and notation designers have ignored or undervalued issues of visual representation. in evaluating and comparing notations, details of visual syntax are rarely discussed. in designing notations, the majority of effort is spent on semantics, with graphical conventions often an afterthought. typically no design rationale, scientific or otherwise, is provided for visual representation choices. while se has developed mature methods for evaluating and designing semantics, it lacks equivalent methods for visual syntax. this tutorial defines a set of principles for designing cognitively effective visual notations: ones that are optimised for human communication and problem solving. together these form a design theory, called the physics of notations as it focuses on the physical (perceptual) properties of notations rather than their logical (semantic) properties. the principles were synthesised from theory and empirical evidence from a wide range of fields and rest on an explicit theory of how visual notations communicate. they can be used to evaluate, compare and improve existing visual notations as well as to construct new ones. the tutorial identifies serious design flaws in some of the leading se notations together with practical suggestions for improving them. it also showcases some examples of visual notation design excellence from se and other fields.
the 6 international workshop on software engineering for secure systems (sess'10). the 6th edition of the sess workshop aims at providing a venue for software engineers and security researchers to exchange ideas and techniques. in fact, software is at core of most of the business transactions and its smart integration in an industrial setting may be the competitive advantage even when the core competence is outside the ict field. as a result, the revenues of a firm depend directly on several complex software-based systems. thus, stakeholders and users should be able to trust these systems to provide data and elaborations with a degree of confidentiality, integrity, and availability compatible with their needs. moreover, the pervasiveness of software products in the creation of critical infrastructures has raised the value of trustworthiness and new efforts should be dedicated to achieve it. however, nowadays almost every application has some kind of security requirement even if its use is not to be considered critical.
penalty policies in professional software development practice: a multi-method field study. organizational punishment/penalty is a pervasive phenomenon in many professional organizations. in some software development organizations, punishment measures have been adopted in an attempt to improve software developers' performance, reduce the software defects, and hence ensure software quality. it is unclear whether these measures are effective. this article presents the results of a multi-method field study that analyzes software engineers' perception towards penalty policies in relation to software quality in a software development process. the results were generated via both qualitative and quantitative methods. through interviews, we collected the individuals' perception towards the penalty policy. by extracting data in a software configuration management system, we identified several patterns of defects change. we found that while a penalty mechanism does help to reduce software defects in daily coding activity, it fails in achieving programmers' maximum work potential. meanwhile, experienced software programmers require less time to adapt to penalty policies and benefit from exist of less experienced developers. some additional findings and implications are also discussed.
a cost-benefit framework for making architectural decisions in a business context. in any it-intensive organization, it is useful to have a model to associate a value with software and system architecture decisions. more generally, any effort---a project undertaken by a team---needs to have an associated value to offset its labor and capital costs. unfortunately, it is extremely difficult to precisely evaluate the benefit of "architecture projects"---those that aim to improve one or more quality attributes of a system via a structural transformation without (generally) changing its behavior. we often resort to anecdotal and informal "hand-waving" arguments of risk reduction or increased developer productivity. these arguments are typically unsatisfying to the management of organizations accustomed to decision-making based on concrete metrics. this paper will discuss research done to address this long-standing dilemma. specifically, we will present a model derived from analyzing actual projects undertaken at vistaprint corporation. the model presented is derived from an analysis of effort tracked against modifications to specific software components before and after a significant architectural transformation to the subsystem housing those components. in this paper, we will discuss the development, implementation, and iteration of the model and the results that we have obtained.
domain-specific tailoring of code smells: an empirical study. code smells refer to commonly occurring patterns in source code that indicate poor programming practices or code decay. detecting code smells helps developers find design problems that can cause trouble in future maintenance. detection rules for code smells, based on software metrics, have been proposed, but they do not take domain-specific characteristics into consideration. in this study we investigate whether such generic heuristics can be tailored to include domain-specific factors. input into these domain-specific heuristics comes from an iterative empirical field study in a software maintenance project. the results yield valuable insight into code smell detection.
using invariant functions and invariant relations to compute loop functions. in this short paper we discuss the design, implementation and operation of an automated tool that computes the function of while loops written in c-like programming languages.
visualizing the java heap. many of the problems that occur in long-running systems involve the way that the system uses memory. we have developed a framework for extracting and building a model of the heap from a running java system. such a model is only useful if programmers can extract from it the information they need to understand, find, and eventually fix memory-related problems in their system. we demonstrate the tool in action, showing how it works dynamically on running processes and how it is designed to address a variety of specific memory issues.
code clone detection in practice. due to the negative impact of code cloning on software maintenance efforts as well as on program correctness [4--6], the duplication of code is generally viewed as problematic. however, the techniques and tools developed by the research community in the last decade have not found broad acceptance in software engineering practice yet. this tutorial contributes to a more widespread application of existing approaches by illustrating where cloning comes from, what its consequences are, and how it can be detected.
generative software development. generation of software from modeling languages such as uml and domain specific languages (dsls) has become an important paradigm in software engineering. in this contribution, we present some positions on software development in a model based, generative manner based on home grown dsls as well as the uml. this includes development of dsls as well as development of models in these languages in order to generate executable code, test cases or models in different languages. development of formal dsls contains concepts of metamodels or grammars (syntax), context conditions (static analysis and quality assurance) as well as possibilities to define the semantics of a language. the growing number and complexity of dsls is addressed by concepts for the modular and compositional development of languages and their tools. moreover, we introduce approaches to code generation and model transformation. finally, we give an overview of the relevance of dsls for various steps of software development processes.
smt-based bounded model checking for multi-threaded software in embedded systems. the transition from single-core to multi-core processors has made multi-threaded software an important subject over the last years in computer-aided verification. model checkers have been successfully applied to discover subtle errors, but they suffer from combinatorial state space explosion when verifying multi-threaded software. in our previous work, we have extended the encodings from smt-based bounded model checking (bmc) to provide more accurate support for program verification and to use different background theories and solvers in order to improve scalability and precision in a completely automatic way. we now focus on extending this work to support an smt-based bmc formulation of multithreaded software which allows the state space to be reduced by abstracting the number of state variables and interleavings from the proof of unsatisfiability generated by the smt solvers. the core idea of our approach aims to extract the proof objects produced by the smt solvers in order to control the number of interleavings and to remove logic that is not relevant to a given property. this work aims to develop a new algorithmic method and corresponding tools based on smt to verify embedded software in multi-core systems.
soabench: performance evaluation of service-oriented middleware made easy. soabench is a framework for the automatic generation, execution and analysis of testbeds for evaluating the performance of service-oriented middleware. testbeds can be characterized in terms of the composite services to execute, the workload to generate, the deployment configuration to use, the performance metrics to gather, the data analyses to perform on them, and the reports to produce.
exploratory study of a uml metric for fault prediction. this paper describes the use of a uml metric, an approximation of the ck-rfc metric, for predicting faulty classes before their implementation. we built a code-based prediction model of faulty classes using logistic regression. then, we tested it in different projects, using on the one hand their uml metrics, and on the other hand their code metrics. to decrease the difference of values between uml and code measures, we normalized them using linear scaling to unit variance. our results indicate that the proposed uml rfc metric can predict faulty code as well as its corresponding code metric does. moreover, the normalization procedure used was of great utility, not just for enabling our uml metric to predict faulty code, using a code-based prediction model, but also for improving the prediction results across different packages and projects, using the same model.
software architecture for systems of software intensive systems (s3): the concepts and detection of inter-system relationships. key to software architecture is the description of relationships between software components [10] supported by commonly understood semantic definitions [9][8]. however, the definitions do not adequately capture the inter-system level software relationships. this leaves software architects either unaware of critical relationships or, to 'roll their own' based on aggregations of code-level call/use structures. this leads to critical gaps in the architectural description and communication problems within distributed development environments - as poorly understood relationships can inadvertently propagate changes and break system interoperability [2]. the solution requires a description of new system level relationships and a new systematic, repeatable technique to detect both immediate and linked system level relationships. the solution will be developed through the mining of existing software ecosystems and industry systems of software intensive systems (s3) architectures. validation will be performed through case studies from industry collaborations.
bridging the gap between the theory and practice of software test automation. in software development practice, testing often accounts for as much as 50% of the total development effort. it is therefore imperative to reduce the cost and improve the effectiveness of software testing by automating the testing process. in the past decades, a substantial amount of research effort has been invested into the development and study of automatic test case generation, automatic test oracles, and other (semi-)automated testing techniques. as the theory and practice of software testing becomes more mature, a deeper and more meaningful automation of the testing process is possible. therefore, the automation of various testing activities is now becoming an integral part of industrial practice. in response to and in support of these exciting developments, the 5th workshop on the automation of software test provides a publication forum that bridges the gap between the theory and practice of automated testing.
using ethnographic methods in software engineering research. this tutorial provides an overview of the role of ethnography in software engineering research. it describes the use of ethnographic methods as a means to provide an in-depth understanding of the socio-technological realities surrounding everyday software development practice. the knowledge gained can be used to improve processes, methods and tools as well as develop observed industrial practices. the tutorial begins with a brief historical account of ethnography in the fields of software engineering, cscw, information systems and other related areas. this sets the stage for a more in-depth discussion of methods for data collection and analysis used in ethnographic studies. it then describes how these methods can be and have been used by software engineering researchers to understand developers' work practices, to inform the development of processes, methods and tools and to evaluate the applicability of current processes, methods and tools. finally, some practical issues concerning the selection and use of ethnographic methods by software engineers are discussed. throughout the tutorial, examples from the presenters' experience illustrate the points made.
software architecture and agile software development: a clash of two cultures? software architecture is taking a bad rap with the agilists---proponents of agile and lean software development approaches: "bufd big up-front design", "yagni you ain't gonna need it", "massive documentation", "smells of waterfall", it is pictured as a typical non-agile practice. however, certain classes of system, ignoring architectural issues too long "hit a wall" and collapse by lack of an architectural focus. 'agile architecture': a paradox, an oxymoron, two totally incompatible approaches? in this tutorial, we examine the real issues at stake, beyond the rhetoric and posturing, and show that the two cultures can coexist and support each other, where appropriate. we define heuristics to scope how much architecture a project really needs, to assign actual value to an otherwise invisible architecture; and we review management and development practices that do work in the circumstances where some significant architectural effort is needed, when you are actually going to need it.
lm: a miner for scenario-based specifications. we present lm, a tool for mining scenario-based specifications in the form of live sequence charts, a visual language that extends sequence diagrams with modalities. lm comes with a project management component, a wizard-like interface to the mining algorithm, a set of pre- and post-processing extensions, and a visualization module.
formal methods for web services: a taxonomic approach. formal methods can be used to verify different perspective of a web service. an ensemble of specific techniques is not supported by a general approach to the problem. to understand which formal method should be combined and used is a challenge. this paper outlines our approach to address this problem.
improving wide-area distributed system availability. the software-as-a-service (saas) paradigm and corresponding service-oriented technologies have simplified the development of larger, more complex software systems that routinely span administrative and organisational boundaries. these systems inhabit a complex operating environment with numerous threats to the dependability of service compositions. these threats include many system-level failures whose causes are difficult and time-consuming to determine. it is difficult to detect vulnerabilities to these failures prior to deployment of an application into production and applications are currently not well-equipped to handle them effectively. this results in lengthy downtimes of production systems and hence low availability. the goal of this phd is to increase the availability of such systems by eliminating as many failures as possible before deployment and by assisting administrators to diagnose their causes more efficiently. we propose a novel monitoring technique and apply failure injection techniques that target these difficult failures and enable separate administrative domains to cooperate in handling them. furthermore, we investigate the extent to which we can equip these systems to be self-diagnosing.
requirements reflection: requirements as runtime entities. computational reflection is a well-established technique that gives a program the ability to dynamically observe and possibly modify its behaviour. to date, however, reflection is mainly applied either to the software architecture or its implementation. we know of no approach that fully supports requirements reflection- that is, making requirements available as runtime objects. although there is a body of literature on requirements monitoring, such work typically generates runtime artefacts from requirements and so the requirements themselves are not directly accessible at runtime. in this paper, we define requirements reflection and a set of research challenges. requirements reflection is important because software systems of the future will be self-managing and will need to adapt continuously to changing environmental conditions. we argue requirements reflection can support such self-adaptive systems by making requirements first-class runtime entities, thus endowing software systems with the ability to reason about, understand, explain and modify requirements at runtime.
portable secure identity management for software engineering. identity management refers to authentication, sharing of personally identifiable information (pii) and provision of mechanisms protecting the privacy thereof. the most commonly implemented is federated authentication, permitting users to maintain a single set of credentials to access many services. specifications exist for profile exchange between a service provider (sp) and the identity provider (idp), but are rarely used. most frequently, local storage of profile data is utilised due to security and privacy concerns. key work in this area includes that of the prime project, which provides privacy enhancing identity management [1]. their work utilises local data stores and/or trusted third parties.
first international workshop on product line approaches in software engineering (please 2010). please is a new workshop series that focuses on exploring the present and the future of software product line engineering (sple) techniques. the goal of the workshop is to bring together researchers and practitioners with special interest in sple in order to discuss ongoing research and new ideas for advancing the field. the workshop's main theme, beyond product lines, focuses on the adaptation of sple to dynamic settings in which neither the goal nor the organizational structure is stable. we seek to foster exchange of ideas, techniques, and approaches with the broader software engineering community. in a special session of this year's edition, we examine how to leverage existing research by discussing synergy opportunities with members of the software clones community. the first edition of please is held in conjunction with the 32st international conference in software engineering (may 2--8, 2010. cape town, south africa).
supporting program comprehension with source code summarization. one of the main challenges faced by today's developers is keeping up with the staggering amount of source code that needs to be read and understood. in order to help developers with this problem and reduce the costs associated with it, one solution is to use simple textual descriptions of source code entities that developers can grasp easily, while capturing the code semantics precisely. we propose an approach to automatically determine such descriptions, based on automated text summarization technology.
2nd international workshop on software engineering in health care (sehc 2010). society faces increasing reliance on software-intensive systems to manage health services, from scheduling, billing, and patient records to the control of life-critical devices and procedures. there are important concerns about software quality, security, and privacy, user interfaces, system interoperability, process automation and improvement, and many other issues of current concern to software engineering practitioners and researchers. it is widely recognized that information and communication technologies (icts) will transform healthcare of the future, being a driving force for improving care and access, while reducing the overall cost when broadly calculated based on overall productivity and quality of life.
experiences in initiating concurrency software research efforts. multi-core cpus are now common in modern computers. to get access to effectively an unlimited supply of compute resources, software programs that have been highly optimized to use a single cpu need to be converted where possible to use concurrency. we have initiated our concurrency software research for performance enhancement on a large-scale system with high throughput and low latency transactions. in this paper, we report our experience, experiments, and results in various aspects of concurrency design and programming, including multi-threaded prototypes, static and dynamic concurrency analysis, future techniques and trends, concurrency experiments, and concurrency design patterns. based on the concurrency experiments, we achieved at least 80 percent overall performance increases as measured by transaction throughput. as a result, capital expenditures for large scale deployments can be significantly reduced.
improved social trustability of code search results. search is a fundamental activity in software development. however, to search source code efficiently, it is not sufficient to implement a traditional full text search over a base of source code, human factors have to be taken into account as well. we looked into ways of increasing the search results code trustability by providing and analysing a range of meta data alongside the actual search results.
performance modeling in industry: a case study on storage virtualization. in software engineering, performance and the integration of performance analysis methodologies gain increasing importance, especially for complex systems. well-developed methods and tools can predict non-functional performance properties like response time or resource utilization in early design stages, thus promising time and cost savings. however, as performance modeling and performance prediction is still a young research area, the methods are not yet well-established and in wide-spread industrial use. this work is a case study of the applicability of the palladio component model as a performance prediction method in an industrial environment. we model and analyze different design alternatives for storage virtualization on an ibm* system. the model calibration, validation and evaluation is based on data measured on a system z9* as a proof of concept. the results show that performance predictions can identify performance bottlenecks and evaluate design alternatives in early stages of system development. the experiences gained were that performance modeling helps to understand and analyze a system. hence, this case study substantiates that performance modeling is applicable in industry and a valuable method for evaluating design decisions.
ssg: a model-based development environment for smart, security-aware guis. we present a development environment for automatically building smart, security-aware guis following a model-based approach. our environment consists of a number of plugins that have been developed using the eclipse framework and includes three model editors, a model-transformation tool, and a code generator.
bridging lightweight and heavyweight task organization: the role of tags in adopting new task categories. in collaborative software development projects, tasks are often used as a mechanism to coordinate and track shared development work. modern development environments provide explicit support for task management where tasks are typically organized and managed through predefined categories. although there have been many studies that analyze data available from task management systems, there has been relatively little work on the design of task management tools. in this paper we explore how tagging with freely assigned keywords provides developers with a lightweight mechanism to further categorize and annotate development tasks. we investigate how tags that are frequently used over a long period of time reveal the need for additional predefined categories of keywords in task management tool support. finally, we suggest future work to explore how integrated lightweight tool features in a development environment may improve software development practices.
software development governance (sdg) workshop. this is the introduction of the 3rd workshop on software development governance (sdg), which will take place as part of icse 2010. this year we have combined two successful workshops (sdg - software development governance and lmsa -- leadership and management in software architecture) since both workshops deal with decisions that are part of the development process e.g., business and organizational decisions that impact the technical decisions concerned with the product architecture and the product quality.
1st international workshop on replication in empirical software engineering research (reser). the reser 2010 workshop provides a venue in which empirical software engineering researchers may present and discuss theoretical foundations and methods of replication, as well as the results of replicated studies.
sm@rt: representing run-time system data as mof-compliant models. runtime models represent the dynamic data of running systems, and enable developers to manipulate the data in an abstract, model-based way. this paper presents sm@rt, a tool that help realize runtime models on a wide class of systems. receiving a meta-model specifying the target system's data type and an api description specifying how to manipulate the data, sm@rt automatically generates the synchronizer to maintain the runtime model for this system.
synthesize software product line. in the development of a software product line (spl), it is useful to compare various products in order to identify reusable assets and synthesize them in an optimized way. current differencing approaches provide the difference on a low level thus still leaves the spl practitioner considerable manual synthesis work. this paper presents a comparison approach based on common variability language (cvl), which is able to identify the difference on a higher conceptual level. we believe that our cvl compare approach will offer better model comparison support in the context of identifying and synthesizing spls.
flat: feature location and textual tracing tool. feature location is the process of finding the source code that implements a functional requirement of a software system. it plays an important role in software maintenance activities, but when it is performed manually, it can be challenging and time-consuming, especially for large, long-lived systems. this paper describes a tool called flat3 that integrates textual and dynamic feature location techniques along with feature annotation capabilities and a useful visualization technique, providing a complete suite of tools that allows developers to quickly and easily locate the code that implements a feature and then save these annotations for future use.
workshop on emerging trends in software metrics (wetsom 2010). the workshop on emerging trends in software metrics aims at bringing together researchers and practitioners to discuss the progress of software metrics. the motivation for this workshop is the low impact that software metrics has on current software development. the goals of this workshop are to critically examine the evidence for the effectiveness of existing metrics and to identify new directions for development of software metrics.
cloud service engineering. building on compute and storage virtualization, cloud computing provides scalable, network-centric, abstracted it infrastructure, platforms, and applications as on-demand services that are billed by consumption. cloud service engineering is the application of a systematic approach to leverage cloud computing in the context of the internet in its combined role as a platform for technical, economic, organizational and social networks. this tutorial introduces concepts and technology of cloud computing and cloud service engineering, providing an overview of state-of-the-art in research and practice. we show how to set up a private cloud that delivers infrastructure-as-a-service (iaas). eucalyptus and opennebula are popular open source software frameworks for creating on-premise clouds. promises, challenges and solutions for integrating services of a private cloud with public cloud services such as amazon ec2 and sqs are discussed. we show how the best of both worlds - private and public clouds - can be combined to build scalable and secure systems.
staying afloat in an expanding sea of choices: emerging best practices for eclipse rich client platform development. the eclipse rich client platform attracts considerable attention for being a promising candidate for providing the component model java never had. this is even truer since the incorporation of osgi for providing services within the framework. however, the rapid sequence of new versions and the continuous growth of features lead to a discussion that almost exclusively focused on technological aspects while leaving application developers in the midst of a sea of sometimes conflicting choices of how to implement their business-oriented applications. this lack of guidance leads to systems with vastly different architectures (or lack thereof) which often force complete rewrites when further development steps are to be taken. the best practices and architectural blueprints that provide this guidance in the field of object- or service-orientation haven't emerged yet. in this experience report, we render our observations made in several projects over the last years about the challenges that cooperating teams of application developers face when using rcp. we provide a first business-oriented architectural blue-print and best practices that have helped us greatly to overcome these challenges.
second international workshop on software research and climate change. this workshop will explore the contributions that software research can make to the challenge of tackling climate change. software is a critical enabling technology in nearly all aspects of climate change, from the computational models used by climate scientists to improve our understanding of the impact of human activities on earth systems, through to the information and control systems needed to build an effective carbon-neutral society. the intent of the workshop is to explore how software research can contribute to this challenge, to build a community of researchers interested in responding to the challenge, and to map out a research agenda.
emerging faculty symposium 2010. the challenge and prospect of becoming a new teaching faculty member at a research university is one that most people accept with enthusiasm and energy, but also with some trepidation: &bull; how do i get a position? &bull; how do i get to develop and publish strong research results? &bull; how will i be able to balance the many aspects of work as well as my personal life? &bull; what is my academic path to tenure and beyond?
suite 2010: 2nd international workshop on search-driven development - users, infrastructure, tools & evaluation. suite is a workshop that focuses on exploring the notion of search as a fundamental activity during software development. the first edition of suite (suite 2009 [4]) was held at icse 2009. suite 2010, like its predecessor, devotes its attention to various research topics pertaining to the information needs of software developers. in suite 2010, we plan to emphasize open issues identified in suite 2009. we aim to continue building an active network of people interested in the research area that suite addresses.
2010 icse international workshop on advances and applications of problem orientation (waapo-2010). software problems originate from real world problems. a software solution must address its real world problem in a satisfactory way. a software engineer must therefore understand the real world problem that their software intends to address. to be able to do this, the software engineer must understand the problem context and how it is to be affected by the proposed software, expressed as the requirements. without this knowledge the engineer can only hope to chance upon the right solution for the problem. application of problem-oriented approaches may well be a way of meeting this challenge.
cuts: a system execution modeling tool for realizing continuous system integration testing. this paper presents the component workload emulator (cowork-er) utilization test suite (cuts), which is a system execution modeling tool for validating quality-of-service (qos) properties, e.g., end-to-end response time, throughput, and scalability, on the target architecture continuously throughout the software lifecycle.
detecting recurring and similar software vulnerabilities. new software security vulnerabilities are discovered on almost daily basis and it is vital to be able to identify and resolve them as early as possible. fortunately, many software vulnerabilities are recurring or very similar, thus, one could effectively detect and fix a vulnerability in a system by consulting the similar vulnerabilities and fixes from other systems. in this paper, we propose, securesync, an automatic approach to detect and provide suggested resolutions for recurring software vulnerabilities on multiple systems sharing/using similar code or api libraries. the core of securesync includes a usage model and a mapping algorithm for matching vulnerable code across different systems, a model for the comparison of vulnerability reports, and a tracing technique from a report to corresponding source code. our preliminary evaluation with case studies showed the potential usefulness of securesync.
staying aware of relevant feeds in context. to stay aware of relevant information and avoid productivity loss, a developer has to continuously read through new incoming information. our approach supports the integration of dynamic and static information in a development environment that allows the developer to continuously monitor the relevant information in context of his work.
reverse engineering with the reclipse tool suite. design pattern detection is a reverse engineering methodology that helps software engineers to analyze and understand legacy software by recovering its design and thereby aiding in the preparation of re-engineering activities. we present reclipse, a reverse engineering tool suite for static and dynamic design pattern detection in combination with a pattern candidate rating used to assess the detection results' reliability.
testful: automatic unit-test generation for java classes. this paper presents testful, an eclipse plugin for the generation of tests for java classes. it is based on the idea of search-based testing, working both at class and method level. the former puts objects in useful states, used by the latter to exercise the uncovered parts of the class.
visar3d: an approach to software architecture teaching based on virtual and augmented reality. this paper aims to present an approach entitled visar3d to support software architecture teaching by means of virtual and augmented reality. thus, it intends to define a 3d visualization environment which includes exploration, interaction and simulation resources to establish a practical and attractive learning, focusing on large scale systems.
coaching agile software projects: tutorial proposal - icse 2010. our tutorial for icse 2010 focuses on coaching agile software teams. based on eight years of experience guiding agile software projects in the academia and industry, we focus in the tutorial on a coaching framework for agile software projects. the tutorial participants become familiar with coaching practices and gain experience with some of the practices. the tutorial has two main parts. in the first part, we present the coaching framework, including the goals, structure, and guiding principles. in the second part, we focus on the following central themes in agile development processes which, we suggest, are appropriate to be included in such a coaching framework: teamwork and collaboration, time and measures, learning and reflection, and change and leadership. since 2003, we have facilitated this tutorial and similar ones in different settings (industry, academia, conferences). the coaching framework, as well as the themes, case studies, and analysis approach presented in the tutorial, are summarized in our book agile software engineering published by springer in 2008 (hazzan and dubinsky, 2008).
a proposal for consistency checking in dynamic software product line models using ocl. ubiquitous applications use context information to provide services and relevant information for their users. on the other hand, in software product line approaches, commonality and variability of a system family should be identified and documented through variability modeling. thus, one of the challenges to build context-aware product lines, called dynamic software product lines, is the consistent representation of context information that influences the variability model. this work proposes the use of uml profiles and ocl to formalize and represent variability and context concepts in a consistent manner.
a framework for handling variants of software models. the united nations centre for trade facilitation and electronic business (un/cefact) envisions seamless information exchange between business partners in electronic commerce. therefore, un/cefact provides the uml profile for core components for the definition of document models based on uml class diagrams. having used this approach for three years in practice, it became evident that managing document model versions is a prerequisite for successfully utilizing core components. while managing software versions in the area of software engineering is well understood and successfully applied in industrial projects, the direct application of the same techniques for versioning models is conditionally appropriate. in this research abstract we propose to combine techniques from traditional software configuration management with the concepts of reference modeling, where similar problems are addressed in a different context.
impact analysis for event-based components and systems. in my dissertation, i aim to develop a dependence-based impact analysis technique for event-based systems and event-based components that communicate via messages. this paper motivates the problem, summarizes the open challenges and outlines proposed solution and evaluation strategies.
summarizing software concerns. while working on software concerns to perform evolution tasks, developers often encounter a lack of abstraction. they have to work with all the details of large subsets of code that constitute a concern at a low level of abstraction. in this paper we propose a framework to summarize software concerns in order to raise the level of abstraction and to subsequently improve the productivity of software developers. we use a combination of static analysis, information retrieval, and natural language processing techniques to extract and deduct knowledge about different parts of the concern and its interactions with other concerns. then we produce a description of the concern using natural language generation and summarization techniques.
analysing "people" problems in requirements engineering. the aim of this tutorial is to explain in an accessible manner the psychology of people in the context of misunderstandings, politics and social issues that affect software development. it focuses on user-stakeholder interaction techniques for analysis and interpretation of human behaviour, and how psychological knowledge can be used to improve the requirements engineering (re) process as well as interpreting the implications of human motivations and values for requirements and software systems architecture. soft issues, such as politics and people's feelings, are often cited as problems in the re process and as key causes of system failure. it is clear from the re literature that understanding user beliefs and values is vital for the success of software development. the london ambulance service is a canonical example of system failure caused, in part, by inadequate understanding of ambulance crews' motivations, values of self esteem and autonomy, and the emotional reaction to lack of involvement in the requirements process, leading to technology failure.
dynamic symbolic data structure repair. generic repair of complex data structures is a new and exciting area of research. existing approaches can integrate with good software engineering practices such as program assertions. but in practice there is a wide variety of assertions and not all of them satisfy the style rules imposed by existing repair techniques. i.e., a "badly" written assertion may render generic repair inefficient or ineffective. in this paper we build on the state of the art in generic repair and discuss how generic repair can work effectively with a wider range of correctness conditions. we motivate how dynamic symbolic techniques enable generic repair to support a wider range of correctness conditions and present dsdsr, a novel repair algorithm based on dynamic symbolic execution. we implement the algorithm for java and report initial empirical results to demonstrate the promise of our approach for generic repair.
change impact analysis from business rules. impact analysis is the identification of the potential consequences of a change, or estimating what needs to be modified to accomplish a change, including related costs and schedule estimates. in this work, we distinguish between two kinds of concerns related to impact analysis: (1) business-specific concerns, those related to stakeholders interested in checking if other business rules are impacted by the change and also need to be modified; and (2) software-specific concerns, those related to stakeholders interested in the impacted software artifacts that need to be modified. several traceability techniques have been studied and none of them supported impact analysis that dealt with business-specific concerns with reasonable values of precision and recall for the discovered impacts. our research work aims to support business-specific concerns during impact analysis, by proposing and evaluating a traceability technique that resorts on a new traceability model defined over business rules, with expected precision and recall values of 100%.
combinatorial test design in practice. combinatorial testing is a specification based sampling technique that provides a systematic way to select combinations of program inputs or features for testing. it has been applied over the years to test input data, configurations, web forms, protocols, graphical user interfaces and for testing software product lines. this tutorial introduces the fundamentals of combinatorial testing, including both practical and theoretical foundations, to provide a comprehensive introduction that is relevant to both test practitioners and software engineering researchers. the tutorial will present an overview of combinatorial test design (ctd) and describe some state of the art research advances and domains where ctd has been applied. it will present the theoretical underpinnings of ctd and explain a few algorithmic techniques used to generate ctd samples, as well as describe recent work on practical extensions to these algorithms that allow for a broader use of ctd. a session devoted to modeling test problems using ctd will follow, with attendees obtaining hands-on experience using several realistic problems.
an analysis of the effects of company culture, education and experience on confirmation bias levels of software developers and testers. in this paper, we present a preliminary analysis of factors such as company culture, education and experience, on confirmation bias levels of software developers and testers. confirmation bias is defined as the tendency of people to verify their hypotheses rather than refuting them and thus it has an effect on all software testing.
eliminating dead-code from xquery programs. one of the challenges in web software development is to help achieving a good level of quality in terms of code size and runtime performance, for increasingly popular domain specific languages such as xquery. we present an ide equipped with static analysis features for assisting the programmer. these features are capable of identifying and eliminating dead code automatically. the tool is based on newly developed formal programming language verification techniques [4, 3], which are now mature enough to be introduced in the process of software development.
cost effectiveness analysis in software engineering. the tutorial presented an approach that leverages well-known economic and financial concepts for evaluating the cost effectiveness of software development processes and techniques. software engineering studies often report separately on the costs and benefits of a phenomenon of interest, and rarely adequately address the combined bottom line implications. in particular, tensions between quality and productivity are hard to reconcile, making objective, high-level insights elusive. to address this need, the tutorial focused on quantitative methods for synthesizing co-dependent cost-benefit effects and analyzing the resulting behaviors.
new processes for new horizons: the incremental commitment model. the wide variety of software-intensive systems needed to support the new horizons of evolving technology, system and software complexity, high dependability, global interoperability, emergent requirements, and adaptability to rapid change make traditional and current one-size-fits-all process models infeasible. this tutorial presents the process framework, principles, practices, and case studies for a new model developed and being used to address these challenges. it has a series of risk-driven decision points that enable projects to converge on whatever combination of agile, plan-driven, formal, legacy-oriented, reuse-oriented, or adaptive processes that best fit a project's situation. the tutorial discusses the decision table for common special cases; exit ramps for terminating non-viable projects; support of concurrent engineering of requirements, solutions and plans; and evidence-based commitment milestones for synchronizing the concurrent engineering. the tutorial will include case studies and exercises for participants' practice and discussion.
a research demonstration of code bubbles. today's integrated development environments (ides) are hampered by their dependence on files and file-based editing. we propose a novel user interface that is based on collections of lightweight editable fragments, called bubbles, which when grouped together form concurrently visible working sets. we describe the design of a prototype ide user interface for java based on working sets.
developing and evaluating the code bubbles metaphor. today's integrated development environments (ides) are hampered by their dependence on files and file-based editing. a novel user interface that is based on collections of lightweight editable fragments, called bubbles, which when grouped together form concurrently visible working sets is proposed. an overview of this interface, as well as a summary of the results of a quantitative and a qualitative evaluation of the interface is presented.
can we certify systems for freedom from malware. malicious code is any code that has been modified with the intention of harming its usage or the user. typical categories of malicious code include trojan horses, viruses, worms etc. with the growth in complexity of computing systems, detection of malicious code is becoming horrendously complex. for security of embedded devices it is important to ensure the integrity of software running in it. the general virus detection is undecidable. however, in the case of embedded systems or personal systems, the software and hardware configurations are known a priori. we are experimenting to see whether we can certify such systems for malware freedom. most of the current efforts on malware detection rely heavily on detection of syntactic patterns. malware writers are resorting to simple syntactic transformations (which preserve the program semantics) such as various compiler optimizations and program obfuscation techniques to evade detection. our work is based on semantic behaviour of programs. we are working towards developing a model of the behaviour of a program executing in an environment. our approach to detect tampering is based on benchmarking the behaviour of a program executing in an environment, and then matching the observed behaviour of the program in a similar environment with the benchmark (a la translation validation in a sense or bisimulation that is widely used in model checking). since execution behaviour remains the same in majority of obfuscations, our approach is resilient to such exploits. we have performed several experiments in this direction and obtained encouraging results. differences between the benchmarked behaviour and the observed behaviour quantifies the damage due to a virus. this enables us to arrive at refined notions of "harm" done by a virus and appropriate measures for protection.
analysis of execution log files. log analysis can be used to find problems, define operational profiles, and even pro-actively prevent issues. the goal of my dissertation research is to investigate log management and analysis techniques suited for very large and very complex logs, such as those we might expect in a computational cloud system.
the role of emergent knowledge structures in collaborative software development. many collaboration features in software development tools draw on lightweight technologies such as tagging and wikis. we propose to study the role of emergent knowledge structures created through these features. using a mixed-methods approach, we investigate which processes emergent knowledge structures support and how tool support can leverage them.
providing support for creating next generation software architecture languages. many languages for software architectures have been proposed, each dealing with different stakeholder concerns, operating at different levels of abstraction and with different degrees of formality. it is known that a universal architectural language cannot exist since the various concerns, requirements, and domains may change. moreover, stakeholder concerns and needs are various and ever evolving even while designing a single system. model-driven techniques may be used to answer the need for supporting the creation of extensible, customizable and stakeholder-oriented architectural languages (i.e., next generation architectural languages). part of this approach is developed in a framework called byadl. in this paper i present the big picture behind the approach, the research aspects considered in order to get byadl closer to an ideal architectural framework and future research issues.
flexible architecture conformance assessment with conqat. the architecture of software systems is known to decay if no counter-measures are taken. in order to prevent this architectural erosion, the conformance of the actual system architecture to its intended architecture needs to be assessed and controlled; ideally in a continuous manner. to support this, we present the architecture conformance assessment capabilities of our quality analysis framework conqat. in contrast to other tools, conqat is not limited to the assessment of use-dependencies between software components. its generic architectural model allows the assessment of various types of dependencies found between different kinds of artifacts. it thereby provides the necessary tool-support for flexible architecture conformance assessment in diverse contexts.
software architecture: foundations, theory, and practice. software architecture has become a centerpiece subject for software engineers, both researchers and practitioners alike. at the heart of every software system is its software architecture, i.e., "the set of principal design decisions about the system". architecture permeates all major facets of a software system, for principal design decisions may potentially be made at any time during a system's lifetime, and potentially by any stakeholder. such decisions encompass structural concerns, such as the system's high-level building blocks---components, connectors, and configurations; the system's deployment; the system's non-functional properties; and the system's evolution patterns, including runtime adaptation. software architectures found particularly useful for families of systems---product lines---are often codified into architectural patterns, architectural styles, and reusable, parameterized reference architectures. this tutorial affords the participant an extensive treatment of the field of software architecture, its foundation, principles, and elements, including those mentioned above. additionally, the tutorial introduces the participants to the state-of-the-art as well as the state-of-the-practice in software architecture, and looks at emerging and likely future trends in this field. the discussion is illustrated with numerous real-world examples. one example given prominent treatment is the architecture of the world wide web and its underlying architectural style, representational state transfer (rest).
transparent combination of expert and measurement data for defect prediction: an industrial case study. defining strategies on how to perform quality assurance (qa) and how to control such activities is a challenging task for organizations developing or maintaining software and software-intensive systems. planning and adjusting qa activities could benefit from accurate estimations of the expected defect content of relevant artifacts and the effectiveness of important quality assurance activities. combining expert opinion with commonly available measurement data in a hybrid way promises to overcome the weaknesses of purely data-driven or purely expert-based estimation methods. this article presents a case study of the hybrid estimation method hydeep for estimating defect content and qa effectiveness in the telecommunication domain. the specific focus of this case study is the use of the method for gaining quantitative predictions. this aspect has not been empirically analyzed in previous work. among other things, the results show that for defect content estimation, the method performs significantly better statistically than purely data-based methods, with a relative error of 0.3 on average (mmre).
sesena 2010: workshop on software engineering for sensor network applications. this editorial preface describes the aims and motivation as well as some details of the reviewing process of sesena 2010, the first international workshop on software engineering for sensor network applications, which took place under the umbrella of icse 2010, the 32rd acm/ieee international conference on software engineering, in cape town, south africa, may 2010. see also our workshop's website at http://www.sesena.info/
slicing and dicing bugs in concurrent programs. a lack of scalable verification tools for concurrent programs has not allowed concurrent software development to keep abreast with hardware trends in multi-core technologies. the growing complexity of modern concurrent systems necessitates the use of abstractions in order to verify all the expected behaviors of the system. current abstraction refinement techniques are restricted to verifying mostly sequential and simpler concurrent programs. in this work, we present a novel incremental underapproximation technique that uses program slicing. based on a reachability property, an initial backward slice for a single thread is generated. the information in the program slice is coupled with a concrete execution to drive the lone thread; generating an underapproximation of the program behavior space. if the target location is reached in the underapproximation, then we have an actual concrete trace. otherwise, the initial single-thread slice is refined to include another thread that affects the reachability of the target location. in this case, the concrete execution only considers the two threads in the slice and preemption points between the threads only occur at locations in the slice. this refinement process is repeated until the target location is reached or is shown to be unreachable. initial results indicate that the incremental technique can potentially allow the discovery of errors in larger systems using fewer resources and produce a better reduction in systems that are correct.
can clone detection support quality assessments of requirements specifications? due to their pivotal role in software engineering, considerable effort is spent on the quality assurance of software requirements specifications. as they are mainly described in natural language, relatively few means of automated quality assessment exist. however, we found that clone detection, a technique widely applied to source code, is promising to assess one important quality aspect in an automated way, namely redundancy that stems from copy&paste operations. this paper describes a large-scale case study that applied clone detection to 28 requirements specifications with a total of 8,667 pages. we report on the amount of redundancy found in real-world specifications, discuss its nature as well as its consequences and evaluate in how far existing code clone detection approaches can be applied to assess the quality of requirements specifications in practice.
codesign: a highly extensible collaborative software modeling framework. large, multinational software development organizations face a number of issues in supporting software design and modeling by geographically distributed architects. to address these issues, we present codesign, an extensible, collaborative, event-based software modeling framework developed in a distributed, collaborative setting by our two organizations. codesign's core capabilities include real-time model synchronization between geographically distributed architects, as well as detection and resolution of a range of modeling conflicts via several off-the-shelf conflict detection engines.
umple: a model-oriented programming language. our research tool, umple, has the objective of raising the abstraction level of programming languages by including modeling abstractions such as uml associations, attributes and state machines. my research focuses on the syntax and semantics of state machines in umple and the empirical validation of umple as a whole.
fifth workshop on software engineering for adaptive and self-managing systems (seams 2010). the software engineering for adaptive and self-managing systems (seams) workshop has consolidated the interest in the software engineering community on self-adaptive and self-managing systems. seams provides a forum for researchers and practitioners to share new results, discuss challenging issues, raise awareness, and promote collaboration within the community. the seams 2010 workshop aims to continue the success of previous icse seams workshops: in shanghai in 2006, in minneapolis in 2007, in leipzig in 2008, and in vancouver in 2009.
end-user requirements blogging with irequire. end-user involvement in software engineering is an ambivalent topic. however, novel paradigms such as service-oriented computing suggest more active end-user involvement to gather individual needs for software personalization. in this paper, we present a mobile requirements elicitation tool which enables end-users to blog needs in situ without analysts' facilitation.
engineering safety- and security-related requirements for software-intensive systems: tutorial summary. this full-day tutorial introduces the attendee to the engineering of safety- and security-related requirements for software-intensive systems. it provides a consistent, effective, and efficient method for identifying, analyzing, specifying, verifying, and validating the four different types of safety- and security-related requirements.
enhancing collaboration of multi-developer projects with synchronous changes. in a multi-developer project, team collaboration is essential for the success of the project. when team members are spread across different locations, informal interactions are lost, having an impact on individual awareness of the activity of others. in this scenario, collaboration becomes a challenge. a number of works have tried to reestablish team awareness by sharing change information across developers' workspaces. the main challenge of these approaches is to balance the tradeoff between offering useful information about the activity of others and avoiding information overload. in this work, we address the challenge of enhancing group awareness and stimulating collaboration by providing relevant information to developers in a non-intrusive manner. the novelty of our approach is that we model changes as first-class entities to deliver precise change information to targeted developers.
making program refactoring safer. automated refactorings may change the program behavior. we propose an approach and its implementation called saferefactor for making program refactoring safer. we applied 10 eclipse refactorings in a number of automatically generated programs, and used saferefactor to identify 50 bugs that lead to behavioral changes or compilation errors.
behavioural validation of software engineering artefacts. software engineering artefacts that define behaviour tend to be of a fragmented nature in order to facilitate their construction, modification, and modular reasoning (e.g. modular code, pre/post-conditions specifications). however, fragmentation makes the validation of global behaviour difficult. typically synthesis techniques that yield global representations of large or infinite states are used in combination with simulation or partial explorations, techniques which necessarily lose the global view of system behaviour. i am working on the development of abstraction-for-validation techniques that automatically produce finite state abstractions that are sufficiently small to support validating the emergent behaviour of a fragmented description "at a glance".
a flexible tool suite for change-aware test-driven development of web applications. though web applications development fits well with test-driven development, there are some problems that hinder its success. in this demo we present a tool suite to improve tdd; the suite supports the representation of web requirements using a domain-specific language and the automatic generation of interaction tests among others.
improving throughput via slowdowns. many service-oriented systems are not well equipped to guarantee that service time is optimized. we have specifically examined two industrial systems which implement service-oriented architectures in real, field environments. we discovered that both were not engineered to properly address surges in service request rate. in the absence of an integral solution, it is difficult and costly to (re-) engineer such a solution in the field. the challenge faced by this study was to deliver a low cost solution, without re-engineering the target systems. this paper introduces such a generic solution. the solution slows-down some components to deliver improvement in request service time. it was implemented, tested, and successfully applied to two industrial systems with no need to modify their logic or architecture. experiments with those systems exhibited significant improvement in performance. these results have validated our solution and its industrial applicability across systems and environments.
managing iterations with unicase. planning iterations in software projects requires considering artifacts from different aspects such as requirements, specifications, tasks or even bug reports. unicase is a unified case tool integrating these relevant artifacts into one model. we demonstrate how the tool supports planning and executing iterations.
comprehending module dependencies and sharing. software often lives in a complex software eco-system with complex interactions and dependencies between different modules or components. in windows, this problem is exacerbated both by the overall system complexity and its closed source nature. even when source is available, there are still interactions with modules which are only in binary form. this paper proposes two visualizations for investigating the dependencies between programs and other binaries, such as, dynamically linked libraries on windows. our visualizations are based on run-time traces obtained either from the windows kernel or through binary instrumentation. thus, our techniques do not need to rely on source code. we use the following scenarios to explain how our visualizations can be used to investigate various aspects of software dependencies: (i) visualizing whole system software dependencies; (ii) visualizing the interactions between selected modules of some software; (iii) discovering unexpected module interactions; and (iv) understanding the source of the modules being used.
rsse 2010: second international workshop on recommendation systems for software engineering. the goal of this one-day workshop is to bring together researchers and practitioners with interest and experience in the theory, elaboration, and evaluation of concepts, techniques, and tools for providing recommendations to developers, managers, and other stakeholders involved in software engineering tasks.
test-driven roles for pair programming. pair programming is the practice of having two programmers work together on the same code in a single development environment. the goals of pair programming are to improve communication and the sharing of knowledge within a team; to increase productivity; to improve developer process and help team members stay productive; and ultimately to strengthen the quality of the resulting software [1].
assessments in global software development: a tailorable framework for industrial projects. assessments are an effective technique for software quality assurance. as global software development (gsd) becomes the standard, an assessment framework must be flexible to support different sourcing and shoring models. although much work exists on inspections and reviews, an assessment framework which addresses these challenges is missing. we present a systematic yet flexible assessment framework. the paper contributes: i) the description of our assessment framework which addresses four challenges: appropriateness of a software requirements specification (srs), viability of software architectures and srs, wholeness of work packages, and compliance of results with predefined quality objectives. ii) a detailed explanation how the assessment framework can be tailored to support offshore and outsourcing scenarios. this paper describes the result of a two years research initiative at capgemini sd&m and serves the practitioner to implement assessment frameworks according to his needs. we also discuss open research questions of high relevance for the software industry.
a methodology to support load test analysis. performance analysts rely heavily on load testing to measure the performance of their applications under a given load. during the load test, analyst strictly monitor and record thousands of performance counters to measure the run time system properties such as cpu utilization, disk i/o, memory consumption, network traffic etc. the most frustrating problem faced by analysts is the time spent and complexity involved in analysing these huge counter logs and finding relevant information distributed across thousands of counters. we present our methodology to help analysts by automatically identifying important performance counters for load test and comparing them across tests to find performance gain/loss. further, our methodology help analysts to understand the root cause of a load test failure by finding previously solved problems in test repositories. a case study on load test data of a large enterprise application shows that our methodology can effectively guide performance analysts to identify and compare top performance counters across tests in limited time thereby archiving 88% counter data reduction.
software engineering abstractions for the multi-touch revolution. multi-touch interfaces allow users to use multiple fingers to provide input to a graphical user interface. the idea of allowing users to touch and manipulate digital information with their hands has been subject of research for more than 25 years [5, 4]. recently several of these research artifacts have found their way to industry, with examples like the iphone and the microsoft surface. mainstream programming languages do not offer support to deal with the complexity of these new devices. unlike the evolution in the hardware technology, the complexity of these new devices has not yet been addressed by adequate software engineering abstractions.
social computing networks: a new paradigm for engineering self-adaptive pervasive software systems. software systems are increasingly permeating a variety of domains including medical, industrial automation, and emergency response. the advances in portable and embedded computing devices and the recent advances in wireless network connectivity have paved the way for the proliferation of smart spaces in such domains. at the same time, the emergence of service-oriented technology (e.g., web services [10]) and interoperability standards (e.g., wsdl [11], uddi [5]) has made it possible to develop pervasive software systems intended for execution in smart spaces that were not even conceivable a few years back.
a role-based qualification and certification program for software architects: an experience report from siemens. in this experience report, we describe the motivation, experience, lessons learned, and future directions of a software engineering curriculum used at a large international company. the "curriculum for software engineers" project, which developed the content and a role-based qualification and certification program, was started at siemens in 2006. this paper includes an overview of various kinds of certification in the software engineering area and why we chose the knowledge- and experience-based type of certification. the experience report part focuses mainly on the "certified senior software architect" role, as this role has the longest history and participants from many different business units and countries.
making defect-finding tools work for you. given the high costs of software testing and fixing bugs after release, early detection of bugs using static analysis can result in significant savings. however, despite their many benefits, recent availability of many such tools, and evidence of a positive return-on-investment, static-analysis tools are not used widely because of various usability and usefulness problems. the usability inhibitors include the lack of features, such as capabilities to merge reports from multiple tools and view warning deltas between two builds of a system. the usefulness problems are related primarily to the accuracy of the tools: identification of false positives (or, spurious bugs) and uninteresting bugs among the true positives. in this paper, we present the details of an online portal, developed at ibm research, to address these problems and promote the adoption of static-analysis tools. we report our experience with the deployment of the portal within the ibm developer community. we also highlight the problems that we have learned are important to address, and present our approach toward solving some of those problems.
predicting build outcome with developer interaction in jazz. investigating the human aspect of software development is becoming prominent in current research. studies found that the misalignment between the social and technical dimensions of software work leads to losses in developer productivity and defects. we use the technical and social dependencies among pairs of developers to predict the success of a software build. using the ibm jazz&trade; data we found information about developers and their social and technical relation can build a powerful predictor for the success of a software build. investigating human aspects of software development is becoming prominent in current research. high misalignment between the social and technical dimensions of software work lowers productivity and quality.
mining software engineering data. software engineering data (such as code bases, execution traces, historical code changes, mailing lists, and bug databases) contains a wealth of information about a project's status, progress, and evolution. using well-established data mining techniques, practitioners and researchers have started exploring the potential of this valuable data in order to better manage their projects and to produce higher quality software systems that are delivered on time and within budget. this tutorial presents the latest research in mining software engineering data, discusses challenges associated with mining software engineering data, highlights success stories of mining software engineering data, and outlines future research directions. attendees will acquire the knowledge and skills needed to integrate the mining of software engineering data in their own research or practice. this tutorial builds on several successful offerings at icse since 2007.
towards better support for the evolution of safety requirements via the model monitoring approach. the research is motivated by the challenge from the evolution of safety requirements, which leads to revision of system designs at design-time or post-implementation at a high cost. this paper proposes a complementary methodology, namely the model monitoring approach, to better support the evolution throughout the life-cycle at a lower cost.
choreography of intelligent e-services. electronic services (e-services), referred to as a set of automated enterprise services using ict to achieve a business goal, have significantly contributed to the growth of e-commerce, science, and telecommunications. however, applications that use e-services seldom interoperate effectively, and this restricts the benefits they offer. the main purpose of e-services is to have an anthology of network-resident software services accessed via standardised protocols whose meaning can be regularly discovered and integrated into applications. our study supplements the definition provided for e-service by complementing it with an intelligent capability for the purpose of effective and efficient choreography of processes, hence the term "intelligent e-services". the aim of the study is to propose the composition of intelligent e-services in a manner which encourages the interoperability of a range of services pertaining to various autonomous virtual enterprises (ves). it is expected that a framework that defines and supports the composition of intelligent e-services will be formed. it is also anticipated that the study will play an important role in contributing to the formation of dynamic virtual enterprises (dves) as an application business scenario.
adinda: a knowledgeable, browser-based ide. in practice, many people have to work together to develop and maintain a software system. however, the programmer's key tool, the integrated development environment (ide), is a solo-tool, serving to help individual programmers understand and modify the system. such an ide does not leverage the knowledge other team members may have of the design and implementation of the system. we propose to resolve this problem by exploring, experimentally, new ways of inferring knowledge from past ide-interactions, and of maximizing collaboration among developers. our approach, called adinda, revolves around transforming the ide into a set of integrated services, accessible via a web browser, and enriched with web 2.0 technologies. such services will not only help developers perform traditional ide tasks, but also facilitate the required informal communication and collaboration needs of software development projects. in this paper, we report on our vision, approach and challenges for building adinda, and initial results.
stakesource: harnessing the power of crowdsourcing and social networks in stakeholder analysis. projects often fail because they overlook stakeholders. unfortunately, existing stakeholder analysis tools only capture stakeholders' information, relying on experts to manually identify them. stakesource is a web-based tool that automates stakeholder analysis. it "crowdsources" the stakeholders themselves for recommendations about other stakeholders and aggregates their answers using social network analysis.
syde: a tool for collaborative software development. team collaboration is essential for the success of multi-developer projects. when team members are spread across different locations, individual awareness of the activity of others drops due to communication barriers. we built syde, a tool infrastructure to reestablish team awareness by sharing change and conflict information across developer's workspaces. our main challenge is to balance the tradeoff between offering relevant information about the activity of the team and avoiding information overload. the novelty of our approach is that we model source code changes as first-class entities to record the detailed evolution of a multi-developer project. hence, syde delivers precise change information to interested developers.
formalization and validation of a subset of the european train control system. the european train control system (etcs) is a control system for the interoperability of the railways across europe. in this paper, we report on the activities of the eurailcheck project, promoted by the european railway agency, for the development of a methodology and tools for the formalization and validation of the etcs specifications. within the project, we achieved three main results. first, we developed a methodology for the formalization and validation of the etcs specifications. the methodology is based on a three-phases approach that goes from the informal analysis of the requirements, to their formalization and validation. second, we developed a set of support tools, covering the various phases of the methodology. third, we formalized a realistic subset of the specification in an industrial setting. the results of the project were positively evaluated by domain experts from different manufacturing and railway companies.
multicore software engineering: the next challenge in software engineering. due to stagnating clock rates, future increases in processor performance will have to come from parallelism. inexpensive multicore processors with several cores on a chip have become standard in pcs, laptops, servers, and embedded devices will follow; manycore chips with hundreds of processors on a single chip are predicted. software engineers are now asked to write parallel applications of all sorts, and need to quickly grasp the relevant aspects of general-purpose parallel programming. this tutorial at icse 2010 prepares them for this challenge.
cooperative and human aspects of software engineering (chase 2010). software is created by people---software engineers---working in varied environments, under various conditions. thus understanding cooperative and human aspect of software development is crucial to comprehend how methods and tools are used, and thereby improving the creation and maintenance of software. inspired by the hosting country's concept of co-responsibility -- ubuntu -- we especially invited contributions that address community-based development like open source development and sustainability of ict eco-systems. the goal of this workshop is to provide a forum for discussing high quality research on human and cooperative aspects of software engineering. we aim at providing both a meeting place for the growing community and the possibility for researchers interested in joining the field to present their work in progress and get an overview over the field.
the small project observatory: a tool for reverse engineering software ecosystems. software evolution researchers have focused mostly on analyzing single software systems. however, often projects are developed and co-exist within software ecosystems, i.e., the larger contexts of companies, research groups or open-source communities. we present the small project observatory, a web-based analysis platform for ecosystem reverse engineering through interactive visualization and exploration.
legacy component integration by the fujaba real-time tool suite. we present a tool suite which supports the (re-)construction of a behavioral model of a legacy component based on a learning approach by exploiting knowledge of known models of the existing component environment. this in turn enables to check whether the legacy component can be integrated correctly into its environment.
balancing collaboration and discipline in software development processes. neither traditional, agile or free/open software development models can be effective to all projects contexts. we claim that collaboration and discipline can be the driver to tailor software development processes to meet projects and organizations needs. this work proposes that process tailoring can be conducted through a context management approach.
commit 2.0: enriching commit comments with visualization. software developers use commit comments to document changes and as a mean of communication in their team. however, the support given by ides is restricted with this respect, as they limit the users to use only text to document changes. in this paper we propose and implement an approach to enrich commit comments with software visualization: commit 2.0 generates visualizations of the performed changes at different granularity levels, and let the user enrich them with annotations.
qed: a proof system based on reduction and abstraction for the static verification of concurrent software. we present a proof system and supporting tool, qed, for the static verification of concurrent software. our key idea is to simplify the verification of a program by rewriting it with larger atomic actions. we demonstrated the simplicity and effectiveness of our approach on benchmarks with intricate synchronization.
capturing the long-term impact of changes. developers change source code to add new functionality, fix bugs, or refactor their code. many of these changes have immediate impact on quality or stability. however, some impact of changes may become evident only in the long term. the goal of this thesis is to explore the long-term impact of changes by detecting dependencies between code changes and by measuring their influence on software quality, software maintainability, and development effort. being able to identify the changes with the greatest long-term impact will strengthen our understanding of a project's history and thus shape future code changes and decisions.
automatic enforcement of architectural design rules. current techniques for modeling software architecture lacks support for the modeling of architectural design rules, i.e. rules defined by the architect that have to be followed in the detailed design. this is a problem in the context of model-driven development in which it is assumed that major design artifacts are represented as formal or semi-formal models. the phd project presented in this paper addresses this problem by the definition of a method for modeling architectural design rules in a form that is easily interpreted by developers. a tool for automatic validation of the design model against the architectural rules has also been developed. the method is designed to be easy to learn and use for both architects and developers. as a part of the phd project the method is also currently validated in a case study on an industrial development project.
empirical evaluation of effort on composing design models. the importance of model composition in model-centric software development is recognized by researchers and practitioners. however, the lack of empirical evidence about the impact of model composition techniques on developers' effort is a key impairment for their adoption in real-world design settings. software engineers are left without any guidance on how to properly use certain model techniques in a way that effectively reduces their development effort. this work aims to address this problem by: (1) providing empirical evidence on model composition effort through a family of experimental studies; (2) defining quantitative indicators to objectively assess key attributes of model composition effort; (3) deriving a method to support the systematic application of composition techniques; and (4) conceiving a new model composition technique to overcome the problems identified throughout the experimental evaluations.
risk assessment on distributed software projects. risk assessment is a growing discipline on the context of distributed software projects. the complexity to develop software and the related knowledge require automated support for project managers in order to analyze actions to reduce the project's risks and measure the impact of such actions. my thesis aims to investigate an approach for the assessment of risks in globally distributed software projects. this research proposes to apply stochastic simulation technique to analyze project data and identify factors that are likely to impact team productivity and that could affect the team's ability to meet its schedule objective. we aim this thesis to be applied by project management groups to perform risk assessment early in the software development process and to help decision-making process.
helios: impact analysis for event-based components and systems. the event-based software architectural style [4] is widely used in the domain of user-interface software and wide-area applications (e.g., financial markets, logistics, and sensor networks). a gartner study determined that the market size for message-oriented (a.k.a event-based) middleware licenses was about $1 billion in 2005 [2]. in event-based systems, components do not directly call other components, but rather indirectly using messages or events. however, this high decoupling and use of implicit invocations render an event-based system more difficult to analyze since, in the absence of explicit dependency information, an engineer has to assume that any component in the system may potentially interact with, and thus depend on, any other component.
knowledge transfer in global software development: leveraging acceptance test case specifications. effective knowledge transfer (kt) is always important in software development projects, but crucial in global software development (gsd). two challenges arise: first, reviews of the software requirements specification (srs) are indispensable, but not always effective. second, using knowledge representations that support kt from customers to developers is paramount. however, 'classical' srs often don't support srs comprehension of all stakeholders. we address these two challenges with a new approach that exploits the multi-fold power of a acceptance test case specifications (atc-specs): 1) a specific two-stage test-based review technique is used. we argue that these two-stage reviews of atc-specs increase the quality of the atc-specs and the srs. 2) additionally to the srs, atc-specs are delivered to the offshore team, bridging the mental models of different stakeholders, and thus effectively transferring knowledge. we provide preliminary evidence of the validity of our approach based on a commercial gsd project at capgemini sd&m.
using dynamic execution traces and program invariants to enhance behavioral model inference. software behavioral models have proven useful for design, validation, verification, and maintenance. however, existing approaches for deriving such models sometimes overgeneralize what behavior is legal. we outline a novel approach that utilizes inferred likely program invariants and method invocation sequences to obtain an object-level model that describes legal execution sequences. the key insight is using program invariants to identify similar states in the sequences. we exemplify how our approach improves upon certain aspects of the state-of-the-art fsa-inference techniques.
zenet: generating and enforcing real-time temporal invariants. generating correct specifications for real-time event-driven software systems is difficult and time-consuming. even when such specifications have been created, they are often used to guide development rather than state properties guaranteed by the actual system. we propose a specification generator that reads execution traces and can generate invariants with real-time constraints. that specification can also offer programmers the ability to repair violated invariants at runtime. creating fault-tolerant systems in this manner would provide software engineers guarantees about the software's high-level operation and its ability to recover from errors.
integrating legacy systems with mde. integrating several legacy software systems together is commonly performed with multiple applications of the adapter design pattern in oo languages such as java. the integration is based on specifying bi-directional translations between pairs of apis from different systems. yet, manual development of wrappers to implement these translations is tedious, expensive and error-prone. in this paper, we explore how models, aspects and generative techniques can be used in conjunction to alleviate the implementation of multiple wrappers. briefly the steps are, (1) the automatic reverse engineering of relevant concepts in apis to high-level models; (2) the manual definition of mapping relationships between concepts in different models of apis using an ad-hoc dsl; (3) the automatic generation of wrappers from these mapping specifications using aop. this approach is weighted against manual development of wrappers using an industrial case study. criteria are the relative code length and the increase of automation.
new horizons in multicore software engineering. this paper provides a summary of the third international workshop on multicore software engineering (iwmse 2010). motivated by multicore and manycore processors that are available on every desktop, software engineers need to exploit parallelism to make applications run faster. at the same time, programmers are facing many challenges due to the complexity of parallel programming. the workshop brought together researchers and practitioners to advance the state-of-the-art in software engineering for multicore and manycore systems. the contributions covered topics ranging from programming models, performance engineering, parallel patterns, fault-tolerance, to testing.
parameterized unit testing: theory and practice. unit testing has been widely recognized as an important and valuable means of improving software reliability, as it exposes bugs early in the software development life cycle. however, manual unit testing is often tedious and insufficient. testing tools can be used to enable economical use of resources by reducing manual effort. recently parameterized unit testing has emerged as a very promising and effective methodology to allow the separation of two testing concerns or tasks: the specification of external, black-box behavior (i.e., assertions or specifications) by developers and the generation and selection of internal, white-box test inputs (i.e., high-code-covering test inputs) by tools. a parameterized unit test (put) is simply a test method that takes parameters, calls the code under test, and states assertions. puts have been supported by various testing frameworks. various open source and industrial testing tools also exist to generate test inputs for puts. this tutorial presents latest research on principles and techniques, as well as practical considerations to apply parameterized unit testing on real-world programs, highlighting success stories, research and education achievements, and future research directions in developer testing. the tutorial will help improve developer skills and knowledge for writing puts and give overview of tool automation in supporting puts. attendees will acquire the skills and knowledge needed to perform research or conduct practice in the field of developer testing and to integrate developer testing techniques in their own research, practice, and education.
informal software design knowledge reuse. in this paper, i describe a novel approach for developing and evaluating an infrastructure for supporting informal knowledge capture, representation, and reuse during software design meetings. it is the goal of this work to address the challenges that exist in reusing knowledge while at the whiteboard. the research centers on the design and evaluation of designminders, a tool that augments electronic whiteboards to support the capture and exploration of knowledge using electronic note cards, which can be used over time to preserve knowledge generated during past sessions. the tool will be analyzed in an evaluation that will compare designs produced by two teams, one using designminders and one not.
2010 icse 2nd international workshop on principles of engineering service-oriented systems (pesos 2010). service-oriented systems have attracted great interest from industry and research communities worldwide. service integrators, developers, and providers are collaborating to address the various challenges in the field. pesos 2010 is a forum for all these communities to present and discuss a wide range of topics related to service-oriented systems. the goal of pesos was to bring together researchers from academia and industry, as well as practitioners working in the areas of software engineering and service-oriented systems to discuss research challenges, recent developments, novel applications, as well as methods, techniques, experiences, and tools to support the engineering and use of service-oriented systems.
software engineering in south africa. the tourist slogan used to market south africa a world in one country cuts across many more dimensions than just those of interest to tourists. everywhere in the country, there is evidence of both a highly advanced and sophisticated economy and lifestyle, as well as of poverty and underdevelopment. the purpose of this session is to reflect on whether and how this peculiar positioning of the country impacts on the it industry in general, and on software engineering in particular. based on their experience of south african it in general, and on the practice, teaching and research of software engineering in particular, session panelists will give their perspectives on what is being done and on what should be done. are the challenges and opportunities significantly different from elsewhere? are there the opportunities, threats and challenges for disseminating it skills into the underdeveloped contexts in south africa and africa? what does south africa need to do to become the outsourcing point of choice for north atlantic it? how do companies that operate both in south africa and elsewhere spread the development load, and what are the challenges in doing this?
lsdiff: a program differencing tool to identify systematic structural differences. program differencing tools such as gnu diff identify individual differences but do not determine how those differences are related to each other. for example, an extract superclass refactoring on several subclasses will be represented by diff as a scattered collection of line additions and deletions which must be manually pieced together. in our previous work, we developed lsdiff, a novel program differencing technique that automatically identifies systematic structural differences as logic rules. this paper presents an lsdiff eclipse plug-in that provides a summary of systematic structural differences along with textual differences within an eclipse integrated development environment. this plugin provides several additional features to allow developers to interpret lsdiff rules easily, to select the abstraction level of program differencing analysis, and to reduce its running time through incremental program analysis.
storm: static unit checking of concurrent programs. concurrency is inherent in today's software. unexpected interactions between concurrently executing threads often cause subtle bugs in concurrent programs. such bugs are hard to discover using traditional testing techniques since they require executing a program on a particular unit test (i.e. input) through a particular thread interleaving. a promising solution to this problem is static program analysis since it can simultaneously check a concurrent program on all inputs as well as through all possible thread interleavings. this paper describes a scalable, automatic, and precise approach to static unit checking of concurrent programs implemented in a tool called storm. storm has been applied on a number of real-world windows device drivers, and the tool found a previously undiscovered concurrency bug in a driver from microsoft's driver development kit.
code canvas: zooming towards better development environments. the user interfaces of today's development environments have a "bento box" design that partitions information into separate areas. this design makes it difficult to stay oriented in the open documents and to synthesize information shown in different areas. code canvas takes a new approach by providing an infinite zoomable surface for software development. a canvas both houses editable forms of all of a project's documents and allows multiple layers of visualization over those documents. by uniting the content of a project and information about it onto a single surface, code canvas is designed to leverage spatial memory to keep developers oriented and to make it easy to synthesize information.
an incremental methodology for quantitative software architecture evaluation with probabilistic models. probabilistic models are crucial in the quantification of non-functional attributes in safety-and mission-critical software systems. these models are often re-evaluated in assessing the design decisions. evaluation of such models is computationally expensive and exhibits exponential complexity with the problem size. this research aims at constructing an incremental quality evaluation framework and delta evaluation scheme to address this issue. the proposed technique will provide a computational advantage for the probabilistic quality evaluations enabling their use in automated design space exploration by architecture optimization algorithms. the expected research outcomes are to be validated with a range of realistic architectures and case studies from automotive industry.
synthesized essence: what game jams teach about prototyping of new software products. the development of video games comprises engineering teams within various disciplines, e.g., software engineering, game production, and creative arts. game jams are a promising approach for (software+) development projects to foster on new product development. this paper evaluates the concept of game jam, a community design/development activity, and its positive effects on new software product development with tight schedules in time-oriented, competitive environments. game jams have received more public attention in recent times, but the concept itself has not been formally discussed so far. a game jam is a composition of design and development strategies: new product development, participatory design, lightweight construction, rapid experience prototyping, product-value focusing, aesthetics and technology, concurrent development and multidisciplinarity. although game jams are normally used for rapid prototyping of small computer games, the constellation of the mentioned elements provides a powerful technique for rapidly prototyping new product ideas and disruptive innovations.
refresh: weak privacy model for rfid systems. privacy-preserving authentication (ppa) is crucial for radio frequency identifcation (rfid)-enabled applications. without appropriate formal privacy models, it is difficult for existing ppa schemes to explicitly prove their privacy. even worse, rfid systems cannot discover potential security flaws that are vulnerable to new attacking patterns. recently, researchers propose a formal model, termed as strong privacy, which strictly requires tags randomly generate their output. adopting the strong privacy model, ppa schemes have to employ brute-force search in tags' authentications, which incurs unacceptable overhead and delay to large-scale rfid systems. instead of adopting strong privacy, most ppa schemes improve the authentication efficiency at the cost of the privacy degradation. due to the lack of proper formal models, it cannot be theoretically proven that the degraded ppa schemes can achieve acceptable privacy in practical rfid systems. to address these issues, we propose a weak privacy model, refresh, for designing ppa schemes with high efficiency as well as acceptable privacy. based on refresh, we show that many well-known ppa schemes do not provide satisfied privacy protection, even though they achieve relatively high authentication efficiency. we further propose a light-weight privacy-preserving authentication scheme, last, which can guarantee the privacy based on the refresh model and realize o(1) authentication efficiency, simultaneously.
topbt: a topology-aware and infrastructure-independent bittorrent client. bittorrent (bt) has carried out a significant and continuously increasing portion of internet traffic. while several designs have been recently proposed and implemented to improve the resource utilization by bridging the application layer (overlay) and the network layer (underlay), these designs are largely dependent on internet infrastructures, such as isps and cdns. in addition, they also demand large-scale deployments of their systems to work effectively. consequently, they require multiefforts far beyond individual users' ability to be widely used in the internet. in this paper, aiming at building an infrastructure-independent user-level facility, we present our design, implementation, and evaluation of a topology-aware bt system, called topbt, to significantly improve the overall internet resource utilization without degrading user downloading performance. the unique feature of topbt client lies in that a topbt client actively discovers network proximities (to connected peers), and uses both proximities and transmission rates to maintain fast downloading while reducing the transmitting distance of the bt traffic and thus the internet traffic. as a result, a topbt client neither requires feeds from major internet infrastructures, such as isps or cdns, nor requires large-scale deployment of other topbt clients on the internet to work effectively. we have implemented topbt based on widely used open-source bt client code base, and made the software publicly available. by deploying topbt and other bittorrent clients on hundreds of internet hosts, we show that on average topbt can reduce about 25% download traffic while achieving a 15% faster download speed compared to several prevalent bt clients. topbt has been widely used in the internet by many users all over the world.
energy efficient algorithms for the rfid estimation problem. rfid has been gaining popularity for inventory control, object tracking, and supply chain management in warehouses, retail stores, hospitals, etc. periodically and automatically estimating the number of rfid tags deployed in a large area has many important applications in inventory management and theft detection. the prior work focuses on designing time-efficient algorithms that can estimate tens of thousands of tags in seconds. we observe that, for a rfid reader to access tags in a large area, active tags are likely to be used. these tags are batterypowered and use their own energy for information transmission. however, recharging batteries for tens of thousands of tags is laborious. unlike the prior work, this paper studies the rfid estimation problem from the energy angle. our goal is to reduce the amount of energy that is consumed by the tags during the estimation procedure. we design several energy-efficient probabilistic algorithms that iteratively refine a control parameter to optimize the information carried in the transmissions from the tags, such that both the number and the size of the transmissions are minimized.
capacity of data collection in arbitrary wireless sensor networks. how to efficiently collect sensing data from all sensor nodes is critical to the performance of wireless sensor networks. in this paper, we aim to understand the theoretical limitations of data collection in terms of possible and achievable maximum capacity. previously, the study of data collection capacity [1]-[6] has only concentrated on large-scale random networks. however, in most of practical sensor applications, the sensor network is not deployed uniformly and the number of sensors may not be as huge as in theory. therefore, it is necessary to study the capacity of data collection in an arbitrary network. in this paper, we derive the upper and constructive lower bounds for data collection capacity in arbitrary networks. the proposed data collection method can lead to order-optimal performance for any arbitrary sensor networks. we also examine the design of data collection under a general graph model and discuss performance implications.
how do superpeer networks emerge? in this paper, we develop an analytical framework which explains the emergence of superpeer networks on execution of the commercial peer-to-peer bootstrapping protocols by incoming nodes. bootstrapping protocols exploit physical properties of the online peers like resource content, processing power, storage space, connectivity etc as well as take the finiteness of bandwidth of each online peer into consideration. with the help of rate equations, we show that execution of these protocols results in the emergence of superpeer nodes in the network - the exact degree distribution is evaluated. we validate the framework developed in this paper through extensive simulation. the analysis of the results shows that the amount of superpeers produced in the network depends on the protocol as well as the properties of the joining nodes. interestingly, our analysis reveals that increase in the amount of resource and the number of resourceful nodes do not always help to increase the fraction of superpeer nodes in the network. the impact of the frequent leaving of the peers on the topology of the emerging network is also evaluated. as an application study, we show that our framework can explain the topological configuration of commercial gnutella networks. the developed model can almost perfectly match the degree distribution of gnutella network.
toward the practical use of network tomography for internet topology discovery. accurate and timely identification of the routerlevel topology of the internet is one of the major unresolved problems in internet research. topology recovery via tomographic inference is potentially an attractive complement to standard methods that use ttl-limited probes. in this paper, we describe new techniques that aim toward the practical use of tomographic inference for accurate router-level topology measurement. specifically, prior tomographic techniques have required an infeasible number of probes for accurate, large scale topology recovery. we introduce a depth-first search (dfs) ordering algorithm that clusters end host probe targets based on shared infrastructure, and enables the logical tree topology of the network to be recovered accurately and efficiently. we evaluate the capabilities of our dfs ordering topology recovery algorithm in simulation and find that our method uses 94% fewer probes than exhaustive methods and 50% fewer than the current state-of-the-art. we also present results from a case study in the live internet where we show that dfs ordering can recover the logical router-level topology more accurately and with fewer probes than prior techniques.
scalable nids via negative pattern matching and exclusive pattern matching. in this paper, we identify the unique challenges in deploying parallelism on tcam-based pattern matching for network intrusion detection systems (nidses). we resolve two critical issues when designing scalable parallelism specifically for pattern matching modules: 1) how to enable fine-grained parallelism in pursuit of effective load balancing and desirable speedup simultaneously; and 2) how to reconcile the tension between parallel processing speedup and prohibitive tcam power consumption. to this end, we first propose the novel concept of negative pattern matching to partition flows, by which the number of tcam lookups can be significantly reduced, and the resulting (fine-grained) flow segments can be inspected in parallel without incurring false negatives. then we propose the notion of exclusive pattern matching to divide the entire pattern set into multiple subsets which can later be matched against selectively and independently without affecting the correctness. we show that exclusive pattern matching enables the adoption of smaller and faster tcam blocks and improves both the pattern matching speed and scalability. finally, our theoretical and experimental results validate that the above two concepts are inherently complementary, enabling our integrated scheme to provide performance gain in any scenario (with either clean or dirty traffic).
password strength: an empirical analysis. it is a well known fact that user-chosen passwords are somewhat predictable: by using tools such as dictionaries or probabilistic models, attackers and password recovery tools can drastically reduce the number of attempts needed to guess a password. quite surprisingly, however, existing literature does not provide a satisfying answer to the following question: given a number of guesses, what is the probability that a state-of-the-art attacker will be able to break a password? to answer the former question, we compare and evaluate the effectiveness of currently known attacks using various datasets of known passwords. we find that a "diminishing returns" principle applies: in the absence of an enforced password strength policy, weak passwords are common; on the other hand, as the attack goes on, the probability that a guess will succeed decreases by orders of magnitude. even extremely powerful attackers won't be able to guess a substantial percentage of the passwords. the result of this work will help in evaluating the security of authentication means based on user-chosen passwords, and our methodology for estimating password strength can be used as a basis for creating more effective proactive password checkers for users and security auditing tools for administrators.
cross-layer optimization for wireless networks with deterministic channel models. existing work on cross-layer optimization for wireless networks adopts simple physical-layer models, i.e., treating interference as noise. in this paper, we adopt a deterministic channel model proposed in [11, 12], a simple abstraction of the physical layer that effectively captures the effect of channel strength, broadcast and superposition in wireless channels. within the network utility maximization (num) framework, we study the cross-layer optimization for wireless networks based on this deterministic channel model. first, we extend the well-applied conflict graph model to capture the flow interactions over the deterministic channels and characterize the feasible rate region. then we study distributed algorithms for general wireless multi-hop networks. the convergence of algorithms is proved by lyapunov stability theorem and stochastic approximation method. further, we show the convergence to the bounded neighborhood of optimal solutions with probability one under constant steps and constant update intervals. our numerical evaluation validates the analytical results.
analyzing nonblocking switching networks using linear programming (duality). the main task in analyzing a switching network design (including circuit-, multirate-, and photonic-switching) is to determine the minimum number of some switching components so that the design is non-blocking in some sense (e.g., strictor wide-sense). we show that, in many cases, this task can be accomplished with a simple two-step strategy: (1) formulate a linear program whose optimum value is a bound for the minimum number we are seeking, and (2) specify a solution to the dual program, whose objective value by weak duality immediately yields a sufficient condition for the design to be non-blocking. we illustrate this technique through a variety of examples, ranging from circuit to multirate to photonic switching, from unicast to f-cast and multicast, and from strict- to wide-sense non-blocking. the switching architectures in the examples are of clos-type and banyan-type, which are the two most popular architectural choices for designing non-blocking switching networks. to prove the result in the multirate clos network case, we formulate a new problem called dynamic weighted edge coloring which generalizes the dynamic bin packing problem. we then design an algorithm with competitive ratio 5.6355 for the problem. the algorithm is analyzed using the linear programming technique. we also show that no algorithm can have competitive ratio better than 4 - o(log n/n) for this problem. new lower- and upper-bounds for multirate wide-sense non-blocking clos networks follow, improving upon a couple of 10-year-old bounds on the same problem.
from theory to practice: evaluating static channel assignments on a wireless mesh network. multi-radio nodes in wireless mesh networks introduce extra complexity in utilizing channel resources. depending on the configuration of the radios, bad mappings between radio to wireless frequencies may result in sub-optimal network topologies. static channel assignments in wireless mesh networks have been studied in theory and through simulation but very little work has been done through experiments. this paper focuses on evaluating static channel assignments on a live wireless mesh network. we chose three popular types of static channel assignment algorithms for implementation and comparison purposes. the three types are breadth-first search, priority-based selection and integer linear programming. we find that there is no single channel assignment algorithm that does well overall. bfs algorithm can create the shortest paths to the gateway and also generate balanced channel usage topologies. the pbs algorithm can use all the best links in the network but have poor performance from each radio to the gateway. overall, we find the channel assignments given by the algorithms to be suboptimal when applied to a live mesh network because temporal variations in the link quality metrics are not taken into account. looking at the interflow and intraflow performance of these channel assignment algorithms in a live mesh network, we can conclude that routing protocols must be modified to take advantage of the underlying channel assignment algorithms.
on scheduling for minimizing end-to-end buffer usage over multihop wireless networks. while there has been much progress in designing backpressure based stabilizing algorithms for multihop wireless networks, end-to-end performance (e.g., end-to-end buffer usage) results have not been as forthcoming. in this paper, we study the end-to-end buffer usage (sum of buffer utilization along a flow path) over a network with general topology and with fixed, loopfree routes using a large-deviations approach. we first derive bounds on the best performance that any scheduling algorithm can achieve. based on the intuition from the bounds, we propose a class of (backpressure-like) scheduling algorithms called αβ-algorithms. we show that the parameters α and β can be chosen such that the system under the αβ-algorithm performs arbitrarily closely to the best possible scheduler (formally the decay rate function for end-to-end buffer overflow is shown to be arbitrarily close to optimal in the large-buffer regime). we also develop variants which have the same asymptotic optimality property, and also provide good performance in the small-buffer regime. our results are substantiated using both analysis and simulation.
group device pairing based secure sensor association and key management for body area networks. body area networks (ban) is a key enabling technology in e-healthcare such as remote health monitoring. an important security issue during bootstrap phase of the ban is to securely associate a group of sensor nodes to a patient, and generate necessary secret keys to protect the subsequent wireless communications. due to the the ad hoc nature of the ban and the extreme resource constraints of sensor devices, providing secure, fast, efficient and user-friendly secure sensor association is a challenging task. in this paper, we propose a lightweight scheme for secure sensor association and key management in ban. a group of sensor nodes, having no prior shared secrets before they meet, establish initial trust through group device pairing (gdp), which is an authenticated group key agreement protocol where the legitimacy of each member node can be visually verified by a human. various kinds of secret keys can be generated on demand after deployment. the gdp supports batch deployment of sensor nodes to save setup time, does not rely on any additional hardware devices, and is mostly based on symmetric key cryptography, while allowing batch node addition and revocation. we implemented gdp on a sensor network testbed and evaluated its performance. experimental results show that that gdp indeed achieves the expected design goals.
cooperative bridges: topology control in cooperative wireless ad hoc networks. cooperative communication (cc) is a technology that allows multiple nodes to simultaneously transmit the same data. it can save power and extend transmission coverage. however, prior research work on topology control considers cc only in the aspect of energy saving, not that of coverage extension. we identify the challenges in the development of a centralized topology control scheme, named cooperative bridges, which reduces transmission power of nodes as well as increases network connectivity. we observe that cc can bridge (link) disconnected networks. we propose two algorithms that select the most energy efficient neighbor nodes, which assist a source to communicate with a destination node; an optimal method and a greedy heuristic. in addition, we consider a distributed version of the proposed topology control scheme. our findings are substantiated by an extensive simulation study, through which we show that the cooperative bridges scheme substantially increases the connectivity while consuming a similar amount of transmission power compared to other existing topology control schemes.
when watchdog meets coding. we consider the problem of misbehavior detection in wireless networks. a commonly adopted approach is to exploit the broadcast nature of the wireless medium, where nodes monitor their downstream neighbors locally using overheard messages. we call such nodes the watchdogs.we propose a lightweight misbehavior detection scheme which integrates the idea of watchdogs and error detection coding.we show that even if the watchdog can only observe a fraction of packets, by choosing the error detection code properly, an attacker can be detected with high probability while achieving throughput arbitrarily close to optimal. such properties reduce the incentive for the attacker to attack. we then consider the problem of locating the misbehaving node and propose a simple protocol, which locates the misbehaving node with high probability. the protocol requires exactly two watchdogs per unreliable relay node.
the capacity of heterogeneous wireless networks. although capacity has been extensively studied in wireless networks, most of the results are for homogeneous wireless networks where all nodes are assumed identical. in this paper, we investigate the capacity of heterogeneous wireless networks with general network settings. specifically, we consider a dense network with n normal nodes and m = nb (0 < b < 1) more powerful helping nodes in a rectangular area with width b(n) and length 1/b(n), where b(n) = nw and -1/2 < w ≤ 0. we assume there are n flows in the network. all the n normal nodes are sources while only randomly chosen nd (0 < d < 1) normal nodes are destinations. we further assume the n normal nodes are uniformly and independently distributed, while the m helping nodes are either regularly placed or uniformly and independently distributed, resulting in two different kinds of networks called regular heterogeneous wireless networks and random heterogeneous wireless networks, respectively. in this paper, we attempt to find out what a heterogeneous wireless network with general network settings can do by deriving a lower bound on the capacity. we also explore the conditions under which heterogeneous wireless networks can provide throughput higher than traditional homogeneous wireless networks.
simple efficient tcam based range classification. in recent years, hardware based packet classification has became an essential component in many networking devices. ternary content-addressable memories (tcams) are one of the most popular solutions in this domain, allowing to compare in parallel the packet header against a large set of rules, and to retrieve the first match. however, using tcam to match a range of values is much more problematic and dramatically reduces the cost effectiveness of the solution. in this paper we study ways to use simple built-in tcam mechanisms in order to increase the efficiency of range coverage. while current techniques have a worst expansion ratio of 2ċw-4, we present an efficient algorithm enabling to encode any range with at most w tcam entries (where w in the number of bits), without using additional processing, extra bits, and without any external encoding. the same paradigm can be applied to multiple raging rules as well, resulting in significant improvement over current known techniques. moreover, our simulation results indicate that these techniques can be used to reduce the actual tcam size of hardware networking devices under realistic scenarios.
on the feasibility and efficacy of protection routing in ip networks. with network components increasingly reliable, routing is playing an ever greater role in determining network reliability. this has spurred much activity in improving routing stability and reaction to failures, and rekindled interest in centralized routing solutions, at least within a single routing domain. centralizing decisions eliminates uncertainty and many inconsistencies, and offers added flexibility in computing routes that meet different criteria. however, it also introduces new challenges; especially in reacting to failures where centralization can increase latency. this paper leverages the flexibility afforded by centralized routing to address these challenges. specifically, we explore when and how standby backup forwarding options can be activated, while waiting for an update from the centralized server after the failure of an individual component (link or node). we provide analytical insight into the feasibility of such backups as a function of network structure, and quantify their computational complexity. we also develop an efficient heuristic reconciling protectability and performance, and demonstrate its effectiveness in a broad range of scenarios. the results should facilitate deployments of centralized routing solutions.
efficient resource allocation with flexible channel cooperation in ofdma cognitive radio networks. recently, a cooperative paradigm for single-channel cognitive radio networks has been advocated, where primary users can leverage secondary users to relay their traffic. however, it is not clear how such cooperation can be exploited in multi-channel networks effectively. conventional cooperation entails that data on one channel has to be relayed on exactly the same channel, which is inefficient in multi-channel networks with channel and user diversity. moreover, the selfishness of users complicates the critical resource allocation problem, as both parties target at maximizing their own utility. this work represents the first attempt to address these challenges. we propose flec, a novel design of flexible channel cooperation. it allows secondary users to freely optimize the use of channels for transmitting primary data along with their own data, in order to maximize performance. further, we formulate a unifying optimization framework based on nash bargaining solutions to fairly and efficiently address resource allocation between primary and secondary networks, in both decentralized and centralized settings. we present an optimal distributed algorithm and sub-optimal centralized heuristics, and verify their effectiveness via realistic simulations.
network positioning from the edge - an empirical study of the effectiveness of network positioning in p2p systems. network positioning systems provide an important service to large-scale p2p systems, potentially enabling clients to achieve higher performance, reduce cross-isp traffic and improve the robustness of the system to failures. because traces representative of this environment are generally unavailable, and there is no platform suited for experimentation at the appropriate scale, network positioning systems have been commonly implemented and evaluated in simulation and on research testbeds. the performance of network positioning remains an open question for large deployments at the edges of the network. this paper evaluates how four key classes of network positioning systems fare when deployed at scale and measured in p2p systems where they are used. using 2 billion network measurements gathered from more than 43,000 ip addresses probing over 8 million other ips worldwide, we show that network positioning exhibits noticeably worse performance than previously reported in studies conducted on research testbeds. to explain this result, we identify several key properties of this environment that call into question fundamental assumptions driving network positioning research.
mset: a mobility satellite emulation testbed. satellite systems are ideal for distributing the same content to a large number of users, as well as providing broadband connectivity in remote areas or backup in case of terrestrial network failures. unlike terrestrial networks, satellite networks face a unique set of challenges, such as signal fading and interference from multiple transmitters combined with long propagation delays. a well known challenge is that these unique characteristics can have an adverse impact on various protocols, making it necessary to study protocol behavior in satellite networks. the challenge of our research, and the focus of this paper, is to develop an architecture for a high-fidelity and scalable emulation testbed tailored for mobile satellite communications research. the testbed is designed to provide multi-beam, multi-satellite, tdma, and mobility functionality. our validation studies demonstrate that the testbed is capable of achieving delay, loss, and jitter that can be associated with a mobile satellite link.
demand-oblivious routing: distributed vs. centralized approaches. until recent years, it was more or less undisputed common-sense that an accurate view on traffic demands is indispensable for optimizing the flow of traffic through a network. lately, this premise has been questioned sharply: it was shown that setting just a single routing, the so called demandoblivious routing, is sufficient to accommodate any admissible traffic matrix in the network with moderate link overload, so no prior information on demands is absolutely necessary for efficient traffic engineering. demand-oblivious routing lends itself to distributed implementations, so it scales well. in this paper, we generalize demand-oblivious routing in a new way: we show that, in contrast to the distributed case, centralized demand-oblivious routing can eliminate link overload completely. what is more, our centralized scheme allows for optimizing the routes with respect to arbitrary linear or quadratic objective function. we realize, however, that a centralized scheme can become prohibitively complex, therefore, we propose a hybrid distributed-centralized algorithm, which, according to our simulations, strikes a good balance between efficiency, scalability and complexity.
an efficient algorithm for constructing maximum lifetime tree for data gathering without aggregation in wireless sensor networks. data gathering is a broad research area in wireless sensor networks. the basic operation in sensor networks is the systematic gathering and transmission of sensed data to a sink for further processing. the lifetime of the network is defined as the time until the first node depletes its energy. a key challenge in data gathering without aggregation is to conserve the energy consumption among nodes so as to maximize the network lifetime. we formalize the problem of tackling the challenge as to construct a min-max-weight spanning tree, in which the bottleneck nodes have the least number of descendants according to their energy. however, the problem is np-complete. a ω(log n/log log n)- approximation algorithm mitt is proposed to solve the problem without location information. simulation results show that mitt can achieve longer network lifetime than existing algorithms.
beyond triangle inequality: sifting noisy and outlier distance measurements for localization. knowing accurate positions of nodes in wireless ad-hoc and sensor networks is essential for a wide range of pervasive and mobile applications. however, errors are inevitable in distance measurements and we observe that a small number of outliers can degrade localization accuracy drastically. to deal with noisy and outlier ranging results, triangle inequality is often employed in existing approaches. our study shows that triangle inequality has a lot of limitations which make it far from accurate and reliable. in this study, we formally define the outlier detection problem for network localization and build a theoretical foundation to identify outliers based on graph embeddability and rigidity theory. our analysis shows that the redundancy of distance measurements plays an important role. we then design a bilateration generic cycles based outlier detection algorithm, and examine its effectiveness and efficiency through a network prototype implementation of micaz motes as well as extensive simulations. the results shows that our design significantly improves the localization accuracy by wisely rejecting outliers.
frequency-domain packet scheduling for 3gpp lte uplink. in this paper, we investigate the frequency-domain packet scheduling (fdps) problem for 3gpp lte uplink (ul). instead of studying a specific scheduling policy, we provide a unified approach to tackle this issue. first we formalize a general lte ul fdps problem which is suitable for various scheduling policies. then we prove that the problem is max snp-hard, which implies that approximation algorithms with constant approximation ratios are the best that we can hope for. therefore we design two approximation algorithms, both of which have polynomial runtime. subsequently, we analyze the two algorithms and find their approximation ratios. the first algorithm is easy to follow, since it is based on a simple greedy method. the second one is based on the local ratio technique and it can approximately solve the lte ul fdps problem with a approximation ratio of 2.
bayesian inference for localization in cellular networks. in this paper, we present a general technique based on bayesian inference to locate mobiles in cellular networks. we study the problem of localizing users in a cellular network for calls with information regarding only one base station and hence triangulation or trilateration cannot be performed. in our call data records, this happens more than 50% of time. we show how to localize mobiles based on our knowledge of the network layout and how to incorporate additional information such as round-trip-time and signal to noise and interference ratio (sinr) measurements. we study important parameters used in this bayesian method through mining call data records and matching gps records and obtain their distribution or typical values. we validate our localization technique in a commercial network with a few thousand emergency calls. the results show that the bayesian method can reduce the localization error by 20% compared to a blind approach and the accuracy of localization can be further improved by refining the a priori user distribution in the bayesian technique.
enabling a bufferless core network using edge-to-edge packet-level fec. internet traffic is expected to grow phenomenally over the next five to ten years, and to cope with such large traffic volumes, core networks are expected to scale to capacities of terabits-per-second and beyond. increasing the role of optics for switching and transmission inside the core network seems to be the most promising way forward to accomplish this capacity scaling. unfortunately, unlike electronic memory, it remains a formidable challenge to build even a few packets of integrated all-optical buffers. in the context of envisioning a bufferless (or near-zero buffer) core network, our contributions are threefold: first, we propose a novel edge-to-edge based packet-level forward error correction (fec) framework as a means of combating high core losses, and investigate via analysis and simulation the appropriate fec strength for a single core link. second, we consider a realistic multi-hop network and develop an optimisation framework that adjusts the fec strength on a per-flow basis to ensure fairness between singleand multi-hop flows. third, we study the efficacy of fec for various system parameters such as relative mixes of short-lived and long-lived tcp flows, and average offered link loads. our study is the first to show that packet-level fec, when tuned properly, can be very effective in mitigating high core losses, thus opening the doors to a bufferless core network in the future.
mac-layer time fairness across multiple wireless lans. wireless lans have been densely deployed in many urban areas. contention among nearby wlans is locationsensitive, which makes some hosts much more capable than others to obtain the channel for their transmissions. another reality is that wireless hosts use different transmission rates to communicate with the access points due to attenuation of their signals. we show that location-sensitive contention aggravates the throughput anomaly caused by different transmission rates. it can cause throughput degradation and host starvation. this paper studies the intriguing interaction between location-sensitive contention and time fairness across contending wlans. achieving time fairness across multiple wlans is a very difficult problem because the hosts may perceive very different channel conditions and they may not be able to communicate and coordinate their operations due to the disparity between the interference range and the transmission range. in this paper, we design a mac-layer time fairness solution based on two novel techniques: channel occupancy adaptation, which applies aimd on the channel occupancy of each flow, and queue spreading, which ensures that all hosts and only those hosts in a saturated channel detect congestion and reduce their channel occupancies in response. we show that these two techniques together approximate the generic adaptation algorithm for proportional fairness.
optimizing the batch mode of group rekeying: lower bound and new protocols. in group communications, an efficient rekeying scheme plays a key role in providing access control when a membership change happens. for reducing the communication cost in the rekeying operation, one proposed model is to rekey upon individual membership change. it is theoretically proved that given the forward secrecy requirement, the optimal amortized communication cost is at least o(log n) (n is the group size) for an individual rekeying (ir). another model is to rekey upon a batch of multiple membership changes: batch rekeying (br), which largely reduces the rekeying communication cost, and relieves implementation difficulties in the ir model (e.g., extremely intensive rekey messages and key arriving disorders in large-size and highly dynamic groups). unlike ir, however, the communication lower bound in br is not yet explicitly stated. this paper first extends the communication lower bound for ir to the br model. specifically, we prove that given the batch level forward secrecy, the communication costs for updating the whole group subset by subset in a sequence of b batch rekeyings are at least o(b ċ (log2 b - 1)) + o(n). this bound, as a superset, inclusively explains the ir bound as a special case of b = n. second, for achieving the found bound, we provide a departing-time related key topology that works optimally under the bound. third, to further implement the proposed optimal topology, we propose two novel br protocols, one with support of forward secrecies and the other with support of two-way secrecies. through extensive analyses and simulations, the proposed protocols are shown to achieve notable upgrades in major performance metrics: 60% ∼ 70% reduction in communication overheads, 50% ∼ 60% reduction in key storage overheads, and elimination of key tree unbalance.
a collaboration-based autonomous reputation system for email services. this paper presents care, an autonomous email reputation system based on inter-domain collaboration. within the framework of care, each domain independently builds its reputation database based on both the local email history and the information exchanged with other collaborating domains. care examines the trustworthiness of the email histories obtained from collaborators by correlating them with the local email history. to validate the efficacy of care, we have analyzed real email logs, conducted a dns-based estimation experiment, and performed a series of simulations. our experimental results show that care can effectively improve the reliability and performance of email systems.
asymptotic analysis of precoded small cell networks. in this paper, we study precoded mimo based small cell networks. we derive the theoretical sum-rate capacity, when multi-antenna base stations transmit precoded information to its multiple single-antenna users in the presence of intercell interference from neighboring cells. due to an interference limited scenario, increasing the number of antennas at the base stations does not yield necessarily a linear increase of the capacity. we assess exactly the effect of multi-cell interference on the capacity gain for a given interference level. we use recent tools from random matrix theory to obtain the ergodic sum-rate capacity, as the number of antennas at the base station, number of users grow large. simulations confirm the theoretical claims and also indicate that in most scenarios the asymptotic derivations applied to a finite number of users give good approximations of the actual ergodic sum-rate capacity.
neighbor discovery with reception status feedback to transmitters. neighbor discovery is essential for the process of self-organization of a wireless network, where almost all routing and medium access protocols need knowledge of one-hop neighbors. in this paper we study the problem of neighbor discovery in a static and synchronous network, where time is divided into slots, each of duration equal to the time required to transmit a hello message, and potentially, some sort of feedback message. our main contributions lie in detailing the physical layer mechanism for how nodes in receive mode detect the channel status, describing algorithms at higher layers that exploit such a knowledge, and characterizing the significant gain obtained. in particular, we describe one possible physical layer architecture that allows receivers to detect collisions, and then introduce a feedback mechanism that makes the collision information available to the transmitters. this allows nodes to stop transmitting packets as soon as they learn about the successful reception of their discovery messages by the other nodes in the network. hence, the number of nodes that need to transmit packets decreases over time. these nodes transmit with a probability that is inversely proportional to the number of active nodes in their neighborhood, which is estimated using the collision information available at the nodes. we show through analysis and simulations that our algorithm allows nodes to discover their neighbors in a significantly smaller amount of time compared to the case where reception status feedback is not available to the transmitters.
design and analysis of a robust pipelined memory system. many network processing applications require wirespeed access to large data structures or a large amount of flowlevel data, but the capacity of srams is woefully inadequate in many cases. in this paper, we analyze a robust pipelined memory architecture that can emulate an ideal sram by guaranteeing with very high probability that the output sequence produced by the pipelined memory architecture is the same as the one produced by an ideal sram under the same sequence of memory read and write operations, except time-shifted by a fixed pipeline delay of δ. the design is based on the interleaving of dram banks together with the use of a reservation table that serves in part as a data cache. in contrast to prior interleaved memory solutions, our design is robust even under adversarial memory access patterns, which we demonstrate through a rigorous worstcase theoretical analysis using a combination of convex ordering and large deviation theory.
routing primitives for wireless mesh networks: design, analysis and experiments. in this paper, we consider routing in multi-hop wireless mesh networks. we analyze three standardized and commonly deployed routing mechanisms that we term "node-pair discovery" primitives. we show that use of these primitives inherently yields inferior route selection, irrespective of the protocol that implements them. this behavior originates due to overhead reduction actions that systematically yield insufficient distribution of routing information, effectively hiding available paths from nodes. to address this problem, we propose a set of "deter and rescue" routing primitives that enable nodes to discover their hidden paths by exploiting already available historic routing information. we use extensive measurements on a large operational wireless mesh network to show that with node-pair discovery primitives, inferior route selections occur regularly and cause long-term throughput degradations for network users. in contrast, the deter and rescue primitives largely identify and prevent selection of inferior paths. moreover, even when inferior paths are selected, the new primitives reduce their duration by several orders of magnitude, often to sub-second time scales.
p2p trading in social networks: the value of staying connected. the success of future p2p applications ultimately depends on whether users will contribute their bandwidth, cpu and storage resources to a larger community. in this paper, we propose a new incentive paradigm, networked asynchronous bilateral trading (nabt), which can be applied to a broad range of p2p applications. in nabt, peers belong to an underlying social network, and each pair of friends keeps track of a credit balance between them. when user alice provides a service (a file, storage space, computation and so on) to her friend bob, she charges bob credits. thus, in nabt, there is no global currency; instead, there are only credit balances maintained between pairs of friends. nabt allows peers to supply each other asynchronously and further allows peers to trade with remote peers through intermediaries. we theoretically show that nabt is perfectly efficient with balanced demands and supports "networked tit-for-tat". the efficiency of nabt with unbalanced demands is determined by the min-cut of credit limits of the underlying social network. using simulations driven by myspace traces, we demonstrate that a simple two-hop nabt design can have high trading efficiency, provide service differentiation, exploit trading intermediaries, and discourage free-riders.
on the connectivity analysis over large-scale hybrid wireless networks. many real systems are hybrid networks which include infrastructure nodes in multi-hop wireless networks, such as sinks in sensor networks and mesh routers in mesh networks. however, we have very little understanding of network connectivity in such networks. therefore, in this paper, we consider hybrid networks denoted by h(α, β) with ad hoc nodes and base stations and prove how base stations can improve the connectivity of ad hoc nodes in subcritical phase, that is, the ad hoc node density, λα is lower than the critical density λαc. we find that with the existence of a positive density of base stations, i.e., the density of base stations λβ > 0 which have the same transmission range as ad hoc nodes, the number of connected ad hoc nodes is θ(n) with probability nearly 1, where n is the number of ad hoc nodes. however, the size of connected ad hoc component scales linearly with λβ when it is lower than c1(λα) with probability nearly 1, which demonstrates a tremendous benefit of using base stations to enhance the connectivity of ad hoc nodes. further, we study a hybrid network architecture that makes a significant connectivity improvement with transmission range rβ larger than rα for ad hoc nodes. therefore, our results provide a theoretical understanding of to what extent ad hoc nodes can benefit from base stations in multihop wireless networks.
dac: distributed asynchronous cooperation for wireless relay networks. cooperative relay is a communication paradigm that aims to realize the capacity of multi-antenna arrays in a distributed manner. however, the symbol-level synchronization requirement among distributed relays limits its use in practice. we propose to circumvent this barrier with a cross-layer protocol called distributed asynchronous cooperation (dac). with dac, multiple relays can schedule concurrent transmissions with packet-level (hence coarse) synchronization. the receiver then extracts multiple versions of each relayed packet via a collision-resolution algorithm, thus realizing the diversity gain of cooperative communication. we demonstrate the feasibility of dac by prototyping and testing it on the gnuradio/usrp software radio platform. to explore its relevance at the network level, we introduce a dac-based mac, and a generic approach to integrate the dac mac/phy layer into a typical routing algorithm. considering the use of dac for multiple network flows, we analyze the fundamental tradeoff between the improvement in diversity gain and the reduction in multiplexing opportunities. dac is shown to improve the throughput and delay performance of lossy networks with medium-level link quality. our analytical results are also confirmed by network-level simulation in ns-2.
two samples are enough: opportunistic flow-level latency estimation using netflow. the inherent support in routers (snmp counters or netflow) is not sufficient to diagnose performance problems in ip networks, especially for flow-specific problems where the aggregate behavior within a router appears normal. to address this problem, in this paper, we propose a consistent netflow (cnf) architecture for measuring per-flow performance measurements within routers. cnf utilizes existing netflow architecture that already reports the first and last timestamps per-flow, and proposes hash-based sampling to ensure that two adjacent routers record the same flows. we devise a novel multiflow estimator that approximates the intermediate delay samples from other background flows to improve the per-flow latency estimates significantly compared to the naive estimator that only uses actual flow samples. in our experiments using real backbone traces and realistic delay models, we show that the multiflow estimator is accurate with a median relative error of less than 20% for flows of size greater than 100 packets. we also show that prior approach based on trajectory sampling performs about 2-3x worse.
bgp churn evolution: a perspective from the core. the scalability limitations of bgp have been a major concern in the networking community lately. an important issue in this respect is the rate of routing updates (churn) that bgp routers must process. this paper presents an analysis of the evolution of churn in four networks in the backbone of the internet over the last six years, using update traces from the routeviews project. the churn rate varies widely over time and between networks, and cannot be understood through "blackbox" statistical analysis. instead we take a different approach with a focus on investigating the underlying reasons for bgp churn evolution. through our analysis we are able to identify and isolate the main reasons behind many of the anomalies in the churn time series. we find that duplicate announcements is a major churn contributor, and responsible for most large spikes in the churn time series. other intense periods of churn are caused by misconfigurations or other special events in or close to the monitored as, and hence limiting these is an important mean to limit churn. we then analyze the remaining "baseline" churn, and find that it is increasing with a rate much slower than the increase in the routing table size.
exploiting multiple-antenna diversity for shared secret key generation in wireless networks. generating a secret key between two parties by extracting the shared randomness in the wireless fading channel is an emerging area of research. previous works focus mainly on single-antenna systems. multiple-antenna devices have the potential to provide more randomness for key generation than single-antenna ones. however, the performance of key generation using multiple-antenna devices in a real environment remains unknown. different from the previous theoretical work on multiple-antenna key generation, we propose and implement a shared secret key generation protocol, multiple-antenna key generator (make) using off-the-shelf 802.11n multiple-antenna devices. we also conduct extensive experiments and analysis in real indoor and outdoor mobile environments. using the shared randomness extracted from measured received signal strength indicator (rssi) to generate keys, our experimental results show that using laptops with three antennas, make can increase the bit generation rate by more than four times over single-antenna systems. our experiments validate the effectiveness of using multi-level quantization when there is enough mutual information in the channel. our results also show the trade-off between bit generation rate and bit agreement ratio when using multi-level quantization. we further find that even if an eavesdropper has multiple antennas, she cannot gain much more information about the legitimate channel.
queuing analysis in multichannel cognitive spectrum access: a large deviation approach. the queueing performance of a (secondary) cognitive user is investigated for a hierarchical network where there are n independent and identical primary users. each primary user employs a slotted transmission protocol, and its channel usage forms a two-state (busy,idle) discrete-time markov chain. the cognitive user employs the optimal policy to select which channel to sense (and use if found idle) at each slot. in the framework of effective bandwidths, the stationary queue tail distribution of the cognitive user is estimated using a large deviation approach for which closed-form expressions are obtained when n = 2. upper and lower bounds are obtained for the general n primary user network. for positively correlated primary transmissions, the bounds are shown to be asymptotically tight. monte carlo simulations using importance sampling techniques are used to validate the obtained large deviation estimates.
high quality sensor placement for shm systems: refocusing on application demands. there are heavy studies recently on applying wireless sensor networks for structural health monitoring. these works usually focus on the computer science aspect, and the considerations include energy consumption, network connectivity, etc. it is commonly believed that for the current resource limited wireless sensors, system design could be more efficient if the application requirements are incorporated. nevertheless, we often find that, rather than integration, assumptions have to be made due to lack of knowledge of civil engineering; for example, to evaluate routing algorithms, the sensor placement is assumed to be random or on grids/trees. these may not be practically meaningful to the respective application demands, and make the great efforts by the computer science community on developing efficient methods from the sensor network aspect less useful. in this paper, we study the very first problem of the shm systems: the sensor placement and focus on the civil requirements. we first study the current general framework of structure health monitoring. we redevelop the framework that includes a new sensor placement module. this module implements the most widely accepted sensor placement scheme from civil engineering but focusing on its usefulness for computer science. it provides such interfaces that can rank the placement quality of the candidate locations in a step by step manner. we then optimize system performance by considering network connectivity and data routing issues; with the objective on energy efficiency. we evaluate our scheme using the data from the structural health monitoring system on the ting kau bridge, hong kong. we show that a uniform and a state-of-the-art placement are not very meaningful in placement quality. our scheme achieves almost the same sensor placement quality with that of the civil engineering with five-fold improvement in system lifetime. we conduct an experiment on the in-built guangzhou new tv tower, china; and the results validate the effectiveness of our scheme.
delay performance of scheduling with data aggregation in wireless sensor networks. in-network aggregation has become a promising technique for improving the energy efficiency of wireless sensor networks. aggregating data at various nodes in the network results in a reduction in the amount of bits transmitted over the network, and hence, saves energy. in this paper, we focus on another important aspect of aggregation, i.e., delay performance. in conjunction with link scheduling, in-network aggregation can reduce the delay by lessening the demands for wireless resources and thus expediting data transmissions. we formulate the problem that minimizes the sum delay of sensed data, and analyze the performance of optimal scheduling with innetwork aggregation in tree networks under the node-exclusive interference model. we provide a system wide lower bound on the delay and use it as a benchmark for evaluating different scheduling policies. we numerically evaluate the performance of myopic and non-myopic scheduling policies, where myopic one considers only the current system state for a scheduling decision while non-myopic one simulates future system states. we show that the one-step non-myopic policies can substantially improve the delay performance. in particular, the proposed nonmyopic greedy scheduling achieves a good tradeoff between performance and implementability.
reliable broadcasting in random networks and the effect of density. broadcasting algorithms are of fundamental importance for distributed systems engineering. in this paper we revisit the classical and well-studied push protocol for message broadcasting and we investigate a faulty version of it. assuming that initially only one node has some piece of information, at each stage every one of the informed nodes chooses randomly and independently one of its neighbors and passes the message to it with some probability q; that is, it fails to do so with probability 1 - q. the performance of the push protocol on a fully connected network, where each node is joined by a link to every other node, with q = 1 is very well understood. in particular, frieze and grimmett proved that with probability 1 - o(1) the push protocol completes the broadcasting of the message within (1 ± ɛ)(log2 n + ln n) stages, where n is the number of nodes in the network. however, there are no tight bounds for the broadcast time on networks that are significantly sparser than the complete graph. in this work we consider random networks on n nodes, where every edge is present with probability p, independently of every other edge. we show that if p ≥ α(n) ln n/n, where α(n) is any function that tends to infinity as n grows, then the push protocol with faulty transmissions broadcasts the message within (1 ± ɛ) (log1+q n + 1/q ln n) stages with probability 1 - o(1). in other words, in almost every network of density d such that d ≥ α(n) ln n, the push protocol broadcasts a message as fast as in a fully connected network and the speed is only affected by the success probability q. this is quite surprising in the sense that the time needed remains essentially unaffected by the fact that most of the links are missing. our results are accompanied by experimental evaluation.
malicious shellcode detection with virtual memory snapshots. malicious shellcodes are segments of binary code disguised as normal input data. such shellcodes can be injected into a target process's virtual memory. they overwrite the process's return addresses and hijack control flow. detecting and filtering out such shellcodes is vital to prevent damage. in this paper, we propose a new malicious shellcode detection methodology in which we take snapshots of the process's virtual memory before input data are consumed, and feed the snapshots to a malicious shellcode detector. these snapshots are used to instantiate a runtime environment that emulates the target process's input data consumption to monitor shellcodes' behaviors. the snapshots can also be used to examine the system calls that shellcodes invoke, these system call parameters, and the process's execution flow. we implement a prototype system in debian linux with kernel version 2.6.26. our extensive experiments with real traces and thousands of malicious shellcodes illustrate our system's performance with low overhead and few false negatives and few false positives.
throughput and delay analysis on uncoded and coded wireless broadcast with hard deadline constraints. multimedia streaming applications have stringent qos requirements. typically each packet is associated with a packet delivery deadline. this work models and considers realtime streaming broadcast for stored-video over the downlink of a single cell. the broadcast capacity of the system subject to deadline constraints are derived for both uncoded and coded wireless broadcast schemes. even under the deadline requirements, it is shown in this work that network coding is asymptotically throughput-optimal and can strictly outperform the best noncoding policy by analytically quantifying the optimal capacity when the file size is sufficiently large. a simple network coding policy is also proposed that achieves the asymptotic capacity while maintaining finite transmission delay (queueing + decoding delay). a new temporal-queue-length-based lyapunov function is used to prove the optimality of this policy. simulation shows that the simple coding policy outperforms the best non-coding policies even for broadcasting files of small sizes.
characterizing the spread of correlated failures in large wireless networks. correlated failures pose a great challenge for the normal functioning of large wireless networks, because an initial local failure may trigger a global sequence of related failures. given their potentially devastating impact, we characterize the spread of correlated failures in this paper, which lays the foundation for evaluating and improving the failure resilience of existing wireless networks. we model the failure contagiousness as two generic functions: the failure impact radius distribution function fr(x) and the failure connection function g(x). by using the percolation theory, we determine the respective characteristic regimes of fr(x) and g(x) in which correlated failures will and will not percolate in the network. as our model represents various failure scenarios, the results are generally applicable in understanding the spread of a wide range of correlated failures.
information quality aware routing in event-driven sensor networks. upon the occurrence of a phenomenon of interest in a wireless sensor network, multiple sensors may be activated, leading to data implosion and redundancy. data aggregation and/or fusion techniques exploit spatio-temporal correlation among sensory data to reduce traffic load and mitigate congestion. however, this is often at the expense of loss in information quality (iq) of data that is collected at the fusion center. in this work, we address the problem of finding the leastcost routing tree that satisfies a given iq constraint. we note that the optimal least-cost routing solution is a variation of the classical np-hard steiner tree problem in graphs, which incurs high overheads as it requires knowledge of the entire network topology and individual iq contributions of each activated sensor node. we tackle these issues by proposing: (i) a topology-aware histogram-based aggregation structure that encapsulates the cost of including the iq contribution of each activated node in a compact and efficient way; and (ii) a greedy heuristic to approximate and prune a least-cost aggregation routing path. we show that the performance of our iq-aware routing protocol is: (i) bounded by a distance-based aggregation tree that collects data from all the activated nodes; and (ii) comparable to another iq-aware routing protocol that uses an exhaustive brute-force search to approximate and prune the least-cost aggregation tree.
magnetworks: how mobility impacts the design of mobile ad hoc networks. in this paper we study the optimal placement and optimal number of active relay nodes through the traffic density in mobile sensor ad hoc networks. we consider a setting in which a set of mobile sensor sources is creating data and a set of mobile sensor destinations is receiving that data through multihop wireless paths. we make the assumption that the network is massively dense, i.e., there are so many sources, destinations, and relay nodes, that it is best to describe the network in terms of macroscopic parameters rather than in terms of microscopic parameters. a simple one-dimensional scenario is used to introduce the problem. we solve the two-dimensional scenario where the mobility of the nodes is deterministic and when it follows the brownian mobility model.
a self-organized mechanism for thwarting malicious access in ad hoc networks. this paper introduces a self-organized mechanism to control user access in ad hoc networks without requiring any infrastructure or a central administration entity. the proposed mechanism authenticates and monitors nodes with the so-called controller sets, which are resistant to the dynamic network membership. the analysis shows that the proposed scheme is robust even to collusion attacks and provides availability up to 90% better than proposals based on threshold cryptography. the performance improvement arises mostly from the controller sets autonomy to recover after network partitions.
the k-constrained bipartite matching problem: approximation algorithms and applications to wireless networks. in communication networks, resource assignment problems appear in several different settings. these problems are often modeled by a maximum weight matching problem in bipartite graphs and efficient matching algorithms are well known. in several applications, the corresponding matching problem has to be solved many times in a row as the underlying system operates in a time-slotted fashion and the edge weights change over time. however, changing the assignments can come with a certain cost for reconfiguration that depends on the number of changed edges between subsequent assignments. in order to control the cost of reconfiguration, we propose the k-constrained bipartite matching problem for bipartite graphs, which seeks an optimal matching that realizes at most k changes from a previous matching. we provide fast approximation algorithms with provable guarantees for this problem. furthermore, to cope with the sequential nature of assignment problems, we introduce an online variant of the k- constrained matching problem and derive online algorithms that are based on our approximation algorithms for the k-constrained bipartite matching problem. finally, we establish the applicability of our model and our algorithms in the context of ofdma wireless networks finding a significant performance improvement for the proposed algorithms.
optimizing throughput and latency under given power budget for network packet processing. current state-of-the-art task scheduling algorithms for network packet processing schedule the program into a parallel-pipeline topology on network processors to maximize the throughput. however, there has been no existing work targeting power budget for packet processing on off-the-shelf multicore architectures. as energy consumption, reliability and cooling cost for packet processing systems become increasingly important, it is necessary to integrate power-awareness into a scheduler to meet the power budget. in this paper, we propose a novel scheduling algorithm to optimize both throughput and latency given a power budget for network packet processing on multicore architectures. this algorithm addresses power-aware parallel-pipeline scheduling problem by applying per-core dvfs to optimally adjust frequency on each core. we implement our algorithm on an amd machine with two quad-core opteron 2350 processors and compare the results with existing algorithms given the same power budget. for six real packet processing applications, our algorithm improves throughput and reduces latency by an average of 64.6% and 25.2%, respectively.
towards efficient designs for in-network computing with noisy wireless channels. in this paper we study distributed function computation in a noisy multi-hop wireless network, in which n nodes are uniformly and independently distributed in a unit square. we adopt the adversarial noise model, for which independent binary symmetric channels are assumed for any point-to-point transmissions, with (not necessarily identical) crossover probabilities bounded above by some constant ε. each node holds an m-bit integer per instance and the computation is started after each node collects n readings. the goal is to compute a global function with a certain fault tolerance, in this distributed setting; we mainly deal with divisible functions, which essentially covers the main body of interest for wireless applications. we focus on protocol designs that are efficient in terms of communication complexity. we first devise a general protocol for evaluating any divisible functions, addressing both one-shot (n = o(1)) and block computation, and both constant and large m scenarios; its bottleneck in different scenarios is also analyzed. based on this analysis, we then endeavor to improve the design for two special cases: identity function, and some restricted type-threshold functions, both focusing on the constant m and n scenario.
multi-round sensor deployment for guaranteed barrier coverage. deploying wireless sensor networks to provide guaranteed barrier coverage is critical for many sensor networks applications such as intrusion detection and border surveillance. to reduce the number of sensors needed to provide guaranteed barrier coverage, we propose multi-round sensor deployment which splits sensor deployment into multiple rounds and can better deal with placement errors that often accompany sensor deployment. we conduct a comprehensive analytical study on multi-round sensor deployment and identify the tradeoff between the number of sensors deployed in each round of multiround sensor deployment and the barrier coverage performance. both numerical and simulation studies show that, by simply splitting sensor deployment into two rounds, guaranteed barrier coverage can be achieved with significantly less sensors comparing to singleround sensor deployment. moreover, we propose two practical solutions for multi-round sensor deployment when the distribution of a sensor's residence point is not fully known. the effectiveness of the proposed multi-round sensor deployment strategies is demonstrated by numerical and simulation results.
high performance dictionary-based string matching for deep packet inspection. dictionary-based string matching (dbsm) is used in network deep packet inspection (dpi) applications virus scanning [1] and network intrusion detection [2]. we propose the pipelined affix search with tail acceleration (pasta) architecture for solving dbsm with guaranteed worst-case performance. our pasta architecture is composed of a pipelined affix search relay (pasr) followed by a tail acceleration finite automaton (tafa). pasr consists of one or more pipelined binary search tree (pbst) modules arranged in a linear array. tafa is constructed with the aho-corasick goto and failure functions [3] in a compact multi-path and multi-stride tree structure. both pasr and tafa achieve good memory efficiency of 1.2 and 2 b/ch (bytes per character) respectively and are pipelined to achieve a high clock rate of 200 mhz on fpgas. because pasta does not depend on the effectiveness of any hash function or the property of the input stream, its performance is guaranteed in the worst case. our prototype implementation of pasta on an fpga with 10 mb on-chip block ram achieves 3.2 gbps matching throughput against a dictionary of over 700k characters. this level of performance surpasses the requirements of next-generation security gateways for deep packet inspection.
cooperative boundary detection for spectrum sensing using dedicated wireless sensor networks. spectrum sensing is one of the key enabling technologies in cognitive radio networks (crns). in crns, secondary users (sus) are allowed to exploit the spectrum opportunities by sensing and accessing the spectrum, which exhibit many critical limitations in practical environments. in this paper, we propose a new sensing service model that uses dedicated wireless spectrum sensor networks (wssn) for spectrum sensing. the major challenge in wssn is the design of data fusion, for which the traditional fusion scheme will produce a large amount of errors. we formulate the problem as a boundary detection problem with notable unknown erroneous inputs. to solve the problem, we propose a novel cooperative boundary detection scheme that intelligently incorporates the cooperative spectrum sensing concept and the recent advances in support vector machine (svm). cooperative boundary detection consists of two major components, a declaration calibration algorithm and a boundary derivation algorithm. we prove that cooperative spectrum sensing can asymptotically approach the optimal solution. a prototype system as well as simulation experiments show that compared with the traditional approaches, cooperative boundary detection can reduce the errors by up to 95% with an average reduction about 85%.
maximizing the contact opportunity for vehicular internet access. with increasing popularity of media enabled handhelds, the need for high data-rate services for mobile users is evident. large-scale wireless lans (wlans) can provide such a service, but they are expensive to deploy and maintain. open wlan access-points (aps), on the other hand, need no new deployments, but can offer only opportunistic services with no guarantees on short term throughput. in contrast, a carefully planned sparse deployment of roadside wifi provides an economically scalable infrastructure with quality of service assurance to mobile users. in this paper, we propose to study deployment techniques for providing roadside wifi services. in particular, we present a new metric, called contact opportunity, as a characterization of a roadside wifi network. informally, the contact opportunity for a given deployment measures the fraction of distance or time that a mobile user is in contact with some ap when moving through a certain path. such a metric is closely related to the quality of data service that a mobile user might experience while driving through the system. we then present an efficient deployment method that maximizes the worst case contact opportunity under a budget constraint. we further show how to extend this concept and the deployment techniques to a more intuitive metric - the average throughput - by taking various dynamic elements into account. simulations over a real road network and experimental results show that our approach achieves more than 200% higher minimum contact opportunity, 30%-100% higher average contact opportunity and a significantly improved distribution of average throughput compared with two commonly used algorithms.
assessing the vanet's local information storage capability under different traffic mobility. wireless networking enabled vehicles can form vehicular ad hoc mesh networks (vmeshs). using cooperative communication among vmeshs, a local transient information could be "retained" within a given geographic region for a certain period of time, without any infrastructure help. in this paper, we study this "storage capability" of vmeshs. we analyze the scenarios of highway traffic (both one-way and two-way highway free flow traffic) and vehicular traffic in a city environment. for highway traffic, we study different properties of the "vmesh storage", using a simulation tool that accurately models the freeway vehicular mobility. for city traffic, we first perform simulations based on real traffic trace of san francisco yellow cabs. then we compare the results with the scenario where a general random way point (rwp) mobility model is used. our results show that transmission range has high impact on the storage lifetime for one-way highway traffic, and the size of the region in which we want the information stored has high impact for two-way highway traffic. for city-wide traffic, the storage's lifetime generated using san francisco yellow cab trace is shorter than that obtained using the rwp mobility model. this is due to the regular movement of the cabs as compared to the random vehicle movement in the rwp mobility model.
intrusion-resilience in mobile unattended wsns. wireless sensor networks (wsns) are susceptible to a wide range of attacks due to their distributed nature, limited sensor resources and lack of tamper-resistance. once a sensor is corrupted, the adversary learns all secrets and (even if the sensor is later released) it is very difficult for the sensor to regain security, i.e., to obtain intrusion-resilience. existing solutions rely on the presence of an on-line trusted third party, such as a sink, or on the availability of secure hardware on sensors. neither assumption is realistic in large-scale unattended wsns (uwsns), characterized by long periods of disconnected operation and periodic visits by the sink. in such settings, a mobile adversary can gradually corrupt the entire network during the intervals between sink visits. as shown in some recent work, intrusionresilience in uwsns can be attained (to a degree) via cooperative self-healing techniques. in this paper, we focus on intrusion-resilience in mobile unattended wireless sensor networks (µuwsns) where sensors move according to some mobility model. we argue that sensor mobility motivates a specific type of adversary and defending against it requires new security techniques. concretely, we propose a cooperative protocol that - by leveraging sensor mobility - allows compromised sensors to recover secure state after compromise. this is obtained with very low overhead and in a fully distributed fashion. we provide a thorough analysis of the proposed protocol and support it by extensive simulation results.
optimal control of constrained cognitive radio networks with dynamic population size. in this paper, we consider the problem of optimal control for throughput utility maximization in cognitive radio networks with dynamic user arrivals and departures. the cognitive radio network considered in this paper consists of a number of heterogeneous sub-networks. these sub-networks may be power-constrained and are required to operate in such a way that the average total interference received on primary channels are kept below given thresholds. we develop a control policy that performs joint admission control and resource scheduling. through lyapunov optimization techniques, we show that the proposed policy achieves a utility performance within o(δ) of optimality for any positive δ. we further show that this arbitrarily closeness to optimality comes at the price of having a delay that is o(1/δ) in admitting users. we also propose constant factor approximations of the policy for distributed implementation.
non-preemptive buffer management for latency sensitive packets. the delivery of latency sensitive packets is a crucial issue in real time applications of communication networks. such packets often have a firm deadline and a packet becomes useless if it arrives after its deadline. the deadline, however, applies only to the packet's journey through the entire network; individual routers along the packet's route face a more flexible deadline. we consider policies for admitting latency sensitive packets at a router. each packet is tagged with a value and a packet waiting at a router loses value over time as its probability of arriving at its destination decreases. the router is modeled as a nonpreemptive queue, and its objective is to maximize the total value of the forwarded packets. when a router receives a packet, it must either accept it (and possibly delay future packets), or reject it immediately. the best policy depends on the set of values that a packet can take. we consider three natural settings: unrestricted model, real-valued model, where any value above 1 is allowed, and an integral-valued model. we obtain the following results. for the unrestricted model, we prove that there is no constant competitive ratio algorithm. the real valued model has a randomized 4-competitive algorithm and a matching lower bound. we also give for the last model a deterministic lower bound of φ3 ≈ 4.236, almost matching the previously known 4.24-competitive algorithm. for the integralvalued model, we show a deterministic 4-competitive algorithm, and prove that this is tight even for randomized algorithms.
mimo-aware routing in wireless mesh networks. multiple-input and multiple-output (mimo) technique is considered as one of the most promising emerging wireless technologies that can significantly improve transmission capacity and reliability in wireless mesh networks. while mimo has been widely studied for single link transmission scenarios in physical layer as well as from mac perspective, its impact on network layer, especially its interaction with routing has not drawn enough research attention. in this paper, we investigate the problem of routing in mimo-based wireless mesh networks. we mathematically formulate the mimo-enabled multi-source multidestination multi-hop routing problem into a multicommodity flow problem by identifying the specific opportunities and constraints brought by mimo transmissions, in order to provide the fundamental basis for mimo-aware routing design. we then use this formulation to develop a polynomial time approximation solution that maximizes the scaling factor for the concurrent flows in the network. moreover, we also consider a more practical case where controllers are distributed, and propose a distributed algorithm to minimize the congestion in the network links based on steepest descent framework, which is proved to provide a fixed approximation ratio. the performance of the algorithms is evaluated through simulations and demonstrated to outperform the counterpart strategies without considering mimo features.
distributed algorithms for approximating wireless network capacity. in this paper we consider the problem of maximizing wireless network capacity (a.k.a. one-shot scheduling) in both the protocol and physical models. we give the first distributed algorithms with provable guarantees in the physical model, and show how they can be generalized to more complicated metrics and settings in which the physical assumptions are slightly violated. we also give the first algorithms in the protocol model that do not assume transmitters can coordinate with their neighbors in the interference graph, so every transmitter chooses whether to broadcast based purely on local events. our techniques draw heavily from algorithmic game theory and machine learning theory, even though our goal is a distributed algorithm. indeed, our main results allow every transmitter to run any algorithm it wants, so long as its algorithm has a learning-theoretic property known as no-regret in a game-theoretic setting.
interactions, competition and innovation in a service-oriented internet: an economic model. this paper presents a new economic approach for studying competition and innovation in a complex and highly interactive system of network providers, users, and suppliers of digital goods and services (i.e., service providers). it employs cournot and bertrand games to model competition among service providers and network providers, respectively, and develops a novel unified model to capture the interaction and competition among these players in a "service-oriented" internet. incentives for service and network innovation are studied in this model.
utility functionals associated with available congestion control algorithms. this paper is concerned with understanding the connection between the existing internet congestion control algorithms and the optimal control theory. the available resource allocation controllers are mainly devised to derive the state of the system to a desired equilibrium point and, therefore, they are oblivious to the transient behavior of the closed-loop system. to take into account the real-time performance of the system, rather than merely its steady-state performance, the congestion control problem should be solved by maximizing a proper utility functional as opposed to a utility function. for this reason, this work aims to investigate what utility functionals the existing congestion control algorithms maximize. in particular, it is shown that there exist meaningful utility functionals whose maximization leads to the celebrated primal, dual and primal/dual algorithms. an implication of this result is that a real network problem may be solved by regarding it as an optimal control problem on which some practical constraints, such as a real-time link capacity constraint, are imposed.
chip error pattern analysis in ieee 802.15.4. ieee 802.15.4 standard specifies physical layer (phy) and medium access control (mac) sublayer protocols for low-rate and low-power communication applications. in this protocol, every 4-bit symbol is encoded into a sequence of 32 chips that are actually transmitted over the air. the 32 chips as a whole is also called a pseudo-noise code (pn-code). due to complex channel conditions such as attenuation and interference, the transmitted pn-code will often be received with some pn-code chips corrupted. in this paper, we conduct a systematic analysis on these errors occurring at chip-level. we find that there are notable error patterns corresponding to different cases. recognizing these patterns will enable us to identify the channel condition in great details. we believe that understanding what happened to the transmission in our setup can potentially bring benefit to channel coding, routing and error correction protocol design.
building scalable virtual routers with trie braiding. many popular algorithms for fast packet forwarding and filtering rely on the tree data structure. examples are the trie-based ip lookup and packet classification algorithms. with the recent interest in network virtualization, the ability to run multiple virtual router instances on a common physical router platform is essential. an important scaling issue is the number of virtual router instances that can run on the platform. one limiting factor is the amount of high-speed memory and caches available for storing the packet forwarding and filtering data structures. an ideal goal is to achieve good scaling while maintaining total isolation amongst the virtual routers. however, total isolation requires maintaining separate data structures in high-speed memory for each virtual router. in this paper, we study the case where some sharing of the forwarding and filtering data structures is permissible and develop algorithms for combining tries used for ip lookup and packet classification. specifically, we develop a mechanism called trie-braiding that allows us to combine tries from the data structures of different virtual routers into just one compact trie. two optimal braiding algorithms are presented and the effectiveness is demonstrated using the real world data sets.
spatio-temporal fusion for small-scale primary detection in cognitive radio networks. in cognitive radio networks (crns), detecting small-scale primary devices--such as wireless microphones (wms)-- is a challenging, but very important, problem that has not yet been addressed well. we identify the data-fusion range as a key factor that enables effective cooperative sensing for detection of small-scale primary devices. in particular, we derive a closed-form expression for the optimal data-fusion range that minimizes the average detection delay. we also observe that the sensing performance is sensitive to the accuracy in estimating the primary's location and transmit-power. based on these observations, we propose an efficient sensing framework, called deloc, that iteratively performs location/transmit-power estimation and dynamic sensor selection for cooperative sensing. our extensive simulation results in a realistic crn environment show that deloc achieves near-optimal detection performance, while meeting the detection requirements specified in the ieee 802.22 standard draft.
cpmc: an efficient proximity malware coping scheme in smartphone-based mobile networks. smartphones are envisioned to provide promising applications and services. at the same time, smartphones are also increasingly becoming the target of malware. many emerging malware can utilize the proximity of devices to propagate in a distributed manner, thus remaining unobserved and making detections substantially more challenging. different from existing malware coping schemes, which are either totally centralized or purely distributed, we propose a community-based proximity malware coping scheme, cpmc. cpmc utilizes the social community structure, which reflects a stable and controllable granularity of security, in smartphone-based mobile networks. the cpmc scheme integrates short-term coping components, which deal with individual malware, and long-term evaluation components, which offer vulnerability evaluation towards individual nodes. a closeness-oriented delegation forwarding scheme combined with a community level quarantine method is proposed as the short-term coping components. these components contain a proximity malware by quickly propagating the signature of a detected malware into all communities while avoiding unnecessary redundancy. the long-term components offer vulnerability evaluation towards neighbors, based on the observed infection history, to help users make comprehensive communication decisions. extensive real- and synthetic-trace driven simulation results are presented to to evaluate the effectiveness of cpmc.
lightweight mutual authentication and ownership transfer for rfid systems. the promise of rfid technology has been evidently foreseeable due to the low cost and high convenience value of rfid tags. however, the low-cost rfid tags poses new challenges to security and privacy. some solutions utilize expensive cryptographic primitives such as hash or encryption functions, and some lightweight approaches have been reported to be broken. in this paper, we propose a lightweight solution to mutual authentication for rfid systems in which only the authenticated readers and tags can successfully communicate with each other. then, we adapt our mutual authentication scheme to secure the ownership transfer of rfid tags. our mutual authentication and ownership transfer protocols are realized utilizing minimalistic cryptography such as physically unclonable functions (puf) and linear feedback shift registers (lfsr). pufs and lfsrs are very efficient in hardware and particularly suitable for the low-cost rfid tags. compared to existing solutions built on top of hash functions that require 8000 to 10000 gates, our schemes demand only 784 gates for 64-bit variables and can be easily accommodated by the cheapest rfid tags with only 2000 gates available for security functions.
uusee: large-scale operational on-demand streaming with random network coding. since the inception of network coding in information theory, we have witnessed a sharp increase of research interest in its applications in communications and networking, where the focus has been on more practical aspects. however, thus far, network coding has not been deployed in real-world commercial systems in operation at a large scale, and in a production setting. in this paper, we present the objectives, rationale, and design in the first production deployment of random network coding, where it has been used in the past year as the cornerstone of a large-scale production on-demand streaming system, operated by uusee inc., delivering thousands of on-demand video channels to millions of unique visitors each month. to achieve a thorough understanding of the performance of network coding, we have collected 200 gigabytes worth of real-world traces throughout the 17-day summer olympic games in august 2008, and present our lessons learned after an in-depth trace-driven analysis.
a framework for joint network coding and transmission rate control in wireless networks. network coding has been proposed as a technique that can potentially increase the transport capacity of a wireless network via processing and mixing of data packets at intermediate routers. however, most previous studies either assume a fixed transmission rate or do not consider the impact of using diverse rates on the network coding gain. since in many cases, network coding implicitly relies on overhearing, the choice of the transmission rate has a big impact on the achievable gains. the use of higher rates works in favor of increasing the native throughput; however, it may in many cases work against effective overhearing. in other words, there is a tension between the achievable network coding gain and the inherent rate gain possible on a link. in this paper1, our goal is to drive the network towards achieving the best trade-off between these two contradictory effects. towards this, we design a distributed framework that (a) facilitates the choice of the best rate on each link while considering the need for overhearing and (b) dictates the choice of which decoding recipient will acknowledge the reception of an encoded packet. we demonstrate that both of these features contribute significantly towards gains in throughput. we extensively simulate our framework in a variety of topological settings. we also fully implement it on real hardware and demonstrate its applicability and performance gains via proof-of-concept experiments on our wireless testbed. we show that our framework yields throughput gains of up to 390% as compared to what is achieved in a rate-unaware network coding framework.
distributed coordination with deaf neighbors: efficient medium access for 60 ghz mesh networks. multi-gigabit outdoor mesh networks operating in the unlicensed 60 ghz "millimeter (mm) wave" band, offer the possibility of a quickly deployable broadband extension of the internet. we consider mesh nodes with electronically steerable antenna arrays, with both the transmitter and receiver synthesizing narrow beams that compensate for the higher path loss at mm-wave frequencies, achieving ranges on the order of 100 meters using the relatively low transmit powers attainable with low-cost silicon implementations. such highly directional networking differs from wifi networks at lower carrier frequencies in two ways that have a crucial impact on protocol design: (1) directionality drastically reduces spatial interference, so that pseudowired link abstractions form an excellent basis for protocol design; (2) directionality induces deafness, which makes medium access control (mac) based on carrier sensing infeasible. interference analysis in our prior work shows that, in such a setting, coordination between transmitters and receivers, rather than interference management, becomes the key mac performance bottleneck. however, the question of whether such coordination can be achieved in a distributed fashion while achieving high medium utilization, was left open. in this paper, we answer this question in the affirmative, presenting a distributed mac protocol that employs memory to achieve approximate time division multiplexed (tdm) schedules without explicit coordination or resource allocation. the efficacy of the protocol is demonstrated via packet level simulations, while a markov chain fixed-point analysis provides insight into the effect of parameter choices.
improving the scalability of data center networks with traffic-aware virtual machine placement. the scalability of modern data centers has become a practical concern and has attracted significant attention in recent years. in contrast to existing solutions that require changes in the network architecture and the routing protocols, this paper proposes using traffic-aware virtual machine (vm) placement to improve the network scalability. by optimizing the placement of vms on host machines, traffic patterns among vms can be better aligned with the communication distance between them, e.g. vms with large mutual bandwidth usage are assigned to host machines in close proximity. we formulate the vm placement as an optimization problem and prove its hardness. we design a two-tier approximate algorithm that efficiently solves the vm placement problem for very large problem sizes. given the significant difference in the traffic patterns seen in current data centers and the structural differences of the recently proposed data center architectures, we further conduct a comparative analysis on the impact of the traffic patterns and the network architectures on the potential performance gain of traffic-aware vm placement. we use traffic traces collected from production data centers to evaluate our proposed vm placement algorithm, and we show a significant performance improvement compared to existing generic methods that do not take advantage of traffic patterns and data center network characteristics.
throughput analysis of multiple access relay channel under collision model. despite much research on the throughput of relaying networks under idealized interference models, many practical wireless networks rely on physical-layer protocols that preclude the concurrent reception of multiple transmissions. in this work, we develop analytical frameworks for the uplink of a multisource single-channel relay-aided wireless system where transmissions are scheduled to avoid collisions. we study amplify-and-forward and decode-and-forward strategies, in both time-sharing and network-coded variants, and provide mathematical models to investigate their achievable rate regions. both general and optimal power allocations are considered. we also find the cut-set outer bounds for the rate regions. moreover, we present a comparison between these methods with the simple time sharing scheme. our numerical results reveal that optimizing power allocation favors the time sharing scheme significantly more than it does the relaying schemes, so that time sharing under some circumstances can provide higher maximum sum rates, even if the links to the relay have strong channel gains. the proposed analysis provides a means to quantitatively evaluate the efficacy of relaying under the collision model, leading to pragmatic design guidelines.
tree-structured data regeneration in distributed storage systems with regenerating codes. distributed storage systems provide large-scale reliable data storage by storing a certain degree of redundancy in a decentralized fashion on a group of storage nodes. to recover from data losses due to the instability of these nodes, whenever a node leaves the system, additional redundancy should be regenerated to compensate such losses. in this context, the general objective is to minimize the volume of actual network traffic caused by such regenerations. a class of codes, called regenerating codes, has been proposed to achieve an optimal trade-off curve between the amount of storage space required for storing redundancy and the network traffic during the regeneration. in this paper, we jointly consider the choices of regenerating codes and network topologies. we propose a new design, referred to as rctree, that combines the advantage of regenerating codes with a tree-structured regeneration topology. our focus is the efficient utilization of network links, in addition to the reduction of the regeneration traffic. with the extensive analysis and quantitative evaluations, we show that rctree is able to achieve a both fast and stable regeneration, even with departures of storage nodes during the regeneration.
random walks on digraphs: a theoretical framework for estimating transmission costs in wireless routing. in this paper we develop a unified theoretical framework for estimating various transmission costs of packet forwarding in wireless networks. our framework can be applied to the three routing paradigms-best path routing, opportunistic routing, and stateless routing-to which nearly all existing routing protocols belong.we illustrate how packet forwarding under each paradigm can be modeled as random walks on directed graphs (digraphs). by generalizing the theory of random walks that has primarily been developed for undirected graphs to digraphs, we show how various transmission costs can be formulated in terms of hitting times and hitting costs of random walks on digraphs. as representative examples, we apply the theory to three specific routing protocols, one under each paradigm. extensive simulations demonstrate that the proposed digraph based analytical model can achieve more accurate transmission cost estimation over existing methods.
a bit-stuffing algorithm for crosstalk avoidance in high speed switching. motivated by the design of high speed switching fabrics, in this paper we propose a bit-stuffing algorithm for generating forbidden transition codes to mitigate the crosstalk effect between adjacent wires in long on-chip buses. we first model a bus with forbidden transition constraints as a forbidden transition channel, and derive the shannon capacity of such a channel. then we perform a worst case analysis and a probabilistic analysis for the bit-stuffing algorithm. we show by both theoretic analysis and simulations that the coding rate of the bit stuffing encoding scheme for independent and identically distributed (i.i.d.) bernoulli input traffic is quite close to the shannon capacity, and hence is much better than those of the existing forbidden transition codes in the literature, including the fibonacci representation.
enhancing wireless tcp: a serialized-timer approach. in wireless networks, tcp performs unsatisfactorily since packet reordering and random losses may be falsely interpreted as congestive losses. this causes tcp to trigger fast retransmission and fast recovery spuriously, leading to under-utilization of available network resources. in this paper, we propose a novel tcp variant, known as tcp for noncongestive loss (tcp-ncl), to adapt tcp to wireless networks by using more reliable signals of packet loss and network overload for activating packet retransmission and congestion response, separately. tcp-ncl can thus serve as a unified solution for effective congestion control, sequencing control, and loss recovery. different from the existing unified solutions, the modifications involved in the proposed variant are limited to sender-side tcp only, thereby facilitating possible future wide deployment. the two signals employed are the expirations of two serialized timers. a smart tcp sender model has been developed for optimizing the timer expiration periods. our simulation studies reveal that tcp-ncl is robust against packet reordering as well as random packet loss while maintaining responsiveness against situations with purely congestive loss.
achieving secure, scalable, and fine-grained data access control in cloud computing. cloud computing is an emerging computing paradigm in which resources of the computing infrastructure are provided as services over the internet. as promising as it is, this paradigm also brings forth many new challenges for data security and access control when users outsource sensitive data for sharing on cloud servers, which are not within the same trusted domain as data owners. to keep sensitive user data confidential against untrusted servers, existing solutions usually apply cryptographic methods by disclosing data decryption keys only to authorized users. however, in doing so, these solutions inevitably introduce a heavy computation overhead on the data owner for key distribution and data management when fine-grained data access control is desired, and thus do not scale well. the problem of simultaneously achieving fine-grainedness, scalability, and data confidentiality of access control actually still remains unresolved. this paper addresses this challenging open issue by, on one hand, defining and enforcing access policies based on data attributes, and, on the other hand, allowing the data owner to delegate most of the computation tasks involved in fine-grained data access control to untrusted cloud servers without disclosing the underlying data contents. we achieve this goal by exploiting and uniquely combining techniques of attribute-based encryption (abe), proxy re-encryption, and lazy re-encryption. our proposed scheme also has salient properties of user access privilege confidentiality and user secret key accountability. extensive analysis shows that our proposed scheme is highly efficient and provably secure under existing security models.
netscope: practical network loss tomography. we present netscope, a tomographic technique that infers the loss rates of network links from unicast endto-end measurements. netscope uses a novel combination of first- and second-order moments of end-to-end measurements to identify and characterize the links that cannot be (accurately) characterized through existing practical tomographic techniques. using both analytical and experimental tools, we show that netscope enables scalable, accurate link-loss inference: in a simulation scenario involving 4000 links, 20% of them lossy, netscope correctly identifies 94% of the lossy links with a false positive rate of 16%--a significant improvement over the existing alternatives. netscope is robust in the sense that it requires no parameter tuning, moreover its advantage over the alternatives widens when the number of lossy links increases. we also validate netscope's performance on an "internet tomographer" that we deployed on an overlay of 400 planetlab nodes.
csma-based distributed scheduling in multi-hop mimo networks under sinr model. we study the problem of distributed scheduling in multi-hop mimo networks. we first develop a "mimo-pipe" model that provides the upper layers a set of rates and sinr requirements, which capture the rate-reliability tradeoff in mimo communications. the main thrust of this study is then dedicated to developing csma-based mimo-pipe scheduling under the sinr model. we choose the sinr model over the extensively studied matching or protocol-based interference models because it more naturally captures the impact of interference in wireless networks. the coupling among the links caused by the interference makes the problem of devising distributed scheduling algorithms particularly challenging. to that end, we explore csma-based mimo-pipe scheduling, from two perspectives. first, we consider an idealized continuous time csma network. we propose a dual-band approach in which control messages are exchanged instantaneously over a channel separate from the data channel, and show that csma-based scheduling can achieve throughput optimality under the sinr model. next, we consider a discrete time csma network. to tackle the challenge due to the coupling caused by interference, we propose a "conservative" scheduling algorithm in which more stringent sinr constraints are imposed based on the mimo-pipe model. we show that this suboptimal distributed scheduling can achieve an efficiency ratio bounded from below.
flashtrie: hash-based prefix-compressed trie for ip route lookup beyond 100gbps. it is becoming apparent that the next generation ip route lookup architecture needs to achieve speeds of 100- gbps and beyond while supporting both ipv4 and ipv6 with fast real-time updates to accommodate ever-growing routing tables. some of the proposed multibit-trie based schemes, such as tree bitmap [1], have been used in today's high-end routers. however, their large data structure often requires multiple external memory accesses for each route lookup. a pipelining technique is widely used to achieve high-speed lookup with a cost of using many external memory chips. pipelining also often leads to poor memory load-balancing. in this paper, we propose a new ip route lookup architecture called flashtrie that overcomes the shortcomings of the multibit-trie based approach. we use a hash-based membership query to limit off-chip memory accesses per lookup to one and to balance memory utilization among the memory modules. we also develop a new data structure called prefix-compressed trie that reduces the size of a bitmap by more than 80%. our simulation and implementation results show that flashtrie can achieve 160-gbps worst-case throughput while simultaneously supporting 2-m prefixes for ipv4 and 279-k prefixes for ipv6 using one fpga chip and four ddr3 sdram chips. flashtrie also supports incremental real-time updates.
multi-channel assignment in wireless sensor networks: a game theoretic approach. in this paper, we formulate multi-channel assignment in wireless sensor networks (wsns) as an optimization problem and show it is np-hard. we then propose a distributed game based channel assignment algorithm (gbca) to solve the problem. gbca takes into account both the network topology information and transmission routing information. we prove that there exists at least one nash equilibrium in the channel assignment game. furthermore, we analyze the sub-optimality of nash equilibrium and the convergence of the best response in the game. simulation results are given to demonstrate that gbca can reduce interference significantly and achieve satisfactory network performance in terms of delivery ratio, throughput, channel access delay and energy consumption.
improved multi-criteria spanners for ad-hoc networks under energy and distance metrics. this paper studies the problem of topology control in random wireless ad-hoc networks through power assignment for n nodes uniformly distributed in a unit square. in particular, we are interested in asymmetric power assignments so that the induced communication graph has a good distance and energy stretch simultaneously, with additional optimization objectives: both minimizing the total energy consumption, interference level, hop-diameter, and maximizing the network lifetime. we present several power assignments with varying construction time complexity. the probability of our results converges to one as the number of network nodes, n, increases. to the best of our knowledge, these are the first results for spanner construction in wireless ad-hoc networks with provable bounds for both, energy and distance, metrics simultaneously.
sybil attacks against mobile users: friends and foes to the rescue. collaborative applications for co-located mobile users can be severely disrupted by a sybil attack to the point of being unusable. existing decentralized defences have largely been designed for peer-to-peer networks but not for mobile networks. that is why we propose a new decentralized defence for portable devices and call it mobid. the idea is that a device manages two small networks in which it stores information about the devices it meets: its network of friends contains honest devices, and its network of foes contains suspicious devices. by reasoning on these two networks, the device is then able to determine whether an unknown individual is carrying out a sybil attack or not. we evaluate the extent to which mobid reduces the number of interactions with sybil attackers and consequently enables collaborative applications.we do so using real mobility and social network data. we also assess computational and communication costs of mobid on mobile phones.
distributed caching algorithms for content distribution networks. the delivery of video content is expected to gain huge momentum, fueled by the popularity of user-generated clips, growth of vod libraries, and wide-spread deployment of iptv services with features such as catchup/pauselive tv and npvr capabilities. the 'time-shifted' nature of these personalized applications defies the broadcast paradigm underlying conventional tv networks, and increases the overall bandwidth demands by orders of magnitude. caching strategies provide an effective mechanism for mitigating these massive bandwidth requirements by replicating the most popular content closer to the network edge, rather than storing it in a central site. the reduction in the traffic load lessens the required transport capacity and capital expense, and alleviates performance bottlenecks. in the present paper, we develop light-weight cooperative cache management algorithms aimed at maximizing the traffic volume served from cache and minimizing the bandwidth cost. as a canonical scenario, we focus on a cluster of distributed caches, either connected directly or via a parent node, and formulate the content placement problem as a linear program in order to benchmark the globally optimal performance. under certain symmetry assumptions, the optimal solution of the linear program is shown to have a rather simple structure. besides interesting in its own right, the optimal structure offers valuable guidance for the design of low-complexity cache management and replacement algorithms. we establish that the performance of the proposed algorithms is guaranteed to be within a constant factor from the globally optimal performance, with far more benign worstcase ratios than in prior work, even in asymmetric scenarios. numerical experiments for typical popularity distributions reveal that the actual performance is far better than the worst-case conditions indicate.
on constructing efficient shared decision trees for multiple packet filters. multiple packet filters serving different purposes (e.g., firewalling, qos) and different virtual routers are often deployed on a single physical router. the hypercuts decision tree is one efficient data structure for performing packet filter matching in software. constructing a separate hypercuts decision tree for each packet filter is not memory efficient. a natural alternative is to construct shared hypercuts decision trees to more efficiently support multiple packet filters. however, we experimentally show that naively classifying packet filters into shared hypercuts decision trees may significantly increase the memory consumption and the height of the trees. to help decide which subset of packet filters should share a hypercuts decision tree, we first identify a number of important factors that collectively impact the efficiency of the resulted shared hypercuts decision tree. based on the identified factors, we then propose to use machine learning techniques to predict whether any pair of packet filters should share a tree. given the pair-wise prediction matrix, a greedy heuristic algorithm is used to classify packets filters into a number of shared hypercuts decision trees. our experiments using both real packets filters and synthetic packet filters show that the shared hypercuts decision trees consume considerably less memory.
bargaining and price-of-anarchy in repeated inter-session network coding games. most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. however, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. as a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. in this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. we propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. a key challenge is to determine a common cooperative coding rate that the users should mutually agree on. we propose to resolve the conflict of interest among the users through a bargaining process. we derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.
improving qos in bittorrent-like vod systems. in recent years a number of research efforts have focused on effective use of p2p-based systems in providing large scale video streaming services. in particular, live streaming and video-on-demand (vod) systems have attracted much interest. while previous efforts mainly focused on the common challenges faced by both types of applications, there are still a number of fundamental open questions in designing p2p-based vod systems, which is the focus of our effort. specifically, in this paper, we consider a bittorrent-like vod system and focus on the following questions: (1) how the lack of load balance, which typically exists in a p2p-based vod system, affects the performance and what steps can be taken to remedy that, and (2) is a fcfs approach to serving requests at a peer sufficient or whether a deadline-aware scheduling (das) approach can lead to performance improvements. given the deadline considerations that exist in vod systems, we also investigate approaches to avoiding unnecessary queueing time. for each of these questions, we first illustrate deficiencies of current approaches in adequately meeting streaming quality of service requirements. motivated by this, we propose several practical schemes aimed at addressing these questions. to illustrate the benefits of our approach, we present an extensive simulation-based performance study.
deterministic broadcast on multiple access channels. we study broadcasting on multiple access channels by deterministic distributed protocols. data arrivals are governed by an adversary. the power of the adversary is constrained by the average rate of data injection and a bound on the number of different packets that can be injected in one round. the injection rate is at most 1, which forbids the adversary from overloading the channel. we consider a number of deterministic protocols. for each of them we give an upper bound on the worst-case packet latency, as a function of the constraints imposed on the adversary. we present results of experiments by simulations to compare packet latency of the deterministic protocols and of backoff-type randomized protocols. the experiments are carried out in a simulation environment that captures the burstiness of data injection and the resulting traffic by admissibility condition defined by the fraction of active stations and the rate of changing the status of active versus passive among the stations.
predicting prefix availability in the internet. the border gateway protocol (bgp) maintains inter-domain routing information by announcing and withdrawing ip prefixes, possibly resulting in temporary prefix unreachability. prefix availability observed from different vantage points in the internet can be lower than standards promised by service level agreements (slas). in this paper, we develop a framework for predicting long-term prefix availability, given short-duration prefix information from publicly available bgp routing databases. we compare three prediction models, and find that bagged decision trees perform the best when predicting for long future durations, whereas a simple model works well for short prediction durations. we show that mean time to failure and to recovery outperform past availability in terms of their importance for predicting availability for long durations. we also find that predictability is higher in the year 2009, compared to four years earlier. our models allow isps to adjust bgp routing policies if predicted availability is low, and the models are useful for cloud computing systems, p2p, and voip applications.
linear programming models for multi-channel p2p streaming systems. most of the commercial p2p video streaming deployments support hundreds of channels and are referred to as multichannel systems. measurement studies show that bandwidth resources of different channels are highly unbalanced and thus recent research studies have proposed various protocols to improve the streaming qualities for all channels by enabling cross-channel cooperation among multiple channels. however, there is no general framework for comparing existing and potential designs for multi-channel p2p systems. the goal of this paper is to establish tractable models for answering the fundamental question in multi-channel system designs: under what circumstances, should a particular design be used to achieve the desired streaming quality with the lowest implementation complexity? to achieve this goal, we first classify existing and potential designs into three categories, namely naive bandwidth allocation approach (nba), passive channel-aware bandwidth allocation approach (pca) and active channel-aware bandwidth allocation approach (aca). then, we define the bandwidth satisfaction ratio as a performance metric to develop linear programming models for the three designs. the proposed models are independent of implementations and can be efficiently solved due to the linear property, which provides a way of numerically exploring the design space of multi-channel systems and developing closedform solutions for special systems.
fuzzy keyword search over encrypted data in cloud computing. as cloud computing becomes prevalent, more and more sensitive information are being centralized into the cloud. for the protection of data privacy, sensitive data usually have to be encrypted before outsourcing, which makes effective data utilization a very challenging task. although traditional searchable encryption schemes allow a user to securely search over encrypted data through keywords and selectively retrieve files of interest, these techniques support only exact keyword search. that is, there is no tolerance of minor typos and format inconsistencies which, on the other hand, are typical user searching behavior and happen very frequently. this significant drawback makes existing techniques unsuitable in cloud computing as it greatly affects system usability, rendering user searching experiences very frustrating and system efficacy very low. in this paper, for the first time we formalize and solve the problem of effective fuzzy keyword search over encrypted cloud data while maintaining keyword privacy. fuzzy keyword search greatly enhances system usability by returning the matching files when users' searching inputs exactly match the predefined keywords or the closest possible matching files based on keyword similarity semantics, when exact match fails. in our solution, we exploit edit distance to quantify keywords similarity and develop an advanced technique on constructing fuzzy keyword sets, which greatly reduces the storage and representation overheads. through rigorous security analysis, we show that our proposed solution is secure and privacy-preserving, while correctly realizing the goal of fuzzy keyword search.
file fragmentation over an unreliable channel. it has been recently discovered that heavy-tailed file completion time can result from protocol interaction even when file sizes are light-tailed. a key to this phenomenon is the restart feature where if a file transfer is interrupted before it is completed, the transfer needs to restart from the beginning. in this paper, we show that independent or bounded fragmentation guarantees light-tailed file completion time as long as the file size is light-tailed, i.e., in this case, heavy-tailed file completion time can only originate from heavy-tailed file sizes. if the file size is heavy-tailed, then the file completion time is necessarily heavy-tailed. for this case, we show that when the file size distribution is regularly varying, then under independent or bounded fragmentation, the completion time tail distribution function is asymptotically upper bounded by that of the original file size stretched by a constant factor. we then prove that if the failure distribution has non-decreasing failure rate, the expected completion time is minimized by dividing the file into equal sized fragments; this optimal fragment size is unique but depends on the file size. we also present a simple blind fragmentation policy where the fragment sizes are constant and independent of the file size and prove that it is asymptotically optimal. finally, we bound the error in expected completion time due to error in modeling of the failure process.
link homophily in the application layer and its usage in traffic classification. we address the following questions. is there link homophily in the application layer traffic? if so, can it be used to accurately classify traffic in network trace data without relying on payloads or properties at the flow level? our research shows that the answers to both of these questions are affirmative in real network trace data. specifically, we define link homophily to be the tendency for flows with common ip hosts to have the same application (p2p, web, etc.) compared to randomly selected flows. the presence of link homophily in trace data provides us with statistical dependencies between flows that share common ip hosts. we utilize these dependencies to classify application layer traffic without relying on payloads or properties at the flow level. in particular, we introduce a new statistical relational learning algorithm, called neighboring link classifier with relaxation labeling (nlc+rl). our algorithm has no training phase and does not require features to be constructed. all that it needs to start the classification process is traffic information on a small portion of the initial flows, which we refer to as seeds. in all our traces, nlc+rl achieves above 90% accuracy with less than 5% seed size; it is robust to errors in the seeds and various seed-selection biases; and it is able to accurately classify challenging traffic such as p2p with over 90% precision and recall.
non-asymptotic delay bounds for networks with heavy-tailed traffic. traffic with self-similar and heavy-tailed characteristics has been widely reported in networks, yet, only few analytical results are available for predicting the delay performance of such networks. we address a particularly difficult type of heavy-tailed traffic where only the first moment can be computed, and present the first non-asymptotic end-to-end delay bounds for such traffic. the derived performance bounds are non-asymptotic in that they do not assume a steady state, large buffer, or many sources regime. our analysis considers a multihop path of fixed-capacity links with heavy-tailed self-similar cross traffic at each node. a key contribution of the analysis is a probabilistic sample-path bound for heavy-tailed arrival and service processes, which is based on a scale-free sampling method. we explore how delays scale as a function of the length of the path, and compare them with lower bounds. a comparison with simulations illustrates pitfalls when simulating self-similar heavytailed traffic, providing further evidence for the need of analytical bounds.
a privacy-preserving scheme for online social networks with efficient revocation. online social networks (osns) are attractive applications which enable a group of users to share data and stay connected. facebook, myspace, and twitter are among the most popular applications of osns where personal information is shared among group contacts. due to the private nature of the shared information, data privacy is an indispensable security requirement in osn applications. in this paper, we propose a privacy-preserving scheme for data sharing in osns, with efficient revocation for deterring a contact's access right to the private data once the contact is removed from the social group. in addition, the proposed scheme offers advanced features such as efficient search over encrypted data files and dynamic changes to group membership. with slight modification, we extend the application of the proposed scheme to anonymous online social networks of different security and functional requirements. the proposed scheme is demonstrated to be secure, effective, and efficient.
optimal waveband switching in optical ring networks. waveband switching saves port costs in optical crossconnects by grouping together a set of consecutive wavelengths and switching them as a single waveband. previous work has focused on either uniform band sizes or non-uniform band sizes considering a single node. in this paper, we show that such solutions are inadequate when considering the entire network, and present a novel framework for optimizing the number of wavebands in a ring network for deterministic traffic. we then consider a specific type of traffic, namely, all-to-all traffic and present bounds and heuristic solutions for the problem. our results show that the number of ports can be reduced by a large amount using waveband switching compared to wavelength switching. we also numerically evaluate the performance of our waveband design algorithms under dynamic stochastic traffic.
pattern mutation in wireless sensor deployment. in this paper, we study the optimal deployment pattern problem in wireless sensor networks (wsns). we propose a new set of patterns, particularly when sensors' communication range (rc) is relatively small compared with their sensing range (rs), and prove their optimality among regular patterns. in this study, we discover a surprising and interesting phenomenon-- pattern mutation. this phenomenon contradicts the conjecture presented in a previous work that there exists a universal elemental pattern among optimal pattern evolution and that pattern evolution is continuous. for example, we find mutation happens among the patterns for full-coverage and 3-connectivity when rc/rs = 1.0459, among the patterns for full-coverage and 4- connectivity when rc/rs = 1.3903, and among the patterns for full-coverage and 5-connectivity when rc/rs = 1.0406. to the best of our knowledge, this is the first time that mutation in pattern evolution has been discovered. also, our work further completes the exploration of optimal patterns in wsns.
on the aggregatability of router forwarding tables. the rapid growth of global routing tables has raised concerns among many internet service providers. the most immediate concern regarding routing scalability is the size of the forwarding information base (fib), which seems to be growing at a faster pace than router hardware can support. this paper focuses on one potential solution to this problem - fib aggregation, i.e., aggregating fib entries without affecting the forwarding paths taken by data traffic. compared with alternative solutions to the routing scalability problem, fib aggregation is particularly appealing because it is a purely local software optimization limited within a router, requiring no changes to routing protocols or router hardware. to understand the feasibility of using fib aggregation to extend router lifetime, we present several fib aggregation algorithms and evaluate their performance using routing tables and updates from tens of networks. we find that fib aggregation can reduce the fib table size by as much as 70% with small computational overhead. we also show that the computational overhead can be controlled through various mechanisms.
secure wireless communication with dynamic secrets. this paper introduces a set of low-complexity algorithms that when coupled with link layer retransmission mechanisms, strengthen wireless communication security. our basic idea is to generate a series of secrets from inevitable transmission errors and other random factors in wireless communications. because these secrets are constantly extracted from the communication process in realtime, we call them dynamic secrets. dynamic secrets have interesting security properties. they offer a complementary mechanism to existing security protocols. even if the adversary exploits a vulnerability and steals the underlying system secret, security can be automatically replenished. in many scenarios, it is also possible to bootstrap a secure communication with the dynamic secrets.
an opportunistic batch bundle authentication scheme for energy constrained dtns. bundle authentication is a critical security service in delay tolerant networks (dtns) that ensures authenticity and integrity of bundles during multi-hop transmissions. public key signatures, which have been suggested in existing bundle security protocol specification, achieve bundle authentication at the cost of an increased computational, transmission overhead and a higher energy consumption, which is not desirable for energy-constrained dtns. on the other hand, the unique "store-carry-and-forward" transmission characteristic of dtns implies that bundles from distinct/common senders can be buffered opportunistically at some common intermediate nodes. this "buffering" characteristic distinguishes dtn from any other traditional wireless networks, for which an intermediate cache is not supported. to exploit such a buffering characteristic, in this paper, we propose an opportunistic batch bundle authentication scheme (obba) to achieve efficient bundle authentication. the proposed scheme adopts batch verification techniques, allowing a computational overhead to be bounded by the number of opportunistic contacts instead of the number of messages. furthermore, we introduce a novel concept of a fragment authentication tree to minimize communication cost by choosing an optimal tree height. finally, we implement obba in a specific dtn scenario setting: pocket-switched networks on campus. the simulation results in terms of computation time, transmission overhead and power consumption are given to demonstrate the efficiency and effectiveness of the proposed schemes.
an auction framework for spectrum allocation with interference constraint in cognitive radio networks. extensive research in recent years has shown the benefits of cognitive radio technologies to improve the flexibility and efficiency of spectrum utilization. this new communication paradigm, however, requires a well-designed spectrum allocation mechanism. in this paper, we propose an auction framework for cognitive radio networks to allow unlicensed secondary users (sus) to share the available spectrum of licensed primary users (pus) fairly and efficiently, subject to the interference temperature constraint at each pu. to study the competition among sus, we formulate a non-cooperative multiple-pu multiple-su auction game and study the structure of the resulting equilibrium by solving a non-continuous two-dimensional optimization problem. a distributed algorithm is developed in which each su updates its strategy based on local information to converge to the equilibrium. we then extend the proposed auction framework to the more challenging scenario with free spectrum bands. we develop an algorithm based on the no-regret learning to reach a correlated equilibrium of the auction game. the proposed algorithm, which can be implemented distributedly based on local observation, is especially suited in decentralized adaptive learning environments as cognitive radio networks. finally, through numerical experiments, we demonstrate the effectiveness of the proposed auction framework in achieving high efficiency and fairness in spectrum allocation.
compactdfa: generic state machine compression for scalable pattern matching. pattern matching algorithms lie at the core of all contemporary intrusion detection systems (ids), making it intrinsic to reduce their speed and memory requirements. this paper focuses on the most popular class of pattern-matching algorithms, the aho-corasick-like algorithms, which are based on constructing and traversing a deterministic finite automaton (dfa), representing the patterns. while this approach ensures deterministic time guarantees, modern idss need to deal with hundreds of patterns, thus requiring to store very large dfas which usually do not fit in fast memory. this results in a major bottleneck on the throughput of the ids, as well as its power consumption and cost. we propose a novel method to compress dfas by observing that the name of the states is meaningless. while regular dfas store separately each transition between two states, we use this degree of freedom and encode states in such a way that all transitions to a specific state can be represented by a single prefix that defines a set of current states. our technique applies to a large class of automata, which can be categorized by simple properties. then, the problem of pattern matching is reduced to the well-studied problem of longest prefix matching (lpm) that can be solved either in tcam, in commercially available ip-lookup chips, or in software. specifically, we show that with a tcam our scheme can reach a throughput of 10 gbps with low power consumption.
resource allocation in multi-cell ofdma-based relay networks. cooperative relay networks combined with orthogonal frequency division multiplexing access (ofdma) technology has been widely recognized as a promising candidate for future cellular infrastructure due to the performance enhancement by flexible resource allocation schemes. the majority of the existing schemes aim to optimize single cell performance gain. however, the higher frequency reuse factor and smaller cell size requirement lead to severe inter-cell interference problem. therefore, the multi-cell resource allocation of subcarrier, time scheduling and power should be jointly considered to alleviate the severe inter-cell interference problem. in this paper, the joint resource allocation problem is formulated. considering the high complexity of the optimal solution, a two-stage resource allocation scheme is proposed. in the first stage, all of the users in each cell are selected sequentially and the joint subcarrier allocation and scheduling is conducted for the selected users without considering the interference. in the second stage, the optimal power control is performed by geometric programming method. simulation results show that the proposed the interference-aware resource allocation scheme improves the system capacity compared with existing schemes. especially, the edge users achieve more benefit.
counting rfid tags efficiently and anonymously. radio frequency identification (rfid) technology has attracted much attention due to its variety of applications, e.g., inventory control and object tracking. one important problem in rfid systems is how to quickly estimate the number of distinct tags without reading each tag individually. this problem plays a crucial role in many real-time monitoring and privacy-preserving applications. in this paper, we present an efficient and anonymous scheme for tag population estimation. this scheme leverages the position of the first reply from a group of tags in a frame. results from mathematical analysis and extensive simulation demonstrate that our scheme outperforms other protocols proposed in the previous work.
on the absence of isolated nodes in wireless ad-hoc networks with unreliable links - a curious gap. we consider an extension to the disk model in one dimension where communication links established between nodes may fail. with the help of the method of first and second moments, we investigate the zero-one laws for the property that there are no isolated nodes in the underlying random graph. two specific situations are discussed: for the unit circle we prove a full zero-one law and determine its critical scaling. for the unit interval we derive a zero-law and a one-law which capture deviations from different critical scalings; a completely symmetric zero-one law is established under an additional condition. analysis and simulations both indicate the possible presence of a gap between the one-law critical scalings for the unit interval and the unit circle. this discrepancy is quite surprising given that the zeroone laws for the absence of isolated nodes are identical in the geometric random graphs on the unit interval and on the unit circle. connections to recent results by yi et al. are discussed.
wormhole-resilient secure neighbor discovery in underwater acoustic networks. neighbor discovery is a fundamental requirement and need be done frequently in underwater acoustic networks (uans) with floating node mobility. in hostile environments, neighbor discovery is vulnerable to the wormhole attack by which the adversary uses secret wormhole links to make distant nodes falsely accept each other as a neighbor. the wormhole attack may lead to many undesirable consequences and cannot be solved by cryptographic methods. existing wormhole defenses for ground wireless networks cannot be directly applied to uans where most of their assumptions no longer hold. this paper presents a suite of novel protocols to enable wormhole-resilient secure neighbor discovery in uans. our protocols are based on the direction of arrival (doa) estimation of acoustic signals, a basic functionality readily available in current uans. the proposed protocols can thwart the wormhole attack with overwhelming probability without conventional hard requirements on secure and accurate time synchronization and localization. detailed theoretical analysis and simulation results confirm the high performance of the proposed protocols.
measurement data reduction through variation rate metering. we present an efficient network measurement primitive that measures the rate of variations, or unique values for a given characteristic of a traffic flow. the primitive is widely applicable to a variety of data reduction and pre-analysis tasks at the measurement interface, and we show it to be particularly useful for building data-reducing preanalysis stages for scan detection within a multistage network analysis architecture. the presented approach is based upon data structures derived from bloom filters, and as such yields high performance with probabilistic accuracy and controllable worst-case time and memory complexity. this predictability makes it suitable for hardware implementation in dedicated network measurement devices. one key innovation of the present work is that it is self-tuning, adapting to the characteristics of the measured traffic.
bgp skeleton - an alternative to ibgp route reflection. the internet is a composition of ases (autonomous systems), bgp (border gateway protocol) is the routing protocol that is responsible of exchanging routes between these ases. it operates in two modes: external bgp (ebgp) and internal bgp (ibgp). ebgp exchanges routing information between ases, while ibgp propagates that information within the as. bgp full mesh solution (fms) is based on that all the asbrs (autonomous system border routers) should be fully meshed and each internal node should have an ibgp session with all of them. this was because an ibgp node does not have the ability to reflect routes. bgp route reflection was widely employed as an alternative to full mesh to reduce the needed number of ibgp sessions and, in turn, increase the scalability inside the as. under particular configuration, it introduces persistent route oscillation, forwarding loops, and non-optimal egress nodes. skeleton is an alternative to route reflection that overcomes these routing anomalies. skeleton is a subgraph of the physical graph with the same set of nodes, its edges are the ibgp sessions between the nodes. all skeleton nodes have the ability of reflecting routes. skeleton eliminates the use of clusters and establishes ibgp sessions only between single hop neighbors. we prove that it holds the sufficient correctness conditions as well as its robustness against med induced oscillations. we evaluate it on five real world topologies and find that the number of ibgp sessions has a linear relationship with the number of asbrs, where in fms this relationship is quadratic.
overhearing-aware joint routing and rate selection in multi-hop multi-rate uwb-based wpans. ultra-wideband (uwb) communications has emerged as a promising technology for high data rate wireless personal area networks (wpans). in this paper, we address a key issue that impacts the performance of multi-hop, multi-rate uwb-based wpans, namely joint routing and rate selection. arbitrary selection of routes (including direct links) and transmission rates along these routes results in unnecessarily long channel reservation time and high blocking rate for prospective reservations, and leads to low network throughput. to remedy this situation, we propose a novel overhearing-aware joint routing and rate selection (orrs) scheme, which improves the network throughput by exploiting the dependence between the channel reservation time and the multi-rate capability of an uwb system. at the same time, orrs takes advantage of packet overhearing, a typical characteristic of broadcast communications. for a given source-destination pair, orrs aims at selecting a path and its transmission rates that achieve the minimum reservation time, leading to low blocking rate for prospective reservations and high network throughput. we show that achieving this goal while simultaneously exploiting packet overhearing and satisfying a target packet delivery probability over the selected route leads to an np-hard problem. accordingly, orrs resorts to approximate solutions (proactive and reactive) to find a near-optimal result with reasonable computational/communication overhead. we further propose other variants that exploit packet overhearing in different ways to improve orrs performance.
arbor: hang together rather than hang separately in 802.11 wifi networks. with 802.11 wifi networks becoming popular in homes, it is common for an end-user to have access to multiple wifi access points (aps) from residents next door. in general, wireless networks have much higher bandwidth than residential internet (dsl or cable) connections. this provides an incentive for an end-user to simultaneously harness bandwidths from multiple aps. this paper introduces arbor, an 802.11 driver that aggregates broadband connections in a neighborhood and maximizes internet access bandwidth in a secure manner. arbor has four important characteristics. first, arbor can sustain a much longer switching cycle without losing packets queued at different aps. second, it can schedule traffic loads and (in)directly aggregate ap backhaul bandwidths. third, arbor designs and implements a light-weight authentication mechanism that provides sufficient amount of security, and at the same time, ensures fast switching time. finally, arbor is transparent to the upper layers of the network stack. a prototype of arbor has been implemented and extensively evaluated. experiment results show that arbor provides significantly better throughput gains and lower internet access delays.
efficient continuous scanning in rfid systems. rfid is an emerging technology with many potential applications such as inventory management for supply chain. in practice, these applications often need a series of continuous scanning operations to accomplish a task. for example, if one wants to scan all the products with rfid tags in a large warehouse, given a limited reading range of an rfid reader, multiple scanning operations have to be launched at different locations to cover the whole warehouse. usually, this series of scanning operations are not completely independent as some rfid tags can be read by multiple processes. simply scanning all the tags in the reading range during each process is inefficient because it collects a lot of redundant data and consumes a long time. in this paper, we develop efficient schemes for continuous scanning operations defined in both spatial and temporal domains. our basic idea is to fully utilize the information gathered in the previous scanning operations to reduce the scanning time of the succeeding ones. we illustrate in the evaluation that our algorithms dramatically reduce the total scanning time when compared with other solutions.
delay-based network utility maximization. it is well known that max-weight policies based on a queue backlog index can be used to stabilize stochastic networks, and that similar stability results hold if a delay index is used. using lyapunov optimization, we extend this analysis to design a utility maximizing algorithm that uses explicit delay information from the head-of-line packet at each user. the resulting policy is shown to ensure deterministic worst-case delay guarantees, and to yield a throughput-utility that differs from the optimally fair value by an amount that is inversely proportional to the delay guarantee. our results hold for a general class of 1-hop networks, including packet switches and multi-user wireless systems with time varying reliability.
on order gain of backoff misbehaving nodes in csma/ca-based wireless networks. backoff misbehavior, in which a wireless node deliberately manipulates its backoff time, can induce significant network problems, such as severe unfairness and denial-ofservice. although great progress has been made towards the design of countermeasures to backoff misbehavior, little attention has been focused on quantifying the gain of backoff misbehaviors. in this paper, we define and study two general classes of backoff misbehavior to assess the gain that misbehaving nodes can obtain. the first class, called continuous misbehavior, keeps manipulating the backoff time unless it is disabled by countermeasures. the second class is referred to as intermittent misbehavior, which tends to evade the detection by countermeasures by performing misbehavior sporadically. our approach is to introduce a new performance metric, namely order gain, which is to characterize the performance benefits of misbehaving nodes in comparison to legitimate nodes. through analytical studies, simulations, and experiments, we demonstrate the impact of a wide range of backoff misbehaviors on network performance with respect to the number of users in csma/ca-based wireless networks.
asymmetry-aware real-time distributed joint resource allocation in ieee 802.22 wrans. in ieee 802.22 wireless regional area networks (wrans), each base station (bs) solves a complex resource allocation problem of simultaneously determining the channel to reuse, power for adaptive coverage, and consumer premise equipments (cpes) to associate with, while maximizing the total downstream capacity of cpes. although joint power and channel allocation is a classical problem, resource allocation in wrans faces two unique challenges that has not yet been addressed: (1) the presence of small-scale incumbents such as wireless microphones (wms), and (2) asymmetric interference patterns between bss using omnidirectional antennas and cpes using directional antennas. in this paper, we capture this asymmetry in upstream/downstream communications to propose an accurate and realistic wran-wm coexistence model that increases spatial reuse of tv spectrum while protecting small-scale incumbents. based on the proposed model, we formulate the resource-allocation problem as a mixed-integer nonlinear programming (minlp) which is np-hard. to solve the problem in real-time, we propose a suboptimal algorithm based on the genetic algorithm (ga), and extend the basic ga algorithm to a fully-distributed ga algorithm (dga) that distributes computational cost over the network and achieves scalability via local cooperation between neighboring bss. using extensive simulation, the proposed dga is shown to perform as good as 99.4-99.8% of the optimal solution, while reducing the computational cost significantly.
multihop transmission opportunity in wireless multihop networks. wireless multihop communication is becoming more important due to the increasing popularity of wireless sensor networks, wireless mesh networks, and mobile social networks. they are distinguished from conventional multihop networks in terms of scale, traffic intensity and/or node density. being readily-available in most of 802.11 radios, multirate facility appears to be useful to address some of these issues and is particularly helpful in high-density scenarios where inter-node distance is short, demanding a prudent multirate adaptation algorithm. however, communication at high bit rates mandates a large number of hops for a given node pair and thus, can easily be depreciated as per-hop overhead at several layers of network protocol is aggregated over the increased number of hops. this paper presents a novel multihop, multirate adaptation mechanism, called multihop transmission opportunity (mtop), that allows a frame to be forwarded a number of hops consecutively but reduces the mac-layer overhead between hops. this seemingly collision-prone multihop forwarding is proven to be safe via analysis and usrp/gnu radio-based experiment. the idea of mtop is in clear contrast to, but not mutually exclusive with, the conventional opportunistic transmission mechanism, referred to as txop, where a node transmits multiple frames back-to-back when it gets an opportunity. we conducted an extensive simulation study via ns-2, demonstrating the performance advantage of mtop under a wide range of network scenarios.
on distributed time-dependent shortest paths over duty-cycled wireless sensor networks. we revisit the shortest path problem in asynchronous duty-cycled wireless sensor networks, which exhibit time-dependent features. we model the time-varying link cost and distance from each node to the sink as periodic functions. we show that the time-cost function satisfies the fifo property, which makes the time-dependent shortest path problem solvable in polynomial-time. using the β-synchronizer, we propose a fast distributed algorithm to build all-to-one shortest paths with polynomial message complexity and time complexity. the algorithm determines the shortest paths for all discrete times with a single execution, in contrast with multiple executions needed by previous solutions. we further propose an efficient distributed algorithm for time-dependent shortest path maintenance. the proposed algorithm is loop-free with low message complexity and low space complexity of o(maxdeg), where maxdeg is the maximum degree for all nodes. the performance of our solution is evaluated under diverse network configurations. the results suggest that our algorithm is more efficient than previous solutions in terms of message complexity and space complexity.
markov approximation for combinatorial network optimization. many important network design problems can be formulated as a combinatorial optimization problem. a large number of such problems, however, cannot readily be tackled by distributed algorithms. the markov approximation framework studied in this paper is a general technique for synthesizing distributed algorithms. we show that when using the log-sum-exp function to approximate the optimal value of any combinatorial problem, we end up with a solution that can be interpreted as the stationary probability distribution of a class of timereversible markov chains. certain carefully designed markov chains among this class yield distributed algorithms that solve the log-sum-exp approximated combinatorial network optimization problem. by three case studies, we illustrate that markov approximation technique not only can provide fresh perspective to existing distributed solutions, but also can help us generate new distributed algorithms in various domains with provable performance. we believe the markov approximation framework will find applications in many network optimization problems, and this paper serves as a call for participation.
approximate models for general cache networks. many systems employ caches to improve performance. while isolated caches have been studied in-depth, multicache systems are not well understood, especially in networks with arbitrary topologies. in order to gain insight into and manage these systems, a low-complexity algorithm for approximating their behavior is required. we propose a new algorithm, termed a-net, that approximates the behavior of multi-cache networks by leveraging existing approximation algorithms for isolated lru caches. we demonstrate the utility of a-net using both per-cache and network-wide performance measures.we also perform factor analysis of the approximation error to identify system parameters that determine the precision of a-net.
on the impact of mobility on multicast capacity of wireless networks. analogous to the beneficial impact that mobility has on the throughput of unicast networks, this paper establishes that mobility can provide a similar gain in the order-wise growth-rate of the throughput for multicast networks. this paper considers an all-mobile multicast network, and characterizes its multicast capacity scaling. the scaling result shows that the growth-rate of the throughput in the all-mobile multicast network is order-wise higher compared to the all-static multicast network. further, the paper considers a static-mobile hybrid multicast network, and establishes that, if there are sufficient number of mobile nodes (that is order-wise smaller than the total number of nodes) in the network, then mobile nodes can enhance the order behavior of the multicast throughput.
recognizing exponential inter-contact time in vanets. inter-contact time between moving vehicles is one of the key metrics in vehicular ad hoc networks (vanets) and central to forwarding algorithms and the end-to-end delay. due to prohibitive costs, little work has conducted experimental study on inter-contact time in urban vehicular environments. in this paper, we carry out an extensive experiment involving thousands of operational taxies in shanghai city. studying the taxi trace data on the frequency and duration of transfer opportunities between taxies, we observe that the tail distribution of the inter-contact time, that is the time gap separating two contacts of the same pair of taxies, exhibits a light tail such as one of an exponential distribution, over a large range of timescale. this observation is in sharp contrast to recent empirical data studies based on human mobility, in which the distribution of the inter-contact time obeys a power law. by performing a least squares fit, we establish an exponential model that can accurately depict the tail behavior of the inter-contact time in vanets. our results thus provide fundamental guidelines on design of new vehicular mobility models in urban scenarios, new data forwarding protocols and their performance analysis.
on computing compression trees for data collection in wireless sensor networks. we address the problem of efficiently gathering correlated data from a wireless sensor network, with the aim of designing algorithms with provable optimality guarantees, and understanding how close we can get to the known theoretical lower bounds. our proposed approach is based on finding an optimal or a near-optimal compression tree for a given sensor network: a compression tree is a directed tree over the sensor network nodes such that the value of a node is compressed using the value of its parent. we focus on broadcast communication model in this paper, but our results are more generally applicable to a unicast communication model as well. we draw connections between the data collection problem and a previously studied graph concept called weakly connected dominating sets, and we use this to develop novel approximation algorithms for the problem. we present comparative results on several synthetic and real-world datasets showing that our algorithms construct near-optimal compression trees that yield a significant reduction in the data collection cost.
an optimal key distribution scheme for secure multicast group communication. many ip multicast-based applications, such as multimedia conferencing, multiplayer games, require controlling the group memberships of senders and receivers. one common solution is to encrypt the data with a session key shared with all authorized senders/receivers. to efficiently update the session key in the event of member removal, many rooted-tree based group key distribution schemes have been proposed. however, most of the existing rooted-tree based schemes are not optimal. in other words, given the o(logn) storage overhead, the communication overhead is not minimized. on the other hand, although flat table scheme [1] achieves optimality [2], it is rather dismissed due to the vulnerability to collusion attacks. in this paper, we propose a key distribution scheme - egk that attains the same optimality as flat table without collusion vulnerability. additionally, egk provides constant message size and requires o(logn) storage overhead at the group controller, which makes egk suitable for applications containing a large number of multicasting group members. moreover, adding members in egk requires just one multicasting message. egk is the first work with such features and out-performs all existing schemes.
opportunistic routing with congestion diversity in wireless multi-hop networks. this paper considers the problem of routing packets across a multi-hop network consisting of multiple sources of traffic and wireless links with stochastic reliability while ensuring bounded expected delay. each packet transmission can be overheard by a random subset of receiver nodes among which the next relay is selected opportunistically. the main challenge in the design of minimum-delay routing policies is balancing the trade-off between routing the packets along the shortest paths to the destination and distributing traffic across the network. opportunistic variants of shortest path routing may, under heavy traffic scenarios, result in severe congestion and unbounded delay. while the opportunistic variants of backpressure, which ensure a bounded expected delay, are known to exhibit poor delay performance at low to medium traffic conditions. combining important aspects of shortest path routing with those of backpressure routing, this paper provides an opportunistic routing policy with congestion diversity (orcd). orcd uses a measure of draining time to opportunistically identify and route packets along the paths with an expected low overall congestion. previously, orcd was proved to ensure a bounded expected delay for all networks and under any admissible traffic (without any knowledge of traffic statistics). this paper proposes practical implementations and discusses criticality of various aspects of the algorithm. furthermore, the expected delay encountered by the packets in the network under orcd is compared against known existing routing policies via simulations where substantial improvements are observed.
multicast scaling laws with hierarchical cooperation. a new class of scheduling policies for multicast traffic are proposed in this paper. by utilizing hierarchical cooperative mimo transmission, our new policies can obtain an aggregate throughput of ω(n/k)1-ε) for any ε gt; 0. this achieves a gain of nearly√n/k compared with non-cooperative scheme in [19]. between the two cooperative strategies in our paper, the converge-based one is superior to the other on delay, while the throughput and energy consumption performances are nearly the same. moreover, to schedule the traffic in a converge multicast manner instead of the simple multicast, we can dramatically reduce the delay by a factor nearly (n/k)h/2, where h gt; 1 is the number of the hierarchical layers. our optimal cooperative strategy achieves an approximate delay-throughput tradeoff d(n, k)/t (n, k) = θ(k) when h ∞. this tradeoff ratio is identical to that of non-cooperative scheme, while the throughput performance is greatly improved. besides, for certain k and h, the tradeoff ratio is even better than that of unicast.
chorus: collision resolution for efficient wireless broadcast. traditional wireless broadcast protocols rely heavily on the 802.11-based csma/ca model, which avoids interference and collision by conservatively scheduling transmissions. while csma/ca is amenable to multiple concurrent unicasts, it tends to degrade broadcast performance, especially when there are a large number of nodes and links are lossy. in this paper, we propose a new, drastically different protocol called chorus that improves the efficiency and scalability of broadcast service with a mac layer that allows packet collisions. chorus is built upon the observation that packets carrying the same data can be effectively detected and decoded, even when they overlap in time and have comparable signal strength. it performs collision resolution using symbol-level iterative decoding, and then combines the resolved symbols to reconstruct the packet. this collision-tolerant mechanism significantly improves the transmission diversity and spatial reuse in wireless broadcast, providing an asymptotic broadcast delay that is proportional to the network radius. this advantage is exploited further by chorus's mac-layer cognitive sensing and scheduling scheme. we evaluate chorus with symbol-level simulation, and validate its network-level performance via ns-2, in comparison with a typical csma/ca broadcast protocol.
malicious hubs: detecting abnormally malicious autonomous systems. while many attacks are distributed across botnets, investigators and network operators have recently targeted malicious networks through high profile autonomous system (as) de-peerings and network shut-downs. in this paper, we explore whether some ases indeed are safe havens for malicious activity. we look for isps and ases that exhibit disproportionately high malicious behavior using 12 popular blacklists. we find that some ases have over 80% of their routable ip address space blacklisted and others account for large fractions of blacklisted ips. overall, we conclude that examining malicious activity at the as granularity can unearth networks with lax security or those that harbor cybercrime.
a general algorithm for interference alignment and cancellation in wireless networks. physical layer techniques have come a long way and can achieve close to shannon capacity for single point to-point transmissions. it is apparent that, to further improve network capacity significantly, we have to resort to concurrent transmissions. multiple concurrent transmission techniques (e.g., zero forcing, interference alignment and distributed mimo) are proposed in which multiple senders jointly encode signals to multiple receivers so that interference is aligned or canceled and each receiver is able to decode its desired information. in this paper, we formulate the interference alignment and cancellation problem in multi-hop mesh networks. we show that the problem is np-hard in general. we then propose a convex programming based algorithm to identify interference alignment and cancellation opportunities. our algorithm effectively utilizes knowledge of both local network topology and overheard packets at the sender side as well as the receiver side. we implement our system using gnu radio to evaluate key practical implementation issues.
minimizing the worst-case playback delay in vod services over passive optical networks. minimizing the worst-case playback delay (wpd) in vod services is both critical and challenging. given a fixed amount of bandwidth for broadcasting and patching, there is no prior work on determining the minimum wpd, let alone guaranteeing it. in this work, we propose novel schemes that leverage the unique properties of a tdm-based passive optical network (pon) by performing rebroadcasting and patching at its optical network unit (onus). for a given bandwidth available for vod services in the pon, we derive the minimum worst-case playback delay (wpd), and also design optimal patch scheduling algorithm as well as onu rebroadcast and patching channel assignment to guarantee such minimum wpd. numerical results confirm the superiority of the proposed schemes over the existing ones in terms of both worst-case and average performance.
haste: practical online network coding in a multicast switch. the use of network coding has been shown to improve throughput in input-queued multicast switches, but not without costs of computational complexity and delays. in this paper, we investigate the design of efficient online network coding algorithms in a switch with multicast traffic. we present haste, an online opportunistic coding algorithm designed to streamline the computation when network coding is involved in a network switch with multicast traffic. haste enjoys the advantage of incurring no decoding delays, which reduces packet delays compared with existing network coding algorithms on switches. we have conducted extensive simulations to show the efficiency of haste, and implemented an emulation framework to emulate input-queued switches using asynchronous network sockets. our emulation framework is able to process actual udp traffic using haste with online network coding, and to show convincing evidence that haste is suitable for practical use, and is beneficial in multicast switches.
the capacity of ad hoc networks with heterogeneous traffic using cooperation. we study the scaling laws for wireless ad hoc networks in which the distribution of n nodes in the network is homogeneous but the traffic they carry is heterogeneous. more specifically, we consider the case in which a given node is the data-gathering sink for k sources sending different information to it, while the rest of the s = n-k nodes participate in unicast sessions with random destinations chosen uniformly. we present a separation theorem for heterogeneous traffic showing that the optimum order throughput capacity can be attained in a wireless network in which traffic classes are distributed uniformly by endowing each node with multiple radios, each operating in a separate orthogonal channel, and by allocating a radio per node to each traffic class. based on this theorem, we show how this order capacity can be attained for the unicast and data-gathering traffic classes by extending cooperative communication schemes that have been proposed previously.
mobicent: a credit-based incentive system for disruption tolerant network. when disruption tolerant network (dtn) is used in commercial environments, incentive mechanism should be employed to encourage cooperation among selfish mobile users. key challenges in the design of an incentive scheme for dtn are that disconnections among nodes are the norm rather than exception and network topology is time varying. thus, it is difficult to detect selfish actions that can be launched by mobile users or to pre-determine the routing path to be used. in this paper, we propose mobicent, a credit-based incentive system for dtn. while mobicent allows the underlying routing protocol to discover the most efficient paths, it is also incentive compatible. therefore, using mobicent, rational nodes will not purposely waste transfer opportunity or cheat by creating non-existing contacts to increase their rewards. mobicent also provides different payment mechanisms to cater to client that wants to minimize either payment or data delivery delay.
q-csma: queue-length based csma/ca algorithms for achieving maximum throughput and low delay in wireless networks. recently, it has been shown that csma-type random access algorithms can achieve the maximum possible throughput in ad hoc wireless networks. however, these algorithms assume an idealized continuous-time csma protocol where collisions can never occur. in addition, simulation results indicate that the delay performance of these algorithms can be quite bad. on the other hand, although some simple heuristics (such as distributed approximations of greedy maximal scheduling) can yield much better delay performance for a large set of arrival rates, they may only achieve a fraction of the capacity region in general. in this paper, we propose a discrete-time version of the csma algorithm. central to our results is a discrete-time distributed randomized algorithm which is based on a generalization of the so-called glauber dynamics from statistical physics, where multiple links are allowed to update their states in a single time slot. the algorithm generates collision-free transmission schedules while explicitly taking collisions into account during the control phase of the protocol, thus relaxing the perfect csma assumption. more importantly, the algorithm allows us to incorporate delay-reduction mechanisms which lead to very good delay performance while retaining the throughput-optimality property.
tracking quantiles of network data streams with dynamic operations. quantiles are very useful in characterizing the data distribution of an evolving dataset in the process of data mining or network monitoring. the method of stochastic approximation (sa) tracks quantiles online by incrementally deriving and updating local approximations of the underly distribution function at the quantiles of interest. in this paper, we propose a generalization of the sa method for quantile estimation that allows not only data insertions, but also dynamic data operations such as deletions and updates.
mobile real-time group communication service. a scalable framework for mobile real-time group communication services is developed in this paper. examples for possible applications of this framework are mobile social networks, mobile conference calls, mobile instant messaging services, and mobile multi-player on-line games. a key requirement for enabling a real-time group communication service is the tight constraint imposed on the call delivery delay. since establishing such communication service for a group of independent mobile users under a tight delay constraint is np-hard, a two-tier architecture is proposed, that can meet the delay constraint imposed by the real-time service requirement for many independent mobile clients in a scalable manner. the time and memory complexity associated with the group services provided by the proposed framework are o(n) for each service, where n is the number of nodes being served, while a distributed scheme requires o(n2) for both time and memory complexity.
safeq: secure and efficient query processing in sensor networks. the architecture of two-tiered sensor networks, where storage nodes serve as an intermediate tier between sensors and a sink for storing data and processing queries, has been widely adopted because of the benefits of power and storage saving for sensors as well as the efficiency of query processing. however, the importance of storage nodes also makes them attractive to attackers. in this paper, we propose safeq, a protocol that prevents attackers from gaining information from both sensor collected data and sink issued queries. safeq also allows a sink to detect compromised storage nodes when they misbehave. to preserve privacy, safeq uses a novel technique to encode both data and queries such that a storage node can correctly process encoded queries over encoded data without knowing their values. to preserve integrity, we propose a new data structure called neighborhood chains that allows a sink to verify whether the result of a query contains exactly the data items that satisfy the query. in addition, we propose a solution to adapt safeq for event-driven sensor networks.
measurouting: a framework for routing assisted traffic monitoring. monitoring transit traffic at one or more points in a network is of interest to network operators for reasons of traffic accounting, debugging or troubleshooting, forensics, and traffic engineering. previous research in the area has focused on deriving a placement of monitors across the network towards the end of maximizing the monitoring utility of the network operator for a given traffic routing. however, both traffic characteristics and measurement objectives can dynamically change over time, rendering a previously optimal placement of monitors suboptimal. it is not feasible to dynamically redeploy/reconfigure measurement infrastructure to cater to such evolving measurement requirements. we address this problem by strategically routing traffic sub-populations over fixed monitors. we refer to this approach as measurouting. the main challenge for measurouting is to work within the constraints of existing intra-domain traffic engineering operations that are geared for efficiently utilizing bandwidth resources, or meeting quality of service (qos) constraints, or both. a fundamental feature of intra-domain routing, that makes measurouting feasible, is that intra-domain routing is often specified for aggregate flows. measurouting, can therefore, differentially route components of an aggregate flow while ensuring that the aggregate placement is compliant to original traffic engineering objectives. in this paper we present a theoretical framework for measurouting. furthermore, as proofs-of-concept, we present synthetic and practical monitoring applications to showcase the utility enhancement achieved with measurouting.
fair scheduling in cellular systems in the presence of noncooperative mobiles. we consider the problem of centrally controlled 'fair' scheduling of resources to one of the many mobile stations connected to a base station (bs). the bs is the only entity making decisions in this framework based on truthful information from the mobiles on their radio channel. we study the well-known family of parametric a-fair scheduling problems from a game-theoretic perspective in which some of the mobiles may be noncooperative. we first show that if the bs is unaware of the noncooperative behavior from the mobiles, the noncooperative mobiles become successful in snatching the resources from the other cooperative mobiles, resulting in unfair allocations. if the bs is aware of the noncooperative mobiles, a new game arises with bs as an additional player. it can then do better by neglecting the signals from the noncooperative mobiles. the bs, however, becomes successful in eliciting the truthful signals from the mobiles only when it uses additional information (signal statistics). this new policy along with the truthful signals from mobiles forms a nash equilibrium (ne) called a truth revealing equilibrium. finally, we propose new iterative algorithms to implement fair scheduling policies that robustify the otherwise non-robust (in presence of noncooperation) a-fair scheduling algorithms.
optimal activation and transmission control in delay tolerant networks. much research has been devoted to maximize the life time of mobile ad-hoc networks. life time has often been defined as the time elapsed until the first node is out of battery power. in the context of static networks, this could lead to disconnectivity. in contrast, delay tolerant networks (dtns) leverage the mobility of relay nodes to compensate for lack of permanent connectivity, and thus enable communication even after some nodes deplete their stored energy. one can thus consider the lifetimes of nodes as some additional parameters that can be controlled to optimize the performance of a dtn. in this paper, we consider two ways in which the energy state of a mobile can be controlled. both listening and transmission require energy, besides each of these has a different type of effect on the network performance. therefore we consider a joint optimization problem consisting of: i) activation, which determines when a mobile will turn on in order to receive packets, and ii) transmission control, which regulates the beaconing. the optimal solutions are shown to be of the threshold type. the findings are validated through extensive simulations.
incorporating random linear network coding for peer-to-peer network diagnosis. recent studies show that network coding improves multicast session throughput. in this paper, we demonstrate how random linear network coding can be incorporated to provide network diagnosis for peer-to-peer systems. we present a new trace collection protocol that allows operators to diagnose peer-topeer networks. it is essential to monitor large-scale peer-to-peer applications by collecting measurements referred to as snapshots from the peers. however, existing solutions are not scalable and fail to collect measurements from peers that departed before the time of collection. we use progressive random linear network coding to disseminate the snapshots in the network, from which the server pulls data in a delayed fashion. we leverage the power of progressive encoding to increase block diversity and tolerate extreme block losses by introducing redundancy in the network. peers cooperate by allocating cache capacity for other peers. snapshots of departed peers can thus be retrieved from the network. we show how our protocol controls the redundancy introduced through progressive encoding and thus scales to large number of peers and tolerates high level of peer dynamics.
walking in facebook: a case study of unbiased sampling of osns. with more than 250 million active users [1], facebook (fb) is currently one of the most important online social networks. our goal in this paper is to obtain a representative (unbiased) sample of facebook users by crawling its social graph. in this quest, we consider and implement several candidate techniques. two approaches that are found to perform well are the metropolis-hasting random walk (mhrw) and a reweighted random walk (rwrw). both have pros and cons, which we demonstrate through a comparison to each other as well as to the "ground-truth" (uni - obtained through true uniform sampling of fb userids). in contrast, the traditional breadth-first-search (bfs) and random walk (rw) perform quite poorly, producing substantially biased results. in addition to offline performance assessment, we introduce online formal convergence diagnostics to assess sample quality during the data collection process. we show how these can be used to effectively determine when a random walk sample is of adequate size and quality for subsequent use (i.e., when it is safe to cease sampling). using these methods, we collect the first, to the best of our knowledge, unbiased sample of facebook. finally, we use one of our representative datasets, collected through mhrw, to characterize several key properties of facebook.
collaborative measurements of upload speeds in p2p systems. in this paper, we study the theory of collaborative upload bandwidth measurement in peer-to-peer environments. a host can use a bandwidth estimation probe to determine the bandwidth between itself and any other host in the system. the problem is that the result of such a measurement may not necessarily be the sender's upload bandwidth, since the most bandwidth restricted link on the path could also be the receiver's download bandwidth. in this paper, we formally define the bandwidth determination problem and devise efficient distributed algorithms. we consider two models, the free-departure and no-departure model, respectively, depending on whether hosts keep participating in the algorithm even after their bandwidth has been determined. we present lower bounds on the timecomplexity of any collaborative bandwidth measurement algorithm in both models. we then show how, for realistic bandwidth distributions, the lower bounds can be overcome. specifically, we present o(1) and o(log log n)-time algorithms for the two models. we corroborate these theoretical findings with practical measurements on a implementation on planetlab.
back-pressure routing for intermittently connected networks. we study a mobile wireless network where groups or clusters of nodes are intermittently connected via mobile "carriers" (the carriers provide connectivity over time among different clusters of nodes). over such networks (an instantiation of a delay tolerant network), it is well-known that traditional routing algorithms perform very poorly. in this paper, we propose a two-level back-pressure with source-routing algorithm (bp+sr) for such networks. the proposed bp+sr algorithm separates routing and scheduling within clusters (fast time-scale) from the communications that occur across clusters (slow time-scale), without loss in network throughput (i.e., bp+sr is throughput-optimal). more importantly, for a source and destination node that lie in different clusters, the traditional back-pressure algorithm results in large queue lengths at each node along its path. this is because the queue dynamics are driven by the slowest time-scale (i.e., that of the carrier nodes) along the path between the source and destination, which results in very large end-to-end delays. on the other-hand, we show that the two-level bp+sr algorithm maintains large queues only at a very few nodes, and thus results in order-wise smaller end-to-end delays. we provide analytical as well as simulation results to confirm our claims.
layered internet video engineering (live): network-assisted bandwidth sharing and transient loss protection for scalable video streaming. this paper presents a novel scheme, layered internet video engineering (live), in which network nodes feed back virtual congestion levels to video senders to assist both media-aware bandwidth sharing and transient loss protection. the video senders respond to such feedback by adapting the rates of encoded h.264/svc streams based on their respective video rate-distortion (r-d) characteristics. the same feedback is employed to calculate the amount of forward error correction (fec) protection for combating transient losses. simulation studies show that live can minimize the total distortion of all participating video streams and hence maximize their overall quality. at steady state, video streams experience no queueing delays or packet losses. in face of transient congestion, the network-assisted adaptive fec scheme effectively protects video packets from losses while minimizing overhead. our theoretical analysis further guarantees system stability for an arbitrary number of streams with heterogenous round trip delays below a prescribed limit. finally, we show that live streams can coexist with tcp flows within the existing explicit congestion notification (ecn) framework.
distributed resource allocation for synchronous fork and join processing networks. many emerging information processing applications require applying various fork and join type operations such as correlation, aggregation, and encoding/decoding to data streams in real-time. each operation will require one or more simultaneous input data streams and produce one or more output streams, where the processing may shrink or expand the data rates upon completion. multiple tasks can be co-located on the same server and compete for limited resources. effective in-network processing and resource management in a distributed heterogeneous environment is critical to achieving better scalability and provision of quality of service. in this paper, we study the distributed resource allocation problem for a synchronous fork and join processing network, with the goal of achieving the maximum total utility of output streams. using primal and dual based optimization techniques, we propose several decentralized iterative algorithms to solve the problem, and design protocols that implement these algorithms. these algorithms have different strengths in practical implementation and can be tailored to take full advantage of the computing capabilities of individual servers. we show that our algorithms guarantee optimality and demonstrate through simulation that they can adapt quickly to dynamically changing environments.
pricing and incentives in peer-to-peer networks. peer-to-peer (p2p) networks offer a cost effective and easily deployable framework for sharing user-generated content. however, intrinsic incentive problems reside in p2p networks as the transfer of content incurs costs both to uploaders and to downloaders while the benefit accrues only to downloaders. we investigate the issues of incentives in content production and sharing over p2p networks using a game theoretic model. peers do not share produced content at all at noncooperative equilibria whereas pareto efficiency requires peers to fully share produced content. there is also a divergence in the total amount of produced content between non-cooperative equilibria and pareto efficiency. by imposing full sharing, we decompose the inefficiency of non-cooperative equilibria into two parts, inefficiency due to no sharing and inefficiency due to underproduction. as a method to remedy the incentive problems in p2p networks, two classes of pricing schemes, mp pricing schemes and linear pricing schemes, are proposed. we show that the proposed pricing schemes can achieve pareto efficiency as non-cooperative equilibria. we also examine a linear pricing scheme that maximizes the revenue of the network manager.
max-contribution: on optimal resource allocation in delay tolerant networks. this is by far the first paper considering joint optimization of link scheduling, routing and replication for disruption-tolerant networks (dtns). the optimization problems for resource allocation in dtns are typically solved using dynamic programming which requires knowledge of future events such as meeting schedules and durations. this paper defines a new notion of optimality for dtns, called snapshot optimality where nodes are not clairvoyant, i.e., cannot look ahead into future events, and thus decisions are made using only contemporarily available knowledge. unfortunately, the optimal solution for snapshot optimality still requires solving an nphard problem of maximum weight independent set and a global knowledge of who currently owns a copy and what their delivery probabilities are. this paper presents a new efficient approximation algorithm, called distributed max-contribution (dmc) that performs greedy scheduling, routing and replication based only on locally and contemporarily available information. through a simulation study based on real gps traces tracking over 4000 taxies for about 30 days in a large city, dmc outperforms existing heuristically engineered resource allocation algorithms for dtns.
mis: malicious nodes identification scheme in network-coding-based peer-to-peer streaming. network coding has been shown to be capable of greatly improving quality of service in p2p live streaming systems (e.g., iptv). however, network coding is vulnerable to pollution attacks where malicious nodes inject into the network bogus data blocks that are combined with other legitimate blocks at downstream nodes, leading to incapability of decoding the original blocks and substantial degradation of network performance. in this paper, we propose a novel approach to limiting pollution attacks by rapidly identifying malicious nodes. our scheme can fully satisfy the requirements of live streaming systems, and achieves much higher efficiency than previous schemes. each node in our scheme only needs to perform several hash computations for an incoming block, incurring very small computational latency. the space overhead added to each block is only 20 bytes. the verification information given to each node is independent of the streaming content and thus does not need to be redistributed. the simulation results based on real pplive channel overlays show that the process of identifying malicious nodes only takes a few seconds even in the presence of a large number of malicious nodes.
phishnet: predictive blacklisting to detect phishing attacks. phishing has been easy and effective way for trickery and deception on the internet. while solutions such as url blacklisting have been effective to some degree, their reliance on exact match with the blacklisted entries makes it easy for attackers to evade. we start with the observation that attackers often employ simple modifications (e.g., changing top level domain) to urls. our system, phishnet, exploits this observation using two components. in the first component, we propose five heuristics to enumerate simple combinations of known phishing sites to discover new phishing urls. the second component consists of an approximate matching algorithm that dissects a url into multiple components that are matched individually against entries in the blacklist. in our evaluation with real-time blacklist feeds, we discovered around 18,000 new phishing urls from a set of 6,000 new blacklist entries. we also show that our approximate matching algorithm leads to very few false positives (3%) and negatives (5%).
on the age of pseudonyms in mobile ad hoc networks. in many envisioned mobile ad hoc networks, nodes are expected to periodically beacon to advertise their presence. in this way, they can receive messages addressed to them or participate in routing operations. yet, these beacons leak information about the nodes and thus hamper their privacy. a classic remedy consists in each node making use of (certified) pseudonyms and changing its pseudonym in specific locations called mix zones. of course, privacy is then higher if the pseudonyms are short-lived (i.e., nodes have a short distance to confusion), but pseudonyms can be costly, as they are usually obtained from an external authority. in this paper, we provide a detailed analytical evaluation of the age of pseudonyms based on differential equations. we corroborate this model by a set of simulations. this paper thus provides a detailed quantitative framework for selecting the parameters of a pseudonym-based privacy system in peer-to-peer wireless networks.
diversity-rate trade-off in erasure networks. this paper addresses a fundamental trade-off between rate and the diversity gain of an end-to-end connection in an erasure network. the erasure network is modeled by a directed graph whose links are orthogonal erasure channels. furthermore, the erasure network is assumed to be nonergodic, meaning that the erasure status of the links are assumed to be fixed during each block of transmission and change independently from block to block. the erasure status of the links is assumed to be known only by the destination node. first, we study the homogeneous erasure networks in which the links have the same erasure probability and capacity. we derive the optimum trade-off between diversity gain and the end-to-end rate and prove that a variant of the conventional routing strategy combined with an appropriate forward error correction at the end-nodes achieves the optimum diversity-rate trade-off. next, we consider the general erasure networks in which different links may have different values of erasure probability and capacity. we prove that there exist general erasure networks for which any conventional routing strategy fails to achieve the optimum diversity-rate trade-off. however, for any general erasure graph, we show that there exists a linear network coding strategy which achieves the optimum diversity-rate trade-off. unlike the previous works which suggest the potential benefit of linear network coding in the error-free multicast scenario (in terms of the achievable rate), our result introduces the benefit of linear network coding in the erasure single-source singledestination scenario (in terms of the diversity gain). finally, we study the diversity-rate trade-off through simulations. the erasure graphs are constructed according to the barabasi-albert random model which is known to capture the scale-free property of the practical packet switched networks like the internet. the error probability is depicted for different network strategies and different rate values. the depicted results confirm the trade-off between the rate and the diversity gain for each network strategy. moreover, the diversity gain is plotted versus the rate for different conventional routing and the linear network coding strategies. it is observed that linear network coding outperforms all conventional routing strategies in terms of the diversity gain.
scalable modulation for scalable wireless videocast. in conventional wireless systems with layered architectures, the physical layer treats all data streams from upper layers equally and apply the same modulation and coding schemes. newer systems such as digital video broadcast start to introduce hierarchical modulation schemes with superposition coding (spc) and support data streams of different priorities. however, spc requires specialized hardware and has high complexity beyond most existing handheld devices. we thus propose scalable modulation (s-mod) by reusing the current mainstream modulation schemes with software-based bit-remapping. in this paper, we study how to optimize the configuration of the physical layer s-mod and coding schemes to maximize the utility of videocast with scalable video coding (svc). simulation results demonstrate significant performance gains using s-mod and the cross-layer optimization, indicating s-mod and svc is a good combination for wireless video multicast and unicast.
twister networks and their applications to load-balanced switches. inspired by the recent development of optical queueing theory, in this paper we study a class of multistage interconnection networks (mins), called twister networks. unlike the usual recursive constructions of mins (either by two-stage expansion or by three-stage expansion), twister networks are constructed directly by a concatenation of bipartite networks. moreover, the biadjacency matrices of these bipartite networks are sums of subsets of the powers of the circular shift matrix. though mins have been studied extensively in the literature, we show there are several distinct properties for twister networks, including routability and conditionally nonblocking properties. in particular, we show that a twister network satisfying (a1) in the paper is routable, and packets can be self-routed through the twister network by using the c-transform developed in optical queueing theory. moreover, we define an n-modulo distance and use it to show that a twister network satisfying (a2) in the paper is conditionally nonblocking if the n-modulo distance between any two outputs is not greater than two times of the n-modulo distance between the corresponding two inputs. such a conditionally nonblocking property allows us to show that a twister network with n inputs/outputs can be used as a p × p rotator and a p × p symmetric tdm switch for any 2 ≤ p ≤ n. as such, one can use a twister network as the switch fabric for a two-stage load balanced switch that is capable of providing incremental update of the number of linecards.
an interaction-based mobility model for dynamic hot spot analysis. in this paper, we analyze phenomena related to user clumps and hot spots occuring in mobile networks at the occasion of large urban mass gatherings. our analysis is based on observations made on mobility traces of gsm users in several large cities. classical mobility models, such as the random waypoint, do not allow one to represent the observed dynamics of clumps in a proper manner. this motivates the introduction and the mathematical analysis of a new interaction-based mobility model, which is the main contribution of the present paper. this model is shown to allow one to describe the dynamics of clumps and in particular to predict key phenomena such as the building of hot spots and the scattering between hot spots, which play a key role in the engineering of wireless networks. we show how to obtain the main parameters of this model from simple communication activity measurements and we illustrate this calibration process on real cases.
routing and scheduling for energy and delay minimization in the powerdown model. energy conservation is drawing increasing attention in data networking. one school of thought believes that a dominant amount of energy saving comes from turning off network elements. the difficulty is that transitioning between the active and sleeping modes consumes considerable energy and time. this results in an obvious trade-off between saving energy and provisioning performance guarantees such as end-toend delays. we study the following routing and scheduling problem in a network in which each network element either operates in the full-rate active mode or the zero-rate sleeping mode. for a given network and traffic matrix, routing determines the path along which each traffic stream traverses. for frame-based periodic scheduling, a schedule determines the active period per element within each frame and prioritizes packets within each active period. for a line topology, we present a schedule with close-tominimum delay for a minimum active period per element. for an arbitrary topology, we partition the network into a collection of lines and utilize the near-optimal schedule along each line. additional delay is incurred only when a path switches from one line to another. by minimizing the number of switchings via routing, we show a logarithmic approximation for both energy consumption and end-to-end delays. if routing is given as input, we present two schedules one of which has active period proportional to the traffic load per network element, and the other proportional to the maximum load over all elements. the end-to-end delay of the latter is much improved compared to the delay for the former. this demonstrates the trade-off between energy and delay.
privacy-preserving public auditing for data storage security in cloud computing. cloud computing is the long dreamed vision of computing as a utility, where users can remotely store their data into the cloud so as to enjoy the on-demand high quality applications and services from a shared pool of configurable computing resources. by data outsourcing, users can be relieved from the burden of local data storage and maintenance. however, the fact that users no longer have physical possession of the possibly large size of outsourced data makes the data integrity protection in cloud computing a very challenging and potentially formidable task, especially for users with constrained computing resources and capabilities. thus, enabling public auditability for cloud data storage security is of critical importance so that users can resort to an external audit party to check the integrity of outsourced data when needed. to securely introduce an effective third party auditor (tpa), the following two fundamental requirements have to be met: 1) tpa should be able to efficiently audit the cloud data storage without demanding the local copy of data, and introduce no additional on-line burden to the cloud user; 2) the third party auditing process should bring in no new vulnerabilities towards user data privacy. in this paper, we utilize and uniquely combine the public key based homomorphic authenticator with random masking to achieve the privacy-preserving public cloud data auditing system, which meets all above requirements. to support efficient handling of multiple auditing tasks, we further explore the technique of bilinear aggregate signature to extend our main result into a multi-user setting, where tpa can perform multiple auditing tasks simultaneously. extensive security and performance analysis shows the proposed schemes are provably secure and highly efficient.
safeguarding data delivery by decoupling path propagation and adoption. false routing announcements are a serious security problem, which can lead to widespread service disruptions in the internet. a number of detection systems have been proposed and implemented recently, however, it takes time to detect attacks, notify operators, and stop false announcements. thus detection systems should be complemented by a mitigation scheme that can protect data delivery before the attack is resolved. we propose such a mitigation scheme, qbgp, which decouples the propagation of a path and the adoption of a path for data forwarding. qbgp does not use suspicious paths to forward data traffic, but still propagates them in the routing system to facilitate attack detection. it can protect data delivery from routing announcements of false sub-prefixes, false origins, false nodes and false links. qbgp incurs overhead only when there are suspicious paths, which happen infrequently in real bgp traces. results from large scale simulations and bgp trace analysis show that qbgp is light-weight yet effective, and it converges faster and incurs less overhead than pretty good bgp.
delay tolerant event collection in sensor networks with mobile sink. we are interested in event collection in a 2d region where sensors are deployed to detect and collect interested events. using traditional multi-hop routing in wireless sensor networks to report events to a sink node or base station, will result in severe imbalanced energy consumption of static sensors. in addition, full connectivity among all the static sensors may not be possible in some cases since generally the sensors are randomly deployed in the target region. in this paper, we exploit a mobile sensor as the sink node to assist the event collection by controlling the movement of the mobile sink to collect static sensor readings. a key observation of our work is that an event has spatial-temporal correlation. specifically, the same event can be detected by multiple nearby sensors within a period of time. thus, it is more energy-efficient if the mobile sink can selectively communicate with only a portion of static sensors, while still collecting all the interested events. in this paper, we discuss the event collection problem by leveraging the mobility of the sink node and the spatial-temporal correlation of the event, in favor of maximizing the network lifetime with a guaranteed event collection rate. we first model the problem as sensor selection problem and show that it could be solved in polynomial time, if global knowledge of events is available and there is no velocity constraints on mobile sink. we also analyze the design of a feasible movement route for mobile sink to minimize the velocity requirements for a practical system. an online scheme is then proposed to relax the assumption about global knowledge of events and we prove that the expected event collection rate can be guaranteed in theory. through comprehensive simulation on real trace data, we demonstrate that the network lifetime can be significantly extended, comparing to some other schemes.
low-complexity scheduling algorithms for multi-channel downlink wireless networks. this paper considers the problem of designing scheduling algorithms for multi-channel (e.g., ofdm) wireless downlink networks with n users/ofdm sub-channels. for this system, while the classical maxweight algorithm is known to be throughput-optimal, its buffer-overflow performance is very poor (formally, we show it has zero rate function in our setting). to address this, we propose a class of algorithms called ihlqf (iterated heaviest matching with longest queues first) that is shown to be throughput optimal for a general class of arrival/channel processes, and also rate-function optimal (i.e., exponentially small buffer overflow probability) for certain arrival/channel processes. ihlqf however has higher complexity than maxweight (n4 vs. n2 respectively). to overcome this issue, we propose a new algorithm called ssg (server-side greedy). we show that ssg is throughput optimal, results in a much better per-user buffer overflow performance than the maxweight algorithm (positive rate function for certain arrival/channel processes), and has a computational complexity (n2) that is comparable to the maxweight algorithm. thus, it provides a nice trade-off between buffer-overflow performance and computational complexity. these results are validated by both analysis and simulations.
a formal study of trust-based routing in wireless ad hoc networks. recently, trust-based routing has received much attention as an effective way to improve security of wireless ad hoc networks (wanets). although various trust metrics have been designed and incorporated into the routing metrics, as far as we know, none of the existing works have used mathematical tools such as routing algebra to analyze the compatibility of trust related routing metrics and routing protocols in wanets. in this paper, we first identify unique features of trust metrics compared with qos-based routing metrics. then, we provide a systematic analysis of the relationship between trust metrics and trust-based routing protocols by identifying the basic algebraic properties that a trust metric must have in order to work correctly and optimally with different generalized distance-vector or link-state routing protocols in wanets. moreover, we extend our framework to model the interactions between different trustbased routing protocols. finally, our results are applied to check the compatibility of the trust metrics proposed in previous literature and the popular routing protocols used in wanets.
channel-based unidirectional stream protocol (cusp). this paper presents a novel transport protocol, cusp, specifically designed with complex and dynamic network applications in mind. peer-to-peer applications benefit in particular, as their requirements are met by neither udp nor tcp. while other modern transports like sctp or sst have also tried to combine the advantages of tcp and udp, cusp overcomes their technical and conceptual shortcomings. cusp makes it possible to directly express application logic in the message flow. modern applications need a mixture of request-response, request-multiple-response, publish-subscribe, and message-passing. all of these operations can be conveniently implemented using cusp's unidirectional streams. we separate low-level packet management from streams into reusable channels. a channel connects two applications providing negotiation, congestion control, and cryptography. developers operate on the stream level, sending messages as reliable and ordered byte-streams. although they may share a common channel, a stall or loss in one stream does not block the others.
on the cost of knowledge of mobility in dynamic networks. in this paper, an information-theoretic framework is developed for characterizing the minimum cost, in bits per second, of tracking the motion state information, such as locations and velocities, of nodes in dynamic networks. the minimumcost motion-tracking problem is formulated as a rate-distortion problem, where the minimum cost is the minimum rate of information required to identify the network state at a sequence of tracking time instants within a certain distortion bound. the formulation is general in that it can be applied to a variety of mobility models, distortion criteria, and stochastic sequences of tracking time instants. under the gauss-markov mobility model, lower bounds on the information rate of tracking the motion state information of nodes in dynamic networks are derived, where the motion state of a node is 1) the node's locations only, or 2) both its locations and velocities. the results are then used to analyze the protocol overhead of geographic routing protocols in mobile ad hoc networks. the minimum overhead incurred by maintaining the geographic information of the nodes is characterized in terms of node mobility, packet arrival process and distortion bounds. this leads to precise mathematical description of the observation that, given certain state-distortion allowance, protocols aimed at tracking motion state information (such as geographic routing protocols) may not scale beyond a certain level of node mobility.
practical and general amplify-and-forward designs for cooperative networks. cooperative networks allow the nodes relaying each other's messages to enhance the transmission reliability over wireless fading channels by achieving cooperative diversity. among the various relaying protocols, the amplify-and-forward (af) strategy is well studied for its simplicity. however, to collect the cooperative diversity, there are two main issues that the af protocol is facing. one is that the channel state information (csi) of the source-to-relay link (i.e., two-hop csi) is needed at the destination. the other concern is that the power scaling factor (psf) and output signals at the relay are unbounded. these two issues make af less practical in resource constrained networks, e.g., blind and peak power constrained relays. in this paper, we reveal the necessary and sufficient conditions on designing the psf for the maximum ratio combining (mrc) receiver at the destination with two-hop (th) csi to achieve full cooperative diversity. furthermore, we also provide the necessary conditions on the psf design so that mrc with only one-hop (oh) csi still collects full cooperative diversity. these designs make af strategies more general and practical. the theoretical analysis is corroborated by numerical simulations.
on providing non-uniform scheduling guarantees in a wireless network. significant research effort has been directed towards the design and performance analysis of imperfect scheduling policies for wireless networks. these imperfect schedulers are of interest despite being sub-optimal, as they allow for more tractable implementation at the expense of some loss in performance. however much of this prior work takes a uniform scaling approach to analyzing scheduling performance, whereby the performance of a scheduling policy is characterized in terms of a single scalar quantity, the efficiency-ratio. while suitable for characterizing worst-case performance, this approach limits one's ability to understand the different extents of performance degradation that may be experienced by different links in a network. such an understanding is very valuable when average performance is of greater interest than the worst-case, or when certain links are more important than others. furthermore, once one approaches scheduler design with non-uniform performance guarantees in mind, one finds that simple modifications to well-known scheduling algorithms can yield substantially improved non-uniform scaling results compared to the original algorithms. in this paper, we make a comprehensive case for adopting such an approach by presenting non-uniform scaling results for a set of algorithms that are variants of well-known algorithms from the class of maximal schedulers.
optimal probing for unicast network delay tomography. network tomography has been proposed to ascertain internal network performances from end-to-end measurements. in this work, we present priority probing, an optimal probing scheme for unicast network delay tomography that is proven to provide the most accurate estimation. we first demonstrate that the fisher information matrix in unicast network delay tomography can be decomposed into an additive form where each term can be obtained numerically. this establishes the space over which we can design the optimal probing scheme. then, we formulate the optimal probing problem into a semidefinite programming (sdp) problem. high computation complexity constrains the sdp solution to only small scale scenarios. in response, we propose a greedy algorithm that approximates the optimal solution. evaluations through simulation demonstrate that priority probing effectively increases estimation accuracy with a fixed number of probes.
reliable gps-free double-ruling-based information brokerage in wireless sensor networks. because the global positioning system (gps) consumes a large amount of power and does not work indoors, many gps-free information brokerage schemes are proposed for wireless sensor networks. each of them, however, either cannot guarantee successful data retrieval or demands a great deal of message overhead to replicate the data. in this paper, we propose a gps-free information brokerage scheme, rdrib, in which the double-ruling technique is used to replicate and retrieve the data. rdrib guarantees successful data retrieval, and, in addition, simulations show that rdrib has good performance in terms of the replication message overhead and the construction message overhead.
towards reliable scheduling schemes for long-lived replaceable sensor networks. to address energy constraint problem in sensor networks, node reclamation and replacement strategy has been proposed for networks accessible to human beings and robots. the major challenge in realizing the strategy is how to minimize the system maintenance cost, especially the frequency in replacing sensor nodes with limited number of backup nodes. new duty cycle scheduling schemes are required in order to address the challenge. tong et al. have proposed a staircase-based scheme to address the problem based on ideal assumptions of sensor nodes that are free of failure and have regular energy consumption rate. since sensor nodes are often deployed in outdoor unattended environment, node failures are inevitable. energy consumption rates of sensor nodes are irregular due to manufacture or environmental reasons. hence, this paper proposes several new schemes to achieve reliable scheduling for node reclamation and replacement. extensive simulations have been conducted to verify that the proposed scheme is effective and efficient.
elastic rate limiting for spatially biased wireless mesh networks. ieee 802.11-based mesh networks can yield a throughput distribution among nodes that is spatially biased, with traffic originating from nodes that directly communicate with the gateway obtaining higher throughput than all other upstream traffic. in particular, if single-hop nodes fully utilize the gateway's resources, all other nodes communicating with the same gateway will attain very little (if any) throughput. in this paper, we show that it is sufficient to rate limit the single-hop nodes in order to give transmission opportunities to all other nodes. based on this observation, we develop a new rate limiting scheme for 802.11 mesh networks, which counters the spatial bias effect and does not require, in principle, any control overhead. our rate control mechanism is based on three key techniques. first, we exploit the system's inherent priority nature and control the throughput of the spatially disadvantaged nodes by only controlling the transmission rate of the spatially advantaged nodes. namely, the single-hop nodes collectively behave as a proxy controller for multi-hop nodes in order to achieve the desired bandwidth distribution. second, we devise a rate limiting scheme that enforces a utilization threshold for advantaged single-hop traffic and guarantees a small portion of the gateway resources for the disadvantaged multi-hop traffic. we infer demand for multi-hop flow bandwidth whenever gateway resource usage exceeds this threshold, and subsequently reduce the rates of the spatially advantaged single-hop nodes. third, since the more bandwidth the spatially disadvantaged nodes attain, the easier they can signal their demands, we allow the bandwidth unavailable for the advantaged nodes to be elastic, i.e., the more the disadvantaged flows use the gateway resources, the higher the utilization threshold is. we develop an analytical model to study a system characterized by such priority, dynamic utilization thresholds, and control by proxy. moreover, we use simulations to evaluate the proposed elastic rate limiting technique.
socially-aware network design games. in many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. this is the case of the internet, where connectivity is due to autonomous systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. recent works have used game theory, and in particular the concept of nash equilibrium, to characterize stable networks created by a set of selfish agents. the majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. to improve efficiency, in this paper we propose two novel socially-aware network design games. in the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient nash equilibria. we provide bounds on the price of anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real internet service provider networks. numerical results demonstrate that (1) introducing some incentives to make users more socially-aware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.
a systematic approach for evolving vlan designs. enterprise networks are large and complex, and their designs must be frequently altered to adapt to changing organizational needs. the process of redesigning and reconfiguring enterprise networks is ad-hoc and error-prone, and configuration errors could cause serious issues such as network outages. in this paper, we take a step towards systematic evolution of network designs in the context of virtual local area networks (vlans). we focus on vlans given their importance and prevalence, the frequent need to change vlan designs, and the time-consuming and error-prone process of making changes. we present algorithms for common design tasks encountered in evolving vlans such as deciding which vlan a new host must be assigned to. our algorithms trade off multiple criteria such as broadcast traffic costs, and costs associated with maintaining spanning trees for each vlan in the network, while honoring correctness and feasibility constraints on the design. our algorithms also enable automatic detection of network-wide dependencies which must be factored when reconfiguring vlans. we evaluate our algorithms on longitudinal snapshots of configuration files of a large-scale operational campus network obtained over a two year period. our results show that our algorithms can produce significantly better designs than current practice, while avoiding errors and minimizing human work. our unique data-sets also enable us to characterize vlan related change activities in real networks, an important contribution in its own right.
distributed opportunistic scheduling for ad-hoc communications under delay constraints. with the convergence of multimedia applications and wireless communications, there is an urgent need for developing new scheduling algorithms to support real-time traffic with stringent delay requirements. however, distributed scheduling under delay constraints is not well understood and remains an under-explored area. a main goal of this study is to take some steps in this direction and explore the distributed opportunistic scheduling (dos) with delay constraints. consider a network with m links which contend for the channel using random access. distributed scheduling in such a network requires joint channel probing and distributed scheduling. using optimal stopping theory, we explore dos for throughput maximization, under two different types of average delay constraints: 1) a network-wide constraint where the average delay should be no greater than a; or 2) individual user constraints where the average delay per user should be no greater than αm, m = 1, . . . , m. since the standard techniques for constrained optimal stopping problems are based on sample-path arguments and are not applicable here, we take a stochastic lagrangian approach instead. we characterize the corresponding optimal scheduling policies accordingly, and show that they have a pure threshold structure, i.e. data transmission is scheduled if and only if the rate is above a threshold. specifically, in the case with a network-wide delay constraint, somewhat surprisingly, there exists a sharp transition associated with a critical time constant, denoted by α*. if α is less than α*, the optimal rate threshold depends on α, otherwise it does not depends on α at all, and the optimal policy is the same as that in the unconstrained case. in the case with individual user delay constraints, we cast the threshold selection problem across links as a non-cooperative game, and establish the existence of nash equilibria. again we observe a sharp transition associated with critical time constants {αm*}, in the sense that when αm ≥ αm* for all users, the nash equilibrium becomes the same one as if there were no delay constraints.
value-aware resource allocation for service guarantees in networks. the traditional formulation of the total value of information transfer is a multi-commodity flow problem. here, each data source is seen as generating a commodity along a fixed route, and the objective is to maximize the total system throughput under some concept of fairness, subject to capacity constraints of the links used. this problem is well studied under the framework of network utility maximization and has led to several different distributed congestion control schemes. however, this idea of value does not capture the fact that flows might associate value, not just with throughput, but with link-quality metrics such as packet delay, jitter and so on. the traditional congestion control problem is redefined to include individual source preferences. it is assumed that degradation in link quality seen by a flow adds up on the links it traverses, and the total utility is maximized in such a way that the quality degradation seen by each source is bounded by a value that it declares. decoupling source-dissatisfaction and link-degradation through an "effective capacity" variable, a distributed and provably optimal resource allocation algorithm is designed, to maximize system utility subject to these quality constraints. the applicability of our controller in different situations is illustrated, and results are supported through numerical examples.
approximation algorithms for many-to-many traffic grooming in wdm mesh networks. a large number of network applications today allow several users to interact together using the many-to-many service mode. in many-to-many communication, also referred to as group communication, a session consists of a group of users (we refer to them as members), where each member transmits its traffic to all other members in the same group. in this paper, we address the problem of grooming sub-wavelength many-to-many traffic (e.g., oc-3) into high-bandwidth wavelength channels (e.g., oc-192) in wdm mesh networks. the cost of a wdm network is dominated by the cost of higher layer electronic ports (i.e., transceivers). a transceiver is needed for each initiation and termination of a lightpath. therefore, our objective is to minimize the total number of lightpaths established. unfortunately, the grooming problem even with unicast traffic has been shown to be np-hard. for a number of special cases where the many-to-many traffic grooming problem is tractable, we efficiently derive the optimal solution, while in the general case, we introduce two novel approximation algorithms. we also consider the routing and wavelength assignment problem with the objective of minimizing the number of wavelengths used. through extensive experiments, we show that the two algorithms use a number of lightpaths that is very close to that of a derived lower bound. also, we compare the two algorithms on the several costs mentioned in the paper including the number of lightpaths and the number of wavelengths used.
approximate capacity subregions of uniform multihop wireless networks. the capacity region of multihop wireless network is involved in many capacity optimization problems. however, the membership of the capacity region is np-complete in general, and hence the direct application of capacity region is quite limited. as a compromise, we often substitute the capacity region with a polynomial approximate capacity subregion. in this paper, we construct polynomial µ-approximate capacity subregions of multihop wireless network under either 802.11 interference model or protocol interference model in which all nodes have uniform communication radii normalized to one and uniform interference radii ρ ≥ 1. the approximation factor µ decreases with ρ in general and is smaller than the best-known ones in the literature. for example, µ = 3 when ρ ≥ 2.2907 under the 802.11 interference model or when ρ ≥ 4.2462 under the protocol interference model. our construction exploits a nature of the wireless interference called strip-wise transitivity of independence discovered in this paper and utilize the independence polytopes of cocomparability graphs in a spatial-divide-conquer manner. we also apply these polynomial µ-approximate capacity subregions to compute µ-approximate solutions for maximum (concurrent) multiflows
topology control for effective interference cancellation in multi-user mimo networks. in multi-user mimo networks, receivers decode multiple concurrent signals using successive interference cancellation (sic). with sic a weak target signal can be deciphered in the presence of stronger interfering signals. however, this is only feasible if each strong interfering signal satisfies a signal-to-noise-plus-interference ratio (sinr) requirement. this necessitates the appropriate selection of a subset of links that can be concurrently active in each receiver's neighborhood; in other words, a sub-topology consisting of links that can be simultaneously active in the network is to be formed. if the selected sub-topologies are of small size, the delay between the transmission opportunities on a link increases. thus, care should be taken to form a limited number of sub-topologies. we find that the problem of constructing the minimum number of sub-topologies such that sic decoding is successful with a desired probability threshold, is np-hard. given this, we propose music, a framework that greedily forms and activates sub-topologies, in a way that favors successful sic decoding with a high probability. music also ensures that the number of selected sub-topologies is kept small. we provide both a centralized and a distributed version of our framework. we prove that our centralized version approximates the optimal solution for the considered problem. we also perform extensive simulations to demonstrate that (i) music forms a small number of sub-topologies that enable efficient sic operations; the number of sub-topologies formed is at most 17% larger than the optimum number of topologies, discovered through exhaustive search (in small networks). (ii) music outperforms approaches that simply consider the number of antennas as a measure for determining the links that can be simultaneously active. specifically, music provides throughput improvements of up to 4 times, as compared to such an approach, in various topological settings. the improvements can be directly attributable to a significantly higher probability of correct sic based decoding with music.
transition from heavy to light tails in retransmission durations. retransmissions serve as the basic building block that communication protocols use to achieve reliable data transfer. until recently, the number of retransmissions were thought to follow a light tailed (in particular, a geometric) distribution. however, recent work seems to suggest that when the distribution of the packets have infinite support, retransmission-based protocols may result in heavy tailed delays and even possibly zero throughput. while this result is true even when the distribution of packet sizes are light-tailed, it requires the assumption that the packet sizes have infinite support. however, in reality, packet sizes are often bounded by the maximum transmission unit (mtu), and thus the aforementioned result merits a deeper investigation. to that end, in this paper, we allow the distribution of the packet size l to have finite support. this packet is sent over an on-off channel {(ai, ui)} with alternating available ai and unavailable ui periods. if l ≥ ai, the transmission fails and we wait for the next period ai+1 to retransmit the packet. the transmission duration is thus measured from the first attempt to a point when a channel available period larger than l. under mild conditions, we show that the transmission duration distribution exhibits a transition from a power law main body to an exponential tail with weibull type distributions between the two. the time scale to observe the power law main body is roughly equal to the average transmission duration of the longest packet. both the power law main body and the exponential tail could dominate the overall performance. for example, the power law main body, if significant, may cause the channel throughput to be very close to zero. on the other hand, the exponential tail, if more evident, may imply that the system operates in a benign environment. these theoretical findings provide an understanding on why some empirical measurements suggest heavy tails and light tails for others (e.g., wireless networks). we use these results to further highlight the engineering implications from distributions with power law main bodies and light tails by analyzing two cases: (1) the throughput of on-off channels with retransmissions, where we show that even when packet sizes have small means and bounded support the variability in their sizes can greatly impact system performance. (2) the distribution of the number of jobs in an m/m/∞ queue with server failures. here we show that retransmissions can cause long-range dependence and quantify the impact of the maximum job sizes on the long-range dependence.
robust and scalable integrated routing in manets using context-aware ordered meshes. a new context-aware routing framework for multicast and unicast routing in mobile ad hoc networks is introduced. this framework, which is called carom (context-aware routing over ordered meshes), uses regions of interest to identify connected componnets of the network that span sources and destinations of interest to restrict signaling to occur mostly within these regions. context information is used to compute routing meshes composed of shortest-paths located inside of regions of interest. experimental results based on extensive simulations show that carom attains similar or better data delivery and end-to-end delays than traditional unicast and multicast routing schemes for manets (aodv, olsr, odmrp), and that carom incurs only a fraction of the signaling overhead of traditional routing schemes.
survivable distributed storage with progressive decoding. we propose a storage-optimal and computation efficient primitive to spread information from a single data source to a set of storage nodes, to allow recovery from both crash-stop and byzantine failures. a progressive data retrieval scheme is employed, which retrieves minimal amount of data from live storage nodes. the scheme adapts the cost of successful data retrieval to the degree of errors in the system. implementation and evaluation studies demonstrate comparable performance to that of a genie-aid decoding process.
an attack-defense game theoretic analysis of multi-band wireless covert timing networks. we discuss malicious interference based denial of service (dos) attacks in multi-band covert timing networks using an adversarial game theoretic approach. a covert timing network operating on a set of multiple spectrum bands is considered. each band has an associated utility which represents the critical nature of the covert data transmitted in the band. a malicious attacker wishes to cause a dos attack by sensing and creating malicious interference on some or all of the bands. the covert timing network deploys camouflaging resources to appropriately defend the spectrum bands. a two tier game theoretic approach is proposed to model this scenario. the first tier of the game is the sensing game in which, the covert timing network determines the amount of camouflaging resources to be deployed in each band and the malicious attacker determines the optimal sensing resources to be deployed in each band. in the second tier of the game, the malicious attacker determines the optimal transmit powers on each spectral band it chooses to attack. we prove the existence of nash equilibriums for the games. we compare the performance of our proposed game theoretic mechanism with that of other well known heuristic mechanisms and demonstrate the effectiveness of the proposed approach.
towards an efficient reservation algorithm for distributed reservation protocols. with the proliferation of wireless technologies and the convenience they offer, transporting quality-of-service (qos) demanding traffic such as compressed video over wireless links becomes a trend and a challenging issue. among many factors, media access control (mac) protocols play an important role in the network stack to ensure the qos provisioning for multimedia applications and the efficient utilization of wireless channels. various contention-based or contention-free mac protocols have been proposed to solve these problems. in this paper, we model, analyze with an existing framework, and evaluate two reservation algorithms, subframe-fit and isozone-fit, proposed for distributed reservation protocols exampled by wimedia uwb mac. the models have been validated by extensive simulations using ns- 2 and an mpeg-4 traffic generator. we further improve the system performance by introducing cross-isozone allocation and on-demand compaction to isozone-fit, and discuss how to leverage both contention-based and contention-free mac protocols.
mobility assisted secret key generation using wireless link signatures. we propose an approach where wireless devices, interested in establishing a secret key, sample the channel impulse response (cir) space in a physical area to collect and combine uncorrelated cir measurements to generate the secret key. we study the impact of mobility patterns in obtaining uncorrelated measurements. using extensive measurements in both indoor and outdoor settings, we find that (i) when movement step size is larger than one foot the measured cirs are mostly uncorrelated, and (ii) more diffusion in the mobility results in less correlation in the measured cirs. we develop efficient mechanisms to encode cirs and reconcile the differences in the bits extracted between the two devices. our results show that our scheme generates very high entropy secret bits and that too at a high bit rate. the secret bits, that we generate using our approach, also pass the 8 randomness tests of the nist test suite.
routing in socially selfish delay tolerant networks. existing routing algorithms for delay tolerant networks (dtns) assume that nodes are willing to forward packets for others. in the real world, however, most people are socially selfish; i.e., they are willing to forward packets for nodes with whom they have social ties but not others, and such willingness varies with the strength of the social tie. following the philosophy of design for user, we propose a social selfishness aware routing (ssar) algorithm to allow user selfishness and provide better routing performance in an efficient way. to select a forwarding node, ssar considers both users' willingness to forward and their contact opportunity, resulting in a better forwarding strategy than purely contact-based approaches. moreover, ssar formulates the data forwarding process as a multiple knapsack problem with assignment restrictions (mkpar) to satisfy user demands for selfishness and performance. trace-driven simulations show that ssar allows users to maintain selfishness and achieves better routing performance with low transmission cost.
stable maximum throughput broadcast in wireless fading channels. this research considers network coded broadcast system with multi-rate transmission and dual queue stability constraints. existing network coded broadcast systems consider single rate transmission without receiver queue constraints. first, we shall illustrate that broadcast without network coding cannot support maximum throughput in wireless fading channels. however, the network coded broadcast poses new constraints for the receivers to manage stable queues while the fading channel characteristics suggest the broadcast to operate at multi-rate to achieve higher throughput. in this research, we propose a joint scheduling and network coding (jsnc) strategy for such network coded broadcast system to achieve maximum throughput under queue stability constraint. in a single cell broadcast networks with exogenous arrivals of packets at the base station, we prove that jsnc can stabilize the system as long as the rate of the exogenous arrival flow is within the capacity region. sufficient control parameters are provided in jsnc for trading off between sender's buffer and the receivers' buffers. jsnc can be viewed as a generalization of the classical backpressure scheduling rule to coded information flow. alternatively, jsnc can also be viewed as an extension of network coding theory to queuing system.
inpac: an enforceable incentive scheme for wireless networks using network coding. wireless mesh networks have been widely deployed to provide broadband network access, and their performance can be significantly improved by using a new technology called network coding. in a wireless mesh network using network coding, selfish nodes may deviate from the protocol when they are supposed to forward packets. this fundamental problem of packet forwarding incentives is closely related to the incentive compatible routing problem in wireless mesh networks using network coding, and to the incentive compatible packet forwarding problem in conventional wireless networks, but different from both of them. in this paper, we propose inpac, the first incentive scheme for this fundamental problem, which uses a combination of game theoretic and cryptographic techniques to solve it. we formally prove that, if inpac is used, then following the protocol faithfully is a subgame perfect equilibrium. to make inpac more practical, we also provide an extension that achieves two improvements: (a) an online authority is no longer needed; (b) the computation and communication overheads are reduced. we have implemented and evaluated inpac on the orbit lab testbed. our evaluation results verify the incentive compatibility of inpac and demonstrate that it is efficient.
urca: pulling out anomalies by their root causes. traffic anomaly detection has received a lot of attention over recent years, but understanding the nature of these anomalies and identifying the flows involved is still a manual task, in most cases. we introduce unsupervised root cause analysis (urca) which isolates anomalous traffic and classifies alarms with minimal manual assistance and high accuracy. urca proceeds by successive reduction of the anomalous space, eliminating normal traffic based on feedback from the anomaly detection method. classification is done by clustering a new anomaly with previously labeled events. we validate urca using manually analyzed real anomalies as well as synthetic anomaly injection. our validation shows that urca can accurately diagnose a large range of anomaly types, including network scans, ddos attacks, and major routing changes.
network reliability with geographically correlated failures. fiber-optic networks are vulnerable to natural disasters, such as tornadoes or earthquakes, as well as to physical failures, such as an anchor cutting underwater fiber cables. such real-world events occur in specific geographical locations and disrupt specific parts of the network. therefore, the geography of the network determines the effect of physical events on the network's connectivity and capacity. in this paper, we develop tools to analyze network failures after a 'random' geographic disaster. the random location of the disaster allows us to model situations where the physical failures are not targeted attacks. in particular, we consider disasters that take the form of a 'random' line in a plane. using results from geometric probability, we are able to calculate some network performance metrics to such a disaster in polynomial time. in particular, we can evaluate average two-terminal reliability in polynomial time under 'random' line-cuts. this is in contrast to the case of independent link failures for which there exists no known polynomial time algorithm to calculate this reliability metric. we also present some numerical results to show the significance of geometry on the survivability of the network and discuss network design in the context of random line-cuts. our novel approach provides a promising new direction for modeling and designing networks to lessen the effects of geographical disasters or attacks.
first-fit scheduling for beaconing in multihop wireless networks. beaconing is a primitive communication task in which every node locally broadcasts a packet to all its neighbors within a fixed distance. assume that all communications proceed in synchronous time-slots and each node can transmit at most one fixed-size packet in each time-slot. the problem minimum-latency beaconing schedule (mlbs) in multihop wireless networks seeks a shortest schedule for beaconing subject to the interference constraint. mlbs has been intensively studied since the mid-1980s, but all assume the protocol interference model with uniform interference radii. in this paper, we first present a constant-approximation algorithm for mlbs under the protocol interference model with arbitrary interference radii. then, we develop a constant-approximation algorithm for mlbs under the physical interference model. both approximation algorithms have efficient implementations in a greedy first-fit manner.
reliable adaptive multipath provisioning with bandwidth and differential delay constraints. robustness and reliability are critical issues in network management. to provide resiliency, a popular protection scheme against network failures is the simultaneous routing along multiple disjoint paths. most previous protection and restoration schemes were designed for all-or-nothing protection and thus, an overkill for data traffic. in this work, we study the reliable adaptive multipath provisioning (ramp) problem with reliability and differential delay constraints. we aim to route the connections in a manner such that link failure does not shut down the entire stream but allows a continuing flow for a significant portion of the traffic along multiple (not necessary disjoint) paths, allowing the whole network to carry sufficient traffic even when link/node failure occurs. the flexibility enabled by a multipath scheme has the tradeoff of differential delay among the diversely routed paths. this requires increased memory in the destination node in order to buffer the traffic until the data arrives on all the paths. increased buffer size will raise the network element cost and could cause buffer overflow and data corruption. therefore, differential delay between the multiple paths should be bounded by containing the delay of a path in a range. we first prove that ramp is an np-hard problem. then we present a pseudo-polynomial time solution to solve a special case of ramp, representing edge delays as integers. next, an (1 + ε)-approximation algorithm is proposed to solve the optimization version of the ramp problem. an efficient heuristic is also provided for the ramp problem. we also present numerical results confirming the advantage of our schemes as the first solution for the ramp problem.
slideor: online opportunistic network coding in wireless mesh networks. opportunistic routing significantly increases unicast throughput in wireless mesh networks by effectively utilizing the wireless broadcast medium. with network coding, opportunistic routing can be implemented in a simple and practical way without resorting to a complicated scheduling protocol. traditionally, due to the constraints of computational complexity, a protocol utilizing network coding needs to partition the data into multiple segments and encode only packets in the same segment. however, it is extremely challenging to decide the optimal time to move to the transmissions of the next segment, and existing designs all resort to different heuristic ideas that might harm network throughput. to address this problem, we propose slideor, a new protocol to encode source packets in overlapping sliding windows such that coded packets from one window position may be useful towards decoding the source packets inside another window position. through extensive simulations, we show that slideor outperforms the existing solutions and is amenable to much simpler implementation than solutions with complicated scheduling among multiple segments.
maintaining approximate minimum steiner tree and k-center for mobile agents in a sensor network. we study the problem of maintaining group communication between m mobile agents, tracked and helped by n static networked sensors. we develop algorithms to maintain a o(lg n)-approximation to the minimum steiner tree of the mobile agents such that the maintenance message cost is on average o(lg n) per each hop an agent moves. the key idea is to extract a 'hierarchical well-separated tree (hst)' on the sensor nodes such that the tree distance approximates the sensor network hop distance by a factor of o(lg n). we then prove that maintaining the subtree of the mobile agents on the hst uses logarithmic messages per hop movement. with the hst we can also maintain o(lg n) approximate k-center for the mobile agents with the same message cost. both the minimum steiner tree and the k-center problems are np-hard and our algorithms are the first efficient algorithms for maintaining approximate solutions in a distributed setting.
efficient tag identification in mobile rfid systems. in this paper we consider how to efficiently identify tags on the moving conveyor. considering conditions like the path loss and multi-path effect in realistic settings, we first propose a probabilistic model for rfid tag identification. based on this model, we propose efficient solutions to identify moving rfid tags, according to the fixed-path mobility on the conveyor. a dynamic program based solution and an adaptive solution are proposed to select optimized frame sizes during the query cycles. simulation results indicate that by leveraging the probabilistic model our solutions can achieve much better performance than using parameters for the ideal propagation situations.
pinpoint time difference of arrival for unsynchronized 802.11 wireless cards. the ability to measure location using time of flight in 802.11 networks is impeded by the standard one microsecond clock resolution, imprecise synchronization of the 802.11 protocol, and the inaccuracy of available clock oscillators. we demonstrate a technique for off-the-shelf 802.11 hardware that enables accurate determination of location of transmitting 802.11 devices using time difference of arrival (tdoa). the technique refines the pinpoint clock model for 802.11 wireless cards, enabling accurate translation of times from one frame of reference to another for free-running clocks and producing accurate location of transmitting nodes to within 3m. this technique can locate nodes regardless of their participation in the location system and may be applied to other wireless communication protocols where send and receive timestamps are available.
measurement and diagnosis of address misconfigured p2p traffic. misconfigured p2p traffic caused by bugs in volunteer-developed p2p software or by attackers is prevalent. it influences both end users and isps. in this paper, we discover and study address-misconfigured p2p traffic, a major class of such misconfiguration. p2p address misconfiguration is a phenomenon in which a large number of peers send p2p file downloading requests to a "random" target on the internet. on measuring three honeynet datasets spanning four years and across five different /8 networks, we find address-misconfigured p2p traffic on average contributes 38.9% of internet background radiation, increasing by more than 100% every year. in this paper, we design the p2pscope, a measurement tool, to detect and diagnose such unwanted traffic. after analyzing about two tb data and tracking millions of peers, we find, in all the p2p systems, address misconfiguration is caused by resource mapping contamination, i.e., the sources returned for a given file id through p2p indexing are not valid. different p2p systems have different reasons for such contamination. for emule, we find that the root cause is mainly a network byte ordering problem in the emule source exchange protocol. for bittorrent misconfiguration, one reason is that anti-p2p companies actively inject bogus peers into the p2p system. another reason is that the ktorrent implementation has a byte order problem. we also design approaches to detect anti-p2p peers without false positives.
m-polar: channel allocation for throughput maximization in sdr mesh networks. in traditional wireless networks, nodes use only a single channel per radio interface, thus limiting the overall channel diversity of the network. this restriction is due to the inherent limitations of commercially-available rf devices. with the advent of high-bandwidth software-defined radios (sdrs), we now have the option of assigning multiple contiguous, independent channels to a single wireless interface. this new-found opportunity raises an important question: how do we assign contiguous channels to nodes in order to maximize overall network throughput? this question lies at the often-ignored intersection of single-radio-multi-channel and multi-radio-multi-channel assignment schemes. in this paper, we develop a protocol that assigns contiguous channels with the goal of evenly spreading the load across the multiple channels. neighboring nodes greedily adjust their channel ranges according to channel conditions to achieve an overall pattern of partially-overlapping bandwidths that maximizes the network throughput. the end-result is a network that can dynamically adapt its bandwidth usage to the network load and the conditions of the different channels. the proposed protocol is evaluated with a prototype built upon the usrp as well as with detailed simulation.
throughput, delay, and mobility in wireless ad hoc networks. throughput capacity in wireless ad hoc networks has been studied extensively under many different mobility models such as i.i.d. mobility model, brownian mobility model, random walk model, and so on. most of these research works assume global mobility, i.e., each node moves around in the whole network, and the results show that a constant per-node throughput can be achieved at the cost of very high expected average end-to-end delay. thus, we are having a very big gap here, either low throughput and low delay in static networks or high throughput and high delay in mobile networks. in this paper, employing a more practical restricted random mobility model, we try to fill in this gap. specifically, we assume a network of unit area with n nodes is evenly divided into n2α cells with an area of n-2αwhere 0 ≤ α ≤ 1/2 , each of which is further evenly divided into squares with an area of n-2β where 0 ≤ β ≤ 1/2. all nodes can only move inside the cell which they are initially distributed in, and at the beginning of each time slot, every node moves from its current square to a uniformly chosen point in an uniformly chosen adjacent square. proposing a new multi-hop relay scheme, we present an upper bound and a lower bound on per-node throughput capacity and expected average end-to-end delay, respectively. we finally explicitly show smooth trade-offs between throughput and delay by controlling nodes' mobility.
designing low-capacity backup networks for fast restoration. there are two basic approaches to allocate protection resources for fast restoration. the first allocates resources upon the arrival of each connection request; yet, it incurs significant setup time and is often capacity-inefficient. the second approach allocates protection resources during the network configuration phase; therefore, it needs to accommodate any possible arrival pattern of connection requests, hence potentially calling for a substantial over-provisioning of resources. however, in this study we establish the feasibility of this approach. specifically, we consider a scheme that, during the network configuration phase, constructs an (additional) low-capacity backup network. upon a failure, traffic is rerouted through a bypass in the backup network. we establish that, with proper design, backup networks induce feasible capacity overhead. we further impose several design requirements (e.g., hop-count limits) on backup networks and their induced bypasses, and prove that, commonly, they also incur minor overhead. motivated by these findings, we design efficient algorithms for the construction of backup networks.
towards mobile phone localization without war-driving. this paper identifies the possibility of using electronic compasses and accelerometers in mobile phones, as a simple and scalable method of localization without war-driving. the idea is not fundamentally different from ship or air navigation systems, known for centuries. nonetheless, directly applying the idea to human-scale environments is non-trivial. noisy phone sensors and complicated human movements present practical research challenges. we cope with these challenges by recording a person's walking patterns, and matching it against possible path signatures generated from a local electronic map. electronic maps enable greater coverage, while eliminating the reliance on wifi infrastructure and expensive war-driving. measurements on nokia phones and evaluation with real users confirm the anticipated benefits. results show a location accuracy of less than 11m in regions where today's localization services are unsatisfactory or unavailable.
overcoming failures: fault-tolerance and logical centralization in clean-slate network management. we investigate the design of a clean-slate control and management plane for data networks using the abstraction of 4d architecture, utilizing and extending 4d's concept of logically centralized decision plane that is responsible for managing network-wide resources. in this paper, a dynamically adaptable algorithm for assigning data plane devices to a physically distributed decision plane is presented, which enables a network to operate with minimal configuration and human intervention, while providing optimal convergence and robustness against failures. our work is especially relevant in the context of isps and large geographically dispersed enterprise networks, where robust and scalable network-wide control of a large number of heterogeneous devices is desired.
sparsetrack: enhancing indoor pedestrian tracking with sparse infrastructure support. accurate indoor pedestrian tracking has wide applications in the healthcare, retail, and entertainment industries. however, existing approaches to indoor tracking have various limitations. for example, location-fingerprinting approaches are labor-intensive and vulnerable to environmental changes. trilateration approaches require at least three line-of-sight (los) beacons to cover any point in the service area, which results in heavy infrastructure cost. dead reckoning (dr) approaches rely on knowledge of the initial user location and suffer from tracking error accumulation. despite this, we adopt dr for location tracking because of the recent emergence of affordable hand-held devices equipped with low cost dr-enabling sensors. in this paper, we propose an indoor pedestrian tracking system which comprises a dr sub-system implemented on a mobile phone, and a ranging sub-system with a sparse infrastructure. a probabilistic fusion scheme is applied to bound the accumulated tracking error of dr when new range measurements are available from sparsely deployed beacons. experimental results show that the proposed system is able to track users much better than dr alone, with reductions in average error by up to 71.9%. the system is robust and works well even when the initial user location is not available and range updates are intermittent. this highlights the potential of using sparse but reasonably accurate partial information to limit location tracking errors.
diffprobe: detecting isp service discrimination. we propose an active probing method, called differential probing or diffprobe, to detect whether an access isp is deploying forwarding mechanisms such as priority scheduling, variations of wfq, or wred to discriminate against some of its customer flows. diffprobe aims to detect if the isp is doing one or both of delay discrimination and loss discrimination. the basic idea in diffprobe is to compare the delays and packet losses experienced by two flows: an application flow a and a probing flow p. the paper describes the statistical methods that diffprobe uses, a novel method for distinguishing between strict priority and wfq-variant packet scheduling, simulation and emulation experiments, and a few real-world tests at major access isps.
price of anarchy in non-cooperative load balancing. we investigate the price of anarchy of a load balancing game with k dispatchers. the service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. the performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. for this game, we first show that, for a fixed amount of total incoming traffic, the worst-case nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. for this symmetric game, we provide the expression for the loads on the servers at the nash equilibrium. using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the nash equilibrium to the global cost of the centralized setting, is lower bounded by k/(2√k - 1) and upper bounded by √k, independently of the number of servers.
an axiomatic theory of fairness in network resource allocation. we present five axioms for fairness measures in resource allocation. a family of fairness measures satisfying the axioms is constructed. special cases of this family include a-fairness, jain's index, and entropy. properties of fairness measures satisfying the axioms are proven, including schurconcavity. among the engineering implications is a generalized jain's index that tunes the resolution of fairness measure, a new understanding of a-fair utility functions, and an interpretation of "larger a is more fair". we also construct an alternative set of axioms to capture system efficiency and feasibility constraints.
universal rigidity: towards accurate and efficient localization of wireless networks. a fundamental problem in wireless ad-hoc and sensor networks is that of determining the positions of nodes. often, such a problem is complicated by the presence of nodes whose positions cannot be uniquely determined. most existing work uses the notion of global rigidity from rigidity theory to address the non-uniqueness issue. however, such a notion is not entirely satisfactory, as it has been shown that even if a network localization instance is known to be globally rigid, the problem of determining the node positions is still intractable in general. in this paper, we propose to use the notion of universal rigidity to bridge such disconnect. although the notion of universal rigidity is more restrictive than that of global rigidity, it captures a large class of networks and is much more relevant to the efficient solvability of the network localization problem. specifically, we show that both the problem of deciding whether a given network localization instance is universally rigid and the problem of determining the node positions of a universally rigid instance can be solved efficiently using semidefinite programming (sdp). then, we give various constructions of universally rigid instances. in particular, we show that trilateration graphs are generically universally rigid, thus demonstrating not only the richness of the class of universally rigid instances, but also the fact that trilateration graphs possess much stronger geometric properties than previously known. finally, we apply our results to design a novel edge sparsification heuristic that can reduce the size of the input network while provably preserving its original localization properties. one of the applications of such heuristic is to speed up existing convex optimization-based localization algorithms. simulation results show that our speedup approach compares very favorably with existing ones, both in terms of accuracy and computation time.
a balanced consistency maintenance protocol for structured p2p systems. a fundamental challenge of managing mutable data replication in a peer-to-peer (p2p) system is efficiently maintaining consistency under various sharing patterns with heterogeneous resource capabilities. this paper presents a framework for balanced consistency maintenance (bcom) in structured p2p systems. replica nodes of each object are organized into a tree for disseminating updates, and a sliding window update protocol is developed to bound the consistency. the effect of window size in response to dynamic network conditions, workload updates and resource limits is analyzed through a queueing model. this enables us to balance availability, performance and consistency strictness for various application requirements. on top of the dissemination tree, two enhancements are proposed: a fast recovery scheme to strengthen the robustness against node and link failures; and a node migration policy to remove and prevent the bottleneck for better system performance. simulations are conducted using p2psim to evaluate bcom in comparison to scope [2]. the experimental results demonstrate that bcom significantly improves the availability of scope by lowering the discard rate from almost 100% to 5% with slight increase in latency.
delay analysis for cognitive radio networks with random access: a fluid queue view. we consider a cognitive radio network where multiple secondary users (sus) contend for spectrum usage, using random access, over available primary user (pu) channels. our focus is on sus' queueing delay performance, for which a systematic understanding is lacking. we take a fluid queue approximation approach to study the steady-state delay performance of sus, for cases with a single pu channel and multiple pu channels. using stochastic fluid models, we represent the queue dynamics as poisson driven stochastic differential equations, and characterize the moments of the sus' queue lengths accordingly. since in practical systems, a secondary user would have no knowledge of other users' activities, its contention probability has to be set based on local information. with this observation, we develop adaptive algorithms to find the optimal contention probability that minimizes the mean queue lengths. moreover, we study the impact of multiple channels and multiple interfaces, on sus' delay performance. as expected, the use of multiple channels and/or multiple interfaces leads to significant delay reduction.
an investigation on the nature of wireless scheduling. the paper studies the complexity of the wireless scheduling problem under interference constraints.we first relate the definition of the capacity region to the weighted fractional coloring problem. then, the scheduling-for-stability problem under deterministic arrivals is studied in light of this relationship. we emphasize the requirement that the scheduling algorithm uses a tractable amount of processing and storage resources. two classes of algorithms are defined and a complexity result is derived for the intersection of the two classes. we also exhibit an algorithm that can achieve the storage requirement by relaxing the processing requirement. the results are used to examine interesting sections of the capacity region. finally, we relate the new interpretation and theory about the capacity region to the notion of set σ-local pooling.
change management in enterprise it systems: process modeling and capacity-optimal scheduling. we provide a formal model for the change management process for enterprise it systems, and develop change scheduling algorithms that seek to attain the "change capacity" of the system. the change management process handles critical updates in the system that often use overlapping sets of servers, resulting in scheduling conflicts between the corresponding change classes. furthermore, applications are typically associated with certain permissible downtime windows, which impose constraints on the timing of the change executions. scheduling of changes for such systems represent a complex dynamic optimization question. in a limiting fluid regime, where changes are assumed nonatomic, we develop a scheduling policy that provably attains the change capacity of the system. we then propose and evaluate an atomic approximation of the optimal fluid scheduling policy, which is well suited for application to a real change management system. simulation results demonstrate that the expected change execution delay and the capacity attained by the approximate policy is close to the best attainable values, when unavoidable capacity losses due to fragmentation effects are taken into account and is significantly better than a randomized scheduling policy.
mobile sensor deployment in unknown fields. in this paper we propose grease, a distributed algorithm to deploy mobile sensors in an unknown environment with obstacles and field asperities that may cause sensing anisotropies and non uniform device capabilities. these aspects are not taken into account by traditional approaches to the problem of mobile sensor self-deployment. grease works by realizing a grid-shaped deployment throughout the area of interest (aoi) and adaptively refining the grid to find new sensor positions to cover the target area more precisely in the zones where devices experience reduced movement, sensing and communication capabilities. we give bounds on the number of sensors necessary to cover an aoi with obstacles and noisy zones. simulations show that grease provides a fast deployment with precise movements and no oscillations, with moderate energy consumption.
flow control for cost-efficient peer-to-peer streaming. in this paper we address the issue of network cost efficiency for live streaming peer-to-peer systems. we formalize this as an optimization problem, which features a generic cost function. the latter is appropriate to capture not only ispspecific link weights, but also non-linear, congestion-dependent costs. our main contribution is the introduction of the implicit-primal-dual scheme for flow control in live streaming peer-topeer systems. it is fully distributed in that it relies only on local state variable exchanges. moreover, we show that at a fluid scale, combined with random linear network coding, it admits the cost optimal operating point as a fixed point.we also prove asymptotic boundedness of fluid trajectories for particular cost functions.we finally show via experiments that these optimality properties are resilient to operational constraints such as finite generation size and finite field size.
spring: a social-based privacy-preserving packet forwarding protocol for vehicular delay tolerant networks. in this paper, we propose a social-based privacy-preserving packet forwarding protocol, called spring, for vehicular delay tolerant networks (dtns). with spring, roadside units (rsus) deployed along the roadside can assist in packet forwarding to achieve highly reliable transmissions. in specific, we first heuristically define how to evaluate each traffic intersection's social degree in a vehicular dtn. based on the social degree information, we then strategically place rsus at some high-social intersections. as a result, these rsus can provide tremendous assistance in temporarily storing packets and helping packet forwarding to achieve high delivery ratio. performance evaluations via extensive simulations demonstrate the spring's efficiency. in addition, detailed security analyses show that the proposed spring can achieve conditional privacy preservation and resist most attacks existing in vehicular dtns.
metrics for evaluating video streaming quality in lossy ieee 802.11 wireless networks. peak signal-to-noise ratio (psnr) is the simplest and the most widely used video quality evaluation methodology. however, traditional psnr calculations do not take the packet loss into account. this shortcoming, which is amplified in wireless networks, contributes to the inaccuracy in evaluating video streaming quality in wireless communications. such inaccuracy in psnr calculations adversely affects the development of video communications in wireless networks. this paper proposes a novel video quality evaluation methodology. as it not only considers the psnr of a video, but also with modificatioils to handle the packet loss issue, we name this evaluation method mpsnr. mpsnr rectifies the inaccuracies in traditional psnr computation, and helps us to approximate subjective video quality, mean opinion score (mos), more accurately. using psnr values calculated from mpsnr and simple network measurements, we apply linear regression techniques to derive two specific objective video quality metrics, psnr-based objective mos (pomos) and rates-based objective mos (romos). through extensive experiments and human subjective tests, we show that the two metrics demonstrate high correlation with mos. pomos takes the averaged psnr value of a video calculated from mpsnr as the only input. despite its simplicity, it has a pearson correlation of 0.8664 with the mos. by adding a few other simple network measurements, such as the proportion of distorted frames in a video, romos achieves an even higher pearson correlation (0.9350) with the mos. compared with the psnr metric from the traditional psnr calculations, our metrics evaluate video streaming quality in wireless networks with a much higher accuracy while retaining the simplicity of psnr calculation.
peoplerank: social opportunistic forwarding. in opportunistic networks, end-to-end paths between two communicating nodes are rarely available. in such situations, the nodes might still copy and forward messages to nodes that are more likely to meet the destination. the question is which forwarding algorithm offers the best trade off between cost (number of message replicas) and rate of successful message delivery. we address this challenge by developing the peoplerank approach in which nodes are ranked using a tunable weighted social information. similar to the pagerank idea, peoplerank gives higher weight to nodes if they are socially connected to other important nodes of the network. we develop centralized and distributed variants for the computation of peoplerank. we present an evaluation using real mobility traces of nodes and their social interactions to show that peoplerank manages to deliver messages with near optimal success rate (i.e., close to epidemic routing) while reducing the number of message retransmissions by 50% compared to epidemic routing.
optimal sinr-based random access. random access protocols, such as aloha, are commonly modeled in wireless ad-hoc networks by using the protocol model. however, it is well-known that the protocol model is not accurate and particularly it cannot account for aggregate interference from multiple interference sources. in this paper, we use the more accurate physical model, which is based on the signal-to-interference-plus-noise-ratio (sinr), to study optimization-based design in wireless random access systems, where the optimization variables are the transmission probabilities of the users. we focus on throughput maximization, fair resource allocation, and network utility maximization, and show that they entail non-convex optimization problems if the physical model is adopted. we propose two schemes to solve these problems. the first design is centralized and leads to the global optimal solution using a sum-of-squares technique. however, due to its complexity, this approach is only applicable to small-scale networks. the second design is distributed and leads to a close-to-optimal solution using the coordinate ascent method. this approach is applicable to medium-size and large-scale networks. based on various simulations, we show that it is highly preferable to use the physical model for optimization-based random access design. in this regard, even a sub-optimal design based on the physical model can achieve a significantly better performance than an optimal design based on the inaccurate protocol model.
a secondary market for spectrum. dynamic spectrum trading amongst small cognitive users is fundamentally different along two axes: temporal variation, and spatial variation of user demand and channel condition. we advocate that a spectrum secondary market, analogous to the stock market, is to be established for users to dynamically trade among themselves their channel holdings obtained in the primary market from legacy owners. we design a market mechanism based on dynamic double auctions, creating a marketplace in the air to match bandwidth demand with supply. in the analysis we prove important economic properties of the mechanism, notably its truthfulness and asymptotic efficiency in maximizing spectrum utilization. complimentary simulation studies corroborate that spectrum utilization and user performance can be improved by establishing the spectrum secondary market.
chameleon: adaptive peer-to-peer streaming with network coding. layered streaming can be used to adapt to the available download capacity of an end-user, and such adaptation is very much required in real world http media streaming. the multiple layer codec has become more refined, as svc (the scalable extension of the h.264/avc standard) has been standardized with a bit rate overhead of around 10% and an indistinguishable visual quality, compared to the state of the art single layer codec. peer-to-peer streaming systems have also become the reality. the important question is how such layered coding can be used in real world peer-to-peer streaming systems. this paper tries to explore the feasibility of using network coding to make layered peer-to-peer streaming much more realistic, by combining network coding and svc in a fine granularity manner. we present chameleon, our new peer-to-peer streaming algorithm designed to incorporate network coding seamlessly with svc. key components with different design options of chameleon are presented and experimentally evaluated, with the objective of investigating benefits of network coding in combination with svc. we carry out extensive experiments on real stream data to (i) evaluate the performance of chameleon in terms of playback skips and delivered video quality, and (ii) understand its insights. our results demonstrate the feasibility of the approach and bring us one step closer to real adaptive peer-to-peer streaming.
optimal solutions for single fault localization in two dimensional lattice networks. achieving fast, precise, and scalable fault localization has long been a highly desired feature in all-optical mesh networks. monitoring tree (m-tree) is an interesting method that has been introduced as the most general monitoring structure for achieving unambiguous failure localization (ufl). ideally, with j m-trees one can monitor up to 2j - 1 links when a single failure has to be located. such a logarithmic behavior has also been observed in numerous case studies of real life network topologies [1], [2]. it is expected that the m-tree framework will lead to a highly scalable link failure monitoring mechanism for not only all-optical mesh networks, but any possible future information system with mesh topologies, such as all-optical mesh networks, touch panels, quantum computing, and vlsi. it is an important task to investigate the extent such an optimal logarithmic behavior may hold, in particular in practically relevant network topologies. as an endeavor toward this goal, the paper investigates the problem by identifying essentially tight logarithmic bounds for two dimensional lattice networks. experiments are conducted to show the feasibility and performance of the proposed constructions.
an experimental case for simo random access in multi-hop wireless networks. in this paper, we demonstrate that multiple concurrent asynchronous and uncoordinated single-input multiple-output (simo) transmissions can successfully take place even though the respective receivers do not explicitly null out interfering signals. thus motivated, we propose simple modifications to the widely deployed ieee 802.11 mac to enable multiple nonspatially-isolated simo sender-receiver pairs to share the medium. namely, we propose to increase the physical carrier sensing threshold, disable virtual carrier sensing, and enable message in message packet detection.we use experiments to show that while increasing the peak transmission rate, spatial multiplexing schemes such as those employed by the ieee 802.11n are highly non-robust to asynchronous and uncoordinated interferers. in contrast, we show that the proposed multi-flow simo mac scheme alleviates the severe unfairness resulting from uncoordinated transmissions in 802.11 multi-hop networks.
handling triple hidden terminal problems for multi-channel mac in long-delay underwater sensor networks. in this paper, we investigate the multi-channel mac problem in underwater acoustic sensor networks. to reduce hardware cost, only one acoustic transceiver is often preferred on every node. in a single-transceiver multi-channel long-delay underwater network, new hidden terminal problems, namely multi-channel hidden terminal and long-delay hidden terminal (together with the traditional multi-hop hidden terminal problem, we refer to them as "triple hidden terminal problems"), are identified and studied in this paper. based on our findings, we propose a new mac protocol, called cumac, for long delay multi-channel underwater sensor networks. cumac utilizes the cooperation of neighboring nodes for collision detection, and a simple tone device is designed for distributed collision notification, providing better system efficiency while keeping overall cost low. analytical and simulation results show that cumac can greatly improve the system throughput and energy efficiency via effectively solving the complicated triple hidden terminal problems.
risk-aware routing for optical transport networks. a service level agreement (sla) typically specifies the availability a service provider (sp) promises to a customer. in an optical transport network, finding a lightpath for a connection is commonly based on whether the availability of a lightpath availability complies with the connection's sla-requested availability. because of the stochastic nature of network failures, the actual availability of a lightpath over a specific time period is subject to uncertainty, and the sla is usually at risk. we consider the network uncertainty, and study routing to minimize the probability of sla violation. first, we use a single-link model to study sla violation risk (i.e., the probability of sla violation) under different settings. we show that sla violation risk may vary by paths and is affected by other factors (e.g., failure rate, connection holding time, etc.), and hence cannot be simply described by path availability. we then formulate the problem of risk-aware routing in mesh networks, in which routing decisions are dictated by sla violation risk. in particular, we focus on devising a scheme capable of computing lightpath(s) that are likely to successfully accommodate a connection's sla-requested availability. a novel technique is applied to convert links with heterogeneous failure profiles to reference links which capture the main risk features in a relative manner. based on the "reference link" concept, we present a polynomial risk-aware routing scheme using only limited failure information. in addition, we extend our risk-aware routing scheme to incorporate shared path protection (spp) when protection is needed. we evaluate the performance and demonstrate the effectiveness of our schemes in terms of sla violation ratio and, more generally, contrast them with the generic availability-aware approaches.
hand: fast handoff with null dwell time for ieee 802.11 networks. how to reduce the handoff delay and how to make appropriate handoff decisions are two fundamental challenges in designing an effective handoff scheme for 802.11 networks to provide seamless and satisfactory data roaming services to mobile users. in this paper, we propose a unique fast handoff scheme called hand (handoff with null dwell time). hand adopts a novel zero-channel-dwell-time architecture which leverages on the communication backbone between aps to relay the information about wireless channels, and allows the ap (rather than the station) to make appropriate handoff decisions aiming at providing fair service satisfaction to all stations. hand is a software-only solution and compatible with the 802.11 standard without modifying the 802.11 protocol or introducing new wireless frames. we have implemented it in the madwifi device driver and demonstrated its effectiveness via experiments.
characterizing interactive behavior in a large-scale operational iptv environment. we investigate the user viewing activity for broadcast tv, pre-recorded content using digital video recording (dvr) and video on demand (vod) in an ip-based content distribution environment. advanced stream control functions (play, pause, skip, rewind, etc.) provide users with a high level of interactivity, but place demands on the distribution infrastructure (servers, network, home-network) that can be difficult to manage at large scale. to support system design as well as network capacity planning, it is necessary to have a good model of user interaction. using traces from a well-provisioned operational environment with a large user population, we first characterize interactivity for broadcast tv, dvr and vod. we then develop parametric models of individual users stream control operations for vod. our analysis shows that interactive behavior is adequately characterized by two semi-markov models, one for weekdays and another for weekends. we propose a parametric model for the underlying sojourn time distributions and show that it results in a superior fit compared to well known distributions (generalized pareto and weibull). in order to validate that our models faithfully capture user behavior, we compare the workload that a vod server experiences in response to actual traces and synthetic data generated from our proposed models.
tight performance bounds in the worst-case analysis of feed-forward networks. network calculus theory aims at evaluating worstcase performances in communication networks. it provides methods to analyze models where the traffic and the services are constrained by some minimum and/or maximum envelopes (service/arrival curves). while new applications come forward, a challenging and inescapable issue remains open: achieving tight analyzes of networks with aggregate multiplexing. the theory offers efficient methods to bound maximum endto-end delays or local backlogs. however as shown recently, those bounds can be arbitrarily far from the exact worst-case values, even in seemingly simple feed-forward networks (two flows and two servers), under blind multiplexing (i.e. no information about the scheduling policies, except fifo per flow). for now, only a network with three flows and three servers, as well as a tandem network called sink tree, have been analyzed tightly. we describe the first algorithm which computes the maximum end-to-end delay for a given flow, as well as the maximum backlog at a server, for any feed-forward network under blind multiplexing, with concave arrival curves and convex service curves. its computational complexity may look expensive (possibly super-exponential), but we show that the problem is intrinsically difficult (np-hard). fortunately we show that in some cases, like tandem networks with cross-traffic interfering along intervals of servers, the complexity becomes polynomial. we also compare ourselves to the previous approaches and discuss the problems left open.
convergence speed of binary interval consensus. we consider the convergence time for solving the binary interval consensus problem using a distributed algorithm proposed by benezit at al (2009) for computing the quantized average value. in the binary consensus problem, each node initially holds one of two states and the goal for each node is to correctly decide which one of the two states was initially held by a majority of nodes. we derive an upper bound on the expected convergence time that holds for arbitrary connected graphs, which is based on the location of eigenvalues of some contact rate matrices. we instantiate our bound for particular networks of interest, including complete graphs, star-shaped networks, and erdös-rényi random graphs, and in the former two cases compare with alternative computations. we find that for all these examples our bound is of exact order with respect to the number of nodes. we pinpoint the fact that the expected convergence time critically depends on the voting margin defined as the difference between the fraction of the nodes that initially held the majority and the minority states, respectively. we derive an exact relation between the expected convergence time and the voting margin, for some of these graphs, which reveals how the expected convergence time tends to infinity as the voting margin approaches zero. our results provide insights on how the expected convergence time depends on the network topology which can be used for performance evaluation and network design. the results are of interest in the context of peer-to-peer systems; in particular, for sensor networks and distributed databases.
a signal processing view on packet sampling and anomaly detection. anomaly detection methods typically operate on preprocessed traffic traces. firstly, most traffic capturing devices today employ random packet sampling, where each packet is selected with a certain probability, to cope with increasing link speeds. secondly, temporal aggregation, where all packets in a measurement interval are represented by their temporal mean, is applied to transform the traffic trace to the observation timescale of interest for anomaly detection. these preprocessing steps affect the temporal correlation structure of traffic that is used by anomaly detection methods such as kalman filtering or pca, and have thus an impact on anomaly detection performance. prior work has analyzed how packet sampling degrades the accuracy of anomaly detection methods; however, neither theoretical explanations nor solutions to the sampling problem have been provided. this paper makes the following key contributions: (i) it provides a thorough analysis and quantification of how random packet sampling and temporal aggregation modify the signal properties by introducing noise, distortion and aliasing. (ii) we show that aliasing introduced by the aggregation step has the largest impact on the correlation structure. (iii) we further propose to replace the aggregation step with a specifically designed low-pass filter that reduces the aliasing effect. (iv) finally, we show that with our solution applied, the performance of anomaly detection systems can be considerably improved in the presence of packet sampling.
from time domain to space domain: detecting replica attacks in mobile ad hoc networks. a common vulnerability of wireless networks, in particular, the mobile ad hoc network (manet), is their susceptibility to node compromise/physical capture attacks since the wireless devices are often not protected by tamper-resistant hardware due to small form factors and low cost, and can be easily stolen/lost or temporarily controlled by unauthorized entities due to their harsh working environments. a serious consequence of the device capture attack is the node replication attacks in which adversaries deploy a large number of replicas of the compromised/captured nodes throughout the network. replicated nodes have all legitimate security credentials and therefore can launch various insider attacks, or even take over the network easily. they are indeed "attack multipliers" and therefore are extremely destructive to the network. detecting replication attacks is a nontrivial problem in manets due to the challenges resulted from node mobility, cloned/compromised node collusion, and the large number and wide spread of the replicas. existing approaches either fail in mobile environments due to the limitations caused by local views or their dependence on invariant claims such as location and neighbor list, or are constrained by the number, distribution, and colluding activities of the replicas. in this paper, we propose two replication detection schemes (tdd and sdd) to tackle all these challenges from both the time domain and the space domain. our theoretical analysis indicates that tdd and sdd provide high detection accuracy and excellent resilience against smart and colluding replicas, have no restriction on the number and distribution of replicas, and incur low communication/computation overhead. to our best knowledge, tdd and sdd are the only approaches that support mobile networks while place no restrictions on the number and distribution of the cloned frauds and on whether the replicas collude or not.
characterization of non-manipulable and pareto optimal resource allocation strategies for interference coupled wireless systems. this paper investigates the properties of social choice functions that represent resource allocation strategies in interference coupled wireless systems. the allocated resources can be physical layer parameters such as power vectors or antenna weights. strategy proofness and efficiency of social choice functions are used to capture the respective properties of resource allocation strategy outcomes being non-manipulable and pareto optimal. in addition, this paper introduces and investigates the concepts of (strict) intuitive fairness and nonparticipation in interference coupled systems. the analysis indicates certain inherent limitations when designing strategy proof and efficient resource allocation strategies, if the intuitive fairness and nonparticipation are imposed. these restrictions are investigated in an analytical social choice function framework for interference coupled wireless systems. among other results, it is shown that a strategy proof and efficient resource allocation strategy for interference coupled wireless systems cannot simultaneously satisfy continuity and the frequently encountered property of non-participation.
performance modeling and analysis of multi-path routing in integrated fiber-wireless networks. in an integrated fiber and wireless access (fiwi) network, multi-path forwarding may be applied in the wireless subnetwork to improve throughput. due to the delay difference along multiple paths, reordered packets of a flow may arrive at the optical line terminal (olt) waiting for dispatching to the internet, which may deteriorate the tcp performance. as all traffic in a fiwi network is sent out through the olt, the olt serves as a convergence node which naturally makes it possible to resequence packets at the olt before they are sent to the internet. the fundamental difference between resequencing at the end systems and resequencing at an intermediate node (e.g., the olt) is that very tight resequencing delay can be tolerated in the latter. thus, resequencing at the intermediate nodes must be fast enough. in this paper, we propose an integrated flow assignment and resequencing approach which jointly determines the probability of sending packets along each path from the source and needs virtually zero resequencing delay at the olt to reduce the out-of-order probability when packets are injected to the internet from the access network. simulation results validate our analysis and the effectiveness of the proposed integrated flow assignment and resequencing approach.
user-centric network fairness through connection-level control. methods for network resource allocation have mainly focused on establishing fairness among the rates of individual flows. however, since multiple tcp connections in one or many paths can serve a common user, we advocate in this paper a user-centric notion of fairness, which we formulate in the network utility maximization (num) framework. in particular, we develop control laws for the number of connections identified with a certain user, which can include single-path, multipath or more general aggregates of flows, and prove convergence to the optimal resource allocation. this theory applies directly to the case of cooperative users. in the case where connections are generated exogenously by possibly non-cooperative users, we develop admission control policies that ensure both network stability and user-centric fairness.
design and optimization of a tiered wireless access network. although having high potential for broadband wireless access, wireless mesh networks are known to suffer from throughput and fairness problems, and are thus hard to scale to large size. to this end, hierarchical architectures provide a solution to this scalability problem. in this paper, we address the problem of design and optimization of a tiered wireless access network. at the lower tier, mesh routers are clustered based on traffic demands and delay requirements. the cluster heads are equipped with wireless optical transceivers and form the upper tier free space optical (fso) network. we first present a plane sweeping and clustering algorithm aiming to minimize the number of clusters. psc sweeps the network area and captures cluster members under delay and traffic load constraints. we then present an algebraic connectivity-based formulation for fso network topology optimization and develop a greedy edge-appending algorithm that iteratively inserts edges to maximize algebraic connectivity. the proposed algorithms are analyzed and evaluated via simulations, and are shown to be highly effective as compared to the performance bounds derived in this paper.
stimulating cooperation in multi-hop wireless networks using cheating detection system. in multi-hop wireless networks, the mobile nodes usually act as routers to relay packets generated from other nodes. however, selfish nodes do not cooperate but make use of the honest ones to relay their packets, which has negative effect on fairness, security, and performance of the network. in this paper, we propose a novel incentive mechanism to stimulate cooperation in multi-hop wireless networks. fairness can be achieved by using credits to reward the cooperative nodes. the overhead can be significantly reduced by using a cheating detection system (cds) to secure the payment. extensive security analysis demonstrates that the cds can identify the cheating nodes effectively under different cheating strategies. simulation results show that the overhead of the proposed incentive mechanism is incomparable with the existing ones.
on-line pricing of secondary spectrum access with unknown demand function and call length distribution. we consider a wireless provider who caters to two classes of customers, namely primary and secondary users. primary users have long term contracts while secondary users are admitted and priced according to current availability of excess spectrum. secondary users accept an advertised price with a certain probability defined by an underlying demand function. we analyze the problem of maximizing profit gained by admission of secondary users. previous studies in the field usually assume that the demand function is known and that the call length distribution is also known and exponentially distributed. in this paper, we analyze more realistic settings where both of these quantities are unknown. our main contribution is to derive near-optimal pricing strategies under such settings. we focus on occupancy-based pricing policies, which depend only on the total number of ongoing calls in the system. we first show that such policies are insensitive to call length distribution except through the mean. next, we introduce a new on-line, occupancy-based pricing algorithm, called measurement-based threshold pricing (mtp) that operates by measuring the reaction of secondary users to a specific price and does not require the demand function to be known. mtp optimizes a profit function that depends on price only. we prove that while the profit function can be multimodal, mtp converges to one of the local optima as fast as if the function were unimodal. lastly, we provide numerical studies demonstrating the near-optimal performance of occupancy-based policies for diverse sets of call length distributions and demand functions and the quick convergence of mtp to near-optimal on-line profit.
limitations and possibilities of path trading between autonomous systems. when forwarding packets in the internet, autonomous systems (ases) frequently choose the shortest path in their network to the next-hop as in the bgp path, a strategy known as hot-potato routing. as a result, paths in the internet are suboptimal from a global perspective. for peering ases who exchange traffic without payments, path trading - complementary deviations from hot-potato routing - appears to be a desirable solution to deal with these inefficiencies. in recent years, path trading approaches have been suggested as means for interdomain traffic engineering between neighboring ases, as well as between multiple ases to achieve global efficiency. surprisingly, little is known on the computational complexity of finding path trading solutions, or the conditions which guarantee the optimality or even approximability of a path trading protocol. in this paper we explore the computational feasibility of computing path trading solutions between ases. we first show that finding a path trading solution between a pair of ases is np-complete, and that path-trading solutions are even nphard to approximate. we continue to explore the feasibility of implementing policies between multiple ases and show that, even if the bilateral path trading problem is tractable for every as pair in the set of trading ases, path trading between multiple ases is np-hard, and np-hard to approximate as well. despite the above negative results, we show a pseudopolynomial algorithm to compute path trading solutions. thus, if the range of the instances is bounded, we show one can compute solutions efficiently for peering ases. we evaluate the path trading algorithm on pairs of ases using real network topologies. specifically, we use real pop-level maps of ases in the internet to show that path trading can substantially mitigate the inefficiencies associated with hot-potato routing.
joint energy management and resource allocation in rechargeable sensor networks. energy harvesting sensor platforms have opened up a new dimension to the design of network protocols. in order to sustain the network operation, the energy consumption rate cannot be higher than the energy harvesting rate, otherwise, sensor nodes will eventually deplete their batteries. in contrast to traditional network resource allocation problems where the resources are static, time variations in recharging rate presents a new challenge. in this paper, we first explore the performance of an efficient dual decomposition and subgradient method based algorithm, called quickfix, for computing the data sampling rate and routes. however, fluctuations in recharging can happen at a faster time-scale than the convergence time of the traditional approach. this leads to battery outage and overflow scenarios, that are both undesirable due to missed samples and lost energy harvesting opportunities respectively. to address such dynamics, a local algorithm, called snapit, is designed to adapt the sampling rate with the objective of maintaining the battery at a target level. our evaluations using the tossim simulator show that quickfix and snapit working in tandem can track the instantaneous optimum network utility while maintaining the battery at a target level. when compared with ifrc, a backpressure-based approach, our solution improves the total data rate by 42% on the average while significantly improving the network utility.
near-optimal power control in wireless networks: a potential game approach. we study power control in a multi-cell cdma wireless system whereby self-interested users share a common spectrum and interfere with each other. our objective is to design a power control scheme that achieves a (near) optimal power allocation with respect to any predetermined network objective (such as the maximization of sum-rate, or some fairness criterion). to obtain this, we introduce the potential-game approach that relies on approximating the underlying noncooperative game with a "close" potential game, for which prices that induce an optimal power allocation can be derived. we use the proximity of the original game with the approximate game to establish through lyapunov-based analysis that natural user-update schemes (applied to the original game) converge within a neighborhood of the desired operating point, thereby inducing near-optimal performance in a dynamical sense. additionally, we demonstrate through simulations that the actual performance can in practice be very close to optimal, even when the approximation is inaccurate. as a concrete example, we focus on the sumrate objective, and evaluate our approach both theoretically and empirically.
minimizing end-to-end delay in wireless networks using a coordinated edf schedule. we study the end-to-end delay bounds that can be achieved in wireless networks using packet deadlines. we assume a set of flows in the network, for which flow i has burst parameter ωi, injection rate ρi, and path length ki. it was already known that, in wireline networks, the coordinated-earliest-deadline-first (cedf) protocol can achieve and end-to-end delay of approximately (ωi/ρi)+ki, whereas other schedulers such as weighted fair queuing, have end-to-end delay bounds of the form (ωi + ki)/ρi. for the case of wireless networks of arbitrary topology, the focus has typically been more on throughput optimality than minimizing delay. in this paper, we study the delay bounds that can be achieved by combining wireless link scheduling algorithms with a cedf packet scheduler. we first present a centralized scheduler that has an end-to-end delay of approximately o(ω/ρi + σl∈pi n/rl), where rl is the total rate of flows through link l, n is the number of links in the network, and pi is the path followed by packets of flow i. we then show how to convert this into a distributed scheduler. we also study the extent to which results on the schedulability of packet deadlines can be carried over from the wireline to the wireless context. lastly, we examine ways in which the theoretical schedulers considered in this paper can be transferred to a more practical random-access based setting. this work was supported by nsf contract ccf-0728980 and was performed while the first author was visiting bell labs in summer, 2009.
opportunistic routing in multi-radio multi-channel multi-hop wireless networks. two major factors that limit the throughput in multi-hop wireless networks are the unreliability of wireless transmissions and co-channel interference. one promising technique that combats lossy wireless transmissions is opportunistic routing (or). or involves multiple forwarding candidates to relay packets by taking advantage of the broadcast nature and spacial diversity of the wireless medium. furthermore, recent advances in multi-radio multi-channel transmission technology allows more concurrent transmissions in the network, and shows the potential of substantially improving the system capacity. however, the performance of or in multi-radio multi-channel multi-hop networks is still unknown, and the methodology of studying the performance of traditional routing (tr) can not be directly applied to or. in this paper, we present our research on computing an end-to-end throughput bound of or in multiradio multi-channel multi-hop wireless networks. we formulate the capacity of or as a linear programming (lp) problem which jointly solves the radio-channel assignment and transmission scheduling. leveraging our analytical model, we gain the following insights into or: 1) or can achieve better performance than tr under different radio/channel configurations, however, in particular scenarios, tr is more preferable than or; 2) or can achieve comparable or even better performance than tr by using less radio resource; 3) for or, the throughput gained from increasing the number of potential forwarding candidates becomes marginal.
topological properties affect the power of network coding in decentralized broadcast. there exists a certain level of ambiguity regarding whether network coding can further improve download performance in p2p content distribution systems, as compared to commonly applied heuristics such as rarest first protocols. in this paper, we revisit the problem of broadcasting multiple data blocks from a single source in an overlay network using gossiplike protocols. our new finding reveals that the marginal benefit of network coding critically depends on the dynamics of network topologies. we show that although network coding is optimal as a block selection mechanism, simple non-coding protocols are close to optimal in complete and random graphs, leading to marginal benefits of network coding. however, network coding demonstrates salient benefits in clustered and time-varying topologies, which are common in real-world systems with isp-locality mechanisms implemented. through both theoretical analysis and simulation results, we unveil the underlying reasons behind discrepancies in the power of network coding under different scenarios.
adaptive calibration for fusion-based wireless sensor networks. wireless sensor networks (wsns) are typically composed of low-cost sensors that are deeply integrated with physical environments. as a result, the sensing performance of a wsn is inevitably undermined by various physical uncertainties, which include stochastic sensor noises, unpredictable environment changes and dynamics of the monitored phenomenon. traditional solutions (e.g., sensor calibration and collaborative signal processing) work in an open-loop fashion and hence fail to adapt to these uncertainties after system deployment. in this paper, we propose an adaptive system-level calibration approach for a class of sensor networks that employ data fusion to improve system sensing performance. our approach features a feedback control loop that exploits sensor heterogeneity to deal with the aforementioned uncertainties in calibrating system performance. in contrast to existing heuristic based solutions, our control-theoretical calibration algorithm can ensure provable system stability and convergence. we also systematically analyze the impacts of communication reliability and delay, and propose an optimal routing algorithm that minimizes the impact of packet loss on system stability. our approach is evaluated by both experiments on a testbed of tmotes as well as extensive simulations based on data traces gathered from a real vehicle detection experiment. the results demonstrate that our calibration algorithm enables a network to maintain the optimal detection performance in the presence of various system and environmental dynamics.
optimal channel choice for collaborative ad-hoc dissemination. collaborative ad-hoc dissemination has been proposed as an efficient means to disseminate information among devices in wireless ad-hoc networks. it is based on each device forwarding channels that the user of this device is subscribed to and helping forward some other channels. we consider the case where devices have limited resources and thus have to decide which channels to help. the goal is to identify a channel selection strategy that optimizes a global system welfare that is a function of the dissemination times across all distinct channels. we consider a random mixing mobility model under which the channel dissemination time is a function of the number of nodes that forward this channel. we show that maximizing system welfare is equivalent to an assignment problem whose solution can be obtained by a centralized greedy algorithm. we provide empirical evidence that the difference between the system welfare of an optimum assignment and some heuristics proposed in the past can be significant. furthermore, we show that the optimum social welfare can be approximated by a decentralized algorithm based on metropolis-hastings sampling and give a variant that also accounts for the battery energy. our work provides guidelines how to design decentralized channel selection algorithms that optimize an a priori defined global objective.
on the impact of tcp and per-flow scheduling on internet performance. internet performance is tightly related to the properties of tcp and udp protocols, jointly responsible for the delivery of the great majority of internet traffic. it is well understood how these protocols behave under fifo queuing and what are the network congestion effects. however, no comprehensive analysis is available when flow-aware mechanisms such as per-flow scheduling and dropping policies are deployed. previous simulation and experimental results leave a number of unanswered questions. in the paper, we tackle this issue by modeling via a set of fluid non-linear odes the instantaneous throughput and the buffer occupancy of n longlived tcp sources under three per-flow scheduling disciplines (fair queuing, longest queue first, shortest queue first) and with longest queue drop buffer management. we study the system evolution and analytically characterize the stationary regime: closed-form expressions are derived for the stationary throughput/sending rate and buffer occupancy which give a thorough understanding of short/long-term fairness for tcp traffic. similarly, we provide the characterization of the loss rate experienced by udp flows in presence of tcp traffic. as a result, the analysis allows to quantify benefits and drawbacks related to the deployment of flow-aware scheduling mechanisms in different networking contexts. the model accuracy is confirmed by a set of ns2 simulations and by the evaluation of the three scheduling disciplines in a real implementation in the linux kernel.
multicast scheduling with cooperation and network coding in cognitive radio networks. cognitive radio networks (crns) have recently emerged as a promising technology to improve spectrum utilization by allowing secondary users to dynamically access idle primary channels. as progress are made and computationally powerful wireless devices are proliferated, there is a compelling need of enabling multicast services for secondary users. thus, it is crucial to design an efficient multicast scheduling protocol in crns. however, state-of-the-art multicast scheduling protocols are not well designed for crns. first, due to primary channel dynamics and user mobility, there may not exist commonly available channels for secondary users, which inevitably makes the multicast scheduling infeasible. second, the potential benefits provided by user and channel diversities are overlooked, which leads to under-utilization of the scarce wireless bandwidth. in this paper, we present an optimization framework for multicast scheduling in crns, by fully embracing its characteristics. in this framework, base station multicasts data to a subset of secondary users first by carefully tuning the power. concurrently, secondary users opportunistically perform cooperative transmissions using locally idle primary channels, in order to mitigate multicast loss and delay effects. network coding is adopted during the transmissions to reduce overhead and perform error control and recovery. we jointly consider important design factors in our scheduling protocols, including power control, relay assignment, buffer management, dynamic spectrum access, primary user protection, and fairness. we also incorporate user, channel, and cooperative diversities. two forms of multicast scheduling protocols in crns are proposed accordingly: (i) a greedy protocol based on centralized optimization; (ii) an online protocol based on stochastic optimization in both centralized and decentralized manners. with rigorous analysis based on lyapunov optimization, we provide closed-form bounds to characterize the performance of our protocols, in terms of the interference to primary users and throughput utility of secondary users. with extensive simulations, we show that our proposed protocols can significantly improve the multicast performance in crns.
forward contracts for complementary segments of a communication network. congestion-dependent pricing is a form of traffic management that would ensure the efficient allocation of bandwidth between users and applications. as the unpredictability of congestion prices creates revenue uncertainty for network providers and cost uncertainty for users, it has been suggested that longer-term financial agreements such as forward contracts could be used to manage these risks. in a network managed by a single service provider, long-term forward contracts are beneficial for both the provider and the users. we investigate whether forward contracts would be adopted by multiple service providers in a future internet with congestion-dependent pricing. we develop a novel game-theoretic model of a multi-provider communication network with two complementary segments. service on the upstream segment is provided by a single internet service provider (isp) and priced dynamically to maximize profit, while several smaller isps sell connectivity on the downstream network segment, with the advance possibility of entering into forward contracts with their users for some or all of their capacity. we show that the equilibrium forward contracting levels are necessarily asymmetric, with one downstream provider entering into fewer forward contracts than the other competitors, thus ensuring a high subsequent downstream price level. in practice, network providers will choose the extent of forward contracting strategically based not only on their risk tolerance, but also on the market structure in the interprovider network and their peers' actions.
ccack: efficient network coding based opportunistic routing through cumulative coded acknowledgments. the use of random linear network coding (nc) has significantly simplified the design of opportunistic routing (or) protocols by removing the need of coordination among forwarding nodes for avoiding duplicate transmissions. however, nc-based or protocols face a new challenge: how many coded packets should each forwarder transmit? to avoid the overhead of feedback exchange, most practical existing nc-based or protocols compute offline the expected number of transmissions for each forwarder using heuristics based on periodic measurements of the average link loss rates and the etx metric. although attractive due to their minimal coordination overhead, these approaches may suffer significant performance degradation in dynamic wireless environments with continuously changing levels of channel gains, interference, and background traffic. in this paper, we propose ccack, a new efficient nc-based or protocol. ccack exploits a novel cumulative coded acknowledgment scheme that allows nodes to acknowledge network coded traffic to their upstream nodes in a simple way, oblivious to loss rates, and with practically zero overhead. in addition, the cumulative coded acknowledgment scheme in ccack enables an efficient credit-based, rate control algorithm. our evaluation shows that, compared to more, a state-of-the-art nc-based or protocol, ccack improves both throughput and fairness, by up to 20x and 124%, respectively, with average improvements of 45% and 8.8%, respectively.
virtual appliance content distribution for a global infrastructure cloud service. cloud computing in general and virtualized infrastructure provisioning in particular, are significant trends with the potential to increase agility and lower costs of it. an emerging cloud service is a virtual server shop, that allows cloud customers to order virtual appliances to be delivered virtually on the cloud. like physical shops, customers want to customize the ordered products, e.g., have them pre-installed with their desired applications and pre-configured. global cloud providers need to create customized virtual-server disk images and deliver them on time to meet the customer reservations and service level. this framework creates a new flavor of content distribution over the web, where large virtual server images need to be delivered to the target compute farms (either on the global cloud or on customer private clouds). in order to reduce provisioning time and meet reservation deadlines, one approach is to stage images on storage near the customer. this introduces an optimization problem of finding an optimal staging schedule, according to network bandwidth, pending reservations schedule, and customer value. this problem has some similarities to cache pre-filling and production-line scheduling. it combines scheduling, bandwidth considerations, and storage capacity constraints. in this paper we study the fundamental properties of this approach and formalize several flavors of the related optimization problem. we prove useful properties of the problem and then use those properties to provide exact efficient algorithms to solve it. we also derive efficient approximate solutions with proven error bounds.
a novel xcast-based caching architecture for inter-gateway handoffs in infrastructure wireless mesh networks. handoff management plays an important role in wireless mesh networks (wmns) in delivering quality of service to mobile users. inter-gateway (across subnets) movement in wmns usually requires the handoff support from multilayers and thus causes nonnegligible delays and packet loss. previous solutions on handoff management in infrastructure wmns mainly focus on intra-gateway mobility (e.g., single gateway is assumed in ieee 802.11s wmns) and exert the reduction of handoff delay so as to reduce packet loss. furthermore, some handoff issues involved in inter-gateway mobility in wmns (e.g., the network-layer handoff detection issue) have not been properly addressed. in this paper, we present a novel architectural design, namely explicit multicast-based (xcast-based) wmns (xmesh), to facilitate inter-gateway handoff management. the proposed xmesh architecture enables parallel executions of handoffs from multilayers, in conjunction with a xcast-based caching mechanism which builds on top of mesh routing protocols to guarantee minimum packet loss during handoffs in wmns. the required number and optimal placement of special mesh routers that form the xmesh architecture are modeled as a set covering problem which is solved based on a greedy algorithm. a comprehensive simulation study shows that the xmesh architecture enables fast handoffs and re-establishment of session communications in the inter-gateway mobility environment. with both the parallel handoff execution and data caching mechanism, our architecture offers a seamless handoff for supporting real-time applications.
cooperative resource management in cognitive wimax with femto cells. wimax with femto cells is a cost-effective next-generation broadband wireless communication system. cognitive radio (cr) has recently emerged as a promising technology to improve spectrum utilization by allowing dynamic spectrum access. there will be large potential benefits by applying the cr technique to wimax with femto cells, which are barely explored in the literature. in this paper, we propose a novel cognitive wimax architecture with femto cells, where the base station and users are equipped with crs and intelligently adjusts power, channel, and other resources to accommodate the entire network ecosystem. in this new design, we develop an optimization framework for location-aware cooperative resource management, by jointly employing multi-hop cooperative communication, power control, channel assignment, primary user protection, buffer management, and fairness, and incorporating user, channel, and cooperative diversities. to achieve optimality, it is designed based on stochastic lyapunov optimization, aiming to take advantage of the radio flexibility and fully utilize the spectrum. evaluated by the rigorous analysis and extensive simulations, our resource management protocol is near-optimal with closed-form bounds, with which cognitive wimax achieves substantial performance improvement.
efficient similarity estimation for systems exploiting data redundancy. many modern systems exploit data redundancy to improve efficiency. these systems split data into chunks, generate identifiers for each of them, and compare the identifiers among other data items to identify duplicate chunks. as a result, chunk size becomes a critical parameter for the efficiency of these systems: it trades potentially improved similarity detection (smaller chunks) with increased overhead to represent more chunks. unfortunately, the similarity between files increases unpredictably with smaller chunk sizes, even for data of the same type. existing systems often pick one chunk size that is "good enough" for many cases because they lack efficient techniques to determine the benefits at other chunk sizes. this paper addresses this deficiency via two contributions: (1) we present multiresolution (mr) handprinting, an application-independent technique that efficiently estimates similarity between data items at different chunk sizes using a compact, multi-size representation of the data; (2) we then evaluate the application of mr handprints to workloads from peer-to-peer, file transfer, and storage systems, demonstrating that the chunk size selection enabled by mr handprints can lead to real improvements over using a fixed chunk size in these systems.
greedy forwarding in dynamic scale-free networks embedded in hyperbolic metric spaces. we show that complex (scale-free) network topologies naturally emerge from hyperbolic metric spaces. hyperbolic geometry facilitates maximally efficient greedy forwarding in these networks. greedy forwarding is topology-oblivious. nevertheless, greedy packets find their destinations with 100% probability following almost optimal shortest paths. this remarkable efficiency sustains even in highly dynamic networks. our findings suggest that forwarding information through complex networks, such as the internet, is possible without the overhead of existing routing protocols, and may also find practical applications in overlay networks for tasks such as application-level routing, information sharing, and data distribution.
is network coding always good for cooperative communications? network coding (nc) is a promising approach to reduce time-slot overhead for cooperative communications (cc) in a multi-session environment. most of the existing works take advantage of the benefits of nc in cc but do not fully recognize its potential adverse effect. in this paper, we show that employing nc may not always benefit cc. we substantiate this important finding in the context of analog network coding (anc) and amplify-and-forward (af) cc. this paper, for the first time, introduces an important concept of network coding noise (nc noise). specifically, we analyze the signal aggregation at a relay node and signal extraction at a destination node. we then use the analysis to derive a closed-form expression for nc noise at each destination node in a multi-session environment. we show that nc noise can diminish the advantage of nc in cc. our results formalizes an important concept on using nc in cc.
analyzing the performance of greedy maximal scheduling via local pooling and graph theory. efficient operation of wireless networks and switches requires using simple scheduling algorithms. in general, simple greedy algorithms (known as greedy maximal scheduling - gms) are guaranteed to achieve only a fraction of the maximum possible throughput. it was recently shown that in networks in which the local pooling conditions are satisfied, gms achieves 100% throughput. moreover, in networks in which the σ-local pooling conditions hold, gms achieves σ% throughput. in this extended abstract, we characterize all the network graphs in which local pooling holds under primary interference constraints. we then show that in all bipartite graphs (i.e., input-queued switches) of size up to 7×n, gms is guaranteed to achieve 66% throughput, thereby improving upon the previously known 50% lower bound. finally, we study the performance of gms in interference graphs and show that in certain specific topologies its performance could be very bad. overall, we demonstrate that using graph theoretical techniques can significantly contribute to our understanding of greedy scheduling algorithms. the proofs of the results have been omitted for brevity and can be found in [1].
isp-enabled behavioral ad targeting without deep packet inspection. online advertising is a rapidly growing industry currently dominated by the search engine 'giant' google. in an attempt to tap into this huge market, internet service providers (isps) started deploying deep packet inspection techniques to track and collect user browsing behavior. however, such techniques violate wiretap laws that explicitly prevent intercepting the contents of communication without gaining consent from consumers. in this paper, we show that it is possible for isps to extract user browsing patterns without inspecting contents of communication. our contributions are threefold. first, we develop a methodology and implement a system that is capable of extracting web browsing features from stored non-content based records of online communication, which could be legally shared. when such browsing features are correlated with information collected by independently crawling the web, it becomes possible to recover the actual web pages accessed by clients. second, we systematically evaluate our system on the internet and demonstrate that it can successfully recover user browsing patterns with high accuracy. finally, our findings call for a comprehensive legislative reform that would not only enable fair competition in the online advertising business, but more importantly, protect the consumer rights in a more effective way.
online scheduling of targeted advertisements for iptv. behavioral targeting of content to users is a huge and lucrative business, valued as a $20 billion industry that is growing rapidly. so far dominant players in this field like google and yahoo examine the user requests coming to their servers and place appropriate ads based on the user's search keywords. triple play service providers have access to all the traffic generated by the users and can generate more comprehensive profiles of users based on their tv, broadband and mobile usage. using such multi-source profile information they can generate new revenue streams by smart targeting of ads to their users over multiple screens (computer, tv and mobile handset). this paper proposes methods to place targeted ads to a tv based on user's interests. it proposes an ad auction model that can leverage multi-source profile and can handle dynamic profile-based targeting like google's adwords vis-a-vis static demography-based targeting of legacy tv. we then propose a 0.502-competitive revenue maximizing scheduling algorithm that chooses a set of ads in each time slot and assigns users to one of these selected ads.
dplc: dynamic packet length control in wireless sensor networks. previous packet length optimizations for sensor networks often employ a fixed optimal length scheme, while in this study we present dplc, a dynamic packet length control scheme. to make dplc more efficient in terms of channel utilization, we incorporate a lightweight and accurate link estimation method that captures both physical channel conditions and interferences. we further provide two easy-touse services, i.e., small message aggregation and large message fragmentation, to facilitate upper-layer application programming. the implementation of dplc based on tinyos 2.1 is lightweight, with respect to computation, memory, and header overhead. our experiments using a real indoor testbed running ctp show that dplc results in a 13% reduction in transmission overhead and a 41.8% reduction in energy consumption compared with the original protocol, and a 21% reduction in transmission overhead and a 15.1% reduction in energy consumption compared with simple aggregation schemes.
minimum power energy spanners in wireless ad hoc networks. a power assignment is an assignment of transmission power to each of the nodes of a wireless network, so that the induced communication graph has some desired properties. the cost of a power assignment is the sum of the powers. the energy of a transmission path from node u to node v is the sum of the squares of the distances between adjacent nodes along the path. for a constant t > 1, an energy t-spanner is a graph g′, such that for any two nodes u and v, there exists a path from u to v in g′, whose energy is at most t times the energy of a minimum-energy path from u to v in the complete euclidean graph. in this paper, we study the problem of finding a power assignment, such that (i) its induced communication graph is a 'good' energy spanner, and (ii) its cost is 'low'. we show that for any constant t > 1, one can find a power assignment, such that its induced communication graph is an energy t-spanner, and its cost is bounded by some constant times the cost of an optimal power assignment (where the sole requirement is strong connectivity of the induced communication graph). this is a very significant improvement over the best current result due to shpungin and segal [1], presented in last year's conference.
p-coding: secure network coding against eavesdropping attacks. though providing an intrinsic secrecy, network coding is still vulnerable to eavesdropping attacks, by which an adversary may compromise the confidentiality of message content. existing studies mainly deal with eavesdroppers that can intercept a limited number of packets. however, real scenarios often consist of more capable adversaries, e.g., global eavesdroppers, which can defeat these techniques. in this paper, we propose p-coding, a novel security scheme against eavesdropping attacks in network coding. with the lightweight permutation encryption performed on each message and its coding vector, p-coding can efficiently thwart global eavesdroppers in a transparent way. moreover, p-coding is also featured in scalability and robustness, which enable it to be integrated into practical network coded systems. security analysis and simulation results demonstrate the efficacy and efficiency of the p-coding scheme.
reliability in layered networks with random link failures. we consider network reliability in layered networks where the lower layer experiences random link failures. in layered networks, each failure at the lower layer may lead to multiple failures at the upper layer. we generalize the classical polynomial expression for network reliability to the multi-layer setting. using random sampling techniques, we develop polynomial time approximation algorithms for the failure polynomial. our approach gives an approximate expression for reliability as a function of the link failure probability, eliminating the need to resample for different values of the failure probability. furthermore, it gives insight on how the routings of the logical topology on the physical topology impact network reliability. we show that maximizing the min cut of the (layered) network maximizes reliability in the low failure probability regime. based on this observation, we develop algorithms for routing the logical topology to maximize reliability.
castor: scalable secure routing for ad hoc networks. wireless ad hoc networks are inherently vulnerable, as any node can disrupt the communication of potentially any other node in the network. many solutions to this problem have been proposed. in this paper, we take a fresh and comprehensive approach that addresses simultaneously three aspects: security, scalability and adaptability to changing network conditions. our communication protocol, castor, occupies a unique point in the design space: it does not use any control messages except simple packet acknowledgements, and each node makes routing decisions locally and independently without exchanging any routing state with other nodes. its novel design makes castor resilient to a wide range of attacks and allows the protocol to scale to large network sizes and to remain efficient under high mobility. we compare castor against four representative protocols from the literature. our protocol achieves up to two times higher packet delivery rates, particularly in large and highly volatile networks, while incurring no or only limited additional overhead. at the same time, castor is able to survive more severe attacks and recovers from them faster.
retiring replicants: congestion control for intermittently-connected networks. the widespread availability of mobile wireless devices offers growing opportunities for the formation of temporary networks with only intermittent connectivity. these intermittently-connected networks (icns) typically lack stable end-to-end paths. in order to improve the delivery rates of the networks, new store-carry-and-forward protocols have been proposed which often use message replication as a forwarding mechanism. message replication is effective at improving delivery, but given the limited resources of icn nodes, such as buffer space, bandwidth and energy, as well as the highly dynamic nature of these networks, replication can easily overwhelm node resources. in this work we propose a novel node-based replication management algorithm which addresses buffer congestion by dynamically limiting the replication a node performs during each encounter. the insight for our algorithm comes from a stochastic model of message delivery in icns with constrained buffer space. we show through simulation that our algorithm is effective, nearly tripling delivery rates in some scenarios, and imposes no or little overhead.
efficient active probing for fault diagnosis in large scale and noisy networks. active probing is an effective tool for monitoring networks. by measuring probing responses, we can perform fault diagnosis actively and efficiently without instrumentation on managed entities. in order to reduce the traffic generated by probing messages and the measurement infrastructure costs, an optimal set of probes is desirable. however, the computational complexity for obtaining such an optimal set is very high. existing works assume single-fault scenarios, apply only to small size networks, or use simplistic methods that are vulnerable to noises. in this paper, by exploiting the conditionally independent property in bayesian networks, we prove a theorem on the information provided by a set of probes. based on this theorem and structure property of bayesian networks, we propose two approaches which can effectively reduce the computation time. a highly efficient adaptive probing algorithm is then presented. compared with previous techniques, experiments have shown that our approach is more efficient in selecting an optimal set of probes without degrading diagnosis quality in large scale and noisy networks.
joint routing and scheduling in multi-hop wireless networks with directional antennas. long-distance multi-hop wireless networks have been used in recent years to provide connectivity to rural areas. the salient features of such networks include tdma channel access, nodes with multiple radios, and point-to-point long-distance wireless links established using high-gain directional antennas mounted on high towers. it has been demonstrated previously that in such network architectures, nodes can transmit concurrently on multiple radios, as well as receive concurrently on multiple radios. however, concurrent transmission on one radio, and reception on another radio causes interference. under this scheduling constraint, given a set of source-destination demand rates, we consider the problem of satisfying the maximum fraction of each demand (also called the maximum concurrent flow problem). we give a novel joint routing and scheduling scheme for this problem, based on linear programming and graph coloring. we analyze our algorithm theoretically and prove that at least 50% of a satisfiable set of demands is satisfied by our algorithm for most practical networks (with maximum node degree at most 5).
measuring availability in the domain name system. the domain name system (dns) is critical to internet functionality. the availability of a domain name refers to its ability to be resolved correctly. we develop a model for server dependencies that is used as a basis for measuring availability. we introduce the minimum number of servers queried (msq) and redundancy as availability metrics and show how common dns misconfigurations impact the availability of domain names. we apply the availability model to domain names from production dns and observe that 6.7% of names exhibit sub-optimal msq, and 14% experience false redundancy. the msq and redundancy values can be optimized by proper maintenance of delegation records for zones.
collaborative data compression using clustered source coding for wireless multimedia sensor networks. data redundancy caused by correlation has motivated the application of collaborative multimedia in-network processing for data filtering and compression in wireless multimedia sensor networks (wmsns). this paper proposes an information theoretic data compression framework with an objective to maximize the overall compression of the visual information gathered in a wmsn. to achieve this, an entropy-based divergence measure (edm) scheme is proposed to predict the compression efficiency of performing joint coding on the images collected by spatially correlated cameras. the novelty of edm relies on its independence of the specific image types and coding algorithms, thereby providing a generic mechanism for prior evaluation of compression under different coding solutions. utilizing the predicted results from edm, a distributed multi-cluster coding protocol (dmcp) is proposed to construct a compression-oriented coding hierarchy. the dmcp aims to partition the entire network into a set of coding clusters such that the global coding gain is maximized. moreover, in order to enhance decoding reliability at data sink, the dmcp also guarantees that each sensor camera is covered by at least two different coding clusters. experiments on h.264 standards show that the proposed edm can effectively predict the joint coding efficiency from multiple sources. further simulations demonstrate that the proposed compression framework can reduce 10% - 23% total coding rate compared with the individual coding scheme, i.e., each camera sensor compresses its own image independently.
surfing the blogosphere: optimal personalized strategies for searching the web. we propose a distributed mechanism for finding websurfing strategies that is inspired by the stumbleupon recommendation engine. each day, a websurfer visits a sequence of websites recommended by our mechanism, and selects one that matches her daily interests. we formally show that even with this minimal feedback from the surfer--the selected website-- our mechanism finds a websurfing strategy that matches the surfer's interests optimally. the surfer does not need to know--or declare--what her daily interests are before she is presented with content she likes. moreover, our mechanism is content-agnostic: it is oblivious to the nature of the content the surfer selects. in addition, we study how the performance of this mechanism can be improved if surfers with similar interests share their feedback. such surfers can be found indirectly, e.g., if they are all registered as friends in a social networking application. our analysis characterizes the improvement in the mechanism's accuracy, based on the size of the group and the degree of similarity between the surfers' interests. in particular, we show that sharing feedback can significantly accelerate the convergence of our mechanism. our results are derived analytically using stochastic approximation techniques, but are also validated through a numerical study.
prisense: privacy-preserving data aggregation in people-centric urban sensing systems. people-centric urban sensing is a new paradigm gaining popularity. a main obstacle to its widespread deployment and adoption are the privacy concerns of participating individuals. to tackle this open challenge, this paper presents the design and evaluation of prisense, a novel solution to privacypreserving data aggregation in people-centric urban sensing systems. prisense is based on the concept of data slicing and mixing and can support a wide range of statistical additive and non-additive aggregation functions such as sum, average, variance, count, max/min, median, histogram, and percentile with accurate aggregation results. prisense can support strong user privacy against a tunable threshold number of colluding users and aggregation servers. the efficacy and efficiency of prisense are confirmed by thorough analytical and simulation results.
know thy neighbor: towards optimal mapping of contacts to social graphs for dtn routing. delay tolerant networks (dtn) are networks of self-organizing wireless nodes, where end-to-end connectivity is intermittent. in these networks, forwarding decisions are generally made using locally collected knowledge about node behavior (e.g., past contacts between nodes) to predict future contact opportunities. the use of complex network analysis has been recently suggested to perform this prediction task and improve the performance of dtn routing. contacts seen in the past are aggregated to a social graph, and a variety of metrics (e.g., centrality and similarity) or algorithms (e.g., community detection) have been proposed to assess the utility of a node to deliver a content or bring it closer to the destination. in this paper, we argue that it is not so much the choice or sophistication of social metrics and algorithms that bears the most weight on performance, but rather the mapping from the mobility process generating contacts to the aggregated social graph. we first study two well-known dtn routing algorithms - simbet and bubblerap - that rely on such complex network analysis, and show that their performance heavily depends on how the mapping (contact aggregation) is performed. what is more, for a range of synthetic mobility models and real traces, we show that improved performances (up to a factor of 4 in terms of delivery ratio) are consistently achieved for a relatively narrow range of aggregation levels only, where the aggregated graph most closely reflects the underlying mobility structure. to this end, we propose an online algorithm that uses concepts from unsupervised learning and spectral graph theory to infer this "correct" graph structure; this algorithm allows each node to locally identify and adjust to the optimal operating point, and achieves good performance in all scenarios considered.
impact of correlated mobility on delay-throughput performance in mobile ad-hoc networks. we extend the analysis of the scaling laws of wireless ad hoc networks to the case of correlated nodes movements, which are commonly found in real mobility processes. we consider a simple version of the reference point group mobility model, in which nodes belonging to the same group are constrained to lie in a disc area, whose center moves uniformly across the network according to the i.i.d. model. we assume fast mobility conditions, and take as primary goal the maximization of pernode throughput. we discover that correlated node movements have huge impact on asymptotic throughput and delay, and can sometimes lead to better performance than the one achievable under independent nodes movements.
solarcode: utilizing erasure codes for reliable data delivery in solar-powered wireless sensor networks. solar-powered sensor nodes have incentive to spend extra energy, especially when the battery is fully charged, because this energy surplus would be wasted otherwise. in this paper, we consider the problem of utilizing such energy surplus to adaptively adjust the redundancy level of erasure codes used in communication, so that the delivery reliability is improved while the network lifetime is still conserved. we formulate the problem as maximizing the end-to-end packet delivery probability under energy constraints. this formulated problem is hard to solve because of the combinatorics involved and the special curvature of its objective function. by exploiting its inherent properties, we propose an effective solution called solarcode, which has a constant approximation ratio. we evaluate solarcode in the context of our solar-powered sensor network testbed. experiments show that solarcode is successful in utilizing energy surplus and leads to higher data delivery reliability.
performing joint learning for passive intrusion detection in pervasive wireless environments. recent years have witnessed increasing interests in passive intrusion detection for wireless environments, e.g., asset protection in industrial facilities and emergency rescue of trapped people. most previous studies have focused primarily on exploiting a single intrusion indicator, such as moving variance, for capturing an intrusion pattern at a time. however, in real-world, there are many intrusion patterns which may be only detectable by combining different intrusion indicators and performing detection jointly. to this end, we propose a joint intrusion learning approach, which has the ability in combining the detection power of several complementary intrusion indicators and detects different intrusion patterns at the same time. we developed the greek algorithm, which utilizes grid-based clustering over kneighborhood to effectively diagnose the presence of intrusions. further, we show that the performance of intrusion detection can be enhanced by utilizing the collaborative detecting efforts among multiple transmitter-receiver pairs. to validate the effectiveness of the joint intrusion learning method, we conducted experiments in a real-office environment using an ieee 802.15.4 (zigbee) network. our experimental results provide strong evidence of the effectiveness of our joint learning approach in performing passive intrusion detection with a minimized false positive rate.
pressure routing for underwater sensor networks. a sea swarm (sensor equipped aquatic swarm) is a sensor cloud that drifts with water currents and enables 4d (space and time) monitoring of local underwater events such as contaminants, marine life and intruders. the swarm is escorted at the surface by drifting sonobuoys that collect the data from underwater sensors via acoustic modems and report it in realtime via radio to a monitoring center. the goal of this study is to design an efficient anycast routing algorithm for reliable underwater sensor event reporting to any one of the surface sonobuoys. major challenges are the ocean current and the limited resources (bandwidth and energy). in this paper, we address these challenges and propose hydrocast, a hydraulic pressure based anycast routing protocol that exploits the measured pressure levels to route data to surface buoys. the paper makes the following contributions: a novel opportunistic routing mechanism to select the subset of forwarders that maximizes greedy progress yet limiting co-channel interference; and an efficient underwater dead end recovery method that outperforms recently proposed approaches. the proposed routing protocols are validated via extensive simulations.
estimating link reliability in wireless networks: an empirical study and interference modeling. recently, it has been received in the community that the link reliability is strongly related to rssi (or sinr) and the external interference makes it unpredictable, but the unpredictability has not been fully explained yet. in order to examine the causes of the unpredictable link state, we first configured an empirical testbed, performed a measurement study, and observed that the link reliability actually depends on an intra-frame sinr distribution. we also discovered that a rssi (or sinr) value is not always a good indicator to estimate the link state. based on these results, we propose a modeling framework for estimating the link state in the presence of the wireless interference. we vision that the framework can be used for developing link-aware protocols to achieve their optimal performance in a hostile wireless environment.
routing for energy minimization in the speed scaling model. we study network optimization that considers energy minimization as an objective. studies have shown that mechanisms such as speed scaling can significantly reduce the power consumption of telecommunication networks by matching the consumption of each network element to the amount of processing required for its carried traffic. most existing research on speed scaling focuses on a single network element in isolation. we aim for a network-wide optimization. specifically, we study a routing problem with the objective of provisioning guaranteed speed/bandwidth for a given demand matrix while minimizing energy consumption. optimizing the routes critically relies on the characteristic of the energy curve f(s), which is how energy is consumed as a function of the processing speed s. if f is superadditive, we show that there is no bounded approximation in general for integral routing, i.e., each traffic demand follows a single path. this contrasts with the well-known logarithmic approximation for subadditive functions. however, for common energy curves such as polynomials f(s) = µsα, we are able to show a constant approximation via a simple scheme of randomized rounding. the scenario is quite different when a non-zero startup cost σ appears in the energy curve, e.g. f(s) = {0 σ + µsα if s =0 if s > 0. for this case a constant approximation is no longer feasible. in fact, for any α > 1, we show an ω(log1/4 n hardness result under a common complexity assumption. (here n is the size of the network.) on the positive side we present o((σ/µ)1/α) and o(k) approximations, where k is the number of demands.
vbs: maximum lifetime sleep scheduling for wireless sensor networks using virtual backbones. wireless sensor network (wsn) applications require redundant sensors to guarantee fault tolerance. however, the same degree of redundancy is not necessary for multi-hop communication. in this paper, we present a new scheduling method called virtual backbone scheduling (vbs). vbs employs heterogeneous scheduling, where backbone nodes work with duty-cycling to preserve network connectivity, and nonbackbone nodes turn off radios to save energy. we formulate a maximum lifetime backbone scheduling (mlbs) problem to maximize the network lifetime using this scheduling model. because the mlbs problem is np-hard, two approximation solutions based on the schedule transition graph (stg) and virtual scheduling graph (vsg) are proposed. we also present an iterative local replacement (ilr) scheme as an distributed implementation of vbs. the path stretch problem is analyzed in order to explore the impact of vbs on the network structure. we show, through simulations, that vbs significantly prolongs the network lifetime under extensive conditions.
a frequency domain model to predict the estimation accuracy of packet sampling. in network measurement systems, packet sampling techniques are usually adopted to reduce the overall amount of data to collect and process. being based on a subset of packets, they hence introduce estimation errors that have to be properly counteracted by a fine tuning of the sampling strategy and sophisticated inversion methods. this problem has been deeply investigated in the literature with particular attention to the statistical properties of packet sampling and the recovery of the original network measurements. herein, we propose a novel approach to predict the energy of the sampling error on the real time traffic volume estimation, based on a spectral analysis in the frequency domain. we start by demonstrating that errors due to packet sampling can be modeled as an aliasing effect in the frequency domain. then, we exploit this theoretical finding to derive closed-form expressions for the signal-to-noise ratio (snr), able to predict the distortion of traffic volume estimates over time. the accuracy of the proposed snr metric is validated by means of real packet traces.
reliable wireless broadcasting with near-zero feedback. we examine the problem of minimizing feedbacks in reliable wireless broadcasting, by pairing rateless coding with extreme value theory. our key observation is that, in a broadcast environment, this problem resolves into estimating the maximum number of packets dropped among many receivers rather than for each individual receiver.with rateless codes, this estimation relates to the number of redundant transmissions needed at the source in order for all receivers to correctly decode a message with high probability. we develop and analyze two new data dissemination protocols, called random sampling (rs) and full sampling with limited feedback (fslf), based on the moment and maximum likelihood estimators in extreme value theory. both protocols rely on a single-round learning phase, requiring the transmission of a few feedback packets from a small subset of receivers. with fixed overhead, we show that fslf has the desirable property of becoming more accurate as the receivers's population gets larger. our protocols are channel agnostic, in that they do not require a-priori knowledge of (i.i.d.) packet loss probabilities, which may vary among receivers. we provide simulations and an improved full-scale implementation of the rateless deluge overthe-air programming protocol on sensor motes as a demonstration of the practical benefits of our protocols, which translate into about 30% latency and energy consumption savings.
joint random access and power selection for maximal throughput in wireless networks. in wireless networks, how to select transmit power that maximizes throughput is a challenging problem. on one hand, transmissions at a high power level could increase interference to others; on the other hand, transmissions at a low power level are prone to being interfered by others. prior works consider this problem as a search for a fixed optimal power setting that maximizes communication spatial reuse. in this paper, we pursue a novel approach that combines power selection with a random medium access mechanism. for each transmission, a node randomly selects a transmit power from all available power levels to access the medium. in this way, all combinations of network power settings could be selected with some probability. using a recently developed markov chain model, we derive a distributed scheme that determines the access probabilities of each power setting, according to the arrival rate of traffic and the service rate achieved by the scheme. we show that this scheme always converges to the optimal solution. moreover, we also show that the random scheme can attain the maximal throughput region that can be obtained by any time-sharing between power settings, and which is consequently larger than the region any fixed power setting can achieve.
towards automatic creation of usable security configuration. the objective of this work is to create usable security architecture that will minimize network risk while considering usability and budget. we propose and formulate a novel framework for automatic creation of network security architecture including configuration rules and device placements in order to minimize risk while satisfying the business requirements, service usability and budget constraints. our framework also automates the creation of external and internal demilitarized zones (dmz) to improve security by increasing isolation. we formalize this as an optimization problem and show that it is np-hard. we then provide heuristic approximation algorithms. the implemented systems, called secbuilder, were evaluated under different network sizes, topologies and security requirements. our evaluation study shows that the results obtained by secbuilder are close to the theoretical lower bound and the performance is scalable with the network size.
compressive sensing based positioning using rss of wlan access points. the sparse nature of location finding problem makes the theory of compressive sensing desirable for indoor positioning in wireless local area networks (wlans). in this paper, we address the received signal strength (rss)-based localization problem in wlans using the theory of compressive sensing (cs), which offers accurate recovery of sparse signals from a small number of measurements by solving an l1-minimization problem. a pre-processing procedure of orthogonalization is used to induce incoherence needed in the cs theory. in order to mitigate the effects of rss variations due to channel impediments, the proposed positioning system consists of two steps: coarse localization by exploiting affinity propagation, and fine localization by the cs theory. in the fine localization stage, access point selection problem is studied to further increase the accuracy. we implement the positioning system on a wifi-integrated mobile device (hp ipaq hx4700 with windows mobile 2003 pocket pc) to evaluate the performance. experimental results indicate that the proposed system leads to substantial improvements on localization accuracy and complexity over the widely used traditional fingerprinting methods.
a theoretical framework for hierarchical routing games. most theoretical research on routing games in telecommunication networks has so far dealt with reciprocal congestion effects between routed entities. yet in networks that support differentiation between flows, the congestion experienced by a packet depends on its priority level. another differentiation is made by compressing the packets in the low priority flow while leaving the high priority flow intact. in this paper we study such kind of routing scenarios for the case of non-atomic users and we establish conditions for the existence and uniqueness of equilibrium.
path stitching: internet-wide path and delay estimation from existing measurements. many measurement systems have been proposed in recent years to shed light on the internal performance of the internet. their common goal is to allow distributed applications to improve end-user experience. a common hurdle they face is the need to deploy yet another measurement infrastructure. in this work, we demonstrate that without any new measurement infrastructure or active probing we obtain composite performance estimates from as-by-as segments and the estimates are as good as (or even better than) those from existing estimation methodologies that use on-demand, customized active probing. the main contribution of this paper is an estimation algorithm that breaks down measurement data into segments, identifies relevant segments efficiently, and, by carefully stitching segments together, produces delay and path estimates between any two end points. fittingly, we call our algorithm path stitching. our results show remarkably good accuracy: error in delay is below 20 ms in 80% of end-to-end paths.
opportunistic spectrum access with multiple users: learning under competition. the problem of cooperative allocation among multiple secondary users to maximize cognitive system throughput is considered. the channel availability statistics are initially unknown to the secondary users and are learnt via sensing samples. two distributed learning and allocation schemes which maximize the cognitive system throughput or equivalently minimize the total regret in distributed learning and allocation are proposed. the first scheme assumes minimal prior information in terms of pre-allocated ranks for secondary users while the second scheme is fully distributed and assumes no such prior information. the two schemes have sum regret which is provably logarithmic in the number of sensing time slots. a lower bound is derived for any learning scheme which is asymptotically logarithmic in the number of slots. hence, our schemes achieve asymptotic order optimality in terms of regret in distributed learning and allocation.
learning to optimally exploit multi-channel diversity in wireless systems. consider a wireless system where a transmitter may send data to a set of receivers, or on various channels, experiencing random time-varying fading. the transmitter can send data to a single receiver or on a single channel at a time and may adapt its transmission power to the radio conditions of the chosen receiver/channel. its objective is to implement a strategy defining at each time how to select the receiver/channel and transmission power, so as to maximize its throughput, i.e., its average sending rate, under an average power constraint. the optimization problem is easy when the fading conditions of all the receivers/channels are known. in many situations however, the instantaneous fading conditions are not known a priori, instead they have to be acquired, i.e., receivers/channels have to be probed, which consumes resources (time, spectrum, energy) in proportion of the number of probed receivers/channels. hence, the transmitter may choose not to acquire the radio conditions of all the receivers/channels so as to spare resources for actual transmissions. in this paper, we aim at characterizing a joint probing, receiver/channel selection and power control strategy maximizing throughput. we provide an adaptive algorithm converging to the throughput optimal strategy. this algorithm may be used in a wide class of wireless systems with limited information, such as broadcast systems without a priori knowledge of the instantaneous channel-state information (csi). but it can be also used to solve dynamic spectrum access problems such as those arising in cognitive radio systems, where secondary users can access large parts of the spectrum, but have to discover which portions of the spectrum offer more favorable radio conditions or less interference from primary users.
dynamic power allocation under arbitrary varying channels - the multi-user case. we consider the power control problem in a time-slotted wireless channel, shared by a finite number of mobiles that transmit to a common base station. the channel between each mobile and the base station is time varying, and the system objective is to maximize the overall data throughput. it is assumed that each transmitter has a limited power budget, to be sequentially divided during the lifetime of the battery. we deviate from the classic work in this area, by considering a realistic scenario where the channel quality of each mobile changes arbitrarily from one transmission to the other. assuming first that each mobile is aware of the channel quality of all other mobiles, we propose an online power-allocation algorithm, and prove its optimality under mild assumptions. we then indicate how to implement the algorithm when only local state information is available, requiring minimal communication overhead. notably, the competitive ratio of our algorithm (nearly) matches the bound obtained for the (much simpler) single-transmitter case [2], albeit requiring significantly different algorithmic solutions.
maximum damage malware attack in mobile wireless networks. malware attacks constitute a serious security risk that threatens to slow down the large scale proliferation of wireless applications. as a first step towards thwarting this security threat, we seek to quantify the maximum damage inflicted on the system owing to such outbreaks and identify the most vicious attacks. we represent the propagation of malware in a battery-constrained mobile wireless network by an epidemic model in which the worm can dynamically control the rate at which it kills the infected node and also the transmission range and/or the media scanning rate. at each moment of time, the worm at each node faces the following trade-offs: (i) using larger transmission range and media scanning rate to accelerate its spread at the cost of exhausting the battery and thereby reducing the overall infection propagation rate in the long run or (ii) killing the node to inflict a large cost on the network, however at the expense of loosing the chance of infecting more susceptible nodes at later times. we mathematically formulate the decision problems and utilize pontryagin maximum principle from optimal control theory to quantify the damage that the malware can inflict on the network by deploying optimum decision rules. next, we establish structural properties of the optimal strategy of the attacker over time. specifically, we prove that it is optimal for the attacker to defer killing of the infective nodes in the propagation phase for a certain time and then start the slaughter with maximum effort. we also show that in the optimal attack policy, the battery resources are used according to a decreasing function of time, i.e., mostly during the initial phase of the outbreak. finally, our numerical investigations reveal a framework for identifying intelligent defense strategies that can limit the damage by appropriately selecting network parameters.
extending access point connectivity through opportunistic routing in vehicular networks. nowadays, the navigation systems available on cars are becoming more and more sophisticated. they greatly improve the experience of drivers and passengers by enabling them to receive map and traffic updates, news feeds, advertisements, media files, etc. unfortunately, the bandwidth available to each vehicle with the current technology is severely limited. there have been many reports on the inability of 3g networks to cope with large size file downloads, especially in dense and mobile settings. a possible alternative is provided by wifi access points (aps) that are being installed in several countries along the main routes and in popular areas. although this approach significantly increases the available bandwidth, it still does not provide a fully satisfactory solution due to the limited transmission range (usually a few hundred meters). in this paper we present a novel routing protocol, based on opportunistic vehicle to vehicle communication, to enable efficient multi-hop routing capabilities between mobile vehicles and aps. unlike prior work, this protocol fully supports twoway communication, i.e., the traditional vehicle-to-ap as well as the more challenging ap-to-vehicle. we leverage the information offered by the navigation system in terms of final destination and path, to i) route packets to the closest ap and ii) to route replies back to the moving vehicle efficiently.
on approximation of new optimization methods for assessing network vulnerability. assessing network vulnerability before potential disruptive events such as natural disasters or malicious attacks is vital for network planning and risk management. it enables us to seek and safeguard against most destructive scenarios in which the overall network connectivity falls dramatically. existing vulnerability assessments mainly focus on investigating the inhomogeneous properties of graph elements, node degree for example, however, these measures and the corresponding heuristic solutions can provide neither an accurate evaluation over general network topologies, nor performance guarantees to large scale networks. to this end, in this paper, we investigate a measure called pairwise connectivity and formulate this vulnerability assessment problem as a new graph-theoretical optimization problem called β-disruptor, which aims to discover the set of critical node/edges, whose removal results in the maximum decline of the global pairwise connectivity. our results consist of the np-completeness and inapproximability proof of this problem, an o(log n log log n) pseudo-approximation algorithm for detecting the set of critical nodes and an o(log1.5 n) pseudoapproximation algorithm for detecting the set of critical edges. in addition, we devise an efficient heuristic algorithm and validate the performance of the our model and algorithms through extensive simulations.
evaluating potential routing diversity for internet failure recovery. as the internet becomes a critical infrastructure component of our global information-based society, any interruption to its availability can have significant economical and societal impacts. although many researches tried to improve the resilience through the bgp policy-compliant paths, it has been demonstrated that the internet is still highly vulnerable when major failures happen. in this paper, we aim to overcome the inherent constraint of the existing bgp-compliant recovery schemes and propose to seek additional potential routing diversity by relaxing bgp peering links and through internet exchange points (ixps). the focus of this paper is to evaluate the potentiality of these two schemes, rather than on their implementations. by collecting most complete as link map up-to-date with 31k nodes and 142k links, we demonstrate that the proposed potential routing diversity can recover 40% to 80% of the disconnected paths on average beyond bgp-compliant paths. this work suggests a promising venue to address the internet failures.
sample path bounds for long memory fbm traffic. fractional brownian motion (fbm) emerged as a useful model for self-similar and long-range dependent internet traffic. asymptotic, respectively, approximate performance measures are known from large deviations theory for single queuing systems with fbm traffic. in this paper we prove a rigorous sample path envelope for fbm that complements previous results. we find that both approaches agree in their outcome that overflow probabilities for fbm traffic have a weibull tail. we show numerical results on the impact of the variability and the correlation of fbm traffic on the queuing performance.
energy-conserving scheduling in multi-hop wireless networks with time-varying channels. maxweight algorithm, a.k.a., back-pressure algorithm, has received much attention as a viable solution for dynamic link scheduling in multi-hop wireless networks. the basic principle of the maxweight algorithm is to select a set of interference-free links with the maximum overall link weights in the network, where the link weight is determined by the queue difference between the transmitter and the receiver. while the throughput-optimality of the maxweight algorithm is well understood in the literature, the energy consumption induced by the maxweight algorithm is less studied, which is of great interest in energy-constrained wireless networks such as wireless sensor networks. in this paper, we propose an energy-conserving scheduling scheme, a.k.a., minimum energy scheduling (mes) algorithm for multi-hop wireless networks with stochastic traffic arrivals and time-varying channel conditions. we show that our algorithm is energy optimal in the sense that the proposed mes algorithm can achieve an energy consumption which is arbitrarily close to the global minimum solution. moreover, the energy efficiency of the mes algorithm is achieved without losing the throughputoptimality. in other words, the proposed mes algorithm is still throughput optimal whereas the average consumed energy in the network is significantly reduced, as compared to the traditional maxweight algorithm. the theoretical results are substantiated via simulations.
buffer management for aggregated streaming data with packet dependencies. in many applications the traffic traversing the network has inter-packet dependencies due to application-level encoding schemes. for some applications, e.g., multimedia streaming, dropping a single packet may render useless the delivery of a whole sequence. in such environments, the algorithm used to decide which packet to drop in case of buffer overflows must be carefully designed, to avoid goodput degradation. we present a model that captures such inter-packet dependencies, and design algorithms for performing packet discards. traffic consists of an aggregation of multiple streams, each of which consists of a sequence of inter-dependent packets. we provide two guidelines for designing buffer management algorithms for this problem, and demonstrate the effectiveness of these criteria. we devise an algorithm according to these guidelines and evaluate its performance analytically, using competitive analysis. we also present a simulation study that shows that the performance of our algorithm is within a small fraction of the performance of the best offline algorithm.
green wave: latency and capacity-efficient sleep scheduling for wireless networks. while scheduling the nodes in a wireless network to sleep periodically can save energy, it also incurs higher latency and lower throughput. we consider the problem of designing optimal sleep schedules in wireless networks, and show that finding sleep schedules that can minimize the latency over a given subset of source-destination pairs is np-hard. we also derive a latency lower bound given by d+o(1/p) for any sleep schedule with a required active rate (i.e., the fraction of active slots of each node) p, and the shortest path length d. we offer a novel solution to optimal sleep scheduling using green-wave sleep scheduling (gwss), inspired by coordinated traffic lights, which is shown to meet our latency lower bound (hence is latency-optimal) for topologies such as the line, grid, ring, torus and tree networks, under light traffic. for high traffic loads, we propose noninterfering gwss, which can achieve the maximum throughput scaling law given by t(n, p) = ω(p/√n) bits/sec on a grid network of size n, with a latency scaling law d(n, p) = o(√n)+o(1/p). finally, we extend gwss to a random network with n poisson-distributed nodes, for which we show an achievable throughput scaling law of t(n, p) = ω(p/√n log n) bits/sec and a corresponding latency scaling law d(n, p) = o(√n/ log n) + o(1/p); hence meeting the well-known gupta-kumar achievable throughput rate ω(1/√n log n) when p → 1.
truthful least-priced-path routing in opportunistic spectrum access networks. we study the problem of finding the least-priced path (lpp) between a source and a destination in opportunistic spectrum access (osa) networks. this problem is motivated by economic considerations, whereby spectrum opportunities are sold/leased to secondary radios (srs). this incurs a communication cost, e.g., for traffic relaying. as the beneficiary of these services, the end user must compensate the service-providing srs for their spectrum cost. to give an incentive (i.e., profit) for srs to report their true cost, typically the payment to a sr should be higher than the actual cost. however, from an end user's perspective, unnecessary overpayment should be avoided. so we are interested in the optimal route selection and payment determination mechanism that minimizes the price tag of the selected route and at the same time guarantees truthful cost reports from srs. this setup is in contrast to the conventional truthful least-cost path (lcp) problem, where the interest is to find the minimum-cost route. the lpp problem is investigated with and without capacity constraints at individual srs. for both cases, our algorithmic solutions can be executed in polynomial time. the effectiveness of our algorithms in terms of price saving is verified through extensive simulations.
bittorrent darknets. a private bittorrent site (also known as a "bit-torrent darknet") is a collection of torrents that can only be accessed by members of the darknet community. the private bittorrent sites also have incentive policies which encourage users to continue to seed files after completing downloading. although there are at least 800 independent bittorrent darknets in the internet, they have received little attention in the research community to date. we examine bittorrent darknets from macroscopic, medium-scopic and microscopic perspectives. for the macroscopic analysis, we consider 800+ private sites to obtain a broad picture of the darknet landscape, and obtain a rough estimate of the total number of files, accounts, and simultaneous peers within the entire darknet landscape. although the size of each private site is relatively small, we find the aggregate size of the darknet landscape to be surprisingly large. for the medium-scopic analysis, we investigate content overlap between four private sites and the public bittorrent ecosystem. for the microscopic analysis, we explore in-depth one private site and examine its user behavior. we observe that the seed-to-leecher ratios and upload-to-download ratios are much higher than in the public ecosystem. the macroscopic, medium-scopic and microscopic analyses when combined provide a vivid picture of the darknet landscape, and provide insight into how the darknet landscape differs from the public bittorrent ecosystem.
understanding node localizability of wireless ad-hoc networks. location awareness is highly critical for wireless ad-hoc and sensor networks. many efforts have been made to solve the problem of whether or not a network can be localized. nevertheless, based on the data collected from a working sensor network, it is observed that the network is not always entirely localizable. theoretical analyses also suggest that, in most cases, it is unlikely that all nodes in a network are localizable, although a (large) portion of the nodes can be uniquely located. existing studies merely examine whether or not a network is localizable as a whole; yet two fundamental questions remain unaddressed: first, given a network configuration, whether or not a specific node is localizable? second, how many nodes in a network can be located and which are them? in this study, we analyze the limitation of previous works and propose a novel concept of node localizability. by deriving the necessary and sufficient conditions for node localizability, for the first time, it is possible to analyze how many nodes one can expect to locate in sparsely or moderately connected networks. to validate this design, we implement our solution on a real-world system and the experimental results show that node localizability provides useful guidelines for network deployment and other location-based services.
deploying mesh nodes under non-uniform propagation. wireless mesh networks are popular as a cost-effective means to provide broadband connectivity to large user populations. a mesh network placement provides coverage, such that each target client location has a link to a deployed mesh node, and connectivity, such that each mesh node wirelessly connects directly to a gateway or via intermediate mesh nodes. prior work on placement assumes wireless propagation to be uniform in all directions, i.e., an unrealistic assumption of circular communication regions. in this paper, we present approximation algorithms to solve the np-hard mesh node placement problem for non-uniform propagation settings. the first key challenge is incorporating non-uniform propagation, which we address by formulating the problem input as a connectivity graph consisting of discrete target coverage locations and potential mesh node locations. this graph incorporates non-uniform propagation by specifying the estimated signal quality per link. secondly, our algorithms are the first to minimize the number of deployed mesh nodes with constant-factor approximation ratio in the non-uniform propagation setting. to achieve this, we formulate the degree-constrained terminal steiner tree problem and present approximation algorithms which leverage prior results on the steiner tree problem. third, it is impractical to measure all possible potential mesh links, and therefore deployment planning must rely on estimations. to address this challenge, we extend our algorithm to iteratively measure the links in the solution steiner tree, refining the graph input on a per-link basis in order to ensure the deployed network is not disconnected. finally, we use propagation measurements at 35,000 locations in the deployed googlewifi network to investigate placement in a realistic, non-uniform propagation environment. under this measured propagation setting, our algorithms result in up to 80% fewer mesh nodes than current algorithms and only require an average of 3 measurements per deployed mesh node to ensure backhaul connectivity.
distributed monitoring and aggregation in wireless sensor networks. self-monitoring the sensor statuses such as liveness, node density and residue energy is critical for maintaining the normal operation of the sensor network. when building the monitoring architecture, most existing work focuses on minimizing the number of monitoring nodes. however, with less monitoring points, the false alarm rate may increase as a consequence. in this paper, we study the fundamental tradeoff between the number of monitoring nodes and the false alarm rate in the wireless sensor networks. specifically, we propose fully distributed monitoring algorithms, to build up a poller-pollee based architecture with the objective to minimize the number of overall pollers while bounding the false alarm rate. based on the established monitoring architecture, we further explore the hop-by-hop aggregation opportunity along the multihop path from the polee to the poller, with the objective to minimize the monitoring overhead. we show that the optimal aggregation path problem is np-hard and propose an opportunistic greedy algorithm, which achieves an approximation ratio of 5/4. as far as we know, this is the first proved constant approximation ratio applied to the aggregation path selection schemes over the wireless sensor networks.
cooperative communications in multi-hop wireless networks: joint flow routing and relay node assignment. it has been shown that cooperative communications (cc) have the potential to significantly increase the capacity of wireless networks. however, most of the existing results are limited to single-hop wireless networks. to illustrate the benefits of cc in multi-hop wireless networks, we solve a joint optimization problem of relay node assignment and flow routing for concurrent sessions. we study this problem via mathematical modeling and solve it using a solution procedure based on the branch-and-cut framework. we design several novel components to speed-up the computation time of branch-and-cut. via numerical results, we show the significant rate gains that can be achieved by incorporating cc in multi-hop networks.
wireless network virtualization as a sequential auction game. we propose a virtualization framework to separate the network operator (no) who focuses on wireless resource management and service providers (sp) who target distinct objectives with different constraints. within the proposed framework, we model the interactions among sps and no as a stochastic game, each stage of which is played by sps (on behalf of the end users) and is regulated by the no through the vickrey-clarke-groves (vcg) mechanism. due to the strong coupling between the future decisions of sps and lack of global information at each sp, the stochastic game is notoriously hard. instead, we introduce conjectural prices to represent the future congestion levels the end users potentially will experience, via which the future interactions between sps are decoupled. then, the policy to play the dynamic rate allocation game becomes selecting the conjectural prices and announcing a strategic value function (i.e., the preference on the rate) at each time. we prove that there exists one nash equilibrium in the conjectural prices and, given the conjectural prices, the sps have to truthfully reveal their own value function. we further prove that this nash equilibrium results in efficient rate allocation in our virtualized wireless network. in other words, there are enough incentives for no to advertise such a conjectural price and sps to follow this advice.
employing the one-sender-multiple-receiver technique in wireless lans. in this paper, we study the one-sender-multiple-receiver (osmr) transmission technique, which allows one sender to send to multiple receivers simultaneously by utilizing multiple antennas at the sender. we implemented a prototype osmr transmitter/receiver with gnu software defined radio, and conducted experiments in a university building to study the physical layer characteristics of osmr. our results are positive and show that wireless channels allow osmr for a significant percentage of the time. motivated by our physical layer study, we propose extensions to the 802.11 mac protocol to support osmr transmission, which is backward compatible with existing 802.11 devices. we also note that the ap needs a packet scheduling algorithm to efficiently exploit osmr. we show that the scheduling problem without considering the packet transmission overhead can be formalized as a linear programming problem, but the scheduling problem considering the overhead is np-hard.we then propose a greedy algorithm to schedule osmr transmissions. we tested the proposed protocol and algorithm with simulations driven by traffic traces collected from wireless lans and channel state traces collected from our experiments, and the results show that osmr significantly improves the downlink performance
a hybrid decision approach for the association problem in heterogeneous networks. the area of networking games has had a growing impact on wireless networks. this reflects the recognition in the important scaling advantages that the service providers can benefit from by increasing the autonomy of mobiles in decision making. this may however result in inefficiencies that are inherent to equilibria in non-cooperative games. due to the concern for efficiency, centralized protocols keep being considered and compared to decentralized ones. from the point of view of the network architecture, this implies the co-existence of network-centric and terminal centric radio resource management schemes. instead of taking part within the debate among the supporters of each solution, we propose in this paper hybrid schemes where the wireless users are assisted in their decisions by the network that broadcasts aggregated load information. we derive the utilities related to the quality of service (qos) perceived by the users and develop a bayesian framework to obtain the equilibria. numerical results illustrate the advantages of using our hybrid game framework in an association problem in a network composed of hsdpa and 3g lte systems.
a flexible platform for hardware-aware network experiments and a case study on wireless network coding. in this paper, we present the design and implementation of a general, flexible hardware-aware network platform which takes hardware processing behavior into consideration to accurately evaluate network performance. the platform adopts a network-hardware co-simulation approach in which the ns-2 network simulator supervises the network-wide traffic flow and the systemc hardware simulator simulates the underlying hardware processing in network nodes. in addition, as a case study, we implemented wireless all-to-all broadcasting with network coding on the platform. we analyze the hardware processing behavior during the algorithm execution and evaluate the overall performance of the algorithm. our experimental results demonstrate that hardware processing has a significant impact on the algorithm performance and hence should be taken into consideration in the algorithm design. we expect that this hardwareaware platform will become a very useful tool for more accurate network simulations and optimal designs of processingintensive applications.
a new constant factor approximation for computing 3-connected m-dominating sets in homogeneous wireless networks. in this paper, we study the problem of constructing quality fault-tolerant connected dominating sets (cdss) in homogeneous wireless networks, which can be defined as minimum k-connected m-dominating set ((k,m)-cds) problem in unit disk graphs (udgs). we found that every existing approximation algorithm for this problem is incomplete for k ≥ 3 in a sense that it does not generate a feasible solution in some udgs. based on these observations, we propose a new polynomial time approximation algorithm for computing (3, m)-cdss. we also show that our algorithm is correct and its approximation ratio is a constant.
understanding sub-stream scheduling in p2p hybrid live streaming systems. the p2p pull-push hybrid architecture has achieved great success in delivering live video traffic over the internet. however, a formal study on the sub-stream scheduling problem, a key design issue in hybrid systems, is still lacking. in this paper, we propose a max-flow model for mathematical analysis of this problem. we find that the sub-stream scheduling schemes used in existing hybrid systems, including coolstreaming+, gridmedia and lstreaming, individually solve one special case of the proposed max-flow model. moreover, this model can also serve as a benchmark to assess the performance of these existing sub-stream scheduling schemes. further, we propose a weighted max-flow scheme to address the issue of peer heterogeneity in scheduling sub-streams. finally, we point out the benefits of combining the hybrid streaming architecture and layered coding, and we also investigate how to schedule sub-streams in hybrid layered streaming systems.
randomized differential dsss: jamming-resistant wireless broadcast communication. jamming resistance is crucial for applications where reliable wireless communication is required. spread spectrum techniques such as frequency hopping spread spectrum (fhss) and direct sequence spread spectrum (dsss) have been used as countermeasures against jamming attacks. traditional anti-jamming techniques require that senders and receivers share a secret key in order to communicate with each other. however, such a requirement prevents these techniques from being effective for anti-jamming broadcast communication, where a jammer may learn the shared key from a compromised or malicious receiver and disrupt the reception at normal receivers. in this paper, we propose a randomized differential dsss (rd-dsss) scheme to achieve anti-jamming broadcast communication without shared keys. rd-dsss encodes each bit of data using the correlation of unpredictable spreading codes. specifically, bit "0" is encoded using two different spreading codes, which have low correlation with each other, while bit "1" is encoded using two identical spreading codes, which have high correlation. to defeat reactive jamming attacks, rd-dsss uses multiple spreading code sequences to spread each message and rearranges the spread output before transmitting it. our theoretical analysis and simulation results show that rd-dsss can effectively defeat jamming attacks for anti-jamming broadcast communication without shared keys.
leaping multiple headers in a single bound: wire-speed parsing using the kangaroo system. more fundamental than ip lookups and packet classification in routers is the extraction of fields such as ip dest and tcp ports that determine packet forwarding. while parsing of packet fields used to be easy, new shim layers (e.g., mpls, 802.1q, mac-in-mac) of possibly variable length have greatly increased the worst-case path in the parse tree. the problem is exacerbated by the need to accommodate new packet headers and to extract other higher layer fields. programmable routers for projects such as geni will need such flexible parsers. in this paper, we describe the design and implementation of the kangaroo system, a flexible packet parser that can run at 40 gbps even for worst-case packet headers. because conventional solutions that traverse the parse tree one protocol at a time are too slow, kangaroo uses lookahead to parse several protocol headers in one step using a new architecture in which a cam directs the next set of bytes to be extracted. the challenge is to keep the number of cam entries from growing exponentially with the amount of lookahead. we deal with this challenge using a non-uniform traversal of the parse tree, and an offline dynamic programming algorithm that calculates the optimal walk. our experiments on a netfpga prototype show a speedup of 2 compared to an architecture with a lookahead of 1. the architecture can be implemented as a parsing block in a standard 400 mhz asic at 40 gbps using less than 1% of chip area.
distributed power control for cognitive user access based on primary link control feedback. we venture beyond the "listen-before-talk" strategy that is common in many traditional cognitive radio access schemes. we exploit the bi-directional nature of most primary communication systems. by intelligently choosing their transmission parameters based on the observation of primary user (pu) communications, secondary users (sus) in a cognitive network can achieve higher spectrum usage while limiting their interference to the pu. specifically, we propose that the sus listen to the pu's feedback channel to assess their interference on the primary receiver (pu-rx), and adjust radio power accordingly to satisfy the pu's interference constraint. we investigate both centralized and distributed power control algorithms without active pu cooperation. we show that the pu feedback information inherent in many two-way primary systems can be used as important coordination signal among multiple sus to distributively achieve a joint performance guarantee on the primary receiver's quality of service.
acr: active collision recovery in dense wireless sensor networks. packet collision causes packet loss and wastes resources in wireless networks. it becomes even worse in dense wsns, due to burst-traffic and congestion around sinks. in this paper, we propose a novel protocol to recover collided packets. our experiments on a testbed reveal that collisions between long packets and short packets cause a partial error pattern on collided packets, which can be used for efficient recovery. we give a theoretical analysis that demonstrates that combining such collision recovery with csma protocols achieves a significant performance improvement. then, we design acr, an active collision recovery protocol, which actively converts most potential collisions into ls-collisions, and then applies a lightweight fec scheme to recover collided packets with such partial error patterns. we implement acr on a tmote testbed, and compare its performance with other packet recovery schemes. results show that acr significantly reduces the number of retransmissions, and achieves around 25% improvement on transmission efficiency over other schemes.
distance estimation by constructing the virtual ruler in anisotropic sensor networks. distance estimation is fundamental for many functionalities of wireless sensor networks and has been studied intensively in recent years. a critical challenge in distance estimation is handling anisotropic problems in sensor networks. compared with isotropic networks, anisotropic networks are more intractable in that their properties vary according to the directions of measurement. anisotropic properties result from various factors, such as geographic shapes, irregular radio patterns, node densities, and impacts from obstacles. in this paper, we study the problem of measuring irregularity of sensor networks and evaluating its impact on distance estimation. in particular, we establish a new metric to measure irregularity along a path in sensor networks, and identify turning nodes where a considered path is inflected. furthermore, we develop an approach to construct a virtual ruler for distance estimation between any pair of sensor nodes. the construction of a virtual ruler is carried out according to distance measurements among beacon nodes. however, it does not require beacon nodes to be deployed uniformly throughout sensor networks. compared with existing methods, our approach neither assumes global knowledge of boundary recognition nor relies on uniform distribution of beacon nodes. therefore, this approach is robust and applicable in practical environments. simulation results show that our approach outperforms some previous methods, such as dvdistance and pdm.
efficient two-dimensional data allocation in ieee 802.16 ofdma. the ieee 802.16 standard uses orthogonal frequency division multiple access (ofdma) for mobility support. therefore, the medium access control frame extends in two dimensions, i.e., time and frequency. at the beginning of each frame, i.e., every 5 ms, the base station is responsible both for scheduling packets, based on the negotiated quality of service requirements, and for allocating them into the frame, according to the restrictions imposed by 802.16 ofdma. to break down the complexity, a split approach has been proposed in the literature, where the two tasks are solved in separate and subsequent stages. in this paper we focus on the allocation task alone, which is addressed in its full complexity, i.e., by considering that data within the frame must be allocated as bursts with rectangular shape, each consisting of a set of indivisible sub-bursts, and that a variable portion of the frame is reserved for in-band signaling. after proving that the resulting allocation problem is np-hard, we develop an efficient heuristic algorithm, called recursive tiles and stripes (rts), to solve it. rts, in addition to handle a more general problem, is shown to perform better than state-of-the-art solutions via numerical analysis with realistic system parametrization.
an optimization based distributed algorithm for mobile data gathering in wireless sensor networks. recent advances have shown a great potential of anchor based mobile data gathering in wireless sensor networks. in such a scheme, during each periodic data gathering tour, the mobile collector stays at each anchor point for a period of sojourn time and collects data from nearby sensors via multi-hop communications. we provide an optimization based distributed algorithm for such data gathering in this paper. we adopt network utility, which is a properly defined function, to characterize the data gathering performance, and formalize the problem as a network utility maximization problem under the constraint of guaranteed network lifetime. to efficiently solve the problem, we decompose it into two sets of subproblems and solve them in a distributed manner, which facilitates the scalable implementations. finally, we provide numerical results to demonstrate the convergence of the proposed distributed algorithm.
a node-failure-resilient anonymous communication protocol through commutative path hopping. with rising concerns on user privacy over the internet, anonymous communication systems that hide the identity of a participant from its partner or third parties are highly desired. existing approaches either rely on a relative small set of pre-selected relay servers to redirect the messages, or use structured peer-to-peer systems to multicast messages among a set of relay groups. the pre-selection approaches provide good anonymity, but suffer from node failures and scalability problem. the peer-to-peer approaches are subject to node churns and high maintenance overhead, which are the intrinsic problems of p2p systems. in this paper, we present cat, a node-failure-resilient anonymous communication protocol. in this protocol, relay servers are randomly assigned to relay groups. the initiator of a connection selects a set of relay groups instead of relay servers to set up anonymous paths. a valid path consists of relay servers, one from each selected relay group. the initiator explores valid anonymous paths via a probing process. since the relative positions of relay servers in the path are commutative, there exist multiple anonymous yet commutative paths, which form an anonymous tunnel. when a connection encounters a node failure, it quickly switches to a nearest backup path in the tunnel through "path hopping", without tampering the initiator or renegotiating the keys. hence, the protocol is resilient to node failures. we also show that the protocol provides good anonymity even when facing types of active and passive attacks. finally, the operating cost of cat is analyzed and shown to be similar to other node-based anonymous communication protocols.
on the viability of paris metro pricing for communication and service networks. paris metro pricing (pmp) is a simple multi-class flat-rate pricing scheme already practiced by transport systems, specifically by the paris metro at one time. the name is coined after andrew odlyzko proposed it for the internet as a simple way to provide differentiated services. subsequently, there were several analytical studies of this promising idea. the central issue of these studies is whether pmp is viable, namely, whether it will produce more profit for the service provider, or whether it will achieve more social welfare. the previous studies considered similar models, but arrived at different conclusions. in this paper, we point out that the key is how the users react to the congestion externality of the underlying system. we derive sufficient conditions of congestion functions that can guarantee the viability of pmp, and provide the relevant physical meanings of these conditions.
implementation and evaluation of cooperative communication schemes in software-defined radio testbed. cooperative communication is a promising technique for future wireless networks, which significantly improves link capacity and reliability by leveraging broadcast nature of wireless medium and exploiting cooperative diversity. however, most of existing works investigate its performance theoretically or by simulation. it has been widely accepted that simulations often fail to faithfully capture many real-world radio signal propagation effects, which can be overcome through developing physical wireless network testbeds. in this work, we build a cooperative testbed based on gnu radio and universal software radio peripheral (usrp) platform, which is a promising open-source software-defined radio system. both single-relay cooperation and multi-relay cooperation can be supported in our testbed. some key techniques are provided to solve the main challenges during the testbed development: e.g., maximum ratio combine in single-relay transmission and synchronized transmission among multiple relays. extensive experiments are carried out in the testbed to evaluate performance of various cooperative communication schemes. the results show that cooperative transmission achieves significant performance enhancement in terms of link reliability and end-to-end throughput.
resource allocation over network dynamics without timescale separation. we consider a widely applicable model of resource allocation where two sequences of events are coupled: on a continuous time axis (t), network dynamics evolve over time. on a discrete time axis [t], certain control laws update resource allocation variables according to some proposed algorithm. the algorithmic updates, together with exogenous events out of the algorithm's control, change the network dynamics, which in turn changes the trajectory of the algorithm, thus forming a loop that couples the two sequences of events. in between the algorithmic updates at [t - 1] and [t], the network dynamics continue to evolve randomly as influenced by the previous variable settings at time [t - 1]. the standard way used to avoid the subsequent analytic difficulty is to assume the separation of timescales, which in turn unrealistically requires either slow network dynamics or high complexity algorithms. in this paper, we develop an approach that does not require separation of timescales. it is based on the use of stochastic approximation algorithms with continuous-time controlled markov noise. we prove convergence of these algorithms without assuming timescale separation. this approach is applied to develop simple algorithms that solve the problem of utility-optimal random access in multi-channel, multiradio wireless networks.
high-speed per-flow traffic measurement with probabilistic multiplicity counting. on today's high-speed backbone network links, measuring per-flow traffic information has become very challenging. maintaining exact per-flow packet counters on oc-192 or oc-768 links is not practically feasible due to computational and cost constrains. packet sampling as implemented in today's routers results in large approximation errors. here, we present probabilistic multiplicity counting (pmc), a novel data structure that is capable of accounting traffic per flow probabilistically. the pmc algorithm is very simple and highly parallelizable, and therefore allows for efficient implementations in software and hardware. at the same time, it provides very accurate traffic statistics. we evaluate pmc with both artificial and real-world traffic data, demonstrating that it outperforms other approaches.
optimal control of wireless networks with finite buffers. this paper considers network control for wireless networks with finite buffers. we investigate the performance of joint flow control, routing, and scheduling algorithms which achieve high network utility and deterministically bounded backlogs inside the network. our algorithms guarantee that buffers inside the network never overflow. we study the tradeoff between buffer size and network utility and show that if internal buffers have size (n - 1)/ε then a high fraction of the maximum utility can be achieved, where ε captures the loss in utility and n is the number of network nodes. the underlying scheduling/routing component of the considered control algorithms requires ingress queue length information (iqi) at all network nodes. however, we show that these algorithms can achieve the same utility performance with delayed ingress queue length information. numerical results reveal that the considered algorithms achieve nearly optimal network utility with a significant reduction in queue backlog compared to the existing algorithm in the literature. finally, we discuss extension of the algorithms to wireless networks with time-varying links.
the impact of virtualization on network performance of amazon ec2 data center. cloud computing services allow users to lease computing resources from large scale data centers operated by service providers. using cloud services, users can deploy a wide variety of applications dynamically and on-demand. most cloud service providers use machine virtualization to provide flexible and costeffective resource sharing. however, few studies have investigated the impact of machine virtualization in the cloud on networking performance. in this paper, we present a measurement study to characterize the impact of virtualization on the networking performance of the amazon elastic cloud computing (ec2) data center. we measure the processor sharing, packet delay, tcp/udp throughput and packet loss among amazon ec2 virtual machines. our results show that even though the data center network is lightly utilized, virtualization can still cause significant throughput instability and abnormal delay variations. we discuss the implications of our findings on several classes of applications.
worst-case tcam rule expansion. designers of tcams (ternary cams) for packet classification deal with unpredictable sets of rules, resulting in highly variable rule expansions, and rely on heuristic encoding algorithms with no reasonable expansion guarantees. in this paper, given several types of rules, we provide new upper bounds on the tcam worst-case rule expansions. in particular, we prove that a w-bit range can be encoded using w tcam entries, improving upon the previously-known bound of 2w-5. we also propose a modified tcam architecture that uses additional logic to significantly reduce the rule expansions, both in the worst case and in experiments with real-life classification databases.
ripple authentication for network coding. by allowing routers to randomly mix the information content in packets before forwarding them, network coding can maximize network throughput in a distributed manner with low complexity. however, such mixing also renders the transmission vulnerable to pollution attacks, where a malicious node injects corrupted packets into the information flow. in a worst case scenario, a single corrupted packet can end up corrupting all the information reaching a destination. in this paper, we propose ripple, a symmetric key based in-network scheme for network coding authentication. ripple allows a node to efficiently detect corrupted packets and encode only the authenticated ones. despite using symmetric key based homomorphic message authentication code (mac) algorithms, ripple achieves asymmetry by delayed disclosure of the mac keys. our work is the first symmetric key based solution to allow arbitrary collusion among adversaries. it is also the first to consider tag pollution attacks, where a single corrupted mac tag can cause numerous packets to fail authentication farther down the stream, effectively emulating a successful pollution attack.
on the fundamental limits of broadcasting in wireless mobile networks. in this paper, we investigate the fundamental properties of broadcasting in mobile wireless networks. in particular, we characterize broadcast capacity and latency of a mobile network, subject to the condition that the stationary node spatial distribution generated by the mobility model is uniform. we first study the intrinsic properties of broadcasting, and present a broadcasting scheme that simultaneously achieves asymptotically optimal broadcast capacity and latency, subject to a weak upper bound on the maximum node velocity. we then investigate the broadcasting problem when the burden related to selecting relay nodes is taken into account, and present a combined distributed leader election and broadcasting scheme achieving a broadcast capacity and latency which is within a poly-logarithmic factor from optimal.
coupled 802.11 flows in urban channels: model and experimental evaluation. contending flows in multi-hop 802.11 wireless networks compete with two fundamental asymmetries: (i) channel asymmetry, in which one flow has a stronger signal, potentially yielding physical layer capture, and (ii) topological asymmetry, in which one flow has increased channel state information, potentially yielding an advantage in winning access to the channel. prior work has considered these asymmetries independently with a highly simplified view of the other. however, in this work, we perform thousands of measurements on coupled flows in urban environments and build a simple, yet accurate model that jointly considers information and channel asymmetries. we show that if these two asymmetries are not considered jointly, throughput predictions of even two coupled flows are vastly distorted from reality when traffic characteristics are only slightly altered (e.g., changes to modulation rate, packet size, or access mechanism). these performance modes are sensitive not only to small changes in system properties, but also small-scale link fluctuations that are common in an urban mesh network. we analyze all possible capture relationships for two-flow sub-topologies and show that capture of the reverse traffic can allow a previously starving flow to compete fairly. finally, we show how to extend and apply the model in domains such as modulation rate adaptation and understanding the interaction of control and data traffic.
a greedy link scheduler for wireless networks with gaussian multiple access and broadcast channels. information theoretic broadcast channels (bc) and multiple access channels (mac) enable a single node to transmit data simultaneously to multiple nodes, and multiple nodes to transmit data simultaneously to a single node respectively. in this paper, we address the problem of link scheduling in multihop wireless networks containing nodes with bc and mac capabilities. we first propose an interference model that extends protocol interference models, originally designed for point to point channels, to include the possibility of bc and mac. due to the high complexity of optimal link schedulers, we introduce the multiuser greedy maximum weight algorithm for link scheduling in multihop wireless networks containing bcs and macs. given a network graph, we develop new local pooling conditions and show that the performance of our algorithm can be fully characterized using the associated parameter, the multiuser local pooling factor. we provide examples of some network graphs, on which we apply local pooling conditions and derive the multiuser local pooling factor. we prove optimality of our algorithm in tree networks and show that the exploitation of bcs and macs improve the throughput performance considerably in multihop wireless networks.
designing a practical access point association protocol. in a wireless local area network (wlan), the access point (ap) selection of a client heavily influences the performance of its own and others. through theoretical analysis, we reveal that previously proposed association protocols are not effective in maximizing the minimal throughput among all clients. accordingly, we propose an online ap association strategy that not only achieves a minimal throughput (among all clients) that is provably close to the optimum, but also works effectively in practice with a reasonable computational overhead. the association protocol applying this strategy is implemented on the commercial hardware and compatible with legacy aps without any modification. we demonstrate its feasibility and performance through real experiments.
a tractable and accurate cross-layer model for multi-hop mimo networks. mimo-based communications have great potential to improve network capacity for multi-hop wireless networks. although there has been significant progress on mimo at the physical layer or single-hop communication, advances in the theory of mimo for multi-hop wireless networks remain limited. this stagnation is mainly due to the lack of an accurate and more important, analytically tractable model that can be used by networking researchers. in this paper, we propose such a model to enable the networking community to carry out crosslayer research for multi-hop mimo networks. in particular, at the physical layer, we develop a simple model for mimo channel capacity computation that captures the essence of spatial multiplexing and transmit power limit without involving complex matrix operations and the water-filling algorithm. we show that the approximation gap in this model is negligible. at the link layer, we devise a space-time scheduling scheme called obic that significantly advances the existing zero-forcing beamforming (zfbf) to handle interference in a multi-hop network setting. the proposed obic scheme employs simple algebraic computation on matrix dimensions to simplify zfbf in a multi-hop network. as a result, we can characterize link layer scheduling behavior without entangling with beamforming details. finally, we apply both the new physical and link layer models in cross-layer performance optimization for a multi-hop mimo network.
minimizing electricity cost: optimization of distributed internet data centers in a multi-electricity-market environment. the study of cyber-physical system (cps) has been an active area of research. internet data center (idc) is an important emerging cyber-physical system. as the demand on internet services drastically increases in recent years, the power used by idcs has been skyrocketing. while most existing research focuses on reducing power consumptions of idcs, the power management problem for minimizing the total electricity cost has been overlooked. this is an important problem faced by service providers, especially in the current multi-electricity market, where the price of electricity may exhibit time and location diversities. further, for these service providers, guaranteeing quality of service (i.e. service level objectives-slo) such as service delay guarantees to the end users is of paramount importance. this paper studies the problem of minimizing the total electricity cost under multiple electricity markets environment while guaranteeing quality of service geared to the location diversity and time diversity of electricity price. we model the problem as a constrained mixed-integer programming and propose an efficient solution method. extensive evaluations based on reallife electricity price data for multiple idc locations illustrate the efficiency and efficacy of our approach.
maximizing energy efficiency for convergecast via joint duty cycle and route optimization. the energy efficiency of the widely used converge-cast pattern depends substantially on the choice of medium access control (mac) and routing protocol. in this paper, we formalize the maximization of convergecast energy efficiency with respect to its mac and routing as a resource constrained optimization problem. we then analytically show that this maximization problem is linear in the context of two prototypical macs -- a locally synchronized wakeup (as in s-mac) and a locally staggered wakeup mac (as in o-mac)-- assuming low, uniform traffic that is delivered reliably and without interference. with this insight, we present a centralized algorithm, meecast, that solves the optimization problem utilizing linear programming techniques. we also design a distributed version of meecast, for the case where the traffic is ultra-low, and prove that it achieves optimality as well as fast convergence time. notably, this version is self-stabilizing, so it autonomically handles changes in traffic load, network topology, loss of coordination and state corruption. in comparison with dozer, a state-of-the-art convergecast protocol, meecast achieves better energy efficiency and application lifetime in the context of s-mac and identical energy efficiency but better application lifetime in the context of o-mac.
tracking skype voip calls over the internet. peer-to-peer (p2p) voip calls such as those provided by skype have been becoming popular due to their quality-of-service, free of cost, security and convenience. skype is a distributed p2p network with no centralized call servers. calls traverse through a myriad of possible paths before reaching to the destination and each packet is encrypted with 256 bit aes encryption. in this paper, we are particularly interested in tracing out from this entangled web of peer nodes, who has called a target subscriber or to whom the target subscriber is calling. to this end, we present a transparent packet marking scheme that not only determines the origination and destination of a call but also the path taken through various hosts in p2p networks.
optimal linear network coding design for secure unicast with multiple streams. linear network coding is a promising technology that can maximize the throughput capacity of communication network. despite this salient feature, there are still many challenges to be addressed, and security is clearly one of the most important challenges. in this paper, we will address the design of secure linear network coding. specifically, we will investigate the network coding design that can both satisfy the weakly secure requirements and maximize the transmission data rate of multiple unicast streams between the same source and destination pair, which has not been addressed in the literature. in our study, we first prove that the secure unicast routing problem is equivalent to a constrained link-disjoint path problem. we then develop efficient algorithm that can find the optimal unicast topology in a polynomial amount of time. based on the topology, we design deterministic linear network code that is weakly secure and can be constructed at the source node. and finally, we investigate the potential of random linear code for weakly secure unicast and prove the low bound of the probability that a random linear code is weakly secure.
robust and fast pattern matching for intrusion detection. the rule language of an intrusion detection system (ids) plays a critical role in its effectiveness. a rule language must be expressive, in order to describe attack patterns as precisely as possible. it must also allow for a matching algorithm with predictable and low complexity, in order to ensure robustness against denial-of-service attacks. unfortunately, these requirements often conflict. we show, for instance, that a single rule, when coupled with a backtracking matching algorithm, can bring the processing rate down to nearly one packet per second. performance vulnerabilities of this type are known for patterns described using regular expressions, and can be avoided by using a deterministic matching algorithm. increasingly, however, rules are being written using the more powerful regex syntax, which includes non-regular features such as back-references. the matching algorithm for general regex's is based on backtracking, and is thus vulnerable to attacks. the main contribution of this paper is a deterministic algorithm for the full regex syntax, which builds upon the deterministic algorithm for regular expressions. we provide a (rough) complexity bound on the worst-case performance, and show that this bound can be tightened through compile-time analysis of the regex structure. these bounds can be used as an admissibility check, to isolate expressions that require further analysis. finally, we present an implementation of these algorithms in the context of the snort ids, and experimental results on several packet traces which show substantial improvement over the backtracking algorithm.
minimizing energy consumption with probabilistic distance models in wireless sensor networks. minimizing energy consumption in wireless sensor networks has been a challenging issue, and grid-based clustering and routing schemes have attracted a lot of attention due to their simplicity and feasibility. thus how to determine the optimal grid size in order to minimize energy consumption and prolong network lifetime becomes an important problem during the network planning and dimensioning phase. so far most existing work uses the average distances within a grid and between neighbor grids to calculate the average energy consumption, which we found largely underestimates the real value. in this paper, we propose, analyze and evaluate the energy consumption models in wireless sensor networks with probabilistic distance distributions. these models have been validated by numerical and simulation results, which shows that they can be used to optimize grid size and minimize energy consumption accurately. we also use these models to study variable-size grids, which can further improve the energy efficiency by balancing the relayed traffic in wireless sensor networks.
source-location privacy through dynamic routing in wireless sensor networks. wireless sensor networks (wsns) have the potential to be widely used in many areas for unattended event monitoring. mainly due to lack of a protected physical boundary, wireless communications are vulnerable to unauthorized interception and detection. privacy is becoming one of the major issues that jeopardize the successful deployment of wireless sensor networks. while confidentiality of the message can be ensured through content encryption, it is much more difficult to adequately address the source-location privacy. for wsns, source-location privacy service is further complicated by the fact that the sensor nodes consist of low-cost and low-power radio devices, computationally intensive cryptographic algorithms and large scale broadcasting-based protocols are not suitable for wsns. in this paper, we propose source-location privacy schemes through routing to randomly selected intermediate node(s) before the message is transmitted to the sink node. we first describe routing through a single a single randomly selected intermediate node away from the source node. our analysis shows that this scheme can provide great local source-location privacy. we also present routing through multiple randomly selected intermediate nodes based on angle and quadrant to further improve the global source location privacy. while providing source-location privacy for wsns, our simulation results also demonstrate that the proposed schemes are very efficient in energy consumption, and have very low transmission latency and high message delivery ratio. our protocols can be used for many practical applications.
critical sensor density for partial connectivity in large area wireless sensor networks. assume sensor deployment follows the poisson distribution. for a given partial connectivity requirement ρ, 0.5 < ρ < 1, we prove, for a hexagon model, that there exists a critical sensor density λ0, around which the probability that at least 100ρ% of sensors are connected in the network increases sharply from ɛ to 1- ɛ within a short interval of sensor density λ. the location of λ0 is at the sensor density where the above probability is about 1/2. we also extend the results to the disk model. simulations are conducted to confirm the theoretical results.
a practical on-line pacing scheme at edges of small buffer networks. for the optical packet-switching routers to be widely deployed in the internet, the size of packet buffers on routers has to be significantly small. such small-buffer networks rely on traffic with low levels of burstiness to avoid buffer overflows and packet losses. we present a pacing system that proactively shapes traffic in the edge network to reduce burstiness. our queue length based pacing uses an adaptive pacing on a single queue and paces traffic indiscriminately where deployed. in this work, we show through analysis and simulation that this pacing approach introduces a bounded delay and that it effectively reduces traffic burstiness. we also show that it can achieve higher throughput than end-system based pacing.
topology discovery for virtual local area networks. in this paper we investigate the problem of finding the physical layer topology of large, heterogeneous networks that comprises multiple vlans and may include uncooperative network nodes. we prove that finding a layer-2 network topology for a given incomplete input is an np-hard problem even when the network comprises only two vlans and the network contains one loop and deciding whether a given input defines a unique vlans topology is a co-np-hard problem. we design several heuristic algorithms to find vlans topology. our first algorithm is designed for geographically wide-spread networks that may contain uncooperative devices. for such networks the algorithm discovers the topology for each vlan then merges them to infer the network topology in o(n3) time, where n is the number of internal network nodes. our second algorithm is designed for smaller, active networks where each device in the network provides access to their mib and few aft entries are missing. for such networks, the algorithm finds the unique topology of vlans in o(n3) time. we have implemented both the algorithms described in this paper and conducted extensive experiments on multiple networks. our experiments demonstrate that our approach is quite practical and discovers the accurate vlans topology of large and heterogeneous networks whose input may not necessarily be complete. to the best of our knowledge, this is the first paper investigating topology discovery for vlans.
pricing under constraints in access networks: revenue maximization and congestion management. this paper investigates pricing of internet connectivity services in the context of a monopoly isp selling broadband access to consumers. we first study the optimal combination of flat-rate and usage-based access price components for maximization of isp revenue, subject to a capacity constraint on the datarate demand. next, we consider time-varying consumer utilities for broadband data rates that can result in uneven demand for data-rate over time. practical considerations limit the viability of altering prices over time to smoothen out the demanded datarate. despite such constraints on pricing, our analysis reveals that the isp can retain the revenue by setting a low usage fee and dropping packets of consumer demanded data that exceed capacity. regulatory attention on isp congestion management discourages such "technical" practices and promotes economics based approaches. we characterize the loss in isp revenue from an economics based approach. regulatory requirements further impose limitations on price discrimination across consumers, and we derive the revenue loss to the isp from such restrictions. we then develop partial recovery of revenue loss through non-linear pricing that does not explicitly discriminate across consumers. while determination of the access price is ultimately based on additional considerations beyond the scope of this paper, the analysis here can serve as a benchmark to structure access price in broadband access networks.
practical scheduling algorithms for concurrent transmissions in rate-adaptive wireless networks. optimal scheduling for concurrent transmissions in rate-nonadaptive wireless networks is np-hard. optimal scheduling in rate-adaptive wireless networks is even more difficult, because, due to mutual interference, each flow's throughput in a time slot is unknown before the scheduling decision of that slot is finalized. the capacity bound derived for rate-nonadaptive networks is no longer applicable either. in this paper, we first formulate the optimal scheduling problems with and without minimum per-flow throughput constraints. given the hardness of the problems and the fact that the scheduling decisions should be made within a few milliseconds, we propose two simple yet effective searching algorithms which can quickly move towards better scheduling decisions. thus, the proposed scheduling algorithms can achieve high network throughput and maintain long-term fairness among competing flows with low computational complexity. for the constrained optimization problem involved, we consider its dual problem and apply lagrangian relaxation. we then incorporate a dual update procedure in the proposed searching algorithm to ensure that the searching results satisfy the constraints. extensive simulations are conducted to demonstrate the effectiveness and efficiency of the proposed scheduling algorithms which are found to achieve throughputs close to the exhaustive searching results with much lower computational complexity.
towards cooperative localization of wearable sensors using accelerometers and cameras. this work describes a new approach for localizing people by cooperative sensor fusion of lightweight camera and wearable accelerometer measurements. we present the algorithm to identify people moving around as they are detected by cameras deployed in the infrastructure. the algorithm uses a correlation metric to develop an id matching algorithm that can associate people in the scene to their global id emitted from a wireless accelerometer sensor node worn on their belts. first we conduct a set of preliminary experiments to verify that the quantities of interest easily measurable by off-the-shelf components. we validate our metric and the performance of the proposed id matching algorithm using simulations on testbed data that also includes a crowded scenario.
distributed dynamic speed scaling. in recent years we have witnessed a great interest in large distributed computing platforms, also known as clouds. while these systems offer enormous computing power, they are major energy consumers. in existing data centers cpus are responsible for approximately half of the energy consumed by the servers. a promising technique for saving cpu energy consumption is dynamic speed scaling, in which the speed at which the processor is run is adjusted based on demand and performance constraints. in this paper we look at the problem of allocating the demand in the network of processors (each being capable to perform dynamic speed scaling) to minimize the global energy consumption/cost subject to a performance constraint. the nonlinear dependence between the energy consumption and the performance as well as the high variability in the energy prices result in a nontrivial resource allocation. the problem can be abstracted as a fully distributed convex optimization with a linear constraint. on the theoretical side, we propose two low-overhead fully decentralized algorithms for solving the problem of interest and provide closed-form conditions that ensure stability of the algorithms. then we evaluate the efficacy of the optimal solution using simulations driven by the real-world energy prices. our findings indicate a possible cost reduction of 10-40% compared to power-oblivious 1/n load balancing, for a wide range of load factors.
verifiable fine-grained top-k queries in tiered sensor networks. most large-scale sensor networks are expected to follow a two-tier architecture with resource-poor sensor nodes at the lower tier and resource-rich master nodes at the upper tier. master nodes collect data from sensor nodes and then answer the queries from the network owner on their behalf. in hostile environments, master nodes may be compromised by the adversary and then instructed to return fake and/or incomplete data in response to data queries. such application-level attacks are more harmful and difficult to detect than blind dos attacks on network communications, especially when the query results are the basis for making critical decisions such as military actions. this paper presents three schemes whereby the network owner can verify the authenticity and completeness of fine-grained topk query results in tired sensor networks, which is the first work of its kind. the proposed schemes are built upon symmetric cryptographic primitives and force compromised master nodes to return both authentic and complete top-k query results to avoid being caught. detailed theoretical and quantitative results confirm the high efficacy and efficiency of the proposed schemes.
capauth: a capability-based handover scheme. existing handover schemes in wireless lans, 3g/4g networks, and femtocells rely upon protocols involving centralized authentication servers and one or more access points. these protocols are invariably complex and use extensive signaling on the wireless backhaul since they aim to be be efficient (minimal handover latency) without sacrificing robustness. however, the mobile user has little involvement especially with the so-called context transfer stage; this stage involves the transfer of necessary state to the new access point as well as the enforcement of security goals such as user authentication and single point of access. we propose the incorporation of user capabilities, network-asserted proofs of user identity and access control, as a general mechanism to simplify the context transfer stage. to this end, we have designed capauth, a capability-based scheme that has reduced complexity, low overhead, high level of fault tolerance and is general enough to implement a range of security policies.
reciprocity and barter in peer-to-peer systems. this work investigates reciprocity in peer-to-peer systems. the scenario is one where users arrive to the network with a set of contents and content demands. peers exchange contents to satisfy their demands, following either a direct reciprocity principle (i help you and you help me) or indirect reciprocity principle (i help you and someone helps me). first, we prove that any indirect reciprocity schedule of exchanges, in the absence of relays, can be replaced by a direct reciprocity schedule, provided that users (1) are willing to download undemanded content for bartering purposes and (2) use up to twice the bandwidth they would use under indirect reciprocity. motivated by the fact that, in the absence of relays, the loss of efficiency due to direct reciprocity is at most two, we study various distributed direct reciprocity schemes through simulations, some of them involving a broker to facilitate exchanges.
resilient routing for sensor networks using hyperbolic embedding of universal covering space. we study how to characterize the families of paths between any two nodes s, t in a sensor network with holes. two paths that can be deformed to one another through local changes are called homotopy equivalent. two paths that pass around holes in different ways have different homotopy types. with a distributed algorithm we compute an embedding of the network in hyperbolic space by using ricci flow such that paths of different homotopy types are mapped naturally to paths connecting s with different images of t. greedy routing to a particular image is guaranteed with success to find a path with a given homotopy type. this leads to simple greedy routing algorithms that are resilient to both local link dynamics and large scale jamming attacks and improve load balancing over previous greedy routing algorithms.
minimum energy per bit for wideband wireless multicasting: performance of decode-and-forward. we study the minimum energy per bit required for communicating a message to all the destination nodes in a wireless network. the physical layer is modeled as an additive white gaussian noise channel affected by circularly symmetric fading. the fading coefficients are known at neither transmitters nor receivers. we provide an information-theoretic lower bound on the energy requirement of multicasting in arbitrary wireless networks as the solution of a linear program. we study the broadcast performance of decode-and-forward operating in the non-coherent wideband scenario, and compare it with the lower bounds. for arbitrary networks with k nodes, the energy requirement of decode-and-forward is within a factor of k - 1 of the lower bound regardless of the magnitude of channel gains. we also show that decode-and-forward achieves the minimum energy per bit in networks that can be represented as directed acyclic graphs, thus establishing the exact minimum energy per bit for this class of networks. we also study regular networks where the area is divided into cells, each cell containing at least k and at most k nodes placed arbitrarily within the cell. a path loss model (with path loss exponent α > 2) dictates the channel gains between the nodes. it is shown that the ratio between the upper bound using decode-and-forward based flooding, and the lower bound is at most a constant times kα+2/k.
capacity region of a wireless mesh backhaul network over the csma/ca mac. this paper studies the maximum throughput that can be supported by a given wireless mesh backhaul network, over a practical csma/ca medium access control (mac) protocol. we resort to the multi-commodity flow (mcf) formulation, augmented with the conflict-graph constraints, to jointly compute the maximum throughput and the associated optimal network dimensioning; while use a novel approach to take into account the collision overhead in the distributed csma/ca mac. such overhead has been ignored by the existing mcf-based capacity studies, which assume impractical centralized scheduling and result in aggressive network dimensioning, unachievable over the csma/ca mac. we develop a generic method to integrate the csma/ca mac analysis with the mcf formulation for optimal network capacity analysis, and derive both an upper bound and a lower bound of the network throughput over a practical csma/ca protocol. to the best of our knowledge, this paper is the first rigorous theoretical study of the achievable capacity over a multi-hop csma/ca based wireless network.
a reaction-diffusion model for epidemic routing in sparsely connected manets. we propose and investigate a deterministic traveling wave model for the progress of epidemic routing in disconnected mobile ad hoc networks. in epidemic routing, broadcast or unicast is achieved by exploiting mobility: message-carrying nodes "infect" non message-carrying nodes when they come within communication range of them. early probabilistic analyses of epidemic routing follow a "well-mixed" model which ignores the spatial distribution of the infected nodes, and hence do not provide good performance estimates unless the node density is very low. more recent work has pointed out that the infection exhibits wave-like characteristics, but does not provide a detailed model of the wave propagation. in this paper, we model message propagation using a reaction-diffusion partial differential equation that has a traveling wave solution, and show that the performance predictions made by the model closely match simulations in regimes where the well-mixed model breaks down. in particular, we show that well-mixed models are generally overly optimistic in regard to the scaling of the message delivery delay with problem parameters such as communication range, node density, and total area. in contrast to prior work, our model provides insight into the spatial distribution of the "infection," and reveals that the performance is sensitive to the geometry of the deployment region, not just its area.
joint power and secret key queue management for delay limited secure communication. in recent years, the famous wiretap channel has been revisited by many researchers and information theoretic secrecy has become an active area of research in this setting. in this paper, we design a wireless communication system that achieves constant bit rate data transmission over a block fading channel, securely from an eavesdropper that listens to the transmitter over another independent block fading channel. it is well known that, the method of sending secure information using the binning techniques inspired by the wiretap channel fails to secure the information at times when the eavesdropper channel has favorable conditions over the main channel. this phenomenon is called secrecy outage. in our system, however, we exploit the times at which the main channel is favorable over the eavesdropper channel for us to be able to transmit some random secret key bits along with the data bits. these key bits are stored in a separate key queue at the transmitter as well as the receiver, and are utilized to secure data bits, whenever the channel conditions favor the eavesdropper. we show that, our system achieves a high performance at any given desired outage probability by jointly controlling the key queue and the transmit power. we show that the optimal power control involves a time sharing between secure waterfilling and channel inversion strategies and the key queue operates in the heavy traffic regime to achieve the maximum delay limited rate possible, under a small outage constraint. this work can be viewed as a first step in providing a framework that combines both information theory and queueing analysis for the study of information theoretic security.
dynamics of conversations. how do online conversations build? is there a common model that human communication follows? in this work we explore these questions in detail. we analyze the structure of conversations in three different social datasets, namely, usenet groups, yahoo! groups, and twitter. we propose a simple mathematical model for the generation of basic conversation structures and then refine this model to take into account the identities of each member of the conversation.
discriminative topic modeling based on manifold learning. topic modeling has been popularly used for data analysis in various domains including text documents. previous topic models, such as probabilistic latent semantic analysis (plsa) and latent dirichlet allocation (lda), have shown impressive success in discovering low-rank hidden structures for modeling text documents. these models, however, do not take into account the manifold structure of data, which is generally informative for the non-linear dimensionality reduction mapping. more recent models, namely laplacian plsi (lapplsi) and locally-consistent topic model (ltm), have incorporated the local manifold structure into topic models and have shown the resulting benefits. but these approaches fall short of the full discriminating power of manifold learning as they only enhance the proximity between the low-rank representations of neighboring pairs without any consideration for non-neighboring pairs. in this paper, we propose discriminative topic model (dtm) that separates non-neighboring pairs from each other in addition to bringing neighboring pairs closer together, thereby preserving the global manifold structure as well as improving the local consistency. we also present a novel model fitting algorithm based on the generalized em and the concept of pareto improvement. as a result, dtm achieves higher classification performance in a semi-supervised setting by effectively exposing the manifold structure of data. we provide empirical evidence on text corpora to demonstrate the success of dtm in terms of classification accuracy and robustness to parameters compared to state-of-the-art techniques.
large linear classification when data cannot fit in memory. recent advances in linear classification have shown that for applications such as document classification, the training can be extremely efficient. however, most of the existing training methods are designed by assuming that data can be stored in the computer memory. these methods cannot be easily applied to data larger than the memory capacity due to the random access to the disk. we propose and analyze a block minimization framework for data larger than the memory size. at each step a block of data is loaded from the disk and handled by certain learning methods. we investigate two implementations of the proposed framework for primal and dual svms, respectively. as data cannot fit in memory, many design considerations are very different from those for traditional algorithms. experiments using data sets 20 times larger than the memory demonstrate the effectiveness of the proposed method.
versatile publishing for privacy preservation. motivated by the insufficiency of the existing quasi-identifier/sensitive-attribute (qi-sa) framework on modeling real-world privacy requirements for data publishing, we propose a novel versatile publishing scheme with which privacy requirements can be specified as an arbitrary set of privacy rules over attributes in the microdata table. to enable versatile publishing, we introduce the guardian normal form (gnf), a novel method of publishing multiple sub-tables such that each sub-table is anonymized by an existing qi-sa publishing algorithm, while the combination of all published tables guarantees all privacy rules. we devise two algorithms, guardian decomposition (gd) and utility-aware decomposition (uad), for decomposing a microdata table into gnf, and present extensive experiments over real-world datasets to demonstrate the effectiveness of both algorithms.
fast query execution for retrieval models based on path-constrained random walks. many recommendation and retrieval tasks can be represented as proximity queries on a labeled directed graph, with typed nodes representing documents, terms, and metadata, and labeled edges representing the relationships between them. recent work has shown that the accuracy of the widely-used random-walk-based proximity measures can be improved by supervised learning - in particular, one especially effective learning technique is based on path-constrained random walks (pcrw), in which similarity is defined by a learned combination of constrained random walkers, each constrained to follow only a particular sequence of edge labels away from the query nodes. the pcrw based method significantly outperformed unsupervised random walk based queries, and models with learned edge weights. unfortunately, pcrw query systems are expensive to evaluate. in this study we evaluate the use of approximations to the computation of the pcrw distributions, including fingerprinting, particle filtering, and truncation strategies. in experiments on several recommendation and retrieval problems using two large scientific publications corpora we show speedups of factors of 2 to 100 with little loss in accuracy.
automatic malware categorization using cluster ensemble. in this paper, resting on the analysis of instruction frequency and function-based instruction sequences, we develop an automatic malware categorization system (amcs) for automatically grouping malware samples into families that share some common characteristics using a cluster ensemble by aggregating the clustering solutions generated by different base clustering algorithms. we propose a principled cluster ensemble framework for combining individual clustering solutions based on the consensus partition. the domain knowledge in the form of sample-level constraints can be naturally incorporated in the ensemble framework. in addition, to account for the characteristics of feature representations, we propose a hybrid hierarchical clustering algorithm which combines the merits of hierarchical clustering and k-medoids algorithms and a weighted subspace k-medoids algorithm to generate base clusterings. the categorization results of our amcs system can be used to generate signatures for malware families that are useful for malware detection. the case studies on large and real daily malware collection from kingsoft anti-virus lab demonstrate the effectiveness and efficiency of our amcs system.
malstone: towards a benchmark for analytics on large data clouds. developing data mining algorithms that are suitable for cloud computing platforms is currently an active area of research, as is developing cloud computing platforms appropriate for data mining. currently, the most common benchmark for cloud computing is the terasort (and related) benchmarks. although the terasort benchmark is quite useful, it was not designed for data mining per se. in this paper, we introduce a benchmark called malstone that is specifically designed to measure the performance of cloud computing middleware that supports the type of data intensive computing common when building data mining models. we also introduce malgen, which is a utility for generating data on clouds that can be used with malstone.
fast euclidean minimum spanning tree: algorithm, analysis, and applications. the euclidean minimum spanning tree problem has applications in a wide range of fields, and many efficient algorithms have been developed to solve it. we present a new, fast, general emst algorithm, motivated by the clustering and analysis of astronomical data. large-scale astronomical surveys, including the sloan digital sky survey, and large simulations of the early universe, such as the millennium simulation, can contain millions of points and fill terabytes of storage. traditional emst methods scale quadratically, and more advanced methods lack rigorous runtime guarantees. we present a new dual-tree algorithm for efficiently computing the emst, use adaptive algorithm analysis to prove the tightest (and possibly optimal) runtime bound for the emst problem to-date, and demonstrate the scalability of our method on astronomical data sets.
active learning for biomedical citation screening. active learning (al) is an increasingly popular strategy for mitigating the amount of labeled data required to train classifiers, thereby reducing annotator effort. we describe a real-world, deployed application of al to the problem of biomedical citation screening for systematic reviews at the tufts medical center's evidence-based practice center. we propose a novel active learning strategy that exploits a priori domain knowledge provided by the expert (specifically, labeled features)and extend this model via a linear programming algorithm for situations where the expert can provide ranked labeled features. our methods outperform existing al strategies on three real-world systematic review datasets. we argue that evaluation must be specific to the scenario under consideration. to this end, we propose a new evaluation framework for finite-pool scenarios, wherein the primary aim is to label a fixed set of examples rather than to simply induce a good predictive model. we use a method from medical decision theory for eliciting the relative costs of false positives and false negatives from the domain expert, constructing a utility measure of classification performance that integrates the expert preferences. our findings suggest that the expert can, and should, provide more information than instance labels alone. in addition to achieving strong empirical results on the citation screening problem, this work outlines many important steps for moving away from simulated active learning and toward deploying al for real-world applications.
unifying dependent clustering and disparate clustering for non-homogeneous data. modern data mining settings involve a combination of attribute-valued descriptors over entities as well as specified relationships between these entities. we present an approach to cluster such non-homogeneous datasets by using the relationships to impose either dependent clustering or disparate clustering constraints. unlike prior work that views constraints as boolean criteria, we present a formulation that allows constraints to be satisfied or violated in a smooth manner. this enables us to achieve dependent clustering and disparate clustering using the same optimization framework by merely maximizing versus minimizing the objective function. we present results on both synthetic data as well as several real-world datasets.
mining uncertain data with probabilistic guarantees. data uncertainty is inherent in applications such as sensor monitoring systems, location-based services, and biological databases. to manage this vast amount of imprecise information, probabilistic databases have been recently developed. in this paper, we study the discovery of frequent patterns and association rules from probabilistic data under the possible world semantics. this is technically challenging, since a probabilistic database can have an exponential number of possible worlds. we propose two effcient algorithms, which discover frequent patterns in bottom-up and top-down manners. both algorithms can be easily extended to discover maximal frequent patterns. we also explain how to use these patterns to generate association rules. extensive experiments, using real and synthetic datasets, were conducted to validate the performance of our methods.
discovering frequent patterns in sensitive data. discovering frequent patterns from data is a popular exploratory technique in datamining. however, if the data are sensitive (e.g., patient health records, user behavior records) releasing information about significant patterns or trends carries significant risk to privacy. this paper shows how one can accurately discover and release the most significant patterns along with their frequencies in a data set containing sensitive information, while providing rigorous guarantees of privacy for the individuals whose information is stored there. we present two efficient algorithms for discovering the k most frequent patterns in a data set of sensitive records. our algorithms satisfy differential privacy, a recently introduced definition that provides meaningful privacy guarantees in the presence of arbitrary external information. differentially private algorithms require a degree of uncertainty in their output to preserve privacy. our algorithms handle this by returning 'noisy' lists of patterns that are close to the actual list of k most frequent patterns in the data. we define a new notion of utility that quantifies the output accuracy of private top-k pattern mining algorithms. in typical data sets, our utility criterion implies low false positive and false negative rates in the reported lists. we prove that our methods meet the new utility criterion; we also demonstrate the performance of our algorithms through extensive experiments on the transaction data sets from the fimi repository. while the paper focuses on frequent pattern mining, the techniques developed here are relevant whenever the data mining output is a list of elements ordered according to an appropriately 'robust' measure of interest.
compressed fisher linear discriminant analysis: classification of randomly projected data. we consider random projections in conjunction with classification, specifically the analysis of fisher's linear discriminant (fld) classifier in randomly projected data spaces. unlike previous analyses of other classifiers in this setting, we avoid the unnatural effects that arise when one insists that all pairwise distances are approximately preserved under projection. we impose no sparsity or underlying low-dimensional structure constraints on the data; we instead take advantage of the class structure inherent in the problem. we obtain a reasonably tight upper bound on the estimated misclassification error on average over the random choice of the projection, which, in contrast to early distance preserving approaches, tightens in a natural way as the number of training examples increases. it follows that, for good generalisation of fld, the required projection dimension grows logarithmically with the number of classes. we also show that the error contribution of a covariance misspecification is always no worse in the low-dimensional space than in the initial high-dimensional space. we contrast our findings to previous related work, and discuss our insights.
nonnegative shared subspace learning and its application to social media retrieval. although tagging has become increasingly popular in online image and video sharing systems, tags are known to be noisy, ambiguous, incomplete and subjective. these factors can seriously affect the precision of a social tag-based web retrieval system. therefore improving the precision performance of these social tag-based web retrieval systems has become an increasingly important research topic. to this end, we propose a shared subspace learning framework to leverage a secondary source to improve retrieval performance from a primary dataset. this is achieved by learning a shared subspace between the two sources under a joint nonnegative matrix factorization in which the level of subspace sharing can be explicitly controlled. we derive an efficient algorithm for learning the factorization, analyze its complexity, and provide proof of convergence. we validate the framework on image and video retrieval tasks in which tags from the labelme dataset are used to improve image retrieval performance from a flickr dataset and video retrieval performance from a youtube dataset. this has implications for how to exploit and transfer knowledge from readily available auxiliary tagging resources to improve another social web retrieval system. our shared subspace learning framework is applicable to a range of problems where one needs to exploit the strengths existing among multiple and heterogeneous datasets.
negative correlations in collaboration: concepts and algorithms. this paper studies efficient mining of negative correlations that pace in collaboration. a collaborating negative correlation is a negative correlation between two sets of variables rather than traditionally between a pair of variables. it signifies a synchronized value rise or fall of all variables within one set whenever all variables in the other set go jointly at the opposite trend. the time complexity is exponential in mining. the high efficiency of our algorithm is attributed to two factors: (i) the transformation of the original data into a bipartite graph database, and (ii) the mining of transpose closures from a wide transactional database. applying to a yeast gene expression data, we evaluate, by using pearson's correlation coefficient and p-value, the biological relevance of collaborating negative correlations as an example among many real-life domains.
multiple kernel learning for heterogeneous anomaly detection: algorithm and aviation safety case study. the world-wide aviation system is one of the most complex dynamical systems ever developed and is generating data at an extremely rapid rate. most modern commercial aircraft record several hundred flight parameters including information from the guidance, navigation, and control systems, the avionics and propulsion systems, and the pilot inputs into the aircraft. these parameters may be continuous measurements or binary or categorical measurements recorded in one second intervals for the duration of the flight. currently, most approaches to aviation safety are reactive, meaning that they are designed to react to an aviation safety incident or accident. in this paper, we discuss a novel approach based on the theory of multiple kernel learning to detect potential safety anomalies in very large data bases of discrete and continuous data from world-wide operations of commercial fleets. we pose a general anomaly detection problem which includes both discrete and continuous data streams, where we assume that the discrete streams have a causal influence on the continuous streams. we also assume that atypical sequences of events in the discrete streams can lead to off-nominal system performance. we discuss the application domain, novel algorithms, and also discuss results on real-world data sets. our algorithm uncovers operationally significant events in high dimensional data streams in the aviation industry which are not detectable using state of the art methods.
semantic relation extraction with kernels over typed dependency trees. an important step for understanding the semantic content of text is the extraction of semantic relations between entities in natural language documents. automatic extraction techniques have to be able to identify different versions of the same relation which usually may be expressed in a great variety of ways. therefore these techniques benefit from taking into account many syntactic and semantic features, especially parse trees generated by automatic sentence parsers. typed dependency parse trees are edge and node labeled parse trees whose labels and topology contains valuable semantic clues. this information can be exploited for relation extraction by the use of kernels over structured data for classification. in this paper we present new tree kernels for relation extraction over typed dependency parse trees. on a public benchmark data set we are able to demonstrate a significant improvement in terms of relation extraction quality of our new kernels over other state-of-the-art kernels.
fast nearest-neighbor search in disk-resident graphs. link prediction, personalized graph search, fraud detection, and many such graph mining problems revolve around the computation of the most "similar" k nodes to a given query node. one widely used class of similarity measures is based on random walks on graphs, e.g., personalized pagerank, hitting and commute times, and simrank. there are two fundamental problems associated with these measures. first, existing online algorithms typically examine the local neighborhood of the query node which can become significantly slower whenever high-degree nodes are encountered (a common phenomenon in real-world graphs). we prove that turning high degree nodes into sinks results in only a small approximation error, while greatly improving running times. the second problem is that of computing similarities at query time when the graph is too large to be memory-resident. the obvious solution is to split the graph into clusters of nodes and store each cluster on a disk page; ideally random walks will rarely cross cluster boundaries and cause page-faults. our contributions here are twofold: (a) we present an efficient deterministic algorithm to find the k closest neighbors (in terms of personalized pagerank) of any query node in such a clustered graph, and (b) we develop a clustering algorithm (rwdisk) that uses only sequential sweeps over data files. empirical results on several large publicly available graphs like dblp, citeseer and live-journal (~ 90 m edges) demonstrate that turning high degree nodes into sinks not only improves running time of rwdisk by a factor of 3 but also boosts link prediction accuracy by a factor of 4 on average. we also show that rwdisk returns more desirable (high conductance and small size) clusters than the popular clustering algorithm metis, while requiring much less memory. finally our deterministic algorithm for computing nearest neighbors incurs far fewer page-faults (factor of 5) than actually simulating random walks.
biosnowball: automated population of wikis. internet users regularly have the need to find biographies and facts of people of interest. wikipedia has become the first stop for celebrity biographies and facts. however, wikipedia can only provide information for celebrities because of its neutral point of view (npov) editorial policy. in this paper we propose an integrated bootstrapping framework named biosnowball to automatically summarize the web to generate wikipedia-style pages for any person with a modest web presence. in biosnowball, biography ranking and fact extraction are performed together in a single integrated training and inference process using markov logic networks (mlns) as its underlying statistical model. the bootstrapping framework starts with only a small number of seeds and iteratively finds new facts and biographies. as biography paragraphs on the web are composed of the most important facts, our joint summarization model can improve the accuracy of both fact extraction and biography ranking compared to decoupled methods in the literature. empirical results on both a small labeled data set and a real web-scale data set show the effectiveness of biosnowball. we also empirically show that biosnowball outperforms the decoupled methods.
the topic-perspective model for social tagging systems. in this paper, we propose a new probabilistic generative model, called topic-perspective model, for simulating the generation process of social annotations. different from other generative models, in our model, the tag generation process is separated from the content term generation process. while content terms are only generated from resource topics, social tags are generated by resource topics and user perspectives together. the proposed probabilistic model can produce more useful information than any other models proposed before. the parameters learned from this model include: (1) the topical distribution of each document, (2) the perspective distribution of each user, (3) the word distribution of each topic, (4) the tag distribution of each topic, (5) the tag distribution of each user perspective, (6) and the probabilistic of each tag being generated from resource topics or user perspectives. experimental results show that the proposed model has better generalization performance or tag prediction ability than other two models proposed in previous research.
balanced allocation with succinct representation. motivated by applications in guaranteed delivery in computational advertising, we consider the general problem of balanced allocation in a bipartite supply-demand setting. our formulation captures the notion of deviation from being balanced by a convex penalty function. while this formulation admits a convex programming solution, we strive for more robust and scalable algorithms. for the case of l1 penalty functions we obtain a simple combinatorial algorithm based on min-cost flow in graphs and show how to precompute a linear amount of information such that the allocation along any edge can be approximated in constant time. we then extend our combinatorial solution to any convex function by solving a convex cost flow. these scalable methods may have applications in other contexts stipulating balanced allocation. we study the performance of our algorithms on large real-world graphs and show that they are efficient, scalable, and robust in practice.
feature selection for support vector regression using probabilistic prediction. this paper presents a novel wrapper-based feature selection method for support vector regression (svr) using its probabilistic predictions. the method computes the importance of a feature by aggregating the difference, over the feature space, of the conditional density functions of the svr prediction with and without the feature. as the exact computation of this importance measure is expensive, two approximations are proposed. the effectiveness of the measure using these approximations, in comparison to several other existing feature selection methods for svr, is evaluated on both artificial and real-world problems. the result of the experiment shows that the proposed method generally performs better, and at least as well as the existing methods, with notable advantage when the data set is sparse.
transfer metric learning by learning task relationships. distance metric learning plays a very crucial role in many data mining algorithms because the performance of an algorithm relies heavily on choosing a good metric. however, the labeled data available in many applications is scarce and hence the metrics learned are often unsatisfactory. in this paper, we consider a transfer learning setting in which some related source tasks with labeled data are available to help the learning of the target task. we first propose a convex formulation for multi-task metric learning by modeling the task relationships in the form of a task covariance matrix. then we regard transfer learning as a special case of multi-task learning and adapt the formulation of multi-task metric learning to the transfer learning setting for our method, called transfer metric learning (tml). in tml, we learn the metric and the task covariances between the source tasks and the target task under a unified convex formulation. to solve the convex optimization problem, we use an alternating method in which each subproblem has an efficient solution. experimental results on some commonly used transfer learning applications demonstrate the effectiveness of our method.
semi-supervised sparse metric learning using alternating linearization optimization. in plenty of scenarios, data can be represented as vectors and then mathematically abstracted as points in a euclidean space. because a great number of machine learning and data mining applications need proximity measures over data, a simple and universal distance metric is desirable, and metric learning methods have been explored to produce sensible distance measures consistent with data relationship. however, most existing methods suffer from limited labeled data and expensive training. in this paper, we address these two issues through employing abundant unlabeled data and pursuing sparsity of metrics, resulting in a novel metric learning approach called semi-supervised sparse metric learning. two important contributions of our approach are: 1) it propagates scarce prior affinities between data to the global scope and incorporates the full affinities into the metric learning; and 2) it uses an efficient alternating linearization method to directly optimize the sparse metric. compared with conventional methods, ours can effectively take advantage of semi-supervision and automatically discover the sparse metric structure underlying input data patterns. we demonstrate the efficacy of the proposed approach with extensive experiments carried out on six datasets, obtaining clear performance gains over the state-of-the-arts.
frequent regular itemset mining. concise representations of frequent itemsets sacrifice readability and direct interpretability by a data analyst of the concise patterns extracted. in this paper, we introduce an extension of itemsets, called regular, with an immediate semantics and interpretability, and a conciseness comparable to closed itemsets. regular itemsets allow for specifying that an item may or may not be present; that any subset of an itemset may be present; and that any non-empty subset of an itemset may be present. we devise a procedure, called regularmine, for mining a set of regular itemsets that is a concise representation of frequent itemsets. the procedure computes a covering, in terms of regular itemsets, of the frequent itemsets in the class of equivalence of a closed one. we report experimental results on several standard dense and sparse datasets that validate the proposed approach.
extracting temporal signatures for comprehending systems biology models. systems biology has made massive strides in recent years, with capabilities to model complex systems including cell division, stress response, energy metabolism, and signaling pathways. concomitant with their improved modeling capabilities, however, such biochemical network models have also become notoriously complex for humans to comprehend. we propose network comprehension as a key problem for the kdd community, where the goal is to create explainable representations of complex biological networks. we formulate this problem as one of extracting temporal signatures from multi-variate time series data, where the signatures are composed of ordinal comparisons between time series components. we show how such signatures can be inferred by formulating the data mining problem as one of feature selection in rank-order space. we propose five new feature selection strategies for rank-order space and assess their selective superiorities. experimental results on budding yeast cell cycle models demonstrate compelling results comparable to human interpretations of the cell cycle.
medical coding classification by leveraging inter-code relationships. medical coding or classification is the process of transforming information contained in patient medical records into standard predefined medical codes. there are several worldwide accepted medical coding conventions associated with diagnoses and medical procedures; however, in the united states the ninth revision of icd(icd-9) provides the standard for coding clinical records. accurate medical coding is important since it is used by hospitals for insurance billing purposes. since after discharge a patient can be assigned or classified to several icd-9 codes, the coding problem can be seen as a multi-label classification problem. in this paper, we introduce a multi-label large-margin classifier that automatically learns the underlying inter-code structure and allows the controlled incorporation of prior knowledge about medical code relationships. in addition to refining and learning the code relationships, our classifier can also utilize this shared information to improve its performance. experiments on a publicly available dataset containing clinical free text and their associated medical codes showed that our proposed multi-label classifier outperforms related multi-label models in this problem.
clustering by synchronization. synchronization is a powerful basic concept in nature regulating a large variety of complex processes ranging from the metabolism in the cell to social behavior in groups of individuals. therefore, synchronization phenomena have been extensively studied and models robustly capturing the dynamical synchronization process have been proposed, e.g. the extensive kuramoto model. inspired by the powerful concept of synchronization, we propose sync, a novel approach to clustering. the basic idea is to view each data object as a phase oscillator and simulate the interaction behavior of the objects over time. as time evolves, similar objects naturally synchronize together and form distinct clusters. inherited from synchronization, sync has several desirable properties: the clusters revealed by dynamic synchronization truly reflect the intrinsic structure of the data set, sync does not rely on any distribution assumption and allows detecting clusters of arbitrary number, shape and size. moreover, the concept of synchronization allows natural outlier handling, since outliers do not synchronize with cluster objects. for fully automatic clustering, we propose to combine sync with the minimum description length principle. extensive experiments on synthetic and real world data demonstrate the effectiveness and efficiency of our approach.
temporal recommendation on graphs via long- and short-term preference fusion. accurately capturing user preferences over time is a great practical challenge in recommender systems. simple correlation over time is typically not meaningful, since users change their preferences due to different external events. user behavior can often be determined by individual's long-term and short-term preferences. how to represent users' long-term and short-term preferences? how to leverage them for temporal recommendation? to address these challenges, we propose session-based temporal graph (stg) which simultaneously models users' long-term and short-term preferences over time. based on the stg model framework, we propose a novel recommendation algorithm injected preference fusion (ipf) and extend the personalized random walk for temporal recommendation. finally, we evaluate the effectiveness of our method using two real datasets on citations and social bookmarking, in which our proposed method ipf gives 15%-34% improvement over the previous state-of-the-art.
probably the best itemsets. one of the main current challenges in itemset mining is to discover a small set of high-quality itemsets. in this paper we propose a new and general approach for measuring the quality of itemsets. the method is solidly founded in bayesian statistics and decreases monotonically, allowing for efficient discovery of all interesting itemsets. the measure is defined by connecting statistical models and collections of itemsets. this allows us to score individual itemsets with the probability of them occuring in random models built on the data. as a concrete example of this framework we use exponential models. this class of models possesses many desirable properties. most importantly, occam's razor in bayesian model selection provides a defence for the pattern explosion. as general exponential models are infeasible in practice, we use decomposable models; a large sub-class for which the measure is solvable. for the actual computation of the score we sample models from the posterior distribution using an mcmc approach. experimentation on our method demonstrates the measure works in practice and results in interpretable and insightful itemsets for both synthetic and real-world data.
tiara: a visual exploratory text analytic system. in this paper, we present a novel exploratory visual analytic system called tiara (text insight via automated responsive analytics), which combines text analytics and interactive visualization to help users explore and analyze large collections of text. given a collection of documents, tiara first uses topic analysis techniques to summarize the documents into a set of topics, each of which is represented by a set of keywords. in addition to extracting topics, tiara derives time-sensitive keywords to depict the content evolution of each topic over time. to help users understand the topic-based summarization results, tiara employs several interactive text visualization techniques to explain the summarization results and seamlessly link such results to the original text. we have applied tiara to several real-world applications, including email summarization and patient record analysis. to measure the effectiveness of tiara, we have conducted several experiments. our experimental results and initial user feedback suggest that tiara is effective in aiding users in their exploratory text analytic tasks.
growing a tree in the forest: constructing folksonomies by integrating structured metadata. many social web sites allow users to annotate the content with descriptive metadata, such as tags, and more recently to organize content hierarchically. these types of structured metadata provide valuable evidence for learning how a community organizes knowledge. for instance, we can aggregate many personal hierarchies into a common taxonomy, also known as a folksonomy, that will aid users in visualizing and browsing social content, and also to help them in organizing their own content. however, learning from social metadata presents several challenges, since it is sparse, shallow, ambiguous, noisy, and inconsistent. we describe an approach to folksonomy learning based on relational clustering, which exploits structured metadata contained in personal hierarchies. our approach clusters similar hierarchies using their structure and tag statistics, then incrementally weaves them into a deeper, bushier tree. we study folksonomy learning using social metadata extracted from the photo-sharing site flickr, and demonstrate that the proposed approach addresses the challenges. moreover, comparing to previous work, the approach produces larger, more accurate folksonomies, and in addition, scales better.
using data mining techniques to address critical information exchange needs in disaster affected public-private networks. crisis management and disaster recovery have gained immense importance in the wake of recent man and nature inflicted calamities. a critical problem in a crisis situation is how to efficiently discover, collect, organize, search and disseminate real-time disaster information. in this paper, we address several key problems which inhibit better information sharing and collaboration between both private and public sector participants for disaster management and recovery. we design and implement a web based prototype implementation of a business continuity information network (bcin) system utilizing the latest advances in data mining technologies to create a user-friendly, internet-based, information-rich service and acting as a vital part of a company's business continuity process. specifically, information extraction is used to integrate the input data from different sources; the content recommendation engine and the report summarization module provide users personalized and brief views of the disaster information; the community generation module develops spatial clustering techniques to help users build dynamic community in disasters. currently, bcin has been exercised at miami-dade county emergency management.
class-specific error bounds for ensemble classifiers. the generalization error, or probability of misclassification, of ensemble classifiers has been shown to be bounded above by a function of the mean correlation between the constituent (i.e., base) classifiers and their average strength. this bound suggests that increasing the strength and/or decreasing the correlation of an ensemble's base classifiers may yield improved performance under the assumption of equal error costs. however, this and other existing bounds do not directly address application spaces in which error costs are inherently unequal. for applications involving binary classification, receiver operating characteristic (roc) curves, performance curves that explicitly trade off false alarms and missed detections, are often utilized to support decision making. to address performance optimization in this context, we have developed a lower bound for the entire roc curve that can be expressed in terms of the class-specific strength and correlation of the base classifiers. we present empirical analyses demonstrating the efficacy of these bounds in predicting relative classifier performance. in addition, we specify performance regions of the roc curve that are naturally delineated by the class-specific strengths of the base classifiers and show that each of these regions can be associated with a unique set of guidelines for performance optimization of binary classifiers within unequal error cost regimes.
boosting with structure information in the functional space: an application to graph classification. boosting is a very successful classification algorithm that produces a linear combination of "weak" classifiers (a.k.a. base learners) to obtain high quality classification models. in this paper we propose a new boosting algorithm where base learners have structure relationships in the functional space. though such relationships are generic, our work is particularly motivated by the emerging topic of pattern based classification for semi-structured data including graphs. towards an efficient incorporation of the structure information, we have designed a general model where we use an undirected graph to capture the relationship of subgraph-based base learners. in our method, we combine both l1 norm and laplacian based l2 norm penalty with logit loss function of logit boost. in this approach, we enforce model sparsity and smoothness in the functional space spanned by the basis functions. we have derived efficient optimization algorithms based on coordinate decent for the new boosting formulation and theoretically prove that it exhibits a natural grouping effect for nearby spatial or overlapping features. using comprehensive experimental study, we have demonstrated the effectiveness of the proposed learning methods.
inferring networks of diffusion and influence. information diffusion and virus propagation are fundamental processes talking place in networks. while it is often possible to directly observe when nodes become infected, observing individual transmissions (i.e., who infects whom or who influences whom) is typically very difficult. furthermore, in many applications, the underlying network over which the diffusions and propagations spread is actually unobserved. we tackle these challenges by developing a method for tracing paths of diffusion and influence through networks and inferring the networks over which contagions propagate. given the times when nodes adopt pieces of information or become infected, we identify the optimal network that best explains the observed infection times. since the optimization problem is np-hard to solve exactly, we develop an efficient approximation algorithm that scales to large datasets and in practice gives provably near-optimal performance. we demonstrate the effectiveness of our approach by tracing information cascades in a set of 170 million blogs and news articles over a one year period to infer how information flows through the online media space. we find that the diffusion network of news tends to have a core-periphery structure with a small set of core media sites that diffuse information to the rest of the web. these sites tend to have stable circles of influence with more general news media sites acting as connectors between them.
grafting-light: fast, incremental feature selection and structure learning of markov random fields. feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of markov random fields (mrfs) can automatically discover the inherent structures underlying complex data. both problems can be cast as solving an l1-norm regularized parameter estimation problem. the existing grafting method can avoid doing inference on dense graphs in structure learning by incrementally selecting new features. however, grafting performs a greedy step to optimize over free parameters once new features are included. this greedy strategy results in low efficiency when parameter learning is itself non-trivial, such as in mrfs, in which parameter learning depends on an expensive subroutine to calculate gradients. the complexity of calculating gradients in mrfs is typically exponential to the size of maximal cliques. in this paper, we present a fast algorithm called grafting-light to solve the l1-norm regularized maximum likelihood estimation of mrfs for efficient feature selection and structure learning. grafting-light iteratively performs one-step of orthant-wise gradient descent over free parameters and selects new features. this lazy strategy is guaranteed to converge to the global optimum and can effectively select significant features. on both synthetic and real data sets, we show that grafting-light is much more efficient than grafting for both feature selection and structure learning, and performs comparably with the optimal batch method that directly optimizes over all the features for feature selection but is much more efficient and accurate for structure learning of mrfs.
metric forensics: a multi-level approach for mining volatile graphs. advances in data collection and storage capacity have made it increasingly possible to collect highly volatile graph data for analysis. existing graph analysis techniques are not appropriate for such data, especially in cases where streaming or near-real-time results are required. an example that has drawn significant research interest is the cyber-security domain, where internet communication traces are collected and real-time discovery of events, behaviors, patterns, and anomalies is desired. we propose metricforensics, a scalable framework for analysis of volatile graphs. metricforensics combines a multi-level "drill down" approach, a collection of user-selected graph metrics, and a collection of analysis techniques. at each successive level, more sophisticated metrics are computed and the graph is viewed at finer temporal resolutions. in this way, metricforensics scales to highly volatile graphs by only allocating resources for computationally expensive analysis when an interesting event is discovered at a coarser resolution first. we test metricforensics on three real-world graphs: an enterprise ip trace, a trace of legitimate and malicious network traffic from a research institution, and the mit reality mining proximity sensor data. our largest graph has 3m vertices and 32m edges, spanning 4.5 days. the results demonstrate the scalability and capability of metricforensics in analyzing volatile graphs; and highlight four novel phenomena in such graphs: elbows, broken correlations, prolonged spikes, and lightweight stars.
semi-supervised feature selection for graph classification. the problem of graph classification has attracted great interest in the last decade. current research on graph classification assumes the existence of large amounts of labeled training graphs. however, in many applications, the labels of graph data are very expensive or difficult to obtain, while there are often copious amounts of unlabeled graph data available. in this paper, we study the problem of semi-supervised feature selection for graph classification and propose a novel solution, called gssc, to efficiently search for optimal subgraph features with labeled and unlabeled graphs. different from existing feature selection methods in vector spaces which assume the feature set is given, we perform semi-supervised feature selection for graph data in a progressive way together with the subgraph feature mining process. we derive a feature evaluation criterion, named gsemi, to estimate the usefulness of subgraph features based upon both labeled and unlabeled graphs. then we propose a branch-and-bound algorithm to efficiently search for optimal subgraph features by judiciously pruning the subgraph search space. empirical studies on several real-world tasks demonstrate that our semi-supervised feature selection approach can effectively boost graph classification performances with semi-supervised feature selection and is very efficient by pruning the subgraph search space using both labeled and unlabeled graphs.
estimating rates of rare events with multiple hierarchies through scalable log-linear models. we consider the problem of estimating rates of rare events for high dimensional, multivariate categorical data where several dimensions are hierarchical. such problems are routine in several data mining applications including computational advertising, our main focus in this paper. we propose lmmh, a novel log-linear modeling method that scales to massive data applications with billions of training records and several million potential predictors in a map-reduce framework. our method exploits correlations in aggregates observed at multiple resolutions when working with multiple hierarchies; stable estimates at coarser resolution provide informative prior information to improve estimates at finer resolutions. other than prediction accuracy and scalability, our method has an inbuilt variable screening procedure based on a "spike and slab prior" that provides parsimony by removing non-informative predictors without hurting predictive accuracy. we perform large scale experiments on data from real computational advertising applications and illustrate our approach on datasets with several billion records and hundreds of millions of predictors. extensive comparisons with other benchmark methods show significant improvements in prediction accuracy.
towards mobility-based clustering. identifying hot spots of moving vehicles in an urban area is essential to many smart city applications. the practical research on hot spots in smart city presents many unique features, such as highly mobile environments, supremely limited size of sample objects, and the non-uniform, biased samples. all these features have raised new challenges that make the traditional density-based clustering algorithms fail to capture the real clustering property of objects, making the results less meaningful. in this paper we propose a novel, non-density-based approach called mobility-based clustering. the key idea is that sample objects are employed as "sensors" to perceive the vehicle crowdedness in nearby areas using their instant mobility, rather than the "object representatives". as such the mobility of samples is naturally incorporated. several key factors beyond the vehicle crowdedness have been identified and techniques to compensate these effects are proposed. we evaluate the performance of mobility-based clustering based on real traffic situations. experimental results show that using 0.3% of vehicles as the samples, mobility-based clustering can accurately identify hot spots which can hardly be obtained by the latest representative algorithm umicro.
connecting the dots between news articles. the process of extracting useful knowledge from large datasets has become one of the most pressing problems in today's society. the problem spans entire sectors, from scientists to intelligence analysts and web users, all of whom are constantly struggling to keep up with the larger and larger amounts of content published every day. with this much data, it is often easy to miss the big picture. in this paper, we investigate methods for automatically connecting the dots -- providing a structured, easy way to navigate within a new topic and discover hidden connections. we focus on the news domain: given two news articles, our system automatically finds a coherent chain linking them together. for example, it can recover the chain of events starting with the decline of home prices (january 2007), and ending with the ongoing health-care debate. we formalize the characteristics of a good chain and provide an efficient algorithm (with theoretical guarantees) to connect two fixed endpoints. we incorporate user feedback into our framework, allowing the stories to be refined and personalized. finally, we evaluate our algorithm over real news data. our user studies demonstrate the algorithm's effectiveness in helping users understanding the news.
tropical cyclone event sequence similarity search via dimensionality reduction and metric learning. the earth observing system data and information system (eosdis) is a comprehensive data and information system which archives, manages, and distributes earth science data from the eos spacecrafts. one non-existent capability in the eosdis is the retrieval of satellite sensor data based on weather events (such as tropical cyclones) similarity query output. in this paper, we propose a framework to solve the similarity search problem given user-defined instance-level constraints for tropical cyclone events, represented by arbitrary length multidimensional spatio-temporal data sequences. a critical component for such a problem is the similarity/metric function to compare the data sequences. we describe a novel longest common subsequence (lcss) parameter learning approach driven by nonlinear dimensionality reduction and distance metric learning. intuitively, arbitrary length multidimensional data sequences are projected into a fixed dimensional manifold for lcss parameter learning. similarity search is achieved through consensus among the (similar) instance-level constraints based on ranking orders computed using the lcss-based similarity measure. experimental results using a combination of synthetic and real tropical cyclone event data sequences are presented to demonstrate the feasibility of our parameter learning approach and its robustness to variability in the instance constraints. we, then, use a similarity query example on real tropical cyclone event data sequences from 2000 to 2008 to discuss (i) a problem of scientific interest, and (ii) challenges and issues related to the weather event similarity search problem.
finding effectors in social networks. assume a network (v,e) where a subset of the nodes in v are active. we consider the problem of selecting a set of k active nodes that best explain the observed activation state, under a given information-propagation model. we call these nodes effectors. we formally define the k-effectors problem and study its complexity for different types of graphs. we show that for arbitrary graphs the problem is not only np-hard to solve optimally, but also np-hard to approximate. we also show that, for some special cases, the problem can be solved optimally in polynomial time using a dynamic-programming algorithm. to the best of our knowledge, this is the first work to consider the k-effectors problem in networks. we experimentally evaluate our algorithms using the dblp co-authorship graph, where we search for effectors of topics that appear in research papers.
document clustering via dirichlet process mixture model with feature selection. one essential issue of document clustering is to estimate the appropriate number of clusters for a document collection to which documents should be partitioned. in this paper, we propose a novel approach, namely dpmfs, to address this issue. the proposed approach is designed 1) to group documents into a set of clusters while the number of document clusters is determined by the dirichlet process mixture model automatically; 2) to identify the discriminative words and separate them from irrelevant noise words via stochastic search variable selection technique. we explore the performance of our proposed approach on both a synthetic dataset and several realistic document datasets. the comparison between our proposed approach and stage-of-the-art document clustering approaches indicates that our approach is robust and effective for document clustering.
privacy-preserving outsourcing support vector machines with random transformation. outsourcing the training of support vector machines (svm) to external service providers benefits the data owner who is not familiar with the techniques of the svm or has limited computing resources. in outsourcing, the data privacy is a critical issue for some legal or commercial reasons since there may be sensitive information contained in the data. existing privacy-preserving svm works are either not applicable to outsourcing or weak in security. in this paper, we propose a scheme for privacy-preserving outsourcing the training of the svm without disclosing the actual content of the data to the service provider. in the proposed scheme, the data sent to the service provider is perturbed by a random transformation, and the service provider trains the svm for the data owner from the perturbed data. the proposed scheme is stronger in security than existing techniques, and incurs very little redundant communication and computation cost.
beyond heuristics: learning to classify vulnerabilities and predict exploits. the security demands on modern system administration are enormous and getting worse. chief among these demands, administrators must monitor the continual ongoing disclosure of software vulnerabilities that have the potential to compromise their systems in some way. such vulnerabilities include buffer overflow errors, improperly validated inputs, and other unanticipated attack modalities. in 2008, over 7,400 new vulnerabilities were disclosed--well over 100 per week. while no enterprise is affected by all of these disclosures, administrators commonly face many outstanding vulnerabilities across the software systems they manage. vulnerabilities can be addressed by patches, reconfigurations, and other workarounds; however, these actions may incur down-time or unforeseen side-effects. thus, a key question for systems administrators is which vulnerabilities to prioritize. from publicly available databases that document past vulnerabilities, we show how to train classifiers that predict whether and how soon a vulnerability is likely to be exploited. as input, our classifiers operate on high dimensional feature vectors that we extract from the text fields, time stamps, cross references, and other entries in existing vulnerability disclosure reports. compared to current industry-standard heuristics based on expert knowledge and static formulas, our classifiers predict much more accurately whether and how soon individual vulnerabilities are likely to be exploited.
up-growth: an efficient algorithm for high utility itemset mining. mining high utility itemsets from a transactional database refers to the discovery of itemsets with high utility like profits. although a number of relevant approaches have been proposed in recent years, they incur the problem of producing a large number of candidate itemsets for high utility itemsets. such a large number of candidate itemsets degrades the mining performance in terms of execution time and space requirement. the situation may become worse when the database contains lots of long transactions or long high utility itemsets. in this paper, we propose an efficient algorithm, namely up-growth (utility pattern growth), for mining high utility itemsets with a set of techniques for pruning candidate itemsets. the information of high utility itemsets is maintained in a special data structure named up-tree (utility pattern tree) such that the candidate itemsets can be generated efficiently with only two scans of the database. the performance of up-growth was evaluated in comparison with the state-of-the-art algorithms on different types of datasets. the experimental results show that up-growth not only reduces the number of candidates effectively but also outperforms other algorithms substantially in terms of execution time, especially when the database contains lots of long transactions.
flexible constrained spectral clustering. constrained clustering has been well-studied for algorithms like k-means and hierarchical agglomerative clustering. however, how to encode constraints into spectral clustering remains a developing area. in this paper, we propose a flexible and generalized framework for constrained spectral clustering. in contrast to some previous efforts that implicitly encode must-link and cannot-link constraints by modifying the graph laplacian or the resultant eigenspace, we present a more natural and principled formulation, which preserves the original graph laplacian and explicitly encodes the constraints. our method offers several practical advantages: it can encode the degree of belief (weight) in must-link and cannot-link constraints; it guarantees to lower-bound how well the given constraints are satisfied using a user-specified threshold; and it can be solved deterministically in polynomial time through generalized eigendecomposition. furthermore, by inheriting the objective function from spectral clustering and explicitly encoding the constraints, much of the existing analysis of spectral clustering techniques is still valid. consequently our work can be posed as a natural extension to unconstrained spectral clustering and be interpreted as finding the normalized min-cut of a labeled graph. we validate the effectiveness of our approach by empirical results on real-world data sets, with applications to constrained image segmentation and clustering benchmark data sets with both binary and degree-of-belief constraints.
gls-sod: a generalized local statistical approach for spatial outlier detection. local based approach is a major category of methods for spatial outlier detection (sod). currently, there is a lack of systematic analysis on the statistical properties of this framework. for example, most methods assume identical and independent normal distributions (i.i.d. normal) for the calculated local differences, but no justifications for this critical assumption have been presented. the methods' detection performance on geostatistic data with linear or nonlinear trend is also not well studied. in addition, there is a lack of theoretical connections and empirical comparisons between local and global based sod approaches. this paper discusses all these fundamental issues under the proposed generalized local statistical (gls) framework. furthermore, robust estimation and outlier detection methods are designed for the new gls model. extensive simulations demonstrated that the sod method based on the gls model significantly outperformed all existing approaches when the spatial data exhibits a linear or nonlinear trend.
divrank: the interplay of prestige and diversity in information networks. information networks are widely used to characterize the relationships between data items such as text documents. many important retrieval and mining tasks rely on ranking the data items based on their centrality or prestige in the network. beyond prestige, diversity has been recognized as a crucial objective in ranking, aiming at providing a non-redundant and high coverage piece of information in the top ranked results. nevertheless, existing network-based ranking approaches either disregard the concern of diversity, or handle it with non-optimized heuristics, usually based on greedy vertex selection. we propose a novel ranking algorithm, divrank, based on a reinforced random walk in an information network. this model automatically balances the prestige and the diversity of the top ranked vertices in a principled way. divrank not only has a clear optimization explanation, but also well connects to classical models in mathematics and network science. we evaluate divrank using empirical experiments on three different networks as well as a text summarization task. divrank outperforms existing network-based ranking methods in terms of enhancing diversity in prestige.
mass estimation and its applications. this paper introduces mass estimation--a base modelling mechanism in data mining. it provides the theoretical basis of mass and an efficient method to estimate mass. we show that it solves problems very effectively in tasks such as information retrieval, regression and anomaly detection. the models, which use mass in these three tasks, perform at least as good as and often better than a total of eight state-of-the-art methods in terms of task-specific performance measures. in addition, mass estimation has constant time and space complexities.
unsupervised transfer classification: application to text categorization. we study the problem of building the classification model for a target class in the absence of any labeled training example for that class. to address this difficult learning problem, we extend the idea of transfer learning by assuming that the following side information is available: (i) a collection of labeled examples belonging to other classes in the problem domain, called the auxiliary classes; (ii) the class information including the prior of the target class and the correlation between the target class and the auxiliary classes. our goal is to construct the classification model for the target class by leveraging the above data and information. we refer to this learning problem as unsupervised transfer classification. our framework is based on the generalized maximum entropy model that is effective in transferring the label information of the auxiliary classes to the target class. a theoretical analysis shows that under certain assumption, the classification model obtained by the proposed approach converges to the optimal model when it is learned from the labeled examples for the target class. empirical study on text categorization over four different data sets verifies the effectiveness of the proposed approach.
parallel simrank computation on large graphs with iterative aggregation. recently there has been a lot of interest in graph-based analysis. one of the most important aspects of graph-based analysis is to measure similarity between nodes in a graph. simrank is a simple and influential measure of this kind, based on a solid graph theoretical model. however, existing methods on simrank computation suffer from two limitations: 1) the computing cost can be very high in practice; and 2) they can only be applied on static graphs. in this paper, we exploit the inherent parallelism and high memory bandwidth of graphics processing units (gpu) to accelerate the computation of simrank on large graphs. furthermore, based on the observation that simrank is essentially a first-order markov chain, we propose to utilize the iterative aggregation techniques for uncoupling markov chains to compute simrank scores in parallel for large graphs. the iterative aggregation method can be applied on dynamic graphs. moreover, it can handle not only the link-updating problem but also the node-updating problem. extensive experiments on synthetic and real data sets verify that the proposed methods are efficient and effective.
detecting abnormal coupled sequences and sequence changes in group-based manipulative trading behaviors. in capital market surveillance, an emerging trend is that a group of hidden manipulators collaborate with each other to manipulate three trading sequences: buy-orders, sell-orders and trades, through carefully arranging their prices, volumes and time, in order to mislead other investors, affect the instrument movement, and thus maximize personal benefits. if the focus is on only one of the above three sequences in attempting to analyze such hidden group based behavior, or if they are merged into one sequence as per an investor, the coupling relationships among them indicated through trading actions and their prices/volumes/times would be missing, and the resulting findings would have a high probability of mismatching the genuine fact in business. therefore, typical sequence analysis approaches, which mainly identify patterns on a single sequence, cannot be used here. this paper addresses a novel topic, namely coupled behavior analysis in hidden groups. in particular, we propose a coupled hidden markov models (hmm)-based approach to detect abnormal group-based trading behaviors. the resulting models cater for (1) multiple sequences from a group of people, (2) interactions among them, (3) sequence item properties, and (4) significant change among coupled sequences. we demonstrate our approach in detecting abnormal manipulative trading behaviors on orderbook-level stock data. the results are evaluated against alerts generated by the exchange's surveillance system from both technical and computational perspectives. it shows that the proposed coupled and adaptive hmms outperform a standard hmm only modeling any single sequence, or the hmm combining multiple single sequences, without considering the coupling relationship. further work on coupled behavior analysis, including coupled sequence/event analysis, hidden group analysis and behavior dynamics are very critical.
mining top-k frequent items in a data stream with flexible sliding windows. we study the problem of finding the k most frequent items in a stream of items for the recently proposed max-frequency measure. based on the properties of an item, the max-frequency of an item is counted over a sliding window of which the length changes dynamically. besides being parameterless, this way of measuring the support of items was shown to have the advantage of a faster detection of bursts in a stream, especially if the set of items is heterogeneous. the algorithm that was proposed for maintaining all frequent items, however, scales poorly when the number of items becomes large. therefore, in this paper we propose, instead of reporting all frequent items, to only mine the top-k most frequent ones. first we prove that in order to solve this problem exactly, we still need a prohibitive amount of memory (at least linear in the number of items). yet, under some reasonable conditions, we show both theoretically and empirically that a memory-efficient algorithm exists. a prototype of this algorithm is implemented and we present its performance w.r.t. memory-efficiency on real-life data and in controlled experiments with synthetic data.
topic dynamics: an alternative model of bursts in streams of topics. for some time there has been increasing interest in the problem of monitoring the occurrence of topics in a stream of events, such as a stream of news articles. this has led to different models of bursts in these streams, i.e., periods of elevated occurrence of events. today there are several burst definitions and detection algorithms, and their differences can produce very different results in topic streams. these definitions also share a fundamental problem: they define bursts in terms of an arrival rate. this approach is limiting; other stream dimensions can matter. we reconsider the idea of bursts from the standpoint of a simple kind of physics. instead of focusing on arrival rates, we reconstruct bursts as a dynamic phenomenon, using kinetics concepts from physics -- mass and velocity -- and derive momentum, acceleration, and force from these. we refer to the result as topic dynamics, permitting a hierarchical, expressive model of bursts as intervals of increasing momentum. as a sample application, we present a topic dynamics model for the large pubmed/medline database of biomedical publications, using the mesh (medical subject heading) topic hierarchy. we show our model is able to detect bursts for mesh terms accurately as well as efficiently.
community-based greedy algorithm for mining top-k influential nodes in mobile social networks. with the proliferation of mobile devices and wireless technologies, mobile social network systems are increasingly available. a mobile social network plays an essential role as the spread of information and influence in the form of "word-of-mouth". it is a fundamental issue to find a subset of influential individuals in a mobile social network such that targeting them initially (e.g. to adopt a new product) will maximize the spread of the influence (further adoptions of the new product). the problem of finding the most influential nodes is unfortunately np-hard. it has been shown that a greedy algorithm with provable approximation guarantees can give good approximation; however, it is computationally expensive, if not prohibitive, to run the greedy algorithm on a large mobile network. in this paper we propose a new algorithm called community-based greedy algorithm for mining top-k influential nodes. the proposed algorithm encompasses two components: 1) an algorithm for detecting communities in a social network by taking into account information diffusion; and 2) a dynamic programming algorithm for selecting communities to find influential nodes. we also provide provable approximation guarantees for our algorithm. empirical studies on a large real-world mobile social network show that our algorithm is more than an order of magnitudes faster than the state-of-the-art greedy algorithm for finding top-k influential nodes and the error of our approximate algorithm is small.
data mining with differential privacy. we consider the problem of data mining with formal privacy guarantees, given a data access interface based on the differential privacy framework. differential privacy requires that computations be insensitive to changes in any particular individual's record, thereby restricting data leaks through the results. the privacy preserving interface ensures unconditionally safe access to the data and does not require from the data miner any expertise in privacy. however, as we show in the paper, a naive utilization of the interface to construct privacy preserving data mining algorithms could lead to inferior data mining results. we address this problem by considering the privacy and the algorithmic requirements simultaneously, focusing on decision tree induction as a sample application. the privacy mechanism has a profound effect on the performance of the methods chosen by the data miner. we demonstrate that this choice could make the difference between an accurate classifier and a completely useless one. moreover, an improved algorithm can achieve the same level of accuracy and privacy as the naive implementation but with an order of magnitude fewer learning samples.
discovery of significant emerging trends. we describe a system that monitors social and mainstream media to determine shifts in what people are thinking about a product or company. we process over 100,000 news articles, blog posts, review sites, and tweets a day for mentions of items (e.g., products) of interest, extract phrases that are mentioned near them, and determine which of the phrases are of greatest possible interest to, for example, brand managers. case studies show a good ability to rapidly pinpoint emerging subjects buried deep in large volumes of data and then highlight those that are rising or falling in significance as they relate to the firms interests. the tool and algorithm improves the signal-to-noise ratio and pinpoints precisely the opportunities and risks that matter most to communications professionals and their organizations.
mining advisor-advisee relationships from research publication networks. information network contains abundant knowledge about relationships among people or entities. unfortunately, such kind of knowledge is often hidden in a network where different kinds of relationships are not explicitly categorized. for example, in a research publication network, the advisor-advisee relationships among researchers are hidden in the coauthor network. discovery of those relationships can benefit many interesting applications such as expert finding and research community analysis. in this paper, we take a computer science bibliographic network as an example, to analyze the roles of authors and to discover the likely advisor-advisee relationships. in particular, we propose a time-constrained probabilistic factor graph model (tpfg), which takes a research publication network as input and models the advisor-advisee relationship mining problem using a jointly likelihood objective function. we further design an efficient learning algorithm to optimize the objective function. based on that our model suggests and ranks probable advisors for every author. experimental results show that the proposed approach infer advisor-advisee relationships efficiently and achieves a state-of-the-art accuracy (80-90%). we also apply the discovered advisor-advisee relationships to bole search, a specific expert finding task and empirical study shows that the search performance can be effectively improved (+4.09% by ndcg@5).
suggesting friends using the implicit social graph. although users of online communication tools rarely categorize their contacts into groups such as "family", "co-workers", or "jogging buddies", they nonetheless implicitly cluster contacts, by virtue of their interactions with them, forming implicit groups. in this paper, we describe the implicit social graph which is formed by users' interactions with contacts and groups of contacts, and which is distinct from explicit social graphs in which users explicitly add other individuals as their "friends". we introduce an interaction-based metric for estimating a user's affinity to his contacts and groups. we then describe a novel friend suggestion algorithm that uses a user's implicit social graph to generate a friend group, given a small seed set of contacts which the user has already labeled as friends. we show experimental results that demonstrate the importance of both implicit group relationships and interaction-based affinity ranking in suggesting friends. finally, we discuss two applications of the friend suggest algorithm that have been released as gmail labs features.
data winnowing. massive quantities of digital data are being collected in every aspect of modern life. examples include personal photos and videos, biological and medical images and recordings from sensor arrays. to transform these massive data streams into useful information we use a sequence of "winnowing" stages. each step reduces the size of the data by an order of magnitude; extracting the wheat form the chaff. in this talk i will describe this approach in a variety of contexts, ranging from the analysis of genetic pathways in fruit-fly embryos and c-elegans worms to counting birds and helping elderly people living alone keep in touch with their family and caregivers.
scalable similarity search with optimized kernel hashing. scalable similarity search is the core of many large scale learning or data mining applications. recently, many research results demonstrate that one promising approach is creating compact and efficient hash codes that preserve data similarity. by efficient, we refer to the low correlation (and thus low redundancy) among generated codes. however, most existing hash methods are designed only for vector data. in this paper, we develop a new hashing algorithm to create efficient codes for large scale data of general formats with any kernel function, including kernels on vectors, graphs, sequences, sets and so on. starting with the idea analogous to spectral hashing, novel formulations and solutions are proposed such that a kernel based hash function can be explicitly represented and optimized, and directly applied to compute compact hash codes for new samples of general formats. moreover, we incorporate efficient techniques, such as nystrom approximation, to further reduce time and space complexity for indexing and search, making our algorithm scalable to huge data sets. another important advantage of our method is the ability to handle diverse types of similarities according to actual task requirements, including both feature similarities and semantic similarities like label consistency. we evaluate our method using both vector and non-vector data sets at a large scale up to 1 million samples. our comprehensive results show the proposed method outperforms several state-of-the-art approaches for all the tasks, with a significant gain for most tasks.
scalable influence maximization for prevalent viral marketing in large-scale social networks. influence maximization, defined by kempe, kleinberg, and tardos (2003), is the problem of finding a small set of seed nodes in a social network that maximizes the spread of influence under certain influence cascade models. the scalability of influence maximization is a key factor for enabling prevalent viral marketing in large-scale online social networks. prior solutions, such as the greedy algorithm of kempe et al. (2003) and its improvements are slow and not scalable, while other heuristic algorithms do not provide consistently good performance on influence spreads. in this paper, we design a new heuristic algorithm that is easily scalable to millions of nodes and edges in our experiments. our algorithm has a simple tunable parameter for users to control the balance between the running time and the influence spread of the algorithm. our results from extensive simulations on several real-world and synthetic networks demonstrate that our algorithm is currently the best scalable solution to the influence maximization problem: (a) our algorithm scales beyond million-sized graphs where the greedy algorithm becomes infeasible, and (b) in all size ranges, our algorithm performs consistently well in influence spread --- it is always among the best algorithms, and in most cases it significantly outperforms all other scalable heuristics to as much as 100%--260% increase in influence spread.
overlapping experiment infrastructure: more, better, faster experimentation. at google, experimentation is practically a mantra; we evaluate almost every change that potentially affects what our users experience. such changes include not only obvious user-visible changes such as modifications to a user interface, but also more subtle changes such as different machine learning algorithms that might affect ranking or content selection. our insatiable appetite for experimentation has led us to tackle the problems of how to run more experiments, how to run experiments that produce better decisions, and how to run them faster. in this paper, we describe google's overlapping experiment infrastructure that is a key component to solving these problems. in addition, because an experiment infrastructure alone is insufficient, we also discuss the associated tools and educational processes required to use it effectively. we conclude by describing trends that show the success of this overall experimental environment. while the paper specifically describes the experiment system and experimental processes we have in place at google, we believe they can be generalized and applied by any entity interested in using experimentation to improve search engines and other web applications.
unsupervised feature selection for multi-cluster data. in many data analysis tasks, one is often confronted with very high dimensional data. feature selection techniques are designed to find the relevant feature subset of the original features which can facilitate clustering, classification and retrieval. in this paper, we consider the feature selection problem in unsupervised learning scenario, which is particularly difficult due to the absence of class labels that would guide the search for relevant information. the feature selection problem is essentially a combinatorial optimization problem which is computationally expensive. traditional unsupervised feature selection methods address this issue by selecting the top ranked features based on certain scores computed independently for each feature. these approaches neglect the possible correlation between different features and thus can not produce an optimal feature subset. inspired from the recent developments on manifold learning and l1-regularized models for subset selection, we propose in this paper a new approach, called multi-cluster feature selection (mcfs), for unsupervised feature selection. specifically, we select those features such that the multi-cluster structure of the data can be best preserved. the corresponding optimization problem can be efficiently solved since it only involves a sparse eigen-problem and a l1-regularized least squares problem. extensive experimental results over various real-life data sets have demonstrated the superiority of the proposed algorithm.
online discovery and maintenance of time series motifs. the detection of repeated subsequences, time series motifs, is a problem which has been shown to have great utility for several higher-level data mining algorithms, including classification, clustering, segmentation, forecasting, and rule discovery. in recent years there has been significant research effort spent on efficiently discovering these motifs in static offline databases. however, for many domains, the inherent streaming nature of time series demands online discovery and maintenance of time series motifs. in this paper, we develop the first online motif discovery algorithm which monitors and maintains motifs exactly in real time over the most recent history of a stream. our algorithm has a worst-case update time which is linear to the window size and is extendible to maintain more complex pattern structures. in contrast, the current offline algorithms either need significant update time or require very costly pre-processing steps which online algorithms simply cannot afford. our core ideas allow useful extensions of our algorithm to deal with arbitrary data rates and discovering multidimensional motifs. we demonstrate the utility of our algorithms with a variety of case studies in the domains of robotics, acoustic monitoring and online compression.
a hierarchical information theoretic technique for the discovery of non linear alternative clusterings. discovery of alternative clusterings is an important method for exploring complex datasets. it provides the capability for the user to view clustering behaviour from different perspectives and thus explore new hypotheses. however, current algorithms for alternative clustering have focused mainly on linear scenarios and may not perform as desired for datasets containing clusters with non linear shapes. our goal in this paper is to address this challenge of non linearity. in particular, we propose a novel algorithm to uncover an alternative clustering that is distinctively different from an existing, reference clustering. our technique is information theory based and aims to ensure alternative clustering quality by maximizing the mutual information between clustering labels and data observations, whilst at the same time ensuring alternative clustering distinctiveness by minimizing the information sharing between the two clusterings. we perform experiments to assess our method against a large range of alternative clustering algorithms in the literature. we show our technique's performance is generally better for non-linear scenarios and furthermore, is highly competitive even for simpler, linear scenarios.
the quantification of advertising: (+ lessons from building businesses based on large scale data mining). as electronic communication, media and commerce increasingly permeate every aspect of modern life, real-time personalization of consumer experience through data-mining becomes practical. effective classification, prediction and change modeling of consumer interests, behaviors and purchasing habits using machine learning and statistical methods drives efficiency, insights and consumer relevance that were never before possible. the internet has brought on a rapid evolution in advertising. everything about behavior on the internet can be quantified and responses to behavior can occur in real time. this dynamic interaction with the user has created opportunities to better understand the way in which individuals move from awareness of a product to considering a purchase, through to intent and ultimately a sale for the marketer. when a marketer can answer the question 'did those tv ads cause consumers to switch shampoo brands?' they can model behavior change and adjust marketing strategies accordingly. underpinning this shift in how the world's trillion dollar marketing budget is spent is transactional data on an unprecedented scale, creating new challenges for software that must interpret this stream and make real time decisions tens, even hundreds of thousands of times every second. i will explore advances in modeling media consumption, advertising response and the real-time evaluation of media opportunities through reference to quantcast, a business launched in september 2006 which today interprets in excess of 10 billion new digital media consumption records every day. we will examine the challenges of applying machine learning to non-search advertising and in doing so explore the creation of business environments - organization, infrastructure, tools, processes (and costs considerations) - in which scientists can quickly develop new petabyte scale algorithmic approaches, migrate them rapidly to real-time production and deliver fully customized experiences for marketers, publishers and consumers alike.
the new iris data: modular data generators. in this paper we introduce a modular, highly flexible, open-source environment for data generation. using an existing graphical data flow tool, the user can combine various types of modules for numeric and categorical data generators. additional functionality is added via the data processing framework in which the generator modules are embedded. the resulting data flows can be used to document, deploy, and reuse the resulting data generators. we describe the overall environment and individual modules and demonstrate how they can be used for the generation of a sample, complex customer/product database with corresponding shopping basket data, including various artifacts and outliers.
an efficient algorithm for a class of fused lasso problems. the fused lasso penalty enforces sparsity in both the coefficients and their successive differences, which is desirable for applications with features ordered in some meaningful way. the resulting problem is, however, challenging to solve, as the fused lasso penalty is both non-smooth and non-separable. existing algorithms have high computational complexity and do not scale to large-size problems. in this paper, we propose an efficient fused lasso algorithm (efla) for optimizing this class of problems. one key building block in the proposed efla is the fused lasso signal approximator (flsa). to efficiently solve flsa, we propose to reformulate it as the problem of finding an "appropriate" subgradient of the fused penalty at the minimizer, and develop a subgradient finding algorithm (sfa). we further design a restart technique to accelerate the convergence of sfa, by exploiting the special "structures" of both the original and the reformulated flsa problems. our empirical evaluations show that, both sfa and efla significantly outperform existing solvers. we also demonstrate several applications of the fused lasso.
mining positive and negative patterns for relevance feature discovery. it is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. most existing popular text mining and classification methods have adopted term-based approaches. however, they have all suffered from the problems of polysemy and synonymy. over the years, people have often held the hypothesis that pattern-based methods should perform better than term-based ones in describing user preferences, but many experiments do not support this hypothesis. the innovative technique presented in paper makes a breakthrough for this difficulty. this technique discovers both positive and negative patterns in text documents as higher level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the higher level features. substantial experiments using this technique on reuters corpus volume 1 and trec topics show that the proposed approach significantly outperforms both the state-of-the-art term-based methods underpinned by okapi bm25, rocchio or support vector machine and pattern based methods on precision, recall and f measures.
ensemble pruning via individual contribution ordering. an ensemble is a set of learned models that make decisions collectively. although an ensemble is usually more accurate than a single learner, existing ensemble methods often tend to construct unnecessarily large ensembles, which increases the memory consumption and computational cost. ensemble pruning tackles this problem by selecting a subset of ensemble members to form subensembles that are subject to less resource consumption and response time with accuracy that is similar to or better than the original ensemble. in this paper, we analyze the accuracy/diversity trade-off and prove that classifiers that are more accurate and make more predictions in the minority group are more important for subensemble construction. based on the gained insights, a heuristic metric that considers both accuracy and diversity is proposed to explicitly evaluate each individual classifier's contribution to the whole ensemble. by incorporating ensemble members in decreasing order of their contributions, subensembles are formed such that users can select the top $p$ percent of ensemble members, depending on their resource availability and tolerable waiting time, for predictions. experimental results on 26 uci data sets show that subensembles formed by the proposed epic (ensemble pruning via individual contribution ordering) algorithm outperform the original ensemble and a state-of-the-art ensemble pruning method, orientation ordering (oo).
learning with cost intervals. existing cost-sensitive learning methods require that the unequal misclassification costs should be given as precise values. in many real-world applications, however, it is generally difficult to have a precise cost value since the user maybe only knows that one type of mistake is much more severe than another type, yet it is infeasible to give a precise description. in such situations, it is more meaningful to work with a cost interval instead of a precise cost value. in this paper we report the first study along this direction. we propose the cisvm method, a support vector machine, to work with cost interval information. experiments show that when there are only cost intervals available, cisvm is significantly superior to standard cost-sensitive svms using any of the minimal cost, mean cost and maximal cost to learn. moreover, considering that in some cases other information about costs can be obtained in addition to cost intervals, such as the distribution of costs, we propose a general approach codis for using the distribution information to help improve performance. experiments show that this approach can reduce 60% more risks than the standard cost-sensitive svm which assumes the expected cost is the true value.
diagnosing memory leaks using graph mining on heap dumps. memory leaks are caused by software programs that prevent the reclamation of memory that is no longer in use. they can cause significant slowdowns, exhaustion of available storage space and, eventually, application crashes. detecting memory leaks is challenging because real-world applications are built on multiple layers of software frameworks, making it difficult for a developer to know whether observed references to objects are legitimate or the cause of a leak. we present a graph mining solution to this problem wherein we analyze heap dumps to automatically identify subgraphs which could represent potential memory leak sources. although heap dumps are commonly analyzed in existing heap profiling tools, our work is the first to apply a graph grammar mining solution to this problem. unlike classical graph mining work, we show that it suffices to mine the dominator tree of the heap dump, which is significantly smaller than the underlying graph. our approach identifies not just leaking candidates and their structure, but also provides aggregate information about the access path to the leaks. we demonstrate several synthetic as well as real-world examples of heap dumps for which our approach provides more insight into the problem than state-of-the-art tools such as eclipse's mat.
discovering significant relaxed order-preserving submatrices. mining order-preserving submatrix (opsm) patterns has received much attention from researchers, since in many scientific applications, such as those involving gene expression data, it is natural to express the data in a matrix and also important to find the order-preserving submatrix patterns. however, most current work assumes the noise-free opsm model and thus is not practical in many real situations when sample contamination exists. in this paper, we propose a relaxed opsm model called ropsm. the ropsm model supports mining more reasonable noise-corrupted opsm patterns than another well-known model called aopc (approximate order-preserving cluster). while opsm mining is known to be an np-hard problem, mining ropsm patterns is even a harder problem. we propose a novel method called ropsm-growth to mine ropsm patterns. specifically, two pattern growing strategies, such as column-centric strategy and row-centric strategy, are presented, which are effective to grow the seed opsms into significant ropsms. an effective median-rank based method is also developed to discover the underlying true order of conditions involved in an ropsm pattern. our experiments on a biological dataset show that the ropsm model better captures the characteristics of noise in gene expression data matrix compared to the aopc model. importantly, we find that our approach is able to detect more quality biologically significant patterns with comparable efficiency with the counterparts of aopc. specifically, at least 26.6% (75 out of 282) of the patterns mined by our approach are strongly associated with more than 10 gene categories (high biological significance), which is 3 times better than that obtained from using the aopc approach.
dust: a generalized notion of similarity between uncertain time series. large-scale sensor deployments and an increased use of privacy-preserving transformations have led to an increasing interest in mining uncertain time series data. traditional distance measures such as euclidean distance or dynamic time warping are not always effective for analyzing uncertain time series data. recently, some measures have been proposed to account for uncertainty in time series data. however, we show in this paper that their applicability is limited. in specific, these approaches do not provide an intuitive way to compare two uncertain time series and do not easily accommodate multiple error functions. in this paper, we provide a theoretical framework that generalizes the notion of similarity between uncertain time series. secondly, we propose dust, a novel distance measure that accommodates uncertainty and degenerates to the euclidean distance when the distance is large compared to the error. we provide an extensive experimental validation of our approach for the following applications: classification, top-k motif search, and top-k nearest-neighbor queries.
mining program workflow from interleaved traces. successful software maintenance is becoming increasingly critical due to the increasing dependence of our society and economy on software systems. one key problem of software maintenance is the difficulty in understanding the evolving software systems. program workflows can help system operators and administrators to understand system behaviors and verify system executions so as to greatly facilitate system maintenance. in this paper, we propose an algorithm to automatically discover program workflows from event traces that record system events during system execution. different from existing workflow mining algorithms, our approach can construct concurrent workflows from traces of interleaved events. our workflow mining approach is a three-step coarse-to-fine algorithm. at first, we mine temporal dependencies for each pair of events. then, based on the mined pair-wise tem-poral dependencies, we construct a basic workflow model by a breadth-first path pruning algorithm. after that, we refine the workflow by verifying it with all training event traces. the re-finement algorithm tries to find out a workflow that can interpret all event traces with minimal state transitions and threads. the results of both simulation data and real program data show that our algorithm is highly effective.
combined regression and ranking. many real-world data mining tasks require the achievement of two distinct goals when applied to unseen data: first, to induce an accurate preference ranking, and second to give good regression performance. in this paper, we give an efficient and effective combined regression and ranking method (crr) that optimizes regression and ranking objectives simultaneously. we demonstrate the effectiveness of crr for both families of metrics on a range of large-scale tasks, including click prediction for online advertisements. results show that crr often achieves performance equivalent to the best of both ranking-only and regression-only approaches. in the case of rare events or skewed distributions, we also find that this combination can actually improve regression performance due to the addition of informative ranking constraints.
an efficient causal discovery algorithm for linear models. bayesian network learning algorithms have been widely used for causal discovery since the pioneer work [13,18]. among all existing algorithms, three-phase dependency analysis algorithm (tpda) [5] is the most efficient one in the sense that it has polynomial-time complexity. however, there are still some limitations to be improved. first, tpda depends on mutual information-based conditional independence (ci) tests, and so is not easy to be applied to continuous data. in addition, tpda uses two phases to get approximate skeletons of bayesian networks, which is not efficient in practice. in this paper, we propose a two-phase algorithm with partial correlation-based ci tests: the first phase of the algorithm constructs a markov random field from data, which provides a close approximation to the structure of the true bayesian network; at the second phase, the algorithm removes redundant edges according to ci tests to get the true bayesian network. we show that two-phase algorithm with partial correlation-based ci tests can deal with continuous data following arbitrary distributions rather than only gaussian distribution.
on community outliers and their efficient detection in information networks. linked or networked data are ubiquitous in many applications. examples include web data or hypertext documents connected via hyperlinks, social networks or user profiles connected via friend links, co-authorship and citation information, blog data, movie reviews and so on. in these datasets (called "information networks"), closely related objects that share the same properties or interests form a community. for example, a community in blogsphere could be users mostly interested in cell phone reviews and news. outlier detection in information networks can reveal important anomalous and interesting behaviors that are not obvious if community information is ignored. an example could be a low-income person being friends with many rich people even though his income is not anomalously low when considered over the entire population. this paper first introduces the concept of community outliers (interesting points or rising stars for a more positive sense), and then shows that well-known baseline approaches without considering links or community information cannot find these community outliers. we propose an efficient solution by modeling networked data as a mixture model composed of multiple normal communities and a set of randomly generated outliers. the probabilistic model characterizes both data and links simultaneously by defining their joint distribution based on hidden markov random fields (hmrf). maximizing the data likelihood and the posterior of the model gives the solution to the outlier inference problem. we apply the model on both synthetic data and dblp data sets, and the results demonstrate importance of this concept, as well as the effectiveness and efficiency of the proposed approach.
data mining to predict and prevent errors in health insurance claims processing. health insurance costs across the world have increased alarmingly in recent years. a major cause of this increase are payment errors made by the insurance companies while processing claims. these errors often result in extra administrative effort to re-process (or rework) the claim which accounts for up to 30% of the administrative staff in a typical health insurer. we describe a system that helps reduce these errors using machine learning techniques by predicting claims that will need to be reworked, generating explanations to help the auditors correct these claims, and experiment with feature selection, concept drift, and active learning to collect feedback from the auditors to improve over time. we describe our framework, problem formulation, evaluation metrics, and experimental results on claims data from a large us health insurer. we show that our system results in an order of magnitude better precision (hit rate) over existing approaches which is accurate enough to potentially result in over $15-25 million in savings for a typical insurer. we also describe interesting research problems in this domain as well as design choices made to make the system easily deployable across health insurance companies.
evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora. mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. in this paper, we propose an approach called evolutionary hierarchical dirichlet processes (evohdp) to discover interesting cluster evolution patterns from such text data. we formulate the evohdp as a series of hierarchical dirichlet processes~(hdp) by adding time dependencies to the adjacent epochs, and propose a cascaded gibbs sampling scheme to infer the model. this approach can discover different evolving patterns of clusters, including emergence, disappearance, evolution within a corpus and across different corpora. experiments over synthetic and real-world multiple correlated time-varying data sets illustrate the effectiveness of evohdp on discovering cluster evolution patterns.
latent aspect rating analysis on review text data: a rating regression approach. in this paper, we define and study a new opinionated text data analysis problem called latent aspect rating analysis (lara), which aims at analyzing opinions expressed about an entity in an online review at the level of topical aspects to discover each individual reviewer's latent opinion on each aspect as well as the relative emphasis on different aspects when forming the overall judgment of the entity. we propose a novel probabilistic rating regression model to solve this new text mining problem in a general way. empirical experiments on a hotel review data set show that the proposed latent rating regression model can effectively solve the problem of lara, and that the detailed analysis of opinions at the level of topical aspects enabled by the proposed model can support a wide range of application tasks, such as aspect opinion summarization, entity ranking based on aspect ratings, and analysis of reviewers rating behavior.
multi-label learning by exploiting label dependency. in multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. due to the tremendous (exponential) number of possible label sets, the task of learning from multi-label examples is rather challenging. therefore, the key to successful multi-label learning is how to effectively exploit correlations between different labels to facilitate the learning process. in this paper, we propose to use a bayesian network structure to efficiently encode the conditional dependencies of the labels as well as the feature set, with the feature set as the common parent of all labels. to make it practical, we give an approximate yet efficient procedure to find such a network structure. with the help of this network, multi-label learning is decomposed into a series of single-label classification problems, where a classifier is constructed for each label by incorporating its parental labels as additional features. label sets of unseen examples are predicted recursively according to the label ordering given by the network. extensive experiments on a broad range of data sets validate the effectiveness of our approach against other well-established methods.
learning to combine discriminative classifiers: confidence based. much of research in data mining and machine learning has led to numerous practical applications. spam filtering, fraud detection, and user query-intent analysis has relied heavily on machine learned classifiers, and resulted in improvements in robust classification accuracy. combining multiple classifiers (a.k.a. ensemble learning) is a well studied and has been known to improve effectiveness of a classifier. to address two key challenges in ensemble learning-- (1) learning weights of individual classifiers and (2) the combination rule of their weighted responses, this paper proposes a novel ensemble classifier, enlr, that computes weights of responses from discriminative classifiers and combines their weighted responses to produce a single response for a test instance. the combination rule is based on aggregating weighted responses, where a weight of an individual classifier is inversely based on their respective variances around their responses. here, variance quantifies the uncertainty of the discriminative classifiers' parameters, which in turn depends on the training samples. as opposed to other ensemble methods where the weight of each individual classifier is learned as a part of parameter learning and thus the same weight is applied to all testing instances, our model is actively adjusted as individual classifiers become confident at its decision for a test instance. our empirical experiments on various data sets demonstrate that our combined classifier produces "effective" results when compared with a single classifier. our novel classifier shows statistically significant better accuracy when compared to well known ensemble methods -- bagging and adaboost. in addition to robust accuracy, our model is extremely efficient dealing with high volumes of training samples due to the independent learning paradigm among its multiple classifiers. it is simple to implement in a distributed computing environment such as hadoop.
training and testing of recommender systems on data missing not at random. users typically rate only a small fraction of all available items. we show that the absence of ratings carries useful information for improving the top-k hit rate concerning all items, a natural accuracy measure for recommendations. as to test recommender systems, we present two performance measures that can be estimated, under mild assumptions, without bias from data even when ratings are missing not at random (mnar). as to achieve optimal test results, we present appropriate surrogate objective functions for efficient training on mnar data. their main property is to account for all ratings - whether observed or missing in the data. concerning the top-k hit rate on test data, our experiments indicate dramatic improvements over even sophisticated methods that are optimized on observed ratings only.
fast online learning through offline initialization for time-sensitive recommendation. recommender problems with large and dynamic item pools are ubiquitous in web applications like content optimization, online advertising and web search. despite the availability of rich item meta-data, excess heterogeneity at the item level often requires inclusion of item-specific "factors" (or weights) in the model. however, since estimating item factors is computationally intensive, it poses a challenge for time-sensitive recommender problems where it is important to rapidly learn factors for new items (e.g., news articles, event updates, tweets) in an online fashion. in this paper, we propose a novel method called fobfm (fast online bilinear factor model) to learn item-specific factors quickly through online regression. the online regression for each item can be performed independently and hence the procedure is fast, scalable and easily parallelizable. however, the convergence of these independent regressions can be slow due to high dimensionality. the central idea of our approach is to use a large amount of historical data to initialize the online models based on offline features and learn linear projections that can effectively reduce the dimensionality. we estimate the rank of our linear projections by taking recourse to online model selection based on optimizing predictive likelihood. through extensive experiments, we show that our method significantly and uniformly outperforms other competitive methods and obtains relative lifts that are in the range of 10-15% in terms of predictive log-likelihood, 200-300% for a rank correlation metric on a proprietary my yahoo! dataset; it obtains 9% reduction in root mean squared error over the previously best method on a benchmark movielens dataset using a time-based train/test data split.
online multiscale dynamic topic models. we propose an online topic model for sequentially analyzing the time evolution of topics in document collections. topics naturally evolve with multiple timescales. for example, some words may be used consistently over one hundred years, while other words emerge and disappear over periods of a few days. thus, in the proposed model, current topic-specific distributions over words are assumed to be generated based on the multiscale word distributions of the previous epoch. considering both the long-timescale dependency as well as the short-timescale dependency yields a more robust model. we derive efficient online inference procedures based on a stochastic em algorithm, in which the model is sequentially updated using newly obtained data; this means that past data are not required to make the inference. we demonstrate the effectiveness of the proposed method in terms of predictive performance and computational efficiency by examining collections of real documents with timestamps.
an energy-efficient mobile recommender system. the increasing availability of large-scale location traces creates unprecedent opportunities to change the paradigm for knowledge discovery in transportation systems. a particularly promising area is to extract energy-efficient transportation patterns (green knowledge), which can be used as guidance for reducing inefficiencies in energy consumption of transportation sectors. however, extracting green knowledge from location traces is not a trivial task. conventional data analysis tools are usually not customized for handling the massive quantity, complex, dynamic, and distributed nature of location traces. to that end, in this paper, we provide a focused study of extracting energy-efficient transportation patterns from location traces. specifically, we have the initial focus on a sequence of mobile recommendations. as a case study, we develop a mobile recommender system which has the ability in recommending a sequence of pick-up points for taxi drivers or a sequence of potential parking positions. the goal of this mobile recommendation system is to maximize the probability of business success. along this line, we provide a potential travel distance (ptd) function for evaluating each candidate sequence. this ptd function possesses a monotone property which can be used to effectively prune the search space. based on this ptd function, we develop two algorithms, lcp and skyroute, for finding the recommended routes. finally, experimental results show that the proposed system can provide effective mobile sequential recommendation and the knowledge extracted from location traces can be used for coaching drivers and leading to the efficient use of energy.
why label when you can search?: alternatives to active learning for applying human resources to build classification models under extreme class imbalance. this paper analyses alternative techniques for deploying low-cost human resources for data acquisition for classifier induction in domains exhibiting extreme class imbalance - where traditional labeling strategies, such as active learning, can be ineffective. consider the problem of building classifiers to help brands control the content adjacent to their on-line advertisements. although frequent enough to worry advertisers, objectionable categories are rare in the distribution of impressions encountered by most on-line advertisers - so rare that traditional sampling techniques do not find enough positive examples to train effective models. an alternative way to deploy human resources for training-data acquisition is to have them "guide" the learning by searching explicitly for training examples of each class. we show that under extreme skew, even basic techniques for guided learning completely dominate smart (active) strategies for applying human resources to select cases for labeling. therefore, it is critical to consider the relative cost of search versus labeling, and we demonstrate the tradeoffs for different relative costs. we show that in cost/skew settings where the choice between search and active labeling is equivocal, a hybrid strategy can combine the benefits.
social action tracking via noise tolerant time-varying factor graphs. it is well known that users' behaviors (actions) in a social network are influenced by various factors such as personal interests, social influence, and global trends. however, few publications systematically study how social actions evolve in a dynamic social network and to what extent different factors affect the user actions. in this paper, we propose a noise tolerant time-varying factor graph model (ntt-fgm) for modeling and predicting social actions. ntt-fgm simultaneously models social network structure, user attributes and user action history for better prediction of the users' future actions. more specifically, a user's action at time t is generated by her latent state at t, which is influenced by her attributes, her own latent state at time t-1 and her neighbors' states at time t and t-1. based on this intuition, we formalize the social action tracking problem using the ntt-fgm model; then present an efficient algorithm to learn the model, by combining the ideas from both continuous linear system and markov random field. finally, we present a case study of our model on predicting future social actions. we validate the model on three different types of real-world data sets. qualitatively, our model can uncover some interesting patterns of the social dynamics. quantitatively, experimental results show that the proposed method outperforms several baseline methods for action prediction.
neighbor query friendly compression of social networks. compressing social networks can substantially facilitate mining and advanced analysis of large social networks. preferably, social networks should be compressed in a way that they still can be queried efficiently without decompression. arguably, neighbor queries, which search for all neighbors of a query vertex, are the most essential operations on social networks. can we compress social networks effectively in a neighbor query friendly manner, that is, neighbor queries still can be answered in sublinear time using the compression? in this paper, we develop an effective social network compression approach achieved by a novel eulerian data structure using multi-position linearizations of directed graphs. our method comes with a nontrivial theoretical bound on the compression rate. to the best of our knowledge, our approach is the first that can answer both out-neighbor and in-neighbor queries in sublinear time. an extensive empirical study on more than a dozen benchmark real data sets verifies our design.
cold start link prediction. in the traditional link prediction problem, a snapshot of a social network is used as a starting point to predict, by means of graph-theoretic measures, the links that are likely to appear in the future. in this paper, we introduce cold start link prediction as the problem of predicting the structure of a social network when the network itself is totally missing while some other information regarding the nodes is available. we propose a two-phase method based on the bootstrap probabilistic graph. the first phase generates an implicit social network under the form of a probabilistic graph. the second phase applies probabilistic graph-based measures to produce the final prediction. we assess our method empirically over a large data collection obtained from flickr, using interest groups as the initial information. the experiments confirm the effectiveness of our approach.
direct mining of discriminative patterns for classifying uncertain data. classification is one of the most essential tasks in data mining. unlike other methods, associative classification tries to find all the frequent patterns existing in the input categorical data satisfying a user-specified minimum support and/or other discrimination measures like minimum confidence or information-gain. those patterns are used later either as rules for rule-based classifier or training features for support vector machine (svm) classifier, after a feature selection procedure which usually tries to cover as many as the input instances with the most discriminative patterns in various manners. several algorithms have also been proposed to mine the most discriminative patterns directly without costly feature selection. previous empirical results show that associative classification could provide better classification accuracy over many datasets. recently, many studies have been conducted on uncertain data, where fields of uncertain attributes no longer have certain values. instead probability distribution functions are adopted to represent the possible values and their corresponding probabilities. the uncertainty is usually caused by noise, measurement limits, or other possible factors. several algorithms have been proposed to solve the classification problem on uncertain data recently, for example by extending traditional rule-based classifier and decision tree to work on uncertain data. in this paper, we propose a novel algorithm uharmony which mines discriminative patterns directly and effectively from uncertain data as classification features/rules, to help train either svm or rule-based classifier. since patterns are discovered directly from the input database, feature selection usually taking a great amount of time could be avoided completely. effective method for computation of expected confidence of the mined patterns used as the measurement of discrimination is also proposed. empirical results show that using svm classifier our algorithm uharmony outperforms the state-of-the-art uncertain data classification algorithms significantly with 4% to 10% improvements on average in accuracy on 30 categorical datasets under varying uncertain degree and uncertain attribute number.
a probabilistic model for personalized tag prediction. social tagging systems have become increasingly popular for sharing and organizing web resources. tag prediction is a common feature of social tagging systems. social tagging by nature is an incremental process, meaning that once a user has saved a web page with tags, the tagging system can provide more accurate predictions for the user, based on user's incremental behaviors. however, existing tag prediction methods do not consider this important factor, in which their training and test datasets are either split by a fixed time stamp or randomly sampled from a larger corpus. in our temporal experiments, we perform a time-sensitive sampling on an existing public dataset, resulting in a new scenario which is much closer to "real-world". in this paper, we address the problem of tag prediction by proposing a probabilistic model for personalized tag prediction. the model is a bayesian approach, and integrates three factors - ego-centric effect, environmental effects and web page content. two methods - both intuitive calculation and learning optimization - are provided for parameter estimation. pure graphbased methods which may have significant constraints (such as every user, every item and every tag has to occur in at least p posts), cannot make a prediction in most of "real world" cases while our model improves the f-measure by over 30% compared to a leading algorithm, in our "real-world" use case.
the community-search problem and how to plan a successful cocktail party. a lot of research in graph mining has been devoted in the discovery of communities. most of the work has focused in the scenario where communities need to be discovered with only reference to the input graph. however, for many interesting applications one is interested in finding the community formed by a given set of nodes. in this paper we study a query-dependent variant of the community-detection problem, which we call the community-search problem: given a graph g, and a set of query nodes in the graph, we seek to find a subgraph of g that contains the query nodes and it is densely connected. we motivate a measure of density based on minimum degree and distance constraints, and we develop an optimum greedy algorithm for this measure. we proceed by characterizing a class of monotone constraints and we generalize our algorithm to compute optimum solutions satisfying any set of monotone constraints. finally we modify the greedy algorithm and we present two heuristic algorithms that find communities of size no greater than a specified upper bound. our experimental evaluation on real datasets demonstrates the efficiency of the proposed algorithms and the quality of the solutions we obtain.
pet: a statistical model for popular events tracking in social communities. user generated information in online communities has been characterized with the mixture of a text stream and a network structure both changing over time. a good example is a web-blogging community with the daily blog posts and a social network of bloggers. an important task of analyzing an online community is to observe and track the popular events, or topics that evolve over time in the community. existing approaches usually focus on either the burstiness of topics or the evolution of networks, but ignoring the interplay between textual topics and network structures. in this paper, we formally define the problem of popular event tracking in online communities (pet), focusing on the interplay between texts and networks. we propose a novel statistical method that models the the popularity of events over time, taking into consideration the burstiness of user interest, information diffusion on the network structure, and the evolution of textual topics. specifically, a gibbs random field is defined to model the influence of historic status and the dependency relationships in the graph; thereafter a topic model generates the words in text content of the event, regularized by the gibbs random field. we prove that two classic models in information diffusion and text burstiness are special cases of our model under certain situations. empirical experiments with two different communities and datasets (i.e., twitter and dblp) show that our approach is effective and outperforms existing approaches.
evaluating online ad campaigns in a pipeline: causal models at scale. display ads proliferate on the web, but are they effective? or are they irrelevant in light of all the other advertising that people see? we describe a way to answer these questions, quickly and accurately, without randomized experiments, surveys, focus groups or expert data analysts. doubly robust estimation protects against the selection bias that is inherent in observational data, and a nonparametric test that is based on irrelevant outcomes provides further defense. simulations based on realistic scenarios show that the resulting estimates are more robust to selection bias than traditional alternatives, such as regression modeling or propensity scoring. moreover, computations are fast enough that all processing, from data retrieval through estimation, testing, validation and report generation, proceeds in an automated pipeline, without anyone needing to see the raw data.
multi-task learning for boosting with application to web search ranking. in this paper we propose a novel algorithm for multi-task learning with boosted decision trees. we learn several different learning tasks with a joint model, explicitly addressing the specifics of each learning task with task-specific parameters and the commonalities between them through shared parameters. this enables implicit data sharing and regularization. we evaluate our learning method on web-search ranking data sets from several countries. here, multitask learning is particularly helpful as data sets from different countries vary largely in size because of the cost of editorial judgments. our experiments validate that learning various tasks jointly can lead to significant improvements in performance with surprising reliability.
combining predictions for accurate recommender systems. we analyze the application of ensemble learning to recommender systems on the netflix prize dataset. for our analysis we use a set of diverse state-of-the-art collaborative filtering (cf) algorithms, which include: svd, neighborhood based approaches, restricted boltzmann machine, asymmetric factor model and global effects. we show that linearly combining (blending) a set of cf algorithms increases the accuracy and outperforms any single cf algorithm. furthermore, we show how to use ensemble methods for blending predictors in order to outperform a single blending algorithm. the dataset and the source code for the ensemble blending are available online.
an integrated machine learning approach to stroke prediction. stroke is the third leading cause of death and the principal cause of serious long-term disability in the united states. accurate prediction of stroke is highly valuable for early intervention and treatment. in this study, we compare the cox proportional hazards model with a machine learning approach for stroke prediction on the cardiovascular health study (chs) dataset. specifically, we consider the common problems of data imputation, feature selection, and prediction in medical datasets. we propose a novel automatic feature selection algorithm that selects robust features based on our proposed heuristic: conservative mean. combined with support vector machines (svms), our proposed feature selection algorithm achieves a greater area under the roc curve (auc) as compared to the cox proportional hazards model and l1 regularized cox feature selection algorithm. furthermore, we present a margin-based censored regression algorithm that combines the concept of margin-based classifiers with censored regression to achieve a better concordance index than the cox model. overall, our approach outperforms the current state-of-the-art in both metrics of auc and concordance index. in addition, our work has also identified potential risk factors that have not been discovered by traditional approaches. our method can be applied to clinical prediction of other diseases, where missing data are common and risk factors are not well understood.
optimizing debt collections using constrained reinforcement learning. the problem of optimally managing the collections process by taxation authorities is one of prime importance, not only for the revenue it brings but also as a means to administer a fair taxing system. the analogous problem of debt collections management in the private sector, such as banks and credit card companies, is also increasingly gaining attention. with the recent successes in the applications of data analytics and optimization to various business areas, the question arises to what extent such collections processes can be improved by use of leading edge data modeling and optimization techniques. in this paper, we propose and develop a novel approach to this problem based on the framework of constrained markov decision process (mdp), and report on our experience in an actual deployment of a tax collections optimization system at new york state department of taxation and finance (nys dtf).
discovering frequent subgraphs over uncertain graph databases under probabilistic semantics. frequent subgraph mining has been extensively studied on certain graph data. however, uncertainties are inherently accompanied with graph data in practice, and there is very few work on mining uncertain graph data. this paper investigates frequent subgraph mining on uncertain graphs under probabilistic semantics. specifically, a measure called φ-frequent probability is introduced to evaluate the degree of recurrence of subgraphs. given a set of uncertain graphs and two numbers 0 s with probability at least (1 - δ/2)s, where s is the number of edges of s. in addition, it is thoroughly discussed how to set δ to guarantee the overall approximation quality of the algorithm. the extensive experiments on real uncertain graph data verify that the algorithm is efficient and that the mining results have very high quality.
minefleet®: an overview of a widely adopted distributed vehicle performance data mining system. this paper describes the minefleet distributed vehicle performance data mining system designed for commercial fleets. minefleet analyzes high throughput data streams onboard the vehicle, generates the analytics, sends those to the remote server over the wide-area wireless networks and offers them to the fleet managers using stand-alone and web-based user-interface. the paper describes the overall architecture of the system, business needs, and shares experience from successful large-scale commercial deployments. minefleet is probably one of the first commercially successful distributed data stream mining systems. this patented technology has been adopted, productized, and commercially offered by many large companies in the mobile resource management and gps fleet tracking industry. this paper offers an overview of the system and offers a detailed analysis of what made it work.
k-support anonymity based on pseudo taxonomy for outsourcing of frequent itemset mining. for any outsourcing service, privacy is a major concern. this paper focuses on outsourcing frequent itemset mining and examines the issue on how to protect privacy against the case where the attackers have precise knowledge on the supports of some items. we propose a new approach referred to as k-support anonymity to protect each sensitive item with k-1 other items of similar support. to achieve k-support anonymity, we introduce a pseudo taxonomy tree and have the third party mine the generalized frequent itemsets under the corresponding generalized association rules instead of association rules. the pseudo taxonomy is a construct to facilitate hiding of the original items, where each original item can map to either a leaf node or an internal node in the taxonomy tree. the rationale for this approach is that with a taxonomy tree, the k nodes to satisfy the k-support anonymity may be any k nodes in the taxonomy tree with the appropriate supports. so this approach can provide more candidates for k-support anonymity with limited fake items as only the leaf nodes, not the internal nodes, of the taxonomy tree need to appear in the transactions. otherwise for the association rule mining, the k nodes to satisfy the k-support anonymity have to correspond to the leaf nodes in the taxonomy tree. this is far more restricted. the challenge is thus on how to generate the pseudo taxonomy tree to facilitate k-support anonymity and to ensure the conservation of original frequent itemsets. the experimental results showed that our methods of k-support anonymity can achieve very good privacy protection with moderate storage overhead.
trust network inference for online rating data using generative models. in an online rating system, raters assign ratings to objects contributed by other users. in addition, raters can develop trust and distrust on object contributors depending on a few rating and trust related factors. previous study has shown that ratings and trust links can influence each other but there has been a lack of a formal model to relate these factors together. in this paper, we therefore propose trust antecedent factor (taf) model, a novel probabilistic model that generate ratings based on a number of rater's and contributor's factors. we demonstrate that parameters of the model can be learnt by collapsed gibbs sampling. we then apply the model to predict trust and distrust between raters and review contributors using a real data-set. our experiments have shown that the proposed model is capable of predicting both trust and distrust in a unified way. the model can also determine user factors which otherwise cannot be observed from the rating and trust data.
modeling relational events via latent classes. many social networks can be characterized by a sequence of dyadic interactions between individuals. techniques for analyzing such events are of increasing interest. in this paper, we describe a generative model for dyadic events, where each event arises from one of c latent classes, and the properties of the event (sender, recipient, and type) are chosen from distributions over these entities conditioned on the chosen class. we present two algorithms for inference in this model: an expectation-maximization algorithm as well as a markov chain monte carlo procedure based on collapsed gibbs sampling. to analyze the model's predictive accuracy, the algorithms are applied to multiple real-world data sets involving email communication, international political events, and animal behavior data.
topic models with power-law using pitman-yor process. one important approach for knowledge discovery and data mining is to estimate unobserved variables because latent variables can indicate hidden specific properties of observed data. the latent factor model assumes that each item in a record has a latent factor; the co-occurrence of items can then be modeled by latent factors. in document modeling, a record indicates a document represented as a "bag of words," meaning that the order of words is ignored, an item indicates a word and a latent factor indicates a topic. latent dirichlet allocation (lda) is a widely used bayesian topic model applying the dirichlet distribution over the latent topic distribution of a document having multiple topics. lda assumes that latent topics, i.e., discrete latent variables, are distributed according to a multinomial distribution whose parameters are generated from the dirichlet distribution. lda also models a word distribution by using a multinomial distribution whose parameters follows the dirichlet distribution. this dirichlet-multinomial setting, however, cannot capture the power-law phenomenon of a word distribution, which is known as zipf's law in linguistics. we therefore propose a novel topic model using the pitman-yor(py) process, called the py topic model. the py topic model captures two properties of a document; a power-law word distribution and the presence of multiple topics. in an experiment using real data, this model outperformed lda in document modeling in terms of perplexity.
data mining in the online services industry. the online services industry is a rapidly growing industry with a worldwide online ad market projected to grow from $48 billion in 2011 to $67 billion in 2013, of which 47% will come from display advertising and 53% from search advertising. online services division (osd) within microsoft is a leader in the consumer cloud space today with a strong portfolio of a set of 3 mutually reinforcing businesses: search, portal, advertising. they are supported by a shared foundational asset of intent & knowledge stores and a shared technology platform supporting large scale data and high performance systems. msn (portal) and bing (search) generate the content, traffic and data, that make for an exciting fertile environment for large scale data mining practice and system development. our advertisers are thus given more valuable targeting opportunities and better roi, which in turn, provide better economics, usability data, and allows for a higher quality services for our advertisers and experience for our users. the ability to transform data into meaningful, actionable insight is an important source of competitive advantage for osd. the data mining initiatives within the division continue to strive for excellence around the following goals: actionable insights through deep data analysis, data mining and data modeling at scale and with speed, increased productivity from deployed large scale data systems and tools, improved product and service development and decision making gained from effective measurement and experimentation, and a mature data culture in product teams that made the above possible. with many technical and data challenges ahead of us, we are committed to utilizing our huge data asset well to understand the need, intent, and behavior of our users for the purpose of serving them better.
mixture models for learning low-dimensional roles in high-dimensional data. archived data often describe entities that participate in multiple roles. each of these roles may influence various aspects of the data. for example, a register transaction collected at a retail store may have been initiated by a person who is a woman, a mother, an avid reader, and an action movie fan. each of these roles can influence various aspects of the customer's purchase: the fact that the customer is a mother may greatly influence the purchase of a toddler-sized pair of pants, but have no influence on the purchase of an action-adventure novel. the fact that the customer is an action move fan and an avid reader may influence the purchase of the novel, but will have no effect on the purchase of a shirt. in this paper, we present a generic, bayesian framework for capturing exactly this situation. in our framework, it is assumed that multiple roles exist, and each data point corresponds to an entity (such as a retail customer, or an email, or a news article) that selects various roles which compete to influence the various attributes associated with the data point. we develop robust, mcmc algorithms for learning the models under the framework.
generative models for ticket resolution in expert networks. ticket resolution is a critical, yet challenging, aspect of the delivery of it services. a large service provider needs to handle, on a daily basis, thousands of tickets that report various types of problems. many of those tickets bounce among multiple expert groups before being transferred to the group with the right expertise to solve the problem. finding a methodology that reduces such bouncing and hence shortens ticket resolution time is a long-standing challenge. in this paper, we present a unified generative model, the optimized network model (onm), that characterizes the lifecycle of a ticket, using both the content and the routing sequence of the ticket. onm uses maximum likelihood estimation, to represent how the information contained in a ticket is used by human experts to make ticket routing decisions. based on onm, we develop a probabilistic algorithm to generate ticket routing recommendations for new tickets in a network of expert groups. our algorithm calculates all possible routes to potential resolvers and makes globally optimal recommendations, in contrast to existing classification methods that make static and locally optimal recommendations. experiments show that our method significantly outperforms existing solutions.
on the quality of inferring interests from social neighbors. this paper intends to provide some insights of a scientific problem: how likely one's interests can be inferred from his/her social connections -- friends, friends' friends, 3-degree friends, etc? is "birds of a feather flocks together" a norm? we do not consider the friending activity on online social networking sites. instead, we conduct this study by implementing a privacy-preserving large distribute social sensor system in a large global it company to capture the multifaceted activities of 30,000+ people, including communications (e.g., emails, instant messaging, etc) and web 2.0 activities (e.g., social bookmarking, file sharing, blogging, etc). these activities occupy the majority of employees' time in work, and thus, provide a high quality approximation to the real social connections of employees in the workplace context. in addition to such "informal networks", we investigated the "formal networks", such as their hierarchical structure, as well as the demographic profile data such as geography, job role, self-specified interests, etc. because user id matching across multiple sources on the internet is very difficult, and most user activity logs have to be anonymized before they are processed, no prior studies could collect comparable multifaceted activity data of individuals. that makes this study unique. in this paper, we present a technique to predict the inference quality by utilizing (1) network analysis and network autocorrelation modeling of informal and formal networks, and (2) regression models to predict user interest inference quality from network characteristics. we verify our findings with experiments on both implicit user interests indicated by the content of communications or web 2.0 activities, and explicit user interests specified in user profiles. we demonstrate that the inference quality prediction increases the inference quality of implicit interests by 42.8%, and inference quality of explicit interests by up to 101%.
exploitation and exploration in a performance based contextual advertising system. the dynamic marketplace in online advertising calls for ranking systems that are optimized to consistently promote and capitalize better performing ads. the streaming nature of online data inevitably makes an advertising system choose between maximizing its expected revenue according to its current knowledge in short term (exploitation) and trying to learn more about the unknown to improve its knowledge (exploration), since the latter might increase its revenue in the future. the exploitation and exploration (ee) tradeoff has been extensively studied in the reinforcement learning community, however, not been paid much attention in online advertising until recently. in this paper, we develop two novel ee strategies for online advertising. specifically, our methods can adaptively balance the two aspects of ee by automatically learning the optimal tradeoff and incorporating confidence metrics of historical performance. within a deliberately designed offline simulation framework we apply our algorithms to an industry leading performance based contextual advertising system and conduct extensive evaluations with real online event log data. the experimental results and detailed analysis reveal several important findings of ee behaviors in online advertising and demonstrate that our algorithms perform superiorly in terms of ad reach and click-through-rate (ctr).
user browsing models: relevance versus examination. there has been considerable work on user browsing models for search engine results, both organic and sponsored. the click-through rate (ctr) of a result is the product of the probability of examination (will the user look at the result) times the perceived relevance of the result (probability of a click given examination). past papers have assumed that when the ctr of a result varies based on the pattern of clicks in prior positions, this variation is solely due to changes in the probability of examination. we show that, for sponsored search results, a substantial portion of the change in ctr when conditioned on prior clicks is in fact due to a change in the relevance of results for that query instance, not just due to a change in the probability of examination. we then propose three new user browsing models, which attribute ctr changes solely to changes in relevance, solely to changes in examination (with an enhanced model of user behavior), or to both changes in relevance and examination. the model that attributes all the ctr change to relevance yields substantially better predictors of ctr than models that attribute all the change to examination, and does only slightly worse than the model that attributes ctr change to both relevance and examination. for predicting relevance, the model that attributes all the ctr change to relevance again does better than the model that attributes the change to examination. surprisingly, we also find that one model might do better than another in predicting ctr, but worse in predicting relevance. thus it is essential to evaluate user browsing models with respect to accuracy in predicting relevance, not just ctr.
learning incoherent sparse and low-rank patterns from multiple tasks. we consider the problem of learning incoherent sparse and low-rank patterns from multiple tasks. our approach is based on a linear multi-task learning formulation, in which the sparse and low-rank patterns are induced by a cardinality regularization term and a low-rank constraint, respectively. this formulation is non-convex; we convert it into its convex surrogate, which can be routinely solved via semidefinite programming for small-size problems. we propose to employ the general projected gradient scheme to efficiently solve such a convex surrogate; however, in the optimization formulation, the objective function is non-differentiable and the feasible domain is non-trivial. we present the procedures for computing the projected gradient and ensuring the global convergence of the projected gradient scheme. the computation of projected gradient involves a constrained optimization problem; we show that the optimal solution to such a problem can be obtained via solving an unconstrained optimization subproblem and an euclidean projection subproblem. in addition, we present two projected gradient algorithms and discuss their rates of convergence. experimental results on benchmark data sets demonstrate the effectiveness of the proposed multi-task learning formulation and the efficiency of the proposed projected gradient algorithms.
designing efficient cascaded classifiers: tradeoff between accuracy and cost. we propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. the approach relies on the idea of optimizing soft cascades. in particular, instead of optimizing a deterministic hard cascade, we optimize a stochastic soft cascade where each stage accepts or rejects samples according to a probability distribution induced by the previous stage-specific classifier. the overall system accuracy is maximized while explicitly controlling the expected cost for feature acquisition. experimental results on three clinically relevant problems show the effectiveness of our proposed approach in achieving the desired tradeoff between accuracy and feature acquisition cost.
a scalable two-stage approach for a class of dimensionality reduction techniques. dimensionality reduction plays an important role in many data mining applications involving high-dimensional data. many existing dimensionality reduction techniques can be formulated as a generalized eigenvalue problem, which does not scale to large-size problems. prior work transforms the generalized eigenvalue problem into an equivalent least squares formulation, which can then be solved efficiently. however, the equivalence relationship only holds under certain assumptions without regularization, which severely limits their applicability in practice. in this paper, an efficient two-stage approach is proposed to solve a class of dimensionality reduction techniques, including canonical correlation analysis, orthonormal partial least squares, linear discriminant analysis, and hypergraph spectral learning. the proposed two-stage approach scales linearly in terms of both the sample size and data dimensionality. the main contributions of this paper include (1) we rigorously establish the equivalence relationship between the proposed two-stage approach and the original formulation without any assumption; and (2) we show that the equivalence relationship still holds in the regularization setting. we have conducted extensive experiments using both synthetic and real-world data sets. our experimental results confirm the equivalence relationship established in this paper. results also demonstrate the scalability of the proposed two-stage approach.
redefining class definitions using constraint-based clustering: an application to remote sensing of the earth's surface. two aspects are crucial when constructing any real world supervised classification task: the set of classes whose distinction might be useful for the domain expert, and the set of classifications that can actually be distinguished by the data. often a set of labels is defined with some initial intuition but these are not the best match for the task. for example, labels have been assigned for land cover classification of the earth but it has been suspected that these labels are not ideal and some classes may be best split into subclasses whereas others should be merged. this paper formalizes this problem using three ingredients: the existing class labels, the underlying separability in the data, and a special type of input from the domain expert. we require a domain expert to specify an l × l matrix of pairwise probabilistic constraints expressing their beliefs as to whether the l classes should be kept separate, merged, or split. this type of input is intuitive and easy for experts to supply. we then show that the problem can be solved by casting it as an instance of penalized probabilistic clustering (ppc). our method, class-level ppc (cppc) extends ppc showing how its time complexity can be reduced from o(n2) to o(nl) for the problem of class re-definition. we further extend the algorithm by presenting a heuristic to measure adherence to constraints, and providing a criterion for determining the model complexity (number of classes) for constraint-based clustering. we demonstrate and evaluate cppc on artificial data and on our motivating domain of land cover classification. for the latter, an evaluation by domain experts shows that the algorithm discovers novel class definitions that are better suited to land cover classification than the original set of labels.
new perspectives and methods in link prediction. this paper examines important factors for link prediction in networks and provides a general, high-performance framework for the prediction task. link prediction in sparse networks presents a significant challenge due to the inherent disproportion of links that can form to links that do form. previous research has typically approached this as an unsupervised problem. while this is not the first work to explore supervised learning, many factors significant in influencing and guiding classification remain unexplored. in this paper, we consider these factors by first motivating the use of a supervised framework through a careful investigation of issues such as network observational period, generality of existing methods, variance reduction, topological causes and degrees of imbalance, and sampling approaches. we also present an effective flow-based predicting algorithm, offer formal bounds on imbalance in sparse network link prediction, and employ an evaluation method appropriate for the observed imbalance. our careful consideration of the above issues ultimately leads to a completely general framework that outperforms unsupervised link prediction methods by more than 30% auc.
universal multi-dimensional scaling. in this paper, we propose a unified algorithmic framework for solving many known variants of mds. our algorithm is a simple iterative scheme with guaranteed convergence, and is modular; by changing the internals of a single subroutine in the algorithm, we can switch cost functions and target spaces easily. in addition to the formal guarantees of convergence, our algorithms are accurate; in most cases, they converge to better quality solutions than existing methods in comparable time. moreover, they have a small memory footprint and scale effectively for large data sets. we expect that this framework will be useful for a number of mds variants that have not yet been studied. our framework extends to embedding high-dimensional points lying on a sphere to points on a lower dimensional sphere, preserving geodesic distances. as a complement to this result, we also extend the johnson-lindenstrauss lemma to this spherical setting, by showing that projecting to a random o((1/µ2) log n)-dimensional sphere causes only an eps-distortion in the geodesic distances.
mining periodic behaviors for moving objects. periodicity is a frequently happening phenomenon for moving objects. finding periodic behaviors is essential to understanding object movements. however, periodic behaviors could be complicated, involving multiple interleaving periods, partial time span, and spatiotemporal noises and outliers. in this paper, we address the problem of mining periodic behaviors for moving objects. it involves two sub-problems: how to detect the periods in complex movement, and how to mine periodic movement behaviors. our main assumption is that the observed movement is generated from multiple interleaved periodic behaviors associated with certain reference locations. based on this assumption, we propose a two-stage algorithm, periodica, to solve the problem. at the first stage, the notion of observation spot is proposed to capture the reference locations. through observation spots, multiple periods in the movement can be retrieved using a method that combines fourier transform and autocorrelation. at the second stage, a probabilistic model is proposed to characterize the periodic behaviors. for a specific period, periodic behaviors are statistically generalized from partial movement sequences through hierarchical clustering. empirical studies on both synthetic and real data sets demonstrate the effectiveness of our method.
collusion-resistant privacy-preserving data mining. recent research in privacy-preserving data mining (ppdm) has become increasingly popular due to the wide application of data mining and the increased concern regarding the protection of private and personal information. lately, numerous methods of privacy-preserving data mining have been proposed. most of these methods are based on an assumption that semi-honest is and collusion is not present. in other words, every party follows such protocol properly with the exception that it keeps a record of all its intermediate computations without sharing the record with others. in this paper, we focus our attention on the problem of collusions, in which some parties may collude and share their record to deduce the private information of other parties. in particular, we consider a general problem in ppdm - multiparty secure computation of some functions of secure summations of data spreading around multiple parties. to solve such a problem, we propose a new method that entails a high level of security - full-privacy. with this method, no sensitive information of a party will be revealed even when all other parties collude. in addition, this method is efficient with a running time of o(m). we will also show that by applying this general method, a large number of problems in ppdm can be solved with enhanced security.
detecting inefficiently-used containers to avoid bloat. runtime bloat degrades significantly the performance and scalability of software systems. an important source of bloat is the inefficient use of containers. it is expensive to create inefficiently-used containers and to invoke their associated methods, as this may ultimately execute large volumes of code, with call stacks dozens deep, and allocate many temporary objects. this paper presents practical static and dynamic tools that can find inappropriate use of containers in java programs. at the core of these tools is a base static analysis that identifies, for each container, the objects that are added to this container and the key statements (i.e., heap loads and stores) that achieve the semantics of common container operations such as add and get. the static tool finds problematic uses of containers by considering the nesting relationships among the loops where these semantics-achieving statements are located, while the dynamic tool can instrument these statements and find inefficiencies by profiling their execution frequencies. the high precision of the base analysis is achieved by taking advantage of a context-free language (cfl)-reachability formulation of points-to analysis and by accounting for container-specific properties. it is demand-driven and client-driven, facilitating refinement specific to each queried container object and increasing scalability. the tools built with the help of this analysis can be used both to avoid the creation of container-related performance problems early during development, and to help with diagnosis when problems are observed during tuning. our experimental results show that the static tool has a low false positive rate and produces more relevant information than its dynamic counterpart. further case studies suggest that significant optimization opportunities can be found by focusing on statically-identified containers for which high allocation frequency is observed at run time.
a context-free markup language for semi-structured text. an ad hoc data format is any nonstandard, semi-structured data format for which robust data processing tools are not easily available. in this paper, we present anne, a new kind of markup language designed to help users generate documentation and data processing tools for ad hoc text data. more specifically, given a new ad hoc data source, an anne programmer edits the document to add a number of simple annotations, which serve to specify its syntactic structure. annotations include elements that specify constants, optional data, alternatives, enumerations, sequences, tabular data, and recursive patterns. the anne system uses a combination of user annotations and the raw data itself to extract a context-free grammar from the document. this context-free grammar can then be used to parse the data and transform it into an xml parse tree, which may be viewed through a browser for analysis or debugging purposes. in addition, the anne system generates a pads/ml description, which may be saved as lasting documentation of the data format or compiled into a host of useful data processing tools. in addition to designing and implementing anne, we have devised a semantic theory for the core elements of the language. this semantic theory describes the editing process, which translates a raw, unannotated text document into an annotated document, and the grammar extraction process, which generates a context-free grammar from an annotated document. we also present an alternative characterization of system behavior by drawing upon ideas from the field of relevance logic. this secondary characterization, which we call relevance analysis, specifies a direct relationship between unannotated documents and the context-free grammars that our system can generate from them. relevance analysis allows us to prove important theorems concerning the expressiveness and utility of our system.
decoupled lifeguards: enabling path optimizations for dynamic correctness checking tools. dynamic correctness checking tools (a.k.a. lifeguards) can detect a wide array of correctness issues, such as memory, security, and concurrency misbehavior, in unmodified executables at run time. however, lifeguards that are implemented using dynamic binary instrumentation (dbi) often slow down the monitored application by 10-50x, while proposals that replace dbi with hardware still see 3-8x slowdowns. the remaining overhead is the cost of performing the lifeguard analysis itself. in this paper, we explore compiler optimization techniques to reduce this overhead. the lifeguard software is typically structured as a set of event-driven handlers, where the events are individual instructions in the monitored application's dynamic instruction stream. we propose to decouple the lifeguard checking code from the application that it is monitoring so that the lifeguard analysis can be invoked at the granularity of hot paths in the monitored application. in this way, we are able to find many more opportunities for eliminating redundant work in the lifeguard analysis, even starting with well-optimized applications and hand-tuned lifeguard handlers. experimental results with two lifeguard frameworks - one dbi-based and one hardware-assisted - show significant reduction in monitoring overhead.
a gpgpu compiler for memory optimization and parallelism management. this paper presents a novel optimizing compiler for general purpose computation on graphics processing units (gpgpu). it addresses two major challenges of developing high performance gpgpu programs: effective utilization of gpu memory hierarchy and judicious management of parallelism. the input to our compiler is a naïve gpu kernel function, which is functionally correct but without any consideration for performance optimization. the compiler analyzes the code, identifies its memory access patterns, and generates both the optimized kernel and the kernel invocation parameters. our optimization process includes vectorization and memory coalescing for memory bandwidth enhancement, tiling and unrolling for data reuse and parallelism management, and thread block remapping or address-offset insertion for partition-camping elimination. the experiments on a set of scientific and media processing algorithms show that our optimized code achieves very high performance, either superior or very close to the highly fine-tuned library, nvidia cublas 2.2, and up to 128 times speedups over the naive versions. another distinguishing feature of our compiler is the understandability of the optimized code, which is useful for performance analysis and algorithm refinement.
schism: fragmentation-tolerant real-time garbage collection. managed languages such as java and c# are being considered for use in hard real-time systems. a hurdle to their widespread adoption is the lack of garbage collection algorithms that offer predictable space-and-time performance in the face of fragmentation. we introduce schism/cmr, a new concurrent and real-time garbage collector that is fragmentation tolerant and guarantees time-and-space worst-case bounds while providing good throughput. schism/cmr combines mark-region collection of fragmented objects and arrays (arraylets) with separate replication-copying collection of immutable arraylet spines, so as to cope with external fragmentation when running in small heaps. we present an implementation of schism/cmr in the fiji vm, a high-performance java virtual machine for mission-critical systems, along with a thorough experimental evaluation on a wide variety of architectures, including server-class and embedded systems. the results show that schism/cmr tolerates fragmentation better than previous schemes, with a much more acceptable throughput penalty.
jinn: synthesizing dynamic bug detectors for foreign language interfaces. programming language specifications mandate static and dynamic analyses to preclude syntactic and semantic errors. although individual languages are usually well-specified, composing languages is not, and this poor specification is a source of many errors in multilingual programs. for example, virtually all java programs compose java and c using the java native interface (jni). since jni is informally specified, developers have difficulty using it correctly, and current java compilers and virtual machines (vms) inconsistently check only a subset of jni constraints. this paper's most significant contribution is to show how to synthesize dynamic analyses from state machines to detect foreign function interface (ffi) violations. we identify three classes of ffi constraints encoded by eleven state machines that capture thousands of jni and python/c ffi rules. we use a mapping function to specify which state machines, transitions, and program entities (threads, objects, references) to check at each ffi call and return. from this function, we synthesize a context-specific dynamic analysis to find ffi bugs. we build bug detection tools for jni and python/c using this approach. for jni, we dynamically and transparently interpose the analysis on java and c language transitions through the jvm tools interface. the resulting tool, called jinn, is compiler and virtual machine independent. it detects and diagnoses a wide variety of ffi bugs that other tools miss. this approach greatly reduces the annotation burden by exploiting common ffi constraints: whereas the generated jinn code is 22,000+ lines, we wrote only 1,400 lines of state machine and mapping code. overall, this paper lays the foundation for a more principled approach to developing correct multilingual software and a more concise and automated approach to ffi specification.
composing parallel software efficiently with lithe. applications composed of multiple parallel libraries perform poorly when those libraries interfere with one another by obliviously using the same physical cores, leading to destructive resource oversubscription. this paper presents the design and implementation of lithe, a low-level substrate that provides the basic primitives and a standard interface for composing parallel codes efficiently. lithe can be inserted underneath the runtimes of legacy parallel libraries to provide bolt-on composability without needing to change existing application code. lithe can also serve as the foundation for building new parallel abstractions and libraries that automatically interoperate with one another. in this paper, we show versions of threading building blocks (tbb) and openmp perform competitively with their original implementations when ported to lithe. furthermore, for two applications composed of multiple parallel libraries, we show that leveraging our substrate outperforms their original, even expertly tuned, implementations.
mixing type checking and symbolic execution. static analysis designers must carefully balance precision and efficiency. in our experience, many static analysis tools are built around an elegant, core algorithm, but that algorithm is then extensively tweaked to add just enough precision for the coding idioms seen in practice, without sacrificing too much efficiency. there are several downsides to adding precision in this way: the tool's implementation becomes much more complicated; it can be hard for an end-user to interpret the tool's results; and as software systems vary tremendously in their coding styles, it may require significant algorithmic engineering to enhance a tool to perform well in a particular software domain. in this paper, we present mix, a novel system that mixes type checking and symbolic execution. the key aspect of our approach is that these analyses are applied independently on disjoint parts of the program, in an off-the-shelf manner. at the boundaries between nested type checked and symbolically executed code regions, we use special mix rules to communicate information between the off-the-shelf systems. the resulting mixture is a provably sound analysis that is more precise than type checking alone and more efficient than exclusive symbolic execution. in addition, we also describe a prototype implementation, mixy, for c. mixy checks for potential null dereferences by mixing a null/non-null type qualifier inference system with a symbolic executor.
green: a framework for supporting energy-conscious programming using controlled approximation. energy-efficient computing is important in several systems ranging from embedded devices to large scale data centers. several application domains offer the opportunity to tradeoff quality of service/solution (qos) for improvements in performance and reduction in energy consumption. programmers sometimes take advantage of such opportunities, albeit in an ad-hoc manner and often without providing any qos guarantees. we propose a system called green that provides a simple and flexible framework that allows programmers to take advantage of such approximation opportunities in a systematic manner while providing statistical qos guarantees. green enables programmers to approximate expensive functions and loops and operates in two phases. in the calibration phase, it builds a model of the qos loss produced by the approximation. this model is used in the operational phase to make approximation decisions based on the qos constraints specified by the programmer. the operational phase also includes an adaptation function that occasionally monitors the runtime behavior and changes the approximation decisions and qos model to provide strong statistical qos guarantees. to evaluate the effectiveness of green, we implemented our system and language extensions using the phoenix compiler framework. our experiments using benchmarks from domains such as graphics, machine learning, signal processing, and finance, and an in-production, real-world web search engine, indicate that green can produce significant improvements in performance and energy consumption with small and controlled qos degradation.
inferable object-oriented typed assembly language. a certifying compiler preserves type information through compilation to assembly language programs, producing typed assembly language (tal) programs that can be verified for safety independently so that the compiler does not need to be trusted. there are two challenges for adopting certifying compilation in practice. first, requiring every compiler transformation and optimization to preserve types is a large burden on compilers, especially when adopting certifying compilation into existing optimizing non-certifying compilers. second, type annotations significantly increase the size of assembly language programs. this paper proposes an alternative to traditional certifying compilers. it presents italx, the first inferable tal type system that supports existential types, arrays, interfaces, and stacks. we have proved our inference algorithm is complete, meaning if an assembly language program is typeable with italx then our algorithm will infer an italx typing for that program. furthermore, our algorithm is guaranteed to terminate even if the assembly language program is untypeable. we demonstrate that it is practical to infer such an expressive tal by showing a prototype implementation of type inference for code compiled by bartok, an optimizing c# compiler. our prototype implementation infers complete type annotations for 98% of functions in a suite of realistic c# benchmarks. the type-inference time is about 8% of the compilation time. we needed to change only 2.5% of the compiler code, mostly adding new code for defining types and for writing types to object files. most transformations are untouched. type-annotation size is only 17% of the size of pure code and data, reducing type annotations in our previous certifying compiler [4] by 60%. the compiler needs to preserve only essential type information such as method signatures, object-layout information, and types for static data and external labels. even non-certifying compilers have most of this information available.
lock elision for read-only critical sections in java. it is not uncommon in parallel workloads to encounter shared data structures with read-mostly access patterns, where operations that update data are infrequent and most operations are read-only. typically, data consistency is guaranteed using mutual exclusion or read-write locks. the cost of atomic update of lock variables result in high overheads and high cache coherence traffic under active sharing, thus slowing down single thread performance and limiting scalability. in this paper, we present solero (software optimistic lock elision for read-only critical sections), a new lock implementation called for optimizing read-only critical sections in java based on sequential locks. solero is compatible with the conventional lock implementation of java. however, unlike the conventional implementation, only critical sections that may write data or have side effects need to update lock variables, while read-only critical sections need only read lock variables without writing them. each writing critical section changes the lock value to a new value. hence, a read-only critical section is guaranteed to be consistent if the lock is free and its value does not change from the beginning to the end of the read-only critical section. using java workloads including specjbb2005 and the hashmap and treemap java classes, we evaluate the performance impact of applying solero to read-mostly locks. our experimental results show performance improvements across the board, often substantial, in both single thread speed and scalability over the conventional lock implementation (mutual exclusion) and read-write locks. solero improves the performance of specjbb2005 by 3-5% on single and multiple threads. the results using the hashmap and treemap benchmarks show that solero outperforms the conventional lock implementation and read-write locks by substantial multiples on multi-threads.
bringing extensibility to verified compilers. verified compilers, such as leroy's compcert, are accompanied by a fully checked correctness proof. both the compiler and proof are often constructed with an interactive proof assistant. this technique provides a strong, end-to-end correctness guarantee on top of a small trusted computing base. unfortunately, these compilers are also challenging to extend since each additional transformation must be proven correct in full formal detail. at the other end of the spectrum, techniques for compiler correctness based on a domain-specific language for writing optimizations, such as lerner's rhodium and cobalt, make the compiler easy to extend: the correctness of additional transformations can be checked completely automatically. unfortunately, these systems provide a weaker guarantee since their end-to-end correctness has not been proven fully formally. we present an approach for compiler correctness that provides the best of both worlds by bridging the gap between compiler verification and compiler extensibility. in particular, we have extended leroy's compcert compiler with an execution engine for optimizations written in a domain specific and proved that this execution engine preserves program semantics, using the coq proof assistant. we present our compcert extension, xcert, including the details of its execution engine and proof of correctness in coq. furthermore, we report on the important lessons learned for making the proof development manageable.
an analysis of the dynamic behavior of javascript programs. the javascript programming language is widely used for web programming and, increasingly, for general purpose computing. as such, improving the correctness, security and performance of javascript applications has been the driving force for research in type systems, static analysis and compiler techniques for this language. many of these techniques aim to reign in some of the most dynamic features of the language, yet little seems to be known about how programmers actually utilize the language or these features. in this paper we perform an empirical study of the dynamic behavior of a corpus of widely-used javascript programs, and analyze how and why the dynamic features are used. we report on the degree of dynamism that is exhibited by these javascript programs and compare that with assumptions commonly made in the literature and accepted industry benchmark suites.
safe to the last instruction: automated verification of a type-safe operating system. typed assembly language (tal) and hoare logic can verify the absence of many kinds of errors in low-level code. we use tal and hoare logic to achieve highly automated, static verification of the safety of a new operating system called verve. our techniques and tools mechanically verify the safety of every assembly language instruction in the operating system, run-time system, drivers, and applications (in fact, every part of the system software except the boot loader). verve consists of a "nucleus" that provides primitive access to hardware and memory, a kernel that builds services on top of the nucleus, and applications that run on top of the kernel. the nucleus, written in verified assembly language, implements allocation, garbage collection, multiple stacks, interrupt handling, and device access. the kernel, written in c# and compiled to tal, builds higher-level services, such as preemptive threads, on top of the nucleus. a tal checker verifies the safety of the kernel and applications. a hoare-style verifier with an automated theorem prover verifies both the safety and correctness of the nucleus. verve is, to the best of our knowledge, the first operating system mechanically verified to guarantee both type and memory safety. more generally, verve's approach demonstrates a practical way to mix high-level typed code with low-level untyped code in a verifiably safe manner.
drfx: a simple and efficient memory model for concurrent programming languages. the most intuitive memory model for shared-memory multithreaded programming is sequential consistency(sc), but it disallows the use of many compiler and hardware optimizations thereby impacting performance. data-race-free (drf) models, such as the proposed c++0x memory model, guarantee sc execution for datarace-free programs. but these models provide no guarantee at all for racy programs, compromising the safety and debuggability of such programs. to address the safety issue, the java memory model, which is also based on the drf model, provides a weak semantics for racy executions. however, this semantics is subtle and complex, making it difficult for programmers to reason about their programs and for compiler writers to ensure the correctness of compiler optimizations. we present the drfx memory model, which is simple for programmers to understand and use while still supporting many common optimizations. we introduce a memory model (mm) exception which can be signaled to halt execution. if a program executes without throwing this exception, then drfx guarantees that the execution is sc. if a program throws an mm exception during an execution, then drfx guarantees that the program has a data race. we observe that sc violations can be detected in hardware through a lightweight form of conflict detection. furthermore, our model safely allows aggressive compiler and hardware optimizations within compiler-designated program regions. we formalize our memory model, prove several properties about this model, describe a compiler and hardware design suitable for drfx, and evaluate the performance overhead due to our compiler and hardware requirements.
flumejava: easy, efficient data-parallel pipelines. mapreduce and similar systems significantly ease the task of writing data-parallel code. however, many real-world computations require a pipeline of mapreduces, and programming and managing such pipelines can be difficult. we present flumejava, a java library that makes it easy to develop, test, and run efficient data-parallel pipelines. at the core of the flumejava library are a couple of classes that represent immutable parallel collections, each supporting a modest number of operations for processing them in parallel. parallel collections and their operations present a simple, high-level, uniform abstraction over different data representations and execution strategies. to enable parallel operations to run efficiently, flumejava defers their evaluation, instead internally constructing an execution plan dataflow graph. when the final results of the parallel operations are eventually needed, flumejava first optimizes the execution plan, and then executes the optimized operations on appropriate underlying primitives (e.g., mapreduces). the combination of high-level abstractions for parallel data and computation, deferred evaluation and optimization, and efficient parallel primitives yields an easy-to-use system that approaches the efficiency of hand-optimized pipelines. flumejava is in active use by hundreds of pipeline developers within google.
software data spreading: leveraging distributed caches to improve single thread performance. single thread performance remains an important consideration even for multicore, multiprocessor systems. as a result, techniques for improving single thread performance using multiple cores have received considerable attention. this work describes a technique, software data spreading, that leverages the cache capacity of extra cores and extra sockets rather than their computational resources. software data spreading is a software-only technique that uses compiler-directed thread migration to aggregate cache capacity across cores and chips and improve performance. this paper describes an automated scheme that applies data spreading to various types of loops. experiments with a set of spec2000, spec2006, nas, and microbenchmark workloads show that data spreading can provide speedup of over 2, averaging 17% for the spec and nas applications on two systems. in addition, despite using more cores for the same computation, data spreading actually saves power since it reduces access to dram.
line-up: a complete and automatic linearizability checker. modular development of concurrent applications requires thread-safe components that behave correctly when called concurrently by multiple client threads. this paper focuses on linearizability, a specific formalization of thread safety, where all operations of a concurrent component appear to take effect instantaneously at some point between their call and return. the key insight of this paper is that if a component is intended to be deterministic, then it is possible to build an automatic linearizability checker by systematically enumerating the sequential behaviors of the component and then checking if each its concurrent behavior is equivalent to some sequential behavior. we develop this insight into a tool called line-up, the first complete and automatic checker for deterministic linearizability. it is complete, because any reported violation proves that the implementation is not linearizable with respect to any sequential deterministic specification. it is automatic, requiring no manual abstraction, no manual specification of semantics or commit points, no manually written test suites, no access to source code. we evaluate line-up by analyzing 13 classes with a total of 90 methods in two versions of the .net framework 4.0. the violations of deterministic linearizability reported by line-up exposed seven errors in the implementation that were fixed by the development team.
breadcrumbs: efficient context sensitivity for dynamic bug detection analyses. calling context--the set of active methods on the stack--is critical for understanding the dynamic behavior of large programs. dynamic program analysis tools, however, are almost exclusively context insensitive because of the prohibitive cost of representing calling contexts at run time. deployable dynamic analyses, in particular, have been limited to reporting only static program locations. this paper presents breadcrumbs, an efficient technique for recording and reporting dynamic calling contexts. it builds on an existing technique for computing a compact (one word) encoding of each calling context that client analyses can use in place of a program location. the key feature of our system is a search algorithm that can reconstruct a calling context from its encoding using only a static call graph and a small amount of dynamic information collected at cold (infrequently executed) callsites. breadcrumbs requires no offline training or program modifications, and handles all language features, including dynamic class loading. we use breadcrumbs to add context sensitivity to two dynamic analyses: a data-race detector and an analysis for diagnosing null pointer exceptions. on average, it adds 10% to 20% runtime overhead, depending on a tunable parameter that controls how much dynamic information is collected. collecting less information lowers the overhead, but can result in a search space explosion. in some cases this causes reconstruction to fail, but in most cases breadcrumbs >produces non-trivial calling contexts that have the potential to significantly improve both the precision of the analyses and the quality of the bug reports.
evaluating iterative optimization across 1000 datasets. while iterative optimization has become a popular compiler optimization approach, it is based on a premise which has never been truly evaluated: that it is possible to learn the best compiler optimizations across data sets. up to now, most iterative optimization studies find the best optimizations through repeated runs on the same data set. only a handful of studies have attempted to exercise iterative optimization on a few tens of data sets. in this paper, we truly put iterative compilation to the test for the first time by evaluating its effectiveness across a large number of data sets. we therefore compose kdatasets, a data set suite with 1000 data sets for 32 programs, which we release to the public. we characterize the diversity of kdatasets, and subsequently use it to evaluate iterative optimization.we demonstrate that it is possible to derive a robust iterative optimization strategy across data sets: for all 32 programs, we find that there exists at least one combination of compiler optimizations that achieves 86% or more of the best possible speedup across all data sets using intel's icc (83% for gnu's gcc). this optimal combination is program-specific and yields speedups up to 1.71 on icc and 2.23 on gcc over the highest optimization level (-fast and -o3, respectively). this finding makes the task of optimizing programs across data sets much easier than previously anticipated, and it paves the way for the practical and reliable usage of iterative optimization. finally, we derive pre-shipping and post-shipping optimization strategies for software vendors.
pacer: proportional detection of data races. data races indicate serious concurrency bugs such as order, atomicity, and sequential consistency violations. races are difficult to find and fix, often manifesting only after deployment. the frequency and unpredictability of these bugs will only increase as software adds parallelism to exploit multicore hardware. unfortunately, sound and precise race detectors slow programs by factors of eight or more and do not scale to large numbers of threads. this paper presents a precise, low-overhead sampling-based data race detector called pacer. pacer makes a proportionality guarantee: it detects any race at a rate equal to the sampling rate, by finding races whose first access occurs during a global sampling period. during sampling, pacer tracks all accesses using the dynamically sound and precise fasttrack algorithm. in nonsampling periods, pacer discards sampled access information that cannot be part of a reported race, and pacer simplifies tracking of the happens-before relationship, yielding near-constant, instead of linear, overheads. experimental results confirm our theoretical guarantees. pacer reports races in proportion to the sampling rate. its time and space overheads scale with the sampling rate, and sampling rates of 1-3% yield overheads low enough to consider in production software. the resulting system provides a "get what you pay for" approach that is suitable for identifying real, hard-to-reproduce races in deployed systems.
2010 athena lecture. susan eggers, a professor of computer science and engineering at the university of washington, joined her department in 1989. she received a b.a. in 1965 from connecticut college and a ph.d. in 1989 from the university of california, berkeley. her research interests are in computer architecture and back-end compiler optimization, with an emphasis on experimental performance analysis. with her colleague hank levy and their students, she developed the first commercially viable multithreaded architecture, simultaneous multithreading, adopted by intel (as hyperthreading), ibm, sun and others. her current research is in the areas of distributed dataflow machines, fpgas and chip multiprocessors. in 1989 professor eggers was awarded an ibm faculty development award, in 1990 an nsf presidential young investigator award, in 1994 the microsoft professorship in computer science and engineering, and in 2009 the acm-w athena lecturer. she is a fellow of the acm and ieee, a fellow of the aaas, and a member of the national academy of engineering.
adversarial memory for detecting destructive races. multithreaded programs are notoriously prone to race conditions, a problem exacerbated by the widespread adoption of multi-core processors with complex memory models and cache coherence protocols. much prior work has focused on static and dynamic analyses for race detection, but these algorithms typically are unable to distinguish destructive races that cause erroneous behavior from benign races that do not. performing this classification manually is difficult, time consuming, and error prone. this paper presents a new dynamic analysis technique that uses adversarial memory to classify race conditions as destructive or benign on systems with relaxed memory models. unlike a typical language implementation, which may only infrequently exhibit non-sequentially consistent behavior, our adversarial memory implementation exploits the full freedom of the memory model to return older, unexpected, or stale values for memory reads whenever possible, in an attempt to crash the target program (that is, to force the program to behave erroneously). a crashing execution provides concrete evidence of a destructive bug, and this bug can be strongly correlated with a specific race condition in the target program. experimental results with our jumble prototype for java demonstrate that adversarial memory is highly effective at identifying destructive race conditions, and in distinguishing them from race conditions that are real but benign. adversarial memory can also reveal destructive races that would not be detected by traditional testing (even after thousands of runs) or by model checkers that assume sequential consistency.
guesstimate: a programming model for collaborative distributed systems. we present a new programming model gueesstimate for developing collaborative distributed systems. the model allows atomic, isolated operations that transform a system from consistent state to consistent state, and provides a shared transactional store for a collection of such operations executed by various machines in a distributed system. in addition to "committed state" which is identical in all machines in the distributed system, guesstimate allows each machine to have a replicated local copy of the state (called "guesstimated state") so that operations on shared state can be executed locally without any blocking, while also guaranteeing that eventually all machines agree on the sequences of operations executed. thus, each operation is executed multiple times, once at the time of issue when it updates the guesstimated state of the issuing machine, once when the operation is committed (atomically) to the committed state of all machines, and several times in between as the guesstimated state converges toward the committed state. while we expect the results of these executions of the operation to be identical most of the time in the class of applications we study, it is possible for an operation to succeed the first time when it is executed on the guesstimated state, and fail when it is committed. guesstimate provides facilities that allow the programmer to deal with this potential discrepancy. this paper presents our programming model, its operational semantics, its realization as an api in c#, and our experience building collaborative distributed applications with this model.
traceable data types for self-adjusting computation. self-adjusting computation provides an evaluation model where computations can respond automatically to modifications to their data by using a mechanism for propagating modifications through the computation. current approaches to self-adjusting computation guarantee correctness by recording dependencies in a trace at the granularity of individual memory operations. tracing at the granularity of memory operations, however, has some limitations: it can be asymptotically inefficient (\eg, compared to optimal solutions) because it cannot take advantage of problem-specific structure, it requires keeping a large computation trace (often proportional to the runtime of the program on the current input), and it introduces moderately large constant factors in practice. in this paper, we extend dependence-tracing to work at the granularity of the query and update operations of arbitrary (abstract) data types, instead of just reads and writes on memory cells. this can significantly reduce the number of dependencies that need to be kept in the trace and followed during an update. we define an interface for supporting a traceable version of a data type, which reports the earliest query that depends on (is changed by) revising operations back in time, and implement several such structures, including priority queues, queues, dictionaries, and counters. we develop a semantics for tracing, extend an existing self-adjusting language, δml, and its implementation to support traceable data types, and present an experimental evaluation by considering a number of benchmarks. our experiments show dramatic improvements on space and time, sometimes by as much as two orders of magnitude.
evaluating the accuracy of java profilers. performance analysts profile their programs to find methods that are worth optimizing: the "hot" methods. this paper shows that four commonly-used java profilers (xprof , hprof , jprofile, and yourkit) often disagree on the identity of the hot methods. if two profilers disagree, at least one must be incorrect. thus, there is a good chance that a profiler will mislead a performance analyst into wasting time optimizing a cold method with little or no performance improvement. this paper uses causality analysis to evaluate profilers and to gain insight into the source of their incorrectness. it shows that these profilers all violate a fundamental requirement for sampling based profilers: to be correct, a sampling-based profilermust collect samples randomly. we show that a proof-of-concept profiler, which collects samples randomly, does not suffer from the above problems. specifically, we show, using a number of case studies, that our profiler correctly identifies methods that are important to optimize; in some cases other profilers report that these methods are cold and thus not worth optimizing.
finding low-utility data structures. many opportunities for easy, big-win, program optimizations are missed by compilers. this is especially true in highly layered java applications. often at the heart of these missed optimization opportunities lie computations that, with great expense, produce data values that have little impact on the program's final output. constructing a new date formatter to format every date, or populating a large set full of expensively constructed structures only to check its size: these involve costs that are out of line with the benefits gained. this disparity between the formation costs and accrued benefits of data structures is at the heart of much runtime bloat. we introduce a run-time analysis to discover these low-utility data structures. the analysis employs dynamic thin slicing, which naturally associates costs with value flows rather than raw data flows. it constructs a model of the incremental, hop-to-hop, costs and benefits of each data structure. the analysis then identifies suspicious structures based on imbalances of its incremental costs and benefits. to decrease the memory requirements of slicing, we introduce abstract dynamic thin slicing, which performs thin slicing over bounded abstract domains. we have modified the ibm j9 commercial jvm to implement this approach. we demonstrate two client analyses: one that finds objects that are expensive to construct but are not necessary for the forward execution, and second that pinpoints ultimately-dead values. we have successfully applied them to large-scale and long-running java applications. we show that these analyses are effective at detecting operations that have unbalanced costs and benefits.
mint: java multi-stage programming using weak separability. multi-stage programming (msp) provides a disciplined approach to run-time code generation. in the purely functional setting, it has been shown how msp can be used to reduce the overhead of abstractions, allowing clean, maintainable code without paying performance penalties. unfortunately, msp is difficult to combine with imperative features, which are prevalent in mainstream languages. the central difficulty is scope extrusion, wherein free variables can inadvertently be moved outside the scopes of their binders. this paper proposes a new approach to combining msp with imperative features that occupies a "sweet spot" in the design space in terms of how well useful msp applications can be expressed and how easy it is for programmers to understand. the key insight is that escapes (or "anti-quotes") must be weakly separable from the rest of the code, i.e. the computational effects occurring inside an escape that are visible outside the escape are guaranteed to not contain code. to demonstrate the feasibility of this approach, we formalize a type system based on lightweight java which we prove sound, and we also provide an implementation, called mint, to validate both the expressivity of the type system and the effect of staging on the performance of java programs.
safe programmable speculative parallelism. execution order constraints imposed by dependences can serialize computation, preventing parallelization of code and algorithms. speculating on the value(s) carried by dependences is one way to break such critical dependences. value speculation has been used effectively at a low level, by compilers and hardware. in this paper, we focus on the use of speculation by programmers as an algorithmic paradigm to parallelize seemingly sequential code. we propose two new language constructs, speculative composition and speculative iteration. these constructs enable programmers to declaratively express speculative parallelism in programs: to indicate when and how to speculate, increasing the parallelism in the program, without concerning themselves with mundane implementation details. we present a core language with speculation constructs and mutable state and present a formal operational semantics for the language. we use the semantics to define the notion of a correct speculative execution as one that is equivalent to a non-speculative execution. in general, speculation requires a runtime mechanism to undo the effects of speculative computation in the case of mis predictions. we describe a set of conditions under which such rollback can be avoided. we present a static analysis that checks if a given program satisfies these conditions. this allows us to implement speculation efficiently, without the overhead required for rollbacks. we have implemented the speculation constructs as a c# library, along with the static checker for safety. we present an empirical evaluation of the efficacy of this approach to parallelization.
ur: statically-typed metaprogramming with type-level record computation. dependent types provide a strong foundation for specifying and verifying rich properties of programs through type-checking. the earliest implementations combined dependency, which allows types to mention program variables; with type-level computation, which facilitates expressive specifications that compute with recursive functions over types. while many recent applications of dependent types omit the latter facility, we argue in this paper that it deserves more attention, even when implemented without dependency. in particular, the ability to use functional programs as specifications enables statically-typed metaprogramming: programs write programs, and static type-checking guarantees that the generating process never produces invalid code. since our focus is on generic validity properties rather than full correctness verification, it is possible to engineer type inference systems that are very effective in narrow domains. as a demonstration, we present ur, a programming language designed to facilitate metaprogramming with first-class records and names. on top of ur, we implement ur/web, a special standard library that enables the development of modern web applications. ad-hoc code generation is already in wide use in the popular web application frameworks, and we show how that generation may be tamed using types, without forcing metaprogram authors to write proofs or forcing metaprogram users to write any fancy types.
z-rays: divide arrays and conquer speed and flexibility. arrays are the ubiquitous organization for indexed data. throughout programming language evolution, implementations have laid out arrays contiguously in memory. this layout is problematic in space and time. it causes heap fragmentation, garbage collection pauses in proportion to array size, and wasted memory for sparse and over-provisioned arrays. because of array virtualization in managed languages, an array layout that consists of indirection pointers to fixed-size discontiguous memory blocks can mitigate these problems transparently. this design however incurs significant overhead, but is justified when real-time deadlines and space constraints trump performance. this paper proposes z-rays, a discontiguous array design with flexibility and efficiency. a z-ray has a spine with indirection pointers to fixed-size memory blocks called arraylets, and uses five optimizations: (1) inlining the first n array bytes into the spine, (2) lazy allocation, (3) zero compression, (4) fast array copy, and (5) arraylet copy-on-write. whereas discontiguous arrays in prior work improve responsiveness and space efficiency, z-rays combine time efficiency and flexibility. on average, the best z-ray configuration performs within 12.7% of an unmodified java virtual machine on 19 benchmarks, whereas previous designs have two to three times higher overheads. furthermore, language implementers can configure z-ray optimizations for various design goals. this combination of performance and flexibility creates a better building block for past and future array optimization.
the reachability-bound problem. we define the reachability-bound problem to be the problem of finding a symbolic worst-case bound on the number of times a given control location inside a procedure is visited in terms of the inputs to that procedure. this has applications in bounding resources consumed by a program such as time, memory, network-traffic, power, as well as estimating quantitative properties (as opposed to boolean properties) of data in programs, such as information leakage or uncertainty propagation. our approach to solving the reachability-bound problem brings together two different techniques for reasoning about loops in an effective manner. one of these techniques is an abstract-interpretation based iterative technique for computing precise disjunctive invariants (to summarize nested loops). the other technique is a non-iterative proof-rules based technique (for loop bound computation) that takes over the role of doing inductive reasoning, while deriving its power from the use of smt solvers to reason about abstract loop-free fragments. our solution to the reachability-bound problem allows us to compute precise symbolic complexity bounds for several loops in .net base-class libraries for which earlier techniques fail. we also illustrate the precision of our algorithm for disjunctive invariant computation (which has a more general applicability beyond the reachability-bound problem) on a set of benchmark examples.
printing floating-point numbers quickly and accurately with integers. we present algorithms for accurately converting floating-point numbers to decimal representation. they are fast (up to 4 times faster than commonly used algorithms that use high-precision integers) and correct: any printed number will evaluate to the same number, when read again. our algorithms are fast, because they require only fixed-size integer arithmetic. the sole requirement for the integer type is that it has at least two more bits than the significand of the floating-point number. hence, for ieee 754 double-precision numbers (having a 53-bit significand) an integer type with 55 bits is sufficient. moreover we show how to exploit additional bits to improve the generated output. we present three algorithms with different properties: the first algorithm is the most basic one, and does not take advantage of any extra bits. it simply shows how to perform the binary-to-decimal transformation with the minimal number of bits. our second algorithm improves on the first one by using the additional bits to produce a shorter (often the shortest) result. finally we propose a third version that can be used when the shortest output is a requirement. the last algorithm either produces optimal decimal representations (with respect to shortness and rounding) or rejects its input. for ieee 754 double-precision numbers and 64-bit integers roughly 99.4% of all numbers can be processed efficiently. the remaining 0.6% are rejected and need to be printed by a slower complete algorithm.
type-preserving compilation of end-to-end verification of security enforcement. a number of programming languages use rich type systems to verify security properties of code. some of these languages are meant for source programming, but programs written in these languages are compiled without explicit security proofs, limiting their utility in settings where proofs are necessary, e.g., proof-carrying authorization. others languages do include explicit proofs, but these are generally lambda calculi not intended for source programming, that must be further compiled to an executable form. a language suitable for source programming backed by a compiler that enables end-to-end verification is missing. in this paper, we present a type-preserving compiler that translates programs written in fine, a source-level functional language with dependent refinements and affine types, to dcil, a new extension of the .net common intermediate language. fine is type checked using an external smt solver to reduce the proof burden on source programmers. we extract explicit lcf-style proof terms from the solver and carry these proof terms in the compilation to dcil, thereby removing the solver from the trusted computing base. explicit proofs enable dcil to be used in a number of important scenarios, including the verification of mobile code, proof-carrying authorization, and evidence-based auditing. we report on our experience using fine to build reference monitors for several applications, ranging from a plugin-based email client to a conference management server.
bamboo: a data-centric, object-oriented approach to many-core software. traditional data-oriented programming languages such as dataflow languages and stream languages provide a natural abstraction for parallel programming. in these languages, a developer focuses on the flow of data through the computation and these systems free the developer from the complexities of low-level, thread-oriented concurrency primitives. this simplification comes at a cost --- traditional data-oriented approaches restrict the mutation of state and, in practice, the types of data structures a program can effectively use. bamboo borrows from work in typestate and software transactions to relax the traditional restrictions of data-oriented programming models to support mutation of arbitrary data structures. we have implemented a compiler for bamboo which generates code for the tilepro64 many-core processor. we have evaluated this implementation on six benchmarks: tracking, a feature tracking algorithm from computer vision; kmeans, a k-means clustering algorithm; montecarlo, a monte carlo simulation; filterbank, a multi-channel filter bank; fractal, a mandelbrot set computation; and series, a fourier series computation. we found that our compiler generated implementations that obtained speedups ranging from 26.2x to 61.6x when executed on 62 cores.
smooth interpretation. we present smooth interpretation, a method to systematically approximate numerical imperative programs by smooth mathematical functions. this approximation facilitates the use of numerical search techniques like gradient descent for program analysis and synthesis. the method extends to programs the notion of gaussian smoothing, a popular signal-processing technique that filters out noise and discontinuities from a signal by taking its convolution with a gaussian function. in our setting, gaussian smoothing executes a program according to a probabilistic semantics; the execution of program p on an input x after gaussian smoothing can be summarized as follows: (1) apply a gaussian perturbation to x -- the perturbed input is a random variable following a normal distribution with mean x. (2) compute and return the expected output of p on this perturbed input. computing the expectation explicitly would require the execution of p on all possible inputs, but smooth interpretation bypasses this requirement by using a form of symbolic execution to approximate the effect of gaussian smoothing on p. the result is an efficient but approximate implementation of gaussian smoothing of programs. smooth interpretation has the effect of attenuating features of a program that impede numerical searches of its input space -- for example, discontinuities resulting from conditional branches are replaced by continuous transitions. we apply smooth interpretation to the problem of synthesizing values of numerical control parameters in embedded control applications. this problem is naturally formulated as one of numerical optimization: the goal is to find parameter values that minimize the error between the resulting program and a programmer-provided behavioral specification. solving this problem by directly applying numerical optimization techniques is often impractical due to the discontinuities in the error function. by eliminating these discontinuities, smooth interpretation makes it possible to search the parameter space efficiently by means of simple gradient descent. our experiments demonstrate the value of this strategy in synthesizing parameters for several challenging programs, including models of an automated gear shift and a pid controller.
complete functional synthesis. synthesis of program fragments from specifications can make programs easier to write and easier to reason about. to integrate synthesis into programming languages, synthesis algorithms should behave in a predictable way - they should succeed for a well-defined class of specifications. they should also support unbounded data types such as numbers and data structures. we propose to generalize decision procedures into predictable and complete synthesis procedures. such procedures are guaranteed to find code that satisfies the specification if such code exists. moreover, we identify conditions under which synthesis will statically decide whether the solution is guaranteed to exist, and whether it is unique. we demonstrate our approach by starting from decision procedures for linear arithmetic and data structures and transforming them into synthesis procedures. we establish results on the size and the efficiency of the synthesized code. we show that such procedures are useful as a language extension with implicit value definitions, and we show how to extend a compiler to support such definitions. our constructs provide the benefits of synthesis to programmers, without requiring them to learn new concepts or give up a deterministic execution model.
memsat: checking axiomatic specifications of memory models. memory models are hard to reason about due to their complexity, which stems from the need to strike a balance between ease-of-programming and allowing compiler and hardware optimizations. in this paper, we present an automated tool, memsat, that helps in debugging and reasoning about memory models. given an axiomatic specification of a memory model and a multi-threaded test program containing assertions, memsat outputs a trace of the program in which both the assertions and the memory model axioms are satisfied, if one can be found. the tool is fully automatic and is based on a sat solver. if it cannot find a trace, it outputs a minimal subset of the memory model and program constraints that are unsatisfiable. we used memsat to check several existing memory models against their published test cases, including the current java memory model by manson et al. and a revised version of it by sevcik and aspinall. we found subtle discrepancies between what was expected and the actual results of test programs.
parameterized verification of transactional memories. we describe an automatic verification method to check whether transactional memories ensure strict serializability a key property assumed of the transactional interface. our main contribution is a technique for effectively verifying parameterized systems. the technique merges ideas from parameterized hardware and protocol verification--verification by invisible invariants and symmetry reduction--with ideas from software verification--template-based invariant generation and satisfiability checking for quantified formulæ (modulo theories). the combination enables us to precisely model and analyze unbounded systems while taming state explosion. our technique enables automated proofs that two-phase locking (tpl), dynamic software transactional memory (dstm), and transactional locking ii (tl2) systems ensure strict serializability. the verification is challenging since the systems are unbounded in several dimensions: the number and length of concurrently executing transactions, and the size of the shared memory they access, have no finite limit. in contrast, state-of-the-art software model checking tools such as blast and tvla are unable to validate either system, due to inherent expressiveness limitations or state explosion.
supporting speculative parallelization in the presence of dynamic data structures. the availability of multicore processors has led to significant interest in compiler techniques for speculative parallelization of sequential programs. isolation of speculative state from non-speculative state forms the basis of such speculative techniques as this separation enables recovery from misspeculations. in our prior work on cord [35,36] we showed that for array and scalar variable based programs copying of data between speculative and non-speculative memory can be highly optimized to support state separation that yields significant speedups on multicore machines available today. however, we observe that in context of heap-intensive programs that operate on linked dynamic data structures, state separation based speculative parallelization poses many challenges. the copying of data structures from non-speculative to speculative state (copy-in operation) can be very expensive due to the large sizes of dynamic data structures. the copying of updated data structures from speculative state to non-speculative state (copy-out operation) is made complex due to the changes in the shape and size of the dynamic data structure made by the speculative computation. in addition, we must contend with the need to translate pointers internal to dynamic data structures between their non-speculative and speculative memory addresses. in this paper we develop an augmented design for the representation of dynamic data structures such that all of the above operations can be performed efficiently. our experiments demonstrate significant speedups on a real machine for a set of programs that make extensive use of heap based dynamic data structures.
cache topology aware computation mapping for multicores. the main contribution of this paper is a compiler based, cache topology aware code optimization scheme for emerging multicore systems. this scheme distributes the iterations of a loop to be executed in parallel across the cores of a target multicore machine and schedules the iterations assigned to each core. our goal is to improve the utilization of the on-chip multi-layer cache hierarchy and to maximize overall application performance. we evaluate our cache topology aware approach using a set of twelve applications and three different commercial multicore machines. in addition, to study some of our experimental parameters in detail and to explore future multicore machines (with higher core counts and deeper on-chip cache hierarchies), we also conduct a simulation based study. the results collected from our experiments with three intel multicore machines show that the proposed compiler-based approach is very effective in enhancing performance. in addition, our simulation results indicate that optimizing for the on-chip cache hierarchy will be even more important in future multicores with increasing numbers of cores and cache levels.
a method for application evaluations in context of enterprise architecture. this contribution presents a method to evaluate business applications. the method allows for using artifacts of enterprise architectures. artifacts like business processes or hardware can exert influence on the application's quality and thus have to be regarded. a central aspect is to modularize the method's basic components, which are key figures and their metrics. the modularization allows for flexible usage and customization to fit the heterogeneity of different organizations. to make the method more intuitive, a key figure is encapsulated by a fuzzy logic based component denoted as criterion. a criterion addresses a certain aspect to evaluate an application and allows for using linguistic terms to represent a key figure.
energy-aware dual-mode voltage scaling for weakly hard real-time systems. in this paper we study the problem of minimizing energy while ensuring the designated qos requirements for weakly hard realtime systems on a dual-mode variable voltage processor. the qos is quantified with the (m, k)-constraints. we proposed a dynamic scheduling strategy, based on pattern variation and the enhanced dual priority scheduling, to guarantee the (m, k)-constraints while optimizing the energy consumption. the simulation results demonstrate that our proposed techniques can achieve significant energy saving performance while ensuring the (m, k)-guarantee.
a format to design narrative multimedia applications for cultural heritage communication. in this paper we introduce the "instant multimedia" (imm) approach to ict-based communication. imm is characterized for being quick (30 days to deliver the application) and low cost (5,000 us dollars for a medium-sized applications). it is therefore a suitable solution in a number of occasions: when a sudden communication need arises, in the case of small institutions with scarce resources, when niche target and content are to be addressed etc. we will introduce a concrete case-study, "enigma helvetia tales", a multimedia (text, images, audios) and multichannel (web, cd-rom, podcast) application that was developed in spring 2008 in the occasion of an art exhibition held in lugano (ch). an extensive user study -- involving more than 200 users -- proved the efficacy of the approach in terms of satisfaction, better understanding of content, knowledge retention and enhanced curiosity towards the event.
a framework for handling revisions in distributed ontologies. one of the important issues in ontology management is handling incoming updates and dealing with possible inconsistencies that they may induce. this is even more challenging in the context of a modular and distributed representation, because of the side-effects of the propagation of changes to the other connected or related ontologies. in this paper, we analyze the notion of ontology revision in a distributed ontology representation. we introduce a revision operator for distributed ontologies and show that it satisfies important postulates for knowledge base revision. in addition, based on a tableau algorithm for alc ontologies, we propose an algorithm for applying the received changes and revising the original ontology through the proposed operator.
transformation templates: adding flexibility to model-driven engineering of user interfaces. model-based user interface (ui) development environments are aimed at generating one or many uis from one or many models. model-driven engineering (mde) of uis is assumed to be superior to those environments since they make the ui design knowledge visible, explicit, and external, for instance as model-to-model transformations and model-to-code compilation rules. these transformations and rules are often considered inflexible, complex to express, and hard to develop by ui designers and developers who are not necessarily experts in mde. in order to overcome these shortcomings, this paper introduces "transformation templates", an approach that is adding flexibility to the mde of uis by externalizing the transformation logic of ui models, and making it editable, customizable, and reusable. it is also intended to make it easier for ui designers to specify the transformations. a transformation template specifies a series of parameters that enable designers to parameterize the model transformation process at the concept level that is of a higher level of abstraction than at the level of physical properties of ui widgets. this paper presents an editor for transformation templates and an example of parameter type. transformation templates can be effectively and efficiently used in any circumstances where the transformation knowledge needs to be modified by non-experts, such as in domain specific languages where flexibility is required.
software adaptation patterns for service-oriented architectures. this paper describes the concept of software adaptation patterns and how they can be used in software adaptation of service-oriented architectures. the patterns are described in terms of a three-layer architecture for self-management. a software adaptation pattern defines how a set of components that make up an architecture pattern dynamically cooperate to change the software configuration to a new configuration. in our approach, adaptation connectors are introduced to encapsulate adaptation state machine models so that the adaptation patterns can be more reusable. a change management model for dynamically evolving service-oriented applications is also described with a case study.
on the use of patterns to recover business processes. legacy systems keep key business knowledge from companies over time. this knowledge is hidden in the source code lines and must be recovered through software archeology processes to maintain and help the legacy systems to evolve, so that the roi and lifespan of those systems can be improved. this paper proposes a set of patterns to obtain, in a deterministic manner, business models from the source code of legacy systems. thus, the business process models recovered from the legacy systems preserve the business knowledge and can be used to modernize and maintain the legacy systems.
an approach to developing reusable domain services for service oriented applications. today, the software environment paradigm is shifting to service-oriented computing, based on key features that reflect business concerns. the soma and soup methodologies can be used to develop service-oriented applications. however, these approaches focus on developing monolithic service applications. therefore, we propose a feature-based reusable domain service development approach to create more reusable and flexible domain services offering commonality and variability.
scalable analysis of collective behaviour in smart service systems. the long term vision of smart service systems in which electronic environments are made sensitive and responsive to the presence of, possibly many, people is gradually taking shape through a number of pilot projects. the purposes of such systems vary from intelligent homes that assist their inhabitants to make their lives more independent and comfortable to much larger environments such as airports in which people are provided with context aware, personalised, adaptive and anticipatory services that are most relevant for them given their location and their current activities. this paper is concerned with the exploration of scalable formal models that can address the collective behaviour of a large number of people moving through a smart environment.
quality and perceived usefulness of process models. modeling is now an essential ingredient in business process management and information systems development. the general usefulness of models in these areas is therefore generally accepted. it is also undisputed that the quality of the models has a significant impact on their usefulness. in the literature we can find any number of quality metrics, but hardly any study that investigates their relation with (perceived) usefulness and none that considers their relative impact on usefulness. we take a look at some of the most frequent quality dimensions and their relative impact on the perceived usefulness of models.
cooperation enablement for centralistic early warning systems. from large-scale acquisition of information on security incidents by early warning systems (ews) arises the opportunity to draw up a situation picture that allows detection of trends and upcoming threats. while the need for integrating such information is widely accepted, there typically exist reservations concerning the distribution of information allowing outsiders insights into security incidents of individual organizations. these reservations so far prohibit the deployment of ews in practice. in order to make ews practical we study the conflicting interests of all involved parties regarding information processed by the ews, and propose a resolution of the conflict based on information reduction by pseudonymization. we develop a fair balanced trade-off respecting most interests of parties as well as privacy of involved persons and propose privacy mechanisms to be applied to respective information. an implementation of the privacy mechanisms is experimentally evaluated to demonstrate the practicality of our approach.
modeling pomdps for generating and simulating stock investment policies. analysts and investors use technical analysis tools to create charts and price indicators that help them in decision making. chart patterns and indicators are not deterministic and even analysts may have different interpretations, depending on their experience, background and emotional state. in this way, tools that allow users to formalize these concepts and study investment policies based on them can provide a more solid basis for decision making. in this paper, we present a tool we have built to formally model stock investment contexts as partially observable markov decision processes (pomdp), so that investment policies in the stock market can be generated and simulated, taking into consideration the accuracy of technical analysis techniques. in our models, we assume that the trend for the future prices is part of the state at a certain time and can be "partially observed" by means of technical analysis techniques. historical series are used to provide probabilities related to the accuracy of technical analysis techniques, which are used by an automated planning algorithm to create policies that try to maximize the profit. the tool also provides flexibility for trying and comparing different models.
automatic k-complex detection using hjorth parameters and fuzzy decision. k-complex is a stereotyped transient wave in the human electroencephalogram (eeg), it appears frequently during sleep recordings. its role and significance have been disregarded since its discovery until recently, when the american association of sleep medicine (aasm) proposed a new classification of sleep with a relevant role for the k-complexes in the definition of the sleep stages. it is now one of the key features that contribute to sleep stage assessment. k-complexes are associated with sleep arousal and can occur spontaneously or as an evoked response to external stimuli. since the eeg has a stochastic nature, k-complex can have a wide variety of shapes and it can be difficult to distinguish it from other eeg waves. the visual scoring of k-complex is a very complex, time consuming and expensive procedure and reported agreement between human expert scorers is very poor. in this paper a new method for k-complex automatic detection is presented. the detection method is based on hjorth parameters and employs fuzzy decision. the performance of the detection system is compared to the visual human scoring.
organizing master data management: findings from an expert survey. master data management (mdm) is defined as an application-independent process which describes, owns and manages core business data entities. the establishment of the mdm process is a business engineering (be) tasks which requires organizational design. this paper reports on the results of a questionnaire survey among large enterprises aiming at delivering insight into what tasks and master data classes mdm organizations cover ("scope") and how many people they employ ("size"). the nature of the study is descriptive, i.e. it allows for the identification of patterns and trends in organizing the mdm process.
goal and model driven design of an architecture for a care service platform. service-oriented architecture holds the potential of allowing the development on-the-fly of flexible applications that can adapt rapidly by combining and reusing existing services. we believe that in order to react swiftly and coherently to changes, an architecture must provide a capability to capture how services, and the more complex applications based on them, realize business motivations. this research develops a framework and a method for goal-driven, model-driven, and service-oriented design. the framework includes goal modeling in the mda stack, from cim to code. by using this framework, we are able to create a system that is compatible with its business goals, and thus is flexible when business demands change. a case study demonstrates how our framework can be used to combine mda, soa, and goal modeling with business rules as an architecture for a care service platform.
nudge: intermediaries' role in interdependent network security. by employing an interdependent security game-theoretic framework, we study how individual internet service providers can coordinate the investment decisions of end users to improve the security of the overall system. we study two different forms of intervention: rebates in combination with penalties (pay for outcome) and costsubsidies (pay for effort).
spanders: distributed spanning expanders. we consider self-stabilizing and self-organizing distributed construction of a spanner that forms an expander. we use folklore results to randomly define an expander graph. given the randomized nature of our algorithms, a monitoring technique is presented for ensuring the desired results. the monitoring is based on the fact that expanders have a rapid mixing time and the possibility of examining the rapid mixing time by o(nlogn) short (o(log4 n) length) random walks even for non regular expanders. we then employ our results to construct a hierarchical sequence of spanders, each of them an expander spanning the previous one. such a sequence of spanders may be used to achieve different quality of service assurances in different applications. several snap-stabilizing algorithms that are used to utilize the monitoring are presented, including reset and token tracing algorithms for message passing systems.
constrained colocation mining: application to soil erosion characterization. spatial data mining has been extensively studied for gis applications. to deal with a fast increasing of data, investigations for spatial data analysis are needed. in this paper, we propose a spatial data mining approach which adapts the existing colocation concept to characterize soil erosion hazard. in order to manage this task, we put the colocation mining task into a more general framework. based on this framework, new constraints linked to domain knowledge are pushed into the colocation mining algorithm. finally, we developed a prototype and lead experiments on real scientific datasets.
efficient inline caching without dynamic translation. inline caching is a very important optimization technique for interpreters, effectively eliminating the overhead in dynamic typing. unfortunately, inline caches are mostly used together with dynamic translation, which is expensive in terms of implementation costs. we present efficient inlinecaching techniques that do not require dynamic translation.
evolutionary testing of object-oriented software. it is estimated that 80% of software development cost is spent on detecting and fixing defects. to tackle this issue, a number of tools and testing techniques have been developed to improve the existing testing framework. although techniques such as static analysis, random testing and evolutionary testing have been used to automate the testing process, it is not clear what is the best approach. previous research on evolutionary testing has mainly focused on procedural programming languages with code coverage as the main optimization parameter. in this work, we present an approach that combines a genetic algorithm with static analysis to automatically test eiffel classes using the number of faults found as the optimization parameter. a total of 115 experiments on 22 eiffel classes were executed to evaluate the effectiveness of evolutionary testing compared to the results obtained by running a random test case generator for 15, 30 and 60 minutes. the results show a genetic algorithm combined with static analysis can considerably increase the number of faults found compared to a random testing approach. in some cases, evolutionary testing found more faults in 15 minutes than a random testing strategy found in 60 minutes.
named and default arguments for polymorphic object-oriented languages: a discussion on the design implemented in the scala language. this article describes the design and implementation of named and default arguments in the scala programming language. while these features are available in many other languages there are significant differences in the actual implementations. we present a design that unifies the most reasonable properties for an object-oriented language and provides new possibilities by allowing default arguments on generic and implicit parameters. we also present a solution for the problem of writing a lightweight generic update function for algebraic datatypes.
extending a hybrid tag-based recommender system with personalization. tagging activity has been recently identified as a potential source of knowledge about personal interests, preferences, goals, and other attributes known from user models. tags themselves can be therefore used for finding personalized recommendations of items. this paper proposes a semantic extension for a hybrid tag-based recommender system, which suggests similar web pages based on the similarity of their tags. the semantic extension aims at discovering tag relations which are not considered in basic syntax similarity. with the goal of generating more semantically grounded recommendations, the proposal extends a hybrid tag-based recommender system with a semantic factor, which looks for tag relations in different semantic sources. in order to evaluate the benefits acquired with the semantic extension, we have compared the new findings with results from a previous experiment involving 38 people from 12 countries using data from del.icio.us.
mining uncertain data for frequent itemsets that satisfy aggregate constraints. many existing algorithms mine transaction databases of precise data for frequent itemsets. however, there are situations in which the user is interested in only some tiny portions of all the frequent itemsets, and there are also situations in which data in the transaction databases are uncertain. this calls for both (i) constrained mining (for finding only those frequent itemsets that satisfy user constraints, which express the user interest) and (ii) mining uncertain data. in this paper, we propose a tree-based algorithm that effectively mines transaction databases of uncertain data for only those frequent itemsets satisfying the user-specified aggregate constraints. the algorithm avoids candidate generation and pushes the aggregate constraints inside the mining process, which reduces computation and avoids unnecessary constraint checking.
clearminer: a new algorithm for mining association patterns on heterogeneous time series from climate data. recently, improvements in sensor technology contributed to increasing in spatial data acquisition. the use of remote sensing in many countries and states, where agricultural business is a large part of their gross income, can provide a valuable source to improve their economy. the combination of climate and remote sensing data can reveal useful information, which can help researchers to monitor and estimate the production of agricultural crops. data mining techniques are the main tools to analyze and extract relationships and patterns. in this context, this paper presents a new algorithm for mining association patterns in geo-referenced databases of climate and satellite images. the clearminer (climate association patterns miner) algorithm identifies patterns in a time series and associates them with patterns in other series within a temporal sliding window. experiments were performed with synthetic and real data of climate and noaa-avhrr sensor for sugar cane fields. results show a correlation between agroclimate time series and vegetation index images. rules generated by our new algorithm show the association patterns in different periods of time in each time series, pointing to a time delay between the occurrences of patterns in the series analyzed, corroborating what specialists usually forecast having the burden of dealing with many data charts.
s-search: finding rfid tags using scalable and secure search protocol. massively deploying rfid systems that preserve data integrity and security is a major challenge of the coming years. since rfid tags are extremely constrained in time and space, enforcing high level of security with excessive cryptographic computation is not possible. secured mechanisms for tag authentication have been in the midst of researcher's interest for almost a decade. one extension of rfid authentication is rfid tag searching, which has not been given much attention so far. but we firmly believe that in near future tag searching will be a significant issue. and tag searching need to be scalable as rfid tags are deployed comprehensively within a system. in this paper we propose a scalable and lightweight rfid tag searching protocol. this protocol can search a particular tag efficiently as the approach is not based on exhaustive search. this approach does not employ extreme computing or cryptographic functions. our proposed scalable search protocol is secured against major security threats and it is suitable to be used in numerous real life situations.
profit and penalty aware (pp-aware) scheduling for tasks with variable task execution time. as computing devices and the internet technology advances, real-time on-line services are emerging. different from traditional real-time applications for which the scheduling objective is to meet task deadlines, the optimization goal for on-line service systems is to maximize profit obtained through providing timely services. for this class of applications, there are two distinctive characteristics: (1) tasks, i.e., client requests, are associated with a pair of unimodal time functions, representing system accrued profit when a task is completed before its deadline, or accrued penalty if otherwise; and (2) requests execution times vary in a wide range. the paper presents a new scheduling algorithm, i.e., the profit and penalty aware (pp-aware) scheduling algorithm, with an objective to maximize system's total accrued profit. our simulation results have empirically shown the advantages, in respect of system total accrued profit, of the proposed algorithm over other commonly used scheduling algorithms, such as earliest deadline first (edf) and utility accrual (ua) algorithms.
an approach for architectural layer recovery. in this paper we present an approach to identify software layers for the understanding and evolution of object oriented software systems. the approach first identifies relations between the classes and then uses the kleinberg algorithm to group them into layers. additionally to assess the approach and the underlying techniques, the paper also presents a prototype of a supporting tool to identify layers within java software systems. to assess the feasibility of both the approach and the system prototype, the results from a case study conducted on an open source java software system are presented and discussed.
online mining of temporal maximal utility itemsets from data streams. data stream mining has become an emerging research topic in the data mining field, and finding frequent itemsets is an important task in data stream mining with wide applications. recently, utility mining is receiving extensive attentions with two issues reconsidered: first, the utility (e.g., profit) of each item may be different in real applications; second, the frequent itemsets might not produce the highest utility. in this paper, we propose a novel algorithm named guide (generation of temporal maximal utility itemsets from data streams) which can find temporal maximal utility itemsets from data streams. a novel data structure, namely, tmui-tree (temporal maximal utility itemset tree), is also proposed for efficiently capturing the utility of each itemset with one-time scanning. the main contributions of this paper are as follows: 1) guide is the first one-pass utility-based algorithm for mining temporal maximal utility itemsets from data streams, and 2) tmui-tree is efficient and easy to maintain. the experimental results show that our approach outperforms other existing utility mining algorithms like two-phase algorithm under the data stream environments.
an electronic-signature based circular resolution database system. secure and efficient decision making processes are of particular importance especially for small and medium-sized enterprises. in this context, delocalization of responsible decision makers often leads to decision making processes relying on circular resolutions. although circular resolutions based on written consent are usually efficiently manageable for a limited number of decision makers, involving a potential large number of persons inevitably complicates these processes in practice. in this paper, a circular resolution database system that addresses this problem is introduced. our solution, which is based on the austrian citizen card concept, makes use of qualified electronic signatures that provide means for secure authentication of users as well as for electronic signing of digital documents. by enhancing decision making processes in terms of security, usability, and effectiveness while assuring auditing acceptability, the presented circular resolution database system especially contributes to the future competitiveness of small and medium-sized enterprises.
a well-founded approach to service modelling with casl4soa: part 1 (service in isolation). we propose in this paper the first part of casl4soa a notation and a technique to model a soa (service oriented architecture), i.e., here we consider only services in isolation. our casl4soa approach is to provide a well-founded modelling to soa, using the casl-ltl formal specification language as an underlying foundation. we explore then the various possible visual presentation of the casl4soa notation, so as to ensure as much as possible readability and communicability. given the casl-ltl concept of a simple system as a labelled transition system we propose a new way to model the services that is not object-oriented. while modelling the static, the behavioural, and the semantic aspects of a service, we pay a specific attention to the protocols between the provider and the consumer of the service for which we propose either a logical specification of their properties, or a constructive specification expressed by interaction machines. our ideas are illustrated by the example of a printing service offered by a printer to a user.
can complexity, coupling, and cohesion metrics be used as early indicators of vulnerabilities? it is difficult to detect vulnerabilities until they manifest themselves as security failures in the operational stage of software, because the security concerns are not addressed or known sufficiently early during software development. complexity, coupling, and cohesion (ccc) related software metrics can be measured during the earlier phases of software development. if empirical relationships can be discovered between ccc metrics and vulnerabilities, these metrics could aid software developers to take proactive actions against potential vulnerabilities in software. in this paper, we conduct an extensive case study on mozilla firefox to provide empirical evidence on how vulnerabilities are related to complexity, coupling, and cohesion. we find that ccc metrics are correlated to vulnerabilities at a statistically significant level. we further examine the correlations to determine which level (design or code) of ccc metrics are better indicators of vulnerabilities. we also observe that the correlation patterns are stable across multiple releases of the software. these observations show that ccc metrics can be dependably used as early indicators of vulnerabilities in software.
towards automatic extraction of epistemic items from scientific publications. the exponential growth of the world wide web in the last decade, brought with it an explosion in the information space. one, heavily affected area is the scientific literature, where finding relevant work in a particular field, and exploring links between relevant publications represents a cumbersome task. in this paper we make the initial steps in the direction of automatic extraction of epistemic items (i.e. claims, positions, arguments) from scientific publications. our approach will provide the foundation for a comprehensive solution that will partly alleviate the information overload problem. we detail the actual extraction process, the evaluation we have performed and relevant use-cases for our work.
an approach based upon owl-s for method fragments documentation and selection. it is currently admitted in both mainstream software engineering and agent-oriented software engineering that there is no one-size-fit-all methodology or process. one solution is proposed by the situational method engineering paradigm that provides means for constructing ad-hoc software engineering processes following an approach based on the reuse of portions of existing design processes, the so called method fragments, stored in a repository called method base. one problem raised by this type of approaches is to describe or document fragments and to choose among existing fragments in order to build a new process. the approach proposed in this paper uses owl-s and documents fragments as services in order to semantically annotate methodologies concepts and fragments. a scenario illustrating an example of fragment selection is reported.
a secure multiparty computation privacy preserving olap framework over distributed xml data. privacy preserving distributed olap is becoming a critical challenge for next-generation business intelligence (bi) scenarios, due to the "natural suitability" of olap in analyzing distributed massive bi repositories in a multidimensional and multigranularity manner. in particular, in these scenarios xml-formatted bi repositories play a dominant role, due to the wellknow amenities of xml in modeling and representing distributed business data. however, while privacy preserving distributed data mining has been widely investigated, very few efforts have focused on the problem of effectively and efficiently supporting privacy preserving olap over distributed collections of xml documents. in order to fulfill this gap, we propose a novel secure multiparty computation (smc)-based privacy preserving olap framework for distributed collections of xml documents. the framework has many novel features ranging from nice theoretical properties to an effective and efficient protocol. the efficiency of our approach has been validated by an experimental evaluation over distributed collections of synthetic xml documents.
image representation and classification based on data compression. with the development of the information technology, the number of different electronic information has been increased rapidly. in which, for enormous number of digital images the demand of automatic classification technology exceeded human processing capacity. as an automatic classification technique, representing and classifying text-transformed image based on data compression is proposed in this paper. in the step of transforming image into text, image is divided into segments which are replaced as characters. then, the similarity between compressibility vectors is used in the classification step. in which, we focus on the compressibility of the text string. finally, the effectivity of the proposed method is verified in our experiments.
traveling among clusters: a way to reconsider the benefits of the cluster hypothesis. relying on the cluster hypothesis which states that relevant documents tend to be more similar one to each other than to non-relevant documents, most of information retrieval systems organizing search results as a set of clusters seek to gather all relevant documents in the same cluster. we propose here to reconsider the benefits of the entailed concentration of the relevant information. contrary to what is commonly admitted, we believe that systems which aim to distribute the relevant documents in different clusters, since being more likely to highlight different aspects of the subject, may be at least as useful for the user as systems gathering all relevant documents in a single group. since existing evaluation measures tend to greatly favor the latter systems, we first investigate ways to more fairly assess the ability to reach the relevant information from the list of cluster descriptions. at last, we show that systems distributing the relevant information in different clusters may actually provide a better information access than classical systems.
a heterogeneous approach to service-oriented systems specification. service-oriented architecture (soa) is a relatively new approach to software system development. it divides system functionality to independent, loosely coupled, interoperable services. in this paper we propose a new heterogeneous specification approach for soa systems where a heterogeneous structured specification consists of a number of specifications of individual services written in a "local" logic and where the specification of their interactions is separately described in a "global" logic. a main feature of our global logic is the possibility of describing the dynamic change of service communications over time. our approach is based on the theory of institutions: we show that both logics form institutions and that these institutions are connected by an institution comorphism. we illustrate our approach by a simple scenario of an e-university management system and show the power of the heterogeneous specification approach by a compositional refinement of the scenario.
an empirical investigation on the relation between analysis models and source code comprehension. this paper presents a controlled experiment to investigate whether the comprehension of source code increases in case novice software engineers use abstract software models produced in the early phase of the software development, i.e., requirements analysis. the study has revealed that there is not significant difference in the comprehension of source code achieved by using or not abstract software models.
paving the road for formally defined architecture description in software development. informal and formal approaches to documenting software architecture design offer disjoint advantages and disadvantages. informal approaches are often used in practice since they are easily accessible and support creativity and flexibility during design. but they are hard to maintain and validate. this is the strength of formally defined approaches, which can be automatically processed, maintained and validated, but are expensive to use. combining the advantages of both approaches promises to increase the reach of formal approaches and to make the aforementioned advantages more accessible. we present an approach that offers a seamless transition from relaxed and informal architecture descriptions to a detailed and formally defined architecture definition.
an approach to intelligently crop and scale video for broadcast applications. within the scope of the eu-funded project portivity (portable interactivity), an application has been developed, that automatically modifies sdtv (standard definition television) sports productions for viewing on mobile tv displays by means of intelligent cropping and scaling. it crops regions of interest of sports productions based on a smart combination of production metadata and systematic video analysis methods. this approach allows a context-based composition for cropped images. it provides a differentiation between the original sd-version of the production and the processed one adapted to the requirements for mobile tv. envisaged is the integration of the tool in post-production and live workflows.
dynamic context-aware business process: a rule-based approach supported by pattern identification. making a business process more dynamic is an open issue, and we think it is feasible if we decompose the business process structure in a set of rules, like eca (event condition action) rules, each of them representing a transition of the business process, i.e. an edge of the business process graph structure. as a consequence the business process engine can be realized by reusing and integrating an existing rule engine. we are proposing a way for representing dynamic business process in terms of rules based on patterns identification. with this approach it is easy to apply on a business process instance both user-based personalization rules and automatic rules inferred by an underlying context-aware system.
mining temporal relationships among categories. temporal text mining deals with discovering temporal patterns in text over a period of time. a theme evolution graph (teg) is used to visualize when new themes are created and how they evolve with respect to time. teg, however, does not represent relationships among themes (or categories) that share same timestamp. we focus on identifying such relationships and represent them in relationship evolution graph (reg). we favorably compare passage misclassification and association rule mining with three existing approaches, namely kl divergence (kld), consistent bipartite spectral co-partitioning graph (cbscg) and document misclassification. our evaluations indicate that association rule mining approach statistically significantly (99% confidence) outperforms the other existing approaches, while passage misclassification approach is the second most effective approach.
mitigating denial of capability attacks using sink tree based quota allocation. network capabilities have been proposed to prevent distributed denial of service (ddos) attacks proactively. a capability is a ticket-like token, checkable by routers, that a server can issue for legitimate traffic. still, malicious hosts may swamp a server with requests for capability establishment, essentially causing possible denial-of-capability (doc). in this paper, we propose an algorithm to mitigate doc attacks. the algorithm divides the server's capacity for handling capability requests into quotas. quotas are allocated based on a sink tree architecture. randomization and bloom filters are used as tools against threats (attacking scenarios). we both analytically and experimentally show that legitimate hosts can get service with guaranteed probability. we also address issues on fault-tolerance and the deployment of the approach proposed.
a novel stable and low-maintenance clustering scheme. clustering is one of the most important features of mobile ad hoc networks (manets), enabling their performance and scalability for a large number of mobile nodes. the design of clustering schemes is quite complex, due to the highly dynamic topology of such networks. until now, a wide variety of clustering schemes has been proposed, focusing different metrics and purposes. in this article a distinct, fully distributed and clusterhead-free, clustering scheme is proposed, named as novel stable and low-maintenance clustering scheme for mobile ad hoc networks (nsloc). the proposed clustering scheme was evaluated by simulation on topologies with up to 1000 nodes and variable node speeds. results showed that the two mains goals of nsloc, namely stability and low-maintenance, were fulfilled, while introducing less overhead than existing clustering solutions.
refinement of models of software components. models of software components at different levels of abstraction, component interfaces, contracts, implementations and publications are important for component-based design. refinement relations among models at the same level and between different levels are essential for model-driven development of components. classical refinement theories mainly focus on verification and put little attention on design. therefore, most of them are not suitable for component-based model-driven development (cb-mdd). to address this issue, in this paper, we propose two refinement relations for cb-mdd, that is a trace-based refinement and a state-based refinement. both are discussed in the framework of rcos, which is a formal model of component and object systems. these refinement relations provide different granularity of abstraction and can capture the intuition that a refined component provides "more" and "better" services to the environment. we also show how to extend these refinement relations to allow us to compare contracts, components and publications with different interfaces by exploiting the primitive operator internalizing over contracts, components and publications.
an evaluation of the sinuosity effect on visualization of rdp simplified maps: an empirical study. the process of line simplification consists of extracting a subset of points whose trend approximates the original line according to a more or less significant tolerance. in spite of the apparent straightforwardness of this concept, the process meant to accomplish this task may result very complex. the goal of the research we are carrying out is to contribute to the automation of the simplification process for visualization purposes by investigating what and how specific map and system properties affect it. to this aim, users' capability to recognize the differences between a map and a simplified version of it, may represent a key factor in evaluating how much a map can be automatically simplified preserving its visual content in terms of features and relationships. in this paper we illustrate the results collected through an empirical experimental study in which we have focused our observation on line sinuosity and users' perception related to its changes. results processed by this study demonstrate that the sinuosity is a relevant factor, whose management may contribute to automate the simplification process for visualization purposes.
towards higher throughput and energy efficiency in dense wireless ad hoc and sensor networks. traditional single-channel mac protocols for wireless ad hoc and sensor networks favor energy-efficiency over throughput. more recent multi-channel mac protocols display higher throughput but less energy efficiency. in this paper we propose namac, a negotiator-based multi-channel mac protocol in which specially designated nodes maintain the sleeping and communication schedules of nodes. negotiators facilitate the assignation of channels and coordination of communications windows, thus allowing individual nodes to sleep and save energy. simulation results show that na-mac, at high network loads, consumes 36% less energy while providing 25% more throughput than comparable state-of-art multi-channel mac protocols for ad hoc networks. additionally, we propose a lightweight version of namac and show that it outperforms (55% higher throughput with 36% less energy) state of art mac protocols for wireless sensor networks.
quality of service for multicasting using nice. to distribute data from one sender to multiple receivers efficiently and concurrently, multicasting is one of the most appropriate mechanisms. application layer multicast (alm), often also referred to as overlay multicast, has been introduced to overcome the limitations of ip multicast. the om-qos (quality of service for overlay multicast) framework aims to enable qos for different alm protocols. we applied the om-qos mechanisms to the overlay multicast protocol nice and performed evaluations in qos environments using resource reservations and measurement based qos. our evaluations show that we can support the qos requirements of all paths in the multicast tree, while introducing an acceptable overhead in terms of delay.
a method for business process decomposition based on the separation of concerns principle. functional decomposition breaks down a business process into a set of progressively more detailed activities. it facilitates the modular design of a system, the reuse of its parts and also contributes to increasing its comprehensibility. but achieving these qualities requires a business process to be decomposed consistently. separation of concerns is the principle of separating a system into distinct features with a minimum of overlapping. this paper proposes using this principle to consistently decompose a business process into its constituent activities. an activity is modelled as a collaboration between role types that are played by entities. the decomposition method successively separates the overlapping roles until an activity is specified by the collaboration of an orthogonal set of role types. this method facilitates the consistent decomposition of a business process and the unambiguous identification of its atomic activities.
sysml-based requirement modeling environment for multicore embedded system. the requirements engineering plays an important role during the lifespan of a complex system development project. the writing of system requirements in system developments process is through the natural language frequently. natural language usually contains uncertainty. additionally, requirements engineer lacks field knowledge and often shows shortages of relevant experiences. all these cause equivocal and wrong requirements analysis of the system requirements specification. in order to avoid these, the appropriate requirements modeling tools and can offer engineer's appropriate mechanism to understand what the customer want, analyze the requirements, assess feasibility, consult the rational solution, clearly point out the solution, confirm the specification, and reduce the possibility that the specific project may fail. we have presented a requirements modeling tool based on sysml. this research copes with model driven approach and requirements definition template for precise, consistent requirements specifications definition. mda offers a procedure of analyzing the requirements to prevent a specific project from procrastinating. it assists users to confirm and improve the exactness of the requirements contents via the "profile" of the requirements. the ocl leads users to write the template of the requirements, and brings in the characteristics of multi-core embedded system in the requirements documents through "profile".
a hardware peripheral for java bytecodes translation acceleration. java has gained great popularity in a wide range of applications. just-in-time compilation is crucial for providing efficient execution of java programs, but it is generally a hard task, not suited for embedded systems. this paper presents a hardware acceleration unit for efficient execution of jit translation in embedded socs. the translation is limited to only first level optimizations, which include translation of java bytecodes to native risc instructions (stack folding). for experimentation, we developed a soc with arm7tdmi processor. in a f 80nm asic technology and 80mhz clock, we measured a speed up of up to 4 times over the software only jit translation.
expressing aspectual interactions in requirements engineering: experiences in the slot machine domain. aspect oriented requirements engineering (aore) provides support for modularizing crosscutting requirements. in the context of an industrial project in the domain of slot machines we needed to perform aore, with a special emphasis on dependencies and interactions among concerns. we were however unable to find any report of large-scale industrial applications of aore approaches that treat dependencies and interactions. we therefore evaluated two aore approaches: theme/doc and mdsocre, to establish their applicability in our setting. in this paper we report on our experience, showing successful uses of both approaches as well as where they fall short. we furthermore propose possible enhancements for both approaches, to address these limitations.
personal identification using periocular skin texture. in this paper, we propose the use of periocular skin texture as a biometric modality. salient skin texture features are extracted and represented using local binary patterns (lbps). matching is performed using cityblock distance as a measure of similarity. we investigate the use of each periocular region separately in addition to their use in conjunction. verification and identification experiments involving over 400 subjects were performed using a datasets constructed from the frgc and feret datasets. reported recognition rates of nearly 90%, demonstrate the effectiveness of this novel technique.
automatic recognition of finger spelling for libras based on a two-layer architecture. different feature extraction techniques have been applied to the problem of automatic finger spelling (and gesture) recognition problem. however, different hand postures and gestures with different complexities have been given the same space representation. our approach tries to get rid off the assumption that one size fits all. a two level architecture was investigated where signs with similar hand postures were grouped together for a preliminary artificial neural network (ann) classification. a second ann was applied to disambiguate the confusions among symbols, using another space representation. our results indicate that it is possible to improve recognition rates with this approach.
energy-efficient real-time scheduling of multimedia tasks on multi-core processors. in recent years, various multi-core architectures have become popular selections for the designs of mobile platforms. with the strong computing demands from many multimedia applications, how to energy-efficiently utilize the computing power of mobile platforms without violations of timing constraints has become a critical design problem. in this paper, a data-partitioning-based approach is proposed to explore the parallelism of multimedia workload processing over multiple cores. dynamic voltage scaling and dynamic power management strategies are both considered in the dynamic scaling of the computing power of cores and the adjustment of the set of active cores, respectively. the practicability and the energy efficiency of the proposed algorithms were evaluated by a series of experiments and simulations, for which we have encouraging results.
using passage-based language model for opinion detection in blogs. in this work, we evaluate the importance of passages in blogs especially when we are dealing with the task of opinion detection. we argue that passages are basic building blocks of blogs. therefore, we use passage-based language modeling approach as our approach for opinion finding in blogs. our decision to use language modeling (lm) in this work is totally based on the performance lm has given in various opinion detection approaches. in addition to this, we propose a novel method for bi-dimensional query expansion with relevant and opinionated terms using wikipedia and relevance-feedback mechanism respectively. we also compare the impacts of two different query terms weighting (and ranking) approaches on final results. besides all this, we also compare the performance of three passage-based document ranking functions (linear, avg, max). for evaluation purposes, we use the data collection of trec blog06 with 50 topics of trec 2006 over trec provided best baseline with opinion finding map of 0.3022. our approach gives a map improvement of almost 9.29% over best trec provided baseline (baseline4).
a semantic web-based approach for personalizing news. hermes is an ontology-based framework for building news personalization services. this framework consists of a news classification phase, which classifies the news, a knowledge base updating phase, which keeps the knowledge base up-to-date, a news querying phase, allowing the user to search the news for concepts of interest, and a results presentation phase, showing the returned news items. the focus of this paper is on how to keep the knowledge base up-to-date. for this purpose, we elaborate on the updating phase that searches for key events in the news. using rules based on patterns and actions, these events can be extracted and the knowledge base is updated. this is a semi-automatic process since user validation is required before updating the knowledge base.
energy efficient program updating for sensor nodes with flash memory. updating sensor node programs is an essential task for maintaining stability and modifying the characteristics of wireless sensor networks. the updating mechanism must consider energy and memory efficiency, because of resource constraints of sensor nodes. in this paper, we propose a novel program updating mechanism, which considers resource constraints of sensor nodes. the proposed mechanism was designed for sensor nodes with the nor flash memory. this is generally used to store program image. it was designed to minimize the number of flash write/erase operations, which consume a great deal of energy, and to provide wear-leveling for the nor flash memory. we set a function as the basic unit of program updating, and partition a function into fixed-sized blocks that can be separately relocated in memory. experimental results show that the proposed mechanism outperforms other mechanisms in terms of energy, memory and wear-leveling for flash memory.
content cloaking: preserving privacy with google docs and other web applications. web office suites such as google docs offer unparalleled collaboration experiences in terms of low software requirements, ease of use, data ubiquity, and availability. when the data holder (google, microsoft, etc.) is not perceived as trusted though, those benefits are considered at stake with important privacy requirements. content cloaking is a lightweight, cryptographic, client-side solution to protect content from data holders while using web office suites and other "web 2.0", ajax-based, collaborative applications.
dual-level defense for networks under ddos attacks. ddos has become one of the thorniest problems in the internet, and aims to deny legitimate users of the services they should have. in this paper, we introduce novel dual - level attack defense against the ddos attacks. the macroscopic level detectors attempt to detect voluminous congestion inducing attacks which cause apparent slowdown in network functionality. the subsequent characterization process identifies these large volumes attacks that have been detected early in transit domain. the microscopic level detectors detect sophisticated attacks that cause network performance to degrade gracefully and remain undetected in transit domain. the subsequent characterization process identifies such attacks that have been detected at border routers in stub domain near the victim. we employ the concepts of change point detection on entropy with time to improve the detection rate. honeypots help achieve high detection and filtering accuracy. in addition to being competitive than other techniques, the defense works well in the presence of different ddos attacks. the compromise of detection and characterization accuracy and time of confirming is a critical aspect and the proposed technique provides the quite demanded solution.
timing analyzing for systems with execution dependencies between tasks. in this paper, a novel approach to timing analysis of complex real-time systems with intricate execution dependencies between tasks, such as asynchronous message-passing and globally shared state variables, is presented. by applying the method to a model taken from a real robotic control system, we show the benefit, in terms of reduced pessimism, when compared to a combination of standard static wcet analysis and response-time analysis.
a cytoscape based framework for efficient sub-graph isomorphic protein-protein interaction motif lookup. study of interactomes requires assembling complex tools, ontologies and online interaction network databases and so on to validate hypotheses and gain insight. one of the major bottlenecks is the discovery of similar or isomorphic subgraphs in very large interactomes and cross referencing the relationships a set of proteins or genes share. these interactomes are so large that most traditional subgraph isomorphism computation tools are unable to handle efficiently as stand alone tool, or as part of systems such as r. in this paper, we present a cytoscape plugin to compute and discover isomorphic subnetworks in large interactomes based on a novel and efficient isomorphic subgraph computation method developed in our laboratory. given an input interactome and a given query subnetwork, the plugin can efficiently compute interactome subnetworks similar to the query network, and cross reference the results from go or other interactome databases with the aid of other available cytoscape plugins such as bingo. we describe the tool with respect to real life applications biologists may want to contemplate.
using interaction requirements to operationalize usability. in the context of today's software development, usability is often seen as a fuzzy concept: although considered important for the overall success of a software product, usability is not taken into account systematically during development, and effective human-computer interaction design depends in many cases on the whim of individual developers. this paper presents inspire, a pragmatic approach to operationalizing particular usability facets by specifying interaction requirements. interaction elements of a use case-based functional specification are identified and categorized. based on this categorization, matching interaction attributes, i.e. patterns of interaction design, are selected from a library of interaction attributes known to improve usability, and are further refined to meet the specific software functionality, user profiles, and context of use. the resulting interaction requirements are both realizable and testable, thus operationalizing usability in a way that allows developers to consider usability aspects explicitly during software design, implementation and test.
monitoring mpi programs for performance characterization and management control. monitoring distributed programs on high performance supercomputers is a challenging task, yet it is essential for the proper administration of the machines and for users to understand what their program is doing on production runs. to this end, we created a flexible monitoring capability for a major class of scientific applications, programs using mpi, that efficiently gathers information from the distributed program and collects it at a central point. this data can then be used to both understand application-centric issues and system-centric issues; and for improvement, administration, and maintenance of both the complex applications producing important scientific results and the complex systems that execute them.
efficient mapping and voltage islanding technique for energy minimization in noc under design constraints. voltage islanding technique in network-on-chip (noc) can significantly reduce the computational energy consumption by scaling down the voltage levels of the processing elements (pes). this reduction in energy consumption comes at the cost of the energy consumption of the level shifters between voltage islands. moreover, from physical design perspective it is desirable to have a limited number of voltage islands. considering voltage islanding during mapping of the pes to the noc routers can significantly reduce both the computational and the level-shifter energy consumptions and the communication energy consumption on the noc links. in this paper, we formulate the problem as an optimization problem with an objective of minimizing the overall energy consumption constrained by the performance in terms of delay and the maximum number of voltage islands. we provide the optimal solution to our problem using mixed integer linear program (milp) formulation. we also propose a heuristic based on random greedy selection to solve the problem. experimental results using e3s benchmark applications and some real applications show that the heuristic finds near-optimal solution in almost all cases in a very small fraction of the time required to achieve the optimal solution.
transport congestion events detection (tced): towards decorrelating congestion detection from tcp. tcp(transmission control protocol) uses a loss-based algorithm to estimate whether the network is congested or not. the main difficulty for this algorithm is to distinguish spurious from real network congestion events. other research studies have proposed to enhance the reliability of this congestion estimation by modifying the internal tcp algorithm. in this paper, we propose an original congestion event algorithm implemented independently of the tcp source code. basically, we propose a modular architecture to implement a congestion event detection algorithm to cope with the increasing complexity of the tcp code and we use it to understand why some spurious congestion events might not be detected in some complex cases. we show that our proposal is able to increase the reliability of tcp newreno congestion detection algorithm that might help to the design of detection criterion independent of the tcp code. we find out that solutions based only on rtt (round-trip time) estimation are not accurate enough to cover all existing cases. furthermore, we evaluate our algorithm with and without network reordering where other inaccuracies, not previously identified, occur.
constraint processing in relational database systems: from theory to implementation. constraint satisfaction problems (csp) are frequently solved over data residing in relational database systems. in such scenarios, the database is typically just used as a data storage back end. however, there exist important advantages, such as the wide availability of database practices and tools for modeling, to having database systems that are capable of natively modeling and solving csps. this paper introduces general concepts and techniques to extend a database system with constraint processing capabilities. input csps are modeled via sql, augmented with a non-deterministic guess operator as introduced by cadoli and mancini (tplp 2007). problems are represented with a combination of internal relations and parse trees, and are translated to a flexible intermediate problem representation that is subsequently translated into several common representations for sat. benchmarks with a prototype system show the feasibility of the approach and demonstrate the promise of a strong integration of csp solvers and database systems.
a time optimal algorithm for evaluating tree pattern queries. the tree pattern matching, which is used to find all occurrences of a tree pattern in an xml database, is a core operation for xml query processing. in this paper, we study this issue and discuss a new algorithm for processing unordered tree pattern queries, which works bottom-up. its main idea is a new labeling method for tree pattern queries. both the time and space complexities of the algorithm are bounded by o(|d|&middot;|q|), where q stands for a tree pattern and d is a largest data stream associated with a node q of q, which contains the database nodes that match the node predicate at q. in addition, the algorithm can be adapted to an indexing environment with xb-trees being used.
gray networking: a step towards next generation computer networks. modern networks are very complex. it is highly desirable to reduce management complexity in next generation network design. researchers have been seeking inspiration in natural observations to help better manage the ever increasing complexity of modern networks. bio-inspired and cognitive networks have shown tremendous promise towards better adapting networks to local stimuli intelligently, and to some extent without human intervention. in this paper, we discuss why the human brain is an excellent model for designing next generation smart networks. insights gained into macro-behavior of the human brain and its structural organization in the last decade are discussed. we identify features that can be adapted for network modeling. we then propose a network design model based on our understanding of the mind, how cognition is achieved, how memory is formed, etc. we end this paper with a real life network design problem we address using the proposed general model.
focused retrieval with proximity scoring. we present in this paper a scoring method for information retrieval based on the proximity of the query terms in the documents. the idea of the method first is to assign to each position in the document a fuzzy proximity value depending on its closeness to the surrounding keywords. these proximity values can then be summed on any range of text -- including any passage or any element -- and after normalization this sum is used as the relevance score for the extent. some experiments on the wikipedia collection used in the inex 2008 evaluation campaign are presented and discussed.
infrastructureless storage in dynamic environments. this paper studies the use of highly dynamic networks as infrastructures for persistent storage of data that offer services at specific geographical zones in a decentralized and distributed way. we propose a new algorithm, based on repulsion techniques, to self-organize the nodes that store and serve the information. in this work, we focus on the evaluation of our algorithm when faced to different simulated failures in order to measure its robustness and compare it with an existing approach.
where people and cars meet: social interactions to improve information sharing in large scale vehicular networks. efficient delivery of information in vehicular networks is crucial for the creation of useful and usable applications that need to cope with nomadic large-scale environments. context-awareness is often key to improve efficiency of a vehicle network since it allows to make informed decisions on the data routing, data locality and data necessity for different moving objects. in this paper we show how the social network of vehicle residents, as part of the overall context, allows us to improve the information sharing in the vehicular network significantly. we demonstrate this by deploying a social ubiquitous-help-system (uhs) on top of a vehicular network. we analyze how uhs operates in a vehicular network using a network simulation of realistic large scale vehicular movement data and show that the social interactions increases the efficiency, relevance and quality of information in data delivery.
a fast multiplier-less edge detection accelerator for fpgas. real time video is used in a wide variety of applications, ranging from video surveillance to medical imaging. these operations require significant amounts of processing power, especially when high resolution frames are used. a large percentage of processing time is used in edge detection kernels. thus, accelerating these kernels is of vital importance in achieving satisfactory frame rates for real time performance, even in high resolutions. this paper proposes a hardware coprocessor to the xilinx microblaze processor which accelerates edge detection significantly, while keeping the hardware requirements low, by using no multipliers at all. using a xilinx spartan 3e fpga, we have reported a frame rate of 157 frames per second in 4cif format, which corresponds to a 4x speedup over the software only solution. the speedup was achieved with only 1131 slices and 5 block rams hardware occupation, which makes the solution very attractable.
a fast approximation strategy for summarizing a set of streaming time series. summarizing a set of streaming time series is an important issue that reliably allows information to be monitored and stored in domains such as finance [12], networks [2, 1], etc. to date, most of existing algorithms have focused on this problem by summarizing the time series separately [12, 4]. moreover, the same amount of memory has been allocated to each time series. yet, memory management is an important subject in the data stream field, but a framework allocating equal amount of memory to each sequence is not appropriate. we introduce an effective and efficient method which succeeds to respond to both challenges: (1) a memory optimized framework along with (2) a fast novel sequence merging method. experiments with real data show that this method is effective and efficient.
t2d: a peer to peer trust management system based on disposition to trust. while the trust paradigm is essential to broadly extend the communication between the environment's actors, the evaluation of trust becomes a challenge when confronted with initializing the trust relationship and validating the transitive propriety of trust. whether between users or between organizations, existing solutions work to create for peer to peer networks, flexible and decentralized security mechanisms with trust approach. however, we have noticed that the trust management systems do not make the most of the subjectivity, more specifically, the notion of disposition to trust although this aspect of subjectivity has a strong influence on how to assess direct and a transitive trust. for this reason in our study, we tackle this problem by introducing a new distributed trust model called t2d (trust to distrust) which is designed to incorporate the following contributions: (i) a behavior model which represents the disposition to trust; (ii) initialization of trust relationship (direct and transitive) according to the defined behavior model.
optimized java card transaction mechanism based on object locality. transaction mechanism is important for reliable update of data on multi-application cards like java card. the improvement of transaction performance is critical because of limited resources on smart cards. this paper presents an optimized transaction mechanism based on high object locality on java card. at first, the analysis of object access and storage locality in applet transactions is given and then the transaction memory scheme in ram and eeprom is designed based on new value logging. secondly, we design the caching and search method of logging items based on access locality so as to improve the speed of the transaction logging. at last, we optimize the commit process based on storage locality in order to reduce the number of eeprom writing. the test results show that this optimized mechanism expands the transaction capacity and improves the execution speed of java card applets.
a lightweight framework for testing database applications. testing is one of the most expensive tasks in today's software development cycle and it is very important to devise techniques that speed up the whole testing process. in a recent paper [9], it has been shown that tests on database applications can be speeded up by using proper test execution strategies and test optimization algorithms. this papers proposes a new test execution strategy called safe-optimistic and a new test optimization algorithm called slice*. safe-optimistic is better than the strategy proposed in [9] in which it reduces testing time without jeopardizing test quality. slice* has a better performance than the test optimization algorithms in [9] in all cases and it keeps on performing well even if the subject application and the test suite evolve.
query-oriented clustering: a multi-objective approach. document clustering techniques have been widely applied in information retrieval to reorganize results furnished as a response to user's queries. following the cluster hypothesis which states that relevant documents tend to be more similar one to each other than to non-relevant ones, most of relevant documents are likely to be gathered in a single cluster. usually, systems organizing search results as a set of clusters consider this tendency as a very advantageous phenomenon, since it allows to filter the results provided by the initial search. adopting a different point of view, we rather consider the cluster hypothesis as a hindrance to the information access since it prevents the emergence of the various aspects of the query. the risk induced is to restrict the perception of the subject to an unique point of view. therefore, we propose to rather distribute the relevant documents over clusters by orienting the organization of the clusters according to the user's topic. the aim is to attract the clusters around the latter in order to highlight the thematic differences between documents which are strongly connected to the query. rather than modifying the inter-documents similarity computation as it is the case in several studies, we propose to directly act on the organization of the clusters by using a multi-objective evolutionary clustering algorithm which, besides the classical internal cohesion, also optimizes the query proximity of the clusters. first experimental results highlight the great benefit which may be gained by our way of query consideration.
transpeer: adaptive distributed transaction monitoring for web2.0 applications. in emerging web2.0 applications such as virtual worlds or social networking websites, the number of users is very important (tens of thousands), hence the amount of data to manage is huge and dependability is a crucial issue. the large scale prevents from using centralized approaches or locking/two-phase-commit approach. moreover, web2.0 applications are mostly interactive, which means that the response time must always be less than few seconds. to face these problems, we present a novel solution, transpeer, that allows applications to scale-up without the need to buy expensive resources at a data center. to this end, databases are replicated over a p2p system in order to achieve high availability and fast transaction processing thanks to parallelism. a distributed shared dictionary, implemented on top of a dht, contains metadata used for routing transactions efficiently. both metadata and data are accessed in an optimistic way: there is no locking on metadata and transactions are executed on nodes in a tentative way. we demonstrate the feasibility of our approaches through experimentation.
combining global and local information for enhanced deep classification. compared to traditional text classification with a flat category set or a small hierarchy of categories, classifying web pages to a large-scale hierarchy such as open directory project (odp) and yahoo! directory is challenging. while a recently proposed "deep" classification method makes the problem tractable, it still suffers from low classification performance. a major problem is the lack of training data, which is unavoidable with such a huge hierarchy. training pages associated with the category nodes are short, and their distributions are skewed. to alleviate the problem, we propose a new training data selection strategy and a na&iuml;ve bayes combination model, which utilize both local and global information. we conducted a series of experiments with the odp hierarchy containing more than 100,000 categories to show that the proposed method of using both local and global information indeed helps avoiding the training data sparseness problem, outperforming the state-of-art method.
semantic content distribution with aggregated profiles. content-based networks have similar characteristics with traditional publish/subscribe system. these networks are more dynamic, scalable and disseminate the data based on user interests. end users subscribe to network according to their interest profiles, publishers publish contents to the network and network delivers them asynchronously according to user subscriptions. expressive subscription methodology of user interests and compact interest representation is essential to build scalable content-based network. this paper presents an approach for distributing rdf documents in information dissemination network called semantic content-based network (scbn). this architecture supports information dissemination with complex information representation through graphs. this paper has the following two key contributions. in first part, we present a semantic based user profile description and methodology for user interest subscription to semantic content-based network. second part describes a distributed profile aggregation framework for generating generic and compact profiles in the network.
tracking random finite objects using 3d-lidar in marine environments. this paper presents a random finite set theoretic formulation for multi-object tracking as perceived by a 3d-lidar in a dynamic environment. it is mainly concerned with the joint detection and estimation of the unknown and time varying number of objects present in the environment and the dynamic state of these objects, given a set of measurements. this problem is particularly challenging in cluttered dynamic environments such as in urban settings or marine environments, because, given a measurement set, there is absolutely no knowledge of which object generated which measurement, and the detected measurements are indistinguishable from false alarms. the proposed approach to multi-object tracking is based on the rigorous theory of finite set statistics (fisst). the optimal bayesian multi-object tracking is not yet practical due to its computational complexity. however, a practical alternative to the optimal filter is the probability hypothesis density (phd) filter, that propagates the first order statistical moment of the full multi-object posterior distribution. in contrast to classical approaches, this random finite set framework does not require any explicit data associations. in this paper, a gaussian mixture approximation of the phd filter is applied to track variable number of objects from 3d-lidar measurements by estimating both the number of objects and their respective locations in each scan. experimental results obtained in marine environments demonstrate the efficacy and tracking performance of the proposed approach.
feature selection for ordinal regression. ordinal regression (also known as ordinal classification) is a supervised learning task that consists of automatically determining the implied rating of a data item on a fixed, discrete rating scale. this problem is receiving increasing attention from the sentiment analysis and opinion mining community, due to the importance of automatically rating increasing amounts of product review data in digital form. as in other supervised learning tasks such as (binary or multiclass) classification, feature selection is needed in order to improve efficiency and to avoid overfitting. however, while feature selection has been extensively studied for other classification tasks, is has not for ordinal regression. in this paper we present four novel feature selection metrics that we have specifically devised for ordinal regression, and test them on two datasets of product review data.
xtemplate 3.0: adding semantics to hypermedia compositions and providing document structure reuse. hypermedia composite templates define generic structures of nodes and links that can be reused in different document compositions. the xtemplate language is an xml-based solution for defining composite templates for hypermedia documents in order to embed semantics into a composition that does not have it in prior. the use of templates intend to facilitate the authoring of interactive applications in digital tv systems, as long as iptv systems. xtemplate 3.0 extends the previous xtemplate versions, incorporating new features to the language and increasing its expressiveness. as an application of xtemplate, this work extends ncl (nested context language) with xtemplate, adding semantics to ncl contexts and providing document structure reuse.
semiotic inspection method in the context of educational simulation games. software process simulation is increasingly being used as an approach for analyzing complex business, for supporting management planning, for helping with software process training and learning and for supporting the software process improvement. in addition to providing to users a simulation tool that supports all these aspects, it is also important to consider some other requirements during the tool's design, such as efficient and effective communication of the designer's message to the user. in this way, we show how semiotic concepts can be used in the analysis and generation of knowledge through the application of the semiotic inspection method (sim), a semiotic engineering evaluation method. in this paper we present a scientific application of sim to a software engineering simulation game focusing the analysis on feedback aspects and issues. the results go beyond the system analyzed and point to considerations regarding simulation games used in educational contexts.
a formal approach to reuse successful traceability practices in spl projects. software product line (spl) engineering has to deal with interrelated, complex models such as feature and architecture models, hence traceability is fundamental to keep them consistent. commonly, a traceability schema must be started from scratch from project to project. to avoid that, useful traceability practices to solve day to day problems should be modeled explicitly and kept as part of the traceability knowledge gained, and then organizations can reduce time and effort in implementing traceability in new projects. this paper presents an approach for formalizing and reusing traceability practices in spl engineering. using this formalization approach a traceability metamodel is defined, incorporating the particular traceability practices performed in spl engineering. customized traceability methodologies for spl projects will be systematically and formally generated from this metamodel. these resulting methodologies will have already incorporated the traceability knowledge proven as successful in previous projects, facilitating the reuse of such practices. in this paper, we focus specifically on the product derivation process, to show the advantages of this formalization approach to reuse traceability knowledge.
towards semantic-based adaptation decisions for context-aware mobile computing. this paper studies the problem of adaptation decisions for context-aware mobile computing. in most context-aware systems to date, context-aware adaptation decisions are made by developers during the design-time or compile-time. such approaches inevitably place an immense load on developers, especially in an extremely dynamic environment like mobile computing, to anticipate, formulate, and maintain adaptation rules. in this paper, we explore automated context-aware adaptation decisions at run-time to get around this problem. the resulting middleware system, campus, utilizes ontologies to capture the underlying semantics of involved entities, and perform dl and fol reasoning on these ontologies to automatically derive adaptation decisions at run-time. the campus implementation has been evaluated with a number of case studies. the results are significant in that they show that campus can greatly reduce the efforts required to developed context-aware mobile application without significant degradation in its performance.
an adaptive information extraction system based on wrapper induction with pos tagging. information extraction (ie) performs two important tasks: identifying certain pieces of information from documents and storing them for future use. this work proposes an adaptive ie system based on boosted wrapper induction (bwi), a supervised wrapper induction algorithm. however, some authors have shown that boosting techniques face difficulties during the processing of natural language texts. this fact became the rationale for coupling parts-of-speech tagging with the bwi algorithm in our proposed system. in order to evaluate its performance, several experiments were carried out on three standard corpora. the results obtained suggest that the union of pos tagging and bwi offers a small gain of 3--5% of performance over the original bwi algorithm for unstructured texts. these results position our system among the very best similar ie systems endowed with pos tagging, according to a comparison presented and discussed in the article.
detecting narrow passages in configuration spaces via spectra of probabilistic roadmaps. in this paper, we explore the connection between the spectral properties of a configuration space with those of the underlying probabilistic road map. we explore this relationship in a simple motion planning example which leads to a new method of characterizing narrow passages using the so called graph laplacian of the prm.
reactive parallel processing for synchronous dataflow. the control flow of common processors does not match the specific needs of reactive systems. key issues for these systems are preemption and concurrency, combined with timing predictability. to model reactive systems, synchronous programming languages are well-suited, which can be either synthesized to hardware or compiled to c and run on a normal processor. both of these approaches have significant drawbacks: the generation of hardware is inflexible, the timing analysis of the generated c code is complicated. we propose a special parallel processor, designed to execute programs written in the synchronous dataflow language lustre, or its graphical variant scade. this approach achieves an efficient but still predictable execution. we introduce the processor as well as compiler from lustre and scade. to validate our approach, we compare a prototype of the processor, running on an fpga, with a microblaze processor that executes c code generated from lustre programs.
using logic-based reduction for adversarial component recovery. a current means to protect intellectual property embedded in both circuits and software involves creating a functionally equivalent variant with subjective qualities related to difficulty of reverse engineering. in this paper, we consider the problem of protection in a smaller, generalized class of programs based on boolean logic primitives. we consider boolean logic reduction as one means to quantify hardness of undoing structural transformations designed to impede reverse engineering. we detail our experiences in using both commercial synthesis tools and organic red-team tools that simplify transformations using known basic logic patterns. using simple component recovery on candidate circuits, we show how specific variation methods impact adversarial analysis and posit relationships between specific transformations and corresponding difficulty of reversal.
checking concurrent contracts with aspects. the applicability of aspects as a means of implementing runtime contract checking has been demonstrated in prior work, where contracts are identified as cross-cutting concerns [12, 13]. checking contracts at runtime encounters a set of challenges within concurrent environments, such as the risk that evaluation will introduce deadlock to code which is otherwise deadlock-free. this paper presents a simple methodology for generating runtime contract checking aspects targeted at concurrent programs. the novel features of this approach allow contracts to depend on active objects without race conditions or deadlock, and addresses issues relating to timing and blame assignment. the cojava language is discussed whose tool-supported aspect generation methodology allows the correct checking of contracts predicated on active objects.
an improved wlan-first access scheme for umts/wlan integrated system. in a tunnel-wlan model of a umts/wlan interworking system, a user always prefers to access the wlan as soon as he/she moves to a wlan hotspot. thus a user never misses the higher bit rate of wlan as long as its bandwidth is available. we have examined that overall dropping probability of a request in a mixed cell (i.e., a umts cell with underlying wlans) improves if and only if the blocking probability of a request in wlan remains lower than that in the umts system. thus dropping probability increases with increasing blocking probability in wlan. we propose a wlan-first access scheme which transfers all blocked requests of wlan to overlaying umts system, thereby preventing compulsory dropping of blocked requests in wlan. this technique improves the request dropping probability in an entire mixed cell.
g-tries: an efficient data structure for discovering network motifs. in this paper we propose a novel specialized data structure that we call g-trie, designed to deal with collections of subgraphs. the main conceptual idea is akin to a prefix tree in the sense that we take advantage of common topology by constructing a multiway tree where the descendants of a node share a common substructure. we give algorithms to construct a g-trie, to list all stored subgraphs, and to find occurrences on another graph of the subgraphs stored in the g-trie. we evaluate the implementation of this structure and its associated algorithms on a set of representative benchmark biological networks in order to find network motifs. to assess the efficiency of our algorithms we compare their performance with other known network motif algorithms also implemented in the same common platform. our results show that indeed, g-tries are a feasible, adequate and very efficient data structure for network motifs discovery, clearly outperforming previous algorithms and data structures.
semantic scene detection system for baseball videos based on the mpeg-7 specification. in this paper, we proposed a content-based multimedia analysis/retrieval system mainly based on the mpeg-7 specification which is capable of handling the high-level content analysis such as the semantic scene detection for baseball broadcast videos. here, eight semantic scene classes were predefined for baseball videos. first, an effective shot boundary detection scheme based on scalable color histogram was proposed to segment a video into many shots. then, various visual features including field color features, skin color features, and camera motion information were extracted to analyze the semantics for each shot. according to the visual properties of different scenes, we developed a two-stage classification strategy for the semantic scene detection. finally, the experimental results showed that the proposed framework identifies eight semantic baseball scenes with 81% of precision rates and 84% of recall rates.
link prediction using probabilistic group models of network structure. modeling of complex networks is a crucial task such as in biology and social sciences. a large number of researches have been conducted for such a problem; however, most of them require explicit, specific prior knowledge on target networks. on the other hand, a few recent works on multinomial mixture models presented that those models do not require such explicit prior knowledge and turned out to be effective for the task of group detection of vertices such as in social networks. this paper focuses on another task, link prediction in such complex networks, using a bayesian multinomial mixture model, which assumes unobservable prior distributions over multinomial mixtures based on network structure and are estimated using bayesian inference via gibbs sampling. we demonstrate that link prediction performance was significantly improved using this method, compared to five conventional methods, through experiments using a metabolic network and a co-authorship network.
a morphologic three-stage approach for detecting exudates in color eye fundus images. an efficient detection of exudate lesions in color eye fundus images is an essential stage for grading the diabetic macular edema automatically. in this work, we present a new automatic method based on mathematical morphology to locate exudate lesions. the proposed method was evaluated using the publicly available diaretdb1 database, and it obtains 72.21% of mean sensitivity and 98.97% of mean specificity. this results indicate that our approach potentially can achieve a better performance than other known methods proposed in the literature.
a network polling solution through a p2p-based distributed management environment. network management involves several activities for operation, administration, and maintenance of network devices. among them, network polling is one of the most cpu and network-intensive tasks, showing serious scalability and fault tolerance drawbacks when executed through traditional management architectures. this way, alternative approaches have to be investigated and analyzed for the execution of such operation. this paper proposes a distributed network polling architecture through a p2p-based distributed management environment. it presents the model followed by the architecture, the polling architecture and services responsible by polling operations.
inductive reasoning and semantic web search. extensive research activities are recently directed towards the semantic web as a future form of the web. consequently, web search as the key technology of the web is evolving towards some novel form of semantic web search. a very promising recent approach to such semantic web search is based on combining standard web search with ontological background knowledge and using standard web search engines as the main inference motor of semantic web search. in this paper, we propose to further enhance this approach to semantic web search by the use of inductive reasoning. this adds the important ability to handle inconsistencies, noise, and incompleteness, which often occur in distributed and heterogeneous environments, such as the web. we report on a prototype implementation of the new approach and extensive experimental results.
an improved algorithm to enumerate all traces that sort a signed permutation by reversals. in 2008, braga et al. proposed an algorithm to perform the enumeration of traces that sort a signed permutation by reversals. this algorithm has exponential complexity in both time and space. the original implementation uses a special structure, to handle the information during the process. however, even with this structure, memory consumption is still a problem. in this work, we propose a stack structure to represent the set of traces that is being enumerated by the algorithm. this new structure consumes less memory and can be kept in the main memory, improving the space and time performance of the algorithm.
query systems in similarity-based databases: logical foundations, expressive power, and completeness. this paper presents logical foundations for an extension of codd's relational model of data which aims at utilizing various aspects of similarity in data processing. a need for development of solid foundations for such extensions, sometimes called similarity-based relational databases, has repeatedly been emphasized by leading database experts. this paper argues that, contrary to what may be perceived from the literature, solid foundations for similarity-based databases can be developed in a conceptually sound way. in this paper, we outline the foundations and propose two query systems for similarity-based databases: a domain relational calculus (drc) and a relational algebra (ra). we compare the expressive power of drc and ra in our model and prove relational completeness of ra over drc. a major implication of the paper is that similarity-based data querying can be made an integral part of an extended, similarity-based, relational model of data which is based on first-order predicate logics using residuated structures of truth values in much the same way as the querying in the codd's model is based on the classic first-order predicate logic.
separation of concerns in service-oriented applications based on pervasive design patterns. service-oriented computing (soc) allows developers to build applications by reusing and invoking web-accessible services. soc promotes loose coupling between applications and services, which has been mostly addressed by using techniques for separation of concerns (soc). contemporary soc development models based on soc either rely on difficult-to-adopt, ad-hoc programming facilities and languages or fail at isolating applications from details of the application-service interaction. we propose di4ws, a soc programming model that combines the well-known adapter and dependency injection patterns. we show that di4ws allows reducing couplings to services, which has a positive effect on application maintenance, without requiring developers to learn such facilities or languages. di4ws follows a contract-last approach to service invocation, whereby developers first code the logic of their applications and then non-invasively "adapt" and "inject" required services. an empirical comparison of di4ws with two related approaches to decouple services is also reported, showing that the di4ws versions of 4 evaluated applications used less memory and ran faster than the others.
distributed data stream classification for wireless sensor networks. it has been established experimentally that in-network processing in wireless sensor networks is the acceptable mode of operation. however, this solution is faced by resource constraints of the sensor nodes, especially when running traditional data mining techniques that tend to consume the resources rapidly. on the other hand, data stream mining algorithms still fall short with the limited computational capabilities of the nodes. these algorithms need real-time adaptation to availability of resources. distributed processing is also essential to produce a global model of the data streams emanated from the network. in this paper, we propose a novel distributed data stream classification technique that is able to adapt to availability of resources in wireless sensor networks.
efficiently detecting clusters of mobile objects in the presence of dense noise. we address the problem of detecting and tracking clusters of moving objects in very noisy environments. monitoring a crowded football stadium for small groups of individuals acting suspiciously is an example of one such environment. in this scenario the vast majority of individuals are not part of suspicious groups and are considered noise. existing spatio-temporal clustering algorithms are either incapable of detecting small clusters in extreme noise, or have high computation and storage requirements that prohibit their use in real-time alerting systems. we propose a technique called dynamic density based clustering (ddbc) that utilizes the relational history of the moving objects to increase the accuracy of the clustering algorithm. the incorporation of this information into the clustering algorithm is done efficiently and implicitly by using a relationship graph. the relationship graph incrementally estimates the strength of the relationships between moving objects. a modified dbscan algorithm is then used to find clusters of highly related objects from the relationship graph. we evaluate the ddbc technique experimentally on a number of data sets of mobile objects. the experiments show that ddbc outperforms both trajectory mining and moving cluster mining techniques in terms of accuracy, memory usage, and computation time as the density of noise increases.
energy-efficient scheduling on homogeneous multiprocessor platforms. low-power and energy-efficient system implementations have become very important design issues to extend operation duration or cut power bills. to balance the energy consumption resulting from the dynamic power consumption and the static power consumption, the concept of critical speed has been adopted widely in the literature. most scheduling algorithms for such systems assume that the critical speed is the lowest speed for scheduling and then perform job/task procrastination to turn the processor(s) to the dormant mode when there is no job for execution. this paper shows that the critical speed might be too optimistic and turning the processor(s) to the dormant mode might be energy-inefficient. by allowing tasks to run at lower speeds than the critical speed, in this paper, a new approximation algorithm is developed for homogeneous multiprocessor systems with a 1.21-approximation factor, which significantly improves the state-of-the-art approximation algorithm with a 1.667-approximation factor. performance evaluation shows the effectiveness of the proposed algorithm with comparison to the state-of-the-art approximation algorithm. our algorithm can reduce the energy consumption by at most 15% in our simulations.
the impact of random samples in ensemble classifiers. the use of ensemble classifiers, e.g., bagging and boosting, is wide spread to machine learning. however, most of studies in this area are based on empirical comparisons that suffer from a lack of care to the randomness of these methods. this paper describes the dangers of experiments with ensemble classifiers by analyzing the efficiency of bagging and boosting methods over 32 different data sets. the experiments show that variations due to randomness are often more relevant than the advantages among methods encountered in the literature. this paper main contribution is the claim, supported by statistical analysis, that no empirical comparison of ensemble classifiers can be scientifically done without paying attention to the random choices taken.
fact-oriented declarative semantic enterprise modeling. in this paper we will investigate the extent to which the extension of the fact-oriented approach with modeling constructs that cover the information-, the process- and behavioural perspectives can provide declarative modeling constructs for declarative semantic enterprise modeling.
generic flow-sensitive optimizing transformations in c++ with concepts. compilers are typically hardwired to attempt optimizations only on expressions involving particular built-in types. ideally, an optimizing compiler can recognize a rewrite opportunity whenever the operands in an expression satisfy the (algebraic) properties that justify the rewrite. this paper applies the principles and techniques of generic programming and the planned "concepts" language feature of c++ to approximate this ideal. concretely, a concept defines the signature and algebraic laws of a class of types. we attach rewrite rules to a concept, so that the rules apply to all types in the class defined by a concept. the annotation burden to a programmer is thus small---the declaration that a type models a particular concept is simultaneously taken as an annotation that enables optimizations. to increase the applicability of generic rewrite rules, we instantiate them to type-specific rules, enabling the use of data-flow information from the compiler's existing analyses, and interleave the application of rewrite rules with function inlining. our prototype is implemented as an extension of the conceptgcc compiler; our experiments show the approach is effective in eliminating abstraction penalties.
an improved k-view algorithm for image texture classification using new characteristic views selection methods. image texture classification plays an important role in the computer processing of images. many methods including the gray level co-occurrence (glco), local binary patterns and k-view algorithms for image texture classification have been proposed. there exist several variations of the k-view algorithms. among them, the k-view algorithm using rotation-invariant features can produce higher classification accuracy; however, the algorithm is not stable. this paper presents an improved k-view algorithm using new characteristic views selection methods. we propose three different methods for selecting characteristic views. the first method chooses characteristic views based on the interval of minimum mean gray level and maximum mean gray level of all views in the primitive set and then randomly select the same number of views in each sub-interval. the second method divides the sorted interval with equal sub-interval and then select one view randomly in each sub-interval. the third method chooses views in an equal distance starting from the minimum gray level in the sorted list. experimental results show that the proposed characteristic views selection methods improve the performance of the k-view algorithms. this improved k-view algorithm is more robust and accurate compared with the results of the previous k-view algorithms.
load forecasting applied to soft real-time web clusters. dynamic configuration techniques such as dvfs (dynamic voltage and frequency scaling) and turning on/off computers are well known ways to promote energy consumption reduction in web server clusters. this paper demonstrates how the application of forecasting methods improves energy savings in a soft real-time application, and compares it with other energy aware methods. instead of a synthetic workload, a real traffic pattern was used to make the experiments more realistic. our system promotes energy reduction while maintaining user's satisfaction with respect to deadlines being met. the results obtained show that prediction capabilities increase the qos of the system, while maintaining or improving the energy savings over state-of-the-art power management mechanisms.
detecting metamorphic malwares using code graphs. malware writers and detectors have been running an endless battle. self-defense is the weapon most malware writers prepare against malware detectors. malware writers have tried to evade the improved detection techniques of anti-virus(av) products. packing and code obfuscation are two popular evasion techniques. when these techniques are applied to malwares, they are able to change their instruction sequence while maintaining their intended function. we propose a detection mechanism defeating these self-defense techniques to improve malware detection. since an obfuscated malware is able to change the syntax of its code while preserving its semantics, the proposed mechanism uses the semantic invariant. we convert the api call sequence of the malware into a graph, commonly known as a call graph, to extract the semantic of the malware. the call graph can be reduced to a code graph used for semantic signatures of the proposed mechanism. we show that the code graph can represent the characteristics of a program exactly and uniquely. next, we evaluate the proposed mechanism by experiment. the mechanism has an 91% detection ratio of real-world malwares and detects 300 metamorphic malwares that can evade av scanners. in this paper, we show how to analyze malwares by extracting program semantics using static analysis. it is shown that the proposed mechanism provides a high possibility of detecting malwares even when they attempt self-protection.
searching for knee regions in multi-objective optimization using mobile reference points. evolutionary algorithms have amply demonstrated their effectiveness and efficiency in approximating the pareto front of different multi-objective optimization problems. fewer attentions have been paid to search for the preferred parts of the pareto front according to the decision maker preferences. knee regions are special portions of the pareto front containing solutions having the maximum marginal rates of return, i.e., solutions for which an improvement in one objective implies a severe degradation in at least another one. such characteristic makes knee regions of particular interest in practical applications from the decision maker perspective. in this paper, we propose a new updating strategy for a reference points based multi-objective evolutionary algorithm which forces this latter to focus on knee regions. the proposed idea uses a set of mobile reference points guiding the search towards knee regions. the extent of the obtained regions could be controlled by the means of a user-defined parameter. the verification of the proposed approach is assessed on two- and three-objective knee-based test problems a priori and interactively. the obtained results are promising.
chemical-inspired self-composition of competing services. this paper aims at pushing the clear relationship between software service composition and chemical dynamics a step forward. we developed a coordination model where services and clients are coordinated via a tuple space handling services as if they were interacting chemical substances: on the one hand, services get equipped with an "activity value" resembling chemical concentration and measuring their reactiveness as imposed by the tuple space; on the other hand, services automatically compose via interaction ports resembling chemical bonding. the tuple space enacts a feedback loop that regulates and balances the activity level of (atomic or composite) services, decreasing it over time as in chemical decay, but reinforcing it each time the service is correctly used. this behaviour promotes service competition: losing (i.e. unused) services literally extinguish. which services or service compositions survive competition is automatically decided solely based on resulting performance, i.e. the rate at which services are actually exploited.
a persistent hy-tree to efficiently support itemset mining on large datasets. this paper presents the hy-tree persistent tree structure that provides a compact representation of a transactional dataset for frequent itemset mining. the hy-tree is characterized by a hybrid structure that easily adapts to different data distributions. the data representation is complete, since no support threshold is enforced during the hy-tree creation process. the hy-tree can be profitably exploited by a variety of itemset mining algorithms (e.g., lcm v.2, nonordfp). it effectively supports the data retrieval step in the itemset mining process by reducing both the i/o cost and the memory requirements for data loading. experiments on large synthetic datasets show the compactness of the hy-tree data representation and the efficiency and scalability on large datasets of the mining algorithms supported by it.
a distributed protocol for ensuring replicated database consistency in mobile computing environments. a mobile replicated database is comprised of several mobile and fixed servers and clients interconnected through a wireless network. in order to ensure data consistency in mobile replicated databases, several replication control protocols have been proposed. however, most of them reveal relevant limitations, such as: possessing a single failure point and flooding the network with messages exchange. in this paper we introduce a protocol which guarantees data consistency of replicated databases in mobile computing. the proposed approach is completely distributed, avoids the existence of a single failure point, uses a read-any/write-any replication scheme, increases data availability, and reduces the number of messages exchanged among the replicated servers. furthermore, it allows the user to choose a transaction isolation level (degree in which the execution of a given transaction is isolated from all other concurrent transactions). experimental results show the potential efficiency of the proposed approach.
a supervisory control approach for safe behavior of service robot case study: friend. this paper presents an approach based on supervisory control theory for design of a safety controller in service robot system. as case study we focus on friend system and develop a discrete event controller for safety requirements, related to a part of the whole task to be accomplished by robot. the controller will be implemented in a safety module parallel to the system and by enabling the admissible sequences of events, keep the system safe and working according to the specifications.
secret interest groups (sigs) in social networks with an implementation on facebook. in this paper we present the first framework that allows the creation of secret interest groups (sigs) in online social networks; sigs are self managed groups formed outside of the social network, around secret, sensitive or private topics. members exchange credentials that can be used inside the social network to authenticate upon friendship requests or to secure user-generated content. to this end we present a set of cryptographic algorithms leveraging on well-studied primitives, and we describe a java implementation of the framework for facebook.
blade geometry design with kinematic ruled surface approximation. a blade geometry design method is proposed in this paper, which adopts a novel kinematic ruled surface approximation algorithm. the algorithm is applied to approximate a free-form blade surface as a ruled surface in order to reduce the manufacturing cost. by applying klein mapping and study mapping, a ruled surface in euclidean space is transformed to a curve on a dual unit sphere (dus). the kinematic ruled surface approximation algorithm is set up based on the novel definition of a spline on the dus and the corresponding spline interpolation algorithm. this representation of ruled surface links directly to the manufacture procedure.
towards lightweight self-configuration in wireless sensor networks. this paper proposes a new algorithm called sds for solving distributed constraint satisfaction problems in wireless sensor networks. it introduces minimal overhead by using piggybacking for information dissemination and is naturally insusceptible against message loss. partitioning into coordinating cliques has been used to demonstrate the feasibility of our approach.
proposal of an improved motion estimation module for svc. in october 2007 itu-t and mpeg organizations published the scalable video coding (svc) specification as an addendum to the h.264 standard. basically svc enables h.264 video encoders to support temporal, spatial and snr scalability. this new functionalities lead to more flexibility on bandwidth management and robustness against packet losses. it is therefore more suitable for heterogeneous multimedia applications like iptv and mobile networks. however implementations of svc specification are still limited due the augmented computational complexity. one of the most critical svc algorithms is the motion estimation module, which allows identification of extra intra and inter-layer redundancies. the great computation demand of this module is responsible for the large svc encoder latency time, restraining its use in real-time applications. we propose in this paper a new motion estimation approach specially designed to reduce memory accesses and data comparisons in order to increase performance. experimental results prove significant gains in speed (up to 6 times faster) with small effects on quality (less than 0.2 db).
botzilla: detecting the "phoning home" of malicious software. hosts infected with malicious software, so called malware, are ubiquitous in today's computer networks. the means whereby malware can infiltrate a network are manifold and range from exploiting of software vulnerabilities to tricking a user into executing malicious code. monitoring and detection of all possible infection vectors is intractable in practice. hence, we approach the problem of detecting malicious software at a later point when it initiates contact with its maintainer; a process referred to as "phoning home". in particular, we introduce botzilla, a method for detection of malware communication, which proceeds by repetitively recording network traffic of malware in a controlled environment and generating network signatures from invariant content patterns. experiments conducted at a large university network demonstrate the ability of botzilla to accurately identify malware communication in network traffic with very low false-positive rates.
an incremental algorithm for efficient unique signature discoveries on dna databases. dna signatures are distinct short nucleotide sequences that can be used to detect the presence of certain organisms and to distinguish that organisms from all other species. the signatures provide valuable information for many applications, such as pcr primer designs and microarray experiments. in practice, we use a discovery algorithm to discover unique signatures from dna databases, and then apply the signatures to microarray experiments. if the discovered result is not satisfying, we will change the parameter settings of the algorithm to get a new result. the process of changing parameter settings may be consecutively performed until a satisfying result is obtained, which is called consequtively multiple discoveries. the situation occurs frequently especially when we handle unfamiliar dna databases. the challenge is how to accomplish every new discoveries efficiently. the needs of consequtively multiple discoveries are not considered in existing discovery algorithms. in this paper, we propose an incremental algorithm specifically for consecutively multiple discoveries. the algorithm is designed based on the observations on the properties of the signatures. our algorithm finds out the new result by employing the previously discovered results as candidates rather than performing complete discoveries on the whole database. since the candidates in the incremental discovery are reduced and limited to the discovered signatures, the discovery process accelerates. compared with the typical discovery algorithms that perform complete discoveries on a whole database, our incremental algorithm saves at most 87% of the execution time in our experiments.
load balancing for structured p2p networks using the advanced finger selection algorithm (afsa). structured peer-to-peer (p2p) networks, such as networks based on distributed hash tables (dhts), can be enhanced by using load balancing mechanisms. current load balancing mechanisms are either trying to achieve even distribution of objects among nodes, make the address space as evenly populated as possible, or both. however, we have taken a different approach to load balancing in this paper and we have defined the advanced finger selection algorithm (afsa) which is not focused on balancing the objects among the nodes and does not require evenly populated address space. afsa is an algorithm which changes the way how nodes are selected as fingers to the overlay routing tables in structured p2p networks. we implemented the afsa algorithm for both chord and bamboo and we evaluated it with simulations.
dealing with anonymity in wireless sensor networks. nowadays wireless sensor networks (wsn) are used in many application contexts. data handled by wsn are required to be protected for privacy reasons since they can be directly or indirectly related to individuals. the problem of preventing the identification of individuals starting from their data, known as anonymity, is a fundamental requirement for privacy aware systems. this paper proposes a solution to guarantee anonymity for a wide spread type of wsn by means of privacy policies. the solution is based on a uml model that introduces the conceptual elements and guidelines that are needed to build privacy policies for wsn.
adsandbox: sandboxing javascript to fight malicious websites. we present adsandbox, an analysis system for malicious websites that focusses on detecting attacks through javascript. since, in contrast to java, javascript does not have any built-in sandbox concept, the idea is to execute any embedded javascript within an isolated environment and log every critical action. using heuristics on these logs, adsandbox decides whether the site is malicious or not. in contrast to previous work, this approach combines generality with usability, since the system is executed directly on the client running the web browser before the web page is displayed. we show that we can achieve false positive rates close to 0% and false negative rates below 15% with a performance overhead of only a few seconds, what is a bit high for real time application, but supposes a great potential for future versions of our tool.
comparison of enterprise service buses based on their support of high availability. in this paper, we compare and evaluate four enterprise service buses -- fuse, mule, openesb and artix -- based on their support of high availability. we rate artix first, followed by fuse, mule and openesb. these rates are based on the fault tolerance test results as well as the published documentation from providers.
rationale visualization of software architectural design decision using compendium. the justification for software architectural design decisions made throughout the architecting process is necessary for understanding, (re)using, communicating, and modifying an architecture design. although there are many existing tools to capture, store, manage, and share the architectural design decisions explicitly, there still remains a need to visualize and explore architectural design decisions and their underlying rationale. this paper investigates how compendium tool can be employed to visualize architectural design decisions and their rationale, in order to improve the understandability and promote the communication of architectural design decisions.
avoiding to dispense with accuracy: a method to make different dtds documents comparable. the italian regulations about web content accessibility impose html 4.01 strict, xhtml 1.0 strict or superior grammar validity. such markup constraints are complied by a low percentage of public institution sites. in order to include the largest amount of not strict dtd sites on a synthetic, realistic representation of accessibility degree, this paper presents an experimental approach to set up parameters for making validity measures uniform, despite they are taken from evaluating different grammars. the proposed method allows for effectiveness in computing and storing information which otherwise will be quite unfeasible. finally, the generalization of such an approach is shown to be suited for markup quality evaluations, beyond explicit law requirements.
mode independent session directory service architecture: a unified approach for asm and ssm multicast networks. in this paper we describe architectural changes incorporated into dns aware multicast session directory (mdns) that enable it to co-exist in both any source multicast (asm) and source specific multicast (ssm) environments. mdns is a distributed, global, scalable and hierarchical approach that allows multicast sessions to be searched based on multiple parameters including keywords, session-type, geo-locality, etc. mdns design being tightly coupled with existing domain name service (dns) enables sessions to be assigned a uniform resource locator (url) that can be book-marked for future access. we also describe the caching strategy added to mdns and present arguments on its possible benefits. afterwards, we will discuss the slight search strategy alteration required by caching and its security implications. this paper also describes our simulation design. we describe how we automated our experiments. the integration of fully implemented mdns software and our "simulated" network hierarchy will be explained. we provide simulation results and explain their significance with respect to network topography.
a tool for rapid development of ws-bpel applications. we present blitec, a software tool we have developed for supporting a rapid and easy development of ws-bpel applications. blitec translates service orchestrations written in blite, a formal language inspired to but simpler than ws-bpel, into executable ws-bpel programs. we illustrate our approach by means of an example borrowed from the official specification of ws-bpel.
intensional changes: modularizing crosscutting features. feature-oriented programming (fop) targets the encapsulation of software building blocks as features which better match the specification of requirements. as a result, programmers find it easier to design and compose different variations of their systems. change-based fop (cfop) proposes to specify features as sets of first-class change objects which can add, modify or delete building blocks to or from a software system. first, we show how cfop supports the modularization of crosscutting functionality. afterwards, we expose a weakness of cfop which is a consequence from features holding extensional sets of changes. we elaborate on a solution for that weakness which is based on intensional changes: descriptions that can evaluate to an extension of changes.
variable ranges in linear constraints. we introduce an extension of linear constraints, called linear- range constraints, which allows for (meta-)reasoning about the approximation width of variables. semantics for linear- range constraints is provided in terms of parameterized linear systems. we devise procedures for checking satisfiability and for entailing the maximal width of a variable. an extension of the constraint logic programming language clp(r) is proposed by admitting linear-range constraints.
virus dna-fragment classification using taxonomic hidden markov model profiles. in most viral metagenomic studies, genetic material from a diversity of organisms is sampled from the environment and sequenced using sanger or 454 sequencing. this process typically results in dna-fragments that need to be assembled into contigs and annotated before any inferences or conclusions can be drawn from the data in hand. however, one problem subsists: both the relatively short length of the sequenced dna-fragments and the high level of diversity present in a viral community result in a large number of unassembled and unannotated dna-fragments. this problem limits our capability to better understand the viral community under study. we present the preliminary results of a new annotation method, targeting the virus sequences highly likely to be left unannotated by conventional methods. the resulting system, called anacle, gives a taxonomic annotation for virus sequences excluded by a pre-screening with blast. anacle uses an automated method relying a) on the markov clustering (mcl) of all protein sequences belonging to the same taxon and b) on constructing each taxon's genetic variations (skeletons) using hidden markov model (hmm) profiles. the taxonomic annotation consists of comparing each unannotated dna-fragment to all the skeletons, and labeling them as belonging to the taxon associated with the best similarity score. we have evaluated anacle's performance on a simulated metagenomes dataset with 100 and 700 base pairs. the results show that anacle can taxonomically annotate viruses dna-fragments with high precision and specificity. it indicates that the proposed method can provide valuable taxonomic information about dna-fragments that could be left unannotated by other methods. we also present anacle's performance on a small sargasso sea dataset.
recovering uncertain mappings through structural validation and aggregation with the moto system. we present an automated ontology matching methodology, supported by various machine learning techniques, as implemented in the system moto. the methodology is two-tiered. on the first stage it uses a meta-learner to elicit certain mappings from those predicted by single matchers induced by a specific base-learner. then, uncertain mappings are recovered passing through a validation process, followed by the aggregation of the individual predictions through linguistic quantifiers. experiments on benchmark ontologies demonstrate the effectiveness of the methodology.
dealing with application requirements and energy consumption in wireless sensor networks: a novelty detection approach for quality of query services. this paper presents an approach for adapting query processing in wireless sensor networks (wsn) based on the notions of quality of query services (qoqs) and novelty detection (nd). while the former concept captures the idea of possibly having different queries serviced in different ways by the same wsn, the second relates to a machine learning technique embedded in the wsn components that allows them to modify their query processing behavior in a dynamic fashion. this approach aims at the intelligent consumption of the limited resources available in these networks while still trying to deliver the data quality as expected by their client applications. in this context, four classes of qoqs (coqos) have been specified having in mind distinct levels of requirements in terms of accuracy and temporal behavior of the sensed data. moreover, a new nd-based algorithm, named as adaquali (after adaptive quality control for query processing in wsn), is introduced in detail as a way to control the sensor node activities through the adjustment of their rates of data collection and transmission. for validation purposes, experiments with a simulation prototype have been conducted over real data, and the results achieved so far point to gains in terms of energy consumption reduction that vary from 1.73% to 42.99% for different coqos.
resource partitioning for real-time processing on a multicore architecture. this paper presents an approach to the execution of real-time applications on a multicore architecture which is based on the partitioning of computing resources among different operating systems at core level. this means that different operating systems are assigned to different cores where they run in parallel. a working implementation based on the linux kernel and the s. ha.r.k. real-time kernel is described. in this implementation, the linux kernel is configured to use one core only, so that the s. ha.r.k. real-time kernel can be started to run independently in the remaining cores.
cloudxplor: a tool for configuration planning in clouds based on empirical data. configuration planning for modern information systems is a highly challenging task due to the implications of various factors such as the cloud paradigm, multi-bottleneck workloads, and green it efforts. nonetheless, there is currently little or no support to help decision makers find sustainable configurations that are systematically designed according to economic principles (e.g., profit maximization). this paper explicitly addresses this shortcoming and presents a novel approach to configuration planning in clouds based on empirical data. the main contribution of this paper is our unique approach to configuration planning based on an iterative and interactive data refinement process. more concretely, our methodology correlates economic goals with sound technical data to derive intuitive domain insights. we have implemented our methodology as the cloudxplor tool to provide a proof of concept and exemplify a concrete use case. cloudxplor, which can be modularly embedded in generic resource management frameworks, illustrates the benefits of empirical configuration planning. in general, this paper is a working example on how to navigate large quantities of technical data to provide a solid foundation for economical decisions.
dynamic optimization of power and performance for virtualized server clusters. in this paper we present an optimization solution for power and performance management in a platform running multiple independent applications. our approach assumes a virtualized server environment and includes an optimization model and strategy to dynamically control the cluster power consumption, while meeting the application's workload demands.
towards in-network data prediction in wireless sensor networks. researches in wireless sensor networks (wsn) have been focused on saving power in sensor nodes. an efficient strategy to achieve this goal is to reduce the amount of data sent through the network, in this work, we propose an efficient strategy that predicts data in wsns aiming at reducing the data traffic in wsns and thus maximizing the network lifetime. the proposed prediction strategy, denoted adaga-p, is based on a linear regression model, using data acquired from one or several sensors. adaga-p is executed in an in-network fashion by several sensors geographically distributed in a wsn. furthermore, in adaga-p the regression model is adjusted dynamically, if any sensor in the wsn senses an "outlier". experimental results are presented using real data. these results show that the proposed strategy reduces energy consumption in wsns.
constraint-based ln-curves. we consider the design of parametric curves from geometric constraints such as distance from lines or points and tangency to lines or circles. we solve the hermite problem with such additional geometric constraints. we use a family of curves with linearly varying normals, ln curves, over the parameter interval [0, u]. the nonlinear equations that arise can be of algebraic degree 60. we solve them using the gpu on commodity graphics cards and achieve interactive performance. the family of curves considered has the additional property that the convolution of two curves in the family is again a curve in the family, assuming common gauss maps, making the class more useful to applications. we also remark on the larger class of ln curves and how it relates to b&eacute;zier curves.
spatiotemporal sampling for trajectory streams. in this paper, we present a summarization technique adapted to trajectory streams. the spatiotemporal stream sampling (stss) algorithm is a single-pass sampling technique that takes advantage of both the spatial and temporal dimensions inherent to these streams in order to reduce their processing and storage costs.
hypervisor-based prevention of persistent rootkits. rootkits are prevalent in today's internet. in particular, persistent rootkits pose a serious security threat because they reside in storage and survive system reboots. using hypervisors is an attractive way to deal with rootkits, especially when the rootkits have kernel privileges, because hypervisors have higher privileges than os kernels. however, most of the previous studies do not focus on prevention of persistent rootkits. this paper presents a hypervisor-based file protection scheme for preventing persistent rootkits from residing in storage. based on security policies created in a secure environment, the hypervisor makes critical system files read-only and unmodifiable by rootkits even if they have kernel privileges. our scheme is designed to significantly reduce the size of hypervisors when combined with the architecture of bitvisor, a thin hypervisor for enforcing i/o device security, thereby contributing to the reliability of hypervisors. our hypervisor consists of only 37 kilo lines of code in total, and its overhead on windows xp with a fat32 file system is only 1.1% -- 14.0%.
time and alternation: an automata based framework to software model checking. in this paper, we present a class of powerful canonical timed alternating automata and a formalism for describing timed linear temporal logic to software model checking. time and alternation, these two "metaphors" have dominated automata theory research in recent years. for real-time systems, it is important to augment untimed and asynchronous models of computation with the notion of time. nevertheless, alternation is a powerful parallelism feature that has the potential to improve and reduce the state-space explosion problem in building large software model checking systems. we show that the dual connection between timed automata-theoretical and propositional-logic frameworks support and model software specifications. this can be established through languages over infinite timed words; and has a direct impact for expressing logical aspects and properties of model checking software systems.
extraction of component-environment interaction model using state space traversal. scalability of software engineering methods can be improved by application of the methods to individual components instead of complete systems. this is, however, possible only if a model of interaction between each component and its environment (rest of the system) is available. since constructing formal models of interaction by hand is hard and tedious, techniques and tools for automated inference of the models from code are needed. we present a technique for automated extraction of models of component-environment interaction from multi-threaded software systems implemented in java, which is based on state space traversal. models are captured in the formalism of behavior protocols, which allows to express parallel behavior explicitly. java pathfinder is used to perform the state space traversal. we have implemented the technique in the java2bp tool and applied the tool on two non-trivial software systems to show that our approach is feasible.
addressing the limited scope problem of focused crawling using a result merging approach. focused crawling refers to a process of fetching domain-specific pages from the web. it is an important method to build domain-specific document collections, but it suffers from low recall due to the local nature of crawling algorithms associated with web's community structure. in this study, we address the problem of limited crawling scope of focused crawling using a result merging approach. the results of crawling processes based on different start url sets and focused crawling methods were merged. we found that merging improves considerably the effectiveness of focused crawling. the results reported here are based on 10 test topics and 140 crawls in the domains of genomics and genetics.
visualizing time-series data in processlines: design and evaluation of a process enterprise application. in modern process industry, it is often difficult to analyze a manufacture process due to its numerous time-series data. analysts wish to not only interpret the evolution of data over time in a working procedure, but also examine the changes in the whole production process through time. to meet such analytic requirements, we have developed processlines, an interactive visualization tool for a large amount of time-series data in process industry. the data are displayed in a fisheye timeline. processlines provides good overviews for the whole production process and details for the focused working procedure. a user study using beer industry production data has shown that the tool is effective.
micho: a scalable constraint-based algorithm for learning bayesian networks. bayesian networks have a wide array of applications with its ability to model causal relationships in any given system. given the immense complexity and size of real problems, it is impossible to manually construct bayesian networks. the automatic learning of bayesian networks from data is hence an important task. however, in most industrial applications, the number of variables involved in any given system is large. existing algorithms need an impractical amount of time to learn such networks due to poor scalability with dimensionality. in this paper, a constraint-based algorithm, named micho, is introduced to overcome this barrier. micho synergistically integrates an information-theory-based approach and an independence-based approach to efficiently learn a bayesian network. using mutual information (mi), basic bayesian network and graph concepts to reduce the search space, a preliminary base graph can be quickly generated. refinements are then carried out using a minimal number of higher order tests involving minimum cardinality d-separating sets to obtain the final bayesian network structure. experiments involving real, large and high-dimensional datasets show that micho can perform up to 25 times faster than k2 while achieving similar accuracy.
making sense of unstructured flash-memory dumps. this paper presents an alternative to traditional file carving, targeted to flash-memory based devices. the proposed algorithm processes the flash memory dump thanks to a previous partial knowledge of the content of the regular files present in the device. the memory dump is decomposed into elementary parts, each part classified according to the file type it is supposed to belong to, and finally ordered in a sequence representing the recovered file. the sequence is then transformed into a real file. this paper presents the formal model behind the algorithm.
dispatching agvs with noisy estimation of crane operation time. the operation of both quay cranes and stacking cranes used in a container terminal is dynamically affected by a variety of factors. for this reason, errors could arise regarding the estimation of the time involved in processing containers. these errors make it difficult to dispatch automated guided vehicles (agvs) used for internal transportation of containers in the terminal. in this paper, we propose a simulation-based dispatching algorithm which reduces the impact of the noisy estimation of crane processing time. when dispatching an agv, the proposed algorithm collects stochastic samples of the evaluation value for each dispatching option by conducting multiple stochastic simulations of the agv operation. based on such samples, the proposed algorithm compares the dispatching options and selects the best one. for the stochastic simulation, we use a simple noise model of crane processing time. the effectiveness of the proposed algorithm is validated by simulation experiments.
multi-objective evolutionary approach for solving facility layout problem using local search. facility layout problem (flp) is an emerging problem in the manufacturing industries due to the fact that the computational complexity increases with the number of departments, which leads it to a combinatorial optimization problem. evolutionary algorithms have successfully been applied to flp by many researchers. unfortunately, most of these researches are predominantly on a single objective. previously, we proposed an evolutionary approach for multi-objective flp using pareto optimality [1]. simulation results indicate that it was capable of maintaining consistency and convergence of the trade-off, nondominated layout solutions. however, sometimes the solutions may be too diverse and the gap between the best and average solution is too large. this paper extends this idea by incorporating local search in the form of jumping gene operations introduced in jumping gene genetic algorithm (jgga). experimental results reveal that our proposed approach can search for the near-optimal and non-dominated solutions with better convergence and controlled-diversity by optimizing multiple criteria simultaneously.
towards the induction of terminological decision trees. a concept learning framework for terminological representations is introduced. it is grounded on a method for inducing logic decision trees as an adaptation of the classic tree induction methods to the description logics representations adopted in the semantic web context. differently from the original setting of logical trees based on clausal representations, tree-nodes contain terminological concept descriptions (corresponding to owl-dl classes) which makes it appealing for the semantic web applications. the method has been implemented in a prototypical system which has been experimentally evaluated on real ontologies.
mistral: open source biometric platform. mistral is an open source software for biometrics applications. this software, based on the well-known ubm/gmm approach includes also the latest speaker recognition developments such as latent factor analysis, unsupervised adaptation or svm supervectors. the software performance is highlighted in the framework of the nist evaluation campaigns.
a hybrid prefetch policy for the retrieval of link-associated information on vehicular networks. this paper proposes and measures the performance of a hybrid prefetch scheme for the gateway cache in the vehicular telematics network. aiming at improving response time and instant reply ratio, the proposed scheme combines the advantage of lru and far to best exploit temporal and spatial locality. for the advanced path recommendation service, links are categorized into two groups, namely, one referenced during the given interval, and the other not referenced. each group orders the links according to the distance from the gateway, finalizing the prefetch order. simulation results, based on the real-life trajectory data obtained from a real-time tracking system, show that the hybrid prefetch can improve instant reply ratio by up to 5.3% and response time by up to 12.5%, compared with far in spite of low link-level hit ratio.
a bayesian classifier for uncertain data. data uncertainty is widespread in a variety of applications. this paper proposes a new bayesian classification algorithm for classifying uncertain data. in the paper, we apply probability and statistics theory on uncertain data model, and provide solutions for model parameter estimation for both uncertain numerical data and uncertain categorical data. we also prove the correctness of the solutions. the experimental results demonstrate the proposed uncertain bayesian classifier can be efficiently constructed, and it significantly outperforms the traditional bayesian classifier in prediction accuracy when data is highly uncertain.
jaaf+t: a framework to implement self-adaptive agents that apply self-test. appropriate implementation of self-adaptive software systems able not only to check the needs for the adaptations and perform them but also to ensure their compliance with new environment requirements is still an open issue. therefore, this paper proposes an extension to the java self-adaptive agent framework (jaaf) in order to apply the self-test concept. this framework allows for the creation of self-adaptive agents based on a process composed of a set of four main activities (monitor, analyze, plan and execute). in this paper we extend the process and framework by including the test activity that will check the adapted behavior before its execution. the applicability of the proposed process is demonstrated by a case study where a system responsible for generating susceptibility maps, i.e., maps that show locations with landslides risks in a given area, searches to adapt its behavior and checks the adaptations before using them.
mining preorder relation between knowledge units from text. preorder relation between knowledge units (ku) is the precondition for navigation learning. although possible solutions, existing link mining methods lack the ability of mining preorder relation between knowledge units which are linearly arranged in text. through the analysis of sample data, we discovered and studied two characteristics of knowledge units: the locality of preorder relation and the distribution asymmetry of domain terms. based on these two characteristics, a method is presented for mining preorder relation between knowledge units from text documents, which proceeds in three stages. firstly, the associations between text documents are established according to the distribution asymmetry of domain terms. secondly, candidate ku-pairs are generated according to the locality of preorder relation. finally, the preorder relations between ku-pairs are identified by using classification methods. the experimental results show the method can efficiently extract the preorder relation, and reduce the computational complexity caused by the quadratic problem of link mining.
dynamic register-renaming scheme for reducing power-density and temperature. the manufacturing process of microprocessors becomes increasingly fine and the clock frequency is rapidly growing. since the corresponding power consumption, however, is not reduced, the power density is increased dramatically. the high temperature and heat generated by the power density causes many problems: malfunction, aging, leakage power and cooling costs. the register file produces the highest temperature in the microprocessor because of extremely high access frequency and its small area. we demonstrated that the traditional renaming unit causes high temperature since it allocates registers imbalanced. our idea is to redistribute evenly register allocations and accesses across the full range of the register file; consequently, the overall power density is lowered and then the temperature is reduced. the proposed method can be implemented by adding a small logic to the traditional renaming unit with around 1.5% overheads. the results are as follows. temperature drop was up to 11% on average 6%; leakage power saving was up to 24% on average 13%; performance improvement was up to 103% on average 84%.
efficient shortest path finding of k-nearest neighbor objects in road network databases. this paper addresses an efficient path finding scheme that complements classic k-nn (nearest neighbor) queries for the road network. aiming at finding both k objects and the shortest paths to them at the same time, this paper first selects candidate objects by the k-nn search scheme based on the underlying index structure and then finds the path to each of them by the modified a* algorithm. the path finding step stores the intermediary paths from the query point to all of the scanned nodes and then attempts to match the common segment with a path to a new node, instead of repeatedly running the a* algorithm for all k points. additionally, the cost to the each object calculated in this step makes it possible to finalize the k objects from the candidate set as well as to order them by the path cost. judging from the result, the proposed scheme can eliminate redundant node scans and provide one of the most fundamental building blocks for location-based services in the real-life road network.
scalable indexing for layout based document retrieval and ranking. in this paper we propose a schema for querying large documents collections by document layout. we develop a model of layout indexing of a collection adapted for the quick retrieval of top k relevant documents. fort the sake of scalability, we avoid a direct evaluation of the similarity between a query and each document in the collection; their similarity is instead approximated by the similarity between their projections on the set of representative blocks which are inferred from the collection on the indexed step. the technique also proposes new functions for the relevance ranking and the cluster pruning that ensure a scalable retrieval and ranking.
a robust link-translating proxy server mirroring the whole web. link-translating proxies are widely used for anonymous browsing, policy circumvention and webvpn functions. these are implemented by encoding the destination url in the path of the url submitted to the proxy and rewriting all links before returning the document to the client. commonly these are based on the cgiproxy implementation or a variant. while popular, broken links and very slow load times are common. this is so, since the use of scripting languages makes finding and translating links (the essential task of such a proxy) very difficult. some web-sites become entirely non-functional when loaded. this paper proposes a novel architecture for a link-translating proxy. using a sub-domain mapping technique we entirely eliminate the need to translate (or even find) relative links in content. then, using robust absolute link rewriting, cookie re-assignment, and wildcard certificates we achieve an extremely robust and performant proxy. our architecture preserves the same-origin policy separation of sites, and thus entirely eliminates cookie-stealing and other security concerns of cgiproxy. in measurements our proxy is far more robust, loads pages more quickly, and is more scalable than cgiproxy. we call our system aboproxy, since it involves the address bar only. it is invoked by appending. aboproxy. com to the hostname of any url.
collaborative context management framework for mobile ad hoc network environments. managing context in mobile ad hoc network (manet) environments is challenging due to environmental characteristics and limitations. different aspects of context management such as location management, context acquisition, context quality management, context discovery and other related tasks need to be dealt with to provide reliable context management support. in this paper, we propose a new approach to context management in the manet environments. we model contexts and situations based on context spaces (cs) theory and the dempster-shafer (ds) theory of evidences. a heuristic approach to computing the relevancy value of context information to the defined situation of context-aware applications is also proposed and developed. the relevancy value is then incorporated in the fusion mechanism based on the discount rule. we have developed a hybrid location model and integrated the approach to the model. the prototype of the framework is built based on the on-demand multicast routing protocol (odmrp) as the underlying messaging protocol among the collaborative hosts. finally, the implementation and experimentation issues of the prototype are discussed.
ncl-inspector: towards improving ncl code. ginga-ncl and the ncl language were selected as a recommendation as the interactive multimedia environment and language for iptv by the international telecommunication union (itu) [5]. in order to promote the use of these technologies, it is necessary to create tools to help develop applications using ncl. at present, the support provided by tools for ncl development is quite limited. in this paper, we propose ncl-inspector, a critique system of the ncl code, which aims at leveraging the developer's skills in detecting error-prone ncl applications. we also present a taxonomy of ncl code problems, which has proven useful to help develop ncl-inspector and may also improve the developers' knowledge of the domain.
canonical random correlation analysis. canonical correlation analysis (cca) is one of the most well-known methods to extract features from multi-view data and has attracted much attention in recent years. however, classical cca is unsupervised and does not take class label information into account. in this paper, we introduce the within-class cross correlation into cca and propose a new method called canonical random correlation analysis (rca). in rca, besides considering the correlation between two views from the same sample, the cross correlations between two views respectively from different within-class samples are also used to achieve good performance. two approaches for randomly generating cross correlation samples are developed.
transparent security for cloud. large distributed systems such as clouds are increasingly becoming targets of attacks. virtualization can be leveraged to increase the security of such systems by protecting the integrity of guest components. this paper discusses the integrity protection problem in the clouds and sketches a novel architecture, transparent cloud protection system (tcps) for increased security of cloud resources. tcps can be tailored to different cloud flavors to monitor the integrity of guests and infrastructure components while remaining transparent to virtual machines.
box consistency through adaptive shaving. the canonical algorithm to enforce box consistency over a constraint relies on a dichotomic process to isolate the leftmost and rightmost solutions. we identify some weaknesses of the standard implementations of this approach and review the existing body of work to tackle them; we then present an adaptive shaving process to achieve box consistency by tightening a domain from both bounds inward. experimental results show a significant improvement over existing approaches in terms of robustness for difficult problems.
a wavelet-based sampling algorithm for wireless sensor networks applications. this work proposes and evaluates a sampling algorithm based on wavelet transforms with coiflets basis to reduce the data sensed in wireless sensor networks applications. the coiflets basis is more computationally efficient when data are smooth, which means that, data are well approximated by a polynomial function. as expected, this algorithm reduces the data traffic in wireless sensor network and, consequently, decreases the energy consumption and the delay to delivery the sensed information. the main contribution of this algorithm is the capability to detect some event by adjusting the sampling dynamically. in order to evaluate the algorithm, we compare it with a static sampling strategy considering a real sensing data where an external event is simulated. the results reveal the efficiency of the proposed method by reducing the data without loosing its representativeness, including when some event occurs. this algorithm can be very useful to design energy-efficient and time-constrained sensor networks when it is necessary to detect some event.
an experience in using a tool for evaluating a large set of natural language requirements. requirements analysis is an important phase in a software project. it is often performed in an informal way by specialists who review documents looking for ambiguities, technical inconsistencies and incompleteness. automatic evaluation of natural language (nl) requirements documents has been proposed as a means to improve the quality of the system under development. we show how the tool quars express, introduced in a quality analysis process, is able to manage complex and structured requirement documents containing metadata, and to produce an analysis report rich of categorized information that points out linguistic defects and indications about the writing style of nl requirements. in this paper we report our experience using this tool in the automatic analysis of a large collection of natural language requirements, produced inside the modcontrol project.
design pattern implementation in object teams. implementing the 23 gang-of-four design patterns in the aspect-oriented programming language object teams/java (ot/j) yields modularity and reusability results roughly comparable to those obtained in a similar study of aspectj, though not in the same exact set of patterns. due to differences in composition mechanisms, the two languages seem complementary rather than overlapping. aspectj is clearly superior to ot/j in terms of quantification capability while ot/j is clearly superior to aspectj as regards extensibility of pattern modules.
the 'dresden image database' for benchmarking digital image forensics. this paper introduces and documents a novel image database specifically built for the purpose of development and bench-marking of camera-based digital forensic techniques. more than 14,000 images of various indoor and outdoor scenes have been acquired under controlled and thus widely comparable conditions from altogether 73 digital cameras. the cameras were drawn from only 25 different models to ensure that device-specific and model-specific characteristics can be disentangled and studied separately, as validated with results in this paper. in addition, auxiliary images for the estimation of device-specific sensor noise pattern were collected for each camera. another subset of images to study model-specific jpeg compression algorithms has been compiled for each model. the 'dresden image database' will be made freely available for scientific purposes when this accompanying paper is presented. the database is intended to become a useful resource for researchers and forensic investigators. using a standard database as a benchmark not only makes results more comparable and reproducible, but it is also more economical and avoids potential copyright and privacy issues that go along with self-sampled benchmark sets from public photo communities on the internet.
coverage-hole trap model in target tracking using distributed relay-robot network. target tracking is an important issue in wireless sensor network applications. in this paper, we design a coverage-hole trap model (ctm) based on a system that contains one moving target, one moving pursuer and a distributed relay robot network with sensing coverage holes. usually, the coverage hole is harmful for target tracking in wireless mobile robot network (wmrn). many algorithms have been proposed to detect and avoid coverage holes. in this paper, we try to use coverage holes as traps to point out the region where the target is moving into, and help the pursuer to catch the target. after the coverage holes are discovered by multiple relay robots in the initialization phase, the pursuer calculates the target position and predicts where it should move to. we propose distributed coverage-hole detection algorithm (dcda), which is based on 3mesh method to discover coverage holes and tackle this challenge by introducing the coverage-hole based pursuer algorithm (cbpa). cbpa is a prediction-based algorithm for the pursuer using the information about the target and coverage holes obtained from the relays. simulation results show that our methods address the limitation of the previous work, considerably improve the required tracking time and reduce the average total traveling distance of target.
early identification of crosscutting concerns in the domain model guided by states. by nature, software applications involve a myriad of different concerns, which many times crosscut each other. the problem of crosscutting concerns may be solved by aspect oriented techniques which allow to separate core functionality from aspects. this separation must be done as soon as possible during software construction in order to minimize reworking of the software artifacts. our work identifies aspects very early in the software development process. this paper presents an approach for using the problem domain language captured by the language extended lexicon to identify crosscutting concerns during the domain analysis stage.
web-based image matting. we present ntust image matting (nim), an interactive and web-based tool for image matting. it is the first image matting tool accessible through a web browser. nim can extract a foreground with thin, thread-like shapes. it begins to process inputs immediately after the user has started to paint with a brush roughly along the boundary between the foreground and the background. the user can stop anywhere while painting, and change the width of brush as needed. this helps achieve good matting quality. the quality of the foreground extracted by nim is generally better or not worse than those done by the other two online tools and photoshop. the amount of time required to complete matting by nim is reasonable.
a stochastic approach to candidate disease gene subnetwork extraction. experimental methods are beginning to define the networks of interacting genes and proteins that control most biological processes. there is significant interest in developing computational approaches to identify subnetworks that control specific processes or that may be involved in specific human diseases. because genes associated with a particular disease (i.e., disease genes) are likely to be well connected within the interaction network, the challenge is to identify the most well-connected subnetworks from a large number of possible subnetworks. one way to do this is to search through chromosomal loci, each of which has many candidate disease genes, to find a subset of genes well connected in the interaction network. in order to identify a significantly connected subnetwork, however, an efficient method of selecting candidate genes from each locus needs to be addressed. in the current study, we describe a method to extract important candidate subnetworks from a set of loci, each containing numerous genes. the method is scalable with the size of the interaction networks. we have conducted simulations with our method and observed promising performance.
peer-to-peer collaboration in the lively kernel. with the increasing popularity of the world wide web, end-user applications are moving from the desktop to the browser. more and more applications that we have come to know as desktop applications are now making their way into the web. this has made online collaboration a key aspect for many applications. collaborative applications like facebook, flickr and google docs are just an early hint of how we can benefit from users being able to share data. still, collaborative features are not easy to implement in web applications. most web programming environments aim at easy user interface creation and persistence, but not for online collaboration and pushing data from one user to another. the lively kernel is a highly dynamic web programming platform and runtime environment developed at sun microsystems laboratories. by utilizing the lively kernel platform, it is easy to implement desktop like applications for the web using javascript. in this paper we summarize the experiences from adding peer-to-peer collaboration into the lively kernel. these additions include persistent data storage, communication channels between users and user identification.
seal object detection in document images using ght of local component shapes. due to noise, overlapped text/signature and multi-oriented nature, seal (stamp) object detection involves a difficult challenge. this paper deals with automatic detection of seal from documents with cluttered background. here, a seal object is characterized by scale and rotation invariant spatial feature descriptors (distance and angular position) computed from recognition result of individual connected components (characters). recognition of multi-scale and multi-oriented component is done using support vector machine classifier. generalized hough transform (ght) is used to detect the seal and a voting is casted for finding possible location of the seal object in a document based on these spatial feature descriptor of components pairs. the peak of votes in ght accumulator validates the hypothesis to locate the seal object in a document. experimental results show that, the method is efficient to locate seal instance of arbitrary shape and orientation in documents.
transparency versus security: early analysis of antagonistic requirements. information systems designers have been increasingly convinced about the importance of dealing with quality issues at early stages of development. over the landscape of quality issues, several proposals have been published as to help with respect to security. on the other hand, designers do also need to care about other quality issues; for instance, transparency. transparency is the quality of having open information to the public. at first, the general intuition is that security and transparency conflict, but how should designers deal with these antagonistic issues? departing from the use of the non-functional requirements framework we propose a process, based on personal construct theory, to perform early analysis of antagonistic design issues. having early analysis of antagonistic quality issues makes it possible for informed decision to be taken early on during is design. we use the election domain to illustrate the application of our proposal.
novel immune-based framework for securing ad hoc networks. one of the main security issues in mobile ad hoc networks (manets) is a malicious node that can falsify a route advertisement, overwhelm traffic without forwarding it, help to forward corrupted data and inject false or uncompleted information, and many other security problems. mapping immune system mechanisms to networking security is the main objective of this paper which may significantly contribute in securing manets. in a step for providing secured and reliable broadband services, formal specification logic along with a novel immuneinspired security framework (i2manets) are introduced. the different immune components are synchronized with the framework through an agent that has the ability to replicate, monitor, detect, classify, and block/isolate the corrupted packets and/or nodes in a federated domain. the framework functions as the human immune system in first response, second response, adaptability, distributability, and survivability and other immune features and properties. interoperability with different routing protocols is considered. the framework has been implemented in a real environment. desired and achieved results are presented.
a dewarping algorithm to compensate volume binding distortion in scanned documents. this paper presents a new algorithm for dewarping the volume binding distortion often found whenever one scans a book. the existing algorithms in the literature need scanner parameters, seldom known by the end user. the algorithm proposed here only needs the user to print a calibration grid and to scan it in the central page of a volume. the algorithm collects all the data needed to dewarp all pages in the volume.
can domain-specific languages be implemented by service-oriented architecture? although there have been many benefits of domain-specific languages (dsls) reported from both academia and industry, the need to evolve a dsl definition in the presence of limited tool support results in several challenges that increase dsl development cost and constrain dsl adoption opportunities. as a new approach to address such limitations, this paper introduces a service-oriented architecture (soa) technique to implement an existing imperative dsl. the approach utilizes wsdl to perform lexical analysis and assist with syntax analysis. the paper also explores how ws-bpel can be used to define a dsl grammar. web services have potential to define the semantics of a dsl. the advantages that soa offers in dsl implementation are realized through soa's characteristics of interoperability, loose coupling, and technology-neutral implementation.
captcha smuggling: hijacking web browsing sessions to create captcha farms. captchas protect online resources and services from automated access. from an attacker's point of view, they are typically perceived as an annoyance that prevents the mass creation of accounts or the automated posting of messages. hence, miscreants strive to effectively bypass these protection mechanisms, using techniques such as optical character recognition or machine learning. however, as captcha systems evolve, they become more resilient against automated analysis approaches. in this paper, we introduce and evaluate an attack that we denote as captcha smuggling. to perform captcha smuggling, the attacker slips captcha challenges into the web browsing sessions of unsuspecting victims, misusing their ability to solve these challenges. a key point of our attack is that the captchas are surreptitiously injected into interactions with benign web applications (such as web mail or social networking sites). as a result, they are perceived as a normal part of the application and raise no suspicion. our evaluation, based on realistic user experiments, shows that captcha smuggling attacks are feasible in practice.
evaluating trust in grid certificates. digital certificates are used to secure international computation and data storage grids used for e-science projects, like the worldwide large hadron collider computing grid. the international grid trust federation has defined the grid certificate profile: a set of guidelines for digital certificates used for grid authentication. we have designed and implemented a program and related test suites for checking x.509 certificates against the certificate profiles and policies relevant for use on the grid. the result is a practical tool that assists implementers and users of public key infrastructures to reach appropriate trust decisions.
rttm: real-time transactional memory. hardware transactional memory is a promising synchronization technology for chip-multiprocessors. it simplifies programming of concurrent applications and allows for higher concurrency than lock based synchronization. standard transactional memory is optimized for average case throughput, but for real-time systems we are interested in worst-case execution times. we propose real-time transactional memory (rttm) as a time-predictable synchronization solution for chip-multiprocessors in real-time systems. we define the hardware for time-predictable transactions and provide a bound for the maximum transaction retries. the proposed rttm is evaluated with a simulation of a java chip-multiprocessor.
embedded contract languages. specifying application interfaces (apis) with information that goes beyond method argument and return types is a long-standing quest of programming language researchers and practitioners. the number of type system extensions or specification languages is a testament to that. unfortunately, the number of such systems is also roughly equal to the number of tools that consume them. in other words, every tool comes with its own specification language. in this paper we argue that for modern object-oriented languages, using an embedding of contracts as code is a better approach. we exemplify our embedding of code contracts on the microsoft managed execution platform (.net) using the c# programming language. the embedding works as well in visual basic. we discuss the numerous advantages of our approach and the technical challenges, as well as the status of tools that consume the embedded contracts.
a method for validating the compliance of business processes to business rules. regulatory compliance of business operations and practices is increasingly becoming an area of great concern for management, costing tens of billions of dollars in compliance actions a year. this paper presents a method for validating business processes with respect to the business rules. in the proposed method, business processes are modeled with uml activity diagrams, whilst business rules are represented as ocl expressions attached to process activities and the business conceptual model. the model validation is based on the simulation of the execution of process instances based on specific scenarios. the simulation algorithm steps through the process model executing the actions associated to the activities with the help of the use tool and checking for violations of the associated business rules. the proposed method allows the modeler to have an early feedback of possible defects that may exist in a business process model.
introducing global scaling parameters into ncut. gaussian similarity is usually used in spectral clustering. it generates the affinity matrix by mainly considering point-to-point distances in a local region with respect to the scaling parameters &delta;. as a result, global information is not considered. to address this problem, we design a mapping and rescaling framework (referred as m-r framework) to introduce global scaling parameters into spectral clustering. the m-r framework is applied on normalized cut to form the m-r ncut algorithm which obtains remarkable performance improvements in our experimental evaluations.
general constant expressions for system programming languages. most mainstream system programming languages provide support for builtin types, and extension mechanisms through userdefined types. they also come with a notion of constant expressions whereby some expressions (such as array bounds) can be evaluated at compile time. however, they require constant expressions to be written in an impoverished language with minimal support from the type system; this is tedious and error-prone. this paper presents a framework for generalizing the notion of constant expressions in modern system programming languages. it extends compile time evaluation to functions and variables of user-defined types, thereby including formerly ad hoc notions of read only memory (rom) objects into a general and type safe framework. it allows a programmer to specify that an operation must be evaluated at compile time. furthermore, it provides more direct support for key meta programming and generative programming techniques. the framework is formalized as an extension of underlying type system with a binding time analysis. it was designed to meet real-world requirements. in particular, key design decisions relate to balancing expressive power to implementability in industrial compilers and teachability. it has been implemented for c++ in the gnu compiler collection, and is part of the next iso c++ standard.
e-mail authorship verification for forensic investigation. the internet provides a convenient platform for cyber criminals to anonymously conduct their illegitimate activities, such as phishing and spamming. as a result, in recent years, authorship analysis of anonymous e-mails has received some attention in the cyber forensic and data mining communities. in this paper, we study the problem of authorship verification: given a set of e-mails written by a suspect along with an e-mail dataset collected from the sample population, we want to determine whether or not an anonymous e-mail is written by the suspect. to address the problem of authorship verification of textual documents and employ detection measures that are more suited in the context of forensic investigation, we borrow the nist's speaker recognition evaluation (sre) framework. our experimental results on real world e-mail dataset suggest that the employed framework addresses the e-mail authorship verification problem with a matching success as in case of speaker verification. the proposed framework produces an average equal error rate of 15--20% and mindcf equal to 0.0671 (with 10-fold cross validation technique) in correctly verifying the author of a malicious e-mail.
dynamic set-up of monitoring infrastructures for service based systems. service based systems are intrinsically dynamic as the services deployed by them can be replaced at runtime. when this happens, the service level agreements (slas) that regulate the provision of services may also need to change. following such changes, the monitoring infrastructure that is used to monitor slas may also need to be modified to ensure the continuous provision of the necessary runtime checks. this paper presents a framework that supports the dynamic assessment of the monitorability of slas terms and the dynamic setup of an appropriate infrastructure for monitoring them following such changes. the monitorability checks are based on comparisons between the sla terms for specific services and descriptions of the monitoring capabilities of these services which are expressed in languages introduced in the paper. the paper presents a prototype implementation of the framework and the results of a preliminary evaluation of it.
modeling cardinal directions in the 3d space with the objects interaction cube matrix. in gis and spatial databases, cardinal directions are frequently used as selection and join criteria in query languages. however, most cardinal direction models are only able to handle two-dimensional spatial objects. but, e.g., geoscientists and engineers in fields like geography, cartography, soil engineering, and landscape modeling have shown an increasing demand for modeling cardinal directions between objects in the three-dimensional space. unfortunately, the few available 3d cardinal direction models suffer from several problems like the coarse approximation of the two operand 3d objects in terms of single points and minimum bounding boxes, the lacking property of converseness of the cardinal direction relations computed, and the incomplete coverage of all possible direction relations. all problems mentioned can lead to incorrect results. this paper proposes a new model that solves these problems and in a first stage introduces an objects interaction cube and, as its representation, an objects interaction cube matrix to capture all possible interactions between any two 3d spatial objects. in a second stage, an interpretation technique is applied to the objects interaction cube matrix to determine the cardinal directions.
simulated annealing based algorithm for smooth robot path planning with different kinematic constraints. in this paper, we present a simulated annealing (sa) based algorithm for robot path planning. the kernel of our sa engine is based on voronoi diagram and composite bezier curve to obtain the shortest smooth path under given kinematic constraints. in our algorithm, a voronoi diagram is constructed according to the global environment. the piecewise linear path in the voronoi diagram which keeps away from the obstacles is obtained by performing dijkstra's shortest path algorithm. the control points on the reference path are used to create the control variables for our sa engine. our sa engine then updates the control variables to obtain the shortest composite bezier curve path while satisfying given kinematic constraints. experimental results on two maps containing sharp turns demonstrate the effectiveness of the proposed sa-based smooth path planning algorithm.
probabilistic developmental program evolution. a probabilistic model building genetic programming technique for automatic program synthesis is introduced. the approach, called probabilistic developmental program evolution (pdpe), draws on the probabilistic incremental program evolution (pipe) learning algorithm, but employs the developmental genetic programming representations of gene expression programming (gep). pdpe induces a population of programs, encoded as fixed-length gep chromosomes, by iteratively refining and randomly sampling a probability distribution of program instructions stored in a vector called probability prototype chromosome (ppc). this refining, however, is accomplished solely by means of mutation of the ppc. we compared pdpe with pipe and gep on a function regression problem and the 6-bit parity problem. our results show that pdpe outperforms pipe in terms of solution quality and variance. it also outperforms gep in terms of solution quality, but not in terms of variance.
analysis of collision probability in unsaturated situation. a large number of the mac protocols proposed for establishing wireless sensor networks are based on the 802.11 standard. the trade-off in these protocols is the control packet overhead and the retransmission cost due to collision without it. in this paper we evaluate the collision probability of a csma/ca mac protocol in an unsaturated situation as a function of nodes' sampling and transmission rates. we provide an accurate and comprehensive analytical model in which a finite number of nodes exist. we assume an ideal channel condition, independent collision probability of packets as well as infrequent communication between sensor nodes. we will demonstrate that the collision probability changes from 0 to 0.22 as the sampling rate changes from 0 to 0.94mbps. moreover, we will demonstrate that collision only begins after the sampling rate reaches 0.31mbps, which implies that for a sampling rate below this threshold, the control overhead can be avoided by altogether avoiding the collision avoidance mechanism.
filtering the shadows from poorly illuminated photos. this paper presents a new algorithm for filtering shadowy photos degraded by uneven light condition. the dark photos are harder to use for face recognition or even an analysis of the scene. corrections can be made using commercial tools as photoshop&trade; but this is done manually and it requires a specialized user. we propose an automatic method which inproves the visibility of the scenes. this method is based on wavelet analysis but it uses different filters.
a rough set approach to mining connections from information systems. mining data changes and connections from information systems (or databases) is made difficult by the different data behaviors and relationships across multiple data sets. when making a decision, such a dynamic and integrated knowledge base can be used to set useful rules (e.g., causality) that differ from the statistical associations in a single resource. in this paper, using techniques based on the rough set theory, we propose a change and connection mining algorithm for discovering a time delay between the quantitative changes in the data of two temporal information systems and for generating the association rules of changes from their connected decision table. we establish evaluation criteria for the connectedness of two temporal information systems with varying time delays by calculating weight-based accuracy and coverage of the association rules of changes, adjusted by a fuzzy membership function.
a knowledge-rich similarity measure for improving it incident resolution process. the aim of incident management is to restore a given it service disruption, simply called incident, to normal state as quickly as possible. in incident management, it is essential to resolve a new incident efficiently and accurately. however, typically, incident resolution process is largely manual, thus, it is time-consuming and error-prone. this paper proposes a new knowledge-rich similarity measure for improving this process. the role of this measure is to retrieve the most similar past incident cases for a new incident without human intervention. the solution information contained the retrieved incident cases can be utilized to resolve the new incident. the main feature of our similarity measure is to incorporate additional useful meta knowledge, outside of incident description that is the only exploited information in typical similarity measures used in cbr, to improve effectiveness. moreover, this measure exploits as much semantic knowledge as possible about features contained in previous incident cases. through an experimental evaluation, we show the effectiveness, technical coherence and feasibility of this measure using a real dataset.
a general energy optimization model for wireless networks using configurable antennas. we consider two fundamental problems of minimizing energy consumption and maximizing the lifetime of a given communication request in multi-hop wireless networks that use configurable antennas and have limited energy resources. we provide a globally optimal solution to this problem by developing a general optimization model that can apply to many antenna models including highly and moderately directional antenna types. our numerical experiments validate our formulations and the obtained results reveal the performance behavior as a function of antenna and multicast configurations for some network examples.
a new methodology for photometric validation in vehicles visual interactive systems. this work proposes a new methodology for automatically validating the internal lighting system of an automotive, i.e., assessing the visual quality of an instrument cluster (ic) from the point of view of the user. although the evaluation of the visual quality of a component is a subjective matter, it is highly influenced by some photometric features of the component, such as the light intensity distribution. the methodology proposed here uses this last photometric feature to classify regions in images of instrument cluster components as homogenous or not, while also taking into account the user subjective evaluation. in order to achieve that, we acquired a set of 107 ic component images, and preprocessed them. these same components were evaluated by a user to identify their non-homogenous regions. then, for each component region, we extracted a set of homogeneity descriptors. these descriptors were associated with the results of the user evaluation, and given to two machine learning algorithms. these algorithms were trained to identify a region as homogenous or not, and showed that the proposed methodology obtains precision above 95%.
flash-aware record management method. in this paper, we analyze how unique characteristics of flash memory affect the performance of clustering and non-clustering strategies for record management, and show that non-clustering is more suitable in flash memory environment. also, we identify the problems of the existing non-clustering method when applied to flash memory environment, and propose an effective method for record management in flash memory databases.
exploring, visualizing and slicing the soul of xml documents. in this paper we introduce exvisxml, a visual tool to explore documents annotated with the mark-up language xml, in order to easily perform over them tasks as knowledge extraction or document engineering. exvisxml was designed mainly for two kind of users. those who want to analyze an annotated document to explore the information contained---for them a visual inspection tool can be of great help, and a slicing functionality can be an effective complement. the other target group is composed by document engineers who might be interested in assessing the quality of the annotation created. this can be achieved through the measurements of some parameters that will allow to compare the elements and attributes of the dtd/schema against those effectively used in the document instances. both functionalities and the way they were delineated and implemented will be discussed along the paper.
a generative pattern model for mining binary datasets. in many application fields, huge binary datasets modeling real life-phenomena are daily produced. these datasets record observations of some events, and people are often interested in mining them in order to recognize recurrent patterns. however, the discovery of the most important patterns is very challenging. for example, these patterns may overlap, or be related only to a particular subset of the observations. finally, the mining can be hindered by the presence of noise. in this paper, we introduce a generative pattern model, and an associated cost model for evaluating the goodness of the set of patterns extracted from a binary dataset. we propose an efficient algorithm, named gpm, for the discovery of the most relevant patterns according to the model. we show that the proposed model generalizes other approaches and supports the discovery of high quality patterns.
an automatic linking service of document images reducing the effects of ocr errors with latent semantics. robust information retrieval (ir) systems have been demanded due to the widespread and multipurpose use of document images, and the high number of document images repositories available nowadays. this paper presents a novel approach to support the automatic generation of relationships among document images by exploiting latent semantic indexing (lsi) and optical character recognition (ocr). the linkdi service extracts and indexes document images content, obtains its latent semantics, and defines relationships among images as hyperlinks. linkdi was experimented with document images repositories, and its performance was evaluated by comparing the quality of the relationships created among textual documents and among their respective document images. results show the feasibility of linkdi relating ocr output with high degradation.
fraud detection in reputation systems in e-markets using logistic regression. reputation systems are specially important in e-markets, where they help buyers to decide whether or not to purchase a product. this work addresses the task of finding attempts to deceive reputation systems in e-markets. our goal is to generate a list of users (sellers) ranked by the probability of fraud. first we describe characteristics related to transactions that may indicate frauds evidence and they are expanded to the sellers. we describe results of a simple approach that ranks sellers by counting characteristics of fraud. then we incorporate characteristics that cannot be used by the counting approach, and we apply logistic regression to both, improved and not improved. we use real data from a large brazilian e-market to train and evaluate our methods and the improved set with logistic regression performes better. the list with 32.1% of topmost probable fraudsters against the reputation system was selected. we increased by 110% the number of identified fraudsters against the reputation system and no false positives were confirmed.
semantics for intelligent delivery of multimedia content. this paper describes a new generic metadata model, called cam metamodel, that merges altogether information about content, services, physical and technical environment in order to enable homogenous delivery and consumption of content. we introduce a metadata model that covers all these aspects and which can be easily extended so as to absorb new types of models and standards. we ensure this flexibility by introducing an abstract metamodel, which defines structured archetypes for metadata and metadata containers. the metamodel is the foundation for the technical metadata specification. we also introduce new structures in the abstract and core metamodels supporting the management of distributed community created metadata.
structural handwritten and machine print classification for sparse content and arbitrary oriented document fragments. discriminating handwritten and printed text is a challenging task in an arbitrary orientation scenario. the task gets even tougher when the text content is by nature sparse in the document, e.g. in torn document pieces. we here propose a system for discriminating handwritten and printed text in the context of sparse data and arbitrary orientation. a chain-code feature is used with support vector machine (svm) classifier for the purpose. prior to feature extraction and classification some preprocessing steps (like region growing and angle estimation using principle component analysis) are performed in order to resolve the arbitrary orientation issue. we got promising results of 96.90% accuracy, even when the document consists of sparse data with arbitrary orientation.
new theoretical findings in multiple personalized recommendations. within personalized marketing, a recommendation issue known as multicampaign assignment is to overcome a critical problem, known as the multiple recommendation problem which occurs when running several personalized campaigns simultaneously. this paper mainly deals with the hardness of multicampaign assignment, which is treated as a very challenging problem in marketing. the objective in this problem is to find a customer-campaign matrix which maximizes the effectiveness of multiple campaigns under some constraints. we present a realistic response suppression function, which is designed to be more practical, and explain how this can be learned from historical data. moreover, we provide a proof that this more realistic version of the problem is np-hard, thus justifying to use of heuristics presented in previous work.
mining interesting sets and rules in relational databases. in this paper we propose a new and elegant approach toward the generalization of frequent itemset mining to the multi-relational case. we define relational itemsets that contain items from several relations, and a support measure that can easily be interpreted based on the key dependencies as defined in the relational scheme. we present an efficient depth-first algorithm, which mines relational itemsets directly from arbitrary relational databases. several experiments show the practicality and usefulness of the proposed approach.
implementing software product lines using traits. a software product line (spl) is a set of software systems with well-defined commonalities and variabilities that are developed by managed reuse of common artifacts. in this paper, we present a novel approach to implement spl by fine-grained reuse mechanisms which are orthogonal to class-based inheritance. we introduce the featherweight record-trait java (frtj) calculus where units of product functionality are modeled by traits, a construct that was already shown useful with respect to code reuse, and by records, a construct that complements traits to model the variability of the state part of products explicitly. records and traits are assembled in classes that are used to build products. this composition of product functionalities is realized by explicit operators of the calculus, allowing code manipulations for modeling product variability. the frtj type system ensures that the products in the spl are type-safe by type-checking only once the records, traits and classes shared by different products. moreover, type-safety of an extension of a (type-safe) spl can be guaranteed by checking only the newly added parts.
evolutionary metaheuristic for biclustering based on linear correlations among genes. a new measure to evaluate the quality of a bicluster is proposed in this paper. this measure is based on correlations among genes. moreover, a new evolutionary metaheuristic based on scatter search, which uses this measure as the fitness function, is presented to obtain biclusters that contain groups de highly-correlated genes. later, an analysis of the correlation matrix of these biclusters is made to select these groups of genes that define new biclusters with shifting and scaling patterns. experimental results from human bcell lymphoma are presented.
interaction refinement in the design of business collaborations. to tackle the complexity of inter-organizational business collaborations, the design of such collaborations may require explicit modelling at multiple abstraction levels. at a high abstraction level, the collaboration is specified as a single abstract interaction; and at a lower abstraction level, the collaboration is specified as a composition of more-concrete interactions. interaction refinement is a design operation in which an abstract interaction is replaced with multiple related more-concrete interactions. the availability of an interaction design concept that is suitable for modelling interactions at multiple abstraction levels would facilitate the refinement. supporting design operations are necessary to check whether an interaction refinement is correct or conforms to the abstract interaction it replaces. this paper presents an interaction design concept and associated operations to support the design of business collaborations at successive abstraction levels.
investigating the influence of social computing applications on website quality. social computing applications hold immense potential in enriching communication, enabling collaboration and fostering innovation. however, little work has been done to studying social computing applications in library websites. this paper therefore seeks to investigate the prevalence of social computing applications in library websites, and in particular, examine if the presence of such applications enhance the quality of these sites. in our work, 120 libraries' websites, from north america, europe and asia, divided equally between public and academic, were sampled and their content analyzed. prevalence of social computing applications was found to vary across regions but only marginally by library type. further, the presence of social computing applications was found to correlate to the overall quality of library websites. the paper concludes by highlighting implications for both librarians and scholars interested to delve deeper into the implementation of social computing applications.
semi-join computation on distributed file systems using map-reduce-merge model. semi-join is the most used technique to optimize the treatment of complex relational queries on distributed architectures. however, the overhead related to semi-join computation can be very high due to data skew and to the high cost of communication in distributed architectures. internet search engines needs to process vast amounts of raw data every day. hence, systems that manage such data should assure scalability, reliability and availability issues with reasonable query processing time. hadoop and google's file system are examples of such systems. in this paper, we present a new algorithm based on map-reduce-merge model and distributed histograms for processing semi-join operations on such systems. a cost analysis of this algorithm shows that our approach is insensitive to data skew while reducing communication and disk input/output costs to a minimum.
evaluating the usability of a mobile content sharing game. we propose marge, a game which incorporates multiplayer, pervasive gaming elements into mobile content sharing. a pilot study of marge was conducted, and in general, results suggest the potential of the application in terms of entertainment and content sharing value.
a simple role mining algorithm. complex organizations need to establish access control policies in order to manage access to restricted resources. role based access control paradigm has been introduced in '90 years aiming at simplifying the management of centralized access control. the definition of a good set of roles in order to match the organizational requirements of a company is a problem partially solved by role mining techniques, which return automatically a set of roles compatible with the permissions assigned to users. unfortunately, the problem of finding an optimal role set has been proved to be np-hard; so heuristics have been introduced in order to approximate the optimal solution. in this work we propose a novel heuristic and compare its results showing its efficiency and effectiveness.
experimental study on the impact of robust watermarking on iris recognition accuracy. watermarking has been suggested as a means to improve security of biometric systems or to add additional functionalities to such systems. we experimentally investigate the impact of applying a set of blind robust watermarking schemes on the recognition performance of two iris recognition algorithms. we find that different watermarking schemes result in a very different amount of impact rendering the choice of a particular watermarking scheme an important issue to be considered in the investigated context.
exploiting assumption-based verification for the adaptation of service-based applications. service-based applications (sbas) need to operate in a highly dynamic world, in which their constituent services could fail or become unavailable. monitoring is typically used to identify such failures and, if needed, to trigger an adaptation of the sba to compensate for those failures. however, existing monitoring approaches exhibit several limitations: (1) monitoring individual services can uncover failures of services. yet, it remains open whether those individual failures lead to a violation of the sba's requirements, which would necessitate an adaptation. (2) monitoring the sba can uncover requirements deviations. however, it will not provide information about the failures leading to this deviation, which constitutes important information needed for the adaptation activities. even a combination of (1) and (2) is limited. for instance, a requirements deviation will only be identified after it has occurred, e. g., after the execution of the whole sba, which then in case of failures might require costly compensation actions. in this paper we introduce an approach that addresses those limitations by augmenting monitoring techniques for individual services with formal verification techniques. the approach explicitly encodes assumptions that the constituent services of an sba will perform as expected. based on those assumptions, formal verification is used to assess whether the sba requirements are satisfied and whether a violation of those assumptions during run-time leads to a violation of the sba requirements. thereby, our approach allows for (a) pro-actively deciding whether the sba requirements will be violated based on monitored failures, and (b) identifying the specific root cause for the violated requirements.
tokdoc: a self-healing web application firewall. the growing amount of web-based attacks poses a severe threat to the security of web applications. signature-based detection techniques increasingly fail to cope with the variety and complexity of novel attack instances. as a remedy, we introduce a protocol-aware reverse http proxy tokdoc (the token doctor), which intercepts requests and decides on a per-token basis whether a token requires automatic "healing". in particular, we propose an intelligent mangling technique, which, based on the decision of previously trained anomaly detectors, replaces suspicious parts in requests by benign data the system has seen in the past. evaluation of our system in terms of accuracy is performed on two real-world data sets and a large variety of recent attacks. in comparison to state-of-the-art anomaly detectors, tokdoc is not only capable of detecting most attacks, but also significantly outperforms the other methods in terms of false positives. runtime measurements show that our implementation can be deployed as an inline intrusion prevention system.
extending relational algebra to handle bipolarity. this paper presents an extension of relational algebra suited to the handling of bipolar concepts. the type of queries considered involves two parts: a first one which expresses a (possibly flexible) constraint, and a second one that corresponds to a (possibly flexible) wish. the framework considered is that of bipolar fuzzy relations where each tuple is associated with a pair of degrees in the unit interval.
adaptability in xml-to-relational mapping strategies. one of the ways how to manage xml documents is to exploit tools and functions offered by (object-)relational database systems. the key aim of such techniques is to find the optimal mapping strategy, i.e. the way the xml data are stored into relations. currently the most efficient approaches, so-called adaptive methods, search a space of possible mappings and choose the one which suits the given sample data and query workload the most. in the paper we exploit a general heuristic method called ant colony optimization (aco) to solve the xml-to-relational mapping problem. we also adapt the algorithm so it can be used on a dynamic variant of the problem. the algorithms are evaluated in a set of experiments with a conclusion that the aco-based algorithms are suitable for the problem and can be even used as a basis of a dynamic mapping mechanism.
identifying and modeling aspectual scenarios with theme and mata. aspect-oriented requirements engineering emerged to deal with crosscutting requirements. there are several aspect-oriented requirements approaches, such as theme and mata. through the theme approach, one can identify a set of actions associated to verbs present in requirements documentation, which are then analyzed in order to identify crosscutting behaviors, i.e., potential aspectual scenarios. however, the theme's composition mechanism is not expressive enough even when dealing with analysis models. the mata approach can overlap this point with its powerful composition mechanisms, based on graph transformations that use uml models, in particular behavioral models. these models express scenarios that constitute a very popular and used technique to specify a system's behavior. although, mata is well-succeeded approach to specify aspectual behavior, it does not provide enough mechanisms to identify (aspectual) scenarios. also, it does not identify negative scenarios, i.e., unexpected situations, making their treatment more manageable using aspect-orientation. all these scenarios could be identified with theme and refined with mata. this paper describes an approach that can be seen as a synergy between these two complementary techniques, where identification, modularization, specification and composition of aspectual behavior is realized in a seamless and systematic way.
scheduling intense applications most 'surprising' first. certain streaming applications are required to perform sophisticated analytics within bounded time on arriving streams of data. such applications have the interesting characteristic that the total amount of work that could be performed is unbounded. we show how recent result from algorithmic theory are useful in scheduling such applications as they allow the efficient creation of synopses of unprocessed data. these synopses can then be used to schedule the processing of the stream. in particular, we describe a scheduler that optimizes the information rate available to applications by estimating the entropy of arriving streams. we describe the theory underlying such a scheduler and show how existing programming models can be extended to accommodate it.
task-aware based co-scheduling for virtual machine system. today, virtualization technique is increasingly mature and prevalent in server consolidation and hpc. virtual machine monitor plays a significant role in the resource management by dynamically mapping the virtual cpus of virtual machines to physical cpus according to chosen scheduling policy. however, since a virtual machine monitor lacks the insight into each virtual machine, the unpredictability of each workload makes effective resource allocation difficult. particularly, current virtual machine scheduling policy has a critical impact on the performance of concurrent workload due to the non-synchronization of virtual cpus. this paper presents a task-aware co-scheduling scheduler for virtual machine system. the task-aware mechanism is based on inference techniques using gray-box knowledge which can infer the concurrency and synchronization of guest os level tasks. with this inference, proposed scheduler schedules the designated virtual machine to make it possible that corresponding virtual cpus in this virtual machine can run on the physical cpus synchronously in order to reduce the cost of synchronization between processes or threads. all implementation is confined to the virtualization layer based on xen virtual machine monitor and the credit scheduler. we evaluated our prototype in terms of synchronization performance and cpu fairness over synthetic mixed workloads and realistic applications. the experiment results indicate that task-aware based co-scheduling policy is feasible to improve the performance of virtual machine system for concurrent tasks.
using surface effect measures to model parallel performance. many factors affect the performance of parallel programs including idle time, wait time, and communication costs. the latter often constitute a significant source of overhead. we consider in this paper the impact of such costs on the performance of parallel implementations of three domain decompositions of a three-dimensional model for tissue growth on a cluster. these are regular domain decompositions that comprise a slab decomposition, a rod decomposition, and a block decomposition. using a set of measures that qualify each decomposition, we explore their capability to predict the parallel performance of each implementation. the results of our experiments confirm the applicability of using these measures as predictors of performance for our application, and potentially for other similar ones.
a new technique for data privatization in user-level threads and its use in parallel applications. user-level threads have been used to implement migratable mpi processes. this is a better strategy to implement load balancing mechanisms. that is because, in general, these threads are faster to create, manage and migrate than heavy processes and kernel threads. however, they present some issues concerning private data because they break the private address space that mpi programs typically assume. in this paper, we propose a new approach to privatize data in user-level threads. this approach is based on thread local storage, which is used by kernel threads. we apply this technique to enable mpi processes based on user thread to execute a wider range of parallel programs. we show that this alternative has a more efficient context switch and lower migration cost than other approaches.
esb federation for large-scale soa. embracing service-oriented architectures in the context of large systems, such as the web, rises a set of new and challenging issues: increased size and load in terms of users and services, distribution, and dynamicity. a top-down federation of service infrastructure support that we name "service cloud" and that is capable of growing to the scale of the internet, is seen as a promising response to such new challenges. in this paper, we define the service cloud concept, its promises and the requirements in terms of architecture and the corresponding middleware. we present some preliminary proofs of concept through the integration of a jbi-compliant enterprise service bus, extended to our needs, and a scalable semantic space infrastructure, both relying on an established grid middleware environment. the new approach offers service consumers and providers a fully transparent, distributed and federated means to access, compose and deploy services on the internet. technically, our contribution advances core service bus technology towards the service cloud by scaling the registries and message routers to the level of federations via a hierarchical approach, and by incorporating the communication and coordination facilities offered by a global semantic space.
an apqc-pcf based framework to compare service offerings in business transformation projects. in the services market for business transformation, a pressing problem for customers is that they cannot easily compare software and service vendors. the root of the problem is that tools, methods and content offerings are not only represented without a common terminology but also there is lack of a common delivery-oriented framework to compare such offerings. in this paper, we propose to fill this gap by enhancing apqc's process classification framework (apqc for short), a well-known standard for terminology on process definitions, to become such a common framework. specifically, our extensions comprise of: (a) an enrichment of apqc terminology created by analyzing hundreds of process documentation from live client projects, (b) an addition to the enriched apqc to map data sources from different vendors, and (c) an addition to the enriched apqc to map heterogeneous business transformation methodologies. a prototype tool, discussed in the paper, then uses these extensions to provide the capability to a customer to scope the business landscape of interest, tailor the methods, compare tools, and integrate content across hither-to insurmountable vendor boundaries. the presented approach lays the basis for a new generation of tools being developed in ibm to accelerate sap and oracle business transformation projects.
measuring the alignment between business processes and software systems: a case study. the alignment degree existing between a business process and the supporting software systems strongly affects the performance of the business process execution. methods are needed for detecting this kind of alignment and keeping a business process aligned with a supporting software system even when one of the two evolves. actually, any modification performed in the business process activities and/or supporting software systems may impact the process activities and/or software components, in terms of input/output and/or purpose and, therefore, cause misalignment. this paper proposes a framework including a set of metrics codifying the alignment concept with the aim of measuring it and detecting misalignment if it occurs. the application of the framework is explored through a case study.
extracting ontology concept hierarchies from text using markov logic. ontologies have proven to be a powerful tool for many tasks such as natural language processing and information filtering and retrieval. however their development is an error prone and expensive task. one approach for this problem is to provide automatic or semi-automatic support for ontology construction. this work presents the probabilistic relational hierarchy extraction (prehe) technique, an approach for extracting concept hierarchies from text that uses statistical relational learning and natural language processing for combining cues from many state-of-the-art techniques. a markov logic network has been developed for this task and is described here. a preliminary evaluation of the proposed approach is also outlined.
reachability analysis of gspdis: theory, optimization, and implementation. analysis of systems containing both discrete and continuous dynamics, hybrid systems, is a difficult issue. most problems have been shown to be undecidable in general, and decidability holds only for few classes where the dynamics are restricted and/or the dimension is low. in this paper we present some theoretical results concerning the decidability of the reachability problem for a class of planar hybrid systems called generalized polygonal hybrid systems (gspdi). these new results provide means to optimize a previous reachability algorithm, making the implementation feasible. we also discuss the implementation of the algorithm into the tool gspeedi.
sub-clone refactoring in open source software artifacts. we present a study of revisions made to open source projects that documents the actual refactoring of code associated with code clones (i.e., sections of duplicated code). the study identifies a characteristic in which some clone refactorings were performed on only part of the clone (i.e., a sub-clone). we conclude that sub-clones should be considered during the clone maintenance activity.
applying taxonomic knowledge to bayesian belief network for personalized search. keyword-based search returns its results without concern for the information needs of users at a particular time. in general, search queries are too short to represent what users want, and thus it is necessary to more exactly represent the users' intended semantics. hence, our goal is to enrich the semantics of user-specific information (e.g., users' queries and preferences) with a set of concepts for personalized search. to achieve this goal, we adopt a bayesian belief network (bbn) as a strategy for personalized search since the bayesian belief network provides a clear formalism for mapping user-specific information to its corresponding concepts. nevertheless, as the concept layer of the bayesian belief network consists of only index terms extracted from documents, it does not use domain knowledge which is required for computers to understand the intended semantics of queries. thus, we extend the bayesian belief network to represent the semantics of user-specific information as concepts (not index terms). the concepts are extracted from a taxonomic knowledge base such as the open directory project web directory. in our experiments, we have shown that the extended bayesian belief network using taxonomic knowledge significantly outperforms the conventional methods for personalized search.
lfrp-search: multi-layer ranked visual faceted search: an approach to cope with complex search situations. in enterprise search scenarios information needs are quite diverse. if users know exactly which items they are looking for, they need support in known-item searches. but often information needs are vague and unclear, which means that users cannot explicitly define the search criteria that specify their search request. in these cases, exploratory search approaches are necessary to support users in interactively refining their search queries. our approach for a retrieval system for complex search situations can be characterized by its four constituent parts: the approach deals with the heterogeneity of potential target objects when performing a search considering multiple artifact layers (e. g. projects, products, persons, and documents). the basic search paradigm applied is faceted search which is well-suited for exploratory interactive retrieval. to cope with result sets of different granularity, we include ranking facilities based on facet values as well as query-by-example (qbe) functionalities. users can easily state their priorities visually by using preference functions. finally, parallel coordinates (pc) are used to visualize the characteristics and dependencies of (intermediate) results in order to provide users with a deeper understanding of the data under investigation. these four cornerstones of our approach are reflected in the acronym lfrp-search (multi-<u>l</u>ayer <u>f</u>aceted search with <u>r</u>anking using <u>p</u>arallel <u>c</u>oordinates). the main contribution of this paper is the semi-formal description of the query options.
a real-time architecture design language for multi-rate embedded control systems. this paper presents a language dedicated to the description of the software architecture of complex embedded control systems. the language relies on the synchronous approach but extends it to support efficiently systems with multiple real-time constraints, such as deadline constraints or periodicity constraints. it provides a high-level of abstraction and benefits from the formal properties of synchronous languages. the language defines a small set of rate transition operators, which enable the description of user-defined deterministic multi-rate communication patterns between components of different rates. the compiler of the language automatically translates a program into a set of communicating real-time tasks implemented as concurrent c threads that can be executed on a standard real-time operating system.
msp algorithm: multi-robot patrolling based on territory allocation using balanced graph partitioning. this article addresses the problem of efficient multi-robot patrolling in a known environment. the proposed approach assigns regions to each mobile agent. every region is represented by a subgraph extracted from the topological representation of the global environment. a new algorithm is proposed in order to deal with the local patrolling task assigned for each robot, named multilevel subgraph patrolling (msp) algorithm. it handles some major graph theory classic problems like graph partitioning, hamilton cycles, non-hamilton cycles and longest path searches. the flexible, scalable, robust and high performance nature of this approach is testified by simulation results.
design and development of a real-time embedded inertial measurement unit. micro-electro-mechanical systems (mems) sensors are used nowadays in a wide range of applications, from robotics to entertainment. recently, this technology has also been adopted to equip inertial measurement units (imus) replacing traditional electro-mechanical sensors. in this work we present a low-cost embedded imu which is based on a low-cost embedded microcontroller with limited resources in terms of computing power and memory. the developed software runs on the top of the erika enterprise real-time kernel to manage the computing tasks that perform sensor data sampling and processing. low-cost mems accelerometers, gyroscopes and magnetometers provide the required data and a kalman filter analyses raw values in real-time. experimental results are obtained using a six degrees of freedom anthropomorphic manipulator to drive the imu with accurate known trajectory, acceleration and rotation. performances are evaluated both in terms of sensor fusion effectiveness and real-time execution.
towards mobile process as a service. process as a service (paas) addresses modeling, execution and management of business processes without running extensive and costly process management software. such a flexible outsourcing strategy is especially advantageous in the context of mobile devices and services which are increasingly relevant for contemporary business activities. based on the concept of context-based cooperation, this paper proposes a paas solution for mobile participants which enables them to share existing local and remote resources and to utilize paas functionality of cooperating providers in a user-defined way. the approach is realized and evaluated by an extended prototype implementation of the demac (distributed environment for mobility aware computing) platform.
on processing location based top-k queries in the wireless broadcasting system. in this paper, we explore the problem of processing a novel type of location based queries, named the location based top-k query, which involves both of spatial and non-spatial specifications for data objects in the wireless broadcasting system. we introduce two methods for processing location based top-k queries on the broadcast stream. in the first method, the search algorithm runs on the broadcast aggregate r-tree (ar-tree). however, the ar-tree may deteriorate the search performance, especially in terms of the tuning time. with this problem in mind, we propose a novel index structure, called the bit-vector r-tree (br-tree), which stores additional bit-vector information to facilitate processing of location based top-k queries. the search algorithm on the broadcast br-tree is also described. our simulation experiments demonstrate that the br-tree method clearly outperforms the ar-tree method in terms of the tuning time, while maintaining similar or better performance in terms of the access time.
reality cues-based interaction using whole-body awareness. the exploration of 3d environments using 6 degrees-of-freedom interaction is still a challenge since users easily become disoriented. in this paper we discuss the benefits of the whole-body awareness in 3d interactive applications. we propose a technique for navigation and selection in 3d environments which explores the peephole metaphor with a tablet pc. in practice, the tablet is held by the participant who moves it around and points it in any direction for visualization and interaction. the method was tested with a set of users who were asked to perform selection tasks. the technique presented competitive results when compared with conventional interaction methods and also showed that real world body orientation memory helps users to perform better in the virtual world.
modeling the variability of architectural patterns. architectural patterns provide proven solutions to recurring design problems that arise in a system context. a major challenge for modeling patterns in a system design is effectively expressing pattern variability. however, modeling pattern variability in a system design remains a challenging task mainly because of the infinite pattern variants addressed by each architectural pattern. this paper is an attempt to solve this problem by categorizing the solution participants of patterns. more precisely, we identify variable participants that lead to specializations within individual pattern variants and participants that appear over and over again in the solution specified by several patterns. with examples and a case study, we demonstrate the successful applicability of this approach for designing systems. using the uml extension mechanism, we offer extensible architectural modeling constructs that can be used for modeling several pattern variants.
adaptive internet services through performance and availability control. cluster-based multi-tier systems provide a means for building scalable internet services. building adaptive internet services that are able to apply appropriate system sizing and configuration is a challenging objective for nowadays system administrators. this paper addresses two issues for building adaptive internet services: (i) the control of service cost, performance and availability, three antagonist and primary aspects of internet services, and (ii) an adaptive control of internet services that does not shift the complexity of system administration from the internet service to its controller. this paper presents the design and implementation of moka - a middleware for controling performance and availability of cluster-based multi-tier systems. the contribution of the paper is multifold. first, we improve an analytic model to predict the performance, availability and cost of cluster-based multi-tier applications. second, we define a utility function and use it to build a capacity planning algorithm that calculates the optimal application configuration which guarantees performance and availability objectives while minimizing functioning cost. finally, we propose a novel approach for dynamic provisioning of multi-tier applications that removes the burden of manual (re-)configuration of the controller itself. our experiments on the tpc-w multi-tier online bookstore show that moka provides significant benefits on application performance and availability.
how to manage interactive dialogues of avatar agents by using 3d spatial information of virtual world. chat and instant messaging are crucial functions in the internet environment. internet chat and instant messaging services are becoming increasingly popular among internet users. one of the crucial issues in internet chat is how to manage the corresponding pairs of questions and answers in a sequence of conversations. there are numerous novel methodologies for coping with this problem, but most are poor at managing interruptions, organizing turn-taking and conveying comprehension. nowadays, since the internet environment is evolving into the 3d internet environment, it is highly desirable to exploit this 3d information in virtual chat environments. there are a few chat systems based on 3d virtual environments that made improvements to these 3d chat systems, such as rendering avatars and 3d spaces, but the problems(managing chat dialogues) in the standard 2d text-based chat remained. so, we proposed more realistic 3d virtual chat system using 3d spatial information[8]. in this paper, we improve our previous work. finally, our experiment shows that our system is highly effective in a virtual chat environment.
interchangeable consistency constraints for public health care systems. severe data quality problems exist in most public health care systems and inconsistent data sets often occur. consistency constraints can be used to define valid and invalid data. existing solutions of such constraints like rule systems are often difficult to maintain, not human-readable, and of a bad quality like containing contradictory rules. with in-daqu we present an approach that allows domain experts to easily create and maintain consistency constraints using an introduced domain-specific language. these constraints are being stored in an ontology, which allows for an automated inconsistency detection in the defined rules themselves. we identified several scenarios in which consistency constraints can be interchanged and exchanged between different participants. the approach has been successfully evaluated in the cancer registry of lower saxony.
constrained viterbi decoding for embedded user-customised password speaker recognition. embedded speaker recognition in mobile devices could involve several ergonomic constraints and a limited amount of computing resources. gmm/ubm systems have proved their efficiency in more classical contexts where good accuracy depends on a relatively large quantity of speech data. the proposed gmm/ubm extension addresses the situations with limited resources and takes advantage from the temporal structure of speech by using client-customised utterances harnessed by a markov model. new temporal information is then used to enhance discrimination with viterbi decoding increasing the gap between client and impostor scores. experiments on the myidea database are performed when impostors know the client-utterance and also when they do not, highlighting the potential of this new approach. a relative gain up to 64% in terms of eer is achieved when impostors do not know the client utterances and performance is equivalent to the gmm/ubm baseline system in other configurations.
an ontology-based software framework to provide educational data mining. this paper presents an ontology-based software framework for providing educational data mining applications, mainly offering flexibility of encapsulate mining techniques with semantic web services. it consists of an architecture based on three layers. a case study and illustrative scenario have been implemented to evaluate the framework feasibility. currently, the evaluation shows the pontential benefits for both the developer and the teacher.
client-side load balancer using cloud. web applications' traffic demand fluctuates widely and unpredictably. the common practice of provisioning a fixed capacity would either result in unsatisfied customers (underprovision) or waste valuable capital investment (overprovision). by leveraging an infrastructure cloud's on-demand, pay-per-use capabilities, we finally can match the capacity with the demand in real time. this paper investigates how we can build a large-scale web server farm in the cloud. our performance study shows that using existing cloud components and optimization techniques, we cannot achieve high scalability. instead, we propose a client-side load balancing architecture, which can scale and handle failure on a milli-second time scale. we experimentally show that our architecture achieves high throughput in a cloud environment while meeting qos requirements.
a standard-driven implementaion of ws-bpel 2.0. we present a systematic study of the ws-bpel 2.0 standard based on two complementary methods: the process of constructing a new high-level ws-bpel implementation driven by the structure of the standard, and an empirical evaluation of existing interpretations of the standard reflected in five widely available ws-bpel-implementations, both commercial and open source. in doing so we uncover a number of new ambiguities. most notably, ws-bpel's integration of xpath 1.0, the data access component of ws-bpel, turns out to be inconsistent with the xpath standard itself, which is evidenced by substantially differing results produced by existing implementations on test cases constructed to exercise their interpretation. the core concepts in ws-bpel have been formalized and analyzed successfully previously. our choice to study the standard by constructing a high-level, standard-driven implementation rather than an abstract, mathematical formalization has made it feasible to cover the complete standard, notably the integration with xpath. given ws-bpel's design goal of being platform-independent the inconsistencies are arguably a serious concern since they cannot be attributed to the quality of any particular implementation.
wms-extracting multiple sections data records from search engine results pages. in this paper, we develop an automatic wrapper for the extraction of multiple sections data records from search engine results pages. in the information extraction world, less attention has been focused on the development of wrappers for the extraction of multiple sections data records. this is evidenced by the fact that there is only one automatic wrapper, mse developed for this purpose. using the separation distance of data records and sections, mse is able to distinguish sections and data records and extract them from search engine results pages. in this study, our approach is the use of dom tree properties to develop an adaptive search method which is able to detect, differentiate, and partition sections and data records. the multiple sections data records labeled are used to pass through a few filtering stages, each filter is designed to filter out a particular group of irrelevant data until one data region containing the relevant records is found. our filtering rules are designed based on visual cue such as text and image size obtained from the browser rendering engine. experimental results show that our wrapper is able to obtain better results than the currently available mse wrapper.
towards the introduction of qos information in a component model. assuring quality of service (qos) properties is critical in the development of component-based distributed systems. this paper presents an approach to introduce qos constraints into a coalgebraic model of software components. such constraints are formally captured through the concept of a q-algebra which, in its turn, can be smoothly integrated in the definition of component combinators.
wikipedia driven autonomous label assignment in wrapper induced tables with missing column names. as the volume of information available on the internet is growing exponentially, it is clear that most of this information will have to be processed and digested by computers to produce useful information for human consumption. unfortunately, most web contents are currently designed for direct human consumption in which it is assumed that a human will decipher the information presented to him in some context and will be able to connect the missing dots, if any. in particular, information presented in some tabular form often does not accompany descriptive titles or column names similar to attribute names in tables. while such omissions are not really an issue for humans, it is truly hard to extract information in autonomous systems in which a machine is expected to understand the meaning of the table presented and extract the right information in the context of the query. it is even more difficult when the information needed is distributed across the globe and involve semantic heterogeneity. in this paper, our goal is to address the issue of how to interpret tables with missing column names by developing a method for the assignment of attributes names in an arbitrary table extracted from the web in a fully autonomous manner. we propose a novel approach by leveraging wikipedia for the first time for column name discovery for the purpose of table annotation. we show that this leads to an improved likelihood of capturing the context and interpretation of the table accurately and producing a semantically meaningful query response.
expert finding in question-answering websites: a novel hybrid approach. question answering websites are becoming an ever more popular knowledge sharing platform. on such websites, people may ask any type of question and then wait for someone else to answer the question. however, in this manner, askers may not obtain correct answers from appropriate experts, and knowledge sharing through question answering websites is interfered. recently, various approaches have been proposed to automatically find experts in question answering websites. in this paper, we propose a novel hybrid approach to effectively find experts for the category of the target question in question answering websites. our approach considers user subject relevance, user reputation and authority of a category in finding experts. the experiment results show that our proposed methods outperform other conventional methods.
similar triangles and orientation in plane elementary geometry for coq-based proofs. in plane elementary geometry, the concept of similar triangles not only forms an important foundation for trigonometry, but it also can be used to solve many geometric problems. the notion of orientation allows us to remove the usual ambiguities in presentation of object. in this paper, we present the formalization of these notions in coq. we also introduce their properties and how they are applied to the proof of two theorems: the ptolemy's theorem and the intersecting chords theorem.
improving complex distributed software system availability through information hiding. for distributed software systems, ensuring their availability under intentional attacks is critical. traffic analysis, conducted by the attacker, could reveal the protocol being carried out by the components. furthermore, having inferred the protocol, the attacker can use the pattern of the messages as a guide to the most critical components. we thwart these directed attacks by using message forwarding to reduce traffic differences, thus diverge attackers from targeted attack to random attack, which probabilistically prolongs the availability of important components in the system. the simulation results also show that message forwarding effectively balance the traffic flow and hence indicate the validity of our approach.
probabilistic anti-spam filtering with dimensionality reduction. one of the biggest problems of e-mail communication is the massive spam message delivery. everyday, billion of unwanted messages are sent by spammers and this number does not stop growing. helpfully, there are different approaches able to automatically detect and remove most of these messages, and a well-known ones are based on bayesian decision theory. however, many machine learning techniques applied to text categorization have the same difficulty: the high dimensionality of the feature space. many term selection methods have been proposed in the literature. nevertheless, it is still unclear how the performance of naive bayes anti-spam filters depends on the methods applied for reducing the dimensionality of the feature space. in this paper, we compare the performance of most popular methods used as term selection techniques with some variations of the original naive bayes anti-spam filter.
art: adaptive, reliable, and fault-tolerant task management for computational grids. the main goal of art is reducing the number of replications by using checkpointing and rollback scheme for each replication. in art, the minimum number of replications is adaptively selected based on analysis of probability of successful execution within the given deadline and reliability requirement of each task. simulation results show that art outperforms existing mechanisms.
metaself: an architecture and a development method for dependable self-* systems. this paper proposes a software architecture and a development process for engineering dependable and controllable self-organising (so) systems. our approach addresses dependability by exploiting metadata to support decision making and adaptation based on the dynamic enforcement of explicitly defined policies. control is obtained by actively modifying metadata, policies or components. we show how this applies to two different systems: (1) a dynamically resilient web service system; and (2) an industrial assembly system with self-adaptive and so capabilities.
a meta model for representing arbitrary meta model hierarchies. "the only constant is change" is an often contemplated sentence in literature which refers to the re-occurring need for adaption of existing information systems -- especially of that category which handles models. here, applying a change often means to re-generate and deploy a complete chain of tools ranging from repositories over modeling environments to frameworks that use models to produce some output (e.g. code generators). using an orthogonal classification as atkinson and k&uuml;hne [3] suggested could resolve this issue. therefore, we developed a meta model that can be used for representing arbitrary meta model hierarchies and can thus be used as a linguistic meta model within the orthogonal classification. one of its features is its support for advanced meta modeling paradigms such as (extended) powertypes, clabjects and deep instantiation.
a novel music recommender by discovering preferable perceptual-patterns from music pieces. nowadays, advanced information and communication technologies ease the access of music pieces. however, it is still hard for the users to find what she/he prefers from a huge amount of music works. to solve this problem, most music recommenders based on collaborative filtering (called cf) utilize the rating logs to predict the user's preference. unfortunately, cf-like recommenders cannot capture the user's preference effectively due to the gap between the complicated musical contents and diverse user preferences. to reduce the gap, in this paper, we propose a novel recommender that integrates musical contents mining and collaborative filtering to achieve high-quality music recommendation. for musical contents mining, the proposed perceptual patterns derived by two-stage clustering are adopted as a kind of musical genes to support music recommendation. for collaborative filtering, pattern-based preference prediction can imply the user's preferred music effectively. the experimental results reveal that our proposed recommender well outperforms the existing recommenders in terms of recommendation quality.
fangs: high speed sequence mapping for next generation sequencers. next generation sequencing machines are generating millions of short dna sequences (reads) everyday. there is a need for efficient algorithms to map these sequences to the reference genome to identify snps or rare transcripts and to fulfill the dream of personalized medicine. we present a fast algorithm for next generation sequencers (fangs), which dynamically reduces the search space by using q-gram filtering and pigeon hole principle to rapidly map 454-roche reads onto a reference genome. fangs is a sequential algorithm designed to find all the matches of a query sequence in the reference genome tolerating a large number of mismatches or insertions/deletions. using fangs, we mapped 50000 reads with a total of 25 million nucleotides to the human genome in as little as 23.3 minutes on a typical desktop computer. through our experiments, we found that fangs is upto an order of magnitude faster than the state-of-the-art techniques for queries of length 500 allowing 5 mismatches or insertion/deletions.
automatically detecting and classifying noises in document images. image filtering to remove noise in document images follows two different approaches. the first one uses human classification of the noise present in an image for identifying a noise filter to use. the second approach is to blindly apply a batch of filters to an image. the former approach, although widely used, may insert noise in the filtering process due to the incorrect classification of the noise or even unsuitable filtering parameters. this paper presents a new paradigm for document image filtering. it aims at doing a more accurate and computationally efficient document cleanup by pre-characterizing the noise that is present in the document based on a set of human labeled training samples. the current focus of the project is on pre-characterization of the following types of noise: back-to-front interference or bleed through, skew and orientation, blur and framing.
evolutionary model tree induction. model trees are a particular case of decision trees employed to solve regression problems. they have the advantage of presenting an interpretable output with an acceptable level of predictive performance. since generating optimal model trees is a np-complete problem, the traditional model tree induction algorithms make use of a greedy heuristic, which may not converge to the global optimal solution. we propose the use of the evolutionary algorithms paradigm (ea) as an alternate heuristic to generate model trees in order to improve the convergence to global optimal solutions. we test the predictive performance of this new approach using public uci datasets, and compare the results with traditional greedy regression/model trees induction algorithms.
prom-oogle: data mining and integration of on-line databases to discover gene promoters. the vast number of on-line biological and medical databases available can be a great resource for biomedical researchers. however, the different types of data and interfaces available can be overwhelming for many biomedical researchers to learn and make effective use of. moreover, the available resources lack needed integration. here we focus on an important task in medical research: to provide researchers with promoter analysis for a given gene. prom-oogle is a web based data mining tool that provides a means for researchers to take a gene name of interest and obtain its promoter sequence in return after automatic integration of text databases. additionally, the program is capable of returning multiple promoters from different genes allowing researchers to study how promoters regulate genes. this tool facilitates the process of acquiring information on a promoter and may lead to interesting discoveries.
listening the photos. in the music field, an open issue is represented by the creation of innovative tools for acquisition, preservation and sharing of information. the strong difficulties in preserving the original carriers, together dedicated equipments able to read any (often obsolete) format, encouraged the analog/digital (a/d) transfer of audio contents in order to make them available in digital libraries. unfortunately, the a/d transfer is often an invasive process. this work proposes an innovative and not-invasive approach to audio extraction from complex source material, such as shellac phonographic discs: pog (photos of ghosts) is the new system, able to reconstruct the audio signal from a still image of a disc surface. it is automatic, needs of low-cost hardware, recognizes different rpm and performs an automatic separation of the tracks; also it is robust with respect to dust and scratches.
a group-based security policy for wireless sensor networks. the protection of wireless sensor networks is an important task, especially for critical situations such as intrusion detection, tamper monitoring, or military applications. to date, much of the emphasis on protecting sensor networks has focused on key management and secure routing. however, as sensors become more capable and ubiquitous, the need for more fine-grained control over their resources grows. in this paper, we present a security policy for wireless sensor networks which provide designers and administrators the ability to fine-tune access to sensor resources. we build on the notion of group-based key establishment to show how group membership can be utilized in deploying a dynamic, robust, and flexible security policy for wireless sensor networks.
estimating node similarity from co-citation in a spatial graph model. co-citation (number of nodes linking to both of a given pair of nodes) is often used heuristically to judge similarity between nodes in a complex network. we investigate the relation between node similarity and co-citation in the context of the spatial preferred attachment (spa) model. the spa model is a spatial model, where nodes live in a metric space, and nodes that are close together in space are considered similar, and are more likely to link to one another. theoretical analysis of the spa model leads to a measure to estimate spatial distance from the link information, based on co-citation as well as the degrees of both nodes. simulation results show this measure to be highly accurate in predicting the actual spatial distance.
an overview and an empirical evaluation of uml-aof: an uml profile for aspect-oriented frameworks. in this paper we present uml-aof and an empirical evaluation about it. uml-aof is a profile that aims to make the design characteristics of aspect-oriented frameworks (aofs) more evident in models than standard profiles for aspect-oriented programming (aop). uml-aof gathers several stereotypes and tagged values which represent design and architectural details commonly found in aofs, such as some idioms, patterns and extension mechanisms. in order to evaluate the applicability of this profile, an empirical study was conducted to analyze the number of errors and the time spent by software engineers using both uml-aof and a conventional profile for aop. based on the collected data, we have observed that the number of errors as well the time spent analyzing the models were significantly better than using the conventional profile.
dynamic contract layers. design by contract (dbc) is a programming technique to separate contract enforcement from application code. dbc provides information about the applicability of methods and helps to narrow down the search space in case of a software failure. however, most dbc implementations suffer from inflexibility: contract enforcement can only be activated or deactivated at compile-time or start-up, contracts are checked globally and cannot be restricted in their scope such as to the current thread of execution, and contracts cannot be grouped according to the concerns they relate to. in this paper, we present dynamic contract layers (dcl) for fine-grained and flexible contract management. based on ideas from context-oriented programming, we extend dbc by a grouping mechanism for contracts, thread-local activation and deactivation of such groups, and selective contract enforcement at run-time. pydcl, our proof-of-concept implementation of dcl, is built onto contextpy, our cop extension for the python programming language. we evaluate our approach by applying pydcl contracts to the moin-moin wiki framework.
graph-based verification of static program constraints. software artifacts usually have static program constraints and these constraints should be satisfied in each reuse. in addition to this, the developers are also required to satisfy the coding conventions used by their organization. because in a complex software system there are too many coding conventions and program constraints to be satisfied, it becomes a cumbersome task to check them all manually. this paper presents a process and tools that allow computer-aided program constraint checking that work on the source code. we developed a modeling language called source code modeling language (scml) in which program elements from the source code can be represented. in the process, the source code is converted into scml models. the constraint detection is realized by graph transformation rules which are also modeled in scml; the rules detect the violation and extract information from the scml model of the source code to provide feedback on the location of the problem. the constraint violations can be queried from a querying mechanism that automatically searches the graph for the extracted information. the process has been applied to an industrial software system.
probabilistic constraints for reliability problems. reliability quantifies the ability of a system to perform its required function under stated conditions. the reliability of a decision is usually represented as the probability of an adequate functioning of the system where both the decision and uncontrollable variables are subject to uncertainty. in this paper we extend previous work on probabilistic constraint programming to compute such reliability, assuming probability distributions for the uncertain values. usually this computation is very hard and requires a number of approximations, thus the computed value may be far from the exact one. traditional methods do not provide any guarantees with respect to correctness of the results provided. we guarantee the computation of safe bounds for the reliability of a decision, which is of major relevance for problems dealing with non-linear constraints.
accelerating multi-core simulators. simulation is an important means of evaluating new microarchitectures. with the invention of multi-core (cmp) platforms, simulators are becoming larger and more complex. however, with the availability of cmps with larger caches and higher operating frequency, the wall clock time required for simulating an application has become comparatively shorter. reducing this simulation time further is a great challenge, especially in the case of multi-threaded workload due to indeterminacy introduced due to simultaneously executing various threads. in this paper, we propose a technique for speeding multi-core simulation. the model of the processor core and cache are replaced with functional models, to achieve speedup. a timed petri net model is used to estimate the execution time of the processor and the memory access latencies are estimated using hit/miss information obtained from the functional model of the cache. this model can be used to predict performance of data parallel applications or multiprogramming workload on cmp platform with various cache hierarchies and shared bus interconnect. the error in estimation of the execution time of an application is within 6%. the speedup achieved ranges between an average of 2x--4x over the cycle accurate simulator.
harnessing input redundancy in a mapreduce framework. the proliferation of data parallel programming on large clusters has set a new research avenue: accommodating numerous types of data-intensive applications with a feasible plan. behind the many research efforts, we can observe that there exists a nontrivial amount of redundant i/o in the execution of data-intensive applications. even the locality-aware scheduling policy in a mapreduce framework is not effective in a cluster environment where storage nodes cannot provide a computation service. in this paper, we introduce split-cache to improve the performance of data-intensive olap-style applications by reducing redundant i/o in a mapreduce framework. the key strategy to achieve the goal is to cut down the i/o redundancy of reading common input data among applications. splitcache caches the first input stream in the computing nodes and reuses them for future demand. in execution of the tpc-h benchmark, we achieved 65.5% faster execution and 87% reduction in network traffic in average.
hypothesis generation and ranking based on event similarities. accelerated by the technological advances in the domain, the size of the biomedical literature has been growing rapidly. as a result, it is not feasible for individual researchers to comprehend and synthesize all the information related to their interests. therefore, it is conceivable to discover hidden knowledge, or hypotheses, by linking fragments of information independently described in the literature. in fact, such hypotheses have been reported in the literature mining community; some of which have even been corroborated by experiments. this paper mainly focuses on hypothesis ranking and investigates an approach to identifying reasonable ones based on semantic similarities between events which lead to respective hypotheses. our assumption is that hypotheses generated from semantically similar events are more reasonable. the validity of our approach is demonstrated in comparison with those based on term frequencies, often adopted in the related work.
fast, flexible, and highly resilient genuine fifo and causal multicast algorithms. we study the fifo and causal multicast problem, two group-communication abstractions that deliver messages in an order consistent with their context. with fifo multicast, the context of a message m at a process p is all messages that were previously multicast by m's sender and addressed to p. causal multicast extends the notion of context to all messages that are causally linked to m by a chain of multicast and delivery events. we propose multicast algorithms for systems composed of a set of disjoint groups of processes: server racks or data centers. these algorithms offer several desirable properties: (i) the protocols are latency-optimal, (ii) to deliver a message m only m's sender and addressees communicate, (iii) messages can be addressed to any subset of groups, and (iv) these algorithms are highly resilient: an arbitrary number of process failures is tolerated and we only require the network to be quasi-reliable, i.e., a message m is guaranteed to be received only if the sender and receiver of m are always up. to the best of our knowledge, these are the first multicast protocols to offer all of these properties at the same time.
an operating system abstraction layer for portable applications in wireless sensor networks. portability of software modules is a major concern in application development for wireless sensor networks (wsn), stressed by the typical lack of resources in embedded systems. abstractions of the hardware platform which are introduced by the operating system (os) allow the development of modules which can be reused in new applications. however, the lack of standards in this domain, restricts the chances to achieve efficient portability to those systems running on very similar platforms (e.g. same os). in this paper, we present an operating system abstraction layer (osal), which unifies the os architecture and establishes a common api across multiple os. portability of applications is effectively granted thanks to a common set of primitives, which are independent of the underlaying os and its particular architecture. we highlight the efficiency of the osal as well as detailed description of its main features and design considerations. we have implemented the osal on top of two well known os and performed extensive evaluations, which show that it effectively reduces portability efforts at the expenses of minimal run-time overhead as well as negligible increase of memory footprint.
a metrics suite for evaluating agent-oriented architectures. the multi-agent systems (mass) paradigm continues to consolidate itself as a new branch of software engineering. traditional software engineering strongly recommends to apply metrics in software developments. however, several research groups of experts in agent-oriented software engineering agree that classical software metrics and object-oriented metrics cannot directly measure the quality of mas architectures. for this reason, this work proposes a suite of metrics to measure certain quality attributes of mas architectures, considering agents and their organization. most of these metrics are inspired by object-oriented metrics but they are adapted to agent-oriented concepts. proposed metrics are validated by the application to four problem domains and eight architectures.
standardized interoperable image retrieval. digital still images are generated, distributed and stored worldwide at an ever increasing rate. yet, the large number of available metadata description formats prevents consistent and efficient access to image repositories. standardized solutions for unifying the access and the retrieval of image repositories are therefore strongly needed. the iso/iec sc29 wg1 (more commonly known as jpeg) established the jpsearch project, which aims to standardize interfaces of an abstract image retrieval framework. in this context, the paper introduces our contribution consisting of a reference metadata model, which in combination with the jpeg query format improves interoperable image retrieval for users. second, a transformation rule declaration language for query reformulation is presented, which contributes to interoperability at the repository side.
a multi-view model-driven approach for packaging software components. tool support in chemical process modeling evolved towards using more complex and more integrated systems, often made by combining smaller sub-systems, coming from different vendors. the increasingly growing heterogeneity of these systems led to the emergence of interoperability standards such as cape-open. however, the component-based architecture imposed by this standard made the development and maintenance of process modelling components more complex. indeed, it requires accurate knowledge about three interconnected domains: the process itself, the standard specification, and the middleware (e.g. com or .net). consequently, both development and maintenance tasks require the collaboration of several experts throughout the entire component lifecycle. tools that assist experts in performing these tasks are thus required. this paper presents an iterative model-driven approach that allows expressing changes through three separated views, each of which is associated to an expert domain, and automatically propagating the effects of these changes in order to generate compliant code. the approach is based on domain-specific modeling and model transformations, and is illustrated through a prototype that has been validated with respect to expected changes impacting the three domains.
external sorting for index construction of large semantic web databases. today's semantic web datasets become increasingly larger containing up to several hundred million triples. the performance of index construction is a crucial factor for the success of large semantic web databases. in this paper, we propose two new approaches for rdf index construction: external chunks merge sort and distribution sort for rdf. the former stores and retrieves chunks from a special chunks heap to speed up replacement selection. the latter leverages the rdf-specific properties to construct rdf indices and significantly improves the performance. our experimental results show that our approaches significantly speed up rdf index construction, and are important techniques for large semantic web databases.
inter-dsl coordination support by combining megamodeling and model weaving. model-driven engineering (mde) advocates the use of models at every step of the software development process. within this context, a team of engineers collectively and collaboratively contribute to a large set of interrelated models. even if the main focus can be on a single model (e.g. a class diagram model), related elements in other models (e.g. a requirement model) often have to be considered and/or accessed. moreover, all the involved models do not necessarily conform to the same metamodel and thus may have been built using different independent domain-specific languages (dsls). such a situation has already been frequently observed in many large-scale industrial deployments of mde. manually coordinating all the involved models, i.e. being able to both manage and use the links existing between them, can become a cumbersome and difficult task. as a proposal to solve this inter-dsl coordination issue, we introduce in this paper a generic and extensible inter-model traceability and navigation environment based on the complementary use of megamodeling and model weaving. we illustrate our solution with a concrete working example.
ontomo: web-based ontology building system: ---instance recommendation using bootstrapping---. in the web research, ontologies are widely used these days. however, several difficulties in ontology building have been pointed out so far and its costs are raising problems currently. in this paper, we propose ontomo that enables internet users to take part in building ontologies as a part of collective intelligence. after introducing an overview of ontomo, an instance and property recommendation mechanism based on the editing history of multiple users will be presented together with experimental evaluations.
advanced motion detection for intelligent video surveillance systems. in this paper, we propose a novel background subtraction method that makes use of spectral, spatial, and temporal features extracted from the video sequence in determination of the best background candidates for background modeling. as the final step of our process, the binary moving object detection mask is computed using prompt background subtraction with our proposed background model. the overall results of these analyses thus demonstrate that our proposed method substantially outperforms existing methods by an f1 metric accuracy rate increase of up to 79%.
background knowledge in formal concept analysis: constraints via closure operators. the aim of this short paper is to present a general method of using background knowledge to impose constraints in conceptual clustering of object-attribute relational data. the proposed method uses the background knowledge to extract only particular clusters from the input data---those which are compatible with the background knowledge and thus satisfy the constraint. as a result, the method allows for extracting less clusters in a shorter time which are in addition more interesting. the paper presents the idea of constraints formalized by means of closure operators and introduces such constraints to a particular clustering technique, namely to formal concept analysis. among the benefits of the presented approach are its versatility (the approach covers several examples studied before, e.g. extraction of closed frequent itemsets in generation of non-redundant association rules) and computational efficiency (polynomial time-delay algorithm for computing constrained clusters). due to scope limitations, we present the main ideas only. details will be available in a full version of this paper.
a two stage yard crane workload partitioning and job sequencing algorithm for container terminals. we propose a new yc workload partitioning scheme which employs dynamic data driven simulations to conduct what-if experiments in container terminals. both the optimal partition of the workload in a row of yard blocks and the optimal dispatching sequences for individual ycs are achieved. the practical consideration of the safety constraints is included. a dynamic programming (dp) approach is used to avoid re-computation. an efficient two stage workload partition algorithm (tswp) is proposed which successfully reduces the number of full what-if simulations while maintaining solution optimality. an effective lower bound (lb) generator with adjustable lb accuracy is designed in supporting the tswp algorithm. experimental results show that the tswp algorithm outperforms the pure dp approach in all tested scenarios and takes less than 1 part per thousand computational time of the dp approach.
feature-based 3d morphing based on geometrically constrained sphere mapping optimization. current trends in free form editing suggest the development of a new novel editing paradigm for cad models beyond traditional cad editing of mechanical parts. to this end we wish to develop accurate, robust and efficient 3d mesh deformation techniques such as 3d structural morphing. in this paper, we present a feature-based approach to 3d morphing of arbitrary genus-0 polyhedral objects that is appropriate for cad editing. the technique is based on a sphere mapping process built on an optimization technique that uses a target function to maintain the correspondence among the initial polygons and the mapped ones while preserving topology and connectivity through a system of geometric constraints. finally, we introduce a fully automated feature-based technique that matches surface areas (feature regions) with similar morphological characteristics between the two morphed objects and performs morphing according to this feature correspondence list. alignment is obtained without user intervention and is based on pattern matching between the feature graphs of the two morphed objects.
swap-before-hibernate: a time efficient method to suspend an os to a flash drive. unlike a magnetic disk, a flash drive needs no seek time when performing random access. in addition, the read speed of a flash drive is faster than the write speed, and the write speed depends on the i/o request size: the bigger the request size, the faster the write speed. system hibernation stores the machine status completely in non-volatile memory. when the system reboots, the data will be reloaded to the machine, and the system status will be recovered completely. the user can continue immediately where they stopped the last time. we use the characteristic that the flash drives requires no seek time when performing random access to write the data in the memory to swap space or a hibernation file, or simply discard it without any i/o. the write process will try to combine random small writes into continuous large writes, if possible, to optimize the write speed. when the system resumes, it only reloads the data that the user needs, and the resume technique is based on paging on demand. paging on demand is actually a kind of random access; however, since the flash drive requires no seek time, it does not drag down the system response time due to reducing the number of i/o.
improving cost and accuracy of dpi traffic classifiers. traffic classification through deep packet inspection (dpi) is considered extremely expensive in terms of processing costs, leading to the conclusion that this technique is not suitable for dpi analysis on high speed networks. however, we believe that performance can be improved by exploiting some common characteristics of the network traffic. in this paper we present and evaluate some optimizations that can definitely decrease the processing cost and can even improve the classification precision.
convex onion peeling genetic algorithm: an efficient solution to map labeling of point-feature. map labeling of point-feature is the problem of placing text labels to corresponding point features on a map in a way that minimizes overlaps while satisfying basic rules for the quality. this problem is a critical problem in the applications of cartography and geographical information systems (gis). in this paper we study the fundamental issues related to map labeling of point-feature and develop a new genetic algorithm to solve this problem. we adopt a data structure called convex onion peeling and utilize it in our proposed convex onion peeling genetic algorithm (copga) to efficiently manage point features. we evaluated the performance of the proposed algorithm through extensive experiments on both synthetic and real datasets. the experimental results show that our genetic algorithm based on the convex onion peeling structure is an efficient, robust and extensible algorithm for automated map labeling of point-feature.
understanding meta-communication in an inclusive scenario. meta-communication can be defined as all exchanges of information that are related to the conceptual model of the system, including the communication that takes place in order to clarify or overcome problems during the communication process. the scenario of having users with low levels of literacy and familiarity with technology has not yet been addressed in help systems. this paper examines previous literature on meta-communication and other support frameworks, and draws on semio-participatory practices conducted within an inclusive scenario to extend the concept of help systems, aiming at a broader scaffolding instrument to let users climb up in the process of learning with the use of inclusive systems. preliminary findings of the investigation inform the design of support systems instantiated in the context of online social networks meant to be inclusive.
network-adaptive management of computation energy in wireless sensor networks. today's sensor nodes can be equipped with powerful microcontrollers to address the increasing need of real-time processing of sensed data. for instance, body sensor networks for gesture recognition require filtering of acceleration values at line rate. this requirement imposes a paradigm shift with regard to more traditional sensor networks characterized by low activity duty cycles. therefore, energy conservation strategies applied to wireless sensor nodes to increase their lifetime must take into account computation power rather than focusing only on communication power. in this paper we present a novel approach which aims at exploiting the knowledge of network status to optimize the power consumption of the node microcontroller. the proposed approach is tested in various network conditions, both synthetic and realistic, in the context of ieee 802.15.4 standard. experimental results demonstrate that the proposed approach allows to achieve power savings of up to 70% with minimum performance penalty.
dual analysis for proving safety and finding bugs. program bugs remain a major challenge for software developers and various tools have been proposed to help with their localization and elimination. most present-day tools are based either on over-approximating techniques that can prove safety but may report false positives, or on under-approximating techniques that can find real bugs but with possible false negatives. in this paper, we propose a dual static analysis that is based on only over-approximation. its main novelty is to concurrently derive conditions that lead to either success or failure outcomes and thus we provide a comprehensive solution for both proving safety and finding real program bugs. we have proven the soundness of our approach and have implemented a prototype system that is validated by a set of experiments.
subjective video quality assessment applied to scalable video coding and transmission instability. this paper presents a study of subjective quality of scalable video sequences, coded using the scalable extension of the h.264 standard (svc). a group of experiments was performed to measure, primarily, the effects that the transmission instability has in the video quality and the relationship between the three scalability methods (spatial, temporal and quality) in terms of subjective quality. the decisions taken to model the tests were based on layered transmission systems that use protocols for adaptability and congestion control. to run the subjective assessments we used the acrhrr methodology and recommendations given by itu-r rec. bt.500 and itu-t rec. p.910. the results show that the instability modeled does not cause signifficant alterations on the overall video quality when compared to a stable video and that temporal scalability usually produces videos with worse quality than spatial and quality scalabilities, the latter being the one with the better quality.
business modeling for service engineering: a case study in the it outsourcing domain. service engineering for both, service-oriented architectures and evolving service market places in the internet, is still a challenge due to dynamic environments, high uncertainties, and increasing coopetition of market participants. against this context, this paper introduces the integrated service engineering framework, presents a conducted case study in the it outsourcing domain, and discusses the framework's performance. additionally, it reviews work related to business modeling. the case study shows that the ise framework is particularly strong in process and data modeling and their derivation from one perspective into the other.
oasnet: an optimal allocation approach to influence maximization in modular social networks. influence maximization in a social network is to target a given number of nodes in the network such that the expected number of activated nodes from these nodes is maximized. a social network usually exhibits some degree of modularity. previous research efforts that made use of this topological property are restricted to random networks with two communities. in this paper, we firstly transform the influence maximization problem in a modular social network to an optimal resource allocation problem in the same network. we assume that the communities of the social network are disconnected. we then propose a recursive relation for finding such an optimal allocation. we prove that finding an optimal allocation in a modular social network is np-hard and propose a new optimal dynamic programming algorithm to solve the problem. we name our new algorithm oasnet (optimal allocation in a social network). we compare oasnet with equal allocation, proportional allocation, random allocation and selecting top degree nodes without any allocation strategy on both synthetic and real world datasets. experimental results show that oasnet outperforms these four heuristics.
enhancing semantic search using case-based modular ontology. in this paper, we present a semantic search approach based on case-based modular ontology. our work aims to improve ontology-based information retrieval by the integration of the traditional information retrieval, the use of ontology and the case based reasoning (cbr). in fact, our recommender approach uses the cbr with ontology for case representation and indexing. ontology-based similarity is used to retrieve similar cases and to provide end users with alternative recommendations. the main contribution of this work is the use of a cbr mechanism and an ontological representation for two purposes: resource retrieval from web and ontology enrichment from cases.
separating the reputation and the sociability of online community users. in online communities or blogospheres, the users publish their posts, and then their posts get feedback actions from other users in the form of a comment, a trackback or a recommendation. these interactions form a graph in which the vertices represent a set of users while the edges represent a set of feedbacks. thus, the problem of users' rankings can be approached in terms of the analysis of the social relationships between the users themselves within this graph. pagerank and hits have often been applied for users' rankings, especially for users' reputation, but there has been no consideration of the fact that the user's sociability can affect the user's reputation. to address this problem, in this paper, we newly propose two different factors that affect the score of every user: the user's reputation and the user's sociability. furthermore, we present novel schemes that effectively and separately can estimate the reputation and the sociability of the users. our experimental results show that: 1) our schemes can effectively separate the user's pure reputation from the user's sociability 2) pure reputation, as it stands alone or when it is combined with sociability, is capable of producing more optimal user ranking results than can the previous works.
mopsi location-based search engine: concept, architecture and prototype. traditional location-based services use databases where all entries have been explicitly georeferenced beforehand. we propose an alternative approach based on web search and using ad-hoc georeferencing of web-pages. we denote it as location-based search engine and emphasize its seemingly small but significant distinction from traditional location-based services. we outline how to construct such search engine and prove its effectiveness using a prototype called mopsi search.
improving the efficiency of dynamic malware analysis. each day, security companies see themselves confronted with thousands of new malware programs. to cope with these large quantities, researchers and practitioners alike have developed dynamic malware analysis systems. these systems automatically execute a program in a controlled environment and produce a report describing the program's behavior. during the last three years, the number of malware programs appearing each day has increased by a factor of ten, and this number is expected to continue to grow. to keep pace with these developments without causing even more hardware costs for operating dynamic analysis systems, we have developed a technique that drastically reduces the overall analysis time. our solution is based on the insight that the huge number of new malicious files is due to mutations of only a few malware programs. to save analysis time, we suggest a technique that avoids performing a full analysis of the same polymorphic file multiple times. in an experiment conducted on a set of 10,922 randomly chosen executable files, our prototype implementation was able to avoid a full dynamic analysis in 25.25 percent of the cases.
a multi-objective optimization approach for fault-tolerance provisioning in multi-radio hybrid wireless-optical broadband access networks. wireless-optical broadband-access networks (wobans), currently being deployed at the access section, should integrate fault-tolerance in their design so that geographically continuous wireless coverage can be provided without service breaks. in this paper we propose a joint wireless and optical fault-tolerance planning approach for wobans having multiple radios in each router. the problem is formalized, as a multi-objective optimization problem, and a heuristic is proposed to solve this problem. two fault-tolerance planning scenarios, where gateways are arranged differently in the risk groups, are analysed. it is shown that multi-radio routers can be exploited to improve the performance of wobans, providing wireless and optical fault-tolerance. results also indicate that, when using our approach, a small increase in the number of radios can significantly decrease the total capacity required to provide any degree of fault-tolerance.
adaptive fuzzy-valued service selection. service composition concerns both integration of heterogeneous distributed applications and dynamic selection of services. qos-aware selection enables a service requester with certain qos requirements to classify services according to their qos guarantees. in this paper we present a method that allows for a fuzzy-valued description of qos parameters. fuzzy sets are suited to specify both the qos preferences raised by a service requester such as 'response time must be as lower as possible and cannot be more that 1000ms' and approximate estimates a provider can make on the qos capabilities of its services like 'availability is roughly between 95% and 99%'. we propose a matchmaking procedure based on a fuzzy-valued similarity measure that, given the specifications of qos parameters of the requester and the providers, selects the most appropriate service among several functionally-equivalent ones. we also devise a method for dynamical update of service offers by means of runtime monitoring of the actual qos performance.
adapting the tf idf vector-space model to domain specific information retrieval. the default implementation in lucene, an open-source search engine, is the well-known vector-space model with tf idf weighting. the objective of this paper is to propose and evaluate additional techniques that can be adapted to this search model, in order to meet the particular needs of domainspecific information retrieval (ir). in this paper, we suggest certain specificity measures derived from either information theory or corpus-based linguistics. as an additional feature we suggest accounting for the number of search terms that a query and retrieved documents have in common. to integrate these methods we design and implement four extensions to the classical tf idf model and then evaluate the new ir models by applying them to four different domain-specific collections and comparing them to results found by a probabilistic retrieval model. the results tend to demonstrate that the adapted vector-space models clearly outperform the baseline approach (tf idf) and that performance levels obtained even surpass those found in the okapi model.
identification and control of intrinsic bias in a multiscale computational model of drug addiction. personalized medicine is rapidly evolving with the objective of providing a patient with medications based on the "use of genetic susceptibility or pharmacogenetic testing to tailor an individual's preventive care or drug therapy" [1]. it is reasonable to foresee that this domain will incorporate sources of biological knowledge other than genetics including computational modeling of diseases. for this purpose, a critical issue is how to identify and control systematic biases that may arise. in this paper, a multiscale computational model of drug addiction is presented and the interpretations of the simulated behavioral profiles of a virtual subject are discussed. these outcomes are analyzed using mathematical analytical techniques with particular attention directed to minimization of systematic biases. the simulations exemplify how a structural analysis of the model, prior to the actual simulations, may benefit the overall framework in terms of accuracy. while this paper focuses on an equation-based model for drug addiction, a similar methodology could be applied to other types of computational models for other diseases.
mining models of exceptional objects through rule learning. a new technique, sniper, is proposed for learning a model that deals with continuous values of exceptionality. specifically, given some training objects associated with a continuous attribute f, sniper induces a rule-based model for the identification of those objects likely to score the maximum values for f. the purpose of sniper differs from the one pursued in regression problems, since its main objective is to retrieve those objects more likely to score the highest values of f. although there are opportunities for improvement, the results of a preliminary evaluation are encouraging. sniper is competitive in the quality of the attained results with respect to some established competitors, while outperforming them when the exceptional objects are very rare. additionally, sniper is much faster in the induction of a model of object exceptionality.
a requirements elicitation framework and tool for sourcing business-it aligned e-services. this paper describes a multiple perspectives goal-oriented requirements elicitation framework aimed at identifying it service requirements for service sourcing in a service-oriented software marketplace (e-services marketplace). the framework is based on decomposing strategic goals into tactical and operational it goals adopting a multiple perspectives elicitation approach that facilitates business-it alignment in the elicitation/mapping of the service requirements and in the choice of the target service offerings. the framework is applicable in a scenario where there is a marketplace of software service providers (e.g. asp's or web service yellow pages) and the sourcing organization is interested in developing service requirements and searching for services available in the marketplace that are aligned with the organizational goals. the framework is supported by a tool that helps the requirements analyst in the process of developing multiple perspectives service goal trees and also in the process of matching service goals to keywords describing service offerings available in the e-service marketplace.
photoland: a new image layout system using spatio-temporal information in digital photos. this paper describes photoland, a system that visualizes hundreds of photos on a 2d grid space to help users manage their photos. it closely places similar photos in the grid based on temporal and spatial information. most photograph management systems use a scrollable view based on a sequential grid layout that arranges the thumbnails of photos in some default order on the screen. our system decreases drag and drop mouse interaction when they classify their photos into small groups comparing to the sequential grid layout. we conducted experiments to evaluate our system. they consider four features: space efficiency, temporal stability and spatial consistency between neighbor photos of the grid, and cluster similarity. although photoland decreases space efficiency, it improves other features compared to the sequential grid layout.
of mice and terms: clustering algorithms on ambiguous terms in folksonomies. developed using the principles of the model-view-controller architectural pattern, folksengine is a parametric search engine for folksonomies that allows us to test arbitrary search improvement algorithms by specifying them in three phases: expansion, where the original query is converted in multiple ones according to semantic rules associated to the query terms, search, executing the queries on a standard folksonomy search engine such as delicious, and ranking, sorting the results according to rules. in this paper we extend our previous studies using folksengine and offer a new query expansion algorithms based on natural language processing techniques, and a new view for the results based on semantic web technologies. we also describe some tests of the algorithms developed, in order to obtain a clear and effective evaluation of them.
enhancing document structure analysis using visual analytics. during the last decade national archives, libraries, museums and companies started to make their records, books and files electronically available. in order to allow efficient access of this information, the content of the documents must be stored in database and information retrieval systems. state-of-the-art indexing techniques mostly rely on the information explicitly available in the text portions of documents. documents usually contain a significant amount of implicit information such as their logical structure which is not directly accessible (unless the documents are available as well-structured xml-files) and is therefore not used in the search process. in this paper, a new approach for analyzing the logical structure of text documents is presented. the problem of state-of-the-art methods is that they have been developed for a particular type of documents and can only handle documents of that type. in most cases, adaptation and re-training for a different document type is not possible. our proposed method allows an efficient and effective adaptation of the structure analysis process by combining state-of-the-art machine learning with novel interactive visualization techniques, allowing a quick adaptation of the structure analysis process to unknown document classes and new tasks without requiring a predefined training set.
a data perturbation approach to sensitive classification rule hiding. this paper focuses on privacy preservation in classification rule mining. the subject at hand is approached through the proposition of a data perturbation approach for hiding sensitive classification rules in categorical datasets. such a methodology is absolutely necessary in case the data needs to be published on the web so that it is amply available for public use as opposed to other approaches like output perturbation or cryptographic techniques that restrict the usability of the data in different ways. this methodology is based upon the unique characteristics of sequential covering classification algorithms. it modifies the tuples of sensitive rules of a dataset d in such a way that these are distributed to the "more important" non-sensitive rules. in addition it assures that the tuples belonging to the sensitive rules are assigned to the non-sensitive rules in proportion to their rank in the ruleset. in that way, it is ensured that not only the sensitive rules are hidden but also that the current structure of the ruleset, thus the information value of the dataset, is preserved. moreover a modification of the basic method which exhibits an alternative distribution procedure is also presented. finally, a series of experiments are executed in order to evaluate the validity and effectiveness of the proposed approaches against existing similar ones.
collaborative interaction through spatially aware moving displays. in many real life situations, people work together using each their own computers. in practice, besides personal communication, such situations often involve exchanging documents and other digital objects. since people are working in a common physical space, it is a natural idea to enlarge the virtual space to a common area where they can exchange objects while taking advantage of the collaborators' physical proximity. in this work we propose a way to allow collaboration through the interaction with objects in a common virtual workspace built on the top of tablet pcs. the concepts of dynamic multiple displays and real world position tracking are implemented exploiting the tablet's embodied resources such as webcam, touch-screen and stylus. also, a multiplayer game was implemented to show how users can exchange information through intercommunicating tablets. we performed user tests to demonstrate the feasibility of collaborative tasks in such environment, and drawn conslusions regarding the impact of the new paradigm of extended multi-user workspaces.
ontologies and summarizability in olap. summarizability, i.e. the correctness of aggregation operations, is essential for olap analysis. summarizability has commonly been studied in the context of dimension hierarchies, but the role of semantics of measure attributes and aggregation functions (sum, avg, min, max, count) has received less research interest. in this paper, we focus on the relationship between measure and dimension attributes and its effect on summarizability. we define the concept of measure-dimension consistency and show how it can be concluded from an olap ontology constructed by using semantic web technologies. measure-dimension consistency can be used both for olap cube construction and queries and it is also very useful when integrating data over the internet.
a service-based context management framework for cross-enterprise collaboration. the more service based applications appear in different business areas such as location based services (lbs) and field service management (fsm), the more important it becomes to support context-awareness in service based systems. exposition, collection, management and consumption of context information are the main processes to be addressed in a service based context management framework. this paper presents a framework, namely cosco, tackling these processes to enrich service applications with context-aware decisions. the presented framework follows the service oriented architecture (soa) principles. adopting soa eases the deployment of our framework into highly dynamic environments where the source of context information can show high level of variability. as a general guideline, we also provide an empirical study of our framework to elicit the performance with different deployment scenarios. the results of our study can help system administrators deploy systems with different capabilities. a context-aware calendar application built by using our framework is also presented at the end of the paper.
oncoviz: a user-centric mining and visualization tool for cancer-related literature. a plethora of health informatioin available on the internet potentially benefits a variety of people, including patients and care providers. however, due to the sheer volume of such information, the benefits have not been fully realized. in this poster, we present a user-centric text information retrieval and knowledge discovery tool, called "oncoviz," for cancer-related literature and navigation of the extracted knowledge as associations using a novel interactive information visualization tool. based on our current results, it shows that a user-centric, integrated information extraction and visualization tool indeed can provide valuable information to users, such as cancer patients and care providers.
evaluation of different feature sets in an ocr free method for word spotting in printed documents. this paper presents the evaluation of tree feature sets in an ocr free word spotting method under a strong experimental protocol. different feature sets are evaluated under the same experimental conditions. in addition, a tuning process in the document segmentation step is proposed which provides a significant reduction in terms of the processing time. for this purpose, a complete ocr-free method for word spotting in printed documents was implemented, and a document database containing document images and their corresponding ground truth text files was created. a strong experimental protocol based on 800 document images allows us to compare the results of the three feature sets used to represent the word image.
asynchronous byzantine consensus with 2f+1 processes. byzantine consensus in asynchronous message-passing systems has been shown to require at least 3f + 1 processes to be solvable in several system models (e.g., with failure detectors, partial synchrony or randomization). recently a couple of solutions to implement byzantine fault-tolerant state-machine replication using only 2f + 1 replicas have appeared. this reduction from 3f + 1 to 2f + 1 is possible with a hybrid system model, i.e., by extending the system model with trusted/trustworthy components that constrain the power of faulty processes to have certain behaviors. despite these important results, the problem of solving byzantine consensus with only 2f + 1 processes is still far from being well understood. in this paper we present a methodology to transform crash consensus algorithms into byzantine consensus algorithms with different characteristics, with the assistance of a reliable broadcast primitive that requires trusted/trustworthy components to be implemented. we exemplify the methodology with two algorithms, one that uses failure detectors and one that is randomized. we also define a new flavor of consensus and use it to solve atomic broadcast, showing the practical interest of the transformations.
integration of a human face annotation technology in an audio-visual search engine platform. search-based web applications are configurable and customizable platforms for multimedia search over the web. this paper describes the results of the integration of an annotation component for automatic face recognition within a configurable multimedia web search platform. we integrate a third-party image analysis technology for human face recognition, by extending it in order to cope with the requirements of video annotation solutions on the web and wrapping it according to the platform's integration specification. as a result, the annotator outcomes are indexed within the platform and can be used for multi-modal and content-based search. we evaluate our experience in terms of development effort required, indexing performances, and perceived quality of the annotation results.
an investigation into the notion of non-functional requirements. although non-functional requirements (nfrs) are recognized as very important contributors to the success of software projects, studies to date indicate that there is still no general consensus in the software engineering community regarding the notion of nfrs. this paper presents the result of an extensive and systematic analysis of the extant literature over three nfrs dimensions: (1) definition and terminology; (2) types; and (3) relevant nfrs in various types of systems and application domains. two different perspectives to consider nfrs are described. a comprehensive catalogue of nfrs types as well as the top five nfrs that are frequently considered are presented. this paper also offers a novel classification of nfrs based on types of systems and application domains. this classification could assist software developers in identifying which nfrs are important in a particular application domain and for specific systems.
se-155 dbsa: a device-based software architecture for data mining. in this paper a new architecture for a variety of data mining tasks is introduced. the device-based software architecture (dbsa) is a highly portable and generic data mining software framework where processing tasks are modeled as components linked together to form a data mining application. the name of the architecture comes from the analogy that each processing task in the framework can be thought of as a device. the framework handles all the devices in the same manner, regardless of whether they have a counterpart in the real world or whether they are just logical devices inside the framework. the dbsa offers many reusable devices, ready to be included in applications, and the application programmer can easily code new devices for the architecture. the framework is bundled with connections to several widely used external tools and languages, making prototyping new applications easy and fast. in the paper we compare dbsa to existing data mining frameworks, review its design and present a case study application implemented with the framework. the paper shows that the dbsa can act as a base for diverse data mining applications.
ressd: a software layer for resuscitating ssds from poor small random write performance. nand flash-based solid state drives have emerged as revolutionary storage media during recent years. however, the wide-spread of ssd technology is currently obstructed by the fact that the random write bandwidth is lower than the sequential write bandwidth by several orders of magnitude. this paper proposes a novel software layer called ressd whose purpose is to resuscitate ssds from poor small random write performance with low memory usage. ressd works as a virtual block device on ssd which does not require any modifications of the operating system kernel and applications. by inspecting all incoming requests, ressd identifies small random writes which have potential to degrade ssd's performance significantly and transforms them into sequential and ordered-sequential writes which are more favorable to ssds. our evaluation results with postmark show that ressd improves the overall performance by up to 72% using a few megabytes of kernel memory.
virtual protocol stack interface for multiple wireless sensor network simulators. we present vpsi, which is a virtual protocol stack interface for wireless network simulators. vpsi provides two features; 1) a unified programming interface for developing network protocols, and 2) separation of simulator engine and the network protocols. by using vpsi, developers do not need to understand multiple different simulator engines. we implemented and adapted vpsi on existing well-known simulation packages, and we observed that vpsi works well with different wireless network simulators.
towards a god-theory for organizational engineering: continuously modeling the continuous (re)generation, operation and deletion of the enterprise. much time is lost, in organizations, in the handling of unknown exceptions because organizational models are not current or coherent with reality and there is a lack of concepts and methods in organizational engineering (oe), for a continuous and timely update of models of organizational reality. to address these problems, a renowned methodology for oe -- demo (design and engineering methodology for organizations) and its underlying theory are improved and extended enabling a precise and integrated modeling of three aspects that we consider to be part of the function perspective of an organization: (1) viability -- specification of vital norms of operation that ensure the viability of the organization, dysfunctions and their causing exceptions, (2) change -- specification of the organizational engineering processes responsible for generation, operation and discontinuation of organizational artifacts (oas) -- for example, business rules or organizational actors -- in order to solve dysfunctions and (3) architecture -- specification of design rules that guide the referred engineering processes, restricting the "shape" of their end result -- oas.
coordination in open and dynamic environments with tucson semantic tuple centres. with the goal of addressing open and dynamic scenarios like the web, in this paper we introduce a semantic-oriented extension of the tuple space model. in our model, each tuple space is equipped with the ontological description of the coordination domain (e.g. expressed in w3c's owl language). tuples represent individuals of the domain along with their properties, and retrieval templates correspond to queries used to check whether an individual is the instance of an ontological concept (as typical in description logics, the logic of semantic reasoning). differently from existing approaches in literature, we obtain a model that is fully expressive -- compared to owl -- with a smooth extension of the standard syntactic setting of tuple spaces, namely, by an intuitive extension of the language for tuples and tuple templates. we discuss an incarnation of this model in the tucson coordination model and infrastructure.
distributed discrimination of media moments and media intervals: a watch-and-comment approach. the watch-and-comment paradigm has been proposed as the seamless capture of comments made by users when appreciating a video, which is watched using a computer or a tv set, for example. the comments can be associated with the original media in several ways so as to generate interactive videos automatically -- the interactive video corresponding to the original video annotated with the captured comments. in this paper we explore the application of the watch-and-comment approach in situations in which the annotations are represented by operators used for the discrimination of instants and time intervals within continuous media. this particular type of annotation can be performed collectively by several users, over distinct instances of media and, for recorded media, at different times. once these discriminations are available, combinations of the annotations may be employed by several classes of applications such as those which exploit collaborative selection, voting, cutting, classification and evaluation. we show the feasibility of the operators by implementing a proof-of-concept prototype on a digital television platform: the prototype supports multiple geographically distributed users who, using distinct input devices, perform collaborative tasks not planned in the original interactive-tv applications.
local lemma: a new strategy of pruning in sat solvers. this paper proposes a search tree pruning strategy for sat solving. it is called local lemma, because it generates lemmas from explored subtrees and these lemmas are valid only in a part of the search tree. the paper explains the basic principle of the strategy, illustrates it with an example, and presents some experimental results.
a committee machine implementing the pattern recognition module for fingerspelling applications. in several countries, deaf communities adopt the sign language as their official and natural language. this fact inserts a new field for the software application development that can improve sign language dissemination and social inclusion of deaf people. alphabetic character-based applications, like games and educational softwares, can be adapted to run as fingerspelling-based applications, in which the inputs are signs (static images or videos) rather than letters (typed letters). in this paper, we present a pattern recognition module, implemented by committee machine, for fingerspelling applications. the committee experts are built with supervised and unsupervised fuzzy learning vector quantization models using the "boosting by filtering" strategy. the module was tested in a specific sign language context considering hand configurations and hand movements.
recognizing affect from non-stylized body motion using shape of gaussian descriptors. in this paper, we address the problem of recognizing affect from non-stylized human body motion. we utilize a novel feature descriptor which is based on the shape of signal probability density function framework to represent the motion capture data. combining the feature representation scheme with support vector machine classifier, we detect implicitly communicated affect in human body motion. we test our algorithm using a comprehensive database of affectively performed motion. experiment results show state-of-the-art performance compared with the existing methods.
a machine-checked soundness proof for an efficient verification condition generator. verification conditions (vcs) are logical formulae whose validity implies the correctness of a program with respect to a specification. the technique of checking software properties by specifying them in a program logic, then generating vcs, and finally feeding these vcs to a theorem prover, is several decades old. it is the underlying technology for state-of-the-art program verifiers such as the spec# programming system, or esc/java. the classic way of computing vcs is by means of dijkstra's weakest precondition calculus. however, modern verification condition generators (vcgens), including spec# and esc/java's vcgens, are based on an optimized version of this algorithm, that avoids an exponential growth of the vcs in the length of the program to be verified. for this optimized vcgen algorithm, only informal soundness arguments are available. the main contribution of this paper is a fully formal, machine-checked proof of the soundness of such an efficient vcgen algorithm.
software tools for requirements management in an erp system context. identification and specification of business requirements are extremely important when development of enterprise resource planning systems (erps) take place. our aim is to present some prescriptive thoughts about requirements management useful when developing future requirements management software tools in the erp system realm. from an initial test we suggest further research in this area that could end up in some more practical guidelines on how to develop a requirement management software tool that can be used when developing future erps.
fast file-type identification. this paper proposes two techniques to reduce the classification time of content-based file type identification. the first is a feature selection technique, which uses a subset of highly-occurring byte patterns in building the representative model of a file type and classifying files. the second is a content sampling technique, which uses a subset of file content in obtaining its byte-frequency distribution. our initial experiments show that the proposed approaches are promising even the simple 1-gram features are used for the classification.
feature interaction networks. a quantitative approach for measuring and describing feature interactions in object-oriented software components based on source code inspection is presented. the methodical arsenal is borrowed from the field of network analysis. based on data gathering through source code harvesting, network representations of feature implementations (i.e., feature interaction networks, fins) are constructed. by applying established network statistics, various properties of interaction structures between features can be captured, e.g. the scatteredness, the degree of crosscutting (scattering), and the scattering concentration. this approach contrasts with related proposals based on frequency and dispersion measures.
an ontology-based semantic foundation for aris epcs. this paper presents an ontological analysis of the epc (event-driven process chain) business process modeling notation supported in the aris toolset. this ontological analysis provides an interpretation of the modeling elements in epc diagrams in terms of the ufo foundational ontology. this enables us to define the precise real-world semantics for business process models represented through epcs and allows us to identify problems affecting the clarity and expressiveness of epcs. in our analysis, we consider an up-to-date metamodel of the aris method that we have defined in our earlier work, which specifies epcs as currently supported by the aris toolset. to the best of our knowledge, the interpretation proposed here is presently the most complete ontological account for epcs.
assessing the impact of refactoring activities on the jhotdraw project. refactoring is a well-known technique for improving the maintainability of software products. however, it is not easy to justify the time and effort needed to refactor code as the benefits are difficult to quantify, especially the perception of improved maintainability. in this paper, we highlight some results of a retrospective case study undertaken to shed light on how refactoring affects maintainability of a software product. there are several findings. first of all, refactoring affects the amount of subsequent changes. furthermore, refactoring has a positive impact on the coupling relationships with dependent software applications.
web-based graphical querying of databases through an ontology: the wonder system. biological scientists have made large amounts of data available on the web, which can be accessed by canned or precomputed queries presented via web forms. to satisfy further information needs, users currently have to have a good understanding of sql and how the data is stored in the database. while accessing information at the ontological layer seems more appropriate, this poses two challenges: (1) to query data in databases and triple stores through an ontology with little performance overhead, and (2) to provide an intuitive web-based access to users that are not it experts. to address these issues, we draw upon the theory and technology developed for ontology-based data access for dl-lite. with an owl ontology and the dig-quonto reasoner as building blocks, we have developed an application that allows for graphical ontology browsing, query formulation, and answer retrieval via a web browser. we have evaluated our system for web-ontology based extraction of relational data (wonder) with an existing large genomics database about horizontal gene transfer and found that it meets both the scalability and the usability requirements.
smac: spatial map caching technique for mobile devices. applications for location-based services (lbs) are becoming more and more popular. however, the continuous access to the wireless internet to get map tiles from servers can significantly affect the quality of the user experience, or might be too expensive. in this paper, we present smac, spatial map caching, a caching technique devised for storing map tiles on the secondary memory of mobile devices. differently from classical caching techniques, such as lru, smac is based on the spatial locality principle that characterizes the way maps are shown to moving users.
towards modular i* models. the i* framework cannot effectively model crosscutting concerns, compromising modularity, reusability and evolution of the results. our approach embodies a specific notation to represent and compose aspectual i* models, using aspect-orientation to address modularity and composition of crosscutting concerns. this represents a step forward to improve separation of concerns in i*.
semantically enabled business process discovery. business process descriptions are usually stored in internal enterprise repositories. in order to be able to reuse business processes (a.k.a. bps), bp designers require some tools to help them to discover processes (or fragments of processes) in the repository based on these descriptions. in most cases discovery is a difficult task (the diversity of modeling languages, the process descriptions are very close to the it level being far from the business level, there is a lack of automatic tools, etc.). in this paper we investigate the use of semantics to alleviate the above mentioned problems providing with a method for the discovery of bps. we have developed an rdf vocabulary to annotate and store bps. first we use the vocabulary to annotate functional and non functional properties of basic activities of xml-based bp descriptions. then we build an rdf knowledge base following the developed rdf vocabulary by extracting, in an automatic way, these properties and the structural properties from the bp description. in addition, functional and non functional properties of structured activities are automatically computed and added to the rdf knowledge base. then the rdf knowledge base can be queried with sparql to achieve bps discovery. in addition, we present an implementation prototype.
mobile air pollution monitoring network. current methods of estimating air quality involve assigning a single value called the air quality index (aqi) to a large land area for a 24-hour period based on a very few, sparsely-located sensors. this produces a low-resolution image of the air quality in that region. we have devised a new mobile air quality monitoring network with the ability to provide high-resolution realtime pollution data at any location within the coverage area. we have prototyped sensors and proven the feasibility of the approach, and are currently testing a small-scale implementation using irregularly-sampled spatiotemporal measurements from mobile car-mounted sensors coupled with existing static data. this data feeds a web-based application, enabling users to view air quality in specific regions as well as estimate exposure over specified time periods and plan routes based on minimal exposure to a given pollutant.
rdfswarms: selforganized distributed rdf triple store. we present and evaluate a distributed rdf storage that uses swarm algorithms to cluster similar rdf triples based on a configurable similarity measure.
maintaining data reliability without availability in p2p storage systems. peer-to-peer (p2p) storage is a promising technology to provide users with cheap and online persistence. however, due the instability of these infrastructures, p2p storage systems must introduce redundancy in order to guarantee a reliable storage service. besides, they need data repair algorithms to maintain this redundancy in front of permanent node departures. to ensure that such repairs can always be run, existing p2p storage systems aim to maintain 100% data availability. unfortunately, this solution seems to overkill in preventing data loses, introducing network and data overheads. in this paper we propose a new data repair algorithm able to guarantee a high reliable storage service without 100% data availability. the main idea is to ensure that objects are kept stored instead of maintaining them available. we analytically prove that our approach reduces considerably the total amount of redundancy. moreover, through simulation, we show how our approach significantly reduces the required number of repairs, decreasing both, the network and the storage overheads.
text line detection and segmentation: uneven skew angles and hill-and-dale writing. a line detection and segmentation technique is presented. the proposed technique is an improved version of an older technique. the experiments have been performed on the dataset of the icdar 2007 handwriting segmentation contest in order to be able to compare, objectively, the performance of the two techniques. the improvement between the older and newer version is more than 24% while the average extra cpu time cost is less than 200 ms per page.
trustworthy interaction balancing in mixed service-oriented systems. web-based collaboration systems typically require dynamic and context-based interactions between people and services. to support such complex interaction scenarios, we introduce a mixed service-oriented system that is composed of both humans and software services, collaborating and interacting to perform certain activities. as an example, consider a professional online help and support community spanning interactions between human participants and software-based services. trust between these members is essential for successful collaborations and has been extensively studied in the context of social and collaborative networks. in this paper, we discuss trust from a collaborative and social point of view instead of a security perspective. our approach follows an interaction monitoring and an interpretative rule-based trust inference model established on previous behavior. however, trust relations encourage network members to continue interacting with successful (and thus trusted) collaboration partners, and to avoid, or even refuse, interactions with unknown actors. this behavior has negative side-effects from a global community perspective. given the help and support environment, a small number of popular network members will become increasingly overloaded with support requests. we solve this load and interaction balancing problem by the means of trustworthy request delegations.
a discriminated correlation classifier for face recognition. in this paper, a discriminated correlation classifier is proposed to improve the performance of the two-dimensional (2-d) face recognition algorithm. until now, many methods have been proposed to address the problems encountered by face recognition system, such as small number problem, pose and illumination variation, etc. all these works are aiming at enhancing the performance of the face recognition system. however, as far as we know, few work are concerning about how to improve the classifier, whose performance directly determines the final recognition accuracy. so, in this paper, our motivation is to improve the performance of correlation classifier, which is widely used in face recognition problems, to improve the recognition accuracy. inspired by a correlation filter design method called minimal average correlation energy(mace) filter, we propose a novel classifier called discriminated semi-normalized correlation (dsnc) classifier using our discriminative learning method. compared with the classical discriminative learning methods that need many intra-class samples and can only be applied on close set recognition problems, our method needs only one intra-class sample and can be performed on open set face recognition problem. the validity of our method is tested on two benchmark face database(frgc2.0 and feret), and a private face database(thfaceid).
document retrieval using image features. this paper describes a new approach to document classification based on visual features alone. text-based retrieval systems perform poorly on noisy text. we have conducted series of experiments using cosine distance as our similarity measure, selecting varying numbers local interest points per page, and varying numbers of nearest neighbour points in the similarity calculations. we have found that a distance-based measure of similarity outperforms a rank-based measure except when there are few interest points. we show that using visual features substantially outperforms text-based approaches for noisy text, giving average precision in the range 0.4--0.43 in several experiments retrieving scientific papers.
using xml schema to improve writing, validation, and structure of ws-policies. ws-policies provide a standard to describe non-functional properties of web services. these properties are usually defined by domain-specific assertions. in some domains, for example security, nested assertions are heavily used to formalize detailed properties. since the ws-policy schema syntactically allows the use of arbitrary child elements for the elements defined in the ws-policy namespace, the validation of policy documents against concrete policy schemata is also complicated. additionally, policies become bloated by requiring the use of nested policies that are often empty or just containing one entry. in this paper, we suggest to enhance the xml schema of concrete policies to allow for easier writing, better validation, simpler structure, and better tool support when working with policies. the enhancements are realized using domain-specific policy elements and omitting unnecessary nested policy elements. a template for enhancing the xml schema to support these requirements is provided. old policy documents still remain compatible with the new schema. the proposed improvements are applied to a complex concrete policy, namely ws-securitypolicy.
cross-organizational process monitoring based on service choreographies. business process monitoring in the area of service oriented computing is typically performed using business activity monitoring technology in an intra-organizational setting. due to outsourcing and the increasing need for companies to work together to meet their joint customer demands, there is a need for monitoring of business processes across organizational boundaries. thereby, partners in a choreography have to exchange monitoring data, in order to enable process tracking and evaluation of process metrics. in this paper, we describe an event-based monitoring approach based on bpel4chor service choreography descriptions. we show how to define monitoring agreements specifying events each partner in the choreography has to provide. we distinguish between resource events and complex events for calculation of process metrics using complex event processing technology. we present our implementation and evaluate the concepts based on a scenario.
flash-aware cluster allocation method based on filename extension for fat file system. to support conventional file systems such as fat, the nand flash memory needs the ftl to provide transparent block device emulation to the file system. however, the log-block ftl, the most popularly used ftl, suffers from the performance decline in workloads that contain many random writes. when the file system is not aware of the nand flash, it often allocates files fragmented in the nand flash, and this causes many random writes. consequently, to improve the performance of the ftl, the file system must allocate files defragmented in the nand flash. in this paper, we propose a nand flash-aware cluster allocation method for fat file system, named feca (flash-aware extension-based cluster allocation). feca exploits the following two observations. the first one is that the effort to defragment small-sized files may not improve the performance at all times. the second one is that there is a very strong correlation between the size and the filename extension of files in most cases. based on those observations, feca predicts sizes of files by using their extensions and determines the allocation policy for them. to evaluate the effectiveness of feca, we devise two defragmentation metrics considering the features of the nand flash. we prove that feca outperforms previous methods in terms of both metrics through extensive experiments. the results show that feca improves the performance by 10 % and reduces the garbage collection frequency up to 35% compared to the previous methods.
transductive learning for spatial regression with co-training. many spatial phenomena are characterized by positive autocorrelation, i.e., variables take similar values at pairs of close locations. this property is strongly related to the smoothness assumption made in transductive learning, according to which if points in a high-density region are close, corresponding outputs should also be close. this observation, together with the prior availability of large sets of unlabelled data, which is typical in spatial applications, motivates the investigation of transductive learning for spatial data mining. the task considered in this work is spatial regression. we apply the co-training technique in order to iteratively learn two separate models, such that each model is used to make predictions on unlabeled data for the other. one model is built on the set of attribute-value observations measured at specific sites, while the other is built on the set of aggregated values measured for the same attributes in nearby sites. experiments prove the effectiveness of the proposed approach on spatial domains.
target-based database synchronization. synchronizing source and target databases is an important task in many database applications. there are instances when the synchronization of source and target databases must be driven from the target's side and involve no changes to the source's schema or triggers. we describe an algorithm for such synchronization. our algorithm groups tuples into partitions and compares hashes of matching source and target partitions before synchronizing only those partitions whose hashes do not match. the hash comparisons decrease the number of tuples that must be exchanged when the source and target are nearly synchronized already. two variants of full replication that differ on locking strategies are used as benchmarks. empirical results show that our method outperforms both when there are few changes to the database and outperforms row-level locking when fewer than 70% of the partitions are changed.
an indoor tracking algorithm with the virtual reference based positioning. the widespread popularization of ubiquitous devices promotes fervent demands for location-based services (lbs). this paper technically proposes a methodology named virtual reference based positioning (vrbp) for the location positioning, which models the rfid positioning systems with virtual reference tags and constructs such information with a classical radio propagation model in order to enhance positioning accuracy. instead of deploying a high density of rfid tags, the notion of vrbp decreases the possibility of signal interference. furthermore, we propose the vt-landmarc, a tracking algorithm which applies the vrbp and manifests a superior performance over the original landmarc in positioning accuracy. besides these advantages, with the help of the vrbp, the vt-landmarc ameliorates the defect in original landmarc that the location error may increase significantly in the margin area. and the vrbp methodology offers a practical solution for the location estimation with a scarce density of reference tags.
an algorithm to generate the context-sensitive synchronized control flow graph. the verification of industrial systems specified with csp often implies the analysis of many concurrent and synchronized components. the cost associated to these analyses is usually very high, and sometimes prohibitive, due to the complexity imposed by the non-deterministic execution order of processes and to the restrictions imposed on this order by synchronizations. to overcome this problem, there has been a recent proposal that allows to statically simplify a specification before the analyses. this simplification allows to drastically reduce the time needed by the analyses because it reduces the state explosion. unfortunately, the approach has been implemented but it has not been formalized neither proved correct. in this paper, we formally define the data structures needed to automatically simplify a csp specification and we define an algorithm able to automatically generate these data structures.
input device for disabled persons using expiration and tooth-touch sound signals. this paper presents the realization of an input device for disabled persons, a hands-free man-machine interface using expiration and tooth-touch sound signals. in our research, the expiration signal was detected by a piezo film sensor array and the tooth-touch sound signal by a bone-conduction microphone. the piezo film sensor had two useful effects, piezoelectric and pyroelectric. utilizing both these effects, we could detect vibration and temperature variation simultaneously. thus, the duration and strength of expiration could be detected more accurately, minimizing the effect of interference from outside disturbance. the sensors also had added benefits, including being very light weight, small in size and of low-price. the device enabled disabled persons to dramatically extend the number of control channels hands-free by changing the strength and duration of expiration, in conjunction with the tooth-touch sound signal. we developed a novel method for separating the pyroelectric and piezoelectric signals from the original signal. we then designed the device using hardware description language (vhdl) and applied it in a field programmable gate array (fpga) chip. we tested our device in a head mounted display (hmd) controller. finally, we evaluated its performance using the following categories: input error rate, usability and input efficiency compared with a tooth-touch sound alone based input device.
r-leap+: randomizing leap+ key distribution to resist replay and jamming attacks. the unique properties of wireless sensor networks make key distribution a particularly difficult problem. two protocols, leap+ and eschenauer-gligor (eg), offer creative and effective solutions to this problem via time-limited key establishment and randomized key pre-distribution, respectively. however, leap+ key establishment may be thwarted by jamming attacks, and eg is vulnerable to node compromise attacks. in this paper, we offer a hybrid of these two schemes that preserves the desirable properties of each scheme, but is immune to each scheme's greatest weakness.
a framework for risk analysis in virtual directory security. directory services are used by almost every enterprise computing environment. virtual directories are components that provide directory services in a highly customized manner. unfortunately, an analysis of risks posed by their unique position and architecture has not been completed. we present a detailed analysis of six attacks to virtual directory services. we also describe various categories of attack risks, and discuss what is necessary to launch an attack. finally, we present a framework to use in analyzing these risks.
serviso: a selective retransmission scheme for video streaming in overlay networks. several works proposed methods to make video streaming scalable over the number of clients, avoiding the linear growth of bandwidth requirements for the media source node. some are based on overlay networks built on top of the ip protocol and distribute content between overlay partners. in this way the clients share their bandwidth, reducing the burden on the source node. similar to data-oriented proposals, this work breaks the media into segments which are requested from partners when available. novel in this technique is the explicit handling of losses with a selective retransmission mechanism based on h.264 content, controlled by estimated decoding importance of packets.
semi-automated diagnosis of foda feature diagram. a semi-automated model diagnostic method is proposed for foda feature diagram, a primary modeling notation used in software product line engineering. the proposed method includes a propositional logic interpretation of the feature diagram and a diagram-slicing algorithm for locating bugs. in addition to logic-based formalization of the semantics, the novelty of our approach is that it uses heuristics taking into account the diagram graph structure. although human intelligence is always involved in removing bugs from feature diagrams, the checking and diagnosing of them can be automated to some extent.
text versus non-text distinction in online handwritten documents. the aim of this paper is to explore how well the task of text vs. nontext distinction can be solved in online handwritten documents using only offline information. two systems are introduced. the first system generates a document segmentation first. for this purpose, four methods originally developed for machine printed documents are compared: x-y cut, morphological closing, voronoi segmentation, and whitespace analysis. a state-of-the art classifier then distinguishes between text and non-text zones. the second system follows a bottom-up approach that classifies connected components. experiments are performed on a new dataset of online handwritten documents containing different content types in arbitrary arrangements. the best system assigns 94.3% of the pixels to the correct class.
design of a market-based mechanism for quality attribute tradeoff of services in the cloud. cloud computing, with its promise of (almost) unlimited computation, storage and bandwidth, is increasingly becoming the infrastructure of choice for many organizations. as applications gain in popularity and mature, the quality attributes demanded of them change significantly. applications that manage themselves and exhibit different quality attributes, based on demand, are the ideal that we would like to have. creating self-managing applications for the cloud present significant problems, since the cloud infrastructure is not under the application architect's control. we propose an initial design of novel market-based mechanism to allow web-applications living on the cloud to self-manage with regard to their quality attributes. we use a scenario to exemplify and evaluate the approach.
performance analysis of flexray-based systems using real-time calculus, revisited. the flexray protocol [4] is likely to be the de facto standard for automotive communication systems. hence, there is a need to provide hard performance guarantees on properties like worst case response times of messages, their buffer requirements, end-to-end latency (for example, from sensor to actuator), etc., for flexray based systems. the paper [11] provides an analysis for finding worst case response times of the messages transmitted on the flexray bus, but the analysis is done using ilp formulation and is thus computationally expensive. the paper [5] models the flexray in the analytic framework of real-time calculus [12, 3] and is compositional as well as scalable. in this paper, we show that the analysis of [5] may lead to results that are over optimistic; in particular, we show that obtaining the "upper service curves" is not trivial and does not follow the reasoning of the "lower service curves" which the authors obtain. we also provide tighter "lower service curves" than that of [5]. finally we show that our model allows the messages to be of variable size which is not the case with [5].
digital energy metering for electrical system management. electrical energy metering is investigated due to the demand for energy efficiency. the scope was digital dc metering (ac later), in a cost effective and accurate manner. accurate voltage, current and time values were necessary. detailed algorithms were needed and created. an energy calibrator system was designed with two agilent meters, an rto-b sense resistor, and a pc interface (visual basic). a prototype meter was designed using the msp430 microcontroller and bvs-m sense resistor (1m&omega;), and was tested. special attention had to be given to the msp430's embedded 16-bit adc and op-amp system which was complicated, yet powerful. from the msp430, a highly functional, low cost energy meter was realized.
exploring business value models from the inter-organizational collaboration perspective. from a strategic enterprise perspective, the success of e-services depends on their ability to work as a medium for the exchange of business values. thus, there is a need to be able to describe and analyze business collaborations in a structured way, in order to identify the needs and appropriate offerings of the participating actors. to model business collaborations, business value models are increasingly used. however, a question remains - how to systematically create value models in order to identify the offerings of the involved actors, while spanning the whole life-cycle of a business collaboration? in this study we propose a method for designing more exploratory business models with a focus to how: (a). consumers classify values, and (b). the values are elicited in different phases of business collaboration life-cycle. a case study from the swedish health care sector is used to ground and apply the presented method.
classification of violent web images using context based analysis. the development of the web has been paralleled by the proliferation of a harmful content on its pages. using violent web images as a case study, we tend to present a novel approach to their classification. this subject is of high importance as it has a potential use in many applications such as violent web sites filtering. we, therefore, focus our attention on the extraction of contextual image features from the web page. also, we present a comparative study of different data mining techniques to classify violent web images. the results we achieved show that our approach can detect violent content effectively.
agents & artefacts for multiple models coordination: objective and decentralized coordination of simulators. complex systems simulation implies the interaction of different scientific fields. however, most of the time people involved into the simulation process do not know intricate distributed simulation tools and only care about their own domain modelling. we propose a framework (called aa4mm) to build a simulation as a society of interacting models. the main goal is to reuse existing models and simulators and to make them interact. the coordination challenges remain to the aa4mm framework so that the simulation design and implementation stay as simple as possible. in this paper, we present the coordination model which intends to decentralize the simulators interactions. we propose to use the environment through the notion of artefact in order to deal with the coherence, compatibility and coordination issues that appear in parallel simulations.
exploiting non-functional preferences in architectural adaptation for self-managed systems. among the many challenges of engineering dependable, self-managed, component-based systems is their need to make informed decisions about adaptive reconfigurations in response to changing requirements or a changing environment. such decisions may be made on the basis of non-functional or qos aspects of reconfiguration in addition to the purely functional properties needed to meet a goal. we present a practical approach for using non-functional information to guide a procedure for assembling, and subsequently modifying, configurations of software components, and compare the performance of two variants of the approach. in addition, we outline a scheme for monitoring non-functional properties in the running system such that more accurate information can be utilised in the next adaptation.
quantitative assessments of key success factors in software process improvement for small and medium web companies. this replicated study investigates spi success factors for small and medium web companies using data from 20 pakistani web companies and 72 respondents. it applies the same theoretical model of spi success factors, techniques and data collection questionnaire proposed and employed in [17]; however, it differs from [17] in that dyba investigated spi success factors for software companies, whereas this study focuses solely on web companies. therefore the contribution of this work is twofold: i) to replicate dyba's study assessing similarity of patterns within the context of small and medium web companies; ii) to extend the theoretical model proposed in [19] [21] to small and medium web companies. the significance of six contributing independent variables, 42 sub-factors and the effects of two moderating variables on dependent variable spi success have been analyzed.
parallel genetic algorithm approaches applied to solve a synchronized and integrated lot sizing and scheduling problem. this paper evaluates different parallel approaches for multipopulation genetic algorithm. these approaches are applied to solve a synchronized and integrated lot sizing and scheduling problem. in this problem, the challenge is to simultaneously determine lot sizing and scheduling for raw materials in tanks and products in lines. first, the parallel algorithms are designed to be executed using a multicore server. the best approach is also executed by duo core computers using mpi. a set of real-world instances found in the literature are solved. also, a new set of instances is proposed. the speedups improvements are showed as well as the quality of final solutions found.
mobile intelligent interruptions management (miim): a context aware unavailability system. mobile phones that currently cause interruptions by blindly allowing calls to ring at busy moments and inappropriate situations can be managed using context aware computing, ubiquitous computing, and the available sensors built into a modern handheld. this paper proposes the architecture of a system named mobile intelligent interruptions management (miim), created for the automated administration of personal unavailability with regard to cell phones. here, we provide the description of the problem, desirable characteristics and architecture of such an interruption management system. the system is being simulated and the initial results show that miim's computational volumes are low enough for a mobile device. platform support has been found in google android.
chemotaxis-based sorting of self-organizing heterotypic agents. cell sorting is a fundamental phenomenon in morphogenesis, which is the process that leads to shape formation in living organisms. the sorting of heterotypic cell populations is produced by a variety of inter-cellular actions, e.g. differential chemotactic response, adhesion and motility. via a process called chemotaxis, living cells respond to chemicals released by other cells into the environment. each cell can respond to the stimulus by moving in the direction of the gradient of the cumulative chemical field detected at its surface. inspired by the biological phenomena of chemotaxis and cell sorting in heterotypic cell aggregates, we propose a chemotaxis-based algorithm for the sorting of self- organizing heterotypic agents. in our algorithm two types of agents are initially randomly placed in a toroidal environment. agents emit a chemical signal and interact with nearby agents. given the appropriate parameters, the two kinds of agents self-organize into a complex aggregate consisting of a group of one type of agents surrounded by agents of the second type. this paper describes the chemotaxis- based sorting algorithm, the behaviors of our self-organizing heterotypic agents, evaluation of the final aggregates and parametric studies of the results.
a study of relative redundancy in test-suite reduction while retaining or improving fault-localization effectiveness. test-suite reduction technique aims to find a subset of the test suite while still satisfying the original test requirements; therefore, it can save the cost of software testing. because many test cases have been removed, the testing information is also lost. fault localization is a technique using testing information to locate the fault and widely used by programmers to debug programs, so it suffers from the side effects of test-suite reduction. how to reduce the test-suite size in software testing with the premise of retaining or improving fault-localization effectiveness has become the hot spot in the area of software debugging recently. in this paper, we propose a new approach that selectively keeps the limited redundant test cases in the reduced set; it makes the new reduced set relatively redundant compared to the original one, and we expect that it retains or even improves fault-localization effectiveness. we also describe a framework that implements our approach and conduct a set of empirical studies for evaluation. the results show that our approach can retain or even improve fault-localization effectiveness as expected.
relational consistency by constraint filtering. in this paper, we propose a new algorithm for enforcing relational consistency on every set of k constraints of a finite constraint satisfaction problem (csp). this algorithm operates by filtering the constraint while leaving the topology of the graph unchanged. we study the resulting relational consistency property and compare it to existing ones. we evaluate the effectiveness of our algorithm in a search procedure for solving csps and demonstrate the applicability, effectiveness, and usefulness of enforcing high levels of consistency.
polytope-based computation of polynomial ranges. polynomial ranges are commonly used for numerically solving polynomial systems with interval newton solvers. often ranges are computed using the convex hull property of the tensorial bernstein basis, which is exponential size in the number n of variables. in this paper, we consider methods to compute tight bounds for polynomials in n variables by solving two linear programming problems over a polytope. we formulate several polytopes based on the tensorial bernstein basis, and we formulate a polytope for the quadratic patch qn:= (x1, ..., xn, x21, ..., x2n, x1x2, ..., xn-1xn) by projections. this bernstein polytope has &theta;(n2) hyperplanes. we give the number of vertices, the number of hyperplanes, and the volume of each polytope for n = 1, 2, 3, 4, and we compare the computed range widths for random n-variate polynomials for n &le; 10. the bernstein polytope of polynomial size gives only marginally worse range bounds compared to the range bounds obtained with the tensorial bernstein basis of exponential size.
referrer graph: a low-cost web prediction algorithm. this paper presents the referrer graph (rg) web prediction algorithm as a low-cost solution to predict next web user accesses. rg is aimed at being used in a real web system with prefetching capabilities without degrading its performance. the algorithm learns from user accesses and builds a markov model. these kinds kind of algorithms use the sequence of the user accesses to make predictions. unlike previous markov model based proposals, the rg algorithm differentiates dependencies in objects of the same page from objects of different pages by using the object uri and referrer in each request. this permits us to build a simple data structure that is easier to handle and, consequently, with a lower computational cost in comparison with other algorithms. the rg algorithm has been evaluated and compared with the best prediction algorithms proposed in the open literature, and the results show that it achieves similar precision values and page latency savings but requiring much less computational and memory resources.
formal analysis of policy-based self-adaptive systems. pobsam is a flexible actor-based model with formal foundation for model-based development of self-adaptive systems. in pobsam policies are used to control and adapt the system behavior, and allow us to decouple the adaptation concerns from the application code. in this paper, we use the actor-based language rebeca to model check pobsam models. since policies are used to govern the system behavior, it is required to verify if the governing policies are enforced correctly. to this aim, we present a new generic classification of the policy conflicts and provide temporal patterns expressed in ltl to detect each class of conflicts. moreover, we propose ltl patterns for checking the correctness of adaptation. an approach based on static analysis of adaptation policies is presented to check the system stability as well.
social music making on the web with codes. music making is usually considered as mostly a solitary activity done by composers, but with the current web 2.0 technology it is possible to provide new possibilities for social music making. codes is a web-based networked music environment designed to support music creation by novices in a cooperative and prototypical way, since no previous musical knowledge is required. differently from others social media, where people only publish their content created elsewhere, in codes novices can draft and refine cooperatively simple musical pieces, actually creating their own music, instead of only consuming it. this paper presents the main characteristics of codes for social music making, with special focus on novices in music.
integrating real-time hybrid task scheduling into a sensor node platform. in general, two different types of low-end sensor node platforms are currently considered: event driven and multi-tasking operating systems. it is commonly assumed that event driven operating systems are more suited to wsn (wireless sensor networks) as they use less memory and resources. hence one of event driven operating systems, tinyos incorporating a non-preemptive scheduling policy, is quickly deployed for wsn today. while the tinyos can keep the memory overhead down, it has been shown that scheduling periodic and aperiodic non-preemptive tasks on the tinyos is np-hard. in this paper, we present a technique that makes it possible to guarantee the real-time scheduling of periodic tasks and minimize the average response time of aperiodic tasks for low-end sensor node platforms. this paper considers the following two perspectives. first, sensor node platforms available in the literature have not addressed the concept of scheduling for hybrid task sets where both types of periodic and aperiodic tasks exist. second, each system service in sensor node platforms is decomposed to either a periodic or an aperiodic task in order to provide fully optimal real-time scheduling for given real-time requirements of wsn applications. a case study shows that the proposed technique yields efficient performance in terms of guaranteeing the completion of all the periodic tasks within their deadlines and aiming to provide aperiodic tasks with good average response time.
implicit invocation of traits. we propose the introduction of a special kind of traits that implement methods implicitly invoked when an event of a given type occurs. events are announced explicitly in the source code at their place of origin, and classes publishing events, as well as traits subscribing to them, are explicitly marked as such. the result is greater independence of publisher and subscriber (when compared to other implementations), as well as an explicit interface between the two. an implementation in scala is briefly sketched.
ontology-based generation of it-security metrics. legal regulations and industry standards require organizations to measure and maintain a specified it-security level. although several it-security metrics approaches have been developed, a methodology for automatically generating iso 27001-based it-security metrics based on concrete organization-specific control implementation knowledge is missing. based on the security ontology by fenz et al., including information security domain knowledge and the necessary structures to incorporate organization-specific facts into the ontology, this paper proposes a methodology for automatically generating iso 27001-based it-security metrics. the conducted validation has shown that the research results are a first step towards increasing the degree of automation in the field of it-security metrics. using the introduced methodology, organizations are enabled to evaluate their compliance with information security standards, and to evaluate control implementations' effectiveness at the same time.
modeling and analyzing architectural change with alloy. although adaptivity based on reconfiguration has the potential to improve dependability of systems, the cost of a failed attempt at reconfiguration is prohibitive in precisely the applications where high dependability is required. existing work on formal modeling and verification of architectural reconfigurations partly achieve the goal of ensuring correctness, however the formalisms used often lack tool support and the ensuing models have uncertain relation to a concrete implementation. thus a practical way to ensure with formal certainty that specific architectural changes are correct remains a barrier to the uptake of reconfiguration techniques in industry. using the alloy language and associated tool, we propose a practical way to formally model and analyze runtime architectural change expressed as architectural scripts. our evaluation shows the performance to be acceptable; our experience that the modelling language is convenient and expressive, and that our model accurately repesents the implementation it is used to reason about.
using aspects and annotations to separate application code from design patterns. design patterns are an invaluable resource to generate effective design solutions. however, employing some of them can be cumbersome for some application classes when these are forced to mix domain- with pattern-related code. indeed, for a number of design patterns, we view the code implementing the behaviour required by their roles as a snippet, or concern, which is not involved in the domain issues that a class is supposed to address. this paper proposes a methodology to obtain the behaviour described by some well-known design patterns, which allows better separation between domain and non-domain concerns through recourse to aspects and annotations. indeed, application classes retain all the benefits that the design patterns are supposed to give them, while staying thoroughly separated from non-domain concerns. moreover, fewer lines of code are needed to obtain a design pattern than in other approaches, and the propagation of changes to application code, caused by the introduction or removal of a design pattern, are greatly reduced.
visual processing-inspired fern-audio features for noise-robust speaker verification. in this paper, we consider the problem of speaker verification as a two-class object detection problem in computer vision, where the object instances are 1-d short-time spectral vectors obtained from the speech signal. more precisely, we investigate the general problem of speaker verification in the presence of additive white gaussian noise, which we consider as analogous to visual object detection under varying illumination conditions. inspired by their recent success in illumination-robust object detection, we apply a certain class of binary-valued pixel-pair based features called ferns for noise-robust speaker verification. intensive experiments on a benchmark database according to a standard evaluation protocol have shown the advantage of the proposed features in the presence of moderate to extremely high amounts of additive noise.
load-based covert channels between xen virtual machines. multiple virtual machines on a single virtual machine monitor are isolated from each other. a malicious user on one virtual machine usually cannot relay secret data to other virtual machines without using explicit communication media such as shared files or a network. however, this isolation is threatened by communication in which cpu load is used as a covert channel. unfortunately, this threat has not been fully understood or evaluated. in this study, we quantitatively evaluate the threat of cpu-based covert channels between virtual machines on the xen hypervisor. we have developed cccv, a system that creates a covert channel and communicates data secretly using cpu loads. cccv consists of two user processes, a sender and a receiver. the sender runs on one virtual machine, and the receiver runs on another virtual machine on the same hypervisor. we measured the bandwidth and communication accuracy of the covert channel. cccv communicated 64-bit data with a 100% success rate in an ideal environment, and with a success rate of over 90% in an environment where web servers are processing requests on other virtual machines.
application-guided tool development for architecturally diverse computation. architecturally diverse computation exploits non-traditional computing platforms (e.g., field-programmable gate arrays, graphics processors, heterogeneous chip multiprocessors) to execute user applications. we have designed the auto-pipe tool set with the goal of easing the task of developing applications for architecturally diverse systems. prior to and during the course of auto-pipe's design, we have developed a number of real, substantial applications, and the the lessons learned during the development of these applications has had a direct bearing on the capabilities of auto-pipe. in this paper, we describe the relationship between our application development experience and auto-pipe. in short, how have applications guided the tools' evolution and development?
a novel framework to detect source code plagiarism: now, students have to work for real! our work focuses on detecting plagiarism within a source code corpus. the case study is to help a human corrector to find out plagiarism within source code written by computer science students. like other approaches, we use the notion of similarity distance. however, in this work we introduce segmentation to split documents into smaller parts and propose a document-wise distance based on the cost of permuting segments to transform one document to another. our framework is laid out as a pipeline, where each stage can be parameterized to build up a plagirism detector fitting user needs. the approach makes no assumption about the programming language being analyzed. furthermore, it provides a synthetical report of the results to ease the decision making process, as we consider that only a human user has final word on wether it is plagiarism or not. we tested our framework on hundreds of real source files, involving many programming languages, allowing us to discover previously undetected frauds.
prediction of social bookmarking based on a behavior transition model. we propose an algorithm to predict users' future bookmarking using social bookmarking data. it is a problem that primitive collaborative filtering cannot exactly catch users' preferences in social bookmarkings containing enormous items (urls) because in many cases user's adoption data is sparse. there can be various influences on bookmarking such as effects from the environment and changes in user preference. we use temporal sequence among the bookmarking-users to represent word-of-mouth and among the bookmarked-urls to represent user's interest, and model each sequential order as a continuous-time markov chain. this idea comes from diffusion of innovation theory. a transition probability from a state (user/url) to another state is defined by the transition rate calculated from the time taken for the transition. we predicted user's preferences through a combination of estimating the most likely transition between users using urls as input and between urls using users as input. we conducted evaluation experiments with a social bookmarking service in japan called hatena bookmark. the proposed algorithm predicts users' preferences with higher accuracy than collaborative filtering or simple transition models based on either user or url.
towards fine-grained and application-centric access control for wireless sensor networks. the emerging reality of wireless sensor networks deployed as long-lived infrastructure required to serve multiple applications necessitates the development of fine-grained security support. specifically, to allow sensor nodes to participate in multiple concurrent applications, access control is required on a per-application basis. this paper presents a policy-driven security architecture for wireless sensor networks that addresses the concern of fine-grained access control and secure deployment of security policies, while respecting the resource-constrained nature of wireless sensor networks. a prototype of this system has been realized and evaluated using the looci component model and the sun spot sensor network platform.
cnl4dsa: a controlled natural language for data sharing agreements. a data sharing agreement (dsa) is an agreement among contracting parties regulating how they share data. a dsa represents a flexible mean to assure privacy of data exchanged on the web. as an example, a set of intelligent user agents may interact with each other, and by means of dsa, may negotiate privacy requirements on behalf of human users. however, a key factor for the adoption of privacy's technologies is not only their reliability, but also their usability. here, we propose cnl4dsa, a controlled natural language for dsa aiming at lowering the barrier to adoption of dsa, and, at the same time, ensuring mapping to formal languages that enable the automatic verification of agreements.
dynamic linking and personalization on web. web browsing is a complex activity and users need to be supported with additional guidance. in our research, we developed a novel semantic web browser, which is called semweb, in order to assist web browsing using linked data and adaptive hypermedia (ah). semweb is an extension to the mozilla firefox web browser. semweb adds a semantic layer to web documents: it annotates web pages using a linked data domain (i.e. dbpedia) and creates context-based hyperlinks on web pages to guide users to relevant pages. in addition, the information presented to the user is personalized based on a novel behavior based user model. we evaluated our approach on dbpedia, dblp and ecs (university of southampton) linked data domains. our study showed that semweb provides a new way of supporting dynamic linking and personalization on web documents using different linked data domains.
concept for providing guaranteed service level over an array of unguaranteed commodity connections. as residential internet access has become increasingly commoditized, the incentives to lower costs in enterprise and similar networks have grown as well. the business networks' expensive costs stem primarily from a service level agreement, or sla, where the service provider or operator gives assurances on reliability and similar attributes. implementing these assurances is expensive. we have devised an approach to virtualize networks over commodity internet access while being able to provide service level assurances at fraction of a cost and with possibly even better service level compared to traditional methods. in this paper we present our concept in detail, including some initial results on the feasibility of the approach based on simulations.
checking architectural compliance in component-based systems. the software architecture of software systems often imposes constraints upon the design and the implementation of a system, for example upon how components are logically grouped or upon how they may interact. it is of great importance for the sake of maintainability and smooth operation of a software system that its design and implementation are compliant to its intended software architecture. due to the complexity of today's software systems and the diversity of those constraints, guaranteeing the compliance by manual checks is impossible. unfortunately, current tool support is not flexible enough to easily check different aspects of architectural compliance. this paper outlines a rule-based approach to architectural compliance checking for component-based systems. it is based upon a sound formalization of component-based descriptions of software systems and on the definition of architectural rules. it will be demonstrated by an exemplary industrial case study.
leveraging fuzzy query processing to support applications in wireless sensor networks. in this paper, we describe a fuzzy query processing approach to support application development in sensor networks. using a fuzzy query, an application programmer can provide a linguistic and semantic specification of the desired data, eliminating the need to specify explicit and exact thresholds as part of a query. the returned fuzzy query results are each associated with a degree of membership measurement that indicates how closely each returned data value matches the semantic intent of the fuzzy query, providing applications with additional information that can be used to reason about the query result. our approach to in-network fuzzy query processing allows for each sensor node to tailor its evaluation of a fuzzy query; this feature allows for consideration of micro-environments embedded within the sensor network that can impact how individual sensor data values should be interpreted with respect to the semantic intent of the query. to demonstrate that a fuzzy query processing approach is feasible, we use an application scenario to evaluate the implementation of our fuzzy query processing system in a simulated sensor network environment; results show that precision and overhead for our approach are comparable to traditional query processing.
flexible document-query matching based on a probabilistic content and structure score combination. the goal of an xml retrieval system is to select from a set of xml documents all elements (nodes) that fit the user information need, usually expressed by a set of keywords with some structural conditions. structural conditions are simply given by an ordered list of tag names that gives the target element where to search for relevant content. consequently a potential relevant node should not only contain similar text to the query but also its localization path should fit the structural conditions. we describe in this paper a new approach for ranking xml content-and-structure queries based on a probabilistic combination of two independent scores assigned to each xml element: content score and structural score. content score measures the content similarity between an element and a query, the structural score measures the path similarity between an element path and the structural conditions of a query. we showed experimentally that both scores follow well-known distributions. we then proposed a probabilistic combination of these distributions in order to assign a final score to each node. some experiments have been undertaken on a dataset provided by inex to show the effectiveness of our approach. we emphasize our experiments on the vvcas task which is appropriate to our model.
a framework for cross-disciplinary hypothesis generation. the complexity of cross-disciplinary knowledge discovery is two-fold: integration of vast amount of information in disparate silos, and dissemination of discovery to stakeholders with different interests. here we propose a framework that combines semantic web technology, graph algorithms, and user profiling to discover and prioritize novel associations among biomedical entities across disciplines. a proof-of-concept system was developed and tested through case studies tailored for three different user groups involved in colorectal cancer (crc). in this document, we describe in detail the major components of the system and summarize the results of the case studies. the results demonstrate the potential of user profiling and semantic graphs in discovering novel associations that are intellectually engaging to a cross-disciplinary audience.
expression microarray classification using topic models. classification of samples in expression microarray experiments represents a crucial task in bioinformatics and biomedicine. in this paper this scenario is addressed by employing a particular class of statistical approaches, called topic models. these models, firstly introduced in the text mining community, permit to extract from a set of objects (typically documents) an interpretable and rich description, based on an intermediate representation called topics (or processes). in this paper the expression microarray classification task is cast into this probabilistic context, providing a parallelism with the text mining domain and an interpretation. two different topic models are investigated, namely the probabilistic latent semantic analysis (plsa) and the latent dirichlet allocation (lda). an experimental evaluation of the proposed methodologies on three standard datasets confirms their effectiveness, also in comparison with other classification methodologies.
hybrid evolutionary quantum inspired method to adjust time phase distortions in financial time series. this work presents a hybrid evolutionary quantum inspired method to adjust time phase distortions present in financial time series, overcoming the random walk dilemma for financial prediction. it is composed of a qubit multilayer perceptron (qumlp) with a quantum inspired evolutionary algorithm (qiea), which is able to evolve the complete qumlp architecture and parameters, as well as searches for the best time lags to describe the time series generator phenomenon. an experimental analysis is conducted with the proposed approach through two real world financial time series, and the obtained results are discussed and compared to results found with classical models in literature.
eigenvector-based clustering using aggregated similarity matrices. clustering of high dimensional data is often performed by applying singular value decomposition (svd) on the original data space and building clusters from the derived eigenvectors. often no single eigenvector separates the clusters. we propose a method that combines the self-similarity matrices of the eigenvector in such a way that the concepts are well separated. we compare it with a k-means approach on public domain data sets and discuss when and why our method outperforms the k-means on svd method.
evidential reasoning for the treatment of incoherent terminologies. many reasoning algorithms and techniques require consistent terminologies to be able to operate correctly and efficiently. however, many ontologies become inconsistent during their evolution and lifecycle. many methods have been proposed to handle inconsistent terminologies including those that tolerate or repair inconsistencies. most of these approaches focus on the syntactic properties of ontology terminologies and attempt to address inconsistency from that perspective and satisfy postulates such as the principle of minimal change. in this paper, we will employ evidential reasoning to take into account assertional statements of an ontology as observations and probable indications for the correctness and validity of one axiom over other competing axioms. we will show how ontology assertions are beneficial in ranking axioms to be used in reiter's hitting set algorithm.
a review of approaches for representing rcc8 in owl. this paper investigates several approaches for qualitative spatial knowledge representation on the semantic web, by using rcc8 relations. we discuss several issues arising when representing rcc8 in owl dl, e.g., the lack of required features like role reflexivity, role boolean operators, and role inclusion axioms. we conclude that, although some of these features are to be included in the new version of the owl standard, owl 2, this language still lacks the expressive power to support role negations, conjunctions, and disjunctions, and complex role inclusion axioms.
a business driven cloud optimization architecture. in this paper, we discuss several facets of optimization in cloud computing, the corresponding challenges and propose an architecture for addressing those challenges. we consider a layered cloud where various cloud layers virtualize parts of the cloud infrastructure. the architecture takes into account different stakeholders in the cloud (infrastructure providers, platform providers, application providers and end users). the architecture supports self-management by automating most of the activities pertaining to optimization: monitoring, analysis and prediction, planning and execution.
an optimized capacity planning approach for virtual infrastructure exhibiting stochastic workload. traditionally, any capacity planning problem is modeled with deterministic workloads by considering the peak workload for resource allocation. in the context of businesses using cloud service, cloud provider could allocate resources for peak workload which could lead to under utilization of resource and charging users for unused yet provisioned resources. hence we came up with a better capacity planning algorithm which could ensure that we plan for peak usage but do not provision for it. in our approach, we modeled the problem as a stochastic optimization problem with the objective of minimizing the number of servers considering two important constraints a) stochastic nature of workloads and b) minimizing the application sla violations. we implemented the model using genetic algorithm and to address the stochastic nature of work loads, we reserved a free pool of resources in each server by the quantity determined by our algorithm. we evaluated the solution with real sever utilization data from a datacenter seeking consolidation. we did comparative analysis on the number of servers required suggested by our solution vs. peak work loads based solutions for various service levels. our results illustrate that reserving certain amount of resources in servers for addressing variability of workloads gives better results in terms of lesser number of servers compared to packing resources based on peak workloads for the same service levels.
dynamic task set partitioning based on balancing resource requirements and utilization to reduce power consumption. power consumption is a major design concern in current high-performance microprocessors. to deal with consumption, many systems apply dynamic voltage scaling (dvs) techniques which dynamically change the system speed depending on the workload characteristics. dvs costs in a multicore system can be reduced by sharing the same dvs regulator among the cores. in this context, to handle energy efficiently, the workload must be properly balanced among the cores. this paper proposes a new heuristic algorithm to balance the workload in a coarse-grain multicore system. the algorithm works on hard real-time tasks and dynamically drives the frequency/voltage level in order to guarantee real-time constraints. the proposed heuristic is aimed at improving the overlapping time between the memory and the processor while keeping utilization balanced among cores. energy savings depend on the range of frequency/voltage levels that dvs implements. experimental results show that the proposed heuristic reduces the energy consumption in almost 3 times with respect to a system with no dvs regulator and applying no heuristic.
a deidealisation semantics for kaos. kaos is a goal directed requirements engineering framework based on the decomposition and refinement of goals. decomposition and refinement continue until a point is reached at which agents, identifiable in the application environment, can be assigned responsibility for operations that manipulate variables over which they have control, and where the information for determining changes in the controlled variables resides in variables which the agent can monitor. although many of the 'refinements' that arise in the kaos process can be viewed as acceptable according to one or other model based refinement formalism, many cannot. those that cannot correspond to 'deidealisation' steps, not covered by conventional refinement formalisms. it is shown that such deidealisations can be seen as retrenchments, and the smooth interworking between refinement and retrenchment leads to a fuller formalisation of the kaos process than is otherwise possible.
programming assistance based on contracts and modular verification in the automation domain. in industrial automation, control software often has to get changed and adapted by domain experts and end users who have no or only limited software development expertise. this results in high demands on programming environments with respect to supporting, guiding, and supervising the programming tasks. in this paper we present an approach based on model checking and artificial intelligence techniques to guide domain experts in building control software which is guaranteed to obey specified contracts and constraints. the work is based on monaco which is a domain-specific language for programming automation solutions. as monaco employs a hierarchical component approach, the verification is done hierarchically where an upper component is verified against the contracts of its subcomponents. the verification approach is leveraged in different programming support systems which give immediate feedback about valid and invalid programs in an integrated development environment.
energy efficient management scheme for heterogeneous secondary storage system in mobile computers. flash memory is widely used because of its shock-resistance and power-efficient features. however, it cannot replace hard disks as secondary storage devices due to their greater cost per unit storage and low capability. in this paper, we propose an energy efficient heterogeneous secondary storage system management scheme for mobile systems. we employ flash memory device as a file cache of hard disk and extend existing data cache management algorithms to distribute files between two devices with consideration of file level cache restrictions. as a result, most file accesses are conducted in flash memory device and disk is spun-down to save energy. we develop a trace-driven simulator to evaluate our scheme in comparison with other alternatives. results demonstrate that with the help of our scheme, energy consumption of secondary storage system can be saved by up to 90% and i/o access time is improved. furthermore, the file cache management algorithms can result in high hit ratios.
complex objects ranking: a relational data mining approach. a key task in data mining and information retrieval is learning preference relations. most of methods reported in the literature learn preference relations between objects which are represented by attribute-value pairs or feature vectors (propositional representation). the growing interest in data mining techniques which are able to directly deal with more sophisticated representations of complex objects, motivates the investigation of relational learning methods for learning preference relations. in this paper, we present a probabilistic relational data mining method which permits to model preference relations between complex objects. preference relations are then used to rank objects. experiments on two ranking problems for scientific literature mining prove the effectiveness of the proposed method.
abba: adaptive bicluster-based approach to impute missing values in binary matrices. missing values frequently pose problems in binary matrices analysis since they can hinder downstream analysis of the datasets. despite the presence of many imputation methods that have been developed to substitute missing values with estimated values, these available techniques have some common disadvantages: they need to fix some parameters (e.g., number of patterns, number of rows to consider) to estimate missing values---with little theoretical support to determine these parameters---; and, missing values need to be recomputed from scratch as parameters change. in this paper we propose a novel algorithm (abba: adaptive bicluster-based approach) that does not have the above limitations. further, a formal framework that justifies the rationales behind abba is detailed. finally, experimental results over both synthetic and real data confirm the viability of our approach and the quality of the results, that overcomes the ones achieved by the main competing algorithm (knn).
filtering spams using the minimum description length principle. spam has become an increasingly important problem with a big economic impact in society. spam filtering poses a special problem in text categorization, of which the defining characteristic is that filters face an active adversary, which constantly attempts to evade filtering. in this paper, we present a novel approach to spam filtering based on the minimum description length principle. the proposed model is fast to construct and incrementally updateable. additionally, we offer an analysis concerning the measurements usually employed to evaluate the quality of the anti-spam classifiers. in this sense, we present a new measure in order to provide a fairer comparison. furthermore, we conducted an empirical experiment using six well-known, large and public databases. finally, the results indicate that our approach outperforms the state-of-the-art spam filters.
performance and extension of user space file systems. several efforts have been made over the years for developing file systems in user space. many of these efforts have failed to make a significant impact as measured by their use in production systems. recently, however, user space file systems have seen a strong resurgence. fuse is a popular framework that allows file systems to be developed in user space while offering ease of use and flexibility. in this paper, we discuss the evolution of user space file systems with an emphasis on fuse, and measure its performance using a variety of test cases. we also discuss the feasibility of developing file systems in high-level programming languages, by using as an example java bindings for fuse that we have developed. our benchmarks show that fuse offers adequate performance for several kinds of workloads.
a simulation of large-scale groundwater flow on cuda-enabled gpus. this paper presents a simulation method for large-scale groundwater flow on cuda-enabled gpus. the discretization method for a three-dimensional groundwater flow equation is introduced. when using the preconditioned conjugate gradient algorithm to solve the discretized equation, the implementing methods for the sparse matrix-vector multiplication and the vector inner product on cuda-enabled gpus are given. the experimental results show that gpus can speed up the groundwater simulation significantly.
capacon: access control mechanism for inter-device communications through tcp connections. we present capacon, an access control mechanism for interdevice communications through tcp connections. capacon provides capability-based access control for a system composed of devices. using capacon, an administrator does not need to set access control policies for each device and can manage these policies outside the system. a capability consists of an object device identifier and the list of permitted operations for that object device. subject devices that maintain capabilities can access object devices corresponding with those capabilities. to protect a capability from being fabricated, capacon uses a digital signature. capacon can be used without modifying existing device programs. we analyzed the safety of capabilities in capacon, and measured network throughputs and processing times of capacon. these experimental results show the practicality of capacon.
probabilistic context prediction using time-inferred multiple pattern networks. we propose a probabilistic method for context prediction of mobile users based on their historic context data. the proposed method predicts general context based on the probability theory through a novel graphical data structure, which is a kind of weighted directed multi-graphs. user context data are transformed into the new graphical structure, in which each node represents a context or a combined context and each directed edge indicates a context transfer with the time weight inferred from corresponding time data. the periodic property of context data is also considered. we bring a nice solution to context data with such property. through simulation, we could show the merits of the proposed method.
data-aware design and verification of service compositions with reo and mcrl2. service-based systems can be modeled as stand-alone services coordinated by external connectors. reo is a channel-based coordination language with well-defined semantics that enables a compositional construction of complex connectors from a set of primitive channels. it has been successfully applied in the area of web service composition specification as well as in business process modeling. in this paper, we present a mapping from reo to mcrl2, a specification language based on the process algebra acp, extended with data and time. the mapping enables verification of reo process models and service compositions using the mcrl2 model checking facilities. the supporting eclipse coordination tools suite provides a user-friendly environment for the modeling and verification process.
reparameterization based consistent graph-structured linear programs. a class of maximum a posteriori(map) formulations built on various graph models are of great interests for both theoretical and practical applications. recent advances in this field have extended the connections between the linear program (lp) relaxation and various tree-reweighted message passing algorithms. at both sides, many algorithms and their optimality certificates are proved, provided no conflict exists between the node marginal maximum and the corresponding edge marginal maximum. however, these conflicts are usually inevitable for general non-trivial markov random fields (mrfs). our work is aimed at reducing such conflicts by reparameterizing the original energy distributions in pairwise markov random field. all node potentials will be decomposed and attached to local edges according to their local graph structures. and thus, only edge marginals are needed in our linear program relaxation, and the node marginals are only used to exchange information among different parts of the graph. we incorporated this consistent graph-structured reparameterization into some latest lp optimality guaranteed proximal solvers, and the resulted algorithms outperform the original ones in convergence rate and also have a better behavior to converge to map optimality monotonously even for some highly noisy mrfs.
data stream anomaly detection through principal subspace tracking. we consider the problem of anomaly detection in multiple co-evolving data streams. in this paper, we introduce frahst (fast rank-adaptive row-householder subspace tracking). it automatically learns the principal subspace from n numerical data streams and an anomaly is indicated by a change in the number of latent variables. our technique provides state-of-the-art estimates for the subspace basis and has a true dominant complexity of only 5nr operations while satisfying all desirable streaming constraints. frahst successfully detects subtle anomalous patterns and when compared against four other anomaly detection techniques, it is the only with a consistent f1 &ge; 80% in the abilene datasets as well as in the isp datasets introduced in this work.
towards the modeling reactive and proactive agents by using mas-ml. the existence of mas where agents with different internal architectures interact promotes the need for a language capable of modeling these applications. this paper aims to extend the mas-ml language in order to support the modeling of proactive and reactive agents.
privacy preserving linear discriminant analysis from perturbed data. the ubiquity of the internet not only makes it very convenient for individuals or organizations to share data for data mining or statistical analysis, but also greatly increases the chance of privacy breach. there exist many techniques such as random perturbation to protect the privacy of such data sets. however, perturbation often has negative impacts on the quality of data mining or statistical analysis conducted over the perturbed data. this paper studies the impact of random perturbation for a popular data mining and analysis method: linear discriminant analysis. the contributions are two fold. first, we discover that for large data sets, the impact of perturbation is quite limited (i.e., high quality results may be obtained directly from perturbed data) if the perturbation process satisfies certain conditions. second, we discover that for small data sets, the negative impact of perturbation can be reduced by publishing additional statistics about the perturbation along with the perturbed data. we provide both theoretical derivations and experimental verifications of these results.
design-level metrics estimation based on code metrics. fault detection based on mining code and design metrics has been an active research area for many years. basically "module"-based metrics for source code and design level are calculated or obtained and data mining is used to build predictor models. however, in many projects due to organizational or software process models, design level metrics are not available and/or accurate. it has been shown that performance of these classifiers or predictors decline if only source code features are used for training them. based on best of our know knowledge no set of rule to estimate design level metrics based on code level metrics has been presented since it is believed that design level metrics have additional information and cannot be estimated without access to design artifacts. in this study we present a fuzzy modeling system to find and present these relationships for projects presented in nasa metrics data repository (mdp) datasets. interestingly, we could find a set of empirical rules that govern all the projects regardless of size, programming language and software development methodology. comparison of fault detectors built based on estimated design metrics with actual design metrics on various projects showed a very small difference in accuracy of classifiers and validated our hypothesis that estimation of design metrics based on source code attributes can become a practical exercise.
experiences in reading detection with eeg signals. this short paper introduces the use of neurophysiological signals, electroencephalogram (eeg), as a technique for reading detection. reading detection is a focused problem, yet with multiple facets and application relevance. the paper refers to the system architecture that supports the reading detection experiments, describes the sample tools designed for the experiment and discusses the results. the experiences demonstrate that the approach to reading detection is feasible. in addition, they highlight the technical and usability limitations of the approach, which are expected to be reduced both through system tuning and optimization, and through the technological evolution of the peripheral devices.
profit-based on-demand broadcast scheduling of real-time multi-item requests. on-demand broadcast is a widely accepted approach for dynamic and scalable wireless information dissemination systems. with the proliferation of real-time applications, minimizing the deadline miss ratio in scheduling multi-item requests becomes an emergent task in the current architecture. in this paper, we propose a profit-based scheduling algorithm, called pvc, which utilizes two new concepts "profit" of a data item and "opportunity cost" of a request. note that, to the best of our knowledge, it is also the first time to introduce opportunity cost, which is derived from economics, into on-demand scheduling. finally, the simulation results show the great improvement in comparison with traditional algorithms. on average, pvc has more than 5% advantage in terms of deadline miss ratio than the best of others.
proving consistency of vdm models using hol. although consistency of formal models is crucial, consistency proofs should not be a large burden to the user. hence, it is important to have access to efficient proof support which is able to automate a large part of the consistency proofs. we have developed a tool that automatically translates a large subset of vdm and its associated proof obligations, which ensure model consistency, to the theorem prover hol. in addition, powerful tactics have been constructed to discard most of the proof obligations automatically. the application of our approach to four case studies shows that a high degree of automation can be achieved.
a study on interestingness measures for associative classifiers. associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. support and confidence are the de-facto "interestingness measures" used for discovering relevant association rules. the support-confidence framework has also been used in most, if not all, associative classifiers. although support and confidence are appropriate measures for building a strong model in many cases, they are still not the ideal measures and other measures could be better suited. there are many other rule interestingness measures already used in machine learning, data mining and statistics. this work focuses on using 53 different objective measures for associative classification rules. a wide range of uci datasets are used to study the impact of different "inter-estingness measures" on different phases of associative classifiers based on the number of rules generated and the accuracy obtained. the results show that there are interesting-ness measures that can significantly reduce the number of rules for almost all datasets while the accuracy of the model is hardly jeopardized or even improved. however, no single measure can be introduced as an obvious winner.
combining independent model transformations. model transformation is one of the key principles of model driven engineering. many approaches have been proposed to design and realize them. however, for all the approaches, model transformations are considered as single entities that can only be chained if their input and output metamodels are compatible. this approach has the major drawback to focus on the satisfaction of the compliance property when building a transformation chain. in this paper we propose a mechanism for combining independent model transformations which jointly work towards a common objective but do not initially handle compatible metamodels. our proposal is independent of any model transformation approach. it has been validated using gaspard, an environment dedicated to code generation for embedded systems.
software transactional memory for implicitly parallel functional language. during the last decade, software transactional memory (stm) gained wide popularity in many areas of parallel computing. in this paper, we introduce lisp-derived language equipped with automatic parallel execution and mutations based on software transactional memory. the novel idea is that we do not incorporate transactions as a language construct but rather use them as a mean of runtime environment to run each computation in a consistent memory and thus provide correct results. stm enables us to efficiently manage concurrent object updates and resolve collisions. in this paper, we describe a variant of deferred lockless stm mechanism with direct updates that enables us to use mutations with minimal costs.
recomap: an interactive and adaptive map-based recommender. with the growing availability of geo-referenced information on the web, the problem of spatial information overload has attracted interest both in the commercial and academic world. in order to tackle this issue, personalisation techniques can be used to tailor spatial contents based upon user interests. recomap, the system described in this paper, deducts user interests by monitoring user interaction and context to provide personalised spatial recommendations. after an overview of existing recommendation systems within the geospatial domain, the novel approach adopted by recomap to produce such recommendations is described. a case study related to a university campus setting is used to outline an application of this technique. details of the implementation and initial testing of this prototype are provided.
towards interactionflows for smart products. nowadays, the interaction between a product and the user is described using different methods than for product to product communication. this makes it difficult to replace users and products mutually to create really dynamical environments, capable of reducing the amount of interactions, if possible. to advance the design of interactive smart environments, we introduce a concept for describing productinitiated interaction with users and demonstrate, how they can be applied in practice. this allows to combine both, automated procedures and interaction with the user, to a new concept called interactionflows.
uplink scheduling algorithm with dynamic polling management in ieee 802.16 broadband wireless networks. scheduling algorithms is an important component in any communications network to satisfy the qos requirements. in this paper, a new scheduling algorithm for uplink traffic in ieee 802.16 networks is proposed. the proposed algorithm is applied directly to the bandwidth request queues of the base station (bs) and work along with the polling mechanism to control the periodicity of sending polling for the rtps and nrtps services. its evaluation by means of modeling and simulation showed satisfactory results.
publication and discovery of yasa web services. in this paper, we present new algorithms for matching web services described in yasa4wsdl (yasa for short). we have already defined yasa that overcomes some issues missing in wsdl or sawsdl. in this paper, we continue on our contribution and show how yasa web services are matched based on the specificities of yasa descriptions. our matching algorithm consists of three variants based on three different semantic matching degree aggregations. this algorithm was implemented in yasa-m, a new web service matchmaker. yasa-m is evaluated and compared to well known approaches for service matching. experiments show that yasa-m provides better results, in terms of precision, response time, and scalability, than a well known match-maker.
improving automatic music genre classification with hybrid content-based feature vectors. current research on the task of automatic music genre classification has been focusing on new classification approaches based on combining information from other sources than the music signal. the reason for this is that the use of content-based approaches, i.e. using features extracted directly from the audio signal, seems to have reached a glass ceiling. in this work we show that by using different types of content-based features together it is possible to substantially improve the classification accuracy. this is an interesting result as different types of content-based features aim, at a conceptual level, to capture the same type of information. in order to identify which types of content-based features are responsible for the predictive accuracy gain, we also used a feature selection (fs) approach based on a genetic algorithm (ga). the analysis of the results in two databases shows that the use of the ga for fs succeeds in selecting a representative subset without significant loss in accuracy. it also shows that all the different types of content-based features employed are important for the improvement of the accuracy in classifying music genres.
considerations on developing mobile applications based on the capuchin project. the development of applications for mobile devices is becoming increasingly popular, with manufacturers struggling to support different programming environments and embedding libraries on their devices. in this pursuit for a straight-forward development of mobile applications, java micro edition (jme) is a natural solution. although jme has innumerous benefits, it offers limited support for user interface (ui) development. on a different path, adobe's flash lite is tailored to develop rich ui for mobile applications. to bring together the advantages of both jme and flash lite, sony ericsson's capuchin project permits the creation of interactive mobile applications, using flash lite to implement the user interface and jme to implement application core. the use of flash lite and jme in a single application has rised design issues that must be dealt by software engineers, such as performance, maintainability and reusability of both flash lite and jme programming languages. to guide software engineers design mobile applications, this paper presents a development process for interactive mobile applications based on capuchin project. to validate it, a mobile application is developed based on this process, and relevant topics of the process are discussed.
sporadic server revisited. the sporadic server (ss) overcomes the major limitations of other resource reservation fixed priority based techniques, but it also presents some drawbacks, mainly related to an increased scheduling overhead and a not so efficient behavior during overrun situations. in this paper we introduce and prove the effectiveness of an improved ss with reduced overhead and fairer handling of server overrun situations. we also show how this can be efficiently exploited to provide temporal isolation in a multiprocessor platform, adapting already existing schedulability tests.
data generation in model-based testing. in this paper we show how context free grammars extended with limited state information can be used to enhance model-based testing. abstract models can be made more specific using the values generated by these grammars. the approach allows the association of data to the model without changing the model itself. we present two examples to illustrate the applicability of the framework. we also show how this approach is implemented in a real model-based testing tool.
aho-corasick like multiple subtree matching by pushdown automata. a simple yet efficient algorithm to find all occurrences of a set of subtrees in a subject tree is described. the presented algorithm is similar to the well-known aho-corasick string matching method -- instead of a deterministic finite automaton a deterministic pushdown automaton is used as the computation model for reading the subject tree in prefix notation.
network state consistency of virtual machine in live migration. the current virtual machine (vm) live migration research mainly focuses on transferring run-time memory state of vms, but neglects the consistency of the network state while migration. this paper designs an efficient and reliable virtual network (ervin) system, which applies several techniques: central information management distributed data transmission (cidd), layer-two network virtualization, store and replay. it guarantees that the established network connections do not interrupt during migration. the experiments show that ervin is efficient. the degradation time of network performance is only around 400 ms, which can almost be neglected.
haptic manipulation of rational parametric planar cubics using shape constraints. in this paper, we show how to deform a planar rational cubic based on a local interpolation constraint while retaining the qualitative shape of the curve. an impedance-type, parallel haptic device is used to signal changes of the number of inflection points, cusps and loops during the deformation. in this way, the user is provided with an intuitive and natural guidance throughout the curve's shape generation process in cad.
an aspect-oriented framework for operating system evolution. this paper presents an aspect-oriented framework which enables dynamically weaving aspects into operating system in order to adjust its functionalities during system operation. the framework is designed based on the notion of dynamic aspect weaving in aspect-oriented programming (aop) arena, which can achieve modulating, at runtime, the behavior of an existing program by injecting a piece of code (called advice in aop terminology) at selected location (called join point) of the program. it is useful in making program adaptable, especially for non-stopping systems of which, in general, going off-line for maintenance and undertaking system restart is either unacceptable or too expensive. the design of this framework includes a join point model and management functions on aspects. the join point model supports weaving multiple aspects to the same join point and the chained execution of advices of the same type. the management functions provide the creation, deployment, and runtime management of aspects, in addition to sequencing the execution of advices. an example implementation of this framework working on linux operating system is described in this paper, which demonstrates both the feasibility and the effectiveness of this framework.
empirical analysis of database server scalability using an n-tier benchmark with read-intensive workload. the performance evaluation of database servers in n-tier applications is a serious challenge due to requirements such as non-stationary complex workloads and global consistency management when replicating database servers. we conducted an experimental evaluation of database server scalability and bottleneck identification in n-tier applications using the rubbos benchmark. our experiments are comprised of a full scale-out mesh with up to nine database servers and three application servers. additionally, the fourtier system was run in a variety of configurations, including two database management systems (mysql and postgresql), two hardware node types (normal and low-cost), and two database replication techniques (c-jdbc and mysql cluster). in this paper we present the analysis of results generated with a read-intensive interaction pattern (browse-only workload) in the client emulator. these empirical data can be divided into two kinds. first, for a relatively small number of servers, we find simple hardware resource bottlenecks. consequently, system throughput increases with an increasing number of database (and application) servers. second, when sufficient hardware resources are available, non-obvious database related bottlenecks have been found that limit system throughput. while the first kind of bottlenecks shows that there are similarities between database and application/web server scalability, the second kind of bottlenecks shows that database servers have significantly higher sophistication and complexity that require in-depth evaluation and analysis.
mmsrp: multi-wavelength markov-based split reservation protocol for dwdm optical networks. during wavelength reservation in wavelength division multiplexed (wdm) optical networks, often multiple connection requests unknowingly compete for the same wavelength, even when other free wavelengths are available, resulting in a collision. the markov model used in markov based reservation protocol (mbrp), is very effective to reduce such conflicts by intelligently guessing a wavelength in advance. even then a connection request may be blocked because of the vulnerable period between wavelength probing and actual reservation. to minimize the effect of such vulnerability, splitting the probe process to fork out a partial reservation from an intermediate node is an efficient solution. in markov-selection split reservation protocol (msrp), the above two strategies are combined, but only one wavelength is guessed during probing. if the attempt with this single wavelength fails, the connection request is blocked. to take care of this limitation, we propose here a new scheme called multi-wavelength msrp (mmsrp), where a set of wavelengths (instead of one) is selected by markov model and continuously updated for possible future use. in case of failure, during reservation in the backward direction, it retries to reserve the next best wavelength through another splitting at the failure point. thus, mmsrp handles multiple wavelengths sequentially through multiple splitting. simulation results show that the blocking probability in mmsrp decreases considerably (~25% over msrp and ~50% over mbrp in some cases) as the number of wavelengths increases. compared to msrp, though the average setup time is marginally higher in mmsrp, it appears quite promising for delay-tolerant applications, where blocking is very crucial, in dense wdm networks.
matchbox: combined meta-model matching for semi-automatic mapping generation. data integration is a well-known challenge offering a common view on heterogeneous data, e. g. to ensure consistency or tool interoperability. to implement this integration mde proposes to apply model transformations. a model transformation requires meta-model matching, i. e. the task of discovering semantic correspondences between elements. recently, semi-automatic matching has been proposed to support transformation development by mapping generation. however, current meta-model matching approaches concentrate on a fixed non-configurable set of matching algorithms and often miss a thorough evaluation, thus no estimate concerning their quality can be made. we tackle these issues by proposing matchbox, an approach using a configurable combination of matchers in a common framework. thereby, we adapt and extend established schema matching techniques for the purpose of meta-model matching. additionally, we present a benchmark for meta-model matching consisting of 23 real-world model transformations and mappings. this benchmark is used to comprehensively evaluate matchbox. the results obtained lead to conclusions regarding our approach and the effectiveness of meta-model matching.
summarizing observational client-side data to reveal web usage patterns. client-side event logs may reveal patterns of usage of web pages. nevertheless, extracting useful and novel information from this voluminous data set is a challenge for evaluation tools, since a few minutes simple task may result in a sequence of hundreds of events. this work contributes with a technique to process these logs and build a web page's usage graph summarizing statistical information of the web page usage concerning one or more sessions. this graph reveals patterns of real usage data, which human-computer interaction specialists may find useful for inspecting accessibility and usability issues. moreover, web usage miners can reuse the usage graph to apply other techniques to discover other patterns or rules.
towards quality-aware development and evolution of enterprise information systems. information systems have been used to support business processes for a long time. consequently, there has been an ongoing trend towards connecting and integrating the isolated it solutions of enterprises into coherent systems in order to support the seamless execution of business processes electronically. due to the often business critical nature of the processes such systems need to adhere to service level agreements that guarantee quality aspects such as a specific throughput or availability for a given process. however, a key weakness of existing development approaches for information systems is that they mostly focus on functional aspects of system development and lack an integrated view between different stakeholders and views in development, e.g. between business process management and software architecture. in this paper we introduce a novel approach for universal und uniform modeling of non-functional system properties that bridges the four areas of business and use case modeling as well as architecture and component design. by means of an example process, we first identify the key weaknesses of existing development methodologies and then derive the challenges for an improved approach. after that we describe the central aspects of our envisaged composition approach for non-functional requirements and how it might be supported by a novel breed of case tools in the future.
on the incoherencies in web browser access control policies. web browsers' access control policies have evolved piecemeal in an ad-hoc fashion with the introduction of new browser features. this has resulted in numerous incoherencies. in this paper, we analyze three major access control flaws in today's browsers: (1) principal labeling is different for different resources, raising problems when resources interplay, (2) runtime changes to principal identities are handled inconsistently, and (3)browsers mismanage resources belonging to the user principal. we show that such mishandling of principals leads to many access control incoherencies, presenting hurdles for web developers to construct secure web applications. a unique contribution of this paper is to identify the compatibility cost of removing these unsafe browser features. to do this, we have built webanalyzer, a crawler-based framework for measuring real-world usage of browser features, and used it to study the top 100,000 popular web sites ranked by alexa. our methodology and results serve as a guideline for browser designers to balance security and backward compatibility. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
inspector gadget: automated extraction of proprietary gadgets from malware binaries. unfortunately, malicious software is still an unsolved problem and a major threat on the internet. an important component in the fight against malicious software is the analysis of malware samples: only if an analyst understands the behavior of a given sample, she can design appropriate countermeasures. manual approaches are frequently used to analyze certain key algorithms, such as downloading of encoded updates, or generating new dns domains for command and control purposes. in this paper, we present a novel approach to automatically extract, from a given binary executable, the algorithm related to a certain activity of the sample. we isolate and extract these instructions and generate a so-called gadget, i.e., a stand-alone component that encapsulates a specific behavior. we make sure that a gadget can autonomously perform a specific task by including all relevant code and data into the gadget such that it can be executed in a self-contained fashion. gadgets are useful entities in analyzing malicious software: in particular, they are valuable for practitioners, as understanding a certain activity that is embedded in a binary sample (e.g., the update function) is still largely a manual and complex task. our evaluation with several real-world samples demonstrates that our approach is versatile and useful in practice. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
reflections on the 30th anniversary of the ieee symposium on security and privacy. this article is a retrospective of concepts and people who have contributed significantly to the ieee symposium on security and privacy over the past 30 years.
chip and pin is broken. emv is the dominant protocol used for smart card payments worldwide, with over 730 million cards in circulation. known to bank customers as “chip and pin”, it is used in europe; it is being introduced in canada; and there is pressure from banks to introduce it in the usa too. emv secures credit and debit card transactions by authenticating both the card and the customer presenting it through a combination of cryptographic authentication codes, digital signatures, and the entry of a pin. in this paper we describe and demonstrate a protocol flaw which allows criminals to use a genuine card to make a payment without knowing the card’s pin, and to remain undetected even when the merchant has an online connection to the banking network. the fraudster performs a man-in-the-middle attack to trick the terminal into believing the pin verified correctly, while telling the card that no pin was entered at all. the paper considers how the flaws arose, why they remained unknown despite emv’s wide deployment for the best part of a decade, and how they might be fixed. because we have found and validated a practical attack against the core functionality of emv, we conclude that the protocol is broken. this failure is significant in the field of protocol design, and also has important public policy implications, in light of growing reports of fraud on stolen emv cards. frequently, banks deny such fraud victims a refund, asserting that a card cannot be used without the correct pin, and concluding that the customer must be grossly negligent or lying. our attack can explain a number of these cases, and exposes the need for further research to bridge the gap between the theoretical and practical security of bank payment systems. it also demonstrates the need for the next version of emv to be engineered properly.
overcoming an untrusted computing base: detecting and removing malicious hardware automatically. the computer systems security arms race between attackers and defenders has largely taken place in the domain of software systems, but as hardware complexity and design processes have evolved, novel and potent hardware-based security threats are now possible. this paper presents a hybrid hardware/software approach to defending against malicious hardware. we propose bluechip, a defensive strategy that has both a design-time component and a runtime component. during the design verification phase, bluechip invokes a new technique, unused circuit identification (uci), to identify suspicious circuitry—those circuits not used or otherwise activated by any of the design verification tests. bluechip removes the suspicious circuitry and replaces it with exception generation hardware. the exception handler software is responsible for providing forward progress by emulating the effect of the exception generating instruction in software, effectively providing a detour around suspicious hardware. in our experiments, bluechip is able to prevent all hardware attacks we evaluate while incurring a small runtime overhead. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
all you ever wanted to know about dynamic taint analysis and forward symbolic execution (but might have been afraid to ask). dynamic taint analysis and forward symbolic execution are quickly becoming staple techniques in security analyses. example applications of dynamic taint analysis and forward symbolic execution include malware analysis, input filter generation, test case generation, and vulnerability discovery. despite the widespread usage of these two techniques, there has been little effort to formally define the algorithms and summarize the critical issues that arise when these techniques are used in typical security contexts. the contributions of this paper are two-fold. first, we precisely describe the algorithms for dynamic taint analysis and forward symbolic execution as extensions to the run-time semantics of a general language. second, we highlight important implementation choices, common pitfalls, and considerations when using these techniques in a security context.
taintscope: a checksum-aware directed fuzzing tool for automatic software vulnerability detection. fuzz testing has proven successful in finding security vulnerabilities in large programs. however, traditional fuzz testing tools have a well-known common drawback: they are ineffective if most generated malformed inputs are rejected in the early stage of program running, especially when target programs employ checksum mechanisms to verify the integrity of inputs. in this paper, we present taintscope, an automatic fuzzing system using dynamic taint analysis and symbolic execution techniques, to tackle the above problem. taintscope has several novel contributions: 1) taintscope is the first checksum-aware fuzzing tool to the best of our knowledge. it can identify checksum fields in input instances, accurately locate checksum-based integrity checks by using branch profiling techniques, and bypass such checks via control flow alteration. 2) taintscope is a directed fuzzing tool working at x86 binary level (on both linux and window). based on fine-grained dynamic taint tracing, taintscope identifies which bytes in a well-formed input are used in security-sensitive operations (e.g., invoking system/library calls) and then focuses on modifying such bytes. thus, generated inputs are more likely to trigger potential vulnerabilities. 3) taintscope is fully automatic, from detecting checksum, directed fuzzing, to repairing crashed samples. it can fix checksum values in generated inputs using combined concrete and symbolic execution techniques. we evaluate taintscope on a number of large real-world applications. experimental results show that taintscope can accurately locate the checksum checks in programs and dramatically improve the effectiveness of fuzz testing. taintscope has already found 27 previously unknown vulnerabilities in several widely used applications, including adobe acrobat, google picasa, microsoft paint, and imagemagick. most of these severe vulnerabilities have been confirmed by secunia and ocert, and assigned cve identifiers (such as cve-2009-1882, cve-2009-2688). corresponding patches from vendors are released or in progress based on our reports.
round-efficient broadcast authentication protocols for fixed topology classes. we consider resource-constrained broadcast authentication for $n$ receivers in a static, known network topology. there are only two known broadcast authentication protocols that do not use asymmetric cryptography, one-time signatures, multi-receiver macs, or time synchronization [1], [2]. both these protocols require three passes of a message front traversing the network. we investigate whether this amount of interaction can be improved efficiently for specific common topology classes, namely, linear topologies, tree topologies and fully connected topologies. we show modifications to the protocols allowing them to complete in just two passes in the linear and fully connected cases with a small constant factor increase in per-node communication overhead, and a further optimization that achieves the equivalent of just a single pass in the linear case with $o(\log n)$ increase in per-node communication overhead. we also prove new lower bounds for round complexity, or the maximum number of consecutive interactions in a protocol. we show that protocols with efficient per-node communication overhead (polylogarithmic in $n$) must require at least $2\log n$ rounds in any topology; this implies that our two-pass protocol in the fully-connected topology requires the fewest possible passes, and this bound is asymptotically tight for the full-duplex communication model. furthermore, we show that communication-efficient protocols must take asymptotically more than $2\log n$ rounds on trees; this implies that that there are some tree topologies for which two passes do not suffice and the existing three-pass algorithms may be optimal.
identifying dormant functionality in malware programs. to handle the growing flood of malware, security vendors and analysts rely on tools that automatically identify and analyze malicious code. current systems for automated malware analysis typically follow a dynamic approach, executing an unknown program in a controlled environment (sandbox) and recording its runtime behavior. since dynamic analysis platforms directly run malicious code, they are resilient to popular malware defense techniques such as packing and code obfuscation. unfortunately, in many cases, only a small subset of all possible malicious behaviors is observed within the short time frame that a malware sample is executed. to mitigate this issue, previous work introduced techniques such as multi-path or forced execution to increase the coverage of dynamic malware analysis. unfortunately, using these techniques is potentially expensive, as the number of paths that require analysis can grow exponentially. in this paper, we propose reanimator, a novel solution to determine the capabilities (malicious functionality) of malware programs. our solution is based on the insight that we can leverage behavior observed while dynamically executing a specific malware sample to identify similar functionality in other programs. more precisely, when we observe malicious actions during dynamic analysis, we automatically extract and model the parts of the malware binary that are responsible for this behavior. we then leverage these models to check whether similar code is present in other samples. this allows us to statically identify dormant functionality (functionality that is not observed during dynamic analysis) in malicious programs. we evaluate our approach on thousands of real-world malware samples, and we show that our system is successful in identifying additional, malicious functionality. as a result, our approach can significantly improve the coverage of malware analysis results.
investigation of triangular spamming: a stealthy and efficient spamming technique. spam is increasingly accepted as a problem associated with compromised hosts or email accounts. this problem not only makes the tracking of spam sources difficult but also enables a massive amount of illegitimate or unwanted emails to be disseminated quickly. various attempts have been made to analyze, backtrack, detect, and prevent spam using both network as well as content characteristics. however, relatively less attention has been given to understanding how spammers actually carry out their spamming activities from a network angle. spammers’ network behavior has significant impact on spammers’ common goal, sending spam in a stealthy and efficient manner. our work thoroughly investigates a fairly unknown spamming technique we name as triangular spamming that exploits routing irregularities of spoofed ip packets. it is highly stealthy and efficient in that triangular spamming enables 1) exploiting bandwidth diversity of botnet hosts to carry out spam campaigns effectively without divulging precious high-bandwidth hosts and 2) bypassing the current smtp traffic blocking policies. despite its relative obscurity, its use has been confirmed by the network operator community. through carefully devised probing techniques and actual deployment of triangular spamming on planetlab (a wide-area distributed testbed), we investigate the feasibility, impact of triangular spamming and propose practical detection and prevention methods. from our probing experiments, we found that 97% of the networks which block outbound smtp traffic are vulnerable to triangular spamming and only 44% of them are listed on spamhaus policy blocking list (pbl). the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
a practical attack to de-anonymize social network users. social networking sites such as facebook, linkedin, and xing have been reporting exponential growth rates and have millions of registered users. in this paper, we introduce a novel de-anonymization attack that exploits group membership information that is available on social networking sites. more precisely, we show that information about the group memberships of a user (i.e., the groups of a social network to which a user belongs) is sufficient to uniquely identify this person, or, at least, to significantly reduce the set of possible candidates. that is, rather than tracking a user's browser as with cookies, it is possible to track a person. to determine the group membership of a user, we leverage well-known web browser history stealing attacks. thus, whenever a social network user visits a malicious website, this website can launch our de-anonymization attack and learn the identity of its visitors. the implications of our attack are manifold, since it requires a low effort and has the potential to affect millions of social networking users. we perform both a theoretical analysis and empirical measurements to demonstrate the feasibility of our attack against xing, a medium-sized social network with more than eight million members that is mainly used for business relationships. furthermore, we explored other, larger social networks and performed experiments that suggest that users of facebook and linkedin are equally vulnerable. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
reconciling belief and vulnerability in information flow. belief and vulnerability have been proposed recently to quantify information flow in security systems. both concepts stand as alternatives to the traditional approaches founded on shannon entropy and mutual information, which were shown to provide inadequate security guarantees. in this paper we unify the two concepts in one model so as to cope with (potentially inaccurate) attackers' extra knowledge. to this end we propose a new metric based on vulnerability that takes into account the adversary's beliefs.
authenticating primary users' signals in cognitive radio networks via integrated cryptographic and wireless link signatures. to address the increasing demand for wireless bandwidth, cognitive radio networks (crns) have been proposed to increase the efficiency of channel utilization; they enable the sharing of channels among secondary (unlicensed) and primary (licensed) users on a non-interference basis. a secondary user in a crn should constantly monitor for the presence of a primary user's signal to avoid interfering with the primary user. however, to gain unfair share of radio channels, an attacker (e.g., a selfish secondary user) may mimic a primary user's signal to evict other secondary users. therefore, a secure primary user detection method that can distinguish a primary user's signal from an attacker's signal is needed. a unique challenge in addressing this problem is that federal communications commission (fcc) prohibits any modification to primary users. consequently, existing cryptographic techniques cannot be used directly. in this paper, we develop a novel approach for authenticating primary users' signals in crns, which conforms to fcc's requirement. our approach integrates cryptographic signatures and wireless link signatures (derived from physical radio channel characteristics) to enable primary user detection in the presence of attackers. essential to our approach is a {\em helper node} placed physically close to a primary user. the helper node serves as a "bridge" to enable a secondary user to verify cryptographic signatures carried by the helper node's signals and then obtain the helper node's authentic link signatures to verify the primary user's signals. a key contribution in our paper is a novel physical layer authentication technique that enables the helper node to authenticate signals from its associated primary user. unlike previous techniques for link signatures, our approach explores the geographical proximity of the helper node to the primary user, and thus does not require any training process.
hypersafe: a lightweight approach to provide lifetime hypervisor control-flow integrity. virtualization is being widely adopted in today’s computing systems. its unique security advantages in isolating and introspecting commodity oses as virtual machines (vms) have enabled a wide spectrum of applications. however, a common, fundamental assumption is the presence of a trustworthy hypervisor. unfortunately, the large code base of commodity hypervisors and recent successful hypervisor attacks (e.g., vm escape) seriously question the validity of this assumption. in this paper, we present hypersafe, a lightweight approach that endows existing type-i bare-metal hypervisors with a unique self-protection capability to provide lifetime control flow integrity. specifically, we propose two key techniques. the first one, non-bypassable memory lockdown, reliably protects the hypervisor’s code and static data from being compromised even in the presence of exploitable memory corruption bugs (e.g., buffer overflows), therefore successfully providing hypervisor code integrity. the second one, restricted pointer indexing, introduces one layer of indirection to convert the control data into pointer indexes. these pointer indexes are restricted such that the corresponding call/return targets strictly follow the hypervisor control flow graph, hence expanding protection to control-flow integrity. we have built a prototype and used it to protect two open-source type-i hypervisors: bitvisor and xen. the experimental results with synthetic hypervisor exploits and benchmarking programs show hypersafe can reliably enable the hypervisor self-protection and provide the integrity guarantee with a small performance overhead.
how good are humans at solving captchas? a large scale evaluation. captchas are designed to be easy for humans but hard for machines. however, most recent research has focused only on making them hard for machines. in this paper, we present what is to the best of our knowledge the first large scale evaluation of captchas from the human perspective, with the goal of assessing how much friction captchas present to the average user. for the purpose of this study we have asked workers from amazon’s mechanical turk and an underground captchabreaking service to solve more than 318 000 captchas issued from the 21 most popular captcha schemes (13 images schemes and 8 audio scheme). analysis of the resulting data reveals that captchas are often difficult for humans, with audio captchas being particularly problematic. we also find some demographic trends indicating, for example, that non-native speakers of english are slower in general and less accurate on english-centric captcha schemes. evidence from a week’s worth of ebay captchas (14,000,000 samples) suggests that the solving accuracies found in our study are close to real-world values, and that improving audio captchas should become a priority, as nearly 1% of all captchas are delivered as audio rather than images. finally our study also reveals that it is more effective for an attacker to use mechanical turk to solve captchas than an underground service.
bootstrapping trust in commodity computers. trusting a computer for a security-sensitive task (such as checking email or banking online) requires the user to know something about the computer's state. we examine research on securely capturing a computer's state, and consider the utility of this information both for improving security on the local computer (e.g., to convince the user that her computer is not infected with malware) and for communicating a remote computer's state (e.g., to enable the user to check that a web server will adequately protect her data). although the recent "trusted computing" initiative has drawn both positive and negative attention to this area, we consider the older and broader topic of bootstrapping trust in a computer. we cover issues ranging from the wide collection of secure hardware that can serve as a foundation for trust, to the usability issues that arise when trying to convey computer state information to humans. this approach unifies disparate research efforts and highlights opportunities for additional work that can guide real-world improvements in computer security.
object capabilities and isolation of untrusted web applications. a growing number of current web sites combine active content (applications) from untrusted sources, as in so-called mashups. the object-capability model provides an appealing approach for isolating untrusted content: if separate applications are provided disjoint capabilities, a sound object-capability framework should prevent untrusted applications from interfering with each other, without preventing interaction with the user or the hosting page. in developing language-based foundations for isolation proofs based on object-capability concepts, we identify a more general notion of authority safety that also implies resource isolation. after proving that capability safety implies authority safety, we show the applicability of our framework for a specific class of mashups. in addition to proving that a javascript subset based on google caja is capability safe, we prove that a more expressive subset of javascript is authority safe, even though it is not based on the object-capability model.
experimental security analysis of a modern automobile. modern automobiles are no longer mere mechanical devices; they are pervasively monitored and controlled by dozens of digital computers coordinated via internal vehicular networks. while this transformation has driven major advancements in efficiency and safety, it has also introduced a range of new potential risks. in this paper we experimentally evaluate these issues on a modern automobile and demonstrate the fragility of the underlying system structure. we demonstrate that an attacker who is able to infiltrate virtually any electronic control unit (ecu) can leverage this ability to completely circumvent a broad array of safety-critical systems. over a range of experiments, both in the lab and in road tests, we demonstrate the ability to adversarially control a wide range of automotive functions and completely ignore driver input\dash including disabling the brakes, selectively braking individual wheels on demand, stopping the engine, and so on. we find that it is possible to bypass rudimentary network security protections within the car, such as maliciously bridging between our car's two internal subnets. we also present composite attacks that leverage individual weaknesses, including an attack that embeds malicious code in a car's telematics unit and that will completely erase any evidence of its presence after a crash. looking forward, we discuss the complex challenges in addressing these vulnerabilities while considering the existing automotive ecosystem.
tamper evident microprocessors. most security mechanisms proposed to date unquestioningly place trust in microprocessor hardware. this trust, however, is misplaced and dangerous because microprocessors are vulnerable to insider attacks that can catastrophically compromise security, integrity and privacy of computer systems. in this paper, we describe several methods to strengthen the fundamental assumption about trust in microprocessors. by employing practical, lightweight attack detectors within a microprocessor, we show that it is possible to protect against malicious logic embedded in microprocessor hardware. we propose and evaluate two area-efficient hardware methods - trustnet and datawatch - that detect attacks on microprocessor hardware by knowledgeable, malicious insiders. our mechanisms leverage the fact that multiple components within a microprocessor (e.g., fetch, decode pipeline stage etc.) must necessarily coordinate and communicate to execute even simple instructions, and that any attack on a microprocessor must cause erroneous communications between micro architectural subcomponents used to build a processor. a key aspect of our solution is that trustnet and datawatch are themselves highly resilient to corruption. we demonstrate that under realistic assumptions, our solutions can protect pipelines and on-chip cache hierarchies at negligible area cost and with no performance impact. combining trustnet and datawatch with prior work on fault detection has the potential to provide complete coverage against a large class of microprocessor attacks.
crossing the "valley of death": transitioning research into commercial products - a personal perspective. many researchers with innovative ideas just never seem to be able to bring those ideas to market. one of the biggest problems with the cyber security research community is transitioning technology into commercial product. this paper discusses these technology transition activities from the view of a program manager and offers several examples of successful transition for consideration.
scifi - a system for secure face identification. we introduce scifi, a system for secure computation of face identification. the system performs face identification which compares faces of subjects with a database of registered faces. the identification is done in a secure way which protects both the privacy of the subjects and the confidentiality of the database. a specific application of scifi is reducing the privacy impact of camera based surveillance. in that scenario, scifi would be used in a setting which contains a server which has a set of faces of suspects, and client machines which might be cameras acquiring images in public places. the system runs a secure computation of a face recognition algorithm, which identifies if an image acquired by a client matches one of the suspects, but otherwise reveals no information to neither of the parties. our work includes multiple contributions in different areas: a new face identification algorithm which is unique in having been specifically designed for usage in secure computation. nonetheless, the algorithm has face recognition performance comparable to that of state of the art algorithms. we ran experiments which show the algorithm to be robust to different viewing conditions, such as illumination, occlusions, and changes in appearance (like wearing glasses). a secure protocol for computing the new face recognition algorithm. in addition, since our goal is to run an actual system, considerable effort was made to optimize the protocol and minimize its online latency. a system - scifi, which implements a secure computation of the face identification protocol. experiments which show that the entire system can run in near real-time: the secure computation protocol performs a preprocessing of all public-key cryptographic operations. its online performance therefore mainly depends on the speed of data communication, and our experiments show it to be extremely efficient.
noninterference through secure multi-execution. a program is defined to be noninterferent if its outputs cannot be influenced by inputs at a higher security level than their own. various researchers have demonstrated how this property (or closely related properties) can be achieved through information flow analysis, using either a static analysis (with a type system or otherwise), or using a dynamic monitoring system. we propose an alternative approach, based on a technique we call secure multi-execution. the main idea is to execute a program multiple times, once for each security level, using special rules for i/o operations. outputs are only produced in the execution linked to their security level. inputs are replaced by default inputs except in executions linked to their security level or higher. input side effects are supported by making higher-security-level executions reuse inputs obtained in lower-security-level threads. we show that this approach is interesting from both a theoretical and practical viewpoint. theoretically, we prove for a simple deterministic language with i/o operations, that this approach guarantees complete soundness (even for the timing and termination covert channels), as well as good precision (identical i/o for terminating runs of termination-sensitively noninterferent programs). on the practical side, we present an experiment implementing secure multi-execution in the mainstream spider-monkey javascript engine, exploiting parallelism on a current multi-core computer. benchmark results of execution time and memory for the google chrome v8 benchmark suite show that the approach is practical for a mainstream browser setting. certain programs are even executed faster under secure multi-execution than under the standard execution. we discuss challenges and propose possible solutions for implementing the technique in a real browser, in particular handling the dom tree and browser callback functions. finally, we discuss how secure multi-execution can be extended to handle language features like exceptions, concurrency or no determinism.
a symbolic execution framework for javascript. as ajax applications gain popularity, client-side javascript code is becoming increasingly complex. however, few automated vulnerability analysis tools for javascript exist. in this paper, we describe the first system for exploring the execution space of javascript code using symbolic execution. to handle javascript code’s complex use of string operations, we design a new language of string constraints and implement a solver for it. we build an automatic end-to-end tool, kudzu, and apply it to the problem of finding client-side code injection vulnerabilities. in experiments on 18 live web applications, kudzu automatically discovers 2 previously unknown vulnerabilities and 9 more that were previously found only with a manually-constructed test suite. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
history of us government investments in cybersecurity research: a personal perspective. this paper traces the history of cyber security research funding by the u.s. government. difficulties in accurately measuring the level of u.s. government research funding for cyber security are first described. some of the legislative and bureaucratic mechanisms involved in funding and reporting such research today are reviewed. a qualitative, personal perspective on the ups and downs of us cyber security research funding from the late 1960s to 2010 is then provided. the essay is written for the thirtieth anniversary meeting of the ieee symposium on security and privacy, held in may 2010.
side-channel leaks in web applications: a reality today, a challenge tomorrow. with software-as-a-service becoming mainstream, more and more applications are delivered to the client through the web. unlike a desktop application, a web application is split into browser-side and server-side components. a subset of the application’s internal information flows are inevitably exposed on the network. we show that despite encryption, such a side-channel information leak is a realistic and serious threat to user privacy. specifically, we found that surprisingly detailed sensitive information is being leaked out from a number of high-profile, top-of-the-line web applications in healthcare, taxation, investment and web search: an eavesdropper can infer the illnesses/medications/surgeries of the user, her family income and investment secrets, despite https protection; a stranger on the street can glean enterprise employees' web search queries, despite wpa/wpa2 wi-fi encryption. more importantly, the root causes of the problem are some fundamental characteristics of web applications: stateful communication, low entropy input for better interaction, and significant traffic distinctions. as a result, the scope of the problem seems industry-wide. we further present a concrete analysis to demonstrate the challenges of mitigating such a threat, which points to the necessity of a disciplined engineering practice for side-channel mitigations in future web application developments.
state of the art: automated black-box web application vulnerability testing. black-box web application vulnerability scanners are automated tools that probe web applications for security vulnerabilities. in order to assess the current state of the art, we obtained access to eight leading tools and carried out a study of: (i) the class of vulnerabilities tested by these scanners, (ii) their effectiveness against target vulnerabilities, and (iii) the relevance of the target vulnerabilities to vulnerabilities found in the wild. to conduct our study we used a custom web application vulnerable to known and projected vulnerabilities, and previous versions of widely used web applications containing known vulnerabilities. our results show the promise and effectiveness of automated tools, as a group, and also some limitations. in particular, "stored" forms of cross site scripting (xss) and sql injection (sqli) vulnerabilities are not currently found by many tools. because our goal is to assess the potential of future research, not to evaluate specific vendors, we do not report comparative data or make any recommendations about purchase of specific tools. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
towards static flow-based declassification for legacy and untrusted programs. simple non-interference is too restrictive for specifying and enforcing information flow policies in most programs. exceptions to non-interference are provided using declassification policies. several approaches for enforcing declassification have been proposed in the literature. in most of these approaches, the declassification policies are embedded in the program itself or heavily tied to the variables in the program being analyzed, thereby providing little separation between the code and the policy. consequently, the previous approaches essentially require that the code be trusted, since to trust that the correct policy is being enforced, we need to trust the source code. in this paper, we propose a novel framework in which declassification policies are related to the source code being analyzed via its i/o channels. the framework supports many of the of declassification policies identified in the literature. based on flow-based static analysis, it represents a first step towards a new approach that can be applied to untrusted and legacy source code to automatically verify that the analyzed program complies with the specified declassification policies. the analysis works by constructing a conservative approximation of expressions over input channel values that could be output by the program, and by determining whether all such expressions satisfy the declassification requirements stated in the policy. we introduce a representation of such expressions that resembles tree automata. we prove that if a program is considered safe according to our analysis then it satisfies a property we call policy controlled release, which formalizes information-flow correctness according to our notion of declassification policy. we demonstrate, through examples, that our approach works for several interesting and useful declassification policies, including one involving declassification of the average of several confidential values. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
scalable parametric verification of secure systems: how to verify reference monitors without worrying about data structure size. the security of systems such as operating systems, hypervisors, and web browsers depend critically on reference monitors to correctly enforce their desired security policy in the presence of adversaries. recent progress in developing reference monitors with small code size and narrow interfaces has made automated formal verification of reference monitors a more tractable goal. however, a significant remaining factor for the complexity of automated verification is the size of the data structures (e.g., access control matrices) over which the programs operate. this paper develops a parametric verification technique that scales even when reference monitors and adversaries operate over unbounded, but finite data structures. specifically, we develop a parametric guarded command language for modeling reference monitors and adversaries. we also present a parametric temporal specification logic for expressing security policies that the monitor is expected to enforce. the central technical results of the paper are a set of small model theorems. these theorems state that in order to verify that a policy is enforced by a reference monitor with an arbitrarily large data structure, it is sufficient to model check the monitor with just one entry in its data structure. we apply our methodology to verify the designs of two hypervisors, secvisor and the shype mandatory-access-control extension to xen. our approach is able to prove that shype and a variant of the original secvisor design correctly enforces the expected security properties in the presence of powerful adversaries.
trustvisor: efficient tcb reduction and attestation. an important security challenge is to protect the execution of security-sensitive code on legacy systems from malware that may infect the os, applications, or system devices. prior work experienced a tradeoff between the level of security achieved and efficiency. in this work, we leverage the features of modern processors from amd and intel to overcome the tradeoff to simultaneously achieve a high level of security and high performance. we present trustvisor, a special-purpose hypervisor that provides code integrity as well as data integrity and secrecy for selected portions of an application. trustvisor achieves a high level of security, first because it can protect sensitive code at a very fine granularity, and second because it has a very small code base (only around 6k lines of code) that makes verification feasible. trustvisor can also attest the existence of isolated execution to an external entity. we have implemented trustvisor to protect security-sensitive code blocks while imposing less than 7% overhead on the legacy os and its applications in the common case.
outside the closed world: on using machine learning for network intrusion detection. in network intrusion detection research, one popular strategy for finding attacks is monitoring a network's activity for anomalies: deviations from profiles of normality previously learned from benign traffic, typically identified using tools borrowed from the machine learning community. however, despite extensive academic research one finds a striking gap in terms of actual deployments of such systems: compared with other intrusion detection approaches, machine learning is rarely employed in operational "real world" settings. we examine the differences between the network intrusion detection problem and other areas where machine learning regularly finds much more success. our main claim is that the task of finding attacks is fundamentally different from these other applications, making it significantly harder for the intrusion detection community to employ machine learning effectively. we support this claim by identifying challenges particular to network intrusion detection, and provide a set of guidelines meant to strengthen future research on anomaly detection.
a proof-carrying file system. we present the design and implementation of pcfs, a file system that adapts proof-carrying authorization to provide direct, rigorous, and efficient enforcement of dynamic access policies. the keystones of pcfs are a new authorization logic bl that supports policies whose consequences may change with both time and system state, and a rigorous enforcement mechanism that combines proof verification with conditional capabilities. we prove that our enforcement using capabilities is correct, and evaluate our design through performance measurements and a case study.
revocation systems with very small private keys. in this work, we design a method for creating public key broadcast encryption systems. our main technical innovation is based on a new "two equation" technique for revoking users. this technique results in two key contributions: first, our new scheme has ciphertext size overhead $o(r)$, where $r$ is the number of revoked users, and the size of public and private keys is only a \emph{constant} number of group elements from an elliptic-curve group of prime order. in addition, the public key allows us to encrypt to an unbounded number of users. our system is the first to achieve such parameters. we give two versions of our scheme: a simpler version which we prove to be selectively secure in the standard model under a new, but non-interactive assumption, and another version that employs the new dual system encryption technique of waters to obtain adaptive security under the d-bdh and decisional linear assumptions. second, we show that our techniques can be used to realize attribute-based encryption (abe) systems with non-monotonic access formulas, where our key storage is significantly more efficient than previous solutions. this result is also proven selectively secure in the standard model under our new non-interactive assumption. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
synthesizing near-optimal malware specifications from suspicious behaviors. fueled by an emerging underground economy, malware authors are exploiting vulnerabilities at an alarming rate. to make matters worse, obfuscation tools are commonly available, and much of the malware is open source, leading to a huge number of variants. behavior-based detection techniques are a promising solution to this growing problem. however, these detectors require precise specifications of malicious behavior that do not result in an excessive number of false alarms. in this paper, we present an automatic technique for extracting optimally discriminative specifications, which uniquely identify a class of programs. such a discriminative specification can be used by a behavior-based malware detector. our technique, based on graph mining and concept analysis, scales to large classes of programs due to probabilistic sampling of the specification space. our implementation, called holmes, can synthesize discriminative specifications that accurately distinguish between programs, sustaining an 86% detection rate on new, unknown malware, with 0 false positives, in contrast with 55% for commercial signature-based antivirus (av) and 62-64% for behavior-based av (commercial or research).
tensor-rank and lower bounds for arithmetic formulas. we show that any explicit example for a tensor a:[n]r -> f with tensor-rank ≥ nr ⋅ (1- o(1)), (where r ≤ log n / log log n), implies an explicit super-polynomial lower bound for the size of general arithmetic formulas over f. this shows that strong enough lower bounds for the size of arithmetic formulas of depth 3 imply super-polynomial lower bounds for the size of general arithmetic formulas. one component of our proof is a new approach for homogenization and multilinearization of arithmetic formulas, that gives the following results: we show that for any n-variate homogenous polynomial f of degree r, if there exists a (fanin-2) formula of size s and depth d for f then there exists a homogenous formula of size o ( d+r+1/r ⋅ s) for f. in particular, for any r ≤ log n / log log n, r ≤ log n, if there exists a polynomial size formula for f then there exists a polynomial size homogenous formula for f. this refutes a conjecture of nisan and wigderson [10] and shows that super-polynomial lower bounds for homogenous formulas for polynomials of small degree imply super-polynomial lower bounds for general formulas. we show that for any n-variate set-multilinear polynomial f of degree r, if there exists a (fanin-2) formula of size s and depth d for f then there exists a set-multilinear formula of size o ( (d+2)r ⋅ s ) for f. in particular, for any r ≤ log n / log log n, if there exists a polynomial size formula for f then there exists a polynomial size set-multilinear formula for f. this shows that super-polynomial lower bounds for set-multilinear formulas for polynomials of small degree imply super-polynomial lower bounds for general formulas.
near-optimal extractors against quantum storage. we show that trevisan's extractor and its variants [22,19] are secure against bounded quantum storage adversaries. one instantiation gives the first such extractor to achieve an output length θ(k-b), where k is the source's entropy and b the adversary's storage, together with a poly-logarithmic seed length. another instantiation achieves a logarithmic key length, with a slightly smaller output length θ((k-b)/kγ) for any γ>0. in contrast, the previous best construction [21] could only extract (k/b)1/15 bits. some of our constructions have the additional advantage that every bit of the output is a function of only a polylogarithmic number of bits from the source, which is crucial for some cryptographic applications. our argument is based on bounds for a generalization of quantum random access codes, which we call quantum functional access codes. this is crucial as it lets us avoid the local list-decoding algorithm central to the approach in [21], which was the source of the multiplicative overhead.
a full characterization of quantum advice. we prove the following surprising result: given any quantum state rho on n qubits, there exists a local hamiltonian h on poly(n) qubits (e.g., a sum of two-qubit interactions), such that any ground state of h can be used to simulate rho on all quantum circuits of fixed polynomial size. in terms of complexity classes, this implies that bqp/qpoly is contained in qma/poly, which supersedes the previous result of aaronson that bqp/qpoly is contained in pp/poly. indeed, we can exactly characterize quantum advice, as equivalent in power to untrusted quantum advice combined with trusted classical advice. proving our main result requires combining a large number of previous tools -- including a result of alon et al. on learning of real-valued concept classes, a result of aaronson on the learnability of quantum states, and a result of aharonov and regev on "qma+ super-verifiers" -- and also creating some new ones. the main new tool is a so-called majority-certificates lemma, which is closely related to boosting in machine learning, and which seems likely to find independent applications. in its simplest version, this lemma says the following. given any set s of boolean functions on n variables, any function f in s can be expressed as the pointwise majority of m=o(n) functions f1,...,fm in s, such that each fi is the unique function in s compatible with o(log|s|) input/output constraints.
the maximum multiflow problems with bounded fractionality. this paper addresses a fundamental issue in the multicommodity flow theory. for an undirected capacitated supply graph (g,c) having commodity graph h, the maximum multiflow problem is to maximize the total flow-value of multicommodity flows with respect to (g,c;h). for a commodity graph h, the fractionality of h is the least positive integer k with property that there exists a 1/k-integral optimal multiflow in the maximum multiflow problem for every integer-capacitated supply graph (g,c) having h as a commodity graph. if such a positive integer k does not exist, then the fractionality is defined to be infinity. around 1990, karzanov raised the problem of classifying commodity graphs with finite fractionality, gave a necessary condition (property p) for the finiteness of fractionality, and conjectured that the property p is also sufficient. our main result affirmatively solves karzanov's conjecture in algorithmic form: if h has property p, then there exists a 1/24-integral optimal multiflow in maximum multiflow problem for every integer-capacitated supply graph having h as a commodity graph, and there exists a strongly polynomial time algorithm to find it. our proof is based on a special combinatorial duality relation involving a class of cat(0) complexes, and on a fractional version of the splitting-off method for finding an optimal multiflow with a bounded denominator.
erratum for: on basing one-way functions on np-hardness. this is an errata for our stoc'06 paper, "on basing one-way functions on np-hardness". there is a gap in the proof of our results regarding adaptive reductions, and we currently do not know whether theorem 3 (as stated in section 2) holds.
on the structure of cubic and quartic polynomials. in this paper we study the structure of polynomials of degree three and four that have high bias or high gowers norm, over arbitrary prime fields. in particular we obtain the following results. 1. we give a canonical representation for degree three or four polynomials that have a significant bias (i.e. they are not equidistributed). this result generalizes the corresponding results from the theory of quadratic forms. this significantly improves previous results for such polynomials. 2. for the case of degree four polynomials with high gowers norm we show that (a subspace of constant co-dimension of) fn can be partitioned to subspaces of dimension omega(n) such that on each of the subspaces the polynomial is equal to some degree three polynomial. it was previously shown that a quartic polynomial with a high gowers norm is not necessarily correlated with any cubic polynomial. our result shows that a slightly weaker statement does hold. the proof is based on finding a structure in the space of partial derivatives of the underlying polynomial.
on the searchability of small-world networks with arbitrary underlying structure. revisiting the "small-world" experiments of the '60s, kleinberg observed that individuals are very effective at constructing short chains of acquaintances between any two people, and he proposed a mathematical model of this phenomenon. in this model, individuals are the nodes of a base graph, the square grid, capturing the underlying structure of the social network; and this base graph is augmented with additional edges from each node to a few long-range contacts of this node, chosen according to some natural distance-based distribution. in this augmented graph, a greedy search algorithm takes only a polylogarithmic number of steps in the graph size. following this work, several papers investigated the correlations between underlying structure and long-range connections that yield efficient decentralized search, generalizing kleinberg's results to broad classes of underlying structures, such as metrics of bounded doubling dimension, and minor-excluding graphs. we focus on the case of arbitrary base graphs. we show that for a simple long-range contact distribution consistent with empirical observations on social networks, a slight variation of greedy search, where the next hop is to a distant node only if it yields sufficient progress towards the target, requires no(1) steps, where $n$ is the number of nodes. precisely, the expected number of steps for any source-target pair is at most 2(log n)1/2+o(1). this bound almost matches the best known lower bound of ω(2√log n) steps, which applies to a general class of search algorithms. in the context of social networks, our result could be interpreted as: individuals may well be able to construct short chains between people regardless of the underlying structure of the social network.
the limits of buffering: a tight lower bound for dynamic membership in the external memory model. we study the dynamic membership (or dynamic dictionary) problem, which is one of the most fundamental problems in data structures. we study the problem in the external memory model with cell size b bits and cache size m bits. we prove that if the amortized cost of updates is at most 0.999 (or any other constant b log n(n/m)), where n is the number of elements in the dictionary. in contrast, when the update time is allowed to be 1 + o(1), then a bit vector or hash table give query time o(1). thus, this is a threshold phenomenon for data structures. this lower bound answers a folklore conjecture of the external memory community. since almost any data structure task can solve membership, our lower bound implies a dichotomy between two alternatives: (i) make the amortized update time at least 1 (so the data structure does not buffer, and we lose one of the main potential advantages of the cache), or (ii) make the query time at least roughly logarithmic in n. our result holds even when the updates and queries are chosen uniformly at random and there are no deletions; it holds for randomized data structures, holds when the universe size is o(n), and does not make any restrictive assumptions such as indivisibility. all of the lower bounds we prove hold regardless of the space consumption of the data structure, while the upper bounds only need linear space. the lower bound has some striking implications for external memory data structures. it shows that the query complexities of many problems such as 1d-range counting, predecessor, rank-select, and many others, are all the same in the regime where the amortized update time is less than 1, as long as the cell size is large enough (b = polylog(n) suffices). the proof of our lower bound is based on a new combinatorial lemma called the lemma of surprising intersections (losi) which allows us to use a proof methodology where we first analyze the intersection structure of the positive queries by using encoding arguments, and then use statistical arguments to deduce properties of the intersection structure of all queries, even the negative ones. in most other data structure arguments that we know, it is difficult to argue anything about the negative queries. therefore we believe that the losi and this proof methodology might find future uses for other problems.
a quantum lovász local lemma. the lovasz local lemma (lll) is a powerful tool in probability theory to show the existence of combinatorial objects meeting a prescribed collection of "weakly dependent" criteria. we show that the lll extends to a much more general geometric setting, where events are replaced with subspaces and probability is replaced with relative dimension, which allows to lower bound the dimension of the intersection of vector spaces under certain independence conditions. our result immediately applies to the k-qsat problem: for instance we show that any collection of rank 1 projectors with the property that each qubit appears in at most 2k/(e*k) of them, has a joint satisfiable state. we then apply our results to the recently studied model of random k-qsat. recent works have shown that the satisfiable region extends up to a density of 1 in the large k limit, where the density is the ratio of projectors to qubits. using a hybrid approach building on work by laumann et al. we greatly extend the known satisfiable region for random k-qsat to a density of ω(2k/k2). since our tool allows us to show the existence of joint satisfying states without the need to construct them, we are able to penetrate into regions where the satisfying states are conjectured to be entangled, avoiding the need to construct them, which has limited previous approaches to product states.
distributed computation in dynamic networks. in this paper we investigate distributed computation in dynamic networks in which the network topology changes from round to round. we consider a worst-case model in which the communication links for each round are chosen by an adversary, and nodes do not know who their neighbors for the current round are before they broadcast their messages. the model captures mobile networks and wireless networks, in which mobility and interference render communication unpredictable. in contrast to much of the existing work on dynamic networks, we do not assume that the network eventually stops changing; we require correctness and termination even in networks that change continually. we introduce a stability property called t -interval connectivity (for t >= 1), which stipulates that for every t consecutive rounds there exists a stable connected spanning subgraph. for t = 1 this means that the graph is connected in every round, but changes arbitrarily between rounds. we show that in 1-interval connected graphs it is possible for nodes to determine the size of the network and compute any com- putable function of their initial inputs in o(n2) rounds using messages of size o(log n + d), where d is the size of the input to a single node. further, if the graph is t-interval connected for t > 1, the computation can be sped up by a factor of t, and any function can be computed in o(n + n2/t) rounds using messages of size o(log n + d). we also give two lower bounds on the token dissemination problem, which requires the nodes to disseminate k pieces of information to all the nodes in the network. the t-interval connected dynamic graph model is a novel model, which we believe opens new avenues for research in the theory of distributed computing in wireless, mobile and dynamic networks.
an improved lp-based approximation for steiner tree. the steiner tree problem is one of the most fundamental np-hard problems: given a weighted undirected graph and a subset of terminal nodes, find a minimum-cost tree spanning the terminals. in a sequence of papers, the approximation ratio for this problem was improved from 2 to the current best 1.55 [robins,zelikovsky-sidma'05]. all these algorithms are purely combinatorial. a long-standing open problem is whether there is an lp-relaxation for steiner tree with integrality gap smaller than 2 [vazirani,rajagopalan-soda'99]. in this paper we improve the approximation factor for steiner tree, developing an lp-based approximation algorithm. our algorithm is based on a, seemingly novel, iterative randomized rounding technique. we consider a directed-component cut relaxation for the k-restricted steiner tree problem. we sample one of these components with probability proportional to the value of the associated variable in the optimal fractional solution and contract it. we iterate this process for a proper number of times and finally output the sampled components together with a minimum-cost terminal spanning tree in the remaining graph. our algorithm delivers a solution of cost at most ln(4) times the cost of an optimal k-restricted steiner tree. this directly implies a ln(4)+ε
bilipschitz snowflakes and metrics of negative type. we show that there exists a metric space (x,d) such that (x,√d) admits a bilipschitz embedding into l2, but (x,d) does not admit an equivalent metric of negative type. in fact, we exhibit a strong quantitative bound: there are n-point subsets yn ⊆ x such that mapping (yn, d) to a metric of negative type requires distortion ~ω(log n)1/4. in a formal sense, this is the first lower bound specifically against bilipschitz embeddings into negative-type metrics, and therefore unlike other lower bounds, ours cannot be derived from a 1-dimensional poincare inequality. this answers an open question about the strength of strong vs. weak triangle inequalities in a number of semi-definite programs. our construction sheds light on the power of various notions of "dual flows" that arise in algorithms for approximating the sparsest cut problem. it also has other interesting implications for bilipschitz embeddings of finite metric spaces.
satisfiability allows no nontrivial sparsification unless the polynomial-time hierarchy collapses. consider the following two-player communication process to decide a language l: the first player holds the entire input x but is polynomially bounded; the second player is computationally unbounded but does not know any part of x; their goal is to cooperatively decide whether x belongs to l at small cost, where the cost measure is the number of bits of communication from the first player to the second player. for any integer d ≥ 3 and positive real ε we show that if satisfiability for n-variable d-cnf formulas has a protocol of cost o(nd-ε) then conp is in np/poly, which implies that the polynomial-time hierarchy collapses to its third level. the result even holds when the first player is conondeterministic, and is tight as there exists a trivial protocol for ε = 0. under the hypothesis that conp is not in np/poly, our result implies tight lower bounds for parameters of interest in several areas, namely sparsification, kernelization in parameterized complexity, lossy compression, and probabilistically checkable proofs. by reduction, similar results hold for other np-complete problems. for the vertex cover problem on n-vertex d-uniform hypergraphs, the above statement holds for any integer d ≥ 2. the case d=2 implies that no np-hard vertex deletion problem based on a graph property that is inherited by subgraphs can have kernels consisting of o(k2-ε) edges unless conp is in np/poly, where k denotes the size of the deletion set. kernels consisting of o(k^2) edges are known for several problems in the class, including vertex cover, feedback vertex set, and bounded-degree deletion.
the price of privately releasing contingency tables and the spectra of random matrices with correlated rows. marginal (contingency) tables are the method of choice for government agencies releasing statistical summaries of categorical data. in this paper, we derive lower bounds on how much distortion (noise) is necessary in these tables to ensure the privacy of sensitive data. we extend a line of recent work on impossibility results for private data analysis [9, 12, 13, 15] to a natural and important class of functionalities. consider a database consisting of n rows (one per individual), each row comprising d binary attributes. for any subset of t attributes of size |t|=k, the marginal table for t has 2k entries; each entry counts how many times in the database a particular setting of these attributes occurs. we provide lower bounds for releasing all d k k-attribute marginal tables under several different notions of privacy. (1) we give efficient polynomial time attacks which allow an adversary to reconstruct sensitive information given insufficiently perturbed marginal table releases. in particular, for a constant k, we obtain a tight bound of ~ω(min √n, √dk-1) on the average distortion per entry for any mechanism that releases all k-attribute marginals while providing "attribute" privacy (a weak notion implied by most privacy definitions). (2) our reconstruction attacks require a new lower bound on the least singular value of a random matrix with correlated rows. let m(k) be a matrix with d k rows formed by taking all possible k-way entry-wise products of an underlying set of d random vectors from {0,1}n. for constant k, we show that the least singular value of m(k) is ~ω(√dk) with high probability (the same asymptotic bound as for independent rows). (3) we obtain stronger lower bounds for marginal tables satisfying differential privacy. we give a lower bound of ~ω(min {√n, √ dk), which is tight for n ~ω (dk). we extend our analysis to obtain stronger results for mechanisms that add instance-independent noise and weaker results when k is super-constant.
solving polynomial equations in smoothed polynomial time and a near solution to smale's 17th problem. the 17th of the problems proposed by steve smale for the 21st century asks for the existence of a deterministic algorithm computing an approximate solution of a system of n complex polynomials in $n$ unknowns in time polynomial, on the average, in the size n of the input system. a partial solution to this problem was given by carlos beltran and luis miguel pardo who exhibited a randomized algorithm, call it lv, doing so. in this paper we further extend this result in several directions. firstly, we perform a smoothed analysis (in the sense of spielman and teng) of algorithm lv and prove that its smoothed complexity is polynomial in the input size and σ-1, where σ controls the size of the random perturbation of the input systems. secondly, we perform a condition-based analysis of lv. that is, we give a bound, for each system f, of the expected running time of lv with input f. in addition to its dependence on n this bound also depends on the condition of f. thirdly, and to conclude, we return to smale's 17th problem as originally formulated for deterministic algorithms. we exhibit such an algorithm and show that its average complexity is no(log log n). this is nearly a solution to smale's 17th problem.
non-commutative circuits and the sum-of-squares problem. we initiate a direction for proving lower bounds on the size of non-commutative arithmetic circuits. this direction is based on a connection between lower bounds on the size of non-commutative arithmetic circuits and a problem about commutative degree four polynomials, the classical sum-of-squares problem: find the smallest n such that there exists an identity (x12+x22+•• + xk2)• (y1^2+y22+•• + yk2)= f12+f22+ ... +fn2, where each fi = fi(x,y) is bilinear in x={x1,... ,xk} and y={y1,..., yk}. over the complex numbers, we show that a sufficiently strong super-linear lower bound on n in, namely, n ≥ k1+ε with ε >0, implies an exponential lower bound on the size of arithmetic circuits computing the non-commutative permanent. more generally, we consider such sum-of-squares identities for any m polynomial h(x,y), namely: h(x,y) = f12+f22+...+fn2. again, proving n ≥ k1+ε in for any explicit h over the complex numbers gives an exponential lower bound for the non-commutative permanent. our proofs relies on several new structure theorems for non-commutative circuits, as well as a non-commutative analog of valiant's completeness of the permanent. we proceed to prove such super-linear bounds in some restricted cases. we prove that n ≥ ω(k6/5) in (1), if f1,..., fn are required to have integer coefficients. over the real numbers, we construct an explicit m polynomial h such that n in (2) must be at least ω(k2). unfortunately, these results do not imply circuit lower bounds. we also present other structural results about non-commutative arithmetic circuits. we show that any non-commutative circuit computing an ordered non-commutative polynomial can be efficiently transformed to a syntactically multilinear circuit computing that polynomial. the permanent, for example, is ordered. hence, lower bounds on the size of syntactically multilinear circuits computing the permanent imply unrestricted non-commutative lower bounds. we also prove an exponential lower bound on the size of non-commutative syntactically multilinear circuit computing an explicit polynomial. this polynomial is, however, not ordered and an unrestricted circuit lower bound does not follow.
graph expansion and the unique games conjecture. the edge expansion of a subset of vertices s ⊆ v in a graph g measures the fraction of edges that leave s. in a d-regular graph, the edge expansion/conductance φ(s) of a subset s ⊆ v is defined as φ(s) = (|e(s, v\s)|)/(d|s|). approximating the conductance of small linear sized sets (size δ n) is a natural optimization question that is a variant of the well-studied sparsest cut problem. however, there are no known algorithms to even distinguish between almost complete edge expansion (φ(s) = 1-ε), and close to 0 expansion. in this work, we investigate the connection between graph expansion and the unique games conjecture. specifically, we show the following: we show that a simple decision version of the problem of approximating small set expansion reduces to unique games. thus if approximating edge expansion of small sets is hard, then unique games is hard. alternatively, a refutation of the ugc will yield better algorithms to approximate edge expansion in graphs. this is the first non-trivial "reverse" reduction from a natural optimization problem to unique games. under a slightly stronger ugc that assumes mild expansion of small sets, we show that it is ug-hard to approximate small set expansion. on instances with sufficiently good expansion of small sets, we show that unique games is easy by extending the techniques of [4].
on the complexity of #csp. bulatov (2008) has given a dichotomy for the counting constraint satisfaction problem, #csp. a problem from #csp is characterized by a constraint language γ, which is a fixed, finite set of relations over a finite domain. an instance of the problem uses these relations to constrain the values taken by a finite set of variables. bulatov showed that, for any fixed γ, the problem of counting the satisfying assignments of instances of any problem from #csp is either in polynomial time (fp) or #p-complete, according on the structure of the constraint language γ. his proof draws heavily on techniques from universal algebra and cannot be understood without a secure grasp of that field. we give an elementary proof of bulatov's dichotomy, based on succinct representations, which we call frames, of a class of highly structured relations, which we call strongly rectangular. we show that these are precisely the relations that are invariant under a mal'tsev polymorphism. en route, we give a simplification of a decision algorithm for strongly rectangular constraint languages due to bulatov and dalmau (2006). out proof uses no universal algebra, except for the straightforward concept of the mal'tsev polymorphism and is accessible to readers with little background in #csp.
qip = pspace. we prove that the complexity class qip, which consists of all problems having quantum interactive proof systems, is contained in pspace. this containment is proved by applying a parallelized form of the matrix multiplicative weights update method to a class of semidefinite programs that captures the computational power of quantum interactive proofs. as the containment of pspace in qip follows immediately from the well-known equality ip = pspace, the equality qip = pspace follows.
a shorter proof of the graph minor algorithm: the unique linkage theorem. at the core of the seminal graph minor theory of robertson and seymour is a powerful theorem which describes the structure of graphs excluding a fixed minor. this result is used to prove wagner's conjecture and provide a polynomial time algorithm for the disjoint paths problem when the number of the terminals is fixed (i.e, the graph minor algorithm). however, both results require the full power of the graph minor theory, i.e, the structure theorem. in this paper, we show that this is not true in the latter case. namely, we provide a new and much simpler proof of the correctness of the graph minor algorithm. specifically, we prove the "unique linkage theorem" without using graph minors structure theorem. the new argument, in addition to being simpler, is much shorter, cutting the proof by at least 200 pages. we also give a new full proof of correctness of an algorithm for the well-known edge-disjoint paths problem when the number of the terminals is fixed, which is at most 25 pages long.
extensions and limits to vertex sparsification. suppose we are given a graph g = (v, e) and a set of terminals k ⊂ v. we consider the problem of constructing a graph h = (k, eh) that approximately preserves the congestion of every multicommodity flow with endpoints supported in k. we refer to such a graph as a flow sparsifier. we prove that there exist flow sparsifiers that simultaneously preserve the congestion of all multicommodity flows within an o(log k / log log k)-factor where |k| = k. this bound improves to o(1) if g excludes any fixed minor. this is a strengthening of previous results, which consider the problem of finding a graph h = (k, eh) (a cut sparsifier) that approximately preserves the value of minimum cuts separating any partition of the terminals. indirectly our result also allows us to give a construction for better quality cut sparsifiers (and flow sparsifiers). thereby, we immediately improve all approximation ratios derived using vertex sparsification in [14]. we also prove an ω(log log k) lower bound for how well a flow sparsifier can simultaneously approximate the congestion of every multicommodity flow in the original graph. the proof of this theorem relies on a technique (which we refer to as oblivious dual certifcates) for proving super-constant congestion lower bounds against many multicommodity flows at once. our result implies that approximation algorithms for multicommodity flow-type problems designed by a black box reduction to a "uniform" case on k nodes (see [14] for examples) must incur a super-constant cost in the approximation ratio.
odd cycle packing. we consider the following problem, which is called the odd cycle packing problem. input: a graph $g$ with n vertices and m edges, and an integer k. output: k vertex disjoint odd cycles. we also consider the edge disjoint case, and the node- and arc-disjoint directed case. this problem is known to be np-hard, even for planar graphs, if k is part of input. in this paper, we first present the integrality gap and hardness results for these problems. we prove that the integrality gap of the standard lp-relaxation of the odd cycle packing problem is θ (√n). this result is obtained by giving an algorithm to compute an odd cycle packing, which gives rise to an o(√n) approximating algorithm for the fractional odd cycle packing problem (this gives rise to an upper bound), and by showing that there is a graph g such that there is an o(√n) half-integral odd cycle packing in g, but there are no two disjoint odd cycle in g (this gives rise to a lower bound). for the hardness result, we prove that for any ε, the node-disjoint directed odd cycle packing problem is np-hard to approximate within m1/2-ε, where m is the number of arcs of a given digraph g. this is true not only for the node-disjoint directed odd cycle packing problem but also for the arc-disjoint directed odd cycle packing problem. in addition, we prove that there is an o(m1/2)-approximation algorithm for the node- and arc- directed odd cycle packing problems. thus this approximation algorithm almost matches the hardness result. for the positive side, we consider the case when the number of odd cycles, k, is fixed. this is a natural direction, for example, the seminal result of robertson and seymour for the disjoint paths problem in the graph minors project. we present an o(m α(m,n) n) algorithm for any fixed k, where the function α(m,n) is the inverse of the ackermann function (see by tarjan [72]). this is the first polynomial time algorithm for this problem (and in fact, it is the first fixed parameter tractable algorithm). this proves a conjecture by lovasz and schrijver in early 1980's, who gave a polynomial time algorithm for the case k=2. our algorithm can be applied to decide whether or not g has k edge disjoint odd cycle with the same time complexity for any fixed k. we also show that our algorithm gives rise to the graph minor algorithm for the k vertex-disjoint paths problem by robertson and seymour for any fixed k. thus our algorithm is beyond the framework of the graph minor theory. our algorithm has several appealing features: we use the odd s-path theorem, which is a generalization of the well-known s-paths theorem by mader. we also introduce an odd clique minor, which can be viewed as a clique minor with some parity condition. as with the robertson-seymour algorithm to solve the k disjoint paths problem for any fixed k, in each iteration, we would like to either use a huge clique minor as a "crossbar", or exploit the structure of graphs in which we cannot find such a minor. here, however, we must maintain the parity of the cycles and can only use an "odd clique minor". we must also describe the structure of those graphs in which we cannot find such a minor and discuss how to exploit it. this part needs the seminal result of robertson and seymour for the graph minor decomposition theorem for h-minor-free graphs. we also use some deep results of robertson and seymour that are needed to prove the correctness of their algorithm for the disjoint paths problem.
improved algorithms for computing fisher's market clearing prices: computing fisher's market clearing prices. we give the first strongly polynomial time algorithm for computing an equilibrium for the linear utilities case of fisher's market model. we consider a problem with a set b of buyers and a set g of divisible goods. each buyer i starts with an initial integral allocation ei of money. the integral utility for buyer i of good j is uij. we first develop a weakly polynomial time algorithm that runs in o(n4 log umax + n3 emax) time, where n = |b| + |g|. we further modify the algorithm so that it runs in o(n4 log n) time. these algorithms improve upon the previous best running time of o(n8 log umax + n7 log emax), due to devanur et al.
public-key cryptography from different assumptions. this paper attempts to broaden the foundations of public-key cryptography. we construct new public-key encryption schemes based on new hardness-on-average assumptions for natural combinatorial np-hard optimization problems. we consider the following assumptions: it is infeasible to solve a random set of sparse linear equations mod 2, of which a small fraction is noisy. it is infeasible to distinguish between a random unbalanced bipartite graph, and such a graph in which we "plant" at random in the large side a set s with only |s|/3 neighbors. there is a pseudorandom generator in ncz where every output depends on a random constant-size subset of the inputs. we obtain semantically secure public key encryption schemes based on several combinations of these assumptions with different parameters. in particular we obtain public key encryption from assumption~1 on its own, yielding the first noisy-equations type public key scheme in which the noise rate is higher than one over the square root of the number of equations. we also obtain public-key encryption based on a combination of assumptions~2 and~3. these are arguably of more "combinatorial"/"private-key" nature than any assumptions used before for public-key cryptography. our proof involves novel "search to decision" and "search to prediction" reductions for sparse noisy linear equations. the strength of our assumptions raise new algorithmic and pseudorandomness questions (and new parameters for old ones). we give some evidence for these assumptions by studying their resistance to certain classes of natural algorithms, including semi-definite programs, aco circuits, low-degree polynomials, and cycle counting. we also relate our assumptions to other problems such as planted clique and learning juntas.
almost tight bounds for rumour spreading with conductance. we show that if a connected graph with $n$ nodes has conductance φ then rumour spreading, also known as randomized broadcast, successfully broadcasts a message within ~o(φ-1 • log n), many rounds with high probability, regardless of the source, by using the push-pull strategy. the ~o(••) notation hides a polylog φ-1 factor. this result is almost tight since there exists graph of n nodes, and conductance φ, with diameter ω(φ-1 • log n). if, in addition, the network satisfies some kind of uniformity condition on the degrees, our analysis implies that both both push and pull, by themselves, successfully broadcast the message to every node in the same number of rounds.
a sparse johnson: lindenstrauss transform. dimension reduction is a key algorithmic tool with many applications including nearest-neighbor search, compressed sensing and linear algebra in the streaming model. in this work we obtain a sparse version of the fundamental tool in dimension reduction -- the johnson-lindenstrauss transform. using hashing and local densification, we construct a sparse projection matrix with just ~o(1/ε) non-zero entries per column. we also show a matching lower bound on the sparsity for a large class of projection matrices. our bounds are somewhat surprising, given the known lower bounds of ω(1/ε2) both on the number of rows of any projection matrix and on the sparsity of projection matrices generated by natural constructions. using this, we achieve an ~o(1/ε) update time per non-zero element for a (1 ε)-approximate projection, thereby substantially outperforming the ~o(1/ε2) update time required by prior approaches. a variant of our method offers the same guarantees for sparse vectors, yet its ~o(d) worst case running time matches the best approach of ailon and liberty.
oblivious rams without cryptogrpahic assumptions. ithmic increase in the time and space requirements is possible on a probabilistic (coin flipping) ram without using any cryptographic assumptions. the simulation will fail with a negligible probability. if n memory locations are used, then the probability of failure is at most n-log n. pippenger and fischer has shown in 1979, see [7], that a turing machine with one-dimensional tapes, performing a computation of length n can be simulated on-line by an oblivious turing machine with two dimensional tapes, in time o(n log n), where a turing machine is oblivious if the movements of it heads as a function of time are independent of its input. for rams the notion of obliviousness was defined by goldreich in 1987 in [2], and he proved a simulation theorem about it. a ram is oblivious if the distribution of its memory access pattern, which memory cells are accessed at which time, is independent of the program running on the ram, provided that the time used by the program is fixed. that is, an adversary watching the memory access will not know anything about the program running on the machine apart from its total time. ostrovsky, improving goldreich's theorem, has shown in 1990, see [4], [5], [3], that a ram using n memory cells can a be simulated by an oblivious ram with a random oracle (where the random bits can be accessed repeatedly) so that the increase of the space and time requirement is only about a factor of ln (goldreich's factor was about exp[(log n)1/2]). in both cases the oblivious ram with a random oracle, can be replaced, by an oblivious probabilistic (coin-flipping) ram, provided that we accept some unproven cryptographic assumptions, e.g., the existence of a one-way function. in this paper we show that simulation with an oblivious, coin-flipping ram, with only a factor of ln increase in time and space requirements, is possible, even without any cryptographic assumptions.
towards polynomial lower bounds for dynamic problems. we consider a number of dynamic problems with no known poly-logarithmic upper bounds, and show that they require nω(1) time per operation, unless 3sum has strongly subquadratic algorithms. our result is modular: (1) we describe a carefully-chosen dynamic version of set disjointness (the "multiphase problem"), and conjecture that it requires n^omega(1) time per operation. all our lower bounds follow by easy reduction. (2) we reduce 3sum to the multiphase problem. ours is the first nonalgebraic reduction from 3sum, and allows 3sum-hardness results for combinatorial problems. for instance, it implies hardness of reporting all triangles in a graph. (3) it is plausible that an unconditional lower bound for the multiphase problem can be established via a number-on-forehead communication game.
conditional hardness of precedence constrained scheduling on identical machines. already in 1966, graham showed that a simple procedure called list scheduling yields a 2-approximation algorithm for the central problem of scheduling precedence constrained jobs on identical machines to minimize makespan. till this date it has remained the best algorithm and whether it can or cannot be improved has become a major open problem in scheduling theory. we address this problem by establishing a quite surprising relation between the approximability of the considered problem and that of scheduling precedence constrained jobs on a single machine to minimize weighted completion time. more specifically, we prove that if the single machine problem is hard to approximate within a factor of 2-ε then the considered parallel machine problem, even in the case of unit processing times, is hard to approximate within a factor of 2-ζ, where ζ tends to 0 as ε tends to 0. combining this with bansal & khot's recent hardness result for the single machine problem gives that it is np-hard to improve upon the approximation ratio obtained by graham, assuming a new variant of the unique games conjecture.
deterministic identity testing of depth-4 multilinear circuits with bounded top fan-in. we give the first sub-exponential time deterministic polynomial identity testing algorithm for depth-4 multilinear circuits with a small top fan-in. more accurately, our algorithm works for depth-4 circuits with a plus gate at the top (also known as σπσπ circuits) and has a running time of exp(poly(log(n),log(s),k)) where n is the number of variables, s is the size of the circuit and k is the fan-in of the top gate. in particular, when the circuit is of polynomial (or quasi-polynomial) size, our algorithm runs in quasi-polynomial time. in [av08], it was shown that derandomizing polynomial identity testing for general σπσπ circuits implies a derandomization of polynomial identity testing in general arithmetic circuits. prior to this work sub-exponential time deterministic algorithms were known for depth-$3$ circuits with small top fan-in and for very restricted versions of depth-4 circuits. the main ingredient in our proof is a new structural theorem for multilinear σπσπ(k) circuits. roughly, this theorem shows that any nonzero multilinear σπσπ(k) circuit contains an `embedded' nonzero multilinear σπς(k) circuit. using ideas from previous works on identity testing of sums of read-once formulas and of depth-3 multilinear circuits, we are able to exploit this structure and obtain an identity testing algorithm for multilinear σπσπ(k) circuits.
local list-decoding and testing of random linear codes from high error. in this paper, we give surprisingly efficient algorithms for list-decoding and testing random linear codes. our main result is that random sparse linear codes are locally list-decodable and locally testable in the high-error regime with only a constant number of queries. more precisely, we show that for all constants c> 0 and γ > 0, and for every linear code c ⊆ 0,1n which is: sparse: |c| ≤ nc, and unbiased: each nonzero codeword in c has weight in (1/2 - n-γ, 1/2 + n-γ), c is locally testable and locally list-decodable from (1/2 - ε)-fraction worst-case errors using only poly(1/ε) queries to a received word. we also give subexponential time algorithms for list-decoding arbitrary unbiased (but not necessarily sparse) linear codes in the high-error regime. in particular, this yields the first subexponential time algorithm even for the problem of (unique) decoding random linear codes of inverse-polynomial rate from a fixed positive fraction of errors. earlier, kaufman and sudan had shown that sparse, unbiased codes can be locally (unique) decoded and locally tested from a constant fraction of errors, where this constant fraction tends to 0 as the number of codewords grows. our results significantly strengthen their results, while also having significantly simpler proofs. at the heart of our algorithms is a natural "self-correcting" operation defined on codes and received words. this self-correcting operation transforms a code c with a received word w into a simpler code c' and a related received word w', such that w is close to c if and only if w' is close to c'. starting with a sparse, unbiased code c and an arbitrary received word w, a constant number of applications of the self-correcting operation reduces us to the case of local list-decoding and testing for the hadamard code, for which the well known algorithms of goldreich-levin and blum-luby-rubinfeld are available. this yields the constant-query local algorithms for the original code c. our algorithm for decoding unbiased linear codes in subexponential time proceeds similarly. applying the self-correcting operation to an unbiased code c and an arbitrary received word a super-constant number of times, we get reduced to the problem of learning noisy parities, for which non-trivial subexponential time algorithms were recently given by blum-kalai-wasserman and feldman-gopalan-khot-ponnuswami. our result generalizes a result of lyubashevsky, which gave a subexponential time algorithm for decoding random linear codes of inverse-polynomial rate from random errors.
efficiency improvements in constructing pseudorandom generators from one-way functions. we give a new construction of pseudorandom generators from any one-way function. the construction achieves better parameters and is simpler than that given in the seminal work of hastad, impagliazzo, levin, and luby [sicomp '99]. the key to our construction is a new notion of "next-block pseudoentropy", which is inspired by the notion of "inaccessible entropy" recently introduced in [haitner, reingold, vadhan, wee, stoc '09]. an additional advantage over previous constructions is that our pseudorandom generators are parallelizable and invoke the one-way function in a non-adaptive manner. using [applebaum, ishai, kushilevitz, sicomp '06], this implies the existence of pseudorandom generators in nc^0 based on the existence of one-way functions in nc^1.
differential privacy under continual observation. differential privacy is a recent notion of privacy tailored to privacy-preserving data analysis [11]. up to this point, research on differentially private data analysis has focused on the setting of a trusted curator holding a large, static, data set; thus every computation is a "one-shot" object: there is no point in computing something twice, since the result will be unchanged, up to any randomness introduced for privacy. however, many applications of data analysis involve repeated computations, either because the entire goal is one of monitoring, e.g., of traffic conditions, search trends, or incidence of influenza, or because the goal is some kind of adaptive optimization, e.g., placement of data to minimize access costs. in these cases, the algorithm must permit continual observation of the system's state. we therefore initiate a study of differential privacy under continual observation. we identify the problem of maintaining a counter in a privacy preserving manner and show its wide applicability to many different problems.
how to compress interactive communication. we describe new ways to simulate 2-party communication protocols to get protocols with potentially smaller communication. we show that every communication protocol that communicates c bits and reveals i bits of information about the inputs to the participating parties can be simulated by a new protocol involving at most ~o(√ci) bits of communication. if the protocol reveals i bits of information about the inputs to an observer that watches the communication in the protocol, we show how to carry out the simulation with ~o(i) bits of communication. these results lead to a direct sum theorem for randomized communication complexity. ignoring polylogarithmic factors, we show that for worst case computation, computing n copies of a function requires √n times the communication required for computing one copy of the function. for average case complexity, given any distribution μ on inputs, computing n copies of the function on n inputs sampled independently according to μ requires √n times the communication for computing one copy. if μ is a product distribution, computing n copies on n independent inputs sampled according to μ requires n times the communication required for computing the function. we also study the complexity of computing the sum (or parity) of n evaluations of f, and obtain results analogous to those above.
message passing algorithms: a success looking for theoreticians. message passing algorithms have emerged as a powerful heuristic for addressing hard problems in a variety of applied fields. interesting and successful examples can be found in domain as diverse as coding and communications, signal processing, artificial intelligence, game theory, high-dimensional statistics. at least four reasons can be found for this success: 1. they are widely applicable whenever the underlying problem has a 'local' structure with respect to a suitable graph; 2. they are easy to implement and have linear or next-to-linear complexity (within coding they are widely implemented in hardware); 4. they often subsume existing heuristics as special cases; 5. on some random instance distributions which are important in practice, they can be analyzed precisely and tuned to achieve near-optimal performances. each of these five points can be argued through examples. it would be highly desirable to make sense of them (of any subset of them)in a consistent theory.
matroid matching: the power of local search. we consider the classical matroid matching problem. unweighted matroid matching for linear matroids was solved by lovasz, and the problem is known to be intractable for general matroids. we present a ptas for unweighted matroid matching for general matroids. in contrast, we show that natural lp relaxations have an ω(n) integrality gap and moreover, ω(n) rounds of the sherali-adams hierarchy are necessary to bring the gap down to a constant. more generally, for any fixed k>=2 and ε>0, we obtain a (k/2+ε)-approximation for matroid matching in k-uniform hypergraphs, also known as the matroid k-parity problem. as a consequence, we obtain a (k/2+ε)-approximation for the problem of finding the maximum-cardinality set in the intersection of k matroids. we have also designed a 3/2-approximation for the weighted version of a special case of matroid matching, the matchoid problem.
privacy amplification with asymptotically optimal entropy loss. we study the problem of "privacy amplification": key agreement between two parties who both know a weak secret w, such as a password. (such a setting is ubiquitous on the internet, where passwords are the most commonly used security device.) we assume that the key agreement protocol is taking place in the presence of an active computationally unbounded adversary eve. the adversary may have partial knowledge about w, so we assume only that w has some entropy from eve's point of view. thus, the goal of the protocol is to convert this non-uniform secret w into a uniformly distributed string r that is fully secret from eve. r may then be used as a key for running symmetric cryptographic protocols (such as encryption, authentication, etc.). because we make no computational assumptions, the entropy in r can come only from w. thus such a protocol must minimize the entropy loss during its execution, so that r is as long as possible. the best previous results have entropy loss of θ(κ2), where κ is the security parameter, thus requiring the password to be very long even for small values of κ. in this work, we present the first protocol for information-theoretic key agreement that has entropy loss linear in the security parameter. the result is optimal up to constant factors. we achieve our improvement through a somewhat surprising application of error-correcting codes for the edit distance.
multi-parameter mechanism design and sequential posted pricing. we study the classic mathematical economics problem of bayesian optimal mechanism design where a principal aims to optimize expected revenue when allocating resources to self-interested agents with preferences drawn from a known distribution. in single parameter settings (i.e., where each agent's preference is given by a single private value for being served and zero for not being served) this problem is solved [20]. unfortunately, these single parameter optimal mechanisms are impractical and rarely employed [1], and furthermore the underlying economic theory fails to generalize to the important, relevant, and unsolved multi-dimensional setting (i.e., where each agent's preference is given by multiple values for each of the multiple services available) [25]. in contrast to the theory of optimal mechanisms we develop a theory of sequential posted price mechanisms, where agents in sequence are offered take-it-or-leave-it prices. we prove that these mechanisms are approximately optimal in single-dimensional settings. these posted-price mechanisms avoid many of the properties of optimal mechanisms that make the latter impractical. furthermore, these mechanisms generalize naturally to multi-dimensional settings where they give the first known approximations to the elusive optimal multi-dimensional mechanism design problem. in particular, we solve multi-dimensional multi-unit auction problems and generalizations to matroid feasibility constraints. the constant approximations we obtain range from 1.5 to 8. for all but one case, our posted price sequences can be computed in polynomial time. this work can be viewed as an extension and improvement of the single-agent algorithmic pricing work of [9] to the setting of multiple agents where the designer has combinatorial feasibility constraints on which agents can simultaneously obtain each service.
load balancing and orientability thresholds for random hypergraphs. let h>w>0 be two fixed integers. let h be a random hypergraph whose hyperedges are all of cardinality h. to w-orient a hyperedge, we assign exactly w of its vertices positive signs with respect to the hyperedge, and the rest negative. a (w,k)-orientation of h consists of a w-orientation of all hyperedges of h, such that each vertex receives at most k positive signs from its incident hyperedges. when k is large enough, we determine the threshold of the existence of a (w,k)-orientation of a random hypergraph. the (w,k)-orientation of hypergraphs is strongly related to a general version of the off-line load balancing problem. the graph case, when h=2 and w=1, was solved recently by cain, sanders and wormald and independently by fernholz and ramachandran, thereby settling a conjecture made by karp and saks. motivated by a problem of cuckoo hashing, the special hypergraph case with w=k=1, was solved in three separate preprints dating from october 2009, by frieze and melsted, by fountoulakis and panagiotou, and by dietzfelbinger, goerdt, mitzenmacher, montanari, pagh and rink.
bounding the average sensitivity and noise sensitivity of polynomial threshold functions. we give the first non-trivial upper bounds on the average sensitivity and noise sensitivity of degree-d polynomial threshold functions (ptfs). these bounds hold both for ptfs over the boolean hypercube {-1,1}n and for ptfs over rn under the standard n-dimensional gaussian distribution n(0,in). our bound on the boolean average sensitivity of ptfs represents progress towards the resolution of a conjecture of gotsman and linial [17], which states that the symmetric function slicing the middle d layers of the boolean hypercube has the highest average sensitivity of all degree-d ptfs. via the l1 polynomial regression algorithm of kalai et al. [22], our bounds on gaussian and boolean noise sensitivity yield polynomial-time agnostic learning algorithms for the broad class of constant-degree ptfs under these input distributions. the main ingredients used to obtain our bounds on both average and noise sensitivity of ptfs in the gaussian setting are tail bounds and anti-concentration bounds on low-degree polynomials in gaussian random variables [20, 7]. to obtain our bound on the boolean average sensitivity of ptfs, we generalize the "critical-index" machinery of [37] (which in that work applies to halfspaces, i.e. degree-1 ptfs) to general ptfs. together with the "invariance principle" of [30], this lets us extend our techniques from the gaussian setting to the boolean setting. our bound on boolean noise sensitivity is achieved via a simple reduction from upper bounds on average sensitivity of boolean ptfs to corresponding bounds on noise sensitivity.
weighted geometric set cover via quasi-uniform sampling. there has been much progress on geometric set cover problems, but most known techniques only apply to the unweighted setting. for the weighted setting, very few results are known with approximation guarantees better than that for the combinatorial set cover problem. in this article, we employ the idea of quasi-uniform sampling to obtain improved approximation guarantees in the weighted setting for a large class of problems for which such guarantees were known in the unweighted case. as a consequence of this sampling method, we obtain new results on the fractional set cover packing problem.
changing base without losing space. we describe a simple, but powerful local encoding technique, implying two surprising results: 1. we show how to represent a vector of n values from some alphabet s using ceiling(n * log2 |s|) bits, such that reading or writing any entry takes o(1) time. this demonstrates, for instance, an "equivalence" between decimal and binary computers, and has been a central toy problem in the field of succinct data structures. previous solutions required space of n * log2 |s| + n/logo(1) n bits for constant access. 2. given a stream of n bits arriving online (for any n, not known in advance), we can output a *prefix-free* encoding that uses n + log2 n + o(loglog n) bits. the encoding and decoding algorithms only require o(log n) bits of memory, and run in constant time per word. this result is interesting in cryptographic applications, as prefix-free codes are the simplest counter-measure to extensions attacks on hash functions, message authentication codes and pseudorandom functions. our result refutes a conjecture of [maurer, sjodin 2005] on the hardness of online prefix-free encodings.
are many small sets explicitly small? we discuss various aspects of a conjecture that spans analysis, probability and combinatorics. we find it interesting enough to offer a $1000 prize for a solution of any of the main problems.
a deterministic single exponential time algorithm for most lattice problems based on voronoi cell computations. we give deterministic ~o(22n+o(n))-time algorithms to solve all the most important computational problems on point lattices in np, including the shortest vector problem (svp), closest vector problem (cvp), and shortest independent vectors problem (sivp). this improves the no(n) running time of the best previously known algorithms for cvp (kannan, math. operation research 12(3):415--440, 1987) and sivp (micciancio, proc. of soda, 2008), and gives a deterministic and asymptotically faster alternative to the 2o(n)-time (and space) randomized algorithm for svp of (ajtai, kumar and sivakumar, stoc 2001). the core of our algorithm is a new method to solve the closest vector problem with preprocessing (cvpp) that uses the voronoi cell of the lattice (described as intersection of half-spaces) as the result of the preprocessing function. in the process, we also give algorithms for several other lattice problems, including computing the kissing number of a lattice, and computing the set of all voronoi relevant vectors. all our algorithms are deterministic, and have 2o(n) time and space complexity.
complexity theory for operators in analysis. we propose a new framework for discussing computational complexity of problems involving uncountably many objects, such as real numbers, sets and functions, that can be represented only through approximation. the key idea is to use a certain class of string functions, which we call regular functions, as names representing these objects. these are more expressive than infinite sequences, which served as names in prior work that formulated complexity in more restricted settings. an important advantage of using regular functions is that we can define their size in the way inspired by higher-type complexity theory. this enables us to talk about computation on regular functions whose time or space is bounded polynomially in the input size, giving rise to more general analogues of the classes p, np, and pspace. we also define np- and pspace-completeness under suitable many-one reductions. because our framework separates machine computation and semantics, it can be applied to problems on sets of interest in analysis once we specify a suitable representation (encoding). as prototype applications, we consider the complexity of functions (operators) on real numbers, real sets, and real functions. the latter two cannot be represented succinctly using existing approaches based on infinite sequences, so ours is the first treatment of them. as an interesting example, the task of numerical algorithms for solving the initial value problem of differential equations is naturally viewed as an operator taking real functions to real functions. as there was no complexity theory for operators, previous results could only state how complex the solution can be. we now reformulate them to show that the operator itself is polynomial-space complete.
interactive privacy via the median mechanism. we define a new interactive differentially private mechanism --- the median mechanism --- for answering arbitrary predicate queries that arrive online. given fixed accuracy and privacy constraints, this mechanism can answer exponentially more queries than the previously best known interactive privacy mechanism (the laplace mechanism, which independently perturbs each query result). with respect to the number of queries, our guarantee is close to the best possible, even for non-interactive privacy mechanisms. conceptually, the median mechanism is the first privacy mechanism capable of identifying and exploiting correlations among queries in an interactive setting. we also give an efficient implementation of the median mechanism, with running time polynomial in the number of queries, the database size, and the domain size. this efficient implementation guarantees privacy for all input databases, and accurate query results for almost all input distributions. the dependence of the privacy on the number of queries in this mechanism improves over that of the best previously known efficient mechanism by a super-polynomial factor, even in the non-interactive setting.
efficiently learning mixtures of two gaussians. given data drawn from a mixture of multivariate gaussians, a basic problem is to accurately estimate the mixture parameters. we provide a polynomial-time algorithm for this problem for the case of two gaussians in $n$ dimensions (even if they overlap), with provably minimal assumptions on the gaussians, and polynomial data requirements. in statistical terms, our estimator converges at an inverse polynomial rate, and no such estimator (even exponential time) was known for this problem (even in one dimension). our algorithm reduces the n-dimensional problem to the one-dimensional problem, where the method of moments is applied. one technical challenge is proving that noisy estimates of the first six moments of a univariate mixture suffice to recover accurate estimates of the mixture parameters, as conjectured by pearson (1894), and in fact these estimates converge at an inverse polynomial rate. as a corollary, we can efficiently perform near-optimal clustering: in the case where the overlap between the gaussians is small, one can accurately cluster the data, and when the gaussians have partial overlap, one can still accurately cluster those data points which are not in the overlap region. a second consequence is a polynomial-time density estimation algorithm for arbitrary mixtures of two gaussians, generalizing previous work on axis-aligned gaussians (feldman {\em et al}, 2006).
approximations for the isoperimetric and spectral profile of graphs and related parameters. the spectral profile of a graph is a natural generalization of the classical notion of its rayleigh quotient. roughly speaking, given a graph g, for each 0g(δ) minimizes the rayleigh quotient (from the variational characterization) of the spectral gap of the laplacian matrix of g over vectors with support at most δ over a suitable probability measure. formally, the spectral profile λg of a graph g is a function λg : [0,1/2] -> r defined as: λg(δ) def= minx∈ rvd(supp(x))≤ δ (∑gij (xi-xj)2)/(∑i di xi2) where gij is the weight of the edge (i,j) in the graph, di is the degree of vertex i, and d(\supp(x)) is the fraction of edges incident on vertices within the support of vector x. while the notion of the spectral profile has numerous applications in markov chain, it is also is closely tied to its isoperimetric profile of a graph. specifically, the spectral profile is a relaxation for the problem of approximating edge expansion of small sets in graphs. in this work, we obtain an efficient algorithm that yields a log(1/δ)-factor approximation for the value of λg(δ). by virtue of its connection to edge-expansion, we also obtain an algorithm for the problem of approximating edge expansion of small linear sized sets in a graph. this problem was recently shown to be intimately connected to the unique games conjecture in [18]. finally, we extend the techniques to obtain approximation algorithms with similar guarantees for restricted eigenvalue problems on diagonally dominant matrices.
combinatorial approach to the interpolation method and scaling limits in sparse random graphs. we establish the existence of free energy limits for several sparse random hypergraph models corresponding to certain combinatorial models on erdos-renyi (er) graph g(n,c/n) and random r-regular graph g(n,r). for a variety of models, including independent sets, max-cut, coloring and k-sat, we prove that the free energy both at a positive and zero temperature, appropriately rescaled, converges to a limit as the size of the underlying graph diverges to infinity. in the zero temperature case, this is interpreted as the existence of the scaling limit for the corresponding combinatorial optimization problem. for example, as a special case we prove that the size of a largest independent set in these graphs, normalized by the number of nodes converges to a limit w.h.p., thus resolving an open problem, (see conjecture 2.20 in wormald's random graph models, or aldous's list of open problems. our approach is based on extending and simplifying the interpolation method of guerra and toninelli. among other applications, this method was used to prove the existence of free energy limits for viana-bray and k-sat models on er graphs. the case of zero temperature was treated by taking limits of positive temperature models. we provide instead a simpler combinatorial approach and work with the zero temperature case (optimization) directly both in the case of er graph g(n,c/n) and random regular graph g(n,r). in addition we establish the large deviations principle for the satisfiability property for constraint satisfaction problems such as coloring, k-sat and nae-k-sat.
saving space by algebraization. the subset sum and knapsack problems are fundamental np-complete problems and the pseudo-polynomial time dynamic programming algorithms for them appear in every algorithms textbook. the algorithms require pseudo-polynomial time and space. since we do not expect polynomial time algorithms for subset sum and knapsack to exist, a very natural question is whether they can be solved in pseudo-polynomial time and polynomial space. in this paper we answer this question affirmatively, and give the first pseudo-polynomial time, polynomial space algorithms for these problems. our approach is based on algebraic methods and turns out to be useful for several other problems as well. then we show how the framework yields polynomial space exact algorithms for the classical traveling salesman, weighted set cover and weighted steiner tree problems as well. our algorithms match the time bound of the best known pseudo-polynomial space algorithms for these problems.
zero-one frequency laws. data streams emerged as a critical model for multiple applications that handle vast amounts of data. one of the most influential and celebrated papers in streaming is the "ams" paper on computing frequency moments by alon, matias and szegedy. the main question left open (and explicitly asked) by ams in 1996 is to give the precise characterization for which functions g on frequency vectors mi (1≤ i ≤ n) can σi∈ [n] g(mi) be approximated efficiently, where "efficiently" means by a single pass over data stream and poly-logarithmic memory. no such characterization was known despite a tremendous amount of research on frequency-based functions in streaming literature. in this paper we finally resolve the ams main question and give a precise characterization (in fact, a zero-one law) for all monotonically increasing functions on frequencies that are zero at the origin. that is, we consider all monotonic functions g: r → r such that g(0) = 0 and g can be computed in poly-logarithmic time and space and ask, for which g in this class is there an (1±ε)-approximation algorithm for computing σi∈ [n] g(mi) for any polylogarithmic ε? we give an algebraic characterization for all such g so that: for all functions g in our class that satisfy our algebraic condition, we provide a very general and constructive way to derive an efficient (1±ε)-approximation algorithm for computing σi∈ [n] g(mi) with polylogarithmic memory and a single pass over data stream; while: for all functions g in our class that do not satisfy our algebraic characterization, we show a lower bound that requires greater then polylog memory for computing an approximation to σi∈ [n] g(mi) by any one-pass streaming algorithm. thus, we provide a zero-one law for all monotonically increasing functions g which are zero at the origin. our results are quite general. as just one illustrative example, our main theorem implies a lower bound for g(x) =(x(x-1))0.5arctan(x+1), while for a function g(x) =(x(x+1))0.5arctan(x+1) our main theorem automatically yields a polylog memory one-pass (1±ε)-approximation algorithm for computing σi∈ [n] g(mi). for both of these examples no lower or upper bounds were known. of course, these are just illustrative examples, and there are many others. one might argue that these two functions may not be of interest in practical applications -- we stress that our law works for all functions in this class, and the above examples illustrate the power of our method. to the best of our knowledge, this is the first zero-one law in the streaming model for a wide class of functions, though we suspect that there are many more such laws to be discovered. surprisingly, our upper bound requires only 4-wise independence and does not need the stronger machinery of nisan's pseudorandom generators, even though our class captures multiple functions that previously required nisan's generators. furthermore, we believe that our methods can be extended to the more general models and complexity classes. for instance, the law also holds for a smaller class of non-decreasing and symmetric functions (i.e., g(x) = g(-x) and g(0) = 0) which, due to negative values, allow deletions.
maintaining a large matching and a small vertex cover. we consider the problem of maintaining a large matching and a small vertex cover in a dynamically changing graph. each update to the graph is either an edge deletion or an edge insertion. we give the first randomized data structure that simultaneously achieves a constant approximation factor and handles a sequence of k updates in k*polylog(n) time, where n is the number of vertices in the graph. previous data structures require a polynomial amount of computation per update.
connectivity oracles for failure prone graphs. dynamic graph connectivity algorithms have been studied for many years, but typically in the most general possible setting, where the graph can evolve in completely arbitrary ways. in this paper we consider a dynamic subgraph model. we assume there is some fixed, underlying graph that can be preprocessed ahead of time. the graph is subject only to vertices and edges flipping "off" (failing) and "on" (recovering), where queries naturally apply to the subgraph on edges/vertices currently flipped on. this model fits most real world scenarios, where the topology of the graph in question (say a router network or road network) is constantly evolving due to temporary failures but never deviates too far from the ideal failure-free state. we present the first efficient connectivity oracle for graphs susceptible to vertex failures. given vertices u and v and a set d of d failed vertices, we can determine if there is a path from u to v avoiding d in time polynomial in d log n. there is a tradeoff in our oracle between the space, which is roughly mnε, for 0d)) or update time ω(dn), that is, linear in the number of vertices. our connectivity oracle is therefore the first of its kind. as a byproduct of our oracle for vertex failures we reduce the problem of constructing an edge-failure oracle to 2d range searching over the integers. we show there is an ~o(m)-space oracle that processes any set of d failed edges in o(d2 log log n) time and, thereafter, answers connectivity queries in o(log log n) time. our update time is exponentially faster than a recent connectivity oracle of patrascu and thorup for bounded d, but slower as a function of d.
the hom problem is decidable. we provide an algorithm that, given a tree homomorphism h and a regular tree language l represented by a tree automaton, determines whether h(l) is regular. this settles a question that has been open for a long time. along the way, we develop new constructions and techniques which are interesting by themselves, and provide several significant intermediate results. for example, we prove that the universality problem is decidable for languages represented by tree automata with equality constraints, and that the equivalence and inclusion problems are decidable for images of regular tree languages through tree homomorphisms. our algorithms are based on the following constructions. we describe a simple transformation for converting a tree automaton with equality constraints into a tree automaton with inequality constraints recognizing the complementary language. we also define a new class of automata with arbitrary inequality constraints and a particular kind of equality constraints. an automaton of this new class essentially recognizes the intersection of a tree automaton with inequality constraints and the image of a regular tree language through a tree homomorphism. we prove decidability of emptiness and finiteness for this class by a pumping mechanism.
an optimal ancestry scheme and small universal posets. in this paper, we solve the ancestry problem, which was introduced more than twenty years ago by kannan et al. [stoc '88], and is among the most well-studied problems in the field of informative labeling schemes. specifically, we construct an ancestry labeling scheme for n-node trees with label size log2 n + o(log log n) bits, thus matching the log2 n + ω(log log n) bits lower bound given by alstrup et al. [soda '03]. besides its optimal label size, our scheme assigns the labels in linear time, and guarantees that any ancestry query can be answered in constant time. in addition to its potential impact in terms of improving the performances of xml search engines, our ancestry scheme is also useful in the context of partially ordered sets. specifically, for any fixed integer k, our scheme enables the construction of a universal poset of size o(nk log4k n) for the family of n-element posets with tree-dimension at most k. this bound is almost tight thanks to a lower bound of nk-o(1) due to alon and scheinerman [order '88].
spectral methods for matrices and tensors. while spectral methods have long been used for principal component analysis, this survey focusses on work over the last 15 years with three salient features: (i) spectral methods are useful not only for numerical problems, but also discrete optimization problems (constraint optimization problems - csp's) like the max. cut problem and similar mathematical considerations underlie both areas. (ii) spectral methods can be extended to tensors. the theory and algorithms for tensors are not as simple/clean as for matrices, but the survey describes methods for low-rank approximation which extend to tensors. these tensor approximations help us solve max-$r$-csp's for $r>2$ as well as numerical tensor problems. (iii) sampling on the fly plays a prominent role in these methods. a primary result is that for any matrix, a random submatrix of rows/columns picked with probabilities proportional to the squared lengths (of rows/columns), yields estimates of the singular values as well as an approximation to the whole matrix.
on the complexity of circuit satisfiability. in this paper, we are concerned with the exponential complexity of the circuit satisfiability (cktsat) problem and more generally with the exponential complexity of np-complete problems. over the past 15 years or so, researchers have obtained a number of exponential-time algorithms with improved running times for exactly solving a variety of np-complete problems. the improvements are typically in the form of better exponents compared to exhaustive search. our goal is to develop techniques to prove specific lower bounds on the exponents under plausible complexity assumptions. we consider natural, though restricted, algorithmic paradigms and prove upper bounds on the success probability. our approach has the advantage of clarifying the relative power of various algorithmic paradigms. our main technique is a success probability amplification technique, called the exponential amplification lemma, which shows that for any f(n,m)-size bounded probabilistic circuit family a that decides cktsat with success probability at least 2-α n for α-α2 n > 2-α n. in contrast, the standard method for boosting success probability by repeated trials will improve it to (1-(1-2-α n)t) (approx t2-α n for t=o(2α n)) using circuits of size about tf(n,m). using this lemma, we derive tight bounds on the exponent of the success probability for deciding the cktsat problem in a variety of probabilistic computational models under complexity assumptions. for example, we show that the success probability cannot be better than 2-n+o(n) for deciding cktsat by probabilistic polynomial size circuits unless cktsat (thereby all of np) for polynomial size instances can be decided by 2nμ size deterministic circuits for some μ -n+o(n) unless cktsat (as well as np) has o(mo(lg lg m)) size deterministic circuits, which is very close to the statement np ⊆ p/poly, an unlikely scenario.
faster approximation schemes for fractional multicommodity flow problems via dynamic graph algorithms. we combine the work of garg and konemann, and fleischer with ideas from dynamic graph algorithms to obtain faster (1-ε)-approximation schemes for various versions of the multicommodity flow problem. in particular, if ε is moderately small and the size of every number used in the input instance is polynomially bounded, the running times of our algorithms match -- up to poly-logarithmic factors and some provably optimal terms -- the ω(mn) flow-decomposition barrier for single-commodity flow.
augmenting undirected node-connectivity by one. we present a min-max formula for the problem of augmenting the node-connectivity of a graph by one and give a polynomial time algorithm for finding an optimal solution. we also solve the minimum cost version for node-induced cost functions.
budget constrained auctions with heterogeneous items. in this paper, we present the first approximation algorithms for the problem of designing revenue optimal bayesian incentive compatible auctions when there are multiple (heterogeneous) items and when bidders have arbitrary demand and budget constraints (and additive valuations). our mechanisms are surprisingly simple: we show that a sequential all-pay mechanism is a 4 approximation to the revenue of the optimal ex-interim truthful mechanism with a discrete type space for each bidder, where her valuations for different items can be correlated. we also show that a sequential posted price mechanism is a o(1) approximation to the revenue of the optimal ex-post truthful mechanism when the type space of each bidder is a product distribution that satisfies the standard hazard rate condition. we further show a logarithmic approximation when the hazard rate condition is removed, and complete the picture by showing that achieving a sub-logarithmic approximation, even for regular distributions and one bidder, requires pricing bundles of items. our results are based on formulating novel lp relaxations for these problems, and developing generic rounding schemes from first principles.
improving exhaustive search implies superpolynomial lower bounds. the p vs np problem arose from the question of whether exhaustive search is necessary for problems with short verifiable solutions. we still do not know if even a slight algorithmic improvement over exhaustive search is universally possible for all np problems, and to date no major consequences have been derived from the assumption that an improvement exists. we show that there are natural np and bpp problems for which minor algorithmic improvements over the trivial deterministic simulation already entail lower bounds such as nexp is not in p/poly and logspace is not equal to np. these results are especially interesting given that similar improvements have been found for many other hard problems. optimistically, one might hope our results suggest a new path to lower bounds; pessimistically, they show that carrying out the seemingly modest program of finding slightly better algorithms for all search problems may be extremely difficult (if not impossible). we also prove unconditional superpolynomial time-space lower bounds for improving on exhaustive search.
cross-lingual semantic relatedness using encyclopedic knowledge. in this paper, we address the task of crosslingual semantic relatedness. we introduce a method that relies on the information extracted from wikipedia, by exploiting the interlanguage links available between wikipedia versions in multiple languages. through experiments performed on several language pairs, we show that the method performs well, with a performance comparable to monolingual measures of relatedness.
weighted alignment matrices for statistical machine translation. current statistical machine translation systems usually extract rules from bilingual corpora annotated with 1-best alignments. they are prone to learn noisy rules due to alignment mistakes. we propose a new structure called weighted alignment matrix to encode all possible alignments for a parallel text compactly. the key idea is to assign a probability to each word pair to indicate how well they are aligned. we design new algorithms for extracting phrase pairs from weighted alignment matrices and estimating their probabilities. our experiments on multiple language pairs show that using weighted matrices achieves consistent improvements over using n-best lists in significant less extraction time.
non-projective parsing for statistical machine translation. we describe a novel approach for syntax-based statistical mt, which builds on a variant of tree adjoining grammar (tag). inspired by work in discriminative dependency parsing, the key idea in our approach is to allow highly flexible reordering operations during parsing, in combination with a discriminative model that can condition on rich features of the source-language string. experiments on translation from german to english show improvements over phrase-based systems, both in terms of bleu scores and in human evaluations.
simple coreference resolution with rich syntactic and semantic features. coreference systems are driven by syntactic, semantic, and discourse constraints. we present a simple approach which completely modularizes these three aspects. in contrast to much current work, which focuses on learning and on the discourse component, our system is deterministic and is driven entirely by syntactic and semantic compatibility as learned from a large, unlabeled corpus. despite its simplicity and discourse naivete, our system substantially outperforms all unsupervised systems and most supervised ones. primary contributions include (1) the presentation of a simple-to-reproduce, high-performing baseline and (2) the demonstration that most remaining errors can be attributed to syntactic and semantic factors external to the coreference phenomenon (and perhaps best addressed by non-coreference systems).
graph alignment for semi-supervised semantic role labeling. unknown lexical items present a major obstacle to the development of broad-coverage semantic role labeling systems. we address this problem with a semi-supervised learning approach which acquires training instances for unseen verbs from an unlabeled corpus. our method relies on the hypothesis that unknown lexical items will be structurally and semantically similar to known items for which annotations are available. accordingly, we represent known and unknown sentences as graphs, formalize the search for the most similar verb as a graph alignment problem and solve the optimization using integer linear programming. experimental results show that role labeling performance for unknown lexical items improves with training data produced automatically by our method.
active learning by labeling features. methods that learn from prior information about input features such as generalized expectation (ge) have been used to train accurate models with very little effort. in this paper, we propose an active learning approach in which the machine solicits "labels" on features rather than instances. in both simulated and real user experiments on two sequence labeling tasks we show that our active learning method outperforms passive learning with features as well as traditional active learning with instances. preliminary experiments suggest that novel interfaces which intelligently solicit labels on multiple features facilitate more efficient annotation.
global learning of noun phrase anaphoricity in coreference resolution via label propagation. knowledge of noun phrase anaphoricity might be profitably exploited in coreference resolution to bypass the resolution of non-anaphoric noun phrases. however, it is surprising to notice that recent attempts to incorporate automatically acquired anaphoricity information into coreference resolution have been somewhat disappointing. this paper employs a global learning method in determining the anaphoricity of noun phrases via a label propagation algorithm to improve learning-based coreference resolution. in particular, two kinds of kernels, i.e. the feature-based rbf kernel and the convolution tree kernel, are employed to compute the anaphoricity similarity between two noun phrases. experiments on the ace 2003 corpus demonstrate the effectiveness of our method in anaphoricity determination of noun phrases and its application in learning-based coreference resolution.
on the role of lexical features in sequence labeling. we use the technique of svm anchoring to demonstrate that lexical features extracted from a training corpus are not necessary to obtain state of the art results on tasks such as named entity recognition and chunking. while standard models require as many as 100k distinct features, we derive models with as little as 1k features that perform as well or better on different domains. these robust reduced models indicate that the way rare lexical features contribute to classification in nlp is not fully understood. contrastive error analysis (with and without lexical features) indicates that lexical features do contribute to resolving some semantic and complex syntactic ambiguities -- but we find this contribution does not generalize outside the training corpus. as a general strategy, we believe lexical features should not be directly derived from a training corpus but instead, carefully inferred and selected from other sources.
discriminative substring decoding for transliteration. we present a discriminative substring decoder for transliteration. this decoder extends recent approaches for discriminative character transduction by allowing for a list of known target-language words, an important resource for transliteration. our approach improves upon sherif and kondrak's (2007b) state-of-the-art decoder, creating a 28.5% relative improvement in transliteration accuracy on a japanese katakana-to-english task. we also conduct a controlled comparison of two feature paradigms for discriminative training: indicators and hybrid generative features. surprisingly, the generative hybrid outperforms its purely discriminative counterpart, despite losing access to rich source-context features. finally, we show that machine transliterations have a positive impact on machine translation quality, improving human judgments by 0.5 on a 4-point scale.
supervised learning of a probabilistic lexicon of verb semantic classes. the work presented in this paper explores a supervised method for learning a probabilistic model of a lexicon of verbnet classes. we intend for the probabilistic model to provide a probability distribution of verb-class associations, over known and unknown verbs, including polysemous words. in our approach, training instances are obtained from an existing lexicon and/or from an annotated corpus, while the features, which represent syntactic frames, semantic similarity, and selectional preferences, are extracted from unannotated corpora. our model is evaluated in type-level verb classification tasks: we measure the prediction accuracy of verbnet classes for unknown verbs, and also measure the dissimilarity between the learned and observed probability distributions. we empirically compare several settings for model learning, while we vary the use of features, source corpora for feature extraction, and disam-biguated corpora. in the task of verb classification into all verbnet classes, our best model achieved a 10.69% error reduction in the classification accuracy, over the previously proposed model.
language models based on semantic composition. in this paper we propose a novel statistical language model to capture long-range semantic dependencies. specifically, we apply the concept of semantic composition to the problem of constructing predictive history representations for upcoming words. we also examine the influence of the underlying semantic space on the composition task by comparing spatial semantic representations against topic-based ones. the composition models yield reductions in perplexity when combined with a standard n-gram language model over the n-gram model alone. we also obtain perplexity reductions when integrating our models with a structured language model.
sinuhe - statistical machine translation using a globally trained conditional exponential family translation model. we present a new phrase-based conditional exponential family translation model for statistical machine translation. the model operates on a feature representation in which sentence level translations are represented by enumerating all the known phrase level translations that occur inside them. this makes the model a good match with the commonly used phrase extraction heuristics. the model's predictions are properly normalized probabilities. in addition, the model automatically takes into account information provided by phrase overlaps, and does not suffer from reference translation reachability problems. we have implemented an open source translation system sinuhe based on the proposed translation model. our experiments on europarl and gigafren corpora demonstrate that finding the unique map parameters for the model on large scale data is feasible with simple stochastic gradient methods. sinuhe is fast and memory efficient, and the bleu scores obtained by it are only slightly inferior to those of moses.
multi-word expression identification using sentence surface features. much nlp research on multi-word expressions (mwes) focuses on the discovery of new expressions, as opposed to the identification in texts of known expressions. however, mwe identification is not trivial because many expressions allow variation in form and differ in the range of variations they allow. we show that simple rule-based baselines do not perform identification satisfactorily, and present a supervised learning method for identification that uses sentence surface features based on expressions' canonical form. to evaluate the method, we have annotated 3350 sentences from the british national corpus, containing potential uses of 24 verbal mwes. the method achieves an f-score of 94.86%, compared with 80.70% for the leading rule-based baseline. our method is easily applicable to any expression type. experiments in previous research have been limited to the compositional/non-compositional distinction, while we also test on sentences in which the words comprising the mwe appear but not as an expression.
learning linear ordering problems for better translation. we apply machine learning to the linear ordering problem in order to learn sentence-specific reordering models for machine translation. we demonstrate that even when these models are used as a mere preprocessing step for german-english translation, they significantly outperform moses' integrated lexicalized reordering model. our models are trained on automatically aligned bitext. their form is simple but novel. they assess, based on features of the input sentence, how strongly each pair of input word tokens wi, wj would like to reverse their relative order. combining all these pairwise preferences to find the best global reordering is np-hard. however, we present a non-trivial o(n3) algorithm, based on chart parsing, that at least finds the best reordering within a certain exponentially large neighborhood. we show how to iterate this reordering process within a local search algorithm, which we use in training.
latent document re-ranking. the problem of re-ranking initial retrieval results exploring the intrinsic structure of documents is widely researched in information retrieval (ir) and has attracted a considerable amount of time and study. however, one of the drawbacks is that those algorithms treat queries and documents separately. furthermore, most of the approaches are predominantly built upon graph-based methods, which may ignore some hidden information among the retrieval set. this paper proposes a novel document re-ranking method based on latent dirichlet allocation (lda) which exploits the implicit structure of the documents with respect to original queries. rather than relying on graph-based techniques to identify the internal structure, the approach tries to find the latent structure of "topics" or "concepts" in the initial re-trieval set. then we compute the distance between queries and initial retrieval results based on latent semantic information deduced. empirical results demonstrate that the method can comfortably achieve significant improvement over various baseline systems.
graded word sense assignment. word sense disambiguation is typically phrased as the task of labeling a word in context with the best-fitting sense from a sense inventory such as wordnet. while questions have often been raised over the choice of sense inventory, computational linguists have readily accepted the best-fitting sense methodology despite the fact that the case for discrete sense boundaries is widely disputed by lexical semantics researchers. this paper studies graded word sense assignment, based on a recent dataset of graded word sense annotation.
chinese novelty mining. automated mining of novel documents or sentences from chronologically ordered documents or sentences is an open challenge in text mining. in this paper, we describe the preprocessing techniques for detecting novel chinese text and discuss the influence of different part of speech (pos) filtering rules on the detection performance. experimental results on apwsj and trec 2004 novelty track data show that the chinese novelty mining performance is quite different when choosing two dissimilar pos filtering rules. thus, the selection of words to represent chinese text is of vital importance to the success of the chinese novelty mining. moreover, we compare the chinese novelty mining performance with that of english and investigate the impact of preprocessing steps on detecting novel chinese text, which will be very helpful for developing a chinese novelty mining system.
classifying relations for biomedical named entity disambiguation. named entity disambiguation concerns linking a potentially ambiguous mention of named entity in text to an unambiguous identifier in a standard database. one approach to this task is supervised classification. however, the availability of training data is often limited, and the available data sets tend to be imbalanced and, in some cases, heterogeneous. we propose a new method that distinguishes a named entity by finding the informative keywords in its surrounding context, and then trains a model to predict whether each keyword indicates the semantic class of the entity. while maintaining a comparable performance to supervised classification, this method avoids using expensive manually annotated data for each new domain, and thus achieves better portability.
parser adaptation and projection with quasi-synchronous grammar features. we connect two scenarios in structured learning: adapting a parser trained on one corpus to another annotation style, and projecting syntactic annotations from one language to another. we propose quasi-synchronous grammar (qg) features for these structured learning tasks. that is, we score a aligned pair of source and target trees based on local features of the trees and the alignment. our quasi-synchronous model assigns positive probability to any alignment of any trees, in contrast to a synchronous grammar, which would insist on some form of structural parallelism. in monolingual dependency parser adaptation, we achieve high accuracy in translating among multiple annotation styles for the same sentence. on the more difficult problem of cross-lingual parser projection, we learn a dependency parser for a target language by using bilingual text, an english parser, and automatic word alignments. our experiments show that unsupervised qg projection improves on parses trained using only high-precision projected annotations and far outperforms, by more than 35% absolute dependency accuracy, learning an unsupervised parser from raw target-language text alone. when a few target-language parse trees are available, projection gives a boost equivalent to doubling the number of target-language trees.
geo-mining: discovery of road and transport networks using directional patterns. one of the most desired information types when planning a trip to some place is the knowledge of transport, roads and geographical connectedness of prominent sites in this place. while some transport companies or repositories make some of this information accessible, it is not easy to find, and the majority of information about uncommon places can only be found in web free text such as blogs and forums. in this paper we present an algorithmic framework which allows an automated acquisition of map-like information from the web, based on surface patterns like "from x to y". given a set of locations as initial seeds, we retrieve from the web an extended set of locations and produce a map-like network which connects these locations using transport type edges. we evaluate our framework in several settings, producing meaningful and precise connection sets.
gazpacho and summer rash: lexical relationships from temporal patterns of web search queries. in this paper we investigate temporal patterns of web search queries. we carry out several evaluations to analyze the properties of temporal profiles of queries, revealing promising semantic and pragmatic relationships between words. we focus on two applications: query suggestion and query categorization. the former shows a potential for time-series similarity measures to identify specific semantic relatedness between words, which results in state-of-the-art performance in query suggestion while providing complementary information to more traditional distributional similarity measures. the query categorization evaluation suggests that the temporal profile alone is not a strong indicator of broad topical categories.
detecting speculations and their scopes in scientific text. distinguishing speculative statements from factual ones is important for most biomedical text mining applications. we introduce an approach which is based on solving two sub-problems to identify speculative sentence fragments. the first sub-problem is identifying the speculation keywords in the sentences and the second one is resolving their linguistic scopes. we formulate the first sub-problem as a supervised classification task, where we classify the potential keywords as real speculation keywords or not by using a diverse set of linguistic features that represent the contexts of the keywords. after detecting the actual speculation keywords, we use the syntactic structures of the sentences to determine their scopes.
collocation extraction using monolingual word alignment method. statistical bilingual word alignment has been well studied in the context of machine translation. this paper adapts the bilingual word alignment algorithm to monolingual scenario to extract collocations from monolingual corpus. the monolingual corpus is first replicated to generate a parallel corpus, where each sentence pair consists of two identical sentences in the same language. then the monolingual word alignment algorithm is employed to align the potentially collocated words in the monolingual sentences. finally the aligned word pairs are ranked according to refined alignment probabilities and those with higher scores are extracted as collocations. we conducted experiments using chinese and english corpora individually. compared with previous approaches, which use association measures to extract collocations from the co-occurring word pairs within a given window, our method achieves higher precision and recall. according to human evaluation in terms of precision, our method achieves absolute improvements of 27.9% on the chinese corpus and 23.6% on the english corpus, respectively. especially, we can extract collocations with longer spans, achieving a high precision of 69% on the long-span (>6) chinese collocations.
k-best combination of syntactic parsers. in this paper, we propose a linear model-based general framework to combine k-best parse outputs from multiple parsers. the proposed framework leverages on the strengths of previous system combination and re-ranking techniques in parsing by integrating them into a linear model. as a result, it is able to fully utilize both the logarithm of the probability of each k-best parse tree from each individual parser and any additional useful features. for feature weight tuning, we compare the simulated-annealing algorithm and the perceptron algorithm. our experiments are carried out on both the chinese and english penn treebank syntactic parsing task by combining two state-of-the-art parsing models, a head-driven lexicalized model and a latent-annotation-based un-lexicalized model. experimental results show that our f-scores of 85.45 on chinese and 92.62 on english outperform the previously best-reported systems by 1.21 and 0.52, respectively.
using word-sense disambiguation methods to classify web queries by intent. three methods are proposed to classify queries by intent (cqi), e.g., navigational, informational, commercial, etc. following mixed-initiative dialog systems, search engines should distinguish navigational queries where the user is taking the initiative from other queries where there are more opportunities for system initiatives (e.g., suggestions, ads). the query intent problem has a number of useful applications for search engines, affecting how many (if any) advertisements to display, which results to return, and how to arrange the results page. click logs are used as a substitute for annotation. clicks on ads are evidence for commercial intent; other types of clicks are evidence for other intents. we start with a simple na&iuml;ve bayes baseline that works well when there is plenty of training data. when training data is less plentiful, we back off to nearby urls in a click graph, using a method similar to word-sense disambiguation. thus, we can infer that designer trench is commercial because it is close to www.saksfifthavenue.com, which is known to be commercial. the baseline method was designed for precision and the backoff method was designed for recall. both methods are fast and do not require crawling webpages. we recommend a third method, a hybrid of the two, that does no harm when there is plenty of training data, and generalizes better when there isn't, as a strong baseline for the cqi task.
accurate semantic class classifier for coreference resolution. there have been considerable attempts to incorporate semantic knowledge into coreference resolution systems: different knowledge sources such as wordnet and wikipedia have been used to boost the performance. in this paper, we propose new ways to extract wordnet feature. this feature, along with other features such as named entity feature, can be used to build an accurate semantic class (sc) classifier. in addition, we analyze the sc classification errors and propose to use relaxed sc agreement features. the proposed accurate sc classifier and the relaxation of sc agreement features on ace2 coreference evaluation can boost our baseline system by 10.4% and 9.7% using muc score and anaphor accuracy respectively.
cross-cultural analysis of blogs and forums with mixed-collection topic models. this paper presents preliminary results on the detection of cultural differences from people's experiences in various countries from two perspectives: tourists and locals. our approach is to develop probabilistic models that would provide a good framework for such studies. thus, we propose here a new model, cclda, which extends over the latent dirichlet allocation (lda) (blei et al., 2003) and cross-collection mixture (ccmix) (zhai et al., 2004) models on blogs and forums. we also provide a qualitative and quantitative analysis of the model on the cross-cultural data.
accuracy-based scoring for dot: towards direct error minimization for data-oriented translation. in this work we present a novel technique to rescore fragments in the data-oriented translation model based on their contribution to translation accuracy. we describe three new rescoring methods, and present the initial results of a pilot experiment on a small subset of the europarl corpus. this work is a proof-of-concept, and is the first step in directly optimizing translation decisions solely on the hypothesized accuracy of potential translations resulting from those decisions.
the feature subspace method for smt system combination. recently system combination has been shown to be an effective way to improve translation quality over single machine translation systems. in this paper, we present a simple and effective method to systematically derive an ensemble of smt systems from one baseline linear smt model for use in system combination. each system in the resulting ensemble is based on a feature set derived from the features of the baseline model (typically a subset of it). we will discuss the principles to determine the feature sets for derived systems, and present in detail the system combination model used in our work. evaluation is performed on the data sets for nist 2004 and nist 2005 chinese-to-english machine translation tasks. experimental results show that our method can bring significant improvements to baseline systems with state-of-the-art performance.
fully lexicalising ccgbank with hat categories. we introduce an extension to ccg that allows form and function to be represented simultaneously, reducing the proliferation of modifier categories seen in standard ccg analyses. we can then remove the non-combinatory rules ccgbank uses to address this problem, producing a grammar that is fully lexicalised and far less ambiguous. there are intrinsic benefits to full lexicalisation, such as semantic transparency and simpler domain adaptation. the clearest advantage is a 52--88% improvement in parse speeds, which comes with only a small reduction in accuracy.
an empirical study of semi-supervised structured conditional models for dependency parsing. this paper describes an empirical study of high-performance dependency parsers based on a semi-supervised learning approach. we describe an extension of semi-supervised structured conditional models (ss-scms) to the dependency parsing problem, whose framework is originally proposed in (suzuki and isozaki, 2008). moreover, we introduce two extensions related to dependency parsing: the first extension is to combine ss-scms with another semi-supervised approach, described in (koo et al., 2008). the second extension is to apply the approach to second-order parsing models, such as those described in (carreras, 2007), using a two-stage semi-supervised learning approach. we demonstrate the effectiveness of our proposed methods on dependency parsing experiments using two widely used test collections: the penn treebank for english, and the prague dependency tree-bank for czech. our best results on test data in the above datasets achieve 93.79% parent-prediction accuracy for english, and 88.05% for czech.
quantifier scope disambiguation using extracted pragmatic knowledge: preliminary results. it is well known that pragmatic knowledge is useful and necessary in many difficult language processing tasks, but because this knowledge is difficult to acquire and process automatically, it is rarely used. we present an open information extraction technique for automatically extracting a particular kind of pragmatic knowledge from text, and we show how to integrate the knowledge into a markov logic network model for quantifier scope disambiguation. our model improves quantifier scope judgments in experiments.
multi-document summarisation using generic relation extraction. experiments are reported that investigate the effect of various source document representations on the accuracy of the sentence extraction phase of a multi-document summarisation task. a novel representation is introduced based on generic relation extraction (gre), which aims to build systems for relation identification and characterisation that can be transferred across domains and tasks without modification of model parameters. results demonstrate performance that is significantly higher than a non-trivial baseline that uses tf*idf-weighted words and at least as good as a comparable but less general approach from the literature. analysis shows that the representations compared are complementary, suggesting that extraction performance could be further improved through system combination.
improving web search relevance with semantic features. most existing information retrieval (ir) systems do not take much advantage of natural language processing (nlp) techniques due to the complexity and limited observed effectiveness of applying nlp to ir. in this paper, we demonstrate that substantial gains can be obtained over a strong baseline using nlp techniques, if properly handled. we propose a framework for deriving semantic text matching features from named entities identified in web queries; we then utilize these features in a supervised machine-learned ranking approach, applying a set of emerging machine learning techniques. our approach is especially useful for queries that contain multiple types of concepts. comparing to a major commercial web search engine, we observe a substantial 4% dcg5 gain over the affected queries.
discriminative corpus weight estimation for machine translation. current statistical machine translation (smt) systems are trained on sentence-aligned and word-aligned parallel text collected from various sources. translation model parameters are estimated from the word alignments, and the quality of the translations on a given test set depends on the parameter estimates. there are at least two factors affecting the parameter estimation: domain match and training data quality. this paper describes a novel approach for automatically detecting and down-weighing certain parts of the training corpus by assigning a weight to each sentence in the training bitext so as to optimize a discriminative objective function on a designated tuning set. this way, the proposed method can limit the negative effects of low quality training data, and can adapt the translation model to the domain of interest. it is shown that such discriminative corpus weights can provide significant improvements in arabic-english translation on various conditions, using a state-of-the-art smt system.
improving dependency parsing with subtrees from auto-parsed data. this paper presents a simple and effective approach to improve dependency parsing by using subtrees from auto-parsed data. first, we use a baseline parser to parse large-scale unannotated data. then we extract subtrees from dependency parse trees in the auto-parsed data. finally, we construct new subtree-based features for parsing algorithms. to demonstrate the effectiveness of our proposed approach, we present the experimental results on the english penn treebank and the chinese penn treebank. these results show that our approach significantly outperforms baseline systems. and, it achieves the best accuracy for the chinese data and an accuracy which is competitive with the best known systems for the english data.
refining grammars for parsing with hierarchical semantic knowledge. this paper proposes a novel method to refine the grammars in parsing by utilizing semantic knowledge from hownet. based on the hierarchical state-split approach, which can refine grammars automatically in a data-driven manner, this study introduces semantic knowledge into the splitting process at two steps. firstly, each part-of-speech node will be annotated with a semantic tag of its terminal word. these new tags generated in this step are semantic-related, which can provide a good start for splitting. secondly, a knowledge-based criterion is used to supervise the hierarchical splitting of these semantic-related tags, which can alleviate overfitting. the experiments are carried out on both chinese and english penn treebank show that the refined grammars with semantic knowledge can improve parsing performance significantly. especially with respect to chinese, our parser achieves an f1 score of 87.5%, which is the best published result we are aware of.
enhancement of lexical concepts using cross-lingual web mining. sets of lexical items sharing a significant aspect of their meaning (concepts) are fundamental in linguistics and nlp. manual concept compilation is labor intensive, error prone and subjective. we present a web-based concept extension algorithm. given a set of terms specifying a concept in some language, we translate them to a wide range of intermediate languages, disambiguate the translations using web counts, and discover additional concept terms using symmetric patterns. we then translate the discovered terms back into the original language, score them, and extend the original concept by adding back-translations having high scores. we evaluate our method in 3 source languages and 45 intermediate languages, using both human judgments and wordnet. in all cases, our cross-lingual algorithm significantly improves high quality concept extension.
first- and second-order expectation semirings with applications to minimum-risk training on translation forests. many statistical translation models can be regarded as weighted logical deduction. under this paradigm, we use weights from the expectation semiring (eisner, 2002), to compute first-order statistics (e.g., the expected hypothesis length or feature counts) over packed forests of translations (lattices or hypergraphs). we then introduce a novel second-order expectation semiring, which computes second-order statistics (e.g., the variance of the hypothesis length or the gradient of entropy). this second-order semiring is essential for many interesting training paradigms such as minimum risk, deterministic annealing, active learning, and semi-supervised learning, where gradient descent optimization requires computing the gradient of entropy or risk. we use these semirings in an open-source machine translation toolkit, joshua, enabling minimum-risk training for a benefit of up to 1.0 bleu point.
construction of a blog emotion corpus for chinese emotional expression analysis. there is plenty of evidence that emotion analysis has many valuable applications. in this study a blog emotion corpus is constructed for chinese emotional expression analysis. this corpus contains manual annotation of eight emotional categories (expect, joy, love, surprise, anxiety, sorrow, angry and hate), emotion intensity, emotion holder/target, emotional word/phrase, degree word, negative word, conjunction, rhetoric, punctuation and other linguistic expressions that indicate emotion. annotation agreement analyses for emotion classes and emotional words and phrases are described. then, using this corpus, we explore emotion expressions in chinese and present the analyses on them.
joint optimization for machine translation system combination. system combination has emerged as a powerful method for machine translation (mt). this paper pursues a joint optimization strategy for combining outputs from multiple mt systems, where word alignment, ordering, and lexical selection decisions are made jointly according to a set of feature functions combined in a single log-linear model. the decoding algorithm is described in detail and a set of new features that support this joint decoding approach is proposed. the approach is evaluated in comparison to state-of-the-art confusion-network-based system combination methods using equivalent features and shown to outperform them significantly.
perceptron reranking for ccg realization. this paper shows that discriminative reranking with an averaged perceptron model yields substantial improvements in realization quality with ccg. the paper confirms the utility of including language model log probabilities as features in the model, which prior work on discriminative training with log linear models for hpsg realization had called into question. the perceptron model allows the combination of multiple n-gram models to be optimized and then augmented with both syntactic features and discriminative n-gram features. the full model yields a state-of-the-art bleu score of 0.8506 on section 23 of the ccgbank, to our knowledge the best score reported to date using a reversible, corpus-engineered grammar.
improving verb clustering with automatically acquired selectional preferences. in previous research in automatic verb classification, syntactic features have proved the most useful features, although manual classifications rely heavily on semantic features. we show, in contrast with previous work, that considerable additional improvement can be obtained by using semantic features in automatic classification: verb selectional preferences acquired from corpus data using a fully unsupervised method. we report these promising results using a new framework for verb clustering which incorporates a recent subcategorization acquisition system, rich syntactic-semantic feature sets, and a variation of spectral clustering which performs particularly well in high dimensional feature space.
integrating sentence- and word-level error identification for disfluency correction. while speaking spontaneously, speakers often make errors such as self-correction or false starts which interfere with the successful application of natural language processing techniques like summarization and machine translation to this data. there is active work on reconstructing this errorful data into a clean and fluent transcript by identifying and removing these simple errors. previous research has approximated the potential benefit of conducting word-level reconstruction of simple errors only on those sentences known to have errors. in this work, we explore new approaches for automatically identifying speaker construction errors on the utterance level, and quantify the impact that this initial step has on word- and sentence-level reconstruction accuracy.
matching reviews to objects using a language model. we develop a general method to match unstructured text reviews to a structured list of objects. for this, we propose a language model for generating reviews that incorporates a description of objects and a generic review language model. this mixture model gives us a principled method to find, given a review, the object most likely to be the topic of the review. extensive experiments and analysis on reviews from yelp show that our language model-based method vastly outperforms traditional tf-idf-based methods.
better synchronous binarization for machine translation. binarization of synchronous context free grammars (scfg) is essential for achieving polynomial time complexity of decoding for scfg parsing based machine translation systems. in this paper, we first investigate the excess edge competition issue caused by a left-heavy binary scfg derived with the method of zhang et al. (2006). then we propose a new binarization method to mitigate the problem by exploring other alternative equivalent binary scfgs. we present an algorithm that iteratively improves the resulting binary scfg, and empirically show that our method can improve a string-to-tree statistical machine translations system based on the synchronous binarization method in zhang et al. (2006) on the nist machine translation evaluation tasks.
bayesian learning of phrasal tree-to-string templates. we examine the problem of overcoming noisy word-level alignments when learning tree-to-string translation rules. our approach introduces new rules, and re-estimates rule probabilities using em. the major obstacles to this approach are the very reasons that word-alignments are used for rule extraction: the huge space of possible rules, as well as controlling overfitting. by carefully controlling which portions of the original alignments are reanalyzed, and by using bayesian inference during re-analysis, we show significant improvement over the baseline rules extracted from word-level alignments.
reverse engineering of tree kernel feature spaces. we present a framework to extract the most important features (tree fragments) from a tree kernel (tk) space according to their importance in the target kernel-based machine, e.g. support vector machines (svms). in particular, our mining algorithm selects the most relevant features based on svm estimated weights and uses this information to automatically infer an explicit representation of the input data. the explicit features (a) improve our knowledge on the target problem domain and (b) make large-scale learning practical, improving training and test time, while yielding accuracy in line with traditional tk classifiers. experiments on semantic role labeling and question classification illustrate the above claims.
chinese semantic role labeling with shallow parsing. most existing systems for chinese semantic role labeling (srl) make use of full syntactic parses. in this paper, we evaluate srl methods that take partial parses as inputs. we first extend the study on chinese shallow parsing presented in (chen et al., 2006) by raising a set of additional features. on the basis of our shallow parser, we implement srl systems which cast srl as the classification of syntactic chunks with iob2 representation for semantic roles (i.e. semantic chunks). two labeling strategies are presented: 1) directly tagging semantic chunks in one-stage, and 2) identifying argument boundaries as a chunking task and labeling their semantic types as a classification task. lor both methods, we present encouraging results, achieving significant improvements over the best reported srl performance in the literature. additionally, we put forward a rule-based algorithm to automatically acquire chinese verb formation, which is empirically shown to enhance srl.
fast, cheap, and creative: evaluating translation quality using amazon's mechanical turk. manual evaluation of translation quality is generally thought to be excessively time consuming and expensive. we explore a fast and inexpensive way of doing it using amazon's mechanical turk to pay small sums to a large number of non-expert annotators. for $10 we redundantly recreate judgments from a wmt08 translation task. we find that when combined non-expert judgments have a high-level of agreement with the existing gold-standard judgments of machine translation quality, and correlate more strongly with expert judgments than bleu does. we go on to show that mechanical turk can be used to calculate human-mediated translation edit rate (hter), to conduct reading comprehension experiments with machine translation, and to create high quality reference translations.
fast translation rule matching for syntax-based statistical machine translation. in a linguistically-motivated syntax-based translation system, the entire translation process is normally carried out in two steps, translation rule matching and target sentence decoding using the matched rules. both steps are very time-consuming due to the tremendous number of translation rules, the exhaustive search in translation rule matching and the complex nature of the translation task itself. in this paper, we propose a hyper-tree-based fast algorithm for translation rule matching. experimental results on the nist mt-2003 chinese-english translation task show that our algorithm is at least 19 times faster in rule matching and is able to help to save 57% of overall translation time over previous methods when using large fragment translation rules.
generating high-coverage semantic orientation lexicons from overtly marked words and a thesaurus. sentiment analysis often relies on a semantic orientation lexicon of positive and negative words. a number of approaches have been proposed for creating such lexicons, but they tend to be computationally expensive, and usually rely on significant manual annotation and large corpora. most of these methods use wordnet. in contrast, we propose a simple approach to generate a high-coverage semantic orientation lexicon, which includes both individual words and multi-word expressions, using only a roget-like thesaurus and a handful of affixes. further, the lexicon has properties that support the polyanna hypothesis. using the general inquirer as gold standard, we show that our lexicon has 14 percentage points more correct entries than the leading wordnet-based high-coverage lexicon (sentiwordnet). in an extrinsic evaluation, we obtain significantly higher performance in determining phrase polarity using our thesaurus-based lexicon than with any other. additionally, we explore the use of visualization techniques to gain insight into the our algorithm beyond the evaluations mentioned above.
a probabilistic model for associative anaphora resolution. this paper proposes a probabilistic model for associative anaphora resolution in japanese. associative anaphora is a type of bridging anaphora, in which the anaphor and its antecedent are not coreferent. our model regards associative anaphora as a kind of zero anaphora and resolves it in the same manner as zero anaphora resolution using automatically acquired lexical knowledge. experimental results show that our model resolves associative anaphora with good performance and the performance is improved by resolving it simultaneously with zero anaphora.
cube pruning as heuristic search. cube pruning is a fast inexact method for generating the items of a beam decoder. in this paper, we show that cube pruning is essentially equivalent to a* search on a specific search space with specific heuristics. we use this insight to develop faster and exact variants of cube pruning.
unsupervised tokenization for machine translation. training a statistical machine translation starts with tokenizing a parallel corpus. some languages such as chinese do not incorporate spacing in their writing system, which creates a challenge for tokenization. moreover, morphologically rich languages such as korean present an even bigger challenge, since optimal token boundaries for machine translation in these languages are often unclear. both rule-based solutions and statistical solutions are currently used. in this paper, we present unsupervised methods to solve tokenization problem. our methods incorporate information available from parallel corpus to determine a good tokenization for machine translation.
graphical models over multiple strings. we study graphical modeling in the case of string-valued random variables. whereas a weighted finite-state transducer can model the probabilistic relationship between two strings, we are interested in building up joint models of three or more strings. this is needed for inflectional paradigms in morphology, cognate modeling or language reconstruction, and multiple-string alignment. we propose a markov random field in which each factor (potential function) is a weighted finite-state machine, typically a transducer that evaluates the relationship between just two of the strings. the full joint distribution is then a product of these factors. though decoding is actually undecidable in general, we can still do efficient joint inference using approximate belief propagation; the necessary computations and messages are all finite-state. we demonstrate the methods by jointly predicting morphological forms.
a rich feature vector for protein-protein interaction extraction from multiple corpora. because of the importance of protein-protein interaction (ppi) extraction from text, many corpora have been proposed with slightly differing definitions of proteins and ppi. since no single corpus is large enough to saturate a machine learning system, it is necessary to learn from multiple different corpora. in this paper, we propose a solution to this challenge. we designed a rich feature vector, and we applied a support vector machine modified for corpus weighting (svm-cw) to complete the task of multiple corpora ppi extraction. the rich feature vector, made from multiple useful kernels, is used to express the important information for ppi extraction, and the system with our feature vector was shown to be both faster and more accurate than the original kernel-based system, even when using just a single corpus. svm-cw learns from one corpus, while using other corpora for support. svm-cw is simple, but it is more effective than other methods that have been successfully applied to other nlp tasks earlier. with the feature vector and svm-cw, our system achieved the best performance among all state-of-the-art ppi extraction systems reported so far.
sentiment analysis of conditional sentences. this paper studies sentiment analysis of conditional sentences. the aim is to determine whether opinions expressed on different topics in a conditional sentence are positive, negative or neutral. conditional sentences are one of the commonly used language constructs in text. in a typical document, there are around 8% of such sentences. due to the condition clause, sentiments expressed in a conditional sentence can be hard to determine. for example, in the sentence, if your nokia phone is not good, buy this great samsung phone, the author is positive about "samsung phone" but does not express an opinion on "nokia phone" (although the owner of the "nokia phone" may be negative about it). however, if the sentence does not have "if', the first clause is clearly negative. although "if' commonly signifies a conditional sentence, there are many other words and constructs that can express conditions. this paper first presents a linguistic analysis of such sentences, and then builds some supervised learning models to determine if sentiments expressed on different topics in a conditional sentence are positive, negative or neutral. experimental results on conditional sentences from 5 diverse domains are given to demonstrate the effectiveness of the proposed approach.
a comparison of model free versus model intensive approaches to sentence compression. this work introduces a model free approach to sentence compression, which grew out of ideas from nomoto (2008), and examines how it compares to a state-of-art model intensive approach known as tree-to-tree transducer, or t3 (cohn and lapata, 2008). it is found that a model free approach significantly outperforms t3 on the particular data we created from the internet. we also discuss what might have caused t3's poor performance.
human-competitive tagging using automatic keyphrase extraction. this paper connects two research areas: automatic tagging on the web and statistical keyphrase extraction. first, we analyze the quality of tags in a collaboratively created folksonomy using traditional evaluation techniques. next, we demonstrate how documents can be tagged automatically with a state-of-the-art keyphrase extraction algorithm, and further improve performance in this new domain using a new algorithm, "maui", that utilizes semantic information extracted from wikipedia. maui outperforms existing approaches and extracts tags that are competitive with those assigned by the best performing human taggers.
toward completeness in concept extraction and classification. many algorithms extract terms from text together with some kind of taxonomic classification (is-a) link. however, the general approaches used today, and specifically the methods of evaluating results, exhibit serious shortcomings. harvesting without focusing on a specific conceptual area may deliver large numbers of terms, but they are scattered over an immense concept space, making recall judgments impossible. regarding precision, simply judging the correctness of terms and their individual classification links may provide high scores, but this doesn't help with the eventual assembly of terms into a single coherent taxonomy. furthermore, since there is no correct and complete gold standard to measure against, most work invents some ad hoc evaluation measure. we present an algorithm that is more precise and complete than previous ones for identifying from web text just those concepts 'below' a given seed term. comparing the results to wordnet, we find that the algorithm misses terms, but also that it learns many new terms not in wordnet, and that it classifies them in ways acceptable to humans but different from wordnet.
joint learning of preposition senses and semantic roles of prepositional phrases. the sense of a preposition is related to the semantics of its dominating prepositional phrase. knowing the sense of a preposition could help to correctly classify the semantic role of the dominating prepositional phrase and vice versa. in this paper, we propose a joint probabilistic model for word sense disambiguation of prepositions and semantic role labeling of prepositional phrases. our experiments on the propbank corpus show that jointly learning the word sense and the semantic role leads to an improvement over state-of-the-art individual classifier models on the two tasks.
natural language generation with tree conditional random fields. this paper presents an effective method for generating natural language sentences from their underlying meaning representations. the method is built on top of a hybrid tree representation that jointly encodes both the meaning representation as well as the natural language in a tree structure. by using a tree conditional random field on top of the hybrid tree representation, we are able to explicitly model phrase-level dependencies amongst neighboring natural language phrases and meaning representation components in a simple and natural way. we show that the additional dependencies captured by the tree conditional random field allows it to perform better than directly inverting a previously developed hybrid tree semantic parser. furthermore, we demonstrate that the model performs better than a previous state-of-the-art natural language generation model. experiments are performed on two benchmark corpora with standard automatic evaluation metrics.
nested named entity recognition. many named entities contain other named entities inside them. despite this fact, the field of named entity recognition has almost entirely ignored nested named entity recognition, but due to technological, rather than ideological reasons. in this paper, we present a new technique for recognizing nested named entities, by using a discriminative constituency parser. to train the model, we transform each sentence into a tree, with constituents for each named entity (and no other syntactic structure). we present results on both newspaper and biomedical corpora which contain nested named entities. in three out of four sets of experiments, our model outperforms a standard semi-crf on the more traditional top-level entities. at the same time, we improve the overall f-score by up to 30% over the flat model, which is unable to recover any nested entities.
a structural support vector method for extracting contexts and answers of questions from online forums. this paper addresses the issue of extracting contexts and answers of questions from post discussion of online forums. we propose a novel and unified model by customizing the structural support vector machine method. our customization has several attractive properties: (1) it gives a comprehensive graphical representation of thread discussion. (2) it designs special inference algorithms instead of general-purpose ones. (3) it can be readily extended to different task preferences by varying loss functions. experimental results on a real data set show that our methods are both promising and flexible.
bilingually-constrained (monolingual) shift-reduce parsing. jointly parsing two languages has been shown to improve accuracies on either or both sides. however, its search space is much bigger than the monolingual case, forcing existing approaches to employ complicated modeling and crude approximations. here we propose a much simpler alternative, bilingually-constrained monolingual parsing, where a source-language parser learns to exploit reorderings as additional observation, but not bothering to build the target-side tree as well. we show specifically how to enhance a shift-reduce dependency parser with alignment features to resolve shift-reduce conflicts. experiments on the bilingual portion of chinese treebank show that, with just 3 bilingual features, we can improve parsing accuracies by 0.6% (absolute) for both english and chinese over a state-of-the-art baseline, with negligible (~6%) efficiency overhead, thus much faster than biparsing.
lattice-based system combination for statistical machine translation. current system combination methods usually use confusion networks to find consensus translations among different systems. requiring one-to-one mappings between the words in candidate translations, confusion networks have difficulty in handling more general situations in which several words are connected to another several words. instead, we propose a lattice-based system combination model that allows for such phrase alignments and uses lattices to encode all candidate translations. experiments show that our approach achieves significant improvements over the state-of-the-art baseline system on chinese-to-english translation test sets.
classifier combination for contextual idiom detection without labelled data. we propose a novel unsupervised approach for distinguishing literal and non-literal use of idiomatic expressions. our model combines an unsupervised and a supervised classifier. the former bases its decision on the cohesive structure of the context and labels training data for the latter, which can then take a larger feature space into account. we show that a combination of both classifiers leads to significant improvements over using the unsupervised classifier alone.
topic-wise, sentiment-wise, or otherwise? identifying the hidden dimension for unsupervised text classification. while traditional work on text clustering has largely focused on grouping documents by topic, it is conceivable that a user may want to cluster documents along other dimensions, such as the author's mood, gender, age, or sentiment. without knowing the user's intention, a clustering algorithm will only group documents along the most prominent dimension, which may not be the one the user desires. to address this problem, we propose a novel way of incorporating user feedback into a clustering algorithm, which allows a user to easily specify the dimension along which she wants the data points to be clustered via inspecting only a small number of words. this distinguishes our method from existing ones, which typically require a large amount of effort on the part of humans in the form of document annotation or interactive construction of the feature space. we demonstrate the viability of our method on several challenging sentiment datasets.
adapting a polarity lexicon using integer linear programming for domain-specific sentiment classification. polarity lexicons have been a valuable resource for sentiment analysis and opinion mining. there are a number of such lexical resources available, but it is often suboptimal to use them as is, because general purpose lexical resources do not reflect domain-specific lexical usage. in this paper, we propose a novel method based on integer linear programming that can adapt an existing lexicon into a new one to reflect the characteristics of the data more directly. in particular, our method collectively considers the relations among words and opinion expressions to derive the most likely polarity of each lexical item (positive, neutral, negative, or negator) for the given domain. experimental results show that our lexicon adaptation technique improves the performance of fine-grained polarity classification.
eeg responds to conceptual stimuli and corpus semantics. mitchell et al. (2008) demonstrated that corpus-extracted models of semantic knowledge can predict neural activation patterns recorded using fmri. this could be a very powerful technique for evaluating conceptual models extracted from corpora; however, fmri is expensive and imposes strong constraints on data collection. following on experiments that demonstrated that eeg activation patterns encode enough information to discriminate broad conceptual categories, we show that corpus-based semantic representations can predict eeg activation patterns with significant accuracy, and we evaluate the relative performance of different corpus-models on this task.
descriptive and empirical approaches to capturing underlying dependencies among parsing errors. in this paper, we provide descriptive and empirical approaches to effectively extracting underlying dependencies among parsing errors. in the descriptive approach, we define some combinations of error patterns and extract them from given errors. in the empirical approach, on the other hand, we re-parse a sentence with a target error corrected and observe errors corrected together. experiments on an hpsg parser show that each of these approaches can clarify the dependencies among individual errors from each point of view. moreover, the comparison between the results of the two approaches shows that combining these approaches can achieve a more detailed error analysis.
using the web for language independent spellchecking and autocorrection. we have designed, implemented and evaluated an end-to-end system spellchecking and autocorrection system that does not require any manually annotated training data. the world wide web is used as a large noisy corpus from which we infer knowledge about misspellings and word usage. this is used to build an error model and an n-gram language model. a small secondary set of news texts with artificially inserted misspellings are used to tune confidence classifiers. because no manual annotation is required, our system can easily be instantiated for new languages. when evaluated on human typed data with real misspellings in english and german, our web-based systems outperform baselines which use candidate corrections based on hand-curated dictionaries. our system achieves 3.8% total error rate in english. we show similar improvements in preliminary results on artificial data for russian and arabic.
extending statistical machine translation with discriminative and trigger-based lexicon models. in this work, we propose two extensions of standard word lexicons in statistical machine translation: a discriminative word lexicon that uses sentence-level source information to predict the target words and a trigger-based lexicon model that extends ibm model 1 with a second trigger, allowing for a more fine-grained lexical choice of target words. the models capture dependencies that go beyond the scope of conventional smt models such as phrase-and language models. we show that the models improve translation quality by 1% in bleu over a competitive baseline on a large-scale task.
entity extraction via ensemble semantics. combining information extraction systems yields significantly higher quality resources than each system in isolation. in this paper, we generalize such a mixing of sources and features in a framework called ensemble semantics. we show very large gains in entity extraction by combining state-of-the-art distributional and pattern-based systems with a large set of features from a webcrawl, query logs, and wikipedia. experimental results on a web-scale extraction of actors, athletes and musicians show significantly higher mean average precision scores (29% gain) compared with the current state of the art.
a study on the semantic relatedness of query and document terms in information retrieval. the use of lexical semantic knowledge in information retrieval has been a field of active study for a long time. collaborative knowledge bases like wikipedia and wiktionary, which have been applied in computational methods only recently, offer new possibilities to enhance information retrieval. in order to find the most beneficial way to employ these resources, we analyze the lexical semantic relations that hold among query and document terms and compare how these relations are represented by a measure for semantic relatedness. we explore the potential of different indicators of document relevance that are based on semantic relatedness and compare the characteristics and performance of the knowledge bases wikipedia, wiktionary and wordnet.
using morphological and syntactic structures for chinese opinion analysis. this paper employs morphological structures and relations between sentence segments for opinion analysis on words and sentences. chinese words are classified into eight morphological types by two proposed classifiers, crf classifier and svm classifier. experiments show that the injection of morphological information improves the performance of the word polarity detection. to utilize syntactic structures, we annotate structural trios to represent relations between sentence segments. experiments show that considering structural trios is useful for sentence opinion analysis. the best f-score achieves 0.77 for opinion word extraction, 0.62 for opinion word polarity detection, 0.80 for opinion sentence extraction, and 0.54 for opinion sentence polarity detection.
a joint language model with fine-grain syntactic tags. we present a scalable joint language model designed to utilize fine-grain syntactic tags. we discuss challenges such a design faces and describe our solutions that scale well to large tagsets and corpora. we advocate the use of relatively simple tags that do not require deep linguistic knowledge of the language but provide more structural information than pos tags and can be derived from automatically generated parse trees - a combination of properties that allows easy adoption of this model for new languages. we propose two fine-grain tagsets and evaluate our model using these tags, as well as pos tags and superarv tags in a speech recognition task and discuss future directions.
employing the centering theory in pronoun resolution from the semantic perspective. in this paper, we employ the centering theory in pronoun resolution from the semantic perspective. first, diverse semantic role features with regard to different predicates in a sentence are explored. moreover, given a pronominal anaphor, its relative ranking among all the pronouns in a sentence, according to relevant semantic role information and its surface position, is incorporated. in particular, the use of both the semantic role features and the relative pronominal ranking feature in pronoun resolution is guided by extending the centering theory from the grammatical level to the semantic level in tracking the local discourse focus. finally, detailed pronominal subcategory features are incorporated to enhance the discriminative power of both the semantic role features and the relative pronominal ranking feature. experimental results on the ace 2003 corpus show that the centering-motivated features contribute much to pronoun resolution.
a relational model of semantic similarity between words using automatically extracted lexical pattern clusters from the web. semantic similarity is a central concept that extends across numerous fields such as artificial intelligence, natural language processing, cognitive science and psychology. accurate measurement of semantic similarity between words is essential for various tasks such as, document clustering, information retrieval, and synonym extraction. we propose a novel model of semantic similarity using the semantic relations that exist among words. given two words, first, we represent the semantic relations that hold between those words using automatically extracted lexical pattern clusters. next, the semantic similarity between the two words is computed using a mahalanobis distance measure. we compare the proposed similarity measure against previously proposed semantic similarity measures on miller-charles benchmark dataset and wordsimilarity-353 collection. the proposed method outperforms all existing web-based semantic similarity measures, achieving a pearson correlation coefficient of 0.867 on the millet-charles dataset.
feature-rich translation by quasi-synchronous lattice parsing. we present a machine translation framework that can incorporate arbitrary features of both input and output sentences. the core of the approach is a novel decoder based on lattice parsing with quasi-synchronous grammar (smith and eisner, 2006), a syntactic formalism that does not require source and target trees to be isomorphic. using generic approximate dynamic programming techniques, this decoder can handle "non-local" features. similar approximate inference techniques support efficient parameter estimation with hidden variables. we use the decoder to conduct controlled experiments on a german-to-english translation task, to compare lexical phrase, syntax, and combined models, and to measure effects of various restrictions on non-isomorphism.
real-time decision detection in multi-party dialogue. we describe a process for automatically detecting decision-making sub-dialogues in multi-party, human-human meetings in real-time. our basic approach to decision detection involves distinguishing between different utterance types based on the roles that they play in the formulation of a decision. in this paper, we describe how this approach can be implemented in real-time, and show that the resulting system's performance compares well with other detectors, including an off-line version.
an alternative to head-driven approaches for parsing a (relatively) free word-order language. applying statistical parsers developed for english to languages with freer word-order has turned out to be harder than expected. this paper investigates the adequacy of different statistical parsing models for dealing with a (relatively) free word-order language. we show that the recently proposed relational-realizational (rr) model consistently outperforms state-of-the-art head-driven (hd) models on the hebrew treebank. our analysis reveals a weakness of hd models: their intrinsic focus on configurational information. we conclude that the form-function separation ingrained in rr models makes them better suited for parsing nonconfigurational phenomena.
empirical exploitation of click data for task specific ranking. there have been increasing needs for task specific rankings in web search such as rankings for specific query segments like long queries, time-sensitive queries, navigational queries, etc; or rankings for specific domains/contents like answers, blogs, news, etc. in the spirit of "divide-and-conquer", task specific ranking may have potential advantages over generic ranking since different tasks have task-specific features, data distributions, as well as feature-grade correlations. a critical problem for the task-specific ranking is training data insufficiency, which may be solved by using the data extracted from click log. this paper empirically studies how to appropriately exploit click data to improve rank function learning in task-specific ranking. the main contributions are 1) the exploration on the utilities of two promising approaches for click pair extraction; 2) the analysis of the role played by the noise information which inevitably appears in click data extraction; 3) the appropriate strategy for combining training data and click data; 4) the comparison of click data which are consistent and inconsistent with baseline function.
recognizing implicit discourse relations in the penn discourse treebank. we present an implicit discourse relation classifier in the penn discourse treebank (pdtb). our classifier considers the context of the two arguments, word pair information, as well as the arguments' internal constituent and dependency parses. our results on the pdtb yields a significant 14.1% improvement over the baseline. in our error analysis, we discuss four challenges in recognizing implicit relations in the pdtb.
supervised and unsupervised methods in employing discourse relations for improving opinion polarity classification. this work investigates design choices in modeling a discourse scheme for improving opinion polarity classification. for this, two diverse global inference paradigms are used: a supervised collective classification framework and an unsupervised optimization framework. both approaches perform substantially better than baseline approaches, establishing the efficacy of the methods and the underlying discourse scheme. we also present quantitative and qualitative analyses showing how the improvements are achieved.
polylingual topic models. topic models are a useful tool for analyzing large text collections, but have previously been applied in only monolingual, or at most bilingual, contexts. meanwhile, massive collections of interlinked documents in dozens of languages, such as wikipedia, are now widely available, calling for tools that can characterize content in many languages. we introduce a polylingual topic model that discovers topics aligned across multiple languages. we explore the model's characteristics using two large corpora, each with over ten different languages, and demonstrate its usefulness in supporting machine translation and tracking topic trends across languages.
semi-supervised learning for semantic relation classification using stratified sampling strategy. this paper presents a new approach to selecting the initial seed set using stratified sampling strategy in bootstrapping-based semi-supervised learning for semantic relation classification. first, the training data is partitioned into several strata according to relation types/subtypes, then relation instances are randomly sampled from each stratum to form the initial seed set. we also investigate different augmentation strategies in iteratively adding reliable instances to the labeled set, and find that the bootstrapping procedure may stop at a reasonable point to significantly decrease the training time without degrading too much in performance. experiments on the ace rdc 2003 and 2004 corpora show the stratified sampling strategy contributes more than the bootstrapping procedure itself. this suggests that a proper sampling strategy is critical in semi-supervised learning.
improved statistical machine translation using monolingually-derived paraphrases. untranslated words still constitute a major problem for statistical machine translation (smt), and current smt systems are limited by the quantity of parallel training texts. augmenting the training data with paraphrases generated by pivoting through other languages alleviates this problem, especially for the so-called "low density" languages. but pivoting requires additional parallel texts. we address this problem by deriving paraphrases monolingually, using distributional semantic similarity measures, thus providing access to larger training resources, such as comparable and unrelated monolingual corpora. we present what is to our knowledge the first successful integration of a collocational approach to untranslated words with an end-to-end, state of the art smt system demonstrating significant translation improvements in a low-resource setting.
automatically evaluating content selection in summarization without human models. we present a fully automatic method for content selection evaluation in summarization that does not require the creation of human model summaries. our work capitalizes on the assumption that the distribution of words in the input and an informative summary of that input should be similar to each other. results on a large scale evaluation from the text analysis conference show that input-summary comparisons are very effective for the evaluation of content selection. our automatic methods rank participating systems similarly to manual model-based pyramid evaluation and to manual human judgments of responsiveness. the best feature, jensen-shannon divergence, leads to a correlation as high as 0.88 with manual pyramid and 0.73 with responsiveness evaluations.
projecting parameters for multilingual word sense disambiguation. we report in this paper a way of doing word sense disambiguation (wsd) that has its origin in multilingual mt and that is cognizant of the fact that parallel corpora, wordnets and sense annotated corpora are scarce resources. with respect to these resources, languages show different levels of readiness; however a more resource fortunate language can help a less resource fortunate language. our wsd method can be applied to a language even when no sense tagged corpora for that language is available. this is achieved by projecting wordnet and corpus parameters from another language to the language in question. the approach is centered around a novel synset based multilingual dictionary and the empirical observation that within a domain the distribution of senses remains more or less invariant across languages. the effectiveness of our approach is verified by doing parameter projection and then running two different wsd algorithms. the accuracy values of approximately 75% (f1-score) for three languages in two different domains establish the fact that within a domain it is possible to circumvent the problem of scarcity of resources by projecting parameters like sense distributions, corpus-co-occurrences, conceptual distance, etc. from one language to another.
web-scale distributional similarity and entity set expansion. computing the pairwise semantic similarity between all words on the web is a computationally challenging task. parallelization and optimizations are necessary. we propose a highly scalable implementation based on distributional similarity, implemented in the mapreduce framework and deployed over a 200 billion word crawl of the web. the pairwise similarity between 500 million terms is computed in 50 hours using 200 quad-core nodes. we apply the learned similarity matrix to the task of automatic set expansion and present a large empirical study to quantify the effect on expansion performance of corpus size, corpus quality, seed composition and seed size. we make public an experimental testbed for set expansion analysis that includes a large collection of diverse entity sets extracted from wikipedia.
segmenting email message text into zones. in the early days of email, widely-used conventions for indicating quoted reply content and email signatures made it easy to segment email messages into their functional parts. today, the explosion of different email formats and styles, coupled with the ad hoc ways in which people vary the structure and layout of their messages, means that simple techniques for identifying quoted replies that used to yield 95% accuracy now find less than 10% of such content. in this paper, we describe zebra, an svm-based system for segmenting the body text of email messages into nine zone types based on graphic, orthographic and lexical cues. zebra performs this task with an accuracy of 87.01%; when the number of zones is abstracted to two or three zone classes, this increases to 93.60% and 91.53% respectively.
semi-supervised speech act recognition in emails and forums. in this paper, we present a semi-supervised method for automatic speech act recognition in email and forums. the major challenge of this task is due to lack of labeled data in these two genres. our method leverages labeled data in the switchboard-damsl and the meeting recorder dialog act database and applies simple domain adaptation techniques over a large amount of unlabeled email and forum data to address this problem. our method uses automatically extracted features such as phrases and dependency trees, called subtree features, for semi-supervised learning. empirical results demonstrate that our model is effective in email and forum speech act recognition.
a syntactified direct translation model with linear-time decoding. recent syntactic extensions of statistical translation models work with a synchronous context-free or tree-substitution grammar extracted from an automatically parsed parallel corpus. the decoders accompanying these extensions typically exceed quadratic time complexity. this paper extends the direct translation model 2 (dtm2) with syntax while maintaining linear-time decoding. we employ a linear-time parsing algorithm based on an eager, incremental interpretation of combinatory categorial grammar (ccg). as every input word is processed, the local parsing decisions resolve ambiguity eagerly, by selecting a single supertag-operator pair for extending the dependency parse incrementally. alongside translation features extracted from the derived parse tree, we explore syntactic features extracted from the incremental derivation process. our empirical experiments show that our model significantly outperforms the state-of-the art dtm2 system.
review sentiment scoring via a parse-and-paraphrase paradigm. this paper presents a parse-and-paraphrase paradigm to assess the degrees of sentiment for product reviews. sentiment identification has been well studied; however, most previous work provides binary polarities only (positive and negative), and the polarity of sentiment is simply reversed when a negation is detected. the extraction of lexical features such as unigram/bigram also complicates the sentiment classification task, as linguistic structure such as implicit long-distance dependency is often disregarded. in this paper, we propose an approach to extracting adverb-adjective-noun phrases based on clause structure obtained by parsing sentences into a hierarchical representation. we also propose a robust general solution for modeling the contribution of adverbials and negation to the score for degree of sentiment. in an application involving extracting aspect-based pros and cons from restaurant reviews, we obtained a 45% relative improvement in recall through the use of parsing methods, while also improving precision.
tree kernel-based svm with structured syntactic knowledge for btg-based phrase reordering. structured syntactic knowledge is important for phrase reordering. this paper proposes using convolution tree kernel over source parse tree to model structured syntactic knowledge for btg-based phrase reordering in the context of statistical machine translation. our study reveals that the structured syntactic features over the source phrases are very effective for btg constraint-based phrase reordering and those features can be well captured by the tree kernel. we further combine the structured features and other commonly-used linear features into a composite kernel. experimental results on the nist mt-2005 chinese-english translation tasks show that our proposed phrase reordering model statistically significantly outperforms the baseline methods.
less is more: significance-based n-gram selection for smaller, better language models. the recent availability of large corpora for training n-gram language models has shown the utility of models of higher order than just trigrams. in this paper, we investigate methods to control the increase in model size resulting from applying standard methods at higher orders. we introduce significance-based n-gram selection, which not only reduces model size, but also improves perplexity for several smoothing methods, including katz backoff and absolute discounting. we also show that, when combined with a new smoothing method and a novel variant of weighted-difference pruning, our selection method performs better in the trade-off between model size and perplexity than the best pruning method we found for modified kneser-ney smoothing.
labeled lda: a supervised topic model for credit attribution in multi-labeled corpora. a significant portion of the world's text is tagged by readers on social bookmarking websites. credit attribution is an inherent problem in these corpora because most pages have multiple tags, but the tags do not always apply with equal specificity across the whole document. solving the credit attribution problem requires associating each word in a document with the most appropriate tags and vice versa. this paper introduces labeled lda, a topic model that constrains latent dirichlet allocation by defining a one-to-one correspondence between lda's latent topics and user tags. this allows labeled lda to directly learn word-tag correspondences. we demonstrate labeled lda's improved expressiveness over traditional lda with visualizations of a corpus of tagged web pages from del.icio.us. labeled lda outperforms svms by more than 3 to 1 when extracting tag-specific document snippets. as a multi-label text classifier, our model is competitive with a discriminative baseline on a variety of datasets.
hypernym discovery based on distributional similarity and hierarchical structures. this paper presents a new method of developing a large-scale hyponymy relation database by combining wikipedia and other web documents. we attach new words to the hyponymy database extracted from wikipedia by using distributional similarity calculated from documents on the web. for a given target word, our algorithm first finds k similar words from the wikipedia database. then, the hypernyms of these k similar words are assigned scores by considering the distributional similarities and hierarchical distances in the wikipedia database. finally, new hyponymy relations are output according to the scores. in this paper, we tested two distributional similarities. one is based on raw verb-noun dependencies (which we call "rvd"), and the other is based on a large-scale clustering of verb-noun dependencies (called "cvd"). our method achieved an attachment accuracy of 91.0% for the top 10,000 relations, and an attachment accuracy of 74.5% for the top 100,000 relations when using cvd. this was a far better outcome compared to the other baseline approaches. excluding the region that had very high scores, cvd was found to be more effective than rvd. we also confirmed that most relations extracted by our method cannot be extracted merely by applying the well-known lexico-syntactic patterns to web documents.
mining search engine clickthrough log for matching n-gram features. user clicks on a url in response to a query are extremely useful predictors of the url's relevance to that query. exact match click features tend to suffer from severe data sparsity issues in web ranking. such sparsity is particularly pronounced for new urls or long queries where each distinct query-url pair will rarely occur. to remedy this, we present a set of straightforward yet informative query-url n-gram features that allows for generalization of limited user click data to large amounts of unseen query-url pairs. the method is motivated by techniques leveraged in the nlp community for dealing with unseen words. we find that there are interesting regularities across queries and their preferred destination urls; for example, queries containing "form" tend to lead to clicks on urls containing "pdf". we evaluate our set of new query-url features on a web search ranking task and obtain improvements that are statistically significant at a p-value < 0.0001 level over a strong baseline with exact match clickthrough features.
synchronous tree adjoining machine translation. tree adjoining grammars have well-known advantages, but are typically considered too difficult for practical systems. we demonstrate that, when done right, adjoining improves translation quality without becoming computationally intractable. using adjoining to model optionality allows general translation patterns to be learned without the clutter of endless variations of optional material. the appropriate modifiers can later be spliced in as needed. in this paper, we describe a novel method for learning a type of synchronous tree adjoining grammar and associated probabilities from aligned tree/string training data. we introduce a method of converting these grammars to a weakly equivalent tree transducer for decoding. finally, we show that adjoining results in an end-to-end improvement of +0.8 bleu over a baseline statistical syntax-based mt model on a large-scale arabic/english mt task.
the infinite hmm for unsupervised pos tagging. we extend previous work on fully unsupervised part-of-speech tagging. using a non-parametric version of the hmm, called the infinite hmm (ihmm), we address the problem of choosing the number of hidden states in unsupervised markov models for pos tagging. we experiment with two non-parametric priors, the dirichlet and pitman-yor processes, on the wall street journal dataset using a parallelized implementation of an ihmm inference algorithm. we evaluate the results with a variety of clustering evaluation metrics and achieve equivalent or better performances than previously reported. building on this promising result we evaluate the output of the unsupervised pos tagger as a direct replacement for the output of a fully supervised pos tagger for the task of shallow parsing and compare the two evaluations.
what's in a name? in some languages, grammatical gender. this paper presents an investigation of the relation between words and their gender in two gendered languages: german and romanian. gender is an issue that has long preoccupied linguists and baffled language learners. we verify the hypothesis that gender is dictated by the general sound patterns of a language, and that it goes beyond suffixes or word endings. experimental results on german and romanian nouns show strong support for this hypothesis, as gender prediction can be done with high accuracy based on the form of the words.
the role of named entities in web people search. the ambiguity of person names in the web has become a new area of interest for nlp researchers. this challenging problem has been formulated as the task of clustering web search results (returned in response to a person name query) according to the individual they mention. in this paper we compare the coverage, reliability and independence of a number of features that are potential information sources for this clustering task, paying special attention to the role of named entities in the texts to be clustered. although named entities are used in most approaches, our results show that, independently of the machine learning or clustering algorithm used, named entity recognition and classification per se only make a small contribution to solve the problem.
phrase dependency parsing for opinion mining. in this paper, we present a novel approach for mining opinions from product reviews, where it converts opinion mining task to identify product features, expressions of opinions and relations between them. by taking advantage of the observation that a lot of product features are phrases, a concept of phrase dependency parsing is introduced, which extends traditional dependency parsing to phrase level. this concept is then implemented for extracting relations between product features and expressions of opinions. experimental evaluations show that the mining task can benefit from phrase dependency parsing.
generalized expectation criteria for bootstrapping extractors using record-text alignment. traditionally, machine learning approaches for information extraction require human annotated data that can be costly and time-consuming to produce. however, in many cases, there already exists a database (db) with schema related to the desired output, and records related to the expected input text. we present a conditional random field (crf) that aligns tokens of a given db record and its realization in text. the crf model is trained using only the available db and unlabeled text with generalized expectation criteria. an annotation of the text induced from inferred alignments is used to train an information extractor. we evaluate our method on a citation extraction task in which alignments between dblp database records and citation texts are used to train an extractor. experimental results demonstrate an error reduction of 35% over a previous state-of-the-art method that uses heuristic alignments.
unbounded dependency recovery for parser evaluation. this paper introduces a new parser evaluation corpus containing around 700 sentences annotated with unbounded dependencies, from seven different grammatical constructions. we run a series of off-the-shelf parsers on the corpus to evaluate how well state-of-the-art parsing technology is able to recover such dependencies. the overall results range from 25% accuracy to 59%. these low scores call into question the validity of using parseval scores as a general measure of parsing capability. we discuss the importance of parsers being able to recover unbounded dependencies, given their relatively low frequency in corpora. we also analyse the various errors made on these constructions by one of the more successful parsers.
estimating semantic distance using soft semantic constraints in knowledge-source - corpus hybrid models. strictly corpus-based measures of semantic distance conflate co-occurrence information pertaining to the many possible senses of target words. we propose a corpus-thesaurus hybrid method that uses soft constraints to generate word-senseaware distributional profiles (dps) from coarser "concept dps" (derived from a roget-like thesaurus) and sense-unaware traditional word dps (derived from raw text). although it uses a knowledge source, the method is not vocabulary-limited: if the target word is not in the thesaurus, the method falls back gracefully on the word's co-occurrence information. this allows the method to access valuable information encoded in a lexical resource, such as a thesaurus, while still being able to effectively handle domain-specific terms and named entities. experiments on word-pair ranking by semantic distance show the new hybrid method to be superior to others.
bidirectional phrase-based statistical machine translation. this paper investigates the effect of direction in phrase-based statistial machine translation decoding. we compare a typical phrase-based machine translation decoder using a left-to-right decoding strategy to a right-to-left decoder. we also investigate the effectiveness of a bidirectional decoding strategy that integrates both mono-directional approaches, with the aim of reducing the effects due to language specificity. our experimental evaluation was extensive, based on 272 different language pairs, and gave the surprising result that for most of the language pairs, it was better decode from right-to-left than from left-to-right. as expected the relative performance of left-to-right and right-to-left strategies proved to be highly language dependent. the bidirectional approach outperformed the both the left-to-right strategy and the right-to-left strategy, showing consistent improvements that appeared to be unrelated to the specific languages used for translation. bidirectional decoding gave rise to an improvement in performance over a left-to-right decoding strategy in terms of the bleu score in 99% of our experiments.
domain adaptive bootstrapping for named entity recognition. bootstrapping is the process of improving the performance of a trained classifier by iteratively adding data that is labeled by the classifier itself to the training set, and retraining the classifier. it is often used in situations where labeled training data is scarce but unlabeled data is abundant. in this paper, we consider the problem of domain adaptation: the situation where training data may not be scarce, but belongs to a different domain from the target application domain. as the distribution of unlabeled data is different from the training data, standard bootstrapping often has difficulty selecting informative data to add to the training set. we propose an effective domain adaptive bootstrapping algorithm that selects unlabeled target domain data that are informative about the target domain and easy to automatically label correctly. we call these instances bridges, as they are used to bridge the source domain to the target domain. we show that the method outperforms supervised, transductive and bootstrapping algorithms on the named entity recognition task.
wikipedia as frame information repository. in this paper, we address the issue of automatic extending lexical resources by exploiting existing knowledge repositories. in particular, we deal with the new task of linking framenet and wikipedia using a word sense disambiguation system that, for a given pair frame -- lexical unit (f, l), finds the wikipage that best expresses the the meaning of l. the mapping can be exploited to straightforwardly acquire new example sentences and new lexical units, both for english and for all languages available in wikipedia. in this way, it is possible to easily acquire good-quality data as a starting point for the creation of framenet in new languages. the evaluation reported both for the monolingual and the multilingual expansion of framenet shows that the approach is promising.
learning term-weighting functions for similarity measures. measuring the similarity between two texts is a fundamental problem in many nlp and ir applications. among the existing approaches, the cosine measure of the term vectors representing the original texts has been widely used, where the score of each term is often determined by a tfidf formula. despite its simplicity, the quality of such cosine similarity measure is usually domain dependent and decided by the choice of the term-weighting function. in this paper, we propose a novel framework that learns the term-weighting function. given the labeled pairs of texts as training data, the learning procedure tunes the model parameters by minimizing the specified loss function of the similarity score. compared to traditional tfidf term-weighting schemes, our approach shows a significant improvement on tasks such as judging the quality of query suggestions and filtering irrelevant ads for online advertising.
finding short definitions of terms on web pages. we present a system that finds short definitions of terms on web pages. it employs a maximum entropy classifier, but it is trained on automatically generated examples; hence, it is in effect unsupervised. we use rouge-w to generate training examples from encyclopedias and web snippets, a method that outperforms an alternative centroid-based one. after training, our system can be used to find definitions of terms that are not covered by encyclopedias. the system outperforms a comparable publicly available system, as well as a previously published form of our system.
deriving lexical and syntactic expectation-based measures for psycholinguistic modeling via incremental top-down parsing. a number of recent publications have made use of the incremental output of stochastic parsers to derive measures of high utility for psycholinguistic modeling, following the work of hale (2001; 2003; 2006). in this paper, we present novel methods for calculating separate lexical and syntactic surprisal measures from a single incremental parser using a lexicalized pcfg. we also present an approximation to entropy measures that would otherwise be intractable to calculate for a grammar of that size. empirical results demonstrate the utility of our methods in predicting human reading times.
efficient kernels for sentence pair classification. in this paper, we propose a novel class of graphs, the tripartite directed acyclic graphs (tdags), to model first-order rule feature spaces for sentence pair classification. we introduce a novel algorithm for computing the similarity in first-order rewrite rule feature spaces. our algorithm is extremely efficient and, as it computes the similarity of instances that can be represented in explicit feature spaces, it is a valid kernel function.
acquiring translation equivalences of multiword expressions by normalized correlation frequencies. in this paper, we present an algorithm for extracting translations of any given multiword expression from parallel corpora. given a multiword expression to be translated, the method involves extracting a short list of target candidate words from parallel corpora based on scores of normalized frequency, generating possible translations and filtering out common subsequences, and selecting the top-n possible translations using the dice coefficient. experiments show that our approach outperforms the word alignment-based and other naive association-based methods. we also demonstrate that adopting the extracted translations can significantly improve the performance of the moses machine translation system.
multilingual spectral clustering using document similarity propagation. we present a novel approach for multilingual document clustering using only comparable corpora to achieve cross-lingual semantic interoperability. the method models document collections as weighted graph, and supervisory information is given as sets of must-linked constraints for documents in different languages. recursive k-nearest neighbor similarity propagation is used to exploit the prior knowledge and merge two language spaces. spectral method is applied to find the best cuts of the graph. experimental results show that using limited supervisory information, our method achieves promising clustering results. furthermore, since the method does not need any language dependent information in the process, our algorithm can be applied to languages in various alphabetical systems.
person cross document coreference with name perplexity estimates. the person cross document coreference systems depend on the context for making decisions on the possible coreferences between person name mentions. the amount of context required is a parameter that varies from corpora to corpora, which makes it difficult for usual disambiguation methods. in this paper we show that the amount of context required can be dynamically controlled on the basis of the prior probabilities of coreference and we present a new statistical model for the computation of these probabilities. the experiment we carried on a news corpus proves that the prior probabilities of coreference are an important factor for maintaining a good balance between precision and recall for cross document coreference systems.
stream-based randomised language models for smt. randomised techniques allow very big language models to be represented succinctly. however, being batch-based they are unsuitable for modelling an unbounded stream of language whilst maintaining a constant error rate. we present a novel randomised language model which uses an online perfect hash function to efficiently deal with unbounded text streams. translation experiments over a text stream show that our online randomised model matches the performance of batch-based lms without incurring the computational overhead associated with full retraining. this opens up the possibility of randomised language models which continuously adapt to the massive volumes of texts published on the web each day.
large-scale verb entailment acquisition from the web. textual entailment recognition plays a fundamental role in tasks that require indepth natural language understanding. in order to use entailment recognition technologies for real-world applications, a large-scale entailment knowledge base is indispensable. this paper proposes a conditional probability based directional similarity measure to acquire verb entailment pairs on a large scale. we targeted 52,562 verb types that were derived from 108 japanese web documents, without regard for whether they were used in daily life or only in specific fields. in an evaluation of the top 20,000 verb entailment pairs acquired by previous methods and ours, we found that our similarity measure outperformed the previous ones. our method also worked well for the top 100,000 results.
discovery of term variation in japanese web search queries. in this paper we address the problem of identifying a broad range of term variations in japanese web search queries, where these variations pose a particularly thorny problem due to the multiple character types employed in its writing system. our method extends the techniques proposed for english spelling correction of web queries to handle a wider range of term variants including spelling mistakes, valid alternative spellings using multiple character types, transliterations and abbreviations. the core of our method is a statistical model built on the mart algorithm (friedman, 2001). we show that both string and semantic similarity features contribute to identifying term variation in web search queries; specifically, the semantic similarity features used in our system are learned by mining user session and click-through logs, and are useful not only as model features but also in generating term variation candidates efficiently. the proposed method achieves 70% precision on the term variation identification task with the recall slightly higher than 60%, reducing the error rate of a na&iuml;ve baseline by 38%.
combining collocations, lexical and encyclopedic knowledge for metonymy resolution. this paper presents a supervised method for resolving metonymies. we enhance a commonly used feature set with features extracted based on collocation information from corpora, generalized using lexical and encyclopedic knowledge to determine the preferred sense of the potentially metonymic word using methods from unsupervised word sense disambiguation. the methodology developed addresses one issue related to metonymy resolution - the influence of local context. the method developed is applied to the metonymy resolution task from semeval 2007. the results obtained, higher for the countries subtask, on a par for the companies subtask - compared to participating systems - confirm that lexical, encyclopedic and collocation information can be successfully combined for metonymy resolution.
consensus training for consensus decoding in machine translation. we propose a novel objective function for discriminatively tuning log-linear machine translation models. our objective explicitly optimizes the bleu score of expected n-gram counts, the same quantities that arise in forest-based consensus and minimum bayes risk decoding methods. our continuous objective can be optimized using simple gradient ascent. however, computing critical quantities in the gradient necessitates a novel dynamic program, which we also present here. assuming bleu as an evaluation measure, our objective function has two principle advantages over standard max bleu tuning. first, it specifically optimizes model weights for downstream consensus decoding procedures. an unexpected second benefit is that it reduces overfitting, which can improve test set bleu scores when using standard viterbi decoding.
it's not you, it's me: detecting flirting and its misperception in speed-dates. automatically detecting human social intentions from spoken conversation is an important task for dialogue understanding. since the social intentions of the speaker may differ from what is perceived by the hearer, systems that analyze human conversations need to be able to extract both the perceived and the intended social meaning. we investigate this difference between intention and perception by using a spoken corpus of speed-dates in which both the speaker and the listener rated the speaker on flirtatiousness. our flirtation-detection system uses prosodic, dialogue, and lexical features to detect a speaker's intent to flirt with up to 71.5% accuracy, significantly outperforming the baseline, but also outperforming the human inter-locuters. our system addresses lexical feature sparsity given the small amount of training data by using an autoencoder network to map sparse lexical feature vectors into 30 compressed features. our analysis shows that humans are very poor perceivers of intended flirtatiousness, instead often projecting their own intended behavior onto their interlocutors.
can chinese phonemes improve machine transliteration?: a comparative study of english-to-chinese transliteration models. inspired by the success of english grapheme-to-phoneme research in speech synthesis, many researchers have proposed phoneme-based english-to-chinese transliteration models. however, such approaches have severely suffered from the errors in chinese phoneme-to-grapheme conversion. to address this issue, we propose a new english-to-chinese transliteration model and make systematic comparisons with the conventional models. our proposed model relies on the joint use of chinese phonemes and their corresponding english graphemes and phonemes. experiments showed that chinese phonemes in our proposed model can contribute to the performance improvement in english-to-chinese transliteration.
polynomial to linear: efficient classification with conjunctive features. this paper proposes a method that speeds up a classifier trained with many conjunctive features: combinations of (primitive) features. the key idea is to precompute as partial results the weights of primitive feature vectors that appear frequently in the target nlp task. a trie compactly stores the primitive feature vectors with their weights, and it enables the classifier to find for a given feature vector its longest prefix feature vector whose weight has already been computed. experimental results for a japanese dependency parsing task show that our method speeded up the svm and llm classifiers of the parsers, which achieved accuracy of 90.84/90.71%, by a factor of 10.7/11.6.
character-level analysis of semi-structured documents for set expansion. set expansion refers to expanding a partial set of "seed" objects into a more complete set. one system that does set expansion is seal (set expander for any language), which expands entities automatically by utilizing resources from the web in a language-independent fashion. in this paper, we illustrated in detail the construction of character-level wrappers for set expansion implemented in seal. we also evaluated several kinds of wrappers for set expansion and showed that character-based wrappers perform better than html-based wrappers. in addition, we demonstrated a technique that extends seal to learn binary relational concepts (e.g., "x is the mayor of the city y") from only two seeds. we also show that the extended seal has good performance on our evaluation datasets, which includes english and chinese, thus demonstrating language-independence.
improved word alignment with statistics and linguistic heuristics. we present a method to align words in a bitext that combines elements of a traditional statistical approach with linguistic knowledge. we demonstrate this approach for arabic-english, using an alignment lexicon produced by a statistical word aligner, as well as linguistic resources ranging from an english parser to heuristic alignment rules for function words. these linguistic heuristics have been generalized from a development corpus of 100 parallel sentences. our aligner, ualign, outperforms both the commonly used giza++ aligner and the state-of-the-art leaf aligner on f-measure and produces superior scores in end-to-end statistical machine translation, +1.3 bleu points over giza++, and +0.7 over leaf.
word buffering models for improved speech repair parsing. this paper describes a time-series model for parsing transcribed speech containing disfluencies. this model differs from previous parsers in its explicit modeling of a buffer of recent words, which allows it to recognize repairs more easily due to the frequent overlap in words between errors and their repairs. the parser implementing this model is evaluated on the standard switchboard transcribed speech parsing task for overall parsing accuracy and edited word detection.
a compact forest for scalable inference over entailment and paraphrase rules. a large body of recent research has been investigating the acquisition and application of applied inference knowledge. such knowledge may be typically captured as entailment rules, applied over syntactic representations. efficient inference with such knowledge then becomes a fundamental problem. starting out from a formalism for entailment-rule application we present a novel packed data-structure and a corresponding algorithm for its scalable implementation. we proved the validity of the new algorithm and established its efficiency analytically and empirically.
improved statistical machine translation for resource-poor languages using related resource-rich languages. we propose a novel language-independent approach for improving statistical machine translation for resource-poor languages by exploiting their similarity to resource-rich ones. more precisely, we improve the translation from a resource-poor source language x1 into a resource-rich language y given a bi-text containing a limited number of parallel sentences for x1-y and a larger bi-text for x2-y for some resource-rich language x2 that is closely related to x1. the evaluation for indonesian&rarr;english (using malay) and spanish&rarr;english (using portuguese and pretending spanish is resource-poor) shows an absolute gain of up to 1.35 and 3.37 bleu points, respectively, which is an improvement over the rivaling approaches, while using much less additional data.
model adaptation via model interpolation and boosting for web search ranking. this paper explores two classes of model adaptation methods for web search ranking: model interpolation and error-driven learning approaches based on a boosting algorithm. the results show that model interpolation, though simple, achieves the best results on all the open test sets where the test data is very different from the training data. the tree-based boosting algorithm achieves the best performance on most of the closed test sets where the test data and the training data are similar, but its performance drops significantly on the open test sets due to the instability of trees. several methods are explored to improve the robustness of the algorithm, with limited success.
semi-supervised semantic role labeling using the latent words language model. semantic role labeling (srl) has proved to be a valuable tool for performing automatic analysis of natural language texts. currently however, most systems rely on a large training set, which is manually annotated, an effort that needs to be repeated whenever different languages or a different set of semantic roles is used in a certain application. a possible solution for this problem is semi-supervised learning, where a small set of training examples is automatically expanded using unlabeled texts. we present the latent words language model, which is a language model that learns word similarities from unlabeled texts. we use these similarities for different semi-supervised srl methods as additional features or to automatically expand a small training set. we evaluate the methods on the propbank dataset and find that for small training sizes our best performing system achieves an error reduction of 33.27% f1-measure compared to a state-of-the-art supervised baseline.
towards domain-independent argumentative zoning: evidence from chemistry and computational linguistics. argumentative zoning (az) is an analysis of the argumentative and rhetorical structure of a scientific paper. it has been shown to be reliably used by independent human coders, and has proven useful for various information access tasks. annotation experiments have however so far been restricted to one discipline, computational linguistics (cl). here, we present a more informative az scheme with 15 categories in place of the original 7, and show that it can be applied to the life sciences as well as to cl. we use a domain expert to encode basic knowledge about the subject (such as terminology and domain specific rules for individual categories) as part of the annotation guidelines. our results show that non-expert human coders can then use these guidelines to reliably annotate this scheme in two domains, chemistry and computational linguistics.
on the use of virtual evidence in conditional random fields. virtual evidence (ve), first introduced by (pearl, 1988), provides a convenient way of incorporating prior knowledge into bayesian networks. this work generalizes the use of ve to undirected graphical models and, in particular, to conditional random fields (crfs). we show that ve can be naturally encoded into a crf model as potential functions. more importantly, we propose a novel semi-supervised machine learning objective for estimating a crf model integrated with ve. the objective can be optimized using the expectation-maximization algorithm while maintaining the discriminative nature of crfs. when evaluated on the classifieds data, our approach significantly outperforms the best known solutions reported on this task.
a simple unsupervised learner for pos disambiguation rules given only a minimal lexicon. we propose a new model for unsupervised pos tagging based on linguistic distinctions between open and closed-class items. exploiting notions from current linguistic theory, the system uses far less information than previous systems, far simpler computational methods, and far sparser descriptions in learning contexts. by applying simple language acquisition techniques based on counting, the system is given the closed-class lexicon, acquires a large open-class lexicon and then acquires disambiguation rules for both. this system achieves a 20% error reduction for pos tagging over state-of-the-art unsupervised systems tested under the same conditions, and achieves comparable accuracy when trained with much less prior information.
self-training pcfg grammars with latent annotations across languages. we investigate the effectiveness of self-training pcfg grammars with latent annotations (pcfg-la) for parsing languages with different amounts of labeled training data. compared to charniak's lexicalized parser, the pcfg-la parser was more effectively adapted to a language for which parsing has been less well developed (i.e., chinese) and benefited more from self-training. we show for the first time that self-training is able to significantly improve the performance of the pcfg-la parser, a single generative parser, on both small and large amounts of labeled training data. our approach achieves state-of-the-art parsing accuracies for a single parser on both english (91.5%) and chinese (85.2%).
statistical estimation of word acquisition with application to readability prediction. models of language learning play a central role in a wide range of applications: from psycholinguistic theories of how people acquire new word knowledge, to information systems that can automatically match content to users' reading ability. we present a novel statistical approach that can infer the distribution of a word's likely acquisition age automatically from authentic texts collected from the web. we then show that combining these acquisition age distributions for all words in a document provides an effective semantic component for predicting reading difficulty of new texts. we also compare our automatically inferred acquisition ages with norms from existing oral studies, revealing interesting historical trends as well as differences between oral and written word acquisition processes.
re-ranking models based-on small training data for spoken language understanding. the design of practical language applications by means of statistical approaches requires annotated data, which is one of the most critical constraint. this is particularly true for spoken dialog systems since considerably domain-specific conceptual annotation is needed to obtain accurate language understanding models. since data annotation is usually costly, methods to reduce the amount of data are needed. in this paper, we show that better feature representations serve the above purpose and that structure kernels provide the needed improved representation. given the relatively high computational cost of kernel methods, we apply them to just re-rank the list of hypotheses provided by a fast generative model. experiments with support vector machines and different kernels on two different dialog corpora show that our re-ranking models can achieve better results than state-of-the-art approaches when small data is available.
reading to learn: constructing features from semantic abstracts. machine learning offers a range of tools for training systems from data, but these methods are only as good as the underlying representation. this paper proposes to acquire representations for machine learning by reading text written to accommodate human learning. we propose a novel form of semantic analysis called reading to learn, where the goal is to obtain a high-level semantic abstract of multiple documents in a representation that facilitates learning. we obtain this abstract through a generative model that requires no labeled data, instead leveraging repetition across multiple documents. the semantic abstract is converted into a transformed feature space for learning, resulting in improved generalization on a relational learning task.
semantic dependency parsing of nombank and propbank: an efficient integrated approach via a large-scale feature selection. we present an integrated dependency-based semantic role labeling system for english from both nombank and propbank. by introducing assistant argument labels and considering much more feature templates, two optimal feature template sets are obtained through an effective feature selection procedure and help construct a high performance single srl system. from the evaluations on the date set of conll-2008 shared task, the performance of our system is quite close to the state of the art. as to our knowledge, this is the first integrated srl system that achieves a competitive performance against previous pipeline systems.
multi-class confidence weighted algorithms. the recently introduced online confidence-weighted (cw) learning algorithm for binary classification performs well on many binary nlp tasks. however, for multi-class problems cw learning updates and inference cannot be computed analytically or solved as convex optimization problems as they are in the binary case. we derive learning algorithms for the multi-class cw setting and provide extensive evaluation using nine nlp datasets, including three derived from the recently released new york times corpus. our best algorithm out-performs state-of-the-art online and batch methods on eight of the nine tasks. we also show that the confidence information maintained during learning yields useful probabilistic information at test time.
convolution kernels on constituent, dependency and sequential structures for relation extraction. this paper explores the use of innovative kernels based on syntactic and semantic structures for a target relation extraction task. syntax is derived from constituent and dependency parse trees whereas semantics concerns to entity types and lexical sequences. we investigate the effectiveness of such representations in the automated relation extraction from texts. we process the above data by means of support vector machines along with the syntactic tree, the partial tree and the word sequence kernels. our study on the ace 2004 corpus illustrates that the combination of the above kernels achieves high effectiveness and significantly improves the current state-of-the-art.
improving nominal srl in chinese language with verbal srl information and automatic predicate recognition. this paper explores chinese semantic role labeling (srl) for nominal predicates. besides those widely used features in verbal srl, various nominal srl-specific features are first included. then, we improve the performance of nominal srl by integrating useful features derived from a state-of-the-art verbal srl system. finally, we address the issue of automatic predicate recognition, which is essential for a nominal srl system. evaluation on chinese nombank shows that our research in integrating various features derived from verbal srl significantly improves the performance. it also shows that our nominal srl system much outperforms the state-of-the-art ones.
statistical bistratal dependency parsing. we present an inexact search algorithm for the problem of predicting a two-layered dependency graph. the algorithm is based on a k-best version of the standard cubic-time search algorithm for projective dependency parsing, which is used as the backbone of a beam search procedure. this allows us to handle the complex non-local feature dependencies occurring in bistratal parsing if we model the interdependency between the two layers. we apply the algorithm to the syntactic---semantic dependency parsing task of the conll-2008 shared task, and we obtain a competitive result equal to the highest published for a system that jointly learns syntactic and semantic structure.
predicting subjectivity in multimodal conversations. in this research we aim to detect subjective sentences in multimodal conversations. we introduce a novel technique wherein subjective patterns are learned from both labeled and unlabeled data, using n-gram word sequences with varying levels of lexical instantiation. applying this technique to meeting speech and email conversations, we gain significant improvement over state-of-the-art approaches. furthermore, we show that coupling the pattern-based approach with features that capture characteristics of general conversation structure yields additional improvement.
investigation of question classifier in question answering. in this paper, we investigate how an accurate question classifier contributes to a question answering system. we first present a maximum entropy (me) based question classifier which makes use of head word features and their wordnet hypernyms. we show that our question classifier can achieve the state of the art performance in the standard uiuc question dataset. we then investigate quantitatively the contribution of this question classifier to a feature driven question answering system. with our accurate question classifier and some standard question answer features, our question answering system performs close to the state of the art using trec corpus.
a unified model of phrasal and sentential evidence for information extraction. information extraction (ie) systems that extract role fillers for events typically look at the local context surrounding a phrase when deciding whether to extract it. often, however, role fillers occur in clauses that are not directly linked to an event word. we present a new model for event extraction that jointly considers both the local context around a phrase along with the wider sentential context in a probabilistic framework. our approach uses a sentential event recognizer and a plausible role-filler recognizer that is conditioned on event sentences. we evaluate our system on two ie data sets and show that our model performs well in comparison to existing ie systems that rely on local phrasal context.
subjectivity word sense disambiguation. this paper investigates a new task, subjectivity word sense disambiguation (swsd), which is to automatically determine which word instances in a corpus are being used with subjective senses, and which are being used with objective senses. we provide empirical evidence that swsd is more feasible than full word sense disambiguation, and that it can be exploited to improve the performance of contextual subjectivity and sentiment analysis systems.
clustering to find exemplar terms for keyphrase extraction. keyphrases are widely used as a brief summary of documents. since manual assignment is time-consuming, various unsupervised ranking methods based on importance scores are proposed for keyphrase extraction. in practice, the keyphrases of a document should not only be statistically important in the document, but also have a good coverage of the document. based on this observation, we propose an unsupervised method for keyphrase extraction. firstly, the method finds exemplar terms by leveraging clustering techniques, which guarantees the document to be semantically covered by these exemplar terms. then the keyphrases are extracted from the document using the exemplar terms. our method outperforms sate-of-the-art graph-based ranking methods (textrank) by 9.5% in f1-measure.
unsupervised morphological segmentation and clustering with document boundaries. many approaches to unsupervised morphology acquisition incorporate the frequency of character sequences with respect to each other to identify word stems and affixes. this typically involves heuristic search procedures and calibrating multiple arbitrary thresholds. we present a simple approach that uses no thresholds other than those involved in standard application of x2 significance testing. a key part of our approach is using document boundaries to constrain generation of candidate stems and affixes and clustering morphological variants of a given word stem. we evaluate our model on english and the mayan language uspanteko; it compares favorably to two benchmark systems which use considerably more complex strategies and rely more on experimentally chosen threshold values.
unsupervised semantic parsing. we present the first unsupervised approach to the problem of learning a semantic parser, using markov logic. our usp system transforms dependency trees into quasi-logical forms, recursively induces lambda forms from these, and clusters them to abstract away syntactic variations of the same meaning. the map semantic parse of a sentence is obtained by recursively assigning its parts to lambda-form clusters and composing them. we evaluate our approach by using it to extract a knowledge base from biomedical abstracts and answer questions. usp substantially outperforms textrunner, dirt and an informed baseline on both precision and recall on this task.
a comparison of windowless and window-based computational association measures as predictors of syntagmatic human associations. distance-based (windowless) word assocation measures have only very recently appeared in the nlp literature and their performance compared to existing windowed or frequency-based measures is largely unknown. we conduct a large-scale empirical comparison of a variety of distance-based and frequency-based measures for the reproduction of syntagmatic human assocation norms. overall, our results show an improvement in the predictive power of windowless over windowed measures. this provides support to some of the previously published theoretical advantages and makes windowless approaches a promising avenue to explore further. this study also serves as a first comparison of windowed methods across numerous human association datasets. during this comparison we also introduce some novel variations of window-based measures which perform as well as or better in the human association norm task than established measures.
a bayesian model of syntax-directed tree to string grammar induction. tree based translation models are a compelling means of integrating linguistic information into machine translation. syntax can inform lexical selection and reordering choices and thereby improve translation quality. research to date has focussed primarily on decoding with such models, but less on the difficult problem of inducing the bilingual grammar from data. we propose a generative bayesian model of tree-to-string translation which induces grammars that are both smaller and produce better translations than the previous heuristic two-stage approach which employs a separate word alignment step.
effective use of linguistic and contextual information for statistical machine translation. current methods of using lexical features in machine translation have difficulty in scaling up to realistic mt tasks due to a prohibitively large number of parameters involved. in this paper, we propose methods of using new linguistic and contextual features that do not suffer from this problem and apply them in a state-of-the-art hierarchical mt system. the features used in this work are non-terminal labels, non-terminal length distribution, source string context and source dependency lm scores. the effectiveness of our techniques is demonstrated by significant improvements over a strong base-line. on arabic-to-english translation, improvements in lower-cased bleu are 2.0 on nist mt06 and 1.7 on mt08 newswire data on decoding output. on chinese-to-english translation, the improvements are 1.0 on mt06 and 0.8 on mt08 newswire data.
feasibility of human-in-the-loop minimum error rate training. minimum error rate training (mert) involves choosing parameter values for a machine translation (mt) system that maximize performance on a tuning set as measured by an automatic evaluation metric, such as bleu. the method is best when the system will eventually be evaluated using the same metric, but in reality, most mt evaluations have a human-based component. although performing mert with a human-based metric seems like a daunting task, we describe a new metric, rypt, which takes human judgments into account, but only requires human input to build a database that can be reused over and over again, hence eliminating the need for human input at tuning time. in this investigative study, we analyze the diversity (or lack thereof) of the candidates produced during mert, we describe how this redundancy can be used to our advantage, and show that rypt is a better predictor of translation quality than bleu.
identification of event mentions and their semantic class. complex tasks like question answering need to be able to identify events in text and the relations among those events. we show that this event identification task and a related task, identifying the semantic class of these events, can both be formulated as classification problems in a word-chunking paradigm. we introduce a variety of linguistically motivated features for this task and then train a system that is able to identify events with a precision of 82% and a recall of 71%. we then show a variety of analyses of this model, and their implications for the event identification task.
the impact of parse quality on syntactically-informed statistical machine translation. we investigate the impact of parse quality on a syntactically-informed statistical machine translation system applied to technical text. we vary parse quality by varying the amount of data used to train the parser. as the amount of data increases, parse quality improves, leading to improvements in machine translation output and results that significantly outperform a state-of-the-art phrasal baseline.
learning phrasal categories. in this work we learn clusters of contextual annotations for non-terminals in the penn treebank. perhaps the best way to think about this problem is to contrast our work with that of klein and manning (2003). that research used tree-transformations to create various grammars with different contextual annotations on the non-terminals. these grammars were then used in conjunction with a cky parser. the authors explored the space of different annotation combinations by hand. here we try to automate the process -- to learn the "right" combination automatically. our results are not quite as good as those carefully created by hand, but they are close (84.8 vs 85.7).
learning field compatibilities to extract database records from unstructured text. named-entity recognition systems extract entities such as people, organizations, and locations from unstructured text. rather than extract these mentions in isolation, this paper presents a record extraction system that assembles mentions into records (i.e. database tuples). we construct a probabilistic model of the compatibility between field values, then employ graph partitioning algorithms to cluster fields into cohesive records. we also investigate compatibility functions over sets of fields, rather than simply pairs of fields, to examine how higher representational power can impact performance. we apply our techniques to the task of extracting contact records from faculty and student homepages, demonstrating a 53% error reduction over baseline approaches.
capturing out-of-vocabulary words in arabic text. the increasing flow of information between languages has led to a rise in the frequency of non-native or loan words, where terms of one language appear transliterated in another. dealing with such out of vocabulary words is essential for successful cross-lingual information retrieval. for example, techniques such as stemming should not be applied indiscriminately to all words in a collection, and so before any stemming, foreign words need to be identified. in this paper, we investigate three approaches for the identification of foreign words in arabic text: lexicons, language patterns, and n-grams and present that results show that lexicon-based approaches outperform the other techniques.
a discriminative model for tree-to-tree translation. this paper proposes a statistical, tree-to-tree model for producing translations. two main contributions are as follows: (1) a method for the extraction of syntactic structures with alignment information from a parallel corpus of translations, and (2) use of a discriminative, feature-based model for prediction of these target-language syntactic structures---which we call aligned extended projections, or aeps. an evaluation of the method on translation from german to english shows similar performance to the phrase-based model of koehn et al. (2003).
unsupervised named entity transliteration using temporal and phonetic correlation. in this paper we investigate unsupervised name transliteration using comparable corpora, corpora where texts in the two languages deal in some of the same topics --- and therefore share references to named entities --- but are not translations of each other. we present two distinct methods for transliteration, one approach using an unsupervised phonetic transliteration method, and the other using the temporal distribution of candidate pairs. each of these approaches works quite well, but by combining the approaches one can achieve even better results. we believe that the novelty of our approach lies in the phonetic-based scoring method, which is based on a combination of carefully crafted phonetic features, and empirical results from the pronunciation errors of second-language learners of english. unlike previous approaches to transliteration, this method can in principle work with any pair of languages in the absence of a training dictionary, provided one has an estimate of the pronunciation of words in text.
priming effects in combinatory categorial grammar. this paper presents a corpus-based account of structural priming in human sentence processing, focusing on the role that syntactic representations play in such an account. we estimate the strength of structural priming effects from a corpus of spontaneous spoken dialogue, annotated syntactically with combinatory categorial grammar (ccg) derivations. this methodology allows us to test a range of predictions that ccg makes about priming. in particular, we present evidence for priming between lexical and syntactic categories encoding partially satisfied sub-categorization frames, and we show that priming effects exist both for incremental and normal-form ccg derivations.
partially supervised sense disambiguation by learning sense number from tagged and untagged corpora. supervised and semi-supervised sense disambiguation methods will mis-tag the instances of a target word if the senses of these instances are not defined in sense inventories or there are no tagged instances for these senses in training data. here we used a model order identification method to avoid the misclassification of the instances with undefined senses by discovering new senses from mixed data (tagged and untagged corpora). this algorithm tries to obtain a natural partition of the mixed data by maximizing a stability criterion defined on the classification result from an extended label propagation algorithm over all the possible values of the number of senses (or sense number, model order). experimental results on senseval-3 data indicate that it outperforms svm, a one-class partially supervised classification algorithm, and a clustering based model order identification algorithm when the tagged data is incomplete.
distributed language modeling for n-best list re-ranking. in this paper we describe a novel distributed language model for n-best list re-ranking. the model is based on the client/server paradigm where each server hosts a portion of the data and provides information to the client. this model allows for using an arbitrarily large corpus in a very efficient way. it also provides a natural platform for relevance weighting and selection. we applied this model on a 2.97 billion-word corpus and re-ranked the n-best list from hiero, a state-of-the-art phrase-based system. using bleu as a metric, the re-ranked translation achieves a relative improvement of 4.8%, significantly better than the model-best translation.
arabic ocr error correction using character segment correction, language modeling, and shallow morphology. this paper explores the use of a character segment based character correction model, language modeling, and shallow morphology for arabic ocr error correction. experimentation shows that character segment based correction is superior to single character correction and that language modeling boosts correction, by improving the ranking of candidate corrections, while shallow morphology had a small adverse effect. further, given sufficiently large corpus to extract a dictionary and to train a language model, word based correction works well for a morphologically rich language such as arabic.
a weakly supervised learning approach for spoken language understanding. in this paper, we present a weakly supervised learning approach for spoken language understanding in domain-specific dialogue systems. we model the task of spoken language understanding as a successive classification problem. the first classifier (topic classifier) is used to identify the topic of an input utterance. with the restriction of the recognized target topic, the second classifier (semantic classifier) is trained to extract the corresponding slot-value pairs. it is mainly data-driven and requires only minimally annotated corpus for training whilst retaining the understanding robustness and deepness for spoken language. most importantly, it allows the employment of weakly supervised strategies for training the two classifiers. we first apply the training strategy of combining active learning and self-training (tur et al., 2005) for topic classifier. also, we propose a practical method for bootstrapping the topic-dependent semantic classifiers from a small amount of labeled sentences. experiments have been conducted in the context of chinese public transportation information inquiry domain. the experimental results demonstrate the effectiveness of our proposed slu framework and show the possibility to reduce human labeling efforts significantly.
empirical study on the performance stability of named entity recognition model across domains. when a machine learning-based named entity recognition system is employed in a new domain, its performance usually degrades. in this paper, we provide an empirical study on the impact of training data size and domain information on the performance stability of named entity recognition models. we present an informative sample selection method for building high quality and stable named entity recognition models across domains. experimental results show that the performance of the named entity recognition model is enhanced significantly after being trained with these informative samples.
a hybrid markov/semi-markov conditional random field for sequence segmentation. markov order-1 conditional random fields (crfs) and semi-markov crfs are two popular models for sequence segmentation and labeling. both models have advantages in terms of the type of features they most naturally represent. we propose a hybrid model that is capable of representing both types of features, and describe efficient algorithms for its training and inference. we demonstrate that our hybrid model achieves error reductions of 18% and 25% over a standard order-1 crf and a semi-markov crf (resp.) on the task of chinese word segmentation. we also propose the use of a powerful feature for the semi-markov crf: the log conditional odds that a given token sequence constitutes a chunk according to a generative model, which reduces error by an additional 13%. our best system achieves 96.8% f-measure, the highest reported score on this test set.
entity annotation based on inverse index operations. entity annotation involves attaching a label such as 'name' or 'organization' to a sequence of tokens in a document. all the current rule-based and machine learning-based approaches for this task operate at the document level. we present a new and generic approach to entity annotation which uses the inverse index typically created for rapid key-word based searching of a document collection. we define a set of operations on the inverse index that allows us to create annotations defined by cascading regular expressions. the entity annotations for an entire document corpus can be created purely of the index with no need to access the original documents. experiments on two publicly available data sets show very significant performance improvements over the document-based annotators.
feature subsumption for opinion analysis. lexical features are key to many approaches to sentiment analysis and opinion detection. a variety of representations have been used, including single words, multi-word ngrams, phrases, and lexico-syntactic patterns. in this paper, we use a subsumption hierarchy to formally define different types of lexical features and their relationship to one another, both in terms of representational coverage and performance. we use the subsumption hierarchy in two ways: (1) as an analytic tool to automatically identify complex features that outperform simpler features, and (2) to reduce a feature set by removing unnecessary features. we show that reducing the feature set improves performance on three opinion classification tasks, especially when combined with traditional feature selection.
relevance feedback models for recommendation. we extended language modeling approaches in information retrieval (ir) to combine collaborative filtering (cf) and content-based filtering (cbf). our approach is based on the analogy between ir and cf, especially between cf and relevance feedback (rf). both cf and rf exploit users' preference/relevance judgments to recommend items. we first introduce a multinomial model that combines cf and cbf in a language modeling framework. we then generalize the model to another multinomial model that approximates the polya distribution. this generalized model outperforms the multinomial model by 3.4% for cbf and 17.4% for cf in recommending english wikipedia articles. the performance of the generalized model for three different datasets was comparable to that of a state-of-the-art item-based cf method.
sentiment retrieval using generative models. ranking documents or sentences according to both topic and sentiment relevance should serve a critical function in helping users when topics and sentiment polarities of the targeted text are not explicitly given, as is often the case on the web. in this paper, we propose several sentiment information retrieval models in the framework of probabilistic language models, assuming that a user both inputs query terms expressing a certain topic and also specifies a sentiment polarity of interest in some manner. we combine sentiment relevance models and topic relevance models with model parameters estimated from training data, considering the topic dependence of the sentiment. our experiments prove that our models are effective.
unsupervised relation disambiguation with order identification capabilities. we present an unsupervised learning approach to disambiguate various relations between name entities by use of various lexical and syntactic features from the contexts. it works by calculating eigen-vectors of an adjacency graph's laplacian to recover a submanifold of data from a high dimensionality space and then performing cluster number estimation on the eigenvectors. this method can address two difficulties encoutered in hasegawa et al. (2004)'s hierarchical clustering: no consideration of manifold structure in data, and requirement to provide cluster number by users. experiment results on ace corpora show that this spectral clustering based approach outperforms hasegawa et al. (2004)'s hierarchical clustering method and a plain k-means clustering method.
semantic role labeling via instance-based learning. this paper demonstrates two methods to improve the performance of instance-based learning (ibl) algorithms for the problem of semantic role labeling (srl). two ibl algorithms are utilized: k-nearest neighbor (knn), and priority maximum likelihood (pml) with a modified back-off combination method. the experimental data are the wsj23 and brown corpus test sets from the conll-2005 shared task. it is shown that applying the tree-based predicate-argument recognition algorithm (para) to the data as a preprocessing stage allows knn and pml to deliver f1: 68.61 and 71.02 respectively on the wsj23, and f1: 56.96 and 60.55 on the brown corpus; an increase of 8.28 in f1 measurement over the most recent published pml results for this problem (palmer et al., 2005). training times for ibl algorithms are very much faster than for other widely used techniques for srl (e.g. parsing, support vector machines, perceptrons, etc); and the feature reduction effects of para yield testing and processing speeds of around 1.0 second per sentence for knn and 0.9 second per sentence for pml respectively, suggesting that ibl could be a more practical way to perform srl for nlp applications where it is employed; such as realtime machine translation or automatic speech recognition.
quality assessment of large scale knowledge resources. this paper presents an empirical evaluation of the quality of publicly available large-scale knowledge resources. the study includes a wide range of manually and automatically derived large-scale knowledge resources. in order to establish a fair and neutral comparison, the quality of each knowledge resource is indirectly evaluated using the same method on a word sense disambiguation task. the evaluation framework selected has been the senseval-3 english lexical sample task. the study empirically demonstrates that automatically acquired knowledge resources surpass both in terms of precision and recall the knowledge resources derived manually, and that the combination of the knowledge contained in these resources is very close to the most frequent sense classifier. as far as we know, this is the first time that such a quality assessment has been performed showing a clear picture of the current state-of-the-art of publicly available wide coverage semantic resources.
phrasetable smoothing for statistical machine translation. we discuss different strategies for smoothing the phrasetable in statistical mt, and give results over a range of translation settings. we show that any type of smoothing is a better idea than the relative-frequency estimates that are often used. the best smoothing techniques yield consistent gains of approximately 1% (absolute) according to the bleu metric.
humor: prosody analysis and automatic recognition for f*r*i*e*n*d*s*. we analyze humorous spoken conversations from a classic comedy television show, friends, by examining acoustic-prosodic and linguistic features and their utility in automatic humor recognition. using a simple annotation scheme, we automatically label speaker turns in our corpus that are followed by laughs as humorous and the rest as non-humorous. our humor-prosody analysis reveals significant differences in prosodic characteristics (such as pitch, tempo, energy etc.) of humorous and non-humorous speech, even when accounted for the gender and speaker differences. humor recognition was carried out using standard supervised learning classifiers, and shows promising results significantly above the baseline.
partially supervised coreference resolution for opinion summarization through structured rule learning. combining fine-grained opinion information to produce opinion summaries is important for sentiment analysis applications. toward that end, we tackle the problem of source coreference resolution -- linking together source mentions that refer to the same entity. the partially supervised nature of the problem leads us to define and approach it as the novel problem of partially supervised clustering. we propose and evaluate a new algorithm for the task of source coreference resolution that outperforms competitive baselines.
extremely lexicalized models for accurate and fast hpsg parsing. this paper describes an extremely lexicalized probabilistic model for fast and accurate hpsg parsing. in this model, the probabilities of parse trees are defined with only the probabilities of selecting lexical entries. the proposed model is very simple, and experiments revealed that the implemented parser runs around four times faster than the previous model and that the proposed model has a high accuracy comparable to that of the previous model for probabilistic hpsg, which is defined over phrase structures. we also developed a hybrid of our probabilistic model and the conventional phrase-structure-based model. the hybrid model is not only significantly faster but also significantly more accurate by two points of precision and recall compared to the previous model.
solving the problem of cascading errors: approximate bayesian inference for linguistic annotation pipelines. the end-to-end performance of natural language processing systems for compound tasks, such as question answering and textual entailment, is often hampered by use of a greedy 1-best pipeline architecture, which causes errors to propagate and compound at each stage. we present a novel architecture, which models these pipelines as bayesian networks, with each low level task corresponding to a variable in the network, and then we perform approximate inference to find the best labeling. our approach is extremely simple to apply but gains the benefits of sampling the entire distribution over labels at each stage in the pipeline. we apply our method to two tasks -- semantic role labeling and recognizing textual entailment -- and achieve useful performance gains from the superior pipeline architecture.
unsupervised information extraction approach using graph mutual reinforcement. information extraction (ie) is the task of extracting knowledge from unstructured text. we present a novel unsupervised approach for information extraction based on graph mutual reinforcement. the proposed approach does not require any seed patterns or examples. instead, it depends on redundancy in large data sets and graph based mutual reinforcement to induce generalized "extraction patterns". the proposed approach has been used to acquire extraction patterns for the ace (automatic content extraction) relation detection and characterization (rdc) task. ace rdc is considered a hard task in information extraction due to the absence of large amounts of training data and inconsistencies in the available data. the proposed approach achieves superior performance which could be compared to supervised techniques with reasonable training data.
joint extraction of entities and relations for opinion recognition. we present an approach for the joint extraction of entities and relations in the context of opinion recognition and analysis. we identify two types of opinion-related entities --- expressions of opinions and sources of opinions --- along with the linking relation that exists between them. inspired by roth and yih (2004), we employ an integer linear programming approach to solve the joint opinion recognition task, and show that global, constraint-based inference can significantly boost the performance of both relation extraction and the extraction of opinion-related entities. performance further improves when a semantic role labeling system is incorporated. the resulting system achieves f-measures of 79 and 69 for entity and relation extraction, respectively, improving substantially over prior results in the area.
discriminative methods for transliteration. we present two discriminative methods for name transliteration. the methods correspond to local and global modeling approaches in modeling structured output spaces. both methods do not require alignment of names in different languages -- their features are computed directly from the names themselves. we perform an experimental evaluation of the methods for name transliteration from three languages (arabic, korean, and russian) into english, and compare the methods experimentally to a state-of-the-art joint probabilistic modeling approach. we find that the discriminative methods outperform probabilistic modeling, with the global discriminative modeling approach achieving the best performance in all languages.
automatic classification of citation function. citation function is defined as the author's reason for citing a given paper (e.g. acknowledgement of the use of the cited method). the automatic recognition of the rhetorical function of citations in scientific text has many applications, from improvement of impact factor calculations to text summarisation and more informative citation indexers. we show that our annotation scheme for citation function is reliable, and present a supervised machine learning framework to automatically classify citation function, using both shallow and linguistically-inspired features. we find, amongst other things, a strong relationship between citation function and sentiment classification.
detecting parser errors using web-based semantic filters. nlp systems for tasks such as question answering and information extraction typically rely on statistical parsers. but the efficacy of such parsers can be surprisingly low, particularly for sentences drawn from heterogeneous corpora such as the web. we have observed that incorrect parses often result in wildly implausible semantic interpretations of sentences, which can be detected automatically using semantic information obtained from the web. based on this observation, we introduce web-based semantic filtering---a novel, domain-independent method for automatically detecting and discarding incorrect parses. we measure the effectiveness of our filtering system, called woodward, on two test collections. on a set of trec questions, it reduces error by 67%. on a set of more complex penn treebank sentences, the reduction in error rate was 20%.
bestcut: a graph algorithm for coreference resolution. in this paper we describe a coreference resolution method that employs a classification and a clusterization phase. in a novel way, the clusterization is produced as a graph cutting algorithm, in which nodes of the graph correspond to the mentions of the text, whereas the edges of the graph constitute the confidences derived from the coreference classification. in experiments, the graph cutting algorithm for coreference resolution, called bestcut, achieves state-of-the-art performance.
random indexing using statistical weight functions. random indexing is a vector space technique that provides an efficient and scalable approximation to distributional similarity problems. we present experiments showing random indexing to be poor at handling large volumes of data and evaluate the use of weighting functions for improving the performance of random indexing. we find that random index is robust for small data sets, but performance degrades because of the influence high frequency attributes in large data sets. the use of appropriate weight functions improves this significantly.
style & topic language model adaptation using hmm-lda. adapting language models across styles and topics, such as for lecture transcription, involves combining generic style models with topic-specific content relevant to the target document. in this work, we investigate the use of the hidden markov model with latent dirichlet allocation (hmm-lda) to obtain syntactic state and semantic topic assignments to word instances in the training corpus. from these context-dependent labels, we construct style and topic models that better model the target document, and extend the traditional bag-of-words topic models to n-grams. experiments with static model interpolation yielded a perplexity and relative word error rate (wer) reduction of 7.1% and 2.1%, respectively, over an adapted trigram baseline. adaptive interpolation of mixture components further reduced perplexity by 9.5% and wer by a modest 0.3%.
statistical machine reordering. reordering is currently one of the most important problems in statistical machine translation systems. this paper presents a novel strategy for dealing with it: statistical machine reordering (smr). it consists in using the powerful techniques developed for statistical machine translation (smt) to translate the source language (s) into a reordered source language (s'), which allows for an improved translation into the target language (t). the smt task changes from s2t to s'2t which leads to a monotonized word alignment and shorter translation units. in addition, the use of classes in smr helps to infer new word reorderings. experiments are reported in the esen wmt06 tasks and the zhen iwslt05 task and show significant improvement in translation quality.
context-dependent term relations for information retrieval. co-occurrence analysis has been used to determine related words or terms in many nlp-related applications such as query expansion in information retrieval (ir). however, related words are usually determined with respect to a single word, without relevant information for its application context. for example, the word "programming" may be considered to be strongly related to "java", and applied inappropriately to expand a query on "java travel". to solve this problem, we propose to add another context word in the relation to specify the appropriate context of the relation, leading to term relations of the form "(java, travel) &rarr; indonesia". the extracted relations are used for query expansion in ir. our experiments on several trec collections show that this new type of context-dependent relations performs much better than the traditional co-occurrence relations.
two graph-based algorithms for state-of-the-art wsd. this paper explores the use of two graph algorithms for unsupervised induction and tagging of nominal word senses based on corpora. our main contribution is the optimization of the free parameters of those algorithms and its evaluation against publicly available gold standards. we present a thorough evaluation comprising supervised and unsupervised modes, and both lexical-sample and all-words tasks. the results show that, in spite of the information loss inherent to mapping the induced senses to the gold-standard, the optimization of parameters based on a small sample of nouns carries over to all nouns, performing close to supervised systems in the lexical sample task and yielding the second-best wsd systems for the senseval-3 all-words task.
corrective models for speech recognition of inflected languages. this paper presents a corrective model for speech recognition of inflected languages. the model, based on a discriminative framework, incorporates word n-grams features as well as factored morphological features, providing error reduction over the model based solely on word n-gram features. experiments on a large vocabulary task, namely the czech portion of the malach corpus, demonstrate performance gain of about 1.1--1.5% absolute in word error rate, wherein morphological features contribute about a third of the improvement. a simple feature selection mechanism based on x2 statistics is shown to be effective in reducing the number of features by about 70% without any loss in performance, making it feasible to explore yet larger feature spaces.
re-evaluating machine translation results with paraphrase support. in this paper, we present paraeval, an automatic evaluation framework that uses paraphrases to improve the quality of machine translation evaluations. previous work has focused on fixed n-gram evaluation metrics coupled with lexical identity matching. paraeval addresses three important issues: support for paraphrase/synonym matching, recall measurement, and correlation with human judgments. we show that paraeval correlates significantly better than bleu with human assessment in measurements for both fluency and adequacy.
lexical reference: a semantic matching subtask. semantic lexical matching is a prominent subtask within text understanding applications. yet, it is rarely evaluated in a direct manner. this paper proposes a definition for lexical reference which captures the common goals of lexical matching. based on this definition we created and analyzed a test dataset that was utilized to directly evaluate, compare and improve lexical matching models. we suggest that such decomposition of the global semantic matching task is critical in order to fully understand and improve individual components.
protein folding and chart parsing. how can proteins fold so quickly into their unique native structures? we show here that there is a natural analogy between parsing and the protein folding problem, and demonstrate that cky can find the native structures of a simplified lattice model of proteins with high accuracy.
a skip-chain conditional random field for ranking meeting utterances by importance. we describe a probabilistic approach to content selection for meeting summarization. we use skipchain conditional random fields (crf) to model non-local pragmatic dependencies between paired utterances such as question-answer that typically appear together in summaries, and show that these models outperform linear-chain crfs and bayesian models in the task. we also discuss different approaches for ranking all utterances in a sequence using crfs. our best performing system achieves 91.3% of human performance when evaluated with the pyramid evaluation metric, which represents a 3.9% absolute increase compared to our most competitive non-sequential classifier.
spmt: statistical machine translation with syntactified target language phrases. we introduce spmt, a new class of statistical translation models that use syntactified target language phrases. the spmt models outperform a state of the art phrase-based baseline model by 2.64 bleu points on the nist 2003 chinese-english test corpus and 0.28 points on a human-based quality metric that ranks translations on a scale from 1 to 5.
domain adaptation with structural correspondence learning. discriminative learning methods are widely used in natural language processing. these methods work best when their training and test data are drawn from the same distribution. for many nlp tasks, however, we are confronted with new domains in which labeled data is scarce or non-existent. in such cases, we seek to adapt existing models from a resource-rich source domain to a resource-poor target domain. we introduce structural correspondence learning to automatically induce correspondences among features from different domains. we test our technique on part of speech tagging and show performance gains for varying amounts of source and target training data, as well as improvements in target domain parsing accuracy using our improved tagger.
automatically assessing review helpfulness. user-supplied reviews are widely and increasingly used to enhance e-commerce and other websites. because reviews can be numerous and varying in quality, it is important to assess how helpful each review is. while review helpfulness is currently assessed manually, in this paper we consider the task of automatically assessing it. experiments using svm regression on a variety of features over amazon.com product reviews show promising results, with rank correlations of up to 0.66. we found that the most useful features include the length of the review, its unigrams, and its product rating.
distributional measures of concept-distance: a task-oriented evaluation. we propose a framework to derive the distance between concepts from distributional measures of word co-occurrences. we use the categories in a published thesaurus as coarse-grained concepts, allowing all possible distance values to be stored in a concept--concept matrix roughly .01% the size of that created by existing measures. we show that the newly proposed concept-distance measures outperform traditional distributional word-distance measures in the tasks of (1) ranking word pairs in order of semantic distance, and (2) correcting real-word spelling errors. in the latter task, of all the wordnet-based measures, only that proposed by jiang and conrath outperforms the best distributional concept-distance measures.
inducing temporal graphs. we consider the problem of constructing a directed acyclic graph that encodes temporal relations found in a text. the unit of our analysis is a temporal segment, a fragment of text that maintains temporal coherence. the strength of our approach lies in its ability to simultaneously optimize pairwise ordering preferences and global constraints on the graph topology. our learning method achieves 83% f-measure in temporal segmentation and 84% accuracy in inferring temporal relations between two segments.
fully automatic lexicon expansion for domain-oriented sentiment analysis. this paper proposes an unsupervised lexicon building method for the detection of polar clauses, which convey positive or negative aspects in a specific domain. the lexical entries to be acquired are called polar atoms, the minimum human-understandable syntactic structures that specify the polarity of clauses. as a clue to obtain candidate polar atoms, we use context coherency, the tendency for same polarities to appear successively in contexts. using the overall density and precision of coherency in the corpus, the statistical estimation picks up appropriate polar atoms among candidates, without any manual tuning of the threshold values. the experimental results show that the precision of polarity assignment with the automatically acquired lexicon was 94% on average, and our method is robust for corpora in diverse domains and for the size of the initial lexicon.
unsupervised discovery of a statistical verb lexicon. this paper demonstrates how unsupervised techniques can be used to learn models of deep linguistic structure. determining the semantic roles of a verb's dependents is an important step in natural language understanding. we present a method for learning models of verb argument patterns directly from unannotated text. the learned models are similar to existing verb lexicons such as verbnet and propbank, but additionally include statistics about the linkings used by each verb. the method is based on a structured probabilistic model of the domain, and unsupervised learning is performed with the em algorithm. the learned models can also be used discriminatively as semantic role labelers, and when evaluated relative to the propbank annotation, the best learned model reduces 28% of the error between an informed baseline and an oracle upper bound.
competitive generative models with structure learning for nlp classification tasks. in this paper we show that generative models are competitive with and sometimes superior to discriminative models, when both kinds of models are allowed to learn structures that are optimal for discrimination. in particular, we compare bayesian networks and conditional loglinear models on two nlp tasks. we observe that when the structure of the generative model encodes very strong independence assumptions (a la naive bayes), a discriminative model is superior, but when the generative model is allowed to weaken these independence assumptions via learning a more complex structure, it can achieve very similar or better performance than a corresponding discriminative model. in addition, as structure learning for generative models is far more efficient, they may be preferable for some tasks.
better informed training of latent syntactic features. we study unsupervised methods for learning refinements of the nonterminals in a treebank. following matsuzaki et al. (2005) and prescher (2005), we may for example split np without supervision into np[0] and np[1], which behave differently. we first propose to learn a pcfg that adds such features to nonterminals in such a way that they respect patterns of linguistic feature passing: each node's nonterminal features are either identical to, or independent of, those of its parent. this linguistic constraint reduces runtime and the number of parameters to be learned. however, it did not yield improvements when training on the penn treebank. an orthogonal strategy was more successful: to improve the performance of the em learner by treebank preprocessing and by annealing methods that split nonterminals selectively. using these methods, we can maintain high parsing accuracy while dramatically reducing the model size.
sentence ordering with manifold-based classification in multi-document summarization. in this paper, we propose a sentence ordering algorithm using a semi-supervised sentence classification and historical ordering strategy. the classification is based on the manifold structure underlying sentences, addressing the problem of limited labeled data. the historical ordering helps to ensure topic continuity and avoid topic bias. experiments demonstrate that the method is effective.
efficient search for inversion transduction grammar. we develop admissible a* search heuristics for synchronous parsing with inversion transduction grammar, and present results both for bitext alignment and for machine translation decoding. we also combine the dynamic programming hook trick with a* search for decoding. these techniques make it possible to find optimal alignments much more quickly, and make it possible to find optimal translations for the first time. even in the presence of pruning, we are able to achieve higher bleu scores with the same amount of computation.
exploiting discourse structure for spoken dialogue performance analysis. in this paper we study the utility of discourse structure for spoken dialogue performance modeling. we experiment with various ways of exploiting the discourse structure: in isolation, as context information for other factors (correctness and certainty) and through trajectories in the discourse structure hierarchy. our correlation and paradise results show that, while the discourse structure is not useful in isolation, using the discourse structure as context information for other factors or via trajectories produces highly predictive parameters for performance analysis.
is it really that difficult to parse german? this paper presents a comparative study of probabilistic treebank parsing of german, using the negra and t&uuml;ba-d/z tree-banks. experiments with the stanford parser, which uses a factored pcfg and dependency model, show that, contrary to previous claims for other parsers, lexicalization of pcfg models boosts parsing performance for both treebanks. the experiments also show that there is a big difference in parsing performance, when trained on the negra and on the t&uuml;ba-d/z treebanks. parser performance for the models trained on t&uuml;ba-d/z are comparable to parsing results for english with the stanford parser, when trained on the penn treebank. this comparison at least suggests that german is not harder to parse than its west-germanic neighbor language english.
short text authorship attribution via sequence kernels, markov chains and author unmasking: an investigation. we present an investigation of recently proposed character and word sequence kernels for the task of authorship attribution based on relatively short texts. performance is compared with two corresponding probabilistic approaches based on markov chains. several configurations of the sequence kernels are studied on a relatively large dataset (50 authors), where each author covered several topics. utilising moffat smoothing, the two probabilistic approaches obtain similar performance, which in turn is comparable to that of character sequence kernels and is better than that of word sequence kernels. the results further suggest that when using a realistic setup that takes into account the case of texts which are not written by any hypothesised authors, the amount of training material has more influence on discrimination performance than the amount of test material. moreover, we show that the recently proposed author unmasking approach is less useful when dealing with short texts.
statistical ranking in tactical generation. in this paper we describe and evaluate several statistical models for the task of realization ranking, i.e. the problem of discriminating between competing surface realizations generated for a given input semantics. three models (and several variants) are trained and tested: an n-gram language model, a discriminative maximum entropy model using structural information (and incorporating the language model as a separate feature), and finally an svm ranker trained on the same feature set. the resulting hybrid tactical generator is part of a larger, semantic transfer mt system.
automatic construction of predicate-argument structure patterns for biomedical information extraction. this paper presents a method of automatically constructing information extraction patterns on predicate-argument structures (pass) obtained by full parsing from a smaller training corpus. because pass represent generalized structures for syntactical variants, patterns on pass are expected to be more generalized than those on surface words. in addition, patterns are divided into components to improve recall and we introduce a support vector machine to learn a prediction model using pattern matching results. in this paper, we present experimental results and analyze them on how well protein-protein interactions were extracted from medline abstracts. the results demonstrated that our method improved accuracy compared to a machine learning approach using surface word/part-of-speech patterns.
broad-coverage sense disambiguation and information extraction with a supersense sequence tagger. in this paper we approach word sense disambiguation and information extraction as a unified tagging problem. the task consists of annotating text with the tagset defined by the 41 wordnet supersense classes for nouns and verbs. since the tagset is directly related to wordnet synsets, the tagger returns partial word sense disambiguation. furthermore, since the noun tags include the standard named entity detection classes -- person, location, organization, time, etc. -- the tagger, as a by-product, returns extended named entity information. we cast the problem of supersense tagging as a sequential labeling task and investigate it empirically with a discriminatively-trained hidden markov model. experimental evaluation on the main sense-annotated datasets available, i.e., semcor and senseval, shows considerable improvements over the best known "first-sense" baseline.
using linguistically motivated features for paragraph boundary identification. in this paper we propose a machine-learning approach to paragraph boundary identification which utilizes linguistically motivated features. we investigate the relation between paragraph boundaries and discourse cues, pronominalization and information structure. we test our algorithm on german data and report improvements over three baselines including a reimplementation of sporleder & lapata's (2006) work on paragraph segmentation. an analysis of the features' contribution suggests an interpretation of what paragraph boundaries indicate and what they depend on.
multilingual deep lexical acquisition for hpsgs via supertagging. we propose a conditional random field-based method for supertagging, and apply it to the task of learning new lexical items for hpsg-based precision grammars of english and japanese. using a pseudo-likelihood approximation we are able to scale our model to hundreds of supertags and tens-of-thousands of training sentences. we show that it is possible to achieve start-of-the-art results for both languages using maximally language-independent lexical features. further, we explore the performance of the models at the type- and token-level, demonstrating their superior performance when compared to a unigram-based baseline and a transformation-based learning approach.
an empirical approach to the interpretation of superlatives. in this paper we introduce an empirical approach to the semantic interpretation of superlative adjectives. we present a corpus annotated for superlatives and propose an interpretation algorithm that uses a wide-coverage parser and produces semantic representations. we achieve f-scores between 0.84 and 0.91 for detecting attributive superlatives and an accuracy in the range of 0.69--0.84 for determining the correct comparison set. as far as we are aware, this is the first automated approach to superlatives for open-domain texts and questions.
boosting unsupervised relation extraction by using ner. web extraction systems attempt to use the immense amount of unlabeled text in the web in order to create large lists of entities and relations. unlike traditional ie methods, the web extraction systems do not label every mention of the target entity or relation, instead focusing on extracting as many different instances as possible while keeping the precision of the resulting list reasonably high. ures is a web relation extraction system that learns powerful extraction patterns from unlabeled text, using short descriptions of the target relations and their attributes. the performance of ures is further enhanced by classifying its output instances using the properties of the extracted patterns. the features we use for classification and the trained classification model are independent from the target relation, which we demonstrate in a series of experiments. in this paper we show how the introduction of a simple rule based ner can boost the performance of ures on a variety of relations. we also compare the performance of ures to the performance of the state-of-the-art knowitall system, and to the performance of its pattern learning component, which uses a simpler and less powerful pattern language than ures.
lexicon acquisition for dialectal arabic using transductive learning. we investigate the problem of learning a part-of-speech (pos) lexicon for a resource-poor language, dialectal arabic. developing a high-quality lexicon is often the first step towards building a pos tagger, which is in turn the front-end to many nlp systems. we frame the lexicon acquisition problem as a transductive learning problem, and perform comparisons on three transductive algorithms: transductive svms, spectral graph transducers, and a novel transductive clustering method. we demonstrate that lexicon learning is an important task in resource-poor domains and leads to significant improvements in tagging accuracy for dialectal arabic.
graph-based word clustering using a web search engine. word clustering is important for automatic thesaurus construction, text classification, and word sense disambiguation. recently, several studies have reported using the web as a corpus. this paper proposes an unsupervised algorithm for word clustering based on a word similarity measure by web counts. each pair of words is queried to a search engine, which produces a co-occurrence matrix. by calculating the similarity of words, a word co-occurrence graph is obtained. a new kind of graph clustering algorithm called newman clustering is applied for efficiently identifying word clusters. evaluations are made on two sets of word groups derived from a web directory and wordnet.
modeling impression in probabilistic transliteration into chinese. for transliterating foreign words into chinese, the pronunciation of a source word is spelled out with kanji characters. because kanji comprises ideograms, an individual pronunciation may be represented by more than one character. however, because different kanji characters convey different meanings and impressions, characters must be selected carefully. in this paper, we propose a transliteration method that models both pronunciation and impression, whereas existing methods do not model impression. given a source word and impression keywords related to the source word, our method derives possible transliteration candidates and sorts them according to their probability. we evaluate our method experimentally.
paraphrase recognition via dissimilarity significance classification. we propose a supervised, two-phase framework to address the problem of paraphrase recognition (pr). unlike most pr systems that focus on sentence similarity, our framework detects dissimilarities between sentences and makes its paraphrase judgment based on the significance of such dissimilarities. the ability to differentiate significant dissimilarities not only reveals what makes two sentences a non-paraphrase, but also helps to recall additional paraphrases that contain extra but insignificant information. experimental results show that while being accurate at discerning non-paraphrasing dissimilarities, our implemented system is able to achieve higher paraphrase recall (93%), at an overall performance comparable to the alternatives.
semantic role labeling of nombank: a maximum entropy approach. this paper describes our attempt at nombank-based automatic semantic role labeling (srl). nombank is a project at new york university to annotate the argument structures for common nouns in the penn treebank ii corpus. we treat the nombank srl task as a classification problem and explore the possibility of adapting features previously shown useful in propbank-based srl systems. various nombank-specific features are explored. on test section 23, our best system achieves f1 score of 72.73 (69.14) when correct (automatic) syntactic parse trees are used. to our knowledge, this is the first reported automatic nombank srl system.
incremental integer linear programming for non-projective dependency parsing. integer linear programming has recently been used for decoding in a number of probabilistic models in order to enforce global constraints. however, in certain applications, such as non-projective dependency parsing and machine translation, the complete formulation of the decoding problem as an integer linear program renders solving intractable. we present an approach which solves the problem incrementally, thus we avoid creating intractable integer linear programs. this approach is applied to dutch dependency parsing and we show how the addition of linguistically motivated constraints can yield a significant improvement over state-of-the-art.
loss minimization in parse reranking. we propose a general method for reranker construction which targets choosing the candidate with the least expected loss, rather than the most probable candidate. different approaches to expected loss approximation are considered, including estimating from the probabilistic model used to generate the candidates, estimating from a discriminative model trained to rerank the candidates, and learning to approximate the expected loss. the proposed methods are applied to the parse reranking task, with various baseline models, achieving significant improvement both over the probabilistic models and the discriminative rerankers. when a neural network parser is used as the probabilistic model and the voted perceptron algorithm with data-defined kernels as the learning algorithm, the loss minimization model achieves 90.0% labeled constituents f1 score on the standard wsj parsing task.
learning information status of discourse entities. in this paper we address the issue of automatically assigning information status to discourse entities. using an annotated corpus of conversational english and exploiting morpho-syntactic and lexical features, we train a decision tree to classify entities introduced by noun phrases as old, mediated, or new. we compare its performance with hand-crafted rules that are mainly based on morpho-syntactic features and closely relate to the guidelines that had been used for the manual annotation. the decision tree model achieves an overall accuracy of 79.5%, significantly outperforming the hand-crafted algorithm (64.4%). we also experiment with binary classifications by collapsing in turn two of the three target classes into one and retraining the model. the highest accuracy achieved on binary classification is 93.1%.
text data acquisition for domain-specific language models. the language modeling community is showing a growing interest in using large collections of text mined from the world wide web (www) to supplement sparse in-domain text resources. however, in most cases the style and content of the text harvested from these corpora differs significantly from the specific nature of these domains. in this paper we present a relative entropy (r.e.) based method to select relevant subsets of sentences whose distribution in an n-gram sense matches the domain of interest. using simulations, we provide an analysis of how the proposed scheme outperforms filtering techniques proposed in recent language modeling literature on mining text from the web. a comparative study is presented using a text collection of over 800m words collected from the www. experimental results show that by using the proposed subset selection scheme we can get performance improvement in both word error rate (wer) and perplexity (ppl) over the models built from the entire collection by using just 10% of the data. improvements in data selection also translated to a significant reduction in the vocabulary size as well as the number of estimated parameters in the adapted language model.
restoring punctuation and capitalization in transcribed speech. adding punctuation and capitalization greatly improves the readability of automatic speech transcripts. we discuss an approach for performing both tasks in a single pass using a purely text-based n-gram language model. we study the effect on performance of varying the n-gram order (from n = 3 to n = 6) and the amount of training data (from 58 million to 55 billion tokens). our results show that using larger training data sets consistently improves performance, while increasing the n-gram order does not help nearly as much.
joint source/relay precoders design in amplify-and-forward relay systems: a geometric mean decomposition approach. existing precoder designs for an amplify-and-forward (af) cooperative system often assume a linear receiver at the destination, and a precoder at the relay. the performance enhancement of such a system is then limited. in this paper, we consider a nonlinear successive interference cancellation (sic) receiver, and at the same time take the source precoder into consideration. using the geometric mean decomposition (gmd), we propose a joint source/relay precoders design method, fully exploring information provided by direct and relay links. with our method, the design problem can be transformed to a standard scalar concave optimization problem, and a closed-form solution can be obtained. simulations show that the proposed design can significantly enhance the performance of a mimo af cooperative system.
full covariance state duration modeling for hmm-based speech synthesis. this paper proposes a state duration modeling method using full covariance matrix for hmm-based speech synthesis. in this method, a full covariance matrix instead of the conventional diagonal covariance matrix is adopted in the multi-dimensional gaussian distribution to model the state duration of each context-dependent phoneme. at synthesis stage, the state durations are predicted using the clustered context-dependent distributions with full covariance matrices. experimental results show that the synthesized speech using full-covariance state duration models is more natural than the conventional method when we change the speaking rate of synthesized speech.
what happens when cognitive terminals compete for a relaying node? we introduce a new channel, which consists of an interference channel (ic) in parallel with an interference relay channel (irc), to analyze the interaction between two selfish and cognitive transmitters who compete for a relay implementing the amplify-and-forward protocol. it is shown that whatever the relay location there is always an equilibrium in the resource allocation game where the users selfishly share their power between the ic and irc. the uniqueness and determination of this equilibrium is analyzed for two cases: the relay amplification gain is fixed; the irc direct links are negligible. we show how to exploit this analysis to optimally locate the relay either in terms of individual rate or system sum-rate. simulations are provided and show, in particular, how the users' selfish behavior leads to sharing the space in regions where the relay is used by only one user or not used at all.
analog flat filter design. this paper proposes a systematic approach for the design of a general class of analog infinite-impulse-response (iir) filters, which includes all well-known classical analog filters as a special case. all specifications including the conventional ones and also filter flatness degrees are explicitly incorporated into design process. several numerical examples are presented to demonstrate the efficiency and flexibility of the proposed method.
vector perturbation precoding for receivers with limited dynamic range. in this paper we consider the vector perturbation (vp) precoding scheme for the multiuser miso broadcast channel proposed by hochwald et al. under the practical assumption that the receivers have limited dynamic range. in this case, vp precoding is shown to suffer from an error floor at high signal-to-noise ratio (snr). as an alternative, we propose precoding with restricted vp (rvp), which takes the limited dynamic range of the receivers explicitly into account by restricting to a finite set of possible perturbation vectors at the transmitter side. we derive the diversity order of this rvp scheme and show that no error floor occurs and that the performance is superior to vp for the entire range of snrs.
rate-constrained distributed distance testing and its applications. we investigate a practical approach to solving one instantiation of a distributed hypothesis testing problem under severe rate constraints that shows up in a wide variety of applications such as camera calibration, biometric authentication and video hashing: given two distributed continuous-valued random sources, determine if they satisfy a certain euclidean distance criterion. we show a way to convert the problem from continuous-valued to binary-valued using binarized random projections and obtain rate savings by applying a linear syndrome code. in finding visual correspondences, our approach uses just 49% of the rate of scalar quantization to achieve the same level of retrieval performance. to perform video hashing, our approach requires only a hash rate of 0.0142 bpp to identify corresponding groups of pictures correctly.
compressed sensing and multistatic sar. we demonstrate that the remarkable advantages of compressed sensing remain in force when the information operator is constrained to obey the physical rules of a multistatic sar measurement. the design guidelines of the sar information operator for ℓ2 reconstructions is compared to those provided for generic ℓ1 reconstructions. we report little or no degradation in compression performance when using an information operator obeying sar sampling constraints. simulations for a shepp-logan image show an image is faithfully reconstructed when the number of measurements is about a third of the number of image pixels, using a minimum total-variation technique. we observed high sensitivity in performance and algorithm convergence to small perturbations in the measurement vectors.
distributed beamforming for wireless sensor networks with random node location. due to the unsupervised nature of wireless sensor networks (wsns), intensive communications are required among the selected nodes to reach a consensus and synchronize prior to entering a distributed beamforming (dbf) procedure. therefore, a sensible approach to select the nodes should not only take into account the required beampattern, but also should aim to preserve the inter-node connectivity and the network energy. we show for a uniformly distributed wsn that when the nodes are selected from a ring of proper radii, the resulting beampattern mainlobe is narrower compared to that of the classical dbf technique proposed in [1]. at the same time, our proposed technique may preserve a substantial amount of network energy and reduce the probability of network disconnectivity. directivity of the proposed dbf technique is analyzed and an extension of the technique to a multi-ring case is presented. it is shown that the sidelobe peaks can be considerably decreased if the nodes are selected from multiple concentric rings.
a weighted logarithmic merit function for canonical correlation analysis. a weighted logarithmic merit function that incorporates a diagonal matrix is utilized for deriving a gradient dynamical system that converges to the actual canonical correlation coordinates of arbitrary data matrices. the equilibrium points of the resulting gradient system are determined and their stability is thoroughly analyzed. qualitative properties of the proposed systems are analyzed in detail including the limit of solutions as time approaches infinity. the performance of this system is also examined. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
new discrete inverse s transform with least square error in filtering. the s transform is a useful linear time-frequency distribution and has been applied to various fields. since the inverse s transform is an over-determined problem, there exist several different algorithms, which result in different filtering effects. this paper models the discrete s transform in matrix form and proposes a new inverse s transform algorithm with least square error in filters. this paper also compares the new inverse s transform with the previous ones.
low bitrate audio coding using generalized adaptive gain shape vector quantization across channels. audio coding at low bitrates suffers from artifacts due to spectrum truncation. typical audio codecs code multi-channel sources using transforms across the channels to remove redundancy such as middle (mid) - side (m/s) coding. at low bitrates, the spectrum of the coded channels is truncated and the spectrum of the channels with lower energy, such as the side channel, is truncated severely, sometimes entirely. this results in a muffled sound due to truncation of all coded channels beyond a certain frequency. it also results in a loss of spatial image even at low frequencies due to severe truncation of the side channel. previously we have developed a low bitrate coding method to combat the loss of higher frequencies caused by spectrum truncation. in this paper, we present a novel low bitrate audio coding scheme to mitigate the loss of spatial image. listening tests show that the combination of the two low bitrate coding methods results in a audio codec that can get good quality even at bitrates as low as 32kbps for stereo content with low decoder complexity.
optimum multi-target detection using an anc neuro-fuzzy scheme and wideband replica correlator. an optimum target detection algorithm is developed for underwater active wideband sonar signal in the presence of reverberation and ambient noise. the hybrid algorithm makes use of an adaptive anc neuro-fuzzy scheme in the first instance to provide an effective fine tuned signal followed by an iterative cross correlation-based target motion estimation (tme) scheme for efficient target detection. computer simulations based on real input data sets demonstrate capability and efficiency of the proposed hybrid algorithm in extracting even zero-doppler target signals from a highly reverberated noisy environment.
eeg signal classification using nonlinear independent component analysis. one of the preprocessors can be used to improve the performance of brain-computer interface (bci) systems is independent component analysis (ica). ica is a signal processing technique in which observed random data are transformed into components that are statistically independent from each other. this suggests the possibility of using ica to separate different independent brain activities during motor imagery into separate components. however, there is no guarantee for linear combination of brain sources in eeg signals. thus the identification of nonlinear dynamic of eeg signals should be taken into consideration. in this paper, a new method is proposed for eeg signal classification in bci systems by using nonlinear ica algorithm. the effectiveness of the proposed method is evaluated by using the classification of eeg signals. the tasks to be discriminated are the imaginative hand movement and the resting state. the results demonstrate that the proposed method performed well in several experiments on different subjects and can improve the classification accuracy in the bci systems.
time-space-sequential algorithms for distributed bayesian state estimation in serial sensor networks. we consider distributed estimation of a time-dependent, random state vector based on a generally nonlinear/non-gaussian state-space model. the current state is sensed by a serial sensor network without a fusion center. we present an optimal distributed bayesian estimation algorithm that is sequential both in time and in space (i.e., across sensors) and requires only local communication between neighboring sensors. for the linear/gaussian case, the algorithm reduces to a time-space-sequential, distributed form of the kalman filter. we also demonstrate the application of our state estimator to a target tracking problem, using a dynamically defined “local sensor chain” around the current target position.
new strategies for pronunciation by analogy. the synthesis quality is influenced by many important factors, among which the correctness of the grapheme-to-phoneme (g2p) conversion is one of the crucial ones. automatic letter-to-sound systems have been in the center of attention for the last decade. one of the most effective and promising methods resulted to be the so-called “pronunciation by analogy” method [8], based on the analogy in the grapheme context, allowing derivation of the correct pronunciation for a new word from the parts of similar words present in the dictionary. this paper aims at further development of this method. novel scoring strategies for determining the best pronunciations were proposed. a word error rate reduction of 1.5–2.5 percent is obtained. a detailed analysis shows that one of the new strategies consistently outperforms the others. the results obtained are compared to other g2p methods using the same data.
minimum generation error training by using original spectrum as reference for log spectral distortion measure. this paper improves a minimum generation error (mge) based hmm training technique for hmm-based speech synthesis by directly using the original spectrum instead of line spectral pairs (lsps) as reference spectrum for log spectral distortion (lsd) measure. two types of original reference spectra for lsd calculation are investigated, including the spectrum extracted from speech waveform by straight, and the short-time fft spectrum calculated from speech waveforms. since only the harmonics of the fft spectrum are coincident with the underlying spectral envelope, the lsd between generated lsps and original fft spectrum is calculated by sampling at the harmonic frequencies, and a weighting function is designed to simulate the sampling strategy on lsps. from the experimental results, the mge-lsd training using the fft spectrum as reference spectrum achieved the best performance.
distributed adaptive estimation of correlated node-specific signals in a fully connected sensor network. we introduce a distributed adaptive estimation algorithm operating in an ideal fully connected sensor network. the algorithm estimates node-specific signals at each node based on reduced-dimensionality sensor measurements of other nodes in the network. if the node-specific signals to be estimated are linearly dependent on a common latent process with a low dimension compared to the dimension of the sensor measurements, the algorithm can significantly reduce the required communication bandwidth and still provide the optimal linear estimator at each node as if all sensor measurements were available in every node. because of its adaptive nature and fast convergence properties, the algorithm is suited for real-time applications in dynamic environments, such as speech enhancement in acoustic sensor networks.
diffusion least-mean squares with adaptive combiners. this paper presents an efficient adaptive combination strategy for diffusion algorithms over adaptive networks in order to improve the robustness against the spatial variation of snr over the network. the diffusion least-mean square (lms) algorithm with the proposed combination rule and its mean transient analysis are included. simulation results show that the diffusion lms algorithm with our combiners outperforms those with existing static combiners and the incremental lms algorithm.
understanding the method of interval errors from the information theory perspective. nonlinear parameter estimation often displays a threshold phenomenon, that is, below certain signal-to-noise ratio (snr) the estimation mean-square error (mse) increases dramatically. the method of interval errors (mie) has been shown to provide accurate mse prediction of related nonlinear techniques well into the estimation threshold region, yet relatively simple and robust in evaluation compared to a global performance bound. however those features have not been understood on a strict theoretical basis. this paper investigates numerical sensitivity of the mie to parameter sampling resolution, aiming to understanding, from information theory perspective, the underlying mechanism leading to robust mse approximation. a recently-developed information theory resolution bound is reinterpreted and applied to specify the parameter sampling resolution. numerical evaluation of the relevant results for array-based bearing estimation supports the proposed connection between the resolution bound and the mie.
robust joint localization and time synchronization in wireless sensor networks with bounded anchor uncertainties. a unified framework to jointly solve the problems of localization and synchronization at the same time is presented in this paper. the joint approach is attractive because it can solve both localization and synchronization using the same set of message exchanges, which is extremely important for energy saving in wireless sensor networks. the inaccuracy of anchor locations and timings is taken into account to provide accurate joint localization and synchronization. the anchor uncertainties are assumed to be bounded, but knowledge of the statistics of anchor uncertainties is not required. the problem is formulated into a linear model with uncertainties on both sides of the equation. a robust joint estimator is then proposed based on minimizing the worst-case mean square error and the solution is obtained by solving a semidefinite programming problem. simulation results show that the proposed estimator outperforms the traditional least squares estimator at the cost of higher computational complexity.
centra catadioptric camera calibration with single image. central catadioptric camera is a class of omnidirectional sensor having single effective viewpoint with reflective surfaces and lenses. this work studies the geometry of central catadioptric projection of a set of lines and adopts it into calibration. in this paper, we propose a practical calibration method for central catadioptric cameras by manually labeling the corners on planar grids. this method analytically parameterizes the intersection of a set of lines, regardless whether they are parallel or not. algebraic distance is introduced in order to robustify this method since the conic which is the projection of line, is difficult to be obtained precisely. moreover, it is proved that central catadioptric is able to calibrate by at least one image with two lines. the performance of this method is validated by both simulation data and real image data.
automatic visual-only language identification: a preliminary study. we describe experiments in visual-only language identification, in which only lip-shape and lip-motion are used to determine the language of a spoken utterance. we focus on the task of discriminating between two or three languages spoken by the same speaker, and we have recorded a suitable database for these experiments. we use a standard audio language identification approach in which the feature vectors are tokenized and then a language model for each language is estimated over a stream of tokens. although rate of speaking appeared to affect our results, it was found that different languages spoken at rather similar speeds were as well discriminated as a single language spoken at three extreme speeds, indicating that there is a language effect present in our results.
on the importance of modeling temporal information in music tag annotation. music is an art form in which sounds are organized in time; however, current approaches for determining similarity and classification largely ignore temporal information. this paper presents an approach to automatic tagging which incorporates temporal aspects of music directly into the statistical models, unlike the typical bag-of-frames paradigm in traditional music information retrieval techniques. vector quantization on song segments leads to a vocabulary of acoustic segment models. an unsupervised, iterative process that cycles between viterbi decoding and baum-welch estimation builds transcripts of this vocabulary. latent semantic analysis converts the song transcriptions into a vector for subsequent classification using a support vector machine for each tag. experimental results demonstrate that the proposed approach performs better in 15 of the 18 tags. further analysis demonstrates an ability to capture local timbral characteristics as well as sequential arrangements of acoustic segment models.
joint estimation of signal and noise correlation matrices and its application to inverse filtering. noise suppression by linear filters for a time series is discussed. we propose a method for jointly estimating signal and noise correlation matrices by incorporating steering vectors of the noise or eigenvectors of the noise correlation matrix as well as steering vectors of the target signals. our estimates bring us two significant advantages. one is reduction of computational cost in obtaining the wiener filter since the wiener post filter, which is combined to the minimum variance distortionless response filter (mvdrf), is no longer needed with the estimates of signal and noise correlation matrices. the other is an improvement of the performance of the mvdrf since we can construct the regularized version of it with an estimate of the noise correlation matrix.
low-complexity frequency-domain turbo equalization for single-carrier transmissions over doubly-selective channels. single-carrier transmissions with frequency-domain equalization have gained much interest due to their comparable complexity and performance to ofdm, which conversely suffers from a high peak-to-average power ratio. in this paper, we develop a new frequency-domain block turbo equalizer for single-carrier (sc) transmissions over doubly-selective channels. the main feature of the proposed equalizer is its low complexity, which is only linear in the block length. a comparison between sc and ofdm systems with channel coding in doubly-selective channels is also given.
aspect modeling of parsed representation for image retrieval. a probabilistic framework based on a universal source coding for content-based image retrieval is proposed. by a multidimensional incremental parsing technique, which is an extension of the lempel-ziv incremental parsing algorithm, a given image is parsed into a number of variable-size rectangular blocks, called parsed representations. to achieve a semantically relevant pattern matching, we introduce a new similarity measure from the first- and second-order statistics of given image patches. once the occurrence patterns of images in the corpus are analyzed, the term-document joint distribution is estimated by an aspect modeling technique under the assumption of latent aspects. to compare the performance of the proposed image retrieval framework based on the parsed representations, we implement a benchmark system based on the fixed-shape block representations trained by vector quantization. in addition to these two systems, we bring two content-based image retrieval systems into the performance evaluation. the experimental results on a database of 20,000 natural scene images demonstrate that the proposed image retrieval system significantly outperforms other existing and the benchmark systems.
multiview video compression and streaming based on predicted viewer position. recent technological advances have made possible a number of new applications in the area of 3d video. one of the enabling technologies for many of these 3d applications is multiview video coding, which has received significant attention in the last several years. however, the fundamental need of multiview coding for applications like immersive tele-conferencing has not been addressed. in this paper we define the boundaries of the problem, and show how a simple algorithm can yield gains of up to 2× reduction in bitrate with similar psnr in the synthesized view. our algorithm is based on using an estimate of the viewer position to compute the expected contribution of each pixel to the synthesized view, and encoding each macroblock of each camera views with quality proportional to the likelihood that the pixel will be used in the synthetic image.
probablistic modelling of f0 in unvoiced regions in hmm based speech synthesis. hmm based synthesis has attracted great interest due to its compact and flexible modelling of spectral and prosodic parameters. in this approach, short term spectra, fundamental frequency (f0) and duration are simultaneously modelled by multi-stream hmms. however, since f0 values in unvoiced regions are normally considered as undefined, it is difficult to use standard hmms for f0 modelling. the currently preferred solution to this is to use a multi-space distribution hmm (msdhmm) in which discrete distributions are used for modelling the voiced/unvoiced decision and continuous gaussian distributions are used for modelling the f0 values within the voiced regions. however, the assumption of undefined unvoiced f0 regions and the special structure of the msdhmm lead to limitations in the accurate modelling of f0 patterns. in this paper an alternative is explored whereby unvoiced f0 values are assumed to exist and are modelled within the standard hmm framework using a globally tied distribution (gtd). subjective evaluations show that these regular hmms with gtd can produce significant improvements in the naturalness of the synthesised speech compared to the msdhmm, and furthermore, the method is insensitive to the exact method used for unvoiced f0 generation.
modeling of contours in wavelet domain for generalized lifting image compression. this paper introduces the design of context-based models of contours in the wavelet domain, which are used to construct generalized lifting (gl) mappings for image compression. the gl context-based mapping may significantly reduce the signal energy and the resulting bitrate. here, we propose a strategy to define a reduced set of structured models to design the gl. the models capture the contour structures and are contrast-invariant. initial experimental results applying the strategy on a wavelet subband exhibit potential gains. iterations of the gl scheme as well as an adaptive entropy coding strategy may increase the coding gain.
unsupervised pronunciation validation. this paper addresses selecting between candidate pronunciations for out-of-vocabulary words in speech processing tasks. we introduce a simple, unsupervised method that outperforms the conventional supervised method of forced alignment with a reference. the success of this method is independently demonstrated using three metrics from large-scale speech tasks: word error rates for large vocabulary continuous speech recognition, decision error tradeoff curves for spoken term detection, and phone error rates compared to a handcrafted pronunciation lexicon. the experiments were conducted using state-of-the-art recognition, indexing, and retrieval systems. the results were compared across many terms, hundreds of hours of speech, and well known data sets.
sound localisation with a silicon cochlea pair. a neuromorphic sound localisation system is proposed. it employs two microphones and a pair of silicon cochleae with address event interface for front-end processing. this allows subsequent processing to be implemented with spike-based algorithms. the system is adaptive and supports online learning. its localisation capability was tested with white noise and pure tone stimuli, with an average error of around 3° in the −45° to 45° range.
investigating glottal parameters for differentiating emotional categories with similar prosodics. speech prosodics (i.e., pitch, energy, etc.) play an important role in the interpretation of emotional expression. however, certain pairs of emotions can be difficult to discriminate due to similar displayed tendencies in prosodic statistics. the purpose of this paper is to target speaker dependent expressions of emotional pairs that share statistically similar prosodic information and investigate a set of glottal features for their ability to find measurable differences in these expressions. evaluation is based on acted emotional utterances from the emotional prosody and speech transcript (epst) database. while it is in no way assumed that acted speech provides a complete picture of authentic emotion, the value of this information is that the actors adjusted their voice quality to fit their perception of different emotions. results show statistically significant differences (p ≪ 0.05) in at least one glottal feature for all 30 emotion pairs where prosodic features did not show a significant difference. in addition, the use of single glottal features reduced classification error for 24 emotion pairs in comparison to pitch or energy.
small-group learning projects to make signal processing more appealing: from speech processing to ofdma synchronization. whereas lecturing is the most widely used mode of instruction, we have explored small-group learning projects to make signal processing more appealing at the university and in engineering schools in bordeaux (france). the projects cover a wide range of applications, from audio processing to mobile communication system analysis and can be based on problems suggested by industrial partners. after a state of the art in the area, the students develop signal processing algorithms and usually deliver new softwares. at the end of the semester, they provide a final 8-page report and present their work during a one-day workshop. the projects enable the students to experience cooperative works, which is mostly done in industry. in addition, they help the students to see more easily the links between the courses they follow, including project managing. the students are hence involved in dialog inside their own group, in writing english reports as well as in problem solving, analysis and synthesis. this paper presents four examples dealing with speech processing, spectral analysis, universal mobile telecommunications system (umts) mobile positioning and orthogonal frequency division multiple access (ofdma) synchronization.
progressive distributed estimation over noisy channels in wireless sensor networks. this paper presents a new progressive distributed estimation scheme (des) along with the power scheduling among sensors under awgn channels. the progressive des consists of a transmission bit allocation scheme and a quasi best linear unbiased estimate (blue) of the unknown parameter at each sensor. this scheme is shown to outperform the traditional progressive des. moreover, the power scheduling among sensors, which minimizes the total transmission power subject to the desired mse performance tolerance, is formulated as a convex problem and the optimal solution is derived analytically.
a new method for speaker adaptation using bilinear model. in this paper, a novel method for speaker adaptation using bilinear model is proposed. bilinear model can express both characteristics of speakers (style) and phonemes across speakers (content) independently in a training database. the mapping from each speaker and phoneme space to observation space is carried out using bilinear mapping matrix which is independent of speaker and phoneme space. we apply the bilinear model to speaker adaption. using adaptation data from a new speaker, speaker-adapted model is built by estimating the style(speaker)-specific matrix. experimental results showed that the proposed method outperformed eigenvoice and mllr. in vocabulary-independent isolated word recognition for speaker adaptation, bilinear model reduced word error rate by about 38% and about 10% compared to eigenvoice and mllr respectively using 50 words for adaptation.
transcription and expressiveness detection system for violin music. in this paper, a transcription system for music played by violin is presented. the transcription system not only detects the pitch and duration of the notes but also identifies successfully the employed technique to play each note: détaché with and without accent and with and without vibrato, pizzicato, tremolo, spiccato and flageolett-töne. the transcription system is based on a combined analysis of the time domain and frequency domain properties of the music signal.
speaker recognition using syllable-based constraints for cepstral frame selection. we describe a new gmm-ubm speaker recognition system that uses standard cepstral features, but selects different frames of speech for different subsystems. subsystems, or “constraints”, are based on syllable-level information and combined at the score level. results on both the nist 2006 and 2008 test data sets for the english telephone train and test condition reveal that a set of eight constraints performs extremely well, resulting in better performance than other commonly-used cepstral models. given the still largely-unexplored world of possible constraints and combinations, it is likely that the approach can be even further improved.
multiple-peak model fitting function for dct sign phase correlation with non-integer shift precision. we propose two fitting functions for shift estimation using discrete cosine transform sign phase correlation (dct-spc) with non-integer accuracy. the dct-spc can be used in order to estimate the shift values and the similarity between two signals. however, the estimated shift values are limited to integer numbers. the proposed fitting functions enable the dct-spc to estimate the non-integer shift values using only the sign of the dct coefficients. the multiple-peak model in the proposed fitting functions provides more accurate values than other models. simulations are presented to demonstrate the effectiveness of the proposed fitting functions.
copulas based multivariate gamma modeling for texture classification. this paper deals with texture modeling for classification or retrieval systems using multivariate statistical features. the proposed features are defined by the hyperparameters of a copula-based multivariate distribution characterizing the coefficients provided by image decomposition in scale and orientation. as it belongs to the multivariate stochastic models, the copulas are useful to describe pairwise non-linear association in the case of multivariate non-gaussian density. in this paper, we propose the d-variate gaussian copula associated to univariate gamma densities for modeling the texture. experiments were conducted on the vistex database aiming to compare the recognition rates of the proposed model with the univariate generalized gaussian model, the univariate gamma model, and the generalized gaussian copula-based multivariate model.
data pruning-based compression using high order edge-directed interpolation. this paper proposes a data pruning-based compression scheme to improve the rate-distortion relation of compressed images and video sequences. the original frames are pruned to a smaller size before compression. after decoding, they are interpolated to their original size by an edge-directed interpolation. the data pruning is optimized to obtain the minimal distortion in the interpolation phase. furthermore, a novel high order interpolation is proposed to adapt the interpolation to many edge directions. this high order filtering uses extra surrounding pixels and achieves more robust edge-directed image interpolation. simulation results are shown for both image interpolation and coding applications.
head-mounted active noise control system for mr noise. recently, magnetic resonance imaging (mri) devices are used in many medical institutions on the grounds of safety and convenience. an open-configuration mr system is introduced at shiga university of medical science in order to conduct microwave coagulation therapy by using near-real-time mr images. however, this system has a fatal defect. when mri device works to take images, it also generates serious noises (mr noise). hence, an operator and other medical staff (ex. nurses and anesthetists) suffer from mr noise and cannot communicate with each other during the operation. in this paper, we therefore propose a head-mounted anc system in order to reduce the mr noise, and some experimental results demonstrate cancellation performance of the system implemented by digital signal processor (dsp).
the i4u system in nist 2008 speaker recognition evaluation. this paper describes the performance of the i4u speaker recognition system in the nist 2008 speaker recognition evaluation. the system consists of seven subsystems, each with different cepstral features and classifiers. we describe the i4u primary system and report on its core test results as they were submitted, which were among the best-performing submissions. the i4u effort was led by the institute for infocomm research, singapore (iir), with contributions from the university of science and technology of china (ustc), the university of new south wales, australia (unsw), nanyang technological university, singapore (ntu) and carnegie mellon university, usa (cmu).
maximizing the continuity in segmentation - a new approach to model, segment and recognize speech. this paper presents a new approach to speech modeling and recognition. the new approach consists of a statistical model to represent up to sentence-long temporal dynamics in the training data, and an algorithm to identify the matching segments with maximum continuities between the training and testing sentences. recognition is performed by combining the longest matching segments found from the training sentences. because of their richer and more distinct temporal dynamics, longer speech segments as whole units can be recognized with lower error rates than shorter speech segments. therefore basing recognition on the longest matching segments optimizes the discrimination and hence recognition of speech. the new approach has been evaluated on the timit database for identifying matching speech segments. the results obtained are encouraging given the very low parametric complexity of the new model. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
multi-channel audio segmentation for continuous observation and archival of large spaces. in most real-world situations, a single microphone is insufficient for the characterization of an entire auditory scene. this often occurs in places such as office environments which consist of several interconnected spaces that are at least partially acoustically isolated from one another. to this end, we extend our previous work on segmentation of natural sounds to perform scene characterization using a sparse array of microphones, strategically placed to ensure that all parts of the environment are within range of at least one microphone. by accounting for which microphones are active for a given sound event, we perform a multi-channel segmentation that captures sound events occurring in any part of the space. the segmentation is inferred from a custom dynamic bayesian network (dbn) that models how event boundaries influence changes in audio features. example recordings illustrate the utility of our approach in a noisy office environment.
multiple time resolution analysis of speech signal using mce training with application to speech recognition. in this paper, we propose two methods of multiple time-resolution analysis of speech and their application to automatic speech recognition (asr). constant frame-rate multi-scale analysis is proposed based on a box of multi-scale features. then a variable rate analysis is proposed based on the selection of the optimal temporal resolution on the fly by a properly trained non-linear classifier unit. the classifier's parameters are trained using the discriminative method of minimum classification error (mce) training. we use the recently proposed conditional random fields (crf) phonetic recognition system that effectively combines highly correlated features. results are reported on a frame-wise classification task and also on timit phone recognition task. results show that (i) crfs can effectively combine multi-scale features and (ii) mce trained variable rate crfs are competitive with the “box” combination method.
modeling and tracking of faces in real-life illumination conditions. in this paper, we address the problem of face tracking across illumination changes and occlusions. the method is based on leveraging the strengths of both adaboost to deal with clutter and the image based parametric illumination model proposed by kale and jaynes. we show that a simple non-linear transformation of the adaboost score multiplied with the illumination compensated likelihood leads to a fast robust tracking paradigm. we demonstrate the ability of our method to detect occlusions at the same time ensuring that mis-assignments between the occluder and the occluded does not occur. we present experimental results of our method on low resolution surveillance indoor and outdoor videos using an off the shelf dsp. we also demonstrate the power of the parametric illumination model for pose constrained face recognition when matching across known illumination conditions.
phase unwrapping for interferometric sar using multibaseline joint data group. phase unwrapping is the key problem in building the digital elevation model (dem) of a scene from interferometric synthetic aperture radar (sar) system data. in this paper, we propose a method of phase unwrapping based on the model of the multibaseline joint data group. the method can not only adaptively coregister the sar images, but also accurately provide the accurate estimation of the terrain unwrapped phase in the presence of the large coregistration errors. moreover, the improvement in computational complexity is achieved by using the multibaseline joint data group. the method is investigated by simulations, and results show successful phase unwrapping even if the image coregistration error is close to one pixel.
the dsp of money. this paper discusses a simple framework that can be used to connect a significant number of the tools and techniques developed in a first course in either discrete-time signals and systems or digital signal processing. while this framework is not revolutionary, it allows for the rapid placement of new material into the course's context. additionally, a simple model of an unstable financial system allows for a rapid introduction and overview of the course while observably increasing student interest and motivation. in these challenging economic times, it is somewhat reassuring to know that some unstable financial accounts are actually a good thing.
cubic higher-order criterion and algorithm for blind extraction of a source signal. the paper deals with the problem of the blind extraction of a source signal after a mimo convolutive mixture. the extraction is performed using a miso equalizer. a contrast function based on high order statistics is first proposed. it is more general than the existing contrast in the same context and exhibits a cubic dependence w.r.t. the unknown equalizer parameters. this allows us to propose a new extraction algorithm based on a third order tensor decomposition. computer simulations illustrate the good behavior and the usefulness of our algorithm.
a custom-designed mental task-based brain-computer interface. at present, brain-computer interfaces cannot be used in real-life applications mainly because of their high false activation rates. to achieve a zero false positive rate, a mental task-based brain-computer interface custom designed for each subject and each task is proposed. the most discriminatory mental task is determined for each subject. we used the eeg signals of four subjects recorded while they were performing five different mental tasks. autoregressive modeling and stationary wavelet transform are used in the process of feature extraction. classification is based on quadratic discriminant analysis. for the most discriminatory mental task of each subject, we achieved a false positive rate of zero value while the true positive rate obtained was above 60%.
hands-free speech recognition challenge for real-world speech dialogue systems. in this paper, we describe and review our recent development of hands-free speech dialogue system which is used for railway station guidance. in the application at the real railway station, robustness against reverberation and noise is the most essential issue for the dialogue system. to address the problem, we introduce two key techniques in our proposed hands-free system; (a) speech dialogue system construction with real speech database collection and language/acoustic model improvement, and (b) microphone array preprocessing using blind spatial subtraction array which can solve the reverberation-naiveness problem inherent in conventional microphone arrays. the experimental assessment of the proposed dialogue system reveals that our system can provide the recognition accuracy of more than 80% under realistic railway-station conditions.
experimental study of extended target imaging by time reversal sar. conventional sar images under rich scattering suffer degradation because of ghost images caused by multipath propagation. in this paper, we develop a time reversal sar (tr-sar) imaging algorithm for extended (nonpoint-like) targets in rich multipath scattering. we test the tr-sar algorithm using experimental electromagnetic data collected in a laboratory environment where the extended target (a galvanized steel sheet) is surrounded by a large amount of pvc rods. our experiments show that the collected em data in frequency and aperture after tr-sar processing produces a higher resolution, cleaner target map compared with conventional sar images.
an algorithm for speech segregation of co-channel speech. this paper introduces an algorithm to separate speech streams from a single-channel speech mixture. most current speech segregation algorithms allocate speech regions to participating speakers depending on which speaker dominates in which spectro-temporal region. the proposed method is a different approach to speech segregation, in that it separates the participating speaker streams rather than decide in the favor of the dominating speaker. the algorithm depends on a lease-squares fitting approach to model the speech mixture as a sum of complex exponentials. the algorithm gives results that are better than an existent algorithm when tested on the same task. the performance on a different database yielded good segregation results, even for target-to-masker ratios as low as −15 db. the algorithm has immense promise for improvement and practical implementation.
shadow detection for moving humans using gradient-based background subtraction. cast shadows cause serious problems in the functionality of vision-based applications, such as video surveillance, traffic monitoring and various other applications. accurate detection and removal of cast shadows is a challenging task. common shadow detection techniques normally use color information, which is not a reliable base in every scenario. this paper presents a novel scheme for real time detection of cast shadows using contour like structures of objects, which are obtained by gradient-based background subtraction. the scheme does not use any color information. two basic rules are followed for shadow detection. the first rule is that shadows do not change the texture of the background. the second rule is a cast shadow lies outside the boundary of an object and has a relatively small common boundary with the object. experimental results show the performance of the proposed scheme. objective evaluation shows that the algorithm classifies 90 percent of the pixels of the objects and their shadow correctly.
utterance verification using improved confidence measures based on alignment confusion rate in chinese digits recognition. in this paper, we explore an approach to improved confidence measures based on a novel alignment confusion rate (acr) which integrates alignment information from two different modeling unit sets in chinese digits recognition system. both initial-final (if) phone set and head-body-tail (hbt) models have proven to obtain good recognition performance for connected digit strings. these two different modeling can produce similar results but with different time-marked word boundaries. the objective of our proposed method is combining posterior probability with alignment confusion rate score provided by word alignment of if-based results to hbt-based reference results that minimizes word error rate to get an effective confidence measure for utterance verification. the efficiency of the proposed algorithm is demonstrated with various experiments on data collected from car-kit microphone.
a cost-error optimized architecture for 9/7 lifting based discrete wavelet transform with balanced pipeline stages. discrete wavelet transform (dwt) is increasingly recognized in image/video compression standards, as indicated by its use in jpeg2000. the lifting scheme algorithm is an alternative dwt implementation that has a lower computational complexity. in this paper, a new high performance lifting-based architecture is presented for the 9/7 dwt engine. the proposed architecture has a balanced pipeline and improves both the computational error and hardware complexity for any given working frequency. in the proposed architecture, the constant coefficients are modified by introducing new variables to the conventional lifting structure to minimize hardware cost and computational error, imposed by quantization of coefficients. simulation results indicate a quality improvement of up to 15 db when compared to an architecture using the standard coefficients that has the same hardware cost and working frequency. similarly, the hardware cost is reduced by about 20% when both architectures deliver the same psnr when operating at the same frequency.
a scale transform based method for rhythmic similarity of music. this paper introduces scale transforms to measure rhythmic similarity between two musical pieces. the rhythm of a piece of music is described by the scale transform magnitude, computed by transforming the sample autocorrelation of its onset strength signal to the scale domain. then, two pieces can be compared without the impact of tempo differences by using simple distances between these descriptors like the cosine distance. a widely used dance music dataset has been chosen for proof of concept. on this data set, the proposed method based on scale transform achieves classification results as high as other state of the art approaches. on a second data set, which is characterized by much larger intra-class tempo variance, the scale transform based measure improves classification compared to previously presented measures by 41%.
l1 regularized super-resolution from unregistered omnidirectional images. in this paper, we address the problem of super-resolution from multiple low-resolution omnidirectional images with inexact registration. such a problem is typically encountered in omnidirectional vision scenarios with reduced resolution sensors in imperfect settings. several spherical images with arbitrary rotations in the so(3) rotation group are used for the reconstruction of higher resolution images. we propose an l1 regularized total least squares normminimization method for joint registration and reconstruction with better stabilization and denoising. experimental results show that regularization offers a quality improvement of up to 1db. in addition, it reduces the number of low resolution images that are necessary to reconstruct a high resolution image at a target quality.
maximizing global entropy reduction for active learning in speech recognition. we propose a new active learning algorithm to address the problem of selecting a limited subset of utterances for transcribing from a large amount of unlabeled utterances so that the accuracy of the automatic speech recognition system can be maximized. our algorithm differentiates itself from earlier work in that it uses a criterion that maximizes the lattice entropy reduction over the whole dataset. we introduce our criterion, show how it can be simplified and approximated, and describe the detailed algorithm to optimize the criterion. we demonstrate the effectiveness of our new algorithm with directory assistance data collected under the real usage scenarios and show that our new algorithm consistently outperforms the confidence based approach by a significant margin. using the algorithm cuts the number of utterances needed for transcribing by 50% to achieve the same recognition accuracy obtained using the confidence-based approach, and by 60% compared to the random sampling approach.
speech rhythm guided syllable nuclei detection. in this paper, we present a novel speech-rhythm-guided syllable-nuclei location detection algorithm. as a departure from conventional methods, we introduce an instantaneous speech rhythm estimator to predict possible regions where syllable nuclei can appear. within a possible region, a simple slope based peak counting algorithm is used to get the exact location of each syllable nucleus. we verify the correctness of our method by investigating the syllable nuclei interval distribution in timit dataset, and evaluate the performance by comparing with a state-of-the-art syllable nuclei based speech rate detection approach.
fast algorithm for gmm-based pattern classifier. this work proposes a fast decision algorithm in pattern classification based on gaussian mixture models (gmm). statistical pattern classification problems often meet a situation that comparison between probabilities is obvious and involve redundant computations. when gmm is adopted for the probability model, the exponential function should be evaluated. this work firstly reduces the exponential computations to simple and rough interval calculations. the exponential function is realized by scaling and multiplication with powers of two so that the decision is efficiently realized. for finer decision, a refinement process is also proposed. in order to verify the significance, experimental results on ti dm6437 evm board are shown through the application to a skin-color extraction problem. it is verified that the classification was almost completed without any refinement process and the refinement process can proceed the residual decisions.
tracking of random number of targets with random number of sensors using random finite set theory. variation in the number of targets and sensors needs to be addressed in any realistic sensor system. targets may come in or out of a region or may suddenly stop emitting detectable signal. sensors can be subject to failure for many reasons. we derive a tracking algorithm with a model that includes these variations using random finite set theory (rfst). rfst is a generalization of standard probability theory into the finite set theory domain. this generalization does come with additional mathematical complexity. however, many of the manipulations in rsft are similar in behavior and intuition to those of standard probability theory.
high-level feature extraction using svm with walk-based graph kernel. we investigate a method using support vector machines (svms) with walk-based graph kernels for high-level feature extraction from images. in this method, each image is first segmented into a finite set of homogeneous segments and then represented as a segmentation graph where each vertex is a segment and edges connect adjacent segments. given a set of features associated with each segment, we then obtain a positive definite kernel between images by comparing walks in the respective segmentation graphs, and image classification is carried out with an svm based on this kernel. in a benchmark experiment on the mediamill challenge problem, the mean average precision increased from 0.216 (baseline) to 0.341 when our method was utilized.
modeling characters versuswords for mandarin speech recognition. word based models are widely used in speech recognition since they typically perform well. however, the question of whether it is better to use a word-based or a character-based model warrants being for the mandarin chinese language. since chinese is written without any spaces or word delimiters, a word segmentation algorithm is applied in a pre-processing step prior to training a word-based language model. chinese characters carry meaning and speakers are free to combine characters to construct new words. this suggests that character information can also be useful in communication. this paper explores both word-based and character-based models, and their complementarity. although word-based modeling is found to outperform character-based modeling, increasing the vocabulary size from 56k to 160k words did not lead to a gain in performance. results are reported for the gale mandarin speech-to-text task.
joint estimation and compensation of frequency, dc-offset, i-q imbalance and channel in mimo receivers. direct-conversion is a low-cost rf architecture that requires fewer external components in chip implementation. it introduces, however, extra rf impairments such as i-q imbalance and dc-offset that degrade severely the receiver performance if left uncompensated. in this paper, a new method of joint estimation and compensation of frequency, dc-offset, i-q imbalance and channel is developed for mimo receivers. numerical results show that the proposed method has a very good performance; less than 2 db loss is observed at bit-error rate 10−4, as compared to the ideal receiver. in addition, a new training sequence along with a low-complexity architecture is proposed to reduce largely the receiver complexity with negligible performance loss.
delay-based overlay construction in p2p video broadcast. we consider streaming video content over an overlay network of peer nodes. each of the nodes employs a mesh-pull mechanism to organize the download of data units from its neighbours. we propose a novel algorithm for constructing the distribution overlay, where peers are arranged in neighbourhoods that exhibit similar latency values from the origin media server. such an organization increases data sharing between neighbours in broadcast applications and reduces the play-out latency at a peer. each of the nodes in the overlay is further equipped with a packet scheduling procedure that requests data units from neighbours in the order of their importance and their popularity within the neighbourhood. finally, requesting peers share the upload bandwidth of a sending peer in proportion to their transmission rate to that peer in order to discourage free-riding in the system. our simulation results show that the proposed mesh construction procedure provides improved performance in terms of frame-freeze and playback latency relative to a conventional approach where peer neighbours are selected at random. corresponding gains in video quality for the media presentation are also registered due to the improved continuity of the playback experience.
denoising scheme for realistic digital photos from unknown sources. this paper targets denoising of digital photos taken by cameras with unknown sensor parameters and image processing pipeline. common noise characteristics in such images originate from camera-internal processing, such as demosaicing, tone mapping, and jpeg compression. three of the noise characteristics that are not adequately addressed by existing denoising algorithms are spatially correlated low-frequency noise, strong signal dependency of the noise level and high levels of the chrominance noise relative to the luminance noise. we propose a generic scheme that extends existing denoisers such as the bilateral filter to account for all the problems above. our solution combines a novel progressive pyramidal filtering scheme to address the correlated noise, filter adaptation via local noise level estimation and luminance-guided chrominance filtering to address the low-snr of the chrominance channels. we demonstrate the effectiveness of our solution for challenging realistic noisy photos.
a study on recognizing distorted speech over local distributed transducer networks. in a collaborative scenario, a multiplicity of portable devices may constitute a network of distributed microphones, without a clearly defined geometric configuration or synchronization that can be taken advantage of for traditional microphone array processing to enhance the acquired signal. this application scenario represents a severe, but interesting challenge for automatic speech recognition systems. in this paper, we investigate a variety of robust speech recognition techniques with a focus on the distributed transducer scenario. we also report some important study results that lead to new thinking in the design of robust speech recognition for broadened applications. two issues that are inherent to distributed transducer networks are specially investigated. first, we study the effect of the sampling rate skew of microphones to the system performance; second, we explore the possibility of combining recognition hypotheses from multiple transducer channels for improved recognition accuracy.
nonparametric spectral density estimation with missing observations. self-consistency is a fundamental principle in statistics for retaining maximum amount of information in the data. in this paper this principle is applied to develop a new method for nonparametric spectrum estimation with missing data. one major advantage of the proposed method is that it can be coupled with any complete data nonparametric spectrum estimation procedure, including kernel smoothing, wavelet and spline estimators. the practical performance of the method is illustrated by a simulation study.
feature based classification of computer graphics and real images. photorealistic images can now be created using advanced techniques in computer graphics (cg). synthesized elements could easily be mistaken for photographic (real) images. therefore we need to differentiate between cg and real images. in our work, we propose and develop a new framework based on an aggregate of existing features. our framework has a classification accuracy of 90% when tested on the de facto standard columbia dataset, which is 4% better than the best results obtained by other prominent methods in this area. we further show that using feature selection it is possible to reduce the feature dimension of our framework from 557 to 80 without a significant loss in performance (≪ 1%). we also investigate different approaches that attackers can use to fool the classification system, including creation of hybrid images and histogram manipulations. we then propose and develop filters to effectively detect such attacks, thereby limiting the effect of such attacks to our classification system.
blind soft-output equalization of block-oriented wireless communications. we consider blind equalization for block transmissions over the frequency selective rayleigh fading channel. in the absence of pilot symbols, the receiver must be able to perform joint equalization and blind channel identification. relying on a mixed discrete-continuous state-space representation of the communication system, we introduce a blind bayesian equalization algorithm based on a gaussian mixture parameterization of the a posteriori probability density function (pdf) of the transmitted data and the channel. the performances of the proposed algorithm are compared with existing blind equalization techniques using numerical simulations. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
doubly weighted nonnegative matrix factorization for imbalanced face recognition. we propose in this paper a novel doubly weighted nonnegative matrix factorization (dwnmf) method for imbalanced face recognition. motivated by the fact that some face samples and certain parts of each face sample are more useful for recognition, we construct two weighted matrices based on the pairwise similarity of face samples in the same class and the discriminant score of each face pixel. compared with the existing nmf algorithm, the proposed dwnmf method can more effectively exploit the discriminative and geometrical information of face samples, and it is especially suitable for imbalanced face recognition. experimental results are presented to demonstrate the efficacy of the proposed method.
multi-modal speaker diarization of real-world meetings using compressed-domain video features. speaker diarization is originally defined as the task of determining “who spoke when” given an audio track and no other prior knowledge of any kind. the following article shows a multi-modal approach where we improve a state-of-the-art speaker diarization system by combining standard acoustic features (mfccs) with compressed domain video features. the approach is evaluated on over 4.5 hours of the publicly available ami meetings dataset which contains challenges such as people standing up and walking out of the room. we show a consistent improvement of about 34% relative in speaker error rate (21% der) compared to a state-of-the-art audio-only baseline.
semi-supervised ensemble tracking. in this paper, we propose a semi-supervised ensemble tracking approach under the framework of particle filter. the particle filter is used not only for object searching, but also for unlabelled sample generation. by adopting the semi-supervised learning technology, these unlabelled samples which are generated online are utilized to progressively modify the classifier and make the ensemble tracker to be more robust to environment changing. on the other hand, utilizing semi-supervised learning technology can avoid the drifting phenomenons which are often encountered when using supervised learning. finally, the performance of the proposed approach is evaluated using real visual tracking examples.
the fractional hilbert transform and dual-tree gabor-like wavelet analysis. we provide an amplitude-phase representation of the dual-tree complex wavelet transform by extending the fixed quadrature relationship of the dual-tree wavelets to arbitrary phase-shifts using the fractional hilbert transform (fht). the fht is a generalization of the hilbert transform that extends the quadrature phase-shift action of the latter to arbitrary phase-shifts—a real shift parameter controls this phase-shift action. next, based on the proposed representation and the observation that the fht operator maps well-localized b-spline wavelets (that resemble gaussian-windowed sinusoids) into b-spline wavelets of the same order but different shift, we relate the corresponding dual-tree scheme to the paradigm of multiresolution windowed fourier analysis.
acoustically discriminative training for language models. this paper introduces a discriminative training for language models (lms) by leveraging phoneme similarities estimated from an acoustic model. to train an lm discriminatively, we needed the correct word sequences and the recognized results that automatic speech recognition (asr) produced by processing the utterances of those correct word sequences. but, sufficient utterances are not always available. we propose to generate the probable n-best lists, which the asr may produce, directly from the correct word sequences by leveraging the phoneme similarities. we call this process the “pseudo-asr”. we train the lm discriminatively by comparing the correct word sequences and the corresponding n-best lists from the pseudo-asr. experiments with real-life data from a japanese call center showed that the lm trained with the proposed method improved the accuracy of the asr.
a fast and efficient heuristic nuclear-norm algorithm for affine rank minimization. the problem of affine rank minimization seeks to find the minimum rank matrix that satisfies a set of linear equality constraints. generally, since affine rank minimization is np-hard, a popular heuristic method is to minimize the nuclear norm that is a sum of singular values of the matrix variable [1]. a recent intriguing paper [2] shows that if the linear transform that defines the set of equality constraints is nearly isometrically distributed and the number of constraints is at least o(r(m + n) logmn), where r and m × n are the rank and size of the minimum rank matrix, minimizing the nuclear norm yields exactly the minimum rank matrix solution. unfortunately, it takes a large amount of computational complexity and memory buffering to solve the nuclear norm minimization problem with known nearly isometric transforms. this paper presents a fast and efficient algorithm for nuclear norm minimization that employs structurally random matrices [3] for its linear transform and a projected subgradient method that exploits the unique features of structurally random matrices to substantially speed up the optimization process. theoretically, we show that nuclear norm minimization using structurally random linear constraints guarantees the minimum rank matrix solution if the number of linear constraints is at least o(r(m+n) log3 mn). extensive simulations verify that structurally random transforms still retain optimal performance while their implementation complexity is just a fraction of that of completely random transforms, making them promising candidates for large scale applications.
independent vector analysis incorporating active and inactive states. independent vector analysis (iva) is a method for separating convolutedly mixed signals that avoids the well-known permutation problem in frequency domain blind source separation (bss). in this paper, we exploit the nonstationarity of signals, a common feature, for bss. one common type of nonstationarity, especially in speech, is that the signal can have silence periods intermittently, hence varying the set of active sources with time. to deal with such situations, we propose a novel state-based iva algorithm. moreover, we consider additive noise in our model. computer simulations are conducted to compare the proposed method with the standard iva and the results compare favorably.
automatic pronunciation verification of english letter-names for early literacy assessment of preliterate children. children need to master reading letter-names and letter-sounds before reading phrases and sentences. pronunciation assessment of letter-names and letter-sounds read aloud is an important component of preliterate children's education, and automating this process can have several advantages. the goal of this work was to automatically verify letter-names spoken by kindergarteners and first graders in realistic classroom noise conditions. we applied the same techniques developed in our previous work on automatic letter-sound verification by comparing and optimizing different acoustic models, dictionaries, and decoding grammars. our final system was unbiased with respect to the child's grade, age, and native language and achieved 93.1% agreement (0.813 kappa agreement) with human evaluators, who agreed among themselves 95.4% of the time (0.891 kappa).
statistics for complex random variables revisited. complex random signals play an increasingly important role in array, communications, and biomedical signal processing and related fields. however, the mathematical foundations of complex-valued signals and tools developed for handling them are scattered in literature. there appears to be a need for a concise, unified, and rigorous treatment of such topics. in this paper such a treatment is provided. moreover, we establish connections between seemingly unrelated objects such as real differentiability and circularity. in addition, a novel complex-valued extension of taylor series is presented and a measure for circularity is proposed.
efficient musical noise suppression for speech enhancement system. noise reduction techniques that are relying on spectral weighting rules often generate annoying musical noise artifacts in the processed signal. in this paper, we present a postfilter (pf) for the spectral weighting gains that is capable of reducing musical noise in a simple but efficient way. it includes a robust detector for speech pauses and low snr conditions and adaptively smoothes the weighting gains over frequency based on soft-decisions. objective and subjective measurements show consistent improvements if the postfilter is applied to conventional noise reduction techniques.
noise adaptive training using a vector taylor series approach for noise robust automatic speech recognition. in traditional methods for noise robust automatic speech recognition, the acoustic models are typically trained using clean speech or using multi-condition data that is processed by the same feature enhancement algorithm expected to be used in decoding. in this paper, we propose a noise adaptive training (nat) algorithm that can be applied to all training data that normalizes the environmental distortion as part of the model training. in contrast to the feature enhancement methods, nat estimates the underlying “pseudo-clean” model parameters directly without relying on point estimates of the clean speech features as an intermediate step. the pseudo-clean model parameters learned with nat are later used with vector taylor series (vts) model adaptation for decoding noisy utterances at test time. experiments performed on the aurora 2 and aurora 3 tasks, demonstrate that the proposed nat method obtain relative improvements of 18.83% and 32.02%, respectively, over vts model adaptation.
an objective measure for the musical noise assessment in noise reduction systems. in this paper, a new objective measure is proposed to assess the amount of the wide-band musical noise in an acoustic signal. the measure uses time and frequency characteristics of the musical noise to determine the musicalness of the residual noise. the proposed measure uses noise masking thresholds to measure how much audible the musical noise components are. furthermore, a harmonicity measure is used to discriminate between the musical noise components and the speech components. at the end, the correlation of the proposed measure with the subjective listening test results is calculated and its performance is verified in experiments.
speaker diarization using unsupervised discriminant analysis of inter-channel delay features. when multiple microphones are available estimates of inter-channel delay, which characterise a speaker-s location, can be used as features for speaker diarization. background noise and reverberation can, however, lead to noisy features and poor performance. to ameliorate these problems, this paper presents a new approach to the discriminant analysis of delay features for speaker diarization. this novel and nonetheless unsupervised approach aims to increase speaker separability in delay-space. we assess the approach on subsets of four standard nist rt datasets and demonstrate a relative improvement in diarization error rate of 25% on a separate evaluation set using delay features alone.
a spatial adaptive filter for smoothing of non-gaussian texture noise. this paper contributes a novel technique for reducing the interference of non-gaussian texture noise from images. since the inherent properties of texture noise are very different from those of gaussian white noise, the basic assumption of conventional image denoising techniques is invalid. here we present a spatial adaptive filtering scheme to remove non-gaussian texture noise from textile images based on local and non-local similarities. in order to exploit the high correlations among pixels, pixels with uniform texture local regions are estimated differently from those pixels located near edges, that is, for points located in local uniform texture regions, gaussian weighted averaging of their neighbors can achieve the adaptive effect of the human visual system, whereas for edge points, to find pixels with similar local statistics both in the vicinity and far away can produce a sufficient set of pixels for reasonable averaging. this filtering strategy is applied to textile images corrupted by texture noise and the performance is demonstrated to outperform current state-of-art image denoising techniques. non-gaussian
predicting the progress and the peak of an epidemic. the problem is statistical prediction of the number of people that will be infected with a contagious illness in a closed population over time. the prediction is based on the susceptible-infectious-recovered (sir) model of epidemic dynamics with inhomogeneous population mixing. the paper presents a theoretical analysis of the predictive accuracy based on the cramér-rao lower bound (crlb). the crlb provides a tool that enables us to quantify the prediction accuracy of a scale of an epidemic as a function of the prior uncertainty of sir model parameters, measurement accuracy of the number of infected people and the amount of data available for processing. a verification of the theoretical analysis is carried out by monte carlo simulations.
alternatives to spherical microphone arrays: hybrid geometries. we present a novel theory and design for constructing microphone arrays to extract spherical harmonic components from soundfields. the proposed non-spherical array structure provides a flexible and alternative design to the traditional spherical microphone arrays with lesser restriction on sensor locations. we use the properties of the associated legendre functions and the spherical bessel functions to develop a systematic approach to place circular microphone arrays in three dimensions for hybrid array geometries. as an illustration, we design and simulate a fifth order spherical harmonic decomposition array using 70 microphones to operate over a frequency band of an octave.
a binary wavelet-based scheme for grayscale image compression. this paper proposes a novel grayscale image compression approach using the binary wavelet transform (bwt) and context-based arithmetic coding, namely the context-based binary wavelet transform coding algorithm (cbwtc). in our cbwtc, in order to alleviate the degradation of predictability caused by the bwt and eliminate the correlation within the same level subbands, three highpass wavelet coefficients at the same location are combined to form an octave symbol and then encoded with a ternary arithmetic coder. the conditional context of the cbwtc is properly modeled by exploiting the properties of the bwt as well as taking the advantages of non-causal adaptive context modeling. experimental results show that the coding performance of the cbwtc is better than that of the state-of-the-art grayscale image coders except for images containing rich texture, and always outperforms the jbig2 algorithm and other bwt-based binary coding technique.
normalized minimum-redundancy and maximum-relevancy based feature selection for speaker verification systems. in this paper, an information theoretical approach to select features for speaker recognition systems is proposed. conventional approaches having a fixed interval of analysis frames are not appropriate to represent dynamically varying characteristics of speech signals. to maximize the speaker-related information varied by the characteristics of speech signals, we propose an information theory based feature selection method where features are selected to have minimum-redundancy with in selected features but maximumrelevancy to training speaker models. experimental results verify that the proposed method reduces the error rates of speaker verification systems by 27.37 % in nist 2002 database.
fast and efficient dimensionality reduction using structurally random matrices. structurally random matrices (srm) are first proposed in [1] as fast and highly efficient measurement operators for large scale compressed sensing applications. motivated by the bridge between compressed sensing and the johnson-lindenstrauss lemma [2] , this paper introduces a related application of srms regarding to realizing a fast and highly efficient embedding. in particular, it shows that a srm is also a promising dimensionality reduction transform that preserves all pairwise distances of high dimensional vectors within an arbitrarily small factor ∈, provided that the projection dimension is on the order of o(∈−2 log3 n), where n denotes the number of d-dimensional vectors. in other words, srm can be viewed as the sub-optimal johnson-lindenstrauss embedding that, however, owns very low computational complexity o(d log d) and highly efficient implementation that uses only o(d) random bits, making it a promising candidate for practical, large scale applications where efficiency and speed of computation are highly critical.
objective evaluation of english learners' timing control based on a measure reflecting perceptual characteristics. automatic evaluation of english timing control proficiency is carried out by comparing segmental duration differences between learners and reference native speakers. to obtain an objective measure matched to human subjective evaluation, we introduced a measure reflecting perceptual characteristics. the proposed measure evaluates duration differences weighted by the loudness of the corresponding speech segment and the differences or jumps in loudness from the two adjacent speech segments. experiments showed that estimated scores using the new perception-based measure provided a correlation coefficient of 0.72 with subjective evaluation scores given by native english speakers on the basis of naturalness in timing control. this correlation turned out to be significantly higher than that of 0.54 obtained when using a simple duration difference measure.
an em algorithm for scfg in formal syntax-based translation. in this paper, we investigate the use of bilingual parsing on parallel corpora to better estimate the rule parameters in a formal syntax-based machine translation system, which are normally estimated from the inaccurate heuristics. we use an expectation-maximization (em) algorithm to re-estimate the parameters of synchronous context-free grammar (scfg) rules according to the derivation knowledge from parallel corpora based on maximum likelihood principle, rather than using only the heuristic information. the proposed algorithm produces significantly better bleu scores than a state-of-the-art formal syntax-based machine translation system on the iwslt 2006 chinese to english task.
improved clustered hierarchical tandem system with bottom-up processing. the outputs of multi-layer perceptron (mlp) classifiers have been successfully used in tandem systems as features for hmm-based automatic speech recognition. in a previous paper, we proposed data-driven clustered hierarchical mlp (chmlp) tandem system yielding improved performance by dividing the complicated global phone classification problem into simpler hierarchical tasks, in which specialized mlps are trained to classify small clusters of confusing phones in a hierarchical structure. in this paper a bottom-up processing is further proposed to enhance the classification in the above chmlp and offer even better performance. mlp rescoring for the tandem system is also investigated. the best result achieved 19.1% relative error reduction over the mfcc baseline.
flicker noise mitigation in direct-conversion receivers for ofdm systems. direct-conversion receiver (dcr) architecture has received considerable attention recently owing to its portable architecture and superior performance in terms of power and cost over its super-heterodyne counterpart. flicker noise is one of the major impairments which severely affects the performance of the system. in this work, we investigate the use of signal processing techniques in the mitigation of flicker noise in ofdm-based systems which employ dcr architecture. the statistical properties of flicker noise are exploited to develop adaptive signal processing algorithms that reduce the effect of flicker noise in dcrs. results indicate that signal processing algorithms can provide significant performance gain under low snr conditions.
on the pts method and ber-minimizing power allocation of the multi-channel ofdm system. in multiple-access multicarrier systems, it is possible to serve multiple users at high data rates from a single base station. in this paper, we propose the multi-channel partial transmit sequences (mcpts) method for multiple-access ofdm peak-to-average power ratio (par) reduction. by applying the pts phase rotations to each access channel separately and assuming that the rotations can be detected by each user as a channel fading, mcpts avoids two major disadvantages of standard pts: i) the phase rotations can be detected without side information, and ii) the set of possible phase rotation values does not need to be finite. in addition, an iterative method of joint mcpts and power allocation is proposed to minimize the average ber. the results show a significant ber improvement.
visual saliency with side information. we propose novel algorithms for organizing large image and video datasets using both the visual content and the associated side-information, such as time, location, authorship, and so on. earlier research have used side-information as pre-filter before visual analysis is performed, and we design a machine learning algorithm to model the join statistics of the content and the side information. our algorithm, diverse-density contextual clustering (d2c2), starts by finding unique patterns for each sub-collection sharing the same side-info, e.g., scenes from winter. it then finds the common patterns that are shared among all subsets, e.g., persistent scenes across all seasons. these unique and common prototypes are found with multiple instance learning and subsequent clustering steps. we evaluate d2c2 on two web photo collections from flickr and one news video collection from trecvid. results show that not only the visual patterns found by d2c2 are intuitively salient across different seasons, locations and events, classifiers constructed from the unique and common patterns also outperform state-of-the-art bag-of-features classifiers.
a highly robust audio hashing system using auditory-based front-end processing. in this paper, a robust perceptual audio hashing system is presented. a model of the human auditory system is used to extract robust features from the outputs of a non-linear filter bank that mimics the human basilar membrane. experiments on various audio excerpts show that this new ear-based front-end processing provides very effective hash values. the proposed audio hashing system performs very satisfactorily in identification and it turned out very resilient to a large variety of severe audio attacks.
improved svm speaker verification through data-driven background dataset collection. the problem of background dataset selection in svm-based speaker verification is addressed through the proposal of a new data-driven selection technique. based on support vector selection, the proposed approach introduces a method to individually assess the suitability of each candidate impostor example for use in the background dataset. the technique can then produce a refined background dataset by selecting only the most informative impostor examples. improvements of 13% in min. dcf and 10% in eer were found on the sre 2006 development corpus when using the proposed method over the best heuristically chosen set. the technique was also shown to generalise to the unseen nist 2008 sre corpus.
generating matrix of discrete fourier transform eigenvectors. this paper provides a novel method to obtain the eigenvectors of discrete fourier transform (dft), which are accurate approximations to the continuous hermite-gaussian functions (hgfs). the proposed method uses a generating matrix and an initial eigenvector. by multiplying the initial eigenvector with the generating matrix, we can derive a new eigenvector. repeating this procedure we can acquire all the eigenvectors. compare with the conventional o(n3) commutative matrix method, this new method can generate all the dft eigenvectors with complexity reduced to o(n2logn). the generating matrix can be further used to intensify the conventional commuting matrix. the simulation result shows that the hermite-gaussian like (hgl) eigenvectors of the strengthened commuting matrix outperform those of santhanam's.
face recognition and gender classification in personal memories. face annotation is an important concept for personal memories retrieval. using automatic face recognition to annotate and find people in those memories provides an improvement of a personal memories management system. however, its results are limited by the uncontrolled conditions inherent to personal memories. in this paper, we propose a face recognition method to address these limitations which includes techniques of skin detection and pose estimation. it is also proposed a gender classification method to provide more information about the detected faces. experimental results are presented that show that these methods improve the overall performance of face recognition and gender classification in personal memories.
a comparison between sequence kernels for svm speaker verification. we present a comparative study of several svm speaker verification (sv) systems based on sequence kernels: the gmm-supervectors kernel, the fisher kernel, the generalized linear discriminant sequence (glds) kernel, our feature space normalized sequence (fsns) kernel and a “novel” sequence kernel in sv, the correlation kernel. we also compare these svm systems to the conventional generative ubm-gmm. we carry out experiments on the nist'2005 sre evaluation set. the results show that the fsns system yields comparable performances to ubm-gmm and significantly outperforms glds. they also show that the gmm-supervectors system outperforms all the others. finally, they show that the best performances are achieved by fusing the fsns and the gmm-supervectors systems.
discriminating subsequent lane-crossing and driver-correction events using trajectory models of lateral slopes. in this paper, we propose a new framework to discriminate the initial maneuver of lane-crossing event from driver-correction event, which is the primary reason for false warnings of the lane departure prediction systems. the proposed algorithm validates the beginning episode of the trajectory of driving signals whether it will cause a lane crossing event or not, by employing driver behavior models of directional sequence of piecewise lateral slopes (dspls) representing lane-crossing and driver-correction events. the framework utilizes only common driving signals, and allows adaptation scheme of driver behavior models to better represent individual driving characteristics. the experimental evaluation shows that the proposed dspls has detection error as low as 17% equal error rate. furthermore, the proposed algorithm reduces the false alarm rate of the original lane departure prediction system from 38.8% to 6.1% with less trade-off for the prediction accuracy.
a fast feature extraction method. a fast subspace analysis and feature extraction algorithm is proposed which is based on fast haar transform and integral vector. in rapid object detection and conventional binary subspace learning, haar-like functions have been frequently used but true haar functions are seldom employed. in this paper we have shown that true haar functions can be successfully used to accelerate subspace analysis and feature extraction. both the training and testing speed of the proposed method is higher than conventional algorithms. experimental results on face database demonstrated its effectiveness.
asymmetric gradient-based image alignment. a new method for template-based image alignment is presented in this paper. a gradient-based optimization of motion compensated error difference is addressed to solve the image alignment problem. its novelty lies in the minimized error, which considers the bi-directional compensation of the reference template and the current image onto each other in a constrained asymmetrical fashion. the proposed approach is shown to be a generalization of previous state-of-the art gradient-based methods. an experimental evaluation is provided to show how the new method outperforms the former in presence of noisy images, and to give some insights into its properties.
stereo-based stochastic noise compensation based on trajectory gmms. this paper proposes a novel stereo-based stochastic noise compensation technique based on trajectory gmms. although the gmm-based noise compensation techniques such as splice work effective, their performance sometimes degrades due to the inappropriate dynamic characteristics caused by the frame-by-frame mapping. while the use of dynamic feature constraints on the mapping stage can alleviate this problem, it also introduces an inconsistency between training and mapping. the recently proposed trajectory gmm-based feature mapping technique can solve this inconsistency while keeping the benefits of the use of dynamic features, and offers an entire sequence-level transformation rather than the frame-by-frame mapping. results from a noise compensation experiment on the aurora-2 task show that the proposed trajectory gmm-based noise compensation technique outperforms the conventional ones.
asymptotic performance analysis of pca algorithms based on the weighted subspace criterion. this paper studies the asymptotic distribution of the eigenvectors estimated by some pca algorithms based on the weighted subspace criterion. this enables us to analyse how the choice of the weighting matrix affects the algorithm's performance, an issue previously overlooked.
sparse imputation for noise robust speech recognition using soft masks. in previous work we introduced a new missing data imputation method for asr, dubbed sparse imputation. we showed that the method is capable of maintaining good recognition accuracies even at very low snrs provided the number of mask estimation errors is sufficiently low. especially at low snrs, however, mask estimation is difficult and errors are unavoidable. in this paper, we try to reduce the impact of mask estimation errors by making soft decisions, i.e., estimating the probability that a feature is reliable. using an isolated digit recognition task (using the aurora-2 database), we demonstrate that using soft masks in our sparse imputation approach yields a substantial increase in recognition accuracy, most notably at low snrs.
temporally variable multi-aspect auditory morphing enabling extrapolation without objective and perceptual breakdown. a generalized framework of auditory morphing based on the speech analysis, modification and resynthesis system straight is proposed that enables each morphing rate of representational aspects to be a function of time, including the temporal axis itself. two types of algorithms were derived: an incremental algorithm for real-time manipulation of morphing rates and a batch processing algorithm for off-line post-production applications. by defining morphing in terms of the derivative of mapping functions in the logarithmic domain, breakdown of morphing resynthesis found in the previous formulation in the case of extrapolations was eliminated. a method to alleviate perceptual defects in extrapolation is also introduced.
sparse lms for system identification. we propose a new approach to adaptive system identification when the system model is sparse. the approach applies ℓ1 relaxation, common in compressive sensing, to improve the performance of lms-type adaptive methods. this results in two new algorithms, the zero-attracting lms (za-lms) and the reweighted zero-attracting lms (rza-lms). the za-lms is derived via combining a ℓ1 norm penalty on the coefficients into the quadratic lms cost function, which generates a zero attractor in the lms iteration. the zero attractor promotes sparsity in taps during the filtering process, and therefore accelerates convergence when identifying sparse systems. we prove that the za-lms can achieve lower mean square error than the standard lms. to further improve the filtering performance, the rza-lms is developed using a reweighted zero attractor. the performance of the rza-lms is superior to that of the za-lms numerically. experiments demonstrate the advantages of the proposed filters in both convergence rate and steady-state behavior under sparsity assumptions on the true coefficient vector. the rza-lms is also shown to be robust when the number of non-zero taps increases.
on noise reduction in the karhunen-loève expansion domain. in this paper, we study the noise-reduction problem in the karhunen-loève expansion domain. we develop two classes of optimal filters. the first class estimates a frame of speech by filtering the corresponding frame of the noisy speech. we will show that several well-known existing methods belong or are closely related to this category. the second class, which has not been studied before, obtains noise reduction by filtering not only the current frame, but also a number of previous consecutive frames of the noisy speech. we will discuss how to design the optimal noise-reduction filters in each class and demonstrate the properties of the deduced optimal filters.
arx-lf-based source-filter methods for voice modification and transformation. two arx-lf-based source/filters models for speech signals are presented. a robust glottal inversion technique is used to deconvolve the signal into an excitation component and a filter component. the excitation component is further decomposed into an lf part and a residual part. the first model, referred to as the lf-vocoder, is a high quality vocoder that replaces the residual part with modulated noise. the second model uses a sinusoidal harmonic representation of the residual signal. the latter does not degrade the signal during analysis/synthesis and provides higher quality for small modification factors, while the former has the advantage of being a compact, fully parametric representation that is suitable for low-bit-rate speech coding as well as parametric speech synthesis applications.
near-lossless compression and protection by turbo source-channel (de-)coding using irregular index assignments. in this paper, we present a novel near-lossless compression scheme for scalar-quantized source codec parameters. the scheme is comparable to a turbo source coding approach and can inherently incorporate protection against transmission errors. we show that using the concept of exit charts and irregular codes, a linear programming optimization problem can be formulated and the solution of this problem leads to an irregular index assignment offering the best possible compression given the considered system model and a fixed channel quality. the performance of the compression scheme is demonstrated by a simulation example.
a simple iterative algorithm for range-based localization. the range-based localization problem often arises in toa or rssi based position estimation schemes. it is well-known that such a localization problem can be formulated as a nonlinear least-squares (nls) estimation problem. in this paper, we formulate the problem as a constrained optimization problem, which is equivalent to the general nls problem. by using a greedy optimization strategy, we derive a simple iterative algorithm with closed-form expressions for the nls localization, which can be implemented in a distributed way. simulation results show that the localization performance of the proposed localization algorithm is very close to the cramer-rao lower bound.
embedded celp with adaptive codebooks in enhancement layers and multi-layer gain optimization. the paper describes an embedded celp coder in which an adaptive codebook is included in every enhancement layer and the lower-layer codebook gains are re-optimized in the higher layers to further improve speech quality. each layer maintains its own filter memories to generate required target vectors, adds adaptive and fixed codebook contributions, and re-optimizes all codebook gains to improve coder performance (multi-layer gain optimization). the common elements across the embedded layers include the lower-layer adaptive and fixed codebook entries. the pitch-lag used in the core layer is also re-used in the enhancement layers to maintain time synchronization between layers. estimation and encoding of selected lower-layer parameters may take into account their estimated impact on the higher layers. the described embedded celp coder has been implemented in the embedded variable bit-rate (ev-vbr) codec standardized by itu-t as recommendation g.718. the characterization test results of the g.718 embedded celp are summarized.
a quantitative evaluation for 3d face reconstruction algorithms. in this work, we proposed to use quantitative method to evaluate the accuracy of 3d face reconstruction algorithms. the reconstructed 3d faces are first aligned to the ground truth by iterative closest point (icp) algorithm and then the shape difference between the two 3d faces is described by signal to noise ratio (snr). finally, the error maps (em) illustrated the reconstruction errors on corresponded vertices in different dimensions. comparing with the subjective and indirect evaluation methods, the proposed method provides more precise and detailed evaluations for face shape reconstruction. based on the snr, different 3d face reconstruction algorithms can be compared directly and the em also can suggest guidance for feature extraction.
single-channel speech separation and recognition using loopy belief propagation. we address the problem of single-channel speech separation and recognition using loopy belief propagation in a way that enables efficient inference for an arbitrary number of speech sources. the graphical model consists of a set of n markov chains, each of which represents a language model or grammar for a given speaker. a gaussian mixture model with shared states is used to model the hidden acoustic signal for each grammar state of each source. the combination of sources is modeled in the log spectrum domain using non-linear interaction functions. previously, temporal inference in such a model has been performed using an n-dimensional viterbi algorithm that scales exponentially with the number of sources. in this paper, we describe a loopy message passing algorithm that scales linearly with language model size. the algorithm achieves human levels of performance, and is an order of magnitude faster than competitive systems for two speakers.
ranging signal design and its detection for ofdma systems. a single-symbol based initial ranging signal structure and the associated signal detection and timing synchronization methods for ofdma systems are presented. the proposed structure makes it feasible and flexible for a receiver to detect single and multiple ranging codes and estimate the corresponding timing offsets. our approach offers improved performance and enhanced robustness against multi-user interference and multi-path fading. numerical results verify the effectiveness of the proposed method and its advantages over existing alternatives.
jamming mitigation using space-time coded collision-free frequency hopping. frequency hopping (fh) system, which is robust under jamming interference, was originally developed for secure military communication applications. however, the efficiency of the conventional fh scheme is very low due to inappropriate use of the total available bandwidth and transmission collisions. to improve the system capacity, we develop a space-time coded collision-free frequency hopping (stc-cffh) system based on the ofdm framework. the capacity and performance analysis of the proposed scheme is presented under frequency selective fading and partial-band jamming through both theoretical analysis and simulation examples. our analysis indicates that the stc-cffh scheme improves the spectral efficiency and inherent anti-jamming features of conventional fh systems.
introduction of quality measures in audio-visual identity verification. audiovisual identity verification exploits both image and audio information to improve the performance of the identification system. unfortunately, both image and audio systems are sensitive to signal quality. in this paper, we propose a method to combine output classifiers based on both image and audio quality measures. we define classes of signal degradation within which we estimate the fusion weights and normalization parameters. results of experiments on the banca database show that fusion using quality measures improves verification performance by 25% compared to the baseline fusion method.
duality between widely linear and dual channel adaptive filtering. we address the duality between adaptive filtering in ℂ and ℝ2 and provide a comparison between the well understood dual channel real valued least mean square (dcrlms) algorithm in ℝ2 and the corresponding algorithms in ℂ. these include the complex lms (clms) and the recently introduced augmented clms (aclms), a widely linear algorithm designed for the processing of noncircular complex valued signals. the analysis shows that the standard clms and dcrlms in general provide different adaptive filtering solutions, whereas the aclms and dcrlms are isomoprhic and can be made equivalent. the analysis is supported by simulations on noncircular real world signals.
phoneme cluster based state mapping for text-independent voice conversion. this paper takes phonetic information into account for data alignment in text-independent voice conversion. hidden markov models are used for representing the phonetic structure of training speech. states belonging to same phoneme are grouped together to form a phoneme cluster. a state mapped codebook based transformation is established using information on the corresponding phoneme clusters from source and targets speech and weighted linear transform. for each source vector, several nearest clusters are considered simultaneously while mapping in order to generate a continuous and stable transform. experimental results indicate that the proposed use of phonetic information increases the similarity between converted speech and target speech. the proposed technique is applicable to both intra-lingual and cross-lingual voice conversion.
audio-based automatic management of tv commercials. although tv commercial identification and clustering are suitable applications for automatic multimedia indexing technology, they remain as problems still unsolved. most current systems either require a big computational load and therefore can not be executed online, or just perform a detection, without clustering nor identification. in this paper two advertisement indexing approaches are presented: an off-line detection and clustering system and an online identification system, both based only on audio features for computational reasons. for the off-line clustering two metrics are evaluated, and an initial commercial boundary detection algorithm, based on identifying drop energy points which are also acoustic change boundaries, is presented. for the on-line system we analyze the response-time/identification scores constraints. experiments performed on real data validate both off-line and on-line implementations as well as that audio only features are enough discriminant to detect and classify tv commercials.
estimation of the hyperspectral tucker ranks. in hyperspectral image analysis, one often assumes that observed pixel spectra are linear combinations of pure substance spectra. unmixing a hyperspectral image consists in finding the number of pure substances in the scene, finding their spectral signatures and estimating the abundance fraction of each pure substance spectrum in each spectral pixel. in this paper, we show that the tensor tucker decomposition could be considered to solve this problem, and a preliminary problem to overcome consists in estimating the 3 required data tucker ranks, corresponding to the 3 dimensions of the data cube. then, we propose an optimal method to estimate them.
digital beamforming using a gpu. in this paper we investigate the use of gpus as digital beamformers. we specify a parallel implementation of a beamformer in time and frequency domain and measure its performance. we also give examples of the processing limits of nvidia geforce 8800 gpu with respect to application parameters: number of sensors, sampling frequency, bandwidth, and number of simultaneous beams. the results are compared to those of algorithms similarly implemented on a intel xeon cpu. we find that the gpu is able to process a larger amount of information than the cpu, and that it can be used as a digital beamformer for arrays with a large number of elements sampled at high rates. exact results are given for the abovementioned application parameters.
optimal generalized design of transform-based block digital filters. transform-based block implementation of digital filters is useful for high throughput filtering due to inherent parallelism and complexity reduction provided by using the fast transforms. in basic form, for example the overlap-save implementation, the block digital filter (bdf) is represented by a vector. in this paper, the basic form of block filtering and the optimal design of bdf are described. therefore, we propose a generalization of the block digital filtering where the bdf is represented by a matrix. this generalized form and its corresponding optimal bdf design are developed. the generalized bdf allows reducing the global distortion of the block filtering.
control of prosodic focus in corpus-based generation of fundamental frequency contours of japanese based on the generation process model. a total corpus-based process of generating prosodic features from text is developed. the process first predicts pauses and phone durations, and then generates f0 contours. since f0 contour generation is based on the generation process model, it is rather easy to manipulate the generated f0 contours in command level. a method was developed for generating sentence f0 contours, when a focus is placed in one of the “bunsetsu” of an utterance. the method is to predict differences in the f0 model commands between with and without focus utterances, and apply them to the f0 model commands predicted beforehand by the baseline method. the validity of the method was proved by the experiment on f0 contour generation and speech synthesis.
using phase linearity in frequency-domain ica to tackle the permutation problem. this paper describes a method for solving the permutation problem in the frequency-domain independent component analysis (fd-ica) approach to blind source separation (bss). fd-ica is a well-known method for bss of convolutive mixtures. however, fd-ica has a source permutation problem, where estimated source components can become swapped at different frequencies. many researchers have suggested methods to solve the source permutation problem including using correlation between adjacent frequencies and direction of arrival (doa). we propose a modification to the doa method, based on phase linearity of the fd-ica de-mixing matrix, that can extend the range of frequencies over which the permutation problem can be resolved. experiments indicate that our method can provide a better performance than the inter-frequency correlation method and the doa method in real environments.
transmit beamforming for wireless multicasting using channel orthogonalization and local refinement. the problem of transmit beamforming for single-group multicasting is considered, where the objective is to transmit common information to a (large) number of users. the transmitter is assumed to have accurate downlink channel state information (csi) for all users, and the objective is to design the beamformer weights to minimize the total transmitted power subject to meeting the quality-of-service (qos) constraints of all users. this is an np-hard problem that has recently drawn considerable interest (e.g., in the context of umts-lte / e-mbms). several channel orthogonalization-based methods are proposed to solve this problem in an approximate way. our techniques are shown to offer an improved performance-to-complexity tradeoff as compared to the original semidefinite relaxation (sdr) based multicasting technique.
using complex-valued ica to efficiently combine radar polarimetric data for target detection. target detection in sea clutter is a challenging problem in radar detection, specifically, when the doppler return of the target and clutter are collocated. polarization diverse radars provide additional information that enhances target detection. in this paper, we use an effective independent component analysis (ica) approach, adaptive complex maximization of non-gaussianity (a-cmn) [1], to efficiently combine polarimetric radar data prior to detection. we show that a-cmn estimates the polarimetric scatter coefficients for the single target in clutter case, thereby providing matched-filter performance without the need for clutter or target models. the detection performance using ica is evaluated with sea clutter collected with the mcmaster ipix radar off the coast of canada [2]. we also demonstrates the ability of this approach to adapt to the changing sea clutter conditions using simulation results.
iterative filtering of phonetic transcriptions of proper nouns. this paper focuses on an approach to enhancing automatic phonetic transcription of proper nouns by using an iterative filter to retain only the most relevant part of a large set of phonetic variants, obtained by combining rule-based generation with extraction from actual audio signals. using this technique, we were able to reduce the error rate affecting proper nouns during automatic speech transcription of the ester corpus of french broadcast news. the role of the filtering was to ensure that the new phonetic variants of proper nouns would not induce new errors in the transcription of the rest of the words.
detecting sweethearting in retail surveillance videos. a significant portion of retail shrink is attributed to employees and occurs around the point of sale (pos). in this paper, we target a major type of retail fraud in surveillance videos, known as sweethearting (or fake scan), where a cashier intentionally fails to enter one or more items into the transaction in an attempt to get free merchandise for the customer. we first develop a motion-based algorithm to identify video segments as candidates for primitive events at the pos. we then apply spatio-temporal features to recognize true primitive events from the candidates and prune those falsely alarmed. in particular, we learn location-aware event models by multiple-instance learning to address the location-sensitive issues that appear in our problem. finally, we validate the entire transaction by combining primitive events according to temporal ordering constraints. we demonstrate the effectiveness of our approach on data captured from a real grocery store.
field inversion by consensus and compressed sensing. we study the inversion of a random field from pointwise measurements collected by a sensor network. we assume that the field has a sparse representation in a known basis. to illustrate the approach, consider the inversion of an acoustic field created by the superposition of a discrete number of propagating noisy acoustic sources. our method combines compressed sensing (sparse reconstruction by ℓ1-constrained optimization) with distributed average consensus (mixing the pointwise sensor measurements by local communication among the sensors). the paper describes the approach and demonstrates its good performance with synthetic data for several scenarios of practical interest.
combining independent component analysis with geometric information and its application to speech processing. in this paper, we propose two approaches for combining geometric information with ica algorithm to solve permutation problem under the scenario where a rough information about the direction of the desired source is known. the first approach is a new blind extraction algorithm with a soft quadratic geometric constraint. the desired source is guaranteed to be conveyed to the output with little distortion by the quadratic constraint and the negentropy maximization criterion is used to ensure that the other sources get suppressed at the output. the second approach employs a quadratic geometric test as a post-processing step to pickup the desired source after ica processing. an advantage of the proposed two approaches is that they do not require accurate knowledge of the number of sources in the mixtures to recover the desired source, in contrast, other geometric ica approaches usually fail if the number of sources is not known accurately.
an overlap save algorithm for block convolution with reduced complexity. we propose a block convolution algorithm that requires shorter length fft than the conventional overlap save algorithm (osa). it is shown that the osa can be split into two separate processes related to the previous and current data blocks. hence, only current data block needs to be transformed in the proposed osa, whereas the concatenated block of previous and current data is transformed in the conventional method. as a result, the number of arithmetic operations for the block convolution is reduced. also, the reduced transform size gives additional advantage in data manipulation when implemented on dsp and pc.
sub-band implementation of the harmonic music algorithm. in this paper, we present a novel method for joint estimation of the order and fundamental frequency of a set of harmonically related sinusoids. this method uses a subband based approach to estimate the involved parameters using subspace techniques, and the resulting algorithm is termed frequency-selective harmonic music (f-hmusic). the performance of f-hmusic is evaluated and compared to both harmonic music (hmusic) and cramér-rao lower bound (crlb). especially, in a low signal-to-noise ratio (snr) with colored noise scenarios, where f-hmusic outperforms hmusic. f-hmusic is concluded to be more computationally efficient and more robust against colored noise than other subspace based fundamental frequency estimators.
map approach to learning sparse gaussian markov networks. recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse markov networks result into convex problems that can be solved optimally and efficiently. however, the accuracy of such methods can be very sensitive to the choice of regularization parameter, and optimal selection of this parameter remains an open problem. herein, we propose a maximum a posteriori probability (map) approach that investigates different priors on the regularization parameter and yields promising empirical results on both synthetic data and real-life application such as brain imaging data (fmri).
assessment of baroreflex control of heart rate during general anesthesia using a point process method. evaluation of baroreflex control of heart rate (hr) has important implications in clinical practice of anesthesia and postoperative care. in this paper, we present a point process method to assess the dynamic baroreflex gain using a closed-loop model of the cardiovascular system. specifically, the inverse gaussian probability distribution is used to model the heartbeat interval, whereas the instantaneous mean is identified by a linear or bilinear bivariate regression on the previous r-r intervals and blood pressure (bp) measures. the instantaneous baroreflex gain is estimated in the feedback loop with a point process filter, while the rr→bp feedforward frequency response is estimated by a kalman filter. in addition, the instantaneous cross-spectrum and cross-bispectrum (as well as their ratio) can also be estimated. all statistical indices provide a valuable quantitative assessment of the interaction between heartbeat dynamics and hemodynamics during general anesthesia.
unsupervised equalization of lombard effect for speech recognition in noisy adverse environment. when exposed to environmental noise, speakers adjust their speech production to maintain intelligible communication. this phenomenon, called lombard effect (le), is known to considerably impact the performance of automatic speech recognition (asr) systems. in this study, novel frequency and cepstral domain equalizations that reduce the impact of le on asr are proposed. short-time spectra of le speech are transformed towards neutral asr models in a maximum likelihood fashion. dynamics of cepstral coefficients are normalized to a constant range using quantile estimations. the algorithms are incorporated in a recognizer employing a codebook of noisy acoustic models. in a recognition task on connected czech digits presented in various levels of background car noise, the resulting system provides an absolute reduction in word error rate (wer) on 10 db snr data of 8.7% and 37.7% for female neutral and le speech, and of 8.7% and 32.8% for male neutral and le speech when compared to the baseline system employing perceptual linear prediction (plp) coefficients and cepstral mean and variance normalization.
joint linear-circular stochastic models for texture classification. in this paper, we investigate both linear and circular stochastic models in the context of texture discrimination. these models aim at representing the magnitudes and orientations obtained by a complex wavelet decomposition, such as the steerable pyramid.the novelty consists in considering specific parametric models for circular data such as von mises and ψ- distributions to describe the distributions of orientations. particular attention is paid to the choice of a metric and to its adequation to the models. indexing experiments are conducted to quantitatively evaluate the performances of the proposed models and of the chosen matrices, i.e. the l1 and kullback-leibler distances.
nonmatrix closed-form expressions of the cramér-rao bounds for near-field localization parameters. near-field source localization problem by a passive antenna array makes the assumption that the time-varying sources are located near the antenna. in this situation, the far-field assumption (planar wavefront) is no longer valid and we have to consider a more complicated model parameterized by the bearing (as in the far-field case) and by the distance, named range, between the source and a reference sensor. we can find a plethora of estimation schemes in the literature but the ultimate performance has not been fully investigated. in this paper, we derive and analyze the cramér-rao bound (crb) for a single time-varying source. in this case, we obtain nonmatrix closed-form expressions. our approach has two advantages: (i) the computational cost for a large number of snapshots of a matrix-based crb can be high while our approach is cheap and (ii) some useful informations can be deduced from the behavior of the bound. in particular, we show that closer is the source from the array and/or higher is the carrier frequency, better is the estimation of the range.
using a pitch-synchronous residual codebook for hybrid hmm/frame selection speech synthesis. this paper proposes a method to improve the quality delivered by statistical parametric speech synthesizers. for this, we use a codebook of pitch-synchronous residual frames, so as to construct a more realistic source signal. first a limited codebook of typical excitations is built from some training database. during the synthesis part, hmms are used to generate filter and source coefficients. the latter coefficients contain both the pitch and a compact representation of target residual frames. the source signal is obtained by concatenating excitation frames picked up from the codebook, based on a selection criterion and taking target residual coefficients as input. subjective results show a relevant improvement compared to the basic technique.
random patch based video tracking via boosting the relative spaces. in this paper, we propose a new visual tracking method based on the recently popular tracking-as-classification idea. we concentrate on exploring the intra-class variance of the foreground target to construct and update a classification based tracker. in our approach, foreground target is represented by a set of model patches. different types of features are jointly used to represent those patches. individual weak learners are trained based on each model patch's relative space. adaboost framework is applied to choose those weak classifiers to combine a strong classifier as the tracker for next frame. moreover, with the new tracking result, the tracker is adjusted adaptively according to the change of scene to keep itself discriminative during the entire sequence. we demonstrate the effectiveness of our approach with comparison results on common video sequences.
facial age estimation by multilinear subspace analysis. automatic estimation of human facial age is an interesting yet challenging topic appearing in recent years. since different people might age in different ways, solving the problem of age estimation involves two semantic labels: identity and age. in this paper, aging face images are organized in a third-order tensor according to both identity and age. due to the difficulty in data collection, the aging pattern for each person in the training set is always incomplete. therefore, the tensor contains a large amount of missing values. through a series of multilinear subspace analysis algorithms operating on tensor with missing values, the aging pattern contained in the training aging images can be iteratively learned and be used to predict the age of a given test image. in the experiment, the proposed method not only outperforms the existing algorithms, but also exceeds the human ability in age estimation.
local and global convergence behavior of non-equidistant sampling series. in this paper we analyze the local and global convergence behavior of sampling series with non-equidistant sampling points for the paley-wiener space pwπ1 and sampling patterns that are made of the zeros of sine-type functions. it is proven that the sampling series are locally uniformly convergent if no oversampling is used and globally uniformly convergent if oversampling is used. furthermore, we show that oversampling is indeed necessary for global uniform convergence, because for every sampling pattern there exists a signal such that the peak value of the approximation error grows arbitrarily large if no oversampling is used. finally, we use these findings to obtain similar results for the mean-square convergence behavior of sampling series for bandlimited wide-sense stationary stochastic processes.
context-independent phoneme recognition using a k-nearest neighbour classification approach. in this paper we investigate a non-parametric classification of english phonemes in speaker-independent continuous speech. we employ the “voting” k-nearest neighbour (k-nn) classifier, a powerful technique in pattern recognition problems, along with a new representation of phonemes for the speech recognition task. we also exploit the idea behind “approximate” k-nn that results in a very fast way of computing the k approximate closest neighbours of each data point. comparing the recognition performance of the proposed method with the hmm-based recognizer of htk toolkit reveals that the k-nn-based recognizer outperforms its counterpart. in addition, incorporating the “approximate” nearest neighbour search instead of the “exact” one results in completing the training step much faster than the hmm-based system, and the testing step with a comparable computational time. we also reduced the amount of the training data by applying a pattern recognition technique, called “thinning” algorithm. the outcome was a considerable reduction in the k-nn search space and hence the execution time, and also a slight increase in the recognition performance.
on the impact of spatial correlation and precoder design on the performance of mimo systems with space-time coding. the symbol error performance of spatially correlated multi-antenna systems is analyzed herein. when the transmitter only has statistical channel information, the use of space-time block codes still permits spatial multiplexing and mitigation of fading. the statistical information can be used for precoding to optimize some quality measure. herein, we analyze the performance in terms of the symbol error rate (ser). it is shown analytically that spatial correlation at the receiver decreases the performance both without precoding and with an ser minimizing precoder. without precoding, correlation should also be avoided at the transmitter side, but with an ser minimizing precoder the performance is actually improved by increasing spatial correlation at the transmitter. the structure of the optimized precoder is analyzed and the asymptotic properties at high and low snrs are characterized and illustrated numerically.
subspace tracking of fast time-varying channels in precoded mimo-ofdm systems. this paper presents a blind subspace-based tracking scheme for precoded mimo-ofdm systems over rapidly time-varying wireless channels. subspace-based tracking is normally considered for slow time-varying channels only. thanks to the frequency correlation of the wireless channels, the proposed scheme is able to collect data not only from the time but also from the frequency domain to speed up the update of the required second-order statistics. after each update of the statistics, the subspace information is also updated using orthogonal iteration, and then a new channel estimate is computed. the proposed algorithm is verified in 3gpp-scm suburban macro scenario, in which a mobile station is allowed to move in any direction with a constant speed of 100km/h. the simulation results show that the root mean square error of the channel estimates converges to the level of 2 × 10−2 within less than 5 ofdm symbols even for such a high doppler rate.
robust downlink beamforming using covariance channel state information. the problem of multiuser downlink beamforming is studied under the assumption that the transmitter has erroneous covariance-based channel state information (csi). the goal is to minimize the transmit power under the worst-case quality-of-service (qos) constraints. previous convex optimization-based solutions to this problem involve several coarse approximations of the original problem. in our proposed solution, such coarse approximations are avoided and an exact representation of the worst-case solution is obtained using lagrange duality. the so-obtained problem is then converted to a convex form using semidefinite relaxation (sdr). computer simulations show that the sdr step does not involve any approximation as the resulting solution is always rank-one. simulation results demonstrate substantial performance improvements over earlier worst-case optimization-based downlink beamforming techniques.
novel schemes for nonlinear acoustic echo cancellation based on filter combinations. nonlinear acoustic echo cancellers (nlaec) are becoming increasingly important in hands-free applications. however, in some situations, an nlaec is inferior to a linear aec, especially when the channel generates a negligible (or no) nonlinear echo. in general, the ratio of the linear to nonlinear echo signal power is unknown a priori, and will vary over time, thus making it difficult to know if an nlaec would improve or degrade the cancellation. in this paper, we present two novel solutions to this problem based on the adaptive combination of linear and nonlinear echo cancellers. both solutions perform efficiently regardless of the level of nonlinear echo. the benefits and robustness of both schemes are illustrated by experiments using laplacian colored noise and speech input signals.
power-aware content-adaptive h.264 video encoding. h.264 is a computationally intensive video codec striving for achieving the best quality for the compressed video. the computational complexity poses as a challenge for power-constrained applications. we present a system level complexity reduction for h.264 video encoding by allocating resources based on computational complexity and quality trade-off. we develop a framework which allocates the computational power of the encoder adaptive to video contents and also scales with the available battery power using a roi classification method. analysis is done to profile the key modules of the encoder which can be power-optimized while allocating resources. the results of the encoder module analysis are combined with the motion content analysis to obtain a power efficient encoder parameter set which reduces the computations and hence the power consumed. our simulation results on the jm h.264 framework confirm our hypothesis and computational savings of more than 50% with quality degradation less than 1% is achieved thereby extending it's feasibility for battery powered wireless devices.
strategies for modeling reverberant speech in the feature domain. the length of the room impulse response characterizing the acoustic path between speaker and microphone is significantly larger than the length of the analysis window used for feature extraction in automatic speech recognition (asr) systems. therefore, reverberation caused by multi-path propagation of sound waves from the speaker to distant-talking microphones has a dispersive effect on speech feature sequences. this dispersive effect causes a mismatch between the input speech and the acoustic models of the recognizer, usually trained on clean speech, and leads to a significant reduction of recognition performance. in this contribution, different strategies for obtaining acoustic models capturing the dispersive effect of reverberation are investigated in terms of modeling accuracy, flexibility with respect to changing reverberation conditions, effort for obtaining the reverberation representation and decoding complexity.
motion effect modeling in multipath configuration using warping based lag-doppler filtering. the estimation of the impulse response (ir) of a propagation channel is necessary for a large number of acoustic applications: underwater communication, detection and localization, etc. basically, it informs us about the distortions of a transmitted signal in one channel. this operation is usually subject to additional distortions due to the motion of the transmitter-channel-receiver configuration. this paper points on the effects of the motion while estimating the ir by matching filtering between the transmitted and the received signals and introduces a new motion compensation method. knowing the transmitted signal, the “apparent” speed of each propagation path can be estimated using wideband ambiguity function [1]. indeed, some interference appears in the wideband ambiguity plane because of the multipath propagation. a warping-based lag-doppler filtering method is proposed allowing us to accurately estimate the ir of the channel.
data-driven online variational filtering in wireless sensor networks. in this paper, a data-driven extension of the variational algorithm is proposed. based on a few selected sensors, target tracking is performed distributively without any information about the observation model. tracking under such conditions is possible if one exploits the information collected from extra inter-sensor rssi measurements. the target tracking problem is formulated as a kernel matrix completion problem. a probabilistic kernel regression is then proposed that yields a gaussian likelihood function. the likelihood is used to derive an efficient and accelerated version of the variational filter without resorting to monte carlo integration. the proposed data-driven algorithm is, by construction, robust to observation model deviations and adapted to non-stationary environments.
evaluation of a fused fm and cepstral-based speaker recognition system on the nist 2008 sre. in this paper, the fusion of two speaker recognition subsystems, one based on frequency modulation (fm) and another on mfcc features, is reported. the motivation for their fusion was to improve the recognition accuracy across different types of channel variations, since the two features are believed to contain complementary information. it was found that the mfcc-based subsystem outperformed the fm-based subsystem on telephone conversations from nist sre-06 dataset, while the opposite was true for nist sre-08 telephone data. as a result, the fm-based subsystem performed as well as the mfcc-based subsystem and their fusion gave up to 23% relative improvement in terms of eer over the mfcc subsystem alone, when evaluated on the nist 2008 core condition.
gain allocation in proportionate-type nlms algorithms for fast decay of output error at all times. in this paper, we propose three new proportionate-type nlms algorithms: the water filling algorithm, the feasible water filling algorithm, and the adaptive μ-law proportionate nlms (mpnlms) algorithm. the water filling algorithm attempts to choose the optimal gains at each time step. the optimal gains are found by minimizing the mean square error (mse) at each time with respect to the gains, given the previous mean square weight deviations. while this algorithm offers superior convergence times, it is not feasible. the second algorithm is a feasible version of the water filling algorithm. the adaptive mpnlms (ampnlms) algorithm is a modification of the mpnlms algorithm. in the mpnlms algorithm, the parameter μ of the μ-law compression is constant. in the ampnlms algorithm the parameter μ is allowed to vary with time. this modification allows the algorithm more flexibility when attempting to minimize the mse. compared with several feasible algorithms, the ampnlms algorithm has the fastest mse decay for almost all times.
modelling uncertainty in transcriptome measurements enhances network component analysis of yeast metabolic cycle. using high throughput dna binding data for transcription factors and dna microarray time course data, we constructed four transcription regulatory networks and analysed them using a novel extension to the network component analysis (nca) approach. we incorporated probe level uncertainties in gene expression measurements into the nca analysis by the application of probabilistic principal component analysis (ppca), and applied the method to data from yeast metabolic cycle. analysis shows statistically significant enhancement to periodicity in a large fraction of the transcription factor activities inferred from the model. for several of these we found literature evidence of post-transcriptional regulation. accounting for probe level uncertainty of microarray measurements leads to improved network component analysis. transcription factor profiles showing greater periodicity at their activity levels, rather than at the corresponding mrna levels, for over half the regulators in the networks points to extensive post-transcriptional regulations.
field lines and players detection and recognition in soccer video. objects like field lines and players are important for semantic analysis in soccer video. in this paper, we propose effective methods for field lines and players detection and recognition. regions of field lines and players are first segmented from shot of wide angle view. gray value top-hat transform is then performed on the segmented region to detect field lines. mid-lines, end-lines and penalty-lines are then recognized based on their positions. template matching method is adopted to detect and recognize players. four types of templates for players are matched on the segmented region. accurate position of player can be obtained after template matching, and the type of player is also identified. experiment results on various data-sets with different production styles show effectiveness of our method.
minimum subspace noise tracking for noise power spectral density estimation. speech enhancement is the processing of speech signals in order to improve one or more perceptual aspects. if the statistics of the clean signal and the noise process are explicitly known, enhancement could be ‘optimally’ accomplished (minimizing a distortion measure between the clean and the estimated signals). in practice however, these statistics are not explicitly available, and the overall enhancement accuracy critically depends on the estimation quality of the unknown statistics. the estimation of noise (and speech) statistics is particularly a critical issue and a challenging problem under non-stationary noise conditions. in this paper, we investigate the noise floor estimation using subspace decomposition. we examine the speech dft rank limited assumption. we propose a new noise psd estimation scheme (called minimum subspace noise tracking (msnt)). the proposed scheme can be interpreted as a combination of the subspace structure and the minimum statistics tracking. experimental investigation of the msnt tracking performance and comparison with the state of the art is also presented.
monotonic optimization framework for the miso ifc. resource allocation and transmit optimization for the multiple-antenna gaussian interference channel are important but difficult problems. recently, there has been a large interest in algorithms that find operating points which are optimal in the sum-rate, proportional-fair, or minimax sense. finding these points entails solving a nonlinear, non-convex optimization problem. in this paper, we develop an algorithm that solves these problems exactly, to within a prescribed level of accuracy and in a finite number of steps. the main idea is to rewrite the objective functions so that methods for monotonic optimization can be used. more precisely, we write each objective function as a difference between two functions which are strictly increasing over a normal constraint set. the so-obtained reformulated, equivalent problem can then be solved efficiently by using so-called polyblock optimization. numerical examples illustrate the advantages of the proposed framework compared to an exhaustive grid search.
a unified view for discriminative objective functions based on negative exponential of difference measure between strings. this paper presents a novel unified view of a wide variety of objective functions suitable for discriminative training applied to sequential pattern recognition problems, such as automatic speech recognition. focusing on a central component of conventional objective functions, the sum of modified joint probabilities of observations and strings, the analysis generalizes these objective functions by weighting each term in the sum by an important function, the negative exponential of difference measure between strings. the interesting and valuable results of this investigation are highlighted in a comprehensive relationship chart that covers all of the common approaches (maximum mutual information, minimum classification error, minimum phone/word error), as well as corresponding novel generalizations and modifications of those approaches.
using filter banks to enhance images for fluid lens cameras based on color correlation. the novel field of fluid lens cameras introduces unique image processing challenges. intended for surgical applications, these fluid optics systems have improved miniaturization over glass lenses and do not have moving parts while zooming. however, the liquid medium creates non-uniform color blur, which causes certain color planes to appear sharper than others. we propose an adapted perfect reconstruction filter bank that uses high frequency sub-bands of sharp color planes to improve blurred color planes. the approach is refined by adjusting the decomposition level based on limited channel information. this paper primarily considers the use of a sharp green color plane to improve a blurred blue color plane. more generally, these methods could improve the red color plane as well as any system with high edge correlation between two images.
maximum-likelihood estimation of autoregressive models with conditional independence constraints. we propose a convex optimization method for maximum likelihood estimation of autoregressive models, subject to conditional independence constraints. this problem is an extension to times series of the classical covariance selection problem in graphical modeling. the conditional independence constraints impose quadratic equalities on the autoregressive model parameters, which makes the maximum likelihood estimation problem nonconvex and difficult to solve. we formulate a convex relaxation and prove that it is exact when the sample covariance matrix is block-toeplitz. we also observe experimentally that in practice the relaxation is exact under much weaker conditions. we discuss applications to topology selection in graphical models of time series, by enumerating all possible topologies, and ranking them using information-theoretic model selection criteria. the method is illustrated by an example of air pollution data.
no-reference video quality evaluation for high-definition video. a no-reference video quality metric for high-definition video is introduced. this metric evaluates a set of simple features such as blocking or blurring, and combines those features into one parameter representing visual quality. while only comparably few base feature measurements are used, additional parameters are gained by evaluating changes for these measurements over time and using additional temporal pooling methods. to take into account the different characteristics of different video sequences, the gained quality value is corrected using a low quality version of the received video. the metric is verified using data from accurate subjective tests, and special care was taken to separate data used for calibration and verification. the proposed no-reference quality metric delivers a prediction accuracy of 0.86 when compared to subjective tests, and significantly outperforms psnr as a quality predictor.
using fourier-based shape alignment to add geometric prior to snakes. in this paper, we present a new algorithm of snakes with geometric prior. a method of shape alignment using fourier coefficients is introduced to estimate the euclidean transformation between the evolving snake and a template of the searched object. this allows the definition of a new field of forces making the evolving snake to have a shape similar to the template one. furthermore, this strategy can be used to manage several possible templates by computing a shape distance to select the best one at each iteration. the new method also solves some well-known limitations of snakes such as evolution in concave boundaries, and enhances the robustness to noise and partially occluded objects. a series of experimental results is presented to illustrate performances.
a semi-blind em algorithm for overcomplete ica. overcomplete independent component analysis (ica) is a challenge of ica to estimate more sources from less mixtures. the statistical properties of the sources such as sparsity are often assumed to solve the problem. other available information about the sources such as waveform, however, is scarcely used. motivated by the fact that semi-blind ica in complete case can improve the potential of ica by incorporating source information, this paper proposes a semi-blind algorithm for overcomplete ica by explicitly utilizing waveform information about some sources. an approximate expecta tion-maximization (em) algorithm is explored to provide normal cost function of the semi-blind algorithm while the prior information is utilized to form an extended one. computer simulations results demonstrate that the proposed algorithm has much improved performance in snr, convergence speed, and elimination of order ambiguity compared to the original em algorithm.
asynchronous stereo vision system for front-vehicle detection. this study uses two low-cost and compact cmos cameras to construct an asynchronous binocular system and proposes an effective real-time front-vehicle detection algorithm with the binocular system. the proposed vehicle detection algorithm uses the edge information to detect the region of each front vehicle, and then computes the disparities of the front vehicles by an adaptive search method. according to the disparity values, the relative distances between the front and the host vehicles can be computed. the proposed algorithm of the manuscript conquers the asynchronous exposure problem and cost issue of a binocular system. experimental results show that the proposed system can robustly and accurately detect obstacles or other vehicles in real time under different illumination and road conditions.
an improved approach for image segmentation based on color and local homogeneity features. in this paper, we propose an improved approach for image segmentation based on color and local homogeneity features. a given image is transformed into a quantized image by a self-constructing fuzzy clustering. then, a color-based region image and an initial seeded region image are obtained from the quantized image by color-based and homogeneity-based region growing methods, respectively. after that, we combine these two images to generate a refined seeded region image and obtain an initial segmented image by a region-based region growing. finally, merging based on color similarities and sizes of regions is performed for avoiding the problem of over-segmentation. compared with the other method, experimental results show that the segmented regions obtained by our approach are more reasonable and precise.
latent topic modelling of word co-occurence information for spoken document retrieval. in this paper, we present a word topic model (wtm) approach, discovering the co-occurrence relationship between words as well as the long-span latent topic information, for spoken document retrieval (sdr). a given document as a whole is modeled as a composite wtm model for generating an observed query. the underlying characteristics and different kinds of model structures are extensively investigated, while the performance of wtm is thoroughly analyzed and verified by comparison with a few existing retrieval models on the tdt-2 sdr task. we also attempt to incorporate part-of-speech (pos) weighting into the representations of the query observations and the wtm models for obtaining better retrieval performance.
parameter estimation of non-rayleigh rcs models for sar images based on the mellin transformation. the mellin transformation-based method is developed to estimate the parameters of non-rayleigh radar cross section (rcs) models for synthetic aperture radar (sar) images from the observed image. models investigated include heavy-tailed rayleigh and weibull. for each model, we consider the three kinds of images: intensity, square-root of intensity, and multi-look averaged amplitude. using the mellin transformation, we derive the analytical expressions of the first two second-kind cumulants for speckle and rcs respectively, and obtain the estimators according to the multiplicative model of sar images and the mellin convolution. results of parameter estimation from monte carlo simulation and real sar images demonstrate that the proposed estimators, which are easy to implement in the form of closed expressions, are efficient in estimating the parameters of non-rayleigh rcs models from the observed sar images.
a study of pronunciation verification in a speech therapy application. techniques are presented for detecting phoneme level mispronunciations in utterances obtained from a population of impaired children speakers. the intended application of these approaches is to use the resulting confidence measures to provide feedback to patients concerning the quality of pronunciations in utterances arising within interactive speech therapy sessions. the pronunciation verification scenario involves presenting utterances of known words to a phonetic decoder and generating confusion networks from the resulting phone lattices. confidence measures are derived from the posterior probabilities obtained from the confusion networks. phoneme level mispronunciation detection performance was significantly improved with respect to a baseline system by optimizing acoustic models and pronunciation models in the phonetic decoder and applying a nonlinear mapping to the confusion network posteriors.
quadtree structured restoration algorithms for piecewise polynomial images. iterative shrinkage of sparse and redundant representations are at the heart of many state of the art denoising and deconvolution algorithms. they assume the signal is well approximated by a few elements from an overcomplete basis of a linear space. if one instead selects the elements from a nonlinear manifold it is possible to more efficiently represent piecewise polynomial signals. this suggests that image restoration algorithms based around nonlinear transformations could provide better results for this class of signals. this paper uses iterative shrinkage ideas and a nonlinear quadtree decomposition to develop image restoration algorithms suitable for piecewise polynomial images.
q-sift: efficient feature descriptors for distributed camera calibration. we consider camera self-calibration, i.e. the estimation of parameters for camera sensors, in the setting of a visual sensor network where the sensors are distributed and energy-constrained. with the objective of reducing the communication burden and thereby maximizing network lifetime, we propose an energy-efficient approach for self-calibration where feature points are extracted locally at the cameras and efficient descriptions for these features are transmitted to a central processor that performs the self-calibration. specifically, in this work we use reduced-dimensionality quantized approximations as efficient feature descriptors. the effectiveness of the proposed technique is validated through feature matching, and epipolar geometry estimation which enable self-calibration of the network.
vibe: a powerful random technique to estimate the background in video sequences. background subtraction is a crucial step in many automatic video content analysis applications. while numerous acceptable techniques have been proposed so far for background extraction, there is still a need to produce more efficient algorithms in terms of adaptability to multiple environments, noise resilience, and computation efficiency. in this paper, we present a powerful method for background extraction that improves in accuracy and reduces the computational load. the main innovation concerns the use of a random policy to select values to build a samples-based estimation of the background. to our knowledge, it is the first time that a random aggregation is used in the field of background extraction. in addition we propose a novel policy that propagates information between neighboring pixels of an image. experiment detailed in this paper show how our method improves on other widely used techniques, and how it outperforms these techniques for noisy images.
robust word boundary detection in spontaneous speech using acoustic and lexical cues. we consider the problem of word boundary detection in spontaneous speech utterances. acoustic features have been well explored in the literature in the context of word boundary detection; however, in spontaneous speech of switchboard-i corpus, we found that the accuracy of word boundary detection using acoustic features is poor (f-score ∼ 0.63). we propose a new feature - that captures lexical cues in the context of the word boundary detection problem. we show that including proposed lexical feature along with the usual acoustic features, the accuracy of the word boundary detection improves considerably (f-score ∼ 0.81). we also demonstrate the robustness of our proposed feature in presence of different noise levels for additive white and pink noise.
trajectory training considering global variance for hmm-based speech synthesis. this paper presents a novel method for training hidden markov models (hmms) for use in hmm-based speech synthesis. the primary goal of hmm parameter optimization is to ensure that parameters generated from the trained models exhibit similar properties to natural speech. in this paper, two major problems in conventional training are addressed: 1) the inconsistency between the training and synthesis optimization criterion; and 2) the over-smoothing caused by the statistical modeling process. the proposed method integrates the global variance (gv) criterion into a trajectory training method to give a unified framework for both training and synthesis which provides both a consistent optimization criterion and a closed form solution for parameter generation. the experimental results demonstrate that the proposed method yields a significant improvement in the naturalness of synthetic speech.
eeg-based emotion recognition in music listening: a comparison of schemes for multiclass support vector machine. currently, how to equip machines with the ability for properly recognizing users' felt-emotion during multimedia presentation is a growing issue. in this study we focused on the approach for recognizing music-induced emotional responses from brain activity. a comparative study was conducted to testify the feasibility of using hierarchical binary classifiers to improve the classification performance as compared with nonhierarchical schemes. according to our classification results, we not only found that using one-against-one scheme of hierarchical binary classifier results in an improvement to performance, but also established an alternative solution for emotion recognition by proposed model-based scheme depending on 2d emotion model.
on simulation of first-order auto-regressive processes with near laplace marginals. the focus of this paper is the modeling of a class of stationary non-gaussian auto-regressive processes that often find applications in statistical signal processing. we propose a general simulation procedure for constructing a time series model with a near-laplace marginal distributions. our approach is based on a class of monte carlo rejection algorithms. a theoretical analysis of the average complexity of the proposed algorithms for simulating the time series model is included.
aerial image registration using projective polar transform. image registration is an essential step in many image processing applications that need visual information from multiple images for comparison, integration or analysis. recently researchers have introduced image registration techniques using the log-polar transform (lpt) for its rotation and scale invariant properties. however, the accuracy of the approach limits by the number of samples used in the mapping process, which affects directly the computational cost. motivated by the success of lpt based approach and its limitation, we propose a novel projective polar transform (ppt) based image registration method that is robust to translation, scale, and rotation and yields high accuracy while requires low computational cost. unlike lpt that 2d interpolation is needed in the mapping process, our method uses one-to-one mapping mechanism that directly arranges image from cartesian to polar coordinate according to pre-computed ppt map. an innovative projection mechanism is proposed to reduce the image from two to one dimensional vectors. with the proposed approach, the mapping procedure is accelerated and the matching process can be performed in 1d. this results in great reduction of the computational cost.
achievable throughput approximation for rbd precoding at high snrs. in this paper, we study the achievable throughput for regularized block diagonalization (rbd) precoding in multi-user mimo broadcast channels at high snrs. by applying an analytical framework for a high snr affine approximation to capacity, we derive the multiplexing gains and the power offsets for rbd in two cases separately. in the first case, we assume that the aggregate number of receive antennas is less than or equal to the number of transmit antennas. it is found that rbd can maintain the same multiplexing gain as dirty paper coding (dpc) and block diagonalization (bd) precoding at high snrs and has a smaller power offset than bd. the sum rate differences relative to dpc and bd are analyzed and bounded as simple functions of the system parameters. in the second case, we assume that the aggregate number of receive antennas is larger than the number of transmit antennas. although rbd can still be performed, the achievable throughput is degraded with an increasing number of receive antennas. the benefit of spatial multiplexing is completely lost due to a unit spatial multiplexing gain at high snrs.
main vowel domain tone modeling with lexical and prosodic analysis for mandarin asr. the tone is a distinctive discriminative feature in mandarin chinese. often functional, yet seldom thorough are most large-scale mandarin speech recognition systems in treating tone modeling. in particular, many lack the necessary sophistication to deal with the myriad variations arising from the combination of acoustic and lexical contexts. this paper reports an attempt to account for these variabilities and to bring richer tone modeling into the ibm mandarin broadcast transcription system. in particular, we describe a system that combines the embedded approach and a novel explicit tone modeling technique characterized by a. robust tone tracking in the main-vowel domain, and b. context-dependent models with lexical and prosodic contexts. the proposed method is validated on a connected-digits set and subsequently evaluated on a large-vocabulary broadcast transcription task. it is shown that 14.8% and 5.4% relative reductions in character error rate are achieved respectively.
voice convergin: speaker de-identification by voice transformation. speaker identification might be a suitable answer to prevent unauthorized access to personal data. however we also need to provide solutions to secure transmission of spoken information. this challenge divides into two major aspects. first, the secure transmission of the content of the spoken input and second the secure transmission of the identity of the speaker. in this paper we concentrate on the latter, i.e. how to securely transmit information via voice without revealing the identity of the speaker to unauthorized listeners. in order to make the first steps toward solving this problem we study in this paper the potential of voice transformation for speaker de-identification. we use two speaker identification approaches to verify the success of de-identification with voice transformation, a gmm-based and a phonetic approach, and study different voice transformation strategies to disguise speaker identity information while preserving understandability.
statistical nonidentifiability of close emitters: maximum-likelihood estimation breakdown and its gsa analysis. we investigate the “ambiguity region” associated with erroneous maximum-likelihood (ml) direction-of-arrival (doa) estimates of closely spaced signals, near and below the “resolution limit”. we demonstrate that the general statistical analysis (gsa) technique can accurately predict the ambiguity region for a given scenario. we consider that this prediction may be used together with the barankin bound (bb) to form a more comprehensive description of maximum-likelihood estimation (mle) performance in the problematic “threshold region” where ml techniques suffer from a dramatic failure rate (“performance breakdown”).
the expected amplitude of overlapping partials of harmonic sounds. in analyzing polyphonic signals, the handling of overlapping partials is one important problem. the assumptions usually made for partial overlaps are the additivity of the linear spectrum or that of the power spectrum. in this study, the expected amplitude of two overlapping partials is derived based on the assumption that the partials overlap at the same frequency and the phase is uniformly distributed. an overlap chain rule algorithm is proposed to estimate the amplitude for the case that more than two partials overlap. the proposed algorithm has demonstrated its better accuracy over the usual two model assumptions.
information hiding for g.711 speech based on substitution of least significant bits and estimation of tolerable distortion. in this paper, we propose a novel data hiding technique for g.711 speech based on the lsb substitution method. the novel feature of the proposed method is that a low-bitrate encoder, g.726 adpcm, is used as a reference for deciding how many bits can be embedded in a sample. experiments showed that the method outperformed the simple lsb substitution method and the selective embedding method proposed by aoki. we achieved 4-kbit/s embedding with almost no subjective degradation of speech quality, and 10 kbit/s while keeping good quality.
a pixel-wise, learning-based approach for occlusion estimation of iris images in polar domain. on normalized iris images, there are many kinds of noises, such as eyelids, eyelashes, shadows or specular reflections, that often occlude the true iris texture. if high recognition rate is desired, those occluded areas must be estimated accurately in order for them to be excluded during the matching stage. in this paper, we propose a unified, probabilistic and learning-based approach to estimate all kinds of occlusions within one unified model. experiments have shown that our method not only estimates occlusion very accurately, but also does it with high speed, which makes it useful for practical iris recognition systems.
classification via group sparsity promoting regularization. recently a new classification assumption was proposed in [1]. it assumed that the training samples of a particular class approximately form a linear basis for any test sample belonging to that class. the classification algorithm in [1] was based on the idea that all the correlated training samples belonging to the correct class are used to represent the test sample. the lasso regularization was proposed to select the representative training samples from the entire training set (consisting of all the training samples). lasso however tends to select a single sample from a group of correlated training samples and thus does not promote the representation of the test sample in terms of all the training samples from the correct group. to overcome this problem, we propose two alternate regularization methods, elastic net and sum-over-l2-norm. both these regularization methods favor the selection of multiple correlated training samples to represent the test sample. experimental results on benchmark datasets show that our regularization methods give better recognition results compared to [1].
neural network based language models for highly inflective languages. speech recognition of inflectional and morphologically rich languages like czech is currently quite a challenging task, because simple n-gram techniques are unable to capture important regularities in the data. several possible solutions were proposed, namely class based models, factored models, decision trees and neural networks. this paper describes improvements obtained in recognition of spoken czech lectures using language models based on neural networks. relative reductions in word error rate are more than 15% over baseline obtained with adapted 4-gram backoff language model using modified kneser-ney smoothing.
instantaneous pose estimation using rotation vectors. an algorithm for estimating the pose, i.e., translation and rotation, of an extended target object is introduced. compared to conventional methods, where pose estimation is performed on the basis of time-of-flight (tof) measurements between external sources and sensors attached to the object, the proposed approach directly uses the amplitude values measured at the sensors for estimation purposes without an intermediate tof estimation step. this is achieved by modeling the wave propagation by a nonlinear dynamic system comprising a system and a measurement equation. the nonlinear system equation includes a model of the time-variant structure of the object rotation based on rotation vectors. as a result, the measured amplitude values at the sensors can be processed instantaneously in a recursive fashion. uncertainties in the measurement process are systematically considered by employing a stochastic filter for estimating the pose, i.e., the state of the nonlinear dynamic system.
a low complexity orthogonal matching pursuit for sparse signal approximation with shift-invariant dictionaries. we propose a variant of orthogonal matching pursuit (omp), called locomp, for scalable sparse signal approximation. the algorithm is designed for shift-invariant signal dictionaries with localized atoms, such as time-frequency dictionaries, and achieves approximation performance comparable to omp at a computational cost similar to matching pursuit. numerical experiments with a large audio signal show that, compared to omp and gradient pursuit, the proposed algorithm runs in over 500 less time while leaving the approximation error almost unchanged.
mobile media search. this panel paper presents motivations for discussing mobile media search and contains statements from the panelists who are industry research leaders in this field.
unified speech and audio coding scheme for high quality at low bitrates. traditionally, speech coding and audio coding were separate worlds. based on different technical approaches and different assumptions about the source signal, neither of the two coding schemes could efficiently represent both speech and music at low bitrates. this paper presents a unified speech and audio codec, which efficiently combines techniques from both worlds. this results in a codec that exhibits consistently high quality for speech, music and mixed audio content. the paper gives an overview of the codec architecture and presents results of formal listening tests comparing this new codec with he-aac(v2) and amr-wb+. this new codec forms the basis of the reference model in the ongoing mpeg standardization activity for unified speech and audio coding.
signal processing challenges for future wireless communications. the mobile internet has finally arrived with the sky-rocketing usage increase of hspa. lte, wimax and evolved wifi are the upcoming wireless standards which are based on ofdm and mimo. the mentioned standards have already started the evolution process with lte-advanced, ieee 802.16m and ieee 802.11n. new technology building blocks are on its way like cooperative mimo, relaying and self-organizing networks. increase of data-rate is one target, but the energy consumption both on the terminal and network side are important as well. this paper discusses the challenges imposed by developments in the wireless industry. advanced signal processing can play a major role in addressing these challenges.
language identification of individualwords in a multilingual automatic speech recognition system. this paper presents a new algorithm for identifying the language of words in a multilingual automatic speech recognition system. the new algorithm uses as input written words and it is composed of a method for language modelling and a method to select the language of a given word based on the available models. we also present two selection rules for the model's parameters. one of the rules uses a free parameter that controls the accuracy of the resulted model, as well as its size. on average, the classification accuracy of the new algorithm is above 70% for the first best and above 80% for the first two best.
sparse decomposition over non-full-rank dictionaries. sparse decomposition (sd) of a signal on an overcomplete dictionary has recently attracted a lot of interest in signal processing and statistics, because of its potential application in many different areas including compressive sensing (cs). however, in the current literature, the dictionary matrix has generally been assumed to be of full-rank. in this paper, we consider non-full-rank dictionaries (which are not even necessarily overcomplete), and extend the definition of sd over these dictionaries. moreover, we present an approach which enables to use previously developed sd algorithms for this non-full-rank case. besides this general approach, for the special case of the smoothed ℓ0 (sl0) algorithm, we show that a slight modification of it covers automatically non-full-rank dictionaries.
overlay collaboration towards reduced bandwidth costs in multi-view streaming. delivering high-quality multiview video (mv) through internet is very challenging due to its excessive consumption on server bandwidth resources. existing solutions encode video contents independently for each view and deliver them separately in isolated view channels, without leveraging the features of mv and taking advantage of multiview video coding(mvc). to minimize the server bandwidth costs, we introduce a novel overlay collaboration framework that unifies all view channels to cooperate in delivering mv: i pictures in mvc are shared among them instead of requesting from server respectively; surplus resources of hotspot view channels are effectively utilized to help channels with insufficient resources, both of which contribute to remarkable reduction in server bandwidth costs. simulation experiments show that our method achieves more than 40% reduced bandwidth costs on server while maintaining scalability and resilience to user dynamics.
improved prosody generation by maximizing joint likelihood of state and longer units. the current state-of-art hmm-bsed tts can produce highly intelligible output speech and deliver a decent segmental quality. however, its prosody, especially at the phrase or sentence level, tends to be bland. the blandness of synthesized prosody is partially due to the fact that a state-based hmm is rather inadequate in modeling a global, hierarchical prosodic structure at a sentence or phrase level. in this study, the prosody of longer units are first modeled explicitly by appropriate parametric distributions. the resultant models are then integrated with the state-level baseline models to generate an optimal prosody by maximizing the joint likelihood of all, from state to longer, units. experimental results in both mandarin and english show consistent improvements over the state-based baseline system. the improvements are both objectively measurable and subjectively perceivable.
adaptive dereverberation of speech signals with speaker-position change detection. this paper proposes a method for adaptive speech dereverberation and speaker-position change detection, which have not previously been addressed. signal transmission channels in rooms are modeled as auto-regressive systems in individual frequency bands. the proposed method adaptively estimates the regression coefficients of this model, which are called room regression coefficients (rrcs). the proposed method has two distinguishing features: (1) the method is based on the weighted recursive least squares algorithm, which enables an efficient rrc-estimate update as well as a fast convergence rate; (2) the method detects changes in speaker position and so can quickly catch up with the sudden channel changes that such position changes cause. detection is realized by finding time frames where the power of dereverberated speech is anomalously amplified. experimental results showed that the proposed method attained convergence in 5 seconds and successfully detected changes in speaker position.
sparse boosting. we propose a boosting algorithm that seeks to minimize the adaboost exponential loss of a composite classifier using only a sparse set of base classifiers. the proposed algorithm is computationally efficient and in test examples produces composite classifiers that are sparser and generalize as well those produced by adaboost. the algorithm can be viewed as a coordinate descent method for the l1-regularized adaboost exponential loss function.
improved lattice-based spoken document retrieval by directly learning from the evaluation measures. lattice-based approaches have been widely used in spoken document retrieval to handle the speech recognition uncertainty and errors. position specific posterior lattices (pspl) and confusion network (cn) are good examples. it is therefore interesting to derive improved model for spoken document retrieval by properly integrating different versions of lattice-based approaches in order to achieve better performance. in this paper we borrow the framework of ‘learning to rank’ from text document retrieval and try to integrate it into the scenario of lattice-based spoken document retrieval. two approaches are considered here, adarank and svm-map. with these approaches, we are able to learn and derived improved models using different versions of pspl/cn. preliminary experiments with broadcast news in mandarin chinese showed significant improvements.
parameter estimation of multidimensional nmr signals based on high-resolution subband analysis of 2d nmr projections. nmr spectroscopy is a powerful technique used in protein research for comprehensive functional characterizations, e.g. structure determination at atomic resolution. due to the molecular size (typically≫1000 atoms), protein nmr spectra contain a large number of signal frequencies. resolving these requires high-dimensional spectroscopy. however, when the number of frequency exceeds three, conventional approaches start to demand unrealistic long experiment time, and the data analysis becomes challenging. in this paper we explore a combination of novel methods: data from 5d nmr experiments are recorded as a series of 2d projections, which are then subjected to 2d subband filters and 2d ls-esprit for estimation of signal parameters. based on the relations established between 5d nmr signals and their 2d counterparts, projection spectroscopy allows to extract highly similar information as what would be found in conventional 5d nmr experiments; however, while the latter would require months of experiment time, the recording of all necessary projections can be accomplished within 1–2 days. preliminary results show the efficiency of the method with respect to accuracy and resolution of the parameter estimates as compared with conventional methods.
spatiotemporal latent semantic cues for moving people tracking. effective and robust visual tracking is one of the most important tasks for the intelligent visual surveillance. in this paper, we proposed a novel method for detecting and tracking moving people using the spatiotemporal latent semantic cues and the incremental eigenspace tracking techniques. during tracking process, the target appearance model is incrementally learned in low dimensional tensor eigenspace by adaptively updating the eigenbasis and sample mean. at the same time, the spatiotemporal latent semantic cues calibrate the estimation of tracking and detect new moving people coming in the same surveillance scene. experiment results show that with the calibration based on spatiotemporal latent semantic cues, the proposed method can track the moving people automatically and effectively.
low complexity azimuth and elevation estimation for arbitrary array configurations. in this paper we propose azimuth and elevation angle of arrival estimation algorithms for arbitrary array configurations. the proposed algorithms extend the polynomial rooting intersection for multidimensional estimation (prime) [1] and statistically efficient modified variable projection (mvp) [2] algorithms to arbitrary sensor array configurations without explicit knowledge of the steering vector. the proposed algorithms exploit the concept of manifold separation technique (mst) [3], [4]. thus, the data are processed in the element-space domain and are not subject to mapping errors. moreover, closed-form derivatives of the weighted subspace fitting (wsf) cost function are obtained, even for real-world arrays with imperfections, making the proposed mvp computationally attractive. the obtained estimates for both elevation and azimuth show an error variance close to the cramér-rao lower bound (crlb).
study of the quaternion lms and four-channel lms algorithms. the recently proposed quaternion least-mean-square (qlms) algorithm for adaptive filtering of three- and four-dimensional signals has been analysed in the context of multi-step ahead prediction. for rigour, the relationship between multichannel lms (mlms) and qlms is examined, and their differences are highlighted. this is achieved both in terms of the input-output relationship and in terms of the dynamics of weight updates. the convergence of qlms is investigated and stability bounds confirm that qlms and mlms are fundamentally different. simulations on both synthetic and real world multidimensional signals support the analysis.
application of voice conversion for cross-language rap singing transformation. voice conversion enables generation of a desired speaker's voice from audio recordings of another speaker. in this paper, we focus on a music application and describe the first steps towards generating voices of music celebrities using conventional voice conversion techniques. specifically, rap singing transformations from english to spanish are performed using parallel training material in english. weighted codebook mapping based voice conversion with two different alignment methods and temporal smoothing of the transformation filter are employed. the first aligner uses a hmm trained for each source recording to force-align the corresponding target recording. the second aligner employs speaker-independent hmms trained from a large number of speakers. additionally, a smoothing step is devised to reduce discontinuities and to improve performance. the results of subjective evaluations indicate that both aligners perform equivalently well. the proposed smoothing technique improves both similarity to target singer and quality significantly regardless of the alignment method.
distributed karhunen-loève transform with nested subspaces. a network in which sensors observe a common gaussian source is analyzed. using a fixed linear transform, each sensor compresses its high-dimensional observation into a low-dimensional representation. the latter is provided to a central decoder that reconstructs the source according to a mean squared error (mse) distortion metric. the distributed karhunen-loève transform (d-klt) has been shown to provide a (locally) optimal linear solution for compression at each sensor. while the d-klt achieves the lowest distortion linear reconstruction known, it does not maintain a nested subspace structure. in the case of ideal links to the decoder, this paper presents transforms that maintain nested subspaces, allowing the decoder to approximate a delay-limited source in an online fashion according to a desired sensor schedule. a distortion envelope for one distributed transform with nested subspace properties (d-nested-klt) is provided. in the case of i.i.d. noise to the decoder, under assumptions of power allocation over subspaces, it is also possible to achieve nested subspaces utilizing correlations between sensors' observations. results are applicable for data access over networks, and online information processing in sensor networks.
freshman design: a signal-processing approach. this paper describes development and evaluation of a freshman design course focusing on signal processing and communications, entitled “the digital world of multimedia.” the course covers basic concepts of sampling, frequency analysis, and filtering without calculus but with coverage of these topics in both audio and image processing. six labs provide collaborative, experimental learning as well as design opportunities. connections to modern technology are provided in guest lectures and reading assignments that leverage ieee magazines, and the topics provide opportunities for discussing the societal impact of signal processing technology.
complete characterization of the pareto boundary of interference-coupled wireless systems with power constraints - the log-convex case. in this paper we analyze the structure of certain power-constrained utility sets, based on the axiomatic framework of log-convex interference functions. log-convex interference functions contain convex and linear interference functions as a special case. we analyze the boundary of the set. it is shown how pareto optimality of boundary points depends on the interference coupling between the users. finally, we investigate feasible sets of signal-to-interference-plus-noise ratios for individual power constraints and a sum power constraint. we show certain properties that are desirable, e.g. in the context of cooperative game theory.
fast structure-preserving image retargeting. several different methods have been proposed for image/video retargeting while retaining the content. however, they sometimes produce some artifacts, such as ridge or structure twist. in this paper, we present a structure-preserving image resizing technique for the image retargeting applications. based on the warping-based retargeting technique proposed by wolf et al.[13], we propose an efficient and adaptive image resizing algorithm that preserves the content and image structure as best as possible. we first downsample the size of the original image by using bilinear interpolation. in order to preserve the content, we introduce the structure constraints derived from the line detection into the large linear system. then, the mapping matrices are enlarged to the original size by joint-bilateral upsampling and the resized image can be produced to preserve the content and structure as best as possible. most of the computation is on the low-resolution layer and therefore it can be very efficient. from our experiments, the proposed method can provide resized images with higher image quality and faster speed than that in [13].
using collective information in semi-supervised learning for speech recognition. training accurate acoustic models typically requires a large amount of transcribed data, which can be expensive to obtain. in this paper, we describe a novel semi-supervised learning algorithm for automatic speech recognition. the algorithm determines whether a hypothesized transcription should be used in the training by taking into consideration collective information from all utterances available instead of solely based on the confidence from that utterance itself. it estimates the expected entropy reduction each utterance and transcription pair may cause to the whole unlabeled dataset and choose the ones with the positive gains. we compare our algorithm with existing confidence-based semi-supervised learning algorithm and show that the former can consistently outperform the latter when the same amount of utterances is selected into the training set. we also indicate that our algorithm may determine the cutoff-point in a principled way by demonstrating that the point it finds is very close to the achievable peak point.
bandwidth adaptive hardware architecture of k-means clustering for intelligent video processing. k-means is a clustering algorithm that is widely applied in many fields, including pattern classification and multimedia analysis. due to real-time requirements and computational-cost constraints in embedded systems, it is necessary to accelerate k-means algorithm by hardware implementations in soc environments, where the bandwidth of the system bus is strictly limited. in this paper, a bandwidth adaptive hardware architecture of k-means clustering is proposed. experiments show that the proposed hardware has the maximum clock speed 400mhz with tsmc 90nm technology, and it can deal with feature vectors with different dimensions using five parallel modes to utilize the input bandwidth efficiently.
on the recovery of nonnegative sparse vectors from sparse measurements inspired by expanders. this paper studies compressed sensing for the recovery of non-negative sparse vectors from a smaller number of measurements than the ambient dimension of the unknown vector. we focus on measurement matrices that are sparse, i.e., have only a constant number of nonzero (and non-negative) entries in each column. for such measurement matrices we give a simple necessary and sufficient condition for l1 optimization to successfully recover the unknown vector. using a simple “perturbation” to the adjacency matrix of an unbalanced expander, we obtain simple closed form expressions for the threshold relating the ambient dimension n, number of measurements m and sparsity level k, for which l1 optimization is successful with overwhelming probability. simulation results suggest that the theoretical thresholds are fairly tight and demonstrate that the “perturbations” significantly improve the performance over a direct use of the adjacency matrix of an expander graph.
combining vts model compensation and support vector machines. it is difficult to adapt discriminative classifiers, particularly kernel based ones such as support vector machines (svms), to handle mismatches between the training and test data. in previous work adaptation was performed by modifying the kernel used with the svm, rather changing the svm parameters themselves. however an idealised form of compensation, single pass retraining, was used to alter the generative models associated with the generative kernel. in this paper vector taylor series model compensation is used. this scheme is more efficient and allows a noise model to be estimated. the performance of the new scheme is evaluated on two continuous digit tasks. on both tasks svm-rescoring outperformed the baseline vts compensated models.
registration of multimodal data for estimating the parameters of an articulatory model. being able to animate a speech production model with articulatory data would open applications in many domains. in this paper, we first consider the problem of acquiring articulatory data from non invasive image and sensor modalities: dynamic ultrasound (us) images, stereovision 3d data, electromagnetic sensors and mri. we here especially focus on automatic registration methods which enable the fusion of the articulatory features in a common frame. we then derive articulatory parameters by fitting these features with maeda's model. to our knowledge, it is the first attempt to derive articulatory parameters from features automatically extracted and registered between the modalities. results prove the soundness of the approach and the reliability of the fused articulatory data.
on gmm kalman predictive coding of lsfs for packet loss. gaussian mixture model (gmm)-based kalman predictive coders have been shown to perform better than baselinegmm recursive coders in predictive coding of line spectral frequencies (lsfs) for both clean and packet loss conditions however, these stationary gmm kalman predictive coders were not specifically designed for operation in packet loss conditions. in this paper, we demonstrate an approach to the the design of gmm-based predictive coding for packet loss channels. in particular, we show how a stationary gmm kalman predictive coder can be modified to obtain a set of encoding and decoding modes, each with different kalman gains. this approach leads to more robust performance of predictive coding of lsfs in packet loss conditions, as the coder mismatch between the encoder and decoder are minimized. simulation results show that this robust gmm kalman predictive coder performs better than other baseline gmm predictive coders with no increase in complexity. to the best of our knowledge, no previous work has specifically examined the design of gmm predictive coders for packet loss conditions.
convex analysis based minimum-volume enclosing simplex algorithm for hyperspectral unmixing. hyperspectral unmixing aims at identifying the hidden spectral signatures (or endmembers) and their corresponding proportions (or abundances) from an observed hyperspectral scene. many existing approaches to hyperspectral unmixing rely on the pure-pixel assumption, which may be violated for highly mixed data. a heuristic unmixing criterion without requiring the pure-pixel assumption has been reported by craig: the endmember estimates are determined by the vertices of a minimum-volume simplex enclosing all the observed pixels. in this paper, using convex analysis, we show that the hyperspectral unmixing by craig's criterion can be formulated as an optimization problem of finding a minimum-volume enclosing simplex (mves). an algorithm that cyclically solves the mves problem via linear programs (lps) is also proposed. some monte carlo simulations are provided to demonstrate the efficacy of the proposed mves algorithm.
parallel multi-frequency narrowband active noise control systems. this paper analyzes and optimizes narrowband active noise control systems using multiple second-order adaptive filters. theoretical analysis of the overall parallel structure is based on autocorrelation and cross-correlation matrices. analytical result shows the use of single error signal to update all adaptive filters with different input signals will introduce extra tonal components in the residual noise. an optimized algorithm that uses bandpass filters to split the fullband error signal into multiple bandlimited subband error signals according to the frequencies of reference signals is developed to improve steady-state performance.
annotating images by harnessing worldwide user-tagged photos. automatic image tagging is important yet challenging due to the semantic gap and the lack of learning examples to model a tag's visual diversity. meanwhile, social user tagging is creating rich multimedia content on the web. in this paper, we propose to combine the two tagging approaches in a search-based framework. for an unlabeled image, we first retrieve its visual neighbors from a large user-tagged image database. we then select relevant tags from the result images to annotate the unlabeled image. to tackle the unreliability and sparsity of user tagging, we introduce a joint-modality tag relevance estimation method which efficiently addresses both textual and visual clues. experiments on 1.5 million flickr photos and 10 000 corel images verify the proposed method.
capacity scaling of wireless networks with complex field network coding. network coding in wired networks has been shown to achieve considerable throughput gains relative to traditional routing networks. while the ergodic capacity of wireless multihop networks is unknown, the scaling of capacity with the number of nodes (n) has recently received increasing attention. while existing works mainly focus on networks with n source-destination pairs, this paper deals with capacity scaling in any-to-any wireless links, where each node communicates with all other nodes. complex field network coding (cfnc) is adopted at the physical layer to allow n nodes exchanging information with simultaneous transmissions from multiple sources. a hierarchical cfnc-based scheme is developed and shown to achieve asymptotically (as n → ∞) optimal quadratic capacity scaling in a dense network, where the area is fixed and the density of nodes increases. this is possible by dividing the network into many clusters, with each cluster sub-divided into many sub-clusters, hierarchically.
automatic voice assignment tool for instant casting movie system. in instant casting movie system, a personal cg character is automatically generated. the character resembles a participant in a face geometry and texture. however, the voice of a character was an alternative voice determined by the gender of the participant. therefore sometimes it's not enough to identify the personality of a cg character. in this paper, an automatic pre-scored voice assignment tool for a personal cg character is presented. voice is essential to identify a personal character as well as a face feature. our proposed system selects the most similar voice to the participants from voice database, and assigns it as a voice of cg character. voice similarity criterion is presented by combination of eight acoustic features. after assigning voice data to a personal character, the voice track is played back in synchronization with the movement of the cg character. 60 voice variations have been prepared to our voice database. validity of the assigned voice has been evaluated by mos value. the proposed method has achieved 68% of the theoretical figure that is calculated by preliminary experiments.
enhancement of reverberant speech using the celp postfilter. in this paper we investigate the application of adaptive postfiltering for the enhancement of reverberant speech. the considered method is commonly used in code excited linear prediction (celp) speech coding to lower the impact of quantization noise in the excitation signal and the spectral envelope. we show that the underlying additive noise model is accurate enough to enhance speech which is recorded in an enclosed space where the resulting early reflections are usually modeled as a convolutive distortion. by means of adaptive filtering, the amplitudes of the unwanted peaks in the excitation signal are attenuated and the signal components at the harmonic peaks are emphasized. both, single- and multi-channel dereverberation algorithms are proposed having a moderate computational complexity. experiments have shown that this approach is capable of reducing early reverberation and attenuate the “distance-effect” arising from room reflections.
a flat direct model for speech recognition. we introduce a direct model for speech recognition that assumes an unstructured, i.e., flat text output. the flat model allows us to model arbitrary attributes and dependences of the output. this is different from the hmms typically used for speech recognition. this conventional modeling approach is based on sequential data and makes rigid assumptions on the dependences. hmms have proven to be convenient and appropriate for large vocabulary continuous speech recognition. our task under consideration, however, is the windows live search for mobile (wls4m) task [1]. this is a cellphone application that allows users to interact with web-based information portals. in particular, the set of valid outputs can be considered discrete and finite (although probably large, i.e., unseen events are an issue). hence, a flat direct model lends itself to this task, making the adding of different knowledge sources and dependences straightforward and cheap. using e.g. hmm posterior, m-gram, and spotter features, significant improvements over the conventional hmm system were observed.
model assessment with kolmogorov-smirnov statistics. one of the most basic problems in science and engineering is the assessment of a considered model. the model should describe a set of observed data and the objective is to find ways of deciding if the model should be rejected. it seems that this is an ill-conditioned problem because we have to test the model against all the possible alternative models. in this paper we use the kolmogorov-smirnov statistic to develop a test that shows if the model should be kept or it should be rejected. we explain how this testing can be implemented in the context of particle filtering. we demonstrate the performance of the proposed method by computer simulations.
factor analysis-based information integration for arabic dialect identification. in this study, we propose a new factor analysis-based modeling technique to more clearly describe the composition of the supervector defined by the gmm model for dialect identification. the method utilizes knowledge types of information contained in the transcript file of the data. we evaluate the effects of the proposed modeling algorithm on a gmm-based arabic dialect identification system. in particular, we compare eigenchannel modeling and our proposed information integration modeling. we show that the proposed modeling can obtain a 4.23% relative eer reduction with the same total number of factors, and a 9.37% relative eer reduction with the same number of channel/session factors versus eigenchannel modeling.
bayesian large margin hidden markov models for speech recognition. this paper presents a bayesian learning approach to large margin classifier for hidden markov model (hmm) based speech recognition. we build the bayesian large margin hmms (blm-hmms) and improve the model generalization for handling unknown test environments. using blm-hmms, the variational bayesian hmm parameters are estimated by maximizing lower bound of a marginal likelihood over the uncertainties of hmm parameters. the bayesian large margin estimation is performed with frame selection mechanism, and is illustrated to meet the objective of support vector machines, i.e. maximal class margin and minimal training errors. the new objective function is not only interpreted as a discriminative criterion, but also feasible to deal with model selection and adaptive training. experiments on phone recognition show that blm-hmms perform better than other generative and discriminative models.
one-handed gesture recognition using ultrasonic doppler sonar. this paper presents a new device based on ultrasonic sensors to recognize one-handed gestures. the device uses three ultrasonic receivers and a single transmitter. gestures are characterized through the doppler frequency shifts they generate in reflections of an ultrasonic tone emitted by the transmitter. we show that this setup can be used to classify simple one-handed gestures with high accuracy. the ultrasonic doppler based device is very inexpensive - $20 usd for the whole setup including the acquisition system, and computationally efficient as compared to most traditional devices (e.g. video). these gestures, could potentially be used to control and drive a device.
compressive imaging of color images. in this paper, we propose a novel compressive imaging framework for color images. we first introduce an imaging architecture based on combining the existing single-pixel compressive sensing (cs) camera with a bayer color filter, thereby enabling acquisition of compressive color measurements. then we propose a novel cs reconstruction algorithm that employs joint sparsity models in simultaneously recovering the r, g, b channels from the compressive measurements. experiments simulating the imaging and reconstruction procedures demonstrate the feasibility of the proposed idea and the superior quality in reconstruction.
instrumentation analysis and identification of polyphonic music using beat-synchronous feature integration and fuzzy clustering. in this paper, a music instrumentation analysis and identification method is proposed. in contrast to existing systems, it tries to identify the whole instrument set in polyphonic music and also decide whether each instrument actually dominates at a particular moment or not, but without calculating the exact pitch, onset timing, or the volume of each note. moreover, it does not require the music source separation in advance. we address this problem by incorporating the beatsynchronous scheme with fuzzy clustering to analyze the instrument components. experiments show that the instrument identification process results in an 85.19% averaging recognition rate, which is comparable with other existing systems. in addition, it generates the extra time-varying instrumentation information. this information can be considered as a new mid-level feature in music information retrieval systems.
a post-processing technique for regeneration of over-attenuated speech. despite the success of recent speech enhancement algorithms, the enhanced signals still suffer from undesirable speech distortion caused by over-attenuation of weak speech spectral components. in this paper, a post-processing technique based on the regeneration of both voiced and unvoiced speech is proposed to alleviate this problem. a non-linear transformation is first applied to awiener filtered speech and the transformed signal is multiplied by a pre-estimated spectral envelop to form the regenerated speech. the resulting speech is then obtained using a weighted combination of the regenerated speech components and the filtered speech. this process significantly improves the resulting speech quality as compared to the original filtered version. it results in speech that sounds less lowpassed. also, the residual musical noise is significantly masked by the regenerated speech components. objective measures show that the quality of the resulting speech is much closer to the clean speech as compared to the original wiener filtered speech.
a pde characterization of the intrinsic mode functions. for the first time, a proof of the sifting process (sp) and so the empirical mode decomposition (emd), is given. for doing this, lower and upper envelopes are modeled in a more convenient way that helps us prove the convergence of the sp towards a solution of a partial differential equation (pde). we also prove that such a pde has a unique solution, which ensures the uniqueness of the emd decomposition. the new formulation of envelopes has another benefit. in fact, it removes interpolation problems and related issues. not only helps the modelization of envelopes to give a mathematical framework on the emd, but also, as confirmed by the numerical simulations, the pde-based emd improves a lot the classical emd.
new hybrid adaptive blind equalization algorithms for qam signals. this paper introduces new hybrid blind equalization algorithms for qam signals, the first term of which is the constant modulus criterion (cma) or its extended version (ecma) and the second are a penalty term that vanishes at constellation points coordinates. several penalties, based on cosine, gaussian and polynomial ℓ1-norm fonctions respectively are investigated. simulations show the effectiveness of these algorithms.
progressive lossy-to-lossless coding of arbitrarily-sampled image data using the modified scattered data coding method. in earlier work, demaret and iske proposed the scattered data coding (sdc) method for (single-rate) coding of arbitrarily-sampled image data. in this paper, several modifications to the sdc method are proposed in order to remove some limitations of the original scheme, improve coding efficiency, and add a progressive lossy-to-lossless coding capability. through experimental results, the proposed method is shown to yield a significant improvement in coding efficiency (relative to the original sdc method) as well as provide an efficient progressive lossy-to-lossless coding capability.
spatial filtering using directional audio coding parameters. directional audio coding (dirac) is a recent method for spatial audio processing, based on a perceptually motivated representation of spatial sound. due to its efficiency, dirac has already been proposed for spatial audio teleconferencing scenarios. modern hands-free communication systems usually include beamforming techniques to improve speech intelligibility by suppressing diffuse background noise and interfering sources. in this paper, we propose a novel spatial filtering method which can be integrated into the dirac spatial codec. it uses a spectral weighting of the recorded audio signal, where the design of the corresponding spatial filter transfer function is based on the dirac parameters, i. e., direction-of-arrival and diffuseness of the sound field. simulation results show that compared to a standard beamformer the novel technique offers significantly higher interference attenuation, while introducing similar distortion of the desired signal.
modified mpe/mmi in a transducer-based framework. in this paper we show how common training criteria like for example mpe or mmi can be extended to incorporate a margin term. in addition, a transducer-based training implementation is presented, which covers a large variety of discriminative training criteria for asr, including the standard mmi, mpe, and mce criteria, as well as the modifications to these criteria presented here. the modified criteria are directly related with the conventional large margin formulation of svms. in the proposed approach, we can take advantage of the generalization guarantees of large margin classifiers while keeping the existing framework for the discriminative training, including the efficient algorithms for conventional mpe or mmi. on the conceptual side, this allows for a direct evaluation of the margin term. finally, experimental results are presented for different large vocabulary continuous speech recognition tasks (one of which is trained on a very large amount of training data) using these modified criteria.
separation of layers from images containing multiple reflections and transparency using cyclic permutation. in the paper, we propose a new method for blind separation of an arbitrary number of images from a set of their linear mixtures with unknown coefficients. this approach is as follows. we first introduce a novel multiple correlation between one image and a set of multiple images. then this multiple correlation leads us to provide a set of simultaneous linear equations for updating each mixture of images. finally, source images are recovered by iterating between solving the sets of equations and cyclically permuting the mixtures of images. the technique can be applied for extracting multiple layers from images containing multiple reflections and transparency.
minimum-disturbance description for the development of adaptation algorithms and a new leakage least squares algorithm. usual methods for the development of adaptive filters are based on a stochastic approximation of the gradient vector and hessian matrix, or on a deterministic minimization of quadratic a posteriori output errors. gradient-based algorithms are usually placed in the first group, whereas least squares (ls) based algorithms are placed in the second group. these are just how algorithms are usually presented and analyzed and alternative descriptions exit. this paper proposes to shed new light onto known adaptation algorithms by means of a minimum-disturbance approach to the cost function together with constraints added to improve their robustness. the resulting algorithms are able to perform extremely well in many demanding applications.
a fast, accurate approximation to log likelihood of gaussian mixture models. it has been a common practice in speech recognition and elsewhere to approximate the log likelihood of a gaussian mixture model (gmm) with the maximum component log likelihood. while often a computational necessity, the max approximation comes at a price of inferior modeling when the gaussian components significantly overlap. this paper shows how the approximation error can be reduced by changing component priors. in our experiments the loss in word error rate due to max approximation, albeit small, is reduced by 50–100% at no cost in computational efficiency. furthermore, we expect acoustic models will become larger with time and increase component overlap and word error rate loss. this makes reducing the approximation error more relevant. the techniques considered do not use the original data and can easily be applied as a post-processing step to any gmm.
svm-based state transition framework for dynamical human behavior identification. this investigation proposes an svm-based state transition framework (named as stsvm) to provide better performance of discriminability for human behavior identification. the stsvm consists of several state support vector machines (ssvm) and a state transition probability (stpm). the intra-structure information and inter-structure information of a human activity are analyzed and correlated by the ssvm and stpm, respectively. the integration of the ssvm and the stpm effectively provides human behavior understanding. with a database consisting of five kinds of human behaviors: raising hand, standing up, squatting down, falling down, and sitting, the proposed algorithm has been demonstrated with a significant recognition rate of 88.6%.
regression-based clustering for hierarchical pitch conversion. this study presents a hierarchical pitch conversion method using regression-based clustering for conversion function modeling. the pitch contour of a speech utterance is first extracted and decomposed into sentence-, word and sub-syllable-level features in a top-down mechanism. the pair-wise source and target pitch feature vectors at each level are then clustered to generate the pitch conversion function. regression-based clustering, which clusters the feature vectors to achieve a minimum conversion error between the predicted and the real feature vectors is proposed for conversion function generation. a classification and regression tree (cart), incorporating linguistic, phonetic and source prosodic features, is adopted to select the most suitable function for pitch conversion. several objective and subjective evaluations were conducted and the comparison results to the gmm-based methods for pitch conversion confirm the performance of the proposed regression-based clustering approach.
enhanced error resilience of video communications for burst losses using an extended rope algorithm. video communications over wireless networks suffers various patterns of losses, including burst losses that cause great degradation in video quality. in this paper, we propose an algorithm based on recursive optimal per-pixel estimate (rope) to accurately estimate the overall distortion accounting for the loss pattern. the estimated distortion is applied to the rate-distortion (rd)-based mode selection to provide the optimal tradeoff between intra and inter coding. simulation results show that in lossy networks, the proposed extended rope algorithm achieves gains in average psnr and psnrr,f by up to 0.8 db and 3.6 db respectively. this shows that the proposed algorithm can enhance error resilience for video communications over networks with burst losses.
connecting spectral and spring methods for manifold learning. diffusion maps (diffmaps) has recently provided a general framework that unites many other spectral manifold learning algorithms, including laplacian eigenmaps, and it has become one of the most successful and popular frameworks for manifold learning to date. however, diffusion maps still often creates unnecessary distortions, and its performance varies widely in response to parameter value changes. in this paper, we draw a previously unnoticed connection between diffmaps and spring-motivated methods. we show that diffmaps has a physical interpretation: it finds the arrangement of high-dimensional objects in low-dimensional space that minimizes the elastic energy of a particular spring network. within this interpretation, we recognize the root cause of a variety of problems that are commonly observed in the diffusion maps output, including sensitivity to user-specified parameters, sensitivity to sampling density, and distortion of boundaries. we then show how to exploit the connection between diffusion map and spring criteria to create a method that can be efficiently applied post hoc to alleviate these commonly observed deficiencies in the diffusion maps output.
dirichlet process mixture models with multiple modalities. the dirichlet process can be used as a nonparametric prior for an infinite-dimensional probability mass function on the parameter space of a mixture model. the set of parameters over which it is defined is generally used for a single, parametric distribution. we extend this idea to parameter spaces that characterize multiple distributions, or modalities. in this framework, observations containing multiple, incompatible pieces of information can be mixed upon, allowing for all information to inform the final clustering result. we provide a general mcmc sampling scheme and demonstrate this framework on a gaussian-hmm mixture model applied to synthetic and major league baseball data.
component-wise pose normalization for pose-invariant face recognition. the pose variation involved in facial images significantly degrades the performance of face recognition systems. in this paper, a component-wise pose normalization method for facilitating pose-invariant face recognition is proposed. the main idea is to normalize a non-frontal facial image to a virtual frontal image component by component. in this method, we first partition the whole non-frontal facial image into different facial components and then the virtual frontal view for each component is estimated separately. the final virtual frontal image is generated by integrating the virtual frontal components. the proposed method relies only on 2d images, therefore complex 3d modeling is not needed. the experimental results using the cmu-pie database demonstrate the advantages of the proposed method.
expectation-maximization algorithm for multi-pitch estimation and separation of overlapping harmonic spectra. this paper addresses the problem of multi-pitch estimation, which consists in estimating the fundamental frequencies of multiple harmonic sources, with possibly overlapping partials, from their mixture. the proposed approach is based on the expectation-maximization algorithm, which aims at maximizing the likelihood of the observed spectrum, by performing successive single-pitch and spectral envelope estimations. this algorithm is illustrated in the context of musical chord identification.
pilot-assisted channel estimation for mimo ofdm systems using theory of sparse signal recovery. in this work, a new framework for channel estimation in mimo ofdm systems is provided. sparse channel estimation refers to estimating the time domain channel impulse response by exploiting the fact that the channel has a very few nonzero taps. we formalize the problem and drive necessary and sufficient condition on the number of pilots for perfect channel recovery which leads to a l0 norm optimization problem. a practical suboptimal solution is proposed that is a modified orthogonal matching pursuit (omp) which exploits the sparsity structure of the mimo channel. the investigations reveal that the training overhead can be drastically reduced while maintaining the same accuracy as the current state of the art techniques.
posterior-based confidence measures for spoken term detection. confidence measures play a key role in spoken term detection (std) tasks. the confidence measure expresses the posterior probability of the search term appearing in the detection period, given the speech. traditional approaches are based on the acoustic and language model scores for candidate detections found using automatic speech recognition, with bayes' rule being used to compute the desired posterior probability. in this paper, we present a novel direct posterior-based confidence measure which, instead of resorting to the bayesian formula, calculates posterior probabilities from a multi-layer perceptron (mlp) directly. compared with traditional bayesian-based methods, the direct-posterior approach is conceptually and mathematically simpler. moreover, the mlp-based model does not require assumptions to be made about the acoustic features such as their statistical distribution and the independence of static and dynamic co-efficients. our experimental results in both english and spanish demonstrate that the proposed direct posterior-based confidence improves std performance.
a polynomial segment model based statistical parametric speech synthesis sytem. in this paper, we present a statistical parametric speech synthesis system based on the polynomial segment model (psm). as one of the segmental models for speech signals, psm explicitly describes the trajectory of the features in a speech segment, and keeps the internal dynamics of the segment. in this work, spectral and excitation parameters are modeled by psms simultaneously, while the duration for each segment is modeled by a single gaussian distribution. a top-down k-means clustering technique is applied for model tying. mean trajectories acquired from psms are used directly to generate speech parameters according to the estimated segment duration. an english speech synthesizer back-end is implemented on cmu arctic corpus and the performance of the new approach is compared with the classical hmm-based one. experimental results show that psm modeling can achieve similar naturalness and intelligence of the synthetic speech as hmm modeling. the system is in the early stage of its development.
upper bound for the loss factor of energy detection of random signals in multipath fading cognitive radios. in this paper, the loss of energy detection compared with optimal sensing caused by neglecting signal correlation due to multipath fading is considered. the loss factor or relative performance of energy detection compared with optimal sensing is analyzed using pitman's asymptotic relative efficiency (are) which is defined as the ratio of the required number of samples of one detector to that of the other to yield the same detection performance in large sample scheme. under the assumption of l-tap finite impulse response (fir) channel with zero-mean independent and identically distributed (i.i.d.) tap coefficients, it is shown that the loss factor of the energy detection relative to optimal sensing is no larger than 1/2 in large delay spread case (i.e., strong correlation); under the same signal power condition the required number of samples for energy detection neglecting the signal correlation is no more than twice of that required for optimal sensing exploiting the signal correlation fully.
a variable step size and variable tap length lms algorithm for impulse responses with exponential power profile. step size and tap length play critical roles in balancing the complexity and steady-state performance of an adaptive filter. for an impulse response with an exponential power decay profile, which models a wide range of practical systems, such as an acoustic echo path, this paper proposes a new variable step-size and tap-length least mean square (lms) algorithm. in each iteration, the optimal step-size and tap-length are derived by minimizing the mean square deviation (msd) between the true and the estimated filter coefficients. the proposed algorithm performs better in terms of both convergence rate and steady-state performance than the existing ones. effectiveness of the proposed algorithm is demonstrated through computer simulations.
multichannel spectral pattern separation - an eeg processing application -. a problem of information separation in multichannel recordings is important in engineering applications such as brain computer/machine interfaces (bci/bmi). whereas this problem is not entirely new, engineering approaches connecting the mental states of humans and the observed electroencephalography (eeg) recordings are still in their infancy, mostly due to problems with electrophysiological denoising. the electrophysiological signals captured in form of the eeg carry brain activity in form of the neurophysiological components which are usually embedded in much higher power electrical muscle activity components (electromyography - emg; electrooculography - eog; etc.). in this paper we present an approach to remove muscular interference caused by eye-movements from eeg recorded during auditory experiments in an eight channel recording setting. this is achieved by analyzing the correlation of the oscillatory modes within a multichannel signal in the hilbert domain. simulations in a real world auditory bci setting support the analysis.
robust adaptive algorithm for active noise control of impulsive noise. the paper concerns active control of impulsive noise. the most famous filtered-x least mean square (fxlms) algorithm for active noise control (anc) systems is based on the minimization of variance of error signal. the impulsive noise can be modeled using non-gaussian stable process for which second order moments do not exist. the fxlms algorithm, therefore, becomes unstable for the impulsive noise. among the existing algorithms for anc of impulsive noise, one is based on the minimizing least mean p-power (lmp) of the error signal, resulting in fxlmp algorithm. the other is based on modifying; on the basis of statistical properties; the reference signal in the update equation of the fxlms algorithm. in this paper, the proposed algorithm is a modification and combination of these two approaches. extensive simulations are carried out, which demonstrate the effectiveness of the proposed algorithm. it achieves the best performance among the existing algorithms, and at the same computational complexity as that of fxlmp algorithm.
towards automatic argument diagramming of multiparity meetings. this paper focuses on a lesser studied multiparty meetings processing task of argument diagramming. argument diagramming aims at tagging the utterances and their relationships to represent the flow and structure of reasoning in conversations, especially in discussions and arguments. in this work, we tackle the problem of automatically assigning node types to user utterances using several lexical and prosodic features. we performed experiments using the ami meeting corpus annotated according to the the twente argumentation schema. our results indicate that while lexical and prosodic features both provide orthogonal information for this task, using a cascaded approach, eliminating backchannel utterances improves the performance. with this final approach, when all features are used, we achieve about 9% relatively better error rates than a simpler classifier based on only lexical features.
performance issues in recursive least-squares adaptive gsc for speech enhancement. one fundamental non-stationary scenario involves a time-varying system in which the cross-correlation between the input signal and the desired response is time-varying. this case occurs in speech enhancement applications, where the optimal solution is time-varying due to the speech signal non-stationarity. adaptive filtering performance analysis of time-varying systems is crucial to further understand the tracking behavior and to ‘optimally’ design the update schemes. in this work, we investigate the tracking performance of the adaptive gsc applied for speech denoising. first, we interpret the noise cancellation in terms of non-stationary system identification. then, we formulate the rls adaptation as a filtering operation on the (time-varying) optimal filter and the instantaneous gradient noise (induced by the measurement noise). under some structural assumptions, we derive an expression for the excess mean squared error (emse). monte-carlo simulations show that the proposed expression allows for a good prediction of the emse, and outperforms the state-of-the-art approximations.
a robust nlms algorithm with a novel noise modeling based on stationary/nonstationary noise decomposition. this paper proposes a robust nlms algorithm with a novel noise modeling based on stationary/nonstationary noise decomposition. the ambient noise including the near-end signal is modeled as a weighted sum of the stationary and the nonstationary components. these components are independently estimated with an appropriate time constant for better accuracy. the estimates are weighted by the stationary/ nonstationary likelihood before summation. the integrated noise estimate controls the coefficient adaptation stepsize such that it is an upward convex function of the reference input with a noise offset for robustness. evaluations in a fullband and a subband echo cancellation scenarios show that erle has been improved by as much as 40 db over the algorithm with a conventional noise model in both single- and double-talk sections with no double-talk detection.
digital camera identification based on curvelet transform. in this paper, a new method is proposed for digital camera identification from its color images using image sensor noise. currently the proposed camera identification methods use wavelet-based denoising filter to extract the sensor noise feature. however, the wavelet methods may smooth the edged while denoising and this will lead to low accuracy for those images including highly textured regions. in order to overcome some inherent limitations of wavelet transform, we use curvelet-based denoising filter to obtain the camera fingerprint. experimental results show that this method provides higher accuracy than other methods on the condition of using a few color images to compute reference pattern, especially for those color images including highly textured regions.
logarithmic quantization index modulation: a perceptually better way to embed data within a cover signal. in this paper, a new method for logarithmic quantization index modulation (qim) is proposed. in this regard a logarithmic function is first applied to the host signal. then the transformed signal is quantized using uniform quantization as conventional qim to embed watermark data within. finally using inverse transform the watermarked signal is obtained. the watermark extraction is performed using minimum distance decoder. the optimum parameter for data embedding with minimum quantization distortion is derived. also the probability of error is analytically calculated and verified by simulation. furthermore data hiding using secret key is proposed and the probability of error is obtained. simulation results show that the proposed method outperforms the conventional qim in terms of robustness when the perceptual quality of watermarked image for both methods are similar. moreover, simulation shows that the proposed scheme has outstanding robustness in comparison with a recent quantization based data hiding method.
a novel pattern identification scheme using distributed video coding concepts. pattern-based video coding focusing on moving region in a macroblock has already established its superiority over recent h.264 video coding standard at very low bit rate. obviously, a large number of pattern templates approximate the moving regions better however, after a certain limit no coding gain is observed due to the increase number of pattern identification bits. recently, distributed video coding schemes used syndrome coding to predict the original information in decoder using side information. in this paper a novel pattern identification scheme is proposed which predicts the pattern from the syndrome codes and side information in decoder so that actual pattern identification number is not needed in the bitstream. the experimental results confirm that this new scheme successfully improves the rate-distortion performance compared to the existing pattern-based video coding as well as h.264 standard. this new scheme will also open another window of syndrome coding application.
why the stochastic mv-pure estimator excels in highly noisy situations? the stochastic mv-pure estimator has recently emerged as the robust solution for frequently occuring in practice problem of linear estimation in ill-conditioned and imperfectly known linear stochastic model. in this paper we provide theoretical results showing that the stochastic mv-pure estimator can be used to the greatest effect in highly noisy settings. in such settings, we discuss the relation between the stochastic mv-pure estimator and the well-known reduced rankwiener filter. we verify the theoretical results presented by a means of numerical simulations.
a near optimum detection in alpha-stable impulsive noise. alpha stable distribution has gained much attention due to its generality to represent heavy-tailed and impulsive interference. in such non-gaussian interference, the detection key is to evaluate the zero-memory nonlinearity (zmnl) function of locally optimal (lo) detector. unfortunately, there is no closed form expression for the probability density function (pdf) of alpha-stable distributions. hereby, sub-optimum zmnl function is adopted as an unavoidable approximation, such as classical cauchy and gaussian-tailed zmnl (gzmnl). in this paper, an algebraic-tailed zmnl (azmnl) with a concise form is proposed. based on such zmnl, derived detector has near optimal performance in various impulsive noise environments. furthermore, using bi-parameter cgm (bcgm), a concise approximate expression for pdf of symmetric α-stable (sαs) distribution, the test threshold can be evaluated according with preset false alarm ratio easily.
h.264/svc scene motion analysis. we present a simple and lightweight approach to scene analysis in the h.264/svc domain. the method is entirely based on the motion vectors found in the compressed stream. motion segmentation and object detection is performed after the estimation of the camera motion. important object properties are calculated, which are used for object matching and trajectory estimation. the relative distance to the camera is estimated, resulting in a pseudo 3-d representation of the object trajectories.
split convex minimization algorithm for signal recovery. a broad range of signal recovery problems can be abstracted into the problem of minimizing the sum of several convex functions in a hilbert space. we propose a proximal decomposition algorithm which, under mild conditions, provides a solution to such a problem. a significant improvement over the methods currently in use in the area of signal recovery is that it is not limited to two nondifferentiable functions. an application to image restoration is demonstrated.
fast lcd motion deblurring by decimation and optimization. the lcd deblurring problem is considered as a simple bounded quadratic programming problem and is solved using conjugate gradient with early stopping criteria to avoid excessive search. a decimation and interlace interpolation method is introduced to reduce the computing time. solutions are competitive to those the generated by conventional lucy richardson algorithm, but using much shorter amount of time. the method can be extended to higher decimation factors. visual subjective tests are conducted to justify our proposed method.
fast mean square convergence of consensus algorithms in wsns with random topologies. the average consensus in wireless sensor networks is achieved under assumptions of symmetric or balanced topology at every time instant. however, communication and/or node failures, as well as node mobility or changes in the environment make the topology vary in time, and instantaneous symmetry of the links is not guaranteed unless an acknowledgment protocol or an equivalent approach is implemented. in this paper, we evaluate the convergence in the mean square sense of a well-known consensus algorithm assuming a random topology and asymmetric communication links. a closed form expression for the mean square error of the state is derived as well as the optimum choice of parameters to guarantee fastest convergence of the mean square error.
a study on multilingual acoustic modeling for large vocabulary asr. we study key issues related to multilingual acoustic modeling for automatic speech recognition (asr) through a series of large-scale asr experiments. our study explores shared structures embedded in a large collection of speech data spanning over a number of spoken languages in order to establish a common set of universal phone models that can be used for large vocabulary asr of all the languages seen or unseen during training. language-universal and language-adaptive models are compared with language-specific models, and the comparison results show that in many cases it is possible to build general-purpose language-universal and language-adaptive acoustic models that outperform language-specific ones if the set of shared units, the structure of shared states, and the shared acoustic-phonetic properties among different languages can be properly utilized. specifically, our results demonstrate that when the context coverage is poor in language-specific training, we can use one tenth of the adaptation data to achieve equivalent performance in cross-lingual speech recognition.
mutual information based channel selection for speaker diarization of meetings data. in the meeting case scenario, audio is often recorded using multiple distance microphones (mdm) in a non-intrusive manner. typically a beamforming is performed in order to obtain a single enhanced signal out of the multiple channels. this paper investigates the use of mutual information for selecting the channel subset that produces the lowest error in a diarization system. conventional systems perform channel selection on the basis of signal properties such as snr, cross correlation. in this paper, we propose the use of a mutual information measure that is directly related to the objective function of the diarization system. the proposed algorithms are evaluated on the nist rt 06 eval dataset. channel selection improves the speaker error by 1.1% absolute (6.5% relative) w.r.t. the use of all channels.
a game-theoretic framework for multi-user multimedia rate allocation. how to efficiently and fairly allocate data rate among different users is a key problem in the field of multiuser multimedia communication. however, most of the existing optimization-based methods, such as minimizing the weighted sum of the distortions or maximizing the weighted sum of the psnrs, have their weights heuristically determined. moreover, those approaches mainly focus on the efficiency issue while ignoring the fairness issue. in this paper, we address this problem by proposing a game-theoretic framework, in which the utility/payoff function of each user/player is jointly determined by the characteristic of the transmitted video sequence and the allocated bitrate. we show that with the proportional fairness criterion, the game has a unique nash equilibrium, according to which the controller can efficiently and fairly allocate the available network bandwidth to the users. finally, we show several experimental results on real video data to verify the proposed method.
combined image plus depth seam carving for multiview 3d images. multiview 3d displays have to multiplex a set of views on a single lcd panel. due to this, each view has to be downsampled by a considerable amount leading to loss of details. in this paper, we extend the seam carving technique for adaptive resizing of images. it is proposed that the depth information be used along with the image pixel intensity values for resizing. this results in better resized multiview images. it is clear from the results presented that the object structure is maintained when the proposed method is used as compared to vanilla seam carving.
conversation detection in ambient telephony. in some speech communication applications such as distributed hands-free telephony it is important that the system can detect the conversational state of a call. this cannot be performed by speech activity only because the captured signal may also contain conversation between two local people, or additional speech noise sources such as speech sounds from a radio or television. in this paper we compare known algorithms and introduce a new algorithm for the real-time detection of active conversation between an incoming caller and a local user. the method is based on the mutual information in speech activity, detection of back-channel speech activity, and statistics of overlapping speech. the proposed method gives over 90% accuracy within one minute observation period which is a clear improvement over the performance of earlier techniques.
distributed parameter estimation with selective cooperation. this paper proposes selective update and cooperation strategies for parameter estimation in distributed adaptive sensor networks. a set-membership filtering approach is employed that results in reduced complexity for updating parameter estimates at each network node, a significant reduction in information exchange between cooperating nodes, and an optimal strategy to obtain consensus estimates. the proposed strategies and the estimation algorithm offer a new way to explore cooperation in adaptive distributed sensor networks.
speech emotion recognition via a max-margin framework incorporating a loss function based on the watson and tellegen's emotion model. this paper considers a method for speech emotion recognition by a max-margin framework incorporating a loss function based on a well-known model called thewatson and tellegen's emotion model. each emotion is modeled by a single-state hidden markov model (hmm) that is trained by maximizing the minimum separation margin between emotions, and the margin is scaled by a loss function. the framework is optimized by the semi-definite programming. experiments were performed to evaluate the framework using the berlin database of emotional speech. the framework performed better than other conventional training criteria for hmm such as maximum likelihood estimation and maximum mutual information estimation.
a low-complexity noise estimation algorithm based on smoothing of noise power estimation and estimation bias correction. this paper presents a low-complexity algorithm for tracking the noise spectral variance of speech contaminated by non-stationary noise sources. the proposed algorithm is based upon a recursive refinement process in which each step of the algorithm expectation of the instantaneous noise power is calculated based on information from the incoming signal and the current estimated distribution parameters, and estimation of the distribution parameter is refined accordingly to incorporate the expectation results. a bias estimation correction method is also introduced in the algorithm to avoid estimation errors that may occur when there is a significant mismatch between the statistics of the input signal and the current estimated distribution parameters. the proposed algorithm is compared to the minimum statistics method and it is found that the proposed algorithm achieves similar or better performances for various noise conditions and snr settings. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
voronoi cell shaping for feature selection with discrete hmms. in this paper, we introduce a novel vector quantization (vq) scheme for distributing the quantization error equally among the quantized dimensions. afterwards, the proposed vq scheme is used to perform feature selection in on-line handwritten whiteboard note recognition based on discrete hidden-markov-models (hmms). in an experimental section we show that the novel vq scheme derives feature sets which contain less than 50% features, enabling recognition with better performance at less computational costs. finally, the derived feature set is compared to the quantized features selected within a continuous hmm-based system: the features selected after quantization with the proposed vq scheme are proved to perform significantly better than those in the continuous system.
a regularized kernel-based approach to unsupervised audio segmentation. we introduce a regularized kernel-based rule for unsupervised change detection based on a simpler version of the recently proposed kernel fisher discriminant ratio. compared to other kernel-based change detectors found in the literature, the proposed test statistic is easier to compute and has a known asymptotic distribution which can effectively be used to set the false alarm rate a priori. this technique is applied for segmenting tracks from tv shows, both for segmentation into semantically homogeneous sections (applause, movie, music, etc.) and for speaker diarization within the speech sections. on these tasks, the proposed approach outperforms other kernel-based tests and is competitive with a standard hmm-based supervised alternative.
the effect of formant trajectories and phoneme durations on vowel intelligibility. we examined how much listeners can benefit from listening to “clear” (clr) speech compared to “conversational” (cnv) speech, both spoken at different speaking rates. vowel intelligibilities of four front vowels (/i:/, /i/, /e/, and /ei/) in background noise were measured with four speaking styles (cnv/slow, cnv, clr, and clr/fast). results showed only tense vowels of clr speech had a significant difference between cnv and clr speaking styles, after energy and f0 contour were normalized. we synthesized hybrid (hyb) speech whose formant features were equal to those of clr speech, while all other features were taken from cnv speech. primary conclusions from this study are (1) naturally-spoken fast clr speech was not as intelligible as clr speech, (2) enhancing formant frequencies to resemble those of clr speech was effective at improving vowel intelligibility, and (3) spectral tilt and formant bandwidths were not contributing factors to the clr speech benefit.
motion-based object segmentation using local background sprites. it is well known that video material with a static background allows easier segmentation than that with a moving background. one approach to segmentation of sequences with a moving background is to use preprocessing to create a static background, after which conventional background subtraction techniques can be used for segmenting foreground objects. it has been recently shown that global motion estimation and/or background sprite generation techniques are reliable. we propose a new background modeling technique for object segmentation using local background sprite generation. experimental results show the excellent performance of this new method compared to recent algorithms proposed.
network gossip algorithms. unlike the telephone network or the internet, many of the next generation networks are not engineered for the purpose of providing efficient communication between various networked entities. examples abound: sensor networks, peer-to-peer networks, mobile networks of vehicles and social networks. indeed, these emerging networks do require algorithms for communication, computation, or merely spreading information. for example, estimation algorithms in sensor networks, broadcasting news through a peer-to-peer network, or viral advertising in a social network. these networks lack infrastructure; they exhibit unpredictable dynamics and they face stringent resource constraints. therefore, algorithms operating within them need to be extremely simple, distributed, robust against network dynamics, and efficient in resource utilization. gossip algorithms, as the name suggests, are built upon a gossip or rumor style unreliable, asynchronous information exchange protocol. due to their immense simplicity and wide applicability, this class of algorithms has emerged as a canonical architectural solution for the next generation networks. this has led to exciting recent progress to understand the applicability as well as limitations of the gossip algorithms. in this survey, i will discuss some of these recent results on gossip network algorithms. the algorithmic results described here in a natural way bring together tools and techniques from markov chain theory, optimization, percolation, random graphs, spectral graph theory, and coding.
comparison of convex combination and affine combination of adaptive filters. in the area of combination of adaptive filters, two main approaches, namely convex and affine combinations have been introduced. in this article, the relation between these two approaches is investigated. first, the problem of obtaining optimal convex combination coefficients is formulated as the projection of the optimal affine combination weights to the unit simplex in a weighted inner product space. based on this formulation the closed form expressions for optimal combination weights and target mse levels are obtained for two and three branch cases.
on robustness of coupled adaptive filters. we provide a time domain analysis of the robustness and stability performance for coupled adaptive algorithms of gradient type. the considered coupling may occur inherently as well as by desire of the designer. the presented analyses focus on system identification. examples are presented to investigate convergence and steady-state behaviour by simulations which are compared to theory. in particular, the presented approach allows for a deeper understanding of cascaded adaptive filters in terms of robustness and l2-stability.
strategies for bit allocation reuse in audio transcoding. we study the reuse of the bit allocation information in audio transcoding by exploiting the similarity in subband audio coding schemes. we show that important information can be deduced to reduce the encoder complexity even if the two coders employ different psychoacoustic model. we give a case study on mpeg aac/dolby ac-3 transcoding. the proposed algorithms can be extended to other audio transcoding schemes.
people location and orientation tracking in multiple views. this paper presents a multi-view approach to the tracking of people location and orientation. to achieve efficient and accurate likelihood evaluation, a novel likelihood computation method is proposed. mixtures of gaussian (mog) are used to represent the color models of subjects. the scaled unscented transformation is used to project the mog color models onto the image plane to predict the color distribution for a motion sample. the efficacy of the proposed approach is demonstrated by experiment results obtained using real videos.
classification of movement-related single-trial meg data using adaptive spatial filter. in this paper, a method for extracting and classifying movement-related brain signals is proposed. a single-trial meg observation is first processed with a pre-whitening filter so that strong stationary interference is eliminated. next, a brain signal effective for classification is extracted using an adaptive spatial filter. the extracted signal is then classified with a support vector machine. from the experimental results, it is shown that the classification rate of 62.6 % is obtained for the brain signals related to the three types of hand movements (“scissors-paper-rock”).
detecting real life anger. acoustic anger detection in voice portals can help to enhance human computer interaction. a comprehensive voice portal data collection has been carried out and gives new insight on the nature of real life data. manual labeling revealed a high percentage of non-classifiable data. experiments with a statistical classifier indicate that, in contrast to pitch and energy related features, duration measures do not play an important role for this data while cepstral information does. also in a direct comparison between gaussian mixture models and support vector machines the latter gave better results.
a reduced-reference video structural similarity metric based on no-reference estimation of channel-induced distortion. the reduced-reference (rr) approximation of a full-reference (fr) video quality assessment method is a convenient way to build evaluation metrics which are both intrinsically well correlated with human judgments and feasible to implement in a network scenario, without the need to explore the perceptual significance of new video features through mean opinion score tests. in this paper, we propose a rr approximation of the video structural similarity index (vssim), a fr metric which is known to be well descriptive of the video quality perceived by users. we focus on the visual degradation produced by channel transmission errors: first, at the encoder, a small set of salient structural video features is assembled and transmitted through the rr channel to the end-user; then, at the decoder the feature vector is combined with a fine-granularity, no-reference estimate of the channel-induced distortion to produce the vssim approximation. by uniformly quantizing the feature vector and compressing it using a context-adaptive, variable length encoder, we show that good correlation coefficients with ground-truth vssim (ρ = 0.85) may be achieved spending, respectively, less than 12 and 27 kbps for a video sequence with cif or sd resolution.
perturbation and pitch normalization as enhancements to speaker recognition. this study proposes an approach to improving speaker recognition through the process of minute vocal tract length perturbation of training files, coupled with pitch normalization for both train and test data. the notion of perturbation as a method for improving the robustness of training data for supervised classification is taken from the field of optical character recognition, where distorting characters within a certain range has shown strong improvements across disparate conditions. this paper demonstrates that acoustic perturbation, in this case analysis, distortion, and resynthesis of vocal tract length for a given speaker, significantly improves speaker recognition when the resulting files are used to augment or replace the training data. a pitch length normalization technique is also discussed, which is combined with perturbation to improve open-set speaker recognition from an eer of 20% to 6.7%.
hierarchical clustering of neural data using linked-mixtures of hidden markov models for brain machine interfaces. in this paper, we build upon previous brain machine interface (bmi) signal processing models that require a-priori knowledge about the patient's arm kinematics. specifically, we propose an unsupervised hierarchical clustering model that attempts to discover both the interdependencies between neural channels and the self-organized clusters represented in the spatial-temporal neural data. given that bmis must work with disabled patients who lack arm kinematic information, the clustering work describe within this paper is very relevant for future bmis.
using the pearson correlation coefficient to develop an optimally weighted cross relation based blind simo identification algorithm. blind simo identification is challenging when additive noise is strong and for ill-conditioned/acoustic simo systems. a weighted cross relation (cr) algorithm presumably can be robust to noise but there lacks a practical way to define the weights. in this paper, the pearson correlation coefficient (pcc) is used to develop an optimally weighted cr algorithm, which is validated by simulations.
learning a music similarity measure on automatic annotations with application to playlist generation. this paper presents an approach to learn a better music similarity measure and presents an application to music playlist generation. different from previous work, in our approach, automatically detected music attributes are used to represent each song. a set of kernels is employed in similarity measure, with each kernel measuring on a subset of music attributes and having a different importance weight. in automatic music playlist generation, a ranking method is presented, which considers multiple seed songs and possible outlier seed. experiments show the effectiveness of the proposed approach, and the quality of the playlist generated based on automatic annotations is comparable to that based on manual annotations.
a dsk based simplified speech processing module for cochlear implant research. a simple yet flexible research module for laboratory experiments in evaluating performance of different speech processing strategies of cochlear implant is developed. it enables algorithm development and evaluation through a series of three sub-modules. software evaluation module provides a graphical environment to the researchers to develop new strategies as well as experiment with parametric variation of these strategies. evaluation is done by means of waveform analyzer and audible reconstruction of the synthesized sound. hardware evaluation module evaluates real-time operational performance of the algorithms in dsp environment. it highlights the practical bottlenecks of any algorithm when transferred from software to hardware domain. finally, real-time patient evaluation module allows performance evaluation of the developed strategy on actual cochlear implant patients. simple and easy to use guis enable clinicians and researchers to experiment with speech processing strategies with great ease and flexibility without requiring advanced programming skills.
averaged acoustic emission events for accurate damage localization. localizing micro cracks in critical components is crucial in the field of continuous structural health monitoring. in this paper, we utilize several signal processing and machine learning techniques such as hierarchical clustering and support vector machines (svm) to process multisensor acoustic emission (ae) data generated by the inception and propagation of cracks. we present preliminary laboratory results that explore the pairwise event correlation of ae waveforms generated in the process of controlled crack propagation, and use these characteristics for clustering ae. by averaging the ae events within each cluster obtained from hierarchical clustering, we compute super-acoustics with higher signal to noise ratio (snr) and use them in the second step of our analysis for calculating the time of arrival information (toa) for crack localization. we utilize a svm classifier to recognize the so called p-waves in the presence of noise by using features extracted from the frequency domain for accurate earliest arrival detection. preliminary results show that our method has the potential to be a component of a structural health monitoring system based on acoustic emissions for instance for bridges.
joint mimo radar waveform and receiving filter optimization. the concept of mimo (multiple-input multiple-output) radar allows each transmitting antenna element to transmit an arbitrary waveform. this provides extra degrees of freedom compared to the traditional transmit beamforming approach. it has been shown in the recent literature that mimo radar systems have many advantages. in this paper, we consider the joint optimization of waveforms and receiving filters in the mimo radar when the prior information of target and clutter are available. a novel iterative algorithm is proposed to optimize the waveforms and receiving filters such that the detection performance can be maximized. the proposed algorithm guarantees that the sinr performance improves in each iteration step. the numerical results show that the proposed methods have better sinr performances than existing design methods.
timing and frequency synchronization for ofdm based cooperative systems. in this paper, we investigate the timing and carrier frequency offset (cfo) synchronization problem in decode and forward cooperative systems operating over frequency selective channels. a training sequence which consists of one ofdm block having a tile structure in the frequency domain is proposed to perform synchronization. timing offsets are estimated using correlation-type algorithms. and since some subcarriers are nulled in the proposed tile structure, cfos are readily estimated using subspace-based methods. by judiciously designing the size of the tile, these algorithms are shown to have better performance, in terms of synchronization errors and bit error rate, than the computationally demanding sage algorithm.
cross-layer optimization of wireless fading ad-hoc networks. this paper develops near-optimal designs of wireless networks in the presence of fading. the novel approach optimizes jointly application level rates, routes, link capacities, power consumption and physical layer parameters. the physical layer is interference limited with terminals distributing their power budget among frequency tones, neighboring nodes and fading states. the present contribution builds on recent results establishing the optimality of layered architectures and develops physical layer resource allocation algorithms that are seamlessly integrated into layered architectures without loss of optimality.
affinely constrained online learning and its application to beamforming. this paper presents a novel method for incorporating a-priori affine constraints in online kernel-based learning tasks. the proposed technique elaborates the generic tool of projections to form a sequence of estimates in reproducing kernel hilbert spaces (rkhs). the method guarantees that the whole sequence of estimates lies in the given affine constraint set. to validate the algorithm, a beamforming task is considered. the numerical results show that the proposed frame provides with solutions in cases where the classical linear approach collapses, and forms proper beam-patterns as opposed to a recent unconstrained kernel-based regression method.
optimal and robust waveform design for mimo radars. waveform design for target identification and classification in mimo radar systems has been studied in several recent works. while the previous works considered signal independent noise, here we extend the results to the case where signal-dependent noise, clutter, is also present and then we find the optimum waveform for several estimators differing in the assumptions on the given statistics. computing the optimal waveforms for mmse estimator leads to the semi-definite programming (sdp) problem. finding the optimal transmit signals for csls estimator results in a minimax eigenvalue problem. finally it is shown that equal power waveforms are the best transmit signals for the sls estimator.
multi-user mimo and adaptive frequency reuse for next-generation mobile broadband networks. in order to meet the constantly increasing demand for ubiquitous, mobile access to the internet, next-generation mobile broadband communications systems based on ofdma, such as ieee 802.16m, require a significant performance increase over previous generation systems, such as ieee 802.16e-2005, particularly in cell-edge and average spectral efficiency [2]. in this paper, we address the downlink adaptive frequency reuse (afr) and multi-user mimo (mu-mimo) techniques which are considered to be the most promising candidates for meeting the requirements on cell-edge and average spectral efficiency of next-generation mobile broadband systems.
state-space analysis on time-varying correlations in parallel spike sequences. a state-space method for simultaneously estimating time-dependent rate and higher-order correlation underlying parallel spike sequences is proposed. discretized parallel spike sequences are modeled by a conditionally independent multivariate bernoulli process using a log-linear link function, which contains a state of higher-order interaction factors. a nonlinear recursive filtering formula is derived from a log-quadratic approximation to the posterior distribution of the state. together with a fixed-interval smoothing algorithm, time-dependent log-linear parameters are estimated. the smoothed estimates are optimized via em-algorithm such that their prior covariance matrix maximizes the expected complete data log-likelihood. in addition, we perform model selection on the hierarchical log-linear state-space models to avoid over-fitting. application of the method to simultaneously recorded neuronal spike sequences is expected to contribute to uncover dynamic cooperative activities of neurons in relation to behavior.
plane-wave decomposition of a sound scene using a cylindrical microphone array. the analysis for microphone arrays formed by mounting microphones on a sound-hard spherical or cylindrical baffle is typically performed using a decomposition of the sound field in terms of orthogonal basis functions. an alternative representation in terms of plane waves and a method for obtaining the coefficients of such a representation directly from measurements was proposed recently for the case of a spherical array. it was shown that representing the field as a collection of plane waves arriving from various directions simplifies both source localization and beamforming. in this paper, these results are extended to the case of the cylindrical array. similarly to the spherical array case, localization and beamforming based on plane-wave decomposition perform as well as the traditional orthogonal function based methods while being numerically more stable. both simulated and experimental results are presented.
emg signal denoising via bayesian wavelet shrinkage based on garch modeling. in this paper, we introduce a novel noise suppression method for electromyography (emg) signals, based on statistical modeling of wavelet coefficients. first, we demonstrate that generalized autoregressive conditional heteroscedasticity (garch) effect exists in wavelet coefficients of emg signals. then, we use garch model for these coefficients. in consequence, we introduce a maximum a-posteriori (map) estimator, based on garch modeling, for estimating the clean wavelet coefficients. to evaluate the performance of garch based method in noise suppression, we compare our proposed method with other wavelet based denoising methods and we verify the performance improvement in utilizing the new strategy.
spatial redundancy in higher order ambisonics and its use for lowdelay lossless compression. when higher order ambisonics (hoa) is used to represent a sound field, the channels might contain a lot of redundancy in some cases. this redundancy can be exploited in order to provide more efficient network transmission and storage. in this work the amount of inter-channel redundancy for higher order ambisonics is investigated. furthermore, lossless compression techniques that build on this redundancy are studied, with a focus on low-delay algorithms for real-time, or two-way, applications. the presented encoding scheme results in a delay of 256 samples, but with a rather high computational complexity both for encoding and decoding. the system also preserves the desired features of the hoa format, such as the scalability and the ability to reproduce over arbitrary loudspeaker layouts.
high resolution audio synchronization using chroma onset features. the general goal of music synchronization is to automatically align the multiple information sources such as audio recordings, midi files, or digitized sheet music related to a given musical work. in computing such alignments, one typically has to face a delicate tradeoff between robustness and accuracy. in this paper, we introduce novel audio features that combine the high temporal accuracy of onset features with the robustness of chroma features. we show how previous synchronization methods can be extended to make use of these new features. we report on experiments based on polyphonic western music demonstrating the improvements of our proposed synchronization framework.
the sri nist 2008 speaker recognition evaluation system. the sri speaker recognition system for the 2008 nist speaker recognition evaluation (sre) incorporates a variety of models and features, both cepstral and stylistic. we highlight the improvements made to specific subsystems and analyze the performance of various subsystem combinations in different data conditions. we show the importance of language and nativeness conditioning, as well as the role of asr for speaker verification.
optimal parameter estimation for model-based quantization. we address optimal model estimation for model-based vector quantization for both the constrained resolution (cr) and constrained entropy (ce) cases. to this purpose we derive under high-rate (hr) theory assumptions the rate-distortion (rd) relations for these two quantization scenarios assuming a gaussian model. based on the rd relations we show that the maximum likelihood (ml) criterion leads to optimal performance for ce quantization, but not for cr quantization. we introduce a new model estimation criterion for cr quantization that is optimal (under hr theory assumptions) in terms of the rd relation. our experiments confirm that the proposed criterion for model identification outperforms the ml criterion for a range of conditions.
blind ranges, frequencies and doas estimation for near field sources. two novel algorithms are proposed for ranges, frequencies and direction-of-arrivals (doas) estimation of the narrow-band near field sources. by exploiting the time-domain and space-domain correlations of impinging signals jointly, we can identify 2p independent sources and estimate 3 groups of parameters with a uniformly linear array (ula) of 2p + 1 elements, being double of the conventional methods. in addition, the peak search and pairing operations, needed in most algorithms for near field sources, can be omitted completely in our methods. simulation results show that our two esprit-based methods provide the improved performance over conventional ones based on the second-order statistics.
sparse decomposition of mixed audio signals by basis pursuit with autoregressive models. we develop a framework to detect when certain sounds are present in a mixed audio signal. we focus on the regime where out of a large number of possible sounds, a small but unknown number are combined and overlapped to yield the observed signal. to infer which sounds are present, we attempt to decompose the observed signal as a linear combination of a small number of sources. to encourage sparse solutions with this property, we balance the modeling errors from individual sources against an ℓ1-norm penalty of the type used in basis pursuit and regularized linear regression with grouped variables. our approach can be viewed as a novel generalization of basis pursuit in two ways: first, with a dictionary of fixed size, we attempt to model acoustic waveforms of potentially variable duration; second, for dictionary entries, we do not store basis vectors representing static templates, but the coefficients of autoregressive models that characterize the acoustic variability of individual sources. we derive the required optimizations in this framework and present experimental results on combinations of periodic and aperiodic sources.
graphical models: statistical inference vs. determination. using discrete hidden-markov-models (hmms) for recognition requires the quantization of the continuous feature vectors. in handwritten whiteboard note recognition it turns out that the pen-pressure information, which is important for recognition, is not adequately quantized and looses significance. in this paper, the implicit modeling of the pressure information presented in previous work which uses the deterministic knowledge on the actual pressure is generalized using a graphical model (gm) representation based on statistical inference. the results of two state-of-the-art toolboxes implementing hmms and gms are compared. it can be seen that the statistical inference approach based on gms is inferior to the implicit modeling of the pressure information. it is shown that a direct implementation of hmms outperforms the mathematic identical gm representation.
acoustic compensation methods for body transmitted speech conversion. statistical voice conversion is very effective for enhancing body transmitted speech recorded with non-audible murmur (nam) microphone. in this method, a probabilistic model to convert body transmitted speech into natural speech is trained previously. because acoustic characteristics of body transmitted speech is sensitive to recording conditions such as a location of nam microphone, significant degradation of the conversion performance is often caused in practical situations by acoustic mismatches between training and conversion processes. to alleviate this problem, we propose unsupervised acoustic compensation methods for body transmitted voice conversion. experimental results demonstrate that the proposed methods significantly reduce the quality degradation of converted speech caused by the acoustic mismatches.
on a tradeoff between dereverberation and noise reduction using the mvdr beamformer. the minimum variance distortionless response (mvdr) beamformer can be used for both speech dereverberation and noise reduction. in this paper we analyse the tradeoff between the amount of speech dereverberation and noise reduction achieved by the mvdr beamformer. we show that the amount of noise reduction that is sacrificed when desiring both speech dereverberation and noise reduction depends on the direct-to-reverberation ratio of the acoustic transfer function between the desired source and a reference microphone. the performance evaluation supports the theoretical analysis and demonstrates the tradeoff between speech dereverberation and noise reduction.
optimized opportunistic multicast scheduling (oms) over heterogeneous cellular networks. optimized opportunistic multicast scheduling (oms) has been studied previously by the authors for homogeneous cellular networks, where the problem of efficiently transmitting a common set of data from a single base station to multiple users that have identical channel statistics was examined. it has been demonstrated that oms can achieve significant performance improvement by exploiting the optimal tradeoff between multiuser diversity and multicast gain. in this work, we extend our studies to heterogeneous networks with users subject to different channel statistics. specifically, we consider a single cell wireless network with users uniformly distributed in a circular region around the base station. since users with low snr are the ones that hinder system throughput, we argue that system performance may be predicted by the behavior of users in the outmost ring of the cell, which are approximately homogeneous. using extreme value theory and results obtained from the homogeneous case, we determine the optimal user selection ratio for a homogeneous ring of users near the edge of the cell and then use it to derive the optimal selection ratio over the entire heterogeneous network. simulations confirm theoretical results and illustrate the effectiveness of the proposed scheme.
hands-on engineering and science: discovering cosmic rays using radar-based techniques and mobile technology. this paper reports on the latest efforts of the mariachi1 program at stony brook university, a unique endeavor that detects and studies ultra-high-energy cosmic rays. this is done by using a novel detection technique based on radar-like technology and traditional scintillator ground detectors. using the phenomena of cosmic rays and meteors as vehicles to motivate research and educational activities, innovative hands-on modules in physics, engineering and cyberinfrastructure based on a learning by doing philosophy are offered to high school teachers and students. participants at all levels are engaged in research projects, seminars, and workshops, where they will learn to use tools needed in mariachi by means of mobile technology.
evolutionary spectrum estimation for uniformly modulated processes with improved boundary performance. the evolutionary spectrum (es) is a time-dependent analogue of the spectrum of a stationary process. existing estimators of the es suffer from bias problems in the boundary region of the time-frequency domain, due to windowing effects. we propose a new estimator of the es of a uniformly modulated process which mitigates these problems. our estimator is based on an extrapolation of the es in time, using an estimate of the time derivative of the es. we apply our estimator to a simulated example of a uniformly modulated process with known es.
target speech extractionwith learned spectral bases. in this paper we present a method for extracting a speech signal of target speaker from noisy convolutive mixtures of target speech and an interference source, when training utterances of the target speaker are available. we incorporate a statistical latent variable model into blind source separation (bss), where we make use of spectral bases learned from the training utterances of the target speaker to identify which source corresponds to the target speaker. combined with any existing bss methods, our post-processing (which is the main contribution) consists of two steps: (1) channel selection where we identify the source corresponding to the target speaker; (2) enhancement where we further suppress the remaining interference. numerical experiments confirm that our method substantially improves the separation quality of existing bss methods and successfully restores the target speaker's speech.
a modified distortion metric for audio coding. current audio coding standards employ the modified discrete cosine transform (mdct) where overlapped frames of audio are windowed and transformed to the frequency domain. encoding parameters are chosen so as to minimize a distortion measure subject to a rate constraint. at the decoder, inverse transformation involves additional windowing and overlap-add of frames. an analysis of the time domain error in the reconstructed frame reveals that distortion metrics based solely on the mdct domain error are in fact unable to capture the effects of windowing and overlap-add at the decoder. the main contribution of this paper is a modified distortion metric that does capture these effects via modified discrete sine transform analysis. when incorporated into an advanced audio coder the proposed distortion metric significantly improves subjective quality of reconstructed audio.
bayesian sparse image reconstruction for mrfm. in this paper, we propose a bayesian model and a monte carlo markov chain (mcmc) algorithm for reconstructing images that consist of only few non-zero pixels. an appropriate distribution that promotes sparsity is proposed as prior distribution for the pixel values. the hyperparameters involved in the modeling are also assigned prior distributions, resulting in a hierarchical model. a gibbs sampler allows us to draw samples distributed according the full posterior of interest. these samples are then used to approximate standard maximum a posteriori (map) estimator. by conducting some simulations, we show that the proposed estimator clearly outperforms previous estimators proposed in the literature.
a hjs filter to track visually interacting targets. visual tracking with explicit occlusion models is computationally hard, in the sense that the complexity explodes as the number of targets increases. recently, the hybrid joint-separable (hjs) model has been proposed that enables tracking the local appearance of a number of bodies through occlusions with a quadratic, no more exponential, upper bound. in this paper we extend that method to account for a larger spectrum of visual interactions, captured by a full-image likelihood enabling true bayesian inference, without compromising scalability. the resulting tracker then proves to be significantly more robust, and able to resolve long term occlusion among five people aligned on a single line-of-sight, observed from a single camera, at a manageable computational cost.
adaptive rhythmic component extractionwith regularization for eeg data analysis. rhythmic component extraction (rce) is a method for extracting a signal oscillating at a certain frequency from multi-channel sensor signals. this method can be effectively used for detecting rhythmic signals such as alpha and beta waves, which are the feature signals in brain computer/machine interfaces (bci/bmi). we are addressing a problem in developing an on-line adaptive algorithm for rce. since a rhythmic signal in the brain slowly varies, the signals extracted in adjacent frames should not largely different. we propose introducing a regularization term that evaluates the correlation between the signal extracted in the last step and the one to be extracted to achieve this. we show that the maximization of the cost function with the proposed regularization term is reduced to a generalized eigenvalue problem and experimental results from practical eeg data support this analysis.
query by tapping system based on alignment algorithm. query-by-tapping systems are content-based music retrieval systems that allow users to tap or clap in a microphone the rhythmic pattern of the melody requested. in this paper, a new query-by-tapping system is described. this system is based on adaptations of alignment algorithms successfully applied for melodic similarity estimation. a similarity score is computed according to the cost of the elementary operations necessary to transform the query into the musical piece tested. a new method for extracting the rhythmic pattern from audio signals is also presented. this method is based on the analysis of the variations of the kurtosis computed from the audio samples. experiments performed on the mirex 2008 database show that the alignment technique proposed performs better than the participating algorithms. they also confirm the interest of the kurtosis-based analysis method in the case of noisy percussive queries.
wrapping snakes for improved lip segmentation. a key step in the process of lip-reading is determining the shape of the speaker's lips. this has previously been achieved through an energy method known as “snakes”, however this approach has some limitations. this paper presents an adapted approach called wrapping snakes, where the image forces are modified based on the snake's location and orientation. this modification encourages wrapping snakes to continue along features they have already partially found, overcoming one of the problems of traditional snakes. the use of wrapping snakes allows for more accurate and robust lip segmentation, as well as increasing the speed of the segmentation.
joint estimation of short-term and long-term predictors in speech coders. in low bit-rate coders, the near-sample and far-sample redundancies of the speech signal are usually removed by a cascade of a short-term and a long-term linear predictor. these two predictors are usually found in a sequential and therefore suboptimal approach. in this paper we propose an analysis model that jointly finds the two predictors by adding a regularization term in the minimization process to impose sparsity constraints on a high order predictor. the result is a linear predictor that can be easily factorized into the short-term and long-term predictors. this estimation method is then incorporated into an algebraic code excited linear prediction scheme and shows to have a better performance than traditional cascade methods and other joint optimization methods, offering lower distortion and higher perceptual speech quality.
pitch bends and tonguing articulation in clarinet physical modeling synthesis. a physical modeling approach is used to investigate playing effects in woodwind instruments. this builds upon prior work concerning both empirical studies of the acoustics of the clarinet and extensive development of computer simulations of musical instrument systems. specifically, explicit implementations of two performance gestures for the clarinet are given and demonstrated: tonguing and pitch bending. physical modeling for the clarinet is briefly reviewed. following this we show how both tonguing and pitch bending map to changes in the clarinet physical model itself and in the control parameter data. to our knowledge, tonguing in particular is one effect that has not been widely discussed in the literature, at least in the exact form we present. finally, some possible future research directions are indicated.
comparison of mpeg-7 descriptors for long term selection of reference frames. during the last years, the amount of multimedia content has greatly increased. this has multiplied the need of efficient compression of the content but also the ability to search, retrieve, browse, or filter it. generally, video compression and indexing have been investigated separately. however, as the amount of multimedia content grows, it will be very interesting to study representations that, at the same time, provide good compression and indexing functionalities. moreover, even if the indexing metadata is created for functionalities such as search, retrieval, browsing, etc., it can also be employed to increase the efficiency of current video codecs. here, we use it to improve the long term prediction step of the h.264/avc video codec. this paper focuses on the comparison between four different mpeg-7 descriptors when used in the proposed scheme.
inversion of short-time fourier transform magnitude spectrograms with adaptive window lengths. in this paper, we extend the real-time iterative spectrogram inversion method (rtisi) for generating a time-domain audio signal from a magnitude spectrogram such that it can handle changing spectrogram window lengths. for each desired window length, we use a separate buffer structure and synchronize the buffers each time the window length changes. this way, the proposed method helps to improve the time/frequency-resolution trade-off for algorithms that operate on magnitude-only spectra.
diversity analysis of antenna selection over frequency-selective mimo channels. antenna selection is a simple yet efficient technique to obtain diversity advantage from multi-input and multi-output (mimo) communication systems. without specifying system factors such as antenna selection criterion, coding and decoding, equalization, and channel statistics, we evaluate diversity orders of antenna selections over frequency-selective mimo channels. we show that the diversity order of any configuration approximately scales in the numbers of transmit and receive antennas. numerical simulations are provided to validate our analysis.
fast belief propagation process element for high-quality stereo estimation. belief propagation is a popular global optimization technique for many computer vision problems. however, it requires extensive computation due to the iterative message passing operations. in this paper, we present a new process element (pe) for efficient message construction. the efficiency is gained by exploiting the unique characteristics of the generalized potts model (truncated linear mode) of the smoothness term in the markov random field. for stereo estimation with l disparity values, the algorithm successfully reduces the computation from o(l2) to o(l) and retains the high throughput and low latency. compared with the direct message construction pe, our method achieves 87.14% computation saving and a 94.38% pe area reduction.
efficient blind decoding of mimo using sequential monte carlo. in this paper, blind decoding of ostbc based mimo systems using sequential monte-carlo methods is considered. similar receivers developed earlier have suffered from the high computational complexity. by introducing some simplification and approximation techniques, we present a new decoding algorithm that requires much less computation. in addition to that, an efficient interlaced maximum likelihood estimator approach is developed to blindly estimate the statistical parameters of the channel. while a comparative analysis on the computational complexity shows significant computational savings, the simulation results show that the performance of the proposed algorithm is not compromised.
automatic generation of maps of memory accesses for energy-aware memory management. many signal processing systems are synthesized to execute data-dominated applications. their behavior is described in a high-level programming language, where the code is typically organized in sequences of loop nests and the main data structures are multidimensional arrays. since data transfer and storage have a significant impact on both the system performance and the major cost parameters - power consumption and chip area, the designer must spend a significant effort during the system development process on the exploration of the memory subsystem in order to achieve a cost-optimized design. this paper focuses on the reduction of the dynamic energy consumption in the hierarchical memory subsystem of multidimensional signal processing systems, starting from the high-level behavioral specification of the application. the paper presents an algorithm which identifies those parts of arrays from a high-level specification that are intensely accessed (for read and/or write operations), whose storage on-chip yields the highest benefit in terms of dynamic energy consumption. tested on a two-layer memory hierarchy (scratch-pad and off-chip memories), this algorithm led to significant savings of energy in comparison to previous computation models.
on the use of bayesian modeling for predicting noise reduction performance. in speech enhancement applications, a validated metric of noise reduction performance is vital in the relative ranking of noise reduction algorithms and in enhancing the performance of a noise reduction algorithm. subjective scores of enhanced speech remain the yardstick for performance, but objective metrics that emulate subjective evaluations are preferred for cost- and time-effectiveness. in this paper, we analyze the performance of two objective methods for predicting the quality of enhanced speech. the first method employs the coherence-based speech intelligibility index, while the second method uses features derived from the moore - glasberg auditory model. in both cases, the features are mapped to a quality score using the bayesian modeling approach. results show that the combination of the auditory model-based feature set and the bayesian modeling provides the best performance in predicting the quality scores of enhanced speech.
spoken dialog strategy based on understanding graph search. we regarded information retrieval as a graph search problem and proposed several novel dialog strategies that can recover from misrecognition through a spoken dialog that traverses the graph. to recover from misrecognition without seeking confirmation, our system kept multiple understanding hypotheses at each turn and searched for a globally optimal hypothesis in the graph whose nodes express understanding states across user utterances in a whole dialog. as for a dialog strategy, we introduced a new criterion based on efficiency in information retrieval and consistency with understanding hypotheses to select an appropriate system response. using such criterion, the system removes the ambiguity so that users do not feel that a response that conflicts with the actual user intent is unnatural. we developed a spoken dialog system using these techniques and showed dialog examples in which misrecognition was naturally corrected. we also showed that our strategy was efficient in terms of the number of turns.
optimal distributed microphone phase estimation. this paper presents a minimum mean-square error spectral phase estimator for speech enhancement in the distributed multiple microphone scenario. the estimator uses gaussian models for both the speech and noise priors under the assumption of a diffuse incoherent noise field representing ambient noise in a widely dispersed microphone configuration. experiments demonstrate significant benefits of using the optimal multichannel phase estimator as compared to the noisy phase of a reference channel.
challenges and opportunities of obtaining performance from multi-core cpus and many-core gpus. multi-core processors represent a major development in computing technology. for example, intel® core™ 2 quad processors, ibm cell processors, and nvidia geforce 9800 gx2, are widely used. however, most applications struggle to make the best use of the power provided by many-core processors. easy-to-use software tools are hard to find. furthermore, it's not clear what changes need to be made to algorithms to fully utilize many-core cpus or gpus. in this paper, we try to offer a bird's eye view of the opportunities lying ahead in two folds: (1) software tools and (2) workload analysis. with good software tools and insightful workload analysis, software and algorithm developers can not only harness the power of many computing cores, but also innovate new algorithms that best utilize the many computing cores. new algorithms and applications are thus made possible with the computing power not available before.
musical audio semantic segmentation exploiting analysis of prominent spectral energy peaks and multi-feature refinement. in this paper we present a novel hierarchical and scalable three-stage algorithm to effectively perform musical audio semantic segmentation. in the first stage, the energy spectrum of the entire audio track is analyzed to find significant energy textures that may characterize different semantic segments; in the second and third stages, tonal and timbric features are used to refine the segmentation by moving or deleting segment boundaries. experimental results on a set of 58 songs show that our algorithm is able to attain good semantic segmentation just after the first step, with a precision of 64% and a recall of 96%. after second step the precision increases to 79%; the best precision result is obtained after the third step, where a value of 85% is reached. in this step the minimum average recall value of 92% is obtained.
background recovery from video sequences using motion parameters. this paper presents a novel scheme for extracting a still background occluded by a number of foreground objects, moving in different directions and velocities in a video sequence, such that every background pixel is exposed in at least one of the frames. each identified foreground object is decomposed into blocks. the proposed scheme is able to efficiently estimate, for each foreground block, a source frame from which the occluded background pixels can be extracted. the pixels of the identified source frames are used to populate the co-located occluded pixels in the initial frame. the efficacy and the simplicity of the algorithm lie in its capacity to recover the background directly from the estimated source frames instead of performing a foreground-background classification for every frame. the proposed algorithm is robust to variations in lighting and is effective in removing both rigid and deformable foreground objects. simulation results are presented to illustrate the performance of the proposed scheme.
evaluating digital audio authenticity with spectral distances and enf phase change. this paper discusses the use of spectral distances obtained from adaptive filters employed as linear predictors and phase change of the electric network frequency to evaluate digital audio authenticity. an authenticity evaluation may be of paramount importance for audio forensics and may help a criminalistic laboratory when dealing with audio evidence in a court of law. we present in this paper a theoretical background of the proposed scheme and show results with digitally edited speech.
extensions of absolute discounting (kneser-ney method). the problem of estimating the parameters of an n-gram language model is a typical problem of estimating small probabilities. so far, two methods have been proposed and used to handle this problem: 1. the empirical bayes method resulting in the turing-good estimates. theses estimates do not have any constraints and tend to be very noisy. 2. discounting models like absolute (or linear) discounting. the discounting models are heavily constrained and typically have only a single free parameter. both methods can be formulated in a leaving-one-out framework. in this paper, we study methods that lie between these two extremes. we design models with various types of constraints and derive efficient algorithms for estimating the parameters of these models. we propose two novel types of constraints or models: interval constraints and the exact extended kneser-ney model. the proposed methods are implemented and applied to language modelling in order to compare the methods in terms of perplexities. the results show that the new constrained methods outperform other unconstrained methods.
lossless data hiding for electronic ink. this paper presents a novel lossless data hiding technique for electronic inks. the proposed algorithm first computes the analytical ink-curve function for each stroke as a set of smoothly concatenated cubic bezier curves. during embedding, a set of data carrier points on the ink-curve are computed, perturbed and inserted back into the original point array together with some marker points. in extraction, data carrier points are identified and compared with their original positions in order to decode the secret message. through experiments, we demonstrate that significant mount of secret message can be embedded and the ink-curve computed from the marked ink data closely resembles the original ink-curve.
multilinear generalization of common spatial pattern. the common spatial patterns (csp) algorithm has been widely used in eeg classification and brain computer interface (bci). in this paper, we propose a multilinear formulation of the csp, termed as tensorcsp or common tensor discriminant analysis (ctda) for high-order tensor data. as a natural extension of csp, the proposed algorithm uses the analogous optimization criteria in csp and a new framework for simultaneous optimization of projection matrices on each mode based on tensor analysis theory is developed. experimental results demonstrate that our proposed algorithm is able to improve classification accuracy of multi-class motor imagery eeg.
exponential error bounds for binary detection using arbitrary binary sensors and an all-purpose fusion rule in wireless sensor networks. wireless sensor networks are considered in which sensors convey binary decisions over fading channels to a common fusion center. the fusion center first takes each received signal and makes an estimate of the transmitted bit. the average of the estimated bits is compared to a threshold to make a global decision. exponential error bounds are derived that allow one to trade off signal-to-noise ratio versus the number of sensors to achieve desired average error levels. an attractive feature of the bounds is that they do not require exact knowledge of the wireless channel statistics; approximations are sufficient.
periodic event detection and recognition in video. periodicity attracts special attention in human cognition. hence it is important to consider that in automatic analysis of motion events. this paper presents a method for representing periodic events with which events can be compared irrespective of their duration. the effectiveness of such a representation is verified with event classification.
multipath diversity and coding gains of cyclic-prefixed single carrier systems. the multipath diversity and coding gain metrics for cyclic-prefixed single-carrier (sc-cp) systems, which characterize the bit error rate (ber) at high snr, have not been carefully studied in the literature. we first show that, unlike ofdm, the diversity and coding gains for sc-cp are data-realization-dependent. then, we show that there is a signal-tonoise ratio (snr) threshold beyond which the dominant diversity order starts deviating from the maximum diversity order to eventually reduce to one at higher snrs. using the averaged pairwise probability, we derive an analytical expression for this snr threshold. the latter is shown to increase with the block length and to be unrealistically high for moderate/high block lengths. comparisons of sc-cp with rotated constellations and zero-padded sc systems are also provided.
psychoacoustically constrained and distortion minimized speech enhancement algorithm. a psychoacoustically constrained and distortion minimized speech enhancement algorithm is considered. in general, noise reduction leads to speech distortion, and thus, the goal of an enhancement algorithm should reduce noise and speech distortion so that both are inaudible. in this paper, a constrained optimization problem is formulated so that speech distortion is minimized while distortion that includes residual noise and speech distortion is kept below the masking threshold of the clean speech. experimental results show that the algorithm considered in this paper outperforms some of the more popular algorithms in terms of improvement in segmental signal-to-noise ratio (segsnr) and spectral distance (sd).
data-driven lexicon expansion for mandarin broadcast news and conversation speech recognition. we present a data-driven framework for expanding the lexicon to improve mandarin broadcast news and conversation speech recognition. the lexicon expansion includes the generation of pronunciation variants for frequent words and vocabulary augmentation with new words and phrases derived from the training data. to learn multiple pronunciations, we first generate all possible pronunciation candidates for a word from its character pronunciation network. the top pronunciation variants are then selected from forced alignment statistics. to augment the acoustic vocabulary, we propose an efficient algorithm that derives new words based on n-gram statistics. experiments show that a dictionary expanded in this manner yields significant improvements on a mandarin broadcast speech recognition task.
quantifying morphology changes in time series data with skew. this paper examines strategies to quantify differences in the morphology of time series while accounting for time skew in the observed data. we adapt four measures originally designed for signal shape comparison: dynamic time-warping (dtw), earth mover's distance (emd), fréchet distance (fd), and hausdorff distance (hd). these morphology difference metrics on time series are compared in discriminative power and noise resistance on ecg signals as well as on a synthetic dataset. we use data from our experiments to shed light on the relative strengths of the methods.
blind subspace-based channel estimation using the em algorithm. we propose an application of the expectation-maximization (em) algorithm to the problem of blind estimation of single-input multiple-output (simo), finite-impulse-response (fir) channels. we first assume gaussian input to formulate an em-based estimation of the signal subspace of the output covariance matrix. this gaussian assumption allows us to utilize knowledge from em-based probabilistic principle component analysis (p-pca). next, we show that the equilibrium point of the em iteration equations is reached without the gaussian assumption, which suggests usage of non-gaussian communication input signals. the estimated signal subspace is then utilized to identify the channels. in principle, the proposed method yields the same channel estimates as the widely-known subspace method, but is computationally more efficient. in addition, unlike typical em applications, the proposed scheme is free from cumbersome parameter initialization issue, which greatly increases flexibility of the proposed scheme.
a compact microphone array system with spatial post-filtering for automotive applications. compact microphone arrays allow for directional filtering with a minimum of installation space. they are therefore particularly suitable for automotive applications. typically, compact arrays are realized as differential arrays or filter-and-sum beamformers which both show limited performance in terms of directivity. in this contribution we present a novel system for directional filtering for compact arrays. this system consists of two closely spaced microphones and incorporates an adaptive beamformer as well as a spatial post-filter which is designed to suppress non-stationary noise.
a physical approach to moving cast shadow detection. this paper presents a physics-based approach capable of detecting cast shadows in video sequence effectively. we develop a new physical model of cast shadows without making prior assumption of the spectral power distribution (spd) of the light sources and ambient illumination in the scene. the background appearance variation caused by cast shadows is characterized as the interaction of the blocked light sources and the background surface reflectance. we then take advantage of the statistical prevalence of cast shadows to learn and update the shadow model parameters using the gaussian mixture model (gmm) over time. the proposed algorithm is completely unsupervised and can adapt to specific environment with complex illumination condition as well as changing shadow conditions. experimental results on three challenging sequences demonstrate the effectiveness of the proposed method.
multidimensional signal reconstruction from multichannel acquisition. we provide an analysis of the algorithms necessary for the optimal use of multidimensional signal reconstruction from multichannel acquisition. first, we provide computable conditions to test the matrix invertibility and propose algorithms to find a particular inverse. second, we determine the existence of perfect reconstruction systems for given fir analysis filters with some sampling matrices and some fir synthesis polyphase matrices. then, we present the development of an efficient algorithm designed to find a sampling matrix with maximum sampling rate and fir synthesis polyphase matrix for given fir analysis filters so that the system provides a perfect reconstruction. once a particular synthesis matrix is found, we can characterize all synthesis matrices and find an optimal one according to a design criterion.
robust speech dereverberation based on non-negativity and sparse nature of speech spectrograms. this paper presents a blind dereverberation method designed to recover the subband envelope of an original speech signal from its reverberant version. the problem is formulated as a blind deconvolution problem with non-negative constraints, regularized by the sparse nature of speech spectrograms. we derive an iterative algorithm for its optimization, which can be seen as a special case of the non-negative matrix factor deconvolution. we confirmed through experiments that the algorithm is fast and robust to speaker movement.
energy-efficient graph-based wavelets for distributed coding in wireless sensor networks. this work presents a class of unidirectional lifting-based wavelet transforms for an arbitrary communication graph in a wireless sensor network. these transforms are unidirectional in the sense that they are computed as data is forwarded towards the sink on a routing tree. we derive a set of conditions under which a lifting transform is unidirectional, then find the full set of those transforms. among this set, we construct a unidirectional transform that allows nodes to transform their own data using data forwarded to them from their descendants in the tree and data broadcasted to them from their neighbors not in the tree. this provides a higher quality data representation than existing methods for a fixed communication cost.
detection and classification of liquid explosives using nmr. in this work, we present a novel method for non-invasive identification of liquids, for instance to allow for the detection of liquid explosives at airports or border controls. the approach is based on a nuclear magnetic resonance technique with an inhomogeneous magnetic field, forming estimates of the liquid's spin-spin relaxation time, t2, and diffusion constant, d, thereby allowing for a unique classification of the liquid. the proposed detectors are evaluated using both simulated and measured data sets.
on the phonetic information in ultrasonic microphone signals. we study the phonetic information in the signal from an ultrasonic “microphone”, a device that emits an ultrasonic wave toward a speaker and receives the reflected, doppler-shifted signal. this can be used in addition to audio to improve automatic speech recognition. this work is an effort to better understand the ultrasonic signal, and potentially to determine a set of natural sub-word units. we present classification and clustering experiments on cvc and vcv sequences in speaker-dependent and multi-speaker settings. using a set of ultrasonic spectral features and diagonal gaussian models, it is possible to distinguish all consonants and most vowels. when clustering the confusion data, the consonant clusters mostly correspond to places and manners of articulation; the vowel data roughly clusters into high, low, and rounded vowels.
approaching user capacity in a dsl system via harmonic mean-rate optimization. in this paper we consider a digital subscriber line (dsl) system with n orthogonal narrowband tones. each user has a limited power budget, and our goal is to determine the power allocation of each user that enables the ‘user capacity’ of the system to be approached. in this paper, we use ‘user capacity’ to denote the maximum number of users that can be supported by the system, provided that each user is guaranteed to have a data rate that lies within a prescribed range. finding a power allocation that enables this capacity to be approached directly can be quite cumbersome because it involves solving a (non-convex) integer-program. in order to circumvent this difficulty, in this paper we propose an alternate approach that is based on exploiting the fairness and per-tone convexity of the harmonic mean-rate objective. using these features, we devise a computationally-efficient power allocation technique that enables the user capacity of the dsl system to be approached more closely than power allocation techniques that are more computationally demanding.
reversible data hiding in highly efficient compression scheme. nowadays, most multimedia is stored in compressed bit stream format to save the storage apace or transmission time. this study proposes a novel technique for embedding flexible amounts of data in the bitmap of the improved ordered dither block truncation coding (odbtc) image, where the ordered dithering is used to dither the quantized btc image to avoid the annoying false contour and blocking effect inherently existed in btc image. moreover, the lut strategy is also used to significantly reduce the complexity. the inverse halftoning and the second round of halftoning are employed as the key steps in locating the embedded information bits. experimental results demonstrate that an objective good quality image with flexible capacity and reasonable complexity is obtained. moreover, the correct decoding rate of 100% is maintained, and the original host odbtc image can also be reconstructed in the decoder when needed, which significantly boosts the flexibility in image quality control.
video quality monitoring of streamed videos. this paper describes a video quality analysis system for inservice monitoring of streamed videos, particularly over mobile/wireless networks. the algorithm adopts the no-reference method, and enables real-time measurement of video quality at any point in the content production and delivery chain using any given video. the technologies developed include no-reference methods for measuring picture freeze, picture loss, and blockiness. the developed system (where the software has not been optimized for speed) is able to process video of cif size (352×288 pixels) at more than 30 fps on a pentium-iv 3ghz computer. the experimental results show that the proposed video quality analysis system gives good accuracy for picture freeze, picture loss, and blocking detections.
wheezing sounds detection using multivariate generalized gaussian distributions. a wheeze is a continuous, coarse, whistling sound produced in the respiratory airways during breathing, commonly experienced by persons suffering from asthma. in this paper, we present a new method for the detection of wheezing sounds in the normal breathing sounds. in our study we perform an accurate statistical analysis of breathing signals. we suggest a modeling for wheezing and normal sounds in the wavelet packet domain using generalized gaussian distributions. our detection method is based on a specific multimodal markovian modeling proposed in a bayesian framework. we cope with the multidimensional aspect of the generalized gaussian distribution by using the theory of copulas. experimental results are given in detail in this paper.
an effective flowestimation method with particle filter based on helmholtz decomposition theorem. this paper proposes a novel flow estimation method with a particle filter based on a helmholtz decomposition theorem. the proposed method extends a model of the helmholtz decomposition theorem and enables the decomposition of flows into rotational, divergent, and translational components. from the extended model, the proposed method defines a state transition model and an observation model of the particle filter. furthermore, the proposed method derives an observation density of the particle filter from an energy function based on the helmholtz decomposition theorem. by utilizing these novel approaches, the proposed method provides a solution to the problem in the traditional ones of not being able to realize an effective flow estimation with the particle filter based on rotation, divergence, and translation, which are important geometric features. consequently, the proposed method can accurately estimate the flows.
robust video fingerprinting based on visual attention regions. this paper presents a robust video fingerprinting based on visual attention regions. video fingerprints, which are a set of short feature vectors, are unique to video clips and used for video identification. the performance of video fingerprinting is usually measured in terms of robustness and accuracy of identification. in our proposed approach, we extract video fingerprints using visual attention regions which remain the same for the perceptually same scenes with different types of distortions and different for different scenes. the experimental results show that the proposed video fingerprinting is effective for constructing video fingerprints that are robust against various content-preserving distortions and accurate in identifying different video clips.
robust sampling and reconstruction methods for compressed sensing. recent results in compressed sensing show that a sparse or compressible signal can be reconstructed from a few incoherent measurements. compressive sensing systems are not immune to noise, which is always present in practical acquisition systems. in this paper we propose robust methods for sampling and reconstructing sparse signals in the presence of impulsive noise. analysis of the proposed methods demonstrates their robustness under heavy-tailed models. simulations show that the proposed methods outperform existing compressed sensing techniques in impulsive environments, while having similar performance in light-tailed environments.
symmetric distributed multiview video coding. symmetric distributed source coding has made great progress in the past several years. however, few attempts have been tried to use the symmetric distributed source coding schemes in real data compression scenarios. in this paper, with the inspiration of previous symmetric distributed source coding schemes, we first put forward a novel syndrome-based symmetric distributed coding scheme which can achieve the whole slepian-wolf rate region. then we propose a general architecture for symmetric distributed multiview video schemes. our experiments show very encouraging results. in the high-rate case, our scheme can achieve great rate saving from separate h.264 coding scheme at the same video quality.
vectorized deblocking filter for hd h.264 decoding on cell/b.e. for high definition (hd) h.264 decoding, deblocking filter is one of the most time-consuming modules. this paper proposes several vectorization approaches to speed up it on a single synergistic processor element (spe) of ibm cell broadband engine (cell/b.e.) processor, by which great performance improvements are achieved. the average deblocking speed is 42.4 frames per second (fps) for 141 1080p h.264 video streams. the steady-going performance is obtained for different streams of various contents and bitrates. with the vectorized deblocking filter, the new hd h.264 decoder is able to decode two 1080p h.264 video streams simultaneously on playstation® 3 (ps3) in real-time. the proposed approaches are practical on many other vector processor platforms, but not limited to cell/b.e. processor.
from rule-based to statistical grammars: continuous improvement of large-scale spoken dialog systems. statistical spoken language understanding grammars (sslus) are often used only at the top recognition contexts of modern large-scale spoken dialog systems. we propose to use sslus at every recognition context in a dialog system, effectively replacing conventional, manually written grammars. furthermore, we present a methodology of continuous improvement in which data are collected at every recognition context over an entire dialog system. these data are then used to automatically generate updated context-specific sslus at regular intervals and, in so doing, continually improve system performance over time. we have found that sslus significantly and consistently outperform even the most carefully designed rule-based grammars in a wide range of contexts in a corpus of over two million utterances collected for a complex call-routing and troubleshooting dialog system.
inventory based speech enhancement for speaker dedicated speech communication systems. we are presenting a method for the enhancement of speech in speaker dedicated speech communication systems. the proposed procedure is fundamentally different from most state-of-the-art filtering approaches. instead of filtering a distorted signal we are re-synthesizing a new “clean” signal based on its likely characteristics. these characteristics are estimated from the distorted signal. we present a successful implementation of the proposed method for a communication system for which speaker enrollment and noise enrollment are feasible. forty minutes of clean speech training data is usually sufficient for successful denoising. the proposed method compares very favorably to other state-of-the-art systems in both objective and subjective speech quality assessments.
linear predictive modelling of gait patterns. the use of a wearable triaxial accelerometer for unsupervised monitoring of human movement has become a major research focus in recent years. in this paper, the relationship between accelerometry signals and human gait is analysed using a linear prediction (lp) model. we explore the use of the lp model for analysing five gait patterns and show that the lp cepstrum can be used for gait pattern classification with high accuracy. this is then compared to a filterbank based approach to estimate the cepstral coefficients. fifty subjects participated in collection of gait pattern data involving walking on level surfaces, and walking up and down stairs and ramps. the results show that an overall accuracy of 93% can be achieved using features derived from the cepstral coefficients for the five different walking patterns.
multi-modal activity and dominance detection in smart meeting rooms. in this paper a new approach for activity and dominance modeling in meetings is presented. for this purpose low level acoustic and visual features are extracted from audio and video capture devices. hidden markov models (hmm) are used for the segmentation and classification of activity levels for each participant. additionally, more semantic features are applied in a two-layer hmm approach. the experiments show that the acoustic feature is the most important one. the early fusion of acoustic and globalmotion features achieves nearly as good results as the acoustic feature alone. all the other early fusion approaches are outperformed by the acoustic feature. more over, the two-layer model could not achieve the results of the acoustic features.
a low complexity channel decomposition and feedback strategy for mimo precoder design. in classical mimo systems, singular value decomposition (svd) is adopted as a common way to decompose the mimo channel into parallel subchannels. however, in addition to its high complexity, it is also sensitive to the ill-conditioning of the channel matrix. in this paper, we propose a channel decomposition strategy called ldlh decomposition for low complexity mimo precoder design. we show that the computation complexity of ldlh achieves one degree of magnitude lower than that of svd, as well as some svd-based decomposition scheme such as geometric mean decomposition (gmd) and uniform channel decomposition (ucd). in addition, we also show that ldlh-based precoder requires less quantization effort and feedback bandwidth.
on the side-information dependency of the temporal correlation in wyner-ziv video coding. current models in wyner-ziv video coding consider the temporal correlation noise to be side-information independent (sii). this paper goes beyond this assumption and proposes a novel model, of which the parameters are side-information dependent (sid). the proposed model is experimentally validated showing remarkable accuracy improvement over the conventional sii model. moreover, a novel sid technique for the accurate estimation of the correlation channel in video is introduced. the proposed technique enables the design of a novel pixel-domain wyner-ziv video coding system operating without a feedback channel. preliminary experimental results show that the proposed codec achieves superior performance compared to the state-of-the-art in pixel-domain wyner-ziv coding.
contrasting emotion-bearing laughter types in multiparticipant vocal activity detection for meetings. the detection of laughter in conversational interaction presents an important challenge in meeting understanding, important primarily because laughter is predictive of the emotional state of participants. we present evidence which suggests that ignoring unvoiced laughter improves the prediction of emotional involvement in collocated speech, making a case for the distinction between voiced and unvoiced laughter during laughter detection. our experiments show that the exclusion of unvoiced laughter during laughter model training as well as its explicit modeling lead to detection scores for voiced laughter which are much higher than those otherwise obtained for all laughter. furthermore, duration modeling is shown to be a more effective means of improving precision than interaction modeling through joint-participant decoding. taken together, the final detection f-scores we present for voiced laughter on our development set comprise a 20% reduction of error, relative to f-scores for all laughter reported in previous work, and 6% and 22% relative reductions in error on two larger datasets unseen during development.
robust-sl0 for stable sparse representation in noisy settings. in the last few years, we have witnessed an explosion in applications of sparse representation, the majority of which share the need for finding sparse solutions of underdetermined systems of linear equations (usle's). based on recently proposed smoothed ℓ0-norm (sl0), we develop a noise-tolerant algorithm for sparse representation, namely robust-sl0, enjoying the same computational advantages of sl0, while demonstrating remarkable robustness against noise. the proposed algorithm is developed by adopting the corresponding optimization problem for noisy settings, followed by theoretically-justified approximation to reduce the complexity. stability properties of robust-sl0 are rigorously analyzed, both analytically and experimentally, revealing a remarkable improvement in performance over sl0 and other competing algorithms, in the presence of noise.
a parafac-based technique for detection and localization of multiple targets in a mimo radar system. in this paper, we show that the problem of detection and localization of multiple targets in a bistatic mimo radar system can be solved by parallel factor (parafac) analysis. our method is deterministic and fully capitalizes on the strong algebraic structure of the received data, where the radar cross section (rcs) fluctuation is not regarded as a nuisance parameter but rather as a source of time diversity. simulation results show that our technique outperforms existing beamforming-based radar imaging methods at a lower complexity.
a specific qrs detector for electrocardiography during mri: using wavelets and local regularity characterization. automatic electrocardiogram (ecg) analysis, especially qrs detection, is still a challenging task. this is even more the case when ecg is acquired during magnetic resonance (mr) examination. the mr environment highly distorts ecg, with hall effect, due to the important static magnetic field, and artifacts, caused by fast switching magnetic field gradients. detection of qrs complexes is then affected. in this paper, a new specific mr qrs detector is presented. this method is based on the modulus maximum lines and on the lipschitz exponent estimation they offer. the use of this regularity characterization enables to distinguish between qrs complexes and mr artifacts. this detector outperforms existing algorithms with almost 99% sensitivity and positive prediction value.
structuring and analyzing low-quality lecture videos. this paper presents a lecture video structuring and analysis scheme to provide students an efficient way to access the lecture content. instead of using color-based or histogram-based methodologies, we propose a new edge-based shot boundary detection algorithm to accurately rebuild the slide structure. the proposed approach can successfully resist the unwanted influences induced from the variant illumination condition and occlusions. besides, original slide content can be extracted excluding any obstruction by using human removing techniques. furthermore, the teaching focus is analyzed so that this system becomes more useful for learning.
improving the performance of vtln under mismatched speaker conditions and making it approach that of matched speaker conditions. the performance of conventional vtln for mis-matched train and test speaker conditions (e.g. adult-train child-test) does not approach the performance of matched speaker conditions (e.g. child-train child-test). in this paper, we investigate this problem and propose methods to reduce this gap in performance. we use our recently proposed linear transformation approach to vtln, that also enables us to study the effect of jacobian unlike conventional vtln. the main advantage of transform-based vtln over adaptation based approaches (like cmllr), is that it does not require any matrix estimation. we argue that the degraded vtln performance under mismatched speaker conditions is due to the significant frequency warping that is necessary for normalization which leads to a mis-match between the correlation in the feature components of the test data and the covariance structure of the trained/normalized model. we show that the use of a global de-correlating transform (mllt) leads to improved vtln performance. we finally show that using both jacobian and mllt together improves the vtln performance for mis-matched cases with the performance approaching that of matched speaker conditions.
instantaneous frequency rate estimation for high-order polynomial-phase signal. for a high-order polynomial-phase signal (pps), instantaneous frequency rate (ifr), which is defined as the second derivative of the phase, is estimated by using an estimator with only a second-order nonlinearity. compared to high-order phase function (hpf), the proposed ifr estimator presents improved performance including smaller mean-squared error (mse) and lower snr threshold. statistical analysis via a multivariate first-order perturbation analysis is derived for the estimate bias and mse. numerical results verify our analytical results.
optimizing segment label boundaries for statistical speech synthesis. this paper introduces a new optimization technique for moving segment labels (phone and subphonetic) to optimize statistical parametric speech synthesis models. the choice of objective measures is investigated thoroughly and listening tests show the results to significantly improve the quality of the generated speech equivalent to increasing the database size by 3 fold.
multi-level non-rigid image registration using graph-cuts. non-rigid image registration is widely used in medical image analysis and image processing. it remains a challenging research problem due to its smoothness requirement and high degree of freedoms in the deformation process. in [1], a method is proposed to solve non-rigid image registration via graph-cuts algorithm by modeling the registration process as a discrete labeling problem. a displacement label (vector) is assigned to each pixel in the source image to indicate the corresponding position in the floating image. the whole system is then optimized by using the graph-cuts algorithm via alpha-expansions [2]. as the initial point is not required for the graph-cuts algorithm, the method proposed by [1] is a single-level registration. in this paper, rather single-level, we enable multi-level non-rigid image registration using graph-cuts by passing the deformation field of the current resolution level to the successive finer one. by applying the proposed multi-level registration method, the number of labels used in each level is greatly reduced due to lower image resolution being used in coarser levels. therefore, the speed of the registration process is improved. we compare our results with the original single-level version, demons and ffd. it is found that our method improves the speed of non-rigid image registration by 50% and meanwhile maintains similar robustness and registration accuracy with the single-level version.
2d sound source mapping from mobile robot using beamforming and particle filtering. this paper describes a particle filter based sound source mapping system that builds 2d sound source maps from directional sound readings taken from a mobile robot. the method uses a sound source localization model that is represented by gaussian distribution for both direction and distance. to do this, accurate directional localization of sound sources is required, and two key components have been developed to achieve this: 1) a 32ch low side-lobe microphone array that is designed by beam forming simulation to have a) an omni-directional response, b) a narrower main-lobe, and c) lower side-lobes, in 700–2500[hz] acoustic signals; 2) directional localization of different pressure sound sources by combining the delay and sum beam forming (dsbf) and the frequency band selection (fbs) methods. finally, experimental results show the proposed method can map sound sources in two dimesionals with high accuracy (less than 50[cm] error).
cooperative mimo for alien noise cancellation in upstream vdsl. we present cooperative mimo for alien noise cancellation (comac): a per-tone, blind, low-complexity, linear, and adaptive noise whitening algorithm for alien crosstalk mitigation in upstream vectored vdsl systems. comac directly acts on the residual errors of the vectored users after self-fext cancellation and frequency domain equalization, and thus, leverages the inherent alien-crosstalk-induced spatial correlation across users. comac employs a lowcomplexity recursion scheme derived from the optimal mmse noise whitener to non-disruptively initialize, engage, and adapt the noise canceller while the vectored users operate in data mode. assuming reliable transmit symbol estimation at its input, we show that comac achieves the cramer-rao lower bound. further, the snr improvements accruing from comac can be translated into substantial rate improvements for upstream vectored vdsl.
exploitation of srtm dem in insar processing and its application to phase unwrapping problem. a novel approach is proposed in this paper to exploit the shuttle radar topography mission (srtm) digital elevation model (dem) in the interferometric synthetic aperture radar interferometry (insar) processing. the proposed algorithm includes three steps: the first step is to patch the void cells in the srtm dem; the second step is to determine a one-to-one correspondence between the interferogram and the srtm dem; the third step is to eliminate the phase trend between the original and simulated interferogram. meanwhile this algorithm can be applied to help the phase unwrapping problem. conventional techniques approach phase unwrapping as an optimization problem, where the total branch-cuts, or the gradient errors, etc. are to be minimized. generally speaking, they consider phase unwrapping as a blind procedure, i.e., without any external guidance. the purpose of this paper is to fill this gap by introducing the srtm dem as a phase unwrapping guidance. some experimental results with jesr verify our theoretical analysis and show that our method can improve the performance of the phase unwrapping to a great degree.
nonparametric estimation for compound poisson processes on compact lie groups. motivated by applications in multiple scattering, we study the problem of decompounding on compact lie groups. employing tools from harmonic analysis, we give a nonparametric approach to this problem. the case of the special orthogonal group so(3) is discussed in detail.
a reduced-rank square root filtering framework for noninvasive functional imaging of volumetric cardiac electrical activity. to noninvasively reconstruct transmembrane potential (tmp) dynamics throughout the 3d myocardium using body surface potential recordings, it is necessary to combine prior physiological models and patient's data with regard to their respective uncertainties. to fulfill model-data melding for this large-scale and high-dimensional system, data assimilation with proper computational reduction is needed for computational feasibility and efficiency. in this paper, we develop a reduced-rank square root tmp estimation algorithm, using dominant components of estimation uncertainties to guide a more efficient model-data coupling in the square root structure. the svd-based reduced-rank error covariance is used to represent and track the dominant estimation errors, and unified into an integrated square root filtering framework. phantom experiments demonstrate the ability of this framework to bring substantial computational reduction at slight expense of degraded estimation accuracy. it therefore improves the efficiency and applicability of the volumetric myocardial tmp imaging in practice.
voice conversion for various types of body transmitted speech. in this paper, we review our proposed statistical voice conversion approaches to enhancing various types of body transmitted speech captured with non-audible murmur (nam) microphone. body transmitted speech conversion is a potential technique to bring a new paradigm to human-to-human speech communication. in addition to our previously proposed methods of enhancing body transmitted unvoiced speech for silent speech communication and of enhancing body transmitted artificial speech for speaking aid, we further propose conversion methods of enhancing body transmitted voiced speech for noise robust speech communication. an experimental result demonstrates that the proposed methods yield significant improvements in quality of body transmitted voiced speech.
spatial structure characterization of textures in ihls colour space. we present model based approaches for colour texture characterization in ihls colour space. pure chrominance structure information is used in parallel with luminance structure information for colour texture classification. hue and saturation channels are combined through a complex exponential to give a single channel which holds all the chrominance information of the image. two dimensional complex multichannel versions of non-symmetric half plane autoregressive model and gauss markov random field model are used to perform parametric power spectrum estimation of both luminance and the “combined chrominance” channels of the image. colour texture classification is done using k-nearest neighbor algorithm on spectral distance measures both for luminance and chrominance channels individually as well as combined through a combination coefficient. experimental results show that colour texture characterization obtained by combined luminance and chrominance structure informations is better than the one obtained by using only luminance structure information.
improved sift-based image registration using belief propagation. scale invariant feature transform (sift) is a very powerful technique for image registration. while sift descriptors accurately extract invariant image characteristics around keypoints, the commonly used matching approach for registration is overly simplified, because it completely ignores the geometric information among descriptors. in this paper, we formulate keypoint matching as a global optimization problem and provide a suboptimum solution using belief propagation. experimental results show significant improvement over previous approaches.
a suffix array approach to video copy detection in video sharing social networks. to address the multiplicity and copyright issues on file sharing social networks, we propose a fast video copy detection algorithm using the suffix array data structure in this work. the proposed algorithm consists of two steps. in the first step, we extract robust features which are discriminative yet insensitive to various attacks. specifically, we develop a compact one-dimensional signature based on the shot change position of video files. unlike images and audio, the size of a video file is usually large, which makes it computationally expensive to match two long signature sequences. thus, in the second step, we adopt an efficient matching technique based on the suffix array data structure. the proposed system can perform the sequence matching in linear time while the complexity of conventional duplicate video detection algorithms grows at least quadratically with the video length.
semi-blind channel estimation for mimo single carrier with frequency domain equalization systems. we propose a semi-blind channel estimation method for multiple-input multiple-output (mimo) single carrier with frequency domain equalization systems. by taking advantage of periodic precoding and the block circulant channel model after cyclic prefix removal, we obtain the channel product matrices by solving a series of decoupled linear systems, which is gained from the covariance matrix of the received data. then the channel impulse response matrix is obtained by computing the positive eigenvalues and eigenvectors of a hermitian matrix formed from the channel product matrices. we also propose an optimal design of the precoding sequence which minimizes the noise effect and numerical error in covariance matrix estimation. simulations are used to demonstrate the performance of the proposed method. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
optimization of training sequences for spatially correlated mimo-ofdm. the optimal training sequence for channel estimation in spatially correlated multiple-input multiple-output (mimo) orthogonal frequency-division multiplexing (ofdm) systems has not been found for an arbitrary signal-to-noise ratio (snr). only one class of training sequences was proposed in the literature in which the power allocation is given only for the extreme conditions of low and high snr. provided in this paper are (i) a necessary and sufficient condition for the optimal training sequence together with a convex programming to find the solution, and (ii) efficient procedures to find the optimal training sequence. simulation results confirms the superiority of the proposed design over the existing one.
a beamforming particle filter for eeg dipole source localization. recently we have developed a method for electroencephalogram (eeg) dipole source localization based on particle filtering (pf). in this study the method is combined with beamforming to eliminate the noise which is spatially uncorrelated with the desired signal and accordingly to improve its performance. the proposed beamforming is an optimum, linear and data independent filter which can be applied to stationary as well as non-stationary data. simulation and real data results have been provided to show its better performance over pf and beamforming approaches for dipole source localization.
rhythm map: extraction of unit rhythmic patterns and analysis of rhythmic structure from music acoustic signals. this paper discusses an approach to extract constituent percussive bar-long patterns in a music piece given as acoustic signal and to analyze the music structure with a map of constituent rhythmic patterns. possible applications include music genre classification, music information retrieval (mir) and music modification such as replacing rhythmic patterns with others. we propose a mathematical method based on one-pass dp algorithm and k-means clustering to extract unit percussive rhythmic patterns. as the result of identifying and localization the unit patterns in the entire piece, we obtained a music structure in the form of a map of rhythmic patterns.
cheat-proof cooperation strategies for wireless live streaming social networks. multimedia social network analysis is an emerging research area, which analyzes the behavior of users who share multimedia content and investigates the impact of human dynamics on multimedia systems. users watching live streaming in the same wireless network share the same backbone connection to the internet, thus they might want to cooperate with each other to obtain better video quality. these users form a wireless live-streaming social network and every user wishes to watch video with as high as possible quality while paying as less as cost for cooperation. thus full cooperation cannot be guaranteed and the cooperation strategy must give incentives to the users. this paper proposes a game-theoretic framework to model user behavior and designs incentive-based strategies to stimulate user cooperation in wireless live streaming. we analyze the pareto optimality and time-restricted bargaining equilibrium of the game. we also take into consideration selfish users' cheating behavior and propose cheat-proof strategies. both our analytical and simulation results show that the proposed strategies can effectively stimulate user cooperation, achieve cheat free and help provide reliable services.
throughput analysis of cooperative wireless medium access scheme exploiting multi-beam adaptive arrays. cooperative wireless network medium access schemes can achieve high throughput through collision resolution. by using a multi-beam adaptive array (mbaa) at a base station or access point, it can concurrently communicate with multiple nodes/users and thus the network performance can be further enhanced. in this paper, we provide an efficient packet resolution method and analyze the throughput of cooperative wireless medium access scheme exploiting mbaas.
speaker adaptation by variable reference model subspace and application to large vocabulary speech recognition. recently, we presented a rapid speaker adaptation technique, reference model interpolation (rmi), which is based on the linear interpolation of speaker-dependent models and the a posteriori selection of reference models. the approach uses the a priori knowledge provided by a set of representative speakers to guide the estimation of a new speaker model in the speaker space. rmi achieved rapid supervised adaptation in phoneme decoding tasks. in this paper, we present two new results of rmi: firstly, we apply the rmi technique in a practical large vocabulary continuous speech recognition (lvcsr) system with unsupervised instantaneous adaptation. secondly, we propose an evolutional subspace scenario which integrates the slow update of reference models with rmi rapid adaptation to achieve incremental adaptation. the unsupervised adaptation experiments carried out on broadcast news transcription task show encouraging results for both instantaneous and incremental adapatation.
non-speech audio event detection. audio event detection is one of the tasks of the european project vidivideo. this paper focuses on the detection of non-speech events, and as such only searches for events in audio segments that have been previously classified as non-speech. preliminary experiments with a small corpus of sound effects have shown the potential of this type of corpus for training purposes. this paper describes our experiments with svm and hmm-based classifiers, using a 290-hour corpus of sound effects. although we have only built detectors for 15 semantic concepts so far, the method seems easily portable to other concepts. the paper reports experiments with multiple features, different kernels and several analysis windows. preliminary experiments on documentaries and films yielded promising results, despite the difficulties posed by the mixtures of audio events that characterize real sounds.
generalized baum-welch algorithm for discriminative training on large vocabulary continuous speech recognition system. we propose a new optimization algorithm called generalized baum welch (gbw) algorithm for discriminative training on hidden markov model (hmm). gbw is based on lagrange relaxation on a transformed optimization problem. we show that both baum-welch (bw) algorithm for ml estimate ofhmmparameters, and the popular extended baum-welch (ebw) algorithm for discriminative training are special cases of gbw.we compare the performance of gbw and ebw for farsi large vocabulary continuous speech recognition (lvcsr).
benchmarking flexible adaptive time-frequency transforms for underdetermined audio source separation. we have implemented several fast and flexible adaptive lapped orthogonal transform (lot) schemes for underdetermined audio source separation. this is generally addressed by time-frequency masking, requiring the sources to be disjoint in the time-frequency domain. we have already shown that disjointness can be increased via adaptive dyadic lots. by taking inspiration from the windowing schemes used in many audio coding frameworks, we improve on earlier results in two ways. firstly, we consider non-dyadic lots which match the time-varying signal structures better. secondly, we allow for a greater range of overlapping window profiles to decrease window boundary artifacts. this new scheme is benchmarked through oracle evaluations, and is shown to decrease computation time by over an order of magnitude compared to using very general schemes, whilst maintaining high separation performance and flexible signal adaptivity. as the results demonstrate, this work may find practical applications in high fidelity audio source separation.
orthogonalized discriminant analysis based on generalized singular value decomposition. generalized singular value decomposition (gsvd) has been used for linear discriminant analysis (lda) to solve the small sample size problem in pattern recognition. however, this algorithm may suffer from the over-fitting problem. in this paper, we propose a novel orthogonalization technique for the lda/gsvd algorithm to address the over-fitting problem. in this technique, an orthogonalization of the basis of the discriminant subspace derived from the lda/gsvd algorithm is carried out through an eigen-decomposition of a small size inner product matrix. it is computationally efficient when data are high dimensional. the technique is further applied to the kernelized lda/gsvd algorithm, mgsvd-kda, leading to a new algorithm, referred to as gsvd-okda. it is shown that with linear and nonlinear kernels, this new algorithm successfully overcomes the over-fitting problem of the lda/gsvd and mgsvd-kda algorithms. simulation results show that the proposed algorithms provide high recognition accuracy with low computational complexity.
identifiability and performance concerns for location estimation. common localization approaches require a large amount of information to be available in order to achieve identifiability, when the signal propagates in a strictly non-line-of-sight (nlos) environment. furthermore, even if they achieve identifiability, they usually perform poorly. in this contribution we investigate the conditions that must be met for identifiability to be feasible and for performance to be adequate. through basic theorems and simple numerical examples, we study the benefit of exploiting additional information, if such is available and we provide intuitive conclusions that can be proved useful for any localization scheme.
bandwidth-efficient cache-based motion compensation architecture with dram-friendly data access control. for h.264/avc decoder system, the motion compensation bandwidth comes from two parts, the reference data loading bandwidth and the equivalent bandwidth from dram access overhead latency. in this paper, a bandwidth-efficient cache-based mc architecture is proposed. it exploits both intra-mb and inter-mb data reuse and reduce up to 46% mc bandwidth compared to conventional scheme. to reduce the equivalent bandwidth from dram access overhead latency, the dram-friendly data mapping and access control scheme are proposed. they can reduce averagely 89.8% of equivalent dram access overhead bandwidth. the average mc burst length can be improved to 9.59 words/burst. the total bandwidth reduction can be up to 32∼71% compared to previous works.
discriminative pronounciation learning using phonetic decoder and minimum-classification-error criterion. in this paper, we report our recent research aimed at improving the pronunciation-modeling component of a speech recognition system designed for mobile voice search. our new discriminative learning technique overcomes the limitation of the traditional ways of introducing alternative pronunciations that often enlarge confusability across different lexical items. instead, we make use of a phonetic recognizer to generate pronunciation candidates, which are then evaluated and selected using the global minimum-classification-error measure, guaranteeing a reduction of the training-set error rate after introducing alternative pronunciations. a maximum entropy approach is subsequently used to learn the weight parameters of the selected pronunciation candidates. our experimental results demonstrate the effectiveness of the discriminative pronunciation learning technique in a real-world speech recognition task where pronunciation of business names presents special difficulty for high-accuracy speech recognition.
improved virtual channel noise model for transform domain wyner-ziv video coding. distributed video coding (dvc) has been proposed as a new video coding paradigm to deal with lossy source coding using side information to exploit the statistics at the decoder to reduce computational demands at the encoder. a virtual channel noise model is utilized at the decoder to estimate the noise distribution between the side information frame and the original frame. this is one of the most important aspects influencing the coding performance of dvc. noise models with different granularity have been proposed. in this paper, an improved noise model for transform domain wyner-ziv video coding is proposed, which utilizes cross-band correlation to estimate the laplacian parameters more accurately. experimental results show that the proposed noise model can improve the rate-distortion (rd) performance.
extended vts for noise-robust speech recognition. model compensation is a standard way of improving speech recognisers' robustness to noise. currently popular schemes are based on vector taylor series (vts) compensation. they often use the continuous time approximation to compensate dynamic parameters. in this paper, the accuracy of dynamic parameter compensation is improved by representing the dynamic features as a linear transformation of a window of static features. a modified version of vts compensation is applied to the distribution of the window of static features and, importantly, their correlations. these compensated distributions are then transformed to standard static and dynamic distributions. the proposed scheme outperformed the standard vts scheme by about 10% relative.
a fast and accurate "shoebox" room acoustics simulator. we present a new “shoebox” room acoustics simulator that is designed to support research into signal processing algorithms that are robust to reverberation. it is an improvement over existing room acoustics simulators because it is computationally fast, portable to many kinds of research environments, and flexible to use. the proposed simulator is also perceptually accurate because it models both specular and diffuse surface reflections. an efficient implementation of the simulator is made freely available for download from the open source project roomsim on sourceforge.
a dimensional approach to emotion recognition of speech from movies. in this paper we present a novel method for extracting affective information from movies, based on speech data. the method is based on a 2-d representation of speech emotions (emotion wheel). the goal is twofold. first, to investigate whether the emotion wheel offers a good representation for emotions associated with speech signals. to this end, several humans have manually annotated speech data from movies using the emotion wheel and the level of disagreement has been computed as a measure of representation quality. the results indicate that the emotion wheel is a good representation of emotions in speech data. second, a regression approach is adopted, in order to predict the location of an unknown speech segment in the emotion wheel. each speech segment is represented by a vector of ten audio features. the results indicate that the resulting architecture can estimate emotion states of speech from movies, with sufficient accuracy.
formant-based technique for automatic filled-pause detection in spontaneous spoken english. detection of filled pauses is a challenging research problem which has several practical applications. it can be used to evaluate the spoken fluency skills of the speaker, to improve the performance of automatic speech recognition systems or to predict the mental state of the speaker. this paper presents an algorithm for filled pause detection that is based on the premise that the vocal tract characteristics, and hence the formants, are stable during the production of a filled pause. the performance of the proposed algorithm is evaluated on real-life recordings of call center agents where the locations of the filled pauses are hand labeled. the proposed algorithm outperforms a standard cepstral stability based filled pause detection algorithm and a standard pitch-based detection technique.
higher dimensional consensus algorithms in sensor networks. this paper introduces higher dimensional consensus, a framework to capture a number of different, but, related distributed, iterative, linear algorithms of interest in sensor networks. we show that, by suitably choosing the iteration matrix of the higher dimensional consensus, we can capture, besides the standard average-consensus, a broad range of applications, including sensor localization, leader-follower, and distributed jacobi algorithm. we work with the concept of anchors and explicitly derive the consensus subspace and provide the dimension of the limiting state of the sensors.
assessing robustness of particle filtering by the kolmogorov-smirnov statistics. one of the most criticized aspects of particle filtering algorithms is their dependence on model assumptions. however, a rigorous study of the effect of modeling errors on the performance of such algorithms is still missing. in this paper, the problem of using an inaccurate discrete state-space model is considered and a systematic methodology for studying the effects on its performance is proposed. the methodology is based on the use of the kolmogorov-smirnov statistic, which in this case is a distance metric between the posterior characterization when respectively correct and incorrect model assumptions are made. an example with functional and distributional inaccuracies is studied.
modal expansion of hrtfs: continuous representation in frequency-range-angle. this paper proposes a continuous hrtf representation in both 3d spatial and frequency domains. the method is based on the acoustic reciprocity principle and a modal expansion of the wave equation solution to represent the hrtf variations with different variables in separate basis functions. the derived spatial basis modes can achieve hrtf near-field and far-field representation in one formulation. the hrtf frequency components are expanded using fourier spherical bessel series for compact representation. the proposed model can be used to reconstruct hrtfs at any arbitrary position in space and at any frequency point from a finite number of measurements. analytical simulated and measured hrtfs from a kemar are used to validate the model.
a collaborative bayesian image retrieval framework. in this paper, an image retrieval framework combining content-based and content-free methods is proposed, which employs both short-term relevance feedback (strf) and long-term relevance feedback (ltrf) as the means of user interaction. the strf refers to iterative query-specific model learning during a retrieval session, and the ltrf is the estimation of a user history model from the past retrieval results approved by previous users. the framework is formulated based on the bayes' theorem, in which the results from strf and ltrf play the roles of refining the likelihood and the a priori information, respectively, and the images are ranked according to the a posteriori probability. since the estimation of the user history model is based on the principle of collaborative filtering, the system is referred to as a collaborative bayesian image retrieval (clbir) framework. to evaluate the effectiveness of the proposed framework, nearest neighbor clbir (nn-clbir) and support vector machine active learning clbir (svmal-clbir) were implemented. experimental results showed the improvement over content-based methods in terms of both accuracy and ranking due to the integration in the proposed framework.
transmit/receive beamforming for mimo radar with colocated antennas. we propose a new technique for multiple-input multiple-output (mimo) radar with colocated antennas. the essence of the proposed technique is to partition the transmitting array into a number of subarrays that are allowed to overlap. each subarray is used to coherently transmit a waveform which is orthogonal to the waveforms transmitted by other subarrays. coherent processing gain can be achieved by designing a weight vector for each subarray to form a beam towards a certain direction in space. moreover, the subarrays are combined jointly to form a mimo radar resulting in higher resolution capabilities. simulation results show the substantial improvements offered by the proposed technique as compared to previous techniques that validate its effectiveness.
doa estimation method based on sparseness of speech sources for human symbiotic robots. in this paper, direction of arrival (doa) estimation methods (both azimuth and elevation) based on sparseness of human speech, “modified delay-and-sum beamformer based on sparseness (mdsbf)” and “stepwise phase difference restoration (spire)”, are introduced for human symbiotic robots. mdsbf can achieve good doa estimation, whose computational cost is proportional to resolution of azimuth and elevation space. doa estimation result of spire is less accurate than that of mdsbf, but computational cost is independent of resolution. to achieve more accurate doa estimation result than spire with small computational cost, we propose a novel doa estimation method which is combination of mdsbf and spire. in the proposed method, mdsbf with rough resolution is performed prior to spire execution, and spire precisely estimates doa of sources after mdsbf. experimental results show that sparseness based methods are superior to conventional methods. the proposed combination method achieved more accurate doa estimation result than spire with smaller computational cost than mdsbf.
design of a morphological moving object signature and application to human identification. many computer vision systems try to infer semantic information about a video scene content by looking at the time series of the silhouettes of the moving objects. this paper proposes a new inter-frame feature set (signature) based on piecewise surfacic descriptions of binary silhouettes. it captures the dynamics of moving objects and compacts it into a robust set of features suitable for classification. to assess its ability to represent motion information, we use it to build a complete gait recognition algorithm that we test on a database of 21 different subjects. to highlight the efficiency of our signature, we use frontal views instead of side views of persons, which is less discussed in literature and is considered to be harder as the movement of legs is not visible. in that context, the high recognition rates obtained (over 95% of correct identifications) proves that our signature is appropriate to describe moving objects.
flatbed scanner identification based on dust and scratches over scanner platen. in this paper, a novel individual source scanner identification scheme is proposed. the scheme uses traces of dust, dirt, and scratches over scanner platen on scanned images to characterize a source scanner. the efficacy of the proposed scheme is substantiated with experimental analysis. the robustness of the scheme to the jpeg compression is also investigated. experimental results show that proposed scheme could be used to match a scanned image to its source.
a new method for tracking performance evaluation based on a reflective model and perturbation analysis. in this paper, we present a novel methodology for tracking performance evaluation. considering the continuity of the image sequences in a video, we define a new measurement called tracking difficulty which incorporates the local sequence information among a small image sequence centered at each frame. we subsequently use a reflective model to formulate tracking difficulty. tracking difficulty curves can not only illustrate at which parts of the video one tracking algorithm performs well or poor, but also provide a way to compare the performance of different tracking algorithms. we further add perturbation analysis to the reflective model to examine how sensitive the tracking algorithm is to noise. results on data sets are presented to show the effectiveness of our evaluation method.
a differential geometric approach to discrete-coefficient filter design. this paper is concerned with the problem of computing a discrete-coefficient approximation to a digital filter. in contrast to earlier works that have approached this problem using standard combinatorial optimization tools, we take a geometric approach. we define a riemannian manifold, arising from the difference in frequency response between the two systems of interest, on which we design efficient algorithms for sampling and approximation. this additional structure enables us to tame the computational complexity of the native combinatorial optimization problem. we illustrate the benefits of this approach with design examples involving iir and fir filters.
an efficient first-order method for l1 compression of images. we consider the problem of lossy compression of images using sparse representations from overcomplete dictionaries. this problem is in principle easy to solve using standard algorithms for convex programming, but often the large dimensions render such an approach intractable. we present a highly efficient method based on recently developed first-order methods, which enables us to compute sparse approximations of entire images with modest time and memory consumption.
periodically gapped data spectral velocity estimation in medical ultrasound using spatial and temporal dimensions. modern medical ultrasound scanners estimate blood velocity distribution by computing the spectrogram of a temporal data sequence, typically using periodogram methods which require long observation windows. furthermore, an additional b-mode image is often displayed, resulting in gaps in the data at b-mode emissions. we propose a data-adaptive velocity estimator for periodically gapped (pg) data that extends pg-capon and pg-apes by using two dimensional spatial and temporal data to estimate a one dimensional spectrum. we show through realistic flow simulations that our method improves spectral resolution and reduces leakage in comparison to pg-capon, pg-apes, and correlogram based gapped data velocity estimators, potentially increasing the maximum detectable velocity and temporal resolution of blood flow using ultrasound.
voice conversion using artificial neural networks. in this paper, we propose to use artificial neural networks (ann) for voice conversion. we have exploited the mapping abilities of ann to perform mapping of spectral features of a source speaker to that of a target speaker. a comparative study of voice conversion using ann and the state-of-the-art gaussian mixture model (gmm) is conducted. the results of voice conversion evaluated using subjective and objective measures confirm that anns perform better transformation than gmms and the quality of the transformed speech is intelligible and has the characteristics of the target speaker.
optimal gaussian fingeprint decoders. this paper proposes codes that achieve the fundamental capacity limits of digital fingerprinting subject to mean-squared distortion constraints on the fingerprint embedder and the colluders. we first show that the traditional method of fingerprint decoding by thresholding correlation statistics falls short of this goal: reliable performance is impossible at code rates greater than some value c1 that is strictly less than capacity. to bridge the gap to capacity, a more powerful decoding method is needed. the maximum penalized gaussian mutual information decoder presented here meets this requirement. finally, a mathematical framework and a capacity expression for fingerprinting of social networks are presented.
emotional speech recognition based on style estimation and adaptation with multiple-regression hmm. this paper proposes a technique for emotional speech recognition which enables us to extract paralinguistic information as well as linguistic information contained in speech signal. the technique is based on style estimation and style adaptation using multiple-regression hmm. recognition process consists of two stages. in the first stage, a style vector that represents the emotional expression category and intensity of its variation of input speech is estimated on a sentence-by-sentence basis. then the acoustic models are adapted using the estimated style vector and standard hmm-based speech recognition is performed in the second stage. we assess the performance of the proposed technique on the recognition of acted emotional speech uttered by both professional narrators and non-professional speakers and show the effectiveness of the technique.
distributed sensing of signals linked by sparse filtering. we consider the task of recovering correlated vectors at a central decoder based on fixed linear measurements obtained by distributed sensors. a general formulation of the problem is proposed, under both a universal and an almost sure reconstruction requirement. we then study a specific correlation model which involves a filter that is sparse in the time domain. while this sparsity assumption does not allow reducing the description cost in the universal case, we show that large gains can be achieved in the almost sure scenario by means of a novel distributed scheme based on annihilating filters. the robustness of the proposed method is also investigated.
fft-based estimation of large motions in images: a robust gradient-based approach. a fast and robust gradient-based motion estimation technique which operates in the frequency domain is presented. the algorithm combines the natural advantages of a good feature selection offered by gradient-based methods with the robustness and speed provided by fft-based correlation schemes. experimentation with real images taken from a popular database showed that, unlike any other fourier-based techniques, the method was able to estimate translations, arbitrary rotations and scale factors in the range 4–6.
exploiting user feedback for language model adaptation in meeting recognition. we investigate languagemodel (lm) adaptation in a meeting recognition application, where the lm is adapted based on recognition output from relevant prior meetings and partial manual corrections. unlike previous work, which has considered either completely unsupervised or supervised adaptation, we investigate a scenario where a human (e.g., a meeting participant) can correct some of the recognition mistakes. we find that recognition accuracy using the adapted lm can be enhanced substantially by partial correction. in particular, if all content words (about half of all recognition errors) are corrected, recognition improves to the same accuracy as if completely error-free (manually created) transcriptions had been used for adaptation. we also compare and combine a variety of adaptation methods, including linear interpolation, unigram marginal adaptation, and a discriminative method based on “positive” and “negative” n-grams.
ifly system for the nist 2008 speaker recognition evaluation. the description of ifly system submitted for nist 2008 speaker recognition evaluation (sre), which has achieved excellent performance in the 2008 sre evaluation, is presented in this paper. our primary system is a fusion of two subsystems gmm-ubm and gmm-svm. for each sub-system, two kinds of short-time acoustic features plp and lpcc are adopted. we focus on three key issues in this evaluation: channel compensation, multi-lingual or bi-lingual cues and the voice activity detection. we also point out that data selection and factor analysis play key roles in the system improvement.
efficient subword lattice retrieval for german spoken term detection. we present a lattice-based std method for german broadcast news data and compare it to a previously proposed fuzzy search. due to the important out-of-vocabulary (oov) problem in german, we evaluate suitable subword indexing units for lattice retrieval. hybrid lattice retrieval of words and subwords is investigated because of the robust nature of words as an indexing unit. we show that by using efficient lattice graph and score pruning techniques, precision of subword retrieval is increased by 8% absolute with only a small loss in recall. additionally, a speed-up of up to 6 times can be observed.
higher order teager-kaiser operators for image analysis: part i - a monocomponent image demodulation. we present in this paper a new narrowband image demodulation method. our approach is based on the 2d higher order teager-kaiser operators (hotko). we show that the introduction of higher orders in the teager-kaiser operator, improves a lot the demodulation results, in comparison to the discrete energy separation algorithm (desa) and the analytic image (ai) method. more precisely, for synthetic images, we show that the approximation errors on both the amplitude and the frequency components are much more lower with our proposed demodulation method than the desa and the ai method. moreover, it turns out that for the presented real images, the algorithm is so efficient, especially the amplitude counterpart, that it tracks the most important parts in images, and segments the regions of interest. we show how the algorithm could be used in sonar images for extracting mines'shadows, which is very important for both military and civil applications.
connectivity similarity based transductive learning for interactive image segmentation. we propose a novel graph-based transductive learning approach for interactive image segmentation. here the term “transductive” indicates a process that iteratively propagates information from user-labeled regions to unlabeled image pixels. for the application of interactive image segmentation, transductive approach has several advantages compared with traditional color probabilistic model based approach. however, previous transductive approaches for image segmentation usually utilize an 8-connected neighborhood system, which has low efficacy when transferring local information to remote pixels. the main contribution of this paper is to estimate pairwise pixel similarity based on a novel path-based metric (i.e. connectivity similarity), rather than local comparison with 8-connected neighbors. we further theoretically prove the computing complexity is on a polynomial order and provide convergence guarantee for the extra local smoothing operation that is introduced to further refine the initial results. especially, the proposed method shows promising performance in the multi-label case. various experiments are presented to illustrate its effectiveness.
space-time-range three dimensional adaptive processing. space-time adaptive processing (stap) is an effective tool for moving target detection. conventional stap methodologies process the angular and doppler two dimensional data vector. in practical applications, adjacent range cells are statistically dependent due to filtering, since the point spreading function of a target is not an ideal delta function. in this paper, a novel approach incorporating range (fast time) information in stap is presented for clutter rejection, which we term space-time-range adaptive processing (strap). this method takes advantage of the correlation information of neighboring range cells. therefore, the stationary clutter can be suppressed better compared with traditional stap algorithms ignoring fast time information, resulting in more effective moving target detection. the validity of the strap algorithm is verified by the experiments of processing the real measured data of the three-channel x-band radar and mcarm radar systems.
robust modeling of musical chord sequences using probabilistic n-grams. the modeling of music as a language is a core issue for a wide range of applications such as polyphonic music retrieval, automatic style identification, audio to symbolic music transcription and computer-assisted composition. in this paper, we focus on the modeling of chord sequences by probabilistic n-grams. previous studies using these models have achieved limited success, due to overfitting and to the use of a single chord labeling scheme. we investigate these issues using model smoothing and selection techniques initially designed for spoken language modeling. this approach is evaluated over a set of songs by the beatles, considering several chord labeling schemes. initial results show that the accuracy of n-grams is increased but that additional improvements may still be achieved in the future using more advanced, possibly music-specific, smoothing techniques.
language model parameter estimation using user transcriptions. in limited data domains, many effective language modeling techniques construct models with parameters to be estimated on an in-domain development set. however, in some domains, no such data exist beyond the unlabeled test corpus. in this work, we explore the iterative use of the recognition hypotheses for unsupervised parameter estimation. we also evaluate the effectiveness of supervised adaptation using varying amounts of user-provided transcripts of utterances selected via multiple strategies. while unsupervised adaptation obtains 80% of the potential error reductions, it is outperformed by using only 300 words of user transcription. by transcribing the lowest confidence utterances first, we further obtain an effective word error rate reduction of 0.6%.
voice transformation: a survey. voice transformation refers to the various modifications one may apply to the sound produced by a person, speaking or singing. voice transformation is usually seen as an add-on or an external system in speech synthesis systems since it may create virtual voices in a simple and flexible way. in this paper we review the state-of-the-art voice transformation methodology showing its limitations in producing good speech quality and its current challenges. addressing quality issues of current voice transformation algorithms in conjunction with properties of the speech production and speech perception systems we try to pave the way for more natural voice transformation algorithms in the future. facing the challenges, will allow voice transformation systems to be applied in important and versatile areas of speech technology; applications that are far beyond speech synthesis. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
action recognition in unconstrained amateur videos. in this paper, we propose a systematic framework for action recognition in unconstrained amateur videos. inspired by the success of local features used in object and pose recognition, we extract local static features from the sampled frames to capture local pose shape and appearance. in addition, we extract spatiotemporal features (st features), which have been successfully used in action recognition, to capture the local motions. in the action recognition phase, we use the pyramid match kernel based on weighted similarities of multi-resolution histograms to match two videos within the same feature types. in order to handle complementary but heterogeneous features, i.e., static and motion features, we chose a multi-kernel classifier for feature fusion. to reduce the noise introduced by the background clutter, our system also tries to automatically find the rough region of interest/action. preliminary tests on the kth action dataset, ucf sports dataset, and a youtube action dataset have shown promising results.
frame-level temporal calibration of unsynchronized cameras by using longest consecutive common subsequence. we present a computationally efficient and robust method for temporally calibrating video sequences from unsynchronized cameras by using object trajectories. existing methods remain restricted in terms of their assumptions, and/or they are computationally expensive. to match and align the object trajectories, and thus to recover the frame offset between video sequences, we present an algorithm that is based on the longest consecutive common subsequence. the candidate frame offsets are obtained from each matched trajectory pair, and then a confidence check is performed. the algorithm is robust against possible errors due to background subtraction and location extraction, and can handle large frame offsets. we present experimental results for different frame offset values on different video sequences, which show the robustness of the algorithm in recovering the frame offsets. we also compare the presented algorithm with our previous work to demonstrate the computational efficiency provided.
a nonparametric test for stationarity based on local fourier analysis. in this paper we propose a nonparametric hypothesis test for stationarity based on local fourier analysis. we employ a test statistic that measures the variation of time-localized estimates of the power spectral density of an observed random process. for the case of a white gaussian noise process, we characterize the asymptotic distribution of this statistic under the null hypothesis of stationarity, and use it to directly set test thresholds corresponding to constant false alarm rates. for other cases, we introduce a simple procedure to simulate from the null distribution of interest. after validating the procedure on synthetic examples, we demonstrate one potential use for the test as a method of obtaining a signal-adaptive means of local fourier analysis and corresponding signal enhancement scheme.
detection from a multi-channel sensor using a hierarchical bayesian model. direct imaging of exoplanets involves very low signal-to-noise ratio data, that need to be carefully acquired and processed. multi-band devices enable the simultaneous record of images in different spectral bands. they can be used either for spectroscopy purposes or to improve detection capabilities.
approximating 3d shape using bezier surface. estimating 3d shape of the object is an important research topic in the area of computer vision, with a wide range of applications. this paper introduces a new method for focused-based passive methods (like sff) to approximate the 3d shape of the object using bezier surface. the discrete nature of image sampling results in the loss of information between two consecutive images. conventional approximation methods optimize or interpolate focus values. we have suggested interpolating depth values instead of focus value over a small patch on the object surface. the method approximates the surface more accurately and also reduces any noise caused by focus measure. the proposed method is tested and analyzed to demonstrate the effectiveness against traditional methods.
training-based bayesian mimo channel and channel norm estimation. training-based estimation of channel state information in multi-antenna systems is analyzed herein. closed-form expressions for the general bayesian minimum mean square error (mmse) estimators of the channel matrix and the squared channel norm are derived in a rayleigh fading environment with known statistics at the receiver side. when the second-order channel statistics are available also at the transmitter, this information can be exploited in the training sequence design to improve the performance. herein, mean square error (mse) minimizing training sequences are considered. the structure of the general solution is developed, with explicit expressions at high and low snrs and in the special case of uncorrelated receive antennas. the optimal length of the training sequence is equal or smaller than the number of transmit antennas.
extracting regions of attention by imitating the human visual system. detecting and segmenting out the regions of interest (rois) is one of the foundations in image processing and analysis. because the final information sink of images is human, for segmenting out the rois effectively, we need to study human visual system (hvs) and imitate the behaviors when human viewing a scene. researchers have found several factors which affect human attentions by studying eye movements when one views an image. in this paper, a method is proposed to detect the rois automatically based on hvs. in the proposed algorithm, the properties of pixels such as the contrast, location and edges are analyzed, and the pixels are enhanced according to the sensitivity of hvs. then these factors are combined to a salient map, which classifies each pixel of the image in relation to its perceptual importance. finally, the rois are segmented according to the salient map. this algorithm is easy to work, and can segment the objects from complex background efficiently.
improved design of two and four-group decodable stbcs with larger diversity product for eight transmit antennas. recently, full rate and full diversity two-group (2gp) and four-group (4gp) decodable space-time block codes (stbc) derived from quasi-orthogonal stbc (qstbc) and designed under diversity product maximization criterion have been proposed. in this paper, we derive an upper bound of diversity product for those stbcs and discover that the diversity product of the current 2gp-qstbc and 4gp-qstbc has the potential to approach the upper bound for 8 transmit antennas. to this end, we propose an improved design of 2gp and 4gp stbc with increased diversity product for 8 transmit antennas by allowing sufficient number of dimensions for constellation rotation. the diversity product of the proposed two-group decodable stbc achieves the derived upper bound.
real-time speech enhancement in noisy reverberant multi-talker environments based on a location-independent room acoustics model. this paper describes a new real-time speech enhancement method that reduces signal distortion caused by stationary noise and late reflections of reverberation in speech signals captured by a single distant microphone under multi-talker conditions. a major problem here is how to estimate the energy of the late reflections in real time when the room impulse responses from individual talkers to the microphone are not given or fixed in advance. to solve this problem, we introduce a probabilistic room acoustics model, and provide a method for estimating the energy of late reflections based on this model. in this method, parameters of the model for a room can be fixed in advance only from a few seconds of observation. by incorporating the proposed approach into a conventional frequency domain noise reduction scheme, we realize an integrated real-time speech enhancement framework. the effectiveness of the proposed method is confirmed experimentally for a case where there are two talkers in a room.
bounds on distributed tdoa-based localization of ofdm sources. one main drawback of using time difference of arrival (tdoa) methods for source localization and navigation is that they require centralization of multiple copies of a signal. this paper considers blindly estimating the location of a cyclic prefix (cp) in an orthogonal frequency division multiplexing (ofdm) signal, enabling distributed tdoa computation up to an integer ambiguity. this ambiguity can be resolved using integer least-squares methods, if enough tdoas are available. the contributions of this paper are derivation of the cramer-rao lower bound (crlb) on locating the cp, and hence on the underlying source localization problem.
sinr distribution for lte downlink multiuser mimo systems. the lte downlink multiuser multiple input multiple output (mimo) systems are analyzed in this paper. two spatial division multiplexing (sdm) multiuser mimo schemes are investigated: single user (su) and multi-user (mu) mimo schemes. the main contribution of this paper is the establishment of a mathematical model for the signal to interference plus noise ratio (sinr) distribution for multiuser sdm mimo systems with frequency domain packet scheduler.
robust mobile terminal tracking in nlos environments using interacting multiple model algorithm. an extended kalman filter-based interacting multiple model algorithm (imm-ekf) is proposed for mobile terminal tracking in cellular networks based on time of arrival estimates. the proposed imm-ekf is able to cope with line-of-sight (los) and non-line-of-sight (nlos) conditions modeled by a markov chain, where the los and nlos errors are described by different noise models. road-constraints are included into the imm-ekf to improve performance. simulation results show that the imm-ekf outperforms conventional methods. a comparison to the posterior cramér-rao lower bound is given to demonstrate the effectiveness of the imm-ekf.
document reconstruction using dynamic programming. in this work we propose a methodology for document reconstruction based on dynamic programming and a modified version of the prim's algorithm. firstly, we use polygonal approximation to reduce the complexity of the boundaries and extract features from them. thereafter, these features are used to feed the lcs dynamic programming algorithm. the scores yielded by the lcs algorithm are then used into a modified prim's algorithm to find the best match among all pieces. comprehensive experiments on a database composed of 100 shredded documents support the efficiency of the proposed methodology. when compared to global search algorithms, this approach brings an improvement of 18% in the number of fragments reconstructed.
estimating multiple transmitter locations from power measurements at multiple receivers. we consider the estimation of the locations of multiple transmitters based on received signal strength measurements at a network of randomly-placed receivers. we generalize the expectation-maximization (em) method to create a quasi em algorithm for localization under lognormal shadowing. simulated performance is compared to a state-of-the-art global optimizer and to random guessing. results reveal that the proposed quasi em algorithm outperforms both alternatives in median and ninety-fifth percentile error, especially as the number of receivers increases.
fingerprint matching based on distance metric learning. this paper considers a method for learning a distance metric in a fingerprinting system which identifies a query content by measuring the distance between its fingerprint and a fingerprint stored in a database. a metric having a general form of the mahalanobis distance is learned with the goal that the distance between fingerprints extracted from perceptually similar contents should be smaller than the distance between fingerprints extracted from perceptually dissimilar contents. the metric is learned by minimizing a cost function designed to achieve the goal. the cost function is convex, and the global minimum can be obtained using convex optimization. in our experiment, the distance metric learning is applied in an audio fingerprinting system, and it is experimentally shown that the learned distance metric improves the identification performance.
multi-dimensional space-time-frequency component analysis of event related eeg data using closed-form parafac. the efficient analysis of electroencephalographic (eeg) data is a long standing problem in neuroscience, which has regained new interest due to the possibilities of multidimensional signal processing. we analyze event related multi-channel eeg recordings on the basis of the time-varying spectrum for each channel. it is a common approach to use wavelet transformations for the time-frequency analysis (tfa) of the data. to identify the signal components we decompose the data into time-frequency-space atoms using parallel factor (parafac) analysis. in this paper we show that a tfa based on the wigner-ville distribution together with the recently developed closed-form parafac algorithm enhance the separability of the signal components. this renders it an attractive approach for processing eeg data. additionally, we introduce the new concept of component amplitudes, which resolve the scaling ambiguity in the parafac model and can be used to judge the relevance of the individual components.
geometric distortion signatures for printer identification. we present a forensic technique for analyzing a printed image in order to trace the originating printer. our method, which is applicable for commonly used electrophotographic (ep) printers, operates by exploiting the geometric distortion that these devices inevitably introduce in the printing process. in the proposed method, first a geometric distortion signature is estimated for an ep printer. this estimate is obtained using only the images printed on the printer and without access to the internal printer controls. once a database of printer signatures is available, the printer utilized to print a test image is identified by computing the geometric distortion signature from test image and correlating the computes signatures against the printer signatures in the database. experiments conducted over a corpus of ep printers demonstrate that the geometric distortion signatures of test documents exhibit high correlation with the corresponding printer signatures and a low correlation with other printer signatures. the method is therefore quite promising for forensic printer identification applications. we highlight several of the capabilities and challenges for the method.
real-time pda-based recursive fourier transform implementation for cochlear implant applications. this paper presents a real-time and interactive implementation of the recursive fourier transform approach on pda platforms for cochlear implant signal processing applications. pda platforms provide a cost-effective and portable platform for cochlear implant studies. the computational complexities of the two commonly used signal processing strategies that are being used in commercial cochlear implants are compared. a more computationally efficient approach using recursive fourier transform is discussed and a real-time implementation of this approach is then accomplished on a pda platform. different versions of the implementation are examined and compared in terms of speed and accuracy.
frequency invariant mvdr beamforming without filters and implementation using mimo radar. frequency invariant beamforming with sensor arrays is generally achieved using filters in the form of tapped delay-lines following each sensor. however it has been recently shown that with the help of the rectangular smart antenna array, it is possible to generate frequency invariant beampattern without using filters. in this paper, this frequency invariant beamforming technique is utilized to perform mvdr beamforming in the beamspace by designing frequency invariant beams spanning the desired range of azimuthal angles and optimally combining them. however the performance of the frequency invariant beamformer depends on the number of sensors which could be large for a rectangular array of size m × n. making use of the virtual array concept used in mimo radar, a novel method of producing the same frequency invariant beam, using only m transmitting and n receiving antennas, is proposed and a design example is provided to demonstrate the idea.
exploiting multiple shift invariances in harmonic retrieval. a novel algorithm for estimating multi-dimensional damped harmonics is proposed. a matrix polynomial is formed from the weighed sum of multiple shift invariances contained in the data model. necessary and sufficient conditions are derived that reveal that the damped harmonics can be uniquely determined from the roots of the matrix polynomial. the proposed algorithm reveal a seamless link between two important classes of search free subspace methods. the classical rooting based harmonic estimation methods that exploit the complete invariance structure and the single invariance esprit algorithms. we show that both approaches can be expressed under this general framework by an appropriate choice of the weights. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
does canonical correlation analysis provide reliable information on data correlation in array processing? this work provides analytical results on the canonical correlation analysis (cca) of data sets from two spatially separated arrays of sensors. our case studies cover both single source and multiple source signals in either white or colored noise fields for array signal processing. we derive analytical expressions of the canonical correlation for these examples and present a computer simulation analysis of empirical canonical correlations as a function of nominal correlation, signal-to-noise ratio (snr), and sample support. results obtained reveal an interesting fact that the canonical coefficients from cca provide reliable information on the spatial correlation existing among data sets from two arrays only when the snrs at both arrays are reasonably high. when sample correlation matrices (scm) are used in the empirical cca, reliable correlation can be estimated from cca asymptotically (either at high snrs from both arrays, or with a large number of snapshots in comparison with array dimensionality).
a speech fragment approach to localising multiple speakers in reverberant environments. sound source localisation cues are severely degraded when multiple acoustic sources are active in the presence of reverberation. we present a binaural system for localising simultaneous speakers which exploits the fact that in a speech mixture there exist spectro-temporal regions or ‘fragments’, where the energy is dominated by just one of the speakers. a fragment-level localisation model is proposed that integrates the localisation cues within a fragment using a weighted mean. the weights are based on local estimates of the degree of reverberation in a given spectro-temporal cell. the paper investigates different weight estimation approaches based variously on, i) an established model of the perceptual precedence effect; ii) a measure of interaural coherence between the left and right ear signals; iii) a data-driven approach trained in matched acoustic conditions. experiments with reverberant binaural data with two simultaneous speakers show appropriate weighting can improve frame-based localisation performance by up to 24%.
light-weight salient foreground detection with adaptive memory requirement. designing algorithms, which require less memory and consume less power, is very important for the portability to embedded smart cameras, which have limited resources. we present a light-weight and efficient algorithm for salient foreground detection that is highly robust against lighting variations and non-static backgrounds such as scenes with swaying trees. contrary to traditional methods, memory requirement for the data saved for each pixel is very small in the proposed algorithm. moreover, the total memory requirement is adaptive, and is decreased even more depending on the amount of activity in the scene. as opposed to existing methods, we treat each pixel differently based on its history. instead of requiring the same amount of memory for every pixel, we allocate less memory for stable background pixels. the plot of the required memory at each frame also serves as a tool to find the video portions with high activity.
stochastic modeling of vehicle trajectory during lane-changing. a signal processing approach for modeling vehicle trajectory during lane changing driving is discussed. because individual driving habits are not a deterministic process, we developed a stochastic method. the proposed model consists of two parts: a dynamic system represented by a hidden markov model and a cognitive distance space derived from the range distance distribution. the first part models the local dynamics of vehicular movements and generates a set of probable trajectories. the second part selects an optimal trajectory by stochastically evaluating the distances from surrounding vehicles. from experimental evaluation, we show that the model can predict the vehicle trajectory at given traffic conditions with 17.6 m prediction error for two different drivers.
co-adaptation: adaptive co-training for semi-supervised learning. inspired by popular co-training and domain adaptation methods, we propose a co-adaptation algorithm. the goal is improving the performance of a dialog act segmentation model by exploiting the vast amount of unlabeled data. this task provides a nice framework for multiview learning, as it has been shown that lexical and prosodic features provide complementary information. instead of simply adding machine-labeled data to the set of manually labeled data, co-adaptation technique adapts the existing models. while both co-training and domain adaptation techniques have been employed for dialog act segmentation, our experiments show that the proposed co-adaptation algorithm results in significantly better performance.
resampling auxiliary data for language model adaptation in machine translation for speech. performance of n-gram language models depends to a large extent on the amount of training text material available for building the models and the degree to which this text matches the domain of interest. the language modeling community is showing a growing interest in using large collections of auxiliary textual material to supplement sparse in-domain resources. one of the problems in using such auxiliary corpora is that they may differ significantly from the specific nature of the domain of interest. in this paper, we propose three different methods for adapting language models for a speech to speech (s2s) translation system when auxiliary corpora are of different genre and domain. the proposed methods are based on centroid similarity, n-gram ratios and resampled language models. we show how these methods can be used to select out of domain textual data such as newswire text to improve a s2s system. we were able to achieve an overall relative improvement of 3.8% in bleu score over a baseline system that uses only in-domain conversational data.
joint uncertainty decoding with the second order approximation for noise robust speech recognition. joint uncertainty decoding has recently achieved promising results by integrating the front-end uncertainty into the back-end in a mathematically consistent framework. in this paper, joint uncertainty decoding is compared with the widely used vector taylor series (vts). we show that the two methods are identical except that joint uncertainty decoding applies the taylor expansion on each regression class whereas vts applies it to each hmm mixture. the relatively rougher expansion points used in joint uncertainty decoding make it computationally cheaper than vts but inevitably worse on recognition accuracy. to overcome this drawback, this paper proposes an improved joint uncertainty decoding algorithm which employs second-order taylor expansion on each regression class in order to reduce the expansion errors. special considerations are further given to limit the overall computational cost by adopting different number of regression classes for different orders in the taylor expansion. experiments on the aurora 2 database show that the proposed method is able to beat vts on recognition accuracy and computational cost with relative improvement up to 6% and 60%, respectively.
joint watermarking and compression for gaussian and laplacian sources using uniform vector quantization. using fixed rate uniform vector quantization, in this paper, we consider how to design a joint watermarking and compression (jwc) system for gaussian and laplacian sources to maximize the robustness in the presence of additive gaussian attacks under constraints on the compression rate and quantization distortion. firstly, we construct vector quantizers shaped to match the multidimensional distribution of source signals. then we scale codebooks corresponding to the vector quantizers to maximize the robustness of the watermarks against the additive gaussian attacks. simulation results show that the proposed scheme can achieve up to 0.92 db distortion-to-noise ratio (dnr) gain over jwc schemes using uniform scalar quantization while maintaining the simplicity of implementation with uniform quantization.
incorporating spectral subtraction and noise type for unvoiced speech segregation. unvoiced speech poses a big challenge to current monaural speech segregation systems. it lacks harmonic structure and is highly susceptible to interference due to its relatively weak energy. this paper describes a new approach to segregate unvoiced speech from nonspeech interference. the system first estimates a voiced binary mask, and then performs unvoiced speech segregation in two stages: segmentation and grouping. in segmentation, time-frequency units labeled as 0 in the voiced binary mask are first used to estimate the noise energy and spectral subtraction is then performed to generate time-frequency segments in unvoiced intervals. based on the type of noise, unvoiced segments are grouped either by selecting segments consistent with those generated by onset/offset analysis or by bayesian classification of acoustic-phonetic features. systematic evaluation and comparison show that the proposed approach improves the performance of unvoiced speech segregation considerably.
training and adapting mlp features for arabic speech recognition. features derived from multi-layer perceptrons (mlps) are becoming increasingly popular for speech recognition. this paper describes various schemes for applying these features to state-of-the-art arabic speech recognition: the use of mlp-features for short-vowel modelling in graphemic systems; rapid discriminative model training by standard plp feature lattice re-use; and mlp feature adaptation using linear input networks (lin). the use of rapid training using mlp features and their use for short-vowel modelling and lin adaptation gave reductions in word error rate. however significant improvements over explicit short-vowel modelling with standard multi-pass adaptation were not obtained, although they were useful in combination.
blind monte carlo detection-estimation method for optical coherence tomography. we consider the parametric analysis of frequency-domain optical coherence tomography (oct) signals. a monte carlo (gibbs sampler) detection-estimation method for determining the depths and reflection coefficients of tissue interfaces (reflective sites in the tissue) is proposed. our method is blind since it estimates the instrumentation-dependent “fringe” function along with the tissue parameters. sparsity of the detected interfaces is enforced by an impulse detector and a modified bernoulli-gaussian prior with a minimum distance constraint. numerical results using synthetic and real signals demonstrate the excellent performance and fast convergence of our method.
marginalized population monte carlo. population monte carlo is a statistical method that is used for generation of samples approximately from a target distribution. the method is iterative in nature and is based on the principle of importance sampling. in this paper, we show that in problems where some of the parameters are conditionally linear on the remaining parameters, we can improve the computational efficiency of population monte carlo by generating samples of the nonlinear parameters only and marginalizing the linear parameters. we demonstrate the marginalized population monte carlo on the problem of frequency estimation of closely spaced sinusoids.
optimized non-uniform fast fourier transform (nufft) for iterative tomographic reconstruction. the main focus of this paper is the efficient approximation of the non-uniform fourier transform (nufft). we reformulate the standard nufft approximation as a projection of the exact discrete fourier transform onto a shift-invariant space. this reformulation enables the use of sophisticated tools, developed in the context of shift-invariant representations, to analyze the performance of the approximation. using these techniques, we derive the optimal scale factors for a specified interpolator. assuming these scale factors, we develop a worst-case error criterion that is only dependent on the interpolating function. we propose an iterative re-weighted optimization algorithm to derive the optimized least square (ols) interpolator. this interpolator significantly reduces the approximation error in comparison to the standard methods. the improved performance of this scheme, for low oversampling factors, could lead to a memory efficient algorithm for non-cartesian fourier inversion.
mpeg-4 scalable lossless audio transparent bitrate and its application. in this paper, the relevance between the bit-plane levels and the perceptual quality of the mpeg-4 scalable lossless audio is explored. it is observed that only the top 3 bit-planes in sls with aac core of 64kbps are closely related to the transparent quality. the result is used in the application of the data hiding process. the proposed hiding method has low complexity as no side information is required at the data extraction process. a data hiding capacity of 98kbps is achieved for sls lossless bitstream.
acoustic holography with a concentric rigid and open spherical microphone array. we present a new method and performance data related to volumetric acoustic intensity imaging using a spherical microphone array (sma) consisting of a dual, concentric rigid and open sma. the dual, concentric array was designed to improve the frequency range of a standard sma. we apply standard techniques associated with interior spherical near-field acoustic holography (nah) and, in particular, consider issues related to the optimal use of information from both arrays for nah projection and the advantages that thus accrue from utilising a dual, concentric sma.
low power embedded speech recognition system based on a mcu and a coprocessor. in speech recognition systems, chmm (continuous hidden markov model) based speech recognition algorithms have the best accuracy but with the most computational cost. neither general purpose processor (gpp) nor dedicated hardware implementation is a good solution for the algorithm, due to high power consumption for the former and lack of flexibility for the later. to reduce power consumption and enhance flexibility, this paper presents a speech recognition system composed of a coprocessor and a mcu. the coprocessor is a dedicated hardware design for output probability calculation (opc), which is the most computation-intensive part in chmm, and mcu is a 32bit risc (arm). tested with a 358-state 3-mixture 27-feature 800-word hmm, mcu operates at 40mhz and coprocessor operates at 10mhz to meet real-time requirement. the power consumption of mcu is 10mw, and coprocessor 1.8mw.
a new approach for modelling the dynamic feedback path of digital hearing aids. this paper proposes a reflection model for the dynamic feedback path of digital hearing aids and compares it with two existing models: a direct model and an initialization model, based on the measured dynamic feedback paths. the comparison shows that the proposed model is superior to the existing two models in terms of maximum stable gain (msg). for hearing aids with dual microphones, the possibility of relating the two dynamic feedback paths is also investigated. it is shown that in a complicated acoustic environment, the relation between the two feedback paths can be very intricate and difficult to exploit in modelling the dynamic feedback paths.
rls-weighted lasso for adaptive estimation of sparse signals. the batch least-absolute shrinkage and selection operator (lasso) has well-documented merits for estimating sparse signals of interest emerging in various applications, where observations adhere to parsimonious linear regression models. to cope with linearly growing complexity and memory requirements that batch lasso estimators face when processing observations sequentially, the present paper develops a recursive lasso algorithm that can also track slowly-varying sparse signals of interest. performance analysis reveals that recursive lasso can either estimate consistently the sparse signal's support or its nonzero entries, but not both. this motivates the development of a weighted version of the recursive lasso scheme with weights obtained from the recursive least-squares (rls) algorithm. the resultant rls-weighted lasso algorithm provably estimates sparse signals consistently. simulated tests compare competing alternatives and corroborate the performance of the novel algorithms in estimating time-invariant and tracking slow-varying signals under sparsity constraints.
bounded conditional mean imputation with gaussian mixture models: a reconstruction approach to partly occluded features. in this work we show how conditional mean imputation can be bounded through the use of box-truncated gaussian distributions. that is of interest when signals or features are partly occluded by a superimposed interference, as then the noisy observation poses an upper bound. unfortunately, the occurring integrals are not analytic. hence an approximate solution has to be used. in the experimental section we apply the bounded approach to the reconstruction of partly occluded speech spectra and demonstrate its superiority over the unbounded case with respect to automatic speech recognition performance.
recent advances in sri's iraqcomm iraqi arabic-english speech-to-speech translation system. we summarize recent progress on sri's iraqcomm™ iraqi arabic-english two-way speech-to-speech translation system. in the past year we made substantial developments in our speech recognition and machine translation technology, leading to significant improvements in both accuracy and speed of the iraqcomm system. on the 2008 nist-evaluation dataset our twoway speech-to-text (s2t) system achieved 6% to 8% absolute improvement in bleu in both directions, compared to our previous year system [1].
pilot design for multi-user mimo. in this paper, challenges regarding the provision of channel state information (csi) on a multi-user (mu) mimo-ofdm downlink are addressed. reference symbols (pilots) support coherent detection at the receiver and enable link adaptation at the transmitter, but add overhead and consume transmit power. as spatial transmit processing combined with multiple access essentially requires the provision of dedicated and common pilots, i.e. pilots that include respectively exclude user-specific transmit processing, the potential gains of mu-mimo may partly be canceled by the incurred pilot overhead. fortunately, spatial correlation at the transmitter has the potential to substantially reduce overheads, by introducing spatial reuse of dedicated pilots, and by utilizing spatial interpolation of common pilots. we demonstrate that a reduction in overhead is traded with compromised channel estimation accuracy, which particularly limits the attainable spectral efficiency in the high snr regime. this implies that a bandwidth efficient pilot design is to be complemented by advanced channel estimation schemes, which enhance accuracy by utilizing data symbols together with pilots.
source adaptive blind signal extraction using closed-form ica for hands-free robot spoken dialogue system. in this paper, we propose a new ica-based bss algorithm including estimation of sources' probability density functions (pdfs) to adapt the nonlinear activation function to various noise conditions. in the proposed method, closed-form second-order ica is introduced as a computational-cost-efficient preprocessing to extract sources' pdfs, which is beneficial for real-time application. compared with various type of conventional icas, e.g., fixed activation-function type and ml-based type, our proposed algorithm can give a faster and higher convergence. based on the proposed source-adaptive ica, we show a real-time noise reduction results under diffuse noise environment. also we can demonstrate our recently developed hands-free robot spoken dialogue system via real-time ica.
dynamic updating and downdating matrix svd and tensor hosvd for adaptive indexing and retrieval of motion trajectories. motion information is regarded as one of the most important cues for developing semantics in video data. yet it is extremely challenging to build indexing and browsing tools for video data, particularly when it involves interactive motions of multiple objects. the problem is further complicated when the video archives are dynamically updated, and/or queries contains partial information. an efficient solution would require that the feature space used to represent the data be dynamically updated or downdated to allow frequent additions/deletions and matching of queries. assuming tensor hosvd as the feature space, in this paper, we propose two novel algorithms, namely, dynamic tensor hosvd updating algorithm (dtsv d+) and dynamic tensor hosvd downdating algorithm (dtsv d−), for dynamically updating and downdating existing tensor hosvd, without recalculating it from the raw data. the proposed algorithms are robustly applied to both full and partial multiple motion trajectories events with varying number of objects, trajectory lengths, and sampling rates. simulations on real-world multiple motion trajectories data demonstrate the robustness and accuracy of the proposed algorithms.
maximum margin linear kernel optimization for speaker verification. this paper describes a novel approach for discriminative modeling and its application to automatic text-independent speaker verification. this approach maximizes the margin between the model scores for pairs of utterances belonging to the same speaker and for pairs of utterances belonging to different speakers. a low-dimensional linear kernel is estimated which maximizes this margin. this approach emphasizes features which have a better ability to discriminate between scores belonging to pairs of utterances of the same target speakers and those of different speakers. in this paper, we apply this approach to the nist 2005 speaker verification task. compared to the gaussian mixture model (gmm) baseline system, a 17.7% relative improvement in the minimum detection cost function (dcf) and a 11.7% relative improvement in equal error rate (eer) are obtained. we achieve also a 5.7% relative improvement in eer and 2.3% relative improvement in dcf by using our approach on top of a nuisance attribute projection (nap) compensated gmmbased kernel baseline system.
application of characteristic function to detection in sinusoidal interference plus gaussian noise. in this work, a detector scheme for the detection of signal in a group of non-gaussian narrowband interferences and white gaussian noise is developed. since there exists no closed-form probability distribution for this type of disturbance modeling, the key innovation lies in the use of characteristic function rather than the probability distribution to both design and implement the detector. parameter estimation is performed at first step to find the unknown disturbance parameters. the utilized detector uses these parameters to form an approximately gaussian distributed test statistic based on the empirical characteristic function of received data. performance of the detector is investigated by means of both analytical and monte carlo simulations.
improved morphological decomposition for arabic broadcast news transcription. in this paper, we show the progress for arabic speech recognition by incorporating contextual information into the process of morphological decomposition. the new approach achieves lower out-of-vocabulary and word error rates when compared to our previous work, in which the morphological decomposition relies on word-level information only. we also describe how the vocalization procedure is improved to produce pronunciations for some dialect arabic words. by using the new approach, we reduced the word error by 0.8% absolute (4.7% relative) when compared to the baseline approach.
exploiting prosodic information for speaker recognition. in this paper, we study speaker characterization using prosodic supervectors with negative within-class covariance normalization (nwccn) projection and speaker modeling with support vector regression (svr). we also propose a segmental weight fusion (swf) technique that combines acoustic and prosodic subsystems effectively, despite the big performance gap between the subsystems. we validate the effectiveness of our proposed techniques on the nist 2006 speaker recognition evaluation (sre) in comparison with other prominent solutions. the experiments have reported competitive results of 17.72% equal error rate for the prosodic subsystem alone and 4.50% for the fusion system on nist 2006 sre core test condition.
a noiseless code length method (nclm) to estimate dimensionality of hyperspectral data. hyperspectral image analysis has been subjected to many improvements made in past decade. yet the accurate estimation of dimensionality is still a challenge. since dimension estimation of the hyperspectral data is the first step in analysis of an image, the accuracy of analysis results highly depends on the accuracy of the dimension estimation step. mostly, existing methods isolate the process of dimension estimation and process of denoising which leads to an inaccurate estimation of constituent components in the signal. in this paper, the problem of estimating the dimensionality of hyperspectral data using the concept of “noiseless code length” is addressed. in our proposed method, nclm, a set of nested subsets including the hyperspectral data is generated first and then an error comparison approach is utilized by estimating the noiseless data error rather than noisy data error used by the existing methods to find the optimum subset. it has been shown that the estimated noiseless error has a minimum that represents the accurate estimation of the dimensionality of hyperspectral data. the comparison of nclm to other methods shows a substantial improvement in estimation of dimensionality in hyperspectral imagery.
multi-level diffusion adaptive networks. we study the problem of distributed estimation, where a set of nodes are required to collectively estimate some parameter of interest from their measurements. diffusion algorithms have been shown to achieve good performance, increased robustness and are amenable for real-time implementations. in this work we focus on multi-level diffusion algorithms, where a network running a diffusion algorithm is enhanced by adding special nodes that can perform different processing. these special nodes form a second network where a second diffusion algorithm is implemented. we illustrate the concept using diffusion lms, provide performance analysis for multi-level collaboration and present simulation results showing improved performance over conventional diffusion.
subband nonstationary noise reduction based on multichannel spatial prediction under reverberant environments. we propose a novel non-stationary and convolutive noise reduction method under reverberant environments. unlike many multichannel noise reduction methods, the proposed method does not need pre knowledge of impulse response or direction of arrival (doa) of the target source. the proposed method is composed of two processes. on the noise reduction process, the noise component is reduced without the impulse response of the target source. the target source component in the output signal is distorted, but the distortion is removed by the distortion-restoration process. importantly, possibility of complete noise reduction with no distortion based on the proposed framework is assured by mint theory. experimental results under the reverberant environment (rt60 ≈ 300 ms) show that the proposed method can reduce more noise than the conventional method and the distortion of the target source is not so big.
extraction of velocity fields for geophysical fluids from a sequence of images. we consider the assimilation of satellite images, within the framework of data assimilation in geophysical systems. based on the constant brightness assumption, we define a nonlinear functional measuring the difference between two consecutive images, the first one being transported to the second one by the unknown velocity. by considering a multi-scale approach and a gauss-newton minimization algorithm, we can estimate the entire velocity fields at a high frame rate and then assimilate these pseudo-observations.
a hardware-efficient implementation of the fast affine projection algorithm. this paper presents a high-throughput, low-latency, hardware-efficient fixed-point implementation of the fast affine projection (fap) algorithm. the proposed architecture utilizes reusable distributed arithmetic (rda) in combination with optimizations in the update process to enable the coefficients to be updated in a fixed number of cycles independent of filter length. fixed-point simulations show that the effect of replacing some of the multiplications with arithmetic shifts is minor, with rda-fap maintaining a faster convergence rate than nlms. the proposed design is also compared against a multiplier-based design in terms of number of computations and number of clock cycles needed for a single fap update cycle.
quantizer noise benefits in nonlinear signal detection with alpha-stable channel noise. two new theorems show how deliberately adding quantizer noise can improve statistical signal detection in array-based nonlinear correlation detection even in the case of infinite-variance α-stable channel noise. the first theorem gives a necessary and sufficient condition for such quantizer noise to increase the detection probability for a fixed false-alarm probability. the second theorem shows that the array must contain more than one quantizer for a stochastic-resonance noise benefit and that the noise benefit improves in the small-quantizer noise limit as the number of array quantizers increases. it further shows that symmetric uniform quantizer noise gives the optimal noise benefit among all symmetric scale-family noise types.
singing voice detection in music tracks using direct voice vibrato detection. in this paper we investigate the problem of locating singing voice in music tracks. as opposed to most existing methods for this task, we rely on the extraction of the characteristics specific to singing voice. in our approach we suppose that the singing voice is characterized by harmonicity, formants, vibrato and tremolo. in the present study we deal only with the vibrato and tremolo characteristics. for this, we first extract sinusoidal partials from the musical audio signal . the frequency modulation (vibrato) and amplitude modulation (tremolo) of each partial are then studied to determine if the partial corresponds to singing voice and hence the corresponding segment is supposed to contain singing voice. for this we estimate for each partial the rate (frequency of the modulations) and the extent (amplitude of modulation) of both vibrato and tremolo. a partial selection is then operated based on these values. a second criteria based on harmonicity is also introduced. based on this, each segment can be labelled as singing or non-singing. post-processing of the segmentation is then applied in order to remove short-duration segments. the proposed method is then evaluated on a large manually annotated test-set. the results of this evaluation are compared to the one obtained with a usual machine learning approach (mfcc and sfm modeling with gmm). the proposed method achieves very close results to the machine learning approach : 76.8% compared to 77.4% f-measure (frame classification). this result is very promising, since both approaches are orthogonal and can then be combined.
modelling the prepausal lengthening effect for speech recognition: a dynamic bayesian network approach. speech has a property that the speech unit preceding a speech pause tends to lengthen. this work presents the use of a dynamic bayesian network to model the prepausal lengthening effect for robust speech recognition. specifically, we introduce two distributions to model inter-state transitions in prepausal and non-prepausal words, respectively. the selection of the transition distributions depends on a random variable whose value is influenced by whether a pause will appear between the current and the following word. two experiments are presented here. the first one considers pauses hypothesised during speech decoding. the second one employs an extra component for speech/non-speech determination. by modelling the prepausal lengthening effect we achieve a 5.5% relative reduction in word error rate on the 500-word task of the svitchboard corpus.
a bayesian networks approach for dialog modeling: the fusion bn. bayesian networks, bns, are suitable for mixed-initiative dialog modeling allowing a more flexible and natural spoken interaction. this solution can be applied to identify the intention of the user considering the concepts extracted from the last utterance and the dialog context. subsequently, in order to make a correct decision regarding how the dialog should continue, unnecessary, missing, wrong, optional and required concepts have to be detected according to the inferred goals. this information is useful to properly drive the dialog prompting for missing concepts, clarifying for wrong concepts, ignoring unnecessary concepts and retrieving those required and optional. this paper presents a novel bns approach where a single bn is obtained from n goal-specific bns through a fusion process. the new fusion bn enables a single concept analysis which is more consistent with the whole dialog context.
time-varying opportunistic protocol for maximizing sensor networks lifetime. we consider transmission scheduling by medium access control (mac) protocols for energy limited wireless sensor networks (wsn) in order to maximize the network lifetime. time-varying opportunistic protocol (top) for maximizing the network lifetime is proposed. by executing top each sensor exploits local channel state information (csi) and local residual energy information (rei). top implements opportunistic strategy in terms of favoring sensors with better channels when the network is young, while less opportunistic and more conservative strategy in terms of prioritizing sensors with higher residual energy when the network is old. top significantly simplifies the implementation of carrier sensing as compared to other distributed mac protocols. simulation results show that top achieves significant performance gains over other distributed mac protocols.
segmentation of malaria parasites in peripheral blood smear images. detection of malaria parasites in stained blood smears is critical for treatment of the disease. automation of this process will help in reducing the time taken for diagnosis and the chance for human errors. however, the variability and artifacts in microscope images of blood samples pose significant challenges for accurate detection. a scheme based on hsv color space that segments red blood cells and parasites by detecting dominant hue range and by calculating optimal saturation thresholds is presented in this paper. methods that are less computation-intensive than existing approaches are proposed to remove artifacts. the scheme is evaluated using images taken from leishman-stained blood smears. sensitivity and specificity of the scheme are found to be 83% and 98% respectively.
ensemble speaker and speaking environment modeling approach with advanced online estimation process. recently, we proposed an ensemble speaker and speaking environment modeling (essem) framework to characterize speaker variability and speaking environments. in contrast to multi-style training, essem uses single-style training to prepare multiple sets of environment-specific acoustic models. the ensemble of these acoustic models forms a prior structure of the environment for flexible prediction of unknown environment during testing. in this study, we present methods to further improve the precision for model characterization. we first study a weighted n-best information technique to well utilize the n-best transcription hypothesis in an unsupervised adaptation manner. next, we introduce cohort selection and environment space adaptation techniques to online improve the resolution and coverage of the prior structure. with an integration of the proposed methods, we further improve the essem performance over our previous study. on the aurora-2 task, essem achieves an average word error rate (wer) of 4.64%, corresponding to a 15.64% relative wer reduction over our best baseline result (5.50% to 4.64% wer) obtained with multi-condition training.
empirical error rate minimization based linear discriminant analysis. linear discriminant analysis (lda) is designed to seek a linear transformation that projects a data set into a lower-dimensional feature space while retaining geometrical class separability. however, lda cannot always guarantee better classification accuracy. one of the possible reasons lies in that its formulation is not directly associated with the classification error rate, so that it is not necessarily suited for the allocation rule governed by a given classifier, such as that employed in automatic speech recognition (asr). in this paper, we extend the classical lda by leveraging the relationship between the empirical classification error rate and the mahalanobis distance for each respective class pair, and modify the original between-class scatter from a measure of the squared euclidean distance to the pairwise empirical classification accuracy for each class pair, while preserving the lightweight solvability and taking no distributional assumption, just as what lda does. experimental results seem to demonstrate that our approach yields moderate improvements over lda on the large vocabulary continuous speech recognition (lvcsr) task.
robust nlos multipath mitigation for toa estimation. a technique that consists of correlation followed by thresholding is widely used to mitigate multipath effects, especially in the presence of non-line-of-sight (nlos) effects, for toa estimation. in practice, an accurate threshold that the technique relies on is difficult to obtain, since optimizing the threshold requires prior knowledge of channel statistics and signal/noise power, which are not always known a priori nor are easy to estimate. in this paper, we propose a new thresholding method that does not rely on such prior knowledge and is robust against an inaccurate threshold.
lattice-based mllr for speaker recognition. maximum-likelihod linear regression (mllr) transform coefficients have shown to be useful features for text-independent speaker recognition systems. these use mllr coefficients computed on a large vocabulary continuous speech recognition system (lvcsr) as features and support vector machines(svm) classification. however, performance is limited by transcripts, which are often erroneous with high word error rates (wer) for spontaneous telephone speech applications. in this paper, we propose using lattice-based mllr to overcome this issue. using wordlattices instead of 1-best hypotheses, more hypotheses can be considered for mllr estimation and, thus, better models are more likely to be used. as opposed to standard mllr, language model probabilities are taken into account as well. we show how systems using lattice mllr outperform standard mllr systems in the speaker recognition evaluation (sre) 2006. comparison to other standard acoustic systems is provided as well.
recognizing coordinated multi-object activities using a dynamic event ensemble model. while video-based activity analysis and recognition has received broad attention, existing body of work mostly deals with single object/person case. modeling involving multiple objects and recognition of coordinated group activities, present in a variety of applications such as surveillance, sports, biological records, and so on, is the main focus of this paper. unlike earlier attempts which model the complex spatial temporal constraints among different activities of multiple objects with a parametric bayesian network, we propose a dynamic ‘event ensemble’ framework as a data-driven strategy to characterize the group motion pattern without employing any specific domain knowledge. in particular, we exploit the riemannian geometric property of the set of ensemble description functions and develop a compact representation for group activities on the ensemble manifold. an appropriate classifier on the manifold is then designed for recognizing new activities. experiments on football play recognition demonstrate the effectiveness of the framework.
realizable equalizers for frequency selective mimo channels with cochannel interference. we consider realizable linear and decision feedback equalization (dfe) of frequency selective multiple-input multiple-output (mimo) channels in the presence of cochannel interference (cci). equalizers that are optimal in the minimum mean square error (mmse) sense are derived with and without zero forcing (zf) constraint. it is shown that all problems can be reduced to h2 optimal deconvolution, for which a novel algorithm is presented.
a detection-based approach to broadcast news video story segmentation. a detection-based paradigm decomposes a complex system into small pieces, solves each subproblem one by one, and combines the collected evidence to obtain a final solution. in this study of video story segmentation, a set of key events are first detected from heterogeneous multimedia signal sources, including a large scale concept ontology for images, text generated from automatic speech recognition systems, features extracted from audio track, and high-level video transcriptions. then a discriminative evidence fusion scheme is investigated. we use the maximum figure-of-merit learning approach to directly optimize the performance metrics used in system evaluation, such as precision, recall, and f1 measure. some experimental evaluations conducted on the trecvid 2003 dataset demonstrate the effectiveness of the proposed detection-based paradigm. the proposed framework facilitates flexible combination and extensions of event detector design and evidence fusion to enable other related video applications.
covariate shift adaptation for semi-supervised speaker identification. in this paper, we propose a novel semi-supervised speaker identification method that can alleviate the influence of non-stationarity such as session dependent variation, the recording environment change, and physical condition/emotion. we assume that the utterance variation follows the covariate shift model, where only the utterance sample distribution changes in the training and test phases. our method consists of weighted versions of kernel logistic regression and cross-validation and is theoretically shown to have the capability of alleviating the influence of covariate shift. we experimentally show through text-independent speaker identification simulations that the proposed method is promising in dealing with variations in session dependent utterance variation.
speech enhancement based on joint time-frequency segmentation. we present an algorithm to decompose speech into transient and non-transient components. our algorithm, the joint timefrequency segmentation algorithm, uses the wavelet packet coefficients of the speech signal and represents them as tiles of a time-frequency representation adapted to the characteristics of the signal itself. any wavelet packet coefficient, whose tiling height is larger than or equal to the tiling width is characterized as a transient coefficient and vice versa for the nontransient coefficient. the transient component is selectively amplified and recombined with the original speech to generate the modified speech with energy adjusted to be equal to the energy of the original speech. the psychoacoustic tests performed with fourteen human listeners show that the speech modification significantly improves speech intelligibility in background noise, i.e., for 10% absolute at 0db to 31% absolute at −30db.
the use of acoustically detected filled and silent pauses in spontaneous speech recognition. in recognizing spontaneous speech, the performance of typical speech recognizers tends to be degraded by filled and silent pauses, which are hesitation phenomena frequently occurred in such speech. in this paper, we present a method for improving the performance of a speech recognizer by detecting and handling both filled pauses (lengthened vowels) and silent (unfilled) pauses. our method automatically detects these pauses by using a bottom-up acoustical analysis in parallel with a typical speech decoding process, and then incorporates the detected results into the decoding process. from the results of experiments conducted using the ciair spontaneous speech corpus, the effectiveness of the proposed method was confirmed.
bispectrum on finite groups. the algebraic theory of finite groups appears in signal processing problems involving the statistical analysis of ranked data and the construction of invariants for pattern recognition. standard signal processing techniques involving spectral analysis are, in theory, possible for data defined on finite groups by using the fourier transform provided by group representations. however, one such technique, the bispectrum, which is useful for analysing non-gaussian data as well as for constructing geometric invariants, has not been explored in detail for finite groups. this paper shows how to construct the bispectrum on an arbitrary finite group or homogeneous space and explores its properties. examples are given using the symmetric group as well as wreath-product groups. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
efficient speech indexing and search for embedded devices using uniterms. in this paper, we present an efficient method of speech indexing and search using phoneme sequences called uniterms. in the indexing stage, a collection of uniterms and uniterm sequences is extracted from the target speech database by applying statistical scoring to each data item's phoneme lattice. in the search stage, each speech query's phoneme lattice is used to select candidate uniterms from the collection. these uniterms are applied in a speech recognition engine to convert the speech query into a uniterm lattice, from which we obtain a set of candidate uniterm sequences, each of which can be mapped to a search result item. not only is this method a significant improvement over previous phoneme-based methods, it is shown that explicit sequential comparison of uniterms in query and target data can be avoided using the proposed method without loss of search performance. avoiding sequential comparison allows better handling of transposition of words, and for the case where queries have word orders different from their intended targets, the proposed method can potentially bring about significant improvement.
mimo multi-channel beamforming in double-scattering channels. in this paper, we investigate the performance of multiple-input multiple-output (mimo) multi-channel beamforming (mb) systems in double-scattering channels. in particular, we first derive new expressions for the marginal ordered eigen-value distributions of the double-scattering channel matrices. based on these results, we present analytical expressions for the symbol error rate of mimo mb. it is demonstrated that mb sub-channels can achieve full spatial diversity even in the presence of double scattering, if the number of effective scatterers is greater than or equal to the maximum number of transmit and receive antennas.
maximum likelihood principle for dna copy number analysis. microarray technologies had been used to measure dna copy number data. the copy number represents the relative fluorescent intensity level between control and test dna samples. variation of this number may lead to many genetic diseases such as cancer. unfortunately, the observed copy numbers are corrupted by noise due to experimental errors and probes accuracy, making the variations hard to detect. different techniques had been proposed to denoise the data and to extract the important feature such as the breakpoints from the variant regions. in this paper, we present a robust procedure for the analysis of dna copy number data based on maximum likelihood principle using global information of the entire data record. we show that dynamic programming can be used to compute the dna copy number estimates and reduce the computational complexity. furthermore, we employ the minimum description length rule to estimate the number of unknown parameters. using simulated and real data, we show that the proposed method outperforms other popular commercial software and published algorithms.
low delay moving-horizon multiple-description audio coding forwireless hearing aids. in this work, we construct a novel scheme for efficient perceptual coding of audio for robust communication between encoders and wireless hearing aids. to limit the physical size of the hearing aids and to reduce power consumption and thereby increase the lifetime expectancy of the batteries, the hearing aids are constrained to be of low complexity. we therefore provide an asymmetric strategy where most of the computational load is placed at the encoding side. we make use of multiple-description coding. this combats possible erasures on the wireless link between the encoder and the hearing aids without introducing significant delay. furthermore, we employ psychoacoustically optimized noise-shaping quantizers based on the moving-horizon principle, which exploits a finite prediction horizon.
full diversity under multiple carrier frequency offsets of a family of space-frequency codes. a cooperative system may have both timing errors and multiple carrier frequency offsets (cfos). to combat timing errors, space-frequency (sf) coded ofdm systems have been recently proposed for cooperative communications to achieve both full cooperative and full multipath diversities without time synchronization requirement. in this paper, we study the effect of multiple cfos from relay nodes on a family of rotation based sf codes. we find that they can still achieve full diversities under the condition that the absolute values of normalized cfos are less than 0.5. we further show that this full diversity property still holds for a complexity-reduced two-stage zero forcing (zf) aided maximum likelihood (ml) decoding method, for which a zf method is used to equalize multiple cfos before ml decoding.
data hiding in hard-copy text documents robust to print, scan and photocopy operations. this paper describes a method for hiding data inside printed text documents that is resilient to print/scan and photocopying operations. using the principle of channel coding with side information, the embedder inserts a message into a text document while treating the content of the document as known interference. the data is embedded by making small changes to text characters before the document is printed. using a simple correlation-based detector in conjunction with an error correction code, the hidden data can be extracted from a photocopy of the printed document. by enhancing the detector with an optical character recognition algorithm, the embedded data can be extracted even after multiple rounds of photocopying. results from subjective tests show that the changes made by the embedding algorithm, while perceptible, are not obtrusive to a lay reader.
efficient minimum-phase prefilter computation using fast ql-factorization. this paper presents a novel approach for computing both the minimum-phase filter and the associated all-pass filter in a computationally efficient way using fast ql-factorization. a desirable property of this approach is that the complexity is independent of the size of the matrix being ql-factorized. instead, the complexity scales with the required precision of the filters as well as the filter length.
vlsi implementation of an effective lattice reduction algorithm with fixed-point considerations. lattice reduction-aided equalization techniques have emerged as a low-complexity method to achieve the same diversity as maximum likelihood detectors. we address the vlsi implementation of these lr-aided equalizers by modifying the clll algorithm from a fixed-point hardware perspective. we then apply the modified algorithm together with additional micro-architecture and operation scheduling enhancements to create an updated clll processor. finally, through ber simulations and fpga synthesis results we demonstrate the suitability of our clll processor for integration into a 64-qam mimo system.
quickest change detection in multiple on-off processes. a bayesian formulation of quickest change detection in multiple on-off processes is obtained within a decision-theoretic framework. for geometrically distributed busy and idle times, we show that the optimal joint design of channel switching and change detection has a simple threshold structure under a mild condition. extensions to arbitrarily distributed busy and idle times, in particular, heavy tail distributions, are discussed. we show that this problem presents a fresh twist to the classic problem of quickest change detection that considers only one stochastic process. we demonstrate that the key to quickest change detection in multiple processes is to abandon the current process when its state is unlikely to change in the near future (as indicated by the measurements obtained so far) and seek opportunities in a new process to avoid realizations of long busy periods. this problem arises in spectrum opportunity detection in cognitive radio networks where a secondary user searches for idle channels in the spectrum.
chirp rate estimation of speech based on a time-varying quasi-harmonic model. the speech signal is usually considered as stationary during short analysis time intervals. though this assumption may be sufficient in some applications, it is not valid for high-resolution speech analysis and in applications such as speech transformation and objective voice function assessment for detection of voice disorders. in speech, there are non stationary components, for instance time-varying amplitudes and frequencies, which may change quickly over short time intervals. in this paper, a previously suggested time-varying quasi-harmonic model is extended in order or to estimate the chirp rate for each sinusoidal component, thus successfully tracking fast variations in frequency and amplitude. the parameters of the model are estimated through linear least squares and the model accuracy is evaluated on synthetic chirp signals. experiments on speech signals indicate that the new model is able to efficiently estimate the signal component chirp rates, providing means to develop more accurate speech models for high-quality speech transformations.
image deconvolution using a gaussian scale mixtures model to approximate the wavelet sparseness constraint. this paper proposes to use an extended gaussian scale mixtures (gsm) model instead of the conventional l1 norm to approximate the sparseness constraint in the wavelet domain. we combine this new constraint with subband-dependent minimization to formulate an iterative algorithm on two shift-invariant wavelet transforms, the shannon wavelet transform and dual-tree complex wavelet transform (dtcwt). this extented gsm model introduces spatially varying information into the deconvolution process and thus enables the algorithm to achieve better results with fewer iterations in our experiments.
iterative inverse filtering by lattice filters for time-varying analysis and synthesis of speech. in this contribution, an analysis procedure is proposed for time-varying analysis and synthesis of speech based on lattice filters. the estimation is performed by an iterative inverse filtering approach exploiting analytical suboptimal solutions. starting from an initial configuration of coefficients, the procedure estimates a continuous piece-wise linear trajectory in terms of reflection coefficients. in this way, smooth trajectories can be estimated which have additionally a high time resolution. one advantage of this analysis technique is that the coefficient trajectories are estimated in the same way as they are used for the synthesis. examples of synthesized speech signals show that the proposed algorithm suppresses artifacts which are caused by the use of time-invariant estimation procedures.
solutions and comparison of maximum likelihood and full-least-squares estimations for circle fitting. the fitting of a number of noisy data points with a circle has found numerous applications in image processing and pattern recognition. this paper examines two methods to estimate the circle parameters: the maximum likelihood (ml) method and the full-least-squares (fls) method. the ml method is based on the noisy model from the data while the fls method minimizes the geometric distance square. we first provide the iterative solutions of them using taylor-series linearization approach. we then show analytically that fls does not yield the ml solution. this is in contrast to previous study that the fls method gives the same solution as ml. fls method approximates the ml estimation only if the noise power is much less than the circle radius square. simulations are included to support the theoretical development.
combining mixture weight pruning and quantization for small-footprint speech recognition. semi-continuous acoustic models, where the output distributions for all hidden markov model states share a common codebook of gaussian density functions, are a well-known and proven technique for reducing computation in automatic speech recognition. however, the size of the parameter files, and thus their memory footprint at runtime, can be very large. we demonstrate how non-linear quantization can be combined with a mixture weight distribution pruning technique to halve the size of the models with minimal performance overhead and no increase in error rate.
reconstruction of isometrically deformable flat surfaces in 3d from multiple camera images. this paper deals with the reconstruction of smooth, flexible, isometrically embedded flat surfaces in 3d, such as a sheet of paper or a flag waving in the wind, from a set of 2d projected observations such as camera images. to solve the problem, a set of matched features of the waving object at different poses is needed, which are then applied to the reconstruction algorithm here described. the complete algorithm consists of 2 phases, the first obtaining an initial approximation from local features, the second uses this result to iterate a global cost function, trying to achieve a better estimate. to validate the algorithm, synthetic data with noise is generated, reconstructed and compared to ground truth data. also, a second experiment consisting of real images of a sheet of paper is shown.
forward adaptive klt coding. a framework for implementing the forward adaptive karhunen-loève transform (faklt) is described. unlike backward adaptive methods, faklt computes transform coefficients using basis vectors derived from the most recent signal frame. as a result, it exhibits improved energy compaction compared to the backward adaptive klt. the method encodes only the klt coefficients and a small amount of side information, the klt basis vectors (eigenvectors) are not encoded. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
partial update pnlms algorithm for network echo cancellation. the proportionate normalized least mean square (pnlms) algorithm has been proposed for network echo cancellation to take advantages of the sparseness of the echo path impulse responses. the pnlms algorithm has fast initial convergence but slows down dramatically after the initial period. in this paper, a novel algorithm to combine the pnlms algorithm with the technique of partial update is proposed. simulation results show that the proposed algorithm can achieve faster overall convergence with less computation.
robust two-channel tdoa estimation for multiple speaker localization by using recursive ica and a state coherence transform. a novel method is presented for a robust two channel multiple time difference of arrival (tdoa) estimation for multispeaker localization which can provide satisfactory performance even in highly reverberant environment. the method is based on a recursive frequency-domain independent component analysis (ica) and on a novel state coherence transform (sct). exploiting the phase coherence of the demixing matrices obtained in the ica stage the sct is able to generate envelopes with clear peaks in the corresponding maximum-likelihood tdoas. the sct envelopes are computed independently in each time-block and accurate multiple tdoas are estimated by means of a time-frequency sparse representation of the sources. the method has been applied to real data obtained by recording many sources in a room with a reverberation time of 700ms. experimental results show that an accurate localization of 7 closely-spaced sources is possibile given only few seconds of data even in the case of low snr. experiments also show the advantage of using the proposed solution rather than the well-known gcc-phat.
sparse variable pca using a steepest descent on a grassman manifold. recently there has developed considerable interest in using sparseness with pca. almost all previous methods concentrate on zeroing out some loadings. here we develop a new approach which zeros out whole variables automatically. we formulate a vector l1 penalized pca criterion and optimize it by steepest descent along geodesic on a grassman manifold. this ensures that each step obeys pca orthogonality as well as an invariance property of the criterion. we show in simulations that it outperforms a previous svpca algorithm and apply it to a real high dimensional functional magnetic resonance imaging (fmri) data.
design of oversampled dft modulated filter banks optimized for acoustic echo cancellation. this paper describes a method for designing oversampled dft filter banks (fb) optimized for subband acoustic echo cancellation (aec). for this application, the design requirements typically are good echo cancellation quality, low delay, small reconstruction error, and low computation complexity. our method explicitly includes a model for echo return loss enhancement (erle) as part of the optimization criteria. convergence of the high-dimensional, nonlinear optimization problem is facilitated by decorrelating the prototype filter impulse response via a discreet cosine transform (dct), discarding many insignificant coefficients and thus reducing the dimensionality of the search. the experimental results demonstrate the effectiveness of our design and the effects on the performance of aec, with elre improvements on the order of 3 db or better. the method is flexible and could also be extended to other application domains.
spatial multizone soundfield reproduction. spatial multizone soundfield reproduction is a difficult problem, which has many potential applications. this paper provides a framework to recreate 2d spatial multizone soundfields using an array of loudspeakers. we derive the desired global soundfield by translating individual desired soundfields to a single global co-ordinate system and applying appropriate angular window functions. we reveal some of the fundamental limits of 2d multizone soundfield reproduction. we show that the ability of multizone reproduction is dependent on (i) maximum radius of multizones, (ii) window length (size, and nature), and (iii) radial distance to the furthermost zone. we illustrate the framework by designing and simulating a two dimensional two zone soundfield.
reconciliation of human and machine speech recognition performance. this paper focuses on resolving a number of issues that appear when the performance of human speech recognition is compared to that of automatic speech recognition. in particular human experimental data suggest that the resulting error is a product of the individual streams. on the other hand, bayesian combination requires a multiplication of the estimates of prior probabilities and likelihoods. we show that, in principle, there is no discrepancy. the product of errors is a performance measure and human and machine performance may be consistent with this empirically established regularity. the product of probabilities is step in an algorithm to achieve the performance that may or may not be consistent with the product of errors. the main problem is that most of prior discussions failed to distinguish the performance measures from the estimates of the parameters used in the algorithm.
covert timing channels codes for communication over interactive traffic. this paper presents the first practical perfectly-secure steganography codes for covert communication via packet timings across interactive traffic relayed over network queuing systems. it has recently been shown that sparse-graph linear codes followed by shaping techniques, combined with message-passing decoding, can enable practical timing channel codes with low symbol error rates near the information capacity of the famous “bits through queues” channel. inspired by this new class of codes, we use an alternative shaping technique that employs random dithers and construct provably secure steganographic codes for communication using packet timings in interactive traffic. to validate the perfect secrecy of our steganographic codes, we model interactive traffic as a two-state markov modulated poisson process (mmpp) and show its goodness-of-fit.
using the scaling ambiguity for filter shortening in convolutive blind source separation. in this paper, we propose to use the scaling ambiguity of convolutive blind source separation for shortening the unmixing filters. an often used approach for separating convolutive mixtures is the transformation to the time-frequency domain where an instantaneous ica algorithm can be applied for each frequency separately. this approach leads to the so called permutation and scaling ambiguity. while different methods for the permutation problem have been widely studied, the solution for the scaling problem is usually based on the minimal distortion principle. we propose an alternative approach that allows the unmixing filters to be as short as possible. shorter unmixing filters will suffer less from circular-convolution effects that are inherent to unmixing approaches based on bin-wise ica followed by permutation and scaling correction. the results for the new algorithm will be shown on a real-world example.
focusing-based approach for wide-band source localization in near-field. a wide-band near-field source localization method is presented in this paper. based on a pre-estimated source location, we form a focusing matrix which is able to compensate the wavefront distortion (with respect to far-field wavefront) due to near-field propagation and frequency dependent phase shift simultaneously. the focused covariance matrix has been proved to have a partially far-field narrow band structure, which allows us to estimate the bearings of the sources by the well studied far-field doa estimators. the range estimation is then carried out via peak searching of the 1d music spectral with the estimated bearings. the performance of the algorithm is tested by simulations.
robust detection of a set of outliers for image changes based on rerunning the regression. by comparing two images, which are captured with the same scene at different times, we can detect the image changes due to moving objects. to reduce the influence from the different intensity properties of the images, an intensity compensation scheme, which is based on the polynomial regression model, is employed. for an accurate detection of outliers alleviating the influence from a set of outliers, a simple technique that reruns the regression is employed. in this paper, the algorithm that iteratively reruns the regression is theoretically analyzed by observing the convergency of the estimates of the noise variance. using an empirical compensation constant for the estimate is also proposed. the compensation enables the detection algorithm robust to the choice of thresholds for selecting outliers. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
a low-complexity spectro-temporal based perceptual model. the use of psychoacoustical masking models for audio coding applications has been wide spread over the past decades. in such applications, it is typically assumed that the original input signal serves as a masker for the distortions that are introduced by the lossy coding method that is used. up to now, these masking models are mostly based on spectral masking. in this paper, we propose a new perceptual model for audio and speech processing algorithms based on spectro-temporal masking. a sophisticated perceptual model is simplified, such that the eventual distortion measure can be written as a frequency-weighted l2-norm. this yields the same computational complexity as conventional spectral-based methods, but with the preservation of the temporal fine structure of the clean signal. it is shown that the new model can successfully avoid pre-echoes and can correctly predict masking curves for various maskers.
glottal closure instant detection using lines of maximum amplitudes (loma) of thewavelet transform. the lines of maximum amplitude (loma) of the wavelet transform are used for glottal closure instant detection. following kadambe & al. (1992), the wavelet transform modulus maxima can be used for singularity detection. the loma method extends this idea. all the lines chaining maxima of a wavelet transform across scales are built. then a back-tracking procedure allows for selection of the optimal line for each pitch period, the top of which indicates the gci. the loma method is then evaluated by comparing its results to the dypsa (naylor & al.) algorithm, with the option of using inverse filtering as preprocessing. the loma method compares favorably to dypsa, particularly on accuracy. one of the advantage of the loma method is its ability to deal with variations in the glottal source parameters.
a framework for distributed multimedia stream mining systems using coalition-based foresighted strategies. in this paper, we propose a distributed solution to the problem of configuring classifier trees in distributed stream mining systems. the configuration involves selecting appropriate false-alarm detection tradeoffs for each classifier to minimize end-to-end penalty in terms of misclassification cost. in the proposed solution, individual classifiers select their operating points (i.e., actions) to maximize a local utility function. the utility may be purely local to the current classifier, corresponding to a myopic strategy, or may include the impact of the classifier actions on successive classifiers in the tree, corresponding to a foresighted strategy. we analytically show that actions determined by the foresighted strategies can improve the end-to-end performance of the classifier tree and derive an associated probability bound. we then evaluate our solutions on an application for hierarchical sports scene classification. by comparing centralized, myopic and foresighted solutions, we show that foresighted strategies result in better performance than myopic strategies, and also asymptotically approach the centralized optimal solution.
online blind source separation based on time-frequency sparseness. recently, blind source separation (bss) has been proposed to separate signals recorded by a microphone array in a reverberant environment. this paper deals with bss of a time-varying number of moving sources, which often occurs in practical situations. we develop two online algorithms based on time-frequency (tf) sparseness that are able to deal with moving sources: a block-online algorithm that estimates the number of sources and a gradient-based online algorithm with prespecified maximum number of sources. both algorithms are evaluated in simulations and real-world scenarios and show good separation performance.
affine invariant features and their application to speech recognition. this paper proposes a set of affine invariant features (aifs) for sequence data. the proposed aifs can be calculated directly from the sequence data, and their invariance to affine transformation is proved mathematically through algebraic calculation. we apply the aifs to speech recognition. since the vocal tract length (vtl) difference causes to frequency warping which can be approximated well by affine transform on cepstral features [1], the aifs of cepstral sequence provide robust features for vtl variations. we experimentally examine the invariance of aifs of speech signals, and apply aifs for japanese isolated word recognition. the experimental results show that the combination of aifs with mfcc or mfcc+δ can lead to higher recognition rates than mfcc or mfcc+δ only. especially in the mismatched experiments, the combination with aifs can reduce the error rates about 30% when compared to mfcc or mfcc+δ only. the aifs are expected to have other applications than speech recognition, since their invariance is general.
acoustic-based pitch-accent detection in speech: dependence on word identity and insensitivity to variations inword usage. past work has produced fairly accurate automatic pitch-accent detectors, but it has often been noted that the accent class of a word is highly dependent on word identity, with some words and word types usually being accented and others not. we argue that a good accent detector should not only have high overall accuracy, but also be able to distinguish between accented and unaccented variants of the same word. we report on experiments with several classifiers trained on a hand-labeled corpus, using a large set of acoustic features. results show that while the classifiers have a high overall accuracy, they perform disappointingly on words with atypical accent status or whose prior accent status is more uncertain. we further report on attempts to improve the performance on these sub-tasks via feature selection and engineering of the training set.
compressive sampling of pulse trains: spread the spectrum! in this paper we consider the problem of sampling far below the nyquist rate signals that are sparse linear superpositions of shifts of a known, potentially wide-band, pulse. this signal model is key for applications such as ultra wide band (uwb) communications or neural signal processing. following the recently proposed compressed sensing methodology, we study several acquisition strategies and show that the approximations recovered via ℓ1 minimization are greatly enhanced if one uses spread spectrum modulation prior to applying random fourier measurements. we complement our experiments with a discussion of possible hardware implementation of our technique.
single and multichannel sampling of bilevel polygons using exponential splines. in this paper we present a novel approach for sampling and reconstructing any k-sided convex and bilevel polygon with the use of exponential splines [1]. it will be shown that with k+1 projections we are able to perfectly reconstruct a k-sided bilevel polygon from its samples. we will also investigate the multichannel sampling scenario, consisting of a bank of e-spline filters, each with a different delay parameter compared to the reference signal. we show how by retrieving the delay parameters, we can symmetrically sample and reconstruct a given bilevel polygon using exponential splines.
sound source separation of moving speakers for robot audition. this paper addresses sound source separation and speech recognition for moving sound sources. real-world applications such as robots should cope with both moving and stationary sound sources. however, most studies assume only stationary sound sources. we introduce two key techniques to cope with moving sources, that is, adaptive step-size control (as) and optima controlled recursive average (ocra) to improve blind source separation. we implemented a real-time robot audition system with these techniques for our humanoid robot asimo with an 8ch microphone array by using hark which is our open-source software for robot audition. the performance of the system will be shown through sound source separation for moving sources and automatic speech recognition of separated speeches.
a portable usb-based microphone array device for robust speech recognition. we present a usb-based, highly directional, and portable microphone array device that delivers a crisp, clear and noise-reduced speech signal. this device consists of four linearly distributed microphone sensors and a filter-and-sum beamformer designed using broadband beam-forming algorithm. the device has a narrow acoustic beam pattern and identical frequency responses for almost all speech bands. in addition to beamforming, an adaptive noise reduction algorithm is used to further reduce the background noise. by utilizing both the spatial and temporal information, the snr of speech signals is improved and speech recognition performance in noisy environments is significantly improved as reported in our experiments.
adaptive distributed transforms for irregularly sampled wireless sensor networks. we develop energy-efficient, adaptive distributed transforms for data gathering in wireless sensor networks. in particular, we consider a class of unidirectional transforms that are computed as data is forwarded to the sink along a given routing tree and develop a tree-based karhunen-loàve transform (klt) that is optimal in that it achieves maximum data de-correlation among this class of transforms. as an alternative to this klt (which incurs communication overhead in order to learn second order data statistics), we propose a backward adaptive filter optimization algorithm for distributed wavelet transforms that i) achieves near optimal performance and ii) has no communication overhead in learning statistics.
robust face recognition with partially occluded images based on a single or a small number of training samples. this paper investigates the problem of face recognition with partially occluded images without assuming prior information about the distortion, and with only a single training image or a small number of training images for each class to be identified. a new approach is presented, which is an extension of our previous posterior union model. the new approach is formulated by using a similarity measure in place of the probability measure, thereby allowing the use of a single training image to represent a class. the new approach achieves improved robustness to partial occlusion by focusing the recognition mainly on the matched local regions, which are selected automatically subject to an optimality criterion to maximize the similarity of the correct class. two databases, xm2vts and ar, have been used to evaluate the new approach. the results indicate that the new system is able to perform as well as an oracle model for dealing with various simulated and realistic partial distortions/occlusions without requiring prior information.
underdetermined audio source separation from anechoic mixtures with long time delay. we propose a technique to separate audio sources from their anechoic mixtures with long delay in an underdetermined setting (i.e., the number of audio sensors is smaller than that of sources). it consists of two stages: 1) to estimate anechoic mixing parameters of attenuation and arrival delay and 2) to recover original audio sources based on estimated mixing parameters. when delay is longer than one sample, previous algorithms perform poorly. to address this shortcoming, we estimate the maximum delay and use it to find a proper frequency range that produces no phase ambiguity. then, we determine mixing parameters with time-frequency points in this range. finally, mathematical tools are used to solve the underdetermined linear system to recover original audio sources. the effectiveness of the proposed technique on various mixing scenarios with noisy observation of mixtures and different types of sounds is demonstrated by experimental results.
a multistage approach for blind separation of convolutive speech mixtures. in this paper, we propose a novel algorithm for the separation of convolutive speech mixtures using two-microphone recordings, based on the combination of independent component analysis (ica) and ideal binary mask (ibm), together with a post-filtering process in the cepstral domain. essentially, the proposed algorithm consists of three steps. first, a constrained convolutive ica algorithm is applied to separate the source signals from two-microphone recordings. in the second step, we estimate the ibm by comparing the energy of corresponding time-frequency (t-f) units from the separated sources obtained with the convolutive ica algorithm. the last step is to reduce musical noise caused typically by t-f masking using cepstral smoothing. the performance of the proposed approach is evaluated based on both reverberant mixtures generated using a simulated room model and real recordings. the proposed algorithm offers considerably higher efficiency, together with improved speech quality while producing similar separation performance as compared with a recent approach.
inpainting with sparse linear combinations of exemplars. we introduce a new exemplar-based inpainting algorithm that represents the region to be inpainted as a sparse linear combination of example blocks, extracted from the image being inpainted or an external training image set. this method is conceptually simple, being computed by minimization of a simple functional, and avoids the complexity of correctly ordering the filling in of missing regions of other exemplar-based methods. initial performance comparisons on small inpainting regions indicate that this method provides similar or better performance than other recent methods.
target detection using incremental learning on single-trial evoked response. the human neural responses associated with cognitive events, referred as event related potentials (erps), can provide reliable inference for target image detection. incremental learning has been widely investigated to deal with large datasets. to solve the problem of data growing over time in cross session studies, we apply an incremental learning support vector machines (svm) method on single-trial erp detection for identifying targets in satellite images. we implement the incremental learning svm by keeping only the support vectors, instead of all the data, from the previous sessions and incorporating them with the data of the current session. thus the incremental learning dramatically reduces the computational load. the results demonstrate that the incremental learning erp detection system performs as well as the naive method, which uses only the current training session, and the batch mode, which uses all training data. furthermore, it is more computationally efficient, which allows it to better cope with a continuous stream of eeg data.
conditional random fields for the prediction of signal peptide cleavage sites. correct prediction of signal peptide cleavage sites has a significant impact on drug design. state-of-the-art approaches to cleavage site prediction typically use generative models (such as hmms) to represent the statistics of amino acid sequences or use neural networks to detect the changes in short amino-acid segments along a query sequence. by formulating cleavage site prediction as a sequence labeling problem, this paper demonstrates how conditional random fields (crfs) can be applied to cleavage site prediction. the paper also demonstrates how amino acid properties can be exploited and incorporated into the crfs to boost prediction performance. results show that the performance of crfs is comparable to that of a state-of-the-art predictor (signalp v3.0). further performance improvement was observed when the decisions of signalp and the crf-based predictor are fused.
a semi-supervised learning approach to online audio background detection. we present a framework for audio background modeling of complex and unstructured audio environments. the determination of background audio is important for understanding and predicting the ambient context surrounding an agent, both human and machine. our method extends the online adaptive gaussian mixture model technique to model variations in the background audio. we propose a method for learning the initial background model using a semi-supervised learning approach. this information is then integrated into the online background determination process, providing us with a more complete background model. we show that we can utilize both labeled and unlabeled data to improve audio classification performance. by incorporating prediction models in the determination process, we can improve the background detection performance even further. experimental results on real data sets demonstrate the effectiveness of our proposed method.
amplify-and-forward based cooperation for secure wireless communications. a physical layer approach to security for wireless networks is considered. in single-antenna wireless systems, such approaches are hampered by channel conditions in the presence of one or more eavesdroppers. cooperation has the potential to overcome this problem and improve the security of of wireless communications. in this paper, an amplify-and-forward based cooperative protocol is proposed. assuming availability of global channel state information, system design that maximizes the secrecy capacity is considered. since the optimal solution to this problem is intractable, suboptimal closed-form solutions are proposed that optimize bounds on secrecy capacity for the case of a single eavesdropper, or that introduce additional constraints, such as nulling of signals at all eavesdroppers, for the case of multiple eavesdroppers.
challenges in mobile network operation: towards self-optimizing networks. this paper reviews current status and trends in the application of self-organizing principles to advanced wireless networks, such as 3gpp long-term evolution (lte). the transfer of research results and concepts to real-world networks imposes additional constraints and requirements, which open a multitude of interesting new fields for applied research. particular challenges include defining appropriate assessment criteria, evaluation methodology, as well as a variety of interrelations between use cases with conflicting goals and mutual parameter dependencies yielding non-closed-form problems. furthermore only partial, error-prone and potentially inconsistent information is available. additional challenges include minimization of overhead, stability, and convergence issues, in particular for decentralized solutions.
model-based early termination scheme for h.264/avc inter prediction. inter prediction is the most power-consumed component in h.264/avc encoder. for the power-aware design, it is necessary to reduce the power consumption by using fast inter prediction techniques. in this paper, a system-level power-aware algorithm based on the early termination scheme of h.264/avc inter prediction is proposed. the proposed early termination scheme for h.264 motion estimation is based on the statistical modeling of the motion compensated residual data. we develop a power-aware adaptive mechanism with multiple thresholds derived from the statistical model to early terminate the motion estimation (me). according to the experimental results, our early termination scheme for h.264/avc inter prediction not only preserves fine rd performance but also eliminates the unnecessary operation in both ime stage and fme stage to realize the power-aware h.264 encoder system.
real-time dynamic mr image reconstruction using kalman filtered compressed sensing. in recent work, kalman filtered compressed sensing (kf-cs) was proposed to causally reconstruct time sequences of sparse signals, from a limited number of “incoherent” measurements. in this work, we develop the kf-cs idea for causal reconstruction of medical image sequences from mr data. this is the first real application of kf-cs and is considerably more difficult than simulation data for a number of reasons, for example, the measurement matrix for mr is not as “incoherent” and the images are only compressible (not sparse). greatly improved reconstruction results (as compared to cs and its recent modifications) on reconstructing cardiac and brain image sequences from dynamic mr data are shown.
receiver nonlinearity optimization in clipping channels. in this paper the effects of receiver nonlinearities are examined for clipping channels. the objective of this work is to determine the optimal receiver functions for additive noise clipping channels. in this case the optimal receiver function will be the one that maximizes the signal-to-noise-plus-distortion ratio (sndr) between the transmitted and received variables. to solve the problem we utilize functional analysis to find a necessary condition for the sndr-maximizing receiver function. the results are general and can be applied for any noise and signal distribution. furthermore, the results show that for the example given, the linear receiver is not sndr-optimal.
two dimensional maximum margin criterion. maximum margin criterion is a well-known method for feature extraction and dimensionality reduction. in this paper, we propose a novel feature extraction method, namely two dimensional maximum margin criterion (2dmmc), specifically for matrix representation data, e.g. images. 2dmmc aims to find two orthogonal projection matrices to project the original matrices to a low dimensional matrix subspace, in which a sample is close to those in the same class but far from those in different classes. both theoretical analysis and experiments on benchmark face recognition data sets illustrate that the proposed method is very effective and efficient.
generalized mutual interdependence analysis. the mean of a data set is one trivial representation of data from one class. recently, mutual interdependence analysis (mia) has been successfully used to extract more involved representations, or “mutual features”, accounting for samples in the class. for example a mutual feature is a speaker signature under varying channel conditions or a face signature under varying illumination conditions. a mutual representation is a linear regression that is equally correlated with all samples of the input class. we present the mia optimization criterion from the perspectives of regression, canonical correlation analysis and bayesian estimation. this allows us to state and solve the above criterion concisely, to contrast the mia solution to the sample mean, and to infer other properties of its closed form, unique solution under various statistical assumptions. we define a generalized mia solution (gmia) and apply mia and gmia in a text-independent speaker verification task using the ntimit database. both methods show competitive performance with equal-error-rates of 7.5 % and 6.5 % respectively over 630 speakers.
low-complexity sinusoidal component selection using loudness patterns. sinusoidal modeling of audio at low-bit rates involves selecting a limited number of parameters according to a quantitative or perceptual criterion. most perceptual sinusoidal component selection strategies are computationally intensive and not suitable for real-time applications. in this paper, a computationally efficient sinusoidal selection algorithm based on a novel hybrid loudness estimation scheme is presented. the hybrid scheme first estimates efficiently the loudness of a multi-tone signal from the loudness patterns of its constituent sinusoidal components. then it refines this estimate by performing a full evaluation of loudness but only in select critical bands. experimental results show that the proposed technique maintains a low perceptual sinusoidal synthesis error at a much lower computational complexity.
model-based non-linear estimation for adaptive image restoration. we propose a new image restoration algorithm that is driven by an adaptive piecewise autoregressive model (par). the strength of the new algorithm is its ability to preserve spatial structures better than its predecessors. the high adaptability is achieved by locally fitting 2d image waveform to the par model in moving windows. the problem is posed as one of nonlinear least-square estimation of both par parameters and original pixels, constrained by the degradation function. robust solutions of the underlying underdetermined inverse problem are obtained by an innovative use of multiple par models that circumvent the issue of model overfitting, and by applying a structured total least-square technique.
web-derived pronunciations. pronunciation information is available in large quantities on the web, in the form of ipa and ad-hoc transcriptions. we describe techniques for extracting candidate pronunciations from web pages and associating them with orthographic words, filtering out poorly extracted pronunciations, normalizing ipa pronunciations to better conform to a common transcription standard, and generating phonemic from ad-hoc transcriptions. we show improvements on a letter-to-phoneme task when using web-derived vs. pronlex pronunciations.
multiterminal source coding of bernoulli-gaussian correlated sources. this paper presents a practical coding scheme for the direct symmetric multiterminal source coding problem with remote source, when the noise between the remote source and the observations is gaussian-bernoulli-gaussian. the idea behind the design is to take advantage from the observed symbols being in the real field, in order to perform low-dimensional compressed sensing. the coding scheme is based on channel coding techniques involving bch codes over the real field. simulations with respect to the rate distortion performance are provided, along with insights about optimization issues. robustness to variations of the probability of impulse is also investigated. perspectives about the application to the ceo problem in presence of gaussian-bernoulli-gaussian correlation noise between the remote source and the observations conclude the paper.
multi-antenna cognitive radio systems: environmental learning and channel training. this paper presents a multi-antenna cognitive radio (cr) system that is capable of operating concurrently with the primary radio (pr) link. the operation of the cr system consists of three stages: environmental learning, cr channel training and cr data transmission. in environmental learning stage, partial channel information between pr and cr are obtained blindly, based on which the transmit beamforming and the receive beamforming strategies are designed at cr to remove/reduce the interference to and from pr, respectively. we characterize all the interference values analytically and study the problem of learning/training tradeoff associated with the proposed scheme. the optimal balancing between learning and training is examined via the minimum mean square error (mse) of the channel estimation. it is shown that for a given total learning/training time, there indeed exists a optimal learning time that minimizes the mse of the channel estimation, yet the interference power to the pr is regulated.
multiuser mimo-mac capacity in the low snr regime: channel knowledge and double-scattering. we investigate the sum capacity of the uplink multiuser multiple-input multiple-output (mimo) multiple-access channel (mac) in the low signal-to-noise ratio (snr) regime. for each user, the mimo channel is modeled according to a general class of stochastic channel matrices, known as double-scattering. assuming that each user knows only their own spatial correlation matrices and employs optimal statistical beamforming transmission, we present new analytical approximations for the sum capacity of the mimo-mac for low snr values. our approximations are accurate, and lead to key insights into the effect of correlation.
on the effect of transmitter iq imbalance at ofdma receivers. one limiting issue in implementing high-speed wireless systems is the impairment associated with analog processing due to component imperfections. in uplink transmission of multiuser systems, a major source of such impairment is iq imbalance (iqi) introduced at multiple transmitters. in this paper, we analyze the effect of the transmitter (tx) iqi on ofdma receiver. to cope with the inter-user interference problem due to tx iqi, we propose a novel subcarrier allocation scheme, which has high tolerance to such tx iq distortion.
reduced-complexity delay-doppler correlator for time-frequency hopping signals. the delay-doppler correlator is most commonly used for target detection in a radar system. it is essentially a two-dimensional filter matched to the hypothesized delay and doppler shifts of echoes reflected from the illuminating signal. more recently, it has been applied in communication to the detection of signature sequences generated from artificially introduced time-frequency shifts of a base sequence. in this paper, we derive a computationally efficient delay-doppler correlator for a class of time-frequency hopping waveforms that can be represented by segments of equal-length sinusoids. these sequences can be found in applications such as continuous waveform radar and device identification in wireless communication. by applying sliding discrete fourier transform and exploiting the structure of the waveform, the number of multiplications required for evaluating the entire delay-doppler range can be reduced by a factor equaling the length of the sequence. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
factor graph based design of an ofdm-idma receiver performing joint data detection, channel estimation, and channel length selection. we present a factor graph based design of a receiver for pilot-assisted ofdm-idma systems transmitting over frequency-selective channels. the receiver performs joint iterative multiuser data detection and channel estimation with a complexity that is linear in the number of users, and it includes estimation of the channel length. simulation results demonstrate large performance gains compared to ofdm-idma receivers using separate mmse channel estimation.
sparse source separation from orthogonal mixtures. this paper addresses source separation from a linear mixture under two assumptions: source sparsity and orthogonality of the mixing matrix. we propose efficient sparse separation via a two-stage process. in the first stage we attempt to recover the sparsity pattern of the sources by exploiting the orthogonality prior. in the second stage, the support is used to reformulate the recovery task as an optimization problem. we then suggest a solution based on alternating minimization. random simulations are performed to analyze the behavior of the resulting algorithm. the simulations demonstrate convergence of our approach as well as superior recovery rate in comparison with alternative source separation methods and k-svd, a leading algorithm in dictionary learning.
a new method for oov detection using hybrid word/fragment system. in this paper, we propose a new method for detecting regions with out-of-vocabulary (oov) words in the output of a large vocabulary continuous speech recognition (lvcsr) system. the proposed method uses a hybrid system combining words and data-driven variable length sub word units. with the use of a single feature, the posterior probability of sub word units, this method outperforms existing methods published in the literature. we also presents a recipe to discriminatively train a hybrid language model to improve oov detection rate. results are presented on the rt04 broadcast news task.
advances in syntax-based malay-english speech translation. in this paper, we present advanced techniques that improved the performance of ibm malay-english speech translation system significantly. during this work, we generated linguistics-driven hierarchical rules to enhance the formal syntax-based translation model; designed an active learning approach with bi-directional translations that outperformed unsupervised training; utilized translation direction information in parallel training corpus to build direction-specific interpolated language models for machine translation. there is 20% relative improvement achieved in the translation performance through all these techniques. a state-of-the-art malay speech recognition system was also established as one of the crucial modules in the rapidly developed malay-english speech translation.
sparse multivariate autoregressive (mar)-based partial directed coherence (pdc) for electroencephalogram (eeg) analysis. partial directed coherence (pdc) has recently been proposed for studying brain connectivity in eeg studies. pdc provides a quantitative spectral measure of the causal relations between signals by its central use of a multivariate autoregressive (mar) model. yet, in real applications, the successful estimation of pdc depends on the accuracy of mar parameter estimation, which is often sensitive to the data size and model order. in addition, it is generally believed that connections between eeg nodes (brain regions) may be sparse. to address these concerns, we propose a sparse mar-based pdc technique where pdc estimates are computed from sparse mar coefficient matrices derived from penalized regression. the proposed technique is applied to both simulated data and real eeg recordings, and results show enhanced stability and accuracy of the proposed technique compared to the traditional, non-sparse approach. the sparse mar-based pdc technique is promising for analyzing brain connectivity in eeg analysis.
fishervoice and semi-supervised speaker clustering. speaker subspace modeling has become increasingly important in speaker recognition, diarization, and clustering. principal component analysis (pca) is a popular linear subspace learning technique and the approach that represents an arbitrary utterance or speaker as a linear combination of a set of basis voices based on pca is known as the eigenvoice approach. in this paper, a novel technique, namely the fishervoice approach, is proposed. the fishervoice approach is based on linear discriminant analysis, another successful linear subspace learning technique that provides an optimized low-dimensional representation of utterances or speakers with focus on the most discriminative basis voices. we apply the fishervoice approach to speaker clustering in a semi-supervised manner and show that the fishervoice approach significantly outperforms the eigenvoice approach in all our experiments on the gale mandarin dataset.
ber improved transmit power allocation for d-sttd systems with qr-based successive symbol detection. we propose a ber improved power allocation scheme for d-sttd systems over i.i.d. rayleigh fading channels under the qr-based successive detection framework. instead of relying on ber under a fixed channel realization, the adopted design criterion is the mean ber (assuming there is no inter-layer error propagation) averaged with respect to the channel distribution. such a design metric has two-fold advantages: (i) it is analytically tractable and is closely related to a block error probability upper bound when inter-layer error propagation occurs, and (ii) there is no need for repeated feedback of the instantaneous channel information. by exploiting a distinctive channel matrix structure unique to d-sttd systems we derive a closed-form approximate upper bound of the considered ber metric; through minimization of this bound an optimal power allocation scheme is obtained. numerical simulation is used to illustrate the performance of the proposed method.
revisiting graphemes with increasing amounts of data. letter units, or graphemes, have been reported in the literature as a surprisingly effective substitute to the more traditional phoneme units, at least in languages that enjoy a strong correspondence between pronunciation and orthography. for english however, where letter symbols have less acoustic consistency, previously reported results fell short of systems using highly-tuned pronunciation lexicons. grapheme units simplify system design, but since graphemes map to a wider set of acoustic realizations than phonemes, we should expect grapheme-based acoustic models to require more training data to capture these variations. in this paper, we compare the rate of improvement of grapheme and phoneme systems trained with datasets ranging from 450 to 1200 hours of speech. we consider various grapheme unit configurations, including using letter-specific, onset, and coda units. we show that the grapheme systems improve faster and, depending on the lexicon, reach or surpass the phoneme baselines with the largest training set.
shrinkage estimation of high dimensional covariance matrices. we address covariance estimation under mean-squared loss in the gaussian setting. specifically, we consider shrinkage methods which are suitable for high dimensional problems with small number of samples (large p small n). first, we improve on the ledoit-wolf (lw) method by conditioning on a sufficient statistic via the rao-blackwell theorem, obtaining a new estimator rblw whose mean-squared error dominates the lw under gaussian model. second, to further reduce the estimation error, we propose an iterative approach which approximates the clairvoyant shrinkage estimator. convergence of this iterative method is proven and a closed form expression for the limit is determined, which is called the oas estimator. both of the proposed estimators have simple expressions and are easy to compute. although the two methods are developed from different approaches, their structure is identical up to specific constants. the rblw estimator provably dominates the lw method; and numerical simulations demonstrate that the oas estimator performs even better, especially when n is much less than p.
spoken term detection using fast phonetic decoding. while spoken term detection (std) systems based on word indices provide good accuracy, there are several practical applications where it is infeasible or too costly to employ an lvcsr engine. an std system is presented, which is designed to incorporate a fast phonetic decoding front-end and be robust to decoding errors whilst still allowing for rapid search speeds. this goal is achieved through monophone open-loop decoding coupled with fast hierarchical phone lattice search. results demonstrate that an std system that is designed with the constraint of a fast and simple phonetic decoding front-end requires a compromise to be made between search speed and search accuracy.
synthesis of planar arrays with arbitrary geometry for flat-top footprint patterns. this paper presents a new synthesis algorithm to produce flat-top main beams with arbitrary footprint for array elements placed in an arbitrary planar geometry. the general framework of the paper would encompass the patterns produced by circular aperture distribution. it is shown that for patterns generated by circular apertures some efficient simplifying facts based on properties of bessel functions can be applied. the method shows a high performance in generating optimally flat-top patterns with detailed geometry footprints.
a sum-of-products model for effective coherent modulation filtering. modulation filtering is a technique for filtering slowly-varying envelopes of frequency subbands of a nonstationary signal, ideally without affecting the signal's phase and fine-structure. coherent modulation filtering is a promising subtype of such techniques where subband envelopes are determined through demodulation of the subband signal with a coherently detected subband carrier. in this paper we demonstrate how modulation filtering, when done coherently, is far more effective than standard incoherent methods. we show that empirical results can be made to be almost ideal, and significantly better than previous coherent attempts, as long as fine-structure information is retained as side information and the filterbank reduces subband interference.
loquendo - politecnico di torino's 2008 nist speaker recognition evaluation system. this paper describes the improvements introduced in the loquendo-politecnico di torino (lpt) speaker recognition system submitted to the nist sre08 evaluation campaign. this system, which was among the best participants in this evaluation, combines the results of three core acoustic systems, two based on gaussian mixture models (gmms), and one on phonetic gmms. we discuss the results of the experiments performed for the 10sec-10sec condition and for the core condition, including the challenging tasks involving a target speaker and an interviewer. the error rate reduction of our sre08 system compared to the sre06 system ranges from 25% of the telephone-interview condition to 57% of the interview-interview condition. on the test with telephone and microphone conversations, the improvements range from 9% to 32%.
musical noise analysis based on higher order statistics for microphone array and nonlinear signal processing. in this paper, we conduct an analysis for reduction of musical noise in integration method of microphone array signal processing and nonlinear signal processing. in these days, for better noise reduction, integration methods of microphone array signal processing and nonlinear signal processing have been researched. however, non-linear signal processing causes musical noise. since such musical noise make users uncomfortable, it is desired that musical noise is mitigated. moreover, in these days, it is reported that higher-order statistics is strongly related with the amount of generated musical noise. thus, we analyze the integrated method of microphone array signal processing and nonlinear signal processing, based on higher-order statistics. also, we propose an architecture for reducing musical noise based on the analysis. the effectiveness of the proposed architecture and analysis correctness are shown via a computer simulation and a subjective evaluation.
modelling the neurovascular habituation effect on fmri time series. in this paper, a novel non-stationary model of functional magnetic resonance imaging (fmri) time series is proposed. it allows us to account for some putative habituation effect arising in event-related fmri paradigms that involves the so-called repetition-suppression phenomenon [1] and induces decreasing magnitude responses over successive trials. akin to [2], this model is defined over functionnally homogeneous regions-of-interest (rois) and embedded in a joint detection-estimation approach of brain activity. importantly, its non-stationarity character is embodied in the trial-varying nature of the bold response magnitude. habituation and activation maps are then estimated within the bayesian framework in a fully unsupervised mcmc procedure. on artificial fmri datasets, we show that habituation effects can be accurately recovered in activating voxels.
combination strategies for a factor analysis phone-conditioned speaker verification system. this work aims to take advantage of recent developments in joint factor analysis (jfa) in the context of a phonetically conditioned gmm speaker verification system. previous work has shown performance advantages through phonetic conditioning, but this has not been shown to date with the jfa framework. our focus is particularly on strategies for combining the phone-conditioned systems. we show that the classic fusion of the scores is suboptimal when using multiple gmm systems. we investigate several combination strategies in the model space, and demonstrate improvement over score-level combination as well as over a non-phonetic baseline system. this work was conducted during the 2008 clsp workshop at johns hopkins university.
optimal learning of p-layer additive f0 models with cross-validation. in this paper, we present the derivation of the backfitting training algorithms for generic p-layer additive f0 models for arbitrary positive integer p. we have presented the special cases of the algorithms with p = 2 and p = 3 that have been successfully applied to the modelings of japanese and english f0 contours, whereas the derivation of the algorithm was presented only for the two-layer case. the additive f0 model have smoothing parameters that establish a trade-off between the fit to the training data and the smoothness of the fitted curves, which have been all set to unity in the previous works. in this paper, we also present an optimal approach to set the values of these parameters using cross validation. we performed the training using the boston university radio news corpus and confirmed the effectiveness of the proposed method.
providing invariance to nonlinear valumetric scaling for quantization basedwatermarking. a novel framework providing invariance to a class of nonlinear valumetric distortions, such as gamma correction, for qim-based watermarking techniques [1] is presented. valumetric distortions are quite common in image and video processings and the sensitivity to valumetric scalings represents the main weakness of the watermarking techniques belonging to the quantization based class. the proposed method amounts to perform a mapping of the host samples in a proper transformed domain where the watermark is subsequently embedded using a gain invariant qim-based technique. the effectiveness of this approach has been verified by applying the watermarking system using rdm [2], aqim [3] and dm in the logarithmic domain [4] as embedding algorithms. simulation results provide a useful comparison of the performance of these different techniques within the proposed scheme as well as they confirm the invariance to nonlinear distortions.
emotion-based music retrieval on a well-reduced audio feature space. music expresses emotion. a number of audio extracted features have influence on the perceived emotional expression of music. these audio features generate a high-dimensional space, on which music similarity retrieval can be performed effectively, with respect to human perception of the music-emotion. however, the real-time systems that retrieve music over large music databases, can achieve order of magnitude performance increase, if applying multidimensional indexing over a dimensionally reduced audio feature space. to meet this performance achievement, in this paper, extensive studies are conducted on a number of dimensionality reduction algorithms, including both classic and novel approaches. the paper clearly envisages which dimensionality reduction techniques on the considered audio feature space, can preserve in average the accuracy of the emotion-based music retrieval.
ensembles of landmark multidimensional scalings. landmark multidimensional scaling (lmds) uses a subset of data (landmark points) to solve classical mds, where the scalability is increased but the approximation is noise-sensitive. in this paper we present an ensemble of lmdss, referred to as landmark mds ensemble (lmdse), where we use a portion of the input in a piecewise manner to solve classical mds, combining individual lmds solutions which operate on different partitions of the input. ground control points (gcps) that are shared by partitions considered in the ensemble, allow us to align individual lmds solutions in a common coordinate system through affine transformations. lmdse solution is determined by averaging aligned lmds solutions. we show that lmdse is less noise-sensitive while maintaining the scalability as well as the speed of lmds. experiments on synthetic data (noisy grid) and real-world data (similar image retrieval) confirm the high performance of the proposed lmdse.
a systolic array for linear mimo detection based on an all-swap lattice reduction algorithm. a systolic array to implement lattice-reduction-aided linear detection is proposed for a mimo receiver. the lattice reduction algorithm and the ensuing linear detections are operated in the same array, which can be hardware-efficient. all-swap lattice reduction algorithm (aslr) is considered for the systolic design. aslr is a variant of the lll algorithm, which processes all lattice basis vectors within one iteration. lattice-reduction-aided linear detection based on aslr and lll algorithms have very similar bit-error-rate performance, while aslr is more time efficient in the systolic array, especially for systems with a large number of antennas.
estimation of mb steganography based on least square method. in the available jpeg steganography methods, model-based (mb) steganography technique is more secure than jsteg, f5 and outguess. in this paper, we consider the problem of estimating the embedded length of secret messages of mb steganography. we provide an expected distribution of the non-zero ac coefficients' high precision histogram to fit the stegotexts', and adopt the cropped and recompressed calibration to obtain the carrier image approximation. then, we present a new algorithm to estimate the embedding rates based on least square method. the attacks towards mb are successful with experimental evidence on 2700 carrier images and the stego images of different quality factor and different embedding rates.
microarray classification using block diagonal linear discriminant analysis with embedded feature selection. in this paper, block diagonal linear discriminant analysis (bdlda) is improved and applied to gene expression data. bdlda is a classification tool with embedded feature selection, that has demonstrated good performance on simulated data. however, by using cross validation in training, bdlda is time consuming, thus not an appropriate algorithm for gene expression data, which has a large number of features and relatively small number of samples. in our algorithm, estimated error rate is used as a measure to choose the best model. the algorithm is optimized by repeating the model construction procedure with previously selected features removed, which leads to increased classification robustness. our algorithm is tested using 10 fold cross validation. in most simulated and real data, our method outperforms the state-of-the-art techniques, showing promise for its use in microarray classification problems. the resulting block structure allows to identify discriminating correlated genes, which is potentially useful in cancer research.
panorama recovery from noisy uav surveillance video. this paper proposes an efficient and robust algorithm to recover a panorama from poorly-obtained uav video frames contaminated with significant noise. in this algorithm, the eigen-space based neighborhood region will be introduced with our novel feature-based random m least-sqaures (rmls) registration technique. meanwhile, the corresponding similarity regions will be assigned weights according to the relativity between these neighboring regions. next, bayesian multi-frame sampling will be implemented utilizing the homography estimated by the frame registration. finally, the sub-region in each frame which is applicable to the multi-frame sampling will be stitched utilizing multi-resolution blending.
musical noise generation analysis for noise reduction methods based on spectral subtraction and mmse stsa estimation. in this paper, we reveal new findings about the generated musical noise in minimum mean-square error short-time spectral amplitude (mmse stsa) processing. recently we have proposed a objective metric of musical noise based on kurtosis change ratio on spectral subtraction (ss). also we found an interesting relationship among the degree of generated musical noise, the shapes of signal-s probability density function, the strength parameter of ss processing. this paper is aimed to automatically evaluate the sound quality of various types of noise reduction methods using kurtosis change ratio. we give a mathematical analysis based on higher-order statistics viewpoint, and lead to a valuable relation in that mmse stsa has a weakness in speech period distortion rather than noise period, and vice versa in ss.
bayesian discriminative adaptation for speech recognition. linear transform-based speaker adaptation is a standard part of many speech recognition systems. for unsupervised adaptation maximum likelihood estimation is typically used, as discriminative transforms are more heavily biased towards the supervision hypothesis which may contain errors. in this work a bayesian framework for discriminative adaptation is investigated. this reduces the hypothesis bias and allows robust estimates even with a limited amount of data. various forms of discriminative maximum-a-posteriori estimation, and associated issues, are detailed. to address these problems, the use of discriminative mapping transforms is also described. the proposed framework is evaluated on an english conversational speech task.
online estimation of the optimum quadratic kernel size of second-order volterra filters using a convex combination scheme. this paper presents a method for estimating the optimum memory size for identification of an unknown second-order volterra kernel. as these structures may imply considerable computational demands, it is highly desirable to design adaptive realizations with a minimum number of coefficients. therefore, we propose a combination scheme comprising two volterra filters with time-variant sizes of the actually used quadratic kernels. by following some simple rules, the number of diagonals in the quadratic kernels is increased or decreased in order to find the optimum memory configuration in parallel to the coefficient adaptation. thus, the arbitrary choice of the nonlinear system size is overcome by a dynamically growing/shrinking system. experimental results for various signals and nonlinear scenarios demonstrate the effectiveness of the proposed method.
functional estimation in hilbert space for distributed learning in wireless sensor networks. in this paper, we propose a distributed learning strategy in wireless sensor networks. taking advantage of recent developments on kernel-based machine learning, we consider a new sparsification criterion for online learning. as opposed to previously derived criteria, it is based on the estimated error and is therefore is well suited for tracking the evolution of systems over time. we also derive a gradient descent algorithm, and we demonstrate its relevance to estimate the dynamic evolution of temperature in a given region.
an analysis of articulatory-acoustic data based on articulatory strokes. an articulatory gestural unit representation called “articulatory stroke” is introduced. it aims to capture the constriction formation and release of a speech articulator such as the tongue tip. in that regard, the articulatory stroke is an attempt at a practical realization of the abstract articulatory gestures central to articulatory phonology. in this study we focus on the articulatory strokes associated with the critical articulator that is essential to realize a target phone. the critical articulatory stroke is parameterized in order to investigate the predictability of the parameters from phonetic contexts and to check the statistical dependency of acoustic changes associated with the critical articulatory strokes. canonical correlation analysis between the articulatory strokes and δmfccs showed that the critical articulatory strokes are more responsible to the acoustic changes inside target phonemes than non-critical articulators. this implies that modeling acoustic changes due to critical articulations could provide an edge in improving asr performance.
exploiting statically schedulable regions in dataflow programs. dataflow descriptions have been used in a wide range of digital signal processing (dsp) applications, such as multi-media processing, and wireless communications. among various forms of dataflow modeling, synchronous dataflow (sdf) is geared towards static scheduling of computational modules, which improves system performance and predictability. however, many dsp applications do not fully conform to the restrictions of sdf modeling. more general dataflow models, such as cal [1], have been developed to describe dynamically-structured dsp applications. such generalized models can express dynamically changing functionality, but lose the powerful static scheduling capabilities provided by sdf. this paper focuses on detection of sdf-like regions in dynamic dataflow descriptions — in particular, in the generalized specification framework of cal. this is an important step for applying static scheduling techniques within a dynamic dataflow framework. our techniques combine the advantages of different dataflow languages and tools, including cal [1], dif [2] and cal2c [3]. the techniques are demonstrated on the idct module of mpeg reconfigurable video coding (rvc).
law recognition via histogram-based estimation. in this paper, we study the problem of recognizing an unknown probability density function from one of its sample which is of interest in signal and image processing or telecommunication applications. by opposition with the classical kolmogorov-smirnov method based on empirical cumulative functions, we consider histogram estimators of the density itself built from our data. those histograms are generated via model selection, more specifically via a codelength-based information criterion. from the histograms, we may compute a kullback-leibler distance to any theoretical law which is used to complete the recognition. we apply this histogram-based method for law recognition in a theoretical setup where the true density is known as well as in a real setup where data come from radio channel propagation experimentation.
gray-scale erosion algorithm based on image bitwise decomposition: application to focal plane processors. a novel approach to implement gray-scale morphological operations is presented in this work. this new technique is based on the bitwise decomposition of the gray-scale image, yielding bitplanes disposed according to their bit of significance. it is of particular interest for implementations on focal plane processors. our approach relies on the binary search method to obtain either the maximum or minimum on a local neighborhood by manipulating the binary levels resulting from the bitwise decomposition with simple logic functions. this contrasts significantly with the classical threshold decomposition (td) approach, on which most of the current techniques are based on. our method shows better efficiency than td implementations. further gains can be obtained because our method shows a strong dependency on the image dynamic range.
active learning for semi-supervised multi-task learning. we present an algorithm for active learning (adaptive selection of training data) within the context of semi-supervised multi-task classifier design. the semi-supervised multi-task classifier exploits manifold information provided by the unlabeled data, while also leveraging relevant information across multiple data sets. the active-learning component defines which data would be most informative to classifier design if the associated labels are acquired. the framework is demonstrated through application to a real landmine detection problem.
a novel rejection sampling scheme for posterior probability distributions. rejection sampling (rs) is a well-known method to draw from arbitrary target probability distributions, which has important applications by itself or as a building block for more sophisticated monte carlo techniques. the main limitation to the use of rs is the need to find an adequate upper bound for the ratio of the target probability density function (pdf) over the proposal pdf from which the samples are generated. there are no general methods to analytically find this bound, except in the particular case in which the target pdf is log-concave. in this paper we adopt a bayesian view of the problem and propose a general rs scheme to draw from the posterior pdf of a signal of interest using its prior density as a proposal function. the method enables the analytical calculation of the bound and can be applied to a large class of target densities. we illustrate its use with a simple numerical example.
automatic named identification of speakers using diarization and asr systems. in this paper, we consider the extraction of speaker identity from audio records of broadcast news without a priori acoustic information about speakers. using an automatic speech recognition system and an automatic speaker diarization system, we present improvements for a method which allows to extract speaker identities from automatic transcripts and to assign them to speech segments. experiments are carried out on french broadcast news records from the ester 1 evaluation campaign. experimental results using outputs of automatic speech recognition and automatic diarization are presented.
on acoustic surveillance of hazardous situations. the present study presents a practical methodology for automatic space monitoring based solely on the perceived acoustic information. we consider the case where atypical situations such as screams, explosions and gunshots take place in a metro station environment. our approach is based on a two stage recognition schema, each one exploiting hmms for approximating the density function of the corresponding sound class. the main objective is to detect abnormal events that take place in a noisy environment. a thorough evaluation procedure is carried out under different snr conditions and we report high detection rates with respect to false alarm and miss probabilities rates.
cart-based modeling of chinese tonal patterns with a functional model tracing the fundamental frequency trajectories. we propose an approach to modeling chinese tonal patterns, focusing on the basic fundamental frequency (f0) patterns characterized by the contextual linguistic features that can be directly extracted from text. we analyze tonal patterns as sparse target points (tonal f0 peaks and valleys) and represent them in parametric form within the framework of a functional f0 model. the relationships between the target points and underlying linguistic features are trained using classification and regression tree analysis (carts), and this functional model is used to trace the f0 trajectories when training the carts and to synthesize a tonal pattern from the target points predicted by the carts. our experiments indicate that the proposed method has low f0 prediction errors. utilization of the f0 ranges measured from training samples could significantly reduce the influences of differences in voice ranges on training a speaker-independent model. furthermore, the most important roles in characterizing tonal patterns were played by a few linguistic features such as lexical tone context and the distinction between voiced from unvoiced initials.
joint reconstruction of compressed multi-view images. this paper proposes a distributed representation algorithm for multi-view images that are jointly reconstructed at the decoder. compressed versions of each image are first obtained independently with random projections. the multiple images are then jointly reconstructed by the decoder, under the assumption that the correlation between images can be represented by local geometric transformations. we build on the compressed sensing framework and formulate the joint reconstruction as a l2-l1 optimization problem. it tends to minimize the mse distortion of the decoded images, under the constraint that these images have sparse and correlated representations over a structured dictionary of atoms. simulation results with multi-view images demonstrate that our approach achieves better reconstruction results than independent decoding. moreover, we show the advantage of structured dictionaries for capturing the geometrical correlation between multi-view images.
design of large planar diaphragm incorporating multiple vibrators for sound directivity control via fem and bem. we have realized a sound directivity control of a large planar diaphragm by controlling the bending vibrations using multiple vibrators. this paper proposes a method to determine the parameters such as the shape and thickness of the diaphragm and the position of the vibrators. in this method, the finite element method (fem) is used to simulate the diaphragm vibrations and the boundary element method (bem) is used to simulate the radiated sound. we first validate the simulation results by measuring the actual bending vibrations and sound directivity and comparing them with the simulated results. we then show that metaheuristics are effective in finding appropriate parameters because the sound directivity largely varies in a continuous manner with variations in the parameters.
discriminative training of hierarchical acoustic models for large vocabulary continuous speech recognition. in this paper we propose discriminative training of hierarchical acoustic models for large vocabulary continuous speech recognition tasks. after presenting our hierarchical modeling framework, we describe how the models can be generated with either minimum classification error or large-margin training. experiments on a large vocabulary lecture transcription task show that the hierarchical model can yield more than 1.0% absolute word error rate reduction over non-hierarchical models for both kinds of discriminative training.
particle filtering for quantized innovations. in this paper, we re-examine the recently proposed distributed state estimators based on quantized innovations. it is widely believed that the error covariance of the quantized innovation kalman filter [1, 2] follows a modified riccati recursion. we present stable linear dynamical systems for which this is violated and the filter diverges. we propose a particle filter that approximates the optimal nonlinear filter and observe that the error covariance of the particle filter follows the modified riccati recursion of [1]. we also simulate a posterior cramer-rao bound (pcrb) for this filtering problem.
adaptive quickest change detection with unknown parameter. quickest detection of an abrupt distribution change with an unknown time varying parameter is considered. a novel adaptive approach is proposed to tackle this problem, which is shown to outperform the celebrated parallel cusum test. performance is evaluated through theoretical analysis and numerical simulations.
sequential best range matching: an error concealment technique with application in high packet loss image transmission. suffering from the inadequacy of reliable received data and their lack of sufficient a priori knowledge about the lost regions, the existing error concealment (ec) techniques fail to perform well in high packet loss transmission of compressed images. in order to obviate such a deficiency, we propose the sequential best range matching (sbrm) algorithm: the correctly received regions of image are employed to fabricate the lost regions according to the spatial similarities within the image. our simulation results show that sbrm not only outperforms the existing ec methods especially in high packet loss conditions, but also provides suitable prior knowledge to initialize further estimation and denoising processes.
image spam filtering using fourier-mellin invariant features. image spam is a new obfuscating method which spammers invented to more effectively bypass conventional text based spam filters. in this paper, a framework for filtering image spams by using the fourier-mellin invariant features is described. fourier-mellin features are robust for most kinds of image spam variations. a one-class classifier, the support vector data description (svdd), is exploited to model the boundary of image spam class in the feature space without using information of legitimate emails. experimental results demonstrate that our framework is effective for fighting image spam.
genre effects on automatic sentence segmentation of speech: a comparison of broadcast news and broadcast conversations. we investigate genre effects on the task of automatic sentence segmentation, focusing on two important domains - broadcast news (bn) and broadcast conversation (bc). we employ an hmm model based on textual and prosodic information and analyze differences in segmentation accuracy and feature usage between the two genres using both manual and automatic speech transcripts. experiments are evaluated using czech broadcast corpora annotated for sentence-like units (sus). prosodic features capture information about pause, duration, pitch, and energy patterns. textual knowledge sources include words, part-of-speech, and automatically induced classes. we also analyze effects of using additional textual data that is not annotated for sus. feature analysis reveals significant differences in both textual and prosodic feature usage patterns between the two genres. the analysis is important for building automatic understanding systems when limited matched-genre data are available, or for designing eventual genre-independent systems.
brain mri t1-map and t1-weighted image segmentation in a variational framework. in this paper we propose a constrained version of mumford-shah's[1] segmentationwith an information-theoretic point of view[2] in order to devise a systematic procedure to segment brain mri data for two modalities of parametric t1-map and t1-weighted images in both 2-d and 3-d settings. the incorporation of a tuning weight in particular adds a probabilistic flavor to our segmentation method, and makes the three-tissue segmentation possible. our method uses region based active contours which have proven to be robust. the method is validated by two real objects which were used to generate t1-maps and also by two simulated brains of t1-weighted data from the brainweb[3] public database.
a new stochastic estimator for tremor frequency tracking. an important parameter in analysis of physiological tremor is the diagnosis and study of neurological disorders. the instantaneous tremor frequency (itf) is an important parameter in tremor analysis. this paper proposes a novel stochastic filter, the multiple extended kalman filter (m-ekf), for tracking of itf from neural microelectrode recordings. the m-ekf mitigates degradations in filter performance resulting from a mismatch between assumed initial conditions and those of a particular realization of a stochastic system. specifically, the m-ekf is comprised of a bank of extended kalman filters (ekf), each initialized with different conditions, selected according to the unscented transform. the final estimate is a weighted average of the individual estimates provided by each ekf where the weights reflect how closely the assumed ekf initial conditions match those of the true system. the m-ekf is applied to a synthetic tremor model to display its superior performance to that of the ekf and the unscented kalman filter.
generating high performance pruned fft implementations. we derive a recursive general-radix pruned cooley-tukey fast fourier transform (fft) algorithm in kronecker product notation. the algorithm is compatible with vectorization and parallelization required on state-of-the-art multicore cpus. we include the pruned fft algorithm into the program generation system spiral, and automatically generate optimized implementations of the pruned fft for the intel core2duo multicore processor. experimental results show that using the pruned fft can indeed speed up the fastest available fft implementations by up to 30% when the problem size and the pattern of unused inputs and outputs are known in advance.
variational bayesian joint factor analysis for speaker verification. joint factor analysis (jfa) has been successfully applied to speaker verification tasks to tackle speaker and session variability. in the sense of bayesian statistics, it is beneficial to take account of the uncertainties in jfa to better characterize its speaker enrollment and verification processes, e.g. representing target speaker model by posteriori distribution of latent speaker factors and evaluating model likelihood by integrating over all latent factors. however, in a jfa model which has a large number of latent factors, it is computationally demanding to carry out these things in their exact form. in this paper, an alternative approach based on variational bayesian is developed to explore uncertainties in jfa in an approximate yet efficient way. in this method, fully correlated posteriori distribution is approximated by a variational distribution of factorial form to facilitate inference; and a tight lower bound on model likelihood is derived. experimental results on the 10sec4w-10sec4w task of the 2006 nist sre show that variational bayesian jfa could obtain better performance than jfa using point estimate.
unsupervised speaker adaptation for telephone call transcription. the use of the pc and internet for placing telephone calls will present new opportunities to capture vast amounts of un-transcribed speech for a particular speaker. this paper investigates how to best exploit this data for speaker-dependent speech recognition. supervised and unsupervised experiments in acoustic model and language model adaptation are presented. using one hour of automatically transcribed speech per speaker with a word error rate of 36.0%, unsupervised adaptation resulted in an absolute gain of 6.3%, equivalent to 70% of the gain from the supervised case, with additional adaptation data likely to yield further improvements. lm adaptation experiments suggested that although there seems to be a small degree of speaker idiolect, adaptation to the speaker alone, without considering the topic of the conversation, is in itself unlikely to improve transcription accuracy.
compressive sensing for sparsely excited speech signals. compressive sensing (cs) has been proposed for signals with sparsity in a linear transform domain. we explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of speech production, for recovering compressive sensed speech. since the linear transform is signal dependent and unknown, unlike the standard cs formulation, a codebook of transfer functions is proposed in a matching pursuit (mp) framework for cs recovery. it is found that mp is efficient and effective to recover cs encoded speech as well as jointly estimate the linear model. moderate number of cs measurements and low order sparsity estimate will result in mp converge to the same linear transform as direct vq of the lp vector derived from the original signal. there is also high positive correlation between signal domain approximation and cs measurement domain approximation for a large variety of speech spectra.
an analytical approach to sound field reproduction with a movable sweet spot using circular distributions of loudspeakers. sound field reproduction methods like higher order ambisonics which are based on orthogonal expansions always introduce a limitation of the spatial bandwidth of the secondary source driving function. this spatial truncation creates a sweet spot in the center of the secondary source distribution. this spot, or rather area, is “sweet” both in terms of spatial aliasing artifacts as well as in terms of accuracy of the desired component of the reproduced wave field. the higher the temporal frequency of the reproduced wave field the smaller is the sweet spot. in this paper we show that the location sweet spot can be moved freely inside the secondary source distribution. the accuracy of the actual reproduced wave field is then significantly higher in the sweet spot than in the same region in the conventional approach.
model-based analysis of speech and audio signals for real-time processing based on time-varying lattice filters. in this paper, a time-varying analysis procedure based on lattice filters is proposed for real-time processing. the analysis procedure estimates the reflection coefficients from the signal frames successively in a way that the current frame is analyzed with respect to previous frames. for that purpose, a linear coefficient trajectory covering the current and previous frames is estimated under condition that the left-sided starting value of the trajectory is prescribed by analysis results of previous frames. the coefficients of the current frame can be determined from the trajectory at a particular point. analyses of speech signals show that the algorithm yields good spectral modeling simultaneously with a smooth time development.
multichannel nonnegative matrix factorization in convolutive mixtures. with application to blind audio source separation. we consider inference in a general data-driven object-based model of multichannel audio data, assumed generated as a possibly under-determined convolutive mixture of source signals. each source is given a model inspired from nonnegative matrix factorization (nmf) with the itakura-saito divergence, which underlies a statistical model of superimposed gaussian components. we address estimation of the mixing and source parameters using two methods. the first one consists of maximizing the exact joint likelihood of the multichannel data using an expectation-maximization algorithm. the second method consists of maximizing the sum of individual likelihoods of all channels using a multiplicative update algorithm inspired from nmf methodology. our decomposition algorithms were applied to stereo music and assessed in terms of blind source separation performance.
accelerated 3d mri of vocal tract shaping using compressed sensing and parallel imaging. 3d mri of the upper airway has provided valuable insights into vocal tract shaping and data for the modeling of speech production. small movements of articulators can lead to large changes in the produced sound, therefore improving the resolution of these datasets, within the constraints of a sustained sound (6–12 seconds), is an important area for investigation. this paper provides the first application of compressed sensing (cs) with parallel imaging to high-resolution 3d upper airway mri. we use spatial finite difference as the sparsifying transform, and investigate the use of high-resolution phase information as a constraint during cs reconstruction. in a retrospective subsampling experiment with no sound production, 5x undersampling produced acceptable image quality when using phase-constrained cs reconstruction. the prospective use of this accelerated acquisition enabled 3d vocal-tract mri during sustained production of english /s/,/∫/,/i/,/r/ with 1.33×1.33×1.33-mm3 spatial resolution and 10-seconds of scan time.
lsh banding for large-scale retrieval with memory and recall constraints. locality sensitive hashing (lsh) is widely used for efficient retrieval of candidate matches in very large audio, video, and image systems. however, extremely large reference databases necessitate a guaranteed limit on the memory used by the table lookup itself, no matter how the entries crowd different parts of the signature space, a guarantee that lsh does not give. in this paper, we provide such guaranteed limits, primarily through the design of the lsh bands. when combined with data-adaptive bin splitting (needed on only 0.04% of the occupied bins) this approach provides the required guarantee on memory usage. at the same time, it avoids the reduced recall that more extensive use of bin splitting would give.
iterative target detection approach for through-the-wall radar imaging. we consider the problem of target detection in through-the-wall radar imaging when no a priori knowledge about the image statistics is available. an iterative approach which adapts itself to the unknown image statistics and thus allows for automatic target detection is presented. two variants, based on 2d median filtering and morphological operations, are described in details. the proposed detection schemes are tested using experimental data, considering the problem of 3d reconstruction of a scene hidden behind a concrete wall.
partial iterative equalization and channel decoding. this paper proposes a bit-selective iterative processing scheme for turbo equalization. we consider convolutionally coded and turbo coded transmissions over inter-symbol interference (isi) channels. the receiver starts with conventional iterative channel equalization and decoding. after each iteration, bit convergence status is measured via cross-entropy. short windows are then applied around unconverged bits and the subsequent detection/decoding iterates only within the windows. the rapid decrease in selected bits after each such iteration reduces computational complexity significantly, but performance is well maintained by utilizing the markov property in the trellis detection/decoding.
a differential motion estimation method for image interpolation in distributed video coding. motion estimation methods based on differential techniques proved to be very useful in the context of video analysis, but have a limited employment in classical video compression because, though accurate, the dense motion vector field they produce requires too much coding resource and computational effort. on the contrary, this kind of algorithm could be useful in the framework of distributed video coding (dvc). in this paper we propose a differential motion estimation algorithm which can run at the decoder in a dvc scheme, without requiring any increase in coding rate. this algorithm allows a performance improvement in image interpolation with respect to state-of-the-art algorithms.
fault detection combining interacting multiple model and multiple solution separation for aviation satellite navigation system. in civil aviation applications, satellite failures yield unacceptable positioning errors when using the global positioning system (gps). to ensure the user security, the navigation system has to fulfill stringent performance requirements. thus, detecting and excluding the faulty gps measurements is necessary prior to estimating the mobile location. classical fault detection algorithms based on kalman filters (kf) are sensitive to the choice of an appropriate motion model for the mobile. to overcome this difficulty, we propose in this paper a new fault detection algorithm wherein the kf are replaced by multiple model algorithms. in this way, both the false alarm rate and the position mean square error are shown to be decreased.
large margin semi-tied covariance transforms for discriminative training. we discuss the applicability of large margin techniques to the problem of estimating linear transforms for discriminative training of a semi-tied covariance (stc) model. since stc models are good proxies for full-covariance (fc) gaussian models, the idea is to combine the benefit of the latest discriminative training techniques and the modeling advantage of fc gaussians at a much lower computational cost. we study the interaction of these transforms with feature-space and model-space discriminative training on state-of-the-art speaker adapted systems built for a large-scale arabic broadcast news transcription task.
exploiting t-junctions for depth segregation in single images. occlusion is one of the major consequences of the physical image generation process: it occurs when an opaque object partly obscures the view of another object further away from the viewpoint. local signatures of occlusion in the projected image plane are t-shaped junctions. they represent, in some sense, one of the most primitive depth information. in this paper, we investigate the usefulness of t-junctions for depth segregation in single images. our strategy consists in incorporating ordering information provided by t-junctions into a region merging algorithm and then reasoning about the depth relations between the regions of the final partition using a graph model. experimental results demonstrate the effectiveness of the proposed approach.
voice conversion based on simultaneous modelling of spectrum and f0. this paper proposes a simultaneous modeling of spectrum and f0 for voice conversion based on msd (multi-space probability distribution) models. as a conventional technique, a spectral conversion based on gmm (gaussian mixture model) has been proposed. although this technique converts spectral feature sequences nonlinearly based on gmm, f0 sequences are usually converted by a simple linear function. this is because f0 is undefined in unvoiced segments. to overcome this problem, we apply msd models. the msd-gmm allows to model continuous f0 values in voiced frames and a discrete symbol representing unvoiced frames within an unified framework. furthermore, the msd-hmm is adopted to model long term correlations in f0 sequences.
independent component analysis for noisy speech recognition. independent component analysis (ica) is not only popular for blind source separation but also for unsupervised learning when the observations can be decomposed into some independent components. these components represent the specific speaker, gender, accent, noise or environment, and act as the basis functions to span the vector space of the human voices in different conditions. different from eigenvoices built by principal component analysis, the proposed independent voices are estimated by ica algorithm, and are applied for efficient coding of an adapted acoustic model. since the information redundancy is significantly reduced in independent voices, we effectively calculate a coordinate vector in independent voice space, and estimate the hidden markov models (hmms) for speech recognition. in the experiments, we build independent voices from hmms under different noise conditions, and find that these voices attain larger redundancy reduction than eigenvoices. the noise adaptive hmms generated by independent voices achieve better recognition performance than those by eigenvoices.
statistical dialog management applied to wfst-based dialog systems. we have proposed an expandable dialog scenario description and platform to manage dialog systems using a weighted finite-state transducer (wfst) in which user concept and system action tags are input and output of the transducer, respectively. in this paper, we apply this framework to statistical dialog management in which a dialog strategy is acquired from a corpus of human-to-human conversation for hotel reservation. a scenario wfst for dialog management was automatically created from an n-gram model of a tag sequence that was annotated in the corpus with interchange format (if). additionally, a word-to-concept wfst for spoken language understanding (slu) was obtained from the same corpus. the acquired scenario wfst and slu wfst were composed together and then optimized. we evaluated the proposed wfst-based statistic dialog management in terms of correctness to detect the next system actions and have confirmed the automatically acquired dialog scenario from a corpus can manage dialog reasonably on the wfst-based dialog management platform.
speaker identification with whispered speech based on modified lfcc parameters and feature mapping. much research recently in speaker recognition has been devoted to robustness due to microphone and channel effects. however, changes in vocal effort, especially whispered speech, present significant challenges in maintaining system performance. due to the absence of any periodic excitation in whisper, the spectral structure in whisper and neutral speech will differ. therefore, performance of speaker id systems, trained mainly with high energy voiced phonemes, degrades when tested with whisper. this study considers a front-end feature compensation method for whispered speech to improve speaker recognition using a neutral trained system. first, an alternative feature vector with linear frequency cepstral coefficients (lfcc) is introduced based on spectral analysis from both speech modes. next, for the first time a feature mapping is proposed for reducing whisper/neutral mismatch in speaker id. feature mapping is applied on a frame-by-frame basis between two speaker independent gmms (gaussian mixture models) of whispered and neutral speech. text independent closed set speaker id results show an absolute 20% improvement in accuracy when compared with a traditional mfcc feature based system. this result confirms a viable approach to improving speaker id performance between neutral and whispered speech conditions.
blind source extraction of periodic signals. a new algorithm is developed here for blind extraction of periodic signals. it is assumed that the fundamental frequencies of the sources (or alternatively one of the harmonics for each source) are known a priori. necessary and sufficient conditions for blind source extraction of cyclostationary signals are introduced and the optimization problem is solved using steepest descent method for complex matrices. computer simulation results verify the effectiveness and good performance of the algorithm.
optimal inference of the inverse gamma texture for a compound-gaussian clutter. we first derive the stochastic dynamics of a gaussian-compound model with an inverse gamma distributed texture from jakeman's random walk model with step number fluctuations. following a similar approach existing for the k-distribution, we show how the scattering cross-section may be inferred from the fluctuations of the scattered field intensity. by discussing the sources of discrepancy arising during this process, we derive an analytical expression for the inference error based on its asymptotic behaviours, together with a condition to minimize it. simulated data enables verification of our proposed technique. the interest of this strategy is discussed in the context of radar applications.
ranging energy optimization for robust sensor positioning. we address ranging energy optimization for an unsynchronized localization system, which features robust sensor positioning, in the sense that specific accuracy requirements are fulfilled within a prescribed service area. optimization problems related to the ranging energy of a sensor and beacons are proposed, after which a practical algorithm based on semidefinite programming is presented. the effectiveness of the algorithm is illustrated by a numerical experiment.
maximin robust design for mimo communication systems against imperfect csit. this paper considers robust transmit strategies, against the imperfectness of csit, for mimo communication systems. following a deterministic model that assumes the actual channel inside an ellipsoid centered at a nominal channel, we maximize the worst-case received snr. it is shown that, for a general class of power constraints, the resulting maximin problem can be equivalently transformed into a convex problem, or even further into a semidefinite program. the most important result is that the optimal transmit directions are just the right singular vectors of the nominal channel under some mild conditions. this result reduces the complicated matrix-valued problems to scalar power allocation problems, for which the closed-form solutions are provided.
an adaptive quantization scheme for distributed consensus. the problem of distributed average consensus with quantized data is considered in this paper. we firstly propose a simple modification to the classical consensus protocol. under a condition that the quantization noise variance converges to zero, the proposed protocol achieves a consensus in a mean squared sense and the consensus value is equal to the average of the initial state. based on this result, we develop an adaptive quantization scheme which can adaptively adjust its quantization threshold and step-size by learning from previous runs, in a way such that the quantization noise variance at each sensor decreases to zero. simulation results are presented to illustrate the effectiveness of the proposed algorithm.
auditory coding based speech enhancement. this paper demonstrates a speech enhancement system based on an efficient auditory coding approach, coding of time-relative structure using spikes. the spike coding method can more compactly represent the non-stationary characteristics of speech signals than the fourier transform or wavelet transform. enhancement is accomplished through the use of mmse thresholding on the spike code. experimental results show that compared with the spectral domain logstsa filter, both the subjective spectrogram evaluation and objective ssnr improvement for the proposed approach is better in suppressing noise in high noise situations, with fewer musical artifacts.
erp source reconstruction by using particle swarm optimization. localization of the sources of event related potentials (erp) is a challenging inverse problem, especially to resolve sources of neural activity occurring simultaneously. by using an effective dipole source model, we propose a new technique for accurate source localization of erp signals. the parameters of the dipole erp sources are optimally chosen by using particle swarm optimization technique. obtained results on synthetic data sets show that proposed method well localizes the dipoles on their actual locations. on real data sets, the fit error between the actual and reconstructed data is successfully reduced to noise level by localizing a few dipoles in the brain.
the data deluge: challenges and opportunities of unlimited data in statistical signal processing. recently, there has been a dramatic increase of the amount of audio, video, and images created and shared on the internet by users around the world. much of this content is publicly available and free of cost. when viewed through the lens of pattern classification, this content can be seen as a virtually unlimited supply of training data for various statistical modeling and labeling tasks such as speech recognition and computer vision. in order to effectively exploit this data resource, significant research challenges must be addressed. in this paper, we present three significant challenges that must be solved to harness the potential of this “data deluge”. we then describe recent work in spoken language processing and image processing that has begun to address these challenges in order to tackle large-scale classification tasks. by bringing together the work of these two communities, we hope to stimulate the cross-pollination of ideas and methods among different signal processing communities.
emotion recognition from speech: putting asr in the loop. this paper investigates the automatic recognition of emotion from spoken words by vector space modeling vs. string kernels which have not been investigated in this respect, yet. apart from the spoken content directly, we integrate part-of-speech and higher semantic tagging in our analyses. as opposed to most works in the field, we evaluate the performance with an asr engine in the loop. extensive experiments are run on the fau aibo emotion corpus of 4k spontaneous emotional child-robot interactions and show surprisingly low performance degradation with real asr over transcription-based emotion recognition. in the result, bag of words dominate over all other modeling forms based on the spoken content.
design of robust superdirective beamformers as a convex optimization problem. broadband data-independent beamforming designs aiming at constant beamwidth often lead to superdirective beamformers for low frequencies, if the sensor spacing is small relative to the wavelengths. superdirective beamformers are extremely sensitive to spatially white noise and to small errors in the array characteristics. these errors are nearly uncorrelated from sensor to sensor and affect the beamformer in a manner similar to spatially white noise. hence the white noise gain (wng) is a commonly used measure for the robustness of beamformer designs. in this paper, we present a method which incorporates a constraint for the wng into a least-squares beamformer design and still leads to a convex optimization problem that can be solved directly, e.g. by sequential quadratic programming. the effectiveness of this method is demonstrated by design examples.
image deblocking using dual adaptive fir wiener filter in the dct transform domain. blocking artifacts exist in images and video sequences compressed to low bit rates using block discrete cosine transform (dct) compression standards. in order to reduce blocking artifacts, a novel dct domain technique is presented in this paper. firstly, a new fir wiener filter which exploits the dependence of neighboring dct coefficients based on the linear minimum mean-square-error (lmmse) criterion is proposed. then we apply the new fir wiener filter twice in a dual adaptive filtering structure to restore each quantized dct coefficient. in addition, an efficient parameter estimation method is proposed for the designed filter. experimental results show that the performance of the proposed method is comparable to the state-of-the-art methods but has low computational complexity.
optimal transmission codebook design in fading channels for the decentralized estimation in wireless sensor networks. in this paper, we design the near optimal transmission codebook for decentralized estimation in wireless sensor networks with uniform quantizations and digital communications over orthogonal rayleigh fading channels. we start from deriving the maximum likelihood estimator (mle) for arbitrary transmission codebook with known and unknown channel state information (csi) at the fusion center (fc). because the mle is not a convex problem in the system we considered, it is not trivial to obtain an analytical expression of either its mean square error or cramer-rao lower bound (crlb). by analyzing the likelihood function, we convert the optimal transmission codebook design minimizing the crlb to a two-stage optimization problem, where the problem in each stages is convex. it is shown that the estimation accuracy with our designed codebooks and mle is superior to that with available transmission schemes. the proposed codebook suggests that the sensors should use orthogonal codes to transmit different observations for unknown csi, while the optimal codebook for known csi is not orthogonal.
a new hardware implementation of the h.264 8×8 transform and quantization. h.264/avc is the most powerful technology in video compression/transmission area because of its high coding efficiency and robustness. in this paper, we propose a new hardware architecture of 8×8 integer transform and quantization for h.264 which promises very low resource utilization. in the architecture, each pixel is processed one by one on a simplified pipeline without multiplication. thus, redundant modules, which are used for block-based or row-based parallel processing, can be reduced. experimental results show that it can reduce resource usage 30% compared to previously proposed models. it can be used for mobile applications. it covers a wide range of parameters as well.
experimenting with a global decision tree for state clustering in automatic speech recognition systems. in modern automatic speech recognition systems, it is standard practice to cluster several logical hidden markov model states into one physical, clustered state. typically, the clustering is done such that logical states from different phones or different states can not share the same clustered state. in this paper, we present a collection of experiments that lift this restriction. the results show that, for aurora 2 and aurora 3, much smaller models perform as least as well as the standard baseline. on a timit phone recognition task, we analyze the tying structures introduced, and discuss the implications for building better acoustic models.
improving multi-lattice alignment based spoken keyword spotting. in previous work, we showed that using a lattice instead of the 1-best path to represent both the query and the utterance being searched is beneficial for spoken keyword spotting. in this paper, we introduce several techniques that further improve our multi-lattice alignment approach, including edit operation modeling and supervised training of the conditional probability table, something which cannot be directly trained by traditional maximum likelihood estimation. experiments on timit show that the proposed methods significantly improve the performance of spoken keyword spotting.
sparse beamforming for active underwater electrolocation. weakly electric fish have the ability to navigate and locate prey in the dark using a unique weak electrosense system. imitating that ability of electric fish, we develop an electric-field sensing system capable of high-resolution imaging of the surrounding environment, by use of a novel beamforming technique that exploits the sparsity of sources in a scanned space. both simulation and experimental results show that the sparse beamforming technique accurately images not only a single object but also multiple objects with highly correlated signals.
top-down image segmentation using the mumford-shah functional and level set image representation. a top-down image segmentation method is proposed in this paper, utilizing level set image representation and the piecewise-constant mumford-shah functional. the method achieves top-down hierarchical segmentation by taking advantage of the tree structure provided by level set image representation. the piecewise-constant mumford-shah functional is utilized in the proposed method to determine if each node in the tree segments the image. experimental results show that this method is able to segment complicated real images. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
optimal design of hybrid filterbank analog-to-digital converters using input statistics. the hybrid filterbank architecture permits implementing accurate, high speed analog-to-digital converters. however, its design is technically involved since perfect reconstruction of the desired samples cannot be achieved in general. in this paper we propose a design method which generalizes existing approaches by dropping the bandlimited assumption on the input signal. the design minimizes the power of the reconstruction error in the samples, for a given input signal power spectrum. we discuss the use of blind techniques to estimate the analysis filterbank parameters as well as the input power spectrum, and we present simulation results to demonstrate the clear advantage of the proposed design, even under input spectrum uncertainties.
a parallel architecture for 3gpp2/umb turbo interleavers. in this paper, an efficient architecture for a parallel pruned turbo interleaver for 3gpp2/umb physical layer standard [1] is presented. turbo interleaving in umb turbo codes is based on filling a 2d array row by row, interleaving each row using a linear congruential sequence, bit-reversing the order of the rows, and then reading the interleaved addresses column by column. pruning creates a serial bottleneck since the interleaved address of a linear address x is a function of the number of pruned addresses up to x. an architecture based on the parallel lookahead pruned interleaving algorithm proposed in [2] is presented. the algorithm breaks this dependency and interleaves any address in o(log2 x) steps by enabling a parallel turbo interleaver design with a desired degree of parallelism. the architecture can be implemented efficiently in hardware using basic arithmetic building blocks.
detection of stop landmarks using gaussian mixture modeling of speech spectrum. perception of speech under adverse listening conditions may be improved by processing it to incorporate properties of clear speech. it needs automated detection of stop landmarks and enhancement of bursts and transition segments. a technique for accurate detection of stop landmarks in continuous speech based on parameters derived from gaussian mixture modeling of log magnitude spectrum, a voicing onset-offset detector, and a spectral flatness measure is presented. applying the technique on sentences from the timit database resulted in burst detection rates of 98, 97, 95, 90, and 73 % at temporal accuracies of 30, 20, 15, 10, and 5 ms respectively.
secure exp-golomb coding using stream cipher. in this paper, we propose a secure exp-golomb coding scheme by incorporating with a stream cipher. different from the traditional case of using stream cipher where the key stream is directly xored with the plaintext, we here use the key stream to control the switching between two coding conventions (leading zeros and leading ones). security analysis results show that the proposed system can provide high level of security with the same coding efficiency and negligible additional cost, compared with a regular exp-golomb coding. this scheme could potentially be applied to the state-of-the-art multimedia compression systems, e.g., h. 264, to offer security features.
combining discriminative re-ranking and co-training for parsing mandarin speech transcripts. discriminative reranking has been able to significantly improve parsing performance, and co-training has proven to be an effective weakly supervised learning algorithm to bootstrap parsers from a small in-domain seed labeled corpus using a large amount of unlabeled in-domain data. in this paper, we present systematic investigations on combining discriminative reranking and co-training, including co-training reranked parsers and co-training rerankers. we show that combining discriminative reranking and co-training could improve the f-measure by 1.8%-2% absolute compared to co-training two state-of-the-art chinese parsers without reranking, for parsing mandarin broadcast news and conversation transcripts. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
grouping motion trajectories. we present a method to group trajectories of moving objects extracted from real-world surveillance videos. the trajectories are first mapped into a low dimensionality feature space generated through linear regression. next the regression coefficients are clustered by a gaussian mixture model initialized by k-means for improved efficiency. the model selection problem is solved with bayesian information criterion that penalizes models with high complexity. we demonstrate the proposed approach on both synthetic and real-world scenes. experimental results show that the proposed clustering method outperforms k-means and mixture of regression models, while also reducing the computational complexity compared to the latter.
an improved satd-based intra mode decision algorithm for h.264/avc. in the previous work [3] we presented a satd-based intra mode decision algorithm for h.264/avc to reduce the computational complexity, based upon satd coefficients. in this paper, we extend the previous work and propose an improved satd-based intra mode decision, which uses low-frequency components to provide local characteristics for intra mode selection. the experimental results reveal that our proposed algorithm can achieve significant reduction of computation time compared to the reference program, while still maintaining good coding performance. the proposed algorithm is also compared with two distinct algorithms and the results indicate that the proposed algorithm brings out higher reduction in computation that these two algorithms.
probabilistic matrix tri-factorization. nonnegative matrix tri-factorization (nmtf) is a 3-factor decomposition of a nonnegative data matrix, x ≈ usv┬, where factor matrices, u, s, and v , are restricted to be nonnegative as well. motivated by the aspect model used for dyadic data analysis as well as in probabilistic latent semantic analysis (plsa), we present a probabilistic model with two dependent latent variables for nmtf, referred to as probabilistic matrix tri-factorization (pmtf). each latent variable in the model is associated with the cluster variable for the corresponding object in the dyad, leading the model suited to co-clustering. we develop an em algorithm to learn the pmtf model, showing its equivalence to multiplicative updates derived by an algebraic approach. we demonstrate the useful behavior of pmtf in a task of document clustering. moreover, we incorporate the likelihood in the pmtf model into existing information criteria so that the number of clusters can be detected, while the algebraic nmtf cannot.
recursive least-squares decision-directed tracking of doubly-selective channels using exponential basis models. we present a decision-directed tracking approach to doubly-selective channel estimation exploiting the complex exponential basis expansion model (ce-bem). the time-varying nature of the channel is well captured by the ce-bem while the time-variations of the (unknown) bem coefficients are likely much slower than those of the channel. we track the bem coefficients via the exponentially-weighted recursive least-squares (rls) algorithm, aided by symbol decisions from a decision-feedback equalizer (dfe). simulation examples demonstrate its superior performance over an existing subblock-wise channel tracking scheme.
modified filtered-x dichotomous coordinate descent recursive affine projection algorithm. in this paper, we propose a new multichannel filtered-x affine projection algorithm based on dichotomous coordinate descent (dcd) iterations for active noise control (anc) systems. it includes a fast recursive filtering procedure with the filter update incorporated in the dcd iterations. it is shown that the proposed algorithm has a lower complexity, and superior convergence properties than the multichannel filtered-x lms algorithm. also, it compares favorably to a previously published dcd based algorithm for anc systems.
structured variational methods for distributed inference in wireless ad hoc and sensor networks. in this paper, a variational message passing framework is proposed for markov random fields, which is computationally more efficient and admits wider applicability compared to the belief propagation algorithm. based on this framework, structured variational methods are explored to take advantage of both the simplicity of variational approximation (for inter-cluster processing) and the accuracy of exact inference (for intra-cluster processing). its performance is elaborated on a gaussian markov random field, through both theoretical analysis and simulation results.
idempotent h.264 intraframe multi-generation coding. this paper studies the idempotence of h.264 intraframe multi-generation coding. we analyze the h.264 transform and quantization and reveal that for some quantization parameters there always exists at least one clipping compensation matrix to make the h.264 intraframe multi-generation coding idempotent as long as the same prediction mode and the same quantization parameter are selected for each coding generation. in addition, an idempotent h.264 intraframe multi-generation coding procedure is presented.
band clustering and selection and decision fusion for target detection in hyperspectral imagery. a band clustering and selection approach based on a hyperspectral measure, spectral information divergence (sid) is presented in this paper. hyperspectral image data is analyzed for target detection. hyperspectral image data and spectral signatures of the targets are used to measure the sid. virtual dimensionality (vd) is used to select optimal number of bands. for endmember extraction, vertex component analysis (vca) is used. for decision fusion a new approach based on spectral discriminatory entropy (sde) is proposed. a comparative study is conducted to show the effectiveness of new approach of band clustering and selection. decision fusion is also compared with full band and individual sid detection schemes.
modeling instantaneous intonation for speaker identification using the fundamental frequency variation spectrum. in recent years, the field of automatic speaker identification has begun to exploit high-level sources of speaker-discriminative information, in addition to traditional models of spectral shape. these sources include pronunciation models, prosodic dynamics, pitch, pause, and duration features, phone streams, and conversational interaction. as part of this broader thrust, we explore a new frame-level vector representation of the instantaneous change in fundamental frequency, known as fundamental frequency variation (ffv). the ffv spectrum consists of 7 continuous coefficients, and can be directly modeled in a standard gaussian mixture model (gmm) framework. our experiments indicate that ffv features contain useful information for discriminating among speakers, and that model-space combination of ffv and cepstral features outperforms cepstral features alone. in particular, our results on 16khz wall street journal data show relative reductions in error rate of 54% and 40% for female and male speakers, respectively.
robust cross-race gene expression analysis. this paper develops a bayesian network (bn) predictor to profile cross-race gene expression data. cross-race studies face more data variability than single-lab studies. our design handles this problem by using the bn framework. in addition, unlike existing methods that unrealistically assume independent genes, our bn approach can capture the dependencies among genes. existing bn algorithms in biomedicine applications quantize data, leading to information loss; we adopt linear gaussian model to keep the data intact, so our resulting model is more reliable. the application of our bn predictor to a lung adenocarcinoma study shows high prediction accuracy, and performance evaluation demonstrates our gene signature agreeable with those reported in the literature. our tool has a promising potential in finding disease biomarkers common to multiple races.
the australian english speech corpus for in-car speech processing. the australian in-car speech corpus is a multi-channel recording of a series of prompts from an in-car navigation task collected over a range of speakers in a variety of driving conditions. its purpose is to provide a significant resource of speech data appropriate for investigating speech processing needs in the adverse environment of a car. utterances spoken by 50 speakers were collected in seven different driving conditions, providing the foundation for investigation into noisy, speaker-independent speech processing. speech recognition experiments are performed to validate the data, to provide baseline results for in-car speech recognition research, and to show that this data can improve speech recognition performance under adverse in-car conditions for australian english when adapting from american english acoustic models.
a bayesian approach to spectrum sensing, denoising and anomaly detection. this paper deals with the problem of discriminating samples that contain only noise from samples that contain a signal embedded in noise. the focus is on the case when the variance of the noise is unknown. we derive the optimal soft decision detector using a bayesian approach. the complexity of this optimal detector grows exponentially with the number of observations and as a remedy, we propose a number of approximations to it. the problem under study is a fundamental one and it has applications in signal denoising, anomaly detection, and spectrum sensing for cognitive radio. we illustrate the results in the context of the latter.
voice search of structured media data. this paper addresses the problem of using unstructured queries to search a structured database in voice search applications. by incorporating structural information in music metadata, the end-to-end search error has been reduced by 15% on text queries and up to 11% on spoken queries. based on that, an hmm sequential rescoring model has reduced the error rate by 28% on text queries and up to 23% on spoken queries compared to the baseline system. furthermore, a phonetic similarity model has been introduced to compensate speech recognition errors, which has improved the end-to-end search accuracy consistently across different levels of speech recognition accuracy.
learning to maximize signal-to-noise ratio for reverberant speech segregation. monaural speech segregation in reverberant environments is a very difficult problem. we develop a supervised learning approach by proposing an objective function that directly relates to the computational goal of maximizing signal-to-noise ratio. the model trained using this new objective function yields significantly better results for time-frequency unit labeling. in our segregation system, a segmentation and grouping framework is utilized to form reliable segments under reverberant conditions and organize them into streams. systematic evaluations show very promising results.
voxel selection in fmri data analysis: a sparse representation method. this paper proposes an iterative sparse representation-based algorithmfor voxel selection in functionalmagnetic resonance imaging (fmri) data. the output of the algorithm is a sparse weight vector, of which the magnitude of each entry represents the significance of its corresponding voxel with respect to mental tasks or stimulus. to demonstrate the validity of our algorithm and illustrate its application, we apply this algorithm to the pittsburgh brain activity interpretation competition (pbaic) 2007 fmri data set for selecting the voxels which are the most relevant to the tasks of the subjects. compared with three baseline methods, general linear model (glm)-based statistical parametric mapping (spm), correlation method and mutual information method, our method shows satisfactory performance for voxel selection.
a robust harmony structure modeling scheme for classical music opus identification. a robust algorithm to model the harmony structure of a music piece is proposed. the harmony structure is extracted directly from a music audio signal using a second-order statistic of chroma feature vectors. the method is experimentally shown to be robust against the degradation of chroma feature vectors due to noisy pitch estimation in our classical music opus identification evaluation. to analyze the effects of the noisy pitch estimation, we propose a noise model that describes difference between the oracle chroma feature vectors as obtained from a symbolic representation and those extracted from the rendered audio signal. the results suggest that the harmony structure modeling scheme employing the covariance matrix is more robust than the alternative investigated second-order statistics. the results also show that the proposed method obtains 84.3% accuracy with the symbolic representations and 72.0% with the synthesized audio data, which suggest that the proposed harmony structure modeling method has room for further improvement by addressing the signal processing challenges of pitch extraction, or through employing more robust features.
recent improvements of probability based prosody models for unit selection in concatenative text-to-speech. the work presented in this paper is subsequent to the paper “probability based prosody model for unit selection” which was published in icassp'2004. in the improved probability prosody model for corpus based concatenative text-to-speech (tts), likelihood is replaced with posterior probability in the cost functions which conduct the following step, unit selection. objective and subjective experiments show that posterior probability has obvious advantages over likelihood on robustness, flexibility and overall quality.
billiards wizard: a tutoring system for broadcasting nine-ball billiards videos. in this work, we propose a framework to build a billiards tutoring system based on broadcasting nine-ball video analysis. a robust table detection module is developed by mapping the displayed video frames to a predefined billiard table model. in addition, we detect balls and trace their positions at every time instant. the real-world spatial relationships between the table and the balls are used to provide the aiming and position play suggestions. ball position information is also utilized to distinguish each play into corresponding event by a rule-based method. the experimental results are encouraging and are more comprehensive than existing works of billiards video analysis.
risk-distortion analysis for video collusion attack. collusion attack is a cost-effective attack against digital fingerprint. to develop an efficient collusion-resistant fingerprint scheme, it is very important for the detector to study the behavior of the colluders and the performance of collusion attack. although several prior works have been proposed in the literature to analyze the performance of collusion attack, few effort has been made to explicitly study the relationship between risk, i.e., the probability of the colluders to be detected, and distortion of collusion attack. in this paper, we investigate the risk-distortion relationship of the linear video collusion attack with gaussian fingerprint. we formulate the optimal linear collusion attack as an optimization problem, where the colluders try to minimize the distortion subject to a risk constraint. for any fixed risk constraint, the optimal distortion can be found using numerical optimization methods. by varying the risk constraint, we can obtain the risk-distortion model. we also conduct experiments to verify the proposed risk-distortion model using real video data.
a joint decoding algorithm for multiple-example-based addition of words to a pronunciation lexicon. we propose an algorithm that enables joint viterbi decoding of multiple independent audio recordings of a word to derive its pronunciation. experiments show that this method results in better pronunciation estimation and word recognition accuracy than that obtained either with a single example of the word or using conventional approaches to pronunciation estimation using multiple examples.
long-time span acoustic activity analysis from far-field sensors in smart homes. smart homes for the aging population have recently started attracting the attention of the research community. one of the problems of interest is this of monitoring the activities of daily living (adls) of the elderly, in order to help identify critical problems, aiming to improve their protection and general well-being. in this paper, we report on our initial attempts to recognize such activities, based on input from networks of far-field microphones distributed inside the home. we propose two approaches to the problem: the first models the entire activity, which typically covers long time spans, with a single statistical model, for example a hidden markov model (hmm), a gaussian mixture model (gmm), or gmm super-vectors in conjunction with support vector machines (svms). the second is a two-step approach: it first performs acoustic event detection (aed) to locate distinctive events, characteristic of the adls, and it is subsequently followed by a post-processing stage that employs activity-specific language models (lms) to classify the output sequences of detected events into adls. experiments are reported on a corpus containing a small number of acted adls, collected as part of the netcarity integrated project inside a two-room smart home. our results show that svm gmm supervector modeling improves six-class adl classification accuracy to 76%, compared to 56% achieved by the gmms, while also outperforming hmms by 8% absolute. preliminary results from lm scoring of acoustic event sequences are comparable to those from gmms on a three-class adl classification task.
a fast and efficient algorithm for low rank matrix recovery from incomplete observations. minimizing the rank of a matrixx over certain constraints arises in diverse areas such as machine learning, control system and is known to be computationally np-hard. in this paper, a new simple and efficient algorithm for solving this rank minimization problem with linear constraints is proposed. by using gradient projection method to optimize s while consecutively updating matrices u and v (where x = usvt ) in combination with the use of an approximation function for l0-norm of singular values [1], our algorithm is shown to run significantly faster with much lower computational complexity than general-purpose interior-point solvers, for instance, the sedumi package [2]. in addition, the proposed algorithm can recover the matrix exactly with much fewer measurements and is also appropriate for large-scale applications.
transcoding based robust streaming of compressed video. a variety of techniques have been proposed to enhance the error robustness of the video streaming system. however, most of them improves the error resilience during compression rather than after compression. in this paper, we propose a novel transcoding based scheme called lossless inter frame transcoding (lift) scheme to improve the error resilience of existing compressed video stream. in the lift scheme, inter coded blocks are selectively transcoded into new kind of blocks called ‘l-block’. at the decoder, the l-block can be transcoded back to the original p-block when the prediction is available and can also be robustly decoded as i-block when the prediction is unavailable. by offline transcoding and online adjusting the ratio of p-blocks and l-blocks, the proposed streaming server achieves error robustness scalability. experimental results demonstrate the correctness and effectiveness of the proposed method.
structured least squares with bounded data uncertainties. in many signal processing applications the core problem reduces to a linear system of equations. coefficient matrix uncertainties create a significant challenge in obtaining reliable solutions. in this paper, we present a novel formulation for solving a system of noise contaminated linear equations while preserving the structure of the coefficient matrix. the proposed method has advantages over the known structured total least squares (stls) techniques in utilizing additional information about the uncertainties and robustness in ill-posed problems. numerical comparisons are given to illustrate these advantages in two applications: signal restoration problem with an uncertain model and frequency estimation of multiple sinusoids embedded in white noise.
a global optimization framework for meeting summarization. we introduce a model for extractive meeting summarization based on the hypothesis that utterances convey bits of information, or concepts. using keyphrases as concepts weighted by frequency, and an integer linear program to determine the best set of utterances, that is, covering as many concepts as possible while satisfying a length constraint, we achieve rouge scores at least as good as a rouge-based oracle derived from human summaries. this brings us to a critical discussion of rouge and the future of extractive meeting summarization.
color extended visual cryptography using error diffusion. this paper introduces a color visual cryptography encryption method that produces meaningful color shares via visual information pixel (vip) synchronization and error diffusion halftoning. vip synchronization retains the positions of pixels carrying visual information of original shares throughout the color channels and error diffusion generates shares pleasant to human eyes. comparisons with previous approaches show the superior performance of the new method.
you are fired! nonverbal role analysis in competitive meetings. this paper addresses the problem of social interaction analysis in competitive meetings, using nonverbal cues. for our study, we made use of “the apprentice” reality tv show, which features a competition for a real, highly paid corporate job. our analysis is centered around two tasks regarding a person's role in a meeting: predicting the person with the highest status and predicting the fired candidates. the current study was carried out using nonverbal audio cues. results obtained from the analysis of a full season of the show, representing around 90 minutes of audio data, are very promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words.
multi-flow attack resistant watermarks for network flows. in this work we present a multi-flow attack resistant interval centroid based watermarking (mar-icbw) scheme for network flows. our proposed scheme can withstand the newly introduced multi-flow watermarking attack that defeats the state-of-the-art interval-based network flow watermarking schemes. multi-flow attack uses the dependent correlations among the flows marked with the same watermark to recover the secret parameters, and remove the watermark from a flow. the attack can be effective even if different flows are marked with different values of a watermark. mar-icbw survives the attack by virtue of randomizing the location of the embedded watermark across multiple flows and therefore, effectively removing the correlations between the flows. while we represent our counter measure to multi-flow attack in terms of an improved version of icbw, the same methodology can be used to strengthen other interval-based flow watermarking schemes.
energy-constrained discriminant analysis. dimensionality reduction algorithms have become an indispensable tool for working with high-dimensional data in classification. linear discriminant analysis (lda) is a popular analysis technique used to project high-dimensional data into a lower-dimensional space while maximizing class separability. although this technique is widely used in many applications, it suffers from overfitting when the number of training examples is on the same order as the dimension of the original data space. when overfitting occurs, the direction of the lda solution can be dominated by low-energy noise and therefore the solution becomes non-robust to unseen data. in this paper, we propose a novel algorithm, energy-constrained discriminant analysis (ecda), that overcomes the limitations of lda by finding lower dimensional projections that maximize inter-class separability, while also preserving signal energy. our results show that the proposed technique results in higher classification rates when compared to comparable methods. the results are given in terms of sar image classification, however the algorithm is broadly applicable and can be generalized to any classification problem.
multidimensional localization of multiple sound sources using averaged directivity patterns of blind source separation systems. in this paper, we propose a versatile acoustic source localization framework exploiting the self-steering capability of blind source separation (bss) algorithms. we provide a way to produce an acoustical map of the scene by computing the averaged directivity pattern of bss demixing systems. since bss explicitly accounts for multiple sources in its signal propagation model, several simultaneously active sound sources can be located using this method. moreover, the framework is suitable to any microphone array geometry, which allows application for multiple dimensions, in the near field as well as in the far field. experiments demonstrate the efficiency of the proposed scheme in a reverberant environment for the localization of speech sources.
interpolation of head-related transfer functions by spatial linear prediction. head-related transfer functions (hrtfs) are essential for creating a virtual sound source when sound waves are transmitted through headphones. the measurement of hrtfs is a complicated and time-consuming task. therefore, the interpolation of hrtfs is crucial for virtual auditory display systems in which both listeners and sound objects are likely to move in a virtual auditory space. in this study, hrtfs are measured with a high spatial resolution in order to develop an effective interpolation method. an analysis of hrtfs indicates that the functions exhibit periodicity in amplitude along the azimuthal angle. the optimum filter coefficients required to interpolate hrtfs from several functions measured along multiple azimuthal directions are derived. computer simulations indicate that in comparison to conventional methods, the proposed method yields less estimation error in the interpolation of hrtfs. listening tests indicate that the proposed method can provide better perception of virtual sound.
gaussian backend design for open-set language detection. this paper proposes a new approach to the challenging open-set language detection task. most state-of-the-art approaches make use of data sources with several out-of-set languages to model such languages. in the proposed approach, no additional data from out-ofset languages is required, only date from the target languages is used. experiments are conducted using the lre-05 and the lre-07 evaluation data sets with the 30s condition. a cavg of 4.5% and 3.4% is obtained on these data set, respectively. these results are comparable with other reported results.
speaker dependency of spectral features and speech production cues for automatic emotion classification. spectral and excitation features, commonly used in automatic emotion classification systems, parameterise different aspects of the speech signal. this paper groups these features as speech production cues, broad spectral measures and detailed spectral measures and looks at how they differ in their performance in both speaker dependent and speaker independent systems. the extent of speaker normalisation on these features is also considered. combinations of different features are then compared in terms of classification accuracies. evaluations were conducted on the ldc emotional speech corpus for a fiveclass problem. results indicate that mfccs are very discriminative but suffer from speaker variability. further, results suggest that the best front end for a speaker independent system is a combination of pitch, energy and formant information.
adaptive lifting scheme-based method for joint coding 3d-stereo images with luminance correction and optimized prediction. this paper proposes a new adaptive scheme for stereo image coding . the original left and right images are jointly coded in order to exploit the high correlation between the two images for a lossless coding. our goal is to design an efficient transform that reduces the existing redundancy in the stereo pair. this approach is inspired by the lifting scheme (ls). first, illumination change compensation has been made. secondly, the prediction filtering is locally adapted and is based on local horizontal and vertical gradient information. in the sense that small gradient evokes predictability in the same direction. the coefficients of the predictor are then optimized. experimental results show improvement in term of performance and complexity compared to other proposed methods.
robust 3d modeling from silhouette cues. we consider the problem of 3d modeling under the environments where colors of the foreground objects are similar to the background, which poses a difficult problem of foreground and background classification. a purely image-based algorithm is adopted in this paper, with no prior information about the foreground objects. we classify foreground and background by fusing the information at the pixel and region levels to obtain the similarity probability map, followed by a bayesian sensor fusion framework to infer the space occupancy grid. the estimation of the occupancy allows incremental updating once a new observation is available, and the contribution of each observation can be adjusted according to its reliability. finally, three parameters in the algorithm are analyzed in detail and experiments show the effectiveness of this method.
linear receivers for frequency-selective mimo channels with redundant linear precoding can achieve full diversity. since the introduction of the diversity-multiplexing tradeoff (dmt) by zheng and tse for ml reception in frequency-flat mimo channels, some results have been obtained also for the dmt of frequency-selective mimo channels and for the dmt of suboptimal receivers such as linear (les) and decision-feedback equalizers (dfes) for frequency-selective simo channels or frequency-flat mimo channels. we have recently extended these results to the case of linear receivers for frequency-selective mimo channels. however, the diversity properties of linear receivers turn out to be fairly catastrophic. in this paper we show that full diversity can be restored by the introduction of a convolutive linear mimo precoding scheme that we showed earlier to allow to attain the optimal dmt for ml or dfe detection (in the frequency-flat case). the precoder needs to be used with a moderate amount of redundancy in the form of zero-padding, and with a mmse design for the linear equalizer. a mmse-zf design also benefits substantially from the precoding. the proposed scheme is a significant extension of an earlier siso result by tepelenlioglu to the mimo case.
robust discriminative keyword spotting for emotionally colored spontaneous speech using bidirectional lstm networks. in this paper we propose a new technique for robust keyword spotting that uses bidirectional long short-term memory (blstm) recurrent neural nets to incorporate contextual information in speech decoding. our approach overcomes the drawbacks of generative hmm modeling by applying a discriminative learning procedure that non-linearly maps speech features into an abstract vector space. by incorporating the outputs of a blstm network into the speech features, it is able to make use of past and future context for phoneme predictions. the robustness of the approach is evaluated on a keyword spotting task using the humaine sensitive artificial listener (sal) database, which contains accented, spontaneous, and emotionally colored speech. the test is particularly stringent because the system is not trained on the sal database, but only on the timit corpus of read speech. we show that our method prevails over a discriminative keyword spotter without blstm-enhanced feature functions, which in turn has been proven to outperform hmm-based techniques.
distance blurring for space-variant image coding. we present a novel selective blurring algorithm that mimics the optical distance blur effects that occur naturally in cameras and eyes. the proposed algorithm provides a realistic simulation of distance blurring, with the desirable properties of aiming to mimic occlusion effects as occur in natural blurring, and of being able to handle any number of blurring and occlusion levels with the same order of computational complexity. we have performed subjective experiments to compare the perceived quality of distance blurred images with that of foveation-filtered images under equivalent conditions, when both are used as space-variant prefiltering stages prior to a jpeg encoder. the results show that the distance-based blurring was significantly preferable to the foveation blurring for four out of nine test images, whereas a significant converse preference was found for only one test image.
a hierarchical grid feature representation framework for automatic image annotation. we propose a hierarchical-grid (hg) feature analysis framework for representing images in automatic image annotation (aia). we explore the properties of codebooks constructed with different-sized grids in image sub-blocks, and co-occurrence relationship between vq codewords constructed from different grid systems. the proposed hg approach is evaluated on the trecvid 2005 data set using classifiers obtained with maximal figure-of-merit discriminative training. with multi-level and cross-level grid systems incorporating bigram information within and between higher and lower grid levels, we show that the aia performance can be significantly improved. for 20 selected concepts from the 39-concept lscom-lite annotation set, we achieve a best f1 in almost all the concepts. the overall performance improvement with the combined multi-level and cross-level grid systems over the best single-size grid system in micro f1 is about 12.1%.
making chroma features more robust to timbre changes. chroma-based audio features are a well-established tool for analyzing and comparing music data. by identifying spectral components that differ by a musical octave, chroma features show a high degree of invariance to variations in timbre. in this paper, we describe a novel procedure for making chroma features even more robust to changes in timbre and instrumentation while keeping their discriminative power. our idea is based on the generally accepted observation that the lower mel-frequency cepstral coefficients (mfccs) are closely related to timbre. now, instead of keeping the lower coefficients, we will discard them and only keep the upper coefficients. furthermore, using a pitch scale instead of a mel scale allows us to project the remaining coefficients onto the twelve chroma bins. our systematic experiments show that the resulting chroma features have indeed gained a significant boost towards timbre invariance.
a fast method for classifying surface textures. surface texture classification is an important aspect of computer vision and a well studied problem. in this paper, we greatly increase speed for texture classification while maintaining accuracy. we take inspiration form past work and propose a new method for texture classification which is extremely fast due to the low dimensionality of our feature space. we extract distinctive features at a very early stage, thus removing the dependency on expensive and sensitive operations such as k-means clustering which is used by much work in this field of research. we present experimental results on the colombia-utrecht reflectance and texture database (curet), to date the most challenging dataset for texture classification, and show that our method achieves comparable classification accuracy in comparison with the state-of-the-art, but at a 10-fold increased speed.
inverse halftoning with variance classified filtering. inverse halftoning is a key technology to yield a continuous tone image from a halftone image. the main application is to make some image enhancement or further compression of halftones more feasible. many former approaches have been proposed in the literature. among these, a recent method proposed by chung and wu using edge-based lookup table achieves good image quality, where the edge feature is adopted to refine the trained look-up table (lut). however, it has three deficiencies, including 1) the edge features are limited in some predefined cases, which cannot full represent every potential possibility, 2) the lookup table grows exponentially when extreme grayscales are attempted to be recorded, and 3) the trained lookup table cannot fully include all the cases, which leaves some halftone patterns in practice have no associated output grayscale. chang et al.'s method employed one trained filter to compensate the halftone patterns that are not recorded in lut. however, one filter cannot fully characterize the full textures in an image. in this study, the halftone patterns are classified according to its variance and then used to train the corresponding filter sets, which are then employed to provide higher prediction accuracy by inner product with the corresponding halftone patterns. as documented in the experimental results, the proposed inverse halftoning provides excellent performance in image quality and memory consumption than former approaches.
adaptive coding of images via multiresolution ica. multiresolution (mr) representations have been very successful in image encoding, due to both their algorithmic performance and coding efficiency. however these transforms are fixed, suggesting that coding efficiency could be further improved if a multiresolution code could be adapted to a specific signal class. among adaptive coding methods, independent component analysis (ica) provides the best linear code by finding a linear transform with maximally independent coefficients, given a specific signal distribution. this technique, however, scales poorly with the dimensionality of the data, and has been ill-suited for large-scale image coding. we propose a hybrid method (multi-resolution ica) which derives an ica basis for each subband space produced by a given mr transform over the image class. we find that this method produces a significantly more efficient code compared to the mr transform alone. we provide both quantitative and qualitative assessments of coding performance, and illustrate improvement over standard (i.e., non-adaptive) wavelet-based representations such as that used in jpeg2000.
packetized video transmission for ofdm wireless systems with dynamic ordered subcarrier selection algorithm. in this paper, we proposed a dynamic ordered subcarrier selection algorithm (dossa) for ofdm based video transmission system. the proposed scheme is shown to achieve lower bit error rate (ber) than the previously proposed ossa by first selecting a fraction of the subcarriers with highest channel gain. the content information is then exploited in order to extend the ossa to achieve unequal error protection (uep) for packets of different importance. simulation results show that system that utilizes the proposed scheme can achieve higher psnr, especially at low snr, compared to those that use the equal error protection (eep) ossa.
array interpolation based on local polynomial approximation with application to doa estimation using weighted music. the problem of direction-of-arrival (doa) estimation using an array of sensors has received much attention for more than 3 decades. this is due to a rich interest from application areas such as radar, sonar and wireless communication channel characterization. however, high resolution doa estimation requires an accurate model of the array response. this is usually achieved by measuring the response using sources at known positions (calibration). this paper considers interpolation of the calibration measurements using knowledge of a nominal response model. standard linear interpolation is compared to an approach based on local polynomial approximation (lpa). we also derive a weighted music estimator, which is applied using error estimates from the interpolation. both lpa interpolation and weighted music are found to improve the performance, but not uniformly in all scenarios.
phonological features in discriminative classification of dysarthric speech. in an attempt to overcome problems associated with articulatory limitations and generative models, this work considers the use of phonological features in discriminative models for disabled speech. specifically, we train feed-forward and recurrent neural networks, and radial basis and sequence-kernel support vector machines to abstractions of the vocal tract, and apply these models to phone recognition on dysarthric speech. the results show relative error reduction of between 1.5% and 10.9% with this approach against standard hidden markov modeling, and increases in accuracy with speaker intelligibility across all classifiers. this work may be applied within components of assistive software for speakers with dysarthria.
temporal contrast normalization and edge-preserved smoothing on temporal modulation structure for robust speech recognition. in this paper, we propose a two-step processing algorithm which adaptively normalizes the temporal modulation of speech to extract robust speech feature for automatic speech recognition systems. the first step processing is to normalize the temporal modulation contrast (tmc) of the cepstral time series for both clean and noisy speech. the second step processing is to smooth the normalized temporal modulation structure to reduce the artifacts due to noise while preserving the speech modulation events (edges). we tested our algorithm on speech recognition experiments in additive noise condition (aurora-2j data corpus), reverberant noise condition (convolution of clean speech utterances from aurora-2j with a smart room impulse response), and noisy condition with both reverberant and additive noise (air conditioner noise in a smart room). for comparison, the etsi advanced front-end (afe) algorithm was used. our results showed that the algorithm provided: (1) for additive noise condition, 57.26% relative word error reduction (rwer) rate for clean conditional training (59.37% for afe), and 33.52% rwer rate for multi-conditional training (35.77% for afe), (2) for reverberant condition, 51.28% rwer rate (10.17% for afe) and (3) for noisy condition with both reverberant and additive noise, 71.74% rwer rate (48.86% for afe).
degraded image analysis using zernike moment invariants. in real imaging system, the observed image is usually corrupted by blurring, spatial degradations. the classical recognition methods in degraded image analysis are to obtain blur invariants based on geometric moments or complex moments. in this paper, we introduce blur invariants based on zernike moments which are orthogonal over a unit circle. both the expression of zernike moments of blurred image and the set of blur invariants based on zernike moments are presented and proved mathematically. compared with the pattern classification results of complex moments, the experimental results of zernike moment demonstrate that the proposed method performs well in object and pattern recognition.
audio-assisted trajectory estimation in non-overlapping multi-camera networks. we present an algorithm to improve trajectory estimation in networks of non-overlapping cameras using audio measurements. the algorithm fuses audiovisual cues in each camera's field of view and recovers trajectories in unobserved regions using microphones only. audio source localization is performed using stereo audio and cycloptic vision (stac) sensor by estimating the time difference of arrival (tdoa) between microphone pair and then by computing the cross correlation. audio estimates are then smoothed using kalman filtering. the audio-visual fusion is performed using a dynamic weighting strategy. we show that using a multi-modal sensor with combined visual (narrow) and audio (wider) field of view can enable extended target tracking in non-overlapping camera settings. in particular, the weighting scheme improves performance in the overlapping regions. the algorithm is evaluated in several multi-sensor configurations using synthetic data and compared with state of the art algorithm.
progressive lossless compression of medical images. this paper describes a lossless compression method for medical images that produces an embedded bit-stream, allowing progressive lossy-to-lossless decoding with l-infinity oriented rate-distortion. the experimental results show that the proposed technique produces better average lossless compression results than several other compression methods, including jpeg2000, jpeg-ls and jbig, in a publicly available medical image database containing images from several modalities.
scalable superwideband extension for wideband coding. recent trends in speech and audio codec standardization include scalability and extending the signal bandwidth beyond wideband (wb) to superwideband (swb). in this paper we introduce a swb extension for the itu-t g.718 wb codec. in the swb extension the high frequency content is generated utilizing the quantized mdct domain coefficients of the wb core, which enables low additional delay. the proposed implementation is scalable with 4 kbps layers. in the first layer two different coding modes are used depending on the input signal type. the proposed swb extension is evaluated with listening tests and complexity analysis.
extraction of cochlear processed formants for prediction of temporally localized distortions in synthesized speech. temporally localized distortions account for the most variance in subjective evaluation of coded speech signals [1, 2]. the ability to discern and decompose perceptually relevant temporally localized coding noise from other types of distortions is both of theoretical importance as well as a valuable tool for deploying and designing speech synthesis systems. the work described within, uses a physiologically motivated cochlear model to provide a trackable analysis of formant trajectories as processed by the cochlea. subsequent statistical analysis shows simple relationships between the jilter of these trajectories and temporal attributes of the diagnostic acceptability meausre (dam).
robust bayesian tracking on riemannian manifolds via fragments-based representation. recently, the covariance region descriptor [1] has been proved robust and versatile for a modest computational cost. it enables efficient fusion of different types of features. based on the covariance descriptor and the metric on riemannian manifolds, we develop a robust bayesian tracking framework via fragments-based representation in this paper. in this framework, the template object is represented by multiple image fragments or patches. every patch votes on the possible state of the object in the current frame, by comparing its covariance descriptor with the corresponding image patch model. tracking is then led by the bayesian state inference framework in which a particle filter is used for propagating sample distributions over time. the weight of each particle is formulated by combining the votes of the patches using a robust statistic. further, we extend the fast covariance computation to the bayesian tracking problem, which makes the tracking procedure more efficient. we present extensive experimental results on challenging sequences, which demonstrate the robust tracking achieved by our algorithm.
design of critically subsampled dft filter-banks with allpass polyphase filters and near-perfect reconstruction. a new design for a recursive dft analysis-synthesis filter-bank (as fb) with critical subsampling and near-perfect reconstruction is proposed. the analysis filter-bank consists of allpass polyphase filters to achieve a high frequency selectivity with a low algorithmic complexity and low signal delay. the condition for perfect reconstruction (pr) leads to either unstable or anti-causal synthesis filters. this problem is solved by stable allpass polyphase synthesis filters which are designed by analytical closed-form expressions. the first design can achieve arbitrarily small aliasing, amplitude and phase distortions in dependence of the tolerable signal delay and algorithmic complexity. the second design avoids aliasing and amplitude distortions and minimizes the phase distortions at the expense of an increased system delay. the proposed iir filter-bank possesses also a significantly lower algorithmic complexity than comparable fir filter-banks.
a novel robust kernel for applications to images. robustness is an essential issue to computer vision and pattern recognition in developing multimedia applications. in this work, we present a robust kernel approach that is highly robust against random noises and intra-class deformations. by incorporating the robust error function used in robust statistics together with a deformation-invariant distance measure, the derived robust kernel is shown to be insensitive to the influence of outliers and robust to intra-class deformations. in the experiments, we justify our robust kernel with different kernel machines with applications to handwritten digit recognition and data visualization on the usps database.
joint power allocation based on link reliability for mimo systems assisted by relay. a new optimization criterion is proposed to minimize error probability for the proposed joint optimal power allocation (pa) of the mimo systems enhanced by relay in this paper. it is proved that the cost function obtained is only convex with respect to (w.r.t.) the power parameters of the source or those of the relay separately, but not convex w.r.t. the whole parameters. in order to use convex optimization methods with high efficiency to solve this complicated problem, a tight upper bound of the sum mse (mean squared error) is derived, and employed to modify the cost function in order to obtain a convex problem. it is verified through simulation results that the proposed pa scheme outperforms the existing one.
tampering identification using empirical frequency response. with the widespread popularity of digital images and the presence of easy-to-use image editing software, content integrity can no longer be taken for granted, and there is a strong need for techniques that not only detect the presence of tampering but also identify its type. this paper focusses on tampering-type identification and introduces a new approach based on the empirical frequency response (efr) to address this problem. we show that several types of tampering operations, both linear shift invariant (lsi) and non-lsi, can be characterized consistently and distinctly by their efrs. we then extend the approach to estimate the efr for scenarios where only the final image is available. theoretical reasoning supported by experimental results verify the effectiveness of this method for identifying the type of a tampering operation.
low-power application-specific processor for fft computations. in this paper, we describe a processor architecture tailored for radix-4 and mixed-radix fft algorithms, which have lower arithmetic complexity than radix-2 algorithms. the processor is based on transport triggered architecture and several optimizations have been used to improve the energy-efficiency. the processor has been synthesized on a 130nm standard cell technology and analysis show that a programmable solution can possess energy-efficiency comparable to a fixed-function asic.
a factor automaton approach for the forced alignment of long speech recordings. this paper addresses the problem of aligning long speech recordings to their transcripts. previous work has focused on using highly tuned language models trained on the transcripts to reduce the search space. in this paper we propose the use of a factor automaton, a well known method to represent all substrings from a string. this automaton encodes a highly constrained language model trained on the transcripts. we show competitive results with n-gram models in several testing scenarios. preliminary experiments show perfect alignments at a reduced computational load and with a smaller memory footprint when compared to n-gram models.
dominant speech enhancement based on snr-adaptive soft mask filtering. in this paper, we present a snr-adaptive soft mask filter for multi-channel noisy speech enhancement. incorporating frame-by-frame spectral magnitude ratios into the time-frequency(t-f) mask filter framework, the adaptive filter can be designed robust to changing environments. experimental results show that the proposed adaptive mask filter can effectively suppress non-stationary noise components even in a closely-spaced microphone pair. moreover, the soft mask compressed with sigmoidal nonlinearity can reduce musical noises so that improved pesq values are obtained.
distributed signal subspace projection algorithms with maximum convergence rate for sensor networks with topological constraints. the observations gathered by the individual nodes of a sensor network may be unreliable due to malfunctioning, observation noise or low battery level. global reliability is typically recovered by collecting all the measurements in a fusion center which takes proper decisions. however, centralized networks are more vulnerable and prone to congestion around the sink nodes. to relax the congestion problem, decrease the network vulnerability and improve the network efficiency, it is appropriate to bring the decisions at the lowest possible level. in this paper, we propose a distributed algorithm allowing each node to improve the reliability of its own reading thanks to the interaction with the other nodes, assuming that the field monitored by the network is a smooth function. in mathematical terms, this only requires that the useful field belongs to a subspace of dimension smaller than the number of nodes. although fully decentralized, the proposed algorithm is globally optimal, in the sense that it performs the projection of the overall set of observations onto the signal subspace through an iterative decentralized algorithms, that requires minimum convergence time, for any given node coverage.
reduced-rank multiuser relaying (rr-mur) scheme for uplink cdma networks. cooperative relaying has been studied extensively in the literature to exploit spatial diversity gains by having each source transmit its messages through multiple independently fading relay paths. in multiuser systems where multiple sources may access the same set of relays simultaneously, cdma spreading techniques along with multiuser detection schemes have been proposed in the literature to eliminate multiple access interference (mai). in order for each relay to forward messages from all sources, a tremendous increase in dimensions (or spreading gain) is used to accommodate the relay transmissions. to reduce the required bandwidth or dimensions, we propose a reduced-rank multiuser relaying (rr-mur) scheme where the data received from multiple users are first compressed into lower dimensions before being retransmitted. more specifically, linear compression precoders at the relays and decoder at the destination are found by imposing a recursive joint optimization procedure with the objective of minimizing the mean square error (mmse) of the estimate at the destination. we show through numerical simulations that the rr-mur scheme outperforms the often adopted q-selection scheme in terms of increased spectral efficiency.
broadband ml estimation under model order uncertainty. the number of signals plays a crucial role in array processing. the performance of most direction finding algorithms relies strongly on a correctly specified number of signals. when this information is not available, conventional approaches apply information theoretic criteria or multiple hypothesis tests to simultaneously estimate model order and parameter. these methods are usually computationally intensive, since ml estimates are required for a hierarchy of nested models. in the previous work [1], we proposed a computationally efficient solution to avoid this full search procedure and demonstrated its feasibility by extensive simulations. here we extend [1] to broadband data, and address issues unique to the broadband case. our max-search approach computes ml estimates only for the maximally hypothesized number of signals, and selects relevant components through hypothesis testing. another novelty of this work is the reduction of indistinguishable components caused by overparameterization. our approach is based on the rank of the estimated steering matrix. numerical experiments show that despite an unknown number of signals, the proposed method achieves comparable estimation and detection accuracy as standard methods, but at much lower computational expense.
decentralized variational filtering for simultaneous sensor localization and target tracking in binary sensor networks. resource limitations in wireless sensor networks have put stringent constraints on distributed signal processing. in this paper, we propose a cluster-based decentralized variational filtering algorithm with minimum resource allocation for simultaneous sensor localization and target tracking. at each sampling instant, only one cluster of sensors is activated according to the prediction of the target state. slave sensors employ a binary proximity observation model to reduce energy consumption and minimize communication cost. based on the binary measurements between sensors and the target, activated sensors and target location estimates are interdependently improved. by adopting the variational method, the inter-cluster information exchange is reduced to one single gaussian statistic, further minimizing resource consumption in the network. since the measurement incorporation and the approximation of the filtering distribution are jointly performed by variational calculus, an effective and lossless compression is achieved compared to the classical particle filtering. effectiveness of the proposed approach is evaluated in terms of tracking accuracy and localization precision.
compressive spectral estimation for nonstationary random processes. we propose a “compressive” estimator of the wigner-ville spectrum (wvs) for time-frequency sparse, underspread, nonstationary random processes. a novel wvs estimator involving the signal's gabor coefficients on an undersampled time-frequency grid is combined with a compressed sensing transformation in order to reduce the number of measurements required. the performance of the compressive wvs estimator is analyzed via a bound on the mean square error and through simulations. we also propose an efficient implementation using a special construction of the measurement matrix.
efficient combination of likelihood recycling and batch calculation based on conditional fast processing and acoustic back-off. this paper proposes an efficient combination of state likelihood recycling and batch state likelihood calculation for accelerating acoustic likelihood calculation in an hmm-based speech recognizer. recycling and batch calculation are each based on different technical approaches, i.e. the former is a purely algorithmic technique while the latter fully exploits pc architecture, and their good acceleration performances are reported in the literatures, respectively. to accelerate the recognition process further by combining them efficiently, we introduce conditional fast processing and acoustic back-off strategies. our combination algorithm employs the conditional fast processing strategy that is conditioned by two criteria. the first potential activity criterion is used to control not only the recycling of state likelihoods at the current frame but also the precalculation of state likelihoods for several succeeding frames. the second reliability criterion and acoustic back-off are used to control the choice of recycled or batch calculated state likelihoods when they are contradictory in the combination and to prevent word accuracies from degrading. large vocabulary spontaneous speech recognition experiments using four pcs with different specifications showed that, despite the pc specification dependence, the combined acceleration technique further reduced the total recognition time on all of the pcs.
cmos compressed imaging by random convolution. we present a cmos imager with built-in capability to perform compressed sensing coding by random convolution. it is achieved by a shift register set in a pseudo-random configuration. it acts as a convolutive filter on the imager focal plane, the current issued from each cmos pixel undergoing a pseudo-random redirection controlled by each component of the filter sequence. a pseudo-random triggering of the adc reading is finally applied to complete the acquisition model. the feasibility of the imager and its robustness under noise and non-linearities have been confirmed by computer simulations, as well as the reconstruction tools supporting the compressed sensing theory.
a new look into the issue of the cramér-rao bound for delay estimation of digitally modulated signals. the cramér-rao bound (crb) with its modifications is a well known lower bound on the variance of any unbiased estimator of an unknown parameter. focusing on the estimation of the time-delay experienced by a digitally modulated signal, we first introduce an approximation of the modified cramér-rao bound (mcrb) as a function of the spectral properties of the modulated signal, irrespective of the specific format of the digital modulation. in particular, we show the equivalence of the mcrb for single carrier modulation and for multicarrier modulation. as a corollary, it is shown that multicarrier signals with uneven power distribution and/or non-contiguous frequency allocation bear a smaller mcrb than equally spaced and powered modulations.
reducing f0 frame error of f0 tracking algorithms under noisy conditions with an unvoiced/voiced classification frontend. in this paper, we propose an f0 frame error (ffe) metric which combines gross pitch error (gpe) and voicing decision error (vde) to objectively evaluate the performance of fundamental frequency (f0) tracking methods. a gpe-vde curve is then developed to show the trade-off between gpe and vde. in addition, we introduce a model-based unvoiced/voiced (u/v) classification frontend which can be used by any f0 tracking algorithm. in the u/v classification, we train speaker independent u/v models, and then adapt them to speaker dependent models in an unsupervised fashion. the u/v classification result is taken as a mask for f0 tracking. experiments using the keele corpus with additive noise show that our statistically-based u/v classifier can reduce vde and ffe for the pitch tracker tempo [1] in both white and babble noise conditions, and that minimizing ffe instead of vde results in a reduction in error rates for a number of f0 tracking algorithms, especially in babble noise.
fusion of fmri, smri, and eeg data using canonical correlation analysis. typically data acquired through imaging techniques such as functional magnetic resonance imaging (fmri), structural mri (smri), and electroencephalography (eeg) are analyzed separately. each modality records brain structure and function at different scales, and fusing information from such complementary modalities promises to provide additional insight into connectivity across brain networks and changes due to disease. recently, a number of methods have been proposed for data integration and fusion of two brain imaging modalities. we propose a new data fusion scheme based on canonical correlation analysis that enables the detection of associations across multiple modalities. our multimodal canonical correlation analysis (mcca) scheme works at the feature level using multi-set cca to determine inter-subject covariations across modalities. we apply mcca to fmri, smri, and eeg data collected from patients diagnosed with schizophrenia and healthy controls. through data collected from an auditory oddball task, we show that the fusion of multiple modalities detects more specific associations as compared to fusion of two modalities.
interval consensus: from quantized gossip to voting. we design distributed and quantized average consensus algorithms on arbitrary connected networks. by construction, quantized algorithms cannot produce a real, analog average. instead, our algorithm reaches consensus on the quantized interval that contains the average. we prove that this consensus in reached in finite time almost surely. as a byproduct of this convergence result, we show that the majority voting problem is solvable with only 2 bits of memory per agent.
a simple, efficient and near optimal algorithm for compressed sensing. when sampling signals below the nyquist rate, efficient and accurate reconstruction is nevertheless possible, whenever the sampling system is well behaved and the signal is well approximated by a sparse vector. this statement has been formalised in the recently developed theory of compressed sensing, which developed conditions on the sampling system and proved the performance of several efficient algorithms for signal reconstruction under these conditions. in this paper, we prove that a very simple and efficient algorithm, known as iterative hard thresholding, has near optimal performance guarantees rivalling those derived for other state of the art approaches.
sub-band stap for stretch processed systems. this paper considers adaptive jammer rejection algorithms applicable to wideband stretch-processed systems. specifically, sub-banding algorithms in which the received data is first pre-processed into narrow frequency bins are studied. in conventional sub-band stap, the received signal is divided into narrowband frequency bins, following which the interference is adaptively rejected in each bin. this usually requires that a different weight vector be computed for each sub-band. alternatively, the received data can be pre-processed so that every sub-band is shifted to a common central sub-band. this enables computation of a single weight vector that can be applied to all of the shifted sub-bands. simulation results are presented to assess the behavior and performance of these algorithms.
classification between normal and abnormal respiratory sounds based on maximum likelihood approach. in this paper, we have proposed a novel classification procedure for distinguishing between normal respiratory and abnormal respiratory sounds based on a maximum likelihood approach using hidden markov models. we have assumed that each inspiratory/expiratory period consists of a time sequence of characteristic acoustic segments. the classification procedure detects the segment sequence with the highest likelihood and yields the classification result. we have proposed two elaborate acoustic modeling methods: one method is individual modeling for adventitious sound periods and for breath sound periods for the detection of abnormal respiratory sounds, and the other is a microphone-dependent modeling method for the detection of normal respiratory sounds. classification experiments conducted using the former method revealed that this method demonstrated an increase of 19.1% in its recall rate of abnormal respiratory sounds as compared with the recall rate of a baseline method. it has also been revealed that the latter modeling method demonstrates an increase in its recall rate for the detection of not only normal respiratory sounds but also for abnormal respiratory sounds. these experimental results have confirmed the validity of our proposed classification procedure.
on radius control of tree-pruned sphere decoding. in this paper, we propose a novel radius control strategy for sphere decoding referred to as inter search radius control that provides further improvement of the computational complexity with minimal extra cost and negligible performance penalty. the proposed method focuses on the sphere radius control strategy when a candidate lattice point is found. for this purpose, the dynamic radius update strategy as well as the lattice independent radius selection scheme are jointly exploited. from simulations in multiple-input and multiple-output (mimo) channels, it is shown that the proposed method provides a substantial improvement in complexity with near-ml performance.
sparse approximation with an orthogonal complementary matching pursuit algorithm. this paper presents the orthogonal extension of the recently introduced complementary matching pursuit (cmp) algorithm for sparse approximation [1]. the cmp algorithm is analogous to the matching pursuit (mp) but done in the row-space of the dictionary matrix. it suffers from a similar sub-optimality as the mp. the orthogonal complementary matching pursuit algorithm (ocmp) presented here tries to remove this sub-optimality by updating the coefficients of all selected atoms at each iteration. its development from the cmp follows the same procedure as of the orthogonal matching pursuit (omp). in contrast with omp, the residual errors resulting from the ocmp may not be orthogonal to all the atoms selected up to the respective iteration. though the residual energy may increase over the omp during the first iterations, it is shown that, compared with omp, the convergence speed is increased in the subsequent iterations and the sparsity of the solution vector is improved.
postural time-series analysis using empirical mode decomposition and second-order difference plots. this paper presents a new method for analysis of center of pressure (cop) signals using empirical mode decomposition (emd). the emd decomposes a cop signal into a finite set of band-limited signals termed as intrinsic mode functions (imfs). thereafter, a signal processing technique used in continuous chaotic modeling is used to investigate the difference between experimental conditions on the summed imfs. this method is used to detect the degree of variability from a second-order difference plot, which is quantified using a central tendency measure (ctm). seventeen subjects were tested under eyes open (eo) and eyes closed (ec) conditions, with different vibration frequencies applied for the ec condition in order to provide additional sensory perturbation. this study has demonstrated an effective way to differentiate vibration frequencies by combining emd and second-order difference (sod) plots.
cepstral modulation ratio regression (cmrare) parameters for audio signal analysis and classification. in this paper we propose a new set of parameters for audio signal analysis and classification. these parameters are regressions computed on the normalized modulation spectrum of high-resolution cepstral coefficients. the parameter set is scalable in its size and gives a compact representation of the modulation content of speech and other audio signals. these parameters as well as the regression approximation error are well suited for characterizing audio signals in a unified framework. in particular we use a set of eight parameters in a speech/music/noise classification task in which we achieve a classification accuracy which compares very well with other approaches including static and dynamic mfccs.
outage-based designs for multi-user transceivers. we consider a broadcast channel with multiple antennas at the base station and single-antenna receivers, and we study transceiver design with quality of service (qos) requirements in the presence of uncertain channel state information (csi) at the transmitter. each user's qos requirement is formulated as an upper bound on the outage probability of the mean square error (mse), and we demonstrate that these constraints imply bounds on the outage of the received signal-to-interference-plus-noise-ratio. using this mse framework, we provide a unified approach to the design of non-linear and linear transceivers that minimize the transmitted power required to satisfy the qos constraints. we present three conservative design approaches that yield (deterministic) convex and efficiently-solvable design formulations that guarantee the satisfaction of the qos constraints, and we propose computationally-efficient algorithms that can reduce the level of conservatism in the initial formulations.
distributed subgradient projection algorithm for convex optimization. we consider constrained minimization of a sum of convex functions over a convex and compact set, when each component function is known only to a specific agent in a time-varying peer to peer network. we study an iterative optimization algorithm in which each agent obtains a weighted average of its own iterate with the iterates of its neighbors, updates the average using the subgradient of its local function and then projects onto the constraint set to generate the new iterate. we obtain error bounds on the limit of the function value when a constant stepsize is used.
spatial super-resolution of a diffusion field by temporal oversampling in sensor networks. we study the spatial-temporal sampling of a linear diffusion field, and show that it is possible to compensate for insufficient spatial sampling densities by oversampling in time. our work is motivated by the following issue often encountered in sensor network sampling, namely increasing the temporal sampling density is often easier and less expensive than increasing the spatial sampling density of the network. for the case of sampling a diffusion field, we show that, to achieve trade-off between spatial and temporal sampling, the spatial arrangement of the sensors must satisfy certain conditions. we provide in this paper the precise relationships between the achievable reduction of spatial sampling density, the required temporal oversampling rate, the spatial arrangement of the sensors, and the bound for the condition numbers of the resulting sampling and reconstruction procedures.
a mimo channel perturbation analysis for robust bit loading. in narrowband multiple-input multiple-output (mimo) communication systems, when the channel state information (csi) is known perfectly at the transmitter and the receiver, techniques such as waterfilling may use the singular value decomposition to separate the mimo channel into independent single-input single-output subchannels. the signal-to-noise ratios of these subchannels are easily found, and, therefore, so are the subchannel bit allocations. in practice, perfect csi is difficult to obtain. imperfect csi results in subchannel coupling and co-channel interference. in this paper, simple first-order expressions are presented for the signal and interference/noise powers for each subchannel for the imperfect csi case. these expressions may be used to obtain more realistic subchannel bit allocations, allowing for fewer channel outages. numerical simulations demonstrate the applicability and usefulness of the derived expressions.
leveraging multiple query logs to improve language models for spoken query recognition. a voice search system requires a speech interface that can correctly recognize spoken queries uttered by users. the recognition performance strongly relies on a robust language model. in this work, we present the use of multiple data sources, with the focus on query logs, in improving asr language models for a voice search application. our contributions are three folds: (1) the use of text queries from web search and mobile search in language modeling; (2) the use of web click data to predict query forms from business listing forms; and (3) the use of voice query logs in creating a positive feedback loop. experiments show that by leveraging these resources, we can achieve recognition performance comparable to, or even better than, that of a previously deploy system where a large amount of spoken query transcripts are used in language modeling.
inter-tone noise reduction in a low bit rate celp decoder. in this paper we present a novel technique to enhance music signals encoded using a low bit rate celp coder. the method is based on reduction of inter-tone quantization noise for decoded music signals without affecting the quality for speech signals. the proposed technique consists of two modules. the first module is used to discriminate between stable tonal sounds and other sounds and the second module is used to reduce the inter-tone quantization noise in the stable tonal segments. the inter-tone noise is reduced by means of spectral subtraction. the proposed method is a part of the newly standardised itu-t g.718 codec.
steady-state analysis of the normalized least mean fourth algorithm without the independence and small step size assumptions. in this work, the steady-state analysis of the normalized least mean fourth (nlmf) algorithm under very weak assumptions is investigated. no restrictions are made on the dependence between input successive regressors, the dependence among input regressor elements, the length of the adaptive filter, the distribution of noise and the filter input. moreover, in our approach, there is no restriction made on the step size value and therefore the analysis holds for all the values of the step size in the range where the nlmf algorithm is stable. the analysis is based on the effective weight deviation vector performance measure [1]. this vector is the component of weight deviation vector in the direction of the input regressor. the asymptotic time-averaged convergence for the mean square effective weight deviation, the mean absolute excess estimation error, and the mean square excess estimation error for the nlmf algorithm are derived. finally, a number of simulation results are carried out to corroborate the theoretical findings.
a simple design of space-time block codes achieving full diversity with linear receivers. orthogonal space-time block codes (ostbc) are attractive in that they can achieve full diversity and linear complexity of maximum likelihood (ml) decoding. however, the ostbc have a low symbol rate due to the limitation of the orthogonality of the code structure. most of the high-rate stbc achieve full diversity based on ml decoding at the receiver that is computationally expensive. in order to achieve full diversity with linear receivers, recently liu-zhang-wong and shang-xia introduced new stbc. in this paper, we propose a simple design of stbc which have a high rate and achieve full diversity with linear receivers. the proposed stbc are constructed by embedding alamouti codes into a toeplitz matrix. simulation results show that in comparison with some existing codes for a given codeword length the proposed stbc can give a better bit error rate (ber) performance while having a high rate.
a quality prediction model for jpeg2000-based color images. a quality prediction model is proposed for color images coded with jpeg2000. this model estimates the quality (psnr) of a color image at a given compression ratio without coding. the image activity measure as the image feature and compression ratio are taken as the input of the model. experimental results show that the prediction error is less than 1db for more than 75% images, and less than 2db for over 95% images. the computation of the prediction process is much lower than that of the compression and quality calculation.
a fast cabac rate estimator for h.264/avc mode decision. h.264/avc coders use the rate-distortion (r-d) cost function to decide the coding mode for each coding unit for better r-d tradeoff. to evaluate the r-d cost function, both the bit rate and the video quality degradation of the candidate mode must be calculated. in this paper, a fast context-adaptive binary arithmetic coding (cabac) rate estimation scheme is proposed to accelerate the rate calculation. the speed of the proposed rate estimator depends only on the number of contexts used in the coding unit. experimental results show that the proposed rate estimator reduces about 20% of the computational complexity of the r-d optimized mode decision when it is implemented as software. the entire encoder implemented as software is then accelerated by 16% with negligible degradation in the r-d performance. if implemented as hardware, the proposed scheme is expected to accelerate the rate estimation for a macroblock by 5 to 18 times faster than the conventional cabac operation.
generic video coding with abstraction and detail completion. this paper presents a generic video coding framework with the texture abstraction and completion, inspired by a strong grouping bias of local elements in gestalt psychology. abstracting imagery by grouping perceptual salience from anisotropic diffusion, it decomposes video images into two layers composing of semantic components and residual detail. the similarity between textures of abstraction layer is motivated to infer the restoration of missing detail, under the spatio-temporal variation regularity. through a motion and spatial context of moton, hence, a group of pictures (gop) is divided into key frames and abstracted frames to form the final compressed data. an abstraction refinement is tuned to improve matching of detail restoration based on bilateral filtering. the proposed approach is more generic without incurring any specific side information, and achieves up to 20% bit saving versus standard h.264 at similar visual quality levels.
the gigavision camera. we propose a new image device called gigavision camera. the main differences between a conventional and a gigavision camera are that the pixels of the gigavision camera are binary and orders of magnitude smaller. a gigavision camera can be built using standard memory chip technology, where each memory bit is designed to be light sensitive. a conventional gray level image can be obtained from the binary gigavision image by low-pass filtering and sampling. the main advantage of the gigavision camera is that its response is non-linear and similar to a logarithmic function, which makes it suitable for acquiring high dynamic range scenes. the larger the number of binary pixels considered, the higher the dynamic range of the gigavision camera will be. in addition, the binary sensor of the gigavision camera can be combined with a lens array in order to realize an extremely thin camera. due to the small size of the pixels, this design does not require deconvolution techniques typical of similar systems based on conventional sensors.
on ica of improper and noncircular sources. we provide a review of independent component analysis (ica) for complex-valued improper and noncircular random sources. an improper random signal is correlated with its complex conjugate, and a noncircular random signal has a rotationally variant probability distribution. we present methods for ica using second-order statistics, and higher-order statistics. for ica based on second-order statistics, we emphasize the key role played by the circularity coefficients, which are the canonical correlations between the source and the complex conjugate. for ica based on higher-order statistics, we show how to extend algorithms for real-valued ica to the complex domain using wirtinger calculus.
a compressive sensing approach to object-based surveillance video coding. this paper studies the feasibility and investigates various choices in the application of compressive sensing (cs) to object-based surveillance video coding. the residual object error of a video frame is a sparse signal and cs, which aims to represent information of a sparse signal by random measurements, is considered for coding of object error. this work proposes several techniques using two approaches- direct cs and transform-based cs. the techniques are studied and analyzed by varying the different trade-off parameters such as the measurement index, quantization levels etc. finally we recommend an optimal scheme for a range of bitrates. experimental results with comparative bitrates-vs-psnr graphs for the different techniques are presented
on the error exponents for detecting randomly sampled noisy diffusion processes. this paper deals with the detection of a continuous random process described by an ornstein-uhlenbeck (o-u) stochastic differential equation. randomly spaced sensors or equivalently a random time sampler which deliver noisy samples of the process are used for this detection. two types of tests are considered: either h0 refers to the presence of the noisy o-u process or h0 refers to the sole presence of noise. for any fixed false alarm probability, it is shown that the type ii error probability decreases to zero exponentially in the number of samples. the exponents, which do not depend on the false alarm probability, are characterized. this work completes former contributions that consider noiseless o-u process with a random sampling or noisy o-u processes with a regular sampling.
proportionate adaptive algorithm for nonsparse systems based on krylov subspace and constrained optimization. in this paper, we propose an efficient design of proportionality factors in the recently established algorithm named krylov-proportionate normalized least mean-square (kpnlms), which is an extention of the pnlms algorithm to nonsparse (or dispersive) unknown systems by means of a krylov subspace. the designing task takes a form of minimizing the number of iterations that is needed for an upper bound of the system mismatch to reach a specified target value. the minimization is performed under several constraints related to numerical stability, computational requirements, and nonnegativity, and its closed-form solution is derived. numerical examples demonstrate that the proposed design significantly reduces the number of iterations needed to achieve target values of system mismatch especially when a low level of system mismatch is required.
optimal linear fusion for distributed spectrum sensing via semidefinite programming. as an enabling functionality of overlay cognitive radio networks, spectrum sensing needs to reliably detect licensed signal in the band of interest. to achieve reliable sensing, we propose a linear fusion scheme for distributed spectrum sensing to combine the sensing results from multiple spatially distributed cognitive radios. the optimal linear fusion design is formulated into a nonconvex optimization problem. we show that the optimal solution of such a nonconvex problem can be solved via semi-definite programming reformulation.
multichannel speech enhancement using convolutive transfer function approximation in reverberant environments. recently, we have presented a transfer-function generalized sidelobe canceler (tf-gsc) beamformer in the short time fourier transform domain, which relies on a convolutive transfer function approximation of relative transfer functions between distinct sensors. in this paper, we combine a delay-and-sum beamformer with the tf-gsc structure in order to suppress the speech signal reflections captured at the sensors in reverberant environments. we demonstrate the performance of the proposed beamformer and compare it with the tf-gsc. we show that the proposed algorithm enables suppression of reverberations and further noise reduction compared with the tf-gsc beamformer.
speaker diarization in meeting audio. this paper describes speaker diarization system on a nist rich transcription 2007 (rt-07) meeting recognition evaluation data set for the task of multiple distant microphone (mdm). our implementation includes three components: initial clustering, non-speech removal and cluster purification. initial clusters are generated using directional of arrival (doa) information and bootstrap clustering. multiple gmm modeling for speech/non-speech classification is employed for non-speech removal component. in addition, a novel system fusion strategy using information from receiver operating curve (roc) is proposed for non-speech removal component. finally, consensus clustering approach together with iterative gmm clustering method is employed for speaker cluster purification. the system achieves the overall der of 10.81%.
the effect of language factors for robust speaker recognition. from the results of the nist speaker recognition evaluation in resent years, speaker recognition systems which are mainly developed based on english training data suffer the language gap problem, namely, the performance of non-english trails is much worse than that of english trails. this problem is addressed in this paper. based on the conventional joint factor analysis model, we enrolled in the language factors which are mean to capture the language character of each testing and training speech utterance, and compensation was carried out by removing the language factors in order to shrink the difference between languages. experiments on 2006 nist sre data show that, the language factor compensation alone can reduce the gap between the performance of english and non-english trails, and the score level combination with eigenchannels can further improve the performance of non-english trails, e.g., for female part, we observed about 19% relatively reduction in eer, when compared with eigenchannels session variability compensation alone.
generalization of specialized on-the-fly composition. in the weighted finite state transducer (wfst) framework for speech recognition, we can reduce memory usage and increase flexibility by using on-the-fly composition which generates the search network dynamically during decoding. methods have also been proposed for optimizing wfsts in on-the-fly composition, however, these operations place restrictions on the structure of the component wfsts. we propose extended on-the-fly optimization operations which can operate on wfsts of arbitrary structure by utilizing a filter composition. the evaluations illustrate the proposed method is able to generate more efficient wfsts.
evolution of social p2p networks based on the dynamics of heterogeneous multimedia peers. in this paper, we consider social peer-to-peer (p2p) networks, where peers are sharing their resources (i.e., multimedia content and upload bandwidth). in the considered p2p networks, peers are self-interested, thereby determining their resource divisions (i.e., actions) among their associated peers such that their utility (e.g., multimedia quality) is maximized. peers determine their optimal strategies for selecting their action based on a markov decision process (mdp) framework, which enables the peers to maximize their cumulative utilities. we consider heterogeneous peers that have different and limited ability to characterize their resource reciprocations using only a limited number of states. we investigate how the limited number of states impacts the resource reciprocation and the resulting multimedia quality over time. simulation results show that peers simultaneously refining their state descriptions can improve the multimedia quality in the resource reciprocation. moreover, peers prefer to interact with other peers that have higher available upload bandwidths as well as have similar capabilities for refining their number of states.
a new optimization method for reference-based quadratic contrast functions in a deflation scenario. this paper deals with the problem of blind source separation of convolutive mimo mixtures by a deflation procedure. contrast functions showing a quadratic dependence with respect to the searched parameters have recently been proposed. combined with a fast svd-based optimization technique, they proved to be very efficient for the extraction of one source signal. in this contribution, we examine how these contrast functions behave in a deflation scenario. we show that the svd-based optimization method requires a good knowledge of the filter orders due to its sensitivity on a rank estimation. to overcome the difficulty, we propose an optimal step size gradient algorithm.
nonlinear acoustic echo control using an accelerometer. a typical echo canceller uses an fir adaptive filter to estimate the impulse response of the near-end echo path. however nonlinear echo components due to the loudspeaker and driving amplifier are not captured by such an arrangement. we propose a novel scheme for nonlinear acoustic echo cancellation where an accelerometer sensor captures loudspeaker vibration and this sensor signal is used along with the error signal to adapt the adaptive filter coefficients. the accelerometer sensor is used in lieu of explicit nonlinear modeling in the echo cancelling loop and hence it is compatible with typical nlms and rls echo cancellation algorithms. experiments with an accelerometer mounted on the magnet of a hands-free kit show an echo reduction improvement by as much as 15 db in situations of nonlinear loudspeaker distortion.
a novel algorithm for calculating the qr decomposition of a polynomial matrix. a novel algorithm for calculating the qr decomposition (qrd) of polynomial matrix is proposed. the algorithm operates by applying a series of polynomial givens rotations to transform a polynomial matrix into an upper-triangular polynomial matrix and, therefore, amounts to a generalisation of the conventional givens method for formulating the qrd of a scalar matrix. a simple example is given to demonstrate the algorithm, but also illustrates two clear advantages of this algorithm when compared to an existing method for formulating the decomposition. firstly, it does not demonstrate the same unstable behaviour that is sometimes observed with the existing algorithm and secondly, it typically requires less iterations to converge. the potential application of the decomposition is highlighted in terms of broadband multi-input multi-output (mimo) channel equalisation.
decentralized dynamic spectrum allocation based on adaptive antenna array interference mitigation diversity: algorithms and markov chain analysis. decentralized dynamic spectrum allocation (dsa) that exploit adaptive antenna array interference mitigation (im) diversity at the receiver, is proposed for interference-limited environments with high level of frequency reuse. the system consists of base stations (bss) that may belong to different providers, who can optimize uplink frequency allocation to their subscriber stations (sss) to achieve the least impact of im on the useful signal, assuming no control over band allocation of other bss sharing the same bands. “selfish” and “good neighbor” decentralized dsa strategies are considered. convergence and convergence rate of the introduced techniques are investigated by means of the theory of absorbing markov chains.
robust speech feature extraction based on gabor filtering and tensor factorization. in this paper, we investigate the speech feature extraction problem in the noisy environment. a novel approach based on gabor filtering and tensor factorization is proposed. from recent physiological and psychoacoustic experimental results, localized spectro-temporal features are essential for auditory perception. we employ 2d-gabor functions with different scales and directions to analyze the localized patches of power spectrogram, by which speech signal can be encoded as a general higher order tensor. then nonnegative tensor pca with sparse constraint is used to learn the projection matrices from multiple interrelated feature subspaces and extract the robust features. experimental results confirm that our proposed method can improve the speech recognition performance, especially in noisy environment, compared with traditional speech feature extraction methods.
nonsubsampled higher-density discrete wavelet transform for image denoising. recently, a new set of dyadic wavelet frames based on oversampled filter banks is introduced that provides a higher sampling in both time and frequency, compared to the usual dyadic wavelets. this transform [1] (called hddwt) is not shift-invariant; a feature which is desirable particularly for signal denoising. in this paper we propose a new transform, referred to as nonsubsampled hddwt (ns-hddwt), which is the shift-invariant version of hddwt. the ns-hddwt filter bank is built upon iterated nonsubsampled filter banks which are derived from the hddwt filter bank in a way that is similar to the a trous algorithm. we employ hddwt and ns-hddwt for decomposition of images by performing the separable filtering. the performance of both hddwt and ns-hddwt is assessed in image denoising. experimental results show that the performance of ns-hddwt is superior to that of hddwt, and in some cases ns-hddwt outperforms powerful wavelet-based image denoising methods.
joint map adaptation of feature transformation and gaussian mixture model for speaker recognition. this paper extends our previous work on feature transformation-based support vector machines for speaker recognition by proposing a joint map adaptation of feature transformation (ft) and gaussian mixture models (gmm) parameters. in the new approach, the prior probability density functions (pdfs) of ft and gmm parameters are jointly estimated using the background data under the maximum likelihood criteria. in this way, we derive a generic prior gmm that is more compact than the universal background model due to the reduction of speaker variations. with the prior pdfs, we construct a supervector to characterize a speaker using ft and gmm parameters. we conducted experiments on nist 2006 speaker recognition evaluation (sre06) data set. the results validated the effectiveness of the joint map adaptation approach.
optimal distributed detection of multiple hypotheses using blind algorithm. in a parallel distributed detection in order to design the optimal fusion rule, the fusion center needs to have perfect knowledge of the performance of the local detectors as well as the prior probabilities of the hypotheses. such knowledge is not available in most practical cases. in this paper, we propose a blind technique for the m-ary distributed detection problem. we derive the probability mass function of the local decisions and use this result to develop maximum likelihood estimates of unknown parameters. we also derive analytically the overall detection performance for both binary and m-ary distributed detection and discuss the difference of the overall detection performance obtained using the estimated values of unknown parameters and their true values. finally, we demonstrate the applicability of our results through numerical examples.
perceptual time varying linear prediction model for speech applications. a new perceptual time varying model for non-stationary analysis of speech signals is presented. some researches have already shown that the time varying linear prediction coding (tvlpc) model that was applied to speech signals increases the recognition performance of automatic speech recognition (asr) systems. this improvement has been achieved due to the incorporation of the speech dynamics information in the model. another work, perceptual linear prediction (plp) analysis of speech, has shown that a modified estimation of the auto correlation function (acf) of stationary speech frame yields major improvement to the recognition rate. the presented model, perceptual time varying linear prediction (ptvlp) analysis of speech, adopts the perceptual concepts, of how to estimate the acf, into the tvlpc model. this research shows that the proposed ptvlp model is more accurate, robust to noise and achieves better recognition rates than plp and tvlpc over wide snr range.
self-optimizing scheme for active noise and vibration control. this paper presents a new approach to rejection of sinusoidal disturbances acting at the output of a discrete-time complex-valued linear stable plant (e.g. acoustic channel) with unknown and possibly time-varying dynamics. it is assumed that the instantaneous frequency of the sinusoidal disturbance may be slowly varying with time and that the output signal is contaminated with wideband measurement noise. it is not assumed that a reference signal, correlated with the disturbance, is available. the proposed disturbance rejection algorithm automatically adjusts its adaptation gains to the rate of system and/or disturbance variation.
novel similarity invariant for space curves using turning angles and its application to object recognition. we present a new similarity invariant signature for space curves. this signature is based on the information contained in the turning angles of both the tangent and the binormal vectors at each point on the curve. for an accurate comparison of these signatures, we define a riemannian metric on the space of the invariant. we show through relevant examples that, unlike classical invariants, the one we define in this paper enjoys multiple important properties at the same time, namely, a high discrimination level, independence of any reference point, uniqueness property, as well as a good preservation of the correspondence between curves. moreover, we illustrate how to match 3d objects by extracting and comparing the invariant signatures of their curved skeletons.
an improved signal-selective direction finding algorithm using second-order cyclic statistics. a new signal-selective direction finding algorithm which exploits the property of the cyclostationarity of incoming signals is proposed. after dimensionality reducing by projecting the observed array data onto the signal subspace, the array manifold matrix is identified by the simultaneous diagonalization structure of the matrix pencil consisting of the cyclic correlation matrix and the cyclic conjugate correlation matrix. then the direction-of-arrivals (doas) are obtained from the phase-differences of the estimated array manifold matrix. simulation results demonstrate that the proposed algorithm is superior to the cyclic-music and cyclic-esprit in terms of the root mean squares errors (rmses) of the doa estimates.
relative pitch estimation of multiple instruments. we present an algorithm based on probabilistic latent component analysis and employ it for relative pitch estimation of multiple instruments in polyphonic music. a multilayered positive deconvolution is performed concurrently on mixture constant-q transforms to obtain a relative pitch track and timbral signature for each instrument. initial experimental results on mixtures of two instruments are quite promising and show high levels of accuracy.
intensity vector direction exploitation for exhaustive blind source separation of convolutive mixtures. this article presents a technique that uses the intensity vector direction exploitation (ivde) method for exhaustive separation of convolutive mixtures. while only a four-element compact sensor array is used, multiple channels for all possible source directions are produced by exhaustive separation. singular value decomposition (svd) is then applied to determine the signal subspace and the directions of the local maxima of the signal energy. this information is then used to select the channels containing the individual sources. while the original ivde method requires the prior knowledge of the directions of sources for separation, the present method eliminates this need and achieves fully blind separation. performing svd at a post-processing stage also improves the sound quality. the method has been tested for convolutive mixtures of up to four sources and typical separation performances are given.
a phonetic feature based lattice rescoring approach to lvcsr. large vocabulary continuous speech recognition (lvcsr) systems decode the input speech using diverse information sources, such as acoustic, lexical, and linguistic. although most of the unreliable hypotheses are pruned during the recognition process, current state-of-the-art systems often make errors that are “unreasonable” for human listeners. several studies have shown that a proper integration of acoustic-phonetic information can be beneficial to reducing such errors. we have previously shown that high-accuracy phone recognition can be achieved if a bank of speech attribute detectors is used to compute a confidence score describing attribute activation levels that the current frame exhibits. in those experiments, the phone recognition system did not rely on the language model to follow their word sequence constraints, and the vocabulary was small. in this work, we extend our approach to lvcsr by introducing a second recognition step during which additional information not directly used during conventional log-likelihood based decoding is introduced. experimental results show promising performance.
constrained optimisation of 3d polygonal mesh watermarking by quadratic programming. in this paper, we propose a blind and robust watermarking method for 3d polygonal meshes by minimising the mean square error between the original mesh and the watermarked mesh under several constraints. we have formulated the problem of assigning distortions to points in a 3d mesh to a quadratic programming problem, so it can be solved reliably and efficiently. comparing with similar approaches in [1], experiments indicate the advantages of our method in resisting gaussian noise.
inferring functional cortical networks from spike train ensembles using dynamic bayesian networks. a fundamental goal in systems neuroscience is to infer the functional connectivity among neuronal elements coordinating information processing in the brain. in this work, we investigate the applicability of dynamic bayesian networks (dbn) in inferring the structure of cortical networks from the observed spike trains. dbns have unique features that make them capable of detecting causal relationships between spike trains such as modeling time-dependent relationships, detecting non-linear interactions and inferring connectivity between neurons from the observed ensemble activity. a probabilistic point process model was used to assess the performance under systematic variations of the model parameters. results demonstrate the utility of dbn in inferring functional connectivity in cortical network models.
a novel fusion-based method for expression-invariant gender classification. in this paper, we propose a novel fusion-based gender classification method that is able to compensate for facial expression even when training samples contain only neutral expression. we perform experimental investigation to evaluate the significance of different facial regions in the task of gender classification. three most significant regions are used in our fusion-based method. the classification is performed by using support vector machines based on the features extracted using two-dimension principal component analysis. experiments show that our fusion-based method is able to compensate for facial expressions and obtained the highest correct classification rate of 95.33%.
detection of sparse signals under finite-alphabet constraints. in this paper, we solve the problem of detecting the entries of a sparse finite-alphabet signal from a limited amount of data, for instance obtained by compressive sampling. while existing methods either rely on the sparsity property, the finite-alphabet property, or none of those properties to solve the under-determined system of linear equations, we capitalize on both the sparsity and the finite-alphabet features of the signal. the problem is first formulated in a bayesian framework to incorporate the prior knowledge of sparsity, which is then shown to be solvable using sphere decoding (sd) or semi-definite relaxation (sdr) for efficient boolean programming. a few toy simulations show how our method can outperform existing works.
frame bounds estimation of frequency warping operators. in this work we provide an accurate analytical estimation of the frame bounds for frequency warping operators of arbitrary shaped non-smooth warping maps. we deal with both the nonuniform fourier transform approximation and the aliasing suppressed form of the frequency warping operator. the estimation procedure is obtained by using an analytical model of the aliasing operators which has been previously introduced. the provided estimations can be used as design formulas for the parameters, such as degree of smoothness and redundancy, involved in the definition of the frequency warping operators.
space kernel analysis. in this paper, we propose a novel nonparametric modeling technique, namely space kernel analysis (ska), as a result of the definition of the space kernel. we analyze the uncertainty of ska and show that ska is subjected to the bias/variance dilemma. nevertheless, we demonstrate that, by a proper choice of the space kernel matrix, ska is able to balance between the robustness and accuracy and hence outperforms other kernel-based learning methods. the cost function of ska is derived, and it proves that ska minimizes the weighted least squared cost function whose weight matrix is diagonal and determined by the space kernel matrix. the parallels between ska and several other nonparametric modeling techniques are examined. study shows that the traditional kernel regression, general regression neural network, similarity based modeling and radial basis function network are examples of ska with specified space kernel matrices.
nonlinear distributed source-channel coding over orthogonal additive white gaussian noise channels. the problem of designing simple and energy-efficient nonlinear distributed source-channel codes is considered. by demonstrating similarities between this problem and the problem of bandwidth expansion, a structure for source-channel codes is presented and analyzed. based on this analysis an understanding about desirable properties for such a system is gained and used to produce an explicit source-channel code which is then analyzed and simulated. it is shown that the code has a substantial gain compared to a linear source-channel code.
nonlinear filtering for continuous-time systems using the linear fractional transformation model. in this paper, we propose bayesian filtering technique for continuous-time dynamical models with sampled-data measurements using the linear fractional transformation (lft) model which transforms the nonlinear state space model into an exact equivalent linear model with a simple nonlinear feedback loop. the linear model is amenable to euler discretization. simulation results demonstrate that the proposed filtering technique gives better approximation and tracking performance than the unscented kalman filter (ukf) which diverges for highly nonlinear problems.
jitter compensation in sampling via polynomial least squares estimation. sampling error due to jitter, or noise in the sample times, affects the precision of analog-to-digital converters in a significant, nonlinear fashion. in this paper, a polynomial least squares (pls) estimator is derived for an observation model incorporating both independent jitter and additive noise, as an alternative to the linear least squares (lls) estimator. after deriving this estimator, its implementation is discussed, and it is simulated using matlab. in simulations, the pls estimator is shown to improve the mean squared error performance by up to 30 percent versus the optimal linear estimator.
transforms for the motion compensation residual. the discrete-cosine-transform (dct) is the most widely used transform in image and video compression. its use in image compression is often justified by the notion that it is the statistically optimal transform for first-order markov signals, which have been used to model images. in standard video codecs, the motion-compensation residual (mc-residual) is also compressed with the dct. the mc-residual may, however, possess different characteristics from an image. hence, the question that arises is if other transforms can be developed that can perform better on the mc-residual than the dct. inspired by recent research on direction-adaptive image transforms, we provide an adaptive auto-covariance characterization for the mc-residual that shows some statistical differences between the mc-residual and the image. based on this characterization, we propose a set of block transforms. experimental results indicate that these transforms can improve the compression efficiency of the mc-residual.
kernel-based nonlinear independent component analysis for underdetermined blind source separation. in this paper we propose a new unsupervised training method for nonlinear spatial filter using a new independent component analysis based on kernel infomax. the nonlinearity of the spatial filter used in this paper is equivalent to the integration of beamforming and spectral subtraction, and the whole structure is optimized by independent component analysis in the reproducing kernel hilbert space. the optimized filter is shown to be capable of achieving better quality output than the conventional method based on time-frequency binary masking.
a differential cooperative transmission scheme with low rate feedback. the use of cooperative schemes in wireless networks has recently attracted much attention in scenarios where application of multiple-antenna systems is impractical. in such scenarios, the requirement of having full channel state information (csi) at the receiver side can be relaxed by using differential distributed (dd) transmission schemes. however, in the dd schemes proposed so far, the decoding complexity as well as the delay requirements increase with the number of relays. in this paper, we propose a low-rate feedback-based dd approach (with one-bit feedback per relay) that enjoys full diversity, linear maximum likelihood (ml) decoding complexity, and unrestrictive delay requirements. in addition, the proposed feedback scheme does not require any csi knowledge at the receiver, and its implementation is simple. computer simulations demonstrate substantial performance improvements of the proposed techniques as compared to several popular cooperative transmission schemes.
an audio indexing system for election video material. in the 2008 presidential election race in the united states, the prospective candidates made extensive use of youtube to post video material. we developed a scalable system that transcribes this material and makes the content searchable (by indexing the meta-data and transcripts of the videos) and allows the user to navigate through the video material based on content. the system is available as an igoogle gadget1 as well as a labs product (labs.google.com/gaudi). given the large exposure, special emphasis was put on the scalability and reliability of the system. this paper describes the design and implementation of this system.
bandwidth extension for china avs-m standard. we proposed a new frequency domain bandwidth extension (bwe) technology. in the new technology, fft based frequency domain gain shaping combined with linear prediction coding (lpc) based spectral envelope shaping is used for generating high frequency signals. to preserve the amount of noise component in the reconstructed band, gain reduction controlled by spectrum flatness measurement (sfm) is employed. subjective testing results show that the presented technology exhibits a comparable performance compared to 3gpp amr-wb+ with the same bit-rate in the framework of audio video coding of china standard (avs) part 10 - mobile speech and audio codec. this technology has been formally adopted as the artificial high band coding module in avs p10.
distributed peer-to-peer beamforming for multiuser relay networks. a computationally efficient distributed beamforming technique for multi-user relay networks is developed. the channel state information is assumed to be known at the relays or destinations, and the total relay transmitted power is minimized subject to the destination quality-of-service constraints. it is shown that this problem can be approximately converted to a convex second-order cone programming form. as a result, the proposed network beamforming technique offers a substantially reduced computational complexity than earlier state-of-the-art techniques that are based on semidefinite relaxation.
applying discretized articulatory knowledge to dysarthric speech. this paper applies two dynamic bayes networks that include theoretical and measured kinematic features of the vocal tract, respectively, to the task of labeling phoneme sequences in unsegmented dysarthric speech. speaker dependent and adaptive versions of these models are compared against two acoustic-only baselines, namely a hidden markov model and a latent dynamic conditional random field. both theoretical and kinematic models of the vocal tract perform admirably on speaker-dependent speech, and we show that the statistics of the latter are not necessarily transferable between speakers during adaptation.
novel approaches to parallel h.264 decoder on symmetric multicore systems. novel approaches to parallel h.264 decoder for symmetric multicore processors are presented. the basic partitioning of the decoder is coarse-grained and hybrid method of the data partitioning and functional partitioning. we investigate the performance bottleneck of the parallelized decoder, and propose two new approaches, software memory throttling and fair load balancing. the software memory throttling limits the number of cores involved in the parallel motion compensation to achieve better speedup and power-saving. the fair load balancing for deblocking filter reduces load imbalance caused by the conventional static partitioning method. from the evaluation on two different symmetric multicore platforms, proposed approaches show up to 24% of speedup when there is much bandwidth contention.
blind noise variance estimation for ofdma signals. we present two new noise variance estimation methods for ofdma signals transmitted through an unknown multipath fading channel. we focus on blind estimation as it does not require any pilot sequences and is therefore applicable to contexts, such as cognitive radio for instance, where little prior signal knowledge is available. the two estimators are respectively based on the time-frequency sparsity of ofdma signals and on the redundancy induced by the cyclic prefix. numerical simulations compare the performance of the two algorithms and highlight their complementarity.
outage minimized relay selection with partial channel information. selection relaying is a promising technique for practical implementation of cooperative systems with multiple relays. however, to select the best relay, globe channel knowledge is required at the selecting entity. in this paper, we consider the relay selection problem in dual-hop amplify-and-forward (af) communication systems with partial channel state information (csi). we present relay selection strategies aiming at minimizing the outage probability with different kinds of channel knowledge available, including perfect, statistical and quantized csi. simulation results show that near optimal performance is achievable with a few bits feedback to the selecting entity. thus the signaling overhead of relay selection can be greatly reduced with quantized csi feedback.
a dynamic game model for amplify-and-forward cooperative communications. cooperative wireless communication protocols are designed with the assumption that users always behave in a socially efficient manner. this assumption may not be valid in commercial wireless networks where users may violate rules of cooperation to reap benefits of cooperation at no cost. disobeying the rules of cooperation creates a social-dilemma where well-behaved users exhibit uncertainty about intention of other users. cooperation in social-dilemma is characterized by a non-cooperative nash equilibrium which indicates the difficulty of maintaining a socially optimal cooperation without establishing a mechanism to detect and mitigates effects of misbehavior. in this paper, we formulate interaction of users in cooperative amplify-and-forward as a dynamic game with incomplete information. we show the existence of a perfect bayesian equilibrium.
correlation noise classification based on matching success for transform domain wyner-ziv video coding. distributed source coding strongly depends on the knowledge of statistical dependency between source and side information. in transform domain wyner-ziv video coding (tdwz) this statistical dependency (also known as correlation noise) has been usually modeled by a unique laplacian distribution for each frequency band. in this paper, we propose a method to define different classes of correlation noise for each frequency band based on the accuracy of the side information. with this approach the correlation between source and side information is estimated separately for each frequency band of each class. therefore, the decoder can discriminate blocks in order to estimate the correlation noise of their frequency bands. simulation results show that applying the proposed method improves rate-distortion performance.
fundamental properties of non-negative impulse response filters - theoretical bounds ii. this paper presents several fundamental frequency-domain bounds for a non-negative impulse response (nnir) filter. upper-bounds on power spectral attenuation and power spectral gain in geometrically spaced frequency regions are derived, when power spectral attenuation near frequency zero is limited. by analyzing the tightnesses of these bounds, the relationship between the maximally allowable power attenuation and gain is also treated. all results hold for both continuous and discrete-time domains.
some statistical issues in estimating information in neural spike trains. information theory provides an attractive framework for attacking the neural coding problem. this entails estimating information theoretic quantities from neural spike train data. this paper highlights two issues that may arise: non-parametric entropy estimation and non-stationarity. it gives an overview of these issues and some of the progress that has been made.
one-pass multi-layer rate-distortion optimization for quality scalable video coding. in this paper, a one-pass multi-layer rate-distortion optimization algorithm is proposed for quality scalable video coding. to improve the overall coding efficiency, the mb mode in the base layer is selected not only based on its rate-distortion performance relative to this layer but also according to its impact on the enhancement layer. moreover, the optimization module for residues is also improved to benefit inter-layer prediction. simulations show that the proposed algorithm outperforms the most recent svc reference software. for eight test sequences, a gain of 0.35 db on average and 0.75 db at maximum is achieved at a cost of less than 8% increase of the total coding time.
a fast iterative shrinkage-thresholding algorithm with application to wavelet-based image deblurring. we consider the class of iterative shrinkage-thresholding algorithms (ista) for solving linear inverse problems arising in signal/image processing. this class of methods is attractive due to its simplicity, however, they are also known to converge quite slowly. in this paper we present a fast iterative shrinkage-thresholding algorithm (fista) which preserves the computational simplicity of ista, but with a global rate of convergence which is proven to be significantly better, both theoretically and practically. initial promising numerical results for wavelet-based image deblurring demonstrate the capabilities of fista.
multi-microphone maximum a posteriori fundamental frequency estimation in the cepstral domain. in this work we derive a new cepstrum based maximum likelihood fundamental frequency estimator that exploits the information of multiple microphones. the new approach results in a maximum search on the sum of the microphone cepstra. we compare the new approach to a maximum search on the cepstrum of the output signal of a delay-and-sum beamformer. we show that the new approach outperforms the beamforming approach for all considered input signal-to-noise ratios. we develop a general framework which includes the cepstral harmonics of the fundamental frequency and extend the approach towards a maximum a posteriori fundamental period tracker that further enhances the results and increases the robustness in noisy environments.
detecting bandlimited audio in broadcast television shows. for tv and radio shows containing narrowband speech, speech-to-text (stt) accuracy on the narrowband audio can be improved by using an acoustic model trained on acoustically matched data. to selectively apply it, one must first be able to accurately detect which audio segments are narrowband. the present paper explores two different bandwidth classi??cation approaches: a traditional gaussian mixture model (gmm) approach and a spline-based classifier that categorizes audio segments based on their power spectra. we focus on shows found in the darpa gale mandarin training and test sets, where the ratio of wideband to narrowband shows is very large. in this setting, the spline-based classifier reduces the number of misclassified wideband segments by up to 95% relative to the gmm-based classi??er for the same number of misclassified narrowband segments.
oscillator phase noise compensation using kalman tracking. phase noise (pn) is a serious challenge in wireless transmission systems as it can cause significant degradation of the system performance. recent publications propose iterative pn compensation algorithms for single or multicarrier systems. in this paper we will present an unscented kalman filter pn tracking algorithm working in time domain, which is independent of the underlying system. furthermore, we propose a reduced complexity tracking algorithm, where we perform an interpolation between the estimated pn samples. simulation results for an ofdm setup show that by using this technique the system performance can be improved significantly.
on-line speaker adaptation on telephony speech data with adaptively trained acoustic models. this paper addresses speaker adaptive acoustic modeling, based on feature space maximum likelihood linear regression, in the context of on-line telephony applications. an adaptive acoustic modeling method, that we previously proved effective in off-line applications, is used to train acoustic models to be used in text-dependent and text-independent on-line adaptation. experiments on telephony speech data indicate that feature space maximum a posteriori linear regression (fmaplr) greatly helps to cope with sparse adaptation data when performing instantaneous and incremental adaptation with both baseline models and speaker adaptively trained models. the use of speaker adaptively trained models in conjunction with fmaplr leads to the best recognition results in both instantaneous and incremental adaptation. the proposed text-independent adaptation approach, exploiting speaker adaptively trained models, is also proven effective.
a criterion for the enhancement of time-frequency masks in missing data recognition. despite their effectiveness for robust speech processing, missing data techniques are vulnerable to errors in the classification of the input speech signal's time-frequency points. a direct method for the removal of these mask errors is through the top-down optimization of the estimated mask, however this requires a measure to evaluate the mask quality without a priori noise knowledge. in this paper we propose the normalized likelihood confidence as such a criterion for robust speaker recognition. in this approach the accuracy with which an estimated mask classifies time-frequency points as corrupt or reliable is related to its likelihood score confidence. this is based on the conceptual effect of binary mask errors on the model likelihood distributions produced by accumulated marginalization densities. experimental results confirm a relationship between the normalized likelihood distance and the accuracy of the time-frequency mask produced by various estimation strategies.
image denoising based on statistical jump regression analysis and local segmentation using normalized cuts. the edge-preserving surface estimation based on statistical jump regression analysis is a powerful approach for image denoising. however, it requires an accessorial corner-preserving technique in which a corner threshold needs to be tuned. in this paper, we suggest a novel procedure based on local segmentation using normalized cuts which can well preserve the edges and corners at the same time without using the corner-preserving technique. extensive experiments show that the proposed approach outperforms the state-of-the-art existing approaches.
efficient gradient f0 tree model for prosody modeling and unit-selection, applied for the embedded us english concatenative tts. modeling of pitch dynamics in addition to absolute pitch modeling is highly desirable for robust pitch curve prediction and unit selection in concatenative tts systems. transition prosody models have been reported to improve consistency and naturalness for pitch-accent and tonal languages, like japanese and mandarin. in the current work we revise a gradient f0 tree model, originally developed for japanese, and adjust it for american english. the resultant model requires few computational resources at a runtime that makes it highly suitable for embedded tts applications. we report encouraging results of applying it for an embedded concatenative tts system for american english.
adaptive filters using modified sliding-block distributed arithmetic with offset binary coding. an efficient way for computing the response of an adaptive digital filter is to use sliding-block distributed arithmetic (sbda). one disadvantage of distributed arithmetic is the amount of memory utilized. by encoding the memory tables in offset binary code (obc), the size of the memory tables is reduced in half. however, the computational workload remains unchanged. by modifying the computational flow, the computational workload can be reduced by almost half at the expense of slightly more memory. this modified sbda structure is called sbda-obc. it has memory requirements 25%–50% lower than sbda depending on the size of the sub-filter. in terms of the computational workload, sbda-obc is most advantageous for large sub-filters and when the filter is split into few subfilters. in this case, the computational workload is reduced almost in half.
efficient merging of multiple audio streams for spatial sound reproduction in directional audio coding. directional audio coding (dirac) is an efficient technique to capture and reproduce spatial sound. the analysis step outputs a mono dirac stream, comprising an omnidirectional microphone pressure signal and side information, i.e., direction of arrival and diffuseness of the sound field expressed in time-frequency domain. this contribution proposes a method to merge two or more mono dirac streams for a joint playback at the reproduction side. this problem arises in applications such as immersive spatial audio teleconferencing. with respect to a trivial direct merging, the proposed method is more efficient as it does not require the synthesis step. from this follows the benefit that the loudspeaker setup at the reproduction side does not have to be known in advance. simulations and informal listening tests confirm the absence of any artifacts and that the proposed method is practically indistinguishable from the ideal merging.
optimum ambiguity-free isotropic antenna arrays. based on the crb of the 2d-doa estimation problem, we prove a condition on the sensor coordinates of a planar array to be ambiguity-free and isotropic. a systematic search of such antenna arrays is conducted leading to the identification of all possible ambiguity-free isotropic arrays. in particular, we select the arrays that outperform the popular uniform circular array (uca). it is shown that these arrays allow to enhance the doa estimation by as much as 25%, in comparison with uca. as the number of sensors increases, the best isotropic array tends towards the non-intuitive v-shape.
low complexity essentially maximum likelihood decoding of perfect space-time block codes. perfect space-time block codes (stbcs) were first introduced by oggier et al. to have full rate, full diversity and non-vanishing determinant. a maximum likelihood decoder based on the sphere decoder has been used for efficient decoding of perfect stbcs. however the worst-case complexity for the sphere decoder is an exhaustive search. in this paper we present a reduced complexity algorithm for 3 × 3 perfect stbc which gives essentially maximum likelihood (ml) performance and which can be extended to other perfect stbc. the algorithm is based on the conditional maximization of the likelihood function with respect to one of the set of signal points given another. there are a number of choices for which signal points to condition on and the underlying structure of the code guarantees that one of the choices is good with high probability. furthermore, the approach can be integrated with the sphere decoding algorithm with worst case complexity corresponding exactly to that of our algorithm.
weighted harmonic mean sinr maximization for the mimo downlink. leakage-based methods which are based on the harmonic mean signal-to-interference ratio (sir) maximization deliver a good tradeoff between the sum rate and bit-error rate (ber). in this paper, we present the joint design of linear transmit and receive beamformers that maximize the weighted harmonic mean signal-to-interference-and-noise ratio (sinr) for the downlink of the multiuser mimo channel. by exploiting the uplink-downlink sinr duality, the non-convex optimization problem is transformed into a series of simpler problems which can be solved by geometric programming. when the minimum mean square error (mmse) receive beamformers are employed, it is shown that the harmonic mean sinr maximization becomes a close approximation to the sum mse minimization problem in the high sinr region. the simulations show that the proposed scheme outperforms other leakage-based schemes in terms of harmonic mean sinr, sum mse, ber and sum rate.
a mimo-ofdm digital baseband receiver design with adaptive equalization technique for ieee 802.16 wman. in this paper, a 2×2 mimo-ofdm digital baseband receiver for ieee 802.16 wman-ofdm phy is presented. the inner receiver design includes the timing and carrier frequency synchronization, the channel estimation and the mimo detection with adaptive equalization technique. in order to enhance the robustness of the system, the blms algorithm is derived to track the channel variation for the alamouti-scheme stbc feq. the simulation results demonstrate that the mimo receiver with adaptive equalization technique has superior ser performance over frequency selective fading channel.
efficacy of a constantly adaptive language modeling technique for web-scale applications. in this paper, we describe calm, a method for building statistical language models for the web. calm addresses several unique challenges dealing with the web contents. first, calm does not rely on the whole corpus to be available to build the language model. instead, we design calm to progressively adapt itself as web chunks are made available by the crawler. second, given the dynamic and dramatic changes in the web contents, calm is designed to quickly enrich its lexicon and n-grams as new vocabulary and phrases are discovered. to reduce the amount of heuristics and human interventions typically needed for model adaptation, we derive an information theoretical formula for calm to facilitate the optimal adaptation in the maximum a posteriori (map) sense. testing against a collection of web chunks where new vocabulary and phrases are dominant, we show calm can achieve comparable and satisfactory model measured in perplexity. we also show calm is robust against over training and the initial condition, suggesting that any assumptions made in obtaining the initial model can gradually see their impacts diminished as calm runs its full course and adapt to more data.
tables for practical wyner-ziv coding of laplacian sources. many practical coding scenarios deal with sources with transform coefficients that are well modeled as laplacians. for the wyner-ziv coding problem for such sources when correlated side-information is available at the decoder, the side-information is modeled as obtained by independent additive laplacian or gaussian innovation on the source. this paper deals with the optimal choice of encoding parameters for practical wyner-ziv coding in such scenarios, using the same quantizer family as in the regular codec to cover a range of rate-distortion trade-offs, given the variances of the source and innovation. using our prior analysis of a general encoding model based on multi-level coset codes combining source and channel coding, we present comprehensive tables with optimal encoding parameters. these tables can be readily incorporated into a practical codec to read off the encoding parameters.
h.264/svc temporal bit allocation with dependent distortion model. the bit allocation problem for hierarchical b-pictures in h.264/svc is studied with a gop-based dependent distortion model in this work. inter-dependency between temporal layers of h.264/svc is often neglected because of the complexity involved, which often leads to poorer rate control performance. to address this shortcoming, we propose a distortion model that takes inter-dependency into consideration while preserving the low complexity of the encoding process. it is demonstrated by experimental results that the new distortion model results in a highly efficient bit allocation scheme, which outperforms the rate control algorithm in the jsvm 9.12 reference codec by a significant margin.
distributed distance estimation for manifold learning and dimensionality reduction. given a network of n nodes with the i-th sensor's observation xi ∈ rm, the matrix containing all euclidean distances among measurements ||xi − xj || ∀i, j ∈ {1,…, n} is a useful description of the data. while reconstructing a distance matrix has wide range of applications, we are particularly interested in the manifold reconstruction and its dimensionality reduction for data fusion and query. to make this map available to the all of the nodes in the network, we propose a fully decentralized consensus gossiping algorithm which is based on local neighbor communications, and does not require the existence of a central entity. the main advantage of our solution is that it is insensitive to changes in the network topology and it is fully decentralized. we describe the proposed algorithm in detail, study its complexity in terms of the number of inter-node radio transmissions and showcase its performance numerically.
distributed estimation using binary data transmitted over fading channels. we study the parametric distributed estimation problem using a wireless sensor network (wsn) where each sensor observes an unknown scalar parameter, quantizes its observation and sends its quantized observation to a fusion center via fading and noisy communication channels. we propose to incorporate channel statistics rather than the instantaneous channel state information (csi) into the maximum likelihood (ml) formulation and show that the resulting likelihood function is strictly log-concave almost surely with a change of variable provided that at least one of the communication channels between the sensors and the fusion center has nonzero capacity. we also investigate the effects of channel layer on the sensor threshold design and show that the threshold design problem is coupled with the channel layer and the sensor signal-to-noise ratio (snr) only for nonsymmetric channels. our formulation is very general in the sense that no assumptions are made about the physical layer in terms of the modulation schemes and the reception techniques.
tdoa estimation for cyclostationary sources: new correlations-based bounds and estimators. we consider the problem of time difference of arrival (tdoa) estimation for cyclostationary signals in additive white gaussian noise. classical approaches to the problem either ignore the cyclostationarity and use ordinary cross-correlations, or exploit the cyclostationarity by using cyclic cross-correlations, or combine these approaches into a multicycle approach. despite contradicting claims in the literature regarding the performance-ranking of these approaches, there has been almost no analytical comparative performance study. we propose to regard the estimated (ordinary or cyclic) correlations as the “front-end” data, and based on their asymptotically gaussian distribution, to compute the asymptotic cramér-rao bounds (crb) for the various combinations (ordinary/single-cycle/multi-cycle). using our cyclic-correlations-based crb (termed “crbcrb”), we can bound the performance of any (unbiased) estimator which exploits a given set of correlations. moreover, we propose an approximate maximum likelihood estimator (with respect to the correlations), and show that it attains our crbcrb asymptotically in simulations, outperforming the competitors.
a hybrid method for deconvolution of bernoulli-gaussian processes. we investigate a hybrid method which improves the quality of state inference and parameter estimation in blind deconvolution of a sparse source modeled by a bernoulli-gaussian process. in this problem, when both the signal and the filter are jointly estimated, the true posterior is typically highly multimodal. therefore, when not properly initialized, standard stochastic inference methods, (mcem, sem or saem), tend to get stuck and suffer from poor convergence. in our approach, we first relax the bernoulli-gaussian prior model by a student-t model. our simulations suggest that deterministic inference in the relaxed model is not only efficient, but also provides a very good initialization for the bernoulli-gaussian model. we provide simulation studies that compare the results obtained with and without our initialization method for several combinations of state inference and parameter estimation methods used for the bernoulli-gaussian model.
the effectiveness of histogram equalization on environmental model adaptation. in this paper, we introduce a new histogram equalization-based environmental model adaptation method for robust speech recognition in noise environments. the proposed method adapts initially-trained acoustic mean models of a speech recognizer into the environmentally matched models. the covariance models are adapted by using utterance-level local covariance matrices. we performed a series of experiments based on the aurora2 framework to examine the effectiveness of the proposed environmental model adaptation technique. in both clean and multi-condition trainings, the proposed approach achieved substantial performance improvements over the baseline speech recognizers.
ordering random object poses. complete or partial three-dimensional reconstruction of objects from multiple angle-views, or poses, is important in several applications such as photogrammetry, machine vision, and computer-aided design. knowledge of the pose angles and their proper ordering are required for accurate reconstruction. when these multiple angle images are acquired in random order and the angle of view information is not available the poses have to be put into proper order. this work presents an approach based on principal component analysis (pca) for automatic ordering of random object poses. a measure based on local curvature and correlation of the estimated pose trajectory in a multidimensional manifold is also developed to assess confidence in the ordering. in addition to providing a degree of confidence for pose ordering with single cameras, this measure enhances the pose estimation accuracy in double and multiple camera systems by providing a basis for camera selection for different poses. the paper presents theoretical development and experimental results.
camera motion influence on dynamic saliency central bias. saliency models have been extensively studied for static images and the focus is now on moving images. there is a central bias in both cases that is emphasized in the dynamic case. one aspect in this latter is the camera motion that influences the scene interpretation. the movie director exploits this motion to make the observer focus on the targeted object which is often in the center of the scene. this aspect is not taken into account in current saliency dynamic models. in this paper, we study the camera motion influence on the gaze distribution in order to include it in a new saliency model. observers' gazes are recorded with an eye tracker, camera motions (e.g. tracking, zoom…) are calculated thanks to a polynomial projection of the motion field and the motion influence is statistically tested on the recorded gazes.
testing fractal connectivity in multivariate long memory processes. within the framework of long memory multivariate processes, fractal connectivity is a particular model, in which the low frequencies (coarse scales) of the interspectrum of each pair of process components are determined by the autospectra of the components. the underlying intuition is that long memories in each components are likely to arise from a same and single mechanism. the present contribution aims at defining and characterizing a statistical procedure for testing actual fractal connectivity amongst data. the test is based on fisher's z transform and pearson correlation coefficient, and anchored in a wavelet framework. its performance are analyzed theoretically and validated on synthetic data. its usefulness is illustrated on the analysis of internet traffic packet and byte count time series.
a fast asymptotically efficient algorithm for blind separation of a linear mixture of block-wise stationary autoregressive processes. we propose a novel blind source separation algorithm called block autoregressive blind identification (barbi). the algorithm is asymptotically efficient in separation of instantaneous linear mixtures of blockwise stationary gaussian autoregressive processes. a novel closed-form formula is derived for a cramér rao lower bound on elements of the corresponding interference-to-signal ratio (isr) matrix. this theoretical isr matrix can serve as an estimate of the separation performance on the particular data. in simulations, the algorithm is shown to be applicable in blind separation of a linear mixture of speech signals.
jointly optimized mode decisions in redundant video streaming. this paper revisits the problem of source-channel coding for error-resilient video streaming, using redundant encoding. we propose a new method to jointly optimize the macroblock (mb) mode in both the primary and the secondary, redundant encoding. encoding decisions are based on end-to-end distortion using the rope estimate, and are adaptive at the mb level. further, we present a reduced complexity approach to redundant encoding. the proposed methods are general in nature, and could be implemented on top of any (hybrid) video codec. an example implementation employs the redundant slice mechanism of h.264 (jm 13.2). simulation results show significant performance gains over conventional methods such as fixed redundant encoding schemes or non-redundant optimal mb mode selection.
sensor subset selection for surface electromyograpy based speech recognition. the authors previously reported speaker-dependent automatic speech recognition accuracy for isolated words using eleven surface-electromyographic (semg) sensors in fixed recording locations on the face and neck. the original array of sensors was chosen to ensure ample coverage of the muscle groups known to contribute to articulation during speech production. in this paper we systematically analyzed speech recognition performance from sensor subsets with the goal of reducing the number of sensors needed and finding the best combination of sensor locations to achieve word recognition rates comparable to the full set. we evaluated each of the different possible subsets by its mean word recognition rate across nine speakers using hmm modeling of mfcc and co-activation features derived from the subset of sensor signals. we show empirically that five sensors are sufficient to achieve a recognition rate to within a half a percentage point of that obtainable from the full set of sensors.
a new scheme for synchronization of inactive nodes in a sender-receiver protocol. this paper targets the problem of clock synchronization for a set of receivers lying within the broadcast range of two nodes implementing a general sender-receiver protocol using a wireless channel. the maximum likelihood estimate of the clock offset of the inactive node (and mean link delay) hearing the broadcasts from both the master and slave nodes was derived in [1] assuming symmetric exponential link delays. in this paper, the minimum variance unbiased estimate for the clock offset of such nodes is derived by applying the rao-blackwell-lehmann-scheffé theorem. the result is important in the realm of wireless sensor networks, where a tight network synchronization along with a conservative energy utilization plays a major role in network performance.
an improvement of subgradient projection operator by composing monotonic functions. the subgradient projection operator has been utilized as a computationally efficient tool not only for suppression but also for minimization of convex functions in many applications. in this paper, we propose a systematic scheme to improve significantly the monotone approximation ability, of the subgradient projection, to the level set of a convex function. the proposed scheme is based on a simple observation: the level set of a convex function does not change by composing any zero-crossing monotonically increasing function. a numerical example demonstrates the effectiveness of the proposed scheme in an application to a simple boosting problem.
latent semantic retrieval of personal photos with sparse user annotation by fused image/speech/text features. while users prefer high-level semantic photo descriptions (e.g., who, what, when, where), we wish to minimize the need to annotate photos using such descriptions by the user. we propose a latent semantic personal photo retrieval approach using fused image/speech/text features. we use low-level image features to derive relatoionships among sparsely annotated photos, and probabilistic latent semantic analysis (plsa) models based on fused image/speech/text features to analyze photo “topics”. we then retrieve the photos using text or speech queries of simple high-level semantic words only. in preliminary experiments, while only 10% of the photos were manually annotated, the photos could be well retrieved with very encouraging results.
hdr image compression using optimized tone mapping model. in this paper, we propose a coding algorithm for high dynamic range images (hdri). our encoder applies a tone mapping model based on scaled μ-lawencoding, followed by a conventional low dynamic range image (ldri) encoder. the tone mapping model is designed to minimize the difference between the tone mappedhdri and its ldr version. by virtue of the nature of the model, not only the quality of the hdri but also the one of ldri are improved, compared with a state of the art in conventional hdri compression. furthermore the error caused by our tone mapping model encoding is theoretically analyzed.
spatio-temporal adaptive detector in non-homogeneous and low-rank clutter. reducing the number of secondary data used to estimate the clutter covariance matrix (ccm) for space time adaptive processing (stap) techniques is still an active research topic. low rank ccm estimates have already been proposed but only for homogeneous and gaussian clutter. we propose in this paper to extend the low-rank ccm methods for heterogeneous and/or non-gaussian clutter. we derive a new detector based on low-rank techniques and exploiting properties of the normalized sample covariance matrix (nscm). this detector is shown to exhibit a smaller snr loss than classical stap detectors. moreover, the new detector has a texture-cfar property with respect to non-gaussian sirv model and has more robust behavior when some targets are present in the secondary data. we also give experimental comparison results between the classical stap detectors and the new one for stap data.
range image quality assessment by structural similarity. we propose a new quality metric for range images that is based on the multi-scale structural similarity (ms-ssim) index. the new metric operates in a manner to ssim but allows for special handling of missing data. we demonstrate its utility by reevaluating the set of stereo algorithms evaluated in the middlebury stereo vision page http://vision.middlebury.edu/stereo/. the new algorithm which we term range ssim (r-ssim) index possesses features that make it an attractive choice for assessing the quality of range images.
improved maximum likelihood location estimation accuracy in wireless sensor networks using the cross-entropy method. this paper considers the problem of target location estimation in a wireless sensor network based on ieee 802.15.4 radio signals and proposes a novel implementation of the maximum likelihood (ml) location estimator based on the cross-entropy (ce) method. in the proposed ce method, the ml criterion is translated into a stochastic approximation problem which can be solved effectively. simulation results comparing the performance of a ml target estimation scheme employing the conventional newton method and the conjugate gradient method are presented. the simulation results show that the proposed ce method provides higher location estimation accuracy throughout the sensor field1 the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
a new bitplane coder for scalable transform audio coding. this paper proposes a new bit plane coding method for signed integer sequences. this method consists in mapping successive bit planes onto quinary symbols (+, “, 0, 1, eop), where the symbol “eop” stands for “end of plane”, and applying arithmetic coding. sign bits are efficiently coded in combination with the corresponding most significant bit of non-zero integers. moreover, bit planes are scanned and coded in a non-sequential manner to exploit the correlation between successive planes. results for conversational transform coding of wideband speech and audio signals - sampled at 16 khz - show that the performance/complexity of the proposed bitplane coder is near equivalent to non-embedded coding (stack-run coding), while offering additional flexibility (bitstream scalability).
dense disparity estimation in a multi-view distributed video coding system. distributed video coding (dvc) is a recent paradigm which aims at transferring part of the coding complexity fromthe encoder to the decoder. the performance of such a coding scheme strongly depends on the capacity to estimate correlation at the decoder and, consequently, on the side information quality. in this paper we consider a multi-view dvc framework and propose a very efficient dense disparity estimation technique for side information construction, based on a variational formulation. the simulation results show that our approach clearly outperforms the existing methods for inter-view side-information generation.
rational canonical form of polyphase matrices with applications to designing paraunitary filter banks. in this paper we consider the rational canonical form of arbitrary polyphase matrices and use it to derive a simple implementation of paraunitary filter banks (pufbs) based on a cascade of elementary building blocks. furthermore, this decomposition is shown to be easily extendable to include a large class of perfect reconstruction filter banks (prfbs) and can be especially useful for deriving the initial condition of pufb design algorithms.
automatic musical meter detection. a method that automatically estimates the metrical structure of a piece of music is presented. the approach is based on the generation of a beat similarity matrix, which provides information about the similarity between any two beats of a piece of music. the repetitive structure of most music is exploited by processing the beat similarity matrix in order to identify similar patterns of beats in different parts of a piece. this principle proves to be equally effective for the detection of both duple and triple meters as well as complex meters. the use of beat positions and dynamic programming techniques allows tracking similar musical patterns formed by beats with moderate tempo deviations. the robustness of the presented approach is reflected by the results presented, where 361 songs are used in order to compare the presented approach against the use of the autocorrelation function in existing state of the art meter detection methods. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
multi-task classification with infinite local experts. we propose a multi-task learning (mtl) framework for non-linear classification, based on an infinite set of local experts in feature space. the usage of local experts enables sharing at the expert-level, encouraging the borrowing of information even if tasks are similar only in subregions of feature space. a kernel stick-breaking process (ksbp) prior is imposed on the underlying distribution of class labels, so that the number of experts is inferred in the posterior and thus model selection issues are avoided. the mtl is implemented by imposing a dirichlet process (dp) prior on a layer above the task-dependent ksbps.
multimodal blind source separation for moving sources. a novel multimodal approach is proposed to solve the problem of blind source separation (bss) of moving sources. the challenge of bss for moving sources is that the mixing filters are time varying, thus the unmixing filters should also be time varying, which are difficult to track in real time. in the proposed approach, the visual modality is utilized to facilitate the separation for both stationary and moving sources. the movement of the sources is detected by a 3-d tracker based on particle filtering. the full bss solution is formed by integrating a frequency domain blind source separation algorithm and beamforming: if the sources are identified as stationary, a frequency domain bss algorithm is implemented with an initialization derived from the visual information. once the sources are moving, a beamforming algorithm is used to perform real time speech enhancement and provide separation of the sources. experimental results show that by utilizing the visual modality, the proposed algorithm can not only improve the performance of the bss algorithm and mitigate the permutation problem for stationary sources, but also provide a good bss performance for moving sources in a low reverberant environment.
chinese intonation assessment using sev features. intonation assessment is an important part of chinese call system. nowadays, most systems use the correlation and rmse features to assess the quality of the intonation of a given speech. as correlation and rmse assign unoptimized weights to different degrees of mismatching errors, they may lead to performance degradation. in this paper, we propose a new feature called sorted error vector (sev) for intonation assessment. the basic idea is to calculate mismatching quantities, sort them with ascending order, and then re-sample them to a k-points vector. this feature has four benefits: first, it is text-length independent; second, weights are let to train by classifiers; third, the relationship between the errors and the final results is not limited to any assumption; fourth, sev is not sensitive to the performance of different pitch extracting algorithms. experiments show that no matter in which case, sev feature performs the best.
enhanced spatially interleaved dvc using diversity and selective feedback. systems with cheap/simple/power efficient encoders but complex decoders make applications such as low cost, low power remote sensors practical. bandwidth considerations however are still an issue and compression efficiency has to remain high. in this paper, we present a distributed video codec (dvc) that we are developing with the aim of achieving such a low power paradigm at the cost of only a small compression performance deficit relative to the current state of the art, h.264. the proposed system employs spatial interleaving of key and wyner-ziv data which allows efficient side information (si) generation through block-based error concealment, a gray code that increases the accuracy of bit probability estimation, and a diversity scheme that produces more reliable results by exploiting multiple si generated data. simulation results show an improvement of the proposed scheme over h.264 intra coding of up to 1.5 db. we additionally propose two mechanisms for selective parity bit feedback requests that can fizrther reduce the wz bitrate by up to 15%.
impact of novel sources on content-based image and video retrieval. the problem of content-based image and video retrieval with textual queries is often posed as that of visual concept classification, where classifiers for a set of predetermined visual concepts are trained using a set of manually annotated images. such a formulation implicitly assumes that the training data has similar distributional characteristics as that of the data which need to be indexed. in this paper we demonstrate empirically that even within the relatively narrow domain of news videos collected from a variety of news programs and broadcasters, the assumption of distributional similarity of visual features does not hold across programs from different broadcasters. this is manifested in considerable degradation of ranked retrieval performance on novel sources. we observe that concepts whose spatial locations remain relatively fixed between various sources are also more robust to source mismatches, and vice versa. we also show that a simple averaging of multiple visual detectors is more robust than any of the individual detectors. furthermore, we show that for certain sources using only 20% of the available annotated data can bridge roughly 80% of the performance drop, while others can require larger amounts of annotated data.
joint carrier frequency offset and channel estimation in ofdm based non-regenerative wireless relay networks. cooperative relaying is an effective approach to combat wireless fading. however, the reliability enhancements depend strongly on the accuracy of the carrier frequency offset (cfo) compensation and channel estimation algorithms. in this paper, we show that cfo compensation at relay is necessary in non-regenerative ofdm based wireless relay networks with relays employing space-time coding. a simple training scheme available for estimating space-time channel is exploited to estimate the cfo at the relay. maximum likelihood (ml) and least squares (ls) based joint cfo and channel estimators are constructed for estimating the cfo and the product channel (effective channel from source to destination) at destination. for non-regenerative ofdm based wireless relays, we prove that the ls based estimator is equivalent to the ml based estimator. theoretical mean square error for the product channel estimator is also derived.
skellamshrink: poisson intensity estimation for vector-valued data. owing to the stochastic nature of discrete processes such as photon counts in imaging, a variety of real-world data are well modeled as poisson random variables whose means are in turn proportional to an underlying vector-valued signal of interest. certain wavelet and filterbank transform coefficients corresponding to measurements of this type are distributed as sums and differences of poisson counts, taking in the simplest case the so-called skellam distribution. we show that a skellam mean estimator provides a poisson intensity estimation method based on shrinkage of filterbank coefficients, and a means of estimating the risk of any skellam mean estimator is derived in closed form under a frequentist model.
refactoring acoustic models using variational density approximation. in model-based pattern recognition it is often useful to change the structure, or refactor, a model. for example, we may wish to find a gaussian mixture model (gmm) with fewer components that best approximates a reference model. one application for this arises in speech recognition, where a variety of model size requirements exists for different platforms. since the target size may not be known a priori, one strategy is to train a complex model and subsequently derive models of lower complexity. we present methods for reducing model size without training data, following two strategies: gmm-approximation and gaussian clustering based on divergences. a variational expectation-maximization algorithm is derived that unifies these two approaches. the resulting algorithms reduce the model size by 50% with less than 4% increase in error rate relative to the same-sized model trained on data. in fact, for up to 35% reduction in size, the algorithms can improve accuracy relative to baseline.
using context information and local feature points in face clustering for consumer photos. we introduce local feature points to achieve face clustering for consumer photos. after combining eigenfaces with context information like clothes, we further investigate the usage of local feature points to match face images. the relationships between face images are constructed by feature matching and then described as a graph. outliers in the results of preliminary clustering are detected and are re-clustered according to matching characteristics. we report complete performance comparison for different datasets and show that the proposed method has superior performance than conventional approaches.
query parsing for voice-enabled mobile local search. with the exponential growth in the number of mobile devices, voice enabled local search is emerging as one of the most popular applications. although the application is essentially an integration of automatic speech recognition (asr) and text or database search, the potential usefulness of this application has been widely acknowledged. in this paper, we present a data-driven approach to voice query parsing, that segments the input query into several fields that are necessary for high-precision local search. we also demonstrate the robustness of our approach to asr errors. we present an approach for exploiting multiple hypotheses from asr, in the form of word confusion networks, in order to achieve tighter coupling between asr and query parsing. a confusion-network based query parsing outperforms asr 1-best based query-parsing by 2.6% absolute.
iris recognition using 2d-lda + 2d-pca. this paper presents a biometric iris recognition using 2d-lda with embedding 2d-pca. a new approach that the 2d-pca is embedded into the 2d-lda to improve its performance is proposed. the approach first finds the most concentrated training samples in each class, and uses the sample mean to represent the class. then the 2d-pca is adopted to find the projection matrix which can scatter the variance between classes. the results show that the new approach has an encouraging performance. the recognition rate up to 99.20% can be achieved.
a tempering approach for itakura-saito non-negative matrix factorization. with application to music transcription. in this paper we are interested in non-negative matrix factorization (nmf) with the itakura-saito (is) divergence. previous work has demonstrated the relevance of this cost function for the decomposition of audio power spectrograms. this is in particular due to its scale invariance, which makes it more robust to the wide dynamics of audio, a property which is not shared by other popular costs such as the euclidean distance or the generalized kulback-leibler (kl) divergence. however, while the latter two cost functions are convex, the is divergence is not, which makes it more prone to convergence to irrelevant local minima, as observed empirically. thus, the aim of this paper is to propose a tempering scheme that favors convergence of is-nmf to global minima. our algorithm is based on nmf with the beta-divergence, where the shape parameter beta acts as a temperature parameter. results on both synthetical and music data (in a transcription context) show the relevance of our approach.
block jacobi-type methods for non-orthogonal joint diagonalisation. in this paper, we study the problem of non-orthogonal joint diagonalisation of a set of real symmetric matrices via simultaneous conjugation. a family of block jacobi-type methods are proposed to optimise two popular cost functions for the non-orthogonal joint diagonalisation, namely, the off-norm function and the log-likelihood function. by exploiting the appropriate underlying manifold, namely the so-called oblique manifold, rigorous analysis shows that, under the exact non-orthogonal joint diagonalisation setting, the proposed methods converge locally quadratically fast to a joint diagonaliser. finally, performance of our methods is investigated by numerical experiments for both exact and approximate non-orthogonal joint diagonalisation.
rate-distortion optimized bitstream extractor for motion scalability in scalable video coding. motion scalability is designed to improve the coding efficiency of a scalable video coding framework, especially in the medium to low range of decoding bit rates or spatial resolutions. in order to fully benefit from the superiority of motion scalability, a rate-distortion optimized bitstream extractor, which determines the optimal motion quality layer for each decoding scenario, is required. in this paper, the determination process first starts off with a brute force searching algorithm. although guaranteed by the optimal performance within the search domain, it has high computational complexity. two properties, i.e. the monotonically non-decreasing property and the unimodal property, are then derived to accurately describe the rate-distortion behavior of motion scalability. based on these two properties, modified searching algorithms are proposed to reduce the complexity by a factor up to 5.
vlsi for 5000-word continuous speech recognition. we have developed a vlsi chip for 5,000 word speaker-independent continuous speech recognition. this chip employs a context-dependent hmm (hidden markov model) based speech recognition algorithm, and contains emission probability and viterbi beam search pipelined hardware units. the feature vector for speech recognition is computed using a host processor in software in order to adopt various enhancement algorithms. the amount of internal sram size is minimized by moving data out to the external dram, and a custom dram controller module is designed to efficiently read and write consecutive data. the experimental result shows that the implemented system has a real-time factor of 0.77 and 0.55 using sdram and ddr sdram, respectively.
improved video segmentation through robust statistics and mpeg-7 features. video segmentation is an important task for a wide range of applications like content-based video coding or video retrieval. in this paper, a new spatio-temporal video segmentation framework is presented. it is based upon robust statistics, namely an m-estimator, and incorporates an mpeg-7 descriptor for consistent temporal labeling of identified textures. the algorithm is based on assumptions about the geometric modifications a given moving region undergoes with time as well as on its surface properties. homogeneously moving segments are described using a parametric motion scheme. the latter is used to piecewise fit the optical flow field in order to extract rigid motion areas. robust statistics are used to carefully constrain split, merge and contour refinement decisions. experimental results show that regions detected by the proposed method are more reliable than the state-of-the-art. true region boundaries are moreover better detected.
quality control of automatic labelling using hmm-based synthesis. this paper presents a measure to verify the quality of automatically aligned phone labels. the measure is based on a similarity cost between automatically generated phonetic segments and phonetic segments generated by an hmm-based synthesiser. we investigate the effectiveness of the measure for identifying problems of three types: alignment errors, phone identity problems and noise insertion. our experiments show that the measure is best at finding noise errors, followed by phone identity mismatches and serious misalignments.
blind sparse source separation for unknown number of sources using gaussian mixture model fitting with dirichlet prior. in this paper, we propose a novel sparse source separation method that can be applied even if the number of sources is unknown. recently, many sparse source separation approaches with time-frequency masks have been proposed. however, most of these approaches require information on the number of sources in advance. in our proposed method, we model the histogram of the estimated direction of arrival (doa) with a gaussian mixture model (gmm) with a dirichlet prior. then we estimate the model parameters by using the maximum a posteriori estimation based on the em algorithm. in order to avoid one cluster being modeled by two or more gaussians, we utilize a sparse distribution modeled by the dirichlet distributions as the prior of the gmm mixture weight. by using this prior, without any specific model selection process, our proposed method can estimate the number of sources and time-frequency masks simultaneously. experimental results show the performance of our proposed method.
comparison of frequency domain noise reduction strategies based on multichannel wiener filtering and spatial prediction. in this paper two multichannel noise reduction strategies are compared in the context of binaural hearing aids. recently a novel noise reduction method based on spatial-temporal prediction (stp) was introduced which showed an improvement over methods based on multichannel wiener filtering, although at the cost of a higher computational complexity. whereas this newmethod operates in the time domain, hearing aids typically demand faster frequency domain implementations. in this paper we therefore propose a frequency domain equivalent of the stp method. the performance of the new so-called spatial prediction (sp) method will be compared to a frequency domain implementation of the speech distortion weighted multichannel wiener filter (sdw-mwf), theoretically as well as based on simulations with a binaural hearing aid configuration. it will be shown that the frequency domain sp method still achieves some improvement over the sdw-mwf, at the cost of higher computational complexity.
non-linear mapping for multi-channel speech separation and robust overlapping spech recognition. this paper investigates a non-linear mapping approach to extract robust features for asr and speech separation of overlapping speech. based on our previous studies, we continue to use two additional sound sources, namely from the target and interfering speakers. the focuses of this work are: 1) we investigate the feature mapping between different domains with the consideration of mmse criterion and regression optimizations, demonstrating the mapping of log melfilterbank energies to mfcc can be exploited to improve the effectiveness of the regression; 2) we investigate the data-driven filtering for the speech separation by using the mapping method, which can be viewed as a generalized log spectral subtraction and results in better separation performance. we demonstrate the effectiveness of the proposed approach through extensive evaluations on the monc corpus, which includes both non-overlapping single speaker and overlapping multi-speaker conditions.
estimating side-information for wyner-ziv video coding using resolution-progressive decoding and extensive motion exploration. in wyner-ziv video coding (wzvc), the quality of side information (si) has a critical impact on the coding efficiency. most existing wzvc schemes generate si using decoder-side motion estimation (me), where the current frame is unavailable and the me accuracy is greatly impaired. in this paper, without introducing additional bitrate overhead, we incorporate fractional-pel motion search, reduced block sizes and multiple hypothesis prediction into our previously proposed decoder-side multi-resolution motion refinement framework [1], where the current frame is progressively decoded, and based on which the decoder iteratively refines the motion to improve its accuracy. theoretical analysis shows significant gain of the combination of these advanced techniques. a practical si estimator is implemented and provides prediction performance comparable to h.264/avc.
a variational em algorithm for learning eigenvoice parameters in mixed signals. we derive an efficient learning algorithm for model-based source separation for use on single channel speech mixtures where the precise source characteristics are not known a priori. the sources are modeled using factor-analyzed hidden markov models (hmm) where source specific characteristics are captured by an “eigenvoice” speaker subspace model. the proposed algorithm is able to learn adaptation parameters for two speech sources when only a mixture of signals is observed. we evaluate the algorithm on the 2006 speech separation challenge data set and show that it is significantly faster than our earlier system at a small cost in terms of performance.
dynamic texture models of music. in this paper, we consider representing a musical signal as a dynamic texture, a model for both the timbral and rhythmical qualities of sound. we apply the new representation to the task of automatic song segmentation. in particular, we cluster sequences of audio feature-vectors, extracted from the song, using a dynamic texture mixture model (dtm). we show that the dtm model can both detect transition boundaries and accurately cluster coherent segments. the similarities between the dynamic textures which define these segments are based on both timbral and rhythmic qualities of the music, indicating that the dtm model simultaneously captures two of the important aspects required for automatic music analysis.
non-uniform sampling: a novel approach. in this paper a novel approach to non-uniform sampling is proposed. two engineering methods are discussed.
distributed compressive video sensing. low-complexity video encoding has been applicable to several emerging applications. recently, distributed video coding (dvc) has been proposed to reduce encoding complexity to the order of that for still image encoding. in addition, compressive sensing (cs) has been applicable to directly capture compressed image data efficiently. in this paper, by integrating the respective characteristics of dvc and cs, a distributed compressive video sensing (dcvs) framework is proposed to simultaneously capture and compress video data, where almost all computation burdens can be shifted to the decoder, resulting in a very low-complexity encoder. at the decoder, compressed video can be efficiently reconstructed using the modified gpsr (gradient projection for sparse reconstruction) algorithm. with the assistance of the proposed initialization and stopping criteria for grsr, derived from statistical dependencies among successive video frames, our modified gpsr algorithm can terminate faster and reconstruct better video quality. the performance of our dcvs method is demonstrated via simulations to outperform three known cs reconstruction algorithms.
humming-based human verification and identification. this paper considers humming-based systems for human verification and identification. humming of a target person is modeled as a gaussian mixture model, and the matching score between a target model and humming is computed as the likelihood of humming given a target model. verification is performed by comparing the matching score to the likelihood given a universal background model, and identification is performed by selecting the best-matched model. the verification and identification performances are evaluated using various acoustical features. the experimental results show that linear prediction cepstral coefficients and perceptually linear prediction coefficients are conducive to verification and identification, respectively.
adaptive tracking in the time-frequency plane and its application in causal real-time speech analysis. this paper proposes a causal approach to adaptive estimation of time-frequency localized signals using adaptive notch filters (anf). by adaptively estimating the envelope of each sinusoidal component, it is possible to specify the tracking quality and restart the anf unit whenever the tracked sinusoid disappears, as well as preventing the anf from “tracking” non-existent sinusoids (the frequency mis-lock situation). employing multiple anfs allows an efficient approach to tracking time-frequency localized signals such as speech.
a mixed time-scale algorithm for distributed parameter estimation : nonlinear observation models and imperfect communication. the paper considers the algorithm nlu for distributed (vector) parameter estimation in sensor networks, where, the local observation models are nonlinear, and inter-sensor communication is imperfect, in the sense, that the network links fail randomly and inter-sensor transmission is quantized. the paper introduces the class of separably estimable observation models, which generalizes the notion of observability in centralized linear estimation to distributed nonlinear estimation. we show that the nlu algorithm leads to consistent and asymptotically unbiased estimates of the parameter at each sensor for separably estimable observation models. in other words, the sensors reach consensus almost sure (a.s.) to the true parameter value. the algorithm nlu is a mixed time scale stochastic algorithm, characterized by two different decreasing weight sequences associated with the consensus and innovation updates. the analysis of the nlu algorithm, thus, does not follow under the purview of standard stochastic approximation, making the analysis developed in the paper of independent theoretical interest.
reverse channel training for reciprocal mimo systems with spatial multiplexing. this paper investigates the problem of designing reverse channel training sequences for a tdd-mimo spatial-multiplexing system. assuming perfect channel state information at the receiver and spatial multiplexing at the transmitter with equal power allocation to the m dominant modes of the estimated channel, the pilot is designed to ensure an estimate of the channel which improves the forward link capacity. using perturbation techniques, a lower bound on the forward link capacity is derived with respect to which the training sequence is optimized. thus, the reverse channel training sequence makes use of the channel knowledge at the receiver. the performance of orthogonal training sequence with mmse estimation at the transmitter and the proposed training sequence are compared. simulation results show a significant improvement in performance.
generic invertibility of multidimensional fir multirate systems and filter banks. we study the invertibility of m-variate polynomial (respectively : laurent polynomial) matrices of size n by p. such matrices represent multidimensional systems in various settings including filter banks, multiple-input multiple-output systems, and multirate systems. the main result of this paper is to prove that when n − p ≥ m, then h(z) is generically invertible; whereas when n − p ≪ m, then h(z) is generically noninvertible. as a result, we can have an alternative approach in design of the multidimensional systems.
receiver error concealment using acknowledge preview (recap) - an approach to resilient video streaming. high-quality and low-latency video streaming is essential to providing a natural user experience in video conferencing. this is challenging over lossy networks since compressed video is highly fragile while the low-latency requirement limits the effectiveness of traditional error control approaches such as retransmission and forward error correction. in this paper, we advocate a practical solution for low-latency video communications over best-effort networks that employs an additional low-quality, low-resolution but robustly coded copy of the video. this approach, called recap, incurs minimal rate overhead, and can be combined with previously decoded frames to achieve effective concealment of isolated and burst losses even under tight delay constraints. recap achieves psnr gains of 2–6 db against complete frame loss.
robust implementation of the music algorithm. the problem of estimating frequencies of sinusoids in noise has been studied intensively by the signal processing community during the last decades. traditionally high resolution subspace-based techniques suffer from high computational complexity, and generally sensitive to the colored noise. we present here a frequency-domain based subspace parameter estimation algorithm termed frequency-selective multiple signal classification (f-music) that is based on the signal and noise subspace orthogonality property. the method is computationally efficient in providing estimates in the selected subband compared to the classic music. the performance of f-music is evaluated and compared to both music and cramér-rao lower bound (crlb). in a low signal to noise ratio (snr) with colored noise scenarios, f-music outperforms music.
blind detection of high rate orthogonal space-time block codes. we present a new approach to blind equalization for generalized orthogonal space-time block codes. our method takes the form of linear programming (lp) and is globally convergent. we exploit the implicit structure of orthogonal space-time block codes to cast the problem as linear programming that can be solved efficiently. unlike several known methods, the proposed technique is applicable to many full-rate orthogonal space time codes such as the popular almouti code. our algorithm allows receiver detection of full diversity codes without channel knowledge with detection performance comparable to the optimum maximum-likelihood (ml) detection.
online speaker clustering using incremental learning of an ergodic hidden markov model. a novel online speaker clustering method suitable for real-time applications is proposed. using an ergodic hidden markov model, it employs incremental learning based on a variational bayesian framework and provides probabilistic (non-deterministic) decisions for each input utterance, directly considering the specific history of preceding utterances. it makes possible more robust cluster estimation and precise classification of utterances than do conventional online methods. experiments on meeting-speech data show that the proposed method produces 70–80% fewer errors than a conventional method does.
cosine - a corpus of multi-party conversational speech in noisy environments. we present an overview of the data collection and transcription efforts for the conversational speech in noisy environments (cosine) corpus. the corpus is a set of multi-party conversations recorded in real world environments with background noise that can be used to train noise-robust speech recognition systems. we explain the motivation for creating such a corpus and describe the resulting audio recordings and transcriptions that comprise the corpus. these recordings include a 4-channel array and close-talking, far-field, and throat microphones on separate synchronized channels, allowing for unique algorithm research.
a localized vibration response technique for damage detection in bridges. traditional techniques for damage detection in civil infrastructures that are based on the global vibration response of the system are limited in their capabilities to detect damage. because damage detection based on the global vibration response relies on global parameters to describe the dynamic behavior of local structural elements, it suffers from limiting factors such as poorly-formed aggregate system models, very low signal to noise ratio, unrealistic boundary conditions. an alternative to the use of global detection techniques is the use of an adaptive local analysis technique based on the local response of the structure. this is achieved using wavelet packet decomposition at the sensor outputs and interpreting this decomposition as a subband framework for a bank of adaptive beamformers. the beamformer adaptive processors guaranties the maximization of the output snr and in the same time allows for spatial selectivity and a highly directive vibration response in the structure. scanning the structure over time produces a detailed vibration signature of the structure. the structural damage can be localized with high probability by comparing two vibration signatures before and after the damage occurs.
perceptually motivated quasi-periodic signal selection for polyphonic music transcription. a multiple fundamental frequency estimator is a key building block in music transcription and indexing operations. however, systems trying to perform this task tend to be very complex [1]. indeed, music transcription requires an analysis accounting for both physical and psycho-acoustical matters. in this work, we propose a physically-motivated audio signal analysis followed by an auditory-based selection. the audio signal model allows for a better time/frequency resolution tradeoff, while the auditory distance discards the redundant/non-relevant information. no prior information on the musical instrument, musical genre, and/or maximum polyphony are needed. simulations show that the proposed technique achieves good transcription results for a variety of string and wind instruments. the proposed scheme is also shown to be robust in the presence of noise, percussive sounds and in unbalanced signal-to-interference ratio (sir) situations.
a blind speech enhancement algorithm for the suppression of late reverberation and noise. this paper proposes a new speech enhancement algorithm for the suppression of background noise and late reverberation without a priori knowledge. a generalized spectral weighting rule based on estimations for the spectral variances of the late reverberant speech and background noise is used for speech enhancement. this allows to suppress speech distortions due to late room reflections without knowledge about the complete room impulse response. in contrast to existing methods, all needed quantities are estimated entire blindly from the reverberant and noisy speech signal. the new algorithm has also a low signal delay which is important, e.g., for speech enhancement in mobile communication devices or hearing aids.
coordination and cooperation for next generation wireless systems- overhead signalling requirements and cross layer considerations. in the evolution of wireless systems to the next generation, it is becoming increasingly important to offer substantial improvements, not only in terms of peak and average cell rates but also in terms of outage performance. to this end, interference management by means of coordination between different base stations and coverage/capacity improvements by means of cooperation with relays are considered potential candidate technologies. the introduction of multiuser mimo processing principles and cross-layer optimized resource allocation may offer promising performance gains for coordination and cooperation but their feasibility depends on overhead signaling constraints and system deployment assumptions. in this paper, we present two realistic approaches for coordination and cooperation, analyze their performance merits and discuss their complexity requirements.
a single-chip speech dialogue module and its evaluation on a personal robot, papero-mini. this paper presents a single-chip speech dialogue module and its evaluation on a personal robot. this module is implemented on an application processor that was developed primarily for mobile phones to provide a compact size, low power-consumption, and low cost. it performs speech recognition with preprocessing functions such as direction-of-arrival (doa) estimation, noise cancellation, beamforming with an array of microphones, and echo cancellation. text-to-speech (tts) conversion is also equipped with. evaluation results obtained on a new personal robot, papero-mini, which is a scale-down version of papero, demonstrate an 85% correct rate in doa estimation, and as much as 54% and 30% higher speech recognition rates in noisy environments and during robot utterances, respectively. these results are shown to be comparable to those obtained by papero.
optimization of text database using hierachical clustering. many speech and language related techniques employ models that are trained using text data. in this paper, we introduce a novel method for selecting optimized training sets from text databases. the coverage of the subset selected for training is optimized using hierarchical clustering and the generalized levenshtein distance. the validity of the proposed subset optimization technique is verified in a data-driven syllabification task. the results clearly indicate that the proposed approach meaningfully optimizes the training set, which in turn improves the quality of the trained model. compared to the existing state-of-the-art data selection technique, the proposed hierarchical clustering approach improves the compactness of data clusters, decreases the computational complexity and makes data set selection scalable. the presented idea can be used in a wide variety of language processing applications that require training with text data.
new polarimetric signal subspace detectors for sar processors. this paper deals with three new polarimetric sar processors based on subspace detectors. these algorithms aim at using models with physical and polarimetric scattering properties not exploited by the isotropic point model. these processors are implemented by computing the corresponding target subspaces. results on simulated data with realistic targets show the interest of these new processors.
acoustic model combination to compensate for residual noise in multi-channel source separation. in this paper, we propose an acoustic model combination technique for reducing a mismatch in a multi-channel noisy environment. to this end, we first apply a mask-based multi-channel source separation method, typically computational auditory scene analysis (casa), to separate the speech source from noise. however, a certain degree of noise remains in the separated speech source, especially under low signal-to-noise ratio (snr) conditions since the estimated mask is not ideal. thus, the performance of automatic speech recognition (asr) is limited. to improve asr performance, the remaining noise can be further compensated in the acoustic model domain under a framework of parallel model combination. in particular, a noise model for pmc is estimated from the noise remained after application of the maskbased source separation, and snr for pmc is also estimated based on the average of relative magnitude of mask along the utterance. it is shown from the experiments that the proposed acoustic model combination method relatively reduces the word error rate by 52.14% compared to mask-based source separation alone.
directed markov stationary features for visual classification. we investigate how to effectively incorporate spatial structure information into histogram features for boosting visual classification performance motivated by recently proposed markov stationary features (msf). first, we show that due to the symmetric property of the image occurrence modeling procedure, the stationary distribution derived from the normalized co-occurrence matrix has a trivial informative solution which only approximates the original histogram representation, i.e., does not encode proper spatial structure information. to eliminate this ambiguity, we propose in this work the so called directed markov stationary features (dmsf) to encode spatial information into histogram features, and the asymmetric essence of the co-occurrence matrices in dmsf avoids the trivial informative solutions in msf. extensive experiments on face recognition show the significant performance improvement brought by our proposed dmsf.
binaural artificial bandwidth extension (b-abe) for speech. efficient teleconference system can be created by extending the speech bandwidth and using spatial audio. if wideband speech transmission was not supported as such, an alternative way to extend the bandwidth is by exploiting an artificial bandwidth extension (abe) algorithm. in such methods the audio bandwidth is extended in the receiving end, without any transmitted extra information. when considering spatial audio it should be noted that abe methods have been developed for monaural signals and they cannot be applied as such to binaural signals due to a possible mismatch of binaural cues in the created frequency range. in this paper binaural abe, b-abe, is proposed. subjective listening tests were used to evaluate the proposed method. the results showed that the localization information is preserved well in b-abe processing.
filter-and-forward distributed beamforming for relay networks in frequency selective fading channels. a half-duplex distributed beamforming technique for relay networks with frequency selective fading channels is developed. the network relays use the filter-and-forward (ff) strategy to compensate for the transmitter-to-relay and relay-to-destination channels using finite impulse response (fir) filters. with the channel state information (csi) being available at the receiver, the transmit relay power is minimized subject to the destination quality-of-service (qos) constraint. this distributed beamforming problem is shown to have a closed-form solution. simulation results demonstrate substantial improvements in terms of the relay transmitted power and feasibility of the destination qos constraint as compared to amplify-and-forward (af) distributed beamforming techniques.
audio segmentation for speech recognition using segment features. audio segmentation is an essential preprocessing step in several audio processing applications with a significant impact e.g. on speech recognition performance. we introduce a novel framework which combines the advantages of different well known segmentation methods. an automatically estimated log-linear segment model is used to determine the segmentation of an audio stream in a holistic way by a maximum a posteriori decoding strategy, instead of classifying change points locally. a comparison to other segmentation techniques in terms of speech recognition performance is presented, showing a promising segmentation quality of our approach.
a generalized iterative water-filling algorithm for distributed power control in the presence of a jammer. consider a scenario in which k users and a jammer have a limited power budget and share a common spectrum of n orthogonal tones. the goal of each user is to allocate its power across the n tones in such a way that maximizes the total sum rate that he/she can achieve, while treating the interference of other users and the jammer's signal as additive gaussian noise. the jammer, on the other hand, wishes to allocate its power in such a way that minimizes the utility of the whole system; that being the total sum of the rates communicated over the network. for this non-cooperative game, we propose a generalized version of the existing iterative water-filling algorithm whereby the users and the jammer update their power allocations in a greedy manner. we study conditions under which the generalized iterative water-filling algorithm converges to a nash equilibrium of the game. the conditions that we derive in this paper depend only on the system parameters, and hence can be checked a priori.
on perfect channel identifiability of semiblind ml detection of orthogonal space-time block coded ofdm. this paper considers maximum-likelihood (ml) detection of orthogonal space-time block coded ofdm (ostbc-ofdm) systems without channel state information. our previous work has shown an interesting identifiability result, that the whole time-domain channel can be uniquely identified by only having one subchannel to transmit pilots. however, this identifiability is in a probability-one sense, under some mild assumptions on the channel statistics. in this paper we establish a “perfect” channel identifiability (pci) condition under which the channel is always uniquely identifiable. it is shown that pci can be achieved by judiciously applying the so-called non-intersecting subspace ostbcs. the resultant pci achieving scheme has its number of pilots larger than that used in the previous probability-one identifiability achieving scheme, but smaller than that required in conventional pilot-aided channel estimation. simulation results are presented to show that the proposed scheme can provide a better performance than the other schemes.
pushing information over acoustic channels. we propose a unidirectional communication system capable of pushing information from audio speakers to nearby audience via acoustic channels. though constrained by short transmission distances and low data throughput of sound waves, information push services based on acoustic channels can be regarded as a cost-free message delivery scheme since music playback systems and handheld devices equipped with recording capabilities have become ubiquitous in our life. furthermore, the proposed approach can provide better non-intrusiveness and more convenient user access than other auxiliary information delivery approaches like 2-d barcodes or watermarking schemes based on visual contents. to the best of our knowledge, our system is the first one that can effectively push information to receivers at feasible transmission throughput/robustness/distance within common noisy environments. various interesting applications and new business models can be facilitated with the proposed scheme.
multiple description video coding and iterative decoding of ldpca codes with side information. in this paper, we propose the use of multiple description coding to increase the robustness of distributed video coding while keeping good rate-distortion performance. the video sequence is structured into key frames and wyner-ziv frames. for each type of frame, two descriptions are generated by a multiple description scalar quantizer and sent on a loss-prone channel. when both wyner-ziv descriptions are received, they are jointly decoded along with the side information. we investigate the influence of the amount of redundancy and of the iterative decoding of the descriptions on the performance.
monaural voiced speech segregation based on elaborate harmonic grouping strategy. monaural speech segregation is a very challenging problem which has been studied by many researchers. in this paper, we focus on voiced speech segregation. different strategies are used to segregate resolved and unresolved harmonics respectively. for resolved harmonics, “harmonicity” principle and a novel mechanism based on “minimum amplitude” principle are employed. amplitude modulation rate is extracted by “enhanced” autocorrelation function of envelope to segregate unresolved harmonics which is more robust than previous method. an elaborate rule is also introduced to determine the regions dominated by resolved and by unresolved harmonics. proposed algorithm is evaluated on cooke's 100 mixtures and compared with a state-of-the-art algorithm hu and wang model. results show that proposed algorithm is more robust than the hu and wang model.
summarization of large scale social network activity. this paper presents a novel social media summarization framework. summarizing media created and shared in large scale online social networks unfolds challenging research problems. the networks exhibit heterogeneous social interactions and temporal dynamics. our proposed framework relies on the co-presence of multiple important facets: who (users), what (concepts and media), how (actions) and when (time). first, we impose a syntactic structure of the social activity (relating users, media and concepts via specific actions) in our temporal multi-graph mining algorithm. second, important activities along each facet are extracted as activity themes over time. experiments on flickr datasets demonstrate that our technique captures nontrivial evolution of media use in social networks.
minimum variance modulation filter for robust speech recognition. this paper describes a way of designing modulation filter by datadriven analysis which improves the performance of automatic speech recognition systems that operate in real environments. the filter for each nonlinear channel output is obtained by a constrained optimization process which jointly minimizes the environmental distortion as well as the distortion caused by the filter itself. recognition accuracy is measured using the cmu sphinx-iii speech recognition system, and the darpa resource management and wall street journal speech corpus for training and testing. it is shown that feature extraction followed by modulation filtering provides better performance than traditional mfcc processing under different types of background noise and reverberation.
cramér-rao bound for range estimation. in this paper, we derive the cramér-rao bound (crb) for range estimation, which does not only exploit the range information in the time delay, but also in the amplitude of the received signal. this new bound is lower than the conventional crb that only makes use of the range information in the time delay. we investigate the new bound in an additive white gaussian noise (awgn) channel with attenuation by employing both narrowband (nb) signals and ultra-wideband (uwb) signals. for nb signals, the new bound can be 3db lower than the conventional crb under certain conditions. however, there is not much difference between the new bound and the conventional crb for uwb signals. further, shadowing effects are added into the data model. several crb-like bounds for range estimation are derived to take these shadowing effects into account.
packet loss concealment based on extrapolation of speech waveform. a class of packet loss concealment algorithms for speech coding is presented. it generates the replacement waveform for the lost frame by direct extrapolation of the past speech waveform, with or without look-ahead. the itu-t g.722 appendix iii standard is based on it. when a future frame is unavailable (without look-ahead), the plc algorithm gives significantly better speech quality than g.711 appendix i - by about 0.2 pesq for high packet loss rates. when a future frame is available (with look-ahead), the plc algorithm uses the decoded speech waveform in the future frame to guide the pitch contour of waveform extrapolation during the lost frame such that the extrapolated waveform is phase-aligned with the decoded waveform after the packet loss. this technique further improved pesq by another 0.2 for high packet loss rates. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
weighted nonnegative matrix factorization. nonnegative matrix factorization (nmf) is a widely-used method for low-rank approximation (lra) of a nonnegative matrix (matrix with only nonnegative entries), where nonnegativity constraints are imposed on factor matrices in the decomposition. a large body of past work on nmf has focused on the case where the data matrix is complete. in practice, however, we often encounter with an incomplete data matrix where some entries are missing (e.g., a user-rating matrix). weighted low-rank approximation (wlra) has been studied to handle incomplete data matrix. however, there is only few work on weighted nonnegative matrix factorization (wnmf) that is wlra with nonnegativity constraints. existing wnmf methods are limited to a direct extension of nmf multiplicative updates, which suffer from slow convergence while the implementation is easy. in this paper we develop relatively fast and scalable algorithms for wnmf, borrowed from well-studied optimization techniques: (1) alternating nonnegative least squares; (2) generalized expectation maximization. numerical experiments on movielens and netflix prize datasets confirm the useful behavior of our methods, in a task of collaborative prediction.
phase scrambling for blind image matching. we propose a phase-scrambling method for blind image matching, which is a direct image matching between invisible images. the phase scrambling is motivated by visual protection of images and prevention of illegal image matching. phase-only correlation (poc) can be directly applied to images protected by the proposed phase scrambling in order to estimate similarity and translation between images. poc with synchronized scrambling provides blind image matching, in which phase scrambling does not affect the accuracy of poc. the effect of visual protection and prevention of illegal image matching is evaluated through simulations to show the effectiveness of the proposed method.
instantaneous rate estimation of neuronal point processes from a compressed representation of their nonbinary spike trains. estimating rate functions underlying neural point processes is essential for characterizing the firing patterns of cortical neurons involved in sensory and motor processing. this paper introduces a new method for directly estimating neuronal firing rates from a compressed representation of their extracellular recordings. the approach is based on extending a near-optimal sparse representation of the extracellular recordings to time scales matching those of the underlying rate functions, thereby performing the same role as a kernel-density estimator but at a much lower computational cost. experimental results demonstrate that this method achieves comparable performance to the conventional gaussian kernel estimation methods at a fraction of the computational cost. this makes it suitable to brain machine interface applications where real time decoding of neural activity for neuro-motor prosthetic control using firing rate estimates is strongly desired.
dictionary learning for the sparse modelling of atrial fibrillation in ecg signals. we propose a new method for ventricular cancellation and atrial modelling in the ecg of patients suffering from atrial fibrillation. our method is based on dictionary learning. it extends both the average beat subtraction and the sparse source separation approaches. experiments on synthetic data show that this method can almost completely suppress the ventricular activity, but it generates some artifacts. contrary to other ventricular cancellations methods, our approach also learns a model for the atrial activity.
detection of short distance wireless transmitted audio. with the advance of short distance wireless technologies, it becomes popular to include fm transmission capability to mobile devices such as hands-free car kits, cellular phones with hands-free features, and mp3 players so that in addition to playing audio signal through the on-device loudspeaker, they can relay audio signal to other audio system to utilized their superior audio quality. traditionally, the switch between the on-device loudspeaker and the fm transmitter is done manually. this paper proposes an automatic and switching algorithm which leverages the aec capability already exists in many of these mobile devices. the algorithm detects the presence of audio through fm channel and switches off the on-device loudspeaker, which adds to user convenience and power saving efficiency.
kalman fitler with phase spectrum compensation algorithm for speech enhancement. in this paper, we propose to combine the kalman filter with a recent speech enhancement technique, called the phase spectrum compensation procedure, or psc. more specifically, we apply the psc technique to initialise the kalman filter, whereby psc is used to clean the noisy speech prior to lpc estimation for the kalman recursion. we refer to the combined technique as the kalman-psc filter. using an objective speech quality measure, formal subjective listening tests and spectrogram analysis, we show that the proposed method results in improved speech quality.
on separating glottal source and vocal tract information in telephony speaker verification. the popular mel-frequency cepstral coefficients (mfccs) capture a mixture of speaker-related, phonemic and channel information. speaker-related information could be further broken down according to articulatory criteria. how these underlying components are exactly mixed in the features is not well understood. to this end, in this paper we aim at separating the spectra of glottal source and vocal tract using glottal inverse filtering, with an application to speaker recognition over telephone lines. our experiments on the 10sec-10sec condition of the nist 2006 sre corpus suggest that the mel-frequency cepstrum of the voice source is not too useful for recognizing speakers. on the contrary, fusing the vocal tract spectrum with conventional mfccs improves accuracy, suggesting that vocal tract information should be enhanced.
a three-class roc for evaluating doubletalk detectors in acoustic echo cancellation. doubletalk detector (dtd) is essential to keep adaptive filter from diverging in the presence of near-end speech in acoustic echo cancellation (aec), and there was a receiver operating characteristic (roc) to characterize dtd performance. however, the traditional roc for evaluating dtd used a static time-invariant room acoustic impulse response and could not evaluate dtds which distinguish echo path change from doubletalk. we solve these problems by extending the traditional binary detection roc to three-class, and simulations show the efficiency of the proposed method.
an auditory-based feature for robust speech recognition. a conventional automatic speech recognizer does not perform well in the presence of noise, while human listeners are able to segregate and recognize speech in noisy conditions. we study a novel feature based on an auditory periphery model for robust speech recognition. specifically, gammatone frequency cepstral coefficients are derived by applying a cepstral analysis on gammatone filterbank responses. our evaluations show that the proposed feature performs considerably better than conventional acoustic features. we further demonstrate that integrating the proposed feature with a computational auditory scene analysis system yields promising recognition performance.
a parametric copula based framework for multimodal signal processing. we present a framework for the joint processing of multimodal data such as audio-video data streams. we first consider the problem of estimating the joint distribution of statistically dependent multimodal random variables. we discuss the issues involved and provide a copula based solution. application of this approach to solve a multisensor fusion problem for the detection of a random event is also discussed.
distributed detection of a nuclear radioactive source based on a hierarchical source model. detection of a nuclear radioactive source is considered using a parallel sensor network architecture and a fusion center. a poisson-gamma hierarchical model is used to represent the distribution of the count data received by the sensors. local sensors are assumed to be single threshold binary quantizers that send a vector of sensor decisions over time to the fusion center for global decision-making. using the developed count model, a generalized likelihood ratio test (glrt) using a restricted range mle (rmle) is proposed to declare the global decision. the performance improvement resulting from using the restricted range mle over the unrestricted mle while implementing the glrt is depicted using simulated as well as real data collected from a test-bed using radiation sensors. using bootstrap, 95% confidence bounds on the roc curves, evaluated using real data, are obtained.
regular simplex criterion: a novel feature extraction criterion. feature extraction is an important topic in machine learning. there are two representative criterions for feature extraction, i.e. fisher criterion and maximum margin criterion. in this paper, we propose a new criterion, called regular simplex criterion. this criterion requires that samples from the same class are projected to the same point, while samples from different classes have unit distance. under this criterion, we present a novel dimensionality reduction method, namely linear simplex analysis (lsa). lsa is solved by multivariate linear regression with a specific definition of class indicator matrix which has a strong geometrical interpretation, i.e. each column of this matrix corresponds to a vertex of a regular simplex. several variants of lsa, e.g. regularized simplex analysis (rsa) and kernel simplex analysis (ksa), are also proposed. encouraging experimental results on uci machine learning database indicate that the new criterion as well as the proposed methods are very effective.
correction of b0 inhomogeneity distortion in magnetic resonance spectroscopic imaging. in this paper we reconstruct the 3-d mr spectroscopic data acquired using an echo-planar spectroscopic imaging (epsi) sequence. we propose to compensate for b0 inhomogeneity artifact by using the b0 field map and t2* decay estimated from a higher resolution, multi-slice proton imaging data scanned with similar shimming to the epsi one. we employ total variation (tv) regularization to obtain more uniform spectral peaks and lineshapes, and exploit the sparsity of the spectral data by using the ℓ1 norm in the reconstruction.
a fully affine invariant image comparison method. a fully affine invariant image comparison method, affine-sift (asift) is introduced. while sift is fully invariant with respect to only four parameters namely zoom, rotation and translation, the new method treats the two left over parameters : the angles defining the camera axis orientation. against any prognosis, simulating all views depending on these two parameters is feasible. the method permits to reliably identify features that have undergone very large affine distortions measured by a new parameter, the transition tilt. state-of-the-art methods hardly exceed transition tilts of 2 (sift), 2.5 (harris-affine and hessian-affine) and 10 (mser). asift can handle transition tilts up 36 and higher (see fig. 1).
bit-depth scalable video coding using inter-layer prediction from high bit-depth layer. scalable video coding (svc) is currently developed as an extension of h.264/avc video coding standard. in this paper, we propose three h.264/avc compliant bit-depth scalable video coding schemes, named lh mode (low bit-depth to high bit-depth), hl mode (high bit-depth to low bit-depth) and combined lh-hl mode for different applications. all these schemes efficiently exploit the high correlation between the high bit-depth layer and the low bit-depth layer on macroblock level. experimental results indicate that the hl mode outperforms the other two schemes and it achieves up to 7 db improvement over the simulcast where the high bit-depth video and low bit-depth representations are 12-bit and 8-bit, respectively.
using dependencies to pair samples for multi-view learning. several data analysis tools such as (kernel) canonical correlation analysis and various multi-view learning methods require paired observations in two data sets. we study the problem of inferring such pairing for data sets with no known one-to-one pairing. the pairing is found by an iterative algorithm that alternates between searching for feature representations that reveal statistical dependencies between the data sets, and finding the best pairs for the samples. the method is applied on pairing probe sets of two different microarray platforms.
underwater image enhancement by attenuation inversionwith quaternions. in this paper, an underwater image enhancement method using quaternions is presented. this work aims to improve color rendition and contrast of the objects, as if the scene has been taken out of water. this method is based on light attenuation inversion after processing a color space contraction using quaternions. applied to the white, the attenuation gives a hue vector caracterizing the water color. using this reference axis, geometrical transformations into the color space are computed with quaternions. pixels of water areas of processed images are moved to gray or colors with a low saturation whereas the objects remain fully colored. thus, the contrast of the observed scene is significantly improved and the difference between the background and the rest of the image is increased, giving a first approach towards a pre-segmentation step.
distributions of 3d dct coefficients for video. the three-dimensional discrete cosine transform (3d dct) has been proposed as an alternative to motion-compensated transform coding for video content. however, so far no definitive study has been done on the distribution of 3d dct coefficients of video sequences. this study performs two goodness-of-fit tests, the kolmogorov-smirnov (ks) test and the x2-test, to determine the distribution that best fits the 3d dct coefficients of the luminance components of video sequences with low motion or structured motion. the results indicate that the dc coefficient can be well approximated by a gaussian distribution and a majority of the high-energy ac coefficients can be approximated by a gamma distribution. knowledge of the coefficient distributions can be used to design quantizers optimized for 3d dct coefficients and hence achieve better coding efficiency.
gtd-based transceivers for decision feedback and bit loading. we consider new optimization problems for transceivers with dfe receivers and linear precoders, which also use bit loading at the transmitter. first, we consider the mimo qos (quality of service) problem, which is to minimize the total transmitted power when the bit rate and probability of error of each data stream are specified. the developments of this paper are based on the generalized triangular decomposition (gtd) recently introduced by jiang, li, and hager. it is shown that under some multiplicative majorization conditions there exists a custom gtd-based transceiver which achieves the minimal power. the problem of maximizing the bit rate subject to the total power constraint and given error probability is also considered in this paper. it is shown that the gtd-based systems also give the optimal solutions to the bit rate maximization problem.
a filter bank approach for led illumination sensing based on frequency division multiplexing. in this work, we consider illumination sensing in a light emitting diode (led) based illumination system that normally consists of a large number of leds. illumination sensing is used in order to facilitate the control of such system whose complexity, due to the large number of leds, can be quite high. in this paper, key requirements, i.e. accuracy and speed, on illumination sensing are described. furthermore, we present a filter bank sensor structure based on frequency division multiplexing. the design of the filter response is discussed in the context of supporting maximum number of leds, while the key requirements on illumination sensing are satisfied. in particular, it is shown that, through the use of the filter with a triangular filter response, a large number of leds can be supported in the presence of frequency offsets in a practical range.
the applicability of biased estimation in model and model order selection. biased estimation has the advantage of reducing the mean squared error (mse) of an estimator. the question of interest is how biased estimation affects model selection. in this paper, we introduce biased estimation to a range of model selection criteria. specifically, we analyze the performance of the minimum description length (mdl) criterion based on biased and unbiased estimation and compare it against modern model selection criteria such as kay's conditional model order estimator (cme), the bootstrap and the more recently proposed hook-and-loop resampling based model selection. the advantages and limitations of the considered techniques are discussed. the results indicate that, in some cases, biased estimators can slightly improve the selection of the correct model. we also give an example for which the cme with an unbiased estimator fails, but could regain its power when a biased estimator is used.
perception-based objective speech quality assessment. a joint spectro-temporal auditory model is utilized to assess speech quality objectively. the model mimics early and central auditory functions and serves as a spectro-temporal modulation filterbank. three perceptual relevant parameters, intelligibility, clarity and naturalness, are addressed by the model and are combined to estimate the subjective mean opinion score (mos) for speech quality measure. through a simple multiple linear regression analysis, we demonstrate the performance of our proposed perception-based objective speech quality measure is better than that of the state-of-the-art p.563 standard in estimating mos of the codec-distorted speech in itu-t supp. 23 database.
semi-definite programming approach to sensor network node localization with anchor position uncertainty. the problem of node localization in a wireless sensor network (wsn) with the use of the incomplete and noisy distance measurements between nodes as well as anchor position information is currently an an important yet challenging research topic. most wsn localization studies at present have assumed that the anchor positions are perfectly known which is not valid in the underwater and underground scenarios. in this paper, semi-definite programming (sdp) algorithms are devised for finding the localizations of unknown-position nodes in the presence of anchor position uncertainty. computer simulations are included to contrast the performance of the proposed algorithms with the conventional sdp method and cramér-rao lower bound.
color image feature extraction using color index local auto-correlations. in this paper, we propose a method for extracting color image features, called color index local auto-correlations. pixel color is quantized and described sparsely in a manner similar to the color indexing of color histograms. in addition, by utilizing spatial auto-correlations of the color indexes, the characteristics of color texture can be extracted more effectively than ordinary histogram-based methods. the proposed method has variants in terms of the color space and basic colors used for indexing colors. these various settings are comprehensively compared in the experiments of image retrieval and image classification, and are shown to exhibit favorable results compared to the other conventional methods.
h.264 fast intra mode selection algorithm based on direction difference measure in the pixel domain. in this paper, a fast mode decision algorithm for intra prediction in the h.264/avc is proposed. we use the characteristics of each directional prediction mode to compute the strength of directional differences in the original pixel domain to find the minimal direction error. this is the first time reported in the literature that the intrinsic differences between the real-data and the predictors of modes are used to form an algorithm for mode decision. the approach allows us to select several better candidate modes for evaluation instead of using the full search. experimental results show that the proposed method can achieve more than 80% reduction in computation with negligible degradation in rate-distortion performance, and the results are better than other algorithms available in the literature.
architecture design and implementation of the increasing radius - list sphere detector algorithm. a list sphere detector (lsd) is an enhancement of a sphere detector (sd) that can be used to approximate the optimal map detector. in this paper, we introduce a novel architecture for the increasing radius (ir)-lsd algorithm, which is based on the dijkstra's algorithm. the parallelism possibilities are introduced in the presented architecture, which is also scalable for different multiple-input multiple-output (mimo) systems. the novel architecture is implemented on a virtex-iv field programmable gate array (fpga) chip using high-level ansi c++ language based catapult c synthesis tool from mentor graphics. the used word lengths, the latency of the design, and the required resources are presented and analyzed for 4 × 4 mimo system with 16- quadrature amplitude modulation (qam). the detector implementation achieves a maximum throughput of 12.1mbps at high signal-to-noise ratio (snr).
a watermarking-based method for single-channel audio source separation. in this paper, we address the issue of audio source separation with a single channel, i.e. the estimation of source signals from a single mixture of these signals. this problem is addressed with a specific configuration: source signals are assumed to be available before the mix is processed. we propose an original method that uses a watermarking technique to embed information about the source signals into the mix signal. extracting this watermark enables an end-user who has no access to the original sources to separate these signals from their mixture. thereby several instruments or voice signals can be segregated from a single piece of music to enable post-mixing processing such as volume control.
feature transformation based on discriminant analysis preserving local structure for speech recognition. to improve speech recognition performance, a feature transformation based on discriminant analysis has been widely used to reduce redundant dimensions of features. linear discriminant analysis (lda) and heteroscedastic discriminant analysis (hda) are often used for this purpose, and a generalization method for lda and hda called power lda (plda) has been proposed. however, these methods may result in unexpected dimensionality reduction for multimodal data. it is important to preserve the local structure of the data in reducing the dimensionality of multimodal data. in this paper we introduce two methods, locality preserving hda and locality preserving plda. we also give an efficient calculation scheme to obtain an optimal projection.
lower bounds on the mean square error derived from mixture of linear and non-linear transformations of the unbiasness definition. it is well known that in non-linear estimation problems the ml estimator exhibits a threshold effect, i.e. a rapid deterioration of estimation accuracy below a certain snr or number of snapshots. this effect is caused by outliers and is not captured by standard tools such as the cramér-rao bound (crb). the search of the snr threshold value can be achieved with the help of approximations of the barankin bound (bb) proposed by many authors. these approximations result from a linear transformation (discrete or integral) of the uniform unbiasness constraint introduced by barankin. nevertheless, non-linear transformations can be used as well for some class of p.d.f. including the gaussian case. the benefit is their combination with existing linear transformation to get tighter lower bounds improving the snr threshold prediction.
supervised nonlinear dimensionality reduction by neighbor retrieval. many recent works have combined two machine learning topics, learning of supervised distance metrics and manifold embedding methods, into supervised nonlinear dimensionality reduction methods. we show that a combination of an early metric learning method and a recent unsupervised dimensionality reduction method empirically outperforms previous methods. in our method, the riemannian distance metric measures local change of class distributions, and the dimensionality reduction method makes a rigorous tradeoff between precision and recall in retrieving similar data points based on the reduced-dimensional display. the resulting supervised visualizations are good for finding (sets of) similar data samples that have similar class distributions.
model-based human gait recognition using fusion of features. in this paper, we investigate the fusion of several features extracted from manually-labelled silhouettes. a novel approach for human gait recognition based on the combination of three discriminative features, i.e., the area, the gravity centre, and the orientation of each body component, is also proposed. experimental results show that the proposed method exhibits considerably better performance, in comparison to all existing methods that use manually-extracted silhouettes.
inflating compressed samples: a joint source-channel coding approach for noise-resistant compressed sensing. recently, a lot of research has been done on compressed sensing, capturing compressible signals using random linear projections to a space of radically lower dimension than the ambient dimension of the signal. the main impetus of this is that the radically dimension-lowering linear projection step can be done totally in analog hardware, in some cases even in constant time, to avoid the bottleneck in sensing and quantization steps where a large number of samples need to be sensed and quantized in short order, mandating the use of a large number of fast expensive sensors and a/d converters. reconstruction algorithms from these projections have been found that come within distortion levels comparable to the state of the art in lossy compression algorithms. this paper considers a variation on compressed sensing that makes it resistant to spiky noise. this is achieved by an analog real-field error-correction coding step. it results in a small asymptotic overhead in the number of samples, but makes exact reconstruction under spiky measurement noise, one type of which is the salt and pepper noise in imaging devices, possible. simulations are performed that corroborate our claim and in fact substantially improve reconstruction under unreliable sensing characteristics and are stable even under small perturbations with gaussian noise.
large scale natural image classification by sparsity exploration. we consider in this paper the problem of large scale natural image classification. as the explosion and popularity of images in the internet, there are increasing attentions to utilize millions of or even billions of these images for helping image related research. beyond the opportunities brought by unlimited data, a great challenge is how to design more effective classification methods under these large scale scenarios. most of existing attempts are based on k-nearest-neighbor method. however, in spite of the optimistic performance in some tasks, this strategy still suffers from that, one single fixed global parameter k is not robust for different object classes from different semantic levels. in this paper, we propose an alternative method, called ℓ1-nearest-neighbor, based on a sparse representation computed by ℓ1-minimization. we first treat a testing sample as a sparse linear combination of all training samples, and then consider the related samples as the nearest neighbors of the testing sample. finally, we classify the testing sample based on the majority of these neighbors' classes. we conduct extensive experiments on a 1.6 million natural image database on different semantic levels defined based on wordnet, which demonstrate that the proposed ℓ1-nearest-neighbor algorithm outperforms k-nearest-neighbor in two aspects: 1) the robustness of parameter selection for different semantic levels, and 2) the discriminative capability for large scale image classification task.
hashing the mar coefficients from eeg data for person authentication. electroencephalogram (eeg) recordings of brain waves have been shown to have unique pattern for each individual and thus have potential for biometric applications. in this paper, we propose an eeg feature extraction and hashing approach for person authentication. multi-variate autoregressive (mar) coefficients are extracted as features from multiple eeg channels and then hashed by using our recently proposed fast johnson-lindenstrauss transform (fjlt)-based hashing algorithm to obtain compact hash vectors. based on the eeg hash vectors, a naive bayes probabilistic model is employed for person authentication. our eeg hashing approach presents a fundamental departure from existing methods in eeg-biometry study. the promising results suggest that hashing may open new research directions and applications in the emerging eeg-based biometry area.
a probabilistic approach to clock synchronization of cascaded network elements. precision time protocol (ptp) synchronizes clocks of networked elements by exchanging messages containing precise time-stamps. based on the available timing information, different algorithms can be developed for the clock synchronization. this paper introduces a novel ptp-based method in which clock synchronization is formulated as a probabilistic inference problem and is solved by kalman filtering. the performance of this approach is verified by numerical results.
shape adaptive estimation of variance in steerable pyramid domain and its application for spatially adaptive image enhancement. in the recent years, denoising based on the spatially adaptive algorithms that employ anisotropic adaption have been developed. these methods are able to match to the local statistics, preserve the edges and truly remove the noise from the texture of the images. on the other hand, a huge proportion of image enhancement methods are implemented in the sparse domains (e.g., wavelets, curvelets, contourlets and steerable pyramid decomposition) due to impressive properties of these transforms such as heavy-tailed nature of marginal distribution, locality and multiresolution. in this paper we try to establish a relation between two mentioned approaches by estimating the local variances of steerable pyramid coefficients using a shape-adaptive window. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
user behavior modeling in peer-to-peer file sharing networks: dissecting download and removal actions. user behavior models are important for building realistic simulation environment for research on p2p multimedia file-sharing systems. in this paper, we build a user download behavior model and a user removal behavior model, which can describe important user characteristics that are not captured in the existing models. the proposed download behavior model incorporates retry behavior, and the removal behavior model integrates free-riding, file usage, and file removal. based on two-year real user logs, we derive the range of all the model parameters and generate many interesting observations. to validate the proposed models, we compare several models in a case study on the number of living replicas in p2p file-sharing systems. the results demonstrate the accuracy, usability, and advantage of the proposed models.
a multiplicative weight perturbation scheme for distributed beamforming in wireless relay networks with 1-bit feedback. this paper focuses on perturbation-based distributed beamforming with 1-bit feedback for wireless amplify-and-forward relay networks. we propose to use multiplicative perturbations based on givens rotations to adapt the beamforming weights while guaranteeing a sum power constraint for the relays. this perturbation scheme is shown to be computationally efficient and easy to design, thus allowing for low-complexity relay nodes. an adaptation of the givens rotation angle allows to approach optimum performance arbitrarily close. numerical simulations demonstrate noticeable performance gains over additive perturbation schemes that have been exclusively considered up to now.
coping with out-of-vocabulary words: open versus huge vocabulary asr. this paper investigates methods for coping with out-of-vocabulary words in a large vocabulary speech recognition task, namely the automatic transcription of italian broadcast news. two alternative ways for augmenting a 64k(thousand)-word recognition vocabulary and language model are compared: introducing extra words with their phonetic transcription up to 1.2m (million) words, or extending the language model with so-called graphones, i.e. subword units made of phone-character sequences. graphones and phonetic transcriptions of words are automatically generated by adapting an off-the-shelf statistical machine translation toolkit. we found that the word-based and graphone-based extensions allow both for better recognition performance, with the former performing significantly better than the latter. in addition, the word-based extension approach shows interesting potential even under conditions of little supervision. in fact, by training the grapheme to phoneme translation system with only 2k manually verified transcriptions, the final word error rate increases by just 3% relative, with respect to starting from a lexicon of 64k words.
fourier-based modeling of topologically complex bone data using various alternatives of 3d scalar fields. this article presents a new approach for fourier-based modeling of bone anatomies for compression and smoothing. by treating the bone surface as a level set of a 31) scalar field, we can model topologically complex models such as bones. in particular, we experiment with five different alternatives, and prove that 31) scalar field which allows monotonous continuity around the boundary can be a good choice for volumetric description of the surface. this allows avoiding gibbs phenomena which previous volume-based methods have suffered from, returning better results in compression and smoothing than other scalar fields. we demonstrate the efficacy of the proposed method by showing results with various bone data.
stochastic resource allocation for orthogonal access based on quantized csi: optimality, convergence and delay analysis. dynamic allocation of power, rate and channel access is a critical task in wireless networks. capitalizing on convex optimization and stochastic approximation tools, this paper develops a stochastic resource allocation algorithm that minimizes average transmit power under individual average rate constraints. focus is placed on networks where users transmit orthogonally over a set of parallel channels and transmissions are adapted based on quantized channel state information (csi) allowing even channel statistics to be unknown. convergence of the developed stochastic scheme is characterized and the average queue delays are obtained in closed form.
candidate proposal for itu-t super-wideband speech and audio coding. this paper describes the speech and audio codec that has been submitted to itu-t by huawei and etri as a candidate for the upcoming super-wideband and stereo extensions of rec. g.729.1 and g.718. the core codec in the current implementation is g.729.1 and the encoded frequency range is increased from 7 khz to 14 khz. therefore, the maximum bit rate is raised from 32 kbit/s to 64 kbit/s by adding five bitstream layers. a comprehensive overview of the codec is presented with a focus on the mono coding components. the results of the listening tests that have been conducted during the itu-t qualification phase are summarized. the proposed codec passes all quality requirements for mono input signals.
second-order differential adaptive microphone array. an adaptive second-order differential microphone design is proposed here that is constructed from a weighted sum of omnidirectional microphones. theoretically, only three microphones are required to form a second-order array. the three microphone signals are combined to form three unique fixed second-order beams. any second-order differential beampattern can be realized using a weighted sum of these three “building-block” beam outputs. if certain simple constraints are placed on the weighting of the three fixed beams, the two null locations that define the final second-order beampattern can be constrained to defined angular regions.
square-root free orthogonalization algorithms. this paper is concerned with the derivation and analysis of higher order algorithms of polynomial type for computing an orthonormal basis of a subspace. these algorithms are derived from unconstrained optimization of certain cost functions. the proposed methods are efficient and do not require square root computation. based on these, algorithms for orthonormalization with respect to a positive definite matrix and principal and minor subspace methods are developed. numerical experiments illustrate the theoretical results.
distributed optimization in an energy-constrained network using a digital communication scheme. we consider a distributed optimization problem where n nodes, sl, l ∈ {1, …, n}, wish to minimize a common strongly convex function ƒ(x), x = [x1, … , xn]t , and suppose that node sl only has control of variable xl. the nodes locally update their respective variables and periodically exchange their values over noisy channels. previous studies of this problem have mainly focused on the convergence issue and the analysis of convergence rate. in this work, we focus on the communication energy and study its impact on convergence. in particular, we study the minimum amount of communication energy required for nodes to obtain an ∈-minimizer of ƒ(x) in the mean square sense. in an earlier work, we considered analog communication schemes and proved that the communication energy must grow at the rate of ω(∈−1) to obtain an ∈-minimizer of a convex quadratic function. in this paper, we consider digital communication schemes and propose a distributed algorithm which only requires communication energy of o ((log ∈−1)3) to obtain an ∈-minimizer of ƒ(x). furthermore, the algorithm provided herein converges linearly. thus, distributed optimization with digital communication schemes is significantly more energy efficient than with analog communication schemes.
fast noise psd estimation with low complexity. although noise psd estimation is a crucial part of noise reduction algorithms, most noise psd estimators have problems in tracking non-stationary noise sources. recently, a noise psd estimator based on dft-subspace decompositions was proposed, which improves estimation of the psd of such noise sources. however, as this approach is based on eigenvalue decompositions per dft bin, it might be too computationally demanding for low-complexity applications like hearing aids. in this paper we present a method with similar noise tracking performance as the dft-subspace approach, but with low computational costs. this method is based on computation of high resolution perodiograms, and can estimate the noise psd when both speech and noise are present in a frequency bin. when combined with a complete noise reduction system, the proposed method can lead to an improvement for non-stationary noise sources of more than 1 db segmental snr and 0.3 on a pesq scale, compared to standard noise tracking methods such as minimum statistics and the quantile based approach, while computational complexity is in the same order of magnitude.
a speech presence microphone array beamformer using model based speech presence probability estimation. the purpose of this study is to investigate the performance of speech presence (sp) microphone array beamforming. when the presence uncertainty of the desired speech is considered, noise reduction is greatly achieved while preserving low speech distortion level. furthermore, we propose a novel model based speech presence probability (spp) estimator, exploring both the sinusoid structure of speech and signal-to-noise ratio (snr). finally, experiments verify the effectiveness of the proposed sp-beamformer, resulting in a better trade-off between speech distortion and noise leakage, and a corresponding higher output segmental snr, when compared with the classical beamformers.
effective metric-based speaker segmentation in the frequency domain. in this paper, we present an approach, called freqdist, for speaker segmentation based on a distance measurement applied in the frequency domain. to enhance the detection performance, the spectrum is reweighted using normalization techniques. additionally, noise-like (i.e. flat) spectra are removed based on the entropy. experiments using the timit database [1] and westdeutscher rundfunk broadcast data show that our segmentation approach yields a good performance compared to the distbic algorithm [2]. in particular, for the timit data our algorithm reaches a false alarm rate (far) less than half of the value of the distbic algorithm and a missed detection rate (mdr) of 7.0% instead of 13.1%.
an error robust ultra low delay audio coder using an ma prediction model. this paper compares two prediction structures for predictive perceptual audio coding in the context of the ultra low delay (uld) coding scheme. one structure is based on the commonly used ar signal model, leading to an iir predictor in the decoder. the other structure is based on an ma signal model, leading to an fir predictor in the decoder. we find that the ar-based predictor has a slightly better performance in case of an undisturbed transmission channel, but the ma-based predictor has a much better performance in case of transmission errors. for a bit error rate (ber) of 1.0e-5, the perceptual quality of the proposed ma model predictor achieves a mean objective difference grade (odg) of −0.66 odg whereas the ar model predictor only reaches −3.42 odg.
compressive wide-band spectrum sensing. we present a compressive wide-band spectrum sensing scheme for cognitive radios. the received analog signal at the cognitive radio sensing receiver is transformed in to a digital signal using an analog-to-information converter. the autocorrelation of this compressed signal is then used to reconstruct an estimate of the signal spectrum. we evaluate the performance of this scheme in terms of the mean squared error of the power spectrum density estimate and the probability of detecting signal occupancy.
power level difference as a criterion for speech enhancement. this paper deals with the problem of speech enhancement in near field condition, when two microphones are available. proposed technique relies on the difference in power of received signals at the two microphones. this difference is employed to estimate the clean speech signal power. the method has the capability of dealing with non-stationary noise, a drawback of many noise reduction techniques. superiority of the presented method over some of prominent methods in this field is demonstrated by conducting both subjective and objective quality tests.
narrowband interference mitigation in bicm ofdm systems. orthogonal frequency division multiplexing (ofdm) is noted for its resistance to narrowband interference when equipped with forward error correction. this technique along with erasure insertion is adequate when the the signal-to-interference ratio (sir) is moderate, around 0 db, however, when the interference is severe, i.e. sir = −20 db, a non-orthogonal interference corrupts a large number of the data subcarriers due to spectral leakage. this situation requires a large number of erasures that compromise the code's error correction capability. the prediction-error filter (pef) is proposed as an erasure insertion mechanism that localizes the erasures to the tones surrounding the interference, while not affecting the remaining tones. the simulation results indicate excellent performance, for the bit-interleaved coded modulated (bicm) ofdm system using the pef and bpsk modulation when the sir = −20 db in a frequency-selective fading channel.
compression of line spectral frequency parameters with asynchronous interpolation. tts systems require a trade-off between size and speech quality. a larger acoustic inventory allows synthesis of speech that sounds more natural. the asynchronous interpolation model improves the quality to size ratio, allowing better compression of large acoustic inventories, as well as better quality speech from a small system. at maximum compression, our method represents most phonemes by a single frame of data. coarticulation effects are specified as context-specific non-linear interpolation functions. dividing the speech features into multiple data streams allows asynchronous interpolation. in this study, aim was applied to lsf parameters. varying the number of streams allows for variable amount of compression. we used three different objective measures to investigate the effect of number and partitioning of streams. the first few weight functions (and the last one) seem to offer the most error reduction. partitions separating the first 6 lsfs score well with all three measures.
product-hmms for automatic sign language recognition. we address multistream sign language recognition and focus on efficient multistream integration schemes. alternative approaches are investigated and the application of product-hmms (phmm) is proposed. the phmm is a variant of the general multistream hmm that also allows for partial asynchrony between the streams. experiments in classification and isolated sign recognition for the greek sign language using different fusion methods, show that the phmms perform the best. fusing movement and shape information with the phmms has increased sign classification performance by 1,2% in comparison to the parallel hmm fusion model. isolated sign recognition rate increased by 8,3% over movement only models and by 1,5% over movement-shape models using multistream hmms.
the speed of greed: characterizing myopic gossip through network voracity. this paper analyzes the rate of convergence of greedy gossip with eavesdropping (gge). in previous work, we proposed gge, a fast gossip algorithm based on exploiting the broadcast nature of wireless communications rather than location information. assuming all transmissions are wireless broadcasts, nodes can keep track of their neighbors' values by eavesdropping on their communications. then, when it comes time to gossip, a node greedily and myopically gossips with the neighbor whose value is most different from its own, rather than with a randomly chosen neighbor. previously, we have proved that gge converges to the average consensus on connected network topologies and demonstrated that gge outperforms standard randomized gossip (rg). in this paper we study the rate of convergence of gge in terms of network voracity which is a topology-dependent constant analogous to the second-largest eigenvalue characterization for rg. simulations demonstrate that the convergence rate of gge is superior to existing average consensus algorithms such as geographic gossip.
real-time implementation of robust face detection on mobile platforms. although many face detection algorithms have been introduced in the literature, only a handful of them can meet the real-time constraints of mobile devices. this paper presents the real-time implementation of our previously introduced face detection algorithm on a mobile device. the steps taken to achieve such a real-time implementation are discussed. real-time comparison results with the widely used viola-jones face detection algorithm in terms of detection rate and processing speed are presented to demonstrate the robustness of our real-time solution.
a gmm supervector kernel with the bhattacharyya distance for svm based speaker recognition. gaussian mixture model (gmm) supervector is one of the effective techniques in text independent speaker recognition. in our previous work, we introduce the gmm-ubm mean interval (gumi) concept based on the bhattacharyya distance. subsequently gumi kernel was successfully used in conjunction with support vector machine (svm) for speaker recognition. besides the first order statistics, it is generally believed that speaker cues are also partly conveyed by second order statistics. in this paper, we extend the bhattacharyya-based svm kernel by constructing the supervector with the mean statistical vector and the covariance statistical vector. comparing with the kullback-leibler (kl) kernel, we demonstrate the effectiveness of the new kernel on the 2006 national institute of standards and technology (nist) speaker recognition evaluation (sre) dataset.
exploring functional connectivity in fmri via clustering. in this paper we investigate the use of data driven clustering methods for functional connectivity analysis in fmri. in particular, we consider the k-means and spectral clustering algorithms as alternatives to the commonly used seed-based analysis. to enable clustering of the entire brain volume, we use the nyström method to approximate the necessary spectral decompositions. we apply k-means, spectral clustering and seed-based analysis to resting-state fmri data collected from 45 healthy young adults. without placing any a priori constraints, both clustering methods yield partitions that are associated with brain systems previously identified via seed-based analysis. our empirical results suggest that clustering provides a valuable tool for functional connectivity analysis.
dna coding using finite-context models and arithmetic coding. the interest in dna coding has been growing with the availability of extensive genomic databases. although only two bits are sufficient to encode the four dna bases, efficient lossless compression methods are still needed due to the size of dna sequences and because standard compression algorithms do not perform well on dna sequences. as a result, several specific coding methods have been proposed. most of these methods are based on searching procedures for finding exact or approximate repeats. low order finite-context models have only been used as secondary, fall back mechanisms. in this paper, we show that finite-context models can also be used as main dna encoding methods. we propose a coding method based on two finite-context models that compete for the encoding of data, on a block by block basis. the experimental results confirm the effectiveness of the proposed method.
unsupervised acoustic and language model training with small amounts of labelled data. we measure the effects of a weak language model, estimated from as little as 100k words of text, on unsupervised acoustic model training and then explore the best method of using word confidences to estimate n-gram counts for unsupervised language model training. even with 100k words of text and 10 hours of training data, unsupervised acoustic modeling is robust, with 50% of the gain recovered when compared to supervised training. for language model training, multiplying the word confidences together to get a weighted count produces the best reduction in wer by 2% over the baseline language model and 0.5% absolute over using unweighted transcripts. oracle experiments show that a larger gain is possible, but better confidence estimation techniques are needed to identify correct n-grams.
automatic prosodic events detection using syllable-based acoustic and syntactic features. automatic prosodic event detection is important for both speech understanding and natural speech synthesis since prosody provides additional information over the short-term segmental features and lexical representation of an utterance. similar to previous work, this paper focuses on automatic detection of coarse level representation of pitch accents, intonational phrase boundaries (ipb), and break indices. we exploit various classifiers and identify effective feature sets to improve performance of prosodic event detection according to acoustic, lexical, and syntactic evidence. our experiments on the boston university radio news corpus show that the neural network classifier achieves the best performance for modeling acoustic evidence, and that support vector machines are more effective for the lexical and syntactic evidence. the combination of the acoustic and the syntactic models yields 89.8% accent detection accuracy, 93.3% ipb detection accuracy, and 91.1% break index detection accuracy. compared with previous work, the ipb perfromance is similar, whereas the results for accent and break index detection are significantly better.
subspace based doa estimation in the presence of correlated signals and model errors. high-resolution subspace based direction-of-arrival (doa) estimation requires a number of assumptions about the signal and antenna. in our application automotive radar, among many practical problems, signals are often correlated and the antenna is not calibrated. this difficult combination has been seldom addressed in the literature. in this paper, we study their simultaneous impact on doa estimation, describe a so called “coherent model error interference” phenomenon, propose a prewhitening scheme for algebraic subspace based doa estimation, and show some simulation results.
joint source decoding in large scale sensor networks using markov random field models. scalable joint decoding of correlated observations transmitted using distributed quantization in a sensor-network is considered. in particular, quantized observations are modeled as a markov-random filed (mrf), from which we construct a factor-graph for implementing the decoder using the well known sum-product algorithm. an attractive property of this approach is that the decoder complexity can be controlled by the choice of the clique structure used to define the gibbs distribution of the mrf model. the experimental results obtained with a widely used correlated gaussian observation model is presented, which demonstrate that substantial performance gains can be achieved by joint decoding based on simple clique structures and potential functions.
incorporating monolingual corpora into bilingual latent semantic analysis for crosslingual lm adaptation. the major limitation in bilingual latent semantic analysis (blsa) is the requirement of parallel training corpora. motivated by semi-supervised learning, we propose a clusterbased blsa training approach to incorporate monolingual corpora. treating each parallel document pair as centroids of the parallel document clusters, each monolingual document is associated to the closest centroid according to their topic similarity. the resulting parallel document clusters are used as constraints to enforce a one-to-one topic correspondence in variational em. slight performance improvement in crosslingual language model adaptation is observed compared to the baseline without monolingual corpora.
complete characterization of perfectly secure stego-systems with mutually independent embedding operation. without any assumption on the cover source, this paper presents a complete characterization of all perfectly secure stego-systems that employ mutually independent embedding operation. it is shown that for a fixed embedding operation, the only perfectly secure stego-systems are those whose cover distribution is an element of a linear vector space with basis vectors determined by the embedding operation. moreover, we also prove that such stego-systems are perfectly secure if and only if the fisher information with respect to the embedding change rate is zero and thus fisher information can be seen as an equivalent descriptor of steganographic security. this result is important for deriving steganographic capacity of imperfect stego-systems with covers modeled as markov chains [1]. it also suggests that fisher information could be used for benchmarking.
optimal cepstrum estimation using multiple windows. the aim of this paper is to find a multiple window estimator that is mean square error optimal for cepstrum estimation. the estimator is compared with some known multiple window methods as well as with the parametric ar-estimator. the results show that the new estimator has high performance, especially for data with large spectral dynamics, and that it is also robust against parameter choices. simulated speech data is used for the evaluation. it is also shown that the windows of the estimator can be approximated with the sinusoidal multiple windows and that the weighting factors of the different periodograms can be analytically computed.
real-time stereo matching: a cross-based local approach. we propose an area-based local stereo matching algorithm that yields accurate disparity estimates, while achieving the real-time speed completely on the graphics processing unit (gpu). for a local stereo method, the key challenge is to decide an appropriate support window for the pixel under consideration. our stereo method starts with computing an upright local cross adaptively for each anchor pixel, which defines a per-pixel support skeleton. next, based on this compact local cross representation, we aggregate the matching costs in a shape adaptive full support region using two orthogonal integration steps. approximating scene structures accurately, the proposed method is among the best-performing real-time stereo methods according to the benchmark middlebury stereo evaluation. additionally, our method is very easy to implement, memory efficient, and hence it is promising for many practical applications.
an efficient hardware design of an optimal nonstationary filtering system. the development of a multi-cycle hardware design of a time-varying (tv) filtering system, suitable for real-time implementation on an integrated chip is outlined in this work. based on results of time-frequency (tf) analysis and the instantaneous frequency (if) estimation, the proposed design enables multiple detection of the local filter's region of support (frs) in the observed time-instant, resulting in the efficient filtering of multicomponent fm signals. the proposed design optimizes critical design performances (such as hardware complexity, energy consumption and hardware cost), making it a suitable system for real-time implementation on a chip. the design has been verified by an fpga (field-programmable gate array) circuit design.
applying improved spectral modeling for high quality voice conversion. in this work, accurate spectral envelope estimation is applied to voice conversion in order to achieve high-quality timbre conversion. true-envelope based estimators allow model order selection leading to an adaptation of the spectral features to the characteristics of the speaker. optimal residual signals can also be computed following a local adaptation of the model order in terms of the f0. a new perceptual criteria is proposed to measure the impact of the spectral conversion error. the proposed envelope models show improved spectral conversion performance as well as increased converted-speech quality when compared to linear prediction.
consensus-tracking in distributed networks by one-hop averaging. for a connected network of sensors we consider deriving the linear update weights required by a 1-hop distributed linear averaging algorithm (denoted 1-dla) such that average-consensus is reached when the sensor nodes simultaneously track, by linear stochastic approximation, a set of distinct markov chains with time-varying regime. it is found the desired consensus is infeasible for any 1-hop 1-dla type algorithm in this setting, which includes the consensus filter proposed in [2]. however, assuming a symmetric communication graph we show the average-consensus can be approached with zero asymptotic error by an alternative 1-hop algorithm (denoted 4-dla) that requires each sensor compute 4 estimates {π̂ s, s0, ŝ} rather than only {s} as required under 1-dla. we demonstrate a simulation of 4-dla and explain its advantages compared to alternative multi-hop algorithms.
automatic parameter optimization for a perceptual audio codec. in audio codec design, often various parameters have to be fixed which may have a dramatic impact on codec performance. in this paper, we report on successful optimization of a codec based on perceptual criteria. specifically, the peaq measure is used to determine the audio quality over a set of test items and search algorithms are used for optimization. first, simulated annealing is used for global search, then rosenbrock's method is used to further refine the result. as shown by an example, the improvements gained by optimization compared to an educated guess are substantial.
voiced/unvoiced pattern-based duration modeling for language identification. most existing duration modeling approaches facilitates phone recognizer and require manually annotated corpus to train the segmentation models, which is usually cost- and time-consuming. in this paper, a novel duration modeling approach is proposed, which does not require phone recognizer/annotated training data, and facilitates fast computation of language identification. in this approach, the segmentation is implemented by using articulatory features like voicing status. a pair of connected unvoiced and voiced segments is considered as the unit, and the duration of each segment is normalized for each utterance and then quantized into 20 discrete ranges. the ranges of units are later considered as symbol sequences and are modeled by n-gram models, to capture the temporal pattern, which is hypothesized to vary in different languages. the experiments based on the nist lre 2005 tasks show a relative 19.7% eer improvement by introducing the proposed duration modeling-based system into a fusion system containing two gmm-ubm based acoustic systems using mfcc and pitch+intensity features.
multi-resolution based hybrid spatiotemporal compression of encrypted videos. compression of encrypted data can be viewed as a special case of distributed source coding and can be achieved by applying slepian-wolf coding. however, how to compress the encrypted video efficiently remains a challenging problem especially for those videos with irregular high motion. this paper proposes a novel multi-resolution based approach which makes it possible not only to effectively derive the temporal side information from previous frames, but also to generate the spatial side information by having partial access to the current frame. the spatial and temporal side information can then be integrated adaptively to facilitate the compression. simulation results show that the proposed scheme significantly outperforms other schemes, especially for those video clips with irregular high motion.
part-of-speech histograms for genre classification of text. this work addresses the problem of classifying the genre of text, which is useful for a variety of language processing problems. we propose statistics of pos histograms as classification features, coupled with a quadratic discriminant classifier. in experiments on six different text and speech genres, we demonstrate enhanced performance compared to standard techniques using word frequency count features and pos trigram features. experiments on genres that were not seen in training show intuitive overlaps with the training classes.
ofdm symbol detection with interspersed pilot symbols and channel distribution information at the receiver. detection of ofdm transmissions with interspersed pilot symbols is considered. a hard output detection algorithm developed by taricco et. al. for flat fading channels is extended for this frequency selective scenario. in the investigated systems with 128 subcarriers, this algorithm outperforms conventional approaches and performs close to a genie aided receiver even with the use of a single pilot symbol for the whole frame. furthermore, a novel soft output generating algorithm is developed, which is more suitable for channel coded systems. the resultant algorithm is capable of detecting coded ofdm transmissions with fewer pilot symbols than that required for noiseless channel identification.
context-dependent pronunciation modeling for iraqi asr. in this paper, we introduce a novel pronunciation modeling technique that in contrast to existing techniques uses word context information. this context-dependent pronunciation modeling is designed to overcome the challenges posed by absence of diacritics in transcripts for training acoustic models for arabic dialects. to demonstrate the efficacy of the proposed pronunciation modeling, we present experimental results with both manually created and automatically generated vowelized lexicons on the darpa transtac colloquial iraqi corpus.
speech enhancement based on minima controlled recursive averaging incorporating conditional maximum a posteriori criterion. in this paper, we propose a novel approach to improve the performance of minima controlled recursive averaging (mcra) based on a conditional maximum a posteriori (map) criterion. from an investigation of the mcra scheme, it is discovered that mcra method cannot take full consideration of the inter-frame correlation of voice activity since the noise power estimate is adjusted by the speech presence probability depending on an observation of the current frame. to avoid this phenomenon, the proposed mcra approach incorporates the conditional map criterion in which the noise power estimate is obtained using the speech presence probability conditioned on both the current observation and the speech activity decision in the previous frame experimental results show that the proposed mcra technique based on conditional map yields better results compared to the conventional mcra method.
resource usage prediction for groups of dynamic image-processing tasks using markov modeling. with the introduction of dynamic image processing, such as in image analysis, the computational complexity has become data dependent and memory usage irregular. therefore, the possibility of runtime estimation of resource usage would be highly attractive and would enable quality-of-service (qos) control for dynamic image-processing applications with shared resources. a possible solution to this problem is to characterize the application execution using model descriptions of the resource usage. in this paper, we attempt to predict resource usage for groups of dynamic image-processing tasks based on markov-chain modeling. as a typical application, we explore a medical imaging application to enhance a wire mesh tube (stent) under x-ray fluoroscopy imaging during angioplasty. simulations show that markov modeling can be successfully applied to describe the resource usage function even if the flow graph dynamically switches between groups of tasks. for the evaluated sequences, an average prediction accuracy of 97% is reached with sporadic excursions of the prediction error up to 20–30%.
missing data recovery via a nonparametric iterative adaptive approach. we introduce a missing data recovery methodology based on a weighted least squares iterative adaptive approach (iaa). the proposed method is referred to as the missing-data iaa (miaa) and it can be used for uniform or non-uniform sampling as well as for arbitrary data missing patterns. miaa uses the iaa spectrum estimates to retrieve the missing data, based on a spectral least squares criterion similar to that used by iaa. numerical examples are presented to show the effectiveness of miaa for missing data recovery. we also show that miaa can outperform an existing competitive approach, and this at a much lower computational cost.
comparison of four estimators of the 3d cardiac electrical activity for surface ecg synthesis from intracardiac recordings. the aim of this study is to facilitate the home follow-up of patients treated with cardiac implantable devices. a new procedure to synthesize 12-lead ecg from intracardiac egm is proposed. it is based on the estimation of: (i) a 3d representation of the cardiac electrical activity both for ecg (vcg) and egm (vgm), and (ii) the transfer function between the vgm and the vcg. the extraction of vcg and vgmis performed by comparing four different algorithms based on pca and ica, whereas the non-linear transfer function between vcg and vgm is estimated using a specific neural network. results demonstrate the effectiveness of the proposed method in comparison with our previous work. indeed, the correlation coefficients, between the real ecg and the synthesized ecg, lie between 0.78 and 0.99, whereas correlation coefficients of the previous method (combining pca and linear wiener filter) lie between 0.6 and 0.94.
sparse probabilistic state mapping and its application to speech bandwidth expansion. in this paper we present a probabilistic algorithm that extracts a mapping between two subspaces by representing each subspace as a collection of states. an arbitrary increase in number of states results in over-fitting the training data without exploring the underlying structure of the map. this paper suggests a method to impose sparsity constraints on the state map by using entropic priors. this probabilistic model is applied to the problem of artificial bandwidth expansion that involves estimating the missing frequency components (3.7 – 8 khz and 0 – 0.3 khz) of speech given the narrowband speech signal (0.3 – 3.7 khz).
a practical walsh layering scheme for reliable transmission. concerning the uncertainty of channels and peak power constraint, we give a new practical layering scheme to do reliable transmission. in our scheme, walsh matrix is employed to do layer-time coding. regarding columns of a layer-time coding matrix as layers and rows as time, after walsh layer-time coding, interference among layers can be removed or diminished by adding rows up. when there are layers decoded successfully after the previous transmission, only not-yet-decoded layers will be retransmitted. simulation results show that our walsh layering scheme with hybrid automatic repeat request (harq) performs much better than the traditional single-layer arq sequential transmission with respect to average time delay.
anti-collusion fingerprinting with scalar costa scheme (scs) and colluder weight recovery. an anti-collusion fingerprinting system is developed to protect media files against time-varying collusion attacks based on the scalar costa scheme (scs) and colluder weight recovery. we treat the host signal as a parallel gaussian channel and fingerprints as transmitted user signals. we decompose the gaussian channel into multiple independent subchannels, and assign different user messages to different subchannels. then, colluder weights in collusion attacks can be estimated using pilot symbols at the decoder, and all weights can be estimated and compensated. as a result, the decoding region on the parametric space can be recovered as an original format. it is shown by experimental results that the proposed fingerprinting system has excellent performance in colluder detection.
a scalable method for voice search to nationwide business listings. voice search or 411-service is the task that finds a ranked set of directory listings that match a spoken query, where the target entries in the listing database and the spoken query may differ moderately in their syntactic form. while the conventional paradigm uses a two-box input (location + name), a single-box paradigm to voice search can allow users to provide all the information in a single utterance, thereby increasing query efficiency. furthermore, the scalability of traditional methods used in the two-box paradigm is infeasible, and alternative strategies that sacrifice accuracy are normally adopted. this work presents a scalable algorithm for directory search over a nationwide database of listings (millions of entries) without compromising recognition accuracy.
stereo-based stochastic mapping with discriminative training for noise robust speech recognition. this paper presents an enhanced stochastic mapping technique in the discriminative feature (fmpe) space that exploits stereo data for noise robust lvcsr. both mmse and map estimates of the mapping are given and the performance of the two is investigated. due to the iterative nature of the map estimate, we show that combining mmse and map estimates is possible and yields superior performance than each individual estimate. a multi-style discriminative training with minimum phone error (mpe) criterion is further applied to the compensated features and obtains significant performance improvement on real-world noisy test sets.
a reduced order model of head-related impulse responses based on independent spatial feature extraction. a reduced order model for large numbers of head-related impulse responses (hrirs) is proposed for real-time three-dimensional (3d) sound rendering. independent spatial features are firstly extracted from measured hrirs using independent component analysis (ica). these spatial feature vectors are not only mutually statistical independent but independent from all the measured azimuths. therefore filtering sound sources with numerous hrirs is transformed into filtering them using the extracted lower-dimensional feature vectors. furthermore balanced model truncation (bmt) method in a state space is adopted to reduce the order of each independent feature vector. simulation results demonstrate that our proposed algorithm not only acquires better approximated accuracy but has significantly lower computational complexity.
cross-validation of multiple language recognition systems using pseudo keys. in this paper, we present a pseudo-key analysis approach for cross-validation of language recognition systems before the ground truth (true key) becomes available. a state-of-the-art language recognition system typically employs multiple language recognition classifiers which are fused to form a mixture of experts. the individual classifiers are also called subsystems. to avoid the fused system from being brought down by some outlier classifiers, pseudo keys are designed to cross-examine the integrity of individual classifier candidates. the language recognition experiments are conducted on the nist 2007 language recognition evaluation (lre) corpus using the subsystems in the primary submission from the institute for infocomm research (iir).
time-sensitive behavior dynamics in multimedia fingerprinting social networks. multimedia social network is a network infrastructure in which the social network members share multimedia contents with all different purposes. analyzing user behavior in multimedia social networks help design more secured and efficient multimedia and networking systems. in this paper, we focus on the colluder social network in multimedia fingerprinting systems in which colluders gain reward by redistributing the colluded multimedia signal. however, the market value of the redistributed multimedia content is time sensitive. the earlier the colluded copy being released, the more the people who are willing to pay for it. thus the colluders have to reach agreement on how to distribute reward and the probability being detected among themselves as soon as possible. this paper incorporates the time-sensitiveness of the colluders' reward, and models the dynamics among colluders as a noncooperative game, and studies the time-restricted bargaining equilibrium. we provide the solution to the equilibrium that all the colluders have no inventive to disagree in order to maximize their own payoff.
blind system identification for speech dereverberation with forced spectral diversity. the common zeros problem for blind system identification (bsi) is well known. it degrades the performance of classic bsi algorithms and therefore imposes the limit on the performance of subsequent speech dereverberation. the effect of near-common zeros has recently been studied in terms of channel diversity and the degradation in performance of bsi and multichannel equalization algorithms has been shown. we now introduce a novel approach to improve channel diversity which we refer to as forced spectral diversity (fsd). the fsd concept uses a combination of spectral shaping filters and effective channel undermodelling. simulation results show that the proposed approach achieves improved performance with reduced complexity for multichannel bsi in a room acoustics example.
two microphone based direction of arrival estimation for multiple speech sources using spectral properties of speech. a two microphone direction of arrival (doa) estimation technique for multiple speech sources is developed which exploits speech specific properties, namely sparsity in time-frequency (spectrum) domain. for robustness, we exploit the sparsity in the frequency domain by focusing on the spectral content concentrated in sinusoidal tracks obtained through sinusoidal modeling. when multiple speeches are mixed in the two microphone system, the inter-channel phase differences (ipd) between the dual channels on those sinusoidal tracks will be dominated by the spatial information of the most powerful source at that specific time-frequency point because of the spectrum sparsity and masking effects. thereby, the source localization problem is turned into a clustering problem on the ipd versus frequency plot, and the generalized mixture decomposition algorithm (gmda) is used to cluster the groups of points corresponding to multiple sources. the doa of each source is derived from the parameters of each cluster. experimental results conducted show the scheme to be very effective.
role of head pose estimation in speech acquisition from distant microphones. reverberant environments pose a challenge to speech acquisition from distant microphones. approaches using microphone arrays have met with limited success. recent research using audio-visual sensors for tasks such as speaker localization has shown improvement over traditional audio-only approaches. using computer vision techniques we can estimate the orientation of the speaker's head in addition to the location of the speaker. in this paper we study the utility of using the head pose information for effective beamforming and clean speech acquisition from distant microphones. the improvements in speech recognition accuracy relative to that of a close talking microphone are presented and the results provide sufficient motivation for incorporating head pose information in beamforming techniques.
qualitative analysis of rotational modes within three dimensional empirical mode decomposition. an analysis of quaternion-valued intrinsic mode functions (imfs) within three dimensional empirical mode decomposition is presented. this is achieved by using the delay vector variance (dvv) method, which examines the signal predictability in phase space to assess the determinism and nonlinearity within the signal. the study illustrates that the contribution of the first few imfs contain information related to the stochastic/nonlinear signal nature, whereas the lower order imfs are largely deterministic. the analysis is supported by simulation results on a quaternion signal composed of linear/nonlinear benchmark signals and on real world wind data.
a split quaternion nonlinear adaptive filter. a split quaternion learning algorithm for the training of nonlinear finite impulse response filters for the modelling of hypercomplex signals is proposed. a rigorous derivation takes into account the non-commutativity of the quaternion product, an aspect not taken into account in the existing nonlinear architectures, such as the quaternion multilayer perceptron (qmlp). it is shown that the additional information present within the proposed algorithm provides an improved performance over qmlp. simulation on both benchmark and real-world signals support the approach.
robust and fast non asymmetric distributed source coding using turbo codes on the syndrome trellis. we consider the distributed compression of two (binary memoryless) correlated sources and propose a unique codec that can reach any point in the slepian-wolf region. in a previous method based on channel codes, the decoder multiply the compressed data by an inverse submatrix of the code. this multiplication presents two drawbacks. first, if turbo codes are used, the submatrix has no periodic structure s.t. the whole inverse has to be stored and no fast implementation exists for the multiplication. second, this multiplication may lead to error propagation. in this paper, we propose a method that is both robust and fast.
optimal widely linear mvdr beamforming for noncircular signals. this paper introduces the optimal widely linear (wl) minimum variance distorsionless response (mvdr) beamformer for the reception of an unknown signal of interest (soi) corrupted by potentially second order (so) noncircular background noise and interference. the soi, whose waveform is unknown, is assumed to be so noncircular with arbitrary noncircular properties. in the steady state and for so noncircular soi and/or interference, this new wl beamformer, that is derived from an original orthogonal decomposition, is shown to always improve the performance of both the well-known capon's beamformer and a wl mvdr beamformer introduced recently in the literature. this optimal wl mvdr beamformer is first introduced and some of its performance are analyzed. then, several adaptive implementations of this optimal wl beamformer are presented.
video event detection and summarization using audio, visual and text saliency. detection of perceptually important video events is formulated here on the basis of saliency models for the audio, visual and textual information conveyed in a video stream. audio saliency is assessed by cues that quantify multifrequency waveform modulations, extracted through nonlinear operators and energy tracking. visual saliency is measured through a spatiotemporal attention model driven by intensity, color and motion. text saliency is extracted from part-of-speech tagging on the subtitles information available with most movie distributions. the various modality curves are integrated in a single attention curve, where the presence of an event may be signified in one or multiple domains. this multimodal saliency curve is the basis of a bottom-up video summarization algorithm, that refines results from unimodal or audiovisual-based skimming. the algorithm performs favorably for video summarization in terms of informativeness and enjoyability.
on the performance of semidefinite relaxation mimo detectors for qam constellations. due to their computational efficiency and strong empirical performance, semidefinite relaxation (sdr)-based algorithms have gained much attention in multiple-input multiple-output (mimo) detection. in the case of a binary phase-shift keying (bpsk) constellation, the theoretical performance of the sdr approach is relatively well-understood. however, little is known about the case of quadrature amplitude modulation (qam) constellations, although simulation results suggest that the sdr approach should work well in the low signal-to-noise ratio (snr) region. in this paper we make a first step towards explaining such phenomenon by showing that in the case of qam constellations, several commonly used sdr-based algorithms will provide a constant factor approximation to the optimal log-likelihood value in the low snr region with exponentially high probability. our result gives some theoretical justification for using sdr-based algorithms for the mimo detection of qam signals, at least in the low snr region.
incorporating prior knowledge on the digital media creation process into audio classifiers. in the process of music content creation, a wide range of typical audio effects such as reverberation, equalization or dynamic compression are very commonly used. despite the fact that such effects have a clear impact on the audio features, they are rarely taken into account when building an automatic audio classifier. in this paper, it is shown that the incorporation of prior knowledge of the digital media creation chain can clearly improve the robustness of the audio classifiers, which is demonstrated on a task of musical instrument recognition. the proposed system is based on a robust feature selection strategy, on a novel use of the virtual support vector machines technique and a specific equalization used to normalize the signals to be classified. the robustness of the proposed system is experimentally evidenced using a rather large and varied sound database.
new insights into non-causal multichannel linear filtering for noise reduction. we investigate a general framework for noise reduction which consists in controlling the level of signal distortion while reducing the level of noise. a parameterized non-causal filter that allows for tuning the signal distortion and noise reduction inversely is obtained and is referred to as parameterized multichannel non-causal wiener filter (pmwf) herein. the same optimization problem leads to the minimum variance distortionless response (mvdr) as a particular case of the pmwf. in contrast to earlier works, the proposed expressions of the pmwf and mvdr are simplified and require the knowledge of the speech and noise statistics only. to rigorously quantify the gains and losses when using these filters, we establish simplified closed-form expressions for three measures, namely, the signal distortion index, the noise reduction factor, and the output signal-to-noise ratio (snr), and highlight the tradeoff between noise reduction and speech distortion in the multichannel case.
a new robust estimation method for arma models. this paper presents a new robust method to estimate the parameters of arma models. this method makes use of the autocorrelations estimates based on the ratio of medians together with a robust filter cleaner able to reject a large fraction of outliers, and a gaussian maximum likelihood estimation which handles missing values. the main advantages of the procedure are its easiness, robustness and fast execution. its effectiveness is demonstrated on an example of the forecasting of the french daily electricity consumptions.
structured spectrum balancing in dsl multiuser communications. finding the power allocations that maximize the sum-rate of a k-user n-tone digital subscriber line (dsl) system is known to be np-hard. in this paper we devise a polynomial-time algorithm to approximate the maximum sum rate of the system. the development of this algorithm is guided by the fact that, to approach the sumrate maximum, the users should operate in an fdma-mode over frequency tones where the crosstalk coefficients exceed a certain threshold, and should share the tones for which the crosstalk coefficients are sufficiently small. drawing on this insight, the algorithm partitions the n tones into three sections and imposes an appropriate signalling structure on each section. the first section contains those tones for which the crosstalk coefficients are small and uses an iterative water-filling technique to determine the power allocations. the second section contains the tones with intermediate crosstalk coefficients and uses a primal-dual algorithm, and the third section contains the tones with large crosstalk coefficients and uses a dual fdma algorithm. to decouple the overall optimization of power allocation across the three sections, we use tools from lagrangian duality and sensitivity analysis to devise an iterative scheme that can optimally allocate each user's power budget to the three sections. our numerical simulations, show that the sum-rate of the proposed algorithm is very close to that of the ‘optimal’ spectrum balancing algorithm, but requires considerably less computational effort.
layers and layer interfaces in wireless networks. this paper proposes an optimal architecture for wireless networks based on layers and layer interfaces. in the presence of fading the architecture is shown to be optimal. the result follows from a subgradient descent algorithm on the dual function of a generic wireless networking optimization problem. the fact that these non-convex optimization problems have nonetheless zero duality gap is exploited.
adaptive predistortion of nonlinear volterra systems using spectral magnitude matching. digital compensation of nonlinear systems is an important topic in many practical applications. this paper considers the problem of predistortion of nonlinear systems described using volterra series by connecting in tandem an adaptive volterra predistorter. the suggested direct learning architecture (dla) approach utilizes the spectral magnitude matching (smm) method that minimizes the sum squared error between the spectral magnitudes of the output signal of the nonlinear system and the desired signal. the coefficients of the predistorter are estimated recursively using the generalized newton iterative algorithm. a comparative simulation study with the nonlinear filtered-x least mean squares (nfxlms) algorithm shows that the suggested smm approach achieves much better performance but with higher computation complexity.
recursive errors-in-variables approach for ar parameter estimation from noisy observations. application to radar sea clutter rejection. ar modeling is used in a wide range of applications from speech processing to rayleigh fading channel simulation. when the observations are disturbed by an additive white noise, the standard least squares estimation of the ar parameters is biased. some authors of this paper recently reformulated this problem as an errors-in-variables (eiv) issue and proposed an off-line solution, which outperforms other existing methods. nevertheless, its computational cost may be high. in this paper, we present a blind recursive eiv method that can be implemented for real-time applications. it has the advantage of converging faster than the noise-compensated lms based solutions. in addition, unlike ekf or sigma point kalman filter, it does not require a priori knowledge such as the variances of the driving process and the additive noise. the approach is first tested with synthetic data; then, its relevance is illustrated in the field of radar sea clutter rejection.
a class of comprehensive constraints for the pcwlse filter design: a boost in performance. the complex chebyshev error criterion is usually used as a general constraint in design of peak constraint weighted least square error (pcwlse) filters. it applies an upper bound on the maximum magnitude of error between the desired and designed transfer functions of the filter. therefore, it confines the corresponding maximum phase error as well. however, it imposes an over restricted constraint which reduces the feasibility region of the filter design problem. in this paper, a new and comprehensive class of constraints is proposed for design of pcwlse filters that provides a larger feasible region than that of the complex chebyshev constraint. hence, the filter weights acquire larger feasible space to search and select better optimal values and consequently boost up the performance of the designed filter by achieving less weighted least square error. simulation results show superiority of the proposed constraints over that of the complex chebyshev criterion.
on-line adaptation and bayesian detection of environmental changes based on a macroscopic time evolution system. acoustic characteristics are often changed over time as a result of various factors including changes of speakers, speaking styles, and noise sources. incremental adaptation techniques for speech recognition are aimed at adjusting acoustic models quickly and stably to such time-variant acoustic characteristics. recently we proposed a novel incremental adaptation framework based on a macroscopic time evolution system, which models the time-variant characteristics by successively updating posterior distributions of acoustic model parameters. this paper proposes fast incremental adaptation based on a macroscopic time evolution system that realizes an utterance-by-utterance update by approximating the posterior distributions. this adaptation was used to perform on-line adaptation of japanese broadcast news for very large vocabulary continuous speech recognition (700k vocabulary size) in real time. the word accuracy was improved from 73.9% to 85.1%. in addition, by incorporating a bayesian model selection approach, we realized the simultaneous on-line adaptation and detection of environmental changes.
modifications to the sliding-window kernel rls algorithm for time-varying nonlinear systems: online resizing of the kernel matrix. a kernel-based recursive least-squares algorithm that implements a fixed size “sliding-window” technique has been recently proposed for fast adaptive nonlinear filtering applications. we propose a methodology of resizing the kernel matrix to assist in system identification of time-varying nonlinear systems. to be applicable in practice, the modified algorithm must preserve its ability to operate online. given a bound on the maximum kernel matrix size, we define the set of all obtainable sizes as the resizing range. we then propose a simple online technique that resizes the kernel matrix within the resizing range. the modified algorithm is applied to the nonlinear system identification problem that was used to evaluate the original algorithm. results show that an increase in performance is achieved without increasing the original algorithm's computation time.
improving acoustic speaker verification with visual body-language features. we show how an svm based acoustic speaker verification system can be significantly improved in incorporating new visual features that capture the speaker's “body language.” we apply this system to many hours of internet videos and tv broadcasts of politicians and other public figures. our data ranges from current and former us election candidates to the queen of england, the president of france, and the pope, while giving speeches.
room impulse response shortening with infinity-norm optimization. the purpose of room impulse response (rir) shortening is to improve the intelligibility of the received signal by prefiltering the source signal before it is played with a loudspeaker in a closed room. in this paper, we propose to use the infinity-norm as optimization criterion for the design of shortening filters of rirs. similar to the equiripple filter design method, design errors will be uniformly distributed over the unwanted temporal range of the shortened global impulse response. the d50 measure is exploited during the design of the shortening filter, which makes it possible to significantly reduce the length of the prefilter without affecting the perceived performance.
optimal variable fractional delay filters in time-domain l-infinity norm. this paper presents an efficient implementation of the variable fractional-delay (vfd) filter, which is optimal in the time-domain l-infinity norm. the proposed filter has two stages. the first consist in computing the conventional lagrange interpolator from the signal samples, but weighted using a set of fixed coefficients. and the second consists in multiplying the result of the previous step by a smooth function, which can be well approximated by a polynomial. the paper includes a numerical evaluation of this interpolator and a low-complexity, low-latency implementation based on multiplications. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
using information theory to detect voice activity. voice activity detection systems attempt to discriminate between voice and other ambient sounds. most systems use a single microphone approach and rely on training prior to employment. the performance of these systems relies heavily on reverberation and noise levels. in this paper we present an unsupervised voice activity detection system that uses pairs of microphones to discern between a coherent acoustic source and spatially diffuse noise of low coherence. measurement of coherency is performed using an information theoretic metric that integrates means to filter out more effectively the effect of reverberation and noise. using extensive experiments, the performance of the system is investigated. based on the conditions imposed by the experimental environments it is shown that the proposed system remains more robust than its counterparts in all cases.
multivariate spatial gaussian mixture modeling for statistical clustering of hemodynamic parameters in functional mri. in this paper, a novel statistical parcellation of intra-subject functional mri (fmri) data is proposed. the key idea is to identify functionally homogenous regions of interest from their hemodynamic parameters. to this end, a non-parametric voxel-based estimation of hemodynamic response function is performed as a prerequisite. then, the extracted hemodynamic features are entered as the input data of a multivariate spatial gaussian mixture model (msgmm) to be fitted. the goal of the spatial aspect is to favor the recovery of connected components in the mixture. our statistical clustering approach is original in the sense that it extends existing works done on univariate spatially regularized gaussian mixtures [1]. a specific gibbs sampler is derived to account for different covariance structures in the feature space. on realistic artificial fmri datasets, it is shown that our algorithm is helpful for identifying a parsimonious functional parcellation required in the context of joint detection-estimation of brain activity [2]. this allows us to overcome the classical assumption of spatial stationarity of the bold signal model.
distributed sampling and reconstruction of non-bandlimited fields in sensor networks based on shift-invariant spaces. we use the theory and algorithms developed for so-called shift-invariant spaces to develop a novel distributed architecture for sampling and reconstructing non-bandlimited fields in wireless sensor networks. our scheme groups neighboring sensors into clusters that locally perform highly accurate field reconstruction with limited communication overhead. the overall complexity of our method scales only linearly with the number of sensors. numerical simulations illustrate that the proposed field reconstruction scheme outperforms band-limited reconstruction, even though the latter has much larger complexity.
single-microphone late-reverberation suppression in noisy speech by exploiting long-term correlation in the dft domain. we consider blind late-reverberation suppression in speech signals measured with a single microphone in noisy environments. we exploit that reverberant speech shows correlation over longer time spans than clean speech by predicting the contribution of reverberant energy to the current observed spectrum from the enhanced spectra of previous frames. the prediction parameters are recursively updated with estimates of the correlation coefficients between the current reverberant spectrum and enhanced previous spectra. the contributions of late reverberation and noise are suppressed by a standard noise reduction algorithm. the algorithm is shown to decrease the long-term correlation. it achieves significant improvements in segmental speech-to-interference ratio and bark spectral distortion for typical reverberation times and noise levels, while almost no distortions are introduced in clean speech.
sensor fusion method using gps/imu data for fast uav surveillance video frame registration. this paper proposes an innovative framework for fast image registration of uav surveillance video frames by fusing the data from a gps receiver high-frequency imu sensor (piccolo autopilot) and a feature-domain registration method through a non-linear filter. the high-frequency imprecise data from the piccolo autopilot is refined by the low-frequency precise data from our feature-domain based random m least squares (rmls) method. the projective transformation model is chosen to achieve high precision. the state and measurement models are non-linear to approximate the real-world imaging dynamics. a periodic hybrid particle filter (phpf), composed of extended kalman filter (ekf) and unscented kalman filter (ukf), is proposed to minimize running time while maintaining accuracy. both the efficiency and effectiveness of the proposed algorithm will be evaluated through our experiments.
a bayesian approach to hmm-based speech synthesis. this paper proposes a new framework of speech synthesis based on the bayesian approach. the bayesian method is a statistical technique for estimating reliable predictive distributions by marginalizing model parameters. in the proposed framework, all processes for constructing the system can be derived from one single predictive distribution which represents the basic problem of speech synthesis directly. using hmm as the likelihood function and assuming some approximations, it can be regarded as an application of the variational bayesian method to the hmm-based speech synthesis. experimental results show that the proposed method outperforms the conventional one in a subjective test.
fixed sinr solutions for the mimo wiretap channel. this paper studies the use of artificial interference in reducing the likelihood that a message transmitted between two multi-antenna nodes is intercepted by an undetected eavesdropper. unlike previous work that assumes some prior knowledge of the eavesdropper's channel and focuses on the information theoretic concept of secrecy capacity, we also consider the case where no information regarding the eavesdropper is present, and we use the relative signal-to-interference-plus-noise-ratio (sinr) of a single transmitted data stream as our performance metric. a portion of the transmit power is used to broadcast the information signal with just enough power to guarantee a certain sinr at the desired receiver, and the remainder of the power is used to broadcast artificial noise in order to mask the desired signal from a potential eavesdropper. the interference is designed to be orthogonal to the information signal when it reaches the desired receiver, and we study the resulting relative sinr of the desired receiver and the eavesdropper assuming both employ optimal beamformers.
optimal geometry configuration of bistatic forward-looking sar. with appropriate geometry configurations, bistatic synthetic aperture radar (sar) can break through the limitations of monostatic sar on forward-looking imaging. with such a capability, bistatic forward-looking sar (bfsar) has extensive potential applications. in this paper, based on the resolution calculation using gradient theory, we give a general rule to determine the optimal geometry configuration of different modes of bfsar. the results can be used to design bfsar flight campaign and measure the performance of a specific bfsar system.
tracking forecast memories in stochastic decoders. this paper proposes tracking forecast memories (tfms) as a novel method for implementing re-randomization and decorrelation of stochastic bit streams in stochastic channel decoders. we show that tfms are able to achieve decoding performance similar to that of the previous methods in the literature (i.e., edge memories or ems), but they exhibit much lower hardware complexity. tfms significantly reduce the area requirements of asic implementations of stochastic decoders.
estimating correspondence between multiple cameras using joint invariants. the joint invariants of the projective group psl(3,ℝ) on ℝℙ2, the five-point volume cross-ratios, are studied to address the problem of correspondence in a camera network. the distribution of cross-ratios over the unit square as well as in a small local-neighbourhood of a reference point are found to have a heavy tail. no cross ratio value is unique but the collection of five point cross ratios generated by taking all possible combination of five points completely prescribes the curve. sections of the signature submanifold that admit large enough variation of cross ratios are found to be sufficient in providing correspondence across wide perspectives. such invariant signatures may be collected independently at cameras with different viewpoints and shared, thereby achieving the registration of objects in the image. experimental results with license plate database are provided.
exploring the automatic mispronunciation detection of confusable phones for mandarin. mispronunciation detection is one of the vital tasks of the call (computer assisted language learning) systems. many methods have been introduced to accomplish this task. however, few of them have addressed the detection task on confusable phones. in this paper, phone-level classifiers are utilized to improve the detection performance on the confusable phones. features of the classifiers are posterior probability vectors calculated from their corresponding acoustic models. moreover, confusion matrix is also extracted and incorporated to calculate derivatives of the posterior probability vectors. experiments on our mandarin database validate the effectiveness of our proposed method, compared with the commonly used posterior probability and phone dependent thresholds methods.
joint optimization of the redundancy of multiple-description coders for multicast. we consider the optimization of multicast over packet-switched communication networks with a non-zero packet-loss probability. for the system setup consisting of a number of multiple-description coders, we jointly optimize these coders. we propose an analytic solution, asymptotically optimal in the number of multiple-description coders. the analytic solution allows for fast system adaptation to changing network conditions. a locally optimal optimization algorithm that is useful when the number of multicast groups is small is derived. simulations show that the utilization of the analytic solution incurs a low overhead on the performance when compared to the locally optimal solution, even for a small number of multiple-description coders.
gridnews: a distributed automatic greek broadcast transcription system. in this paper, a distributed system storing and retrieving broadcast news data recorded from the greek television is presented. these multimodal data are processed in a grid computational environment interconnecting distributed data storage and processing subsystems. the innovative element of this system is the implementation of the signal processing algorithms in this grid environment, offering additional flexibility and computational power. among the developed signal processing modules are: the segmentor, cutting up the original videos into shorter ones, the classifier, recognizing whether these short videos contain speech or not, the greek large-vocabulary speech recognizer, transcribing speech into written text, and finally the text search engine and the video retriever. all the processed data are stored and retrieved in geographically distributed storage elements. a user-friendly, web-based interface is developed, facilitating the transparent import and storage of new multimodal data, their off-line processing and finally, their search and retrieval.
combining frontend-based memory with mfcc features for bandwidth extension of narrowband speech. in this paper, we continue our previous work on improving bandwidth extension (bwe) of narrowband speech. we have shown that including memory into the parametrization frontend (through delta features) results in higher highband certainty irrespective of feature type, with mfccs exhibiting higher correlation, in general, between both bands, reaching twice that using lsfs. by incorporating memory into the frontend of a conventional lp-based bwe system, we were able to translate the higher correlation due to memory into bwe performance improvement. using high-resolution inverse dct, we also achieved high quality speech reconstruction from mfccs, thus enabling mfcc-based bwe with improved performance compared to conventional static lp-based bwe. we continue this work by incorporating the superior correlation properties of frontend memory into our mfcc-based bwe system. log-spectral distortion as well as the more perceptually-correlated itakura-based measures show that incorporating memory into our mfcc-based bwe system results in bwe performance superior to that of our dynamic lp-based bwe system.
semi-tied covariance matrices for acoustic models based on random forests of phonetic decision trees. in this paper, we investigate combining semi-tied covariance matrices and random forests (rfs) based phonetic decision trees (pdts) for acoustic modeling in conversational speech recognition. we first use the rf method to train multiple pdts for each phone state unit, and generate multiple sets of acoustic models accordingly. we then apply semi-tied covariance matrices to each set of acoustic models to improve their fit to data. in decoding search we combine the likelihood scores from the multiple acoustic models for each speech frame. the viability of semi-tied covariance matrices with different tying classes are studied from their effects on the diversity of rf-based acoustic models as well as on the word accuracy of our task of telehealth automatic captioning. experimental results indicate that semi-tied covariance matrices help enhance the diversity of the rfs-pdts based acoustic models as well as increase word accuracy.
multi-view tracking of articulated human motion in silhouette and pose manifolds. this paper presents a multi-view articulated human motion tracking framework using particle filter with manifold learning through gaussian process latent variable model. the dimensionality of the input image observation and joint angles are reduced using gaussian process models to improve the tracking efficiency. the forward and backward mappings between the two low dimensional spaces are then obtained using relevance vector machine and batesian mixture of experts (bme). improved sampling schemes and auto-initialization are obtained using bme.without using a 3d body model, effective likelihood evaluation is obtained through rvm using images from multiple views. tracking results obtained using real videos with complex dance movement show the efficacy of the proposed approach.
an approximate l0 norm minimization algorithm for compressed sensing. ℓ0 norm based signal recovery is attractive in compressed sensing as it can facilitate exact recovery of sparse signal with very high probability. unfortunately, direct ℓ0 norm minimization problem is np-hard. this paper describes an approximate ℓ0 norm algorithm for sparse representation which preserves most of the advantages of ℓ<sup>0 norm. the algorithm shows attractive convergence properties, and provides remarkable performance improvement in noisy environment compared to other popular algorithms. the sparse representation algorithm presented is capable of very fast signal recovery, thereby reducing retrieval latency when handling
adaptive reconstruction method of missing textures based on kernel canonical correlation analysis. this paper presents an adaptive reconstruction method of missing textures based on kernel canonical correlation analysis (cca). the proposed method calculates the correlation between two areas, which respectively correspond to a missing area and its neighbor area, from known parts within the target image and realizes the estimation of the missing textures. in order to obtain this correlation, the kernel cca is applied to each set containing the same kind of textures, and the optimal result is selected for the target missing area. specifically, a new approach monitoring errors caused in the above estimation process enables the selection of the optimal result. this approach provides a solution to the problem in traditional methods of not being able to perform adaptive reconstruction of the target textures due to the missing intensities. experimental results show subjective and quantitative improvement of the proposed reconstruction technique over previously reported reconstruction techniques.
phoneme recognition using spectral envelope and modulation frequency features. we present a new feature extraction technique for phoneme recognition that uses short-term spectral envelope and modulation frequency features. these features are derived from sub-band temporal envelopes of speech estimated using frequency domain linear prediction (fdlp). while spectral envelope features are obtained by the short-term integration of the sub-band envelopes, the modulation frequency components are derived from the long-term evolution of the sub-band envelopes. these features are combined at the phoneme posterior level and used as features for a hybrid hmm-ann phoneme recognizer. for the phoneme recognition task on the timit database, the proposed features show an improvement of 4.7% over the other feature extraction techniques.
a complex cross-spectral distribution model using normal variance mean mixtures. we propose a model for the density of cross-spectral coefficients using normal variance mean mixtures. we show that this model density generalizes the corresponding marginal density of the complex wishart distribution for the cross-spectral density. the maximum likelihood estimate of parameters in the distribution is derived, and examples are given from alpha brain wave sources in separated eeg data.
an algebraic polyphase approach to wireless network coding. network coding has been shown to improve throughput, minimize delay and economize the energy requirements in wireless networks. this paper presents an algebraic polyphase approach to the wireless linear network coding problem. by modeling wireless nodes as consisting of linear periodic time varying filters, the model incorporates realistic constraints including omni directionality of transmissions, half-duplex operation and interference effects. a rank criterion is introduced, which together with the transmission constraints, constitutes the necessary and sufficient conditions for the existence of a wireless network code.
multi-layer ratio semi-definite classifiers. we develop a novel extension to the ratio semi-definite classifier, a discriminative model formulated as a ratio of semi-definite polynomials. by adding a hidden layer to the model, we can efficiently train the model, while achieving higher accuracy than the original version. results on artificial 2-d data as well as two separate phone classification corpora show that our multi-layer model still avoids the overconfidence bias found in models based on ratios of exponentials, while remaining competitive with state-of-the-art techniques such as multi-layer perceptrons.
game theory for precoding in a multi-user system: bargaining for overall benefits. a precoding strategy for multi-user spectrum sharing over an interference channel is proposed and analyzed from a game-theoretic perspective. the proposed strategy is based on finding the nash bargaining solution for precoding matrices in a cooperative scenario over frequency selective channels under a spectrum mask constraint. an in-time update of the precoding matrices is enabled by using time slots to guarantee the effectiveness of the bargaining solution when the number of users varies. a dual decomposition approach is exploited to construct a distributed structure for solving the bargaining problem. the proposed distributed algorithm realizes the physical process of bargaining, which is not present in the nash bargaining theory.
a new perceptual quality metric for compressed video. this paper presents a new video quality metric for automatically estimating the perceptual quality of compressed video sequences. distortion measures such as the mean squared error (mse) and the peak signal to noise ratio (psnr) have been found to poorly correlate with visual quality at lower bit-rates. the proposed quality metric (mosp) predicts perceptual quality of compressed video using sequence characteristics and the mean squared error (mse) between the original and compressed video sequences. the metric has been tested on various video sequences compressed using the h.264 video compression standard at different bit-rates. results show that the proposed metric has better correlation with subjective quality compared to popular metrics such as psnr, ssim and psnrplus. the new metric is simple to compute and hence suitable for incorporation into real-time applications such as the standard video compression codecs inorder to improve the visual quality of compressed video sequences.
on the role of localization cues in binaural segregation of reverberant speech. approaches to binaural and stereo speech segregation have often assumed that localization information can be used as a primary cue to achieve segregation of a target signal. results produced by these systems degrade significantly in the presence of room reverberation. in this work, we present an alternative framework to achieve localization of groups of time-frequency units. we show that grouping across time and frequency allows the use of localization as an important cue for sequential grouping of time-frequency objects. we analyze the level of time-frequency grouping needed to achieve accurate object localization and show preliminary binaural segregation results using the proposed framework. results indicate that both localization and segregation performance can be improved by grouping across time and frequency.
memory characterization to analyze and predict multimedia performance and power in embedded systems. main memory performance and power are becoming increasingly critical for embedded and general purpose computing systems. that is the primary motivation for us to focus on analyzing and modeling memory utilization for multimedia applications in embedded systems like cell-phones and pdas with limited hardware resources and battery supply. in addition, the paper presents scenarios of utilizing the memory characteristic model to predict multimedia application performance, optimize embedded software, and adapt hardware resources to save system power while guaranteeing adequate performance. we present a simple, but effective indicator to identify the application's dynamic memory and computational composition. using this, we can easily and accurately forecast application performance and help determine optimal resources needed by the multimedia applications.
motion-compensated techniques for enhancement of low-quality compressed videos. algorithms for enhancement of low quality compressed videos are described and evaluated in this paper. cascaded and combined spatio-temporal filters using hierarchical motion estimation and occlusion area detection are investigated for removal of severe coding artifacts and temporal flickering. both objective and subjective evaluations prove that temporal filtering can significantly improve the video quality of low bit rate video sequences. the proposed methods could therefore be a differentiating feature for future iptv design.
speech enhancement in car noise envoronment based on an analysis-synthesis approach using harmonic noise model. this paper presents a speech enhancement method based on an analysis-synthesis framework using harmonic noise model (hnm) in car noise environment. the major advantages of this method are effective suppression of car noise even in very low signal-to-noise ratio environments and mitigation of “musical tones” which are generally introduced by conventional methods. in this paper, we devise a complete analysis-synthesis based speech enhancement system, and give details in hnm modeling, parameter estimation, and car noise adaptation. subjective evaluation results show that the proposed method exhibits better noise suppression ability over conventional approaches without obvious degradation of speech quality.
artifact removal in eeg using morphological component analysis. to reduce the effects of artifacts in electroencephalography (eeg), we propose the use of morphological component analysis (mca). taking advantage of the sparse representation of data in overcomplete dictionaries, mca decomposes eeg signals into parts that have different morphological characteristics. for denoising purpose, the parts related to artifacts are removed. an overcomplete dictionary is constructed using the discrete cosine transform, daubechies wavelet basis, and dirac basis. movement-related potentials (mrp) and eeg signals contaminated by spikes, eye-blinks, and muscle artifacts caused by eye-brow raising are used to evaluate the performance of the method. the results demonstrate that mca can be used to decompose the single-channel eeg signals into artifacts and mrp components. the correlation coefficient between the denoised mrp and the original mrp using mca is significantly higher than that obtained using stationary wavelet transform.
a new optimization algorithm for network component analysis based on convex programming. network component analysis (nca) has been established as a promising tool for reconstructing gene regulatory networks from microarray data. nca is a method that can resolve the problem of blind source separation when the mixing matrix instead has a known sparse structure despite the correlation among the source signals. the original nca algorithm relies on alternating least squares (als) and suffers from local convergence as well as slow convergence. in this paper, we develop new and more robust nca algorithms by incorporating additional signal constraints. in particular, we introduce the biologically sound constraints that all nonzero entries in the connectivity network are positive. our new approach formulates a convex optimization problem which can be solved efficiently and effectively by fast convex programming algorithms. we verify the effectiveness and robustness of our new approach using simulations and gene regulatory network reconstruction from experimental yeast cell cycle microarray data.
energy-efficient transmission of h.264 scalable video over ieee 802.11e. achieving low energy consumption is one of the main challenges for wireless video transmission on battery-limited devices. moreover, the bandwidth is scarce and must be shared efficiently among users. the focus in this paper is on the timely delivery of multiple delay-sensitive video flows over a distributed access wireless lan with minimal energy cost. this is done taking into consideration the enhanced distributed channel access (edca) mode and the scalable video codec (svc). in this context, a method is presented for energy-efficient resource allocation across the physical layer and medium access layer, by properly leveraging transmission modes and the available prioritization mechanisms. global energy savings around 60% are achieved with respect to state-of-the-art edca under a wide range of network loads.
pulse coupled oscillators' primitive for low complexity scheduling. pulse coupled oscillators (pcos) are pulsing devices that pulse individually in a periodic manner but alter their pulsing patterns in response to the pulsing of other nodes. a network of pcos can produce a number of different dynamics from their pulsing activities, among which the synchrony of pulsing is perhaps the most well known. in this paper, we study the primitive that falls into the class of “desynchronization”. specifically, we propose a simple pulse-coupling mechanism that allows each node in the network to converge to a desynchronized state where the nodes will pulse periodically with a constant spacing among each others firing times. we discuss the convergence of the pco mechanism and propose to apply this primitive to resolve contention in the reservation phase of a reservation-based mac protocol.
phmm based asynchronous acoustic model for chinese large vocabulary continuous speech recognition. in this paper, we presented an asynchronous multiple stream based chinese tonal acoustic modeling framework. in this framework, toneless phonetic units and tones are modeled separately with different acoustic features. during the training and decoding process, a set of models are coupled together with a product hidden markov models (phmm) to represent whole tonal phonetic units. through this, a compound context dependent tonal model can be generated from a few simple models. experiments show that such model scheme generates more compact and accurate model presentation and brings improvement on the performance for large vocabulary speech recognition tasks.
dct based multiple hashing technique for robust audio fingerprinting. audio fingerprinting techniques should successfully perform content-based audio identification even when the audio files are slightly or seriously distorted. in this paper, we present a novel audio fingerprinting technique based on combining fingerprint matching results for multiple hash tables in order to improve the robustness of hashing. multiple hash tables are built based on the discrete cosine transform (dct) which is applied to the time sequence of energies in each sub-band. experimental results show that the recognition errors are significantly reduced compared with philips robust hash (prh) [1] under various distortions.
single parameter optimization approach to the optimal power allocation of ofdm relaying system. in this paper, we investigate the power allocation optimization problem for dual-hop nonregenerative ofdm relaying networks, where an aggregate power constraint is imposed on all relays. we first formulate the model into a single-parameter optimization problem, in which we found the related functions are monotonically decreasing. then based on the monotonicity, we propose a bisection algorithm to solve the problem. we further illustrate that pairing of ofdm subcarriers will not provide performance gain when the aggregate power constraint is very large.
mixture of probabilistic linear regressions: a unified view of gmm-based mapping techiques. this paper introduces a model of mixture of probabilistic linear regressions (mplr) to learn a mapping function between two feature spaces. the mplr consists of weighted combination of several probabilistic linear regressions, whose parameters are estimated by using matrix calculation. the mixture nature of mplr allows it to model nonlinear transformation. the formulation of mplr is general and independent of the types of the density models used. two well-known gmm-based mapping methods for voice conversion [1, 2] can be regarded as special cases of mplr. this unified view not only provides insights to the gmm-based mapping techniques, but also indicates methods to improve them. compared to [1], our formulation of mplr avoids solving complex linear equations and yields a faster estimation of the transform parameters. as for [2], the mplr estimation provides a modified mapping function which overcomes an implicit problem in [2]-s mapping function. we carried out experiments to compare the mplr-based methods with the traditional gmm-based methods [1, 2] on a voice conversion task. the experimental results show that the mplr-based methods always have better performance in various parameter setups.
an efficient lsf quantization using dynamic bit allocation. the current paper is concerned with an effective method to quantize a spectrum envelope of a speech signal without having an inter-frame prediction. in this paper, we proposed a method referred to as dynamic bit allocation-split vector quantization (dba-svq). the main feature of this structure is that it makes use of the ordering property of line spectral frequencies (lsf) and exploits multiple codebooks, normalization and the dba technique. as a result, we can limit the dynamic range of lsf sub-vectors and allocate different numbers of bits in accordance with the range sizes to maximize the overall efficiency of quantization. the performance is compared with delta line spectral pairs (lsp) vq, which is used in evrc-b, demonstrating reduction in spectral distortion (sd).
cache-based integer motion/disparity estimation for quad-hd h.264/avc and hd multiview video coding. to provide more vivid perception, more and more advanced features, like the 4k×2k resolution and the multiview functionality, are emerging for tv. for a multiview video coding (mvc) encoder, motion and disparity estimation (me/de) take at least half the hardware requirement. to solve these challenges, a cache-based integer me/de algorithm is proposed. with a cache memory as the search window buffer, a predictor-centered me/de algorithm is presented. the search range can be reduced to ±16 pixels with less than 0.1db quality drop compared with full search algorithm. based on this algorithm, an integer me/de chip design is realized. it can reduce 82% on-chip sram and 39% system bandwidth. moreover, the search candidate requirement is also reduced by 79%. as the result, an me/de chip design for 4k×2k quad-hd h.264 and hdtv mvc is implemented.
music analysis with a bayesian dynamic model. a bayesian dynamic model is developed to model complex sequential data, with a focus on audio signals from music. the music is represented in terms of a sequence of discrete observations, and the sequence is modeled using a hidden markov model (hmm) with time-evolving parameters. the model imposes the belief that observations that are temporally proximate are more likely to be drawn from hmms with similar parameters, while also allowing for “innovation” associated with abrupt changes in the music texture. segmentation of a given musical piece is constituted via the model inference and the results are compared with other models and also to a conventional music-theoretic analysis.
towards unsupervised learning for automatic multi-class object detection in surveillance videos. object detection is a critical step in automated surveillance. a common approach to constructing object detectors consists of annotating large datasets and using them to train the detectors. however, due to inevitable limitations of a typical training data set, such supervised approach is unsuitable for building generic surveillance systems applicable to a wide variety of scenes and camera setups. in our previous work we proposed an unsupervised method for learning and detecting the dominant object class in a general dynamic scene observed by a static camera. in this paper, we investigate the possibilities to expand the applicability of this method to the problem of multiple dominant object classes. we propose an idea how to approach this expansion, and perform a proof-of-concept evaluation of this idea using a representative surveillance video sequence.
interpolating hidden markov model and its application to automatic instrument recognition. this paper proposes an interpolating extension to hidden markov models (hmms), which allows more accurate modeling of natural sounds sources. the model is able to produce observations from distributions which are interpolated between discrete hmm states. the model uses gaussian mixture state emission densities, and the interpolation is implemented by introducing interpolating states in which the mixture weights, means, and variances are interpolated from the discrete hmm state densities. we propose an algorithm extended from the baum-welch algorithm for estimating the parameters of the interpolating model. the model was evaluated in automatic instrument classification task, where it produced systematically better recognition accuracy than a baseline hmm recognition algorithm.
spectrum separation of magnetic resonance spectroscopy based on sparse representation. in this paper, a novel spectrum separation technique based on sparse representation is proposed to deal with magnetic resonance spectroscopy (mrs) quantification which is used to measure the levels of different metabolites in brain tissues. since a measured mr spectrum contains the spectra of numbers of metabolites and a baseline, the separation and quantification of them becomes difficult. a nonnegative pursuit algorithm based on regularized focuss algorithm is proposed here to decompose a measured spectrum with respect to an overcomplete dictionary. benefitting from the a priori knowledge, the dictionary is built by lorentzian and gaussian basis functions representing different metabolites and baseline. using this algorithm, not only the baseline is separated from the spectra of interest, but also the spectra of different metabolites are separated. the accuracy of quantification and the robustness are improved, from simulation data, compared with a commonly used estimation method [1]. the quantification on tumor metabolism with in vivo brain mr spectra is also demonstrated.
spoken language interpretation: on the use of dynamic bayesian networks for semantic composition. in the context of spoken language interpretation, this paper introduces a stochastic approach to infer and compose semantic structures. semantic frame structures are directly derived from word and basic concept sequences representing the users' utterances. a rule-based process provides a reference frame annotation of the speech training data. then dynamic bayesian networks are used to hypothesize frames from test data. the semantic frames used in this work are specialized on the task domain from the berkeley framenet set. experiments are reported on the french media dialog corpus. for all the data, the manual transcriptions and annotations at the word and concept levels are available. tests are performed under 3 different conditions raising in difficulty wrt the errors in the word and concept sequence inputs. three different stochastic models are compared and the results confirm the ability of the proposed probabilistic frameworks to carry out a reliable semantic frame annotation.
accelerating em by targeted aggressive double extrapolation. the expectation-maximization (em) algorithm is one of the most popular algorithms for parameter estimation from incomplete data, but its convergence can be slowfor some large-scale or complex problems. extrapolation methods can effectively accelerate em, but to ensure stability, the learning rate of extrapolation must be compromised. this paper describes the tj2aem method, a targeted extrapolation method that can extrapolate much more aggressively than competing methods without causing instability problems. we analyze its convergence properties and report experimental results.
a wavelet-based quadratic extension method for image deconvolution in the presence of poisson noise. iterative optimization algorithms such as the forward-backward and douglas-rachford algorithms have recently gained much popularity since they provide efficient solutions to a wide class of non-smooth convex minimization problems arising in signal/image recovery. however, when images are degraded by a convolution operator and a poisson noise, a particular attention must be paid to the associated minimization problem. to solve it, we propose a new optimization method which consists of two nested iterative steps. the effectiveness of the proposed method is demonstrated via numerical comparisons.
class-dependent and differential huffman coding of compressed feature parameters for distributed speech recognition. in this paper, we propose an entropy coding method for compressing quantized mel-frequency cepstral coefficients (mfccs) used for distributed speech recognition (dsr). in the european telecommunication standards institute (etsi) extended dsr standard, mfccs are compressed with additional parameters such as pitch and voicing class. the entropy of compressed mfccs in each analysis frame varies according to the voicing class of the frame, thereby enabling the design of different huffman trees for mfccs according to voicing class, referred to here as class-dependent huffman coding. in addition to the voicing class, the correlation in subvector-wise is utilized for huffman coding, which is called subvector-wise huffman coding. it is also explored that differential huffman coding can further enhance a coding gain against class-dependent huffman coding and subvector-wise huffman coding. based on the benefits above, hybrid types of huffman coding by combining class-dependent and subvector-wise with differential huffman coding are compared in this paper. subsequent experiments show that the average bitrate of subvector-wise differential huffman coding is measured at 33.93 bits/frame, whereas that of a traditional huffman coding which does not consider voicing class and encodes with a single huffman coding tree for all the subvectors is at 42.22 bits/frame.
manifold regularization for semi-supervised sequential learning. the sequential data flux in many time-series applications require that only a small fraction of the data are stored for future processing. furthermore, labels for these data are possibly sparse and they might show some biases. to support learning under such restrictive constraints, we combine manifold regularization with sequential learning under a semi-supervised learning scenario. the online learning mechanism integrates a regularization based on the data smoothness assumptions. we present a proof-of-concept for illustrative toy problems, and we apply the algorithm to a real-world sparse online classification task for music categories.
predictive power control and multiple-description coding for wireless sensor networks. we study state estimation via wireless sensor networks over fading channels affected by random packet loss. in the configuration examined, the sensors send their measurements to a single gateway, which decides upon the source coding scheme and the sensor transmitter power levels. the decision process is carried out on-line and adapts to changing channel conditions to achieve an optimal trade-off between estimation quality and sensor energy expenditure. in particular, if some channel conditions are poor, then the gateway commands the corresponding sensors to increase power levels and use multiple-description coding. simulations based on measured channel data illustrate that the proposed scheme gives excellent results.
steady-state performance analysis for adaptive filters with error nonlinearities. a unified approach to the steady-state mean square error (mse) and tracking performance analyses for real and complex adaptive filtes with error nonlinearities is developed. some general clofied-form analytical expressions for the steady-state performances are given. our analyses are based on taylor series expansion and and so-called complex brandwood-form series expansion (bse). under these general explicit expressions, some well-known adaptive filters can be viewed as special cases. in addition, the closed-form analytical expressions for the steady-state performance for real and complex least-mean p-power (lmp) algorithm with different choices of parameter p are also given. a mass of simulations show the accuration of our analyses.
data sampling based ensemble acoustic modelling. in this paper, we propose a novel technique of using cross validation (cv) data sampling to construct an ensemble of acoustic models for conversational speech recognition. we further propose using hierarchical gaussian mixture model (hgmm) and repartition training data to increase the ensemble size and diversity. the proposed methods are found to work well together for ensemble acoustic modeling. we also evaluated the quality of the ensemble acoustic models by using the measures of classification margin, average correct score and variance of correct score. we have found that the ensemble of acoustic models increases the margin and the average correct score, and reduces the variance. we compared the performance of our proposed method with a recently reported method of cv expectation maximization (cvem) for single acoustic models. our experimental results on a telemedicine automatic captioning task showed that the proposed ensemble acoustic modeling has led to significant improvements in word recognition accuracy.
a new nonparametric measure of conditional independence. in this paper we propose a new measure of conditional independence that is loosely based on measuring the l2 distance between the conditional joint and the product of the conditional marginal density functions. however, we propose to smooth the arguments prior to measuring the distance and use kernel density estimation to derive the estimator. we show that under suitable conditions the proposed smoothing does not affect the conditional independence but using proper smoothing function helps in choosing the bandwidth parameter robustly. we discuss the computational issues and propose an approximation to evaluate the estimator efficiently. we apply the proposed measure in different experiments to show its validity.
complex nmf: a new sparse representation for acoustic signals. this paper presents a new sparse representation for acoustic signals which is based on a mixing model defined in the complex-spectrum domain (where additivity holds), and allows us to extract recurrent patterns of magnitude spectra that underlie observed complex spectra and the phase estimates of constituent signals. an efficient iterative algorithm is derived, which reduces to the multiplicative update algorithm for non-negative matrix factorization developed by lee under a particular condition.
transceiver design with vector perturbation technique and iterative power loading. in this paper we consider the optimization of transceivers which use the nonlinear vector perturbation technique at the transmitter. since the perturbation vector can be almost totally removed at the receiver, the transmitter can use this extra freedom to reduce the transmitted power while maintaining the performance. the two cases considered in this paper are linear transceivers and transceivers with decision feedback (dfe). for both cases, efficient iterative power loading algorithms are developed to reduce the average bit error rate under the total transmitted power constraint. we present simulation results showing that the proposed technique performs better than the existing state-of-the-art uniform channel decomposition (ucd) system and the vector perturbation (vp) precoder.
high improvement of speaker identification and verification by combining mfcc and phase information. in conventional speaker recognition methods based on mfcc, phase information has been ignored. we proposed a method that integrated the phase information with mfcc on a speaker identification method, and a preliminary experiment was performed. in this paper, we propose a new modified feature parameter (that is, coordidates on an unit circle) obtained from the original phase information, and evaluated it by using speech database consisting of normal, fast and slow speaking modes. the speaker identification experiments were performed using ntt database which consists of sentences uttered by 35 japanese speakers (22 males and 13 females) on five sessions over ten months. each speaker uttered only 5 training utterances at a normal speaking mode (about 20 seconds in total). the proposed new phase information was more robust than the original phase information for all speaking modes. by integrating the new phase information with the mfcc, the speaker identification error rate was remarkably reduced for normal, fast and slow speaking rates in comparison with a standard mfcc-based method. in this paper, speaker verification experiments were also evaluated using the phase information. the experiments show that the phase information is also very useful for the speaker verification.
speech enhancement using minimum mean-square error estimation and a post-filter derived from vector quantization of clean speech. in this paper, a novel post-filtering method applied after the logstsa filter is proposed. since the post-filter is derived from vector quantization of clean speech database, it has an equivalent effect of imposing clean source spectral constraints on the enhanced speech. when combined with the logstsa filter, the additional filter can noticeably suppress residual artifacts by effectively lowering the residual white noise of decision-directed estimation as well as reducing the musical noise of maximum likelihood estimation. compared to the logstsa enhanced speech, the overall enhanced speech is able to raise the pesq score by nearly half a point.
performance analysis of recursive least moduli algorithm for fast convergent and robust adaptive filters. this paper derives a new adaptation algorithm named recursive least moduli (rlm) algorithm that combines least mean modulus (lmm) algorithm for complex-domain adaptive filters with recursive estimation of the inverse covariance matrix of the filter reference input. the rlm algorithm achieves significant improvement in the filter convergence speed of the lmm algorithm with a strongly correlated filter reference input, while it preserves robustness of the lmm algorithm against impulsive observation noise. analysis of the rlm algorithm is developed for calculating transient and steady-state behavior of the filter convergence. through experiment with simulations and theoretical calculations of the filter convergence for the rlm algorithm, we demonstrate its effectiveness in making adaptive filters fast convergent and robust in the presence of impulse noise. good agreement between the simulations and theory proves the validity of the analysis. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
linear-time block noncoherent detection of psk. we propose a new algorithm for noncoherent sequence detection of m-ary phase-shift-keying (m-psk) symbols transmitted over a block fading channel. the algorithm is of complexity o(t), where t is the sequence length, and is therefore computationally superior to existing maximum-likelihood (ml) detectors of complexity o(t logt). our detector is based on a new approximation we propose to the noncoherent ml function. we show that by using this close approximation, the detection problem reduces to a nearest lattice point problem for the lattice an*, from which we derive our o(t) approach. simulation results are provided that show the difference in bit error rate is negligibly small for a wide range of signal-to-noise ratios.
phase-based alignment of two signals having partially overlapped spectra. this paper proposes a novel method for aligning two signals using the information contained in the overlapped band. in particular the proposed method aligns two signals by compensating both time-delay and phase-offset in the second signal using the estimated gradient of phase difference in the overlapped band. compared with other conventional methods, this method can align two signals without requiring a pilot tone or additional hardware. the proposed method was experimentally validated using rf pulses.
multidimensional unitary tensor-esprit for non-circular sources. recently, many authors have shown that high-resolution parameter estimation schemes can be significantly improved if the sources are non-circular. for example, enhanced versions of root music and standard esprit for non-circular sources as well as the entirely real-valued nc unitary esprit algorithm have been proposed.
polyphase interpretation of empirical image interpolation. we observe several characteristics of empirical image interpolating algorithms and contribute four novel concepts and claims. first, we interpret well-known classification-based filtering algorithms in terms of their polyphase components. we examine the underlying principles behind the various fixed-scale linear interpolating kernels. second, we conceptually extend the properties of the multiple filters to two dimensions to analyze frequency domain characteristics common to all empirically-designed interpolating filters. third, we propose a general linear filter for image interpolation, which uses a universal magnitude response and zero-phase. finally, the proposed filter is further generalized to support arbitrary scaling factors. we claim that at any scaling factor, the proposed algorithm yields low-complexity at a minimal loss of high image-quality with the ability to interpolate diverse image content.
minimax design of adjustable fir filters using 2d polynomial methods. the problem under study here is the minimax design of linear-phase lowpass fir filters having variable passband width and implemented through a farrow structure. we have two main contributions. the first is the design of adjustable fir filters without discretization, using 2d positive trigonometric polynomials, an approach leading to semidefinite programming (sdp) formulation of the design problem. the second is to modify the design problem by a special choice for the passband and stopband edges of the variable fir filter. the advantage is a lower implementation complexity. the new problem is solved using positive hybrid real-trigonometric polynomials and their sdp parameterization. design examples prove the viability of our methods.
on the eigendistribution of the steady-state error covariance matrix for the extended rls algorithm. in an earlier work [1], we used transform methods from the theory of random matrices to analytically compute the asymptotic eigendistribution of the error covariance matrix of the single-measurement rls filter. when we have a multiplicity of measurements, as happens in extended rls filtering, the analysis is much more complicated. in this paper we study the multiple measurement case and obtain a system of two coupled equations for the stieltjes transform of the asymptotic eigendistribution. numerical solutions of this system very well predict the actual asymptotic eigendistribution for systems with as low as n = 10 − 20 state dimensions.
bayesian feature enhancement using a mixture of unscented transformation for uncertainty decoding of noisy speech. a new parameter estimation method for the model-based feature enhancement (mbfe) is presented. the conventional mbfe uses the vector taylor series to calculate the parameters of non-linearly transformed distributions, though the linearization leads to a degraded performance. we use the unscented transformation to estimate the parameters, where a minimal number of samples propagated through the nonlinear transformation are used. by avoiding the linearization, the parameters are estimated more accurately. experimental results on aurora2 show that the proposed method reduces the word error rate by 8.48% relatively, while the computational cost is just modestly higher, compared with the conventional mbfe.
region-based weighted-norm approach to video super-resolution with adaptive regularization. we propose a super-resolution (sr) algorithm that takes into account inaccurate estimates of the registration parameters. when frames obey the assumed global motion model, these inaccurate estimates, along with the additive gaussian noise in the low-resolution image sequence, result in different noise level for each frame. however, in case of existence of local motion and/or occlusion, regions that have local motion and/or occlusion have different noise level. to cope with this problem, we propose to adaptively weight each region according to its reliability and the regularization parameter is simultaneously estimated for each region. the regions are generated by segmenting the reference frame using watershed segmentation. the experimental results using real video sequences show the effectiveness of the proposed algorithm compared to three state-of-the-art sr algorithms.
an iterative approach to monaural musical mixture de-soloing. in this article, we introduce a novel approach for monaural source separation with the specific aim to separate a polyphonic musical recording into two main sources: a main instrument (or melody) track and an accompaniment track. to that aim, we propose to model the power spectral densities (psds) of both contributions with a source/filter model for the main instrument while retaining a model emphasizing temporal repetitions of the musical background. we show that improved source separation performances can be obtained by a two-step estimation strategy where the model parameters are re-estimated in a second stage by adequately exploiting the main melody line estimated in a first stage. the experiments conducted on several monaural signal databases show that our system achieves state-of-the-art performances compared to other unsupervised source separation algorithms.
ica-based efficient blind dereverberation and echo cancellation method for barge-in-able robot audition. this paper describes a new method that allows “barge-in” in various environments for robot audition. “barge-in” means that a user begins to speak simultaneously while a robot is speaking. to achieve the function, we must deal with problems on blind dereverberation and echo cancellation at the same time. we adopt independent component analysis (ica) because it essentially provides a natural framework for these two problems. to deal with reverberation, we apply a multiple input/output inverse-filtering theorem-based model of observation to the frequency domain ica. the main problem is its high-computational cost of ica. we reduce the computational complexity to the linear order of reverberation time by using two techniques: 1) a separation model based on observed signal independence, and 2) enforced spatial sphering for preprocessing. the experimental results revealed that our method improved word correctness of reverberant speech by 10–20 points.
incorporating mask modelling for noise-robust automatic speech recognition. in this paper we investigate an incorporation of mask modelling into an hmm-based asr system. the mask model is estimated for each hmm state and mixture by using a separate viterbi-style training procedure and it expresses which regions of the spectrum are expected to be uncorrupted by noise for the hmm state. experimental evaluation is performed on noisy speech data from the aurora 2 database. significant performance improvements are achieved when the mask modelling is incorporated within the standard model and two models that had already compensated for the effect of the noise.
target tracking based network active queue management. active queue management (aqm) methods attempt to predict and control network router queue levels and provide feedback regarding network congestion to data sources through packet marking/ dropping. aqm methods have not employed statistical signal processing principles largely due to the requirement of low complexity. in this paper, we apply optimal filtering and target tracking methods to the design of aqm. in particular, we develop kalman filter based aqm which results in router queues with reduced queue level variance. to account for networks with more bursty traffic, we use interacting multiple models (imm) which similarly result in reduced queue variance in simulations with both long-term and bursty short-term traffic. in comparisons with other aqm methods, these low complexity target tracking-based aqm methods give a more constant queue length without any loss in source throughput.
consistent recovery of stimuli encoded with a neural ensemble. we consider the problem of reconstructing finite energy stimuli from a finite number of contiguous spikes. the reconstructed signal satisfies a consistency condition: when passed through the same neuron, it triggers the same spike train as the original stimulus. the recovered stimulus has to also minimize a quadratic smoothness criterion. we show that under these conditions, the problem of recovery has a unique solution and provide an explicit reconstruction algorithm for stimuli encoded with a population of integrate-and-fire neurons. we demonstrate that the quality of reconstruction improves as the size of the population increases. finally, we demonstrate the efficiency of our recovery method for an encoding circuit based on threshold spiking that arises in neuromorphic engineering.
fast dependent components for fmri analysis. canonical correlation analysis (cca) can be used to find correlating projections of two datasets with co-occurring samples. instead of correlation, we would typically want to find more general dependencies, measured by mutual information. variants of cca based on non-parametric estimation of mutual information have been proposed previously; they outperform traditional cca for non-gaussian data but require infeasible amounts of computation for already quite modest sample sizes. we introduce a novel variant that uses a semiparametric estimate leading to a considerably faster algorithm. we apply the method on searching for statistical dependencies between multi-sensory stimuli and functional magnetic resonance imaging (fmri) of brain activity- in contrast to using regression on either of them.
comparison of scoring methods used in speaker recognition with joint factor analysis. the aim of this paper is to compare different log-likelihood scoring methods, that different sites used in the latest state-of-the-art joint factor analysis (jfa) speaker recognition systems. the algorithms use various assumptions and have been derived from various approximations of the objective functions of jfa. we compare the techniques in terms of speed and performance. we show, that approximations of the true log-likelihood ratio (llr) may lead to significant speedup without any loss in performance.
tree configuration games for distributed stream mining systems. we consider the problem of configuring classifier trees in distributed stream mining system. the configuration involves selecting appropriate false-alarm detection tradeoffs for each classifier to minimize end-to-end penalty in terms of misclassification cost. we model this as a tree configuration game and design solutions, where individual classifiers select their operating points to maximize a local utility. we derive appropriate misclassification cost coefficients for intermediate classifiers, and determine the information that needs to be exchanged across classifiers, in order to successfully design the game. we analytically show that there is a unique pure strategy nash equilibrium in operating points, which guarantees a convergence of the proposed approach. we evaluate the performance of our algorithm on an application for sports scene classification, and compare against centralized solutions. we show that our algorithm results in better performance than the centralized solution on average. moreover, the algorithm approaches the optimal solution asymptotically with increasing number of actions per classifier.
log-likelihood ratio clipping in mimo-bicm systems: information geometric analysis and impact on system capacity. the clipping of log-likelihood ratios (llrs) in soft demodulators for multiple-input multiple-output (mimo) systems with bit-interleaved coded modulation (bicm) was recently observed to allow for enormous complexity savings. in this paper we first provide an information-geometric interpretation of llr clipping as information projection onto a log-convex manifold. then we study the system capacity of mimo-bicm systems that use llr clipping. our results show that strong llr clipping is possible without significant capacity loss. we finally propose an llr transformation scheme which is necessary for approaching capacity in case of strong clipping. the usefulness of this llr transformation is illustrated by numerical simulations for mimo-bicm systems employing low-density parity check (ldpc) codes.
towards source-filter based single sensor speech separation. we present a new source-filter based method to separate two speakers talking simultaneously at equal level mixed into a single sensor. first, the relation between the spectral whitened mixture and the speakers excitation signals is analyzed. therefore, a factorial hmm capturing also time dependencies is exploited. then, the estimated excitation signals are combined with best fitting vocal tract information taken from a trained dictionary. we report results on the database of cooke considering 108 speech mixtures. the average improvement of 2.9 db in sir for all data is lower but not significantly lower compared to the gaussian mixture method which relies on known pitch-tracks. although the performance is currently moderate we believe in this approach and its significance towards the development of speaker independent single sensor speech separation.
comparing maximum a posteriori vector quantization and gaussian mixture models in speaker verification. gaussian mixture model - universal background model (gmm-ubm) is a standard reference classifier in speaker verification. we have recently proposed a simplified model using vector quantization (vq-ubm). in this study, we extensively compare these two classifiers on nist 2005, 2006 and 2008 sre corpora, while having a standard discriminative classifier (glds-svm) as a reference point. we focus on parameter setting for n-top scoring, model order, and performance for different amounts of training data. the most interesting result, against a general belief, is that gmm-ubm yields better results for short segments whereas vq-ubm is good for long utterances. the results also suggest that maximum likelihood training of the ubm is sub-optimal, and hence, alternative ways to train the ubm should be considered.
sparse decomposition of two dimensional signals. in this paper, we consider sparse decomposition (sd) of two-dimensional (2d) signals on overcomplete dictionaries with separable atoms. although, this problem can be solved by converting it to the sd of one-dimensional (1d) signals, this approach requires a tremendous amount of memory and computational cost. moreover, the uniqueness constraint obtained by this approach is too restricted. then in the paper, we present an algorithm to be used directly for sparse decomposition of 2d signals on dictionaries with separable atoms. moreover, we will state another uniqueness constraint for this class of decomposition. our algorithm is obtained by modifying the smoothed l0 (sl0) algorithm, and hence we call it two-dimensional sl0 (2d-sl0).
state mapping for cross-language speaker adaptation in tts. cross-language speaker adaptation has many interesting applications, e.g. speech-to-speech translation. however, in cross-language speaker adaptation, a common phoneme set, assumed to be used by different speakers of the same language, does not exist any longer. instead, a nearest neighbor based phoneme mapping from one language to the other has been adopted. in this study, we used our recently proposed sub-phonemic hmm state mapping for cross-language adaptations. the sub-phonemic hmm states, due to their phonetic segment nature, tend to be more sharable across different languages than phonemes. kullback-leibler divergence, an information-theoretic measure, is chosen here to measure the similarity between given states in different languages. experimental results show that new state mapping outperforms the phoneme mapping baseline system in terms of three objective measures: log spectral distance, f0 adaptation error and f0 correlations. in comparing with intra-language adaptation, the cross-language result of the new algorithm is also fairly decent.
view-invariant tensor null-space representation for multiple motion trajectory retrieval and classification. in this paper, we propose a novel general framework for tensor based null space affine invariants, namely, tensor null space invariants (tnsi) with a linear classifier for high order data classification and retrieval. we first derive tnsi, which is perfectly invariant to multidimensional affine transformations due to camera motions for multiple motion trajectories in consecutive motion events. we subsequently propose an efficient classification and retrieval system relying on tnsi for archiving and searching motion events consisting of multiple motion trajectories. the simulation results demonstrate superior performance of the proposed systems.
filtering web text to match target genres. in language modeling for speech recognition, both the amount of training data and the match to the target task impact the goodness of the model, with the trade-off usually favoring more data. for conversational speech, having some genre-matched text is particularly important, but also hard to obtain. this paper proposes a new approach for genre detection and compares different alternatives for filtering web text for genre to improve language models for use in automatic transcription of broadcast conversations (talk shows).
mitigation of narrowband interference in differentially modulated communication systems. integration of rf/analog and digital into a single chip can result in the coupling of digital spurs in the analog front end of a communication systems and can severely degrade the receiver performance. in this paper, we propose a novel receiver architecture of a notch filter together with the feedback filter (fbf) of the decision feedback equalizer (dfe) to mitigate the impact of narrowband interference in differentially modulated communication systems without enhancing the inter-symbol interference (isi). the proposed solution can be adapted to receiver architectures that employ either coherent or non-coherent demodulation of differentially modulated systems. simulation results demonstrating the spur mitigation capability of the proposed solution is presented.
lattice-based optimization of sequence classification criteria for neural-network acoustic modeling. acoustic models used in hidden markov model/neural-network (hmm/nn) speech recognition systems are usually trained with a frame-based cross-entropy error criterion. in contrast, gaussian mixture hmm systems are discriminatively trained using sequence-based criteria, such as minimum phone error or maximum mutual information, that are more directly related to speech recognition accuracy. this paper demonstrates that neural-network acoustic models can be trained with sequence classification criteria using exactly the same lattice-based methods that have been developed for gaussian mixture hmms, and that using a sequence classification criterion in training leads to considerably better performance. a neural network acoustic model with 153k weights trained on 50 hours of broadcast news has a word error rate of 34.0% on the rt04 english broadcast news test set. when this model is trained with the state-level minimum bayes risk criterion, the rt04 word error rate is 27.7%.
perceptual quality based packet dropping for generalized video gop structures. our work builds a general visibility model of video packets which is applicable to various types of gop (group of pictures). the data used for analysis and building the model come from three subjective experiment sets with different encoding and decoding parameters on h.264 and mpeg-2 videos. we consider factors not only within a packet but also across its vicinity to account for possible temporal and spatial masking effects. this model can be useful for an intermediate router in a congested network to drop less visible packets to maintain overall video quality. experiments are done to compare our perceptual-quality-based packet dropping approach with existing drop-tail and hint-track-inspired cumulative-mse-based dropping methods. the result shows that our dropping method produces videos of higher perceptual quality for different network conditions and gop structures.
analysis-by-synthesis based switched transform domain split vq using gaussian mixture model. using analysis-by-synthesis (abs) approach, we develop a soft decision based switched vector quantization (vq) method for high quality and low complexity coding of wideband speech line spectral frequency (lsf) parameters. for each switching region, a low complexity transform domain split vq (trsvq) is designed. the overall rate-distortion (r/d) performance optimality of new switched quantizer is addressed in the gaussian mixture model (gmm) based parametric framework. in the abs approach, the reduction of quantization complexity is achieved through the use of nearest neighbor (nn) trsvqs and splitting the transform domain vector into higher number of subvectors. compared to the current lsf quantization methods, the new method is shown to provide competitive or better trade-off between r/d performance and complexity.
an evidence framework for bayesian learning of continuous-density hidden markov models. we present an evidence bayesian framework, which can learn both the prior distributions and posterior distributions from data, for continuous-density hidden markov models (cdhmm). the goal of this study is to build the regularized cdhmms to improve model generalization, and achieve desirable recognition performance for unknown test speech. under this framework, we develop an em iterative procedure to estimate the marginal distribution or the evidence function for exponential family distributions. by adopting the variational bayesian inference, we derive an empirical bayesian solution to cdhmm parameters and their hyperparameters. such a regularized cdhmm compensates the model uncertainty and the ill-posed conditions. compared with maximum likelihood (ml) or other bayesian approaches with heuristic hyperparameters, the proposed approach can utilize available data more effectively. the experiments on noisy speech recognition using aurora2 show that the proposed bayesian approach performs better than the baseline ml cdhmms especially with mismatched test data or limited training data.
separation of a subspace-sparse signal: algorithms and conditions. in this paper, we show how two classical sparse recovery algorithms, orthogonal matching pursuit and basis pursuit, can be naturally extended to recover block-sparse solutions for subspace-sparse signals. a subspace-sparse signal is sparse with respect to a set of subspaces, instead of atoms. by generalizing the notion of mutual incoherence to the set of subspaces, we show that all classical sufficient conditions remain exactly the same for these algorithms to work for subspace-sparse signals, in both noiseless and noisy cases. the sufficient conditions provided are easy to verify for large systems. we conduct simulations to compare the performance of the proposed algorithms.
spectrally rich phase distortion sound synthesis using an allpass filter. this paper examines a recently introduced technique for sound synthesis that uses a coefficient modulated allpass filter to cause phase modifications to its input signal. the intention in this work is to outline some of the properties of the coefficient modulated allpass filter and then to establish a connection between this new method and the older technique of phase distortion. results are presented to demonstrate how the allpass technique provides a spectrally richer output signal.
improvements on minimum covariance based spatial correlation transformation. in order to take advantage of the correlation information among different acoustic units in speech recognition, a novel approach named minimum covariance based spatial correlation transformation was proposed in [8], which achieves satisfactory performance. however, there are two issues of this approach which can still be improved, 1) the estimation of the transformation matrix; 2) the construction of the history data. in this paper, a new algorithm of estimating the transformation matrix and a new strategy of constructing history supervector are proposed. experimental results show that the improved approach achieves better performance than the original one.
signal characterization using generalized "time-phase derivatives" representation. natural signals are often characterized by a complex time-frequency behaviour. these signals exist in many different applications and systems from underwater acoustic to audio signals with sound attacks or electrical systems with partial discharges and commutation switches, for example. there is a huge number of time-frequency (tf) methods that aim to characterize these signals in terms of first phase derivative analysis (i.e instantaneous frequency law). recently, we introduced the time frequency distribution based on complex lag arguments. this distribution is able to reduce inner interferences terms which appear when studying non-linear tf components. it also offers access to an instantaneous law representation of any phase derivative order. in this paper, we use these two properties to study highly non-stationary signals as well as transient signals.
neighborhood gossip: concurrent averaging through local interference. in this paper, we study a gossip algorithm for distributed averaging over a wireless sensor network. the usual assumption is that, through properly chosen codes, the physical layer is reduced to a set of reliable bit pipes for the distributed averaging algorithm. however, with a new channel coding technique, computation coding, we can exploit the interference property of the wireless medium for efficient averaging. this then provides a new abstraction for the physical layer: reliable linear equations instead of reliable bit pipes. the “neighborhood gossip” algorithm operates modularly on top of this abstraction. we will show that for certain regimes, such an approach can lead to energy savings that are exponential in the network size and time savings that are polynomial.
a performance-weighted mixture of lms filters. in this paper, we explore the use of a particular multistage adaptation algorithm for a variety of adaptive filtering applications where the structure of the underlying process to be estimated is unknown. the proposed algorithm uses a performance-weighted mixture of lms filters of various orders to construct its final output. the algorithm is analyzed in a stochastic context with respect to its convergence and mean-square error (mse) behaviors and is shown to achieve the best mse performance of the constituent algorithms in the mixture. through simulations, it has been observed that the mixture structure can offer considerable performance improvement for both stationary and time varying observation sequences.
ofdm turbo decodulation with exit optimized bit loading and signal constellations. we propose the combination of orthogonal frequency division multiplexing (ofdm) and turbo decodulation (tdec) - a multiple turbo process consisting of iterative demodulation and iterative source-channel decoding - for transmission of correlated source codec parameters over wireless frequency-selective broadband fading channels. as ofdm systems split up frequency-selective fading channels into orthogonal flat-fading channels, individual modulation signal constellations sets with different bit mapping rules can be assigned to subcarriers taking into account the iterative reception and decoding process. the superior performance of the proposed ofdm-tdec system is demonstrated by analyzing the achieved residual bit error rate (ber) and parameter signal-to-noise ratio (snr).
adaptive newton algorithms for blind equalization using the generalized constant modulus criterion. two newton-type algorithms using the generalized complex modulus (gcm) criterion for blind equalization and carrier phase recovery are proposed. first the partial hessian and full hessian of the real gcm loss function with complex valued arguments are calculated by second-order differential. then an adaptive pseudo newton learning algorithm and a full newton learning algorithm are designed. by using the matrix inversion lemma, both newton algorithms can be implemented with a computational complexity of o(l2) efficiently, where l is the length of equalizer. simulation results demonstrate that the two newton algorithms can achieve automatic carrier phase recovery and exhibit fast convergence rates.
optimal network beamforming for bi-directional relay networks. we consider a relay network which consists of two transceivers and r relay nodes. we study a half-duplex two-way relaying scheme. first, the two transceivers transmit their information symbols simultaneously and the relays receive a noisy mixture of the two transceiver signals. then each relay adjusts the phase and the amplitude of its received signal by multiplying it with a complex beamforming coefficient and transmits the so-obtained signal. aiming at optimally calculating the beamforming weight vector as well as the transceiver transmit powers, we minimize the total transmit power subject to two constraints on the receive signal-to-noise ratios (snrs) at the two transceivers. we show that the optimal weight vector can be obtained through a simple iterative algorithm which enjoys a linear computational complexity per iteration.
fast gender recognition by using a shared-integral-image approach. we develop a new approach for gender recognition. in this paper, our approach uses the rectangle feature vector (rfv) as a representation to identify humans' gender from their faces. the rfv is computationally fast and effective to encode intensity variations of local regions of human face. by only using few rectangle features learned by adaboost, we present a gender identifier. we then use nonlinear support vector machines for classification, and obtain more accurate identification results.
cultural style based music classification of audio signals. music classification based on cultural style is useful for music analysis and has potential applications in retrieval and recommendation systems. in this paper, we present the first attempt to classify audio signals automatically according to their cultural styles, which are characterized by timbre, rhythm, wavelet coefficients and musicology-based features. machine learning algorithms are employed to investigate the effectiveness of various features on a data set of 1300 music pieces. experimental results show that the proposed method can achieve an overall accuracy of 86% for six cultural styles, which shows the feasibility of integrating cultural style classification into music retrieval systems.
support vector machines and joint factor analysis for speaker verification. this article presents several techniques to combine between support vector machines (svm) and joint factor analysis (jfa) model for speaker verification. in this combination, the svms are applied to different sources of information produced by the jfa. these informations are the gaussian mixture model supervectors and speakers and common factors. we found that using svm in jfa factors gave the best results especially when within class covariance normalization method is applied in order to compensate for the channel effect. the new combination results are comparable to other classical jfa scoring techniques.
bayesian and hybrid cramer-rao bounds for qam dynamical phase estimation. in this paper, we study bayesian and hybrid cramer-rao bounds for the dynamical phase estimation of qam modulated signals. we present the analytical expressions for the various crbs. this avoids the calculation of any matrix inversion and thus greatly reduces the computation complexity. through simulations, we also illustrate the behaviors of the bcrb and of the hcrb with the signal-to-noise ratio.
openmp-based parallel implementation of a continuous speech recognizer on a multi-core system. we have implemented a 20,000-word continuous speech recognizer on a multi-core based system. a fine grain parallel processing approach is employed for good scalability, and the openmp library is used for enhanced portability. in the emission probability computation, a dynamic workload distribution method is employed for good load balancing. however, the search network involved in the viterbi beam search is statically partitioned into independent subtrees to reduce memory synchronization overhead. in order to further improve the performance, a workload predictive thread assignment strategy as well as a false cache line sharing prevention method are employed. the test was conducted using wsj1 20k test and development set. we achieved the speed-up of 3.90 by utilizing four threads parallelization in a four-core system compared to four copies of the baseline single thread speech recognizer running simultaneously. the final recognition system runs about twice the speed of the real-time requirement.
interpolation error as a quality metric for stereo: robust, or not? to properly benchmark and stimulate current stereo algorithms specifically in the application context of view interpolation, a robust quantitative evaluation approach is important. as a prevailing quality assessment method, interpolation error has been widely used. it measures the distortions between an interpolated image and a real camera image for a desired virtual viewpoint. however, is it a robust quality metric, especially when state-of-the-art stereo technology is developing so fast? this paper hence focuses on revealing several rarely attended weaknesses that make the interpolation error evaluation paradigm vulnerable. in addition, we propose an alternative evaluation method as an early attempt at addressing these challenges, from a perspective of communication system. evaluation of representative stereo methods from the middlebury website shows that the new approach yields consistent quality assessment outcomes.
event recognition with time varying hidden markov model. standard hidden markov model (hmm) and the more general dynamic bayesian network (dbn) models assume stationarity of state transition distribution. however, this assumption does not hold for many real life events of interest. in this paper, we propose a new time sequence model that extends hmm to time varying scenario. the time varying property is realized in our model by explicitly allowing the change of state transition density as the time spent in a particular state passes by. rather than keeping transition densities at different time spots independent of each other, we exploit their temporal correlation by applying a hierarchical dirichlet prior. this leads to a more robust time varying model, especially when training data are scarce. we also employ markov chain monte carlo (mcmc) sampling in learning the map estimate of time varying parameters, with a transition kernel incorporating linear optimization. the proposed model is applied to recognizing real video events, and is shown to outperform existing hmm-based methods.
multiple ica-based real-time blind source extraction applied to handy size microphone. a new blind source extraction method in widespread noise conditions is proposed, which is based on multiple frequency-domain independent component analysis (fdica) combining projection back and spectral subtraction. in addition, we implement the proposed method to digital signal processor (dsp) for a more realistic real-time operation, and develop a new blind source extraction (bse) microphone which can extract a target sound in real-time. in this paper, we illustrate and evaluate the proposed method and bse microphone. and experimental results reveal that the extraction performance of the proposed method are superior to that of conventional methods, and we show the efficacy of microphone.
language model transformation applied to lightly supervised training of acoustic model for congress meetings. for effective training of acoustic and language models for spontaneous speech such as meetings, it is significant to exploit the texts available in a large scale, which may not be faithful transcripts of the utterances. we have proposed a language model transformation scheme to cope with the differences between verbatim transcripts of spontaneous utterances and human-made transcripts such as those in proceedings. in this paper, we investigate its application to lightly supervised training of the acoustic model. by transforming the corresponding text in the proceedings, we can generate a very constrained model to predict the actual utterances. the experimental evaluation with the transcription system for the japanese congress meetings demonstrated that the proposed scheme can generate accurate labels for acoustic model training and thus realizes the comparable asr (automatic speech recognition) performance to the case using manual transcripts.
scalable distributed source coding. this paper considers the problem of scalable distributed coding of correlated sources that are communicated to a central unit. the general setting is typically encountered in sensor networks. the conditions of communication channels between the source encoders and fusion center may be time-varying and it is often desirable to guarantee a base layer of coarse information during channel fades. in addition the desired system should be robust to various scenarios of channel failure and should utilize all the available information to attain the best possible compression efficiency. although a standard ‘lloyd-style’ distributed coder design algorithm can be generalized to scalable distributed source coding, the resulting algorithm depends heavily on initialization and will virtually always converge to a poor local minimum on the distortion-cost surface. we propose an efficient initialization scheme for such a system, which employs a properly designed multi-stage distributed coder. in our prior work, we highlighted the fundamental conflict that arises when multi-stage coding is directly combined with distributed quantization. here we use the multi-stage distributed coding system to initialize a scalable distributed coder and propose an iterative algorithm for joint design of all system components once the structural constraint is removed. simulation results show considerable gains over randomly initialized scalable distributed coder design.
morphing of transient sounds based on shift-invariant discrete wavelet transform and singular value decomposition. in this paper, a new morphing algorithm for transient sounds is introduced. input sounds are first projected onto orthogonal bases from which intermediate or novel sounds can be generated. the proposed algorithm uses a shift invariant version of discrete wavelet transform and the singular value decomposition (svd) to represent the input sound signals over a set of orthogonal bases. interpolation is carried out between the weight vectors from the svd to produce a new weight vector used for synthesising a new set of wavelet coefficients. the morphed sound is generated by taking the inverse discrete wavelet transform of the combined weighted bases. the proposed algorithm not only generates a range of new sounds, but also represents the input sounds in a more compact fashion.
performance bounds of mimo receivers in the presence of radio frequency interference. multi-input multi-output (mimo) receivers have generally been designed and their communication performance analyzed under the assumption of additive gaussian noise. wireless transceivers, however, may also be affected by radio frequency interference (rfi) that is well modeled using non-gaussian impulsive statistics. in this paper, we derive bounds on the communication performance for a two transmit, two receive antenna mimo system in the presence of rfi. our contributions include derivation of (1) channel capacity in the presence of rfi, (2) probability of symbol error for uncoded transmissions, and (3) chernoff bound on the pairwise error probability and cutoff rate as a measure of the throughput performance for coded transmissions. comparison with the communication performance bounds for receivers designed assuming additive gaussian noise demonstrates degradation in communication performance in the presence of rfi.
cadence analysis of temporal gait patterns for seismic discrimination between human and quadruped footsteps. this paper reports on a method of cadence analysis for the discrimination between human and quadruped using a cheap seismic sensor. previous works in the domain of seismic detection of human vs. quadruped have relied on the fundamental gait frequency. slow movement of quadrupeds can generate the same fundamental gait frequency as human footsteps therefore causing the recognizer to be confused when quadruped are ambling around the sensor. here we propose utilizing the cadence analysis of temporal gait pattern which provides information on temporal distribution of the gait beats. we also propose a robust method of extracting temporal gait patterns. features extracted from gait patterns are modeled with optimum number of gaussian mixture models (gmms). the performance of the system during the test for discriminating between horse, dog, multiple people walk, and single human walk/run was over 95%.
rate distribution between model and signal for multiple descriptions. we consider the rate allocation problem for multiple-description quantization of the signal described by an adaptive model with a fixed structure. the source modeling in coding generally results in a two-stage description of the data, where one of the stages describes the model parameters, and the other describes the signal. such a setup implies the existence of a trade-off between the rate spent on the parameters and the rate spent on the signal. we optimize this trade-off analytically for the multiple-description case using a method inspired by minimum description length principle. we also provide an algorithm for optimizing the rate allocation between the components of the model-based multiple description coder. finally we experimentally confirm our results. our method facilitates the rate-adaptive multiple-description coding.
a new method to find an optimal warping function in image stitching. in image stitching applications, it is very important to find a suitable warping function for the visual quality of a composite (stitching result). in this paper, we present a new mathematical criterion to select an optimal warping function among a set of possible candidates (e.g., parametric family). the proposed criterion can be considered as a direct view condition for image stitching , i.e., it is desirable that each part of the composite image looks like its corresponding input image. more specifically, we do not use an explicit modeling of a compositing surface, but, we focus on the differential properties of a warping function. that is we design a cost function so that the jacobian matrix of a warping function is close to a shape preserving matrix such as rotation and reflection matrices. the proposed cost function can be effectively minimized by using levenberg-marquardt algorithm. the experimental results show that the proposed method results in visually pleasing stitched results because the original shape of each image is preserved in the composite.
revisiting quantization theorem through audiowatermarking. in this paper, we propose the concept of “doping watermarking”, whose principle is to add an imperceptible noise to an host signal in order to improve its properties. especially, our aim is to reduce the spectral support of the probability density function (pdf) of an audio signal in order to match the conditions of the quantization theorem. in this context, we develop a specific audiowatermarking algorithm and test its performance on real audio signals. this watermark allows to recover the pdf of a digital signal from a sub-quantized version of the signal, with very low error.
nonparametric curve alignment. congealing is a flexible nonparametric data-driven framework for the joint alignment of data. it has been successfully applied to the joint alignment of binary images of digits, binary images of object silhouettes, grayscale mri images, color images of cars and faces, and 3d brain volumes. this research enhances congealing to practically and effectively apply it to curve data. we develop a parameterized set of nonlinear transformations that allow us to apply congealing to this type of data. we present positive results on aligning synthetic and real curve data sets and conclude with a discussion on extending this work to simultaneous alignment and clustering.
multi-foveation filtering. we present a method for computing a function of average multi-viewer eye sensitivity based on the geisler & perry contrast threshold formula, and, from this, the cut-off frequency map (as used in foveation filtering) that is optimal in the sense of discarding frequencies in least-noticeable-first order. existing approaches usually solve the multi-viewer foveation problem as a number of single-viewer foveations, effectively taking collective sensitivity to be the maximum of the individual viewer eye sensitivities. this has inherent problems such as over-sensitivity to outliers which are not problems with the proposed approach. furthermore, the proposed approach can be employed in the infinite-viewer (probability-based) scenario without additional cost.
unimodular sequence design for good autocorrelation properties. unimodular (i.e., constant modulus) sequences with good autocorrelation properties are useful in several areas, including communications, radar and sonar. the integrated sidelobe level (isl) is often used to express the goodness of the autocorrelation properties of a given sequence. in this paper, we present several cyclic algorithms for the local minimization of isl-related metrics. to illustrate the performance of the proposed algorithms, we present a number of examples including the design of sequences that have virtually zero autocorrelation sidelobes in a specified lag interval, and of long sequences that could hardly be handled by means of other algorithms previously suggested in the literature.
volterra series for analyzing mlp based phoneme posterior estimator. we present a framework to apply volterra series to analyze multi-layered perceptrons trained to estimate the posterior probabilities of phonemes in automatic speech recognition. the identified volterra kernels reveal the spectro-temporal patterns that are learned by the trained system for each phoneme. to demonstrate the applicability of volterra series, we analyze a multilayered perceptron trained using mel filter bank energy features and analyze its first order volterra kernels.
a frequency hopping spread spectrum transmission scheme for uncoordinated cognitive radios. one of the major challenges to cognitive radios is the synchronization of distributed radios onto the same spectrum white spaces which vary in time and space. in this paper, we propose a frequency-hopping spread spectrum transmission scheme which works reliably without any a priori handshaking assumption. each cognitive radio independently detects white spaces, and then selects one of them to transmit or receive signals according to a pre-defined frequency hopping pattern. while exploiting the reliability of the white space detection capability of cognitive radios, the new scheme is robust to even large detection errors. according to the accuracy of the spectrum sensing, both the secondary data rate and the interference to primary users can be optimized by adjusting the spreading gain. its performance is analyzed and demonstrated by simulations.
a new approach for the reassignment of time-frequency representations. the reassignment method is a widespread approach for obtaining high resolution time-frequency representations. nevertheless, its performance is not always optimal and can deteriorate for low signal-to-noise ratio (snr) values. in order to overcome these obstacles, a novel method for obtaining high resolution time-frequency representations is proposed in this paper. the new method implements recently proposed nonparametric snakes in order to obtain accurate locations of the signal ridges in the time-frequency domain. the results of numerical analysis show that the proposed method is capable of achieving significantly higher concentration of signals in the time-frequency domain in comparison to the spectrogram and the traditional reassignment method. furthermore, the new scheme also maintains good performance for low snr values, while the performance of the other two considered methods significantly diminishes. it is clear from the results that the proposed method might be of significance in applications where accurate estimation of the signal components is required for low snr values.
a game theoretical algorithm for joint power and topology control in distributed wsn. in this paper, the issue of network topology control in wireless networks using a fully distributed algorithm is considered. whereas the proposed distributed algorithm is designed applying game theory concepts to design a non-cooperative game, network connectivity is guaranteed based on asymptotic results of network connectivity. simulations show that for a relatively low node density, the probability that the proposed algorithm leads to a connected network is close to one.
parsimonious dictionary learning. sparse modeling of signals has recently received a lot of attention. often, a linear under-determined generative model for the signals of interest is proposed and a sparsity constraint imposed on the representation. when the generative model is not given, choosing an appropriate generative model is important, so that the given class of signals has approximate sparse representations. in this paper we introduce a new scheme for dictionary learning and impose an additional constraint to reduce the dictionary size. small dictionaries are desired for coding applications and more likely to “work” with suboptimal algorithms such as basis pursuit. another benefit of small dictionaries is their faster implementation, e.g. a reduced number of multiplication/addition in each matrix vector multiplication, which is the bottleneck in sparse approximation algorithms.
latent dirichlet learning for document summarization. automatic summarization is developed to extract the representative contents or sentences from a large corpus of documents. this paper presents a new hierarchical representation of words, sentences and documents in a corpus, and infers the dirichlet distributions for latent topics and latent themes in word level and sentence level, respectively. the sentence-based latent dirichlet allocation (slda) is accordingly established for document summarization. different from the vector space summarization, slda is built to fit the fine structure of text documents, and is specifically designed for sentence selection. slda acts as a sentence mixture model with a mixture of dirichlet themes, which are used to generate the latent topics in observed words. the theme model is inherent to distinguish sentences in a summarization system. in the experiments, the proposed slda outperforms other methods for document summarization in terms of precision, recall and f-measure.
improved subspace doa estimation methods with large arrays: the deterministic signals case. this paper is devoted to the subspace doa estimation using a large antennas array when the number of available snapshots is of the same order of magnitude than the number of sensors. in this context, the traditional subspace methods fail because the empirical covariance matrix of the observations is a poor estimate of the true covariance matrix. mestre et al. proposed recently to study the behaviour of the traditional estimators when the number of antennas m and the number of snapshots n converge to +∞ at the same rate. using large random matrix theory results, they showed that the traditional subspace estimate is not consistent in the above asymptotic regime and they proposed a new consistent subspace estimate which outperforms the standard subspace method for realistic values of m and n. however, the work of mestre et al. assumes that the source signals are independent and identically distributed in the time domain. the goal of the present paper is to propose new consistent estimators of the doas in the case where the source signals are modelled as unknown deterministic signals. this, in practice, allows to use the proposed approach whatever the statistical properties of the source signals are.
differential feedback of mimo channel correlation matrices based on geodesic curves. this paper proposes a differential quantization strategy to be used in the feedback link of a multi-input-multi-output (mimo) communication system. this algorithm is applied to the channel correlation matrix exploiting geodesic curves and the intrinsic geometry of positive definite hermitian matrices. simulation results in the paper show that the proposed algorithm improves other techniques based on the direct quantization of the channel response matrix or the quantization of the subspace spanned by the strongest eigenmodes of the mimo channel, i.e., grassmannian based techniques. the main drawback of grassmananian based algorithms is that the transmitter is constrained to apply a uniform power allocation among eigenmodes, which is not forced in the algorithm proposed in this paper.
compression of image patches for local feature extraction. local features are widely used for content-based image retrieval and object recognition. we present an efficient method for encoding digital images suitable for local feature extraction. first, we find the patches in the image corresponding to the detected features. then, we extract these patches at their characteristic scale and orientation and encode them for efficient transmission. a discrete cosine transform (dct) with adaptive block size is used for patch compression. we compare this method to directly compressing feature descriptors using transform coding. experimental results show the superior performance of our technique. image patches can be compressed to rates around 55 bits/patch (18x compression relative to uncompressed sift feature descriptors) and still achieve good image matching performance.
high-rate distributed multi-source cooperation using complex field coding. a multisource cooperative protocol is developed capable of achieving diversity order up to the number of cooperating users at a high throughput. in this design each source jointly encodes its own new information symbol with the information symbols received from other sources at past instants. joint encoding is done using linear complex-field coefficients. throughput analysis shows gains with respect to existing multi-source protocols and approaches the throughput of non-cooperative schemes. diversity analysis shows that full spatial diversity is achievable. simulations confirm the analytically established assessments.
i/q imbalance mitigation for time-reversal stbc systems over frequency-selective fading channels. this work studies the effect of in-phase/quadrature (i/q) imbalance on time-reversal space-time block coded (tr-stbc) communication systems operating over frequency-selective fading channels. the transceiver i/q imbalance in a 2 × 1 tr orthogonal stbc (tr-ostbc) system is studied in detail, and low-complexity mitigation solutions are proposed by exploiting the special structure of the received data. our results show that the proposed solutions both in time domain and in frequency domain can effectively mitigate the i/q distortion in such a system.
joint estimation of i/q imbalance, cfo and channel response for ofdm systems. in this paper, we study the joint estimation of i/q imbalance, cfo and channel response for ofdm systems. using two repeated ofdm blocks for training, we propose a new method to solve the joint estimation problem. the implementation complexity is low. simulation results show that the proposed method has a good performance and its ber is very close to the ideal case where all the parameters are known perfectly at the receiver.
robust 2-d channel estimation for multi-carrier systems with finite dimensional pilot grid. pilot-aided channel estimation for multi-carrier systems can be significantly improved by exploiting time and frequency correlations between the channel frequency response coefficients. but in practice, the knowledge of channel correlation function is not accurately available, thereby necessitating the need of an estimator that employs a fixed correlation function and is robust to mismatches with the actual one. while the maximally robust channel estimator for multi-carrier systems for the case of an infinite number of observations is well known for almost a decade, the one for the case of a finite number of observations has been only recently proposed. we extend the proposed maximally robust estimator to the practical case of small finite dimensional pilot grids by taking into account the grid edge effects. this paves the way for application of the estimator to practical systems such as 3g lte. simulation results for an lte uplink system under different transmission scenarios demonstrate the superiority of the proposed maximally robust estimator over the heuristic one by as much as 1.35 db in terms of the coded ber.
decision-based median filter using k-nearest noise-free pixels. traditional median filter replaces each pixel in an image with the median value of their k-nearest pixels (commonly known as pixels in 2-d window). the problem associated with this approach is that the restored pixel is noise if median value of their k-nearest pixels is a corrupted pixel. to mitigate the above problem, this paper proposes a novel decision-based median filter that replaces each corrupted pixel with the median value of their k-nearest noise-free pixels. advantages of the median filter using k-nearest noise-free pixels instead of k-nearest pixels are two facets: first, it guarantees that pixels after being restored must be noise-free, because the median filter operator is executed on noise-free pixels; second, the median filter using k-nearest noise-free pixels adaptively adjusts its window size for each pixel such that the number of noise-free pixels locating in the window increases up to k. to realize it, the median filter using k-nearest noise-free pixels firstly detects noise-free pixels in an image, then replaces each corrupted pixel with the median value of their knearest noise-free pixels. the proposed median filter is tested on four real images corrupted by different levels of salt-and-pepper noise. experimental results confirm the effectiveness of decision-based median filter using k-nearest noise-free pixels.
didstributed source coding authentication of images with affine warping. media authentication is important in content delivery via untrusted intermediaries, such as peer-to-peer (p2p) file sharing. many differently encoded versions of a media file might exist. our previous work applied distributed source coding not only to distinguish the legitimate diversity of encoded images from tampering but also to localize tampered regions in an image already deemed to be inauthentic. in both cases, authentication requires a slepian-wolf encoded image projection that is supplied to the decoder. we extend our scheme to authenticate images that have undergone affine warping. our approach incorporates an expectation maximization algorithm into the slepian-wolf decoder. experimental results demonstrate that the proposed algorithm can distinguish legitimate encodings of authentic images from illegitimately modified versions, despite an arbitrary affine warping, using authentication data of less than 250 bytes per image.
automatic pronunciation error detection based on linguistic knowledge and pronunciation space. this paper presents a new approach that uses linguistic knowledge and pronunciation space for automatic detection of typical phone-level errors made by non-native speakers of mandarin. firstly, linguistic knowledge of common learner mistakes is embedded in the calculation of log-posterior probability and the revised log-posterior probability (rlpp) is regarded as the measure of mispronunciation; secondly, a restricted pronunciation space is constructed by using rlpp vectors to describe the characteristics of pronunciation and support vector machine (svm) classifier is applied into the detection of typical pronunciation errors. experiments based on a nonnative speaker database of mandarin confirm the promising effectiveness of our methods.
secure image retrieval through feature protection. this paper addresses the problem of image retrieval from an encrypted database, where data confidentiality is preserved both in the storage and retrieval process. the paper focuses on image feature protection techniques which enable similarity comparison among protected features. by utilizing both signal processing and cryptographic techniques, three schemes are investigated and compared, including bit-plane randomization, random projection, and randomized unary encoding. experimental results show that secure image retrieval can achieve comparable retrieval performance to conventional image retrieval techniques without revealing information about image content. this work enriches the area of secure information retrieval and can find applications in secure online services for images and videos.
a mimo-ofdm channel estimation scheme utilizing complementary sequences. we present a pilot-assisted method for estimating the frequency selective channel in a mimo-ofdm system. the pilot sequence is designed using the dft of the golay complementary sequences. novel exploitation of the perfect autocorrelation property of golay complementary sequences, in conjunction with ostbc based pilot waveform scheduling across multiple ofdm frames, facilitates simple separation of the channel mixtures at the receive antennas. the dft length used to transform the complementary sequence into the frequency domain is shown to be a key critical parameter for correctly estimating the channel. this channel estimation scheme is then extended to antenna arrays of arbitrary sizes.
fast acoustic computations using graphics processors. in this paper we present a fast method for computing acoustic likelihoods that makes use of a graphics processing unit (gpu). after enabling the gpu acceleration the main processor runtime dedicated to acoustic scoring tasks is reduced from the largest consumer to just a few percent even when using mixture models with a large number of gaussian components. the results show a large reduction in decoding time with no change in accuracy and we also show by using a 16bit half precision floating point format for the acoustic model parameters, storage requirements can be halved with no reduction in accuracy.
acoustic fall detection using gaussian mixture models and gmm supervectors. we present a system that detects human falls in the home environment, distinguishing them from competing noise, by using only the audio signal from a single far-field microphone. the proposed system models each fall or noise segment by means of a gaussian mixture model (gmm) supervector, whose euclidean distance measures the pairwise difference between audio segments. a support vector machine built on a kernel between gmm supervectors is employed to classify audio segments into falls and various types of noise. experiments on a dataset of human falls, collected as part of the netcarity project, show that the method improves fall classification f-score to 67% from 59% of a baseline gmm classifier. the approach also effectively addresses the more difficult fall detection problem, where audio segment boundaries are unknown. specifically, we employ it to reclassify confusable segments produced by a dynamic programming scheme based on traditional gmms. such post-processing improves a fall detection accuracy metric by 5% relative.
posterior features applied to speech recognition tasks with user-defined vocabulary. this paper presents a novel approach for those applications where vocabulary is defined by a set of acoustic samples. in this approach, the acoustic samples are used as reference templates in a template matching framework. the features used to describe the reference templates and the test utterances are estimates of phoneme posterior probabilities. these posteriors are obtained from a mlp trained on an auxiliary database. thus, the speech variability present in the features is reduced by applying the speech knowledge captured by the mlp on the auxiliary database. moreover, information theoretic dissimilarity measures can be used as local distances between features. when compared to state-of-the-art systems, this approach outperforms acoustic-based techniques and obtains comparable results to orthography-based methods. the proposed method can also be directly combined with other posterior-based hmm systems. this combination successfully exploits the complementarity between templates and parametric models.
syllable nucleus durations estimation using linear regression based ensemble model. unlike conventional automatic continuous speech segmentation models that deal with each boundary time-mark individually, in this paper, we propose an interval-data-based linear regression model for syllable nucleus durations estimation (lrm-de), which treats syllable boundary time-marks in pairs. this characteristic of lrm-de makes it more suitable for estimating syllable durations for english sentences, which can be used for sentence stress detection. lrm-de combines the outcomes of multiple base automatic speech segmentation machines (asms) to generate final boundary time-marks that miminize the average distance of the predicted and reference boundary-pairs of syllable nuclei. experimental results show that on timit dataset, lrm-de reduces the average difference between the predicted syllable nucleus durations and their reference ones from 13.64ms (the best result of a single asm) to 11.81ms. also, lrm-de improves the syllable nucleus segmentation accuracy from 81.59% to 83.98% within a tolerance of 20ms.
phase diffusion for the synchronization of heterogenous sensor streams. the analysis of complex human activity typically requires multiple sensors: cameras that take videos from different directions and in different areas, microphones, proximity sensors, range finders, and more. scenarios where it is not possible to associate reliable clocks to each of the sensors pose a synchronization problem between heterogeneous data streams. in this paper, we propose a new theoretical framework for measuring the synchrony between heterogenous sensor streams. the main idea is to model the phase disparity between two data streams explicitly as an ornstein-uhlenbeck random process. based on this model, we derive a simple method for synchronizing of underlying sources. we illustrate the ideas with experiments on audio-visual synchronization and human motion categorization, and report promising results.
face recognition with enhanced privacy protection. this paper presents a novel approach for face based biometric recognition. the proposed method is based on the sorted index numbers (sin) of appearance based facial features. a new algorithm is introduced to measure the similarity between sin vectors. due to the non-invertibility of the transformation from the original features to the sin vectors, the proposed method can preserve the privacy of the users. the effectiveness of the proposed method is tested on a large generic data set, which contains images from several well known face databases. experimental results demonstrate that the proposed solution may improve the recognition accuracy in both identification and verification scenarios.
precoder design for mimo broadcast channels with power leakage constraints. we investigate the design of mimo linear precoders for multiuser broadcast channels under signal leakage constraints. this power leakage constraints reflect both an important security consideration and the need for interference suppression at receivers. defining a convex optimization problem, we propose two sequential semi-definite program algorithms. in principle, our algorithms exploit both spatial diversity and multiuser diversity to enhance the overall system performance. the resulting mimo precoded transmission demonstrates superior performance over time-division multiplexed multiuser transmission in conjunction with the traditional space-time transmission.
mmse estimation in a linear signal model with ellipsoidal constraints. the estimation of an unknown parameter vector in a gaussian linear model is studied in this paper. two different cases are analyzed: the parameter vector is assumed to lie either in or on a given ellipsoid. the best estimator in terms of the mean squared error is derived. the performance of this estimator is analyzed and compared with the ordinary least squares, the constrained least squares and the linear minimax approach.
phase based features for cognitive load measurement system. the current automatic cognitive load measurement system based on mfcc and prosodic features does not take into account phase based speech information. this paper aims to improve the performance of the baseline system by introducing phase based features into the system. the additional features proposed are group delay features, all-pole model based fm features and zero crossing count based fm features. decrease in performance is observed when phase based features are considered individually or when concatenated with baseline features. however, significant performance improvement is observed when group delay features are fused with baseline features using linear combination score level fusion.
generative model-based speaker clustering via mixture of von mises-fisher distributions. this paper proposes a generative model-based speaker clustering algorithm in the maximum a posteriori adapted gaussian mixture model (gmm) mean supervector space. the algorithm can be viewed as an extension of the standard expectation maximization algorithm for fitting a mixture model to the data, which iterates between two steps - a sample re-assignment step (e-step) and a model re-estimation step (m-step) - until it converges. the directional scattering patterns of gmm mean supervectors suggest that we employ a mixture of von mises-fisher distributions in the model re-estimation step. in the sample re-assignment step, four sample-to-mixture assignment strategies, namely soft, hard, stochastic, and deterministic annealing assignments, are used. our experiments on the gale mandarin dataset show that the use of a mixture of von mises-fisher distributions as the underlying model yields significantly higher speaker clustering accuracies than the use of a mixture of gaussian distributions. it is further shown that deterministic annealing assignment outperforms soft assignment, that soft assignment is comparable to stochastic assignment, and that both soft and stochastic assignments outperform hard assignment.
a generalized family of parameter estimation techniques. the extended baum-welch (ebw) transformations is one of a variety of techniques to estimate parameters of gaussian mixture models. in this paper, we provide a theoretical framework for general parameter estimation and show the relationship between these different techniques. we introduce a general family of model parameter updates that generalizes a baum-welch (bw) recursive process to an arbitrary objective function of gaussian mixture models, and show how other common parameter estimation techniques belong to this family of model update rules. furthermore, we formulate the construction of an even more general family of update rules that has any specified value as a gradient steepness which belongs to the family of ebw gradient steepness, measuring how much an initial model is moved to an estimated updated model.
image inpainting via sparse representation. this paper proposes a novel patch-wise image inpainting algorithm using the image signal sparse representation over a redundant dictionary, which merits in both capabilities to deal with large holes and to preserve image details while taking less risk. different from all existing works, we consider the problem of image inpainting from the view point of sequential incomplete signal recovery under the assumption that the every image patch admits a sparse representation over a redundant dictionary. to ensure the visually plausibility and consistency constraints between the filled hole and the surroundings, we propose to construct a redundant signal dictionary by directly sampling from the intact source region of current image. then we sequentially compute the sparse representation for each incomplete patch at the boundary of the hole and recover it until the whole hole is filled. experimental results show that this approach can efficiently fill in the hole with visually plausible information, and take less risk to introduce unwanted objects or artifacts.
robust speech recognition based on structured modeling, irrelevant variability normalization and unsupervised online adaptation. we present a new approach to robust speech recognition based on structured modeling, irrelevant variability normalization (ivn) and unsupervised online adaptation (ola). in offline training stage, a set of generic hmms for basic speech units relevant to phonetic classification is trained along with several sets of feature transforms with different degrees of freedom by using a maximum likelihood (ml) ivn-based training strategy. in recognition stage, after a first-pass recognition, the most appropriate set of feature transforms is identified and adapted under ml criterion by using the unknown utterance itself, which is recognized again to achieve better performance by using the adapted feature transforms and the pre-trained generic hmms. the effectiveness of the proposed approach is confirmed by evaluation experiments on finnish aurora3 database.
learning in diffusion networks with an adaptive projected subgradient method. we present an algorithm that minimizes asymptotically a sequence of non-negative convex functions over diffusion networks. to account for possible node failures, position changes, and/or reachability problems (because of moving obstacles, jammers, etc), the algorithm can cope with dynamic networks and cost functions, a desirable feature for online algorithms where information arrives sequentially. many projection-based algorithms can be straightforwardly extended to diffusion networks with the proposed scheme. we use the acoustic source localization problem in sensor networks as an example of a possible application.
a harmonic bandwidth extension method for audio codecs. today's efficient audio codecs for low bitrate application scenarios often rely on parametric coding of the upper frequency band portion of a signal while the lower frequency band portion of the same is conveyed by a waveform preserving coding method. at the decoder, the upper frequency signal is approximated from the lower frequency data using the upper frequency band parameters. however, commonly used methods of bandwidth extension almost inevitably suffer from a sensation of unpleasant roughness, which is especially present for tonal music items. in this paper we expose the origin of the roughness and propose a bandwidth extension method, which does not introduce roughness into the reconstructed audio signal. a listening test demonstrates the advantage of the proposed method compared to a standard bandwidth extension.
unsupervisec cross-validation adaptation algorithms for improved adaptation performance. an unsupervised cross-validation adaptation algorithm and its variation are proposed that introduce the idea of cross-validation in the unsupervised batch-mode adaptation framework to improve the adaptation performance. the first algorithm is constructed on a general adaptation technique such as mllr and can be used in combination with any adaptation method. the second algorithm is a modified version of the first algorithm and works with lower computational cost by assuming mllr. these algorithms are extensions of our previously proposed cv training methods and are useful to suppress the negative effect of the conventional unsupervised batch-mode adaptation process that reinforces the errors included in automatic transcriptions. the proposed algorithms were evaluated in domain adaptation, speaker adaptation, and in their combination for large vocabulary spontaneous speech recognition. when the domain and speaker adaptations were combined using a read speech initial model, the relative word error rate reduction by the proposed method was 29% whereas the reduction by the conventional approach was 23%.
robust target localization in moving radar platform through semidefinite relaxation. accurate target localization is an important task in various commercial and military applications. one way to achieve this goal is to use the time-of-arrival (toa) or time-delay-of-arrival (tdoa) information observed at multiple distributed sensors. on the other hand, there is a great need to use moving sensors to form a radar platform with synthetic apertures. in this paper, we consider the problem of target localization based on the range information estimated from two-way time-of-flight (tw-tof) at multiple synthetic array locations, where the position of these synthetic array locations is subject to certain random errors. the nonconvex estimation problem is approximated by a convex optimization problem using the semidefinite relaxation (sdr) approach. simulation results show that the proposed estimator provides mean square position error performance close to the cramer-rao lower bound.
low-delay scheduling for grassmannian beamforming with a sinr constraint. we are presenting an algorithm for scheduling users in a single-cell broadcast scenario. the presented algorithm aims to minimize the number of transmissions that are necessary to serve all the users in the cell a single time, while the different users still fulfill a strict sinr constraint. depending on the individual channel characteristics, the algorithm adapts the number of users scheduled for transmission on the fly, and dynamically allocates the transmit power to the scheduled users. a high-performance and a low-complexity variant of the algorithm are presented and their performance is evaluated through simulations.
direction of arrival estimation using single tripole radio antenna. we consider the problem of estimating the direction of arrival (doa) of multiple waves incident on a single tripole sensor. using the physical properties of the electric and magnetic fields, we show that we can disambiguate the doa of multiple simultaneously incident waves using a set of time sampled 3d measurements from the single sensor. this is different from the traditional approach that uses arrays of antennas to estimate doa. we use the unitary matrix pencil method to estimate the frequencies of the waves, and use a least squares solver to estimate the amplitude and phase coefficients. we combine these to compute the doa and evaluate the approach using simulations. we show that the method is very effective at estimating doa for different numbers of incident waves, and different noise levels.
applications of complex augmented kernels to wind profile prediction. this paper combines complex signal processing with kernel methods for applications in wind prediction. specifically, we consider developing least squares kernel algorithms for both complex data and augmented complex data. the augmented complex kernel algorithms have advantages over complex kernel algorithms in both the areas of performance and complexity. use of kernels also allow implementation of nonlinear algorithms by working in the dual space. we apply our algorithm to wind series time prediction and show that our augmented complex algorithms outperform other complex least square algorithms.
improved 3d assisted pose-invariant face recognition. recent face recognition algorithm can achieve high accuracy when testing face samples are frontal. however, when face pose changes largely, the performance of existing methods drop drastically. in this paper, we propose an improved algorithm aiming at recognizing faces of different poses when each face class has only one frontal training sample. for each sample, a 3d face is constructed by using 3d morphable model (3dmm). the shape and texture parameters of 3dmm are recovering by fitting the model to the 2d face sample which is a non-linear optimization problem. the virtual faces of different views are generated from the 3dmm to assist face recognition. different from the conventional optimization energy function, proposed energy function takes not only image intensity but also shape constraint into account. in this paper, we locate 88 sparse points from the 2d face sample by automatic face fitting and use their correspondence in the 3d face as shape constraint. we experiment proposed method on the publicly available cmupie database which includes faces viewed from 11 different poses and the results show that proposed method is effective and the face recognition results towards pose-variant are promising.
multiuser transmit beamforming for mimo uplink with individual sinr targets. for multiuser multiple-input multiple-output (mimo) uplink communications where the signal-to-interference-plus-noise ratio (sinr) of the k-th user, denoted as sinrk, is expected to achieve the target value γk, we first consider the ideal scenario where multiuser channel matrices are perfectly known to every user and we solve the problem of maximizing mink(sinrk/γk) over all possible beamformers under individual transmit power constraints via alternating optimization strategies and the generalized eigenvalue problem (gevp) programming. then, we study a more realistic situation where only a few number of bits are allowed to feed back to users. we propose to integrate the genetic algorithm into the lloyd's vector quantization method to design the optimum codebook in terms of maximizing e(mink(sinrk/γk)) with expectation taken with respect to fading channels.
music emotion ranking. content-based retrieval has emerged as a promising approach to information access. in this paper, we propose an approach to music emotion ranking. specifically, we rank music in terms of arousal and valence and represent each song as a point in the 2d emotion space. novel ranking-based methods for annotation, learning, and evaluation of music emotion recognition are developed and tested on a moderately large-scale database composed of 1240 pop songs. results are provided to show the feasibility of the proposed approach.
analog compressed sensing. a traditional assumption underlying most data converters is that the signal should be sampled at a rate exceeding twice the highest frequency. practical signals often posses a sparse structure so that a large part of the bandwidth is not exploited. in this paper, we consider a framework for utilizing this sparsity in order to sample such analog signals at a low rate. by relying on results developed in the context of compressed sensing (cs) of finite-length vectors, we develop a general framework for low-rate sampling of signals in shift-invariant spaces. in contrast to the problems treated in the context of cs, here we explicitly consider sampling of analog signals for which no underlying finite-dimensional model exists.
biometric recognition by fusing palmprint and hand-geometry based on morphology. this paper presents a novel biometric recognition system fusing the palmprint and hand geometry of a human hand based on morphology. we utilize the image morphology and concept of voronoi diagram to cut the image of the front of the whole palm apart into several irregular blocks in accordance with the hand geometry. furthermore, statistic characteristics of the gray level in the blocks are employed as characteristic values. the experimental results show that the proposed system has an encouraging performance. the false acceptance rate (far) and false rejection rate (frr) are reduced down to 0.0035% and 5.7692%, respectively.
video coding using variable block-size spatially varying transforms. in our previous work, we introduced spatially varying transforms (svt) for video coding, where the location of the transform block within the macroblock is not fixed but varying. in this paper, we extend this concept and present a novel method, called variable block-size spatially varying transforms (vbsvt). vbsvt utilizes variable block-size transforms (vbt) in the svt framework, and is shown to be more preferable for coding prediction error with different characteristics than fixed block-size svt and also the standard methods that use fixed or adaptive block sizes at fixed spatial locations. in addition, vbsvt has similar decoding complexity with fixed block-size svt and lower decoding complexity compared to standard methods as only a portion of the prediction error needs to be decoded. experimental results show that, vbsvt achieves 4.1% gain over h.264/avc on average over a wide range of test set. gains become more significant at high quality levels and go up to 13.5%, which makes the proposed algorithm very suitable for future video coding solutions focusing on high fidelity applications.
audiovisual celebrity recognition in unconstrained web videos. the number of video clips available online is growing at a tremendous pace. conventionally, user-supplied metadata text, such as the title of the video and a set of keywords, has been the only source of indexing information for user-uploaded videos. automated extraction of video content for unconstrained and large scale video databases is a challenging and yet unsolved problem. in this paper, we present an audiovisual celebrity recognition system towards automatic tagging of unconstrained web videos. prior work on audiovisual person recognition relied on the fact that the person in the video is speaking and the features extracted from audio and visual domain are associated with each other throughout the video. however, this assumption is not valid on unconstrained web videos. proposed method finds the audiovisual mapping and hence improve upon the association assumption. considering the scale of the application, all pieces of the system are trained automatically without any human supervision. we present the results on 26,000 videos and show the effectiveness of the method per-celebrity basis.
interpolatory mercer kernel construction for kernel direct lda on face recognition. this paper proposes a novel methodology on mercer kernel construction using interpolatory strategy. based on a given symmetric and positive semi-definite matrix (gram matrix) and cholesky decomposition, it first constructs a nonlinear mapping φ, which is well-defined on the training data. this mapping is then extended to the whole input feature space by utilizing lagrange interpolatory basis functions. the kernel function constructed by inner product is proven to be a mercer kernel function. the self-constructed interpolatory mercer (im) kernel keeps the gram matrix unchanged on the training samples. to evaluate the performance of the proposed im kernel, a popular kernel direct linear discriminant analysis (kdda) method for face recognition is selected. comparing with rbf kernel based kdda method on two face databases, namely feret and cmu pie databases, the im kernel based kdda approach could increase the performance by around 20% on cmu pie database.
speech reinforcement based on partial masking effect. perceived quality of the speech signal deteriorates significantly in the presence of ambient noise. in this paper, based on the analysis that the partial masking effect is a main source of the quality degradation when interfering signals are present, we propose a novel approach to enhance the perceived quality of speech signal when the ambient noise cannot be directly controlled by reinforcing it so that it can be heard more clearly. to find a suitable reinforcement rule, the loudness perception model proposed by moore et al. [1] is adopted with the consideration on the prevention of the hearing damage. experimental results show that the perceived quality and intelligibility can be enhanced under various noise environments.
tensor-based channel estimation (tence) for two-way relaying with multiple antennas and spatial reuse. in this paper we study two-way relaying with amplify-and-forward (af) relays. in two-way relaying, two terminals exchange data with the help of an intermediate relay station. in order to enable mass deployment of these relays, we focus on very simple af relays that do not have any channel state information. hence, to separate the data streams in two-way relaying, both user terminals need reliable knowledge of all relevant channel parameters. we therefore propose the novel tensor-based channel estimation algorithm tence that provides both terminals with full knowledge of all channel parameters involved in the transmission. the solution is algebraic, i.e., it does not require any iterative procedures. moreover, tence is applicable to arbitrary antenna configurations. we also derive criteria for the design of the pilot symbols and the corresponding relay amplification matrices. computer simulations demonstrate the achievable channel estimation accuracy.
minimum ber beamforming in the rf domain for ofdm transmissions and linear receivers. in this paper, we study transmission schemes for a novel ofdm-based mimo system which performs adaptive signal combining in radio-frequency (rf). specifically, we consider the problem of selecting the linear precoder and the transmit and receive rf weights (or beamformers) for minimizing the bit error rate (ber) under the assumption of perfect channel knowledge and linear receivers. firstly, it is shown that the optimal precoder amounts to uniformly distribute the overall mean square error (mse) among the information symbols. secondly, we propose a gradient search algorithm to obtain the optimal pair of beamformers. interestingly, in the case of low signal to noise ratios (snr), the proposed beamforming criterion is equivalent to the maximization of the received snr. however, for moderate and high snrs, part of the received snr is sacrificed in order to improve the channel response of the worst subcarriers, which translates into significant advantages over other previously proposed approaches. finally, the performance of the proposed scheme is illustrated by means of some numerical examples.
robust localization in sensor networkswith iterative majorization techniques. self localization in sensor networks with measurements that include outliers is an important problem. e.g., distance measurements based on non-line-of-sight observations can be quite wrong. if not handled properly, such outliers can greatly influence the positioning accuracy. to achieve robustness we consider positioning with huber estimators. the huber cost function interpolates between the ℓ1 and the ℓ2 norms. the minimization of the huber cost function can be efficiently obtained via iterative majorization techniques, with the advantageous property of guaranteed convergence to a local minimum.
widely-linear recursive least-squares algorithm for adaptive beamforming. adaptive beamforming algorithms typically rely on a complex linear model between the sensor measurements and the desired signal output that does not enable the best performance from the data in some situations. in this paper, we present an extension of the well-known recursive least-squares algorithm for adaptive filters to widely-linear complex-valued signal and system modeling. the widely-linear rls algorithm exploits a structured covariance matrix update that maintains information about the non-circularity of the input data to solve the widely-linear least-squares task at each snapshot. in addition, the wl-rls algorithm can easily be switched between conventional and widely-linear complex modeling as needed. application of the method to adaptive beamforming of mixed bpsk and qpsk signal transmissions shows that the system can extract all of the transmitted signal outputs in certain overloaded scenarios, and it performs up to 3db better than the conventional rls beamformer when the array is not overloaded.
on combinations of cma equalizers. we extend the affine combination of one fast and one slow least mean-square (lms) filter to blind equalization, considering the combination of two constant modulus algorithms (cma). we analyze the proposed combination in stationary and nonstationary environments verifying that there are situations where the absence of the restriction on the mixing parameter can be advantageous for the combination. furthermore, we propose a combination of two cmas with different initializations. preliminary simulations show that this scheme can avoid local minima and eventually can present a faster convergence rate than that of its components.
low-complexity bandwidth extension in mdct domain for low-bitrate speech coding. we propose a low-complexity bandwidth extension (bwe) method operating in the modified discrete cosine transform (mdct) domain to reduce the bitrate of wideband and super-wideband speech codecs. the proposed method generates a high-frequency signal by copying the mdct spectrum from the low frequency part, and then adjusts tonality to improve the subjective quality of the generated high-frequency signal. in combination with an mdct-based transform codec, it requires only 64.9% of the computational complexity of mpeg-4 spectral band replication (sbr). it also achieves subjective quality better than sbr for many speech samples.
mobhrg: fast k-nearest-neighbor search by overlap reduction of hyperspherical regions. we propose a minimum overlap based hyperspherical region graph indexing structure to achieve fast similarity-based queries for both low and high dimensional datasets. specifically, we reduce the region overlaps in the graph construction phase by incrementally dividing each saturated hyperspherical region and removing the longest edge of a minimum spanning tree representation of the internal objects. this overlap reduction scheme creates more separated regions, so fewer regions as potential paths are traversed when a query is issued. we also introduce a k-nearest-neighbor search scheme by automatically deciding the search radius to return the required number of nearest neighbors. our extensive experimental results show the effectiveness of the proposed indexing structure compared with other tree and graph based indexing structures.
comparative evaluation of pedestrian detection methods for mobile bus surveillance. we present a comparative evaluation of the state-of-art algorithms for detecting pedestrians in low frame rate and low resolution footage acquired by mobile sensors. four approaches are compared: a) the histogram of oriented gradient (hog) approach [1]; b) a new histogram feature that is formed by the weighted sum of both the gradient magnitude and the filter responses from a set of elongated gaussian filters [2] corresponding to the quantised orientation, called histogram of oriented gradient banks (hogb) approach; c) the codebook based hog feature with branch-and-bound (efficient subwindow search) algorithm [3] and; d) the codebook based hogb approach. results show that the hog based detector achieves the highest performance in terms of the true positive detection, the hogb approach has the lowest false positives whilst maintaining a comparable true positive rate to the hog, and the codebook approaches allow computationally efficient detection.
blind adaptive beamforming for wideband circular arrays. an approach for blind adaptive wideband beamforming is proposed based on a uniform circular array. the received array signals are first transformed into different phase modes and each phase mode output is then processed by a filter to achieve a frequency independent response. as a result, a set of instantaneous mixtures of the original source signals is obtained and the original wideband beamforming problem can be readily solved using the standard instantaneous bss algorithms and the original source signals can be recovered one by one or simultaneously, depending on the specific requirement.
bayesian pursuit algorithm for sparse representation. in this paper, we propose a bayesian pursuit algorithm for sparse representation. it uses both the simplicity of the pursuit algorithms and optimal bayesian framework to determine active atoms in sparse representation of a signal. we show that using bayesian hypothesis testing to determine the active atoms from the correlations leads to an efficient activity measure. simulation results show that our suggested algorithm has better performance among the algorithms which have been implemented in our simulations in most of the cases.
an efficient and robust method for detecting copy-move forgery. copy-move forgery is a specific type of image tampering, where a part of the image is copied and pasted on another part of the same image. in this paper, we propose a new approach for detecting copy-move forgery in digital images, which is considerably more robust to lossy compression, scaling and rotation type of manipulations. also, to improve the computational complexity in detecting the duplicated image regions, we propose to use the notion of counting bloom filters as an alternative to lexicographic sorting, which is a common component of most of the proposed copy-move forgery detection schemes. our experimental results show that the proposed features can detect duplicated region in the images very accurately, even when the copied region was undergone severe image manipulations. in addition, it is observed that use of counting bloom filters offers a considerable improvement in time efficiency at the expense of a slight reduction in the robustness.
multiband perceptual modulation analysis, processing and synthesis of audio signals. the decomposition of audio signals into perceptually meaningful multiband modulation components opens up new possibilities for advanced signal processing. the signal adaptive analysis approach proposed in this paper will be shown to provide a powerful handle on the signal's perceptual properties: pitch, timbre or roughness can be manipulated straight forward. additionally a synthesis method is specified providing high subjective perceptual quality. furthermore, as an application example, a novel audio processing technique is proposed which changes the key mode of a given piece of music e.g. from major to minor key or vice versa.
social correlates of turn-taking behavior. the goal of this research is to infer traits about groups of people from their turn-taking behavior in natural conversation. these traits are latent attributes in a social network, whose relative frequencies we estimate from content-derived metadata. our approach is to train statistical models of turn-taking behavior using automatic labels of speech activity, and measure the association of these models with socially correlated traits. we experimentally evaluate these ideas using the switchboard-1 speech corpus, which provides speech content and metadata associated with each speaker, such as gender, age and education, as well as inferred social correlates such as willingness to participate and initiate. we show that population proportions of these socially correlated externals can be predicted with a root meansquared error of approximately 0.1 across all mixture proportions.
effect of pronounciations on oov queries in spoken term detection. the spoken term detection (std) task aims to return relevant segments from a spoken archive that contain the query terms whether or not they are in the system vocabulary. this paper focuses on pronunciation modeling for out-of-vocabulary (oov) terms which frequently occur in std queries. the std system described in this paper indexes word-level and sub-word level lattices or confusion networks produced by an lvcsr system using weighted finite state transducers (wfst).we investigate the inclusion of n-best pronunciation variants for oov terms (obtained from letter-to-sound rules) into the search and present the results obtained by indexing confusion networks as well as lattices. the following observations are worth mentioning: phone indexes generated from sub-words represent oovs well and too many variants for the oov terms degrade performance if pronunciations are not weighted.
optimal and suboptimal micro-doppler estimation schemes using carrier diverse doppler radars. carrier diverse radars employing two different frequencies, termed as dual-frequency radars, prove effective in determining the target range in urban sensing and through-the-wall applications. in this paper, we derive the maximum likelihood (ml) estimator for the dual frequency radar returns for a micro-doppler motion profile, which is commonly exhibited by indoor moving targets. unlike linear models, the respective ml estimator does not have a closed form. we solve the ml estimator for dual frequency radar operations, using iterative reweighted least squares (irls). the ml-irls algorithm is applied to experimental radar returns for estimating the motion parameters of indoor targets.
an analysis of the map seeking circuit and monte carlo extensions. the map seeking circuit (msc) has been suggested to address the inverse problem of transformation discovery as found in signal processing, vision, inverse kinematics and many other natural tasks. according to this idea, a parallel search in the transformation space of a high dimensional problem can be decomposed into parts efficiently using the ordering property of superpositions. deterministic formulations of the circuit have been suggested. here, we provide a probabilistic interpretation of the architecture whereby the superpositions of the circuit are seen as a series of marginalisations over parameters of the transform. based on this, we interpret the weights of the msc as importance weights. the latter suggests the incorporation of monte-carlo approaches in the msc, providing improved resolution of parameter estimates within resource constrained implementations. as a final contribution, we model mixed serial/parallel search strategies of biological vision to reduce the problem of collusions, a common problem in the standard msc approach.
polyphonic musical instrument recognition based on a dynamic model of the spectral envelope. we propose a new method for detecting the musical instruments that are present in single-channel mixtures. such a task is of interest for audio and multimedia content analysis and indexing applications. the approach is based on grouping sinusoidal trajectories according to common onsets, and comparing each group's overall amplitude evolution with a set of pre-trained probabilistic templates describing the temporal evolution of the spectral envelopes of a given set of instruments. classification is based on either an euclidean or a probabilistic definition of timbral similarity, both of which are compared with respect to detection accuracy.
two-dimensional phase unwrapping using semidefinite relaxation. in many imaging applications, the continuous phase information of the measured signal is wrapped to a single period of 2π, resulting in phase ambiguity. in this paper we consider the two-dimensional phase unwrapping problem and propose a maximum a posteriori (map) framework for estimating the true phase values based on the wrapped phase data. in particular, assuming a joint gaussian prior on the original phase image, we show that the map formulation leads to a binary quadratic minimization problem. the latter can be efficiently solved by semidefinite relaxation (sdr). we compare the performances of our proposed method with the existing l1/l2-norm minimization approaches. the numerical results demonstrate that the sdr approach significantly outperforms the existing phase unwrapping methods.
an information geometric approach to supervised dimensionality reduction. due to the curse of dimensionality, high-dimensional data is often pre-processed with some form of dimensionality reduction for the classification task. many common methods of supervised dimensionality reduction have focused on separating and collapsing the data near the class centroids. these methods often make assumptions on the distributions of the data classes - namely gaussianity - which can lead to ad-hoc and sub-optimal implementation. in this paper we present a method of supervised dimensionality reduction which takes an information-geometric approach by maximizing the between class information distances. this is shown to have direct relation to the chernoff and bhattacharya performance bounds for classification error. we illustrate our methods on real data and compare to several existing methods.
learning the basic units in american sign language using discriminative segmental feature selection. the natural language for most deaf signers in the united states is american sign language (asl). asl has internal structure like spoken languages, and asl linguists have introduced several phonemic models. the study of asl phonemes is not only interesting to linguists, but also useful for scalability in recognition by machines. since machine perception is different than human perception, this paper learns the basic units for asl directly from data. comparing with previous studies, our approach computes a set of data-driven units (fenemes) discriminatively from the results of segmental feature selection. the learning iterates the following two steps: first apply discriminative feature selection segmentally to the signs, and then tie the most similar temporal segments to re-train. intuitively, the sign parts indistinguishable to machines are merged to form basic units, which we call asl fenemes. experiments on publicly available asl recognition data show that the extracted data-driven fenemes are meaningful, and recognition using those fenemes achieves improved accuracy at reduced model complexity.
spoken language understanding from unaligned data using discriminative classification models. while data-driven methods for spoken language understanding reduce maintenance and portability costs compared with handcrafted parsers, the collection of word-level semantic annotations for training remains a time-consuming task. a recent line of research has focused on building generative models from unaligned semantic representations, using expectation-maximisation techniques to align semantic concepts. this paper presents an efficient, simple technique that parses a semantic tree by recursively calling discriminative semantic classification models. results show that it outperforms methods based on the hidden vector state model and markov logic networks, while performance is close to more complex grammar induction techniques. we also show that our method is robust to speech recognition errors, by improving over a handcrafted parser previously used for dialogue data collection.
two-directional two-dimensional discriminant locality preserving projections for image recognition. we propose in this paper an improved manifold learning method called two-directional two-dimensional discriminant locality preserving projections, (2d)2-dlpp, for efficient image recognition. as the existing method of two-dimensional discriminant locality preserving projections (2d-dlpp) mainly relies upon the local structure information in the rows of images, we first derive an alternative 2d-dlpp algorithm that makes use of the information in the columns. exploiting the local structure and discriminant information in both the rows and the columns, we develop the (2d)2-dlpp method for efficient image feature extraction and dimensionality reduction. experimental results on two benchmark image datasets show the effectiveness of the proposed method.
hierarchical fusion of color and depth information at partition level by cooperative region merging. a high level scheme for information fusion to create hierarchical region-based image representations based on a region merging process is presented. the strategy is based on an iterative evolution where the different merging criteria work independently and cooperate at the partition level to obtain a further consensus that increases the reliability of the resulting partitions. this cooperative scheme is applied to the creation of hierarchical region-based representations of the image based on color and depth information. the proposed technique is compared with approaches using only one source of information or linear combinations of both, in datasets with ground truth as well as estimated disparity information.
automatic evaluation of spoken english fluency. this paper presents a method to automatically quantify the spoken english fluency skills of speakers. the focus of this work is to automatically compute a numeric score of spoken fluency that is correlated with the numerical score the human assessors would assign. the proposed method combines several novel prosodic and lexical features to compute the fluency score. it is shown that the prosodic and the lexical features provide complementary information for fluency evaluation. extensive evaluation on human-labeled utterances shows that the proposed technique exhibits similar trends in performance and confusions as shown by human assessors. the proposed technique leads to 84.2% classification accuracy when the two extreme classes of fluency are considered.
doa estimation of quasi-stationary signals via khatri-rao subspace. this paper addresses the problem of direction-of-arrival (doa) estimation of quasi-stationary signals, which finds applications in array processing of speech and audio. by studying the subspace structures of the local second-order statistics (soss) of quasi-stationary signals, we develop a khatri-rao (kr) subspace approach that has two notable advantages. first, the approach can operate in underdetermined cases. it is proven that if n is the number of sensors in the array, then the proposed approach can identify up to 2n − 2 source doas in an unambiguous fashion. second, the approach can handle the problem of unknown noise covariance. essentially, the kr subspace formulation is found to provide a simple and effective way of annihilating the (unknown) noise covariance from the observed signal soss. simulation results, with an emphasis on underdetermined and colored-noise cases, illustrate that the kr subspace approach provides promising mean square estimation error performance.
fast bayesian compressive sensing using laplace priors. in this paper we model the components of the compressive sensing (cs) problem using the bayesian framework by utilizing a hierarchical form of the laplace prior to model sparsity of the unknown signal. this signal prior includes some of the existing models as special cases and achieves a high degree of sparsity. we develop a constructive (greedy) algorithm resulting from this formulation where necessary parameters are estimated solely from the observation and therefore no user-intervention is needed. we provide experimental results with synthetic 1d signals and images, and compare with the state-of-the-art cs reconstruction algorithms demonstrating the superior performance of the proposed approach.
sampling signals with finite rate of innovation in the presence of noise. recently, it has been shown that it is possible to sample non-bandlimited signals that possess a limited number of degrees of freedom and uniquely reconstruct them from a finite number of uniform samples. these signals include, amongst others, streams of diracs. in this paper, we investigate the problem of estimating the innovation parameters of a stream of diracs from its noisy samples taken with polynomial or exponential reproducing kernels. for the one-dirac case, we provide exact expressions for the cramér- rao bounds of this estimation problem. furthermore, we propose methods to reconstruct the location of a single dirac that reach the optimal performance given by the unbiased cramér-rao bounds down to noise levels of 5db.
a trust region based optimization for maximum mutual information estimation of hmms in speech recognition. in this paper, we present a new optimization method for mmie-based discriminative training of hmms in speech recognition. in our method, the mmie training of gaussian mixture hmms is formulated as a so-called trust region problem, where a quadratic objective function is minimized under a spherical constraint, so that an efficient global optimization method for the trust region problem can be used to solve the mmie training problem of hmms. experimental results on the wsj0 nov'92 evaluation task demonstrate that the trust region based optimization significantly outperforms the conventional ebwmethod in terms of optimization convergence behavior as well as speech recognition performance. it has been observed that the trust region method achieves up to 23.3% relative recognition error reduction over a well-trained mle system while the ebw method gives only 13.3% relative error reduction.
separable pca for image classification. as an alternative to standard pca, matrix-based image dimensionality reduction methods have recently been proposed and have gained attention due to reported computational efficiency and robust performance in classification. we unify all of these methods through one concept: separable principle component analysis (spca).we show that the proposed matrix methods are either equivalent to, special cases of, or approximations to spca. we include performance comparisons of the methods on two face data sets and a handwritten digit data set. the empirical results indicate that two existing methods, bd-pca and its variant nglram, are very good, efficiently computable, approximate solutions to practical spca problems.
an efficient mispronounciation detction method using glds-svm and formant enhanced features. mispronunciation detection is an important component in computer assisted language learning (call) system. in this work, we introduce an efficient glds-svm based detection method, which is successfully used in language and speaker identification systems, and combine it with traditional methods. the main ideas include: extended mfcc features with normalized formant trajectory information, and then propose a novel multi-model strategy for model training to make full use of samples and solve the problem of data unbalance, finally combine glds-svm method with ubm-gmm system to further improve the performance. experiments show that glds-svm is highly efficient than traditional rbf-svm, and the fused system can achieve a significant relative improvement of 17.5% in eer reduction, compared with the baseline ubm-gmm system.
identification of neurons participating in cell assemblies. chances to detect assembly activity are expected to increase if the spiking activities of large numbers of neurons are recorded simultaneously. although such massively parallel recordings are now becoming available, methods able to analyze such data for spike correlation are still rare, because it is often infeasible to extend methods developed for smaller data sets due to a combinatorial explosion. by evaluating pattern complexity distributions the existence of correlated groups can be detected, but their member neurons cannot be identified. in this contribution, we present approaches to actually identify the individual neurons involved in assemblies. our results may complement other methods and also provide the opportunity for a reduction of data sets to the “relevant” neurons, thus allowing us to carry out a refined analysis of the detailed correlation structure due to reduced computation time.
a variational framework for simultaneous motion and disparity estimation in a sequence of stereo images. in this paper, we present a variational framework for joint disparity and motion estimation in a sequence of stereo images. the problem involves the estimation of four dense fields: two motion fields and two disparity fields. in order to reduce computational complexity and improve estimation accuracy, the two motion fields, for the left and right sequences, and the disparity field of the current stereo pair are jointly estimated, using the stereo-motion consistency constraint. in the proposed variational framework, the joint estimation problem is formulated as a convex programming problem in which a convex objective function is minimized under specific convex constraints. this minimization is achieved using an efficient parallel block-iterative algorithm. experimental results involving real stereo sequences indicate the feasibility and robustness of our approach.
syntactically-informed models for comma prediction. providing punctuation in speech transcripts not only improves readability, but it also helps downstream text processing such as information extraction or machine translation. in this paper, we improve by 7% the accuracy of comma prediction in english broadcast news by introducing syntactic features inspired by the role of commas as described in linguistics studies. we conduct an analysis of the impact of those features on other subsets of features (prosody, words…) when combined through crfs. the syntactic cues can help characterizing large syntactic patterns such as appositions and lists which are not necessarily marked by prosody.
efficient semidefinite relaxation for energy-based source localization in sensor networks. recently, energy-based localization using acoustic energy measurements has received much attention in wireless sensor networks. since the objective function of the energy-based maximum likelihood (ml) localization is non-convex, the global solutions are hardly obtained without good initial estimates. in this paper, we relax this non-convex problem as a convex semidefinite programming (sdp), based on which a good estimate can be obtained and be improved by a procedure called randomization. simulation results show that the proposed method is effective and outperforms the existing methods.
rate efficient remote video file synchronization. video file synchronization between remote users is an important task in many applications. re-transmission of a video that has been only slightly modified is expensive, wasteful and avoidable. we propose a scheme that automatically detects and sends only modified content according to some user defined distortion constraint to enable rate savings under a wide range of video edits. through the use of a low-rate hierarchical hashing scheme, we can detect modifications with some spatial granularity. we also apply distributed source coding techniques to exploit correlation between remote copies for a further rate rebate. experimental results show that the proposed approach achieves up to 7× rate reduction when compared to re-transmitting.
incremental predictive and adaptive noise compensation. model compensation schemes are a powerful approach to handling mismatches between training and testing conditions. normally these schemes are run in a batch adaptation mode, re-recognising the utterance used to estimate the noise model parameters. for many applications this introduces unacceptable latency. this paper examines three forms of incremental mode model-based compensation: vector taylor series; joint uncertainty decoding; and predictive cmllr. these predictive schemes can also be combined with adaptive schemes such as cmllr. by combining the approaches, weaknesses of each can be addressed. the performance is evaluated on in-car recorded data, where the combined incremental scheme shows gains over either individually.
classification of electroencephalography (eeg) signals for different mental activities using kullback leibler (kl) divergence. automatic classification of electroencephalography (eeg) signals, for different type of mental activities, is an active area of research and has many applications such as brain computer interface (bci) and medical diagnoses. we introduce a simple yet effective way to use kullback-leibler (kl) divergence in the classification of raw eeg signals. we show that k-nearest neighbor (k-nn) algorithm with kl divergence as the distance measure, when used using our feature vectors, gives competitive classification accuracy and consistently outperforms the more commonly used euclidean k-nn. we also develop and demonstrate the use of a kl-based kernel to classify eeg data using support vector machines (svms). our kl-distance based kernel compares favorably to other well established kernels such as linear and radial basis function (rbf) kernel. the eeg data, used in our experiments for classification, was recorded while the subject performed 5 different mental activities such as math problem solving, letter composing, 3-d block rotation, counting and resting (baseline). we present classification results for this data set that are obtained by using raw eeg data with no explicit artifact removal in the pre-processing steps.
image recolorization for the colorblind. in this paper, we propose a new re-coloring algorithm to enhance the accessibility for the color vision deficient (or colorblind). compared to people with normal color vision, people with color vision deficiency (cvd) have difficulty in distinguishing between certain combinations of colors. this may hinder visual communication owing to the increasing use of colors in recent years. to address this problem, we re-color the image to preserve visual detail when perceived by people with cvd. we first extract the representing colors in an image. then we find the optimal mapping to maintain the contrast between each pair of these representing colors. the proposed algorithm is image content dependent and completely automatic. experimental results on natural images are illustrated to demonstrate the effectiveness of the proposed re-coloring algorithm.
data-driven voice soruce waveform modelling. this paper presents a data-driven approach to the modelling of voice source waveforms. the voice source is a signal that is estimated by inverse-filtering speech signals with an estimate of the vocal tract filter. it is used in speech analysis, synthesis, recognition and coding to decompose a speech signal into its source and vocal tract filter components. existing approaches parameterize the voice source signal with physically- or mathematically-motivated models. though the models are well-defined, estimation of their parameters is not well understood and few are capable of reproducing the large variety of voice source waveforms. here we present a data-driven approach to classify types of voice source waveforms based upon their melfrequency cepstrum coefficients with gaussian mixture modelling. a set of “prototype” waveform classes is derived from a weighted average of voice source cycles from real data. an unknown speech signal is then decomposed into its prototype components and resynthesized. results indicate that with sixteen voice source classes, low resynthesis errors can be achieved.
sound field reproduction around a scatterer in reverberation. we devise a method for sound field reproduction (sfr) around a solid object in a reverberant room. until now, work have focussed on reproducing sound in an empty listening space and, for the most part, in non-reverberant environments. however, in a reverberant, room as soon as a listener steps into the space he alters his acoustic environment, generating a sound component which is body-scattered and successively reverberated throughout the room. building on the model of the sound field around a solid sphere in free space, we extend to reproduction around a human head in a reverberant room. in doing so, we show the relationship between the pressure matching and mode matching approaches of sfr.
using speech transformation to increase speech intelligibility for the hearing- and speaking-impaired. we present two speech transformation approaches designed to increase the intelligibility of speech. the first approach is used in the context of increasing the intelligibility of conversationally spoken speech for hearing-impaired listeners. an initial experiment showed that a relatively simple mapping function can map spectral features of conversationally spoken speech closer to context-equivalent spectral features of clearly spoken speech. the second approach aims to increase the intelligibility of speaking-impaired individuals by the general population. results of listening tests indicated that although an intelligibility increase was not achieved, listeners preferred the transformed speech of the proposed system over that of an alternative system.
compressive confocal microscopy. in this paper, a new framework for confocal microscopy based on the novel theory of compressive sensing is proposed. unlike wide field microscopy or conventional parallel beam confocal imaging systems that use charge-coupled devices (ccd) as acquisition devices in addition to complex mechanical scanning system, the proposed compressive confocal microscopy is a kind of parallel beam confocal imaging system which exploits the rich theory of compressive sensing by using a single pixel detector and a digital micromirror device (dmd) to capture linear projections of the in-focus image. with the proposed system, confocal imaging of high optical sectioning ability can be achieved at sub-nyquist sampling rates. theoretical analysis, simulations and experimental results are shown to demonstrate the characteristics and potential of the proposed approach.
statistical analysis of amplitude modulation in speech signals using an am-fm model. several studies have been dedicated to the analysis and modeling of am-fm modulations in speech and different algorithms have been proposed for the exploitation of modulations in speech applications. this paper details a statistical analysis of amplitude modulations using a multi-band am-fm analysis framework. the aim of this study is to analyze the phonetic- and speaker-dependency of modulations in the amplitude envelope of speech resonances. the analysis focuses on the dependence of such modulations on acoustic features such as, fundamental frequency, formant proximity, phone identity, as well as, speaker identity and contextual features. the results show that the amplitude modulation index of a speech resonance is mainly a function of the speaker-s average fundamental frequency, the phone identity, and the proximity between neighboring formant resonances. the results are especially relevant for speech and speaker recognition application employing modulation features.
detecting lsb matching by characterizing the amplitude of histogram. in this paper, we present an improved method for detecting lsb matching steganography in gray-scale image. our improvements focus on three aspects: (1) instead of using the amplitude of local extrema of the image's histogram in the previous work, we turn to considering the sum of the amplitude of each point in the histogram; (2) incorporating the calibration (downsample) technique with the current method; (3) the sum/difference image (which is defined as the sum or difference of two adjacent pixels in the original image) is taken into consideration to provide additional statistical features. extensive experimental results show that the novel steganalyzer out-performs the previous ones.
cross-lingual speech recognition under runtime resource constraints. this paper proposes and compares four cross-lingual and bilingual automatic speech recognition techniques under the constraint that only the acoustic model (am) of the native language is used at runtime. the first three techniques fall into the category of lexicon conversion where each phoneme sequence (phs) in the foreign language (fl) lexicon is mapped into the native language (nl) phoneme sequence. the first technique determines the phs mapping through the international phonetic alphabet (ipa) features; the second and third techniques are data-driven. they determine the mapping by converting the phs into corresponding context-independent and context-dependent hidden markov models (hmms) respectively and searching for the nl phs with the least kullback-leibler divergence (kld) between the hmms. the fourth technique falls into the category of am merging where the fl's am is merged into the nl's am by mapping each senone in the fl's am to the senone in the nl's am with the minimum kld. we discuss the strengths and limitations of each technique developed, report empirical evaluation results on recognizing english utterances with a korean recognizer, and demonstrate the high correlation between the average kld and the word error rate (wer). the results show that the am merging technique performs the best, achieving 60% relative wer reduction over the ipa-based technique.
learning on demand - course lecture distillation by information extraction and semantic structuring for spoken documents. this paper presents a new approach of organizing the course lectures (as spoken documents) for efficient learning on demand by the users. by the properly matching the course lectrues with the slides used, we divide the course lectures into hierarchical “major segments” with variable length based on the tiopics discussed. key term extraction, hierarhical summarization and semantic structuring are then performed over these “major segments”. a key term graph is also constructed, based on which the various major segments of the course can be linked. in this way, the user can ask questions to the system, and develop his own road map of learning the knowledge he needs considring his available time and his background knowledge, based on the semantic structure provided by the system. a preliminary prototype system has been successfully developed with encouraging initial test results.
improved speaker diarization system for meetings. in this paper, we investigate new approaches to improve speech activity detection, speaker segmentation and speaker clustering. the main idea behind them is to deal with the problem of speaker diarization for meetings where error rates are relatively high. in opposition to existing methods, a new iterative scheme is proposed considering those three tasks as only one problem. new bidirectional source segmentation is proposed based on the glr/bic method. the well-known bic clustering is also reviewed and a new unsupervised post-processing is added to increase clusters purity. those new proposals applied on meeting data show a relative improvement of about 40% compared to a standard speaker diarization system.
improving mispronunciation detection using machine learning. in this paper, we investigate the problem of mispronunciation detection by considering the influence of speaker and syllables. machine learning techniques are used to make our method more convenient and flexible for new features, such as syllables normalization. the experimental results on our database, consisting of 9898 syllables pronounced by 100 speakers, show the effectiveness of our method by reducing the average false acceptance rate (far) by 42.5% using data set generated by model without adaptation to observation set and reducing average far by 32.5% using data set generated by model with adaptation to observation set.
preface. there are times when those who have attended a symposium as well as those who purchase the proceedings afterwards, wish to communicate directly with the author or authors of a specific paper or even a session chairman. therefore, for your convenience we have included the following list of names and addresses.
editorial. from a mere technical point of view, the tv/video screen comes alive by a controlled beam of electrons in the cathode-ray tube. for "energie!" an uncontrolled high-voltage discharge of approximately 30.000 volts exposes photographic paper, which is then arranged in time to create new visual systems of electron organization. even though the result is abstract, it tells a universal story older than the world itself.
data association and occlusion handling for vision-based people tracking by mobile robots. this paper presents an approach for tracking multiple persons on a mobile robot with a combination of colour and thermal vision sensors, using several new techniques. first, an adaptive colour model is incorporated into the measurement model of the tracker. second, a new approach for detecting occlusions is introduced, using a machine learning classifier for pairwise comparison of persons (classifying which one is in front of the other). third, explicit occlusion handling is incorporated into the tracker. the paper presents a comprehensive, quantitative evaluation of the whole system and its different components using several real world data sets.
towards modelling complex robot training tasks through system identification. previous research has shown that sensor-motor tasks in mobile robotics applications can be modelled automatically, using narmax system identification, where the sensory perception of the robot is mapped to the desired motor commands using non-linear polynomial functions, resulting in a tight coupling between sensing and acting - the robot responds directly to the sensor stimuli without having internal states or memory. however, competences such as for instance sequences of actions, where actions depend on each other, require memory and thus a representation of state. in these cases a simple direct link between sensory perception and the motor commands may not be enough to accomplish the desired tasks. the contribution of this paper to knowledge is to show how fundamental, simple narmax models of behaviour can be used in a bootstrapping process to generate complex behaviours that were so far beyond reach. we argue that as the complexity of the task increases, it is important to estimate the current state of the robot and integrate this information into the system identification process. to achieve this we propose a novel method which relates distinctive locations in the environment to the state of the robot, using an unsupervised clustering algorithm. once we estimate the current state of the robot accurately, we combine the state information with the perception of the robot through a bootstrapping method to generate more complex robot tasks: we obtain a polynomial model which models the complex task as a function of predefined low level sensor-motor controllers and raw sensory data. the proposed method has been used to teach scitos g5 mobile robots a number of complex tasks, such as advanced obstacle avoidance, or complex route learning.
6d scan registration using depth-interpolated local image features. this paper describes a novel registration approach that is based on a combination of visual and 3d range information. to identify correspondences, local visual features obtained from images of a standard color camera are compared and the depth of matching features (and their position covariance) is determined from the range measurements of a 3d laser scanner. the matched depth-interpolated image features allow one to apply registration with known correspondences. we compare several icp variants in this paper and suggest an extension that considers the spatial distance between matching features to eliminate false correspondences. experimental results are presented in both outdoor and indoor environments. in addition to pair-wise registration, we also propose a global registration method that registers all scan poses simultaneously.
novel solutions for global urban localization. in this study, novel solutions to global urban localization problem is proposed and examined rigorously. classical approaches including particle filter, mixture of gaussians, as well as novel solutions like viterbi algorithm and differential evolution are evaluated. the contribution of this paper is twofold: the viterbi algorithm is extended by exploiting the structure of the problem at hand that is the states are partially connected temporally. differential evolution is modified by taking into account the covariance matrix of states. thus states encoded in genes are only allowed to interact locally within the region described by covariance matrix. this prevents the differential evolution from getting trapped into false maxima in the early stages of optimization. finally, it is demonstrated with extensive experiments that solution of global urban localization problem is possible.
sift, surf & seasons: appearance-based long-term localization in outdoor environments. in this paper, we address the problem of outdoor, appearance-based topological localization, particularly over long periods of time where seasonal changes alter the appearance of the environment. we investigate a straightforward method that relies on local image features to compare single-image pairs. we first look into which of the dominating image feature algorithms, sift or the more recent surf, that is most suitable for this task. we then fine-tune our localization algorithm in terms of accuracy, and also introduce the epipolar constraint to further improve the result. the final localization algorithm is applied on multiple data sets, each consisting of a large number of panoramic images, which have been acquired over a period of nine months with large seasonal changes. the final localization rate in the single-image matching, cross-seasonal case is between 80% to 95%.
structural synthesis of 5 dofs 3t2r parallel manipulators with prismatic actuators on the base. a method is presented to synthesize 5 degrees of freedom (dofs) of 3 translational and 2 rotational (3t2r) parallel kinematic structures. this method is based on the theory of linear transformation and geometrical analysis. central to this method is a set of novel 5 dofs 3t2r parallel mechanisms (pms). based on the legs configuration, the generated mechanisms are classified. moreover, the promising mechanisms of each class are introduced with respect to some criteria, i.e.: (a) degree of coupling between the actuators and degrees of freedom; (b) easy kinematics and control command; (c) easy construction (or low cost construction); and, (d) manufacturability. with reference to these criteria, some discussions are given on the promising mechanisms. finally, to demonstrate the role of legs configuration in relation to the characteristics of a manipulator, the kinematic analysis of two of the introduced mechanisms is compared.
planar bipedal locomotion control based on state discretization. in this paper, a new control method for a planar bipedal robot, which we call graph-based model predictive control, is proposed. this method makes use of a directed graph constructed on the state space of the robot. the vertices of the directed graph are called waypoints, and they serve as intermediate target states to compose complex motions of the robot. by simply tracing the directed edges of the graph, one can achieve model predictive control over the waypoint set. such a directed graph is pre-designed and stored into the controller's memory to significantly reduce the computational effort required in real time. in addition, by constructing multiple directed graphs based on different objective functions, one can design multiple motions and switching trajectories among them in a uniform way. the proposed method is applied to variable-speed walking control of a bipedal walker on a two-dimensional plane, and its effectiveness is verified by numerical simulations.
human-robot communication for collaborative decision making - a probabilistic approach. humans and robots need to exchange information if the objective is to achieve a task collaboratively. two questions are considered in this paper: what and when to communicate. to answer these questions, we developed a human-robot communication framework which makes use of common probabilistic robotics representations. the data stored in the representation determines what to communicate, and probabilistic inference mechanisms determine when to communicate. one application domain of the framework is collaborative human-robot decision making: robots use decision theory to select actions based on perceptual information gathered from their sensors and human operators. in this paper, operators are regarded as remotely located, valuable information sources which need to be managed carefully. robots decide when to query operators using value-of-information theory, i.e. humans are only queried if the expected benefit of their observation exceeds the cost of obtaining it. this can be seen as a mechanism for adjustable autonomy whereby adjustments are triggered at run-time based on the uncertainty in the robots' beliefs related to their task. this semi-autonomous system is demonstrated using a navigation task and evaluated by a user study. participants navigated a robot in simulation using the proposed system and via classical teleoperation. results show that our system has a number of advantages over teleoperation with respect to performance, operator workload, usability, and the users' perception of the robot. we also show that despite these advantages, teleoperation may still be a preferable driving mode depending on the mission priorities.
online topological map building and qualitative localization in large-scale environment. a novel topological map representation as well as an online map construction approach is presented in this paper. by virtue of the topological map whose nodes are represented with the free beams of the laser range finder together with the visual scale-invariant features, the mobile robot can autonomously navigate in unknown, large-scale and indoor environments. different from the traditional navigation methods that rely on precise global localization, the robot locates itself qualitatively by location recognition rather than calculating its global pose in the world reference frame. by combining the reactive navigational method, beam curvature method (bcm), with the topological map, a smooth, real-time navigation without precise localization can be realized.
continuous free-crab gaits for hexapod robots on a natural terrain with forbidden zones: an application to humanitarian demining. autonomous robots are leaving the laboratories to master new outdoor applications, and walking robots in particular have already shown their potential advantages in these environments, especially on a natural terrain. gait generation is the key to success in the negotiation of natural terrain with legged robots; however, most of the algorithms devised for hexapods have been tested under laboratory conditions. this paper presents the development of crab and turning gaits for hexapod robots on a natural terrain characterized by containing uneven ground and forbidden zones. the gaits we have developed rely on two empirical rules that derive three control modules that have been tested both under simulation and by experiment. the geometrical model of the silo-6 walking robot has been used for simulation purposes, while the real silo-6 walking robot has been used in the experiments. this robot was built as a mobile platform for a sensory system to detect and locate antipersonnel landmines in humanitarian demining missions.
agent formations in 3d spaces with communication limitations using an adaptive q-structure. in this article, we further extend the queue-formation structure (or q-structure) in 3d spaces with additional features including: (i) specifying orientation information, (ii) a mechanism for forming sub-formations before the convergence into the final formation, and (iii) adapting the communication structure when communications are limited. the virtual bobber-agents are used to guide each vehicle toward the appropriate queue, by acting as intermediate targets. in addition, virtual constellation-agents bias the motion of each vehicle to within a user-defined cone to the front of the vehicle so that abrupt direction changes are avoided as far as possible. the proposed scheme relies mainly on simple behaviors between embodied and virtual agents and is computationally inexpensive method. extensive simulations show the effectiveness of the proposed method.
distributed control of multi-robot systems using bifurcating potential fields. the distributed control of multi-robot systems has been shown to have advantages over that of conventional single-robot systems. these include scalability, flexibility and robustness to failures. this paper considers pattern formation and reconfigurability in a multi-robot system using a new control algorithm developed through bifurcating potential fields. it is shown how various patterns can be achieved autonomously through a simple free parameter change, with the stability of the system proven to ensure that desired behaviours always occur.
programming-by-demonstration of reaching motions - a next-state-planner approach. this paper presents a novel approach to skill acquisition from human demonstration. a robot manipulator with a morphology which is very different from the human arm simply cannot copy a human motion, but has to execute its own version of the skill. when a skill once has been acquired the robot must also be able to generalize to other similar skills, without a new learning process. by using a motion planner that operates in an object-related world frame called hand-state, we show that this representation simplifies skill reconstruction and preserves the essential parts of the skill.
sensing and gait planning of quadruped walking and climbing robot for traversing in complex environment. in this paper, a general study on improving adaptability of quadruped walking and climbing robot in complex environment is presented. first, a sensing system composed of range and gyroscope sensors in a novel arrangement is developed. by combining the sensing signals and the internal state of the robot, the surface geometry of the environment is sufficiently reconstructed in real-time. secondly, a planning algorithm for the robot to overcome the reconstructed environment is conducted. based on the reshaped surface, the planning algorithm not only provides the exact body trajectory and foot positions but also the adaptability of the robot in a specific environment. a method to improve the adaptability of the walking and climbing robot is also introduced. thanks to the adherent ability of the robot, the center of gravity of the robot is allowed to move outside the support polygon to increase the reach-ability of the next swing leg. finally, the effectiveness of the proposed approach is verified by the performances of the experiments in complex environments using a quadruped walking and climbing robot named mrwallspect iv.
on visual servoing based on efficient second order minimization. this paper deals with the efficient second order minimization (esm) and the image-based visual servoing schemes. in other words, it deals with the minimization based on the pseudo-inverse of the mean of the jacobians or on the mean of jacobian pseudo-inverses. chronologically, it has been noticed in tahri and chaumette (2003) [22] that esm generally improves the system behavior when compared with the system in which only the simple jacobian pseudo-inverses are used. subsequently, a mathematical explanation has been given in malis (2004) [12]. in this paper, the proofs given by malis are discussed and it will be shown that there is a limitation to the validity of the esm. we will also show that the use of esm does not necessarily ensure a better system behavior, especially in the situations where large rotational motions are involved. further, a new appropriate formula of the esm is proposed and validated using several kinds of features.
programmable differential brake for passive haptics. this paper outlines work on a novel programmable braking system, which is widely applicable to most passive haptic applications and benefits from a simple design, theoretically infinite positional resolution and the ability to generate stiff collision forces, without the need for any explicit force measurements. results are also given of a preliminary concept demonstrator which is based on a simple 2-degrees-of-freedom (dof) revolute-revolute (rr) manipulator incorporating the programmable brakes. performance measures for the joint, as well as figures describing the ability of the 2-dof prototype to constrain the end effector motion to a plane and a circle, are also provided.
omnivision-based kld-monte carlo localization. mobile robots operating in real and populated environments usually execute tasks that require accurate knowledge on their position. monte carlo localization (mcl) algorithms have been successfully applied for laser range finders. however, vision-based approaches present several problems with occlusions, real-time operation, and environment modifications. in this article, an omnivision-based mcl algorithm that solves these drawbacks is presented. the algorithm works with a variable number of particles through the use of the kullback-leibler divergence (kld). the measurement model is based on an omnidirectional camera with a fish-eye lens. this model uses a feature-based map of the environment and the feature extraction process makes it robust to occlusions and changes in the environment. moreover, the algorithm is scalable and works in real-time. results on tracking, global localization and kidnapped robot problem show the excellent performance of the localization system in a real environment. in addition, experiments under severe and continuous occlusions reflect the ability of the algorithm to localize the robot in crowded environments.
gait planning based on kinematics for a quadruped gecko model with redundancy. recent research on mobile robots has focused on locomotion in various environments. in this paper, a gait-generation algorithm for a mobile robot that can travel from the ground to a wall and climb vertical surfaces is proposed. the algorithm was inspired by a gecko lizard. our gait planning was based on inverse kinematics using the jacobian of the whole body, where the redundancy was solved by defining an object function for the gecko posture to avoid collisions with the surface. the optimal scalar factor for these two objects was obtained by defining a superior object function to minimize the angular acceleration of joints. the algorithm was verified through simulation of the gecko model travelling on given task paths and avoiding abnormal joint movements and collisions.
reliable and efficient landmark-based localization for mobile robots. this paper describes an efficient and robust localization system for indoor mobile robots and agvs. the system utilizes a sensor that measures bearings to artificial landmarks, and an efficient triangulation method. we present a calibration method for the system components and overcome typical problems for sensors of the mentioned type, which are localization in motion and incorrect identification of landmarks. the resulting localization system was tested on a mobile robot. it consumes less than 4% of a pentium4 3.2 ghz processing power while providing an accurate and reliable localization result every 0.5 s. the system was successfully incorporated within a real mobile robot system which performs many other computational tasks in parallel.
a new strategy combining empirical and analytical approaches for grasping unknown 3d objects. this paper proposes a novel strategy for grasping 3d unknown objects in accordance with their corresponding task. we define the handle or the natural grasping component of an object as the part chosen by humans to pick up this object. when humans reach out to grasp an object, it is generally in the aim of accomplishing a task. thus, the chosen grasp is quite related to the object task. our approach learns to identify object handles by imitating humans. in this paper, a new sufficient condition for computing force-closure grasps on the obtained handle is also proposed. several experiments were conducted to test the ability of the algorithm to generalize to new objects. they also show the adaptability of our strategy to the hand kinematics.
kinematic control of a redundant manipulator using an inverse-forward adaptive scheme with a ksom based hint generator. this paper proposes an online inverse-forward adaptive scheme with a ksom based hint generator for solving the inverse kinematic problem of a redundant manipulator. in this approach, a feed-forward network such as a radial basis function (rbf) network is used to learn the forward kinematic map of the redundant manipulator. this network is inverted using an inverse-forward adaptive scheme until the network inversion solution guides the manipulator end-effector to reach a given target position with a specified accuracy. the positioning accuracy, attainable by a conventional network inversion scheme, depends on the approximation error present in the forward model. but, an accurate forward map would require a very large size of training data as well as network architecture. the proposed inverse-forward adaptive scheme effectively approximates the forward map around the joint angle vector provided by a hint generator. thus the inverse kinematic solution obtained using the network inversion approach can take the end-effector to the target position within any arbitrary accuracy. in order to satisfy the joint angle constraints, it is necessary to provide the network inversion algorithm with an initial hint for the joint angle vector. since a redundant manipulator can reach a given target end-effector position through several joint angle vectors, it is desirable that the hint generator is capable of providing multiple hints. this problem has been addressed by using a kohonen self organizing map based sub-clustering (ksom-sc) network architecture. the redundancy resolution process involves selecting a suitable joint angle configuration based on different task related criteria. the simulations and experiments are carried out on a 7 dof powercube(tm) manipulator. it is shown that one can obtain a positioning accuracy of 1 mm without violating joint angle constraints even when the forward approximation error is as large as 4 cm. an obstacle avoidance problem has also been solved to demonstrate the redundancy resolution process with the proposed scheme.
dynamically balanced optimal gaits of a ditch-crossing biped robot. this paper deals with the generation of dynamically balanced gaits of a ditch-crossing biped robot having seven degrees of freedom (dofs). three different approaches, namely analytical, neural network (nn)-based and fuzzy logic (fl)-based, have been developed to solve the said problem. the former deals with the analytical modeling of the ditch-crossing gait of a biped robot, whereas the latter two approaches aim to maximize the dynamic balance margin of the robot and minimize the power consumption during locomotion, after satisfying a constraint stating that the changes of joint torques should lie within a pre-specified value to ensure its smooth walking. it is to be noted that the power consumption and dynamic balance of the robot are also dependent on the position of the masses on various links and the trajectory followed by the hip joint. a genetic algorithm (ga) is used to provide training off-line, to the nn-based and fl-based gait planners developed. once optimized, the planners will be able to generate the optimal gaits on-line. both the nn-based and fl-based gait planners are able to generate more balanced gaits and that, too, at the cost of lower power consumption compared to those yielded by the analytical approach. the nn-based and fl-based approaches are found to be more adaptive compared to the other approach in generating the gaits of the biped robot.
a modified adaptive controller design for teleoperation systems. in this paper, a new adaptive controller is proposed to ensure the stability and good performance of a teleoperation system while a wide range of time delays is considered. for this means, a feedforward compensator is designed to ensure system passivity and then a new model reference adaptive controller (mrac) is developed to provide good performance. the developed system demonstrates good stability and force tracking capabilities. a command generator tracker (cgt) is designed for a sample teleoperation system and the results are compared with the proposed system.
an application of lyapunov stability analysis to improve the performance of narmax models. previously we presented a novel approach to program a robot controller based on system identification and robot training techniques. the proposed method works in two stages: first, the programmer demonstrates the desired behaviour to the robot by driving it manually in the target environment. during this run, the sensory perception and the desired velocity commands of the robot are logged. having thus obtained training data we model the relationship between sensory readings and the motor commands of the robot using armax/narmax models and system identification techniques. these produce linear or non-linear polynomials which can be formally analysed, as well as used in place of ''traditional robot'' control code. in this paper we focus our attention on how the mathematical analysis of narmax models can be used to understand the robot's control actions, to formulate hypotheses and to improve the robot's behaviour. one main objective behind this approach is to avoid trial-and-error refinement of robot code. instead, we seek to obtain a reliable design process, where program design decisions are based on the mathematical analysis of the model describing how the robot interacts with its environment to achieve the desired behaviour. we demonstrate this procedure through the analysis of a particular task in mobile robotics: door traversal.
affective social robots. for human-robot interaction to proceed in a smooth, natural manner, robots must adhere to human social norms. one such human convention is the use of expressive moods and emotions as an integral part of social interaction. such expressions are used to convey messages such as ''i'm happy to see you'' or ''i want to be comforted,'' and people's long-term relationships depend heavily on shared emotional experiences. thus, we have developed an affective model for social robots. this generative model attempts to create natural, human-like affect and includes distinctions between immediate emotional responses, the overall mood of the robot, and long-term attitudes toward each visitor to the robot, with a focus on developing long-term human-robot relationships. this paper presents the general affect model as well as particular details of our implementation of the model on one robot, the roboceptionist. in addition, we present findings from two studies that demonstrate the model's potential.
multi-component information-equalized extended strong tracking filter for global localization: a scheme robust to kidnapping and symmetrical environments. this paper proposes a novel multi-component information-equalized extended strong tracking filtering (mist) method for mobile robot global localization. the main contributions of this paper come into three aspects: (1) it is the first time that a strong tracking filter (stf) is introduced into the robotics domain and is extended to be suitable for fusing observations with arbitrarily time-varying dimensionality, based on the proposed extended orthogonality principle and the equivalent space transformation; (2) the information asymmetry problem is analyzed, and an information equalization method based on extracting and equalizing the information underlying the residuals between actual and predicted observations is proposed and integrated with the extended strong tracking filter (estf) so as to make it to be equally sensitive to the saltation and estimation-error in any dimension of the state space; (3) a probabilistic data association mechanism and the dynamic multiple component-filters evolving mechanism are proposed and combined with the information-equalized estf (iestf), which results in the final form of the proposed mist localization method. mist uses multiple individual iestfs (component filters) to track multiple probable pose hypotheses. the number of iestfs is automatically tuned through merging, splitting, deletion and generation, so as to adapt to the time-varying multimodal posterior distribution of the estimated robot's pose. the correctness of each hypothesis (tracked by an individual iestf) is evaluated based on a probabilistic formulation. the effectiveness of the proposed mist method has been validated by real robot experiments and compared with the performances of popular existing methods such as mhl and mcl, which shows that mist has a definite robustness to sensor noises, the kidnapped robot problem, nonlinearity of the system, and symmetric environments, as well as a high convergence speed and computational efficiency.
biologically and psychophysically inspired adaptive support weights algorithm for stereo correspondence. in this paper a novel stereo correspondence algorithm is presented. it incorporates many biologically and psychologically inspired features to an adaptive weighted sum of absolute differences (sad) framework in order to determine the correct depth of a scene. in addition to ideas already exploited, such as the color information utilization, gestalt laws of proximity and similarity, new ones have been adopted. the presented algorithm introduces the use of circular support regions, the gestalt law of continuity as well as the psychophysically-based logarithmic response law. all the aforementioned perceptual tools act complementarily inside a straightforward computational algorithm applicable to robotic applications. the results of the algorithm have been evaluated and compared to those of similar algorithms.
particle filter based information-theoretic active sensing. this work addresses the task of active sensing, or information-seeking control of mobile sensor platforms. formulation of a control objective in terms of information gain allows mobile sensors to be both autonomous and easily reconfigurable to include a variety of sensor and target models. tracking a moving target using a camera mounted on a fixed-wing unmanned aircraft is considered, but the control formulation is not specific to this choice of sensor or estimation task. a control formulation is developed which minimizes the entropy of an estimate distribution over a receding horizon subject to stochastic non-linear models for both the target motion and sensors. previous similar work has been restricted to either a stationary target, a horizon of length one, or gaussian estimates. the prediction of conditional entropy is shown to be inherently complex, and a computationally efficient sequential monte carlo method is developed. the entropy prediction depends on this monte carlo method as well as a novel approach for entropy calculation in the context of particle filtering. these methods are verified through simulation and post-processing of experimental flight data.
energy constrained multi-robot sensor-based coverage path planning using capacitated arc routing approach. multi-robot sensor-based coverage path planning requires every point given in the workspace has to be covered at least by a sensor of a robot in the robot team. in this study, a novel algorithm was proposed for the sensor-based coverage of narrow environments by considering energy capacities of the robots. for this purpose, the environment was modeled by a generalized voronoi diagram-based graph to guarantee complete sensor-based coverage. then, depending on the required arc set, a complete coverage route was created by using the chinese postman problem or the rural postman problem, and this route was partitioned among robots by considering energy capacities. route partitioning was realized by modifying the ulusoy partitioning algorithm which has polynomial complexity. this modification handles two different energy consumptions of mobile robots during sensor-based coverage, which was not considered before. the developed algorithm was coded in c++ and implemented on p3-dx mobile robots both in laboratory and in mobilesim simulation environments. it was shown that the convenient routes for energy constrained multi-robots could be generated by using the proposed algorithm in less than 1 s.
bridging the gap between feature- and grid-based slam. one important design decision for the development of autonomously navigating mobile robots is the choice of the representation of the environment. this includes the question of which type of features should be used, or whether a dense representation such as occupancy grid maps is more appropriate. in this paper, we present an approach which performs slam using multiple representations of the environment simultaneously. it uses reinforcement to learn when to switch to an alternative representation method depending on the current observation. this allows the robot to update its pose and map estimate based on the representation that models the surrounding of the robot in the best way. the approach has been implemented on a real robot and evaluated in scenarios, in which a robot has to navigate in- and outdoors and therefore switches between a landmark-based representation and a dense grid map. in practical experiments, we demonstrate that our approach allows a robot to robustly map environments which cannot be adequately modeled by either of the individual representations.
clustering and line detection in laser range measurements. this article presents two algorithms that extract information from laser range data. they are designed to work sequentially. the first method (dcc) separates the data into clusters by means of a convolution operation, using a high-pass filter. the second one (reholt) performs line detection in each of the clusters previously discovered. the reliability of the algorithms devised is tested on the experimental data collected both indoors and outdoors. when compared with other methods found in the literature, the ones proposed here prove to achieve higher performance.
learning grasping points with shape context. this paper presents work on vision based robotic grasping. the proposed method adopts a learning framework where prototypical grasping points are learnt from several examples and then used on novel objects. for representation purposes, we apply the concept of shape context and for learning we use a supervised learning approach in which the classifier is trained with labelled synthetic images. we evaluate and compare the performance of linear and non-linear classifiers. our results show that a combination of a descriptor based on shape context with a non-linear classification algorithm leads to a stable detection of grasping points for a variety of objects.
swarm-supported outdoor localization with sparse visual data. the localization of mobile systems with video data is a challenging field in robotic vision research. apart from support technologies like a gps, a self-sufficient visual system is desirable. we introduce a new heuristic approach to outdoor localization in a scenario with sparse visual data and without odometry readings. localization is interpreted as an optimization problem, and a swarm-based optimization method is adapted and applied, remaining independent of the specific visual feature type. the new method obtains similar or better localization results in our experiments while requiring only two-thirds of the number of image comparisons, indicating an overall speed-up by 25%.
a mathematical model, implementation and study of a swarm system. the work reported in this paper is motivated towards the development of a mathematical model for swarm systems based on macroscopic primitives. a pattern formation and transformation model is proposed. the pattern transformation model comprises two general methods for pattern transformation, namely a macroscopic transformation method and a mathematical transformation method. the problem of transformation is formally expressed and four special cases of transformation are considered. simulations to confirm the feasibility of the proposed models and transformation methods are presented. comparison between the two transformation methods is also reported.
mobility evaluation of wheeled all-terrain robots. standardized performance evaluation is uncommon in mobile robotics. therefore, it is difficult to compare published results and estimate their value. this work aims at providing a basis for the evaluation and comparison of the mobility performance of wheeled, all-terrain robots with respect to terrainability. precisely defined existing and novel metrics are proposed for this purpose. the utility of these metrics is shown by applying them in a comparison to a selection of rover suspension systems known from the literature. appropriate models for evaluation of the performance are described as well as the validation of the metrics by means of experimental testing. the simulations reveal significant differences in performance between the rovers which is confirmed by the test results. the correlation of the performance in simulation and reality is highly satisfying and supports the applicability of the proposed metrics.
comparison of sensor fusion methods for an sma-based hexapod biomimetic robot. this paper compares the performances of different sensor fusion algorithms in a shape memory alloy (sma)-based hexapod biomimetic robot, smabot iv. the algorithms considered include a kalman filter that minimizes the estimation error variance, an h"~ filter that minimizes the worst-case estimation error, and a robust mixed kalman/h"~ filter that allows for uncertainties in both the system and measurement matrices. the sensors installed on the robot include an inertial measurement unit and an electric compass sensor for inertial guidance. in addition, a stride-length-estimation algorithm for an sma-based legged robot was proposed to establish the legged odometry of the robot. allan variance analysis is employed to identify the noise sources of inertial sensors, and the calculated variance values are used to design the parameters of the kalman filter algorithm. finally, experimental results of two-dimensional navigation are presented, and the performances of three sensor fusion algorithms are compared. the results indicate that after identifying the noise characteristics of inertial sensors, the kalman filter provides the best performance.
towards a unified visual framework in a binocular active robot vision system. this paper presents the results of an investigation and pilot study into an active binocular vision system that combines binocular vergence, object recognition and attention control in a unified framework. the prototype developed is capable of identifying, targeting, verging on and recognising objects in a cluttered scene without the need for calibration or other knowledge of the camera geometry. this is achieved by implementing all image analysis in a symbolic space without creating explicit pixel-space maps. the system structure is based on the 'searchlight metaphor' of biological systems. we present results of an investigation that yield a maximum vergence error of ~6.5 pixels, while ~85% of known objects were recognised in five different cluttered scenes. finally a 'stepping-stone' visual search strategy was demonstrated, taking a total of 40 saccades to find two known objects in the workspace, neither of which appeared simultaneously within the field of view resulting from any individual saccade.
formation path following control of unicycle-type mobile robots. this paper presents a control strategy for the coordination of multiple mobile robots. a combination of the virtual structure and path following approaches is used to derive the formation architecture. a formation controller is proposed for the kinematic model of two-degree-of-freedom unicycle-type mobile robots. the approach is then extended to consider the formation controller by taking into account the physical dimensions and dynamics of the robots. the controller is designed in such a way that the path derivative is left as a free input to synchronize the robot's motion. simulation results with three robots are included to show the performance of our control system. finally, the theoretical results are experimentally validated on a multi-robot platform.
an information-based exploration strategy for environment mapping with mobile robots. the availability of efficient mapping systems to produce accurate representations of initially unknown environments is recognized as one of the main requirements for autonomous mobile robots. in this paper, we present an efficient mapping system that has been implemented on a mobile robot equipped with a laser range scanner. the system builds geometrical point-based maps of environments employing an information-based exploration strategy that determines the best observation positions by taking into account both the distance travelled and the information gathered. our exploration strategy, being based on solid mathematical foundations, differs from many ad hoc exploration strategies proposed in literature. we present: (a) the theoretical aspects of the criterion for determining the best observation positions for a robot building a map, (b) the implementation of a mapping system that uses the proposed criterion, and (c) the experimental validation of our approach.
maximum-likelihood sample-based maps for mobile robots. the problem of representing the environment of a mobile robot has been studied intensively in the past. the predominant approaches for geometric representations are grid-based or line-based maps. in this paper, we consider sample-based maps which use the data points obtained by range scanners to represent the environment. the main advantage of this representation over the other techniques is that it is able to represent arbitrary structures and at the same time provide an arbitrary accuracy. however, range measurements come in large amounts and not every measurement necessarily contributes to the representation in the same way. we present a novel approach for calculating maximum-likelihood subsets of the data points by sub-sampling laser range data. in particular, our method applies a variant of the fuzzy k-means algorithm to find a map that maximizes the likelihood of the original data. experimental results with real data show that the resulting maps are better suited for robot localization than maps obtained with other sub-sampling techniques.
interactive teaching of task-oriented robot grasps. this paper focuses on the problem of grasp stability and grasp quality analysis. an elegant way to evaluate the stability of a grasp is to model its wrench space. however, classical grasp quality measures suffer from several disadvantages, the main drawback being that they are not task related. indeed, constructive approaches for approximating the wrench space including also task information have been rarely considered. this work presents an effective method for task-oriented grasp quality evaluation based on a novel grasp quality measure. we address the general case of multifingered grasps with point contacts with friction. the proposed approach is based on the concept of programming by demonstration and interactive teaching, wherein an expert user provides in a teaching phase a set of exemplar grasps appropriate for the task. following this phase, a representation of task-related grasps is built. during task planning and execution, a grasp could be either submitted interactively for evaluation by a non-expert user or synthesized by an automatic planning system. grasp quality is then assessed based on the proposed measure, which takes into account grasp stability along with its suitability for the task. to enable real-time evaluation of grasps, a fast algorithm for computing an approximation of the quality measure is also proposed. finally, a local grasp optimization technique is described which can amend uncertainties arising in supplied grasps by non-expert users or assist in planning more valuable grasps in the neighborhood of candidate ones. the paper reports experiments performed in virtual reality with both an anthropomorphic virtual hand and a three-fingered robot hand. these experiments suggest the effectiveness and task relevance of the proposed grasp quality measure.
a local obstacle avoidance method for mobile robots in partially known environment. local obstacle avoidance is a principle capability for mobile robots in unknown or partially known environment. a series of velocity space methods including the curvature velocity method (cvm), the lane curvature method (lcm) and the beam curvature method (bcm) formulate the local obstacle avoidance problem as one of constrained optimization in the velocity space by taking the physical constraints of the environment and the dynamics of the vehicle into account. we present a new local obstacle avoidance approach that combines the prediction model of collision with the improved bcm. not only does this method inherit the quickness of bcm and the safety of lcm, but also the proposed prediction based bcm (pbcm) can be used to avoid moving obstacles in dynamic environments.
entropy based robust estimator and its application to line-based mapping. this paper presents a robust mapping algorithm for an application in autonomous robots. the method is inspired by the notion of entropy from information theory. a kernel density estimator is adopted to estimate the appearance probability of samples directly from the data. an entropy based robust (ebr) estimator is then designed that selects the most reliable inliers of the line segments. the inliers maintained by the entropy filter are those samples that carry more information. hence, the parameters extracted from ebr estimator are accurate and robust to the outliers. the performance of the ebr estimator is illustrated by comparing the results with the performance of three other estimators via simulated and real data.
a novel low-cost, limited-resource approach to autonomous multi-robot exploration and mapping. mobile robots are becoming more heavily used in environments where human involvement is limited, impossible, or dangerous. these robots perform some of the more laborious human tasks on earth and throughout the solar system, simultaneously saving resources and offering automation. higher levels of autonomy are also being sought in these applications, such as distributed exploration and mapping of unknown areas. smaller, less expensive mobile robots are becoming more prevalent, which introduces unique challenges in terms of limited sensing accuracy and onboard computing resources. this paper presents a novel low-cost, limited-resource approach to autonomous multi-robot mapping and exploration in unstructured environments. design and implementation details are presented, along with results from two planetary style environments. results demonstrate that low-cost ($ 1250) mobile robots capable of simultaneous localization and mapping can be successfully constructed. the multi-robot system presented in this paper participated in the 2008 international conference on robotics and automation (icra) space robotics challenge, receiving two awards for successfully completing the 'onto the surface' and 'map the environment' events in a simulated planetary environment. this work demonstrates not only that such systems are possible, but also that this direction of research is important and needs attention.
motion in ambiguity: coordinated active global localization for multiple robots. the task of the robot in localization is to find out where it is, through sensing and motion. in environments which possess relatively few features that enable a robot to unambiguously determine its location, global localization algorithms can result in 'multiple hypotheses' locations of a robot. this is inevitable with global localization algorithms, as the local environment seen by a robot repeats at other parts of the map. thus, for effective localization, the robot has to be actively guided to those locations where there is a maximum chance of eliminating most of the ambiguous states - which is often referred to as 'active localization'. when extended to multi-robotic scenarios where all robots possess more than one hypothesis of their position, there is an opportunity to do better by using robots, apart from obstacles, as 'hypotheses resolving agents'. the paper presents a unified framework which accounts for the map structure as well as measurement amongst robots, while guiding a set of robots to locations where they can singularize to a unique state. the strategy shepherds the robots to places where the probability of obtaining a unique hypothesis for a set of multiple robots is a maximum. another aspect of framework demonstrates the idea of dispatching localized robots to locations where they can assist a maximum of the remaining unlocalized robots to overcome their ambiguity, named as 'coordinated localization'. the appropriateness of our approach is demonstrated empirically in both simulation & real-time (on amigo-bots) and its efficacy verified. extensive comparative analysis portrays the advantage of the current method over others that do not perform active localization in a multi-robotic sense. it also portrays the performance gain by considering map structure and robot placement to actively localize over methods that consider only one of them or neither. theoretical backing stems from the proven completeness of the method for a large category of diverse environments.
robot contact tasks in the presence of control target distortions. this work refers to the problem of controlling robot motion and force in frictional contacts under environmental errors and particularly orientation errors that distort the desired control targets and control subspaces. the proposed method uses online estimates of the surface normal (tangent) direction to dynamically modify the control target and control space decomposition. it is proved that these estimates converge to the actual value even though the elasticity and friction parameters are unknown. the proposed control solution is demonstrated through simulation examples in three-dimensional robot motion tasks contacting both planar and curved surfaces.
a strategy for grasping unknown objects based on co-planarity and colour information. in this work, we describe and evaluate a grasping mechanism that does not make use of any specific object prior knowledge. the mechanism makes use of second-order relations between visually extracted multi-modal 3d features provided by an early cognitive vision system. more specifically, the algorithm is based on two relations covering geometric information in terms of a co-planarity constraint as well as appearance based information in terms of co-occurrence of colour properties. we show that our algorithm, although making use of such rather simple constraints, is able to grasp objects with a reasonable success rate in rather complex environments (i.e., cluttered scenes with multiple objects). moreover, we have embedded the algorithm within a cognitive system that allows for autonomous exploration and learning in different contexts. first, the system is able to perform long action sequences which, although the grasping attempts not being always successful, can recover from mistakes and more importantly, is able to evaluate the success of the grasps autonomously by haptic feedback (i.e., by a force torque sensor at the wrist and proprioceptive information about the distance of the gripper after a gasping attempt). such labelled data is then used for improving the initially hard-wired algorithm by learning. moreover, the grasping behaviour has been used in a cognitive system to trigger higher level processes such as object learning and learning of object specific grasping.
visual control through the trifocal tensor for nonholonomic robots. we present a new vision-based control approach which drives autonomously a nonholonomic vehicle to a target location. the vision system is a camera fixed on the vehicle and the target location is defined by an image taken previously in that location. the control scheme is based on the trifocal tensor model, which is computed from feature correspondences in calibrated retina across three views: initial, current and target images. the contribution is a trifocal-based control law defined by an exact input-output linearization of the trifocal tensor model. the desired evolution of the system towards the target is directly defined in terms of the trifocal tensor elements by means of sinusoidal functions without needing metric or additional information from the environment. the trifocal tensor presents important advantages for visual control purposes, because it is more robust than two-view geometry as it includes the information of a third view and, contrary to the epipolar geometry, short baseline is not a problem. simulations show the performance of the approach, which has been tested with image noise and calibration errors.
estimation of pointing poses for visually instructing mobile robots under real world conditions. in this paper, we present an approach for directing a mobile robot under real-world conditions into a target position by means of pointing poses only. because one important objective of our work is the development of a low-cost platform, only monocular vision at web-cam level should be employed. our previous approach presented in gross et al. (2006) [1], richarz et al. (2007) [2] has been improved by several additional processing steps. finally, a background subtraction technique and a histogram equalization have been integrated in the preprocessing stage to be able to work in environments with structured backgrounds and under variable lighting conditions. furthermore, a discriminant analysis was used to find the most relevant input features for the pointing pose estimator. the contribution of this paper is, however, not only the presentation of an approach to estimating pointing poses in a demanding real-world scenario on a mobile robot, but also the detailed and evaluative comparison between different image-preprocessing techniques, alternative feature extraction methods, and several function approximators with the same set of test- and training data. reasonable combinations of the different methods are tested, and for each component on the processing chain the effect on the accuracy of the target estimation is quantized. the approach presented in this paper has been implemented on the mobile interaction robot horos to determine the performance and estimation accuracy under real-world conditions. furthermore, we compared the accuracy of our approach with that of humans performing the same estimation task, and achieved very comparable results for the best estimator.
dimensional synthesis of kinematically redundant serial manipulators for cluttered environments. a systematic procedure for synthesizing kinematically redundant serial manipulators is proposed in this paper. for a given cluttered workcell, the task space locations (tsl's) for the desired manipulator are prescribed. the synthesis is performed with the objective of reachability of the manipulator at specified tsl's, while avoiding obstacles. the problem is formulated as a constrained optimization problem, minimizing the positional error and simultaneously avoiding any collision of the manipulator with either the obstacles or within its links. the technique used to solve the resulting constrained optimization problem is the classical augmented lagrangian method. the paper presents a discussion on the past works in this field. it is observed that the presented literature is confined to special cases only while the proposed method involves full generality of the synthesis problem. the availability of such an algorithm working for full generality is important, particularly for highly constrained environments. the efficiency of the proposed approach to synthesize the desired redundant manipulators is exhibited through diverse cases. the resulting synthesized manipulators are further checked for the possibility of feasible paths between tsl's. an outline of the development of a redundant manipulator, synthesized through the presented approach, is also included in this paper.
a developmental algorithm for ocular-motor coordination. this paper presents a model of ocular-motor development, inspired by ideas and data from developmental psychology. the learning problem concerns the growth of the transform between image space and motor space necessary for the control of visual saccades. an implementation is used to produce experimental results and these are presented and discussed. the algorithm is simple, extremely fast, self-calibrating, adaptive to change, and exhibits emergent stages of behaviour as learning progresses.
a review of log-polar imaging for visual perception in robotics. log-polar imaging consists of a type of methods that represent visual information with a space-variant resolution inspired by the visual system of mammals. it has been studied for about three decades and has surpassed conventional approaches in robotics applications, mainly the ones where real-time constraints make it necessary to utilize resource-economic image representations and processing methodologies. this paper surveys the application of log-polar imaging in robotic vision, particularly in visual attention, target tracking, egomotion estimation, and 3d perception. the concise yet comprehensive review offered in this paper is intended to provide novel and experienced roboticists with a quick and gentle overview of log-polar vision and to motivate vision researchers to investigate the many open problems that still need solving. to help readers identify promising research directions, a possible research agenda is outlined. finally, since log-polar vision is not restricted to robotics, a couple of other areas of application are discussed.
what is analytic infrastructure and why should you care? we define analytic infrastructure to be the services, applications, utilities and systems that are used for either preparing data for modeling, estimating models, validating models, scoring data, or related activities. for example, analytic infrastructure includes databases and data warehouses, statistical and data mining systems, scoring engines, grids and clouds. note that, with this definition, analytic infrastructure does not need to be used exclusively for modeling but simply useful as part of the modeling process. in this article, we discuss the importance of analytic infrastructure and some of the standards that can be used to support analytic infrastructure. we also discuss some specialized analytic infrastructure applications and services, including applications that can manage very large datasets and build models over them and cloud based analytic services.
efficient deployment of predictive analytics through open standards and cloud computing. over the past decade, we have seen tremendous interest in the application of data mining and statistical algorithms, first in research and science and, more recently, across various industries. this has translated into the development of a myriad of solutions by the data mining community that today impact scientific and business applications alike. however, even in this scenario, interoperability and open standards still lack broader adoption among data miners and modelers. in this article we highlight the use of the predictive model markup language (pmml) standard, which allows for models to be easily exchanged between analytic applications. with a focus on interoperability and pmml, we also discuss here emerging trends in cloud computing and software as a service, which have already started to play a critical role in promoting a more effective implementation and widespread application of predictive models. as an illustration of how the benefits of open standards and cloud computing can be combined, we describe a predictive analytics scoring engine platform that leverages these elements to deliver an efficient deployment process for statistical models.
challenging research issues in data mining, databases and information retrieval. data mining research along with related fields such as databases and information retrieval poses challenging problems, especially for doctoral students. the research spreads over a variety of topics such as text mining, semantic web, multilingual information analysis, heterogeneous data management, database learning, digital libraries and more. much of this research cuts across multiple fields and presents interesting issues for discussion at conferences with a confluence of several tracks. the acm conference on information and knowledge management provides an excellent environment for presenting such research problems spanning the three tracks of database systems, information retrieval and knowledge management. this article provides an overview of the dissertation problems presented at a ph.d. workshop in the acm conference on information and knowledge management. the goal of such workshops is to allow students to showcase their creative ideas at an early stage. this enables experts to critique their work and also gives the students an opportunity to exchange their thoughts with each other, besides providing excellent networking opportunities with industry and academia. this article provides an overview of the papers presented at the ph.d workshop. it serves as a motivation for researchers to delve deeper into the innovative dissertation problems summarized here and the related work in these areas.
adaptive learning and mining for data streams and frequent patterns. this thesis is devoted to the design of data mining algorithms for evolving data streams and for the extraction of closed frequent trees. first, we deal with each of these tasks separately, and then we deal with them together, developing classification methods for data streams containing items that are trees. in the data stream model, data arrive at high speed, and the algorithms that must process them have very strict constraints of space and time. in the first part of this thesis we propose and illustrate a framework for developing algorithms that can adaptively learn from data streams that change over time. our methods are based on using change detectors and estimator modules at the right places. we propose an adaptive sliding window algorithm adwin for detecting change and keeping updated statistics from a data stream, and use it as a black-box in place or counters or accumulators in algorithms initially not designed for drifting data. since adwin has rigorous performance guarantees, this opens the possibility of extending such guarantees to learning and mining algorithms. we test our methodology with several learning methods as naíve bayes, clustering, decision trees and ensemble methods. we build an experimental framework for data stream mining with concept drift, based on the moa framework, similar to weka, so that it will be easy for researchers to run experimental data stream benchmarks. trees are connected acyclic graphs and they are studied as link-based structures in many cases. in the second part of this thesis, we describe a rather formal study of trees from the point of view of closure-based mining. moreover, we present efficient algorithms for subtree testing and for mining ordered and unordered frequent closed trees. we include an analysis of the extraction of association rules of full condence out of the closed sets of trees, and we have found there an interesting phenomenon: rules whose propositional counterpart is nontrivial are, however, always implicitly true in trees due to the peculiar combinatorics of the structures. and finally, using these results on evolving data streams mining and closed frequent tree mining, we present high performance algorithms for mining closed unlabeled rooted trees adaptively from data streams that change over time. we introduce a general methodology to identify closed patterns in a data stream, using galois lattice theory. using this methodology, we then develop an incremental one, a sliding-window based one, and finally one that mines closed trees adaptively from data streams. we use these methods to develop classification methods for tree data streams.
the weka data mining software: an update. more than twelve years have elapsed since the first public release of weka. in that time, the software has been rewritten entirely from scratch, evolved substantially and now accompanies a text on data mining [35]. these days, weka enjoys widespread acceptance in both academia and business, has an active community, and has been downloaded more than 1.4 million times since being placed on source-forge in april 2000. this paper provides an introduction to the weka workbench, reviews the history of the project, and, in light of the recent 3.6 stable release, briefly discusses what has been added since the last stable version (weka 3.4) released in 2003.
what's pmml and what's new in pmml 4.0? the predictive model markup language (pmml) data mining standard has arguably become one of the most widely adopted data mining standards in use today. two years in the making, the latest release of pmml contains several new features and many enhancements to existing ones. this paper provides a primer on the pmml standard and its applications along with a description of the new features in pmml 4.0 which was released in may 2009.
development and user experiences of an open source data cleaning, deduplication and record linkage system. record linkage, also known as database matching or entity resolution, is now recognised as a core step in the kdd process. data mining projects increasingly require that information from several sources is combined before the actual mining can be conducted. also of increasing interest is the deduplication of a single database. the objectives of record linkage and deduplication are to identify, match and merge all records that relate to the same real-world entities. because real-world data is commonly 'dirty', data cleaning is an important first step in many deduplication, record linkage, and data mining project. in this paper, an overview of the febrl (freely extensible biomedical record linkage) system is provided, and the results of a recent survey of febrl users is discussed. febrl includes a variety of functionalities required for data cleaning, deduplication and record linkage, and it provides a graphical user interface that facilitates its application for users who do not have programming experience.
open source analytics: an introduction to the special issue. this special issue contains six articles on open source analytics. it includes an article describing the weka data mining system, two articles on infrastructure to support analytics, an article on the pmml standard for statistical and data mining models, an article on how clouds are being used in analytics, and an article about an open source tool for cleaning data.
knime - the konstanz information miner: version 2.0 and beyond. the konstanz information miner is a modular environment, which enables easy visual assembly and interactive execution of a data pipeline. it is designed as a teaching, research and collaboration platform, which enables simple integration of new algorithms and tools as well as data manipulation or visualization methods in the form of new modules or nodes. in this paper we describe some of the design aspects of the underlying architecture, briey sketch how new nodes can be incorporated, and highlight some of the new features of version 2.0.
correlation clustering. this is a short summary of the author's thesis on "correlation clustering" (ludwig-maximilians-universität münchen, germany, 2008). the complete thesis is available at http://edoc.ub.uni-muenchen.de/8736/.
a linear algorithm for computing convex hulls for random lines. finding the convex hull of n points in the plane requires o(n log n) time in general. in devroye and toussaint [1993] and golin et al. [2002] the problem of computing the convex hull of the intersection points of n lines was considered, where the lines are chosen randomly according to two various models. in both models, linear-time algorithms were developed. here we improve the results of devroye and toussaint [1993] by giving a universal algorithm for a wider range of distributions.
polynomial constraint satisfaction problems, graph bisection, and the ising partition function. we introduce a problem class we call polynomial constraint satisfaction problems, or pcsp. where the usual csps from computer science and optimization have real-valued score functions, and partition functions from physics have monomials, pcsp has scores that are arbitrary multivariate formal polynomials, or indeed take values in an arbitrary ring. although pcsp is much more general than csp, remarkably, all (exact, exponential-time) algorithms we know of for 2-csp (where each score depends on at most 2 variables) extend to 2-pcsp, at the expense of just a polynomial factor in running time. specifically, we extend the reduction-based algorithm of scott and sorkin [2007]; the specialization of that approach to sparse random instances, where the algorithm runs in polynomial expected time; dynamic-programming algorithms based on tree decompositions; and the split-and-list matrix-multiplication algorithm of williams [2004]. this gives the first polynomial-space exact algorithm more efficient than exhaustive enumeration for the well-studied problems of finding a maximum bisection of a graph, and calculating the partition function of an ising model. it also yields the most efficient algorithm known for certain instances of counting and/or weighted maximum independent set. furthermore, pcsp solves both optimization and counting versions of a wide range of problems, including all csps, and thus enables samplers including uniform sampling of optimal solutions and gibbs sampling of all solutions.
enumeration of isolated cliques and pseudo-cliques. in this article, we consider isolated cliques and isolated dense subgraphs. for a given graph g, a vertex subset s of size k (and also its induced subgraph g(s)) is said to be c-isolated if g(s) is connected to its outside via less than ck edges. the number c is sometimes called the isolation factor. the subgraph appears more isolated if the isolation factor is smaller. the main result in this work shows that for a fixed constant c, we can enumerate all c-isolated maximal cliques (including a maximum one, if any) in linear time. in more detail, we show that, for a given graph g of n vertices and m edges, and a positive real number c, all c-isolated maximal cliques can be enumerated in time o( c4 22cm). from this, we can see that: (1) if c is a constant, all c-isolated maximal cliques can be enumerated in linear time, and (2) if c &equlas; o(log n), all c-isolated maximal cliques can be enumerated in polynomial time. moreover, we show that these bounds are tight. that is, if f(n) is an increasing function not bounded by any constant, then there is a graph of n vertices and m edges for which the number of f(n)-isolated maximal cliques is superlinear in n + m. furthermore, if f(n) &equals; &omega;(log n), there is a graph of n vertices and m edges for which the number of f(n)-isolated maximal cliques is superpolynomial in n + m. we next introduce the idea of pseudo-cliques. a pseudo-clique having an average degree &alpha; and a minimum degree &beta;, denoted by pc(&alpha;,&beta;), is a set v&prime; &sube; v such that the subgraph induced by v&prime; has an average degree of at least &alpha; and a minimum degree of at least &beta;. this article investigates these, and obtains some cases that can be solved in polynomial time and some other cases that have a superpolynomial number of solutions. especially, we show the following results, where k is the number of vertices of the isolated pseudo-cliques: (1) for any &epsiv; > 0 there is a graph of n vertices for which the number of 1-isolated pc(k &minus; (log k)1 + &epsiv;, k/(log k)1 + &epsiv;) is superpolynomial, and (2) there is a polynomial-time algorithm which enumerates all c-isolated pc(k &minus; log k, k/log k), for any constant c.
sublinear estimation of entropy and information distances. in many data mining and machine learning problems, the data items that need to be clustered or classified are not arbitrary points in a high-dimensional space, but are distributions, that is, points on a high-dimensional simplex. for distributions, natural measures are not &ell;p distances, but information-theoretic measures such as the kullback-leibler and hellinger divergences. similarly, quantities such as the entropy of a distribution are more natural than frequency moments. efficient estimation of these quantities is a key component in algorithms for manipulating distributions. since the datasets involved are typically massive, these algorithms need to have only sublinear complexity in order to be feasible in practice. we present a range of sublinear-time algorithms in various oracle models in which the algorithm accesses the data via an oracle that supports various queries. in particular, we answer a question posed by batu et al. on testing whether two distributions are close in an information-theoretic sense given independent samples. we then present optimal algorithms for estimating various information-divergences and entropy with a more powerful oracle called the combined oracle that was also considered by batu et al. finally, we consider sublinear-space algorithms for these quantities in the data-stream model. in the course of doing so, we explore the relationship between the aforementioned oracle models and the data-stream model. this continues work initiated by feigenbaum et al. an important additional component to the study is considering data streams that are ordered randomly rather than just those which are ordered adversarially.
improved online algorithms for the sorting buffer problem on line metrics. an instance of the sorting buffer problem consists of a metric space and a server, equipped with a finite-capacity buffer capable of holding a limited number of requests. an additional ingredient of the input is an online sequence of requests, each of which is characterized by a destination in the given metric space; whenever a request arrives, it must be stored in the sorting buffer. at any point in time, a currently pending request can be served by drawing it out of the buffer and moving the server to its corresponding destination. the objective is to serve all input requests in a way that minimizes the total distance traveled by the server. in this article, we focus our attention on instances of the problem in which the underlying metric is either an evenly-spaced line metric or a continuous line metric. our main findings can be briefly summarized as follows. (1) we present a deterministic o(log n)-competitive algorithm for n-point evenly-spaced line metrics. this result improves on a randomized o(log2 n)-competitive algorithm due to khandekar and pandit [2006b]. it also refutes their conjecture, stating that a deterministic strategy is unlikely to obtain a nontrivial competitive ratio. (2) we devise a deterministic o(log n log log n)-competitive algorithm for continuous line metrics, where n denotes the length of the input sequence. in this context, we introduce a novel discretization technique of independent interest. (3) we establish the first nontrivial lower bound for the evenly-spaced case, by proving that the competitive ratio of any deterministic algorithm is at least 2 + &sqrt;3/&sqrt;3 &ap; 2.154. this result settles, to some extent, an open question due to khandekar and pandit [2006b], who posed the task of attaining lower bounds on the achievable competitive ratio as a foundational objective for future research.
computing rank-convolutions with a mask. rank-convolutions have important applications in a variety of areas such as signal processing and computer vision. we define a mask as a function taking only values zero and infinity. rank-convolutions with masks are of special interest to image processing. we show how to compute the rank-k convolution of a function over an interval of length n with an arbitrary mask of length m in o(n&sqrt;m log m) time. the result generalizes to the d-dimensional case. previously no algorithm performing significantly better than the brute-force o(nm) bound was known. our algorithm seems to perform well in practice. we describe an implementation, illustrating its application to a problem in image processing. already on relatively small images, our experiments show a signficant speedup compared to brute force.
latency-constrained aggregation in sensor networks. a sensor network consists of sensing devices which may exchange data through wireless communication; sensor networks are highly energy constrained since they are usually battery operated. data aggregation is a possible way to save energy consumption: nodes may delay data in order to aggregate them into a single packet before forwarding them towards some central node (sink). however, many applications impose constraints on the maximum delay of data; this translates into latency constraints for data arriving at the sink. we study the problem of data aggregation to minimize maximum energy consumption under latency constraints on sensed data delivery, and we assume unique communication paths that form an intree rooted at the sink. we prove that the offline problem is strongly np-hard and we design a 2-approximation algorithm. the latter uses a novel rounding technique. almost all real-life sensor networks are managed online by simple distributed algorithms in the nodes. in this context we consider both the case in which sensor nodes are synchronized or not. we assess the performance of the algorithm by competitive analysis. we also provide lower bounds for the models we consider, in some cases showing optimality of the algorithms we propose. most of our results also hold when minimizing the total energy consumption of all nodes.
exponential time algorithms for the minimum dominating set problem on some graph classes. the minimum dominating set problem remains np-hard when restricted to any of the following graph classes: c-dense graphs, chordal graphs, 4-chordal graphs, weakly chordal graphs, and circle graphs. developing and using a general approach, for each of these graph classes we present an exponential time algorithm solving the minimum dominating set problem faster than the best known algorithm for general graphs. our algorithms have the following running time: o(1.4124n) for chordal graphs, o(1.4776n) for weakly chordal graphs, o(1.4845n) for 4-chordal graphs, o(1.4887n) for circle graphs, and o(1.2273(1+&sqrt;1&minus;2c)n) for c-dense graphs.
quantum algorithms for simon's problem over nonabelian groups. daniel simon's 1994 discovery of an efficient quantum algorithm for finding &ldquo;hidden shifts&rdquo; of z2n provided the first algebraic problem for which quantum computers are exponentially faster than their classical counterparts. in this article, we study the generalization of simon's problem to arbitrary groups. fixing a finite group g, this is the problem of recovering an involution m &equals; (m1,&hellip;,mn) &isin; gn from an oracle f with the property that f(x &sdot; y) &equals; f(x) &harr; y &isin; {1, m}. in the current parlance, this is the hidden subgroup problem (hsp) over groups of the form gn, where g is a nonabelian group of constant size, and where the hidden subgroup is either trivial or has order two. although groups of the form gn have a simple product structure, they share important representation--theoretic properties with the symmetric groups sn, where a solution to the hsp would yield a quantum algorithm for graph isomorphism. in particular, solving their hsp with the so-called &ldquo;standard method&rdquo; requires highly entangled measurements on the tensor product of many coset states. in this article, we provide quantum algorithms with time complexity 2o(&sqrt;n) that recover hidden involutions m &equals; (m1,&hellip;mn) &isin; gn where, as in simon's problem, each mi is either the identity or the conjugate of a known element m which satisfies &kappa;(m) &equals; &minus;&kappa;(1) for some &kappa; &isin; &gcirc;. our approach combines the general idea behind kuperberg's sieve for dihedral groups with the &ldquo;missing harmonic&rdquo; approach of moore and russell. these are the first nontrivial hsp algorithms for group families that require highly entangled multiregister fourier sampling.
approximating the minimum quadratic assignment problems. we consider the well-known minimum quadratic assignment problem. in this problem we are given two n &times; n nonnegative symmetric matrices a &equals; (aij) and b &equals; (bij). the objective is to compute a permutation &pi; of v &equals; {1,&hellip;,n} so that &sum; i,j&isin;vi&ne;j a&pi;(i),&pi;(j)bi,j is minimized. we assume that a is a 0/1 incidence matrix of a graph, and that b satisfies the triangle inequality. we analyze the approximability of this class of problems by providing polynomial bounded approximations for some special cases, and inapproximability results for other cases.
minimum cycle bases: faster and simpler. we consider the problem of computing exact or approximate minimum cycle bases of an undirected (or directed) graph g with m edges, n vertices and nonnegative edge weights. in this problem, a {0, 1} (&minus;1,0,1}) incidence vector is associated with each cycle and the vector space over f2 (q) generated by these vectors is the cycle space of g. a set of cycles is called a cycle basis of g if it forms a basis for its cycle space. a cycle basis where the sum of the weights of the cycles is minimum is called a minimum cycle basis of g. cycle bases of low weight are useful in a number of contexts, for example, the analysis of electrical networks, structural engineering, chemistry, and surface reconstruction. there exists a set of &theta;(mn) cycles which is guaranteed to contain a minimum cycle basis. a minimum basis can be extracted by gaussian elimination. the resulting algorithm [horton 1987] was the first polynomial-time algorithm. faster and more complicated algorithms have been found since then. we present a very simple method for extracting a minimum cycle basis from the candidate set with running time o(m2 n), which improves the running time for sparse graphs. furthermore, in the undirected case by using bit-packing we improve the running time also in the case of dense graphs. for undirected graphs we derive an o(m2 n/log n + n2 m) algorithm. for directed graphs we get an o(m3 n) deterministic and an o(m2 n) randomized algorithm. our results improve the running times of both exact and approximate algorithms. finally, we derive a smaller candidate set with size in &omega;(m) &cap; o(mn).
simultaneous source location. we consider the problem of simultaneous source location: selecting locations for sources in a capacitated graph such that a given set of demands can be satisfied simultaneously, with the goal of minimizing the number of locations chosen. for general directed and undirected graphs we give an o(log d)-approximation algorithm, where d is the sum of demands, and prove matching &omega;(log d) hardness results assuming p &ne; np. for undirected trees, we give an exact algorithm and show how this can be combined with a result of r&auml;cke to give a solution that exceeds edge capacities by at most o(log2 n log log n), where n is the number of nodes. for undirected graphs of bounded treewidth we show that the problem is still np-hard, but we are able to give a ptas with at most (1 + &epsis;) violation of the capacities for arbitrarily small &epsis;, or a (k+1) approximation with exact capacities, where k is the treewidth.
inverse auctions: injecting unique minima into random sets. we consider auctions in which the winning bid is the smallest bid that is unique. only the upper-price limit is given. neither the number of participants nor the distribution of the offers are known, so that the problem of placing a bid to win with maximum probability looks, a priori, ill-posed. indeed, the essence of the problem is to inject a (final) minimum into a random subset (of unique offers) of a larger random set. we will see, however, that here no more than two external (and almost compelling) arguments make the problem meaningful. by appropriately modeling the relationship between the number of participants and the distribution of the bids, we can then maximize our chances of winning the auction and propose a computable algorithm for placing our bid.
resilient dictionaries. we address the problem of designing data structures in the presence of faults that may arbitrarily corrupt memory locations. more precisely, we assume that an adaptive adversary can arbitrarily overwrite the content of up to &delta; memory locations, that corrupted locations cannot be detected, and that only o(1) memory locations are safe. in this framework, we call a data structure resilient if it is able to operate correctly (at least) on the set of uncorrupted values. we present a resilient dictionary, implementing search, insert, and delete operations. our dictionary has o(log n + &delta;) expected amortized time per operation, and o(n) space complexity, where n denotes the current number of keys in the dictionary. we also describe a deterministic resilient dictionary, with the same amortized cost per operation over a sequence of at least &delta;&epsis; operations, where &epsis; > 0 is an arbitrary constant. finally, we show that any resilient comparison-based dictionary must take &omega;(log n + &delta;) expected time per search. our results are achieved by means of simple, new techniques which might be of independent interest for the design of other resilient algorithms.
optimizing throughput and energy in online deadline scheduling. this article extends the study of online algorithms for energy-efficient deadline scheduling to the overloaded setting. specifically, we consider a processor that can vary its speed between 0 and a maximum speed t to minimize its energy usage (the rate is believed to be a cubic function of the speed). as the speed is upper bounded, the processor may be overloaded with jobs and no scheduling algorithms can guarantee to meet the deadlines of all jobs. an optimal schedule is expected to maximize the throughput, and furthermore, its energy usage should be the smallest among all schedules that achieve the maximum throughput. in designing a scheduling algorithm, one has to face the dilemma of selecting more jobs and being conservative in energy usage. if we ignore energy usage, the best possible online algorithm is 4-competitive on throughput [koren and shasha 1995]. on the other hand, existing work on energy-efficient scheduling focuses on a setting where the processor speed is unbounded and the concern is on minimizing the energy to complete all jobs; o(1)-competitive online algorithms with respect to energy usage have been known [yao et al. 1995; bansal et al. 2007a; li et al. 2006]. this article presents the first online algorithm for the more realistic setting where processor speed is bounded and the system may be overloaded; the algorithm is o(1)-competitive on both throughput and energy usage. if the maximum speed of the online scheduler is relaxed slightly to (1+&epsis;)t for some &epsis; > 0, we can improve the competitive ratio on throughput to arbitrarily close to one, while maintaining o(1)-competitiveness on energy usage.
periodicity testing with sublinear samples and space. in this work, we are interested in periodic trends in long data streams in the presence of computational constraints. to this end; we present algorithms for discovering periodic trends in the combinatorial property testing model in a data stream s of length n using o(n) samples and space. in accordance with the property testing model, we first explore the notion of being &ldquo;close&rdquo; to periodic by defining three different notions of self-distance through relaxing different notions of exact periodicity. an input s is then called approximately periodic if it exhibits a small self-distance (with respect to any one self-distance defined). we show that even though the different definitions of exact periodicity are equivalent, the resulting definitions of self-distance and approximate periodicity are not; we also show that these self-distances are constant approximations of each other. afterwards, we present algorithms which distinguish between the two cases where s is exactly periodic and s is far from periodic with only a constant probability of error. our algorithms sample only o(&sqrt;nlog2 n) (or o(&sqrt;nlog4 n), depending on the self-distance) positions and use as much space. they can also find, using o(n) samples and space, the largest/smallest period, and/or all of the approximate periods of s. these algorithms can also be viewed as working on streaming inputs where each data item is seen once and in order, storing only a sublinear (o(&sqrt;nlog2 n) or o(&sqrt;nlog4 n)) size sample from which periodicities are identified.
facility location with hierarchical facility costs. we consider the facility location problem with hierarchical facility costs, and give a (4.236 + &epsilon;)-approximation algorithm using local search. the hierarchical facility location problem models multilevel service installation costs. shmoys, swamy and levi [13] gave an approximation algorithm for a two-level version of the problem. here we consider a multilevel problem, and give a constant factor approximation algorithm, independent of the number of levels, for the case of identical costs on all facilities.
a 4 kernel for feedback vertex set. we prove that given an undirected graph g on n vertices and an integer k, one can compute, in polynomial time in n, a graph g&prime; with at most 4k2 vertices and an integer k&prime; such that g has a feedback vertex set of size at most k iff g&prime; has a feedback vertex set of size at most k&prime;. this result improves a previous o(k11) kernel of burrage et al., and a more recent cubic kernel of bodlaender. this problem was communicated by fellows.
a fast algorithm to generate open meandric systems and meanders. an open meandric system is a planar configuration of acyclic curves crossing an infinite horizontal line in the plane such that the curves may extend in both horizontal directions. we present a fast, recursive algorithm to exhaustively generate open meandric systems with n crossings. we then illustrate how to modify the algorithm to generate unidirectional open meandric systems (the curves extend only to the right) and nonisomorphic open meandric systems where equivalence is taken under horizontal reflection. each algorithm can be modified to generate systems with exactly k curves. in the unidirectional case when k &equals; 1, we can apply a minor modification along with some additional optimization steps to yield the first fast and simple algorithm to generate open meanders.
a linear-time algorithm to find a separator in a graph excluding a minor. let g be an n-vertex m-edge graph with weighted vertices. a pair of vertex sets a, b &sube; v(g) is a 2/3-separation of order &verbar;a &cap; b&verbar; if a &cup; b &equals; v(g), there is no edge between a &minus; b and b &minus; a, and both a &minus; b and b &minus; a have weight at most 2/3 the total weight of g. let &ell; &isin; z+ be fixed. alon et al. [1990] presented an algorithm that in o(n1/2m) time, outputs either a k&ell;-minor of g, or a separation of g of order o(n1/2). whether there is a o(n + m)-time algorithm for this theorem was left as an open problem. in this article, we obtain a o(n + m)-time algorithm at the expense of a o(n2/3) separator. moreover, our algorithm exhibits a trade-off between time complexity and the order of the separator. in particular, for any given &epsi; &isin; [0,1/2], our algorithm outputs either a k&ell;-minor of g, or a separation of g with order o(n(2&minus;&epsi;)/3 in o(n1 + &epsi;+m) time. as an application we give a fast approximation algorithm for finding an independent set in a graph with no k&ell;-minor.
approximating the distance to monotonicity in high dimensions. in this article we study the problem of approximating the distance of a function f: [n]d &rarr; r to monotonicity where [n] &equals; {1,&ldots;,n} and r is some fully ordered range. namely, we are interested in randomized sublinear algorithms that approximate the hamming distance between a given function and the closest monotone function. we allow both an additive error, parameterized by &delta;, and a multiplicative error. previous work on distance approximation to monotonicity focused on the one-dimensional case and the only explicit extension to higher dimensions was with a multiplicative approximation factor exponential in the dimension d. building on goldreich et al. [2000] and dodis et al. [1999], in which there are better implicit results for the case n&equals;2, we describe a reduction from the case of functions over the d-dimensional hypercube [n]d to the case of functions over the k-dimensional hypercube [n]k, where 1&le; k&le; d. the quality of estimation that this reduction provides is linear in &lceil; d/k &rceil; and logarithmic in the size of the range &vert; r &vert; (if the range is infinite or just very large, then log &vert; r &vert; can be replaced by d log n). using this reduction and a known distance approximation algorithm for the one-dimensional case, we obtain a distance approximation algorithm for functions over the d-dimensional hypercube, with any range r, which has a multiplicative approximation factor of o(dlog &vert; r &vert;). for the case of a binary range, we present algorithms for distance approximation to monotonicity of functions over one dimension, two dimensions, and the k-dimensional hypercube (for any k&ge; 1). applying these algorithms and the reduction described before, we obtain a variety of distance approximation algorithms for boolean functions over the d-dimensional hypercube which suggest a trade-off between quality of estimation and efficiency of computation. in particular, the multiplicative error ranges between o(d) and o(1).
a near-optimal algorithm for estimating the entropy of a stream. we describe a simple algorithm for approximating the empirical entropy of a stream of m values up to a multiplicative factor of (1+&epsi;) using a single pass, o(&epsi;&minus;2 log (&delta;&minus;1) log m) words of space, and o(log &epsi;&minus;1 + log log &delta;&minus;1 + log log m) processing time per item in the stream. our algorithm is based upon a novel extension of a method introduced by alon et al. [1999]. this improves over previous work on this problem. we show a space lower bound of &omega;(&epsi;&minus;2/log2 (&epsi;&minus;1)), demonstrating that our algorithm is near-optimal in terms of its dependency on &epsi;. we show that generalizing to multiplicative-approximation of the kth-order entropy requires close to linear space for k&ge;1. in contrast we show that additive-approximation is possible in a single pass using only poly-logarithmic space. lastly, we show how to compute a multiplicative approximation to the entropy of a random walk on an undirected graph.
approximating corridors and tours via restriction and relaxation techniques. given a rectangular boundary partitioned into rectangles, the minimum-length corridor (mlc-r) problem consists of finding a corridor of least total length. a corridor is a set of connected line segments, each of which must lie along the line segments that form the rectangular boundary and/or the boundary of the rectangles, and must include at least one point from the boundary of every rectangle and from the rectangular boundary. the mlc-r problem is known to be np-hard. we present the first polynomial-time constant ratio approximation algorithm for the mlc-r and mlck problems. the mlck problem is a generalization of the mlc-r problem where the rectangles are rectilinear c-gons, for c &le; k and k is a constant. we also present the first polynomial-time constant ratio approximation algorithm for the group traveling salesperson problem (gtsp) for a rectangular boundary partitioned into rectilinear c-gons as in the mlck problem. our algorithms are based on the restriction and relaxation approximation techniques.
an approximation algorithm for the maximum leaf spanning arborescence problem. we present an o(&sqrt;opt)-approximation algorithm for the maximum leaf spanning arborescence problem, where opt is the number of leaves in an optimal spanning arborescence. the result is based upon an o(1)-approximation algorithm for a special class of directed graphs called willows. incorporating the method for willow graphs as a subroutine in a local improvement algorithm gives the bound for general directed graphs.
adaptive sampling strategies for quickselects. quickselect with median-of-3 is largely used in practice and its behavior is fairly well understood. however, the following natural adaptive variant, which we call proportion-from-3, had not been previously analyzed: &ldquo;choose as pivot the smallest of the sample if the relative rank of the sought element is below 1/3, the largest if the relative rank is above 2/3, and the median if the relative rank is between 1/3 and 2/3.&rdquo; we first analyze the average number of comparisons made when using proportion-from-2 and then for proportion-from-3. we also analyze &nu;-find, a generalization of proportion-from-3 with interval breakpoints at &nu; and 1-&nu;. we show that there exists an optimal value of &nu; and we also provide the range of values of &nu; where &nu;-find outperforms median-of-3. then, we consider the average total cost of these strategies, which takes into account the cost of both comparisons and exchanges. our results strongly suggest that a suitable implementation of &nu;-find could be the method of choice in a practical setting. we also study the behavior of proportion-from-s with s>3 and in particular we show that proportion-from-s-like strategies are optimal when s&rarr;&infin;.
achieving anonymity via clustering. publishing data for analysis from a table containing personal records, while maintaining individual privacy, is a problem of increasing importance today. the traditional approach of deidentifying records is to remove identifying fields such as social security number, name, etc. however, recent research has shown that a large fraction of the u.s. population can be identified using nonkey attributes (called quasi-identifiers) such as date of birth, gender, and zip code. the k-anonymity model protects privacy via requiring that nonkey attributes that leak information are suppressed or generalized so that, for every record in the modified table, there are at least k&minus;1 other records having exactly the same values for quasi-identifiers. we propose a new method for anonymizing data records, where quasi-identifiers of data records are first clustered and then cluster centers are published. to ensure privacy of the data records, we impose the constraint that each cluster must contain no fewer than a prespecified number of data records. this technique is more general since we have a much larger choice for cluster centers than k-anonymity. in many cases, it lets us release a lot more information without compromising privacy. we also provide constant factor approximation algorithms to come up with such a clustering. this is the first set of algorithms for the anonymization problem where the performance is independent of the anonymity parameter k. we further observe that a few outlier points can significantly increase the cost of anonymization. hence, we extend our algorithms to allow an &epsi; fraction of points to remain unclustered, that is, deleted from the anonymized publication. thus, by not releasing a small fraction of the database records, we can ensure that the data published for analysis has less distortion and hence is more useful. our approximation algorithms for new clustering objectives are of independent interest and could be applicable in other clustering scenarios as well.
clustering for metric and nonmetric distance measures. we study a generalization of the k-median problem with respect to an arbitrary dissimilarity measure d. given a finite set p of size n, our goal is to find a set c of size k such that the sum of errors d(p,c) &equals; &sum;p &in; p minc &in; c {d(p,c)} is minimized. the main result in this article can be stated as follows: there exists a (1+&epsis;)-approximation algorithm for the k-median problem with respect to d, if the 1-median problem can be approximated within a factor of (1+&epsis;) by taking a random sample of constant size and solving the 1-median problem on the sample exactly. this algorithm requires time n2o(mklog(mk/&epsis;)), where m is a constant that depends only on &epsis; and d. using this characterization, we obtain the first linear time (1+&epsis;)-approximation algorithms for the k-median problem in an arbitrary metric space with bounded doubling dimension, for the kullback-leibler divergence (relative entropy), for the itakura-saito divergence, for mahalanobis distances, and for some special cases of bregman divergences. moreover, we obtain previously known results for the euclidean k-median problem and the euclidean k-means problem in a simplified manner. our results are based on a new analysis of an algorithm of kumar et al. [2004].
geodesic delaunay triangulations in bounded planar domains. we introduce a new feature size for bounded domains in the plane endowed with an intrinsic metric. given a point x in a domain x, the systolic feature size of x at x measures half the length of the shortest loop through x that is not null-homotopic in x. the resort to an intrinsic metric makes the systolic feature size rather insensitive to the local geometry of the domain, in contrast with its predecessors (local feature size, weak feature size, homology feature size). this reduces the number of samples required to capture the topology of x, provided that a reliable approximation to the intrinsic metric of x is available. under sufficient sampling conditions involving the systolic feature size, we show that the geodesic delaunay triangulation dx(l) of a finite sampling l is homotopy equivalent to x. under similar conditions, dx(l) is sandwiched between the geodesic witness complex cwx(l) and a relaxed version cwx,&nu;(l). in the conference version of the article, we took advantage of this fact and proved that the homology of dx(l) (and hence the one of x) can be retrieved by computing the persistent homology between cwx(l) and cwx,&nu;(l). here, we investigate further and show that the homology of x can also be recovered from the persistent homology associated with inclusions of type cwx,&nu;(l)&rarrhk;cwx,&nu;&prime;(l), under some conditions on the parameters &nu;&le;&nu;&prime;. similar results are obtained for vietoris-rips complexes in the intrinsic metric. the proofs draw some connections with recent advances on the front of homology inference from point cloud data, but also with several well-known concepts of riemannian (and even metric) geometry. on the algorithmic front, we propose algorithms for estimating the systolic feature size of a bounded planar domain x, selecting a landmark set of sufficient density, and computing the homology of x using geodesic witness complexes or rips complexes.
finding equitable convex partitions of points in a polygon efficiently. previous work has developed algorithms for finding an equitable convex partition that partitions the plane into n convex pieces each containing an equal number of red and blue points. motivated by a vehicle routing heuristic, we look at a related problem where each piece must contain one point and an equal fraction of the area of some convex polygon. we first show how algorithms for solving the older problem lead to approximate solutions for this new equitable convex partition problem. then we demonstrate a new algorithm that finds an exact solution to our problem in o(n nlog n) time or operations, where n is the number of points, m the number of vertices or edges of the polygon, and n:&equals;n+m the sum.
nondecreasing paths in a weighted graph or: how to optimally read a train schedule. a travel booking office has timetables giving arrival and departure times for all scheduled trains, including their origins and destinations. a customer presents a starting station and demands a route with perhaps several train connections taking him to his destination as early as possible. the booking office must find the best route for its customers. this problem was first considered in the theory of algorithms by minty [1958], who reduced it to a problem on directed edge-weighted graphs: find a path from a given source to a given target such that the consecutive weights on the path are nondecreasing and the last weight on the path is minimized. minty gave the first algorithm for the single-source version of the problem, in which one finds minimum last weight nondecreasing paths from the source to every other vertex. in this article we give the first linear-time algorithm for this problem in the word-ram model of computation. we also define an all-pairs version for the problem and give a strongly polynomial truly subcubic algorithm for it. finally, we discuss an extension of the problem in which one also has prices on trip segments and one wishes to find a cheapest valid itinerary.
mind change complexity of inferring unbounded unions of restricted pattern languages from positive data. this paper shows that the mind change complexity of inferring from positive data the class of unbounded unions of languages of regular patterns with constant segment length bound is of the form @w^@w^^^@a+@b, assuming that the patterns are defined over a finite alphabet containing at least two elements. here @a and @b are natural numbers, and we give tight bounds on their values based on the length of the constant segments and the size of the alphabet of the pattern languages. this is, to the authors' knowledge, the first time a natural class of languages has been shown to be inferable with mind change complexity above @w^@w. the proof uses the notion of closure operators on a class of languages, and also uses the order type of well-partial-orderings to obtain a mind change bound. the inference algorithm presented can be easily applied to a wide range of classes of languages. finally, we show an interesting connection between proof theory and mind change complexity.
comparing free algebras in topological and classical domain theory. we compare how computational effects are modelled in classical domain theory and topological domain theory. both of these theories provide powerful toolkits for denotational semantics: classical domain theory having been introduced by scott, and well established and developed since; topological domain theory being a generalization in which topologies more general than the scott-topology are admitted. computational effects can be modelled using free algebra constructions, according to plotkin and power, and we show that for a wide range of computational effects, including all the classical powerdomains, this free algebra construction coincides in classical and topological domain theory, when restricted to countably-based continuous domains.
symbolic protocol analysis in the union of disjoint intruder theories: combining decision procedures. most of the decision procedures for symbolic analysis of protocols are limited to a fixed set of algebraic operators associated with a fixed intruder theory. examples of such sets of operators comprise xor, multiplication, abstract encryption/decryption. in this report we give an algorithm for combining decision procedures for arbitrary intruder theories with disjoint sets of operators, provided that solvability of ordered intruder constraints, a slight generalization of intruder constraints, can be decided in each theory. this is the case for most of the intruder theories for which a decision procedure has been given. in particular our result allows us to decide trace-based security properties of protocols that employ any combination of the above mentioned operators with a bounded number of sessions.
alternating states for dual nondeterminism in imperative programming. the refinement calculus of back, morgan, morris, and others is based on monotone predicate transformers (weakest preconditions) where conjunctions stand for demonic choices between commands and disjunctions for angelic choices. arbitrary monotone predicate transformers cannot be modelled by relational semantics but can be modelled by so-called multirelations. results of morris indicate, however, that the natural domain for the combination of demonic and angelic choice is the free distributive completion (fdc) of the state space. the present paper provides a new axiomatization and more explicit construction of the fdc of an arbitrary ordered set. the fdc concept is self-dual, but the construction is not. we therefore determine the duality function from the fdc to the dual of the fdc of the dual ordered set. the elements of the fdc are classified according to their conjunctivity and disjunctivity. the theory is applied to imperative programming with operators for sequential composition and demonic and angelic choice. the theory based on the fdc is shown to be equivalent to a weakest precondition theory for up-closed predicates. if the order is discrete (i.e., the equality relation), the fdc turns out to be the domain of the choice semantics of back and von wright, whereas up-closed multirelations are functions towards this domain.
parameterized algorithms for d-hitting set: the weighted case. we are going to analyze search tree algorithms for weightedd-hitting set. although the algorithms that we develop are fairly simple, their analysis is technically involved. we compare the weighted case with the previously analyzed unweighted one, exhibiting that the advantage of the unweighted case dwindles with growing d.
on decision problems for parameterized machines. in this paper, we investigate various decision problems concerning parameterized versions of some classes of machines. let c(s,m,t) be the class of nondeterministic multitape turing machine (tm) acceptors with a two-way read-only input, at most s states, at most m read-write worktapes, and at most t symbols in the worktape alphabet, where s,m,t are fixed positive integers. there is no restriction on the cardinality of the input alphabet. we are able to show the emptiness, disjointness, and universe (also called universality) problems to be decidable for c(s,m,t). for the class consisting of machines in c(s,m,t) that always halt or whose minimal-time accepting computations can be bounded by some recursive function f(n) (where n is the input length), the containment and equivalence problems are decidable. these results hold for other machines, e.g., when the worktapes are pushdown stacks (where on every step, each pushdown can only pop the top of the stack or replace the top of the stack by at most two symbols) or when stacks are counters (where on every step, a counter can be incremented by 1, decremented by 1, or remain unchanged, and can be tested for zero). our results are the best possible in the sense that not parameterizing one of s,m,t (or, in the case of counter machines, allowing the counters to increment by arbitrary integers that may change from machines to machines) makes the universe problem undecidable. we also give a simple characterization of the languages defined by c(s,m,t). finally, we investigate the applicability of our techniques to machines with multiple input heads or multiple input tapes.
non-cooperative facility location and covering games. we consider a general class of non-cooperative games related to combinatorial covering and facility location problems. a game is based on an integer programming formulation of the corresponding optimization problem, and each of the k players wants to satisfy a subset of the constraints. for that purpose, resources available in integer units must be bought, and their cost can be shared arbitrarily between players. we consider the existence and cost of exact and approximate pure-strategy nash equilibria. in general, the prices of anarchy and stability are in @q(k) and deciding the existence of a pure nash equilibrium is np-hard. under certain conditions, however, cheap nash equilibria exist, in particular if the integrality gap of the underlying integer program is 1, or in the case of single constraint players. we also present algorithms that compute simultaneously near-stable and near-optimal approximate nash equilibria in polynomial time.
playing monotone games to understand learning behaviors. we deal with a special class of games against nature which correspond to subsymbolic learning problems where we know a local descent direction in the error landscape but not the amount gained at each step of the learning procedure. namely, alice and bob play a game where the probability of victory grows monotonically by unknown amounts with the resources each employs. for a fixed effort on alice's part bob increases his resources on the basis of the results of the individual contests (victory, tie or defeat). quite unlike the usual ones in game theory, his aim is to stop as soon as the defeat probability goes under a given threshold with high confidence. we adopt such a game policy as an archetypal remedy to the general overtraining threat of learning algorithms. namely, we deal with the original game in a computational learning framework analogous to the probably approximately correct formulation. therein, a wise use of a special inferential mechanism (known as twisting argument) highlights relevant statistics for managing different trade-offs between observability and controllability of the defeat probability. with similar statistics we discuss an analogous trade-off at the basis of the stopping criterion of subsymbolic learning procedures. as a conclusion, we propose a principled stopping rule based solely on the behavior of the training session, hence without distracting examples into a test set.
minimizing the makespan on a single parallel batching machine. in this paper, we consider the problem of scheduling with release dates and rejection on a single parallel batching machine, where the jobs have non-identical sizes. our objective is to minimize the makespan of the accepted jobs plus the total penalty of the rejected jobs. first, we give a polynomial time approximation scheme (ptas) for the case where jobs can be split. then, we propose a 2-approximation algorithm for the special case with identical release dates. finally, we present an approximation algorithm for the general problem with worst-case ratio 2+@e, where @e>0 is an arbitrarily small constant.
rotations in the stable b-matching problem. this paper deals with the stable b-matching problem on general multigraphs. we generalize the notion of singular and dual rotations and establish a one-one correspondence between stable b-matchings and certain sets of rotations. this correspondence is used to find all stable edges and a minimum regret stable b-matching in polynomial time. we also recall the np-completeness of the egalitarian stable b-matching problem.
efficient enumeration of all ladder lotteries and its application. a ladder lottery, known as ''amidakuji'' in japan, is a common way to choose a permutation randomly. a ladder lottery l corresponding to a given permutation @p is optimal if l has the minimum number of horizontal lines among the ladder lotteries corresponding to @p. in this paper we show that for any two optimal ladder lotteries l"1 and l"2 of a permutation, there exists a sequence of local modifications which transforms l"1 into l"2. we also give an algorithm to enumerate all optimal ladder lotteries of a given permutation. by setting @p=(n,n-1,...,1), the algorithm enumerates all arrangements of n pseudolines efficiently. by implementing the algorithm we compute the number of arrangements of n pseudolines for each n@?11.
infinite labeled trees: from rational to sturmian trees. this paper studies infinite unordered d-ary trees with nodes labeled by {0,1}. we introduce the notions of rational and sturmian trees along with the definitions of (strongly) balanced trees and mechanical trees, and study the relations among them. in particular, we show that (strongly) balanced trees exist and coincide with mechanical trees in the irrational case, providing an effective construction. such trees also have a minimal factor complexity, hence are sturmian. we also give several examples illustrating the inclusion relations between these classes of trees.
arrows for secure information flow. this paper presents an embedded security sublanguage for enforcing information-flow policies in the standard haskell programming language. the sublanguage provides useful information-flow control mechanisms including dynamic security lattices, run-time code privileges and declassification all without modifying the base language. this design avoids the redundant work of producing new languages, lowers the threshold for adopting security-typed languages, and also provides great flexibility and modularity for using security-policy frameworks. the embedded security sublanguage is designed using a standard combinator interface called arrows. computations constructed in the sublanguage have static and explicit control-flow components, making it possible to implement information-flow control using static-analysis techniques at run time, while providing strong security guarantees. this paper presents a formal proof that our embedded sublanguage provides noninterference, a concrete haskell implementation and an example application demonstrating the proposed techniques.
on the expressiveness of interaction. subbisimilarity is proposed as a general tool to classify the relative expressive power of process calculi. the expressiveness of several variants of ccs is compared in terms of the subbisimilarity relationship. similar investigation is also carried out for the variants of the pi calculus. the relative expressiveness of the different forms of the choice operation and the different ways of introducing infinite behaviors are systematically studied in both the frameworks of ccs and pi. some issues concerning the expressiveness of both ccs and pi are clarified. several open problems are solved along the way. the subbisimilarity approach and the relative expressiveness results are applied to show the independence of the operators of the pi calculus. the definition of the subbisimilarity relationship can be further strengthened with computational requirement, leading to a uniform treatment of computation and interaction.
transducers for the bidirectional decoding of prefix codes. we construct a transducer for the bidirectional decoding of words encoded by the method introduced by girod (1999) in [5] and we prove that it is bideterministic and that it can be used both for the left-to-right and the right-to-left decoding. we also give a similar construction for a transducer that decodes in both directions words encoded by a generalization of girod's encoding method. we prove that it has the same properties as those of the previous transducer. in addition we show that it has a single initial/final state and that it is minimal.
bounded sequence testing from deterministic finite state machines. the w- andwp-methods are the basis for conformance testing from a deterministic finite state machine (dfsm) when the conformance relation considered is equivalence. however, many dfsm applications use only input sequences of limited length. in such cases, the test data only need to establish that the implementation under test produces the specified responses for sequences of length less than or equal to the upper bound l. this paper extends the w- and wp-methods to the case in which only bounded sequences are allowed. the methods for bounded sequences are stronger than the originals since test suites for the unbounded case can be obtained as a particular case (in which the upper bound l is sufficiently large) from the new formulae. furthermore, the generalization is not straightforward as it is not sufficient to extract the sequences of length at most l from the test suites produced in the unbounded case, or even all prefixes of length at most l of the original test sequences. the practicality of the methods is also improved in comparison to the unbounded case: the size of the test suites may be considerably reduced while the complexity of the test generation algorithms remains basically unchanged.
average long-lived binary consensus: quantifying the stabilizing role played by memory. consider a system composed of n sensors operating in synchronous rounds. in each round an input vector of sensor readings x is produced, where the i-th entry of x is a binary value produced by the i-th sensor. the sequence of input vectors is assumed to be smooth: exactly one entry of the vector changes from one round to the next one. the system implements a fault-tolerant averaging consensus functionf. this function returns, in each round, a representative output valuev of the sensor readings x. assuming that at most t entries of the vector can be erroneous, f is required to return a value that appears at least t+1 times in x. we introduce the definition of instability of the system, which consists in the number of output changes over a random sequence of input vectors. we first design optimal (with respect to the instability measure) consensus systems: d"0 without memory, and d"1 with memory. then we quantify the gain factor due to memory by computing c"n(t), the number of decision changes performed by d"0 per decision change performed by d"1.
accepting splicing systems. in this paper, we propose a novel approach to splicing systems, namely we consider them as accepting devices. two ways of iterating the splicing operation and two variants of accepting splicing system are investigated. altogether, we obtain four models, which are compared with each other as well as with the generating splicing systems from the computational power point of view. several decision problems concerning the accepting splicing systems are discussed.
an operational semantics for a calculus for wireless systems. in wireless systems, the communication mechanism combines features of broadcast, synchrony, and asynchrony. we develop an operational semantics for a calculus of wireless systems. we present different reduction semantics and a labelled transition semantics and prove correspondence results between them. finally, we apply cws to the modelling of the alternating bit protocol, and prove a simple correctness result as an example of the kind of properties that can be formalized in this framework. a major goal of the semantics is to describe the forms of interference among the activities of processes that are peculiar of wireless systems. such interference occurs when a location is simultaneously reached by two transmissions. the reduction semantics differ on how information about the active transmissions is managed. we use the calculus to describe and analyse a few properties of a version of the alternating bit protocol.
hyperbolicity of the fixed point set for the simple genetic algorithm. we study an infinite population model for the genetic algorithm, where the iteration of the algorithm corresponds to an iteration of a map g. the map g is a composition of a selection operator and a mixing operator, where the latter models effects of both mutation and crossover. we examine the hyperbolicity of fixed points of this model. we show that for a typical mixing operator all the fixed points are hyperbolic.
computing the graph-based parallel complexity of gene assembly. we consider a graph-theoretical formalization of the process of gene assembly in ciliates introduced in ehrenfeucht et al. (2003) [3], where a gene is modeled as a signed graph. the gene assembly, based on three types of operations only, is then modeled as a graph reduction process (to the empty graph). motivated by the robustness of the gene assembly process, the notions of parallel reduction and parallel complexity of signed graphs have been considered in harju et al. (2006) [7]. we describe in this paper an exact algorithm for computing the parallel complexity of a given signed graph and for finding an optimal parallel reduction for it. checking the parallel applicability of a given set of operations and scanning all possible selections amount to a high computational complexity. we also briefly discuss a faster approximate algorithm that however, cannot guarantee finding the optimal reduction.
euclidean tsp on two polygons. we give an o(n^2m+nm^2+m^2logm) time and o(n^2+m^2) space algorithm for finding the shortest traveling salesman tour through the vertices of two simple polygonal obstacles in the euclidean plane, where n and m are the number of vertices of the two polygons. by obstacle, we mean that the tour may not cross between the interior and exterior of either polygon. we also consider the problem's extension to higher dimensions, proving that, if p
hybrid automata, reachability, and systems biology. hybrid automata are a powerful formalism for the representation of systems evolving according to both discrete and continuous laws. unfortunately, undecidability soon emerges when one tries to automatically verify hybrid automata properties. an important verification problem is the reachability one that demands to decide whether a set of points is reachable from a starting region. if we focus on semi-algebraic hybrid automata the reachability problem is semi-decidable. however, high computational costs have to be afforded to solve it. we analyse this problem by exploiting some existing tools and we show that even simple examples cannot be efficiently solved. it is necessary to introduce approximations to reduce the number of variables, since this is the main source of runtime requirements. we propose some standard approximation methods based on taylor polynomials and ad hoc strategies. we implement our methods within the software saha-tool and we show their effectiveness on two biological examples: the repressilator and the delta-notch protein signaling.
on the complexity of finding chordless paths in bipartite graphs and some interval operators in graphs and hypergraphs. in this paper we show that the problem of finding a chordless path between a vertex s and a vertex t containing a vertex v remains np-complete in bipartite graphs, thereby strengthening the previous results on the same problem. we show a relation between this problem and two interval operators: the simple path interval operator in hypergraphs and the even-chorded path interval operator in graphs. we show that the problem of computing the two mentioned intervals is np-complete.
translating propositional extended conjunctions of horn clauses into boolean circuits. horn^@? is a logic programming language which extends usual horn clauses by adding intuitionistic implication in goals and clause bodies. this extension can be seen as a way of structuring programs in logic programming. we are interested in finding correct and efficient translations from horn^@? programs into some representation type that, preserving the signature, allows us suitable implementations of these kinds of programs. in this paper we restrict to the propositional setting of horn^@? and we study correct translations into boolean circuits, i.e. graphs; into boolean formulas, i.e. trees; and into conjunctions of propositional horn clauses. different results for the efficiencies of the transformations are obtained in the three cases.
quantum circuit oracles for abstract machine computations. this paper considers a very general model of computation via conditional iteration, the abstract machines of hines (2008) [23], and studies the conditions under which these describe reversible computations. using this, we demonstrate how to construct quantum circuits that act as oracles for these abstract machines. for a classical computation with worst-case performance t, the resulting quantum circuit requires an ancilla of 1+log(t) qubits, and takes o(t) steps. the ancilla starts and finishes in the constant state |0>, so garbage collection is performed automatically.
the complexity of the hajós calculus for planar graphs. the planar hajos calculus is the hajos calculus with the restriction that all the graphs that appear in the construction (including a final graph) must be planar. we prove that the planar hajos calculus is polynomially bounded iff the hajos calculus is polynomially bounded.
chromatic index of graphs with no cycle with a unique chord. the class c of graphs that do not contain a cycle with a unique chord was recently studied by trotignon and vuskovic (in press) [23], who proved for these graphs strong structure results which led to solving the recognition and vertex-colouring problems in polynomial time. in the present paper, we investigate how these structure results can be applied to solve the edge-colouring problem in the class. we give computational complexity results for the edge-colouring problem restricted to c and to the subclass c^' composed of the graphs of c that do not have a 4-hole. we show that it is np-complete to determine whether the chromatic index of a graph is equal to its maximum degree when the input is restricted to regular graphs of c with fixed degree @d>=3. for the subclass c^', we establish a dichotomy: if the maximum degree is @d=3, the edge-colouring problem is np-complete, whereas, if @d=3, for r>=3.
simple algorithms for minimal triangulation of a graph and backward selection of a decomposable markov network. in this paper we propose a simple algorithm called cliquemintriang for computing a minimal triangulation of a graph. if f is the set of edges that is added to g to make it a complete graph k"n then the asymptotic complexity of cliquemintriang is o(|f|(@d^2+|f|)) where @d is the degree of the subgraph of k"n induced by f. therefore our algorithm performs well when g is a dense graph. we also show how to exploit the existing minimal triangulation techniques in conjunction with cliquemintriang to efficiently find a minimal triangulation of nondense graphs. finally we show how the algorithm can be adapted to perform a backward stepwise selection of decomposable markov networks; the resulting procedure has the same time complexity as that of existing similar algorithms.
two-group knapsack game. this paper presents a ''two-group knapsack game''. a number of investors colligate into two groups to bid on a common pool of potential projects. each investor has his/her own budget limit and a cost estimation for undertaking each possible project. each group represents a power by its market share. associated with each project, there is a potential profit that can be realized. investors in the same group hold an internal agreement of putting the group's collective interest ahead of the individual's interest and not bidding on the same project by more than one investor in the group. the profit of a particular project can be wholly taken by the sole bidder or shared proportionally by two bidders in different groups according to their group power. the objective of each group may be based not only on its own group profit but also on the other group's profit. assuming that each investor acts in a selfish manner with the best response to optimize its group's objective subject to the budget constraint, we show that a pure nash equilibrium exists under certain conditions. we also have some interesting findings of the ''price of anarchy'' (the ratio of the worst nash equilibrium to the social optimum) associated with a simplified version of the two-group knapsack game with three investors.
semigroup automata with rational initial and terminal sets. we consider a natural extension of the usual definition of m-automata (also known as extended automata or valence automata) which permits the automaton to utilise more of the structure of each monoid, and additionally allows us to define s-automata for s an arbitrary semigroup. in the monoid case, the resulting automata are equivalent to the valence automata with rational target sets which arise in the theory of regulated rewriting systems. we study these automata in the case where the register semigroup is completely simple or completely 0-simple, obtaining a complete characterisation of the classes of languages corresponding to such semigroups, in terms of their maximal subgroups. in the process, we obtain a number of results about rational subsets of rees matrix semigroups which are likely to be of independent interest.
pursuing a fast robber on a graph. the cops and robbers game as originally defined independently by quilliot and by nowakowski and winkler in the 1980s has been much studied, but very few results pertain to the algorithmic and complexity aspects of it. in this paper we prove that computing the minimum number of cops that are guaranteed to catch a robber on a given graph is np-hard and that the parameterized version of the problem is w[2]-hard; the proof extends to the case where the robber moves s time faster than the cops. we show that on split graphs, the problem is polynomially solvable if s=1 but is np-hard if s=2. we further prove that on graphs of bounded cliquewidth the problem is polynomially solvable for s@?2. finally, we show that for planar graphs the minimum number of cops is unbounded if the robber is faster than the cops.
analysis of particle interaction in particle swarm optimization. in this paper, we analyze the behavior of particle swarm optimization (pso) on the facet of particle interaction. we firstly propose a statistical interpretation of particle swarm optimization in order to capture the stochastic behavior of the entire swarm. based on the statistical interpretation, we investigate the effect of particle interaction by focusing on the social-only model and derive the upper and lower bounds of the expected particle norm. accordingly, the lower and upper bounds of the expected progress rate on the sphere function are also obtained. furthermore, the sufficient and necessary condition for the swarm to converge is derived to demonstrate the pso convergence caused by the effect of particle interaction.
codes and maximal monoids. some results are given on maximal monoids in the language of the soficsystem generated by a finite code of words.
on the problem of freeness of multiplicative matrix semigroups. the following problem looking as a high-school exercise hides an unexpected difficulty. do the matrices a=(2003)andb=(3505) satisfy any nontrivial equation with the multiplication symbol only? this problem was mentioned as open in cassaigne et al. [j. cassaigne, t. harju, j. karhumaki, on the undecidability of freeness of matrix semigroups, internat. j. algebra comput. 9 (3-4) (1999) 295-305] and in a book by blondel et al. [v. blondel, j. cassaigne, j. karhumaki, problem 10.3: freeness of multiplicative matrix semigroups, in: v. blondel, a. megretski (eds.), unsolved problems in mathematical systems and control theory, princeton university press, 2004, pp. 309-314] as an intriguing instance of a natural computational problem of deciding whether a given finitely generated semigroup of 2x2 matrices is free. in this paper we present a new partial algorithm for the latter which, in particular, easily finds that the following equation ab^1^0a^2ba^2ba^1^0=b^2a^6b^2a^2bababa^2b^2a^2bab^2 holds for the matrices above. our algorithm turns out quite practical and allows us to settle also other related open questions posed in the mentioned article.
a hierarchical strongly aperiodic set of tiles in the hyperbolic plane. we give a new construction of strongly aperiodic set of tiles in h^2, exhibiting a kind of hierarchical structure, simplifying the central framework of margenstern's proof that the domino problem is undecidable in the hyperbolic plane (margenstern (2008) [16]).
analyzing the dynamics of stigmergetic interactions through pheromone games. the concept of stigmergy provides a simple framework for interaction and coordination in multi-agent systems. however, determining the global system behavior that will arise from local stigmergetic interactions is a complex problem. in this paper we propose to use game theory to analyze stigmergetic interactions. we show that a system where agents coordinate by sharing local pheromone information can be approximated by a limiting pheromone game in which different pheromone vectors represent player strategies. this game view allows us to use established methods and solution concepts from game theory to describe the properties of stigmergy based systems. our goal is to provide a new framework to aid in the understanding and design of pheromone interactions. we demonstrate how we can use this system to determine the long term system behavior of a simple pheromone model, by analyzing the convergence properties of the pheromone update rule in the approximating game. we also apply this model to cases where multiple colonies of agents concurrently optimize different objectives. in this case a limiting colony game can be linked to colony level interactions to characterize the global system behavior.
an exact correspondence between a typed pi-calculus and polarised proof-nets. this paper presents an exact correspondence in typing and dynamics between polarised linear logic and a typed @p-calculus based on io-typing. the respective incremental constraints, one on geometric structures of proof-nets and one based on types, precisely correspond to each other, leading to the exact correspondence of the respective formalisms as they appear in olivier laurent (2003) [27] (for proof-nets) and kohei honda et al. (2004) [24] (for the @p-calculus).
a polynomial solution to the k-fixed-endpoint path cover problem on proper interval graphs. we study a variant of the path cover problem, namely, the k-fixed-endpoint path cover problem, or kpc for short. given a graph g and a subset t of k vertices of v(g), a k-fixed-endpoint path cover of g with respect to t is a set of vertex-disjoint paths p that covers the vertices of g such that the k vertices of t are all endpoints of the paths in p. the kpc problem is to find a k-fixed-endpoint path cover of g of minimum cardinality; note that, if t is empty (or, equivalently, k=0), the stated problem coincides with the classical path cover problem. the kpc problem generalizes some path cover related problems, such as the 1hp and 2hp problems, which have been proved to be np-complete. note that the complexity status for both 1hp and 2hp problems on interval graphs remains an open question (damaschke (1993) [9]). in this paper, we show that the kpc problem can be solved in linear time on the class of proper interval graphs, that is, in o(n+m) time on a proper interval graph on n vertices and m edges. the proposed algorithm is simple, requires linear space, and also enables us to solve the 1hp and 2hp problems on proper interval graphs within the same time and space complexity.
on the undecidability of the limit behavior of cellular automata. cellular automata (ca) are discrete dynamical systems and an abstract model of parallel computation. the limit set of a cellular automaton is its maximal topological attractor. a well-known result, due to kari, says that all nontrivial properties of limit sets are undecidable. in this paper we consider the properties of limit set dynamics, i.e. properties of the dynamics of ca restricted to their limit sets. there can be no equivalent of kari's theorem for limit set dynamics. anyway we show that there is a large class of undecidable properties of limit set dynamics, namely all properties of limit set dynamics which imply stability or the existence of a unique subshift attractor. as a consequence we have that it is undecidable whether the cellular automaton map restricted to the limit set is the identity map and whether it is closing, injective, expansive, positively expansive and transitive.
query-based verification of qualitative trends and oscillations in biochemical systems. we investigate the application of query-based verification to the analysis of behavioural trends of stochastic models of biochemical systems. we derive temporal logic properties which address specific behavioural questions, such as the likelihood for a species to reach a peak/deadlock state, or to exhibit monotonic/oscillatory trends. we introduce a specific modelling convention through which stochastic models of biochemical systems are made suitable to verification of the behavioural queries we define. based on the queries we identify, we define a classification procedure which, given a stochastic model, allows for identifying meaningful qualitative behavioural trends. we illustrate the proposed query-based classification on a number of simple abstract models of biochemical systems.
optimal bounds on finding fixed points of contraction mappings. the banach fixed-point theorem states that a contraction mapping on a complete metric space has a unique fixed point. given an oracle access to a finite metric space (m,d) and a contraction mapping f:m->m on it, we show that the fixed point of f can be found with an expected o(|m|) oracle queries. we also show that every randomized algorithm for finding a fixed point must make an expected @w(|m|) oracle queries to (m,d) and f for some finite metric space (m,d) and some contraction mapping f:m->m on it. as a generalization of the banach fixed-point theorem, the caristi-kirk fixed-point theorem gives weaker conditions on (m,d) and f guaranteeing the existence of a fixed point of f. we show that every randomized algorithm that finds a fixed point must make the expected @w(|m|) oracle queries to (m,d) and f for some finite metric space (m,d) and some function f:m->m satisfying the conditions of the caristi-kirk fixed-point theorem.
gödel's system tau revisited. the linear lambda calculus, where variables are restricted to occur in terms exactly once, has a very weak expressive power: in particular, all functions terminate in linear time. in this paper we consider a simple extension with natural numbers and a restricted iterator: only closed linear functions can be iterated. we show properties of this linear version of godel's tusing a closed reduction strategy, and study the class of functions that can be represented. surprisingly, this linear calculus offers a huge increase in expressive power over previous linear versions of t, which are 'closed at construction' rather than 'closed at reduction'. we show that a linear twith closed reduction is as powerful as t.
stability analysis of the reproduction operator in bacterial foraging optimization. in his seminal paper published in 2002, passino pointed out how individual and groups of bacteria forage for nutrients and how to model it as a distributed optimization process, which he named the bacterial foraging optimization algorithm (bfoa). one of the major operators of bfoa is the reproduction phenomenon of virtual bacteria, each of which models one trial solution of the optimization problem. during reproduction, the least healthy bacteria (with a lower accumulated value of the objective function in one chemotactic lifetime) die and the other healthier bacteria each split into two, which then starts exploring the search place from the same location. the phenomenon has a direct analogy with the selection mechanism of classical evolutionary algorithms. this paper attempts to model reproduction as a dynamics and then analyses the stability of the reproductive system very near to an equilibrium point, which in this case is an isolated optimum. it also finds conditions under which a stable reproduction event can take place, to direct a worse bacterium towards a better one. our analysis reveals that a stable reproduction event contributes to the quick convergence of the bacterial population near optima.
hybrid dynamics of stochastic programs. we provide stochastic concurrent constraint programming (sccp), a stochastic process algebra based on ccp, with a semantics in terms of hybrid automata. we associate with each sccp program both a stochastic and a non-deterministic hybrid automaton. then, we compare such automata with the standard stochastic semantics (given by a continuous time markov chain) and the one based on ordinary differential equations, obtained by a fluid-flow approximation technique. we discuss in detail two case studies: repressilator and the circadian clock, with particular regard to the robustness exhibited by the different semantic models and to the effect of discreteness in dynamical evolution of such systems.
using abstract interpretation to add type checking for interfaces in java bytecode verification. java interface types support multiple inheritance. because of this, the standard bytecode verifier ignores them, since it is not able to model the class hierarchy as a lattice. thus, type checks on interfaces are performed at run time. we propose a verification methodology that removes the need for run-time checks. the methodology consists of: (1) an augmented verifier that is very similar to the standard one, but is also able to check for interface types in most cases; (2) for all other cases, a set of additional simpler verifiers, each one specialized for a single interface type. we obtain these verifiers in a systematic way by using abstract interpretation techniques. finally, we describe an implementation of the methodology and evaluate it on a large set of benchmarks.
a trajectory-based strict semantics for program slicing. we define a program semantics that is preserved by dependence-based slicing algorithms. it is a natural extension, to non-terminating programs, of the semantics introduced by weiser (which only considered terminating ones) and, as such, is an accurate characterisation of the semantic relationship between a program and the slice produced by these algorithms. unlike other approaches, apart from weiser's original one, it is based on strict standard semantics which models the 'normal' execution of programs on a von neumann machine and, thus, has the advantage of being intuitive. this is essential since one of the main applications of slicing is program comprehension. although our semantics handles non-termination, it is defined wholly in terms of finite trajectories, without having to resort to complex, counter-intuitive, non-standard models of computation. as well as being simpler, unlike other approaches to this problem, our semantics is substitutive. substitutivity is an important property because it greatly enhances the ability to reason about correctness of meaning-preserving program transformations such as slicing.
probabilistic anonymity via coalgebraic simulations. there is a growing concern about anonymity and privacy on the internet, resulting in lots of work on formalization and verification of anonymity. in particular, the importance of probabilistic aspects of anonymity has recently been highlighted by many authors. several different notions of ''probabilistic anonymity'' have been studied so far, but proof methods for such probabilistic notions have not yet been elaborated. in this paper we introduce a simulation-based proof method for one notion of probabilistic anonymity introduced by bhargava and palamidessi, called strong probabilistic anonymity. the method is a probabilistic adaptation of the one by kawabe, sakurada et al. for non-deterministic anonymity; anonymity of a protocol is proved by finding a forward/backward simulation between certain automata. for the jump from non-determinism to probability we exploit a generic, coalgebraic theory of traces and simulations developed by hasuo, jacobs and sokolova. in particular, an appropriate notion of probabilistic simulation is obtained as an instantiation of the generic definition, for which soundness theorem comes for free. additionally, we show how we can use a similar idea to verify a weaker notion of probabilistic anonymity called probable innocence.
criteria for the matrix equivalence of words. this paper investigates the criteria for deciding whether two words are matrix equivalent. certain upper diagonal matrices, generally referred to as the parikh matrices, have been widely investigated because of their usefulness in computing the numbers of subword occurrences and thereby characterizing words by numbers. however, apart from the binary alphabet, not much is known about the properties of the matrix equivalent words, that is, words possessing the same matrix. the paper investigates both the general criteria, as well as the criteria valid in natural special cases. an exhaustive solution is obtained for ternary alphabets.
distributional analysis of swaps in quick select. we investigate the number of swaps made by quick select (a variant of quick sort for finding order statistics) to find an element with a randomly selected rank under realistic partition algorithms such as lomuto's or hoare's. this kind of grand average provides a smoothing over all individual distributions for specific fixed order statistics. the grand distribution for the number of swaps (when suitably scaled) is a perpetuity (a sum of products of independent mixed continuous random variables supported on the interval (0,1)). the tool for this proof is contraction in the wasserstein metric space, and identifying the limit as the fixed-point solution of a distributional equation. the same methodology carries over when quick select is commissioned to find an extremal order statistic (of a relatively small or relatively large rank) and the results are of similar nature. it is one of our purposes to show that analysis under different partition algorithms leads to different results.
a self-stabilizing algorithm for cut problems in synchronous networks. consider a synchronized distributed system where each node can only observe the state of its neighbors. such a system is called self-stabilizing if it reaches a stable global state in a finite number of rounds. allowing two different states for each node induces a cut in the graph. in each round, every node decides whether it is (locally) satisfied with the current cut. afterwards all unsatisfied nodes change sides independently with a fixed probability p. using different notions of satisfaction enables the computation of maximal and minimal cuts, respectively. we analyze the expected time until such cuts are reached on several graph classes and study the impact of the parameter p and the initial cut.
the pos/neg-weighted 1-median problem on tree graphs with subtree-shaped customers. in this paper we consider the pos/neg-weighted median problem on a tree graph where the customers are modeled as continua subtrees. we address the discrete and continuous models, i.e., the subtrees' boundary points are all vertices, or possibly inner points of an edge, respectively. we consider two different objective functions. if we minimize the overall sum of the minimum weighted distances of the subtrees from the facilities, there exists an optimal solution satisfying a generalized vertex optimality property, e.g., there is an optimal solution such that all facilities are located at vertices or the boundary points of the subtrees. based on this property we devise a polynomial time algorithm for the pos/neg-weighted 1-median problem on a tree with subtree-shaped customers.
preface. there have been a number of letters included in the forum of the communications of the association for computing machinery (acm) over the last two years which discuss various types of meetings with which the acm might or should become involved. a sizeable group of individuals have felt that, despite the large number of meetings sponsored by the acm and their sigs and sics as well as by other organizations, an appreciable part of the computer science community is not being adequately considered. much of the impetus for this type of a consideration was given originally by professor preston hammer, chairman of the department of computer science at pennsylvania state university, in a letter which he wrote in the november 1971 forum of the acm communications.
detecting synchronisation of biological oscillators by model checking. we define a subclass of timed automata, called oscillator timed automata, suitable to model biological oscillators. coupled biological oscillators may synchronise, as emerging behaviour, after a period of time in which they interact through physical or chemical means. we introduce a parametric semantics for their interaction that is general enough to capture the behaviour of different types of oscillators. we instantiate it both to the kuramoto model, a model of synchronisation based on smooth interaction, and to the peskin model of pacemaker cells in the heart, a model of synchronisation based on pulse interaction. we also introduce a logic, biological oscillators synchronisation logic (bosl), that is able to describe collective synchronisation properties of a population of coupled oscillators. a model checking algorithm is proposed for the defined logic and it is implemented in a model checker. the model checker can be used to detect synchronisation properties of a given population of oscillators. this tool might be the basic step towards the generation of suitable techniques to control and regulate the behaviour of coupled oscillators in order to ensure the reachability of synchronisation.
all-to-all personalized exchange in generalized shuffle-exchange networks. an all-to-all communication algorithm is said to be optimal if it has the smallest communication delay. previous all-to-all personalized exchange algorithms are mainly for hypercube, mesh, and torus. in yang and wang (2000) [13], yang and wang proved that a multistage interconnection network (min) is a better choice for implementing all-to-all personalized exchange and they proposed optimal all-to-all personalized exchange algorithms for mins. in massini (2003) [9], massini proposed a new optimal algorithm for mins, which is independent of the network topology. do notice that the algorithms in [9] and [13] work only for mins with the unique path property (meaning that there is a unique path between each pair of source and destination) and satisfying n=2^n, in which n is the number of processors, 2 means all the switches are of size 2x2, and n is the number of stages. in padmanabhan (1991) [10], padmanabhan proposed the generalized shuffle-exchange network (gsen), which is a generalization of the shuffle-exchange network. since a gsen does not have the unique path property, the algorithms in [9] and [13] cannot be used. the purpose of this paper is to consider the all-to-all personalized exchange problem in gsens. an optimal algorithm and several bounds will be proposed.
error-repair parsing schemata. robustness, the ability to analyze any input regardless of its grammaticality, is a desirable property for any system dealing with unrestricted natural language text. error-repair parsing approaches achieve robustness by considering ungrammatical sentences as corrupted versions of valid sentences. in this article we present a deductive formalism, based on sikkel's parsing schemata, that can be used to define and relate error-repair parsers and study their formal properties, such as correctness. this formalism allows us to define a general transformation technique to automatically obtain robust, error-repair parsers from standard non-robust parsers. if our method is applied to a correct parsing schema verifying certain conditions, the resulting error-repair parsing schema is guaranteed to be correct. the required conditions are weak enough to be fulfilled by a wide variety of popular parsers used in natural language processing, such as cyk, earley and left-corner.
deterministic solutions to qsat and q3sat by spiking neural p systems with pre-computed resources. in this paper we continue previous studies on the computational efficiency of spiking neural p systems, under the assumption that some pre-computed resources of exponential size are given in advance. specifically, we give a deterministic solution for each of two well known pspace-complete problems: qsat and q3sat. in the case of qsat, the answer to any instance of the problem is computed in a time which is linear with respect to both the number n of boolean variables and the number m of clauses that compose the instance. as for q3sat, the answer is computed in a time which is at most cubic in the number n of boolean variables.
single-machine scheduling under the job rejection constraint. in this paper, we consider single-machine scheduling problems under the job rejection constraint. a job is either rejected, in which case a rejection penalty has to be paid, or accepted and processed on the single machine. however, the total rejection penalty of the rejected jobs cannot exceed a given upper bound. the objective is to find a schedule such that a given criterion f is minimized, where f is a non-decreasing function on the completion times of the accepted jobs. we analyze the computational complexities of the problems for distinct objective functions and present pseudo-polynomial-time algorithms. in addition, we provide a fully polynomial-time approximation scheme for the makespan problem with release dates. for other objective functions related to due dates, we point out that there is no approximation algorithm with a bounded approximation ratio.
on convex complexity measures. khrapchenko's classical lower bound n^2 on the formula size of the parity function f can be interpreted as designing a suitable measure of sub-rectangles of the combinatorial rectangle f^-^1(0)xf^-^1(1). trying to generalize this approach we arrived at the concept of convex measures. we prove the negative result that convex measures are bounded by o(n^2) and show that several measures considered for proving lower bounds on the formula size are convex. we also prove quadratic upper bounds on a class of measures that are not necessarily convex.
combinatorics of labelling in higher-dimensional automata. the main idea for interpreting concurrent processes as labelled precubical sets is that a given set of n actions running concurrently must be assembled to a labelled n-cube, in exactly one way. the main ingredient is the non-functorial construction called the labelled directed coskeleton. it is defined as a subobject of the labelled coskeleton, the latter coinciding in the unlabelled case with the right adjoint to the truncation functor. this non-functorial construction is necessary since the labelled coskeleton functor of the category of labelled precubical sets does not fulfil the above requirement. we prove in this paper that it is possible to force the labelled coskeleton functor to be well behaved by working with labelled transverse symmetric precubical sets. moreover, we prove that this solution is the only one. a transverse symmetric precubical set is a precubical set equipped with symmetry maps and with a new kind of degeneracy map called transverse degeneracy. finally, we also prove that the two settings are equivalent from a directed algebraic topological viewpoint. to illustrate, a new semantics of the calculus of communicating systems (ccs), equivalent to the old one, is given.
runtime analysis of a binary particle swarm optimizer. we investigate the runtime of a binary particle swarm optimizer (pso) for optimizing pseudo-boolean functions f:{0,1}^n->r. the binary pso maintains a swarm of particles searching for good solutions. each particle consists of a current position from {0,1}^n, its own best position and a velocity vector used in a probabilistic process to update its current position. the velocities for a particle are then updated in the direction of its own best position and the position of the best particle in the swarm. we present a lower bound for the time needed to optimize any pseudo-boolean function with a unique optimum. to prove upper bounds we transfer a fitness-level argument that is well-established for evolutionary algorithms (eas) to pso. this method is applied to estimate the expected runtime for the class of unimodal functions. a simple variant of the binary pso is considered in more detail for the test function onemax, showing that there the binary pso is competitive to eas. an additional experimental comparison reveals further insights.
a fluid analysis framework for a markovian process algebra. markovian process algebras, such as pepa and stochastic @p-calculus, bring a powerful compositional approach to the performance modelling of complex systems. however, the models generated by process algebras, as with other interleaving formalisms, are susceptible to the state space explosion problem. models with only a modest number of process algebra terms can easily generate so many states that they are all but intractable to traditional solution techniques. previous work aimed at addressing this problem has presented a fluid-flow approximation allowing the analysis of systems which would otherwise be inaccessible. to achieve this, systems of ordinary differential equations describing the fluid flow of the stochastic process algebra model are generated informally. in this paper, we show formally that for a large class of models, this fluid-flow analysis can be directly derived from the stochastic process algebra model as an approximation to the mean number of component types within the model. the nature of the fluid approximation is derived and characterised by direct comparison with the chapman-kolmogorov equations underlying the markov model. furthermore, we compare the fluid approximation with the exact solution using stochastic simulation and we are able to demonstrate that it is a very accurate approximation in many cases. for the first time, we also show how to extend these techniques naturally to generate systems of differential equations approximating higher order moments of model component counts. these are important performance characteristics for estimating, for instance, the variance of the component counts. this is very necessary if we are to understand how precise the fluid-flow calculation is, in a given modelling situation.
partially dynamic efficient algorithms for distributed shortest paths. we study the dynamic version of the distributed all-pairs shortest paths problem. most of the solutions given in the literature for this problem, either (i) work under the assumption that before dealing with an edge operation, the algorithm for the previous operation has to be terminated, that is, they are not able to update shortest paths concurrently, or (ii) concurrently update shortest paths, but their convergence can be very slow (possibly infinite) due to the looping and counting infinity phenomena. in this paper, we propose partially dynamic algorithms that are able to concurrently update shortest paths. we experimentally analyze the effectiveness and efficiency of our algorithms by comparing them against several implementations of the well-known bellman-ford algorithm.
on generic context lemmas for higher-order calculi with sharing. this paper proves several generic variants of context lemmas and thus contributes to improving the tools for observational semantics of deterministic and non-deterministic higher-order calculi that use a small-step reduction semantics. the generic (sharing) context lemmas are provided for may- as well as two variants of must-convergence, which hold in a broad class of extended process- and extended lambda calculi, if the calculi satisfy certain natural conditions. as a guide-line, the proofs of the context lemmas are valid in call-by-need calculi, in call-by-value calculi if substitution is restricted to variable-by-variable and in process calculi like variants of the @p-calculus. for calculi employing beta-reduction using a call-by-name or call-by-value strategy or similar reduction rules, some iu-variants of ciu-theorems are obtained from our context lemmas. our results reestablish several context lemmas already proved in the literature, and also provide some new context lemmas as well as some new variants of the ciu-theorem. to make the results widely applicable, we use a higher-order abstract syntax that allows untyped calculi as well as certain simple typing schemes. the approach may lead to a unifying view of higher-order calculi, reduction, and observational equality.
csp is a retract of ccs. automata theory provides two ways of defining an automaton: either by its transition system, defining its states and events, or by its language, the set of sequences (traces) of events in which it can engage. for many classes of automaton, these forms of definition have been proved equivalent. for example, there is a well-known isomorphism between regular languages and finite deterministic automata. this paper suggests that for (demonically) the non-deterministic automata (as treated in process algebra), the appropriate link between transition systems and languages may be a retraction rather than an isomorphism. a pair of automata, defined in the tradition of ccs by their transition systems, may be compared by a pre-ordering based on some kind of simulation or bisimulation, for example, weak, strong, or barbed. automata defined in the tradition of csp are naturally ordered by set inclusion of their languages (often called refinement); variations in ordering arise from different choices of basic event, including for example, refusals and divergences. in both cases, we characterise a theory by its underlying transition system and its choice of ordering. our treatment is therefore wholly semantic, independent of the syntax and definition of operators of the calculus. we put forward a series of retractions relating the above-mentioned versions of csp to their corresponding ccs transition models. a retraction is an injection that is (with respect to the chosen ordering) monotonic, increasing and idempotent (up to equivalence). it maps the nodes of a transition system of its source theory to those of a system that has been saturated by additional transitions. each retraction will be defined by a transition rule, in the style of operational semantics; the proofs use the familiar technique of co-induction, often abbreviated by encoding in the relational calculus. the aim of this paper is to contribute to unification of theories of reactive system programming. more practical benefits may follow. for example, we justify a method to improve the efficiency of model checking based on simulation. furthermore, we show how model checking of a transition network fits consistently with theorem-proving tools, which reason directly about specifications and designs that are expressed in terms of sets of sequences of observable events.
approximating minimum power covers of intersecting families and directed edge-connectivity problems. given a (directed) graph with costs on the edges, the power of a node is the maximum cost of an edge leaving it, and the power of the graph is the sum of the powers of its nodes. let g=(v,e) be a graph with edge costs {c(e):e@?e} and let k be an integer. we consider problems that seek to find a min-power spanning subgraph g of g that satisfies a prescribed edge-connectivity property. in the min-powerk-edge-outconnected subgraph problem we are given a root r@?v, and require that g contains k pairwise edge-disjoint rv-paths for all v@?v-r. in the min-powerk-edge-connected subgraph problem g is required to be k-edge-connected. for k=1, these problems are at least as hard as the set-cover problem and thus have an @w(ln|v|) approximation threshold. for k=@w(n^@e), they are unlikely to admit a polylogarithmic approximation ratio [15]. we give approximation algorithms with ratio o(kln|v|). our algorithms are based on a more general o(ln|v|)-approximation algorithm for the problem of finding a min-power directed edge-cover of an intersecting set-family; a set-family f is intersecting if x@?y,x@?y@?f for any intersecting x,y@?f, and an edge set i covers f if for every x@?f there is an edge in i entering x.
finding common structured patterns in linear graphs. a linear graph is a graph whose vertices are linearly ordered. this linear ordering allows pairs of disjoint edges to be either preceding (
game authority for robust and scalable distributed selfish-computer systems. distributed algorithm designers often assume that system processes execute the same predefined software. alternatively, when they do not assume that, designers turn to non-cooperative games and seek an outcome that corresponds to a rough consensus when no coordination is allowed. we argue that both assumptions are inapplicable in many real distributed systems, e.g., the internet, and propose designing self-stabilizing and byzantine fault-tolerant distributed game authorities. once established, the game authority can secure the execution of any complete information game. as a result, we reduce costs that are due to the processes' freedom of choice. namely, we reduce the price of malice.
incremental learning with temporary memory. in the inductive inference framework of learning in the limit, a variation of the bounded example memory (bem) language learning model is considered. intuitively, the new model constrains the learner's memory not only in how much data may be stored, but also in how long those data may be stored without being refreshed. more specifically, the model requires that, if the learner commits an example x to memory, and x is not presented to the learner again thereafter, then eventually the learner forgetsx, i.e., eventually x no longer appears in the learner's memory. this model is called temporary example memory (tem) learning. many interesting results concerning the tem-learning model are presented. for example, there exists a class of languages that can be identified by memorizing k+1 examples in the tem sense, but that cannot be identified by memorizing k examples in the bem sense. on the other hand, there exists a class of languages that can be identified by memorizing just one example in the bem sense, but that cannot be identified by memorizing any number of examples in the tem sense. results are also presented concerning the special case of learning classes of infinite languages.
characterizing geometric patterns formable by oblivious anonymous mobile robots. in a system in which anonymous mobile robots repeatedly execute a ''look-compute-move'' cycle, a robot is said to be oblivious if it has no memory to store its observations in the past, and hence its move depends only on the current observation. this paper considers the pattern formation problem in such a system, and shows that oblivious robots can form any pattern that non-oblivious robots can form, except that two oblivious robots cannot form a point while two non-oblivious robots can. therefore, memory does not help in forming a pattern, except for the case in which two robots attempt to form a point. related results on the pattern convergence problem are also presented.
active learning in heteroscedastic noise. we consider the problem of actively learning the mean values of distributions associated with a finite number of options. the decision maker can select which option to generate the next observation from, the goal being to produce estimates with equally good precision for all the options. if sample means are used to estimate the unknown values then the optimal solution, assuming that the distributions are known up to a shift, is to sample from each distribution proportional to its variance. no information other than the distributions' variances is needed to calculate the optimal solution. in this paper we propose an incremental algorithm that asymptotically achieves the same loss as an optimal rule. we prove that the excess loss suffered by this algorithm, apart from logarithmic factors, scales as n^-^3^/^2, which we conjecture to be the optimal rate. the performance of the algorithm is illustrated on a simple problem.
an improved approximation algorithm for the maximum tsp. in this paper, we consider the maximum traveling salesman problem with @c-parameterized triangle inequality for @c@?[12,1), which means that the edge weights in the given complete graph g=(v,e,w) satisfy w(uv)@?@c@?(w(ux)+w(xv)) for all distinct nodes u,x,v@?v. for the maximum traveling salesman problem with @c-parameterized triangle inequality, r. hassin and s. rubinstein gave a constant factor approximation algorithm with polynomial running time, they achieved a performance ratio @c only for @c@?[12,57) in [8], which is the best known result. we design a k@c+1-2@ck@c-approximation algorithm for the maximum traveling salesman problem with @c-parameterized triangle inequality by using a similar idea but very different method to that in [11], where k=min{|c"i||i=1,2,...,m},c"1,c"2,...,c"m is an optimal solution of the minimum cycle cover in g, which is better than the @c-approximation algorithm for almost all @c@?[12,1).
complex network dimension and path counts. large complex networks occur in many applications of computer science. the complex network zeta function and the graph surface function have been used to characterize these networks and to define a dimension for complex networks. in this work we present three new results related to the complex network dimension. first, we show the relationship of the concept to kolmogorov complexity. second, we show how the definition of complex network dimension can be reformulated by defining the concept for a single node, and then defining the complex network dimension as the supremum over all nodes. this makes the concept work better for formally infinite graphs. third, we study interesting parallels to zeta dimension, a notion originally from number theory which has found connections to theoretical computer science. these parallels lead to a deeper insight into the complex network dimension, e.g., the formulation in terms of the entropy and a theorem relating dimension to connectivity.
prequential randomness and probability. this paper studies dawid's prequential framework from the point of view of the algorithmic theory of randomness. our first main result is that two natural notions of randomness coincide. one notion is the prequential version of the measure-theoretic definition due to martin-lof, and the other is the prequential version of the game-theoretic definition due to schnorr and levin. this is another manifestation of the close relation between the two main paradigms of randomness. the algorithmic theory of randomness can be stripped of its algorithmic aspect and still give meaningful results; the measure-theoretic paradigm then corresponds to kolmogorov's measure-theoretic probability and the game-theoretic paradigm corresponds to game-theoretic probability. our second main result is that measure-theoretic probability coincides with game-theoretic probability on all analytic (in particular, borel) sets.
dynamic programming based algorithms for set multicover and multiset multicover problems. given a universe n containing n elements and a collection of multisets or sets over n, the multiset multicover (msmc) problem or the set multicover (smc) problem is to cover all elements at least a number of times as specified in their coverage requirements with the minimum number of multisets or sets. in this paper, we give various exact algorithms for these two problems with or without constraints on the number of times a multiset or set may be chosen. first, we show that the msmc without multiplicity constraints problem can be solved in o^*((b+1)^n|f|) time and polynomial space, where b is the maximum coverage requirement and |f| denotes the total number of given multisets over n. (the o^* notation suppresses a factor polynomial in n.) to our knowledge, this is the first known exact algorithm for the msmc without multiplicity constraints problem. second, by combining dynamic programming and the inclusion-exclusion principle, we can exactly solve the smc without multiplicity constraints problem in o((b+2)^n) time. compared with two recent results, in [q.-s. hua, y. wang, d. yu, f.c.m. lau, set multi-covering via inclusion-exclusion, theoretical computer science, 410 (38-40) (2009) 3882-3892] and [j. nederlof, inclusion exclusion for hard problems, master thesis, utrecht university, the netherlands, 2008], respectively, ours is the fastest exact algorithm for the smc without multiplicity constraints problem. finally, by directly using dynamic programming, we give the first known exact algorithm for the msmc or the smc with multiplicity constraints problem in o((b+1)^n|f|) time and o^*((b+1)^n) space. this algorithm can also be easily adapted as a constructive algorithm for the msmc without multiplicity constraints problem.
average complexity of the jiang-wang-zhang pairwise tree alignment algorithm and of a rna secondary structure alignment algorithm. we prove that the average complexity of the pairwise ordered tree alignment algorithm of jiang, wang and zhang is in o(nm), where n and m stand for the sizes of the two trees, respectively. we show that the same result holds for the average complexity of pairwise comparison of rna secondary structures, using a set of biologically relevant operations.
information measures for infinite sequences. we revisit the notion of computational depth and sophistication for infinite sequences and study the density of the sets of deep and sophisticated infinite sequences. koppel defined the sophistication of an object as the length of the shortest total program that, given some data as input, produces the object and such that the sum of the size of the program with the size of the data is as concise as the smallest description of the object. however, the notion of sophistication is not properly defined for all sequences. we propose a new definition of sophistication for infinite sequences as the limit of the ratio of the sophistication of the initial segments and its length. we prove that the set of sequences with sophistication equal to zero has lebesgue measure one and that the set of sophisticated sequences is dense, when the sophistication is, respectively, defined either using lim inf or lim sup. antunes, fortnow, van melkebeek and vinodchandran captured the notion of useful information by computational depth, the difference between time bounded and unbounded kolmogorov complexities. we show that the set of deep infinite sequences is dense. we also prove that sophistication and depth for infinite sequences are distinct information measures.
theoretical underpinnings for maximal clique enumeration on perturbed graphs. the problem of enumerating the maximal cliques of a graph is a computationally expensive problem with applications in a number of different domains. sometimes the benefit of knowing the maximal clique enumeration (mce) of a single graph is worth investing the initial computation time. however, when graphs are abstractions of noisy or uncertain data, the mce of several closely related graphs may need to be found, and the computational cost of doing so becomes prohibitively expensive. here, we present a method by which the cost of enumerating the set of maximal cliques for related graphs can be reduced. by using the mce for some baseline graph, the mce for a modified, or perturbed, graph may be obtained by enumerating only the maximal cliques that are created or destroyed by the perturbation. when the baseline and perturbed graphs are relatively similar, the difference set between the two mces can be overshadowed by the maximal cliques common to both. thus, by enumerating only the difference set between the baseline and perturbed graphs' mces, the computational cost of enumerating the maximal cliques of the perturbed graph can be reduced. we present necessary and sufficient conditions for enumerating difference sets when the perturbed graph is formed by several different types of perturbations. we also present results of an algorithm based on these conditions that demonstrate a speedup over traditional calculations of the mce of perturbed, real biological networks.
randomized priority algorithms. borodin, nielsen and rackoff [13] introduced the class of priority algorithms as a framework for modeling deterministic greedy-like algorithms. in this paper we address the effect of randomization in greedy-like algorithms. more specifically, we consider approximation ratios within the context of randomized priority algorithms. as case studies, we prove inapproximation results for two well-studied optimization problems, namely facility location and makespan scheduling.
tight results for next fit and worst fit with resource augmentation. it is well known that the two simple algorithms for the classic bin packing problem, nf and wf both have an approximation ratio of 2. however, wf seems to be a more reasonable algorithm, since it never opens a new bin if an existing bin can still be used. using resource augmented analysis, where the output of an approximation algorithm, which can use bins of size b>1, is compared to an optimal packing into bins of size 1, we give a complete analysis of the asymptotic approximation ratio of wf and of nf, and use it to show that wf is strictly better than nf for any 1=2, and for b=1.
inapproximability results for equations over infinite groups. an equation over a group g is an expression of form w"1...w"k=1"g, where each w"i is either a variable, an inverted variable, or a group constant and 1"g denotes the identity element; such an equation is satisfiable if there is a setting of the variables to values in g such that the equality is realized (engebretsen et al. (2002) [10]). in this paper, we study the problem of simultaneously satisfying a family of equations over an infinite group g. let eq"g[k] denote the problem of determining the maximum number of simultaneously satisfiable equations in which each equation has occurrences of exactly k different variables. when g is an infinite cyclic group, we show that it is np-hard to approximate eq^1"g[3] to within 48/47-@e, where eq^1"g[3] denotes the special case of eq"g[3] in which a variable may only appear once in each equation; it is np-hard to approximate eq^1"g[2] to within 30/29-@e; it is np-hard to approximate the maximum number of simultaneously satisfiable equations of degree at most d to within d-@e for any @e; for any k>=4, it is np-hard to approximate eq"g[k] within any constant factor. these results extend hastad's results (hastad (2001) [17]) and results of (engebretsen et al. (2002) [10]), who established the inapproximability results for equations over finite abelian groups and any finite groups respectively.
a class of hierarchical graphs as topologies for interconnection networks. we study some topological and algorithmic properties of a recently defined hierarchical interconnection network, the hierarchical crossed cube hcc(k,n), which draws upon constructions used within the well-known hypercube and also the crossed cube. in particular, we study: the construction of shortest paths between arbitrary vertices in hcc(k,n); the connectivity of hcc(k,n); and one-to-all broadcasts in parallel machines whose underlying topology is hcc(k,n) (with both one-port and multi-port store-and-forward models of communication). moreover, some of our proofs are applicable not just to hierarchical crossed cubes but to hierarchical interconnection networks formed by replacing crossed cubes with other families of interconnection networks. as such, we provide a generic construction with accompanying generic results relating to some topological and algorithmic properties of a wide range of hierarchical interconnection networks
dykstra's algorithm for constrained least-squares doubly symmetric matrix problems. in this work we apply dykstra's alternating projection algorithm for minimizing @?ax-b@? where @?@?@? is the frobenius norm and a@?r^m^x^n, b@?r^m^x^n and x@?r^n^x^n are doubly symmetric positive definite matrices with entries within prescribed intervals. we first solve the constrained least-squares matrix problem by using the special structure properties of doubly symmetric matrices, and then use the singular value decomposition to transform the original problem into a simpler one that fits nicely with the algorithm originally developed by [r. escalante, m. raydan, dykstra's algorithm for a constrained least-squares matrix problem, numer. linear algebra appl. 3 (1996) 459-471].
exact leaf powers. we define and study the new notion of exact k-leaf powers where a graph g=(v"g,e"g) is an exact k-leaf power if and only if there exists a tree t=(v"t,e"t) - an exact k-leaf root of g - whose set of leaves equals v"g such that uv@?e"g holds for u,v@?v"g if and only if the distance of u and v in t is exactly k. this new notion is closely related to but different from leaf powers and neighbourhood subtree tolerance graphs. we prove characterizations of exact 3- and 4-leaf powers which imply that such graphs can be recognized in linear time and that also the corresponding exact leaf roots can be found in linear time. furthermore, we characterize all exact 5-leaf roots of chordless cycles and derive several properties of exact 5-leaf powers.
an optimal algorithm to generate rooted trivalent diagrams and rooted triangular maps. a trivalent diagram is a connected, two-colored bipartite graph (parallel edges allowed but not loops) such that every black vertex is of degree 1 or 3 and every white vertex is of degree 1 or 2, with a cyclic order imposed on every set of edges incident to the same vertex. a rooted trivalent diagram is a trivalent diagram with a distinguished edge, its root. we shall describe and analyze an algorithm giving an exhaustive list of rooted trivalent diagrams of a given size (number of edges), the list being non-redundant in that no two diagrams of the list are isomorphic. the algorithm will be shown to have optimal performance in that the time necessary to generate a diagram will be seen to be bounded in the amortized sense, the bound being independent of the size of the diagrams. we call this the cat property. one objective of the paper is to provide a reusable theoretical framework for algorithms generating exhaustive lists of complex combinatorial structures with attention paid to the case of unlabeled structures and to those generators having the cat property.
two-dimensional online bin packing with rotation. in two-dimensional bin packing problems, the input items are rectangles which need to be packed in a non-overlapping manner. the goal is to assign the items into unit squares using an axis-parallel packing. most previous work on online packing concentrated on items of fixed orientation, which must be assigned such that their bottom side is parallel to the bottom of the bin. in this paper we study the case of rotatable items, which can be rotated by ninety degrees. we give almost tight bounds on the (asymptotic) competitive ratio of bounded space bin packing of rotatable items, and introduce a new unbounded space algorithm. this improves the results of fujita and hada.
approximability and inapproximability of the minimum certificate dispersal problem. given an n-vertex directed graph g=(v,e) and a set r@?vxv of requests, we consider assigning a set of edges to each vertex in g so that for every request (u,v) in r the union of the edge sets assigned to u and v contains a path from u to v. the minimum certificate dispersal problem (mcd) is defined as one to find an assignment that minimizes the sum of the cardinalities of the edge sets assigned to each vertex. this problem has been shown to be np-hard in general, though it is polynomially solvable for some restricted classes of graphs and restricted request structures, such as bidirectional trees with requests of all pairs of vertices. in this paper, we give an advanced investigation about the difficulty of mcd by focusing on the relationship between its (in)approximability and request structures. we first show that mcd with general r has @q(logn) lower and upper bounds on approximation ratio under the assumption p
the bridge-connectivity augmentation problem with a partition constraint. in this paper, we consider the augmentation problem of an undirected graph with k partitions of its vertices. the main issue is how to add a set of edges with the smallest possible cardinality so that the resulting graph is 2-edge-connected, i.e., bridge-connected, while maintaining the original partition constraint. to solve the problem, we propose a simple linear-time algorithm. to the best of our knowledge, the most efficient sequential algorithm runs in o(n(m+nlogn)logn) time. however, we show that it can also run in o(logn) parallel time on an erew pram using a linear number of processors, where n is the number of vertices in the input graph. if a simple graph exists, our main algorithm ensures that it is as simple as possible.
efficient frequent connected subgraph mining in graphs of bounded tree-width. the frequent connected subgraph mining problem, i.e., the problem of listing all connected graphs that are subgraph isomorphic to at least a certain number of transaction graphs of a database, cannot be solved in output polynomial time in the general case. if, however, the transaction graphs are restricted to forests then the problem becomes tractable. in this paper we generalize the positive result on forests to graphs of bounded tree-width. in particular, we show that for this class of transaction graphs, frequent connected subgraphs can be listed in incremental polynomial time. since subgraph isomorphism remains np-complete for bounded tree-width graphs, the positive complexity result of this paper shows that efficient frequent pattern mining is possible even for computationally hard pattern matching operators.
factors of characteristic words: location and decompositions. let @a be an irrational number with 0
deterministic on-line call control in cellular networks. we study an on-line call control problem in cellular networks that are based on the frequency division multiplexing (fdm) technology. in such networks, interference may occur when the same frequency is assigned to two different calls emanating from the same cell or its neighboring cells. the number of frequencies supporting the networks is limited. the goal is to maximize the number of calls served without causing any interference. we focus on the case that the number of frequencies is sufficiently large and the calls stay forever. we give a deterministic on-line algorithm with asymptotic competitive ratio of 2.5 and show a general lower bound of 2. for the special case of linear cellular networks, we achieve a best possible deterministic on-line algorithm with asymptotic competitive ratio of 3/2.
window-games between tcp flows. we consider network congestion problems between tcp flows and define a new game, the window-game, which models the problems of network congestion caused by the competing flows. analytical and experimental results show the relevance of the window-game to real tcp congestion games and provide interesting insight into the respective nash equilibria. furthermore, we propose a new algorithmic queue mechanism, called prince, which at congestion makes a scapegoat of the most greedy flow. we provide evidence which shows that prince achieves efficient nash equilibria while requiring only limited computational resources.
online scheduling with reassignment on two uniform machines. in this paper, we investigate the online scheduling problem on two uniform machines, where the last job of each machine can be reassigned after all jobs have been assigned. the objective is to minimize the makespan. we prove that the classical list scheduling algorithm with the competitive ratio s+1s is optimal for s>=1+52, where s is the speed ratio between the two machines. also, we prove the lower bound s+1 for 1@?s
an upper bound for the circuit complexity of existentially quantified boolean formulas. the expressive power of existentially quantified boolean formulas @?cnf with free variables is investigated. we introduce a hierarchy of subclasses @?mu^*(k) of @?cnf formulas based on the maximum deficiency k of minimal unsatisfiable subformulas of the bound part of the formulas. we will establish an upper bound of the size of minimally equivalent circuits. it will be shown, that there are constants a and b, such that for every formula in @?mu^*(k) of length m of the bound part and length l of the free part of the formula there is an equivalent circuit of size less than l+a@?m^b^(^l^o^g^"^2^(^m^)^+^k^)^^^2.
a compact fixpoint semantics for term rewriting systems. this work is motivated by the fact that a ''compact'' semantics for term rewriting systems, which is essential for the development of effective semantics-based program manipulation tools (e.g. automatic program analyzers and debuggers), does not exist. the big-step rewriting semantics that is most commonly considered in functional programming is the set of values/normal forms that the program is able to compute for any input expression. such a big-step semantics is unnecessarily oversized, as it contains many ''semantically useless'' elements that can be retrieved from a smaller set of terms. therefore, in this article, we present a compressed, goal-independent collecting fixpoint semantics that contains the smallest set of terms that are sufficient to describe, by semantic closure, all possible rewritings. we prove soundness and completeness under ascertained conditions. the compactness of the semantics makes it suitable for applications. actually, our semantics can be finite whereas the big-step semantics is generally not, and even when both semantics are infinite, the fixpoint computation of our semantics produces fewer elements at each step. to support this claim we report several experiments performed with a prototypical implementation.
a polynomial-time algorithm for the weighted link ring loading problem with integer demand splitting. we are given an n-node undirected ring network, in which each link of the ring is associated with a weight. traffic demand is given for each pair of nodes in the ring. each demand is allowed to be split into two integer parts, which are then routed in different directions, clockwise and counterclockwise, respectively. the load of a link is the sum of the flows routed through the link and the nonnegative weighted load of a link is the product of its weight and its load. the objective is to find a routing scheme such that the maximum weighted load on the ring is minimized. based on some useful structural properties of the decision version of the problem, we design a polynomial-time combinatorial algorithm for the optimization problem.
left-forbidding cooperating distributed grammar systems. a left-forbidding grammar, introduced in this paper, is a context-free grammar, where a set of nonterminal symbols is attached to each context-free production. such a production can rewrite a nonterminal provided that no symbol from the attached set occurs to the left of the rewritten nonterminal in the current sentential form. the present paper discusses cooperating distributed grammar systems with left-forbidding grammars as components and gives some new characterizations of language families of the chomsky hierarchy. in addition, it also proves that twelve nonterminals are enough for cooperating distributed grammar systems working in the terminal derivation mode with two left-forbidding components (including erasing productions) to characterize the family of recursively enumerable languages.
the surviving rate of an infected network. let g be a connected network. let k>=1 be an integer. suppose that a vertex v of g becomes infected. a program is then installed on k-nodes not yet infected. afterwards, the virus spreads to all its unprotected neighbors in each time interval. the virus and the network administrator take turns until the virus can no longer spread further. let sn"k(v) denote the maximum number of vertices in g the network administrator can save when a virus infects v. the k-surviving rate @r"k(g) of g is defined to be the average value @?"v"@?"v"("g")sn"k(v)/n^2. in particular, we write @r(g)=@r"1(g). in this paper, we first use a probabilistic method to show that almost all networks have k-surviving rate arbitrarily close to 0. then, we prove the following results: (1) @r(g)>=235 for a planar network g of girth at least 9; (2) @r"2(g)>=116 for a series-parallel network g; and (3) @r"""2"""d"""-"""1(g)>=25d for a d-degenerate network g.
acyclic automata and small expressions using multi-tilde-bar operators. a regular expression with n occurrences of symbol can be converted into an equivalent automaton with (n+1) states, the so-called glushkov automaton of the expression. conversely, it is possible to decide whether a given (n+1)-state automaton is a glushkov one and, if so, to convert it back to an equivalent regular expression of width n. our goal is to extend the class of automata for which such a linear retranslation is possible. we define new regular operators, called multi-tilde-bars, allowing us to simultaneously apply a multi-tilde operator and a multi-bar one to a list of expressions. the main results are that a multi-tilde-bar expression of width n can be converted into an (n+1)-state position-like automaton and that any acyclic n-state automaton can be turned into an extended expression of width o(n).
the college admissions problem with lower and common quotas. we study two generalised stable matching problems motivated by the current matching scheme used in the higher education sector in hungary. the first problem is an extension of the college admissions problem in which the colleges have lower quotas as well as the normal upper quotas. here, we show that a stable matching may not exist and we prove that the problem of determining whether one does is np-complete in general. the second problem is a different extension in which, as usual, individual colleges have upper quotas, but, in addition, certain bounded subsets of colleges have common quotas smaller than the sum of their individual quotas. again, we show that a stable matching may not exist and the related decision problem is np-complete. on the other hand, we prove that, when the bounded sets form a nested set system, a stable matching can be found by generalising, in non-trivial ways, both the applicant-oriented and college-oriented versions of the classical gale-shapley algorithm. finally, we present an alternative view of this nested case using the concept of choice functions, and with the aid of a matroid model we establish some interesting structural results for this case.
reconstructing hv-convex multi-coloured polyominoes. in this paper, we consider the problem of reconstructing polyominoes from information about the thickness in vertical and horizontal directions. we focus on the case where there are multiple disjoint polyominoes (of different colours) that are hv-convex, i.e., any intersection with a horizontal or vertical line is contiguous. we show that reconstruction of such polyominoes is polynomial if the number of colours is constant, but np-hard for an unbounded number of colours.
checking experiments for stream x-machines. stream x-machines are a state based formalism that has associated with it a particular development process in which a system is built from trusted components. testing thus essentially checks that these components have been combined in a correct manner and that the orders in which they can occur are consistent with the specification. importantly, there are test generation methods that return a checking experiment: a test that is guaranteed to determine correctness as long as the implementation under test (iut) is functionally equivalent to an unknown element of a given fault domain @j. previous work has show how three methods for generating checking experiments from a finite state machine (fsm) can be adapted to testing from a stream x-machine. however, there are many other methods for generating checking experiments from an fsm and these have a variety of benefits that correspond to different testing scenarios. this paper shows how any method for generating a checking experiment from an fsm can be adapted to generate a checking experiment for testing an implementation against a stream x-machine. this is the case whether we are testing to check that the iut is functionally equivalent to a specification or we are testing to check that every trace (input/output sequence) of the iut is also a trace of a nondeterministic specification. interestingly, this holds even if the fault domain @j used is not that traditionally associated with testing from a stream x-machine. the results also apply for both deterministic and nondeterministic implementations.
algorithm for two disjoint long paths in 2-connected graphs. in this paper, we prove that 2-connected graphs have either a dominating path or two disjoint paths, wherein the length of the two paths is bounded by the minimum among n and a parameter defined on the neighborhood condition of any four independent vertices of the graph.
the continuous skolem-pisot problem. we study decidability and complexity questions related to a continuous analogue of the skolem-pisot problem concerning the zeros and nonnegativity of a linear recurrent sequence. in particular, we show that the continuous version of the nonnegativity problem is np-hard in general and we show that the presence of a zero is decidable for several subcases, including instances of depth two or less, although the decidability in general is left open. the problems may also be stated as reachability problems related to real zeros of exponential polynomials or solutions to initial value problems of linear differential equations, which are interesting problems in their own right.
analysis of a cellular automaton model for car traffic with a slow-to-stop rule. we propose a modification of the widely known benjamin-johnson-hui (bjh) cellular automaton model for single-lane traffic simulation. in particular, our model includes a 'slow-to-stop' rule that exhibits more realistic microscopic driver behaviour than the bjh model. we present some statistics related to fuel economy and pollution generation and show that our model differs greatly in these measures. we give concise results based on extensive simulations using our system.
a note on the complexity of c-words. let @c(n) be the number of c^~-words of length n. say that a c^~-word w is left doubly extendable (lde) if both 1w and 2w are c^~. we show that for any positive real number @f and positive integer n such that the proportion of 2's is greater than 12-@f in each lde word of length exceeding n, there are positive constants c"1 and c"2 such that c"1n^l^o^g^3^l^o^g^(^(^3^/^2^)^+^@f^+^(^2^/^n^)^)
enumeration of the perfect sequences of a chordal graph. a graph is chordal if and only if it has no chordless cycle of length more than three. the set of maximal cliques in a chordal graph admits special tree structures called clique trees. a perfect sequence is a sequence of maximal cliques obtained by using the reverse order of repeatedly removing the leaves of a clique tree. this paper addresses the problem of enumerating all the perfect sequences. although this problem has statistical applications, no efficient algorithm has been proposed. there are two difficulties with developing this type of algorithm. first, a chordal graph does not generally have a unique clique tree. second, a perfect sequence can normally be generated by two or more distinct clique trees. thus it is hard using a straightforward algorithm to generate perfect sequences from each possible clique tree. in this paper, we propose a method to enumerate perfect sequences without constructing clique trees. as a result, we have developed the first polynomial delay algorithm for dealing with this problem. in particular, the time complexity of the algorithm on average is o(1) for each perfect sequence.
recognition of directed acyclic graphs by spanning tree automata. in this paper, we study tree automata for directed acyclic graphs (dags). we define the movement of a tree automaton on a dag so that a dag is accepted by a tree automaton if and only if the dag has a spanning tree accepted by the tree automaton. we call this automaton a spanning tree automaton. the np-completeness of the membership problem of dags for spanning tree automata is shown. however, if inputs are restricted to series-parallel graphs or generalized series-parallel graphs, it is shown that the membership problem for spanning tree automata is solvable in linear time.
parametric random generation of deterministic tree automata. uniform random generators deliver a simple empirical means to estimate the average complexity of an algorithm. we present a general rejection algorithm that generates sequential letter-to-letter transducers up to isomorphism. we also propose an original parametric random generation algorithm to produce sequential letter-to-letter transducers with a fixed number of transitions. we tailor this general scheme to randomly generate deterministic tree walking automata and deterministic top-down tree automata. we apply our implementation of the generator to the estimation of the average complexity of a deterministic tree walking automata to nondeterministic top-down tree automata construction we also implemented.
embedding of tori and grids into twisted cubes. the hypercube is one of the most popular interconnection networks since it has a simple structure and is easy to implement. an n-dimensional twisted cube, tq"n, is an important variation of hypercube q"n and preserves many of its desirable properties. the problem of how to embed a family of disjoint meshes (or tori) into a host graph has attracted great attention in recent years. however, there is no systematic method proposed to generate the desired meshes and tori in tq"n. in this paper, we develop two systematic linear time algorithms for embedding disjoint multi-dimensional tori into tq"n, n>=7, as follows: (1) for a positive integer m with @?n2@?@?m@?n-4, a family of 2^m disjoint k-dimensional tori of size 2^s^"^1x2^s^"^2x...x2^s^"^k each can be embedded with unit dilation, where k>=2 and @?"i"="1^ks"i@?n-m, and (2) for a positive integer m with 2@?m@?n-5, a family of 2^m disjoint k-dimensional tori of size 2^s^"^1x2^s^"^2x...x2^s^"^k each can be embedded with unit dilation, where k>=2, s"i>=2, @?"i"="1^ks"i@?n-m, and max"1"@?"i"@?"k{s"i}>=n-2m. moreover, we also provide similar embedding results for meshes and hypercubes. our results mean that a family of torus-structured (mesh-structured, or hypercube-structured) parallel algorithms can be executed on the same twisted cube efficiently and in parallel.
improved upper bounds for vertex cover. this paper presents an o(1.2738^k+kn)-time polynomial-space algorithm for vertex cover improving the previous o(1.286^k+kn)-time polynomial-space upper bound by chen, kanj, and jia. most of the previous algorithms rely on exhaustive case-by-case branching rules, and an underlying conservative worst-case-scenario assumption. the contribution of the paper lies in the simplicity, uniformity, and obliviousness of the algorithm presented. several new techniques, as well as generalizations of previous techniques, are introduced including: general folding, struction, tuples, and local amortized analysis. the algorithm also improves the o(1.2745^kk^4+kn)-time exponential-space upper bound for the problem by chandran and grandoni.
preemptive scheduling with simple linear deterioration on a single machine. in this paper we study the problem of scheduling n deteriorating jobs with release dates on a single machine. the processing time of a job is assumed to be the product of its deteriorating rate and its starting time. precedence relations may be imposed on the set of jobs. unlike the classical time-dependent scheduling problems, we assume that the execution of a job can be preempted in the sense that the job's deteriorating rate is reduced when it is preempted and each continuously processed part of a job can be regarded as an independent job with a specified deteriorating rate. the objective is to minimize some common regular scheduling performance measures. we first show that minimizing a class of regular symmetric functions is polynomially solvable. then we construct an o(n^2) algorithm for minimizing the maximum job completion cost with or without precedence constraints. finally we show that minimizing the total weighted completion time is np-hard even if there are only two distinct release dates.
fixed point guided abstraction refinement for alternating automata. in this paper, we develop and evaluate two new algorithms for checking emptiness of alternating automata. these algorithms build on previous works. first, they rely on antichains to efficiently manipulate the state-spaces underlying the analysis of alternating automata. second, they are abstract algorithms with built-in refinement operators based on techniques that exploit information computed by abstract fixed points (and not counter-examples as it is usually the case). the efficiency of our new algorithms is illustrated by experimental results.
growth rates of complexity of power-free languages. we present a new fast algorithm for calculating the growth rate of complexity for regular languages. using this algorithm we develop a space and time efficient method to approximate growth rates of complexity of arbitrary power-free languages over finite alphabets. through extensive computer-assisted studies we sufficiently improve all known upper bounds for growth rates of such languages, obtain a lot of new bounds and discover some general regularities.
the picker-chooser diameter game. positional games are played under several rules on the same hypergraph. we consider some intriguing connections among the outcomes of the maker-breaker and the picker-chooser versions. the latter one was introduced by beck (2002) [5] and proved to be important in understanding positional games in general. beck had the profound conjecture that playing on the same hypergraph, picker has better chances than maker. the main goal of this paper is to confirm this conjecture for the notoriously hard diameter-2 game that was studied by balogh et al. (2009) [1]. the diameter-2 game is also an example of the fact that the probabilistic intuition, or ''erdos paradigm'' can fail completely, however, the acceleration of the game can restore it. the picker-chooser version is closer to erdos paradigm: there are almost matching lower and upper bounds for the critical density. pursuing these goals, we extend the theory of picker-chooser games to biased and discrepancy games, and develop erdos-selfridge type results.
amount of nonconstructivity in deterministic finite automata. when d. hilbert used nonconstructive methods in his famous paper on invariants (1888), p. gordan tried to prevent the publication of this paper considering these methods as non-mathematical. l.e.j. brouwer in the early twentieth century initiated intuitionist movement in mathematics. his slogan was ''nonconstructive arguments have no value for mathematics''. however, p. erdos got many exciting results in discrete mathematics by nonconstructive methods. it is widely believed that these results either cannot be proved by constructive methods or the proofs would have been prohibitively complicated. the author (freivalds, 2008) [10] showed that nonconstructive methods in coding theory are related to the notion of kolmogorov complexity. we study the problem of the quantitative characterization of the amount of nonconstructiveness in nonconstructive arguments. we limit ourselves to computation by deterministic finite automata. the notion of nonconstructive computation by finite automata is introduced. upper and lower bounds of nonconstructivity are proved.
csp duality and trees of bounded pathwidth. we study non-uniform constraint satisfaction problems definable in monadic datalog stratified by the use of non-linearity. we show how such problems can be described in terms of homomorphism dualities involving trees of bounded pathwidth and in algebraic terms. for this, we introduce a new parameter for trees that closely approximates pathwidth and can be characterised via a hypergraph searching game.
playing the perfect kriegspiel endgame. retrograde analysis is an algorithmic technique for reconstructing a game tree starting from its leaves; it is useful to solve some specific subsets of a complex game, for example a chess endgame, achieving optimal play in these situations. position values can then be stored in ''tablebases'' for instant access, in order to save analysis time, as is the norm in professional chess programs. this paper shows that a similar approach can be used to solve subsets of certain imperfect information games such as kriegspiel (invisible chess) endgames. using a brute force retrograde analysis algorithm, a suitable data representation and a special lookup algorithm, one can achieve perfect play, with perfection meaning fastest checkmate in the worst case and without making any assumptions on the opponent. we investigate some kriegspiel endgames (krk, kqk, kbbk and kbnk), building the corresponding tablebases and casting light on some long standing open problems.
taking advantage of symmetries: gathering of many asynchronous oblivious robots on a ring. one of the recently considered models of robot-based computing makes use of identical, memoryless mobile units placed in nodes of an anonymous graph. the robots operate in look-compute-move cycles; in one cycle, a robot takes a snapshot of the current configuration (look), takes a decision whether to stay idle or to move to one of the nodes adjacent to its current position (compute), and in the latter case makes an instantaneous move to this neighbor (move). cycles are performed asynchronously for each robot. in such a restricted scenario, we study the influence of symmetries of the robot configuration on the feasibility of certain computational tasks. more precisely, we deal with the problem of gathering all robots at one node of the graph, and propose a solution based on a symmetry-preserving strategy. when the considered graph is an undirected ring and the number of robots is sufficiently large (more than 18), such an approach is proved to solve the problem for all starting situations, as long as gathering is feasible. in this way we also close the open problem of characterizing symmetric situations on the ring which admit a gathering [r. klasing, e. markou, a. pelc: gathering asynchronous oblivious mobile robots in a ring, theoret. comput. sci. 390 (1) (2008) 27-39]. the proposed symmetry-preserving approach, which is complementary to symmetry-breaking techniques found in related work, appears to be new and may have further applications in robot-based computing.
class constrained bin packing revisited. we study the following variant of the bin packing problem. we are given a set of items, where each item has a (non-negative) size and a color. we are also given an integer parameter k, and the goal is to partition the items into a minimum number of subsets such that for each subset s in the solution, the total size of the items in s is at most 1 (as in the classical bin packing problem) and the total number of colors of the items in s is at most k (which distinguishes our problem from the classical version). we follow earlier work on this problem and study the problem in both offline and online scenarios.
optimality of some algorithms to detect quasiperiodicities. improving a 1993 algorithm of apostolico and ehrenfeucht, independently iliopoulos and mouchard in 1999 and brodal and pedersen in 2000 provided o(nlog(n)) algorithms to determine all maximal quasiperiodicities of a word of length n. we show here the optimality of this bound providing an infinite family of words w containing o(|w|log|w|) maximal quasiperiodicities. we also show that this bound is not reached for the celebrated family of fibonacci words.
parallel-machine scheduling with deteriorating jobs and rejection. we consider several parallel-machine scheduling problems in which the processing time of a job is a (simple) linear increasing function of its starting time and jobs can be rejected by paying penalties. the objective is to minimize the scheduling cost of the accepted jobs plus the total penalty of the rejected jobs. three variations of the scheduling cost are considered in this paper. the first is the makespan, the second is the total weighted completion time (for simple linear deterioration), and the third is the total completion time. for the former two problems, we propose two fully polynomial-time approximation schemes to solve them when the number of machines is fixed. for the last problem, we present an optimal o(n^2)-time dynamic programming algorithm when the deteriorating rates are equal for all jobs.
verifying parallel programs with dynamic communication structures. we address the verification problem of networks of communicating pushdown systems modeling communicating parallel programs with procedure calls. processes in such networks can read the control state of the other processes according to a given communication structure (specifying the observability rights between processes). the reachability problem of such models is undecidable in general. first, we define a class of networks that effectively preserves recognizability (hence, its reachability problem is decidable). then, we consider networks where the communication structure can change dynamically during the execution according to a phase graph. the reachability problem for these dynamic networks being undecidable in general, we define a subclass for which it becomes decidable. then, we consider reachability when the switches in the communication structures are bounded. we show that this problem is undecidable even for one switch. we define a natural class of models for which this problem is decidable. this class can be used in the definition of an efficient semi-decision procedure for the analysis of the general model of dynamic networks. our techniques allowed to find bugs in two versions of a windows nt bluetooth driver.
a combinatorial approach to the analysis of bucket recursive trees. in this work we provide a combinatorial analysis of bucket recursive trees, which have been introduced previously as a natural generalization of the growth model of recursive trees. our analysis is based on the description of bucket recursive trees as a special instance of the so-called bucket increasing trees, which is a family of combinatorial objects introduced in this paper. using this combinatorial description we obtain exact and limiting distribution results for the parameter depth of a specified element, descendants of a specified element and degree of a specified element.
treewidth and minimum fill-in on permutation graphs in linear time. permutation graphs form a well-studied subclass of cocomparability graphs. permutation graphs are the cocomparability graphs whose complements are also cocomparability graphs. a triangulation of a graph g is a graph h that is obtained by adding edges to g to make it chordal. if no triangulation of g is a proper subgraph of h then h is called a minimal triangulation. the main theoretical result of the paper is a characterisation of the minimal triangulations of a permutation graph, that also leads to a succinct and linear-time computable representation of the set of minimal triangulations. we apply this representation to devise linear-time algorithms for various minimal triangulation problems on permutation graphs, in particular, we give linear-time algorithms for computing treewidth and minimum fill-in on permutation graphs.
sharp thresholds for hamiltonicity in random intersection graphs. random intersection graphs, g"n","m","p, is a class of random graphs introduced in karonski (1999) [7] where each of the n vertices chooses independently a random subset of a universal set of m elements. each element of the universal sets is chosen independently by some vertex with probability p. two vertices are joined by an edge iff their chosen element sets intersect. given n, m so that m=@?n^@a@?, for any real @a different than one, we establish here, for the first time, a sharp threshold for the graph property ''contains a hamilton cycle''. our proof involves new, nontrivial, coupling techniques that allow us to circumvent the edge dependencies in the random intersection graph model.
on the number of episturmian palindromes. episturmian words are a suitable generalization to arbitrary alphabets of sturmian words. in this paper we are interested in the problem of enumerating the palindromes in all episturmian words over a k-letter alphabet a"k. we give a formula for the map g"k giving for any n the number of all palindromes of length n in all episturmian words over a"k. this formula extends to k>2 a similar result obtained for k=2 by the second and third authors in 2006. the map g"k is expressed in terms of the map p"k counting for each n the palindromic prefixes of all standard episturmian words (epicentral words). for any n>=0, p"2(n)=@f(n+2), where @f is the totient euler function. the map p"k plays an essential role also in the enumeration formula for the map @l"k counting for each n the finite episturmian words over a"k. similarly to euler's function, the behavior of p"k is quite irregular. the first values of p"k and of the related maps g"k, and @l"k for 3@?k@?6 have been calculated and reported in the paper. some properties of p"k are shown. in particular, broad upper and lower bounds for p"k, as well as for @?"m"="0^np"k(m) and g"k, are determined. finally, some conjectures concerning the map p"k are formulated.
deadline scheduling and power management for speed bounded processors. in this paper we consider online deadline scheduling on a processor that can manage its energy usage by scaling the speed dynamically or entering a sleep state. a new online scheduling algorithm called soa is presented. assuming speed can be scaled arbitrarily high (the infinite speed model), soa can complete all jobs with reduced energy usage, improving the competitive ratio for energy from 2^2^@a^-^2@a^@a+2^@a^-^1+2 (irani et al. (2007) [17]) to @a^@a+2, where @a is the constant involved in the speed-to-power function, commonly believed to be 2 or 3. more importantly, soa is the first algorithm that works well even if the processor has a fixed maximum speed and the system is overloaded. in this case, soa is 4-competitive for throughput and (@a^@a+@a^24^@a+2)-competitive for energy. note that the throughput ratio cannot be better than 4 even if energy is not a concern.
adaptive star grammars and their languages. motivated by applications that require mechanisms for describing the structure of object-oriented programs, adaptive star grammars are introduced, and their fundamental properties are studied. in adaptive star grammars, rules are actually schemata which, via the cloning of so-called multiple nodes, may adapt to potentially infinitely many contexts when they are applied. this mechanism makes adaptive star grammars more powerful than context-free graph grammars. nevertheless, they turn out to be restricted enough to share some of the basic characteristics of context-free devices. in particular, the underlying substitution operator enjoys associativity and confluence properties quite similar to those of context-free graph grammars, and the membership problem for adaptive star grammars is decidable.
an nlogn algorithm for hyper-minimizing a (minimized) deterministic automaton. we improve a recent result [a. badr, hyper-minimization in o(n^2), internat. j. found. comput. sci. 20 (4) (2009) 735-746] for hyper-minimized finite automata. namely, we present an o(nlogn) algorithm that computes for a given deterministic finite automaton (dfa) an almost-equivalent dfa that is as small as possible-such an automaton is called hyper-minimal. here two finite automata are almost-equivalent if and only if the symmetric difference of their languages is finite. in other words, two almost-equivalent automata disagree on acceptance on finitely many inputs. in this way, we solve an open problem stated in [a. badr, v. geffert, i. shipman, hyper-minimizing minimized deterministic finite state automata, rairo theor. inf. appl. 43 (1) (2009) 69-94] and by badr. moreover, we show that minimization linearly reduces to hyper-minimization, which shows that the time-bound o(nlogn) is optimal for hyper-minimization. independently, similar results were obtained in [p. gawrychowski, a. jez, hyper-minimisation made efficient, in: proc. 34th int. symp. mathematical foundations of computer science, in: lncs, vol. 5734, springer, 2009, pp. 356-368].
optimal byzantine-resilient convergence in uni-dimensional robot networks. given a set of robots with arbitrary initial location and no agreement on a global coordinate system, convergence requires that all robots asymptotically approach the exact same, but unknown beforehand, location. robots are oblivious-they do not recall the past computations-and are allowed to move in a one-dimensional space. additionally, robots cannot communicate directly, instead they obtain system related information only via visual sensors. even though convergence and the classical distributed approximate agreement problem (that requires correct processes to decide, for some constant @e, values distance @e apart and within the range of initial proposed values) are similar, we provide evidence that solving convergence in robot networks requires specific assumptions about synchrony and byzantine resilience. in more detail, we prove necessary and sufficient conditions for the convergence of mobile robots despite a subset of them being byzantine (i.e. they can exhibit arbitrary behavior). additionally, we propose two deterministic convergence algorithms for robot networks and analyze their correctness and complexity in various atomicity and synchrony settings. the first algorithm tolerates f byzantine robots for (2f+1)-sized robot networks in fully synchronous atom networks, while the second proposed algorithm tolerates f byzantine robots for (3f+1)-sized robot networks in non-atomic corda networks. the resilience of these two algorithms is proved to be optimal.
contract-based discovery of web services modulo simple orchestrators. web services are distributed processes exposing a public description of their behavior, or contract. the availability of repositories of web service descriptions enables interesting forms of dynamic web service discovery, such as searching for web services having a specified contract. this calls for a formal notion of contract equivalence satisfying two contrasting goals: being as coarse as possible so as to favor web services reuse, and guaranteeing successful client/service interaction. we study an equivalence relation that achieves both goals under the assumption that client/service interactions may be mediated by simple orchestrators. in the framework we develop, orchestrators play the role of proofs (in the curry-howard sense) justifying an equivalence relation between contracts. this makes it possible to automatically synthesize orchestrators out of web services contracts.
the parameterized complexity of editing graphs for bounded degeneracy. we examine the parameterized complexity of the problem of editing a graph to obtain an r-degenerate graph. we show that for the editing operations vertex deletion and edge deletion, both separately and combined, the problem is w[p]-complete, and remains w[p]-complete even if the input graph is already (r+1)-degenerate, or has maximum degree 2r+1 for all r>=2. we also demonstrate fixed-parameter tractability for several clique based problems when the input graph has bounded degeneracy.
computational complexity of long paths and cycles in faulty hypercubes. the problem of existence of an optimal-length (long) fault-free cycle in the n-dimensional hypercube with f faulty vertices is np-hard. this holds even in case that f is bounded by a polynomial of degree three (six) with respect to n. on the other hand, there is a linear (quadratic) bound on f which guarantees that the problem is decidable in polynomial time. similar results are obtained for paths as well as for paths between prescribed endvertices.
n-player partizan games. conway's theory of partizan games is both a theory of games and a theory of numbers. an extension of this theory to classify partizan games with an arbitrary finite number of players is presented.
port-based modeling and simulation of mechanical systems with rigid and flexible links. in this paper, a systematic procedure for the definition of the dynamical model in port-hamiltonian form of mechanical systems is presented as the result of the power-conserving interconnection of a set of basic components (rigid bodies, flexible links, and kinematic pairs). since rigid bodies and flexible links are described within the port-hamiltonian formalism, their interconnection is possible once a proper relation between the power-conjugated port variables is deduced. these relations are the analogous of the kirchhoff laws of circuit theory. from the analysis of a set of oriented graphs that describe the topology of the mechanism, an automatic procedure for deriving the dynamical model of a mechanical system is illustrated. the final model is a mixed port-hamiltonian system, because of the presence of a finite-dimensional subsystem (modeling the rigid bodies) and an infinite-dimensional one (describing the flexible links). besides facilitating the deduction of the dynamical equations, it is shown howthe intrinsic modularity of this approach also simplifies the simulation phase.
nonlinear and filtered force/position mappings in bilateral teleoperation with application to enhanced stiffness discrimination. motivated by applications involving soft-tissue manipulation such as robotic surgery, the transparency objectives in bilateral teleoperation are redefined to include monotonic non-linear and linear-time-invariant filter mappings between the master/slave position and force signals. to demonstrate the utility of the new performance measures, a stiffness discrimination telemanipulation task of soft environments is considered. a nonlinear force mapping can enhance stiffness discrimination thresholds as shown through a set of psychophysics experiments.lyapunov-based adaptive motion/force controllers are presented that can achieve the new transparency objectives in the presence of dynamic uncertainty in the master, slave, user, and environment and in the absence of time delay. given a priori known bounds on unknown dynamic parameters, a framework for robust stability analysis is proposed that uses an off-axis circle criterion and the nyquist envelope of interval plant systems. nonlinear- and linear-filtered mappings are achieved in experiments with a two-axis teleoperation system.
dynamic manipulation inspired by the handling of a pizza peel. this paper discusses dynamic manipulation inspired by the handling mechanism of a pizza chef. the chef handles a tool called "pizza peel," where a plate is attached at the tip of a bar, and he remotely manipulates a pizza on the plate. we found that he aggressively utilizes only two degrees of freedom (dofs) from the remote handling location during manipulation: translation along the bar and rotation about the bar. from the viewpoint of a dynamic system, the inertial loads for these specific dofs are never affected by the length of the bar. this is important for the production of quick plate motions so that the object on the plate can be dynamically and remotely manipulated. applying this handling mechanism to a robot system, we first reveal how tomake the object's motion for three dofs by using two dofs of platemotion. we then show that it is guaranteed to achieve an arbitrary desired set of position and orientation of the object by the proposed manipulation scheme. the proposed method has good manipulability because the translational motion of the object can be fully decoupled from the rotational motion (though not vice versa). finally, we show a couple of experiments that confirm the basic idea.
improving the human-robot interface through adaptive multispace transformation. teleoperation is essential for applications in which, despite the availability of a precise geometrical definition of the working area, a task cannot be explicitly programmed. this paper describes a method of assisted teleoperation that improves the execution of such tasks in terms of ergonomics, precision, and reduction of execution time. the relationships between the operating spaces corresponding to the human-robot interface triangle are analyzed. the proposed teleoperation aid is based on applying adaptive transformations between these spaces.
swarmorph: multirobot morphogenesis using directional self-assembly. in this paper, we propose swarmorph: a distributed morphology generation mechanism for autonomous self-assembling mobile robots. self-organized growth of global morphological structures emerges through the repeated application of local morphology extension rules. we present details of the directional self-assembly mechanism that provides control over the orientation of interrobot connections. we conduct realworld experiments to validate the low-level directional self-assembly mechanism and the growth of global morphologies. we demonstrate the scalability of the approach with large numbers of robots in simulation-based experiments.
fast generation of multiple collision-free and linear trajectories in dynamic environments. a fast and complete collision-detection procedure is presented in this paper. given a straight-line path for a mobile robot, the current instant of time, and estimations of the obstacles motions, a set of speeds is obtained in real time with neither space nor time discretization. the mobile-robot path together with each one of these speeds, if they exist, states a different collision-free trajectory. all these trajectories verify that the minimum distance between the mobile robot and the obstacles at anytime is greater than or equal to a configurable parameter. this set of speeds is fast updated when a change in the original mobile-robot path is considered. if the current mobile-robot speed does not belong to the mentioned set of speeds, then the mobile robot will collide with at least one obstacle and, in this case, a set of accelerations is fast-tuned to avoid all the obstacles. collision-free trajectories that do not verify the dynamic constraints of the mobile robot are simply rejected.
increasing accuracy in image-guided robotic surgery through tip tracking and model-based flexion correction. robot assistance can enhance minimally invasive image-guided surgery, but flexion of the thin surgical instrument shaft impairs accurate control by creating errors in the kinematic model. two controller enhancements that can mitigate these errors are improved kinematic models that account for flexing and direct measurement of the instrument tip's position. this paper presents an experiment quantifying the benefits of these enhancements in an effort to inform development of an image-guided robot control system accurate in the presence of quasi-static instrument flexion. the study measured a controller's ability to guide a flexing instrument along user-commanded motions while preventing incursions into a forbidden region virtual fixture. compared with the controller using neither enhancement, improved kinematics and reduced maximum incursion depth into the forbidden region by 28%, tip tracking by 67%, and both enhancements together by 83%.
global output tracking control of flexible joint robots via factorization of the manipulator mass matrix. this paper investigates the problem of global output feedback tracking control of flexible joint robots. despite the fact that only link position and actuator position are available from measurements, the proposed controller ensures that the link position globally tracks the desired trajectory while keeping all the remaining signals bounded. the controller development uses a partial state-feedback linearization technique combined with the integrator backstepping control design method whereas a filter and an observer are utilized to remove the requirement of link and actuator velocity measurements. partial state-feedback linearization of robot dynamics is performed by factoring the manipulator mass matrix into a quadratic form involving an integrable root matrix. the applicability of the proposed general design methodology is illustrated by an example of flexible joint planar robots. numerical results for a two-link flexible joint planar robot are also provided.
automatic camera-based microscope calibration for a telemicromanipulation system using a virtual pattern. in the context of virtualized-reality-based telemicromanipulation, this paper presents a visual calibration technique for an optical microscope coupled to a charge-coupled device (ccd) camera. the accuracy and flexibility of the proposed automatic virtual calibration method, based on parallel single-plane properties, are outlined. in contrast to standard approaches, a 3-d virtual calibration pattern is constructed using the micromanipulator tip with subpixel-order localization in the image frame. the proposed procedure leads to a linear system whose solution provides directly both the intrinsic and extrinsic parameters of the geometrical model. computer simulations and real data have been used to test the proposed technique, and promising results have been obtained. based on the proposed calibration techniques, a 3-d virtual microenvironment of the workspace is reconstructed through the real-time imaging of two perpendicular optical microscopes. our method provides a flexible, easy-to-use technical alternative to the classical techniques used in micromanipulation systems.
velocity-scheduling control for a unicycle mobile robot: theory and experiments. improvement over classical dynamic feedback linearization for a unicycle mobile robots is proposed. compared to classical extension, the technique uses a higher-dimensional state extension, which allows rejecting a constant disturbance on the robot rotational axis. the proposed dynamic extension acts as a velocity scheduler that specifies, at each time instant, the ideal translational velocity that the robot should have. by using a higher-order extension, both the magnitude and the orientation of the velocity vector can be generated, which introduces robustness in the control scheme. stability for both asymptotic convergence to a point and trajectory tracking is proven. the theoretical results are illustrated first in simulation, and then experimentally on the autonomous mobile robot fouzy iii.
identification of contact dynamics parameters for stiff robotic payloads. this paper investigates and demonstrates the feasibility of identifying contact dynamics parameters for stiff robotic payloads using a robotic system. the contact dynamics model for stiff payloads is motivated, and theoretical parameter values and bounds are provided. then, the effect of nonidealities such as surface roughness and plastic deformation on the theoretical values is demonstrated. a row-wise-scaled total least-squares parameter estimation algorithm is proposed and applied to experimental data measured using the special purpose dexterous manipulator task verification facility manipulator at the canadian space agency. the experimental results are compared to a separate set of experiments with a material testing machine as well as finite-element modeling results. finally, the experimental findings are generalized by providing guidelines for the maximum identifiable payload stiffness as a function of the position resolution, the maximum exertable force, and the structural stiffness of the robotic system.
kinematic modeling and analysis of skid-steered mobile robots with applications to low-cost inertial-measurement-unit-based motion estimation. skid-steered mobile robots are widely used because of their simple mechanism and high reliability. understanding the kinematics and dynamics of such a robotic platform is, however, challenging due to the complex wheel/ground interaction and kinematic constraints. in this paper, we develop a kinematic modeling scheme to analyze the skid-steered mobile robot. based on the analysis of the kinematics of the skid-steered mobile robot, we reveal the underlying geometric and kinematic relationships between the wheel slips and locations of the instantaneous rotation centers. as an application example, we also present how to utilize the modeling and analysis for robot positioning and wheel slip estimation using only low-cost strapdown inertial measurement units. the robot positioning and wheel slip-estimation scheme is based on an extended kalman filter (ekf) design that incorporates the kinematic constraints for accuracy enhancement. the performance of the ekf-based positioning and wheel slip-estimation scheme are also presented. the estimation methodology is tested and validated experimentally on a robotic test bed.
configuration tracking for continuum manipulators with coupled tendon drive. robotic control of flexible devices can enhance and simplify many medical procedures. we present a method for controlling a tendon-driven continuum manipulator by means of specifying the shape configuration. the basis for control is a linear beam configuration model that transforms beam configuration to tendon displacement by modeling internal loads of the compliant system. an essential aspect of this model is the inclusion of both themechanical and geometrical coupling among serial articulating sections. important capabilities of this model are the general forward kinematics and the decoupled inverse kinematics that allow for independent control of multiple sections. tracking results are presented for a cardiac catheter with two articulating sections.
a sensor-based controller for homing of underactuated auvs. a new sensor-based homing integrated guidance and control law is presented to drive an underactuated autonomous underwater vehicle (auv) toward a fixed target, in three dimensions, using the information provided by an ultrashort baseline (usbl) positioning system. the guidance and control law is first derived using quaternions to express the vehicle's attitude kinematics, which are directly obtained from the time differences of arrival (tdoa) measured by the usbl sensor. the dynamics are then included resorting to backstepping techniques. the proposed lyapunov based control law yields global asymptotic stability in the absence of external disturbances and is further extended, keeping the same properties, to the case where constant known ocean currents affect the dynamics of the vehicle. finally, a globally exponentially stable nonlinear tdoa and range-based observer is introduced to estimate the ocean current and uniform asymptotic stability is obtained for the overall closed-loop system. simulations are presented illustrating the performance of the proposed solutions.
shortest paths to obstacles for a polygonal dubins car. in this paper, we characterize the time-optimal trajectories leading a dubins car in collision with the obstacles in its workspace. due to the constant velocity constraint characterizing the dubins car model, these trajectories form a sufficient set of shortest paths between any robot configuration and the obstacles in the environment.based on these paths, we define and give the algorithm for computing a distance function that takes into account the nonholonomic constraints and captures the nonsymmetric nature of the system. the developments presented here assume that the obstacles and the robot are polygons although the methodology can be applied to different shapes.
interpersonal synchronization of body motion and the walk-mate walking support robot. everyone has probably experienced the phenomenon where their footsteps unconsciously synchronize with their partner while walking together. this interpersonal synchronization of body motion has been widely observed and is significant in the context of social psychology. however, the mechanism of this embodied cooperation still remains obscure and has not been substantially developed as an engineering application. in this study, by assuming "mutual entrainment" as an interpersonal synchronization mechanism, we establish a new cooperative walking system between a walking human and a walking robot (an agent as a virtual robot). in this system, rhythmic sounds corresponding to the timing of footsteps are exchanged between them on the basis of our previous studies. as a result, it was demonstrated that the two walking rhythms adapt mutually after the start of interaction, and stable synchronization is generated automatically. this global entrained state exhibits dynamic stability with small fluctuation in the walking period. applying this method to walking support for parkinson's disease and hemiplegia patients, its effectiveness in stabilizing the walking of the patient was shown. these results indicate the importance of interpersonal mutual entrainment of rhythmic motion for walking support, and new human-robot interaction technologies are expected as an extension of this framework.
nonlinear feedback control of a gravity-assisted underactuated manipulator with application to aircraft assembly. a nonlinear feedback scheme for a gravity-assisted underactuated manipulator with second-order nonholonomic constraints is presented in this paper. the joints of the hyper articulated arm have no dedicated actuators but are activated by gravity. by tilting the base link appropriately, the gravitational torque drives the unactuated links to a desired angular position.with simple locking mechanisms, the hyperarticulated arm can change its configuration using only one actuator at the base. this underactuated arm designwas motivated by the need for a compact snakelike robot that can go into aircraft wings and perform assembly operations using heavy end-effectors. the dynamics of the unactuated links are essentially second-order nonholonomic constraints for which there are no general methods to design closed-loop control. we propose a nonlinear closed-loop control law that is guaranteed to be stable in positioning one unactuated joint at a time. we synthesize a lyapunov function to prove the convergence of this control scheme. the lyapunov function also generates estimates of the domain of convergence of the control law for various control gains. the control algorithm is implemented on a prototype three-link system. finally, we provide some experimental results to demonstrate the efficacy of the control scheme.
vision-aided inertial navigation for spacecraft entry, descent, and landing. in this paper, we present the vision-aided inertial navigation (visinav) algorithm that enables precision planetary landing. the vision front-end of the visinav system extracts 2-d-to- 3-d correspondences between descent images and a surface map (mapped landmarks), as well as 2-d-to-2-d feature tracks through a sequence of descent images (opportunistic features). an extended kalman filter (ekf) tightly integrates both types of visual feature observations with measurements from an inertial measurement unit. the filter computes accurate estimates of the lander's terrain-relative position, attitude, and velocity, in a resource-adaptive and hence real-time capable fashion. in addition to the technical analysis of the algorithm, the paper presents validation results from a sounding-rocket test flight, showing estimation errors of only 0.16 m/s for velocity and 6.4 m for position at touchdown. these results vastly improve current state of the art for terminal descent navigation without visual updates, and meet the requirements of future planetary exploration missions.
a miniature mobile robot for navigation and positioning on the beating heart. robotic assistance enhances conventional endoscopy; yet, limitations have hindered its mainstream adoption for cardiac surgery. heartlander is a miniature mobile robot that addresses several of these limitations by providing precise and stable access over the surface of the beating heart in a less-invasive manner. the robot adheres to the heart and navigates to any desired target in a semiautonomous fashion. the initial therapies considered for heartlander generally require precise navigation to multiple surface targets for treatment. to balance speed and precision, we decompose any general target acquisition into navigation to the target region followed by fine positioning to each target. in closed-chest, beating-heart animal studies, we demonstrated navigation to targets located around the circumference of the heart, as well as acquisition of target patterns on the anterior and posterior surfaces with an average error of 1.7 mm. the average drift encountered during station-keeping was 0.7 mm. these preclinical results demonstrate the feasibility of precise semiautonomous delivery of therapy to the surface of the beating heart using heartlander.
extending collision avoidance methods to consider the vehicle shape, kinematics, and dynamics of a mobile robot. most collision avoidance methods do not consider the vehicle shape and its kinematic and dynamic constraints, assuming the robot to be point-like and omnidirectional with no acceleration constraints. the contribution of this paper is a methodology to consider the exact shape and kinematics, as well as the effects of dynamics in the collision avoidance layer, since the original avoidance method does not address them. this is achievable by abstracting the constraints from the avoidance methods in such a way that when the method is applied, the constraints already have been considered. this study is a starting point to extend the domain of applicability to a wide range of collision avoidance methods.
the flying brick: a cautionary note on testing flying robots using guide wires. a simple experiment demonstrates that an average vertical force can be produced by a small vibrator motor attached to a frame constrained to slide vertically on guide wires. the vertical force produced is sufficient to make the sliding element hover, similarly to a biologically inspired robotic insect. we show that this effect depends on the natural resonance frequency of the guide wires and the nature of the mechanical coupling between wires and sliding element. based on the result of this experiment, we recommend that a control experiment should be performed in order to reach unambiguous conclusions concerning the actual flying capabilities of robotic insects tested using this kind of methodology.
development of a flying robot with a pantograph-based variable wing mechanism. we develop a flying robot with a new pantographbased variable wing mechanism for horizontal-axis rotorcrafts (cyclogyro rotorcrafts). a key feature of the new mechanism is to have a unique trajectory of variable wings that not only change angles of attack but also expand and contract according to wing positions. as a first step, this paper focuses on demonstrating the possibility of the flying robot with this mechanism. after addressing the pantograph-based variable wing mechanism and its features, a simulation model of this mechanism is constructed. next, we present some comparison results (between the simulation model and experimental data) for a prototype body with the proposed pantograph-based variable wing mechanism. both simulation and experimental results show that the flying robot with this new mechanism can generate enough lift forces to keep itself in the air. furthermore, we construct a more precise simulation model by considering rotational motion of each wing. as a result of optimizing design parameters using the precise simulation model, flight performance experimental results demonstrate that the robot with the optimal design parameters can generate not only enough lift forces but a 155 gf payload as well.
the role of modular robotics in mediating nonverbal social exchanges. this paper outlines the use of modular robotics to encourage and facilitate nonverbal communication during therapeutic intervention in dementia care. a set of new socially interactive modular robotic devices called rolling pins (rps) has been designed and developed to assist the therapist in interacting with dementiaaffected patients. the rps are semitransparent plastic tubes that are capable of measuring their orientation and the speed of their rotation; at a local level, they have three types of feedback: red, green, and blue light, sound, and vibration. the peculiarity of the rps is that they are able to communicate with each other or with other devices equipped with the same radio communication technology. the rps are usually used in pairs, as the local feedback of an rp can be set depending not only on its own speed and orientation but also on the speed and the orientation of the peer rp. the system is not used as a therapeutic tool per se but as a facilitator and a mediator of social dynamics during normal therapy to counteract social isolation that can result in dementia through the loss of social skills. an experiment is reported that shows that by using the rps, the patients participated in the activity by coordinating their behavior with the therapist and imitating the same interaction patterns generated by the therapist.
nims-pl: a cable-driven robot with self-calibration capabilities. we present the networked infomechanical system for planar translation, which is a novel two-degree-of-freedom (2-dof) cable-driven robot with self-calibration and online drift-correction capabilities. this system is intended for actuated sensing applications in aquatic environments. the actuation redundancy resulting from in-plane translation driven by four cables results in an infinite set of tension distributions, thus requiring real-time computation of optimal tension distributions. to this end, we have implemented a highly efficient, iterative linear programming solver, which requires a very small number of iterations to converge to the optimal value. in addition, two novel self-calibration methods have been developed that leverage the robot's actuation redundancy. the first uses an incremental displacement, or jitter method, whereas the second uses variations in cable tensions to determine end-effector location. we also propose a novel least-squares drift-detection algorithm, which enables the robot to detect long-term drift. combined with self-calibration capabilities, this drift-monitoring algorithm enables long-term autonomous operation. to verify the performance of our algorithms, we have performed extensive experiments in simulation and on a real system.
visual servoing path planning via homogeneous forms and lmi optimizations. path planning is a useful technique for visual servoing as it allows one to take into account system constraints and achieve desired performances during the camera motion. in this paper, we propose a new framework for path planning based on the use of homogeneous forms and linear matrix inequalities (lmis). specifically, we introduce a general parametrization of the trajectories from the initial to the desired location based on homogeneous forms and a parameter-dependent version of the rodrigues formula. this allows us to impose typical constraints (field of view, workspace, joint, avoidance of collision, and occlusion) via positivity conditions on suitable homogeneous forms. then, we reformulate the problem of finding a trajectory in the 3-d space satisfying all these constraints as an lmi optimization that can handle the maximization of typical performances (e.g., visibility margin, similarity to a straight line). the planned camera path is tracked by using an image-based controller. the proposed approach is illustrated and validated through simulations and experiments.
control of a class of underactuated mechanical systems using sliding modes. in this paper, we present a sliding mode control algorithm to robustly stabilize a class of underactuated mechanical systems that are not linearly controllable and violate brockett's necessary condition for smooth asymptotic stabilization of the equilibrium, with parametric uncertainties. in defining the class of systems, a few simplifying assumptions are made on the structure of the dynamics; in particular, the damping forces are assumed to be linear in velocities. we first propose a switching surface design for this class of systems, and subsequently, a switched algorithm to reach this surface in finite time using conventional and higher order sliding mode controllers. the stability of the closed-loop system is investigated with an undefined relative degree of the sliding functions. the controller gains are designed such that the controller stabilizes the actual system with parametric uncertainty. the proposed control algorithm is applied to two benchmark problems: a mobile robot and an underactuated underwater vehicle. simulation results are presented to validate the proposed scheme.
construction methodology for a remote ultrasound diagnostic system. in the present paper, we describe a method for constructing a remote ultrasound diagnostic system. remote diagnosis can be realized using a communication network. we have developed a master-slave type remote medical system to diagnose shoulder diseases, such as dialysis-related amyloid arthropathy (draa), by ultrasonographic images. proper positioning" orientation, and contact force between the ultrasound probe and the affected area of the patient are required in order to acquire proper diagnostic images. safety and manipulability are also required when operating the remote medical system through a communication network. therefore, the system has impedance control cnpability for positioning of the master and slave manipulators in order to convey the contact force and enhance manipulability. in addition, the system has continuous-path control capability for the orientation of the slave manipulator in order to realize smooth and accurate motion of the ultrasound probe, even if the sampling rate of the transmission of the orientation data of the master manipulator is not sufficient. the results of remote diagnostic experiments demonstrated that a healthcare professional could diagnose real patients through a communication network using the constructed system.
power consumption modeling of skid-steer tracked mobile robots on rigid terrain. power consumption is a key element in outdoor mobile robot autonomy. this issue is very relevant in skid-steer tracked vehicles on account of their large ground contact area. in this paper, the power losses due to dynamic friction have been modeled from two different perspectives: 1) the power drawn by the rigid terrain and 2) the power supplied by the motors. comparison of both approaches has provided new insight on skid steering on hard flat terrains at walking speeds. experimental power models, which also include traction resistance and other power losses, have been obtained for two different track widths over marble flooring and asphalt with auriga-β, which is a full-size mobile robot. to this end, various internal probes have been set at different points of the power stream. furthermore, new energy implications for navigation of these kinds of vehicles have been deduced and tested.
a hybrid motion classification approach for emg-based human-robot interfaces using bayesian and neural networks. in a human-robot interface, the prediction of motion, which is based on context information of a task, has the potential to improve the robustness and reliability of motion classification to control prosthetic devices or human-assisting manipulators. this paper proposes a task model using a bayesian network (bn) for motion prediction. given information of the previous motion, this task model is able to predict occurrence probabilities of the motions concerned in the task. furthermore, a hybrid motion classification framework has been developed based on the bn motion prediction. besides the motion prediction, electromyogram (emg) signals are simultaneously classified by a probabilistic neural network (nn). then, the motion occurrence probabilities are combined with the nn classifier's outputs to generate motion commands for control. with the proposed motion classification framework, it is expected that classification performance can be enhanced so that motion commands can be more robust and reliable. experiments have been conducted with four subjects to demonstrate the feasibility of the proposed methods. in these experiments, forearm motions are classified with emg signals considering a cooking task. finally, robot manipulation experiments were carried. out to verify the proposed human interface system with a task of taking meal. the experimental results indicate that the proposed methods improved the robustness and stability of motion classification.
impairment-based 3-d robotic intervention improves upper extremity work area in chronic stroke: targeting abnormal joint torque coupling with progressive shoulder abduction loading. the implementation of a robotic system (act3d) that allowed for a quantitative measurement of abnormal joint torque coupling in chronic stroke survivors and, most importantly, a quantitative means of initiating and progressing an impairment-based intervention, is described. individuals with chronic moderate to severe stroke (n = 8) participated in this single-group pretest-posttest design study. subjects were trained over eight weeks by progressively increasing the level of shoulder abduction loading experienced by the participant during reaching repetitions as performance improved. reaching work area was evaluated pre- and postintervention for ten different shoulder abduction loading levels along with isometric single-joint strength and a qualitative clinical assessment of impairment. there was a significant effect of session (pre versus post) with an increase in reaching work area, despite no change in single-joint strength. this data suggests that specifically targeting the abnormal joint torque coupling impairment through progressive shoulder abduction loading is an effective strategy for improving reading work area following hemiparetic stroke. application of robotics, namely, the act3d allowed for quantitative control ofthe exercise parameters needed to directly target the synergistic coupling impairment. the targeted reduction of abnormal joint torque coupling is likely the key factor explaining the improvements in reaching range of motion achieved with this intervention.
intrinsic constraints of neural origin: assessment and application to rehabilitation robotics. ideally, robots used for motor rehabilitation, in particular, during assessment, should minimally perturb the voluntary movements of a subject. in this paper, we show how a state-of-theart back-drivable robot, i.e., a robot that can be moved by the user with a low perceived mechanical impedance, when used for assessment can still perturb the voluntary movements of a subject. in particular, we show that, despite its low mechanical impedance, a robot may still not comply with the intrinsic kinematic constraints, which are of neural origin and are adopted by the human brain to solve redundancy in motor tasks. specifically, the redundant task under consideration is the 2-d pointing task, which is performed by a subject with the sole use of the wrist [3 degree of freedom (dof) kinematics]. wrist orientations during pointing tasks are assessed in two different scenarios. in the first experiment, a lightweight handheld device is used, which introduces no loading effect. in the second experiment, similar pointing tasks are performed with the subject interacting with a state-of-the-art robot for wrist rehabilitation. in the first case, intrinsic kinematic constraints arise as 2-d surfaces embedded in the 3-d space of wrist configuration. such surfaces are typically subject-dependent and reveal personal motor strategies. in the second case, a strong influence of the robot is remarked. in particular, 2-d surfaces still arise but are similar for all subjects and are referable to a mechanical origin (excessive loading by the robot). the assessment approach described in this paper, including both the experimental apparatus and dataanalysis method, can be used as a test for the degree of backdrivability of mechanisms and robots in relation to constraints of neural origin, thus allowing the design of robots that can actually cope with such constraints. the clinical potential impact is also discussed.
a distributed heuristic for energy-efficient multirobot multiplace rendezvous. we consider the problem of finding a set of trajectories for a heterogeneous group of mobile robots, such that a single service robot can rendezvous with every other member of the team in a prescribed order, and the total travel cost is minimized. we present a simple heuristic controller that runs independently on each robot, yet is guaranteed to achieve an approximation to global solution in bounded time linear in population size. simulation experiments empirically show that the methocl finds approximated solutions of near-optimal quality on average.
partially flagged parallel manipulators: singularity charting and avoidance. there are only three 6-sps parallel manipulators with triangular base and platform, i.e., the octahedral, the flagged, and the partially flagged, which are studied in this paper. the forward kinematics of the octahedral manipulator is algebraically intricate, while those of the other two can be solved by three trilaterations. as an additional nice feature, the flagged manipulator is the only parallel platform for which a cell decomposition of its singularity locus has been derived. here, we prove that the partially flagged manipulator also admits a well-behaved decomposition, technically called a stratification, some of whose strata are not topological cells, however. remarkably, the adjacency diagram of the 5-d and 6-d strata (which shows what 5-d strata are contained in the closure of a 6-d one) is the same as for the flagged manipulator. the availability of such a decomposition permits devising a redundant 7-sps manipulator, combining two partially flagged ones, which admits a control strategy that completely avoids singularities. simulation results support these claims.
extending the limits of feature-based slam with b-splines. this paper describes a simultaneous localization and mapping (slam) algorithm for use in unstructured environments that is effective regardless of the geometric complexity of the environment. features are described using b-splines as modeling tool, and the set of control points defining their shape is used to form a complete and compact description of the environment, thus making it feasible to use an extended kalman-filter (ekf) based slam algorithm. this method is the first known ekf-slam implementation capable of describing general free-form features in a parametric manner. efficient strategies for computing the relevant jacobians, perform data association, initialization, and map enlargement are presented. the algorithms are evaluated for accuracy and consistency using computer simulations, and for effectiveness using experimental data gathered from different real environments.
qualitative vision-based path following. we present a simple approach for vision-based path following for a mobile robot. based upon a novel concept called the funnel lane, the coordinates of feature points during the replay phase are compared with those obtained during the teaching phase in order to determine the turning direction. increased robustness is achieved by coupling the feature coordinates with odometry information. the system requires a single off-the-shelf, forward-looking camera with no calibration (either external or internal, including lens distortion). implicit calibration of the system is needed only in the form of a single controller gain. the algorithm is qualitative in nature, requiring no map of the environment, no image jacobian, no homography, no fundamental matrix, and no assumption about a flat ground plane. experimental results demonstrate the capability of real-time autonomous navigation in both indoor and outdoor environments and on flat, slanted, and rough terrain with dynamic occluding objects for distances of hundreds of meters. we also demonstrate that the same approach works with wide-angle and omnidirectional cameras with only slight modification.
vibration-induced frequency-controllable bidirectional locomotion for assembly and microrobotic applications. this paper describes vibration-induced bidirectional locomotion of a milliscale cylindrical body. using a laterally vibrating platform, we achieved a frequency-controlled bidirectional movement by attaching two polydimethylsiloxane cylindrical rods with microscale ratchet-shaped legs of different densities facing in opposite directions. the polymeric body (2 × 2 × 20 mm3) was placed on a glass slide covered by thin lubricating oil and vibrated at a constant amplitude of 0.2 mm. the micromobile composite cylinder changed its direction of motion at a cross-over frequency of 156 hz. the cross-over phenomena is due to the difference between static and kinetic friction coefficients of the two opposing parts.
a synchronization approach to trajectory tracking of multiple mobile robots while maintaining time-varying formations. in this paper, we present a synchronization approach to trajectory tracking of multiple mobile robots while maintaining time-varying formations. the main idea is to control each robot to track its desired trajectory while synchronizing its motion with those of other robots to keep relative kinematics relationships, as required by the formation. first, we pose the formation-control problem as a synchronization control problem and identify the synchronization control goal according to the formation requirement. the formation error is measured by the position synchronization error, which is defined based on the established robot network. second, we develop a synchronous controller for each robot's translation to guarantee that both position and synchronization errors approach zero asymptotically. the rotary controller is also designed to ensure that the robot is always oriented toward its desired position. both translational and rotary controls are supported by a centralized high-level planer for task monitoring and robot global localization. finally, we perform simulations and experiments to demonstrate the effectiveness of the proposed synchronization control approach in the formation control tasks.
dynamic manipulability of multifingered grasping. in this paper, we extend the concept of dynamic manipulability to evaluate the dynamic property of multifingered grasping systems consisting of amultifingered hand and a grasped object, and propose a measure of dynamic manipulability of multifingered grasping. similar to the original dynamic manipulability, the proposed measure evaluates the mapping from a set of realizable joint torques to a set of resultant accelerations of the grasped object, which forms an ellipsoid under a constant internal force constraint. it is clearly shown that the internal forces not only affect the volume of the ellipsoid, but also the amount of offset of the ellipsoid, while the gravity forces simply induce an offset. a new measure, i.e., omnidirectionality, is introduced to add a penalty to the original manipulability measure, which simply evaluates the volume of the ellipsoid, depending on how much the ellipsoid is offset. numerical examples by using a simple two-fingered robot hand are shown to demonstrate the effectiveness of the proposed measure.
minimum-order kalman filter with vector selector for accurate estimation of human body orientation. this paper describes a new quaternion-based kalman filter (kf) for estimating human body orientation using an inertial/magnetic sensor. the proposed algorithm is comprised of a quaternion measurement step and a kf step that are connected in feedback relationship. this allows the algorithm to have a minimum-order structure (i.e., fourth order) that is computationally very efficient. furthermore, to offer more reliable information to the quaternion measurement step, a vector selector scheme is adopted, which effectively adds the gyro measurement to the so-called wahba's problem that conventionally uses only the accelerometer and magnetometer measurements. this protects the algorithm against undesirable conditions such as fast movements and temporary magnetic disturbances, enabling it to compute an accurate orientation estimate. due to the computational efficiency of the algorithm, it is suitable for real-time ambulatory human motion tracking applications that require multiple and untethered inertial/magnetic sensors with low-cost onboard processing.
an adaptive automated robotic task-practice system for rehabilitation of arm functions after stroke. we present a novel robotic task-practice system, i.e., adaptive and automatic presentation of tasks (adapt), which is designed to enhance the recovery of upper extremity functions in patients with stroke. we designed adapt in accordance with current training guidelines for stroke rehabilitation; adapt engages the patient intensively, actively, and adaptively in a variety of realistic functional tasks that require reaching and manipulation. a general-purpose robot simulates the dynamics of the functional tasks and presents these functional tasks to the patient. a novel tool-changing system enables adapt to automatically switch between the tools corresponding to the functional tasks. the control architecture of adapt is composed of three main components: a high-level task scheduler, a functional task model, and a low-level admittance controller. the high-level task scheduler adaptively selects the task to practice and sets the task difficulty based on the previous performance of the patients. the functional task model generates desired trajectories based on learned models of task dynamics. tasks dynamics are modeled with receptive field weighted regression (rfwr), such that the feel of the task tools is accurately modeled, and the task difficulty can be easily adjusted. the low-level admittance controller, which is also learned with rfwr, implements the selected task trajectory for robot-patient interaction. the results of a preliminary experiment with a healthy subject demonstrate the successful operation of adapt.
a reactive robotized interface for lower limb rehabilitation: clinical results. this paper presents clinical results from the use of monitor-nomad (monimad), which is a reactive robotized interface for lower limb rehabilitation of patients suffering from cerebellar disease. the first problem to be addressed is the postural analysis of sit-to-stand motion. experiments with healthy subjects were performed for this purpose. analysis of external forces shows that sit-to-stand transfer can be subdivided into several phases: preacceleration, acceleration, start rising, and rising. observation of center of pressure, ground forces, and horizontal components force on handles yields rules that identify the stability of the patient and adjust the robotic interface motion to the human voluntary movement. these rules are used in a fuzzy-based controller implementation. the controller is validated on experiments with diseased patients at bellan hospital, paris, france.
structural shakiness of nonoverconstrained translational parallel mechanisms with identical limbs. one important category of parallel mechanisms is the translational parallel mechanism (tpm). this paper focuses on the structural shakiness of the nonoverconstrained tpm. such a structural shakiness is due to the unavoidable lack of rigidity of the real bodies, which leads to uncheckable orientation changes ofthe moving platform of a tpm. using algebraic properties of displacement subsets and, especially, displacement lie subgroup theory, we show that the structural shakiness of the nonoverconstrained tpm is inherently determined by the structural type of its limb chains. a structural shakiness index (ssi) for a nonoverconstrained tpm is introduced. when the set of feasible displacements of the end body of a 5-degree-of.freedom (dofs) limb chain contains two infinities of parallel axes of rotation, we have ssi = 2; when the displacement set of the end body of a 5-dof limb chain contains only one infinity of parallel axes of rotation, we have ssi = 1. it is proven that nonoverconstained tpms constructed with limb chains with ssi = 1 are much less prone to orientation changes than those constructed with limb chains with ssi = 2. based on the ssi, we enumerate limh kinematic chains and construct 21 nonoverconstrained tpms with less shakiness.
asymptotically stable walking of a five-link underactuated 3-d bipedal robot. this paper presents three feedback controllers that achieve an asymptotically stable, periodic, and fast walking gait for a 3-d bipedal robot consisting of a torso, revolute knees, and passive (unactuated) point feet. the walking surface is assumed to be rigid and flat; the contact between the robot and the walking surface is assumed to inhibit yaw rotation. the studied robot has 8 dof in the single support phase and six actuators. in addition to the reduced number of actuators, the interest of studying robots with point feet is that the feedback control solution must explicitly account for the robot's natural dynamics in order to achieve balance while walking. we use an extension of the method of virtual constraints and hybrid zero dynamics (hzd), a very successful method for planar bipeds, in order to simultaneously compute a periodic orbit and an autonomous feedback controller that realizes the orbit, for a 3-d (spatial) bipedal walking robot. this method allows the computations for the controller design and the periodic orbit to be carried out on a 2-dof subsystem of the 8-dof robot model. the stability of the walking gait under closed-loop control is evaluated witt the linearization of the restricted poincare map of the hzd. most periodic walking gaits for this robot are unstable when the controlled outputs are selected to be the actuated coordinates. three strategies are explored to produce stable walking. the first strategy consists of imposing a stability condition during the search of a periodic gait by optimization. the second strategy uses an event-based controller to modify the eigenvalues of the (linearized) poincare map. in the third approach, the effect of output selection on the zero dynamics is discussed and a pertinent choice of outputs is proposed, leading to stabilization without the use of a supplemental event-based controller.
planar bipedal jumping gaits with stable landing. in this paper, landing stability of jumping gaits is studied for a four-link planar biped model. rotation of the foot during the landing phase leads to underactuation due to the passive degree of freedom at the toe, which results in nontrivial zero dynamics (zd). compliance between the foot and ground is modeled as a spring-damper system. rotation of the foot along with the compliance model introduces switching in the zd. the stability conditions for the "switching zd" and closed-loop dynamics (cld) are established. "critical potential index" and "critical kinetic index" are introduced as measures of the stability of the cld of the biped during landing. landing stability is achieved by utilizing the stability conditions. stable jumping motion is experimentally realized on a biped robot.
a linear relaxation technique for the position analysis of multiloop linkages. this paper presents a new method to isolate all configurations that a multiloop linkage can adopt. the problem is tackled by means of formulation and resolution techniques that fit particularly well together. the adopted formulation yields a system of simple equations (only containing linear, bilinear, and quadratic monomials, and trivial trigonometric terms for the helical pair only) whose structure is later exploited by a branch-and-prune method based on linear relaxations. the method is general, as it can be applied to linkages with single or multiple loops with arbitrary topology, involving lower pairs of any kind, and complete, as all possible solutions get accurately bounded, irrespective of whether the linkage is rigid or mobile.
self-aligning exoskeleton axes through decoupling of joint rotations and translations. to automatically align exoskeleton axes to human anatomical axes, we propose to decouple the joint rotations from the joint translations. decoupling can reduce setup times and painful misalignment forces, at the cost of increased mechanical complexity and movement inertia. the decoupling approach was applied to the dampace and limpact exoskeletons.
adaptive/robust control for time-delay teleoperation. the control of time-delay bilateral teleoperation systems involves a delicate tradeoff between the conflicting requirements of transparency and robust stability. the control design is complicated by latency in data communication between the master and slave sites as well as uncertainties in the dynamics of operator, master, slave, and environment. this paper proposes a systematic design procedure for improving teleoperation fidelity while maintaining its stability in the presence of dynamic uncertainty and a constant time delay. in a two-step control approach, first local lyapunov-based adaptive/nonlinear controllers are applied to linearize the system dynamics and eliminate dependency on the master and slave parameters. teleoperation coordination, subject to parametric uncertainty in the user and environment dynamics, is then achieved by formulating an i/o time-delay h∞ robust control synthesis that is solved via its decomposition to the so-called adobe problems. the transparency and robust stability properties of the proposed method is examined via numerical analysis, furthermore, the results are successfully validated in experiments.
robotic cell injection system with position and force control: toward automatic batch biomanipulation. biological cell injection is laborious work that requires lengthy training and suffers from a low success rate. in this paper, a robotic cell-injection system for automatic injection of batch-suspended cells is proposed. to facilitate the process, these suspended cells are held and fixed to a cell array by a specially designed cell-holding device, and injected one by one through an "outof-plane" cell-injection process. a micropipette equipped with a polyvinylidene fluoride microforce sensor to measure real-time injection force is integrated in the proposed system. through calibration, an empirical relationship between the cell-injection force and the desired injector pipette trajectory is obtained in advance. then, after decoupling the out-of-plane cell injection into a position control in the x-y horizontal plane and an impedance control in the z-axis, a position and force control algorithm is developed to control the injection pipette. the depth motion of the injector pipette, which cannot be observed by microscope, is indirectly controlled via the impedance control, and the desired force is determined from the online x-y position control and cell calibration results. finally, experimental results demonstrate the effectiveness of the proposed approach.
return maps, parameterization, and cycle-wise planning of yo-yo playing. this note presents a unified approach to nominal control generation and return map parameterization for yo-yo playing. the approach is based on choosing an intermediate state of the yo-yo as the parameter and formulating an optimization problem with appropriate boundary conditions that incorporate the corresponding parameter. by solving the optimization problems, both the return map and the nominal optimal control for the robot can be obtained. the return map is naturally parameterized with the intermediate state, which can be treated as a virtual control. the return map facilitates the application of standard analysis and design methods for discrete-time control systems. the approach is promising as it might be extended to control other cyclic dynamic systems.
sensorless position control using feedforward internal force for completely restrained parallel-wire-driven systems. generally, point-to-point control for a completely restrained (cr) parallel-wire-driven system requires a balancing internal force to prevent slackening of wires, along with a feedback term based on some displacement sensor. this paper specifically describes cr systems' internal force properties, then presents the possibility of motion convergence at a desired position when the internal force balancing at a position is given as sensorless feedforward input. subsequently, we use the property of internal force positively for sensorless position control. this positioning method is applicable for low-cost manipulation, which does not require high accuracy, and for emergency positioning of systems when sensors malfunction.
a new assessment of singularities of parallel kinematic chains. this paper presents a novel assessment of singularities of general parallel kinematic chains. hierarchical levels in which different critical phenomena originate are recognized. at each level, the causes of singular events are identified and interpreted, and on their basis, a comprehensive taxonomy is proposed. first, the unactuated kinematic chain is studied.the concepts of leg and passive-constraint singularities are described, and stationary and increased instantaneous mobility configurations are identified. then, a set of motorized joints is chosen. the effects of first-level singularities on the actuated chain are investigated, and further phenomena are identified, such as redundancy singularities and active-constraint singularities. the notions of reaction and action spaces are originally discussed. the consequences on the ability of the actuated chain to effectively govern its local and global freedoms are analyzed, and the complex interactions between the various singular events are studied. the instantaneous redundancy of actuators, which occur when these work either against each other or against joint constraints, is also evaluated. finally, when the input-output mechanism is considered, the events described at the previous stages are interpreted within the perspective of the machine's desired use.
using haptic feedback to improve grasp force control in multiple sclerosis patients. we describe a simple and low-cost system that can help multiple sclerosis (ms) patients with asymmetric impairment to exert better grasp force control in manipulation tasks. the approach consists of measuring force vectors at the fingertips of the impaired hand, computing the force imbalance among the fingers, and providing corresponding haptic signals to the fingers of the opposite hand. tests conducted on 24 ms patients indicated that for those with mild impairment, slightly better results were obtained with an "event-cue" feedback (ecf) that alerted them when the grasp forces were straying outside of a desirable range. for patients with more severe impairment, better results were obtained by providing a proportional signal, in which the frequency and duty cycle of vibration pulses were correlated directly with the magnitudes of the fingertip forces. post-test surveys of the patients also indicated that mildly impaired subjects preferred an eventcue feedback, and more severely impaired subjects preferred the proportional feedback.
optimal design of a 4-dof parallel manipulator: from academia to industry. this paper presents an optimal design of a parallel manipulator aiming to perform pick-and-place operations at high speed and high acceleration. after reviewing existing architectures of high-speed and high-acceleration parallel manipulators, a new design of a 4-dof parallel manipulator is presented, with an articulated traveling plate, which is free of internal singularities and is able to achieve high performances. the kinematic and simplified, but realistic, dynamic models are derived and validated on a manipulator prototype. experimental tests show that this design is able to perform beyond the high targets, i.e., it reaches a speed of 5.5 m/s and an acceleration of 165 m/s2. the experimental prototype was further optimized on the basis of kinematic and dynamic criteria. once the motors, gear ratio, and several link lengths are determined, a modified design of the articulated traveling plate is proposed in order to reach a better dynamic equilibrium among the four legs of the manipulator. the obtained design is the basis of a commercial product offering the shortest cycle times among all robots available in today's market.
description of instantaneous restriction space for multi-dofs bilateral teleoperation systems using position sensors in unstructured environments. this paper investigates a novel position-sensor-based force reflection framework for multi-degree-of-freedom (dof) bilateral teleoperation systems in unstructured environments. the conventional position-sensor-based force reflection method, which is known as position error feedback, may generate grossly inaccurate force reflection directions during collisions involving the slave manipulator links. the proposed restriction space projection framework calculates the instantaneous restriction space to provide the accurate force reflection, regardless of kinematic dissimilarity (kds) conditions of bilateral teleoperation systems. simulation results confirmed the validity of the proposed framework in a kds bilateral teleoperation system under various constraint conditions.
flow-through policies for hybrid controller synthesis applied to fully actuated systems. this paper addresses the coupled navigation and control problem for fully actuated dynamical systems operating in cluttered environments. the proposed method composes local feedback control policies to address the global problem in a formally correct manner. our contribution extends the method of sequential composition to a new class of flow-through policies, which are defined for an idealized point robot that is subject to bounds on velocity and acceleration. these policies, which are defined over convex polytopes, express natural behaviors and guarantee safe trajectories while respecting system constraints. this paper presents a constructive technique for building hybrid control systems with guaranteed transitions and stability properties. simulation results demonstrate policy-based decision making for various initial conditions.
mechanics of precurved-tube continuum robots. this paper presents a new class of thin, dexterous continuum robot, which we call active cannulas due to their potential medical applications. an active cannula is composed of telescoping, concentric, precurved superelastic tubes that can be axially translated and rotated at the base relative to one another. active cannulas derive bending not from tendon wires or other external mechanisn 15 but from elastic tube interaction in the backbone itself, permitting high dexterity and small size, and dexterity improves with miniaturization. they are designed to traverse narrow and winding environments without relying on "guiding" environmental reaction forces. these features seem ideal for a variety of applications where a very thin robot with tentacle-like dexterity is needed. in this paper, we apply beam mechanics to obtain a kinematic model of active cannula shape and describe design tools that result from them modeling process. after deriving general equations, we apply them to a simple three-link active cannula. experimental results illustrate the importance of including torsional effects and the ability of our model to predict energy bifurcation and active cannula shape.
design and analysis of a totally decoupled flexure-based xy parallel micromanipulator. in this paper, a concept of totally decoupling is proposed for the design of a flexure parallel micromanipulator with both input and output decoupling. based on flexure hinges, the design procedure for an xy totally decoupled parallel stage (tdps) is presented, which is featured with decoupled actuation and decoupled output motion as well. by employing (double) compound parallelogram flexures and a compact displacement amplifier, a class of novel xy tdps with simple and symmetric structures are enumerated, and one example is chosen for further analysis. the kinematic and dynamicmodeling of the manipulator are conducted by resorting to compliance and stiffness analysis based on the matrix method, which are validated by finite-element analysis (fea). in view of predefined performance constraints, the dimension optimization is carried out by means of particle swarm optimization, and a prototype of the optimized stage is fabricated for performance tests. both fea and experimental studies well validate the decoupling property of the xy stage that is expected to be adopted into micro-/nanoscale manipulations.
image-based visual servo control of the translation kinematics of a quadrotor aerial vehicle. in this paper, we investigate a range of image-based visual servo control algorithms for regulation of the position ofa quadrotor aerial vehicle. the most promising control algorithms have been successfully implemented on an autonomous aerial vehicle and demonstrate excellent performance.
stabilization of a hierarchical formation of unicycle robots with velocity and curvature constraints. the paper proposes a new geometric approach to the stabilization of a hierarchical formation of unicycle robots. hierarchical formations consist of elementary leader-follower units disposed on a rooted tree: each follower sees its relative leader as a fixed point in its own reference frame. robots' linear velocity and trajectory curvature are forced to satisfy some given bounds. the major contribution of the paper is to study the effect of these bounds on the admissible trajectories of the main leader. in particular, we provide recursive formulas for the maximum velocity and curvature allowed for the main leader, so that the robots can achieve the desired formation while respecting their input constraints. an original formation control law is proposed and the asymptotic stabilization is proved. simulation experiments illustrate the theory and show the effectiveness of the proposed designs.
3-d source seeking for underactuated vehicles without position measurement. our past work introduced source seeking methods for gps-denied autonomous vehicles using only local signal measurement and operating in two dimensions. in this paper, we extend these results to three dimensions. the 3-d extensions introduce many interesting challenges, including the choice of vehicle models in 3-d, sensov placement to allow probing-based gradient estimation of an unknown signal field in 3-d, the question of what type of pattern of vehicle motion can be produced in an underactuated 3-d vehicle to allow tuning by single-loop or multiloop extremum seeking, and the shape of attractors, which become very complex in 3-d. we present two control schemes that address these questions. the first scheme focuses on vehicles with a constant forward velocity and the ability to actuate pitch and yaw velocities. the second scheme employs vehicles with constant forward and pitch velocities and actuate only the roll velocity. our results include convergence analysis and simulation results.
control of nonholonomic mobile robots based on the transverse function approach. the problem of stabilizing reference trajectories-- also referred to as the trajectory tracking problem--for nonholonomic mobile robots is revisited. theoretical difficulties and impossibilities that set inevitable limits to what is achievable with feedback control are surveyed, and properties of kinematic control models are recalled, with a focus on controllable driftless systems that are invariant on a lie group. this geometric framework takes advantage of ubiquitous symmetry properties involved in the motion of mechanical bodies.the transverse function approach, a control design method developed by the authors for the past few years, is reviewed. a salient feature of this approach, which singles it out of the abundant literature devoted to the subject, is the obtention of feedback laws that unconditionally achieve the practical stabilization of arbitrary reference trajectories, including fixed points and nonadmissible trajectories. this property is complemented with novel results showing how the more common property of asymptotic stabilization of a large class of admissible trajectories can also be granted with this type of control. application to unicycle-type and car-like vehicles is presented and illustrated via simulations. complementary issues (transient maneuvers monitoring, extensions of the approach to systems that are not invariant on a lie group, etc.) are also addressed with the concern of practicality.
source seeking for two nonholonomic models of fish locomotion. in this paper, we present a method of locomotion control for underwater vehicles that are propelled by a periodic deformation of the vehicle body, which is similar to the way a fish moves. we have developed control laws employing "extremum seeking" for two different "fish" models. the first model consists of three rigid body links and relies on a 2-degree-of-freedom (dof)movement that propels the fish without relying on vortices. the second fish model uses a joukowski airfoil that has only 1 dof in its movement and, thus, relies on vortex shedding for propulsion. we achieve model-free and position-free "source seeking," and, if position is available, navigation along a predetermined path.
performance evaluation for multi-arm manipulation of hollow suspended organs. this paper presents a unified mathematical framework for modeling and evaluating the performance of multiple robotic arms that operate on hollow suspended organs. this framework is applied 10 a novel two-armed hybrid robotic system being developed for ophthalmic vitreous surgeries. four cases are designated to capture the general movements required for any surgical procedure associated with hollow suspended organs. dexterity measures, based on multiple characteristic lengths, are presented for procedures corresponding to these mauipulation cases. simulation results of the dual-arm robotic system for ophthalmic surgery are presented for all four manipulation cases. a comparison of this robotic system with current surgical tools shows a significant improvement in intraocular dexterity.
impedance compensation of subar for back-drivable force-mode actuation. the sogang university biomedical assistive robot (subar), which is an advanced version of the exoskeleton for patients and the old by songang (expos) is a wearable robot developed to assist physically impaired people. it provides a person with assistive forces controlled by human intentions. if a standard geared dc motor is applied, however, the control efforts will be used mainly to overcome the resistive forces caused by the friction, the damping, and the inertia in actuators. in this paper, such undesired properties are rejected by applying a flexible transmission. with the proposed method, it is intended that an actuator exhibits zero impedance without friction while generating the desired torques precisely. since the actuation system of subar has a large model variation due to human-robot interaction, a control algorithm for the flexible transmission is designed based on a robust control method. in this paper, the mechanical design of subar, including the flexible transmission and its associated control algorithm, are presented. they are also verified by experiments.
compliant terrain adaptation for biped humanoids without measuring ground surface and contact forces. this paper reports the applicability of our passivity-based contact force control framework for biped humanoids. we experimentally demonstrate its adaptation to unknown rough terrain. adaptation to uneven ground is achieved by optimally distributed antigravitational forces applied to preset contact points in a feedforward manner, even without explicitly measuring the external forces or the terrain shape. adaptation to unknown inclination is also possible by combining an active balancing controller based on the center-of-mass (com) measurements with respect to the inertial frame. furthermore, we show that a simple impedance controller for supporting the feet or hands allows the robot to adapt to low-friction ground without prior knowledge of the ground friction. this presentation includes supplementary experimental videos that show a full-sized biped humanoid robot balancing on uneven ground or time-varying inclination.
design strategy of serial manipulators with certified constraint satisfaction. this paper presents the design strategy of serial manipulators with constraint satisfaction. the algorithm provides certified solutions to the range of values of the manipulator design parameters that satisfy the given constraints for all points inside a desired workspace. alternatively, it can also be used to obtain the achievable workspace of a particular manipulator topology within which a set of given constraints are satisfied. this strategy can therefore be applied to the general case of a serial manipulator design problem. robots of adjustable parameters, or even reconfigurable robot strategy to obtain a suitable topology. the intervalbased algorithm was implemented on an example serial anthropomorphic manipulator with joint displacement constraints and obtains the possible variations to the manipulator topology that allow the required workspace to be achievable under the given joint displacement constraints. results are presented and discussed.
a hybrid mav for ingress and egress of urban environments. small bird-sized aerial robots are expendable and can fly over obstacles and through small openings to assist in the acquisition and distribution of intelligence during reconnaissance, surveillance, and search-and-rescue missions in urban environments. however, limited flying space and densely populated obstacle fields require a vehicle that is capable of hovering but is also maneuverable. a secondary flight mode was incorporated into a fixed-wing aircraft to preserve its maneuverability while adding the capability of hovering. an inertial measurement sensor and onboard flight control system were interfaced and used to transition the hybrid prototype from cruise to hover flight and sustain a hover autonomously. furthermore, the hovering flight mode can be used to maneuver the aircraft through small openings such as doorways. an ultrasonic and infrared sensor suite was designed to follow exterior building walls until an ingress route was detected. reactive control was then used to traverse the doorway and gather reconnaissance. this paper describes the holistic approach of platform development, sensor suite design, and control of the hybrid prototype.
modeling and system identification of a life-size brake-actuated manipulator. safety is a critical factor when designing a robotic rehabilitation environment. whole-limb or life-size haptic interaction would allow virtual robotic rehabilitation of daily living activities such as sweeping or shelving. however, it has been too dangerous to implement such an environment with conventional active robots that use motor, hydraulic, or pneumatic actuation. to address this issue, a life-size 6-degree-of-freedom (dof) brakeactuated manipulator (bam) was designed and constructed. this paper details the bam's system models including mechanisms, kinematics, and dynamics, as well as detailed input and friction models. in addition, a new system-identification technique that utilizes human input to excite the robot's dynamics with unscented kalman filtering was employed to identify system parameters. noise sources are discussed, and the model is validated through force estimation with inverse dynamics. model parameters and performance are compared with other commercially available haptic devices. the bam shows a significantly larger workspace, maximum force, and stiffness over other devices exhibiting its promise toward rehabilitative applications.
a modularized personal robot drp i: design and implementation. in this paper, we investigate comprehensive issues of modularized robot systems and present architecture for effective development of personal robots. the proposed architecture includes the interface and interaction methodology of the hardware modules and the software among the modules. based on the architecture, we present a fully modularized personal robot dynamically reconfigurable personal robot i. its hardware modules are easily added to or removed from the original system, and also the distributed software functions of the modules are rearrangeable accordingly. we focus on how to effectively build up the robot, and discuss the dynamically reconfigurable features of it for evaluating the proposed idea and approach.
a geometric algorithm to compute time-optimal trajectories for a bidirectional steered robot. this paper addresses the problem of determining time-optimal trajectories, between two specified configurations, for a nonholonomic bidirectional steered robot. it presents an original geometric reasoning that is grounded on pontryagin's maximum principle, which provides analytical solutions of this problem in a visually clear way and allows for an effective algorithm to compute the exact optimal trajectories between two arbitrarily specified configurations. the proposed geometric reasoning is based on the analysis of the switching functions of the optimal controller and the definition of a switching vector from which it is able to determine a unit vector rotating along a unit circle of an appropriate coordinate system. it is shown that simple geometric rules are sufficient to determine all possible rotations of this unit vector, from which the time-optimal trajectories can be uniquely determined. the proposed algorithm, which is based on this geometric reasoning, is guaranteed to be complete and has a low computational cost. moreover, the proposed geometric representation provides an interesting insight into the structure of this class of nonholonomic systems, thereby offering a model for further studies.
a multisensor decision fusion system for terrain safety assessment. this paper describes an onboard automated hybrid reasoning system for terrain safety assessment using multiple heterogeneous sensors onboard a spacecraft. an innovative feature of this system is integration of multiple sensing modalities and different reasoning engines into a unified approach. three different frameworks for representation of data uncertainty are considered: fuzzy set theory, bayesian probability theory, and dempster-shafer belief theory. the hybrid reasoning system is composed of three subsystems, namely, multisensor fusion, multidecision fusion, and tier-based fusion selection, where each tier represents a range of spacecraft altitudes. simulation results are presented to illustrate the multisensor decision fusion methodology described in this paper. the developed capabilities will enable future spacecraft to land safely in more challenging planetary regions with scientifically qileresting terrain features.
a reconfigurable robot with lockable cylindrical joints. this paper presents a new conceptual design for reconfigurable robots. unlike conventional reconfigurable robots, our design does not achieve reconfigurability by utilizing modular joints. rather, the robot is equipped with passive joints, i.e., joints without actuator or sensor, which permit changing the denavit-hartenberg (dh) parameters such as the link length and twist angle. the passive joints will become controllable when the robot forms a closed kinematic chain. also, each passive joint is equipped with a built-in brake mechanism that is normally locked, but the lock can be released whenever the parameters are to be changed. such a versatile and agile robot is particularly suitable for space application for its simple, compact, and light design. the kinematics and recalibration of this kind of reconfigurable robot are thoroughly analyzed. a stable reconfiguration-control algorithm is devised to take the robot from one configuration to another by directly regulating the passive joints to the associated, desired dh parameters. conditions for the observability and the controllability of the passive joints are also derived in detail.
image guidance of flexible tip-steerable needles. image guidance promises to improve targeting accuracy and broaden the scope of medical procedures performed with needles. this paper takes a step toward automating the guidance of a flexible tip-steerable needle as it is inserted into the human tissue. we build upon a previously proposed nonholonomic model of needles that derive steering from asymmetric bevel forces at the tip. the bevel-tip needle is inserted and rotated at its base in order to steer it in 6 dof. as a first step for control, we show that the needle tip can be automatically guided to a planar slice of the tissue as it is inserted. our approach keeps the physician in the loop to control insertion speed. the distance of the needle tip position from the plane of interest is used to drive an observer-based feedback controller that we prove is locally asymptotically stable. numerical simulations demonstrate a large domain of attraction and robustness of the controller in the face of parametric uncertainty and measurement noise. physical experiments with tip-steerable nitinol needles inserted into a transparent plastisol tissue phantom under stereo image guidance validate the effectiveness of our approach.
a new mechanism for mesoscale legged locomotion in compliant tubular environments. we present design and experimental performance results for a novel mechanism for robotic legged locomotion at the mesoscale (from hundreds of microns to tens of centimeters). the new mechanism is compact and strikes a balance between conflicting design objectives, exhibiting high foot forces and low power consumption. it enables a small robot to traverse a compliant, slippery, tubular environment, even while climbing against gravity. this mechanism is useful for many mesoscale locomotion tasks, including endoscopic capsule robot locomotion in the gastrointestinal tract. it has enabled fabrication of the first legged endoscopic capsule robot whose mechanical components match the dimensions of commercial pill cameras (11 mm diameter by 25 mm long). a novel slot-follower mechanism driven via lead screw enables the mechanical components of the capsule robot to be as small while simultaneously generating 0.63 n average propulsive force at each leg tip. in this paper, we describe kinematic and static analyses of the lead screw and slot-follower mechanisms, optimization of design parameters, and experimental design and tuning of a gait suitable for locomotion. a series of ex vivo experiments demonstrate capsule performance and ability to traverse the intestine in a manner suitable for inspection of the colon in a time period equivalent to standard colonoscopy.
robot-aided neurorehabilitation: a novel robot for ankle rehabilitation. in this paper, we present the design and characterization of a novel ankle robot developed at the massachusetts institute of technology (mit). this robotic module is being tested with stroke patients at baltimore veterans administration medical center. the purpose of the on-going study is to train stroke survivors to overcome common foot drop and balance problems in order to improve their ambulatory performance. its design follows the same guidelines of our upper extremity designs, i.e., it is a low friction, backdriveable device with intrinsically low mechanical impedance. here, we report on the design and mechanical characteristics of the robot. we also present data to demonstrate the potential of this device as an efficient clinical measurement tool to estimate intrinsic ankle properties. given the importance of the ankle during locomotion, an accurate estimate of ankle stiffness would be a valuable asset for locomotor rehabilitation. our initial ankle stiffness estimates compare favorably with previously published work, indicating that our method may serve as an accurate clinical measurement tool.
cooperative robot control and concurrent synchronization of lagrangian systems. concurrent synchronization is a regime where diverse groups of fully synchronized dynamic systems stably coexist. we study global exponential synchronization and concurrent synchronization in the context of lagrangian systems control. in a network constructed by adding diffusive couplings to robot manipulators or mobile robots, a decentralized tracking control law globally exponentially synchronizes an arbitrary number of robots, and represents a generalization of the average consensus problem. exact nonlinear stability guarantees and synchronization conditions are derived by contraction analysis. the proposed decentralized strategy is further extended to adaptive synchronization and partialstate coupling.
biologically inspired mobile robot vision localization. we present a robot localization system using biologically inspired vision. our system models two extensively studied human visual capabilities: 1) extracting the "gist" of a scene to produce a coarse localization hypothesis and 2) refining it by locating salient landmark points in the scene. gist is computed here as a holistic statistical signature of the image, thereby yielding abstract scene classification and layout. saliency is computed as a measure of interest at every image location, which efficiently directs the time-consuming landmark-identification process toward the most likely candidate locations in the image. the gist features and salient regions are then further processed using amonte carlo localization algorithm to allow the robot to generate its position. we test the system in three different outdoor environments--building complex (38.4m × 54.86 m area, 13 966 testing images), vegetation-filled park (82.3m × 109.73m area, 26 397 testing images), and openfield park (137.16m × 178.31m area, 34 711 testing images)--each with its own challenges. the system is able to localize, on average, within 0.98, 2.63, and 3.46 m, respectively, even with multiple kidnapped-robot instances.
robust impedance control of a flexible structure mounted manipulator performing contact tasks. this paper presents a robustness analysis and design approach for impedance control of a flexible structure mounted manipulator (fsmm) performing contact tasks. in the analysis, the dynamics of the flexible structure are treated as uncertain. the environment is also treated as uncertain, but with force-displacement characteristics satisfying a sectorbound condition. first, a one dimensional model for an end-effector under impedance control is considered. the effect of base flexibility on stability under contact conditions is then assessed via the popov criterion. based on these results, an approach to robust impedance control is proposed. it is shown that by augmenting low-order filters within a standard impedance control law, robust global stability in the presence of base flexibility can be achieved. the controller is shown to perform successfully in experiments on a two-link lab-scale fsmm.
dynamic performance of a scara robot manipulator with uncertainty using polynomial chaos theory. this short paper outlines how polynomial chaos theory (pct) can be utilized for manipulator dynamic analysis and controller design in a 4-dof selective compliance assembly robot-arm-type manipulator with variation in both the link masses and payload. it includes a simple linear control algorithm into the formulation to show the capability of the pct framework.
swedish wheeled omnidirectional mobile robots: kinematics analysis and control. swedish wheeled robots have received growing attention over the last few years. their kinematic models have interesting properties in terms of mobility and possible singularities. this paper addresses the issue of kinematic modeling, singularity analysis, and motion control for a generic vehicle equipped with n swedish wheels.
a unified approach to integrate unilateral constraints in the stack of tasks. the control approaches based on the task function formalism, and particularly those structured as a prioritized hierarchy of tasks, enable complex behaviors with elegant properties of robustness and portability to be built. however, it is difficult to consider a straight forward integration of tasks described by unilateral constraints in such frameworks. indeed, unilateral constraints exhibit irregularities that prevent the insertion of unilateral tasks at any priority level, other than the lowest, of a hierarchy. in this paper, we present an original method to generalize the hierarchy-based control schemes to account for unilateral constraints at any priority level.we develop our method first for task sequencing using only the kinematics description; then, we expand it to the task description, using the operational space formulation. the method applies in robotics and computer graphics animation. its practical implementation is exemplified by realizing a real-manipulator visual servoing task and a humanoid avatar reaching task; both experiments are achieved under the unilateral constraints of joint limits.
design and implementation of nims3d, a 3-d cabled robot for actuated sensing applications. we present nims3d, a novel 3-d cabled robot for actuated sensing applications. we provide a brief overview of the main hardware components. next, we describe installation procedures, including novel calibration methods, that enable rapid in-field deployability for nonexpert end users, and provide simulations and experimental results to highlight their effectiveness. kinematic and dynamic analysis of the system are provided, followed by a description of control methods.we provide experimental results that illustrate tracking of linear and nonlinear paths by nims3d. thereafter, we briefly present an example of an actuated sensing task performed by the system. finally, we describe methods of improving energy efficiency by leveraging nonlinear trajectories and energy-optimal tension distributions. experimental and simulated results show that energy efficiency can be improved significantly by using optimized parabolic trajectories. furthermore, we provide simulation results that demonstrate improved efficiency enabled by optimal, least norm tension distributions.
powered ankle--foot prosthesis improves walking metabolic economy. at moderate to fast walking speeds, the human ankle provides net positive work at high-mechanical-power output to propel the body upward and forward during the stance period. on the contrary, conventional ankle-foot prostheses exhibit a passive-elastic response during stance, and consequently, cannot provide net work. clinical studies indicate that transtibial amputees using conventional prostheses have higher gait metabolic rates than normal. researcher s believe that the main cause for these higher rates is due to the inability of conventional prostheses to provide sufficient positive power at terminal stance in the trailing leg to limit heel strike losses of the adjacent leading leg. in this investigation, we evaluate the hypothesis that a powered ankle-foot prosthesis, capable of providing human-like ankle work and power during stance, can decrease the metabolic cost of transport (cot) compared to a conventional passive-elastic prosthesis. to test the hypothesis, a powered prosthesis is built that comprises a unidirectional spring, configured in parallel with a force-controllable actuator with series elasticity. the prosthesis is shown to deliver the high mechanical power and net positive work observed in normal human walking. the rate of oxygen consumption and carbon dioxide production is measured as a determinant of metabolic rate on three unilateral transtibial amputees walking at self-selected speeds. we find that the powered prosthesis decreases the amputee's metabolic cot on average by 14% compared to the conventional passive-elastic prostheses evaluated (flex-foot ceterus® and freedom innovations sierra), even thuugh the powered system is over twofold heavier than the conventional devices. these results highlight the clinical importance of prosthetic interventions that closely mimic the mass distribution, kinetics, and kinematics of the missing limb.
a passive 2-dof walker: hunting for gaits using virtual holonomic constraints. a planar compass-like biped on a shallow slope is one of the simplest models of a passive walker. it is a 2-degree-of-freedom (dof) impulsive mechanical system that is known to possess periodic solutions reminiscent of human walking. finding such solutions is a challenging computational task that has attractedmany researchers who are motivated by various aspects of passive and active dynamic walking. we propose a new approach to find stable as well as unstable hybrid limit cycles without integrating the full set of differential equations and, at the same time, without approximating the dynamics. the procedure exploits a time-independent representation of a possible periodic solution via a virtual holonomic constraint. the description of the limit cycle obtained in this way is useful for the analysis and characterization of passive gaits as well as for design of regulators to achieve gaits with the smallest required control efforts. some insights into the notion of hybrid zero dynamics, which are related to such a description, are presented as well.
geometrical optimization of parallel mechanisms based on natural frequency evaluation: application to a spherical mechanism for future space applications. this paper presents an optimization procedure conceived to design parallel mechanisms (pms) with legs of constant and/or variable length connected, at their endpoints, to a fixed base and a movable platform through universal and spherical joints, respectively. in the proposed procedure, the first natural frequency of the mechanism is the objective function to be maximized. the optimization problem is formulated by using dimensionless variables in order to identify the optimal geometry independently of mechanism size, platform density, and leg cross-sectional area and material. as a case study, the procedure is employed to find the optimal geometry of a 2-dof spherical pm to be used as an orienting device in future space missions.
a foldable 3-dof parallel mechanism with application to a flat-panel tv mounting device. this paper deals with a new 3-degree-of-freedom (dof) parallel mechanism for a flat-panel tv mounting device with two rotations and one translation. the most important operational requirements of this device are that it should support the heavy weight of the flat-panel tv and should be foldable to save space between the flat panel and the wall. an asymmetric parallel structure that has three kinematic chains with internal four-bar linkage is proposed to meet such requirements. kinematic modeling was performed along with actuator sizing. finally, the mechanism was developed and tested to show its effectiveness as a flat-panel tv mounting device.
online segmentation and clustering from continuous observation of whole body motions. this paper describes a novel approach for incremental learning of human motion pattern primitives through online observation of human motion. the observed time series data stream is first stochastically segmented into potential motion primitive segments, based on the assumption that data belonging to the same motion primitive will have the same underlying distribution. the motion segments are then abstracted into a stochastic model representation and automatically clustered and organized. as new motion patterns are observed, they are incrementally grouped together into a tree structure, based on their relative distance in the model space. the tree leaves, which represent the most specialized learned motion primitives, are then passed back to the segmentation algorithm so that as the number of known motion primitives increases, the accuracy of the segmentation can also be improved. the combined algorithm is tested on a sequence of continuous human motion data that are obtained through motion capture, and demonstrates the performance of the proposed approach.
case studies of musculoskeletal-simulation-based rehabilitation program evaluation. variability in motor rehabilitation program outcomes can be attributed not only to individual components (human patient/rehabilitation equipment) but also to their system-level interactions. thus, effective deployment of a rehabilitation program depends upon: 1) suitable therapist selection of user-device ergonomics; 2) adjustable device settings; and 3) exercise regimen parameters; to achieve desired system-levelmotor performance. in this paper, we discuss aspects of creation of a virtual design environment, leveraging tools from musculoskeletal analysis, optimization, and simulation-based design, to permit therapists to rapidly evaluate and systematically customize rehabilitation programs. specifically, this framework is intended to facilitate 1) parametric study of ergonomic/device/regimen settings on musculoskeletal performance; 2) use of design tools such as optimization for decision support in arriving at the best program; and 3) scaffolded examination of linkage between form and function by iterative what-if type of analyses. we use two case studies (bicep-curling and motor rehabilitative driving) to highlight benefits of such simulation-based rehabilitation program evaluation.
parallel mechanisms with bifurcation of schoenflies motion. type synthesis of lower mobility parallel mechanisms (pms) has attracted extensive attention in research community of robotics over the last seven years. one important trend in this area is to synthesize pms with prespecified motion properties. this paper focuses on the type synthesis of a special family of pms whose moving platform can undergo a bifurcation of schoenflies motion. first, bifurcation of schoenfties motion in pms is interpreted in terms of displacement group theory and the basic limb bond {x(y)} {r(n, x)} is identified. further, the geometric condition for constructing a pm with bifurcation of schoenflies motion is presented. the kinematic equivalence between {x(y)} {r(n,x)} and {x(y)} {x(x)} is proven. four subcategories of irreducible representation of the product {x(y)} {x(x)} are proposed and the limb chains that produce the desired limb bond are synthesized. finally, the partitioned mobility of pms with bifurcation of schoenflies motion and its effect on actuation selection are discussed.
swing-up control of the pendubot: an impulse-momentum approach. the standard control problem of the pendubot refers to the task of stabilizing its equilibrium configuration with the highest potential energy. linearization of the dynamics of the pendubot about this equilibrium results in a completely controllable system and allows a linear controller to be designed for local asymptotic stability. for the underactuated pendubot, the important task is, therefore, to design a controller that will swing up both links and bring the configuration variables of the system within the region of attraction of the desired equilibrium. this paper provides a new method for swing-up control based on a series of rest-to-rest maneuvers of the first link about its vertically upright configuration. the rest-to-rest maneuvers are designed such that each maneuver results in a net gain in energy of the second link. this results in swing-up of the second link and the pendubot configuration reaching the region of attraction of the desired equilibrium. a four-step algorithm is provided for swing-up control followed by stabilization. simulation results are presented to demonstrate the efficacy of the approach.
needle insertion parameter optimization for brachytherapy. this paper presents a new needle path planning method for the insertion of rigid needles into deformable tissue. the needle insertion point, needle heading, and needle depth are optimized by minimizing the distance between a rigid needle and a number of targets in the tissue. the optimization method is based on iterative simulations performed using a tissue finite element model. at each iteration, the best 3-d line fitted to the displaced targets in the deformed tissue is used as a candidate for a new insertion line. first, this method is implemented in a prostate brachytherapy simulator under different boundary conditions tominimize the targeting error. it is shown that the optimization method converges in a few iterations and decreases the seed misplacement error to less than the needle diameter. second, the efficacy of the optimization algorithm is verified by optimizing the insertion parameters for a brachytherapy needle before insertion into a prostate tissue phantom. the elastic properties of the phantom and the needle-tissue interaction parameters were identified in an independent experiment. the optimization algorithm is effective in decreasing the targeting error.
boundary condition relaxation method for stepwise pedipulation planning of biped robots. a completely stepwise online pedipulation planning method is proposed. it is an analytical approach based on the general solution of the equation of motion of an approximate dynamical biped model whose mass is concentrated at the center of mass. a physically feasible referential trajectory with a constraint about the reaction force taken into account is planned only in one interval by relaxing the boundary condition, namely, by admitting a certain level of error between the desired and actually reached states, and discontinuity of zero-moment point at each end of the interval. it potentially creates responsivemotions that require strong instantaneous acceleration. a semiautomatic continual pedipulation planning method is also presented. it generates a referential trajectory of the whole body only from the next desired foot placement. the validity of the proposed method is ensured through experiments with a small anthropomorphic robot.
a nonlinear set membership approach for the localization and map building of underwater robots. this paper proposes a set membership method based on interval analysis to solve the simultaneous localization and map building (slam) problem. the principle of the approach is to cast the slam problem into a constraint satisfaction problem for which interval propagation algorithms are particularly powerful. the resulting propagation method is illustrated on the localization and map building of an actual underwater robot.
reactive path planning in a dynamic environment. this paper deals with the problem of path planning in a dynamic environment, where the workspace is cluttered with unpredictably moving objects. the concept of the virtual plane is introduced and used to create reactive kinematic-based navigation laws. a virtual plane is an invertible transformation equivalent to the workspace, which is constructed by using a local observer. this results in important simplifications of the collision detection process. based on the virtual plane, it is possible to determine the intervals of the linear velocity and the paths that lead to collisions with moving obstacles and then derive a dynamic window for the velocity and the orientation to navigate the robot safely. the speed of the robot and the orientation angle are controlled independently using simple collision cones and collision windows constructed from the virtual plane. the robot's path is controlled using kinematic-based navigation laws that depend on navigation parameters. these parameters are tuned in real time to adjust the path of the robot. simulation is used to illustrate collision detection and path planning.
estimation of terrain forces and parameters for rigid-wheeled vehicles. this paper provides a methodology for the estimation of resistance, thrust, and resistive torques on each wheel of a rigid-wheeled vehicle generated at the vehicle-terrain interface, and from these forces and moments, a methodology to estimate terrain parameters is presented. terrain force estimation, which is independent of a terrain model, can infer the ability to accelerate, climb, or tow a load independent of the underlying terrain properties. when a terrain model is available, parameters of that model, such as soil cohesion, friction angle, maximum normal stress, and stress distribution parameters, are determined from estimated vehicle-terrain forces using a multiple-model estimation approach, providing parameters that relate to accepted mobility metrics. the methodology requires a standard proprioceptive sensor suite--accelerometers, rate gyros,wheel speeds, motor torques, and ground speed. sinkage sensors are not required. simulation results demonstrate efficacy of the method on three terrains spanning a range of soil cohesions reported in the literature.
visual servo control achieving nanometer resolution in x - y - z. this paperpresents a three-axis vision motion sensor and its applications to visual servo control. the vision sensor is integrated with a three-axis piezo stage to form a visual servo control system that achieves nanometer resolution in all three x- y-z motion axes. motion measurement is achieved using a single interferometer-equipped optical microscope. a real-time imageprocessing algorithm that processes interference fringe patterns and that achieves nanometer out-of-plane resolution is presented. furthermore, a feedback-control scheme is introduced to control the sensor plane using an objective-z-positioner to enable automatic tracking of moving objects. it expands the out-of-plane measurement range of the vision sensor beyond its inherent depth of field of several micrometers to 100 µm and beyond. an integrated visual servo system is implemented and experimental results are shown.
a highly backdrivable, lightweight knee actuator for investigating gait in stroke. many of those who survive a stroke develop a gait disability known as stiff-knee gait (skg). characterized by reduced knee flexion angle during swing, people with skg walk with poor energy efficiency and asymmetry due to the compensatory mechanisms required to clear the foot. previous modeling studies have shown that knee flexion activity directly before the foot leaves the ground, and this should result in improved knee flexion angle during swing the goal of this research is to physically test this hypothesis using robotic intervention. we developed a device that is capable of assisting knee flexion torque before swing but feels imperceptible (transparent) for the rest of the gait cycle. this device uses sheathed bowden cable to control the deflection of a compliant torsional spring in a configuration known as a series elastic remote knee aquator (serka). in this investigation, we describe the design and evaluation of serka, which includes a pilot experiment on stroke subjects. serka could supply a substantial torque (12 n-m) in less than 20 ms, with a maximum torque of 41 n-m. the device resisted knee flexion imperceptibly when desired, at less than 1 n-m rms torque during normal gait. with the remote location of the actuator, the user experiences a mass of only 1-2 kg on the knee. we found that the device was capable of increasing both peak knee flexion angle and velocity during gait in stroke subjects. thus, the serka is a valid experimental device that selectively alters knee kinetics and kinematics in gait after stroke.
motion synchronization control of distributed multisubsystems with invariant local natural dynamics. this paper addresses a new control strategy for synchronizing two or more distributed and interconnected dynamic systems having communication time delays. the proposed strategy that uses the smith predictor principle and delay information not only achieves synchronization but also preserves the natural local dynamics of each subsystem without being affected by the feedback nature of control. the proposed synchronization scheme is generalized to cases that deal with an arbitrary number of heterogeneous interconnected systems through dynamic scaling of input under a ring-type network configuration. in addition, possibility of applying the proposed scheme to nonlinear systems is discussed. simulation and experimental tests are conducted to validate theoretical results.
emg-based control of a robot arm using low-dimensional embeddings. as robots come closer to humans, an efficient human-robot-control interface is an utmost necessity. in this paper, electromyographic (emg) signals from muscles of the human upper limb are used as the control interface between the user and a robot arm. a mathematical model is trained to decode upper limb motion from emg recordings, using a dimensionality-reduction technique that represents muscle synergies and motion primitives. it is shown that a 2-d embedding of muscle activations can be decoded to a continuous profile of arm motion representation in the 3-d cartesian space, embedded in a 2-d space. the system is used for the continuous control of a robot arm, using only emg signals from the upper limb. the accuracy of the method is assessed through real-time experiments, including random arm motions.
autonomous robotic pick-and-place of microobjects. this paper presents a robotic system that is capable of both picking up and releasing microobjects with high accuracy, reliability, and speed. due to force-scaling laws, large adhesion forces at the microscale make rapid, accurate release of microobjects a long-standing challenge in micromanipulation, thus representing a hurdle toward automated robotic pick-and-place of micrometer-sized objects. the system employs a novel microelectromechanical systems (mems) microgripper with a controllable plunging structure to impact amicroobject that gains sufficient momentum to overcome adhesion forces. the performance was experimentally quantified through the manipulation of 7.5-10.9 µm borosilicate glass spheres in an ambient environment. experimental results demonstrate that the system, for the first time, achieves a 100% success rate in release (which is based on 700 trials) and a release accuracy of 0.45±0.24 µm. high-speed, automated microrobotic pick-and-place was realized by visually recognizing the microgripper and microspheres, by visually detecting the contact of the microgripper with the substrate, and by vision-based control. example patterns were constructed through automated microrobotic pick-and-place of microspheres, achieving a speed of 6 s/sphere, which is an order of magnitude faster than the highest speed that has been reported in the literature.
a darboux-frame-based formulation of spin-rolling motion of rigid objects with point contact. this paper investigates the kinematics of spin-rolling motion of rigid objects. this paper does not consider slipping but applies a darboux frame to develop kinematics of spin-rolling motion, which occurs in a nonholonomic system. a new formulation of spin-rolling motion of the moving object is derived in terms of contravariant vectors, rolling velocity, and geometric invariants, including normal curvature, geodesic curvature, and geodesic torsion of the respective contact curve. the equation is represented with geometric invariants. it can be readily generalized to suit both arbitrary parametric surface and contact trajectory and can be differentiated to any order. effect of the relative curvatures and torsion on spin-rolling kinematics is explicitly presented. the translation velocity of an arbitrary point on the moving object is also derived based on the darboux frame.
kinematic-sensitivity indices for dimensionally nonhomogeneous jacobian matrices. numerous performance indices have been proposed to compare robot architectures based on their kinematic properties. however, none of these indices seems to draw a consensus among the robotics community. the most notorious indices, which aremanipulability and dexterity, still entail some drawbacks, which are mainly due to the impossibility to define a single invariant metric for the special euclidean group. the natural consequence is to use two distinct metrics, i.e., one for rotations and one for point displacements, as has already been proposed by other researchers. this is the approach used in this paper, where we define the maximum rotation sensitivity and the maximum point-displacement sensitivity. these two indices provide tight upper bounds to the end-effector rotation and point-displacement sensitivity under a unit-magnitude array of actuated-joint displacements. therefore, their meaning is thought to be clear and definite to the designer of a robotic manipulator. furthermore, methods for the computation of the proposed indices are devised, some of their properties are established and interpreted in the context of robotic manipulator design, and an example is provided.
consequences of geometric imperfections for the control of redundantly actuated parallel manipulators. actuation redundancy increases and homogenizes the kinematic dexterity and stiffness as well as the force distribution among the actuators of parallel-kinematics machines (pkms). it also allows for internal prestresses within the pkm without affecting the environment that can potentially be used to account for secondary tasks, such as active stiffness and backlash-avoiding control. however, in the presence of geometric uncertainties, this feature can become a serious problem, since then, control forces may be annihilated, or even some of the intentional prestress components may interfere with the environment. while model uncertainties can generally be tackled with robust-control concepts, actuation redundancy of pkm impedes the use of established robust-control schemes. the effect of such uncertainties and the applicability of standard model-based control schemes are analyzed in this paper. it is shown that geometric uncertainties lead to parasitic perturbation forces that cannot be compensated by adjustment of the controls. an amended version of the augmented pd and computed torque-control scheme is proposed that does not suffer from such effects.
automatic deployment of distributed teams of robots from temporal logic motion specifications. we present a computational framework for automatic synthesis of decentralized communication and control strategies for a robotic team from global specifications, which are given as temporal and logic statements about visiting regions of interest in a partitioned environment. we consider a purely discrete scenario, where the robots move among the vertices of a graph. however, by employing recent results on invarianec and facet reachability for dynamical systems in environments with polyhedral partitions, the framework from this paper can be directly implemented for robots with continuous dyrtamics. while allowing tor a rich specification language and guaranteeing the correctness of the solution, our approach is conservative in the sense that we might not find a solution, even if one exists. the overall amount of required computation is large. however, most of it is performed offline before the deployment. illustrative simulations and experimental results are included.
interrobot transformations in 3-d. in this paper, we provide a study of motion-induced 3-d extrinsic calibration based on robot-to-robot sensor measurements. in particular, we introduce algebraic methods to compute the relative translation and rotation between two robots using known robot motion and robot-to-robot 1) distance and bearing, 2) bearing-only, and 3) distance-only measurements. we further conduct a nonlinear observability analysis and provide sufficient conditions for the 3-d relative position and orientation (pose) to become locally weakly observable. finally, we present a nonlinear weighted least-squares estimator to refine the algebraic pose estimate in the presence of noise. we use simulations to evaluate the performance of our methods in terms of accuracy and robustness.
pursuit-evasion on trees by robot teams. we present graph-clear: a novel pursuit-evasion problem on graphs which models the detection of intruders in complex indoor environments by robot teams. the environment is represented by a graph, and a robot team can execute sweep and block actions on vertices and edges, respectively. a sweep action detects intruders in a vertex and represents the capability of the robot team to detect intruders in the region associated to the vertex. similarly, a block action prevents intruders from crossing an edge and represents the capability to detect intruders as they move between regions. both actions may require multiple robots to be executed. a strategy is a sequence of block and sweep actions to detect all intruders. when instances of graph-clear are being solved, the goal is to determine optimal strategies, i.e., strategies that use the least number of robots. we prove that for the general case of graphs, the problem of computation of optimal strategies is np-hard. next, for the special case of trees, we provide a polynomial-time algorithm. the algorithm ensures that throughout the execution of the strategy, all cleared vertices form a connected subtree, and we show that it produces optimal strategies.
shortest paths for a robot with nonholonomic and field-of-view constraints. this paper presents a complete characterization of shortest paths to a goal position for a robot with unicycle kinematics and an on-board camera with limited field-of-view (fov), which must keep a given feature in sight. previous work on this subject has shown that the search for a shortest path can be limited to simple families of trajectories. in this paper, we provide a complete optimal synthesis for the problem, i.e., a language of optimal control words, and a global partition of the motion plane induced by shortest paths, such that aword in the optimal language is univocally associated with a region and completely describes the shortest path from any starting point in that region to the goal point. an efficient algorithm to determine the region in which the robot is at any time is also provided.
the actuator with mechanically adjustable series compliance. running is a complex dynamic task that places strict requirements on both the physical components and software-control systems of a robot. this paper explores some of those requirements and, in particular, explores how a variable-compliance actuation system can satisfy many of them. we present the mechanical design and software-control system for such an actuator system. we analyze its performance through simulation and bench-top experimental validation of a prototype version. in conclusion, we demonstrate, through simulation, the application of our proof-of-concept aduator to the problem of biped running.
flat dry elastomer adhesives as attachment materials for climbing robots. in this paper, flat elastomers are proposed as an attachment material for climbing robots on less than a few micrometer-scale rough surfaces due to their energy-efficient, quiet, and residue-free characteristics. the proper elastomer is chosen by the use of the current adhesion, friction, and peeling elastomer-contact-mechanics models. then, adhesion and friction properties of the chosen dry flat-elastomer thick films (vytaflex-10) are characterized on acrylic and smooth and rough glass surfaces for variations in preloads, speeds, contact times, and elastomer thicknesses. a climbing robot with four-bar-based legged-body kinematics is designed and fabricated as simple and lightweight as possible to demonstrate the feasibility of the elastomers as attachment materials on relatively smooth surfaces. the robot utilizes a passive alignment system to make the footpads parallel to the surface on light contact, a peeling mechanism to minimize the detachment vibration, and a passive tail to minimize the pitch-back moment. experimental results showed that the robot can climb stably on vertical, smooth surfaces in any direction and can walk inverted for a limited amount of time.
sliding-mode velocity control of mobile-wheeled inverted-pendulum systems. there has been increasing interest in a type of underactuated mechanical systems, mobile-wheeled inverted-pendulum (mwip) models, which are widely used in the field of autonomous robotics and intelligent vehicles. robust-velocity-tracking problem of the mwip systems is investigated in this study. in the velocity-control problem, model uncertainties accompany uncertain equilibriums, which make the controller design become more difficult. two sliding-mode-control (smc) methods are proposed for the systems, both of which are capable of handling both parameter uncertainties and external disturbances. the asymptotical stabilities of the corresponding closed-loop systems are achieved through the selection of sliding-surface parameters, which are based on some rules. there is still a steady tracking error when the first smc controller is used. by assuming a novel sliding surface, the second smc controller is designed to solve this problem. the effectiveness of the proposed methods is finally confirmed by the numerical simulations.
design and control of concentric-tube robots. a novel approach toward construction of robots is based on a concentric combination of precurved elastic tubes. by rotation and extension of the tubes with respect to each other, their curvatures interact elastically to position and orient the robot's tip, as well as to control the robot's shape along its length. in this approach, the flexible tubes comprise both the links and the joints of the robot. since the actuators attach to the tubes at their proximal ends, the robot itself forms a slender curve that is well suited for minimally invasive medical procedures. this paper demonstrates the potential of this technology. design principles are presented and a general kinematic model incorporating tube bending and torsion is derived. experimental demonstration of real-time position control using this model is also described.
cooperative load transport: a formation-control perspective. we consider a group of agents collaboratively transporting a flexible payload. the contact forces between the agents and the payload are modeled as gradients of nonlinear potentials that describe the deformations of the payload. the load-transport problem is then treated in a similar fashion to the formation-control problem. decentralized control laws are developed such that without explicit communication, the agents and the payload converge to the same constant velocity; meanwhile, the contact forces are regulated. experimental results illustrate the effectiveness of our designs.
deterministic robot-network localization is hard. this paper provides a complexity study of the deterministic localization problem in robot networks using local and relative observations only. this is an important issue in collective and cooperative robotics where global positioning systems (gps) are not available, and the basic premise is the localization ability of the group. we prove that given a set of relative observations made by the robots, the unique unambiguous pose estimation of the robot network in a deterministic way is an np-hard problem. thismeans that no polynomial-time algorithm can deterministically solve the unique pose estimation problem based on relative observations unless p = np. the consequence is that no guarantee can be provided, in a polynomial time, that the possibly estimated poses of the robots will correspond to the effective (actual) ones. the proof is based on complexity theory where we build appropriate polynomial-time reductions interrelating the multirobot localization problem to a well-known np-complete problem (the partition problem). this np-hardness result opens questions and perspectives for research into approximations to overcome its intractability.
online trajectory generation: basic concepts for instantaneous reactions to unforeseen events. this paper introduces a new method for motion-trajectory generation of mechanical systems with multiple degrees of freedom (dofs). the key feature of this new concept is that motion trajectories are generated online, i.e., within every control cycle, typically every millisecond. this enables systems to react instantaneously to unforeseen and unpredictable (sensor) events at any time instant and in any state of motion. as a consequence, (multi)sensor integration in robotics, in particular the development of control systems enabling sensor-guided and sensor-guardedmotions, becomes greatly simplified. we introduce a class of online trajectory-generation algorithms and present themathematical basics of this new approach. the algorithms presented here consist of three steps: calculation of the minimum synchronization time for all dofs, synchronization of all dofs, and calculation of output values. the theory is followed by real-world experimental results indicating new possibilities in robot-motion control.
robot positioning using camera-space manipulation with a linear camera model. this paper presents a new version of the camera-space-manipulation method (csm). the set of nonlinear view parameters of the classic csm is replaced with a linear model. simulations and experiments show a similar precision error for the two methods. however the new approach is simpler to implement and is faster.
invariant trajectory tracking with a full-size autonomous road vehicle. safe hundling of dynamic inner-city scenarios with autonomous road vehicles involves the problem of stabilization of precalculated state trajectories. in order to account for the practical requirements of the holistic autonomous system, we propose two complementary nonlinear lyapunov-based traddng-controllaws to solve the problem for speeds between ±6 m/s. their designs are based on an extended kinematic one-track model, and they provide a smooth, singularity-free stopping transient. with regard to autonomous test applications, the proposed tracking law without orientation control performs much better with respect to control effort and steering-input saturation than the one with orientation control but needs to be prudently combined with the latter for backward driving. the controller performance is illustrated with a full-size test vehicle.
an integrated system for user-adaptive robotic grasping. this paper presents an integrated system that combines learning, a natural-language interface, and robotic grasping to enable the transfer of grasping skills from nontechnical users to robots. the system consists of two parts: a natural-language interface for grasping commands and a learning system. this paper focuses on the learning system and testing of the entire system in a small usability study. the learning system presented consists of two phases. in the first phase, the system learns to predict the next command, which the user is planning to issue based on command sequences recorded during previous grasping sessions. in the second phase, the system predicts the user's current state and moves the robot's gripper to the intended target endpoint to attempt to grasp the object. using eight nontechnical users and a 5-degree-of-freedom (dof) robot arm, a usability study was conducted to observe the impact of the learning system on user performance and satisfaction during a grasping operation. experimental results show that the system was effective in learning users' grasping intentions, which allowed it to reduce the average time to grasp an object. in addition, participants' feedback from the usability study was generally positive toward having an adaptive robotics system that learns from their commands.
sampling-based path planning on configuration-space costmaps. this paper addresses path planning to consider a cost function defined over the configuration space. the proposed planner computes low-cost paths that follow valleys and saddle points of the configuration-space costmap. it combines the exploratory strength of the rapidly exploring random tree (rrt) algorithm with transition tests used in stochastic optimization methods to accept or to reject new potential states. the planner is analyzed and shown to compute low-cost solutions with respect to a path-quality criterion based on the notion of mechanical work. a large set of experimental results is provided to demonstrate the effectiveness of the method. current limitations and possible extensions are also discussed.
multi-uav convoy protection: an optimal approach to path planning and coordination. in this paper, we study the problem of controlling a group of unmanned aerial vehicles (uavs) to provide convoy protection to a group of ground vehicles. the uavs are modeled as dubins vehicles flying at a constant altitude with bounded turning radius.we first present time-optimal paths to provide convoy protection to stationary ground vehicles. then, we propose a control strategy to provide convoy protection to ground vehicles moving in straight lines. the minimum number of uavs required to provide perpetual convoy protection, in both cases, are derived.
null-space grasp control: theory and experiments. akey problem in robot grasping is that of positioning the manipulator contacts so that an object can be grasped. in unstructured environments, contact positions are typically planned based on range or visual measurements that are used to reconstruct object geometry. however, because it is difficult to measure the complete object geometry precisely in common grasp scenarios, it is useful to employ additional techniques to adjust or refine the grasp using local information only. in particular, grasp control techniques can be used to improve a grasp by adjusting the contact configuration after making initial contact with an object by using measurements of local object geometry at the contacts. this paper proposes three variations on null-space grasp control: an approach that combines multiple grasp objectives to improve a grasp. two of these variations are theoretically demonstrated to converge to force-closure configurations for arbitrary convex objects when grasping with two contacts. all variations are found to converge in simulation. robot-grasping experiments are reported that show the approach to be useful in practice.
information-based compact pose slam. pose slamis the variant of simultaneous localization and map building (slam) is the variant of slam, in which only the robot trajectory is estimated and where landmarks are only used to produce relative constraints between robot poses. to reduce the computational cost of the information filter form of poseslam and, at the same time, to delay inconsistency as much as possible, we introduce an approach that takes into account only highly informative loop-closure links and nonredundant poses. this approach includes constant time procedures to compute the distance between poses, the expected information gain for each potential link, and the exact marginal covariances while moving in open loop, as well as a procedure to recover the state after a loop closure that, in practical situations, scales linearly in terms of both time and memory. using these procedures, the robot operates most of the time in open loop, and the cost of the loop closure is amortized over long trajectories. this way, the computational bottleneck shifts to data association, which is the search over the set of previously visited poses to determine good candidates for sensor registration. to speed up data association, we introduce a method to search for neighboring poses whose complexity ranges from logarithmic in the usual case to linear in degenerate situations. the method is based on organizing the pose information in a balanced tree whose internal levels are defined using interval arithmetic. the proposed pose-slam approach is validated through simulations, real mapping sessions, and experiments using standard slam data sets.
tactile sensing - from humans to humanoids. starting from human "sense of touch," this paper reviews the state of tactile sensing in robotics. the physiology, coding, and transferring tactile data and perceptual importance of the "sense of touch" in humans are discussed. following this, a number of design hints derived for robotic tactile sensing are presented. various technologies and transduction methods used to improve the touch sense capability of robots are presented. tactile sensing, focused to fingertips and hands until past decade or so, has now been extended to whole body, even thoughmany issues remain open. trend and methods to develop tactile sensing arrays for various body sites are presented. finally, various system issues that keep tactile sensing away from widespread utility are discussed.
coordinated kinematic control of compliantly coupled multirobot systems in an array format. this paper presents coordinated kinematic control of compliantly coupled multirobot systems for payload transportation. in the robot, unicycle-type axles are connected to a moving platform in an array format using compliant frames. a coordinate system is attached to an ideal center point on the platform to establish robot kinematics. in order to drive the system along a reference trajectory, we coordinate axle velocity commands, while considering frame compliance, nonholonomic constraints, and rigid body kinematics, respectively. these commands are further coordinated to consider configuration stability and physical limitations. simulation and experimental results evaluate the coordination algorithms for various trajectories.
decoupled image-based visual servoing for cameras obeying the unified projection model. this paper proposes a generic decoupled image-based control scheme for cameras obeying the unified projection model. the scheme is based on the spherical projection model. invariants to rotational motion are computed from this projection and used to control the translational degrees of freedom (dofs). importantly, we form invariants that decrease the sensitivity of the interaction matrix to object-depth variation. finally, the proposed results are validated with experiments using a classical perspective camera as well as a fisheye camera mounted on a 6-dof robotic platform.
2-d ultrasound probe complete guidance by visual servoing using image moments. this paper presents a visual-servoing method that is based on 2-d ultrasound (us) images. the main goal is to guide a robot actuating a 2-d us probe in order to reach a desired cross-section image of an object of interest. the method we propose allows the control of both in-plane and out-of-plane probe motions. its feedback visual features are combinations of moments extracted from the observed image. the exact analytical form of the interaction matrix that relates the image-moments time variation to the probe velocity is developed, and six independent visual features are proposed to control the six degrees of freedom of the robot. in order to endow the system with the capability of automatically interacting with objects of unknown shape, a model-free visual servoing is developed. for that, we propose an efficient online estimation method to identify the parameters involved in the interaction matrix. results obtained in both simulations and experiments validate the methods presented in this paper and show their robustness to different errors and perturbations, especially those inherent to the noisy us images.
dual-differential rheological actuator for high-performance physical robotic interaction. today's robotic systems are mostly rigid and position-controlled machines designed to operate in structured environments. to extend their application domains to partially unknown, dynamic, or anthropic environments, improved physical-interaction capabilities are required. in this new context, to blend the requirements for safety, robustness, and versatility is often a challenge, in part, because commonly available actuator technologies are inadequate. this paper presents our solution with the introduction of the dual-differential rheological actuator (ddra) concept, which is based on the synergistic combination of an electromagnetic (em) motor and two differentially coupled magnetorheological (mr) brakes. this paper describes the approach and the prototype design. it then discusses performances in force, motion, and interaction control.
localization: approximation and performance bounds to minimize travel distance. localization, which is the determination of one's location in a known terrain, is a fundamental task for autonomous robots. this paper presents several new basic theoretical results about localization.we show that, even under the idealized assumptions of accurate sensing and perfect actuation, it is intrinsically difficult to localize a robot with a travel distance that is close to minimal. our result helps to theoretically justify the common use of fast localization heuristics, such as greedy localization, which always moves the robot to a closest informative location (where the robot makes an observation that decreases the number of its possible locations). we show that the travel distance of greedy localization is much larger thanminimal in some terrains because the closest informative location can distract greedy localization from a slightly farther, but much more informative, location. however, we also show that the travel distance of greedy localization can be larger, but not much larger, than the terrain size n. thus, the travel distance of greedy localization scales well with the terrain size and is much larger than minimal in some terrains, not because it is large with respect to the terrain size, but because the minimal travel distance is exceptionally small in these terrains. as a corollary to our analysis, we show that the travel distance of greedy mapping (which always moves the robot to a closest location, where it makes an observation that increases its knowledge of the terrain) cannot be much larger than the terrain size. in theoretical terms, we prove the np-hardness of minimization of travel distance for localization to within a logarithmic factor of the terrain size. we prove that the travel distance of greedy localization is at least order n/ log2 n larger than minimal in some terrains and that it is at least order n log n/ log log n in the worst case. finally, we prove that the travel distance of both greedy localization and greedy mapping is at most order n log n. previously, it was only known that it is np-hard to localize with minimal travel distance and that the travel distances of greedy localization and greedy mapping are at most order n3/2.
robustness of image-based visual servoing with a calibrated camera in the presence of uncertainties in the three-dimensional structure. this paper concerns the stability analysis of imagebased visual servoing control laws with respect to uncertainties on the 3-d parameters needed to compute the interaction matrix for any calibrated central catadioptric camera. in the recent past, research on image-based visual servoing has been concentrated on potential problems of stability and on robustness with respect to camera-calibration errors. only little attention, if any, has been devoted to the robustness of image-based visual servoing to estimation errors on the 3-d structure. it is generally believed that a rough approximation of the 3-d structure is sufficient to ensure the stability of the control law. in this paper, we prove that this is not always true and that an extreme care must be taken when approximating the depth distribution to ensure stability of the image-based control law. the theoretical results are obtained not only for conventional pinhole cameras but for the entire class of central catadioptric systems as well.
vector fields for robot navigation along time-varying curves in n -dimensions. this paper presents a methodology for computation of artificial vector fields that allows a robot to converge to and circulate around generic curves specified in n-dimensional spaces. these vector fields may be directly applied to solve several robot-navigation problems such as border monitoring, surveillance, target tracking, and multirobot pattern generation, with special application to fixed-wing aerial robots, which must keep a positive forward velocity and cannot converge to a single point. unlike previous solutions found in the literature, the approach is based on fully continuous vector fields and is generalized to time-varying curves defined in n-dimensional spaces. we provide mathematical proofs and present simulation and experimental results that illustrate the applicability of the proposed approach. we also present a methodology for construction of the target curve based on a given set of its samples.
general-weighted least-norm control for redundant manipulators. this paper presents the general-weighted least-norm (gwln) method for the control of redundant manipulators by a new concept of virtual joints, which consist of the performance function of subtasks. the gwln method enables the redundant manipulator to perform multiple subtasks with the assumption that all the subtasks can be represented by the inequalities as the joint limits avoidance subtask. the number of subtasks to be coped with might be even larger than the number of joints if they do not happen simultaneously. the simulations in contrast to the traditional gradient projection method (gpm) and the recent directional gpm have been made to manifest the advantages of the proposed method. an experiment on the seven-degree-of-freedom redundant manipulator illustrates the good performance for tracking a given trajectory of end-effector position, while both guaranteeing the obstacle free and not violating the joint limits.
detecting region transitions for human-augmented mapping. in this paper, we describe a concise method for the feature-based representation of regions in an indoor environment and show how it can also be applied for door-passage-independent detection of transitions between regions to improve communication with a human user.
human-intent detection and physically interactive control of a robot without force sensors. in this paper, a physically interactive control scheme is developed for a manipulator robot arm. the human touches the robot and applies force in order to make it behave as he/she likes. the communication between the robot and the human is maintained by a physical contact with no sensors. the intent of the human is estimated by observing the change in control effort. the robot receives the estimated human intent and updates its position reference accordingly. the developed method uses the principle of conservation of zero momentum for position-controlled systems. a switching scheme is developed that goes between themodes of pure impedance control with a fixed-position reference and interactive control under human intent. the switching mechanism uses neither a physical switch nor a sensor; it observes the human intent and puts the robot into interactive mode, if there is any. when the human intent disappears, the robot goes into the pure-impedance-control mode, thus stabilizing in the left position.
a fundamental study of wing actuation for a 6-in-wingspan flapping microaerial vehicle. this paper investigates the hovering efficiency of the wing-actuation parameters of a flapping microaerial vehicle with a two-degree-of-freedom (2-dof) driving mechanism, using finite-element analysis based on the arbitrary lagrangian-eulerian method (ale-fea). a 75-mm-long wing and multilinkage mechanism that consisted of thin plates and films was employed. it generated a flapping motion that consisted of horizontal stroke of the wing and twist around its leading edge, which were activated by the rotations of two motors. the application of the ale-fea was successfully extended to the structural behavior of the driving mechanism. the behaviors of the linkage mechanism, the wing, and its surrounding airflow were reproduced numerically. various parameters were obtained, some of which were difficult to measure in real experiments, such as the pressure distribution on the wing. for cases of 25 combinations of wings' twist angles and flapping periods, lift forces and energy requirements for the motors were determined. based on these results, the most efficient flapping combination that generated 1 gf lift force was calculated. in contrast with the combination that created the strongest lift force, the combination of a larger twist angle and a faster flapping cycle was found to provide the most efficient flight.
control of a speech robot via an optimum neural-network-based internal model with constraints. an optimum internal model with constraints is proposed and discussed for the control of a speech robot, which is based on the human-like behavior. the main idea of the study is that the robot movements are carried out in such a way that the length of the path traveled in the internal space, under external acoustical and mechanical constraints, is minimized. this optimum strategy defines the designed internal model, which is responsible for the robot task planning. first, an exact analytical way to deal with the problem is proposed. next, by using some empirical findings, an approximate solution for the designed internal model is developed. finally, the implementation of this solution, which is applied to the control of a speech robot, yields interesting results in the field of task-planning strategies, task anticipation (namely, speech coarticulation), and the influence of force on the accuracy of executed tasks.
steering by gazing: an efficient biomimetic control strategy for visually guided micro aerial vehicles. oscar ii is a twin-engine aerial demonstrator equipped with a monocular visual system, which manages to keep its gaze and its heading steadily fixed on a target (i.e., a dark edge or a bar) in spite of the severe random perturbations applied to its body via a ducted fan. the tethered robot stabilizes its gaze on the basis of two oculomotor reflexes (ors) inspired by studies on animals: 1) a visual-fixation reflex (vfr) and 2) a vestibulo-ocular reflex (vor). one of the key features of this robot is that the eye is decoupledmechanically from the body about the vertical (i.e., yaw) axis. to meet the conflicting requirements of high accuracy and fast ocular responses, a miniature (2.4 g) voice-coil motor (vcm) was used, which enables the eye tomake a change of orientation with an unusually short rise time (19 ms). the robot, which was equipped with a high-bandwidth (7 hz) "vor," which is based on an inertial microrate gyro, is capable of accurate visual fixation as long as there is light. the robot is also able to pursue a moving target in the presence of erratic gusts of wind. here, we present the two interdependent control schemes driving the eye in the robot and the robot in space with no knowledge of the robot's angular position. this "steering-by-gazing" control strategy, which is implemented on this lightweight (100 g) miniature aerial robot, demonstrates the effectiveness of this biomimetic visual/inertial heading control strategy.
influence of vibration modes and human operator on the stability of haptic rendering. developing stable controllers, which are able to display virtual objects with high stiffness, is a persistent challenge in the field of haptics. this paper addresses the effect of internal vibration modes and the human operator on the maximum achievable virtual stiffness. an 11-parameter mechanical model is used to adequately characterize the overall system dynamics. experiments that are carried out on lhifam and phantom haptic interfaces demonstrate the importance of vibration modes to determine the critical stiffness when the user grasps the device.
analysis and experimental verification for dynamic modeling of a skid-steered wheeled vehicle. skid-steered vehicles are often used as outdoor mobile robots due to their robust mechanical structure and high maneuverability. sliding, along with rolling, is inherent to general curvilinearmotion, whichmakes both kinematic and dynamic modeling difficult. for the purpose of motion planning, this paper develops and experimentally verifies dynamic models of a skid-steered wheeled vehicle for general planar (2-d) motion and for linear 3-d motion. these models are characterized by the coefficient of rolling resistance, the coefficient of friction, and the shear deformation modulus, which have terrain-dependent values. the dynamic models also include motor saturation and motor power limitations, which enable correct prediction of vehicle velocities when traversing on hills. it is shown that the closed-loop system that results from inclusion of the dynamics of the [proportional-integral-derivative (pid)] speed controllers for each set of wheels does a much better job than the open-loop model of predicting the vehicle linear and angular velocities. for a vehicle turning with small linear and angular accelerations, the model provides accurate predictions of velocities and reasonable predictions of torques. hence, the closed-loop model is recommended for motion planning.
iterative-learning hybrid force/velocity control for contour tracking. in this paper, we propose a new method, which is based on an iterative-learning-control (ilc) algorithm, for the contour tracking of an object of unknown shape performed by an industrial robot manipulator. in particular, we consider (both implicit and explicit) hybrid force/velocity control whose performance is improved by repeating the task. here, a time-based reference signal is not present, and therefore, a new approach has been developed, which is different from the typical applications of ilc. experimental results show the effectiveness of the technique.
adaptive task-space tracking control of robots without task-space- and joint-space-velocity measurements. the task-space tracking control of robots without the exact knowledge of kinematics and dynamics has been studied before with the assumption that the joint velocities are available for controller designs. however, the velocity measurements can be contaminated by noises, thereby resulting in poor system performance, or even leading to instability problems. therefore, in this paper, we propose a new tracking controller for robots in the task space without the use of both task-space and joint-space-velocity measurements, under the condition that both the robot kinematics and dynamics are unknown. to overcome these incapacities without the velocity measurements, we introduce the well-known sliding-observer-design techniques to estimate the joint velocities for the purpose of our controller design. our main concern, i.e., the stability analysis of our controller design incorporated with the siding observer, is presented with the help of lyapunov-analysis methodology and the sliding-patch concept. simulation results are presented to show the performance of our controller-observer designs.
evolutionary trajectory planner for multiple uavs in realistic scenarios. this paper presents a path planner for multiple unmanned aerial vehicles (uavs) based on evolutionary algorithms (eas) for realistic scenarios. the paths returned by the algorithm fulfill and optimize multiple criteria that 1) are calculated based on the properties of real uavs, terrains, radars, and missiles and 2) are structured in different levels of priority according to the selected mission. the paths of all the uavs are obtained with the multiple coordinated agents coevolution ea (mcacea), which is a general framework that uses an ea per agent (i.e., uav) that share their optimal solutions to coordinate the evolutions of the eas populations using cooperation objectives. this planner works omine and online by means of recalculating parts of the original path to avoid unexpected risks while the uav is flying. its search space and computation time have been reduced using some special operators in the eas. the successful results of the paths obtained in multiple scenarios, which are statistically analyzed in the paper, and tested against a simulator that incorporates complex models of the uavs, radars, and missiles, make us believe that this planner could be used for real-flight missions.
bioinspired visuomotor convergence. in this paper, wide-field integration methods, which are inspired by the spatial decompositions of wide-field patterns of optic flow in the insect visuomotor system, are explored as an efficient means to extract visual cues for guidance and navigation. a control-theoretic framework is developed and used to quantitatively link weighting functions to behaviorally-relevant interpretations such as relative orientation, position, and speed in a corridor environment. it is shown through analysis and demonstration on a ground vehicle that the proposed sensorimotor architecture gives rise to navigational heuristics, namely, centering and speed regulation, which are observed in natural systems.
decentralized localization of sparsely-communicating robot networks: a centralized-equivalent approach. finite-range sensing and communication are factors in the connectivity of a dynamic mobile-robot network. state estimation becomes a difficult problem when communication connections allowing information exchange between all robots are not guaranteed. this paper presents a decentralized state-estimation algorithm guaranteed to work in dynamic robot networks without connectivity requirements. we prove that a robot only needs to consider its own knowledge of network topology in order to produce an estimate equivalent to the centralized state estimate whenever possible while ensuring that the same can be performed by all other robots in the network. we prove certain properties of our technique and then it is validated through simulations. we present a comprehensive set of results, indicating the performance benefit in different network connectivity settings, as well as the scalability of our approach.
passive-set-position-modulation framework for interactive robotic systems. in this paper, we propose a novel framework, passive set-position modulation (pspm), which enables us to connect a (continuous-time) robot's position to a sequence of slowly updating/sparse (discrete-time) set-position signal via the simple (yet frequently used in practice) spring coupling with damping injection, while enforcing passivity of the closed-loop robotic system. the pspm modulates the original set-position signal in such a way that themodulated signal is as close to the original signal as possible (i.e., maximum information recovery for better performance), yet only to the extent permissible by the available energy in the system (i.e., passivity constraints). we present its algorithm and theoretically show its passivity and performance. we also show how this pspm can be applied for two applications, with some experimental results: internet teleoperation with varying delay and packet loss; and haptics with slow and variable-rate data update.
a model of proximity control for information-presenting robots. in this paper, we report a model that allows a robot to appropriately control its position as it presents information to a user. this capability is indispensable, since in the future, many robots will function in daily situations such as shopkeepers presenting products to customers or museum guides presenting information to visitors. psychology research suggests that people adjust their positions to establish a joint view toward a target object. similarly, when a robot presents an object, it should stand at an appropriate position that considers the positions of both the listener and the object to optimize the listener's field of view and establish a joint view. we observed human-human interaction situations, where people presented objects, and developed a model for an information-presenting robot to appropriately adjust its position. our model consists of four constraints to establish o-space: 1) proximity to listener; 2) proximity to object; 3) listener's field of view; and 4) presenter's field of view.we also experimentally evaluate the effectiveness of our model.
optimization of a parallel shoulder mechanism to achieve a high-force, low-mass, robotic-arm exoskeleton. this paper describes a robotic-arm exoskeleton that uses a parallel mechanism inspired by the human forearm to allow naturalistic shoulder movements. the mechanism can produce large forces through a substantial portion of the range of motion (rom) of the human arm while remaining lightweight. this paper describes the optimization of the exoskeleton's torque capabilities by the modification of the key geometric design parameters.
proxy-based sliding mode control: a safer extension of pid position control. high-gain proportional-integral-derivative (pid) position control involves some risk of unsafe behaviors in cases of abnormal events, such as unexpected environment contacts and temporary power failures. this paper proposes a new position-control method that is as accurate as conventional pid control during normal operation, but is capable of slow, overdamped resuming motion without overshoots from large positional errors that result in actuator-force saturation. the proposed method, which we call proxy-based sliding mode control (psmc), is an alternative approximation of a simplest type of sliding mode control (smc), and also is an extension of the pid control. the validity of the proposed method is demonstrated through stability analysis and experimental results.
path planning for improved visibility using a probabilistic road map. this paper focuses on the challenges of vision-based motion planning for industrial manipulators. our approach is aimed at planning paths that are within the sensing and actuation limits of industrial hardware and software. building on recent advances in path planning, our planner augments probabilistic road maps with vision-based constraints. the resulting planner finds collision-free paths that simultaneously avoid occlusions of an image target and keep the target within the field of view of the camera. the planner can be applied to eye-in-hand visual-targettracking tasks for manipulators that use point-to-point commands with interpolated joint motion.
autonomous robot navigation in outdoor cluttered pedestrian walkways. this paper describes an implementation of a mobile robot system for autonomous navigation in outdoor concurred walkways. the task was to navigate through nonmodified pedestrian paths with people and bicycles passing by. the robot has multiple redundant sensors, which include wheel encoders, an inertial measurement unit, a differential global positioning system, and four laser scanner sensors. all the computation was done on a single laptop computer. a previously constructed map containing waypoints and landmarks for position correction is given to the robot. the robot system's perception, road extraction, and motion planning are detailed. the system was used and tested in a 1-km autonomous robot navigation challenge held in the city of tsukuba, japan, named &ldquo;tsukuba challenge 2007.&rdquo; the proposed approach proved to be robust for outdoor navigation in cluttered and crowded walkways, first on campus paths and then running the challenge course multiple times between trials and the challenge final. the paper reports experimental results and overall performance of the system. finally the lessons learned are discussed. the main contribution of this work is the report of a system integration approach for autonomous outdoor navigation and its evaluation. &copy; 2009 wiley periodicals, inc.
view planning and automated data acquisition for three-dimensional modeling of complex sites. constructing highly detailed three-dimensional (3-d) models of large complex sites using range scanners can be a time-consuming manual process. one of the main drawbacks is determining where to place the scanner to obtain complete coverage of a site. we have developed a system for automatic view planning called vueplan. when combined with our mobile robot, avenue, we have a system that is capable of modeling large-scale environments with minimal human intervention throughout both the planning and acquisition phases. the system proceeds in two distinct stages. in the initial phase, the system is given a two-dimensional site footprint with which it plans a minimal set of sufficient and properly constrained covering views. we then use a 3-d laser scanner to take scans at each of these views. when this planning system is combined with our mobile robot it automatically computes and executes a tour of these viewing locations and acquires them with the robot's onboard laser scanner. these initial scans serve as an approximate 3-d model of the site. the planning software then enters a second phase in which it updates this model by using a voxel-based occupancy procedure to plan the next best view (nbv). this nbv is acquired, and further nbvs are sequentially computed and acquired until an accurate and complete 3-d model is obtained. a simulator tool that we developed has allowed us to test our entire view planning algorithm on simulated sites. we have also successfully used our two-phase system to construct precise 3-d models of real-world sites located in new york city: uris hall on the campus of columbia university and fort jay on governors island. &copy; 2009 wiley periodicals, inc.
conops and autonomy recommendations for vtol small unmanned aerial system based on hurricane katrina operations. this field study examines vertical takeoff and landing (vtol) small unmanned aerial system (suas) operations conducted as part of an 8-day structural inspection task following hurricane katrina in 2005. from the observations of the 32 flights spread over 12 missions, four key findings are identified for concept of operations (conops) and the next level of artificial intelligence for rotary-wing suass operating in cluttered urban environments. these findings are (1) the minimum useful standoff distance from inspected structures is 2&ndash;5 m, (2) omnidirectional sensor capabilities are needed for obstacle avoidance, (3) global positioning system waypoint navigation is unnecessary, and (4) these operations require three operators for one suas. based on the findings and other observations, a crewing organization and flight operations protocol for suass are proposed. needed directions in research and development are also discussed. these recommendations are expected to contribute to the design of platforms, sensors, and artificial intelligence as well as facilitate the acceptance of suass in the workplace. &copy; 2009 wiley periodicals, inc.
lidar and vision-based pedestrian detection system. a perception system for pedestrian detection in urban scenarios using information from a lidar and a single camera is presented. two sensor fusion architectures are described, a centralized and a decentralized one. in the former, the fusion process occurs at the feature level, i.e., features from lidar and vision spaces are combined in a single vector for posterior classification using a single classifier. in the latter, two classifiers are employed, one per sensor-feature space, which were offline selected based on information theory and fused by a trainable fusion method applied over the likelihoods provided by the component classifiers. the proposed schemes for sensor combination, and more specifically the trainable fusion method, lead to enhanced detection performance and, in addition, maintenance of false-alarms under tolerable values in comparison with single-based classifiers. experimental results highlight the performance and effectiveness of the proposed pedestrian detection system and the related sensor data combination strategies. &copy; 2009 wiley periodicals, inc.
three-dimensional mapping with time-of-flight cameras. this article investigates the use of time-of-flight (tof) cameras in mapping tasks for autonomous mobile robots, in particular in simultaneous localization and mapping (slam) tasks. although tof cameras are in principle an attractive type of sensor for three-dimensional (3d) mapping owing to their high rate of frames of 3d data, two features make them difficult as mapping sensors, namely, their restricted field of view and influences on the quality of range measurements by high dynamics in object reflectivity; in addition, currently available models suffer from poor data quality in a number of aspects. the paper first summarizes calibration and filtering approaches for improving the accuracy, precision, and robustness of tof cameras independent of their intended usage. then, several ego motion estimation approaches are applied or adapted, respectively, in order to provide a performance benchmark for registering tof camera data. as a part of this, an extension to the iterative closest point algorithm has been developed that increases the robustness under restricted field of view and under larger displacements. using an indoor environment, the paper provides results from slam experiments using these approaches in comparison. it turns out that the application of tof cameras is feasible to slam tasks, although this type of sensor has a complex error characteristic. &copy; 2009 wiley periodicals, inc.
robust outdoor visual localization using a three-dimensional-edge map. visual localization systems that are practical for autonomous vehicles in outdoor industrial applications must perform reliably in a wide range of conditions. changing outdoor conditions cause difficulty by drastically altering the information available in the camera images. to confront the problem, we have developed a visual localization system that uses a surveyed three-dimensional (3d)-edge map of permanent structures in the environment. the map has the invariant properties necessary to achieve long-term robust operation. previous 3d-edge map localization systems usually maintain a single pose hypothesis, making it difficult to initialize without an accurate prior pose estimate and also making them susceptible to misalignment with unmapped edges detected in the camera image. a multihypothesis particle filter is employed here to perform the initialization procedure with significant uncertainty in the vehicle's initial pose. a novel observation function for the particle filter is developed and evaluated against two existing functions. the new function is shown to further improve the abilities of the particle filter to converge given a very coarse estimate of the vehicle's initial pose. an intelligent exposure control algorithm is also developed that improves the quality of the pertinent information in the image. results gathered over an entire sunny day and also during rainy weather illustrate that the localization system can operate in a wide range of outdoor conditions. the conclusion is that an invariant map, a robust multihypothesis localization algorithm, and an intelligent exposure control algorithm all combine to enable reliable visual localization through challenging outdoor conditions. &copy; 2009 wiley periodicals, inc.
leaving flatland: efficient real-time three-dimensional perception and motion planning. in this article we present the complete details of the architecture and implementation of leaving flatland, an exploratory project that attempts to surmount the challenges of closing the loop between autonomous perception and action on challenging terrain. the proposed system includes comprehensive localization, mapping, path planning, and visualization techniques for a mobile robot to operate autonomously in complex three-dimensional (3d) indoor and outdoor environments. in doing so we integrate robust visual odometry localization techniques with real-time 3d mapping methods from stereo data to obtain consistent global models annotated with semantic labels. these models are used by a multiregion motion planner that adapts existing two-dimensional planning techniques to operate in 3d terrain. all the system components are evaluated on a variety of real-world data sets, and their computational performance is shown to be favorable for high-speed autonomous navigation. &copy; 2009 wiley periodicals, inc.
a bayesian regression approach to terrain mapping and an application to legged robot locomotion. we deal with the problem of learning probabilistic models of terrain surfaces from sparse and noisy elevation measurements. the key idea is to formalize this as a regression problem and to derive a solution based on nonstationary gaussian processes. we describe how to achieve a sparse approximation of the model, which makes the model applicable to real-world data sets. the main benefits of our model are that (1) it does not require a discretization of space, (2) it also provides the uncertainty for its predictions, and (3) it adapts its covariance function to the observed data, allowing more accurate inference of terrain elevation at points that have not been observed directly. as a second contribution, we describe how a legged robot equipped with a laser range finder can utilize the developed terrain model to plan and execute a path over rough terrain. we show how a motion planner can use the learned terrain model to plan a path to a goal location, using a terrain-specific cost model to accept or reject candidate footholds. to the best of our knowledge, this was the first legged robotics system to autonomously sense, plan, and traverse a terrain surface of the given complexity. &copy; 2009 wiley periodicals, inc.
path-following algorithms and experiments for an unmanned surface vehicle. this paper addresses the problem of path following in two-dimensional space for underactuated unmanned surface vehicles (usvs), defining a set of guidance laws at the kinematic level. the proposed nonlinear lyapunov-based control law yields convergence of the path-following error coordinates to zero. furthermore, the introduction of a virtual controlled degree of freedom for the target to be followed on the path removes singularity behaviors present in other guidance algorithms proposed in the literature. some heuristic approaches are then proposed to face the problem of speed of advance adaptation based on path curvature measurement and steering action prediction. finally a set of experimental results of all the proposed guidance laws, carried out with the charlie usv, demonstrates the feasibility of the proposed approach and the performance improvements, in terms of precision in following the reference path and transient reduction, obtained by introducing speed adaptation heuristics. &copy; 2009 wiley periodicals, inc.
navigating with ranging radios: five data sets with ground truth. here we present five large data sets with range-only measurements between a mobile robot and stationary nodes. each data set consists of range measurements, surveyed locations of the stationary radio nodes, dead-reckoned trajectory of the robot, and ground truth from a sophisticated inertial navigation system-global positioning system mounted on a robot traveling several kilometers at a time. range measurements are made with two radio-based ranging systems: a rfid tag-based ranging system and an ultra&ndash;wide band ranging system. all the data are accurately time-stamped and presented in standard formats (i.e., text files). in addition to the raw data, we present some noise characteristics of the two different ranging systems to offer insight into the quality of the range data from each system. &copy; 2009 wiley periodicals, inc.
gaussian process modeling of large-scale terrain. building a model of large-scale terrain that can adequately handle uncertainty and incompleteness in a statistically sound way is a challenging problem. this work proposes the use of gaussian processes as models of large-scale terrain. the proposed model naturally provides a multiresolution representation of space, incorporates and handles uncertainties aptly, and copes with incompleteness of sensory information. gaussian process regression techniques are applied to estimate and interpolate (to fill gaps in occluded areas) elevation information across the field. the estimates obtained are the best linear unbiased estimates for the data under consideration. a single nonstationary (neural network) gaussian process is shown to be powerful enough to model large and complex terrain, effectively handling issues relating to discontinuous data. a local approximation method based on a &ldquo;moving window&rdquo; methodology and implemented using k-dimensional (kd)-trees is also proposed. this enables the approach to handle extremely large data sets, thereby completely addressing its scalability issues. experiments are performed on large-scale data sets taken from real mining applications. these data sets include sparse mine planning data, which are representative of a global positioning system&ndash;based survey, as well as dense laser scanner data taken at different mine sites. further, extensive statistical performance evaluation and benchmarking of the technique has been performed through cross-validation experiments. they conclude that for dense and-or flat data, the proposed approach will perform very competitively with grid-based approaches using standard interpolation techniques and triangulated irregular networks using triangle-based interpolation techniques; for sparse and-or complex data, however, it would significantly outperform them. &copy; 2009 wiley periodicals, inc.
performance of laser and radar ranging devices in adverse environmental conditions. a comparative evaluation of millimeter-wave radar and two-dimensional scanning lasers in dust and rain conditions for sensor applications in field robotics is presented. a robust and reliable method for measuring the level of suspended dust (or other obscurant media) by determining the transmission coefficient is developed and used for quantitative assessment of sensor performance. the criteria of target acquisition reliability, precision, and accuracy under varying environmental conditions are assessed via sensor operation in a controlled environment. this environment generated dust and rain of varying densities. sensor performance is also assessed for the potential effect on digital terrain mapping and haul truck localization due to sensor-specific behaviors in these conditions (e.g., false targets, increased noise). trials on a research electric face shovel are conducted to test observed behaviors. it is concluded that laser scanners are suitable for environments with transmissions exceeding 92&percnt;&ndash;93&percnt;-m for targets closer than 25 m. the radar remained relatively unaffected by the generated conditions of rain (50&ndash;70 mm-h) and dust (10-m visibility); however, its accuracy (0.1 m with a corner reflector and 0.3 m on a haul truck), free-space clutter, and scan rate were insufficient for locating unmodified haul trucks for this application. &copy; 2009 wiley periodicals, inc.
coverage path planning algorithms for agricultural field machines. in this article, a coverage path planning problem is discussed in the case of agricultural fields and agricultural machines. methods and algorithms to solve this problem are developed. these algorithms are applicable to both robots and human-driven machines. the necessary condition is to cover the whole field, and the goal is to find as efficient a route as possible. as yet, there is no universal algorithm or method capable of solving the problem in all cases. two new approaches to solve the coverage path planning problem in the case of agricultural fields and agricultural machines are presented for consideration. both of them are greedy algorithms. in the first algorithm the view is from on top of the field, and the goal is to split a single field plot into subfields that are simple to drive or operate. this algorithm utilizes a trapezoidal decomposition algorithm, and a search is developed of the best driving direction and selection of subfields. this article also presents other practical aspects that are taken into account, such as underdrainage and laying headlands. the second algorithm is also an incremental algorithm, but the path is planned on the basis of the machine's current state and the search is on the next swath instead of the next subfield. there are advantages and disadvantages with both algorithms, neither of them solving the problem of coverage path planning problem optimally. nevertheless, the developed algorithms are remarkable steps toward finding a way to solve the coverage path planning problem with nonomnidirectional vehicles and taking into consideration agricultural aspects. &copy; 2009 wiley periodicals, inc.
maneuverability and path following control of wheeled mobile robot in the presence of wheel skidding and slipping. this paper addresses the path following control problem of wheeled mobile robots in the presence of wheel skidding and slipping. a conditional global positioning system (gps)-based path following controller is proposed for four generic wmrs to achieve high-precision path following performance. the proposed controller utilizes real-time kinematic-gps and other aiding sensors to determine the robot's pose and wheel skidding and slipping perturbations to achieve accurate path following control. the reported simulation and experimental results suggest that with this control scheme, the wmrs are able to maneuver with precision. &copy; 2009 wiley periodicals, inc. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
segmented slam in three-dimensional environments. simultaneous localization and mapping (slam) has been shown to be feasible in many small, two-dimensional, structured domains. the next challenge is to develop real-time slam methods that enable robots to explore large, three-dimensional, unstructured environments and allow subsequent operation in these environments over long periods of time. to circumvent the scale limitations inherent in slam, the world can be divided up into more manageable pieces. slam can be formulated on these pieces by using a combination of metric submaps and a topological map of the relationships between submaps. the contribution of this paper is a real-time, three-dimensional slam approach that combines an evidence grid&ndash;based volumetric submap representation, a robust rao&ndash;blackwellized particle filter, and a topologically flexible submap segmentation framework and map representation. we present heuristic methods for deciding how to segment the world and for reconstructing large-scale metric maps for the purpose of closing loops. we demonstrate our method on a mobile robotic platform operating in large, three-dimensional environments. &copy; 2009 wiley periodicals, inc.
developing monocular visual pose estimation for arctic environments. arctic regions present one of the harshest environments on earth for people or mobile robots, yet many important scientific studies, particularly those involving climate change, require measurements from these areas. for the successful deployment of mobile sensors in the arctic, a high-quality localization system is required. although a global positioning system can provide coarse positioning (within several meters), it cannot provide any orientation information. a single-camera-pose-estimation system is presented, based on visual odometry techniques, which is capable of operating in the feature-poor environments of the arctic. to validate the system, a prototype rover was developed and fielded on a glacier in alaska. the resulting pose estimates compare favorably to values obtained by hand registering the same video sequence. although pose errors do accumulate over time, these errors are typical of a standard odometry system but obtained in an environment where standard odometry is not practical. &copy; 2009 wiley periodicals, inc. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
mixed kinematic and dynamic sideslip angle observer for accurate control of fast off-road mobile robots. automation in outdoor applications (farming, surveillance, military activities, etc.) requires highly accurate control of mobile robots, at high speed, although they are moving on low-grip terrain. to meet such expectations, advanced control laws accounting for natural ground specificities (mainly sliding effects) must be derived. in previous work, adaptive and predictive control algorithms, based on an extended kinematic representation, have been proposed. satisfactory experimental results have been reported (accurate to within &plusmn;10 cm, whatever the grip conditions), but at limited velocity (below 3 m&middot;s-1). nevertheless, simulations reveal that control accuracy is decreased when vehicle speed is increased (up to 10 m&middot;s-1). in particular, oscillations are observed at curvature transition. this drawback is due to delays in sideslip angle estimation, unavoidable at high speed because only an extended kinematic representation was used. in this paper, a mixed backstepping kinematic and dynamic observer is designed to improve observation of these variables: the slow-varying data are still estimated from a kinematic representation, which is then injected into a dynamic observer to supply reactive and reliable sliding variable (namely sideslip angle) estimation, without increasing the noise level. the algorithm is evaluated via advanced simulations (coupling adams and matlab software) investigating high-speed capabilities. actual experiments at lower speed (experimental platform maximum velocity) demonstrate the benefits of the proposed approach. &copy; 2009 wiley periodicals, inc. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
generation and visualization of large-scale three-dimensional reconstructions from underwater robotic surveys. robust, scalable simultaneous localization and mapping (slam) algorithms support the successful deployment of robots in real-world applications. in many cases these platforms deliver vast amounts of sensor data from large-scale, unstructured environments. these data may be difficult to interpret by end users without further processing and suitable visualization tools. we present a robust, automated system for large-scale three-dimensional (3d) reconstruction and visualization that takes stereo imagery from an autonomous underwater vehicle (auv) and slam-based vehicle poses to deliver detailed 3d models of the seafloor in the form of textured polygonal meshes. our system must cope with thousands of images, lighting conditions that create visual seams when texturing, and possible inconsistencies between stereo meshes arising from errors in calibration, triangulation, and navigation. our approach breaks down the problem into manageable stages by first estimating local structure and then combining these estimates to recover a composite georeferenced structure using slam-based vehicle pose estimates. a texture-mapped surface at multiple scales is then generated that is interactively presented to the user through a visualization engine. we adapt established solutions when possible, with an emphasis on quickly delivering approximate yet visually consistent reconstructions on standard computing hardware. this allows scientists on a research cruise to use our system to design follow-up deployments of the auv and complementary instruments. to date, this system has been tested on several research cruises in australian waters and has been used to reliably generate and visualize reconstructions for more than 60 dives covering diverse habitats and representing hundreds of linear kilometers of survey. &copy; 2009 wiley periodicals, inc.
kinematic reconfigurability control for an environmental mobile robot operating in the amazon rain forest. this paper addresses the active control problem of reconfigurable mobile robots on irregular terrain. different kinematic control strategies to improve robot mobility are proposed based on (a) ground clearance and orientation, (b) ground clearance and stability margin, and (c) wheel traction efficiency. owing to conflicting objectives associated with these strategies, a multi-objective optimization approach is formulated to determine a set of optimal solutions and establish a trade-off optimal solution. the proposed control is validated through numerical simulations and experimental tests using an amphibious wheel-legged robot, named environmental hybrid robot, designed for environmental monitoring in the amazon rain forest. &copy; 2010 wiley periodicals, inc. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
error modeling and calibration of exteroceptive sensors for accurate mapping applications. reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. in field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. this is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. the whole system is as reliable as the weakest link in this chain. in this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as lidar or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. the coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. this allows the mapping accuracy to be calculated at run time. a generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. this allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. the mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. the techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. &copy; 2009 wiley periodicals, inc.
efficient three-dimensional scene modeling and mosaicing. scene modeling has a key role in applications ranging from visual mapping to augmented reality. this paper presents an end-to-end solution for creating accurate three-dimensional (3d) textured models using monocular video sequences. the methods are developed within the framework of sequential structure from motion, in which a 3d model of the environment is maintained and updated as new visual information becomes available. the proposed approach contains contributions at different levels. the camera pose is recovered by directly associating the 3d scene model with local image observations, using a dual-registration approach. compared to the standard structure from motion techniques, this approach decreases the error accumulation while increasing the robustness to scene occlusions and feature association failures, while allowing 3d reconstructions for any type of scene. motivated by the need to map large areas, a novel 3d vertex selection mechanism is proposed, which takes into account the geometry of the scene. vertices are selected not only to have high reconstruction accuracy but also to be representative of the local shape of the scene. this results in a reduction in the complexity of the final 3d model, with minimal loss of precision. as a final step, a composite visual map of the scene (mosaic) is generated. we present a method for blending image textures using 3d geometric information and photometric differences between registered textures. the method allows high-quality mosaicing over 3d surfaces by reducing the effects of the distortions induced by camera viewpoint and illumination changes. the results are presented for four scene modeling scenarios, including a comparison with ground truth under a realistic scenario and a challenging underwater data set. although developed primarily for underwater mapping applications, the methods are general and applicable to other domains, such as aerial and land-based mapping. &copy; 2009 wiley periodicals, inc.
online three-dimensional slam by registration of large planar surface segments and closed-form pose-graph relaxation. a fast pose-graph relaxation technique is presented for enhancing the consistency of three-dimensional (3d) maps created by registering large planar surface patches. the surface patches are extracted from point clouds sampled from a 3d range sensor. the plane-based registration method offers an alternative to the state-of-the-art algorithms and provides advantages in terms of robustness, speed, and storage. one of its features is that it results in an accurate determination of rotation, although a lack of predominant surfaces in certain directions may result in translational uncertainty in those directions. hence, a loop-closing and relaxation problem is formulated that gains significant speed by relaxing only the translational errors and utilizes the full-translation covariance determined during pairwise registration. this leads to a fast 3d simultaneous localization and mapping suited for online operations. the approach is tested in two disaster scenarios that were mapped at the nist 2008 response robot evaluation exercise in disaster city, texas. the two data sets from a collapsed car park and a flooding disaster consist of 26 and 70 3d scans, respectively. the results of these experiments show that our approach can generate 3d maps without motion estimates by odometry and that it outperforms iterative closest point&ndash;based mapping with respect to speed and robustness. &copy; 2009 wiley periodicals, inc.
automatic appearance-based loop detection from three-dimensional laser data using the normal distributions transform. we propose a new approach to appearance-based loop detection for mobile robots, using three-dimensional (3d) laser scans. loop detection is an important problem in the simultaneous localization and mapping (slam) domain, and, because it can be seen as the problem of recognizing previously visited places, it is an example of the data association problem. without a flat-floor assumption, two-dimensional laser-based approaches are bound to fail in many cases. two of the problems with 3d approaches that we address in this paper are how to handle the greatly increased amount of data and how to efficiently obtain invariance to 3d rotations. we present a compact representation of 3d point clouds that is still discriminative enough to detect loop closures without false positives (i.e., detecting loop closure where there is none). a low false-positive rate is very important because wrong data association could have disastrous consequences in a slam algorithm. our approach uses only the appearance of 3d point clouds to detect loops and requires no pose information. we exploit the normal distributions transform surface representation to create feature histograms based on surface orientation and smoothness. the surface shape histograms compress the input data by two to three orders of magnitude. because of the high compression rate, the histograms can be matched efficiently to compare the appearance of two scans. rotation invariance is achieved by aligning scans with respect to dominant surface orientations. we also propose to use expectation maximization to fit a gamma mixture model to the output similarity measures in order to automatically determine the threshold that separates scans at loop closures from nonoverlapping ones. we discuss the problem of determining ground truth in the context of loop detection and the difficulties in comparing the results of the few available methods based on range information. furthermore, we present quantitative performance evaluations using three real-world data sets, one of which is highly self-similar, showing that the proposed method achieves high recall rates (percentage of correctly identified loop closures) at low false-positive rates in environments with different characteristics. &copy; 2009 wiley periodicals, inc.